5b difference in who is nominated.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from epi_model import *\n",
    "tnets = [\n",
    "    temporalNetwork.load('high school').range(1,2),\n",
    "    temporalNetwork.load('high school2')\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def friendCloseChain_5(sim, vaccinateN=100):\n",
    "    return sampling.friendCloseChain(sim, vaccinateN, 0.5)\n",
    "\n",
    "def friendHighDegRandTop3(sim, vaccinateN):\n",
    "    return sampling.friendHighDegRandTopN(sim, vaccinateN, N=3)\n",
    "def friendHighDegRandTop5(sim, vaccinateN):\n",
    "    return sampling.friendHighDegRandTopN(sim, vaccinateN, N=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "tnet = tnets[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = dict(params.covid_estimate)\n",
    "p['s2e'] = params.daily_to_momentary(tnet, 0.1)\n",
    "sim = simulations.SEIR_daily(tnet, p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_TO_GET = int(0.10 * tnet.Nnodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def friendHighDegNormalErr10(sim, vaccinateN):\n",
    "    return sampling.friendHighDegNormalErr(sim, vaccinateN, sigma=10)\n",
    "def friendHighDegNormalErr20(sim, vaccinateN):\n",
    "    return sampling.friendHighDegNormalErr(sim, vaccinateN, sigma=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "ktransfer = dict(zip(\n",
    "\"\"\"friendChain\n",
    "friendHighDegChain\n",
    "local_betweenness\n",
    "targeted\n",
    "friendHighDeg\n",
    "friend\n",
    "friendHighDegRandTop3\n",
    "friendHighDegRandTop5\n",
    "friendHighDegNormalErr10\n",
    "friendHighDegNormalErr20\"\"\".split(\"\\n\"), \n",
    "\"\"\"NR(c)\n",
    "NP(c)\n",
    "B\n",
    "D\n",
    "NP\n",
    "NR\n",
    "NP(N=3)\n",
    "NP(N=5)\n",
    "NP(ε=10)\n",
    "NP(ε=20)\"\"\".split(\"\\n\")\n",
    "))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "strats = [\n",
    "    sampling.friend,\n",
    "    sampling.friendHighDeg,\n",
    "    sampling.targeted,\n",
    "    #sampling.none,\n",
    "    #sampling.rand,\n",
    "    #sampling.friendHighDegClose,\n",
    "    #sampling.friendClose,\n",
    "    #sampling.local_betweenness,\n",
    "    #sampling.nominate_local_betweenness,\n",
    "    sampling.friendHighDegChain,\n",
    "    sampling.friendChain,\n",
    "    #sampling.friendCloseChain,\n",
    "    #friendCloseChain_5,\n",
    "    #sampling.friendHighDegCloseChain,\n",
    "    #sampling.friendWeightedChain,\n",
    "    #sampling.friendWeighted,\n",
    "    friendHighDegRandTop3,\n",
    "    friendHighDegRandTop5,\n",
    "    friendHighDegNormalErr10,\n",
    "    friendHighDegNormalErr20\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "friendHighDegNormalErr20\n",
      "friendHighDegNormalErr10\n",
      "friendHighDegRandTop5\n",
      "friendHighDegRandTop3\n",
      "friendChain\n",
      "friendHighDegChain\n",
      "targeted\n",
      "friendHighDeg\n",
      "friend\n"
     ]
    }
   ],
   "source": [
    "db = defaultdict(list)\n",
    "for s in reversed(strats):\n",
    "    sn = s.__name__\n",
    "    print(sn)\n",
    "\n",
    "    for i in range(500):\n",
    "        val = s(sim, N_TO_GET)\n",
    "        db[ktransfer[sn]].append(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "ks = \"\"\"NR\n",
    "NR(c)\n",
    "NP(ε=10)\n",
    "NP(ε=20)\n",
    "NP(N=3)\n",
    "NP(N=5)\n",
    "NP\n",
    "NP(c)\n",
    "D\"\"\".split(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "mat = np.zeros( (len(ks),len(ks)) )\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        \n",
    "        overlaps = []\n",
    "        for j in range(50):\n",
    "            s1 = set( db[k1][j] )\n",
    "            s2 = set( db[k2][j] )\n",
    "            \n",
    "            overlap = len(s1.intersection(s2))\n",
    "            overlaps.append(overlap / N_TO_GET)\n",
    "            \n",
    "        mat[i1,i2] = np.mean(overlaps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(mat)\n",
    "plt.colorbar();\n",
    "plt.xticks(\n",
    "    range(len(ks)),\n",
    "    [x+1 for x in range(len(ks))],\n",
    ");\n",
    "\n",
    "plt.yticks(\n",
    "    range(len(ks)),\n",
    "    [x+1 for x in range(len(ks))],\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "mat = np.zeros( (len(ks),len(ks)) )\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        \n",
    "        overlaps = []\n",
    "        for j in range(500):\n",
    "            s1 = set( db[k1][j] )\n",
    "            s2 = set( db[k2][(j+1)%500] )\n",
    "            \n",
    "            overlap = len(s1.intersection(s2))\n",
    "            overlaps.append(overlap)\n",
    "            \n",
    "        mat[i1,i2] = np.mean(overlaps) / N_TO_GET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plt.imshow(mat)\n",
    "#lt.colorbar();\n",
    "plt.xticks(\n",
    "    range(len(ks)),\n",
    "    ks,\n",
    "    rotation=30\n",
    ");\n",
    "\n",
    "plt.yticks(\n",
    "    range(len(ks)),\n",
    "    #x+1 for x in range(len(ks))],\n",
    "    ks\n",
    ");\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        v = mat[i1,i2]\n",
    "        plt.text( i1-0.25, i2, f\"{v:0.0%}\", color='white' if v < 0.6 else 'black' )\n",
    "\n",
    "plt.savefig('figures/comparison.HS1.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. friend\n",
    "2. friendChain\n",
    "3. friendHighDeg\n",
    "4. friendHighDegChain\n",
    "5. local_betweenness\n",
    "6. targeted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1. NR\n",
      "2. NR(c)\n",
      "3. NP(ε=10)\n",
      "4. NP(ε=20)\n",
      "5. NP(N=3)\n",
      "6. NP(N=5)\n",
      "7. NP\n",
      "8. NP(c)\n",
      "9. D\n"
     ]
    }
   ],
   "source": [
    "for i,k in enumerate(ks):\n",
    "    print(f\"{i+1}. {k}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# HS-2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "tnet = tnets[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = dict(params.covid_estimate)\n",
    "p['s2e'] = params.daily_to_momentary(tnet, 0.1)\n",
    "sim = simulations.SEIR_daily(tnet, p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_TO_GET = int(0.10 * tnet.Nnodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "friendHighDegNormalErr20\n",
      "friendHighDegNormalErr10\n",
      "friendHighDegRandTop5\n",
      "friendHighDegRandTop3\n",
      "friendChain\n",
      "friendHighDegChain\n",
      "targeted\n",
      "friendHighDeg\n",
      "friend\n"
     ]
    }
   ],
   "source": [
    "db = defaultdict(list)\n",
    "for s in reversed(strats):\n",
    "    sn = s.__name__\n",
    "    print(sn)\n",
    "\n",
    "    for i in range(500):\n",
    "        val = s(sim, N_TO_GET)\n",
    "        db[ktransfer[sn]].append(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "mat = np.zeros( (len(ks),len(ks)) )\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        \n",
    "        overlaps = []\n",
    "        for j in range(500):\n",
    "            s1 = set( db[k1][j] )\n",
    "            s2 = set( db[k2][(j+1)%500] )\n",
    "            \n",
    "            overlap = len(s1.intersection(s2))\n",
    "            overlaps.append(overlap)\n",
    "            \n",
    "        mat[i1,i2] = np.mean(overlaps) / N_TO_GET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pqRa+fO0nenzYnimfPZz5wQ22wcsNefLZmo78Q+c68o9eTr8xLzq2wes/02NYO6Z8ttDVUW8RViwXZWsV54UBrUlPszBx2FxO7Dv3yOSHh3MdnF7glVIa+Fpr/W7GdD/AT2s9TCk1DOgJRAOewMda61+yLDsKmKe13niH1y4PvKu1fvGBrsRdOL0/gjfDBwFQvl5pblyJAaUY9EtfrBYrP/abSuzVOBenvLPT+8/xZp3BQEb+yNiM/G9jtdgeqvyLf17PzJGL0Rq6DWxNz4878M2bUzhz6CJ9m44AoFztEtyIikMpGDCxJzarjfFDfiU2OsHF6d0g/+QNzPxqiSP/gFb0/Kg937w11ZH/6c+BLPmBARN6YrPYGD/04cgPbrYN+rei54ft+ObtaY78zb4AoFyt4tyIinfkH9/DkX/obw9FfqPRgH8OX95++nNKVi7MwAk9ebH64EcmPzyc6+CKIfo0oK1SKuQO87/RWlcCWgM/KqU8AJRSwUCtOxV3AK31QSC/Uqrgf5z5vnQZ1I4ZH8+l6wcdmPD+NJZNXMMzbzZzday71mVQW2Z88htdP2jPhPens2ziap7p87SrY2WKjU7AbtdorVk+dROlqhS+pU/nd5szc+RiurzXkknD5rJs6mZa92rk/LC34Vb5p22mVOXCt/Tp3LcZM79aQpf3WjDpw7ksm76J1j2fcH7YO3CrbTD9DtvgnWbM/DpjG3w0j2XTNtO6x8OxDa5FxrJlyV4ATuyNwK41gcF+2fo8zPnh4VwHVxR4KzAe6Pt3nbTWJ4FkIGdGUztg+Z/zlVLVlVJblVL7lVJ/KKX8M2YtAjr997H/ncbdGrBj2R4SYhLx8vFC2zV2ux0vH09XR7srjbs1YMfSvSTEJGXJr/Hy8XJ1tExBuQMzfw5vXpmIo9nviXiyU212rjpIYmwyXj6e2P/cBuaHYxs8+vkDMn8Ob1aJiGN/yd+xFjvXHHLkN/+ZXz80+cENtkGuu9gGqx/ebbB12T4q1i0FQFjRXHh4GIm7fvN+oYc9Pzyc66CcfSeiUioRyAccACriGJLPOkSfqLUeqZSqAnyrta6XsdwU4Det9SKllCdwDOiotd6plAoAkrXWVqVUHaC/1rrlbd67F9ALwBufqnXVvZ1FD5zxFhUaliUwxJ+YqDimDptDwo1EXh/9MoGhASTFJnF6XwQDnh4OgJfZk08WD6B/00+wWW2Uq/sYb37fE0u6lc+6fHvbm/Pu2r94vGLgjLeo0KDMzfwfZuT/Nkv+/REMePrTm/kX9af/U8Nv5h/Tw5H/+W9ve3PevTDmyHHPy/Qf34MKdUoREOxHTHQ800cspELdUhQtVwC0Jur8dUa/O50bUXGZ6/DRL30Y2H4UNquNsrWK88aXXbCmW/m890Qunoq6r3V4pPMb7n0f6v9jd0f+oIz8XyyiQnjJm/kvXGd0v+nciIrPyO/BRzP7MLDDKGxWuyP/589htVj5vPckLp6+z8/ffu9/vx6qbWC893Os/uO6U6FOyezboE5JipYtAGTk7zeDG1ezbIMZbzDw2W8d26Bmcd74vLNjG7zy0/1vg/8g/5pfd/DOt90oWjY/VouNCcPmsn/z8Ycy/8O2Diuif9ytta52u3kuKfBaaz+l1EeABUjh1mvwsUBJoKXWennGciuBD7TW2zOutY/TWte5zeuXAGZprav+XY4AFaRrqodjeO1fceEzoP+Vf1PgxX/oXxT4h86/KPAPlX9R4IXI6u8KvCv3rlFAd8D3L+3faK3L4hiSn6SU8s5oTwG8+WfeGX2FEEKI/1kuK/Ba6xvAHBxF/nbzFwK7gBcymo4CxTN+Pg7kVUpVB1BK+Sul/nwioCRw6EHlFkIIIR4Frh4f+gq40930AB8B7yilDMASoCGA1jod6Ah8p5TaD6zi5tn94xl9hRBCiP9ZTn8OXmvtl+XnKMAny/Swv/TdDZTKmNyklPpMKZVDax2rtd4J1MraXynlBVQD3n4w6YUQQohHg6vP4O/Vu8DfPeNeEMcd9FYn5RFCCCEeSo/UV9VqrXf8w/yTwEknxRFCCCEeWo/aGbwQQggh7oIUeCGEEMINSYEXQggh3JAUeCGEEMINSYEXQggh3JAUeCGEEMINSYEXQggh3JAUeCGEEMINSYEXQggh3JAUeCGEEMINSYEXQggh3JAUeCGEEMINSYEXQggh3JAUeCGEEMINSYEXQggh3JAUeCGEEMINmVwdwFWU0YgxINDVMf49o9HVCe5bxI/5XB3hvljO+Ls6wn3JXSHK1RHuW0Kql6sj3JewwDhXR7gvPqZ0V0e4byaD3dUR7k/4nWfJGbwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG5ICrwQQgjhhqTACyGEEG7I5OoAj5K+371IzSYViL2WwCt1hmab1/b1JvT6+FmeLf428TcSqdOyCt0GtCYhJokPn/+ehJgk8hYO5cUhbfms+4+uyf9tN2o2Lu/IX/8jAJ5/rwVPda1L3PVEACYP/52dqw9RpkYx+nzxHBaLjRG9J3L5zFV8A8wMnNiLwR1Ho7V2yTrYklK48sNC0s9fBaXI83przKUKELN0B7HL/gCDAd+qJcjVrQnJx84T9eNilIeRfG+3xzNfMLakFC5/9Sv5Bz+PMrjm+HZDz+4kpVuwaTs2u50202dmzuterSoDGzag2vc/EJOSStMSJXi7Tm3iUlN55feFxKamUjAwkH716vLm4iVOz55y4TonPl2UOZ12JZYCXeviGeLHhWlbSLlwnfKju+JXMi8A8Ycvcva7VSiTgRIDWmIOC8KamMqJ4QspPbwDyqCcvg62xFQujVlE6vlolIKwPq1QniYuj12KtljBYCDfK0/jUzKMuK1HuTpzPUZ/MwUHPIspwIe0yBtETVtHwf9r5/TsAEnnY9j/4bLM6eTIOIq/VIvCHSoDEDF7D8fHbubx33vimcPMlQ2nOPXzdjz8van8SXM8A80kX4rl5MRtVBz6tNPzJ5yPZecHq26uz+V4SveoTvFnK3D6t4OcmXcYZVDkCS9Iuddqc/1AJPu+2oTBZKT6sEb4FchBekIaOz9YRfhXzZ2+DyWci2XbB2tu5r8UT9me1SjZsTwnfz3E6bmHUUYDecMLUOH1Wlw7cIU9X27G4GGg5oeN8C8QSHpCGtsHr6beN80eaH4p8Pdg1cwtLJqwln5ju2drDwnLSdXHyxB14XpmW+uejXiz0XDqtKjC4+1rsnDCWl4Y1IYpw+c7O3amVbO2sWjSOvqNeSlb+/xxa5j7w6psbe1ebcyQzt+Ru2AwzV+oz4Shv9H5nWbMHrXMZcUd4OpPy/GtXJyw9zqiLVbs6RaSD54l8Y9jFPr6VQweJqxxjoOVmIVbyT+4C5arscSu3EWuF5ty/beNBLet57Li/qcuc+YQk5KarS2vvx91CxXiUnx8Zlu3KpV4ZvpMmpYoQavSjzF17z7eqVuHrzdvcXZkAMwFgqk49kUAtM3O7i5jCapTAlualVIftOHM6JXZ+kfO3cljH7cnLSqOqMX7KNz7CS7O3EZYp1ouKe4AkRNX4FelOAX7d8BusaHTLJz/ci65OtXHv2pxEnad5MqUNRQd3o3rS3ZS7KsexG87StzGQwS3qMHVGevJ/XxDl2QH8C2Yk/BJzwGObbC+/U/krlcMgJSrCVzbdR7v3P6Z/c/P20/tcR2J2niayDUnKNS2Iicnbad499ouye9fMAdPTO6QmX/ZM9PIV78I0XsuEbkpgicmd8DoaSQtJgWAk7MOEP5lM5IiEzj7+xHK9wnn+JQ9lOxa2SX7kH+hHDSZ0i4z/6LWMwirX5iruy9zedM5Gk9tj9HTSOoNR/4Tvxyg7ldPkRyZyJn5R6j4Zm2OTt7LYy88+PwyRH8PDm07SUJM0i3tvYd3ZOLQ3yBL4bPb7Xh4mvDy8cRqsVG2VgluXI3n8pmrzoycjSN/8l31tVpteJk98TJ7YrXayFs4hNCwIA5sPfGAU96ZLSmVlCPnCGxUBQDlYcLoayZ2xU6CnqmLwcNxvGoK9HPMNxrRaRZ0mgVlNJB+5QbWa/H4lCvisnX4O4Meb8jnGzdmO4DSWuNpNGL2MGGx26kWFkZ0UhIRsbEuy/mnuH3n8M6bA6/cgfgUDMZcIPiWPspowJ5mwZ5mQZmMpF6OIT06nsCKBV2Q2LEPJR0+T87GlQAweBgx+nmjAHtymqNPchoeQRn7kFKOA8k0K8poJOnweUw5/PDKd+u6usL1PRfwCQvEnCcAgONjNlKyd51sfZRBYbfYsKVZMRgNxBy4hFeQD775c7ggcXZXd1/CNywAnzz+nJ1/mJLPV8boaQTAK6cZAIPJgDXVii3NijIZSLwUR8rVREKrhLkyOgBRuy7jFxaAb15/Ts8/wmNdK2bm9w5y5FcmA7ZUK9bUjPwX40m+mkiuKvkeeD45g79PtZ6uxPXIWM4evpitffaoZXw2/12uX4nli94TGTT5FT7rPt5FKf9eq+4NefLZWpzYf44JH/xGYlwys79dRr/vXyI91cKXr/1Ejw/bM+WzBS7NabkagzHAhytjfiftXBTeRfOS6+WnSY+8TsrR81z7ZS3Kw0ToC00wFw8jqG1dIkfPR3l6kPetZ4iespKQzk+4dB0ANDC5fTvQ8MuBA8w6cJAnixUjKiGRY9HXsvUdu+MPpnVoT1RSIu8sWcaYVi14a/FS1wT/i2vrjxHcsPTf9gnrVItTXy7B4Gmi+P+14NyEdRR4sZ6TEt4qPSoWU6APl0YvJPVsFOZiecnbsyl5ejTh3LCZRP68GrSm6OcvAhDavg5nP5iOR5A/+fu24fwXcynQr63L8v/VlbUnyfNESQCubj6NV6gfAcVDs/Up0qUau96dj1ewL+UHNWX/sKVU+MD5Q/O3c3H1KfI/WQKAxAtxXD8QyZHxf2DwMlL+9drkLJ2Lkl0rs/uTtRi9TFQb8gQHv99GmZ7VXZzc4cLqUxRs7Bg9SbgQx7X9Vzj0404MniYqvlGToDK5KN21En98vB6jl5EaHzzOge+2U66Xc/L/Y4FXSmnga631uxnT/QA/rfUwpdQwoCcQnfFaA7XWCzP6vQ3c0FpP/bfhlFJvAG8DxYBQrfW1jHYFfAs0A5KBF7XWe5RSocA0rfVT//Y974WX2ZNO7zRjYNtvbpm3d/0R+qw/AkCjjrXZueog+Yvnpt0bTUiMTWbcgFmkpaQ7I+bfWjx5AzO/WoLW0G1AK3p+1J5v3prKmUMX6fv05wCUq12CG1FxKGDAhJ7YLDbGD/2V2OgE54a12Uk9E0mu7s0wl8xP1KRl3Ji/GW2zY0tMoeBnPUg9dYnIr36lyA9v4V0kL4VG9AQg+XAEppz+gObyV7+CyUCuF5piyuHn3HUAOv4ym6jERIJ9zExp357TN27waq0avPDr3Fv6bjl3ntbnZgDwTJnSrD9zliI5c9KjelXiU9P4aO06Uq1WZ68CdouNmO2nKPhy/b/t51ssN+W/7QpA/MELeAb5goYTwxegTEYK9Xocz5y+zojsYLOTcjqSvD2fwqdUGJETVhA9dwu2pDTydG9CYHhp4jYf5tJ3iyny8fP4VSpK8UpFAYhZux//qsVJv3ydy/O3YfQzk7dnUwxeHs7Ln4XdYuPqljOU6BmOLdXCmRm7qPplm1v6hVQrSEg1x4jJpRVHCalZmOQLMRyZvQeTvzel+9TH6O38dbBbbFzZco6yr9R0TNvspMen0WD8M8QcvcofH6yiyZznyFEihIbjHQdV1/ZdxjvYB63hjw9WYTAZKPdGbbyDfFyS//Lmc5R/tQYA2urI/8SENsQcjWbbkDU0+60TOUqG0GhCGwCi90biHeIDWrNtyGoMRgMV36z1wPLfzRB9GtBWKRVyh/nfaK0rAR2An5RSBqWUCXgZmHmHZe7WFuBJ4Nxf2p8GSmT86wWMBdBaRwORSqk6OEHewqHkKRjC2E1DmbJvBCH5cjJm/RBy5grI7ONl9qRx53AWTVxH1/6tGPnaTxzeforHO9R0RsR/FBudgN2u0VqzfNpmSlUufEufzn2bMfOrJXR5rwWTPpzLsumbaN3T+WfCpuAATMEBmEvmB8C/dhlSz0RiCg7Av2ZplFKYS+QHpbDF37wUobXm+tyNBLevz7U5Gwjt2pgcT1YlZskOp68DQFSi4x6B68kprDx1ipr581MgMJAlL3RlQ8/u5PH3Z2HX5wnxuflL720y0a5cWabv289b4bV5b9lydl26ROvSf38G/aDE7jyDb/Hcd12ctdaOa+/PhXNx+hYK9WhIrqcrcOX33Q84aXamkAA8QgLwKeUY3g0IL03K6SvErjtAQO3HHG11ypBy8lK25expFmLXHiC4WTWuztxA/rdb41OmALEbDjo1f1bXdkQQUDIUryAfki/HkRIZz9buM9nQ8WfSohPZ1usX0q7fvKRoS7VweflRCj5TgVOTd1BuQBNyls/H5dXHXZL/yvbz5CgZklnczKF+5GtQBKUUQWVyo5QiPfbmfSpaa45P2cNjL1bl2M+7KPdaLQq3LM3pX12zDSK3XSBn1vy5fAnLzJ8Lpbgl/9HJeyjzUhWO/LSHCq/VpGjrxzg559ADy3g3Q/RWYDzQFxh0p05a66NKKSsQAlQC9mitrQBKqY7AUCAFiNNa31V10FrvzVj+r7NaA1O142LldqVUDqVUXq11JPA70AXHwcEDFXH0Ep1KvZM5PWXfCPo88QnxNxIz29r3acqC8WuwWW14enuCBm2342U2P+h4dyUodwA3ohw3dYU3q0TEscvZ5j/ZsRY71xwiMTYZL7MndrvGbtd4mT2dntWU0x+PkEDSL13DMyyE5INn8MwfimeenCQfOotP+SKkX76GttowBtwsjvHr9+NbpQRGfx90mgUMCpRCp1ucvg5mDxMGFEkWC2YPE/UKFeK7bdup8cO4zD4benanzfQZ2W7C61m9GlP27MVqt+NtMqE12LXG7OGaq2zX1h8l5B+G57OKXn2YnNWL4hFgxpZmBaVQSmFPc+428Mjph0dIAGkXr+GVP4TEA2fxLhCKJSqGpEPn8CtfmKQDEXjmC8q23LX5WwluUR1lMmJPd+THBfmzilxzgryNSgHgXzSEx3/vmTlvQ8efqf1jJzxz3Pw7c3bWHgq2rYjBZHTcU6BAGcCe6vwRIPhzeL545nS++oWJ3nOZ0CphJJyPxW614ZnDO3P++eUnyF27IJ4B3thSM7aBQTn2Jxe4sOoUBRrfzB9WvzBX91wmV9V8Gfnt2fKfW3aSPOGO/NZUq+MGO/Vg89/tX4fvgQNKqS/u1EEpVROw4xiurwNkPTTvB7yitd6Ypb8/sOkOL/ec1vrI3+QJAy5kmb6Y0RYJ7AI+uUPGXjjO+PE23PuwYP8JPalQpxQBwX5MO/QF00csZMX0zXfsH5QnkFJVijDjC8djRQsnrGH0mkEkxqXw0fNj7vn971f/H7s78gf5MW3/CKZ/sYgK4SUpWq4AaE3UheuM7jc9s7+X2YPGncIZ2GEUAPPGrebjX/pgtVj5vPckp+cHyNX9aS5/OxdtseGZOyd53miDwcuDyB8WcPbt71EmI3n6tMk8KLSnpRO3bh8FPnAME+dsWZuLw2egTEbyve38x5xCfHwZ27oVAEaDYtHRY2yMiPjbZXL5+lIxbx6+27YdgKl79zL/+edISEvjld8XPujIt7ClphO3J4KibzXNbLu+5QQRP6zGEpfCsSFz8SmWizKfPpvR30L0yoOU/swxna9tNY4O+Q2DyUiJ/i2cnj9vz6e48PXvaKsNzzw5yP9mK/xrliRy4gqw2VEeJsJeu5nLcj2B5BOXydWpAQDBLapz+t2JGH29KTjwWafnB7CmWLi++wJl3r27kbTUa4nEHYui+IuOkcOCbSuy7ZXZePh5UfmT5g8y6m1ZUyxc3XmRyu/dvMRTqPlj7PlsPau7zsbgYaTqoCcyf4+tqRbOLz1OnW8cWYt3qsi295ZiMBmoNuxJl+SP2nmJqu/fzF+kRSl2Dt/Aii6/YvAwUGNwwyz5rUQsPU79UY78JTuVZ9O7yzB4GKk17MGNhqp/euRJKZWotfZTSn0EWHCchd/uGnwCjmvwm5RS44G1WutZGa/xLPAzcBaoq7WOvaeQSkUA1bJcg18MjNBab86YXgO8r7XepZTyAK5orf/2NtdAU6iuHdD6XmI8XIxGVye4bxE/Pvi7SB8kyxn/f+70EMtdIcrVEe5bQqqXqyPcl7DAOFdHuC8+JtffR3S/TAa7qyPcl1/Dx+/WWle73bx7Gd8bBezBUaiz+kZrPfIvbSmAd5bp3kBtrfWBPxvu8wz+ElAgy3T+jDYy3jflb5YVQggh3N5dF3it9Q2l1BygO/DTP3Q/ChTPMl2RjKKrlDIDdq11Ao5r9f/GQuANpdQsoCaO6/qRGfNKAg/urgUhhBDiEXCvX3TzFY6b6P7JMiDr8zOvA78rpfYD24C7+pYIpdSbSqmLOM7QDyilJmbMWgqcAU4BE4DXsiz2OOD87/AUQgghHiL/eAavtfbL8nMU4JNletgdljmnlLqulCqhtT6ptZ4NzL7XcFrr0cDo27RrHAcNt9MKx132QgghxP+sB/lVtf2BvA/w9W+R8UU3X2utY5z5vkIIIcTD5oE9RKu1Pg449RsUMr7o5ndnvqcQQgjxMJL/bEYIIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDdkcnUA19Fg164OcR9srg5w39LP+rs6wn0xRytXR7gvl0+EujrCfTOkP9rb4Kjvo/07gOFR/hua4dHehf6WnMELIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGTK4O8CjpO+YlajatQGx0Aq+Ef5BtXts3mtDrk448W/Qt4m8kUqdVVboNaE1CTBIfdhlDQkwSeQuH8uIHbfns5R9dk/+7F6nZpAKx1xJ4pc5QAJ5/vxVPda1H3PUEACZ/PJ+dqw9SpmZx+ox8Hku6lRE9x3P5zFV8A8wM/PkVBrcfhdbaJeuwsUd3ktIt2LQdm91O6xkzM+d1r1qVQQ0bUPWHH4hJSeWpEiV4O7w2camp9F6wkNjUVAoGBtKvXl3eXLzEJfkBDEoxp89zRMUn8vrkBQC82TScpuVLYtN2Zm87wIyt+2hcrjhvNAknLjmVPlMXEpecSoGgQN56qg79Zi51Wf7N3XqSaEnHbtdYtZ1Wc6YzpmkLiuYIAiDAy4v4tDSazZ5K1Tz5+KRhYyx2G2+uWExEXCwBnl6MeaolLyz8DVfsRRu79yDJko7Nrh370MwZvFW7Nh3Ll+dGcgoAI7dsZv3Zs1TNl4+PGz2JxWbjraVLiIiNxd/LizHNW/DivLkuyQ+w+bleJKWnY9Mam7bTct40ygTnYni9xngZTdi0ncGbVrE/+gpPFynJO9XqEJuWSs8V84lNS6VgQA7+r0Y93li9yDX5O/V2bANtx2bXtPx9KqWDQvm0bhN8PDy5mBDHW+sWk2hJp1ruMD6p0xiL3U6ftYuIiI8hwNOL7xu1otuyX12yDQI8vfi83lOUzBkCwHsbl3E67gbfP9GK/H6BXEyM47U1C4hPT+PpwiV5p2pdYtNS6Lkq4/P3z8H/Va/PG2sXPtCcUuDvwaqZW1g0YQ39xvbI1h4SlpOqj5cl6sL1zLbWvZ7gzSc+oU7LKjzeoSYLx6/lhcHPMOWT+c6OncmRfy39xnbP1j5/3CrmjlmZra3da00Y0vFbchcIpvlLDZkwZA6d+7Vg9tdLXVbc//Tcr3OISUnN1pbX3496hQtxKT4+s61b5Uq0mTGTpiVK0Kr0Y0zdu49369bh681bnB05m651K3Pm6g18vT0BaFOtDHkC/Wnx1WS0hiBfMwDPhVei43czebJccZpXeoyZW/fxZtNwRq/Y6sr4AHSeP4eY1JTM6TdWLM78eVCdhiSkpwHQs3I1Xlo0l/wBgXQpV4nhW9bzRvVa/LB7h8uKI8Bzc37Nlh/gp917mLh7V7a2HlWr8fL8eeQPCOS5ChX5dOMG3qhZix/+cG1+gE6LZ2dbhwE1G/Dt7q2sv3CWxwsUYUCtBnRaNJsXylWm5fxpPF2kJG2Kl2by4b30q16XkX9scmF66LR4FjFpN/N/Xv8phm9fz44rF3i2ZHl6V6jBV7s307N8dV5c8Rv5/QJ5vnQlPtmxjj6Va/P9vu0u2wZDazViw8WzvLpmAR4GA2aTB69XqsWWS+cYe2AHr1aoyWsVazFi5wZeKFuFlr9PdXz+xcow+cge+lWrx8hdD/7zlyH6e3Bo6wkSYpJuae/9aScmDv0VshQ+u13j4WnCy+yJ1WKjbO0S3Lgax+UzV50ZOZtD207eNv/tWK02vMyeePk48uctHEpoWBAHthx/wCn/ncENGzJi48ZsBx92rfE0GjGbTFhtdqqHhRGdlEREbKzLcuYO9KP+Y0WYu/NQZlunWhUZt2Z75u5zI8nxR09rjafJiNnDA6vNTpXCYVxLSOb89VgXJL97zYuXZOGJowBY7XbMHh6ObWC3UTAgkHx+/my/dMHFKe+OxW7HbPLA28OE1W6nYGAgef392XHxoquj3UKj8fN0HDT6e3pxNSnR0a41ngYj3iYTFrud6nnCiE5OIiI+1oVpb1UkMIgdVxz7xaZLETxdpCRwcxuYTR5Y7DYK+ucgr28A2yNdsw/5e3hSM29+Zh0/kJkvPj2NxgVLMPek4/d67slDNClUAsj4/I1GvI0ejs8/d/6Mzz/mgWeVM/j7VKtZJa5HxnL2UPZf+NlfL+WzBe9y/UosX/SayKDJr7psaP6ftOrxBE92DOfEvggmDJ5DYlwys79ZSr+xL5OeYuHLVyfR46MOTBnuutGHP2lgSrt2aOCX/QeYdfAgTxYrxpXERI5FX8vWd9wffzCtQ3uuJibyztJljGnZgjeXuG5oG6B/y4Z8tXQTvl6emW0FggJ5qkIpGpUrTkxSMp8uWM/567FMWL+TiT3aER2fxPuzl/F1lxa8N9N1lxb+pIFprdqj0cw8fIBfDh/InFcjX36upSQTERcLwA+7d/D1k0+TarXSd9VSBtVpyMjtm10TPEO2fejAfmYdPAhAt0qVaFumDAejohi+YT3xaWmM/WMHI59+ilSrlXeXLWNA/QZ8vcW1+QHQmunNOqDRzDi6n1+OHuCjrWuZ2qwDg2o1xKAUbX93XL76fu8OZrZ4lqjkRN5eu4QfnmzNG2tcMzSfZQWY3uxZtNbMOLafX47t52TMNZoUKs7Kc6doXrQUeX0DAPhh33a+btCcNJuVt9cvZlDNx51y9nsnBfxzcD0lhZH1n6ZMUC4OXo9i2LY1hJh9uJriOIG6mpJEiNkHgO/3b2dms46Oz3/dYn5o1Jo31jnn85cCfx+8zJ50eqc5A9t+fcu8veuP0KfhEQAadarNzlUHyF88N+36NCUxNplx/X8hLSXd2ZFvsfin9cz8chFaQ7eBbej5ybN802cyZw5doG+TzwAoV7sEN6LiUEoxYFJvbBYb44fMITY6/h9e/b/37KzZRCUmEmw2M7V9e07fuMFrNWvwwm9zb+m7+dx5Np+bAcAzZUqz/uxZiuTMSc9qVYlLTeOjdetItVqdlr3BY0W4kZjMkUtXqV40f2a7p8lImtXqGI4vW5xPOjSh27g5bDt5nm0nHX+kW1UpzabjZykUmpOX6lcjPiWVzxauJ9XivPx/aj/3F6KSEgk2+zC9dXtOx9zgj8uOA9xWJR5j4YljmX2PXIvmmd8c61AjX36uJieilGJM0xZY7HaGb17PtZRkp+Z/dvasW/ahGfv389327WiteadOHQY1aMj7K1dwNDqadr/8ApA5AqRQjG7eAqvdxqcbNnAt2bn5Adot+IWo5ESCvX2Y3qIDp2Nv0KxIST7eto5lZ0/QvGgpvmjwFF2WzGHzpXO0mDcNgLYlyrLuwhmKBuakV8XqxKWlMmzrWqf+HgC0WzjzZv5mz3I69jrvbVjGsPBGvFk5nFXnT2Gx2wA4cuMqzyycDkCNPPm5mpyEUjDmiVZY7TY+2bHOqfuQ0WCgXEhuhm5bzb7oSIbWeoLXKta8Y//Nl87R4tJUANoWz/j8A3LSq0INx+e/bQ2ptgfz+f/jEL1SSiulvsoy3U8pNSzj52FKqUtKqX1KqUNKqVZZ+r2tlOp2P+GUUjOUUsczXvsnpZRHRrtSSo1WSp1SSh1QSlXJaA9VSi2/n/e8F3mLhJKnUAhjNw9jyoHPCcmXkzEbPiBnroDMPl5mTxo/V4dFE9bRdUBrRr46icPbT/J4h1rOivm3YqPjsds1WmuWT91IqSpFbunTuV8LZn65mC7/15JJQ39l2dSNtO7VyAVpISrRMex4PSWFladOUbNAfvIHBrKkW1c29uhOHn9/Fj3/PCE+PpnLeJtMtCtblmn79vN2eG36LVvOrkuXaF26tFOzVy6cj4ZlirLy/ZcZ+VwzahYrwIiOT3ElLpHVh04BsPrwKUrmDcm2nLeHiTZVy/DL1v280bg2A2cvZ8/Zy7So/JhT8/8pKunPbZDMijOnqJg7DwBGpWharASLTx677XJvVKvF6J3beat6bT7bupFZhw/wYsUqTsv9p7/uQxXz5OVacjJ2rdHArIMHqZAnzy3LvVGzFt/t2M6btWszYuMGZh08yAuVKzs5vUNUcsY6pCaz4uxJKoXmpV3Jciw7ewKAJWeOUzFX9nXwNpnoUKosUw/vpW+1Oryzbhk7r1yiTfEyrs0f4ch/Ou4GXZf9Sovfp7Lw9FHO3eYSQp/KtRm9dytvV6nDZ3+s55djB3ipbFWnZr+SlEBkUgL7oiMBWHr2BOWCc3MtJZlcZl8Acpl9bzno8Daa6FCyHFOP7KVv1bq8s2EpO6MuPtDP/26uwacBbZVSIXeY/43WuhLQAfhJKWVQSpmAl4GZd1jmbs0AHgPKA2bgz7vbngZKZPzrBYwF0FpHA5FKqTr3+b53JeLIJTqV6MsLFd7nhQrvc+1yDG80+IiYqzfPbNu/+RQLflyDzWrD0+wJGrRd4+Xj+Tev7DxBuQMzfw5vUYWIo5eyzX+yUzg7Vx0kMTYJL7Mndq2xuyi/2WTC18Mj8+e6hQtx4EoUNcaOo/7ESdSfOIkrCQm0nD4921lVr+rVmLJ3L1a7HW+TCY3j+rzZ5NwBrFHLt9Do04k0+fwn+s1cyo7TF+g/ezlrD5+mRrECAFQvmp9z0dmvzb3UoBrTt+zDarfjlSW/d8Zn4Uxmk0eWbeBBvQKFOHHdcWmkboFCnIm5wZWMA4Cs2j1WlvXnzhCXlorZ5OHYj1ywDW7ZhwoV5sT1a4T6+mb2aVq8OCeuZb/c07ZMGdafPUtcaireHia0dlxbNZtcvw3q5y/M8ZhoriYnUiuvYz+qE1aQiLjs+1HvijX4+dCeLL8HrtoGHvh6eP4l/zWCvR0H5QpHIZ9xdF+25dpljD7EpaXibTI59iE03k7eBtEpSUQmxVM00PHUSJ2wQpyMvc7q86doV6JcRtZyrDp/MttyvSvU4OfDu7FqO95GEzrzd+DB5b+bLWsFxgN9gUF36qS1PqqUsgIhQCVgj9baCqCU6ggMBVKAOK31E3cTTmudecFUKfUH8Oe4ZmtgqnbcUbVdKZVDKZVXax0J/A50Af7zW6X7T+xFhbqlCAj2Y9rhL5k+YgErpt35elxQnhyUqlKEGZ87HoVY+OMaRq8dTGJcMh91GfNfx/tH/Sf0pEKdjPyHvmD6iIVUqFOKouULgIao89cY/c60zP5eZk8adw5nYLtvAJj3wyo+nv0W1nQbn/ca7/T8Ib6+jGvlGCQyGhQLjx1jY0TE3y6Ty9eXinnyMHrbdgCm7N3L712eIz4tjVcWPNhHVO7WxPU7+bzTU3SrW4Xk9HQ+mLsqc16ovy/l8+dm7GpH/hlb9zG7z3MkpKTRZ6rz84f4+DC+WWsAjMrAghNH2XA+AoCWfxme/5O3yUT7x8rSdeFvAEzct4ufW7Z1PHq20rn3FGTbh5Qhcx/66qmnKZMrFK3hYnw8g1bf3AZ/jgC9MNdxGein3bv5qe0zpNvsvL3U+fdEhJh9GN+0DQAmZWDBqaNsuBDB+5YVDAt/AqPBQJrVSv+NN5+MyeXjS6XQPHy72/EExuRDe1j0TFfi09PoucK599aEmH0Y3/gZR36DgQWnjrDh4lleKluVbmUdIyLLz55gzomDmcs4zn7L8/zSOQBMPLiLyU+1x2Kz8ea6xbe+yQM2dOsavm3YAg+jgfPxcfTbuBSDUvzwRGs6lqrApcQ4XsvyCFwuHz8qhebl270Zn/+RPSxq04349FR6rnpwn7/6p0eelFKJQD7gAFAR6An4aa2HZQzVJ2qtRyqlagLzgTBgGHBNa/1dxmvsBN7VWm/M8rr+wJ3ulHhOa30kS18PYAfwltZ6k1JqMTBCa705Y/4a4H2t9S6lVBiwXGtd/jbr0gvHGT/eyrdqg4COf//pPMwMytUJ7tuJQc4fGvwvma8+2tsgqYDN1RHumyH90d4GNl+7qyPcH4OrHxb8DzzauxDne76/W2td7Xbz7mpsRmsdr5SaCryJ4yw8q75KqeeBBKCj1lorpfICR7P0+RJYppQ6C9TVWsdqrRNwnOnfjR+AjVrru7l18iqOA5Lbrcd4HKMRBJpC3GDPFEIIIW7vXi6+jAL2AD//pf0brfXIv7SlAN5ZpnsDtbXWmc/T3O0ZvFJqKBCa8Rp/ugQUyDKdP6ONjPf960GIEEII8T/lrgu81vqGUmoO0B346R+6HwWKZ5muSEbRVUqZAfvdnMErpXoATYFGWuusY1kLgTeUUrOAmjiu60dmzCsJHEIIIYT4H3av32T3FY6b6P7JMqB+lunXgd+VUvuBbUDwXb7fOCA3sC3jUbw/vwB+KXAGOAVMAF7LsszjgOu/DUQIIYRwoX88g9da+2X5OQrwyTI97A7LnFNKXVdKldBan9RazwZm32s4rfVt82XcPf/6HRZrheMueyGEEOJ/1oP8Lvr+QN4H+Pq3UEqFAl9rrR/8l/wKIYQQD7EH9g0HWuvjgFP/Z5KML7r53ZnvKYQQQjyM5H+TE0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdzQA/v/4B9+CgzK1SH+PaPR1QnuW57yUa6OcF8unwx1dYT70qjGIVdHuG+RKQGujnBfquY87+oI9yWnKcnVEe6bh7K5OsJ9efNv5skZvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGTK4O8Cjp+92L1GxSgdhrCbxSZ2i2eW1fb0Kvj5/l2eJvE38jkTotq9BtQGsSYpL48PnvSYhJIm/hUF4c0pbPuv/omvzfdqNm4/KO/PU/AuD591rwVNe6xF1PBGDy8N/ZufoQZWoUo88Xz2Gx2BjReyKXz1zFN8DMwIm9GNxxNFprp+dPuXCdE58uypxOuxJLga518Qzx48K0LaRcuE750V3xK5kXgPjDFzn73SqUyUCJAS0xhwVhTUzlxPCFlB7eAWVQTl8HgM1de5JoSceuNVa7nVa/TmdMkxYUzRkEQICnF/HpaTSbPZWqefLxSYPGWOw23ly5mIi4WAI8vRjTtCUvLPoNZ2+FuHNxrBu4IXM64XIiVXpVIk/VPGwdsR1rigW/vH40+Kgenn6eRO2/ytbPt2MwGWj4SX0CCwaQlpDOuoHrafptY6dvg8TzMez7cHnmdPLlOEq8XIsiHSoBcHb2Ho79sIVGC3rgmcPMlQ2nOPnTDjz8vagyvDmegWaSLsVxYsJWKg972qnZs9ox7TR7551DAaElAmj1cWUWDd1H5OEYjCYD+crnpNmQihg9DBxddZkNPxzDHOBBh29r4pPDkxsXklg/+ghtv6zukvwbppxjx2+XUQrylPSj0/Ay/PbhMc7sjMHbz1GWOn1alrDS/hxYGcXy787gE+jBS2Mq4JvDk2vnk1k66jTdvi7vkvzrJl9g22+XUUqRt6QvXT59DJOngSXfnmXv8qsYjIq6ncJo0DU/+1ZeZenos/jk8KDnd+XxzelB9PkUFn9zhpe+KftAc0qBvwerZm5h0YS19BvbPVt7SFhOqj5ehqgL1zPbWvdsxJuNhlOnRRUeb1+ThRPW8sKgNkwZPt/ZsTOtmrWNRZPW0W/MS9na549bw9wfVmVra/dqY4Z0/o7cBYNp/kJ9Jgz9jc7vNGP2qGUuKe4A5gLBVBz7IgDaZmd3l7EE1SmBLc1KqQ/acGb0ymz9I+fu5LGP25MWFUfU4n0U7v0EF2duI6xTLZcV9z91/n0OMakpmdNvrFyc+fOgOg1JSEsDoGelary0eC75AwLpUq4Sw7es541qtfhh9w6nF3eAwEKBtJnRCgC7zc7s5r9SqGFB1vZfT/W3qpG3Sh5OLDzJwemHqfpKZQ7NOEyTbxqREJnIsXnHqfl2dfb/tJ+KL1ZwyTbwK5iTupM6A459aG37n8lTrygAKVcTuLbzAt65/TP7n5t3gPAfn+XKxtNcXn2Cwu0qcnLiNkr2qO307H+Kj0rhjxlneOX3J/DwNjK3304OL79E+eb5afNZFQDmv7+bffPOUbVjEXb+cobuM+tzbE0kh5depPpzRVn/3VEavlHaJfnjolLZPP0C/7eoNh7eRqb2PcDepVEAtOhXgopNc2frv3nGBd6eU4ODq66yZ/EV6j1fkGWjT/P0m8VcEZ/YqDQ2TL/IwMU18PQ28lPfQ+xZehWtISYylUFLa2IwKBKupwOwcfol+v1ajf2rotm1JIoGz+dnybdnaP5WkQeeVYbo78GhbSdJiEm6pb338I5MHPobZCl8drsdD08TXj6eWC02ytYqwY2r8Vw+c9WZkbNx5E++q75Wqw0vsydeZk+sVht5C4cQGhbEga0nHnDKuxO37xzeeXPglTsQn4LBmAsE39JHGQ3Y0yzY0ywok5HUyzGkR8cTWLGgCxLfvebFSrLw5FEArHY7ZpMHZpMJq81GwYBA8vn5s/3yBRenhMidkfjn98cvrx9x5+PJU9nxhzlfzXycW3cOAIPJgDXVii3VisFkIP5iPElRyeStmseV0QG4tuciPvkCMecJAODomE2UeiUclfW4QynsFltm/hv7L+EV7Itv/hwuyfwnu82ONc2G3WrHkmrDL9Sb4vVyo5RCKUVY+ZzER6VkrILCanH0M5gU53dfxy/Ei6BCfi7Lb7NpLKl2bFY76al2AnN53bGvMiis6XbSU20YTQbO7IohIMST0MI+TkycnT1LfkuKnYBcXmyedYmnXiuMIePA1T/YMyM/GfntGE2K07tiCQjxJJcT8kuBv0+1nq7E9chYzh6+mK199qhlfDb/XWo2rcj6uX/w3HstmPnl4ju8imu16t6QseuH0PfbbvgFOna62d8uo9/3L9HxradZNHEdLwxsw5TPFrg46U3X1h8juOHfn4GEdarFqS+XcGnWdvK0qsL5yZso8GI9JyW8Mw1Ma9WeRR2ep3OZCtnm1cibn2spyUTExQLww54dfP3k07xWpSZTDu7lvVr1GLljs/ND38aZVREUbeI4C8lZNAfnNzgOOiJWR5AY5TgQrvBieTZ+uJn9Uw5RpsNj7B67lyqvVHZZ5qwi15wgX6MSAERtPoN3iB8BxUOz9SnWpSp/vPM7V7eeJW+jkpyaupNi3VwzrP2ngNxmar9QnNFNVjKq0Qq8/DwoFp4rc77NYufgogsUq+M44KrTowQzem7l5PorlH06P5vGH6de71Kuik9gbm8avlSIjxtt5sMGm/D2M1GqjuMAfdm3pxnZZjsLRhzHmm4H4Imehfmx+x6OrL9G5eZ5WDXuLI1fKeqy/Dlye/HESwUY2mgbg+tvxdvfROk6QVw7n8KeZVf5sv0uxvbaz9UIx8lU456FGPPyPg6tu0bV5rlZPjaCpq8WdkrWfzVEr5TSwNda63czpvsBflrrYUqpYUBPIDrj9QdqrRdm9HsbuKG1nqqUmgw0BopqrdOUUiHALq114bvMMAmoBijgBPCi1jpRKfUGkKy1/unfrNu98DJ70umdZgxs+80t8/auP0Kf9UcAaNSxNjtXHSR/8dy0e6MJibHJjBswi7SU9Acd8R8tnryBmV8tQWvoNqAVPT9qzzdvTeXMoYv0ffpzAMrVLsGNqDgUMGBCT2wWG+OH/kpsdIJLMtstNmK2n6Lgy/X/tp9vsdyU/7YrAPEHL+AZ5AsaTgxfgDIZKdTrcTxz+jojcjbt5/1CVFIiwWYfprdqz+mYG/wR6ThAbFXyMRaePJbZ98i1aJ6ZOxNwFP+rSYkoFGOatMBitzN8y3qupdzdqMx/yWaxcX7jBaq95hgSrjukDtu/2sG+n/ZTsF4BjCYjAMElg2j5U3MAruy5gk+wGbRm3cANGEwGarxVDXOw2en57RYbV7eepVSvcGypFk5P30X1ka1v6RdSvSAh1R0jPpeWHyW0VmGSLsRyaPYePPy8KPNmfYzeHk7NnhKfzvF1V3hjWWO8/T2Y228nBxdfoHyLAgAsG36AglWDKVjVUTSL1s5F0dqOA4ADC89TvG5urkcksn3KKbwDPGn6fjk8zM67WpscZ+Hw2mgGraqD2d/ElL4H2b0wkuZ9i+Mf4onNovl16FHWToygyWtFKRUeTKlwx7rsWnCZ0vVDiD6XzPph5zAHmGgzoBSeZqNT8x9ce42hq2rh42/ip76H2bnwClaLxsPLwHu/VWP/ymhmDj7G29Or8FidIB6r47i/5o/fr1CmfjBXI5JZ+/MFfAJMtBtY4oHl/7dn8GlA24yifDvfaK0rAR2An5RSBqWUCXgZmJmlny2j7d/oq7WuqLWuAJwH3sho/wno8y9f857kLRxKnoIhjN00lCn7RhCSLydj1g8hZ66AzD5eZk8adw5n0cR1dO3fipGv/cTh7ad4vENNZ0T8R7HRCdjtGq01y6dtplTlwrf06dy3GTO/WkKX91ow6cO5LJu+idY9n3B+2AyxO8/gWzz3XRdnrbXj2vtz4VycvoVCPRqS6+kKXPl99wNOentRSY4bGq+nJLPizCkq5nYMVxuVomnREizOUuCzeqNaLUbv2s5bNWrz2baNzDpygBcrVHFa7qwubr1E8GNBmcU5R+FAnvquCa2ntqRokyL4588+/Ku1Zt/PB6jUvSJ7J+6nep+qlGxTgsOzj7oiPtE7zhFQIhSvIB+SL8WREhnPlu6/sL7jZFKjE9nScxZp129ejrOlWri4/BiFninPqZ93UGFAY3JWyMflVcednv3s9mhy5PfBN8gLo4eBxxrl5eK+GwBsHHuM5Jg0Gr9X7pblLClW9i+4QLVORdg49hitPqlCgcpBHFxy8Za+D9LJbTcICjPjF+SJ0cNAhcahROyLIyDUC6UUJk8D1Z/Jy/mD8dmWS0+xsfP3SOp0zs/yMafp9GlZilTJwZ7FV5ya//i2GILDzPhn5K/4ZChn98aRI7cXFRs7RoAqNA7h8vHEW/Lv+D2S+s+FsWzMWZ7/rDRFqwaya1HUA8v6bw/brMB4oC8w6E6dtNZHlVJWIASoBOzRWluzdBkF9FVKTbjXAFrreACllALMOEY+0VonK6UilFI1tNZ/3Ovr3ouIo5foVOqdzOkp+0bQ54lPiL9xc8O279OUBePXYLPa8PT2BA3absfL7PyzltsJyh3AjSjHL1J4s0pEHLucbf6THWuxc80hEmOT8TJ7Yrdr7HaNl9nTFXEBuLb+KCH/MDyfVfTqw+SsXhSPADO2NCtkXKe0p1keYMrbM5s8MChIslgwmzyoV6AQo3dtA6BugUKcibnBlaTEW5ZrV6os68+dIS4tFbPJA7vW2LXGbHLNfbJnVp7NHJ4HSLmRgjnIjLZr9v10gMfaZh8CPrXkNAXC8+MV6IU11QoGxzawpVr/+tJO4RieLwmAf7EQGi3okTlvfcfJhP/YEc8cN39Hz8zaQ+F2FTCYjNjSrCiVcW07zfn5A/OYuXQgBkuKFZO3kbM7rpGvbA72zj3Hma1X6TKhzm1vYNw2+RQ1uhTF6GHAkmp3rINBYU21OTV/jrzenNsfR3qKDQ9vAye3x5C/rD/x0WkEhHqhtebQmmjylMh+AL/up3PU7VIAo4cBa5b86U7eh3Lm9SIiS/4T22MoUM4fbz8TJ3bEUju/mVM7Y2+5xr7mp/M0eD5/9s9fPdj89/PX4XvggFLqizt1UErVBOw4huvrAH89ZToPbAa6AouyLOcPbLrDyz6ntT6S0e9noBlwBHg3S59dQD0gW4FXSvUCegF4G+59aLb/hJ5UqFOKgGA/ph36gukjFrJi+p2vhwblCaRUlSLM+MKxagsnrGH0mkEkxqXw0fNj7vn971f/H7s78gf5MW3/CKZ/sYgK4SUpWq4AaE3UheuM7jc9s7+X2YPGncIZ2GEUAPPGrebjX/pgtVj5vPckp+cHsKWmE7cngqJvNc1su77lBBE/rMYSl8KxIXPxKZaLMp8+m9HfQvTKg5T+zDGdr201jg75DYPJSIn+LZyeP8THh/FPO4aCjQYDC04cZcP5CABaFs8+PP8nb5OJ9o+Vpeui3wCYuG8XP7doi8Vm461VS5yW/U+WFAuXd0RSZ8DNO8nPrDzL0V8dZ7OFHi9IiZbFM+dZU62cXHKap75rDEC558qy6u3VGDwMNPz47y+zPAjWFAvXdl2g7LuP31X/1GuJxB2NosSLjlG3Qm0rsLX3HEx+jkfnnC2sQhCln8zHxI4bMBgVuUsHUrl9IT6vuYTAvGYmd90IQKlG+aj/iuNAK+FqCpcPxVL/1ccAqP5cESY9txFvfw86jKrh1PyFKgZSoUkuvm6/A6NREVban9rP5mdC770k3kgHDfke86f90Mcyl4m7msaFg3E0fd1x7b1ulwKMevYPzAEmXvquolPzF64YSKWmufii3a6M/H6EP5sPS6qNqe8dYf2UC3j5GOn8cfb85w7E8/TrjoPi+s/nZ2SHXZgDTPQY8+Ae9VP/5pEnpVSi1tpPKfURYAFSuP01+AQc1+A3KaXGA2u11rMyXmMysBjYDywAGgJ/3O01+CxZjMB3wE6t9c8ZbT2Bx/68R+B2Ak2hunbArdfcHhlG511zelDiZ+RwdYT7cvlk6D93eog1qnHI1RHuW2RKwD93eohVzXne1RHuS07TrU8VPWo8lHNHMP5rb5Zet1trXe128+53fG8UsAf4+S/t32itR/6lLQXw/usLaK1PKqX2Ac/+2Xa3Z/AZy9uUUrOA/8uSwzvj/YQQQoj/SfdV4LXWN5RSc4DuOG5u+ztHgeJ3mDccyBxr1Fon4Lhmf1sZ192Laa1PZfzcCsg6tlkS2PKPKyCEEEK4qf/iOfivcNxE90+WAbe94Ka1PoxjJOBuKWCKUuogcBDIC3yUZX4dYNXtFhRCCCH+F/yrM3ittV+Wn6MAnyzTw+6wzDml1HWlVAmt9Umt9Yt/md/2Ht7fjqOI30IpVRk4rLW+frv5QgghxP8CZ3+TXX8cZ9sPUggw5AG/hxBCCPFQc+pDtFrr48AD/WYIrbUMzQshhPifJ99FL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEGzK5OoDraLBrV4f499QjnD1DQqqXqyPcF0O6cnWE+xKZEuDqCPctNtXs6gj35WxysKsj3JfrJj9XR7hvXgaLqyM8MHIGL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEG5ICL4QQQrghKfBCCCGEGzK5OsCjpO+Yl6jZtAKx0Qm8Ev4BAM/3b8VT3eoTdz0BgMkfzWPnqoOUqVmcPl8/jyXdxojuP3L5zFV8A80M/PlVBrf7Bq218/OPfoGaTcoTey2BV+p+6Mj/fy15qltd4q4lOvJ/Mp+dqw9RpkYx+ozsgsViZUTPiY78AWYG/tSbwR2+dUl+AFtiKpfGLCL1fDRKQVifVihPE5fHLkVbrGAwkO+Vp/EpGUbc1qNcnbkeo7+ZggOexRTgQ1rkDaKmraPg/7VzSX6AjS/3IMmSjs2usWk7rWfOyJzXvUpVBjVoSNWxPxCTmsJTxUvwdng4camp9F64gNjUVAoGBtKvTj3eXLrY6dkTz8ew78PlmdPJl+Mo8XItinSoBMDZ2Xs49sMWGi3ogWcOM1c2nOLkTzvw8PeiyvDmeAaaSboUx4kJW6k87Gmn50+5cJ0Tny7KnE67EkuBrnXxDPHjwrQtpFy4TvnRXfErmReA+MMXOfvdKpTJQIkBLTGHBWFNTOXE8IWUHt4BZVBOX4f4c3FsHrwuczrhUgIVe1UhV5U8/PH5VuzpNpRRUf29cELKhnJ+bQQHJuzBM8CLBl80wivQm4SL8ewbu5t6wx93en6A/TOOcnTBaQCCi+fg8aG1Sb6WwqqBm0mNSyO0dBCNPgrH6GHk4KzjHJ53Ev88vjz1VX2MHkYi913lzJoL1Hm3qkvy75l+nEO/n0UpCC4eSJNhNTg0/wx7Z54k7mIivde0xpzTC4CTay6ybewhvAM8afl1Hcw5vIi9kMiWMQdp/nntB5pTCvw9WDVzC4smrKHf2B7Z2uf/sIq5Y1Zka2v3RhOGdPiW3AWDaf5yQyYMnkPnfi2Z/fUSlxXHVb9sZdHEdfT74aVs7fPHrmbu96uytbV7vTFDOo0md4EQmr9Ynwkf/Ebnd5sz+5ulLssPEDlxBX5VilOwfwfsFhs6zcL5L+eSq1N9/KsWJ2HXSa5MWUPR4d24vmQnxb7qQfy2o8RtPERwixpcnbGe3M83dFn+Pz3366/EpKZka8vr50+9QoW5FB+f2datUmXazJxB0+IlaPVYaabu28u74XX5eutmZ0cGwK9gTupO6gyAttlZ2/5n8tQrCkDK1QSu7byAd27/zP7n5h0g/MdnubLxNJdXn6Bwu4qcnLiNkj0e7B+2OzEXCKbi2BcBR/7dXcYSVKcEtjQrpT5ow5nRK7P1j5y7k8c+bk9aVBxRi/dRuPcTXJy5jbBOtVxS3AECCgXSbFobAOw2O/NbziZ/g0Ls+Gwz5btXIiy8AJe2XmDvmJ00HtuM478e4amfW3FhXQQRK85Q6tky7P9xNxV7V3FJ/sSryRycfZxOc1pg8jaxsv8mTq2M4PyWy1R47jFKNC3Mhk93cHTBacq1L8mJ5WfpOKs5e346xIVtkRSqF8buiYd4cngdl+XfN+sU3X5risnbxJL3t3J8xXnyVQqhSP18/NZzXbb++2adpPO0Jzm19hLHl5+nUqcSbP3hIOGvl3vgWWWI/h4c2nqChJiku+prtdjwMnviZfbCarGRt3AooWE5ObD5+ANOeWeHtp38F/k9sVqz5N9y4gGnvDNbUipJh8+Ts3ElAAweRox+3ijAnpzm6JOchkeQHwBKKbTFij3NijIaSTp8HlMOP7zyBbtoDf7e4IYNGbFpY7YDKLvWeBqNmD1MWO02qoeFEZ2cRERsrOuCZri25yI++QIx5wkA4OiYTZR6JRyVte4phd1iw5ZqxWAycGP/JbyCffHNn8MlmbOK23cO77w58ModiE/BYMwFbt0vlNGAPc2CPc2CMhlJvRxDenQ8gRULuiDxraJ2ReIX5o9fXj+UUliSLABYEtMxh/oAoAwKW7oNa5oVZTJwdd8VzME+BBQMdFluu01jTbNht9qxplrxCTFzaWcUxRo5PtdSLYoSsf6io7MGu9WOJc2GwWTgxNKzFAjPh3eglwvz22/mT7HhF2om12M5Cczne0tfpRQ2i2M9DSbFpT3R+AZ7k7Og/21e+b8lZ/D/gVa9nuDJzrU5sfccEwbNJjEumdnfLKXfuO6kp1r4svdEenz8LFM+me/qqLfVqsfjPNmxNif2nWPCkF8d+Ucto98PL5OeYuHL1ybR48MOTPl0gUtzpkfFYgr04dLohaSejcJcLC95ezYlT48mnBs2k8ifV4PWFP38RQBC29fh7AfT8QjyJ3/fNpz/Yi4F+rV16ToAaGBK23Zo4JeD+5l18CBPFi3GlcREjl2LztZ33M4/mNauA1eTEnln2VLGtGjJm0uWuCT3X0WuOUG+RiUAiNp8Bu8QPwKKh2brU6xLVf5453e8gn2pOLgJe4cuo9LQp1wR9xbX1h8juGHpv+0T1qkWp75cgsHTRPH/a8G5Ceso8GI9JyX8ZxGrzlC4iWMEperbNVn79gr2frcTrTVNxrcAoGy3CqztsxxziA/hHzZg08C11P3YNUPzAH65fKj0fGmmtfgdk5eRArXyElo6CE9/DwwmQ2afxKvJAJR7tiTzXlxBzmKB5KkYyrJ3N9BizBMuzV+1aykmNVuCyctIwdq5KVQ7zx37V3/5Mea9sgHfUG+e+qQmS97fRrPPajkl6z0XeKWUBr7WWr+bMd0P8NNaD1NKDQN6AtEZrz1Qa70wo9/bwA2t9VSl1GSgMVBUa52mlAoBdmmtC99lhslAAyAuo+lFrfU+pVQLoIbW+oN7Xa9/a/Gk9cz8YhFaQ7dBbeg5vCPfvPEzZw5eoG/jTwEoF16SG1GxKKUY8FNvbBYb4wfPITY6/h9e/cFb/PN6Zo5c7Mg/sDU9P+7AN29O4cyhi/RtOgKAcrVLcCMqDqVgwMSe2Kw2xg/5ldjoBOeGtdlJOR1J3p5P4VMqjMgJK4ieuwVbUhp5ujchMLw0cZsPc+m7xRT5+Hn8KhWleCXHH7+Ytfvxr1qc9MvXuTx/G0Y/M3l7NsXg5eHcdQCenT2LqKREgs1mprZrz+kbN3itRk1emPfbLX03nz/H5pnnAHimdBnWnz1LkZw56VmtGnGpqXy0fh2pVquzVwG7xcbVrWcp1SscW6qF09N3UX1k61v6hVQvSEh1x1nZpeVHCa1VmKQLsRyavQcPPy/KvFkfo7fzt4HdYiNm+ykKvlz/b/v5FstN+W+7AhB/8AKeQb6g4cTwBSiTkUK9Hscz561nbc5gs9i4tOk8lV6tBsDJeceo+lZNCj5RmHOrz7Bj+CYajXmavDXDyFszDIAzS08SFl6AhAtx7BhxCE9/T6q9UwuTt/PO9dLi0zi74SLPL2yNp78nK9/fxIWtkXfsX6p5UUo1d/we75pwkAqdSnF+y2VOLDmDX25fwvtWcerlktT4dE6vv8xLi5vh5efJkve3cnTJOUo3L3Tb/oVq5aFQLccBwJHFERSuk5eYc4nsnrYb7wAPGvSrjIf5wXz+/2aIPg1om1GUb+cbrXUloAPwk1LKoJQyAS8DM7P0s2W0/Vvvaa0rZfzbl9G2BGiplPK5j9e9J7HR8djtGq01y6dupFSVIrf06dyvBTO/WEyX91sxaehvLJu6kda9Gzkr4t+KjU7Ikn8TpaoUvqVP53ebM3PkYrq815JJw+aybOpmWvdyfn5TSAAeIQH4lHL8sQoIL03K6SvErjtAQO3HHG11ypBy8lK25expFmLXHiC4WTWuztxA/rdb41OmALEbDjp9HQCikhw3NF5PSWHlqVPUzF+A/IGBLHm+Gxtf7kEef38WdXmeEJ+bu7G3yUS7MmWZtn8fb9cOp9/yZey6fInWj/39GeiDEr3jHAElQvEK8iH5UhwpkfFs6f4L6ztOJjU6kS09Z5F2/eblIFuqhYvLj1HomfKc+nkHFQY0JmeFfFxe5ZpLVrE7z+BbPPddF2ettePa+3PhXJy+hUI9GpLr6Qpc+X33A056Z5e3XSRnqWDMwWbAUbwLPO4oMgUbFeHakWvZ+ltTrZxZcoqS7UtzYMJewj+oR66KuYlYftqpuS/+cYWAfH6Yc3pjNBko+ngBIvdHk55gwW61A47r3H65sv8ZT4pO5urhaxRpWID9M47S+LO6ePp7cPGPK07Nf35HFIFhvvjk9MboYaD4E/mJPHDtH5ezpFg5sjCCis8WZ9u4QzT9qAb5KoVybNm5B5b13xR4KzAe6Pt3nbTWRzP6hgBPAHu01llPNUYBfTOK/39COy5ergda/Fev+U+Cct+8jhXeogoRR7MXlyc7h7Nz1QESY5Pw8vHEbrdjt2u8fDydFfFvZcvfvDIRRy9nm/9kp9rsXHWQxNjkjPwau92Ol9n5+T1y+uEREkDaRccvU+KBs3gXCMUjyI+kQ45fkqQDEXjmC8q23LX5WwluUR1lMmJPt4JSjmvDaRanr4PZZMLXwyPz57qFCnPgyhVq/DiW+j9NpP5PE7mSkEDLGdO5lpycuVyvatWZsm8vVrsdb5MJjeP6vNnDNVfZHMPzJQHwLxZCowU9aDj7RRrOfhHvUD/qTOiEV/DN4nlm1h4Kt6uAwWTElmbN2AQKW5rzRx8Arq0/Ssg/DM9nFb36MDmrF8UjwOzIrBTKRfvQn86tvDk8D2AO8eHqHkexi9oVSUCBgGz9j0w/SKlny2AwGbBmrAMG5fjZifzy+BJ16BqWVKvjwGnnFYKKBJKvWm5OrzkPwPHFZyjcIH+25f4Ye4Dqr1QEwJZqQymFMiisqc7N75/Hh8iD17GkOPJf+COKoCIB/7jc7qnHqdS5BEYPA7Y0G+DYBNZU2wPL+m//OnwPHFBKfXGnDkqpmoAdx3B9HeCvh7rngc1AV2BRluX8gU13eNnntNZHMn4erpT6AFgD9Ndap2W07wLqAXNuk6kX0AvAW937sFr/ib2oULcUAcF+TDv8JdNHLKBC3ccoWq4AoIk6f53Rb0/N7O9l9qTxc3UY+MzXAMz7fiUfz3kbq8XK5z3G3/P736/+43tQoU5G/oOfM33EQirULeXIrzPyvzs9e/5O4QxsP8qR/4dVfDz7TazpVj7vPdHp+QHy9nyKC1//jrba8MyTg/xvtsK/ZkkiJ64Amx3lYSLstZvHd5brCSSfuEyuTg0ACG5RndPvTsTo603Bgc86PX+Iry/jWrYCwGgwsPDYMTaei/jbZXL5+lIxdx5Gb98GwJR9e/n9uS7Ep6XxykLn3xdhTbFwbdcFyr57d9dxU68lEnc0ihIv1gSgUNsKbO09B5Of49E5Z7OlphO3J4KibzXNbLu+5QQRP6zGEpfCsSFz8SmWizKfPpvR30L0yoOU/swxna9tNY4O+Q2DyUiJ/k47l8jGmmIh8o/L1Oh/807ymgPqsPubHdhtdoyeRmoMuDkvOTqZ60eiqdCjMgClOpRh+UsL8fDzpMEXzh2Ny10uhKKNCvJbl2UooyK0VE7KtC1Oobr5WDVwC3+M3U9IqSBKty6WuUz0sRsAhD7mOHgv/lRhZndagl9uHyp3K+PU/HnLB1OiUX5mdlmFISN/ubZF2fvLCXZPOU7S9VSmd1xB4bp5afxBdQASo1O4cvgGtXqXBaBipxL80nU1Xv4etPz6wT0NoO71kSelVKLW2k8p9RFgAVK4/TX4BBzX4DcppcYDa7XWszJeYzKwGNgPLAAaAn/cwzX4vMAVwBPHaMJprfVHGfMaA69orf/2QedAU4iu7XfrNcNHhtHo6gT37dLPd74x5VGQdNp1dyH/Fx6r+uCGBp0lNtXs6gj3pWjgPw/tPswCTGn/3Okh52Vw3SjMf2FUlTm7tdbVbjfvfsb3RgF7gJ//0v6N1nrkX9pSAO+/voDW+qRSah+QeSp1N2fwWus/78hIU0r9DPTL0sc74/2EEEKI/1n/usBrrW8opeYA3YGf/qH7UaD4HeYNx3Fz3J+vmwBU+rsXU0rl1VpHKqUU0AY4lGV2yb9MCyGEEP9z7veLbr7CcRPdP1kG3PZ5FK31YRwjAfdihlLqIHAw4/0/yTLvcbIcMAghhBD/i+75DF5r7Zfl5yjAJ8v0sDssc04pdV0pVUJrfVJr/eJf5t/Tt49orW/7LQdKqdyAWWvtmuefhBBCiIeEM7+qtj+Q9wG/R0Hg3Qf8HkIIIcRDz2kP0WqtjwMP9FsttNY7H+TrCyGEEI8K+c9mhBBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQ1LghRBCCDckBV4IIYRwQyZXB3AdBQbl6hD/3qOcPUNYYJyrI9yXoz7+ro5wX6rmPO/qCPftbHKwqyPcl6ZBh10d4b4EGxNdHeG+eSuLqyPcl1F/M0/O4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcENS4IUQQgg3JAVeCCGEcEMmVwd4lPT97kVqNqlA7LUEXqkzFIDn32/FU13rEXc9AYDJH89n5+qDlKlZnD4jn8eSbmVEz/FcPnMV3wAzA39+hcHtR6G1dn7+b7tRs3F5R/76H2W2t+rxOC1fbojdZuePVQeZ9NE8ytQoRp8vnsNisTGi98Sb+Sf2YnDH0S7Jn3Q+hv0fLsucTo6Mo/hLtSjcoTIAEbP3cHzsZh7/vSeeOcxc2XCKUz9vx8Pfm8qfNMcz0EzypVhOTtxGxaFPOz3/nzY/14uk9HRsWmPTdlrOm0aZ4FwMr9cYL6MJm7YzeNMq9kdf4ekiJXmnWh1i01LpuWI+sWmpFAzIwf/VqMcbqxe5JP+OaafZO+8cCggtEUCrjyuzaOg+Ig/HYDQZyFc+J82GVMToYeDoqsts+OEY5gAPOnxbE58cnty4kMT60Udo+2V1p2ePPxfH5sHrMqcTLiVQsVcVclXJwx+fb8WebkMZFdXfCyekbCjn10ZwYMIePAO8aPBFI7wCvUm4GM++sbupN/xxp+f/0/KfI9nwazQoKFDShx4jinJydwKzvjiPtoOXj4FenxcjdyFvVk69wrrZVwnO68nbP5TE5Gng+K4Edq28QZeBhVySf8HP11kxOwYNNO2YkzYvBZMQa2XEmxe5etFCrvwe9P+uAP6BRrYsj2f6qKv4BxoZPK4AATlNRJ5LZ8rIKPp/V8Al+ef+HMPS2XFoDc07BtLu5ZxsWJrAlG+vc/5UOt/PL0ipCt4AHNqVwqghUXh4KAZ9m5f8RTxJjLfx0RuRjJgchsGgHlhOOYO/B6tmbmFwh1G3tM8ft4rXG3zE6w0+YufqgwC0e60JQzp+y48DZ9H8pYYAdO7XgtlfL3VJcQRYNWsbgzuNztZWoU5Jaj9Vkdcafkzveh/y2w+rAGj3amOGdP6OHwfPpvkL9QHo/E4zZo9a5rL8vgVzEj7pOcInPUft8Z0wenmQu14xAFKuJnBt13m8c/tn9j8/bz+1x3WkQMtyRK45AcDJSdsp3r22S/Jn1WnxbJrNnULLedMAGFCzAd/u3kqzuVP4eudmBtRqAMAL5SrTcv40Zh7dT5vipQHoV70uI//Y5JLc8VEp/DHjDN1/aUDv+U+g7ZrDyy9Rvnl+Xl3YiF7zHseSamPfvHMA7PzlDN1n1qdKh8IcXnoRgPXfHaXhG6Vdkj+gUCDNprWh2bQ2PDW5FSZvE/kbFGLvmJ2U716JZtPaUKFXFfaO2QnA8V+P8NTPrSjRphQRK84AsP/H3VTsXcUl+QFuXEln5bQoPpxXjs+WVMBu1+xYcp3JwyJ4ZWRxPllYntotQ1jwwyUAti26xvBF5SlRxZ+Dm+PQWrPgh0u0fi3MJfkjjqeyYnYMX88vypjFxfhjbQKXI9L4ddw1Kob7MmFtCSqG+/LruGgAFk29zjfzi/JU55ysXxgHwNSvo+j6Ti6X5D97PI2ls+P4fn5BJiwpxPa1SVyKSKdwSU8+HJuPCjXM2fr/OjGGz34K47UhuVg005F/+pgbPPda0AMt7iAF/p4c2naShJiku+prtdrwMnvi5eOJ1WIjb+FQQsOCOLDl+ANOeWeO/MnZ2lq81IA5o5djSbcCEHfNMRKRmd/sidVqI2/hEEf+rSecnvt2ru+5gE9YIOY8AQAcH7ORkr3rZOujDAq7xYYtzYrBaCDmwCW8gnzwzZ/DBYn/nkbj5+kJgL+nF1eTEh3tWuNpMOJtMmGx26meJ4zo5CQi4mNdltVus2NNs2G32rGk2vAL9aZ4vdwopVBKEVY+J/FRKQAopbBaHP0MJsX53dfxC/EiqJCfy/L/KWpXJH5h/vjl9UMphSXJAoAlMR1zqA/g2Ids6TasaVaUycDVfVcwB/sQUDDQldGxWzXpqXZsVk1aip0cuTxQClKTbACkJFjJmcuxP2kNNqsmPcWO0aTYuuAaFeoH4pfDNQO4F06nUbKSGW+zAaNJUb6GD1tXJLB9dQJPts0BwJNtc7B9leNvkVIKS7pjPU0eikM7k8gZaiKsiJdL8p8/nc5jFb0z81eoaWbTikQKFfeiQFHPW/qbPCA1RZOWasdkgsvn0omOtFCpls8DzypD9P+BVj2e4MmO4ZzYF8GEwXNIjEtm9jdL6Tf2ZdJTLHz56iR6fNSBKcPnuzrqLcKK5aZsrRK8MLAN6WkWJg79jRP7zjH722X0+/4l0lMtfPnaT/T4sD1TPlvg6riZrqw9SZ4nSgJwdfNpvEL9CCgemq1PkS7V2PXufLyCfSk/qCn7hy2lwgeuG5rPpDXTm3VAo5lxdD+/HD3AR1vXMrVZBwbVaohBKdr+PhOA7/fuYGaLZ4lKTuTttUv44cnWvLHGNUPzAAG5zdR+oTijm6zEw9tIkdq5KBZ+80zKZrFzcNEFmrxfHoA6PUowo+dW/EO9af1ZVeb220nbL6q5Kn42EavOULhJUQCqvl2TtW+vYO93O9Fa02R8CwDKdqvA2j7LMYf4EP5hAzYNXEvdj103NA8QlMeTp7vnpW/DvXh6GShXN5DydXPQ/RMDI3sex9NLYfYzMvTXsgA0fj43H3Y4TP4SZkpUyceo107w3qRSLstfqKQ3U7+6SnyMFU9vA7s2JFK8nJnYa1aCcnkAkDPUROw1x0nHs6+GMKhrBMG5TfT7Oj+fvXGB97/N77L8hUt6MmnkNeJibHh5K3asT6JUee879u/8ahCf97uCp7diwFd5GPfZNV56J8QpWR+ZAq+U0sDXWut3M6b7AX5a62FKqWFATyAaxzoN1FovdEauxT+tZ+aXi9Aaug1sQ89PnuWbPpM5c+gCfZt8BkC52iW4ERWHUooBk3pjs9gYP2QOsdHxzoj4t4xGA/45fXn7qRGUrFyYgRN78WK1QZw5dJG+T38OZMkPDJjQ05F/6K/ERie4JLPdYuPqljOU6BmOLdXCmRm7qPplm1v6hVQrSEi1ggBcWnGUkJqFSb4Qw5HZezD5e1O6T32M3h5OTg/tFvxCVHIiwd4+TG/RgdOxN2hWpCQfb1vHsrMnaF60FF80eIouS+aw+dI5WmQM47ctUZZ1F85QNDAnvSpWJy4tlWFb15JqtTote0p8OsfXXeGNZY3x9vdgbr+dHFx8gfItHNdClw0/QMGqwRSsGgxA0dq5KFrbcQBwYOF5itfNzfWIRLZPOYV3gCdN3y+Hh9n5f4ZsFhuXNp2n0quOg42T845R9a2aFHyiMOdWn2HH8E00GvM0eWuGkbemYyj7zNKThIUXIOFCHDtGHMLT35Nq79TC5O3c/ElxVvasieGrtZXw8Tcy5s1TbFlwjV0rb9BvQimKVfRjycTLzPz0PN0/LUqdNqHUaeM4+P19zEWadM3NgY1xbPk9mqC8XnTuX/CBDxVnVbC4F+17hzD4hXN4+xgoWtobozF7H6UUZESqXNePynUdIz5r5sVSraE/l86mM29iJH4BBnp9kBdvs/MGowsV96JT7yDef+Ei3mYDxUt7Yfibty9expsx8xx/hw78kUxwqBGt4eM+lzGaFK8MDCUo9MHsQ4/SEH0a0FYpdadDn2+01pWADsBPSimnrFtsdDx2u0ZrzfKpGylVpcgtfTr3a8HMLxfT5f9aMmnoryybupHWvRo5I94/uhYZy5bFewA4sTcCu10TGJx9+LRz32bM/GoJXd5rwaQP57Js+iZa93zCFXEBuLYjgoCSoXgF+ZB8OY6UyHi2dp/Jho4/kxadyLZev5B2/ealFFuqhcvLj1LwmQqcmryDcgOakLN8Pi6vds3lkqhkx/D79dRkVpw9SaXQvLQrWY5lZx2XP5acOU7FXHmyLeNtMtGhVFmmHt5L32p1eGfdMnZeuUSb4mWcmv3s9mhy5PfBN8gLo4eBxxrl5eK+GwBsHHuM5Jg0Gr9X7pblLClW9i+4QLVORdg49hitPqlCgcpBHFxy0an5/3R520VylgrGHOy4Xnpm6UkKPO644axgoyJcO3ItW39rqpUzS05Rsn1pDkzYS/gH9chVMTcRy087PfvhrXGE5vciIMgDk4eBak1ycnJPAheOJVOsouN3t2azYE7uzX4AHhOVzukDSVRtHMSynyJ5fVQJfPyNHNnm/BONps/mZPTCYnwxqwh+gUbyFfEiR4iJG1cdl0luXLWQIzh70UtNsbN6biwtng9ixrdXeefLMMpU82X9glin52/WMZBxCwsxanYB/AKN5C9y69D8X2mtmT7mBs/3CWba6Ov06h9K806BzJ8S+8ByPkoF3gqMB/r+XSet9dGMvk4ZAwnKffNaXHiLKkQcvZRt/pOdwtm56iCJsUl4mT2xa43drvHy+ecdwhm2Lt1HxbqO4bqwornw8DQSdz0xc/6THWuxc80hEmOTHfntGfnNrssfueYEeRs5MvsXDeHx33vSYPZLNJj9El6hftQe3xmvYN/M/mdn7aFg24oYTEbsaVaUAmUAe6rzznz/ZDZ54Ovhkflz/fyFOR4TzdXkRGrldZwF1wkrSERcTLbleleswc+H9mC12/E2mdBo7FpjNjn37DEwj5lLB2KwpFjRWnN2xzVCivqzd+45zmy9yjOfV0Pd5mxw2+RT1OhSFKOHAUuqPWMbKKypNqfm/9O5lTeH5wHMIT5c3XMFcFybDygQkK3/kekHKfVsGQwmA9Y0KygFBuX42cmC83lxel8iaSk2tNYc3hZPvmJmkhNsRJ513PtweEsc+Yplv9lr7rcXafeWY2jbkmqHjG2QluL8bfDn8PvVy+lsXRFPw1aB1Gzkz+p5sQCsnhdLrSf9sy0zb8I1Wr0QhMlDkZaqQYHBAGkpzr/pNyYjf9QlC5tXJNCotf8/LAEr58VTs6EvATmMpP75O6AgLcX+wHI+MkP0Gb4HDiilvrhTB6VUTcCOY7j+r/N6Ab0AvA2+f539j/pP6EmFOqUICPZj2qEvmD5iIRXqlKJo+QKgIer8NUa/My2zv5fZk8adwxnY7hsA5v2wio9nv4U13cbnvcbf8/vfr/4/dnfkD/Jj2v4RTP9iEStnbuGdb19g3MYPsFpsjHxjcpb8HjTuFM7AjCcH5o1bzce/9MFqsfJ570lOzw9gTbFwffcFyrx7dyMIqdcSiTsWRfEXawJQsG1Ftr0yGw8/Lyp/0vxBRr2tELMP45u2AcCkDCw4dZQNFyJ437KCYeFPYDQYSLNa6b9xZeYyuXx8qRSah293bwVg8qE9LHqmK/HpafRc4dz7OsIqBFH6yXxM7LgBg1GRu3QgldsX4vOaSwjMa2Zy140AlGqUj/qvOA7CEq6mcPlQLPVffQyA6s8VYdJzG/H296DDqBpOzQ+OfSjyj8vU6H/zpsyaA+qw+5sd2G12jJ5Gagy4OS85OpnrR6Kp0MPxOGapDmVY/tJCPPw8afCF80fiilX0o3rTID5ocwiDSVGotA+Pd8pFUB5PvutzEqUUvoFGenx68wAm4ohjRKtwWcffvVotgxnU4iBBeT1p3jOv09fh09cvEB9rw2SCV4flxS/ASIdXQhjR5yKr5sQSGubBgO9uXme/HmXh+P4UnnvTcbmnZbcg+j5zBl9/A0PGFXR6/mGvRWbmf/PD3PgFGNm8IoHvPowm7oaNgd0vUbyMF59PcaxDaoqdFXPj+SJjuv3LORn48iVMnopBox7c569c9cjTvVJKJWqt/ZRSHwEWIIXbX4NPwHEN/m+fIwo0heraAa0fdOwH568XrR5Fv935xpRHwdFjrrvR57/QLXyLqyPct7PJwa6OcF+aBh12dYT7EmxM/OdODzlvZXF1hPvSqOiJ3Vrr2965+qidwQOMAvYAP/+l/Rut9UjnxxFCCCEePo/SNXgAtNY3gDlAd1dnEUIIIR5Wj1yBz/AVTrqJTgghhHgUPTJD9Fprvyw/RwE+WaaHuSKTEEII8bB6VM/ghRBCCPE3pMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbkgKvBBCCOGGpMALIYQQbsjk6gDiX1LK1Qnum48p3dUR7o9BuzrBfclpSnJ1hPt23eTn6gj3JdiY6OoI96Wud5yrI9y3BLvV1REeGDmDF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQFHghhBDCDUmBF0IIIdyQydUBHiV9v3uRmk0qEHstgVfqDAXg+fdb8VTXesRdTwBg8sfz2bn6IGVqFqfPyOexpFsZ0XM8l89cxTfAzMCfX2Fw+1ForZ2ff1RXajYu78jf4OPM9lbdG9Ly5YbYbXb+WH2ISR/No0yNYvT5ojOWdBsjek/i8tmM/BN7Mrjjdy7Jn3A+lp0frMqcTrocT+ke1Sn+bAVO/3aQM/MOowyKPOEFKfdaba4fiGTfV5swmIxUH9YIvwI5SE9IY+cHqwj/qjnKoJy+DgCbO/UmyZKOTdux2TUtf59K6aBQPq3bBB8PTy4mxPHWusUkWtKpljuMT+o0xmK302ftIiLiYwjw9OL7Rq3otuxXnL8VYMOUc+z47TJKQZ6SfnQaXobfPjzGmZ0xePs5/qR0+rQsYaX9ObAyiuXfncEn0IOXxlTAN4cn184ns3TUabp9Xd4F6WH/jKMcXXAagODiOXh8aG2Sr6WwauBmUuPSCC0dRKOPwjF6GDk46ziH553EP48vT31VH6OHkch9Vzmz5gJ13q3qkvwAC36+zorZMWigacectHkpmIRYKyPevMjVixZy5feg/3cF8A80smV5PNNHXcU/0MjgcQUIyGki8lw6U0ZG0f+7Ai7JP3ZiAlNmJqE1vPCcL6/19OfAoXT69o8lLU1jNMHXn+akamVPFixJ5tOR8eTMYWDmpGCCgoycibDy0Yg4Jo8Ldkn+iZOS+GVmChp4rrOZHj18Afjp5ySmTEnGaFQ88YQXgwf5s3NnOgMGxuPpAWO+z0HRIibi4uy8+mos06fnxPAA/w5Jgb8Hq2ZuYdGEtfQb2z1b+/xxq5g7ZmW2tnavNWFIx2/JXSCY5i81ZMKQOXTu14LZXy91SXEEWDVrG4smraffmBcz2yrUKUntpyvy2uOfYEm3Ehji78j/6pMM6TyG3AWDaf5iPSYMnUvnd5oxe9Ryl+X3L5iDJyZ3AEDb7Cx7Zhr56hches8lIjdF8MTkDhg9jaTFpABwctYBwr9sRlJkAmd/P0L5PuEcn7KHkl0ru6y4/6nT4lnEpKVkTn9e/ymGb1/PjisXeLZkeXpXqMFXuzfTs3x1XlzxG/n9Anm+dCU+2bGOPpVr8/2+7S4p7nFRqWyefoH/W1QbD28jU/seYO/SKABa9CtBxaa5s/XfPOMCb8+pwcFVV9mz+Ar1ni/IstGnefrNYi5ID4lXkzk4+zid5rTA5G1iZf9NnFoZwfktl6nw3GOUaFqYDZ/u4OiC05RrX5ITy8/ScVZz9vx0iAvbIilUL4zdEw/x5PA6LskPEHE8lRWzY/h6flE8PBRDXjpHjcf9WD4rhorhvjz7SihzxkXz67hoXn4/D4umXueb+UXZuiKe9QvjaPVCMFO/jqLrO7lckv/IMQtTZiaxdkkuPD0Ubbtco+mTZj4YHkf/d/xp/ISZlWtS+GB4LEt+y8X4nxNZtzQXi5am8OvvKfR+2Y9PvohjyP/9f3v3HR9F8f9x/PW5klw6CUkgdJAmIM1C/aFSVIqCjSYgFlAQFRS/KkqxfREsCKLwBUEFRKWp9KaChS4iYqFI7wkpEHIpdze/P3YTQhMVuM2d83w88iC35fKe425mZ3Z2L9qS/L//nsfH093Mn18cpxO6dU+jRYtQDh7ysnRpDkuXxBMaKqSkeAH434STTJkSy/59XqZNzWLIkGjGjMmk36MRl7VxBz1E/7dsWb2dE2kn/9K2Ho+X0LAQQsND8OR5SaqQQELpODZ/v/Uypzy/LWt2cCI967Rl7Xpez4wxS8jL9QCQkWKMRHjyzPxh+fnjSSgVy+ZV2/ye+1yO/nCAiNLRhJeMYtdnv1C1Wz3sIXYAQmPDALA5bHiyPXhzPIjDRuaBDNxHM0moX9rK6OdUMSaOtYf3AfDtgd20rlgVgDyfjzCHkzCHkzyfl3JRxUiKiGbNoX2WZfV6FXnZPrweH7nZPmISQ8+7rdgET66P3GwvdoeNnRvSiI4PIaFCuB8Tn87nVXhyvPg8PjzZHsLjwziw/ghXtCgHQLV2ldi9Yr+xsQKfx0dejhebw8a2hbso27gUrpjzl/ly2/dHDlXrhuEKs2F3CFddF86qJSdYs/wELe8oBkDLO4qxZpnxWRYR8nIVOW4fDqewZf1JYhMclK5oTRm2bs/j6nohhIfZcDiEpg1DmbfIjQgcP2Ecth4/oShZwl6QPycHstwKhwNWrc2hRIKdKyo5Lcm/Y4eXuvWchIUJDofQsEEIixZnM3Wqm0f6RhAaajTa8fFGfqdDyHYr3G6Fwyns3u3h4EEfjRtd/tdf9+AvgdsebE7LTo3Ztmk3E5+fQWZGFp+OWsjAcfeT687jtT6TePDFu/nwlc+sjnqW0lckUrNhZe59tj25OXm8N2w22zbt4dMxixk4tie52Xm89sj7PDjsTj4cPtfquAX2L99BmZZVAMjcl8GxzYf4dcI6bKF2rnqkEbFXJlK1ez1+ePkr7KEOrhncnJ/fWU2NXtdanBxAMa1NR5RSfPT7T3z8+09sT0vhpvKVWbpnB20rVSMpwuidvLtpDW9e35Ycr4f+K+bzXIMbeX3Dt5Yljynh4ob7yvNSi+9wumxUbVycak2Ks3HBYRaN/oNl43ZRpWEsbZ+ogiPERvNeFfjfAxuJTgyl64haTBmwme6vWzM0DxCZGE7dblcytd3nOELtlG2YRMKVcYREObE5bAXbZB41DoRrdazKnJ5LiL0ihpJ1Elj05ErajW1uWX6A8lVdTHnjKMfTPIS4bGxYmUnlWmGkp3iISzQavdgEB+kpxkF7xz7xPNd9N8VLOBj4ZhmG99vH06PLWJa/RnUnL404TmqqF1eYsPSrbOrVcfLqC8W4o2sKg1/KwKcUS78wRhieeDSK9p2TSSphZ8Lbcdz70DEmv2vN0DxAtWoORow8QVqaD5dL+OrrHGrXdrJzp4e163IZMTKT0FAY/Hw0des66dcvgsf7Z+ByCaNHx/DySyd46j+RfslqSQMvIgp4Uyn1pPl4IBCplBomIsOAXkCymW+QUmquuV1/IFUpNeU8z5sATFVK3XL5S2GYP3kF01+bh1LQY1AHer3ckVGPfsDOLfsYcNNwAGo1qkLqkQxEhGcnPYQ3z8uEwTNITz7ur5jnZbfbiCoWQf/WI6harwKDJvai57XPs3PLfga0GQlArYaVST1yHBF4dsKDeD1eJgydRXryCUsy+/K8HP5+DzUfbmA89vrIPZ7D9RNuJ+23o6wbsoybZnSlWJV4bphwBwApmw7iKh6OUrBuyDJsDhu1+jXCFef/nuSdc6dzJCuT4q5wprXpyB/px3hq5SKGNW7BY/Uas2zvDvJ8xvDer6lHuX3uNACuK1mGo1knEYGxzW/D4/Py8tqvSXFn/dmfu6SyMvL45atknlvWhLAoBx8O+Jkf5h6i7YDKRMWH4M1TzBz6G1+9t5ub+laiWuPiVGtsVMYbvjjIlc3iSd6TxYphewiLdtDh2WqEhNn9lj/neA67Vu6n29z2hESFsPTpb9m36tB5t6/WthLV2lYCYMPEn6nduRp7vz/ItgU7iSwRQeMB9f1+uqdc5VDueiie5+/dgyvcRqUrXdjPeAlFBMxY9ZpGUq+p0aB8OSeda26I4sCuXOa8d4jIaBu9hyThCvPfYG61Kk76PxJFh64pRIQLV9V0YrcJk6ac5L/DYmjfNpw5c7Po92Qacz9NoHkzF82buQD4eOZJbmru4o+deTw+PpNixWyMeDGGcD/mr1LFQd++EXS9J5XwMKFmDQd2O3g9kJ6umDc3jk2b8ujTN51V38dTs6aTeXONz8CaNbkkJtpAQZ8+6TicMGRwFAkJl+czYNUQfQ5wh4jEn2f9KKVUXeBuYLKI2ETEAdwPTD/fkyqlkoFDIuK3E2Tpycfx+RRKKRZP+YZq9SuetU2Xge2Y/tp87vnPrUwaOpNFU76hfe8W/or4p1IOpfP9gh8B2PbjbnxKEVP89KPLLk+0YfqbC7jnqXZMenEOi6Z+R/sHrevFHF6zl2JV4wsa57CESEpdXxERIa5GCUSE3PTsgu2VUmz9cCPVe17N7+9voFbfhlS49Ur+mPmzJfmPZGUCcCw7iyW7t1M3IYk/MlLpvmgm7T6fwtw/fmPP8fSz9nu0XiPG/LiK/vWbMHzdCj7+fTP31fTvRK/tq1OJKx1GZFwIdqeN2q0S2L0pg+iEUEQER4iNa29PYu/Ppx+85rq9rP/8EE26lGHx2D/o/N+aVKxfjI3zD/s1//51h4kuFUlYrAu7w0alG8ty6Kdkck/k4fP4AOM8fWTi6Qd+J5OzOPpLChVvKMtPH/1Gq+FNCYlysn+df/Pnu7ljLGPmXsHITyoSGWOnVMVQisU7SD2aB0Dq0TyKFT+9/5bt9rF8djrtusXx0eijPPFaaWpcE8GKL9L9nr9Hlwi+WVyCRXMSKRZj44pKDj6eeZLb2hin126/NYyNm3JP2yfL7eOjGVn06hnJf984zvjRsTS6NoQZc/x3gJuvS+dwFi2MZ/bs4sTE2KhU0UHJJButWxufg3r1QrAJpKaemimjlGLMmEwefzySN0dl8txzUXTtEs7kyZcvv1UNvAeYAAz4s42UUr+Z28YDzYGNSikPgIhUFpHlIvKTiGwUkfxZO58D91y25GeIKxFT8HvjdvXZ/duB09a37NyY9ct+JjP9JKFhIfiUwudThIaH+Cvin1q1aBN1mlYDoHSlRJxOOxnHMgvWt+zUkPXLt5CZnmXk95n5w6zLbwzPVy54XKpZBZI3HgSMmfY+j5eQYq6C9XsXb6NEo3KERLvwZntABGyCN8fj9+xhDicRzpCC35uVqcDWtBSKu4wGRTAa8o9+23TafndWqcnX+3aSkZONy+Ew3kcoXA7/nocsluRiz08Z5Lq9KKXYviaNxErhHE/OAYxKbMuXyZSsEnHafl9P3kPTe8pid9rwZPsQMc7P52Z7/Zo/smQER7akkJftQSnF/vWHiasYQ6lrSvDHl3sB2Dp/JxWuP30Ie924zVz7cB0AvNleRMSYX5Dt//cQUDD8fvRgLquWHOeG22Jo0CKK5XPSAVg+J52GLaNO22fOxBRuuzcOh1PIyVYgYLNBjtv/0zWTzQlo+w54mLfIzd23h1OyhJ3vVhvvo5Xf5VCp4ukHKGPGZfLwA5E4nUJ2tjI+xjZwW5A/fwLdgQNeFi3OpkMHF7fc7GLVKuOgZOdOD7l5iri4U6M7s2Zl07x5KLGxNtxuhc12+fNbeQ7+HWCziIw83wYi0gDwYQzXNwF+KLT6I+BVpdRnIuLi1MHKBuDl8zxfb6A3gMsWca5N/tQzE3tRu0k1ootHMnXLSKa9OpfaTapR6aqyoODI3hTGPDG1YPvQsBBadWnMoDtHATDn3WW89OnjeHK9jOg94W///Yv1zPgHqN2kKtFxkUzdNJxpI+exdPoqnhjdg/ErB+PJ8/L6ox8Wyu+kVadGDOo42sg/bjkvTe+HJ8/DiIcn+z0/gMedx9H1+6n3VLOCZeXbVmfj8BUs7/4pNqedq59rbgxRAp7sPPYu3EqTUW0BqNy5DqufWojNYeOaYS39nj8+LJwJrW4HwGGz8cWOX1m5fxf31byaHjXrAbB41zZmbDs1uuCyO7i76lV0WzgDgPd+3sAHt9xFntfLY1/P92v+8nViqH1TIm/etRa7XSh9ZRSNOpZh4kM/kpmaCwpKVY/irqHVC/bJOJrDvp8zuPkRY6i76T1leavjOsKiHdz3dh2/5i9RK55KLcox655FiF1IqBZLjTsqU75pKZYN+p51434ivlocV7Y/Ncs/+fdUABKqxwFQ+ZYKfNp5AZElwqnXo4Zf8+f77yP7OJ7uxeGAPsOSiIy2c/fD8bz66H6WzUgnobSTZ98+dZBy7EgeW39y0/Ux47z2rT3iGHD7TiKibAweX87v+bv3OkZqmg+nQ3j9lWIUi7Ex5rVYnh6SjteTQagLRo+MLdj+0GEvP/yYyzNPGHNTet8XyY1tjhITbWP6ZP+fj+/dO520dB8Oh/DKy9HExNjo1CmMJwdm0KJFCs4QeGtUTEE95HYrZsx0M/0jo0y9e0XQvUcaISEw9u1ily2nWHHJk4hkKqUiReRFIA9wc+5z8CcwzsF/KyITgK+UUp+ISBTwm1LqrJkiIuIEDiul/vR/PcaRoBpFt7/EJfMjR+DPjwz/zNpL1S7WD7+efTomkDzedNmFNyridmSVuPBGRVi72E1WR7goTV0ZVke4aCd81ozCXCplyh7+QSl1zbnWWd1KvAVsBN4/Y/kopdTrZyxzAy4uzGVuq2mapmn/WpZeB6+USgVmAA9caFvgN6Cyud8JYL+IdAAQkVARyZ8VUxXYcunTapqmaVrgKAo3unkDYxLdhSwCmhV63B14TEQ2A6uAkubyG4EFlzShpmmapgUYS4bolVKRhX4/AoQXejzsPPvsEZFjIlJFKbVdKbUdY2b9mW4DAvjkuqZpmqZdvKLQg/87ngGSzrfSvNHNm0qpNP9F0jRN07Six+pJdn+LUmorcN6buZs3uvncb4E0TdM0rYgKtB68pmmapml/gW7gNU3TNC0I6QZe0zRN04KQbuA1TdM0LQjpBl7TNE3TgpBu4DVN0zQtCOkGXtM0TdOCkG7gNU3TNC0I6QZe0zRN04KQbuA1TdM0LQjpBl7TNE3TgpBu4DVN0zQtCOkGXtM0TdOCkG7gNU3TNC0I6QZe0zRN04KQbuA1TdM0LQg5rA6g/Xs5bD6rI1wcsTrAxXGK1+oIFy3Ulmd1hIviksDOf8LnsTrCRUtyRFod4bLRPXhN0zRNC0K6gdc0TdO0IKQbeE3TNE0LQrqB1zRN07QgpBt4TdM0TQtCuoHXNE3TtCCkG3hN0zRNC0K6gdc0TdO0IKQbeE3TNE0LQrqB1zRN07QgpBt4TdM0TQtCuoHXNE3TtCCkG3hN0zRNC0K6gdc0TdO0IKQbeE3TNE0LQrqB1zRN07QgpBv4v2HA2z35ZOubjP/+hYJl3Z6+jWlbXuOdlUN4Z+UQrm15FQA1GlRm3LfDGPPl85SqlAhARHQYr8wegIhYk/+t7nzyy0jGrxx82vLbHriBid8P43/fDOGBIXcAUOO6Kxi34nnGLH2WUhUL5Z/xmGX5T+xJZ+m9swt+Pmv5Pts+/RmA7TO3sLjzpyy5Zyab31kDQMrmwyztPovl98/hxL4MAHJP5PDN4wtQPmVJGQCiQ0IZ16I9X971AF/e9QD1E0sRE+piWuuOrLi7F9NadyQ6JBSA1hWqsuzO+5nZrgvFQl0AlIsqxtjmt1mW/+sP9vHfdmsZfus6PnjyF/JyvCilmP/WTl66ZQ2vtF3Lyqn7Adi09Cj/bbeWt7pt5GRaHgDJe928P+AXy/JvnLaVKXctZurdi1n47Go8OV42fbKd929byFv1Z+BOyynYdvuX+5ly12Jm3P8V7nRjefq+TBY8vdqq+ADMfj+NB27Zzf0372b25DQAVi48wf0376blFdvYujm7YNstG9w82Ho3fW7bw/5duQBkHvfynx778Vn0OXhv0klatEiheYsU3nvvZMHyye+f5PobkmneIoWXXzkBwPr1ubRslUKbNins3OUBICPDR9euqZblf2DAEUrW2kXtG/YWLEtN83JTpwNUa7yHmzodIC3dC4BSisefT6Zqoz3Ubb6Xjeb/zdYduVx70z7qNt/L6g1uADwexU0dD5CV5bskOR2X5Fn+JZZN/555E79i4LgHTlv+2fhlzB679LRld/a9icGdRlOibHHa3ncDEwfPoMvAdnz65kKUsuZNueyT1cybtIKBY3sWLKvdpCqNWteh740vk5frISY+ysjfpyWDu4ylRLnitO35f0wcOpsuT7Th07cWW5Y/qnwxbvrwTgCU18e89h9RulkFjv5wkIPf7qHVlLuwh9jJTjU+LNs+3kzTN24h61AmOz/7lTqPNeK3D36k+r31EJs1BykAQxu2YOX+XfT58gucNhthDieP1G3I9wf2MG7zWvrUbkDfOg15df1K7q1Zn1s/n0LrilXpcEUNPvh1IwOv+T9e3/CtJdnTj+Swctp+Bs2/jhCXnckDtrBx4VGUgrRD2Ty3sAE2m3DimNGQfDPtAANnXsNPy5LZsOAI13crw4LRO2n7eEVL8mcezWLTJzvoMetmHC4HC55exdYleylVN56KzUoxq9fXp22/6ZPtdJnakh1fHWDr4r3U7VyFVe/+TONHalmSH2DX1hwWfprBO5+Vw+kUnul5gIbNI6hQNYQXxpVi1HNHTtt+5ntpDJ9cmsP7PcybnkGf5xKYNjaVrn3jsFnwOfj99zw+nu5m/vziOJ3QrXsaLVqEcvCQl6VLc1i6JJ7QUCElxWgg/zfhJFOmxLJ/n5dpU7MYMiSaMWMy6fdohCX5Ae7tGM0j98XQ87GjBctGjE2jRdNwnn40lhFvpzFibBqvPh/Poq+y2L4zj62ryrF2Yw6PPJPM6oVlmTA1g1EvxVOhrJP+g5OZNSmM8R9m0PXOKMLDL03fW/fg/4Ytq7dzIu3khTcEPB4voWEhhIaH4MnzklQhgYTScWz+futlTnl+W9bs4ER61mnL2vW8nhljlpCXax4ZpxhHzZ48M39Yfv54EkrFsnnVNr/nPpcjGw4SWTqaiKQo/vjsV6p3r4M9xA6AKy4MAHHY8GZ78GR7EIeNzP3HyTqaSWL9UpbljnKG0CCpDJ9s3QxAns/H8dwcWpWrwuztWwCYvX0LN5WvAhhH/yF2Oy67kzyfj2tLlCE56yS7j6dZVgafV5GX7cPr8ZHn9hGdGMp3nxzglr4VCircqOIhAIgNPLk+crN92B3CHxvSiY4PIbFCuIX5fXhyvPg8PjxuL5EJYSRWjyWmVMRZ24oI3jwfnmwPNodwYGMyEcVdxJaLsiC5Ye8fuVSv48IVZsPuEGo3COPbJZmUrxxK2UohZ23vcEK2W5GT7cPhgIN7ckk+lEfdhtb8H+zY4aVuPSdhYYLDITRsEMKixdlMnermkb4RhIYa76H4eOPz7HQI2W6F261wOIXduz0cPOijcaNQS/IDNGsURlys/bRlc5ecpEdH433Ro2MUXyw22oq5i0/S/e4oRISGV7tIP+7j0BEPTqeQ5VZkuX04nUJ6hpd5S0/S4+5L997SPfhL4LYHm9OyU2O2bdrNxOdnkJmRxaejFjJw3P3kuvN4rc8kHnzxbj585TOro56l9BWJ1GxYmXufbU9uTh7vDZvNtk17+HTMYgaO7Uludh6vPfI+Dw67kw+Hz7U6boF9y3dQrtUVAJzYl0HKT4fZ8r/12EIc1OnXgLgaiVzZvS7rXlqBPdTOdUNuZPPba6jV+1pLc5eNKsYxt5vXm7WmRlwiPx87wrDVXxIfFs5Rt1EhHHWfJD7MqHzf+WkN09t04khWJv2/ns+7LdrT7+t5luUvViKU5veVZWiL1ThDbVRvEseVTeL48Mlf2LjoKJuXpxAZ5+TOQVVIrBBOq17lGXv/JmISQ+kxsgaT+2+h5xs1LcsfmRjO1d2rManNAhyhdso1KkH5RiXPu/2191dnzsMriUhwccvLDVjw9GraDG/ox8Rnq1A1hEmvp5CR5iXUJaxdcZJqV7nOu32XPnGMGHiYEJfw7BslGT88hfueiPdj4tNVq+ZgxMgTpKX5cLmEr77OoXZtJzt3eli7LpcRIzMJDYXBz0dTt66Tfv0ieLx/Bi6XMHp0DC+/dIKn/hNpWf7zOZLsJamE0aSWTLRzJNkYgThw2EPZUqea2jJJDg4c8tC3Zww9HztCTq5i3MhEXh6VxrOPx17SUYmAb+BFxAv8DDgBDzAFGKWUujQnMS5g/uQVTH9tHkpBj0Ed6PVyR0Y9+gE7t+xjwE3DAajVqAqpRzIQEZ6d9BDePC8TBs8gPfm4PyL+KbvdRlSxCPq3HkHVehUYNLEXPa99np1b9jOgzUgAajWsTOqR44jAsxMexOvxMmHoLNKTT1iS2Zfn5eB3e7iqz3UAKI+P3OM5NJ/YgbTfklk9+EvazOpMsarxtJjYAYDkHw/hig8HpVg9eDk2u406jzXEFeffXozdZqNWfAmGrl7OpuRDDG3YnL51Gpx3++8O7KHdgSkA3FG5Jl/v20ml6Fh6176OjJxshq3+kmyvx1/xycrI4+evUhi6rCHhUQ4mD/iF9XMP48lTOENtPDXrGn5amsz053+n/7T6VG8SR/UmcQCs+/wwNZoV5+juLL56fx/h0Q7uHFSFkDD7Bf7qpZN9PJc/VhzkvvltCI0MYcHTq/htwR6ubFv+nNuXb1iS8g2NA4Bf5++mQpMk0vZk8sPUH3BFO7l+YD2cYf6tRstXDqXzQ3E8fe9+XGE2Kl8Ziu1PxmIr13Axdk45ADavy6J4gh2l4KVHD2J3CA8PSiAuwX9lqFLFQd++EXS9J5XwMKFmDQd2O3g9kJ6umDc3jk2b8ujTN51V38dTs6aTeXOLA7BmTS6JiTZQ0KdPOg4nDBkcRUKC/95Df4WIcKGpSuXKOPlqThkAduzKZf8hD1dWCaFHvyPk5ile/E8cVa84e0Tm7wiGIXq3UqquUqom0ApoDQz11x9PTz6Oz6dQSrF4yjdUq3/2ucUuA9sx/bX53POfW5k0dCaLpnxD+94t/BXxT6UcSuf7BT8CsO3H3fiUIqb46UfHXZ5ow/Q3F3DPU+2Y9OIcFk39jvYPNrciLgCHVu8jtmp8QeMclhhB6esrIiLE1UhEBHLTT00yUkrx2wcbqXFffX6dvJHafRtQqX11ts/Y4vfsh0+e4NDJE2xKPgTAwl3bqFW8BCnuLBLDjCHixLAIUtynn0px2R3cXbUWU379kQFXN+WJlQtZf2Q/HSrX8Gv+ravTKF46jKi4EOxOG3VaJrDrxwyKlQilTqsEAGq3iufg1szT9st1e1n7+SGadS3NorG76Db8SipdHcOGeUfO9Wcum71rjxBTOoLwWBd2p43KzctwaHPKBffLc3v4de5u6nSszOrxW7j5xesoVTeB3xft8UPqs7XpFMP4ueV569OyRMbYKVPxwg2BUoppY1Pp9mhxpo45Ru9nEmjbOYbPPky//IHP0KVzOIsWxjN7dnFiYmxUquigZJKN1q1DERHq1QvBJpCaemq+j1KKMWMyefzxSN4clclzz0XRtUs4kydn/clf8p8SCXYOHTEOtg8d8ZBonmIoXdLBvoOnDsL3H/JQOun0A6rnX03lpafjePu9DB7oGs2I54vz4hupF50pGBr4Akqpo0BvoJ/4aap3XImYgt8bt6vP7t8OnLa+ZefGrF/2M5npJwkNC8GnFD6fIjT84o7MLpVVizZRp2k1AEpXSsTptJNx7FTl3LJTQ9Yv30JmepaR32fmD7Mu/75lOyjbqnLB49LNKnB040EATuxNx+fxEVLs1JDlnkXbKdm4HCHRLuN8vE1ABG+O/3q++ZLdJzl08jiVYoxebZPS5dmefozle3dwZxVj4tadVWqxbO/20/Z7qPZ1vP/LD3iUD5fdgVIKn1KEOZx+zR+bFMrunzLIdRsz57etSaPEFRHUbhHPtrXpAOxYn37WOfYvJ+/l+m5lsDtt5GX7EDF6ObnZXr/mjyoZzqGfj5Hn9qCUYt+6I8RVjL7gfj9M2UrdLlWwO214c4zMIuDxc/58aSnGe/fIgTy+W3KCFu0vfN526ZzjNLghguhidrIL/g8gx+2Xwc7T5E+gO3DAy6LF2XTo4OKWm12sWmVMzty500NuniIu7lQ1PmtWNs2bhxIba8PtVthsYLOB223dFTGF3XpTBFNmGKOaU2ac4LabjQP2W2+OYOrMEyilWPNDNjFRtoKhfICVq9yUKmGnSqUQsty+gnJlXYJyBfwQ/ZmUUjtFxA4kAqd1D0SkN8YBAC7b2RNqLuSZib2o3aQa0cUjmbplJNNenUvtJtWodFVZUHBkbwpjnphasH1oWAitujRm0J2jAJjz7jJe+vRxPLleRvSe8M8L+Q89M/4BajepSnRcJFM3DWfayHksnb6KJ0b3YPzKwXjyvLz+6IeF8jtp1akRgzqONvKPW85L0/vhyfMw4uHJfs8P4HHncWT9Aa5+ulnBsortqrH+lZUsuWcmNqeN656/oeBSPk+2h90Lt9LsrbYAVO18Fd8+uQib007DYdaMQgxd9SWjb2iH025j7/EMBn6zEJsI7zZvT6dqtTmQmUHfr07Nd0gMj6RuQhKjf1wFwAe/bmRehx4cz82m1zL/zuuoUCeGujcnMvLODdjtQukrI2ncsRR52V6mPPUrKz7cR2i4nS4vVS/YJ+NoDns2H6f1I8boVrNuZXj97g2ERTt4cOxVfs2fdFVxqrQow/R7lmGzCwnVYql1RyV+/HgbP3y4lZPHspnWaQkVmibRaogxXyMz2c3hX1Jp+JAxd6BO5yp83H05oVFObn2ziV/z5xvW9xDH0704HPDYCyWIjLbz3ZITvP1CMhmpXgY9cIDKNUIZ8aExBJzt9rFk9nFGmo/vuj+WQfcfwBEiPPdWkt/z9+6dTlq6D4dDeOXlaGJibHTqFMaTAzNo0SIFZwi8NSqm4HPsditmzHQz/aNYY/9eEXTvkUZICIx9u5jf83ftc5iVq9ykpHopV38XQwcW5+l+sXR+6DCTPz5O+TIOPvmfcWqnTYtwFn2ZRdVGewgPszFpVGLB8yileGV0Kp+MN7bt1S2G7o8cweNVvPNqwkXnFKsuebpURCRTKRV5xrJ0oJpS6rzjfzGOBNUouv3ljnf5OAL/2Cz6i8B+76395QqrI1yUgU0XWx3hou10X3wlaKVbi22yOsJFqea0fh7RxUpyFL0Je3+HPWnHD0qpa861LqiG6AFEpBLgBY5eaFtN0zRNC1ZB1cCLSAIwHhirAn1oQtM0TdMuQuCP80KYiGzi1GVyU4E3LU2kaZqmaRYL+AZeKVW0LoDUNE3TtCIgqIboNU3TNE0z6AZe0zRN04KQbuA1TdM0LQjpBl7TNE3TgpBu4DVN0zQtCOkGXtM0TdOCkG7gNU3TNC0I6QZe0zRN04KQbuA1TdM0LQjpBl7TNE3TgpBu4DVN0zQtCOkGXtM0TdOCkG7gNU3TNC0I6QZe0zRN04KQbuA1TdM0LQjpBl7TNE3TgpBu4DVN0zQtCOkGXtM0TdOCkCilrM5gCRFJBvZcxj8RD6Rcxue/3AI9PwR+GXR+6wV6GXR+613uMpRXSiWca8W/toG/3ERkg1LqGqtz/FOBnh8Cvww6v/UCvQw6v/WsLIMeotc0TdO0IKQbeE3TNE0LQrqBv3wmWB3gIgV6fgj8Muj81gv0Muj81rOsDPocvKZpmqYFId2D1zRN07QgpBt4TdM0TQtCuoHXtPMQEbE6w8UKhjJomvbP6Ab+MhGRMBGpICJO83FQvdYiEmL+G1TlKkwFwQSVQC1D/oFJoB6giIjD/Nfy/GZdlCQi9qKS6VIqquXJf72tFLSVs5VE5GHgR2AcMA1AKeWzNNQlJCJVgHdFJDGYypVPROwiMlZE7sk/kAk0gVgGMdhEpA3QBQLzAEVEbgSeBuvzF6qLxgMfFIVMl4qI3AVFrzzmZ+9F4FUR6SUidc3lfm9vdQN/CYlIhIhMAh4F2gK3A81EpK25PqBf70L5d2Lc5ve5/LIFAxGJAlBKeYGPgeuAp0QkztJgf0Mgl0EZfEAy0F5EBotIpNW5/qpCr/E2oIaIvCAiVS3Kkl8X9cOoi7oA14vIbeb6QK+LBOggIoPyG9CiQEQeAFYCpYFNwP8Bc0UkyYrOUED/JxcVIhIrIjcppU4Cu4BPgCylVDbwMnAjBHYvXkTs+fmVUl6l1EvAt0BXEbnZ2nQXxxzCfB/4QkSGi0i8Uup74G2gGPCGpQH/gkAug4jcLCKzRKSPiNRTSq0HngAqAL1EpKS1Cf+ciLQSkfXAHSJiU0odAB4DcoGHRaSiH7MUrot2AjMw6qIsYCLQEwKzLjJHeOxQ0Gt/DOMe78+KSC1LwwEikojxGj+olHpAKfWRUqoHsBxjBMXvdAN/aXQA7hGR6hiNewLQ1DxKbgEki0htC/P9I4XPbSmlvGblMUFEWpmL5wJLgUGWBLx0/gP4gLswvhhirIiEKKV2AC8ALUWkpZUB/4KAK4OIRIvIRGAIsACoCvQUkWizkZwMJAEdLYx5XmYv+R1gFPCiUuq9QgfBxzDqgkyMXrS/dOBUXfQpxnshvy4qCczyY5ZLxjxwUoXqoauUUqnAJGAjxulQSymljmLkaQYgIuHmqkeAxiLyf+Zyv80Z0A38PyQizUWksvlwJcaQdXuzQv0R6Az8Yq5PApaISBcROee3/hQ1ItIUY3gp/8i5GfANcBzjA4VSKheYCRwWkfutyvpPFZoE4wR+NiuMh4BYoLOIuJRSmcArwPMWxfyrQgi8MniAlUqpJkqp9zHeV2lKqePm+lUYn6WKInKFVSH/hMI4mH9LKTUPoHBOpdQfwEIgUUQu25eN/MW66HeMA8AFlyvH5ZDfMco/cBKR/sB6jNMNLnM0cQRQXES6WZe0QH+Mc+8upVSWiIQqpdzA+1gwr0Q38P+AOWS4HPjIfAPuAb4GKojIDZiNHrBYKXWHUqo/xnDSnRhDj4GghfmTrxEwXCk10Oyd5MsG5gHlxLxioCgTkeoi0hsKRiVsGGVwmz1HH8ZwWkcgzNztU+CAiDSwJPQZRKSKiLxjnn+8ylx8EsgOoDLYlFJZSqlp5uNOwKvADSLSz+yhKYyDZCcQamHcs5inrLKAj4BrRWSUiKwD3hCRESJS39x0P8ZQeYnLlOPP6qLrOVUXzVdKPaqUypAiMLv7rxCRFkD7Qo+vAloBNyulxiqlsgvNJRiC2YBayTw1MohTIwr5jXlJ4GfQPfgiTyl1GHgNo2feBuO8y0ZgN5A/DLoQ8Io5CU0pNRPoqpR61u+B/wIRiSs0pAQwH0gyGwwF1AKuNrfNbzTyj6zdgFMplSdFePKOiNyBUfmNF5FroSD/LxjzJEqayz4DIjEOyAAcGJX0CX9nPpOIDMA4oNoJJAL9zV7jD0BzingZ8s+jnuMccAhG/vswGvNnAZRSmzEax/r5+/sx7lkK5fea+b7AeP+XBbphVO7pGD05lFL7gXCMSVeXPP8F6qL8U2n5ddEt5j7eS5nhUhKRYiKSfzCXBrQrtPoWYKdS6g8RCT/jfbQR+L2IjPRMAFqJSEWlVK4YkwCLA2tB9+ADxQsYFeh4wIXxwa6A0RtsiXFuWoBrRCQCCoa0ixTzg/IWsASYJSLlzVVRGMPxSebj8cBVIlJZKeU2z4PlD4mtwrhaIKKIT97JAppgjKK8kL/QbAzdQDsRqWAungaUM9cnY/zfFoXKwwHcq5R6A3gd4z0Wr5RaglG+IlsGs0LOP49aRkTuyq/MlVJTlVJblVK7MHo6J0SkmLnrNIwDTEsviTpH/k7mqleAHkqpbUqpXzFmT58U84oGYBFwPVy2/H+lLrIBDc44iC8yCtVDi4HpIlJWKbUR2CCn5o58h3FFAOboj1dOXbmQC1TCGK2wlFkHdgRmi8jLwIfAHLM8fqUb+H/IHJ57HhimlOqK8SG6AegEPIhx1P4uxvm5k1bl/DMi0hCjMnJhDMEfBv5nrt6E8YGpYT5ei9FLnCYiQ4AvgXoi4lRKHQIGY5xTLXIKjSqsUErtVEq9BZQWkcJDeqMxKsUXxLgO+1FgXaH1rwK/+iHuORUaVn0X+FFEHGbvsCRQxlz3FkWwDHJq5rPXfDwE4/MSppTKOccu7YATSql08/F+jNnglviT/CHm8mSzPsjXBshUSuWPlvwGjLlcow9/sy7KOt/zWOWMeugGIBVjkqgdY8SpjHlOezWwVkQ+Mg+wHgbmiUh587PwI8ZETcsppVYBGUA0cJ1SapJVQfTPP/zBOEDaD9Q2H9fB+CCtARKtzvcnuStjDBk1AKYCNxZatwmoaP7eC+Mc41WF1t+IMWO7VqFlgvnNhEXtB7Cf8Tj/GxTvMssaVWhdEjAAmA3cd679ikIZCi0Pxxh+rVaUygDYMQ4AO56xvDPGgeIIjLkBN2I0TC6MkYn+GBOopgAJhfYL9efr/w/zC9C7UP74Qvs5L3f+QKyLzlcPme+FNIzTGt2BMRiNJBiXfL5rvr/nAHUKPV+xolQPne9z69cMVgcI9B+Mnu86q3P8jbwVMSaAPGo+fhLjWv0ooArwBVC/0PYjzfVNz/FctqL0gToj25kNe3eg2BnLFhV6Ha4/z/MUmYb9zDJgDLcvy98WqGtlGQBXod8fLPy5wBgZWmy+/0qbFfrXQLNC29wP/F/h95efX++Lzd+j8OfEgvwBUxddoB4qjzEpNMx8PBJjEl3hA9lYq17nQPrRQ/QXSRnDRh4pwte5i3HrxJoAyjjHuQaoLMa1sl8AMRh3PfvM3GWWGDdLKQ88h3GJzXARSSr0nKKU8inzE1ZUmJOgRJ0aTu1izm6+GnOCWaEh+97AmyKyF2gtIo78dfnDqVaU70JlKDTUWx44JsZ9CVZhzEC3+7sMYtxe9mXgOxG5UowZ8u8BmSLyjLnZUOBWjEbwc4zL425USn1TaAh8slLq20Ll98t8jkuYf4pS6jt/589X1Ouiv1gPfYJRD30DZCvjNMcHGPNLhot5j3+lVJr5nH5/nQOK1UcYwfBDERiKuUC+5UAOxixfJxAHDAeewRha7EKh3ghQD2MC1x+YQ6UYd8BqBURbXZ4zyib5rz+FeqrAtRjX/M7CmEtQFnO2sbm+BDAd+IlCvcYAKUMpc/3zGNc2z6FQT9LP2WuZ/44CDgHLMC6nBOOAZCdmbwtjjsA7GFdc5O9v6Wcn0POfozxFKs8Z2f5KPfQV0OI8+48DHgCusLosgfKTfz5SC2IiUhbj+ti3MS6tGgRUx5hhuwjYgHFZ0i7gY6VUhrlfOaXUXvN3UUXszSKFLlcyZ1zblVLHRKQrRo/rEYwbfwzCmH37oVLqHXP7kkB1pdQK87ElPfaLLENboIoyJg36/f9IjOuUmymlhopxI5dHgRXAbRj3k5+EMdErQin1kDlRKtvct6DcVgn0/IHmb9ZD05Rxg6b8eyb4zCsAnBgTGPVr/xfoIfp/AaXUPoyj30MYk7JexbhsZ4/5rxv4HuMSsjqF9ttr5VD1+cipu1vlN4yDMO6Ln3/d72dKqWoYM8y/w5iM1iS/YTT3PVyocc+/DaY/G8dLUYYFhRp3mz/yy9nXKbc2s2zAuPa6JPASRm/tZSAP49K96sq4MYmj8OkHfwv0/IHsb9ZD9Qvtl3/73yylVIZ+7f8Gq4cQ9I9/foAI4CjGEXBFjJulrMM4ar4N45KfG63O+RfK0QIYbP7uxJh4NpNCs+HNdbdjXNtfqdCyIjF8GYhlwDjAeAvjvOlsoKy5/B2glfl7BYwZ5PeYj6/G+JIbHzDV4tc8oPMHy0+w1EOB8qN78P8SyrgWfygwURkTXB7EuDFGPaCyUipXKfW1lRnP5xy9rnYASqk8oDFGj+BrMW4Xmj8J5zOl1M1KqZ3mJCpLe12BXAa58HXKpc3h690Yow2NRaS2UuoHjO9Fvxvj/viWCPT8wSSQ66FApM/B/4uYs6v/ADoopX4ylyUp40Y1RY55zu2/QEPgANBfKbVPjG/w+lwptUyMr2hsAzRWSvU294tW5heWWH2uNJDLIMYXmKRhXK/cD5islPraPABJxri7XHOMyYDTlFLrxLiN8USMyYv/U6e+OKbgXKrO/+8WaPVQINM9+H8Rs3K6D+NGHfnLDuVf1mNdsrP9xV5XqDK+orEExpAfIvI4sNScRIfFjXvAlkGM7zB/EuP7E9aa5Wghxu1XS2PcLS0V45KxbOAWEammjG/O+gBYXrhxBP9+B3mg5w9mgVQPBTrdg/8XEuP2snlW5ziXf9jrisWYtJOHcXvI55TxJSWWCNQymAce1ZVSv5iP78WY7DQO4zbEj2NcrpeEMcP8XaWUEpEaGCMQTYC7rDqoCvT8/zZFuR4KFroH/y+kiui3vv3DXld1Zdz0oi3QUyl1q1Jqs1XlC/AyLAE2ikg3Mb76dx7GDUY6YAyprsK4u9hTSql3lNk7UEr9qpR6HeO7DO4V677RK9Dz/6sU1XoomOgX91+qqAw3ysXf3eq/YnzxSqpSaqf5nH69u1UwlMF0H8ZpgmsxZpPHmHkTMGb+L8K413oVEYnM36lQJf0kxgz13f6LfJpAz/+vU1TqoWClG3jNahfb6zrCGb2u/G10Gf4eFeDXKQd6fk271PQ5eM1SEgR3twqGMuQTkQgzZ2mMr6EdgzEB0Aa8iPGFK02K6qVMgZ5f0y4l3YPXLBUMva5gKEOhTAF9nXKg59e0S0n34DXLBUOvKxjKkC/Qr1MO9PyadqnoHrxmuWDodQVDGfIF+nXKgZ5f0y4V3YPXioRg6HUFQxkKC/TrlAM9v6ZdLN2D14qEYOh1BUMZCgv065QDPb+mXSzdg9eKlGDodQVDGTRNC3y6gdeKHAmCL/UIhjJomhbYdAOvaZqmaUFIn5/SNE3TtCCkG3hN0zRNC0K6gdc0TdO0IKQbeE3TNE0LQrqB1zRN07Qg9P9NYok5uDR0kwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plt.imshow(mat)\n",
    "#lt.colorbar();\n",
    "plt.xticks(\n",
    "    range(len(ks)),\n",
    "    ks,\n",
    "    rotation=30\n",
    ");\n",
    "\n",
    "plt.yticks(\n",
    "    range(len(ks)),\n",
    "    #x+1 for x in range(len(ks))],\n",
    "    ks\n",
    ");\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        v = mat[i1,i2]\n",
    "        plt.text( i1-0.25, i2, f\"{v:0.0%}\", color='white' if v < 0.6 else 'black' )\n",
    "\n",
    "plt.savefig('figures/comparison.HS2.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Synthetic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "from simulation_manager import simulation_manager"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "manager = simulation_manager()\n",
    "manager.load_models('synthetic_3000')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes = sorted(manager.G.nodes)\n",
    "edges = sorted(manager.G.edges(data='weight'))\n",
    "tnet = weightedNetwork(nodes, edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_TO_GET = int(0.10 * tnet.Nnodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/alecmcgail/envs/epi/lib/python3.8/site-packages/numpy/core/fromnumeric.py:3440: RuntimeWarning: Mean of empty slice.\n",
      "  return _methods._mean(a, axis=axis, dtype=dtype,\n",
      "/Users/alecmcgail/envs/epi/lib/python3.8/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/alecmcgail/envs/epi/lib/python3.8/site-packages/scipy/optimize/_minpack_py.py:175: RuntimeWarning: The iteration is not making good progress, as measured by the \n",
      "  improvement from the last ten iterations.\n",
      "  warnings.warn(msg, RuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "p = dict(params.covid_estimate)\n",
    "p['s2e'] = params.daily_to_momentary(tnet, 0.1)\n",
    "sim = simulations.SEIR_daily(tnet, p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "friendHighDegNormalErr20\n",
      "friendHighDegNormalErr10\n",
      "friendHighDegRandTop5\n",
      "friendHighDegRandTop3\n",
      "friendChain\n",
      "friendHighDegChain\n",
      "targeted\n",
      "friendHighDeg\n",
      "friend\n"
     ]
    }
   ],
   "source": [
    "db = defaultdict(list)\n",
    "for s in reversed(strats):\n",
    "    sn = s.__name__\n",
    "    print(sn)\n",
    "\n",
    "    for i in range(500):\n",
    "        val = s(sim, N_TO_GET)\n",
    "        db[ktransfer[sn]].append(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "mat = np.zeros( (len(ks),len(ks)) )\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        \n",
    "        overlaps = []\n",
    "        for j in range(500):\n",
    "            s1 = set( db[k1][j] )\n",
    "            s2 = set( db[k2][(j+1)%500] )\n",
    "            \n",
    "            overlap = len(s1.intersection(s2))\n",
    "            overlaps.append(overlap)\n",
    "            \n",
    "        mat[i1,i2] = np.mean(overlaps) / N_TO_GET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "plt.imshow(mat)\n",
    "#lt.colorbar();\n",
    "plt.xticks(\n",
    "    range(len(ks)),\n",
    "    ks,\n",
    "    rotation=30\n",
    ");\n",
    "\n",
    "plt.yticks(\n",
    "    range(len(ks)),\n",
    "    #x+1 for x in range(len(ks))],\n",
    "    ks\n",
    ");\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        v = mat[i1,i2]\n",
    "        plt.text( i1-0.25, i2, f\"{v:0.0%}\", color='white' if v < 0.6 else 'black' )\n",
    "        \n",
    "plt.savefig('figures/comparison.synthetic.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# distributions within?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "db = defaultdict(list)\n",
    "for s in reversed(strats):\n",
    "    sn = s.__name__\n",
    "\n",
    "    for i in range(100):\n",
    "        val = s(sim, N_TO_GET)\n",
    "        db[sn].append(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[100, 100, 100, 100, 100, 100]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[len(x) for x in db.values()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-19-589a681ac398>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      8\u001b[0m         \u001b[0moverlaps\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mj\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m100\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m             \u001b[0ms1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mset\u001b[0m\u001b[1;33m(\u001b[0m \u001b[0mdb\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     11\u001b[0m             \u001b[0ms2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mset\u001b[0m\u001b[1;33m(\u001b[0m \u001b[0mdb\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk2\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "## plt.figure(figsize=(10,10))\n",
    "\n",
    "mat = defaultdict(list)\n",
    "\n",
    "for i1, k1 in enumerate(ks):\n",
    "    for i2, k2 in enumerate(ks):\n",
    "        \n",
    "        overlaps = []\n",
    "        for j in range(100):\n",
    "            s1 = set( db[k1][j] )\n",
    "            s2 = set( db[k2][j] )\n",
    "            \n",
    "            overlap = len(s1.intersection(s2))\n",
    "            overlaps.append(overlap / N_TO_GET)\n",
    "            \n",
    "        plt.subplot(len(ks), len(ks), i1*len(ks)+i2+1)\n",
    "        plt.hist( overlaps, bins=10 )\n",
    "        plt.xlim(-0.1,1.1)\n",
    "        \n",
    "        plt.xticks([0,1],[])\n",
    "        plt.yticks([])"
   ]
  }
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