{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inline graphing\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary packages\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib_venn import venn3, venn2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set working directory to wild-type 1 folder\n",
    "os.chdir('Path/To/Data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading in full data for first wild-type experiment\n",
    "ua1 = pd.read_csv('UnA/rowsum/20190516_UnA_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ua1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ua1.columns = ['Gene_ua1', 'ProteinInfo_ua1', 'Compartment_ua1', 'Probability_ua1']\n",
    "\n",
    "ub1 = pd.read_csv('UnB/rowsum/20190516_UnB_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ub1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ub1.columns = ['Gene_ub1', 'ProteinInfo_ub1', 'Compartment_ub1', 'Probability_ub1']\n",
    "\n",
    "uc1 = pd.read_csv('UnC/rowsum/20190516_UnC_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "uc1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "uc1.columns = ['Gene_uc1', 'ProteinInfo_uc1', 'Compartment_uc1', 'Probability_uc1']\n",
    "\n",
    "ia1 = pd.read_csv('IndA/rowsum/20190516_IndA_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ia1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ia1.columns = ['Gene_ia1', 'ProteinInfo_ia1', 'Compartment_ia1', 'Probability_ia1']\n",
    "\n",
    "ib1 = pd.read_csv('IndB/rowsum/20190516_IndB_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ib1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ib1.columns = ['Gene_ib1', 'ProteinInfo_ib1', 'Compartment_ib1', 'Probability_ib1']\n",
    "\n",
    "ic1 = pd.read_csv('IndC/rowsum/20190516_IndC_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ic1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ic1.columns = ['Gene_ic1', 'ProteinInfo_ic1', 'Compartment_ic1', 'Probability_ic1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set working directory to wild-type 2 folder\n",
    "os.chdir('Path/To/Data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading in full data for second wild-type experiment\n",
    "ua2 = pd.read_csv('UnA/20190518_UnA_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ua2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ua2.columns = ['Gene_ua2', 'ProteinInfo_ua2', 'Compartment_ua2', 'Probability_ua2']\n",
    "\n",
    "ub2 = pd.read_csv('UnB/20190518_UnB_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ub2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ub2.columns = ['Gene_ub2', 'ProteinInfo_ub2', 'Compartment_ub2', 'Probability_ub2']\n",
    "\n",
    "uc2 = pd.read_csv('UnC/20190518_UnC_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "uc2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "uc2.columns = ['Gene_uc2', 'ProteinInfo_uc2', 'Compartment_uc2', 'Probability_uc2']\n",
    "\n",
    "ia2 = pd.read_csv('IndA/20190518_IndA_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ia2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ia2.columns = ['Gene_ia2', 'ProteinInfo_ia2', 'Compartment_ia2', 'Probability_ia2']\n",
    "\n",
    "ib2 = pd.read_csv('IndB/20190518_IndB_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ib2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ib2.columns = ['Gene_ib2', 'ProteinInfo_ib2', 'Compartment_ib2', 'Probability_ib2']\n",
    "\n",
    "ic2 = pd.read_csv('IndC/20190518_IndC_SVCidentified_postiter_threshold.csv', index_col=0)\n",
    "ic2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ic2.columns = ['Gene_ic2', 'ProteinInfo_ic2', 'Compartment_ic2', 'Probability_ic2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set working directory to folder comparing biological replicates\n",
    "os.chdir('Path/To/Data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining commonly detected protein dataframes for uninduced\n",
    "unlist = [ua1, ub1, uc1, ua2, ub2, uc2]\n",
    "\n",
    "un = pd.concat(unlist, axis=1, join='outer', sort='True')\n",
    "\n",
    "for item in un.index:\n",
    "    if un.at[item, 'ProteinInfo_ua1'] is np.nan:\n",
    "        if un.at[item, 'ProteinInfo_ub1'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_ub1']\n",
    "        elif un.at[item, 'ProteinInfo_uc1'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_uc1']\n",
    "        elif un.at[item, 'ProteinInfo_ua2'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_ua2']\n",
    "        elif un.at[item, 'ProteinInfo_ub2'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_ub2']\n",
    "        elif un.at[item, 'ProteinInfo_uc2'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_uc2']\n",
    "                \n",
    "for item in un.index:\n",
    "    if un.at[item, 'Gene_ua1'] is np.nan:\n",
    "        if un.at[item, 'Gene_ub1'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_ub1']\n",
    "        elif un.at[item, 'Gene_uc1'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_uc1']\n",
    "        elif un.at[item, 'Gene_ua2'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_ua2']\n",
    "        elif un.at[item, 'Gene_ub2'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_ub2']\n",
    "        elif un.at[item, 'Gene_uc2'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_uc2']\n",
    "\n",
    "un.drop(columns=['ProteinInfo_ub1', 'ProteinInfo_uc1', 'ProteinInfo_ua2', 'ProteinInfo_ub2', 'ProteinInfo_uc2', \n",
    "                 'Gene_ub1', 'Gene_uc1', 'Gene_ua2', 'Gene_ub2', 'Gene_uc2'], inplace=True)\n",
    "un.rename({'Gene_ua1':'Gene', 'ProteinInfo_ua1':'ProteinInfo'}, axis='columns', inplace=True)\n",
    "un.fillna('ND', inplace=True)\n",
    "ndset = ['ND']\n",
    "un['NDcount'] = (un.isin(ndset).sum(1))/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining commonly detected protein dataframes for induced\n",
    "indlist = [ia1, ib1, ic1, ia2, ib2, ic2]\n",
    "\n",
    "ind = pd.concat(indlist, axis=1, join='outer', sort='True')\n",
    "\n",
    "for item in ind.index:\n",
    "    if ind.at[item, 'ProteinInfo_ia1'] is np.nan:\n",
    "        if ind.at[item, 'ProteinInfo_ib1'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ib1']\n",
    "        elif ind.at[item, 'ProteinInfo_ic1'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ic1']\n",
    "        elif ind.at[item, 'ProteinInfo_ia2'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ia2']\n",
    "        elif ind.at[item, 'ProteinInfo_ib2'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ib2']\n",
    "        elif ind.at[item, 'ProteinInfo_ic2'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ic2']\n",
    "                \n",
    "for item in ind.index:\n",
    "    if ind.at[item, 'Gene_ia1'] is np.nan:\n",
    "        if ind.at[item, 'Gene_ib1'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ib1']\n",
    "        elif ind.at[item, 'Gene_ic1'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ic1']\n",
    "        elif ind.at[item, 'Gene_ia2'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ia2']\n",
    "        elif ind.at[item, 'Gene_ib2'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ib2']\n",
    "        elif ind.at[item, 'Gene_ic2'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ic2']\n",
    "\n",
    "ind.drop(columns=['ProteinInfo_ib1', 'ProteinInfo_ic1', 'ProteinInfo_ia2', 'ProteinInfo_ib2', 'ProteinInfo_ic2', \n",
    "                 'Gene_ib1', 'Gene_ic1', 'Gene_ia2', 'Gene_ib2', 'Gene_ic2'], inplace=True)\n",
    "ind.rename({'Gene_ia1':'Gene', 'ProteinInfo_ia1':'ProteinInfo'}, axis='columns', inplace=True)\n",
    "ind.fillna('ND', inplace=True)\n",
    "ndset = ['ND']\n",
    "ind['NDcount'] = (ind.isin(ndset).sum(1))/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pulling out value counts for ND columns (Not Detected)\n",
    "uncount = un.NDcount.value_counts().to_frame()\n",
    "uncount.sort_index(inplace=True)\n",
    "\n",
    "indcount = ind.NDcount.value_counts().to_frame()\n",
    "indcount.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HIGlpvM0UNNXxu+U7qP5+nji3pDfjHrd5m70Lf/YXwRdEWhrX0weO3Avv17T0AnADQPGNtBj+bK2Rji1B6x2YsxLt3wSP4M/o/fj1WBPvW4XX9YPpnJ2+teYVyl6eXduSpK8CHyntno1/r07GdbHiO/EVwIVJN6mdDZKxDG5wWy/9fzP+LbwssBmthRpfCpyd+tkxt/8myGeHnQLsWjp0O17/bjpLzha09Im5wL/xZ2MOrmdtTKtfeB5wiaTnVegUc2npQc8FCq/sf+HXrUxlyJ/kfXg87e2/6IsexweVi35oY+ACSS81s8tr6jcLH4wreArvb+9K/y+P64xFvz/eMxiDeZmm1jt69JTDX3D/ztL8sYv87Ey2GKE6D9i0JLc0sHJp3/FZ2ieAz1MaOcAb/KdpH4H/YIfyfB/3ungbsFKNzE74UttFfncBSzW8hjMrjq8OXJnJ3Ak8r0N+y9PusXAfProyJZOZigdYfwp/aeUjOjNq8p1C++jnk/jHxNKZzCT84+S2TO5R4Dk1eV6Syb2tRuZrpbwM945RheyitI/QjDov7aOj96b6P4CPbC1Wkt2T9pHR83u1cHe4T9/M8jX8o2itksxzS9fIgH075Dktlx1UWavyrmsnpTQfKaXZoXR8eunePpm2z+btKsmuX/r/taW8/wZsXZJZldFecMd0KG9entk9XJvJ+IdVkfYh4EBKzz3+bH69VJ5Xdcg3l5tWIzMzkyme49vwRXUml57N/Wn3Qjx2gO0jL+vMPvM4uJTPKI+eJPeuktyJlJ71VN/X0f4uPLnDufPrOKuHMq9Ou7fe9cBe+bVPcs/GlcP8vbx2h3zL7fY8YKsKuSXxFczPBg7utx31+ywAW+H9SCF7I24EVCazLHA47SPf51HxDk/yMzK5ob2jS+fJ+/T3lI4tjn+AFse3a5jnfqV78y/8vbZISW4yvijA0cDZDe5xcT1OBNYpya0MLJP9v27p+t2Nfyzk744l8EHLxzO5fwCLV5RjEdr1idOADWrKPA34EG68Xq3i+GlZPtfgulVVv788/oF/LvCmAdzrXUrXc5sauXzmwtpp3xR8kNaAv9WkW7OUf22f3uDZNOYxTzl8wYtC/mlgkw6yMzLZkQ5y49HfD/Pc6+B6QiF7RzrPpExm8fR8PEZzPT2/X7M7nH9V3FhSyD4OfIkKj1X8HfEx3Kg0reL4DriB49O4YajqGV0L+AbtfUCtVyvzjqfcGaVrNOqdV5J/X+kcPwGeXZKZhOtnud7wsw555p5yRZrrgV1Kcqsw2vvqOx3yHainHG5gzs99DvCiCrmpqf7nAp+pyetqvL/bHVii4vhiwL60e4Of1uXe5DaBg3poN1vS7iV/KT7gopLcVrjXXiF3PRXf/kmukJmLDzguVyE3CZ8deBgNPHljW3C35oINjHLp4VkfeA/tRraHged3yT+XN3zUtKPbc0r36izNE3SZLoQroYX8fdRPc2vqkr447caU9ze8hjNLxzagfUrJbLpMHQGOyOQfp8MHAvDe0vXt1NkfUJJ7e4d8n41/TBWydR8Sh2cylQoMLUPgw8B3M/nNK2R3yo7fXpPfjFI9HgNe2KEubyjJV7pJ9/SAubEtV05mdZBdEu8ECtn/dmif0/KyjrWcnfKuayelNHm5nyiXm9FKkgFvbZDvIrQbfq8Elu0gf1TpHNvWyOXlmd3DtTkwS3c/3V3XP5HJ/5N640Re5mk1MjNLcnfXySb5j2WyjwBLDqh95GWY2WceryzlM2r6F24Ey6dzHtwlz2fTPj2ocvoJ/RvlTsnS/bVLO5xM+4f8D2rkXl66Dt+nS2iFlK5y8KdJO+r3WQAuz+RupTSwUJL9aKksb66Rm1GSm/B3dCn/TbK8H6diuhH+AfHM/WqQ58q0jDeGG/06TmPq4R43KkNK94sszYPAc3u4zp+qkNkxO34DsGiDMqjcvnHjVvEhNJfSh22HvCY3keuSx+K0GyA/USEzCdcVRz0fuMHZcINUVVt5S+k6rttj+aaX0k8fZHvv9Vz4e21l/AP6tJL8oV3yz5/1kRqZ8ervh3nu3IDxECVHg5Lsq0t5GmM3yp2Uyc0BXtKgLSxa9TzjRvuu/VOS/Z/svJd2kJuW13ei2nJJfjvaQ2rUDuol+bVodwqoNDhl8hvTPiCydY1cOSzGrcCaHfL9QSY7l4pvpSQ3MKMcPjiWl/H/qNFrS+nq+rOm39rr09Lv5lLjAJJkezbK4X1T7hRzRtUzkJcbN9p36js+nx2f1bAcY+7XYpt/t+aCvcdiKrbzqfGCKOU/O0vzeKcXUSndH7J0hzRMk4+IvGvMF9GnzRb5VRqlKq7hzGz/lrSPAvyjW/1xZfK+LM3XGpRzpHRvZtTIXZPJ/LpBvvmIUeXLEveoKGRuqDiex5M7G/d8KeRHeTTinnvF8VHx5JLMjFJ9D+5SD+FTFAr5rkajBtcmNy7eTskrrEJ+M9q9Ud5dIzctr9tYy9kp77p2ksmXP8BHjWIxWknq2q5Sur1L6UaNxlU8F7Mz+RNq5PLyzG5Yliml9rF/gzTCp/QUaSoHDUp1nFYjM7Mkt1+Xcy9Fu+LYKEZKgzrlZZjZZx7blPIZ9R7GpwYWxy9umG9uiPxJg+s4q2G+z6FlXH8S2LhBmjVpffA/Rua1lMlcmJXlCkqeU2O8N5XtqJ9noeJ+dYzpltr9HzP5P9TIzSjle3CDfAf6ji7l/79Z3pXxsfCR80LmfipG90vyX8jkH2GMhsTS9bqDBh81+Edk3q98tEGan2XyNzHaI/TN2fETx1Cf1fP6DPJ+Njz/Rdn5z6g4vmV2/LjSsYOzY6M8oWnv/yufrS5ly59NY2KNck23W4D3Ncg/f9ZHamTGq78fyrnxqYt5bOpRxu2KNCeVyjGjwf2qbFv4YH9ubKqMVzxO7an8rh4Voy7JTcvrO05tufK5wXW6t+ED4IXsY3QwnKZ0X+nWnirSfCpL86MambJRrnIwK5NfinYvyG/VyA3SKJd/c/+FBs4zA2xTh2Xn/lgHuX6McvkA6X+piU1cSrNtluY/Fcd/mB3v+r0QW2zjPXf5Yjy4fa9xJs6wBvGP5EvNFytiFUFFm3BC9vsltVLNuST7/aJaqQok7YQby1bN8tqxQf13oX2Ofl3ctZxvNSjPxrTHojmyQb7H4iMY4B1x1eq4RVw5gGdJWrd0PI8ndz6tKYLQHjuOin0jDcoI3hZrMTOjtaIa+OjWWMmvxTHWJeaDmV2Fj74XvGYAZRg48tUXd5J0Iq3YcOAGi4MbZPH9hqfK6/8HM7usk7CZzcE/hApeJWlynXyP7ExrRa778OkDHUlt6qfZrkG8b8BH3H/aScDMHsZH8goG0Z4HxX2l/1eokHlb9vuIhvn+JPs9qGsNHhagiHtylpld0y1BeocXcacWx0fjn0HSmri3UcGhVh3Pal4gfw5vAX7ZSTi1+7zv2FbSqnXyGcN4RwO+2hrtq7b9uEb0QvxjE3wwqXY1+EQeT+k4a49RN1ZOMLNHGsi9ilZsnzk0e//mz9zaQHm1yXzl0s1Us1psA/J8VlGXFVrHgTzO2/YV9aiKJ1dwUY1c1b4FKp5c4i7cW+eUAeU3zP5+PM79ElqxqZ/CvWy78d3uIo15Ey29+j4afAMMivSuvjTb1dO30YD5iqSzsu1sSX/EjS/H0YoR+yg+Lb4yhmbGROgmd+EG2lqSjjcr2/XahmXpi/Tdtm2260tm1nEV0wHT97d2A/J7+iMbHZN4FGb2R9wwD7BOisWek/dtWxAEXeh3oYe6wOiTcCX1OenvDmn7jKQ3NvmQSVzcXQRo/6C5ynyZ+ibkRsLndxOWL+09HfdiWgmPa1fX8S8vaUkze7RBvnvio9FFp30O8NqGSvZW2e9/NlT0izhHtctK46uMFczBDWQdMbM5KXD76yryKGQekXQ5rcU/dqG9M5me/R4xs3sk/QO/5jtLUurkkbQY7R3DSLcyAjea2R0N5G7JftcuC98ESdNoGVvBPTSb8GtaAdu3yus+JI6VdGwDuafx0aAmwdebPuN5W+rl+h2Wfi+FB6K+smHaTuTvmwt7MKD09L5pyOVm1nExjcTA2vOAKX/4trXv9OzkAaV/1yRTM7tN0v34gMWqktawhosMdCG/97/tId1VeCBm8Ht/Vk2eT+HTweZV8ufwTKtZlKPEb2jvb7amcx0n/B1d4mW0gkPfR837xsxM0gm45wO4F06lgTwtCpMr6nWLAfRLP+/Ri8zswW4JzOwSSffSCoC+NfCnTOTP2e9N8X7ik2Z2e8MyFee5T9INeEBz4YtG7W9mV/SSzxi4APhM+r0s7hn3l+x4bljLjXDgH4lP4lMfd84PSFqZdqPxyADKOpFcRvViUVPxd/M0PLbVTOATkj5sZk0H2+oYZn8/HufODQdXmdndDfK8mFabGit5H/MbM6ta+KcvJC2DvzO3xAcrl2H04hCbZ7/XYnh0M+AYPiB0mJnd1EkwGV5Wy3Z1/UYCMLObJD2Mt5M1Ja3S5Zv1XDOrXIygxJlAsYjYGgPUearI29MTePsfCJKE2wu2xh1DlsPfNfn3ar4Yx6Db01h0vGnp9/Px+HIF+eIP75f0b3z17oE9h8GCRb9GuTvNrLxS3DOkh2tXfARhE9ywMiJpKzP7T126jH83LEf+wl9T0lm1ku3kK3ytXCck6UV4wNLt6mRqWBYfcenEq/AFGArj3s/wIMBNPrShXdFv5IloZg9Lmo2vHtMk36t7GAX5Oy2jXHm0oGCEllFuOtVGuYdpvchG8LazIn6vC2VnG1qGzDvM7J8NytfkYw/a79uStVLNKF+Hpqse5nIr4B+eE7mSaj9cBnzYzP7QQPb+JqNQkqbQvtpe0+t3La3VfsHvwyCMcvn75vk9vG9yL7Da902PDKM9D5LySlzl9pBf67n4aptN885XzV4ZjxM0VvLyzJBU2/+VyN8B5Xuff7BfPY8rank9Gj2HZvagpP/QUljr+oWCYbfpGdnvk7r0xT+mZZR7qaQ1a7zby558f66QGQtNdaWe718mO70ij+Ij82Ra/f6+wFslXYx/1FwMXNKwXR9By4vnhcDfJP0dH6i8CF8F954eyt0Lv6fdCLIT7Ua54mPtzrKuYWaPSvozrpM8T9JSyXulyCdnfvOU+7iZjdQdTAMnBwHvxHXq70mabGbf6edkw+zvx/Hc62S/GzklmNkT6eN91OrJfZC/fwby7pG0LL5QxDto/5bqxrKDOP84URiEmtQn1wWeAk7qQTfJDa0r01qBs4qmM8zKchsyGJ2nirw9XWVmjw8iU0lvw6fYrtNNNmNg7UnS8ni4kYJPSTqgYfLnZr/LOt5JeL3WwAeijwC+IOlc/Pv2YuCKhoOcwUJAv0a5jiSvnnMk7YgHxF4HH1H7Dj5vuxtNl3XOreYr0fIu6oXKB1vSG/DR735c4auWEi+Te8w8gMdNa2qQg3YPgXt7SHcvnY1y+cdyL/nmCnOd98IIrRGdXYqdqZPfMv17UWYIPB9fdAL8w+DK7HeeZxN6ubbPFK2PNDn5tXyy29TVjPLHx7CNclfhAWcLDI+N9N907IIevRqaXoey4aZRezSzp5K31Epp16C8afL3zdpp65VBKRLDaM+DpKy8lNt3fq0n0d+7HQZwvdN0trwtbkF/UxHKZcmNtU29vIfFWPqFael3t+dwaG06KeV7Zrvqpq4CYGbXJGPMC/D2uS8tj5mc/B4/ZWbladtjpZ936SD79Xfhz3JhgJqMe4wVXmOPS7oIDxlyQoePuG/jH5MfyvZtnraPACbpCvwj54c9zIroSjKsXU7L+35nfDC2COexStpf9pIj278Nrk9vj89IgHaj3C1mdsOgyjwvYGazgf0lzQE+kHZ/XdIZ3byNahhmfz9e587zvb+H8jzQXaQRA+1jkufvCD4bqleafBeNF7vkBub0zbEuHkfwA7iX32bABZK27uI8kusmUxg/3aTpe/o+fOCymH1QbsuDZOA6i6SjaL0/emGQ7WnF0v+9OuIUtN3TNEPslcDptIx+S+PTjIupxvdJOhOPb3xun+cNFhDGNaZc8ob5RrZrjxQHrhtNrcZTey/VKEYp9Wne/HG0DHL34KuH7oZPsVgaD26pYuvjvOfTmm/6TEehAAAgAElEQVS+LG7ErIqrVEf+QurlY6bbyEa/+eaydS/Lwi0ffP59YRzM48mNZPJ5XLldsv3571x+XmMQ17KczzD4mpntnm17mNnrzezdZvbNPqYZNX2+y/UedHvslUG8b8Y7juf8wgtK/5c9fgZxrWEw13uJAeVTziNvlwMZcR5HxrNfmBd4M+3lO0PS/Z022j0m9qvJd7zvcT/v0oHdv2Rk3AWPxXdRRXkWw6dvHwNcJ2kXKjDnQNyo9Qs82HqO8IG7Q4EbJH2IwZJ7se2olutLp3hyBXVx5Rb0eHIFB9O674sD+/eZzzD7+3lN1xiU58yg3z/H0DLIzcWf1X3wd+EKwOKl76KucXeHgZk9YGZXmtmncQNMYTBdFTi+S1zCidJNGrXB5ASTh1IZz352oO1J0ltoN8j9Ax+E2Q73LpuKr/ZbtKddx3rOGsbtnqZwPhsDnwauq0izPL5K9zmSLpDUz2B/sIAwER+I5ZgnO1ZK9Uc+mnRi3hn0slXk+2FaU6BuwJeZ/pSZnWtmN5rZw/lcf0lL91H2C/HlzwvD3JbAeT0Y5vKYML2cv5tsfk37zbdyRDDFysvn2BcK+vRs3/mZ/L20XLN3krMY7bE/Rnoo40STX8slewiEXb7uvYywLkiUR4sH2h77IC/P4X2+b6YNqCzzO9tnv+9n9HSh/Frf0e+7vdP0q6ak91Y+jX/3Pssyo5R13i7Hc3R7EIxbvzCPMKP0/7INtkUz+edI2pbR5HWemqbJDYPx7NfnmtkJZrYT7nHwauBr+HS5PFbkOsCZkraqyKbI6w9m9gb8Q2VnfJX182j/AJwKHCnpwB7q0Y3caLYiHnYFOseTKyhWTHxGPnni5NOaFlijXNLTrs12VS140YRh9vfjde483168tgfl3T+wPkbSFsAe2a63mNkbzOwnZnaVmd1X4Qnbz7fRhGK+qMN7sl07MLo/yMnv6S1j0E26xQNtdO0kLUK7saxrvNAxMGid5VPZ718CW5rZ183sj2Z2u5k9moyOBePVnsrP/wZ93tNDqjI3s4fM7DAzew4+c2A/3MA9uyS6E3B+itcYLIRMhFGu3EmtVinVH3dmvzccYL67Zb+/aN2DT/cVcNLMzsFXbis6sucB56apNN3I695pOuozpNHfaV3E8kC06zXJN5F7QHYKZjuS/Z5e+vsg7bFccvkVcCV3W3qPJzcs8usgGt4n2q/lXOb9eHLjgnlsntxjolF7lFQsxlLQJLhyE8brfbNQkbylc4+ZC210TI38Wq/W58DHIMmnagzq3uf9yrzennruFyr6m0E9hwMlTVEcxEpuMyr2lXWHYd3n8e7XATCz+83sNDP7qJm9EDfEHY4vAgT+8Xhog3weN7MLzeyLZrYrPj3wvbRPp/2CpEF5OPw+KyO0pt8WBqb7qYlTZu4tWKzWuJWkxfHB51y/HhlQOedVcj2/Lx1/mP39OJ47n8bbaKXoZGTp5RntxCD7mPy76AIz+1mDNMNc3KExZnYS7c/ozPQcV5HrJmtIGq9YvU2/F8ptZTxDYQysPclX2d4s/Wt4TOpuMczHqz3dTfsA0rj102b2HzM7zszeaWbPwmOo/ioTWR94/3idP5i3mQijXNnANMhg1vnyyFtKKs8L75c82GTHZdET/c4/x8zOpt0w93zcMNdtFCJf4XLL1JF3YyM8dkIncqPYWpLWrJVsJ/deKxvWckay37tUxJMrrzbUJs/8M3UVXInPO5lt6gRL5NfyajObUyu54JO386bXryxXtRpsbgRqOv08f99M7zLFIajnINr7nqrA4JfS/pH84gGef6z3/iUDKkee5yqS+onTUyZXLAcZQzB/pzd9Djel/YO1U78wTGZkv6/sZWQcn7ZZ8KaKD7kr8fibBf16EY2Vnu9f0kHyNtnz/TOzW8zsU3iw64Kdk8d7L/k8bGbfA96Q7V6G5m2xW/4PUVpxVdJ6tD4Cf18xcJBTeNEtmsqU3+fbzexfgyjnPEyu549Fxx+v/n5Y586/HzZPRrxubE+7F+5YyPuYsb57evouSsaqfmKvDouDst9rAe+ukfsTrX52Eu3fJIOk1qO4g9wTNF8goh/y9rRGw3BUdeTt6U4zu7lBmqbf2j3peGk2RD5bY1A6XlfM7M94fLncE7vfOIXBfM5EGOXKHUGT1VebcgGt6Z+TqX+J9kpu4LJaqRZvH8vJzOws4DW0DHMvoLthLo9vsgztbuV1vLmBzJ9oj2Xwlm4JJG1Ee4youtgr0FrpDLzjewetdli1tHgeV246/S3yMBTMV53Lp+s2uZZTgDdluzpdy4WBvP6v6TB6mbNP9vtqq161L/9QbrqC2NnZ7xWBNzZMFyTSKlszsl2Xp/dfG2b2AP4uKhjkyGE/9z4v4ysk9bJKWB2X4UGaC95TJ9gD/dStCflzuEsa5e5G/hw+APQae3LcSYb1vJw/7zGL02iPDbtXfjCN/I9ku96dxSubSPL7t0FaWb4be9OKqzsX77v75dTs9xRGB9ZuRJqOnntlrTqGMpXJp5juRLOpq1XHd2bhiSeHpFVoN96ORccfr/5+WOf+LS29fgq+Um033ttApinnZL+3kfTcWsnu9Ppd9Bbm7TiibZjZ72n/BvlEVRswj5WeGyXHy6tpu4bxxfLvukuttwUDe+VPtE+PHYvO0lN7SqGdXt0w77HqePuNowfkKNKAz2nZrkH2a8F8xLga5dKo0IezXU8AvxtU/mb2IPDDbNcnk4ForNye/e4YA0/S3rTHR+oLMzuTdsPcC/HAj5VxKNK0zfyj9Qud4tVIWhXoGoMlXdNfZLs+3sAD8SvZ77tpf7mU83+E9g7t49nvUUa5FK+kGMHYmfknnlzBMdnvl0ua3kX+QNpdtI8eeInmL46h1WGvCHyik3D62My9KequX+6Gv1Ldc5ZjZtcBZ2S7vpKeq6ALkiZLOgiYle1+BF+9sY4jst+7paDAgyC/9xs0TPMTWtNCFgG+10OMyErM7Enge9muAyQ9byx50l/dmnAi8Gj6PZkuUxCT0fKAbNePGkxNGQa74QGlC35RJ1hFmvaWK/MzKsS+lf1+PsOZmnIe7VPpDu9kHEzTxT+b7fp1OYxHj8bFsof+M8boXvJJHnb5h/4gQzvkxrPVaTegdBscy4/vgd/nqnwXRL5A+7fEmWPIa7z6+6GcO+mvJ2e7PpOmy9fl+UraB2XHyqlA7oH03THEtezlu2h5vF3Mb3wx+70G9YuW5LrJyyUN8p4VTCqVZxSSdqTdIWPWOJTjGVLMwO9nuw4cg6E3b0+rN/C6+wrNDWz96EFH0XIYWRn4asN0tYyhj1woQxYF42SUSwH5d8NHD/Ppj99KRp9BciitOA7LAL+VtEODMm4l6WeSqlZzGcl+f65utELSK2g3uoyJZJh7HS1PtRfRwTBH+4fRFsAPJY1ye08jDKfRfepqwZdpvZxWAk6vWoBC0iRJXwZele3+34pgr2VGst9F/JH7gb91kV+OlkI+r8eTK/gJcGP2/0l1nZikvYDDsl2/MV+5Z6ElTfvJvVc+J+mtVbJp+t8ptN5rt1HzfJrZrbSMLKKBwTrxKVrTc9bCg7Ju0kG+eE5eIumsAU1RnC9I9d5U0keA63EFs7g3TwFvNrO6Zx78Yyb3QDlWUldPI0nTJH1F0qdrRPJpaluqZkXIHDN7FPhMtmt34ORu8T8lLSlpX0m/rRH5Oi0FchHg7KRod8pz2/TxVkVet/f1Ok2wjuS5eFS2a4akT9aUb3Xg17RWNHuE9o+YeYkZ2e+rzOzaOsEO5O+nXcshH1KIivz+HynpfV2MYutKGpTnPyksxOHZrhcD36r6QJcHmT6FlrFyLu39UsHHJX2nk5Eh5TeV9g/0S5MXecFOks6QtEuDj5hDaH2YPUH7dKqxUl49ttAjyx7vo0j9SdHPb027F8jIgMo3TyHpWZKOod1b5ibgx/3mOV79/ZDP/RlanjtLA7+TtFc+qCNpMUkfAE7CDYMD+ShPAyF5P7gtcGqVPl8qy/uSB2TOSPZ7G0nvqEm/Kj5Q0cSbep7CzM6n3SP4kzV96EnAH7P/fyRp/wa6ybMkfVVSR4Nvxn6SPlqT10apHAWzgZ82zHcsfJWW7rwoPqur47RSSdtLenm+z8z+TbvB+Kia79dJkr5AMy/TglwP2kMNnHXS9NmvZ7veJ+koSR0NgZKWk/QhSSdUHD5J0ickrdwljw1p95Bd0Adyghr6HTFZVdKoKUd4B7UMHrusbEi6EF9Ja6CY2W1plOIs/AWxBnCRpPOA0/EliB/GO8O18BHMl9EKonlsRbbfxFdHUcrvr5K+jb+sHwfWBV5Pyxj1fQY0ddbMzpD0OvyDdFE8XsDZknYrGzTN7DRJP6c1Wrcv8AJJ38fjCiyCK4jvw41f1+Oux/koblUZrpQ0E/hS2rUtcLWk7+FK8Bx8usI7cY++gotpf6nVMUK7ogDVwd5z+Q9V7JvnMbNHJb0d91SYgo/AXCbpWHw65L244fr1eFyBgnvp7EW0MPEBfGR2dfwdc7ykNwM/wz8ClgVeio9qFh3oXOCdyZhQxwm0PHk/L+mdwDW0pqMBfNPMnvHuNbO/p4/l4/D3w8bAlZJOx99BN+IeRcvi74kX4gacQkEdxtS18WQfSeW4OkvhBvS1qR4IuA7Yx8w6xqUxM5P0Rjy+3Nr4+/B7wIcknYTH77kPv+er4AMTO9OKsfLlmnyvkfQ3PJal8I+kK3EFMffmereZ3ZWlO1q+cmTxXO4FvETST/H+7Ta83S2Pvx+3xj2xptIeHDovy93pw+8s/H29MnChpN/gAyk34H3OKvh7e088VtvnccNXmRNoTaveHbg91TXvO35nZt+sKk8XPoePym+e/j8sDUwdB/wLWBI3ZLwHX5in4P+Z2ew+zjeuyMND7Jnt6slLLuN0/J2xOP5+ehvtBjDwaW5/xvWJycD/4VNZT8Q9wR/E282mwK54mIaLaPdKGCvfxdtsEbD9A8COko4Grsb7pxfiHwe5t/aXzazK+LVEkn2vpCtww+Nf8bb+KN4GXoCHqMgHNssr1Al4edpulXQmbgS7Cb8uU/H37Ftoj590lJkNbEVfM3sg1aPsrXpJ8mrtxkWMDs5+V5+G3nmBr0iqMg4tgd/Pcl0fBvZOAxhjYbz6+6Gc28xmS3ovLZ1hNdygd6ek6/DnblNafeVX8QH5YrGRMU1HNLPj08BTYUR7BfBvScfj/dad+GD3uvisn1fj76Kyx+OF+PNdPB8/lDtfnIx7Pa2AT9veH79Ot+IhC17O/MUhtOq+Jv6d83+5gJnNlfR6XDdZE79+P8A9x07CHQxy3WRL/H4WYQO+RHd+hntN/m/Wz96AX9uX4HpI3gbfN4Bnrytmdqc8DMkZeNtdBbhY0hl4X3gD3mZXpaWzbIJ7Xv+mlN2RtDzSdgf+Iuk7+MI5i6R0b6cVm/AHNPsuOgdfFGglXB+9StJf8LZexCp+2sxeV0r3mVTmwlnnA8AbJP0EN8Lehb8XVsCf2W3xe7EI1eEdVsd1gUMkjSSZv+Pfd0+n49Pxb/diEPN+4NsN6hgsiJhZow13i7U+tqfxB29ql/xnZ2mmNy1Xln573OOg1/LtXpPfJxumPx9/Ief7pjW4hjO71OeV+MdYIf9HYJkKuSVwA1W3ct6Ld6a57IwuZfhSD9fxImDZhvdqSfylnaf/cAf5FfBOJ5d/T4PzzMjkRxqWbWaWZlav7bBDvnviI+5NruVtwGZd8puWpxlUOavy7tZOGuY5Pctvdh/pN6T9HdFpewL/OOiW57J4B9kpr8q64x+3D/XwfBTbRjX5NXl/9Nw26eGd08O96LXOxfZ33Li+ZI/nW4NWcOVetsM75PlCXGnulH7UfcA/qr7I6PdRt+2OLnV8Ca6MNc2v9l7iniqd0s4qyU/PjnV8NnEF/K89lPMjXfKbkcmONGwPPT8HNfm8r1TWTcaQ16lZPtfUyKyLf2w0vXaV16NbG+1Szqn4B0vTMhwJqMF9aLp9oiKf6X3kcwqwWL/3q8P1OaKXZ62Udv+KtCeNsTzlazN90HUe430otkuB53bJf0a3tp3JDrS/H+a5s3zfhhuZO+V3BG7ouCTb94oG92t2l3NPwp/lXu7pqHcLbhz/b4O0/8UXwZiV7at8jhgHXbaiLff03KT2XKS9CVi0Rm5NPBxPr8/LITX5XZzJ7IPrGt3ymgu8q0t9Dsnkj+4gd0smt0OXPHfDY8U2rfNBFXlMxgckm6T/Im4QL/6/vkv5Xo0PltXl91RNusXoz95xcZf72WR7sNe2GtuCtQ16+qrho2U34Vb0TwHrmtmB5rHExg3zIJ0b4Q9utyWh/4uPQrwKOLcmv8Nxb7nbq47jRq6ZwEut+3TNnjGzX+PeU8Uo2TbAWfJYL7ncY/jL8fP4tR+VFe6l9QLrcSqkmX0Gfwl28mi5A/c2erE1HKU0H825tLR7pIP8f/FV7BrJz4uY2WnAc4Ff0u6Nk/MoPkVsczMbzxWU5jvMp5ZsgY+qPVQjNhd/72xpZic2yPMB3PPig/h74HbaveQ6pT0V94b6Fq6YdOJ23CN3F2B+mHI9Fp7E34034t4ux+KxxV5gZpub2Tetx9FcM7sNH3QpPBk78Tj+vnsXHUajzexyYLMkcwneJ3SNeWbOZ3Gj3ql092K4Bh8p3blLvr/F+6/vUP0eL3gE77tOrhMws7fhXre/wEetH8H7gTFj7jm4LT6ifG8H0YuB7czsa4M47zixX/b7GjO7egx55dPeNqrwHsXM/oN7jn0MH3ip42l8+srAr13Sw/bADZK3dBC9Enhl0t3q2s7P8fff9d1Oiw9e7mhmVd6rf8d1qctoX3G5imtwj5/XjofeRfW0oaaLLVUtBrEgTkN6HNexL8Hv/85mtpWZlXW0vhmP/n7Y5zazH+OeP4fS8o59BPccPxZ/X/6P+ZTTfOpovwtX5Oeea2YH4jpIYSioYzb+HXVH+YCZXYN7gI/UpH2a1nUZ5NTyiSb35l2blpdhG+bT1rfF9Y1uHrFzcD1zf2q8+Cvy/yxuzK1bmfRq/NvrB03yGyRmdg6us3yP9oUVyjyCT6s9pSKPp3GHha9Sr3tfh7/vP1tzvK58v8I9FL+JDyTeT/f+BTN73Mxm4N5yI7SHNBgljk+VPQhfGKnMYXg83rsrjuU8intCbmq+mFGwkKJ6fWv+Jc3r3wKfZrMy7k32MK4IX4OvktTpQcvzWhR3Z98Ud4O9C++0LrBmUxomDPlqMS8F1sPdaW8F/mhmNw4g73XxD+PV8Glkd+OKxWUdlPaggjRtajo+RWgZ3CBwAz6Ft5FRaGEmPZM74CPaK+LP9q34CHgnQ8F4lWcybqTZBHeXXwRX5m/G3zXXTXSZFmTkiwhsg0+PWBZXaO7BDZ5XWnu8qvEuy1T8vTgNb4tzcSPtDcDfzaxuUKdTnoumPDfA29NcvH7X4qvVjocxomdSu9+aVrt/HDdAX5gMqUENSUfZEh+oWQV/Z9yPG7guM7P7OiQfZDmel8qxMv7BcieuM/y7x3xWxevyLNyzfTJudJiN12fUB35NPkul8qyPX5fF8Of7NuAv8S5d+Bhmfz+Mc6f4U4VjwdP4DJmBTktM8eJ2xL3Qiz70FuBvTZ+xFKdre/w5fQR/Ri9u+qwviKTvpG3wa1Jc17tp6SYd9XtJF9NaOPBtZnZ82j8Jb4fPwfvae/D34Z/Hox69kj0n69Ous1yD6yxdp2CnOIfT8e/XSbhR+Coz+0undOONPG7wDvj32vL44O19eF99RXIaaZLPhriutA4eTmsu3ucXel2nwdhgIWGBNMoFQRAEQRAEQRDML6RFAIqYlH8xsxcMszzBxFFnlAuCYOFgXFZfDYIgCIIgCIIgWJjptipnJvdcPCB+waxxKVAQBEEwzxFGuSAIgiAIgiAIgsGzn6RfSHqVpCXKByUtI+lAPN5bsQrjTYRRLgiCYKFhyrALEARBEARBEARBsAAyBXhd2p6W9C88fuNcPJ7jxngcxoLHgH3MrG6hiSAIgmABI4xyQRAEQRAEQRAEgydfWG4yvmrlRjWy1wNvNbNLx71UQRAEwTxDGOWCIAiCIAiCIAgGzyzc2LYHsBWwOr5K5fL4iq53AZcCvwFOMrOnh1PMIAiCYFjE6qtBEARBEARBEARBEARBMMHEQg9BEARBEARBEARBEARBMMGEUS4IgiAIgiAIgiAIgiAIJpgwygVBEARBEARBEARBEATBBBNGuSAIgiAIgiAIgiAIgiCYYMIoFwRBEARBEARBEARBEAQTTBjlgiAIgiAIgiAIgiAIgmCCCaNcEARBEARBEARBEARBEEwwYZQLgiAIgiAIgiAIgiAIggkmjHJBEARBEARBEARBEARBMMGEUS4IgiAIgiAIgiAIgiAIJpgwygVBEARBEARBEARBEATBBBNGuSAIgiAIgiAIgiAIgiCYYMIoFwRBEARBEARBEARBEAQTTBjlgiAIgiAIgiAIgiAIgmCCCaNcEARBEARBEARBEARBEEwwYZQLgiAIgiAIgiAIgiAIggkmjHJBEARBEARBEARBEARBMMGEUS4IgiAIgiAIgiAIgiAIJpgwygVBEARBEARBEARBEATBBBNGuSAIgiAIgiAIgiAIgiCYYMIoFwRBEARBEARBEARBEAQTTBjlgiAIgiAIgiAIgiAIgmCCCaNcEARBEARBEARBEARBEEwwYZQLgiAIgiAIgiAIgiAIggkmjHJBEARBEARBEARBEARBMMGEUS4IgiAIgiAIgiAIgiAIJpgwygVBEARBEARBEARBEATBBBNGuSAIgiAIgiAIgiAIgiCYYMIoFwRBEARBEARBEARBEAQTTBjlgiAIgiAIgiAIgiAIgmCCCaNcEARBEARBEARBEARBEEwwYZQLgiAIgiAIgiAIgiAIggkmjHJBEARBEARBEARBEARBMMGEUS4IgiAIgiAIgiAIgiAIJpgwygVBEARBEARBEARBEATBBBNGuSAIgiAIgiAIgiAIgiCYYMIoFwRBEARBEARBEARBEAQTTBjlggUSSTMlmaSRIZ1/Vjr/rGGcfxgsjHUukDQl1d0k7dD0WBAEQRAEjqTpRX857LJMFAtjnXMkHZ/qf3Qvx4IgCBYkwigXDBRJs5saZiTNyIwV08a9cME8S2bQK2+PSbpJ0q8kvVGShl3W+R1JKySj9UxJywy7PEEQBMG8QTaguVAaiOY3coNeaXtK0r2S/iDpc5JWGnZZFwQkvSM9IzsNuyxBECxYTBl2AYJgnLgH+Cdw07ALEvTEXODu7P/lgLXTtiewn6TXmtnjwyhcnxjeFgEeHWZBEisAB6ffRwMPDrEsQRAEQRCMnfuAJ9LvxfC+ftu0HSBpdzP7y7AK1ye34frT7cMuSOIdwPbAU8CFQy5LEAQLEOEpFyyQmNlRZraRme077LIEPXGzma1WbMASwMbAr9LxlwMHDa10fWBmT6e2uNF8qBAHQRAEQTDv89pMf1oeH9T8f7ihbmXg55IWGWoJe8TMPp50p88OuyxBEATjSRjlgiCYZzHnWuCNwLVp9zuGWKQgCIIgCIJ5GjN7wMyOAA5Ju9YDdhlikYIgCIIawigXzJOUF2qQ9BJJZ0i6W9IcSddIOljS4k3Sl461LUgg6fWSRiT9V9Kjkv4m6UBJHZ8PSW+V9HtJD0l6QNKfJL27W9yzLObH9A4yI0lmZgeZrSUdK+l6SY9IelDS1ZKOkbRbh3R7STpV0m2SnpB0n6QLJb232yhqv3UeK2b2BPC79O8akpbvUMYlJH041emeVMfbJZ1Sd11UWoxB0uqSvp1iJM5J6X8s6dm9lr2cdwe53SX9LMXQm5Pa4xWSvilp65LspFTOL0u6RNItqZ73prbz7qp7Keli4F/ZrptLcWjOqyn/OySdI+mudJ67JZ2lDnH+Urr3SroglevJ9PdaSSdKmtH4IgZBEARDRaUFCSRtkPSNmyU9nvqhH0has0s+G0n6iaQ7Ul93g6RvSVq1S7qui0mpFat4dgeZFeVx1v6U+tk5qa8/O/VZy9akWz+V8xpJD8v1xWskfUPSOuNR5wFxVvZ7006Ccl37xEwPKfS8j0maWpPmmcUY5Lxf0mVynfRBSRdJ2rufgqvBQg+S1pH01aQvPZDuy/VyPXcfSYuV5NeVdICk30i6Tq4/PyzpH5KOkLR2xTn2T+1++7Trixodx2+tinQvkOvpN8hjJD8k/8b4gqQVOtRpW0knqKWDPpJ+j0g6qNszFgTBfIiZxRbbwDZgNh5Da1YD2RlJ1oBppWMz0/4R4GN4rLG5eMyMuVm63wGTK/J+Jn3FsVlFGYGj0u+nU96WbT+qKbeAYzK5ucB/Ux4G/DQ/R0X6It30DtdmJMnMrDg2GTiyVNaHgUey/++vSLcUcHop3QOl6/kHYPlB17lBWyjSzu4g83/Z+VeqkXkOcH2pnA+U6vytinRTsuMzgDvT70eBh7JjjwK7dkm/Q9Nj6fhU4JelMj4IzMn+v7yUZoOS/JMV9RwBFi+l+xUes6+QuQu4I9tOKsmvDlxWyvf+0v+/BBapqPNvK9LldXpq2O+r2GKLLbbYWhst3ckqjk3P3t+7ZH3jg6kPKo7dCqxZk//upX7gIeCx9Ps24O0dzj+LLjoGLb1yds3x3XDdJe87y7rfXhXp3oVPAy1k5iR9INelRukGY61zg/uV35PpNTJbZTIfrZFZhHYdr7ivT2X/Xw2sXZH2+HT8h8AvaNepc/3y+4A6pD+6l2PZ/c6v7eOM1lE2K6W5uHT8Plq6bPH/tqU0b8F1pKINPES77nQHsHopzSGl+j9SakO3AM+tqNM7S+nmMFq/22fY74rYYottsFt4ygXzOlsAh6dtFWvFyfhCOr4LsF+fee+JK1r/DzdELQ+shAe/B9hX0osr0n0QV6LAjXqrmNkKeFDdmcCbgFf3WaYmHAp8KP0+BniOmS1lZuuyhlQAACAASURBVFOBVYG9aB8ZLfgx8ErcaPUWYBkzWxZYMpX3Bjwg8DEVaYdaZ0mL0pp28aCZ3VMhswJwDrA+cB6wI7BEquPywEdxpegASR/ocLpv4Mr2S4GpZrY0fl3+gce4O0nSGgOpmHMc8BpcCTsMWMvMlknnWgt4G/CnUpongVOA1wNrAoulei6DT++9A9iZ1nMCgJm9OtWl4PmWxfAzszcWB9Lo8q+BFwKX4/H8pprZcsDSeHu4O5X90FL59gFejH94vANYKqVbAm+jrwdO7uEaBUEQBPMOJ+ODohun/moqrgc8BKyB92VtJE+in+GLEFwJbJ3616nAHrhh5OvjVWBJz8MHppbH+/OXA0sm3W8q8CLga6kOebq9cIMSuC46De/LpgIbAT/H+95flD3mhl3nxO7Z7xtqZI7A+/TbgfcCK2R6yIuBK/D4vidLtTMjXofrA58GlkvXdTXgO+n4u4D3jaEebUjaE9dXFwMuAnbAdb7l8O+EnXFD4ROlpH8HPpHqs0Qq52K4bnRuSntS7mFnZieYxzm+NO36ckl3Ws3MnlmMQtJHgc/gbekTwGpJR18Cb2cjuO52mqQls3RL4YPuAn4ErGdmiyf9bqmU9qu0L4gWBMGCwLCtgrEtWBuD95QzKrzFkszJ6fi5FceK9CMVx2Zlec+oyfvydPwHpf2LA/emY8fVpD0sy3/UdciOTe9wbUaq6g48m9aI3pd7uC+vSGlup34Eey3c486ALQdZ5wblK+7J7NJ+4d5vp2T5H1mTxxHp+DnAlBqZNySZO8g8LGn3ZpsDPLsi7Wq0RtSPLB3ry1MOeFl27F1jff6yfLehNdK9aOlY7mW3Voc8DkwyV+BGtSqZYgR+DrBitv/7af+3B1Wn2GKLLbbYxnejuafc74BJFTIfTMcfLffDtLzd78EH9sppNyPzJKo4XugJszqUf0aVLpGOXZSOXQcs2/B6LIp7NBnwjg5yv0oy3xhknRuUL78n00vHlgU+jHuPGT4DYPGKPLag5f21Sc15lsW9+gx4ZenY8VkZPleT/qfp+F0VOknPnnK4Z99/0rHzKXnrj6H9TwGuSvnuXXG88LI7qEMeq+IDkk+X70mp/H9LeR2Q7d+Olu42ahZQbLHFtuBu4SkXzOs8jo8KVVGsyPncPvO+GfdSquK0mrx3w73DoOSFlHE4bqQYD/bDY0HeCxzcQ7r9098fm9mtVQJmdguu3IAbiwomss5rp5grd0i6A1dsrsW9/wB+D4xahUvSZFqefF81s6dq8j8Z95ZbFdiyRuZEM7uuvNPM7qA1Wt5XfJQKikUrrjCzHwwoT8zsEnyKztL0/3wUbebbZvZwzXkuxe/PYvjHQcH96e/qfZ47CIIgmHc51MzmVuwv9LIlgA2Lncm76k3p3++a2V3lhGZ2FT79ceBI2hD3pAL4tJk90DDpHrhH053AsR3kCl3yGd1pCHX+ZaY/3Yf3w0fghsWHgDeaWZWeVvT1p5vZ1VUZp+tV3NuXVcngutXXao4VuuPKwEs6V6MRLwUKr8T/MbMnB5AnSXc8O/1bGwO4C/vgg9l/MrORmvM8iRsqof16FrrTorT07iAIFgKmDLsAQdCFf9QZBPBRO+i/47qsRqnslPcL09+bzez6qoRm9oCkP9MKCDtItkt/z61RruoolIt3S9q3g1wR4HjdbN9E1nkSbjCr4lB8FPbpimOb0Sr78ZLq7iv4xwJ4Hf9ccfx3FfvyYx8HVpG0tpnd3EG2CcX9PL3XhGlqxTtxg+VmwIq4IldmLdzzs5e8l6MVEPowSXXGWGg9I3mbOQOPBfkaSWfgU6cvsGx6RxAEQTDfUg6pUHBb9jvXn56V/d+tj33zGMpVR9HXPg2c2UO6QndaHri9fubmM31v3g9OdJ3rFsD6G/DyDv1vUcdXpcHQOpZKf9etOX6pmT1SdcDMrkl5r4brlL3cgyqK+3mrmf2t18SSdsL1p21wo2vVIhajFm5oSHE9t+xyPXNdtOA6fDGuDYE/SfoOPvvjqhrdNwiCBYQwygXzOg91OFZ4Q/XbjpvkXV7BcpX0t9LbLOOWvkrUndXS3/80TSBfhXOl9O+ytIxXnVgy+z2Rdf6PmU2DZ7zf1sTj383EjWF/B06sSJfHeFu54bmWrNnfqZ75sVVwb8uxUBggG99PAEmr4QspbJLtnoNPkSkUt5VxI2flimldWB2fOgzNjd7PXE8zu0DSp/DR8ZenDUk34/H+fmRmF/RRriAIgmDImFml/mRmT2WGq1x/WiX73amPHW/d6Z46w1ENhW6xKPUDhjlLZL8nus67FJ5ZKcbutsBX8FkB35H0uhrDTlHHpWgZ3jrRj+5UHF+N9uvSL8X9nN1rQklfw2NJFxSLUhSx55bC9aZ+dCdoXc8laG8PdeS601Nppdpf4kbdr6TtEUl/wGd7HGdmj/VZtiAI5lFi+mowaIqOoqeOKEs3v2Dz0fknZ7/3NjM12GaM8ZxjxsyeNrObzOxw4D248fUYSRtXiOd1XKlhHY+vO/Wg69KAXs95JG6QuxuPobOamS1hZitbCjqMx26BlnGtF/Lr+cKG1/OQtgr5fXsWrvz+KpVnbXya8Yikn0qKgaEgCIKFi2HqT72eu+gLz2rYD9b1txOtP/3XzM7AF8i6E1+Ia1Toj0RRx482rONL60474Go0oadzStqDlkHuW/gsg8XMbIVMd/pWId5nmYrreVTD67lBW4XM/oLHj34DHjLlH/j30q7Ad4FrJW1KEAQLFGGUCwZNsSrmmg1kC5m5ePyr+YHC0NHNrb1T/YuRysU7yNR5sxXTD6Z1Of8zpGmuRfyUzZumyxhEnceEmf0IuBA39n6jQiSfItBPHXM61TOv46j4MH1QlHta0wSSFqcVY+/9ZvYjM7uzJLMIY4tHkufX9/U0s1vN7Agz28vMijh+xeq+ewPvHkMZgyAIgvmDvL9s2seWKWYwjEV3WllSLx5QRR89Ft0J+q/zmEhx7D6V/v2kpGkVYmOpY05THXEQulNxP5/VY7oiHvAZZvYhM/tHhffgauVEPTLm62lmT5jZL8zsPWa2Ge5d+H485tw6dI5vGATBfEgY5YJBU8Toel4DxaeIu3DloIK0TgBFbK61Ja1fJSBpGeAFHfK4r8ijJv3S+FLtVfwh/d01GWea8vv09w2Sen3uB1HnQVAsbLGbpBeXjl2BrxwLY1+EYZcGx+4aQDw5aN3PV/WQZhVa8Wv+WiOzE9Xx5cCN4AWVI8Fmdjce2wQGt6gFZnaFmb2TVjyiXQeVdxAEQTDPciOtwddOfWy5b8/pqDsltq7ZX/S1k/HFG5pS6E5rSuo18P8g6jwIjgP+jS/IVBUftqjjq3o0WJbZSlLl1FZJG9EydvUU47aG4n6uKalu0a4qirZTqTsl/bjTvSr0p05edMX13F5Sp7baGDO7x8y+Q8vA+iJJTULRBEEwnxBGuWDQ/Cz9XRL4UJ2QpO2BHdO/J413oQbIubQUw7qpAB+n8/TdK9Lf19Uc/yiuPFUxC/e0WxH4fIdzlClWDX02HoC/FklTJeUGnUHUecykWCmFIvbF0rEn8WsD8A5J23bKK8VbqWNvSRuUd0paBXhX+vdn5eN98sP0dwtJ7+oo2eLB7PcW5YPJS+6Q8v6a9Mt1kCvazMskvb5TgcrXMy1C0YliunoELg6CIFjAMTOjpeu9V9JKZRlJmwCd+ppCd3pRlbEjhbZ4bc35r8e97QEOTQOJTTidllfWkXVGp6wMz/SFA6rzmEmeYF9O/741GchyipXfVwAO75SXpEU7GO6m0h6rLeeg9PceOi960ZTzaMXi/UbSe5pQzBoZpTslPkD9QhbQ0p866U7HAY/jIVeO6jQQLmlSblzrQXeC9gHWIAjmc8IoFwwUM/sjHogU4BBJh+bKk6RlJb0TV3QE3AB8e+JL2h8puGphENpP0jckrQjuLSbps8CnaS1rXsUzy6BL+nyhHEpaSdKhuPJSmT4plv+b/v24pKMlbVgcl7SypDdJOqWU7ldAse9wSd+R9Ows3aKStpb0ZVzRWSVLO4g6D4pD09/tJO1eOjYTD/q7CHCOpA/nSrCk5STtIek4YKTDOR4Hzpa0i1LEaklb4UrgCrhS9uUO6RtjZucCv0j/flfSlyStmc4pSWtKerekH2Rp7gcuSf9+Q9L0QumT9FzgLFzhfLTmnPfQml7x9g5x3b4NXJZ+/zS11WempyTj7XRJ/0fLq67g9NQ2d5ev5FqkWVHSwcD0tOs3NecOgiAIFiwOwxfYWgk4V9IL4Zm+bjd8Rc7KfitxOu4RvwhwkqTnpPSLSHo13kd3WsThQHxBpA2B36f+aZGUx5JJB/qupGdipqXwH+/HY5c9P6V7WT5wKelZkt4j6dIkO8g6D4of4QstTMJ1pWcws8tpxVE7QNLPJD1jtJI0RdKWkj6He9zVTct8APi8pE9IWiqlXVnSUcBbk8znzezxsVbGzJ4CPojfl52B8yRtl+lCy0h6saQTinaSOCv9fZWkTxcGRknLSzoIOAK4t8Opr0p/XyFpjSoBM7sV14kB9sT10bxskrSxpI8AV9PuubmPpIuS3rdesTPdg91p6cAX1S22EgTBfIqZxRbbQDdgaeDXeGdZbA/hbvxzs33/BJ5Tk8fMJDPS4TzTi7x6SY97VBkwq0PeM5LM7Ipjk/CRsKIeT6e6PZX+/2mnc+DTJ36XpS9i6s1N20dxo5EBM2vSH1VxfR/J/r+/It2SqWx5uofTuZ8u7V9zkHVu0GaKtKOud4XsX5PspRXH1geuLNXlPlxZzPddU0o3JTs2A4+pZumaPpQdewzYveK8efodmh5Lx6cCp5bK9wD+8VD8f3kpzVal+z0nK+cTwJvxFd0M2KfD81HU6SbcoHl8SW5l4PyKst1H+7P8WCndxRVpyvfgRGDSsN9XscUWW2yx+Zb3DRXHptcdK8kV7/jpFcdeUerbHsSNUgbchi8EVHsO4J2lfuRBfCDNgD/ink61ugSwGz6AWKR/Atdl8jz3qkj31lKf+yTu9TWnlPYzg65zl2s9nQ7XuyT7YVo65+alY1PwBaTyujyKG6ieKu3fupT2+LT/h/ggo6U0ZZ3/GEAV5SrSH93LsXT87dn9L3Sh+0vl3SyTXxSfXlocK/TvQgf+FW5INeC8ivNtlN3Lp/EBztlpW60k+8nStXs8tZknSuV7U5Zm/9KxOSlNrqPfDDx72O+K2GKLbbBbeMoFA8d89OZVuCJyIh5XYxJufLgTOBt4L7CFmf1zWOXsFzOba2b7AvviHkuP4QrNX/B6vaVL+qfxa3MwcC2tDvocYFcz+2q39GZ2AB6T7ye4QWWRlM8/cMVo1NRYM3vUzN6Mx8v4Me6lOAlf/v0u3FD4cWBD85G+gdV5wBQjhS+StGepnP/GY9vNAM7AFaapuCJ2A77M/NtpxTOs4nrgecB38NVNF8Xb7QnA88zsrA5pe8bMHjGzvfAR1VPxqTJL4AbTK3BF+b2lNJfisXN+jitsk3BF/2fAdmb2UzrzBXyayZ9xpXEtfMpGW4Bj89hyLwZeg3vA3oJPrV4i/f4N/hFUjjX4flwhPRO/npNSmltxpfc1Zra3mcX0iyAIgoUE8xVBn4/rhnfR6l+PwvvdG7uk/yHwclxfeRDXQ67D+5ud6ewph5mdg3vKfQkf4HsM75tm47rpe6iYXmlmPwE2wENDXI73z8vhRpO/pfK/lAov+rHWeYB8//+zd99xclV1H8c/J1tTNp000pjAUIZ+ITQpS6giVaSID4KgCKigoiKyCFy6gAUEwQJSRJEuvThBwAd4GKoLOJBJgEAa6b3snuePczeZ3WxNdudM+b5fr3ltdubOne9M2tnfPb9zcGMaQ4vlT6y1a6y15+DGT7/HfaaNQH9c0epF3Jh1B2vtK7TOAscB38F9JhW4349/4y4OfsNaa7vzDVlrb8MVyn4DvIcbz5Tjxh0P4oqp6azjV+F+n0LgA1xxFdy49gzcJlptLqthrX0fNyb6B27sNQQ3dhoXvW72sVfh1of+NfAOrig3EHcB9VXcn5U9aL6Ez4PA13EXqt/G/RkfED3nFVwnzbbW2pbdCSJS4Ew3//soIlJwohbOpsHZ3tbaF33mEREREcl3xpi7cMWvP1prT/edR0SkEGmmnIiIiIiIiIiISI6pKCciIiIiIiIiIpJjKsqJiIiIiIiIiIjkmIpyIiIiIiIiIiIiOaaNHkRERERERERERHJMM+VERERERERERERyTEU5ERERERERERGRHFNRTkREREREREREJMdUlBMREREREREREckxFeVERERERERERERyTEU5ERERERERERGRHFNRTkREREREREREJMdUlBMREREREREREckxFeVERERERERERERyTEW5dhhjyo0x5xtjPjDGrDTGTDfG/LKbzr21MeYFY8xSY4w1xoxv59hxxph7jDHzjDHLjDFvGWMO6Y4cG8MYc7sx5rWs70+J3ku/bn6d44wxp3TnOUVEREREREREfCr3HSDP3QZMAi4B3gfGANt007l/AQwEjgCWAjNaO8gYMwb4X+At4NTo2B2B3t2Uozs9BuwBLOvm8x4HDAVu7+bzioiIiIiIiIh4oaJcG6KZaCcAO1hr3+2Bl9gKeMRa+1wHx/0CmAIcZq1tjO57tqsvZoypABqttQ1dfW5nWWvnAHN66vwiIiJSfIwx5cB5wGnAWNxY4u/W2u93w7m3Bm4Fdgb6AJtZa6e1cew44CrgYKAa+AD4ibX2yY3NsTGMMbcD21prd4m+PwV34bjGWrukG1/nOKCPtfb27jqniIiItE/tq237BvDPDSnIGWN2NMY8F7WazjfG3G2MGR49Nt4YY4EJwPejds/JbZxnAHAMcFNWQa6zGSYbY+4zxnzLGDMFWAGMih7b1hjzmDFmcXT7uzFmRNZz94tyHWSMeTRqsf3YGPPtDl5zvfZVY0xvY8w1xpiPohbgqcaYK7MeP9kY82LUmjvfGJM0xuyS9fjtwJeBfaNzW2PMxVmPH2mMec0Ys8IYMzN6rYqsx0cbY+41xsw2xiw3xkwxxoRd+SxFRESkR90GfA+4FjgIOB9Y3k3nzu5M2IOOOxMG4joTjgDupPQ6E07p5nOKiIhIOzRTrm27AY8YY24ETsZ9Vk8C37HWftbWk4wxmwCTgfeArwL9cFddn4mKTTNwA6kHgX8CNwCL2jjdzkAFYI0xLwETgVnAb4GrrLW2g/ewF6749xPcwG2hMWZz4CXgNeB/gDIgBP5hjJnY4px/xA1Ib8AVB282xky31j7awes2fRYGeDh6vyGQAjYF9s46bDxwB242YCXuM/uXMWZba20met5Y3CD5rOg506PzHwfcA9wCXBC91ytxxebzomPvwA2ovwUsAGK4WYoiIiLimToTuk6dCSIiIkXEWqtbKzdgJbAYeBH4InA88BHwCmDaed5VuOJP/6z7JgIWODHrvmnAtR1kODF63sLovLXApUADcFYHz52Mu8o8osX9dwL/BSqz7tsiOudh0ff7Ra97a4vnPgO8nPX97cBrWd+fEj2vX/T9wdH3R3TyM++FK36+D1yUdf99wOQWx5ro9+O2Fvd/I3rfQ6LvlwCH+/7zpJtuuummm266rX8D7gWe2sDn7gg8h7vwOB+4GxgePTY+GoNk3ya3cZ4BwKrscVoXMkyOxinfwhX1GoAx0WPb4ma1LY5uf88el2WNtw4CHsWtG/wx8O0Wr9HueCu6rzdwTTQ2WglMBa7Mevxk3Jh2XvRZJYFdWrxGy8/r4qzHj8Rd0F0BzIxeqyLr8dHR7+XsaBw2BQh9//nSTTfddNNNt3y/qX21bSa6HWmtfdxa+zfczLKJwP7tPG8i8LS1du3sN2vtq7gi3Be6mKHp9+cJa+351tqktfYi4M/ATzvx/JS1dmaL+w7AzdJrjHaXLccN3KYBu7Q49sEW3z8ABMaYsk7m3x+YZ619pK0Dol1oHzTGzMINZFcDWwLxDs4dx82gu7fpfUTv5Z+4dWC2jY57E7gyaq0d28ncIiIikhu7AWljzI3GmEXR0h8PGGNGtfekrM6EPrhZ9t8F9sV1JlSyrjNhJvCX6NdntXqyFp0JxpjVxpjpxpifRrP+O7IXcCauM+FwmncmVOPGj6cACVxnQstz/hF4G9eV8ASuM+FLnXhdoFlnwpm4boovAj/HbZLVZDyue+AruM9rOq4zIRY9HuIKdW/gPqs9gD9E5z8ONwZ8FdfWewmuCHnlutNzB25DtG8BhwKXA1WdfQ8iIiKlSu2rbZsPZKy1c7PuexF3JXUb3JXZ1owE6lu5fxYwuIsZ5kVfky3u/ydwqjGmf3bxr43XbGkobtD4k1YeG9Pi+9mtfF8enaO1c7c0hDbWbgEwxtQAT0fn+gHu6u4K3CCwuoNzNw00H2/j8ab3cjxuYPhLYKAx5i3gh7bjNhYRERHpeSNwBau3cG2sNbhZWA8aY3a31ra1VMcPo68HN42FjDFpXEfDl6219wAvG2NWAjOstS93kAHcchg3AxfiuhMuw3Ur3NTBexgI7JR9IdQY81tcQfBQa+2q6L63cd0AX8TNoGvyhLX2gujXT0WFsgtxs+c64yDgQNyF5OwLoXc0/cJae2lWtl647oddga8Bl1prpxhj5gG9sj+rqOD3C+AOa+1ZWfevBH5rjLkyGitPxM00/Ed0yOROZhcRESlpKsq17T1av8JngPY2XZgBDGvl/uG4NdW6mqE1TVdYO9r8obWB7DzcDLg/tPLY5y2+b/k+hgFrWjmuLXNxRcq27IFrdzjQWvt+053RBhcdaSpYfgt3VbelqQDW2k+BU6IB6ETgYtxagWNbFFxFREQk97I7E+YCGGNmAM/jZty3dRGt1c4EY8w0XGfCPV3I0KwzIfp10hgzGteZ0FFRrq3OhD8TdSZE92V3JmQX5VrrTPiNMabMdm5tuk51JgBXAHvSfHzXpc6ErPuzOxOeZ11nwhDcRmkfdyK3iIhIyVP7atseBbY3xmRP/d8H197wVjvPewU4OJoFBoAxZldc28CLXQlgrZ2Gm3U3qcVDk4Ap1tolXTlf5DncACplrX2txW1ai2OPbuX7VCcHiE2vNbidFoymHc1WNt1hjNkT91llW8X6M+f+C3wKjG/lfbzWsuBmrW2Mrvxegmt1GdfJ9yAiIiI9Zz7wTjudCW0ZSeuz9ru7M2G0MaZ/B89vrzNhdYtbjK51JnRGZzsTxuA6E/bGzZJ7i651JmS/j6nR/dmdCa/hOhM+Msa8aYxpOX4VERGRFjRTrm23At/Drf1xBa6d4mrgWWtte8W163FrejxljLmadbuvvgPcvwE56oD7jTG/wA2o9sOtTXLyBpwL3EyxV4HHjDF/ws162xTX9nC7tXZy1rGHGmMux10BPSY65sguvNYzwFPAX4wxlwKv4wbR+1hrzwBexm3E8HtjzDW4WXMX44pt2d4HjjTGHIVbA+Uza+1nxpgfAndGg+UncAP4GHAUcCyugPoUrn0jjZv5+ENcO0lbsxBFREQkd9SZoM4EERGRkqWZcm2I2iH2x13B/Stu4dzngOM6eN4c3DokK3CtE78FXsANhFZtQI4HcQW4L+FaHY4HzrbW3t3Vc0XnSwO743YquxVXzLoEN1vtwxaHn45b/Pih6PXPbq81opXXsrjZdbcC50avdRnRINNaOwu34PAI3ALF5wLfbiXHTbiC5J+A/8MNDIk23zgSt/va33HtHmfhin+rcL8H7wDnAI/g2kiWAQdZa5d39n2IiIhIj1FngjoTRERESpZpe/1cKVXGmP1wLRzbWWv/4zmOiIiIFKlotvt/cIWf7M6E9621B7bzvE2AD4B3o+ObOhPmA7tkba4wDbjPWnteBzmOxnU0XMe6zoTzgZPbuxBqjJkMfG6tPbbF/XFcZ8K/cRcV1+tMyBpvTcfN6m/qTDiDrE0bjDG3A9taa3eJvj8FuA2osdYuiTZjeAK3Xtx6nQnGmOG4C56v4DbRaOpM6AW83JTdGHMRruX2JJp3JhwP3InbCKMrnQlbAzFdCBUREWmbZsqJiIiIiBfqTADUmSAiIlKyNFNO1qOZctIZQZjsDfSPbgOirzVAGW79Hdvia1u/XgEsAhYCC1N1tRvSJiQiIlJQNN6SDZFJxHvjNuAYBFTi1ggvy/ra3q8bcAXTptvS6OsSYGGsPr0il+9FRERUlBORSBAma3Brv4yNvo4DRgEDaV54a/pa0UNRGnBFuvm4q/xNtznR11nANCADfJKqq+1oAW4REZG8o6KcAGQS8SpcO/BoXLFtKG5H3eyv2b/u3fqZusVK3EXSBdHX+bjW8k+i28dNv47Vp3URVUSkG6goJ1IigjA5ANiK5oW37ALcQH/pNthq4CPc7m+ZFrcpqbrahR6ziYiItElFudKRScT7ABOAzVu5jaYwlxSaz/rFuo9xbdH/idWnl3rMJiJSMFSU66JoMd03geuttX+O7rsd+Horh2+dvfV81jl64dbq2Bk43Fr7aBuvdRTwIG4Hrl2y7r8Y+HkbES+w1l7Z6TfUzYwxlcAFwEPW2jc34PnT6MSCzF0856a43cO2t9Zmuuu8+SoIkwY3yNse2CHrVoo7oM0HpgBv49a+eR14M1VXqzVuREREpFtlEvH+QADsgrsQ2lR4GwkYj9FyzeIukL7d4jYlVp/WD58iIllUlOuiaAeqXwATrLWro/tuB3YDTm1x+JvW2vXWZjDGfAu3O9Zw2ijKGWOqcTuK9QGmtyjKjcZdVct2FG7HrJ02pBjWXYwx/YDFwKnW2ts34Pk7AXOttR93c64/AmXW2lO687y+BWGyH+sX37YD+vrMlecagPeBFOsKdW9oLTsRERHprGhtt52AXXFFuF2BOKVVfOuqpUA9zQt1b8bq0+psEJGSpaJcFxljXgImW2t/lnXf7WRtVd/B8wfhtos/H/gDbRfl6oCDcLN8TX1v7gAAIABJREFUOjy3MeYx3LbzW3fh7XRKNDuwqrUCYyvHblRRrqcYY76A281tlLV2ru88GyoIk8OA/YB9o9s2aPDXHRqBD3AFuhRuB79Uqq62wWsqEZES1dOdCcaYtgbAq6y1VVnH7QJcgZv9ZHD/T/zMWvvKhryv7qLOhNzKJOIVuIueu7KuCJfAbaIgG6cRt3vv89HtX7H69Od+I4mI5I6Kcl1gjNkc94P7ztbaN7Luv53OF+VuxM1yOxe3DtZ6RTljzFjcVaR9ge91dG5jzGBgJnCZtfbSdo4bH73mScChuNl1y4HfWmsvyTruYuA70eO/xM3EOt1ae6cxZrPovv1xg9PJwPettR9Gz23tD9Rm1tpp0ey/S4ETgWG42Uo/tdY+nvXa08gaJDZ9tsBPgetw63G8AZxhra3Pet5pwA9wC+U2XYU7q+mYaHD/WfQZ/batzyjfBGFyOK4Itx/uz0O3F12lTQtxf76fBZ5L1dW+5zeOiEjp6OnOBGPM7q287D+Al6y1R0XHjMEVC17HjUEAfoSbHbW9tfajDX6DG0mdCT0vk4hvDxyIu0i+Nz27wYKsY4H3WFekez5Wn57pN5KISM/R1Z2umYQr+LzVymPbGGMWAVW4q7I/s9Y+n32AMWZ73EByhw5e5zrgXmvt666W1KFjcTth/rUzB+MGuY9Gz9sH+Lkx5vMWxao+wJ+Ba3Az+z4zxlThZputBr4JrAEuAZ43xmxnrZ2HK9b9E7gMeCw614zo633ARNx6eFOA44BHjDG7dHCVd2yU+XJcEfFa4F5jzLbWWmuM2Qf4HXAR8L+4nUH3wO0SCkB03MvAAUDeFuWCMDmCdUW4/YAtPcYpdQOAI6MbQZj8DPdnu6lIN91jNhGRYvc94M6mglyWpdbalzt6ctSZcDnrOhOaaXkOY8xE3M6W92TdfRhQAxxjrV0QHfdv3E7gXwRu7vS76YSudCZsrOyLy93sNuA5Y8wPC60zIZOID2ddEe4A3DpwknsG1wmyDXAmQCYRT7OuSDc5Vp/+1F88EZHupaJc1wTAe9baxhb3vwG8glsDbhPgh8AzxpgvWGtfzTruBtystA+jWWvrMcbUAgfj1qTorBOA16216U4eX2+tPSP69VPGmGHABcaYm7PeW2/gB9bah7OyfRtXIIs3tSUYY17BLeR6BnAlriAJMCV7wGuMmYQb3O6XVax82hgTB34GfKWdvIOBvay1H0Tn6oXbAGNL3Gy7icDbLTa4eKSV87yFKybmlSBMbg8cHd06KtiKP6OAr0U3gjCZxhWpnwWe1pp0IiLdI+pM2BM3a39DhcBLuH+nO+ME3IXXf2TdV4G7AJn97/uS6L42r5pubGcC0GFnAm6WHMBtxpjbol9770zAfebzos8zby+CAmQS8WrcDLiDott2aEmQfBWPbt8EyCTirwMPAQ/F6tPv+AwmIrKxVJTrmhG4q6PNWGt/nf19tL7bu7i1PppaIE7AFZEOb+vkxphy4De4FstOTdM2xozEtTX+pHNvAXAFrWwP4AaBo3FbmYObOv5Ei+Mm4op/a9cJsdZOj9bZ+0IHr3kArsX2peh9NnkOOKWD505rKshF3o2+jsYNNN8ErjHG/BL33l621q5q5TyfA8OMMcZ67NsOwmQv3Ey+pkJczFcW2ShNA8QzgeVBmHwSNxv0H6m62sXtPlNERNqTq86EpuMN7uLgw9baZVkP3Y8rbl1njLk8uu8i3M7ef+/EqdWZkGcyifhg4Bjc78m+QLXfRLKBdo5ul2YS8Q+Bh3FFun/H6tMtJ0+IiOQ1FeW6phpY1tFB1trlxpjHiQpwxpgK3CDnaqCXMWYgbiAD0NcYU2OtXYwbeA0E/hwdA1AJlEXfL22ljeM43FW9v3Xhfcxu4/uRrCvKzW+lsDUSmNXK+WYB4zp4zaG4ombL/OB2w2zPghbfN+WqBrDWPmuMORXX6nIOsMQYcxfwI2vt0qznrcT9mS9vI0ePCcJkJe6HjKOBI3Dr20jx6M26IuuKIEw+hfuh6JFUXe0ir8lERApPj3cmtLA37kJfs2VArLWfRR0Mj+LGGOAKXwdba+d04rzqTMgDmUS8P+4i+fG49tQKv4mkm22O+7fgh8DsTCL+CK5A92ysPr3SazIRkU5QUa5r5uEKS53VNBurL26wd310y/ZX3FXMzXGDntG4GWUtzQf+B7irxf0nAC9aaz/pQq5hbXw/I+u+1maSzcDtNNXScNxn0555wKdEMwe7W7Qz25+NMZvgroD+EliEW0umyUBgSSuFzR4RhMlqXGH2GNzaM/3bf4YUiWrWrUW3MgiTT+MKdA+n6moXek0mIlIYerQzoRUn4sZZT7U4/0jcv98pXEcBwNnAY8aYPTuxSYI6Ezx1JmQS8T64PwMnAIegGXGlYhju79jpwJJMIv4kbsbrQ7H6dI+v1SgisiFUlOua/+Km6bfLGNMbt4ZIKrprCVDb4rARuMWEL8C1HwDciLuyk+18YDPcldFmuz9GV393B87qZP4mR9N8ceJjcAW3jhaufwU42RizmbV2apRhU9y6LxdHxzSbxZblOdwVrCXW2ve7mLfToivXtxhjjsEtEJttPK41pEcFYTIATsMN8gd2cLgUtyrcDwWHA6uCMPkMblbrfam62uVek4mI5K+e7kxYKypcfRm4v5UC049wY+Vjs3aA/SfwAXAe62bPtUWdCTnsTMgk4lW4i6DHA1/CXRSX0tUP16Z8LDA/k4jfA/wpVp9Otf80EZHcUlGua14CLjLGbNLUtmCMGYBra7gL+BA3GPo+sCmutRRr7RrcAr1rZbVTvGOtfSU67sPoHNnHnQIMtdY2e37kBNw6I/d18X0kjDG34K4c7YMrIJ3TSptIS7fj1q57whhzEW5wdzHuiugt0XtYZYyZChxnjPkPsAJ4G3gGdwX6GWPM1biFgfsDOwLV1tqfdvE9rGWMuQTXcjE5yrITbp2Q81scugvu97DbBWFyMG5B59PQZg3SukpcS9FhwG+CMHkXcEuqrvY/fmOJiOSdnu5MyDYJ1wp7D+vbCteCurawFI1z6nEbIXREnQk5kEnEd8NdvP4y6kqQ1g3CTWI4K5OIvwX8CbgrVp/u6O+TiEiPU1GuaybjBjuHAHdG960E5gAX4gZbK3CL3+5rrX2th/OcADzXyXVNsv0YdwXxflzeEDdLr13W2pXGmANwA90/sm43sGOiRYebfBu3OPCzuJlCTbuBHYObGXgubq2UebhWiBu6mL+l/8MVQk8AaoCPcMXCtW0uxpihuDVqfryRr7VWECYNbjB/Gm72YVV3nVuK3kDcjnvfCcLkv3FF7XtTdbVqrRAR6fnOhGwn4to9J7fy2EfAF40xlU2z2aJNGLal+S6tbVFnQg/JJOK9ga/iNlsKevK1pOjsgPsZ4ZpMIv4wrkD3jDaIEBFfjMdNKAuSMebXwObW2sN8Z+mqaHbeVOBwa+2jftPkljHmDFyrSXxj1zcJwuRY3K5up9JxG4lIZ83HFftvSdXVvtvRwSIixcoYcxBudv2wTnQm7ITbnKDVC6HtjX2iAtss4HZr7bmtPDcAXgaeBm7CXYw8G7du2y7W2tZ2h81+zc+izE2dCRfgOhNuiI67GPiOtXZoK7newxXesjsTBgNNu69ijMkA06JjmjoTVkevuT2ujbfVzgRjzDTgPmvtedH3twPbWmt3aeuza6Mz4SrgfGvtr7Ke9wrwirW2o/beLssk4k27np+ClgiR7vMxbhfkP8Xq09M8ZxGREqOZcl33C+C/xpi4tbbH1yeTjWeMMbi1Ty7fmIJcECYPxM3yOwTo1U3xRJoMwq3T870gTL6Imz13n2bPiUgJmkxuOhMOBQbQYtfVJtbalDHmEODnWTneAQ5sqyDXgjoTukEmES/D7Vx/Fq5DwXTXuUUiY4E64MJMIv4E8ItYfXqy30giUio0U24DRDt7zcjaar4glOpMuWj3tG8AV1lrO1rkuJkgTFbiWlt+gLvqLJJL83DFuV+m6mq72qYuIlKw1JlQmLqzMyGTiI8AvgV8E7dWoEgu/R9uMsb9am0VkZ6kopxIK4IwOQjXHvEd3C5oIj4tw82W+EWqrvYT32FERHqaMWY0bm25nQqtM6FUi3JRZ0I9cI219vYNPU8mEd8at3HEiUBF96QT2WBTcLNWb4vVp5f7DiMixUdFOZEsQZgciZsVdwauNUMkn6zGrad0VaqutqB+SBUR6Sp1JhSWjelMAMgk4gHwM9zOsWpRlXwzB9d+/ttYfXqu7zAiUjxUlBMBgjAZw61/cgraRVXyXyNujaIrUnW1b/oOIyIisqEyifg+uGLcQb6ziHTCMtyOrdfH6tNTfYcRkcKnopyUtCBMTgAuwS1aXOY5jsiGeBK4PFVX+6LvICIiIp0VFeMuAfbzHEVkQzQAfwMuitWnp/gOIyKFS0U5KUlBmBwOXIRbPFjrlUgxeBG4KFVXm/QdREREpC2ZRPwLuGLc/r6ziHSD1cDvgUtj9elZvsOISOFRUU5KShAma3C7gv0A6Oc5jkhPeAz4Uaqu9j3fQURERJpkEvGJwGXAgb6ziPSAJbgNIa6N1acX+w4jIoVDRTkpCUGYrAC+DVwIDPMcR6SnNQB/wM2cm+07jIiIlK5MIj4auBq3m6o2cJBiNwdXfP5drD69yncYEcl/KspJUQvCpMGtF3cZEPMcRyTXFgPXANel6mqX+w4jIiKlI5OI98ZtovVjoI/nOCK5NhWoA/4Sq0/rB24RaZOKclK0gjB5IHAVsLPvLCKeTccNDO9I1dU2+g4jIiLFK5OIG+CrwJXAGM9xRHx7Ezg/Vp9+yncQEclPKspJ0QnC5BbADcDBvrOI5Jk3gfNSdbXP+Q4iIiLFJ1o37tfA7r6ziOSZZ4HvxurT7/sOIiL5RUU5KRpBmKwEzgcuAKo8xxHJZ48D56bqaj/wHURERApfJhHfFNedcBJaN06kLauA64AwVp/WsiIiAqgoJ0UiCJP7Ar8DtvKdRaRArASuAK5K1dVqIWIREemyaN24H+HWjevrOY5IoZgGnBOrTz/iO4iI+KeinBS0IEwOBa4Fvu47i0iBeg84I1VX+4LvICIiUjgyifg+wB+BzX1nESlQj+BaWj/2HURE/FFRTgpWECZPBX4BDPGdRaTAWeA24Eeputp5vsOIiEj+yiTifXGtqmejVlWRjbUE+BlwY6w+rc24REqQinJScIIwuRWuVXVf31lEisws4KxUXe0DvoOIiEj+ySTi+wN/ADbznUWkyLwCfDNWn37HdxARyS0V5aRgBGGyCrgQt25Jpec4IsXsPuDsVF3tbN9BRETEv0wi3h/XnfBNNDtOpKesxv09uzRWn17pO4yI5IaKclIQgjCZAO4BtvOdRaREzAXOSdXV3u07iIiI+JNJxA8Gfg+M8Z1FpET8BzgxVp/+j+8gItLzVJSTvBeEye8C1wDVvrOIlKCHgdNSdbVzfQcREZHcySTiA4HrgVN9ZxEpQSuAH8fq0zf4DiIiPUtFOclbQZgchlt8/ou+s4iUuOnASam62n/5DiIiIj0vk4gfBtwKjPKdRaTEPQ6cGqtPa0kRkSKlopzkpSBMHooryA33nUVEAGgALgPCVF1tg+8wIiLS/TKJeAVuTatzfGcRkbVm4QpzT/gOIiLdT0U5yStBmKzGtap+By0kLJKPnsfNmvvUdxAREek+mUR8HPA3YDffWURkPRa4AdfSqk0gRIqIinKSN4IwuS1uM4dtfWcRkXbNBU5N1dX+w3cQERHZeJlE/HDgz8Ag31lEpF3v4DaBqPcdRES6h4pykheCMPk94Gq0mYNIIfkN8ONUXa2u2IqIFKBMIl4OXAGchzoURArFCuBHsfr0jb6DiMjGU1FOvArCZF/gduBYz1FEZMO8AZyQqqtN+w4iIiKdl0nERwN/BfbynUVENsjDwP/E6tOLfQcRkQ2nopx4E4TJzYCHgO19ZxGRjbIEOCNVV/sX30FERKRjmUT8EOBOYKjvLCKyUeqBI2P16Sm+g4jIhlFRTrwIwuT+wL3AEN9ZRKTbXAVckKqr1X8sIiJ5KJOIlwEhcD5qVxUpFvOA42P16Wd9BxGRrlNRTnIuWj/uOqDcdxYR6XYPAV9L1dUu9R1ERETWySTig4H7gFrfWUSk2zUA58Xq07/yHUREukZFOcmZIExWATcDp/rOIiI96i3giFRd7ce+g4iICGQS8c2Bx4C47ywi0qNuB74dq09rEy6RAqGinOREECZHAg8Au/vOIiI5MQs4KlVX+7LvICIipSyTiH8BN4tZS4aIlIaXgaNj9emZvoOISMd6+Q4gxS8IkxOB11BBTqSUDAcmB2Hya76DiIiUqkwi/lXgWVSQEykluwOvZRLxXXwHEZGOaaac9KggTJ4M3ApU+c7SxDY0MOulvzH39SdYtXA25X0HMCixL6MPPRuAxjWrmXb/FSz7LM3qxXMpq+xNn1FbMuqAb9BnVPtdH69ftH+r95uyCnb6+VPrZ2ls5P1bzmT5jA+YcNLlDNhyj7WPLXjvRaY/eTONq5azycQjGVn79WbPnZG8g2Uz0kz46mVd/QhEck0bQIiI5FgmEb8IuMR3DhHxZgVweqw+fbfvICLSNi20Lz0mCJM/Ba7wnaOljx66msWZNxix38lUDx3LqkWzWTH7o3UH2EYwhhF7n0jV4FE0rFzG7H/fR/q2H7L1mbdQNXhUm+fe8ps3rnfflLt/Rt+x27Z6/NzXH2f14s/Xu3/N0oVMu/8KRuz7P1QNGslHD19H3zHb0H/zXQFYtWgOs1++ny2/dVMX372IF+cDWwVhUhtAiIj0sEwiXgn8HjjZdxYR8aoauCuTiG8Rq09f7DuMiLRORTnpdkGYNMC1wA98Z2lp4QevMu+dJFuf9Xt6Dxvf6jG9KqqIHXdRs/tqYgFvX3UUC957ieF7faXN8/cds02z75dOf481yxYyaLv1Z9CtWb6Yz579I6MO/CYfP3xti+e9S+WA4YzY+0QAFk99g0VTUmuLcp8+fStDdj6U6iGbdvieRfLEUcBLQZg8NFVXO8N3GBGRYpRJxAfh1vDdz3MUANZYyx/mzufeBYuYsXoNg8vKOLR/Py4csUmrx4cz53D7vAWcNnggF7RxTJMffTqTBxYuXu/+pyeMY0JVJQBvL1/BXfMW8H/LVjB7zRpGVpRzxIAazhgyiKpe61bxSS1bzs9mzGbW6jUcMaCGuhGbUG7M2scfWLCI2+Yt4OHNxtAr636RAvHzaPflc2L1aXUtiOQZFeWkWwVhshz4A/D1jo71Ye7rT1Cz2U5tFuTa0quyGlNeiW1Y3aXnzX8nSa/KagZmtaU2mfHcn+g7dltqYjuv91hjw2p6Vazr+O1VUY1tWAPA0k/eZXHmdRLfu6NLWUTywA7AC0GYPCBVVzvNdxgRkWKSScRjwOPAlr6zNPnJZ7P499JlfHeTIUyorGDG6jV8uHJVq8d+sHIl9y1YRL9enV/yekJlBVePGt7svtEV6368eXThYj5evZozhg5ifGUF769YxS/nzOX9FSu5aYzrfFhtLedMn8mh/fuxR9/e1M2Yw1bVVZw4aAAAyxobuW72XK7fdLgKclLIvgsMyiTip8bq02t8hxGRdVSUk24ThMlq4G/AEb6ztGXZ9PcYsNWefPLor5n71jPYxgb6b74rYw77HpX9hzY71loLjY2sWbaQWf++F9OrF4O2b33NuNZYa5lf/zwDttqLXpXVzXPMnMLcN55iq7N+3+pz+4zcguWzprI48waVg0aw4N1/MXL/U7HW8snjNzJq0jcoq+7b9Q9AxL8JrCvM/dd3GBGRYpBJxHfFFeSGdnRsrjy/ZCmPLlzMoxPGskVVx0sLXzpzDl8fPJCHFi7q9Gv07tWLnfr0bvPxM4YOYkj5uh93du/bh6pehgtnzObTVavZtLKCzMpVLG5s5PzhQykzhg9WruKlJcvWFuVu+nweO/WuZre+fTqdSyRPfQ0YmEnEvxKrT6/wHUZEHO2+Kt0iCJP9gafI44IcwOol85n7xlMsmzmFzb5yIeOO+jHLP0uTueciWm56MuuFe3jjkgN55xfHMu/Np9n8a1dSNXBEp19ryUdvs3rRHAZtW7veY9Mfu4GhE49ss/20atBIRuxzEh/c/kPqf3kS1ZuMZ/B2k5j35tPYxjUM2enQrr1xkfwyGleY29F3EBGRQpdJxPfE7bCaNwU5gPsWLGKPvn06VZB7YtFipqxcxbeHDurWDNkFuSaJapdnbkMD4GbKVRgoi2bBVffqxepoTDh91WrunreQ84fn1UcrsjG+BDyVScT7+w4iIo5myslGC8LkcOBJoAB+wLaAZcJXQ8r7uCugFTWD+eBP32dx5g36T1jXSjpkp0OomRCwevFcPn/1ET68+wLi3/hVp1tf57/zT8p616xdB67JvHf+yYq5nzDhpMvbff7I2pPZZOKRNKxeTtXAETSsXM5nz/6B8V+5ENvYwCeP/poF7/6L8n6DGXv4ufQbt12XPgkRzzYBkkGY/GKqrvZ/fYcRESlEmUR8H+AxoJ/vLC29uXwFk/r15eIZs3lw4WLWWMs+/fpw8YhhDM9qMV3R2MgVsz7nR8OG0qcLrasAH65cxQ7vT2GVtWxXXcUPhw3pcEZbatlyegGbVVYAsFlVJastPLRgEXv168ODCxYxqcZ1I1w163O+NngAo6NjRYrEPsDkTCJ+SKw+Pdt3GJFSp5lyslGCMDkeeJGCKMhBWXUNvYfF1hbkAPqN3Q5TVsGKOdOaHVtRM5i+m27JwK32ZMJJl1Peuz+zXrinU69jGxpY8O4LDNxmb3qVV2Tdv4ZPn7qF4V84AWsta5YvoWGl24yyYdUKGlYua3ae8r4D1s7Om/nCX9wadON34PPX/sHymVPY5pw7GLHvSUy991Ia17S+RotIHhsIPBOEyUm+g4iIFJpMIr4/8AR5WJAD+HxNAw8sXMS7K1byq01HcPWo4fxnxUrO/OSzZt0JN38+n2Hl5Rw1oKZL59+muooLhg/l1jEjuX7T4TQCX//oU95a3nZX3pw1a7jp8/kcNaCGmrIyAPr26sWFw4fyk89msXt6KgY4ZfBAXlm6jNeXL+fMoYM35O2L5LudgBcyifg430FESp1myskGC8LktriW1VG+s3RW9SZjsWta26zBYkzbNWpTVkbv4TFWzu/cppGLM6+zZukCBrfYdbVh1QpWL5rDp0/ezKdP3tzssWl/D6kaPIrEuXetd76V82fy+asPs9WZt7rzT32DQTtMorx3DYO3259PHvsNK+dOp/fwWKfyieSRvsBjQZg8LlVX+4jvMCIihSCTiB8MPAi0vaCaZ9ZaLIZbxoxiULkrgA0rL+fEj6bz76XL2atfHz5ZtZo/zJ3PXeM2xXRxE4VThzRvda3t15eDp3zETZ/P45Yx6w9NV1nLd6fPoG8vs97ur18ZNIBD+vdjbkMD4yoqsMBlWbP3rpv9OX9fsIjephfnDx/Kwf3zsg4q0lVx4MVMIn5QrD79nu8wIqVKRTnZIEGY3B5IAgV1+XBAfHdmJP/MmqULKe/rZsst+ehtbMMaeo+Y0ObzGlevYtmMD+g3NtGp15n3zj8p7zeYfuObTyAsq+zNFqde3+y+1UvmMe3vlzHqgNOp2WynVs/36VO/Y5PdjqJq0Lo17RpXrQTANjZg16xeb008kQJSBdwfhMmTU3W1nZuOKiJSojKJ+JeA+3D/duat/mVljK2sWFuQA9ilTzWVxvDhqlXsRR+umf05+/brw4SqShZFa7w1WldAW9TQQE2vXp0u1lX36sV+/fry3OKl6z1mreW8T2fywcpV3Dt+DAPKytY7pqasbO3sub/NX0gFcNSAGp5dvIRHFy7h4c3G8snq1Zz28WcEfaoZ2sp6dSIFaDRuxtxBsfr0677DiJQi/W8iXRaEya2AZyiwghzA0F2+xOxXHmTK3T9j+D5fpXHVcj59+lZqYsHaNdnmvf0ciz54lf5bTKSiZgirF89lzquPsHrxXIbt+ZW155r75tN89NA1JM69q9kGEI1rVrHw/RcZvOPBmBZro5iyMmo2a16oWzl/JgC9h29G3zFbr5d58dS3WDr9XcYd85O199WM24HZL99P72HjWJx5g7KqPlQPHbPxH5CIP+XAXUGYrEnV1d7qO4yISD7KJOJH43a6z/tFzjavqmRVKxcMrbVr18+ZunIV761cxVP/zTQ75s75C7lz/kJe3GI8Iyu69lZbq+FdNutznl28lDvGbcqEqsp2n7+4oYFfzp7L78aMxBjDy0uXc2BNX4ZXlDO8opzxlRW8tXwFk2o0W06KxhDg6Uwivm+sPl3vO4xIqVFRTrokCJMx4DlgmO8sG6Ksui9bnHId0x+/gWl/vwxTVs6ArfZi9KFnrT2meugY5r31LNOfvImG5UuoqBlMn9Fbs9URN9N72GbrTmYbobHR7R2RZdEHr9KwYul6rasbwjY2Mv2J3zLqgNMpq1zXoTJ04hEsnz2VafdfQXm/IYw/9kJ6lbc/yBQpAL2AW4IwuSZVV/sn32FERPJJJhE/DribAhm/1/bry6/nzGXemgYGR7PlXl22nNXA1tEOqFeMGs6yxsZmzztn+kwm9u3NSYMGMLiVGW1tWdHYyPNLlrJtdfMJhDd/Po875i3ghtEj2KVPx92+N8yZxxf69WGnrGNXZBUXlzc2thz6iRSDIcCzmUR871h9+kPfYURKiVHLm3RWECbHAP8CxnuOIiLFrQE4PlVXe7/vICIi+SCTiJ8E/BnofJXKs8UNDRw65WNGVJRz5tBBLG1s5OpZc5lQVcEd40a3+bx9PpjKITX9uCBr3bcHFizi/M9mkdx8PJtWVrC4oYHTP/6MIwf2Z1xFBfMbGrht3gLeXbGSv40fzfa9qwF4ZOEivv/pLL48oIYTBw1o9jpjKysY0qIFderKVXx56ic8PmEcI6IdYp+hGUTAAAAgAElEQVRetISffDaLy0cN45NVq/nNnHk8v8V4ta9KsfoY2DtWn/7YdxCRUqH/TaRTgjA5HHgWFeREpOeVAX8JwuThqbrap32HERHxKZohdwfQ9o5UeaimrIy7xm/KpTPncM70mVQYwwE1fdfbZKEzGnFXa5qmElQaw+DyMn47Zx7zGhqoNIadelfzl3Gbri3IAbywxO1qf//Cxdy/cHGzc149ajjHDuzf7L4rZ33OqUMGri3IARzUvx9vLl/BRTNm06dXL67ddLgKclLMxuJmzO0Tq0/P9B1GpBRoppx0KAiTQ4DJwLaeo4hIaVkKHJiqq/1f30FERHzIJOKTgMcBrVEhIrn0H2C/WH16ru8gIsVORTlpVxAmBwD/BHb2nUVEStJ8YN9UXe07voOIiORSJhHfCXgeqPGdRURK0mvApFh9epHvICLFrKCmwUtuBWGyL+7qrApyIuLLIODpIExu7juIiEiuZBLxGPAEKsiJiD+7AI9mEvE+voOIFDMV5aRVQZisBh4B9vSdRURK3gjgmSBMbuo7iIhIT8sk4sOAp4HhvrOISMnbG3gwk4hXdXikiGwQFeVkPUGYNMDdwP6+s4iIRMbjZswN8R1ERKSnZBLxfrguhQm+s4iIRA4C/ppJxAtm92eRQqKinLTmSuAY3yFERFrYBngyCJNq5xKRopNJxCuAB4DAdxYRkRaOAq71HUKkGGmjB2kmCJOnALf5ziEi0o4ngC+l6mobfQcREekOmUTcAHcBX/WdRUSkHWfE6tO3+g4hUkw0U07WCsLkPsAtvnOIiHTgUOBq3yFERLrR9aggJyL578ZMIl7rO4RIMdFMOQEg2tnwZUDrNYlIofh6qq72Dt8hREQ2RiYR/wFwne8cIiKdNA/YLVaf/tB3EJFioKKcEITJgbiC3Ja+s4iIdMFKYL9UXe3LvoOIiGyITCJ+APAkoAXURaSQ/BfYPVafXuA7iEihU/tqiQvCZDlwHyrIiUjhqQIeDMLkaN9BRES6KpOIjwf+igpyIlJ4tgT+nknEy30HESl0KsrJjcAk3yFERDbQCOChIEz29h1ERKSzMol4b+BBtGyIiBSuA4Bf+w4hUuhUlCthQZj8PnCG7xwiIhspQLtGi0hhuRXY0XcIEZGNdFYmET/bdwiRQqY15UpUECa/CPwDFWZFpHhcmKqrvdx3CBGR9mQS8XOAX/nOISLSTdYAX4zVp5/xHUSkEKkoV4KCMDkOeB0Y7DuLiEg3ssAxqbrah3wHERFpTSYR3xd4FtA6TCJSTBYAO8fq01N9BxEpNCrKlZggTFYCLwATfWcREekBS4DdU3W19b6DiIhkyyTio4EUMMx3FhGRHvAKsHesPr3adxCRQqLWxdJzLSrIiUjx6gf8NQiT1b6DiIg0ySTiVcADqCAnIsVrN0DLiIh0kYpyJSQIk8cC3/WdQ0Skh22LuwAhIpIvbgJ29R1CRKSHnZdJxA/2HUKkkKh9tUQEYXICbh25/r6ziIjkyJGputpHfIcQkdKWScRPA/7gO4eISI7MBnaM1adn+A4iUghUlCsBQZisAF5CV2hFpLTMBbZP1dV+5juIiJSmTCIex10U7es7i4hIDj0HHBSrTzf6DiKS79S+WhouRwU5ESk9Q4A7gzCp/+tEJOcyiXgFcDcqyIlI6ZkE/NR3CJFCoB9UilwQJg8EzvOdQ0TEk/2BH/sOISIl6VJgF98hREQ8uTiTiO/lO4RIvlP7ahELwuQmwNvACN9ZREQ8WgPslaqrfdV3EBEpDZlEfD9c+5YugItIKfsYt77cfN9BRPKVBgrF7TZUkBMRKQfuCcJkje8gIlL8Mon4AOAONM4WERkL/NF3CJF8psFCkQrC5MnAYb5ziIjkiRhws+8QIlISfgOM8R1CRCRPHJ1JxL/lO4RIvlL7ahEKwuQw4D1gsO8sIiJ55muputq7fYcQkeKUScSPBB7ynUNEJM8sAraO1ac/8x1EJN9oplxxuhEV5EREWvOrIEwO9R1CRIpPJhEfCtziO4eISB7qD9zkO4RIPlJRrsgEYfIo4Cu+c4iI5KmhwPW+Q4hIUboZGO47hIhInjoyk4gf6zuESL5R+2oRCcLkQOBdYKTvLCIiee7AVF3ts75DiEhxyCTixwN/9Z1DRCTPzcK1sWo3VpGIZsoVl+tQQU5EpDN+F4TJ3r5DiEjhi3Zb/ZXvHCIiBWA4cK3vECL5REW5IhGEyUnAN3znEBEpEBOAi3yHEJGicCkwwncIEZEC8Y1MIr6/7xAi+ULtq0UgCJN9gXeAzXxnEREpIGuAnVN1te/4DiIihSmTiO8IvAaU+c4iIlJApgDbxerTy30HEfFNM+WKw+WoICci0lXlwK1BmNT/hSLSZZlE3OB2E1RBTkSkayYAl/gOIZIP9INIgQvC5O7Ad33nEBEpULsDZ/kOISIF6VRgD98hREQK1A8yifjOvkOI+Kb21QIWhEmDa5nQP2YiIhtuMbB1qq72U99BRKQwZBLxwcB/gaG+s4iIFLA3gImx+vQa30FEfNFMucJ2MirIiYhsrBrgRt8hRKSgXIEKciIiG2sn4AzfIUR80ky5AhWEyT5AGtjUdxYRkSJxaKqu9knfIUQkv2US8V2Bl9HFbRGR7jAX2DxWn17gO4iIDxpMFK4fo4KciEh3ujYIk1qwXUTalEnEewE3ozG0iEh3GQL83HcIEV80oChAQZgcBfzIdw4RkSKTAE73HUJE8toZQOA7hIhIkTk7k4jHfYcQ8UFFucJ0BdDHdwgRkSJ0aRAma3yHEJH8k0nEBwGX+84hIlKEKoBrfYcQ8UFFuQIThMmdcRs8iIhI9xsGXOA7hIjkpR8Dg3yHEBEpUodnEvFJvkOI5JqKcoXnesD4DiEiUsTODcLkGN8hRCR/ZBLx4cD3fOcQESlyV2cScf2sKyVFRbkCEoTJo4F9fecQESly1cAlvkOISF75GVo6RESkpwXA8b5DiOSSsdb6ziCdEITJCuBdYHPfWURESkADsH2qrvZd30FExK9MIj4W+ACo9J1FRKQETAG2jtWnV/sOIpILmilXOM5CBTkRkVwpw22qIyLyc1SQExHJlQnAt32HEMkVzZQrAEGYrAamAcM9RxERKTV7pupq/9d3CBHxI5OIx3GdCmW+s4iIlJA5wIRYfXqx7yAiPU0z5QrDN1FBTkTEh6t8BxARry5FBTkRkVzbBDjbdwiRXNBMuTwXhMlK4ENAOwGKiPhRm6qrnew7hIjkViYR3wF4A+16LyLiwyxgfKw+vcJ3EJGepJly+e9kVJATEfHpfN8BRMSLy1BBTkTEl+HAab5DiPQ0zZTLY0GYLAP+i1vsUkRE/NkpVVf7pu8QIpIbmUR8d0DrSYqI+PURsHmsPr3GdxCRnqKZcvntRFSQExHJB5otJ1JaLvUdQEREGAd81XcIkZ6kmXJ5KgiTBqgHtvadRUREaAC2TNXVTvEdRER6VrSWnGbGiojkh/eARKw+rcKFFCXNlMtfX0YFORGRfFEGnOc7hIjkxPd9BxARkbW2Bo7yHUKkp6gol79+5juAiIg0c0oQJof7DiEiPSeTiI/ALR8iIiL546e+A4j0FBXl8lAQJr8E7Og7h4iINFMNnOs7hIj0qLOBSt8hRESkmV0zifgBvkOI9AQV5fKTZsmJiOSnM4Mw2d93CBHpfplEvDfwbd85RESkVRf4DiDSE1SUyzNBmJwI7O47h4iItGoAcKbvECLSI04GhvoOISIirarNJOK7+Q4h0t1UlMs/+mFPRCS/nRuEySrfIUSk+2QScYPa00VE8p023ZKio6JcHgnC5CDgeN85RESkXSOAE3yHEJFudSiwle8QIiLSriMzibg23ZKioqJcfvk60Nt3CBER6dA3fQcQkW71fd8BRESkQxXAqb5DiHQnFeXyixYXFhEpDHsFYXIb3yFEZONlEvHtAO3qJyJSGE6PlhwQKQoqyuWJIEzuD2zpO4eIiHTa6b4DiEi30Cw5EZHCMQFdSJEioqJc/tAsORGRwnJyECYrfYcQkQ2XScT7ozUiRUQKzbd8BxDpLirK5YEgTI4AjvKdQ0REumQIcLTvECKyUb6C1vMVESk0R2YS8WG+Q4h0BxXl8sPpuEUrRUSksGjDB5HC9nXfAUREpMu04YMUDWOt9Z2hpAVhsgyYCozxnUVERLrMApun6mozvoOISNdkEvEY8CGgBcNFRArPFGCLWH1aBQ0paJop598XUUFORKRQGbThg0ih+h9UkBMRKVQTgEm+Q4hsLBXl/DvNdwAREdkopwRhstx3CBHpvEwiboCTfecQEZGNog0fpOCpKOdRECYHAIf4ziEiIhtlJHCY7xAi0iVfAGK+Q4iIyEY5Shs+SKFTUc6vI4Eq3yFERGSjqYVVpLBogwcRkcJXgdtFW6RgqSjn1/G+A4iISLc4KJr9LCJ5LpOI90Y/xImIFItjfQcQ2RgqynkShMlBwIG+c4iISLeoBA73HUJEOuUooL/vECIi0i32VgurFDIV5fw5GjfdVkREisOXfQcQkU5R66qISPEow11sESlIKsr5c5zvACIi0q0ODsJkX98hRKRtmUR8BHCA7xwiItKt1MIqBUtFOQ+CMDkEmOQ7h4iIdKvewKG+Q4hIuw7HzaoQEZHiUZtJxAf7DiGyIVSU8+MYoNx3CBER6XZqYRXJb1r7UUSk+JSjFlYpUCrK+aFdV0VEitNhQZis8h1CRNYX7bqq1lURkeKkFlYpSCrK5VgQJocB+/nOISIiPaIGOMh3CBFp1f64NnMRESk+kzKJ+EDfIUS6SkW53DsGrWUiIlLM1MIqkp/UuioiUrwqgSN8hxDpKhXlck8DQhGR4nZ4ECa1bqhI/vmS7wAiItKj1MIqBUdFuRwKwmQlsK/vHCIi0qMGA7W+Q4jIOplEfGdgU985RESkRx2UScRrfIcQ6QoV5XJrD6Cv7xAiItLjtAOYSH7RLDkRkeJXhSbBSIFRUS63DvQdQEREcmKS7wAi0oyWDxERKQ37+w4g0hUqyuWWinIiIqVhyyBMjvQdQkQgk4iPBALfOUREJCdUlJOCoqJcjgRhchCwi+8cIiKSMxoUiuSHwwDjO4SIiOTE9plEfKjvECKdpaJc7uyPPm8RkVKizR5E8sNhvgOIiEjOGDQGkwKiIlHuqHVVRKS0aKaciGeZRNwAe/vOISIiOaUxmBQMFeVyR0U5EZHSslkQJsf5DiFS4rYChvgOISIiOaWinBQMFeVyIAiTMSDmO4eIiOScBoUifu3lO4CIiORcPJOIj/YdQqQzVJTLDc2SExEpTVrTRMSvL/gOICIiXujCqBQEFeVyQ0U5EZHSpKKciF+aKSciUppUlJOCoKJcbuzpO4CIiHgxOgiTW/gOIVKKMon4cGBz3zlERMQLFeWkIKgo18OCMDkKGOk7h4iIeKNBoYgfmiUnIlK6xmQScV2YkbynolzP28V3ABER8Wof3wFESpSKciIipW033wFEOqKiXM9TUU5EpLTt5DuASInSJg8iIqVtZ98BRDqiolzPU1FORKS0bRmEyT6+Q4iUkkwi3hsVxEVESp3+H5C8p6Jcz1NRTkSktPUCtvcdQqTETAQqfIcQERGvdvQdQKQjKsr1oCBMjgM28Z1DRES806BQJLe0npyIiAzKJOKb+Q4h0h4V5XqWZsmJiAiofUIk11QIFxER0BhM8pyKcj1LRTkREQEVCERybRvfAUREJC+oKCd5TUW5nqWinIiIAGwXhMky3yFESkEmEa8A4r5ziMj/s3fn4U0W2wPHv5Ow22BVWqo00IuKWK5GJXrFnatSIyhS933FBbUV+OF137huqNXgAu6479EiUKMiqGgVi4pLLqJiEXELKlJEoKTz+2MSmoa2aZo3TVrO53nySJI3805qm8x75pwZITKCBOVERpOgXGoNTncHhBBCZITuwMB0d0KIzcSOyCYPQgghjD3S3QEhmiNBuRQZPHFOf2CrdPdDCCFExpASViHahpSuCiGEiNh2yaABvdPdCSGaIkG51Nk13R0QQgiRUaR8Qoi2MSjdHRBCCJFRZAwmMpYE5VJH1jIRQggRTQaEQrQNyZQTQggRTUpYRcaSoFzqSFBOCCFENMmgFqJtSKacEEKIaDJZIzKWBOVSZ6d0d0AIIURG6TV44hxHujshREe2ZNCATsjEqBBCiIb+ke4OCNEUCcqljgwIhRBCxJJBoRCpJTuvCiGEiCXjL5GxJCiXAoMnzskGctPdDyGEEBmnIN0dEKKDk9JVIYQQsfKWDBrQLd2dEKIxEpRLje3T3QEhhBAZqSDdHRCig5N1g4QQQsRSQL90d0KIxkhQLjUkPVYIIURj5PtBiNTaMd0dEEIIkZEK0t0BIRojQbnUkIsuIYQQjSlIdweE6OCc6e6AEEKIjCTX6CIjSVAuNeQPXgghRGMK0t0BITo4CcoJIYRojFyji4wkQbnUkD94IYQQjSlIdweE6KiWDBqggD7p7ocQQoiMVJDuDgjRGAnKpYYE5YQQQjQmO7xDtxDCejlA13R3QgghREaSa3SRkSQolxr56e6AEEKIjFWQ7g4I0UFJ6aoQQoimSFBOZCQJylls8MQ53YEt0t0PIYQQGasg3R0QooOS0lUhhBBN6bVk0AC5ThcZR4Jy1tsm3R0QQgiR0QrS3QEhOqi8dHdACCFERuuX7g4IEUuCctaToJwQQojm5KS7A0J0UL3T3QEhhBAZTa7VRcaRoJz1eqW7A0IIITKabPQgRGpIUE4IIURzZAwmMo4E5awn0XchhBDNkQGhEKkhQTkhhBDNkTGYyDgSlLOeBOWEEEI0RwaEQqSGBOWEEEI0R8ZgIuNIUM56Ur4qhBCiOTIgFCI1ctPdASGEEBltq3R3QIhYEpSznmTKCSGEaI4E5YRIjZ7p7oAQQoiMJmMwkXEkKGc9CcoJIYRojgwIhUiN7unugBBCiIwmYzCRcSQoZz0pXxVCCNEcGRAKkRo90t0BIYQQGU3KV0XGkaCc9SRTTgghRHN6DJ44p3O6OyFER7Jk0AA70CXd/RBCCJHRZGJUZBwJyllv63R3QAghRMaTmVohrCWlq0IIIeKRoJzIOBKUs17XdHdACCFExpNBoRDWktJVIYQQ8cj4S2QcCcpZz57uDgghhMh4MigUwlqSKSeEECIeqVQQGUeCctaToJwQQoh4JKtHCGvJ35QQQoh4ZAJHZBwJylmvU7o7IIQQIuPJBI4Q1pKgnBBCiHhk/CUyjgTlrCd/6EIIIeKR718hrCXZD0IIIeKRa3WRceSiwHryhy6EECIe+a4QwlqSKSeEECKuJYMGSAxEZBT5hbSeXGgJIYSIR74rhLCWBOWEEEK0hIzBREaRoJz1ZE05IYQQ8cj3rxDWkossIYQQLSHfFyKjSADJevJHLkRDZcC8dHdCiAxTle4OCNHBrE93B4TIMBuAi4Bf090RITJMbbo7IEQ0CcpZT7IfhKg3bcHVQ8enuxNCCCE6PAnKCdHQZf2/XHx/ujshhBCieRJAstDgiXMkS06IenOBc9PdCSGEEJuFdenugBAZ5KX+Xy6+I92dEEIIEZ9kyllLgnJCGF8BxQuuHmp5evjCZTW9geHACGBnQFl9DiHamWUup+PQdHdCiDSToJwQxmLgzFQ0XFdVsRswChiYivaFaIcqbG7PtHR3QrRvEpSz1oZ0d0CIDLACGJ6f5/g7FY27nI5fgEeARxYuq+mPCc6NAA4EuqTinEJkOJkQEkKCckIA/AUU5/bLXpOKxm1uz6fAp3VVFTsDxZgA3eBUnEuIdmJ5ujsg2j8pX7XQgquH1gEp+RIUop1YBxyVn+cYDuhUn8zldCxxOR2TXU7HMGAbzADxEeDnVJ9biAwSSncHhMgAsqacEHBubr9sN1CXypPY3J7/2dyeG21ujxvoB5Rili2R7yOxuZHfeZE0CcpZrybdHRAijc7Kz3M4gf3KR7vbNGvB5XSsdjkdL7ucjrOB7YC9gBuAj2mDAKEQaSQDQiEkU06I+3L7Zf8IHJA1a36bjXtsbs/3Nrdnss3tGQrkAWcBM5C/SbF5kDGYSJqUr1qvBuid7k4IkQbX5uc5vgPeAkansyMup0MDH4Vv1y5cVrMd9evQHQxskcbuCWE1GRAKIQEAsXn7cOttHZOADzFZa2lhc3tWAI8Cj9ZVVWQBHkyJ63CgZ7r6JUQKyfJVImkSlLOeZMqJzdET+XmOJ4EPMJ8rM9LcnwZcTsePwIPAgwuX1XQFhlK/Fl2/dPZNCAtIUE4IKV8Vm68VNrs6oVMX+1NAL+D1dHcIwOb2rAZeAF6oq6rogpkUHQWMBHLT2TchLCRjMJE0CcpZb3W6OyBEG3un11bdxwPvADnA7PLR7pVWn8QfCOZjZlrfLSrMCbS2HZfTsQ54LXy7aOGymn9SH6DbG1k0X7Q/MksrhGTKic1THXBSr/wtS4F9gfezZs3/w+qThHxeFzAIqLAXlybcvs3tWQ9UABV1VRXnA/tQv1FEgYVdFaKtSVBOJE2CctaTTDmxOfm6S2fbsd26dnoWGBh+rDwVJyoqzPnBHwi+CTzvDwSzgZmYjLy5RYU5rc6QcDkdXwBfALcsXFazDabUYjhwGJCdfM+FSDkJRgghfwdi83Rdbr/sbOCS8P2KVJzEXly6MOTzZgEfhnzepcDLwCv24tIfE23L5vbUAfPCt3F1VRW7YYJzo4BdLOy2EG1BgnIiaUprWf/cSoMnznkWOD7d/RCiDfwGDMnPc1yGWdQ3om/5aPeyVJ3UHwh2Be4ALgw/tBp4AxOgm1lUmPOLFedZuKymE2bWOZJFN7D5VwiRNjNcTscR6e6EEOm0ZNAAO5I1KjYvs3L6bjlOKfUR4Ag/5s6aNX9Bqk4Y8nm3BKYAJ2I20ZoP+ICX7cWlXyfbfl1VxQ7UB+j2BlSybQqRYqU2t2dyujsh2jcJylls8MQ5DwLnpLsfQqTYeuCQ/DzHvsDNUY9/XD7aPbgtOuAPBI8BHqbhwsEaqKI+i+7josIcSz7kFi6r2Z76AN0BQBcr2hXCAo+5nI4z0t0JIdJtyaABK4Et090PIdpAdbesLvv13KaHH1NWCvALsG1b7Lwa8nlPBe6lPhgI8CUmg+5le3Hpx8meo66qYlvM+nOjMGsBd062TSFS4BSb2/NUujsh2jcJylls8MQ5ZcDYdPdDiBQ7LT/PsRZ4joazmNeWj3bf0Fad8AeC24f70FQg8EdgFiZA90ZRYc4aK867cFmNAzgUE6A7HNlxWaTXnS6nY1y6OyFEui0ZNOArYEC6+yFEiq0D9sntlz0eOCnq8cezZs0/va06EfJ5+wNPYTLaYlUDr2CCdPPsxaV1yZyrrqoiGzPmGoVZXqRHMu0JYaHDbG6PP92dEO2bBOUsNnjinOuBa9LdDyFS6Ib8PMcsYC7QLeY5V/lo92dt2Rl/INgFU856UZxD12L6PAOYUVSYs9SK8y9cVqOAPanPotvdinaFSMBVLqfjxnR3Qoh0WzJowDvA/unuhxApdm5uv+yuwN0xj5+YNWv+s23ZkZDP2wm4FrgCsDVxWBCYjgnQvWkvLk1q/ce6qoruwDDMRhFHAFsl054QSXLb3J6UlYyLzYME5Sw2eOKcCcCkdPdDiBR5Oj/PcSXwIZtuZ7+kfLR7+zT0CQB/IHg0ppy1paVLXxIO0AGVRYU5lizUunBZTR/MRhEjgIOR2VyRemNcTseUdHdCiHRbMmjAC8Ax6e6HECn0aG6/7AeAt2m4jEYIyM2aNf/3dHQq5PMeADwJOOMcWoOpYHgZmGUvLk1qg7y6qopOwIGYDLqjgD7JtCdEK/zD5vZUp7sTon2ToJzFBk+ccw7wYLr7IUQKzNsmu3tx926d5gKFjTx/Z/lod1pL6PyBYH9MOas7wZf+BryGCdC9VlSYs9KK/ixcVtMNsw5KJIuurxXtChHjBJfT8Vy6OyFEui0ZNOAe6jcBEqKj+XTLnC2O6NqjcyWQH/NcZdas+fuko1MRIZ83G7gfOK6FL1kHzMZsFDHdXlwaTOb8dVUVCtiL+o0ipJRdtAWHze1Zne5OiPZNgnIWGzxxzmGkaDtyIdLo206dbPvm9driSeCQJo45qHy0++227FRjwuWstwElrWxiA/Ae9WWui6zq28JlNbtQH6Dbm6ZLPYRIxKEup+PNdHdCiHRbMmjANcD16e6HECmwUin2zOmbPYXGx2HXZM2aP7GtO9WYkM97JjAZyErkZZixV2SjiKSXGKmrqijEBOeKgT2SbU+IRqyzuT2xS/kIkTAJylls8MQ5g4Av0t0PISz0BzAkP88xHhjdxDErgLzy0e6ES0CnVlZ3AU45f0jBI0n0cRP+QHAU8AiQnWRT31K/m+vbRYU565PtG8DCZTXbYDaJGAEUITsGitYb7HI6kt7pToj2bsmgAecBU9PdDyEspoGjcvtl7wVc2cQxe2bNml/VmsZDZSV3Aw/Yx03+vLUd3KRNn3cH4GnMmrut8TH1Abovk+1PXVVFP0x56yhgP8CebJtCAD/a3B4pmRZJkywN6y1LdweEsFAtUJyf5ziSpgNyADOiA3KXlC9SzRwbKxt4eGpl9WNTK6u3aGU/N1FUmPMyZmb0oySb2h6Tdfc6sMIfCL7kDwTP9AeCsWvqJcTldPzmcjqecDkdxwO9MGWudwBfJdlfAfzy848MGbgtu/XtyZq/mq4qWL5sKbv17bnJ7T8XntHgOK01D959G4ftXcheO+ZwwuH78/7bDZPT/lpdw4QLTme/QfmcOvLfLF3ydYPnV638g6G79yfw2SeWvc+w36xqSCm1g1LqfqXUQqVUSCk116q2w+3vrJR6Vyn1l1JKK6UKmjm2n1LqGaXU70qpNeE+HWZlf1pDKTVNKVUVdf+M8HtJJCukJec5Til1hpVtbgZ+SXcHhEiBW3P7ZYcwmyk05lcgmYXmXcD8UFlJaysMNmEvLv0G2NDRwFIAACAASURBVBe4BWjNzqt7ABOBL0I+7+KQz3tryOf9V8jnTWR8uZHN7Vlqc3u8NrfnIGBb4BzMhGtSm06Izd6KdHdAdAwSlLPYgquHrsIsYipERzA6P8+xNXBrnOPKI/+4pHxRPrB1AufoGf7vacBHUyur/5lYF5tWVJjzHWZG1GtRkw5MGcQjwM/+QPBDfyB4tT8QTGrHVZfTscHldMx1OR3/53I6BgI7AmMxa63UJt3rzdCdN15Fjy1aHuMdd9WNPP7KmxtvF064usHzj9xbxgPeWzn+tNHc9dAzbL/jQErOOp4vFtZfBz109+0s/e4bJt03jT7Oflw9/oIGbUy582YOOPgwCne1fINeKxf2HoTJ4FwcvlntNkwg/khgCPBTYwcppZxAZfjYM8PHPwF0T0GfkjUT817WWNzuccAZFrfZ0UlQTnQ0b/XK7/kQ5vOvqYCUP2vW/I2lTxtKjhyU4Dk6Ad0Ab6isZGaorCSpSccIe3Fprb249HLMplc/JNHUjsClwAfAspDPe2/I5z0kvPNrwmxuT9Dm9jxsc3tGADnA8cCzyPWbSJxlk6Ji8yZBudSQbDnREdyYn+cIYHbTam5m8m9MFlnESGBVAufpGfXvnYH5Uyurz07g9c0qKsxZX1SYcwmmZMGSDRzCIgsK3wB87A8Ef/AHgg/4A8Ej/YFgUjuuupyOb1xOx10up+MQTBbdscA0zGy4iOPjD9/n/blvctq5LZ/0L+i/A7vusdfGW9+C+o2Ea9ev55H7yjjzgks4c8xY9jnwEG70PsiOOw3i/jtv2Xjch/Pmcs5F/8c+Bx7ChGtv5bMF8/l7zV8ALPn6K2b6nuXiS6+17o2Gu+dyOqy8kHhVa+3UWh+L2aHYagOBN7TWs7XWH2itm8pSuA1TOj5ca12utX5Ta3271vrlRE6mlOqslEppmZLWOhh+L63JBhHWkqCc6Eh+7NKt0xk2u+15YKtmjtu4lvWGkiO7AgckeJ7o4NbhwGehshJPgm00yV5cOheTjeezoLk+wBjgDeCXkM/7WMjnPSrk87Zqwsbm9tTY3J7nbW7PiZjx1nDgIWS81WrLf11BzwOKse95OKvX/N3ssVWBxRRddCU5hxxPr4OPY9iYK/jwi4ZLOWutuemRZykYcTo99h2J+5SL8Vc2TAyt+WsNx19+E1sddAz7nDmWxUsbxoD/WFVD3rATWfC/hhUMFrA0U06qFeLrqNUKEpRLDQnKifbu2T69sx4AphM/M+X18tHu6AyRortGDkwkuyt2LbXuwENTK6ufsLic9RVgd2C+VW3G6IMp8S0HfvMHgrP8geAYfyCY1I6rLqdjlcvpeNHldJwJ5GE2iPgv8GnSPe6AQqEQt1w7gXNL/0P21ttY0uaypd/x1+oa/rXf0AaP773/UD6YN4fa9WaZwdra9XTrZtb77dbd/NlEnrv9hss484Kx9MrtbUmfoliZJUcygSWl1G5KqdnhwdsfSqmnlFK9w88VKKU0phx8bHgANbeJdrbEZKTel2h/lFJzlVIvKqXOVUp9C6wFtgs/90+l1EylVE349oJSKi/qtQeF+zVMKTUjPGj9Xil1fpxzbjIgVEp1V0pNUkotVUqtU0p9p5S6Oer505RS88KD3T+UUnOUUu6o56cBRwMHhtvWSqnrop4fqZSqUkqtVUr9HD5X56jn85VSzyulflVK/a2U+lYplRGLwKeYBOVER1ELHJvdO+tamt+koI6GE6MHAF0TPFdsxllvYGaorOSuUFlJom01yl5c+ru9uPRo4FysyyreGlNl8TKwIuTz+kI+76nhXWATZnN71tvcnlk2t2c0psT1AOBOoNqi/m4WLp38MFnd48dIl/0cZNiFVxIKhZh23Xgeu/7/2BAKcdhFV7H0p/qP8lunPc/Eh55mzLEjePn2ayjs35eR467noy/rk/lveuQ5vl76I8/efDkF2+Vx1vV3NjjX9Q88xfD99mLwzjta90YNq8tXpVohcR2iWkGCcqkhQTnRnlVuvWW3EqXUTEwQKJ7o0tVsTOArET2bePwUoGpqZfUuCbbXpKLCnGpMOeudcQ5NVjfAA9wLLPUHgp/5A8Gb/IHgPv5AsNWfuy6nQ7ucjg9dTsfVLqdjd8AJnI/ZhKL56cjNxAtPPsz6dWs5/vRzE3rdtf83hj0Ksjlk8I7cfsPlrF1b/+Ncv24tAJ07d27wms5dulC7fj0/fF8NwM677IbvmcdY+cdvPP3IFPL7FtAzeyvemf0a33/3LSefPSa5N9e4jCidUErlAHOBHsBJwMXAgcAbSqkumIHfEOBnzOLfQzDZDo3ZA+gMaKXUe0qpWqXUD0qpy5VSLVlPaF/gAuA/wBHAn0qpHTA7+3UDTsUMtAYBrzbS5sPAZ5jAYAUwRSk1ogXnBSDcXnm4D/diBtjXYrIwIgqAxzFZsCdhSrveUUr1Dz8/EZgDfIL5WQ3BZG+glDoOk3EyHzNQvh5zoXtzffM8jvl8OBfzWXQjiV+otzv9v1z8F9YPzIVIh0tz+2UPBOJVDszPmjU/+nvAg9lFPhGNlYEqoBSz1lyi5bBNsheXPoj5jLd6c6IemIqIx4FfQz7v6yGf94KQz7ttaxqzuT11NrfnXZvbM87m9vyDqDXurOtyx/PuJ1/gr1zA+FOK4x4787351Kz5mxcnXcXw/fZi+H578dJtV7H677XMes8kQq2vreWWx57n0tOO5dLTj6VoyGAev2ECu+xQwA0PPbWxrdkffcLlZx1P0ZDB3DnuXCo//x9//W3Gbv/77nuerHiLG8ecnoq3bPUYTKoVEtRRqhUkKJcaEpQT7dWSTnZbcY/unZ8AWrK2Wwh4Ner+4SQeHGpu19GBwIdTK6ub22QiIUWFObVFhTnjMLtw/WFVu3HsAlyOCQr84g8En/AHgsf7A8Gkdlx1OR0/uJyO+11OxxHANpiyiynA90n3uB1a+cdv3Hf7fxl/9U2bBNCa0qVLV44/fTTXTrqX+595laNPPpMXnniYyy48c+MxffoWoJTiy4UNryG+DK8n9+dK82t03iWX8e3i/3GQ6x88OuUurrjpTmprayn775WMu+pGunRNSUwkUxYZHh/+b5HW+hWt9ZOYoNYuwNFa63Va6w8wi2r/FB5ABZpoKzIZcD/wLjAMs47jfzGBrniyAY/W+kWt9Syt9SpMUOzn8OOvaK1fwpTa74H53IpWobW+Qmvt11qfB7wJXNWC80YMAw4FTtZaTwoPfh/XWm/8HNNa36C1fkBrPRvwY2aiv8dMRqC1/haTBbkq/LP6QGv9QzjgdxvwuNZ6jNb6da31FGAccKFSKpIeuhdwU/i9ztVaP6K1vjSB99CeyRhMtHfP5/bLnosJ6sdTEXPfqqBcxK7AR6GyEstmlezFpV9hJhpux+wsa7XOmM/g+4DlIZ+3MuTzTgjvCNsqNrfnE5vbc43N7dkFGICZ9PmA1PS/XQqFQpTeNpWrzz6JbbKbmm+vt2FDiE52W4Osuqwe3elkt4E2P9Zvf/iJmr/+5uC9dmvw2kP22p03P/yE9bWmMGd97Qa6d+0CQI9uXcOPmefGlT3IpacdS16vRJa7bjFLx2BSrbD5VitIUC41ZEAo2qOVwPC8nC2uBYpa+Jr3yke7o7+QjiKx9eSg6Uy5iO7AA1Mrq5+cWllt2XoBRYU55Zisvg+tarOFemEuvJ/F7OY6xx8IjvcHgjsl06jL6fjb5XTMcjkdY1xORz/M+i1XYtLP2/XsUUvdM2kiu+zuZv9/t/TXF3J653H5xDs4aNjh7Dlkfy4YdwXjr7mJuW/MYtGXnwHg6Lklh408hofuuZ2P3n+HP1f+zjOPTuXDeXMBsNvNV2kfZz9enrOA8rkLmP3xN+xzwME8O+1+cntvx78PO4KPP3yfY4cNYehu/+DGK8ZuLG1NUrUVjVhgL+D1cAAMAK31fEz/9kuwrcjYpEJrfZnWeo7W+hrgMUxwO54FWuufYx47BFPiVKeU6qSU6gR8F+6fO+bY2JlgHzA4gdnefwO/a62nN3WAMuu6vKyU+gUzuVEL7IS52GvOAKAv8HzkfYTfy1uYLMDIZMqnwM3hwWpSJfTtkOxgLdqzRVlbdx8HvIT5m44nej25AsxkZijBc8bbMKE7cG+orGR6qKykV5xjW8ReXLreXlw6ATOJ8aMVbTZBYZb9mAR8HfJ5Pw/5vDeEfN5W77hkc3u+trk9k2xuzxAgH5P1/SaJB0M7lPtfmsXa9esZc1zLEsuL/70vPbp14//uepBff1/Jr7+vZFzZA2zlcHDMIfsDsHa9Cax1iZlo7dqlM+trN7Bkufmq32PgDjz0ip/fVq5i8rPl9O+Tx1Y9HcycN59vli2n9MSjLHynDWTExKhUK9Rrr9UKEpRLDQnKifamFjg6P89xOKYcsqWiS1e7AocBfyZ47vjTacbJmHLWXRNsv0lFhTlLgf2BMqvaTFAn4CDMbPEifyC42B8I3ukPBA/xB4ItS/Vqgsvp+MzldNzkcjr2wawPczrwAon//2kXvvnqf7zy/BOcd8llrPpzJav+XMnav00VW03NqgblqPEccrgZvC36YuHGxyZceyv9dxzI6BNGcOCuBTx2/2TOuXgCAFv3qt+orlOnTvTrvyPdu/fgj99/4+F7bmfCdbewft06Lh1zOudcPIHytz/hf198yktPP2rFW19iRSMW2JbG1/P6hcR2Y4b6dfLmxDz+FpCvlIr3mdFYP3phBoi1Mbf+mIFTtNgFvn/F/K229GJ0G5pYpwVAKeXArAHlxGS47Q/sCSwk/kV4pA+zaPg+vgs/HnkvxwNVmFL9pUqpT5VSB7ew/+3doviHCJGRVgPFPRxdp2A+m+IJYv7OIyKbM1iZKRftCMwmEIcm2H6T7MWlb2ImEZucxLDYP4GrgY9DPu93IZ+3LOTz7h/yeVt1TWxze360uT1TbG7PoUAu9WvcbVZl9L+tXMU19z/B7WNH07lTy36dtsvZhtlTbsY35z22LTqJbYtO4uU571Nx90RytjKFJP375KGUoirQcHm1+V+auZff/zT7XF0z+mQCS5aSe+gJTHr8Re697CJqN2xgwl0PMan0HLp2SWpI3ZzlqWo4QVKtUK9dViu0aitpEZcE5UR7c35+nsOB+aBJxCtR//434CDxTLlESjh3wpSzlp4/pOCBBM/TqKLCnFpgvD8QnIvZ4TQl+e0ttCNwSfi2yh8IvoFZL25mUWFOsLWNupyOFZhZm8cXLqvphAkCjAjf4mXmtAvfV3/LhtpaTjvqkE2eK9prIKNOOI1rJ93TorY2TtpFTd5tvU0vHnx2Br/8tJyaVaso2H5Hnnr4Pnrl9KaPs1+j7dwz6QYOHT6KHQcO4qvA52zYUEvREWadlRHFJ/BR5buccMZ5Cb7TTWRKUO4nzAVJrN7AgkYeb87/mng88j8kXuZnY+VEv2MulB5q5LnYme7Y95GLucht6Yz4b5ggZVMi2RWHaq03BpDCJSPxRAKW52JmcGN9B6C1Xg6coZSyYQaH1wHTlVJ9tdYZsQ5hCkmmnGivRuf2yx6FCX61hD9r1vzoz7vWBuUSWfNpW8AfKiu5E7jcPm5y0inf9uLSFcDIkM97AXAHbbeYfAEwNnz7NeTzTsdkwMy2F5cm/L5sbs8fmMXwn6irquiBCQ4UY8Zaze2e2+5dNeUx9hq0E4fvu2eLX/PTit857rKb2GPgjjxwZSkA970wgyPGXsu8h++gb14uW2ZtwQnDDuSmR55j0Pb9cO3Yn6dfm8Ps+Wavs0ilQsF2vQm88ABLlv9Efu9e9OjWjTuf8tEnZxtGDd2Hdz/5gosn3cdPK37n6IP3467x522SfddK31jRiAUarVZQSlVjqhWeSaCtBtUK4X/PUUrlY6oV7ovz+qaqFR4jXK0Qfiy6WmFm1LGNVStMVkrZtdYtyQJuUbUCcBOwDw3HfAlVK0Q9Hl2t8Db11QrbAG9preMuKySZcqmxDFljQLQft+TnORZi0pkT+Uz4vHy0OzogEMkNT1WmXEQ34P6pldVPT62sdiT42iYVFea8iiln/cCqNpPUE7OewaPAz/5A8AN/IHiVPxDcLc7rmuVyOja4nI45LqdjvMvpiJTLjcN8oSSya25G2X3PITz43MwGtzMvGAvAPY+9yOnnlba4rTdnmlhz4S6b/qh7b9uHHXbamdCGDZQ/9wQjjz+10TYW/+8LZleUM+b/6if3amtrCYXMeOLvNWvQ2pKviUwJyn0IFIWzwABQSu2JueiZl0hDWutqzALHsZldBwPfaq1Xt6J/szGDpQVa66qYW3XMsaMaub+ghYPByLm2bqbcInLBuXGBZaXUPpifVbT1bJo59xVmZr6gkfdRFRtw01rXhWfHr8eUtTQeQe5YJFNOtEd35/bLDgI3JPCa6NLVrpiLUUhdplyEwowbPgiVlQxM8LVNsheXTsFcoC+Md2wK5ALnYLKQgyGf95mQz3tcyOdt1bIpNrdnjc3tecXm9pwWbjuyxl0qS3XT4stvl/Lo9De4ZvTJrKxZzcqa1fy91ny9/bn6r43/jnX7Ey+yIRTihVuv4LB93By2j5sXJ12J3Wbjjid9G4+7c/x5FPZ3csgFl5NzyPHc/sRLXHn2CQD03ro+1tmpk50B/fLp0a0bK1b+yc2PPk/Z+HNZt76WEy6/mSvOOoGvfA/xyaJvePDl16x463+TOZlyUq1Qr11WK0imXAosuHromsET5yxl0wG2EJnmhT69s+7DXFD3SPC1G7PkLilfpDB19ZDaTLloJwKDp1ZWH3f+kAJLBnBFhTnf+wPBAzCzJ+Opz8xJNxvwr/Btoj8Q/AEzqzQTeLOoMKfVO6+6nI6vMV8ady5cVtMTs57gCMyMe06yHW8rW229DXsO2b/BYz/+YCam9thrH3psYcbVR+zvYvDe+3HdbWb97CllN7Hmr9Xs5t6bLbIcfDz/PR6bOpmDPUcyYOf6vU5mvPQMGzZsoE/fAn5evownH74Pm93O2ReOa7Q/k677D+dcPIGttjaZ7AX9d6Rb9+7cddPV7LnPATz3+IOcdu7FVrx1S4NySqke1JcS9AF6KqWOCd+fpbVuqiSnDFPW4FdK3QpkAbcAn2PWRkrU1cBLSqnbMIOngzDrkJzWirbAZIrNB2YqpR7BZL31wVwoTdNaz4061qOUuhEz21kcPmZkAud6A1MO8bRS6gbMLoPbAgeESzE+wJSpPaiUmoTJmruOTQf3i4CRSqmjMOud/Ki1/lEpNR54IjwwrsAE7/pjJkaOwawF48dkxy7GrGMyHlM60lQWYkcimXKivancejvHHcBHtDxrrQ7zdx6xP7BF+N+pDspF7A4sCJWVjLWPm2xJ9YK9uDQQ8nn/hfn+KCU947CewAnh27qQz/smJltnejirLyE2t2cDpgTvzbqqioswY7lR4duOlvU6Tb5etpzaDRvY96xNx0N9h5/GWSOH8eBVl2zy3KLqHyjs369BuWuXzp0p7N+Pb3+oj6nkbLUlb065hR9+WcGfq/9ip375eJ95hbxttqJgu96N9umq+x7nmEP2Y5cd/sHCxUuo3RDiuEMPAOCUww9mTtVCLjyupQmpTfrW5vZkShKOVCvUa5fVChKUS53PkaCcyGwfbrVltzFKqdk0/+HVlPKof+9N/RoEVm/00JwBwAdTK6vHnj+kYGoS7WwULmed4A8E38akWqeznLUp+cB54dvf/kBwDqbMdUZRYU6ry+ddTscqzLpzLyxcVhP5IomUubqS7nUG2BAKbcxWA/jHDgN4/P67efnZx1m79m+23S6f088v4ZyLJjR4XV1dHY9OuZOfli8jy9GTocNGcPF/rtkY7Is2u2I6K379meNPP3fjY127deOWux/hpqvG8fJzT3Do4SM59pSzk307f7ucjiZnA1spF/M7EC1y/x80sbGE1jqolBqKKT16BhMomgWM1VonXAaktX5ZKXUaZrOSUsxaHxdqrZ9KtK1we4uVUntj1kR5AJOtthyT1RZbfnIOpoR8LGYAdmFzZRCNnEsrpUZhFgq+BBPc/hGTjYzW+hel1LGYtSTLga8xa3nGrjdyH+ai9xFM6dP1wHVa6+eUUquAK4CzMIu6L8F8BqwP3/8c83NzYtY2+gAYprVudQC/vej/5eLflgwa8BtmtlyITBe0d7Kd2Kmz/RkSmwj7KGvW/OiLO0/Uv9sqKAdmQvf+UFmJBzjHPm5y0uXx9uLSdcDYkM/7GmYc1njkpW10xexsPxwIhXzeeZjgwsv24tKEd7oPB3E+CN/+U1dVMQgTnCvGfN63O/vtNojZU29p8Jj//QVMevwFZtx1Pf37NH6J0W/bXCre+4j1tbUbS0nXra/ly2+XMmL/vTY5Pr93L/J792LtuvU8+urrnHnksEbb/ezr7/C99R6BF+/f+Nj6DaZSwW6389ffa7GmUCFjSlfBJFdcoJRyaK1rILlqBaVUpFrh/qinrKpWiPfTH0XDXaVbU61wqVJqhNZ6RiPPN1etEB3AjFet8GC8joR3r/1AKXU98D6mWqHRz0hlUfmMiDF44pz/Yi4mhMhE1XabGrJtbtYjNBzItdSy8tHujTv6XVK+6BZMWjLApXeNHNjitemmVla/S+K7MzbmWeDc84cU1FjQFgD+QNAJPIeZVWkvPiMcoAM+LCrMsWTn1YXLavKpD9D9m7Zb80U07UuX0/HP+IeJllBKHYQp19hFa/1FmrsjkrBk0IB5mB3ghMhkIWBYbr/sozC7JSbiuqxZ86+P3NlQcmQA2Dl898hOk6e/2uJOlJX8SXITpBHLgdPs4ya/ZUFbAIR83lzMxMRwq9q00ALqA3RNLZrfYnVVFQWYjOdRmHFxu11matqrb3D2DXfy59svkdXDDBcHjDqbA/bYhYeuNllzC/73NfucOY5D996DC44Zjtaa+16Ywez5nzL/cS+uAWavkydmzaZ2Q4j+ffL4/ucg3qdfZkMoxHuPlG1sO9rB51/GkQfsTelJZlWdtevW0//IMznpsIMYuqeLC2+5l/GnFHPxCYkkwDfqdpvbMyH+YS0XU60wHvN3eW34fpPVCuHdV78GAkB0tcIfgDsyORpeY+5FrfX/xenHKEyVwx3UVytcBpzW3OSoUmousEJrfUzM4wMw1QrvY/6eN6lWiBqD/YDJ9I9UK5wHjIxMjiqlpgH/1Fq7w/fPwCz149Barw5vxlCBWS9uk2oFpVRvTED1Q8yuzJFqBRvwQaTvSqlrMNe2J9OwWuF4zNqR95NYtcLOQP+mJkclUy51Pk93B4Rowp/A8G1zs66idQE5aJglB/XryUHbZspFO4H6ctZPrWiwqDBnWVQ56/+ROeWszdk1fLsCWOEPBCswAbrXigpzEv1/s5HL6fgBmApMXbispjtmxiwyexy7HoRoG1KmJ0TjvkKCciLzXZPbLzuXxANy0HA9uX7UB+SgbTPlovUB3giVldwOXGUfNznpdWrtxaW/AiNCPu9FmM3I4q351JYGh2//Dfm8izEBOh/wkb24NOGsF5vbUw3cBdxVV1WRg1k2YRRmvNXVqk6ni6lUqJ8nHrzzjsyaPJGJDz3F6dfeDsAu2xfgv/fGjQE5gLo6zW2PvcDSn39ly6wtGHngEG4cc3qjATnfW+/x04rfGXNc/ZKu3bp24akbL+WiW+/jkemvc/TB+3Le0bEbfrZKKjLlpFphM61WkEy5FBk8cU4hZqFqITLJBsCTn+cYhPnib61Dy0e73wS4pHzRQBquP3DiXSMHPtvShqZWVn+HtaXe64Cx5w8pmGJhm/gDwcMxsx7ttSSqFpPCPgN4tagw52urGl64rMZFfRbdXrTj2d125kaX05HINvGiGZIp13EsGTTgUky2gBCZ6tWcvlteppSaT/1acC21AuidNWt+HcCGkiPPB6LHPEWdJk9/vaWNhcpK1gFdEuxDPFXASfZxky0ba4R83n9iAg6ZniG+HLPu8svA2/bi0kSDpA3UVVU4MNlTo8L/tWyTM5GUg21uj2VZoZu7zX0MJhdOqbMYEy0VIpOMyc9zdMcsyt5aK4G5Ufdj87/baqOHpnQF7ptaWf3c1Mpqq7LwKCrMmQXsBrxnVZttrDMQmUVb7A8EF/sDwTJ/IPhvfyCY1L7wLqdjocvpuNHldAzBrC14BvAiif8uiMTILpMW0lrP1VqrzXEw2AHJ34bIZEu6O7peoJR6icQDcgD+SEAuLLbqIV2ZctHcwCehspKkF0+NsBeXfoHZJfFuq9pMkT7AhZjNHX4J+bzTQj7vyJDP26plP2xuT43N7XnO5vacgMn6GQE8DAQt67FoDUm+EZaRoFyKLLh66AY2j13ORPtxW36eowozy5jM3/7M8tHu6AHfUTHPJxqISdWM33HAgqmV1ZYtnFtUmPMDZl2FW2l8d6H2ZEdMavhsIOgPBJ/3B4Kn+wPBpHZcdTkdQZfT8ZjL6TgWs3X4wZjdXS2bLRcbSeBBiMZJabfIVGuBox1bdy8DBrayjejS1S6YdV6jJRqUS9X14BbAQ6GykhdCZSVbWdGgvbh0rb24tAQTmGoPQamtgdMxmXPBkM/7UsjnPSXk82a3pjGb27PO5vbMtLk952DWyToQU/my1LIei5b4zeb2/JLuToiOQ8pXU2jwxDlPAKekux9CAL4+vbNKlFIfYmbwknFc+Wj3CwCXlC/Kw9TpR6+1tutdIwe2aE3FqZXVWwCt2cUnEeuA8ecPKbjXykb9gaAHU87ay8p2M0AdZjHWyG6uC61qeOGymgHUl7nuh8neE62jgZ4upyPVfz9CtDtLBg3ohPluaffrMIkO56zcftlbYiarWqMOU7q6AmBDyZEHYzKyou3bafL091vSWKispBNmeYtUWwacah83+W2rGgz5vL2BacBhVrXZhmoxpXovA+X24tKkd1Kvq6rYA1PiOgoYlGx7olnv2NyeA9PdCdFxSKZcaslmDyITfJTt6Hqeq/FHRAAAIABJREFUUmoGyQfk1tFwm+oj2XTzg0Qy5SwrL21GV+CeqZXVz1tczlqBWQA0oa3G2wEbEFmM9VN/IPi9PxCc4g8Eh/sDwaR2XHU5HYtdTkeZy+n4N6YEI7KD0Yqke735WZ6qgJwyFiqlTo967Hql1OdKqVVKqRqlVFV4B6rY1w5SSr2ulFqjlFqhlJqilMqKet6ulPqPUupdpdRv4dvrSqk9U/FeEqWU2kspdV0rX3uQUkorpSxd70gpNUEpNdvKNju6/l8u3gB8ku5+CBHj4dx+2YsxO/61VlUkIBfW2IZdiWTKtdWmf07grVBZyY3hQGDS7MWlv2DWWBuLGZ+2J52BYZi1AJeHfN73Qz7vhJDPu31rG7S5PR/b3J6rbW7PP4EBmN0yP6T9V3ZkIildFZaSoFxqfZbuDojN3vd2mzoqa4suj2LWQ0vW7PLR7uhAQGzpKpjdXVuqLYJyEccCH0+trN7DqgbD5axDMduOd9RBjxOzK9EM4Dd/IDjDHwie7w8E85Np1OV0/OlyOp53OR2nAb0xW5ffhHxutlQghW0fh9lp6umox3piMhKOB47GbDH/rFJq47b3Sqktgbcwu2odj9mx+Gjgyah2umMuFD4CTsVkk9cC85RSg1PzdhKyF3BtK1/7MTAE+Na67gBm1+M9wosgi5b7IN0dECLKx9m9s64Hnie5LPGKmPvtJSgH5rrzCmBeqKyk1cGnaPbiUm0vLr0L+Bep/V5MJYX57pgEfBPyeT8L+bzXh3zeVo/bbW7P1za351ab27M3Zhx3IWa5kqQ2nRAbSVBOWEqCcqklmXIinVYBw7fNzfoPplzQCq9E/nFJ+SIHm65jEjlvS1m9yUM82wPvT62svsiqBosKczYUFeZcjpmt7egZX92B4ZiZ3WX+QPBTfyD4X38guLc/EGz194nL6ahzOR2VLqfjSpfT4QL6AmMw27mvtaTnHc9HKWy7BHhCa72xpElrPVZrfYfWukJr/brW+lzgfeC0qNeNwfyOHKG1flVrPQ2ztf1IpZQ7fMzfQH+t9Tit9SytdQWm1OYnwLK/y2hKqaQyPFtKa71Ka/1Bc1vet7LdGuAl4GIr290MSFBOZIo/lE0d16Vbp8eA7ZJsK3o9ub5AYSPHZGpQLuJfmE0gTo97ZAvZi0sXYjaXmBLv2HZgF+Aa4JOQz7sk5PPeEfJ59wv5vK0aZ9ncnuU2t+c+m9tzCGYSNLLGnaXfVZuZlAXlGqtWiHn+qHBWflXM412UUreFKxH+Vko1miyglJoWfn3srbVrXFpGKTVMKXVJK197Rvh9ZMU/OqF271VKPWxlm42RoFwKLbh66HLg93T3Q2yWNgDH5ec5DsJcYFuhDpgedd/Dpuv1rL5r5MA6Wq4tM+UiugJ3T62sfnFqZbVlQcGiwpzXMNmI71rVZjvgAq4EKoGf/IHgNH8geIw/EExq8w6X07HM5XRMcTkdw4FtMGXSDwDLk+5xx1GZikaVUjtgshZfbMHhvwFdou7vBlRprVdGPfY6Jot0OIDWOqS1/iO6Ea31eswANzdO364Ll8Tuq5T6WCm1Vin1qVJqv5jjqpVSdyilrlZK/UDURIFS6rhwGe46pdQypdSNSqlO4efOILyrX9QgdW7Ua/+plJoZLt+tUUq9oJTKi3p+k/LV8P1SpdRNSqmgUurX8ACva9Qx2Uqph5RSP4bf0/dKqQdj3v5LwAil1NbN/YxEAxKUE5lAA6fmOLccjcmsT8YKGk7INJYlB5kflAOzyde0UFnJM6GyEkvGYvbi0r/txaVjgJF0nEnSfwDjMGPLH0M+7wMhn/ewkM/bJc7rGmVze363uT2P29yeUZg1kSPZ7Cubf6WIkcpMucaqFQBQSnUDyoDGNpnogZkIXYOZNG3OIkx2ZvStutU9ts4woFVBOWAm5n2ssa47ANwGnBweH6eMBOVSTwaFIh0uzs9z2DE7Mlnlw/LR7ugvgZGNHJPozqttnSkX7WhMOatlJXNFhTnLMYPum+i45axNycXMvr6AKXOd7Q8Ex/oDwaS+xFxOxxqX0/Gqy+k4z+V05GPW8bsas05KIgHgjiZV3y0HA38BjW7woZTqFA4inYwZPE2NerobsD7mJRsw/592buqE4QDVYFpWetQDcwExFVOSvhKoiA6OhZ2E2ZVuDKaUFqXUMOA5TJnpSEwA7v+Ae8KvmQncEf53ZJA6JvzaHYD3wu/xVOAMzELaryqlYtfVjDUekx1zCmZwdx5QGvV8GWbjk7FAEaa8K/bz431Mydv+cc4lwvp/uXgpJgNTiHS6KbdfdifgUgvaej1r1vzo772mgnKhBNpMV1Au4gRgYaisZL+4R7aQvbh0OrArm26A0d71BkZjsiWDIZ/36ZDPe2zI521VZpDN7Vljc3t8NrfnVMwYLrLGnXxuNu8Hm9uTyp1/N6lWiDIBM0H9WuwT4QnRrbXWRZgNRJrzVzizP/qWksqUNqxWCIbfh6XXBlrrasz64RdY2W4sCcql3jvp7oDY7JTl5zkqMRefdgvbjS5d7Ywp14yVaFAuHZly0fpjylmtyiakqDAnVFSYcyVmsJzKL+1M1hlT2lwGfO0PBL/yB4J3+APBof5AMKkLAJfT8anL6fivy+nYG9gWOBOTRVSTdK/bj29cTsdvKWp7MPC/xgY1Sqm9Meu//YFZX65Ua/1K1CHfAC6lVPR6SYMxn0PNZXhdiZkVfqgF/esOXKm1fkBr/SqmNL+WxmdWR2itp2utfeH7NwBztdana61f01pPwgR4Ryul8rXWQcIzxVGD1Eig8FrgZ8CjtX5Fa/0SJrC3B41/Fkar1lqfobX2a61vw6zPWBz1/F7AvVrr57TWb2utnwyXB2+ktf4T+D58rGi5D9PdAbFZe7OXc8tpwGNsuilWa8yK/GNDyZFdMJMojWkPmXLR+gFzQ2Ul14fKSiwZt4Z3Mx2GCWLEThZ1BD2BEzFrFAZDPu/0kM97Zsjn3aY1jdncnlqb2/OGze0Zg9kUbh/MJNI3lvW440jZBm/NVSsopfpigvulsc9FaK1TlhAQLnutCpfPLgpn9s9TShXGHKeVUuOUUncppYJELeellLpIKfV1uFrhG6XU2KjnrsNMYvaLqlaYFvX8fkqpt5XZSOw3pdSDSilH1PMNyleVUgXh+8cppe5XSv2plPpBmY3LbFGvy1dKPR+uZPhbKfWtUmpizNt/CZMtl7LYmQTlUk+CcqItlW+Xm1WGueiztKaeqKAccBCQ3cgxiWzyAOkPyoEpv/NOrax+yeJyVj+mnE8+A8wuYOMwmwCs8AeCz/kDwVP9gWCvZBp1OR2/upyOaS6n4xhMmeuhmOzQjj6ITGUGdh5Nl/18DuyJ+TnfA9yjlDox6vkHMbvq3q2UylNKDQLuw2RtNJq5oZQajgnK/Udr/VUL+7hxBlhrvRp4g02DVbOjZ32VUnZMAO2FmOOew4yFhsQ55yHh89aFswU7Ad9hgnju5l6IKeGNFgCiN0r5FJiglBqjlBrQTDsrMP9/RMtJtYJIl2Vdunc+02ZTL2JNVUAd4I+6vx9Nj/PaW1AOzOTNNcA7obKSAksaNJtA3I7ZUb6l3y/tUTfgCOAR4JeQzzsn5POWhHxeZ2sas7k92ub2VNrcnkttbs+O1K9x96l1XW7XUhaUo/lqhTuA57XWH1twnkKl1KpwcGyeUurAFr6uH2bCfSKmImFLwB8uq402ATNxfirhZZSUUqMxFQrTMb+vLwB3KKUuC7/mIUzJ7s/UVytMDL92X8xGJT8Dx2AmYg8HHm1BnycBq8OvexLzu3xM1POPYzZDOReTUHEjmy7P9D4mU3WXFpyvVSQol3pVWF/bLERjFvTM6nKOzaam0/CCzwqLyke7F0fdb6x0FdpX+WqsYuCTqZXVe1rVYFFhzo+YjLEb2bxLLaNtiVkv43HgF38g+L4/ELzCHwjumkyjLqej1uV0vOlyOsa6nI4dgYGY0sS5dLzdxlKynlxYN2BdY09orf/SWldprd/UWo8FngBujXp+EWZQcyKm/OUzYD5mIL/J+idKqT0xQbH7tdYtLbVf3chGCr9iBn/RYs/XC5PBGft45H68tdp6Af/BZOVF3/pjBnPNiV2rZz3m5xxxEWbS4xrgq/As8gmNtLMu5nUiPgnKiXRYDxybnbvFfzFrr1qhKmvW/OgJk6ZKVyGx7zwrKyqssA+mnPVkqxq0F5d+gpmUiV2rsyOyYybOvcD3IZ/3o5DPe0XI521yCYl4bG7PFza3Z6LN7dmdhmvcba7j2lQG5RqtVlBKDcUsb3GlBef4BJORdgRwMuZ35g2lVEsy8XsBp2itnwpXIYzAjL/OiDnuZ6318eGqhFnhDLPrgGla6/HhDcMuxyxFcrlSqpvW+gfM2HFdVLVCZDf7W4D3w23O0lo/gQn4HR29jm8T3gmf8w2t9WWYgGdstcJN4SqIuVrrR7TWscsNfImZXE5ZtYIE5VJswdVDa5FBoUi9ZTbFkT2zuj6MGXhY7ZWY+00F5dpjply0fwDzplZWN5kanqhwOetVwGGY4IGoF8lQuhFY6A8El/oDwfv8geDh/kAwqeCDy+n4yuV03OFyOoZiBhEnYGbIUlX22ZZS+Z3yO41nwTbmY8AZXa6qtX4EM5u4K2YdtYuAHYjpczgjbCZm5jORXUWzGlmfJJdN18CJLeFYgQmixW4m0Tv833ibMv0O3I/JFIy9/Td+t5umtV6ptS7RWudhLuA/BJ6KLQnB/H+RzaMS8xGJra8lhBXG5/bLdmHWWbVKRcx9q4JymZIpF60n8GSorOTJUFmJJeNEe3HpGntx6bmY9YQ3p89RN2aMFQj5vItCPu/NIZ93z5DP26pyapvbU21ze+60uT0HYIIx52J+NztiiXBj/iSqHDMFNqlWCGfmTwb+q7X+OdkTaK29Wusp4eUyXsQkDyzHrGcbz69a642bSGitlwIL2DRYNTPmfj5mTNhYtUJPmslAU0r1wFwrPB+pVAj/TOZhxnXx1gZvSbXCzeHy176NNaC13oCZYE1ZtYIE5dqGlK+JVKoBRmzX2/F/mF0qU6E88o9Lyhe5aToTrz1nykV0Ae6aWlntm1pZ3dLgRFxFhTlvYMpZ51rVZgfUF7OQ6kzMZhHT/YHgef5AsE8yjbqcjj9dTsdzLqcjspjxvsDNpHZglSprMBloqfIVJjjdEvsCP8QuRqy1Xqu1/lxr/QtmcwMbZt0bAJRS22LKsL4FTtRaJxo0GRXVVhamnHZ+cy8In2MBZnOIaMdhZvsj2Yfrw+3GBoVnA/8EFoSzBaNv1Qn2v7l+foYp+7Bhsj0J98eG+ftY3MRLRSP6f7l4De3z71y0X0/n9suuxFxEW2ljUG5DyZFOzEYzTWnvQbmIk4FPQ2Ule1vVoL241IeZNJpjVZvtyE7AZZjvy+9DPu/dIZ/33yGft1W/Aza351eb2/Ogze05HLN0RWSNu9WW9TjzVNrcnlRmCDZWrTAaMyn3WHijrWzMtYo9fL9zbCOJCFcfzKJlSR2NJRe0pFph2yYeb0m1wlaYbL77aFipsA5TAZFstcLxmMrGO4GlSqlPlVKNrdeZ0mqFTP4g7kgkKCdSJQQcn5/n2Bezc18q/ETDxbKbypKD9rfRQ3NGAbtPraw+/vwhBc1e8LdUUWHOT/5A8BDMovFXIhMjzemBSa0/AsAfCH6KWStxBjC/qDCnVYvZupyOOszaEO8DVyxcVtMXk34/ArNzbqaXBy5wOR2pLMd9D7hGKZUT3vgApVQ/zLodTwNLMOsYjcJkH27cjUop1RPze/0O5qJwKKZEYrTW+vfwMd0xF5dbYbLodo3avHSd1vqTOP37G7gxHIz7EVOi3AVTqhPPtZi1Tx4FnsXMzE4EHgyXTQAsCv+3VCn1FrAqvNbddZgLmZlKqUcwM9l9MAHBaVrruS04f6OUUvMw69V9gcnwG41ZUyb6c2cnzM/9vdaeZzP2AWZCRIhU+7LnNj3+gynti12TKBkrMFmfEc1lyUHHCcqBmSR6N1RWcgNwk33c5KQzX+3FpctDPu8hmEXzb8Bc2G9u8jHfwRcBv4V83lcx30Ov24tLE96F0+b2rMJ8rz5bV1XRDbMO6yhMskBS6wdnmFSWroLJ4ozNxtoJ8/+rsSy5PzBlnE9acO6WjKtjqw0ij30Zp62foo6N1pJqhZXh9q4jarObKD8289q4tNbLgTPCk597hc8zXSnVV2sdXV2T0moFuSBsGx9gIrpCWK00P8+hMQtnpsr08tHu6A/Xo5o5NtHy1UzMlItWgClntSzgGS5nvQazNoSUs7bcbsBVmM/Tn/yB4KP+QPBofyDoiPO6Zrmcju9dTsd9LqfjcMxmESMx684k9SWfQqleDmEuZtBxWNRjKzE/j6swA6IHMIv9DtdaT406LgTsjllr7hXMgsXHaq2nRR3TG1OiuSUmwFoZdXuZ+NYApwFjMLthbQUcrrWOLV/dhNb6dUwg0Q28ilko+A7MRUnEu5gd50oxkxH3h1+7GLNY+Jrw+68ArsfMnCa7sUglZj2WFzFZBr0wu7z+EHXMYZiNJeIFLcWm3o9/iBBJqwGO7pbV5QHM2MFKr2fNmh+dnRNvx+eOFJQD08cbMDu0Nlpelih7cWmdvbj0Fswadl9b0WY7tg3mO6gcWBHyeV8M+bwnh3zeVo3RbW7PWpvbM8Pm9pyNCTAdRHiNO4v6m06pDso1Vq1wD2aSM/rmx2TOD8VsdtVq4clSD6aaIJ5cpdQ+Ua/ti8mwi5e88ANmHNlYtcIq6jPaY7PY0Fr/hRn77tRIpUKV1tqS8brWuk5r/QFmbNcDM84FQCmVE34sZdUKKoU754oogyfOeZ/4u7sJkQhvfp7jYUzmRFKBiTg85aPdrwFcUr5oe5q/AB1/18iBZS1teGpldXv6uygHzjx/SMEfVjXoDwS3BZ7CfKmK1lmPycyaAcwoKsz5Ns7xLbZwWc3u1GfR7Qm0ag0WixW7nI6WBK9aTSnlBXbQWg9P5XkSpZS6DrhIa92RZt1bRClVCczUWie1ft3maMmgAduSuUF20XEcm9svuxBzQWe1U7NmzX8SYEPJkV0wa6M2tfMqQLdOk6c3umFPrFBZyb9oX2tfrwTOt4+b/JxVDYZ83i0wk9tnWtVmB1ELvIWZMCu3F5cmvZ5ZXVXFYEwG3Sggdt3UTLceyLa5PbGbTVlGKTUME3DLjVQrNHHcNOCfWmt3zOMeYAvMRN7Z1AfBPtJaL1VKRSZEn8Rcz/XCVFrtDuyrta6Kc87hmCDa1ZjKhRswpafbR3a8V0pp4GKt9T0xrx+Nmei8AxNIPBC4HLhCa31L+JjTgMcwf4tfACu01tVKqf0wy4g8j5nArMEs6TEcuFJrvVgpdQamqsOhtV6tlCrATGYeobWe0djPLvzz8GM2n1uMyXAeD+wM9I9sLBb+uc4EcmKy5ywjmXJtR0pYhZVe3S4361bMB2sqA3I1mC/kiOZKV6H9b/TQnJGY3Vn/ZVWDRYU5P2FS/G9g893FKlldMD/Du4Bv/IHgIn8geLs/EDzIHwgmlQHgcjo+cTkdE11Ox78w62GcBfgwfxfp0hYXT7cBB4U3YxBpppT6F2Z9uXviHSs21f/LxT9hFnIWIlXuzO2XvQpTIm81jblojNiP5gNykNjmJu0hUy5aNvBsqKzk0VBZSbyfQ4vYi0v/sheXnoXJ2oldf2pz1hlT1TEVWB7yeeeFfN7xIZ+3f2sbtLk9C2xuz1U2t2cQpizzckyWVXvIEvo4lQG5sLlsWq2QiCmYzRTODt9/IXyLTP6vA4I0rHxYCRzYXEAuylLMurfXYcqVVwFFkYBcc7TWDwIlmIDsDMwahOMjAbmw54FpwCRMyf514dfOAw7ArF34BKba4VJgGZuuU5eItZgsvVJgOiYguAYYFgnIhR0GvJ2qgBxIplybGTxxzuFsuhOJEK3xiWOLLsO2dHStwJRhpdLz5aPdx0fuXFK+6B1g/2aOP+6ukQNjd9Zp0tTK6mU0vWlEpqoFLjt/SEGLMwJbwh8IHozJmusd71jRYisxFzMzgIqiwhxLvkwXLqvpgpnhG4GZpdveinZb4HuX09Ev/mHJU0qdAPyktX67Lc7XEptrplx4hraz1np6uvvSXi0ZNOAmzMWfEFabt02fnqfZO9k+wpQBWu2jrFnzN+5suKHkyNswa2k2qdPk6S3O6g6VlRxI+92A6hvgJPu4yR/FPbKFQj5vX8xF/wFWtdlBfYbJoHvZXly6MNnG6qoq+mCWxxmFGV9lYrD4dpvbMyHVJ8ngaoVpNJKd19EppeyYYORlWmsr1u5rlGTKtZ15JDZzJURjlivFkVs6uj5A6gNyYNaFAuCS8kU5mLU3mtORM+UiOgN3TK2sLp9aWb2VVY0WFebMxqyb9la8Y0WLZWN2VXoC+MUfCM7zB4KX+QPBJrdebwmX07He5XS84XI6Sl1Oxw6YNPcJwNsktpZPotpskX+t9bOZFJAD0Fpft7kF5AC01hUSkEtaRfxDhEjYL5262E+2d7I9S2oCcrDp7268TR4SvdawJ3h8JtkBeC9UVnJ5qKzEkmtae3Hp95isoqtI7fd5e7crJjP005DP+23I57095PPuG/J5W/X/web2LLe5Pffa3J5DMJPTZ2CWjUl1ZloiUr2eXIRUK2SWYzG/h8+m8iQSlGsjC64eugrZNU0kZzUwos//s3fm4U1VWx9+d1PmVsqQUrAIVkVuUFGpenGuAwFR0Iiz1xnl82qCXL2OdcLZa6QoWhWnq9fZYlGGggMqWkCrorZiVayzUkQQcADC/v7YKR5KS5P2JCfDep8nDz3NPuuslDZZZ+31W6tXdgCzkxRr1rP5lJujaDl4i3j6amllnSK20ttYMwojZ/27XQa9HvePmGmO1yJyVrtxAfsBNwMfVtTU11XU1E+pqKkfUVFT36YpeYP7Zi8Z3Df7P4P7Zh+MKa0/CVP1aHeZ+xyb7QlCulCJyNIEewkBJ3TvnX0pZmJfrNiUlNvgH9UXGNTC+mgTSYlYkRQN7YCbgFdCQb8tyovwEIgbMVLhpXbYTHEKMH245gPfh8pK7guVlXhDZSWtmmqbUThiRUbhiEczCkccjYmpxmBiqmg3/u1EE6f7+PCQp7MxbVME51HA2VrrmCbpRb4aR4ZMfG0CprmhIERLCDg6Py+7D+FpgHFgbvnYwmENB+PLl5RjElFbY9Ck0QNrIjFeWlm3Dc5+wNrFeuAK4I5xQ/vb9oZaUVN/CCYIaTwaXbCftZgGsi8BM7wety1N4Rd/s9qFGWQyEiN13aUN5jTQZ3Df7DY3WhaEdGTpoAHPsOXkN0FoLZfm9sv5DtMwPVb8DOQ2TF7d4B91Li3HgGszJ0+PuNdaKOhPpfY6vwBjXRMmP2+XwVBZSTamn+dpdtlMI1ZhfremAbNcvsDathjb+O6sdpgqxmMwUtd4xsdLMgpH/C2O1xPSDKmUiy/lTjsgJC0T8vOy1wFT4nhNq3S1M6aCqyWiSbIlo3S1KdphSs3LSyvruttl1Otxv4qRs75il02hWbpgEs73A99W1NRXVdTUX19RU793RU19qyeuDu6bHRrcN3v+4L7Zlw/um70r0B+4AJiNabYbDYslIScIbUIkrIJdTMvtl9PQJD2WzGlIyIVpSboK6VcpZ6Ub8Fwo6J8aCvq72GHQ5QusdvkCpwMnkxobyfGkK+bn9iywPFRWUh4qKzkjVFbSKql3RuGI9RmFI+ZkFI74P2BbjPrhP8AXtnncPG/G4RpCGiNJuThSVVz0BVDttB9C0nF3fl72K5gPtXgFTxozhaYBL9ApgvMilq9iPqxTiaOwX876EzAM07dD5KzxQQF7Ysa9LwS+r6ipf6iipt5XUVPfpklvg/tmfzW4b/aUwX2zR2D6Dx0NTAUiqcyThIIgtI3ZJMeEPyGx+axz1w4XAM8DnWN8Lat0tR1waATnpHNSroGzgfdCQf8Quwy6fIEnMRul0oqodXTEbH4+DPwUKit5NVRWcmGorKRVkuOMwhEbMwpHvJ1ROOKSjMIRO/JXj7s2D51ohoqWlwhC65GkXPx5oeUlgrCJmb3dXW7ClH/Hs7Ksqnxs4beW49ERnLMR0/cuUlKlUs7KdsAbpZV1F4d75rUZr8e90etxX48Jxn+ww6YQFXnAmZgbsJ8raurnVNTU+ytq6gvaYnRw3+y1g/tmlw/umz0WM4F4CCagfIemEwez23I9QUh3CqprfyB2N2xCevAbcGxWTqfJQKybsGs2TwTsT2R9eCUpZxgAVIaC/n+Hgn5b4jGXL1CHmQx6LTK8ry24MDLUycDXobKSRaGykstDZSUDW2swo3DERxmFI67PKByxO5v3uLNjQ/tPJCknxBhJysUfkbAKkbI4q3O7012ujBeAfnG+tlW66sL0w2qJ1ZNGD4ymCiHVKuUaaJCzTrdZzjoPs0s71y6bQtS0x8i4S4AvKmrqaypq6m+rqKk/qKKmvtU3NoP7ZuvBfbPfG9w3+/rBfbP3BvpgdvqnYRLdq4C3bfBfENIdqTgV2sK43H45w4Bj43CtqqyZi5ZZjiORrkL0yaJUTcqBicduBeaGgv4+dhh0+QIhly9wHXAgUGeHzTRHAXthhnV8Eior+SRUVnJTqKyksLUGMwpHfJlROCKYUTjiAEw8dR5mY3NdK03OyygcEU3RgSBEjSTl4s+7RCZVEtKb74Ejc7bpWEpsp3o1h7Wi8wCM1K4lopGuQmpWylk5EvigtLJuqF0GvR73MmA4Rlopu7TO8zfgEmAesKyipv7Jipr6Uypq6tuUjB3cN/vHwX2zHxrcN9uH+ds7aHDf7JhOfRKENGFmy0sEoUnuy+2XUwfcEqfrNU4gR5qUk0q5LTkU+DAU9Eei+ogIly/wNmaj9Em7bAoADAQuB94JlZV8HSormRwqKykKlZW4WmMso3DETxmFI+7PKBzqYeAJAAAgAElEQVQxAjPJtaHHXTRJtuktLxGEtiHTVx1gyMTX7gXGOe2HkLCsBQ7Mz8s+HrjUget/Xj62cKeGg/HlS+4Exkdw3seTRg/cNdKLlFbWjSX2TZITgQ3AlcDtNk9nPQgTDMrI9MQjBFRiprm+5PW4pZeoICQASwcNcAH1mIbwghAp73TLyxrTrkPmAuL3mbtv1sxFlQAb/KPygW8iPG9p5uTpO0R6kVDQfybwUCv8S1buAya4Jkz+zS6DobKSf2AGsUUiLxZax3LgRYyCYK7LF/ijLcY2vjurI0b5cAym193Wig+2yygcEenfnyC0CqmUcwaRsArNsRE4OT8ve0+cScjBlr+fke4sSqVc02Ri5BMvlVbWtWriVFN4Pe7XMbu0c+yyKdiGC9P/5xbg44qa+i8raurvrqipH15RU9/BYd8EIW0pqK4NAWVO+yEkFT9nuNSJ7TpkPkb8EnIrMIOGGoi0Sg6kUq4lzgPeDQX9u9tl0OULPIaJxxbYZVPYgp6Y/r7TgfpQWcmzobKSk0NlJa26l8goHPFHRuGIFzMKR5wF9ML0uLuLLZPfH0hCTogHkpRzhleB1U47ISQkF+fnZa8F7nXQB2s/ucHA9hGeF+2o+HRJyjVwBEbOup9dBi1y1qsQOWsi0x/4J0aO9HNFTf0LFTX151TU1EuVoyDEn/857YCQNGwETumZ3/X/MD3E4sWcrJmLrA3qJSlnL38DFoaC/gk2DoFYimn3cgP2DBcQmicLGIN5L68PlZXMCpWVnBsqK+nVGmMZhSNCGYUj5mUUjvBnFI7YDkuPO6SQRogTkpRzgKrionXIJD1hS+7Nz8ueDTyHc0FSPZs3lD86inOjrZRL1UEPWyMfmFdaWXepjdNZtdfjvhE4BOlXmQx0wVSfPgB8V1FT/25FTf21FTX1hRU19bb8TgiCsFXmAd+2tEgQgIm5/XI6AxfH+bqb+slt8I9qBxwWxbmSlIuM9sAdwOxQ0J9nh0GXL7DB5QsUAwcDX9thU2iR9pjN6fuA70NlJfNDZSUTQmUlkRYUbEFG4Yh3MwpHXJlROMKDSbIKQsyRpJxzTHPaASGhmJ3n7nI9MAPIcdCPF8vHFlp3+KJpiiuVcpGRiZE1ziitrOtpl1Gvx/0GRj4hY9uTBwUMAa4B3gG+r6ipf7Cipv6Yipr6LGddE4TUpKC6ViPN2YWWme3u2/UJ4JE4X1ez+cb9fkTXq0ySctExDDME4ki7DLp8gTeBwcAzdtkUIiID8/dyB7A0VFbyQais5JpQWclurTZYOEKGbAlxQZJyzlFOdJNfhNTlo86d2v0j05UxjcilorHCKl3dDtgjinOlUi46RgDvl1bW7W+XQa/HXR+2ewUiZ01G8oCzMD2vllfU1Acd9kcQUhWRsApb46sOnduNVRnqOeK/gfhe1sxFyyzH0UhXQZJyrcENvBgK+u8OBf0d7TDo8gVWunyBEzCf6XK/5wyDgWuBxaGyks9DZSW3h8pK9g2VlYgqQUg4JCnnEFXFRb8Bzzvth+A4PwJHdu/acQrwd4d9WQvMtRxHI10FGfTQGvKB10or6y63Wc56M6Zp7Xd22BQcoQPws9NOCEIqUlBduxj42Gk/hITkT2BMV3eXm4GIJ8rbyKxGx9Em5aLdkJOk3F/8EzMEwrb/d5cv8DBmg/sdu2wKrWIHjAz9LYzMtTRUVuINlZW0c9gvQQAkKec0/3XaAcFRfgOOys/LPg843mlngDnlYwutI8ajka6CyFdbSyamoexMm+Wsb2LkrNK/MnmZ7rQDgpDCSLWc0BTjc/vl7AWc6tD1rf3k8ok+MSiVcm1jELAoFPT77TLo8gU+x8gqb0GGQCQCeZgpvLOBZaGyksdDZSXHhspKujjsl5DGSFLOWV5DGoGmKxuBU/PzsnfBSA0TAat0tRvRTxoT+WrbGI6ZznqAXQa9HvdyzNTXy4k+UBec5Uuvx/2R004IQgrzBKZ/lyA08N/cfjlVwCSHrv8LsNByPLwVNiQp13Y6AiWhoH9mKOjPtcOgyxdY7/IFLgcORQbNJBI5wCmYIXv1obKS8lBZyemhshIn+3sLaYgk5RykqrhIIzu16cql+XnZK4H7nXYkTAh4yXJ8JNEHalIp13a2xchZr7BZznoLZhqYBILJg1TJCUIMKaiu/RqY77QfQsLwYVd3lyswN+ftHfJhTtbMRVb5abTSVYg+KedqxTXShRGYIRCt+X9oEpcvMA/T66zMLpuCbXQCRmGGu+ztrCtCuiFJOed51GkHhLhzf35e9ouYnoKJ0svgzfKxhSssx9FKV0Eq5ezCBdwIzCqtrHPbZdTrcb+FkbPOtMumEFOedtoBQUgDZGNUAFilFGM6dG73ILCdg35YpavtgMNaYUMq5eylFzAjFPRPCgX9Heww6PIFVrh8gWOBsZhWNkJi8TPwqtNOCOmFJOUcpqq46FNM00khPZjTq2fnqzGJkW5OO2PBKl3tCHhbYSPipFxpZV0m0LkV10gnvBg5a7Qy4uYNetw/Y6ogL0XkrIlMndfjrnTaCUFIA54F1jnthOA4Z7i3yzmV1sU+dqHZvAfsvrROUSBJOftRQADTa26QXUZdvsBUYE/gPbtsCrbwgssXkBhZiCuSlEsMHnDaASEuVHfqmHlKu0zX80CB08404gXL14cBWa2wEY18VaSrkdEHeLW0su6q0so6W96vw3LW24CDEDlrovKM0w4IQjpQUF27ApjhtB+Co9ye2y/nT6DYYT/ez5q56CfLcWslk5KUix27Ae+Egv7z7TLo8gU+BYYCtyM9LhOFZ512QEg/JCmXGDxL9P24hOTiJ2Bkj5xOkzETmBKJxeVjC7+yHB/dSjvRyFclKRc5LmAiMLu0ss6WhsMAXo/7bYycVW5IE48nnXZAENKIUqcdEBzj9Z7529wLPI6phnKSWY2OJSmXmHQCpoSC/umhoL+nHQZdvsA6ly/wb2AY8L0dNqPh0VcXknns+C0e91VsXci1au3vnH33E/Q87XK6/+My/jHpMX5evXazNXMXf8opwUfZYdx1ZB47nuuebvxrDqt//4MT//MI3f9xGftedie13y/b7Plf1vxG7zOvouqLb9r+YltmBfBKPC4kCFYkKZcAVBUX/YbchKUyvwOj8vOyzwZOctqZJrBKVzOAo1ppRyrlYsvhGDnrwXYZDMtZj8JhOeucaU8xfFDuFo8ZTz/S4rnz577EhccPY9Se23Hcvjtz5bkn8Mdva5tc+/YrMxk+KJcLjz98s+//tnYNN044B98+OzD+pBF8W/fFZs+vXrWSEw7w8Fn14la/xihY4vW4P4jHhQRBAGAu8JnTTghx54d2HVz/yHBlPAN0d9oZNu8nty2mKqs1SFIuPhyFGQJxeIsrI8TlC7yMGQLhyKCnudf+k/k3j9/0OObvW/8VPCn4KK9Xf879/3ciD11wMu9+/jW+Wx/cbE3F+5/w0Vc/cMiuA+jcoen5KTc9N5fPfljGkxNOZ/vc7px19xObPX/907MZWehhyA592/YCI0Okq4IjyBtx4jAVGOe0E4LtaOC0/LzsgTgvjWgOq3R1KNCaaqz1k0YP/D2K9TLkoXX0Bl4uray7Drhx3ND+G9tq0Otxa+C2ipr6+cBTQFyinqa49aEy2nfsuOm4d36/ra6f9dzj3HPj5Rx31j855+JrWPPrShYvnE8oFNpi7bo//+D+266mW48tZ2c8dd+dfFf3BVfc8QBzX3iaO668kDv/99c8jMfvuZ19DjqcnQYNbsOri5in4nERQRAMBdW1eumgAfcAdzrtixA3NgDHd8vLvgoodNoZ4BdggeV4eBtsbfkBuHXkXrD19AYqQkH/ncDlrgmT29yf0uULLAdGh8pKxgFBTGVeXNhrx+3I6hTZLIvKT79kzgdLePX6Czlw0A4A9OnelX0vu5OXF3/KYYN3BuC200bxnzOMAGf6Ox83aevVj2q5/NhhePf4G7tvn8+2Zxez9o8/6dKxA598+yOPv/EuH026zIZXGBEiXRUcQSrlEoSq4qIqYJHTfgi2c3l+XnY9ids38KvysYXWqpzWSldXR7leKuVajwu4HqiIkZz1JbtsRsuAXXbnb4MLNz1ymkigNbDql5+5/9Zizr/iJk678DIG770f+x02kvOvvJku2Vv+ej370BR65PZmyP6HbPHc+wve4MTzLqJw/0MYd9lEPvng3U3Vdl9/Ucsr05/ljMAV9r3QrSNJOUGIP48gUxDTiUtz++XsAJzrtCNh5mTNXGRNprVWugpSKRdvFDABWBAK+gfaZdTlC5QCQ4C4lOhHy+z3PqFXTvamhBzA3jv1Y/vcHsx+/5NN38vIaDnVsG79Bjq2bwdA5w7m33UbzJ/Dvx5+gUuOPoS8bnG5bViGSFcFh5CkXGJxh9MOCLYyNT8vexpQBjRds+085Y2OR7fSTrQ9EaVSru0chpGzFtll0OtxrwBGAZeQ4NNZ35htfnUPG31Ci2uXff8tzz10N+Muv7HJ59evX0eHDqZCr0OnzuHvrQfgvluLOf7sC+ju7mWH2y3xvtfj/jQeFxIE4S8KqmtXAk+0uFBIBZ7L7ZfzMnCv045YsEpXMzGf760l2s9uVxuuJfzFHkBVKOg/zy6DLl/gE2AfYBJxGAIx4J8T6XDcBDwX3sj9c7beT+7T75ax87Zb7gsPzO/Fp98ta+KM5tlzh748+HIlP69ey+QZb1DQqwfdsjozo6qaz3+oJ3DkwVHZawMPu3yB9fG6mCBYkaRcYvE88KXTTgi28Eqvnp2vxDTRT4ReJc1h7SfnAXZqpZ1ohjyAVMrZRYOc9Rqbp7P+BzgQ+NoOm5Fy5oi9OWK33pw9cigznnl0q2s//fA98rffkYqy/3HqIYMZObgPgROHU/P+lgXH999+DQcMH81Onqb7o+zkGcys5x7n15UreOGx++ndtx/ZXXNY+Ppcvv96KUefZluM3RIPx+tCgiBswd1OOyDEnE+zunUcj4m34yYLbAENzLYc70vbNi6lUs45OgOloaB/Wijo72GHQZcv8KfLF7gIUz35ox02G5PXbRuuO+kIHvGfyguXn8PeO/Xj/PueZdKL85o955e1v5HTecs/oW5ZnfhlbXRFx8XHe6n55kd6nXElt097hbvPPY71G0L8+5Fybjt9NB3axeVXVAP3xeNCgtAUkpRLIKqKi0KY3RAhufmkQ3vXSe0yXc8BOzrtzFZYAbxpOW6tdBWir5STpJx9ZADXAnNKK+tsK+fyetyVmJ3fF+2y2Rzd3bmcduFlXHLzFK6b8jgDd9uTu667hLJHmx+KuGL5Mr798nOevO9OzppQzHV3P07HTp256rwT+WX5X7u0ixfO5723XuMM/+XN2jrl/Iv56vMlHL/fQJ598C4uKL6NDevX88Dt13DOxdfSvn1kPVbayB+YCYCCIDhAQXXtYuA1p/0QYsZa4NjO23ScQmLFZu9nzVz0k+W4LdJVkKRcInA0sDgU9G/ZL6OVuHyBCszwjxl22WzAu8ffuHLMMIbtPpARe3p4xH8qx+27Ozc9N4eNG5tvXazUlgOLtQYV5SDj/rk9qJ58OTV3XcH3D01k2O4DuXvmG/Tp0ZWj99mNN2u+YI+LbiXvzCv5533PsG59TIQcc1y+gBTGCI4hSbnE40FMw1chOVkGjHR373wncIDTzrTAjPKxhdZPttZKVyH6SjmRr9rPoRg5q21BoNfjXuH1uEcBFwMxK+kv3P8QTh43gSH7FbHXAYdyyc1TOHD4aJ68785mA0KtN/L7b2u56PpJHHLkGAoPOISr73qUDJeL6U88BEBowwbuvflKTjrvoq3KT/O23Y6pL73N1BmVPPlGNUP2K6L8f1Ppmdub/Q4bycdVCxh3zEGcsP/fuOv6S1i/rs29nJviOa/HLe/9guAsMuwhdTk3t1/OkbQt1okFsxodS1IuNdgWmBsK+m8NBf3t7DDo8gXqXb7AkcCFmI28mHHs0N1ZseY36pataPL5bl06s3LtlvPdVq79nZwu0RehZrpcDOiTS+cO7Vn+6xpuKXuZ4JnH8Of6DZx0x6NcMWYYS+6+kve+/JYH5lZGbT8Cmt8FFoQ4IEm5BKOquGgt8saQrPwBjM7Pyz4NOMVpZyLAKl3tA+zVBltSKZcY5AFzSyvrrrVLzgrg9bjvwCSZv7LLZkvsP+woVq/6hZ++a1pBm921GwC77b3vpu91ycpmR89ufP2Facs267nHWLN6FYeNPoE1v65iza+r2LB+PRtDoU1fN+DKzCS//w507NSZVb/8zNMPlHDeZRNZt+5PbpxwDiefN4EHZy7g85qPmPXsY7F4yYk6DEYQ0omXgM+cdkKwnXty++V8DzTdWNRZrP3k+gBtHfMtSbnEIQP4N/B2KOhvbXuYLXD5AndjYvamx5naSFPVcAA7b5vbZO+4T7/7qclec9FQ/MQMxgwdzK79+rDku59YHwpx3H57kNOlM6ceuBfzPrb9Lfo74qAKEYStIUm5xGQyEJNSDCFmaOD0/LzsHTBSwkTnD6DCcjwaoqw33xyplEscMoBrMMm5PLuMej3uhRg563S7bEZCcwFh34KdUEqhdaPexxpUeNrXt19+wfIfv+ekg3ZhzNCdGDN0J+bNLOOLJR8zZuhOvD77hSYswyMlN3GA9yi2H+Dh26WfEdqwgQOHjyZrm64cetRxLF4039bXCCzxetxv2G1UEIToKKiu1UgbkVRjYffe2bdhJlsn2lCDX4AFluO2VsmBJOUSkULg/VDQf7ZdBl2+wMeYxNxddtm0UrZgMT236UI/d7cmnx++59/4ceWvzP9k6abvvfv51yz96WeG7/G3Vl/3w7rvKVvwIdeddMSm763bsIFQyKgm1v75ZywmXkx1+QKhlpcJQuyQpFwCUlVc9CPwP6f9EKLiqvy87O8x8uNk4OXysYVrLcdt6ScHMughETkEI2c91C6DXo/7F6/HPRqYQAzlrABvzX2Jrt16kNunb5PP73PQMLTWLF7014Swtat/5bOaxRTsPAiAUSefxa0PT9vsMWS/IrbtvwO3PjyNPYcetIXdpZ9W89bcGZx24WWbvrdh/TpCIROv/fH7WrT9IeFUuw0KgtBqHkXaiKQKyzNc6sTM9q7/AXEZoR0lc7NmLrImA+xIykWbXJCkXHzoAkwNBf3PhoL+pjNdUeLyBf5w+QJ+4EigvrV2jrvtIW6b9jKz3qvhpXerOb3kcZ55632uOs5LRniTc+d/3sDYKU9uOmfoztszbPeBnDn5f0xbsJjyhR9yWslj7Pe3Ag4bvPOmdV8tW8HzlR/wfOUHrNuwgU+++YnnKz9g1ns1Tfpy0UNlXDHmcHpuk2WuG5a0XvrYdGZUVXPv7PkcNGiH1r7UpgghSgUhAZA34sTlP8AZtK16SYgPj+TnZT+D2e2MS0d4G7BKV7cBDm6jvWjlq1IpFx96YQZA3AhcO25o/+Y79kaB1+O+s6Km/i3gaaB/W+1NDJzJzrvuwfY7D2JjKMTrs1/g9Vkv8H9X3LQpIDxz+N7sute+TJhoilgG7LI7Qw8Zzp3F4znroqvYplsPnnvobjIz23HUSWcB0KdfAX36FWx2rbkvPMWvK1cweO/9mvSl9OarOOm8i+jazQxOy99+Rzp07MSDd1zH4H0O4MUnH+bYM89v60u2sg6TBBAEIQEoqK5du3TQgLuAq532RWgTG4GTe+Z3DQBNv+E7j1W6mgkcZoNNqZRLbMYA+4SC/n+4Jkx+3Q6DLl9gRqisZFfgEWB4tOcP2DaXR15dyDfLV6IBT34vHrnwFE49+K+uNhtCIUKNevw+MeE0/vXwC5wz5Uk2as3IIYOYdLZvszXzPv6Msy3JvOcqP+C5yg/o5+7GF6XXbLZ22oLF/PjLr5w//K+W3B3bt+Px8adx4QPP8vArCzh26O6cN8zWP+cZLl/gOzsNCkJrUFtIf4SEYcjE12Ziz66ZEDtey+3R+cT27VxvAgOcdiZCNgK9y8cWLgMYX77kRODJrZ/SIhdMGj1wSqSLSyvrqoA923hNITrmASePG9r/B7sMVtTU5wAP08ZKy4cn3cj8uS+x/Mfv0Vqz3Q4DOPof53LYqOM3rTnt8CHstte+XHzTX0qN39euYeod1/HG7On8+cfvePbYi/Muncj2AzzNXus/V1zIV58v4a5n5m7x3Py5L/FIyU2UTnudzHZ/9WVevHA+d99wKSvqf2L/YUdxwVW30q59+7a8ZCvPeD3uE+wyJghC21k6aEAO8CWQ47QvQqu5OrdfzhLgGacdaQYN9MmauehHgA3+UQcCdiRpijMnT78h0sWhoP9NYH8britEx0bgFuAa14TJtowTDZWVKCAQtpssRQJOc4TLF2g8bEUQ4o4k5RKYIRNfOwR4xWk/hGb5tEN714Hu7p2fAbbUwSUub5WPLdwUgI0vX/IU0NakwD8mjR74eKSLSyvrPgN2bOM1hehZBpw6bmj/LTNSbaCipn48cBtgy4SxNOMAr8dte5M6QRDaxtJBA64GrnPaD6FVzHRv1/VfSqlFQLbTzjTD+1kzF23anNzgH3UzcNlW1kfK5ZmTp98S6eJQ0P82MNSG6wqtYxFwsmvC5C/sMhgqKxkMPAE0v0MpgNl42dHlC9iiIhGEtiA95RKYquKiV4F3nPZDaJLlwBHu7p1vJ7kScrC5dLU99lRjyqCH5CAXmF1aWTextLLOtobXXo97EkYe9KVdNtOERZKQE4SEZRLSWy4ZqeuY1f5cpdTzJG5CDizS1TB2KWNEvppc7I0ZAnG6XQZdvsBizHCJe+2ymaI8IAk5IVGQpFzic5XTDghb8CdwdH5e9snAaU470wqsIyeLsGfoggx6SB4yMO8rr5RW1vW2y6jX434HI0meZpfNNCDotAOCIDRNQXXtr8AdTvshRMWfwLHb9Oh8O4lfJWTtJ9cHGGyTXUnKJR/ZwCOhoP/JUNBvy6a1yxf43eULnA+MxhQSCJuznuQZziekAZKUS3CqiovmAK867YewGWfm52X3Ba532pFWUFM+tvBzy3Fbp642EPGgh9LKug5Ir4tE4CDMdNZhdhn0etwrvR63D9PTZJ1ddlOUr4DnnHZCEIStUgL87LQTQsRcmNsvZz/gJKcdaYGVQKXlOOrm/FtBknLJy4nA4lDQb1uPP5cvMB3YDXjZLpspwjSXL7DMaScEoQFJyiUHlzvtgLCJa/Lzsr/CTDhKxsm4VumqAkbZZDeaSjmpkkscGuSsN9osZ52MyFlbosTrcYecdkIQhOYpqK5dA9zutB9CRDyc2y/nI5KjunFu1sxF1vd/O4e6SVIuuekHzAsF/deFgn5b4jKXL/ADMAy4BNkwbUCkvUJCIUm5JKCquGgRIglLBB7Lz8t+HCgneSu9rNLVvYA+NtmNuFIOScolGgq4Ani1tLLOrt8HvB73u8AewPN22UwhVgFTnXZCEISIuBszJEdIXD7omtvlGuBZkmPgkFW6mgkcbqNtScolPy7gauDNUNC/vS0GfQHt8gX+A/wd+NQOm0nMQpcvMK+1JyuljlNKTVdKfaeUWqOUqlJK2Vadq5TqrZSaqZRapZTSSqmDt7K2h1LqPqXUj0qp35VSS5RSjrdWUkpdq5Rabjk+OPxadrH5OsOUUuPttOkUkpRLHq4CpKrCOd7o2a3Tv4AZQE+nnWkl3wHvWo7tkq5CdJVyMuQhMTkQI2f12mXQ63Gv8nrcYwA/sjtrZarX417dFgMSFLaMBIWCHRRU167FTJcWEpOVSnFch07tHgbynXYmAjQw23I8FHvjomjvFSQpl7gMBT4IBf2n2GXQ5Qu8j+n/+4BdNpOQG9t4/gRgDXARRnH0GvCEUurCtjoW5kpMj8mTML8D7zW1SCm1DfAGsDtwIXAEcBfQ3iY/7OQ9zGuxbcpwmGFASsRfkpRLEqqKi2qAx5z2I035rH27jOM6dsh8GhjotDNtYHr52EJtOR5tk90/Jo0eGE3CRSrlEhc3MKu0su4mm+WsdwH7AkvtspnEbMD0qWorEhRGjwSFQmu5B/jRaSeELdDA6e7tcs4EDnXamQhZnDVz0Q+WYzulqyCVcqnGNsDjoaD/8VDQb0v87PIFfnP5AucCxwIr7LCZRHzg8gVebKONo7TWJ2utn9Fav6q1vhh4EhOX2cFAYKHWeqbWeoHWurnChyswyq2DtdbPaq1f01pP0VpHpcRQSrmUUjGN2bTWv4Zfy++xvE4yI0m55OIazGQpIX78DIzM7dHlFsyk0mTG2k9uJ+ybTBbt5FWplEtsFKaP5WullXXb2mXU63FXYXZn0324wRNej/sbG+xIUBglEhQKraWguvZ34Fan/RC24NbcfjkbSa7ey7MaHTudlLNtA06IKadgquaG2mXQ5QuUYYZAvGaXzSTgprYa0Fo3Nc32fUyf5q2ilNpeKfWCUupXpdRqpdSLSqkdLc9rzAbDMeHK/rqtmDsTeDDamEYp9YhS6l2l1NFKqWrgD2Cf8HPbKaWeUkqtUEr9ppSqUErtbDm3f9ivk5VSj4VfwzKl1DUtXHMLpUI47rtcKVWrlPpTKfWtUuoRy/MjlVJzw/Z/VUotUEoNszx/LfAvoF/Ytm50/v5KqdfDr+NnpdQDSqlsy/M5SqmpSqnvlVJ/KKW+Vko5VkEqSbkkoqq46GukMWU8WQcck5+XPQbzxpfMrGLzD12npKsglXLJwgEYOattU+HCctbjgAtIzw2GEG2XTQASFEpQKDhAKWZqspAYvNozf5upGBVJMg3esvaT642pMrYTqZRLXbYH3ggF/VfbOATiO+AwTGJ7vR02E5hPiF2f432Bmq0tUEp1AF4B/gaMBc7A/J++rpTqHl42FBPLvRb++phmbG2PifdWKtNqZJ1Sql4pFYxwg7M/pi3DzRiFw5dhH+YDOwPjgOOBLsDLSqlOjc6/HfgNGIORQl+jlPpnBNe1ch9wHfAMcCQmlt8GPngAACAASURBVOpieX574EXgH5iqzreBWUqp/cLPTwWewFSxDw0/JgKE17wSfm4MRs1wBPCwxX4Q2B+jOPFiNpmtirK4Im/EyceNwNlAdksLhTZzTn5edm9suol2mFnlYwutH7Z2JuWiGfIAkpRLJnoCM0sr624Drho3tH+0wX6TeD3uKRU19ZWYD+Id7LCZJDzt9bhrY2g/mqBwPSYo3IAJil5XSu2qtV6BCWzuAVZigpQmE6iNg0JMYL8Kc5N8mda6JVl7f0xQeD3wE5sHhT9jgsLfgMswQeGARsm/24GXMAHXgZigcLnWekoL17VyH3Ba2I/Xge5hew00BIX/ATZiqlpmKaUO1Fq/hQkKdwIO4a/guR42CwpfCNvsAdwCdLNcI4j5f7sIEzz2Db8WIcEoqK79Y+mgAROQ4TWJwHftO2aekeHKeAHIcdqZKFgFVFqObdv0siBJudQmE/OZfXgo6D/FNWHy12016PIFNgK3hMpKXsYkOXZqq80E5ebwa7UVpdShmJZAZ7Ww9ExgO2CA1npp+NyFmNYu5wE3a60XKKV+BVZorRdsxVZe+N/bgKcw7yWDMZWAG4B/t+BLD+AwrfUHltcxEZMU2z0cC6KUeguoC782a2xVrbU+L/x1hVIqF7hCKXWv1rrFn7FSaiAmnxHQWk+2PPV0wxda67st6zMwicpB4fPe0lp/q5T6AfiziZ/VLcDbWusTLDa+A15RSu2itf4Y2BuYorV+2nLe4y35HiukUi7JqCouWk5yjHtPdq7Pz8v+DHiU5NqBbQ6rdDUXM33JLkS+mtoo4FJgXmllnW1NtL0e93sYOeszdtlMcDYCN8TKuCUobCkh1RAUjtBaP621fh4TzLkxQSHh4GZTUKi1fr8ZW9ag8LuwnZuA/yOy19oDOF5r/bjWeq7W+ltMcqoLcGhYmvsScBQmmd844K3WWp+nta7QWl8JPIgJCiOKbSxB4cVa66vCPjyttT6uYY3W+m6t9WStdQUmwfZv4OXweYR93hQUhh8NPes2BYVhGfBjhHd8LdV6m4JCrfXr4Z/FuZH4L8SfguraMsz/v+Ac64Hjc3plXYP5DEkm5mbNXGRNmtktXQVJyqUL+wOLQ0H/CS2ujBCXL/AusAebVxOlCl9gEo62opTqH7ZbrrV+pIXlewPvNSTkYFMM8Rbm/zMaGuKcaq312HAbkzsxlW9+pVTnFs7/zpqQC3MYMBf4VSmVqZTKBFYDVUBho7XTGh2XAX2IfNhOQ0uoR5pboJTKV0o9Gk6mbcC89w8DBmzNcPi1DwWeaXgd4dcyP2xjSHjpB8AlSqnzlVJbtRkPJCmXnNyBuQkQYsMT+XnZjwDlQEeHfbGDdcBMy/Eo7P3bl0q59GA/jJz1CLsMej3uX70e9wnAP0l9OetTXo/7k1gYlqBwExIUCvHAT+rLvBKZS3L75TQk1JMNq3TVBRweg2tIUi59yAGeCgX9j4SC/iw7DLp8gbUuX+AsjHRxpR02E4TrXb5AtJOJt0q4sn8W8DVwagSn9MaoAhrzE6ZKPxoaBnQ07gf4KqbPb0sqlKb86AmcgPl8sz6KMFX8VpY1c9y7hes20ANY21y/4vDm6nSMkuDqsA97YX7eLd2bd8P0yryHzV/Hn0A7/notF2CKVq4GPlVKfaaUOjFC/21HknJJSFVx0Rrsa+YtbM78HjmdxgMziKA3U5LwWvnYwtWWYzulqyCVculED+Cl0sq6W0sr62wL5L0e9z2YBMbndtlMMEIYuYntSFDY5LEEhULMKKiu/QQzYViIP0/n9st5nZYrghOV2ZavhxIb6a0k5dKP04H3Q0H/XnYZdPkCz2LkkG/YZdNBPsFmWWJ44+0lzKT5kVrrtRGc9gNN31v2IvopuF9gii62cC38b0sS0qZ6p63AxDx7NfFo3C+u8etoOI60aOhnoItSqrlCjR0xVZsXaq0fDCsJ3gUa97ZripWY13cNTb+WhwC01iu11n6tdR7md30h8D+llF2DEKNCknJJSlVx0VOIhMJuvsjMzBjTqWPmE5gmnKmCVbraBdPA3U5k0EN6oTASvtdtlrO+j5EiPd3S2iTksVj0kpOgUIJCwTGuw/QAFOLHJ1ndO/0L09MvGVUMi7NmLvrechwL6SqYTaBokKRcarAj8HYo6L8iFPTbcn/v8gW+xmxGXUX0yd5E4ho7e8mFq96fxfTeG6G1brxB2BwLgSHhfrwNtrbFbPzNj8aHcM/euZh+tlYOxfTibc0m9yuYnm3VWut3Gz0+bbS28QAKHyb2+jbCa70a/ve0Zp5viLM2qWiUUv0wqh0r62j0eRCOhRcAOzfxOt7VWn/fyAZa6w+BSzC5sYERvgZbkaRccnM+qS/5ihe/ACPzena5ASOfShU0RobbwHDsD2ajla9KpVxqsC9GzjrSLoNej3u11+M+EdOT7A+77DrMeswgA1uRoBCQoFBwiILq2l8xA0iE+LAGOLZzdod7gQKnnWklsxodxyopF3HyJBT0K+ReMJXIxAynezUU9NuyaeryBTa6fIEbMe0tlra0PgH5AHjOZpv3YCZ5TgS6K6X+bnl02Mp5j2BUDbOUUscrpY7FVM8uxwydipbrgT2UUg8rpYYppS7GfC7dpLVuTX4giNnkfVWZ6fYHhf2copQ6qdHaQUqp+8LXvQHTTuDmSIY8AITjufuBO5RS1yulDlNKjVFKPRVesgQTy92hlBoZVhDMwfQvtrIE6KWUOkMpVRhu5wKmeGCMUuoxpdRopdQh4TXPNrQKUUrNV0r9SynlVUoNAyYDa4FFEf/EbETeiJOYquKiz4BbnfYjBVgP+PLzskcD5zjtjM0sKh9baK0asVu6ClIpl870AF4sray7zWY5aylG2vOZXTYd5F6vx/1lDOxKUChBoeAs/2XzSZpC7Dgnt1/OMZihL8mKtZ9cHrB7jK4TTUWTK0Y+CM5yEPBhKOg/1i6DLl9gIeZ39r922YwTxS5foKmq/LYwLPxvCeYzwPpotn1GOCY6DBMzPIgZJvgVcHDDtNNo0FovwrwnDsZMiQ9gkrI3R2srbG85ZhDgEuBOTLxzG6aY4sNGy/+NuZ97HjMkbCJwN9FxPqbq/FRM7/NJwO9hX/7EbLRuwCRVJ2Je1+uNbDyDiWtvA94Brg2fPx8zyd4NPIb5+fwb+Ia/WqdUAmeE7T+DaZ8yItxnOe4ore3+PRXiyZCJr3UEPqbl3j1C85yRn5e9BlN1kgqTVq1cUT628GaA8eVLMjE9l7rZfI1xk0YPjPhmvrSy7gPMB4iQWrwNnDhuaP9v7DJYUVOfjUmaJGuPrZXAjl6P+2e7DSul6oB+zTy9vda6bivnFmCSX4di3vPmARdprT+zrJkHLNdaj4nAFy8mWBqEeY+5H7hxa8kxpdQjwC5a68bDG1BK9cEElkdgei79gKniu1lrXR1Oen2JCeSODD/+wCQqr9XhwEYpdS1wgda6Z/j4YEz/u1211h+Hv+fCTBc+BzMgYhkwV2t9Zvj5vTD9q3bFJOhuBA62+q6U6gjcC4zEBICPaq3PCD+3Dybo3BdzA/wVJgl6ndZ6lVLqdkwFc3+M7Ox94Gqt9ZvN/8SFRGHpoAFDMAlU2eSOHZNz++VMBypI3iTSKqBnw+TVDf5RZxC7CZf7ZE6eHlFSPxT0dyR8EyykLA8CAdeEyZG0t4iIUFnJSZjPvERXvixw+QJDnXYilbDEX0dprV9y1pvUQpJyKcCQia952bx5rBA5N+bnZU/H3JRG0ico2fCUjy38BGB8+ZJDMNIwuzl50uiBT0a6uLSy7kvMDaiQeqwATh83tL+tH9QVNfXnYXbQkq2P0MVej/sOp51INSQoFBKJpYMG3A+MddqPFOXt7n2yT85s53oHk/BOVp7Pmrlo0wbHBv+opzHTLWPBkMzJ09+LZGF4YufqFhcKyU4tcLJrwuQquwyGykr6Y4YnNG7nkEgc4vIFGg+iEtqAxF+xQ3b2UoCq4qIKTJWXEB1Pbdsr6wFMU/FUTMjVNiTkwsRCugrR95QT+Wrq0h2YXlpZ9x+b5az3YUrqbR+WEEO+QCY0CkI6cAWmL61gL8tcmRknZ7ZzPUlyJ+Rgc+mqCzg8hteKRr4qQx7SgwFAZSjo/3e4j2CbcfkCdRiZ7LVEP1wkHjwnCTkhmZCkXOowHtntiobK7l07+pVSMzBTB1OR8kbHo2N0HekpJ1hRwL+AN0or67azy6jX414MDAGesMtmjLnM63E3NZlUEIQUoqC6djlwsdN+pBgh4KQe227zL0x/0WTHqmb5O/a3EbEiSTmhKdph+pDPDQX9feww6PIFQi5f4DpM7646O2zaxBrgIqedSEW01nVaayVVcvYjSbkUoaq46Hvgaqf9SBKWZroyfJ07tXsc0wMpVXmh4Yvx5Uv2AGxLkDQi4qRcaWVdZyQITBeGAu+XVtbZ1pjb63Gv8XrcpwDnktjTWd/yetx2T/sSwkhQKCQaBdW1DwEznPYjhSjO7ZeTC1zotCM28GHWzEXW4TCxmrragCTlhK1xKGYIhG3qGZcv8DZmCETErWxizESXL+BIs35BaC2SlEst7sKMfhaaZyUwMs/d5Vr+mp6TivwELLAcx0q6CtHJV6VKLr1okLPeUVpZ184uo16P+wFgH+BTu2zaiMZUCgqCkF6MxfTVFNrGdPd2XcuBqU47YhOzGh3HOikXjZRQknLpSQ9gWijoLw0F/Z3tMOjyBVa5fIGTgdNwVrlVg5kcKghJhSTlUoiq4qIQZrSvSKaaZj1wbH5e9kjM+OZU5sXysYXWyYexTMpFI19N9ElNQmyYALxZWlnX3LTQqPF63B8ChcD/7LJpE096Pe6F8biQMixWSp3ezPNHK6W0UurdJp4rVErNUUr9rJRaoZR6OTwptOF5l1LqUqXUm+E1P4fX7xXL1xQpSqm9w9NVW3PuweGfyy42+3SJUioWw3SEJKCguvYHUqOyy0m+6JTd4Xyl1PNAF6edsQlrP7lewB4xvp5UygmRch5QFQr6d7fLoMsXeAxTNbegpbUx4p8uX2B9rC/S2vhLKbWXUuphpdTnSqnflFKfKqWuCU9xt667Nnx+48fwWL6uSJD4KzZIUi7FqCouWgxc5bQfCcq4/LzsbYDbnHYkDlilq/2B3WJ4rWiSclIpl77sg5GzjrLLYFjOeiqmQuV3u+y2gZWYBGS8OB7Tm2iLPnvhAC+IqZpt/Fxf4GXMDdlpwD/CX89RSjUkTjsBlwHvhJ8/FbOxMV8pNcT2VxI9ewPXtPLc9zDy6i/scweAUmBPpdTBNtsVkoSC6tongOed9iNJ+R04Nrt7pyAw0GlnbOJX4C3L8XBM39VYIkk5IRoGAgtDQf8EG4dALAUOAG4ANraw3E6edPkC8+J0rVbFX8AJwA6Y/n5HAFMwcWNTG8yrMLGK9VFpg+9tReKvGCBJudTkDkAmzmzOLfl52R9i3vRS/fd+DeaGu4FYVsmtnTR6YDRSCamUS2+6AeWllXV32ixnnYpJ+i2xy2YrucLrcTcVhMUKP/CY1rqpXeFLgO/YvMF4AyOBbMCntZ6htZ4BHANkYYJEMDfIBVrrCVrrmVrrWeE1PwAX2Pw6AFBKxWUKttb6V631Aq21rYlcrfVqTEJGqqXSm/8DljntRBJyfm6/nCLMzW6qMDdr5iJrkizW0lWILinnipkXQjLRHnPvODsU9OfZYdDlC2xw+QLFwMHA13bYbIFfiW/rkNbGX7dqrQ/UWj+gtZ6ntZ4cXu+zbIo2sCEcq1gf0bQMihiJv5wn1ZMTaUlVcdFG4HRM1YYAz27bK+seYDpgS++EBKeifGzhn5bjRJGuglTKCYbxwPzSyrr+dhn0etwfYeSsj9llM0oWAvfF62JKqR2BfYEtBkoopbYD/g0Emjm9HebGbY3le2vC31MAWuuQ1voX60la63VANZDbgm/XKqWWK6X2U0q9p5T6Qyn1gVJq/0br6pRSdyilipVS32J5P1FKHa+U+kgp9adS6hul1I1Kqczwc2dgeqhikXTMs5y7i1JqhlJqdfjxrFIqz/L8FvKJ8HFAKXWTUqpeKbVMKTVFKdXBsiZHKTVVKfV9+DV9rZR6oNHLfx44UinVfWs/IyF1KaiurQfGOe1HkjE1t1/OZ6SeksEqXXURn17GUikntJZhmCEQR9pl0OULvAkMBp6xy2YzXOvyBX6I8TWAtsVfWuv6Jr79fvjfrcZWEfom8VeSxl+SlEtRqoqLvsHs1qY7C7t17Xi+UmoG0NtpZ+KEVbraA9h/K2vbSrQ7NlIpJzSwN0bOalvS2Otxr/V63KcBZxNfOWsIGOf1uOMp0zgUWAssbuK5O4BntNbvNXPu88BvwB1KqVylVC6mMfIvwLPNXTAcIA3BNFJuic7A4xhJwXGYTaJZ1uAszMnAQcD5GFkHSqlhwNMYmcNoTAB4MXB3+JwZ4dcIf0k6zg+fuyNGLtYRI7s9AzNl+0WlVEvSnH8BfTBS3dsx/XasgXUQ8356EeAFrsAM9rDyNibpeUAL1xJSmILq2mmY33+hZaq65WVdh7lpt62COkGwVsrsg6kWjzWSlBPaght4MRT0TwkF/R1bXB0BLl9gpcsXOAE4i803A+3iI8KJojjRlvirKfbFyHwbDy/LCSfY1iul3ldK+SK0J/FXEiJJuRSmqrjoKZrQuqcRda4MdXSXTu3+C+zqtDNxYgPwkuX4SGIrT5BKOaEt5ADTSivrJpVW1rW3y6jX434Ik/T7xC6bLTDZ63HHe/L1EOATrfVmiUClVBEmYLmyuRO11t8DRcCxmJ4nPwE+wNvMLm4DV2JuKiOZitgJuFJrfb/W+kXMe9F6TJVkY47UWk/XWpeFj68H5mmtT9daz9Za3wYUA2OVUvlhH+vCr6VB0tGQKLwG+BEYobV+QWv9PCaw3JO/pLnNUae1PkNrXaG1vh3zXmoNgvcGpmitn9Zav661flxrfa7VQFha8nV4rZDeXIiRMAnN84vKUMe365D5X8wNWSrxYdbMRdb//3hIV0GScoI9nA+8Gwr6bbt/cvkCD2MGnbxjl80w57t8gWh+79tKq+OvxoQTZVdipLDWe6rPMRV3x2Nite+B5yNMzEn8lYRIUi71OZ/4aPkTjVXAyN65WcXELxBKBF4vH1tolS3HUroK0VfKSVJOaIoARs66vV0GvR73x8BewH/tstkM3wJXx/gaTZEHLLd+IywvmAzcoLX+sbkTlVK9MbKLKsz744jw1zPC0oumzhmJCRwv1Vo33s1tjmkNX2it1wBz2TJYekVr/YflOi5MANe4Yu9pTMwytIVrHha+7kalVGb4Z/IlJogsbOHcOY2Oa4B8y/EHwCVKqfOVUgO2Ymc55v9HSGMKqmtXAuc47UcCo4FT3X27novZJEg1ZjU6bumm1C4kKSfYxSBgUSjo99tl0OULfA7sB9yCPUMg/uvyBebbYCcaWh1/NTqnPaZCeA2mAmwT4aRTUGv9qtZ6OiaxtoDI402Jv5IMScqlOFXFRasw0/XiKatymg3AmPy87GGES2rTiPKGL8aXL+lE7PuXRFspJ/JVoTn2At4rraw7xi6DYTnr6RjJxG922W2E3+txx0KO0RIdgT8bfW8spvrw0XD/jRxMA2dX+LhBGnYJ5mZsTHgndDZmJzaEkSlshlJqL0xQdp/WelKE/q1popHvMrZsI9B4MEZPjPyg8fcbjlvqFdITuBSzK2x9FAB9Wzi3cR/WdZifcwMXYNoDXA18qpT6TCl1YhN2/mx0npCmFFTXzgbucdqPBOXG3H457TDVIKmItZ9cL0yFUDyQpJxgJx2BklDQPzMU9Le55xmAyxdY7/IFLsfIQL9tg6lVmHgm3rQl/gIgLOf8LybxeUTjHr6N0VproAzYLZw82xoSfyUhkpRLA6qKi14H/uO0H3Hk/Py87M78pXlPJ16wfH04sR9sIZVygp3kAGWllXWTbZazPozZIYykF1o0POP1uKe1vCwmrMD8vKzsjNlZ/BHTH+4X4CRg9/DXJ4TXDQSqrVPDLEMcdrAaDO9IzgBeIbqpVllqy2leuZjprVYa9wRZjgniGgf/vcL/rmjhuiswAzf2auJxQ8tuN4/WeqXW2q+1zsM0rl4I/E8p5Wm0NCcCP4X0YQL2y7WSnbk9+3Z9FHiU8HCZFONXTG+lBoYTp9eZOXl6KJrlMXNESDVGYIZA2KY+cvkC8zCfpWUtLG2Oq1y+gBOTrtsSfzVwJ0baOVprvSSKazeOmZpC4q8kRJJy6UMxf013SWVuz8/LrsL00ku33+/3yscWfmM5jrV0FaRSTogNFwJv2SxnrcYEBo/aZPJHnK3E/RRo/PO5GyMDsz4qgNrw13PD674CdglLJ4BNQxx2IdwrJPy93uHzvwBO0lpHc7MHsKnqUSmVhdkoWLS1E8LXqMI0J7ZyPKbiuzJ8vC5st/GO6Cvh11GltX630aMOm9Baf4jZoc/AJDkJ+5MBbIf5mQsCBdW1fwJjgJ+d9iVB+KZ9p3ZnZWSo50jdmODlrJmLrBVr8WqjEu17tCTlhGjoBcwIBf2TQkF/hxZXR4DLF1jh8gWOxVSaRaNoeAPnqpDbEn+hlLocE+eeqrWOSHobrqw7BlgcYSwm8VeSkW5Ji7SlqrhoHeaPqnF5aCpRtm2vrMnAi0AXp51xAKt01QUcFYdryqAHIVYUYqazHmuXQa/H/ZvX4z4DMxGqrXLWsV6P28mb7LeA7ZRS7oZvaK0/11rPsz4wycPV4eMGCcJUTFP1aUqpkUqpIzFVtr2B+wHCu6yzMIMdbsBIJv4efkQiw/oduFEpdW7Y/ksYKUdJBOdeAxQppR5WSnmVUhcDE4EHtNYNUpeGneWAUmovpdTO4eNrMUHhDKXUGKXUwUqpU5RSjyilDo7g2s2ilJqvlPpX2KdhmP4xa9k80N0ZyGLzKhkhzSmorv0aOIX0aiXSFOuA43Jyu9yAqXZIVazSVRexbyWy6XJRro/lIDAhNVGYPsCLQkH/ILuMunyBqZh+ZpFMLf0VOM3lCzj1ftrq+EspdTJwE0a6+p0lrvq71Z5S6nWllF8pNUwpdQxGsfB3TIzTEhJ/JSGSlEsjqoqLPseMP07FoPCdnOwO5ymlXiL1JnhFilW6ui9G2x9rRL4qxJKuwHOllXV32SxnfRRTNVfdShMPez3ul1peFlPmYUr0h0d7ota6KnxeNvAYJjjsDByutV4cXtYLc9PcFRPQVVoekUh2f8P0Mz0feB6T3DtCa91YPtGUf3OAEzGJ2RcxE8PuwPQUaeBN4HbMzcFCjGQCrXUtJnD9DZNgnAVch+kz8nkEfm+NSkxC9zlMc+aemClj1p44wzGNjdOhMl2IgoLq2grMZLt0ZkJuv5zBwOlOOxJjZlu+3gfz/hcPok3KSaWc0Fp2A94JBf22KQZcvsCnmGECt7N1mabf5Qt8Zdd1W8E8Whl/8VeC/gw2j6sqgZGWdZ9jYp9y4HFMvDYyPPShJST+SkKU6RsopBNDJr52BXCj037YyNeuDDW0d27W/Wz+hpZOfFk+trCg4WB8+ZI7MH1sYs3YSaMHTo10cWll3ceYpqaCEC1VwPHjhvZfapfBipr6zhjJwZlRnPY1sKvX4462StR2lFIlwI5a64R631NKXQtcoLWOx8ZAQqGUqgRmaK3b1D9FSE2WDhqgMBUP6TQVvoH/5fbLuRNTxWCL9C1B+Shr5qLdGg42+EdNBK6K07VXZU6e3rjXVbOEgv5RWFQWgtBKXgTOck2YvLzFlRESKis5DNNupHGhxfMuX2CMXddpLRJ/JR7JHn9JpVwaUlVcdBMmc54K/AqM7J2bdRnpm5CDLYOq0XG6rlTKCfFiCGY6q23BWFjOehamamNtBKdo4MxESMiFuR04uIXx8EKcUErtg+lvcrfTvgiJSUF1rQZOxdK7MU34eJuenS/FVDmkckIOLNLVMPFMwEqlnOAER2GGQBxul0GXL/AyplrfWhn2I3CeXddoIxJ/JRCpEH9JUi59OYPWS7cShQ3A8fl52UVENxUwFdkkXR1fvmQXGk1QjCEy6EGIJ12BZ0sr66aUVtbZdmPn9bj/i5GzftzC0ilej/tVu67bVsJl+2ez5Zh7wRm6A6drrVO5d6vQRgqqa1dgBj/86bQvcWI1cGzHLu0fAPo77Es8sPaT64XpkxUvJCknOEVvoCIU9N8RCvptaTfi8gWWu3yB0cD/YSSRZ7l8gYQYmCPxV8KR9PGXJOXSlKriojWY6ZxJ+8sLXJifl52JGSudziwHrNN74jF1tYGIk3KllXUK04BTENrK+cDbpZV1tiWfvR73J8DewEPNLKkB/m3X9exCa/2U1vp1p/2worW+Nh2lE1rrWRH2exHSnILq2irSZzPxzNx+OSeSHpLd1WzeZNyLaYwfLyQpJziJwrTOWRAK+ge2tDhSXL5AKbC9yxdoXIXqKBJ/JQ6pEH9JUi6NCQ9+OInkHPwQzM/LXgA8hUyPeql8bKF1PHY8k3LRyFezkfccwT72xMhZj7fLoNfj/t3rcZ8N/IPN5ay/A8d7Pe7f7bqWIAjpTUF17QPAw077EWOCuf1yVmMm+qUDL2fNXLTechzvRGSo5SWbIUk5IRbsAVSFgn7bpKYuX2CZXbYEIRGRG+Q0p6q4aDZQ7LQfUVLeJzcriJkIKJVXln5y48uX5GN6b8WLaOSr0k9OsJttgKdLK+vusVnO+jhm8tRH4W+N93rcyS73FwQh8TgfM70uFXmzx7bb3A08Qfrcb1ilqy7+mrQYL6RSTkgUOgOloaB/Wijo7+G0M4KQ6KTLh6SwFZJs8EPVNlntz8nIUNOBbZ12JgH4HZhjOY7XgIcGoqmUk6ScECv+D6gsrazb0S6DXo97CbAPcK7X477fLruCIAgNFFTX/oFpkv65077YzI+Z7V2nujIzngLS6YbcKq/bG9PnKJ5Em5RLd6WJEHuOBhaHNaPsjQAAIABJREFUgv5DnHZEEBIZScoJDZzBX1Uhico3GYpR22R1eJD4Ns5NZOaUjy38zXIcT+nqRmBNFOtlyIMQS/bAyFlPsMtgWM76gF32BEEQGlNQXVuPkTnWO+2LTWwATujeO/syTGIqXfg4a+aiby3HTvTQk0o5IRHZFpgbCvpvDQX97Zx2RhASEUnKCcCmwQ/Dga+c9qUZVgNH9umVfQkwymlnEgirdDUHOCiO1149afRAHcV6qZQTYk028FRpZV1paWVdR6edEQRBiISC6trPMRVzqdC38orcfjnbYSqY04nGTeglKScIf5GBGZb1dijo38lpZwQh0ZCknLCJquKi7zGTopY77UsjQsAJ+XnZ+wPjnXYmgQgBL1qOjwDiuQMVTT85kEo5IX6ch5GzSuAnCEJSUFBdu5DkHb7VwLTcfjmzgPucdsQBrP3kcolvf99Nl45yvSTlhHhTCLwfCvrPdtoRQUgkJCknbEZVcdGnwEg2nzzoNIH8vGyAyU47kmC8VT620JpAjad0FaJPykmlnBBPdgeqSivrTnTaEUEQhEgoqK4tBy502o9W8lmXrh0vxPQo7uy0M3FmNTDfcuwFlAN+SFJOSAa6AFNDQf+zoaC/m9POCEIiIEk5YQuqiosWAT5gfUtr40BJfl72m8DTSEPaxlilqx0w8uN4Es2QB5CknBB/soEnSyvr7hM5qyAIyUBBde09wG1O+xElvwHHdsnpOBkY4LQzDvBK1sxF1pjZCekqSFJOSC7GYIZAxLP1jiAkJJKUE5qkqrhoDmb4QzQ9w+zmxT65WbcBL2FuroXNecHy9SHE/2ck8lUhWTgXWFBaWZeON4uCICQflwFPOu1EFIzL7ZfjxWzopiNW6WoGMMwhP0JRrpeknOA0fTExmiCkNZKUE5qlqrjoCeAihy7/fnaX9mdlZKjpmDdsYXM+Kh9buNRyHG/pKkilnJBcDMbIWU922hFBEIStUVBdqzEbo/Oc9SQiSnP75XwF3Oy0Iw5iHfKwN9DDIT+kUk5INpaSfkNhhP9n77zDoyraPnxPNiGFTQiQQOhLC10pSySACCotLxIrlk8FSzSiIga78lqwvWKNDY0Fe0HUFQlNiiiCIaEISAi9954QUuf742zCpmchYXeT576uXOycMzPnOQuczPnNU4QSiCgnlEvKxEFvAS+f58vuVoqR9QJ9E3BNolxPoNBLbrwtVeGairTiKSd4GmbgqylLtyVIOKsgCO5Mm3Vp2cBVwBpX21IOy+s3CXwRI8VIbRV41pkTk3Y6tF0VugoiygmeRQ5woyku3tn3CUGocYgoJ1RIysRBjwOfnKfLpQMjmjUOHI9rvL88BZvD54uAMBfYIIUeBE/lTuDvKUu3yb9JQRDcljbr0o4BlwFrXW1LKRz2MqnrfeqYvsI1axB3YVaxtieJcpKrWXAlT5ni4pNcbYQguAOyQyJUlrsw3PGjq/EaecCNzcMCLwImnO0k+Xm5bJ77JTuW/ELmkX3UMdenaa/L6Hp9XKXG6/x8Fr84muM7Uom473XCLri4yPns9GOs/+k99q3+nZzMDAIahNE+6jZaRP4HgNzTGaz67HkOrFtKYJPW9Lj9GcyNW50Zn3GCBf+9lj7j3iK4VaezucWdthhrikPbVeKls+Gr4iknuBMpsZEW2Z0VBMGtabMu7eCWLuGXAguArq62x04+8H8hzeuNBS6uqHMNxzGfXChgdaEt4ikneApzgMmuNkIQ3AXxlBMqRcrEQXnAKIp6aFU1cc3DArOBd85lklVTn2PLgu9oO/hm+jzwNp2uvhdTHd9Kj9/+58+cPnag1HM5meksmXwXx3em0e2Gh+lz/5u0vnQU+blnim6lJX5C+v7tWO9+iYCQpqz89Nkic2yY8SGNu/U/W0EOSv4duEqUE085wVNZDdzraiMEQRAqQ5t1aQcxCjq5i8fcpEatggOAh1xtiItJB/50aA8FlItsARHlBM9gG/B/prh4VxYTFAS3Qh7GQqVJmTgou9ekhdcCXwPXVfH07zQPC1wALOEc/l0eWPsXu5fPZeB/vyawaRunx2dnnCD15/fpdPV9rP78+RLnN876lLzcHAY8OQVTHSMlVUjHopuiB9cvJzzqdhp1iSSoRThzHxpGblYm3r7+nNy7lV3LZjHo2e/O7gYNCkW58bbUjkCHc5nsHJBCD4IncgK4NjbSkulqQwRBECqLG3nMzQ5tUe9rYHllB+Tma97auo8vdh1kZ2Y2IXW8uapJA17u1LLcccdzcnl0/U5m7j9KPjAstB6vdG5Fwzpnlol3/7OFr3cfLjE2+eKudDD7A3AyN49712xl/qEThNf148ML29C+7pm0okdzcum5eA0/WsPpUa9uZW8LYL45MSnboe3K0FUQUU5wfzKAaFNcfMn/tIJQixFPOcEpUiYOygVuBL6qwmkTm4TWfRH4lXMUbnYsmUFIx95nJcgBpNqm0KDthYR27F3G/L/Sqv/IQkGuNPJzc/Cye+Z52/sVeNKt/f512g27Fb96IWdlH3CMotXYqjOcuCKk0IPgidwWG2nZ5GojBEEQnMUNPOa2+wb4xCgv9QNOrNfuWbOVKdv3M651GLbe4TzboTl+XhW/goxZtZk/j5zgnW4W3u/WmpTjGdy4YmOJfuF1/Zjfp1ORn1b+ZyIkJm/ew6aM03zWvS2WAF9i/9lSZPxLG3czLDTYWUEOioauemF4yrkSEeUEd2eMKS7+H1cbIQjuhjyMBadJmTgor9ekhbcCWcDt5zjdanOAz2iTyWsm0KrC3hVwdOtawi4cwD9fv8KuZYnovFxCu0ZywY2P4BccWu7Y47s2svOvGVzy369LPZ9xaDfZJ4/g7R/IsvgHOLg+CR9/M837RNH56vvw8vYBILhVR3b88TMN2nRj2+/TCQhpRp26Qez/508y9u8kYuxr53KLM20xVsdFlyuLYUj4quBpvBYbafnR1UYIgiCcLS70mMsCrq0XWvcloFtlB807eJwf9h5hab8udAz0r/TF/j6azm+HTjDroo70bxAIQFM/HwYtXc/CQ8cZFHJmn6+uyYuI+uYy51p06AQPt23K5aH1uCAogLYLVpGRm0ddbxOp6Zl8u+cwyy+u9C054ljkoTdG7mVXIqKc4M68YIqL/8HVRgiCOyKecsJZkTJxUD5GBcP3z2GaPcCI4CC/KUBEVdiVdeIwO/76lRM70+gV8wLdx/yX49tTSXrvYbQuP3XB2m8mYxl4HeZGLUqf+7jhaf3v9LfxCw6lzwPxtB9+G9t+n876n898DR1GxHBizxZmxw1m4+zPueD/HiM/N5d1096ky3UPYPKpcy636Bi6GoZRedVVVDp8dcrSbSbA6S1oQahCfgUecbURgiAI54qLPObGN2oV3Bu42ZlBX+w6yCUNA50S5MAQ8xrV8S4U5ACswWYs/r7MPehc9oxsrfEzGa88/vY/s+1rwsfX72B86yY09vVxak7gX3Ni0g6HtqtDV8EomOYMIsoJ54tfgImuNkIQ3BV5GAtnTcrEQRoY22vSwixgvJPDM4ArmocF3g9cU1U2aa1RaCLufZU65mAA/OqFsOTVuzmUupzQTqVrf7uT5pK+fzsR971e7twAQU3b0P3WpwAI7dib3KwMNiZOpcMVd+Ht60dASFMufW4apw7txi+4Md6+fmye9xV+9UNp0mMQhzeu5J+vXyHr+CGa9LqMbtdPKPSyq4Asiu7KjsS1CYWd8ZQTLznBlawGboyNtOS72hBBEISq4Dx7zH3eqFVwCkWLGlSK5GMZRDUOZsK67Xyz+xC5Gi4PDeK1zq1o4lf2JmVaRibh5pJCXrjZj7SM00WOpaafpuncFLLyNT2D6/J0+2b0b3hm2dE9qC5Tdx4kItjMxzsO0Nrfl/o+3sw+cIzNGVl827Oxs7cFRddj4B6inHjKCe7Iv8DNUthBEMpGPOWEcyZl4qAHgf85MSQfuKl5WGBPqthzxScgiKBm7QoFOYAG7brj5e3Dyb1bSzcmN5d109+i3dDRoDU5p06SczoDgLysTHLtn+vUNRZ4DTv0KjI+pENv8nOzOXVwV+ExL5M35sat8Pb1I+vkMTYmfkrXURPIy8km+YPHCf/P7Vz2/I8c357K9sU/Vfb25ttirOkObVeGroJzhR5ElBNcxV5gRGykJb3CnoIgCB6Eg8fcymq8zD/1Qus+AfwAOO3qvz8rh692HeKfk6f4tHtb3r/Awqrjp7hpxaZyIxiO5eRRz9tU4nh9HxPHcs5oTxcGBfBixxZ836s9H1/YhjytGbk8jeRjZx75j7drSmp6Jpb5K3ljy17e6NKKnPx8nkjdyfMdW+BrOqvXIcd8ciGAtZy+5wtnRbmSX7AgVC1HMQo7nHS1IYLgzsgOiVAlpEwc9JjdY+6/lej+UPOwwFOcW+hrqQQ2sRQWVXBEa41SpTuV5WVncvroAdZNe4N1094oci4l4UkCQptz+Qs/UTe0eRkebfZFpVfp86f+/B5NrJcT1Lwdx3emofNyaWYdDECLPlEc2pBM60tHVeb2fi74MN6WGoixEHclznjKSZEHwRWcAkbGRlp2VdhTEATBA7F7zA3AEM2qutDAcaW41jfA52Og/FKpZaDtP9/2bF9YNbWxbx2G/53K74dPMjCk7D270pZtWoNyCBIYawkrcn5oo2B6/7GGVzfv5dte7QFoFeBLysXd2JqZRTM/HwJMJt7euo+mfj6MDKvPkiMnmfDvdvadzuHKsPq80rkldcovRJEO/OF4WdzD0UE85QR3Ig+4wRQXL8W1BKEC3OEXiFBDSJk46GngUQpVqlJ5v3lY4ByMxWOVLwYaX9CfE7s2knXyWOGxwxtXovNyCWoeXuoYk68/fSdMKfLT684XAOh01Vh63TEJAC9vH0I7XcSh1OQi4w+uX46pjh91Q0vmoju+ayN7Vyyg48jYwmP5ebnofCPtR252Jrrcr+vMMIx8DAUMA3zL6Hs+yH0zuuMpJ/qLp5xwvtHAzbGRluQKewqCIHgwbdalpQMjgE+qeOoxoS2Db+YcxL5gHxOdA/0LBTmAvvXN1FGK1PTMcscdzymZIu1Ybh71fMp28PI3eTEkNJjVJ4ouUby9FO3r+hFgMnEoO4dXN+/lf51akpWXz+hVm3mkbVNWXdKN1SdO8enOgxXd1nxzYlK2Q9sdQldBRDnBvXjMFBc/19VGCIInIKKcUKWkTBz0CvB/QHYpp2eHhdZ9DphJNXlOtbr4KurUrUfSu3HsW72YXX/PZsUn/yWkUwQN23cv7Pfbk1ex6jO72GbyJqRDryI/9dsY6VkCm7Ur/AwQPuJOju/cwMqpz3Jg3TI2zf2CTbM/o/3w20ot4LD229do/5/b8Q00wmnNYa0w1fFl3fR49v/zJ9sWTiMkvFeJcaXwty3Gut+h7erQVWcrr4qnnHC+eTw20lLp2HBBEARPps26tNw269LuAJ6toiknN2oVnMU5JmfvUEpeODB2TcoIMAAgvK5/idxxABvTTxNe16/C65aXcPe5tN1cFVafLoEBpGWcJidfc3WTBgT7eHNDs4YsPlxhpJ1j6KoXVe+heLaIKCe4CwmmuPhXXW2EIHgKIsoJVU7KxEHfAEMw8ggUsCbA3+cWb5PXT4Cluq7t428mcsL7+AQEkpLwJGu+eYXQjr2x3vVSkX46P6/QW80Z6rfuwkX3vc6JnRtJejeOLfO/pX3UbbQfPqZE3z0rFpB1/BCtB54JTTX5+NLrzhc4sOYvUj6eSGiXPlguqVSdC8fQVR8gymnjqxZnRTnxlBPOJx/HRlqcyXMpCIJQI2izLu0Z4A6cF2gc+T2kedD7wJecY0GpYaH1WHcyk0PZZ1KLLDlykhyt6RoYUOa4waH12J+Vw19HzghkK45nsDUziyGhZe/zZeblM+/gcbrXK33utSdOYdt3lKfCmxUey8nPJ8+e3y4jN78yEQyORR56AyEVDThPiCgnuAM/Ave42ghB8CTkYSxUCykTB/3ea9LCvhgLFz9gRIN6fu8Bfar72uZGLegz7q1y+wx+6ZdyzweENGXkh8tLPdeoSySNukRWaEfTnpfStGfJtG8hHa1c+ty0CscX42eHzwOB4DL6nS+cKfIAIsoJ54+FyGJQEIRaTJt1aZ9s6RK+G5gGBDo5fK+Pr+kWL5PXj0CDc7XlthaNmLL9AKNSNvJQm6ak5+Xx3w07GdQwiL4Nzph24e//0K9BIO91aw3ARfXNXB4SxN3/bOX5js3xUor/bthFZH0zg0IMUe54Ti7XpWzkhqYNaRPgx+GcHN7Zup89p7P5rEfbUu15ZP0OHmnbhJA6Ro7g9nX98Dd58VTqTi5pGETCjgOMax1W6lg7/5oTk3Y4tN0ldBVElBNcz0LgJlNcvPOeD4JQixFPOaHaSJk4KBVDhBvWPCwwFrjOxSZ5Kqm2GGuaQzvaZZacQcJXBXdkA3BNbKSlZLUXQRCEWkSbdWlzgEswKlBXllxgVP2wwKeoomqiQT4mfo3oQH0fb25bvZkJ67ZzScOgEqJZrtaF3moFfNq9Lf0aBHLvmm3cvXoLPYIC+Lpnu8Lzvl5ehNTx5pXNe7gmOY1xa7cT7GNi1kUd6VmvbglbbPuOsC8rh7taNSo85mfy4tPubZl78Dh3rt7CpSFB3NEytLxbmlWs7U6inLNCiIhyQlWSglFpNcvVhgiCpyEPY6FaSZk4aH90QnIU8LirbfFgfi7WdgdRTjzlBHdjOzA4NtJytMKegiAItYA269JWbukSHgkkAp0rMeTRRq2C2wJ3VaUdbev6Md1aerGtAtYNvLDEsWAfb6Zc0BpoXeoYP5MXX/dsX2k7osMaEB1W0vlvQMMgUgZ0q+w0jvnkQqgi8bKKEE85wVWkAcNNcfEVJmQUBKEk4iknVCvRCcmXAh+42g4Px1bwYbwt1Qo0d6EtBYinnOBO7AEujY207HS1IYIgCO5Em3Vp24F+wO8VdP2hUavg34D3q98qjyUd+MOhPRT3epcSUU5wBbuBIaa4+ArLFguCUDryMBaqjeiE5I7AdMDH1bZ4MHuBvx3a7uAlB1LoQXAfDgCXxUZatrjaEEEQBHekzbq0Y1u6hA8GXgPuL6XLBnN9v/HAIqD0cqkCwAJzYlK2Q9udQlfBeVHOVC1WnAc2HTrGawtX8Pf2fazdd4T+bZqyYOzVRfq0fX4q248WddxqHBjA7mfuKHfuZ2Yv4+c1W9h+9AQa6BBanwkDezCqxxlvz21HTtDuhc9KjB3VvT1f3zKssG1bs5mHfvmT9Owc7unbjf8OvahI/0lzk1ix6wA/3T6isrfubhwBhpri4re72hBB8GRElBOqheiE5HrATFxfkMDT+cUWY3VMsnKlyywpirPhq+IpJ1QHR4DLYyMtqa42RBAEwZ1psy4tBxi3pUv4cowIhgLxLQO4JiDI712gXVnjBaBo6KoXhqecO1FrPOX+3XeEWeu3c1GrMLLz8svsd2OPcO69+ExodB1TxY6NJ7JyuLV3Rzo1boDJy4sf/9nETV/OweTlxTUXFv0v8soV/ejbumlhO6SuX+HnQ+mZ3Pr1PJ4c3JvWDYK4e9oC+liaMKRDSwB2H08nfvEqlo4fVen7djNOASNMcfHrXG2IIHg6HvswFtwbW4z1eHRC8sfA84BytT0ejGPoalugqwttcaRWecod2LWNeV99yNZ1K9mzJY12F/Ym7t1vi/R58ur+HNm3u8ixoAYh/O/X0qv4OpJ+/Ci2KZP55495ZKafpEFYM4aNHkuf4dcA8OtHbzLzk9IrCkfHPsywW8cCsOr3ufzw9vNknTrFJdfcwog7HijSd+Yn8exIXcM9ryRU+t7dmOPAkNhIyxpXGyIIguAptFmX9sWWLuFrgB8xkrXd1ahV8AjcxxPfnXEs8mAFQlxlSBnUGlFuROfWjOzaBoBRnyVyKON0qf3CgurSp1W51XRL8Hr0xUXaQzq0ZN2+I3yRnFpClAtvVL/M+Zft2Eer+oE8cmkvABZt2sVvaTsKRbnHZizhtos60y7EI/0XcoBrTHHxS11tiCDUBDz2YSy4P7YY64vRCckbgM+BAFfb44GcBOY7tN1pwVyrCj3s3ZLGuqWLaN2lO3k5ZRf27D0kmoHXji5se/tUHLmdmXGS18dej69/AKPinsFcrwF7t20k1+E6/UZeT+c+lxQZt3rxXOZ+OYUufQYCkH7sCFOfe5DhY+4npGlzvnz5Cdp07UHniwYAcOzgPhZ89wmPfly8bohHkg5ExUZaUlxtiCAIgqfRZl3aqi1dwq3AdY1aBe/BWKcJ5bPenJjkGKLnbqGrUItEOS+v87vf3zDAj+w854rb5uTm4e9z5iv2r+NNjt2rb9n2fSzYtIv1j91SpXaeJ7KBUaa4+NmuNkQQagoe+zAWPANbjHV6dELyNuAXoGkF3YWizLLFWB1zl7hL6CrUskIP3fpfzoUDhgDw4RP3kH689AKf9RqG0qZrD6fmnv3Ze+RmZ/PYJ79Qx9cIe+jQK7JIn/qNmlC/UZMix2Z9+jZhrdrSItwoqLd13UoahDVj6C2xAGxYsYz1y/8sFOV+fPdl+l4xikbNLU7Z54ZkAiNjIy1/udoQQRAET6XNurQj6VERM4AVeHBusfPIrGJtEeU8gKlJ//LOn6vx9/Hm8vAWTL6iP60aVG6fODcvn/TsHBL/3ca8tB18fXPJaOU7v/2NI6eyaGT25/oe4TwfFVkoxHVvFsqavYdYuGkXlvqB/PTPZp4d1getNQ/+vJjnhvUhyK9Old7veSATuFoEOUGoWmr8w1hwPbYYa0p0QrIV+B7o72p7PIhCl6bxttRQoK8LbSlOrfKU8/KqvuJqS2dO49Lrby8U5CpDxoljrF/+J8PH3Fd4LDcnBx+HOer4+hV69W1Zu5INyUt45rsFVWe4a8gGro6NtCx0tSGCIAieTHpUhDfGuqyxq23xEBzzyYUAvV1oS1mIKOfAyK5tuKhlGM2C65K6/yiT5iYx8N3prHroJur5+5Y7dtn2ffSPnwaAt5cX8VdfQnS3toXnfb1NjO3XjcHhLQn0q8Pvm3czeUEKWw4fLyza0LphPR6/vDeD3/8JgOGdWnFDj3C+SE4lNy+f2yI6V9OdVxsZwBWmuHhZgwlCFVOjH8aC+2CLse6NTkgeBPwPiHO1PR5ADpDo0L4C99rJrlWecpXlr1+nsXDaZ/j4+tGpdz+uuf9JGjZpXmb/Q3t2cvLoYfzNQbwz4TZSly/B3xzIRUOv4sqxj+DtU/oO6ooFieTl5mC9/Ey1rhbhXdizeQMbUpbSsElzVi6azciYOLTWTHvzWa64awL+dQOr/J7PI9nAqNhIi+zOCoIgnDuTgX6uNsJDyAD+cGgPAapvt+7scS6+soa/B75x5YDCzxe3aUakpQm9Xv+GqcvX88CA7uWO7RbWkGXjR3EsM4vE9dsZ9+PvBPnW4YaeRgXWJkF1ib96YGH/ge2a0zgwgPumL2LV7oN0bxYKwMQhEdzTtxsZ2Tm0ahBEelY2TyUu5cubh5Kbn8/4Hxfz4z+bCAusyzvXDKR/G7cNKjoBRJni4pe42hBBqInU6Iex4F7YYqy5wITohOS/gE/wcO+pamaRLcbq6I3mTvnkwAlRbsrSbXWA8rckawAXXjyY1l16ENwojH3bNjHzk3heG3s9E7+Yhb+59H/qJw4fBOCn917GetkI7nt9Krs3rcc2ZTJe3iauvvfxUscl//YrLTp0pXHLNoXHQpq2YNjoe3nz/psA6Bo5COvgkSyb9SN5ubn0HeGx1b3AyCF3VWyk5TdXGyIIguDppEdFXAeMd7UdHsQCc2JSlkPbHUNXQTzlyqVrk4Z0CK3Pyl0HKuxb19cHawvDifTy8JacyMzi8ZlLCkW50rjmgnbcN30RK3edEeUAQsz+hNiLHb88P4W+rZswoG0z3v5jNav3HGL9Y7cwd8MObvpiNhufHI2vtzvtwQNwFBhqiouvuHKZIAhnhTvu8gg1HFuMdTqG2/9aV9vixjiGrgYAg11oS2k4E75aK8TXUQ8+Te8hI2nfPYKLr7yJ+9/4jOOH9vPXzB/KHKO1kfC3Sev23Pz4y3S09uWyG+5g6K1jWThtKtmnM0uMOX7oABtX/U3vwVeUOPef28cxOTGF56f/wb2vfUJOdha2KZO57oGJ5Ofl8vUrT/JwVC8m3TyMTas9Zm11GLhUBDlBEIQqIwvn01DUZhxDVxVQMrmYe+CsKOd26s/5QCnni0T0aB7KzmPp5JRT7KFg1rKm33bkBFP+WsPLIwwH1UWbdnFTz3DqB/hxfY9wsnLzSDtYes5iF3IIuFQEOUGoXkSUE1yCLcaaBlwEfOlqW9wQjVEYo4ChYN9icx+cCV+tFaGrxWnWtgONW7Zh54ayteeAoGAAOvQsWtihQ69IcrOzObh7e4kxKfNngtb0umxEiXMA5uAGhSGzcz5/j7YX9KJ9j4tY/NNX7Nq4nme+XcCw0ffy0cT7ycnOKnUON2In0D820iKLQUEQhCrCnJj0C9ATo8iDUDGORR6sQGhZHV2MeMqVw9q9h9lw8Cg9mzdyeuxfW/fSvJ4ZH1PZOub0fzYBlDn/IzP+ZGy/C7A4FJo4lW38leXl55OVl4fWTptWnewDLjHFxa9ytSGCUNOpVQ9jwb2wxVhPAbdEJyQvAd6kFoQ4VpIUW4x1l0Pb3UJXQTzlKk85O7KhzVqWmjdO21dlSpXcN0n+bQZtL7DSoHH5eUcO793F7z99yZNTZwKQtmIZEUOjqRtUj96Dr+C715/mwM6tNGvb0Zm7OZ+kAkNiIy07XW2IIAhCTcOcmLQlPSqiL/AWcLer7XFjUs2JSdsc2u4augq1SJQ7lZ3DrPXGxuXu4xmcPJ3N9NWGKDa8UysWbtrF1ykb+E/n1jSpV5cNB47y4rzltAwOZHTvToXzfJG8nju/m0/a47fSqkEQ24+c4I7v5nNjj3BaNww0B2UcAAAgAElEQVQiIyuHn9du4btVG3n3moGF456d8zcns7LpZ2lCoF8d/tiyh9cWruCqbm25oGlICXt/37ybv7fv49MbzgS+DGjbjPjFq+gU1oCFG3cR6FuHDo3qV9M35jS7MDzkNrraEEGoDXjsw1ioOdhirFOiE5KTgK8At1UIziOOoasmoHSXKNeR9WZ0x2wn+tdKT7ndmzewf8cW+kffWGYfb586dOzdnw0pfxU5viH5L+r4+RPavFWR44f37mLrupXc8NCkCq8//e0XGHjNrUUKTRSEw+bn5ZGbk10o/rkhy4Go2EjLIVcbIgiCUFOx50mLTY+KmAt8CDR0sUnuyKxibRHl3IAD6Zlc/3nRv5qC9qYnR9MiOJAD6ZnE2RZzLDObhnX9GNqhJc9HRRLkd2YzND8f8vI1BauhYH9fmgbV5cXflrPv5CmC/X3p1LgBv9x5BVGdLIXjOjaqz+uLVvLJ3/+SmZNLy+BAJgzqyROXlyzKm5+vmfDzYl6I6ktdX5/C47F9u7F272FGfzWXJkF1+fLmoe6ST249RlGHba42RBBqCx77MBZqFrYY64rohOSewMvA/ZxJzVAbsTl8vhj3WyQ7W3nV4z3lsk9nsvYvowL8sYP7OX0qnRULjOK4XfsOYkPKUpLm/Ey3fpdSL6Qx+7ZvZtbUd6jfuCmR/7m2cJ5ls6bzxYuP8tz3iwrFsv/cfj+vxo7i8+cfxjr4CnZvTmXOl+8TNeZ+fOoUdR5NnjcDL5M3PQeV/06QtnIZW9etYvTE1wqPte9xEQu++4QmrduzIXkpfgF1ixSKcCPmA1fGRlrSXW2IIAhCbcCcmPRjelTEUuBT3DdfmqtwzCfXEIhwoS0VUWtEOUuDIHJfu7/cPvPuuarCeUZHdGJ0xBnPuXr+vnz+f0MqHHd9j3Cu71F20QdHvLwUyRNKbtD6eptIuP4yEq6/rFLznCfmA9eY4uIl56QgnEc89mEs1DxsMdZM4IHohOQZGAvD5hUMqYlsssVYHZOQeXroKtQAT7mTRw+T8NS9RY4VtJ+f/gf1Gzfh5NHDTHtrEqdOnsBcL5jOfS4h+u6H8a8bWDhG52vyiyUJtnTuzthXEvh5ymSWz/uFwPoNGT76XobeOraEHcnzZ9DR2pfA+mXrtPn5+Ux7cxJXxj6Mr39A4fEBV/0fezZv4NNnH6Rew0bc/uxbJUQ/N2A6cFNspMUZT0xBEAThHDEnJu1Nj4oYDtwLvIL75bJ1BRnAYof2ENw7H3etEeWEauFj4B5TXHyOqw0RhNqGcuPwJaEWE52QHAy8B5Qd+1czec0WY32ooDHelroFaO1Ce0pjxZvRHXtVtvOUpdvuBd6pRnuEmsEHwNjYSEu+qw0RBEGozaRHRXTCSCnSw9W2uJhfzYlJhaXOc8eN/By4xYX2VMQl3vG/LK64G+S9Pk4B8vtWAKPA3OOmuPj/udoQQaituPNuj1CLscVYj9lirDcBNwBuVx+8GnHMJ3ch7ifIgfOech4fvipUK3nAg7GRllgR5ARBEFyPOTFpPXAR8BK1W7hxDF1VuH9orzOecuIlJwBkAqNEkBME1yKinODW2GKs3wFdgbmutqW62ZU058Qvd/V+RSl1WCl1+sNb+85P+v598nLKj+Q7vGMjPz19B++O6sEHt0SyYMozZGdmFOmzfdUSZr02gU9iLuOtKzux7JuSjmvZmRkkvvIg79/Um+8euZ6ju7cWOX86/Tgfju7HjtV/OZvvz+PDV4Vq4wgwNDbS8qarDREEQRDOYE5MyjEnJj0BDMCohl0bcawk0Ato5CpDKokzopxbVBQQXMp+YJApLv4HVxsiCLUdEeUEt8cWY91ji7EOBUYDB11tT3VxcvemNcBC4E5geNcho7KSfviAxZ+WvXmVlXGS6RNvIzc7i+EPvc7FYx5h09J5zHnj0SL9tq/4k0PbNtDigj54+5aeJiZp2hSO7tlG1MNvENS4OfPinyhy/u9v36W1dSAtL+y7w8lbE085oTTWAr1jIy3zXW2IIAiCUDrmxKQlwIXAM0CWa605r2wwJyY57k4O352eSfCURHzenkF6dtn6V3ZePo/++S8Df1hC4Hsz8Xl7Rpn9nk9Ko+Pn8wl8byYdP5/Ps8s2kOWQe/Zkdi43zkqm4Qez6Pf9H6QdLVoD6ejpbJp+NIeUA8dAPOWEyvMv0McUF/+3qw0RBEFEOcGDsMVYPwc6Ah8BNS4ZYqer7v2f1vpJrfVPD/y8fnPfm8c37TlyDKmLZlBW7sd/Zn1DXvZpRj75Hm0iBtH5squ4/N5JbEmaz/5NZ+pFXDzmYW55+1cG3/8C3mUk99+5eikR191Nqx79GXDH4+zdsIqc06cAOLJzM+sX/ULfm8eD89VXxVNOKM6PQGRspGWLqw0RBEEQysecmJRtTkx6FuhO0cIHNZlZxdrDH1uyHrNPxVrWqdw8Pvl3BwE+JiKbNCiz3xN/reeVlI3c3c3CjJEXcXdXC6+u2MRjS9YX9nlp+UbSjmXwzbBetA4K4I7fVhWZ47mkNKIsjenVKBhElBMqx29AX1Nc/DZXGyIIgoGIcoJHYYuxHrHFWGMwwinWudqeKiQDmOfQvhLALzCY/NyyiyAd3LqeRu264ms+44zWsns/UIqtyb8XHlNeFf9Xz8vNwWQX7Hzs3nR59msv/uRlrFffQd36oeC8KCeeckIBGsPb4trYSEt6BX0FQRAEN8KcmJQKDATuAo651ppqxzGfXIM/dh++aM72A8T1aFvhwGBfHw7EDCUxug/RbcLK7Pdt2m7u7mrhwR5tGdg8hAd7tuXubha+T9td2Gf+roM8bm3PkFaNeG1AV5btO0pGjqG9rT9ykq9Sd/F8ZMdCU524PxHlah8aeBkYZoqLdzY/tCAI1YiIcoJHYoux/olRFexxjCSlns5cW4z1NIBSypR9Kv2q3f+msOrXL+g27AaUKj2NW15ONiZvnyLHvEwmlPLi6K7NThnQqG0X1s37gcwTR1k143PqNW6Bn7keW5MXcWzPdrpfMbqgqxR6EM6GdODq2EjLs7GRlhrn6SoIglAbMCcmaXNiUgJG5MJ3rranmjgFFO5sZubmDR2/eK3XkxHhNPSvU6kJylq3OZKTn08936JruGBfnyKhINl5+fh7G+nfAux/ZucZtTce+mMdD/dqR1hdv4LuIsoJZXEEGGGKi3/cFBefV2FvQRDOKyLKCR6LLcaaY4uxvgx0ARJdbc858rPD54z3b+o98IcnbqZ5195cPObhMgfVC2vJwW2phR5tAAc2r0Pn53H6pHPaWZ/r7+Xwjk18eGtfkn/8iEGxT5OXm8Mfn75C/9sextuncCEq4auCs2zBCFf9ucKegiAIgttjTkzab05MugEYTs0rBLHQnJhUmD9v0t8bHsjKzWNsN0uVXuT2zi1JWLudJXuOkJ6dy5+7D/PBmm2MvaB1YZ+ejYL5eN12Dmdm8/bqLbQJCqC+Xx0St+5n07EMxnVv7TiliHJCaSwFupvi4j39XUkQaizyQBY8HluMdSvwn+iE5KuAyUDFsQXuRR7wa0Hj0nueeb5Bi3aT9m9cw9/fvYe37yQujX261IFdh1zHql+/YFHCC/S54V5OnzzGwinPobxMKJNzhbWCGjfj1ndncnzfTswhYfj4+rPCNpW6DRrTrs9gdq9LZuGHkzi2Z9srb+VkXwg8oLUuvzSsfWqnDBFqGonALbGRliOuNkQQBEGoWsyJSbPToyJ+A+7BSE9QdhI1z6EwdNVcx7uhj5eK+HxIT3xMVevL8GLfTmTm5jNw+pLCY7HdLDwVEV7YnhgRzrCflxL20RzMPia+j7KSk5fPI3+u43/9O+NbdK3njAeUvAPWDt4AHjXFxZedC0cQBJcjD2ShxmCLsf4UnZA8E7gPmAgEu9ikyvKHLcZaKFh0G3p9d4BmnXvhHxTM3Lcep2f0bQQ3aVliYIPmbbhs7LMs/uRl1s75DuXlRdch14FSBNRr6LQhXiZv6jczdl0zTxxl+Q8fcM2kz8jNySbx1Qe55I4nqN+s9Z1fP3jVBIycMu9UYlrxlKudnAYejo20VObfiCAIguChmBOTcoG306MivgT+C9wL+JQ/yq0pFOUa+tX5oFN9sxpuaVzlF3ltxWa+3rCLNwd05YKQIFYfOsEzy1Jp6OfDM32MPHGWoADW3jyILcdP0dzsR4CPN2+s3ExTsz9Xtm3Cn7sPc//va9iXkUWe1pOOvq3urOSGqbwD1myOAbeZ4uIlQkEQPAB5IAs1CluMNRt4PToh+TPgaSAW918YFv7CHG9L9QOGFrRD23QG4MSBXaWKcgBdLr+GDgNGcGzPdvyDG+AfWJ8Pbomky+Brz8mov758k/b9hhJiCefg1lTyc3MJ7z8cYC/wBTCIyoly4ilX+1gL3BgbaVlbYU9BEAShRmBOTDoKPJgeFfE+RuTCSBebdDakmROTtgAopbp4Ka78algvjmUZjkancgxntOPZOZi8VGG+N2c5lJnFf5elEn9JN+7s2gqAi5s1pI5J8cDvaxl7QWsaBRjFt7y9vAivby4c97/kjcy7qi9ZeXncODuF1wd0ZXDLUJp9NKcLld8wlXfAmksKMMoUFy8V7gXBQ5CcckKNxBZjPWyLsY4DOgPfA+6cWN5xF+tywFzQ2Ju6EoCgRs3LncC7ji8hlnDqBoeQ+vsM0PmE9xt21gYd3LaBTUvnEnnTA4XH8nNzyM/LA6PQQ12gwizGU5ZuC0AWfrWNt4HeIsgJgiDUTsyJSWnmxKRo4DJgtavtcZJZDp/b52tMF0/7k9APZxP64WzG/b4GAMunv/HA72f/a27L8VPk5GsuDC0aTNA9pB65+ZrtJ0uvYTZxaSrXtGtKt5AgUo+kk5Ofz3XtmxLs60N9vzrfYWyYVoazUxMFd+c9oJ8IcoLgWcjLslCjscVYNwHXRyckTwZeofKLlfPFaluMdTuAUmr2BVE3BbfudQnKy8Se1BWstE0lvP/wQi+5qbFDadbFyuD7XwAg61Q6y6dNoVkXK14mb3au+ZuVtqlcNvY5/ALPRO+eOLCb/ZuMxWN+bg5Hdm5m419z8PH1x9JrQAmjFn/0IhHXxeIfVB+A+s1a4+3rz5+fvcq+tNW9MEJTXq3E/YmXXO3hADAmNtIyq8KegiAIQo3HnJi0ID0qoidwI0a+uXautahSFP4OG3dh6zVXtAnLVw5ODHO2H2Tyik3MuCKC1vXqnvVFWgUFALDy4DF6Nz6zXltx0CjSZQnyLzHmn0Mn+GnzXtbefGYpm52nycvXmLwUp3Pz/KnEhqkdeQesWewHYiVcVRA8kxr5QFZKjQE+LeXUPVrrKVUwfyfgQ6AnEAC01lpvK6NvK+BljJBEP2Aj8KjWeva52nEuKKWmAl211lZ7ewzGdxaotU6vwuuMAgK01lOras6zwRZjTQYujU5IvhQj38klrrTHgTO/PJVavnP1ssfWL/gZ5WWiXlhz+t78IN2GXV/YJT8vF52fX9j28vLi4Jb1rJ33A7nZp2nYsj1RD79B2z6XF7nIrjVJzHv7icL2xr9ms/Gv2QSGNuX2hPlF+m5aOpeMowe5IOqmwmPedXwZNuFVFn7wHEd3bXkTmAZU5v+SiHK1g0TgtthIywFXGyIIgiC4D+bEpHzgq/SoiO+A0Rg5f1u51qoyOQX8XtB4bUBXK8WiirbZPdj6N22IuY7xGtXx8/lc3KwhCZd1L+w3e9t+MnLzWH3IKFg/fdMeAKyNgmkVFEDjAF+i24TxxJL1nM7N54KQIFYdPM6kpDSubdeEUH/fEsbFLV7L473DCbGf61DfTICPiceW/Mug5iGcyM69EyNsuDLUyHfAWsrXwP2muHgpqCUIHorS2p2j+s4OB4HpUsDR/3uL1vqcXxqVUr9iLCjGAxnASq11Vin9WgB/Y7juT7H37Q5s1lr/dK52nAuliHKhGFVLk7TW+eWNdfI6PwAhWuuBVTVnVRCdkHwx8BQwxMWm9LDFWFcBjLel9gP+dLE9lcH7zeiOlarwNWXptt5AUjXbI7iO08AjsZGWt11tiCAIguD+pEdF1AFuBx4HSk+W6zpmmhOTRhQ0cseN/Ay41bHDZ+t3cudvqzh69/BCUa7d1N8Y0KwhnwzuUdiv3dTfSg1B/ejy7ozu1AKAE9k5PJ+Uhm3zPvZknKaZ2Y8r2zbhyd7hBNYpqpn9tGkvE5euZ+VNA4tUgV206xD3L1rD3ozTZOTkfZqrdWxlCj3kvT7uImBZZb4UwW3Zh+EdZ3O1IYIgnBs1XZSrUq8vh/k3Ab9oreMq6Pct0Ay45FyELqWUD5CvtXam1HlFc07FQZSrLtxVlCsgOiH5IgxxbkRFfauB7bYYq6WgMd6WOhl4yAV2OEPGm9EdzRV3M5iydNtlwG/VaI/gOlZghKuucbUhgiAIgmdhF+fGAE/gPp5z95kTk94FyB03UmGIHo1ca5JTeHvH/1Kpd4W818d5ykawUDriHScINQgp9FAMpVR3pdR8pdQppdRRpdRXSqnG9nMWpZTG8Ch7UCmllVKLypinHnA18J6zgpxSapFS6gel1F1Kqc0Y3ihN7ee6KqVmKqVO2n+mKaXCHMYOtNs1RCn1q1IqQym1QykVW8E1x9jHmR2O+SulXlFKbVdKZSmltiqlXnI4f6tS6k+l1BH7d7VQKWV1OD8VuAa4xD63Vko943A+WimVrJQ6rZTaZ7+Wj8P55kqp75VSB5RSmUqpzUqpSc58lxVhi7H+bYuxXoERivwj57cgRPGdrejzeO2z5YST/etV3EXwMNKBOCBCBDlBEAThbDAnJmWbE5M+BNpjiHPu8PvEMSdqTzxLkKOyglxB92ozRKhO9gFXmuLi/08EOUGoOdR0UW6zUipXKbVBKXV3RZ3tIZyLMPLE3QTcj5F7bJ5Sqg6wF4jEeCB+bf88tozpegI+gFZKLVFK5SildimlHldKVSYJaz/gHuBR4ArguFKqHbAEIzfdLRiLmC7AjFLm/Bj4B0MYnAW8r5SqtDeYfT6b3YZ3gSjgaSDEoZsF+By4DuP72gUsVkq1sZ+fBCwEVmJ8V5HAR/b5R2GIYEnASOBZjDLuL52Zns+BFvbjw4EXgJJJNqoAW4x1pS3Geg1wAfAZUCIcuRoozCc33pbaGWNh6u44K8pJTrmaxS9A59hIyxuxkZYq89wVBKF24LABWPyn3I1DJ+bvpJT6w74hqZVSlnL6tlJKfWPfWDyllFqtlDr7suVVhFJqqlIq2aFdYtO0iq4zyh5Z4lLMiUk55sSkz8yJSRdgpBRxVc7lNHNikmPFyuEusuNscfZ3sohynsdXQBcJVxWEmkdNfSDvxUgkm4RR8vtGYIpSKkBr/UY54ybY/xyqtT4BoJRKw8gLd43W+htgmVIqC9irtS4vF0OB99oHwPsYIZKDgOeB4xglq8sjGOihtd5XcEAp9S6GIDi8IF+EUuofIBVDNJvpMH6W1rogs/8cu1D2FPBrBdctYAgwGIjWWv/icPzzgg9a6+ccbPMC5gG9gZuB57TWm5VSRwAvx+/KLvhNBj7XWo91OJ4FvKuUeklrfRiIAG7UWs+wd1lUSdvPGluMdS0wJjoh+WEMMfAejBDkquYI8IdD+8pquEZ1cNzJ/iLK1Qx2A/fHRlpcmgtTEIQaQ4mcv1U072SM9dNIjDy+e0vrZM/5uxQj5+9tnMn5W7LkpeuZibGpeaqK5x2FsdE6tYrnPWvMiUnzgHnpURFdgAcx1pPVshlbCsUrh3uaKJfrZP+a+g5YE9kDjBUxThBqLjXygay1ngPMcTg0SynlCzyllHqrnHDSCGBugSBnnytJKbUN6A9844QZBV6Is7TWj9k/L1RKNcdIbluRKJfiKMjZuRzDiytfKVXwd7cV2AZYKSrKFX95/hGIV0qZKpmb7lLgSDFBrgjKqEL7ItCXoi7+4RXMHY6R3Pd7h/sAWIDhBdgVo/rVKuAlpVRDYIHWekcl7K4SbDHWg8AL0QnJ/wOuAsZh/BuoKmbaYqyOCyhPCF0FCV+tbeRjeMo+GRtpOelqYwRBqDEsr46cv0BHjJy/8yvoNxnYDPzHYU3odP5TVQ05f4ujtT4IHKyu+d0Rc2LSOuDO9KiIJ4B7MTZIQ6v5soWiXO64kfWBi6r5elWNs6KcqVqsEKqSLOB14EVTXHx1PC8FQXATanr4qiM/AA0wQi7Logmwv5Tj++1jnaEgzn9hseMLgOZKqYo8iEqzIwQjnDWn2E8bjDBPR4pXmT2AIcKGUDkaUsYOM4BSKhCYa79uHHAxhpfcagxhrTwKbEik6H1stR8vuJfrgWTgDWC7UmqVUuqyStpfJdhirLm2GOs0W4z1YqAH8AlGjr9zxTF0tSnGd+cJiKdc7WEl0Cc20jJOBDlBEFyNkpy/tSrnL4A5MemAOTHpaYyN3JsxIiaqI/dvJsZmcAFD8DzRSjzlahY2jFDVJ0SQE4SaT218IJf3y3wvpSd1bQykOHmd9WUcL8j9VtFCsDQ7j2B4wH1UyrlDxdrF76MRxi/s4v3K4jCGSFkWkUBzYLDWOrXgoH2xWxEFguVdGC/+xdkKoLXeDYyxh8ZGAM8AvyilWtrDW88rthjrKuCO6ITkRzDCXUZjePU5y2mKenJGc+bfhbsjnnI1nwyM/JFvSt44QRCqic12L/jNwOta6w/K66zO5Pxdj5HD1gy8jJHz18qZnL8/YWx+vk3Zv6+K5PzFWF/sx/AKfllrXZHo0w9D/HsUI6TUMedvMkbOXxNGXt0ZSqmIYnN+DHxht/FqjJy/u7TWlUov4pDzN9J+jRSMNBsXO3SzYKQb2QzUwfjOFiulumqtt9jHtcQI9S1II7LLPv8ojMiQDzAqo7bFyPfrxZkK8Z9jhPreBRzD2BzuWBn7zwZzYtJpjHxaX6VHRbQD7sRYg4WVO7DyLLRfowBPC10FEeVqCuuB8aa4+LmuNkQQhPNHbXogX4MhSG0vp8/fwD1KqUCt9UkApVRvjMWNU2XDtdbblFLrgMswFjYFXAZsPsuwjfkYIlBKJRaNV1E0P8ZV9nGVfcmeDzyilBpRxkKxIO9KYUEEpVRfjO/KUcDMpqTn3AaMHFUWrXVCRYbYd7KXKaWeBf4CWmGIhi7BFmM9DLwKvBqdkNwDY2F4I5Wv0vWbLcaa4dD2lNBVkEIPNZk8DE/QZ2IjLXtcbYwgCDUSyfkrOX/PCXNi0ibgsfSoiKeAERgC3TDOzbPNMXRV2efzNESU82yOYzgfvGOKi3f271IQBA+nRj6QlVLTMRZ8/2D8kr7e/jOuglCF1zHyVsxRSv2PMzuxa4DpZ2HKRGC6UmoyRqjnQIwd1FvPYi4wHtZJwEyl1CcYImMzjMXZVK31Ioe+w5VSL2C4419t7+OM+DMPw5vra6XUc8AKDM+5AVrru4FlQDqQoJR6BcNr7hkMsc2RVCBaKXUlxi7sHq31HqXUBOALexjvLAzxrg1GwYNrMXax52AsMtMwEv1OwFj0luWFeN6xxVhXAiujE5IfwljEjcaollteYmLH0NUgjJcBT8HZ8FXxlPMMbMDjsZEWt/m/JQhCzUNy/gKS87dKMCcm5WKsp35Oj4poxpkN0rOJYHDcxO6BESHjaYgo55nkY3jPPmmKi69VuSMFQThDTX0gbwBux8hNpoB/gVu11l+UN0hrfVApNQh4DWOBl42R9+zBgp1PZ9Ba/6SUuhV4EngA2AHcq7X+ytm57POlKaX6YOzmfojhrbYbw6ttU7HudwLjMapXHbFft8wFXCnX0kqpqzBCHMZjJNjdA3xtP79fKXUdhseYDdgIxAKPFJvqPc7kYqsPPAs8o7X+Til1AiM04nYML50tGDvF2fb2GozvrQVGiMgyYIjWOhM3w1604Vfg1+iE5GAMEfgWjAWxY2hqPjDDoR2FEVriKYinXM1iKfBIbKTFKU9gQRCEKuQHjEqgFsquwtoEWFfK8arO+XubUirIUfwr45rFKcj5+2gp55zJ+Vva3MWpbM7f/Rg5f7djpM34COdy/paGY87fFzBy/gYrpVYDEypRYKNaMCcm7cYQIV9Mj4roZLdvFNCpEsM3mhOTNju0PTF0FUSU80T+wAhVXeFqQwRBcC018oFsDwt4osKOpY9dibELWV4fixPzfQl86aQNA8s5l4rhSVYRu7XWZS4stNZjirWnAlOLHcvEyB/yEKWgtZ4NzC52OLFYn0MYobOljZ9FyRL0BeQCMWWcc2tsMdZjGGExH0QnJDfDuP+rgQHAMluM1XFBfqULTDwXpNBDzSANwzPuR1cbIgiCYEdy/lYOyflbDubEpPV2e55Jj4rohiHOjaJsL8Hi61BPFeWczQFbI98BPYRkYKIpLr74O5QgCLUUeSALQjVii7HuBt4B3olOSA7BISRivC21Dp63+JNCD57NPgxv1Y9iIy2Ss0QQBHdAcv5Kzt9qwZyYtAYj6mJielREd4xN7RHAhQ7dHPPJ1Qf6nFcjqw7xlHN/1mKIcT9X2FMQhFqFPJAF4Txhi7EeouhO+CA8z5NMPOU8kxMYYfmvxUZaMirqLAiCUB1Izl9Acv66BHNi0iqMXHhPpUdFNMdIHzKUokUqBnNuBSNcibOinKfepyeyHiMd0HemuPiKPHEFQaiFiChXw7Av/FRF/QS3wNNCV8EJT7kpS7cpILAabREq5hDwFvBObKTlmKuNEQSh1iM5fyXnr8sxJybtwvh7+rDYKU+LXnBEPOXcj7UYz4RpIsYJglAeqmIve0EQqprxtlSFsTPd1NW2OEnXN6M7lpZsuwRTlm4LxPlwV6Fq2I3x8vqheMYJgiC4HqXUQIziEt201mtdbI5QjNxxIxWGuBnmalvOkhXe8b/0qmznvNfHPYjhgSpUPaswRPOfTHHx8qItCEKFeFXcpfahDFYrpUY7HJuqlNKl/HR06GMpo8+3Dn1MSqlHlVJ/KKUO23/m2nOjuBylVB2hgsoAACAASURBVIRS6pmzHDvQfr9nU46+vHkfVkq5pKJXNdIbzxPkwLnwVQldPf9swEjQ3SY20vKGCHKCIAiCUCm647mCHIinnKvRGMXvhgM9TXHxP56NIKeUulYp9Zf9/fC0UmqDUuoppVSdqjBSKdXJ/g6aYX9ns5TTt5VS6hul1BGl1Cn7u/GwqrDjXLC/kyc7tMfY78VcxdcZpZQaU5VzCkJZyAO5dEZhuPJ/Xex4KnBbsWPbShn/ELDEoe2YR8wfeAz4FHgJ4yF+H/CnUqqv1trZKmJVTQTwNEb+EWdZgVH1a3NFHZ1kCvCEUmpgsbwsnownhq6Cc55vUuTh/PEnMBmYERtpkV1ZQRAEQXAOTw5dBRHlXMVJ4DPgbVNcfFoVzNcQw6N2MnCMM9WNwzDeF8+VyUAwMBLIwKhsXQKlVAtgKbAa4903A0O49i+tv4uZifH+eaqK5x0FhABTq3heQSiBPJBLZxzwhdY6p9jxDK31skqM31BOv0ygjdb6aMEBuxdYGsbDtrjod84opfzPR54PrfUJjLwiVT3vSXty6PspmpDXk3EmqbO7kI+x+Kgs4ilXveQBPwGvxkZa/na1MYIgCELZSM5ft0dEOcEZNgHvAJ+a4uKrLFWL1vqDYocW2ouu3KuUur8S1Z0roiPwi9a6ogikyRhOFv9xKMLzm7MXU0r5APlOVJd2Gq31QeBgdc0vCOcDCV8thlKqHdAX+KE65tda5zkKcvZj2cA6oFEFtj2jlDqklOqnlFphd2tepZTqX6zfNqXUa0qpiUqpXTh4N9ldcdcopbKUUjuVUi8opbzt58YAb9s/F4TeLnIY21UpNVMpddL+M00pFeZwvkT4qr39gFLqRaXUQaXUAaXUu0opX4c+wUqpj5RSe+z3tEMplVDs9qcDI5RSDcr/ht2f8bbU9kBnV9txFqS/Gd3RmcWAeMpVD9uA/wKW2EjLdWcryEmIRMVIiIQgCELNJ3fcyGAMTxtPxlnRQ0S5s2MecAXQwRQX/1ZVCnLlcBiocG2mlOqulJpvX0cdVUp9pZRqbD9nUUppoC3wYPF3vGLz1MOoDP1eBVWxSxu7SCn1g1LqLqXUZuA09nQ9TrxHDlFK/WpfP+5QSsVWcM0SazOllL9S6hWl1Hb7O+9WpdRLDudvVUr9aV93HlVKLVRKWR3OTwWuAS5xeCd+xuF8tFIq2b5+3me/lo/D+eZKqe/t772ZSqnNSqlJznyXQu1CHsgluQzDRXd1Kec6K6MilS+wHHhSa/17Kf0+tYtHBzCqhD1ZnqeaXaDqBZRbfcxOAPAlRujrXowy9LOUUu211vsc+t2EIfSNxf73rJQaAnyHUcb+YeACjESkDTEqc83ESA4/gTOLkxP2se0wQnKTgVswSqlPAmYopSIq2LmZACwAbrZf8yVgO/CK/fzrGELog8A+jGpeA4rN8RfgA1yMUU3Mk6kNoasgnnJVSTbGv/uPgN9iIy1VUcVLQiScR0IkBMGFKKUURhL117XWn9mPTQVGl9K9k9Y61d6nDvAC0AewAn5a63K91pRSV2J4I6dora3l9T0f2NdwnbXWb57F2DEYaVMCtdbpVWjTuxjf5R1VNaeLGIyxrvVkxFOu+kjHePeKN8XFrz8fF1RKmTDeN3tiRHC9X967llIqFCOaaD3GO6AZeBmYZxeb9mKsX37CeCd7m7LX9T0x3rm0UmoJxvpwP/Au8HIlvPX6YYh/j2Ksl447+R75McY78dsY4uD7SqldWutfK7huwXehMNbMkfZrpADNMN4hC7BgvA9vxhA8bwIWK6W6aq232Me1xFjHjrWP2WWffxTG+/0HGFWq22K823phpLDCPrc/Rp7nY0AbDC9FQSgVeSCXpBewvpSdgZXA38C/GOXnJ2A86PprrZPsfbIwHlhzMR50AzEeSG0pP1zxSYwcdh9Vwj5/DJHvawCl1EJgBzAeI1edIyO01qcd2s8Bi7TWBYvX2cZzi5eUUs9rrXcppbYBlBJ++zSGYDbc7tmHUuofjDx7URgvq2WxTWs9xv55jlKqH8ZDtkCUiwDe1Vp/5zDmS8cJtNbHlVI77H1FlHMNzhR5ABHlqoINGM+Fz2IjLVXqmi8hEs4jIRKC4HLONudvAHAnkISxyXdpeRdRSvlhbBjuPwdbq5ohwLWA06Ic1behMBlIVUq9pLXeVMVzn088PXQVRJSranIx3ue+BGymuPiq/r9TERkYohyccaYojwn2P4fa0wmhlErDeHe9Rmv9DbBMKZUF7K0gHVOB99oHwPvAU8Ag4HmMd4H3KrAlGOjh6CxiF/Ar+x45S2v9hP3zHKVUG7sNlRLlMJ6Vg4ForfUvDsc/L/igtX7OwTYvDA/I3hgOJM9prTcrpY4AXo7flV3wmwx8rrUe63A8C3jX/iw8jPG+eqPWeoa9y6JK2i7UUiR8tSRhFC3MAIDW+i2t9fta69+11j9gLOh2YyjkBX32aq3v01r/orVepLV+BogDRiqlupd2MaXUfzBEuUe11hsqaeNPDtdMx3iQRBTrM99RkLPvuPQEphXr9x3Gv4OK3PYvt183XynlrYyQ160Yi96KdpDnFmv/CzR3aK8CHlZKjVVKhZczzyE8uzIW422pjTB26j0RZz3lJHz17MjEWDgMiI20dIyNtLxa1YJcOUiIRPnXlBAJQXAt5eb8LfZTuAbSWh8DGmj9/+zdd5ycVdn/8c+XIIQSCR2UElAUBP2JIoooRUUpShMp6qNRaT5KV5oKQUQQUDEiiAWCoAiCFAUEBEIHBRQBDdKCTwBpoZfQrt8f1xn2zmRmdmYzO7ubfN+v17x25y7nPnPP7Ox9X+ec68THqFxDtfB18hrvT12reQOSetIjOCIeKeekG72sq+VOJSca+nI3y+2ll3ffXMCQp0vogk6DciO9Z+Bg+SuwB/DGUXtP3GzU3hNPG4KAHOQIog+SwbYtyPx1rawNXFwLyAGUTiNTgQ8026mJWnzgwojYPyIuj4iDyAktDmhj/5vqRm9BZ/eR9d/RvwfeXe5l2/EhYHpdQG4myhQrZ0t6iBz6/RLwVqDVfShl/QrAGbXXUV7LZcBooJbC6e9kp5fxklZos942F3NQblajyR5vLZXhqBeQga5WarnpZtlO0nvIoNgJHQxHeKbBUNiHgWXrltW37i5BdkWuX1573l+utiXIXn8v1T1WJoebtvJE3fMXyfNc81XgHDJP1h2S7pS0fYNyZtTtNxJtzsj9u3NPucHzMnApeWOz7K7rjPv8ruuMu6oXB5Y0StKCytyUnQyRWJDs7r8bsD7Zc3g++oZI/JfszbIOfV3/6800RELSS5KmSTqgtEb2Z13ynO1H5nipDpEYTQ6RGA+sTg6RqC/zl8A/yMDgheQQiY+3cVxgpiESXyZ7SW9K9ipeorLZODLI+inyfE0jh0isXNYfSg4j/ht5rtah9JouQyR+T/bu2Rw4hBwKcXhf8fyK/A7emeztcRh9retmcwzNZs7fdnv/lhuofckb83brNqkEz7eUNKUE0a+W9La67ULS3pKOkfQIcGtl3VfL9c8MSXdJ2quybgJ5c75iJXg/qbL+A5KuKA0lj0n6uaQxlfUzNSjUGk+U+SxPkPRk+e49RNlrpLZfO0H/s4DPVPcbYf4fs15Dj0TuKTdwU8leYKuO2nvi2qP2njhx1N4THx7KCkXEzRFxdUT8gLw2+7KkN7XYZVka9+x9iP7v8epNLz8vr1t+GbCcclRFK43q0cl9ZP25f5j8vC5BexanScoUgPLdeHE57t5k8PM9ZBqV/u4za3W4gJlfx71lee21bEcO1f0hcJ8yB/yH26y/zYX8hTyr6XTWG6u/i7yo+wmAskfY+eSN+G4dHG9hzTqb6lLM+uVTX69HyS+N+skkli4/p9PadLLlotEQ21l6FnaitGDvDuwu6R3kxfCvJf0jIv5Z2XRsG/Uc7kbq0FVwT7lue5Hs5XoWcN6u64x7bIjq4SESyUMkzIa3buT8bcf3gTMi4ub22gZesyI55PVbZI/nQ8jvlVXqUol8HbiSbDSYB0DSTmT+pB8AF5Hfg9+XNH9EHEFee61C9gDZqpTzSNl3XfJa8hxyeOviZC6pRcvzVo4k/wdtQ57fg8h8xGeU9e3kRbqWvJZ8O43fm+FuThi6Cg7KdWo6OXroVOCaUXtPnN2UHYPp5vJzJTLdRyMP0njCwKXJnGqdaJY3r/aF2F+P20bnspP7yPrXsRT5+W73fvMxWgfa1yFHbG1UyzsKr43e6E/tPnRnsjG13r0AEXE/ML5c99VyNp8naYVy7WY2k7n9C7mRO2hjBqYy5GAT+v+iq10QvbadpGXJi667yZupTnMgbUXJp1JaPTcCftZqh4h4RdJNZG+N4yurtiW/XK8rz2s3saPrLiIvJbvk3tSFXFOt6vkPSV8HPkNe+P2z1Gcesrvwvwfr2INtz3OnLERe9I5Unuhh9j1H9sj6PfDHXdcZ14tZu/rzfrLX29rkDdmxNO/ZBk2GSCjzUX6ATH7brpmGSJTfL5e0HDlEor+gXLMhEidThkiUZdUhEtWgXKMhEhMljWrze7mtIRLAd8nzXL3Q7GiIRGV5dYjEFfQNkVgcuCwi/tNGvc1GotnJ+dsWSRsCH6P/v89GliAD9NeWsm4ir/PGAz+tbPffiNiucsx5yBu2SRFRa/S4uNwgHiDpmJLz90FgRoOGjiOAa+vKvB+4VJm0/LYWdb6ycsxLlLNeb01fUK6doP/t5PCvtXFQbig5KNe/W8lrgPOB60btPXHQctB22brl570ttrmB7E03JiKehtdGZI0jh5i3LSKmSrqdvGep5h/+MHB3DGyymE7uI7cir5Wrz2/q4H75UmBfSR+PxpND1NIGvDYyTtL7yXNVva+vH9kFGSe4HxgXET/vryLl/9X1kg4hGzBWJIOGZjOZG7+Q+3MNcJCkJUtS71rk/I9ka8pd5IXXXuRMLtvWdizDC8aUMp4iZxD9OvD7iPhH2WYB8otmUXLY5jsqLbEzIqJR1L3qeeCwEox7gJzlZT7gR228toPJVtuTgN+SrZqHAj+PiGllm1qLwR6SLgOeKrnuJpBDqM6XdCLZWvFGMiA4KSImt3H8hiRdTd4c30a2ruxEtoZXL6bfSs4kdM1AjzMMbMzIHn7b6fBV95RLT5HfH2cBf9p1nXFDkZukqYiotcBeLelR4GRJ34+IZq2xy5I3YfW6PUTiC5JeXw3+NTlmvdoQif0arOtkiEQ7Cd7bHSLxEDlE4j4y990v6GyIRCPVIRKHkUMkxkq6BdinjQk2zEaapjl/q88lnU8G6A6kg97pJfg9EfhOg2B/Ox6uBeRKve4rgbm1mTkoVz8x1nJkPsxGOX+/TF6r/bVJnRckG5J3qwveX02Ojng3eW3VTKOcv9X8R/0G/SPiZUlPMAJz/r68++aL0EZD/AjhoNysnievJ84Hzh+198Rh32gl6U/kZFe1YPe6ZEPD6S2uyyB72X6ZvM/7Hn2zr95KXn926lvAWZKOIr8nNiB7935uAGVBZ/eRm0g6jGx43Lps02rCxHqXkJ1ffiPp22RPw2WB9SJiF+B6ckbdn0s6kvwOnkAG26qmAFsoZ+KeBjwQEQ9I2gc4pQzjvZAM3q1M/r/ZhkzLchHZ0/jfZA/ufchRHD2ZvddGnrnhC7lTk8kbxY3J6ZghI+mPkMOaliJvqq4D1o+IGyv7TiGDZDuSUfj/kMOPDqtsszSZvwJmHSJ1Hxmlb+U58gvxx8Bq5ZibRkTTG8OaiLhYmavtm2RPtIfJYRoHVza7qtR5DzJv0ZXABhHxb0nvI4eV/ay8vvvJ1ojZnXHrOrIleRz5D+hv5NCzaZVtNiZbiPoLWg5n85ItLG8d6ooMkHvKtedl8sLjcvJi8Opd1xn34tBWqW0eIuEhEmbD1WjamD00Ip6XdAGZZ7ITO5FD4k+WNLYsmw8YVZ4/22CCiapGOajayfm7bJPl7eT8XZRM2H8cjXsWz27O33aD/iM15+9GzDn3Qg7Kpf/Q1xvuslF7T6zPwz3c/ZW+e6KXgXvIkQM/bb5LTuZSevp+nxyx8CLZqLdXLZVHJyLibEmfIycj3IM8r1+JiF93WlYpr5P7yB2BPckOMNPLcZuOSGhwrJC0FdnxZE+yB/UDlFFmEfGQpE8BR5N5ge8EdiXTJ1UdB6wJnEh+1x4CTIiI00u6hAOBL5L3rveQ9/Uvlue3kudtefL/1vXARxvkhTcD5twv5AGLiBclnQpsTwnKlWGcW7ex72/JHmittplK3w3nQOt4FdBwNteyflyLdaeTra/N1gf5pVT/xUS5qWyan6S0cqhu2SyvNXJW2gmV51+n/zxW2wInDubQ2cF2zBarng6cvue5U1YhbxY+QQ73Gyl/h57oobFXyaDJZWQg7qpd1xk3kK79w4GHSHiIhNlw1e2cv/XeSgbRG/WSe5zsJXJqi/0bNVYsxaw9i+vr9WBl26p2cv4+UcqbQONetQ+02LdfHQT9R2rO3zlh1tWaTodijpRrz/7cR46iuRa4YtTeE1v1DB32IuJbZC+1gez7NzKtRqttxnVQ3qm0/s5rtM8GLda1vI+suD8img4rj4jxdc8nAZPqlj1PdpT5WpMy/sSss2tfULfNo/Tl8Kzf/0Jmvn6sepls5DFr25zyhdxtR5GzgL4lIkZsDrM5haT3kvnl5oi8H8dsseqdZDfzH+x57pSxZABi/fJ4O7MZtB1EnughBXmTdVl5XLHrOuPqexsMex4iAXiIhNlI0u2cv/WOJSdLqNqf7Dm8C/3/TS0l6f2VnHIrkDNMn9TPftPI4NmnmPkmb1vy/25thtZZgvcR8ayk64G3RmVSmW5rFfRXzsi9ICMz5++eZE+Zj5bHQHIJDhdzQ0+5l8kh1deUx7Wj9p5Y///UzGzEGYlfyIOuJNT9EnlzNRIvMuY0iwGfj5yldY5yzBarPkEGMs4C2PPcKYuRU3OvT+YkfCc5NGU4mFt7yt1D9oSrPf666zrjHhnaKnWFh0h4iITZSDLgnL9l202AhSgjDSTVemz8NSLui4i7qPuOkDQeWKLNvLmPkkH02uyr3yaHr05qtVNEvFpyEp8g6TEy2L8+2fhxYPRNujUFWLrU6Tbg0TL6Yl9yUodXgTOBp8m8cJuRs9AO6Dq2nNt2gv5rkY1V19aXMdzNO/G8Z4A/lAcv7775imRw7iNkALi/4b/DSadBueFybdnKdLJ3/rXk3/9fRu098dmhrZKZWfdpBI8GNJvj7XnulNeTQ1xrQbq1GLpg+kbHbLHqn9vd+KfXTX2GvAEaKV4hb3r+RvZ4+hvw95HYC85ak7QBOdT47f3MTGhmw4Sk+cihnntGxCll2WgyCP4eZs75OyHqZiktM0Sv2KDoL5ThT42OOQlYIyLW6qduk8hh898lew6vCNwI7FL9jpEUwG4RcWyDMr5KBvdXIHvP/TgiflhZPxo4ngy2LQmcXBvGVUYUHELO8jyKHNL3J+CQiHiyBPJOAsZExDOSxpFpCj5RHXpffb2S5id7D67HzEH/AyLi1so+PwLeEREbtjpHI9HLu2/+BuC9lcdaZO/w4eiYeSeet1e7G7/yg93PpoOJUAbZE2Sv/Zkeo/aeOJAJV8zMRhwH5cxGkD3PnbIQORxmzcrjbeQwtsH23mO2WPUv/W8GP71u6jx0nt+kV54gexvdWx53kQG4W3ddZ5x7F80FHJQzG5lKAOjNEbHZUNelqt3g3ZxGUi0AuH/JPzVHe3n3zUeR11zvoy9Q9zZgnqGsV3H0vBPP6y8/82te+cHufwA+Poj1qRdkz9G7mTn49s9Re0+crdyHZmYjnYevmo0gx2yx6rPkDLlX1Zbtee6U+YHVyVl9Vydb69cgh+90UyfDV4dy6OrzwFT6gm4zPdzzzcxsxHLO3+HlU+T/3JaTnM0p5p14Xi1lwK3AzwFe3n3zMWQPuncDq5E5kFcjUxH00lDmlHuBTBNRfUyre/7gqL0ntpq92ApJInPn/SAiTi7LNiLTWKxD9sQ9pEycV91vdTK1yDuAxckZnC8GvhURD9ZtuwWZ5mMVsqH6kDIZYMdl9VrpNX0gcE5E/H0A+08FzoyIhpNADLBObyTznr4jIu7pVrk293BQzmyEO2aLVWeQwy1vri7f89wpi5DBuTeR/8BXKI8VyaEoC3Z4qE4nejiZHL66cOXnwuT3TpTHq3U/G/0+g5z5rvqY3mDZ48DjI3jmU+uRRjNFm9nw55y/w46AL0VEpwGhOca8E897mux5fXl1+cu7b74UfUG6N5PXYrXHYKT26PQ9uITMD6jymKf8fBV4lpykqP5no2WPj9p74kiceXc425YM6v6msmxjMkB2KbB9k/0WIRugf0Xmt10JOBh4t6T31P5OJX2AzGV9HLA7sClwmqTHI+LiTsoaIvOVukwlg5ed2oouz04fEfdLOh04iMzXbNYRD181m0vtee6UJZg5WFcL2C1FXgzUHrXg3ULHbLHqc0NQVTMzM7M5wsu7b740GZxbjswPWH0sUfd7uxMyTJh34nmHdL+21muSrgEmR8Q3KsvmKbMgI+lR4Nj6nnJNytqI7OH27oi4uSy7CHhdRHyost0FwOsj4gOdlNUtpXfg/JWJbVptuzA5oU3TfKBDoQQ7LwXeEBFdDfrZnM895czmUsdsseqj5GxxN7XargyPHeuAnJmZmdnsmXfieQ+RwwFbenn3zUU2jlYDda8newrNX/k5P3DFYNXXekfSm8kJW75aXV4LyA1ALTg0Xyl/fmBDsodc1W+BkyQtEhHN0tXMVFYjlUlkPgNsQk4m8jzwk4g4pLLdBPI1bgn8kOwFuCM5g/VKZdmHyN6bk4G9ygzZkAE5Sn1PKr+vFBFTy4Q43wZ2IDsZTCEnp7mgcuypVIavVibqOYAcsvsmMtf0LhFxe2W/LwF7AyuTPUVvB/63ss015Eie7YGfNDtHZo04KGdmLZXhsf1ePNrIM9h5SyQdAmxdyhGZb+Ooat6SSnk/JGcafg74HfD1iBjSocjOW2JmZkNl3onnBXmTPx0P155bfJgM+Nwy0AIkzUPe469Ezgb9V6A2UdubyMnhptTt9i9yCPNbyvbtlNXKUcAfgW3IGZwPlvRoRFSDVQuSqW6OJD/fD5Sg4aXAS8BO5LDsQ4ArJL09IqaTwbrLyJx455eyateeZwJrk8Nb7yaHAp8naa1+ruNWKHU+jAwiHg2cIWmNiAhJ6wE/JYenXkcGx9chh/kCULa7HvgIDspZhxyUmwtUbuIWAsZ040ZX0mrAz8iZQBektFA02XZF8ov8Y8Bo4E5gv4j40+zWY3bUz5YmaTxwEl06R5XjbAssOJy6WJsVg5q3hLxomQT8k5yNdxvgt5JeiYgzASQtQl5c/RvYjgzyHUnmjNqyK69y4Jy3xMzMzHrl3cC/ZqNnHMAF5D0X5GiYTSvl1SYgqZ/07PG69e2U1crtEbFL+f0iSUsBB0o6vrL/AsDeEXFubSdJu5IBsrfUGh4l3UBORrELcDh9QcO7I+L6yr4fBjYDNoiIWs/RiyW9BfgGOTFNM4sB60bEnaWseYCzgbeSAcy1gX9ExOGVfc5rUM4tZDDRrCPDYQpvG3xHkclYu13mWGBzsqWg4Uw8kpYnWxTGAl8o259CfhEPN+eTr6XbwzS3xTfPNjztDpwSEdUZ0b4eEatHxJfI1sJZRMS1EfHliPhNREyOiJPIi5B3kgG92nZ7RcT3I+LCiLg4InYGrgU+Vynuf8nvg09ExB9K8HpHYAtJa3XzxUL2DizDGwZdRPwtIv4zCEWfBOwgafFBKNvMekjSGyU9IylKrqRulLmapKskPVvKHddi2xUlnSZpuqTnJN0iaeNu1GN2SJok6cbK8/HdPEeVcrctjbJmw8EyZGqZ2bEb8D7gf8gJ1i5scN1Tn1ReTZa3U1YjZ9c9/z3wBjKPYrUOF9ZttzZwc3UkQERMI4eGNs13V3yEnLzkGknz1h5kI3N/15NTawG54p/lZ62+fwfWlPRDSeuVkRSNPAosVUaimLXNQbk5nKQPkj1fju5y0asCl0TEpRFxfUTMaLLdUWT34c0i4tyI+HNEHB0R9V/WLUl6naR2k90OSEQ8Ul7L7LROmY0IlbwlZ1aXdytvST/bVbd5J3BjRFRbbS8mL9Y2a1aIpHHlBu3Tkk6R9LSkhyUdXLfdBEmPSvqApL8CL1BaSyWtJOkcSU+V/f9QzktNNW9JVG9uJY2WdKSk/5M0o9zIblp37KmSjq48nyTpRkkbSfpHuWG+ugzfre73JUm3S3q+1P2Kum2qeUvMbGRzw2l73HBqc4PRQLN7qrZExJ0RcUNEnEr2clsT+HRZXesRN7Zut9rzmXrQ9VNWKw83eb5sZdnjEfFi3XbL0jhlzkNkb7ZWliCDmi/VPSYAy/ezb33PwVq9RgNExJ/J78j1yBx3j0o6TlL9TMozyJGIHo1oHXFQbg5Wglg/JhNett3qIumdki4tLaaPS/q1pKXLunGSgsxJsFe5SZ3cpJxFyHxSx3V6oy9psqQzJe0s6W7yRvoNZd0aks4vN9FPS/qdpGUq+25Q6vVRSX8sN77/KV2iWx1zllZYSQuUG+/7yo33vZIOr6z/XLmpnl7O1eWq9O5RDpH9JLB+5aZ+QmX9FuUm/QVJ/y3Hel1l/XKSzijBhucl3S3p0E7OpVkTXclbImk+SW+lRa6R0lo5VtJngI+SeTlqRtN38VPzMvAqsFob1TiKvEnbBvg5mbfkK3Xb1PKW/IJspPiL+vKWrEb28htPDsO9QlLtwq82M9l3yJvB6s3tmWWf7wKfKK/9PEnv7Ke+1bwltUTEZ9RaVdWXt+RUMknyF8nehTPlLQFqeUvMbIRyw2n73HBqc4npzBowG7CIuK+UuXJZdDcZqFq1btNVyeuuprkLG5TVylJNnlcbCOp75dXW1+8LsHQ5divTgfuBoDxKaQAAIABJREFU9zR4vK+fffsVESdHxLtLXb5OXgN+q26zscAzdSNQzPrloNycbVfyhrftZJOSliRbABYkW0J2A9YHLlF21X2QvDH9L5mHah1y+Fkj7yKTiYakayS9JGmapANqN6D9WBf4MrAfedP7ZOnFck15Xf9DfiGuDvyhQZm/BP5BBgYvBI6X9PE2jgu8lgT/3FKHnwCbkvmllqhsNo7Mq/Up8nxNA66UVPuHdShwOTmLT+2m/hel/G3J7tx/IVunDwF2JvMl1PyKbN3ZmbxBP4ycZctsdnUrb8kMMt/GYsDH68uT9D7yAvBxMr/cHhFxTmWTu4D/Vw1Gl7qNov9WUSh5SyLiooj4Bvl3f6AyH0hNLW/JCRFxeUTcQbZ4rgBsEhGnR8RZ5M3xkmTeEqjLW1K7uVVf3pJPRcTxZWjujmTw7Bv91Hexst/pEXEesC/wNjJvCVTylpShwedFxAERcW1dObeUbc1sBHLDqRtOzRq4g2wg7IrSaLo4mQeYEqC/nFnzq20HXNdi5tVZyurHVnXPtybvIaf1s98NZH7i186BMjf6+4Gry6KZerFVXEr2lHsmIm6sf7RR57aUBoITgKvI67eqcXhSFhsAd62cQylzDR0KfDYiXmovBgbAPuXnxyLiqVLWv8kvyU9GxGnA9ZJmAA9WE2w2ULsIOwE4HvgmOQ33d4AngeP6qctYYM2I+G/ldf2EDAhuUuvyLOkfZFBgU/pm4QG4MCIOLL9fVAJl3yRnA2rHR4GNgC3KzXPNr2q/RMS3K3WbB7iEbJH5LPDtiLhb0nRgnrpkpCJbqH8VEf9bWT4D+ImkwyPiMfKme4eI+EPZZHKbdTfrT7fyliwGrEL+bV0oad2IeKGyza3k38RYMpB1rKSnyncJZO+2PYAfl5uhxcnvhlfKoz+N8pbsSOYBqeVzaztviaSO85ZUll9K/8OgWuUtmULmLTlS0g/J13Z9g+EdUMlbUnrOmdnIUm04/Uw7O1QaTv9FNgQuTPZSvqQEm2oNp2eTE+j8GHiqSXEzNZyS34kPlfoc0cb3yrpk8G8/srdyteH0RrLhdBR5LfoHSWvXlflLcqjsj8kb9uMlTYuItq7RKg2n65Rj3AS8EfhgZbNx5DXb3WTahE+TDadrlO/+Q8nGmbH0NTBPK+VvC5xGXsMeWF7r4WSHhtqM2r8iG312Joe/rcysPZDMOnENcJCkJSPikdpC5aR57ylP5wPeJmkb4NmIuLBsczQ50uAG8vO4Gtnwdzfw28oxDgUmSzoGOIe8f9qUbJikw7KaWV3SCcBZ5JDPL5GNsv01AEwiv1MulHQQeR04gbzmOQEgIl6UdC+wraTbyEaBf5D3YBeR34ffA24nJxx7JzA6Ig5oo94NSTqEvN6dXOqyJtlpZf+6Tdci30OzjjgoN+c6DLghIi7ocL+1gYtrATmAiPiLpKnkjeppzXZsoNZT5cKIqH1pXS5pOeAA+g/K3VQNyBUfIYehvVq5Gb6XnB1xLWYOyjW6WZ8oaVREtHOz/yFgel1AbibKWWi/S7bgVLtbv6Wfst9CXgieUXdTfxl5kb4GcAV5g354CbJeNkhJ423uNJrZzM1TCS7dIOkq8m/x08CJlW2eJW/QAP5cemd8j/JdEhFTJO0M/JDsofYqObNz0DivSL1WeUtqfy+d5i1ZsZ9jVvOW1Ovvu6XfvCWSvkBOwrEH8IykU8kJOJ6t7FfNW+JhEmYjiBtOATecmjUymRyGuTEZtK7ZkJzkqeZT5XEfGXyGvNbajQwSjyavgc4CDq9eP0TE1SWg9x1yNNC9wKcj4uJK+W2V1cK+wMfLPi+Q33fH9rdTGY3wEeAHZOBe5DnZOiKqw1d3JYf9/5kcQbRSREyVtDUZRN+TvM+aTt5L/biNOrfyV2AvMpfvGPK8TwB+VNtA0hLkSI99Z/NYNhdyUG4OpEwI/kVgPUm1vAQLlp+LSHolIhrOqkjeqN7eYHk7CTbr1b48L69bfhnwBUmvrwb/mhyz3hJkC8p+DdbVJ/FsdLM+bymjnZv9xWmSHBlA0hgyIf1DwN7kF/QL5PDU/mYmqg2BbRY0rb2W7cgA6w+BsZJuAfaJiEvbqL9ZK9PpuymbbRFxX7m56S/XyM3k3//rajk3IuJESb8he9w9TLZCPkYZ6t2P2clbsnqD5Z3kLdmyjfp1LCJOBk4uvWK2Jv/+n2LmFlnnLTEbudxw6oZTs1mUXmCnksGfUyrLJ5G9yFrt+1va68VGSSNyTov1bZfVxJMRsUOL8ieQQa1G6+6hn+urEkB8R4PlM8hUQwfPslPfNuPqno9vsM1U+makpfTg7a/B4JPk992V/WxnNgsH5eZMq5BDEq5rsG4a2fKwY5N9WyXYvKnDevyryfLal1x/XZgb3UhPJy/kGt2s1w/Fa3Sz/nKD7Zp5jJlnCaq3DjnkbKOImFJbWHoC9ad2078zmW+uXi33w/3A+NLCuzb5D+w8SSuUVlqzgbqD/Ax3RQe5RtYFptUHk8qQ11tLWZ8nbxjPaOPQW5G9PGo6yVvyOUkrRcS95bi1vCUTyjat8pbsQwbFpjBIytCVE0rLr/OWmM0B3HD6GjecmjV2FHCHpLdEhP/PjwCld+0ewGFOKWID4aDcnOlqsptz1cbkRdKmwD2z7NHnBuDLksZExNMAkt5D3gBe3WK/WZRuxLeTszyeUFn1YTJx+jOdlFdcSrZQ3tTGl95WzJxHaquyXzstsLVj7Svp401ynCxQfr42q5mk95PnqhrAfJFZLwDvIHvajIuIn/dXkZKD4fqS0+Bacnidg3I2OwY1b0kp5yRyQph7yNxHW5Gtv1+uHO/15OQIV5YyNyQDXjvVDVVoxnlLzGwkccNpcsOpWQMlv+2XyM+3g3IjwzLAr5l5yLFZ2xyUmwNFxKPU5bWQNK78elU/wbAfkDfMF5WbzVoS4VvJm95OfQs4S9JRZIvlBmTy388NoCzIC56/AOdLOpG8eHsjmVdkUkRMrmy7iaTDyCEGW5dttujgWLUb799I+jY57G5ZYL2I2AW4HngG+LmkI8mLvwlksK1qCrCFpC3JC+4HIuIBSfsAp5SgxIVk8G5lssv2NuRF+0VkfpR/kzkT9iHztTS7mDZr12QGN2/JE8ADZI6gZcrzfwKb1Q3ZeoUMPO1EBrpvI2cnbTqsoo7zlpjZSOKG0+SGU7MmyvDREad+2OfcIiIeJHvNmg2Ig3I2k4h4RNKGwPfJ3CQvkt3392qQKL2d8s6W9DmyJ8we5M37VyLi1wOs378lvY9MTvoz8qLrfvLi7K66zXckb5j3Im+Yv9Iq90iDY4Wkrcib/D2BJckgw2/K+ockfYq8YT8XuJO8ga+/UT6ODDqcCCwKHAJMiIjTJT1F3th/kQxO3EPmLHixPL+VPG/Lk0n5rwc+2mJoi1lbBjtvSUQ8SSbT7q8ez5IJuwfKeUvMbMRww+lr3HBqZmYGyMOebU4jaQMyR8rbI+K2Ia6O2bBVEnrfQc6gN6KGSJSb2HuBTzTpJTFHKnlLbgeOLAFUMxvhJI0neyiP6a+HmqQ1yYbT9zFzw+lDlW2mAmdGxNfaOPZnyYbTN5ENp0dHxE/72Wcy8GhEbNNg3apkw+mHmLnh9NAyLG8D8hptY7LBc32y4fS7EXFcpZxJwBoRsVZ5Pp66cyRpAbLhdHsqDacR8Y2yfmOy4fRNZMPp/mTD6Wt1Lz2Pf17qsShwSGnMQdImZMPpu5i54XQCMIrslb0eMzecHhARt7Y6f2ZmZlUOytkcx0E5s/ZJ2h54MCKuGOq6dGIuDsotS/asPaKDYV5mZsOCr9HMzMxm5uGrZmZzMectGVmct8TMzMzMbM7hoJzNcUrOkrnuZt3MzMzMzMzMRg4PXzUzMzMzMzMzM+uxeYa6AjZ8Kd0i6fOVZYdIulXSU5KelnSjpO3q9ltd0p8kPSBphqT/SPpFyYXU7FhbSgpJNw7ma2qXpI9K2nOA+44vr2XhLtfpJ5J+2c0yzczMzMzMzGxoOChnrWxLzkT1m8qy1wOTgO2AT5JT0P9WUnUGrkXIBOxfAz4GHAx8BLhA0ixDpiWNBn4APFS/bgh9lJwVbCDOB9YhZ+LqpqOAz0h6c5fLNTMzsxFiNhpNx5VGw/rHb+u2m9Rku1V79RqbcaOpmZnNaZxTzlrZHTglIl6qLYiIveq2uVjS6sDngDPLNtcC11a2mSxpGnAx8A4ykFf1deB+4G5gja6+ggpJC0TE84NVfk1EPAI8MgjlTpV0NfBlYJ9ul29mZmYjQqtG038CrwDbkI2mr0TEmXX7fw24pvL80QbHmAJ8oW7Z1IFXuWs+Sr62Ywaw72A2mk6RdHhE3NXlss3MbA7nnnLWUOmN9X5KoK0fjwHztbEN9dtJWgHYF9ijg7pNKi3AW0qaIukFSVdLelvddiFpb0nHSHoEuLWy7quS7izDa++StFdl3QQy6LVipXV4UmX9ByRdIek5SY9J+rmkMZX1M7XEVlqmt5V0gqQnJU0rrdrzVPZbTtIZkh6W9LykuyUdWvfyzyJ7y/lv18zMbO7UsNE0Ir4fERdGxMURsTPZQPq5BvvfERHXVx6NAknP1m1zfUS8MBgvRtICg1FuvYh4pLyOV7tc7lSg1mhqZmbWEd/YWzMfBp4Fbmm0UtK8ksZK+gzZavnTBtvMI2k+SW8FjgD+CvylbrPvA2dERH3vuf6sSA55PRT4NDlk9qIyFLbq68CywP+QF7FI2gn4MXAe8Angd8D3Je1f9vkF2fr8X7JFdZ1yHCStC1xa1m1DDnHdFDipjTofCTxT9jsVOKj8XvMrYHlgZ2AT4DBg/royrgWWBt7exvHMzMxsDjIIjaZd40ZTN5qamVnnPHzVmnk38K9GrYmS3gdcV56+DHw1Is5pUMYFZE45gJuATavlSdqwrH/LAOq3BLBFGSqLpJvI4a/jmTlA+N+IeC2nSrlYmgBMiojaENCLJS0CHCDpmIiYJulBYEZEXF933COAa+vKvB+4VNIaEXFbizpfWTnmJZI2BrYGzijL1gZ2iIg/lOeTG5RxOzksZW2aBEzNzMxsjtVvoymwMLAZ2Wi6fYPNTpK0GPAwcBrwjQbpPd4m6SmycfCvZZsr2qhfrdH0W8DzwCFko+kqdT3tvg5cSTaazlPqXms0/QFwEbAh2Wg6f0QcQTaargJ8CNiqlPNI2bfWaHoO2eC5OHnNtigzN4A2ciQZVNuGPL8HkddbteuzXwELkI2mTwArA/X59aqNpr4+MzOztjkoZ80sQ+McI5Atmu8BxpIXfcdKeioiTqvbbjdgMfIC6pvAhZLWjYgXykXjROA7EfHfAdTv4VpADiAi7iuBubWZOSh3ft1+ywFvIHvHVZ1ODjt4O3nxOQtJC5K95nbTzBNWXA28RAYyWwXlLq57/k9ghcrzvwOHS1ocuCwi/lNfQES8LOkJ8v0xMzOzucvsNJrOAH5CXo88BWwA7Ae8Cdiist3fgBvI65Qlyd5pl0j6QETUj3io50ZTB+XMzKwDDspZM6Npkgg3Ip4FbixP/1wumL5HtrZWt7uz/HqDpKvIGVk/DZwI7EQG9U6WNLZsNx8wqjx/tporpYGHmyxbtm5Z/YyuyzZZXnu+WItjLgqMAo4rj3rLt9gXsnW16kXyPNdsRw5Z/SEwVtItwD4RcWndfjPq9jMzM7O5w4AbTSPiQeCrle0nS3oIOE7SOyPi72W7H1ULlXQ+GaA7ENiyn/q50dTMzKwDzntgzUwnL+racTOwvKTXNdsgIu4rZa5cFr2VvAD7L/B4eewAvLP8vl2DYqqWarLswfpD1z1/sLJt1dLl5/QWx3yilHcwedFb/zixdZVbi4j7I2I8OeRiHfLcnFcuAqvG9lNPMzMzmzONJhvnZhERz0bEjRHx54jYCziFbDRtpZab7l3NNihDWy9otU3FUDeavlR5zABeR3caTW8kG03vk/R3SR9uUI4bTc3MrGPuKWfN3EEGhtqxLjCtVc+2MtnD4mRvOYBjybwfVfsDKwG7AP/q55hLSXp/ZXjECuTFYn8TLkwDHgA+BVxYWb4tOZSjlmy4/oKMiHhW0vXAWyPi2/0cZ8DKkJTrJR1C5ihZkTJ7raQlgQWBfw/W8c3MzGzYmk77vbFuBr4g6XUtrtGi7mcr7WzTrNH09n7K6kaj6QQyeFjvgRb79isi7gfGlyG2a5fjnCdphYh4rLKpG03NzKxjDspZM9cAB0laMiJqSXRXJINevwHuIRMJb0UmEX5tGnhJR5O5TG4gL5RWA/Ylc4r8FiAi7gLuqh5Q0nhgiYiY3Eb9HgVOkVRLJPxtsiV2UqudIuLVMnvXCZIeAy4B1i/1P7CShHgKsHSp023Ao2XK+33J/CSvkq3LT5NDHDYjkyAPKFhWhgBfRCYT/jeZWHkfsrdcNUC5FnnheW19GWZmZjbH62qjKX2TINzUbANJC5CzwjfdpsKNpmZmZh1wUM6amUy29m1MDn+ADLA9QE7asEx5/k9gs4iotkzeSE7ysDN54fQfclarw0s+um64D/gumdh3xXLMHepm9mooIn4uaX5gT2AP8kJwn4j4YWWzM8hZv44kkxyfDIyPiKslrUfOJnYKOVziPuBPzDrkohMvkBece5DDLJ4Drgc+Wjcj2sbAFXUts2ZmZjZ3mJ1G0wnAmFLGU8B65Cyov4+If5RtFgH+CJxKNp4uAewFvJEMkPXHjaZmZmYdUEQ7PdFtbiTpR8CbI2Kzoa5LlaRJwBoRsdZQ16WXJNUCgPtHxKlDXR8zMzPrLUnzkUM994yIU8qyRchZVT/AzI2mR1cbTSVtD3wNWAVYgGw0/Q1wWETMKNuMLsveQw4lfYGc0XVCgxlP6+s2CViDWRtNd6nOfiopgN0i4tgGZXyVbDRdgWw0/XG10bTU73gy2LYkcHLJx4uk95KNpu9n5kbTQyLiyRLIOwkYExHPSBpHplX5RET8sf51RMRapRH3WDKAWW00PSAibq3s8yPgHRGxYatzZGZmVs9BOWtK0nLkMIk1B9rCOBjm4qDc9sChwGoR8fJQ18fMzMx6z42mw4sbTc3MbHZ49lVrKiKmAV9i1hmzbGgI+JIDcmZmZnO1o4ANJL1lqCtiQObBe56SN9nMzKwT7ilnZmZmZjaClN7zD0bEFUNdl5q5uKfcDsD9EXHlUNfFzMxGHgflzMzMzMzMzMzMeszDV83MzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMzMzMzMzMysxxyUMzMzMzMzMzMz6zEH5czMzMzMzMzMzHrMQTkzMzMzMzMzM7Mec1DOzMxsDiNpnKQoj3FDXR8bGEmTyns4aajr0i5JoyTtLelvkp6tfA63HOq69YKkyeX1ThjAvlPLvuO7XzMzMzMbjuYd6gqYmdmcSdIo4JPAx4H3AUsBCwJPAP8GrgJ+HRG3DVklzQaoEnSZFBFTh7Aqw80xwFfL7y8CD5XfXxia6piZmZkNXw7KmZlZ10l6H3Ay8JbK4peAp4HFgXXLY39Jvwd2iIgXe17ROddLwB2V3637Di4/JwNTB+kYD5Lv44ODVH5XSRoD7FKe7gscHRExhFUaae4mg5dPDnVFzMzMrDcclDMzs66S9Angd8D8wGPA0cBZEXFnWT8KWJPsRfe/wNZkDzoH5bokIu4HVh3qetjsiYgDgAOGuh4dWBV4Xfn9eAfkOhMRHx7qOpiZmVlvOShnZmZdI2kV4FQyIPdP4GMRMa26TUS8AtwI3CjpKODEnlfUzAbDgrVfIuKZoayImZmZ2UjgiR7MzKybvgO8nhyCtVV9QK5eREyPiC1pMFxL0jKSjpJ0u6RnStL42yUdKWnpRuXVT3AgaUVJP5f0H0kvSLpb0nckLVTZZw1Jp0r6v7LNnZK+Kel1TY7xWiJ3SfNJ2l/SP0r9Hpd0iaRNmr1mSUtJ+qKk30v6l6QnJT0v6S5Jv5C0eot9X0v8r7SjpKslPVZNEN9qogdJG9TWledvlnRief0zJE0r5+yNzepR9nu7pN9K+m85b/dI+nF5fTMdoxPlvIakyeX5tpKukDS9nOObJH219Lgc8DmqbL+IpIMk3SzpqfJe3CnpeEkrNyu/sujyyrkOSVOb1GtLSedIekDSi+WzcqWkXVt81ppO9FD3OZSknSTdUF7D05Kuk/TZJqcZSfNK2rmU86ikl8o5ukPS6ZK+2GzfBmWNL+dkcmVZ9ZxMbrDP1pL+KOmhcj4eKs+3anGcfidRqP/8NNt/IOeslDGqfP5uLp/H6aXcbVrt1w61mOihci43kDRG+T02pXxeHyvn7r2zWwczMzPrLfeUMzOzrlAGymo3pr+OiH+3u2/9MDdJ6wPnAGPLoueAAN5WHjtK2jwirm5R7LuAX5YyniL/560MfANYT9KHgY8CZ5A9fJ4E5gPeDBwKrAFs36L8+YA/Ax8EXgaeKcf6CPARSYdExIQG+x0JfL7yvFa3N5XHZyV9JiLOanFslXpvA7xa6v5qi+0bFyJtCJwHLEzm+5sHeCOwI7CppLXLUNj6/bYCTqdvqOIzwLJkgv9PAgd2Wpcm9fsemZssyAlCRpPv67uAj0vaIiJmNNudfs6RMgD6J2C5sugFMgffm8vjCw3eiyfJyQtqgeHHmXno9SN1x1gYOI2c8KTmKWAR8rPzQeBzkjaLiMebnozmRgFnA1uQn8PngDHk5Crvk7RKRBxc3UEZ0LwA2KjudS0ELEbmgtyW9nuxPk+ek/mARcuyhyrrp1eOPR/wK2C7sqj23iwBbAZsJuk04PMRMVj5EDs+Z6Xu8wPnAh+r1P1FYD1g/fJ5HWzLAjeTn88XSh0WI8/dRyV9IiIu6kE9zMzMrAvcU87MzLplQ/r+r5w90EIkLU9fQO6fwAciYqGIWJi8+b2DvPE/V617c/0SuAlYPSIWIW+6dwdeIQMhBwG/Bv4AjIuIsWQvv8PK/ttJ+kiL8v8XWBvYFRgTEYsCKwBnlvUHS9q8wX73kj0K1wQWLnWbnwwC/rr8frKkN7Q49tbAlsDXgEUjYjEyyNPpzfhZwGXAahHxejIosx0ZoHsDcHj9DqX32KlkQO5mYK2IGEMGNjcigxQ/6LAejbyTDMgdCyxdXuOiwLfIIN3HGtWvouU5Uk5K8AcyIHc/GdRYqJyHdwLXk+/FryX9v1qhEbFHRCxTPU5ELFN5vKeuHqeQAbm7gE8Dry/v+YJkUOgeYB0GPoz7K8AGwPhK2cuX1wbwTeWw8qodyPfqBTIAO6Z8/hcgg41bk5+NtkTE6eWcbF1ZVj0nW1c2/y75GQsy+L14eW+WKOtq9Tu03eMPwEDOGeTn7WNk3b9Jfq4WBZYBjgf2Iz87g+kn5N/Yh8i/14XJ76E7yL/JEyT5+t7MzGykiAg//PDDDz/8mO0HeRMd5fGG2Sjn+FLGdGCZBuuXI3vWBHBs3bpxlTrcBszfYP9fVba5GFCDba4s63/RYN3kyv5fbLB+HuCKsv72Abz+P5Z9v9lg3aTKsXdrUUb1PIyrW7dBZd1lwDwN9t+trH8OmLdu3S/KuoeAxRrs+1Yy2BOUTpAdvv4Jlfr9qp/P2kv1n7UOztF+ZZsXgTUarB9DBlAD+GOD9bVjbNDiGJuVbR4E3thkm+XInoYBvLPJa5nUz+dwwwbr5yeDjQF8o27dcWX5CZ2+P/28d699tpqsf2N5zwL4bpNtvl95X5Zt8pontPH5mdzlc/aGSt2/3eTYv6mU37SOLeo+tew7vsXn7WFgqQbr317ZZt1uvq9++OGHH3744cfgPdySZmZm3bJ45ffpTbdqQZLIYXMAP42I/9ZvE5mn7qflaavhpT+MxkMbq73JjoiIRnnPatu8o0X5/wec1KB+r5I94QDeJuntLcpo5Pzy8wMttnkcOKHDchv5bqlvvXPLzwWA13oMlffnk+Xp8RExy/scEXeQw0a74dtNlh9OLbjFAAAgAElEQVRFDpmct1Kfev2do9rwyTMj4rb6lRHxNDnUGGATSYv0X91Z7Fh+nhINhgGX40wDLi9PP9Zom35cExGX1y8sn/1mn+Mnys9l6K1Pku/ZC8ARTbb5DjCD7PU123namhjIOduGrPvz5IzSjUzoVgVb+FlEPFy/MCJuJYPI0Pp7y8zMzIYRB+XMzKxb1IUyViLzI0Hma2vmkvJzcUkrNdnmL02WV3Nd/bWfbRZtsh6yJ06ziQyuJHNVAaxVv1LS/5N0nHKCiKckvaq+iRGOK5stV79ftd4R8WKL9e26ocnyByq/L1b5fWX68vxd0aLcybNRp5r/i4i7Gq2IiKfIocnQ4PwWTc9RyWtWC1y08zmbh8xj16laYHVn5YQYDR9kHkKAFQdwjGbvIfS9j4vVLb+A7FG1uaQLJe3Qz3Dpbqm9V38t7+EsIvPq3Vi3fbcN5JzV6nJji7r/m+xpN5gGUnczMzMbpjzRg5mZdcujld8XY+bATruWqvze6ua2OqvrUvT1EKl6usm+tWBZrTdUq20azopZNK1fRMyQ9BiZn6v6mpD0VeBH9DWMBTkct9arbwEyt91CNDdLT5mBaPb6I+Ll7BQHzHwOlqz83ur97UZgor8yauuXarK+1TlajEz2399x6j9nbVPOqLpEebpIefRnwU6OUTT7DEOTz3FEXC1pP7JX2sblgaRpZJDyV416knVB7Rz2997WzntH57wDHZ8zOqt7y5mLZ9NA6m5mZmbDlHvKmZlZt9xe+X3NLpTXrBfaQLfrto6PK2k14Bjy/+/vyATtoyNi0ShJ8YG9a5u3KOqVTo/dJdU6tXr93eg1Obvva7vnqNVxosnv7RhV+X37iFAbj/EdHmPAIuIosmfqXuTEKg+TvTPHA5dJ+l0JLA7K4bu8XS8NxzqZmZnZCOWgnJmZdcvlQC0/2VYDLKPau2n5FttVh3Y+MsBjza6mw0slzU9fjr3qa9qGDNb8iwzUNBpi2es8X52ovpZWwx27MRSy1fBd6OuNNJBeg9PpC9q1+pxV13X0OYuIF8gekJBJ+IediHggIo6JiK0iYmlySO8vyuptgC93+ZC196rVOYe+977+nNd6go1use9Acv+1o1b3dj+XZmZmZv1yUM7MzLoiIh4CzipPPy3pLe3uq76xkvfSN0nEh1vsUsvB9VhENBq62gvrV+pd74P0pYi4sbK8Foy4pckEC9D32oaje+ibJGCDFtu1Wteu5SW9qdEKSWOAd5enNzbappUSCP1HedrO5+xV4Ob6YmrVabH/NeXnpyQN+2uuiLg1Inair94bdfkQr+WKazZxhqSxVHLP1a1+vPxsFdR778Cr11K17mMabSBpFfoP2pmZmZm9ZthfIJqZ2YjyTeAZMi/a7yW17DUiaVFJZ1F6t5SJE04vq3eRNEuvsZKQfpfy9LRuVXwAVgA+X7+wBF8OLE//VWZFrHmt51SjgJ6kTehOQGtQlPfn9+XprpJmmQijBCa2rV8+QN9qsnwf8jP2cqU+nfpt+bmNpDXqV0paGNi3PL0gIp6s26SW7H8szf2s/HwL8PVWlZG0UJmAYtCVnpytPF9+dnuY9FnkezYa2K/JNgcC8wMv0Rfkr7ml/PyYpFlyLkr6ELBOd6o6i1rdFyA/f40cNEjHNjMzszmUg3JmZtY1ZfbB/wFeBFYH/i5pP0lvrm0jaZSkNSV9m+x5tXVdMd8le2MtBvxZ0vsr+65LJqIfS/aoO2IwX08/ngSOl7STpNGlfsuTgcINyzbfqNvnT+Xn6sBPJC1W9ltI0i7AmcBjg17z2fNdMmizNHCxpDUhezuWoMhFwHNdOM6TwOcl/UjSEuUYYyQdSF+w7icRMdBJJY4ne2a+DrhQ0ia13myS3k6+jpXIz/I3G+x/W/n5GUkNJ2iIiHOBs8vTIyQdX+1BKmk+Se+V9D3gPgZvYoN650g6sbzm14KKkhaT9E36eg9e0M2DlvfqR+Xp/pIOqR1f0lhJh9IXvPxBRDxYV8QZZK/FxYHTJC1X9l1A0ufJcz2dQVDqXpsZ+VuSDqj1mJO0pKRjgc/SF3g3MzMz65eDcmZm1lURcQ7wIeAucvbJI4A7JdVmJH2RHAr4LbKH3GnAs5X9pwFbkje3qwPXSHpG0jPA1cBqZNBuy9kIyHTDceSQtp8BT0maDvyHvl5i34mIs6s7RMSl9PXQ+jLwmKTHydf6UzLX3ITBr/rARcTdwOfIXkNrATdLeorsIXkpMB99k1XMaFhIe/4OHAnsDjxUPjuPA4eR1y9/BvYfaOFl5tnNydk0lyMDUM9KepIc2vr+Uv/PRMQtDYr4afn5SeAJSdMkTZV0dd12n6XvPd8VuKN8nqeTwc3ryR55i9O7SQQWAL5AvubHJT1ZXvdjwKHkkNwz6csv100HksE1kT3LHivn4jH6gp+n0aCXZAn6H1aefgL4P0lPkL0WJwGX0Rc4Gwz7kZ+7ecjg9OOl7g8BXwG+R35uzczMzNrioJyZmXVdRFwDrArsAPyaDNC9AIwhe7JcTd5crxYRn46Il+r2v6Ls/30yUDUPeRP/L+Dost9VvXk1Tb1I9ig6ELiDHHL3JBmY2iwimg29/AywJxn4mUFO/HArcACwLhncGtYi4kwyIPc7Mhn//GRg4kfkzLu13kJPNCyg/ePsB2xP5jibhzznfwf2ADYukynMTvm3kYHfCaXcl8nXcjcZdFu9vNZG+55K9gq9muwZuCywInU5xSLiuYjYgew9eQrZO3QeYGFy8oDLyKDcKj0MMu9GBpguAO4k/7YWAB4AzgM+GRGfapH3cMAi4sWI2I4MZl5IBuPGlJ8XAls3+k6o7H8Qed6vJ4P5o8j3bley1+2gzUxcPm+bkJ+/v5OfRwFXAdtGxICDxGZmZjZ3UqaHMTMzs3ZImgysDxwSEROGtjbDk6TDyGDlZRHRaiKFRvtOAA4GroiIDbpfOzMzMzOz4cE95czMzKxrJC0J7Fie/qnVtmZmZmZmczMH5czMzKwjknaXtL+kN0uatyybX9KmwJXkhAWPACcOZT3NzMzMzIazeYe6AmZmZjbirEzm1ToceKVMEvB6+q4rniRzbA33mWTNzMzMzIaMg3JmZmbWqZPJhPrrAW8kZw59HrgXuAj40RDPjGtmZmZmNux5ogczMzMzMzMzM7Mec045MzMzMzMzMzOzHnNQzszMzMzMzMzMrMcclDMzMzMzMzMzM+sxB+XMzGzISJokKSRNGuq62PAhaXz5XEztZJ3ZcCRpQvnMTm6wbra/AyVNLWWMn41qmpmZ2RDw7KtmZtYxSRsAGwBTI2LSkFZmmJC0JzAWOCci/j4b5YwDPgC8G3gXsCYwpqxeKSKmzlZFrav8t2CDpQTZxgGTI2LykFbGzMzMBoWDcmZmNhAbAAcDVwCThrQmw8eewIrAVGDAQTlgAvD5LtRnTvUkcAdw/1BXpNgA/y3YwD1Ifp4fbLBuPLB++X1yizLuBl4g/zbMzMxsBHFQzszMbHh5lbzJvhm4CRBw+JDWaBiJiLOBs4e6HmbdEBEHAAfMZhkf7lJ1zMzMrMcclDMzMxtedoqIV2pPyvBIMzMzMzObw3iiBzOzuZSkRSRtL+nXkm6VNF3SC5Luk/QbSe9rsM84SUEO1wNYvyQYrz7Gd7mey0g6QtItkp4sdbxH0i8kva3Ffu+SdJCkK8trekHSE5Kul7SfpIVb7LuApK9Juk7S45JekvSIpH9KOlnSJyvbTijnZMWy6KT6c9LJ660G5LpN0gbVOklas7z/08prnNxgnzdJ+rGkf0l6RtJz5fdjJK3Q5DgzTcYgaSNJF5Zz+Lyk2yV9U9LoAbyGfid6kLSQpL0lXSHpUUkzymu8QtI+kpau275nfwsD/Tz3c07q39e1JJ0p6cFS/l2SjpI0tp9yRpXze5GkhyS9WN6zi8r5UZP9XptoQNLCkr5dzuPTZfm4Dl9PR+9f3Xn4naT7yz6PSrpU0hckjWqyz0yTMEj6sKTzy+t+oXzWD+7vsyppE0mXKL9jninv776SXtfPfrNM9FD7jNM3dPXgBp+tcZXtW070UN7XL0q6rHI+7y/naoMWdZtcyp2gtJOkGyQ9Vd7b6yR9ttXrMzMzs35EhB9++OGHH3Phg8xdFpXH02ReotrzV4Hd6/ZZHvgv8EzZ5sXyvPrYroM6TCrlTGqy/uP/n737Do/rvu98//4BIEAQIEiAIEAC7J2UWESxU4WUKCuSJTcpkuzYluzcxE6cOHbWe5/kOrvXN5u7m92UdXazudnY2bSNEydxYiexE1uyLMvqktV7oUiRYhF7byDO/eM3Y46Hc4YoxAEweL+e5zwD4PzOzHfOnCEwH/5Krq6k4PGOFnx/CvhoyrGFz+0scKDoZy8AbSWOG0ucE67wPBwAzhT8bEtB+8/lnvfZ3L5Dxeekn6/ThoLHnXER7+uW3PnM13yCOKF8YfufKWiT5K6P4wXfHwKuK/E4d+XPE/Cp3DlMSpzHJ4Hmcsf3Zl9u/3LgraLXfn9BDQnwmcF4L9CP67kXr+t7c/eTf31OFezbknYNAe3AI0Xn4WDR998AakscuyW3/98Q50fLP5f8e67H121fXr/ccb9b9HodALoKfvZdYGyZfwfvA/5t7tj88YWPeS9QnVJz8fVTeJ1/H/iP+cfoyb+BwO256yf/3jta4tqaWuL831Xi/scB3yuoravEc/utlOd1X27/fwC+nvv6TO66Kny+/09//l1yc3Nzc3MbyZs95SRp5NoF/FdgDTEYGQvUA7OA38u1+d0QwmX5A5Ik2ZYkySTgt3M/eihJkklF21cvRnEhhFXA14BG4H8CC4H6JEkaib3S/gCoBf44hLCixF3cA3w817YuSZJmYAzwAWJwsAj4wxLH/RKwlBgE3JJ7zGagDugEPgp8J984SZLfzp2Tbfnji89JP07DQPpT4G5gYZIk45IkqSeGcACEEN4H/FHu298krgJZDzQAC4C/BZqAvwspPeaAicRr7O+AabnzOBb4JDG0uQz444v1hEIIU4FvEwOzbcAdxCCmJVf7YmKAsqfo0AF/L1yE67mn/gx4CFiUJMk44ut1OzGImQ78TXGvsRBCLfBPwGpiUPpuoCFJkvG5eu8E3gHeA/znMo/9BeI18QGgMfd6T80de0F9ff1CCL8AfDb37R8BHbnHHpf7eRdwDfClMg+/lHid/yYxrG8mrqb867n9GymxAEsI4T2c6y35t5y7zpuIgfQa4Od68vzzkiT5au7aeij3o98ucW1tK3cfBf6YGNqeBj4NNOXq6wD+V67N50IInyxzH5/K3cdduePHEV+jf8rt/7UQwtwe1iNJkgoNdiro5ubm5jY0N+D3ib0gvlxi3xdI6fnRy8f4U1J6ygGP5fb9epnjfy/X5uu9fNxOYk+obuKH6MJ938rd56/28j63kNJbpZ/naAMD01PuUdJ7/tQC23PtPl7m/r6Ra/PFop/fVfA49wFVJY796YI2K1OO31LiuHL7/iK3by8FPYkuwmvQ7/fCAF/Pha/rK8Swr7jNpoI2P1m071O5nz9Pid5kuTaX594vpyjqYVpw7XcBl/XjPPf69SOGdftyx30lpc0vFjz3FSmvXwJ8IeX4r+X2311i3wsXuM4/UfheKLH/T0n/N/C+cnWVOP93Ff18VcFj/2zKsX+X278HGJ3y+AmwscSxdcRVkBPg83193d3c3Nzc3EbyZk85SVKab+Zur8j6gUMIS4GVxKFSv1Om6Z/nbjelzRlVSpIkbwPPEFc2XVe0+2DudnJP72+Y+q0kff66G4jB5W7gT8rcR/78X1+mzW8kSdJd4ud/Qgz+IPaI6pcQQr5HGMBvJj3vSdQT/XovDPT1XOS3kiQ5UfzDJEnu4VzPq+Lz/X/kbv8gSZIjpe40SZIfEgOoWmKvsVL+NUmSp3pfcr9ev+uAltzXX0hp8wfAztzXH0xpc4pzvR6LfSN3u6TwhyGEJcQet5B+nX+JGFwNhvzrvB34ckqbf5e7bSWey1IeTJLke8U/TJLkFLFnIxSdG0mS1DOuvipJI1gIYRbw88QP2bOJQwuL/8NmStZ1cS78qAJeSZlfHiAfXDQAEygYJhdCqCJ+KL0DWEYcSllqsvbi5/fPxA/uvxBCmAh8FXggSZK9vX8aQ9qDZfblz38zsLPM+a/N3U5P2d8F/KDUjiRJunOT638Y6M9wzbwVQH5S/X8q17CUAX4v9Pt67oV7L7BvHQXnO4QwlnOByn8IIfz7Msfnw6+017vcNXUhfX398s9lW5Ikr5ZqkCTJ2RDCvcBPkX6tvZAkydGUfTtyty1FP8/fV0+u859Kue+BlK/veymBIUmSvBRCeJsYwq+g9Ll/tMxjpJ0bSZLUA4ZykjRChRDeD/wVcQhS3mHOTXBfSwxlGrKvjo7cbTVxAvqeGJP/IoQwhhiuFfboOU2cJ+5M7vsWYgjwY88vSZKv5Ob/+kXOhXqEEF4nziX3v3K9hoa7coFP/vzX0rPzX5/y87253jRp8j2I2nrwGBdSOHff1t4cmMF7oV/Xcy+V65VV6nxP4lz42NNgJa22voSIhXXk9eb1yz+XC/VGy/fKTLvWSvYQzOnK3Rb/3Zy/rwtd59vL7BtIvTk3nfTv3JRdZVaSJJXm8FVJGoFCCBOIcxnVEXvPbADGJHHC//YkTjL+k4NX4Y96DL2cJEno4bal4PjPEwO5E8SJ3qcT50uakJxbfCHf++O8bktJknwGmA/8X8C/EIe0ziH2pHoihPDFAXjOmSozdBXOnf9/7en5T3uYi1z2RZfRe6G/1/NAKhwmu6aHtX0h5b7KXVMDrafX2kBck0P9Oh/McyNJksowlJOkkelG4uqAB4CbkyT5fol5qAZz1dBdudtZubmmeis/l9KvJ0nyxSRJ3kqSpPgDZ9nnlyTJ60mS/KckSW4kDiVcC3w9t/uXcqsuVqr8+V/cz/uZGEKoK7O/M3fbnx5WeTsLvk4bXllKFu+F/l7PvdHZg32F53t3wdf9fb37o6+vX/65TL1Au/zQ4+KVd/sj/9g9vc6zNpjnRpIk9YChnCSNTPkPaa8kSXI8pc2mMsfn5ydKnRyrn/JzU9UC7+/D8fnnV3LS+RDCDGLPtx5JkqQ7SZJHgFuBt3I/Lp4UfaDPSZby578zhNCfhT5qSFkcIcSJ1a7KfftEPx4j7wniEGWAm3txXBbvhf5ez72RtghD4b4fne8kSQ4AL+a+7feCG/3Q19cv/1ymhBDmlWqQWzQj/9wf71t5ZR+73HVeRex92Rf9/TclX9/GXB3nCSEs4FxoeDHPjSRJ6gFDOUkamQ7lbueFEM5b/CCEsAz4UJnjD+dux1/swnKe4Fyg9v/mFlxIFUIongsr//yWphzym2XuK7XHS27IZz44KB6qN9DnJEv/xLmeS7+Xm6MvVYnzX+jzKYHAncC03Ndf7X2JPy4XqP117ttfCSFcqHdQXhbvhf5ez73xuZTnsRFYn/u2+Hz/Ue722hBC2WCun7Wl6sfrdzewL/f1F1LafIJz8/r9VZ8KLCFJkmeBl3Lfpl3nH6fvC4T099+U/Pns5NwKu8V+PXe7F7inj48jSZL6yFBOkkam7xB7YbQAfxlC6AQIIdSGEG7L7S83uffzudtLQgjrLnZxuaGmnwROEYObR0MItxaGQyGEzhDCh0MIdwP/uegu/jV3+2shhA+EEGpyx8wMIXwFuI04XLGUR0MI/y2EsKFwqGEIoSOE8N8518PuW0XH5c/JrSGE5t4943NCCKNCCK35DRhXsLu5cF8IYUAmV0+S5CRx/rwEWA48GEK4PoSQX201fy4/EUJ4LNe2lOPEHkRfCSFMyR03OoTwM8D/l2vzjSRJHrtIpX+eGC5MyNV8WwihPve4dSGEJSGE3wohfKTgmAF/L1yE67k3JgPfDCHMz91vTQjhVuDvcvufBP6+6Jg/5Nwci38RQviNwlAshDAm9374feCNftR2Ib1+/XJDjb+Q+/aDIYQ/DCG0F9T9i0B+DsivDsAiLZ/P3W7k/Ov8k8DvE+ek7Iv8tXVj/rrsjdz76mu5b/97COEX8tdcCGFSCOFLnJsv8d/l3veSJClLSZK4ubm5uY3AjdhbLCnYDhJ7gSXAZmLvoIRcplB0bA3wcsGx+4Etue3WXtTwp7nj/zRl/3XED+n5x+nKfX+sqPYvFR03nTiPV37/mdzzy3//q8B9ua+/UHTsloJ23cTw7mjR4/1uiVqvyrXP17kjf056+bpsKHqsctuGvt53D9v/VNG5PpM7/yeL6vh80XF35X6+BfhUwXnZX3CNJcDTwIQSj/uj43uzL7d/OXE1ycJrZn9BDQnwmcF4L9DH67mX18x7C2o/WPRabQVmptxHK/DdojoOEa//wnN3psSxW3L77roI/y71+vXLHfe7Bfu7ObfScv5n9wJjSxz3hdz++/r6vgF+o+i8FT72/cB/THsMyvwbCMwlLlaTEHvm7iq4tqb05PwTQ/37Cl+/Eufzt1KeV/64L5Q5Nxc8f25ubm5ubm7pmz3lJGmESpLkV4CPAo8RP/iNAl4nfoC8jBgqpR3bBVwLfJn4gbCBGIRNBxovYo13E3um/SrwADEkGE/8QPki8MfAe4BfLDpuK7Aitz//PE4C/wxcnyTJfyrzsHcA/zcxoHiTOA/YKGKg8VXg2iRJfrlErfcD7yYOATsEtHPunAxLSZL8JfH8/wZxCOZR4vk/SQzUfp8431pqz64kSf4HcD2x92J3bnsZ+PfA2iRJ9qUd28eanwQWAr8CPELs5dZADHruA34Z+ErRMZm8F/p6PfdGkiTfANYRe0idJM5H9ibwO8CyJEneTDluL/G1fC+xV9024oq09cDbxFWIfwGY0dfaelh/r1+/3HG/DFxDfN67ief+CPA94hDS65IkKdfjsT81/xpwEzH4O0w8by/lnsO1nBvy3tv7fY3YA+8fiYswTODctVXTw/s4lKvhp4nn7wjx3OwinquNSZL8277UJ0mS+i8kSTLYNUiSpAoSQrgL+BNga5IkMwa3msoXQthADJ9IkqQSFhqRJEkaEewpJ0mSJEmSJGXMUE6SJEmSJEnKmKGcJEmSJEmSlDFDOUmSJEmSJCljLvQgSZIkSZIkZcyecpIkSZIkSVLGDOUkSZIkSZKkjBnKSZIkSZIkSRkzlJMkSZIkSZIyZignSZIkSZIkZcxQTpIkSZIkScqYoZwkSZIkSZKUMUM5SZIkSZIkKWOGcpIkSZIkSVLGDOUkSZIkSZKkjBnKSZIkSZIkSRmrGewCJEmSLoYQqIUf20bltsLvxwD1QB0Q8ocW3k3R16EWEuDkaTgGHAfOpGync9uJJCEZgKcoSZKkChKSxL8ZJUnS0BUCVcQwbQzQkNuagBZgAjAeaCb+Z2M3MUxLAEZBzXioHwsNjVDfBLUNMKoZappg1GgI9RBGQ1UdkLutqgPqoLoWQvW5oC5JICRwNvf12SQ+TnfuZ90JnD0Fp0/BqZNw+iSc7uSZ5MP8wQE4th+O74JjO2HHdnh+N3CUJDmT1bmUJEnS0GEoJ0mShoQQaOBcwNYGdACTiQEcxAAs5LZu4PQEqOmAMW1Q3wYN06ChBeqaoG4sjK6H6ho4XQcn6+BUPZxqgJO1cKoKTlXDmSroqj63namJW9coOFMbf9adr7E7FlF1Fqq6Y0AXuqEqifuqu6HqFNQdhYZjMOYENExgZ/0cXmyCM6OgO0ASIKmGE2dg9zHYehS2HoE9R2D/67DtZTiwn9gz7yhwmCT5UQ2SJEmqDIZykiQpUyHQRAzemomhWwcwiTistJs4520XcajoiVaomQYtE2BcKzTOgMYOaJwADQ3QNQaOjoVjTXCsDg7XwvE6OF4Px8bAyaE7ge7RMXCoGQ5PgEOtsG98LgesgYOn4O3j8MZR2HoQtu2Dt56Fs9uBfcBB4KC97CRJkoYvQzlJkjRgQqCO2OutHZgNzCQOP833ejtDDN+OA10dMHYmtHXChIUwfjqMb4GqBjgyFo6Ng6N1cGgMHG6CA/VxDrcKc7YKDo2FIy1wsgX2joc9bXC8GjafgpeOwluHYdt+eHsHdG0HtgG7gD0kyaFBfgKSJEnqAUM5SZJ0UYRANXGOtzZgOjGEm8i5AO44cIRckDYDmqdD21Ronp8L4MZB9zg42AqHGmIa9c74eIw4UQv72uFYK+wfDwea4fAYeOM0PHkKXt8Pb+yEYweBN4HNwG7gHZLk+ODWLkmSpGKGcpIkqU9yCzBMBKYClxB7wVXlttPAYWIQB8BsmDAXOpfAxIXQ2gpnx8PBCbHn295meKcpzqOmHjs5CvZOgsOT4J1W2N8MW07CEyfg5WMxpDt8EjhEDOpeA3YA+/CPQEmSpEFlKCdJknosBMYBU4D5wELiPHAJsTfbYXKLIlQBs6F1DnQshYkLciFcG+xpgXda4O3m2F4X1dkq2DUZjkyC3RNhfwtsPw5PHoHnD8Nz++BUfr6+l4BXgR0kyYHBrVuSJGnkMZSTJEmpQmA00EnsBbcYaCWGcCeIiw38aKGBSdC4DGYtO9cTrqst1wNuAmx3GOpgOFsF77TDocmwqx3eaYYX98HD++CZg7A7PyffYeAF4A3gbZLE10qSJGmAGcpJkqQfEwJjiSHcMmAucT64LmII92Nzky2A9sUwbS1MngVjJsPuCbCrFbaNg6OZF68LOFELu6bDnk7YPQm2nILHdsLT78DLJ6BrFPH13gY8RZyXbq9DXSVJki4+QzlJkkQINBMXZlhOXKQhIYZqB3JfA1AHVUth2mUwZSVM7oDuTtgxAbZNgh3VueGrGg66gd2TYf80eLsddo+BH+6GR7fAEwegaywxoDsIPEl+ProkOTuIRUuSJFUMQzlJkkaoEBhP7Am3gjhPXEJcEOBQYbsmqF0Js1dB52KY2A6HO2BnK2xphf3ZV66BcagRds+B7VNgewM8vAMe2wJP74PuZqo/ysgAACAASURBVKAaOAk8C7wIvEWSnC53j5IkSUpnKCdJ0ggSAg3APGA1cdXUhNgb7sfmEKuDqpUway1MXwFtHbBvMmxrhzcbYzCjinagCXblArpto+HBt+GxzfD8PqAFqCWusPskMaTbTpLYS1KSJKkXDOUkSapwIVAFTCP2iFtKXBz1AEWrn1YBS2DKFTB7DUzuhENTYNtkeL3BIG4E29sCu2bHgO6tKvj+Nrj/5biqKxOBUcRQ92HgZZLknUEtV5IkaZgwlJMkqULlhqdeAqwHxhFXTN1L0bxv02DcOpi/EabOgLPT4K3J8KoLNeh8u9th5xzYMhWeOgj3vg6PbIauWuLKvNXATmJA96qruEqSJKUzlJMkqYKEwCjigg1riPPFdRODuBOF7Wqgaj3MfRfMWQxjp+Z6xLXD7uyr1vBzpgq2zYW3ZscRzd99C37wErx1CBgLNOcavgg8AmxxeKskSdKPM5STJKkChEALceXUdUAdcTjhj62cCjAJGjfAoutgxmw4Oh1enQqbXTVVfbe3Bd6eD1umwdOHY++5h96ArgSYADQQr8X7gRdIkmODWq4kSdIQYSgnSdIwFgJTiEHcUqALeAc4U9xuOUzdBPNXQ+vMODnYSxNhX8blqqLle89tmw1vNMI3X4d7X4SDJ4ExxOGt3cAPgcdJkh2DWq4kSdIgM5STJGmYCYFqYA6wgbiAwwlgD0W94hpg1JWw8AaYvQCYAW9MhZfr46qZ0gDaPRHeugTemAR3b4PvPAfbDxPnnGsj9ubcTuw99ypJ4jUpSZJGHEM5SZKGiRAYDVwKbATGA4eAg8XtJkHjDbBkE0ybCXunwitTYFvG5UrAoUbYeilsng4P7INvvwDP78ztHEece+4YcC/wNElyIvWuJEmSKoyhnCRJQ1xuFdXLgSuAUcSFG44Xt5sG426EZZtg8hzYOgOecwVVDQ0nR8HWRbB5Hjx1HL71Mjz8Rm4qwzqgnTj8+n7i0FZXbZUkSRXPUE6SpCEqBMYBa4H1xKGpuykxX9xsmHAzLL0aJs6GN2fCs41wMuNypR44W5VbsXURPBvga8/DQ6/nwrlRwKRcw4eBR0iS/YNWqiRJ0gAzlJMkaYgJgbHAGuBKYhi3Czhb3G4RtN8Mi9fDhDnw2gx43vniNHxsnQlvLIGngH94Hh58I7ejmhjO1QBPAg+SJLsGq0pJkqSBYignSdIQEQKNwGrgKiAQw7iu4nbLYMrNcOlqGDsHXp0JL9SWaCcND1tmwxuXxkVZ/+FZeOTN3I5AHNZaBzwH3EuSvDNYVUqSJF1shnKSJA2yEBgDrCQu4FAN7KREyDYfJt4Gl6+Dhjnwykx4sTo37k8a3rqBt+bA64vhh13wtWfh8a25nYG4Yuto4HHg+yTJgcGqVJIk6WIxlJMkaZDkVlNdAVxDnE9rFyXmjOuAsbfCik3QNh9emg3PG8apMnUDW+bD65fAY6fhrx6HF3fndlYRh7VWAw8Qh7W6kIkkSRq2DOUkScpYCFQBlwI3AWOIYdx5c8GNh9Hvg8veDdPnw+a58NToEqGdVHm6gc2L4OVL4e498DePw658AFcNTM41upe4WuuJwapUkiSprwzlJEnKUAhMJYZx04hh3HlhQh1U3QDLboG5C2HnXPhhExzLulZp8J0cBa8thxdnwjc2w9efhBP5od351VpPAd8BniRJnFtRkiQNG4ZykiRlIATGAdcSh6seBvYXt6kCNsLC2+CSxXBoLvywtUQ7aeQ5OBZeXQnPToC/fh6+91LBCO46Yji3B/hHkmTzoJUpSZLUC4ZykiQNoBCoBVYB1wEJcRGH8375LoL2O2H1KuieC091wtsZlyoNAzsnw6sr4NEq+MoT8Ezh+6QJmAA8A3yHJDHQliRJQ5qhnCRJAyAEAjAfuBkYRwzjzpsPrglqPwirboSOS+C52fBSxqVKw9Dm+fDKYvjWXvjKI7D/ZG5HANqJQ1vvBh4hSc6br1GSJGkoMJSTJOkiC4FWYhg3jzikruQKkRth4Ydh8TLYOR8eb4CTpdpJKuXkKHhlBTw9Df7iWfhuYaBdA3QAh4B/BF7FP3olSdIQYygnSdJFEgLVxKGqNxInn3+nVLuZ0PJRWHMVjFoIj02Ovegk9cnudnhxDXz/DPzZw7DlQMHORmAi8DLwTZJk7+DUKEmSdD5DOUmSLoIQmAS8H5hKnA/uvKGq9VDzflh+C8y6BF6aA89VF8xWL6mvuoHXlsJzC+Dv3oirtJ4qfG+1EReE+BbwGElydlDKlCRJKmAoJ0lSP4TAKGA9cSGHo8C+Uu1WwYyPwYrLYP9CeLQJjmVZpzQyHBwLL66FxxvhTx4tWghiFNAJvAX8A0mye3BqlCRJigzlJEnqoxCYAtxC7IXzNtBV3KYBRn0E1r0X2hbBY9Nga9Z1SiPPltnwwnL4+k74y0fgROF7sxUYA3wHeIgkOe99K0mSlAVDOUmSeikE6oCrgQ3Awdx2nmUw5WdhzSrYswgergdXgZQyc2w0vLAOHh4Pf/QgvFjYM66G2GtuJ/D3JMmOwalRkiSNZIZykiT1QghMBW4DxgM7gPPmpqqDqg/C6ltg6mJ4YjpszrpOSXmb58Ozl8Ffvw5fexK6CueaawHGAvcCPyBJDM4lSVJmDOUkSeqB3Mqq64CfIPaMO1Sq3QJo/1lYtw6OXAIPNMLJLOuUVMqhRnj+Cvj+KPjSA0UrtFYTe83tBv7GueYkSVJWDOUkSbqAEBhHXFl1HrCdEnPH1UDVLbD8Dpi9BJ6eBa9kXaekcrqB1xbDM4vgz1+Ebz5X1GACca65rwNP4h/JkiRpgBnKSZJURgjMIw5XDcSeNOeZAc2fgCuvhNOXwgPj4iqskoakvS3w/JXwnVPwpfth7/GCnbXEXnNPA/9MkrhKsiRJGjCGcpIklRACo4BriQs67AaOl2p3Fcz9JFx+ObwwD4p73kgaks5WwQur4LGp8PsPwTNvFzXoAE4AXyVJtmRfnyRJGgkM5SRJKhICE4m94zqAbcRxbz+mBqruhLW3waSl8EB7Si86SUPZ1pnw9Cr4k1fhG08V7RxLHNJ6N3ERiPOGrUuSJPWHoZwkSQVCYClwC3GBhr2l2nTA2E/Bhmvg5FL4fj24YqM0bB0cC89shG+egP/5fThc+H6uBqYSV1D+GklyoPR9SJIk9Z6hnCRJ/Gi46vXAFcDbwKlS7dbAzJ+DVavg1QVQ3LNG0rB0pgqeXwcPtsP/eABeLu752p67/d8kyZtZVydJkiqToZwkacQLgbHA7cBM4C3gvF+ONVB1B6z4IExfCg91xuBOUkXZPB+eXAZffh6+/ULRzkagFfhH4FFXZ5UkSf1lKCdJGtFCoAP4CFAH7CrVpg0aPglXvwtYCvc1piz6IKkS7G2BZ6+Gvz8AX74fThXOKVlDHM76BHF11pI9aiVJknrCUE6SNGKFwGLigg6HgUOl2iyC9s/CVWtgyyJ4vCrTCiUNjtM18NQG+E4dfPG7sP9kwc4ATCGG+H9FkuwflBIlSdKwZygnSRpxQqAauAa4FthBXNThPFfAnE/D5SvhiRnwRoYlShp03cDzq+CBafDF++C14oVfJgJVOM+cJEnqI0M5SdKIEgJjiKurLgS2AWdLtbsFln8cZl8O97dD8aTvkkaMNxbAY0vhvz0GjxSHb/l55v4JeMR55iRJUm8YykmSRowQmAh8GBhH7CF3nhqo+gRcdSuMuwy+Ow6OZlqkpCFox2T44ZXw5VfhH58u2pmfZ+5h4FskSVf29UmSpOHIUE6SNCKEwHTgTuAMsK9UmxYY/Wm45ifgzGXwvVrww7WknINj4clr4W8PwJd/AF2FC0AEYDrwEvC3JEnJIfGSJEmFDOUkSRUvBBYBHwIOAEdKtZkJLZ+FjVfDjkvhYRd0kHS+k6PgqWvgX6rh9+6Bw6eLGuQXgPjfJMnhQShQkiQNI4ZykqSKFgJrgPcCO0lZ0GE5TP0MrFsDz8+FFzItUNIw0w08cwXcPQF+5x5451hRg3bgBPDnJMk72dcnSZKGC0M5SVJFCoEqYBNxldW3SBmKugHmfxqWrYSHpsSFHySpB55fAd+bDv/lbthe3CuuBagF/owk2ToIxUmSpGHAUE6SVHFCoAa4CVgNbCV2bTnPTbDkkzB/JXyvDfZmWaOkSvDqYrh/AfyX78Frxf+GjAWagb8iSeyBK0mSzmMoJ0mqKCFQC9wKXEoM5Er+orsdVvw0TF8BdzeDcz9J6qPN8+GBZfDb98NzO4t2jgYmA98gSR4ZhOIkSdIQZignSaoYITAG+CAwkzhk9TxVwMdg/U9B60q4uxGOZ1mjpEr01gx4ZDX818fgkTeLdtYA04BvkST3Z1+bJEkaqmoGuwBJki6GEGgAPkqcZD01kPs52HA7NK6Af6mH4pUTJakPpm2BmlNQexX8Xi3c90rBzi5ir90bCaEauA//V1ySJGEoJ0mqALlA7k5gIrCjVJsaqPpFuOYWqF0J/1qbsvCDJPVNx05Yfw+MugbqauDbhfPInSUGc9cDowjhboM5SZJkKCdJGtYKeshNBIrncwKgDqp+CTa9H8Ll8K+jUhZ+kKT+mbgP1twDbIIkge+8WLDzLLCFuCJ0NSF8myTx3yJJkkYw55STJA1buTnk7iQOWS3ZQ64eav4NbLoJulbAvdUGcpIG3N4WePRa+OLzcM9LRTurgOnAQ8A3DeYkSRq5qga7AEmS+qIngVxN7CF37XvgjIGcpOy07ofV34XPLIZrFxTt7Cb2mFsLvC83z5wkSRqBDOUkScNOLwK5a94H3cvhewZykrLVuh9W3wOfWQLXzCvamRDnmFsBvN9gTpKkkclQTpI0rOQCufwqqyUDuSrg52HDLVCzHL5rICdpcPyox9wy2DC/aGc+mFsO3EwI/l0uSdII4y9/SdKwURDITaJMIPezcPVtMPpyuMdFHSQNron7YPW98NmlcHVaMLcauIEQQvb1SZKkwWIoJ0kaFkKgFvgQMJmUQA7gY7D+g9B0OdxdC12ZFShJqdr2wpp74bPLYM3Mop0JcY65K4FNBnOSJI0chnKSpCEvBKqBW4AZwNtp7T4Caz8MrSvh26PhTFb1SdKFte2FVffDL6+CpZ1FO/M95q4Frsi+NkmSNBgM5SRJQ1oIBOAGYDHwVlq7O2DlXdC+Ar5dD6ezqk+Sem7yTlj9CHxuPcxtLdp5lvhv3LsJYcUgFCdJkjJmKCdJGuquJvYc2ZrW4CZY8nGYugq+0wgnsytNknpr2lZY9wz8nxthSlPRzi5gO3ALIVwyCMVJkqQMGcpJkoasEFhB7CW3lTi86zxrYdYnYMEKuKcRjmdaoCT1yaxX4MqX4XOboGV00c7TwE7gQ4QwaxCKkyRJGTGUkyQNSSEwH/gAsI04rOs8i6D9l2Dl5fCDZjicaYGS1C/zn4ONO+Czm6C+pmjnSWAv8FFCmDQIxUmSpAwYykmShpwQmAZ8GNhNyvxwHTD2l+Hq1fDE5NirRJKGmUsfgeuPw6c2lviz/BhwAvgIIRQPc5UkSRXAUE6SNKSEQBtwF3CQ+IH0PE1Q+znYdAW8MgPeyLA8SbqIqoDl98H7RsHH1pdocACoBz5ICHWZliZJkgacoZwkacgIgUbgo8TecUdKtamBql+CTRvhnfnwTKYFStJFV90Ny++B29vh+lKLO+wCpgLvIwT/dpckqYL4i12SNCSEQA3wk0AjsD+t3Sfgqhuhawk8mFlxkjSg6k/DZffBJxfD0s4SDd4ClgHXZFuXJEkaSIZykqSh4jpgDrAjrcEdsPInoWk53OsvMEmVpXU/LH8YPr0eOsaWaPAWsIkQlmddmSRJGhh+ppEkDboQWAZcTVxptaSrYO5dMP0y+G4tdGVWnCRlZtpWWPcqfOYaaBhVtPMssB24lRBmDUJxkiTpIjOUkyQNqhCYAtwKvA10l2ozGyb8HCxfBj9oiisSSlKFWvA0bDwEn7y6xJ/qp4G9wIcJYUL2tUmSpIvJUE6SNGhCoAn4CHGl1VOl2jRB7afh6hXwbDvszrRASRoUS++H99TDbStL7DxK7DV3ByHUZlyYJEm6iAzlJEmDIgRGAXcANcDhtHY/C1dfAXvmwEuZFSdJg2pUNyy7Fz46A66YU6LBHmAScCMhhGxrkyRJF4uhnCQpcyEQgBuA6ZTp/XYLLL8JRi92pVVJI07TMVh+P/z85TBtXIkG24HVwGUZFyZJki4SQzlJ0mBYAawjriZY0uUw7aMwZyncNyplrjlJqmztu2H5i/Cpq6Gu+O/2hDgX5wcIoXMQipMkSf1kKCdJylQITAbeQ+zlkZRq0wFjPwVrlsPD4+FIpgVK0pAy/zm4+jh8dH2JnaeJw/8/RAgNGRcmSZL6yVBOkpSZEKgDbieuoHq6VJs6qPoUbFgNr0+BbZkWKElD0pL74ZY2uGpuiZ0HgQZijzn/tpckaRjxF7ckKUvXAxOA/WkN7oJ118LJRfBkZlVJ0pBWfxqWPACfWJ4yv9wOYBFwZcaFSZKkfjCUkyRlIgQWAWuJw1ZLWguz3g+TlsD3s6tMkoaDybvh8pfh5zeUmF8O4hyd1xPCjEzLkiRJfWYoJ0kacCHQDNwK7CJlHrk2aPgZWHEpPFyfMrRVkka2+c/E+eU+vLbEzrPAPuB2QhiTcWGSJKkPDOUkSQMqBGqAW4grqJ5Ia/dxuGIFbO2MqwlKkkpa/AP4ycmwfnaJnUeI88vdkHFRkiSpDwzlJEkD7SpgFvBOWoN3w+J3Qd0ieDy7siRpOGo4CYsfhJ++HFpGl2jwNrCCEC7NujJJktQ7hnKSpAETAjOATZRZRXUmtNwJlyyGB6pjbzpJUlkdO2H5W/CxK0rsTIhTBXyAEMZnXJgkSeoFQzlJ0oAIgTHA7cQ5js6WalMDVZ+AK5fCC61lVmSVJBVb9Bj8xFjYML/EzvxUAe8jBP/elyRpiPKXtCRpoGwizm10JK3BHbDiKjg5D57LrixJqgSjumHxQ/CxZdDWUKLBLmA+sCrjwiRJUg8ZykmSLroQmAmspcyiDUuh8zaYsRh+kF1lklRJ2nfDZW/Cx0sNYwXYDrybECZlWZUkSeoZQzlJ0kUVAnXE1Vb3Eec2Ok891HwC1i6BJxrheKYFSlJFWfQEXDca3rWoxM4zwDHgVkKoybgwSZJ0AYZykqSLbQMwDjic1uB2WLkC9k+HzZlVJUkVqbobLn0Q7lwMHWNLNNgPdAArMy5MkiRdgKGcJOmiCYEpwNXAjrQ282Hie2HaQngku8okqZK17YVlr8FPpw1jfRu4kRAmZFmVJEkqz1BOknRRhMAo4APAQVJWW60C7oK1l8JzDluVpItp/tOwoTZlNdYzwCngZkIIGRcmSZJSGMpJki6WdUA7MZQr6SZYuh665sCL2ZUlSSNBdTcseAw+shSaaks0eIe4GuulGRcmSZJSGMpJkvotBNqBd1FmtdUOGHsHLHTYqiQNlI6dsHQ33LYqpcEu4H2E0JhlVZIkqTRDOUlSv4RANfB+4CjQldbuI7B2MbzRGicdlyQNiAWPws2dsKC9xM4TQA3xP1EkSdIgM5STJPXXYmAasC+twRUw51pomA8/zK4sSRqJGk7CJc/CnatT/tTfAawkhFkZFyZJkooYykmS+iwE6oF3A7vT2jRB7Z1w2SJ4fBR0Z1edJI1Us1+Cdd3wE4tL7EyAvcAHCKHU3HOSJCkjhnKSpP5YD4wmDokq6VZYeRm80wnbsytLkka6BY/ABy+B1jEldh4BmoEVGRclSZIKGMpJkvokBFqBq4lDoUqaCS03wdT58Gh2lUmSoG0vLNkKH1qd0mAn8C5CaMqyKkmSdI6hnCSpr64HTgNn0xrcBisWwKuNcDK7siRJ0bwn4LqJsKjUog+ngQBsyLYmSZKUZygnSeq1EJgNXEqZueSWw9SroWkOPJ1dZZKkc0afgfkvwO2XpzTYCawhhMlZViVJkiJDOUlSr4RADXAzsD+tTRVwOyyfD8+5uIMkDabZL8C6OlhbarXVbuAYcAMhhIwLkyRpxDOUkyT11mVAG3AorcFGWLgaumfBK9mVJUk6XxUw92n44FKoKfW3/x5gLjAv27okSZKhnCSpx0KgEbiBOOSppHqouQMunQtPZFeZJCnd9Ddh2Sl41yUpDfYANxPCqCyrkiRppDOUkyT1xnqgBjiV1uAmWLYY9nWUCe4kSVmb90O4dSE0lArejgLNQNrcc5IkaQAYykmSeiQExhFDudSwrQ0aPgBz5tlLTpKGmPbdcOkeeM9lKQ12AtcTwpgsq5IkaSQzlJMk9dR6IAHOpjW4BVYsgq3NcDi7siRJPTP3CXjvLJjUWGLnaWJP6JUZFyVJ0ohlKCdJuqAQaAbWArvS2kyDcdfBpLnww+wqkyT13PgjsHArvC+tt9wuYCMhlArtJEnSRWYoJ0nqifVAN2V6yd0El82BN+tjbwtJ0pA06ynY1AkdY0vsPANUA6syLkqSpBHJUE6SVFYItABrKDOX3BRouhYmzYJns6tMktR7jSdh7la4cWlKg53A1YRQKrSTJEkXkaGcJOlCrgK6iD3lSroZLpsLbzbAyezKkiT1zaxn4PopKXPLdQEBWJ1xUZIkjTiGcpKkVCHQSpz0O3UuuQ4Yuwkmz4RnsqtMktR3jccv0FtuF3AVITRlWZUkSSONoZwkqZwriXPEpfaSew8smwtbGu0lJ0nDyMxn4fqp0NZQYmcXcbXttRkXJUnSiGIoJ0kqKQQmAiu4cC+5zpnwdHaVSZL6r+kYzNsGNy5JabALWE8I47KsSpKkkcRQTpKUZj2xl1yS1uBmWDoXttpLTpKGo1lPw09Mh9YxJXbmV9tekWVFkiSNJIZykqTzhMA44HJgd1qbSdC4CabMgqeyq0ySdPE0HYN52+GGtLnldgNXEEJ9llVJkjRSGMpJkkpZQewhlzqX3A2wZJ695CRpmJv5DFw/HRpGldh5BhgFLM64KEmSRgRDOUnSjwmBeuAKyvSSa4La62DadHguu8okSRff+CMwey9sWJTSYA+wkRBqsqxKkqSRwFBOklRsCbFnxJm0Bhvhktmwexwcza4sSdLAmPYC3Dgn5aPBCaAJmJttTZIkVT5DOUnSj4RADbCB2DOipBqouhFmT4UXMytMkjSAOnbC/DOwelZKg4PANYQQsqxKkqRKZygnSSo0h9gj4kRag3Uwex6cmFxmeKskabiZ+QrcMD9l5yGgE5iWYUGSJFU8QzlJUqGriB++Ut0A82fAK9mUI0nKxvTXYPlYmNua0uAYcGWWFUmSVOkM5SRJAIRABzCdOEyppAXQvhhGT4XN2VUmSRp41d0wazNcf0lKg73AIkJoy7IqSZIqmaGcJClvFXC6XINNsGAWbK6G7oxqkiRlZurzcFUHtI4psTMh/o5YlnFRkiRVLEM5SRIh0AAsp8w8cS0w+krocIEHSapUjSdh1g7YuCilwR5gDSHUZlmVJEmVylBOkgQwHwiU6QF3FSyaCTsb4WR2ZUmSsjXlZbh2RsrHhDNALXFRIEmS1E+GcpI0woVAAK4ADpRr9y6YOcUFHiSpwrXvhlmnYdnUlAaHgfVZViRJUqUylJMkTQbagaNpDZZC5yzongw7sytLkjQ4pm2Fq9N6wx0EZhDCxCwrkiSpEhnKSZKWEockpVoHc6bB1ozqkSQNqs5XYM0kGD86pUEXsCTLiiRJqkSGcpI0goVALbASeCetTT3UXAEdnQ5dlaQRovEkTNsDa+alNNgDrCWEUVlWJUlSpTGUk6SRbTZQR+z1UNIamDsV9jfBsezKkiQNro7X4LoZKTtPA6OJv0MkSVIfGcpJ0si2BjhSrsEGmN4JWzKpRpI0REzZCvNrYX7a3HFHgbVZViRJUqUxlJOkESoEmoE5lFl1tQPGLoHxU+G17CqTJA2+KmDGNlifNoR1PzCbEMZlWJQkSRXFUE6SRq5FQDeQpDVYC/OmwdujYjtJ0ojS8RJcPQVqyn1mSFulVZIkXYChnCSNQCEQgPXA3nLtNsL0yfB6NlVJkoaW5sPQeQyWT0tpcABYlWVFkiRVEkM5SRqZJgHjgBNpDRbD5NmQTIad2ZUlSRpapmyHVdNTdh4BOgmhJcuKJEmqFIZykjQyzQXOlmuwGmZPh20Z1SNJGpLa34BVk8sMYU2AtHnnJElSGYZykjTC5IaurgT2pbWpAtbA5ImwObPCJElD0Pgj0OEQVkmSBoChnCSNPBOBFsoMXV0EkzuhqzWuridJGtHKDmE9CrQTQmuWFUmSVAkM5SRp5Lng0NWlML3TueQkSQC0vw6rJpUZwnoWmJ9lRZIkVQJDOUkaeVYQhxulWguTW+HNjOqRJA1p449Ax/EyQ1j3A6sIIWRZlSRJw52hnCSNICHQShy+eiytzUxomQE17bA7s8IkSUNc2SGsx4EJxN8vkiSphwzlJGlkmUNcKS/VcpjZATv9BSFJOqf9dVhZbggrQFpPOkmSVIKfuSRpZLkcOFiuwVrobIW3MqpHkjQsjD8C7SfhkskpDQ4By7KsSJKk4c5QTpJGiBBoBiYDR9LadMDYuTCmA7ZnV5kkaXjo2A0LO1N2HgZmEMKYLCuSJGk4M5STpJFj6oUaLIPZk2FXNXRnUZAkaThp2R5XYS0pyW1TMixIkqRhzVBOkkaOhZRZ4AFgNUyaCNsyqkeSNKxM2gEzGqA1rTfcaeLvGkmS1AOGcpI0AoRANTCfOOdPSXVQNQ9a2g3lJEklVXdD2x5YnLYK6wHgUkLwM4YkST3gL0xJGhnagVqgK63BJdA5AY7Ux54OkiSV0L4LlqUt9nAaqAfShrhKkqQChnKSNDJMJc71k2o+dEyGPRnVI0kallq3wrKJZT5GdAMzsqtHkqThy1BOkkaGS4gr46W6DFrHwY6M6pEkDUvjj0DbaViU1lvuELA0y4okSRquDOUkqcKFQB0wkzKhXBPUzoLxCRLjSQAAIABJREFU7YZykqQL6tgFC9NWWT0CdBDC6CwrkiRpODKUk6TK1wEEygxfXRTnk9tfW2bOOUmSovE7YVnrBRo5r5wkSRdgKCdJlW8mcLZcg4UweZLzyUmSemTiDpjZDDVpnyUS4lymkiSpDEM5Sap8lwIHyzVYBm3j4O2M6pEkDWv1p6H5OCxoT2lwGFiQZUWSJA1HhnKSVMFCoBFoA46ltWmFMVOhvg12Z1eZJGl4a9sHM9OGqB4BphHCqCwrkiRpuDGUk6TK1nahBougsxX2VUN3FgVJkirB+Hfg0rR55fJzmKb1pJMkSRjKSVKlm0SZBR4AZkHbRNiXUT2SpIrQsgPmT7hAo85MSpEkaZgylJOkyjabOIwo1SIY1+AiD5KkXhl/BCachRnNKQ2O4LxykiSVZSgnSRUqBAIwAzia1qYGqqbA+FbYlVlhkqQK0boP5kxO2XkEmEkI1VlWJEnScGIoJ0mVqxmoBbrSGsyElvFwsh5OZ1eWJKkyTNgLCyam7DwLVANp885JkjTiGcpJUuVqA0K5BtOhrRkOZFSPJKmiNO2GBS0XaGQoJ0lSCkM5SapcU4Az5RrMhpYWQzlJUp+07oH2MVBfk9KgC+jIsiJJkoYTQzlJqlyzKTOfHMACaGmE3RnVI0mqKNXdMPYIzExbhfUocW5TSZJUgqGcJFWgEKgBOikTytVBVQeMbXXlVUlSn40/DJ1p88odAzoJwc8ckiSV4C9ISapM+Tl8krQGc6F9HBytLbMQhCRJ5TUfgunjU3Z2Exd7aM6wIEmShg1DOUmqTK1cYJGHqTBxAhzMqB5JUkUasxfmNV2gUdrwVkmSRjRDOUmqTG3A2XINZsH4cS7yIEnql+Y90Dm+zMeKBJiUYUGSJA0bhnKSVJk6gOPlGkyHxnpDOUlSvzSchKbTMGVcSoOjwMwsK5IkabgwlJOkyjSZC4Ry7TC2CfZnVI8kqWKNOwTT0hZ7OApMJYSyUypIkjQSGcpJUoUJgVqgCTid1mY8jB4H1U1xZTxJkvqh5TB0tKTs7ALqgDEZFiRJ0rBgKCdJlWc8ZVZdBZgKzfVwJKN6JEkVrf4gTG8s0yAB0oa3SpI0YhnKSVLlaeYCK6+2wfimOKRIkqR+qj8MHQ1lGgRiD25JklTAUE6SKs8ELtBTrg3GjbennCTpohh7ACaW6ykHkDa8VZKkEctQTpIqTwdwolyDWdBYB4cyqkeSVNEaT0ID0DI6pcEJ4gJEkiSpgKGcJFWeC4ZynTC2AQ5kVI8kqeLVH4OO5pSdJ4G2LKuRJGk4MJSTpAoSAtVAK2VCuRqoaoUxzbA/u8okSZWt8Ri0ps0bdwJoI4Sy851KkjTSGMpJUmVpIE6onTqn3BQYVw+nRkF3dmVJkirb+KPQkhbKnQVq+P/Zu/Poqu/7zv/PrySEhBA7BsxmjG1sY4M3jPFu4yzN5rRpmthZpk2TdNL8MnOaNG0nmTY99S9NmiaTNvEkzWrH8ZLFWxwTb4AxBgw2+w4ChCVWgUAICe36zB9fwELce4Vt9JV07/NxDof4ft/IL/UUru+LzwIDEgwkSVKvZyknSdmlhC4ueRgGAwdAfUJ5JEk5of9RmJDpBtYADE4qjSRJfYGlnCRllxMr5dIaDAOL4/N9JEk6S4prYWymUi4C0q2kkyQpJ1nKSVJ26bKUGwQDSizlJElnVckRGJ6plAO3r0qSdApLOUnKLoOJz+5JazgUFVnKSZLOqpJ6KCnM8PGiFRiSYCBJkno9SzlJyi5DgeZMA6OguB/UJZRHkpQT+rVD/1YYUpRmoJn4PUqSJB1nKSdJ2WUY0JRpYDj0L4RjCeWRJOWMfk0wNN0W1mZcKSdJ0iks5SQpu3S5Um4IFA+AownlkSTljKJGGJKplPP2VUmSOrCUk6QsEUVExB940q6UywNKoWig21clSWddUROUFqd52IK3r0qSdApLOUnKHkXEf66HdANDoKg/tPaD9uRiSZJyQ0kTlKa7YbUdKCCK+ieZSJKk3sxSTpKyR7oPQieNhNJCb16VJHWL/o0ZLnqAuJhLt5JOkqScYyknSdmjPxlWyQEMggH9LeUkSd2i3zEYkamUgzP4CyRJknKFpZwkZY/CrgaKobAftCYRRpKUa/o1wLBM21MjXCknSdJJlnKSlD36dTVQCP0KLeUkSd2iXxOUdPVe1OV7lSRJucJSTpKyRyHxKoRMA4WWcpKk7pHfAkX5XQxZykmSdJylnCRlj350XcoVWMpJkrpHv2YoLMgwEGEpJ0nSSZZykpQ9urzooRgK8qEloTySpJzSZSnXDnR1EYQkSTnDUk6SsscAoC3TwCBLOUlSt+nfDP0zlXJtWMpJknSSpZwkZY8iutiaOgD65VnKSZK6Rb92KIigIN1njDa8fVWSpJMs5SQpe3S5Um4A5LtSTpLUffJaYUC61XKulJMkqYNMy8slST0siqKLgI8D7wQmE3+Y2Q78FviPEEJ9h/EiTinlPn4LPHR3/L/XfgkurytJs1JuH/sKpzDln2upHT6LWQuWsOSRbvqWpG5VSWX/z/P525ewZEYttSPyyW8ZxrCq9/LehT/kh6/kE18MOZvZf7yZzRcd5vDIJpqKBzDg6GhG7/osn33+y3x5a+eve5jDBXdx13te4ZXr6qgbXErp4Ru5cckjPPJcKaUnf98tZvGQb/Gt61ax6rJqqs9pprl4EIOqpzFt3b3c++xUptZ3/tpSb3cnd757G9sm7GLXxFpqR5RSWl1L7VdST+e1foP2aT+Cmw7Auc1QVAqHp8Ha78PSy+PzT0+KomgC8FVgNjAWOASsBP49hLCwe78zSZJ6lqWcJPVunwI+DzwFPERcqN0G/P/An0VRdF0IoeH4bDEnS7lXBsNv/xj6NUHLyQ9AxVDQD5o7/0s+ykc/0EDDwG79TqRu1kJLdD3X/4/d7J58JVe+cjmXv9hAQ+HLvDzjJ/zkz7exbcx85j8OUEbZ5LGM3T2LWSuHMKS+iqrBi1k88+/4uy/tYMfPf8gPl3X82rOY9ZktbLniaq5ePI1pO9ay9vw5zLnzFm45ZyUr7z8x9yN+NO1pnn7/RVy0biYzVw9kYON61k9ayMLZ13HdNfOZ/40ZzKhN+P800tvyFE/9cX/6149hTEUTTQMyzf4rj43+KnV3jILX3wvPDoDmDXDeQph9M1y9Hr469vhsFEXnAiuIP5P8CCgDzgU+A7wYRdEHQghzuvN7kySpJ1nKSVLv9ijwjRDCkQ6v/VcURWXEKwv+Erj3+OsFnLx99S/uhsEH4dw9sGYmbwzk53U6d+4+7puwkIWzP8SHHnuURz/cjd+L1K1+zI8n7WLXBTdx07yFLPzNidePcGTBBCb8y2IW3ww8DlBBxbc7//pKKudPYcrXf8Nv/qhjKfc1vnbZFrZccTM3v/ASLz16/OVFt3DLsYUsfMf3+f7CL/CFHQDv431lX+AL/6tT8bboU3yq/D7u+8SX+fI7F7DgUaQ+5Fme/eq7eNdBgBGM+Fozzf3Tzf6QP0wqJe/oetq/NeKN95uX3wm1L8B77oUrvvHG+H8DRgAfDCH87sSLURQ9QlzQfQawlJMkZS3PlJOkXiyEsLxTIXfCr4//fFmH1yIgwN9dAVunwz0PQl47nQaik8UdNNIY/QP/8InJTN7wV/zVqrP+DUgJqqa6CGAEI2o6vj6YwW0DGFDXj35NmX79eMY3FVNc10jjKSuBnuTJawHu4Z55HV8/8c8P8/B1J177M/5sb6qVcF/ja68BVFJ57pv7rqSed6KQOxP1NBYUEzWM6PQXQOdADcCgU1drDzr+855OX2Yf0A643VuSlNUs5SSpbxp3/Of9HV6LoKIQfnAXzFwIf7Wz8y/K49RS7mN87I5DHBr9Q37oGXLq8z7CR3b2p/+xZ3jmXV/ki1cvYMGwJ3ly1B3c8cf72T/xw3z4951/zTrWDVzFqtIHeXDc9Vx/1yEOjbmES9Z3nKmk8rwSSmpu5ubDHV+/mZsPl1BSs5Od53WVbTnLhwIMYpBbV5XVrufSqirazrkF/vQxGL0Qhn4ZrnwC3nsebP8b6Hhm43PHf/5BFEW3RFE0NoqiGcAjQB3wnaTzS5KUJLevSlIfE0VRPvBPxKsQHu7wKA/ufj+ECB58IuWvhehEKfc8zw9/iqc+8D7e9/Qd3FE9l7nDuz+91H2mMOXYN/jG/72Hez75Xb772e/yXQD60a/x7/i7//om31zdcb6Syv7TmHbyQ38BBc0zmPHykzz5m45zddQNGcGIzit5ACiltKaW2qFdZfsn/ukDAB/lo6+8hW9N6jPu40sb/og/r32ZhtkL4R0nXr8KlrwEjxbFi7YBCCEsiKLo88C/AAs6fJky4LoQwqbEgkuS1AMs5SSp7/kP4DrgKyGELW+8/F/nw+Lr4Qs/g8kNqX5hXocPQ5/jcx8bzOCDD/DA3O4OLCVlKEObRjFqz3Smr5nBjO3VVJc8zdO3fofv/GUppT/4Kl89+SF/JCObv87Xv9tCS/4Odgybz/yZjTT2P8CBwnM59+QWu1ZaC/PJb0317yugoKWV1sJMmf6UP33HRjZePYMZL/89f78l06zU1xVS2D6agtpLYNVNsLYEmhfC1BVwwzsgegV+1emXHACWA3OJV9FdBHwZmBNF0S0hhMqEvwVJkhJjKSdJfUgURfcA/x/w4xDCNzq8Xggj7oLJW+F7r2X8EhD+mr+euYMdl/4H//HtUkrbuj24lIBHeGTsp/n039/N3b95gAcWnnh9H/tem8KUr/0b//aJL/GlrxZRFACKKApf4SubT8w10rjoQi7829nM/mI55V8/8XujgILmNtpS/jdTK639Cig47UbjEz7Fp258jMc+dAEXrJvHPLeJK6u10BLdxBdnHqWpYRvck//Go5WzoW4+vPvbsOpvj78YRdFngB8AV4YQTm4bj6LoOWAl8A3g48l9B5IkJcsz5SSpj4ii6J+B/w3cB/z3To8/D9Wj4C9fhDkj3/jRUBQ/XjocnhsRIBzhSMH93P/hC7hg/QVccGQOc0bOYc7INawZBnCMY8VzmDOyjLLiBL896W37Nt++o422fn/P36/o+PpoRjdfxmXrjnJ0+Iu8OCLdry+iKNzGbcuqqR57L/deeOL1gQxMu0X1KEeHDGJQTapnn+bT19/HfR8/n/M3vsqr/2UBrmz3fb5/wTrKh99KyYb8Ts/uhhUA82Fyh5f/F7C5YyEHEEJYB2wGbunWwJIk9TBXyklSHxBF0deArwEPAJ8OIYROIxPjs+S+0rmsO+6zX4GCpkDLghoO92ugoXQb2y5/H++7vPPkGtbMfB/vm/kn/Mmjj/HYC2f7e5G6y2EODwFopvm0v3Rsoy0PoImmjH8h2UhjP4ADHCg58dp4xu9cy9qZC1k4tONlDwtZOLSe+iGXcdmazl/nM3zm+p/z809OYtKmZSz7wVCGptz+KmWTnewcAtBGOO33WQvkA7SeuihgLLA9zZcrwM8qkqQs5xudJPVyURT9E/DPwC+BvwghtKcYuw++XAL5BdDc9MbLj94KFVPg07+A4ccCnDeMka1f5Is/6vwFqqgqfZAH7z6f8zd8kA8uuoVbdnXPdyR1j3GM21tO+aX3cM+sx3n8+ROvl1FWvI51V/Sn/7F38s4DW9gyYDSjmwYz+JSVa3vYUzif+TdGROF9vK/8xOt3cudra1k78x/5x9kv8dKjJ17/R/5xNsBd3PVqx6/zWT4762f87JMTmbhlKUt/MIIRFnLKCddy7V6AudRNOwpPlMLJ32P3wyyAq2Bnh1+yEZgWRdF1IYSlJ16MomgW8dlyc5LILUlST4lOX2whSeotjt9Kdy9QAfwj0LmQ2x9CeCGe5XNAEVD/xuOr/hxWzYK1X4LL6+6FD34YFp0DBzv/u+Yyd/g7eMe/zmLWgiUs8ewr9TnzmT/sPbznfzfRNGA601+dxrRtNdSUvMRLN9VSO/xjfOzhB3nwpX/gH674Ht/7+HSmrxzHuKqBDGyspHLEMpZdV0fd0Hfz7qef4Znfd/zaF3HR58som3Y1Vy+azvQda1hz/gpW3Did6ctWs/rnJ+a+wlemfZNv/nUhhQ13cddjxRS3dPw6gxjU1PkWWKm3+xyfm1lJ5XCA+cy/vZ32/Du44wWA8Yyv/iE/XHZi9jam//MC1o4ZAbtugmXF0PwaTC2DaeNgZxl8uyiE/wsQRdEHgCeAY8B/Ed+6eiHwOeKVdTeGEFYgSVKWcqWcJPVuM47/PAH4RYrnLwEntpi20+F21VTaoT0c30IkZZvbuf3QEzzxja/wlfeWUXbJOtZdk09+yyhGVX6Wz/723/n3VQC3cMvuucxdu5WtU1ay8tpWWguLKKofy9idH+WjD/0L/7Ku89dewpIf3c3d713K0pmrWHXdQAbWvJf3PvUIjzzbcW4VqyYGQtRE04D7uf8Tnb9OKaXVlnLqa+Yw58ZKKi/q9NqdAOMZvxU4Wcr9gXvWfJZPrHuW2kufgg8EiAbBodnwzIOwsAhOrhwNITwVRdE7iG9b/RQwGDgMPAfcE0Lw94okKau5Uk6SskQU8RfAcKA23cy/w3vvgtVjYXdyySRJuePpD8Hn50LFkRQPBwMHCOH+hENJktQrefuqJGWPRrpYBdcIrW3QL6E8kqSc014AjenOUcwnfq+SJElYyklSNjlGF8cS1FvKSZK6VVsB1DeneZiHpZwkSSdZyklS9uhypVwDtLRB/4TySJJySjvQngcNLWkGCrCUkyTpJEs5Scoex+iilDsKbe2ulJMkdYvmftDcfvpF4SflAQ0JBpIkqVezlJOk7NHAGZRybl+VJHWP5kJoTneeHMTvUZZykiQdZyknSdkj3Rk+HQdaWroo7iRJemtaC7oo5SLO4L1KkqRcYSknSdmjBQiZBpriUi7jZRCSJL01LYXQ1NbFUKbSTpKknGIpJ0nZI93B2ic1QUuzpZwkqVu0FkJTpveiwBm8V0mSlCss5SQpezTTxUq5Zmi2lJMkdY+WIjja1fZUt69KknScpZwkZY8uVx80QHMLFCYRRpKUa1qK4WBThoFAfFO4JEnCUk6SskkD8SHaaR2G+iYoSiiPJCmntBbDgcYMAxGWcpIknWQpJ0nZo54uSrkqOGopJ0nqHg1FcLSrUq4hqTSSJPV2lnKSlCVCoAVoBPLTzdRDSyOEBrewSpLOuvr+cDTdSrgCoJEQvH1VkqTjLOUkKbvUAP0zDdRCYx2UJpRHkpQzGovgaLqVcP2AI0mmkSSpt7OUk6TsUkMXq+AOQ0MjlCSUR5KUM5qK4HBdmoeFxO9RkiTpOEs5Scouh+hipdxBaGy2lJMknXXN/aE63fbVQlwpJ0nSKSzlJCm7VNNFKbcfGltgQEJ5JEk5obEfNAH1LWkGCoHDCQaSJKnXs5STpOxSB4RMA4ehoQGKE8ojScoJdaVd3LyaD9QmlUaSpL7AUk6Ssks9XZRydVBfB0UJ5ZEk5YRjg6Aq3XlyEL831SeVRpKkvsBSTpKyS7qzfE46DHWulJMknV2NQ2BXptIt4JlykiSdwlJOkrJLPRBlGtgPtQ2eKSdJOquOlcCeTKVcHpZykiSdwlJOkrLLMaCF+OyelKqgvh7y693CKkk6a46UwMF0pVshUEcIzUkmkiSpt7OUk6QsEgIB2EcXK+Gq4OgRGJpMKklS9qsfCFXpSrkioCrJNJIk9QWWcpKUffbQxZlxFVB3zFJOknRWtAMNA2BPulKumPgvjCRJUgeWcpKUffbQxdbUnXC0EQYlE0eSlN1qS+FIEzS0phnoj6WcJEmnsZSTpOxTQ3zLXVoHoOYwDEwojyQpqx0dClXevCpJ0ptkKSdJ2edwVwP7oeYolCYRRpKU7RoHwa66DAMBqE0qjSRJfYWlnCRln1riD0BRuoEKONQAA9p8H5AkvW31g6HiaIaBCFfKSZJ0Gj+MSVKWCYE24CAZLntogvZqaKyBwcklkyRlp+rBsKc6zcMioIYQmpNMJElSX2ApJ0nZqcsbWPfC0TpvYJUkvW1HB0N5VZqHA4HXk0wjSVJfYSknSdlpN12UcuVwtMFSTpL0thweBIda4VBjmoFiLOUkSUrJUk6SslM1Gc6UA3gdDlVbykmS3pYjI6GipouhA4lEkSSpj7GUk6Ts1OUHoJ1QVQNDEsgiScpax4bB1q5uVj2YSBRJkvoYSzlJyk41QBNQkG5gJxyugX51MCCxVJKkLFM9GHYfSvOwEDhGCHVJJpIkqa+wlJOkLBQCAdgJlGaaK4fD1TAqkVCSpCxUOwQq0q2EKwEqk0wjSVJfYiknSdlrO/EHorQ2Qk09jEgojyQpq9QXQW0hVBxOM1AClCeZSJKkvsRSTpKy176uBirgwAEve5AkvSWHR8KuI9CebiAC9icYSJKkPsVSTpKyVxVd/Dm/HfYfsZSTJL0ltaNhbXWGgQgveZAkKS1LOUnKUiFQT3zhQ/90M/ugrhrCYRiUXDJJUnY4MBy2V6V5WAjUEUJNkokkSepLLOUkKbvtoIvCbUd8C6uXPUiS3oS2PDg0FLbsSTMwGNiaZCJJkvoaSzlJym47gOJMAxuh5iiMTCiPJCkrHBwJexvhUGOagSKgLMlEkiT1NZZykpTdqshwAjfATti3H4YnE0eSlB2OjIH1h7oY2ptIFEmS+ihLOUnKbgeO/5z2z/sNsPsQDGqIz/+RJOkMHBwBW9OdJ1cANAFdlXaSJOU0SzlJymIh0EIX58o1QXsZVFfBuOSSSZL6tkPDoCzTeXLbCCHjSm1JknKdpZwkZb/1QGmmgRVw4DCMSSiPJKlPOzwoXohdcSTNQAmwJcFAkiT1SZZykpT9dnU1sA327POyB0nSGTk0FjZXZxgIeJ6cJEldspSTpOxXRXy2T0G6gc2wvxqK62BAcrEkSX1T9WhYsz/Nw3ygjTfONJUkSWlYyklSlguBdmAzMDTdTCu0b4zPlRufXDJJUt/TDuw7B9a9nmZgCFBGCG0JhpIkqU+ylJOk3LAZKM40sBqqDsHohPJIkvqk/aOgshn2HE0zUAKsSzKRJEl9laWcJOWG3V0NbIHK/Z4rJ0nK6PAEeG1fF0MViUSRJKmPs5STpBwQAoeBGjKsltseb1/NOwyDkksmSepb9o6CjXvSPCwBqgihJslEkiT1VZZykpQ71hOf9ZPWGjhwEM5LJo4kqW+pL4IDg2BtZZqBIcDqJBNJktSXWcpJUu7YDvTLNLACKvfAuQnlkST1KfsnwsZqaGpPM5APlCeZSJKkvsxSTpJyRyXQRoY/+1fAzn0wtB6KkoslSeobqsfA8r1pHhYAzUC6ra2SJKkTSzlJyhEh0Eh8C+vQdDMN0LoGDuyDScklkyT1fu3AvnNgw+tpBoYCGwmhLcFQkiT1aZZykpRb1hAfxJ3Wq7B7H4xNKI8kqU/YNwZeb4WKI2kGioGNSSaSJKmvs5STpNyyEwhAlG5gBZTvg5HN8VYkSZKAqvNh8a40DyPi95aKBANJktTnWcpJUg4JgWNAGRm2sNZA42ao2QMTk0smSeq92oHdY2DFjjQDQ4DthFCXYChJkvo8SzlJyj2rgIGZBhbD7ioYn1AeSVKvtn8MlLdD2cE0A6XA8iQTSZKUDSzlJCn3lNPFFtY1UL4XRrf5PiFJYv+ZbF1Nt4pOkiSl4YctScoxIVBHfLbc4HQze+DoNji2B8YlFkyS1At1uXV1GLCZEI4lGEqSpKxgKSdJuWkF8XajtJbArio4L5k4kqTeaf8Y2NmWYetqCbAyyUSSJGULSzlJyk07yLB9FWAplFXCud7CKkm57MB5sGh3mod5QBvxsQiSJOlNspSTpBwUArXEW1iHpJvZA0fXQs0umJxYMElSL1M5NsPW1eHARkJoTDKRJEnZwlJOknLXUjKcKwfwIpTvdgurJOWoXeNhe6atq8XEN3pLkqS3wFJOknJXGdBChu2py2B7JQytjc8MkiTllD0XwAvptqbmE7+H7EwujyRJ2cVSTpJyVAg0AcuBkelmGqB1EezdDVOSSyZJ6nkNhVAxGpZsTjNwDrCcEJqTTCVJUjaxlJOk3LYaKMw0sAS2VcLEhPJIknqFXRfBawfgULrz4gpx66okSW+LpZwk5bbdwEEybE9dA7t3QN5eGJVcLElSz6qYBAu3p3lYCuwD9iYYSJKkrGMpJ0k5LAQCsJj4Br205sHr++CiZFJJknpW1QjYWQSvpjtPbiiwiBBCkqkkSco2lnKSpE1AAKJ0A0tgSwWMbfF9Q5JywJ4pMP91aE/1MB9oA7Ykm0mSpOzjhytJynEhcJS4mEu7Wm4PHF0DNZVwYXLJJEnJa8uDinGwKF3pNhJYSQjHkkwlSVI2spSTJAG8SoZz5QBegG0VcEFCeSRJPaJiMqyrhYojaQb6AyuTTCRJUraylJMkAewE6ok/bKW0FHZsgwH7vfBBkrJYxYUwd0eahwOBA8CuBANJkpS1LOUkSYRAK7AQOCfdTCu0Pws7KuHi5JJJkpKzfySUlcCisjQDw/CCB0mSzhpLOUnSCWuIL3zITzfwEmwqh3ProSi5WJKkZFRMhWe2Q2uqGx4KgFZgY8KhJEnKWpZykiTg5IUPK4gP8U7pIBxbCHsr4NLkkkmSul/dACgfAwvSlW6jiFfJecGDJElniaWcJKmjV8lwrhzAXNi0Aya3+R4iSVlk51R4cRccakzxMCJeRb0i4VCSJGU1P1BJkk4Kgb1AOfG5QSlthv0roe51uDC5ZJKk7tOSB+XnwwuZVsmtIoTDSaaSJCnbWcpJkjp7CSjNNPAMbCmHKQnlkSR1q4opsPwIbK9OM9AfeCXJRJIk5QJLOUlSZ9uBg8DAdAPLYMcW6LcbxiYXS5LUPcqnwLOb0zwcBuwghD1JJpIkKRdYykmSThEC7cB8YHi6mXZgDmzdCZcllUuS1B12jYdNESzfmWaglHgFtSRJOsss5SRJqWwC6snujeiJAAAgAElEQVRw6cM82LAJBu2NzxqSJPVJOy6Hp7bEf91ymoHEK6d3JJtJkqTcYCknSTpNCDQDC8hQuDVB+xPx2XLTEwsmSTqLdo+FjQNgQbqtq8OB+YSQsrGTJElvj6WcJCmdVUATmVfLrd8Eg/e7Wk6S+qDyy+HxzdCaqnQbANQC6W5klSRJb5OlnCQppRBoAObS9Wq5rTtgWnLJJElv354xsLEUXkxXuo0EniOEliRTSZKUSyzlJEmZrAIaybBabn58ttzQ/fEHOElSn1A+DX6XbpVcCXAEWJ9wKEmScoqlnCQprRBoBF4ARqebaYDW38Wr5TxbTpL6hL1jYNMgmLchzcAI4FlCaE0ylSRJucZSTpLUldXEN7EWpRt4AdZvhmFV8Qc5SVKvtmMaPLEFmlKtkhsIHMaz5CRJ6naWcpKkjEKgiXi1XNqz5Y6vlivbAVckl0yS9ObtHwWbB8O8dFtThwPPuEpOkqTuZyknSToTa4A6oDjdwPOwbjMMd7WcJPVm267IsEquFKgGNiccSpKknGQpJ0nqUgg0A8+T4TKHBmh9FDaXwTXJJZMknbnKCbBmIDy3Ls3AcOKz5NqSTCVJUq6ylJMknam1xKvlBqQbeA7WrYIBFXBeYqkkSWegHSi7En69Ns2Nq4OBfbhKTpKkxFjKSZLOSAi0AM8A56SbaYX2X8GarXBlm+8xktSLlF8Cy9phYVmagWHA04SQqrCTJEndwA9MkqQ3Yz2wBxiSbmAxbF8MTTvgkuRiSZLSay6ArVPh1yvTDIwC1hPCjiRTSZKU6yzlJElnLATagN8DQ4Eo3dyvYMUmmNoAhYmFkySlsX0azD8Ca3aneJgPFBGfGypJkhJkKSdJelNC4HVgFfHKipQ2w/4XoGobXJVcMknS6eqKYNNF8OjyNANjgIWEcCDJVJIkyVJOkvTWvAAUHP+R0qOwfCOcVwOlycWSJJ2q7Bp4ZhfsPJziYX+gBXg54VCSJAlLOUnSWxACh4H5xCssUtoHdb+DHVthRnLJJElvODgMNo2FxzOtknuGEI4lmUqSJMUs5SRJb9UrwDFgQLqBp2DVehixN0N5J0nqLpuvg19vgUONKR4OAqqA1QmHkiRJx1nKSZLekhBoAp4iw9ly9dDyMKzbDNe2+Z4jSQnaMQVe6Qd/WJtmYDjwNCG0JplKkiS9wQ9IkqS3YxOwk/jDXUrzYNMCaCmDaUmFkqTc1lAIG6fDA69Ca3uKgdHAekLYlnQySZL0Bks5SdJbFgLtwNPAQDK8pzwAr6yDi730QZKSsPlamLMX1u9N8bA/8Z/XcxIOJUmSOrGUkyS9LSGwG1gCnJtuZicc/i1s2wTXJxZMknLS3lGwdiz86rU0A2OAOYRQk2QqSZJ0Oks5SdLZMB+oJ14xl9ITsHIpDCiHC5OLJUm5pB3YPBN+uRZqUl3uMByoAFYmm0uSJKViKSdJettCoAF4DBgJRKlmWqH9F/DqRriyAQoTDShJOWHb5bCoDeZtSvEwn/gvTp4khLaEg0mSpBQs5SRJZ0UIbANeI8M21jWw+2nYuwlmJpdMknJBbQlsuBR+sTTNwFhgPiHsSzKVJElKz1JOknQ2PQ+0AAPSDTwMy1bDmD3xuUaSpLNiw43waDlsr07xcBBQA7yccChJkpSBpZwk6awJgTrgcWBUuplaaP4FrNoE17X5PiRJZ8G2S2BxMfxmeYqHEfFZco8RQnPCwSRJUgZ+GJIknW2bgPXA6HQDC6HsBajfANcmF0uSslFNKaybDj9dDK3tKQbGAksJoTzpZJIkKTNLOUnSWRUCAXiaeHVG/3RzP4NFy2HCbhiXWDhJyjobboCHt8GWAykeDgZqiY8WkCRJvYylnCTprAuBI8DvyXDpw0E49hN4bR3M8jZWSXortl4OLxfCkytTPMwHhgK/IYSGhINJkqQzYCknSeouq4GNZCjmlkL5k7B3PdyQXCxJygaHBsOaqfDjRWm2rY4D5hJCRdLJJEnSmbGUkyR1ixBoB54kvo11YLq5B2DpEhi6A6YkFk6S+rR24m2rD22B8kMpBkYCu4CFyeaSJElvhqWcJKnbhMBR4FfEHxDzU800QOuPYfFauKIGShMNKEl90tYrYUEEv1+V4mEhUAQ8SgitCQeTJElvgqWcJKlbhcB2YD4ZLnTYCPsfgu3r4aZUe7AkSSfsHQXLp8BPF8Ur5k4zFniKEFJd/CBJknoRSzlJUhIWEG+lGplu4HFY/iJEW+HKxFJJUp/SUAhrb4IfLYeKIykGxgAbgBUJB5MkSW+BpZwkqduFQAvwW+JtVf1TzbQDP4aXV8FF+2FUkvkkqW9YezM8ug8WbUvxsBRoJV4l56JjSZL6AEs5SVIiQuAg8BjxbaxRqpldUPsjWL0abqqPz0SSJAGw5XJYUAK/XJLiYQEwHHiYEGoTDiZJkt4iSzlJUpLWAcuJi7mUXoItv4Y9a+BWl3pIEsD+UbDiUvjBAmhK9UfjeOAPhFCecDBJkvQ2WMpJkhITAgH4A1ALDEk390tY+gLkbYQZiYWTpF6poRDW3Ag/WpnmHLmxwFog1Qo6SZLUi1nKSZISFQINwCPE5x+l3KLaCu0/gJeWwnmvw6REA0pSr7L2Znh8PywsS/FwKPFfcvzOc+QkSep7LOUkSYkLgT3Ar4lvCsxPNVMF9ffCkpVw7SEYnGhASeoVtkyHhSVwf6pVcP2BgcBDhHAs4WCSJOkssJSTJPWIEFgPzCc+CymlNbD7fti8Gm5tjg8yl6QcUTkBll4M33sxxTlyEfG21d8Swr4eCCdJks4CSzlJUk+aD2wiw8UPT8Ga38HRNXBTcrEkqSdVD4UVs+B7S2BXqttUxwOLCGFt0skkSdLZYyknSeoxIdAGPEZ8JtKwdHM/gYULYfBWuDyxcJLUIxoKYfVt8NONsLIyxcBooAJ4LuFgkiTpLLOUkyT1qBA4BjwIFB//cZoGaP0evPgKXFoBExMNKEmJaScu5H59AOasSzEwDDgGPEIILclmkyRJZ5ulnCSpx4VAFfAw8QqQlBc/VMCR/4DFy2FWFYxINKAkJWL9LHg2H+5bnOJhCfGN1Q8QwtGEg0mSpG5gKSdJ6hVCYAvxdqwJ6WZWw67vw6oVcFtt/AFVkrLE9ovh5bFw73xo7XyxQyEwkriQq+qBcJIkqRtYykmSepOFwGoyFHMLYMvPoXwF3NEI/RJLJkndZu8YePUK+M8FcKix08M8YBzwGCHsSD6bJEnqLpZykqReIwTagSeAnWS4kfVRWP4bqFkFt7f5XiapTzs0GFbcBN9/FcoOphiYCMwnhBVJJ5MkSd3LDzKSpF4lBJqJz5c7BJyTbu6n8PLTEK2BGxILJ0lnVV0RrLgDfrgBXkm1Cm48sAaYm3AwSZKUAEs5SVKvc/xG1geAFmBoqplWaL8X5s+H4RvhykQDStLb1lwAK94B91fCHzakGBgN7AGeIITOZ8xJkqQsYCknSeqVQqAGuB/oD5SmmqmF5u/CvMVwQTlcmGQ+SXrr2vJgxWz47VF4+NUUAyOAOuBBQmhKOJwkSUqIpZwkqdcKgf3ExdwQoDjVzB44+h1YsBiurojPXpKkXqwdWHkzPAX8aGGKgaHHh+4nhKOJRpMkSYmylJMk9WohUAE8RLyVqzDVzBY48C146RWYtSs+g0mSeql1s+C5gfCf86C187bUUuLVwfcRwqEeCCdJkhJkKSdJ6vVCYDPwODAOyE81sw72fgsWvwI37IExiQaUpDOy8SqYOwq+MxcaWjs9HAgMJi7k9vdAOEmSlDBLOUlSnxACrwHPEW9RTVnMrYTKb8PSZXDzfhiVaEBJymjLdFhwPnzrBahp7PRwAPG21fsIobIHwkmSpB5gKSdJ6ksWAHOBCaQp5l6Fnd+B5cvg1qr4sHRJ6mFbLof5F8LXn4Oq+k4Pi4CRwAOEUN4D4SRJUg+xlJMk9RkhEIB5x3+kLeYWw/b/A6tfhdsPwrAkM0rSqbZeDvMvhn99HvZ0vrihP/F2+4cIoawHwkmSpB5U0NMBJEl6M0IgRBHzgAiYDewkvqnwFC/Blv6Qnw+zr4PnhkJtwlEl5bytU2H+FPjm87Cr859BRcQX2DxECBt7IJwkSephlnKSpD7neDE39/g/pi3mnoeN/SA/D945E54bAp1XqUhSNym7FF68FL7xPFQc6fSwGDgHeNBCTpKk3GUpJ0nqk860mJsD6/IhL8C7Z8Dc4XA4yZySctG2S2HB1HjL6mmF3ADiM+R+QQhbeyCcJEnqJaIQQk9nkCTpLYsiIuAO4HbgdVIUcwDvgqlfgKnXwryRUJ1kRkm55EQh9/W5sLPzXwIMJL5l9X5C2N4D4SRJUi9iKSdJ6vPOtJi7HS76n3DFTHhpFOxPMqOkXLBlOrx0EXxzHpQf6vSwFBgM/JwQdiafTZIk9TaWcpKkrNCpmKsEWlPN3QCTvwjXzIRFY2F3khklZbN118KL4+DfXkhxy+og4lVyPyeEih4IJ0mSeiFLOUlSVokibgTeS1y4NaeamQETvwjXzYJXJ0J5ogElZZl2YM1N8Pww+PYLcPBYp4EhxDet/owQ/IsASZJ0kqWcJCnrRBFXAn8G7AMaUs1cBmP+Fm6+EdZMhs2JBpSUJdryYMVt8If+8N25UNv5LwLOAVqIL3XY1wMBJUlSL2YpJ0nKSlHEFODjxLet1qWamQzDvwy33wJlF8PqRANK6uOaC2D5HfBEG3x/HjR1PstyLHAQ+CUh1PRAQEmS1MtZykmSslYUcR7wSaCJuJw7zblQ+mW441aomgaL8xLMJ6mvqiuCFe+A3xyFHy+E1o6FXARMAMqA3xBC5+2skiRJgKWcJCnLRRGjgD8HCklz4+oQKPoC3PZH0H4lzC+Kt5tJUgqHB8HK2fDLvfCLpZ0e5hMXcq8BvycE/yyRJElpWcpJkrJeFDEY+AQwkjQ3rhZA3qfhhg/D8Ktg3hDofHuipJy3eyysuAF+tgWeWtPpYSHxltV5wHxC6LydVZIk6RSWcpKknBBFFAMfAS4EKoCUb4B3wpWfgQuvgpfHwN4kM0rqzbZfDMumw38ug1d3dnpYDIwCHieE5clnkyRJfZGlnCQpZ0QRBcC7gRuIV8x1vikRgFlw/v+AGTNh5aT4XChJOasdWH8dLBoL/2cBbK/uNDCMuJR7iBC2Jh5PkiT1WZZykqScE0VcBXwIOESabapTYOTfwK03QvlUcOWLlJOaC2DVbfBcf/jPuXCosdPAuUAt8CAhVPVAQEmS1IdZykmSclIUMYH4nLkISPlh+hwo+RuYfQccnQ4v9YuXzEjKCUcGxhc6PHYEfroQmjr+/s8HxgMbibesesOqJEl60yzlJEk5K4oYAtxFfDh7JSnOmSuGgv8Ot74fSqbDgmFwJOmckpK2dwysvBF+vg0eX9XpYTEwGngBWOCFDpIk6a2ylJMk5bQoohB4P3ANcTHXmmruAzD9z+HiK2H5ebA9uYSSkrVlOrw2BX6wHF7Z0enhifPjHiGEzT0QTpIkZRFLOUlSzosiIuA64nLuAFCfau4yGPN5uGEW7L4MluW7nVXKIg2FsPZmWFAC974Iu2o7DXh+nCRJOqss5SRJOi6KmAzcffwf96eaGQZFfwW3vhsKpsOCwVCXXEJJ3aNqBKy5GR6rgvuXdDo/rh8wDtiA58dJkqSzyFJOkqQOooihxDeznk+8nbWt80we8CdwzSfh/Ctg6XioSDimpLNm26Ww4nL4yRqY13lL6hBgMPA0sMzz4yRJ0tlkKSdJUidRRD5wE/BOoBo4mmruKhj/eZh1Ley4FJbnJRlS0tvUXADrboCXh8G9C2F7dYeHEfHquMPArwhhT89klCRJ2cxSTpKkNKKI84CPAAOA3almzoGSv4Zb7gCmwstD0hR4knqTqhGw/kb4fS385GWob+nwsAgYA7wG/IEQGnsmoyRJynaWcpIkZRBFlAAfAKYRF3PNnWcKIO9OuOJuuGgarLkANiWdU9KZaAe2XgmrpsAv1sFzGzoNnAMUAI8Swvrk80mSpFxiKSdJUheO3856DXE5Vw8cSjU3BUZ+Bm64Aeovg8UDwQPhpV6jphTW3wQvRvDTRVBxpMPDfOLtqhXEhVx16q8hSZJ09ljKSZJ0hqKI0cTbWUcQr5o77dD3/pD3Ybj2wzBhGqw4D7YnHFPSabZfAmumw8Nb4YmVnX7rDiW+zGEe8BIhtPZIREmSlHMs5SRJehOiiP7A7cCNQA1wJNXcdBj7abhuJlRfBkuKU2x7ldTd6opgw43xwtUfL4YtBzo8LADGAvuBxwlhV89klCRJucpSTpKktyCKmAD8CTAS2AW0dZ4pgX4fh5l3wpjLYNn4eGucpES8PgnWz4BHK+GRZdDUcXnccGAg8AKwmBBaUn8NSZKk7mMpJ0nSWxRFFAI3Ea+cO0qas+ZmwMTPwrVXQtXFsKwEvM1R6jZ1A2DjdbBiGPx0Gays7PCwH/HquN3AY4Swr2cySpIkWcpJkvS2RRHnAn8MnEv8Yf+0M6kGQeGfwbXvh7FTYe1kb2iVzrJ2YPtU2HAZPPY6PLYcGjr+XhwJFAHPAss8O06SJPU0SzlJks6CKKIAuA54F/FKuAOp5i6GUf8NZl4P7ZfAKyPBWx6lt+3AcNg0CxZFcP8rUHaww8MiYAxQDjxJCFU9k1GSJOlUlnKSJJ1FUcQ5wJ3AJGAv0NR5Jg94N1x+F0ydBq9fDK8VplhdJ6krLXmw+RpYNwke2gTPru1ws2oe8erVZuBpYC0hnHZjsiRJUk+xlJMk6SyLIvKAK4H3EJ9htZcUF0GMgAEfg5nvghGXwMrzYHuySaW+bNd42DgDnq+Fh5bCvroOD0cCxcAS4CVCqO+ZjJIkSelZykmS1E2iiBLiiyBuJN7SmnLb3FUw/pMwYwbUXQzLhsGRJHNKfcuhwbD1Wlg9GB5YCa/s6PBwADCKuOB+2oscJElSb2YpJ0lSN4siRgF/BEwBDhLf1HqKAsi7E674U7joYqi8AFYM9JZWqYOGQth6NWycCI9vgzmrO1zkkE+8VfUY8BSwya2qkiSpt7OUkyQpAVFEBFwIfAAYSryltbnz3AgY8EG46j0w7mLYOhnWet6ccltbXnyr6uZL4dl98a2qVSe2o0bEK+P6AQuAxYRgmS1JkvoESzlJkhIURRQCVxPf0gpxOXfam/F5MPRDcPVtMHQKbDgfNuYlmFPqHSrOgy1XwuIm+NVrsKXjrcbnEG9XXQ4sIIRDPRJRkiTpLbKUkySpB0QRg4DbgWuIb2itIkU5dxmM+QhcPRMKLoI1E6E84ahSD9g/ErZdBatK4OHVnc6NGw6UAhuAeZ4bJ0mS+ipLOUmSetDx8+ZuAa4gPg/rACnKuVlw/kfgiiuh8UJYNSZeYSdlmaoRsOMK2DgMfrcF/rAOWk+cDTcYGAbsAJ4jhIqeyylJkvT2WcpJktQLRBFjgNuAqbxRzp2iAPJmwyV/CpdeDEcnwfqxsCvprNLZd3AYbL8CNo2EJ7fC8+s6XOJQSrw6bi/wDLAd/wNWkiRlAUs5SZJ6kShiLDAbuBioI76t9RT9Ie9muPSDMGUqNE6CDRNgZ8JRpbOgeihsvxI2j4TflcFz66C+5fjDIcd/HACeAzZ7o6okScomlnKSJPVCUcR44A7iG1uPAtWdZwog70a48INw6WXQNhk2ToBtXgih3u/Q4LiM2zIKfrcdnl8LtSduIz5xZlwlMA/YZhknSZKykaWcJEm9WBQxEXgHMIn4Qoj9dDpzLg+YBZM/AFOvgPzJsPk82JIPFhnqZfaOgdenwrbhMGcH/GHN8TIuIr5NtQgoAxYAr7tNVZIkZTNLOUmS+oDj21qvB6YDbcTlXGvnuRkw8f0w9RoYcD6UTYBNxdDceU5KTjtQMRl2XgxbiuH3ZbBg4/FtqvnAKKAfsAZYRAh7ejKtJElSUizlJEnqQ6KIocDVwA3ERcYBoKHz3HQYewdccj2MOA92j4eNI1NsgZW6T3MB7LwEdlwEa5thzmZYsv34barFwEjixu414BVCOO38REmSpGxmKSdJUh8URRQDlxHf2DoYqAGOdJ47B0puhUvfBZMmQ92EePXcdre2qvvUlsRbVHdMglcOwbMbYc1u4i2qw4ES4v9/XQhsIIS6nkwrSZLUUyzlJEnqw6KIAuAC4nJuHPG5cweIt7ieVAB5N8CF74QLpkHJJNgxHjYNgvrkUyv7tAO7JsLuC2HnSHipEp7bADsPA4XE58XlA5uBJUC5lzdIkqRcZyknSVIWiCIi4lLuquM/Ckizeu5CGDEbLrkFxk2C/efCtrFQ4a2tevNqS2DXpfD6RNjYDC/sgEVbjp8XN4R4FWcjsBhYTQiHejSuJElSL2IpJ0lSlokiioCLiM+dG0d8IcQBOl34MAgKb4JLZsPEi6D/BKgcA1tHgMWJMmgHKifBrsnw+gh4eTcs2Aqb9xNvTR1GfCnwDmApUEYIXjYiSZLUiaWcJElZLIo4B5gGXEd8uH4dcel2yn8AXAgjrocLb4bxE6FhPFSeC1sHwrHkU6t3qhoB+ydDxXjY2AQvlMOSLVAfEV/akA8cJC7iNhNCTY/GlSRJ6uUs5SRJygHHz547H5gJTDn+cg1Q23GuAPKuggnXw6QZMHosHB4Hr58L24s7rbRTLjg0GPZdBJXjoCI/XhX36jbYcggYAfQnLm6XARuA/fgfl5IkSWfEUk6SpBwTRQwmvhziWmAs8aq5GuBox7liKJgBk26AiVfCyNFQPQb2nAPlXhCRzY4MhH0XQsU42D0AFu+G18ph3QFoHw70I94SvQZYDVQQQlvGLylJkqTTWMpJkpTDooj/1969B9lZ13ccf3832c0mu8luNtlNwiaQgGCBctdS2+lUnA7TOlKsIyNTp1Oc1ipqUSzYauUiKo7V6hRkEJWWW6cdZbxQq7TlNhYGKQaKIPfcIPfNbjbZS3aT3f31j99zwunJyWZhk7NJ9v2aOfOcfZ7v+T2/c84/Zz77u8zntYBuSXF6B3kE3d4fCfOg4WxYcQ50ngkdi2CgEzYvhDUdecqijmg9LbBtBWzohA1z4bFN8OgaeKoHRlrJa8QNkkO454FXSWnPlHZZkiTpCGcoJ0mSgL0B3QrgHOBYchDTTx5Ft3ck1EyoOx06z4Bl58KSpRDHwOYFeaOIV+vzTgA6rI3WwaZO6FkKGxfDxnp4cgus3AAru2H3XCDIgetK4GVgMyn53UqSJB0khnKSJGkfETQDy8mbRJxEXsQfckDXT9kouhNgwRlw3LlwzIkwtx26OqC7Bda3Q1ddrTuv/ehvhC0rYGsnbGmH1QPw8015NNxLw5DqyN/rK8ATwFpS6p7aPkuSJB29DOUkSdK4ik0iFgPHAacBS8nhzQg5pNtVql0Ic06FZSdDx2mwsBNmtUFPB3S1wsZ22GJIVyu7GnIAt2MJbFkIXU3wTBc82gu/7IWeYfJouI3As8BaYBMpDU9lryVJkqYLQzlJkvS6RDCbvEHEm4BfB1qLS0PkzSL2hnQd0HQyLP01aD8N2juhsQ26F0HXvLwm3Ranux4s/Y2wrRN6F+cQbnsTvLgDVg7Ci/2wqgv2jAFd5J1S1wIbSWlwSrstSZI0TRnKSZKkSSnWousETgCOBxbw2vTWAfKmESOQR9KdAp0nwaLTYeFiaJoLA23Q2wq9TdC1ALY2gpsIjGu0DrrboK8ddi7IIVz3HPjVLli5C9Z0w+qtMLobWAesJo+I20JKfeO3LUmSpFowlJMkSQdVBHOADvKU1+PJm0c0FpdHyaPpBoHRWVB3ArQvg/YVMP9EaO2EeXNhcD70tkHvnLw+Xfe8HPBNQ6N1sG0B9C2Cvvl5JvDOFtg0As/thhcHYF03rNkCo+uBVcB68oi47W7OIEmSdHgylJMkSYdUBEGe4tpBXo/uBGAJMJM8oq4O2E2e9jo4E0ZXQNux0H4ctJ0ErUugeS7MmAP9zTDYkudq7pwNO+fC9qMjsNtTB73zYaAVhlphe0seOLh7FmzYk6egvrwTNvTAus3Qv4Ycvm0DtgPdpDQyte9BkiRJE2UoJ0mSaq4I6uaSw7pW8qi6TnJYN4e8zlwUx2FgeC6wDJraoWUBzFsGTUuhqQPmzoUZs2GgCfqbYHgODM+AoXoYaIDBRhick49TPC1290zY0QI7WmHnQtjZBn3NMDIDxgK6dsHGAVjbD5sGYMsOWPcM7FwF9JA31ug1fJMkSTryGcpJkqTDSjH9tRTWLSSvUdcGzAfmkcO60g+YAGgClkBjOzQ3Q8M8mLkI6hdAfSvMaoHGZpjVANTD0CwYaoA9M2FsJozUw+hMGK2H0YCRujxndKQuD18bASLlRx355nUJYgxm7IGZozBjBOpHoH4YZg9CYyr62cHqprN5qR9SHexJsGMItg3Buj54tR96NkPvC/DiKhjYCfQDA6TkunqSJElHMUM5SZJ0xChG2M0Gmskj6prII+4WkEO82cWjsXjM4rUAjyZoaIHZzdDUCA0NUFcPdaVjPdTNzg3H7Pyomw0RMJZgNMHo2GvPx8byGnljozCSYGwE9gzC8G4YSrB9Bmw/i6e2XcHnu6B3A9y/FRjGH2CSJEnTnqGcJEk6ahUhXj3QUHGsLy/b38uLYyJPe91DXvuu9HxPSowegm5LkiRpGjCUkyRJkiRJkmqsbqo7IEmSJEmSJE03hnKSJEmSJElSjRnKSZIkSZIkSTVmKCdJkiRJkiTVmKGcJEmSJEmSVGOGcpIkSZIkSVKNGcpJkiRJkiRJNWYoJ0mSJEmSJNWYoZwkSZIkSZJUY4ZykiRJkiRJUo0ZykmSJEmSJEk1ZignSZIkSZIk1ZihnCRJkiRJklRjhnKSJEmSJElSjRnKSZIkSZIkSTVmKCdJkiRJkiTVmKGcJEmSJEmSVGOGcpIkSZIkSVKNGcpJkiRJkiRJNWYoJ0mSdJiIiLdHRIqIS/KQg1EAAAgBSURBVKa6LxMREdcW/V0+1X2RJEk60hjKSZI0DUXEbRGRDlHbD0XE2kPR9qFQhEq3vc7XlMKzKw5RtyRJknSUM5STJOkwFBGXjDdiKiKWv5EwSZIkSdLhwVBOkqTp6YPA7KnuhCRJkjRdGcpJkjQNpZT2pJSGprofR4uykYvXRsS7IuLxiBiKiE0R8ZWImFnlNRdGxJNF3asRcR1QX6Vuv+u2RcTaiHioyvnzIuLfI6K7aH91RNwaEQsr6t4XEQ9HRF9EDEbEYxHx3irt1UXEpyNiTdHe0xHx/tf3KUmSJKmcoZwkSUeB1xsKVVtTrnQuIloi4uaI2Fq08UhEnFvlnvMj4tsRsS0iBoq15M7ZT/+qTrUtm6b79orz8yLiixHxXNGH7iI8uriibknR11ciYndEbIyIb0VER5V7nRoR9xZ97YmIu6rVTdI7gX8EfgpcDjwFXAF8qqIvfwT8AGgBrgNuBC4CvjzZDkTEh4D7gdOBm4G/BP4ZOAdYWlb3BeBfgT7gKuBvgEHgexHx0YpmvwZcD7xSvJcfATcBfzjZ/kqSJE1X+/zXVpIkHdHeCXwE+CY5HLqQHAptJ4cqE/EfQBc5LFoAfBL4SUQsTyn1AUREfVH3VuBO4OfAmcB9QPdk3kBEtAIPA6cCd5ODpRnAWcC7yEESEXEs8CjQANwKrALeBFwKnBcRb0kp7ShqVwD/DcwCvgG8ClwA3DuZvlZxKnBqSmltcd9vAk+Tg7Hri3MzgH8AeoDfSCltK87fAvxyMjePiKXADcDzwG+llHrLLl8VEXVF3dnA3wJfSil9pqzmhoj4IfCliLgjpdQXEW8GLgMeAM5PKY0WbXwf+MVk+itJkjSdGcpJknR0OWAoNAFPpJQ+UvojIp4Fvgv8MXBLcfoD5EDuupTSNRW1XwfWTeI9XF+8jw+llL5VfqEUKhVuJE/3PCultL6s5nvkkPBy4Nri9BeB+cA7UkoPFnU3Ad8nh30Hyw9Lnz1ASilFxIPAxyKiOaXUTx6xtgz4aimQK2p3FN/XRL+nai4ih5SfqwjkSvcYK56+H0jA7ZVTWoF7yGHu24D/LJ4H8LVSIFe09URE/Bdw/iT6K0mSNG05fVWSpKPLPqEQ8CCwOCKaJ9jG1yv+fqA4nlh27t3AKPD3FbU3Azsn3NsKReh2MfAc8O3K66VQKSJayKPm7gGGImJh6QGsBV6mCIuKNi8AflEK5Iq2EvB3b7Sv+7G6yrnSyMEFxfH44vh8ldpnJ3n/0nf05AHqTiYHbc+TR0WWP24tahYVx0PZX0mSpGnLkXKSJB3ZUsXfBwqF+ifQ5v9rI6XUHRGl15ccD2xKKe2sqB2OiNXkUWlvxMLitfcWodn+vJn8z8U/Kx7VlN5HB9BMbUKl0XGuRcWx2vuLKufG+xwqf8uN13ZlXQL+gP33+VcTaLNafyVJkjQBhnKSJB2edhXHOfu53lRRVzKRUGhc5VMUx3l9KdR5w/cpTCZUArgLuH0/Nbsqag/UZq2sKo4nV7lW7VxPcWwjjwIEICIagSXkUYElLxTHs4CXxunDS8DvA6+klJ57Hf2tDH2r9VeSJEkT4PRVSZIOT2uK4/5Cj9L5aiPjamEVcExEzCs/GRGzgBVV6nvIoVKl4yv+7iJvSnHmAe7/Mjlka0gp3befxyNF7VbyCMFqn+UpB7jPobASWA98oHw9t+Kz/HCV+heL4+9VnL+cfX/L3Q3sBq6p/G6Ke5QCyjuL4/XFxhOVdeW70t5D/qw/WV5bbBZR2SdJkiRNkKGcJEmHpyfIO4ReHBHHlF+IiAbgY+Sg5N+moG8APyLviPpXFecvBfYJg8jB0tsiYu/Iv4iYT94wYq9izbh/AU6JiH2mpZZCpZRSN/AT4D0R8ZvV6iKivagdBX4MvCUizqto61MHfqsHV9Gfy8kh5f9ExKcj4krgMarvXHsfeertdRHx5Yj4cETcRZ62u628sNjw4hPkAPLpiPh8RPx5RFwTEU8AZxR1jwPXkNcG/N+IuLqou6rYfXV9WZvPAzcB7wAeiIjLIuIL5LUGnzpoH4wkSdI04/RVSZIOQymlkYi4FPgBOVz5Dnl02iLgfeTdSa9PKb0wTjOH0j8BfwFcHRErgEfJUyYvKvpZ+RvjG+Sppg9ExJ1AK/BB8i6tiytqP0sOgL4TEecDD5OnoJ5VtPsnRd2lxbWfRcQd5M0N6sij7y4E7uC13Vc/S14/7ccRcSM5dLoAaJ/Mh/BGpZTujoj3AlcXfdwK3Ab8jLzjaXntaERcCNxA3kV3d1Hzu8AjVEgp3RwRq4ArgcuAWcBG4H5y0Fuquy4iVhY1nyBPid4KPAN8vKLZjwObyd/5V8jTXz9K3ljiYO5eK0mSNG3E+GsoS5KkqRQRbyWP5vod8kYLA+Tw6eaU0nfL6paTp7x+LqV0bUUb15JHRa0o7cwaEbcBf5pSirK6fc6VXUvA7SmlS8rOtZEDmncDjcDjwBXAV4HlKaXlFW1cSR7ht5g87fYrwBg54DsvpfRQWW0r8BngPcCxQB95U4YbK973QuCvySHcscAQOXh6ALglpfRsWe1p5N1ifxsYBn5KHrG2pfK9SZIkSYeaoZwkSZIkSZJUY64pJ0mSJEmSJNWYoZwkSZIkSZJUY4ZykiRJkiRJUo0ZykmSJEmSJEk1ZignSZIkSZIk1ZihnCRJkiRJklRjhnKSJEmSJElSjRnKSZIkSZIkSTVmKCdJkiRJkiTV2P8BSoBWNp5wixEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1440 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pie plots of protein replicate counts\n",
    "fig = plt.figure(figsize=(20, 20))\n",
    "ax1 = plt.subplot2grid((2, 2), (0, 0))\n",
    "ax2 = plt.subplot2grid((2, 2), (0, 1))\n",
    "ax3 = plt.subplot2grid((2, 2), (1, 0), colspan=2)\n",
    "\n",
    "cmap = plt.get_cmap('Blues')\n",
    "color = cmap(np.array([175, 150, 125, 100, 75, 50]))\n",
    "ax1.pie(uncount.NDcount, labels=['6 of 6 replicates\\n({:d} proteins)'.format(uncount.at[0.0, 'NDcount']), \n",
    "                                 '5 of 6 replicates\\n({:d} proteins)'.format(uncount.at[1.0, 'NDcount']), \n",
    "                                 '4 of 6 replicates\\n({:d} proteins)'.format(uncount.at[2.0, 'NDcount']), \n",
    "                                 '3 of 6 replicates\\n({:d} proteins)'.format(uncount.at[3.0, 'NDcount']), \n",
    "                                 '2 of 6 replicates\\n({:d} proteins)'.format(uncount.at[4.0, 'NDcount']), \n",
    "                                 '1 of 6 replicates\\n({:d} proteins)'.format(uncount.at[5.0, 'NDcount'])], \n",
    "        autopct='%1.2f%%', colors=color, \n",
    "        explode=(0.0, 0.025, 0.1, 0.1, 0.1, 0.1), pctdistance=0.8, textprops={'fontsize': 15})\n",
    "ax1.set_title('Uninduced Replicates', fontsize=25, y=0.95)\n",
    "\n",
    "cmap = plt.get_cmap('Reds')\n",
    "color = cmap(np.array([175, 150, 125, 100, 75, 50]))\n",
    "ax2.pie(indcount.NDcount, labels=['6 of 6 replicates\\n({:d} proteins)'.format(indcount.at[0.0, 'NDcount']), \n",
    "                                 '5 of 6 replicates\\n({:d} proteins)'.format(indcount.at[1.0, 'NDcount']), \n",
    "                                 '4 of 6 replicates\\n({:d} proteins)'.format(indcount.at[2.0, 'NDcount']), \n",
    "                                 '3 of 6 replicates\\n({:d} proteins)'.format(indcount.at[3.0, 'NDcount']), \n",
    "                                 '2 of 6 replicates\\n({:d} proteins)'.format(indcount.at[4.0, 'NDcount']), \n",
    "                                 '1 of 6 replicates\\n({:d} proteins)'.format(indcount.at[5.0, 'NDcount'])], \n",
    "        autopct='%1.2f%%', colors=color, \n",
    "        explode=(0.0, 0.025, 0.1, 0.1, 0.1, 0.1), pctdistance=0.8, textprops={'fontsize': 15})\n",
    "ax2.set_title('Induced Replicates', fontsize=25, y=0.95)\n",
    "\n",
    "v1 = venn2((set(un.index), set(ind.index)), set_labels=('Uninduced', 'Induced'), ax=ax3)\n",
    "for t in v1.subset_labels:\n",
    "    t.set_fontsize(18)\n",
    "for t in v1.set_labels:\n",
    "    t.set_fontsize(18)\n",
    "v1.get_patch_by_id('10').set_color('blue')\n",
    "v1.get_patch_by_id('01').set_color('red')\n",
    "v1.get_patch_by_id('11').set_color('magenta')\n",
    "ax3.set_title('Comparing proteins found in \\nat least 1 replicate per condition', fontsize=25, y=0.95)\n",
    "\n",
    "plt.suptitle('Breakdown of Protein Detection Across WT Biological Replicates', fontsize=35, y=0.93, x=0.5)\n",
    "plt.savefig('ProteinDetectionComparisons.png', dpi=300, bbox_inches = \"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(244, 15)\n",
      "(188, 15)\n"
     ]
    }
   ],
   "source": [
    "# Commonly detected proteins only in uninduced and induced, respectively\n",
    "un_onlylist = np.setdiff1d((un.index), (ind.index))\n",
    "un_only = un.loc[un_onlylist, :]\n",
    "print(un_only.shape)\n",
    "\n",
    "ind_onlylist = np.setdiff1d((ind.index), (un.index))\n",
    "ind_only = ind.loc[ind_onlylist, :]\n",
    "print(ind_only.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving dataframes un_only and ind_only\n",
    "un_only.to_csv('20190523_UninducedDetectedOnly_1ormore.csv', sep=',')\n",
    "\n",
    "ind_only.to_csv('20190523_InducedDetectedOnly_1ormore.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generating a further refined list for each condition that strictly looks for proteins present in all replicates of one condition and\n",
    "# not at all present in the other condition\n",
    "un6 = un_only[un_only.NDcount == 0]\n",
    "un6 = un6.loc[:, 'Gene':'Probability_uc2']\n",
    "un6.to_csv('20190523_UninducedDetectedOnly6of6.csv', sep=',')\n",
    "\n",
    "ind6 = ind_only[ind_only.NDcount == 0]\n",
    "ind6.loc[:, 'Gene':'Probability_ic2']\n",
    "ind6.to_csv('20190523_InducedDetectedOnly6of6.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving just UniProt IDs from each condition for STRING analysis\n",
    "un = un_only.reset_index()\n",
    "un = un.rename({'index':'ProteinID'}, axis='columns')\n",
    "un = un['ProteinID']\n",
    "un.to_csv('20190523_UninducedIDs.csv', index=False, header=False)\n",
    "\n",
    "ind = ind_only.reset_index()\n",
    "ind = ind.rename({'index':'ProteinID'}, axis='columns')\n",
    "ind = ind['ProteinID']\n",
    "ind.to_csv('20190523_InducedIDs.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProteinID</th>\n",
       "      <th>Gene</th>\n",
       "      <th>ProteinInfo</th>\n",
       "      <th>Compartment_ua1</th>\n",
       "      <th>Probability_ua1</th>\n",
       "      <th>Compartment_ub1</th>\n",
       "      <th>Probability_ub1</th>\n",
       "      <th>Compartment_uc1</th>\n",
       "      <th>Probability_uc1</th>\n",
       "      <th>Compartment_ua2</th>\n",
       "      <th>Probability_ua2</th>\n",
       "      <th>Compartment_ub2</th>\n",
       "      <th>Probability_ub2</th>\n",
       "      <th>Compartment_uc2</th>\n",
       "      <th>Probability_uc2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q14865</td>\n",
       "      <td>ARI5B</td>\n",
       "      <td>ARI5B_HUMAN AT-richinteractivedomain-containin...</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>0.998</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Unclassified</td>\n",
       "      <td>0.542</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>0.988</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q32NC0</td>\n",
       "      <td>CR021</td>\n",
       "      <td>CR021_HUMAN UPF0711proteinC18orf21</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q96AK3</td>\n",
       "      <td>ABC3D</td>\n",
       "      <td>ABC3D_HUMAN ProbableDNAdC-&gt;dU-editingenzymeAPO...</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q9NP50</td>\n",
       "      <td>FA60A</td>\n",
       "      <td>FA60A_HUMAN ProteinFAM60A</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>0.98</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>0.952</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>0.902</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q9UQ84</td>\n",
       "      <td>EXO1</td>\n",
       "      <td>EXO1_HUMAN Exonuclease1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ProteinID   Gene                                        ProteinInfo  \\\n",
       "0    Q14865  ARI5B  ARI5B_HUMAN AT-richinteractivedomain-containin...   \n",
       "1    Q32NC0  CR021                 CR021_HUMAN UPF0711proteinC18orf21   \n",
       "2    Q96AK3  ABC3D  ABC3D_HUMAN ProbableDNAdC->dU-editingenzymeAPO...   \n",
       "3    Q9NP50  FA60A                          FA60A_HUMAN ProteinFAM60A   \n",
       "4    Q9UQ84   EXO1                            EXO1_HUMAN Exonuclease1   \n",
       "\n",
       "         Compartment_ua1 Probability_ua1        Compartment_ub1  \\\n",
       "0  Large Protein Complex           0.998  Large Protein Complex   \n",
       "1  Large Protein Complex               1  Large Protein Complex   \n",
       "2  Large Protein Complex               1  Large Protein Complex   \n",
       "3  Large Protein Complex            0.98  Large Protein Complex   \n",
       "4  Large Protein Complex               1  Large Protein Complex   \n",
       "\n",
       "  Probability_ub1        Compartment_uc1 Probability_uc1  \\\n",
       "0               1           Unclassified           0.542   \n",
       "1               1  Large Protein Complex               1   \n",
       "2               1  Large Protein Complex               1   \n",
       "3           0.952  Large Protein Complex               1   \n",
       "4               1  Large Protein Complex               1   \n",
       "\n",
       "         Compartment_ua2 Probability_ua2        Compartment_ub2  \\\n",
       "0  Large Protein Complex           0.988  Large Protein Complex   \n",
       "1  Large Protein Complex               1  Large Protein Complex   \n",
       "2  Large Protein Complex               1  Large Protein Complex   \n",
       "3  Large Protein Complex           0.902  Large Protein Complex   \n",
       "4  Large Protein Complex               1  Large Protein Complex   \n",
       "\n",
       "  Probability_ub2        Compartment_uc2 Probability_uc2  \n",
       "0               1  Large Protein Complex               1  \n",
       "1               1  Large Protein Complex               1  \n",
       "2               1  Large Protein Complex               1  \n",
       "3               1  Large Protein Complex               1  \n",
       "4               1  Large Protein Complex               1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProteinID</th>\n",
       "      <th>Gene</th>\n",
       "      <th>ProteinInfo</th>\n",
       "      <th>Compartment_ia1</th>\n",
       "      <th>Probability_ia1</th>\n",
       "      <th>Compartment_ib1</th>\n",
       "      <th>Probability_ib1</th>\n",
       "      <th>Compartment_ic1</th>\n",
       "      <th>Probability_ic1</th>\n",
       "      <th>Compartment_ia2</th>\n",
       "      <th>Probability_ia2</th>\n",
       "      <th>Compartment_ib2</th>\n",
       "      <th>Probability_ib2</th>\n",
       "      <th>Compartment_ic2</th>\n",
       "      <th>Probability_ic2</th>\n",
       "      <th>NDcount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HIVNL43_TAT</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>0.928</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HIVNL43_VIF</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>P09486</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPRC_HUMAN SPARC</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>Endosome</td>\n",
       "      <td>1</td>\n",
       "      <td>Unclassified</td>\n",
       "      <td>0.52</td>\n",
       "      <td>Endosome</td>\n",
       "      <td>0.992</td>\n",
       "      <td>Endosome</td>\n",
       "      <td>0.974</td>\n",
       "      <td>Large Protein Complex</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ProteinID        Gene       ProteinInfo        Compartment_ia1  \\\n",
       "0  HIVNL43_TAT  tatprotein        tatprotein  Large Protein Complex   \n",
       "1  HIVNL43_VIF  vifprotein        vifprotein  Large Protein Complex   \n",
       "2       P09486        SPRC  SPRC_HUMAN SPARC  Large Protein Complex   \n",
       "\n",
       "  Probability_ia1        Compartment_ib1 Probability_ib1  \\\n",
       "0               1  Large Protein Complex               1   \n",
       "1               1  Large Protein Complex               1   \n",
       "2               1               Endosome               1   \n",
       "\n",
       "         Compartment_ic1 Probability_ic1        Compartment_ia2  \\\n",
       "0  Large Protein Complex               1  Large Protein Complex   \n",
       "1  Large Protein Complex               1  Large Protein Complex   \n",
       "2           Unclassified            0.52               Endosome   \n",
       "\n",
       "  Probability_ia2        Compartment_ib2 Probability_ib2  \\\n",
       "0               1  Large Protein Complex           0.928   \n",
       "1               1  Large Protein Complex               1   \n",
       "2           0.992               Endosome           0.974   \n",
       "\n",
       "         Compartment_ic2 Probability_ic2  NDcount  \n",
       "0  Large Protein Complex               1      0.0  \n",
       "1  Large Protein Complex               1      0.0  \n",
       "2  Large Protein Complex               1      0.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Saving just UniProt IDs from each condition for STRING analysis on more stringent un6 and ind6\n",
    "un = un6.reset_index()\n",
    "un = un.rename({'index':'ProteinID'}, axis='columns')\n",
    "display(un)\n",
    "un = un['ProteinID']\n",
    "un.to_csv('20190523_UninducedIDs6of6.csv', index=False, header=False)\n",
    "\n",
    "ind = ind6.reset_index()\n",
    "ind = ind.rename({'index':'ProteinID'}, axis='columns')\n",
    "display(ind)\n",
    "ind = ind['ProteinID']\n",
    "ind.to_csv('20190523_InducedIDs6of6.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Links to STRING Analyses for each:\n",
    "##### Note: HIV proteins will not appear here as they are not in the STRING database \n",
    "[Uninduced Replicates Only (detected in 1+ replicate)](https://version-11-0.string-db.org/cgi/network.pl?networkId=ADBdGO3aTNwd)<br>\n",
    "[Uninduced Replicates Only (detected in all 6 replicates)](https://version-11-0.string-db.org/cgi/network.pl?networkId=RdJN2aerUzVb)<br>\n",
    "[Induced Replicates Only (detected in 1+ replicate)](https://version-11-0.string-db.org/cgi/network.pl?networkId=lxDz9264bdmj)<br>\n",
    "[Induced Replicates Only (detected in all 6 replicates)](https://version-11-0.string-db.org/cgi/network.pl?networkId=WRdcPHmlJWmV)<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Partials included (proteins found in subset of fractions for a given technical replicate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set working directory to wild-type 1 folder\n",
    "os.chdir('Path/To/Data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading in full data for first wild-type experiment\n",
    "ua1 = pd.read_csv('UnA/20190308_UnA_raw_partials.csv', index_col=0)\n",
    "ua1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ua1.columns = ['Gene_ua1', 'ProteinInfo_ua1']\n",
    "\n",
    "ub1 = pd.read_csv('UnB/20190308_UnB_raw_partials.csv', index_col=0)\n",
    "ub1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ub1.columns = ['Gene_ub1', 'ProteinInfo_ub1']\n",
    "\n",
    "uc1 = pd.read_csv('UnC/20190308_UnC_raw_partials.csv', index_col=0)\n",
    "uc1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "uc1.columns = ['Gene_uc1', 'ProteinInfo_uc1']\n",
    "\n",
    "ia1 = pd.read_csv('IndA/20190308_IndA_raw_partials.csv', index_col=0)\n",
    "ia1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ia1.columns = ['Gene_ia1', 'ProteinInfo_ia1']\n",
    "\n",
    "ib1 = pd.read_csv('IndB/20190308_IndB_raw_partials.csv', index_col=0)\n",
    "ib1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ib1.columns = ['Gene_ib1', 'ProteinInfo_ib1']\n",
    "\n",
    "ic1 = pd.read_csv('IndC/20190308_IndC_raw_partials.csv', index_col=0)\n",
    "ic1.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ic1.columns = ['Gene_ic1', 'ProteinInfo_ic1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set working directory to wild-type 2 folder\n",
    "os.chdir('Path/To/Data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading in full data for second wild-type experiment\n",
    "ua2 = pd.read_csv('UnA/20190517_UnA_raw_partials.csv', index_col=0)\n",
    "ua2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ua2.columns = ['Gene_ua2', 'ProteinInfo_ua2']\n",
    "\n",
    "ub2 = pd.read_csv('UnB/20190517_UnB_raw_partials.csv', index_col=0)\n",
    "ub2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ub2.columns = ['Gene_ub2', 'ProteinInfo_ub2']\n",
    "\n",
    "uc2 = pd.read_csv('UnC/20190517_UnC_raw_partials.csv', index_col=0)\n",
    "uc2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "uc2.columns = ['Gene_uc2', 'ProteinInfo_uc2']\n",
    "\n",
    "ia2 = pd.read_csv('IndA/20190517_IndA_raw_partials.csv', index_col=0)\n",
    "ia2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ia2.columns = ['Gene_ia2', 'ProteinInfo_ia2']\n",
    "\n",
    "ib2 = pd.read_csv('IndB/20190517_IndB_raw_partials.csv', index_col=0)\n",
    "ib2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ib2.columns = ['Gene_ib2', 'ProteinInfo_ib2']\n",
    "\n",
    "ic2 = pd.read_csv('IndC/20190517_IndC_raw_partials.csv', index_col=0)\n",
    "ic2.drop(columns=['3K', '5.4K', '12.2K', '24K', '78.4K', '110K', '195.5K'], inplace=True)\n",
    "ic2.columns = ['Gene_ic2', 'ProteinInfo_ic2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set working directory to folder comparing biological replicates\n",
    "os.chdir('Path/To/Data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining commonly detected protein dataframes for uninduced\n",
    "unlist = [ua1, ub1, uc1, ua2, ub2, uc2]\n",
    "\n",
    "un = pd.concat(unlist, axis=1, join='outer', sort='True')\n",
    "\n",
    "un.fillna('ND', inplace=True)\n",
    "ndset = ['ND']\n",
    "un['NDcount'] = (un.isin(ndset).sum(1))/2\n",
    "\n",
    "for item in un.index:\n",
    "    if un.at[item, 'ProteinInfo_ua1'] is np.nan:\n",
    "        if un.at[item, 'ProteinInfo_ub1'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_ub1']\n",
    "        elif un.at[item, 'ProteinInfo_uc1'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_uc1']\n",
    "        elif un.at[item, 'ProteinInfo_ua2'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_ua2']\n",
    "        elif un.at[item, 'ProteinInfo_ub2'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_ub2']\n",
    "        elif un.at[item, 'ProteinInfo_uc2'] is not np.nan:\n",
    "            un.at[item, 'ProteinInfo_ua1'] = un.at[item, 'ProteinInfo_uc2']\n",
    "                \n",
    "for item in un.index:\n",
    "    if un.at[item, 'Gene_ua1'] is np.nan:\n",
    "        if un.at[item, 'Gene_ub1'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_ub1']\n",
    "        elif un.at[item, 'Gene_uc1'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_uc1']\n",
    "        elif un.at[item, 'Gene_ua2'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_ua2']\n",
    "        elif un.at[item, 'Gene_ub2'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_ub2']\n",
    "        elif un.at[item, 'Gene_uc2'] is not np.nan:\n",
    "            un.at[item, 'Gene_ua1'] = un.at[item, 'Gene_uc2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defining commonly detected protein dataframes for induced\n",
    "indlist = [ia1, ib1, ic1, ia2, ib2, ic2]\n",
    "\n",
    "ind = pd.concat(indlist, axis=1, join='outer', sort='True')\n",
    "\n",
    "ind.fillna('ND', inplace=True)\n",
    "ndset = ['ND']\n",
    "ind['NDcount'] = (ind.isin(ndset).sum(1))/2\n",
    "\n",
    "for item in ind.index:\n",
    "    if ind.at[item, 'ProteinInfo_ia1'] is np.nan:\n",
    "        if ind.at[item, 'ProteinInfo_ib1'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ib1']\n",
    "        elif ind.at[item, 'ProteinInfo_ic1'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ic1']\n",
    "        elif ind.at[item, 'ProteinInfo_ia2'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ia2']\n",
    "        elif ind.at[item, 'ProteinInfo_ib2'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ib2']\n",
    "        elif ind.at[item, 'ProteinInfo_ic2'] is not np.nan:\n",
    "            ind.at[item, 'ProteinInfo_ia1'] = ind.at[item, 'ProteinInfo_ic2']\n",
    "                \n",
    "for item in ind.index:\n",
    "    if ind.at[item, 'Gene_ia1'] is np.nan:\n",
    "        if ind.at[item, 'Gene_ib1'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ib1']\n",
    "        elif ind.at[item, 'Gene_ic1'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ic1']\n",
    "        elif ind.at[item, 'Gene_ia2'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ia2']\n",
    "        elif ind.at[item, 'Gene_ib2'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ib2']\n",
    "        elif ind.at[item, 'Gene_ic2'] is not np.nan:\n",
    "            ind.at[item, 'Gene_ia1'] = ind.at[item, 'Gene_ic2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pulling out value counts for ND columns (Not Detected)\n",
    "uncount = un.NDcount.value_counts().to_frame()\n",
    "uncount.sort_index(inplace=True)\n",
    "\n",
    "indcount = ind.NDcount.value_counts().to_frame()\n",
    "indcount.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pie plots of protein replicate counts\n",
    "fig = plt.figure(figsize=(20, 20))\n",
    "ax1 = plt.subplot2grid((2, 2), (0, 0))\n",
    "ax2 = plt.subplot2grid((2, 2), (0, 1))\n",
    "ax3 = plt.subplot2grid((2, 2), (1, 0), colspan=2)\n",
    "\n",
    "cmap = plt.get_cmap('Blues')\n",
    "color = cmap(np.array([175, 150, 125, 100, 75, 50]))\n",
    "ax1.pie(uncount.NDcount, labels=['6 of 6 replicates\\n({:d} proteins)'.format(uncount.at[0.0, 'NDcount']), \n",
    "                                 '5 of 6 replicates\\n({:d} proteins)'.format(uncount.at[1.0, 'NDcount']), \n",
    "                                 '4 of 6 replicates\\n({:d} proteins)'.format(uncount.at[2.0, 'NDcount']), \n",
    "                                 '3 of 6 replicates\\n({:d} proteins)'.format(uncount.at[3.0, 'NDcount']), \n",
    "                                 '2 of 6 replicates\\n({:d} proteins)'.format(uncount.at[4.0, 'NDcount']), \n",
    "                                 '1 of 6 replicates\\n({:d} proteins)'.format(uncount.at[5.0, 'NDcount'])], \n",
    "        autopct='%1.2f%%', colors=color, \n",
    "        explode=(0.0, 0.025, 0.1, 0.1, 0.1, 0.1), pctdistance=0.8, textprops={'fontsize': 15})\n",
    "ax1.set_title('Uninduced Replicates', fontsize=25, y=0.95)\n",
    "\n",
    "cmap = plt.get_cmap('Reds')\n",
    "color = cmap(np.array([175, 150, 125, 100, 75, 50]))\n",
    "ax2.pie(indcount.NDcount, labels=['6 of 6 replicates\\n({:d} proteins)'.format(indcount.at[0.0, 'NDcount']), \n",
    "                                 '5 of 6 replicates\\n({:d} proteins)'.format(indcount.at[1.0, 'NDcount']), \n",
    "                                 '4 of 6 replicates\\n({:d} proteins)'.format(indcount.at[2.0, 'NDcount']), \n",
    "                                 '3 of 6 replicates\\n({:d} proteins)'.format(indcount.at[3.0, 'NDcount']), \n",
    "                                 '2 of 6 replicates\\n({:d} proteins)'.format(indcount.at[4.0, 'NDcount']), \n",
    "                                 '1 of 6 replicates\\n({:d} proteins)'.format(indcount.at[5.0, 'NDcount'])], \n",
    "        autopct='%1.2f%%', colors=color, \n",
    "        explode=(0.0, 0.025, 0.1, 0.1, 0.1, 0.1), pctdistance=0.8, textprops={'fontsize': 15})\n",
    "ax2.set_title('Induced Replicates', fontsize=25, y=0.95)\n",
    "\n",
    "v1 = venn2((set(un.index), set(ind.index)), set_labels=('Uninduced', 'Induced'), ax=ax3)\n",
    "for t in v1.subset_labels:\n",
    "    t.set_fontsize(18)\n",
    "for t in v1.set_labels:\n",
    "    t.set_fontsize(18)\n",
    "v1.get_patch_by_id('10').set_color('blue')\n",
    "v1.get_patch_by_id('01').set_color('red')\n",
    "v1.get_patch_by_id('11').set_color('magenta')\n",
    "ax3.set_title('Comparing proteins found in \\nat least 1 replicate per condition', fontsize=25, y=0.95)\n",
    "\n",
    "plt.suptitle('Breakdown of Protein Detection Across WT Biological Replicates', fontsize=35, y=0.93, x=0.5)\n",
    "plt.savefig('ProteinDetectionComparisons_partials.png', dpi=300, bbox_inches = \"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(223, 13)\n",
      "(166, 13)\n"
     ]
    }
   ],
   "source": [
    "# Commonly detected proteins only in uninduced and induced, respectively\n",
    "un_onlylist = np.setdiff1d((un.index), (ind.index))\n",
    "un_only = un.loc[un_onlylist, :]\n",
    "print(un_only.shape)\n",
    "\n",
    "ind_onlylist = np.setdiff1d((ind.index), (un.index))\n",
    "ind_only = ind.loc[ind_onlylist, :]\n",
    "print(ind_only.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving dataframes un_only and ind_only\n",
    "un_only.to_csv('20190523_UninducedDetectedOnly_1ormore_partials.csv', sep=',')\n",
    "\n",
    "ind_only.to_csv('20190523_InducedDetectedOnly_1ormore_partials.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Aaron Oom\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:4025: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  return super(DataFrame, self).rename(**kwargs)\n"
     ]
    }
   ],
   "source": [
    "# Generating a further refined list for each condition that strictly looks for proteins present in all replicates of one condition and\n",
    "# not at all present in the other condition\n",
    "un6 = un_only[un_only.NDcount == 0]\n",
    "un6.rename({'Gene_ua1':'Gene', 'ProteinInfo_ua1':'ProteinInfo'}, axis='columns', inplace=True)\n",
    "un6 = un6.loc[:, 'Gene':'ProteinInfo']\n",
    "un6.to_csv('20190523_UninducedDetectedOnly6of6_partials.csv', sep=',')\n",
    "\n",
    "ind6 = ind_only[ind_only.NDcount == 0]\n",
    "ind6.rename({'Gene_ia1':'Gene', 'ProteinInfo_ia1':'ProteinInfo'}, axis='columns', inplace=True)\n",
    "ind6.loc[:, 'Gene':'ProteinInfo']\n",
    "ind6.to_csv('20190523_InducedDetectedOnly6of6_partials.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving just UniProt IDs from each condition for STRING analysis\n",
    "un = un_only.reset_index()\n",
    "un = un.rename({'index':'ProteinID'}, axis='columns')\n",
    "un = un['ProteinID']\n",
    "un.to_csv('20190523_UninducedIDs_partials.csv', index=False, header=False)\n",
    "\n",
    "ind = ind_only.reset_index()\n",
    "ind = ind.rename({'index':'ProteinID'}, axis='columns')\n",
    "ind = ind['ProteinID']\n",
    "ind.to_csv('20190523_InducedIDs_partials.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProteinID</th>\n",
       "      <th>Gene</th>\n",
       "      <th>ProteinInfo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q14865</td>\n",
       "      <td>ARI5B</td>\n",
       "      <td>ARI5B_HUMAN AT-richinteractivedomain-containin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q96AK3</td>\n",
       "      <td>ABC3D</td>\n",
       "      <td>ABC3D_HUMAN ProbableDNAdC-&gt;dU-editingenzymeAPO...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q9NP50</td>\n",
       "      <td>FA60A</td>\n",
       "      <td>FA60A_HUMAN ProteinFAM60A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q9UQ84</td>\n",
       "      <td>EXO1</td>\n",
       "      <td>EXO1_HUMAN Exonuclease1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ProteinID   Gene                                        ProteinInfo\n",
       "0    Q14865  ARI5B  ARI5B_HUMAN AT-richinteractivedomain-containin...\n",
       "1    Q96AK3  ABC3D  ABC3D_HUMAN ProbableDNAdC->dU-editingenzymeAPO...\n",
       "2    Q9NP50  FA60A                          FA60A_HUMAN ProteinFAM60A\n",
       "3    Q9UQ84   EXO1                            EXO1_HUMAN Exonuclease1"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProteinID</th>\n",
       "      <th>Gene</th>\n",
       "      <th>ProteinInfo</th>\n",
       "      <th>Gene_ib1</th>\n",
       "      <th>ProteinInfo_ib1</th>\n",
       "      <th>Gene_ic1</th>\n",
       "      <th>ProteinInfo_ic1</th>\n",
       "      <th>Gene_ia2</th>\n",
       "      <th>ProteinInfo_ia2</th>\n",
       "      <th>Gene_ib2</th>\n",
       "      <th>ProteinInfo_ib2</th>\n",
       "      <th>Gene_ic2</th>\n",
       "      <th>ProteinInfo_ic2</th>\n",
       "      <th>NDcount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HIVNL43_TAT</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>tatprotein</td>\n",
       "      <td>HIVNL43_TAT|tat</td>\n",
       "      <td>TAT|tat protein|HIV-1 Strain NL4-3</td>\n",
       "      <td>HIVNL43_TAT|tat</td>\n",
       "      <td>TAT|tat protein|HIV-1 Strain NL4-3</td>\n",
       "      <td>HIVNL43_TAT|tat</td>\n",
       "      <td>TAT|tat protein|HIV-1 Strain NL4-3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HIVNL43_VIF</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>vifprotein</td>\n",
       "      <td>HIVNL43_VIF|vif</td>\n",
       "      <td>VIF|vif protein|HIV-1 Strain NL4-3</td>\n",
       "      <td>HIVNL43_VIF|vif</td>\n",
       "      <td>VIF|vif protein|HIV-1 Strain NL4-3</td>\n",
       "      <td>HIVNL43_VIF|vif</td>\n",
       "      <td>VIF|vif protein|HIV-1 Strain NL4-3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>P09486</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPRC_HUMAN SPARC</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPRC_HUMAN SPARC</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPRC_HUMAN SPARC</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPARC</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPARC</td>\n",
       "      <td>SPRC</td>\n",
       "      <td>SPARC</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ProteinID        Gene       ProteinInfo    Gene_ib1   ProteinInfo_ib1  \\\n",
       "0  HIVNL43_TAT  tatprotein        tatprotein  tatprotein        tatprotein   \n",
       "1  HIVNL43_VIF  vifprotein        vifprotein  vifprotein        vifprotein   \n",
       "2       P09486        SPRC  SPRC_HUMAN SPARC        SPRC  SPRC_HUMAN SPARC   \n",
       "\n",
       "     Gene_ic1   ProteinInfo_ic1         Gene_ia2  \\\n",
       "0  tatprotein        tatprotein  HIVNL43_TAT|tat   \n",
       "1  vifprotein        vifprotein  HIVNL43_VIF|vif   \n",
       "2        SPRC  SPRC_HUMAN SPARC             SPRC   \n",
       "\n",
       "                      ProteinInfo_ia2         Gene_ib2  \\\n",
       "0  TAT|tat protein|HIV-1 Strain NL4-3  HIVNL43_TAT|tat   \n",
       "1  VIF|vif protein|HIV-1 Strain NL4-3  HIVNL43_VIF|vif   \n",
       "2                               SPARC             SPRC   \n",
       "\n",
       "                      ProteinInfo_ib2         Gene_ic2  \\\n",
       "0  TAT|tat protein|HIV-1 Strain NL4-3  HIVNL43_TAT|tat   \n",
       "1  VIF|vif protein|HIV-1 Strain NL4-3  HIVNL43_VIF|vif   \n",
       "2                               SPARC             SPRC   \n",
       "\n",
       "                      ProteinInfo_ic2  NDcount  \n",
       "0  TAT|tat protein|HIV-1 Strain NL4-3      0.0  \n",
       "1  VIF|vif protein|HIV-1 Strain NL4-3      0.0  \n",
       "2                               SPARC      0.0  "
      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "# Saving just UniProt IDs from each condition for STRING analysis on more stringent un6 and ind6\n",
    "un = un6.reset_index()\n",
    "un = un.rename({'index':'ProteinID'}, axis='columns')\n",
    "display(un)\n",
    "un = un['ProteinID']\n",
    "un.to_csv('20190523_UninducedIDs6of6_partials.csv', index=False, header=False)\n",
    "\n",
    "ind = ind6.reset_index()\n",
    "ind = ind.rename({'index':'ProteinID'}, axis='columns')\n",
    "display(ind)\n",
    "ind = ind['ProteinID']\n",
    "ind.to_csv('20190523_InducedIDs6of6_partials.csv', index=False, header=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Links to STRING Analyses for each (partials included):\n",
    "##### Note: HIV proteins will not appear here as they are not in the STRING database \n",
    "[Uninduced Replicates Only (detected in 1+ replicate)](https://version-11-0.string-db.org/cgi/network.pl?networkId=EFTh1WoA9sLg)<br>\n",
    "[Uninduced Replicates Only (detected in all 6 replicates)](https://version-11-0.string-db.org/cgi/network.pl?networkId=YYfdv2bjfhPH)<br>\n",
    "[Induced Replicates Only (detected in 1+ replicate)](https://version-11-0.string-db.org/cgi/network.pl?networkId=RM0RsImrSEyI)<br>\n",
    "[Induced Replicates Only (detected in all 6 replicates)](https://version-11-0.string-db.org/cgi/network.pl?networkId=vdSVOdOAYHwf)<br>"
   ]
  }
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