date.ipynb

rats_biochemistry.ipynb

rats_masses.ipynb

rats_microbiology.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Анализ микробиологии"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# install.packages(c(\"gridExtra\", \"ggsignif\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "library(gridExtra)\n",
    "library(ggplot2)\n",
    "library(ggsignif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# графики"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "microbiology <- read.csv(\"microbiology.csv\")\n",
    "\n",
    "microbiology <- subset(microbiology, \n",
    "                       bacteria != 'mushrooms' &\n",
    "                       bacteria != 'st.aureus' &\n",
    "                       bacteria != 'e.coli ehec' &\n",
    "                       bacteria != 'proteus sp.' &\n",
    "                       bacteria != 'staphylococcus sp.' &\n",
    "                       bacteria != 'mushrooms' &\n",
    "                       bacteria != 'lactobacilli' &\n",
    "                       bacteria != 'bifidobacteria' &\n",
    "                       bacteria != 'bacillus spp.')\n",
    "microbiology <- subset(microbiology, group != 'ccl4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "microbiology <- aggregate(value ~ bacteria + group, data = microbiology, median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "title <- 'Результаты микробиологического анализа, медианы'\n",
    "x_label <- 'Группы'\n",
    "y_label <- 'Количество, log(10^n)'\n",
    "group_labels <- c(\"Спирт\", \"Интактная\", \"Парацетамол\", \"Водка\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Transformation introduced infinite values in continuous y-axis”Warning message:\n",
      "“Removed 12 rows containing missing values (geom_bar).”"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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HN1QkZPkL8oCyy3bZs2bRYtWjRv3rxt\n27b5+fm1bt164sSJxqt3Mg8KT0/P58+fP3nyxPQhKVlluwdzs40vPa/8w6RGjRpZn/qR0+XI\nP+TlHAjmTj62OvaNrB6/8s+Z0lyZ7thmy3IL2GrHSWxylgPyodflM3ZySB8fyZo8pA/gSxIT\nE6XEIKlRo0bFihVTU1P//vtvaUhAQEDLli0fPHiwZ8+ebdu2VatWTfpEiNHJkyeFEI0aNcpp\nedKXv7L9sIgkLS3twYMHHh4epmc9g8GQy6cxSb+sJf73xzJHevTo8eTJkyNHjhw4cKBbt25Z\nr6tJHj9+vHDhwsGDB9eqVcvyAqdPny6EmDBhQqaPhUmtavT8+fOrV69qNBrpudPSLpA+Cmb0\n9OnTa9euubq6Sk+gkP7qZP2SxLlz54QQme6AWy5YzuqEvJ4gc1EWWG3bESNG3Lp1Ky0t7fbt\n26tWrTI+T0Qi56CQity/f7/pBCEhIUFBQX/++WemGbPuwdxs40vMa6vDRP5y5B/ylneWhZNP\nHh37Vo9fOd1DCLFr1y4hRJs2bayu0UIL5NE2SnJzlgPyG4Ld/zdo0CAhxPTp002P7T/++KN4\n8eLSLdE//vjDx8fn008/Nd6PiImJiY6OVqlUpk/Mkh6DOWLEiKSkpEzP8Xr+/PmBAweKFSsm\n59/3TKS/XtLZJ1vOzs5FihRJSkq6d++eNMRgMMycOVP6CLPpn4QcSUpKkr5xZmHV5nTq1MnF\nxWX16tVJSUnvv/++ucnmzp3r7Oz89ddfW11gvXr1unTpcv78+Q0bNpgOP3DggPQ5bsnatWvT\n09ObN28u3WCV9mxwcHB6erpxmuDgYK1W27dvX+kLla1atSpbtuyGDRtMb9nfuHFjy5Ytzs7O\nmYq3XLCc1cnsCXIWZZn8trVQgIWDQgghPbkjNDTU+CH0O3fuzJkz5/jx41nvP2bdg7nZxpeY\n11aHiczl5OiQt7CzLJ985G/UunXrVq1aJfOpxVaPXzndIyEhYdu2bdK3MXLTAnl0fpPk5iwH\n5Dfciv3/evbsuX379rCwsLp16/bq1cvT0/PSpUs7duxwdXUdP368EKJp06bNmzffvHnznTt3\n2rVrl56evnHjxhcvXgwZMsTPz8+4nPfff3/kyJHR0dFqtbpfv37G4YsXL966devz589HjRpl\n7tqVqVOnTklfsH369Onu3buPHDlSuXLlPn36WJhl4MCB8+bNa9OmjfS3dteuXfHx8evWrWvf\nvv3mzZv9/f379u0r5/eypFUbDIaHDx9u2rQpNja2U6dOdevWtTpjJh4eHm+//fb27dt9fHws\n3OCIiYkJDQ2Vc2NRCDFjxowdO3ZMmTKlZ8+exucG9+vXr127dt27d69YseKNGzc2btzo6Oho\n/PR0//79IyIifvnllzfeeKNDhw6Ojo5RUVEHDhyoXLmy8ZM3Go1m1apVnTp1atCgQc+ePf38\n/O7cufPzzz8nJycvX74805czLBdsdXXye4Kcyi3LUdtmZfWgkIoMDw/ftWtXjRo1OnTokJyc\nvH379ufPn69cuVL6CksmmfZgbrbx5eaVc5jIaRyry3n27Nnx48flH/IWdpbVk4/MY3/EiBHJ\nycnSI+Ks1mP1+LXaPcLDw3fs2PH8+fMqVapIj7KTSEE8OTl50aJFjRs3Nn5pyXJ3tdWOk9jq\nLAfkO3n5kLx8wfIDijPR6XQrV66Ufh7HwcGhdOnSAwYMuHLlinGClJSUqVOnVqtWzd3d3dXV\ntW7dugsXLjQ+LdNI+ke2devWpgMDAwMLFy7ct2/flJSUTNNn+7RSI0dHx/Lly48ZM+bx48fG\nWbJ9vPCLFy+++uqrChUqODs7+/v7Dx8+XHpa8sCBA93d3UuUKHHhwgXLS8i0ahcXl8DAwODg\nYOMDYGU+oNj4oNGNGzcKIT7++GPp7aFDh0SWBxRXrFgxLS3NuATpv/9sH1As6d69uxDi22+/\nNY5dsmTJ/v37W7Ro4eHh4eHh0aJFiyNHjphWlZGRsWDBgnr16rm5uTk7O1etWnXSpEmmT42W\nnDp1qlu3bkWLFnVwcChWrFiXLl0OHz6cdessF2x1dfJ7gpzKLT+g2GqpWQmTBxQbZBwUUpFz\n586tVauWq6uru7t78+bNDx48aBxreQ/mZhvlzJuVnMNEznNurS5HCJGjQ97yzrJ88pF57Etf\nX7h165a5xsnR8Wuw1j0sPN7IKCQkRGYL2GrH5f4sB+RnKkNOnlYKmUJCQr788ssff/zR9Iod\n8sLkyZO/+eab77//XnrePQAL4uPjixQp8ujRo5e+iJsjjRo1OnfunLlHk+zatatz584hISET\nJ058BcUArwk+Y2d7GRkZS5cu9fX1NX7KBADygyNHjhQrVuzVpDoAdkGws70JEybcu3dv9OjR\ncj7bDgCvzH//+99M3+gCoDB8ecJmrl69unbt2mPHjh09erR27drjxo2zd0UA8H9kejQMAOXh\nip3NxMTEzJkz59y5c7179963b5/VX1gCAACwLb48AQAAoBBcsQMAAFAIgh0AAIBCEOwAAAAU\ngmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCONi7gDyUkZHR\ntm1be1ehHGq1euHChYGBgVlHfffddxEREa++JKV68803Q0NDsw6nS9uWhS69cOHCbdu2vfqS\nlKp+/fpz5szJOjw9Pb1du3avvh6lUqvV3333Xc2aNe1dCOxJycFOCOHm5rZgwQJ7V6EEmzZt\n2rVrl06ny3Zsenp6//79mzVr9oqrUp7U1NSPP/44JSXF3AR0aVux3KUzMjIGDBjQtGnTV1yV\n8ljt0u7u7vPnz3+VJSnVxo0bd+/eba5L4/XBrVgAAACFINgBAAAoBMEOAABAIQh2AAAACkGw\nAwAAUAiCHQAAgEIQ7AqMoKCgI0eOCCFatWolvUAmxiYC8pq5zma1E+a0l1o93o0LpP9nRZvg\nNaTw59gp0oIFC8qWLWvvKmzm/PnzarU624fE2ks+LOmlKWlbXk8KO94B5DWu2BU8tWvXLlSo\nkL2rsJnw8PCLFy/au4r/Ix+W9NKUtC2vJ4Ud7wDyGlfs8kRSUtLKlSuPHz+emJhYtmzZwYMH\n169fP9M0T58+XbJkSVRUlFqtbtCgwYgRI6TTd0JCwtKlS8+cOZOSkiLNW7duXdMZW7VqNWPG\njObNm7+67ckJc9vepk2bCRMmHDly5N9//01JSenSpUvv3r3Hjx9/+vTpEydO7NixY/Pmzebm\nbd269eeff75161ZfX9/Q0FALTfTkyZMJEyZcuHDBx8enV69e7777rhDi/v37ixcvvnLlSnp6\nevny5UeMGFGtWjVhZhe8XEmmLbB///5NmzbFxMQ4OzvXq1fvs88+8/b21ul0QUFBY8aMOXr0\n6KNHj5KTk/v169etW7ecNq9Op5s/f75dmjenPdbc9NkOT09Pb9++fXBw8FtvvSVtZlBQkPQ2\n2/bM1Cx52uaWGQyG2bNn37hx47vvvvPw8DAOt3ASyLaXmttM4/Eu56wiMdfhX7rF8q4l169f\nb6Eec81oobfcuXMnNDT01q1bPj4+w4cPN67IXC9t06bN559/HhkZGRMTo9frx44de+fOnf37\n9z958qRevXoTJkzQaDSWZ8963FnYBTbvzKbDb968mZSUtHPnztq1a+d+16Dg4opdnvjqq69i\nY2OXLVu2a9euTp06TZo0KTY2NtM0M2bMSExMXL58+YoVKx4/fhwcHCwNnz59+sOHDxctWrRt\n27YWLVqMHz8+JibmlW/ByzO37U5OTmFhYaNHj16zZs2kSZNWrFhx9+7dOXPmlCxZ8qOPPtq8\nebPleX/++edx48bNnDlTWGyiLVu29OjRIzw8vFevXvPnzz937pwQYtq0aQ4ODj/++OPPP/9c\nqVKlyZMnS7+6k+0ueLmSjGJjY0NCQj7++OPdu3f/8MMPKSkpK1euFEJoNBq1Wh0eHj5hwoT1\n69dPnTr1u+++e4lradHR0fZq3pz2WHPTmxueLXPt+Srb3LIVK1Zcvnw5NDTUNNUJiyeBrL1U\nzmbKOatIzHV4o5y2WN615LRp05KTky1svvytFkIYDIbJkyf7+PiEh4d///33v//+u16vl0aZ\n66VOTk6//PLLlClTNmzYEBgYOGPGjNTU1GXLli1fvjwyMvLPP/+0OnvW487cLsiLzmw6vEeP\nHoUKFVq6dGnu9wsKNIKd7d2+ffvChQsjR44sUqSIg4ND586dy5cvv2fPHtNpoqOjL1y4MHTo\n0FKlShUvXnzcuHFBQUEGgyE6OvrcuXOffPJJsWLFHB0de/bsWaJEid9++81e25JTlrc9KCio\nePHiQojAwECNRhMdHS1zXpVK1bBhw5o1a7q5uVluombNmtWvX9/Dw+Pdd9/18/OTPjc9b968\nSZMmeXp6urq6durU6enTp7GxseZ2wUuUZDpLSkqKXq/38PDQaDRFihQJCQkZN26cNEqlUrVt\n27ZYsWJCiNq1a5cvXz6nH+u+evVqcnKyXZo3pz3WwvRWm11me76aNrfs559/3r9/f2hoaJEi\nRWS2tsiul1rdTDlnFaNsO7zpBC/RYnnUklWrVk1ISDBXT462Wghx7dq1Bw8eDBgwwN3dvXDh\nwgMHDpS6luWTRps2bTw9PYUQNWrUSE5O7tGjhxCiSJEifn5+9+7dszp7tsddtrsgjzqz6XAn\nJ6dy5crlfr+gQONWrO3dv39fCNG/f3/TgZkOtgcPHggh/Pz8pLelS5cuXbq0cXhAQIBxyrJl\nyxagK3aWt1069Qgh1Gq1o6Njamqq/HnLlCkjvbDcRKbt7OfnJ/09u3v37o8//nj79m2DwSD9\nB5+WlmZuF7xESaYCAgK6des2bty4SpUq1atXr0WLFpUrVzYtyfi6ePHijx8/zroEC6S/GXZp\n3pz2WMvTW252U5bbU840uWxzCw4dOnT48OHJkyeXKFEi0yjLrZ21l1rdTDlnFaNsO7zpBC/X\nYnnRkqVKlXr48KG5enK01UII6XgvWbKk9Nb4pRPLJw0fHx/phZOTk4eHh7Ozs/TW0dExPT3d\n6uzZHnfZ7oK868ymw4sWLWquffCaINjZnnRe2LlzZ6ZbM6ZUKpUQwnibwAKDwSCdXAoEy9su\nbfXLzevgYLavmjaR9IEYIycnp9jY2C+++KJ79+4zZ850dXWNjo7++OOPhbxd8BIlqVSq0aNH\n9+7d++TJk1FRUcOHDx84cGC/fv2ksVqt1jhlprtjcri4uFioJ0+bN6c91tz0MpdjvIZnuT3l\nTJPLNrfgwoULTZo0Wb16dcOGDd3d3U1HWW7trL3U6mbKOatIzHV4Uy/XYnnRktJyzNVjbqsz\nnRKNvSUjI0OYHAgWzpymJw3TA8fyQWR1domFc04edWbT4XIOUigbt2JtT7oCcePGDeOQf//9\nN9PNplKlSgkh7ty5I729f//+hg0bdDqd9I/X7du3peEGg+Hu3buWL2nkK3K2PZfzWm4i6daJ\nJCYmplixYteuXUtNTe3Tp4+rq6sQ4sqVK9JYc7sgl5uj0+mePXtWtGjRjh07zpw5c/Dgwdu3\nbzeONS3vwYMH0h0c+aRrFXZp3pz2WHPTmxuu0Wg0Go30h1mqTXphuT3lTJPLNrdg5MiRU6ZM\ncXZ2zvTtGWGttbP2UqubKb8rmuvwpl6uxfKiJe/evevo6GiuHnNbba63SBfPHj58aFy49CKX\n59Wczm5uF+RdZ87Uo2RuF5SKYGd7fn5+DRs2XLJkyYMHD3Q63R9//DFw4MDLly8LIX7//feN\nGzcKIcqVK1e7du1ly5Y9ePAgNjZ24cKF586d02g00vCVK1c+e/ZMq9WGhYU9evTo7bfftvc2\nyWVh281xdnaOiYlJSkoqWbKknHktNJHBYDh48OD169f1ev2+ffvu37/funVr6TbZhQsXdDpd\nVFRUZGSkEOLx48fmdsFLlGTqwIEDgwYNunz5sk6nS0xMvHHjhukfgMjIyOvXr+t0ur179z54\n8KBVq1bCpFdYFRAQ4OXlZZfmzWmPtTx91uEajcbPz+/UqVNCCJ1Ot2nTJmlfWG7P3LS59MWa\n3NBoNE5OTtOmTTtx4sTOnTtNR1k4ELLtpVY3U/6RZa7D57LFLLSkzN6brTt37s0iHxIAACAA\nSURBVBQuXNhcPea22lxvqV69epEiRdauXZuYmBgbG7tu3TppeC7Pqzmd3dwuyKPObBxuMBhe\nvHhBsAO3YvPExIkTFy9e/Mknn2i1Wn9//y+//LJmzZpCiLNnz0ZHR/ft21cIMWvWrHnz5g0d\nOlSj0bz55psjR46U5p0yZcr3338/ePBg6XvyCxcuLFiPJzW37eZ06dJl2bJlR44c2bx5s8x5\ns20inU6n1+v79u27bNmyK1euFClS5PPPP69SpYoQon///rNnz9br9W+88cbkyZO//fbbadOm\nTZ8+3dwueImSjNq2bfvo0aNZs2bFxcV5eHjUrl170qRJxrHdu3eXvkTp5ub2+eefV61aVfzf\nXmGVv79/yZIlX33zipz3WHPTmxs+duzY+fPn9+7du1ChQgMGDDh69KhWq7Xcnrlsc0dHRzlt\nblnZsmVHjx69YMGCmjVrmn78K9vWNtdLK1eubHUzZe6+ypUrm+vwDRs2fOkWs9ySMntvVsHB\nwVu2bLFQj7mtzra3ODg4zJ49e/78+T179vT19R0+fPjFixel25S5PK/maHYLu6Bbt24278zG\n4efPnzcYDKNHj5a/XVAklcz7OAVRRkZGly5dFixYYO9ClGDTpk27du1atWpVnTp1so4NDQ0t\nXLhws2bNXn1hBUhQUNDUqVMtP4AwNTX1448/btCgwZIlS7KOpUvnlIU2t9qlixQp0rRp07yv\nMX8x12Jyem+2pC7dsGHDxYsXZx2bnp7erVu3+fPnv2S5rxOru2bjxo27d+9evXo1z7F7zXEr\nFgAAQCEIdgAAAArBZ+yAV2T//v32LuG1Q5vnlLkWoyXtjl0DmbhiBwAAoBAEOwAAAIUg2AEA\nACgEwQ4AAEAhFP7lieTk5LCwMHtXoQTZ/jCRqRMnTki/2I3cMP3Nx2zRpW1FTpc2/aUmvByr\nXTopKYkubRNWuzReE0oOdjqdLjk5OdNP/SA3nj9/nu3whw8fnj179uzZs6+4HqV68uRJtsPp\n0jZnrkv/+++/Z86cOXPmzCuuR6nMdWmtVkuXti1zXRqvDyUHO5VK5e3t/eGHH8qcPjk5WaPR\nuLi42GTtGRkZ6enpLi4u0o8V5l5KSoparbZXeUePHj1z5oynp2e2Y319fdu2bVutWrW8WLVV\nStpxGRkZS5cuLVSoULZj6dIW2LxLt2vXzviTTbZdtVVK2nGWu7RarZZ+E0zmqvN5y9i3PMtd\nGq8PJQc7tVrt4eEh/5QRFxfn4OBg7gSUUykpKSkpKV5eXk5OTjZZ4JMnTzQaja3Ke/HiRXJy\nsqenp7Ozs5zp4+PjLVy98PLyCgwM7Nixo5xF2bxlbLvjpJax145LSUlZunSpufP4S3RpR0dH\nb29vubVaq+216tK1a9d+55135CxKahlvb2+b/PisUNa56LXq0vY9Fz19+pRrzBB8eQIAAEAx\nCHYAAAAKQbADAABQCIIdAACAQhDsAAAAFIJgBwAAoBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYA\nAAAKQbADAABQCIIdAACAQhDsAAAAFIJgBwAAoBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAK\nQbADAABQCIIdAACAQhDsAAAAFIJgBwAAoBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAKQbAD\nAABQCIIdAACAQhDsAAAAFIJgBwAAoBAO9i7gZaSkpBw6dEir1QYFBbm7u5uOOnHixLVr16TX\nBoPBYDC8ePFC/pL1en2OprcgIyNDCJGenq7T6WyyQJE35en1ejnTa7Vay4Wlp6fLrE1aVP5v\nGbuUZ3UyurQ5du/SaWlplpeZI4rZcXTpl5bT8mzY/VCgFbxgl5ycPGHCBL1eHx8ff+jQoXnz\n5qnV//+6Y2RkZHh4uPTa0dHRx8cnOTlZ/sL1en2OprcqNTXVhkszGAy2LS8tLS0tLU3OlNIp\nxhydTpeWlpaj2mzbMvJ33MWz8TZZY2DdwvInlr/jrP5JyGkX1el0dOlsye/S6x/etEltA0pU\nlD+xYs5Flru0wWBQWJe2446z3KXx+ih4wW7t2rXVq1cfMWJEYmLiqFGjrl69evXqVRcXl+bN\nm3t4eHzwwQetW7eWptTpdCEhId7e3jKXnJCQoNFoPDw8bFJnampqWlqam5ubo6OjTRaYmJio\nVqttVV5aWlpqaqr88pydnS2MdXBwcHNzk9nUOV21VTnccbYJdvL7VY52nNU2UavVOerSDg4O\nma5qv7TXt0s/tEmBOegzeXEucnd3d3CwzQnfhl1apVIpqUvbdsdJXVr+jrPcpfH6KGDBLiUl\n5fDhw2vWrBFCeHl5FS5ceMGCBX5+fteuXdu2bVtwcHBAQEBAQIA0cUZGhkqlytERm9PpLZD+\neXJwcLDVAoVNy5Mu2ms0GpkLNL0smm1h8heVz1tGpjzqV1Yno0ubY8cuLZN9d5xtN4cubU6+\n7dJ4fRSwfvD48WOVSuXk5CSEuH79+uPHj2fNmjVt2rRly5a5uroab8ICAAC8hgrYFbtSpUo5\nOTlNnDixVq1aBw4caN++fbFixYQQXl5eb7/99smTJ+1dIAAAgN0UsCt2jo6OISEhZcqUSU1N\nbdKkiaenp3HUjRs3qlatasfaAAAA7KvAXLHT6/VXrlxJSUkpV67cZ599JoTYt2/fjz/+WLFi\nxcDAwGPHjp06dWrx4sX2LhMAAMBuCkawS09Pnzx58t27d1Uq1YsXL2rVqtWnT5+WLVv+8ccf\nX331lZOTk4ODw6RJk7y8vOxdKQAAgN0UjGC3evXqUqVKBQcHazSaS5cubdmyZeLEie+88860\nadNu3boVHx9ftWpV+V+YBwAAUKQCEOy0Wu2BAwdWrlwpPcsnMDAwMDDwzz//XLRoUWJi4vjx\n4+1dIAAAQL5QAL48kf4/pgMbN2787bffnjp16q+//rJXYQAAAPlKAQh2bm5utWvXXrBgQaaf\npvH39w8KCrp8+bK9CgMAAMhXCkCwE0KMGTPm8ePHY8aMOX/+vOnwhIQEHx8fe1UFAACQrxSM\nYOfr6zt37tyAgIApU6ZMnz49KioqJiZmx44dV65cadmypb2rAwAAyBcKwJcnJN7e3l9++eWF\nCxe2b9/+7bffarXasmXLTp061fQZxQAAAK+zAhPsdu/e7ezsHBQUVKtWLZ1Ol5aW5ubmZu+i\nAAAA8pF8fSt23bp1p06dEkIkJCSEhYVVqVJFGq7RaEh1AAAAmeTrK3Z+fn7fffddxYoVnZ2d\nW7Ro4e/vb++KAAAA8q98fcUuKCho2bJl7u7ux44dS09PT05OtndFAAAA+Ve+DnZCCDc3t7i4\nuF69esXHxw8bNuzgwYP2rggAACCfyte3YoUQR48eTU5O7t27t1qtPnfu3LNnz+xdEQAAQD6V\nT4Pds2fPTpw4odFoYmJihgwZolarhRB16tSxd10AAAD5V34Mdjdv3pw6dWqxYsXi4uJSU1Pb\ntGlj74oAAAAKgHwX7AwGw9y5c4cNG9aiRYvt27efO3eudOnSQojExEQvLy97VwcAAJB/5bsv\nT1y8eNHFxaVFixYJCQnh4eGDBw8WQuzbt2/VqlX2Lg0AACBfy3fBLi4uzsHBQQixYcOGli1b\nSpfrnJ2dExIS7F0aAABAvpbvgl2tWrWio6PXrl0bFRXVu3dvaeDly5cDAwPtWxgAAEA+l++C\nna+v76effrp9+3ZXV9ezZ8/+888/O3fuPHHiRPv27e1dGgAAQL5m/y9PJCQk6PX6woULG4e0\nadOmbNmy69atmzNnjsFgKFq06Jdffunp6WnHIgEAAPI/+we7sLCwgwcP9ujRo2vXro6OjtLA\nihUrfv3118+fP09MTCxZsqT0HDsAAABYYP/A5ObmVr169fDw8OHDhx8/ftx0lIeHh5+fH6kO\nAABADvtnpqpVq9apU2fZsmU1a9acPXv2V199defOHWnUvn37Vq5cadfqAAAACgz7B7sqVao8\nffq0cOHCY8aMmTt3bkZGxmeffbZ06dKHDx9u3LiRn50AAACQyf6fsfP29jY+1qRixYr//e9/\nDx8+vG7duj179rRr1658+fL2LQ8AAKCgsP8VOyGEq6ur6dsWLVpMmTLF1dW1X79+9ioJAACg\nwMkXwS6rDRs2fPDBB97e3vYuBAAAoMDIj8Hu2bNnycnJnTt3tnchAAAABYn9P2OXVaFChWbP\nnm3vKgAAAAqY/HjFDgAAAC+BYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAA\nUAiCHQAAgEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiC\nHQAAgEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiCHQAA\ngEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiCHQAAgEIQ\n7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiCHQAAgEIQ7AAA\nABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAgHexfw6sy7dELWdPet\njB9bs1Hui3kFtDM+tzDWUYhC0mQWF+Iwba4NSwIAAHmKK3YAAAAKQbADAABQCIIdAACAQhDs\nAAAAFIJgBwAAoBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAKQbADAABQCIIdAACAQhDsAAAA\nFIJgBwAAoBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAKQbADAABQCIIdAACAQhDsAAAAFIJg\nBwAAoBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAKQbADAABQCIIdAACAQhDsAAAAFIJgBwAA\noBAEOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAKQbADAABQCIIdAACAQhDsAAAAFIJgBwAAoBAE\nOwAAAIUg2AEAACgEwQ4AAEAhCHYAAAAK4WDvAvKWwWBITU217TJlLlCr1Qoh0tPT9Xq9rVat\n1+vlb45Ndq1xddLmmKPX6zMyMgpKy9hEjlYnvx9anSynXdqGLZPPd5xUXkZGhsFgkD+9hcLk\nd2mZlLTj6NLm5EWXllme5S6N14fCg50QQuZZ3uYLNE5m2wJsvjm2Wp3BYMhpba9Jy4icNI6c\nyezVzvm8S0vLeYl+aGGB9t3S/Lzj6NJyFmuT5di8H0LxFB7sVCqVq6urbZcpc4EGgyEjI8PJ\nycnJyckm601JSVGr1fI3xyb/uxlX5+Bgqauo1WonJyf5LZOenm7DlklOTs5Ry9iE/NXlaMdZ\nPYPnqEvbtmXs3qWtkvqVs7OznIlt2KVlej133GvVpW1+LsrRqdJyl8brg8/YAQAAKATBDgAA\nQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEI\ndgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAA\nAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApB\nsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMA\nAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAI\ngh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0A\nAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBC\nEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwA\nAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAU\ngmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAH\nAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACg\nEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7\nAAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAA\nhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDY\nAQAAKISDnIm0Wu2RI0f2799/9uzZuLi4Z8+eeXt7Fy1atG7dukFBQc2bN3dwkLUcAAAA5B0r\nV+x0Ot2aNWsqV67cpk2b2bNn//3333q9vkyZMgaD4e+//549e3abNm0qV668Zs0anU73aioG\nAABAtiwFu5iYmFatWg0aNKh69eqbN29+9OjR3bt3T58+feDAgdOnT9+9e/fRo0ebN2+uXr36\noEGDWrduHRMT82qK1ul0BoPh1awLAACgoLB0C7VOnTqVK1c+c+ZM3bp1s53A19e3V69evXr1\nOnv27KhRo+rWrRsbG5s3df4fERERycnJAwcOzDrq4cOH8fHx0msp/2m1WtuuXeYC9Xq9VIMN\nC8iLzbHMuDppc8wxGAzyt1RhLSOH/PKsTpbTLbVhy+TzHZfT8mzYpWV6PXccXfql2bZL4/Vh\nKdgNGTJk5syZGo3G6lLq1q0bGRk5depU2xVmVnx8/C+//DJv3rxsx65duzY8PFx67ejo6OPj\n8+zZM9sWkKMFJicn23DVOp1O/toL2WKNxtWlpaVZmEyr1aakpBSUlrGJHK1OfnkvXrywPIFe\nr8/RqrVarW1bJp/vuJSUlJSUFDlT2rxLW5VHfUYme+04y13aYDDQpS2TX57lLo3Xh6Vg9803\n3+RgQQ4OwcHBua7HurVr17Zv375YsWLS21OnTp09e9bd3b1Tp05eXl6NGjVyd3eXRqlUqr17\n97q6utq2AJkLzMjI0Gq1Tk5OcpKxHKmpqSqVytnZ2SZLk8m4sZa/H6NWq52cnGS2jFarzcjI\nsGHLvHjxQq1Wy26ZeJusVH6/su2OU6vVxlUvj75ok2UOKxcoZ7J83qVz2q9s2KVlkr+0HHZp\nK/LzjlOpVCqVSjEtY9vypC7t7OysVst6fgXfYoREVj948eLFwoUL9+3b9/Dhw6xfkrh69Woe\nFJa969evX7x4ccmSJdLbnTt3rlu3rkqVKrdv346MjAwJCWnZsmXLli2lsRkZGfv27TPmPFuR\nucCUlBStVuvi4uLk5GST9aampqrVavmbY5ObAcbVOTo6WphMo9E4OzvLb5mMjAwbtox0MrX5\njrZM/upytONUKpXVCV7bLm3ZixcvpL+CMv+s2rBLyyR/abbt0vbdcVa7dI629MWLFxqNJt+2\njG13nLFLyyzPcpfG60NWsBs3btySJUsCAgL8/Pzs+z/BypUr/f39pdcPHjz46aef5s+f7+/v\nn5CQ8MUXX0RERAwZMsSO5QEAANiRrJQWERGxePHi4cOH53U1VvXp02fRokUjR44cMWLEnTt3\nOnbsKOU8b2/vli1b3rlzx94FAgAA2I2sO/cJCQnvv/9+XpciR926dRctWlS3bt3p06fv2LGj\nRIkSxlExMTGVKlWyY20AAAD2JSvY1a5d++bNm3ldimV6vf7y5ct//fVXcnLyiBEjZs6c6eLi\nUq1aNWms9BWKdu3a2bdIAAAAO5J1K3bu3Lljx45duXJlYKCsb8/ZXHp6+uTJk+/evatSqV68\neFGrVq0+ffosWbJEpVJFRkauX78+JSVlwoQJnp6edikPAAAgP5AV7GbOnBkbG1urVq1ixYoV\nLVo009hLly7lQWH/x+rVq0uVKhUcHKzRaC5durRly5aJEye+8847gwcP9vHx6dmz55tvvunr\n65vXZQAAAORnsoJdfHx86dKly5Ytm9fVZEur1R44cGDlypXSF3IDAwMDAwP//PPPRYsWJSYm\njh8/3l7XEQEAAPIVWcEuKipKenHnzp2AgIA8LCc76f9jOrBx48b+/v7jxo3766+/6tev/4pL\nAgAAyIdkfXlCCHHnzp0hQ4ZUrlw5T6vJlpubW+3atRcsWJDpp2n8/f2DgoIuX7786ksCAADI\nh6wHO2OkO336dFhY2CuoKasxY8Y8fvx4zJgx58+fNx2ekJDg4+Njl5IAAADyG0vB7t69e1Kk\nu3Tp0rZt286cOfPee++9sspM+fr6zp07NyAgYMqUKdOnT4+KioqJidmxY8eVK1eMPyAGAADw\nmrP0GbvVq1cfO3bs119/DQoKemUFmePt7f3ll19euHBh+/bt3377rVarLVu27NSpU3nECQAA\ngMRSsCtVqtT169eXLVtWpEiRevXqvbKasrV7925nZ+egoKBatWrpdLq0tDQ3Nzf7lgQAAJCv\nWLoVO3To0LNnz6pUqvr167/zzjvHjh17ZWVJ1q1bd+rUKSFEQkJCWFhYlSpVpOEajYZUBwAA\nkImVx50EBgZu3br10qVLM2fObNasWfPmzSMjI19JYUII4efn991331WsWNHZ2blFixb+/v6v\nbNUAAAAFjqzHndSsWXPLli0XL14sXrx4XhdkKigoaNmyZe7u7seOHUtPT09OTn6VawcAAEKI\nyZMnq7KzbNkye5eGzGQ9oDgjI+Pq1auPHj3q37//wYMHS5YsWblyZY1Gk9fFCSHc3Nzi4uJ6\n9eoVHR09bNiwjz/+uHXr1q9gvQAAwNTkyZMzXd9p1qyZvYqBOVaC3eXLl6dNm7Z79+7U1FTT\n4Z6enu+///706dPLlCmTl+WJo0ePJicn9+7dW61Wnzt37tmzZ3m6OgAAkK2+fftWrVrV3lXA\nCku3YqOioho0aBAZGdm/f//vv/9+y5Ytv/zyy5YtWxYuXNi1a9etW7fWrVs3r3/44dGjR0OG\nDFGr1UKIOnXq8NQ6AADyj9q1a7dr127Hjh01a9Z0dnYuUaLEuHHjpF8BbdKkScmSJXU6nen0\n5cuXb9SokRCiZcuWWe/tTp8+XZrM6tiaNWtmW0/p0qW7du2aZ5tbAFi6Yjdx4sSqVasePHjQ\n29s769iHDx+2bNnyiy++2LVrl83Levbs2YkTJzQaTdu2bXlSHQAA+ZOzs/PFixfnzJmzYcOG\ngICAtWvX/uc//1GpVHPmzBk4cODQoUP37t3boUMHaeLTp09HR0d//vnn0tsKFSqEh4dLr589\ne9aqVSvTJVseC3MsXbE7efLkoEGDsk11QogSJUqMHDnyyJEjNq/p5s2bw4cP37Nnz7p16z76\n6KP79+/bfBUAACD31Gr1w4cPFy9eXKdOnUKFCn322WetW7desWKFVqvt1auXq6vr+vXrjRNv\n3brV0dGxV69e0lsXF5c6/5P1CpzlsTDHUrBTqVR6vT43E7wEg8Ewd+7cYcOGLViw4P33369Z\ns2bp0qWFEImJibZdEQAAyL1ixYrVqlXL+LZp06aJiYn379/38vLq1q3b9u3bExISpFHh4eEd\nOnTw9fW1U6WvBUvBrmHDhmvWrDH3fYXHjx8vXry4adOmti3o4sWLLi4uLVq0SEhICA8PHzx4\nsBBi3759q1atsu2KAABA7pUoUcL0rY+PjxDi8ePHQoiBAwempqZu3bpVCHHmzJlbt27179/f\nJiv9+++/XVxcXF1dS5cu3b59+8OHD9tksQpg6TN2wcHBrVu3rlSp0nvvvVe7du1ixYo5OTml\npaU9evTozJkz0p3vsLAw2xYUFxfn4OAghNiwYUPLli2ly3XOzs7GvA8AAPIPlUpl+jYjI0MI\nIX3rsU2bNv7+/j/++OPgwYO3bt1aqFChzp0722SlFStW3LFjh16v/+effyZNmtShQ4fz589X\nqlTJJgsv0CwFu4YNG0ZFRU2fPn3dunWZHnfi4eHRrVu36dOnly9f3rYF1apVa8mSJWvXro2K\nilq6dKk08PLly4GBgbZdEQAAyL2YmBjTt7GxsUKIokWLCiHUanX//v1nz559//79sLCwHj16\nODs722SlTk5O0rNXqlevLoTo0KHDwYMHCXbC6nPsatasGR4enpGRcf369UePHqWmprq6upYo\nUaJSpUp59IBiX1/fTz/99Pvvvy9evPjZs2fLlClz/vz5EydOLFq0KC9WBwAAcuPx48cnT55s\n0KCBEMJgMOzbt69MmTLGXwEdOHBgcHDwuHHj7t69O2DAgLwoQPq4v5OTU14svMCR9csTjo6O\nNWrUqFGjRqbhSUlJcXFxAQEBuakgISFBr9cXLlzYOKRNmzZly5Zdt27dnDlzDAZD0aJFv/zy\nSx56AgBAPlSuXLn+/ftPmjSpZMmSYWFh586dmzVrlvH+bKVKlRo3bvzTTz+VK1euSZMmtlpp\nenr61atXDQaDdCu2UKFC7dq1s9XCCzRZwc6czZs3DxkyxGAw5GYhYWFhBw8e7NGjR9euXR0d\nHaWBFStW/Prrr58/f56YmFiyZEnpVj0AAMhvihYt+u23306YMOHChQuFChWaNGnSxIkTTScY\nOHDgn3/+2a9fv0yfxsuNGzduVKtWTVp7vXr11qxZ4+fnZ6uFF2i5CnY24ebmVr169fDw8L17\n93788cdvvfWWcZSHhwcX6gAAsK9Zs2bNmjXL3FidTteyZcuTJ0+am8DFxUWtVn/00UemAyMj\nI03f+vr6ml4nytFYUzz71lKwu3PnjuWZnzx5kvsKqlat6uXlNWbMmPXr18+ePbtmzZpDhgyR\nbu/u27fv7t27Q4YMyf1aAADAq/fixYuQkJBOnTqVK1fO3rW8FiwFu1ezutRggAAAIABJREFU\nD6pUqXLp0qXChQuPGTOmY8eOK1as+Oyzz9q3b9+tW7eNGzdOmzbtFdQAAABs6969e2fOnFmw\nYEF0dPQvv/xi73JeF5aCXZUqVZKTk0eMGGFugr/++isiIiKXFXh7e/fu3Vt6XbFixf/+97+H\nDx9et27dnj172rVrZ/PHqQAAgFdg7969Q4YMqVChwp49e3gQyStjKdiFhYU1atTIz8/P3HOi\nV61alftgJ4RwdXU1fduiRYsyZcpMmjSpX79+uV84AADIIydOnDA3atCgQYMGDXqVxUBY/kmx\nunXrhoSEfPrpp1evXn1lBUk2bNjwwQcfeHt7v+L1AgAAFFxWvhX7n//8p27duua+n1y5cuUP\nP/zQ5jU9e/YsOTnZVr86AgAA8JqwEuxUKlWrVq3MjW3evHnz5s1tXZIoVKjQ7Nmzbb5YAAAA\nZbN0K3by5Mk6nU7mgnQ63ZQpU2xREgAAAF6GpSt2K1as+OOPPxYtWhQYGGh5KRcvXhw5cuSV\nK1e+/vprm5YHAADsbN4ls9+QeAljazay4dKQiaUrdmfPntXpdLVr1+7atWtERER8fHymCeLj\n4yMiIrp27Vq7dm2dTnf27Nm8LBUAAACWWLpi5+fnFxkZuXr16uDg4F9++UWtVpcrV87X19fb\n2zshISEuLi46Olqv15cpU2bp0qWDBg1ycLD/D5QBAAC8tqxEMQcHh2HDhn300UeHDh3av3//\n2bNnHz9+HBsb6+XlFRAQ0K1bt6CgoFatWjk5Ob2acgEAAGCOrGtsTk5O7du3b9++fV5XAwAA\ngJdm6TN2AAAAKEBkXbGrVauWuZutKpXK09OzTp06n376Kb8EBwAAYEeyrtiVKVMmNTX19OnT\n169f12q1Op3u5s2bp0+ffvHihVqtvn379sKFC2vXrh0VFZXX5QIAAMAcWcFuxowZCQkJmzdv\njo+PP3fu3NmzZ58+fbplyxatVrthw4Y7d+5cuXLF399/8uTJeV0uAABQntjY2LFjx1aqVMnZ\n2dnX17dly5Y//fSTvYsqkGTdih09evTYsWN79eplHKJWq3v06HH//v2xY8fu3LmzcuXKX375\n5ahRo/KsTgAAoEzR0dFNmjRxcXH5+uuv69Spk5CQsGPHjn79+l28eHHWrFn2rq6AkXXF7syZ\nM9WqVcs6vEaNGkeOHJFe+/j46PV6W5YGAABeAyNGjNBoNOfOnevbt2+NGjUaN248e/bslStX\n3r59Oy0tTQjh4eHh4uLi4eHh4eHh5uamUqni4uKk4du3b5cWsnLlSpVKtXnzZq1Wq1KpFi9e\n3LZt26pVq5YsWXLRokVCiA4dOhhnd3d39/DwGDlypB23Oo/ICnaFCxcOCwvLOvz333+XHkqs\n1+t/+OGHypUr27g6AACgaM+ePfv999/HjRvn5eVlOnzgwIGbNm1ydnaW3q5atSopKSkpKWnv\n3r1ZF/L8+fMpU6ZIX/R0cHBQq9ULFy5cs2bN1atXf/rpp1GjRh09evS3335LSko6ePCgEOLW\nrVtJSUlS4FMYWbdiBw4cGBIScvPmzXbt2hUvXlxKygcPHjx48OCwYcOEEH369ImIiPjhhx/y\nuFoAAKAot27d0uv1tWrVys1CZs2a1axZs6NHj0pvVSpV3759/f39hRDNmzevVavWzz//3LRp\nUxuUm+/JCnZff/21s7PzokWL/vzzT+NAT0/P0aNHf/vtt0KI+vXrd+jQ4cMPP8yrMgEAgBKp\nVCohhFarfeklREdHr1ix4ty5c2+88YZxoOkj2MqUKXPv3r3cFFmAyAp2Go1m2rRpU6ZMefDg\nQWxsbFpamo+PT4UKFRwdHaUJPv/887wsEgAAKFOlSpU0Gs3p06fbtm2baVRGRoYxaZijVqvH\njx8/ZsyYsmXLmg5PT083vtZqta6urrYqOJ/LwS9PqNVqvV6fkZHh4ODg4eFhta0BAAAs8/T0\n7Ny5c2ho6KNHj0yHh4eHBwQExMfHW5795MmTp06d+uKLLzINv3btmvH1rVu3ypQpY6uC8zm5\nwW7lypVlypQJCAho3Lhxo0aN/P39q1Spsm3btjwtDgAAKN53333n6upau3bt1atXX7p06cSJ\nExMnTuzTp8/YsWMLFy5sed6FCxeGhoZmvSC3devW06dP63S69evX37hxo2fPnnlWfv4i61bs\nxo0bhw4dWqdOnX79+pUsWVKv1z948GDnzp3vvfferl273nnnnbyuEgAAKJW/v/+ZM2dCQkJC\nQkLu3bvn5eVVp06dHTt2vP3221bnrV+//vvvv591+KhRoyZOnHj8+HFPT88VK1Y0aNAgDwrP\nj2QFu/nz5w8YMGDt2rXSJxwls2fP7tWrV3BwMMEOAADkRtGiRefNmzdv3rxsxyYlJRlfN23a\n1GAwZB0uhJAebifx8/Pbt29f1kU1atTIOLsiyboV+/fff/ft29c01Qkh1Gp1//79z507lzeF\nAQAAIGfkfsZOp9NlM7Naza9NAAAA5BOybsUGBgYuWrSoXbt2Go3GOFCr1a5evbpu3bp5VhsA\nAECO5eapeAWdrGA3ceLE7t2716hRo3Pnzn5+fgaD4d69ezt37rx169bOnTvzukQAAADIISvY\ndevWLSws7KuvvgoNDTUOrFat2rZt2zp27JhntQEAACAHZAU7IcQHH3zwwQcf3L17NyYmRqVS\n+fv7+/n55WllAAAAyBG5wU5StmzZTD/ZAQAAgHzCUrB788035Szi1KlTNioGAADkO2NrNrJ3\nCZDLUrBzcMjZ9TwAAADYkaXoduLEiVdWBwAAyK922XRpnWy6NPwfch9QDAAAgHyOYAcAAKAQ\nBDsAAACFINgBAAAoBMEOAABAIQh2AAAACpGrJ9WtWbNGCOHt7f3GG28EBATYpiIAAAC8lFxd\nsRs6dOigQYN+/vnnZs2aLV261FY1AQAA4CXkKtht2bJl69atmzZtun379ttvv22rmgAAwOuj\nadOms2bNMh2yfPlylUo1btw4e5VUcOXqVmz37t2lF46OjuXKlbNFPQAA4LX24MGDL774olCh\nQvYupEDK2RW7u3fvHj9+PCoq6v79+3lUEAAAeJ0NHz68QYMGrVq1Mg7x8PDYsGGD9DouLk6l\nUkVGRnbo0MHDw8PNzU2lUrm7u3t4eIwcOVIIcf369U6dOhUtWtTT07NJkyZRUVHSjA4ODuHh\n4UKI+/fvu7q67t2719wSsl2dhSUfPHiwUaNG/6+9e4+Lqtr/P75mGARxEDStAFHMVFA0fIBI\namlJeUlRA8zKzDyZ6aPSvuYjsszUHuYl01NalnoEE6m0vJalpllWlvYNb5koXgI1ckxQGG5z\n+f2x+83h62XYI3uYYfF6/nEew95r1v7MmuX0PvvatGnTZs2aBQcH63Q6k8lUO2N1NbXBbunS\npS1btoyIiOjevXtCQkJ4eHj79u3XrVvn1uIAAEC98sknn2zfvv3999+32WzOW27ZsqW4uHjH\njh1CiNzc3OLi4kWLFgkhUlNTfX19jx49eu7cuS5dugwePNhqtVZ942uvvZaYmHj//fdfr4fr\nuWbPFRUVQ4YMiY2N/euvv0wm0+bN2j5X12WqDsVmZmY+9dRTMTExI0aMCAkJsdlsZ86c2bRp\nU3Jy8ubNmwcMGODuKgEAgPT+/vvv5557bubMmTU5v+vrr7/28/MLDAwUQowZM2bx4sWnTp1q\n06aNsvbw4cOrV6/Ozs7WqmchxOXLl1NSUgyGGp3ephVVRSxYsGDkyJHp6ek6nc6xcPbs2Q89\n9NCsWbMIdgAAoOaef/758PDwCRMmXL1q7NixynFSu93uvJMjR47MnDnz0KFDVqtV2e1XWlqq\nrDKbzWPHjp08eXK7du2cd3LNzV2z57Zt2zZt2vSzzz7r2bOnr6+vC5/WPVQdiv3tt98effTR\nqqlOCKHX6x977LEby7wAAAAOOp1u69atWVlZy5Yt8/HxubrB+++/X1hYWFhYmJub66Sf06dP\n9+vXLzY2Nicnp6CgQDk3zmH8+PH79u2Li4urtp6rN3e9nv38/NasWbN9+/aAgIBbb7118ODB\n6j6xu6g9x+6K49P/vFmvr/YQOAAAgHNlZWVjx4594YUX7rjjjpr0s3fvXrPZ/NJLLxmNRiHE\nnj17qq5NT0+fO3fuuHHjCgsLNey5W7duBoNhypQpf/7554YNG2pSf82pCnadOnVatGjRFdnO\nYrEsX768S5cu7ikMAADUF++++26DBg1effXVGvajnJz37bffVlZWbtmyZc2aNUKIqrfyeOaZ\nZ653tPeGex41atQtt9wybdq0GhavCVXn2KWlpT344IMdO3YcNGhQWFiY3W7Py8vbtGlTbm7u\npk2b3F0iAFimT3LewFcI5Z5XFqfNDNPma1USAA1dvHjxs88+8/f3r2E/sbGxU6dOHTVqlNVq\n7dOnT2Zm5ujRo5OTk5UbnQgh9Hr90qVLY2Njk5OTk5KSat5zbGzs8ePHs7Oz9foaPfRBK6qC\n3dChQ7Oysl5++eU333zTsTAqKmrdunUPPPCA22oDAADy271799UL169f73hdXFzseN2sWbOq\nFzQkJCRccTnFjBkzZsyY4fjTcWzUYvnn//dFR0eXl5c76eF6m7tez1X17Nmz2ss73ErtpbnD\nhw8fPnz46dOnz549q9PpwsPDw8LC3FoZAAAAXOLaPVdatWrVqlUrN5UCAACAmlB7PHjbtm2L\nFi1SLvr94osvhgwZ0q9fP+XMQQAAAHgDVXvsPvzww5EjRwohjEbjunXrBg8e7Ovrq9Ppvvrq\nq1WrVj366KNuLhIAAADVU7XHbuHChffee+933333xBNPjBw58uGHH758+XJRUdEjjzyyYMEC\nd5cIAAAANVQFu6NHjz7//PM9e/acNm3auXPnRo8e7ePjYzAYnnjiid9//93dJQIAAEANVcGu\npKQkODhYCHHTTTcJIZTXyouSkhL3FQcAAAD1XLsqFgAA1D8DPV0A1FIb7EaOHBkQEKC8TklJ\nUe4NXVZW5q66AAAA4CJVwa5Xr17XfC2EaNGihcYVAQAAb7Jz2zENe7vnvrYa9oYrqAp233zz\njZvLAAAAQE2pungiODj44MGD7i4FAAAANaEq2BUVFVmtVneXAgAAgJpQ+0gxAAAAeDm1V8Um\nJiYaDNdu/Oeff2pXDwAAAG6Q2mDXpUuXoKAgt5YCAACAmlAb7ObNmxcTE+PWUgAAAFATnGMH\nAAA8KSEhQXctTz/9tKdLq3tU7bEbPHgwx2EBAICbPPjgg9OnT6+6ZPjw4Z4qpk5Ttcdu/fr1\nISEhW7ZscSy5dOlSVlZWaWmp2woDAAD1RZMmTaL/L+XhpYqcnJyBAwc2b948MDCwR48eP/30\nkxDCYrHodLrFixffd999kZGRISEhixYtctJeCGE0GletWqW8Pn78uE6nO3TokPLnxYsXx40b\nFx4eHhAQEBcX99VXXwkh+vfvbzQaAwICdDpdo0aNjEbjM88847x/nU63c+dOR+Xt2rXT6XRf\nfvmlEMJkMo0aNSo8PDw4OPjOO+/csWOHo9no0aN9fX2NRqPRaPT19e3Xr98Nj6SqYHfu3Lmu\nXbsmJyc7lly6dOmRRx7p2rVrQUHBDW8bAACgWqmpqb6+vkePHj137lyXLl0GDx5stVoNBoNe\nr//3v//9n//85/fff//444+fffbZ3bt3X6+9800MHjz4jz/+2Lt3b2Fh4ZgxYwYNGnT69Okt\nW7YUFxcrCSw3N7e4uFjJjk76j4yMXLNmjfJ6//79f//9tyOhpqSknDx58ocffigoKEhJSenb\nt29ubq6yKjc395lnnikuLi4uLn788cdrMlaqgl1aWtr58+czMjIcS0JDQ7/44guTyfTiiy/W\nZPMAAADOff311ytXrmzatKnRaBwzZkxBQcGpU6eEEDqd7tFHHw0PDxdC3H333Z07d/7000+d\ntL+eAwcOfPfddwsWLLj11lsbNGgwduzY6Ojo9PR0V+sRQgwZMmTdunU2m00IsXbt2qFDh1os\nFiHEoUOHdu3a9eabb4aHh/v5+U2aNCkiImLFihXKu44fP962rTaP0FUV7LZt2zZt2rTU1NT/\nvk2v79+//5QpUzZs2KBJHQAAANd05MiR5OTk0NDQW265JTExUQjhOBmsah5q2bJlXl6e8/bX\nlJOTI4Ro376947qNX3/99cSJEzdQT7du3fz8/JQdh59++umwYcPsdrsQ4vjx40KIjh07OjqJ\niopS9tiVlpaeO3euffv2NzI0V1EV7C5evNikSZOrl99yyy3l5eWa1AEAAHC106dP9+vXLzY2\nNicnp6Cg4Jtvvqm6tqKiwvHaYrHo9Xrn7a8pICBACHHx4kV7FVUPVKqvRwiRmpq6du3aw4cP\nnz9//p577rneRu12e1lZmRAiJyfHbrdXzXw1oSrYderU6aOPPlL2KzqUlpa+++67nTt31qQO\nAACAq+3du9dsNr/00ktGo1EIsWfPnqprjx496nidm5vbsmVL5+2vSdnt97//+7+OJSdPnlT2\ntLlajxDioYce2rhx48aNG4cOHep4apeyiQMHDih/2u323377rV27dkKIffv2hYWF3XrrrdXW\nqYaqYPfKK69s2LChc+fOaWlp8+fPnzdv3nPPPRcZGfndd99NmTJFkzoAAACu1rp1ayHEt99+\nW1lZuWXLFuXShPz8fGXtmjVrfvnlF6vVunLlymPHjg0bNsx5+2tq27Zt//79J02adPz4cavV\num7dug4dOvzwww83UI8QIi4uzsfH55NPPhk2bJhjYceOHXv37q1ctFBRUTFnzpz8/PxRo0ZZ\nrdYPP/xwwIABNRuk/1J1H7ukpKQNGza88sorc+bMcSzs0KHDp59+mpSUpFUpAAAAV4iNjZ06\ndaqSgfr06ZOZmTl69Ojk5OS1a9cKIZ599tm0tLQff/wxMDDwgw8+iI+PF0I4af/kk08q9z1W\ndsjFx8d/9dVXd911V0ZGxvPPPx8fH19RUdGuXbtVq1b16NHjBupRDBs2bNmyZVcch83MzJw4\ncWJMTExZWVl0dPSuXbuioqJatWoVFBT0yiuvaDVcah8plpSUlJSUVFBQcPbsWR8fn/Dw8Gue\ndQcAAOCSax4t3bdvn+P1jBkzZsyY4fiz6oWbYWFh27Ztu+K912tfXFx8RUuj0ajcqaR58+aO\nW9xdISEh4YrDstX2/8Ybb7zxxhvKa+WqWCFEaGjoJ598ckXnp0+fvmLJsmXLrlmGSmqDnSIg\nIMDf3z88PFw5rgwAAADvofZZsevWrYuOjm7cuHGHDh2U2zS//fbbc+fOdWdtAAAAcIGqYLdh\nw4bk5GS9Xj958mTHwvLy8hdffNHJ7fsAAADcx2KxpKSk1KSH4uLi3r17a1SOV1AV7GbNmjV0\n6NBff/216hHlyZMnP/300wsXLnRbbQAAAHCBqmB36NChMWPG+Pj4XLE8KSnpyJEjbqgKAAAA\nLlMV7Bo2bKjT6a5eXlZW1qBBA61LAgAAwI1QFeyio6MXLlxYWVlZdWFJScmsWbPi4uLcUxgA\nAABco+p2J1OmTOnfv39sbOygQYOEEKtWrVq1atWaNWsuXLiwdetWN1cIAAAAVVQFu/vvv//z\nzz+fPHnyrFmzhBCLFy8WQnTu3DkjI+Pee+91b4EAAMCj7rmvradLgFpqb1Dcr1+/fv36nTt3\n7syZM0KIli1b3nzzze4sDAAAAK5RFexOnTrleN2sWTMhhNlsdiyMiIjQvCwAAOAlLNMnadib\nYdp8DXvDFVQFu9atWztZe8UD1LyN8gy42u/QZrMp/6thAXa7XfOP45xjc9V+y+o/qdKVNCOj\nhvry1DRjSteEO6a0q5tWQ8OR8ewXp/mUlmZkquVqeV7+32LUGlXBbt68eY7XP//887lz5wYP\nHuy2krRks9mufuJvDansUPmnWFpaWl5ertWmXfo4jbTYomNzFRUVTppZLJby8nKVtSm/Vh4c\nGU2o35zdbldfXmlpqfMG9XZKazKfhStTuqysTNuhdqk3Db9o5YsrKyvT6ovz7JTWfGS89rdI\n+alU/8U5n9KoP1QFuxdeeMHxeu/evSNGjKi6xJvp9fqgoKB//sjTps//duiU2Ww2m82NGjXS\n6lZ/Fy5c8PHxUbl1IYRFi406Nufn5+ekmcFgaNiwoadGxmQyuTIyf2myUfVfhEtfnK+vr/MG\n9XZKazKfhStTOiAg4J/GtTvOwuUpXQ3liwsICPDIF+falK6OO0bGc79F1SgtLS0pKVH/xTmf\n0qg/VN3HrqqIiIicnJz8/Hx3VAMAAIAb5nKwUyJdQUGBG4oBAADAjVN1KHb48OHKC6vV+t13\n3xmNxrZtuaUNAACAd1EV7LZv36688PHxad269fTp0xs3buzOqgAAAOAyVcHOZDK5uw4AAFA/\n9ezZ8/vvv1deG43GiIiIxx9/vK5cpultXD7HDgAAQFupqal5eXl5eXn79u3717/+lZaWtmLF\nCk8XVSepCnYxTrm7RAAAILeAgIAWLVq0aNGiffv2EydObNOmzcGDB5VVJpNp1KhR4eHhwcHB\nd955544dOxzvWrlypV6vNxqNRqNRr9cvWrRIWW4wGNauXSuEyM/Pb9iw4datW4UQOTk5AwcO\nbN68eWBgYI8ePX766ada/5S1QVWwO3DgwP79+3U6XatWrVpcxd0lAgCAesJms23atCkvL8/x\nKISUlJSTJ0/+8MMPBQUFKSkpffv2zc3NVVadOHEiLi6uuLi4uLg4NDT06t5ee+21xMTE+++/\nXwiRmprq6+t79OjRc+fOdenSZfDgwbX85Jvaoeocu717906ePPnbb79NSEiYMWNG8+bN3V0W\nAACoP1avXr1+/XohRElJia+v71tvvdWrVy8hxKFDh3bt2vXzzz+Hh4cLISZNmrRkyZIVK1a8\n/vrrQoijR49GRUVdr8/Dhw+vXr06Oztb+fPrr7/28/MLDAwUQowZM2bx4sWnTp1q06ZNLXy6\n2qRqj11sbOyOHTs2bty4e/fu22+/fc6cORo+gAUAANRzSUlJ2dnZ2dnZBw8ezMjImDNnzoQJ\nE4QQx48fF0J07NjR0TIqKsqxx27//v133HHHNTs0m81jx46dPHlyu3btlCVHjhxJTk4ODQ29\n5ZZbEhMThYpH3tVFLlw8MWDAgP379y9YsOCdd96JjIz8+OOP3VcWAACoP5SLYSMiIiIjI1NT\nUxcsWPD222+fOXPm6pZ2u72srEwIUVRUdPTo0djY2Gt2OH78+H379sXFxSl/nj59ul+/frGx\nsTk5OQUFBd98843bPoqHuXZVrF6vHz169LFjx8aMGfPUU0917959z549bqoMAADUZ0VFRcoD\nEQ4cOKAssdvtv/32m7ITbuvWrf7+/t26dbvme9PT0+fOnTtu3LjCwkIhxN69e81m80svvWQ0\nGoUQEqcXVefYJSQkVP1Tr9f7+/tHRUX9+OOPd955p91ud09tAACgXjCbzcozSy0Wy7Fjx6ZM\nmZKQkBAVFaXT6Xr37p2WlrZmzZqgoKC33norPz9/1KhRQoilS5cOGDDA39//en0+88wzWVlZ\nEyZMyMjIaN26tRDi22+/7du37/bt29esWSOEyM/Pj46OrqVPWFtUBburR81ms/n7+ysnNgIA\nANTEmjVrlLBlMBhCQkKSkpKmT5+u0+mEEJmZmRMnToyJiSkrK4uOjt61a1dUVNQdd9xx4MCB\nBg0aKHvghBBms3nSpEmXLl2aMmWKskSv1y9dujQ2NjY5OTkpKWnq1KmjRo2yWq19+vTJzMwc\nPXp0cnLy2rVr+/fv76lP7Q6qgp3Eh6IBAIBn7d6928na0NDQTz755IqFJSUlWVlZjmfZKwYO\nHFhRUSGEsFgsypLo6GjH5Z4zZsyYMWOGo/GGDRtqXrkX4skTAAAAktBgj13v3r01KQUAAAA1\noSrY3XPPPU7WcvEEAACoTcr97a6wefPm2q/E26gKdkKIefPmRUREuLMSAAAA1IjaYJeYmBgT\nE+PWUgAAAFATXDwBAAAgCbV77Hbs2GGz2dq0aRMUFOTWggAAAHBj1Aa7SZMmKS+aN2/eoUOH\nLl269OzZs3///gEBAW6rDQAAeJ5h2nxPlwC1VAW7EydOnDx5Mjc398SJEydOnMjJyVmyZMnC\nhQubN2+enp4+YMAAd1cJAACAaqkKdq1bt27duvW9997rWFJZWfnjjz9OmzZt/Pjxp06dcld1\nAAAAUO0GL57w9fW9++67Z86c6ePjo21BAAAAuDFqz7FTnD59+uzZs3q9PiwsrEWLFj179szN\nzXVTZQAAAHCJ2j12S5cubdmyZURERPfu3RMSEsLDw9u3b79u3Tq3FgcAAAD1VO2xy8zMfOqp\np2JiYkaMGBESEmKz2c6cObNp06bk5OTNmzdz8QQAAIA3UBXsFixYMHLkyPT0dJ1O51g4e/bs\nhx56aNasWQQ7AAAAb6DqUOxvv/326KOPVk11Qgi9Xv/YY49lZ2e7pzAAAAC4Ru05dlar9Rpv\n1uttNpum9QAAAOAGqQp2nTp1WrRo0RXZzmKxLF++vEuXLu4pDAAAAK5RdY5dWlragw8+2LFj\nx0GDBoWFhdnt9ry8vE2bNuXm5m7atMndJQIAAEANVcFu6NChWVlZL7/88ptvvulYGBUVtW7d\nugceeMBttQEAAMAFam9QPHz48OHDhys3KNbpdOHh4WFhYUKI/Pz8Fi1auLNCAAAAqOLsHLvH\nHnvs77//rrqkVatWd955Z0JCQlhYmNVqXbhwYVRUlJsrBAAAgCrOgt3atWs7dOjw6aefXr3q\nl19+iY+Pf/7550NDQ91WGwAAAFzgLNjt378/MjIyJSVl2LBhJpNJWXj58uWJEyd269bt6NGj\ns2bNOnjwYK3UCQAAgGo4O8euXbt2O3fuXLZs2eTJk6Ojoz/66KPCwsJnn302Pz9/2LBh8+fP\n5+w6AAAA71HNfex0Ot2YMWMOHz7cqVOnPn36DB06NCgoaOfOnR+PrHCqAAASMElEQVR//DGp\nDgAAwKuouio2LCzsq6++Gjhw4IkTJ7Kzsw0GtdfSAqi3dm47pq7heeer77mvbc2LQZ3w1qE9\nqtrlVbP+f6ITal4MUEc5i2i///571T/79Omzffv2Y8eOXfHQ2MjISLeUBgAAAFc4C3bXvJVJ\nhw4drlhit9u1rAgAAAA3xFmwe/nll2utDgAAANSQs2D3+uuv11odAAAAqKFqrooFAABAXUGw\nAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQ\nBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4A\nAEASBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIE\nOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAA\nSRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwA\nAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRB\nsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAA\nkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQBMEO\nAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJCEwdMF3IjK\nyspdu3bZbLYePXo0atTI0+UAAAB4hboX7MrKytLS0i5cuFBWVvbxxx/Pnj27efPmjrULFy7c\nuHGj8tpgMDRo0ODChQvaFqCyQ7vdLoS4fPmyVtu12+0Wi0X9xwnSYqOOzZWWljppVllZWVxc\n7NJQX7p0SafT1ai4KlwaGU2o35zdbrdarSrbOx9nIYT6rtTz1JRWSSlPk/ks3Dml1W9aDQ2n\ntDt+i7Sa0i51pZ4Hp7Tmv0Xqy6v21wP1RN0LditWrLjtttveeuutsrKyWbNmZWVlPffcc461\n/v7+gYGBymsfH5/Kykq9XuPDzSo7tNlsdrtdp9NpFV9sNpv6rWvFsTnnn0L5mCprs9vtdrtd\nr9drNTJWq1V4bmSq5VJ51TZTP87qeWpKq6Tt53XHlHZ109XSdkpr/sVpOKXdMc7VbtTBHSOj\n4cdRfirVl1fL/zDhtepYsDObzd98883y5cv1en1AQMDjjz8+derUZ599VpnQdrv96aeffvrp\np5XGlZWVKSkpTZo0+efNZ7Sp4b8dVleq2Ww2Go0NGjTQZLsXLlzw8fEJDg5W2d6ixUYdH9bf\n399JM4PB0KhRI0+NjMlkMhgMqkfGpMlGVX5Y4eIX5+fn57yBXq+vO1Nay6HWZD6LG5vStTvO\nwuUpXQ3P/hbJNaWrYTKZXPqVdq60tLSkpER9ec6nNOqPOnbxxJ9//qlEOuXPtm3b6vX6s2fP\nKn9u3bp1xYoVnqsOAADAk+pYsAsJCdHr9X/99ZdjScuWLfPy8oQQZrN59erVvXv39lhxAAAA\nHlXHgl3Dhg0XL1586623Opa0aNHi1KlTQoiPPvqoW7durVu39lhxAAAAHlVngp3NZjt8+PDe\nvXstlv9zsk1kZOTBgwfPnj27c+fOESNGeKo8AAAAj6sbF09UVFS88sorp0+f1ul0paWlnTt3\nfuSRR6KiooQQXbp0Wbx48dy5c1NTUxs3buzpSgEAADymbuyxW758eWhoaGZmZlZW1uuvvy6E\nSEtLe//9961W60033ZSYmFhRUfHAAw94ukwAAABPqgN77CwWy9dff7106VKDwSCE6NSpU6dO\nnX744YdFixZdunRp8uTJ48aNUy4y93SlAAAAnlQH9thV/H9VF3bv3n3OnDn79u3bu3evXq+/\n+eabPVUeAACAl6gDwS4gIOCOO+5YuHDhFc9LCQ8PT0xMPHz4sKcKAwAA8Cp1INgJISZMmHD+\n/PkJEybs37+/6vKioqKbbrrJU1UBAAB4lboR7Jo1azZ//vyIiIipU6e+9tprP/3009mzZzdu\n3HjkyBHuSAwAAKCoAxdPKIKCgqZMmXLgwIH169fPmTPHYrG0atXq1VdfDQwM9HRpAAAAXqHO\nBLvPP//cz88vMTGxc+fOVqu1vLzc8cRYAAAACC8/FJuRkbFv3z4hRFFRUVZWVvv27ZXlPj4+\npDoAAIArePUeu7CwsLfffvv222/38/Pr1atXeHi4pysCAADwXl69xy4xMXHJkiWNGjX6/vvv\nKyoqSkpKPF0RAACA9/LqYCeECAgIMJlMDz300MWLF8eOHbtjxw5PVwQAAOClvPpQrBBi9+7d\nJSUlDz/8sF6vz87OLiws9HRFAAAAXsrbg91ff/01ZswYvV4vhIiJifF0OQAAAN7LS4NdYWHh\nnj17fHx87rvvPu5UBwAAoIY3nmN3/Pjx8ePHf/nllxkZGU888UR+fr6nKwIAAKgDvG6Pnd1u\nnz9//tixY3v16rV+/frs7OwWLVoIIS5dutS4cWNPVwcAAOC9vG6P3cGDB/39/Xv16lVUVLR2\n7donn3xSCLFt27Zly5Z5ujQAAACv5nXBzmQyGQwGIcSqVat69+6t7K7z8/MrKirydGkAAABe\nzeuCXefOnU+ePJmenv7TTz89/PDDysLDhw936tTJs4UBAAB4Oa8Lds2aNRs3btz69esbNmz4\n66+//vHHH5s2bdqzZ0/fvn09XRoAAIBX8/zFE0VFRTabrUmTJo4lffr0adWqVUZGxrx58+x2\ne/PmzadMmcJNTwAAAJzzfLDLysrasWNHamrqkCFDfH19lYW33377zJkzL1++fOnSpZCQEOUG\nxQAAAHDC84EpICCgQ4cOa9euHT9+/I8//lh1ldFoDAsLI9UBAACo4fnMFBkZGRMTs2TJkujo\n6NmzZ7/88sunTp1SVm3btm3p0qUerQ4AAKDO8Hywa9++/d9//92kSZMJEybMnz+/srJy4sSJ\n77333p9//pmZmdmnTx9PFwgAAFA3eP4cu6CgIMdtTW6//fa5c+fu2rUrIyPjyy+/vP/++2+7\n7TbPlgcAAFBXeH6PnRCiYcOGVf/s1avX1KlTGzZsOGLECE+VBAAAUOd4RbC72qpVq4YPHx4U\nFOTpQgAAAOoMbwx2hYWFJSUlgwYN8nQhAAAAdYnnz7G7WnBw8OzZsz1dBQAAQB3jjXvsAAAA\ncAMIdgAAAJIg2AEAAEiCYAcAACAJgh0AAIAkCHYAAACSINgBAABIgmAHAAAgCYIdAACAJAh2\nAAAAkiDYAQAASIJgBwAAIAmCHQAAgCQIdgAAAJIg2AEAAEiCYAcAACAJgh0AAIAkCHYAAACS\nINgBAABIgmAHAAAgCYIdAACAJAh2AAAAkiDYAQAASIJgBwAAIAmCHQAAgCQIdgAAAJIg2AEA\nAEiCYAcAACAJgh0AAIAkCHYAAACSINgBAABIgmAHAAAgCYIdAACAJAh2AAAAkiDYAQAASIJg\nBwAAIAmCHQAAgCQIdgAAAJIg2AEAAEiCYAcAACAJgh0AAIAkCHYAAACSINgBAABIgmAHAAAg\nCYIdAACAJAh2AAAAkiDYAQAASIJgBwAAIAmCHQAAgCQIdgAAAJIg2AEAAEiCYAcAACAJgh0A\nAIAkCHYAAACSINgBAABIgmAHAAAgCYIdAACAJAh2AAAAkiDYAQAASIJgBwAAIAmCHQAAgCQI\ndgAAAJIg2AEAAEiCYAcAACAJgh0AAIAkCHYAAACSINgBAABIgmAHAAAgCYIdAACAJAh2AAAA\nkiDYAQAASIJgBwAAIAmCHQAAgCQIdgAAAJIg2AEAAEiCYAcAACAJgh0AAIAkCHYAAACSINgB\nAABIgmAHAAAgCYIdAACAJAh2AAAAkiDYAQAASIJgBwAAIAmCHQAAgCQIdgAAAJIg2AEAAEiC\nYAcAACAJgh0AAIAkDJ4uwL1sNtvFixe17VNlhzabTQhRXFys0+m02rTValX/cQK12KJjc2Vl\nZU6aWSyWkpISlbXZ7Xah9chYLBbNv2jn1G/Obrer/+JKS0udN5BsSquhlKfJfBbumdKubloN\nDae05l8cU9oJl36lnXP1p9L5lEb9IXmw0+v1TZo0+eePM9r0+d8OnTKbzWaz2Wg0NmjQQJPt\nXrhwwcfHJzg4WGV7ixYbdXxYf39/J80MBkOjRo08NTImk8lgMKgeGZMmG1X5YYWLX5yfn5/z\nBnVqSms51JrMZ3FjU7p2x1m4PKWr4dnfIrmmdDVMJpNLv9LOlZaWlpSUqC/P+ZRG/cGhWAAA\nAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDs\nAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAk\nQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMA\nAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATB\nDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJGDxdQO35n+gE5w1MJpPBYAgO\nDq6detzNMG2+k7WlpaUlJSWBgYF+fn61VpI3uOe+ts4bKCPTuHHjBg0a1E5JN0zNlPb19Q0K\nCqqdeq5Q7VBfuHDBx8dH5b845/NZuHNKVzvOZrPZbDYHBQX5+vpqu+n6xsunNFAnsMcOAABA\nEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsA\nAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ\n7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAA\nJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJCEwdMFuJfJZBo/frzKxpWVlTqdzmDQ\nZkysVqvNZvPx8dHrtUnP2pZns9msVqv68vLy8pw3yMjI+Pzzz9V0JdnIVMul8mw2m/MGTOnr\n0XxKp6enb968WU1XysgYDAadTqemfbVk+uKqndLnz59nSl+T5lMa9YTkwa68vPznn3/2dBWS\n8Pf3v/nmm6+39sSJEydOnKjNeiTWqlWr661iSmuIKV1rmNK1w/mURj2hs9vtnq7BjS5duqSy\npd1u79OnT8eOHd955x1NNv3hhx+uWLFi1qxZCQkJmnTYr1+/li1bfvDBB5r09tFHH33wwQfT\np0+/6667VL7Fz8/Pz8/vmqvKy8vLy8tV9pORkZGRkTFnzpyuXbuqfItziYmJbdu2fe+99zTp\nbfXq1cuWLZs5c2aPHj006XDAgAGhoaHLli1T/5bAwMDr7ftRP6VtNltiYiJT2gmtpnR6evrK\nlSvnzp0bFxen8i3OJSYmtmvX7t1339Wkt8zMzOXLl7/++uvdu3fXpMP+/fuHhYVJMKVXrlyZ\nnp7+xhtvdOvWTZMO+/btGxER8f7772vSmzKlX3vttbvvvlvlW5xMadQfku+xa9y4scqWSsD1\n8fFR/xbnlH9dAQEBWnUoNC3P399fCNGwYUNNOnTp18TLR0bz8nQ6nV6v16o39f0oh8C8eWQE\nU/r6vPmL0+l0GpbHlL4eZUprWx7qAy6eAAAAkITke+xcEh8ff9ttt2nVW1hYWHx8fHBwsFYd\nxsXFhYSEaNVbaGhofHx8kyZNtOpQPWVkgoKCtOowPj6+ZcuWWvWmlKfhyMTFxTVr1kyr3tTT\n6XRM6dqh+ZTu2rWrk5PSXOWOL84jJ3J5/5Tu2rVraGioVr2FhITEx8c3bdpUqw5RT0h+jh0A\nAED9waFYAAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEAS\nBDsAAABJEOwAAAAkQbADAACQBMEOAABAEgQ7AAAASRDsAAAAJEGwAwAAkATBDgAAQBIEOwAA\nAEn8P0ZMwxQwY2yTAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(microbiology, aes(group, value, fill = group)) +\n",
    "    geom_bar(stat = \"identity\") +\n",
    "    scale_y_log10() +\n",
    "    scale_x_discrete() +\n",
    "    scale_fill_brewer(palette = \"Set3\",\n",
    "                      name = x_label,\n",
    "                      labels = group_labels) +\n",
    "    theme_bw() +\n",
    "    theme(axis.text.x = element_blank(),\n",
    "          axis.text.y = element_text(angle = 60, hjust = 1)) +\n",
    "    labs(title = title,\n",
    "         x = element_blank(),\n",
    "         y = y_label) +\n",
    "    facet_wrap(~ bacteria, ncol = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Transformation introduced infinite values in continuous y-axis”Warning message:\n",
      "“Removed 12 rows containing missing values (geom_bar).”"
     ]
    }
   ],
   "source": [
    "ggsave(\"microbiology.png\", scale = 1, width = 25, height = 10, units = \"cm\", dpi = 300)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}