numpy_12_22_es_alumno.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introducción a NumPy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numpy es una potente librería para realizar operaciones científicas y matemáticas en Python. Es ampliamente utilizada en el mundo de la ciencia de datos y el aprendizaje automático."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numpy nos proporciona un tipo de datos llamado array, que es una estructura de datos que nos permite almacenar y manipular datos de forma eficiente para trabajar con grandes cantidades de datos.\n",
    "\n",
    "Numpy nos proporciona tambien una amplia colección de funciones matemáticas y estadísticas para trabajar con arrays, que están implementadas en C, lo que las hace muy eficientes. Esto hace que sea mucho más ráìdo realizar operaciones con arrays que con las listas de Python. Numpy tambien soporta operaciones vectorizadas, lo que significa que podemos realizar operaciones sobre arrays sin necesidad de utilizar bucles, aumentando la eficiencia de nuestro código aún más.\n",
    "\n",
    "Numpy es una librería open source, lo que significa que la podemos obtener de forma gratuita utilizarla en nuestros proyectos. Esto hace que sea una herramienta muy popular entre los científicos de datos y los desarrolladores de software."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Numpy Arrays (ndarray)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los arrays de Numpy son mucho más eficientes que las listas de Python para almacenar y manipular datos.\n",
    "\n",
    "1. Los arrays de Numpy son homogéneos, esto significa que todos los elementos de la array deben ser del mismo tipo, al contrario de las listas de Python que pueden contener elementos de diferentes tipos. Esto hace que los arrays de Numpy puedan almacenar datos de una forma más compacta, lo que los hace más eficientes, ya que conoce de antemano el tipo de datos que va a utilizar.\n",
    "\n",
    "2. Los arrays de Numpy son estáticos, esto significa que una vez que se crea un array, no se puede modificar su tamaño. Esto permite a Numpy reservar la memoria necesaria para el array en bloques contíguos de memoria, que hace que sea más eficiente acceder y modificar los elementos del array. Las listas de Python por el contrario, son dinámicas, lo que significa que pueden crecer o reducirse de tamaño dinámicamente, lo que hace que sean más lentas que los arrays de Numpy.\n",
    "\n",
    "3. Los arrays de Numpy se integran de forma muy sencillacon el resto de librerías de Python, como Pandas, Matplotlib, Scikit-Learn, etc. que son ampliamente utilizadas en el mundo de la ciencia de datos y el aprendizaje automático. Esto nos permite crear potentes flujos de trabajo de forma muy sencilla, donde los arrays de Numpy son facilmente convertidos en Dataframes de Pandas on ser pintados con Matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3 4 5]\n"
     ]
    }
   ],
   "source": [
    "# Crea un nuevo array de 5\n",
    "a = np.array([1, 2, 3, 4, 5])\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hemos creado un array a partir de una lista de Python.\n",
    "\n",
    "Podemos observar que el tipo de datos de la array es ndarray (N-dimensional array), que es el tipo de datos de las arrays de Numpy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# imprime el tipo de dato del array\n",
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_1 = [1,2,3,4,5]\n",
    "type(a_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2],\n",
       "       [3, 4]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Crear un array de 4 elementos de 2x2\n",
    "b = np.array([[1,2],[3,4]])\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6]])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Crear un array de 6 elementos de 2x3\n",
    "c = np.array([[1,2,3],[4,5,6]])\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[ 1,  2],\n",
       "        [ 3,  4],\n",
       "        [ 5,  6]],\n",
       "\n",
       "       [[ 7,  8],\n",
       "        [ 9, 10],\n",
       "        [11, 12]]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Crear un array de 12 elementos de 2x3x2\n",
    "d = np.array( [ [ [1,2],[3,4],[5,6] ], [[7,8],[9,10],[11,12]]])\n",
    "d"
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![EA8ED1DC-6E92-4FDB-94B0-76A2BFC2A5CE.jpg](attachment:EA8ED1DC-6E92-4FDB-94B0-76A2BFC2A5CE.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[[ 1,  2],\n",
       "         [ 3,  4],\n",
       "         [ 5,  6]],\n",
       "\n",
       "        [[ 7,  8],\n",
       "         [ 9, 10],\n",
       "         [11, 12]]],\n",
       "\n",
       "\n",
       "       [[[13, 14],\n",
       "         [15, 16],\n",
       "         [17, 18]],\n",
       "\n",
       "        [[19, 20],\n",
       "         [21, 22],\n",
       "         [23, 24]]]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Crear un array de 2x2x3x2\n",
    "d= np.array([[[[1,2],[3,4],[5,6]],[[7,8],[9,10],[11,12]]],[[[13,14],[15,16],[17,18]],[[19,20],[21,22],[23,24]]]])\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[[ 1  2  3]\n",
      "   [ 4  5  6]\n",
      "   [ 7  8  9]]\n",
      "\n",
      "  [[10 11 12]\n",
      "   [13 14 15]\n",
      "   [16 17 18]]]\n",
      "\n",
      "\n",
      " [[[ 1  2  3]\n",
      "   [ 4  5  6]\n",
      "   [ 7  8  9]]\n",
      "\n",
      "  [[10 11 12]\n",
      "   [13 14 15]\n",
      "   [16 17 18]]]]\n",
      "4\n"
     ]
    }
   ],
   "source": [
    "d_1_3d = np.array( [[[1,2,3],[4,5,6],[7,8,9]] , [ [10,11,12],[13,14,15],[16,17,18]]])\n",
    "d_1_3d\n",
    "\n",
    "\n",
    "d_2_3d = np.array( [[[1,2,3],[4,5,6],[7,8,9]] , [ [10,11,12],[13,14,15],[16,17,18]]])\n",
    "d_2_3d\n",
    "\n",
    "\n",
    "d_4d = np.array([d_1_3d,d_2_3d])\n",
    "print(d_4d)\n",
    "print(d_4d.ndim)"
   ]
  },
  {
   "attachments": {
    "54B0598B-506D-4C1A-BC48-D253169B7D57.jpg": {
     "image/jpeg": 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qzmqc4zbdNpS91Jqzakvw+7ePoZniqmDwkq9JRc1KMUppuPvX6Jpv5P77HxP+yp/wW11W7/4I/a1/wUr/AGt/DfhhPEGia54j0C38G/CzT9S0XTvEmtW9+un+GdE0+PW9W8QXNlNqM7YvL6e8nht4lklEQIVG7cVkqWbRy7CylytRbnUs3FWvKTtZO3RJeV5XblyYfNW8uljsRGN05JQppq7vZJJtv53l6Lc/EGH/AIOUP+CyfiPwlqX7Xvhf9g74fSfsTeHfELWet+IovA/xE1DSINOS7WGWyuvioPFENtHqMKlYJ9Vt/CzaXa3bgT2xUhK9p8O5PGSwk8dUWNcbxj7SmpN7p+ycHo10507aq9ry8pZ5mcoyxMMHB4WMrNqE3pe1vac1k+75bLe715f7DP8Agnj+3R8NP+Cif7LXgH9pr4ZWlzo1h4piuNP8ReFr+4jur/wl4t0pkh1zQLi6iSKO8W1uGDW15HFGlzbvHIFBLqvyOYYGpl+KqYao1Ll1jNbTg/hklra6/pbH02DxUMZh4V4Jx5tJRe8ZLeL9D7eriOoKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD//0f7+KAP4+f8Ag6z+D37c/wC0N4a/Zm+E/wCzH8IPjp8YvhfJqHivxP8AEzw58IvA/iHxbpZ8QaYmnw+FbjxU2g2Vyy/ZluL+XTLa8dYPPVrhI2miR0+u4WrYLDyxFbE1aFKraMacqs4wai+bmUOa97tK9raaXd7HzfENLFVo0KdCnVqQvKU404zkm1pG/KmtL395ryT0Z/Prqfx//wCC8PwE/YL8Yfsk6p+xV4y+EX7IGm/DvxBoHjq/vf2PNb8NPZ+F9UhlfxJ4k8SeO7uFGTVrlZHnv/Ed9++GyP7sUMaJ7yw+R18dDFLGxq4tzi6a+txl7y+GMad46dOVPu3a7Z4zrZtQwUsN9VlTwypyhJ/VmrRktZSnpq31a+5WUep/4N4P2lP+Cmfws+JXhj4W/sofCjXvGP7KnxC+PHgZP2ivGWnfBa98d6d4XtZQtjePfeOrdTB4QVNDkubgtO4Eap9qO4JS4hw+W1acqmKqqGKp0Z/V4Ot7Pn6q0Pt6rom+l9Uo1ktfHQnGnh6cpYedaHtpeyclHvedvdunrvbR3VmpfTfxa/5W1PCX/ZwXwr/TwlplcsP+SUn/ANeKv/pxm0/+Sjp/9faP/pDP9DnWdb0bw5pd9rniDVtN0PRtMtpbzUdW1e+ttN02wtIEMk1zeX15LDbW0EUas8ks0qIiqSzKBmvz9RcmoxTk3okk236Jas+0bSTbaSWrbdkl3b6f12P83/8A4LlftT+H/wDgrr/wU9/Zz/Zc/ZGmHxP8OfDnWrb4ZaT4q8Pj7bpXijxn4m8Q2Eni7UtFukTZc+HPD1lpsUUmrBmsp2ivJ4pWtokmf9EyTCyynLcRicX+7lUi6ji/ijCMfdTWnvNu/Ktdet0j4jNcRHMswo4fDP2ipv2alHVSnJrn5XezSta/urfvc/0XPhn4Pi+Hnw48AeAYJRPD4I8FeFvCMc6rsE6eHNDsdHE4Xnb5ws/Mxnjdjmvz2rP2lSpP+ecpf+BSbPtoR5IQh/JGMf8AwFJeXbt9x/KD/wAHh0njBf2JfgNHpZux4Pk+PNr/AMJP5PmfZjeL4a1g6GLvZ8u37VuMIlO3zgmMvtr6rhHk+u1725/Ye5f/ABK/562181tL53iXn+q0bfB7Zc3ryvlvbW17f1c/TH/g38sf2bx/wSf/AGfD8IofBsljdeFdVPxoa3TTmu5viEb+/HilPHBcb2u1tRbqqalmJdJFt5QEB+bzM/eI/tXEe257qa9jvbksnH2fZX00vqvlHvydUP7Po+y5Gmn7W3Wd/e59tbWun073ufxzfs4W/wAE7X/g500O3/Z3GjD4QxftaX6+GF8OeR/wjyXH2FT4jTQvsv8Aoo0pPEx1dbMWv+irGuLb9yEr7DEe3fDU3iOb2v1T3ubSW9o83Xm5VG9/Luz5ih7L+34+xUVS+tPl5fh+F81vLmv3VrWtex61/wAFqfBHh/4lf8HHHwo8BeK7KLUvDXizXP2aND1zT50EkF9pt9rdzDdWs0bYV4po2MciE4dCVOATWGSzlT4drVIO0orEuLTs0+VWs9ba21/Lc2zSmqmd0oS2lKhFre6b2f4fl1P9D3xrpOmaD8JfF2iaLp9npWj6R8PPEOm6Xpmn28VpY6fp9l4bvLazsrO1hVIbe2toI0hghiRUjjRUUAAV8BBuVWEpNtupFtvVtuWre+r9fvPs5JRpuKSSUGklokktkf5+X/BrN8L/AAV4z/4Kc/tP+NPE2habrOt/DfQvGt/4RuNRsoLw6NqOseOdSsLrUbDz1kFtfC2Hlx3USiaNWYI65JX7ziarOnlmEhGTSqzSlZ2uowvZ+WvftvofHcP04yx2InJJun7Rxur2cqklddnpvf7z6c/4PJ5PE/8Ab37F0V2b0fDwx+M2uPJL/Zjrv2m3FwWAIj+1DSdxi3ndjGMjNc/CHLbGNa1Pct6Wdr7aX8/uujfibm5sJvye/tb4v/2dun3H9RP7DWnfskf8Ozfg9b+CLf4cP+zZN8AtNfxSFj0RvC8tm3htT40k8TFwbVtRF5/aB1R9TP2xbgAyMGVK+Zxrxf8AaVbndX6x9Yaj8XN8XucvXa1krei0R7+EWG+oUuTk9h7H3tFy25fe5tlfe9/x1Z/ED/wb3R/D6L/gux47j+E5hb4ZRj46J4DNuc2p8LrqUo0r7Iec2n2fb9lwdvkeXtyu2vtM/wDaf2HT9r/EvQ5+/Nyrmb31ve/nq7NtHymTcn9rT9l/D5qvJ25Vpp5Xv+fU9H/4KA+JNE+HX/B0V8O/FnjXULfw74dsvit8HLy71fU5EtbG3tL3S5bO3uZriUpFHA9xNHGZXcIpbJwAajARlU4YqQgnKTp1Ukt9JJvTW+nZP5XvHTGyjTz+nKb5YqpSbb0SVt/S7tf8tZR/og/4OlfH3g7Rf+CU3jHQ9S8RaVb6v478f/D+38Iacb23a78QvbX0t7cvpUQffeQwWjLcSzQ7o0iZXLYZTXz3DMJvNYSUZONOFRzdnaOiSv5tu1tz2eIJxWXyTkryqU+VX1lvt336f5H5wf8ABOL4Efs9ftMf8G4M/wAFP2j/AI1eDf2ffCfjL4h+ME8N/FHxxr2keH9D8O+ObDWFuvDc1xcaze2FrdxPdAx3Ngtyk1xbu/lBpFUL6WYV8RhuIVWw9GeIlCEealCLk5Qa12u0+qdvLW7OLA0aNfJXSrVY0YznJRqTaSU+a8d99Vqrx730Py60/wCAv/BdD/glX+z/AK94s+A/xB+GX7UP/BPm3iv/ABPqVx4I1P4dftEfs6+IvCst2BqGs6n4C8VWja3pukXrxo2rHSYkhin+ea4fYs9ek6+SZniIwxFOrhcfflSnGph8RGa2ipxcouWrtfp3slHz1RzbL6LlSqQxGCs5NxdOtQkna7dOSckrr3kuXV2u7Ll/rl/4IKft+fD/APb4/ZAu/Fnhr4J/Dz4BeNfAfiqTwx8S/BHwq8O6b4Z8B3viCS1S5i8T+H9M022tVt4NZgHmz21ws09pMDD9pmTY1fJ57gKmBxfLKtUrwqQUqc6s3Oaj/JJu9+Xa/XfS9j6PJ8ZDGYbmjSp0Zwly1IUoqMOa26S01tr20P3ErxT1goAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP/9L+/igAoA+PP+CgHwJ8a/tN/sY/tHfAL4cz6HbeOfit8LPFHg3wxP4mvrnTdBi1fWNPltrRtVv7Ox1K5tbMSOPOmhsbp0XJWJ+RXXgK8MNjMNXqc3s6VWM58qTlyp62TaTfbVa9Vuc2MpSr4WvRhbnqU5QjzO0btW1aUml6J/ifl1/wb5f8ExP2j/8AgmB8Cvjb8OP2j9S+Gepa/wDEL4i6L4q0F/hl4m1jxNpsem6foc2nTrqFxrHhnwzLb3f2iUeXFFbToY8sZQfkX1c/zPD5nVo1MOqiVOEoy9pBQd27qyUp9PM4MmwFfAUasK/JzTmpLkk5KyTWt0rP5y+WiPxu/wCCof8Awbxf8FIP2rf+Chnxk/a1/Z38efAzwf4b8Y6r4d1LwZqmq/Fbxv4P8d6VNpGgWGmTXDf8I/4A1BtLuVubeQwS2WsSP5ZV/MQkrXr5ZxDl2FwFLCYinXnKCkppUoVKck5OX2qsb79YLbY8vH5LjcRjKmIoypKMuXlbqSjJcqtfRafJvtpZyl8nx/8ABsH/AMFnviVLF4a+L37Xvwz/AOENu5o11E6z8fvjf8QrRIS48yQ+G77wpZW98yLkrDJPErn5TIoOa6XxLk1P36ODqc62SoUKd/8At5Sk/wDK/W/u839g5pVajVxEOTrevVmvXls+a3a6/E/pq/4JIf8ABBj9nL/gl2JviNLrU/xv/aU1bTG0y/8Aitrukw6VpvhWwuU232j/AA78Oia7/sS1ux+6vNVvLq81i9gXyfOtLd5bdvm82zzEZn7lvY4dO6pRd3JrZ1JaczW6SSSv10Pey7KKGX/vL+1rtcrqNWUV2px6J93Z/e1L9368M9c+QP26v2LvhP8At+fs0/EH9mj4wQ3Efh3xpYo2ma/p6RNrHhHxNYOLrQfFGjmUFPt2k36RXAicrHcxLJbTZilcV2YHG1cBiaeJo/FB6xe04vSUXvpJafjpZM5sXhaeMoToVNprRrVxkvhkvNPXp87WP4c9M/4NWv8Agqx8O/H2v/Dr4VftU/Dbw98CfFF+1prfjTQfij8TPBp1vw40uzzPEvwv0XSlTUtUFo2JNOfVLywklDRrqKwsC32r4oyupTjVq4WpLERTag6VKajLdctSUnpe2vLHS+iufKLh/Mac3Tp4iEaMm7zVSpDmi/5qSveVvOSeq0TUj7E/Yn/4Nnv2sf2Lv+ClfwQ+P+h/EP4SeN/2dPhH4z0LX7nXNU8T63pvxO1yCLRYl1y5j8HweD59Hs3bW5btdOsW8Tzn7AsDXF2Z2kNceN4kwuMy2vh3TqwxFWEopKEXTjeXurn5oyfu2v7m7drWXN04XIsThcfRrKdOdClNScnJ+0fu2do2SWt7K7031ufWf7dv/BEj9sX9pD/gsr8Lv29fh/rHwWt/gh4O8QfBXVNWsvEfjTxDp3jtrb4f6pLe66LPQrTwXqWmzSyROosFfXIRcPxK9uMMvLgM6weGyergaire2mq1nGEXT99JRvLni1qtVyv/ABa3OrFZXia2Z08ZB0vZQlSbUpSU2oO7tGzXpeSv22R/Vj4x0q517wj4p0OyMS3ms+HNc0q0ad2jgW51HTLqzgMzqkjJEJZkMjqjsqZIRiAtfLQajOMnspRb9E7+X5/ce/JNxklu4tK/drQ/l5/4IZf8EY/2uv8AgnR+1f8AtHfGr4/av8HL/wAH/FbRtU0/wxD8PPGOv+IdainvPFt7rkR1Wz1Xwf4et7WMWdwiu0N5clZ8xhXUeZX0ud5xhMwwmGoUFWU6MuaftKcYp+5b3Wqk29ejSsurPBynLMTgcRiKtZ0nGqnyqEpSlrNy1vGCWj6c3bzP2A/4Kl/8E1fhd/wU/wD2atS+B3jvU5PCPijSr3/hJPhj8RLSzS+u/Bvi2CFo4bia0Z42vtIvkIttVsVljea3O6KRJUXd5WWZlVyzEqtBc0WuWpC9ueP6Nbpu6utU7WPSzDAU8woOjN8sk+anUSu4SW3a6btdX+7U/jl+HP8Awat/8FULPxLdfBvxF+1T8PPBH7Muo6wH8SX3g/4pfEq903X9IE4825i+EUel6Vpc+sXFuCVg1i8W0hmI8y8nRfm+uqcUZW4qtHC1J4lL3FOlS0dutW90r/yq/wB/u/Mw4fzBS9m8RCFBy97kqVPeXf2fLy82+97dL6o/R/8A4JE/8G+/7V//AATq/wCCilz+0F4u8V/CPxF8AtE0Hxt4b8M3Wk+MNbvviLf6fqsccOj3ureHpPBOmaRaXMqRmW+t7XWp0tS3lwyXO3fXnZtn2FzHL1h4RqxruUJSThFU1bdKXPKT300XfSyjHty3JsTgsb7WUqcqKU1FqTc7NaXjyxS66Jvl/vaM8f8A+Cyv7Fv7Hn/BXr9qzTT+wx+2j8A4/wBu/wAMWV94F8c/AjxdqfiHQP8AhNE8HzN5j2+tx+Hrg6b4p8PAPbyQNbXMF3CNwmidS67ZPjcXlOFl9dwdf6lJ88K8FCXI5rZxvrGVt+aLV7tPSMozTB4fMcRF4XEUli1FxlRm5QVRLW6fK7SVul7+Wx+PP7fv/BFX9qX9iv8AYn1L9on9vX9qq18V+NdC1/w14C+BvwV0Tx/4q+I9lENRncamx1zxgtjb2Frp2nRLLHpHhjTTGikNPdKgCV6+AznC4zGLD4HCuMGpVK9Z04020mraQvdt31lLyV9WeXjcqxGFwjr4zEc04yUKNKM5VFq77ytay6RXfZW5f6If+CPP7BvgP9vD/g370r9mz4xR3+iaJ8R/FHjjWfC/ia0t1k1Pw3rVnrAk0DxRp8EzRR3QtLpCZLZ3WG7t2ljMgyrJ8/m+OqYHPniaNpSpRipRe0ote9F9rrydt7O6PayzCQxmT+xqNxVSUnGS3i07qS3v6adrvY/OJv8Ag3U/4Lk+DfCniD9kn4dfts+Cf+GOtb1KeOfRH+L3j/QvCmoaLcXIeR9R+GUPha/uLeeWMLPeaLY6q+lXNwpDXJDB69D/AFgySpJYqpg5rFxV1L2NOUlJf9PLxXWyk05Lre3vcP8AYmbRhLDQxUPq0m3/ABaija+zp8mney5k3e71vL+sH/gkv/wTI8C/8Etv2Zbb4J+H/E0vj3xr4h1ZvFfxO8evZtp1v4h8TzQrBs0jTXlmksNF06EfZtPhlkM8iZmuMSNtX5bNcyqZnifbSj7OEVy04Xvyx312vJvf7tdz6PLsBDL8OqUXzSb5qk9uaXkt7LbV3e+l0fqLXmHeFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB//9P+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/jc/wCCt3/Buj8dvid+0xfftyf8E1fiJpXw++L2t6vH4q8UeALvxPefDzUbfxpCBv8AFvw88b2KNbaZeagVD3+l6mbK3aYl47wq7pX2GU8Q0KWGWBzGm50UuWNTl9onF392pB30XdOWl9HvH5nMckrVMR9bwM1Co3zSg5cnv/zQmtm+t/Pe6UfgPQ/+CBf/AAW9/wCCgXxO8EJ/wUu/aAvtJ+FPgy7hSfUvG3xd074oeI4NJWRft1t4J8J+FHuNEt9W1G3Qw/2zq1xZyIXElwbgqVruee5LgKUv7Nw96s07KNL2Su9nOU1zWT15VzJ7abx4lk+a42pD69Wapw3c6qnJd1CEbpN927J6q+rP7uf2evgP8PP2Y/gv8OvgP8KtKXR/Afwz8M6d4Z0G1IUzyQWMISW9vZFA86+vp/MuruY8vNK2MKFC/D4ivUxNapXqu86knKXlfot9ErJa/fqfXUaMMPSp0aatCnFRXy6u1rtvVu33Hs1YmoUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/U/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//9X+/igDi/E13OJ47VHZIhGJGCsRvYscFsY6AYA59favJzCpNVI002oqPNZO123bX7ttlvre0e3DQi05NXd7ei/r0/C8uV3t/fb82rzdf5pf+ByOq0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4N7f32/NqNf5pf+ByC0ey+4XzJP77/99N/n/PtRr/NL/wADkFo9l9weZJ/ff/vtqNf5pf8AgcgtHsvuDzJP77/99tRr/NL/AMCkFo9l9weZJ/ff/vtqLvvL/wACfT+vn1C0ey+4PMk/vv8A99tTu+8v/An/AF/WoWj2X3B5kn99/wDvtqLy7v7wtHsvuDzJP77/APfbUXl3f3haPZfcHmSf33/77ai8u7+8LR7L7g8yT++//fbUXl3f3haPZfcHmSf33/77ai8u7+8LR7L7g8yT++//AH21F5d394Wj2X3B5kn99/8AvtqLy7v7wtHsvuDzJP77/wDfbUXl3f3haPZfcHmSf33/AO+2ovLu/vC0ey+4PMk/vv8A99tReXd/eFo9l9weZJ/ff/vtqLvu/vC0ey+4PMk/vv8A99tRd9394Wj2X3B5kn99/wDvtqLy7v7wtHsvuDzJP77/APfbUXb6v/wJr8v6+9haPZfcHmSf33/77ald95f+BP8A4b+vNhaPZfcHmP8A33/76ajXvL/wJ/1936ILR7L7g8x/77/99N/npRr3l/4E/wCvu/RBaPZfcHmP/ff/AL6ajX+aX/gcgtHsvuDzH/vv6febp/ntRr/NL/wOQWj2X3B5j/33/wC+m/z/AIfjRr/NL/wOQWj2X3Cb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3Bvb++35tRr/ADS/8DkFo9l9wb2/vt+bUa/zS/8AA5BaPZfcG9v77fm1Gv8ANL/wOQWj2X3Bvb++35tRr/NL/wADkFo9l9wb2/vt+bUa/wA0v/A5BaPZfcG9v77fm1Gv80v/AAOQWj2X3HQ+Hbudb5bfzGaGZXyjMSAyoWDLnOD8uPcHHHBrvwFSarKnzNxkpXT11SvdarXTs/ldnPiYR5OZJJprXbR/0t/1O9r2TgP/1v7+KAOB8Tf8hBf+veP/ANCevFzD+Ov+vcfzkd+F+B+v+ZztcJ0hQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAGCen+P8An/PpQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAGzoH/ACFbf6S/+inrrwP+8w9J/wDpDMMT/CfrH8z0evdPOP/X/v4oA4HxN/x/of8Ap3T9Gf8Ax9Pzrxsw/jR/wL83/md+F+B+v+Z514v8X+GfAHhbxB428aa5p3hrwl4V0m91zxFr+rXCWum6RpOnQPc3t/e3D4WOC3hRpHPXAwMk4rjp051qkKVKLnUqSUYQjrKUm7JJdW3+fmbznGnCVSbUYQTlKT2SW7eq/P7z47/Z/wD+Cj/7I37TPj+H4Y/Cr4iarc+NNS0e78ReGNI8WeBfG3gL/hOfDtjzd694DuvGGhaPaeLtKgiK3D3Wiz3WLV1utpt2D16OLyfH4Gj7evSiqafLOVOpTq+yk9o1VTnP2cm9LS66bpo4sPmeDxVT2VKpLnacoKdOdP2kV9qm5xjzrrpeys762OW8af8ABVL9iXwB4h8YeGvEfxQ1eO++HfjafwD8RbzTfh5491rQ/h7r1slg8knjbX9J8P3ekeGtIP8AaVqItY1S8gsZt0rRyslvOyXTyPMqsKdSFGNq1NVaKlVpRnVi7/w4SnGVSWj92Kv3tePNE83wNOU4zqSvTm4VGqc5RpyX/PySjaK1XvSaVu9mz2P41fts/s2/s/3Hw7tPiX8QPsN38W9G1XXfhpa6BoOv+L7rxvYaRpkOr3H/AAjlt4X03VrjVLq40+4gn060tYXn1ASoLVHJbbz4bLcZi1WdGjdUJKFZznCmqUm3Fc7qSio6pptvTq0mbV8fhcP7P2lR3qxcqfLGU+dJJ+64x1umraa9FH7UXw7/AG4v2YPid8F/HPx/8O/FDT7H4ZfC+41Sy+Jep+KtO1bwjqvw+1HRoVuNQ0rxj4c8Q2VhruhanFA6SxWd5YLNdo8ZtBNvXcq2W42hiaeEnQk69dRdCMJRnGqpfDKnOEpxlFvS6b5XunZoKWPwlWhUxEayVKk2qrmnB0nHVqpGV5RdtbSivR2Oa/Z3/wCChP7K37UfjC/+H/wm8daxP44s9AfxZa+FPGPgbxn8Pdb8QeEkdUbxR4VsfGmh6NL4l0EeZEzaho4u4445YpJQiOrVpjMox2BpqtiKSVLn9m6lOrTqwjUtfkm6cpKErfzfK9/dnDZjhMVN06M5e0UebkqU505SivtwjOMXKP8AeX4X97uNM/bI/Z21X4O/E/49W/xAt4vhj8Gtd8YeGfiVrd7pup2Vz4W17wJcC18R6VfaPc2kWqG7tpmi+yxw2znUEngksfOSZKyll2MhiKGFdJ+3xMKdSjFOLVSFRXhJS1ik1322dre7axuGdGrX9p+7oSnCq2tYSh8Sa3TXbW/TdqP0D4V8SaV4y8M+HfF2hSTzaJ4p0TS/EOjzXVrcWNzNpes2UGoWEs9ldxw3VpLLa3EUj29zFHPCW8uVFdStctSEqc5052UqcpQkk00pRbTSabTs09U36vRnTCSnCM435ZxUo30dpK6dnZq67r7jT1DULLSrC91TU7qCx07TrS4vr+9upEhtrSztYnnubmeaQhIooYkaR5HIVVUkkDmpScmopNttJJd3oNtJNt2STbb6Jat/JHwp+xx+0h8TP2rPEHxg+LtvYaJon7LEGvTeC/2dpH024j8X/Ez/AIRe4uLXxf8AFK4v5roQr4N1DVI30rwlbW9luvoLO41R7lopIFb08xwdHAQw2H5pSx/J7TGar2dHnV6dFK2tSK1qO9k3ZLS55+CxVXGTrVo2jhFJ08Nde/V5NJ1nq/3bekFo3a7te0vzx0/9uT9vjwt8LviV+2B4n1P9nTxv+zl8PP2jPHnwt8RfCez8F+LvCnxT0rwF4Z+J114Eh8RaR45XxHqPh/VdbtbcW17c2F74fihvFWVY5IHOW9h5ZlVSvRy+EcZSxlXB0q8MQ6lOdCVWpQ9rySpcvOoX5leM01o3f4Tzlj8whSqYyTw1TDU8VUoyo8k4VVCNV01JVLyi5bN+7Z7e78Uf3z0fVLbXNI0nWrIsbPWdMsNWtC4w5tdRtIby33jjDeVOm4Y6+lfKyi4ylF7xk4v1Ts/yPoYtSSktpJNejV13/P7zkviV8Vfhp8G/DE/jb4sePPCnw48IWtxBaXHibxnrlh4e0OC6um221vLqWpTQWqTTsCsUbSBnPAzmro0K2JqKlh6VStUavyU4ucrLrZa2Iq1qVCPPWqQpwWjlOSivS77nmnwu/a5/Zc+N3iJ/CPwe/aD+EHxO8Ux2cuov4e8DePPD3iTWEsICBNeNYaXqF1cC2iLASTFAi5+YngVvXy/HYWHtMRhMRQhe3PVpThFt7K70v8/W10ZUsZha8uSjiKVWVr8sKilKy62WtvP/ADZ9E1xnSfFPx1/4KD/su/s6eP7/AOFXxK8YeIl+JGneF7HxpN4J8I+APGnjrxFL4Yv5JEj1e207wpomqyz2kAieS9lX5bOJfMuGjA+b0sLlOOxlFV6FODoyqSpKpUq06UFUjvGTqSik9dNdfJ25uCvmWEw1R0as5e0UVPkhTnOTi+qUFJu3XT79OXc1v9uz9lfw/wDs9+G/2p9S+K2lr8CvFep6To2j+Orax1W7tn1XWrx9Ps9OvNPgs31TT71L2OS1vLW8sop7O4Rop4kfipjleOni54GNCX1qmpSlTcor3Yq7kpc3LJW10lqtetipZhhI4eOKdVewnJRU0m9XpZrRrVW8np72jk79nz9uT9m79p7xZ4s8B/Cfxjqtz418F2dtqus+E/Fvg3xZ4D8QyaDeyGKx8S6VpXjDR9Gu9Y8OXrjbbazp0U9nJlTvTcm8xeWYzBU6dWvTiqVRuMalOpCrDnSu4SdOUlGavrGWvrb3XhsfhcVOdOjN+0gk5QnCVOTi9pJTSco+aVvU+uK887D48/aQ/bx/Zm/ZS13Q/Cfxf8Z6vb+L/EGmXGvWHg/wZ4K8X/EPxTH4ds38u88SahofgvRtbvtM0G2YES6pqEVvbZVgjttNejg8rxuPjKeHpxdODUXUqVKdGHO9oKVScFKT/lV+2m5xYrMMLg5RhWnLnknJQp051JqK3m4wTaj5v5Nbx2dd/bZ/Zi8Pfs9aP+1Vf/FTR5PgLrs+k2unfECwt9Qv9Pe51q9/s2yt57S3tX1GzuEvs2t5b3VtFPYzK8dzHEykNEMtxs8XLAqhL61BScqTsnaK5nZuyatqrb6WbumU8fhY4ZYt1U8O+W00m9ZOyVlre+j2t8m5ZHwR/bw/Zl/aE8Y+Kfh98N/G+py+NfCWiN4pvvDPirwb4t8DavqXhQb8eKvDdp4t0fSJfEfh1yhCarpC3dsflO4q6FqxWV43B04Vq1KPsqk/ZqdOrTqxjU/59z5G+Seu0rW7yJoZhhcTOdOlN88I87hOEqcnD+eCmo88f7yVvS3veVaN/wAFWv2HNd17wvoVh8Wb4xeLvE8ngjTPFFx4D8c2vgS28YpqM2lJ4X1nxzcaBH4X0bXLm/ge3ttP1DVIZpX2YA8xA28sizOEJyeHV6dP2soKrSdX2VlJ1I0lLnlFRd21btpuYrN8BKcYqrL358im6dRU1Pm5eRzcFGMr7JtX8z079o79vj9mH9lXxBo3hD4ueNtWh8Ya5pMviG18JeC/Bfi/4ieJbbw1bttuPE2q6P4K0bWrvSfD8Jzu1XUFtrZgCY2kxlccHlWNx8JVMPSi6cZKDnVqU6MHN/YjKq4qU/7qcmtn05dsTmOEwkowrVJKclzKMKc6klH+ZqHM1G3Vr7949I/7aH7Nf/CF/Bb4jW/xL02/8CftBeJrDwd8LPFmnWepXmi654l1NJDZaReXkVoy6FdzSRS2xj1oWJjvENpIq3A2LH9nY32uJoOi1VwkHVr0248yhHeUVdOa105L3Wtkrsr69huShU9qnTxM1TpTS91zf2X2d9LS5XfRS35fRoPjt8Mbr43Xv7O1r4h+0/FrTPBUHxB1Pw1b2N9MumeFbq8NhaX+oamkDabaSXlyGS1tJblLqdQZEiKKTWLwtdYZYxwth5VfZKbaV52u0ouXM7aX00vtJ25dFiKTrvDKV6yh7RxSbtC9rt7K70s3fte5+e3hLXfih+2X+2v8YdOX4p+NPht+zf8AsZeMfDvhODwN8P8AUl0C/wDjJ8WJdPXWdVuvH+tJbSahceC9Cglitrfw1Zy29vqM7GS9lYDY3rVY0Muy3DP2NKvjMypzqe1qx544fD6xiqUb8vtJ6tz6dFpc86EquOx1de1nSwuBqRgoUnyuvVau/aS1bpx0tFJX6uzRY/4KS6JrXxB+K/7B3wbg+JfxZ+GnhL4s/G7xpovjm7+DnxB1r4beKNX0rSfhrrmu2VifEOhsLuO3j1Oxt5zEUkRgrLgbmajJpRo4fNcR7GhWnQw1KVJYijGtCMnWUW+WXXldvxd7KMjNIupWy+h7StThXr1I1HRqTpSaVJyXvRs9/P7rI+0fip8afgp+xh8HdD174v8AxA1TRvBmgDRfBWi6r4kn1jxp448W6y8ItdK0u2hsLS/8ReMvFmqCBpHSysLm9u5FluZEVN7L5lDDYnMcTOOHpRlVnzVZxhy06VON/elq406VNX6tJbXejO6rXoYGhGVeo4wjaClLmnOcui/mnOX3vd9TD+AP7af7Ov7TPhjxz4o+E3jS71FPhi1wvxD8O+IvDPiPwb418GNb6fJqv/FQeDvFGm6X4gsUn0+N7uzmew8m8iGbaSXBWrxeW4zBVKVPEUlF17exnCcKlOpeXLaFSEpQdpNJ26722Fh8dhsVGpOjNv2V/aRlGVOcLK95QnaSTWzdvlc8c8Ef8FUP2IviF4o+HnhXwz8WL2eT4q30GjeBfEmoeBfHGk+A9d8S3KPJB4Rg8d6loFv4VTxXII3RdCk1Vb7zka3MQuAYa6auR5nRhWnOgl9XXNVgqtJ1YwW9R0lKU/ZrT3+W1ndXScjCGbYGpOnCNV/vXy05uE1TlL+X2nKoc2nwuSfS8nZHRfGL/gpD+yV8CvHXjn4Z+PvHXiAePPhtbaNqPjbwv4V+Hnjrxtqnh7Rtd0yPWLTX9Qg8LaDqvkaDDp0qXF9q0jJZ2YyksgkV0qMNk2YYqlSr0aUPZVnKNKc61KnGcoy5XFOpON5c2iW77K9pVXzPB4epUpVJy9pS5XOMKc5uKkrpvli9LO7d1bv/ACejePv20/2Zvht8DfC/7R3ib4p6OfhH46XR18CeItEtdS8R3Xje88QRGbR9K8JaDodnf65r2s30au0el2FjPeJ5UpmjiETlcaWW42tiZ4OFCX1ilze1hLlgqSjpKVSU5RjGKf2pO3axrUx2FpYeGJlVj7Gpb2cleTqOW0YRXvSk+y26mF8Jf28P2Zvjf8Nvif8AFL4eeN9S1HRPgvaajefFTQ9U8IeKvDvjzwPFpmmvrFwuu+A9c0qw8U20kmmRve2arpj/AG6FS1oZsHbWIyvG4WvRoVqSjLEOKoSjUhOlVcnb3asW6b97Rvm062umTRzDC16VWtTnJxoJurFwnGpCy5runKPNtqrKV+ivaJ1Wrftf/s96P8Mvg/8AGC58fW8/gL49eIPCPhb4T6rp+nanqFx4w1zxwkknh6xsNMtLSXUI3niilmu2uLeNNNiike+eAI+3OOX4uVfE4f2LVXCQqTxEW0lThS+OUpXt6bcz0SdkXLG4aNKjWdROniJQjSaTfPKavFJK7u/TTq0rn0x6e4B5GDyM8jnB9f6YxXH/AF/X9LzS2Or+v63/AD+8+Uv23vj3q37NH7L3xV+L3hm30+98a6LpenaN8PtO1WJ7jT9T8f8Ai3WtP8MeErG7topYJrq3fV9UgmuLeKWOSW3glVZEPNd+WYWONx1DDzclTlJyqyjvGlTi51GnZ2do2Xuy9FucePxLwuEq1o29olGNNS2dSclCCaWr1aulbRfKXn3/AATk/aS+IX7UH7MmheNvjJp2haL8a/DPifxd8Ofi9ovhu2mstF03x14L1y60fVItPsrma4uLW1mWCK5gjmnlYxTI4fay7tc4wdLBY6dPDSlLDThCth5T1k6dRcyu7u/VdO3RozyzE1MVhY1Kyiq0ZTp1lHSKqQdpJJttLqrvr0sfd1eWegfiv/wUJ+PP7dH7P/jvw7pvwR+Pn7NDaz8bPEdt4V/Z5/Z78V/BvxDrHxD8S6pBDajXbvWfGx+IGi6DYeHNE82TUdX8QT6dFDZWzwWcNrdX0sUT/SZRhcrxdObxOExvLhoe0xeLhiIRowi3LlUYeylJzaVowWrd25KKueFmWIx+GqRVDEYa9eXLh8POhKU5NW5nKpzpKMW7uVtLpWd0pemftc/HT9sb4ban+wj8F/hn4r+DXhX4zftG+I9f8J/Evxj4q8Ea14y8D6Vq3hfwEnibU5vD2hWOv6HqIs7nUYrm3ti96XS3eIkEqxbHLsNl1aOa4mvSxNTDYOEKlGnTqwp1ZRqVXBKUmpRckrX0irp2S902xmIxtOWAoUp0Y1sTKUKk5wc6acafNeKTi7XVlrqnd2tafrH7HP7SHxo8efE79ob9mn9pLTPh4PjX+znqvhNr7xh8KY9bsPAvxB8HeOtFXW/DPiPT9A8Q3V/q/hzUBD5trquk3Oo36RXMe63uGjcbefMcHhqVDCY3But9WxkalqVfldWjUpS5Zwc4e7ON9YystN7/AGdcDiq9SriMLilT9vhnG86XNyThUjzQklLWMraON5a7Sep+gleSekFAHzr+0b+1Z8Df2UfDmh+JfjX4vl8PxeKtYPh/wjoekaHrfizxd4u1tYftMumeF/CXhqw1PXtaure2/wBIuhZWbx20OJLiSJSpbrweBxOOnKGGp87px56kpSjCFOLdk5znKMYpu9ryV7aXtY5sTjMPhIxlXny875YRjGU5za1ajCClKVutlpfW/wBnm/hz+21+zZ8VvgT4/wD2jvBPj86h8LfhVa+KLn4lX17oOvaN4h8DS+DNN/tfxLpvifwhq2n2niXSdX0zTtt0+m3Omx3M0TxyWySpKhbStluMoYulgqtK2IruCopTjKNX2kuWDp1IuUJKUtLqUkno7W5SKePwtXD1MTCpelSUnUvGUZU+Rc0lOLtJNLVpxjo1a97nBfCv/gpL+x98ZviV4S+FPgT4mXtz4q+IWl3Oq/DqfWvBXjPwz4Y+IsNjZJqGpWngTxdr+h6d4d8Valptm/n3tho+o3dxHGkxQSiGULrXybMMPQniKtBKnSaVbkqU5zot6L2sIzcoJtWUnCz8rmdLNMFWqwpQqvmqK9PmhOMKlldqnOSUZNJ3aTemuq1jlfFP/gp7+xt8G/F/xH8CeNviLrqeJ/hBrtvoXxSsPD/w68e+K08AG50uw1ka14qu/Dnh3UrTR/DUOnalazz6/eTxachMyCVntrgJVDJMxxNOjVpUYuGIi5UHKtRh7X3uW0FKV5TbTShZS663SFVzXBUZ1ac6kuajJRqqNOpP2d1e8nGMlFK6u27dr68vqHxo/be/Zn+AvgH4e/Ejx58Rorjw98XBbN8KrbwXo2uePfEfxIjutOj1dJvBnhjwjYatreuW8WlzRX9zc2tmba1t5Ea5mjLorYYbLMbiqtajSo2nh7+3dSUKUKNny2qVJyhGL5k0k3unbqa1sfhaFOnVqVPdrfwlCMpyq6c3uRipSlprezstX0Mnw9+3z+yx4q/Z08ZftVaB8SDqHwZ+HM15afELWV8OeI4dd8C3+mXdrZavp3i3wfc6bB4o0K/0eW9t5NTtdQ0uGS1tH+2P/ow82nPKsdTxlPAyoWxFZJ0Y88OWqmm4uFT2koSUknytN32te0ZTHMcJPDTxcal6FO6qS5ZKVNppSU4P304tq65ZW3ej5j1TxR+0h8HfB+vfA3wzrHi6E65+0hqNzpnwbsNOsr7VJPGEll4dbxXe3lubGG4jtNLs9BC39zqd68FlCssEbTCSZEbGGDxFSOKlGn7uCV8S21H2d5ciTu4tyctFFJye/LubTxVGnLDxcrvFNqiopvntHnbVtkotNt2WvdpS9yrlOg/LX9sP44ftYaf+13+zT+y1+zH45+D3w2k+Lvwq+MXxI8SeLvi14C1nx7aRP8NtU8J2NnplhY6P4k8OTW5v4/EUjSStNKA0AOOQle5l2FwEsBjcbjaWJrfV61CjCnh6qpO1aNRuTbjK7Tgumnnd8vkY3EYyOMw2Fws6MPbUq1SUqsHO3s3FJJKUe7b1u9lbaXpv7An7S/xW/aA0H46+E/jdpfgP/hZ37OXxy8SfBDxN4y+FDao3wx+IkuiaZpGr23inwpFrE13faaXt9XSx1nRZr+/bSdWs7q2+1S4KxY5rgqGElhamGdX2GMwsMTCnX5fbUuZuLhUcVGMtVzQml70ZXtH7W2XYqtiI16ddU/a4avOhOpSv7OpZJqUU3daO0krpNWuvtffwxkZ5GeQO4715J6P9f1v+X3n4X/tafHj/AIKK/Cv9o7wL8Dvgt+0B+yl4w8ffGvxXJqvw4+B+q/BnxLbeJvCnwcstWSPXfG3xB8d3PxBt9LtdP0LTxNZQXdrost94j1zy7LSNJl/fva/UYDC5RXwVXFYnCY+nTw1PlrYlYiDp1MRJe7To01ScnJvdSfLGOsm7e/4GLxGZUsTChRxGFnUrycqVB0Zc0KPN706k/apWgtNE3J6JaOZ73+1j8cP2v7H9sH9mT9lP9m3xt8GPAN58Vfgn8U/ij4w8U/FL4e6/48sH1L4d634c0uLTNLsdE8TeHLyytdQGsTM8rTTSRqikYcCuTAYbL3l2Ox+NpYiqsPiaNGnCjWjSly1ouV23Tmm42stH53ub4zEY1YzC4XDTo03VoVa1SVWm5q9OUI2SjOOj5+nbRo9t/YY/aZ+IX7QHh74y+EfjP4d8KeHfjd+zd8aPE/wO+KP/AAgNzqVz4E8QaxoNtY6npnizwkusb9VsdJ8Q6LqdjfLpeoT3V3pszS20l1MFV65s0wVHCTw1TDTqTw2Nw0MVR9ryqrCMnyyp1OX3XKMk1dKKa1tqdGX4qriI1oV4xjXw1aVCr7O7pylHVTg3qlKLTs1dba2Z9z15Z6AUAfMP7Sf7YnwB/ZNtPCknxo8W32l6t47vL6x8EeEPDPhjxJ458ceLZtKhS41Z9A8IeEtM1fXb+10qCSOXUr1LMWdmskYnuEeSNG7sHl2Lx7qfVqalGkk6k5zhTp01J2jz1Kkowi5NNK7u+idjkxWNw+DUPbzalUbUIRjKdSdld8sIqUnZNX0e/mYGk/t4fssa5+zZ4h/a30r4pWN18CfCD3Nv4u8VnStZt73wpqNhqtromp6P4k8N3VjF4h0TWtL1O7t7bUtL1DTobyz8wSzRCIh6qWV46OMhgJUJLFVLOnDmjaonBzUoTTlCUXFNqSdnbptGY5hhJYWWMjVvh4fHKzvB3UWpRs5RabSacVbto2Ufgz+35+y18e/ilL8Gfh14+1Cf4hSaDP4r0DRvEvgzxf4Mi8b+FrOWKC+8SeANQ8VaNpNj400WxmmhS7vtAmvYolljnObaRJXeJyrHYSh9ZrUkqSmqc3CpTqeyqO7jCqoSbpykl7qklfbdNCoZlhMRV9jTqN1OXmjGUJQ9pHrKm58qmlfVx20fM005eZ+J/wDgq3+w74Q1nxDo2u/FfU4P+EL+IurfC3x/rdt8P/HeoeFPh14v0bWI9Bu7bx/4qsfD9xoPhGwfVJUt7TVNZvrazukYXUcrWn7+t4ZFmlSMJRw6ftaMa9GLq0lUrU5R517Km5KdSXLe6jG6elk1JRylnGAi2pVZLkqOlUl7OfJTmny2qTUHGC5tFJtRfdqzPX/2i/25P2bf2WpPBlj8VvGmo/8ACQfEPTr7W/BXg/wL4S8U/Ejxl4i8PaYkT6l4lsfDPgnSdb1X/hHLBZ4Bc65NBFpyvKkSTPK2xebB5ZjMd7V0KceWjKMKtSrUp0acZy0jBzqyhHndm1FNuyvp9rfE4/C4TkVao+aouaEIQlUnKKteShDmlyq+rtZd3pyjft1fstH9n3wz+1LbfFPT9Q+BPivxP4e8G6f490/TdYurGx8R+JvEsXg+w0zxDZJYf2n4bntfE0seja0Nbs7H+w71vK1X7NjdT/svHLFzwLoNYqEJ1HSbim4Qh7RuDvyzTh70XBvnWsb6C/tDCPDwxaqqWHnOMFUSbSlKXIlJaOL5tHzL3ettj1jX/jx8L/DXxj+HfwC1TxHt+KvxS8LeLPG3g3wxaWN9fSXvhPwS1jH4h169vLSGWx0nTba41OxtLe51Ge3S/vJ1trTzpgVrnjha88PWxUYfuKFSnSqTbStUq35IpNqUpe621FOy1dlc2liKUa1LDuX72tCVSnFJu8IfFJvZJd29XolL7PsFc5ufmF+0T8d/2pfF/wC2NoH7Fn7KXiL4TfC7V9J+AP8Aw0P8Sviz8WfCWs/EGGLStW8aXngjwl4N8LeENI1jQUa6v77S9S1DW9Y1DUGFnYwxRWlu08oavbweFwNPLp5lj4YivF4v6pRw+HnGi+ZUlVqVKlSaldJSioxhHfe+0fJxOIxc8YsFg5UqUo4f6xUq1Yyno58kIQinGzbjLmb8rW1Uvqb9kzxr+0J43+EFvdftRfDjTPhr8ZfD/inxZ4P8R2nh6Z5fCXi+08NaxNYaN8RvB0dxdXd9ZeGvG+mLb6zp2m6lO9/pxlms7guYVduHH0sJSxDWBrSr4eUKdSDnpUpuceaVGpZJOdJ+62lZ763OzB1MRUo3xVNUq0ZzhJRd4zUXaNSHVRmrSSdmttdz6XPQ44ODg+hxx+GetcR1H4U+M/jr/wAFHvDn7anw4/ZX8G/tBfsnfFfxHres2PxA+KXgbTPgx4m8L6n8I/2d5tUlkGu+J/FeofEK7gl8V65psf8AZfhHRtM0S7vtavhLq0ttY6RBJdL9RSwuTTy2tjp4TH0YQi6NGpLEQnHEYtR+GEFSTVOMtZzlJJR0XNM+fniMzjjqeEhicLVnKSqVYKhKLo4a696Uud3lJaQj8TlrpFXPa/jf8bf23fFv7f8Arn7J/wCy/wCO/gJ4A0Dwb+y94S+PF/dfGH4ceKPG0niTW/EPjvX/AAkdBS+8M+J9AudHsCmm2sjXSQXckO6V0WVtqLzYXDZZDKY4/HUsVVlUx1TCr6vWp0lTjClCfO1ODUrXenW9rpK5vXxGPnmEsJhZ4enGGGhiL1qcpqTlNwteMota2/4H2vqL9hH9p7Wv2sfgDbfETxh4W03wV8RfDHjz4j/CH4oeGdE1CfVdA074ifCfxfqfgvxRL4e1C5hgurjQNRvtLbUtIN0n2qKxu4oblmmjd24c0wUcBi3RpzlUozpUcRRnJKM3Sr01UgpxTaU4qSjLo5JtXWsuzL8VLGYdVJwVOrCpUo1oxfNFVaM3CfI9LxbV4+Ts72ufZNecdoUAfIX7Sf7dX7Nf7J+teHPCvxf8Y6xD4z8WaVfeIdE8D+CfBXi74jeMp/DOlzfZ9S8UXPhvwVo+t6np/hyyuCIJtYvoLazMwMMTzSIyL6GCyvGY+M54enF06clTlUqVKdKmqkldU1OpOEXNrXlV3bV23OLE5hhcJKMK05c805RpwhOpPlW83GF2oq2709LtljW/25/2WNA/Z38LftXX3xb0N/gD4y1nwz4f0L4h2UGo3mmTax4s1lvD+k2F5bQWj6jptymtRy6dqcN/Z28uk3UE8WoJbvE60o5Zjp4ueAjh5/WqcZzlSfKny01zSknJxi1y2cbP3unNpzOWPwkcPDFOrH2E5RjGau1zTfKk+qd9Hfb7hfgB+2/+zj+0x408XfDn4WeMNVn8feCdMsfEGs+DfF/g3xb8P/Es3hXVLhrTTPF+jaP4z0fRb3W/CmoXUbW9trmmxXFmZQEkdC8YYxeWYzBUqdavTXsqknCNSnUp1Yc6V5U5Spzmo1EtXF2fa+4YfH4bFTnTozbqU0pOE4Tpy5G7KcVOzlB9JJW72Z4tpP8AwVj/AGFda1fwtpdj8XL82XizxjJ8PLPxdP4B8dW3gDS/HX9u3Xhq18JeJfHk2gx+FvDmvalrVq9lp1hq2pWsty8ls2EW6tzL0yyHNIqbdBc0KftnTVSm6sqXJzupCkpupOCi7txj0btJJOWCzjAOUEqr9+bpqfJPkVRScOSc+VRhJyVkpc19NFdI9a/aT/bx/Zo/ZQ1/w74Q+L3jHWo/GninRL7xTpXgrwP4H8YfEjxavhHTJxa6j4v1HQfBGj61f6V4XtLo/ZpNa1GK2s5J1kit5JpInRMMFleNx8J1MPTj7OElCVSrUp0Ye0a5o01KrOClUa15Fd21drXNsVmGGwcowrTl7SSclCFOdSfInZzcYRk1FPS7sr6JreO5/wANq/szyfD/AOAvxWsvihpOqfDb9pfxz4f+G3we8baVa6jf+H/EfjXxT/aEehaDeXsFow0C9vr3Sr/SRHri2Bh1m3fSbhYr/ELR/ZuN9riqDouNbBU5VsRSlKKnCnDlcppfaSi1L3L3i76q0ivr+F9nh6qqp0sVUjSozV3GVSd+WLdvdbcXH3uX3tHroekx/Hb4YzfHe7/Zrg8QG4+MWn/DO3+L+p+FoLC+mGl+Ab3X38MafrOp6okB02xbUdahntdPsZ7lL28FvcTw25hid1x+q1vqqxrhbDuu8OqjlFXrKPO4qPNzO0bXajZX13TNfrFL6x9VUr1vZe2cF9mnzcqk97XloruPzPXq5zY/HLxt8c/+CgPxI/bW/a5+B37MvjP9nDwz4Q/Zd+HfwJ8Xad4Z+L/w78Ya7qHxD1j4seF/Fmt3Gjy+LvDHivTJPDlvHdeFzawXv9k3/wBn+3RyyRSpA6S/Q0sNlNHLsvxONpYydTHVsVTc8PWpwVKNCpTgpeznCXO37RNrmj8PS9zxauIzGeOxdDCzw0YYWlQqKNanKTqOrCcnHmjNWV42XuytzdFc+7P2Lf2kbf8Aa6/Ze+D/AO0PF4ePhG7+Ivh25uNd8Km8Gor4c8U6DrOp+F/FOjwagI4ft1pZ6/ouoJY3ZiQ3FkbeR1V2cN5mZYN5fjsRg+f2iozSjUtbnhOKnCXTVwkuZLZ6apJnoYHE/XMLRxHLyOpF80L35Zxk4zjfraUWfTk4maCZbd0juGhlW3klQyRRzlGEMkkasrSRpIVZ0VlLKCoYE5XiVrq+19fQ6nezs7Po97PvbS/3/cfhlonx4/4KMxft2+Bf2UNP+P8A+yh8af8AhHLnTPHv7T+leFfg14m8EXnwe+D2oq15o9rc+IdV+IOq/bviN40tngXwz4d03RbqSOwaTX9Yk07TfIef6aWFyd5XUx7wmPw/OnSwcp4iFVV8SrxlaMaStSpu7nOclquRczuo+BGvmf1+GEWIwlflanilGjKn7Gi9Y+9zyvUmn7seXZNysmpHc+NPj3/wUE+Iv7af7Z/wY/Zo8Y/s3eHvBP7J/gz4H+JdK8J/F34feMNa1T4ial8T/h3feL73Sbjxn4a8VaW3hyEXumzWdrff2Rei2F1DJLDOkL+blTwuU0csy/E42njZ1cdVxNN1MPVppUVRrRpxkqVSnJT0ldrnjfl8/d0qYjMamOxlDCzw0YYSFCahWpzbm6tLnadSM7R1Vk+V23adrS+/f2Mf2kLL9rv9l34MftG2WgS+E2+KHhJdW1XwvLdrfnw54j03Ub/w/wCKNEjv1jiW/t9N8Q6Rqdra3oii+020cUpjUsRXlZjg3l+OxODc1U9hU5Y1EuXng0pwla7s3CSbV99rHo4LErGYWjiVHk9rC7he/LJNxlG6te0k7d133PpyuI6goA+H/wBor/gop+yf+y143Hw3+LPj3WYvHFv4ctfGeveHPBngPxt8Q7/wb4NvZpYLTxZ44XwXoWtJ4S0C6eC4a2vtba1FxDbzzwxvBE8i+ng8ox+Ope2w9KLpubpwnUq06SqVI6yp0vaTp+0mrq6jzWbS3aUeDE5lg8JU9lWqS9py88owpzqOnB7TqckZ8kX0bS6vWyUvQPiR+2d+zT8KPhB8Nfj540+KeiWnwe+L2ueEPD3w88fadHe63oXiXUfHen32p+FvsU+k215J9n1Sz028kiuHiCLJF9nk23DpE2NHLsZiMRWwtOjJ4jDxqTrUnZSgqTSndNrWLklZa630V3HWrjcNRo0sROrH2NaUI06ivKMnUTlCzS0Ukt2tNrXdjF+CH7c37Nn7Qh+KNr8OfGeq/wBu/BnS49f+I/hDxh4N8W+AvGvh3w1c2d7f6d4ol8J+L9H0fXLnw5q1rp14+l6xaWktpdvA8CyC4Hk1eKyvG4T2DrUlyYmXJRqU6lOrTnUuk6anTlKKnFtXi5J631TvGKGYYbE+1VOUuaguapCcJU5qD1U+WfLJxaWkkmn02tLy/wCHH/BUz9iX4reLPhX4R8G/Fa9upvjb/Z9r8LvEmpeBvG+ieA/GHiDVLA6nZ+DNK8e6toNl4Um8ayWivu8MDVDqaXUcunvCNQhkt12rZHmVCnXqVKCSwt3XgqtOVWnCLs6kqSlzqnf7fK421u01IypZtga06UIVX++t7KTpzVOcmuZQVRxUXNr7N730srPl6j9oj/goz+yX+y545f4bfFn4gavB41sfD1n4v8S6D4O8B+NviFc+BvCGoSyxWPinx63gzQ9ai8H6HdmC4ktrzW3tDPBBNcxRvbxu6xhMnx+Ope2oUo+ycnThKpVp0va1FvCl7SUPaSWitDm1dt7IvE5lg8JU9lWqS51DnlGFOdTkg9pT5OblT7tba6rWPrdz+1Z8A7fVP2ddMT4haXfx/tYNqEfwB1rS4rrUfDfxCm07wx/wmT2+neILWGTS7a5vPDgk1HS7e/ubebU1t7mGzWa4glhXBYDFuOMl7GUfqCTxcZWU6Sc/Z3cLtu09JWb5bpuyty7PGYa+GXtF/td/q8ldwq2jz2UldJuOqTab9U0dT4X+Ovwx8afF34nfAzwz4h/tX4k/BzSPB+tfEfRrewvvs3hm28eQXd14Wt7vV2gGmSanqVnY3F5/ZkFzJe29oqT3MUUcsZfOpha1LD0cTOHLRxEqkaMm1ebpW52o/FyxbS5mrXdle5UMRSnXq4eMr1aMYSqJLSKqX5Ly2u0npuuu6PXq5zc/G68+MP7fvxw/bI/bA+CnwE+M37OHwh+Hn7NN78HNM06P4nfB/wASeO/EXiC4+JPgEeK765fUtJ8c+H4IorK7jlhjja0ZjHLGNw2Zf6JYfKcLl2X4nF4bGYmtjViW/YYiFOMPY1eSKalSluvy63ueI6+Y18bjKGHrYajSwrpL97RlOUnUpqbd1OOiba6eeyZ+qnwvsPiJpfgDwvp/xa8TeF/GXxHtdNEfi3xP4L0G88MeFtZ1PzpWN3ougX+oareaZZm3aGMW8+o3b+YkknmlXVU8KvKjKrOWHhOnRcv3cKk1OcY9pTSSk73d0uvWzPXoqqqcFWnGdVL35wjyxk+6i27aeeu+h0Pie38Q3fhvX7XwjqOm6R4quNH1KDw3qus2M2p6Rpuuy2kqaVfapptvPbT3+n2t6YZ7uzguYJrmBJIY5o3cOsQ5OeHtFKVPmXOoy5ZOF/eUZNNKTWibTtvZ7FT5nGSg0puL5XJXSlbRtaXSe6v9x+MP7OPx+/b88bft0Xv7P2qfHH9l/wCO3wn+CdrfP+1T4j+Hfwm8Q/D+78D+I7/SXk8JfDnw3qGr+O/EE2veNri7uLPVfEEFrpY0zw7o6eXqN+NQvbe0X6PGYXKqeWLFxwuOwtfEtfUYVq8KyqQUvfrTjGlTUaVk4wvNylLVRtF83h4bEZjUx7w7r4WvRoX+typ0nT9nJr3acbyblO9m9HGMd7Sa5eZ1D9rP/goj4j8X/wDBQj4hfCbW/wBmq/8AhP8AsP8Axd17wbb/AAd8b+BfGNp4z+Ifhrwt8NfDHxH1lrT4l6N4n/s/RddubHWLyz0uS98OXdiLyCH7WnkPvW44DKI0sppV4Y1V8zw8Z/WKVWn7OjOpWnSi3SlG8oqUU3yzT5b7u3LLxmZSqZjOi8PKjga0oeynTkpzjCnGpJKqp2i2pPlbpyts+5+xfwL+LGifHn4K/CX42+G7a4stB+Lfw58HfEXSbC7YPd6fZ+LtBsdbj0+6dVRXubD7YbOd1VVeWBnX5Spb57FUJYXE4jCzd54etUoyaVlKVObi2t9Ha68t7O6Paw9ZYihRrxTSrU4VEnuueN7PzV7fI9VrA2CgAoAKACgDZ0D/AJCtv9Jf/RT114H/AHmHpP8A9IZhif4T9Y/mej17p5x//9D+/igDgvE3/H+g/wCmCfqzf4ev5V42Yfxo/wCBfmd+F+B+v+Z8Gf8ABQ3x18SPht+xt8dfGfwm8Ead8QvHGj+EnbTfDereFT4501rW4uoLfVdVu/BojmPiiLQ9NlutWOieVIL/AOx/Z2Rg5WqymlRrZlhKWIqujTnU1nGfs5XSvFKptBylaN3be91a5lmVSpTwVedKmqk1HSLjzq32pcmvO4xvLltrsr3R+Hvwy8an4n/t4f8ABNLxD4U/bA+KP7YOi6FqfxCh8QXd78CPCnwv+Hfwmu9R+FWqRnw5p2peFPAPhW4srmZkexTwvquo6ktjZWaiZUnWJn+mr0vYZVnMKmX0cvnKNPkSxM69Wuo1o+/JTrVE1f3lNJdd73j4FGp7XMMtlHF1MXGMqql+5hSp0ZOlJcvu0ou7atyybdt9HzH6Cf8ABP74UeHvHdt/wVA8CfEfwg954S+KH7ZPxG0TxDp2pWl3pq+KPC1/4E8KWTot2q21xc2TRzXUdtd2sv7l3lMEyyruryM2xE6cskqUalp0Muozg4tP2dSNWe6adpXV7O2nWzPSy6jCp/alOpC8KuMqKSaa54uCTs9Lp6q6fXpoXfjH8LtF8D/8FCv+CWfhHwb4Yu4PAnwu8A/HvQPD4aLUNYtvDOnaN8M49P8AD8E+sX32uWK5ghgit7S6vbs3crKNssrn5jDV5VcozypVmva162FlN3jF1JSr+++VWvd3bSSSv1sFejCnj8qpwi+SlGsop3lyKNPlSv6JWbte3leXU/8ABQLwpH+zF+zV+0/8b/2dPhXpGo/E74yeJPAWq/F3UdT8J3/xU0qKxtL3TfDWq/Eu6+GV0dQ0/W7rwV4We51Y6dZ6eqX8lik13DcMnyxlNT67jcDhsZiJRoYaFWOHSqKg7tOcaPt1yte0mlFNv3b2Vr+9pmMFhcLiq+HpJ1K06brXh7RJJqLq+zakn7ON5NbSs203rH86vgR4sPxF/wCCn/7FHizwr+1r8U/2yvCumfCP456Zf+PfEHwX8K/DTwT4KvLrwnYunhbRtT8I+BPCMdzPcFA0+i6lcal/ZUcFvCHSdmV/XxUPY5JmVOpl9DLZyr4VxoxxU61WolUkvaONSrV2tbmSXM7v3tGeXhp8+aYGUMXUxkVSrqVR0YUoQvC/KuSlS1ejcZc1tuzIv2rvgj8Q7T/goNN+xH4O02f/AIZ+/wCCiPjv4eftH/EGazkRLTwxH8D7yG5+NVhcWyNmG38eabZeGYppDAY7m5aTLGQsjGAxNJ5SsyqNfWsopVsFSvvP6yrYaS01dJuenNdJte8PF0KizH6jBP6vmNSnialndQ9g17dWvGyqRUL6NXT3b97+l83ei6PFb2Bu9N0yC2t4re0tJbu2tBDaW8awwRQxSMuIookSNAo2hVAGMAV8aoznd2lJvVtRb16vS+78/v1PqLxjZXUVbRNpaLte23p910fGv7fnwe+LX7Tf7KfxJ+Df7PPjfwt4c8c+Mxo+m3Go65rd/YaJe+Gf7VtZvE/h7UNW8PW1/q2nQ+INFivNKkuLGBblI7pzHIhG9fQyrEYfA4+jicXSqTp0uZqMYKUozt7k1GfKnyStKzdtOmvNxZhRrYrCVaGGnBTqWi25WXLf3otxu1zLRta9rXufm58G/DX7XHgb/gpJ+yB4B+OHgb4KfD34d+C/2VPjb4a8A+Hf2cNb+ImreBLXS9JTwjZWtv4qTxXp2nWFtqlusUH9jeWstxMJL6Vm3lnf2cRPAVMlzGrhquJrVqmPw0608ZGlCrd+0b9n7OUm4vXmu7bPW1zzKEcZTzPB069OjTp08JXjCOGdR07JQS5lKyT0tHrvve58bSfHTwd43/Yw/aI/YP8AA2m+O/GH7UPxJ/bB+MGnaT8OdD+HnjS4OmabqXx3u9X/AOEo17xC+hx+G9L8N22k28t/LqdzqqQtCFEbOzBW9BYWpSzDCZpVlSp4Gjl2Hcq0q1NXccKo8kIc/NKbbtZR9eXTm4XiKdTA4jAQ554mrja1qcac3aLr83NKVuVRS1bb225m+WP9U3g7SrjQfCHhPQ7sobvRfDOgaTdGM5Q3Om6TaWc+xuQyebA+0g4IwRnNfD1JKdSpNbSnKS9JSbPraacacIveMIp+qVmeSftKeEviX41+F9/ofwm8KfAfxn4wl1CxmttE/aO0jWdb+GcttFITczX1hoVvc6g9/EuGsXSIoj5LEYw2+DqUKdeMsRUxdOlZpywThGvfSyTm1G299evUxxUKtSk40YYec7ppYmMpUtO6im79Fp16anzX+y78Hf2pfAvxFm1j4xfCH/gn14I8Kto13bR6x+zJ4N8baF8QWv5CPJtprzxBplpZHR3AY3UYmErHbsVulduOxOBq0VHDV83qVOZNxx1WlOjyrdr2evMuia81fU5cJQxdOpetQy6EbP3sLCcKnp70Umn1tZ6dbWP0SryD0z8nPCmhXR/4LHfGvxBLo9z9jP7GXgPTbXWpNPm+yGR/EN2bmwg1FovIMjoQZ7VJt5QgvGQRu92pOP8Aq7hocy5v7Srycbq/w6O2/o/l0PHhG+d1pODt9SppScdL897J9/K336n5J+L0bwZ/wSxuLnxH4b1Y6fov/BTn+1X0D+xbl7240aD40z3o/s7RpIVku43gVri1gt4iLrH+jJI7AV78P3mepQqR5pZIlz810pOglrK6t0T2tu0tUeRP3MofNB2Wa35LO7iq3SOl/Ky120ufoz8Gfi94G/aw/wCCp2k/GH4CHW/FPw0+E37Kuq/D74g+O5PCXiLw3olp4y1zxDBdaZ4MN34g0vSnv9Z0uGGRr2wgScaaVZGYZ3V5GIw9TAZHLD4rlhXr46NalT9pCcnTjC0qloybUZN6Se/8q15fSoVqWLzWNbD80qVHCyhOfJKEVOU9IawjeUVuk3y3tvc/QfSv2wfhxrH7W3iP9ja28NfEuP4keGPANl8Q77xPc+DL2D4aT6ReuUjs7Hxg0n2W41VMfvLYQrHu+RZWf5F8iWX1o4CGYudH2M6rpKCn++TXWVOzaXb3k3vboeksZSeLlg+Wp7SMFNy5f3bT7S799LLZuWnL+X37XPx+8YeHP26PGvw98c/tD61+xP8AD6y+EHhyX4W/EHwH+z74W+I3jf8AaB1fVXn/ALd8KJ468V+CPGdtDBolx5dna+ELGK3ubia489twIK+5l+EpzyynVpYSOZVXiJ+3pVcXOjSwkY/BUdKFWldte86jurK146s8jG4iUcfUp1MQ8FTVGDozhho1p4iX2oqcqVRWj/Lfftb3fifwp4X8S33/AARXttD1LSfGGu6hN+23pV3JB4k8JSaT4l1PTpPjdDdHVdV8K2enW0OmG8hIvrq1tdOtbG28whIYo12r6U501xI5KVOK/s1/DUThGSw1uWM23ez0Wrd9HzM4oU5PJOWSnL/brvmhyylH2t7uCSte+qS+/Q/pL8R/Ar4Ya34u8O/HfUPCyTfFjwN8KfEHgbwv4mivNQgm0/wxr2kK+paK2nW9yun3kM0sKGH7VazS2rD/AEZkJG34ynia8ac8Kp2oVcRGrUg0rOcJNRlfdNLdrfrsj6WeHouccQ4L2tOjOEZK6tGUfeVr2d/Nffpy/nZ/wTe/Z++H/wAX/wDgnH4f+FHxk8CvqHhjV/ip8R/EGq+Hb9NT8P3Uur6V8TtS1bSdWMto9hqUN3FdW1vcxXSSo0yKAXeJiG9nOcVVw+c1K+Hq8s40aMIzjyyXJKgoyVmpRafNJWfykrXPOy3DU6+WqlXpXhKtVk4u6d1Vcou6aaae1r7banhn7U3x18W+Ff22viJ8M/Gv7RGu/sRfD/RfhB4WtvhD4w8Bfs9+GPiR45/aIuLq3lj1Xw4fH/izwT40jmi0SZYbK18I2aQXk003nuXZy1dOBwtOeW0a1PCQzOtPEVHiYVcXOhSwav7tT2MK1L4lr7S1ltZJI5sZXlHHVKVSu8FThSh7CVPDwqTxGnvR9pOnP4dlG1763Vvd88/ZP/Z61343/wDBGHxn4Iuj4htPiF4Z+JPxZ+KHw61vxdoqeFvElr4y8C+OLrxb4b1q70kW2n2+h3OpGzfz7e0trW1tvtkkcUUSL5a64/GRw3ElKpHldGdGjQrQpy9pF06sI05x5ryulzXvJyva73IwmGlXySdP3vaxq1atNzjyS54VOeLaUFy36rl62vG94/Un/BHb/hNPjh4W+L37enxZ0WbR/iF+0p4g0nw/pGnXeHn0bwD8LbGPw3aWttLlh9k1PXLfUtTXyiySb1kPLDdw8Q+zw1TD5VQkpUcFCU5NJpSq13ztvzUeVaq6ta8re715Kp141sfWjariZKMerjTpLlSXZOV39lvqrq51X7FfiLRvhN+27+378BPHGoW3h7x38Rvipo3x2+HWn6rNDZN448B6/wCH7ewn1DwyZ5FGrPpOoWzW2o29oZZ7QlWmQAjdGZRliMtyjF0k50qNGeFrOK5vZ1YSlpO1uW6ejaiu3NuXgZxo47MMPUajUqVY16aenPTceW8b6Oz93Rvzs173c/tzSRxftV/8Ex3lkSJB+0F8RsvI6ogz8HfE+MsxCj8T+fNZ5Z/uGd/9glH/ANPo0zB2xeVN6L6zV3/68s5X/gqh8YfHPwug/Zjj0fxFY/CX4X+Kfi3fW3xS/acf4T6b8YtR+BNlZaBNc+HdV0DRdV0fXtL8P6n4k1N20lPF19pl1baZFvUqvmFqvI8PSrvG80XXrwoL2GC9vLDrFOU7VIzlGUXOMY+97OLvLdWt72ebVp0vqqUo0aM6rVTFOiq7oWj7jinGUU5NtczjZdbrmcfir9hy81PxR+2B/wAFI/Ftp8Zfid+0j4a8SfsufDZPD3xs8f8Aw10f4dnxxLa+GPGdo40Cw8M+FfCWkaxp9gVWys9Vi0trm9jVGM80bRO3o5oowy/Jabw9DBzhmNX2mGo13V9n78Pjc6k5Qk3q48yS7Rs+bhwDcsZmUo1qmIhLC0+WrOlGl7T3Jr3YwhBSWllpd2v0Psv/AIJ4fs8/Dn4uf8Exv2Sfh78YPAr3ul+HLTwx8Q7PQ7s6n4evdK8c+FvEl3rei67myl0/ULfULbUf9JmV2VbwO6XaSxykNwZxi62HzvH1sPVSlPnouSUZqVKdNRnCzVuW2i+Hl6faR3ZbhqVfKsHTrU7qPJUS1TVSEm4yuuR3vq+j69y3+zZ4W83/AIKdf8FLrvUtBnGl6/4N/Zy0NNRutPnS11bSj8OJra/0631GSJUvLdfOkjuYoZnCSOfMUSH5Yxs7ZJksY1LyhWxk3FPWMvbRtJro2tm09NFa0lIw0L5pmd4+7Knho3e0r03dLa9k3te12m1seVft1JZ/sV+Af2Ovg98FJrP9nL9m/wD4Wl4otPGvx+Pw0X446n+z5brpkuraBN4dtfFmn+Krbw3e+K9b1G/0+LxVqljdWukW8T2kIhR1VenK75jWzDEYm+LxvsKfs8N7b6rHFvmtLndNw51CMV+7i48273tLLMEsFTwdChbDYZ1Z+0xHslXeH05o8qqcyhzttczUlG263POP+CZwk8Zft2/t6a5e/Fj4i/tJeCPGnwu+BdpZfGH4l/DbRfh3H8RtPOja7p1+NN0vw94V8JaHq+jxQPLYQaoukie+tvnklkjZHbXOrUsqyqCoUcFVp4jFt4ejWlWdB80XG8pzqSjK7T5ebR2uotKJllXv47ML1amIhOjQSrVKUaSqKzTtGMIRcUnZO2u+l+WPi/7HPwb+IN1/wUAtf2M/FWm3N38B/wDgmd4n+JHxc+H+rXEi3FhrM/x0uDdfBrSXBMii68DeEbzWYoonRJLZpIpFC4G7pzHE0VlLzGm0sVncKOHqpN+6sNpiJRWlvaVFHrLXRtmODoVXmKwU1fD5ZOrWpvdN4izop3vZwhdd/SyZ/S1LrejQyPFPq+lxTIxWSOXUbSKRHHVXjdwysD1BGfpkV8aoSa92EmvKLa/D+vuPp+eP80fvX6n5C/8ABVGw+KXxq8S/sWfsxfA++0G08S/EP46D4uar4l8T6Hq3ifwBpHh74G6afEVi/iu20S4s3u7C98S3mnJDZrqNpJPc2kYWQhXVvoMjdDCwzLG4pScKOG+rxpwkoVZTxUuR8nNdxahGXvcrSv5Xj42be1rywOFw8oqVXEe2cpJypqOHTknNRavHma0Uo3dtXaxlf8E89J+NXwD/AGt/24vgP+0Dq/g3WtV8c6p4M/ag0DxZ8PfDGu+EPhtdp4+059E8WWWi2Wv3+qNY3dlrehCbUoJNUncy3gnCBHUKZtLDYvAZXicHCpCNJVMDOnWqRq106TUqbk4qN04zajaFrJK8ULLVWw+Mx+HxDhKVRwxUZ04OFN865ZpJuVmpLv8AJXR+x0et6LM6RRaxpUskjBY449Ss5JJGPRURZdzMeyqST2zXgOnNauE0u7i/1PaUovTmi/JNfofhV/wUA/aH/ZM+INr+0X8Af2vv2etWsvjH4A0XxFpf7KV9deAfE/jPxL8UbjxNoKTeEvFnwM8WeGvD8r6Frp8Umxt7/T7fVbW80m708T38ghUPX02U4TH0ng8Xl+Li8PVlCWPj7WFKFDkn79PFU51LTjyXaesZKVvOPg5jicHU+s0MZh3GvSTWEbpznKrzr3J0JRWkubRrdNa8t05eb/Hnxlr37POgf8EUfiF+1VqWvaTe/DW/8Qr8Y/E97o+veIrzQdWu/g2mmq3iJdFsdWvzfSX00NlcTNAxlvd+4nBNbYSnDFz4mo4FQkqyp/VoKUIKcViG/c5nBW0bW2mul7GVecsNHJKmLbi6V/bTd5OLVCzc0ot3vpfZ36WPrj9gTVp/jl+17+3F+1z4T8O+LdN+CPxUf4QeBvhZ4k8YeGNa8H3Pj/8A4V54U/s3X/EmhaL4hstO1hvDrahObXT7+6sbdL4wyyQEoM15+bL6tgMswFSdOWJofWKlaFKpGoqXtanNGEpU3KPOo6yje6cktbe72Ze/b4zHYyMZqhVdKFGc4OHtPZQ5ZSSlyy5bvRuOvS28vs79nX9rjwD+014y+P8A4U+Hug+L4rL9nn4m3vwl8R+MNZsLK18L+J/FulQpLrEXg67g1C5uNTs9KaWO3vLme1tAtyzQqrMr7fOxeAq4KnhKlWdNvGUFiIU4ybqU6cvgdVOMFFy3STlda6andhsZTxU8RGnGdsPVdJ1JJck5JXfI07tLZtxWva1j6qrhOs/Gr/gpf8bPGnwz+Ov7Kvh26+JUf7MnwW8Q2XxA1DxX+1hZ/BvRfix4k8EeMbJLC30DwHoN94i8PeJ9G8BN4psZLq5u9au9MY6hHbrYxSKy19HkuGp1sLjpqi8biYOkqeAeIlQhVg7uVWajOnKr7NpJRvo3d2subw81rzp18LD2iw1GSqOeL9jGrKE9FGnFzpzjS51e8+u2lnzfDXwKh1/Xf2Wv+C61+vjb4l/Ge28Xad421Dwx8SfHnw8tPAXiP4mwX37Num28HiCw8J6D4c8NadJDqTRxxWNxp2iQTahCsMk8bztivRxXJDH8LR9nRw7pypqdGlV9rCg/rknyOo5yd49U5aO6TcbM4MPzSwuevnqVlNScKs6fs5VL4fVqMYwjq7apXlpfY/Yv9nr9n74YfEj9l79g6++IXgtLvWvgJ4B+Ffj74ZhpdR0W48F+NLf4c2uhS3kdtYz2Zk/4l99d2d3peoRyWc27NzatLGjL8/i8XXo47NVRqWjiq1elWsoyVSm6zmk2/NJqUbO391tS9rC4elVwuAlUh72Hp0alLeLhP2Ue3LdWbvFq2uzPnj9jHwJZa5+1r/wWH0zxX4all8P/ABD+Pfg3w/qJv9PntLfxR4X1D4F+G9K1CyhvWSM31gYru/ti9tNIkEs0vltHNk11ZjVlHA8OunO06OEqSVrN06kcRUabjqk00nZ726aI5sFTU8ZnUZR92pXpxk2mlKLw8Fa6eu7T27Nu3u+J/tk6/H+yV8U/2Lv2fPBXj7/hi79lHwx8KvHVjpH7TGn/AAnsfjP4q8JeJ9FuNH0vw58HNC8U+N9C8aW3gaHXNBkudSvNT1OznutdjsotPhuQY9q9WXQ+v0MyxdSj/aWPqV6blgniPqsKlOSbliJQpyh7Xlm+VJNcu7WiOfHSWEq4LDQqfUsJClVisV7FVpwkuVQoRnUU1TvF8zclK6uk9Hy4/wDwSs8AWfxbg/4Ko+DfiJ4i8d/FrwJ8Zv2gr/SLjx78TvAVh8P9c+J3hTxh8IPD2lXfiqTwrpmheGdItY9Tt52uLSWw0aw85Ut7mSNZyStZ7VeHlkVWjGnQqYfCqSpUarqxozp1pyUedznK6ekk5Ss9E2mmLKaftlm0Ksp1qdXEfHUp+z9rCdCKk/Z8tJJSvppomm27nmn/AASn8FfFz4jftRa/p/xutbq80v8A4JZeANe/Yq+HOuXkq3dv4v8AGut+JrrVNX8e202+RGvY/hRp3w/0OV8m4ie5vElZDMErfPauHpYGLw1ovPKscxqxScXTpRppRpW35frDrSV72smtVaOeU061TFtV1eOVU5YGk91OTk3Kp1bbpKnHfTm6o/oxbXdDRmR9Z0lHUlWVtTs1ZWBwVZTISrA8EHkHg4wRXyHJN6qErd+WR9Lzx/mj96/U/n9/4KoW/wCy+/7e37EWufthWuoT/s/wfAf9ou1v9XsYviA+nw+LL3W/ATeGYJtR+GyHWIpLuGPU2t4jOttcCNzJG+1BX1eRyxv9lZlHLnH639awjjF+xu48tX2jtW9zT3d3o7PU+dzZ4X+0MDLGX+rqhiLyXtGuduKir0mnq7aXWmqatc9//wCCP1na+G/B37Tlj8NtH8Z+GP2LLb48Xtx+yF/ws7SdY8O69P4Jv9D0668ZXNl/wl0Fn4qvfCE3jmbVH8Map4mjl1K8t3l/0qeFUK8nEDdSrgZVp055lLDJZgqLU4e0UpKkv3d6aqeyUeeEGlF7rmZ0ZLaEMUqSqRwSrv6n7VNS5HGLk1ze84c7k4ud3a99FFR/YaDWNGuZo4INX0uWWVgqRxajayyMfRY0cu5AycKM4Bxmvn3CaV+SSXdxaX3s9rmi9FKLfa6/Q/m+/wCCgfx5/Z3/AGifhx8cPhl45/Z58S+DP+ClXgXxRd/Db9mPSLLwH4q1b4t3WtaX40tLn4YfEz4YfEzQNCtrVfAOr2skfibUbk6wmlaTa3GoWOrI8iPu+wynC4vB1sLXp4yFXJqtNVsbJ1oQw/K6dq9GtQm5P2sHamvcUpOzXTl+ZzCvhsTSr0p4aUM0hN08KvZzdXmVTmp1KVWO1Nr3patJNq7PbP2o/jR4X/Zj/wCChv8AwT1+Kn7R+vah4f0TSv2NvjX4T8X+Lrbw34k8SWR8e6nrPgItp8ieGtK1a4W81O7tL+S2RoU87YxBJIrlwWGnjcozfD4OClKWY4edOm5wi/ZRjU9685xTSVrtNfP7O2LrQwuYZfUxMnCKwVeE58k5L2jlTdvdUn7zjJr/ANJd0j6I/wCCXGna/wCIJf21P2ib7wr4o8HeBP2m/wBrPxh8UvhPb+OdDv8Awr4j1f4dWvh3w/4Z0zxVf+HtXittU0ey12XRbnUNNh1K3trp7B4p3iVHRm5M7lGP9m4RThUq4LAU6Nd0pKcI1nOU3TU07ScVJJ8ul9Pdd1Lryrmf17EOM4U8TjJ1aPPFwk6fLCEZOMrNc9uZXSaVt7Xl9bfsjfta+A/2y/h74j+KXwy8P+MdJ8E6L8R/Gvw50rV/F2nWemp4wuPAurS6Hq3iTwzHa3181z4auNTt7q20++uDbzXDWsxNugWuDH4Crl1WFCvOnKrKjTrSjTfN7NVVzRhN2j76i05K2l1ve8uzB4yGNpyq04TjCNSdOMp2XtOR8rnC28G07N8req5fdufVFcJ1n4mf8FCvjt4w+Hf7YXwE8HeIPjO/7HvwR1H4O+Mdfh/ao0X4J+H/AIoeL9R+JTeI7ewPwg0jxR4n8LeLdI8B2c+gxQ69eQNpq3XiOSSGGCX/AEYivpcowlOtl2KqQw39oYpYinD6jLEyoU1Q5W/rDhCcJVWpO2s0o6v3bJx8HMq86eMoQlWWEoOjOX1lUY1ZOq6ij7HmnTmoJwUZNWbk5JJ6RifmboGi+J9Z/wCCYP8AwWMgm1H4j/EqTxR+1drGraL4n8cfD6PwZ4u+Iemanf8AwnmHiibwPo2g6LYWg1yAG7aHTNEtIngPmTQJL5yL7M5wjnfDrtRo+zwKjOFKr7SnSko4m8VVlKTfK9Pem7dHZo82Ck8qzqzqVXLFycZVKahOpd0nzumko3lbm0Xrex/TPY/Aj4W+MNZ/Z3+K3iTwpFcfEH4F+Friz+GOtx3d/p0vha08Y+HNK0nxJp62VnPb2l7Z31lY20P2LUYLi3tXh823ihmLu/xf1qvTji6FOo1RxVROvCyftHTnKUHd3aabd2nd31vZM+ljhqM/qtaUP3mHi/ZPWLjzRSeml9Et1purXZ+cH/BOz4K+Efif8E/+CjXwp+LPgqTUfA/xg/by/a20LxnoWqW1/o58WeE9Z1PSbAMbuL7JfyW8tnlNO1OznV4PLWSxuVeJXX2M3xE6OJyevh6ijVw+VYCVOceWbhOMW2rNNXvpKMlr1tdHm5Zh4VcPmNKtC8K2OxcZpppyhKSW+js1s1tum2rnl/7Wnxb1n4M/tpfD74K6l8ddR/YY+APhT9l7w5F8K/jx4Y+B+hfFfx38UvFEfiG70nWPhFbfEPxn4T8bw6FYeEtF0rRb/wD4RcW51bxLfajHemWcqqvvgKEcTl1fFLDLM8XPHTlXws8TOhSpQcOaNd0YVKfO5ylP3/ejBRtbRuOONrSoY2FCVf6lhoYSPsa6w8a0601K3sfazpz5VFKL5Em3ur3ajzH/AATY/Z4h/aR/4Ju/tq/s9fEafxffWPxh/aY/a90Oz8R+PfCsPgvxXc3Wv+Lpr7wt4+u/C1npmj6foOqjXhp3ihbXStNsbS0vo2FpDBsUJpnWLeCzjLcXRVNPDYPAScKVR1IJRp8tWkptzco8l4ayblDdu7QZbhvrOWY7D1XNqrisYlKpBQlrO8Kjjyxinze9pBJNWtoan/BHGX4tftHfED4v/tgftBaTNY+M/hR4I8F/sB+DPtUiXEM8/wABNw+OfjHTJ1aSNoPG3xPkLPPE+Jo9HQvuPyxTxD9XwdKhl+ElenXq1M1qWvdfW/8Adqcr7OnQWiu+Xntpoh5KquJqVsbiE1OlCOXwvrf6u/384t9J1O2/KfvWde0JSVbWtIBBwQdUsgQe4I8w4I/zjpXy3JNq/JJrvyu34H0HPH+eP3xPxq+PXxa8Efsjf8FULP8AaM+PV1rHg34E/Fj9iTSPhJ4d+KkPhnxD4i8I2fxH8EfFfxB4svfCeu33hvTdVfSNS1Xw/r9vf6CL2KKHVPIuYLaR5k219FhaFTH5HLCYVRqYrD5lKvOh7SEKkqNXD06aqQjNxTjGcXGVm+Xd2XxeJiK9PB5r9ZxDdPD1cDGlGtyTlBVYVpS5JON7OUZJxuknqrn6F/sqftF3n7SXwctvjRrPw58QfB7QPEXivxZZ+BNM8du+l654l8A6TrFxp/hPx7daXqVppt9oUXjbT7c61p+i6jbrf21hLBJNnzcV5GOwaweJeGjWhiJwhTdV0vejCtKKdSipJtTdOT5XONk3stGelhMS8TR9tKnKjFzmoe00coKVoz5ZJOPOlzKLu1ffQ+ihrGn3Cyx6df6bf3ognktrODUbV5LiaOJ3ji+RmZBI4VGk2sIw28ggEVyOEo25oyir7uLX5223019bpHTzJ3s03bRJo/mf/as+N3wP/a10/wCHUvw/+AXib4Xf8FatL/aG+EWg2Hh6z8A+K7b4wfDW0+H/AMT7G08Wav4m+JlhoWl6Pq/wdk+GVjrNx/aV7qk/h/VNH1K3sraBrg7K+zy/DYnASrKrioYjIJYTESc3Vp/V6zrUX7OFOi5SlHEe3lHTl54yUpPm0kfL4vEUMZ7N06E6WbxxFKPKqc/a01Tq2nJ1FBRdH2Slu5Ralpds+mvjF+0v8JP2Tf8AgsL42+IXx21vWfDHhfxR+wL8NfDHhzVNN8F+MPFSeIPFOm/FzxXqt3oGlQ+F9E1mSXVTZkTw2bhHdZI1BLMtcOGweIx/DkKOFjGdSGa15zi6lOHLB0KaU5e0nBct9N/yOqtiqWDzmpVxDlGEsvpwjJQnPmmqzfLFQjq7JvdfI+kP+CTnhHxd8P8A9krxf43+JHhfXPh2fi1+0B+0r+0RpnhrxjYyaN4m0H4ffEj4l+IvF/habxLpVxi40jUrnw1JbandaddrFdWS3Cw3MccquF48+q062Pp06M41vq+EweDlOm+anOtRpRpz9nL3VJKd0mnrbpopdWUQnTwc6lWEqftsRicSozXLKNOrUc48ydmny6tNXV7OzR9Wfsf/ALVXgr9tD4I6P8f/AIceG/GXh3wH4m13xRpPhZ/G2n2emal4i07wvrd3oL+J9OtbO9vlOgavd2NzJo9zLJFNdW0YmaCIMBXDmGBqZdiZYStOnOrTjCU/ZtyjFzip8jdkueKa5ktE9E3a8uvBYunjqCxFKM405SkoOaSclFtcySctG1p3Wut2o/T9cR1n4PftdftAeLvCX/BQHW/APjr9orVv2G/hnp3wH8EX/wAKvi34I/Z+8MfEnx1+0H4j1rWtZk8Y+B4fH3inwV40tLCz8FXNppMdl4AsbSDUNTv9VGoJ5qttr6jL8LTqZTGrSwcczrSxVRYjD1MXOjTwcIxh7Or7KNWnzuonL962lFLlb2cfnsbiJwzCdOpiXgaaw9OVKtDDxqTxEm3z03UlSqJKD5fcWrcotXekfz/8EeEvE19/wRv8D6Dq+j+Mtfv5f+Cs/hjULqDxV4PbR/Eup6M/7Ysuovreu+EbTTbO10dby1kOqajZ2unWel2BmmRYYIU2L61SrTXEdWcZU4L+wJpclTmgprApckJ3fNJaJa8zSvrZo86nCUsmpxlGcv8AhXi/fhaTi8Zzc0oJWjo7tJJJ35bH9Rl58D/hfqPxx0H9ou88MxyfGLw18PdW+FGkeMFv9Qilg8Aa1rVr4gv/AA/Np8dymmXkLavZQXdvcXVpPdWbealpNFHNKjfELE144WeDjP8A2adaFeVOyd6sU486l8S92Tuouz+0pWXL9Z7Ck60MS4/v40nSUrte5JqTTV0m+ZXTautldNo/KL/gmF+zx8PvjP8A8Ew4/gp8bPAcupeC/F/xu+PWseJPC2oJqvhu7vr3Tf2ifFPiTRNXaezbTdWtryK/03TdQtNQgmimkSCLbM0DBW9zOsXWw+dfWcNV5atPCYSMKkeWaXNg4QnHXmjJNNppq2vW94+PlWFpVsq9hXp3hKviHKOsXdYmU07qzTTSa19LWRxH7Vnx78WeEv2+vGHw38cftG63+w18NtG+Avw4k+DfxI8B/s/+GPiR49/aS1fV7/V5fGPg9fH3ivwR41gFp4G1GHTtP034e6dBb399qOotqbCXz03bYDC06mVU61LBxzStLF1ViaNXFzpUcHGKj7Oo6MJ0/eqRvKVZytGMeXW1o54zETjmE6U8Q8DTVCl7GpDDwqzxL15o+0lSnZ05WtSV5SbUl2PF/wBjr9mXxH+0X/wQ++I3wcuH8RaJ8TLP4vftPfET4T6/4x0VPCnibQPiv8Ov2hvGPxE+GXiq90eO1sbbw7eXPiTSrOa/ttMtrSwtIdUv4bGKO12Rr1ZjjYYTiajibU50XhsFQxEYT9pTnh62EpUq9NTd3JcjaTb5tFe92Y4LCyxWRVaPvKqq+Lq0ZTjyyjVp4mpUpTcVpFuSV1FaczSSsuX6o/4I56v4w/aO8M/Hj/gpF8WdAm8NeOf2uvE/hjw34W0bUChm8L/Bv4A+HovAelafbzBjEljrfxBh8f8AigmAi2uUvba9DOZSy+fxDGng54TJ6E+ell8Kk5yX2sTip+1lfZ3jRdKGq05bWWvL2ZK54mOIzOtHlqYuUYQTd+Whh4qCSfRe09pLrvq3ufsoNe0IkAa3pBJOABqlkSSegA8wZJPbP5Zr5/2c9+Sdv8Mj2ueP88fvifgrd/tcfBj9kL/gp7/wUk1T40ah4r0y4+I/wf8A2Qj8M9H8O+APG/jLVfiFqPhbwN8R4tV0XwvD4X0HVYr3VIrvV9Ls/s7zQlZ76EMVUO6fTrL8TmGS5OsMqb9jicw9tKdWlTjRU61BxlUc6kWotRk7qOye28vAljKGEzTMnWc06lDCeyUac5Oo4QqXjHljK7vJdVvpe/u/cv8AwSp+G3jD4Ff8E+v2c/BHxb0iXwH42bRfFXinWfCviGW3sdW8OP498d+KPG+n6Fq0TyFYdZ0/SddsY9UtA3mWd551tKokhcL5ueVqeLzbGVcNL21LnhCM4JyjP2VKFKUo6L3XKD5XrdWd9juymnOhl2GhWXs6jU5uErJx9pUnUUXq9UpK/bbXVy++9Q1xP7K1ifw6bDxFrVlpGpXumaLa6paLJql/a2c01jpxnUuLVb+7WCz+1OjxwGcSOrBcV5XI0486lCLlFOTi/di3rK2l7K7tfW3Q9Bz0lytTkk2oprVpaLTu9PK/qfzY/GT4z/Aj9rvx3+yb4x+AXwQ8S/Cv/gqEP2qPghqPxb0a1+Hni7Qvif8ACXwP4H15dK+OOmfGjx3HoekaLr3w3j+HGl32hWNxqN/eaZ4it5dHGiQswQxfY4bDYrL6ePhi8TCvkjwGJWHm61OVDEVKkebDPDUuaU41nXak0k3FqV+p8xWrYfGVcJUw9CVLNVi6DrRVOUalKFN8tdVqnLyypeyTiru0vds5P4fX739rf4M/skf8FN/+Co9z8YbvxfYX3xL+G/7J/wDwq/QPDXw98b+MdY+Il/oHwb1izvtG8KQ+GtC1KC91OO/1Cxsfs8k8Gye5QSsipIV5lgMTj8kyRUFTao18d7edSrSpxoqWJg1Ko5zi1FqLd7W0srX97aWMo4PNM1ddzTq0sIqUYU5zlUaoyXLFRjK7u0uyff7P2d/wTr0PW/2Of+CWfwfuP2gNJu/Amo/Cj4PePfir8R9C1ARrqvhTS77XfGPxRutI1KLeI4ta0zRdVis7y1aZRFqSPbSMhRq8/NpRzHPMQsJJVY4jE0qNGa0jUahToKS/uylFtPrGz6ndlsZYLKaLxMXTdGjUrVIu3NBXlV5XrbmUXZ/DrpZW937L/Zl+POiftQ/AP4W/tCeGPC3i/wAGeGPi54WtPGfhnQPHlha6X4rt/D+pySnSLzVdOs7zULe0Oq2McOqWkS3cjmxu7Z5BG7FK87G4WWBxdfCTqU6s6E/ZznSbdNyXxKLai3yu8ZXS1TXQ78LiI4qhTxEYShGrHnjGdublb0bs2tVZrbR3tqe61ym5/Ov+0F8fvGi/toftjfDX4iftLeLP2LrLRvD/AMP9A+BfhT4Vfs1eEPHnjj9rrwvqvw++2X2uXnj3xV4B8YyeMJbTxZqOoeBtJ8H6VNaDw9HBLJchFuHmr6/CYSn/AGbl1algqeZOU6s8VUr42pSpZfNVrKPsYVoez5oRjVlN8zley25T5jE4ibx2NpVcS8FyqlHDwp4WFSpi4un8XtJ06nM1JypxhHlUXe+6lHwvwP4S1+7/AOCSf/BE7QNW8M67c3ukftx/ssT63o2qaFdf2hpljpnjz4qSNca3pP2U/wBmW9li3kn86CGysmMQQrEI9/VVnBZ/xLKM48ryzHckoyVm3Rw+kXf3m1fZty37uOUISeTZJFxbax+Eck46r97VbvHWyV/Tba6R/QD8YfgZ8NBq/wAa/wBoy18L7vjXrf7NXjL4N33i2G91NrjU/ANhba34m0zw9NpKXR0y6ltdenluLO+Ni+poJ5bSO5+zSmKvk8Lia/LhcI6lsNDGU8SqbUfdrNwhKfO05JOCs43UetrpSPoa2HpJ18SofvpYadFyV1emuaSjyp2fvNu7V+ifQ+L/APgnd+zv8Nvi1/wSt/4J6+Bvi74Fe8tPAXw8+CXxY0XRrltV8N6h4d+J/ge8bxLoXiECwl07ULXVLPW3lu7yGYql+Z7iHUYriKeVH9LNsZWw+eZtVw1XldaricPKSUZKdCp7koa8ycXGyi1tZNctk48OW4WlWynLqdaF/Zwo1Uvei41YPmjLTlaalq01rs0teb4w/aB/aB8bzftc/tvfDn4kftKeLP2MBpGl+FvDnwN8A/Cn9mnwj468a/tdeD7/AOHC3DeKL/x34o8A+L5fGsz+JNR1HwXpfhXSJ7FvDNvbyC48ovJOvo4TCUlgMsrUcHTzFylOeKrV8bOjTwFRVbezVKNWmqa5EqkqjXv3vZJqJw4nETeLxtKriJYPk5FQp08LGpPGQ9n8ftJUqvPLmbgorla7pNsxvhz8FfGXiv8A4IB/sm+MvD9jfaJ8df2QfBXhj9qj4XDWYG0jV9O8W/Afxv4m8Tat4eu1uVgfTYvE/gS38R+FruDMUAt9SiRQYEjVnVxNOnxXmFKTU8NmFWeArcrUouniqNOEZqyalyVOSadujemoqVGpPh7CVI3WIwcI4uk5K0lOhOUnF3+HmpqUNXZXs7o+/f8AgktpGq+Jf2ffHH7Znj7TJPD/AI+/b2+KniT9pzVbLVSIbzw58OdYEehfBbwncyzH91b6B8N9K0iaKEuY4X1OUj53ct5efSjDF0stoy56WVUYYGLjqp1l72JqK17udaUvN26bHo5PFyw9THVFy1MfVliWpbxpy0owv0UaaWj35r9WfqEmuaJK6xx6xpUkjsESOPUrN3dmOFVEWTczMSAqrkk8AE8V4rpzSu4TSW7cZJHq88f5o/fE/l3+KFn/AME5tP8A+CmH/BQu+/b+0/ULW/1W8/Z0b4VXs9t8Zraz1HRrX4TxReI2sbn4bRx2F4LbUfssUzX0ks0Mp2R4G8V9rRebvJcoWUyi0vrn1lJ4ZuMvbvkTVe9k1e6UfJtWPlaiy1ZpmLzBNc0sO6TtWtJKik/4emjdtbXv/dTl/Rn8DPGHwc1r4MfDPWPg5rFn/wAKjuvCmn2vw5nu5dTsDL4Y0pTpdiiR+KBDrrC2W0MBfU0N4/l+ZMzM4ZvkMTSxMcTXjiIyeIVSTr2UX+8k+aT/AHdoat391W6K1j6TD1KDoUpUJJUXBeyvp7q0Wk9enXb5m98TPHOr+Ffhp8QPGPw+8NL8U/F3hHwjrviLQPh/ous2ltqPjDVdJ064vrHw3Z3uy5js73WZoBY2c0tvJH9pliBBBO2aNFTrUadaf1enUqRhKrOLtTi5JSnbS6ind6/dqVVquFKpOnFVpwhKUaakrzaWiTWzeyvpf5n4G2XxH/Zu/aZ/bR/YV+Kn7Enw01nwT+0lL8V9W8bftp32i/Dfxf4C1Hwn8Jb34d61bfEPwV+0Hqd5o2i6LrOu3HjGbQdM0O31E6jqF7q9nFqOmutqGkr6mVHGYHLczoZlXjVwfsI08sUq1OqqleNWLpVMIlOUoxVJylJWjyxbUlzO0fnlVwuLxuArYGlKniXWdTGuNOUHCl7OXtKeIekXJz5Uk1e+qtys8+sv2qfhj8ENc/4LS/A7xJaePdZ+Nvxv/aH8eQ/B34XeEfhx448TeIviG/i34AeCPBehyaFPpOhXOkfY5/ECy2lxfXeoQWtkkE81zLHFGztt9RrYmHDeJg6Sw2GwlN4ivUrUoQo+zxVSpJT5pcyag9EovmeiT3I+t0qEs8oTVR16+IqqjShTnKdT2lCMIuNotWv1bivXVx/XH4deMtL/AOCeH/BMX4X+LP2goL6xt/2YP2W/h6vxL0vREt7/AFZdX8NeEtGsNS8P6PE1zBbX+qtrMn9kWcYuoorm6xtlVG3V4FaEs4zqvDCWbx2OrewcrqPLOpOSnJ2vGPL7zbWi6bo9ilNZdldKeITX1XC03VS1acYpSitk3zaJfLW1z7T+F/jmP4nfDfwF8SIdA17wrb+PvCPh/wAYWvhvxTbwWniTRLTxFpltqtpp2u2lrcXdva6rb211Et7bRXM6wzb4/MJU7fNr0nRrVaLlGbpVJ03ODvCThJxcotpXi2rrTbud1Kp7WlTq8soe0hGfJO3NFSV0pWbV0nrr9x3VZGgUAFABQBs6B/yFbf6S/wDop668D/vMPSf/AKQzDE/wn6x/M9Hr3Tzj/9H+/igDgfE3/IQX/r3j/wDQnrxcw/jr/r3H85Hfhfgfr/mc7nHSuH+v67HSRxwwwrshhiiTcX2xRJGu9jln2oqjexJLNjcTySaPO7v5tsVktku+xJgegGeuBjP1/wA/zoH/AF/X9fkHpwOOhwMj1weo/wA+9Af1/X9fmHr3BGCDyCD2IPBH1oAZHFFCgjhiihjUkqkUaRopb7xVUVVBY5LbVGScnOSaPv8Avv8A1/XYSSWyS9F/kfPlt+zT4Ci/ac1D9q+7v/Emq/Emf4XxfCTRrHUb60l8LeFPCx1ca1qcnh3TUsI7q01bXbuO3TVr2e/uPPtraGGOOJVFdf1ys8EsBaCoKv8AWJOKl7SpUS5Y88uazjFaxXLe/Va83OsLT+tPGNylV9l7GKbTjCF7vlWjTbWvfztzHN/HL9iL9lb9pXxLp/jD44/B7RviD4l0rTP7G0/VdR1rxdps1tpgma4+yLDoHiPR7V0852ffLA8uTjeVGFvC5ljcFB08NiJUoN8ziowlra17yjJ7L/h7+7NfAYTFSU69FVJJWTc6i03t7sor8Pu+113wH/Ze+An7Mem69o/wI+HGm/DrTfE95aX+vWmm6n4i1NNRvLGKWC1nkfxDrOsSxNDFPKirbyRI28lwzBSueKxuKxsoSxVaVZ004wvGEeVN3fwqN72W60tpa75rw+Ew+FUlh6apqTvK0pO78+Zt/j91z3z8B9cc/n1Fcp0AOCSAFLdSqhS3sSOT+PH6UW/D5/1/XYP6/r+vzCgAoAKACgA49Bn1xz+J7/j0/Gj+v6/r82H9f1/X5ngX7Rf7OfgX9pvwXoPgXx/ea/YaP4d+IHg74kWM3hq8tbC9fXvBGpjVdJhnkurK+ifT5blQt7CsaSyxHbHNC3z11YPF1MFVlVoqLlOjUoPnTa5ai5W+/Na9n03fNqo82JwtPFwjTqOSjGpCouVpO8Hdau+l12d/I95iijhXZFHHGvBYRosYdsYMjhAAzt1Zjlj3J6Ly/e/V3t6dtlp/kdNktvyt/X9dx2xN5k2J5hUIZNi7yo5Cl/vFQeQp4Haj/h/6/r9Q/MR4opDG0kUUjRMHiaSNJGicdHjLqTG3J+ZCp9zxR+qtvbR/1/VxNJ7pP1V/6/rsx+B6D1+6MZ9SO59z9e1H9f12+QwoAPp+gx/n+vWgBjxRSGNpIopGibfE0kaSNE/9+IupMbf7SFT7nij5vXR62/r+rbhZPf8AK/8AX9djhvij4Asfir8OfG3w11LWdd8Pab468N6r4X1LWfDFxbWXiCwsNYtns72bSru6tby3t7028skcc8ttME3ltjEAVrQquhWp1oxjOVKcakYzu4uUdUpJOLtdLZoyrUlWpTpOUoqpFwco/Ek9HZtOz+X3FD4OfCfwh8Cvhb4E+D/gG1ntPB/w88Oaf4Z0GO7kSe9ezsI9oub+eOKFLi/u5C9zeTrDEJriWRxGudqvEV6mKr1cRVd6labqTtorvol0S6LpsFCjDD0qdGmmoU4qMb76dXtdv0+6xi/Ev9nn4KfGLxD4E8X/ABK+G/hvxV4u+GOtReIPh/4rvLZ4PEvhPVIjnztH1uxkttRt4JTxc2LXL2N0PluLWXrVUcXicPCrToV506deLhVgrOFRP+aMk02ujtftaxNXDUK8qc6tKM50nzU5v4oPyas/k20+q1Oc/aK/ZP8A2fP2stF8O+Hv2g/hzZfETSvCWsTa/wCG4bnWfEmg3GjaxcWrWU1/Zah4W1jRNQilltXaBx9rZDGzDyzk7rwePxeXynLCVnRlUjyTajCalFO9mqkZq1/L8icRhMPi1GOIpKqoPminKS5W9Lrlcdbea89kez+GPCnh/wAHeF9E8F+HdOSx8MeHNJstD0fSpZrnUI7XStPgS2tLR7jUpbu7uxFDGiebeTTzvt3SyM5Zq5pzlUnOrUlzVKknOcl7t5N3vaKSj8kvRao3hCMIRpxVoRSjFauyW292/m/vszoAFUBVVVUAKFVVVQqjCqAoACgcBQAB6DpU/wBf1/WnTdlWX9af1/XcX8Mew4/l/n86AD14HPU4GT6ZPU/59qA/r+v6/Ia8aSo0csaSxuNrxyoskbr6OjhlYexB9e1ANX0eq8xVCqAFVVVQAFVQoCrwqjbjCgcAAYHtR/X9f1p03YHz38Fv2a/AfwO8Y/HH4geHb/xHrvjH9oL4hyfEXx7rnii9s767F8mn2ulaXoWkfZLGyWz8OaFp1nDaaTYSCWSCPeZLiZ2LN1YjGVcTTwtKahGnhKPsaUaaaunJylKd73nKT5pNPV+j5uahhadCdepFylPEVPaVHJ31skora0YpWSs9N3u5+O+PP+CaX7DXxO8YeIfH/jz9nvw74i8YeK9TudZ8Q65c+JPH9tPqep3bmS5u5bfTvF9jZQvK5LFLa1hiH8CAZFdNLOczoU4UqWLnCnTiowioUnyxWyu6d3bu7vu3e5jUyvAVZyqVMPGU5ycpS56qu3u7KaS+S+7Q+qPhh8LfAHwY8EaH8OPhh4atfCXgnw3BJbaHoFnc6hewafBLM9xJHHc6teX+oSBppHc+fdzNk4yBgLw169XE1ZVq03Uqzd5TaSu0rbRSW3l9510qNOhTVKlHkhHaKbdvnJt/j9xb+Inw78F/FjwX4g+HfxD0G38T+DPFVl/Z3iDQrq4vrWDUrLzUm+zy3Om3VjfxL5sSPutruB8rjeQcUqNWpQqwrUZuFWm7wkrXT2vZqSvbunb7h1KUK0JU6keaMlaS1V12bTT7dfvPkHwf/wAExP2D/APinw/428H/ALOvhvQ/FPhXVbTW/D+rweJviFPNpuqWMnm2l3FDe+Mbu0leGQBlS5tZYSfvxMBtb0KmdZpVpzpVMXOUKkXCcXCklKL3TtBP7n9xxQyrL6c41IYeKlCSlF89V2a2avNr8PW594sqsyOyIzRnMbMiM0ZIwTGWBZCRwShBYdc4FeXb1XzfX8/0+477LTy26/1/XYCAfvKG/wB4Bse/Pf6UDFbLKVDMpKlVZTtZMjAZP7rL1UjoRmj+v6vf8vvD+v63/L7zw/8AZ+/Z5+Gv7M/gW7+H/wAL7C/tdH1LxX4o8caze6xfNqmta34p8Y6vda3r2r6rqTxRSXlzdX13JsZ0HlQLFAgCIK6cXi62NqqtXcXKNOFKKguWEadNcsVGP2bJa2er1d9Dnw2GpYWm6dJNJzlNtu8nKcnJtvS7bfbyVkke4VzHQMkiimQxzRxzRkgmOWNJIyVOVJSRWQlTyCVODyMdaPz/AK6/1cGk91f11/r+uw/A9B0AxgYwBgDHTGBjHSgLLXz36f1/XcP88cfp2oAMDsB78Yz9fX/PoKA/X+v6/wCCMkiimTy5oopoyyt5c0aSx7kO5W2SK67lIBVsZU8jkCj+tNBNJ7/1/nuyQEg7hgNnIOBwR0OOhwemcjjGCMigLf1/V+mn+V7nzz+zf+zV4C/Zh8I+KvCnga+8R65J45+JPjn4r+MvE/i++tdS8TeJPGfxB1mbWdbv9TvrKx06CSOFpYtP0yFbVfsemWdpahn8oNXXjMZVxtSFSqoR9lRpYenCmnGEKVGPLFRTlKzfxSd9ZNvW9zmwuFp4WE4wcpOpUnWnKbTlKc5czbajG9m7JNaKyuzwHWv+CV3/AAT+8Ravquu61+zX4Zv9W1vUL3VdVvZPFPxHje81DUbiS6vbl0g8axQo088skjJFEkalsRoqgIvXHPM1jGMY4yaUUoxSp0tFFWS+BvRLq797mEspy+TcpYaLk3dvnqq772U0l8l91kfcHhHwj4b8B+F/D/grwlpUGjeF/CukWOg+H9Ihe4uYdM0jTLdLWwsop72a4u5UtreNI1kubiadwuZJXclq8ypUnVnOpUk51KknOcna8pSd23ayu3rordrHdCnCnGMIRtGC5Yq7dkla2t3sur++7Oe+K/wm+Hfxx8C6x8NPit4YtfGXgXxB9k/tjw9e3ep2Nte/YLqK9s99zpF9puoReRdQRSqILyIMV2vuTKNdDEVsLVjWoTdOrC/LNJNq6s9JKS2fb7/szWo0q9N0qseenLeN5JPW+ri09Gr7/emz5i+Hf/BNr9iD4T+NvDnxG+Hf7P8A4e8MeNvCV+NU8O6/a+JPH11caXfiGW3+0xW+p+Lr+wmbyZ5o9l1aTR4cnaGCsvbWzjMq9OdGripzp1Fyzg4U0pJ9LqCa+T++zOWnlmBozjUp4eMZwfNGXPUdmvJzaeje/wBzsj7gKoXWQohkRSiSFF8xUb7yLJtLqpwMqGCnAyDgV5n+d/n/AF/n1Z3WX9L+v617gQp6qrY/vKrY+men4f0oGZev6RB4i0LW9Au57y2tde0fU9Eurmwm+z38FrqtjPp9xNZXGGNvdxQXDtbThWMMyxyAEqBVQlySjJJNwkpJSV02mnqnum977/MmUVKMo9JRcdNNGraPW33aeZ5x8Bvgf8PP2bfhF4F+CHwp0qbR/AXw90aPRdAtLq5a+v5IhJJcXN9qd/IqSX+p6hdzT3l/eyKHubqaWVgpbau2KxNbGYiriq8uarWlzTaVl5KMekUtEtbfhHLD4enhaNOhSVoU1Zd/Vvq22233fmeuVzm4ySKKZQk0UUyBlkCTRpKodDlXCyK4DqeVYAMDyCMUeet152/r5/qJpPdX/r9On4dR/BzkA565UHJ9SO59z/Sgdl/X9f1t0CgA47AD6DGT6n1PvQBHJDDNsE0MUwjcSxiWJJfLlX7ske9W2SL2ddrD+8KabWzavpp1XYTSe6T666/P+v0K+o2j6hp2oWEd5dadJf2N5ZpqNiYkvrGS7t5YFvrNpo5oReWrSC4tnmhljE8aGSKVAyUJ8rTsnZp8r1i7W0a00a0dn16WBq6aTtdWut1fS/qlt/wDw/8AZs/Zx+Hv7LPwR8J/AX4cnWbzwj4Vg1rdqfia8i1HxL4i1PxJq2oa74j1/wAR6lbW1jHfa1rmrarfXt/dxW0AeWc7EQBK6sbjK2OxNTFVuVTny+7BNQhGEVGEIJttRjGKSV36u9zDDYanhaEMPTu4R5rylrKcpO8pSel3Jtt2SWul7ty+bbz/AIJP/wDBPO/ubq8u/wBmTwvNc3s89zdSt4r+JSmWe5keWeQhPG6qpkkkdiERVGcKuBhexZ7mytbGz0tb93R6f9wzleUZc7t4aN3q/fq9fL2lj730fQdH0HQ9J8NaTp8FpoWh6dYaTpWmnfcwWen6XbxWun2yG7eeWQWtvBFHHJPJLMdgZ5WfL15UpynKU5NuU3KUpdW5fE9Lb36L7tD0FCMYqCSUYpKK3SS237HnHxs+Avwi/aN8Gp8PvjX4JsfH3g2PV7LXU0LUL7WtOt11bToriGyvRcaFqek3u+3iu7hEj+1eQRKd8bFUrbDYrEYOp7XDVXSqcrhzJRb5ZWurSTWtl09LamdfD0cTD2deCqQvflbktdr+60+v/Dbx8V+EP/BPv9jn4CeOtN+Jfwi+Bug+CfHOkW99aad4hsdf8b39za2+p2zWl9EltrXinVNPcXFs7RMZbN2UNmNkcBq6cRm2YYqlKjXxMqlKTTlBwppNxd1fljF6PXf7r+9hRy3BYeoqtGhGFSN0pKdRtX3tzTa1X9PaX2PtXeZdieaVEbS7F8woMkIZMbygJOFyVGTgDJLed/w/9f108kdtle9te/X+v66BgZztUkdCVUkfQnn8un40Acp4/wDB2mfEbwN40+H+uXOp2mjeO/CviDwfrF3o142n6xb6V4l0q60bUZdL1BUlax1BbO8mNpeLG720+yZFLotaUqkqNWlVgk5UqkKkVJXi3CXMlJaXjdK6TjdaXX2oqQVSnOm20qkJQbi7NKacXZ9HZv8ApGL8IfhT4I+Bfwu8A/B34baSuh+Avhr4W0fwd4U0oP5r2mi6JaR2dos85Ctc3UiRma7upB5lzcySzyYdzurEV6uKr1cRXlz1a05VKku8pO7t5dF2SJo0aeHpU6FJctOlBQgu0Yqy+Z6NWJqMeKKUxmWKKUwv5kRljSQxSYx5kW9W8t8EjehVscZGRR+unb+v67isnZtLTZ9vT/gD8D0HXPTv6/Xvn15oH/X9fMKADjsAB6AYH5D/AD+dADHiilMbSRRSNC/mQtJGjmGTGPMiLqxjkwcb02vj+LoGP67f1/XcLJ2uttvL0/r9TjfiT4Jg+JXw88dfDu51zXvC9r488I+IvB934i8KXNvY+JtFtPEmlXWkXep6Be3VrfW1prFrb3ckthdz2d0kFyscphcqBWlGo6NalWUYTdKpCooVE3CThJStNKzcXbVX1Wml2Z1aftaVSnzSgqkJQcoaSXMrNxvdJ66NrfXU4/4X/AX4a/CT4C+Df2bPCujN/wAKp8E/Dax+FOnaLezu0974TtdFOhXMWp3ln9klmvtWtZLmbVL63+yzT3t5c3UflSOCutfFVsRiqmMqS/f1KzrykloqjlzLlTvZRdlFO9krO5FLD0qOHhhYL91CkqSTergo8ru0k7tbu123fW58rWn/AASg/wCCedhdWt5afsy+F4bmyuILq1lHir4lMYri2lSaCQB/G7KxjkRXAdGUlfmQjKt3PPc2ad8bPVNP93R67/8ALt930+85FlGXKzWGjo0179Xptp7S3Q/QuKKOFIo40VEhjjiiwoJSOJQkahiS/wAqgAEknjJJPNeRvd93f5v/AILPRSS+X/DfkeF/Hn9mT4E/tO6NoXh/48fDvTviLo/hnVLjWdCsdS1PxDpiadqd1amyuLuOTw9rGjTyvLakwlLiaWIKdyxhzurqwuNxWClOWFrOjKcVGbUYSvFO6T5lLrrovW+nLhiMLh8UoxxFNVFBtxTlKNm1a/uyi9v6X2uI+Bv7Dn7KX7Nfiy98c/A74N6L8PvFmo6Jc+HL3WdO1vxhqU8+i3dzaXlzYNBr/iXWLNY5bmxtJTIlss6mEBJVRnV9cTmeOxlNUsTiJVaakpqLjTS5kmk/djF7N9fu+1FDAYTCzdShRVObTi5KU5aOza96Ul0XT7/s/VgVQ7SBEEkgCvIFUSOq/dV3xvZVySqsSBk4AJJbgOuy36/1/X/DDsDO7au7+9tG7/vr73H/AOrpQH9f1/X5nkvx5+C3g39o34OfEX4F/EVta/4QP4p+Gr3wh4wi8P6nJo+rXnh7U2iGqafb6lFHJLapqVsj2N2yLvezuLiIMpfcvRhcTUweIo4qjy+1oTVSnzx5oqcfhbj1s9V5q5jiKEMTQqUKnN7OrHknyu0uV7pPW10rf5bnoXh3w/o/hPw9oPhXw7p9vpXh/wAM6Npfh/QtLtI1itdO0fRrGDTtNsbeJQFjhtbO3hgjVQAFQYA6VjOcqk5zm3Kc5SnOT1blJ80m/NttmkYxhGMIq0YRUYpbKMVZJbbJJbfcbFSUMaKJ5I5XiieWDd5Mrxo0sO8YfyZGUvHuHDbGXd33Ywru9Vd2e67+v/BFZXvZXXXqv68v1H4HoMdhtGAfUDsfcf1pDCgA+nA9hgfl2/z6UAMaKJ5I5niieWHd5Mrxo0sO/h/KkKl49w+9sZd3fdghXd6q7s9139f+CKydm0tNn29P+AeN/tEfBHw9+0l8EPiZ8BfFmveKfDPhP4r+Fr3wb4n1bwRfWuk+Jo/D2qtEmsWWl6hd2WoW9mdVsVm0y7mNnLILK8uhC0UzJKm+ExMsHiaGKpxhOph6iqwjUTlDnj8LaTT0eq137oxxNCOJoVcPOU4QrQcJOFlLle6Td7XWja1t2umbWpfBv4a6z8I1+BOreFbK++FA8Faf8PH8Hma8s7CTwfpemW2j2ejedptxZXsEMdhaQQ77S5glG3KyAk7pjiK0cR9ajUar+1db2llf2jlzOWqs3dvdPs7lOhSdFYdwTpcip8mycUrW0s1db2/HY+VPC/8AwS8/YJ8F+JNA8XeGP2cfDWkeI/DGsadr2g6pD4n+Ik0um6vpN1Fe6dfRRXXjO4tpJLW6gimRLi3lhZkAkidCyN3zzvNKkJ054ucoTjKE4uFJKUZK0k/3b0abT/S9zkjlWXwkpww8VKLTTVSro07p2c7OzS7fpL73YKxLMiMxOSWRCSfqcfy/LFeUegfN/wAev2Qv2b/2n7jw3dfHn4V6R8RbjwhBqFt4bk1HVfE+lnSoNVkt5dQjhXw7rujJKtzJa27P9pE5UxDyymXDdmFx+MwSmsLXlRVRpzSUJczjs/fhLZNrR+VnZOPNiMFhsU4vEUlUcLqN5Tja+/wyj+X3faj+Av7Hn7Nf7MF/4h1T4DfCrSfhzf8AiqztNP8AENzpuseKdTfU7Owna5tIJV8Q69rMcSwTu0itbLA7E4kdlASjFZhjMaoRxVeVZU25QTjBcras2uWEd1bd+iVm5LD4LC4VyeHpKm5pKTUpyulsvectn5/f9n6TVEQyMiIjSsGlZEVWlYAANIwAMjAAAF8nAAyMAVx/pp/X9fmzqshwAU7gFDf3go3f99fe/H/61AHhv7RH7PPw3/ai+Gdz8Iviza6pqXgTUPEng/xLrGkaXqL6YNal8FeJNN8VaZpOqTRxyPcaHeanpVpHrGngKNQsvNtXdUkeurB4utgayxGHcY1VCpCMpK/L7SDg5R1VppN8stbPW2hz4nDU8XSdGrzOm5QlJJ25uSamk+trrVX1Wjvc9wREiRIokSKKJEiiijUJHFFGoSOONFwqJGiqiKoAVQAAoGK5ToHUAFABQAUAbOgf8hW3+kv/AKKeuvA/7zD0n/6QzDE/wn6x/M9Hr3Tzj//S/v4oA4HxN/yEF/694/8A0J68XMP46/69x/OR34X4H6/5nO1wnSFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAYJ6f4/5/z6UAKQR1BH1GP8/59TR/X9f1+YCUALg+h/KgP6/r+vyDB98/SgP6/r+vzEoAKACgAoAKACgAoAKACgAoAKAFAJ4AJ9hz/L/P5UB/X9f1+QlABQAuD6H8qADBPTP5Z/z/AJ9KAEoAKACgAoAKACgAoAKACgAoAKAD+VABQAUALhvQ/lQAYJ6A/ln/AD/n0oASgAoAKACgAoAKACgAoAKACgAoAXB9D+VACUAFAC4PofyoAMHrg4+lAHOeLPGHhPwHoF/4q8b+JtB8H+GNLELal4i8TatY6HomnrcTR20BvdU1Ke3srYTXEscERmlXfM6Rrl2UVdOnUqzVOlCdSpL4YQi5Sdt7Rim3b0+65M5wpxc6k4wit5SajFerbS/H7yl4T+IPgTx54c/4THwP4z8L+MfCWb1f+Em8Ma7puu6Du00E6gBqumXNzYlrEK32tRMGg2kShMZp1KVWjP2dWlUp1NP3c4yhPXb3ZJPXpp94oVadSHtKdSE4a+/CSlHTfVSa0trqv1NTw54l8OeMNE0/xL4S1/RvFHh3VoRc6Xrvh/U7PWNH1GAnHm2Wo2E1xaXCBgVYxSttYFWwwIqZwnTk4VIyhOLtKE04yj5NOzXzX3aDhOFSKnCUZxlqpRalF+jV1+P3m3UlBQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAGzoH/IVt/pL/6KeuvA/wC8w9J/+kMwxP8ACfrH8z0evdPOP//T/v4oA4HxN/yEF/694/8A0J68XMP46/69x/OR34X4H6/5nO1wnSFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAfOv7THxv8W/AzwRpeteAPgh8QP2gPHPibxLp/hPwx4B8Aixsi2oagssh1bxT4m1h4tE8IeFtPiiZ9R13VZRDGzRQxJJLIFrswWGp4qpKNXE0sJTp05VJ1at37sfs06cfeqTfSEbd30UubFYieHpqVOhUxFSU4whTp2Wsus5v3YRXWTv5J7Hg/7PH7cOs/FTV/j98Nvi38CvEXwF+PH7Onhyz8X+M/htqPi7w1440zV/CutaHe654c8QeFvGnhiSXStSsdWhsbi1dJYLa5srqNkngx81dWMyyNCOEr4fFQxWExlR06VZU50ZRnGahOM6dRcycW763TWt0c+Gx8qssRSrYeWHxGGipzpOcZqUZRlKMozi2rSUfltrvL5p8Bf8FZPFHibwZ8B/jj4o/ZA+Ifgn9mP45eMPDvw6svjFc+OvBurXvhvxh4p1GbRdDn1bwDZOniL/AIQ+/wBahOmw+JAY97vFcmyW0lilfsq5DCFXFYWGYUauNw1OpWeHVKrGM6VOPNLlqv3FUUdXDpqruzUeWnm9SUMPXng6lPC15xp+39pBuE5tpXp/FyOS5ebXy3Tj6p8Sf+Cg/wATtM+Pf7QX7PnwN/ZH8XfHXxT+zr4d8F+MfF+rWnxF8H+B9Du/Dni3w1/wkqJptx4kVXufEKwJcW1hokIle+lgMk1xZxSRb8KOU0JYXCYvE4+nhaeMnVpQj7KdaSnTnyXlyWfJfXmurdYu3va1cyqrEYjD4fCSxEsNCNSbVSFOLjKPNo5XvJapJfE19m94+hH9u9/GX7LXwk/aM+AfwA+Kvxv1r41Xmn6N4T+FehQ6bouraFrU5uotYHxB8TarOvh3wbofhq7srqz1bXr64e0M6RxWi3DzIKx/sv2eOxGCxeLw+Gjhk5TxE3KUZw+z7KnGPPUnJO8YKza1srXNP7R58JRxOHw1avKu1GFKPKnGWvN7SbajCMGmpSd1pZbxRl/BT9urxh8TLP8AaW8FeNP2b/FPwu/aT/Zk8NQ+J/EnwRvPGfhjxVb+L9M1bw/eeIfCt34M8e+HWudFv7TxFDZTWMTzW8M9lfr5NzbfMpq8TlcKDwVWnjKdfB42fJDEqnOm6bUlGaqUZ2knBu7tJpraSs0FDHzqrFQnhp0sThUpToOampRlHmg4VI+6+ZJpLe61s3yxzYf+CkvgbXfgv+x/8U/BPgbWfFevfthfEDQPh94S+HkGq2NprXhi+ltb288dXuu3LxyRfZ/h9Bp11/bCxwhpphHFH5RfNP8AsarHEZhQq1I04ZfSnVnWcW41FdKkoq6s6ra5btWWvvayJ/tSm6GDrQpynLGVY0oU1LWDs3UcnbX2dnfRX8tT9KOR1698HOD3GeM4ORnHPXjNeMeofiv/AMFffH+n+EvEf7DHh3xn+0H45/Zu+EPxA+Ovi3Qviz488DfEZ/hbef8ACP2XgSXUNOtr7xYI5orO1GrLAyCaN0aR9gBZht+k4fpSqQzSdLCUsZiKOFpyw9KrR9uud1bNqn1bjfa34Wl4mc1OSWAjPEVMNSqYicatSnV9i+VU21eeyV9NV16XPoj9gnRP2W4bn4g6x+zZ+2d8Tv2somj0nTfEyeOP2hE+N+neEZI/tNxZGwhjsrZNCvNQSVzPJuZruKKIbQEBbjzaeOaorG5fQwD1cPZYT6q6nR31lzJPZdL31vaPRl8cLeo8Njq2L+FT9pifrChvZq+sW9b666XtaJ+kFeOemfzt/wDBXzQrD4XeLfBWu6b+0b+2l8Hdd+PviJbHWfif4V+KHja1/Zn/AGdvCuhLp9rrHivxJ4b8J+E9VFjeXscqQaLpl9qFhpV1qM0+o6rqdnZW8gb67h+pKtCpGWDyyvDCwvCjUoUnjcXUndxpwnOpFySfxOK50tEno5fNZxBUqlOUcTjaMsRK0qsalT6rhox3nOEIOze0U3ZvV2SZ7Z+2hpPiDX/FH/BLf4CeFf2jPjRYeAfin4r8U+H/ABh8TPhd8RJvCvjX4maJ4e+FaaxpGt3virTYb2O5bUr63TVHlEE8UpnkK4Dlq5stlGEM9xc8Hh3WoU6c6dGvRU6dCc67jKMacrbJ26bdDfGxc5ZXh4Ymv7KrKUJVaVVxnViqV1JzW7dk9nfpbVS9r/Ya8W/E7wR+0r+2D+x345+K/jf42+FfgTcfDLxT8MfHXxOudP1T4i2vhn4leGhrE3hXxP4h0+y0xPEbaJexyx6fqk9jDdPaOiTtK6ZblzSnRqYPLsxpUKeGqYpVqdelQTjRlKjUcVUhB39m2tXFOSvty3sdGAnVp4rGYOpWqV4UHTlSnVs6ijVgpckpL4uWzUXaOm+5+pteIesFAHy1+078fPiN8FbHwTpnwj/Z28f/ALRvxC+IGt3ej6P4d8K3+k+F/DHh+30+0F5e674+8f8AiF49B8JaQsbLBZvdGa61G7byLS3dkeu3BYWjiXVeIxlHB0aUVKVSonOc3J8sYUqMPfqSvq7Ncq1d9jkxWIqUFCNHD1MTUqSajGDjCMf71SpL3YR2Wr32vdng/wAP/wDgoKniP9nn9rD4seO/gp4p+GHxO/Y0g8bRfGP4J6t4j8P65fw6r4R8GQ+OrSPw94w0KS70PWNH8S6Hc20uk6xEiKGeRbi3R4irddXKeTF5fQp4mFahmTp/V8TGEopxnU9k3KlJRlGUJpqUXba6erRzU8y58Ni6s6MqdbBc/tqDlGWsIe0XLON4yUk1Zr0drWOC+Gv/AAUq8XeIfGf7MkPxS/ZQ8e/B/wCEP7YItNN+BnxX1Lxr4R8Sm98WX3hZ/F2maB408HaLK+t+DU8Q6PBczeH7u9ac3BhEd9FYzSeUmtbJqcKeN9hj6WIxGXpzxOHjTqQfs41PZylTqNONRwk4qSXKrt2bSuRSzScqmFVXCVKNLGWjQqucJc03DnUZQXvQ5lflbavaztvKn47/AOCkvxPsviR+1n4A+Dn7HHjn4zw/saeI7ay+LPiGw+IngvwnZ3Ph+TwVYeN57vwlaa+YrrxB4kj0q5vXh8NWy7nWwDTX8Ul5bQsUsnoujgKuIzGlhv7RhfDwlSqVGp+0dNKo4XUYXSvNqKXNs7MVTM6qqYunRwU6/wBSklVkqsIK3s1UfKmm5Ss2uVb2u2rpR9m8W/tv+INa+EH7PXxL/Ze/Zy+JP7SepftKaDB4o8HaRpt7o/gPw34R8PNo1vrFzqfxP8eeJnGg+EvK+0LptpYv9qv9U1FJYbGF1iLtzwy2Ea+Mo47GUcEsFP2dRyUqs6k+blUaFKD5qn8zeiSWrbb5dp5hKVDDVcLhqmJliYqcIq0Ixi1durUlLlp/yq/NeWi/vcP4V/4KMXviT9mX9qL4zXH7PPjjQ/i9+x5q/iHQPjb+ztdeIfD+peItP1bwrp9h4g1YeG/FujG+0DxFp0/hS9PiDSL60Ci/ggktjFBMRWtTKFTx2Bw31ulPD5hGEsNi+ScYNVJOEeenJRnGSqLllFvS97rVyzhmbnhcTX+rzjWwjkq2GcouScEpS5Jp8s7wfPGzV1pd6SPUb/8Abn8FX3jv9i7wJ8PPDd98Qbz9svw7rnxA0K90zU7O2tvA3wv8PeFbHxFqPjnXw6yvc2ZvdV0vw9bWtsEebVLplEoWF65/7MqxpZjVrTVFZbONKalFt1a8p8ipQs3aVk5S5krRV30NnmFN1MFClF1HjYyqRs9IUYQU5VH1dm1BJLWV9rH3PXmnoH5Eftya34s+J37Zf7K37Ik3xm+IHwP+Cvi/4RfHT47fFzxD8LfFcfgDxd4ih+Gd54U0fQvD1x468mW88N+GbaTXrzWNYlsHt5rr7PDHLcxQxsa9/LI06GX47H/VqWKxNOvhsNQhXh7WnB1+duapbTm+VRinffzvHxcfKdbHYXB+3q4ehKjXr1pUp+zlL2Xs1GHPo4xXM5Xjq3o7pJH0n+wx4X8WeBvCXxK8G6p+07pX7VHgLR/iTqUvwc8ZzeLbHxx8RPDfw61Cwsrmw8FfE7xRpyJba74h0XUDfrY6qV+03ejyWf2ppJkd65M0qQq1KNRYF4GrKivrFNU3So1KydnUoU3dxg1a8b2Utkjqy+E6casHio4umqjdGfPGdSNNpPkqyi2nJSbV+qtv8UvuUHBBwDg5weQcdiO4ryz0D+aP/gov4X0b4aftW/CT4eWn7XH7bnwAtvjb4ws/HvxA+Oes/FrxnJ+zl8N9CuvEyW1n8MPCumaV4Wk8Paf4r8a6gh0bR7PxNr2maB4c0mYXd1c3tzLZW0v2mUVJV8BiKzy/LMW8NTlSpYWOHpfXK0lBt16kpT55QpJpy5Iuc3tZKTPlsygqOLo0ljMdQVeaqVMRKtN4alDnsqUYqHKpTl7qUpKKWrfM1CX11+2H4V8UfGH/AIKIfsYfs7Q/Hj49fDD4aeJf2afjj4511vgl8SrnwBq3iPxH4P8AEng+z8Paxqmo2tlqVvqLQW1/cttmtnjl87unDedl9SGGyfMsZ9VwtetTxmGpw+tUPaxhCpCTnFJtNa+elra2R2Y2M6uY4PDrEYinSlha9SXsKnI5ShOmottduZ7PtsrnuP8AwTc+J3xQ1+D9qz4GfFX4g658W9U/ZT/aZ8W/Bfw18T/FcGnw+MfF3gmHR9E8S+GpvGEul29pY6j4j0yy1oaZf6vDa2v9pG2S5khWVnZuXOKFGH1DE0KMMOsdgqeInRp39nCrzThP2ak5OMJON1G/u7a7nTllSs1iqFWrKs8JiZ0I1Z255wSjKLna15JSs3b3vKzP0wrxj1AoA+Rv2nP2hvix8H9T8AeDvgj+zH49/aR8f/EA61cR2+ja3oXgX4f+DtI0GKB7vUPHXxH8USJomh3F/JcJbaFpCpcalq0yymGJYYHeu/BYTD4hVamJx1LBUqXKryhOrVqSltGlRg1KVkm5S92MVu3exxYrFVqMqdOhhKmJqVL/AAyVOnBLrUqSTUd9FbWz2sfNif8ABT7w9a/saftCftTeI/gt408L+L/2W/F+sfDr4zfAjUtY0S68TaF470HWdD0vUdJ03xHpT3mh63YT22vWOq6Rqtizw6layLGqRTF0Xt/sWX9o4TAwxNOdPHU41sNilGahKlKM5KUoStKEvcacWo2Zzf2rH6licU6M4zwtR0q1BuPNGopxi4xl8Mk+ZNSTSa7W93rPhd+3j42139oP4X/Ar42/sw+M/gND+0D4Q8ReMvgB411Pxp4T8Zad4yg8J2en6nrvh3xRp/hyV7rwP4sg0fU7TVodKv3u45bZ3h+0/aY3Rc6+V0o4SvisNjaeKeEqQpYqkqVSm4Oo5RjKnKd/aw5ouLkuWz1V07l0cwqSxFLD18LOh9YjOeHqOpCamoWbjNRu6c1GSfK7dr8ycTwPXP8AgrD44tvDP7RHxR8K/sZfEPxn8FP2TvjH8Q/hf8dviDYfEDwXYXul6V8ONUtrTXvF3gnwjqDR6x41j07S7lde1fTLM2z2For2kVzeXySxRdUcipc+Do1Mxo0sTj8PSr4WlKlUak60bwp1aivGleS5FJ35nraK1OZ5xU5MRWhgqlShhK9WliKkakE4qm1ecIP3p+7q1dWWq1XLL6z+Nv7WfxT8O3fwr0X9mX9ljx7+09q/xS8Ct8S4Nbs/Enh74ZfDPwx4QaKzl06PxB8Q/GLJpUfivXRexnRvCtpDc6jLCkt3c+RaqZF4cNl9GSxEsbjqWCjh6vsHFwnXrTqa8zhRp+84Qt7024q+ive8eyvjKsHSjhcJPFOrT9tzKcaVKFPo5VJJrml9mKWu7aSseQy/8FO/DR/Yj8Sfto2/wZ8cRaf8LfiZP8M/jz8LdS1HSYPGHwj1Dwv8QLbwB8UdSvruzN9pWvWHgC5uP7cnl0ucx6roaPd20kW10ToWSzWZ08teJpt16KrYauoydOup0XVoJJ2lB1rcquvdlprZOeP9qxeBnjVRmlRquliKTceei4VPZ1Ho7SUG+bS/Mtkrn0ff/tZ6BL+1j8LP2V/CPhq78Yaj48+B3iH9oDxL420/UrSPQ/APgO01PT9D8HTahb7JZr+78eateXEOjRQyQhLbTru7YyRqK4o4Cf1Cvjqk1TjSxMMJCm03OrVacqii72Xsopcy974t429/p+uReLo4WnHn9pQliJ1FJWp078tO63bqSvZLom9kfXFcB2n40fGT9tX4f/s0/wDBWL/hE/2gPj7YfCz4J6z+wx4b13Q/D3i7Wrm08HXvxGl+NPiGzvNWtLCOKaI+IJPD1mtrLdbFc2MCxliFXd9DhctrY3IXPCYV18THNJwlOnG9RUVh4Wj091SlzPV69NTw62Op4XN5RxGIVKi8DBxjKTUHU9tJNpbc3LZcz6aaayj6V/wSK+NWt/H79nL4p/EbVviDqXxO02+/a8/af07wV4q1DUZ9USb4fab8Sb2LwZY6Tc3AWRdCsdFa3i0iAKqQ2ZRFAHFZcQYaOExlCjGlGi1l+BdSEUlaq6MfauSVvfc7819b97Nm2TV5YjC1akqjqJ4zFKEm7/u1U9xJ9lGyS0svvl+ppGQR0yCMjgjIxkHsR1HvXhnrf1/W/wCX3n8zPxw8KaF8Of8AgpJ8FP2frb9sP9t74NeHpvFfhb4k+MPiJ8Wvi74y1f4Q/FXxB4kv5tY8Lfs1/CoHwtbeCo9Q1t0WLxFN4h8RQnTtN8rw/o9jqGqXLyQfZ4WpOrk+Jxf9nZZiZ8k6NOjQw9OOIoQguWpjK9p+1ag78ihD3n77lGMeWXy1eMaWZ0cOsZjqMeeFSdWtWnKjVlN3jhqX7tU25fa5pqytBJtn1l8Zvh14w/aR/wCCrni74G3n7RX7SHwd8A+DP2Jvh/8AEzw9pfwL+Js3gS3g8d6z8UvFHh651/UrGTTNW07WHXT7e3T7NeWpik8hFlJQFa4MNWp4PIIYpYTB4itPM61GcsVQVZulGhCSgmpU3HV9L+Vvs9dalPE5vUoPE4mlTp4GnViqFXk/eOry8zVuV6W6fJ6n0/8A8Evvjb8TPjZ+zPqTfGDxI3jf4g/CL43/ABy+AOtePJbG10288cwfB34ja14O0fxXqtjZBLOHWtX0ewsZ9ZNtFDBNqX2meKGJJAlcWd4ajhsavq8PZ0cRhsLi40r3VJ4ikpypxb15Yyb5U27R0uzsyqvVr4V+2m6lSjXr4d1GknU9jUcFOVtOZq3M7K71srn6K15B6QUAfE/7SP7S/wAc/hl498PfDH4AfshfEH9pLxPqXhO88ba9rsHivwv8L/hp4Z0e1vv7Pt9Hm8e+MpV03VPGurThm0/wvp0MtylqBeXs1tbOHX0sFgsNXpTrYrMKWDhGoqUIOE61apJq7kqVNOSpxVrzbSu7K5wYrF16VRUsPg6mJlyOc588KVKCXR1JtRlN9IJXsrto8G8Q/wDBU7wJpf7EfhT9s/S/hJ4+1W31r40+FvgH4g+EDT6Vb+PPCvxJ1f4kS/C7xB4enljluNI1O88OeJreaJGsrlrTVoWgmguoI5WdOqGR1Z5lUy54ilFww08XHEWk6c6EaSrRkou0lzxeidnF3XLKyRzyzemsBDHKjU96tGhKi7KcKrqeylF2unyy6rfyTsep/Av9tHxr43/aQ1f9lj48fs6eJv2dvilc/DN/jP8ADlb7xr4W+Ifh3x78OLbXovDmrzx654UdrfRvFHhzVbmzh1vw/dq4jS8imtLy5iBd8MTl1Kng447C4yGMoe2WHrNUqlGdKs4OcVyTvzQnFPlmn0s0nc2w+OnUxLwmIw08NW9l7anecKkalPm5W+aFuWcXbmi01rpLSx8k6F/wV/8AEurfCXTv2mrv9jj4iaf+ytp/xU1H4UfEf4v/APCfeDZ9S8G6hZfEqf4YSeKdP8Abo/EPiXwZp+uLaf21q9osElot1N9ktr6Oylmb0JcPwjX+pf2jSeOlQjiKOH9lU5akXQ9vyOt8NOo4axg07patc3u8cc5nKisV9SqLCKq6VWt7SDcGqnsnNU9JypqVuaWltlGVmz7V/aL/AGnvjp8OfHmg/Df9nr9j/wCIH7Smt3vgqf4g+IfEsXi/wt8LPht4e0Vb42FhoMXjbxo8djrnjzWJEknsvC2mRNPbWIjvdSmtYJkavNweCwtalKti8wo4KCq+xhBwnXrTly8zl7Km+aNKK0dR2TeiTszuxOLxFKpGlhsFUxUnB1JSU40qcUvs88/dc3uoLW2um0vHP+HoPw+n/Zg/Z8/a0tvht4wtvhj8V/j14f8AgB8Uodbu9O07Xf2e/E2reONW+Fur6l42gja7s9R0rwv8SdMj8N6tdabdLAYb+11a3lktWYV0f2JW+vYvL/bU3Xw+Fni6DjGbji6caca0VSvZqVSi3NJ9uW7aSlh/a1P6rhsYqU1Sq4iOHrKTSlhpOcqUnPdNQqrlck0tU7an0z4f/ag07xX+2P8AEf8AZH8PeEr/AFGb4Q/BnwZ8VPiP8Ro9QthoXh7WviJrmoWHgz4dmwVJLqfxBquh6TfeKZZTNFDa6StsXVnuoq4pYJwy6jj51FH6xialCjR5XzTjRgpVKt27KMZSUFpdy2ta51RxanjquDjBv2NCnVqVb+7GVWTUKdt3Jxi5eS9T6prhOw/DX/grh8KfEVr4q/ZT+Jfg39on9pz4X6h8Yv2v/wBnD9m3xl4Z+GPxg1Lwl4Ib4e+MLjxWniC70rw5a6fLFp/i2/W1t9/iD7RO2YULWrECvqOH8RFwx1CphMFWjh8uxmMpzrYeNSr7Wn7PkUpt3cFd+5ZL/wBu+fzmlJSwlWGJxVKVfGYbDTjSrOFP2c3PmailpN2tzX+W7P2R+GfgC0+FngLwv8O7HxL4z8Y2nhHTRpNv4o+IniCXxX431uOOeeYXviXxHNBbS6vqTGYxvdyQRM0UcSbcIDXzdaq69WdZwp03UfM4UYezpRbS0hDXlj5L8L2PcpU1Rpwpqc5qCsp1Jc9SXnKWnM/O33HaTxCeCaAvJGJ4ZYTJE2yWMSo0ZkifB2SoG3Rvg7XAbBxis1o0+zT+77/62tuW1dNd1bTzP5o5vDGh+Av+CqPwo/ZytP2v/wBtr4YeF/AWveH/ABbqmp/Hv4t+MvEPgX9qfx5rmkf8JPoXwE+E7XfhXTvBFzpOn2Nwl340u9Q8QNrF7Nb/APCL+HtHmmhv7yD7P2kquR4jGPL8srzqxnBLDUKUKuApRl7OeLxFqkqvM5JqmlCMUmqkrWij5fljTzalhljMdShTlGcpYitOcMVUa5o4ej7kaaSv77lLmdnCMXdnvWrfCv4i/tPf8FF/+CjvhT/hqv8Aaf8AgzZ/AP4e/syX/wAHdN+EPxKGgeEfDGveN/hJqutazqep+DNR0nVtF8RRXmsaba3d7Y3ccMd0jXUburTCRORV6OCyfKJ/UMDiXiq2MWIeIoc9SpCniIxjGNVShKFoyaTTfys+bolRqYrM8yj9bxVBYelhXRVGpaEJVKLcm4O6ldxTa626Xufb/wCwN8QR+3X/AME/PgH43/aS8JeCfiRf/EjwnJYfEzQvEfhXSNY8GeLvEPgbxlrHhS81q58Katb6hpHlarqfhddfhsZbeSKxup18jaYk2+bmtJZXmuLp4KpUoqhUvRlCco1KcatONRRU1yy0jPkeuq0d0nzd+X1P7Qy2hPFQhVdSFqqlCLhOUJuLlyNOKu481rNJvS32fBf+CK2gaFon7K3xu8MaNo2laT4b0v8Abs/bc0PTfD+m6faWOiafotp8bdfsLXSLLS7aKOxttMt7FEs4LGGBLWK1RbdIhEAldXEc5zxuFqSlKU5ZXlk5Tk25OTwsG5OTu3JvVtu99dTnyOMVhMRBRSiswx0VFJKKj7aSso6JK2lrWt2sVfgz4L0X9jr/AIKj6p+zd8HLUeFv2eP2qP2XvE/7RNv8ItNeSLwb8NfjP8L/AIhaR4T8Va74D0cyNa+GNK+IOgeI7S413QdKit9KOs6XHqFtbxSXE4p4mpLMMjWNxD58VgcfDBvENfvK2Hr0XUpwqy0dSVKcGoTknLllZvRCoU44LNnhqPu4fF4WWJ9ilaFKtSqRhN01zWipxmuaKja+vdn7GV88e2FABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAbOgf8hS39hL/AOim/wA//qrrwP8AvMPSf/pL/r/hmYYn+E/Vfn/X9NHo9e6ecf/U/v4oA4HxN/yEF/694/8A0J68XMP46/69x/OR34X4H6/5nO1wnSFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAflf/wAFPPg38b/izYfs9z+AvAvjz40/Bnwd8SNR1f8AaI+Afwx+I6fC/wAbfE/wtcaJJa+Hlsddl8QeFItU0/w/rR/tDUfDj+I9K/tJNpEshQIvuZJicNh5YtVqtHDYipRjHB4uvRdenQqKXv3ioT5XOPuqpyzttZWbPIzWjXrfVnTp1K9CFRvEYelU9lUqxcbRtLmhdJu7jzxv1vb3vmj9iL9jr4i/C/8AaA/bd+I2kfss6x+zR8JvjZ+z/wCCvCnwt8FeIfiVZfEHxJdeJNL0TxVZ6nb+Ib1vGfjCXStWnutQtJJrMazd6VZi5SKG9cpIV7MzzGjXwuV0XjoY3EYXGVKtepCi6MFCUouPIvZUuZcq+Llu7Xsr3OXA4KrSxOOqxwrw1Gth6caVOVT2knPlmmpSc52ldrRSlFbLe8fv/wD4J6fBHxb8If2Iv2ffg78aPB9lpvjTwR4StLPxF4Y1YaPr8Ol6xaX9xdW5EttLqWmTXNqXjmt7q0nlMMgDxSh1+Xy82xVPEZni8ThqjdOpO8Jx5oc0XFJ9E1fqmtt73R6OXYeVHAYehXgueEEpRlaVmm7dZLTpZv1W5zHwF+B3xM8Hft8fty/GTxL4YNh8NPi/o3wMs/h/4ge+0yeLxBL4R8FHSPEUK6db3U2oWa2F6fs7HULW2SfO6ASoCy1i8VRqZVleGp1L18NUxTrQtJOCqVYyg+Zqz5opvR373v7s4ehUhmOPrShalWhh405XTUuSFpabqzdrNdNLXPLP+ClXwI+LnxBsv2b4vhj8LvFnxZ+AXgb4ha/q37QX7OXwd8dWfwg8TfEbQdQ0dIPDM9hfQa74LstT07w9rbXmpap4cHiLSDqb3Mc5lmeIpW+TYrD0XjPbVoYfFVaUI4TGYin9YhRlFtzunTqNSnFKKnyyStrZK8sc0oV6iw3saU62Gp1JPE4WhUVGdWLjaFnemnGLu5R51zX2VmeYf8E3f2UPHHwP/au/as+Kx/Zj1P8AZl+C/wAWPA/whtfhz4O8QfEW2+Iuv/bfDlpqsOvw+I7v/hLvGNzY6uJZ4prqxi1W9022WdILS7nKSFd84x9LFYDA4f67HG4nD1cQ61WFF0Y2qWcXD91TUo20jJpSdrte8lHLLMJOhi8XV+qywtCtToqnCVT2krxT5uZ+0qtPy5mlsux4T+w/+zbfw/8ABUf9p2ystZs9d/Zz/Y58SeLrr4LaLbpI1p4S+K/7Sv2Hxn8RdCTd/oy3PhK1KadALcD7JFqTQDBaRF6czxqeR4FyjyYzMIU1iJO150MH7lGbtq1Nrm1evLf3btnPgMM/7VxXK1LDYOc3RS1UKuJ9+pG97XikkrJWUraaRP068e/8FNf2Fvhf4y8RfD/x9+0R4R8N+MfCeqXOjeIdDvbLxE91pmp2jmO5tJnttGmgaSJwVZoppUJHDHFeNSyXM69KFalhZyp1IqUJLkScXs7Oaa+a+7U9apmmApTlTqYmEJwdpRandNbp2g1+P3Hhn7SHgu3/AG3fG/8AwTp+NHwR0rQvjN8DPA3xv8YeNvHWvTxaXLoFv4TvfA19oNpqM+jeKPss2qxPrYW1W2t9OvJ0kUStAECyr04Or/ZlLN8NiZTw2Kq4WFOjC8lJ1I1FLSUbqL5HfV6X62fNzYqmswnl1ago16FOvUnUlo48rpuKfLKz3du/X3b3j+g3iXUfgv8As6+CPFfxD1XTfBPwr8D6DaLqnizXNE8L6boNlBaRyJbpdajF4c0yKa7EbzJGhaCd0D4XC7jXkwWJxlSnSUquIqzfLTjOpKbvvZe0nZbX3j69Y+lJ0MLTlUahRpx1nKMFFJd3y3/L79D5h8Hf8FQv2CviB4q8PeCPB/7R/g/XPFXivVbTQ/D2j2tj4kW41PVb6TyrSzhabRooVknkIRTLLGgP3nFd1TJM1pU51Z4SooU4uU5NwSjFbt/vLu3Zf5nLDNcvqSjCGKhKc2oxilO7b6fBp+P6x8J/aP8AF3/BQO2k/ad+Btl+yzbftIfDr4z6PrXh74C/EXwr4v8Ah94O8NeAdB8Y+G20S/0P426V4r1my16X/hGb+6utSj1jw7peuvq9msMMVrFcD5enB08pf1LEvHfU62GlGeLo1KdapOrKnPmU8NKnGUUpqKi4zlBRe7S+HmxVTMU8TQWE+tUq6ccPVhUpQhTjOPK411JqXutt80VLmWjtpI8Y+Mf7Mn7SPwN8Gf8ABKyX4WfB3xD+01q37Gs+r2vxN0DwT4p8F+HNUuIr34aL4UjutIvviBrvhvTZrRNTlkWJfPaYWkAJi3FFrpw2OwWKqZ77fERwUcyUHQlUp1JRTjW52pKlGcrtWWy1a3SalhWw2Kw9PKfZUJYp4Jv2sYShGVnS5NHUcFa+y1sr7e7E+pv2JPg78eD8dv2p/wBrj9oL4faf8F/EX7RF/wCANF8JfCCPxVpXjLW/CHgj4c+H10TT7zxh4g0FpNAk8QazM013PY6TcXVtYQ7Imu5XyycWZ4jC/VcDl+ErPEwwiqyqYnklTjUq1p80lThO81BLROVm91vc7MDRxHt8VjMRTVGWJdNQo8ynKEKceWPPKPu871uo3S2u7Nnb/sP/ALVPxG/ax1H9pDxTq/gvw54a+Dvw++OXiv4UfBXX9NuNSn1v4gaP4IuW0rX/ABTq63eLKGGTWo7mxsl07fC62skhkYEVjmeBo4BYOEas54ithoV8TCSXLRlVXNCmrcsr8urclptpdOV4DF1cW8TOVOMKFOvOlQkm3KooO0pvoldWSTl1besT74ryz0T8gf8AgpJ8D/jL8T/i5+zh4ot/hB8S/wBpf9l7whYeNbP4vfs+/Cf4pRfDLxLq/jLVnsR4O8a6ks/i/wABw+LdD0S2ju7R9IbxPbtZzzm8+zSqx3e/k+Kw1DD42m8RRwWNqum8Pi8RQdenGnG/tKStSqunOTtJS5bPZ3tY8XNKFarWw0/Y1cVhYKftcPSqezk5trkm/wB5T50ldct9N9fs/OXwD/Yl+M/gv9mr/grL4H0X9nK4+CqftOaX4of9n34UXHxF07xxqN3BrPwOtPC1hpmo+KLzxProg1ZvECSWOo/2nrL2Vteeb9mvJrBYrhuzF5nhqmNyCpLGLE/UZQ+t4hUXSinHE87agqcVbls1aN2t0m2c2HwNenhs3prDOgsVf6vSdVVG70eVJy5pWlzuzvL5tW5f2M/Zv+Ht94Q/Z1/Z88E+PvDthF4t+Hnwu+H2kahYahb6bqs3h7xRoXhXT9L1A2N2ovLeG+tJ47m2F/p1xkpvENw8T5r5/GVlUxmLq0pt061etKLTlFTpzqOUbrRtNWdpL7rHs4WlyYbDwqRXNTpUk07PllGnFNr4rNNNaPa6u0/d+bf2SPgZ8Svhx+07/wAFG/HnjzwsNL8FfHj47eD/ABb8NNQnvNKv4PFnhfTvhX4a8N6neNZW11c3FnDHqtjeWMlpq1vazSiNmWGSB1durH4mjWweTU6U71MJhalOurSTpzdao4q70d1Zpxvv3TUebB4epTxWZVKkLU8RXhOk3b3oqjCDejbWsWveUWvNNM+ev+ChP7PnxT8bfHH9nLxBb/Af4h/tJ/se+C/BPjbw/wCOP2bvgj8SbD4SajZfErVNR0uTwf4+1PSF8X/Dux8V+G9K0eHUdKi0mHxDbjRrq5N+LKdXbf25Ri6FLC4yDxVHBZhVq06lLG4mjLEJ0YqXtKSl7Oq4TlJxk3ye8vdUkc2Y4arOvhmsPUxOEhCqp4ahUVFqrKS9nUceejGcYxXLbnXK7OzWhe/4JafsmeN/gNc/tw2XxE+AsfwR+Hfx0+OUHir4c/DO78bW/wAR9nw81P4d6HoN3pupa+dd8Q3d5eJPFfWGqpf30o+1/aEs5bmzWG4ec8x9PFf2Y6OK+s1cJh3CtWVP2P71VZSUlDlgktU42W1m7NtDynB1MP8AX1Uw7oU8RXU6VJ1Pav2fs1FxlK8tXtJd78tlZnzT/wAEdP2fNb0j49ftUePda8SQeM/hh+y94p8XfsSfsn6rH5ssNj8L/DPjnWPHXi9beWbcs1zY6zrml+C7q8tiYZE8Ix2scjJa4rt4hxkZYXA0Y0/ZV8bTp5njo7XrTpRpUm1ro4xnUSbT/eNtbHNk2HccRiqkp89LCyngMI+ipRq+0lZ2e0pKG6T5WldI/RTW/wDgqz/wT58Oavqug61+0z4LsNX0PUL3StVsZbDxO0tnqGnXElre2shTQijPBcRSRMUZkLISjFSDXkxyLNpxjKODqOMkpRs4O6eqfxX1TutH+kfTeb5dFuMsVTUotxatPRp26Qfbv954X+1p4H8d+Ofjb+yp+3N8B/g9D+198KdM+C/xa+E/xC+EWi6t4Y0bxB4v+F/xvi8N6zp3inwzafEG70Tw54gtVk0X7HrHh7WNQsJLnTdR3IjlXSunAVaVPDY7K8XiP7OryxFCvSxE4zlTp1sM6kZU5ypRlODal7k4wdpWetve5cZCdSvhMdh6P1uj7GtRq0k4qU6ddQalFVOWM7OFpRbjdPrdmN+wz8OtH/YS+Gv7Wv7Sv7Qfw/8ABX7G/gH44/HOL4jaX8G9GfRb3Svg14Ih0Hw/4I8KaTrS+Abe78PQ+INbudPk1TVbLw8t7YWV1qIjNzIwlmas0rSzSvl+DwlWpmFXCYb2MsTLmTxFVznUqTj7W03CKdo89rpX929hYCnHAU8XicRThgqeIrqqqKtajDljCKkqalFSd7y5dLu2tk4/WPw4/wCClv7DXxa8c+Gvhv8ADz9oTwn4p8a+L9RXS/Dvh+ws/EMd5qt8YZbj7NA91o9vbrJ5EE0mZpY0whyQSBXDWyXM6FKdarhakadNc05e41GO1/dlK61XT7/s9tPM8BWnGlTxMJVJu0IpTu3a+l4JbK+/3nw7+1BY/wDBRb40/Bz9o39iTxX+zFp3xHHxl8Ra/wCFfh5+1NovjHwB4d+D3hr4PeIPElnqOi65448K3+rf8J3aePfAehj7E9ho3h3UU1vVrCG/tb6BZn2+lgnk+GxGDzKGNlR+rRjOtgZU6s8RUxEIcso0pqLpOlWk73lOPInZxaT5fPxazKvQxOBnhPautKUaeLjOnCjGi53jKpFv2inTjpaMXzSV01e0ut/aR+Gv7Snwh/a//Ym+Ovwb/Zz8bftQ+E/gn+zB8Tfgp4xh8H+Mvh34T1i28QeIdR8HnRdRu5fiF4m8PxT213BoN1cXUlkt7JH5gJiL/u2jB1sFiMuzPC4nGU8FUxWNo4mm6lOtUjyRUuZJUoTs05Wim0tN2tSsVSxVHGYKvRw1TFQo4SpQqclSnCSlN07N+0lHpBvz8vte+/sCfBj4q/Bnw3+058bf2jNH0H4eePP2k/jp40/aF8S/D/Rtft/FFj8L/DTaJp2maT4e1HxNaxQ2GsaxYaBoCXmuXdgGsEvJJYraV0jLtyZriKGJqYLDYOU6tLB4WnhIVZR5HXnzOUpRg9VFylaCbi313TOnL6VajDFV8VGNKeJxE8RKnFqapRaSSlP3VJxjFOVuWO+9049l/wAE7/2mvij+2B+z6Pj/APEbwL4f+H+j+NPHfjhPhLpWiXGpXNzq3wn0XXrvRvCXirXX1HATVPEsFlNqYjsgLMWU1q8WS7Vnm+Co5fi3hKVWdWVKlS9vKSUUsRKClUhFJvSDajq909jXLsVVxmH+sVKcacZ1KnskuZt0oy5YTle9nOzlZPRNLWx92V5Z3n4xf8FBfgP8XfiL+1F8F/HOv/AX4q/tafsk6L8KvEfhrW/gZ8JPi1b/AA11HQfjNfeI47zTviN4m0m68cfDyHxfpEvhxYtFtG/4SJzoU8U9wbB0mZ2+iyrFYejgcTSjisPgMfOvCccViMP7aMsMoWlRpzVOq6cue8n7nvLbVXPDzHD16mKozlh62MwkaUoyoUqqp8tZzTjUkva0Odci5bc/uu71uz5F8GfsBftG6J/wT3/4KUfBDQ/2ff8AhXHin49/tA3Xjr4IfCSD4haT4sb/AIQm7u/hzdWdufGOqeIb5Jrmzg0XU4rybWtVSZ7uynELTQvavL6FXNsHLNsmxUsX7eGEwnssViPZSp/vIqun+7UFZNzTSjHZ9bNnHTy/Exy3NKCw7pzxOIc6FL2ineMpUre/Kb10d+Z37Xv739F3hzQLOHR/BjaxpOnS6z4c0bTbe2urqzs7u90e6/s21tdQGnXrxSzWbS+V5NxJZyp9ojQI5dABXyE5Pmqcspck5NtJtKaTbV1pzb3Sa+Sv7v0kIJRp80VzQWjdm4vrZ626bP77Lm+EP+Ce/wAA/iH8HvCf7WehfGDwdBpMXxT/AG0/2iPih4a0zUZ9G1yz8R/Dfx5q+nzeH9Vuba1uL+1FrrFpDOZNM1JUukjBjvLOPcEf1M2xVHETwEsPU5nQy7B0JyipRcK1GLUoptJ3i7PmjddndM8/LMPUo08XGvCyq4zEVYp2alTqSTi2ruya6Oz6NaHyt+2t+zn8U/GX7Znhvxv43/Zo+Kf7X37IyfArRvBXw/8AhF8IvjDZ/C7TPhT8YrTxJqd14h8V+L/C8nj74b2+taf4j0KbRdP03XodR1IeHrfT57caYFZC3dluLoU8unSpY2hl2PeKlUq4jEYZ4iVfDuC5KdOfsa/LyzUpuFo8zaetjkx+GqzxsKk8LWxmD9goU6NGv7JUqyk25Th7SimpRaSkpS5UrW1sd1/wTZ/Yv8SfDT9jT9o/9nL9ov4VWPw18OfF/wCOP7TN6Ph+vie38aabZfCX4paldR6N5HiL+0dVub+KHRLomG81Wcap5lql1dxpIQKzznMoV8xweMwdd154fDYJe19m6Tdegk5+600ryTvFLlV+VX3NcswMqWBxWGxNJUoVsRinyOanajVfu3lrdWu/elLtK2x4j/wQq+FvjNfhp8Yv2m/iv4mh8c6z4j1qy/Zu+EnjULMU1L9mv9k46l8O/BOtWklxulMHi3VrPXvEl1InyXcpimAkVInfp4nxFP22HwVCn7GMIvGYmnorY3H8lWpFqLa/dxcYLay9WjDIaU/Z18VWn7RtrDUanfDYS9ODvu1KScrtRvfbc+37z/grT/wTtsLm7s7v9qDwTBc2U89tdRNYeKN0M9tI0U8ZxoRBMciMp2lwSMgkEV5iyHN2k/qdTVXt7n3X51+X3He83y1aPF001o1aej6rSD1T0evTrYyNJ+CWtePf+Cmdv+1NN4M0bxV+z34h/YU8H+AfD3jbVINC1TT7vxjL8WtW8ZpYWui6l52rwtJ4W1G01EX50yO2MUwtzcCcNErliY0cmlgPaShi4ZpVrTpRc4yVP2Ead3JWjpONrc3pbVmaw7q5o8U6anhp4CnCFR8rTm6sp2SfvK8ZJ3S+cfted/sgz6N/wTs/Zo+Lep/tcXmk/A7w/wCJf2zf2ivFHhm41CW31DT7jw58TPiHrHiHwFPbx+Fk1eO0TWdEhe6t7KSOCWyjjMN1FbyARLvmHNm+NoRwCliZQy7BwnZNNTo0Ywqp87jflm7N31b0tf3owTjluFrPGNUIzxuJnFvVctWo5Qfuc/xLp+VlzfT/AMJf+ChH7HX7QPjWz+F/wZ+PXhbxj8QdbsNUuNH0TTrHXRdSLp1lLdXN2Pt2lWtsyWUS/aZI5J0MiIVXJOG4sRlOYYSm6+Iw04UouKlJuCWrslpKT956bdb6293rpZjgsRNUqGJhOrJPliozbvbzjFfj62+1+dHxv8J/8FE/2rfhH4d/Yx+M37M1lZeJIPjn8O/EvjT9sXS/GvgG1+C03w++GPxVsfHeneM/BHhG01af4iWXj7WdC0Sw0WPw1N4dtYNN1S8uriTVntBtf18LUyjA155lh8a+T6tWhSy6VKrLEqtWoOk6dWo1Gi6SlKUvaKcnKNmoreXm4iGY4yjHBVsMlL6xTnPGKdNUHSpVedThGMvaRqOMUuXl0bvzWdj1b416R+1b8Fv+ClHiT9pr4Q/skeN/2lfAPjD9j/wN8F7S+8KfEH4YeDItG8b+HviL4j8Uzr4gfx14l0m/XTmsr2z8690zTdRZWlZkhkKsic+GlgcRk0cFiMfSwdWnmFbEuM6Veq5U50oQXIqVNpu6ejlFdLtpo0rrF4fM5Yqjg6mKpzwcKCcKlKnacajn73PO9rWvaMvnb3ve/wBhH4OeMP2M/wBkPxjqf7QF34e0zx1q/jP4+/tP/Fmx8Pag2o+GvBl78QfE3iL4mat4ZsNYlit/7TtvC2mzJp1xqqxRw3dxbXE8KeSyFubNcRTzHMKccIpypRp4TA4dzSU6ipQhRjNrWznK8km27NJ22j04ChPA4Ko8RyxqSniMVVjGTlCm5ylUcebW/LFK7Ss3dq92eif8E+P2gfi3+1T+yr8Ov2hfjF4D0D4a618Vjrfinwr4R0CfUrlbT4b3Wr3UXgLUdWl1T9//AG1rugQ22s3sUQFtEt7CkORkLjm2Ew+Bx9bB4erOvGhyQnVnyq9bki6iio292Mm4q6u93a7NcuxNbF4Snia1ONJ1bzhCLb/dN/u23/NKNpNK6V9N2o/aleadx+Gv7YH7OnxX8bftvar4/wDip+zD8Wv2z/2ZtZ+EHgnwx8GvBPw0+N0Pw28P/B34l6dqOsS+PNV8e+F5viF8PDfr4vW40aa28Yw3GuyaXYWE1kunM5RK+my/G4ellipUMbQy7Gxr1J4ipWwvtp4ii1H2UaM/ZVtadpJ07RUpSi3tc8DG4arUx0qlbC1sbhZUYQowpVvZKjUTlzua9rTu53jaaUrJWsvij4H4D/YI/ab8Of8ABMPwV+zr/wAKei8P/EzQ/wDgoz4c+OD/AA8sPGGj6zbaF8JNP/aXbx8+q23ifUNYki1W10zweVukF3fNr19HEPMtGvZDDXXUzbBTzyrjfrDnQnk0sL7Z05JyxDwns+VwUbpynppFRi9HJJXOanl+LjlcMO6PLVWZqv7NTjLlo/WvaXUnK0ko66tSa31b5v6OzpmlyapBrMum6c+rW1vNY22rvY2r6pbWNxIstxZQag0RvIbOeWOKWa1imWCWWOOSSNnRGX49yly8qlJRbTcbvlbTWrWzaV9X6dT6ZRjdSaXMly81ldLqk9Wk30T++x+eH/BMr9n3x38Ef2NdE+EHx28EWekeJY/iX8bte1PwprDaH4js5NI8VfFzxX4o8OXNytrPqmk3K3mk6hYahHEzyyWzyIJUS4iZU9bOsVRxOYvEYWq5Q+r4SnGpFSg+anh6cJ2b97SScXpG9ux5uVYedDBRo4inaSq124StJWlVlKL0TWqaf2vVHyT+1t+zh8VPGn7b/inx38V/2Wvix+2f+zh4h+EXw/8AC/wF8KfDn43w/DXwr8EviBpM+q/8LCu/H3hiX4ifD1pv+ExuLnSr2HxrbHxFLY6ZYvp6aejpFHXfgMZQp5ZTo0MdQy3GQxFWpip1sN7epiaMrexVKfsqvwWkvZNRTbTvozjxmGrVMwnUrYStjcNKjTjh4U66pQo1Fze09pF1aXxtp+0tO0U1yv3SX9lb9hzWPC//AASC+NP7I/7U/hfT/hENen/av1jUrNfEFt4hsPAWga58Q/GPjz4feLtP8Rx31608fhu3XQ/Emm6he3Taqq2EUmpRRXrTxK8fmkZ8QYXMMDOVfk+oRj7jg6ko0aVKrTcPd+O8oSSXLrZXV+Z4TAOOTV8HioKjzPFu3NzKnGVSpUpzUrt2iuWSbd9NbXOi/wCCMGheL9C/Yu8R/tn/ALR2sW9x8V/2rtQn+PHxG8WyQXKRQfDLwH4TsvA3wzaOORHvYtKj+H3hBfFkdsYvMV/EdyyxOzoKjiKVOeZQy7BxfsMClhaNNWv7erUdWstLLmdar7O99eRarXlvJIzhgpY3Ev8Ae4p+3qTd9KNOChSsui9nDnskvie+0fpS0/4K0f8ABO6+ubWztP2n/BM11e3Fva2sK6f4o3TXF1KkMES50IANJLIiDJwC3OMVxPIc2SbeDqWSu/4ey/7iHUs3y16LF023olaer+cEvvf3Hzb/AMFRoP2rPid4o/Zq8HfAj9jX4k/Gfwt8Ff2m/gB+1BqnxJ0Dx/8ACHw94f13TPAUniS41vwNpWl+MPGeieIIvEaJqVp5d5eafHo0nm/LeHa+3tyN4ChDGVcVmNHDTxOCxWBjRlRxM5xlW9ny1ZOnSlDk0enNzeiZx5ssXWnhYUMFVrQoYrD4p1Y1KMYyjT5uamozkpKeqs7cvpduP3n4w/bJ+FvwV+FHw3+J37Vskn7MGofEYzWqeBvH17Za/rOgeIYI57q58OX+peBn8RaFeX1vYRJevcadf3NkYpkRLhpVdF8qnl1fEV62HwP+2xo2/fUouMZw2U1GrySSbuveUXpqtYuXpSx1GjRpVcX/ALI6n2KnvOMl9lumpRbS10dtev2c74Sftxfsw/tQ6r4k+Hf7OXxz8LeMviNbeD9a1y0trHTdak/seKFI9Ptteu4NR06yt7qz07VtQ057i0E3mXCN5YQhmZXiMsxuBjCrjMNOFF1IxbcoR5tb8itKTvKKlrbTuripY/C4pyp4bEQnV5JSSUZ6dOZ3jFWTa06+X2vzk+IPhT/goL+194Z/Zq/Zt+PP7MEPw+8R/CP9pH4NfGH4zftX2njvwDP8J9e0n4G+M28Vw618F/DWj6peePoPEfxHTT7PTV0bV/D+jw+G7fVNRjvb6eIBW9ijUynL54zGYXGurDEYPE4bDYB0qqrwliaag44mbSpOFG7lzxlLn5Y2SlZnmVYZjjI4bC4jC8k6WJo1q+MVSn7GUaE+fmoxX7zmqWS5XGPLqnprHf8AFem/tp/Ab9vT9vn4qfCH9i/xT8e/CX7T/gX9nnRfhn43sfih8LfBHg3Sdf8Ah38MdR8L6z/wmSeJfEUHiu10yz1nVE8+XS/Dl/NNBaTm2jffE1RTlluKyrK6GIzGGFqYGti516cqFerUlCrXVSLp8kHTbcY9Z6X15XdRc1jcPmGPq0cFPEQxVPDxpzVWlCEZU6coy5+Z8ySb+zFuy2Wrl9dfso+EPCn/AATR/wCCf/wd8IftG/Ejwr4e0z4LeFYD8T/H801xB4Q0/wAUeM/F1/r+sR2Vw8D3L6VD4l8US6RplxJCJLmGOCZ4l3la4MdOec5riJ4OjUnLEzfsaS1qOFOnGCbv9pwgpS7bdjtwkIZXl1GGJqxiqMf3tT7CnObbSfbmlyp2j6aHz5/wRU8T6Frn7Ivxk8d6VqUN34R8QftsftqeNNF15VljsdR8Kar8Y9e1vTtetmmjR30680mWPUIJygD2zBwOQK6+I4ShjsNSkrVIZZltKcLpuNSOGhGUHrZNSVmr/PW5zZFOLwdeomuSWOxtSMujhKs5KWvRx19Neo79nDxPJ+2p/wAFDda/bU8BaHrtt+zF8Cf2cNb/AGa/hB8Q/EGian4eT41+PvHvj2w8YfEfxR4L0/V7ez1G88BeFLHw/pWgWPiKezis9d1S8u5NMaW2tTM5jIf2dlEctqzi8ZisbDG4ijCUZ/V6VKk6dGFSUdFVm5yk6e8YxXNqww0njsyljacZLC4bDSw1GpKLj7epVqRnVnBNXdOChGKle0m7xsk0fsRXzx7YUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBtaB/yFLf3Ev/opj/T2/TDdeB/3mHpP/wBJf9f8MYYn+E/WP5/1/TPRq9084//V/v4oA4HxN/yEF/694/8A0J68XMP46/69x/OR34X4H6/5nO1wnSFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAA457jmgDhvBfwy+Hvw5m8VXPgPwb4f8JXHjrxLfeMvGdxodhHZz+J/FepBBf+IdbmX95fapdrHGktzKzMUjRRhVCrrUrVa3J7WpOoqUI06ak7+zpx2hHtFb2tu29bszp0qVLn9nCMOeTnPlVuab3k+7fV3+4619O02RmeTTtOkdjl3ksLSR2J6lneFmYn1JJ/IVlr3l/wCBP8EtinGL15YvzaX6lmOKKFFjhiihjXhY4Y0ijUdcKkaqi8+ij8eTR9773d/6/p9WUklolZdl/wAAJI45UaOWOOWNhho5Y1kjYejI4ZWHswI/Oj+tNPx6AVl03TUZXTTdNR1O5XTT7RHVh0KssIZSPUEH3HWi7X2pf+BP9f6+4lRiteWK80l+hcoKCgBGUMrKwyrAqwPQqwwQfYgkH1oA53wp4P8ACngTRYPDfgrw3onhPw/azXVxb6L4e0210nTIbi9uJbu8njs7OOKBZru6mluLmUJvmnkeWQs7s1XOpOrJzqzlUm0k5zblJpKyu3fZJL/K1iIU4U4qNOEYRX2YpJatt6K+7be/36nR1BYUAFABQAUAFAB+f4HB/AjBB9wfyxQBw3w8+GXw9+Evh3/hEfhl4N8P+BPDB1XV9cbQ/DWnxabpz6z4g1C41bXNUkgi/wBbf6tqd1cX1/dSFpbi5mklkZmbNa1q1XET9pXqTqz5YwUqjcpKEEoxim7vlilZLp5aIzpUqdGPJShGEbylaKSXNJ3k9Osm235/M6xtM0xiWbTNMZmJLM2nWZLE8ksTASSSSSSck8nOay1/ml/4HL+v8iuSP8sfuiW0RI1VI0WNFG1URVRFA6BVUKqgdgoAHQdqChssUU6GOeKKeJsbo5o0ljbByN0cishwQCMqfbHWj0bT8nb8f6/ITSe6v6/1/XyIE07TonWSLTtPikQ5SSKxtY5EOMZR0iV1OCRlWBwSOelGveXzk2vue/8ATEoxWvLFeaS/Qt0FBQBUv7Cy1SxvdM1K0gv9O1K0ubDULG6iWa1vbG8hktru0uYXyk1vc28kkM0TjZJE7o2VNNNxalFtNNNNbprVNeaYpJSTi1dSTTT6pqzXXdeX3lHw74c8P+ENC0nwv4V0TS/DfhvQbG30vRNB0Sxt9M0jSNNtEEVrYadYWkcVtaWlvGqxwwQxqiKMAdTTnOdSUp1JSnOb5pzm3KUpPdybu2/P8thQhGnFQhFQjFJRjFJJJaJJLTRGzUlBQAUAFABQAUAVb+xtNUsb3TNQt47vT9Ss7rT7+0mBMV1ZXsEltd20oGCY57eWSKQAglGIBXINNNppp2aaafZp3X4r/MTSaaaummmu6ejX3HNeAvh/4I+Fng7w/wDDz4ceFND8EeBvCmnppXhvwn4bsIdM0PRNOjZ3Sz0+xh/dwQh5HcgZLO7O5LMWa6tWrXqTrVpyq1aj5p1JvmnJ95Se7/ImnSp0acaVKEYU4LlhCKtGMeyWtl5flax0J0vSznOl6Wc5Jzp1mSSepJMGSSeST/Ws7vfmlf8Axy/r/IfJH+WP3RLqqqgKoCqoAVVAVVA6AKMAADgADA7YxQURzQQXC+XcQQXEeQ3l3EMc8e4dG2So67h2OMj1HRjXo2vR2/FCaT0aT8nr+f8AX3EUVhYQOJILCxgkGQJILK2hkAPUCSOJHAPcA89DRr3b9ZN/g/6+9AoxWqik/JL9P6/EtUDCgDL1vRNH8TaNq3h3xFpdjrega9p15pGt6NqltHeabq2lahA9rf6bqFnMrQ3Vle20stvdW0ytFNC7xyKVYhnGUoSjOEnGcJKUZRdpRkndSi1qpJ6prZ+pMoxnGUJJSjJNSi9U09011TWjXXYk0nSdL0DStN0PQ9OstH0XR7G10zSdJ021hstO0zTbGCO2srCxs7dVgtbS1t444LeCJVjiiRUVQAApKUpycpycpSblKUneUpPVybd223q7vr1HGKilGKSjFJJJWSS2SWlkvT7rGhSGFABQAUAFABQBz3i3wn4a8eeFvEXgnxnomn+JfCPi3RdR8OeJ/DurQ/adL13QdYtZbHVNJ1K33KLix1CzmltrqAsFlgleNsqxFXTqTpThVpycKlOUZwnH4ozi7xktrNNXTvo1fQmcIVISp1IqUJxcZRlqpRas011TWjLHh/w5oHhPw9ovhPwzo+naD4Y8OaRp+gaBoGl2kVppOj6HpVpFYabpOn2UaiG20+xsoYbW2to08uOCNIwCoFKcpVJSnOUpznKUpzk7ylKTvKTe7lJttvuEYRhGMIxUYRioxilZKKVkkuyWhbGl6WMY0vSxjBGNOswQR0IIgyCDyCP6VN3vzSv/AI5f1/mHJH+WP3RL1BRDNbW1yFW5tra5VTuVbm3huFViMblWVHCtjjIGccZHIY+bXo2vy3/rsxNJ7pP1Sf5/19yGQ2Vlbv5lvZWVvIQVMlvaW8DlTyVLxRIxXIB2k4zg4PBUu9rtrezk3+f9fgCiltFL0SX5en9XZZoGFAEFza2t7C9teW1veW0mBJb3cEVzbyAEMBJDOkkT4YBhuU4YAjBAKtNp3Taa6p2f3r+unUTSejSfk9fz/r7hlvY2Nnbm0s7GztLQ782trawW9sfN/wBbm3hjSE+Zk+ZlPnyd2c0Ntu7bb7t3f3sFFJWSSXZJJa+W2pNFFFbxRW9vFFbwQRrFBBBGkMEMSDCRwxRqscUaAYWONVRRwByNqbvq9W9W31GkkrJWS2S0RJQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBs6B/yFbf6S/wDop668D/vMPSf/AKQzDE/wn6x/M9Hr3Tzj/9b+/igDhPE8bi8jlKny3hVFbHBZSSRnpnDDjg/kC3j5hF+1jPo4JfNN/wCff7juwrXK49d/z/r5ruc1XnnUFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBu+HonfUo3VSUiWRnbsoKFRk+pZhgZ598V24CLddSSdoqV30V4tL+r/fc58S0qdurat8n/X9Jnode2eef//X/v4oAjkijmUpLGkiH+F1DL+RyP8APbrSlGMlaSUl2auv1/rtuNNrVNr0K39nWH/Plbf9+Y6y+rUP+fVP/wAAiV7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/AH5jo+rUP+fVP/wCIe0n/Mw/s6w/58rb/vzHR9Wof8+qf/gEQ9pP+Zh/Z1h/z5W3/fmOj6tQ/wCfVP8A8AiHtJ/zMP7OsP8Anytv+/MdH1ah/wA+qf8A4BEPaT/mYf2dYf8APlbf9+Y6Pq1D/n1T/wDAIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/8AgEQ9pP8AmYf2dYf8+Vt/35jo+rUP+fVP/wAAiHtJ/wAzD+zrD/nytv8AvzHR9XoLX2VPT+5H/g/l94e0n/Mw/s6w/wCfK2/78x0/YUf+fVPv8KX5W79vLS4e0n/M/wCv6/q7D+zrD/nytv8AvzHR7Ch/z6p/+AL7vTy2D2k/5pdt3/V/PcP7OsP+fK2/78x0ewor/l3D/wAB+Xn/AFtbcPaT/mYf2dYf8+Vt/wB+Y6PYUf8An1Dt8K/y3030fmw9pP8Amffr/X6B/Z1h/wA+Vt/35jo9hR/59w+4PaT/AJmH9nWH/Plbf9+Y6PY0f+fUP/AV0+Xl29b3fMe0n/M/6/r/ACD+zrD/AJ8rb/vzHR7Cj/z7h939fr+CUT2k/wCZ/wBf1/V2H9nWH/Plbf8AfmOj2FH/AJ9w+4PaT/mf9f12+4P7OsP+fK2/78x0/Y0d/ZU+3wr/AOQt+Hz6B7Sf8zD+zrD/AJ8rb/vzHR7Giv8Al1T7/Cv/AJB/p6B7Sf8AMw/s6w/587bnr+5jo9jR/wCfVPX+6v8A5B/gl8w9pP8AmYf2dYf8+Vtj/rjHR7Kl/wA+qf8A4BH/AOVh7Sf8zF/s6w/587fP/XGOj2VL/n1T/wDAI/8AysPaT/mYf2fY9fsdvn/rjH/n/PtR7Kl/z6p/+Ax/+Q/T7w9pP+Zh/Z1h/wA+dvj/AK4x0eypf8+qf/gEf/lYe0n/ADMP7OsOn2O3x/1xj/lR7Kl/z6p/+AR/+Vh7Sf8AMw/s6w/587f/AL8x/wCf8+1HsqX/AD6p/wDgEf8A5WHtJ/zMT+zrD/nytv8AvzH/AJ/z70eypf8APqn/AOAR/wDlYe0n/Mw/s6w/58rb/vzHR7Gjt7Kn/wCAr0/lv+L/AATie0n/ADMP7OsP+fK2/wC/MdL2FH/n3D7v+G/rvuHtJ/zP+v67fcH9nWH/AD5W3/fmOj2FH/n3D7v6/T8WpHtJ/wAz/r+v6sg/s6w/58rb/vzHR7Cj/wA+4fcHtJ/zMP7OsP8Anytv+/MdHsKP/PuH/gPf5fovKwe0n/M/6/r/ADD+zrD/AJ8rb/vzHR9Xo/8APqH/AICv6169+oe0n/Mw/s6w/wCfK2/78x0ewo/8+qf/AICvX+t/LqontJ/zMP7OsP8Anytv+/MdH1eg/wDl1T1d/gj/AJf5ej+ye0n/ADPt1/r9Q/s6w/58rb/vzHS+rUP+fVP/AMAiHtJ/zMP7OsP+fK2/78x0fVqH/Pqn/wCARD2k/wCZh/Z1h/z5W3/fmOj6tQ/59U//AACIe0n/ADMP7OsP+fK2/wC/MdH1ah/z6p/+ARD2k/5mH9nWH/Plbf8AfmOj6tQ/59U//AIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/+ARD2k/5mH9nWH/Plbf9+Y6Pq1D/AJ9U/wDwCIe0n/Mw/s6w/wCfK2/78x0fVqH/AD6p/wDgEQ9pP+Zh/Z1h/wA+Vt/35jo+rUP+fVP/AMAiHtJ/zMP7OsP+fK2/78x0fVqH/Pqn/wCARD2k/wCZh/Z1h/z5W3/fmOj6tQ/59U//AACIe0n/ADMP7OsP+fK2/wC/MdH1ah/z6p/+ARD2k/5mH9nWH/Plbf8AfmOj6tQ/59U//AIh7Sf8zD+zrD/nytv+/MdH1ah/z6p/+ARD2k/5mH9nWH/Plbf9+Y6Pq1D/AJ9U/wDwCIe0n/Mw/s6w/wCfK2/78x0fVqH/AD6p/wDgEQ9pP+Zh/Z1h/wA+Vt/35jo+rUP+fVP/AMAiHtJ/zMsRQQwKVhijiUnJEaKgJ9TtA/Un8K0jCEFaEYxX91JX/r5/koy5OW7b9f6/r5slqhH/0P7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP//R/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA+Av2tf+CjnwL/Y4+Ifw++FnxG8N/GLxb42+JnhzWvFfhnRPhJ8LvEvxKvZdF8P3kVhql3d2vhq1u7q2S3uJoVZmhZAJUZmG4K3bh8DUxNKpWjOjTp05KE5VqsKa5pK8Uube6v1W3XePJXxlPD1IUpQqzqVIuUY0qcqjajv8PM1q1bTXbX7Pzt/w+o/Z5/6IF+3F/wCIjfF7/wCUVa/2dL/oMy//AMLaBn9fh/0D4v8A8Jq//wArD/h9R+zz/wBEC/bi/wDERvi9/wDKKj+zpf8AQZl//hbQD6/D/oHxf/hNX/8AlYf8PqP2ef8AogX7cX/iI3xe/wDlFR/Z0v8AoMy//wALaAfX4f8AQPi//Cav/wDKw/4fUfs8/wDRAv24v/ERvi9/8oqP7Ol/0GZf/wCFtAPr8P8AoHxf/hNX/wDlYf8AD6j9nn/ogX7cX/iI3xe/+UVH9nS/6DMv/wDC2gH1+H/QPi//AAmr/wDysP8Ah9R+zz/0QL9uL/xEb4vf/KKj+zpf9BmX/wDhbQD6/D/oHxf/AITV/wD5WH/D6j9nn/ogX7cX/iI3xe/+UVH9nS/6DMv/APC2gH1+H/QPi/8Awmr/APysP+H1H7PP/RAv24v/ABEb4vf/ACio/s6X/QZl/wD4W0A+vw/6B8X/AOE1f/5WH/D6j9nn/ogX7cX/AIiN8Xv/AJRUf2dL/oMy/wD8LaAfX4f9A+L/APCav/8AKw/4fUfs8/8ARAv24v8AxEb4vf8Ayio/s6X/AEGZf/4W0A+vw/6B8X/4TV//AJWH/D6j9nn/AKIF+3F/4iN8Xv8A5RUf2dL/AKDMv/8AC2gH1+H/AED4v/wmr/8AysP+H1H7PP8A0QL9uL/xEb4vf/KKj+zpf9BmX/8AhbQD6/D/AKB8X/4TV/8A5Wcv4w/4Lufsn+ANFbxH4y+EX7ZXhnQ1v9L0s6rrv7LPxS0mwGo61fwaZpVl9sv9Hgtxdahf3EFpZwGUS3NzLHBCkkrojXDKqtWXJTxOBnKzfLDF0ZPlirybUbWSSu23p5EzzKlTjzTo4qMbpXlh6yV5Oy1lTtq9DqB/wWp/Z4IBHwD/AG4SCAQR+yP8XiCCMgj/AIkQ6jH/ANfrUf2dL/oMy/8A8LKC/V/n91yvr8P+gfF/+E1f9IP8/vD/AIfUfs8/9EC/bi/8RG+L3/yio/s6X/QZl/8A4W0A+vw/6B8X/wCE1f8A+Vh/w+o/Z5/6IF+3F/4iN8Xv/lFR/Z0v+gzL/wDwtoB9fh/0D4v/AMJq/wD8rD/h9R+zz/0QL9uL/wARG+L3/wAoqP7Ol/0GZf8A+FtAPr8P+gfF/wDhNX/+Vh/w+o/Z5/6IF+3F/wCIjfF7/wCUVH9nS/6DMv8A/C2gH1+H/QPi/wDwmr//ACsP+H1H7PP/AEQL9uL/AMRG+L3/AMoqP7Ol/wBBmX/+FtAPr8P+gfF/+E1f/wCVh/w+o/Z5/wCiBftxf+IjfF7/AOUVH9nS/wCgzL//AAtoB9fh/wBA+L/8Jq//AMrD/h9R+zz/ANEC/bi/8RG+L3/yio/s6X/QZl//AIW0A+vw/wCgfF/+E1f/AOVh/wAPqP2ef+iBftxf+IjfF7/5RUf2dL/oMy//AMLaAfX4f9A+L/8ACav/APKw/wCH1H7PP/RAv24v/ERvi9/8oqP7Ol/0GZf/AOFtAPr8P+gfF/8AhNX/APlYf8PqP2ef+iBftxf+IjfF7/5RUf2dL/oMy/8A8LaAfX4f9A+L/wDCav8A/Kw/4fUfs8/9EC/bi/8AERvi9/8AKKj+zpf9BmX/APhbQD6/D/oHxf8A4TV//lY1/wDgtV+zuis7fAP9uFVRWdmP7I/xeCqqgszE/wBhEAKASSeAAScdaP7Nk9PrmX6/9RlD/gfn9wfX4f8AQPi//Cav/wDIL8/uOa8Hf8F2/wBlD4geHrLxX4M+EP7Zfibw7qL3UdlrOhfss/FLVtMunsruaxu0gv7DSLi1ma2u7ea3nEcreVNHJG+HUqt1Mqq0puFTE4GE1a8ZYujFpNJrRtvVNNXX3WZEMzpVI88KOKlFtpSjh6zTa0dnGDWj31++50//AA+o/Z5/6IF+3F/4iN8Xv/lFUf2dL/oMy/8A8LaBf1+H/QPi/wDwmr//ACsP+H1H7PP/AEQL9uL/AMRG+L3/AMoqP7Ol/wBBmX/+FtAPr8P+gfF/+E1f/wCVh/w+o/Z5/wCiBftxf+IjfF7/AOUVH9nS/wCgzL//AAtoB9fh/wBA+L/8Jq//AMrD/h9R+zz/ANEC/bi/8RG+L3/yio/s6X/QZl//AIW0A+vw/wCgfF/+E1f/AOVh/wAPqP2ef+iBftxf+IjfF7/5RUf2dL/oMy//AMLaAfX4f9A+L/8ACav/APKw/wCH1H7PP/RAv24v/ERvi9/8oqP7Ol/0GZf/AOFtAPr8P+gfF/8AhNX/APlYf8PqP2ef+iBftxf+IjfF7/5RUf2dL/oMy/8A8LaAfX4f9A+L/wDCav8A/Kw/4fUfs8/9EC/bi/8AERvi9/8AKKj+zpf9BmX/APhbQD6/D/oHxf8A4TV//lYf8PqP2ef+iBftxf8AiI3xe/8AlFR/Z0v+gzL/APwtoB9fh/0D4v8A8Jq//wArD/h9R+zz/wBEC/bi/wDERvi9/wDKKj+zpf8AQZl//hbQD6/D/oHxf/hNX/8AlYf8PqP2ef8AogX7cX/iI3xe/wDlFR/Z0v8AoMy//wALaAfX4f8AQPi//Cav/wDKw/4fUfs8/wDRAv24v/ERvi9/8oqP7Ol/0GZf/wCFtAPr8P8AoHxf/hNX/wDlZ9Ifsif8FFPgd+2f44+KPw5+Gnh34v8AhTxj8H9K8I614z0H4t/DLxH8NNTtdO8b/wBpnw9cW1h4lt7S8uEvF0e9kVltxH5aK6yMGrHE4KphqdKrKdGpTrSnGE6NSNWLdO3MuaN1dXX/AALpGuHxdPETqU4xqwnSUXKNWnOm7T+FrnjHe3/DWfN97VxnUFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/S/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gz9o5mX/gsJ+xgVYqf+GVf2gBlSQf+Rr8L+hH8/wA8Gt8T/wAiPF/9hdD/ANJZxx/5GtF9sHWf/k39f0z9N/Nl/wCesn/fbf8AxyvkD3A82X/nrJ/323/xygA82X/nrJ/323/xygDOl13TreRoZ9asYJUOHim1K3ikQ+jxvMGU+xH55NUoyevLJ+aT/QV13X3kf/CR6R/0H9M/8G1p/wDH6OSX8kvukF49194f8JHpH/Qf0z/wbWn/AMfo5JfyS+6QXj3X3h/wkekf9B/TP/Btaf8Ax+jkl/JL7pBePdfeH/CR6R/0H9M/8G1p/wDH6OSX8kvukHNHuvv/AK/r5B/wkekf9B/TP/Btaf8Ax+jkl/JL7pBePdfeH/CR6R/0H9M/8G1p/wDH6OSX8kvukF49194f8JHpH/Qf0z/wbWn/AMfo5JfyS+6QXj3X3l221CK8QyWd/Fdxq2xpLa6S4QNgHaXilKhgCDtJzg54yKTTW6a9br8/T+rod09v8/6/rsflh/wWckkP7Dl9mRyP+Ghf2VjyzdR8evBBB+83IPTj88fL7fD3/IyX/YLjf/Uaqedmv+5S7+3wv/p+H9f8MfqlBLL5Fv8AvZP9RD/G3/PJf9sfy/KvDPRJfNl/56yf99t/8coAPNl/56yf99t/8coAhlvVg2ie8SEvnb51ysW7HXbvf5sd8HjIzjNOzeyb9Ff8EF1/Wn9f13I/7Tt/+glb/wDgdD/8cotL+Sf/AILkK8e6+8P7Tt/+glb/APgdD/8AHKLS/kn/AOC5BePdfeH9p2//AEErf/wOh/8AjlFpfyT/APBcgvHuvvE/tS2BAOp2wJ6D7dDk/T957jt+VFpfyy9OR3+7f+vJhdd19/8AXQX+07f/AKCVv/4HQ/8Axyi0v5J/+C5BePdfeH9p2/8A0Erf/wADof8A45RaX8k//BcgvHuvvD+07f8A6CVv/wCB0P8A8cotL+Sf/guQXj3X3jk1GGRxHHfwySNnaiXkbu2Ou1Fk3NgcnA4HJK/xFn1Ul6xa/P8Ar7kO6e3+f9f12IdUll/svVf3sn/IL1H+Nv8Anyn/ANs/y/KnD44/4o/mH/Dff/mj8vP+CLckg/4J1fBICR1A1j4s8BiBz8W/Gvoy/wCfTkt7XEf/ACN8T/hof+mKX9f8Mebk7by6hfpOsl6e0Z+qPmy/89ZP++2/+OV4Z6QebL/z1k/77b/45QAhmkAJMzgDqS7AD6necf56YzQAz7X/ANPP/kb/AO2U7S7P7gD7X/08/wDkb/7ZRaXZ/cAfa/8Ap5/8jf8A2yi0uz+4A+1/9PP/AJH/APsz/L86LS7P7gD7X/08/wDkb/7ZRaXZ/cAfa/8Ap5/8jf8A2yi0uz+4A+1/9PP/AJG/+2UWl2f3AH2v/p5/8j//AGZ/l+dFpdn9wEgmlPImkIPIIduf/IlID8zP2VSW/wCCu/8AwUhLEk/8KJ/Yp5Jyf+QJ8TfXP+fTpX2OH/5EOX/9hOP/APS6B4f/ADN8f/2D4L/0if3n7H1zHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/0/7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH6aV8ge4FADfMTON6ZzjG9adn2dvQdn2f3H4C/s9/sL/sv/ALW/7WH/AAUk8T/tB+BtS8e6z4T/AGpR4c8OXEvxC+IGhW+k6I3gTwzqDafZ2Ph7xPpVjHD9tubibIt2bdIRvCgLX6HhsTVoZZlcaclCMsM3K1ODk5Kb1bcZN6aeXn9n5v6rQr4zMHUi5NYjlT55xslCDtZNJXd/s9Ha1ny/av8Aw5i/4Jt/9EIuf/DufF7/AObqr+v4j/n+/wDwVT/+Vmv9nYT+SX/g2oH/AA5i/wCCbf8A0Qi5/wDDufF7/wCbqj6/iP8An+//AAVT/wDlYf2dhP5Jf+Dago/4Ixf8E28j/iw9yeRx/wALc+L3Pt/yPXej6/iP+f7/APBVP/5Bfn9wf2dhP5Jf+Dah+dn7FP8AwTC/Yk+JXxv/AOCgPhjxx8LdV13QfhN+09ceCPh3YXPxU+KcUXhvwqng/QNQXSbR7fxnFLNAL26uJ/MuXnmLysDIBha7MXjK8KeDanGPPh+abjSpXlLmfvNcvlbRLz/vcGEweHnWx0JRk4wxHLC9Sd4rlTsne/V9Pu3P0S/4cxf8E2/+iEXP/h3Pi9/83Vcf1/Ef8/3/AOCqf/ys7/7Own8kv/BtQP8AhzF/wTb/AOiEXP8A4dz4vf8AzdUfX8R/z/f/AIKp/wDysP7Own8kv/BtQkX/AIIvf8E3zgj4CXjDPb4s/F8g47Z/4TrFNY3Evas//BVL9Y6/dH11Qf2dhP5Jf+Dan/A/P7jxv/gkz8P/AAx8JfEf/BRf4VeBbbUNN8B/D39uvxr4a8G6Hf65rWvjQtCtvh78PpYNNtL7Xr/UtQNtHLNNIqS3T4eRjySWrwOKJOdTLKkrc1TLqcptRjHml7Wrq+VJXfXva7ttHbKIxpxxtON1GGNqKKbbsuSns25O3W1/v+z2P/BZv/kx2/8A+zhP2Vv/AFfXgmuLh7/kZL/sFxv/AKjVTfNf9yl/1/wv/p+J+qMH+og/64Q/+ilrwz0SWgAoD+v6/r8j8Y/+Ch/we8IftBft0f8ABN34NfEa68Xv8PfFlh+1He+ItE8J+OPFPgaTVbjw94P8I6hpD3d/4U1TSr2UWd0zSRI85X5mXG1mDfX8MydPDZpUjGDnH6pyudOFSylOonpOMltq9uj3ScfEzSlGticBTm5qDliLqE5wvammtY2vb+r7Htv/AA5i/YQ/6Fr4z/8AiSvxx/8Am2r2vrtX/n3Q/wDCWh/8of5/eZ/2bhu9f/wpr/8Aya/L7g/4cxfsIf8AQtfGf/xJX44//NtR9dq/yUP/AAlof/KA/s3Dd6//AIU1/wD5YH/DmL9hD/oWvjP/AOJK/HH/AObaj67V/kof+EtD/wCUB/ZuG71//Cmv/wDLD89P2iP+CZP7Kvgv9vP9gP4Q+HLf4y2PgH4w6P8AtKXXxA0Zv2hfjJcNrM3gXwl4Z1LwyUvZ/GD3dl9hvL66lItJoRP5m2fzVVFXro4qpLCYybhh3KnLDqFsNQXL7SbU+ZeySeiTV1tte0jhr4KjHGYKnGVfkqrEc6+sVvsQjKL+NvRt7NW630P0L/4cxfsIf9C18Z//ABJX44//ADbVyfXav/Puh/4S0P8A5Q/z+87v7Nw3ev8A+FNf/wCTX5fcH/DmL9hD/oWvjP8A+JK/HH/5tqPrtX+Sh/4S0P8A5QH9m4bvX/8ACmv/APLA/wCHMP7CB/5lr4z/APiSnxxP8vG3v/nBo+u1f5KH/hLh/wBaH6feH9m4bvX/APCmv/8ALLnyD4h/Y6+C/wCyF/wU7/4J5WnwOPxJ0Ww+Ifhj9p9vF+m+JPi58RfHOmau3h3wdoDaO0mn+LfEGq2kbWT6jdvG0cStvk3E5RCvPmVaVbJsw540fdnhXFwo0qclecrq8KcW7uKfTtrYzpYeGGzPA+ylVtOOI5lKrUqJ8sItfG5bev33fL+7+qf8grVf+wXqX/pFPXwEPjj/AIo/mfRn5e/8EXP+UdfwT/7DHxZ/9W341r2uI/8Akb4n/DQ/9MUjzMn/AORdR/x1v/TjP1Qrwz0woA+Hv+Cmeta34a/4J4/tq+IPDuq6loWvaL+zZ8VNR0fWtIvLjTdU0vULXw1dyW19p9/aSRXNnd28gDw3FvLHLG4DI4Ir0snjGeaZfGcVOLxdG8JJOMlzapp2TTV7r87WOPMG1gcW4txksPVcZRbUk+R2aas009tfuPlz4H/8Ek/2afGPwW+EPi7XfH/7Wlzrfin4YeAfEesXEf7VXxjhjn1XXPCulanqE0cMfiJY4Y5Lu6mdIkGyNCqLhVAr7meKtOpH6vhLRq1IL/ZKW0Jyivsy1tHXXfvry+TRwNKVKnKVXFNyhFv/AGmtu0n0mt22/wDPc9R/4c3/ALKn/Q8/tb/+JXfGb/5pKn62/wDoHwn/AISUf/lZp9Qo/wDPzFf+FNf/AOWB/wAOcP2VB18c/tb/APiV/wAZh/7sn+fxo+tv/oHwn/hJR/8AlYfUKP8Az8xX/hTX/wDlh8jft9f8EwfgJ8EP2J/2p/jB8PviN+1hpvjn4a/BHx14x8J6hdftSfGC+trLXdF0qS6sLm4srjxE8F3FFKoZ4JVKSDg1thsQqmKwtKWHwbhVr06c08JSV4yeqT5FZ6fd23jy43CU6WExFSFXFKcKU5RbxFZpNLs5tP0a++7Pcvg5/wAEj/2ZvFnwi+FfinWfH37Wk+seJfhv4H1/VZ4/2q/jJFHNqWs+GNL1G+ljiTxGqRJJdXErpGo2xqQi4C/NnPFWnUX1fCWjVqRVsJR2jOUUvgtolra2t/Ny2pYGk6dNurim3BNv6zX1bV29Jrdu/X13PR/+HN/7Kn/Q8/tb/wDiV3xm/wDmkqfrb/6B8J/4SUf/AJWafUKP/PzFf+FNf/5YH/DnD9lQdfHP7W//AIlf8Zh/7sn+fxo+tv8A6B8J/wCElH/5W/67bh9Qo/8APzFf+FNf/wCWHx9/wUD/AOCYvwF+B37EH7VXxi+HnxI/av0zx18NPgl418Y+EtQuv2pfjBf21nruj6f59jcXFjceIzBdxRyjc0EvyP0OcYbfDYj2mJw9OWHwbjUrRhL/AGSgnyu+zV7PTez+V248uNwdOlha9SFXFKcKcnFvEVnZ7bSqW6+d9tL3P2c+Ak9xdfAz4MXV3c3F5d3Pwo+HdxdXd3M9xdXVzP4Q0eWe5ubiQtJPcTyu8s00jNJLIzSOSzE1+bYq31nEWSivb1bJaJLnlolrZL+rbH0dFt0aLbbfsqerd2/cW7er+f6nxP8Asqf8pdv+CkP/AGQn9in/ANMnxNr6rD/8iHL/APsJx/8A6XQPI/5m+P8A+wfBf+kVD9kK5jsCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP/9T+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR+mhIAyTgDqTwK+QPcGeZGQR5ic5/jX8fXn/Ix0p2fZ/cHe2/9en5/cfzs/wDBPv8AYG+Ff7WnwZ8Y/GP4x/F39qu88a6l8e/jnokreHf2nvit4X0e30vw78Rtd0nSLOx0XTNejsrKG1sbaGFEgjRMJwBiv0ytVhR9jCnh8HyvDUJO+Eozk26cW23y8zbber1fdWvL5bCYaOIjUqVK2JcnWq6RxFSKSVSSSSTtokukdLaaWj9laN/wRF/Yy8OXuvan4f8AGP7Vuiaj4p1H+2PE19pX7VnxbsLzxBq3kxW39p6zc22uxy6lf/Z4YoPtV2ZZvJijjD7EUUf2jiOWMOXDqMFaKWFhaK3slyWSv0S77m6yrDJykpYlObvJ/WKl2+795a7a317L7PQf8Ocv2W/+iqftk/8AiYHxn/8AmhH8/wAqX9o1/wCXD/8AhLT/APlY/wCzMP8Az4n/AMKKn/ywVf8Agjj+y0SP+Lq/tk4Pf/hsD4z/AJ8+Ix0/3ufbpSeY4i1+XDbf9A1NJ/PkW/8AV9g/szD/APPzE/8AhRU/+WHwH/wTd/4J1fCP9ov9nnVfiB8U/jN+17qvie0+NPxr8GQ3Nj+1d8X9KhXQfBfxE13w7oEDWtt4h8tprfTLG3iluD89xIrSyZdmZuvG42pSrqFOGHSdKlNr6vTesqcW9OWVryb66bK/2eLA4GlXoynUq4mUlVqx/jzS5Y1JRjb3l0XXXrpe0ftvRv8AgiL+xn4dvde1LQPGP7Vuiaj4p1I6z4mvtK/as+Ldhd+INXMKQHVNZuLbXY5dSvzBFFCbu7Ms3lRom/aqiud5niZKKaoNRVo3wsNFe9l7jS1beiXnc645ThYuTjLEJyfNK1epq+799a/N/I6D/hzl+y3/ANFU/bJ/8TA+M/8A80I/n+VT/aNf+XD/APhLT/8AlZX9mYf+fE/+FFT/AOWC/wDDm/8AZe2lh8Uv2zCNpII/a++NJ7cEf8VFj0PU/jR/aNfV8uGdtbfVqa+/Rb+a+8P7Mw/8+J/8KKn/AMsLn/BF281u6/YP8IRa/wCKPFXjG90r4pfHnQYNd8a+ItU8VeI59M0D4weMNH0m3vtc1m4udQvfsenWVtbRNPMxWOMKMAALWZW+uSajGHNThJqKSV3CDbsrL7kvno5PLL/VEnKUuWpVipTblJpVJWu2227ab/dc57/gnD/yWb/gqX/2kH8ef+q6+HNfMcS75T/2LKf/AKdqnVlW+P8A+w6p/wCkQGf8Fm/+THb/AP7OE/ZW/wDV9eCa5OHv+Rkv+wXG/wDqNVNc1/3KX/X/AAv/AKfifqjB/qIP+uEP/opa8M9Elo/r+v6/ID8Rf2g/gvd/tQ/8FXoPgp4l+Nfx/wDhx8O/D37DmhfEi20P4MfFTXPh3DeeLbn4v+IvD82o6kmmGSC8kbTI0gzJAJf3UeZSiLG322RulTyidZ4bD1aksfOnz1qMaklCNCE1FOWtr3ejiuiV3KR4GNjOvmkaLr4ijTWBjO1Go4Xl7aau9+nKk7S08rcnqGp/8ETv2eta8S+GPGer/tC/ts6l4t8FJq8fhDxJe/tK+J59Z8NR6/BDa62mjX0lm81guq29vBDfCBl+0xwxrJwqivWhj5UlKNLDYSmp2U+XC6S5Xdcyuk7Nu19vLeOc8rhUcJTxOLlKF+SUq7bjzb2birX0+y/VHWf8Oivhf/0df+3t/wCJS+Lv/kSn/aNX/nzhP/CSP/ywP7Mh/wBBOL/8Hf8A3MP+HRXwv/6Ov/b2x6/8NS+Lv/kSj+0av/PnCf8AhJH/AOT/AM/xtE/syH/QTi//AAf/APc/6+Z8GwfsCaW//BS3Vf2Zm/ax/bj/AOFaWv7H2ifGKKMftL+L/wC2f+ExvvidqvhaeRtS2EHT/wCy7WIJZ+Qn77dL5o3bK6/rj+o/WPYYR1PrM6V/q8bcsaSl8PMtbt3u32XU5fqUfrvsPrGL9n9W9o/3zvzc/Lf4Xp00VuvK7NS+yNW/4Io/s+674m8L+NNa/aH/AG29U8W+CU1eLwf4kvv2lvE9xrPhmPX4IbbXI9Fv5LIz2Catb28EN+sDAXMcMayZCqK5lmdZRlD2OF5ZtOSWFSUuX4eZczTs/Xe3X3eh5TSk4ydfFOUObkl7bWPMrSt7itzLR6O9raWR1X/Dor4X/wDR1/7e3/iUvi7/AORKn+0av/PnCf8AhJH/AOWFf2ZD/oJxf/g7/wC5i/8ADon4Yf8AR137e5/7ul8Xf/Inej+0Kv8Az5wn/hJFf+3S/L77e6f2ZD/oJxf/AIO/+5njn7Lfwfvv2Z/+CrHxA+B2gfGr4+/Er4eX37EXhL4kLo/xo+KeufEVbDxZqHxb8QaFdahpn9p7IbMvp2l20GY4RJt8wb9rlavEVnWwMJyp0YTWJnTbpU1C8fYqSvbs3/V2Rh6Tw+PnSjVrVIPDqVqs3P3ufdbLp289Nj1j9rz/AJSg/wDBL7/sV/2uf/UM8J15eO/5E+Y/4sJ/6cqHVP8A5GWX/wCHFf8ApED9OtU/5BWq/wDYL1L/ANIp6+Fh8cf8UfzPcPy9/wCCLn/KOv4J/wDYY+LP/q2/Gte1xH/yN8T/AIaH/pikeZk//Iuo/wCOt/6cZ+qGCen+P+f8+leGemfl3/wWF8SeOfC/7Fl3cfD7x94x+GXiLXPj1+zT4Lfxh4D1aTQvFGn6J44+NHhPwr4gi03U40ka3e60nVbmEkxyISV8yN1Gyve4bp0auaQjXpQrU1QxU3TqLmi5QoylFtPe0kn1/G8fKzmpUp4GUqc505Ovhoc0HaVp1owaT7uMn06bxt73O+Mv+COPhL4i+EfEXgTxz+2z+3j4p8HeL9GvvD/ijw3rHxqsrnStc0TU4GttQ0zUbZvDW2e0vIHaKeE4V0YjocN9TTxFGnKFSnl+BhODjOEo0JXhJapxd94vZ3+fU455e6kHCeNxsoSjyyjKqmpLqnpfXrp8uhs6R/wSS03QNJ0vQtE/bt/b80zRtE0+y0nSdNtPjhZxWun6bp1tFaWNlbRjwwRHBbW0MUMSAnaiAcYwuzzC7beDwbbbbbw0rtvu+dX+779BLLuVKMcZjUkrJKtFJJdP4MvzZo/8OqG/6P7/AOCgn/h9LT/5l6Pr6/6AsF/4TS/+WD/s9/8AQbjf/B0f/lB8L/8ABRL9izxz+zJ+zrYfE74fft6/t3XHiG4+OX7Pvw+kj1r41x3Vl/YnxJ+K/hvwdr7iK38P20gu49K1S5aykMhSK5EbvFKoKN04TFU6+IVKpgsFyujiJ6UHFqVOlKUd5O6vurrz3RyY3CTo0VOOMxjbq0oa1ltUmoS2pQd7N9fu3PsLxp/wR28LfEXwn4i8B+Ov23f28/FPg7xdpF5oHibw5rHxss7rS9b0bUIzDe6bqFs3hgLNaXURMc0THDISCTkmuenmTi4VIYTBwlG04uNCV4tar3ufWz62V/K50SyyNSDhPF4yUJL3ouqrNPe69n11v70t9tbGvpf/AASVsNE0zTtF0j9u/wDb907SdIsLTS9M0+1+ONnHa2On2FvHa2dpbRjwviOC2t4o4YkBYKiAA8UnmF228Hg25NybeGd227tt86u/O33lRy7lSisZjUkrJe2X60pP/wAmfy2L/wDw6ob/AKP7/wCCgn/h9LT/AOZej6+v+gLBf+Ez/WoP+z3/ANBuN/8AB0f/AJQfE/7fX7JPjv8AY9+CXhH43/Dv9uP9trxB4i039pD9mXwnJonjX4xpq3hnVNC8dfGjwl4Y8Q2OqWFtoVjLcQ3Wk39zAYxcIjbyJNyEo/Rhq8MTVdCphMGoyoYiXNCjyyjKnSbi0+d9f6e0uTGYeeGpRrQxeLlJV6EbTqqUWp1IxaaVKPST6/Jn6b/8FYP+UZ37dH/ZtXxJ/wDTSa4cC74vBPvXpv8A8lZ3Zh/uGJ/68v8Arr+f3n0B+z9/yQb4Jf8AZIvht/6hui1+f4r/AHnEf9f63/pyR7ND+BR/69U//SEfFn7Kn/KXb/gpD/2Qn9in/wBMnxNr6rD/APIhy/8A7Ccf/wCl0DyP+Zvj/wDsHwX/AKRUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//9X+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9j/tL3t5pv7OXx81HTru5sNQ0/wCDPxNvrC+s5nt7uzvLTwbrM9tdWtxEyyQXFvNGksMsbK8ciqysCoK/M4NKWLwsZJOLxFJNPVNc8bp76NaP9Nz1sRpQrNbqlUa8moOz6bO3X7j8iv2H/wDgmN8Gfjd+yL+zx8XPHnxl/a/u/GfxD+FvhbxX4mubD9p/4l6dZT6xq9hHdXklrYw6g0VrC0zsY4YzsjXCgAAV+i4mtGlia9KGFwSjTqSjG+Fpt2W13pr8vuPnsHhI1cNRqTrYpznCMpP6xUs21fRc6t6a+u59E+Fv+CJP7I3gfTZNG8G+Pf2svC2ky317qcmmaD+038R9LsX1HUriS71G+e2tLuOJru+upZbm7nK+ZPNI8kjM7E0PMcRK14YZ2SX8CL0SslvHRJJLfytaxtHLMNBWhLERV29K81dt3b3erbf+b0Oj/wCHPX7OP/RYP2zP/ErPij/8nUvr9f8Akw3/AITx/wDlhX9n0f58T/4UVDyb49/8EovgP4H+Bnxl8a6B8ZP2x4dd8IfCv4geJ9Fln/am+J9xBFq2g+FNW1TTpJoH1BVmiS7tYWkiZgJEBQ5BxWlHHVpVaUZU8M06kE17CK0cknq5Ss7be6/la5lXwNKNGrJVMSnGnOS/f1N1F20ur23/AMtHHzj9in/gmH8GfjF+yb+z98UvG3xo/bDuvF3jz4X+FvEviK5sv2ofibY2k+q6np8U93Jb2cWoNHbxtKzFYkO1RwAKvFY2pDEVoRp4dRjNpJ0IvS7XddtdHv6GeEwVOphqNSdTEuU4KTtXmld72V3bVX/z3l774X/4IlfsjeCNNfRvB3j39rLwvpMt9fapJpmg/tN/EfTLF9S1S5kvdSvmtrS7jiN3f3k0t1dzlfMuJ5XlkZnYmspZjiZu8o4eT2u6EW7JWSveOyslvZKytqjeGWYamrQliIq97KvNK736v8l87nR/8Oev2cf+iwftmf8AiVnxR/8Ak6p+v1/5MN/4Tx/+WFf2fR/nxP8A4UVDx/8AaF/4JSfAnwJ8A/jd438PfGb9seDX/B3wl+IninQ55/2pvifcQw6voHhLVtU06Wa3fUFSeKO7toWkhY7ZEBQ4DE1pSxtaVWnGVPDWlUgmvYR1Tkk/tvpttrrfQyrYClGjVlGpiU4U6kk/bz3UG1fp96l6aI+7P+Cdmr6vr/7Cf7Kmta9quo65rWp/A3wJeanrGr3k+oanqV5Nodu013f31y8lxdXUzZeaeV2kkclmYkk1x4tJYrFxSso1aiSWitzS6dPlb9ZdWCblhMO27t0o3b66Hzn/AMEXP+TGNC/7LV+0j/6vPx3XRmP+9/8AcKn/AOkQMcs/3b/uNW/9OMwv+CcP/JZv+Cpf/aQfx5/6rr4c18zxLvlP/Ysp/wDp2qdWVb4//sOqf+kQGf8ABZv/AJMdv/8As4T9lb/1fXgmuTh7/kZL/sFxv/qNVNc1/wByl/1/wv8A6fifqjB/qIP+uEP/AKKWvDPRPwc8H/syXH7YP7fn/BRfTvHf7Rv7UvgfQPhF49+DWi+BvC3wm+Mut+CPDWl2PiP4TaPrerKulWsVxbh59RLz7oliG6Rywdm31+g4B0aOU5ZNYTCTnVVdTnVoRnOXLWkoXl15U93r5vaPzcqVTEZhj4vE4mEaU6UYQp1XCKUqUZPT3ktX0S79T3xP+CJ/wIj8cP8AEtP2kv23F+IMnhuPwdJ4yH7ROujxC3hWG/k1SLw+dT+wi4/sqPUppb5LPd5QuZHlCqzE12xx0oQ9nDD4OFPm5+SNCKjz2tzWsrtrTW+nUJZXTlP2ssRi3U5PZ8/t/e5Lt8t+VaX1/wArJx6//h0d8P8A/o739vn/AMSZ8S//ACJR9en/ANA+D/8ACamH9l0/+gnGf+FEg/4dHfD/AP6O9/b5/wDEmfEv/wAiUfXp/wDQPg//AAmph/ZdP/oJxn/hRI+Cv2a/2EE+J37XH7fnwf8AEv7X/wC3IfCH7Pfj34P+Hvh+tl+0X4lt9QXT/GPwm0bxdrH9rXXkyC+mOr3sxtnVIfKt8RkNjc3TWxfJQwc1hsGpVoVZTfsItc0akopK+ysn36eseWjglUxGLpSxOL5aNSEaf7+V0nTjJ3fXV9eiPskf8EUvgWvjeT4lD9pX9t4fECXw5H4Qk8Yj9orXv+EhfwtDfPqcPh9tS+w/aDpUeoyy3qWe7yluZGlHzsTWH9o1eXk9jheTm5uX2EOXmejdtrtabbaao6f7Jpc3P9YxfNy8vN7d35e17bf1e+p1n/Do74f/APR3v7fP/iTPiX/5Eqfr0/8AoHwf/hNTH/ZdP/oJxn/hRIP+HR3w/wD+jvf2+f8AxJnxL/8AIlH16f8A0D4P/wAJqYf2XT/6CcZ/4USOK/4Jj+FfEHwu/aa/4KTfBK6+LPxe+KnhD4TfFr4Q6P4HufjB441Hx1ruj6frfwl0fxFqVvBqWobTFFcapqNxK0cUSJgRg5K7nMbJVMPgavsqVKdSFRzVKHLFtVuVfcla+/3iwEXTxGOpe0q1IwqU+X2s3NxvTTaTaWl3/wABaHcaZ/ym18Y/9o5/A3/q8/GVZz/5F8f+wyf/AKjo1X/Izl/2Cr/0so/tef8AKUH/AIJff9iv+1z/AOoZ4Trhx3/InzH/ABYT/wBOVDSf/Iyy/wDw4r/0iB+nWqf8grVf+wXqX/pFPXwsPjj/AIo/me4fl7/wRc/5R1/BP/sMfFn/ANW341r2uI/+Rvif8ND/ANMUjzMn/wCRdR/x1v8A04zE/wCCn6+P/E3xE/4J3fBjwZ8Zfij8E9G+Ov7U/iLwJ4/8R/CPxBH4b8VX/hux+D/i3xPb6fHqM1pexCJNW0i0m2SWzr9/GWOV6eG6VGbzOpWoUcQ6GCjUpxrQ54xk6tm7Xi9Vpp66aKWeayqJ4KnTq1KKq4lxm6TSk4qnJ21813++6M/4g/8ABF3wj8VvDy+E/iP+3F+3f4y8NJrWgeI00XXPi7ot3YrrvhbVrXXfDuqiI+E0AvNH1ixtNRsZefKureKQA7cV9JRr08NP2tDB4KnUtKKnGhZpSVpJfvOquvn5nNWy9V4clXFYqceaMrOpdc0GpRdrdJJNaS20trzd4P8AglZqvb/goj/wUJA7D/hc+i8f+WpVfW1/0CYD54eT/HnV/wCt7XD6h/1F4z/wd/8AaP8AP7w/4dWar/0kR/4KE/8Ah59F/wDmUo+tr/oEwH/hNL/5YH1D/qLxn/g7/wC5nw5+1d+xv8Tvgp8a/wBhD4eeE/8AgoP+3dPon7Sf7Q+vfC3x3Lqnxd0ye8tfD2mfC3xV4yt5dEli8NxJa37aro1pHJNNFOn2VpUCBnV13o16c6WNnLBYJyw+HhVptUXFc0qqg+ZczukvXtpqzjxOHqUq2DhDF4rlr1pU53q3dvZykre5prFfj8V7R+rPiD/wRj8L/Ffw/H4U+JH7c37ePjPw3Freg+JItF134vaJd2Ka94W1W31vw7qoiPhMAXmj6taW2oWMuMw3MEcgBK4rOGPlTlz08NgoStKN40GnyyVpRvzq6krp6We7tZHTPLIVY8tTE4qSvGVpVb+9F3TXuqzTV+/a17x7cf8ABKzVf+kiP/BQn/w8+i//ADJj+X5VH1tf9AmB+eHbf3qa/rvuX9Q/6i8Z/wCDv/tH+f3h/wAOrNV/6SI/8FCf/Dz6L/8AMpR9bX/QJgP/AAml/wDLA+of9ReM/wDB3/3M+Y/iX8APiX+xz+2B/wAE4E8Nftn/ALW/xR8O/G39onxn4B+IHgv4ufEex8SeFtX8P6P8HfF/iuzik0+z0XTWMi6vp9pKxkldSsQAUGtqdSnXoY5SwuFhKjh41ac6VLkkpOqoveT6efXVP7XNUpTw2KwKjicTKNWtOM41KnNFqNKUlpyrr3T79D6Y/wCC1n/JlWi/9nZ/sa/+tE+Bazy7/fF/2DYv/wBMs3zX/dV/2EYb/wBPQPZv+CsP/KM79uj/ALNq+JP/AKaTWGA/3rA/9fqf/pLNMw/3DEf9eWfQH7P3/JBvgl/2SL4bf+obotfAYr/ecR/1/rf+nJHs0P4FH/r1T/8ASEfFn7Kn/KXb/gpD/wBkJ/Yp/wDTJ8Ta+qw//Ihy/wD7Ccf/AOl0DyP+Zvj/APsHwX/pFQ/ZCuY7AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD//W/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfX37Un/Js37Q/wD2Q/4q/wDqD63XzWB/3zC/9hFH/wBLietiP93r/wDXmr/6Qzy//gmF/wAo+P2QP+yE+A//AE0RV99jP99xf/X6X5s8jLv9yw//AF6h/wCkxPpX476n8QtD+DnxI174VX3hnTvH+geEdb17w5d+MbG91Pw2l3otjNqkkeqWOnXFreTxXFtazQIIbiJkmkjkJKoy1jDkc4qpzcjlFS5Lc1m7aXTV9eq1201Omq5qnNwtzKLa5rtaK/S3bv8AdqeV/sO/Gzxb+0d+yd8DPjf47tNHsPF/xH8C6Z4i8Q2nh+K4g0WDU7kMtyumw3Us1xHab0JiSaV5FU4Z3PK1Xpxo16tKDbjGWnNa/wA7adOlkul9zPC1ZVqFOrNJSnFSdttVfTt87/pHsf2q/wDk2D9oz/shfxZ/9QPXqdD+PR/6+0//AEtDxX+71/8Ar1P/ANJZ45/wTW/5MJ/ZM/7Ih4G/9NMNXjP98xP/AF8l/wClSM8B/ueG/wCvUTvP2ovGP7RWgaR4B8Mfsz+C9E17xx8QfGcfh7VfGvi+C7u/A/wo8LwWFxf6l4y8S6fp89tf6sWaKHTdJ0y1uITc39wDNLFCjM0Uo0ZObrycYRjdRjJKdSb0UI3uu7bemltLpl15VkoRoRTnOVnKXwQjbWUldN+ST9bnl37HXx8+MPxA8e/tI/Ar45/8INrnj/8AZw8aeHPDt14/+GtlqWl+EvGGneLPDFj4n09/7G1W7v7nRNd0uK8+x6vppvrpY5VWRXUPtWq1KnCGHq0eZU8RGcuSbTlBxk1utJJ2Vno/uSlnhq1Wc69KryuVCcY88LqM+aHNs9mr2krv5by9w/a3/wCTVf2lv+yB/F3/ANQLXqmh/Ho/9faf/paNsR/u9f8A681f/SGeQ/8ABNb/AJMB/ZG/7IL4A/8ATFb08b/vmN/6/VP/AEqRlgP9zw3/AF6iflx/wSz/AOChX7F/wN/ZRi+GnxZ/aG+H/gXx1oHxq/aH/tnwzrl/cQalp4vvjT41vbQzxpayKPPtZ4pkCv8AccE4ztXvx+ExNTEqcKM5RdKl7yVk7wh37W8k+m15cOAxuFpUHCpWjGXtq109bfvJdV+vp0Z71/wSd+Ivgn4s+Mv+ClPxF+HPiPT/ABb4J8V/t7+N9V8O+I9JkaXTtW0+b4dfDsR3dpIyRs8TsrAEopypGBj5vlOKac6dTLITXLKGXU4yi90/a1f621/u2sehk9SFRY6cJc0ZY2o011ThTfl36/je52P/AAWb/wCTHb//ALOE/ZW/9X14Jrh4e/5GS/7Bcb/6jVTozX/cpf8AX/C/+n4n6owf6iD/AK4Q/wDopa8M9E/L39h3/lIJ/wAFZP8Asqf7Pv8A6pDRq+9w3/Inyj0xH/p88Gj/AMjHM/8Ar5Q/9MQP1vHv074qzuPhD9m/9or4x/ED9p/9rz9nz4seHfAGmwfAO9+Gmo+Cdb8D3mtXMuu+FPidoup69pQ8RR6ukaW+t2FlaW8V6lgrWhuHlETlFBbetSpwoYetTlNurzRqKdtJQkoy5bWXK3tpfq7bHJRrVZ18RSqRglTlHkcW9YzUmua63Sj3WvfQ+76wOs/Jn9ib/lIX/wAFb/8AsrX7Ov8A6z/4brsxP+7Zf/17rf8Ap6qedhP98zD/AK+0/wD0zA/SX4s/EjQfg78LviJ8WPFBl/4Rz4beCvEvjfW1twDcS6d4a0m61W4t7ZWIDXNytt9ntweDNLGDgEleanB1KkKcfiqTjCPrJ2Xba93rt2sd1WpGlTnUlflhFydt7JX8/wAvvPzc/Zs/bC/aZ+JvxP8AhrpvjXTf2Zda8K/E/T7zVte+H3wp+JTap8Y/2f8AT7nRW13w1dfELTNSu0t/EkF3E0Gka4dBtIJtH1a4i/cz2weRemvQoQjUcHXU4S5VUqUnGlVaahLkkr7O8o3bUl1Xu8/BQxNepUgpewlGpduFOpepRVrx57tc11a/LFWcrWloz9ZK41sv6/z/AD+89I/Jr9h3/k/v/grf/wBlt+Bf/qifDFdmJ/3PLv8Ar3U/9Ps83Cf77mP/AF8o/wDpqJ5D8Uf2gvgn+zz/AMFnNc8RfHD4oeDPhZoWuf8ABPjwVpOj6r411u00Oy1LU4fjZ4yupbGznvHjSa5jt/3zxIWYRkNjH3rjRq1svtSpzqOOLm2oR5mk6EUm7dLvz7dbxipXo0MybrVIUlLDJJzdl8fo/wCujscr8V/2p/2dP2h/+Co//BNe3+B3xm+H3xTn8O+Fv2rTrsXgrxFY64+kjUPBnhn7Cb5bN5Dbi7+y3HkeZt3+RJj7u5eHMaFelkuYyrUalJOeFS5043tOWqutfitv0emqZcMRQr5ngVRqwqOMcS3yyTt7kfPyfTXvokftvqn/ACCtV/7Bepf+kU9fAQ+OP+KP5n0R+Xv/AARc/wCUdfwT/wCwx8Wf/Vt+Na9riP8A5G+J/wAND/0xSPMyf/kXUf8AHW/9OMZ/wUF/5Om/4JE/9nr+Lf8A1n/4g12cNfDnP/Yvj/6dMs1/iZf/ANhUv/TNQ/XuvYOg/Lv4kftj/tL6x8Tv2k/DH7MPwJ8AfELwd+yJPp+lfFfWPH/xCu/CGueL/Fsngix+IuseEPhxp1lo+o2xutJ8L6lYf8TbXrq10+71a6WyjCpHLMvVGhQUMPLEVp05Ypc1NQjdRi5+zjKfvLRy6LW2vdR8+eKrOpXjQpRnHDWVRznyuUuTncYLW9otau176WteX3d8Cvi94b+P3wa+GHxs8HrPH4Z+Kfgjw7440aG62farWz8QabBfrZ3Wwsn2myeV7S42EoZoXK8EVhUhKlUqUpfFTnKDa6uL3+e/Xz7R7KNWNalTqxuo1IqSv5r1ez0/z0cvz2/4KHf8nT/8Ei/+z0fF/wD6oD4g1vh/93zP/sDp/wDqQjhx3+85b/2FS/8ATMz9X65T0j8y/j7+1z+1F4S8Y/HwfBH9nDw94s+Fv7Lnhm08R/Ezxp8S/GeoeA7jx7cDwo3jnXtB+D1uuh3tlrUvh/w7sju9a1K8t9Kk11/7IjdZIp3Xqp0KDjR9tWnGpXdoQpx5lTvJQi6tpNrmb6JO123tE4a2JrxlV9lRUqdCPNOU5OLn7vM/ZrlfMorR9L6KStJn3f8ACH4laL8ZfhT8Nvi34chu7bQPib4G8K+PNGt7+Pyr230zxXollrdlBdx5IS4hgvUjmAOBIrYwCK55wlTnOnKzlCcoNp3TcZWutvy+7Q6qVRVacKiTSnGM0nulJXXRbJrp9+p+b/8AwUM/5O3/AOCQv/Z3/wASP/WePHldWE/g5n/2B0//AE+jhxv+9ZZ/2EVP/TMzM/4Lf6lp+jfsM2usate22m6VpX7U37H+panqN7MlvZ2Gn2P7QXgm5vL27uJCscFta28ck080jKkUSM7kKpNVlqbxkUk23hsXZLVv9zst/wAvvFmzSwl27JYjDNt7Je2gcp/wU9/bW/ZE8Yf8E7v20fCvhX9pX4KeIvEviD9nn4haXoehaP8AETwzqGq6vqV1pey2sdPsbfUHuLq6nb5YoYUeRjwEYgBVgcLio4nBuWHqpRq03JuMvdSi7t+6l9zfls2TjsVhpYLEQjXpSl7JpWnF3a6L3er03fy0Z+jv7PjK/wABPggykMrfCH4alWHQg+DNGwR6gjkHv1r85xStisSv+n9X/wBOSPoKH8Cj/wBeqf8A6Qj4t/ZU/wCUu3/BSH/shP7FP/pk+JtfVYf/AJEOX/8AYTj/AP0ugeR/zN8f/wBg+C/9IqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/X/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfX37Un/Js37Q/wD2Q/4q/wDqD63XzWB/3zC/9hFH/wBLietiP93r/wDXmr/6Qzy//gmF/wAo+P2QP+yE+A//AE0RV99jP99xf/X6X5s8jLv9yw//AF6h/wCkxPrn4laZfa18OPiFo2mQNdalrHgXxfpWnWqEB7m/1Hw9qNnZ26lsKGmuZoolLEKC2SVAzWC0cX2lF/JST/JHXNNwmlu4yS9Wj5i/4J2/DTxt8Hf2Kf2d/hl8RtDuPDXjfwd8PtN0fxHoV20L3GmajA8pltpXt5JoXZQwyY5HU56n+HXEyjPE1pwfNGUtJLRPfvZ/J7ed7mGDhKnhqUJq0oxUWuzSS8r+ttfI9W/ar/5Ng/aM/wCyF/Fn/wBQPXqVD+PR/wCvtP8A9LRWK/3ev/16n/6Szxz/AIJrf8mE/smf9kQ8Df8Apphq8Z/vmJ/6+S/9KkZ4D/c8N/16iT/t2/FT9qL4YfCGH/hkj4Jan8Y/ir4r1ZdAiurS40hbH4c6VMi/bfGt/p2q6jpo124sYnb+ydHhuIkur9E+1ypbh9xhoUJz/wBoqqlTiru9/f8A7iaUrX6votrvWJjKmIp0v9mpOrUk7XVrU11lb7T/AJVffvZnn3/BOnwvqngLwB4m8J698C/jN8NvFl7rL+MviD8SvjTL4VuPEvxm8feI2ebxB4mmm8Na5rIQwyxrBb2Mxgt9N08WllaK0cJ21jJKdSM41adWNuSEKXNy0oR+FXlGPR9NdXe13zRgYuEJRlRq05X5p1KvLzVZyesvdcrXd9G/dVleV1y/Sv7W3P7Kv7Sw7n4CfF0D3J8Ba7gD3JP41lQ/j0f+vtP/ANLR0Yj/AHev/wBeav8A6Qz4J/4J6ftnfsleF/2G/wBlrw54j/aR+C+h69ovwT8Eabq+j6p8QvDVlqOm6haaNBFc2d7Zz38c9vcwyKY5YZVEiMCCoP3t8Xh8RLFYqSoVWp1akotQm7puVmrRad9vLfXVy4sFi8NHCYeLr0VJUo3TqQTWmqs+V6bPXp00UuW/4IxeBPhN45/YZ8PeKbrwV8PvFsmrfGP9om6j8Q3fhjw9rU2pW7/G3xubWf8AtO5sbma6ia3MRgcysvk7NnyFRWmZOccW48042pU7xUpRXwQ6L17ddbWDLI054bm5YSvVrPmsnzL2krP8/wCkza/4JnaXpmi/Fj/gqDpej6dY6Tpll/wUD8dw2enaZaW9hY2kK/Dr4dbYra0tYobeCMdo4o1UdgMmvl+Jm5SypybbeWU223dt+1q7t7/13OzKUl9fSSS+vVNErL4IdFb8vuLf/BZv/kx2/wD+zhP2Vv8A1fXgmuPh7/kZL/sFxv8A6jVTbNf9yl/1/wAL/wCn4n6owf6iD/rhD/6KWvDPRPy9/Yd/5SCf8FZP+yp/s+/+qQ0avvcN/wAifKPTEf8Ap88Gj/yMcz/6+UP/AExA/W+rO4/Pb4DfDjxz4e/b/wD27/iJrXhnVdN8EfEHw3+zPbeC/Et1bNHpfiO48LeBNU07xDFplxyJ30m9mjt7wAL5cjqpya6Kk4vC4ammnOE6zlHrHmqKSv2utV+S0cuSlCSxWIk01GXsnF97RknZ+Ta72263j+hNc51n5M/sTf8AKQv/AIK3/wDZWv2df/Wf/DddmJ/3bL/+vdb/ANPVTzsJ/vmYf9faf/pmB94ftQ/Ce7+O/wCzf8dvgvp94mn6l8UvhR458D6Zfyu0cVnqniDQL2x024lkT50ijvpbdpXX5kj3MvIrnpTVOrSqtXVOpCpa17qMk387Xtvrp1vHrxFL21CrSTs6lOUU+zadvxPxO+HPwT1/xN4k/YF+Hvwx/Yi8bfs3fE39mX4j+HPEPxx+NmseHNH0Dw6fB/hrwfq3h/xr4e0zx9YX09/8VE+KOqXFtLDFMbuMxY1LUGgmhVa9CpU5VjJ1MUq1OvCSp0lJ83NKalBuHK1S9l8N7J62W8UeXSpuUsJCGElQqUZJ1KsoxUeVL3kpq/tHK/dq63TTif0T15S2X9W8vlse0fil+yt8YvhN8Mf+Cgn/AAVgsviN8S/AvgO71T4zfA+60228X+KtF8O3F/bRfA3wxFJcWcWq3ls9zDHKDG8kSsiuCrEMMN6FanUng8v5Kc52p1b8sW0rVr2btZO213r0WlzysPVp08bmHPOMb1KVlKSV/wB1Ha/9fgY+kv8AAH9o/wD4LMeLpVHwo+OPhrRf+CfXgpInZfC/xB0bS9YPxr8WmURlk1Wzs9RNrND5m0JcGF4w3yOtEvbUcvi7VaLeMnfWUG0qC3atdXX/AA9/eEqNfMpfw6qWFjr7s0nzvS/R7p7frLW/aJ+FPwv+HP8AwVE/4JlSfD/4c+BvA8mo+F/2s/7Qk8I+FND8Ovf/AGfwZ4WFv9sbSLK0Nz9nEsvk+dv8vzZNm3cQ3n5hUqTybMVOpOa58I1zScre/Pa/ou35OW3sqdPM8ByQjFuOJu4xSv7kbXtv1/pH686p/wAgrVf+wXqX/pFPXwUPjj/ij+Z75+Xv/BFz/lHX8E/+wx8Wf/Vt+Na9riP/AJG+J/w0P/TFI8zJ/wDkXUf8db/04xn/AAUF/wCTpv8AgkT/ANnr+Lf/AFn/AOINdnDXw5z/ANi+P/p0yzX+Jl//AGFS/wDTNQ/XuvYOg/AT9szwPYeE/wBov9onUI/h9+2j4Uf43eBvDBt/+GXpbnXPh3+1Tr8PhKfw0dA8eJa6ReyfDLxbpckNl4Y1jXV1LRv7V8KPBetqB8g+V6WHm3RoLmwkvYzkv9otGeHjzOfPT39pCWsox5Zcs1ZLY8bFQ5a1f3MTD2kE19X96Fd25bS9393JfC3dXTu9k5fqZ+wp8Gdb/Z4/Y4/Zr+CXiaGO18R/DX4Q+DvDOv2cU/2qKx1m102OXUtPiudzeemn3c8tkJgzCXyN4ZgwduTFVFVxOIqq9qlacldWdtk35tK/S23S8vQwdJ0cLQpPeFKEXbyW3XZab/fY+T/+Ch3/ACdP/wAEi/8As9Hxf/6oD4g1eH/3fM/+wOn/AOpCObHf7zlv/YVL/wBMzP1frlPSPws/4KA/tKeOfiV8W9U/Yxk+FX7Q/hL9muKzsX/aG+NHgX4S+MPFt/8AFXQrxIbu7+Dfwru9AsbiKx0/XLV0sfG3jK4miMGmzXmk6RFLcyzTxehhaUKdP617ShKvr7GjOrGCpyWiqVeZdHrGLu3pLW0Ynj43EVJ1HhfY140NPbVYUpSdSL/5d0rdGlac246Oy1alH9kPhJqPhjVfhh4BvvBXh7VPCXhCTwposXhjwxrWiXXhvVdA0K0sYrPS9IvtBvY4rvSbixs7eG3axuY1mhCBXGea4ZJqc1JqUueV5J3Um3dtPVO7vqtHurbHqUnF04OMXGPLHlTVmlbZp2afdNJ+try/Mr/gpJrWj+Hv2pf+CR+sa9qmn6LpNl+178RnvNT1W8t7DT7VH/Z78cxI9zd3UsNvCrSSJGrSSKC7KoILV14RN0sySTbeDhok29Kyey12ODHSUcTlspNJLEVLt6JfuZen9bXukcD/AMFoPiN8IfH37FmneEbDxx8PvGD63+1J+yHZXfhuz8R6Drb6rps3x/8ABUepWs2mW97dPd2klm8q3cbQvGbdpPNBQtVZdGpHFqXJOHLhsU+Zr4X7J2d7NLXa7WvcjNKlKphVBSjK9fDppPde2hfTrp2v+sei/wCCoH7Hn7J/hP8A4J1ftpeJvC/7NvwR8PeItB/Z4+IWp6JrmjfDXwpp+q6TqNrpZe2vtPv7bTkuLW7gfDwzwvHKjfMrqRWeBr4h4rBJ16vvVqaknOT5lZ3Ul1Te6HjsLho4LETjh6MZKk2mqcE09NU9Hdff67H6Hfs+KF+AnwQVQAo+EPw1AA6ADwZouAOmAOwxx04r87xX+84j/r/V/wDTkj6Ch/Ao/wDXqn/6Qj4t/ZU/5S7f8FIf+yE/sU/+mT4m19Vh/wDkQ5f/ANhOP/8AS6B5H/M3x/8A2D4L/wBIqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf//Q/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfX37Un/Js37RH/ZD/ip/6g+uV81gf98wn/YRR/8ATkT1sR/u9f8A681f/SGfDn/BOL9sj9k/wr+wl+yp4c8S/tG/BnQdf0X4K+CtO1fRdW+IfhnT9T0y/ttLijuLO+s7jUEntrmGQFJIZUV0YYYZyK/Q8Zh8Q8ZiZRoVZRlWk01Cdmt7pqDTWvf7jwcDisPDB4eMq1OMlSgmnOKaailZq0vxUfn9n7W/4bo/Yz/6Oj+BH/hz/Cf/AMsq5/q+J/6Bqv8A4BU/+VnX9cwv/QRS/wDBkf8A5WH/AA3R+xn/ANHR/Aj/AMOf4T/+WVH1fE/9A1X/AMAqf/Kw+uYX/oIpf+DI/wDys8P/AGm/22P2QdW/Zv8Aj/pemftMfBC/1LUvgt8ULDT7G0+JPha4u729u/BOt29raW0EeomSa4uJ5EihijV3kkdUVSWFa0KGIVai3h6qXtad3yT0XOtdYLbff7zHEYvDSoVkq9Jt0p2/eR/lf92P5o8l/wCCeX7Zf7Jnhn9iD9l3QPEP7SHwW0XXNI+Dfgux1TSdT+Ivhiy1DT7yDSoVmtby1n1BJreeJvlkikRXQjDZ/ivF0MQ8XiHGhVknUlZqE7Ozeqag01r+HXeUYLFYaGEoRlXpqUacU05xTuvK0rfcvnb3fsr/AIbo/Yz/AOjo/gR/4c/wn/8ALKuf6vif+gar/wCAVP8A5WdP1zC/9BFL/wAGR/8AlYf8N0fsZ/8AR0fwI/8ADn+E/wD5ZUfV8T/0DVf/AACp/wDKw+uYX/oIpf8AgyP/AMrPB/2pv22P2QtV/Zk/aJ0vS/2mfgjf6nqXwP8AipYadY2fxJ8LXF3e3134I1uC0tbWCPUWkmuJ55EigijBeSRlReSK1oYfEe3o3w9VL2tPXkn/ADx3vBJW3v08r3jjiMXhXh669vSd6NRW9pHW8JafAvz+48j/AOCef7F37IPiz9hr9lnxN4i/Zn+B3iDXtc+CPgfU9W1vVPhz4Yv9R1S/u9FgluL69vbiwkmurm4kYySTSuzyM24sc5q8ZicQsVikq9aKhWnypVJpJJuyUdlpYzweDwk8LQlLD0JSlSg3J04NvTe7jf8AFW20sjT/AOCJWmado37BPhjS9JsbXTdNsfjH+0Za2VjZQpb2trbQfG/xxFBb28EeEihhiRI440CqiIqgAKNzzJt4ttu7dKndv/BT/rzKytKOFSikkqtZJLZJVJafj/Vyh/wTh/5LN/wVL/7SD+PP/VdfDmvmOJd8p/7FlP8A9O1TryrfH/8AYdU/9IgM/wCCzf8AyY7f/wDZwn7K3/q+vBNcnD3/ACMl/wBguN/9Rqprmv8AuUv+v+F/9PxP1Rg/1EH/AFwh/wDRS14Z6J+PP7KXxd+Ffw2/4KF/8FV7X4g/EfwR4IudR+J/wCm0+38VeJ9H0Ge+ih+CejRzSWsWpXcDzxxSERyPGpVHYK2CQK/QcJSqVMmylwpzmlHEXcYykl++dk3H08nv2al89CrTp5jmSnOMW6lCyk0m/wBxDa7127ffpy/pv/w1T+zP/wBF/wDg7/4cbwr/APLKr9hiP+fFT/wCodf1mh/z9p/+BxD/AIap/Zn/AOi//B3/AMON4V/+WVHsMR/z4qf+AT/r8fvD6zQ/5+0//A4h/wANU/sz/wDRf/g7/wCHG8K//LKj2GI/58VP/AKgfWaH/P2n/wCBxPyz/Y2/aH+Aulft8/8ABVfWdT+M3wwsNJ8Q/FT9n240HUrvxx4dt7HWoLP4EeHbO7m0u7lvxBfR2t1G9tcPbO6xTK0bkMK7MRRrPDYC1Ko2qda65ZO376ejtdq6kmr27eR5+Fr0Vi8e3Vp2lUpuPvx1XsYLTZPVPa+3nc/Uz/hqn9mf/ov/AMHf/DjeFf8A5ZVx+wxH/Pip/wCAVD0PrND/AJ+0/wDwOIf8NVfsz/8ARf8A4O49P+FjeFf/AJZ/0/HtR7DEf8+Kn/gNT+vz/G0T6xQ/5+0//Ao/1/XkH/DVP7M//Rf/AIO/+HG8K/8Ayyo9hiP+fFT/AMAqB9Zof8/af/gcT8ef2WvgF+yN+1z+3p/wVM8bfEL4Z/B74/2umfF74KWPhXxPrOm6P4ytbTTZPgr4ca7ttI1JGuoFtnvklM6Qyuv2hHBw6sa7q1XEYfB5fGM6tFunV5oJuF261ruz1sndax3Xf3fMw9PD4nGZhKUIVUqlLll8S/hR2ktN+3z3R6P8D/gP8GPgD/wWZ8feGPgn8MPBnws8O6l/wT58FaxqGi+CdFttD0681WX42eKrWXULi2tQqSXclva28LzMAxSGNeiis61WrUy+PtKk6jWLqJObu0vYXst9E9tfW7bNaVKnSzKSpwjBfVY6RVr/ALx6/wBfqel/tef8pQf+CX3/AGK/7XP/AKhnhOvNx3/InzH/ABYT/wBOVDon/wAjLL/8OK/9Igfp1qn/ACCtV/7Bepf+kU9fCw+OP+KP5nuH5e/8EXP+UdfwT/7DHxZ/9W341r2uI/8Akb4n/DQ/9MUjzMn/AORdR/x1v/TjMv8A4KN6xpOgftLf8Ek9X1zU9P0fSrL9tPxbLealql5b2Fjaxn4A+P0Elxd3UkUEKF3RA0kiguyrnLKK7eGU2s4UU23gIpJK7b9r0S/r7jHNmlPL22kvrT1ei/gz7+f9an6c/wDC8fgv/wBFZ+HH/haeHv8A5ZV7PJV/581PuNPb0f8An5D7xR8c/gwOnxa+HIz1x418PDP/AJUj/L880clT/nzU/wDAf67IPb0f+fkPvE/4Xj8F/wDorPw4/wDC08Pf/LKjkq/8+an3B7ej/wA/Ifeflj/wUB+Lfwr1H9p//gk7d6f8SfAt7a6P+2R4tvdVuLXxXolxDp1m/wABvH1ul1fSRX0i2lu08kcKzTmONpXSMOHYBuvD06n1fM/3VRXwlNL3Xq1Xi7K19beXTqedjatJ4jLrTi7YqV9dv3U/T89fI/U7/hePwX/6Kz8OP/C08Pf/ACyH8vyrk5Kv/Pmp9x6Pt6P/AD8h944fHP4MjgfFv4dAeg8a+Hv/AJZUvZ1HvRn/AOA3/r+uwe3o/wDPyH3jf+F5fBf/AKK18OM/9jp4e/8AllT5Kn/Pmp9we3o/8/IfefkD/wAFNbX4BftJ/tD/APBKv4VeJrv4f/Fzwbr/AO1n4/TxV4NXWtN12yv7CL4DeNLi1/tK00++kmFuuoQWzxsxjUzIg3E4Wu7BOtRp5jUiqlKUcLT5ZWtZ+3Wz2va/Xz0PMx/sMRXy6nLkqQeIqKUd0/3Tts772/XmvaPkP/BVP/gn5+xd8Cf2YvCnxK+EP7Ofw48AeO9I/ar/AGRLTTPFHh/Tbm31SyttU+P/AIJstQhgllupVVLu0keCX5DmNiBjOW2wWMxVXEunUrzlCWGxTlF6J2ou23a/T59CMxwWFo4eNSlQpwmsRh7SitVetBP7/n+sf0q/4Kwf8ozv26P+zaviT/6aTXn4H/esD/1+p/8ApLO3MP8AcMT/ANeWfQH7P3/JBvgl/wBki+G3/qG6LXwGK/3nEf8AX+t/6ckezQ/gUf8Ar1T/APSEfFn7Kn/KXb/gpD/2Qn9in/0yfE2vqsP/AMiHL/8AsJx//pdA8j/mb4//ALB8F/6RUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/9H+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9e/tSAH9mX9ogHofgf8VP/UI1uvmsD/vmF/7CKP8A6cietiP93r/9eav/AKRI+D/+Cc37En7HnjD9hX9lXxP4q/Zg+BfiLxHrnwW8FalrOu6x8NfC+oarquoXWlxSXN7f3txYST3NzPIxeWaV2eR2LMxJJr9GxWLxMMXiYRr1VGNWSilNpJdlZSVvlHy7R8DAYXDTwlCUqFJydKDbcIttuKd3rDW739593oj7SP7AH7DY6/skfs8D6/CnwgP56b7f5wK53jcUv+Yir/4HJ/8Atsfz+77XZ9Uwi3oUv/AIr/26X5fff3QfsAfsNnp+yR+zwfp8KvCB/lpv+fzoWNxL2xFX/wADkvxs/wAvuuw+qYR7UKX/AIBF/wDt0fy+63veJftMfsI/sWaN+zj8ftX0n9lT4Badqml/Bf4oahpuoWfwv8KW95Y31n4J1u4tLy0uItOWSC5tp40mgljZXjkRWUggGtaOLxTrUU8RVt7Wnde0lqudaP3Y6P1+77WOIwmGjQrNYeldUptfu4/yv+9Lt5evQ8m/4J6/sP8A7HHir9iL9l7xF4l/Zd+BOva/rHwb8GX+razq3wz8L32p6nfXGlRPPd315PYPNcXEzktJLIxd2JY8k1eKxeJjisRGNeqoqpKy55Kyu1ZaS008vntHPBYTDSwtCToUrypxb9yOr77xu33t5aJLm+x/+GAP2Gx/zaR+zz/4anwgP56b/n8RWH13Ff8AQRV/8Dk//bY/n91/e6vqeF/6B6X/AILj/wDJ/r94f8MAfsNn/m0j9nn/AMNT4QP8tN/z+BpfXcV/0EVv/ApL9Jfl99vdPqeF/wCgel/4Lj/8sPCP2pP2Ef2LNG/Zl/aI1fSf2VPgHpuq6X8D/irqGm6jY/C/wrbXthf2fgfW7i0vLS4i09ZILm2njjmgljZXjkRWU5Hy60cXiXWop4irb2tO69pLX31o/djo/X7vtY4jB4VUK79hSuqVRp+zjdPklZr3pWa9Pv15fT/+Caiqn/BP/wDZFRFCqvwE+H6qo4CqNCtgAAOAAOAB06Vhjf8Ae8Z5Vqn/AKVL+v8AhjTAf7nhtLfuo6I8F/4Iuf8AJjGhf9lq/aR/9Xn47rfMf97/AO4VP/0iBlln+7f9xq3/AKcZhf8ABOH/AJLN/wAFS/8AtIP48/8AVdfDmvmeJd8p/wCxZT/9O1TqyrfH/wDYdU/9IgM/4LN/8mO3/wD2cJ+yt/6vrwTXJw9/yMl/2C43/wBRqprmv+5S/wCv+F/9PxP1Rg/1EH/XCH/0UteGeifh38Af2UP2a/2hv+CiX/BUzU/jj8EPh18VNR8P/Ev4D2miXvjXw7aa1c6Va3vwW0S4u7eyluAxgiuZ1WWZVXDyAMckZX9DweIr0smypU6tSmpLEXUHy3/fvXTqr2XZaHzf1ehXzHMXWowqONSgouau0vYwel9rt+X43l+g3/DsX/gnr/0Z38BP/CD0v/4xWn1rFf8AQTX/APBkjo/s/Bf9AtH/AMAiH/DsX/gnr/0Z38BP/CD0v/4xS+t4r/oKr/8Agbt9+39WD+z8F/0C0f8AwCIf8Oxf+Cev/RnfwE/8IPS//jFP61iv+gmv/wCDJB/Z+C/6BaP/AIBE/Mj9kP8AYC/Yp8Tft0/8FP8Awlr/AOzB8G9X8MfD/wCJ3wG07wToV94O0+fTfC9jrHwP8P6tqlro1s6OlnDf6nNLfXSRqPNuXMjMWNdmIxWJWGwFsRWTlTq8z53eVqs0m3ZXaSt1/Fs4cNg8LLFY6MsPScYVKainCNop0oOyWttW/wDgbH6b/wDDsX/gnr/0Z38BP/CD0v8A+MVx/WsV/wBBNf8A8GSO7+z8F/0C0f8AwCIf8Oxf+Cev/RnfwE/8IPSv/jH+H8iy+t4r/oKr/wDgbt9+39WD+z8F/wBAtH/wCIf8Oxf+Cev/AEZ38BP/AAg9L/8AjFP61iv+gmv/AODJB/Z+C/6BaP8A4BE+SP8Agmn8LPhz8HP2zv8Agq34D+Ffgvw94A8F6J8afgjFpHhjwvp8WmaPp0dx8E/D97OlrZw/u4hLd3M9w+B80krtxlq6MXUnUwmXSqSlOXs6l5SfNKVq9rt2jrbTb7vtc2ApwpYvMIU4qEFUo2jHRL90unzZ6Bpn/KbXxj/2jn8Df+rz8ZVlP/kXx/7DJ/8AqOjVf8jOX/YKv/Syj+15/wApQf8Agl9/2K/7XP8A6hnhOuHHf8ifMf8AFhP/AE5UNJ/8jLL/APDiv/SIH6dap/yCtV/7Bepf+kU9fCw+OP8Aij+Z7h+Xv/BFz/lHX8E/+wx8Wf8A1bfjWva4j/5G+J/w0P8A0xSPMyf/AJF1H/HW/wDTjOB/4KofDLwD8Y/jh/wSp+G/xP8AC+meM/Avin9szxVYeIfDWsJJJp2q2kfwI8dXiQXKRSRSFFurW3mGx1O+JeQARXfwtUnSeb1KcnGccBFpruq3z/Ffec+cU4VJZfGpFSi8VK6ez/czPqX/AIdM/wDBOX/o0j4Vf+AOqf8Ay2r6D6/jf+gqr/5L/wDKyP7Owf8Az4iH/Dpn/gnL/wBGkfCr/wAAdV/+W3+fxFL+0MYt8XV/8l/+V/1t1Qf2dg/+fEQ/4dM/8E5f+jSPhV/4A6p/8tqf1/G/9BVX/wAl/wDlYf2dg/8AnxE/Nb9uX/gm/wDsNeCv2jv+CYfh7wr+zX8OtE0X4k/tZeJ/C3jrT7K01BYPEvh61+CfjfWbfStRD6hIzWsWqWVreqI3ibzoIyWxmumhjsW6GYN4iblTwsJQk0m4ydaMW17q6X3T3OHF4LCwr5fGNCFp4mSl5r2U9Hquqv1tbs2j9Kf+HTP/AATl/wCjSPhV/wCAOqf/AC2rm+v43/oKq/8Akv8A8rO7+zsH/wA+Ih/w6Z/4Jy/9GkfCr/wB1X/5bf5/EUv7Qxi3xdX/AMl/+V/1t1Qf2dg/+fEQ/wCHTP8AwTl/6NI+FX/gDqn/AMtqf1/G/wDQVV/8l/8AlYf2dg/+fET4I/aa/Yp/ZW/Zr/bU/wCCTvib4FfBLwb8M9e179q74gaTrGp+HLe7hudQ020+AnjnULeznNzeXKmKO9jS4UKF+dQT0roo4rEVsPmMatadSMcJBpSto3Wir6KK202vrbTXm46+FoUMXlrpU1BvEVLtbtKjJ2e2l1f8ddEfTv8AwWs/5Mq0X/s7P9jX/wBaJ8C1jl3++L/sGxf/AKZZ0Zr/ALqv+wjDf+noHs3/AAVh/wCUZ37dH/ZtXxJ/9NJrDAf71gf+v1P/ANJZpmH+4Yj/AK8s+gP2fv8Akg3wS/7JF8Nv/UN0WvgMV/vOI/6/1v8A05I9mh/Ao/8AXqn/AOkI+LP2VP8AlLt/wUh/7IT+xT/6ZPibX1WH/wCRDl//AGE4/wD9LoHkf8zfH/8AYPgv/SKh+yFcx2BQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAH/0v7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH19+1J/ybN+0P8A9kP+Kv8A6g+t181gf98wv/YRR/8AS4nrYj/d6/8A15q/+kM8v/4Jhf8AKPj9kD/shPgP/wBNEVffYz/fcX/1+l+bPIy7/csP/wBeof8ApMT52/4Ks2fxC1W6/ZD0Twj4d+P3i/w1rHxn8SWXj7wt+zz4i1Xwn4s1vT28DXzaDa6p4k026sYdH0VNcEE1xfandwWEIRy7k8Vpg3BfWHJ0otUU4SrR5op8/vWjZ3duii3trHRk4/mtQ5Y1ZJ1GpRpPlk/ddtdkt7t2SWvS0u1/4J2eJvAmmav8afgtD4S/aE+Gnxf8Cah4c1vx98O/2hviTefFHWrPSPEenlvDOv8AhTxNJqWqafc+HNWgtplI0+dAl9BOlxEsiktOLjL9zV5qNSlPmUJ0Yey95OzUocrfMtLptaWs9GGDnG9Wny1qdSDTlCtLnai17ri9nHdaL7nzH2N+1X/ybB+0Z/2Qv4s/+oHr1ZUP49H/AK+0/wD0tHRiv93r/wDXqf8A6Szxz/gmt/yYT+yZ/wBkQ8Df+mmGrxn++Yn/AK+S/wDSpGeA/wBzw3/XqJ6/+0D+z54J/aA0LSNN8ceLfiZ4Q03wxdXmsJffDb4ia98Orlg9sq3Lavf6FPBJe2NvDB5yxXL+VAQ8oxlqilWlRbcYwk30nCM/uUr2bvbRa+dkaV6MK0UpyqRUW3enUlDp1cd1bun8tpfDn/BLDwXeR6N8f/i/pPjf4qeJfhF8SvixqWmfAzSvid4713x3dWvw68BBvDMPiayv9emmuIk8Z6taahraLEVjNnNa4Hdt8dK86NOUKcalOneq6dOMLynaSXur7Ka32fNrujly+FlWqKdSVKpU/dKpNztCC5U030k03vqn0sfb/wC1v/yar+0t/wBkD+Lv/qBa9WFD+PR/6+0//S0deI/3ev8A9eav/pDPIf8Agmt/yYD+yN/2QXwB/wCmK3p43/fMb/1+qf8ApUjLAf7nhv8Ar1E/HT/gmj8cv+CgPg79mN9A+CP7GvgT4rfDay+NX7Qf9g+Oda+O+i+DNR1jzvjN40mvvP8ADt1pd1cWP2S9ee1TzJXEyRCYAh8LpmmLyuli3Cvi6tKqqVLmgsPKajenFr3k0npbTbye5x5ese8Pejhac4OrXtKWIjTb/ey3i0uqfV6W7n6K/wDBN/4P/tDfDpv2uviB+0j8P9A+GPjH9oj9qLxH8Z9K8HeHvF1j41tNK0DV/CHhHRYYZdasIoYpJ1vNFvAyNDG4Xa2CrDb8pn+NwmMqYNYOpOrTw2EhQc503TvKM6kn7rbe0lrf1toerltHEUY4l4mnGnOtiZ1VGM4zSi4xS96PW8Xve++l7HM/8Fm/+THb/wD7OE/ZW/8AV9eCajh7/kZL/sFxv/qNVHmv+5S/6/4X/wBPxP1Rg/1EH/XCH/0UteGeifl7+w7/AMpBP+Csn/ZU/wBn3/1SGjV97hv+RPlHpiP/AE+eDR/5GOZ/9fKH/piB+p3i208RX/hXxLY+ENUs9D8V3ug6taeGta1G0a/sNH165sJ4dJ1S8sUeNr220++eC7mtFdDcJCYd6791aK11e7V1dLRtX1Setm1dXtpvqdkuZxkotKTT5W9k+je+z8vvPwf+GOs+LvhL+39+z78AvB/7S/7QXxV+Ic1t4/l/a7j+NbXen/CXxbpWn+FftdjqXwgstY0zTbBfENp4wntDYaT4JuL6Cz8Ni6/tL5Yllr0pqNTCV6s6FCnC9P6t7LWqnKVpKrq2ounfWSTcm7X908im5U8bRpQr1ak37T6wqt/ZuKjvTurKSl8KjZKLau7I/oBry1svRHsn5M/sTf8AKQv/AIK3/wDZWv2df/Wf/DdduJ/3bL/+vdb/ANPVTzsJ/vmYf9faf/pmB98/tK+KvH/gb9nj44eM/hTpDa/8TPCvwq8da/4C0ZbdrttR8WaV4c1C80S3S0Qhrt/tsUTpaL8106C3AJkUNz0YxlVpRm7QlUgpu9rRclzO/TTr036M68RKcKFWVNXqKnNwW/vKLa7dfPXbTQ/Br4S/tI+DPhf8Q/8Agn54o+G37aXxP/aE8eftOeP9H+G/7RPwy8X+KovE+kWreL/BOsatc+ID4UisLY/CvUvB/jiwt9JstOX7OlxaSXOnyW8zwb19KpSnOnjVVwlOjDD05ToVIx5W+WaXLz6+0U6Vn66rls3HyKdaNOeDnTxNStKvLkrQnK6s4vXl5f3bjLS35297+lKvIWy9Ee6fk1+w7/yf3/wVv/7Lb8C//VE+GK7cT/ueXf8AXup/6fZ5uE/33Mf+vlH/ANNRPmz9on4o/Hn4V/8ABY7UNW+Af7Pk37Q+val+wF4Msdb8Ow+ONC8DNoOlx/GjxlNDqzX2vfuLwT3P+ii2gPmoR5jYUilKphaWXKWLr/V4PGTUZezlU5pewhdWi046PfVa7aMzqSxCzJ/V8P8AWH9WXMvaRp8q5925KXXt6a3vHobK3/bi/aL/AG9/2OfjH8Wv2PJvgL8NfgHoPx1svEPiG4+KnhHxo13c/EbwzpWn6RHHY6KVuogl3pQjdvLkB8/JwFJXyMfjsseV4yhh8Z7atWnQcYOlUhpTm3L4r9Hf4vu1R0UaWOq47C1q2FVClRjX5n7aFR3nFJWtyvdfy+Wm8v2h1T/kFar/ANgvUv8A0inr42Hxx/xR/M94/L3/AIIuf8o6/gn/ANhj4s/+rb8a17XEf/I3xP8Ahof+mKR5mT/8i6j/AI63/pxjP+Cgv/J03/BIn/s9fxb/AOs//EGuzhr4c5/7F8f/AE6ZZr/Ey/8A7Cpf+mah+vdewdB+SP7anhf9o/RLD9qT9ovxH+1drv7O/wAJPgt8OY9b/Z58O/DxPD1xbeIPEej+FZdT1LUvizBrmlXl1rs/iPxubTwtonhTS57fzdNdHhka+u0Re3DSpXoUVh41qlSpatKo5fDKXKlTtorQu3KXLd9LRbPNxcayjXryxEqNOlC9GMFFpyUW71L3c+eXKlFdraXUj9B/2cvFvjnx98APgp44+JujL4e+Ivi/4WeBPEnjjQ1ie3XSvFOteGtO1DW7IW8n7y3EN/cTr9ncs8H+pY7kNctSMYVasYPmhGpOMJd4qVk+nbt6WTR20JTnQozqLlnKnCU49pOKcu3Xy+4+B/8Agod/ydP/AMEi/wDs9Hxf/wCqA+INb4f/AHfM/wDsDp/+pCOLHf7zlv8A2FS/9MzP1frlPSPyK/bT8M/tKaBpf7VH7R/iX9q3Xf2e/hZ8F/Acesfs4+Fvh2nh66svEWuaP4VGo3mofFq31zSLy71+98VeO2h8LaN4T0u4gDaW0Jgd768XZ24eVLmw9CGHjWqVZ2rSqc11GT5f3bTsuWHvOU4pX6NKLj5uKjiEq9d4iVGnTinRhDlfM4xu3U5t7z0Ub7bNP4f0a+AXijxp43+Bvwd8ZfEfRl8PfEDxX8MfA3iPxtoSxtEukeKdZ8NabqGu6esLfNCLXUbi4i8liWi2+WSSprlqRjGpUjB3hGcowfeMZNJ99Ur63+VkjtoylKjTlNWnKEHNdpOKcl8np0/C8vz1/wCChn/J2/8AwSF/7O/+JH/rPHjyunCfwcz/AOwOn/6fRxY3/ess/wCwip/6Zmc//wAF0NR1HR/2CJdW0jRrjxFq2l/tM/skahpfh+0nhtrrXdRs/j54MuLLRra4uMW8FxqdzHFZQzXDLDFJOrysEVjVZbyrGJylyRWGxblJq6S9jq7K7dlrZfhe4s3usJeMeZ+3w9ordv20LJbbvT/O1jwL9sj9oL9vf9pX9lP9oT9n3Rv+CYXxh8O6t8YvhX4q+H+na7qHxR+F11Y6Td+ILP7LDf3Vta6wbmaC3Y75I4SZWX5RtY5Xkw2LyejXoVHmlNqjUjNr2VbVRTVr8rXXey/GwYn69Xw9WjHAVF7SDgm6kLeT6fnr5H7IfBnRdU8OfB/4U+HtctHsNa0H4beBtF1exkZHey1TS/DGl2N/aO6FkZre6glhZkZkYoSpIINfBYmUZYivKD5oyrVJRfeLm2n13T7/AHnv0ouNKlGStKNOEZJ6WkopNddmn1+8+Gf2VP8AlLt/wUh/7IT+xT/6ZPibX1eH/wCRDl//AGE4/wD9LoHj/wDM3x//AGD4L/0iofshXMdgUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB/9P+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9fftSf8mzftD/APZD/ir/AOoPrdfNYH/fML/2EUf/AEuJ62I/3ev/ANeav/pDPL/+CYX/ACj4/ZA/7IT4D/8ATRFX32M/33F/9fpfmzyMu/3LD/8AXqH/AKTE9e/aS+EPxO+Keh+Ebz4OfGTU/gx8Q/AXiiPxNouqjTv7f8I+JYWtJbG+8L+PPDX2m0bWNAvYZRKn2e6t7yxvIorm3diGSopThBy9pTVSMo8rV3GUe0oSWqkmu0k02raG1enUqKLpVXSnCXMnbmjJdYzjo3Fq+z/NOPm/7Mv7L/jr4YfEn4u/Hz43fEzS/il8b/jJaeFdB1jUfDPhqTwl4N8M+DvBNtPB4c8M+G9HuL7Ub4xxSXd3eXt9f3bz3VzcMQqIiLVVasZwpUqdN06VLmdpS5pSnJq8m9FrZWSWm13dkUMPKnUq1qs1OpV5VouWMYx2ild+rffTWycvXP2q/wDk2D9oz/shfxZ/9QPXqmh/Ho/9faf/AKWi8V/u9f8A69T/APSWeOf8E1v+TCf2TP8AsiHgb/00w1eM/wB8xP8A18l/6VIzwH+54b/r1E93/aI+Hfi74ufBL4k/C/wP4xj+H/iLx/4ZvPCkHjJrSW+l0HT9aMdnrd3Z20MsLtfyaLLf2tjJ5irb3M8U7bhHtrOlKMKkJyjzxjJScb2vbVK+vW3T77m1aEqlKdOMuSU48ql2vv26XX+ex1Pwq+HHh34QfDbwN8L/AAnax2fhzwH4Y0fwxpMEahALTSbOK1WRgOsk7RtNKxyzSOzEkkmplKVSc6kvinJyfXfzsv1tsnoVTpxpU4U4q0YRUV00St5/n63ued/tbDP7K37SoJwD8BPi6CfQHwFr2Se/HXjJ44B6VdD+PRXetTX/AJOvNfn95GI/3ev/ANeav/pEj8fP2EP2v/2ufDP7Gn7NXh7w1/wTt+KfjbQNH+D3g7TtH8Xaf8SvhxY2PiPT7fSYorbV7WyvtRjvLWC9jCzRw3KJPGrAOCw+Z42vlkcXilVzCnCp7apzx9lUfK23eLs7XTutpf4lf3fPwdXGrC0FHATlFUo2l7SHvaaNdbPfW3otEfY//BK/4S/Fb4K/se+GfBPxo8Fz/D7x/J8QvjD4r1Lwnc6hZapcaVZ+Nfib4n8U6RFNe6fJLaTSnTdVtmcxOQGJB5FfJZ/iKGKzKrWw1RVaThSjGaVr8lOMXo9d0z1sso1aGEhCtB06jnVnKDaduepNpXTfT7tk3qfovXjHoH5U/wDBZv8A5Mdv/wDs4T9lb/1fXgmvc4e/5GS/7Bcb/wCo1U87Nf8Acpf9f8L/AOn4n6owf6iD/rhD/wCilrwz0T8vf2Hf+Ugn/BWT/sqf7Pv/AKpDRq+9w3/Inyj0xH/p88Gj/wAjHM/+vlD/ANMQP1C8feGbrxp4H8YeELHxDq/hG98T+Gta0Gy8VeH5Ug13w1earp9xZ2uu6RLIrRpqOkzzR31oZFZPOgQONpbdpF8soysnyyUrPZ2adno9Haz0+47JxcoSipOLlFpSjvFtWur6XW+p+anhv9kT9rrx18VP2Yte/aa+MPwl8U+D/wBkzxLqfjHwprvgHw34h034l/FPxLceEdS8F6feeOrnVZDpWh2P9mapcX+uadokt3Dq2qiJt0UMYFdcq2GjDEexpVYzxMVCSnUThTipqbVPl5XdyVk5W5YdJNJS4I4bFTqUHiKtOUcPLmjKEWp1JcnKpTvdLR8zUd5WWnK5H6sVxrRJdv68/wA/vPRPyZ/Ym/5SF/8ABW//ALK1+zr/AOs/+G67MT/u2X/9e63/AKeqnnYT/fMw/wCvtP8A9MwP1N8RaVPrvh/XdEttUvtDudY0fU9Lt9b0xkTUtHnv7Ka1h1TT2kVoxe6fJKt3amRWj86KPepXIbjW6dk7NOz1Ts72e2j6/rsehJXTV2rpq63V+q810Pyq+F/7B/x1b4n/AAZ1z47+NvgPrfg34D+LZviDp+sfDD4ZP4S+Jvxq8fWWh6p4d8LeKfi5qZij06KfQrLWdQ1K5tdHa6i1LXZluy0McYRu2eIpezqKlGsp1o8jVSpz06UOa8o07WfvWteT0i7JSsnLzqeErupSdadFwovmTp0+SdWaXLGVTdNRi3on8T62R+t1cS007f15/n956R/O/wDDH9pD4nfA3/gon/wVJ03wF+yt8Xv2hbXXfi18Fb+/1b4a3HhiGz8O3Fv8E/DNvHp2pjX9W06Vrm5jH2mI26SR+Vwzb+F7cRPCxweXfWMXSw16VZpVOa8l7Z2aajJPVO6+6+qj49GdaONzBUsPUrXqUbuHLaP7qOjvJO+n63dmj3L9nS8+Pfxm/wCClfjn9pTx7+zD8T/2f/h8P2PvC/wg06b4jzaBNPq/irS/ihrnie4SzOhajqMQi/s7VYmAkZX3RvnaNu7wM7xOCnltHD4fGU8RVjjJ1nGnfSDpRhd3UesVsn5293m78FDEPHVa1TD1KMHho0058uslO7Ss5X8tfk9HH9hq+RPZKOqf8grVf+wXqX/pFPVQ+OP+KP5gfl7/AMEXP+UdfwT/AOwx8Wf/AFbfjWva4j/5G+J/w0P/AExSPMyf/kXUf8db/wBOMZ/wUF/5Om/4JE/9nr+Lf/Wf/iDXZw18Oc/9i+P/AKdMs1/iZf8A9hUv/TNQ/XuvYOg/Hz9q39mf9un45/tM6H4ttx+z745/Zc+GNxo3iD4Y/BDxt4t8Y+G7bXPiFpyw3Ufjv4qwaR4b1WDxRLoOpLI/hXw4040Wwlih1O6ju7wIIu2hVw1Ki42rxr1OZVK0FTbjBq3JS5pJxv8AblyptaKyVzzMRQxlWupL2EqEOVwpTlON5q/vzcVJSs9Yxta+rs3eP6r+BJPGk3g/w7L8RrLw9p3jp9Ltm8U2PhO8u9Q8NWmsFf8ASoNEvb+2s7y60+NsLBNc2lvKyj5ohgGuNqKb5XJxu+XmSUrdL2bV+u/3How53GPtFFTt7yi7xv15W9betn+cvzM/4KHf8nT/APBIv/s9Hxf/AOqA+INdOH/3fM/+wOn/AOpCPPx3+85b/wBhUv8A0zM/V+uU9I/Hj9qb9mb9ur44ftO6N41WP9nrx7+zH8LrrSdf+E3wQ8a+LfGXhyz1T4gWCxXMfxA+KdvpHh3UoPFN7od+HPhbQJJf7E02SKHU54bu9EZi7qFbDUqDjy144ifMqlaKpv3Hf3afNJOPMrc7tdrRJxbgeZiKGMq4hS/czoU9adKc5x97+eoowkpNO/Kr2XW93y/q74Gk8ZzeEPDsnxEs/D+n+OX0q1bxTY+FLu7v/DdrrJT/AEyHRL2/trO9udOR+LeW5tYJmQfNGMA1xPlu+Vycb+7zW5rf3raJ+Scktk9j0Yc/Kueynb3uX4b+XWy21s/XRn48/wDBWz4hX/wq+OH/AASs8faZ4B8Y/E++8O/tbeP7i38CeALO1v8Axf4gaf4DeM7NrfRbS9urO1mnhS4a7lWW6iAt4JWG5gFrswfJ7LMfaVIUYvCU06lS6hH9+tZNbK9le0tWlbVnmZjOUMRlso051ZLEVLQgryf7mS06X669Ne54N+3f+0T8cf2x/gt4U+B/gv8AYL/a18IavfftEfs2+M7nxH408JeHrPw3pOg/D34x+FfFniC71G4sPEN9cxrDpOm3MiFbdwXUBiASy4Ua+BoSq1XmWEn/ALLiqahGcuZyqUZRjb3Et9Htve+jUli5YjE06dKOCxUb16E3KcFGKjCpGTbeuyV9unU/oCJySexOa/On/kvuVvL+u+59N/X9b/n94lID8z/2VP8AlLt/wUh/7IT+xT/6ZPibX2OH/wCRDl//AGE4/wD9LoHh/wDM3x//AGD4L/0iofshXMdgUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB/9T+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9s/H7w7rHjD4FfGfwl4etG1DX/FHwq+IHh7RLFWVGvdW1nwrqmnadaq7lUQz3dxFEHchV3ZbgGvmMJONPFYecnaMK9KUm+kVNNvrstf8ALc9itFzo1YRV5SpVIxXduDSXXd+X3n5Kfsn/ALQP7ef7PP7NvwW+B+p/8E2fidr2ofC34f8Ah/wXea1afEPwDbWuqT6JZpaPe28E2sLNFFOU8xElG9VODg5Ffd4jG5TWr1a0cypJVZudnCqrX1S00du/+R4GGWZUMPSpf2dUk6cVHm9pSV7LR6yj+tu70cvoT/hub9ub/pGH8Vv/AA5Xw8/+XNY/Wcq/6GdL/wAArG/tMy/6FlT/AMG0f/lgf8Nzftzf9Iw/it/4cr4ef/Lmj6zlX/Qzpf8AgFYPaZl/0LKn/g2j/wDLDzn4w/tZ/t2/Ef4S/FD4e2n/AATN+KdjdeO/h74y8HWt9L8R/h9JFZXHibw9qOjQ3ckaawXkjt5L1ZZEQb3RGVcEitKWLyqFWnN5nStCpCXwVWnyyTs79NDOq8yqUqkP7NqLmhKN/a0tLr/r4cP+yv8AtE/t6fAP9nP4NfBjVP8Agmt8UNZ1H4aeAPD/AIQvdVtviJ4Bt7e/uNHso7WS6hhm1dJY45WQsqSKrKOD3LViMblNatUqxzKlapJyX7uqtG7rbR7+X6ynDrMaNClS/s6pLkgo39pSV7Lzmn/W70cvfv8Ahub9ub/pGH8Vv/DlfDz/AOXNY/Wcq/6GdL/wCsbe0zL/AKFlT/wbR/8Algf8Nzftzf8ASMP4rf8Ahyvh5/8ALmj6zlX/AEM6X/gFYPaZl/0LKn/g2j/8sPNPjR+1f+3f8TPg78V/hxY/8EzfilY3vj/4b+NvBdnfTfEb4fSxWd14n8Oajo0F1LGmsF3jglvFldEG91UquCRWlHGZVTq05vMqVoThJ+5V2jJPq0v66bxzqvMp0qkP7NqLnpzjf2lJ2vFrZVNf67n3J+w74A8XfCr9kH9nL4cePdIfQfGfgr4SeDfDvibRpJY5pNM1jTdJggvbN5YS0UjQTKyF42ZGK5B5xXxuZ1adfMMZWpSUqdSvUnCS6xb0ffW3X9Uevg6c6WEw1OouWcKNOMo78soxs112afX79D6prgOkKAPyp/4LN/8AJjt//wBnCfsrf+r68E17nD3/ACMl/wBguN/9Rqp52a/7lL/r/hf/AE/E/VGD/UQf9cIf/RS14Z6J+H2heOf2mf2Vf24/29/Gui/sXfGb43eBPjz41+EviDwX4w8B3Hh2LS5bbwl8MdK8Namkg1bUbSVnGowzxr5aceUS23OG+6weJy+WV5fRqY+jQq0FX54Tvze9VbWye6s+ltve1R8/KOKo47G1IYWpVhWlSlGcXFL3aUYvz3T3t5bNy+hv+Hhn7Tn/AEjM/ae/8C/BH/y9rX22W/8AQ0w3/k3/AMrNPbYv/oBrffEP+Hhn7Tn/AEjM/ae/8C/BH/y9o9tlv/Q0w3/k3/ysPbYv/oBrffEP+Hhn7Tn/AEjM/ae/8C/BH/y9o9tlv/Q0w3/k3/ysPbYv/oBrffE+K/2fvj1+2B8Jv2oP22/jdq3/AATj/aMvtE/aW8a/CzxL4Z0y0uvB4vtGt/A3wz0rwXfw6o0utCJ5Lq9sHubf7M8irCyiRt5KJ01sXlc6OEpxzTD3owqKTfNq51JyVvddklK2vor/ABHLRWNp18VUeArWrzhKKvF25acYO7v3V1pHvbpH7U/4eGftOf8ASMz9p7/wL8Ef/L2ub22W/wDQ0w3/AJN/8rOr22L/AOgGt98Q/wCHhn7Tn/SMz9p7/wAC/BH/AMvaPbZb/wBDTDf+Tf8AysPbYv8A6Aa33xD/AIeGftOf9IzP2nv/AAL8Ef8Ay9o9tlv/AENMN/5N/wDKw9ti/wDoBrffE5j/AIJ2aV8bNa/aE/4KA/HX4t/Anxv8BtO+O3xP+FviDwR4c8dPpz6td6b4a+GGl+FtTmLaZdXdsVj1HTXIxKfklQH5q8fiGvhatPLaeGxUMT7CjWjNwTsnKtKce2rUvltrZs0yyniFWx1WtRlRVWpTcFKSbajTUW7LbZd/lb3v1nr5g9gKAKOqf8grVf8AsF6l/wCkU9VD44/4o/mB+Xv/AARc/wCUdfwT/wCwx8Wf/Vt+Na9riP8A5G+J/wAND/0xSPMyf/kXUf8AHW/9OMz/APgppp3xQ0z4hf8ABPb4x/Dn4OfED412PwE/ah8Q+P8Ax34Z+G+mx6p4itfDd98IfFnhe3vYraWaCMo2q6vbRZd1HXk4C10cOVsPSeZQr4inh/b4ONOnKo7KUva3aW99P6VrkZrTrSeDnSpTreyxDnONNXko+zlG/peS3Vr6aXOm/wCHmPxJ/wCkdf7aX/hD6T/8sq9vmwn/AENMF/4HL/5WZe3xH/QFif8AwWH/AA8x+JP/AEjr/bS/8IfSf/llRzYT/oaYL/wOX/ysPb4j/oCxP/gsP+HmPxJ/6R1/tpf+EPpP/wAsqObCf9DTBf8Agcv/AJWHt8R/0BYn/wAFnxJ+1R+1H8e/jb8aP2GPiH4Z/wCCfP7XVrpH7NX7QWu/FPxlBqXg3To7u/0PU/hh4p8GQ22kJHqJSW9XUdatpWSUxr5CSkSAja3TQrYCFLGwlmeDcq+HjThabteNRTd7xXRfO/knHjxLxVWrg5xwOJaoV3Ul7nR05R0XWzae+vVxt7323/w8x+JP/SOv9tL/AMIfSf8A5ZVzc2E/6GmC/wDA5f8Ays7Pb4j/AKAsT/4LD/h5j8Sf+kdf7aX/AIQ+k/8Ayyo5sJ/0NMF/4HL/AOVh7fEf9AWJ/wDBYf8ADzH4k/8ASOv9tL/wh9J/+WVHNhP+hpgv/A5f/Kw9viP+gLE/+Cz5h+KXxj+Nn7Xv7Wn/AATsvNO/Yz/aQ+FPhb4F/tC+L/iD498ZfEnwxZ6ZoOm6FrHwi8W+E7Vzc2t5OwkOq6jaowZANsgIYnC1GJrYOGXZnBY/DVqlfDU6VOFOTblKNeFR6NRv7sX/AJrQyX1mtjsvl9Vr04Ua851JzjyxUZUpx1fk2u2/laX7s5Pqfzr4M+gEoAKAPzP/AGVP+Uu3/BSH/shP7FP/AKZPibX2OH/5EOX/APYTj/8A0ugeH/zN8f8A9g+C/wDSKh+yFcx2BQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAH//V/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Bn9un42fCj4Ef8FXf2MfGXxf8AHWgeAPC4/Zh+O+n/ANt+IrxLKx+23nirw4ba285/l82cQTeWpxu8sjI613Sw1fFZNi6eHpyqz+t0HywV3bklrbsra7b36JS8+dalQzPDyrTjThLC1o80tk+ZdtXv29bn0t/w88/YF/6Om+E//hRW1fO/2Lmn/QHW/wDAD0v7TwH/AEFUf/Aw/wCHnn7Av/R03wn/APCitqP7FzT/AKA63/gAf2ngP+gqj/4GH/Dzz9gX/o6b4T/+FFbUf2Lmn/QHW/8AAA/tPAf9BVH/AMDD/h55+wL/ANHTfCf/AMKK2o/sXNP+gOt/4AH9p4D/AKCqP/gYf8PPP2Bf+jpvhP8A+FFbUf2Lmn/QHW/8AD+08B/0FUf/AAMP+Hnn7Av/AEdN8J//AAoraj+xc0/6A63/AIAH9p4D/oKo/wDgYf8ADzz9gX/o6b4T/wDhRW1H9i5p/wBAdb/wAP7TwH/QVR/8DD/h55+wL/0dN8J//CitqP7FzT/oDrf+AB/aeA/6CqP/AIGH/Dzz9gX/AKOm+E//AIUVtR/Yuaf9Adb/AMAD+08B/wBBVH/wMP8Ah55+wL/0dN8J/wDworaj+xc0/wCgOt/4AH9p4D/oKo/+Bh/w88/YF/6Om+E//hRW1H9i5p/0B1v/AAAP7TwH/QVR/wDAw/4eefsC/wDR03wn/wDCitqP7FzT/oDrf+AB/aeA/wCgqj/4Gfmx/wAFY/2/v2NfiV+x3e+F/Av7Q/w38TeIG+Of7NmrrpWma5BPdtpuhfGrwfqur3gjXJMGn6dbXF5ct0SCF3OAM17GRZVmFHHqdXC1Yx+rYtczj9qWHqRivVt6fdpfmjwZnmGDqYSUIYilKTrYd2Uru0a0G306efydmfpHD/wU7/YFWGFT+1N8JwVhiBH/AAkVtwRGoI79Dkf4dK8f+xc0/wCgOsvLk2O/+08B/wBBVH5yJP8Ah55+wL/0dN8J/wDworaj+xc0/wCgOt/4AH9p4D/oKo/+Bh/w88/YF/6Om+E//hRW1H9i5p/0B1v/AAAP7TwH/QVR/wDAw/4eefsC/wDR03wn/wDCitqP7FzT/oDrf+AB/aeA/wCgqj/4GH/Dzz9gX/o6b4T/APhRW1H9i5p/0B1v/AA/tPAf9BVH/wADD/h55+wL/wBHTfCf/wAKK2o/sXNP+gOt/wCAB/aeA/6CqP8A4GH/AA88/YF/6Om+E/8A4UVtR/Yuaf8AQHW/8AD+08B/0FUf/Aw/4eefsC/9HTfCf/woraj+xc0/6A63/gAf2ngP+gqj/wCBh/w88/YF/wCjpvhP/wCFFbUf2Lmn/QHW/wDAA/tPAf8AQVR/8DD/AIeefsC/9HTfCf8A8KK2o/sXNP8AoDrf+AB/aeA/6CqP/gYf8PPP2Bf+jpvhP/4UVtR/Yuaf9Adb/wAAD+08B/0FUf8AwMP+Hnn7Av8A0dN8J/8Aworaj+xc0/6A63/gAf2ngP8AoKo/+BlPUf8Agpz+wPJp2oxp+1L8Jy8mnX0aD/hI7YbnktJkRRweSxAHHJ44zVRybNFKL+p1rKS+x5/L+u+wf2ngP+gqj/4H/wAP+X3n50/8Elf2/wD9jT4afsH/AAh8H+O/2h/hv4Y8T6ZqvxNkv9E1XXILe+tU1D4neLtRsnmhYkqtzZXUFxEcfNHIrcZxXrZ9lWYV8zr1aWFqyhKNC0lG6dqME/uaaPPyrH4OlgKUJ4mlGSlVdnLXWo7fgk9d77R2P0i/4eefsC/9HT/Ccf8AcxW39Cv8/wAud3j/ANi5p/0B1v8AwA9D+08B/wBBdFf9v7i/8PPf2Bv+jqPhR/4UUH/xyj+xc0/6A63/AIAH9p4D/oKo/wDgYf8ADz39gb/o6j4Uf+FFB/8AHKP7FzT/AKA63/gAf2ngP+gqj/4GH/Dz39gb/o6j4Uf+FFB/8co/sXNP+gOt/wCAB/aeA/6CqP8A4GH/AA89/YG/6Oo+FH/hRQf/AByj+xc0/wCgOt/4AH9p4D/oLor/ALf3D/h57+wN/wBHUfCj/wAKKD/45R/Yuaf9Adb/AMAD+08B/wBBVH/wMP8Ah57+wN/0dR8KP/Cig/8AjlH9i5p/0B1v/AA/tPAf9BVH/wADD/h57+wN/wBHUfCj/wAKKD/45R/Yuaf9Adb/AMAD+08B/wBBVH/wMP8Ah55+wL/0dP8ACj/worf+rn+X5Uf2Lmn/AEB1v/AA/tPAf9BVH/wMT/h55+wL/wBHTfCf/wAKK2o/sXNP+gOt/wCAB/aeA/6CqP8A4GH/AA88/YF/6Om+E/8A4UVtR/Yuaf8AQHW/8AD+08B/0FUf/Aw/4eefsC/9HTfCf/woraj+xc0/6A63/gAf2ngP+gqj/wCBnzh/wT8+M/wu+On/AAVL/wCCjXjj4R+NtC8e+Err4Kfsb2MGveHrxL7TpbvTdJ+JUF/bpOnymW0mkSOZf4WYDvX0f1evhcly+liKcqVT6xjnyyVnaUqLT9Go3+e6s1LzKValXzTHTo1I1IOhg1zRd1eMaikr+T/rQ/d+uA9EKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/9b+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8Rf2ufBXg7xz/wAFcv2MNH8a+FPDni/ST+y18e5zpfibRtP1zT/Ph8V+GfKn+x6lbXNv50W9/Lk8sum9guMk11VatSlkmLlTnOEvrdBXhJxduR9V/X3HC4QnmlBTjGaWEqySlFSV1Nd7/ivNXPuz/hmf9nL/AKIJ8G//AA23g/8A+U1fL/XsZ/0FYj/wbU/+WHs+wof8+aX/AILiH/DM/wCzl/0QT4N/+G28H/8Aymo+vYz/AKCsR/4Nqf8AywPYUP8AnzS/8FxD/hmf9nL/AKIJ8G//AA23g/8A+U1H17Gf9BWI/wDBtT/5YHsKH/Pml/4LiH/DM/7OX/RBPg3/AOG28H//ACmo+vYz/oKxH/g2p/8ALA9hQ/580v8AwXEP+GZ/2cv+iCfBv/w23g//AOU1H17Gf9BWI/8ABtT/AOWB7Ch/z5pf+C4h/wAMz/s5f9EE+Df/AIbbwf8A/Kaj69jP+grEf+Dan/ywPYUP+fNL/wAFxD/hmf8AZy/6IJ8G/wDw23g//wCU1H17Gf8AQViP/BtT/wCWB7Ch/wA+aX/guIf8Mz/s5f8ARBPg3/4bbwf/APKaj69jP+grEf8Ag2p/8sD2FD/nzS/8FxD/AIZn/Zy/6IJ8G/8Aw23g/wD+U1H17Gf9BWI/8G1P/lgewof8+aX/AILiH/DM/wCzl/0QT4N/+G28H/8Aymo+vYz/AKCsR/4Nqf8AywPYUP8AnzS/8FxD/hmf9nL/AKIJ8G//AA23g/8A+U1H17Gf9BWI/wDBtT/5YHsKH/Pml/4LiH/DM/7OX/RBPg3/AOG28H//ACmo+vYz/oKxH/g2p/8ALA9hQ/580v8AwXE/L/8A4LA/AX4HeG/2K77U/D3wb+F2hakPj5+zBaDUNI8CeGdOvRa33xz8GWt7bC5tNLhm+z3ltJJb3UO7y54HeKQFGIb2sgxeKnmKU8RXkvq2MfLKpNq6w1Rp6ylqmrp9PO94+dmtCisG5KlTTVfDWapxvZ1opr5rfXXZ3P07g/Zn/ZzMEBPwE+DZJghJJ+G/g/n92v8A1Bq8X69jP+grEf8Ag2p/8mvy+89H6vQ/580ku3s46Ev/AAzP+zl/0QT4N/8AhtvB/wD8pqPr2M/6CsR/4Nqf/LA9hQ/580v/AAXEP+GZ/wBnL/ognwb/APDbeD//AJTUfXsZ/wBBWI/8G1P/AJYHsKH/AD5pf+C4h/wzP+zl/wBEE+Df/htvB/8A8pqPr2M/6CsR/wCDan/ywPYUP+fNL/wXEP8Ahmf9nL/ognwb/wDDbeD/AP5TUfXsZ/0FYj/wbU/+WB7Ch/z5pf8AguIf8Mz/ALOX/RBPg3/4bbwf/wDKaj69jP8AoKxH/g2p/wDLA9hQ/wCfNL/wXEP+GZ/2cv8Aognwb/8ADbeD/wD5TUfXsZ/0FYj/AMG1P/lgewof8+aX/guIf8Mz/s5f9EE+Df8A4bbwf/8AKaj69jP+grEf+Dan/wAsD2FD/nzS/wDBcQ/4Zn/Zy/6IJ8G//DbeD/8A5TUfXsZ/0FYj/wAG1P8A5YHsKH/Pml/4LiH/AAzP+zl/0QT4N/8AhtvB/wD8pqPr2M/6CsR/4Nqf/LA9hQ/580v/AAXEP+GZ/wBnL/ognwb/APDbeD//AJTUfXsZ/wBBWI/8G1P/AJYHsKH/AD5pf+C4h/wzP+zl/wBEE+Df/htvB/8A8pqPr2M/6CsR/wCDan/ywPYUP+fNL/wXEpan+zR+zmumamw+AnwcBXTdQZSPhv4QBDLZzEEEaOCCCARg9u/FVHG4xyivrWI1kv8Al7U7/wCN/l94PD0Hp7GlZ/8ATuP/AAfy+8/NH/gjt8BPgb4k/wCCffwZ1fxF8G/hdrurXOrfFNbjU9Y8B+GNR1Cdbf4q+MbeBZry70uaeVYLeGKCIO5EcUaRrhVCr7HEGKxNPNcTGGIrxio0LKNWdtaFNv7Uerb9X0veXm5RRovAUpOjSbc6t37OOtqkvnrfbVaaWu+b9O/+GZ/2cv8Aognwb/8ADbeD/wD5TV4v17Gf9BWI/wDBtT/5Yel7Ch/z5pf+C4h/wzP+zl/0QT4N/wDhtvB//wApqPr2M/6CsR/4Nqf/ACwPYUP+fNL/AMFxD/hmf9nL/ognwb/8Nt4P/wDlNR9exn/QViP/AAbU/wDlgewof8+aX/guIf8ADM/7OX/RBPg3/wCG28H/APymo+vYz/oKxH/g2p/8sD2FD/nzS/8ABcQ/4Zn/AGcv+iCfBv8A8Nt4P/8AlNR9exn/AEFYj/wbU/8Algewof8APml/4LiH/DM/7OX/AEQT4N/+G28H/wDymo+vYz/oKxH/AINqf/LA9hQ/580v/BcQ/wCGZ/2cv+iCfBv/AMNt4P8A/lNR9exn/QViP/BtT/5YHsKH/Pml/wCC4h/wzP8As5f9EE+Df/htvB//AMpqPr2M/wCgrEf+Dan/AMsD2FD/AJ80v/BcQ/4Zn/Zy/wCiCfBv/wANt4P/APlNR9exn/QViP8AwbU/+WB7Ch/z5pf+C4h/wzP+zl/0QT4N/wDhtvB//wApqPr2M/6CsR/4Nqf/ACwPYUP+fNL/AMFxD/hmf9nL/ognwb/8Nt4P/wDlNR9exn/QViP/AAbU/wDlgewof8+aX/guIf8ADM/7OX/RBPg3/wCG28H/APymo+vYz/oKxH/g2p/8sD2FD/nzS/8ABcT4Z/Ys8G+EfA//AAVj/wCCj2i+C/C3h7wjo0fwO/Ywnj0nw1o9hommpPc6N8S5LmZLLTre2t1luHVXmkWMNK6hn5HzfVU6tSrkeXyqzlUl9Zxy5ptylZToWV229Lu2v3XPGjCMM1x0YRjFKhg3aKSV3Go27JJXb30++x+2lcZ3BQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAH//X/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfppXyB7gUAFAH4vaP8Yv+Ck/x+/aP/a88Cfs+eKv2avCXw6/Z2+Llp8NNMi+JOgeLb7xFqP2nwro3iM3ctxo8jWrop1TyeY42ynTGC32WGyfK3gsDXxCxUquJoupL2coKCtNqyutNrq7187e74k8Xj6mJxNKg8PGnQq8keeLcpJxTu7JLquvqk2eq/8ACA/8Fmf+isfsU/8AhK/EOtf7IyX+TG/+DKY/aZr/AD4X/wAAkH/CA/8ABZn/AKKx+xT/AOEr8Q6P7IyX+TG/+DKYe0zX+fC/+ASD/hAf+CzP/RWP2Kf/AAlfiH/9b+f5Uf2Rkv8AJjf/AAZAPaZr/Phf/AJHzF8Cfit/wV/+N/xI/aV+HemePv2O9LvP2cvimnww1m8vvC3j022tXz6Dpuu/btNEUrutqItRSEi4VJTIjEKFIretkWS0oYeTWNft6fOvfp6WdtXpZuz0/OyZhRxmaVp14J4SLoVPZv3Z+97t7q7/AE01Tt7vN9O/8ID/AMFmf+isfsU/+Er8Q6w/sjJf5Mb/AODKZv7TNf58L/4BIP8AhAf+CzP/AEVj9in/AMJX4h0f2Rkv8mN/8GUw9pmv8+F/8AkH/CA/8Fmf+isfsU/+Er8Q/wD638/yo/sjJf5Mb/4MgHtM1/nwv/gEjqf+CeHx+/aI+Md1+1h4G/aWn+Ht949/Zz/aN1X4Mpqvw0sNT07w7qthp3g7wr4hF5HBq0st4ZGn16VN8nl5VADGMbq8XPMBhMDPCfVPa+zxGFjXftWnJN1KkbaXVrQXX79Doy7FV8SsTHEKmp4fESo/u00mlCEr66u/M9+xxn/BZv8A5Mdv/wDs4T9lb/1fXgmlw9/yMl/2C43/ANRqo81/3KX/AF/wv/p+J+qMH+og/wCuEP8A6KWvDPRJaACgD8w/26fjr+1X4L+Pv7H37P8A+yxqHwq0bxB+0PN8Yzres/FXTdZ1HSbCH4b+HNH121W2XRZUuY5Llb26iclHUt5WdqhjX0OSZdg8bSxtXF+2th1Q5VRcU/3kpRk3zafy7Po9ubmj5eYYnE0auFo4b2SlXdXmdVNpKEYvS1u/du9rLRmf/wAID/wWZ/6Kx+xT/wCEr8Q69b+yMl/lxv8A4MpmPtM1/nwv/gEg/wCEB/4LM/8ARWP2Kf8AwlfiHR/ZGS/yY3/wZTD2ma/z4X/wCQf8ID/wWZ/6Kx+xT/4SvxDo/sjJf5Mb/wCDKYe0zX+fC/8AgEj5k+KfxV/4K/8Awx/aI/Zm/Z+vvHn7Hd/q37SCfFZ9G1i18L+PBp+if8Kt8PaXr99/aavKs7m/i1OOG0+zxOA6SGbaoBrankeSzo4mtbGpUPZe7zw972kuVWei30aur9L2alz1MZmlOvQo82FbxCqWfJPT2aUn26PdXt16I+m/+EB/4LM/9FY/Yp/8JX4h1j/ZGS/y43/wZTOj2ma/z4X/AMAkH/CA/wDBZn/orH7FP/hK/EOj+yMl/kxv/gymHtM1/nwv/gEg/wCEB/4LM/8ARWP2Kf8AwlfiHR/ZGS/yY3/wZTD2ma/z4X/wCR5tovxo/wCCifwd/bU/ZQ+A/wC0n4m/Z18V+AP2ibL4xSzS/C7QfFNhrulz/DTwtZ61CWuNalW38u6udQt1KojExxyA7SUaufHZTllPLsXicMsSquHlR5VVlFwaqS5enz6ffoKlisfHGYahXdCVOuqrbpxkpL2cU93dbvs+l7H7D6p/yCtV/wCwXqX/AKRT18lD44/4o/me2fl7/wAEXP8AlHX8E/8AsMfFn/1bfjWva4j/AORvif8ADQ/9MUjzMn/5F1H/AB1v/TjP1Qrwz0woA+Z/2zvi54m+AP7JP7SPxv8ABcGn3Pi74TfBrx54+8N2+rRvNpc2seGdDutSsY9QiiZJJLR5oFEyRujsvAYZrsy6hDFY7CYeo2qdfEU6U3H4uWckny30vrpc58XVlQwuIrQtz06U5x5ldcyjpdJq6v5/fY+FfhrZ/wDBZD4i/DnwD8QLT4nfsX2Vp468F+F/GNrZ3Hhb4gG4tLfxNoljrUNtOUZkM0Ed6sUpRmQujFDtxu+tlk+SxlOPLjfdnOPx01flk439HbTyPLhXzWcIT58L78Yy0hK3vJPrbv2+47b/AIQH/gsz/wBFY/Yp/wDCV+IdT/ZGS/yY3/wZTK9pmv8APhf/AACQf8ID/wAFmf8AorH7FP8A4SvxDo/sjJf5Mb/4Mph7TNf58L/4BI8T/aS8T/8ABYj9nb9n74zfHnV/iL+xrrOlfB/4c+KPiFqOk6d4W8fC/wBSs/DOmy6jPZ2TTvHAtzOkJSIzOsYY/MVGTWtDJclq16NHlxqdapGkm6kLJy2b0lovRmOIxWaYehWrOWFkqVOU7ckteVX/AJo/n9253nw907/gsj4+8A+CPHVp8T/2LrS18aeEfDfiy2tJ/C3xBM9tB4i0ez1eG3mKMyGaGO8WOXYxTerbcLtFZyyfJVKceTG+7Ocf4lP7MnG/ztc0hXzSpCE+bCrmjGVuSXVeZ2H/AAgP/BZn/orH7FP/AISvxDpf2Rkv8mN/8GUyvaZr/Phf/AJB/wAID/wWZ/6Kx+xT/wCEr8Q6P7IyX+TG/wDgymHtM1/nwv8A4BI8P/aY8V/8FiP2cf2e/jN8fNX+Iv7G2s6V8H/h34l+IGoaTp3hbx6L/UbTw7YPezWlmZ3jhFxMqFYzK6xhvvMAc1pRyXJalalS5canVqKmn7Sna7vvf/ga/dLKvic1oUalXmwsvZwlK3LLWy+X9d9j9dPg54p1Xxx8I/hb4111bZNb8X/DvwX4n1dLNWS0TU9f8Oabqt8tqjszrAtzdSiJWZmCBQTnO74rEQjTr16cL8tOrUhG+9ozcVe1+i7/AHnuUpOdOnOW86cJNaWTlFNpW6Xbtv8Amo/C/wCyp/yl2/4KQ/8AZCf2Kf8A0yfE2vq8P/yIcv8A+wnH/wDpdA8b/mb4/wD7B8F/6RUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//0P7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH6aV8ge4HXgdT0z/kfz/KgD8RvgR+1j/wAFQ/2nPD3i/wAf/B34FfswSeAtF+KPxF+HmkXHiz4meINH127HgLxRqHhyW7vLCPRbiKJrh7HzRsmYfNxnk19pLh/LIKmqmLxcZzo06rUaMZRTnFNpPmV7PT8dLpR8CnmGY1eeVLC4aUI1KkE51Zxb5JW2Wn569Xa5g/Aj4Of8FfPgX8SP2lPiNpnwn/ZJ1u8/aR+KFt8TtY0+7+LHiC3g8PXtt4b0nw4NNsZY/D7tcwNDpUdwZZVRvMlZQMDNezGOXLD4XD+1xXLhabpqXs0nNOTd38aW706dHq0c0I5pCrXqqjh2681Np1WuV8qVk7O+3Xbayvc+nf8AhN/+Cy3/AEQX9jv/AMPH4l/+Zul7PLf+f+M/8Aj/APKzX2ma/wDQPhv/AAdL/wCVijxt/wAFliQP+FC/sd8/9Vj8TH+XhsH/AD36UOGW/wDP/Gf+AR/+QX5/eHPmv/PjDf8Ag6X/AMrPnj9mf9sP/grN+098P9T+Ingj9nz9k+20fS/HvjnwBPHrHxY8SWV02reA/El/4b1WRIRoEoa1e9sJTbS7gZIirkKWxWtbDZfQqckq+K5nCNTSnFpKcVJX+K7s9Vp5tXSjjQxWZYiDqQw+H5VOcNasou8JOL05ZdVp9+u0cv4F/B//AIK+fA34j/tJ/EXTPhP+yTrV5+0h8U1+KOsafdfFnxBBD4evl0LTdC/s2ylTw8zXNuYtNSbzZQr75GUKAuWqtPLqsKEHVxS9hTVNNU1eS1d7tOzu39lestGKlTzOjOvNUcM3Xn7Rp1X7rtsny6/d063TPpr/AITf/gst/wBEF/Y7/wDDx+Jf/mbrD2eW/wDP/Gf+AR/+Vm/tM1/6B8N/4Ol/8rAeNv8AgsseP+FC/sd/j8Y/Ex/l4bB/z36UOGW2/j4z/wAAj/8AIx/NBz5r/wA+MN/4Ol/8rPfP+CdX7TXj/wDa3/Zi0T4xfE/wr4e8GeN5vHPxQ8Fa7oHhW/utT0K2uvh54913wa0tjfXkUNxPHdf2P9o3PEnMnAxwuWKoQw9f2dOUpwcITUpK0nzwjLXaz17fdY6MFXqYigqlSKhPmnFqLuvck479du0fLqfM/wDwTo/5Lz/wVV9/2/PFH/qrfht/n/8AXXz/ABJ/zKvPLab+6tXX9a/fcrKPjzN/9R8vxpU/8u33B/wWb/5Mdv8A/s4T9lb/ANX14Jrk4e/5GS/7Bcb/AOo1U6M1/wBykv8Ap/hvwrw/z7/efqjB/qIP+uEP/opa8M9EloA/LP8AaN/ak/bA039s/Rv2S/2Vfhh8H/GV2/7O9v8AHbX9a+Kfi/VfCy20E3jrU/Bv9nWB0/Tb9bgh7S3n+cI2HkPQLu+jyvKcFi8DPF4qvXpuOJdCMaVOM/8Al2p3d2v63tdOPlYzGYqlioYbDUaVVuh7aTqzcP8Al5KFlaPSy6r57nzd8Tfgv/wV7+Jf7Qn7Nn7QF78Kf2StO1X9nD/hZ/8AZGhQfFfX5bPxD/ws3w/YaBefbbhtAElr/Z0Vis8HlJJ5ruQ5UABvosBhcswFLFUoV8VUWJ9km3RS5PZyctuaSd72f6/Z87Ef2piKuHrewwsHh/aWj7WTUvaJLqrq1r6t+W/u/Uf/AAm//BZb/ogv7Hf/AIePxL/8zdb+zy3/AJ/4z/wCP/ysv2ma/wDQPhv/AAdL/wCQf5/eH/Cb/wDBZb/ogv7Hf/h4/Ev/AMzdHs8t/wCf+M/8Aj/8rD2ma/8AQPhv/B0v/lZ89D9sH/grOf2pX/ZU/wCGff2Tv+E6T4Kw/G43X/C2PE39jf8ACMz+LJ/CKQ/bhoIJ1D+0IHY23lBRBiTzCTsbT6tl/sPrDr4rlVZ0UvZx5ubkU+tklbW9tdO/u5fWsy9v9X9hh+f2Sq/xZW5XJrfk3urWt536GV8UvhB/wV9+KH7Q/wCzT+0He/Cf9knTNW/ZsT4qpo+g2/xZ8QzWfiIfFPw/pmgXxvrlvD6yWp0yLS457fyo5BK8jK+AoK1CeX06Nej7TFSVf2V26avF0586d9L69oq3d7SmpTzOpWoV3Sw6lh/acsfatqXtYqL15Fy2Ub/avfpoj6a/4Tf/AILLf9EF/Y7/APDx+Jf/AJm6x9nlv/P/ABn/AIBH/wCVm/tM1/6B8N/4Ol/8g/z+8P8AhN/+Cy3/AEQX9jv/AMPH4l/+Zuj2eW/8/wDGf+AR/wDlYe0zX/oHw3/g6X/ysm/Zo/at/bG1r9tLxF+yZ+1T8Lfg54Mnsf2erH45aNrPwt8Yar4q+1QX/je48HxWF8+oafYJAQ9ldTFY0YgeWSfmNFahho4VYnD1K0v30qLVWKVv3fPfS1720089LsqhiMW8S6GIp0ofulVTpzcvtNWd4Ly6997Iyv2xv+Umv/BLL/rw/a3/APVe+Ga4Mb/yJsz9cJ/6dmaz/wCRll/+HFf+kQP071T/AJBWq/8AYL1L/wBIp6+Eh8cf8UfzPcPy9/4Iuf8AKOv4J/8AYY+LP/q2/Gte1xH/AMjfE/4aH/pimeZk/wDyLqP+Ot/6cZ+qFeGemfEX/BQ39pbx3+yX+zFrvxk+GnhfQPGXjaDx98JfAmhaB4nvrjTdDubz4nfEXw/4Dimv721imngitJNdS4LpE+BGSQACa9TJ8DTzHHU8LWnKnTlTrTlOC5pL2VKVTRO1/h/4fY4swxM8JhZV6cYzmqlKEYybUW6tRQ1a1Vr3/VbS+Kv2i/AX/BYL9or4BfGP4D6t8H/2RdA0v4xfDjxV8PL/AFuy+LPiG5u9ItPFWlT6ZNqFtbyeH0Sea1ScyRxyMiuy4LLk7vpsJlWVYXE4fFxxOMm6FWnWUHQiublfMk3zSt93Trdo8uvWzTEUKtB4bCxVWnKDkqs3JXW9mrX/APAfyR6J8NpP+Cxvw4+HfgP4e2fwQ/ZA1C08CeDfDHg61v5/i/4jimvrfwzoljosF3NEvh1ljluY7JZpI1ZlR3KhiAC3qTjl05zn7bFrnnKVlTSS5ne3wy2v3++zZnB5pCEYKhhmoRjFP20teVWv/D62O0/4Tf8A4LLf9EF/Y7/8PH4l/wDmbqfZ5b/z/wAZ/wCAR/8AlZXtM1/6B8N/4Ol/8rPnv9p79sH/AIKz/stfCv8A4Wv44/Z9/ZPudB/4Tn4c+A/L0f4r+Jb68Gq/EnxlpPgrRXNufD8I+zR6lrFvJdSmQeTbrJIAxXDa0cNl9eqqUa+Ku4VJ2lCLVqcOeXSGtl/efZXRjXxWZYen7SdDD256cLKrJtupNQX2Fs5Xeu3exs/tH+D/APgsL+0b+z/8ZPgJq/wc/ZF8PaX8Y/hz4o+Hmoa5ZfFzxFdXmkWnifTZdOmv7a2l8Oxxzz2ySmSOKR1ViMFhnNKg8to1qNf2uMl7KpGqounHVx1S+FW37vt5jrxzSvRq0XRw0VVhKDarN25la9nBX+/7rHd/D24/4LHfD/wF4I8B2nwP/Y/v7XwV4R8OeEra+m+MHiSOa8t/Dmj2ekQ3Usa+HGWOS4js1lkRWYKzEAkDNTOOWznOftsWueUpWUIpLmbdrcj2v3fq9y4PNIQhD2GGfJGMb+2kr8qSvb2el7XOw/4Tf/gst/0QX9jv/wAPH4l/+Zup9nlv/P8Axn/gEf8A5WV7TNf+gfDf+Dpf/Kzw39oP9sL/AIKlfss+B9C+K3xg+An7Lo+HkvxU+Efw88QTeFPij4i1fXrWL4o/EPw/4Ehu9P0+XQreO4ltJdbFwVkmRQI8kgCtKeHwFaTp06+K51Sq1IqcFyv2cObflVunfy5dyKmJzGiozq0cOoe0pwfLVlJ/vJqCaXLHZtX1+69z7a/4Koc/8E2P25D6/sy/FL/1Hrj6fy/KuXB64vBPviKX6+n5fcdeO/3PEf8AXqR7T+zd/wAm7/Ab/sjXwx/9QrRa+Bxf+9Yn/sIrf+nJHrUP4FH/AK9U/wD0hHxx+yp/yl2/4KQ/9kJ/Yp/9MnxNr6nD/wDIhy//ALCcf/6XQPI/5m+P/wCwfBf+kVD9kK5jsCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP/R/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6Ufe/xU8Xz/D74YfEfx7a2kV/deCfAfi7xdbWMztFDeT+G/D+oaxDayyKrNHFcSWaxSOqsyo5IGQN3ytCn7WvRpXsqlWnTv255qN9dNL9T2qkuSnVmtXTpznbvypv9PP8AWP5N/Aj9pL/grR+0B8H/AIdfGvwZ+zd+ylF4U+JfhjTfFugR6r8Z9es9SXS9ViFxaC+tR4ccQXHlFfMjy2xsgZGK+vq8P5XTq1KTxuL5qcuV2w8Wrrs+dX+70vZnh0cfmVanCrHDYflmuZJ1WtHt08+8uzel5cL+yT8JP+Cvf7J3wy1j4a6J8FP2TvFVprHxI+IXxFk1K/8AjLrdjPFdeP8AxNf+JbnThDF4elRodPlv2toZiweVIw7opOK92q8uquDdXFR5KVOlZUU78kVG91KO9rv9LNy5cPDMqEZRVGg+apUn/Gtbnk3b4Zd+/wA3qfUP/Cwf+Cyf/Rt/7IP/AIfHX/8A5m6z9nlv/QRi/wDwT/8AdDf2mZf9A9D/AMHf/czlvHXxt/4LB+AvBPjDxzq/7Nv7JD6V4M8LeIPFepJbfG7xBLcPYeHtKu9XvFgi/wCEcHmTNb2koijyu99q7lzupxpZdKUYqvi25SUdaVt3a93N9Xr9+u0pnVzKEZSeHoWjFyf76+iV9uRX27/ccn8Cv2n/APgrl8efhF8OvjP4S/Zq/ZOh8NfEfwvpfizRIdT+NXiC1v00/VLdbi3W7t/+Ebk8mYKw3pl8HI7ZqquHy6nUqUZYjFc0JOLcaV1fXb95fTzX36k0sRmNWnCrHD0LTjdL2zWj6/B+rs+6Z5v+yZ8J/wDgr5+yj8MtW+Gmi/BT9k7xVa6t8R/iJ8RZNSv/AIza3ZTxXXxC8U6j4outOWGLw9IjQ6fNqDWsMxZXljjDuik7VvEVMuxNRVJVcVC0IU+VUU9IRtfSS1dtdei0VmZ4anmWGpuCo0JXqVJ/xrW55OVvgd7X3vdrfltyx+nf+Fg/8Fk/+jb/ANkH/wAPjr//AMzdY+zy3/oIxf8A4J/+6HR7TMv+geh/4O/+5nI/ED44/wDBYL4eeA/Gvj/WP2bP2SJNJ8D+E/EXi/U47X43eIJbl9P8OaRd6xeLbxf8I2PMma3s5BFHn532rxmqhRy6c4QVfFtzlGKvRtrJ2X2+78rb+UpnWzKEJzdChaEZSf76+kVfb2fkfoN+yL8Zta/aH/Zo+CPxw8RaLY+Hdb+KPw98OeMtT0PTLmS8sNLu9Zso7qaztLqZIpbiCF2KxyyRo7L1UGuStTVGvVpRk5RpzcU2rN2bT891s3K3fY7cNVdahSqtWdSEZNLpdfL/AIG2u58U/wDBF7/kyWL/ALOE/aj/APV8+Oq6Mw/3lf8AXml/6bpnNlv+6r/r7X/9OyML/gnR/wAl5/4Kp/8AZ/fij/1Vvw3r5riX/mUf9iyH/qRXN8o+LNP+xhL/ANNQE/4LN/8AJjt//wBnCfsrf+r68E1ycPf8jJf9guN/9Rqptm3+5v8A6/Yb/wBP0z9UYP8AUQf9cIf/AEUteGekfkTrf7WP7fHxB/au/ai+Av7MvwO+A3ijwn+zdrHw+0e/8R/Ef4kav4V1fVZ/Hfgyy8WwMlja6NewslsLiW3Zo5uAiEqpcrX1eEyPA1cBhMXXxWIpyxKqPlhSjOK5JuFtZJpu1/wSdrni1MdjPreJw9CjSnGh7Nc06ji5OcFJ6WVrO/V/I8bj+EH/AAV6i/bD/wCGvV+Cv7J51w/ACH4B/wDCJH4za3/Z39mweN7vxqNe+3f8I6JftZnuzZfZfK2eWgk80sdre7hMPlmFwksIq+KlGVf27n7BJ35FDltzPtdvzskrXOSf9pTxSxLoYdNUFR5VVf8AO5817PW72tbtbQ+pf+Fg/wDBZP8A6Nv/AGQf/D46/wD/ADN1r7PLf+gjF/8Agn/7oae0zL/oHof+Dv8A7mH/AAsH/gsn/wBG3/sg/wDh8df/APmbo9nlv/QRi/8AwT/90D2mZf8AQPQ/8Hf/AHM+fPhn+2b/AMFYPij8Z/2hfgjoP7M/7K0Xij9nHWfA2i+NJr34za/Bp891498I23jDSTpVx/wjp+2Rx6dcoty+1PKnzH82C1azw+XQhRm8RibVozlFKlraEuV8y9o2nfo7ej0ZjTxOY1KlamsPQ5qMop/vnrzR5r/w7aX8u+t/dxv+FVf8Fff+Gwn/AGu/+FJ/snDXH+ANv8Bv+ES/4XNrX9n/ANm2/jS58ZDXft3/AAjvnfa2uLk2htvL2eWu/wAzJp8+W/Vnhva4qzre25/Zat8ihZrXpfZ7aWbXNKfZ5l9a+sqlQ/gqi4e07S5uZStpv/K79lufTn/Cwf8Agsn/ANG3/sg/+Hx1/wD+ZusfZ5b/ANBGL/8ABP8A90Oj2mZf9A9D/wAHf/cw/wCFg/8ABZP/AKNv/ZB/8Pjr/wD8zdHs8t/6CMX/AOCf/uge0zL/AKB6H/g7/wC5nc/sJ/tV/tE/HL4p/tY/Bn9pL4a/Dv4d+OP2aPFvw+8NuPhx4pv/ABXo+sJ448F23jBbhr6+sbBle3gvLeLbHEy7t4J4BqMTRo0qeGq0J1JwxEZy/ex5ZLlqKC01s9319Y3sVhMRXrVcTSr04U54eVOL5JcyfPDmWto9N9N76q1pcPb/APKbPWv+0dHhv/1e3iKrf/Irf/Ya/wD1HD/mZP8A7BF/6cZn/tjf8pNf+CWX/Xh+1v8A+q98M15+N/5E2Z+uE/8ATsy5/wDIyy//AA4r/wBIgfp3qn/IK1X/ALBepf8ApFPXwkPjj/ij+Z7h+Xv/AARc/wCUdfwT/wCwx8Wf/Vt+Na9niL/kbYj/AAYf/wBR6R5uUf8AIvpf9fK//pxnov7fH7UPxx/Z5v8A9ljwb+z78PvA3xC+If7S3xxvfg/p1j8QPEV74Z0HTDbeBdd8ZDUJNSsrO+dWZNDlgw8G0b1wQSAyyXLsPmM8WsRVqUaeGw8a3NTjzyd6ihblvHv3+S3k8wxdXC/VlRpwqTr1vZWnJxS93mvp6foup8UftcfB3/gr1+1j8G3+D+s/BX9k/wAKWL/EH4V+P/7XsPjLrV7cC5+FvxB8P+P7PT/Im8PRJ5OqXOgR6fPLvDQxXDyqHZFWvpsuy/LMuxUcVHE4qpKMKtNReHSVqtOVNu/O/hUr7dLa3R5mMeZ4ug6LoYeKdSlUv7X/AJ9TU7W63atv9+h9Tj4gf8FkwAP+Gb/2QcAAf8lx1/t/3LQ/l+Vdip5akl9Yxbst/Yb/APk6/L7i+fMlp9Xoaf8AT7/7R/n94v8AwsH/AILJ/wDRt/7IP/h8df8A/mbp+zy3/oIxf/gn/wC6B7TMv+geh/4O/wDuZ8+/Gf8AbM/4KwfBDxx+zv4F8U/sz/srzar+0j8Vbn4S+Cn074zeILm2g8Q23hHXPGMkmqyDw6v2Sz/s3QrpVm+fM7RR7RvBrWnh8uqQrzjiMVbD01VnzUre65qCt77u7+X32MauKzGlOhCWHoXr1HTjeq2r8rlraMbbd/uv72N+118Kv+Cvv7Wfwc/4U/rfwT/ZO8K2P/Cw/hb8Qf7X0/4z63e3H2r4X+O9E8dWdh9nl8OxoYtTuNFjsZ5d6tDFO0qhmULVYeeW4esqyq4qbUKkLOirWqwcG/ieyd91tbqycVTzHE0vZOjQS9pTnf2t/wCHNTS2VrtJPV2+8+mh8QP+CyYAA/Zv/ZBwBgf8Xy8Qdv8AuWh/L8qwVPLbL/aMX/4J/wDt1+S9FsdHtMz/AOfFD/wd/wDaP8/vF/4WD/wWT/6Nv/ZB/wDD46//APM3R7PLf+gjF/8Agn/7oHtMy/6B6H/g7/7mcBd/tg/8FEPhH+0L+yR8MP2kPgL+z54e8C/tN/GDUvhSniH4ffE/WfE+uaNdaZ4H8QeNJbtdNuNEtIGQ2+hmAGSdQWl4wVp/V8HOjiZ0K2IlOhSVW1Snyxac1BK/O+7e3ToQ8VjaVbDQrUaUYV6rp3jU5muWnKbaXJFP4e9/Jby7f/gth/yY0v8A2dB+x3/60f8AD6owH+9f9y2L/wDTRrmX+7L/AK/4b/0/TPcP+CqH/KNj9uT/ALNl+KX/AKj1xWWD/wB7wX/YRS/U0x/+54j/AK9SPaf2bv8Ak3f4Df8AZGvhj/6hWi18Di/96xP/AGEVv/Tkj1qH8Cj/ANeqf/pCPjj9lT/lLt/wUh/7IT+xT/6ZPibX1OH/AORDl/8A2E4//wBLoHkf8zfH/wDYPgv/AEiofshXMdgUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB//9L+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9j/tL/wDJuPx//wCyKfFP/wBQbXa+Zwf++YT/ALCaH/p2B7Fb/d8T/wBg9b/0hnjn/BLb/lHj+x9/2QvwP/6a46++xf8AvmK/6+v9Tx8v/wBywv8A15h+R9EfHv8AaK+FH7NXhKw8Y/FjxDJo1hrWuWnhnw7p1hp19rXiDxP4jvklltdD8OaFpkNzqWsalLFDLL9ms7eV0hR5XCoC6xTpVK0nGnHmaTk23yxjFfalLZJPTX06o3rVqdCKlUdk3ZJJtyb6RS1bMT9n79qj4OftL2/ikfDLW9Rk1rwPqNvpXjTwj4l0LVfCnjDwre3lut3ZR654b1y1stUso761Zbiynkt/IuovnhkYBqVSlUo8ntFG1RXhKMrxdt7NXT17W87bSmjiKVfmUG+aDtOMk4yi3smpWautVpt2Nr9pz/k239oL/siXxU/9QXXadH+LS/6+Q/8ASkPEfwK3/Xuf5Hg3/BMn/kwD9kn/ALIj4J/9NcVXi/8AfMV/19f6mOA/3Oh/17j/AOko+q/il8SvDHwe+H3in4meM31KPwt4O0yTWNbk0jSr/XNRisIXjSaW20rTIbi+vDEJBJIlvC7JEskpARGZcoxlOShFJyk7JNpK783Zfe9dtLnTUnGnCVSXwxV3u9Pld/h95S+Dnxd8C/Hn4ZeDfi/8M9WbXPAfj7RrbX/DGrPa3Fi99pl0MwzPaXccVzbscENFNGkikEMo4onCdOc6VRWnTfLJJ31/H8/TSzkqVWFanGpTd4SV4vun/XnffTY5H9qn/k2D9o7/ALIT8Wv/AFA9drTD/wC8UP8Ar9S/9LROI/3ev/15q/8ApDPEP+CY3/KP79kP/shngP8A9NMNVjP98xX/AF+qf+lzMsB/ueG/69RPCf8Agi8D/wAMSxcH/k4T9qPtn/mvPjr/AD/+qtMwaWJV/wDnzS6/9O6f+TM8t/3Vf9fa/wD6dkYP/BOj/kvP/BVT/s/vxR/6q34b181xL/zKP+xZD/1Irm+UfFmn/Ywl/wCmoCf8Fm/+THb/AP7OE/ZW/wDV9eCa5OHv+Rkv+wXG/wDqNVNs2/3N/wDX7Df+n6Z+qMH+og/64Q/+ilrwz0j8vv2Jv+Uif/BWD/sfP2cP/VLabX3+F/5EuVelf/1IZ4FL/kZ5j60P/TcT9bqZ3nz94j/ai+BvhX9oDwJ+y9rXjrToPjj8R/DeteLfCvgWNZrjUbrQNBiaa/1C6eFHg09BFHLJbJePDJdJFI8CSIpZdFRqypSrxg/ZQkoSnsuZ9FtfTd9PN6GMsRSjWjh3L97NOUY9Wl1fbbv99j6BrNa69/68vy+42Pye/Yy/5SL/APBWn/sof7Mv/qhNHrqxP8DAf9e6/wD6dkcGG/3zH/46P/pmB+quo6hY6Rp99quqXdvYaZplndajqN/dyJDa2VjZQPc3d3czOVSG3treKSaaV2VI40Z2IAJrl3surdl5t7Jebb+Z3NpJtuySu2+iW7Pi74P/APBQz9l/44/EDRPhv4G8X6w2ueL7bWb34fX2veE/EPhzw58SrPw+vmaxc/D7xDq+n2ul+K47KD/SnOlTzl7P/S499uPMreeGr04ucoxtFpTUZJyhfbnWjV/NLXRuJzU8ZQqzjCMned+S6sppbuDej+V+67R+3awOo/Jv9if/AJSF/wDBWv8A7Kp+zv8A+qI8P12Yn/c8u/691P8A0+zzsL/vuZf48N/6YH24J/4LZ61j/pHR4a9/+a7eIv8AP/6qb/5Fb/7DX/6jlf8AMyf/AGCL/wBOMoftjAj/AIKa/wDBLHOf+PD9rftj/mnvhn/P/wCuvPxrTybM7d8J1/6ey/zRc/8AkZZf/hxX/pED9OtU/wCQVqv/AGC9S/8ASKevhIfHH/FH8z3D8vf+CLn/ACjr+Cf/AGGPiz/6tvxrXs8Rf8jbEf4MP/6j0jzco/5F9L/r5X/9OMZ/wUO/5OU/4JI/9nz6v/6ob4jV2cNf8zf/ALAIf+pEDHNf4uW/9hn/ALjmfr3XsnQfO/xZ/ak+D/wS+JPwb+FPxE1jVdH8V/HrxEvhL4beV4f1e/0bVfEknm+Ro95rlpayaZpV9dLbzy2sF/cwvcRQyyRIyRuV0hRqVIznBJxpK9Ta6jp71nJNrWzai7dbXuY1K9OnUp05XUqr5YWTtd7JvVK/9W3Pois/6/rf8/vNj8oP+CjH/Jyv/BI3/s+fWP8A1QnxIrqw/wDu+Z/9gdP/ANSEefjf4+X/APYV/wC4qh+r9cp6B8R/GX/goR+zP8DPHniP4ceMfEniTUPEvgbS9O1v4ix+DfBXibxlYfDbSNWtjfaff+PNR8PaZf2nhqK408HUVTUpYpV0/wD01kEBD1vTw1erGM4KKjNtU+eUYuo07PkUpJys3bTrpdS92PLUxlClKUJSk3BXnywclBPVOdr2ulpddb67S+vfCvinw9438M6B4x8JavY6/wCF/FOj6dr/AIe1vTLhLrT9W0bVrWK907ULK5iJjmtru1mimikU4ZHB4xWLUoylGScZRbjKL3Uluv6/Q6YyU4xlF3jJKSa1TTV0z8uP+Civ/J0v/BIn/s9Txf8A+s/fEOuvCfwcz/7A6f8A6fR5uP8A94y3/sJqf+o1Uj/4LYf8mNL/ANnQfsdf+tH/AA+pYD/ev+5bF/8Apo0zL/dv+4+G/wDT9M9x/wCCqAP/AA7X/bj64/4Zl+KXb/qXbissG08Xgkt/rFLz7/1/wxeO/wByxHT9zL5afoe0fs3f8m7/AAG/7I18Mf8A1CtFr4HF/wC9Yn/sIrf+nJHr0P4FH/r1T/8ASEfHH7Kn/KXb/gpD/wBkJ/Yp/wDTJ8Ta+pw//Ihy/wD7Ccf/AOl0DyP+Zvj/APsHwX/pFQ/ZCuY7AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD//T/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfY/7S/8Aybj8f/8AsinxT/8AUG12vmcH/vmE/wCwmh/6dgexW/3fE/8AYPW/9IZ45/wS2/5R4/sff9kL8D/+muOvvsX/AL5iv+vr/U8fL/8AcsL/ANeYfkeFf8FPpNY1Lxx+wv4S8A6xongT4x6t+0Fq+sfDH4seM1Fx4C8CXOgeDLtvEcHiPSm2DXLnxRot9Jpei6XFdWNy1ykt1Ddp9nZa2wiioYqc4upTVFRqUou0pqU1y2fRJrV6rWztdMyzC7eFhBxhUlWbhUnrCHLHW66uSdlrF9nuc3+wlJ4y0X9un9t3wv8AGbxT4V+K/wAbb7w78G/FGrfFj4cWr6T4GfwTNpV/p3hbwK/hx5ryXRfEvh82t3c6g13qeoXOoQXsFzvhi2RIYnkeEwkqUJ0qSlUgqVRe8pcybnzKycXpZqyurcrvcjB8yxeKjUlGpVcacnUhpHkStGNt01rq73vu7Jn6QftOf8m2/tBf9kS+Kn/qC67XNR/i0v8Ar5D/ANKR3Yj+BW/69z/I8G/4Jk/8mAfsk/8AZEfBP/priq8X/vmK/wCvr/UxwH+50P8Ar3H/ANJR9Y/FD/kmXxJ/7J941/8AUZ1SsOsf8Uf/AEpHTU/h1P8ABL/0lnxb/wAEo/8AlHn+y1/2Tax/9KrqujGf77iv+vn6HNgP90o/4T6R/ap/5Ng/aO/7IT8Wv/UD12pw/wDvFD/r9S/9LRtiP93r/wDXmr/6QzxD/gmN/wAo/v2Qv+yGeA//AE0w1WMa+u4r/r9U/wDS5mWA/wBzw/8A16j+X+R+P3/BNP8AYY8e/Gb9nHV/iDon7cf7Uvwa03WP2gP2kkg+H3w11HwbB4R0ZrH42+NbSV9Ni1fQL6+DXrxG8ufOunBuZpdm1Cq13Y7ExhXjH6rh6jVCj79RT5n+7jvZxVtVbX7vtefgcLKpQc1ia9PmrV2owcUl+9ltsvwt6H1L/wAEjPAOo/C/xn/wUo8Bar4+8W/FDUPDP7c3iPTbrx546lsZvFniWSP4Y/DtzqWtyabbWlk97IJBGxt7aJNkUY25GW+U4pmqk8rmoRpqeXQlyQuox/f1laN3LTrutX1v7vfkkHD+0YucpuOPknKW8r0qer1tfTpe991Z83o//BZv/kx2/wD+zhP2Vv8A1fXgmuDh7/kZL/sFxv8A6jVTqzb/AHN/9fsN/wCn6Z+qMH+og/64Q/8Aopa8M9I/L79ib/lIn/wVg/7Hz9nD/wBUtptff4X/AJEuVelf/wBSGeBS/wCRnmPrQ/8ATcT9G/jf8QNb+FXwg+JHxH8NeB/EHxM8R+DfCOsa7oHw+8LW7XXiDxhrVpbN/ZegaXAvzNNf3rQRSMOYrfzphkoFbSEFUnCDmqalJRc5XtBN6ydtdFd/h1OutOVOlUnGEqkoxbjCOrk+iVu7+7fofzFfC74o3Hhn9s79gf4gfFb4KftIT/tJ/Fv4hfHvxP8AGvxR4k+EPiLSoZ9T8WfDzRdB0Lwb4HN7Esh+HXwmsJItP22+yCy02G6167UTXs7N684XoYqMKuHWHpwpRoxjVjJ2U5Nyn/08qu8rN3vom01y+HSrctfDTqUcQ69WdR1ZSpSXvci0jdK0IJ7JK0dXfTm/rIH+c/5P8/zrxFsvLT7vv/P7z6A/J79jL/lIv/wVp/7KH+zL/wCqE0euvE/wMB/17r/+nZHBhv8AfMf/AI6P/pmB+nfjXSvC2u+D/FWieOIrC48F6v4d1nTfFsGqTm20yfw1e6fcW+tw6jcCWEw2MmmyXKXcvnReXA0jeYuNy80W4yTjfmTTjbfmTvG3ndK3/DnbNRcZKfw2fNfRONtU/K17/wDBPx3+G/i/4Zftn/tQ/s96p8FLvwr4c/ZK/YU1PxTb/DLxBZ6hp9l/wuD4r6l4Vuvh2ug/DbTmuBez/DnwDoEt/BdayiG217WnihsTcw2Mktd04VMLQre1jL6zi1F1Fb+FSjL2idRu0eecmtPdtDXR2UvLhOGKxFF0lGOGwkmqcr29pVcXC1NdYQjpfZtxS5bNy/a6vPWy7W/rt+X3HrH5N/sT/wDKQv8A4K1/9lU/Z3/9UR4frtxP+55d/wBe6v8A6fPOwv8AvuZf48N/6YPnD9pL9n/xF+0L/wAFiofDfhz4/fFz9nu50T9gLQNXn8R/B+50O11rW4ZPjT4itV0jU213TdSt206NyLtBDHHL56qS7IClbUqqpZbKTpUqyeMslV5ml+5TbXLfXRrX8NzKtRdbMrRqzpWwi5nTcbte0ejutn5P5a3PP/Ff7K3iz9nj/gqD/wAE2rrxJ+1L8eP2hE8R6Z+1GlrafGC98N3Vv4dOnfD7RjLJow0HR9NZH1AXSrdm4MuVtoBHtw5rhzGuqmSZmlQo0WpYXWknrepu+bm1Vn1ej20HChKlmeAbr1aiccTpUs9oR7d79dNPNn7+6p/yCtV/7Bepf+kU9fnsPjj/AIo/mfSn5e/8EXP+UdfwT/7DHxZ/9W341r2eIv8AkbYj/Bh//UekeblH/Ivpf9fK/wD6cYz/AIKHf8nKf8Ekf+z59X/9UN8Rq7OGv+Zv/wBgEP8A1IgY5r/Fy3/sM/8Accz9e69k6D8xf+ClBxrn/BPAZ4P/AAUV+CPHv/wivxG/x9Pyrqwm+K/7A6n/AKVE48X8WE/7Cqf5SP07PU/U1ynYfk//AMFGP+Tlf+CRv/Z8+sf+qE+JFdWH/wB3zP8A7A6f/qQjz8b/AB8v/wCwr/3FUP1frlPQP51PFGk/Hfxz8ev+CtF9+zN8afhH+zz4bTUtO8FfFfw98YdJ/wCEh13xp470H4KaNBqvxH0Gf7Vp48H+E9e8G3Vj4b0qXUoddsZtQ0261mG2VGkt29FSoxo5b7ehWryScqcqb5VTg691C2vNOMkpPVPl0bkeJKNadbMPYVqdCN1GpGouaUpKnZzWi5ItWS+O7XRaH6sf8E5Ne8J+Jf2Ef2T9Y8C+F9V8F+EJvgh4GttA8L63dNfalpFhpmlR6YkFxftHF9vWV7N7q3vViiS6tp4Z0ijR1RebFqSxWJUpKcvbTcpKyUm7O9lonZ67a383L0cE4vCYfkjyRVKKUb3tZW30v3T6rXW9z5s/4KK/8nS/8Eif+z1PF/8A6z98Q60wn8HM/wDsDp/+n0c2P/3jLf8AsJqf+o1UxP8Agujpc2u/8E+9b0S31S/0O41n9of9k7SoNb0pol1TRptR/aC8C2keq6a0ySQrqGnPMt3ZtLHJELiGIyIyBlZ5bJRxkZWUlGhiW4t3TSpbO1tHt/nsVmkebCON3G9bDq8dGr1obbq+vX8NGfJn/BQ3/gnf8SPAv7CP7WvjK/8A+ChX7YHjiy8MfAT4g61eeDfFOqeBJPDXiaCx0OaaTRdajs/DNvdvpl8F8m6W3nhmMTMEkRiGrXCYuLxWFX1PCx561OKlFT5oN3s4+9uttlb8Jc+Mwk44SvL61iG1Sk7ScbPTZp30fXT77H7Qfs0oY/2dPgGhdnKfBj4XqXb7zY8E6IMnGBk98D8q/NsY74vFPviK3/pyXp+X3H0lD+BR1b/c0rt9WqcVf1e78/Vnx3+yp/yl2/4KQ/8AZCf2Kf8A0yfE2vqMP/yIcv8A+wnH/wDpdA8j/mb4/wD7B8F/6RUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//1P7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2P+0v/AMm4/H//ALIp8U//AFBtdr5nB/75hP8AsJof+nYHsVv93xP/AGD1v/SGeOf8Etv+UeP7H3/ZC/A//prir77FtLGYq/8Az9fW39f13PHy/wD3LC/9eYfkfVPxb+C3wq+PHhN/A/xf8DaD498LtdwajFpmuW7yfYtStd32bU9MvLeW3v8AS9StwzCG+066trqMMwWUAlWyhVlTlzU6nJLbmi+j6Wd015P8Nzoq0qdaPJVgpx3s+j7p9GujVv0li/Bb9nb4J/s7aNqWhfBf4c6B4Csdavf7R1yXS0urnVNdvwgjS71vW9Uur/WdWniiVYoWv76cQRKI4dq5FOpXnWd6tRza2u7JJ62SWi+W+73FSo0qCcaUFBN3drtv1k9X82/lq5V/2nP+Tbf2gv8AsiXxU/8AUG13/P8A+uii06tKzX8SHW/2l/X/AAwsR/Arf9e5/keDf8Eyf+TAP2Sf+yI+Cf8A01x/5/8A1Vpi2ljMVf8A5+vrb+v67mOA/wBzof8AXuP/AKSv6/4Y+4byzttQs7vT72CO5sr+1uLK8tpV3RXFpdwvBcwSrkbo5oZHjkXPKMRzmue67r7zsavp0ehgeC/BPhL4c+F9G8E+BfD+meFfCXh60Ww0Pw/o1uLXTNLs0YsttZ24LCKIMzEKCeSfQ03Lmk5SlzSl8UnLVvu3rd/0rbExjGEVGKSitkv6X5fceXftUcfsw/tGkjIHwK+LJI9R/wAIJrvB9M9Px961w7TxFCzX8al1/vx/r/hzPEf7vX/681f/AEhn4ufsC/se/treKP2NP2bPEXhP/gpV48+H/hrWvhN4T1DRPBdl8DPh5rFr4Y06506N7XRrfVL3UI7y+isoysKXNzEs0oXc+0kmvQxWIwqxWJUsFGbVWScvbVFzWdnJrZXaeib+V7y8vCYXFywtFwx84RdNOK9hB2T1t8aem3yvrufT/wDwQ403VNH/AGBdB0vWtbm8Savp/wAcP2lLPUtfntYbGbWL62+OHjaK61OWzt2eC2kvple5e3hJihaQxxkoorDMmni7xjyp0aVo3vb93T0v1/rudOVxccJFOTm1UrJyel7VZa29bv5h/wAE6P8AkvP/AAVT/wCz+/FH/qrfhvXzHEv/ADKP+xZD/wBSK505R8Waf9jCX/pqAn/BZv8A5Mdv/wDs4T9lb/1fXgmuTh7/AJGS/wCwXG/+o1U2zb/c3/1+w3/p+mfqjB/qIP8ArhD/AOilrwz0j8vv2Jv+UiX/AAVh/wCx8/Zw/wDVLabX3+F/5EuV+lf/ANSH/X/DHgUv+RnmPrQ/9NRP1uBxyOCOQR2o5l3X3necjrfgLwb4k8UeEPG2veHNM1Xxb4AOtN4L8QXsBl1Lw0fEVnHp+unSZywNt/atlDFbXmAfNijVSOKanZOKnaMrcyTVpW2v6a9L+cftS4xbUmruOz7fivyfyuddSvHuvvKPye/Yy/5SL/8ABWn/ALKH+zL/AOqE0euvE/wMvfT2df8A9OvqcGG/3zH/AOOj/wCmYH6keIvD2h+LtA1rwt4m0uz1vw74i0y90XXdG1CLz7DVdJ1K3ktb/T7yE4Etrd20skM8ZOHjdhxXKpWaalZpppqVmmndNbaprv8Acd0oqcXGSTjJNNPZp7p7XT7X120PmLwN+wZ+xr8M/EPh/wAWfD/9nD4X+DvEfhS8j1Dw3q2gaG1hcaJewq6RXGnLFceRbSIssgXZGFAcjbz82ssVXmnGeIqSjJWaclZrz72318uxzQwWFpSUqdCnBxd48q2fdLZWPrasbx7r7zqP52fAfwE/aI+MX/BSH/gqHffBP9r3xN+zRYaL8QvgJaa5pOg/Dbwr46j8T3lx8EvD01vqNxP4iuraWwks4B9mSG23RyKS7/NgV60qtCngcvVXDqu+Ss1J1Jw5f3zSSUbp69XqvLVniQo16uPzB0sVKglLDqUVTjPmboqz1cbWWm7+Vnzdp+zL8JPjN8I/+CxXi7RfjP8AtG65+0frl5+wJoOo2HifXfBPh7wRcaVpknxp1e3j0WOw8PT3FtcxRXMNxeC6lfzi120TArGjNNepTqZYnSoKili5JxU5Tu/Yt3vLXVW0V0lp5RvD0q1LMpKrXddvCpqTgoWXtH7tk5Ky3+ejd2o/QP7Y3/KTX/gll/14ftb/APqvfDNeTjf+RNmfrhP/AE7M7J/8jLL/APDiv/SIH6d6p/yCtV/7Bepf+kU9fCQ+OP8Aij+Z7h+Xv/BFz/lHX8E/+wx8Wf8A1bfjWvZ4i/5G2I/wYf8A9R6R5uUf8i+l/wBfK/8A6cYz/god/wAnKf8ABJH/ALPn1f8A9UN8Rq7OGv8Amb/9gEP/AE/ExzX+Llv/AGGf+45n6917F491950HIeLfAHgvx3J4Wl8Y+GtK8RyeCfFWn+N/CT6rbi4bw94u0mG6t9N8Q6YSR9n1SygvruK3uBlkS4lAA3ZpqfLflla6s7PeL3TvunbX/gEyhGVuZJ8r5ot7p91s0/T8bJHX0rx7r7yj8oP+CjH/ACcr/wAEjf8As+fWP/VCfEiuvDtPD5nb/oDp+f8Ay/j/AF/wx5+N/j5f/wBhX/uKofq/XJePdfeegfLHxb/Yk/ZT+O3i8ePfiv8ABLwh4v8AF8lpZ6fqOt3I1PT7nX9OsP8Ajx07xRHo2oadb+KLG0X93Ba6/BqMMcP7gKYTsreniqtKPJTquMb3SunZvrFvWL849dTnqYTD1pc9SlGUtLvVcyWiUraSS6KXyPpfSdJ0vQdL07RND02x0fRtIsrbTdK0nTLWGy07TdPsoUt7OxsbO2SO3tbW2gjSGCCGNI440VVUAALi5Jttu7bbbctW3q2+7bd2+u7N0kkkkkloklZJdkun9dj8X/8Agrt4Q8a+Pfi5/wAEtPCPw7+JN/8ACDxnrf7Y3im20H4kaZoen+Jb7wtcp8CvHU8l7b6HqskWn37TW8M1kY7l1REuWlHzom3vwE4RhmMp01VgsHDmp8zjzXrJW5o6rfz897x8rM4ynVy+MJunJ4mdqiipOP7io2+VtJ3Sa3W+6vc+Qf8Agp3+y3+1v8Nf2ZdD8X/FH9v7xn8cfBWn/tMfsnRan8NdX+DvgbwnYa3Le/tAeA7axnm1zRb641C0bS7p47+NYY8TvCIZCEdiu+Er4addxhgo05/V8U41PbTm42papRej5lpdvS3W6Mcbh8TClCVTGyqwVfD3g6MI3/fQS1UpWs7dPvs0frp/wVQ/5Rsftyf9my/FL/1HrivPwf8AveC/7CKX6no47/csR/16l+Xy/L7j2n9m7/k3f4Df9ka+GP8A6hWi18Di/wDesT/2EVv/AE5I9ah/Ao/9eqf/AKQj44/ZU/5S7f8ABSH/ALIT+xT/AOmT4m19Th/+RDl//YTj/wD0ugeR/wAzfH/9g+C/9IqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/1f7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2R+0sQP2c/j8SMgfBX4pkj1H/CDa7kfjXzOD/3vC/9hNDy/wCXsOutvu+89it/u+I/68Vf/SHp89j8bf8Agn3+yR+254q/Yp/Zn8ReDv8Ago94v+H/AIW1n4S+FNQ0HwTa/A/wBrVt4X0y4sEe10aHVb66F5qCWUZES3VyqSyhdzqCa/TMViMKsTXjLAwnJVGpTdWUXJ97cjSva+j+7Q+YwWHxUsJQlHFyhGVOLUVCPuq2ivd3/D8bH2J/wxT/AMFAf+kp3jb/AMR8+Gv/AMl1h9Ywn/Qvp/8Ag6X/AMrOr6ri/wDoOn/4BEP+GKf+CgP/AElO8bf+I+fDX/5Lo+sYT/oX0/8AwdL/AOVh9Vxf/QdP/wAAieS/H39jf9vHTPgT8atR1b/gp34y1zS7D4TfES81LRJfgH8OrSPWLC18I6vNeaVJdQXgmtU1C3SW0e4i3SQrL5iKWUCrpYjCe1p2wEIv2kNVVk/tLpyx231vts7WlnWwuLVGq3jZtKEnbki76PR6r9fQ8d/YF/ZF/bg8S/sZfs2694T/AOCkfi/wN4b1X4T+FL3RfB9t8Dfh/q9v4d0+fT42t9Li1K9ulur1bZPkFxOqySdWAJxWmKxGEWJrxeBhOUZtSk6sk5Pq2uR7+T+4yweGxUsNRccZKMXCNoqnFW023d/J9tGla0frz/hin/goD/0lO8bf+I+fDX/5LrD6xhP+hfT/APB0v/lZ0/VcX/0HT/8AAIh/wxT/AMFAf+kp3jb/AMR8+Gv/AMl0fWMJ/wBC+n/4Ol/8rD6ri/8AoOn/AOARPHP2iv2N/wBvHS/2fvjpqWrf8FOfGevaVp/wf+JN7qehy/AX4dWces6fa+D9YnvNKku4LvzrVNQt45LV7iLMkKymRAWUCtaNfCOtRSwEIt1aaUlWk7NySvbkW35723jlXw2LVGs3jZNKlUbThHVKLuvK60vra+qex9q/8Evo5If+CfH7H8c0xuJV+BXgIPMyhTIw0iHLlQWAJx0BwOgzgbeTG2+u4q3/AD+n9/NJefb/AIbY68B/ueG6/uo/l+H9eZ4f/wAEXv8AkyWL/s4T9qP/ANXz46rTMP8AeV/15pf+m6Znlv8Auq/6+1//AE7Iwv8AgnR/yXn/AIKp/wDZ/fij/wBVb8N6+a4l/wCZR/2LIf8AqRXN8o+LNP8AsYS/9NQE/wCCzf8AyY7f/wDZwn7K3/q+vBNcnD3/ACMl/wBguN/9Rqptm3+5v/r9hv8A0/TP1Rg/1EH/AFwh/wDRS14Z6R/P38PfgT+0d8W/+Ckv/BTy8+CP7XOvfs4WOk+Mf2f4Nc0zSPhv4X8cJ4kuLn4PaVJaXcs/iCeOSxaxhVoFigBSYPvbDD5v0fL6tCGS5Z7XDRrXWItzVJRt++atZKSd3rd9Vtp7vy8qVapmeY+yxEqVpUNFGLv+6XfXS/z/ALtkpfZ//DFP/BQH/pKd42/8R8+Gv/yXW/1jCf8AQvp/+Dpf/Kzf6ri/+g6f/gEQ/wCGKf8AgoD/ANJTvG3/AIj58Nf/AJLo+sYT/oX0/wDwdL/5WH1XF/8AQdP/AMAiH/DFP/BQH/pKd42/8R8+Gv8A8l0fWMJ/0L6f/g6X/wArD6ri/wDoOn/4BE/OP9ln9lL9s/WP24P+Ckfh7Qv+Chvivwz4n8K+N/gHb+M/GcPwW8CX9z8Q7nUvg3pd9pN5d6Xc3X2TRW0LTmj0mKKwZku0jFzNiQkN018RhVQwN8FCSdOs4xdWa5bVXdX5ZJ31l5X6t+7x0MNinicYljJqSnT5nyR969OLT30sml19VZc36Of8MU/8FAf+kp3jb/xHz4a//Jdc31jCf9C+n/4Ol/8AKzs+q4v/AKDp/wDgEQ/4Yp/4KA/9JTvG3/iPnw1/+S6PrGE/6F9P/wAHS/8AlYfVcX/0HT/8AiH/AAxT/wAFAf8ApKd42/8AEfPhr/8AJdH1jCf9C+n/AODpf/Kw+q4v/oOn/wCARPHv+CW3gb4jfDr9sb/gqf4V+KfxavvjZ4y074pfAMar8QdR8N6Z4Uu9baf4L6Pc2zSaLpEstham0tJYbICFv3i24mb53bdWOlCeGy+VOn7KLpVLQT5kn7fVXer+dt3ZJKxll8KlPFZjGpU9rJVKF52te9K6dtttNLbLe75fYrf/AJTZ61/2jo8N/wDq9vEVQ/8AkVv/ALDX/wCo5v8A8zJ/9gi/9OMz/wBsb/lJr/wSy/68P2t//Ve+Ga8/G/8AImzP1wn/AKdmXP8A5GWX/wCHFf8ApED9O9U/5BWq/wDYL1L/ANIp6+Eh8cf8UfzPcPy9/wCCLn/KOv4J/wDYY+LP/q2/GtezxF/yNsR/gw//AKj0jzco/wCRfS/6+V//AE4zzH/grZ4S8b+Ofif/AMEufCvw5+I958JPGesftrata6D8QrDQ7DxHd+GLwfBHx3P/AGhDo2pvHY3zm3guLXybhlTFyZMhkQN6HCs4QnmsqlNVYLAR5qbfLzL2y05tWtWtV+F7nNnMZTll8YT5JPFtKVlKz9lK2j0PZP8Ahin/AIKA/wDSU7xt/wCI+fDX/wCS6+j+sYT/AKF9P/wfL/5B/n95j9Vxf/QdP/wCIf8ADFP/AAUB/wCkp3jb/wAR8+Gv/wAl0fWMJ/0L6f8A4Ol/8rD6ri/+g6f/AIBEP+GKf+CgP/SU7xt/4j58Nf8A5Lo+sYT/AKF9P/wdL/5WH1XF/wDQdP8A8AifnL+3D+yl+2f4e+O//BNbTvFH/BQ7xZ401XxZ+1zqeieCtauPgt4E0qT4eeIU+Dnjq/k8VWlpaXRh1qeXTbe60c6ffFLZY75rncZYYxXTQxGF9jmDWChFRwsHOKqyftIusko35U42et7N7W6nFisPilWwN8ZJt4lqLdOD5Zeyn7yu7PS6s1b1+z+jX/DFP/BQH/pKd42/8R8+Gv8A8l1zfWMJ/wBC+n/4Pl/8g/z+87fquL/6Dp/+ARD/AIYp/wCCgP8A0lO8bf8AiPnw1/8Akuj6xhP+hfT/APB0v/lYfVcX/wBB0/8AwCIf8MU/8FAf+kp3jb/xHz4a/wDyXR9Ywn/Qvp/+Dpf/ACsPquL/AOg6f/gET4m/aD/Z+/ab+E37Zv8AwSm1j41ftleIf2itC1H9rzxPYaV4Z1b4YeE/BMGialF8DvHt1Nq8d9oE8txdST2aSaebaZREqTGYN5iKK3pVaE8PmMaWFjQksJBuUajnzL2yXLZqNtdb2e1upx4ilXp4rLnVxEq0XianuuMVZqhN3TWuqTi9et9NT7R/4LYf8mNL/wBnQfsd/wDrR/w+rlwH+9f9y2L/APTR3Zl/uy/6/wCG/wDT9M9w/wCCqH/KNj9uT/s2X4pf+o9cVlg/97wX/YRS/UvHf7liOn7mWnbQ9p/Zu/5N3+A3/ZGvhj/6hWi18Di/96xP/YRW/wDTkj16H8Cj/wBeqf8A6Qj44/ZU/wCUu3/BSH/shP7FP/pk+JtfU4f/AJEOX/8AYTj/AP0ugeR/zN8f/wBg+C/9IqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/W/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfY/7S/8Aybj8f/8AsinxT/8AUG12vmcH/vmE/wCwmh/6dgexW/3fE/8AYPW/9IZ45/wS2/5R4/sff9kL8D/+muOvvsX/AL5iv+vr/U8fL/8AcsL/ANeYfkX/ANtv9qbx9+zYvwM0j4a+BvB/jbxX8bPiNqfgSzXx54z/AOEF8L6FDpXhbUPFF3q2p679hv1ijFvp7wqjRKu9gS/OKeHoRr+255zhGjTVR8keeUry5eVLTq+/lpdOJjMTPD+xUIxlKrNwXPLlStFyvfXouqfysei/su/FL4zfFbw7ruufFrw18IdBWDUYrXw7P8IfianxN0rUbdYQbxtQ1GPT7COwu4LjMa2wEpdP3hKZAfKrCnCUVTnVknfm9rD2cvKyvJfj99ny6YepVqJuoqaX2XTqe0WvdpRSflZ/L7XZ/tOf8m2/tBf9kS+Kn/qC67To/wAWl/18h/6UisR/Arf9e5/keDf8Eyf+TAP2Sf8AsiPgn/01xVeL/wB8xX/X1/qY4D/c6H/XuP8A6Sj3X47eIP2g/D2i6LP+z38OfA/xH1241CaLXNP8c+NpvBFlYaaIVMFzZ3kOlaq15cPOWjeAxQhEAfzGJwsU40pNqtOcI6WcI8zv1v70bLb/AIF/e2rSrxSdCnCo7vmU58iS6NPq/u/JS8A/Y5/ad+M/x68bftCeCPi18KPCHgG4+BXi7R/A8mu+CPG8vjbw/r/iW50eHVte0q3vpdL0zZdeG/tdpZ6gI1kRLt5YCQ8LhdMRRp0o0J0qs5qtFy5ZwcHFJ6Npyk1ezcX5O97x5ccLiKtadaFSnGHspKN4S5ouVk5JNrXluu2+z+z71+1T/wAmwftHf9kJ+LX/AKgeu1OH/wB4of8AX6l/6WjbEf7vX/681f8A0hniH/BMb/lH9+yH/wBkM8B/+mmGqxn++Yr/AK/VP/S5mWA/3PDf9eon5nf8Esf29f2PPgn+y1f/AA5+K37QXw68DeN9F/aB/aXk1Xw1r+tR2mqWKX/xw8bXlm1xA3KC4tZop4853RurdDhevG4XE1K6nToznF0aNpLRO9OO19dLW8+mxxYDGYanh+SdWEZKrWunJf8AP2dt5R3Xl932vbv+CVXj7wd8UviP/wAFMviF8PtfsPFXgrxZ+3X4l1Xw34k0qQz6XrOmyfDH4dxJe2FwVVZ7dpIpEEiZXcjDJxlvluKISpzyqnNcs4ZbCMovdP29Z2e1rJ63X3Hdk04z/tGcXeM8fJxknpJeyp6rV90rp/dodd/wWb/5Mdv/APs4T9lb/wBX14Jrh4e/5GS/7Bcb/wCo1U6M2/3N/wDX7Df+n6Z+qMH+og/64Q/+ilrwz0j8vv2Jv+Uif/BWD/sfP2cP/VLabX3+F/5EuVelf/1IZ4FL/kZ5j60P/TcT9bh79O+Of04z+f5U/wCv63/L7zv/AK/rb8/uPiP9nj9pv4ifFH9o39qr9n34jfDjQvBV9+z1qHgC40HWtB8UP4ii8X+FviRpWo63oGpXsL2Fn/ZGopp9nEb2wV7lYZpmjEzbK3rUYU6VCtCpKftuZSjJW5ZRlFSSfXV6Oy+RyUa9SdatSqQjH2TjyuMr8ykm03o1eyu1dWvpe59uVgdZ+T37GX/KRf8A4K0/9lD/AGZf/VCaPXVif4GA/wCvdf8A9OyODDf75j/8dH/0zA/UPxVc+IrPw1r114R02x1nxTb6TfzeHdJ1O+bTdN1LWY7aRtOsr/UVinaxtLm6EUVxdLDK0ETNII3KhW5opOSUm1G65mtWlfVpPfT09VudsnJRk4rmkk+VN2TfRN9Nf60PzPj/AGtf2zPCP7Q/7O3wP+LX7OXwm0qP48a74ptzfeCPjBdeKda8MeFPBehPq/iLxhe6RJ4asUOk2VxNpekrJJcR+dqGqW8Me58qvU8PhpUa1SnXqt0oxdpwcYynN2jTUud6vV7bLpdnB9Zxca1GjUoUl7WT1hV5moxXvStppey0t8X2dz9Tq41su9j0T8m/2J/+Uhf/AAVr/wCyqfs7/wDqiPD9duJ/3PLv+vdT/wBPs87C/wC+5l/jw3/pg8b+Mn7RHwT/AGcv+Cy0nib44fEjwz8NNB13/gn34e0bSNU8UXyWFrf6pF8bfEd3JZW7v9+ZLcGZlHROa2p0alfLZRpRc5LGNtJbL2CV+27769LGdWvSoZjerNQTwiSvpd+1fp+L+65yPxY/av8A2dP2kf8Agp3/AME0Lf4F/Fvwh8TpvC+nftUP4ij8KX/9onR01T4faEunNfGNSsAvGtLlYNxzIYnC42mvPzGhWo5LmTrU3Tu8Lbm0vao27b99b2t3fMkXDEUa+Z4BUqkZtRxN+Vp2vCNr2bttfe3XS0j9wNU/5BWq/wDYL1L/ANIp6/P4fHH/ABR/M+iPy9/4Iuf8o6/gn/2GPiz/AOrb8a17PEX/ACNsR/gw/wD6j0jzco/5F9L/AK+V/wD04xn/AAUO/wCTlP8Agkj/ANnz6v8A+qG+I1dnDX/M3/7AIf8AqRAxzX+Llv8A2Gf+45n6917J0H5sftKftW/tSfDPxD8Zr74Ufs4+Gtf+FH7P3hG38W+MvHvxP8fr4BX4gmLw/N4q1zQ/hPbNpt5FrFxoekwG1u9S1CezsX1uRdNicurvXRRo0JqiqtacalabhGFOHPyauKdR8+l3Z2WvLr7tkpcNfEYiDqunRi6dGKlKdSfLz+65NU1rey72u9F3Pt74N/EvTPjN8Jfhp8W9GsNQ0rSfiZ4F8LeOtO0zVoTb6np1n4o0az1i3sr+E48u7to7tYpgON6kjIINYzg6c505NNwnKF1s+VtXW3bt91mdVKoqtOFRJpThGdnuuZJ2fnqfnT/wUY/5OV/4JG/9nz6x/wCqE+JFdGH/AN3zP/sDp/8AqQjjxv8AHy//ALCv/cVQ/V+uU9A+Hf2qP2ofiF+zt8XP2SvC+m/DfQ/Ffw1/aM+NWj/A3xD4uuPE76br/gzxR4h0vxBrWkXNh4fFlMmsae+n+Hbw3UzXdt5MzxRhH3F13o0I1YYmbqSjKhRdaMEvdlGLipJu2jvJfzaPysceJxM8PUw0eSMqdeqqMpc1pRlJNqys7pqL9N7StY+4zwSPQ/59f5/nWB2H5Mf8FFf+Tpf+CRP/AGep4v8A/WfviHXZhP4OZ/8AYHT/APT6PMx/+8Zb/wBhNT/1GqmV/wAFx9W03QP2BNS13WbyHT9H0T9o/wDZI1fVdQuW2W9jpum/tC+A7y+vLhzwkFtawyzSufuojHtTy6Lli1GO7w+KS837Lb5/P0exeaSUcI5SaSVbDtt7Je3h/X5Hk3/BR/8A4KO/sPfEH9gP9sLwN4L/AGlfhj4k8XeLP2fPiNoPhzw/peuR3OpaxrGoaFNBZafY26Kzz3VzKwjiiRdzscDPRawmDxccVhJToThGFenKTdtEu+ttOurtvqY4zG4SWErxjWptulJRSmnd20Ss5XvbdR21V72j+oP7NbK/7OvwFdTlW+DPwwIPTg+CtE7HkfjX5zjFbF4pdsRW/wDTkvX8/vPoaH8Cj/16pP74Rf5P9OjPjr9lT/lLt/wUh/7IT+xT/wCmT4m19Rh/+RDl/wD2E4//ANLoHkf8zfH/APYPgv8A0iofshXMdgUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB//1/7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2P+0v/AMm4/H//ALIp8U//AFBtdr5nB/75hP8AsJof+nYHsVv93xP/AGD1v/SGeOf8Etv+UeP7H3/ZC/A//prjr77F/wC+Yr/r6/1PHy//AHLC/wDXmH5FL/goH4I8OeIvDXwZ8X+MP2cbv9pXwt8MPitbeKdd8MaRNJN4g8L2M+j3umt4u0fQFeKLxSbGSZIb7RJpNstpK0iqzJiqw0pRdWMKyoSnScVJ3tJpp8ja1inbR33elhY2EZKjKVB1406nM0tXFNW5uXTms2rq+19rI8X/AGDfA97d/tM/tO/HPwD8HPEnwB/Z38f+HPhn4f8AB/gXxJoo8Jz+JfG/hi11BPFfjy28GxuYtDgvYbmx00SeVFLfvZvPIDwz1iJfuMPSnUjVrQlUlKUXz8sHJOMOe+rVn10vrd/FnhIP2+Iqwpyo0ZckYxa5eacVaU1Hp+vm9I/fn7Tn/Jtv7QX/AGRL4qf+oLrtYUf4tL/r5D/0pHXiP4Fb/r3P8jwb/gmT/wAmAfsk/wDZEfBP/priq8X/AL5iv+vr/UxwH+50P+vcf/SUfQn7Q/j7xP8AC/4I/E3x34I8Man408a6B4S1Obwd4W0e2a71DWvFV1GLDQLWKFCCYl1S6tbi7fpFZwzyNhUJXOnGM6kISajGUkpSeyj1+9aLfW2jtY3rzlCjUlGLnJRfLFbuT0W+nW7vstTzj9in4GXP7P37OvgTwVrkpvfHWp29342+Jusyc3Wt/EbxndS+IPFuo3UhAaSRtVvZoULklIoo4xhUFXiKvtq05r4E+Skv5acUlFLurJP1v3RGFo+xoxi9ZP35vvOWsn9+3kdp+1QCf2Yf2jQOSfgV8WgB6n/hBNd+v8vzow/+8UP+v1L/ANLRWI/3ev8A9eav/pDPzi/4J1ftz/se+D/2HP2WfC/in9o74U6D4i0H4N+DNL1nRtS8UWlvf6bqNppkUVzZ3cDBminhkBSRCcqR3rpxmFxLxeJkqNSUZVZuLUXqnKTTXTW9vl5o4MFjcLHC0Iyr0lKNOKactVps+zTdn6eaOY/4I2eEPhh45/YqtPFU3hLwV4oGtfHf9pa+ttevPDuj6pNqVlP8cfG8llcLe3djLNPC9q0TQMzkGEptJXFfK8S1a1LNKkFUqwtRw3uxqSjb/Z6XRed/nfsd+TxpzwMZcsJXq13fli3b21S3nrvr+Vj9edC8MeG/C9vPaeGtA0Xw9a3M5uri20TS7LSree5KLGbiaGxhgjkmMaIhlZS5RFUnCgL85Oc6jvOcptKyc5OTt2u9Utf6uz1VGMVaMVFXvZJLXvpb+u+rPzF/4LN/8mO3/wD2cJ+yt/6vrwTXtcPf8jJf9guN/wDUaqedm3+5v/r9hv8A0/TP1Rg/1EH/AFwh/wDRS14Z6R+X37E3/KRP/grB/wBj5+zh/wCqW02vv8L/AMiXKvSv/wCpDPApf8jPMfWh/wCm4n63UzvPzr+APgXxfov/AAUJ/b58cat4e1Sw8I+NfDX7MNv4U8QXNs0ema9P4d8A6rZa5Fp1wfluH0y7ljguwuPLkcKeuW6KsovC4aCacozrOSWrSdRNN9k1tv8AglHjpQksViJNNRl7Llfe0ZJ29Lrr91j9FK5zsPye/Yy/5SL/APBWn/sof7Mv/qhNHrqxP8DAf9e6/wD6dkcGG/3zH/46P/pmB+sQGSB6nHPA/E9q5TvPzt/Zw8FeMPiN+1j+0z+1R8RvD+q6FaaZe2/7OHwA0jXLZre5s/hh4DnN74t8Y2dvIcwR/EXxzdXd7DcKA93pGkaWSSgQL0VZxjQoUIOLbTrV5LX35aRhdOz9nD3Wtfek3ZanFQhKpiK2Imrcr9jRX9yPxy2XxTXTdJNpaH6I1znafhb+z/8AtJ/AT4Ff8FGP+CqmnfGL4teCfhvfa/8AEr9n6+0W18WazBpc2p2lt8DvD9vcXFokoJlihmxFIwGA5A4Jr0KtGrVwWXunTlNKnVu4q6TVZuzt3t3+48iliKFHHZiqtSNNylh3HmdrpUdfz7feVfCPxH+AP7Sv/BZDXNW8DeI/h78ZfDWkf8E/9BsJrywXTvFGl6drEfxq12aW3JuIJ4Ib1ba5gdwqrJ5UsZIAYCvJztV8Pk9JtVKMnmDtZuLa9gtbrW19n+qOnCVKNfM5uDp1orBx10kv4ruvJpNdbq/SzP2B0v4c/D3Q7+DVdF8C+D9H1S2EgttS0vw1o2n31uJV2SiG7tbGG4jEiEpIEkAdDtOQSK+KlXrSTjKrUknupTnJfc9PvvbdbXj7ihBNNQimtmopNX0dmk91puu2tzpdU/5BWq/9gvUv/SKeoh8cf8UfzKPy9/4Iuf8AKOv4J/8AYY+LP/q2/GtezxF/yNsR/gw//qPSPNyj/kX0v+vlf/04xn/BQ7/k5T/gkj/2fPq//qhviNXZw1/zN/8AsAh/6kQMc1/i5b/2Gf8AuOZ+vdeydB+I/wDwUR1Gw+KMvxX+B/7QP7KXxd+Iel6Ppb6z+yd48+DsWqaraeIfEuueF4IxB4leyu7a10LW9B8aW0EcsWtQ3Okz6UkNyUYNMrd+F5qfsqlHEU6blLlxEatk1GM91e11KPw2abenu2seVjUqvtaVahUmoxcsPKnd80pK2vLtJStpK6t53Uf1B/Zd034n6P8As4fAzSfjX9m/4W3pnwq8EWHxGFmsK2yeLrXQLGHWY41t0jgXyrpHikEKLD5qP5ahAorkquDq1XTv7N1JuF9+Tmdvw167q9m2j0KHtFRpKr/EUIKf+LlV9tN+1vwvL4X/AOCjH/Jyv/BI3/s+fWP/AFQnxIrbD/7vmf8A2B0//UhHJjf4+X/9hX/uKofq/XKegfnD/wAFB/AnjHxv4q/4J93PhHw5qviGDwR+3t8MfGni2XTLZrhPD/hTTvAfxJs77X9TZT/o+m2t1f2cE1wysqyXMSn74rrw04xp4xSkk54ScIL+abnTtFebSZ5+PhKbwTim1DG05ystoqFRNvsrtdvLtL9Hz1P1Nch6B+N3/BUzxx4Q+G3x8/4JQ+N/H3iPSvCXhDw/+2b4rutb8Ra5dJZaVpdvJ8BfH1tHNeXT/LEj3E8MKk9XkUd67sFCVSnmUIJyk8HC0Vq3atslp/wN9bNHlZjONOtl05yUIrE1Lyk7JXw9Va/N/PY8O/4K6fte/srfGL9j60+Hvw8+OXwz8f8AinXP2lf2S/svhTQ9dtNW1DU7O0/aD8B3OpKtgqH7RBDZRzS3SMjp5CuXwoNVhMPiKdWpUnSnCMcHjLzs7RboNJt9Ndv+HFjcVhqtGMIVqc5Sr4b3VK7a9tBvTtZO+3n2l+yzfCL4UOrK3wy+HzKwIZT4N8PEEHqCDp3I+pP44r82eJxF9K9bo/4s97ett+l/K/U+j9lT/wCfcLduSP8Al+ny6HfQQQWsENtbQxW9tbxRwwW8EaRQwQxKEjihijCpHHGiqiIiqqqoAAAArFtttu7bd3d3f3u7fzf33L/4Y/NT9lT/AJS7f8FIf+yE/sU/+mT4m19hh/8AkQ5f/wBhOP8A/S6B4f8AzN8f/wBg+C/9IqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/Q/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Gv9o//AJTCfsYf9mq/tAf+pX4XrfE/8iPF/wDYXQ/9IZxr/kaUf+wOt/6UfZH7SwJ/Zy+PwAJJ+CvxTAAGSSfA2ugAAckk9AP618zg/wDfML/2E0P/AE7E9it/u+J/7B63/pDPzw/4Jvfty/sfeCv2Ef2VvCfi39o34U+HfEvh/wCDXg/S9b0PVfFFnaalpeo2mnJHc2V7bSfvIbiCQMkkbhSrDB6V+i4vC4l4vESjQqSjKo2moyaa8nGMr/P8b+789gMXho4PDxlWhGUaUYtN6prSzPtn/h4d+w7/ANHT/Bn/AMLCwrD6pi/+gar/AOAT/wDlZ1/XcJ/0EU/vD/h4d+w7/wBHT/Bn/wALGw/z/P8AUhT6pi/+gar/AOAT/wDlf9dA+u4T/oIp/eeOftE/t+fsV6z+z98dNJ0v9pz4QX+p6n8HviXp+nWNr4tspbm9vr3wZrVtaWlvGvzPPc3EscMSDJZ3UAHOK0pYXFKrSbw9RL2kNXGdl7y7xjsvP7vtZV8ZhXRqpV6d3CaSvu+XZb3b9PvPE/8AgnZ+3V+x34P/AGHf2XfDHij9pD4T6D4h0T4O+D9P1jRtT8U2drqGm31vp0aT2t3bv88U0TDa6MAQeDjBFXi8LiXi8RKNCpJOpJpqMrPXo1GV9LP/AD+zlgsXhoYWgpV6al7ON03tpt/Vu3S8vs//AIeHfsO/9HT/AAZ/8LCwrD6pi/8AoGq/+AVP/lZ1fXcJ/wBBFP7w/wCHh37Dv/R0/wAGf/CwsKPqmL/6Bqv/AIBU/wDlYfXcJ/0EU/vPE/2lv2/P2LNZ/Zy+P2kaT+038IdQ1XVPgt8T9O02wtPFtlLdXt/e+C9atrO0t4ly0k9xcSxwwovLSOoGMg1rQwuKVei3h6tlVpt3jPZSTe8Yrp389bWljiMZhXQrJV6bbpVElzatuDSS7tvp/wAE8n/4Jzfsr/sy+Kf2F/2V/EWufAj4Ua5rGsfBjwXqGpaxqPgrQ7u+1G8udLikmu7u5ns3lnnmcl5JHJYsSWJOa+SzjH42GaY6EMXiIQjiaqjFVZpJc21tf67bHZl+Gw0sFhpOhSbdGDbcE23be/I733vfXyP068E+A/Bfw28PWnhL4f8AhbQ/BvhixkuZrLQPDmnW+laTay3lxJdXckFlaxxQRvc3Mss8zIg3yuznljXiVKtStJzq1J1Jvec5OUnbTVvV2Vlrbt0vL0YU4U4qFOEYRV7KKSWru9r7u73++7OsrMs/Kn/gs3/yY7f/APZwn7K3/q+vBNe5w9/yMl/2C43/ANRqp5ubf7m/+v2G/wDT9M/VGD/UQf8AXCH/ANFLXhnpH4ofs+ftJ/AT4F/8FHP+Cpdl8Yfi14I+G93rvjb9nm40aDxZrMGlSanBZ/BvS4bqWzE/+vS3lZY5WTIR22nk4X9DwVGrVyXK/Z05zsq9+Vc1mq8nZpXav6abu+h82q9GjmWYe1qRp3lRUVJ2b/dRu13t/wANsz9Ev+Hh37Dv/R0/wZ/8LCwrT6pi/wDoGq/+AVP/AJWdX13Cf9BFP7w/4eHfsO/9HT/Bn/wsLCj6pi/+gar/AOAVP/lYfXcJ/wBBFP7w/wCHh37Dv/R0/wAGf/CwsKPqmL/6Bqv/AIBU/wDlYfXcJ/0EU/vPzG/ZJ/bY/ZK0D9vj/gqB4q1r9oT4X6X4b8b+O/2d7vwhrd74ltIdO8R22j/BLStM1SfSblsR3cdjqEb2dy0YYRzq0ZwQa6sRhcTLD4G1Co3GnWUlyyvF+1ejsm9tdYrtbW5xUMXhlisbJ1oJSnS5XzaStSinba9mmtvuP05/4eHfsO/9HT/Bn/wsLCuX6pi/+gar/wCAVP8A5Wdv13Cf9BFP7w/4eHfsO/8AR0/wZ/8ACwsKPqmL/wCgar/4BU/+Vh9dwn/QRT+8P+Hh37Dv/R0/wZ/8LCwo+qYv/oGq/wDgFT/5WH13Cf8AQRT+8/Mr9jnwz+zJ+1b+3d/wVG+IUvh74YfHLw6PiV8BLbwx4qvNJ0vxTYC1X4LaJDfQ6VfXVvKgiF9bypOkR2ieNw3zhq8ziCti8JhsqhTq18M3SruUIycHf20nd2Td7NW1WndGWXRw2JxeY1HGlWXtKCjNpTVvYxvyuz0vf5rrflP168A/AH4I/CzWLvxB8NvhR4C8C65f2P8AZd7qvhXw1pmi311pwmFwLKe4sbeF5bYTqsoiYlfMG7BIynydXF4qvFQrYirVindRqTlNJ2tdc3W3X7j2qdCjSk5U6VOEmuVuEVFtdrpR01fT7rvm9drnNSjqn/IK1X/sF6l/6RT1UPjj/ij+YH5e/wDBFz/lHX8E/wDsMfFn/wBW341r2eIv+RtiP8GH/wDUekeblH/Ivpf9fK//AKcZyX/BUPxx4Q+HHxs/4JU+NfHniLS/CnhLw9+25q1/rniHWrlbTS9Ksv8AhRnxAt/tN7cv8kEPn3EMW98DfKi98N3cMQnN5tGEXKTwELRW7ft46LbX+tbNHPnE4055dOclGEcZdyeiX7uXX+vxPtv/AIeHfsO/9HT/AAZ/8LCwr3vqmL/6Bqv/AIBU/wDlYfXcJ/0EU/vD/h4d+w7/ANHT/Bnjn/kcbH/D+WfoMDcfVMV/0DVX/wBuT0/8ph9dwn/QRT+8P+Hh37Dv/R0/wZ/8LCwo+qYv/oGq/wDgFT/5WH13Cf8AQRT+8/Mj9vj9tj9krxX+0J/wS41fw3+0J8L9c0zwN+2bqviPxhfad4ltLm28OaDJ8EviDpiatq0qfLaWLahdW1mJ5MJ588UfV1DdWHw2JVDMVKhUTnhacYJxleT9sm0k1FtpK+i+a2lwYzF4Z1sC1Wg1HEuUmpfDH2c9X2TenS722al+m/8Aw8O/Yd/6On+DP/hYWFcv1TF/9A1X/wAAqf8Ays7/AK7hP+gin94f8PDv2Hf+jp/gz/4WFhR9Uxf/AEDVf/AKn/ysPruE/wCgin94f8PDv2Hf+jp/gz/4WFhR9Uxf/QNV/wDAKn/ysPruE/6CKf3n5ift5/Hf9lP9qf8AaV/4JY/Djwh8Rfhd8bLP/hr7xPeeKfCGn39j4mtW0h/gd47ht5tV05o5YWtDqAt1jMqbftAjwQwUM508Vhsvzes41aElg6fJO0otNYiF+VtRadn2+77XHXq4bE4zLKcalOqvrU+eGjVvYVLNp/3rfmtj9ULb9kD9lizurS+tP2evhFa3un3lrqFjd2/gbQYbi0vrKdLmzu7eWOyV4p7a4jjmhkU7kkRWGCM18I8wxzunjMQ0000602rPda30t3f36nvfVcMrNUKSaaaahFNNO6afIrNPX/PY+ja4joCgD8z/ANlT/lLt/wAFIf8AshP7FP8A6ZPibX2OH/5EOX/9hOP/APS6B4f/ADN8f/2D4L/0iofshXMdgUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB//R/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/Fz9qDVdK0f/gr5+xhd6vqen6Va/wDDLHx+j+06le21jb738V+GNqeddSxR722nau7c2046YrorxlLJMWoxcn9boaJNv4H2T/L7tTiTSzWhdpXwlWKb0V3La91+tu2p+hN941+Gmp2V5puoeL/BN5Yaha3FlfWdz4i0OW3urS6iaC5tp4mu9skM8MjxSxtlXRmUggkV8oqdaLTVOomndPklo1s17i1X/B1tY9xuDTTlCzTT/eR1T3XTdXW/3HzaP2b/ANgof80o/Zs7n/kFeCOSTknvyScnn867frua/wDQRjPvqHP9WwfSjhV6Kl+v9fgL/wAM4fsFf9Eo/Zs/8Ffgij67mv8A0EYz76gfVsJ/z5w33UQ/4Zw/YK/6JR+zZ/4K/BFH13Nf+gjGffUD6thP+fOG+6iIf2b/ANglgVPwo/ZsIIIIOleCOQeCO3Ue/wCVH13Nf+gjGffUB4bBvR0cNZ+VL/gfn9wifs3fsEIoRPhP+zWqqMKo0rwQAB6Cj67m3/QRjPvqB9Wwf/PnDfdS/r+vUd/wzh+wV/0Sj9mz/wAFfgij67mv/QRjPvqB9Wwn/PnDfdRD/hnD9gr/AKJR+zZ/4K/BFH13Nf8AoIxn31A+rYT/AJ84b7qIjfs3/sEspVvhP+zWysCrKdK8DkEEYII7gjg0fXc2/wCgjGffUD6tg3p7HDa+VL/gfn9x9B+HvEPwj8JaJpnhrwx4i8AaD4f0W0hsNJ0bS9d0Gz07TbG3XZBaWdtDdCKCCFAFjjjCqq8AD+LjnHEVJSnUhVnOTcpSlGXNJvdt8srtvq39/wBnePs4pRi6cYpWjFTikktklra3r99zZ/4WH4A/6Hjwf/4U2i//ACXU+yq/8+qn/gEv/lY7x/nh/wCDIh/wsPwB/wBDx4P/APCm0X/5Lo9lV/59VP8AwCX/AMrC8f54f+DIn5Z/8Fj/ABp4N1H9iO+trDxb4Yvbj/hoH9lqXyLTX9KuZjHF8d/BUksgihujJsijVpJH2lY0Us5VRmvb4fp1FmKcqc4r6rjNXGVrvDVLK/Ild9LvXpc83NpRWDfvR/jYfaaf/L+m/lovP8bx/UeD4h+ARBAP+E48H5EEI/5GbRf+ea/9PdeJ7Kt/z6qf+AS/+Qf5/eelzQ/ng/P2kdTw3xf8IP2NfH/iPUvGHjjwV8BPFninWDA2qeINfh8H6lq1+baBLa3+1XtzJLNN5NvHHDHvc7Y0VBhVAbrp4nMqUI06dXFU4Rvywi6iiru7tFK2r1vf77+7jKhhZyc508POcrc0pezcnbRXbbvZaLRW87s5v/hnD9gr/olH7Nn/AIK/BFX9dzX/AKCMZ99Qn6thP+fOG+6iH/DOH7BX/RKP2bP/AAV+CKPrua/9BGM++oH1bCf8+cN91EP+GcP2Cv8AolH7Nn/gr8EUfXc1/wCgjGffUD6thP8AnzhvuojF/Zs/YHVndfhN+zWGkILkaV4HBYqMAnk5IHHb+lH13Nv+gjGaedT+v68g+q4PV+xw135Uv82vwXz1H/8ADOH7BX/RKP2bP/BX4Io+u5r/ANBGM++oH1bCf8+cN91EP+GcP2Cv+iUfs2f+CvwRR9dzX/oIxn31A+rYT/nzhvuoh/wzh+wV/wBEo/Zs/wDBX4Io+u5r/wBBGM++oH1bCf8APnDfdRPUPhz4c/Zo+EEWrW/wssvhB8PoNeuILrWYvCV14X0WPVLm1iMNtPerZTxC4lghJijaQMVQkDGTuwrVMbiOV13iKrimlzqcrJu+l0+vr8tGaU6dCkmqao009+SUI3tte2+71avvuel/8LD8Af8AQ8eD/wDwptF/+S6w9lV/59VP/AJf/KzS8f54f+DIh/wsPwB/0PHg/wD8KbRf/kuj2VX/AJ9VP/AJf/KwvH+eH/gyJS1P4heAW0zVFHjjweSdM1EAf8JNovJNlPgD/TByfrz71UKVXmj+6qfEvsS7/wCBfn9wOUEr88NP78X+Gl/v+6x+Y/8AwRo8aeDdO/4J4/BW2v8Axd4YsrlNY+K++2u9f0q2uED/ABY8aSIXhmulkUOjq6EoAyMrAkEV7HENOq81r2p1GuTD6qLtpQpf3X+vnbRHm5RKP1Cl70V79Z6yUd6suj9Py8j9AviLpH7OXxd07TtJ+KMXwl8f6XpF82p6XYeLL3wzrVpYai8LW7XtrDe3EiQ3LW7NCZUXcY2KZIJFeXRnjMO5Soe3pSkuWUoKcW1e9naMdLq/y6a83dUhQqpRqqjUUXzRU5QkoytbmV2rO2nX02PJ/wDhnD9gr/olH7Nn/gr8EV0fXc1/6CMZ99Qz+rYT/nzhvuoh/wAM4fsFf9Eo/Zs/8Ffgij67mv8A0EYz76gfVsJ/z5w33UQ/4Zw/YK/6JR+zZ/4K/BFH13Nf+gjGffUD6thP+fOG+6iMb9mz9gdyjN8Jv2a2MbbkJ0rwOSrdMjkYOOOh/U0fXc2/6CMZ99QPq2Df/LnDXW2lL+vz/WL/APhnD9gr/olH7Nn/AIK/BFH13Nf+gjGffUD6thP+fOG+6iH/AAzh+wV/0Sj9mz/wV+CKPrua/wDQRjPvqB9Wwn/PnDfdRD/hnD9gr/olH7Nn/gr8EUfXc1/6CMZ99QPq2E/584b7qJueGfgr+xX4M8Q6R4t8JeA/2f8Aw34n0C6N7ouvaNbeDbDVdLuzE8JuLG8geOa3mMUskZeM7ijsOATumeKzOpGUKlXFThJWlGXtHFrs1/V9nuVGhhYyU40sPGUdYyXslKPRtNaptO3oz3//AIWH4A/6Hjwf/wCFNov/AMl1x+yq/wDPqp/4BL/5WbXj/PD/AMGRD/hYfgD/AKHjwf8A+FNov/yXR7Kr/wA+qn/gEv8A5WF4/wA8P/BkQ/4WH4A/6Hjwf/4U2i//ACXR7Kr/AM+qn/gEv/lYXj/PD/wZE/PD9kPVdL1f/grd/wAFILzSNSsNVtG+Bf7FiLdabeW19bM8ei/EwSIJ7WWWMshOHUPlTwQM19dRTjkWXxknF/Wcfo00/joa2aT1t2+88NNSzbHtNNewwSutdVGon+P9aH7P1ynaFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf//S/v4oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA/AL/goJ+z78LP2kP+CqP7GPgH4uaDP4i8Ln9mb46aqbG31XUdIk+22Hirw6LaT7VptxbXACC4mygkCtuyeg3egsXXweT4urh5KM/rVFXaUlZxd9JadOvp1PNq0KWIzLDwrR5oxw1aaV2ve5rLVbW6b/AC+17R/w6B/YN/6JRqv/AIXvjT/5c14P+sGaf8/4/wDgqmej/ZWC/wCfT/8AA5f/ACwP+HQP7Bv/AESjVf8AwvfGn/y5o/1gzT/n/H/wVTD+ysF/z6f/AIHL/wCWB/w6B/YN/wCiUar/AOF740/+XNH+sGaf8/4/+CqYf2Vgv+fT/wDA5f8AywP+HQP7Bv8A0SjVf/C98af/AC5o/wBYM0/5/wAf/BVMP7KwX/Pp/wDgcv8A5YH/AA6B/YN/6JRqv/he+NP/AJc0f6wZp/z/AI/+CqYf2Vgv+fT/APA5f/LA/wCHQP7Bv/RKNV/8L3xp/wDLmj/WDNP+f8f/AAVTD+ysF/z6f/gcv/lgf8Ogf2Df+iUar/4XvjT/AOXNH+sGaf8AP+P/AIKph/ZWC/59P/wOX/ywP+HQP7Bv/RKNV/8AC98af/Lmj/WDNP8An/H/AMFUw/srBf8APp/+By/+WB/w6B/YN/6JRqv/AIXvjT/5c0f6wZp/z/j/AOCqYf2Vgv8An0//AAOX/wAsD/h0D+wb/wBEo1X/AML3xp/8uaP9YM0/5/x/8FUw/srBf8+n/wCBy/8Algf8Ogf2Df8AolGq/wDhe+NP/lzR/rBmn/P+P/gqmH9lYL/n0/8AwOX/AMsD/h0D+wb/ANEo1X/wvfGn/wAuaP8AWDNP+f8AH/wVTD+ysF/z6f8A4HL/AOWH5y/8FU/+CZn7Hnwm/ZEvPGPgf4c6jpevp8bf2c9DW7l8Y+Kb5RpviT4y+EtF1eDyL3U54d1zp15cQrLtEkJfzImDhSvr5JnOYV8eqdSspR+r4qVlTgtYUJzi7pPaUVps+qZwZlluEp4VyjTal7agviltKtGMvtvo+q+4/RaH/gkF+wcYYWPwp1XLRRMf+K98Z9WRSemsgdT2H5V5D4gzT/n/AB/8FUzv/srBf8+n/wCBy/Wa/L7iT/h0D+wb/wBEo1X/AML3xp/8uaP9YM0/5/x/8FUw/srBf8+n/wCBy/8Algf8Ogf2Df8AolGq/wDhe+NP/lzR/rBmn/P+P/gqmH9lYL/n0/8AwOX/AMsD/h0D+wb/ANEo1X/wvfGn/wAuaP8AWDNP+f8AH/wVTD+ysF/z6f8A4HL/AOWB/wAOgf2Df+iUar/4XvjT/wCXNH+sGaf8/wCP/gqmH9lYL/n0/wDwOX/ywP8Ah0D+wb/0SjVf/C98af8Ay5o/1gzT/n/H/wAFUw/srBf8+n/4HL/5YH/DoH9g3/olGq/+F740/wDlzR/rBmn/AD/j/wCCqYf2Vgv+fT/8Dl/8sD/h0D+wb/0SjVf/AAvfGn/y5o/1gzT/AJ/x/wDBVMP7KwX/AD6f/gcv/lgf8Ogf2Df+iUar/wCF740/+XNH+sGaf8/4/wDgqmH9lYL/AJ9P/wADl/8ALA/4dA/sG/8ARKNV/wDC98af/Lmj/WDNP+f8f/BVMP7KwX/Pp/8Agcv/AJYH/DoH9g3/AKJRqv8A4XvjT/5c0f6wZp/z/j/4Kph/ZWC/59P/AMDl/wDLA/4dA/sG/wDRKNV/8L3xp/8ALmj/AFgzT/n/AB/8FUw/srBf8+n/AOBy/wDlhU1D/gkL+wfFp2oyp8KdVDxaffSof+E98ZnDx2kzocHWCDhlBwRg4wcZNNZ/mjkl7eOsl/y6p916/wBdtw/srBO69k9f78v/AJN/l95+ev8AwSl/4Jlfsd/Fr9hr4S+O/HPw41HVPE2r6p8Sor++i8ZeKrGOZNM+JfivTLIC2s9Ugt4zFZWcERKRrvKGRhvZjXq55nWYUMyrUqVZRhGNFpezg7c1GnJ6tJ7t9WcGWZbg6mCpzlTbk51U3zy15aktfiil93ray5v0V/4dA/sG/wDRKNV/8L3xp/8ALmvJ/wBYM0/5/wAf/BVM7/7KwX/Pp/8Agcv/AJYH/DoH9g3/AKJRqv8A4XvjT/5c0f6wZp/z/j/4Kph/ZWC/59P/AMDl/wDLA/4dA/sG/wDRKNV/8L3xp/8ALmj/AFgzT/n/AB/8FUw/srBf8+n/AOBy/wDlgf8ADoH9g3/olGq/+F740/8AlzR/rBmn/P8Aj/4Kph/ZWC/59P8A8Dl/8sD/AIdA/sG/9Eo1X/wvfGn/AMuaP9YM0/5/x/8ABVMP7KwX/Pp/+By/+WB/w6B/YN/6JRqv/he+NP8A5c0f6wZp/wA/4/8AgqmH9lYL/n0//A5f/LA/4dA/sG/9Eo1X/wAL3xp/8uaP9YM0/wCf8f8AwVTD+ysF/wA+n/4HL/5YH/DoH9g3/olGq/8Ahe+NP/lzR/rBmn/P+P8A4Kph/ZWC/wCfT/8AA5f/ACwP+HQP7Bv/AESjVf8AwvfGn/y5o/1gzT/n/H/wVTD+ysF/z6f/AIHL/wCWB/w6B/YN/wCiUar/AOF740/+XNH+sGaf8/4/+CqYf2Vgv+fT/wDA5f8AywP+HQP7Bv8A0SjVf/C98af/AC5o/wBYM0/5/wAf/BVMP7KwX/Pp/wDgcv8A5YH/AA6B/YN/6JRqv/he+NP/AJc0f6wZp/z/AI/+CqYf2Vgv+fT/APA5f/LDx/8A4JxfAP4Yfs4/8FPv+CjPw5+Euhz+H/CVp8GP2O9Tg0+51TUNXkS81fSviTcX8hu9SuLi5YSzRowRpCqAYQKOK9+WKrYzJsvrYiXPU+sY6N0lHSMqKSstPtPX0unZOPnUKFPD5njqdKPLFUcI7Xb+KM297vt16dbn7615x6QUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB//9P+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR+mlfIHuBQAUAfnp8Sv+Cov7Hvwn+Jnjj4ReLfG3iP/hOfhzqkGjeL9M0TwP4j1+LSNSubODUIbWa80u0nt/Me0uYJtu8ELIDjBr2MPkWY4mjTxFKinSqxcoSc4K6Tts5Rdr9beWn2uCrmWDo1Z0alRqpB2nFQm7N92lJfK2nn9njv+Hv37Ef/AEN/j7/w1Xjb/wCVtbf6uZp/z5j/AODKf/ywj+1sD/z8l/4Lqf8AysP+Hv37Ef8A0N/j7/w1Xjb/AOVtH+rmaf8APmP/AIMp/wDywP7WwP8Az8l/4Lqf/Kw/4e/fsR/9Df4+/wDDVeNv/lbR/q5mn/PmP/gyn/8ALA/tbA/8/Jf+C6n/AMrMjTv+Czf7BmrXmr2Gm/EDxje3mg3gsNYt7b4aeMJ59PvGiSYW13FHp7PbzGKRJBHMI32MrBNpzTfDObJJuhFKSuv3kNVe1/j2/pc124ys4wDbSrNuLs17Opo//AX+X3bGv/w9+/Yj/wChv8ff+Gq8bf8Aytpf6uZp/wA+Y/8Agyn/APLCv7WwP/PyX/gup/8AKw/4e/fsR/8AQ3+Pv/DVeNv/AJW0f6uZp/z5j/4Mp/8AywP7WwP/AD8l/wCC6n/ysP8Ah77+xJ/0N/j7/wANV42/+VtH+rmaf8+Y/wDgyn/8sD+1sD/z8l/4Lqf/ACs+o/2Zv2u/gZ+13onjHX/gd4lvfEWn+AvFB8G+KhqGjahoV5pXiEadaaqbCey1KKK5WT7DfW0x3IMCUAgcV5+Oy7FZdOnDFQ5JVYKpBJppxbaumm76pr8Nd5dOGxdDFxnKhNyUJ8krpq0rXa1s1ZNbrrpbU+Qv+Czf/Jjt/wD9nCfsrf8Aq+vBNd3D3/IyX/YLjf8A1GqnNm3+5v8A6/Yb/wBP0z9UYP8AUQf9cIf/AEUteGekS0AFAHyH+1D+298Cf2Q9T+HWi/F++8UprPxVfxEngrSPCXhXVPFep6p/wisFjc644sdKiluEjsoNQtZHcqQVcnjblvRwGV4vMVWeGjCSoKDqOc1BLn5uXV2v8L2flpdHJicbQwjpqtKSdVyUFGLk3yJOW1+ku3krs+cf+Hvv7Jv/AEC/jx/4Y/xz/wDINd3+rWZ/yUP/AAdH/wCWHP8A2tg/5qv/AIKqf/Kw/wCHvv7Jv/QL+PH/AIY/xz/8g0f6tZn/ACUP/B0f/lgf2tg/5qv/AIKqf/Kw/wCHvv7Jv/QL+PH/AIY/xz/8g0f6tZn/ACUP/B0f/lgf2tg/5qv/AIKqf/KzCvv+C0f7Fuma1onhzUH+M9nr3iRNQk0HSbn4N+Mob/V00qOObUm060e0We8FjFNHJdGBHECOjSYDCqXDGatOSp0Wo2u/bRsr93zPrtqr7eZLznAqSi51OaV7L2U7u29lyLbra/otzd/4e+/sm/8AQL+PH/hj/HP/AMg1P+rWZ/yUP/B0f/lhX9rYP+ar/wCCqn/ysP8Ah77+yb/0C/jx/wCGP8c//INH+rWZ/wAlD/wdH/5YH9rYP+ar/wCCqn/ysP8Ah77+yb/0C/jx/wCGP8c//INH+rWZ/wAlD/wdH/5YH9rYP+ar/wCCqn/ys7z4P/8ABT39lz42fGDwd8C/Clz8RtM+Inj6z8QX3hXTfGPw68ReFLbVbbwvYDUdaa2vNXt4YpDZ2rK8ioWI3oD975cMTkWPwmHqYmtCmqVNxUnCopNObstE5Pf0/Q0o5lha9WFGnKftJ83KpQlG6iryfvRitPw8vtfoBqn/ACCtV/7Bepf+kU9eTD44/wCKP5nefl7/AMEXP+UdfwT/AOwx8Wf/AFbfjWvZ4i/5G2I/wYf/ANR6R5uUf8i+l/18r/8Apxn6oV4h6QUAQ3EyW1vcXMmfLtoJriTAyfLgjaWQgdyEQ4Heha6d/wCvL8/uA/Jrw1/wWV/Zk8Z6Na+I/CPw+/aP8TeHr+S8TTtc0T4M+I9R0nUFsby4sJ5bG9gieG4hW5tpo/MjYjchGSQQv0b4XzFOzlhouydnXimrq6utbaP/ADtax5Uc5wkkpRjXabdmqMmnZ2dn1t/w25u/8PbfgR/0SH9qT/wxnin/AOMUv9WMw/nwv/hREf8Aa+F/kxH/AIJkH/D234Ef9Eh/ak/8MZ4p/wDjFH+rGYfz4X/woiH9r4X+TEf+CZDJP+CuHwFijklk+Ef7UaRxRvLI7fA3xSFSONS7ux8gYVVUsxzwBk4xR/qxmH8+F/8ACiP/AAfy+8P7Xwv8mI/8EyOd8H/8Fnf2YfH3hzTPF3g34eftJeI/DWsxzS6XrWkfBfxJfadfRwXE1pM9tdQxPHKsdxBLC5U4Ekbr2NVLhbMoScZywykt068V+GttLfra1iYZ1g6kVOMcQ4u9pKi7O29vmdL/AMPbfgR/0SH9qT/wxnin/wCMVP8AqxmH8+F/8KIlf2vhf5MR/wCCZB/w9t+BH/RIf2pP/DGeKf8A4xR/qxmH8+F/8KIh/a+F/kxH/gmQyT/grj8BYo5JZPhH+1GscUbyyMfgb4pASONS7sx8gYVVUsTngAk4xR/qxmH8+F/8KI/8H8vvD+18L/JiP/BMj7m/Z1+PngH9qH4L+A/jz8LptSuPAXxF0yfVvDk2r2Mmm6i9pb6heaZL9qsZfnt5FurGddjZOADxnFeNjMJVwOJq4Wvb2tFqM+Xa9r6O7vo/+H0cu7D16eJo069K7p1FzR5lyu12tVd21Xf7j46/ZU/5S7f8FIf+yE/sU/8Apk+JtfUYf/kQ5f8A9hOP/wDS6B5P/M3x/wD2D4L/ANIqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/9T+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR+mlfIHuBQB8H3/wDwU2/YW0vVNX0W+/aJ8FQ6poOq3+h6vaBtQlex1bS7iS0v7GZobKVPOtbiN4pVB+V1wcfxepHJczlGMlhKvLOKlFpXvFq6fz6bfPRnH/aOCvKP1mneLae+jTs0+l9D81f2Mf24/wBifw5+07/wUf8AFfj74qeB7XRfiJ+0X4e8QeA9X13Rrm4h8Q6Db/DPwpps+oaVNc6XKz2keo2tzbsVKjzo3687ft6eBxccuyun7KSnTw9SM483K4y9o3yvW6bVnt5a393w6WKwv1vHylUg4zrxlBvVOPs4K6vy2V7r4vkrxcv0g/4eN/8ABNn/AKLR8Jf/AAQf/eap+pYz/n1P/wAGnX9bwX89L/yX/wCWB/w8b/4Js/8ARaPhL/4If/vKf5fnR9Sxn/Pqf/g0PreC/npf+S//ACb/AC+8p2P/AAUs/wCCZupQtcWPxw+EF1FHNLbvJDoiyKs0DlJYyyaMwDxupVlyzAjBAIxTeBxq0dGotE7Oo9U9t1rddl6roKONwMr2qU2l1037a8vbu/wTl+dn7Fv7bf7DnhD9pL/got4h8Y/Ev4faV4e8fftG6X4g8AX2paBILPXPD8fgLw7ZSX+j79IZfsYvoJ4W8tUXzUfIJJNdeJwmKlRwSjTm3Cg4y/ear3tIt3eqtv1t10kceFxOEjXxvNOFpV7xbjo0oJXTfImr6aNrbe6P0f8A+Hjf/BNn/otHwl/8EH/3mrj+pYz/AJ9T/wDBp2/W8F/PS/8AJf8A5YH/AA8b/wCCbP8A0Wj4S/8Agh/+8p/l+dH1LGf8+p/+DQ+t4L+el/5L/wDJv8vvPq74NePPgD+0D4D034nfBy48DeO/Amr3ep2WneJNG0XTpLC6u9G1CfS9TgRpLJGEllqFtcWsylQVliYHGMVjUp1aM3TqqcJqzcXOTdmk136Nfra1jelKjWgp0uSUW2rpRtdOzV9dU18vK9j87/8AgnRa2tl+0L/wVYt7O2t7S3i/br1JIre1hjt4IkHwk+HJCxxRKsaKCScKqjJJxk/L43E22U3bb/s+Or3f7+vvv+f3hlSXNmH/AGHT8v8Al1S/r/hyb/gs3/yY7f8A/Zwn7K3/AKvrwTXDw9/yMl/2C43/ANRqppm3+5v/AK/Yb/0/TP1Rg/1EH/XCH/0UteGekS0AfI3x2/br/Za/Zq8bab8OvjP8UbDwf4z1fw5H4s0/QZNO1XUr6fw9LfXOnR6p5Wm2dyY7Zr20uLcPJtBeIjPQ16OFyrH42k62Fw8qtOM/ZucdlOyfLrbW0lsnv5XOSvjsLhpxp16sYTlHnjF3u43avotFdNdfRa835HftE/8ABQ79j/xh+31/wT6+JOkfEpdY8BfC/S/2mIfHeu/8Il4klsPD83i7wf4YsfDi3qy6QcNqV5Z3ENvhWy8LEgYBr6zJMrx2GwuYwrUXTnW+rckXKKclCc3Ltol52u7aM8bHZhg6mKwUo1eaNP27m1GTUeaCSu+Vb73s9rW0P0g/4euf8E7v+ix6D/4RWv8A/wAz1d/9n43/AJ8/+TGv9o4L+df+AS/+Vh/w9c/4J3f9Fj0H/wAIrX//AJnqP7Pxn/Pj/wAnD+0cF/Ov/AJf/Kyl/wAPbv8Agm//AGidJ/4Xf4YOpi1F8bD/AIRDWvti2TSGIXRtv7E877OZVaMTeX5ZdSoLMpRT+z8bv7B2782l+3r8/uF/aWBvb2kb6O3K72va9uW/4L5n56ftH/8ABQn9jLxV+39/wT4+Jnh34g2eo+Afhjo37Tdv8QNetvBWviw0Cfxd4Q8MWPhlb8f2IhZtRu7S6itsK+HR8gYzXVSwWJWExtN0+WdSWG5I+0V5qE7ytqmtGt+q/vXjxYjG4WWMwM4z9yn9Y9paErLnhFRvorap9H87Pl/Rj/h65/wTu/6LHoP/AIRWv/8AzPVy/wBn43/nz/5Md39o4L+df+AS/wDlYf8AD1z/AIJ3f9Fj0H/witf/APmeo/s/Gf8APj/ycP7RwX86/wDAJf8Ays9p+Af7bP7I37TvjPWvh98E/H3h3xn4w8PeHovFWsaHDoFzp97ZaBPff2bDqTxalptqzW8t7m3R0BBdWHG1hWVbDYiglKtT5ISbSlzXV0rteTtrq9uxrRxWGxE3ClKMpRjzNctmle3VLr5fefKH7W1paW//AAVB/wCCX/2e1trfd4X/AGuSxgt4Yd2PBnhPG7yo0yRngnp2zk7eTHf8ibMv8eEf/k81+SXb8W5RJJZnl7SV3HFLRW+xH/N+vyP1C1T/AJBWq/8AYL1L/wBIp6+Fh8cf8UfzPdPy9/4Iuf8AKOv4J/8AYY+LP/q2/GtezxF/yNsR/gw//qPSPNyj/kX0v+vlf/04z9UK8Q9I4/4hePPC/wALfAfjL4leN9SXR/B3gHw1rHi7xTqzxvKum6BoNlLqGqXzRR5eQW1pBLKUQbmC4GSRWlKlOvVp0aa5qlWcacFteU3yxV+l20RUqRpQnUm+WFOMpyfaMVdvrsl2+8/OWX/gr/8AsM6voNxc6b8QPF17b6no1zLp9xb/AA08aTQXcV7YSG1lhlTSzHJHOssbRyK21lYMCQc17keG82UlehFcslf95DSz1v76/Lz1PO/tjL3G6rN3WnuT6rTXVfh958Xf8Eu/+CkP7J/wJ/YQ/Z++FHxT1nxj4b8e+EdD8SWviHRbj4XeLp57Ge98beJNUtkklTSijGSyvbaUFSeHAOMV9pi8DiamJqzhGMoycbS542doRWi5lazVt3f5I8jA4/DUsLShOc4zSd705dZNrWyvo/8AhtVH78/4e+/sH/8AQ6+K/wDw1HjD/wCVNc/9nYv+SP8A4HH/AOWHX/aeE/5+S/8ABcinqP8AwWN/YB0iwvdV1Px/4jsNN061mvb+9u/hd4tt7W0tLdDLPcXE8umJHDDFGpeSSR1RFBZiADTWXYxtJU43bsveju/+4gPNMGk26krJXf7uWy/r+rFC+/4LBfsFa14a1CXSvHXia9i1bw/ftps9v8LvF0kN2t/pkws5IJk0go8c/mxmN03qysCGOc0nl2MvrTSd19uKa1X957en3CeZ4Nxf7yVnFtfu5aq3T3Ve/TR3/A+G/wDglt/wUf8A2UPgP+wZ+z78J/irrPjHw34/8IaH4ktfEWiXHwv8XXE9jPe+NvEmp2qSTJpOxzJY3trKCpbiTB+7XXjsFiKuLr1KcYyhJxcZe0i01yRWi5lazTXnvpdKPJl+Ow1LCUac5ShKKmmvZy2dSTXRX3v138rn3/8A8Pff2D/+h18V/wDhqPGH/wAqa5P7Oxf8kf8AwOP/AMsOz+08J/z8l/4LkUtT/wCCx/7AGjadf6vqvxA8R2GmaZaXF/qF9d/C7xbb2tnZ2sbTXFzcTy6UI4YYYkZ5JJCERQWYgDNNZdjG0lTjd7WlF/8At7/L7weZ4NJt1JWSu/ckrLvfpb+tj9FYNf8AD3jT4Z/8Jl4be2v/AA/4r8BS+JNCv1tkjF5o+ueHX1LTLtVYB0FxZ3MMoVl3KHwwBGK42nGVnpKNRRavtKM7NX8mmrnY5KdNyjtKDa9GtO39d9z84f8AgjcAP+CaP7KmBj/ijvEHTj/me/FP+f8A9dfMcRf8jnH/APX7/wBtiaZV/wAi/C/9e3/6XIl/ZU/5S7f8FIf+yE/sU/8Apk+Jtevh/wDkQ5f/ANhOP/8AS6Bx/wDM3x//AGD4L/0iofshXMdgUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQB/9X+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR+kesavp3h/SNU17WLuKw0jRNOvdW1S+nO2Cy07TbaW8vbuZhnbFbW0Ms0jY4RCecV8lGMpyjGKvKTUYru27JK/VvQ9ttJOTdkk230SW7fax8J2/8AwVM/YAmEU0X7Tfw+miZgVkjn1CSNwHwSrpZFHGQRlTg+2a9T+ws2X/MFW+7/AO1f6ei0cuJZngHtiqTXdX/4Y/K7/gmR+1R/wTn8K/A34iW/xp8WfBy18X6r+0l8fvEFu3jDwpDd6xeeHta+I2tX+g6gLi80eaeSzvdPmhnsyzkeSylcKQq/fVsLjrUFGNVKOFoRkoy09ooJSVkpWa2eyutO54GDxOBhCr7SVPmliK0veir2c3Z6xlurP/PTl/Rj/htD/gkZ/wBDt+zn/wCEZp3/AMov8P1IbD6rj+1f75f/ACD/AE9NDr+uZb/NR/8AAI//ACsZJ+2n/wAEiYkeWTxz+zikcaNI7t4N00KiICzMxOhABVUEkk4AGTjBo+qY/tX++X/yC/P7g+uZb/NR/wDAY/8AyC/P7hLT9tj/AIJCXUcNzb+PP2b57eYLJFNF4O02SKRD0dGTQ2V1PYqWB/8AQh4TMEn7te9mrOTT7fy6Ndrp9NbXD65lr2lRa7qCX/tt1/4F5vTQ/Ov/AIJi/tP/APBNzwR8BPHGk/FnxL8FdL8R3X7RHx51jT7fxN4QtpL+TwxqvxF1u88O3UDXGjSONOudLlt5LFFbYtuYwiqoxXZjsPjZ148kaqiqNFPlndcyhqrR59U76v00t73DgMRgadGaqOkm69Zq8U3yubcd4PRp3S6J9Phj+jH/AA2h/wAEjP8Aodv2c/8AwjNO/wDlF/h/MNyfVcf2r7W3l/8AIP8AT00O765lv81H/wAAj/8AKxkv7an/AASIhjkml8c/s4xxRI8sjv4N00KkcalndidCACqoJJJwAMnGDS+qY/tX+9/rBfn94fXct/mo/OMf/kF+f3H2x8P/AIe/sufFHwh4a+IPgH4cfCPxP4M8W6ba614c1/TvBfh6Ww1bSrxRJbXto509C8MyEMjY6dfSuWbr05ThOpUU4XTi5Xtdf9u6rXrutEkkdkI4epCM4U6coSXNGSjGzX/gH4fJrdHw9/wRWtLWw/YouLKyt4bS0tf2k/2rre2tbaNIYLeCH9oDx7HFDDFGqpHHGihERFVVVQqjA+XqzHXExd228Ph229Xd0KXf1OXLFbDSS0X1jE7f9fpGZ/wTw/5OL/4Kt/8AZ9upf+qk+HFfOcTbZT/2L4/+n651ZX8WYf8AYdP/ANNUhP8Ags3/AMmO3/8A2cJ+yt/6vrwTXDw9/wAjJf8AYLjf/UaqaZt/ub/6/Yb/ANP0z9UYP9RB/wBcIf8A0UteGekfEHxO/wCCkP7Gnwd+I/iv4S/ET4y6VoHxA8EzWNv4o8OnTNYvbrSJtTsINTsY7l7Cxuo1a4sbiG4QEjKOCMjFepRybMsTRp16GGnUpVLuE1y2fK7Pea2aa/y2jxVMxwdKpOjUrxhUhbmi1LS6utlLo/8AhtEflFcft5fsRa9/wVdv/jF4l8b6JrnwoH7Deh+ALTxLrPgrV9T0dPHNv8YNd1qfR4UvdFlCX66PdQ3RYRr+4kAy2WVfsMry7H0cpdCdGdOr9flV5eZKTi6EYp6Ss7PXfdW0veXh18bg55p7X2kZ0lgo0+ZxbXP7Wc7axve1tLLo+Z2tH9Cf+Hjf/BLPp/wmfwzx/wBkwm/+Zuuj6jj/AOSt/wCDIm/17Lv56f8A4LD/AIeN/wDBLL/oc/hn/wCGwm/+Zuj6jj/5K3/gyIfXsu/np/8Agso23/BS7/glFeXV/Y2vj/4VT3mlyQxahbRfDZnns5LiITwpcRL4dZ4WlhZZUEgQsjBlBU5o+oY9WfJW1299a27O9u/823k2H1/Lrtc1PR6/u9nvZ9nbvb0W8vz+g/bV/wCCf6/8FUdX+Kza74LHwfm/Yn0HwRDrf/CuLv8AsFvH1v8AFjWNWuNNW2/sHyhqaaNNBO8wh3G3ZVLbRhuz6ri3gPZcs/a/W5T5edc3J7KKUr8y0TV7abpa7nJ9bwX191Lw9n9WUb8mjlzt/wAlrqN9L9d+p+h//Dxv/gln0/4TP4Z4/wCyYTf/ADN1x/Ucf/JW/wDBkTr+vZd/PT/8Fh/w8b/4JZf9Dn8M/wDw2E3/AMzdH1HH/wAlb/wZEPr2Xfz0/wDwWfR37O3xp/Yr/auj8Yy/AVPhr48XwBqOn6V4uFl4I0y1k0XUNUtDfWFtdQ3ukW8qvc2g89PlXKc8jBbGtQxOH5PbOrDnTcbzvezS0s0nq/00veO9CrhcTz+xUJ8jtK0Fo+2qWv3fO6Z8r+E/D2geHP8Agtd40tfD+h6RoVrL/wAE6/A80tto+m2emQSTH44+L0Mrw2UMMbyFUVS7KzFVUZwqhdZt/wBnRTlKX+2VN2/+gdd2/wA/u0MYpRzOXKlH/ZIp8qSWk+tt9f60Za/a8/5Sg/8ABL7/ALFf9rn/ANQzwnXBjv8AkT5j/iwn/pyoaz/5GWX/AOHFf+kQP061T/kFar/2C9S/9Ip6+Fh8cf8AFH8z3D8vf+CLn/KOv4J/9hj4s/8Aq2/GtezxF/yNsR/gw/8A6j0jzco/5F9L/r5X/wDTjPu/48/Hr4W/sz/DHXPjF8ZfEkfhL4feHbrRrLVtcltri7W3u9f1S20bSYFt7VJJ5ZLzUry3tYkjGTJKoGSRt83CYSvja8MNhoe0qzUnGN7XUYuUvuSb/wAtZR7K9elhqbrVp8lOLScrN/E0lou7fl+al+R/7a//AAVE/Y5+Jv7Hf7Uvw68F+OPE+teL/HXwA+K3hPwvo8Xw58aLLqmv694N1bTtJsI2k0dUWS6vbiGFGY4DOCcAE19Dl2QZpQx+Br1KMY06WKw9ScvaU9IRqwcn8bvaKb0Xpax5eNzLBVcHiqcKkpTnh60YLklrKVOSivhXVrr951P7M3/BS7/gn74N/Zx+AfhHxXq72Xijwv8ABv4a+HvEdlcfB7X5bi013R/B2j6fq1tPL/wjr+ZNBfW88Ukm5t7qTk5zX1FbA4udatJK6lVqSi1VjrGU24/b7PbW23S0eShjcJGhRjL4o0qcZfur6qCTv53Wvn6Ht/8Aw9T/AOCb/wD0MSf+Ga8Qf18OH+f5Vl/Z+Lf2X/4Nj/8AJr8vvNfr2D/qkZuq/wDBWv8A4Jk6Fafb9a8Z6fpVj9otrX7ZqHwk1mzthc3s8draQGefw/HGJbm5liggj3b5ZnSOMM7KjNZbjW7KEm+yqJ7elT83FLe+5MswwMVeTsrpX9l1ei/HppfZatKXzd+29/wUe/YM+JP7G/7Ufw+8AanLqnjjxt8Bvid4Y8IabZ/CDxBBdX/iLWvCmo2Wk2ltP/wjyeTNcXk0UccvmLsZgdwxmtcNgcVDE4ecl7sa0JN+0i0op7253+X3mOKxmFnhq8YaylTko2pPdrSzV3+H3na/sz/8FL/+Cfvg39nL4C+EfFervY+KPC/wc+Gvh7xHZXHwe1+W4tNd0fwfpGn6rbTy/wDCOv5s0N9bzRySbjudSec5pV8Di6larNR0lUm1arHVOTafxR79vu+1dDG4SNGlGXxKnBP93fXl1101vv8Arue3f8PU/wDgm/8A9DEn/hmvEH9fDh/n+VZf2fi/5X/4Nj/8mvy+41+vYP8AqkEf/BVX/gmu17pNjN4u02xl1vWtH8PadLqfwo1fTrSbV9f1G30nSbN7u70CG3ie81C6gtovMcbpJABknFH9n4vX3XonLSqm7RV27KUm7LXRfKX2U8wwKtdpXaSvTtq2kl13bS/y3PZ/+CkXhTwpD/wT2/bbuLfwx4dglj/ZY+N8sM0Wh6ZFLE6/D/W2SSORLVZI5EIDK6kMpGRyKxwjf1vCNSl/vNH7cn9tfeaY6MfqWKajH+BU1SX8r7Hr37OH/JmnwP8A+zZfh5/6q3Sqmv8A7xW/7Can/p5mtL/dYf8AXlf+kHx9/wAEb/8AlGl+yp/2J3iD/wBTvxTXynEX/I5x/wD1+/8AbUdGVf8AIvwv/Xv/ANvkS/sqf8pdv+CkP/ZCf2Kf/TJ8Ta9fD/8AIhy//sJx/wD6XQOP/mb4/wD7B8F/6RUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//1v7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2l+0SM/s/fHUHkH4N/FAEHv/xRGuV8zg/98wv/AGE0P/TsT2K38Cv/ANean5Hxj/wTA+A/wS1z/gn5+yZq2s/CL4carqmofBrwndX2o6h4O0G7vby5ls90k9zcz2TSzTSN8zySOzsTlsH736Di6tX63iUqtSKVWVkpf1/XoeFl9GlLB4dunC7pxb93V3Sbvq29Xu3fpofeP/DOXwAP/NE/hZ/4Q3hz+tjWHtK3/P8Aq/8AgZ2ewo/8+4fcH/DOX7P/AP0RP4Wf+EN4c/8AkD/H+YU9rW/5/wBX/wAD/r8/uD2FH/n3D7jyD9oT9nr4DWnwC+ON1a/Bn4YW9zb/AAf+Jc9vcQ+CfD0c0E8PgvWpIpoZEsd0csciq8bqVZGUMDkLV0qtX2tK9ao/3tNWcu84/p+foZV6FFUar9nC6pza91aNReqv10/q6Pnf/gmb8BPghrP7Av7J+qat8IfhvqWpX3wZ8IXN7f33g3Qbq8u7iSxBkmuLiayaWaVzyzuSzHk8mtsbVrfW8QlWqJKfSVu/9dPPe8ssDRpPB4dunC/s4u9tXfXX7/8AguyUfuf/AIZy/Z//AOiJ/Cz/AMIbw5/8gH/Pp1rm9rW/5/1f/A/+H/L7zq9hR/59w+4P+Gcv2f8A/oifws/8Ibw5/wDINHta3/P+r/4H/wABdn3/AFD2FH/n3D7jxX9pP9nv4D2f7Ovx8urT4M/DG2urb4L/ABQnt7iDwR4ejngnh8E63LDNDIliHjlikRXjkUhkZQVIIzWtGpW9tS/fVH+8ho5u3xLt5afP1Mq9GiqFZ+yh/Dn0/uvVb237fec1/wAEtI0i/wCCe37IKRosaL8E/BYVEUKqgWKgAKMAAAdAPy4pY7/esV/jl+cgwKtg8N/15g/vV3+LPE/+CMH/ACZjf/8AZzH7WX/rQfj+tsw/3mP/AGDYf/0xSMct/wB2l/2EYn/09IxP+CeH/Jxf/BVv/s+3Uv8A1Unw4r5zibbKf+xfH/0/XOrK/izD/sOn/wCmqQn/AAWb/wCTHb//ALOE/ZW/9X14Jrh4e/5GS/7Bcb/6jVTTNv8Ac3/1+w3/AKfpn6owf6iD/rhD/wCilrwz0j8lv2OvBPg3xR/wUI/4KvTeJfCfhvxDNbfFH9n9LeXW9E03VJbdH+CWis6QvfW07Rq7AM6pgMRkjIBr7/CznHJspUZSjeOIT5W1/wAv32t/Xe7R8/TjGWY5lzRjK1Sha8U7fuId/wDgfkpfqh/wp/4Tf9Ex+H/0/wCEP8Pf/K7H6fj2quep/wA/av8A4FL+vx+47fZU/wDn3D/wCP8Al+v3/ZjT4S/CCR3jj+G/w6eSI4ljTwn4baSMnp5iDTyyZ/2lH6kUc8/+f1X/AMDl/muum337B7On/JD/AMBj/XRkn/Cn/hN/0TH4f/8AhH+Hv/lbRz1P+ftX/wADkHs6f8kP/AIn5T/sX/DL4b3f/BQH/grDY3Xw/wDBdzZaZ8Vv2eotNtJ/DGizW2nxT/ATw5PPHZQSWTxWqTTM0sqwooeRi7ZZi1duJnP6tgLVJpunWu1KV3++nv32W9+3nHz8LCDxePvTg7VaSXux0XsY6L7/AC/SX6sH4QfCUAk/DL4fgDkk+D/DwA9yf7PAH+eT0ri56n/P2r/4FL+vw+89D2VP/n3D/wAAj/l+v3/ZiX4S/B9iAnw4+HLseir4T8Nsx+iiyYn8F/Poq55/8/qv/gcv/kn102X6B7On/JD/AMBj/X9eRL/wp/4Tf9Ex+H//AIR/h7/5W0+ep/z9q/8Agcg9nT/kh/4BE/M39gfRdH0H9u7/AIK06boelado2nW/xr+BqwWGlWdvYWcKt8DPDUjCK2tYooUDSO7ttXl3YnJbNdmJbeEy5tuT9nU1erf7/v8AL+rHn4NJYzMUkkvaUtErJfuo+n9b31ZraZ/ym18Y/wDaOfwN/wCrz8ZVE/8AkXx/7DJ/+o6LX/Izl/2Cr/0so/tef8pQf+CX3/Yr/tc/+oZ4Trhx3/InzH/FhP8A05UNJ/8AIyy//Div/SIH6dap/wAgrVf+wXqX/pFPXwsPjj/ij+Z7h+Xv/BFz/lHX8E/+wx8Wf/Vt+Na9niL/AJG2I/wYf/1HpHm5R/yL6X/Xyv8A+nGR/wDBZ2OOb9hHX4pY0ljf48/sqI8cqLJG6N+0N8PlZXRgVZWUlWVgQQSCCCRWnDLazihb/n1ivL/mGq/1/wAOTnP+4VP+vlD/ANPQP1Pj8C+B/LT/AIozwn9xf+Zc0f8Aujv9kr6BXsvelsvtSK5I/wAsfuiEngnwHEu+bwj4PiUkLvl8P6JGpY9F3PagFj2HU9s9Kev80v8AwOX9f15ByQ/lj90R/wDwgvgc4P8AwhnhPB5H/FOaPyD0I/0TuD+NGv8ANL/wOQckf5I/dE/KX/gtB4Q8JWX7Dd7PZeFvDlnP/wANG/sjReda6FpdvN5c37R/w5jmj82K2V9ksbNHKmdsiMUcMpK135Zf63u3/s2L3k3/AMuJ9/O39WPNzaMVhF7qV8ThVoktHXpp7eX5+bP1YTwJ4H2J/wAUZ4T+6v8AzLmj+nr9kH8vyrzotuMXzSu4p/HLseioRaXux2T2iNl8FeAoV8yfwj4PhTcF3zeH9EiTcei73tVXcT0GcntjndWv80v/AAOX9f15D5IL7Me20ST/AIQXwOcH/hDPCeDyP+Kc0fkHoR/oncH8aNf5pf8Agcg5I/yR+6J+V3/BZTwl4U079iV7zTvDHh6wu4/2kf2ShHdWWiabaXEYf9oPwIrhJ4LZZVDr8rBWG4HByOK7cubWMj70v93xejk3f9y++3e/+aPOzSMVhU0kn9Yw1rJf8/oLp5N/02fUH/BSb/lHh+27/wBmqfHD/wBV5rlYYP8A3rB/9hFD/wBLRvjf9xxP/YPU/wDSDv8A9nD/AJM0+B//AGbL8PP/AFVmlUq/+8Vv+wmp/wCnmaUv91h/15X/AKQfH3/BG/8A5Rpfsqf9id4g/wDU78U18pxF/wAjnH/9fv8A21HRlX/Ivwv/AF7/APb5Ev7Kn/KXb/gpD/2Qn9in/wBMnxNr18P/AMiHL/8AsJx//pdA4/8Amb4//sHwX/pFQ/ZCuY7AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD/9f+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9pftEf8m/fHX/ALI38T//AFCNcr5nB/75hP8AsJof+nYHsVv4Ff8A681PyPCP+CVn/KOz9kH/ALIl4P8A/SKvvsX/AL5iv+vr/U8bLv8AcsP/ANeof+kxPaf2rP2jNJ/Zs+GEvicWa+IvHvifU7TwX8J/AkMqLqHjf4ha6Tb6HpNuhYOLG3mb7frV4AY7HS7e4mkK/LU0aLrT5b8sUnKpO2kIL4nfvbSK1u+1rmuJrqhTvbmnJqNOC3lN7JfJNvyTfQ+KP+CXmv8Ax2m8V/tpeCv2gfifd/Evxn4J+PGlQrNLNG2meHE8QfD7w14jv/DfhyCM4h0LStR1O4tbJSCSseSxYmujGqly4SdGn7ONSk31vKzklKV93prv5do8mXyrOWKjWqOpKFZfLmhGTikm0lFuy3v5WaP0K/aM/wCTe/jv/wBka+J//qEa5XLT/i0v+vtL/wBLid1f+BW/69VP/SGfN/8AwS7/AOUe37Iv/ZEvBv8A6QLW2N/3zEf4/wDMxwH+54b/AK9RPSv2u/hz4o+JHw4tLLS/ih4u+GPg7w9qsvir4oTfD+3mk8ceLPBmi6ddXM/hTw3d26vc2F1qF0IXlltR9pmii8iL5nrOjJQnf2cak7WpqfwRm3pKS2aSvu7Lzuy8TTdSnb2kqcYvmm4aTlFL4Yvo33VvwtL4w/4JX/EDUvGuqftRWXh/xh8Rdf8Agf4X+JGi6R8JdD+M9zcv8V/DSjw5aSeKYdctNSCataaHe62Zrnw6NQTzJbNvMjZoyK6cdDk+rc0IRqyg3VdK3s5O75bNPWSXxNeTfK3aXJl83J4hKU3RjNKkqrbqR933r8yUrOXwvqu1ko/oT+05/wAm2/tBf9kS+Kn/AKguu1zUf41P/HH80duI/gVv+vc//SWfPv8AwS4/5R8/sh/9kU8Gf+kK1WN/3rFf45fnIzwX+54b/rzT/wDST8jv+Ca37W37Qvws/Z78U+C/AX7DvxZ+M/hjTf2k/wBqCSx+IHhbXvDtjourvefHTxxdXUNtb38y3SPYXEr2UxcBWlgcrwRXoY2hRnWhKeLp0pPD4Zckoybj+5gr3WmqV9dvmeXg8VWpUpwhhKtWPt67U4tW1qz/ALsrW217X6tR+nf+CSXjXxN8Q/iP/wAFM/GHjD4e618LfEWu/ttX97qvgXxBcW13q/hy6f4VeAI20++uLNmt5J0SJJS0RZdsqjIIO75XiqKhLK4xmqkVl8bTjs/31Xb1bf5dD1MmnOax8pwlTbxsnySteP7qkrO3pf5+p6T/AMFm/wDkx2//AOzhP2Vv/V9eCa87h7/kZL/sFxv/AKjVTozb/c3/ANfsN/6fpn6owf6iD/rhD/6KWvDPSPy9/Yd/5SCf8FZP+yp/s+/+qQ0avvcN/wAifKPTEf8Ap88Gj/yMcz/6+UP/AExA+8f2rvibq3wX/Zh/aF+Lugosmu/DT4M/EfxtoqunmINW8O+FdT1LT3eMZLrFdwQysgB3hCvGcr0UKfta1Km9qlSEH6Skk+q1s9NfvN8TUdLD1qsVeVOlOSXmotrt1/p7H4afsq+JbfwH8Q/2NPiZ4w0f9p/4dv8AHLUrXQp/jN488Vf2/wCBvj/4u8a+DrvV4PD/AIn8ITzyHwZBrN/BPq/gq5hhieJbKKxztnwvo11zQxUIyoTVJNqlCNpUY05KLaltL+WS6atOVrx8rDy5JYWc1Xh7VqPtZyUo1pTV7SV/cu17vxNct+bVo/pJryFsv61/4c9w/Jn9ib/lIX/wVv8A+ytfs6/+s/8Ahuu3E/7tl/8A17rf+nqp52E/3zMP+vtP/wBMwPuj9q0eJj+zD+0Qvgr+0/8AhMG+CXxPXwr/AGL5n9sDxCfBmsf2OdL8nEo1EX/kfY/K/efaPL2ZYgVjh+X29Hmty+1p819uXnje/dW38vmdWJ5vq9fkvzulUUbaPmcHaz6O+22vVaM/Ef8AY6u9D+CXi39kfxT8a/gb+038N734uRaB4D8JfEv4ifFfU/EOgar8V9c8Hzyvpvi/wRNcyNojeJZLXVX0Vb1CI7lYo2CSlRXdX/erERpVcPNUW5yhCnZqlfTknu+VW5vd621Xvnl4X93LDyq0q9P2ijCNSVRyXtHFW5ouzV2nvtpvdo/o2rylsvTqe2fk1+w7/wAn9/8ABW//ALLb8C//AFRPhiu3E/7nl3/Xup/6fZ5uE/33Mf8Ar5R/9NRPnH9oP4rfGf4Tf8Fj9R1f4K/APVP2gNb1P9gHwZYav4f0rxFp/hybRNNj+NPjGaLVZLjUcx3Ec1wTbCGP5wQW4yDWtOlTqYC1StGili5NOSb5r0Irl073/G62ZjXq1aWYt0qEqzeGV1FpWXP5tb2ton52ucN4m+N/7QvxZ/4Klf8ABOOL41fswa1+z/BpPhf9qf8AsS41XxVpXiNfEX2rwX4eN8Ik0/BtTp3kW+4ytiX7UoUEoa4szpUqeSZi4V41m6mF0UZR5Upy6u/Nd3fRrazVmVSrVquZ4H2uHlQSjibOUk9eSPbptspdrKz5v321T/kFar/2C9S/9Ip6/PYfHH/FH8z6Y/L3/gi5/wAo6/gn/wBhj4s/+rb8a17PEX/I2xH+DD/+o9I83KP+RfS/6+V//TjE/wCCzP8AyYprv/Ze/wBlP/1of4e1pwz/AMjeh/16xX/qNVJzj/cKn/Xyh/6egfrtH/q4/wDcX/0EV9Atl6I0Pws/4KAeMNAj/bi+G3gf4yS/Grx38E7j9nDW/EGjfC39n671o+JNE+I9r4xnS98Z+PdP8PSRX/8AY2q+Hkt9J8I3U8q241Sy1KIRuzFq9HDRl9VqzpOlCr7dRdSsk4unyfBB7JqSvJWbtJXu2uXycXNLGU41Pazpui5Rp0buSmpO8pJdGlaLvvomrvl+tP8AglD4x8VeOf2N/DGu+KvFup+LW/4T/wCK1h4XPiO8a+8a+GPAdh471i38FeCfiBNLi4Xxx4W0BbTTfEEN0q3MNwiRzbnUs2ONjy4maUVFclJ+6rRlNw9+UP7knrHb9ZdGXSc8LFtya5pqPP8AGoqT5Yz/ALyVr+tuh5//AMFqv+TFb3/s5D9kH/1pP4b1rln+9/8Acti//UeZlm3+6L/sJwn/AKkUz9YE+4v+6v8AKvOh8Ef8MfyPSWy9Efij+2rq3gy6/bg8NeFP2sfFvxH8Ffsrt+zjFqnwwufB+oeJNI8Na78bH8a6pB40h8Tan4Zie6Gu6X4VTQJPDNlclYZEuLuWLdKGK+jh4zeFm8PGE8Qq751LlclRVO8OVSbVpTTvs768srJHl4qUPrUViJVI0PYXhy8yi6jnrzNbySUeVPu2ua0lH3v/AIJNfF3xB8Xf2WNVk17VPFOvQ/Df48fHP4R+FNe8bxzR+L9Y8A+BfHmoWfgS78SC4VLh9XHhe40y2upLhFuJGgDzjzmcVnjoKniOWKiuajRqSUNYqc4XmotaNcyvo3v03lvl9SVTD+9dqFSrCDl8ThGbUHLrzctm72fR7XlzX/BaD/kx2f8A7OS/ZI/H/jITwJ/+v/Jp5d/vkf8AsHxfy/cS/wCG/pGea/7qv+wjDfL9/D/hv6R9Af8ABSbH/DvH9t3JwP8AhlX435OM4H/Cvdc5xxnHpn8s1jg/96wf/YRQ/wDSl6/123Nsb/uOJ/7B6n/pB+f3wK/aX/4KLWf7Lfwj0zSP2B9I1bw7a/ALwTY6Zrz/ABg0m2fUdGh+HmnW9nq7WZiLQNd2Sx3htmbdGX8s5IxXZVpYH6xV5sY0/rE3L921aXtbuPXZ3V1fvrdnHTr472FNLCJx9lFX59WuXVrfpqlfTZ3se4f8EXZry4/4Ji/smTahaiyu5PBWvNPaiQSCGQ+OfFG5PMGA21sjOOfbNfE8R2WdY+zuvarXz5I33t1v6ee56+UNvLcI5Kz9m7rt78jT/ZU/5S7f8FIf+yE/sU/+mT4m16uH/wCRDl//AGE4/wD9LoHJ/wAzfH/9g+C/9IqH7IVzHYFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAf/0P7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2l+0R/yb98df8AsjfxP/8AUI1yvmcH/vmE/wCwmh/6dgexW/gV/wDrzU/I8I/4JWf8o7P2Qf8AsiXg/wD9Iq++xf8AvmK/6+v9Txsu/wByw/8A16h/6TE9f/aM/Y8+B37VF74C1L4v6HrGqaj8Mr3U9R8FX2jeItT0C60W/wBXgjtb67gl06WMm4kt4xCsx/eRxl1RlDsWVHEVcPz+ya/eJKSdmml01T/K3XRpGtfC0cQ4OqpXptuDjJppv0/r72eAfsY/8E9PCf7IXxh/aT+J2heIdc1iH4z+MLLVPDdhqfiHW9Wk0Dw1a6FpennTtUOpXEiahqjahY3FwupEPMLWWK23lI1C6YnFTxFOhSlZeyj7ziuW8m29LLz116aW1RhhMDHDVa9RNv2sk43bbUUrWfTe779NdXH68/aM/wCTe/jv/wBka+J//qEa5WFP+LS/6+0v/S4nVX/gVv8Ar1U/9IZ83/8ABLv/AJR7fsi/9kS8G/8ApAtbY3/fMR/j/wAzHAf7nhv+vUT1z9pj4U/Fv4kaP4K1b4IfFM/DD4hfD3xWPE2nHUbR9S8H+MLKaxlsL/wt4z0yIrLdaVcxyrcQSRESWt3Ekq9TWdKpCDkqlP2kJx5XbSUdV70X0a+/zW0rxFOpUjF0ans6kJcyvrGXeMl2dvOz184+a/sp/s2fE34YfEX45fHP42+M/C/ib4qfHW68JR6xp3gPSJtE8GeH9G8EaSdI0W10+2uSbm81CeJpJ9R1G5HmzOypkrGKqtVhONKlSjKNKlzazd5ScnfX3VppZJNWW92/ejDUKlOdWrVlGU6vLdQi4xSirK127v5eltj3P9psZ/Zu/aBGcZ+CfxUGT2z4G13nv/L86ij/ABqX/XyH/pX9fqbV/wCBW/69VP8A0ln4nf8ABPz/AIKOXPw//Yw/Zs8GL+x5+1d4sXwz8LPDOkr4j8MeAEvvD+tCztAn2/Sbv7UhuLG4xvt5SnzoQcLzXdi8LzYnEP6xh05Tlo6msdXo4+69n3/8Bs+by8JjuTDUIfVsRK1OMeaMLrTS9/8AgffY+o/+CHOut4k/YPsvEB03UdFOtftB/tRaodJ1aP7PqmmG/wDjx46ujY6hAMiG9tDKYLmMH5Jo3UZwKjM48uLUbqVsPh1dXs7UaSur7re2r9Xob5VLnwjlZxvXxDtK11erJ62b/T01Yv8AwTx/5OL/AOCrf/Z9upf+qk+HNfNcTbZT/wBi+P8A6frnZlfxZh/2HT/9NUhP+Czf/Jjt/wD9nCfsrf8Aq+vBNcPD3/IyX/YLjf8A1Gqmmbf7m/8Ar9hv/T9M/VGD/UQf9cIf/RS14Z6R+Xv7Dv8AykE/4Kyf9lT/AGff/VIaNX3uG/5E+UemI/8AT54NH/kY5n/18of+mIH6iePPBegfEjwP4x+Hviq0F/4Y8deF9e8IeIbInH2rRvEemXWk6lCDyAz2l3KEYj5Xw3OBWkZOMoyi7SjJSi+zi0126rv9x2TgqkJQl8M4uL9GrM/Nvwn+wF8WZtY/Z88M/F79on/hYfwN/Zc8X6L43+Fvgm38J22j+ItW1zwfpV9ongOXxv4gjdhqMfhbT7+UxpbIn225SOWbO07up4uC9u6dDkqYiDpzm5e6ozac+Ra25mtXq9bpKzRwxwc37GNStz08PNThFKzk43UHJ3t7qdrLmXW+x+p9caVkegfkz+xN/wApC/8Agrf/ANla/Z1/9Z/8N124n/dsv/691v8A09VPOwn++Zh/19p/+mYH6i+LvDtv4v8ACviTwpdXl/p1t4l0LVtBn1DSrhrPVLCPVrCexe9066T5ra+tRP59pOvMU8cbj7prkT5Wno7NPVXTs72e+jtZ+Wml7nfKPNGUbtXTV07NXVtPNdD84PDv7DHxs13xX8C4fj/+0tN8XPhb+zh4ysPiB8P/AA2PCtvo/iTxJ4u8P6dfaT4Q1j4g6+kjf2rP4etdQnuFFska3t/tuJxnIrpliYJVvY0PZzrQcJScrxjGVudU9LJS7WjZKyUrKMeOOFqt0fa13OFGXNGNrOTWkOeVteVfe9W9Ez9QK5ErJL+v1/P7zuP51fhz+1L4y/Z9/wCCiv8AwVI0rwx+zP8AGP48QeIPiz8FtQutT+GNlYXVloMtv8E/DFslhqj3k8TJdXCf6REEBUxHJyeK9Z0IVsHgHKvSo8tOrpUbTl++lqrNaJ2/LS7cfDhiJ0Mdj1GhUrc06TvTt7v7paO/XS++3ex3n7LPx18SfHv/AILD/EXxN4l+CXxH+Bt3p37AngzR4vDnxKt7S21fUYIvjR4muV1a0SzeWM2Ej3TW6szh/Ot5gRgLWeJoxpZfDlrU6t8XUd6eqT9jZJ3bd7K/XrtZI1w9WVbMZuVGdG2FjZVN3eb1XlbTp87pnv37Xn/KUH/gl7/2K/7XP/qGeEq8rHJLJsxt/NhPL7dT+v8Ahzrn/wAjLL/8OK/9Igfp1qn/ACCtV/7Bepf+kU9fCw+OP+KP5nuH5e/8EXP+UdfwT/7DHxZ/9W341r2eIv8AkbYj/Bh//UekeblH/Ivpf9fK/wD6cYn/AAWZ/wCTFNd/7L3+yn/60P8AD2tOGf8Akb0P+vWK/wDUaqTnH+4VP+vlD/09A/XaP/Vx/wC4v/oIr6BbL0RofAXxm/Ze+NB/aRuv2p/2aviZ4U8G+P8AxT8KtA+D/wAQPD3xD8PT+IfDOt+HvCeuaxrvhbVtMktWW80rVtLuNf1SG4jib7NqMMsXnJvhR16oVqXsFh69OU6cak60HTfLKMppRkno7p2T6u99EnzR4quHq+3eIoTjGc6caU1OLlFxjLmVrSi1Zt/+BPb7XqH7HX7M8n7Lvwx8QeFtV8WyeOvGvxC+J/j74zfEfxSLFNKsdV8e/EjV/wC19ebRtIiJi0vR7ZlgtLCzQArFB5km6WR2aK9b201JR5IQpwpU47tQgrJvu3/w1k+WOuGoewpyi5OUp1J1Zy2vObu7Lololv5t6s+Tf+C1X/Jit7/2ch+yD/60n8N66cs/3v8A7lsX/wCo8zkzb/dF/wBhOE/9SKZ+sCfcX/dX+VedD4I/4Y/kektl6I+Nf2kf2dviv8TPHPg74k/B/wCMNl8P9e8OeGtW8I6t4Y8YeFrPxz8P/EOnalqEGqWetSaBeoRZeKtDvIm/s/Vrdld7WV7SYmMqF3p1KcIzhUpOcZSUlKEnGcdLSin/ACyT2d0nqtUnHnrUak5xnTqKLUXFxlFSg09b2e0k7aq34Wl6H+y3+z7p/wCzR8I9P+G9v4hvvGGtXXiHxb458beM9Thit77xd488eeIL7xP4s1+a2gAhtUvNV1CZbS0jGy0sora2XKxLRWqutUdTl5VaEIw/lhCPLFfJeWr1d7orD0VQpKnfmfNKc5PeU5ycpS+99D4V/wCC4WpXejf8E/fEesWGl3OuX+lfHv8AZa1Gy0SzZEvNYu7L48eCrm20q0aT5FudQmjS0gZ8KJJVLELuNdOWK+OgnonQxSb7J0rXfkrnJmzawbaV2q2HaXdqtBpdd2klpu+tkfLn7d37cv7Sfin9iT9rPwzrX/BPT47eD9H179nX4taPqnivVtV8Nvpnhuwv/BWrWt3rmoJDcmV7PTYZHvLhIlaUxRMqhmrbCYWisRhn9coS5a1KSUeZuVpXSSst7fzO/RbI5sZiq7wmITwVaMXRmnJuKUU477u9vXXpa5+vX7OH/JmfwO/7Nl+Hn/qrNJrz6zvXqv8A6ian/p5/109FsenR/wB1p/8AXlf+kHx9/wAEb/8AlGl+yp/2J3iD/wBTvxTXyvEX/I5x/wD1+/8AbUdGVf8AIvwv/Xv/ANvkS/sqf8pdv+CkP/ZCf2Kf/TJ8Ta9fD/8AIhy//sJx/wD6XQOP/mb4/wD7B8F/6RUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//0f7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2j+0Ucfs+/HY4Jx8GvigcDqceCNd+n+fXpXzOD/wB8wn/YTQ/9OwPYr/7viP8ArzU/9JPxX/4J5/8ABSSP4d/sTfs1eBz+yR+1b4rPhf4WeHdGPiPwv8OX1Hw9rP2K38r7fpF6JwLmxuCN8EuBuTnnq36ZicEnia83icOueo5crnZx8muj/rsfL4LHezwtCH1bEytTiuaNPR2SWm91pv1302Psv/h6vF/0ZR+2Z/4ayT/4/WP1KP8A0E4b/wAGHV/aP/UJiv8AwWH/AA9Xi/6Mo/bM/wDDWSf/AB+j6lH/AKCcN/4MD+0f+oTFf+Czy/44f8FRIta+Cvxf0Y/saftg6d/a3wu+IGmf2hqHwyeCwsft/hPVrX7ZfT+efJtLbzfOuJcfJCjtzirp4Je0p/7ThtKkH/E7TT/Qzq5hzUqkfqmKXNTmrunorxau9tF1/C+x4X/wT7/4KUxeAv2Kv2avBv8AwyL+1h4nPhz4UeGNKOv+Gvhw9/oOrfZrJF+26VeCZftFnNkmKXA3D6VpisGpYqvJ4nDrmqP3XOzjbo10fXr+Fo5YPH8mGox+rYmVqcVdU9Num/Xz++x9if8AD1eL/oyj9sz/AMNZJ/8AH6w+pR/6CcN/4MOn+0f+oTFf+Cw/4erxf9GUftmf+Gsk/wDj9H1KP/QThv8AwYH9o/8AUJiv/BZ5J8fv+CocWufAn41aKf2Nf2v9N/tj4TfETSxqOo/DJ4NPsDf+EdYtRe305nxDZ2vm+dcykNshR2xxWlLBL2tP/acN/Ehp7TV+8tF3f3fhaWdbMb0qi+qYlXpzTbp6JOL16bdeyva+x9lf8Erbprn/AIJ4/sfThZ4PN+CPgpvKlBSRAdPTCsvYgHGMD0wK48dFfW8UnZ+/LW11u/Xy6/edeAd8HhtGv3UNH6eV/wA/vPFv+CMH/JmV/wD9nMftZf8ArQfj+tsw/wB5j/2DYf8A9MUjLLf92l/2EYn/ANPSMT/gnh/ycX/wVb/7Pt1L/wBVJ8OK+c4m2yn/ALF8f/T9c6sr+LMP+w6f/pqkJ/wWb/5Mdv8A/s4T9lb/ANX14Jrh4e/5GS/7Bcb/AOo1U0zb/c3/ANfsN/6fpn6owf6iD/rhD/6KWvDPSP59/hr+1X4p/Z8/4KM/8FQdM8Pfsz/Gz46x6/8AEb4FXc+pfC3SrG/stDez+DWi26WuqNdzwtHcXakz24UMrRKSelfo2Aw6rZNlTdejT5Y4n3ajs3+/eqtvb0Xe+lpfLyxLoZjmKVCrWvOg26aTUf3MN7tav1++yPs//h5n8Tf+keH7YH/hNaL/APJdb/Ul/wBBeG++Rr/aMv8AoCxP3R/+WB/w8z+Jv/SPD9sD/wAJrRf/AJLo+pL/AKC8N98g/tGX/QFifuj/APLA/wCHmfxN/wCkeH7YH/hNaL/8l0fUl/0F4b75B/aMv+gLE/dH/wCWH5wfso/t7ePfDX7a/wDwUn8WW37Ef7TfiC78ffEf4H6hf+GNI0HS5Nc8ESaP8GdC0iKy8TxSXYjt7nVooBqlgsW9Xspo2JDZFdmIwcXh8CvrVBctOrq27SvVbvHXVLma05vwbOPD42UcTjZfVa75qlNuKSvB+ygrS1W/K3o16NNM/R//AIeZ/E3/AKR4ftgf+E1ov/yXXH9SX/QXhvvkdn9oy/6AsT90f/lgf8PM/ib/ANI8P2wP/Ca0X/5Lo+pL/oLw33yD+0Zf9AWJ+6P/AMsD/h5n8Tf+keH7YH/hNaL/APJdH1Jf9BeG++Qf2jL/AKAsT90f/lh5H/wSs+KOq/GD9rb/AIKoeO9X+HHjP4UX+t/Gf4KS3Hgrx5bQ2fiXSGt/gvoVmseoW8EksSNOlut3FtdgYLiI8ElavHU1Tw2Xw541bU6vvw1i719bdtHbeWz10Iy+o6mJzCbpzpt1aXuTVpK1NLXfrpp26bHsOmkn/gtt4xySf+Nc/gYcnPA+OfjLisZK2XRt/wBBlT/1HRsv+RnL/sFX/pZQ/a8/5Sg/8Evv+xX/AGuf/UM8J1w47/kT5j/iwn/pyoaT/wCRll/+HFf+kQP061T/AJBWq/8AYL1L/wBIp6+Fh8cf8UfzPcPy9/4Iuf8AKOv4J/8AYY+LP/q2/GtezxF/yNsR/gw//qPSPNyj/kX0v+vlf/04zF/4Ldand6N/wT48aarY6Vda5ead8aP2Yr610eyKLd6ncWnx88B3EGn2xkIQT3ssSWsJYhfNmXJA5rbhdXzmgr2/dYnXov8AZ6mr0ey9PUjOnbL6jS5rVKD5V1/fQ0v09bS7W1R16f8ABQj9pkIg/wCHan7R/wBxf+Yl4W5+Uc/8ffevro4TD2X+20X5+8vw5Hb7/uucn1vEPbBVrekf/ko/lbtdWcnf8PCf2mf+kan7R/8A4MvC3/yXT+qYf/oNo/fL/wCVh9bxH/QFW+6P/wAsD/h4T+0z/wBI1P2j/wDwZeFv/kuj6ph/+g2j98v/AJWH1vEf9AVb7o//ACw/OL/gqv8Atq/Hvx9+yHd+HfEn7B3x0+HOln45/sz6sfE/iG/8PSaat5ofx38Carp+kFba4kl+16/eWsOj2LYCLeXkLSEIDXXgcNRjiVKOLpSfscTFxV72lRmnL4FpHdpavpbePBmWJrSwtpYWrD99h2pSSteNaLSdp9Wklt+kv0bT/goR+0yFX/jWp+0eflXkal4WweByP9L71xRwmGUUvr1F2Vr+8r2025Hbbv8Adc71i8RZWwVa3TSL/Hmjf7rdrqzk7/h4T+0z/wBI1P2j/wDwZeFv/kuq+qYf/oNo/fL/AOVh9bxH/QFW+6P/AMsD/h4T+0z/ANI1P2j/APwZeFv/AJLo+qYf/oNo/fL/AOVh9bxH/QFW+6P/AMsPz6/4Ka/tkfHT4ofsyaX4L8X/ALD3xs+Eegal+0X+y3Nd+PPFl9oEuh6S9j8d/BF1bxXSWdxJcF7+ZFs7fYuBNKhbCgmunBYajHEqUMXTnJUMUuSPM21Ki7v4Fbltf/K948WYYitPDqM8LVpp18P7z5Uk/bQav70nuulvXVI/Yz/gpMzH/gnf+27knn9lP435GfX4ea4cHp0+nOOMV5mDS+tYPTX6zR6f311/r8T0sdpgsSu1Cp/6R8/z+8779nD/AJM0+B//AGbL8PP/AFVmlUq/+8Vv+wmp/wCnmXS/3WH/AF5X/pB8ff8ABG//AJRpfsqf9id4g/8AU78U18pxF/yOcf8A9fv/AG1HRlX/ACL8L/17/wDb5Ev7Kn/KXb/gpD/2Qn9in/0yfE2vXw//ACIcv/7Ccf8A+l0Dj/5m+P8A+wfBf+kVD9kK5jsCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP/9L+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8a/2j/8AlMJ+xh/2ar+0B/6lfhet8T/yI8X/ANhdD/0hnGv+RpR/7A63/pR9pftEf8m/fHX/ALI38T//AFCNcr5nB/75hP8AsJof+nYHsVv4Ff8A681PyPCf+CVjN/w7s/ZB5P8AyRLwf3/6chX32LSeMxV/+fr6X/r+ux42Xf7lh/8Ar1D/ANJR+gOW9T+dc9o9l9x2nnvgT4tfDb4n3Hiu1+Hnjnw340n8C+Ibnwn4wTw5qtvqn/CO+JbNFkutE1RrZpEttQgR0aW3LlkDc9SFqVNw5eeDjzLmjzRtzRfVaK689b28rkQq06jkoTjNwlyz5Xfll2drWf8AWu5zn7RjN/wz38d+T/yRr4n9/wDqSNc/z/kU6SXtaWi/i0+n9+JNf+BW/wCvVT/0hnzf/wAEu2b/AId7fsi8n/kiXg7v/wBOC1vjUnjMRf8An6q+7dzHAf7nhv8Ar1E+mPi98fPg/wDAPStL1z4x/EHQvh/pOtXsunaVfa9LcRwX17DEs0ttCbeCdjIkTK5DKBgjBzWEKMql1TpubW6itfx9P6ub1KtOkk6k1BN2TfV/c/x+5mT8G/2mvgN+0JJ4hi+CvxU8LfEebwo1kniSHw5eyzzaK2oxvLYC/hmgglg+1xo8kG5f3iKSMjmnOhUpW9rSlT5r8vNH4rb2tvbrv+kVTr0q11TnGfLbmtra97X0jv8A1a15O/acJ/4Zt/aC5P8AyRL4qd/+pG13/P8AkU6CSrUnZfxI7K2t1b8Qr/wK1v8An3P/ANJd/wAD58/4Jcf8o+f2Q/8Asingz/0hWrxv+9Yr/HL85GWC/wBzw3/Xmn/6SeI/8EYAT+xlf4BP/GTH7WXQZ/5uD8f/AOf/ANVbZj/vMf8AsGw3/pil/X/DGOW/7tL/ALCMT/6ekYf/AATx/wCTi/8Agq3/ANn26l/6qT4c185xNtlP/Yvj/wCn651ZX8WYf9h0/wD01SE/4LN/8mO3/wD2cJ+yt/6vrwTXDw9/yMl/2C43/wBRqppm3+5v/r9hv/T9M/VGD/UQf9cIf/RS14Z6R+X37DhI/wCCgn/BWQAkf8XT/Z94Bxn/AIsho3+ef6197h/+RPlHpif/AE+eDR/5GOZ/9fKH/piB+p/izxXoPgbwv4i8aeK9Th0bwx4T0TU/EfiHV7kv9m0vRdGs5tQ1PUJ/LV5PJtLO3mnk2I7lEIVWYgVcYc0lGMU5SaSVt23ZJert+fRnZKUYRc5aRim2+ySu29Vsl39Lnyn8Jf8AgoH+yh8cvF3h/wADfC/4nTeJ/EfimGe40G2j8H+NrCz1GC2spdQlmh1bU/D1npYh+xxPPHK92iTKFEJdnVa3qYOtTi5TpJJO0nzQ0u0tVvvp+L0TOaljsNWmoU5uUnsuSavp3en/AA/nE+zMt6n8657R7L7jrPyZ/YmZv+Hhn/BW/k/8la/Z17/9W/8Ahv1rsxKX1bL1ZW9nWW3/AE+qf5HnYX/fMw/6+0//AEzT/r/hz9YZ7iO2gmubiZILe3ikuLieaRY4YIIUaSaaaRyEjiijRpJJHIREVmYhVzXHyrsvuPRbtr0Wp8nfC79ur9ln4zfEBfhj8OvixpuveL7r+1Tolq2m63pum+LE0JiNYfwdrmp6da6R4qXTQpe6Oi3l3thDTruhVnrephatKPPOk1Fct37rcebbminKS8k2m9luc1PGYerP2cKictbLVKVt+VtJOy10v3vqj62y3qfzrC0ey+46T8mv2HiT+33/AMFbySSf+F2/Avk/9kJ8MetduI/3PLv+vdT/ANPs83Cf77mP/Xyl/wCmoj9LBP8AwW18Y4BOP+Cc/gboM/8ANc/GP+f/ANVTP/kXx/7DJ/8AqOil/wAjOX/YKv8A0so/tegj/gqD/wAEvcgjPhf9rnqMZ/4ozwn/AJ4/rXDjv+RPmX+LCL/yep+jX9NGk/8AkZZf/hxX/pED9OdU/wCQVqv/AGC9S/8ASKevhYfHH/FH8z3D8vf+CLn/ACjr+Cf/AGGPiz/6tvxrXs8Rf8jbEf4MP/6j0jzco/5F9L/r5X/9OMT/AILM/wDJimu/9l7/AGU//Wh/h5WnDP8AyN6H/XrFf+o1UnOP9wqf9fKH/p6B+u8Zby4+T9xe/wDsivfSVlotl0ND5Y+Nv7bP7NP7O3jPTfh78XPiTH4a8aat4cTxdY+HbfQPE3iDUZPDcmoXGlR6vJF4f0jU/s9m+oWtxaJJOY90sTKM8beinhataLnTppxUuVyvGK5rX5VzdUtfNbbSOatjMPh5KFWfLJx5kkpSfLe17R2V9NbfO/u+1fC74peCvjN4H0X4jfDrV5dd8H+IVun0nVJdO1PSHuVsryewuSbDWLSx1CDy7q2niH2i1i3hfMTMbIzZzpOnJwnFKS3WjtpfdabNPrvbdNR2p1IVYqcHeL2eqv8Ael+vrqj83f8AgtUT/wAMK3vJ/wCTkP2Qe/8A1cn8N67MsSWL0S/3bF9Lf8w8/wCv+HPPzb/dF/2E4X/1Ipn6wIW2Lyfur39q86CXLHRfCunkektl6I8T+On7R/wa/Zq8P6H4q+Nvje08CeHvEfiKx8KaTq2oWmp3VnNr2pOkVjYzy6bZXgsvtMsiRR3F55FsZnSISmR1WtqVCdaThSp88lFyaVrqK3dnq7dlr1W0jKtXpYeKnVmoRclFN93t3/4ftue2JKJESRGLJIiujA8MrruUjPYggis7R7L7jY/Kb/gtASf2HZ8k/wDJyX7JHfP/ADcJ4D//AF//AKjXblySxkbL/mHxfS3/AC4l/wAN/wAOjzc1/wB1X/YRhvl+/h/w39I9/wD+Ck3/ACjw/bd/7NU+OH/qvdcrHB/71g/+wih/6WjbG/7jif8AsHqf+kHoP7OCP/wxp8D/AJG/5Nl+Hh+63T/hVmlc/wCf6Uq7X1it/wBhNT/0+zSl/usP+vK/9IPjz/gjf/yjS/ZU/wCxO8Qf+p34pr5TiL/kc4//AK/f+2o6Mq/5F+F/69v/ANLkS/sqf8pdv+CkP/ZCf2Kf/TJ8Ta9fD/8AIhy//sJx/wD6XQOP/mb4/wD7B8F/6RUP2QrmOwKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA//0/7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2l+0R/yb98df8AsjfxP/8AUI1yvmcH/vmE/wCwmh/6dgexW/gV/wDrzU/I8I/4JWf8o7P2Qf8AsiXg/wD9Iq++xf8AvmK/6+v9Txsu/wByw/8A16h/6TE47/gpl+1bf/s/fDzwV8OfDFz4h8O+Mf2gdfuPBCfEnSfC3iHxJYfCjwbHAG8ZeObtfD+m6nNHrFrps5sfC9u8K+brF1FcnEVq7Vrg6Htpyk1GUaMed03OMfaS+xDW2jfx/wB3R35kicfiHRhGEXKM6zcedRlJU4fanpFq6WkVfV9tZR+Pf+CNfjH9nnS/i1+3V8IPgXq2rX+i6d8XvDXiLRZNV8PeJtNvNW0tPhz4U03U9f1a71zTLRv7Y1TXY725vYb1otQmlle5MTRuHbfMY13TwVWuop+ylGVpRsnzSsly6OKVrPorKy3ly5XKiquMp0XJpVVJXjJO3s4KUnfdylvez+TvL9j/ANoz/k3v47/9ka+J/wD6hGuV59P+LS/6+0v/AEuJ6lf+BW/69VP/AEhnzf8A8Eu/+Ue37Iv/AGRLwb/6QLW2N/3zEf4/8zHAf7nhv+vUT66+JEvgHSvCGveLfiTYaFdeFPBWjav4p1e61+ws7600zTdHsJr7UbxRexSxxOtrbuNyhWc7UBOcVzxUpNRi2pSairdW9k9H1+7z2l0VORRcppOMU5PmSdklq9etvv27Hwj/AME1fAEsvw++IX7TuveHbPw14s/ay8dX3xPh0a10+DTv+Ef+HECDR/hd4d+zQRxLELLwlaWN1Mmxc3d7PIdxbdXRjJL2lPDp80cLBQ5nreo9ZtO+zk99fh2Rx4GHuVMQ1yyxE+e1rWgtKat0tFLZWu3sfXH7Tn/Jtv7QX/ZEvip/6guu1lR/i0v+vkP/AEpfnsdVf+BW/wCvVT/0l/lufPv/AAS4/wCUfP7If/ZFPBn/AKQrV43/AHrFf45fnIywX+54b/rzT/8AST8fP+Cbv7Ivxv8Air8APFnjbwZ+3N+0D8FdA1L9pP8AagitPh94EHhb/hG9Jex+Ofje1nmszqWkXV55l/NG17cebM4E80mzagVa5s2zz6li1QeBw1flw+FftKik5vmowevvRSS2SS27W97kwOX1K9CVSONxFFSr1/cg4KKtVmtLxe+/r1V7H65/sX/saL+yJb/Gq4vfi/45+Nfin46fE9/ir4z8Y+P49MTWrjxBL4f0nw7IoOlW1pbtEbPR7VsmENvzzgKK+XzXNJZpOhKVCnQWHpexhClzcvLzOXVvrJ9PuPYwWD+pqt+9nWlXqutOdS3NzuMY20tfSO9vS2p4J/wWb/5Mdv8A/s4T9lb/ANX14Jrbh7/kZL/sFxv/AKjVTLNv9zf/AF+w3/p+mfqjB/qIP+uEP/opa8M9I/L39h3/AJSCf8FZP+yp/s+/+qQ0avvcN/yJ8o9MR/6fPBo/8jHM/wDr5Q/9MQPvH9q3w7B4v/Zh/aH8KXWtWHhu18SfBT4m6HceIdVWd9L0ODVPB2r2Uur6ktrHLcmw05Jjd3fkRPN9nikMaMwAboovlrUpWb5atN2Vk3aa0V7K7e2vra50YiPPQrQuo81KouZ7RvF6vyXz9Hoj8ifhrq3x3/ZGsv8AgnxqMn7Svw8/aH8D/HLxb8P/AIC6j4A8M+B/CenaXBoWp+ANTu9P8d/C3XNJgXxPPaeGY9Agk1ubWLi5W8sL2SW7+zzlFXsfscQ8alQnRlShKtzylJyclUV6dSLtFOTlaKT0tpZI8yEquH+pydenWhVnCi4RjBJKUL89N8vNoopO+vvX0vyn76V5q2X6badj2T8mf2Jv+Uhf/BW//srX7Ov/AKz/AOG67cT/ALtl/wD17rf+nqp52E/3zMP+vtP/ANMwPrj9u1vFC/sV/tXt4KS7k8Vr+z78Vm0OOwMi30l4vg7VWKWjQ5lW4eATLE0Q8xXYFMtiscNy/WcPzW5fb0ua+yXOtX037qS7o6cZzfVcRyX5vY1OW29+R/109Vufkh8Pb/4n/BDT/wDgmR8QPE/xB+DHxj8DfFjxp4A+Gnhf4U+G/h74a0u5+FL+M/hnqbWvi74WeJtML+I7x/DVnZS2HjKXVZJ1vLK8uZ7loZdi12SVOpLHQhTqUp04znKs5t+15KlpRqRtZKbd4JXs7K6TR5sPaU/qM51KVSM5Qiqaglyc0LXpyWt49ZNyvq+TQ/od/wA/56fy/KvMWy/rY9o/Jr9h3/k/v/grf/2W34F/+qJ8MV24n/c8u/691P8A0+zzcJ/vuY/9fKP/AKaifMv7SHwD1/4//wDBYu/8P6B8dPi38B7jQv2A/BmrT698ItZtdF1fWop/jR4xtV0vVJrq0u1msIW/0mKNFVln+YtggNz4vHyy/K6dSNCjXdTHThy1o80UlQg7rs76X1/C8R4X61mU17arR5cJF3pS5W/3lrN7ta7eXkfTXwu/4Jo2/gb9oX4VftGeN/2p/wBoz44eKvg7p/jXTvBej/FLxNpusaHp8fjvS4dJ12RYYNNt5lea3t7dhslUF4kLBgCK+bxef1cXhKuE+qYahTrODm6UXGV6cuZPdLfRqzuu1juo5XCjiKeIeIxFaVJTUVVnzRXPHld1o3p56Oz84/pfqn/IK1X/ALBepf8ApFPXgw+OP+KP5nqH5e/8EXP+UdfwT/7DHxZ/9W341r2eIv8AkbYj/Bh//UekeblH/Ivpf9fK/wD6cYn/AAWZ/wCTFNd/7L3+yn/60P8AD2tOGf8Akb0P+vWK/wDUaqTnH+4VP+vlD/09A/XaP/Vx/wC4v/oIr6BbL0Rofkb8f/gT41+In/BQ6LxB8Pv2n/BfwR1nVf2RtI8Mat4bfwxofiX4najpOifFHX9YtNf8O23iy1udBh8Oi+1NrPWLmCK41BZbeKCSOCGYTN2wrQjg2p4eVVQxDcZObjS5pU7Wly68ySuru3b3rqPm1qM54zmhXjSk8Ok/dUp2jNtNcy5bXetrvo7aRl7/AP8ABOr42ePPjV8EfF//AAse+0DxF4m+Enx1+MHwMl8feFNNttH8N/Euy+GPiiXRrHx1pem2WbG1OsQER6lHYM1kNVtb02+FOxYxdOFOsuS6VSjSrckm3KHtI8zg29+V7b6P5R2wNWdWlNTs3SrVKXPFWU1B6SS22erWjd33PE/+C1X/ACYre/8AZyH7IP8A60n8N62yz/e/+5bF/wDqPMwzb/dF/wBhOE/9SKZ+sCfcX/dX+VedD4I/4Y/kektl6I/MH/gstb283/BOf49STwQyvbah8IZbd5Yo5GglPxq+HiGSFnUmKQozIXQqxViuSDXfl3+/UPN1F8vY1Xb79f8AhkcOZq+CraXs6T9P31PXp/W91dH6aad/yD9P/wCvGz/9J4q4Vt83+Z3LZeiPyw/4LQf8mOzf9nJ/skf+tCeBP8/5Nd2Xf74v+wbF/wDpl/1/SPPzT/dP+4+G/wDT9P8Ar+kfQP8AwUmOP+CeP7bpwDj9lX43nB6HHw91zgj09awwf+9YP/sIof8ApSNcd/uOJ/7B6n/pD9fy+8/O/wDZ4/4Jh2Xib9nf4I6tN+2V+2vpsXiH4NfDnUJtH0r426paaPYR6v4K0i4l03TrRYCtvptstw1raWwO2K2SOLkKa8bF8SYili8RTWEwbUMRVinKirvlqSs3uru13bd6q2wYfKqbw9FvEYv3qVNu1ay96CbSVtFq1az00V7I/Uj9mH9nnwZ+yl8CPh3+z58Pb3XNR8G/DTSbjR9CvfEl7/aOuXFtdale6rK+o3vlx/aJjdX8/wC82j5NowMV87jsXUx2Kq4uqoxqVpc0lBWinZLRdNEusvXU9XDUIYahToQ5uSmnGPO05fE3q1dPfv8AfdnyT+yp/wApdv8AgpD/ANkJ/Yp/9MnxNr6bD/8AIhy//sJx/wD6XQPK/wCZvj/+wfBf+kVD9kK5jsCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP/1P7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH2l+0R/yb98df8AsjfxP/8AUI1yvmcH/vmE/wCwmh/6dgexW/gV/wDrzU/I8I/4JWf8o7P2Qf8AsiXg/wD9Iq++xf8AvmK/6+v9Txsu/wByw/8A16h/6TE+97mysrzb9rs7W72Z2faYIp9meu3zUfbnjOAM988VztJ7/nb+vn+p22T3/K/9f12PLfh58Dfhp8LPFXxQ8aeCPDtvo3iH4xeKIfGPj29iZ2/tbXrfSrLRYrlI2JSzjXT9PtYjb2qxQs6eaU3sWq5TnNU4zleFKPLTVtk23a/k27Xb9EZU6NOnKpOEUpVJc07dXay6aWSto7eWlyt+0Z/yb38d/wDsjXxP/wDUI1ynT/i0v+vtL/0uIV/4Fb/r1U/9IZ83/wDBLr/lHt+yL/2RLwb/AOkArbG/75iP8f8AmY4D/c8N/wBeon1l8V/hd4P+NXw88UfC34gWM+qeC/GdguleI9Mt725059R00XMF1LYyXVnJFcLbXLW6RXUaOqz27SwSZjldawhOVOUakHacXeL7O1r9dr9tN1ex0VKcasJU56xkrNXa/K3X+nsdjo2kab4f0jTNC0e0hsNJ0awtNL0yxt1CQWlhYwJbWttCg4WOGGNEUDsPc1Orbb3k7v1/X10/G8qSUUopWSVkuyR5D+02cfs3ftAkjIHwT+KhI9f+KG13j8a1oa1qS/6eQ/8ASlfv0/pbmWI/gVv+vc//AEl27df6ex+HH7AX7Of/AAUD179jP9m/XPAn/BQSXwL4Q1L4W+Gb3w54PX4JeCdYHhvSprTdaaT/AGneqbq/+xxkRfaZ28yUDLkE1x5lnmDo43F0ZZdzuNacZTVecVJp2cuVNpNvW3TvLc4sHgcbLCYecMe4RlTjJRWHhLlW9rt3623auut0fqV+wn+y1qX7Hf7PmmfBbWviBN8UNZh8afEbxxrHjSfSLfQpNX1b4i+M9Y8Z6kx0y1d7e2EN5rE0SrEQm1QVVR8tfL5rj1mWMlio0vYqVOlTVPm5uVUoKGjdm7qN9fx3PYwOGeEw8aMqjqyU6k3UceXmdScp/DZWte2y9FsfYtecdZ+VP/BZv/kx2/8A+zhP2Vv/AFfXgmvc4e/5GS/7Bcb/AOo1U83Nv9yl/wBfsN/6fh/kfqjB/qIP+uEP/opa8M9I/L39h3/lIL/wVkH/AFVP9nw/n8ENG/z7fjX3uG/5E+UemI/9Png0v+Rjmf8A18oP/wAoxX6f1c/We7tLW/tbmxvbeG7sr23ntLu1uI0mt7q1uY2huLeeGQGOWGaJ3ilicFJEZkYFSRVnc0mmnqno13X4/l958m/DH9hD9lD4O/ECH4n/AA7+Dvh3w/4xsf7QGiX8bXt1beGBqu7+0h4W0y8ubjT/AA59sV2jn/si3td0TGLhDitp4nEVYuE60pQdrppJyttzNX5n/iX3nNDCYenNVIU0pK9nraN3d8qvZX8ku1loj66rE6T8mf2Jv+Uhf/BW/wD7K1+zr/6z/wCG67MT/u2Xv/p3W/CtU/z7feedhP8AfMw/6+0//TMD9YZ4YbmGa2uIo57e4ikgngmRZIpoJkaOWGWNgUkjljZkkRwVdGKsCCRXGeifJfw5/YS/ZS+E/wARYfir4C+D3h3QvGli+pS6JqCNeXVp4Zl1jf8A2pL4W0q7uZ9N8OyXyyPHO+k2tozRO0eQjGtp4jEVIuE6rcHa65fittzO7crb+9zK7vZ6qPNDCYenNTjTSkublb1UebflTcrX12/G6UfrmsTpP5yfAfwL/aF+Lf8AwUW/4Ki3/wAFv2t/Gf7N+naR8V/gtaa3o/hfwf4T8TQeJb2b4K+GprfUrqXxFY3UttNawf6MkUDrGyjcw3EmrzHNKeX4TK4zwlPEupRrS5pynFwSrzjZcve1391lbmPJoYWriMbmEqeKnQSqUouMIwfN+6g7tyjJ31tp0768v3Z+zV+wv8S/hD+0t4r/AGoPjH+1R40/aL8c+Ivg9pfwYtE8T+FPDPhuDRvDWk+KLvxVbtB/wj1rarNJ9vvroYlRztlPz8Lt+azPOo4/C08LDB08NCnWlWbhKUnKUo8r+J76K767Wjb3vUwmAnh6869TE1K8p01TSmklFKXNpa19W9191kfpFXgnpFHVP+QVqv8A2C9S/wDSKeqh8cf8UfzA/L3/AIIuf8o6/gn/ANhj4s/+rb8a17PEWmbYhdoYf/1Hp+v5/eebk+uX0n3qV/8A04/T8vuE/wCCzP8AyYprv/Ze/wBlP/1of4e1pwz/AMjeh/16xX/qNVJzj/cKn/Xyh/6egfrtH/q0/wBxf/QRX0C2XojQ+evjr+yl8A/2k20G4+MXw+03xTqfhdLuHw/rqz3uk+INJtdQ2/b7Cz1zSbmy1OPTr4orXdgLg2s7qryRFhurSnVq0eb2VRwU7cytdO3Wzur9Nk/PUxq4ejWt7SCk43s9U1fdXWtnpfddO7j6d8Nfhn4C+D3grQvh18MvC2k+DfBXhu2a10bw/olslrYWcckrzzOEXmSe5nkknubmUvNcTySSzO7szVMpTnJznJznLeT3dvv/AK7bF06cKUFCnFRjHRJaf0/66o/Nf/gtT/yYre/9nIfsg/8ArSfw3/z/APrruy3/AHv/ALlsX/6jz/r/AIY8/Nv90X/YThP/AFIpn6wJ91f90fyrzofBH/DH8j0lsvRHn3xV+FXgL42+A9b+GfxO8PWnivwR4ifS31nQb4yC1vm0XV7HXdMMpikik/0XVdNsrtNrr+8gUHKllrSM505RnTk4Tjdxkul1Z/g2vns94zUpwrQdOouaErXXezuu2zSe+/Y9BjRY0SNBtSNFjRR0VEUKoH0UAVK0/r/hv677ln5Gf8FxNOvNY/4J9+JdJ0/VrzQL/VPj1+y1p1jruniI3+iXd98ePBVtbavYidJITeadNKl3bCWOSIzQoJEZN6t14Cfs8Wp2UuXD4uXK9pctFtxfdPZ7W37KXnZpHmwqjdrmr4aN1um60Emttm09e3XY4b4g/wDBMj4//FPwB4y+Gfjj/gpn+1Lrngzx/wCF9Z8H+KtFudN+HS22q+H/ABBp82m6rp8zReGVl8m6s7iaFyrq+1shg3NfPw4njCcKkcswinCSnF3qu0ou6a+Ffjp5297eplFSpCVOWY4qUJxcZR5aVmmrNaQTXbR6dG9z9Ufht4Ks/hr8O/Afw60+7uL+w8BeDfDHgyxvroILq8s/DGi2Wi211ciMLGLi4hsklmEaqgkdgoCgCvma9V1q1Ws1Z1ak6jS2TnJyaW+ibstdt7nr04ezpwp3uoQjBPyikulu3/D7na1kWfmf+yp/yl2/4KQ/9kJ/Yp/9MnxNr7HD/wDIhy//ALCcf/6XQPD/AOZvj/8AsHwX/pFQ/ZCuY7AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD/1f7+KACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAPxr/aP/wCUwn7GH/Zqv7QH/qV+F63xP/Ijxf8A2F0P/SGca/5GlH/sDrf+lH6B/ETwoPHnw/8AHXgY3h04eNPB3ifwmdQWMTNYjxHol9o5vFiJAlNsLzzhGSA5TaSM5r5WjU9lWpVbX9nVp1Ld+SalbZ727P0ex7U489OcNueEoX7cy3/q36S/Jb4QfsGf8FCfgb8M/Bnwj+Hn/BSCDSvA/gDRLXw54X02f9nrwPfzWOj2C+XZ20t7czPcXTxRbUM0zs77ckmvq6nE2EqTlUlll5Tk5SaxE0m31tol8l92p4lLLsXRpxpU8b7kIqMb0NbL/uH5npH/AAzH/wAFO/8ApJhZ/wDiN/gD/wCOVH+seD/6Fb/8Kahp9Tx3/Qav/BP/ANzD/hmP/gp3/wBJMLP/AMRv8Af/AByj/WPB/wDQrf8A4U1A+p47/oNX/gn/AO5mF4p/ZA/4KU+MPDHiPwlrX/BSu1n0bxToOseHNXgT9nPwFE0+ma3p9xpl/CsqSh42ktbmVBIhDoW3KQQDTjxHg1KMv7L1jJSV8TU3Tv5/l9+gpYHGyjKLxqtJOL/cdGrP7C/P7jlPhB+wd/wUN+B/wy8E/CTwF/wUjg07wZ4A0Cx8NeG7Gb9nnwNeS2uladEIraGS6uJnnnZUABklZnbv6LdXibCVak6ksr96cnJ8uImk2+ttPy+4mnl2MowjThjrxhFRV6Cvp1doPV+vnrdnpH/DMf8AwU7/AOkmFn/4jf4A/wDjlZ/6x4P/AKFb/wDCmoX9Tx3/AEGr/wAE/wD3MP8AhmP/AIKd/wDSTCz/APEb/AH/AMco/wBY8H/0K3/4U1A+p47/AKDV/wCCf/uZz3i79jv/AIKT+NvCfifwZrn/AAUrtZ9E8W+HtZ8M6zAn7OfgKF5tK13TrnS9QiSVJA8TyWl1MiyId6M25cECqhxJg4zjL+y9YyUlfETdmndOzunbz+Vm7kywGNnGUJY3ScXF2odGrP7C/P7z73/Za+CT/s3/ALPPwh+BUniJ/Fr/AAt8EaL4OPiWSyTTpNaOk24g+3vYxPJHbNORvMKOypnAY4zXzeOxKxmLxGKUPZ+3qyqcid1Hme19L/cvnvL1MNS9hQpUb83soRhdqzdlbY98rkNwoA/Kn/gs3/yY7f8A/Zwn7K3/AKvrwTXucPf8jJf9guN/9Rqp52a/7lL/AK/4X/0/E/VGD/UQf9cIf/RS14Z6J+Uvi/8A4J7fHyL9o/8AaC+P/wACv23/AB18Co/2hta8I654q8G6H4B8G+ILGG98HeFbHwppzx3+vWd5dNmysvMIXy13SsDuwDX02F4hp0MHhsHUwFOv9WVRRnKc4t+0m5u6i0t3Za7d7Hj1csqyxFfEUsZUouu4OcIxha8I8qteMnt2t89UXP8AhjT9vr/pKT8U/wDw0vww/wDlNW3+seG/6FVH/wAGVP8A5YT/AGbi/wDoY1v/AACn/wDKw/4Y0/b6/wCkpPxT/wDDS/DD/wCU1H+seG/6FVH/AMGVP/lgf2bi/wDoY1v/AACn/wDKw/4Y0/b6/wCkpPxT/wDDS/DD/wCU1H+seG/6FVH/AMGVP/lgf2bi/wDoY1v/AACn/wDKzyDwN/wTE/a4+HnxI+MPxV8L/wDBS/4n6f4x+Omr+Gtc+Impr8K/h1I2t6j4T8O2vhfRZ5IptNkt4Ta6Raw2wFtFCHChnDMcrpPiihOFKnLKqPLRUo0/3tTRSfNLrHd9L2XS32s45RiITqVI5jW5qzUp+5T3S5Vb3HokrbK+7uev/wDDGn7fX/SUn4p/+Gl+GH/ymrP/AFjw3/Qqo/8Agyp/8sNP7Nxf/Qxrf+AU/wD5WH/DGn7fX/SUn4p/+Gl+GH/ymo/1jw3/AEKqP/gyp/8ALA/s3F/9DGt/4BT/APlYf8Maft9f9JSfin/4aX4Yf/Kaj/WPDf8AQqo/+DKn/wAsD+zcX/0Ma3/gFP8A+Vnq/wCxb+xj4y/Zf8Y/tF/EX4i/H7xF+0D48/aM8WeEvFfibxJ4i8OaL4buLO58JeF4PCtnBFa6HFFaSJJYWtvuYRRkGIdSzV5mbZrHMo4SEMNDDQwsKkIxjKUrqc+feTdrP7tlfVy6cBgZYN4iU68q88ROM5SlGMbOMeXTlS6efyVj78rxj0QoAo6p/wAgrVf+wXqX/pFPVQ+OP+KP5gfl7/wRc/5R1/BP/sMfFn/1bfjWva4j/wCRvif8ND/0xSPMyf8A5F1H/HW/9OM+qf2zv2XdL/bH/Z/8R/AbV/GviL4d22u+IvAvie28YeFYrCbXdH1XwB4u0nxjo81lHqUFzZMTqej2wk82B8JkqMgFeLLcdLLcXTxcKcKsqcakVCd+V+0g4O9mm7KT0vbvc6cZhli6EqDnKmpShLnhbmi4TUlZPRq61vf5bnyqP2C/2sQAP+Hpn7VHAx/yB/hr/wDMvXtriWC0/szC2X96t/wfz+85P7Nq/wDQxxP/AIDR/wDla/L7hf8Ahgz9rL/pKb+1R/4J/hr/APMvR/rNH/oWYX/wOsH9m1f+hjif/AKP/wArD/hgz9rL/pKb+1R/4J/hr/8AMvR/rNH/AKFmF/8AA6wf2bV/6GOJ/wDAKP8A8rPLvjD/AMEqPjd8efBL/Dz4pf8ABSr9p3xV4Rl8Q+FPFD6Re6T8OlgOueCfEOn+KvDV9mHw1G/maZrml2N9D84UywIH3IStXT4p9lNVIZbhVJRlG/NVfuzi4yXxR3Tt1+W5lWyeVeHs6mYYlx5oyty0lrCSlF6QT0kk9H99z1AfsF/tYgAD/gqZ+1QAAAB/Y/w14x/3LB/n+dR/rLH/AKFmF/8AAqpr/ZtX/oY4m3+Gj/8AIP8AP7xf+GDP2sv+kpv7VH/gn+Gv/wAy9H+s0f8AoWYX/wADrB/ZtX/oY4n/AMAo/wDysP8Ahgz9rL/pKb+1R/4J/hr/APMvR/rNH/oWYX/wOsH9m1f+hjif/AKP/wArOC+I3/BLf4y/GPRdJ8I/F3/gox+0p8Q/A9h418C+OL3whrWlfD+PS9X1L4f+KtM8XaJDePZ+HYLhYV1TSrdnMUqvtzg5I2tcT8vM4ZdhYzlTqU1NSquUVVg4Sau10fnfstyKmUyqqMamOxE4xnCpytU0m6c1ON3GMWtYrr913zfsYBgAZzgAZ9cDGT15PX+WOlfKHsC0AFAH5n/sqf8AKXb/AIKQ/wDZCf2Kf/TJ8Ta+xw//ACIcv/7Ccf8A+l0Dw/8Amb4//sHwX/pFQ/ZCuY7AoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD/9b+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD8V/27/Bf7VPhv9uv9mT9pr4Bfs3Xv7Q/hn4ffBL4pfD/AMVaVp3jzw/4HutP1Xxhr+k32nyLca7FcLOiW+nMzrHAc+aPnypSu+nTw+Jy7EYOtiVhpzr06kZSg5pqEWnovXTX1tocFb29LG0cRSoOvCNGdKaVRQa5pJ9U3stWl6WH/wDDWv8AwUR/6RYeLf8AxIz4d/8Aymrz/wCwcH/0OKX/AIT1Dq+v4j/oBn/4Oj/8rD/hrX/goj/0iw8W/wDiRnw7/wDlNR/YOD/6HFL/AMJ6gfX8R/0Az/8AB0f/AJWH/DWv/BRH/pFh4t/8SM+Hf/ymo/sHB/8AQ4pf+E9QPr+I/wCgGf8A4Oj/APKw/wCGtf8Agoj/ANIsPFv/AIkZ8O//AJTUf2Dg/wDocUv/AAnqB9fxH/QDP/wdH/5WH/DWv/BRH/pFh4t/8SM+Hf8A8pqP7Bwf/Q4pf+E9QPr+I/6AZ/8Ag6P/AMrD/hrX/goj/wBIsPFv/iRnw7/+U1H9g4P/AKHFL/wnqB9fxH/QDP8A8HR/+Vh/w1r/AMFEf+kWHi3/AMSM+Hf/AMpqP7Bwf/Q4pf8AhPUD6/iP+gGf/g6P/wArD/hrX/goj/0iw8W/+JGfDv8A+U1H9g4P/ocUv/CeoH1/Ef8AQDP/AMHR/wDlYf8ADWv/AAUR/wCkWHi3/wASM+Hf/wApqP7Bwf8A0OKX/hPUD6/iP+gGf/g6P/ysP+Gtf+CiP/SLDxb/AOJGfDv/AOU1H9g4P/ocUv8AwnqB9fxH/QDP/wAHR/8AlYf8Na/8FEf+kWHi3/xIz4d//Kaj+wcH/wBDil/4T1A+v4j/AKAZ/wDg6P8A8rD/AIa1/wCCiP8A0iw8W/8AiRnw7/8AlNR/YOD/AOhxS/8ACeoH1/Ef9AM//B0f/lZ8hftyeI/+Ckv7WHwBufg9o/8AwTT8R+FL6f4k/CHxyNYvfj74A1KBbf4bfETQfGt3Y/ZYdOtnMupW+jvYwy+ZtglmWVkdUKN35bluBwGK+sSzWnUSo16fKqE1rWpTppt9EnK+i+6xyY3EYvE0HRhgZJupSnd1oWXs6inZ3it7dn36JH11H+1n/wAFEkjjQ/8ABLHxaSkaJn/hov4dDOxQucf2McZxnr+eK4P7BwX/AEN6X/giodf1/E/9AE15e2jp/wCSP8/vH/8ADWv/AAUR/wCkWHi3/wASM+Hf/wApqP7Bwf8A0OKX/hPUD6/iP+gGf/g6P/ysP+Gtf+CiP/SLDxb/AOJGfDv/AOU1H9g4P/ocUv8AwnqB9fxH/QDP/wAHR/8AlYf8Na/8FEf+kWHi3/xIz4d//Kaj+wcH/wBDil/4T1A+v4j/AKAZ/wDg6P8A8rD/AIa1/wCCiP8A0iw8W/8AiRnw7/8AlNR/YOD/AOhxS/8ACeoH1/Ef9AM//B0f/lYf8Na/8FEf+kWHi3/xIz4d/wDymo/sHB/9Dil/4T1A+v4j/oBn/wCDo/8AysP+Gtf+CiP/AEiw8W/+JGfDv/5TUf2Dg/8AocUv/CeoH1/Ef9AM/wDwdH/5WH/DWv8AwUR/6RYeLf8AxIz4d/8Aymo/sHB/9Dil/wCE9QPr+I/6AZ/+Do//ACsP+Gtf+CiP/SLDxb/4kZ8O/wD5TUf2Dg/+hxS/8J6gfX8R/wBAM/8AwdH/AOVh/wANa/8ABRH/AKRYeLf/ABIz4d//ACmo/sHB/wDQ4pf+E9QPr+I/6AZ/+Do//Kw/4a1/4KI/9IsPFv8A4kZ8O/8A5TUf2Dg/+hxS/wDCeoH1/Ef9AM//AAdH/wCVh/w1r/wUR/6RYeLf/EjPh3/8pqP7Bwf/AEOKX/hPUD6/iP8AoBn/AODo/wDysgu/2r/+CiVxaXduP+CWPi1Tc2lzbhv+Gi/h2dpngkiDEf2Nk435459KayLBpp/2vSdmnb2FQHj8TbTAzv8A9fo//Kz5M/YX8S/8FJf2S/2ZfAfwJ1n/AIJp+IvFmo+Eb3xjdT67ZfH34f6bbXa+JvGWu+J4lS0m065kjNtFq6Wr5lbe8JkBCuFXuzPLcDj8ZVxUc1p041FTSjKhNtclOMLuze/Lfo9bNXTOTA4jFYXDQoSwMm4ubuq0VrKTei5Zbpr7T2t5n11/w1r/AMFEf+kWHi3/AMSM+Hf/AMpq4P7Bwf8A0OKX/hPUOv6/iP8AoBn/AODo/wDysP8AhrX/AIKI/wDSLDxb/wCJGfDv/wCU1H9g4P8A6HFL/wAJ6gfX8R/0Az/8HR/+Vh/w1r/wUR/6RYeLf/EjPh3/APKaj+wcH/0OKX/hPUD6/iP+gGf/AIOj/wDKw/4a1/4KI/8ASLDxb/4kZ8O//lNR/YOD/wChxS/8J6gfX8R/0Az/APB0f/lYf8Na/wDBRH/pFh4t/wDEjPh3/wDKaj+wcH/0OKX/AIT1A+v4j/oBn/4Oj/8AKw/4a1/4KI/9IsPFv/iRnw7/APlNR/YOD/6HFL/wnqB9fxH/AEAz/wDB0f8A5WH/AA1r/wAFEf8ApFh4t/8AEjPh3/8AKaj+wcH/ANDil/4T1A+v4j/oBn/4Oj/8rD/hrX/goj/0iw8W/wDiRnw7/wDlNR/YOD/6HFL/AMJ6gfX8R/0Az/8AB0f/AJWH/DWv/BRH/pFh4t/8SM+Hf/ymo/sHB/8AQ4pf+E9QPr+I/wCgGf8A4Oj/APKw/wCGtf8Agoj/ANIsPFv/AIkZ8O//AJTUf2Dg/wDocUv/AAnqB9fxH/QDP/wdH/5WH/DWv/BRH/pFh4t/8SM+Hf8A8pqP7Bwf/Q4pf+E9QPr+I/6AZ/8Ag6P/AMrD/hrX/goj/wBIsPFv/iRnw7/+U1H9g4P/AKHFL/wnqB9fxH/QDP8A8HR/+Vk//BP7wR+1JrP7bX7Z/wC01+0B+zpe/s8aB8YPhv8As5+EPBmhah460DxxdXt58L7LxrZa5PJeaHFAkKSf21ZyxJJAuAxUM20mvRqww+Gy3B4OjiViZ0auJnOUYuCXtnTkrXS/kt+r2OWh7epjcXiatH2MatLDwgnPnf7pTT1UYrZrp92qP2erzzvCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAP/9f+/igAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgD//2Q=="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![54B0598B-506D-4C1A-BC48-D253169B7D57.jpg](attachment:54B0598B-506D-4C1A-BC48-D253169B7D57.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dimensión de a:  1\n",
      "Dimensión de b:  2\n",
      "Dimensión de c:  2\n",
      "Dimensión de d:  4\n"
     ]
    }
   ],
   "source": [
    "# Obtener la dimensión de un array\n",
    "\n",
    "# Obtener la dimensión del array a\n",
    "print('Dimensión de a: ',a.ndim)\n",
    "\n",
    "# Obtener la dimensión del array b\n",
    "print('Dimensión de b: ',b.ndim)\n",
    "\n",
    "# Obtener la dimensión del array c\n",
    "print('Dimensión de c: ',c.ndim)\n",
    "\n",
    "# Obtener la dimensión del array d\n",
    "print('Dimensión de d: ',d.ndim)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape de a: (5,)\n",
      "Shape de b: (2, 2)\n",
      "Shape de c: (2, 3)\n",
      "Shape de d: (2, 2, 3, 2)\n"
     ]
    }
   ],
   "source": [
    "# El shape de un array es una tupla que indica el tamaño de cada dimensión\n",
    "print('Shape de a:', a.shape )\n",
    "print('Shape de b:', b.shape) \n",
    "print('Shape de c:', c.shape)\n",
    "print('Shape de d:', d.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obtener el tipo de dato de un array\n",
    "print(b)\n",
    "b.dtype\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Representación de un byte en binario -> 1010\n",
    "\n",
    "# El tipo int16 puede representar un número entero de 16 bits (2 bytes)(-32.768 a 32.767)\n",
    "# El tipo int32 puede representar un número entero de 32 bits (4 bytes)(-2.147.483.648 a 2.147.483.647)\n",
    "# El tipo int64 puede representar un número entero de 64 bits (8 bytes)(-9.223.372.036.854.775.808 a 92.23.372.036.854.775.807)\n",
    "\n",
    "#El tipo float32 puede representar un número real de 32 bits (4 bytes)(-3.4028235e+38 a 3.4028235e+38)\n",
    "#El tipo float64 puede representar un número real de 64 bits (8 bytes)(-1.7976931348623157e+308 a 1.7976931348623157e+308)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3 4 5]\n",
      "[1 2 3 4 5]\n"
     ]
    }
   ],
   "source": [
    "a16 = np.array([1,2,3,4,5], dtype= np.int16)\n",
    "print(a16)\n",
    "\n",
    "a32 = np.array([1,2,3,4,5], dtype= np.int32)\n",
    "print(a32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7_/np1j_3td7p74w05s6b0zkz200000gn/T/ipykernel_17705/2295400327.py:2: DeprecationWarning: NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays.  The conversion of 32768 to int16 will fail in the future.\n",
      "For the old behavior, usually:\n",
      "    np.array(value).astype(dtype)`\n",
      "will give the desired result (the cast overflows).\n",
      "  a16[0] = 32768 # Esto es una unidad mayor que el límite (ver dos celdas arriba)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-32768,      2,      3,      4,      5], dtype=int16)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Provocar un overflow\n",
    "a16[0] = 32768 # Esto es una unidad mayor que el límite (ver dos celdas arriba)\n",
    "a16\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hay diversas formas de crear arrays de Numpy, a continuación vamos a ver algunas de ellas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Usando la función np.array()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3 4 5]\n"
     ]
    }
   ],
   "source": [
    "# Crea un nuevo array de 5 elementos de Numpy a partir de una lista.\n",
    "a = np.array([1,2,3,4,5])\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]]\n"
     ]
    }
   ],
   "source": [
    "# Crear un array de numpy a partir de una lista de listas\n",
    "b = np.array([[1,2],[3,4]])\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c: [0 1 2 3 4]\n",
      "c_1: [1 2 3 4 5]\n"
     ]
    }
   ],
   "source": [
    "# Crear un array de numpy a partir de un range\n",
    "\n",
    "# La funcion range() crea una lista de números enteros\n",
    "# Ejemplo:\n",
    "# lista_10 = range(10)\n",
    "# print(list(lista_10))\n",
    "\n",
    "# Crear un array de numpy a partir de un range\n",
    "c = np.array(range(5))\n",
    "print('c:',c)\n",
    "\n",
    "c_1 = np.array(range(1,6))\n",
    "print('c_1:',c_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define un array 'd'  de dim 2x2x3 a partir de una lista de listas anidada\n",
    "\n",
    "'''\n",
    "Hacer en casa\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La funcion np.array() también puede recibir otros tipos de datos como parámetro, como tuplas, etc. En este caso, la función convierte los datos en una lista de Python y crea una array a partir de esta lista."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['a' '12']\n",
      " ['b' '10']\n",
      " ['c' '7']]\n"
     ]
    }
   ],
   "source": [
    "# define una array e a partir de un diccionario\n",
    "datos = { 'a': 12, 'b': 10, 'c': 7 }\n",
    "\n",
    "e = np.array(list(datos.items()))\n",
    "print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Usando las funciones np.zeros() o np.ones()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de ceros\n",
    "#a = np.zeros(5, dtype=np.int32)\n",
    "#print(a)\n",
    "#print('\\n')\n",
    "# Crea un nuevo array de ceros de 2x3\n",
    "b = np.zeros((2,3))\n",
    "#print(b)\n",
    "#print('\\n')\n",
    "# Crea un nuevo array de ceros 4,100,100\n",
    "c = np.zeros((4,100,100))\n",
    "# print(c)\n",
    "# print(c.shape)\n",
    "\n",
    "# Create un nuevo array de unos\n",
    "d = np.ones(5)\n",
    "\n",
    "# Crea un nuevo array de unos del tamaño de b\n",
    "e = np.ones( b.shape )\n",
    "print(e)\n",
    "\n",
    "# Crea un nuevo array de unos del tamaño de c\n",
    "f = np.ones( c.shape )\n",
    "print(f)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[50 50 50 50 50 50 50 50 50 50]\n",
      "[[[50 50 50 50]\n",
      "  [50 50 50 50]\n",
      "  [50 50 50 50]]\n",
      "\n",
      " [[50 50 50 50]\n",
      "  [50 50 50 50]\n",
      "  [50 50 50 50]]]\n"
     ]
    }
   ],
   "source": [
    "# Crear Arrays con un valor determinado\n",
    "\n",
    "\n",
    "# Crea un nuevo array de 10 elementos con valor 50\n",
    "a = np.full( 10, 50 )\n",
    "print(a)\n",
    "# Crea un nuevo array de 2x3x4 elementos con valor 50\n",
    "b = np.full((2,3,4), 50)\n",
    "print(b)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[100 100 100 100]\n",
      "  [100 100 100 100]\n",
      "  [100 100 100 100]]\n",
      "\n",
      " [[100 100 100 100]\n",
      "  [100 100 100 100]\n",
      "  [100 100 100 100]]]\n"
     ]
    }
   ],
   "source": [
    "# Crea un array como el b pero con valor 100\n",
    "c = np.full( b.shape, 100)\n",
    "print(c)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1. 0. 0. 0. 0.]\n",
      " [0. 1. 0. 0. 0.]\n",
      " [0. 0. 1. 0. 0.]\n",
      " [0. 0. 0. 1. 0.]\n",
      " [0. 0. 0. 0. 1.]]\n",
      "[[1. 0. 0. 0. 0.]\n",
      " [0. 1. 0. 0. 0.]\n",
      " [0. 0. 1. 0. 0.]\n",
      " [0. 0. 0. 1. 0.]\n",
      " [0. 0. 0. 0. 1.]]\n"
     ]
    }
   ],
   "source": [
    "# Matriz identidad: Es una matriz cuadrada con unos en la diagonal principal y ceros en el resto de elementos\n",
    "identidad = np.eye(5)\n",
    "print(identidad)\n",
    "\n",
    "# otra forma de crear una matriz identidad\n",
    "identidad_1 = np.identity(5)\n",
    "print(identidad_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Define el array z de dim 1 completo de ceros\n",
    "'''\n",
    "\n",
    "'''\n",
    "Define un array z de dim 8x8 completo de ceros\n",
    "'''\n",
    "\n",
    "'''\n",
    "Define el array 'z' completo de ceros de n dim\n",
    "'''\n",
    "\n",
    "'''\n",
    "Define el array 'd' completo de unos de n dim\n",
    "'''\n",
    "\n",
    "'''\n",
    "Define un array como el que se muestra a continuación:\n",
    "[[0. 0. 0. 0. 0. 0. 0. 0.]\n",
    " [0. 1. 1. 1. 1. 1. 1. 0.]\n",
    " [0. 1. 1. 1. 1. 1. 1. 0.]\n",
    " [0. 1. 1. 1. 1. 1. 1. 0.]\n",
    " [0. 1. 1. 1. 1. 1. 1. 0.]\n",
    " [0. 1. 1. 1. 1. 1. 1. 0.]\n",
    " [0. 1. 1. 1. 1. 1. 1. 0.]\n",
    " [0. 0. 0. 0. 0. 0. 0. 0.]]\n",
    "'''\n",
    "\n",
    "\n",
    "'''\n",
    "Define un array 'g' conun range de 0 a 10 de dim 2\n",
    "'''\n",
    "\n",
    "'''\n",
    "Define un array 'h' con un range de 0 a 100 con un paso de 5 y una dim difrente de 1\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Usando las funciones np.random.random() o np.random.randn()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Las funciones `np.random.random()` y `np.random.randn()` de Numpy se utilizan para generar matrices de valores aleatorios, pero difieren en la distribución de los valores generados.\n",
    "\n",
    "La función `np.random.random()` genera valores aleatorios a partir de una distribución uniforme, lo que significa que todos los valores en el rango entre 0 y 1 tienen la misma probabilidad de ser generados. Esto puede ser útil para generar datos aleatorios para simulaciones o pruebas donde todos los valores en un rango dado son igualmente probables.\n",
    "\n",
    "La función `np.random.randn()`, por otro lado, genera valores aleatorios a partir de una distribución normal, que es una distribución en forma de campana que se utiliza a menudo en estadística y análisis de datos. Esto significa que es más probable que los valores generados estén cerca de la media de la distribución y menos probable que sean valores extremos. Esto puede ser útil para generar datos aleatorios que sigan una distribución del mundo real, como los datos de un proceso gaussiano.\n",
    "\n",
    "En general, la elección entre `np.random.random()` y `np.random.randn()` depende de las necesidades y requisitos específicos de su aplicación. Si necesita valores aleatorios de una distribución uniforme, puede utilizar np.random.rand(), y si necesita valores aleatorios de una distribución normal, puede utilizar np.random.randn()."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.11798926  0.88811708  0.80304088  1.31338216]\n",
      " [-0.75849676 -0.51518594  0.68447373 -3.40024817]\n",
      " [-1.45994995  1.22538073 -0.6750193   1.11305836]]\n"
     ]
    }
   ],
   "source": [
    "# Crea un nuevo array de 10 elementos aleatorios\n",
    "#a = np.random.random(10)\n",
    "#print(a)\n",
    "\n",
    "# otra form\n",
    "#a_1 = np.random.rand(10)\n",
    "#print(a_1)\n",
    "\n",
    "\n",
    "# crear una array de 15 elementos aleatorios enteros entre 0 y 10\n",
    "#b = np.random.randint(0, 10, 15) #  np.random.randint( desde, hasta, nº elementos)\n",
    "#print(b)\n",
    "\n",
    "# crear una array de 15 elementos aleatorios float entre 0 y 10\n",
    "#c = np.random.uniform(0,10,15)\n",
    "#print(c)\n",
    "\n",
    "\n",
    "# crear un array incluyendo los negativos\n",
    "d = np.random.randn( 3,4)\n",
    "print(d)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[5.07294806 5.76198461 4.89141796 5.21373122]\n",
      " [4.54204222 4.31840321 4.98337227 4.68010506]\n",
      " [4.37589526 5.79223708 6.46916573 4.78933699]]\n"
     ]
    }
   ],
   "source": [
    "# Podemos seguir una distribución normal\n",
    "data = np.random.normal(5,1,(3,4)) # np.random.normal( media ,  desviación estanda, shape)  \n",
    "print(data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.82708344 -0.42226374  0.92024819  0.34491232  2.09371626  1.07750121\n",
      " -1.99171752  0.59743948 -0.50285341  0.3075584   0.54714227  0.33630006\n",
      " -0.42331739  1.66610278 -0.34438111 -0.3632682  -0.05118474  0.66281171\n",
      " -1.88512436  0.24382703  0.97979153  0.40757936 -0.03346312  0.27236275\n",
      "  0.07741903 -0.06025871  1.48516329 -0.54643355  0.93126509  1.04518147\n",
      "  0.49094768  1.36611103  1.05446253 -0.36791325  3.12039412  0.81404144\n",
      "  1.19601437  1.38239533  0.51454228 -2.2346319   0.12796113  0.20366518\n",
      " -0.333229    0.85539719  0.18562373  1.04023242  0.63442688  1.39509224\n",
      " -0.37409319  0.7437511   0.54926029  0.61772041  0.09465109 -0.44136075\n",
      "  2.11029538 -0.23069351  0.76089072  0.32299273  0.51712541  0.10415734\n",
      " -0.87911044 -1.46655475 -0.48228603 -2.11976167  3.51881285  1.57052507\n",
      " -0.03950515  0.30395927  0.27839198 -1.03159338 -0.10215673  1.1074774\n",
      "  0.03162828  1.4993924   0.47335093  0.33213193 -0.87491688  0.04871596\n",
      " -1.28964607 -1.35256616 -0.84566095  1.02644953 -1.66147213 -0.17008449\n",
      " -0.36563274  1.59066953  0.4850792   0.6112473   0.22571936 -0.86835971\n",
      "  0.25572568  1.4918228  -0.64750736 -0.63973949  1.19667465  1.05740496\n",
      "  0.60996683  0.36449519  0.05427733  1.24021806]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Crea un nuevo array de 10 elementos siguiendo una distribución normal (Gaussiana)\n",
    "data = np.random.normal(0,1, 100)\n",
    "print(data)\n",
    "\n",
    "# plot the histogram\n",
    "import matplotlib.pyplot as plt\n",
    "plt.hist(data, bins=100)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Usando las funciones np.arange() o np.linspace(): Estas funciones le permiten crear nuevas matrices que contengan una serie de valores espaciados uniformemente. Esto puede ser útil para crear matrices de valores para trazar o otros fines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de valores espaciados uniformemente\n",
    "a = np.linspace(0, 10, 5)\n",
    "#print(a)\n",
    "\n",
    "\n",
    "# Crea un nuevo array de valores espaciados uniformemente\n",
    "b = np.linspace(0, 100, 1001)\n",
    "print(b)\n",
    "\n",
    "\n",
    "# Para no mostrar decimales raros podemos usar la función arange y especificar el número paso.\n",
    "c = np.arange(0, 100, 0.1)\n",
    "print(c)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ejercicios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de Numpy que contiene los valores 1, 2, 3, 4, 5.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de ceros con forma (5, 5).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de valores aleatorios de una distribución uniforme con forma (4, 4).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de valores espaciados uniformemente entre 0 y 1 con 100 elementos.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array que contiene los valores 1, 2, 3, 4, 5, 6 reorganizados en una matriz 2x3.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de ceros con forma (2, 2, 2, 2).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Crea un nuevo array de valores aleatorios de una distribución normal con forma (3, 3, 3).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un nuevo array de valores espaciados uniformemente entre -10 y 10 con 10 elementos.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Accediendo y modificando elementos de una array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para acceder y modificar los elementos de un array de Numpy podemos utiliza el indice para especificar la posición del elemento que queremos acceder o modificar, tal y como hacemos con las listas de Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "primero: 1\n",
      "último: 5\n",
      "último: 5\n"
     ]
    }
   ],
   "source": [
    "# Crea un array de 1 dimensión con los valores 1, 2, 3, 4, 5\n",
    "a = np.array([1,2,3,4,5])\n",
    "\n",
    "# Accede al primer elemento del array\n",
    "print('primero:',a[0])\n",
    "\n",
    "# Accede al último elemento del array\n",
    "print('último:', a[4] ) # Esto solo sirve si el array es de dim 5\n",
    "print('último:', a[-1] ) # Siempre vamos a acceder al último elemento\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para acceder a un subset de elementos del array, podemos especificar un rango de indices, utilizando la sintaxis estandar de las listas de Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3]\n",
      "[1 2 3]\n",
      "[1 2 3]\n",
      "[1 2 3]\n"
     ]
    }
   ],
   "source": [
    "# Crea un array de 1 dimensión con los valores 1, 2, 3, 4, 5\n",
    "a = np.array([1,2,3,4,5])\n",
    "\n",
    "# Accede a las tres primeras posiciones del array\n",
    "print(a[[0,1,2]])\n",
    "\n",
    "# Otra forma de acceder a las tres primeras posiciones del array\n",
    "print(a[0:3])\n",
    "\n",
    "# otra forma de acceder a las tres primeras posiciones del array\n",
    "print(a[:3])\n",
    "\n",
    "# otra forma podría ser:\n",
    "print(a[0:-2]) # Ojo, este solo sirve para un array de dim 5 \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para aceder a elementos arbitrarios de un array, podemos utilizar una lista de indices, utilizando la sintaxis estandar de las listas de Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 30 50]\n",
      "[10 30 50]\n"
     ]
    }
   ],
   "source": [
    "# Create un nuevo array de 1 dimensión con los valores 10, 20, 30, 40, 50\n",
    "a = np.array([10,20,30,40,50])\n",
    "\n",
    "# Accede a los indices 0, 2, 4 del array\n",
    "print(a[[0,2,4]])\n",
    "\n",
    "# otra forma:\n",
    "print(a[0::2]) # a[ desde : hasta el final(implicito): paso ]\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para modificar los valores de una array, podemos utilizar la asignación y operaciones para cambiar los valores de los elementos seleccionados. Por ejemplo, para establecer el valor de un solo elemento a un nuevo valor, podemos utilizar la asignación:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n",
      "[10  1  2  3  4  5  6  7  8  9]\n"
     ]
    }
   ],
   "source": [
    "# Crea un nuevo array\n",
    "a = np.array(range(10))\n",
    "print(a)\n",
    "\n",
    "# Establece el valor del primer elemento a 10\n",
    "a[0] = 10\n",
    "\n",
    "print(a)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para modificar los valores de múltiples elementos a la vez, puede usar operaciones y asignación:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2 4 6 4 5]\n",
      "[2 4 6 4 5]\n"
     ]
    }
   ],
   "source": [
    "# Crea un nuevo array\n",
    "a = np.array([1,2,3,4,5])\n",
    "\n",
    "# Multiplica los valores de los primeros tres elementos por 2 y asigna el resultado al array\n",
    "multiplicado_por_2 = a[:3] * 2\n",
    "a[:3] = multiplicado_por_2\n",
    "print(a)\n",
    "\n",
    "a = np.array([1,2,3,4,5])\n",
    "# Esto sería lo mismo:\n",
    "a[:3] = a[:3] * 2\n",
    "print(a)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 1, 2, 3]\n",
      "[2 4 6]\n"
     ]
    }
   ],
   "source": [
    "ejemplo = [1,2,3]\n",
    "print( ejemplo * 2 )\n",
    "\n",
    "ejemplo_array = np.array([1,2,3])\n",
    "print(ejemplo_array * 2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Slicing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Esto permite seleccionar un subconjunto contiguo de elementos de una matriz, utilizando la sintaxis `start: stop: step` para especificar el rango de valores a incluir y el stride (es decir, el número de elementos a omitir entre valores consecutivos)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10 11 12 13 14 15 16 17 18 19 20]\n",
      "[12 14 16 18]\n",
      "[10 12 14 16 18 20]\n",
      "[11 13 15 17 19]\n"
     ]
    }
   ],
   "source": [
    "# Create a new Numpy array\n",
    "a = np.array(range(10,21))\n",
    "print(a)\n",
    "\n",
    "# Accede a los elementos 2,4,6,8 (esto son los indices) del array\n",
    "print(a[[2,4,6,8]])\n",
    "\n",
    "# Start:start:step: start si que es incluido, stop no es incluido, step es el paso\n",
    "# Selecciona los elementos intercalados del array\n",
    "print(a[::2])\n",
    "\n",
    "# Selecciona los elementos intercalados del array (impares)\n",
    "print(a[1::2])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23] (24,)\n",
      "[[[ 0  1  2  3]\n",
      "  [ 4  5  6  7]\n",
      "  [ 8  9 10 11]]\n",
      "\n",
      " [[12 13 14 15]\n",
      "  [16 17 18 19]\n",
      "  [20 21 22 23]]] (2, 3, 4)\n"
     ]
    }
   ],
   "source": [
    "# crea un array de 4x6\n",
    "a = np.array(range(24))\n",
    "print(a, a.shape)\n",
    "\n",
    "reshaped_a = a.reshape(4,6)\n",
    "#print(reshaped_a, reshaped_a.shape)\n",
    "\n",
    "reshaped_a = a.reshape(2,3,4)\n",
    "print(reshaped_a, reshaped_a.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[ 0  1]\n",
      "  [ 2  3]\n",
      "  [ 4  5]]\n",
      "\n",
      " [[ 6  7]\n",
      "  [ 8  9]\n",
      "  [10 11]]\n",
      "\n",
      " [[12 13]\n",
      "  [14 15]\n",
      "  [16 17]]]\n",
      "[6 7]\n",
      "[[ 6  7]\n",
      " [ 8  9]\n",
      " [10 11]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 0,  2,  4],\n",
       "       [ 6,  8, 10],\n",
       "       [12, 14, 16]])"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define una matriz de 3x3x2\n",
    "a = np.arange(18)\n",
    "reshaped_a = a.reshape(3,3,2)\n",
    "print(reshaped_a)\n",
    "\n",
    "\n",
    "# Selecciona la primera fila de la segunda matriz\n",
    "print(reshaped_a[1,0,:])\n",
    "\n",
    "# Selecciona la segunda matriz completa\n",
    "print(reshaped_a[1,:,:])\n",
    "\n",
    "\n",
    "# seleciona la segunda fila de todas las matrices\n",
    "sub_matriz = reshaped_a[:,1,:]\n",
    "sub_matriz.shape\n",
    "\n",
    "# selecciona la primera columna de todas matrices\n",
    "reshaped_a[:,:,0]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ejercicios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de Numpy que contiene los valores 1, 2, 3, 4, 5, y accede al primer y último elemento del array.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores aleatorios entre 0-9 con forma (10, 10), y accede a los cuatro elementos centrales de la quinta fila del array.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores espaciados uniformemente entre 0 y 50 con 100 elementos, y los elementos intercalados del array.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array que contiene los valores 1, 2, 3, 4, 5, y usa la indexación basada en Booleanos para seleccionar solo los elementos del array que son mayores que 3.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de ceros con forma (5, 5), y usa la indexación basada en enteros para establecer el valor del elemento central del array a 1.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de Numpy que contiene los valores 1, 2, 3, 4, 5, y establece el valor del segundo elemento del array a 10.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores aleatorios entre 0-9 con forma (9, 9), y usa la asignación para establecer el valor del elemento central del array a 999.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores espaciados uniformemente entre 0 y 1 con 100 elementos, y usa la indexación y operaciones para multiplicar los valores de los primeros 50 elementos por 0.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array que contiene los valores 1, 2, 3, 4, 5, y usa la indexación basada en Booleanos y operaciones para sumar 1 a los elementos del array que son menores o iguales a 3.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de ceros con forma (5, 5), y usa la indexación basada en enteros y operaciones para sumar 1 a los valores de la diagonal del array (es decir, los elementos con índices (0, 0), (1, 1), (2, 2), etc.).\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Operaciones con Arrays"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numpy arrays soporta una amplia gama de operaciones matemáticas y estadísticas para realizar cálculos sobre los arrays. Algunas de estas operaciones son:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Operaciones elemento a elemento: Estas operaciones aplican una operación dada a cada elemento de una matriz y devuelven una nueva matriz que contiene los resultados. Por ejemplo, la adición y la sustracción elemento a elemento se pueden realizar utilizando los operadores + y -, respectivamente, y la multiplicación y división elemento a elemento se pueden realizar utilizando los operadores * y /, respectivamente."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 6  8 10 12 14]\n"
     ]
    }
   ],
   "source": [
    "# Crea dos Numpy arrays\n",
    "a = np.array([1,2,3,4,5])\n",
    "b = np.array([5,6,7,8,9])\n",
    "\n",
    "# Suma los dos arrays\n",
    "suma = a + b\n",
    "print(suma)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 5, 6, 7, 8, 9]"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Las listas de python no tienen operaciones elemento a elemento\n",
    "a_1 = [1,2,3,4,5]\n",
    "a_2 = [5,6,7,8,9]\n",
    "a_1 + a_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-4. -4. -4. -4. -4.]\n"
     ]
    }
   ],
   "source": [
    "# Crea dos Numpy arrays\n",
    "a = np.array([1,2,3,4,5])\n",
    "b = np.array([5.,6.,7.,8.,9.])\n",
    "\n",
    "# Realiza la resta de los dos arrays\n",
    "resta = a - b\n",
    "print(resta)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Que ocurre si intentamos sumar dos arrays de distinto tamaño?\n",
    "\n",
    "# Realiza la suma de los dos arrays\n",
    "a = np.array([1,2,3,4,5])\n",
    "b = np.array([5,6,7])\n",
    "\n",
    "suma = a + b\n",
    "print(suma)\n",
    "\n",
    "# Da error porque no son del mismo tamaño\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 2 3 4 5] (5,)\n",
      "[[1 2 3 4 5]] (1, 5)\n",
      "[[ 2  4  6  8 10]] (1, 5)\n"
     ]
    }
   ],
   "source": [
    "# No es necesario que los arrays tengan la misma forma, pero si que sean shapes compatibles.\n",
    "a = np.array([1,2,3,4,5])\n",
    "b = np.array([1,2,3,4,5]).reshape(1,5)\n",
    "\n",
    "print(a, a.shape)\n",
    "print(b, b.shape)\n",
    "\n",
    "suma = a + b\n",
    "print(suma, suma.shape )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 1 2 3 4]\n",
      " [5 6 7 8 9]]\n",
      "[1 2 3 4 5]\n",
      "[[ 1  3  5  7  9]\n",
      " [ 6  8 10 12 14]]\n"
     ]
    }
   ],
   "source": [
    "# Definir un array de 2x5\n",
    "a = np.arange(10).reshape(2,5)\n",
    "print(a)\n",
    "\n",
    "b = np.array([1,2,3,4,5])\n",
    "print(b)\n",
    "# Suma los dos arrays\n",
    "suma = a + b\n",
    "print(suma)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Operaciones de agregación: Estas operaciones calculan una estadística de resumen para una matriz, como la suma, la media o la desviación estándar, y devuelven un valor escalar. Por ejemplo, puede usar las funciones np.sum() y np.mean() para calcular la suma y la media de una matriz, respectivamente."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15\n"
     ]
    }
   ],
   "source": [
    "# Crea un Numpy array\n",
    "a = np.array([1,2,3,4,5])\n",
    "\n",
    "# Calcula la suma de todos los elementos del array\n",
    "print(a.sum())\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0\n"
     ]
    }
   ],
   "source": [
    "# Crea un Numpy array\n",
    "a = np.array([1,2,3,4,5])\n",
    "\n",
    "# Calcula la media de todos los elementos del array\n",
    "print(a.mean())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.1240998703626617\n"
     ]
    }
   ],
   "source": [
    "# Crea un Numpy array\n",
    "a = np.array([2,5,2,2,10])\n",
    "\n",
    "# Calcula la desviación estándar de todos los elementos del array\n",
    "desviacion = a.std()\n",
    "print(desviacion)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hay muchas otras funciones de agregación disponibles en Numpy, como np.min() y np.max() para calcular los valores mínimo y máximo de una matriz, respectivamente. Algunas de estas son:\n",
    "- np.sum(): Suma de todos los elementos de la matriz.\n",
    "- np.prod(): Producto de todos los elementos de la matriz.\n",
    "- np.mean(): Media de todos los elementos de la matriz.\n",
    "- np.std(): Desviación estándar de todos los elementos de la matriz.\n",
    "- np.var(): Varianza de todos los elementos de la matriz.\n",
    "- np.min(): Valor mínimo de todos los elementos de la matriz.\n",
    "- np.max(): Valor máximo de todos los elementos de la matriz.\n",
    "- np.argmin(): Índice del valor mínimo de todos los elementos de la matriz.\n",
    "- np.argmax(): Índice del valor máximo de todos los elementos de la matriz.\n",
    "- np.median(): Mediana de todos los elementos de la matriz.\n",
    "\n",
    "entre otras..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.44782819 0.07945296 0.15124193 0.42462288 0.74457473 0.0789915\n",
      " 0.01892892 0.51750666 0.68076092 0.26341393]\n",
      "6\n"
     ]
    }
   ],
   "source": [
    "# ejemplo np.argmin()\n",
    "\n",
    "a = np.random.random(10)\n",
    "print(a)\n",
    "\n",
    "print(a.argmin())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Broadcasting: Esto se refiere a la capacidad de Numpy de aplicar automáticamente operaciones a matrices de diferentes formas, siempre que las formas sean compatibles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n",
      "[ 0  2  4  6  8 10 12 14 16 18]\n"
     ]
    }
   ],
   "source": [
    "# Crea un array de 10 elementos, y multiplica cada elemento por 2\n",
    "a = np.arange(10)\n",
    "print(a)\n",
    "\n",
    "a_2 = a * 2\n",
    "print(a_2)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 1 2]\n",
      " [3 4 5]]\n",
      "[1 2 3]\n",
      "[[ 0  2  6]\n",
      " [ 3  8 15]]\n"
     ]
    }
   ],
   "source": [
    "# Crea un array de 6 elementos de forma (2, 3)\n",
    "a = np.arange(6).reshape(2,3)\n",
    "print(a)\n",
    "\n",
    "# Crea un array de 3 elementos\n",
    "b = np.array([1,2,3]) # np.arange(1:4)\n",
    "print(b)\n",
    "# multiplica ambos arrays\n",
    "producto = a * b\n",
    "print(producto)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[ 0  1  2  3]\n",
      "  [ 4  5  6  7]]\n",
      "\n",
      " [[ 8  9 10 11]\n",
      "  [12 13 14 15]]\n",
      "\n",
      " [[16 17 18 19]\n",
      "  [20 21 22 23]]]\n",
      "[[[100 101 102 103]\n",
      "  [104 105 106 107]]\n",
      "\n",
      " [[108 109 110 111]\n",
      "  [112 113 114 115]]\n",
      "\n",
      " [[116 117 118 119]\n",
      "  [120 121 122 123]]]\n"
     ]
    }
   ],
   "source": [
    "# Crea un array de 3x2x4\n",
    "a = np.arange(24).reshape(3,2,4)\n",
    "print(a)\n",
    "\n",
    "# Suma 100 a todos los elementos del array\n",
    "sumatorio = a + 100\n",
    "print(sumatorio)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Operaciones de álgebra lineal: Numpy incluye una serie de funciones y métodos para realizar operaciones de álgebra lineal en matrices, como multiplicación de matrices, determinantes y resolución de ecuaciones lineales. Por ejemplo, puede usar la función np.dot() para calcular el producto escalar de dos matrices, o la función np.linalg.solve() para resolver un sistema de ecuaciones lineales representado por una matriz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n",
      "\n",
      "\n",
      "[[ 7  8]\n",
      " [ 9 10]\n",
      " [11 12]]\n",
      "\n",
      "\n",
      "[[ 58  64]\n",
      " [139 154]]\n"
     ]
    }
   ],
   "source": [
    "# Define dos matrices\n",
    "a = np.array([[1,2,3],[4,5,6]])\n",
    "b = np.array([[7,8],[9,10],[11,12]])\n",
    "\n",
    "print(a)\n",
    "print('\\n')\n",
    "print(b)\n",
    "print('\\n')\n",
    "\n",
    "\n",
    "# Realiza la multiplicación de matrices\n",
    "## NO ES ESTO: a * b\n",
    "\n",
    "multiplicadas = a.dot(b)\n",
    "print(multiplicadas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n",
      "-9.51619735392994e-16\n",
      "[[1. 0. 0.]\n",
      " [0. 1. 0.]\n",
      " [0. 0. 1.]]\n",
      "1.0\n"
     ]
    }
   ],
   "source": [
    "# Define una matriz\n",
    "a = np.arange(1,10).reshape(3,3)\n",
    "print(a)\n",
    "\n",
    "# Calcula el determinante de la matriz\n",
    "det = np.linalg.det(a)\n",
    "print(det)\n",
    "\n",
    "# Define la matriz indentidad\n",
    "identidad = np.identity(3)\n",
    "print(identidad)\n",
    "\n",
    "# Calcula el determinante de la matriz\n",
    "det = np.linalg.det(identidad)\n",
    "print(det)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-4.   4.5]\n",
      "5.0\n",
      "6.0\n"
     ]
    }
   ],
   "source": [
    "# Define los coeficientes de la ecuación lineal\n",
    "a = np.array([[1,2],[3,4]])\n",
    "b = np.array([5,6])\n",
    "\n",
    "# Esto representa el sistema de ecuaciones:\n",
    "# 1x + 2y = 5\n",
    "# 3x + 4y = 6\n",
    "\n",
    "\n",
    "# resuelve el sistema de ecuaciones\n",
    "solucion = np.linalg.solve(a, b)\n",
    "print(solucion)\n",
    "\n",
    "# prueba\n",
    "\n",
    "x = -4\n",
    "y = 4.5\n",
    "\n",
    "print(x + 2*y)\n",
    "print(3*x + 4 *y)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de Numpy que contiene los valores 1, 2, 3, 4, 5, y calcula la multiplicacion de todos los \n",
    "elementos del array.\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores aleatorios de una distribución uniforme de números enteros con forma (10, 10), y calcula \n",
    "la media de los elementos de la primera fila del array.\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array que contiene los valores 1, 2, 3, 4, 5, y usa la indexación basada en Booleanos \n",
    "para calcular la suma de solo los elementos del array que son mayores que 3.  \n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de unos con forma (5, 5), y usa la indexación basada en enteros para calcular la suma\n",
    "de los valores de la diagonal del array (es decir, los elementos con índices (0, 0), (1, 1), (2, 2), etc.).\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "\n",
    "Crea dos nuevos arrays de Numpy, x e y, que contienen los valores 1, 2, 3 y 4, 5, 6, respectivamente, \n",
    "y calcula el producto elemento a elemento de x e y.\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores aleatorios de una distribución uniforme con forma (10, 10), y \n",
    "usa el broadcasting para sumar 1 a todos los elementos del array.\n",
    "'''\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de valores espaciados uniformemente entre 0 y 1 con 100 elementos, y usa \n",
    "el broadcasting establecer los valores de los últimos 50 elementos a 0.\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array que contiene los valores 1, 2, 3, 4, 5, y usa la indexación basada en \n",
    "Booleanos y el broadcasting para dividir todos los elementos del array que son menores \n",
    "o iguales que 3 entre 2.\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Crea un nuevo array de ceros con forma (5, 5), y usa la indexación basada en enteros y el broadcasting \n",
    "para sumar los valores 1, 2, 3, 4, 5 a las filas del array en orden (es decir, suma 1 a la primera fila,\n",
    " 2 a la segunda fila, etc.).\n",
    "'''\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('_mpl-gallery')\n",
    "# generar el conjunto de datos\n",
    "np.random.seed(1)\n",
    "\n",
    "x = 4 + np.random.normal(0, 1.5, 200)\n",
    "fig, ax = plt.subplots()\n",
    "ax.hist(x, bins=8, linewidth=0.5, edgecolor=\"white\")\n",
    "ax.set(xlim=(0, 8), xticks=np.arange(1, 8),\n",
    "       ylim=(0, 56), yticks=np.linspace(0, 56, 9))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5noBe+YwGUNhffT5Wm+eB19TUt5QSeV3iuQvcL01EVE1OVeBwbwRRrwOzy1mMzVd/Ee9SKo+5eBZRn6OmArumgloIgWcvLCCTr9JbOCIiQsCl4mhfFG6HgguxNGIJ845pHp/PIODW4FBr50rMmpn6llLizFwSk9yKRURUNc1+J27Z0ACXpmBkKmlqSAOFLVtnZ2ur9VkTQW1IiWRO5/3SRERV1N/gxdG+CKQEXh6PI5m1xmxmMmtgeilbMwvLamLqWwD44blF6DwjlIio4gSAXe1B9Dd6kczoGJpKml3S60wuZhH0aHA7FNtPgdt+RC2lxMhcErHk6m9fISKitXGoAtf3RdDX4EEsnrNkSBedm6uNW7ZsPaKWUiKdN3ByMm52KURENc/nVHG0LwKvU8X4fAazcWsPkNI5AzPLWTQFnLYeVds6qIUQ+NGFJeQ55U1EVFGNPicO94ahCIHT00kkMtboR1/L5GIWYa/D1qvAbTv1bUiJCwspTC1zlTcRUSX1Rj24vj8CADg1HrdNSAOAlIVTy+wa0oBNR9RSSuiGxE/HucqbiKiSdrYFsKHJh1RWx+CkdfvRVxPP6IjFc4j47Hl3tS2DuniWNw82ISKqDE0RONgdQkvAhflEzvYLs8YX0gh6/FAVabuwtt3UtyElZuIZnJuvrQ3tRERW4XWouGVDA5oDLkwuZmwf0gCgG8DYvD2nwG03opYS+BHP8iYiqoio14EjvRGoisDoTArL6dq5hXAhmUcklbfddZi2GlFLKTE4HUeC11cSEZVdV9iNGweiUAQwOJmoqZAuGoulYbd9QrYJ6uKe6aGZhNmlEBHVnG0tfhzoDiObN3ByLIFs3m5xtjpZXWLGZseL2mbqWwiB58eXodvntSUisjxVCOzvDqE96MJiMofRWfv3o69leimLqN8BTbHH3mpbjKgNKTGXyGJssfZ/gYiIqsWtKbhpQxRtQReml7J1EdJA4YatifmMLUIasMmIWgD4yRgXkBERlUvYo+FIbwROVcG52TQWU+ZeT1lt88k8GjM6PE7rX9ph+RG1ISVGYykspuvrl4iIqFLaQy7cNNAATREYmkzWXUgX2WW7luVH1IYh8RIv3SAiKovNzT5saw0gk9MxOJWEUcfnRiWzBmKJHCJea59YZumgllLi5FQcWb2Of5OIiMpAEcC+zhC6Ih4sp/I4PcNDowBgYiGDsEeDhXPaukEtpUQyq2Nkzp5nyxIRWYVLU3C4N4yIx4GZpSzGF3iZUVFel5hayqI1ZN2rMC0b1EIIvDC5DBttdSMispygW8PRvghcmoLzsTTmE/XZj76ameUsGgPW3a5lycVkhpRYTOUwvsh3fUREa9UacOHmDQ1wqgqGJ5MM6SuQEphazJpdxhVZMqgVIfDiJK+wJCJaqw2NXhzuDcMwJE6Ox5HKca3P1cTiOeR0ackTyywX1MXDTaaWrfvuhojIqoQA9nYGsbM9iGRGx8nxBLge99okgMlFax6CYrkeNUfTRERr41QFDvVG0OB1YC6exYUY24elmE/k0Rw04NKEpQLbUiNqQ0pML2cwl8iZXQoRka34XSpu2diAqNeBsfkMQ3qNJhesN6q21Iiao2kiotI1+Z043BOGEAKnp5JIZDnXvVaLqTxSWR1uh3WOFrXMiNqQEuOLaSzU6VF2RERr0dfgxfV9EUgJvDweZ0iXwYTFRtWWGVELgEeFEhGtkgCwsz2AgUYfkhkdQ1M8HKpcltM6Epk8vE7VEoFtiRF1cTS9nOFomojoWhyKwNG+CPobvIglcgzpCphczFoipAGLjKgVITA4kzC7DCIiy/M5VRzti8DrVDGxkMHMMhffVkI8rVumV236iLq40pu9aSKiq2vwOXDLxgZ4HCpGp5MM6QqbWrLGqNr0ETVH00RE19Yd8WBvZxCGITE4EUdWN7ui2reYzCObN+BQzd1XbeqI2pASC6kcZuI8hYyI6Ep2tAWwvyuETM7Ai2MJhnQVTS2Zn0+mBrUiBE5NcaU3EdHlqIrA4d4wNjR6sZDMYXCSi8aqbT6eg26Yewa4aVPfxfumx5d4eg4R0Wt5HAqO9kXgd2mYXMxgeon9aDNIADPLObSGnKbVYGqP+hR700RErxPxOnCkNwJNETg7m8JSinPdZppdzqIl6IRZbWpTpr6llMjqBs7Pp8x4eiIiy+oMu3FTfxSqAIYmkwxpCzAkMBvPmTb9bVqPengmCcN6134SEZlma4sfB7vDyOkGTo4lkMnzOFCrmDHx6mVTpr4lgNEYR9NERACgCmB/VwgdYQ+WUnmcmeHfR6vJ6xKLyTxCXq3qW7WqHtSGlLiwkEaWN5kTEcGtKTjSF0HIrWF6MYOJRfO3A9HlzcZzCPscVX/eqge1IgTOzHGLARFRyKPhaG8ETlXBuVneHmh1iYyOdM6AS6vuAShV7VFLKbGUziGW5DYDIqpv7UEXbh5ogKYKDE0lGdI2MWtCr7rqi8lGZjmaJqL6tqnJh0O9EeR1AyfHE0jn2Aq0i/lEDtVe/F3VqW/dkDg/n67mUxIRWYYigL0dIXRHPYin8xiZ5qIxuzEkEEvk0OB3VG36u2pBbUiJ0fkUdBOPYSMiMotTFTjSG0HE68DMUhbjCzyV0a7m4jk0Bqp3UlnVgpqLyIioXgVcGo72ReDWFFyIpRFLsB9tZ+mcgUQmD69Trcqouio9akNKzMSziGd4wg4R1ZeWgBO3bIzCpSkYnk4ypGvE7HKutqa+FSEwGuNomojqy0CjFzvbAsjrEqcm4+BBY7VjMZmHbkioSuXDuipBnTcMTCxyERkR1QcBYHdHEH0NXiQyOoanOFCpNRKFFeDVWFRW8aAunkSmcw0ZEdUBhypwqCeCRp8DsXgW52NcNFar5hPVWVRW8aBWhMA5nutNRHXA71RxtC8Cj1PF2HwGc3Ee7lTLklkDmbwBp1rZk8oqHtTJrI45nkRGRDWuye/EoZ4wFCFwejqJRIYN6XoQi+fQGqrsqLqiq74NKXGOd04TUY3rjXpwfV8EkMDL43GGdB2ZT1R+9XdFR9SKEDi/wKAmotokAOxoC2BDkw+prI7BSS4aqzc5XVZ8T3XFgrpwAUeee6eJqCZpisB1PWE0+52YT+Rwbo47W+rVfKIQ1JVS0alvTnsTUS3yOlTcsqEBTX4nJhYyDOk6t5Cs7CE2FRtRCyFwYYG/vERUWxq8DhzujUBVBEZnUlhOc9aw3umGxHJaR8BdmenvigS1lBILqRzSPIaHiGpIV9iNfV0hGIbE4GQcWZ4GSisWk3kE3JWZ/q7YiHpskZv8iah2bGv1Y3OzH+msjqHJJDgMoUstpvLohKsij12RoBZCYJxHhhJRDVAVgYNdIbQGXVhM5jA6y79t9Hq6IZHM6PC6yj/9XfagllIintWRyLJvQ0T25nEoONIbQcCtYWopi6nFrNklkYUtpPLwuso//V32Vd8SwBgXkRGRzUU8Dhzb2ICAS8O52RRDmq5pKZm3x2IyRQhMLDGoici+OkJu7O8KQUqJwckkMlwYS6uQ1SVSWR1uh1LWwC57UKdyOhZSXApJRPa0pdmHra0BZHI6Bie4aIxKs5jMw13ms7/LOvVtSMlFZERkS4oADnaHsLU1gOVUHi8zpGkNFlPln/4u64haEQLj3JZFRDbj0hQc6Q0j7HFgejGDCfajaY3SOQPZvAGnVr5xcFmDOq8bmEvwF5yI7CPo1nC0LwKXquDcXLrix0FS7VtM5dHod5RtZF22oDakxHQ8C1muByQiqrDWoAvXdYcBAENTSaRznOym9VtO5dEUKF+fumxBLQBMxzmaJiJ72Njkw/ZWP3K6xOBkAjozmsokkdEhpbTeiFoIgZll9qeJyNoUAezpCKIn6kU8ncfING/5o/IyJJDM6mW7o7psQZ3O6YjzNDIisjCnKnC4N4Ko14HZ5SzG5jm4oMpYTullu6O6LEFtSIlJjqaJyMICLhVH+6JwOxRciKURS3DRGFXOcjqP1nB5LukoS1ArQmCG/WkisqhmvxOHesIQQmBkKolklg1pqqxk1oBuSKiKhaa+p5cZ1ERkPf0NXuxqDyCvS5yaiIOngVK1xNN5BD3auvvUZQnqpXQOWS6ZJCILEQB2tQfR3+hFMqNjaCppdklUZ5bTOoKe9cfsuh/BkBJTHE0TkYU4VIFD3WE0+p2IxXM4H+PRxlR98XQeQrjX/TjrDmr2p4nISnxOFUf7IvA6VYzPZzAbz5ldEtWpTF4irxvQ1PUdJ1qWqe/5JIOaiMzX6HPicG8YihA4PZ1EIsOWHJkrkdER9Ih19anXHdSJbB5ZnQeHEpG5eqIe7OkIQjckTo3HwdNAyQoSGQNBz/oeY11BbUiJOU4rEZHJdrQFsLHJh1RWx+AkF42RdSSzurmrvgWAOU57E5FJNEXgYHcILQEXFhI5nJ3jojGylmR2/ed+ry+ohcB8kiNqIqo+r6OwaMznUjG5mMH0Ev8WkfVIWbij2rOO40TXFdS6IbGU5jF8RFRdUa8DR3ojUBWB0ZkUltO8Z4CsK5HR4XIoUNY4ql7zmnEpJeaTOd4/TURV1RV248aBKBQBDE4mGNJkeYmMvuaQBtYxopZgf5qIqmtbix+bW/xI53QMTSTBhd1kB8nM+t5MrjmoFSEQS7AnRESVpwqB/d0htAddWErmcWaWd0iTfWR1ibwuoalrG1Wvq0c9n2JQE1FluTUFR/oiCLk1TC9lMbnImTyyn2RWR8Ctrmn195qDOqcbyPAaGiKqoLBHw5HeCJyqgrOzaSymuHiV7Cmd0+F3q1jLmHpNQS2l5D8YIqqo9pALB7rCkFJiaDKJNAcGZGOprLHmBWVrDGpgMc1pbyKqjE3NPmxvDSCT0zE4lYTBjCabS6/jTNs1BbUQ4P5pIio7RQD7OkPoiniwnMrj9AwXjVFtyOSMNZ9QtsagFlhkUBNRGbk0BYd7w4h4HJhZymJ8IWN2SURlIwFk8gbcjtJPKFvzYrJlBjURlUnQreFoXwQuTcH5WBrzCf59odqTyhpwaUrJo+o1BXUyqyNv8EwyIlq/1oALB3vCEACGp5JIZdmQptq01j51yUFdWPHNhWREtH4bGr3Y0RZATpcYmkyAC7uplqVza7vysvSgBtifJqJ1EQLY0xFEb9SLRDqP4WkuGqPat9bZopKDWhECyxkGNRGtjVMVONQbQYPXgbl4FhdiXDRG9SGnSxhSlryfek096kSWt9UQUen8rsId0h6HirH5DObibKNRfcnlDbhKXPm95sVkRESlaPI7cbgnDCEETk8lkeCiMapD6byEUyttP3XJQa0bkmd8E1FJ+ho82N0eRF6XODUR56IxqlvZvAGJ0s78LjmoOZomotUSAHa2BzDQ6EMyo2NoKml2SUSmyuaNki/mKCmopZSIZ7mQjIiuzaEIXNcTRpPfiVgih/NzabNLIjJdNm9U9sATKbmQjIiuzecsLBrzOlVMLGQws8xFY0QAkM2XflhYSUEtBJDMMKiJ6MoafA4c7o1AFQKj00ksZ9iQJirKrmGBRolBLZDIMaiJ6PK6Ix7s7QzCMCQGJ+LgBBzRqxkSyOsSmlrBVd8JjqiJ6DJ2tAWwscmHdFbHqUkuGiO6kmzegKaufi91yUGd4oiaiC6hKgIHu0NoDbiwkMzh7CwXjRFdTTZvwONc/S1aJQW1bkjemkVEF3kcCo72ReB3aZhczGB6iYvGiK4lZ0hIYNXbtEoK6qzORSFEVBDxOnCkNwKHInB2NoWlFGfbiFYjr8vKHXiy1rs0iai2dIbd2N8ZgiElBieTPK2QqAR5vbSZ6VUHtZQS6TzfMRPVuy0tfmxt8SOT0zE4kQQjmqg0eaO0Q09WH9QA3zUT1TFVAPu6QugMe7CUyuPMDO+QJlqLio2oAQY1Ub1yawqO9EUQcmuYXsxgYjFrdklEtlWxoBZgUBPVo5BHw9HeCJyqgnOzaSykeN4/0XqUuntq9UEtBIOaqM60B1040B2GhMTQVJILSonKwJCAYUgoSgX2UTOoierHpiYftrcFCovGppIw+M+fqGzyhoSTQU1Ea6EIYG9HCN1RD+LpPEamuWiMqNzyhoRzlZ9bUlCX2gAnIntxqgJHeiOIeB2YWc5ifD5jdklENckooU9dWlDz+FCimhVwaTjaF4HboeBCLI1YgovGiCpFNwrnk6xmP3XJZ30TUe1pCThxXU8YAgIjU0kks2xzEVWSISs0otZLeGAisoeBRi92tgWQ1yVOTcbBpShElWfI1V/Mseqg5miaqLYIALs7guhr8CKR0TE8xTukiaqllEhlUBPVIYcqcKgnjEafE7F4FudjXDRGVE0VWUzGaW+i2uB3qjjaF4HHqWJsPoO5OO+QJqo2Q1bgPmpuzSKyvya/E4d6wlCEwOnpJBIZNqSJzFCRxWTcmkVkb71RD/Z0BJHXJV6e4KIxIjMZBlZ91SWDmqjGCQA72gLY0ORDKqtjcJKLxojMVpERtWSPmsh2NEXgup4wmv1OzCdyODeXNrskIgJQSqSWtI+aiOzD6ygsGvO5VEwsZjCzxEVjRHbEoCaqQQ1eBw73RqAqAqMzKSyndbNLIqJLlDJHzaAmqjFdYTf2dYVgGBKDk3FkeWQ3ka0xqIlqgFMF9naG0BJwwZArBxRJYEOzz+zSiOhyBJDLG3BoyjU/lUFNZGM7Wv3oiXqgKgpURUA3JH54JoYfnV80uzQiuoq+Ri/evLN1VZ/LoCaymc6QC9vbgnBqApqiIJbI4sHhadw8EIXHoeJ3/ulFzCe5cIzIyo5vbWJQE9WSsFvFns4QAm4NmqIgndPx0FAMJ0bmcHIyjkO9YbxrVyu+cN8QQ5rIBpRVHnYCMKiJLKvYd272u6AoApDAj8eW8ODwHH54bgHZS471/fjRbpyPpfAPT18wsWIiWi1l9Tm9+qAuIfyJaB22t/rRe0nf+cxcEg8OzeGR0zEspV+/hPsXDnQg4Hbgt7/1Ik8QJLIJpYSkXnVQlzJMJ6LSdIZc2NYWhKvYd05m8eDQNE4MxzC2eOXTxLwOBW/d1oxHh+bw2PBcFSsmovVQKzH1rZUyTieiawq5VezpCCHo1qCphb7zw8MxPDQ8h5cm46s6EOG3jvVDVQQ+/93BitdLROVTkRE1g5po/ZwqsLcjhKaAC2qx7zy+hIeG5vDMa/rO19IX9WBnexD/68lzODvHizaI7EStRFCX8qBE9Gqv7TuPziXxwNAcHj0dw+Jl+s6r8VvH+pHI5PHVE6PlLZaIKi7g1qAbclXZyqAmqpDOkAvbWgNwOZSLfeeHhqZxYiSGCwvru8Xq1o1RtIXc+P/+9SSW1xj0RGSegFuDISVUMKiJquq1fedM3sDDwzGcGJ7Di6vsO1+LAuAXr+vC0FQc//LceBkekYiqLehxrPpzS1r1LVDajR9E9UBTgX0dITRf0nf+yfgSHhqew9NnS+s7r8bHjnTD59Jw9z2nwN1YRPYUdGur3k1V0oEnqiK4T5NoxbaVvrNWxr7ztYTcGo5tasD9L07h2bMLFXkOIqq8kMex6pnqkoJaY1BTnXtt33k+mcNDwzM4MTyH8+vsO6/GXcf7AQBf/Pfhij8XEVVOxFeBqW+AW7SoPgVdKvZ2XqbvPBLDS5PLVZt+3triw6YmP/76kVGMV+FNARFVTtC9+vgtKagdqgJAL7UeIttRVWB/R+F+5+LBBD9dOWe7En3n1fiNm/sxn8zifz4yWvXnJqLyCrgrNKJ2reKCayI729riR1/DK33ns7FX+s4LKfO2Qb1tWxMa/U78zrdfQCpnmFYHEZWHz6Wu+nMZ1FT3Olb6zu6VvvNCMocHq9h3vhZNAe7Y34HnLyzi3uenzC6HiNbJ41CgqavP01UHtSElg5pqRtClYk9nECG342Lf+ZGRGE4Mx/BiFfvOq/GrN/TC41Bx9z2nzC6FiMogUMIeaqCUEbXkiJrsTV3Z79x6Sd/5+fElPDgUw9PnFpDJW29KucnvxNG+CP71x+N4cXzZ7HKIqAxKWUgGlBLUgkFN9rSlxY/+V/WdU3hwaBaPmNx3Xo3P3NqPnCHxJ/ePmF0KEZVJKQvJgBJPJnM7GNRkDx1BF7a1BeDWCr2ghVQODw3N4MTIHM7Nm993Xo29nUH0NnjxZ98fwWw8a3Y5RFQmQU+lRtQA3NrqV6kRVVvApWJvZxAhjwOaUug7P3p6HidG5vDChLX6zqvxH2/sxeRiGt948rzZpRBRGVVu6huc+ibrUQWwrzOE1uClfedlPDQ8h6fOWrPvvBo/t6cVYY8D/+3/nETWpt8DEV1ec9CFvG6seuV3iQee8GQysoYtzX70N77Sdz43n8IDQ7N4ZMT6fedrcWkKfnZnK545M48HXp4xuxwiKrPOiKekzy8pqIUQcGmKbUcpZG9tQRd2tL2y33kxVTxnO4az8ymzyyub37i5Fw5NwWfv5XYsolrU3eCtzD7qIp9TZVBT1QScKvZ2vbrv/NjpeTw0bM++87V0hNzY1xXCPz4zhuHphNnlEFEFdEe9JX1+yUHtdaqIJXOlfhnRqqkA9nWF0BJ0XbwG7oWJZTw4VDhnO13DbxTvurUf6ayBv3iA27GIapGmCDT6naV9TSmfbEgJn5Mrv6kytjT70N/ovdh3Pj+fwgNDc3hkJIb5VO2/Oby+L4zOsBuf/+4gFm3eZyeiy2sNuS8ufF2tNU19E5VLa8CJne3Bi/udL/adR2I4G6udvvNqfOxID87NpfCPz4yZXQoRVUipC8mAEoNaEQI+V8nZTvQqfqeKfZ1BhLyFvnM2b+DxM4W+8/M12HdejQ8d7EDAreEz//g88vX4AhDVic6oB1JKCLH6UTVH1FQVKoC9XYX9zqoQEOKVvvNTNd53vhafU8HtW5vx8KlZPD4SM7scIqqgzogbeUOWtN255KB2awqEACTf9NMqbG72YeDSvvNCCg8OzuGR0zEuSlzx6WMDUATwhfsGzS6FiCqsI+KBUsJoGlhDUAsh4HWoSGT1Ur+U6kRrwIkdbcGLd64upXO4b6g++87XMtDgxfa2AP7uiXM4x9eGqOb1NHgv7mZZrTU1nH1OBjW9mt9ZOGc77Cnc75zNG3h8dB4nhmP46fhSXfadV+O3jvVhOZ3DX544Y3YpRFQFHeEKLyYDACklfC4ViJf8XFRjCn3nIFqDbqiKgMBK33l4Dk+N1nffeTXeuLkRLUE3/t/vvIR4hm98iWpdwK3BX+KFHMCaghoIuhwAOE1XrzY1ebGhyXex73xh4ZX9zuw7r44C4IMHO3Bqchnf+dGE2eUQURV0rGFrFrCGoFYUgVCJd2mS/V2u7/y94VmcGJ7DKHurJfuV67vhdWq4+55TbAsQ1Ym17KEG1tijDq1h6E72c2nfWVUE8obEE6PzeIh953UJuzXcvKEB33thCj86t2h2OURUJf1N3pKutyxaU+JqqgKPQ0Eqxx5krVEB7OkMoi30St/5xck4HhyaxZPsO5fFZ44PQErgi/8+ZHYpRFRF29qDJR10UrTmoXHQrSGVy671y8liNjV5MdDog0Mt9J3HFtJ4YGgWD7PvXFbbW/3Y2OTDV06cweRixuxyiKiKdnYGS96aBawxqA0pEXQ7MLXMoLazy/Wd7z9V6DufYd+5In795j7MJbL4m8fOml0KEVVR1OdAo9+1pq9d14ia7MfrVLH/NX3nJ0cX8NDIHH4yxr5zJf3MjmY0+Jz47W+9gDTbRkR1ZWtbcM1fu6a0VYRAmCu/beNVfeeVc7ZfnIzjoaE5PHl2nmsNqkBTgPfubcdPzi/ivhemzC6HiKpsW3tgTQvJgHWMqP0uDQIAB2DWtbHJiw2NPmiqgKYoGF98pe88l2DfuZo+eVMfnJqCu+85ZXYpRGSCtS4kA9YR1IoQCLg1LKV5wb2VtASc2HlJ33k5nS/0nUfmcGaOfWcztPidONwTxr/+aAInJ5bNLoeITLDWhWTAOoJaSomI18GgtgDvyv3OkUv7zmcX8NAw+85WcNfxAeR0iT/9wYjZpRCRCSJeB5oCa1tIBqwnqAFEvQ7ehmQSFcDuziDaV/rOiiLw4so520+Osu9sFQe6QuiJevDH9w9jLs5dEkT1aGt7YF1fv66p7wafc11PTqXb2LhyzraqQFPESt95Do+MzGGWfWfLufOGHkwupPHNJ8+bXQoRmWRbexC6Ias/9Q0AAZcGhyKQ49xqRTX5ndjd/uq+8/cHp3FiOIbTc0mzy6MruGNvG0IeB373X15CTue/EaJ6td2sEXVRxOvANKf0ys7rWOk7e1/pOz91Sd+Zf/etza0peMfOFjw1EsOJU7Nml0NEJtrZGVrzaBpYZ1AbUiLKoC4bFcCujiA6wm4oQkBVBF6aXMaDQ4W+c5J9Z9v41C190BQFn/vuoNmlEJGJwutcSAasM6gFgKjPCSCxriLq3YYGLzY2v9J3nrjYd45hJsE3QXbTHXFjd2cQ//D0BYzM8N8GUT3b1ra+aW9gvUEtBKJex7qLqEdNfid2tQfgdaiFvnMmjx+s9J1H2He2tU8f60cqa+DLD502uxQiMtnu7hDyhgFNKf1EsqJ196gdqoKAS8VyRl/vQ9U8j6Nwznax76yz71xzbuyPoj3kxt33DmIpxTMGiOrd9RsaoK7xRLKidQe1lBJRnxPLGe6nvpK9HQF0hD0X+84nV/rOT7DvXHM+eqQLo7NJfPuHY2aXQkQm87vUdR0dWrT+oEZhGpcHn7zaK33nwjnbk0uFvvPDIzHMcPFdTfrwoU74XRp+856fQueWRaK6d6A3sq7V3kXrDmpFCLSs8Y7NWtPkW+k7u1RoioJ4Jo8fDM7hxMgcRmbZd65lfqeCN25uwoMvz+DpM/Nml0NEFnBkIIqcbsCxhhuzLlWWuyqdmoKQW8NiHZ777VnZ7xy9pO/89NkFPDQcw48vLLLvXCfuOj4AIYA/vG/I7FKIyCKu39iw7pAGyhTUUko0B5x1FdR7OgLovLTvPFXsOy8gmeXCunqyscmLrS0BfP2xs7gwzxYQEQEtQRe6ot6yPFZZghoAmv0uDM3U9vTuQIMXm17Vd85cvN+Zfef69alb+rGYyuEvHx41uxQisogjA1FIKde9kAwoU1CLlQs6FIGau1Kx0efA7vYgvM7Cfud4Jo8HhuZwYngOw+w7173btzShOeDC7/7LS5xJIaKLDg9EoRsSmmqRoAYAVRGIep2YrYGTtDyqwL7uEKJe58W+8zPnFvHQ8Bx+xL4zrVAF8IEDHTg5sYT/+5MJs8shIosQAji6oQFaGfrTQBmD2ljpU9s5qHd3BNB1Sd/55ak4Hhyaw+Oj8xwt0et8/PoeeJ0q/uDfTkHyzRsRrdjY7EfIU75TO8sW1AJAS8CFlybj5XrIquhv8GBTkx8OrdB3nlrO4AeDs3hkJMbLRuiKol4NNw5Ece9PJ/HTC0tml0NEFlKc9i7HHmqgnEEtBEJuDU5VIGvxueHX9p0TmTzuf7mw37nWF8RReXzm1gEYhsSX7h82uxQispjrNzSgPBFdULagLmoLunHWgltUPKrA3u4QGnxOqEJAlxLPnC30nX88toR8ra2Co4rZ1R7AQKMPX37oNKaXMmaXQ0QW4tQU7OsJQynTaBooc1BLAO0hl6WCend7AF2RV/rOp6bieHB4Do+fmUeCfWdag0/e1IvZeAZff+yc2aUQkcXs6QrBqZVnEVlRWYNaEQLNftfFldJm6Yt6sLn51X3nBwYL+53Zd6b1eNeuVkS9Tnz6H55HJs8LVYjo1Y5taUJeN8q24huowNS3ogi0BJwYX6zulGCD14HdHUH4Vs7ZTmTzuP/UHE4MxzA0k6hqLVSbnArw7t2t+NG5Bdz/0rTZ5RCRxSgCePPOlrKGNFCBoDakRHvQXZWgdqvAvu7wq/rOP7y435l9ZyqvT97cB6em4LP3nDK7FCKyoH09YUR8zrI/bvlH1EKgLeiCEKjY3tJd7QF0X9p3nl7Z78y+M1VIW9CJ67rD+Jdnx/GyzbYgElF13LajpezT3kAFghoANFVBk89Z1n7wa/vO08uZlfud5zC1zL4zVdZdtw4gqxv48wdGzC6FiCxIVQRu21H+aW+gQkFtSIm2kHvdQX25vvP3V/rOg+w7U5Uc6gmhO+LBH31vCLFEzuxyiMiCDvSGy3oa2aUqEtSKEOgIufCTsdK/1q0C+7pW+s5Koe/87Erf+Tn2nckEH7++BxfmU/j7py+YXQoRWVSlpr2BCgU1ALg0FQ1eB+aSqxuB7GoPoDvsgaIU+s6Dl/Sd4+w7k0k+sL8dQbcD//nbLyJv8RP3iMgcmiLwpu2VmfYGKhjUhpTojHiuGtR9UTc2NwfYdyZL8joUvG17Mx4fnsMjQ3Nml0NEFnWoP4qAu2JxWrmgVoRAV9iNn44vvWr1d4NXw+6OEHwuDZoikMzq+MGpOTw0PMe+M1nKp471Q1UUfP67g2aXQkQWdtuO5opNewMVDGoAcKgKWvwuxJIZ7O8Ko3Gl72xI4Nnzi3hweA7PnV9k35kspzfiwa72IL751HmcmeVFLUR0eQ5V4A3bmisW0kCFg9qQEtf1hAAU+s5DMwk8MDjLvjNZ3qdv7Ucik8dXHjpjdilEZGFHBxrgc1U0Sisb1IoQgBD4zvOT+PeXZzG5zJuGyPpu3hBFW8iN3/+/L2M5nTe7HCKysNt2VnbaGwAq98grpJQYW0gzpMk2PnKoC8PTcfzTs2vYX0hEdcOlKTi+tbLT3kBVgho4vqmx0k9DVBYfPdwFn0vDZ+8ZBJdOENHV3LSpEW6HWvHnqXhQK4rA5hY/WgLlP6icqJxCbg1v2NyI7780jWdG580uh4gs7o5DnVW50rniQQ0AuiFxbENDNZ6KaM0+fWs/AOCL3xsyuRIisrq+Ri8O9EagKqLiz1WVoFYVgTduaYJa+e+HaE22NPuwudmPv3nsLMYW0maXQ0QW996DncjrRlWeqypBDQBhjwMHusPVejqikvzGLX1YTObw14+cNbsUIrI4j1PFO/e1VXwRWVHVglo3JN6yrblaT0e0am/Z1oQmvwt/9L0hpLi/n4iu4S07W+CpwiKyoqoFtaoI7GgLoCPkqtZTEl2TpgDv39+BF8eWcM/zk2aXQ0Q28POHul51NHalVS2ogcKo+k1bmqr5lERXdecNvfA4VNx9z6mq/sMjInva1RnExhY/lCosIiuqalCrisDxTY1waVV9WqLLavQ5cbQvgn/7yQSeH1syuxwisoH3XVe9RWRFVU9Mt6bghv5ItZ+W6HU+c7wfuiHxJ/ePmF0KEdlAxOvAbTsqd+/0lVQ9qCWAt25rqfbTEr3KnvYA+hq8+OqJM5jm8bZEtArv3NdeuMOiyqoe1IoQ6Il6sLHJV+2nJrroP97Ui+mlDP7uifNml0JENqAI4I7rOlHF1vQrz139pywsKnvbdm7VInO8Z08rIl4nPv/dQWTz1e01EZE9Xb+hAa0hN0Q9jKiBwqKyo30Rnv9NVedUgHftbMWzo/P4wckZs8shIpu441BX1ReRFZm2/FpK4O072Kum6vr1W/rh0BR89t5Bs0shIpvoinpwdEO06ovIikwLalUReMOmRgTdmlklUJ3pCLlwoDuEb/9wDINTcbPLISKb+MiNvTBMvPfW1A3NihB4K48VpSr59K39yOQM/MUDp80uhYhsoiPsxjv2VO9c78sxNahVpRDUbh6AQhV2pDeMrrAH/+OB05hP5swuh4hs4sM39kKafGyh6Qnpcih44+ZGs8ugGvcrR7txLpbCPzx9wexSiMgmWkMuvHOvuaNpwAJBLQD8zM5WaGZsTqO68MEDHQi4HfjsvaeQN7HPRET28ks39BZCymTmB7UQiHgduHEganYpVIN8DgVv3taMRwZn8fhwzOxyiMgmmgMuvHt/OzTF9Jg0P6gBwJAS797dasqJL1TbPnVrP1RF4Av3cTsWEa3eL97QY8rhJpdjiaBWhEBb0I0b+zmqpvLpb/BgZ1sQ/+vJczg7lzK7HCKyiUa/Ez93oMMyLVlLBDVQGFX//H7rvDBkf791rB/xdB5fPTFqdilEZCO/eH0PVAtlkWWCWhECjT4Hbt3YYHYpVANu3diA1qAbf/z9YSyn82aXQ0Q2EfU58b7rOhnUVyIBvG9fO5yqdV4gsh8FwC8d6sTQVBz/57lxs8shIhv54NFuS4U0YLGgVoRAyK3hti1NZpdCNvaxo93wOjX8wT2nwN1YRLRaEa8D7z9krdE0YLGgLnrPnjaeVkZrEnJrOLaxAfe/OIXnzi6YXQ4R2cgvHOk2/XCTy7FcRUIIeJ0q76umNfnM8QFICXzx34fNLoWIbCTqc+AXjnRZbjQNWDCogcIU+M/uaoXfqZpdCtnItlYfNjb58LVHz2J8IW12OURkI5841m/J0TRg0aAGAIeq4J27Ws0ug2zk12/ux3wyi689Omp2KURkIwNNPrzHQvumX8uyQa0qAm/f3oyWgNPsUsgG3ra9GY0+J/7wviGkcobZ5RCRjXz69o2m3jd9LZYNaqDQr/7QwU6zyyCL0xTgjn3teP7CIr77/JTZ5RCRjRzdEMXRDQ2WnfYGLB7UqiJwqDeCHW0Bs0shC/uPN/bC41Bx9z2nzC6FiGxEVQR++82boFt4NA1YPKgBQDckPnq4ixd20GU1+Z040hvBd340jhfHl80uh4hs5F372tHT4LXkSu9LWT6oVUWgK+LBGzY1ml0KWdBnjvcjp0v86fdHzC6FiGwk4Nbwa28YMLuMVbF8UAOAlBK/cKADPm7Xokvs7wqiN+rFV06cwWw8a3Y5RGQjv3prP3wuzTJXWV6NLYJaCAG3Q8V797aZXQpZyK/e0IvJxTS+8cQ5s0shIhvZ1OK33MUbV2OLoAYKU+Bv2dqMjpDb7FLIAt67tw0hjwOf/+4gcrq1F4IQkbX8l7dttvR2rNeyTVADhdu1Pnqky+wyyGQuTcE7d7bg6TMxPPjyrNnlEJGNvHlnC/Z0hy29Heu17FMpCqPqXe1B3NgfNbsUMtFv3tIHh6rgc/cOml0KEdmI16niM7dvgiHtM5oGbBbUAGBIiY8e6ULAxYVl9agz5MbeziD+8ekLGJ5OmF0OEdnIL9/ch5DXAcUGC8guZbugVoSAx6Hilw5xCrwe3XW8H+msgb948LTZpRCRjWxvD+BD13fbZgHZpWwX1EBhCvzmDQ3Y3c4Ty+rJ9X0RdITc+PMHRrCYyptdDhHZhFNT8Afv3m6rBWSXsmVQA4UTy+68oRcuzbbfApXol4904+xcEt96ZszsUojIRj5+Sx+6o15bLSC7lD2rRmFUHfU58D7ura4Lv3hdJ/xuDXffM4i8Td8VE1H17egI4pdu6IFiwynvItsGNVDoV799Rwv6Gjxml0IV5HMquG1LE06cmsGTp2Nml0NENlGc8pY2W+X9WrYOagCQsnB7ko3fLNE13HXrABQB/OF9Q2aXQkQ2cuexPnRFPFAVe0edvatHYQq8J+LBz+5qNbsUqoANjV5saw3g7544j3OxlNnlEJFN7OwM4kPX23vKu8j2QQ0UzgJ/3952DDR4zS6FyuxTt/RhOZ3DXz58xuxSiMgmnJqC//4u+095F9VEUBf95rE+OFX7v3uigjdubkRL0I0v/fswEhnd7HKIyCbuPNZfE1PeRbXxXaAwBd7id+FD13WaXQqVgQLggwc78PLEMr7z4wmzyyEimyhMeXfXxJR3Uc0ENQAoisDtW5uxtzNodim0Tr9yfQ+8Tg2fvfcUamT2iogqzKUp+IMamvIuqqmgBgDDkPjkTb08C9zGol4NN2+I4r7np/Cjc4tml0NENnHnrf3orKEp76La+m5QGFX7nRruvKHX7FJoje66dQBSAl+6n9uxiGh19naH8cGjtTXlXVRzQQ0U+tXX9YRx68YGs0uhEu1sDWBDow9/9cgoJhczZpdDRDYQ9TnxxfftrNk2WU0GNQBIKfHRI91oC7rMLoVK8Gs392I2kcXXHztrdilEZAOKAL7w3h0IejRb3oy1GjUb1EIIaIrAZ44PcMuWTfzMzhZEfU780X1DSOcMs8shIhu489Z+7O8J2/bCjdWo3e8MhSnwzpAbHzvSbXYpdA2aArx3Txt+cn4R970wZXY5RGQDN25swMdu6oMQtT0Yq+mgBgqLy27d1Ijj7Fdb2q/d1AenpuDue06ZXQoR2UB72I3PvmeHbe+YLkXNBzVQ6Ff/8tFu9EZ5y5YVtQScONQTxv95bhwnJ5bNLoeILM6pKfjSHbvgdig1ucr7teoiqIUQEELgP71hAF4n91dbzWeODyCnS/zZD06bXQoR2cBdt2/EphZ/TfelL1Uf3yUK/eqo14lfu6nX7FLoEge7QuiOePDlh04jlsiaXQ4RWdxbd7XivQc762IkXVQ3QQ0Uwvpgdxjv2NFidim04hM39GBiIY1vPnne7FKIyOI2NPvwe+/YUnNHhF5LXQV10X842IFtrX6zy6h7d+xrQ8jjwOfuHUROr69/eERUGq9TxZfu2AVVETW/yvu16jKopQR++/gAmv1Os0upW25NwTt2tODJkRhODM6aXQ4RWdx/+5mt6Ih46qYvfan6+45RmAL3OFT8lzdtgFury5fAdJ861gdNUfC57w6aXQoRWdwHDnfhTTtaavbksWup25RSFYG2oBu/cUsf6vNHb57uiBt7OkL4h6cv4PRMwuxyiMjCbt7ciE/fvtHsMkxVt0ENFML6QFcI79/fbnYpdeXTx/qRzOr48kPcjkVEV7ajI4g/fO9Os8swXV0HNVDYY/2u3W04toEnl1XDzQNRtIfc+NPvD2MplTe7HCKyqM6IB3/xC3ugKgJKnS0ee626D2qgcHLZJ27owXauBK+4Dx/uwpnZJP7p2XGzSyEiiwp7HfjKB/fC51Lrti99KQY1Vk4uA/Cf3rAB7bwWs2I+crgTfpeGu+85Bb0OzuclotK5NAV/9v7daA276nKF9+XwVVihKAIuTcHv3rYRQbdmdjk1J+BS8YZNTXjg5DSePjNvdjlEZEGKAP7g3duxvSMITWE8FfGVuISqCDT4nPi92zbC4+BLU0533ToAIYA//N6Q2aUQkUV96raNOL61idPdr8E0eg1VEeiKePA7b9gAh8pflnLY2OTFlhY//vbxcxibT5tdDhFZ0AcOd+E/HOmuu1PHVoNBfRmqIrC11Y/fvLkPfGO3fp+6pR+LqRz+6uFRs0shIgs6vrUJd9X5XumrYVBfgSIErusJ45ePdptdiq3dvqUJzQEXvvi9ISSzutnlEJHF7O4K4bPv2YE6u2ejJAzqqxBC4I2bm/Dz+3ggylpoCvALBzrw0vgS/u2nk2aXQ0QW09PgwZ9/YHdhrzSnL6+IQb0K79nThrduaza7DNv5+PU98DhV3H3PKb5bJqJXaQu58dUP7YPXyb3S18KgXqUPH+7CTQNRs8uwjQavhhv6o7j3p5P46YUls8shIgtpC7nxtY/sR6Pfyb3Sq8BXaJWklPjkjb043Bs2uxRbuOv4BhiGxJfuHza7FCKykGJINzGkV42v0ioJIQAB/NYt/Qzra9jVHsBAgxd/+fAoppcyZpdDRBbBkF4bvlIlUBjWq/LJm3oxE8/gbx8/Z3YpRGQRDOm146tVIob11b1rVyuiXie+8N0hZPKG2eUQkQUwpNeHr9gaMKwvz6kA797dih+dXcD9L02bXQ4RWQBDev34qq0Rw/r1fu2WPjg1BXffe8rsUojIAhjS5cFXbh0Y1q9oCzpxsCuMf352HKcm42aXQ0QmY0iXD1+9dbo0rG/sr9991nfdOoBM3sCf/2DE7FKIyGQM6fLiK1gGihAQAviNW/rq8gSzwz1hdEc8+PKDpzGfzJldDhGZqDXkYkiXGV/FMilezfbhw111dzb4r1zfjQvzKfz90xfMLoWITLSh2YdvfOwgQ7rM+EpWwHv2tOFXjnbXxRWZHzjQgaDbgc/eO4i8zgO9ierVdX0R/N3HDiDidTCky4yvZoW8cXMjPn2sHw61dtPa61Dwtm3NeGxoDo8OzZldDhGZ5G27WvHl/7AHLk1lSFcAX9EKEULgYE8Yv/umjfA4avNl/tSxfqiKwOfvGzS7FCIyyUdv6sV/f/d2qIrgLVgVUpsJYhGKENjS4sfvv2Uzgm7N7HLKqjfqwa72IL751HmMzibNLoeIqkxTBH7vHVvwyeMDAF5Zp0Plx6CuMFUR6Ip48Lm3b0FHyGV2OWXz6Vv7kcjk8ZWHzphdChFVmdep4s8+sBvvrLOFs2ZhUFeBqgg0+Jz43Du2Yld7wOxy1u2WDVG0Bd34k++PYDmdN7scIqqiRr8TX//IfhzqjxbOkaCKY1BXiaoIuFQFv/umjbhtS5PZ5ayZAPDhQ10Yno7jn58dM7scIqqi/iYfvvkrB9Hf5GM/uooY1FWkKAKKIvDLR7vxkcNdtty+9dEjXfC5NNx9zykY3I1FVDf294TxjY8dQIOPe6Srja+2Sd68tQn/9U0b4LXRivCQW8PxTY34/kvT+OHogtnlEFGV3L6jBV/90F64Hdx+ZQa+4iYRQmBHWxCfe8dWtAScZpezKnfd2g8A+OL3hkyuhIiqQVUEPnl8AJ/7uR1QuP3KNAxqE6mKQEvAhS+8Yyu2tfrNLueqtjT7sLnZj689ehZjC2mzyyGiCov6nPjqh/biIzf2AAAXjplISCnZaTSZbkgIAXzjmTF854Ups8u5rK+8dycEgLf+yeNIZXWzyyGiCtrbHcYX37cTQY/GqW4L4E/AAlRFQBECH7yuE799fABep2p2Sa/y1m1NaPQ78UffG2JIE9W4Dx7txl//0j6EeGa3ZXBEbTG6IRFLZvG574/gTCxldjnQFOBv3r8Hp2cS+MBfPgP+thDVJr9Lxe+/azuO2Xj7aK3i2yWLURWBqNeJz759C45vbDC7HNx5Qy88ThV333OKIU1Uoza3+vGtOw/hpk2NZpdCl8GgtqDi4fZ33tiLX72hB06TbuBq9DlxtC+C//vjCTw/tmRKDURUWe/c24ZvfOwgmoNuruq2qNq6KaKGFA+4v2VDAzY0+fD5H4xgYilT1Ro+c7wfuiHxJ98frurzElHluTQF//mtm/HOfe2QUvJSDQvjiNriFEWgI+TGH71zW1Wnwvd2BNDX4MVXTpzBzHK2as9LRJXXFfXgm798EG/f0waAN19ZHReT2UTxHe/TZxfw5cfOYqnCl2H81R27kM7peMefPoFs3qjocxFR9dy+owW/9zNb4FQVruq2Cf6UbKL4jnd/Vwh/8q5t2NcZrNhz/dyeVkS8Dnzhu4MMaaIaEfU58cU7duJzP7cDbo1HgdoJR9Q2ZBgSiiJw38lpfP3pC8jq5fsRujQFX/v5XXh+bAkf+dpzZXtcIjLPbdub8V/fvgVeJwPajriYzIaUlZWZb9rchN0dQXzpwTMYmUuW5bF//eZeODQFn713sCyPR0Tmifoc+C9v24I3bGu++Aaf7IdvrWxMUQSa/S7c/fYtePfu1nVfm9kRcmF/ZwjffmYMQ1Px8hRJRKZ40/ZmfOeTR3DL5sLeaIa0fXHqu0ZIKXF2PoX/8chZnF7j6PqPf3Ybol4H3vLHj2MhmStzhURUDRGvA//17SujaCl5mUYN4Ii6Rggh0BX24HPv2IIPHuyASyvtR3u0L4zOsBt//sBphjSRTb1xWzP+9deO4JYtK6NohnRN4Ii6BhlSIpbI4S8eHcVPxpdX9TV/8/7diCWyeNefP4m8wV8JIjuJeB34z2/djDftaOEougYxqGuUbkioisDDw3P4n0+dx3LmyrdeffBgB35mZys+8bc/wuMjsSpWSUTrdXxrE37vHVvhc6vQFE6S1iKu+q5RxTN7r++PYn9XCH/95HmcuEwI+5wK3ry1GY8MzjKkiWykM+LBf3rLJty4qZErumscR9R1oDgV9vz4Ev7yiXMYW3zlzPD/57YN2N4awLv+x5M4O2f+tZpEdHUeh4IP39iLX7qhBwLgvug6wBF1HSj2q7a1BvCln92Of3txCt/68QTagi7saAviG0+cY0gT2cAbtzXjt9+yCQ0+J0fQdYQj6jpkGBLxbB6GAQgAb/njxxC/Sg+biMw10OTD77x1Mw72RTjNXYc4oq5DiiLgd2kwDInJpQw2tQbw3NkFs8sioteIeB34+LF+/NyBDhTHVAzp+sMRdZ3TDQOqouAHJ6fxpX8fxvkYp8CJzOZQBd5/uAsfv6UPLk29uDiU6hODmgAAeb1wS9Y3nzqPr54YxXKFr9Ekost747Zm/NbtG9ESdHE/NAFgUNNr6IZEMqvjLx4YwbefHec1l0RVsqsziE/fvgm7u0LsQ9OrMKjpdYq/EnOJLP7q4VH887PjyDCwiSpib3cInzjWj0P9UeQNg4eW0OswqOmKpJSQABaSOfz1I6P49g/HkM4xsInK4UBvGJ841o8DvREGNF0Vg5quqRjYS6k8/uejo/jHZ8aQynI7F9FaHOqP4M5j/djTHUZeN3hgCV0Tg5pWrRjY8XQeX3v0LP730xeQZGATrcrRgSg+cWs/dnWGGNBUEgY1rYlhSCSyOr7+2Fn8/VPneWAK0RXcuLEBd97aj23tQU5x05owqGldDEMildPx9cfP4ZtPnue2LqIVt2xuxJ239mNza+DibXZEa8GgprLQDYlMXsc3n7yAb/3wAiYvufiDqF44VIE3bmvGR27sxYYWPwOayoJBTWWlGxJCAA+fmsX/fvoCnjwdA3/DqNa1h914z4EOvOdAB0IeBwOayopBTRVRXCwzNp/C3z91Ht/58QSWUpwWp9ohBHB0oAE/f6gT129sgJRgOFNFMKipogwpAQnkDYnvPj+Jf3j6Al4cXza7LKI1C3sdeOfeNtxxqAttITdXcFPFMaipaop/0E5OLOHvn7yA+16Y4olnZBs7O4O447pO3LajBaoQEAIQPIubqoBBTVWnGxKKABIZHf/83Bi+9cwYzvHWLrIgj0PB7Ttb8f5DndjUGuDomUzBoCZTFfeVPnU6hn/7ySQefHmGW7zIVEIAe7vDuG1HC96+uxVepwopeQ80mYdBTZZQHGXnDYknhufw3eencGJwFgkepEJVIASwqzOE23a04M07WxD1OTl6JstgUJPlFP9A5nQDjwzO4r7np/Dw4CxSvBCEymx7ewC37WjBW3a1oingYjiTJTGoydKKfzgzOR0nTs3ivhem8OjQHBeh0ZptbvUXwnlnC9rCHoYzWR6Dmmyj+Ac1ndPxwMkZ3PfCFB4fnkNO568wXd2GZt9KOLeiM+rhmdtkKwxqsqViaCcyeTw8OIsnR2J4YiSGqSUeXUqA26FgX3cYhweiuHlzI3obfRfXQXBLFdkNg5psL68bUBUBIQQuxFJ4dGgWT56O4Zkz87zVq04oAtjaFsChgSiu39CA3V0hOFSF09pUExjUVHNyugGHqkA3JF4aX8Ljw4XR9vNji8hzmrxmdEY8ODwQxZGBKA73R+F3a4Wz5sGtVFRbGNRU0wwpYRjyYm/7mTPzeHwkhqdGYhiZSZhdHpUg5NFwXV8UhweiuGFjA1pD7lf9fIlqFYOa6sqlI65YPIvnzi3gxfElnBxfxkvjS1jkxSGWoKkCG5r92NYewLa2AHZ3hbChxQ9FiIszJkT1gkFNdU03DADi4q1H00sZPH9h8ZXwnljGQjJnbpE1zqEKbGzxY1t7EFvbAtjVGUR/kw+aqkBKibwhGcxU1xjURK+hGxISgLYS3jPLGTx/YQkvjS/hpfFlnJxYQizB8F4Lp6ZgY7OvEMrtAezqDKGv0QtNVWBICZ2hTPQ6DGqiVSiEt7y493Z2OYOh6QQuxJK4MJ/Chfk0LsynMDafqvuzyjVVoD3kRmfEg46oBx1hDzqjHvQ3+tDb6IWqCI6UiUrAoCZao2LYKOKVqXMASGTyGJtPYXQuibGVEC98TGFiMV0TK8+jPic6IoUwLv7X3eBFV9SDBr8Tyspe5eIoWRWCK7GJ1ohBTVQhuiFhSAltZY83ABiGxGw8i6mlNOaTOSylclhK5bGULnxcTucL/9slH5dTuYqdc64pAgG3hqBHQ9DtQGDlY9CjIehxIOjWVv5/B8JeBxr9TrSF3HA51IuPkdcNSICjY6IKYVATmURKCV0WPgJ43cj8UnndQCKjYzlTCO68IVfeCBTeEOiGhL6yVUmicACIqhQerziaVVce3+tUEfBo8Ls0uC8J3EsVtz1JCWDlsRSe6EVkCgY1ERGRhXGuioiIyMIY1ERERBbGoCYiIrIwBjUREZGFMaiJiIgsjEFNRERkYQxqIiIiC2NQExERWRiDmoiIyML+f/4JQR/9HYcTAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.style.use('_mpl-gallery-nogrid')\n",
    "np.random.seed(10)\n",
    "\n",
    "# make data\n",
    "x =  np.random.randint(0,5,5)\n",
    "colors = plt.get_cmap('Blues')(np.linspace(0.2, 0.7, len(x)))\n",
    "\n",
    "# plot\n",
    "fig, ax = plt.subplots()\n",
    "ax.pie(x, colors=colors, radius=3, center=(4, 4),\n",
    "       wedgeprops={\"linewidth\": 1, \"edgecolor\": \"white\"}, frame=False)\n",
    "\n",
    "ax.xaxis.set_ticks_position('none')  # oculta los ticks del eje x\n",
    "ax.yaxis.set_ticks_position('none')  # oculta los ticks del eje y\n",
    "ax.xaxis.set_ticklabels([])  # oculta las etiquetas del eje x\n",
    "ax.yaxis.set_ticklabels([])  # oculta las etiquetas del eje y\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  },
  "vscode": {
   "interpreter": {
    "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}