Bar charts in jupyter.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1b96ef2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "21fc451c",
   "metadata": {},
   "outputs": [],
   "source": [
    "counties = ['Kilifi', 'Kwale', 'Lamu']\n",
    "prevalence = [11.6, 11.3, 9.5]\n",
    "severity = [70.6, 60.5, 56.7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "733f56a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zbt68acqWLWtKlixpbUst8P/X3b7vGmNMhQoVTKNGjVKM3a5duxTvMXBuTOlBtlW3bl25ubnJ29tb7dq1U2BgoFavXq2AgACbfv89O8bKlSuVN29etW/fXjdv3rTeqlatqsDAQOvX/q6ururZs6eWLl2qmJgYSbfmXM+fP18dOnRQgQIFrGPu2rVLjz76qAoUKCAXFxe5ubmpV69eSkxM1P79+9Pch5UrV8pisahnz542tQQGBqpKlSopztAQGBio2rVr27RVrlzZ5ivd1atXq3Tp0mrevPltt5uexyAtV65c0ciRI1WyZEm5urrK1dVVuXPn1tWrV7V3794U/R999NEUNUv/N/3qxx9/lKQUc627dOkiV9f0/ZTo9ddfV1RUlD7//HMNHDhQuXPn1qxZs1SjRg0tWrRIknT9+nVt2LBBjz32mDw9PW32vU2bNrp+/bq2bdsmSWrdurUCAwM1e/Zs6zbWrl2rkydP2kwnWblypZo0aaLg4GCb8Vq3bi1JioiISPFYuLm5pWuf0jJkyBDt3r1bP//8s6RbU2Pmz5+v3r17K3fu3GmuV7JkSeXLl08jR47UrFmz9Ndff6Xos3r1aknS4MGD0xwn+e/13x/61a5dW+XKldOGDRts2vPly6emTZvatK1cuVIVK1ZU1apVbR63Vq1a2Uy/qVWrlqRbz4Wvvvrqrs/EtXHjRnl5eenxxx+3aU/el//W3rRpU+XLl++utvlvEyZMkCS9+OKL8vX1Tdc6tWvX1pw5czRp0iRt27Yt1amCQ4YM0ZkzZ/T1119LujUlY+bMmWrbtm2KM4NVrVrVZhpRuXLlJN2a2vLv31Ykt/93yoiU8rWa/GPk5OfG7WzcuFHNmjVT4cKFbdr79Omja9eu6ZdffrFpb9eunc395Lratm2bov3ChQs203oy+t58O6tXr1aTJk2sddirWbNmNv+fcnFx0ZNPPqmDBw+mmBL3b45+372d2rVr63//+58GDRqktWvXKjY2Nr27h/sUgR/Z1rx58xQZGaldu3bp5MmT+v3339WgQQObPp6ensqTJ49N2+nTp3Xp0iXlzJlTbm5uNrfo6GidO3fO2rdfv366fv26dX7l2rVrderUKfXt29faJyoqSg8//LBOnDihd999Vz/99JMiIyOtc8Lj4uLS3IfTp0/LGKOAgIAUtWzbts2mFkk2HzKSubu722zj7NmzdzyjhD2PQWq6d++uGTNmqH///lq7dq1+++03RUZGys/PL9X9/W/d7u7ukv7vsUmegx8YGGjTz9XVNdV9TktAQID69u2rWbNm6ffff1dERIRy5sypIUOGWLdz8+ZNvf/++yn2u02bNpJk3XdXV1c99dRTWrZsmfXUmHPmzFFQUJBatWpl3ebp06f13XffpRgveS79fx/LtH5nYI8OHTqoWLFi1ufYnDlzdPXq1duGdEny8fFRRESEqlatqldffVUVKlRQcHCwxo0bZw2RZ8+elYuLS4q/xb/d7jcTwcHB1uXJUut3+vRp/f777ykeN29vbxljrI9bw4YNtXz5ct28eVO9evVSoUKFVLFiReuHOHudP39egYGBNnO0Jcnf31+urq7pqv1uJD/3c+bMme51vvzyS/Xu3Vuffvqp6tWrp/z586tXr16Kjo629qlWrZoefvhh63Ni5cqVOnLkiJ5//vkU4/33bEXJtaTVnjz/P1lqr8vk58t/H7/UnD9/Ps3nTmpjZLTeu3lvvp30vMfeTmqvrfQ8fo5+372d0aNH66233tK2bdvUunVrFShQQM2aNUvxmw44D87Sg2yrXLly1rP0pOW//1OXZP0B05o1a1Jdx9vb2/rv8uXLq3bt2po9e7YGDhyo2bNnKzg4WC1btrT2Wb58ua5evaqlS5eqaNGi1vbdu3ffcR98fX1lsVj0008/Wd+M/y21tjvx8/O77VGi5O2m9zH4r5iYGK1cuVLjxo3TqFGjrO3x8fG6cOGC3fVK//c/pujoaJsjjzdv3kxXgEhLw4YN1bJlSy1fvlxnzpxRvnz55OLioqeeeirNcBwSEmL9d9++ffXmm29q8eLFevLJJ7VixQoNHTpULi4u1j6+vr6qXLmyJk+enOp4ySEmWWrPSXvlyJFDgwcP1quvvqq3335bH374oZo1a6YyZcrccd1KlSpp8eLFMsbo999/15w5czRhwgR5eHho1KhR8vPzU2JioqKjo9MMu8l/r1OnTqUIPidPnkxx5Dqt16GHh4c+//zzVLfx7zE6dOigDh06KD4+Xtu2bdOUKVPUvXt3FStWTPXq1bvjPv+39l9//VXGGJu6zpw5o5s3b6ar9nvN19dX06dP1/Tp0xUVFaUVK1Zo1KhROnPmjM1r+MUXX9QTTzyhnTt3asaMGSpdurRatGjh8HqSX5f/DpTJHz7S8wG9QIECOnXqVIr25B+Upvebjzu5m/fm20nPe+zt/PuD2n/b0nr8MuN993ZcXV01fPhwDR8+XJcuXdIPP/ygV199Va1atdKxY8c4250T4gg/nE67du10/vx5JSYmqmbNmilu/w1Nffv21a+//qotW7bou+++U+/evW0CX3Ig+Hc4N8bok08+SVctxhidOHEi1VoqVapk9/61bt1a+/fv18aNG2+7XXseg3+zWCwyxqT4MPLpp58qMTHR7nolWc/esWDBApv2r776yuZMN2k5ffp0qmdTSkxM1IEDB+Tp6am8efPK09NTTZo00a5du1S5cuVU9/3f/8MtV66c6tSpo9mzZ2vhwoWKj4+3+XZHuvVYJp/+MbXx/hv40+tOR+P69++vnDlzqkePHtq3b1+qR3Jvx2KxqEqVKnrnnXeUN29e7dy5U5KsU5FmzpyZ5rrJ03O++OILm/bIyEjt3bvXejas22nXrp0OHTqkAgUKpPq4pXaBOnd3dzVq1EhTp06VdGu6hr2aNWumK1eupLgg1Lx586zLs7MiRYro+eefV4sWLax/s2SPPfaYihQpopdeekk//PCDBg0alGkfWP77Wl24cKEk2ZyJ57/fPiZr1qyZNm7cmOJMXfPmzZOnp6fDToNpz3tzWrWmpnXr1vrxxx+1b9++DNW1YcMGm7P5JCYm6ssvv1SJEiXS/OYgM953pfTtd968efX4449r8ODBunDhgo4cOZLh7SH74gg/nE7Xrl21YMECtWnTRkOGDFHt2rXl5uam48eP68cff1SHDh302GOPWft369ZNw4cPV7du3RQfH59i3nKLFi2UM2dOdevWTSNGjND169c1c+ZMXbx48Y61NGjQQAMGDFDfvn21fft2NWzYUF5eXjp16pS2bNmiSpUq6bnnnrNr/4YOHaovv/xSHTp00KhRo1S7dm3FxcUpIiJC7dq1U5MmTex+DP4tT548atiwod588035+vqqWLFiioiI0GeffZbhC0SVK1dOPXv21PTp0+Xm5qbmzZvrzz//1FtvvZViSlZq5s+fr48++kjdu3dXrVq15OPjo+PHj+vTTz/Vnj17NHbsWOvX/e+++64eeughPfzww3ruuedUrFgxXb58WQcPHtR3332X4oNSv379NHDgQJ08eVL169dP8WFowoQJWr9+verXr68XX3xRZcqU0fXr13XkyBGtWrVKs2bNytDX/8kf9t5991317t1bbm5uKlOmjPXbl7x586pXr16aOXOmihYtqvbt299xzJUrV+rDDz9Ux44dVbx4cRljtHTpUl26dMl6JPjhhx/WU089pUmTJun06dNq166d3N3dtWvXLnl6euqFF15QmTJlNGDAAL3//vvKkSOHWrdurSNHjuj1119X4cKFNWzYsDvWMnToUC1ZskQNGzbUsGHDVLlyZSUlJSkqKkrr1q3TSy+9pDp16mjs2LE6fvy4mjVrpkKFCunSpUt699135ebmpkaNGtn9uPbq1UsffPCBevfurSNHjqhSpUrasmWLwsLC1KZNm9v+9iU9YmNj9c0336Ro9/Pzy1C9MTExatKkibp3766yZcvK29tbkZGRWrNmjTp16mTT18XFRYMHD9bIkSPl5eWVaRdTypkzp95++21duXJFtWrV0tatWzVp0iS1bt1aDz30kLVfpUqVtGnTJn333XcKCgqSt7e3ypQpo3Hjxll/+zJ27Fjlz59fCxYs0Pfff69p06bJx8fHIXXa895cqVIlLV26VDNnzlSNGjWUI0eONL9BnjBhglavXq2GDRvq1VdfVaVKlXTp0iWtWbNGw4cPV9myZW9bl6+vr5o2barXX39dXl5e+vDDD/X333/f9tScmfG+m7zfixcv1pdffqnixYsrV65cqlSpktq3b2+91o2fn5+OHj2q6dOnq2jRoipVqlSGt4dsLKt+LQykJa3Tcv5X7969jZeXV6rLbty4Yd566y1TpUoVkytXLpM7d25TtmxZM3DgQHPgwIEU/bt3724kmQYNGqQ63nfffWcdq2DBguaVV14xq1evTnGWhdROy2mMMZ9//rmpU6eO8fLyMh4eHqZEiRKmV69eZvv27dY+aZ0BJLUxL168aIYMGWKKFCli3NzcjL+/v2nbtq35+++/M/wY/Nvx48dN586dTb58+Yy3t7d55JFHzJ9//mmKFi1qc1aOtP5WqZ2BIj4+3rz00kvG39/f5MqVy9StW9f88ssvKcZMzV9//WVeeuklU7NmTePn52dcXV1Nvnz5TKNGjcz8+fNT9D98+LDp16+fKViwoHFzczN+fn6mfv36ZtKkSSn6xsTEGA8Pj1RPhZns7Nmz5sUXXzQhISHGzc3N5M+f39SoUcOMGTPGXLlyxbpNSebNN99MtR795yw9xhgzevRoExwcbHLkyJHqGTs2bdpkJJk33njjto9Psr///tt069bNlChRwnh4eBgfHx9Tu3ZtM2fOHJt+iYmJ5p133jEVK1Y0OXPmND4+PqZevXrmu+++s+kzdepUU7p0aePm5mZ8fX1Nz549zbFjx2zGut2Za65cuWJee+01U6ZMGet2KlWqZIYNG2Y9i8nKlStN69atTcGCBU3OnDmNv7+/adOmjfnpp5/uuL9pbfv8+fPm2WefNUFBQcbV1dUULVrUjB492ly/ft2mnyQzePDgO27n39vT/z9L1H9vyWdCud3zIDXXr183zz77rKlcubLJkyeP8fDwMGXKlDHjxo2zOaNOsiNHjhhJ5tlnn011vKJFi5q2bdumaE9tX1OrNfl99ffffzeNGzc2Hh4eJn/+/Oa5556zPteT7d692zRo0MB4enraPAbGGPPHH3+Y9u3bGx8fH5MzZ05TpUqVFM//5PeJf5+u0pi031fGjRtnJNmc/Si9780XLlwwjz/+uMmbN6+xWCzm3/FH/zlLjzG3zqTWr18/ExgYaNzc3ExwcLDp0qWLOX36dIrH9t+SH+cPP/zQlChRwri5uZmyZcuaBQsWpLrv/64xM953jxw5Ylq2bGm8vb2tp0A1xpi3337b1K9f3/j6+lpPw/r000+bI0eO3Hb/cP+yGGNMpn+qAADY7aWXXtLMmTN17Ngxu37cDOf1/vvv68UXX9Sff/55x4uwZUSfPn30zTffpLjAFdLHYrFo8ODBmjFjRlaXAthgSg8AZDPbtm3T/v379eGHH2rgwIGEfWjXrl06fPiwJkyYoA4dOmRK2AfgvAj8AJDN1KtXT56enmrXrp0mTZqU1eUgG3jssccUHR2thx9+WLNmzcrqcgDcZ5jSAwAAADixLD0t5+XLlzV06FAVLVpUHh4eql+/viIjI63LjTEKDQ1VcHCwPDw81LhxY+3ZsycLKwYAAADuL1ka+Pv376/169dr/vz5+uOPP9SyZUs1b97cemn1adOmKTw8XDNmzFBkZKQCAwPVokULXb58OSvLBgAAAO4bWTalJy4uTt7e3vr222/Vtm1ba3vVqlXVrl07TZw4UcHBwRo6dKhGjhwp6dYV5wICAjR16lQNHDgwK8oGAAAA7itZ9qPdmzdvKjExUbly5bJp9/Dw0JYtW3T48GFFR0erZcuW1mXJV2HcunVrmoE/Pj5e8fHx1vtJSUm6cOGCChQokC0uoQ4AAAA4gjFGly9fVnBwsHLkSHviTpYFfm9vb9WrV08TJ05UuXLlFBAQoEWLFunXX39VqVKlFB0dLUkKCAiwWS8gIEBHjx5Nc9wpU6Zo/PjxmVo7AAAAkF0cO3bstld9z9LTcs6fP1/9+vVTwYIF5eLiourVq6t79+7auXOntc9/j8obY257pH706NEaPny49X5MTIyKFCmiY8eOKU+ePI7fCQAAACALxMbGqnDhwvL29r5tvywN/CVKlFBERISuXr2q2NhYBQUF6cknn1RISIgCAwMlSdHR0QoKCrKuc+bMmRRH/f/N3d1d7u7uKdrz5MlD4AcAAIDTudO09Sw9S08yLy8vBQUF6eLFi1q7dq06dOhgDf3r16+39ktISFBERITq16+fhdUCAAAA948sPcK/du1aGWNUpkwZHTx4UK+88orKlCmjvn37ymKxaOjQoQoLC1OpUqVUqlQphYWFydPTU927d8/KsgEAAID7RpYG/piYGI0ePVrHjx9X/vz51blzZ02ePFlubm6SpBEjRiguLk6DBg3SxYsXVadOHa1bt+6O85QAAAAA3JJl5+G/V2JjY+Xj46OYmBjm8AMAAIcyxlhPNQ44mouLi1xdXdOco5/enJulR/gBAADuVwkJCTp16pSuXbuW1aXAiXl6eiooKEg5c+bM8BgEfgAAADslJSXp8OHDcnFxUXBwsHLmzMkFPuFQxhglJCTo7NmzOnz4sEqVKnXbi2vdDoEfAADATgkJCUpKSlLhwoXl6emZ1eXASXl4eMjNzU1Hjx5VQkKCcuXKlaFxssVpOQEAAO5HGT3iCqSXI55jPEsBAAAAJ8aUHgAAAAeJiorSuXPn7tn2fH19VaRIkXu2PdyfCPwAAAAOEBUVpTJly+l63L07a08uD0/t+3uvU4T+Pn366NKlS1q+fHlWl3JHGzdu1KBBg/TXX39leMrNypUr9frrr2vHjh2ZPjWMwA8AAOAA586d0/W4ayrQ7iW5FSic6du7cf6Yzq98W+fOnUt34O/Tp4/mzp0rSXJ1dVXhwoXVqVMnjR8/Xl5eXplZrlMZMWKExowZYw3qu3btUr9+/XTgwAE1bdpUc+fOVb58+SRJN2/eVO3atfXRRx+pVq1a1jHatWunsWPHauHCherZs2em1kvgBwAAcCC3AoXlHlgyq8tI0yOPPKLZs2frxo0b+umnn9S/f39dvXpVM2fOTNH3xo0bcnNzy4Iqs6+tW7fqwIEDeuKJJ6xt/fv3V9OmTfXll1+qf//+CgsL05tvvilJeuutt/TQQw/ZhP1kffv21fvvv5/pgZ8f7QIAADxA3N3dFRgYqMKFC6t79+7q0aOHdRpNaGioqlatqs8//1zFixeXu7u7jDGKiYnRgAED5O/vrzx58qhp06b63//+J0nat2+fLBaL/v77b5vthIeHq1ixYjLGKDExUU8//bRCQkLk4eGhMmXK6N13371tncYYTZs2TcWLF5eHh4eqVKmib775xrp806ZNslgs2rBhg2rWrClPT0/Vr19f+/btsxlnxYoVqlmzpnLlyiVfX1916tTJuiwhIUEjRoxQwYIF5eXlpTp16mjTpk23rWvx4sVq2bKlzSky9+7dq2eeeUalS5dWt27d9Ndff0mS/vnnH33++eeaPHlyqmM9+uij+u233/TPP//cdpt3i8APAADwAPPw8NCNGzes9w8ePKivvvpKS5Ys0e7duyVJbdu2VXR0tFatWqUdO3aoevXqatasmS5cuKAyZcqoRo0aWrBggc24CxcuVPfu3WWxWJSUlKRChQrpq6++0l9//aWxY8fq1Vdf1VdffZVmXa+99ppmz56tmTNnas+ePRo2bJh69uypiIgIm35jxozR22+/re3bt8vV1VX9+vWzLvv+++/VqVMntW3bVrt27bJ+OEjWt29f/fzzz1q8eLF+//13PfHEE3rkkUd04MCBNOvavHmzzRiSVKVKFa1fv143b97Uhg0bVLlyZUnSs88+q2nTpsnb2zvVsYoWLSp/f3/99NNPaW7PEZjSAwAA8ID67bfftHDhQjVr1szalpCQoPnz58vPz0/SrR+o/vHHHzpz5ozc3d0l3Zqmsnz5cn3zzTcaMGCAevTooRkzZmjixImSpP3792vHjh2aN2+eJMnNzU3jx4+3biMkJERbt27VV199pS5duqSo6+rVqwoPD9fGjRtVr149SVLx4sW1ZcsWffTRR2rUqJG17+TJk633R40apbZt2+r69evKlSuXJk+erK5du9psu0qVKpKkQ4cOadGiRTp+/LiCg4MlSS+//LLWrFmj2bNnKywsLNXH7MiRI9b+yT799FMNGjRIb731lho0aKDRo0dr3rx58vT0VK1atdSqVSsdOnRIXbt21aRJk2zWLViwoI4cOZLqthyFwA8AAPAAWblypXLnzq2bN2/qxo0b6tChg95//33r8qJFi1rDviTt2LFDV65cUYECBWzGiYuL06FDhyRJXbt21SuvvKJt27apbt26WrBggapWrary5ctb+8+aNUuffvqpjh49qri4OCUkJKhq1aqp1vjXX3/p+vXratGihU17QkKCqlWrZtOWfDRdkoKCgiRJZ86cUZEiRbR7924988wzqW5j586dMsaodOnSNu3x8fEp9vW/+/3fK95WqFDB5puH8+fPKzQ0VJs3b9YLL7ygBg0aaOnSpapVq5bq1Kmj9u3bW/t6eHjo2rXMPbMTgR8AAOAB0qRJE82cOVNubm4KDg5O8aPc/56tJykpSUFBQanObc+bN6+kW0G7SZMmWrhwoerWratFixZp4MCB1n5fffWVhg0bprffflv16tWTt7e33nzzTf3666+p1piUlCTp1pScggUL2ixL/pYh2b/rt1gsNut7eHik9TAoKSlJLi4u2rFjh1xcXGyW5c6dO831fH19dfHixTSXS9KwYcM0dOhQFSpUSJs2bdKkSZPk5eWltm3batOmTTaB/8KFCzYfsDIDgR8AAOAB4uXlpZIl038WoerVqys6Olqurq4qVqxYmv169OihkSNHqlu3btbpK8l++ukn1a9fX4MGDbK2JX87kJry5cvL3d1dUVFRNtN37FW5cmVt2LBBffv2TbGsWrVqSkxM1JkzZ/Twww+ne8xq1apZf5Sbmg0bNujvv//WnDlzJEmJiYnW30j8+7cSknT9+nUdOnQoxbcWjkbgBwAAcKAb54851XaaN2+uevXqqWPHjpo6darKlCmjkydPatWqVerYsaP1B6ydOnXSc889p+eee05NmjSxOTJfsmRJzZs3T2vXrlVISIjmz5+vyMhIhYSEpLpNb29vvfzyyxo2bJiSkpL00EMPKTY2Vlu3blXu3LnVu3fvdNU+btw4NWvWTCVKlFDXrl118+ZNrV69WiNGjFDp0qXVo0cP9erVS2+//baqVaumc+fOaePGjapUqZLatGmT6pitWrWyXsvgv+Li4jR48GAtXrzYeo7+Bg0a6IMPPtDgwYO1ZMkShYeHW/tv27ZN7u7u1t8pZBYCPwAAgAP4+voql4enzq98+55tM5eHp3x9fTN1GxaLRatWrdKYMWPUr18/nT17VoGBgWrYsKECAgKs/fLkyaP27dvr66+/1ueff24zxrPPPqvdu3frySeflMViUbdu3TRo0CCtXr06ze1OnDhR/v7+mjJliv755x/lzZtX1atX16uvvpru2hs3bqyvv/5aEydO1BtvvKE8efKoYcOG1uWzZ8/WpEmT9NJLL+nEiRMqUKCA6tWrl2bYl6SePXtq5MiR2rdvn8qUKWOzbMKECWrXrp3NbxPee+89de/eXQ0bNlT37t3VuXNn67JFixapR48e8vT0TPc+ZYTFGGMydQtZLDY2Vj4+PoqJiVGePHmyuhwAAOAErl+/rsOHDyskJMTmB5xRUVE6d+7cPavD19c33VfZheOMGDFCMTEx+uijjzI8xtmzZ1W2bFlt3749zW86pLSfa1L6cy5H+AEAABykSJEiBPAHwJgxY/TBBx8oMTExxQ9+0+vw4cP68MMPbxv2HYXADwAAANjBx8fHrqlFqaldu7Zq167toIpujyvtAgAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxTssJAADgIFx4C9kRgR8AAMABoqKiVK5sGV2Lu37PtunpkUt7/97nNKHfYrFo2bJl6tixo8PH3rhxowYNGqS//vpLOXJkbJLLypUr9frrr2vHjh0ZHiMrEPgBAAAc4Ny5c7oWd11fPOahcn6ZHwb3nk1Sz2VxOnfuXLoD/5kzZ/T6669r9erVOn36tPLly6cqVaooNDRU9erVy+SK7+zUqVPKly+fJOnIkSMKCQnRrl27VLVq1bsee8SIERozZow1qO/atUv9+vXTgQMH1LRpU82dO9e67Zs3b6p27dr66KOPVKtWLesY7dq109ixY7Vw4UL17Nnzrmu6Vwj8AAAADlTOL4eqB7lkdRmp6ty5s27cuKG5c+eqePHiOn36tDZs2KALFy5kaV0JCQnKmTOnAgMDM2X8rVu36sCBA3riiSesbf3791fTpk315Zdfqn///goLC9Obb74pSXrrrbf00EMP2YT9ZH379tX7779/XwX+++e7CAAAAGTYpUuXtGXLFk2dOlVNmjRR0aJFVbt2bY0ePVpt27a19ouJidGAAQPk7++vPHnyqGnTpvrf//4nSdq3b58sFov+/vtvm7HDw8NVrFgxGWMkSX/99ZfatGmj3LlzKyAgQE899ZTNbxsaN26s559/XsOHD5evr69atGgh6daUnuXLl0uSQkJCJEnVqlWTxWJR48aNtXnzZrm5uSk6Otpm+y+99JIaNmyY5r4vXrxYLVu2VK5cuaxte/fu1TPPPKPSpUurW7du+uuvvyRJ//zzjz7//HNNnjw51bEeffRR/fbbb/rnn3/SfrCzGQI/AADAAyB37tzKnTu3li9frvj4+FT7GGPUtm1bRUdHa9WqVdqxY4eqV6+uZs2a6cKFCypTpoxq1KihBQsW2Ky3cOFCde/eXRaLRadOnVKjRo1UtWpVbd++XWvWrNHp06fVpUsXm3Xmzp0rV1dX/fzzz/roo49S1PLbb79Jkn744QedOnVKS5cuVcOGDVW8eHHNnz/f2u/mzZv64osv1Ldv3zT3ffPmzapZs6ZNW5UqVbR+/XrdvHlTGzZsUOXKlSVJzz77rKZNmyZvb+9UxypatKj8/f31008/pbm97IbADwAA8ABwdXXVnDlzNHfuXOXNm1cNGjTQq6++qt9//93a58cff9Qff/yhr7/+WjVr1lSpUqX01ltvKW/evPrmm28kST169NDChQut6+zfv187duywTnGZOXOmqlevrrCwMJUtW1bVqlXT559/rh9//FH79++3rleyZElNmzZNZcqUUdmyZVPU6+fnJ0kqUKCAAgMDlT9/fknS008/rdmzZ1v7ff/997p27VqKDxT/duTIEQUHB9u0ffrpp/rmm29UokQJ5cyZU6NHj9a8efPk6empWrVqqVWrVipZsqRee+21FOMVLFhQR44cSXN72Q2BHwAA4AHRuXNnnTx5UitWrFCrVq20adMmVa9eXXPmzJEk7dixQ1euXFGBAgWs3wjkzp1bhw8f1qFDhyRJXbt21dGjR7Vt2zZJ0oIFC1S1alWVL1/eOsaPP/5os35yoE8eQ1KKI+7p1adPHx08eNC6/c8//1xdunSRl5dXmuvExcXZTOeRpAoVKigiIkJHjx7VwoULdePGDYWGhmrGjBl64YUX1KBBA/3vf//T0qVL9d1339ms6+HhoWvXrmWo/qzAj3YBAAAeILly5VKLFi3UokULjR07Vv3799e4cePUp08fJSUlKSgoSJs2bUqxXt68eSVJQUFBatKkiRYuXKi6detq0aJFGjhwoLVfUlKS2rdvr6lTp6YYIygoyPrv2wX02/H391f79u01e/ZsFS9eXKtWrUq13n/z9fXVxYsXb9tn2LBhGjp0qAoVKqRNmzZp0qRJ8vLyUtu2bbVp0ya1b9/e2vfChQvWbyDuBwR+AACAB1j58uWtP5StXr26oqOj5erqqmLFiqW5To8ePTRy5Eh169ZNhw4dUteuXa3LqlevriVLlqhYsWJydc141MyZM6ckKTExMcWy/v37q2vXripUqJBKlCihBg0a3HasatWqWX+Um5oNGzbo77//tn7TkZiYqBs3bkiS9b/Jrl+/rkOHDqlatWr27E6WIvADAAA40N6zSdlyO+fPn9cTTzyhfv36qXLlyvL29tb27ds1bdo0dejQQZLUvHlz1atXTx07dtTUqVNVpkwZnTx5UqtWrVLHjh2t03A6deqk5557Ts8995yaNGmiggULWrczePBgffLJJ+rWrZteeeUV+fr66uDBg1q8eLE++eQTubik75Sl/v7+8vDw0Jo1a1SoUCHlypVLPj4+kqRWrVrJx8dHkyZN0oQJE+44VqtWrTR37txUl8XFxWnw4MFavHix9Rz9DRo00AcffKDBgwdryZIlCg8Pt/bftm2b3N3ds8V1C9KLwA8AAOAAvr6+8vTIpZ7L4u7ZNj09csnX1zddfXPnzq06deronXfe0aFDh3Tjxg0VLlxYzzzzjF599VVJt06LuWrVKo0ZM0b9+vXT2bNnFRgYqIYNGyogIMA6Vp48edS+fXt9/fXX+vzzz222ExwcrJ9//lkjR45Uq1atFB8fr6JFi+qRRx6x6+q0rq6ueu+99zRhwgSNHTtWDz/8sHXqTo4cOdSnTx+FhYWpV69edxyrZ8+eGjlypPbt26cyZcrYLJswYYLatWtnc3Gv9957T927d1fDhg3VvXt3de7c2bps0aJF6tGjhzw9PdO9L1nNYpJPmOqkYmNj5ePjo5iYGOXJkyerywEAAE7g+vXrOnz4sEJCQmx+DBoVFWVzvvnM5uvrm+6r7DqbZ555RqdPn9aKFSvS1X/EiBGKiYlJ9RSg6XX27FmVLVtW27dvt14nILOl9VyT0p9zOcIPAADgIEWKFHlgA/i9EhMTo8jISC1YsEDffvttutcbM2aMPvjgAyUmJqZ7WtF/HT58WB9++OE9C/uOQuAHAADAfaNDhw767bffNHDgQOsVetPDx8fHOnUpo2rXrq3atWvf1RhZgcAPAACA+8adTsGJlLjwFgAAAODECPwAAAAZ5OTnPkE24IjnGIEfAADATm5ubpKka9euZXElcHbJz7Hk51xGMIcfAADATi4uLsqbN6/OnDkjSfL09JTFYsniquBMjDG6du2azpw5o7x582b4zEISgR8AACBDAgMDJcka+oHMkDdvXutzLaMI/AAAABlgsVgUFBQkf39/3bhxI6vLgRNyc3O7qyP7yQj8AAAAd8HFxcUhoQzILFn6o92bN2/qtddeU0hIiDw8PFS8eHFNmDBBSUlJ1j7GGIWGhio4OFgeHh5q3Lix9uzZk4VVAwAAAPePLA38U6dO1axZszRjxgzt3btX06ZN05tvvqn333/f2mfatGkKDw/XjBkzFBkZqcDAQLVo0UKXL1/OwsoBAACA+0OWBv5ffvlFHTp0UNu2bVWsWDE9/vjjatmypbZv3y7p1tH96dOna8yYMerUqZMqVqyouXPn6tq1a1q4cGFWlg4AAADcF7I08D/00EPasGGD9u/fL0n63//+py1btqhNmzaSpMOHDys6OlotW7a0ruPu7q5GjRpp69atqY4ZHx+v2NhYmxsAAADwoMrSH+2OHDlSMTExKlu2rFxcXJSYmKjJkyerW7dukqTo6GhJUkBAgM16AQEBOnr0aKpjTpkyRePHj8/cwgEAAID7RJYe4f/yyy/1xRdfaOHChdq5c6fmzp2rt956S3PnzrXp998LWRhj0ry4xejRoxUTE2O9HTt2LNPqBwAAALK7LD3C/8orr2jUqFHq2rWrJKlSpUo6evSopkyZot69e1svMhAdHa2goCDremfOnElx1D+Zu7u73N3dM794AAAA4D6QpUf4r127phw5bEtwcXGxnpYzJCREgYGBWr9+vXV5QkKCIiIiVL9+/XtaKwAAAHA/ytIj/O3bt9fkyZNVpEgRVahQQbt27VJ4eLj69esn6dZUnqFDhyosLEylSpVSqVKlFBYWJk9PT3Xv3j0rSwcAAADuC1ka+N9//329/vrrGjRokM6cOaPg4GANHDhQY8eOtfYZMWKE4uLiNGjQIF28eFF16tTRunXr5O3tnYWVAwAAAPcHizHGZHURmSk2NlY+Pj6KiYlRnjx5srocAAAAwCHSm3OzdA4/AAAAgMxF4AcAAACcGIEfAAAAcGIEfgAAAMCJEfgBAAAAJ0bgBwAAAJwYgR8AAABwYgR+AAAAwIkR+AEAAAAnRuAHAAAAnBiBHwAAAHBiBH4AAADAiRH4AQAAACdG4AcAAACcGIEfAAAAcGIEfgAAAMCJEfgBAAAAJ0bgBwAAAJwYgR8AAABwYgR+AAAAwIkR+AEAAAAnRuAHAAAAnBiBHwAAAHBiBH4AAADAiRH4AQAAACdG4AcAAACcGIEfAAAAcGIEfgAAAMCJEfgBAAAAJ0bgBwAAAJwYgR8AAABwYgR+AAAAwIkR+AEAAAAnRuAHAAAAnBiBHwAAAHBiBH4AAADAiRH4AQAAACdG4AeyQLFixWSxWFLcBg8eLEkyxig0NFTBwcHy8PBQ48aNtWfPnjuOe+nSJQ0ePFhBQUHKlSuXypUrp1WrVmX27gAAgGzMNasLAB5EkZGRSkxMtN7/888/1aJFCz3xxBOSpGnTpik8PFxz5sxR6dKlNWnSJLVo0UL79u2Tt7d3qmMmJCSoRYsW8vf31zfffKNChQrp2LFjafYHAAAPBgI/kAX8/Pxs7r/xxhsqUaKEGjVqJGOMpk+frjFjxqhTp06SpLlz5yogIEALFy7UwIEDUx3z888/14ULF7R161a5ublJkooWLZq5OwIAALI9pvQAWSwhIUFffPGF+vXrJ4vFosOHDys6OlotW7a09nF3d1ejRo20devWNMdZsWKF6tWrp8GDBysgIEAVK1ZUWFiYzTcJAADgwcMRfiCLLV++XJcuXVKfPn0kSdHR0ZKkgIAAm34BAQE6evRomuP8888/2rhxo3r06KFVq1bpwIEDGjx4sG7evKmxY8dmWv0AACB7I/ADWeyzzz5T69atFRwcbNNusVhs7htjUrT9W1JSkvz9/fXxxx/LxcVFNWrU0MmTJ/Xmm28S+AEAeIAR+IEsdPToUf3www9aunSptS0wMFDSrSP9QUFB1vYzZ86kOOr/b0FBQXJzc5OLi4u1rVy5coqOjlZCQoJy5syZCXsAAACyO+bwA1lo9uzZ8vf3V9u2ba1tISEhCgwM1Pr1661tCQkJioiIUP369dMcq0GDBjp48KCSkpKsbfv371dQUBBhHwCABxiBH8giSUlJmj17tnr37i1X1//7ss1isWjo0KEKCwvTsmXL9Oeff6pPnz7y9PRU9+7drf169eql0aNHW+8/99xzOn/+vIYMGaL9+/fr+++/V1hYmPXc/gAA4MHElB4gi/zwww+KiopSv379UiwbMWKE4uLiNGjQIF28eFF16tTRunXrbM6pHxUVpRw5/u8ze+HChbVu3ToNGzZMlStXVsGCBTVkyBCNHDnynuwPAADInizGGJPVRWSm2NhY+fj4KCYmRnny5MnqcgAAAACHSG/O5Qg/HhhRUVE6d+5cVpcBSb6+vipSpEhWlwEAwAMhSwN/sWLFUj2v+KBBg/TBBx/IGKPx48fr448/tk5r+OCDD1ShQoUsqBb3s6ioKJUrW0bX4q5ndSmQ5OmRS3v/3kfoBwDgHsjSwB8ZGWlzFdA///xTLVq00BNPPCFJmjZtmsLDwzVnzhyVLl1akyZNUosWLbRv3z6buczAnZw7d07X4q7ri8c8VM6P36pnpb1nk9RzWZzOnTtH4AcA4B7I0sDv5+dnc/+NN95QiRIl1KhRIxljNH36dI0ZM0adOnWSJM2dO1cBAQFauHChBg4cmOqY8fHxio+Pt96PjY3NvB3AfaecXw5VD3K5c0cAAAAnkW0OdSYkJOiLL75Qv379ZLFYdPjwYUVHR6tly5bWPu7u7mrUqJG2bt2a5jhTpkyRj4+P9Va4cOF7UT4AAACQLWWbwL98+XJdunRJffr0kXTrKqOSUlxZNCAgwLosNaNHj1ZMTIz1duzYsUyrGQAAAMjuss1Zej777DO1bt1awcHBNu0Wi8XmvjEmRdu/ubu7y93dPVNqBAAAAO432eII/9GjR/XDDz+of//+1rbAwEBJSnE0/8yZMymO+gMAAABIXbYI/LNnz5a/v7/atm1rbQsJCVFgYKDWr19vbUtISFBERITq16+fFWUCAAAA950sn9KTlJSk2bNnq3fv3nJ1/b9yLBaLhg4dqrCwMJUqVUqlSpVSWFiYPD091b179yysGAAAALh/ZHng/+GHHxQVFaV+/fqlWDZixAjFxcVp0KBB1gtvrVu3jnPwAwAAAOmU5YG/ZcuWMsakusxisSg0NFShoaH3tigAAADASWSLOfwAAAAAMgeBHwAAAHBiBH4AAADAiRH4AQAAACdG4AcAAACcGIEfAAAAcGIEfgAAAMCJEfgBAAAAJ0bgBwAAAJwYgR8AAABwYgR+AAAAwIkR+AEAAAAnRuAHAAAAnBiBHwAAAHBiBH4AAADAiRH4AQAAACdG4AcAAACcmKs9nWNiYrRs2TL99NNPOnLkiK5duyY/Pz9Vq1ZNrVq1Uv369TOrTgAAAAAZkK4j/KdOndIzzzyjoKAgTZgwQVevXlXVqlXVrFkzFSpUSD/++KNatGih8uXL68svv8zsmgEAAACkU7qO8FepUkW9evXSb7/9pooVK6baJy4uTsuXL1d4eLiOHTuml19+2aGFAgAAALBfugL/nj175Ofnd9s+Hh4e6tatm7p166azZ886pDgAAAAAdyddU3ruFPbvtj8AAACAzJHhs/RcvnxZr7zyimrVqqXq1avrhRde0Llz5xxZGwAAAIC7lOHA/8wzz+jcuXMaP368xo0bp3/++Uc9evRwZG0AAAAA7lK6T8v5zjvvaOjQobJYLJKkyMhI7d+/Xy4uLpKkMmXKqG7duplTJQAAAIAMSXfgP3jwoOrUqaOPPvpI1apVU4sWLdS2bVt17NhRN27c0Pz589WqVavMrBUAAACAndId+D/44AP98ssv6tevn5o0aaIpU6boiy++0Pr165WYmKgnnnhCzz//fGbWCgAAAMBOdl1pt169eoqMjNQbb7yhevXq6c0339SSJUsyqzYAAAAAd8nuH+26urrqtdde03fffafp06fr8ccfV3R0dGbUBgAAAOAupTvw//HHH6pdu7a8vb3VoEEDJSUlacOGDWrTpo3q16+vmTNnZmadAAAAADIg3YG/b9++euihhxQZGaknnnhCzz77rCSpX79++vXXX7VlyxbVq1cv0woFAAAAYL90z+Hft2+fFi9erJIlS6pUqVKaPn26dZmfn58WLFigdevWZUaNAAAAADIo3YG/cePGGjBggLp27aqNGzeqQYMGKfq0bNnSocUBAAAAuDvpntIzb948Va9eXd9++62KFy/OnH0AAADgPpDuI/z58uXTW2+9lZm1AAAAAHCwdB3hj4qKsmvQEydOZKgYAAAAAI6VrsBfq1YtPfPMM/rtt9/S7BMTE6NPPvlEFStW1NKlSx1WIAAAAICMS1fg37t3r3x8fPTII48oICBAbdu21TPPPKMXXnhBPXv2VPXq1eXv7685c+bozTff1AsvvJDZdQMAcEcnTpxQz549VaBAAXl6eqpq1arasWOHdbkxRqGhoQoODpaHh4caN26sPXv23HbMOXPmyGKxpLhdv349s3cHADIkXYE/f/78euutt3Ty5EnNnDlTpUuX1rlz53TgwAFJUo8ePbRjxw79/PPPat26daYWDABAely8eFENGjSQm5ubVq9erb/++ktvv/228ubNa+0zbdo0hYeHa8aMGYqMjFRgYKBatGihy5cv33bsPHny6NSpUza3XLlyZfIeAUDGpPtHu5KUK1cuderUSZ06dcqsegAAcIipU6eqcOHCmj17trWtWLFi1n8bYzR9+nSNGTPG+v+1uXPnKiAgQAsXLtTAgQPTHNtisSgwMDDTagcAR0r3aTkBALifrFixQjVr1tQTTzwhf39/VatWTZ988ol1+eHDhxUdHW1zDRl3d3c1atRIW7duve3YV65cUdGiRVWoUCG1a9dOu3btyrT9AIC7ReAHADilf/75RzNnzlSpUqW0du1aPfvss3rxxRc1b948SVJ0dLQkKSAgwGa9gIAA67LUlC1bVnPmzNGKFSu0aNEi5cqVSw0aNLBOcwWA7MauKT0AANwvkpKSVLNmTYWFhUmSqlWrpj179mjmzJnq1auXtZ/FYrFZzxiTou3f6tatq7p161rvN2jQQNWrV9f777+v9957z8F7AQB3jyP8AACnFBQUpPLly9u0lStXznptmeQ5+P89mn/mzJkUR/1vJ0eOHKpVqxZH+AFkW3YH/qtXr2ZGHQAAOFSDBg20b98+m7b9+/eraNGikqSQkBAFBgZq/fr11uUJCQmKiIhQ/fr1070dY4x2796toKAgxxQOAA5md+APCAhQv379tGXLlsyoBwAAhxg2bJi2bdumsLAwHTx4UAsXLtTHH3+swYMHS7o1lWfo0KEKCwvTsmXL9Oeff6pPnz7y9PRU9+7dreP06tVLo0ePtt4fP3681q5dq3/++Ue7d+/W008/rd27d+vZZ5+95/sIAOlh9xz+RYsWac6cOWrWrJmKFi2qfv36qVevXgoODs6M+gAAyJBatWpp2bJlGj16tCZMmKCQkBBNnz5dPXr0sPYZMWKE4uLiNGjQIF28eFF16tTRunXr5O3tbe0TFRWlHDn+7/jYpUuXNGDAAEVHR8vHx0fVqlXT5s2bVbt27Xu6fwCQXhZjjMnIiufPn9e8efM0Z84c/fXXX2rVqpX69eunRx99VK6u2ee3wLGxsfLx8VFMTIzy5MmT1eUgi+zcuVM1atTQjgFeqh7kktXlPNB2nkpUjY+vaseOHapevXpWlwMAwH0rvTk3w8m8QIECGjZsmIYNG6b3339fr7zyilatWiVfX189++yzGjVqlDw9Pe84zokTJzRy5EitXr1acXFxKl26tD777DPVqFFD0q25kePHj9fHH39sPfrywQcfqEKFChktHQCQiaKionTu3LmsLuOB5+vrqyJFimR1GQCygQwH/ujoaM2bN0+zZ89WVFSUHn/8cT399NM6efKk3njjDW3btk3r1q277RjJlz1v0qSJVq9eLX9/fx06dCjVy57PmTNHpUuX1qRJk9SiRQvt27fP5itXAEDWi4qKUrmyZXQt7npWl/LA8/TIpb1/7yP0A7A/8C9dulSzZ8/W2rVrVb58eQ0ePFg9e/a0CelVq1ZVtWrV7jhWZl72HABw7507d07X4q7ri8c8VM6PMz9nlb1nk9RzWZzOnTtH4Adgf+Dv27evunbtqp9//lm1atVKtU/x4sU1ZsyYO461YsUKtWrVSk888YQiIiJUsGBBDRo0SM8884ykO1/2PLXAHx8fr/j4eOv92NhYe3cRAHCXyvnl4PcyAJBN2B34T506dce5+R4eHho3btwdx0q+7Pnw4cP16quv6rffftOLL74od3d39erV67aXPT969GiqY06ZMkXjx49P594AAAAAzs3u71u9vb115syZFO3nz5+Xi4t9R3OSkpJUvXp1hYWFqVq1aho4cKCeeeYZzZw506afPZc9Hz16tGJiYqy3Y8eO2VUTAAAA4EzsDvxpncUzPj5eOXPmtGuszLjsubu7u/LkyWNzAwAAAB5U6Z7S895770m6dbT9008/Ve7cua3LEhMTtXnzZpUtW9aujdtz2fPkHwEnX/Z86tSpdm0LAAAAeBClO/C/8847km4d4Z81a5bN9J2cOXOqWLFimjVrll0bHzZsmOrXr6+wsDB16dJFv/32mz7++GN9/PHHkmwve16qVCmVKlVKYWFhKS57DgAAACB16Q78hw8fliQ1adJES5cuVb58+e5644667DkAAACA1Nl9lp4ff/zRoQW0a9dO7dq1S3O5xWJRaGioQkNDHbpdAAAA4EGQrsA/fPhwTZw4UV5eXho+fPht+4aHhzukMAAAAAB3L11n6dm1a5du3LghSdq5c6d27dqV6m337t2ZWSsAAACymdDQUFksFptb8pkWk+3du1ePPvqofHx85O3trbp161rPypiaxo0bpxjTYrGobdu2mb07TildR/j/PY1n06ZNmVULAAAA7kMVKlTQDz/8YL3/75O7HDp0SA899JCefvppjR8/Xj4+Ptq7d69y5cqV5nhLly5VQkKC9f758+dVpUoVPfHEE5mzA07Orjn8N2/eVK5cubR7925VrFgxs2oCAADAfcTV1TXFUf1kY8aMUZs2bTRt2jRrW/HixW87Xv78+W3uL168WJ6engT+DLLrwluurq4qWrSoEhMTM6seAAAA3GcOHDig4OBghYSEqGvXrvrnn38kSUlJSfr+++9VunRptWrVSv7+/qpTp46WL19u1/ifffaZunbtKi8vr0yo3vnZfaXd1157TaNHj9aFCxcyox4AAADcR+rUqaN58+Zp7dq1+uSTTxQdHa369evr/PnzOnPmjK5cuaI33nhDjzzyiNatW6fHHntMnTp1UkRERLrG/+233/Tnn3+qf//+mbwnzsvu03K+9957OnjwoIKDg1W0aNEUn7R27tzpsOIAAACQvbVu3dr670qVKqlevXoqUaKE5s6dq65du0qSOnTooGHDhkmSqlatqq1bt2rWrFlq1KjRHcf/7LPPVLFiRdWuXTtzduABYHfg79ixYyaUAQAAAGfg5eWlSpUq6cCBA/L19ZWrq6vKly9v06dcuXLasmXLHce6du2aFi9erAkTJmRWuQ8EuwP/uHHjMqMOAAAAOIH4+Hjt3btXDz/8sHLmzKlatWpp3759Nn3279+vokWL3nGsr776SvHx8erZs2dmlftAsDvwS9KlS5f0zTff6NChQ3rllVeUP39+7dy5UwEBASpYsKCjawQAAEA29fLLL6t9+/YqUqSIzpw5o0mTJik2Nla9e/eWJL3yyit68skn1bBhQzVp0kRr1qzRd999Z3Oq9169eqlgwYKaMmWKzdifffaZOnbsqAIFCtzLXXI6dgf+33//Xc2bN5ePj4+OHDmiZ555Rvnz59eyZct09OhRzZs3LzPqBAAAQDZ0/PhxdevWTefOnZOfn5/q1q2rbdu2WY/gP/bYY5o1a5amTJmiF198UWXKlNGSJUv00EMPWceIiopSjhy255LZv3+/tmzZonXr1t3T/XFGdgf+4cOHq0+fPpo2bZq8vb2t7a1bt1b37t0dWhwAAACyt8WLF9+xT79+/dSvX780l6d2YdfSpUvLGHM3peH/szvwR0ZG6qOPPkrRXrBgQUVHRzukKAAAAKQtKipK586dy+oyIMnX11dFihTJ6jJuy+7AnytXLsXGxqZo37dvn/z8/BxSFAAAAFIXFRWlcmXL6Frc9awuBZI8PXJp79/7snXotzvwd+jQQRMmTNBXX30lSbJYLIqKitKoUaPUuXNnhxcIAACA/3Pu3Dldi7uuLx7zUDk/u6+hCgfaezZJPZfF6dy5c84V+N966y21adNG/v7+iouLU6NGjRQdHa169epp8uTJmVEjAAAA/qOcXw5VD3LJ6jJwH7A78OfJk0dbtmzRxo0btXPnTiUlJal69epq3rx5ZtQHAAAA4C7YHfiPHDmiYsWKqWnTpmratGlm1AQAAADAQeye+FW8eHE99NBD+uijj3ThwoXMqAkAAACAg9gd+Ldv36569epp0qRJCg4OVocOHfT1118rPj4+M+oDAAAAcBfsDvzVq1fXm2++qaioKK1evVr+/v4aOHCg/P39b3tBBQAAAAD3XobP5WSxWNSkSRN98skn+uGHH1S8eHHNnTvXkbUBAAAAuEsZDvzHjh3TtGnTVLVqVdWqVUteXl6aMWOGI2sDAAAAcJfsPkvPxx9/rAULFujnn39WmTJl1KNHDy1fvlzFihXLhPIAAAAA3A27A//EiRPVtWtXvfvuu6patWomlAQAAADAUewO/FFRUbJYLJlRCwAAAAAHs3sOv8Vi0U8//aSePXuqXr16OnHihCRp/vz52rJli8MLBAAAAJBxdgf+JUuWqFWrVvLw8NCuXbus59+/fPmywsLCHF4gAAAAgIyzO/BPmjRJs2bN0ieffCI3Nzdre/369bVz506HFgcAAADg7tgd+Pft26eGDRumaM+TJ48uXbrkiJoAAAAAOIjdgT8oKEgHDx5M0b5lyxYVL17cIUUBAAAAcAy7A//AgQM1ZMgQ/frrr7JYLDp58qQWLFigl19+WYMGDcqMGgEAAABkkN2n5RwxYoRiYmLUpEkTXb9+XQ0bNpS7u7tefvllPf/885lRIwAAAIAMsjvwS9LkyZM1ZswY/fXXX0pKSlL58uWVO3duR9cGAAAA4C7ZPaUnmaenp2rWrKmAgABFRUUpKSnJkXUBAAAAcIB0B/65c+dq+vTpNm0DBgxQ8eLFValSJVWsWFHHjh1zdH0AAAAA7kK6A/+sWbPk4+Njvb9mzRrNnj1b8+bNU2RkpPLmzavx48dnSpEAAAAAMibdc/j379+vmjVrWu9/++23evTRR9WjRw9JUlhYmPr27ev4CgEAAABkWLqP8MfFxSlPnjzW+1u3brW5AFfx4sUVHR3t2OoAAAAA3JV0B/6iRYtqx44dkqRz585pz549euihh6zLo6Ojbab8AAAAAMh66Z7S06tXLw0ePFh79uzRxo0bVbZsWdWoUcO6fOvWrapYsWKmFAkAAAAgY9Id+EeOHKlr165p6dKlCgwM1Ndff22z/Oeff1a3bt0cXiAAAACAjEt34M+RI4cmTpyoiRMnprr8vx8AAAAAAGS9DF94CwAAAED2R+AHAAAAnBiBHwAAAHBiBH4AAADAiRH4AQAAACeWrrP0DB8+PN0DhoeHZ7gYAAAAAI6VrsC/a9cum/s7duxQYmKiypQpI0nav3+/XFxcbC7ElR6hoaEaP368TVtAQICio6MlScYYjR8/Xh9//LEuXryoOnXq6IMPPlCFChXs2g4AAADwoEpX4P/xxx+t/w4PD5e3t7fmzp2rfPnySZIuXryovn376uGHH7a7gAoVKuiHH36w3ndxcbH+e9q0aQoPD9ecOXNUunRpTZo0SS1atNC+ffvk7e1t97YAAACAB43dc/jffvttTZkyxRr2JSlfvnyaNGmS3n77bbsLcHV1VWBgoPXm5+cn6dbR/enTp2vMmDHq1KmTKlasqLlz5+ratWtauHCh3dsBAAAAHkR2B/7Y2FidPn06RfuZM2d0+fJluws4cOCAgoODFRISoq5du+qff/6RJB0+fFjR0dFq2bKlta+7u7saNWqkrVu3pjlefHy8YmNjbW4AAADAg8ruwP/YY4+pb9+++uabb3T8+HEdP35c33zzjZ5++ml16tTJrrHq1KmjefPmae3atfrkk08UHR2t+vXr6/z589Z5/AEBATbr/HuOf2qmTJkiHx8f661w4cL27iIAAADgNNI1h//fZs2apZdfflk9e/bUjRs3bg3i6qqnn35ab775pl1jtW7d2vrvSpUqqV69eipRooTmzp2runXrSpIsFovNOsaYFG3/Nnr0aJuzCsXGxhL6AQAA8MCyO/B7enrqww8/1JtvvqlDhw7JGKOSJUvKy8vrrovx8vJSpUqVdODAAXXs2FGSFB0draCgIGufM2fOpDjq/2/u7u5yd3e/61oAAAAAZ5DhC295eXmpcuXKqlKlikPCvnRr/v3evXsVFBSkkJAQBQYGav369dblCQkJioiIUP369R2yPQAAAMDZ2X2E/+rVq3rjjTe0YcMGnTlzRklJSTbLk390mx4vv/yy2rdvryJFiujMmTOaNGmSYmNj1bt3b1ksFg0dOlRhYWEqVaqUSpUqpbCwMHl6eqp79+72lg0AAAA8kOwO/P3791dERISeeuopBQUF3XY+/Z0cP35c3bp107lz5+Tn56e6detq27ZtKlq0qCRpxIgRiouL06BBg6wX3lq3bh3n4AcAAADSye7Av3r1an3//fdq0KDBXW988eLFt11usVgUGhqq0NDQu94WAAAA8CCyew5/vnz5lD9//syoBQAAAICD2R34J06cqLFjx+ratWuZUQ8AAAAAB7J7Ss/bb7+tQ4cOKSAgQMWKFZObm5vN8p07dzqsOAAAAAB3x+7An3x+fAAAAADZn92Bf9y4cZlRBwAAAIBMkOELbwEAAADI/uw+wp+YmKh33nlHX331laKiopSQkGCz/MKFCw4rDgAAAMDdsfsI//jx4xUeHq4uXbooJiZGw4cPV6dOnZQjRw7Olw8AAABkM3YH/gULFuiTTz7Ryy+/LFdXV3Xr1k2ffvqpxo4dq23btmVGjQAAAAAyyO7AHx0drUqVKkmScufOrZiYGElSu3bt9P333zu2OgAAAAB3xe7AX6hQIZ06dUqSVLJkSa1bt06SFBkZKXd3d8dWBwAAAOCu2B34H3vsMW3YsEGSNGTIEL3++usqVaqUevXqpX79+jm8QAAAAAAZZ/dZet544w3rvx9//HEVLlxYP//8s0qWLKlHH33UocUBAAAAuDt2B/7/qlOnjurUqeOIWgAAAAA4GBfeAgAAAJwYgR8AAABwYgR+AAAAwIkR+AEAAAAnlqHAf+nSJX366acaPXq0Lly4IEnauXOnTpw44dDiAAAAANwdu8/S8/vvv6t58+by8fHRkSNH9Mwzzyh//vxatmyZjh49qnnz5mVGnQAAAAAywO4j/MOHD1efPn104MAB5cqVy9reunVrbd682aHFAQAAALg7dgf+yMhIDRw4MEV7wYIFFR0d7ZCiAAAAADiG3YE/V65cio2NTdG+b98++fn5OaQoAAAAAI5hd+Dv0KGDJkyYoBs3bkiSLBaLoqKiNGrUKHXu3NnhBQIAAADIOLsD/1tvvaWzZ8/K399fcXFxatSokUqWLClvb29Nnjw5M2oEAAAAkEF2n6UnT5482rJlizZu3KidO3cqKSlJ1atXV/PmzTOjPgAAAAB3we7An6xp06Zq2rSpI2sBAAAA4GB2T+l58cUX9d5776VonzFjhoYOHeqImgAAAAA4iN2Bf8mSJWrQoEGK9vr16+ubb75xSFEAAAAAHMPuwH/+/Hn5+PikaM+TJ4/OnTvnkKIAAAAAOIbdgb9kyZJas2ZNivbVq1erePHiDikKAAAAgGPY/aPd4cOH6/nnn9fZs2etP9rdsGGD3n77bU2fPt3R9QEAAAC4C3YH/n79+ik+Pl6TJ0/WxIkTJUnFihXTzJkz1atXL4cXCAAAACDjMnRazueee07PPfeczp49Kw8PD+XOndvRdQEAAABwgAyfh1+S/Pz8HFUHAAAAgExg9492T58+raeeekrBwcFydXWVi4uLzQ0AAABA9mH3Ef4+ffooKipKr7/+uoKCgmSxWDKjLgAAAAAOYHfg37Jli3766SdVrVo1E8oBAAAA4Eh2T+kpXLiwjDGZUQsAAAAAB7M78E+fPl2jRo3SkSNHMqEcAAAAAI5k95SeJ598UteuXVOJEiXk6ekpNzc3m+UXLlxwWHEAAAAA7o7dgZ+r6QIAAAD3D7sDf+/evTOjDgAAAACZwO45/JJ06NAhvfbaa+rWrZvOnDkjSVqzZo327Nnj0OIAAAAA3B27A39ERIQqVaqkX3/9VUuXLtWVK1ckSb///rvGjRvn8AIBAAAAZJzdgX/UqFGaNGmS1q9fr5w5c1rbmzRpol9++cWhxQEAAAC4O3YH/j/++EOPPfZYinY/Pz+dP3/eIUUBAAAAcAy7A3/evHl16tSpFO27du1SwYIFHVIUAAAAAMewO/B3795dI0eOVHR0tCwWi5KSkvTzzz/r5ZdfVq9evTKjRgAAAAAZZHfgnzx5sooUKaKCBQvqypUrKl++vBo2bKj69evrtddey3AhU6ZMkcVi0dChQ61txhiFhoYqODhYHh4eaty4MWcCAgAAAOxgd+B3c3PTggULtH//fn311Vf64osv9Pfff2v+/PlycXHJUBGRkZH6+OOPVblyZZv2adOmKTw8XDNmzFBkZKQCAwPVokULXb58OUPbAQAAAB40GToPvySVKFFCjz/+uLp06aJSpUpluIArV66oR48e+uSTT5QvXz5ruzFG06dP15gxY9SpUydVrFhRc+fO1bVr17Rw4cIMbw8AAAB4kKTrSrvDhw9P94Dh4eF2FTB48GC1bdtWzZs316RJk6zthw8fVnR0tFq2bGltc3d3V6NGjbR161YNHDgw1fHi4+MVHx9vvR8bG2tXPQAAAIAzSVfg37VrV7oGs1gsdm188eLF2rFjh7Zv355iWXR0tCQpICDApj0gIEBHjx5Nc8wpU6Zo/PjxdtUBAAAAOKt0Bf4ff/zR4Rs+duyYhgwZonXr1ilXrlxp9vvvhwhjzG0/WIwePdrmG4nY2FgVLlz47gsGAAAA7kPpCvyZYceOHTpz5oxq1KhhbUtMTNTmzZs1Y8YM7du3T9KtI/1BQUHWPmfOnElx1P/f3N3d5e7unnmFAwAAAPeRDAX+yMhIff3114qKilJCQoLNsqVLl6ZrjGbNmumPP/6waevbt6/Kli2rkSNHqnjx4goMDNT69etVrVo1SVJCQoIiIiI0derUjJQNAAAAPHDsDvyLFy9Wr1691LJlS61fv14tW7bUgQMHFB0drcceeyzd43h7e6tixYo2bV5eXipQoIC1fejQoQoLC1OpUqVUqlQphYWFydPTU927d7e3bAAAAOCBZHfgDwsL0zvvvKPBgwfL29tb7777rkJCQjRw4ECbqTeOMGLECMXFxWnQoEG6ePGi6tSpo3Xr1snb29uh2wEAAACcld2B/9ChQ2rbtq2kW/Plr169KovFomHDhqlp06Z3dYacTZs22dy3WCwKDQ1VaGhohscEAAAAHmR2X3grf/781ivdFixYUH/++ack6dKlS7p27ZpjqwMAAABwV+w+wv/www9r/fr1qlSpkrp06aIhQ4Zo48aNWr9+vZo1a5YZNQIAAADIILsD/4wZM3T9+nVJt8557+bmpi1btqhTp056/fXXHV4gAAAAgIyzO/Dnz5/f+u8cOXJoxIgRGjFihEOLAgAAAOAYds/hb9KkiT777DPFxMRkRj0AAAAAHMjuwF+pUiW99tprCgwMVOfOnbV8+fIUF98CAAAAkD3YHfjfe+89nThxQt9++628vb3Vu3dvBQYGasCAAYqIiMiMGgEAAABkkN2BX7o1d79ly5aaM2eOTp8+rY8++ki//fabmjZt6uj6AAAAANwFu3+0+2/R0dFavHixvvjiC/3++++qVauWo+oCAAAA4AB2H+GPjY3V7Nmz1aJFCxUuXFgzZ85U+/bttX//fv3666+ZUSMAAACADLL7CH9AQIDy5cunLl26KCwsjKP6AAAAQDZmd+D/9ttv1bx5c+XIkaHp/wAAAADuIbtTe8uWLZWUlKQffvhBH330kS5fvixJOnnypK5cueLwAgEAAABknN1H+I8ePapHHnlEUVFRio+PV4sWLeTt7a1p06bp+vXrmjVrVmbUCQAAACAD7D7CP2TIENWsWVMXL16Uh4eHtf2xxx7Thg0bHFocAAAAgLtj9xH+LVu26Oeff1bOnDlt2osWLaoTJ044rDAAAAAAd8/uI/xJSUlKTExM0X78+HF5e3s7pCgAAAAAjmF34G/RooWmT59uvW+xWHTlyhWNGzdObdq0cWRtAAAAAO6S3VN6wsPD1bRpU5UvX17Xr19X9+7ddeDAAfn6+mrRokWZUSMAAACADLI78BcsWFC7d+/W4sWLtWPHDiUlJenpp59Wjx49bH7ECwAAACDr2RX4b9y4oTJlymjlypXq27ev+vbtm1l1AQAAAHAAu+bwu7m5KT4+XhaLJbPqAQAAAOBAdv9o94UXXtDUqVN18+bNzKgHAAAAgAPZPYf/119/1YYNG7Ru3TpVqlRJXl5eNsuXLl3qsOIAAAAA3B27A3/evHnVuXPnzKgFAAAAgIPZHfhnz56dGXUAAAAAyATpnsOflJSkN998Uw0aNFDt2rX16quv6vr165lZGwAAAIC7lO7AP3XqVI0aNUpeXl4KCgpSeHi4XnzxxcysDQAAAMBdSnfgnzNnjt5//32tW7dO3377rZYvX6558+bJGJOZ9QEAAAC4C+kO/EePHlW7du2s91u1aiVjjE6ePJkphQEAAAC4e+kO/AkJCfLw8LDet1gsypkzp+Lj4zOlMAAAAAB3z66z9Lz++uvy9PS03k9ISNDkyZPl4+NjbQsPD3dcdQAAAADuSroDf8OGDbVv3z6btvr16+uff/6x3rdYLI6rDAAAAMBdS3fg37RpUyaWAQAAACAzpHsOPwAAAID7D4EfAAAAcGIEfgAAAMCJEfgBAAAAJ0bgBwAAAJxYhgL/Tz/9pJ49e6pevXo6ceKEJGn+/PnasmWLQ4sDAAAAcHfsDvxLlixRq1at5OHhoV27dlmvtHv58mWFhYU5vEAAAAAAGWd34J80aZJmzZqlTz75RG5ubtb2+vXra+fOnQ4tDgAAAMDdsTvw79u3Tw0bNkzRnidPHl26dMkRNQEAAABwELsDf1BQkA4ePJiifcuWLSpevLhDigIAAADgGHYH/oEDB2rIkCH69ddfZbFYdPLkSS1YsEAvv/yyBg0alBk1AgAAAMggV3tXGDFihGJiYtSkSRNdv35dDRs2lLu7u15++WU9//zzmVEjAAAAgAyyO/BL0uTJkzVmzBj99ddfSkpKUvny5ZU7d25H1wYAAADgLmX4wluenp6qWbOmypYtqx9++EF79+51ZF0AAAAAHMDuwN+lSxfNmDFDkhQXF6datWqpS5cuqly5spYsWeLwAgEAAABknN2Bf/PmzXr44YclScuWLVNSUpIuXbqk9957T5MmTbJrrJkzZ6py5crKkyeP8uTJo3r16mn16tXW5cYYhYaGKjg4WB4eHmrcuLH27Nljb8kAAADAA8vuwB8TE6P8+fNLktasWaPOnTvL09NTbdu21YEDB+waq1ChQnrjjTe0fft2bd++XU2bNlWHDh2soX7atGkKDw/XjBkzFBkZqcDAQLVo0UKXL1+2t2wAAADggWR34C9cuLB++eUXXb16VWvWrFHLli0lSRcvXlSuXLnsGqt9+/Zq06aNSpcurdKlS2vy5MnKnTu3tm3bJmOMpk+frjFjxqhTp06qWLGi5s6dq2vXrmnhwoX2lg0AAAA8kOwO/EOHDlWPHj1UqFAhBQcHq3HjxpJuTfWpVKlShgtJTEzU4sWLdfXqVdWrV0+HDx9WdHS09QOFJLm7u6tRo0baunVrmuPEx8crNjbW5gYAAAA8qOw+LeegQYNUp04dRUVFqUWLFsqR49ZnhuLFi9s9h1+S/vjjD9WrV0/Xr19X7ty5tWzZMpUvX94a6gMCAmz6BwQE6OjRo2mON2XKFI0fP97uOgAAAABnlKHz8NeoUUM1atSwaWvbtm2GCihTpox2796tS5cuacmSJerdu7ciIiKsyy0Wi01/Y0yKtn8bPXq0hg8fbr0fGxurwoULZ6g2AAAA4H6XocB//PhxrVixQlFRUUpISLBZFh4ebtdYOXPmVMmSJSVJNWvWVGRkpN59912NHDlSkhQdHa2goCBr/zNnzqQ46v9v7u7ucnd3t6sGAAAAwFnZHfg3bNigRx99VCEhIdq3b58qVqyoI0eOyBij6tWr33VBxhjFx8crJCREgYGBWr9+vapVqyZJSkhIUEREhKZOnXrX2wEAAAAeBHYH/tGjR+ull17ShAkT5O3trSVLlsjf3189evTQI488YtdYr776qlq3bq3ChQvr8uXLWrx4sTZt2qQ1a9bIYrFo6NChCgsLU6lSpVSqVCmFhYXJ09NT3bt3t7dsAAAA4IFkd+Dfu3evFi1adGtlV1fFxcUpd+7cmjBhgjp06KDnnnsu3WOdPn1aTz31lE6dOiUfHx9VrlxZa9asUYsWLSRJI0aMUFxcnAYNGqSLFy+qTp06Wrdunby9ve0tGwAAAHgg2R34vby8FB8fL0kKDg7WoUOHVKFCBUnSuXPn7Brrs88+u+1yi8Wi0NBQhYaG2lsmAAAAAGUg8NetW1c///yzypcvr7Zt2+qll17SH3/8oaVLl6pu3bqZUSMAAACADLI78IeHh+vKlSuSpNDQUF25ckVffvmlSpYsqXfeecfhBQIAAADIOLsDf/Hixa3/9vT01IcffujQggAAAAA4To6MrHTp0iV9+umnGj16tC5cuCBJ2rlzp06cOOHQ4gAAAADcHbuP8P/+++9q3ry5fHx8dOTIET3zzDPKnz+/li1bpqNHj2revHmZUScAAACADLD7CP/w4cPVp08fHThwQLly5bK2t27dWps3b3ZocQAAAADujt2BPzIyUgMHDkzRXrBgQUVHRzukKAAAAACOYXfgz5Url2JjY1O079u3T35+fg4pCgAAAIBj2B34O3TooAkTJujGjRuSbl0cKyoqSqNGjVLnzp0dXiAAAACAjLM78L/11ls6e/as/P39FRcXp0aNGqlkyZLy9vbW5MmTM6NGAAAAABlk91l68uTJoy1btmjjxo3auXOnkpKSVL16dTVv3jwz6gMAAABwF+wO/MmaNm2qpk2bSrp1Xn4AAAAA2Y/dU3qmTp2qL7/80nq/S5cuKlCggAoWLKj//e9/Di0OAAAAwN2xO/B/9NFHKly4sCRp/fr1Wr9+vVavXq3WrVvrlVdecXiBAAAAADLO7ik9p06dsgb+lStXqkuXLmrZsqWKFSumOnXqOLxAAAAAABln9xH+fPny6dixY5KkNWvWWH+sa4xRYmKiY6sDAAAAcFfsPsLfqVMnde/eXaVKldL58+fVunVrSdLu3btVsmRJhxcIAAAAIOPsDvzvvPOOihUrpmPHjmnatGnKnTu3pFtTfQYNGuTwAgEAAABknN2B383NTS+//HKK9qFDhzqiHgAAAAAOlK7Av2LFCrVu3Vpubm5asWLFbfs++uijDikMAAAAwN1LV+Dv2LGjoqOj5e/vr44dO6bZz2Kx8MNdAAAAIBtJV+BPSkpK9d8AAAAAsje7T8sJAAAA4P5h1492k5KSNGfOHC1dulRHjhyRxWJRSEiIHn/8cT311FOyWCyZVScAAACADEj3EX5jjB599FH1799fJ06cUKVKlVShQgUdPXpUffr00WOPPZaZdQIAAADIgHQf4Z8zZ442b96sDRs2qEmTJjbLNm7cqI4dO2revHnq1auXw4sEAAAAkDHpPsK/aNEivfrqqynCviQ1bdpUo0aN0oIFCxxaHAAAAIC7k+7A//vvv+uRRx5Jc3nr1q31v//9zyFFAQAAAHCMdAf+CxcuKCAgIM3lAQEBunjxokOKAgAAAOAY6Q78iYmJcnVNe8q/i4uLbt686ZCiAAAAADhGun+0a4xRnz595O7unury+Ph4hxUFAAAAwDHSHfh79+59xz6coQcAAADIXtId+GfPnp2ZdQAAAADIBOmeww8AAADg/kPgBwAAAJwYgR8AAABwYgR+AAAAwIkR+AEAAAAnRuAHAAAAnBiBHwAAAHBiBH4AAADAiRH4AQAAACdG4AcAAACcGIEfAAAAcGIEfgAAAMCJEfgBAAAAJ0bgBwAAAJwYgR8AAABwYgR+AAAAwIllaeCfMmWKatWqJW9vb/n7+6tjx47at2+fTR9jjEJDQxUcHCwPDw81btxYe/bsyaKKAQAAgPtLlgb+iIgIDR48WNu2bdP69et18+ZNtWzZUlevXrX2mTZtmsLDwzVjxgxFRkYqMDBQLVq00OXLl7OwcgAAAOD+4JqVG1+zZo3N/dmzZ8vf3187duxQw4YNZYzR9OnTNWbMGHXq1EmSNHfuXAUEBGjhwoUaOHBgVpQNAAAA3Dey1Rz+mJgYSVL+/PklSYcPH1Z0dLRatmxp7ePu7q5GjRpp69atqY4RHx+v2NhYmxsAAADwoMo2gd8Yo+HDh+uhhx5SxYoVJUnR0dGSpICAAJu+AQEB1mX/NWXKFPn4+FhvhQsXztzCAQAAgGws2wT+559/Xr///rsWLVqUYpnFYrG5b4xJ0ZZs9OjRiomJsd6OHTuWKfUCAAAA94MsncOf7IUXXtCKFSu0efNmFSpUyNoeGBgo6daR/qCgIGv7mTNnUhz1T+bu7i53d/fMLRgAAAC4T2TpEX5jjJ5//nktXbpUGzduVEhIiM3ykJAQBQYGav369da2hIQERUREqH79+ve6XAAAAOC+k6VH+AcPHqyFCxfq22+/lbe3t3Vevo+Pjzw8PGSxWDR06FCFhYWpVKlSKlWqlMLCwuTp6anu3btnZekAAADAfSFLA//MmTMlSY0bN7Zpnz17tvr06SNJGjFihOLi4jRo0CBdvHhRderU0bp16+Tt7X2PqwUAAADuP1ka+I0xd+xjsVgUGhqq0NDQzC8IAAAAcDLZ5iw9AAAAAByPwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxAj8AAADgxAj8AAAAgBMj8AMAAABOjMAPAAAAODECPwAAAODECPwAAACAEyPwAwAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxAj8AAADgxAj8AAAAgBMj8AMAAABOjMAPAAAAODECPwAAAODECPwAAACAEyPwAwAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxAj8AAADgxAj8D5jNmzerffv2Cg4OlsVi0fLly22WL126VK1atZKvr68sFot2796drnEvXbqkwYMHKygoSLly5VK5cuW0atUqx+8AAAAA7ELgf8BcvXpVVapU0YwZM9Jc3qBBA73xxhvpHjMhIUEtWrTQkSNH9M0332jfvn365JNPVLBgQUeVDQAAgAwi8D9gWrdurUmTJqlTp06pLn/qqac0duxYNW/ePN1jfv7557pw4YKWL1+uBg0aqGjRonrooYdUpUoVR5UN3Hcy49u0pUuXqmbNmsqbN6+8vLxUtWpVzZ8/P3N2AADgNAj8uGsrVqxQvXr1NHjwYAUEBKhixYoKCwtTYmJiVpcGZJnM+DYtf/78GjNmjH755Rf9/vvv6tu3r/r27au1a9c6qmwAgBNyzeoCcP/7559/tHHjRvXo0UOrVq3SgQMHNHjwYN28eVNjx47N6vKALNG6dWu1bt06zeVPPfWUJOnIkSPpHrNx48Y294cMGaK5c+dqy5YtatWqVUbKBAA8ADjCj7uWlJQkf39/ffzxx6pRo4a6du2qMWPGaObMmVldGuC0jDHasGGD9u3bp4YNG2Z1OQCAbIwj/LhrQUFBcnNzk4uLi7WtXLlyio6OVkJCgnLmzJmF1QHOJSYmRgULFlR8fLxcXFz04YcfqkWLFlldFgAgGyPw4641aNBACxcuVFJSknLkuPWl0f79+xUUFETYBxzM29tbu3fv1pUrV7RhwwYNHz5cxYsXTzHdBwCAZAT+B8yVK1d08OBB6/3Dhw9r9+7dyp8/v4oUKaILFy4oKipKJ0+elCTt27dPkhQYGKjAwEBJUq9evVSwYEFNmTJFkvTcc8/p/fff15AhQ/TCCy/owIEDCgsL04svvniP9w5wfjly5FDJkiUlSVWrVtXevXs1ZcoUAj8AIE3M4X/AbN++XdWqVVO1atUkScOHD1e1atWsP65dsWKFqlWrprZt20qSunbtqmrVqmnWrFnWMaKionTq1Cnr/cKFC2vdunWKjIxU5cqV9eKLL2rIkCEaNWrUPdwz4MFkjFF8fHxWlwEAyMY4wv+Aady4sYwxaS7v06eP+vTpc9sxNm3alKKtXr162rZt211WBziPzPg2bcqUKapZs6ZKlCihhIQErVq1SvPmzeMH8gCA2yLw3wNRUVE6d+5cVpfxQNu7d29Wl4AHzPbt29WkSRPr/eHDh0uSevfurTlz5mjFihXq27evdXnXrl0lSePGjVNoaKikW+8dyb+LkW6du3/QoEE6fvy4PDw8VLZsWX3xxRd68skn78EeAQDuVwT+TBYVFaUyZcvpety1rC4FwD2UGd+mTZo0SZMmTXJAdYDzunz5sl5//XUtW7ZMZ86cUbVq1fTuu++qVq1aqfbftGmTzYfzZHv37lXZsmUzu1zgniDwZ7Jz587petw1FWj3ktwKFM7qch5Ycf9sV8xPX2R1GchEfJOWPfBtGrJa//799eeff2r+/PkKDg7WF198oebNm+uvv/5SwYIF01xv3759ypMnj/W+n5/fvSgXuCcI/PeIW4HCcg8smdVlPLBunD+W1SUgE/FNGgBJiouL05IlS/Ttt99aL0gXGhqq5cuXa+bMmbf9hszf31958+a9R5UC9xaBH8B9j2/Ssg++TUNWunnzphITE5UrVy6bdg8PD23ZsuW261arVk3Xr19X+fLl9dprr6U6zQe4XxH4ATgNvknLenybhqzk7e2tevXqaeLEiSpXrpwCAgK0aNEi/frrrypVqlSq6wQFBenjjz9WjRo1FB8fr/nz56tZs2batGmT9VsC4H5H4AcAAE5j/vz56tevnwoWLCgXFxdVr15d3bt3186dO1PtX6ZMGZUpU8Z6v169ejp27JjeeustAj+cRpZeeGvz5s1q3769goODZbFYtHz5cpvlxhiFhoYqODhYHh4eaty4sfbs2ZM1xQIAgGyvRIkSioiI0JUrV3Ts2DH99ttvunHjhkJCQtI9Rt26dXXgwIFMrBK4t7I08F+9elVVqlTRjBkzUl0+bdo0hYeHa8aMGYqMjFRgYKBatGihy5cv3+NKAQDA/cTLy0tBQUG6ePGi1q5dqw4dOqR73V27dikoKCgTqwPurSyd0tO6dWu1bt061WXGGE2fPl1jxoxRp06dJElz585VQECAFi5cqIEDB97LUgEAwH1g7dq1MsaoTJkyOnjwoF555RWVKVPGeqG70aNH68SJE5o3b54kafr06SpWrJgqVKighIQEffHFF1qyZImWLFmSlbsBOFS2ncN/+PBhRUdHq2XLltY2d3d3NWrUSFu3bk0z8MfHxys+Pt56PzY2NtNrBQAA2UNMTIxGjx6t48ePK3/+/OrcubMmT54sNzc3SdKpU6cUFRVl7Z+QkKCXX35ZJ06ckIeHhypUqKDvv/9ebdq0yapdABwu2wb+6OhoSVJAQIBNe0BAgI4ePZrmelOmTNH48eMztTYAAJA9denSRV26dElz+Zw5c2zujxgxQiNGjMjkqoCslaVz+NPDYrHY3DfGpGj7t9GjRysmJsZ6O3aMU8QBAADgwZVtj/AHBgZKunWk/98/nDlz5kyKo/7/5u7uLnd390yvDwCAB1FUVJTOnTuX1WU80Pbu3ZvVJeA+k20Df0hIiAIDA7V+/XpVq1ZN0q15dhEREZo6dWoWVwcAwIMnKipKZcqW0/W4a1ldCgA7ZGngv3Llig4ePGi9f/jwYe3evVv58+dXkSJFNHToUIWFhalUqVIqVaqUwsLC5Onpqe7du2dh1QAAPJjOnTun63HXVKDdS3IrUDiry3lgxf2zXTE/fZHVZeA+kqWBf/v27WrSpIn1/vDhwyVJvXv31pw5czRixAjFxcVp0KBBunjxourUqaN169bJ29s7q0oGAOCB51agsNwDS2Z1GQ+sG+f5fSLsk6WBv3HjxjLGpLncYrEoNDRUoaGh964oAAAAwIlk+7P0AAAAAMg4Aj8AAADgxAj8AAAAgBMj8AMAAABOjMAPAAAAODECPwAAAODECPwAAACAEyPwAwAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxAj8AAADgxAj8AAAAgBMj8AMAAABOjMAPAAAAODECPwAAAODECPwAAACAEyPwAwAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxAj8AAADgxAj8AAAAgBMj8AMAAABOjMAPAAAAODECPwAAAODECPwAAACAEyPwAwAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADgxAj8AAADgxAj8AAAAgBMj8AMAAABOjMAPAAAAODECPwAAAODECPwAAACAEyPwAwAAAE6MwA8AAAA4MQI/AAAA4MQI/AAAAIATI/ADAAAATozADwAAADix+yLwf/jhhwoJCVGuXLlUo0YN/fTTT1ldEgAAAHBfyPaB/8svv9TQoUM1ZswY7dq1Sw8//LBat26tqKiorC4NAAAAyPayfeAPDw/X008/rf79+6tcuXKaPn26ChcurJkzZ2Z1aQAAAEC255rVBdxOQkKCduzYoVGjRtm0t2zZUlu3bk11nfj4eMXHx1vvx8TESJJiY2Mzr9DbuHLlyq26og8qKeF6ltQA6cb5Y5KkHScTdSXBZHE1D7Z955Ik3XptOOp1yess++C1lj1kxusseTyJ11pW43WWfWTWay29krdpzB2eByYbO3HihJFkfv75Z5v2yZMnm9KlS6e6zrhx44wkbty4cePGjRs3btweiNuxY8dum6mz9RH+ZBaLxea+MSZFW7LRo0dr+PDh1vtJSUm6cOGCChQokOY6cH6xsbEqXLiwjh07pjx58mR1OYDT4rUGZD5eZ0hmjNHly5cVHBx8237ZOvD7+vrKxcVF0dHRNu1nzpxRQEBAquu4u7vL3d3dpi1v3ryZVSLuM3ny5OHNEbgHeK0BmY/XGSTJx8fnjn2y9Y92c+bMqRo1amj9+vU27evXr1f9+vWzqCoAAADg/pGtj/BL0vDhw/XUU0+pZs2aqlevnj7++GNFRUXp2WefzerSAAAAgGwv2wf+J598UufPn9eECRN06tQpVaxYUatWrVLRokWzujTcR9zd3TVu3LgU070AOBavNSDz8TqDvSzG3Ok8PgAAAADuV9l6Dj8AAACAu0PgBwAAAJwYgR8AAABwYgR+OKU+ffqoY8eO1vuNGzfW0KFDrfeLFSum6dOnW+9HR0erRYsW8vLysl63wWKxaPny5fekXuBB8t/XJwAgcxH4cV9KLTB88803ypUrl6ZNm6Z3331Xc+bMSXP9yMhIDRgwwHr/nXfe0alTp7R7927t379fknTq1Cm1bt06M8oHspU7vZ4AOA4feJEVsv1pOYH0+PTTTzV48GB98MEH6t+//x37+/n52dw/dOiQatSooVKlSlnbAgMDHV4ncD+w9/UEAMjeOMKP+960adP0/PPPa+HChdZwcqcjKP+e0lOsWDEtWbJE8+bNk8ViUZ8+fSQxpQcPpv++nv744w/lyJFD586dkyRdvHhROXLk0BNPPGFdZ8qUKapXr54kKTExUU8//bRCQkLk4eGhMmXK6N13373tNo0xmjZtmooXLy4PDw9VqVJF33zzTebtJJBNhYeHq1KlSvLy8lLhwoU1aNAgXblyxbp8zpw5yps3r1auXKkyZcrI09NTjz/+uK5evaq5c+eqWLFiypcvn1544QUlJiZa10vt/2d58+a97TfhcC4c4cd9bdSoUfrggw+0cuVKNW/ePENjREZGqlevXsqTJ4/effddeXh4OLhK4P6Q2uupYsWKKlCggCIiItS5c2dt3rxZBQoU0ObNm63rbdq0SY0aNZIkJSUlqVChQvrqq6/k6+urrVu3asCAAQoKClKXLl1S3e5rr72mpUuXaubMmSpVqpQ2b96snj17ys/Pzzou8CDIkSOH3nvvPRUrVkyHDx/WoEGDNGLECH344YfWPteuXdN7772nxYsX6/Lly+rUqZM6deqkvHnzatWqVfrnn3/UuXNnPfTQQ3ryySezcG+QnRD4cd9avXq1vv32W23YsEFNmzbN8Dh+fn5yd3eXh4cH03jwwErr9WSxWNSwYUNt2rRJnTt31qZNm9S7d2/NnTtXf/31l0qXLq2tW7dq2LBhkiQ3NzeNHz/eun5ISIi2bt2qr776KtXAf/XqVYWHh2vjxo3WbwmKFy+uLVu26KOPPiLw44Hy75NLhISEaOLEiXruuedsAv+NGzc0c+ZMlShRQpL0+OOPa/78+Tp9+rRy586t8uXLq0mTJvrxxx8J/LAi8OO+VblyZZ07d05jx45VrVq15O3tndUlAfet272eGjdurI8//liSFBERoYkTJ+rw4cOKiIhQTEyM4uLi1KBBA2v/WbNm6dNPP9XRo/+vvfsPqer+4zj+PG6i5E0skJS6S0Obv7ppZa6fmmS2ILKIhA1Wa/sjrGSV9E+4Sb+kwjYqszBapv1hJUSxVdplyv7ZprXLaNf1w34Y5DIyLSq73brfP8JLt3QkX8s8vR5w/jifc87n8z4XDr7O534uXufRo0e4XC4SExO7HdfpdNLZ2UlGRoZPu8vlIikpqe9vVOQd9ssvv7B582acTif37t3D7XbT2dnJgwcPCAoKAmDQoEHesA8wbNgwIiIisFgsPm2tra1vvX55d2kNvwxYw4cPp66ujpaWFmbPns39+/f7uySRAeu/nqe0tDT+/vtvLl++zPnz55k2bRqpqanU1dVRW1vL+PHjvS8Ihw8fZtWqVSxdupTq6mocDgdffvklLper23GfPXsGwE8//YTD4fBuTqdT6/jlvXL9+nXmzJlDQkICVVVVnD17luLiYuD5rH4Xf39/n+sMw+i2revZ6tr3eDw+57zYp5ifAr8MaB999BF1dXW0trYya9Ys7t27198liQxYPT1PXev4N27cyNixYwkODvYJ/C8uu/n111+ZPHkyOTk5JCUlERUVRVNTU49jxsXFERAQQHNzM1FRUT6b1Wp94/cs8q5oaGjA7XZTVFTEJ598wujRo7l582af9B0aGkpLS4t3/9KlSzx8+LBP+paBQYFfBrwRI0ZQW1vLnTt3mDVrFh0dHf1dksiA1d3z1LWOv6KigrS0NOD5EiCXy4Xdbve2AURFRdHQ0MDp06e5ePEi+fn51NfX9zje4MGDycvLY9WqVZSVldHU1MSff/5JcXExZWVlb/huRfpHR0eHzzdaDoeD0NBQ3G43O3fu5MqVK5SXl7Nnz54+GS89PZ1du3Zx7tw5GhoaWLZs2SvfCoi5KfCLKXQtR2hvbycjI4P29vb+LklkwOrueZoxYwZPnz71hnvDMJg2bRoAU6dO9V67bNkyFixYQHZ2NikpKdy5c4ecnJz/HG/Dhg18++23FBYWEhsbS2ZmJidOnCAyMvKN3aNIf6qtrSUpKcln279/P9u3b2fLli0kJCRw6NAhCgsL+2S8oqIirFYr06dP57PPPiMvL49Bgwb1Sd8yMBielxd1iYiIiIiIaWiGX0RERETExBT4RURERERMTIFfRERERMTEFPhFRERERExMgV9ERERExMQU+EVERERETEyBX0RERETExBT4RURERERMTIFfRET6TUFBAYmJif1dhoiIqSnwi4iY3L///svKlSsZNWoUAQEBWK1W5s6di91uf6t1GIbBsWPHfNry8vLeeh0iIu+bD/u7ABEReXOuXbvGlClTCAkJYevWrdhsNp48ecLp06dZvnw5//zzT7/WZ7FYsFgs/VqDiIjZaYZfRMTEcnJyMAyDP/74g4ULFzJ69Gji4+NZvXo1v/32GwDNzc3MmzcPi8VCcHAwixYt4tatW94+lixZQlZWlk+/33zzDWlpad79tLQ0cnNzWbt2LUOHDiUsLIyCggLv8YiICADmz5+PYRje/e6W9Pz444/ExsYSGBhITEwMu3fv9h5zuVysWLGC8PBwAgMDiYiIoLCw8P/+nEREzEyBX0TEpNra2jh16hTLly8nKCjoleMhISF4PB6ysrJoa2ujrq6OmpoampqayM7O7vV4ZWVlBAUF8fvvv7N161bWr19PTU0NAPX19cDzMN/S0uLdf1lpaSnr1q1j06ZNNDY2snnzZvLz8ykrKwNgx44dHD9+nMOHD3PhwgUqKiq8Lw8iItI9LekRETGpy5cv4/F4iImJ6fGcM2fO8Ndff3H16lWsVisA5eXlxMfHU19fT3Jy8muPZ7PZ+O677wCIjo5m165d2O12MjIyCA0NBZ6/ZISFhfXYx4YNGygqKmLBggUAREZG4nQ62bt3L4sXL6a5uZno6GimTp2KYRiMHDnytesTEXlfaYZfRMSkPB4P8PzHsj1pbGzEarV6wz5AXFwcISEhNDY29mo8m83msx8eHk5ra+trX3/79m1u3LjBV1995V3bb7FY2LhxI01NTcDz5UUOh4OPP/6Y3Nxcqqure1WjiMj7SDP8IiImFR0djWEYNDY2vrIGv4vH4+n2heDFdj8/P+/LQ5cnT568co2/v7/PvmEYPHv27LXr7Tq3tLSUlJQUn2MffPABAOPGjePq1aucPHmSM2fOsGjRImbOnMnRo0dfexwRkfeNZvhFRExq6NChZGZmUlxczIMHD1453t7eTlxcHM3Nzdy4ccPb7nQ66ejoIDY2FoDQ0FBaWlp8rnU4HL2ux9/fn6dPn/Z4fNiwYQwfPpwrV64QFRXls0VGRnrPCw4OJjs7m9LSUiorK6mqqqKtra3X9YiIvC80wy8iYmK7d+9m8uTJTJw4kfXr12Oz2XC73dTU1FBSUoLT6cRms/H555/zww8/4Ha7ycnJITU1lQkTJgCQnp7Otm3bOHjwIJMmTaKiooLz58+TlJTUq1oiIiKw2+1MmTKFgIAAhgwZ8so5BQUF5ObmEhwczKeffsrjx49paGjg7t27rF69mu+//57w8HASExPx8/PjyJEjhIWFERIS0hcfl4iIKWmGX0TExCIjIzl37hwzZsxgzZo1JCQkkJGRgd1up6SkxPvPsIYMGcL06dOZOXMmo0aNorKy0ttHZmYm+fn5rF27luTkZO7fv88XX3zR61qKioqoqanBarX2+LLw9ddfs2/fPg4cOMCYMWNITU3lwIED3hl+i8XCli1bmDBhAsnJyVy7do2ff/4ZPz/9ORMR6YnheXlhpoiIiIiImIamRERERERETEyBX0RERETExBT4RURERERMTIFfRERERMTEFPhFRERERExMgV9ERERExMQU+EVERERETEyBX0RERETExBT4RURERERMTIFfRERERMTEFPhFREREREzsf5/XhKdG4vilAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 3: Set up the figure and axes with increased figsize\n",
    "fig, ax = plt.subplots(figsize=(9, 7))\n",
    "\n",
    "# Step 4: Create the bar plot for prevalence\n",
    "x_pos = np.arange(len(counties))\n",
    "bar_width = 0.45\n",
    "\n",
    "# Specify custom colors for the bars\n",
    "prevalence_colors = ['red', 'green', 'blue']\n",
    "severity_colors = ['orange', 'purple', 'yellow']\n",
    "\n",
    "ax.bar(x_pos - bar_width/2, prevalence, bar_width, label='Prevalence (%)', edgecolor='black')\n",
    "\n",
    "# Step 5: Create the bar plot for severity\n",
    "ax.bar(x_pos + bar_width/2, severity, bar_width, label='Severity (%)', edgecolor='black')\n",
    "\n",
    "\n",
    "# Step 6: Set the axis labels, title, and legend\n",
    "ax.set_xlabel('Counties')\n",
    "ax.set_ylabel('Disease Prevalence and Severity (%)')\n",
    "ax.set_title('Prevalence and Severity scores for LY symptomatic plants')\n",
    "ax.set_xticks(x_pos)\n",
    "ax.set_xticklabels(counties)\n",
    "ax.legend()\n",
    "\n",
    "# Set the y-axis limits\n",
    "ax.set_ylim(0, 90)\n",
    "\n",
    "#Step 7: Add percentage labels on top of each bar\n",
    "for i, v in enumerate(prevalence):\n",
    "    ax.text(i - bar_width/2, v + 0.5, str(v), color='black', ha='center')\n",
    "\n",
    "for i, v in enumerate(severity):\n",
    "    ax.text(i + bar_width/2, v + 0.5, str(v), color='black', ha='center')\n",
    "\n",
    "# Display the plot\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5b7a2ba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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