Example2_ProfileAlongLines.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### General Info: This is Notebook for analysing multilayer  tiff exports created with  FLIM-GUIs of SymPhoTime 64 software.\n",
    "\n",
    "Feature List: \n",
    "              -Low and High Intensity Threshod \n",
    "             - Lifetime values along profile lines.\n",
    "              -Autosaving of all plots created as pdf and all ROI masks as ASCII. \n",
    "              -Saving of all layers in tiff as individual ASCCI files."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Before you start:\n",
    "    - Open a  Terminal Window under Jupyter Noebooks and install the following packages :\n",
    "\n",
    "#conda install -c conda-forge pims\n",
    "\n",
    "#conda install -c conda-forge numpy\n",
    "\n",
    "#conda install -c conda-forge matplotlib\n",
    "\n",
    "#conda install -c conda-forge scikit-image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "################################IMPORT NECESSARY PACKAGES################\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pims\n",
    "import skimage\n",
    "import os\n",
    "import datetime\n",
    "#########################################################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load the an EXAMPLE.tiff\n",
    "The tiff file should be in the same directory as the  ROI_Selection_notebook.\n",
    "The number of frames depends on what exactly the image is formed of. \n",
    "If the exported image is a fastFLIM images the tiff file will contain 2 frames: --intensity --average lifetime (unfitted, this is the average photon arrival time) After a \"FLIM FIT \" is performed in SymPhoTime the two frames can be --intensity --average lifetime (intensity weighted average lifetime )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frames:  2\n"
     ]
    }
   ],
   "source": [
    "#load image ->transforms  frame objects into arrays\n",
    "######Image name without the .tiff extension\n",
    "imageName='daisy'\n",
    "###############################################\n",
    "v = pims.TiffStack(imageName +'.tiff')\n",
    "print('frames: ',len(v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Frame objects returned by PIMS are a subclass of numpy.ndarray, adding two new attributes:\n",
    "#frame_no, an integer\n",
    "#metadata, a dictionary\n",
    "intensity=v[0]\n",
    "lifetime=v[1]\n",
    "####################\n",
    "im_size=lifetime.shape # tuple    \n",
    "im_intensity=np.zeros(im_size)  # initilise the intensity image array\n",
    "im_lifetime=np.zeros(im_size)    #  initilise the lifetime image array\n",
    "lifetime2=1E+9*lifetime # lifetime image values given in ns\n",
    "for i in range(1,im_size[1]):\n",
    "    im_intensity[i,:] = intensity[i,:]\n",
    "for j in range(1,im_size[0]):  \n",
    "    im_lifetime[j,:] = lifetime2[j,:]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### A BASE NAME  TO BE USED FOR ALL EXPORTS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "###### A BASE NAME  TO BE USED FOR ALL EXPORTS ##############################\n",
    "basename='DAISY_POLLEN_'\n",
    "###### in Directory  \n",
    "#### \n",
    "DirNAME= datetime.datetime.now().strftime(\"%Y%m%d-%H_%M\")\n",
    "InitDir = os.getcwd()\n",
    "try:\n",
    "    os.mkdir(imageName + str(DirNAME))\n",
    "except:\n",
    "    pass\n",
    "\n",
    "os.chdir(imageName + str(DirNAME))\n",
    "#############\n",
    "#####os.chdir(path)   \n",
    "############################################\n",
    "\n",
    "######Save Intensity and Lifetime image as seperate .dat files \n",
    "IntenNAME =  basename + '_PhCounts.dat'\n",
    "LifetimeNAME = basename + 'AvIntenLifetime.dat'\n",
    "np.savetxt(IntenNAME, im_intensity, fmt=\"%12.6G\")\n",
    "np.savetxt(LifetimeNAME, im_lifetime, fmt=\"%12.6G\")\n",
    "#########################################################\n",
    "TotalPixels=im_lifetime.size                     # TOTAL PIXELS IN THE IMAGE\n",
    "#######################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YBn86BTaeC1mz6B+HtBb4n0y4MAIUXQ8tNbqm0TsL6h/Qs9LVoTs/+90A0XeBGASBliqonwNNV0JwKNiuJ/Pi6RB6Hla/BLmbEMeMg/Cb+rgefJCAL0CJ55F2hx5YF+iUnLQtn1EfCLAloBNL9ISRcO8gwMXyS94B9xo917l7IidfPJ1wLqy7/jwG3dq6nzToMjkBBIbdyJoZg3Tn7ssbKZna/nW0OW7tiC4l6hxO9LQAnW1HAV2xoNrz2d8DLBRCXIleZuLi5HeL0bN1b0ZPfvrzzk6gJje3220QTDQaxel04nK5DHIIBoPk5OQYVo1yZTmdTqLRKA6HA4fDQSwWMybocDhsWFhutxuv12uQX1qabtfm5eXR0tKC0+kkKyuL6urqViSpLCiF1MldtakxAcbxirBgP3nEYjHsdjtVVVVkZ2cTDodpbm42rB9FOj6fj7S0tFZuRsAgZdWnzWYjkUgghDBclS0tLVRUVBAOhxFC0NTU9DV3oSKU1L+F+dV8vanvzce3dVxbnzv6H+jKPt8iC+qwP1fkAos3w4TBes7uCf1gGTB/AixLwBkOsI1AfgaB0+HBOnhxFzqx5aLnMBl4ux75qgI2ueGcqE5W618F93gQ83T/UNZNQDNEx0NzNQ1PjYSsT0HUQe1E8J3DnjNmUnjfYrTjoVEbRGkggBbTCLi6Tg5mBIr2ixiLNY2yQIBABCgChxs2MJ1jN4N9ym/Z3ghbtgVgDpQa66x11AcO/Pwjj0EnZ6DU/vXjtUEagfK2+w0cxPkASqZplM4/uGM7hI2uWVBHAZ0SVAc+e9B/n6TuL4FrD3ggSWvH7XYbE59y+Sm3nM/nI5FI4HLpqnxFZqFQCACXy2VYJMpyCoVCOBwOMjIyDJehskAUUeTm5hoTuLLK7Ha7EQ8yWxWpk7t5klYkpWJNZmtKEYzdbsflcuFyuYjFYoRCIWw2G2lpacb41LU5nU7cbrcxzkQiYVhQ6r7E43FjHGqsLS0thpUZDAax2Wyt4lmp13IgSHXzma2mtvrrynkOZCzfFoI6Is+VT8KVg2HuSni2F1weguLBeoKnH8Ug82MgiBgO8lKoeAbdc1cMrEHP4rgy+RoHPo/qrr44+mqxDcvB8yokZoG4XSc2O8mIux/G1OhaR9uZ/P7imRT+ZSiM/QTCA7FtBfZx0OSUirKUST8RCJAA1tfBsWjU/+Q8UnjpkLBsN/D6R0yY8he0jR+S+VN4v3T/GNojp0PBYSEn+GYT1JFAS0sLoVDIsIjUJJ1IJHC73YbbS0ppxFfUZG6OD0UiEZqbm2lsbKSxsZFIJGK4tpT1kZGRYfSlxArxeJzc3FwSiQQ+n4/MzEzi8bhBCIoAU115sN+iMFtMql2RrCIodS1Op66ZCYfDJBIJ0tPTcblceL1eYrEY0WjUuH7QXZzqHiiXI0AsFmt1LhXLUi5FNU4lBDHHqtSrQlvWlLm9PSLq6DvzPTOjM6urI3xTXHg9AlEBc7cB/aA+T185FQL6fwAt2yDrdsiGpX2BS8HdDKE4eN9FJ6AX0F07jfD778F96++F/BtYmgkn1QGuV/X0xbYMvRxnLhDw0/+nNex42gcra/TUyeuWc98/gZ9vonbvZbgbwfvvjwiMODK3Ie9D+Mo3p1v7POlzYNw03qqE8h0BKO3W7o8slIvvECGEeAY4D9grpRzZzj6TgAeTZ62WUn63oz57xPosRUxKCBEOh7Hb7bjdboBWk6wSSTQ3NxONRhFC4HK5CIVCRCIRamtrDeKKRCIGOUWjUYLBIKFQiFAoZFgidXV1eDwepJT4fD7cbjcZGRmGiELFflLjM6luPkVObe2nNpfLhcfjMfpWUBaSclGqPhOJhHENKjan7oEiL+XWA4zxmgkqHo8Ti8Va7W8eW6qbrr0YkllM0VZ8KvV96rFmtNVPV9FW3Ct1s5BERRyIwEV5umXzqwT0fw/CQ2DDNPDBjuNgzHYgD77yQdCPXiu6GRgAHKO/v++le6H2Bnh7Kic1owduSpKv4Rug5gHYNAuy/sCOlx4F7w5YVQ6flcNJNeCES4CcD58nkg1y2cQjdhtu+A6McXZv3EcKCNQFdHI6yphecojXpkQSnW2dYz56QuU2IfS6do8BP5BSjmC/+7pd9AiCAkhPTzcsCZ/Ph8fjwePxkJaWZriu0tLSDFdZIpEwJvNEIoHNZmPfvn1UV1ezc+dO7HY7fr+fjIwMevXqZbx3Op2GoMDhcJCXl2dMyirupawec1ypLbdWe1BE4XQ6ycjIwO/3k5eXh8/nM9yTZhegavf5fIYVpVyZ5viVsp7MSkWzSzAejxOPx4lGo4awIxQKEQ6HDZdfW+TSlvBBob34kxltWU7tkZgZqVZoZ1DCk2+DSOKIYADw1Ll6tKsZWPghEIQRE2HEQj46EXpvg/hg4Ga4Jw2aHOiWUAs6+WwFqqZCbI3u+nMNh0WPwkdu2Ag44erLgLzfAuOg6AZIrAbbLJ3oMhtg/f1Q/RwvbgO54af435/H649B2hEQC/iGaWQCqzqqe32AGKNpCPUv3Q3qPY3992HUQdyTh0oPkSS7SSQhpfw3UNPBLv8PeFVKuT25/94O9gV6EEEpklHqupaWFkPpFovFiEQiRsxFTcKA8V4IQW1tLTU1NSQSCRobG0kkEmRnZ5OdnW30qawYZWWo8zgcDnw+nyFhV5O5IjMzUidtsyWirCOfz2eIHDIzMw2SM7veQLeevF4veXl55ObmGtabcnUqF6bZtZe6ZkuRUzQaNSwtRU5KUJI6bujYtXYg37VFTh259trq70BIyrKgugj7JpgE5OwF9yBIlMLk3/JsCcSHzuTUZB4KL8B18McGSAj2T0brx+kCCRmE5gV6jKluDoRegDOisNsNTfOZ92c37PoRxJ7Q93GMBtftULAbTjwemq6H4ZchXwVx3EuMmuJlHhBpQyzg6GbSGvYZzHq6PyXvdF+fqwIBAmnJsc+fD4CmRVvto63T0FZ1Lf9CgP33YU3KPXld+/DgB9pVqBjUoVtQnWEIkCOE+EAIUSqEuKwrQzvqUJOKUuOZFXTK3acmH6XSU64tpfILhUIEg8FWk7eyVpSCz+VytRILKJeZcvGpNrUpokh11akxq/fKYlJQn10ul0GMCkrlp65TWUlZWVnY7XaD1BSZmcUaZkWgsgTV9SoiUuuczIuVU92RXZnE27OA2nJztkV87cWz2sOBiCQsguoaRmYCTnjo8pN00jn3ST7KgstOBsdGIB1WvXQzenpdKNgBl6dD/2wYMQA45wt9DVR0OSMuQ49fnRmFzI9gCeAcAQ2zIPtJGPIqnPyObn3lXQsNE2HCRPgEvW0XiDMhcMnFrPnXz3jrc30NUyoSB6lwawv5mgYnwLNX7kBUTe22fttCIOA23pdM0wiMCBAY01Z90QPDDwMdhmi6B10nqE6TMHcCB7pj+FzgTGCWEGJIZ0M76lATcDgcJhKJYLfb2bdvn6FGCwaDrUjJ6/Ua8Sk1ycdiMVwuF5mZmXg8HrxeL4lEgmAwaFhdSqFXX19v9Amwb98+Kisrqa6uJh6PEwwGDetJWVBmAlJEYVbrge4yTEtLw+12k5mZSUZGhhF7UjE2RSRmkuzbty+5ublkZ2eTn59vWFzKfalgVgiqWF00GjVceErYYZ6szSQKHROL+fo6azO759py1R0OorBcfAcG2wqo8cFvRkHlBSCnQZ4Tti+FtZdAy2uQcccdxL6COyZD6RB4exfs2AXrlgCLx8F4IHsH656fCjVu+OwhqB8HxwHHfgEZO7j64ml6Occv7oelQ2E3nH35R/AR8B101V8j9B8B2sJ7ka9AsJcu7/YcRjffsQngtR9x+fxx4Bp12M6TikvX7H+vrfj+ETvvQcOG7s7tbEsmYTZt8w7wTDuBt6WUQSllNfBvoEPna48gKCGEsag0kUiwb98+Y2KPxWJG7Emp6szuuVAoRENDg0FcSlwRjUZpamoyYkvKslAZKFwuF1JKg/gUIUQiEYLBoNG/Ik+zS01N9maBhFnkoAhUCGEQqZnM1LoulQlCLR5WFpeKxUkpDcVfquWlXHrmWJSymswuvbZiSB1ZG+1ZP6ltXbWQuhLDOhBYFlTX4cyGSB7QpK+xjb0Gx02FJvSwg+0GWCghvQKuqoOTGiCzDn3aGAR4ztVl4v2BPgugXxTwgW8qbBoH1fOgDub9ZSgsfgCad0H6DSB/xFtvJk/ySXIwLU+zOAzUXsjme8G3/HEAwt1oMX0Nzw0F10+g5iXY8eODiu8cCLQNdwHwe7Pc/Ph/Hnx/aUdoQa9At2062w4dbwAThRAOIYQXPRv/ho4O6BEEpVx3oVDIiCcpsjBnlFDWlcvlMtY/7dq1iz179hAOh/F4PLhcLkOt19TURENDAzU1NUQiERoaGoxJXC2IVZNaNBpl69atfPHFF61iUCpdUup4AUP27XA4SE9PJysri+zsbLxeL6DHihSJqM+AYZ0VFBRQXFzMgGRKIkVUgwYNonfv3ob7T5GzWjfV0NBAMBg0NiWqSCQSrTJpKFJLdU+mqhPNSLUUOxI4dIUQUgUYXSG/zvqzCKpraKnT19qWvhxgyJPgGgBfJkNJQ98DToX/3gUPnwAvZaOzmCq5uAaIfa6TTDZ6LKphFrT4oekJcN0JRCDzd9B7E0TeBu+fgBjEX4XQQyCXQh+gYSgrzr+SUYuAc4up3xSApl/x4qGqzzrAhSUauB4BUQ2ZMei/HPc/dIHDoaKguO0+AsNuPOS+39KW7e8vcoQUgt1EUEKIvwFLgaFCiJ1CiCuFEL8UQvwSQEq5AXgbWI1eEeApKeXa9nvsIQSl4HK5DItAxZeUawwwLCNFGspqUPElNekqqwUw0hXV19d/TaKtFueqtpqaGioqKgyCUlaXmsg7mtRVnj2v12vsY17HZHa9KSVifn4+hYWFBgF5vV48Ho+hNrTb7YbrTgkg1GdzrKmteJMiGiXaSL2G9pR65km+rbibGW3di84+d8V92BEsF1/XYcvQo9IOTaP0tr7UbtPX4cpAgD3fg/W3wK4cOLsJRrWgM9fngCNZq3H8O3ACUI4eQHpwGkT+BN/ZBM6VQDMIH+ydCLbkvnXX6emR+kyH+LnQNA9svTj+tWtgADRXJfPsjQ5wSdLSqB3XvURV8pXGjqWAayvIPMhaBM0+qJ5Ide2h9d1f06jPAm2lPuaSaQc+dk1rP3f42YEJBz22g4agqy6+DiGl/ImUslBK6ZRS9pNSPi2lfEJK+YRpn/uklMOllCOllA921mePWahrXuhqjrMoKyASiZCRkWHEhNSiWvPkqbJ2K3ec+qxIy263U1tba7j4EokE8Xic8vJyKisr2b59O/F43BBGKBWh2dJKjd+YUxupmJf6rAQdivDUeX0+H4WFhfTp0wePx0NFRQUVFRVG1gebzUZBQQHr1q0z1nUp6yg1vqRe2xJyKLelGo9y/6UKPdoinrbiSqn7tmURpfbZnRaNZSEdIOK6unxMHsR27SICFD6tZ5jNAAo/hIoY+Ctg8nHoFlQzEFupO1/e7Q/sSE5QZ8HvlkP4LvhiA9RPBPd1kPY98J4DXArvvADZV0LRNP038uk1ZA64mm37wJ93B5fIJ7E/Vs6aoYNQmreS32iI10F+qFH63QAlpRprr4HoQbr+tBINNr8GOxK6G3J2Ndw2Tr+u1+ZTuBcCkw+OpbKGauxIjqtAK4OAnhf3QEcaCMQP6vyHDcqC6oHoEcNSk7KUspUVpSZ5NbFHIhHDqlIWjlonpUhAxZSUOKK2Vv9nbGhoMI5RAgolNKioqGhlkSirzUycqROxWUGn3I1qbZa6JiGEEW9qbm424lLp6emGG7ChocFYqFtXV4fT6SQtLc3IsQcY404lBDMJKGIyj1e5R82koVSBHRGPalPtqWR1sARkJtSDJRqLoA4AaeB4A/gpOAMQ0YCnwL9UowKoOFnPYB7yw44vgX3oooZXPtAdMTk3ohf73guP/0BX4w0CRkU48RcBPrvuMXhwGzzzX5B+LdjzdXKKJft5vZxdPxpExrHvweLv8uIzKyB/OQO8sCkAWp1G4OEAWz06OQGUlgQOfMZPouRFTSfG/xkNNdXASu6ggptnT4Jz0rhi9Qc802s+l5f6QHQbAAAgAElEQVR8xNp/QmnugZ2oflMATcshEKil4sWfUEoAvgPaovcJFE3u8FitVCNQcvhcdtobOQQuOEjz0CKojpH6i1/FT1S8yZw4VmX9Vq4y5TqD/SSkskaEw2Gqq6uNtEdmVVxqpgVldQkhjHx+am2WGps5PtPc3IzT6TQsI5X/T40/1SI0u5/U9TocDoLBIF6vl5ycHCNupkQQKilsquVkznTelkpPCSuUeAP2r5Vqi1jMxGf+Xp0r1XJMtd7a6q+tv3F3WFWWC6/rKD0GYseA61EQzZD5NLARBp4KrIS8GljrB4cH+veCHaXAa0OhaBPsWgJ1Z0H2n6G5ijuWvM3NnA5XO+BnLj5jCIypYTareOSKGorJ4VzOZDav8hue4uGmqyA9xuBj/wY0IX0w8orjuQHYFAhQ8huNmqXg/1CDxa+B7SOYUsQaLmD4CljRfGCTuX2Ehqgv1xUgNQnw50FNhAQ7KWIlW06ZwDOLT+XOaVFusucjBr7aIQ9qK3wEjg+2asvQNAKBANqWT0HMIwCs8kCv2hvY1UnuvcNJTsDXyEloGrKrVqhS8fVA9JgYlLIu1MRrlmUrCysajbZKfKosAiVUcLvdRCKRVjEkc4xK5cJTyWCV7Bww+lFEYrYyzJOxmrCdTqfxvXk8qeuszBO9zWYzxqgEG2rtk8oLqMaqcvSpJLKKsFW/alxmK0uRkyJ2RepmUUR7bj4F8zW3JUfvjJxS+zEf1x2wRBJdx0g7uNbDsguBJqi+EpgApffBynchew6cvBZ6R2BHBbqFdMImPRdA5MdgXwbhgbDxWm5e6APqoAwKVBkq8Ttuu+4CaqjibGqYPfp0eGoND88foefxq3ZRyWj41wWIZvi0AkYk406lt/8L/8ew4gTguxfy0YW/RT59AaPWwpbBMLlEo6S58/hOf01D27Ke4z0fctu8f3HF9A/IYIUuXvb0Y87j55HOg9x+01tksIIYMZg6AyIdq+RSyWlHicbQ28qTWR/scObVMG0aYzzlFL6FsWC3J0DTgl0nJ4Ujo+I7YPQIgjKrzpxOJ16v11hkm5aWZixczc7ONlx+SpigquKqBLHKCvN6vfTu3ZuhQ4cyduxYTjnlFMaMGUN+fr4x6SsyUlnPGxoaaGhoMNxyigDMMnKn00l6erpRukOlYzITZWoMx2634/V6KSoqYsSIEeTm5uLxePD7/RQWFpKdnU1eXh52u51evXqRnZ1NS0sLWVlZRpomM4kpay41Q7rK0m4WW3g8nlYJdzuSfbflzmvLMuoKOR0OolDkaokkuoa1zSCGw5dOuGEy2KuB66GxGca+AaTD7iI4LwPO7o2ek22pXy+ncVENZLwLoT7QC5gykclshCXVXEc9UAd758OIGMwoZ85fntWrV631wtknkXkl1MwchHxyBKtOh0BmgLJdAbQtazm2SIPsbPhyKMe/B8wtZ+ID5Wy9EmpGQnFGOduEXsZC+3WOcT2p+fS0/hoFF5Vz95QQU3mR2eSxDhfjiXLrkje5I/w2Rb9axsVczqyHzqaRfG71nE8Rm+HmcmaMvAdtxffRfqKfI2toUvjwpoZWppfaKglqlHyoceFCwAdsngVnXAvv3I229n9ZUTMIGYcxjxxYTahDhbarI/I+wMW9XV8HdcTRI1x8UkpDJm5OLaR+/avYFLS2ZsLhsBGzstlsNDU1GaU1cnNzDRdgMBhk06ZNVFVVsXv3bqLRqBHjMltcZsvCrHpT1pKySpQlo+pMKRekKn0BrdVzoOca7N27N71796axsZGsrCyjGq66zuzsbOx2u5GVXeUntNlsxhjNVpoip1RL0uPxGGNIlZ6nItVKao9Y2rKczH+P1H3bOk93kJZlIR0AItD/OLj8z26u/kUU/+cgn4XT9kDNKRD9DlSkwbrPYd02ID4VzlsAH90LX96AblLBjGvfx0uYe/gDpzGJ9QwABuoxqw9ccM0g+B4Ehn4HbecudjRA/09gy8iRUDLfiClpFRqBogAtftCe+Sm4H6Rmwtn4a7fD1BBFCx+Hld+HDPAPWKQfdtcgxjhhVTxA+RggkMxdt+V5Xfhw3SB4+QkW8Bi/YRwPX30azBvE+6eVk7FkOeOJMuuisymY/jn/RRUvh/ewhmL+sOxlPuPfejaMG8ajbTyXMg2023IInKsnHypp1hA/LYc/fQThaTBwECTmwzuvkXFplMaFOzj++f4Exr520HGzg0Wgb/snPJh6Uy09wlT5OnoEQYE+gSuhgtfrNZKjKhddNBo1YkwOh8MghWg0SiwWo7GxkczMTPx+v2H1hMNhvvjiCyoqKti6dauxfggwJm5ovzifWWzg9XpJS0vD5/NxzDHHGESqquLu3LnTyHphzrenCHPYsGEMHToUIQQZGRn07t2bwsJCampqDBLKy8vD6/VSWVlJXl4eHo+HzMxMmpqaAD3GVldXZ/RvrqSrii9mZ2cb1YVVnEzF4MySedhfQLEt4UJqW3vuPtXW2fvUe2yJJI4A4rCjHBgXZV4EVpwGr6cBe+G8XHilDsa79P0emgLT/74gWTbiGL3u07pJ8G+Yy2h0iV+IJdynv3+yF/jmwP9boNd12hiANyBQCtmahpwK4um1BObPNxKqBnrrE6d/FXDcJnAPwf/8W5w4dSc/JEjjlEacLKKeWprpjzZrOAxfhHtyiPgKDftfxhFAz11XEtcQJ77HRTzHTH7JRVzOw+TAvJ1cxOVsWrKUNRzPJD7m/WVQhY31ZODjz1zBZWSRxUh+xJJpA+GcAYxefCk+gL4NaC/lwJmD4J1y+NPrcMcPYfU6RrGCS6jnZkbRSAkTpnyXJZt24PlXDoETUwQKmgaHcxFyd0KA7FrawCOOHkFQKu4EtFqwa1bdKatFCRc8Ho8hIQ8Gg4Z8u1evXthsNtavX89XX33Fhg0bWqU2UpO7QlvxHPVZuefcbjdut5uioiKKi4sZO3YsmzdvNjKuNzY2snnzZoLBIHv37iUcDtPU1EQ8HqegoIC8vDzGjh1LLBYjPT2dPn364PP5WokYlGpPCIHf78fpdFJXV0dWVhYOh4PevXuTlZVlZHJXYg/l1svKyjIIzZzxvaKiwiA4p9NppHeC1sIK9dqZ+66tv52ZzDoTS5jbD5SolJVroYvIQq/JWwgsheMrgJapfHTJAh4BCsvR6z4FYfo69AW5W5fCyJNg3Ucw4gPm3NpEKVksKp4IZZ+APw3m9IYaOPnqBXz6JhB6CO00jUBpgPAYjU3JiTkAZD2iMfj4Rygdo7eVTNMIrwV5IfyrZRB3257Fh2Q9q8klnwcn/BiWDeJOHoPb9debOBH7lHKYCtos4AYg9y2giTGM53hO5Cb+C5gNVPMyz8KM2TB3JbPRmLHzfebShxfJ5nx+zjP9JlK883zKWA+jy2HxSlY/VUGfzIegLBPm1sE0kq7NwZzIp5xDLZvZyBO8CSyEB8pZ5t9NoGji18kJuoWcPi3ROPlQM5V3AVJAc/tLs44qeoxhp3LpqUWtiUSCUChkCAnMBQSdTmerulDKxeXxeAw1XjAYpL6+vtUaIjPMogez0AC+nhJIufUKCgoYMGAAWVlZ+Hw+I1aVSCSw2+3k5OTQr18/+vfvT//+/RkyZAhDhw5l6NChxgJeRaTmc6jM7CoVkyJFJTcHyM/Px+/3M3DgQPr160fv3r3Jy8ujsLDQOG9hYSH5+fn4fD4yMjKMeBRgWKMKbVlCqr094URH+5rvXVvWVls4GGvIEkkcACLok+xeYBhwPFC8gIlNsGAdUAG8ej9s98Mu9DSejpP0Krqu1+CmScxhgN5XWTV3swb6ARk10H8Ln770EAyA0LjpBEoDaPkaE+8tp2SdhtZfj5HUBwKIjPmU3KmhrbwQcdMi1gcCiD/AGX97C4Bx1LGA/6aAQlhWzTlcTDN2PHi56c4zmcEXUDYIZkPRzmSmhV1DmEwdUaLcxBhgEwA2tlHE8zrJkAfUsZsV6LVHHCwih1E7l1J24yJu4UFGrV7KVN6Dq16HKd+FghAzeBeuL4d9UECI82ngK3wMZzQ7eYYZrGb2b9+Ay11MfH6pcbtLyg9uwbF7eNvHHQlyAgwLqrPtaKBHWFBKNdfQ0GCIAJQVpawU8wSoSEkFxb1er0EANTU1VFdXs27dOnbv3k1dXZ2x3sk8Qau4jJpglbWkzqGsG7vdTkZGBoWFhfTt25dQKGSU51AxL6/XS2ZmJlJK/H4/OTk5+P1+Q9aelpbGvn37yMzMNGJje/fupbKy0jifKk2v1kGpGFZ2drZBxH379qW5udmIuzU0NBAKhZBSGnGnlpYWMjMzcTqdhMNh4vG4kdNQXae5dAe0rk2VGmsyy9lTiStVfq7aUr/vTtKwCKjrGOaFDauvYcklT3LadnRrqi+wC+aOQCeo4uv1LOV7gMXPgfMycL0ANHB7mU4gX7IeGMbMhTFdCFHmh/f9cPUZxEeCc+HjbJ6iS7A5sxaxEgKmQn7hMdMoLQqwQ9Po/+RxFGvFcFs5zN7M+/5TGVGzBHDwIFlksJXFF93D4lVwc9nt3HFTBXP5BbfxJDFe5xPe44rpddzMSAaQ4A4GA70pYhlbpk6gpVhjwOyP2XJaNncsWUYlbvowmitYxjP9JsHOJryspuCuz1lAPlvOmcC6xU7uZjkxYtxy1VBq2cfdi99l92IHTzEdwR/pRTWNCEbzB3xcxWx+x9X8noHTBqHddgZrZg+i1GQ1aTGty+Xso+sDlNypUXrT0XMJ9lQXX4+woIQQRhwpGo3S2NhoKNHMC0YzMzMNRZqSZ8N+pZ/D4aCiooLy8nL27NnTqjaSefGvmoxhv5hBxXMUUamJ3OPxcNxxxzFixAhDVKEUhX6/31AL9urVi169egEYa6uE0JPg1tfXA5CVlUVGRgb79u0zalbV1dVRUVFBVVUVjY2NRsJcp9Np9J+WlmZYcirrud/vJzMzE6/XS1ZWliEiAT2ep4Qd5nvYXpqj9oinvTVPqejIekk9V2dWVWewVHxdx4YokP0kp4XRU3JWoSfnK4dZEfQ8e+uAWvQFuMMv060umqH8e2zFg8TJgid/C6RDw3R4dhkUhWAy4J2Fc+G9gIdReHV1HtB4hl4ocFwy7926xgDDNY3KQIBAST1Zj5ZD0Rwgj4Kaz8kjxM28TiU/4b/Yxt0vv6tbTEAB2wEIUccqcsklnz8xh0vYwjNTJ3EiDZzIp2zxT4AFEe6e/S4fkMY5S/7AzZzKwxQyc8FQPiBNF3Xcks5nxScziQi9mMcli//NeGJUsocQIe5mK/O4j5mM51Ey+AGPctN1Z7KYl2kmBw/TeZmnuJPHmOf/JTNf/CUc909GvbH/vmdr7ZOT1o503kxO3V39tzMoF19n29FAj7CgpJSkpaUZMmql2svKykIIPRt5ZmZmq1LtysrKyckxXGRr165l5cqVNDU1UVdX16rchrICzFkiFMwWhFmhl56eTl5eHpMmTaKlpYWKigqys7NxOp1kZWWRn59vjFUR544dO4zzqNiYiilJKdm5cyc7d+40pPFKxGC328nMzKSlpYW0tDRycnIYOHAg2dnZNDQ04PP5jEzvLS0t5Ofn43K5KCwsNNZNNTY2kp6eTiKRMBb8mtd+qeszX7vZcoLW+fcU6bRFVuZ9VT+qrT3L6VCtn+5w4Qkh+gPPoVdIagHmSSn/VwjhB15E9wVtA6ZIKWuFfoH/C5yDbmtMk1J+kezrcuDmZNd3SCmfPaTBdTeC6VB9Clf73mHe8ehZysuAHwCvAEXoFlU5UH0vRJeB/D2U9oIo5FPFbEZRdM3nOgFc9SHM6ge3b4ZXz6SxBDKSy6M+CgT4ags4NT0GNf0YjYcCAZg0Ce2TJgIjRzK5RKPhpfngngY/+4QJ/I6z+TG3cCw2Ith4kbkejdvC/wJe4V1CjCBGJa/wJmHW9DsJduYwg1N5lfuYvMDG+8WnMrnsY4pqlrGFASRIcAuVODiNxWzmapaxeepI3p96KiwYBPZyZpe9wQP0YRI/50UmMod/MGfCZRQs+5xKXHB3OTfOfIW7uIEXR5dz94Pv0sQlbGcFkzgeDz+jHDfX1TzHgy2/g/jrcFM52sUgR7S2pGaVaNxuzm5u/zpxaRkagcb97aviR9iS6sEiiR5hQSkXn8/nM1RpamJViEajBnmoY8yk09jYaKgAg8GgMZGZ91PWE3y9PpKymlR6JXMpjFAoZKRZMq8/UhaKlNJYG9WrVy9yc3PJzc2lT58+5OfnG6rE+vp6amtr2bdvH3V1dQSDQWpqaoycgQ0NDVRXVxtrsqqqqojFYng8HmPRrtfrpaWlhWAwSEZGBj6fzxBxKAtTjVdBCS3M12t+r4grdZ1Ue3Jx89ZeaY+23H/dgW6IQSWA66WUw4AJwLVCiOHAH4D3pJTFwHvJzwBnoxc7LwauBh5PXpMfuAU9a90JwC1CiBx6FJrA+w4XS/T0Q7ElYPuRXmww0h96wcknoMeextwA7lOgthfM3cyJD35KBhncyVcMIAF3AqTDx8Az02FGOROOgatzgffg8hINrVQjnpycP/m7PoKCXU2wD7TfrOWNFqBpGqOu+iu3sJxJnMMf6cUtbKVF/Va+GR4lE8jjM8bx/uhTAQf5NMNNcCe7qMJGGQ/wvv9UKKvm/eJTATiRLcx68kxuoS833XgmjB7LvHfu4/3TToXj4BL+Ag/CbVxA43XjeRMPTIU5o8+DZVB59wncyi6YuZK7+B7wIdTAzDvPoIFsYoxnLsOJEKEPdexhAKN+Mo6ac97hq7JBBH5US+nQAOmmjOlv/aXtv4y2Zv//6Yqh+uvx9v3HaS8duX8liS4z72w7GugRFpTdbic7O9vInqDW/KjcdmVlZbS0tNCrVy9ycnKMmEteXh7BYJDPPvuMffv28dVXXxmKNVXqQqVCUuuGUrOTw/6ih+qzcu3169eP4cOHE4vFqKqqwu/3G1LzaDRqZIRQ67eUW06RZDwep6KigkgkQmVlJfv27SMSiRhxI3PqppaWFmMxbSwWo7a2lr179xoLeY899lg8Hg+9e/c2rkGJNJTcXr2GQiFcLhcNDQ2kpaWRm5vbqjSHSoir7omCeZJX5zDfo4Mhmu6OQR2qC09KuQc94oKUslEIsQHdjrgAvUA6wLPAB8CMZPtzUr+IZUKIbCFEYXLfd6WUNQBCiHeBs4C/HdIAuxHFufDDH8MZG9EVetHTIPN+qFsHp2yCpT/i02WvQsgNw6Ow5ofJ6jwRPmMIn12UBy9XwI29wRHjfNaw6FdOCqbMYZwcxOL3Qex7ATn/UtZdo5dw17a8S6DoDHgZSk7VKCVA2XiN4kY47R+QccULTKKJL8hm0XUT4Uu4tQy4FFo+Bm7ayDSamEsC/GnMWf0P5lx0Hh+8HGDOr/7BTQzmCioooIZKoB9TuKbs90SIcCcXQs5CbsTOXYyFm5fDma8AEViykb28BHxHt5ieO48WBpOxYDmNF42H1Tu5deYqbuFMGO3gxNWf8hmZeom9hn48TD43UcatlHILk5jNJ6zHyZqnxuAfWw4L34QV30feWdPKgsL3ErlDNPpl6qXiFQKj9j9Lzcl2c3qnwMWHmHb9QCCgxdX5bkcDnfKiEOIZIcReIcRaU9scIcQuIcTK5HaO6buZQojNQohNQogzuzIIFftxu90kEgmEEIbFEAqFjIlRqffUAtasrCxjMq+pqaGmpobGxkbDgohEIsaEZl6blCqJVu43NSGriryZmZkAhpXTq1cvCgsLDTcaQDgcpr6+noqKCrZv386ePXsoLy9n/fr1bNy4kbKyMsrKyowYk1msoCTfKp2TGpMiMZXQtqamhqqqKurq6gzXo8pGoaxKZQWp+6hk5kokoQogKpeeirGZ3Xet/jFMCXzbij+Z+0ptT/4ftPf/1Ob7rqI7VXxCiAHo2rbPgIIkeSkS65XcrS96NSSFncm29tq7eu7D/lyVSbgP9LjTUsi8Eii6Hk7SFW9orwJTIbIedj8Ot0dgFVA8Eq7Lg7NCXMFGiu5aBplrWfSPaUAD5xLi+X0g8kAuv5TShwNElLS86AwyNI3S/w7w3NWgbdlMsQd9ze/eDdSsupSHF6YTRMCTMGfxP7iu7DnYACcu+ZTZbGLu1MnMYAucC3PQ4E1oGa0xh7O4hTKeKZ7Eb6iBa6GYEcziJJaSD1OBqincddqP4Qlgyni4biwwgsk0sYRroGYlcxYKqKljNh8yjSZ4uYIM9vAY+czhbT3hLLqC7w7Wwtwm4Lik+/Bc4ERe52+sufokZlz1JvxxPpSeCxnXUvpygJJNGqPTNC4v0bh9ysUMfHteK3Iao2loGxoBKFmXkh1jbfdmOjfXl2oPUkCzrfPtaKArFtR84BF0v70ZD0gp/2huSLpKLkUvAN0H+JcQYoiUspkOoEQHzc3NhEKhViU20tLSKCoqMrI0SCnJysoiKyuL2tpaoyBgU1OTsRg1EokYsnRFUGaFmiIic8Zwc8ogVddJpRnatGkTHo+HPn36kJ6ezp49e9i9e7dRQwowXHNqPCqupBYcqzx8qk3F0dRiWmV12Ww2Y9GtSnjrcrnYvn076enp+P1+MjIy6NOnD2lpaYb1p65JZadIT083CM3v9xOPx6mpqTGUh+ZCkMrFas7mru6dylRh3tdM8KmE0BaRtff5QC0r8zg6QZ4QwuzInydTylMLIdLRIzHXSSkbOiDLtr6QHbR3FfM5zM8VMVgeg/G94OwT4K0G9HRGtehiiAjgmgi9l8Oi7wPbwDNAl5L74farPmQh2fycWmbdfDaZX8KbiV8xcSc8XgWNY0D8bZGRRME9XGPUPx4iEAhQUKzRtw7wXwovvgWnnw1fDsO54TVuvnQLdzCWW8Nv4sDJQwyHl6v5DD+f4eWKBR8wd+pkWKBbb7PveoOW1RIHDuZwPneXvcun+GDUByy57WEog+oFj8CCwdy2YC2zGcyNlHIXP8b2YICWG8sZf9dLvM9YmJAO7IOHsnFM9zGfdCDCjdQxk/7MOe0EZix5n7mcAFRz89PHkXHlBhoZxdzRF3Pz6tf5M3+jjCu5Y97bNONl9qUubmMQccDx+9sRw2DyyGd5NjACrWwPtZPPx90I3kXlBCbWsioQYM8gDX8Ora0tIDCye9UIZwcmMKsTzYUEIj0i2PN1dDosKeW/0dNHdgUXAC9IKaNSyq3AZnT/fGfnIBwOE4lEjKq45qzjKtivigKaUyApklAyclUCQx1vjjuZrQWze8ssL1euN5XWCDAsFWV5VFdXs2/fPqOO0+7du6mqqqKmpsbIeKH6VRL4/Px8Bg4cSN++fSkqKmLIkCEcc8wxxvuBAwdSVFREUVER/fr1w+/3k5+fj8fjMQivqqqK8vJyvvzySzZu3MjOnTsNYlQEpNZZKcWfkrb37t2bzMxMQ4xiTpZrltQrq0olrjULR1L/ZqnxrNTvFY5CDKpaSqmZtlRycqKT0/NSyleTzZVJ1x3J173J9p3oRc8V+qGXVGqvvavXcdifq1FOGF8K+OGt1Ulzrze61MOFrtyLvALRhXAyQJ5+VWfpx8/iJNY8fhKzmAhPDqJBvMnETcD/lePOhoxnhhIoLmSe9iIluzSaHBAoOhmuu47KsgCFr6zh6u8Bu4Zwd8ETsKwcIr25g9O5lXU8Rj43/fk0PcbFTnjqGLh3LB+Qhm1BgNtYC3dt47a/7eQOzmPOc4vBD1sp11V5U8bCarhowW2sLn4BqGY2g2HCANykwQxoKdaw3RUgG71k8B3L3oaF34Os3cx+9HQaZ42H0QOYef8ZMPo42Alzb5kMxelAAl7JpJEcOCcNVjdxB/ps/wMe5Wau5QPe5jaGAp/gvKUcUVEOwPt/7YNWtocNPzmfnLcm4o0AfReiNWtoE3PYVR5gTSBAydMauUOOrGovFVJAwtb5djRwKDGoXwshLkNfMH69lLIW3cVhtim75PZQYoNYLNZKDKGsC5XVXEmrs7KyDBdYLBajqakJIfQyGarIoLKOzDWRVNzFnChWucWUEk+50FRV3mAwiNvtJj8/n/r6eiorK1m7di1VVVXG2i3QRRzq+JycHAoKCrDb7Rx77LG4XC5j/ZMqoxEKhYxzmMtgKIKIx+NEIhHDiqqtraWxsZG9e/dSV1dHbW0tDoeD/Px8srOz6du3L0IIMjMzjTheQ0MDQgiKi4upqqpi+/bt2Gw2o0aW+XxmQgeMMvJmV56ZdFKVf+a/ZapAoj1V38GgG1R8Anga2CCl/JPpq7+jr/K5J/n6hqn910KIF9AFEfVSyj1CiHeAu0zCiO8DMw9pcDq67blaI0imLAJ80P8V9DpNNXeDdyasd0PmL+HSIejmVAX8ZjBMj8CsNPizF36xDXAQHAi+R4+D9fORSwdxze/hd1dsYuAGjXkLn+fBC8CZtAb6f/wxvVZpIFYw77FyGPAJM5/5Jdj0Ra23sIRbuA54B3a62EI6M9jL3JAXPoAtD0xg9m/fYPY5F1Cw+HMqo8uBa/nNZRfzME3M43SYMBiWbWTUyxuoYTK/KVvCwzNO0x2z168kQCYnzv2Uz+iDD8nM+89g9vVvcPNpF+g356Y+4AfCYCsL0HK9BmyDv7bAjiI4DfAMhsUJuHewHpG8Lh0eTGMKZeQR4gqeph/1jGQPD99/nP6TZkEd7CyHdwfBc0MZdn85/S8fpJcy+d0UuHYKPDgISMbrrgzAl3q29P5HamFuCiSQ6L7fkN2KgyWox4Hb0a/tduB+4AoOwO0hhLgaXRVFQUFBK0tHZZIQQhg1lrxer1GBtrKy0lhfVFNTQ2ZmppHOSMVd1ASpJlK1ONX8qjI2qCSrqpBgWloabrebYDCI0+kkOzsbt9tNTU2NcV61tklKvUhiRkZGq7VRAwcONKTjiiTr6+sNqw8wxCBm68xsCahM5CoXYFNTEy6Xi2AwyJ49ewiHw0aMTllqgCHYUATT1NREVlYWeXl5BrHH43FDfq9IWhGJuTAH/5QAACAASURBVMihupfKJWr8UVNk5eb35utoK+Z0sIR1AC6+jnAKerRijRBiZbLtRnRiWiiEuBJ9Sev/Z+/Mw6Mqz/f/OVknmSWTjYTsJoSdCDIgICirCi4Vl2CruLZY28oXbV1ZZFfw10qxWqHVivSrgtRdFEVAUdaJYELYQkIgC9kzyayZyeT8/njzHg4RBLeWfi+f65oryZmZM2fmTN77PM9zP/d9U+d96xEU8yOI3OPOzmNpUhRlAbC783HzJWHie8QP+n9FCsLz3YHAnyxEf6X1OQg+ANETGXtzNeP4lJl5V0B0D5gH8/iEYwuMvEh/eCILHnXQagV+68Bu70/BTDsrV9pYeQLsVXY8F9mI5hAlvXoxywT//AqUCiBuEA8Oh6eeKwV3KTxUDmlZBPADGzDTTPS8XdxNBc+QwV3Tt5CJm8cnT2D+op+RNnMslX/7kHl33MTjeWApdDCLjSykBw/v2MRuIthEFtDOBEqgFBYt2cBMBvMuPkKoAcD5qhF+DlFEY968mz9QRyihrKmMoWjacEG9x0EcN3PfrTMJpYw5i8ZDCZjZg/Oh7tzFEV5cnwy08wyjgAbGsIg0xlNOGHf9fgsvcjesfQGa74YFpdBvN5jWUvH6C1A+mgOHcuhjLIW3wVb2KVz8KNRPELbxL/2w4BTIsxFeeG777FDAd57SzJVzWSQ6m8nvqara/5vuUxTlUQBVVZ/ovG8DMFdV1e1dn6ePnj17qs8//zyqKgwE29raNOq13++nR48edOvWDZPJhMvloqCggPb2dtLS0jh48CCfffYZ1dXVHDt2TCv16VloshSlL/HJcpbZbCYhIUEDGNnzATCbzZplhbSgdzgcmjCs2jm/FRMTQ0pKCtnZ2Zo1iOzhuFwurY9jMpm0125ra8NgMGiZiuxDqaqqgYveoVd6O0nihMPhoKmpiaNHj2qKG1arldzcXAYMGIDP5+PgwYO0tLQQHh5O9+7dNUCvqKjA7XZrmZTP59MEZmW2KgHf5/NpgAac0ovqPMdfY0iejfF3OnDrjAJVVc9Y78jJyVGXLFnyTV8lAG666aZv3M/5Ej/2/5XSR1HZCP1SofgdBEAVAREvAOHwwCUCcpeXgdIO/9sTplRjvr0K56IhMPMgvPQkbRdvpWjRrTBjBrZSG2oavDUCJn8CNL0AhKJW3IFyNQKu/UDUA+D/E9m3/y9l2ODzXiSNfJXaF3rD3YOYw5+YTw4PU8d+wnn3j6MEd7ISeP4TyM9kDH9mMzPh8WSYtw8e7s/cJe8RSiizGSJMCWcAqa1g/hIIQrA7tCVAuAPCiyAwAMJrwZ8KnqtBMUJHE8Q+C7RCfj7MBhY0dJoc1jCT7XzCu4zlKhY/doPoEkYBj7SSffd+yjCQy2xKct9lYcmHBAkSIMBCsljACdy4eZKHYWkpxHlgbjRU+kiikNpVacAoSIftI9FAxLbvfuz9nz7l/NnCbdgDdobaStllz/k2X61T92OzfeP/Q7/BivrKtrPvZ6Dhm/8/f4z4ThmUoijdJeMJmAxIJtI7wCuKovwJcf2WC+w62/4ktVqKv7a1tWn2G4mJiWRkZNDR0cGxY8dwOByYTCYiIiJobGyksbGR48eP09zcjNfrPfnGOrMi2UORwCG3y4ypT58+mEwmABwOhzYHJeWBGhsbueCCC/D5fBw/fly7+rdYLCQkJJCbm4vRaCQ+Pl5z8JWyRZIYIbNBmcnJ/pbcLoePJUDIEqRUx5DlSgkWklSSmZlJ7969qaqq4sCBAzgcDvbv309KSoqmoC4/I6/Xq2kGShZiTEwMgPbZhIaG4nK5tN5ceHi4RonXg4ks+Z1OOup0caaLoO9SrvshyoTna/zQ/1dEAF9AsRtRgPyoF5jmYc4HJ1FiCmwS8Eq2AIbHCiHEifPhS4T/zwspAPj7QIX6Tya/PgYCgr1HeinMBMw54IeMBxADv7ce4kYWY6EfrdzOOvqTx60UVr9M7VoF+BBWlDD/4xDIgSUgWHK/b4e/+yEQDcXjYBJsnvAMc+9/j+PzTLy4tpXH848y9x+XCI/6X+TAx0sh4SFB/KhBUOlHA6+OAjWLj29czYTVwNVAAFEkbehs3bU+CVMr4J+PCkWNtc+C5yIghEWzJjOgMpkXCIUGoPIgLO8Nv7NQxjDgICV575JduEO4DNOLhTwL3MBs3ieXB4FPePihTSxZNJakyl3Urkqj9vY8+KMBpgP9wBUGsUB8Txv20/l1PFsK05q/FzidS5zPJb5zoZm/CmwHeimKUtlZAlmqKEqRoiiFiGrt/QCqqhYDa4H9wIfAb8/KNOJk41s26iVFWip0y8VPMvNkWU5esUvmnOxd6Ydupbis1MwzmUxaHysxMfEUUVa58OozHjmIK7OvQCCgmQ1KwVYpXyRNE2VIlp6qqprwraSQyxktOa/l9/u18puetCDfSzAY1PpcEtDcbjcGg4GUlBT69u1LSkoKgUCA/fv3c/ToUSIjI4mPjyc6OpqQkBCMRiNGoxGDwaCVI+Pi4jSDRH0fTO2chZLnR5+JymPS25Hoh3xPZ4x4JjLFt43/K1JH/47/K1wIIkQG8BHQXg4VQ3DmDYHZ/QUozSkXg7u/rwZXD3j3EhhUKARjOwwU5W/F/B5Mji4F/93Ye9vZkwHzKzeKIzIDd0HF2tdh627AwbrZc3hx0mjWvTAD5pso/MdzQACqhgCpEPumeO0lRwSord0Ai8Lgl3VC22MpsN4F9TCX/rwYNZqL8xOYN/UaMO4RPlDvTwXXC1DeS0gYpSP6T1uBQVsheTUT3gJ6I7LGXQggStgKt24FQwW8DtyAyCyDpRD9JfhHw5NlFA0bLqjsJcCKnhA9GpZ1wBiYQh08VMZNeGBGGLCTWcOu5GJWA1ZKHnsX1hbTzGHYA7WkwO1x8JgBnsxhxN1CqzD2tlsBSBDTLMTYTk1O7NOaOx18f9yQJb6z3f4TcdYMSlXVn59m8wvf8PhFdM6dn2tIcJI9pI6ODjIzM0lKSiI2NlbLHCRbLzk5Gb/fz759+zh8+LAmCCvBQGZKUpLIZDKRlJREeHg46enpREZGUllZqZkCyn6O7HVJ40AJlIcPH9aONSEhgaysLHJzczXNvZqaGpqbm/H7/ZrdhdTCk8QI6eIrwScQCJyiZhEMBjUZIz0lXc5IyX3p2YdhYWEanT07O5vMzEyqq6uprq7G7/fjcDiwWCya4oR8XmJiogaELpcLt9utqVPIAV95MaAHH73xob5XdabQ95zk39+HMHE6Wvt/a/w7/q9QgbKVgA9MiFRomgumiooBecBvsyDjMBzvCY82wBPR0DEZboWSEZC77goYu4GixhwyWiDmkz9D2VLIHU/a5rH8avNyHp92FdlTdjCetaz8+20Q7IABH0DNVZDeBC/HQeVoAbkfXyL4jnkwYEc9N68rZWa+EXK3wPzRYmbLu0/MYi3eB4TBqi/Y6RwAF+dA0QPQY5rImpwIYLIA4dAvB4o/QmRSWdBWDa/1htt3ATVwYAr02YMArCBwHQK4DMDYPwlQ5gVG3DSBbVaY5VkpQPiew8BLMC0ELoSYzfvhV5eyJC8blh0hBAcP7ihkCdmAAxZb4eGrWIkDDiO2YSVksZ35PMuspVdiuz4HVQHF909GqLC8QCi/20bFUlGTQ22JtCz5N9ht8F+cQf07IhgManNMiYmJ9O3bl+zsbNLTBYt3//79FBQUYDQa6dWrFzU1NRw+fJiSkhKOHTum9UdkiUy/kBoMBiwWCxkZGfTp00fr9Uir9vDwcGJjYzWr9fj4eK30VVtbS1NTkzYjFB8fT05ODikpKbjdbjwej6aYLsEuMjJS6+PIbENmPPphYbm4y54TCHknacXR0dGhESA6OoQtvSxNyn1KIPP7/dr7TkpKIiUl5ZTPtb29nYiICO2zkFbyEuxkmVH2xPSZiB5Q9NmlHny+CTT09+lLhDL02dW5xDnSzH8KACUHCIJzFLQNgFtTxBzQ6kph6z4QkXE4ego786cTIGc3D/4c6NfJtB6xAUsqDFizm5uTgbfmAhnQCNUs5XGm8/jKdxmCn5WMBPNB5t6znovzYyF5C4QMgc3tTCn5DFYeEZnTyr08sfJjioYNZ+azV0B+f8gfDXMOMv/RjUAClPjIxgW0Q4cZzPthVy8I1gtAafmrAKIqxCq2C4obYcHlgBOWW+C+3nB7IQLM4qHPTkQpcID4m4PA4Tjx04DAEdxsKwearxc7utIj6OdLs2AQLFj2ASu5EaIgqXAXYKKDNF4nmvkcYSHlkGdg4ZIPeZytgg+KFaihY4yNB478FnrkYHfYUVa/j91g54uPwHuhyJTsW5tJf72IwQU2+pl1kknnMHD7feL/Is38B4uwsDCys7O1odKIiAiam5vZs2ePNv9jMpmwWq24XC4OHDhARUUFx48fx+FwaEQDfXYhrdqNRiOJiYn06dMHRVE0lfPs7Gytz5OTk0MwGCQQCFBXV8fRo0dxuVzaXFFqaqq2qEdERGgzT62trVo/yWg0agOugGaHER4erpUVAY0+Lo9RsgwDgQAxMTEaWMkymrzJWSxZ4pQAJ2n5EliioqLIyckhLS2NxsZGTTjX4/FoJUuLxUJ9fT3dunXTek6KomiOvXqNQ3kcwCklv9NRzLsClzwfZyJFfJdM6r+lhHdeRFkU3H45XAW8bxH510yANAZM3040KjvpC1M8EOGg383XUPwFLF0LT6WDvcaO7fDfaN19NQwbwgeLS+HmHPh/pSxq2oATJ0/yKfPw8QRHWTOsP9OmPM/cSb8maf0uqBkBz5QCDtaQRzYHKZvYg7GFLpYRI3pC1wN/j4NjgLM3c5YZAB+saqKs7S6wPgm+DyGkG4T+HXyjoOp6iPSI7MmBAJtxMCUe+gPBALiroLgbfJAnHratH+wOgSEBsG/ZyOBHxnNkH+BsIsEDsWvjILQJy53TaT0IxL8BeW/A+kiY3gbhWyHCwXvEQFwCjzStYzMp1JIAaWGU5SUTXP8uc5gAXggSZF7UNTALJvEX1v/jIebd+T7Rq0ohczS264U9iW2wDfVliPqqkyxhc8PfI2m4B47phngn2oed9XTbbLHY7d9eIsmPwPnzMc6LDArQekTyqr++vl4zLUxJScFisWjsMtnn0Q/m6mV54OTiL2WL5DaTyYTZbEZVVcxms3ZfVFSU1h+SEkSSrBATE6NRzSVgytKaJBjIxVgOHMvXk5mOLEFK8oTUzZNgYLFYsFgsmqK7PAafz6f1hGT2IvcFaIxDaesuPaLCwsLo3r07ycnJuFwuvF6vNrdVVVVFe3s7FosFq9WqWc4DWo9KkjkkFV/f19ODlv5n10zodBRz/d9dwepc4qcM6twjlVbwHhFUcy8w08VdbAFcFNGHnfQkicOwJgUyr6H4hXSWXwL+KYi+FeC8ZAX23O7YqzaKDR1LYUcNrbQKphqXYaaZVzCRvWMHKyf9mmHr7+J3NML0GihpR4jDOyh71QJLXGyaPZLah4cKEn1mDuwT/4Ms8wHJkJYFoaMguB/UNDCMhrjVED4KIq+H0ETo+3uR+ZTAg/EwsRv8tRGu3Qv7e0FaKuSHw3ovbDsIVIHtL9BWAVitFLxkpyU1lcxjYL0OUJpgsAA4jiIEsIxAWBsnbgB6jwK/lZ3/6A3D4En6s5OhsHY7VLbDehdbiSWbvVxcsk1o+nmPALB+2JNwZzWPkyooLpan6KeC7cBieL4UxSzevu1gMxUtl2Ef2HYKOAFMH2zDVjTtG893V3Cy2c6tfxVEVFbPdvtPxHkBUBERESQkJGhX9+3t7RQVFVFWVkYwGMRsNhMZGUlhYSG7du2itLSU0tJSzVJD7/Ukb5Kq7nA4aGlpobGxkaqqKlRVJTY2VjP9CwsLo6GhgdLSUq1kWFdXh9Pp1OSN0tLSMJvN1NbWamW/yMhIzYpeqjNERkZqMklSlkgaKepNAltbWykrK9MynEAgoBE54KQ2X0eHMGOUw71tbW1atiVFX6WskczgpCuxFITt1q0bPXv2xGg00tDQgM/nw2q1YjQaaW5u1sggFotFy9L0s2D6vpksVUrw1xMn9ESSrtmVfi5KRlcgORdg0Zdw/9tJEv+OqDJaGEuNoJLTAGkmXpRN9zFWmJ9A7bND4Z0cvPHw5t0VjPhkIxF/BMphcJUN0xGw1dhg7lxwA/U3wNodLMm7STjXRpUyGh+TqKQMK3PWv80O5jCbQUzhMAPkmNjyLKjoy1y2QO5vYMk+oRnvhKRlu+BZYO1eWNUEi38D7aPA+iwoRwGjKM1dC0RexZSfr2BEp+HilFvEoBpASwSETICMFjHsdvw30H8cdLhhYg7QA2b11n1A999PuwGU1QiFDQdsqwHVCQcs4u9Vd0L37bBgKBBlh5ghMNkPT/SGqDDIvwBe8ECeiU1/HUnZ7GHsTBvBxexiASXgLYdGeIxDkDcQ7j0Itw+hWPkUIkez4Nc5qPVgO1QPWROoLbFjs9kYYBTnaXCV+Lm8wI59wCmCKGcN+znazvsRg39nu/0n4rwAKLn4OhwOtmzZQmVlJampqaSlpdGtWzcqKio4evQopaWlVFdXa665UuKnq5aczErkzJDb7dbulwoL0sgvGAxqig4yO5Mlw5SUFLKysjTiwIkTJ3A4HFqGYTAYtMXbZDJpWYfsQcn5JjgpVisJH1LktqWlRRuolcevBywJvNLzSs/ki46Oxmg0aq8lMxw4ueBLgE9ISPjaDJjf7yc8PByz2awROSQTUuoB6inw8rldo6si+rnGN2VYZ4qfMqhvER7YNG2kYNr9zSJo5VNN8KwJhgPZZRCbQ4kXGpIhvcBOyvjxFDTPgv2RFKTaKYixY78nFdsnn6PG5wiQwgCFUBY1jKneP/LumFGEEw4kM3/MzwihAWhnzbBLKVqVCSTA9BzI+oi59IeK5wCTQJHaUmq5SGR4QQtkjYK0DYJtp/5J2IAMmC5o4hWAejdr3oFtVUDERVQAxf8Lbx2EJ8yglENMOKx/B5wzgbmgBOGVOlCuhC9ADMbabAzO/QN35sDWTJh2FfS7FJrCofJK6OMHgnBdDSyfCLP9AKHQvhwaIuBthG/VmDS4uwkeKhOu8yHAozCOE6iEE8fNLCz5kMU8BA/lwBO9yfbuIF29DPy7mf0y1OQD4bUcGCRO29YAFLnt9Im3UZB6EmT0PakfMs7nDOq86EE5nU7WrVtHXFyc1vewWq0UFxfj9/tpaGjA7XZTWlqKy+WioqJCG+jVEw4kCEiWnKqqGn07EAhoQCQHZSVBobW1FbfbTV1dnQZYiYmJpKWlERISQm1tLXV1dbS1tWE0Gk8BI73PkhzMlWy+kJAQrUekKIombyQBVPpWxcTE0NbWRjAYxOFwaKQPWdaU7sFtbW1a5pKUlAQIIoccLpbSUHLmSWobSvXz0NBQzf5D9rJALPpZWVmaRbzVauXIkSMakLnd7q8ZHer7Y/o5LxlnIlKcicl3rsDyEwB9i4hA1KycwO4I0fO5F7ggB6J6wZWHIBRaDtlpAWwDbdQ3AWXXYec6AGxHKqDqZexFMRRcBpCD0wZm3gevlVwuhHiIIgooh68G0oFNyAhdD9wegpkqnH8H8nvCX7NgEYylkk1/zRLlsalhcFUhtE0WPaXGXmA5BJ50iKhgeyrs7i0qhqQigLYCyP1SlO9SYFtPWFYKy3pAdCXsmAg9IiDqK3CkQ7lRVAx39YPP94A1AJUBWOiCHl/CXy6FfX+CgssEIKhtNhr6QHgT3PcGTB4P6XHTxWp+4XTI+IA5M7rBzT6YmiVmm5oqgQQYYyCKaP6ChSbeYhNHYFIp2bfu4BL+yGpuAeVtOPEzaIWqUjsd+TZC7ELfKjYcfHY40NjZl0q1Ya+yU+z8cRh9QaDlB9iPoigvIqbO6tTTDJ/rHjcE8W2coqrqum/a53mRQcnMpqOjQyMT1NXVadp8bW1ttLS04PV6NaUIfbmna0NeZiFyv3I/Xq9XW5RlBiXnkGS5S7r3xsYKiTW5kEoFcmnNIYeLZT9J7keGLMHpF2o5/NtV8Fbfv4mMjNReUwq/mkwmDZxkRiPVHaShYVRUlMYA1Pe+pB2I1+slNjaW7t27awPRshfn8XgwGo0kJyfTvXv3U/Yn58j0vSh9v+90hAkJovromiGdjmRxtvipxPcdYnq5EFBa6YOHgIQOaHkADKMJJICnEfp29ioKwiDx/evJttmwZdlg717sPdKx2wWr1XbkbezYMa+AJFoBByV8xdR1fyRAgEXUQlM5rP0XNFWy4KEP4IlknAwQK83TWUJy6bewaf5IMUtFuai/hZQLtt1QmHbnIQiB5XdXwCcw/HgnOAG44cFQKEpCZGDJYhe3hcD4HAj/CtJT4R/hUN4Gl+VBYjVY/XDvQKgJhzAV2rZtpLbETsshOwWBjbyyFxp+f/JjKx8ANQao6IGw7gCaB8CJoTBiIpAwEULKYJFBqK4/CKSlAQbGbv6c2c9OZBQfch8HmICXkPV2yp4YhoOh5DGDBVTA5nuY32sFtrJNhLzYiwM24cDbT2cfD8B7BzoPqvwH+Up0DT8C7892O4d4CU1q+PShKEooYj57w7ns8LzIoAKBALm5uSQkJADCf8lut2tkiKNHj9LS0qJlOnJuRz73TIrlUi5JKo/LBS41NRWDwUBUVBROpxO3260NzkZHR5Obm0tycjIej4eGhgbKysoIDw/X+mQdHR1aH8pqtWpAFxkZqR2HZPNJ9pwkOsh+VHx8PFar9bRDrlJ1XA7ySuKFHCiWvbO2tjatTAmiHCd7T11tMlpaWvD7/RpVv66uTnMHDgaDVFRUYDabueCCCwgPD9f8tST9XD8XJZ+jL/vpMyI9hb6ryKw8R3Ays/o2bL6fMqhvEUlA/yxC1tvpmGGD5I9gwL20djblqwFDD6iwCxfYdoD2ck4A6hLgg19S8JKdwe/bsD9yciYnfRpURPSAO4ewmkPMYwPriGMKLZipp29+d3ZiYnbURKgFMMBdBbB2B3gzoDoF85zdzFlrgvIeYsC27n4evAWeKoWVrcC1QrMWM7AlHcZV0GKAaZfDUzUwPRq2h8HwEPAPBVcjtIVCeA6o20BJgtmJoi/VnAj7DPB8AYQMhj1BCC5bJvpqAFYrnkEwU4UVL9uEiZYLdhyGYROg+GPotxA8v4FYA4LzcTlQ8Hvw74WXfgNhZXBjNox4h035l8MfYN3SOQKQS2D+6o28/uh23n16FPxjFIVjgX9OZM7TwEvw8PpYHP5f8cHLW1GSR6G+YKPgbju2g83YO0t/ZGX9KF+THyqDUlX1M0VIdH1T3IdwEhhyLvs8LzIok8lERkYG9fX1fPbZZ3z66adUVVVx/PhxDh8+TEVFBfX19TQ3N+NyuTRShCwtyQVOX+qTV9OBQACPxwNAbGysRpgwm82EhIRoWUhHh/BViouLIy0tjbCwMOrq6qioqCA6Olob+AW0TCkqKopgMIjT6Tzl6l3q5unnn+Rz5MIuZ7FMJhOhoaGaTJPM4jwej1Zyk35Pkm4u96M3K5TvQ1qNyJ962SL5eDmMHAgEtNJfa2urBtBRUVEadV722vQ296ejincd2j0Tq+/79op+6kGde0Qcd8M46FjbAFfnQPa9TOkNh399NSVpUH/11VTY7WRm24hphn6fwPI7vqRvAiiPwZHtEGWzUXCVHaXoZHmp4oUioXV3AqAXjzOOouXD2YQJJ+HsJA+mWsXA7Trg1f0wzMrCfIdQEX8bnPSB0mGQ9RZUjoLAVp7ywZQcmGYBXr0ePoMR+UBIBUVJEOODNccBN6RbYHgjnOgQPaa4L2CoFaYZQekLbQHRKip2wDvdYJQLQtLBXQ6DyjkJTp1RA/ylGHhKvG9ln8i2OpZ2DveOF68zsVP1gVWjxDxVymo42g1utYgLgvxLuY/tcCNi5V8JrD7IShZTxBC43wclcPGybbC+EjJzWLj+Q5asbWZDxJ8h6gBcAWxFqJ33jiUp18bgxh9PUUIC1Nlu3zcURUlFSHg9f67POS8yqPb2dj799FNqa2spLy/H4/FoGnLSxBBOKpNLQJGZg35x1F/FK4qCz+dDUYSHU2xsLAkJCXi9Xm3+R/aN3G43ubm5JCUlERISos0EhYSEkJiYqGUlERERmo9SW1sbTU1N2uItRVslWEnqvDwemf1JV2ApMWQ2m/F4PBqtvaWlBYvFgs/n01iNsjQpKeYej+eUzMnj8WigK49RAmNTUxMGgwGz2YzD4SA+Pp7Y2FiioqJwu90axV26EGdmZtLY2EhlZSU+nw+Xy6Ux/GSfC9DKqHp7FOBr2ZTcpg995nSuWZQ+I/wpzh7+zCjonkP9eAjEiXGhIrsd5oI6dy79zDaKnXM5VmYHhwNLznim18GID+3YS8WiZJsUC6VfwiU3wQdx2Ad9BOkD4FgkbF0JTGM+n/PU9Bg2rcqG25sAh5jy/Wt/ocTw8whY+yGziq9kyrzPWHPLpfDAHiBEZCBhWXDdKCwGWLMLigZA/1vfYIwXfH4YcikMiELYhoxD0MsbgffTafhFBQf7g9sCxk+gYhwEy8GVLJSFcMDkKujZDfr64E9Z0FwHkX1s7Nex3HLs8HY/mLwDTgSgKQhxTiAaitLBlAO3mOFfDrgrC9aGbMW8BYFsuTmw9jW4PQFyrTxTMgBGt0KNhUWVG3gHMzvzNrGg8AMOs58cby/mRl1NnHcYTXNLmbUpBzww9xiQCbz6LnS7BsaNADukb3gWe/bFXzu/Nls4dvv3d+CV/JNziLMagZ4llgEPq6oaPNfS/nkBUB6Ph61bt1JfX09DQ4NW1pJqDHoChFwQ9RlLV+YanEpxbm9v1zyjIiMjNe+pbt26aSQDs9lM3759MZlMmlyQ1OnTKzhI5pu+5+VyuWhra9P6SnDS5FBSxPVCtpGRkZpnk94bSrL+UlNTNbsPOVMle0WyF6SXPvL5fFp/S27Tq2nI58uemTxei8VC9ig23gAAIABJREFUMBgkLS0NgOrqag4dOkRGRgYDBw4kMzOTffv2EQgEcDqdtLa2Ultbi8fjwel0anNcPp9PAxl9ea/rRYP+Z1cG308lvh8hIvfT0RO+LLPT65iNotdPMerVmu62sq3geQO71Y66zQb/Y6Og90hYtozi9Tl459uhxi5mg4CWKyDm8zbwT2Muf2YO/cljBoWe14AUmArz5rzPcyRSO20obE7GnN+MkxzW/GM3KHXQegeYX4feq8UiXwXpPaHYCWlOGB4KA4oQK2c64jI/HdIN8EbfTiPGURW8HAVPHYQTyTBtnHh4YW/4qwGec0JaHYT3A/VTUMfBI1/B4QshEhi8yAa/hvZk+LQ/jGyGtlrwWSG8OzQ1QHE2pLbAV7HwdjMkdraZzckIyaRUhM/xrpvhxXdhZV/Glhxk090meHYgM0kVihiFR1BQ8AoaJHgd3MdM5hXmkDT2VYx0cDctvMRfKHFnoVRuhdc+YvbgBdgRDsXprxehLhxAwbpOGaQfAJy0OLuyI3QagX6PV7EBr3X+7ycAkxRFaVdV9a0zPeG8AKhgMKipkcvSnewt6UMSAOQieKbBUP2iLBdy+TqBQEArY0kygSy36RdYOVQLJwVKg8HgKUAg75cZl5yxkvtob2/HYDBoACRLdBKI9P0cWbaUJTx9nykyMlIzHzSZTASDQW2+SpYH9WW2qKioUwR05fuVrDyZKUlJp/r6ejIyMlBVlaKiImpqakhMTCQuLo6+ffvS0dGBw+FAVVWOHz+O2+3G4XBQXS0MZGVWKEuS+qxI7yElmYr6bfI8nWv8BFDfItqz+JJ1GG02DtntQukbRLmoHZT6UdjXxXDgvfdwd2YTBb3s2B6KxT5WDH16O7c3X2Qj9kvx+0QVSlyQ+/5s5jKMOK7GSyIsgmk8T+bqC5gp7HphcAeMMeHcHMtjLGXxnR0wvxuk7oFAg6CtRwM7r2Bhzw2MzwWzBYqCiEVzHCy3wvSXIf02qHDDkAqgOxAOTxXCgR7QfZ+wtV//EdxzOXwA3GOBrE9A3Ql8KJR2+/1BvCcvUAAMCrXhs8KwI1CZAgkvQoSr04q9HIbabKxQYUAH/C4WDnjA1ArpexFSUamAG0rGQu6ma+COrWy6fKSwu1wNTOtP2fgvIN/FLEYDoznEHuZjRyGMPIZQC9xOI68Rx5U8QMkvB8DUUh5ZbeLJm0tp43M2rX0NaqNRnnyTbNshytpuEdqBEcBbpdiv+fYKElqoCJHeHzlUVb1A/q4oyksIO5kzghOcJwDlcrk4cuSIRh3XA4XMBOCkqKx+Me4KWnr2mCw9qaqqDdYGg0FaWloICQnBarWiqiqZmZlkZmZq4NHU1ISiKNoCLsta0rxP9nrk/JMMh8NBXFyclsXITAugsbFRAwqr1YrBYNB6V5JkYDQatffr9/u1rEqCo5xNkqaFiqIQGxurDfNKhqPb7T5lzik0NBSPx6OpXsjP6Pjx45jNZrxeLyEhIWRnZxMSEkJTUxM7d+4EBNVdVVWtjJmRkUEwGKSqqors7GySk5MBAT5SoUJmwY2Njfj9fpxOpwZeMvP8rqW6n0p85x65seVE2mwa+ACYbTaUQ9BiAXXCVgKvQfHrQDHY9s9EXboB+2nM8z5SYErn78sL7FxhOwRv38JjmFlMPdOZxdzKHGL5GzOnjWXAyu0UcQED7tlJNCrd5CX62n2QcjdUvwYcFyAUD+ljNjBZuKUz0QAD3ECqKLXVeoCh8HIHjCkEy3BodSNKfQOgjwceHApPNcKW8YJZv2IT2NtgYQQ8UghhV0PSU8AMiLPZkNN8bULsAVci9HgHXL8D05PA3r0wcCBFdjuTFRsJh2B0ObReATFH4eNRcJcidGqL3ZBbggCsj38BOQtgwihB7z8MtA4S73WSgbHrP2dT1Ej6ej9jzfLx3Dh9N0dRWEccVdzPM9QzjMvYsbqBJxnGWD6nnlDG5rcxineZN+MabuM95tYAj5TCvV98P3ACAVD+77cL0BT6RyNKgZXA4wgNeVRVPee+kz7OC4Dy+/0aM0829vXlIH221LXfpL9PD2TSylxmSbGxsaSlpeFyubRZJ+lIm5qaSlJSEh6Ph6amJkJCQjCbzRgMBq2vJPtJsszm8/m07ERVVS2jkdmRJDfIEp3sG8msy+PxaIu/XiFCGv/JbE+aFErCgqS5ywxP2n8AWtYkZ7Tk5ySPVYKMzGD0JoOtra1a6VH23iR7T76OdBdWVZWqqiqNii6BVIKRnLNqa2vD7XbjdDpPYfR9X4LET3FuEebpQ///PQBuGwW/SIW33yYUsDvtxGy14dwHh3x20dsB7H0XUfDSqYLpxYNtDFRgig7kBrfZ+BS48WerWcxU5vJnvHiJI5FywkhauYui1ang6UbiPUfYhBUzXt5dMRncU0RJzHGzsMJIh/QIeMMPQxxAEB66AI4bobgYyIE+YUAuZLkBJ7zdAZ8bYeVgmAj8uRyiwuHjOEhzw5gmuG8KDCkB9Z/gHwGtPcHXAooBSpxwwXzw/RIMn4DjOjhiAsNIyM+A55YAKTNgyxbYsgUrEGUBtQHMdsAHCW1QUQWEw5QMWONBZDSWGfDrUdB0BNJ6kF25g7JrhgFhsL6cUTSzyVvJeqKYO/09/sqVxPAwV/EbnozaAd6DjOcgeawjFSGW/TipwA1k8QJpy8Yyl2PMzfwzc9fuBv/H2Fpvw24R5yfPYKPQ9x3mpX6A6z719Ar9Z3rsHefyuPMCoKTyAgiQ0VtRAKcAliwbnWnORu9AC2geSHl5eURHR2tzVbLkBdCnTx8CgQDl5eU0NzdrvSQ5ICszIQl8koDQ0dGhZUFRUVGYzWZtAFcO5uqFVuXvkgouj8Pr9WrDsBIY9ew4CUx6QoL8zHw+n0bEMBqNOJ1OjcXncrkAtNkrmYEpiqIRKzweDxERETgcDurr6+nevTs9evSgZ8+eGjVdPlf2yySRomfPnqfc3717d5xOJ+Xl5TQ0NNDY2Ijb7aapqemU7Ph0s1PnCjw/ZVDfLr68BVS7XZScAEcn0NgH2jnUuY4NrrXBMih4QmyIstnwjhzJtq2fM/2mUk3jLdxmI2C3Czfd9cD/jGBuyZ8JEMCMGS9ucmlizbDrYOoReCyETcNGwo4cnP/8GNSHIXIqGL6kZTCE+cBYDZYsmBMBUwbDmgIYfSEUvwS7B4p5X5qAo1DZaSdlq4Qx5TDxUnjmIFzUW5QcE+oFDXxaBiysB/U22LgKJiiwHLjJAYGDgkDR+gC0RkO3SyE2XvSonL3gAz9c4IYOl4svAUaP5tDGjUxMHg9WCNk3ClQ3g8xfit5ZELZlIDKlS4CPfg9/GgHP94A7O+AemHfv+xzDyG4i+ZB4HmcPBgwsJok7cLGLhahUMdP7JkeI5xilNFJPLPGUcgDBnHibF0ljIQ8xi9/iw8cj+ce4mdW06y4eIvYvxZ79Lb8kHfwgGdSPEecFQMGZ9dr0gCT7OpIk0bVU1LUkKAkFCQkJWlYjsyO52MoFXy6g8nlSXkhq28m5JkDrHbW3t+N2uzXvp7a2Nq3kpzf9k1qDssckZ5zgJPNNDsBKIAI0FQlJspBEDfl4Wbr0+XyaBb3P59PAS4KiZDNKZXX9cenLlS6XS1PTSE9P10BeCtJK0kd7eztWqxW/38+JE8IANicnR8vkpEdWZWUlLS0t2jGdDpy+bUb0Uwb1LSLqgACns0RBkh2eOPl3Si2UVixjRAHYHzlZPgrY7djSbaAAaaVQeYS5/A/X8BLvLh0Fj19JtXcL83dsZA6jYbEDgDgSaXolG+64DtzL2BoGq5LhvvWItRe4Gbj9X8AAULYCu2DIVlg1Dm7bBpdcD1YvBIIQbgCy4IN/wZgboLgVcj8BNRQYLYgS/68K7H+HCU1QFA399sPDg6HFCj/vgJ+FQGnnW1O/ACrB/BKov4a9F8FXAG+9BQsXMvgT+FcplI+C7YatDH8TFqTCdXEIksZhxFzUWrD8HFpf3w/TX4KwSymLG4ba9B4vMhIIg6Ww86F2wEESZTwzewwsaGAn0YipYxcPM4hs3MzjAkSOaALaeYy3cRILfzvAk0cjsF/fTHsXvyh79thz+mp8Lc7T677zYg5KLpiSIKGnE+spyF3LfLJsJHs4UrBV+ip1796d4cOHc/nll2O1WmloaADAbDZjMplobW3VDBFbW1tpa2vDYDBo/SMJFBJM9Np48lhkFiNtP1pbW7X7JQgAmkW8LAnK+yUJIjExkYSEBG12S2/bIbMoWfaTg7sSVDweDy0tLafYtctyo6qqtLS0aD0uCZzy/UlWn2Q3FhQUsGXLFg4ePKhJPFVUVNDY2Eh1dTUGg4G4uDjMZjPl5eUaWEu6fU1NDYcOHaK0tJTa2lpaW1tPGeqVx6Y/t9/2u/LTHNQ5hrcPtmQboeeoal0xWDyutGgjtvVCScW2IZbQfjZsNkV4Fn26nDFMgsocxMCOEAS4+KFtzPS+yYtjRhNKEJ4O4z72ANDE53DHDki7jd2/+JKRr8C9hdBwFUzsBwuBFBWm3ABUwJvWzgNyC6p7/+thmxsG1EK4EQ6Y4MEMYCBsC4LTIejley+Hfhb44FWwvA9D9gJW4Qb78GC4zQv3+mCMHz71QcJ2oXnXYYH+t0HlX6CyPwwshIHDYfA/FzJ4Kniy4YtsSGgWg8G7r4NZ20SZ7yk/vNlTHCvJ0NoK+O8Wx69GMLbpc+aTDGvfBvbB3wDaYUYCtfSEBe0QlwCLBiIskJNZEjWWeXnXQFx/mG2CRXAN21kcdQNLZoxF7dmHmYvf/B5fjC6hInqBZ7v9B+K8ACj4+mLVlaas7zfJRVFmHZKpJ4dL4+Li6NOnDxdeeCE5OTlYLBatQW80GomJidEMB6WIqsfj0ezd5X36XpLBYNAyFklaMJlMmEwmzfhQZi56Ojyc9HaSGYm0f5d9MtnDkeVHSVqIjIzUrDokqEiihsz4JJhJlqAEJjkPJbNAyaCDk0O78rjCwsI0AVpAA1qZIUrfq64ZbUxMDNHR0ZjNZo2IERoaitPp1Hp9pyvJyf18F3D6Sero24W9xk7wdFnUz36GQQdctstjSS/ofJzVin1SM7bDNuwXH2XQu0/AzsGMCv+EWfkBLuda4F+MZRUQxgh8jMYn9PhGwkwuAw88Qx/mY4dnw6AtBSpfYMhuOHgjPJYHCZ/A+pVwVTFMKII1h6FiCExeC8svB66E6S/AMpWTlu2hQsj1qeOwPQNwQ8AIrjAoN8CXBxFWIePQZJFynJDvF/p7mW6YZgBDBwQyITvLxqYLYRLQrRqsDmAWguAwD+pWgzEOJlRATRywBXo4QOkB3VuB3WLOineAE7PhQyAbcK4AbxqjaOZBjsLeG2B+f1GLxMU1y7YC7cA+0a+a2cDF1EGaifnejYwt/Jykpl2wYB8zZ77Ju+TCc02ULMhBuQwm20d/7ZQOvuM7MsBVxDDU2W7/gThvSnz6JnrXK2xJp5bgJBd+SdWWenExMTGkp6drPkjR0dE0NjbS3NxMQkICSUlJ5OTk4HQ6OXz4MOHh4URFRVFaWorbLeYToqKiaGlp0UBJqoEHg0F8Pp9GHpClRqld19HRoYm2SgDRMwvlIK/M9NxuNzExMdp7lgxD+RqSMOLxeHC73VitVo0aL/2dZOhnw0JCQjR7d0lzl6AmyQqSFKH/7CXzLzU1lUOHDnH06FH8fj8JCQkYjUbcbremaWg0GjW1DafTSUVFBZGRkTQ1NfHVV1+xf/9+DeBOd567ZsTf9nvyU3y/WDnYxrS37fgAdYAN217gLzD4ECghD4DqZuovQmHtSmz5F3BNUyV1rKYbFbTTzqO5E7ivZDPP5I6BNHhl8wmKCafjCRsPP7qJJTeOhZnlQBZzVnWA8hum3LqBNa8v58Ag6J0JtzdAwd//DoMHclF/G+oaIAsqk4ErBU18awiMGiLAARB9ntjO31theAQ8mAwtTng6Gqa2Q5sZQVsvAq4SNhFxTqgPEQLpymBorQLzo3DkOcg5BMQJdaOnesM04P63oPfFsO8mGHALOKvAtBH2/gLSx8FioKkRTE6I6I1w400FWCAyjcqlcPlDsHk4H7Kaa2hl7OLPGYMTHz4WMYRjPAtjXmPq5lWkkslmUqgnhHmV7/MEjzCTpxgLzOLnBFkCXAKTINd8ZhuNgtOwL885/kMZ0tnivAGo0/Wg9ESIrpmTvPKXUjz60pPJZNJIACDKa5KFJ9lmElC8Xi9OpxNFUYiOjsbv9xMbG6u9jiRESGCSv8usQZbMZFnQaDRq5ISQkBDNV0qCVFd1cJPJREREBC0tQkxEZneyBybByGQyaaAoQc7n8xEZGXnKMLD8/GTvDNAMCaUShLSAl/NmErzCwsKwWCyYzWZaWloICwvDahX1ltbWVk18VpZLi4uLtbJiIBBg3759FBUVaR5XehWJrsDyXUHqJ4D6/jGtM1Ma3Ghjf6SYB2qtBGXbS6iZd6D8pZTVaz8E3OQ2XcO7LOA+monHTQfhLCz5kEU8CCWvMreknDDCUFGZ/aiLJcTB+3AjL9OTfixuuAFiy1mzFg5cPZ0+G6GjQbSeDg0cCMuWoawA1xQw7ewUaPVB+vvwQTTCbLEAISR7Ig7ymoRdvQ9GJMNTe2HEQHjQBbnHxPY3B8NTGfDHgJArWhMNiaGw/FpBlQ8tF+CU1ALKfTB+FhwdJUp4pqsQzsP3iYFhpw8iPECWyNBe7hDCs3FuofGHET6OhLCRMKZVvD7RD8H790DWCnb+zcbO6REwHTYtccFrZVCcRqH/NXgDVnM3SRzmKjy8OHU0j6+uZCbz6SCMOQzjYlZjpAVe2IP6/CAxn/VDhyzxnYdxXpT49IuOzJj04qmShCBVwM1mMzExMSQlJdGjRw8mTJhAfn4+t956KxdddJEGEh6Ph8zMTC688EKGDx9Oeno6jY2NOJ1ObQH2eDwaNVxmPEajURvclWAmF1RJq5bHGh4ers1Yyf6SwWAgJiYGo9FIRkYGkZGRp5Ah5ONlic/j8WglOckSDAsL08A2NTX1FAq7VE+PiIjQjl/OUwFa2U9PxOiq3CCp4LIcKenusbGxpKam4nK5qK2tpaamBpfLpc1byfcYHh6ufY7SsmT79u1UVlZqZU4ZXcV89cfxbcp9P1SJT1GUFxVFqVMUZZ9u21xFUaoURdnbeZuku+9RRVGOKIpySFGUK3Tbr+zcdkRRlEfO+sLnUfRKtKGMhrhmsB0Dy2Eg/w4UeynEw6J8BfLvp4T9wA2sxchyFrKC7vhpw8tunuAEHxDHrLwraacdVkTDjIHg3SvA6R9jIL4OovOhN/R5D6ZcC8ofhVAtADNmUHwPYpB4FthuhgUWODAGLGMQWZMZsYBe2wTHXoJQmNYbttUBvYXTRUMkEA8VuaJkuHWvKPu1Itx21c/F4wDuz4KMSgh3w8vbQBkPWW/CjnSo2Qr7JsDGXwmWYXQTFP1qJPuGw2vA6Ndg0GHoqIfF3eCET5QOj4cgVtM9QBH481bQbwyQ3wf+Vtb5Xk0Q0iQAN+8w5EI2B6nNG8qLuaOhBMycYBGD2MFGoIZxnGD2G79j4l2DKLjqm8HJVnbku30ZzuMS33kBUHIwt6tkUVcKsgQrg8FAYmIiffv2ZdCgQQwfPpxLLrmE9PR0fD6ftqj379+fnJwcYmJiCA0N1cpYclGWV/7R0dFadmMwGLSZJmmZ4ff7aWxs1LTn9GU7+LrUkgQTmfXo34scptX3mCQwSbNDuX9JV9dniZIRJ58jh5dltqgHI0kNlyAgnXb1g7cS3ORnIckUstcmHyOPQWZeLpdLo8RLkoZ8fleljzOBj77cd66Z0Q9EkniJ09sCPK2q6sDO2/rOY++LIJn163zOc4qihCrCNuBZBM2qL/Dzzsf+V8ShejtEgtENaiVQD/NYzoDfbse8bDetnRZ1os90CIAHWUDtw0OZj8DotzCyc/YIiId5cdfAPftZtGwDzB9IKYlQHQcdd9BvygLS84BhnZpvw6DnvYDDATNm0K/TOejox8Af4M4AXB4Nq0B86sNh4rWwxwJk38GDBqF+hAN4FSp2wfA6oBXSP4HiHGg3wEAH3F4qTlDDcEE1f2UvLGqGyGRY21OQMNzVoNwMEzyQ/CXcEwVDa+GNDAjtC9lvfU7/v8LKGgFmZEBIFvzCB91LxbzV7T7gY8D1NFQ/TcS+2RSXA29cBG0J5C25mYeXbYKFo6EJZt5SDD3hVzihcC9TSj6DHUe4n2pgHD3pC1zBYYp57PqlfDC89Kzn1J7d47t9GX4iSXxz6K+i9WAkt+lLebLUFhUVRWJiIhaLhYiICK1Ho++XAFoprKqqCpfLRVVVFbW1tbS3t2OxWDTygAQKCQwyC5AlQVUVWnbSdVdmLFI1wuv1asO4cpGHk1mCLCPKcpwsIcqBW1kO1A/aSvUFOasky3QSnKRquuwN6dmIehNBRVG0oWS9N5Z8LfmZh4eH09DQoH2OUr5IlinT0tIwGAx4vV5KSkoIBALExsbidrs5evQoTqdTA0oZ+vPYNb4rzfz7ApSqqp8hpmvOJX4GvKaqapuqqkeBI8DQztsRVVXLVFX1Iy6wf/at3sy/IWxlQhHElmujV2KXJvor92D54nWU50vh9VIeXzWIfBxcx2dYsAA7GUED4KOWbryFET6AOWyAxwzsHDbi5PzMI8DaambOuAIKYc2KkZCQA8mHKH71Ht7wA+WwbTsolaD8HgbFj8e29XPsBWLA9IINoKTAL8PF4O5kP3RUAMcFM2/QQaBK0LpnlwJW4FroNxSaw6FfT5g2Ga41CAPDciM4w2Ef8Hms6DO5E2FpLEy0CvD6ArgxC1ZFAAFQLoJtDoiJEyoRREDsTnDcCjcng6WbOAaPAwY1ItQjkhEsviuB1vvhovvB9ZIYgA7WQ8QCCnmeJXFjua9wMzTCdhJhWTl+/IzFxZq4S7mYOuZzBXP4ExZimM8K3mASi6feAA9sESzKLpGb+gOpnHecw+0/EOcFQMHXBUWlmoIECQkQctanubmZ8vJyjh8/Tn19PcePH8flctHe3k5sbCyZmZnEx8drGYMkHciejcFgwGq1avNBcq5ILv5tbW2aMGpoaCgGgwGj0ahlEZLNJgFM0smlaaAUltX3YqRkkiwLyvcowUTOEUkqubR0lyAkWYJ68oHMpsxms1YCBbTZKDnnJLM9qR4hHXfl4+Rwrzzmbt26ER0drfW5EhIScDqd7N69m71791JbW4vZbMblclFQUEBpaenXdPi6ntuuIHWm7d8UPzKL73eKohR2lgBlOz6VU8WeKzu3nWn7eRVSBdteYhdZE2Cz2rDtjiXYZwWq6yZYmQOTJsHAUcymD33JY+b8KwAHX7KDiykEHJQTBoVHmM9lsLgGHviI+Us2wkhgOVyTHyU+hXUOHr/nfVAixcI2eQVDymDPUNh8MTyYD6tyIDQbRiB6OqEBUEYDeyAGGPJyHBU+CElEfKpDgRRgMIKUkIgAqCooXgl7E8TzLgH21cCrITDEA/u6i2xrsl9sV4JwfUAM5BIvnrOyFS7yin3tjobNFqAexlXBAkCZBLEecazpwIh+EB2PyOBqQN0AwQqo9wNqHNhnQ2IF5ALDKuDyN+BxK8yGuk6Rpd1EEkIDDUQzhBOQBvG8Qwj7mM8DzOcBwlF5iHK45kM233A3w8IF69B2+G/a+S2p+gF6UlLq6Gy3/0CcFaDOUK+PUxTlY0VRSjp/xnZuVxRFWd5Zky9UFOWicz2Q0zXN9b9LarcELEBTS5Dg5fP5NOq19DSSFHBZqtIP/MqynsxmZBYk9yVJAcApvk56vydZqpPg4Pf7tVKcXjldltBk+UvS1+GkbQWgzXFJGrgkU8iF/3Tb5WchF2e32629FzkzJTO1/8/em8dHVZ/t/+8z2WYm+x6WsCSERRbBDKtQBbUKFhW1oI9FrFq0i9TlqbixCOJSH1sf7AYuD4ptBa0bCrUooCDrCUsgJBACgQTIOplMMpnJNuf3xyf34SSNElz6pf35eb3ymuScM3O2yec+131f93VJ2i4QCJj1K7nOwgYU00RR0dDampA9Ho+ZYuzZsyeBQICqqioqKiraETQkzQf//ODR8Z6fS3DqCnpq20+Spmm65Wd2Fz7+j0Am6pn4NPCcHGZnh/Ily7s8/hX/W66wf37C1j06+sgafjoctBmwMRxIOwT/UwS08DDdmDj/HuBKRjGe6/AxFD+RBHmCI0xkHmBn6nQHIbRy++JNUBogjp3w1l7IiiNAJGiRKjVUDXgh1w4TK5Th4Cwf8KEyos1yKCt2SoDLYOufYfKdbiXIuhf4BHVnGlD1qBRgVQSsQZEohsLED9Tbp9TAkDRY9jYYh2HMepjnUXJKG9JU2s6VD6cboPmEatrdEANDNTDyoDQc/mSDd3pA9CGl4zcOKElQn5+Xq/K9M+JQGoI9UH20QNKbsOtWN1yyWKGpHmob8oDBn6vjB/gZ+NAIEsULCRN5ZswPseXqRDOFZIL0pDdzeZGHV3u5Ub8MPWM00Xt0jANwtFiHXzzYlVvf9SFisf+mCGoF/5yvfwj4xDCMLNTXRwrEk1HPDVkoxuYfz+VgZMKyPg1L3URSWG63m6qqKk6fPk1paSnHjh3j4MGDHDlyBI/HQ2xsLNHR0ZSVleF2u007jcTERHO5pMAMwyA2NtbU3JP6SkREhOmRlJKSQkREBI2NjZw+fZpTp06Zk7GkygKBgKn0IA674qIrgSskJIS4uDjTh0kQVGhoKLGxse0MAQWBCZFCiAkyyQtZQmuji4vdhsg8yWdbfaHEnVhQlbX243a78Xq9Jor0+/2mdJFIRYkUUmVlpSmvVFFRQV5eXjuiRkeSi/lFs3X+VTvXFF8XEVSVYRguy89ZPWsMwyg3DKPVMIwgqp1yVNuqUtpKHm2jJ6rG/0XLz2Ws4Fv+39Kbv/gJe3aOjl6gE71HV30/k38Nrzp5lEJFdiStAAAgAElEQVQ2vryEBTwPQIAA11DG1fhpopGN/JzRHATgZWLJpJEM9rKSXwJJ2Ap1nuEnULpLBZYCYD/MWodKh6XBrjBYfDNMK4PBITB2HaRnAs1w+mpY9z4wCtxi6/4+0AdiYoDPgKmN0B1+ZUfVqcZASRGEN8KhIvh4Gnj6oFqNvFDSpEgSa4HQAmUuHLod1tpgVrWy8ai6Ai6phifqYYwSwWD7BfDnOrX+mQpYPEylCgEaPSoNeGQS2Jrg3dmQvR92JUBMeBuisgNVf4TCi2F8JpXY4D7F8mXKQHAHmLH9My4lwCq+R/lzoyhlLc/cOwmINhumAXIDOq4KF/o/zqh72LvYhP2l498ZQX1Bvv5a2mqYba/XWZa/ZqixHYjTNK1bVw7EOgF3TA8JegoEAmb6S2R5PB4PBQUFHDx40Ez5lZSUtBMpFYsJQRmi7C31F5E4sk6yonYu1HNBZmFhYfj9/nb2GYKo4AxhQlJmISEhZgOslRwhAUYadK36g4LqrAQKUYEQ5NfY2NiuJ0xQZUxMjFkDE3KDsA3leETlXBCVBOZgMGj2Y8l5CKIS9Gil34uvVMf71dm97Li84/quIqlviCTxT6PD93QaqnQBamq8SdO0CE3T+qICxE5gF5ClaVpfTdPCUQ/W75/LPv9V/1tdGbUzQH/yc/TBDn7Q9N8QiOHxX09l4epQbNhYwmQ87GYPCTBzIDsc41jDUI5OGcOjc6/k6B/HwItBIJQgA4EiGLRC2aMnA1fDuMlAk4quIwvhTg/sj4W8ncAweD8AMYmKfffONYoQFz9Q1ZhIBt4Hr7D6vEA23N6A2kclFKbC5DRwXAeXHISIOnjtGqXN561UTxNDAO/34MBU0G6BZ4uBSMitUIKxvjDltTggDtgLrqPQtwl+FQ6bUuDn1bCvGlY1QUQO5FUrBqGWBtfmgG04jFx9PV4vJL+pjpkLfwppXihfCsAMdhPMcjFp7RbAwy7CKSaUGXwGD8AUFsKsTIweP4WMhXDvvbhcDtJdLvSU9g8cgW+Kdn6eIqiv2geVahjGaQDDME5rmpbStvyL8vKnz/aBXzRBdUz9SXpObDNkkiwrKyMYDJKWlmaqo9tsNhwOB+Hh4e2aWcPDw6mvr8fr9ZKcnExNTY3ZxyQUbmlwFbJFaGgo3bt3x2az4XQ6zaZcmciF9SZEDkEpFRUVZg1LEI7RRtMW9XE5JsBEO9XV1SQnJ5tBzOv1mooPUidqbm4mNja23cQsQcZoYwJKABT7DZFykqAsLDwRkhX6uc1mIz4+3tyurKzMDMh2u53KykqOHz9OfX19p/1OHQNTR1RlXX8uZImvGoCsQ+vcFuBSTdOGo54ni4G72vaXp2naapSdUAvwc8MwWts+5xcorZ8Q4BXDMPK+9sF9g/9b+S35Xd5poWWiC8vV0UfXKCPD6ZOoYhdzWcMzix5g7vw3GbzyLZ5edKNy9nuyDJxpCnO6GyBL2a+kFu6k3P8hxMO4YUqS6GKgNly5oI8bDJcDf2qBGaNgVS60dAdvLmQPg7IiJS/k367qRFSikFIOcB3sCcKPwmHQXqAICEJWMnhrgR+rWpPjc7h1DHy/EK7qoeSSthbDgcHwxoOw/hmgN0S1QNwWGHAJxBUD2VD7IGi/hhIvUAZzwqAgGhKiVQMxx4EJsCsa/h4Gp2NgRzd1fJtveptNoTBvIHDyLnXMjj/Bxw8yjndx4GDV7bDh4HimrtzMBTRjx0c44QxkDc2MZO2bT1P3s0yMhSvRZoL+vJ8SvoUeKPj/VR9Ul/PymqbNlhpB29/Wdf80aVnrMNaaiZAURA9PUIUw1sSVVogJVuFTK3nB6XQSFhZmmhFKXUvqXFYBWanRCGlBApKsl6Aj6E/SeGLIKAhIVMityFCCqdS4mpqazDqY7EdQjFhvCJtQ0qNWIoSch+gMWi0/BJFJKtCqaiGoUI7NKrMkKU5rj1iHe9suaHZsuLaipnOtQX0TJAnDMG42DKObYRhhhmH0NAzjZcMwZhqGMdQwjGGGYVwjQaJt+yWGYWQahjHAMIx1luVrDcPo37ZuSed7+8ZGl/63rP9XaXVpX2lHI0La0kYZ98GrXv7Mw4Rgg/llPMNDPM1c5s9/j0ee/BszOMyMtz4DPyxmGxQWQ+ERvs9mcMyDg0Vs/QewQtEc88pUrnKZH/K2wZ5Q2ApwElaHA4XgDYAzDuo1OJmqepoYiKrn9AAqYUQxvNQMs0cB02DPDWDosKM7vHY/BC6E4DDgb5D2igpOwQLwhylZI8bDm5riMLRo8O71EH8IPC7Y1QRbngQ+UWiOPfMYF6PsPsaFw/j3Ib8blMRBaFBB7dvj4PkwZVe/JxQubwYjADNuXgbZyyB0OIyAJ268jkdfHgsPl0EirHFM4BnGUUI0jy64kgJieXJ1JAz/O4evGsK+9UDEBGZlu2Dhwq90P886/gP7oMolvdD2WtG2vMt5ecMwlkuNANrbKFgDVMcUkDVwiRKC1+ulqqqKvXv3kpuba1Ktq6urOXjwIPv27TOVGi688EIyMjLQNI2amhqTcCCBwGazmcGtoaGBiooKTp8+TXl5uRlYvF4vHo/HTKsJyUEIBxIYm5qacDgcppKDUM+FGRgMBomIiCA6OpqwsDBT6SI6OprU1FQzlSaBTNJsfr/fpJtLilJqcz6fz0wXynLxpPL5fDgcjnYMP6kfWfuzhKEodiPipisKG3a7ndTUVLOeJtdQ3ivoTYaVMNFZms96n882vq0U33k0vtb/lvX/Kj4+HlasaLc+e7zrTACyDFfkmWV7WnWyerjIHwT6YAdZ/IZQQnmK/SxiGdG8QStBnkQxBPvQQrR/F/PIAkcfeKQfK/kD3JQCSSfg1EUQjKDkMMxOg1/7IdMJR8bBHB+UfAIMg/s9UHsxzLDDuESFtN6IgteHo8gQ1VCXDjE9ADuM9cJyj1JyGD5J9ShdUQnj6oHj8NPhUOCCuhlgLIO7s+HF/iqgFE9U/VbR22FlqGLsFQyH4344GA7jt8K4y8ATBsemLOYmoMUGn2+A2Ouh/2EodsKIMFWz+mAvrCqDIetgXI5OWK5OTqLOG0NhaX9gwk8h8RMlk14dA0TBBuAumITOhzihGVbRn8XTDYzEn+NaeIALPwJ9yG95NUdn3poP1D08qe6Vq+B/u/ylOuv4D+uDeh+Y1fb7LEy3Gd4Hbm1jHI0Baq1Pol96IG2TG9Dpk3fHYU0NCfOuoaGB/Px8CgoKzLqPIKj9+/dTXFxMSEiI6Xrr9/vN7aQ2ZEVOtbW1/2RP7nQ62zXUSmOseDxZa2aASU0HTKKHPOnLfqQGJT1ZQpLQLE26sg8JHHKcgoLkWKxMPThTV5N1IsMk1HNJl1o1BK21LUlxSpARJCUmitKHJg8VVlPCzoIVnButvLP7/h8eoL7Z/63rrmv3Z84WnT2tOq7q9kFK9+l0txTcCz98CV++jivSxTZ9Jou4n4dJZwVR1NGXMMJgSk8G4eWZl8ZQR194rh/R/l2qXvRIESxKg8AN8F+7IaIRYzssc8CQjeD4FCJqYUYkbL4EaFa1nNhkuLe5Lb+KSu/NalLFuI19IXoXfNgCk/ug0n7AFW/Cls9U6u2YA5IaoCANlu2EhU44GQ/aLxSCexYVoPrmKmIG18DyPIhphp5VsNkOszygDYetARUEe5yAB2tgpxM0v3LzPdwfJmyF4F7od6tqDPa2QvOAM9e0t8tFcGXbU8Xfd8Gay3iqcD2PPvgOrN7DpNwt8Hw9yQRJ5TfYntR5gr3MmzkZ7fMiuAKcVzpxHVDwZbGI+drb7tnAX5719ndp/Ds36rbl67cBAzRNK9U07Q7gaeAKTdMKgSva/gZFkjmKamZ8EfjZ1z3AL5vMOqYABd0UFBSwfv16CgoK6NatG+np6QSDQaqrq02Cg9RXpLFWbMn9fr9p/CfBqHv37iQkJJiECElrifq41bxQUn6iIhEMBgkEAmbQEXKEBAA5D2v9S9CYBCvxX9I0zSRYSA1KpJGEeSi28hIgpbdKrDqMNoq7VRHD2qslyue1tbUmi7KmpsYMPoL86urqGDp0KJdffjkjRoygW7duJrFDzq0jAu4sdXuu6Olb7oP6l45v/X+roQHi4jpdpSf+cz2j+xsWC4fhw3Ed/RTdp7MbHWMH8MeBHB02BhxJ+HFyz9qN+HFy+507uYf98AHUPTWSx+/7EJ4sgPllEDZYHfUY0G8CvRYVKQoUM27VSYVgKmOVLcbkECUddOtWeKQFxjYpmaKMFthig9k3wIS1sG4npA+ExjJlfzHEDQPrVD2pJQxcH8OBofC7Ghh0BAqb4KNmKKmG3zRAbSbsugqM95XlhzcMSpNgzkYoscHsGKAY0hOhqC8kV8KsPGAk0AyD/Mow8eZs4G7Yf/JjDv/pMcJ2nLmEx3Ud21iYVgHY/wozMvkLUSpdev8ELqEWCLCLcK7nRwSJo5wIbl+5icfnfwix4H/9PRbPGovL2pD7+lnvPC7vObD7/p1TfF+Qr682DOMywzCy2l7dbdsahmH8vC0nP9QwjC5X9TqiJ/m9Y+qvs4J7Z6miuro63G63qVguVHHpT+ooeWRlzokoq2GcadyVV0Ezst7alyTLpa4jmn3SHGw9B0E9QmJoaGgwqeoSgCRgyTlFR0fjdDrNACD0eEFvgqYkcIkVSFJSkknSkLSgoDqr9p+gH2lUlsZiOJOW7N27N3379jVTjWJuOGTIEOLi4kySiFwP6zl3vNcdf+/K+E9CUN/2/5az9ni7v12uVhK+hJas90tv/3fGJQBk3+ji45HApZlwISzxf8SfeYIQSgilFh82kmmFUpjx8Ge8RQLMHoiNUnDMgc8KoQ5GVsKL4aD9Erb/WKk3tLax6y6KVzYWj7TAIB200TDBDf8TDkMmwYRTMO/ldIVGQoBE1UN1uLeqDcVtUmoRl8bDo/Hw7hSFyJLWA2mQFaoCH4mQeQyWpqn03bvTlZrEf/eAgR9AzWCIaYDlRcD2iyipUMhpdn/AC+NSAA8Yl6oG3zcehJxEnezyy+G668i7o/01zQnA4hTA9yY0PMf+345lEZdBaT0LuBBWb+HoojEsXPIDoA8vDJvIK/TjLRIYyuvM/VEx854tolJNJbzv+oycX559WhUL+C6Nf2cE9a8eX5TWEwIA8E8TkSABQRtNTU3U1NRw/PhxTp48abLoAoEAdXV1eDwekwhQU6N6CkRZobm52bTeiI6OJj4+vl1DrQSAiIgI4uLiiI2NNY9NhGAlUAQCAVNZAmjX4CvBTSZzITaItJE0BotlugQiISZYU4dSp7Lb7WaaUraXOpfVA0qCrKTv5BpKbUpqUKKk0djYyPHjxykrK8PpdJKenk6/fv1ITk42HXqjoqIYO3Ys48aNM5dLI7PcP+u+vur4TwpQ3/Zo6DbI/D17vAtWPoO7ja2XnfflT9iuwJn1OW/pXPEiSrh1QSaPrhhBFoPZxy5OcJQh+Jj/0jimFm7mTZzciJtJy7cQJE3pGsW/o9JSn93F8jefAw+MfTWBWdUQYod5/zeAEg+URsOEIzD7eyi+Yhys8kJeE4qpd1MJ89ahaOaZMKdYERyctVA8Gb5fDFvLYHmT6q+6qAK0wVAZBsZWGNSiCBDXDlbnNaocLj8BOfUqSB2YCvHFEFsNv8oELtoNH8KsjQr07RkBjxvKol77PfTUwZgB/gtdNN0CF7lcOAHXcBexLheJ/V24dJi3DYi5B+ofUP1mj0QBoTCmJ3Onx0Ar3P7oJsgKZXTuVqAn+2eO5UbcRNHI7Af/xC8S/g+XK5on6EFi/zP35sJOGrG/0jhPaebnVYCy1qE6poY6Q06dIamOqEv6nsT0T2jpgmqam5uJjo5up/hg/QxRGhf6tTWtJy63VrV1kVuShl9rTUiUKRobG81AIw25QLv+KCEvSFOxMPfEH0rSiWLxIQ3Bkl6MjIxspzghwU/qWta6EdAu5ShMRLnmtbW1ppafnIs4BIuIbUhICPHx8cTFxZGQkGAGwc4Ye52hpq4Glv+kFN+3PRzaGZr5vgDogx4x/84Z3PkTtitHTXi6Xa2/oA1x7b9L9SaRB9zmZjSXoHMrK7mWeasdEF3AmpkTCM5zseDeq9lAT5jdE2qvgnEPqu6x8GWk//ABxcj7kRtfHTAQZv/4EESDvRV8dpjnhdNxsDS87aAqgYthciQ09wDGAMWQnwIJDnD0hT7DwHkUTsWA8bFSkdBa4Z3BkFwLmy4FwuGycMUi/EUFxIyFC3pBxhHYUgGhBhAJnIBnV+yCnflKteIUeN98jhGH4Yo/b8TbCvSC1yaBbTBMWA8ROiwxoEc+FPohaw/0PQHsjoCD6dBSBJFvqkD95BGGsge2H+BFHoHHj5BOHRRW0YcWFrAGVmYSJMg8fkE8/VnFj4EBBB0ufhANc9rcj09d+LW+Imr8Ozfq/iuHtbh+tmHdxqozZ00vRUVFER8fT3NzMxUVFSYBICYmxmzcrampMRtiZRJvaWmhtraWpqYmc4IXVCQoRQKPoBxJhQldW4KN1+s161xWGrnUuwSxCc1c2IbBYLCd6Z/UjcTtNz4+3kz5CRoS+SQ5TlHJAMzG3erqajO4yjGKo6+kNCVYWS1CPB4P1dXVlJWV4fF4aGxsJCoqipSUFLKyssjIyCAjI4PLLruMhx9+mPvuu4/Ro0czaNAg4uLiTN8r+Wy5V18WtL7o+/EdgurisFzSlk4aOutGtH/6TuzvQs8+s51rsIuDuk5vl4tGXWfa/w2Amgnw+4FUkMQU/MzgFDx6KcwYpoLQG0AGRFMJywPQFK7amv86AUZCyZ8xG21zewAnYflJVXvqNxS8cWCPhW5hCkR562BcD6BYBZZgOFAGxMEgJ/T6CGrL4YVjsHecIjrcNQUCaYpyPq0AcMKoE4AHvBVKwbx3CvQ6BiWfw2fD4HcpsN6J6rUqGwDFCRAMVTNk+FNQuwS2FkHIG/AaYINZ7yvGIYkwLhvuroGIMMhyq32SBYT2AZsTeiyDuh9CNWRQxf5HxnI7Vbj5mMc4wONcwQK2sZtnWUkyAHnsAUeRUuUAbmQWw/w38QPtRbbeWoTLpdF79QoA4qzuyPu7ouxlGeex1NF5YVgoT9cdn34Fzcg2HZeL86ystwaquLg4unfvjt1up66ujqioKFpbW+nevbspT9TS0kJZWRnp6elmelBEZRMSEkyUERISQnNzs5kilNSYmBY6HA6zV6m1tRWHw2H2OwEm2UDUHCQFB7TrhxLWoEzeUqMSWw4RkHU6nWbDrlWPT0ZUVBQhISEEAgEzwLrd7nb6fVJnEzq6IEGprUktTlKm4mEVCASor683txV6vBA9oqOjGTZsGEOGDKFv3754PB727t1LXV0dpaWllJWVmSlY6V8T0dyujO8QUteHPzjoS9dH72kftKoPt/87PwiDjm5F//hjpmW74Mg7ED6Nube9yTNkkcDdNPMCXA1Ehyoax8LD8Of+1P12JNwH/LwAXrsSRnwEn8DSH8OcPKAVDqdAYx1cNFDJcGgHVJAYcxzIhc/HQkwr0AT5PcHTDBHRUNcK0+NgXQBe+z78GuXyXmuHOeGwfBssLxjA6ZRDkKEkPyJj1PmUOuCKALAH0scCiXCtTdXBXmoGXi6C+FwYvAmogPqlEDoHSIDUTPBOgJVF4DgIIUdYVX0fFMLvh8HaeCBS7W9IMTgagD6HVEAtTIeYJfDMEY4uGsPt8zfxyphLYXuAJxhPBntxE0UhbzIJnaPABVzIvf7XOMwPGcsl+PDRyEQc1MLKTHWTpoMKTZ+DywUvpcOdJWT3cZEz5Add650SBHUejvMCQXXlyVeetq228B0pzJIyE0sOQQ1SU7Gm72Ri7qjmLbUjIR10pGsHg0F8Ph+GYdDQ0GA28soEK5OuKDdYtQSFKBEIBEyb+LCwMNNBV+pFVnQjwc/n82G32810pFWlXSjrkuqTAASYFHwJILGxsWZAhDOmi+Hh4eZyCdISKEUWSRp8PR5PO3deQX9ynaQW17NnT1JSUhg8eDAZGRkMGDCA1NRUYmJiTHah3P9z/a58h6C6Nlyu2q/8Xl++jp4xDtfxRNIBI2caXA/P8BD0HM4cHqOOm7jn+Y1KaXx7gOhbaslYux3uK2A0W7mR1VD3Bzi0FKYplhzVSl1iVhlEDFRU8ik1wF7FwrN7IP9ChXT4RwK8q+pHA7wwuQc80EvJJS22wzLg715FHZ+3UaX4cANph+i2E1gPI+tUr9RAXTXn5gfBn6hULOij9p9XDGNXRMD1mWArhCvvUJYZnl+pHqy+boUimnbC7ScgsABq7gMPLL4FRvx1ALM+AULUOTTFtEl8TESl9a4ogZG3wttXQtoFvLLoUmzbdVi9C15ycjseXhgzESimmFDm8iKLGMDLDGItNzHvqck8nXUjAAsTfsAS/qCo/Chkxcw0WL0U7nyJRSwj5y393Bp7v0NQXzw61pE6Y31ZCRIdG0KtduoSnDIyMkhNTaWkpMQ0MYyPj8dut5tU62AwSFVVlYkEpKgvrDaRCBJVcml4jY2Npb6+3qR+W4ORz+ejtbWVpKSkdjWpyMhInE6nGZQkgAgTTmpHQl+XayKUdtmHBLCwsDDq6+tpamoyCR8SDMXu3ao3aLfb2zndRkREmPU1SVVKKlMCtqT95LpXVFQQFRVFVFQUDQ0NppqGBKTa2lrzYSAQCHDq1Cncbjc7duzA4/GQn59PeXl5OwLHuSKi7wJQ14fTnY+ux5p/u3JczLzrZ/xSv10teP55KC5Wrx3Hu+/iuu0JaIW6O6D+erjr2V8Bz7KEP/BoaTEBAtzOyyRSz6SfbmEDw/lvKnicVG6njDzCeYtXIekHQAisfwMuuAniYOvL6Yy7o4SXG2BQKbSkAAFICyhmenoIlPwD8v/LzaDT8GoMJLTVQip9kBwJFML6C2BpDJTkQu0giN2IQixDlYZf3j9UvEoogRnfgz9VQHyz2hdbFSFj+ecoP6fqg/DeBRCXpsSuLjsEn14JO4vVNWkphrgnYU0vmLQM4jfCJw9yaW9g7CHeGQiTyuBwAsQehsHfA/4M3AD8FSU/PLeIhYUfsPBeCD7iAlbDKScN+GB7PTOoYDBNNFLHXKoJI4xIInn4WeBGWFPYl8XudfyRZxUyBTZzFfwxEwKg6zpKcuNchgZEdGG7wDl+7tcf5xWC6kz6pjNFCSuKkiGTnah/JyQkmEw5p9NJz549ycrKIjIyEq/Xi9vtNllxVVVVZupLkIIEEGsfk8PhIDY2lvj4eFOBXKjqgloEQVmtNQSNWenkQDs9PAk61msixyBMQDkGCSJWqxBxBZb+K6mRCenCyiSUdKZQwmWZ1LkEMVnTiLI8GAya+oaGYeBwOMz+MAlOct0kqPn9fk6fPo3X622H/DoyMbvyPfmOJNH10ZAwyKSVZ3/oYtuP4Zf67bjWKIXs5NdfN4NThsuFa+sZ5WzXpU/Ap3swboDoiUV0i89h+epkZvMrGmgA+pBHKpEYLORyNjCcGewmnHCCy2bwyl920oAGHAKtCRXpBihdjFxYfEcJy/wKbWCHbj44NgrWRMN6G5z4B9QNhEEfKVmhXkEoCUDjUUjaCOvDYE8mXHEUnq0GMpXJ4OCrIeYOQDg/l8EticBeWFUM8ahD2TgESGtros0GKq6Hviug7iB4b4Vw4JMBkPoR9DgEIYcg7llMvnWkDk0jIP5levqBBMUc/FUauLaoz87bhvKsCgBRS2HXRXAPBGll7vMb6PnkJMibDsvhyTE3AKEMoIb5bUm7OOJ4gvG8wlJud2/i3uWvMZQS/DQwhku5sXQRrH6Ncm5GHzMEI0fdRzhDoujaCIWQ5LP//D8Y5wWCkiGByhqArMoEHVUKpF4i79U0DafTSWpqKtHR0YSGhpKSkkJkZCQJCQlERkbidrupr683UZHNZuPYsWMMHDiQqKgoM2hICk78n0RtQVKDQj4QhCN1lKioKDNVJmk3sccQlqAEA6fTaSquR0ZGmvRykR0KDw8nMjLSTENaFciF6CAyTcLis07Qsk+rmrrUv0RVQqw6JMBZNQ+jo6Pxer0muhSmIkDv3r1pbm6mqqqK6upqysvLiYyMJCkpiT179pCfn8/69es5deqU6WAsgbyzINIRNX/Zd+S70fWR0bOI2dmZzEYnLFct06eq1opKC3HiqK6jc8bGgWMJoI1Am12EkZ3JZRe/yob6BynlhySQhA2dbGpZuGwK3GuDq2HVW91ZRRy8VwTTmtj/2r1w71i4ewzcDUzKhKIEmOxmXi70GgazymFGHxU8LoxWgrJz9sH+CdCrFhilmmLTnVASApWpkBwNrfvaPKQiIVgMO4bBmP6wqQgm+iEmGz72QLcAHEhDSQPHwLZmpQ4x0YB3+kOUgQqaJ56Ffrsh5QRELIWmOap+VH4/RP8GHC+D7/cQeS9McsPe70P/CgjJo++H98PU38BnsNwNy5svgojdCpX5UK3YxKn3fgjL6MYcaihlLTxehYOJ+Et3sYgtzKc3U3iabfyAHuwA7mYivyKX13ByO+m8x5P8ApZNg4gq9Oljoe0+5gCiJ7s05xz6oAhR3l3n4TgvAtSXNd52ZPZ9WfOnTKASuKKiokyCgs1mMynm4eHhpq7cyZMnTRQhVhp2u91Mb0lqLDQ01OyPkuAi+5dAIAw1qesIChJZJTnmiIgIk7YtjEMhXkjfUUNDA5GRkeY+JIUofVeyTBCaBCEhVUhfk7AarTU0SQXKuQiTT9KNku5raWkxjzEuLo7o6Gi6d+9OcnIyoaGh5OXlUVlZadLmNU3jwIED7Nu3j8OHD3Pq1CkTgVlTtNZ711lK98vGdwHq3Ib+bg3k6LiejseozURbL2mgLx+G041WUQS7QYsFFoznidt/z2P04+94GML/8BwPkHqXTh9a2HF4HAAZHGHW2h0suPhqbn90Or34gIX8AJ5sUc5/8W7Ig5jvKwkj8mBVd65oE9gAACAASURBVMAO3m1wYCzQCkPDlW5fZY2ybt8GzLFD0j6gFkJGwLEAHIsErQjsg4Fl4CqFwb0gdy/kDoTNUTBhHcyeDD9pgsw6KIyArEqY5kSpGQ5EESC0p8DxQ3BHKAR1CghPh9MJEGuHyNug4UVoWa6oeloL+D+E1kpmRCotPi4GmnerNOPFKCriHqBhBIQNhcwi7qacRxOmwk+AGjv+5WsYzW7m48LGEdZOeZqn1q6njj4s4HlCCaU3fXmUWcAO8I/G7WszL/wm7DY023kboM6LFJ91WCVxrCy+joQIa+CSdQ6Hg5SUFBITE2lqaqK8vNxES36/n7q6OjNtJqjB4XBQU1NDYWEhdrudhIQEU2JI0Iqk0sSTSVCAlfknGnmCzOS4hQloJRr4fD4TjQlqEVah9EAFAgGTvm4ldkiNS45PVMwFmQmiEhaesOQkIIl8kzATJahanYmDwaAZ3GU/ycnJ9O/fn6SkJGpqati+fTt79+6lsLCQqqoqWltb2bVrF3/729/YtGmTWfuzektZ7531fltfv2x8l+L76kN/qIaqVe2Dkyv3FvP37CILTTnHxZFbQJ9QA99rgunA45k8NuYqoIXrWUsiydQRDcAOeoEfllDE0WFj+B9SmPLoQ7yyMoOFDORR3gEOwKkI5ePkvp9YlMfSjKthcTgMTgMKoGRv20G8NoDlTZB8VPUuzQlATAhoFwF9wRdQGnlRLdAyAy7MA4qhOBkOvK+EYofnQlITHBuvnHNHAgmJSoB2RhrUBGDGQMUs52LA+7AKTqF91HG2ApPug9hnIeIWiJ0DrUuhKhy2JSgue+QhCHGzDpj8Y5jRH9xpKFZcNaq5uQGIyQHHClgHjzOCx90fQg1w+S4gjWJCAQ9B7Dy09i0eZiR72YVBEA2NIiKA99D1EPQ8naPFOtmHvqEm3fM4xXdeBChroLHSyjuiJ5mYO75XyBGxsbGkp6eTkpJi9isJuomIiCApKcns9UlMTDQVGQzDwOPxtGP6WQkFgq5EQVxQj7DYPB6P6eEkgVD6qYTwYJ2ow8PD8fl87SzoRT9PJlmp60iKUXT2JEDKNbLb7WZqz8oEFGQkdHOpKck1lOtgrX9JMJLtpRanaRqJiYkmKaS2tpbq6mrCw8PNmpz0SgmjUdJ51vvUGfo5V/bddyy+cx+uMjWRlSeo310uxaDcPPOQ2mDhQjS7ql9kf6p6oWp1HddJF/zkKLyeQCp/ZdH2j+nJz3iL6WzkKeZyivIxo2BpTyis4mViIbeYugUjWTvlaXi2F09xjCVzp3EPNRD3qnLHTf4NJX+FeSfhrznwYIEKKr6JqMCQBbWTDynfpaFQUgbbQpS0ETsBGzQ5obqHkjcKM+DQIPBeA6FOqB+u4o3WX9lllDrgVptq/N3VpFq1pgD1dngoAHlv/lYpVQCMboSo+XBkHYTfD2uvhKg7oG4mfFoE0ZuVGsTlu8A5F7TXIA68H8K6l9NZ9cb9JIQBpRFqu9or28pW1dCaC7mZPEU+CxZdzdTlm7FN11jEFu6ghCUc4lEKySOVicxjLW+is41mmnmFnuC/FtfQM0FJ83WF2NCFIQjqbD9n+xhNe0XTtApN0w58wfpbNE3LbfvZqmnaWduMz5sUnwwrarL+3tn2grSEJNC7d28uuugiU6YnMjLSVO/OyMgAzsgVRUdHk56eTiAQoKysDL/fbxoYSn1G0JbYoUsqTFKIkooT23VRJhf9O+sTv0z0kjaUc2hoaCAsLAy3222iN3mvkCukwVdShkJYEFQkjcFwxpLDMJRqhjAghQABmJ8rkk1iOtjU1ER9fb2J7Gpra0lLSyMtLY0+ffoQCATYs2eP2dzct29fNE1j8+bNFBcXU1RU1I7c0ZGJ+EWkiO9SfN/OcDuVkoSeplBTQNfRAdeLNrJXudCHQl62i8ELdXQWkvDGe+j9rgUg0uVSqak/DoSfvEg5Q4BNlPIKQznN/pkDeWZlCvds38gLjolAPUcTxqieqMer4MUYeDych++9AtZBHmHYpmsEX58J4cOhzwOcjIf+lfDrgfDYUoi8CkUoKFSNrw8CwRzQDsHb/wXTm2DI95Qd+6Y4mNYE7wDrDShwqh6qEkMRH+b4wDgI/lRw9gD/UXVNHHmw/yoYsh5euEZRzMf98D625qIe13MGQNRJCCuDQB5s+QNMyoXmnqrm1DQIhn8CwRJozgPDB5MU/X1dUwm4fwOFwKRGFfQad6kDqm9i/s092cMKXiQM5ge4gGYuoJn5Uy5n0totbHhkPLYndYL0YwYG0dxKgEam6oN5PNuFnqMT5nJx4acudo0B/RszMLSpZuKvP1YAv0O1Mnc2jgGXGIZRo2naZJSjyuizHNn/+2FNmVkns45CsVaVbKv/kLWPR+ovwlALDQ01lSNkUgbMCT0mJoawsDDsdjvV1dWmOaGoK4hckCAXScUJSUH2IWw+QRAiSivBwZqKFPagtZFWtpXgI3UxwEzzWb2apN4m5yT7EYq4z+cz03iCBhsaGswAIoKyoqxhNX+EM4SKXr160a9fP5PtWFFRYSInwzA4evQoubm5lJSUtEslCpqR+ynLOo6OLM2zje9SfF0fCQ0WLb4lLnj3XQD0ET60kSvQ9usMbiumZ7lcYIwyt/fpOiUZwE8PwKogs3mJ+fRhPvvYz1huXLmIpzhNHmFM2riF2ylW/ULAvayFueFQWqrSXI9tJ4ENPEIpNN4PDe9C6W8ZVAMhYTDvE9BmozyL04A4yCuCE4DtJBRcBz9rUyqfdgLSNsA0rzIPnOaDK1bCtGrVE/VsMcwpgxofxI6DlzJVD9Tq/m2Ns1fD0AbwjoKf74WbCuDVelg8DCVrFPWAkiWqeQBan4DLP4G3hkHkZxD6B2ieC7UPQdJiuOEQ42Z+BB5YV6ZSluQrgkZ+N2AwVN7ghm7A1uksmnIta17vwVHskGXnmQWTeMYxCdZ62DBxPPOffI95nGYBm+lHNTeTw5KmWbiOrodV8wAY9jLokTrafktw+hIB4K6NMLClnP3nLMMwjM9QrP4vWr/VMAxh4mxHeZp96ThvEJTUYjojQVgnL+uEJsEjOTmZHj16MHz4cFJSUoiIiKC0tNSchBsaGsjNzSUxMZFevXqZyMHhcNCzZ08yMjLw+Xzk5eVx/PhxRo8ebcoRNTQ0UFlZic1mIzk52eyjkj6hsLAwEhMTTaQGmA28DQ0NREVFAZhsOmsKURBLZGSkef5WW3grWUGukTT1iruuSBtJ0JIACJgOvhK0wsPDTcV0sa6X9YKg0tLSsNlsnDp1itjYWAYOHEhraysbNmzA7/eTkJBAamoqdrudt99+m6KiIlMWypqq7RiUOlvX1aAk47sU3lcbrmoXvA16znW4jh6hfPpN6LqOy9WIrrc9qCWB/pObYdMmXK5oWDsAflXEYtYxb8YvcDOLBeQTjp25bKAI8OChhKUU8oIKUIeB6+F5LgK3h6kcY83KJFg5hGHUM59+zLhjL6te7wP19yndu1yUDMRAGBcCW5cDtnzoP4hemUB/SPXDvnj4kw2a6tQ5vRoDs/4GhgY33QqrUHwE0mF/E8x1qJTg2DZiRH4iHMuE2DpVhzoagCQn/HcMPOZXh7BxBEw8ORuC81Qr0WUjlfbgTFSKL2sl5A2AGLfqkxoJ79VAcivwCTzbB5ZOhDn/gKSR6tyS638Pxs+xPa8TdLjAn6Gm5cJS6BUD/gb4bRq44aONyRwkjLqEkfDrSyHmaZ4/AQXTH6ZemHoXdoKavi5RQvvGENS5jDuAdWfb6LwIUDI6UzKXNJ51YpMakN1ux+FwkJycTFpaGgkJCSaysNvttLa2cvLkSRoaGkybCo/HQ1lZmanKYLPZSE9Px+l0csEFF1BZWUldXR2xsbFmo62VnSfpK8BEXj6fz0RugoisBobSvyTsObGe9/l8REdHY7fbTUo7YDbbSlpRmIfCRhTFc2vTr1VPUFCQ7F8CWENDg5leFBKF9TpbFSTEBj48PJza2lqzf0nMHgOBgEl/F9QiQVb+tjL3rPuxvloDWFfGdwjp3Ibr6Gb06YCuK5R0DEp0naEuF6x+GbiQvGwXj1etYIE+RL3p3lAmTXkVH1uZxxUM5XXeIp1DlFBMKJcSYE3CfFgCVP4Q5tezi9PgrsL2YDHBN8LhRBxrHhwKLzfBizHMz7ocVpayilHw0fdgSjIc/g2MgPwY6L8fQjKAW4DtgyAbZgWAatjXXzXwxjrhF4NheQ9lYFg3ErZ0h1UvJeC73E23PkAA+pfAslzQr4Prw6EkDIwNoPUGKpSKhCdFicOuaoJVJVCSpsRqF18D84oXK9rgRtrwQDo4V0LhTLhhJbwLTAX+Bsk3o7ySnMDFMKcVSIHk/cDJBOj1cygupA87OeovZuHGA/hx8gzd4Rc9uZHn6XbfBABiqWUHlyox3O4lcMMYnA8WwbJMM5n3tmsDAE++OBV+Mghd1zGGutojqnMeIaDFdGXDJE3TrDtabhjG8nPdm6ZpE1EBavzZtj1vApS1x0mGlX4uk6ZsFxERQXJyMsnJyfTt29fsF5K+HKE9W32WioqKqKurM2ssUk/at28fDoeDsWPHkpiYaAappKQknE4njY2NJCYmmmlBQTFWV96kpCQzxSfkDDkHUUCXoOP3+80gIjWjlpYWE9EIwpFzkM8SVqF4WwmxQpiEPp/PJDxIM68EbEFQhmGYyFIQq2gTivCs3++ne/fuxMbGkp+fT21tLVlZWaYNfVlZGZs3b6aoqMhETmIX8kVotzM6+VdBQ98hqHMcj17DLOM+Xs2BQl1Hr1aLg4dAr1M16sE5OrNqXfwBSB9cxBOlf+ex1TZoGM7jt33EAkYzn89ZNOVauL6BnXceYKp7M2v+OAFyPURTyP6JY2FjFcHXE+DDDGaufI6V3AV3FMPLvWBBDJAEy8KhHAjJhvwJpI/azGjAmwAxMeB9OR1uK4E6GBwJd10MEz8D4yV44RE41QPeiFOut7NiYH8zcLObyBKgGIwTwJVwk18RMGZnw7wgaBfC0kSYEwbNIdCtCfKjICYcvEFIL4HFg2FeRdt1uxjG9VICtfN8JVAG+7uvJKkRul2KEtz7PhS2wHXZkBei9o8PCEPBudgX4Lox8N9wK1VEUEcj8AyjeJxP0fylNDGMJxhKKkcpXzIRClAiszcUgT8T+k6A22Ad25msj+F6fRIA1+MzkdPXC04yulTtqTIM42vlEzVNGwa8BEw2DKP6bNufFwHKioxkkrM+hVsbSEWQNCwsjPj4eDRN4/Tp0wSDQYqKitr1/giicDqdZgouPj6eYDBopqr8fj/l5eWUlZWxYcMG0tLSGDp0KC0tLdTU1BAdHU1sbKxpQSGfazUUlBSasOAEPVlNAa0pODkvK8KxNgSHhYWZCAUwJYUkpSepu9raWtMYURh3VtFa2ZcgTunjkkArDcFSW7M2DickJNDc3MypU6cICwujb9++1NXVsX//fk6ePEl5eXk7NfIvC0TWe9xx2bkGnO8CVNdHRHg+m3MzGf821LtcHKrUGRrpYr9PJ69OTWqugS5Y+xy4ivgdG2BLJo8d2wit9Uy97RBBgtzDfhZNuZbRa7eyY+0wynuOYlPpLsgtYyqFrKEbOGAGB1n1oxSGso3u9OIh/s7TXAqeGFjQpBqZ3oOpazdTQQg7+B0lzo8g6UEA0ntB3g9LcHug1QYFLbAnFDaOh7u+p6jiE22wGJhX1ta0Wwc0Q34vZUBYFwahB+DFk+BLVvp8e8bCBcVwXSIYm2DLf0HDcXCmqNasmwYqXUDbCXjErV73fh82A3M+hM1XwuA4+KkDvA6YEQd3psMpDbKKgP2wKxvmh8M6H/DGfoj5APDwmP9dnii+jhxiWfN6D0b/qAwIoBPDGvoCofBcEuWjR0PxTOgNRtZKRaev3IU+RGOe4WJyzhhGhLjY06ruW6jL1alC/VcbGmekN769oWlaL+BtYKZhGIe78p7zgiQBZyarjkjKmhKSSdpqhS60bq/Xy8mTJzl9+jRlZWWUlZVx4sQJamtrqayspLy8HLfbbQqvSg1I0m2i+CB+S0JYEM05p9NpiqKKt1RTU5NJ87bq68l7rcFWzkkCnSBCQUOyL6ltibUGYCIhTdNMsoeVICINxjabzZRwAsz9SeCX6yDrJYjW19ebFHZJQUoK0OFwkJ6eTnNzM+Xl5SaRxKrTZ70/X1Yn6hi8vkpw+o4k0fVRHQrjR8CBG+BQpZrM9vssfVBpLu6Jeolt1z3AI/yNg4Tx2PjnyJh5Cm7uz5q/bAPghYkTYW0m11DHY3zM/NL38KEBLazhNoZSyUNr32IVMTzEAfbzI3bRjdX0BKKUOsOccIb6t8GMU+wkglE0QkIUeF9g4yUQMxHyWoEGJRabHAMTVsGcHPirDZ4vgomHYWMQ7vRAI4pivjkBqIRXnNDTD1FlihixogcUpAHD1Ln2Gwjzm6HuMrioFEKald3756vhEg0qukFIbwgZDto1Kv03shm4WpEzEoA3dioyhBeo12DWOngnU1mA/DJcOezyOeAohaiHgWieuPc6Fq38mDW/ngB6BjtedMHEJC6gGZZ1h2FpjLs/k8EXw7FrVkLGSrSCzRAHg28bSfY+Fx9qqgVgT6tO9nEXA5JdDJ9SxB9c+zq9765zJk1oKNh3tp+zfIqm/RWVHB2gaVqppml3aJp2t6Zpd7dtMh9V3fuDpml7O6QLOx3nBYISxppMekKAsOq1yYTZ2tpKdXU1oaGhVFdXm7URSXXBmdqLtXlVXg8fPkxISIjplpuZmcnAgQPp1q0bVVVVBAIBdu/eTWpqKklJSebEHxUVRXNzM7W1tURGRpqNucKWk/SdBCdQKMbtdpvSR6LoIEFRfKKEpSdBV+pIHUkjEhAl6DidTjNFKMcpqUE4Y4AoyhegJJzk+kigEVmo2tpawsLCiIuLo6mpierqavNaeTwe3G53u+BsTb92lt6zji9i6p0rivoOQXV9lFQMQfv1U2y7YSpj3/0Uapegj/iHuV4v00GHHj54cseD6CE6LpeLiUzh6NZb4NAupuoajx/JpfYvELvzZ+y7Fi7kbxTW3UDWViAT9vcbyf7fj4VWeDqtmqem/4lyjrKB6QA8MnMXT9KL/STDrAbKJ47ihY0w2r2VHXduYqLRBLFroOeDMAiKYoEV6ZBWAgWKi3zzCHjHBhO3watjYVaeQj/rqiC/PwwClsUolvicE0A47IkDmmEEEIMKYI5qKM5Q/VHDKyAnUl2DWhTKNN4HbTgMrQPCYHF/uMYOpwOwyQXUqyD161gwamBLC/wuG7buhaXD1XvoPRl2FKlI9vwRctkKOy9XHcE14YzeuJVn7p0EdwFLYOtf74LvL6NvJFD6e2iOg0+L8I/fDkNuYbeuEznIBfmQ01uHStAX1cCiztuImvfBvuZz/bZ8fQRlGMbNZ1l/J3DnuXzmeYGgHA6HmaayqiJ0TInJE7QgJ6/X287bSZ7eBb1YrS6amprw+XzU1NTg8Xioqqri1KlTFBQUUFhYSHV1NXFxcYSHh+N2u030AlBaWmpaZMjkrWmaSWaQ2pMcr0zYVmkkSVNK7UiQD2A2zUoQDg0NxeFwEBkZab5fgpLf7yciIsKk0ctxBAIBsz4lNShBNZL+i4uLM5EinLGgF9JDXV1dO7SoaZppiij76Aw5We9XZyjY+vpNoKjvGnW7OEoOQGMSY/98EflXP3AmOLUJxGbfpp60u3mhsK0b5XQNPKsvQp89hJIfjwRA75dO4UkdowyadR1abqD2kE7wSmD3c+h6HYQGMUZnQs1sHn71bp5nCg/xAVPZxZNcSTS7YGI/IE6petPCjp7jgHpwFsOKG6D0Od6Jg6FB4KYSpTyRDXhg4gl4DHhnLNycB+9crNqLYv+hhB3wwL462BoFm7sD0ZDhAaMvUAylJ+GqGBU/ep5SpAttTPvL1fqjH6ENB06q9xMC44MquL0ZBx4bihBhh9ccUHMlTDjeJjjbCs+uflPhg3SgxwqWPP4Rqbh5a9h8+BCGPr6Nex7cSB9a4PkjzGUD9DoBKcvg/QH8yg54fw47nXBnJkdXV7B3lzq2QZY+2ezjLlxpX4yS/OcqZm6m+M72868f50WASkpKMq0wrJNdZz8SpDq+WoVI5feOAUtShE1NTTQ0NODxePB4POTk5HDkyBEaGhpwOBykpqaaUkNCJiguLjalh2w2Gw0NDaa9hhAcBF2EhITQ2NhIXV2dyXSTSVtIF16v17TLEG8km81m+j2Fh4cTExPTzk7EijRFvFbo8KI0bk2DSTpU9h8XF2eqQYjTbyAQIDIykhMnTlBfX09KSgoJCQlmLS8jI4OkpCSzziefL59tRbgSrCQIddYyIOOrUM2/qRSf1knHu6ZpCZqmrdc0rbDtNb5tuaZp2lJN045oqgP+Ist7ZrVtX6hp2qwun8i/ctzmhat2M+jt6/nItRMA15TXqbnIBf+rGnI39oSsLeAqcpG2tu19K1ZQruu4mly4NiiVc/9d4PK40PfqpLtc7NZ1lkx34Co6RvldWWh1YLwAGNvglVt5mvGs4TbuYRd1hMHGI5CQpPJz80KZVLqF0eTCLb0YunYbkMy0N9bAO9cruQcZqmzDg6jFx3vDdX+BVdXQPFwhI+Mz6GtTvlLZx+F0M4xLg/pDsLmfMj68GKhJg8v6QzcbGB/ARbgIcbnI3ueixwuvM6OXQmh8MkAFxmOQV604D9MOw+RE2B8Bz5ZBwtsR0AOmnUQRJMJ+qF7/XgjP38ajZHItu2EMzPVvYD/pvLB0Iqu4iEmU8QwZcLgXlM3k2I2HuN8DxMHi5evgwwHMnR7FiJURuNJdyvDq3XdxHT3E9qlt6Bdw9XDxgevzdrf8cNm51qa+mRTftzHOiwDV2RO2/G39vbMCfMcJzjoxytO8oLCOE6eQA0QaqKGhwbTrkJSaMAAbGxupra3FMJTKtzXYiZyQ2FPI54o3lcgJWVGSBNJAIIDH4wEwm2olfSjK4dZzEQQTERFBIBAwUVB0dDQRERFERkaa/WFChhDyhd1uN61AxMm3e/fu1NbWUlVVZVrJOxwO3G63+dmnTp3C6/VSU1NjnrdVncJqBPlFyMl63a3rvsp35RtAUCuAqzosewj4xDCMLOCTtr9BEbmy2n5mA38EFdCABahO+FHAAglq59VY2g+6vQcz3+bRv/xMLQt9jWw35MTq+HSdtTbQ7Tp1MyBnwJnJbU62Cz1cp3FqJq4QF44+oMep9Smfqm2u1EehZ/YllSLclwP/C9zmVN5JjjQAXkiYyD3U8ARHwF3K/8fee8dHVWf//8+b3jskQAIhQ+ggkEsRZQVWF0FZG4KuoogrFpRFWUWkg6BYWVzdFQVBVKRYVgRElKi4FHmPlICAYUJCEkifZNLr/f5x531zM0wCKKv8Pj/O4zGPmbm9zLxf95zzOq8zbOljTF34LoPIZS+dIcKPFPxhbCB4OsB7vD4yhb2pSxu10jXz7i2GpcWQWA10AgLB2w9Ca0Bcr4NSjh/MtUCbYEixgoiFIV5AGNyuwWet4ZsjUFoMo24FpVDPc1QMh5iV0BO4F6DvcfjRl6Nt4JNImJcO+9vrYcVePjAyBpY9UK0XIreC5FuAqgf1tvAPnoY96RDRiRP0ZOHyrSyhN9GchmKYzlZ29L4aXo+HMRZou4b4TRBaCCf/BLMzHkUUPcCSt6YzfNJyiLchqgRq4H2IhC54H2q8RyJbcKO46lf+SC57UC2alNqR3omZ1ecKRubBTg6MZq/LvBzQpC+TuTkfNKW2V1RUcPr0aaPpnqRmV1RUEBERQZcuXfD09OTMmTNUV1cTFRVFSEiIcYwypyNrmgIDAwkLC2vShNBMoggODiYwMJCgoCCCg4ONkKRk57lq8kkWngzbVVRUABghQcVZa+Xv74+fn58RDpTLgF5AXFFRgY+PD1FRUURHR1NTU8O+ffsoLy8nKiqKyMhI6urqCA8PJyQkhOrqavLy8igtLTX0BouLi5vs31wLdb60crNHfCF2MQBKc1/xfhN6eQ3O95tN09/VdNsDhCmK0gYYAWzXNK1I06vjt3M26P3+5g0zSdU/L9MF5wbffg8R+fqkz9X/Ms4qUFV/jjtZYequcNRt4UbLhpRygTYevUurc77SDnxVlaSr9VBT/X4LEYk2lIGg7b0C1v4EkTCPfzC9aAdf8AqzmEwCWSTzIkuH3cPi3rcBOfQq2k0vKllELqPGfgqLe0PQy1A4BOKBznq90vZQPRxJJpS2A7KhR2d4LxL6fw1tiuE1fx1k7IXgkaiz/vZX6etclwG9q8CnB5SF6KQJ66ZHCQROdQSrfRa7AA5Bjz4Q8kA1xwIgqg7SoqHYBx7NA9L1fUz5CB2gPoJhycDHT8GSHOeFj4cA2PHmYGYvGAnTo8hdNgA6nmLJqNt11Y1Wn0IxJF8D1rU3kh0NsSeBDv9Bjfk7dCziBdEDsdOOesAXcZ2pHYqLZV5Q/yd35nEer9/eftVeFUVJVxQlxczIaC5U0pLJcJksEpVA405ZwtxN15XpZx4kXee5emBmAoV5vsPhwMPDg5iYGCMUKL2PNm3aEB0dbeS2JOFA0r49PDwMD0V2nnVtvQ66WKz0vOS2goKCjJCdJDaYm/+Z22VIoAUMYoY8F/P+zO3qJUhKjy4sLMwAurKyMkOuSaqdy7otyRyU10xS5uX1cpVfcuf9yu/n+C2d62diXIv/EYsvWtO0M85jPYMufAPQDqdIgdOynNOam35R7KL8tzqB1tnCoo1/JwVgTzpqmMoyq0A42XxzV/8NgGVaD2M1MdgOrbqjWvVBL1BVUea8a7DDxGA7olhQLQTKv/Qkicch4LAF3rKhpI6HlRZ4GE6TxRKGczcPAR/RnxpI9IPkY3DoGL0oJWXRlaQQTi21XMk1JBzaAyk3g48Dsh+Eb4fAGrjuA6ioBe0WyA0FsvW27VPSoaE17vRTVQAAIABJREFUlHrA+Do9Ghbuqd+cTAf0rQdOwbJ46LtVd4PbpMOAIxD4z3/SDl3aiZtvZjBApM4odAC3AEMO6hT2qGoIDwM8dRmmJ28DDt0K9bdCGAzcuIuZ7CaBLMbzss4gXOgBG4ElB6AKho8/pRcAW4DyP6Clw9WHIfGtz/EMBu/2wOqbgO0s/CNMVo9S2ldF9Klu9jYnjVGJu6D+T66moPcXOdfrt7eLAYvDNE3rozUWcDUXKmnWzK3SoRFozLkn83f52Qxm0FjvI+fLdzlYmlvDywFdeiRy3zKXU1paatDAc3NzyczMxG63U1tbS3R0NGFhYQDExMQYTRGlp6YoCmVlZQZw1dbWUlZW1kQrr6GhocnAL3NKISEhBAYGGsdhVgaXnpQ8VxmCCwwMNEBPgpJcT56TzI2FhYXRpk0b/P392blzJ9999x1lZWW0atXK6Djs7+9vFDiHhYUZdWQOh8Ogmcv+VNLzc31IMIOWNDN4udp5ej7n60FFKYoiTK9J59x48+YOObUWpl9M+1X/rV7BoORtgoZl9FoH7PgjorjpQGbtoX8f7DLApU6qhpvBW1UpF4Jxt9/Dbv35iqSDzsMZOhTRS78Mi+99Q++Yd4eFhrvXwJ4nYKZeeziH/zC39w1AvK4kkZoOk7rCq11JIY5xM79jLqnMW92P2W/9kTR6Qin0uv8IVP8V6t6AkA+hHAJ+fBVFQOJeIPcFhuwDyuG/V0BwNgz5Fl5cC/sDIe4YxFUB/4XadjCkCgbfAsvXw77u8Jc+OjBlAyxdStIRlbtL0VXIy3UR2jjAHgdD6pzdf49BfTGsW6tr/xH4Max9EdS9ACgopNGHNbOnwUQLZBXo3tJ6PYm245mrWVD5FSwBovuTfgtM7g1pYZDwTj/Y9gmih4AXEphdCCsYT/B+/d6U9lUJVVXUtL1N7+HGX1sPpUCD17lfv4P9L/y25kIl52WuYRqzJ+Qu3CeXMXtW7rwsmSORgCQHckVp7PukaZoh4lpQUGCw7KRnJEFHMvrCw8MpLy83PI/g4GCDYWjOy8ickrk4Vx6fVHjw9/c3aOYy3ClBQYb6pMcma6/MHXTlecpzk7VP0kOTuTRN07Db7Rw9epTs7GxDC7BLly4GOUJeEynhFBYWZojjyi68Mhdm9nJdySvmeyCvu7vprvmpluw8PagCTdNU0+t85FhynaE7nO9SUyALJ1HLabHoreyam/6/tAv6b6UUJ0LVXLToKSwbCxRDUomKerRUF48FKC5GtaqEdlFRT6nEOb2kEiEgehtX9Lahpv3IOwpG7kPqwe0qbdSfHCEGIHwET7dZgsf6V4m+sz9wBcsZw1rehkMHmMgBwI/5HOHp5RuJeHwQvchk3bA/kEkwo+5dRsIDPwIn9OMfdiXD7/sJngoAHFBgA+1xPazmDdQ8pT/Y+8GQAsB2K7QCSqHvuiGc7AYlDUA78C6FvqfQVcv/CP33wLpi8OyhEg8kLH2PsqEQZQdiYGQIXJcLmT/oNVP7PODGYJjUGzzrAR9wfAkUd4FeMJfd7CWBZ2NvhvWfwcJi+NEGw6JgYxU8MQgSIXrxD8whFsiB0ymEhsAUBeofuFu/kB5ptFVV6AwiXVBlKsYN3i9IXP86IqF5AXBVzWjpJ+HeNA9o8Dv363ewXwtQGvCloihW01Nqc6GSZk0m3M1hLTmAyQFQAo+78J1ZK89cxOrOm5K0a+MEnNvy8vIyiAA5OTnU1NRQUlJiCL5KL8nhcHDq1Cny8vKMlu5mmaHIyEgiIyObeBXSa5MgJb0PSeGWdUzy3M25L1lAqyiKUTdl7pAri2vr6+sN+rlsVGhWJ5f9nWpqavjhhx9ISUkx2IdxcXFuZaQUReHUqVPG9ZWsPzOZw1xYbL7W5mvr6gGbXxdIbrhYJAl39hnO/Ljz/T+m6fcoug0CSpy/623AnxRFCXeG2v7knHax7Ff/t/qeTAWfRSjlMOUNG9S9izVUwI3DyFkJKiq92l0L10Ni8EeU3gqt39fXVdN+ovzkCMRKO9qmSQxjjbFdCW6DrXrdVGI7lcwkFdWh6sW5u/5MEh/zLK8DBUQwg4Wc4Qg+wAHmMoUjRFPEKlJI5Lnk7SRQxZbXnydt0CB4oQ8srYIbYQdXQyUw9gqIccC4r+Hgcsh9F5LgyST0/P1XtzLp7o91NXRPwH8nHX+G0M3oYJYDfBcBVbo23+o/AEdhpx9UnQCvKqgNhOBa2B0IW6sAK4QMgIPR0P99XVB2+fvO7TesgLxkKNsCS04wn2HwdgjDs76H0TPg1TDo84XeemOQH2SlQ+oxcqcPgLcSYEUA+M4F9KeczDXvQcSPgAenhUA8badLK/061/ZuzC+5glOgS1GuEB1a+kk0b/9HPairNE3rh850mqwoyh/Od0VFUSbJEIy5INc03wjJuT5pywHT3HJDAoAEH8lkczW5PbmsJBTIwVKGGuvq6sjLyzMG+ZqaGsLCwoiNjcXDw8MoEo6IiCA0NJTy8nJDJsjX15eIiAj8/f0NwJR1UbKwWEoWmfXwzAoPEpCltyTXMQOBzNtBY2iyqqqqCYFBejryvIuKiigpKTEo87KxY2BgINXV1QaQ1dbWGnVY8vyl4oUEPdcHCOnBuPOGzDkps1drvt/nYxcDoBQ3Fe/A88B1iqKkAtc5vwNsAdLQH+vfAh5xHkcRuurOPudrgXPaxbJf9N8y/69SiEJ0aYVoLdCmWRAJ3fWFvCHbJhAIXVni6y4I0YHjQugsvqVLEQndSYsG9ee3UPrY2Mh4kkqcg+FUUI/rLAshBKfbwM3vArttpK3PhpcsbFk/mFmfT4Y3O7OX8cxeH0VndgNdmc7zbKIXj3EGZkcxo/d1erfeyccYuGeXrnL+sh9M09mtz1Vuh1FRDLz/MBAPY6PhlatgN7z43q3wjc78X56DTn3xG6/XIx3qokuStoORtwEhRQweAHE+cG8hbB+ky2n/N0GvdYpwMqmXekNmjb6e45Re60QP2LrhXWgYAT9vAC1E11d6AcbwAXNJhr8GsOP1q+GD/XqYcOzVuvDrdTCaTMCLgUt2QegOyAkB5WFKHDqG3ZIOZNlIufFxtiapvKduIthZA2Vm7anPhzfppFt+UeSOFNC8zv36HUz5FU+cTTekKPOAMuABYKimaWecoZJvNE3r0tK6np6eWkBAgNsBxnUwMyuemz0UaPQSACO8JTvaOvdjLCPJALI4VxbGykG7rq7O6LYrwSAiIoK2bdvi5eVFTk4O1dXVdOrUiYCAAPLz8zlz5oxB/Y6IiDDApbq62mDgmTvaSsHahoYGQ4lCDv6yTYc8brkNh8NBQEAAAQEBRjhPEi4k0ElWnVRwl8vYbDaKi4ux2+1Gfi0gIICkpCQ6duxoNHGsqanhu+++M3Jcnp6ebNiwgby8PHJzc41QqLzO5nd5r1zvm2uI1jzPZFatBTHK8PBwbfjw4c3NNuzjjz9ucTv/X7Nf+t/q3r27dnTaUTR/qOsJEVd8SLLohLo/ENp3ozYGDtYKZiepLLTq71sBYRUkFapYIwVqoAqP2BidvJNNsUNggYWSkZCa7WT0HfBl3F8FT4peJE1QUQ4fhPfyWHj3cRQUKignmBBmEMfTHOb5t/5MxAN/oGjQHthjwYN1NBDGfI6zkQhSiAO8YG4MdMyDU62hCBKW7iHt9UGQA88t3M6MZdfp7IjYeLgPZ6fenejUhnJoqIA2C3XPKRAoGkHc+G1klqN3uN0MKE/A8Ff0ZYrRi3Dj0JsmOhsnUhnByL8WsdUKnJgNSm/Y3Y/RS3eyyX8IPO7c3pIqxvACO7meXAKAKMBLF4F9ZgADF++iM7vJZiA71iuw/iq43kLDX0FZAcr9/0W0G4s6JxvCX0Ak6L/z7qpKwIezEV5XQHy82/scp6pktgBUqqq2+H9QOnbTmPdOs+sbNuHK3/x/9YthUVGUQMBD07RS5+c/AQtoDJU8T9NQSYsm8zTgvqWCmexg/u5axCpBQfZtKikpMTrfQmM4UD7xV1dXGy0sKisrKS4ubkI2kJJEAAEBAZw6dYpBgwYREBBARUUFpaWlBmDIMKGmaYaHFRgYaHTYDQsLM4RkpRCsPAdz19yGhgaDsi5BTfZvkl5WdXU1vr6+Rg5Mnpu50FjT9Hosm81meHhyPS8vL9q1a0dMTAy9e/c2gLSqqorq6mqCgoIMcC8vLzfa2pt1/txp77nmnMzTzffNnIu6ELtYD1SXsl3M/5bmD/iB9zAbQtjp7aci+grUJBC1cOUPKlYF+t2isqUTcDNYfUHJS6a8s6r3QxoAmx72hoZDcAcMoT+HJoVzerkF7b9gDQrC3q+MBw8/CZwAn3JmjxnJ9I0bdEp1KpB6gOf/NQYCLRQ9Z9ObE+6xMp/dzB6mMvdgJygqg9lBRC/8gdz5OeiocwDoQ9rUQdBqH+zpzwz6O88uCmYAk49BYlcmptbzEx+xZ+5K3YNaPAGmWHSwabWNzJX7weN+8BsK3V4B2ys6eP30BIx6RW+hd3CF3uK95AmIewW27GPr80ApzF+8mbn+/Rhf+TIH2QfLBsIJH0j6hrmUMj92DgOzdpFLPCQGQSXkVkTB4nQqUFgzfhqsqYKxfvAC4L8V5aORKPWryC+6iow0AadURPvGh7CfhGB7P5VtHm8wQsQDoFpV6gdgCMe2BE7nZ8rv5iGdy37NUUUDnzgBwwv4QNO0LxRF2Qesd4ZNTgG3n8/GXJPo0JjwN4OXO5Ay55tkLZX0kHx9famoqDBEWqFR9UBuz1zLI1/S05EDvQQJSZKQBApJ4ZaadVLpQao7yJChBElvb28DtKTauVQzl3JGkiwh5YvMoT0ZqpMCsdLbkx6VBDHZir60tNQ4l7CwMEML0N/fn169ehEVFWWQL6qqqsjPzyc8PNxQmggPDzdAXua95PUwh9Xk/WuJzCKvt5ze3DIt2f8fAIqL9N8K4CjWLoKtSSpzbvsPSVc/wTflEBw6lKNlzvCQQ6XbCVB+BtHa6RWVq4g3ryZQGU/vu4+h8g0r37yf6AfXcgMriKeOQ8stLOcfTLvqb6iVZXh4rKMhYxwzO7zEopq/w2YbXnhBL2DLASAMHj5mHNssPuXZjGnM/iIVMmBB8lco1DL7PyMZwhds5BEYFoVHchYNpMOVRfBEf6gAxofpHs+yIBIm7yFtVQLMgpV0hcSVPDv/C2YRz3ROs+RtGwxH9z99aiD4KSi+V28+3vAqfPQ4BL6iS1T4jwC/GijZBDVhcHoYfAvc18DcGZuZO340rKmihv7cRlcOnfEhYcke8glkPipkFXAz5ewlB2I74ZEsaHhGZeLidFZGDAV/YH0K5PSHiDTI64wyBCieQNTfIOpulfK+cNTZhGJrksrI4CDCvxGMMGGQSBLsr9eVP4SlcUbSEdVgZV6QaVyyAHXRQny/xmSIDxqZYPIzNIbw5EAmwcoc2pM5p6CgIPz8/GjXrh0hISEEBQVhs9k4ePCgAXhSfdyc45FMPklukPkbs4CtBJUhQ4bg4+NDVVUVMTExxMToFfMOh4Pi4mLq6+ux2+1G+3dZLCxDenJb8niDgoIMFqBUEq+oqKCwsLCJEkZDQwPh4Xrpi6xTkky+qqoqQ2ewvLzcKBiWjD5JH/f29qZ9+/Z06NCByMhI6uvrjYaEiqJw4sQJgoKCKCkpITc3l4aGBnJycti2bZtRMyWBymxmermZLWkmQ0gze08u81oMIYSFhWnXXHPNOX9Pn3322f+pEN8vNSWhs8aSp6keez8pQhCdqBIXAuToCgRqlYrwE9ygprJZJJJUolLWCfI7QALfwvqDsOoG2HKCZznBcY6whjcYzyOs4Q0GcQ177N+i/QTKVduYxWGeXe9Hr7GhpKz9ESZPhnlAcBHc1x+wQkaSHkrbbtNBZkYxvJcEd0M0a5lKCR8QRAr9AS+ms4MlH0bBHQ3oVbtBjGIWW3gUdlwDBStg/VBdy+M0OrTPKMCDdBqI16WVngaeSmci6axMHEp06g/kLhgAS4GiMiYi2EAgpcv6w5QTgBc8Ew+L63iOZGZMvw6WFDORA6wkHmbHw0J4ho8IJIiZdIBBXfWLPgo95BcCTCuA56L0fJQfOu/z2s1QmwiFnaGtBVJtkGiBH21YF1vQNm40Qnkb1P3cLvoCOsVc0s0v1M4Z4ovvqTFr47k39EC33/x/dUkoSUgze1DSK3GlIZs9LfldPtFLcoMc3PPy8khNTSUvT2cMyxyUWfBUgpAcfCWjTpIWzNuV+R1JOZeejyRpSBadr68vQUFBREZGEhwcTGxsLMHBwURGRtKqVStat25NSEiI4f2UlJQYAra5ubnk5+dTXV1tqIzLPFBQUJABcPLYy8rKKCkpIS0tzaCN+/n54e3tbRxPZGQkgYGBhIeH07ZtWzp06GA0eDRrCkpgLC0tNYge8lqbC4VdCQ1mIHJlXcLZpQOuHvCF2P+Qxfd/zvoGpsKBofi+HcdmdRdBVUBnGyJb19ITfgJuuokzwilCfQME7+hHQgYIEUjJkClM37IBTo5gCZF6bU9vG9kMZCH/ZA/fMj78EZSrrIie05ieMQ3GxpJCODw5Ge5Bb00XaIMMYP3X0GEz1bXAeAskWmggieF3r2YBb5KPB+WUk0IvmOoF5OidZ+/wYD7ZQBjM9mILD4F/LKSmQspQ2FiGx1MCuqAD3tQoGiKc4+hw4KkcniOVlS8MZUHqV+TSmUVztrGg6Ct4/zQrew+llG4MnLKL6ZyCSfGwOAv8vZhJOKOX7CSan3VwGhTPqIVPA8UsHnYbtdQSjQMeyoM9WQyf8z3MryN62g8M5xjMKGbe4s9hTo5eoLv+BvAqg3zgSxu8rp+WuNWOJoQBTmraLpasete4l+cCJ/XHXyN3dOmSJC4pv06G86S5Jtql9+RKNpDek1RGkF1fJa1aqjNIsDGDlPQ+5DabC19JwJRt44ODg9E0jZCQEDRNM7wlybZr3749NTU1FBcXExsbS0BAAL6+vjgcDoPRJzvi+vn5UVtbS05ODna73WDZSYCRgrLSs5PeivTOAAO42rRpY4Q3NU0jNDSU2tpaA7T8/PwoKioiLy+PlJQUGhoaaN1aZyu3atWKgIAAMjIyDE80ODiYnJycJk0jXWuv5Gezt2QGn+a8p19ilwHo/M2jGuizE21TJsrJKcxdZ4OjFtT7bAghUNP2cfJoNh2CIfMdFfG9gG3hgIXlSSrL129ge8Pt7PNYzY6yO+AtG4yEHc+cYEf7hbDKxrtXWfjy3iHcd/hpdgTfDW/eBHU2+Duw9DAk9oS6ZBa2h5H5w1ErVXw3fcjqrndw7z4bHu9ZwKeEHetvYOHGrczmZkazk8FLq5hBR5jeFZYUoCNcOiz0I5h8nq48zsy0EbDkBLznQUOKCg+nw6R4EpbuIR9P4qkjZWMVwZxhxtTrYBnMmXQtLK+jggp20wqOdIYxMPrQfjattnDjvQf19u1TY2Hwf2moSGTTBAcQhQcnWLjnODN5CGLDWJi8lfVEkjtsACzSr/kOoiDCi0eLCpk9fiQL1nzFnKk3wtLDTEw9xspbh8LBfoxb/B0bCKBhzTocXSEkuRTRLdi4dyJhMLryX6OpqopoJt8k+v3X7fTzMg1ouKR8FcMumaOST9tmarl8Cnf9bH5il0/jrorlUohV5pfkPGjUppOAImuwzDU9EqhkPkoCgxyoZVhQMtoURTHCc+Zjlt5SaGioUetUVVVl5LIk3TssLIwOHTrQsWNHwsLC8Pf3N4Rkq6uryc/PbxLCk/VIAQEBhIaGEhoaStu2bWnbti3mcKk8brvdjt1uN7zKo0ePUlBQQF5engF0J0+epLa2lrCwMIqKinA4HMb9cfVipZkBw53UlNnMgOWagzofk/f+fyR19H/OrAEgEnpiWfM+3GRDDLZz2gvE35yabmMH03FtKp9YBaK30OnLM+sgeTeTrIKnx6XxoMf7fP3kveTXgPYPC1pvC+yfoPc2igYlCXLFnaS8NYVWn+znyUlA4AT4R3cWkQ3zfgavAcxWNgMQ5wcpN97BvT+DuN3O4LuAuikw+jSzSSSBPWTwOjOIgwWddAB6LooGGvSw2/gYSt9MYubcEdAO3eO5O0QXlU2Mh+U5pI0ZxGOcIqX3lUAYQ6nSZR9eOsRjy5Px4AAOwvgDxbC4mOA5+9j0dhLMbMtsukEXGLh0F1BF8IQMgrHDM/p2ZjIC8GNe1ufMppveuDG5ClKrdA0liuEhmB07EoYXMWe9Aj1qYFRPVq6v13kfi+voSglT+Al2vkhwJxDdglEPNUbP1J/fOut+NgdOv9o0oOY8Xr+DXRIelKviuCvxwTzgmwczSVyQRAXzwCg9C2lmWSPzOhLYzO06zOFDcx2WzFE5HA78/PyMFumg08I1TTOIDx4eHoSHhxMcHIyiKGRmZnLmzBmDwCCtrq6OoqIioqKijBBely5dqK+v5/Tp04YwqzymoKCgJvmstm3bEhQURGhoKJ6enjgcDs6cOYOmaYSFhRlgJot6Ze5N0zS6d+9uTMvOzjYKj0NDQ7Hb7UY9Vnh4ON7e3sZ3CQSu98MdAaK5ZdwRJ87HLntQF2AHE1ELVURQEOr2MlQfGM8jvPuYSvo2fcDr0iqR4HTQspxK5mt/Bs+TVF4xhedftSGG2KEQojYA/wBllw3mWYj2X0vudBjXA/6lQMSwfVS/YcF33SdMnFDEylGrGDHrHWa2eQTSUhBC15I79SUowSB8BJ1jVLbmQOjHNspftBDIXtIYwURWkIuD3DlZzOIwi2cUc4xQWFzFTLby9pp25I4ZABvLWEI/xrOCNf7TIPUwTO/Js0u+oIFQOHQY3urMpgfa8GzlF+Te4ctrU4cxfekGvqEde1f1gAkFlBIMfz0NVMHLPRn48C56UANj/RlAGa/RirmLN/EKMYD+cLuVCADSIgYxt2gT84lj9PJSNuNPw2LgzdZwLAISrwSfbrDFCn3+CK8CeHGMUHrhzcTl36BMtSGwI3qbVMo7P2B8bqWq5LuAk6rWI8RFVBi/RJ/rLgkPSpIVZKM9s1SRu8HOXXGonOaaN5IDmtnDMntOUtXB7G1IoDMvK+fL7UhPStYmyUFftsiQ7TKqqqrIy8sjJyfHYP+FhYURERFh1GzJ/Nfp06cpLCwkMDCQkJAQ2rZtaxT8+vr6GmARExNDSEgIERERBvBKBl5ubq4RipRhPlfgkCQRqSMo28jLhwJJ2ZdkFFnzJO9VS4W4rvOaC/WZj+dC7LIHdQGWUM9zI/6N+nIZ2r8Bi42/iYmE7oKOlZAQr9K2w4eQDwUj9VVEYhtoO4WrP4AzEyyorVR4CaxJAqX6fbQ/WxBHBLlTB1D0pIV5CqQJgXjRzsPdVrD/plt4RFwB71vwfeZZ6sNh9z29UNOOA2CNFAgfgVqvEpINobuBHhCYZGMmO5nPMr7BjwlkMJETPMvNNAxTWUd7prOLRQwhFx88NgqIDWImyTo4BQD0hD4/sYRI5hAD03vCJz5EU8QsOtGKeqKX/sCSxNvZSwRzJ+wlkceZyVEWkgpjejJu2nfcQAWbCeDPlPIaQ3iMfOaPGU1/qoEypvMTo7DzDFaii35gPolMYg/peNGAHwyKgQcPQeJQyA8Az+1AFXSsgcoDTOQbPmMys5jMSmIZvvR71jnVyEPdtGt3BSegCTh1bqF54XlZA5c9qJbMz8+PmJgYI+EvQUjmlaRJUHCtsZHTJRPNnMeSAONKSTeH/Fw9AteEvxyU5XepEFFZWUlISIgRGiwrKyM6OtoQci0qKqKiosKgdoeHhxusOl9fX+Li4tA0zSBaHDlyxMhleXh40LVrV2pqavDy8qJ169Z4eXkZckdt2rQxFCAcDgcFBQXGdkJCQoz8VkNDg0HukPR0SZEXQlBVVUVaWpoBsJK6LrcdGBhIWVmZEdJ0zROC+5CeO2/K1X6JN3TZgzp/i0mrYRd+UGTDMdfCSYeFjn+3ISYJkqwqyvUgRCdAkJEG6hEVhoLIF1h7AF+nc2LMGKyPPqpvsOYLlOxViARY9qqF7Ep4lnd4z1vl5ytgOlB6RB9MhU1QDXimHUTUX4FIaDwu3+4qbAGtHmp7gM8XwFYLXgOXMpcbIBZsWV+ykW48zUae/8ufmZm8n0WjboEiiN6TxkPk4pn1FfuI4rHKZFZtDKI7tfS4s4YQTgGw9K2eTC/awSqCmEgWc4hnHKdZl5rOIjKYSUeGM51FdOIxjsIw6LWxglkvXw/Tqpg53g/2QNvUOhZt3EYDDbRjBUvGT0NXfipjOj+wZNIAli+Pgnc8YEOELg776KfQNZNlSRamHAMG2Uh4YA/jyWcFr1KJjKLEE8EHvLjuE7644xjvuHpKaXubyBu585wuvEGhG7tEn+suCYAya9VBo4SRazJeAoi5lYQrq8zcQM9dTY6ZBWjW/TOTAMzHZR58JbhommbIJMmwnKyzkuoVHh4eOBwOw/sIDQ2lrq7OkEOS5xYVFUVUVBSAAWCyYLagoABPT09CQ0PRtMbmipKmHhwcTFVVlZFrCw0NJTAwEEXRdfsKCgqM9vUVFRVNqOCaphlFyYWFhU2KpD08PAyShNy3rEUzE0yaK7p1ndecXShZ4jJL78IsBx9d/WFGHaH+Ntj8OnQBtZeKQCDyG5f1VFU4qYOTNLXHGObxD2b882/4XuWD6Kq35lDTTiAQ9EpX4eB9rDv+OuyaDKc+wR6nYssUqGk/IRK6IxKuOOu41ga8wJPaU1itAqogYfke0q5dwXx6MpBdjM5ykMJQIAwPFKY/8D0++NBry25GUckSOjOftgzkFPvwYRbZlNIRhQWs5Bngfhhmg6th1cIgckngCD8TTRHr6A7Lopi5Lx7WVLGDOiCL1xYNY+7kTcwiEaYdADrBQfBIFcxgCI+xm9cIZw41sOYwEAbDYlmVrBfksjYPPMt5cnN/XtwMFG9nd+81XGkDdneBJz4lbdXNzN8Cc2hgQeznugiVAAAgAElEQVRNkGVhPtuYa1/N6rDV3HsTqO+mQvhuQ5bKVXvvoob1pGno1PhL0C4JgIqMjGTkyJH89NNPHDx40NCsM4OPefAzg5OcZh7s3HlZ5u2Y20CYGXHS3OW75LSamhq8vb1JSEjAw8PD8KYKCgrw8PAgIyODkpISwsPDsdvtRvO/rKwssrOzDaKEBER/f3+DeSfVJoqKigymnxkApaCrp6cnISEh2O12HA4HdXV1REVFUVdXx5kzZ8jKyiIvLw+73W4ApCSKKIrShDQi9fXMYK0oCna73aDOS1CSHpqUZ3IViG0pH9USaeJC7HII70LMn3lZnzOPv/Fs5evMuvMaHFkWQjJB3RYObUbRa+Js3hFd+ZDnEYXXklSoouSgt3yYZuNGYccnG0S7v6D1UlFSBCKhE8OTdJCjFlT2smDwmzzILdicHoBI6K63h3d24FW7qohj+ud5h5/ikKm9RyAa5AwFTjCAanLxpTX1MD2WxUvCmEsyBQSRQrBOYSeIYcxmALcwlCoWcINeGzV1JU8v3cgRVrHpIDyWnEw4DuyUE0ghLxDPfPYyd0oHBuJgLyEwqCfz99h4aWYp88eMho0wju/YwDEaYlUGHHqD3gzgtd4PwayvWUAdZPZk+rQdLMmKJfedThC4B8ruAp/xnFLeQdt2H6Puuo4rdwODbbB+va7Lt/YneG40C1Lg2bt9KWAuc5kCvWzce8RCdShYuJZPxUe/7c9EQ69NuwTtkgAof39/unfvTklJCUePHm1CIoCzn7TNLD6giffjLtRkBitzKM8MFGZzJUaYp8npksot91FZWYmiKJw+fdoAAofDgaenJ4WFhUa3XvMxyYFfdu/19fU18lxSqknuX+r0yR5N1dXVRr7Nz8/PCI/abDYcDgdlZWVGp2LJWpRNFaW3Z6baS9KIvN5mtXRXb9PVE2vJmpv/S6nmlz2o87c2lKA421bNYjL7qiGkAmqKoWymhXIgV3RF3RaOaPcacC3v/gmOKZBwWIUJ7wNdsLbTwURJcYLNx+E6OAFPqUcQYiAIiE57F9qpCKdOnwFODhU2bYJE/bgOVTmnp6uIeEHK2lDG3fkd+XgQRQW11PIsfWBJFuNIo556XqMVU/mRKFoza1hXkpOncxWCt2gL470IWBMASwsA8CWZhUVleODBHiLYRCvm4GARdhbwNJOYzHJuhIhYRu/ZyVyugEGxPLdxOzMJZ92oPzBuy3d02/I583iKg9wOh26EsT0AP3jndlKwwKIyoAG09nqh8MG/8M6JkSg/6HqGLw1W6XHGAl9vh39FQWoU1MDEe1cwi/vxYB3adaCEwrjQd/D9YA/85c1m76eqliNE4EX7fTSxyx5U8+bj40NQUBC1tbVUVVUZSX5znshc+yTBAhprp8wDnjvlAjOxwvzd/O7qmbnSpuV8yYSTArO1tbUUFxdTUlJiMPvy8/MpKSkx8lCSlGH2QOR5VlZWUlBQQHFxMV5eXsTExBikBdmKXQKIn58f/v7+FBYWkp6eTnBwMEVFRWRlZZGTk0NRUZGRb5LsPQkwEmSkV+Wq/uAuxCnll6RaulRjd3eN3VHH3QHK5Tqo38YUFLJl09+3Iuj/3teETOyLz9ZGynKvQBUxQsCI/8DUqfRYKpirqaw5AhwYRFKgBWt00xyHuFWnqatpOxDCJN77ylWIBJccyp3hiLVCV1aQ0yJVRKEgcwzkCuD60az7HLjHRqui7wjlJ6azD198WPDMTdA9jei7C3DQHl/yIfkwz3CcZ2ffxqSF/2b5tbFsHDUG7gzi+efGMHzG98zmap7lC77BD9YEsGD8QJ4jhUq2spwoBvIjfy46wkx68BxHqdqzn12E0UA887dsxgMPZhMPiV2pTn2HZ9jL4veeAo8HwWsyW1Z3ZtDYWexZP4kD426nTxmQN5KAb4AhQClUOqWkRNdwwO7MJwmiUXntJATuS0MZawMsfPg1rPOFRbwBwGZ1FzeIpnVQFwJOLdVMnWWXcIjvkmDxaZrGqVOnjCd+CUzuqMiug6A7AoRc3szCM3sBrmwzdzkT15yKBChJFCgrK6O4uJj8/HwqKioMuaDMzEyOHz/O3r17OXLkCBkZGeTl5VFQUEBpaanB+isrK6O8vJySkhIKCgrIycnh5MmTZGRkkJ6eTm5uLmfOnKGwsJDy8nLy8vLIz883vKji4mIqKyuN5Y4ePWr0qZKK5eXl5VRWVhpahDK35drHSdaAudZ9ST3AyspKg64uvSszILlep+byTy2B1vn+Ti6z+M7fyvFkOTczn2WMfuAV8Muh5GOdmKCmHadHsIpvt68bV1i6lKRclXXvg88poM8erNGCpCM6S0xVc0nKMPcmagSnT9VvEf/UgavyCn2ZVqqKWGtvelA33YQo1AfOXBkOtAl42QaL4Bv86EBHQgjBGx9mLf4U7r6OXO6kDXaWvPNH+LCBxb1vg3gHodqL4P0eg+58CWL9IG4ewyiFVXnMWh9MKf7wc3vmY+UtgpmDFejBlZygjjqeYS8zGEIaP7OJjkAZ2WRSTTXQFRZ9SUOiyuJ1HWGFjQV/6QeVnaFqCHvW34dI6MJoDYqq0HvM+4xAlDo9TlU1PgOIxxcb5320UCASrmM6OxBCoPwRxPVBzNS7uTQBJ/Xb8GbvcdL17hl8F1Qz1YCucXiu1+9gl4QHpWmakePw8vIyhEnlPHPoSdO0Juw+18S8eZr0wsygY6anu267pZyX9Nz8/f0N+rj0fhoadPXxgoICIwclw2jyJZlzrioV0urq6vDy8jJUzsvKyggKCqJ9+/bGshUVFYSGhpKTk8OZM2eoq6ujoKCAwsJCHA6HwdaTxy2P3bxPOc+1MaT5s2t+ToKWuZjaTOE/F/BcTMLEZQ/q/K3EN4he1SfxwINNq7rw5F+uJFJpRdHKfPC5i6wuwHt/RE17GUKnISIF1t2z4LZnEfUCdYCKuqkflNooUi1oV4K1g/uB72ZxDbuSVAZbBf4H9WVc6dEJqkqam4FT3RcOyVkwIJaHyeN5ormfo+ymE0PJZiYvoaDw7LKbGX3fTj77zwSUN4B4ePEtX7Rlb5JjhzbhFrh7L1MzBjK7w7csoJI5/lfB9zB3xRAI3sP+sREMZA1LaU0wdm6nHJ7zY82McYzmJAMpJ4XuxFHOPL5gXsmfYLcFPoPSZDguBKNVlXohSDqokqUCGsRH6nm7MFVli7aNKemgvQxW84n+52zx+dtFXzhwoBFQ0n4CIGmdinWcE8CvsZ+1njTrF671UeEI0fzybq0BnehxCdol4UHZ7XY2bdrEsWPHDOUEOJvsYKaIm70ms3qDa1jOncdlXk+aOyaaXEe+y/5IFRUVnD59mrS0NA4ePMiuXbv4+uuv2bt3L6dOnTI68UqdO6lmIb0YSUyQuR85T0oc5eTkkJ2dTUFBAXa73SBYlJaWGnmhhoYGiouLyc3N5fTp00YrdrOShgzJmcN3Zu/UFZzM18L13RwmbEmOyh3QuN4H83V13c65zHzczb0um24x1XbS8WL2mJE8N+EgL67qRx9egonbEF0FnT4CLRiKhuvgBMDNN1PRF+aoSzgQBezYgBhspxCwviYYoNqM7X+s7miyv8HW5p/a1bQTTcBpi9o4dCdPsjCVHSxY8hXvEkV/qlnqfw976cyStT1YtK4DdzMNvoNNRydgndkTUfUV+QFAl2qsqwQxPzu9hv0DKQgHCGPO7GupPGBhYfJWCMiCsQ+z6Zkh7MOHZzlBD/5FIBrTZ2yAV2PpTQGzmMw67qNWFv745cCnIHoLjm/cSPcwHZxUVcV6hSBu/bt8Yjrvu1jDYKtAFAqs15zbi1HTVejTx/gu2XsSnC7ErlDVCwcnuOxBncvy8/ONgdUcxmkupyE9KEn5lvPNnpX8bM4tmbfV0tO+u2lmFQapsVdTU0N+fj5FRUUUFRU1CZWZj1cCq9QDlPs3kxTksnJ/dXV1+Pn5GeroUrmivLwcHx8fQkJCDPV0GbaDRg9NvrtS5c3A7lrwbC7CdeehQtNaNHfXsrnr6g60LtTM1+qynds88KR0fTljxi7g+srVPFgOEesC0KaPgAw4eRt8rsF/gQ/vVFFutiEG2gnYCPTYwJaUVWC3AIIOh+GmHio/CEEHVSVDCG415Z/UieFogRasrzWjFZfQqcn3USJJX8+qgroXEqNYkPoVPajlB3yZXrkBP/yYnzCVkoHQkAtEWljg9Sbqtw/C8Rt0EsY13oRxBawDLEDfb4l//xpY9zMoNfh3AW3bo8wu2ApHYVJXC8v/bSOl6DsGMZSltGEgvvD4YXaxg3n8g3mjbmTBlgKCOcnT43/g+XUbnPVH8QR8nYpIKtG1DAtVRIJAjVcRTpB6XXQ769yTjqu6Soe76xL/CxXK/xOOuKkpGB38pVJI9eidiC9BuyQ8qOrqakpLS6moqDA05uRTvnngNIfoXMFLKiqYJY0kmAFuvQbX6dAUJOQ+ZBdeWaxaUlLC8ePHOXToEKmpqeTm5uJwOAygkNszb7uurs4gGEgFC+npSFCrrq42pktPSpInpMZeWFgYoaGhNDToIrcytGfWEjSfg2t+xjW/5wpc7jxPaWaA+L2A4rIHdf522nIKrrufjW/vwMMfIgJh++23Y90o4CWIOwhTlCM8aRUoMTZ2TrKgHroL7QiI92ehrZ0AoZ9AcTHeNti6YRUUF5MhBEmbVZIOmvJRK+1ngZN6RI8bqT/NdHt86sfhzHrwZdg7kOmpO1CoZTP+vKDdyZKTTzMtayrCUxD6JtgyBeKAYDQPon0Iqx/QoyxC1FIsBIr2ib7Rj69BCQfKbwdq0daBkrUf2oxkerfnWb6qH72KdhNIA9G0AarYy3geI59kpvM2rzBuy3ew/ntOZ9zBGPFHNG5HCE/UehWRVELStyqqt0rRCPBWVUS6k5VoO+n2PK3/uvqX3sJmzRWcfpVdwh7UJQFQcDZ1HJqGhly9KhmicwUt8zRz/sVdrQ7g1rtqyWpqaigrK6OiosJoyyHzRq5MODNQQlO5JfN5S+CQLzPY5OfnU1paSllZmSE66+/vT2lpqQGK5jCe3K9ZX9DdwO0avjNPd7eOu4G/OUA41zW80OXMdpkkcf7Wx4be2hzo3RNYC094vIcapmJ9TXCwVsC7T6DmqfCnUwzpboOJK0EF1f8+lH02RKc41GuvxdpOUDp2AurxjqgWFesNAusV+sCclOskUaT9iHrMBFo9/PX37ouaOcCdbKc1HB2ihyJ5lIaXVe5dngpJNkJynMtZwBKnb7deCJTByfzF9NMZqx5HdIrDS1UR7fXiX/4M7BqCMstG/i190TJhyZjbEb2Wc+iju1m5aCgzEq8D4nmMt3mNcKCKLDJYR2uo7kfwrk2oaYexyqaAzsLmE9NA1Aoi1v+LWqfXosaoCEtHkqxuSAtLlwI6M0+/TnvP4+79hlaH7kGd63UOUxRlpaIoeYqiHG5mvqIoyjJFUU4oinJIUZR+59rmJQFQ0quQdT3mgd78RG/OR8lpUnVCKlGYwckVsMzruXpgrsBoJhlIYdaamhocDgenT5/mzJkzBnPPlXEotyHDbubzMb9Lz0nWHLmCU0VFBcXFxWRlZXHixAkyMjI4c+YMp06d4sSJE2RmZp7V6dZcQGven/m8mmNINgdk7rws+d1sF8rS+6Vhvsse1PnZgY6JEADaukysqwR47iRl1ZsUOaNt6rF/gN9Yxo2E8eM3cOYHC6w/gHLDNj55xsL0rA2ohx+HElDT9hH8/lbwteisO5MpTgdBJPRDdD1H36JT+gDeXVWhugN71+5n0oRBrJv6B73LbTmIpBK0DRaj1sreS/egpIluwXgPsqGG6dtaL7qQVK9SJwS9VBVtDmhfgzjxN8RaOwMj3ufEraCNtqD+KRylIBUmWuAh4JkwXqM/c8hgDB/AIBtQReL4yey/czT5105guVMnT8QIVE+VEqMYWW8936WVinDKDVmTnICV9u1Z5y6ZeSJhIKobzb3fzS6eB7UKuL6F+SPRq+ES0bXf/3WuDV4yAOXKrjPPM79L0DHLIknygo+PTxPQckeEkO/mJ+3mQnwSnDw8PKitrTUo2xUVFWd5Qu4GR1f6u3kf5vXNOSN3ICaVNcrLyykvLzdaZ7geh7tzaM7OJ3dkDqs2R35o6fv5eEgX4kWdDzhdBqhG6+bnhWgvULbrg6Xo4Q9eOw2ywty7kyDiftat3s2asjeImQKkXE8uI7glGZass5A7YSf7fYCBDxN8VwkQR6CqkjRD1T0vgFAI7XJ+A65or+87YCVQfQ94xrF86kNEL/0B9q1AjNJDV9bQRkAygxPobEAOAt/uR03TvRK7RW957gsog20ojggqP/mcJJvKscN3YTmO3g79lTywJOrFxBFF0LGGiQjqqCOEP8AI4L3bWCvepW8dZKQJJlkFSSucIFV/NgAfzz97mki4xvisqoVnz/9ftc74JSZZfOd6ncM0TfuOln2tm4B3Nd32AGGKorRpaZuXBEBBY3JfmrkY1wxg7p7SZVGrr68vISEhhjyPBDG5rGs4r6UwlpwnvRoJTOb2Fa7bcAUX4CzgdQUjs8qDGaCkJ1RdXU15eTkZGRmkpaWRkZFBdna2QdIwL2/2Nls6T9dp5vCnqyfp7vP5gkpLYPFLa6Iuh/gu3LT3rzHyQZpTzUHdFM5KbSrYUimacCVjgu5FSdQZem1YxzPDXwDHg0TzLX39j8PeZSjaHcz769/p9t54lAeeg6f15YUQJHrBfeoxt/vvp6oMUf9gfFc9VZi4l6N/zST5tscRd9vZ/FI2DQn3N67k4mGYWX9pQiB22hEdCll9+xRU1R9rBBRfD6x/GQZUQOiTDPEGJVBXrvjR6Y3tn3AlIkzgq6osm9CfXg9Y+Yl3Wex/m17UO99CyF36fsSBRhCx3u+SX7OdvwckRGTTdQ/q45J67B9ul0/a/Bt7V3VA4Xm8fr21A1k5DkCWc1qzdkmw+KDlHkJyGjSKwcqXuTZKURSjeaB5G7IeynVbLYEeYDAFJYjIaebtuANPd/uQn825NjON3pwvk/sxhzTLyspQFIWIiAiKi4uNkKi7AbklT8Id6LvOc7e8tAvxeFpiS/5ST+eyh3RhdoW3yld3gpY8BOXwEERPfaCdNP/fLH8G6JFIBz6kdFB/SuZYCP0KGq6GxSM2Q+jzsNoDqrqAPRWHAvPsf4OPUnAM7UXIzBngHPjFESE/NjH1RCZCCHbSqMRtbws24Uk5guD9+nJJV/4dq3kDLh6GZP2BriMoRtjh2mvpIQRCVDLW433S9t7l9FyqUfe/COs2wI/9GDBHYHOMoy4ESpwED6sQFCrfk7L2RyhaycDJu9iHDyyz4aiynPO6Csu5PSBvVTVyVE3WvUIfi6T4rqtZb/iNvSuN862DilIUxXxwyzVNW34Be3I3eLT4h75kPCizmbX13OU5zOw0uYzME0VERBiNAv38/AwvyuyRye3I95ZCYq41RNA01CS/u053bcDobrvS3ClnyOOV86TqRFZWFqWlpQY5wl14y/V45OfmGIvu7JfO+yXLXYhdjBCfoijpiqKkKIpyQP7hFEWJUBRlu6Ioqc73cOf0C07sXirmrxzlYK3gulVdoAr23bmTpGqVwG4qk8Q4tFAgbQStqOfoHgtxmlM/LwZ4+yEAtE+HwIN7mfvgZnjOBl9ugL/W8HOOQKy50dhXd1WF9HTje9IMVadfd4oD9J5FUonbNWQHYPV1PyirlrO9CTHCjp+qghBGTmu96MKZzno/JTVJRfT9EmHpiBhl5wdhofBnQYkQqMfsBgCMFlcz5s5CiHidkRSxkEIIslCRDeqG5tUbztfcgVNL9vvlpTR0N+pcLwo0TVNNrwsBJ9A9pjjT91jgdEsrXDIAZc4XuXoc0lyf/gGjGFVq1YWGhtK6dWtiY2OJjIw0FMDN2zQDkTlU55rLkZ/lPHeekvn4zZ/dhdxciR9m0DPTt92FCGUIUBb1mkOF7sxd+M71OF2XdwUu12tlvvYX6kldDDOHMy9CiG+Ypml9NE2To8LTwNeapiUCXzu/wy9I7F4qptTrVG5uO45S+glKisDqKxgb+J5em/O9gIRt3KfdRddv4Q654hHQWmVCZTeUT4BRUdRRR8SMQTCuNxBGd1VF/byRnfeTEBAfD+gDrfU5YdCvobFnkbtW5i2ZKyFDVVXUOJUqSVRo3zg/2yZIXLGfY8383Dx7SF28RnuV1RDwCgA11EAt+N+st6OX1ssFOMz0+otp7vJSU5J+C9DS0KmP53r9avsMuMf50DcIKNE07UxLK1wSAOUaYnNl30mygHlQl8Ak+y9VVlZSVlZGaWkp3t7e9O3bl6uvvpqYmBijDbu7kJYrsJjfzcu5ezd/dgekza0vP7tOd1djJAddmQeTGn6ukkbnOr5z5XzMoGNe1p132dz05uxielIXw4Nqxm4CVjs/rwZuNk2/oMTupWLWmijErXa0PSA6xeHZQyVps8o7oiuKXkaE8BPMfjsCa6BgrfIh6tHFTLoTlIpNiHbVulRPMgQQQBH5zGQTsQwnYDUQG6Q3H3Qx80ArO+ka80ytzM22rpmBWE2ZZHyOTtQFUIXTA5vtZp36fn0pM+2/tnfjMvVHBMPUE8b3pM0quQC7bNRSy/zZo2GhTWc8mixFCN0zS9PZ05JefyFm1jC8EFvWjDpHcxp8v8zO24Nq0RRFWQvsBrooipKlKMr9iqI8pCjKQ85FtgBpwAngLXAKD7ZglwRAmc3Vu3HN5cgBW1KxJVVbFrfm5uby888/c/jwYTIzM40Gf+7o1nK77gbZ88nHmI/3XPkW8zxXL8kcfnMFB/ldnqOsu3KtC3MHTs1tq6XjczfI/y9ySb/Uq7pIAKUBXyqKYlUURY6A0fJpzvne2jn9ghO7l4yFFKAeuovQP+kht/ojggfnQD9UNIsu5gpA8GSYN48va+5AdHuGSVYBfUbT/dpr0YKC4M1H2Kw9Att0hfRh3AD3bmOfzUL1B2+3eAgioUuL89XndY9mXDMDsejVGEWKCz1ifE56TGWhm3U8Uz9s8v3KFbYm35NFo6KF9Qah57qWWKinHlQL4lM76vazw3slQiASerZ4Li1ZcxqGv3h7X1zM7V0cgNI07U5N09pomuataVqspmkrNE37t6Zp/3bO/3/tnX+MHHUVwD+PXr1KsSdQNZ5BihXtFdFCh6IBDAnUno2x8Q+0aLQYsMYUc5KLoRoTm2oikSDwh5LU2JQQfthESWrS2D9E1BijnUMCbY8mUCuhNK3cSTzLabnb5x8zcze7N7sz487sd7b7PpfN7c5+d75vvndv3r73/X7fU1XdpqorVfVKVU29iNIMlIgMi8jRMHa/vVVb1fn9RuFnF4Rq4jfxWB91x6Kb9vT0NBMTE3NZGOILJ5L6TrupNVtMkXQjb/W60VDErzMeBowTDwtG2SOazT0lXVue62yULX7tjdeVxcA0a9PK4KXJlzHEt1xE/Nhja8OprlPVqwnCd9tE5OMLOouJmyRKbuELIo9eDZ0dYvLTR3lqzGfsBz73rvXYdf5LPIPP2FKfyXBi3H//Jtixg8XP+XgvPMgHPQ+GwrDd00/D5w4wALACvs8oj4QlIa55Fbw77mjrevzt2TMi+P78TH48a8VbPW9+8+vM5vrPXNNw/oR5Hv/66/mV3g2n+oPX64PPrD0RbkB+e4X2LJVCx0J8uSllFZ+ILAJ+DKwn+MZ5UET2qeqRpPbx1XjNvJ34e1Hb+DLy6OZ19uzZucq2IlK3iTXetnHRRMI1zLWPXsdvrI03/6TFFklGLf48KTzXKEN8XCIvCliwDysLjV5Uo3faKFtamyz95TnezjkbeE3n55aSzvFq+Pu0iDxJUG7ulIi8W1VPhiG802Hz3BO7ZZFXr14fn+Kipx5F7w8yR3xzzOfn04eA9wQlHFaBTniMXTx/s/dXjXDUH5lbT3fp+zzu7r+HT725ne9NBSv1vAcvxB/5J0wkr9zrNNN+sKXXW+LhfyBFoKSFCw88wMNj4O2+EK6eN2hRoUb+CFxRmLgVJPKgqkdZHtQ64EVVPaaqZ4EnCGL5TYnfyOPeVPReoxcTNzDxfUPxjAxRrrvGPpK+wbcK6cXDi/HzJF1Ds7maiMaFGI2GLf6I2kVtkrymPDf7JGOZ1H8S7RiVohZJQPv7oERkqYi8LXoOfAI4RDCBuyVstgWIaiPkntgtkVx6NXjRKzz/2S8gW4OFhxd4HuNnNuEdnmZydCX+C36dcYqQ0MtYe5vH34/53OLfzA0/nA+V+SNhwcIb2l/pViT+f9qzllE9qwXHr6iAFS6VGj3lQZEct7+2WePZ2VmmpqZKEiU7WUNlSe/l8RaSVgtmPUfkQbVLM0+wDIo8bwHnehfwZGg0+4DHVPXXInIQ2CsitwMvA7eE7fcDGwkmdt8AvtyuAG2QS6/GlsGVj4N/cTCPs+p3wIvg3/u1uWwS3nMe/ofrb8AavhdfLOBvWHjz9v9QYMLSDrJlrcfDLUqDnEtMXZUlPFldD6osA5Uatw/nBaK5gX8T7FV+rSR5srC8x/uvggwtZ9RzLIJodY5jwEcSjk8ANyUcV2BbW50WR3692sCEh1f3N/U4VDcX41HqHIvr/6lEGUq+5tT+O8ylIrJVW+5b6i0DlRq3DwdrbsBExG81b1A2vd5/FWSQ+l3qifR4KiPTqy6UwXX/kQzE/i/inIeylDdTz+EixlWWgToIXC4ilwEnCPYAfr6kvoweoqwwZJdgemUUTmCg0vXqnDFQqjojIncCB4BFwG5VPZzyMcNIpZcNlOmVUQaLIJOBckFpyWJVdT/BBHNW8uZ1Kppe7x/cy9Cy//hKyl7F9Or/wrUMrvuHFjL0Ae9gttnbc7yU2qJ4pJe/kRrdRX9/vw4ODqa2O378+JjrmL9hdAvL5DJdx87Udr/hSx3Xq8qU2zCMLNgXKsMolvOA86lmZMJ5LtM0owAAAASVSURBVL48qVsK7DNzuYUC+9wtIqdF5FDsWEdLPDSRYYeInAjH4lkR2Rh771uhDEdFZEMB/V8iIr8VkXEROSwiI+HxTOOQI9VRz+NCr8J+O6pbplft69VilHdSS324wKmBkvnULZ8EVgO3isjqDnWftdxCUewBhhuOdbrEQ5IMAPeHY7EmnOMg/DtsJkjyMgz8JPx7tcMMMKqqQ8BHCfLgrSb7OBSVLPacxrFeQWd1aw+mV23pVeRBpT1c4NqDyp0SqUSalVsoBFX9PTCZsc9SSjw0kaEZm4AnVPW/qvo3gkwK69rs/6SqPhM+nwLGCbIjZB0H86CyUSW9ghJ1y/Sqfb3qA/OgmuCqlEGecgtlUpUSD3eGIY/dsfBLqTKIyArgKuDPZB8H86Cy4bJESBV0y/Qqh14JSh+11IcLXBsoV6UM8pRbcEEnx+UhYCWwBjgJ3Fe2DCJyAfAL4Buq+q9WTes6z2CczEABbkuEVFm3TK+ayKAZflzg2kA5KWWgsXILQF25BQCpL7dQJs367Ni4qOopVZ1V1RpBlcso3FCKDCKymECJHlXVX4aHs46Dhfiy4axESEV0y/QqINM4KMpshh8XuDZQc6lbROQtBJOH+8rsUPKXWygT5yUeGmLwnyEYi0iGzSLSL0FqncuBv7TZlwA/A8ZV9Uext7KOg3lQ2ei4XkGldMv0ar6vbHpVUQ/K6T4odZO6JW+5hUIQkceBGwmqvb4CfBe4p0mfpZR4aCLDjSKyhiDMcBz4KoCqHhaRvcARglVC21S13a9R1wFfBJ4XkWfDY98m+ziYAcqAI70CB7plegUUoVcVTXVkmSSMrqGvr08HBgZS201OTlomCcPIyKBcol9hNLXdTu6yTBKG0Qr7QmUYxVNVD8oMlNFVmIEyjGJRoFbRVEdmoIyuQS2buWGUgJqBMowiMA/KMIrHDJRhFIB5UIZRLDPM8DoTrsVIxAyU0VWYB2UYxVKjxhvBavPKYQbK6BpsI65hFI9SY5ozrsVIxAyU0VVYiM8wimWGGSb4h2sxEjEDZXQV5kEZRrHUmK2sB+U6F59h5KKIXHziqNqsYVSRWhjiS3ukkaZXIvJeCSr//jUsQ7Ix6TxxzIMyuoYi9kHFqs2uJ8jqfFBE9qnqkQJENIyuo4gQX0a9+g6wV1UfCiv+7gdWtDqvGSijqyggxDdXbRZARKJqs2agjJ6kVswiiSx6pcCy8PkAGcqMmIEyuooCDFRSRdNr2z2pYXQrBS0zz6JXOwiqLX8dWArcnHZSM1BGN3FAVZdnaLdERPzY612quit87rLarGFUDqV2YJozndCrW4E9qnqfiHwMeEREPhQWdUzEDJTRNajqcAGncVZt1jCqSAf16nZgOOzzTyKyBFhOiwrLtorP6DWcVJs1jHOcLHr1MnATgIgMAUug9eoM86CMnsJhtVnDOGdpplcishPwVXUfMAr8VETuIgj/3aYpk8pWUdcwDMOoJBbiMwzDMCqJGSjDMAyjkpiBMgzDMCqJGSjDMAyjkpiBMgzDMCqJGSjDMAyjkpiBMgzDMCqJGSjDMAyjkvwPkV+sbxB6xSoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x230.4 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1 = plt.figure(figsize=(6, 3.2))\n",
    "ax11 = fig1.add_subplot(121)\n",
    "ax12 = fig1.add_subplot(122)\n",
    "#cax1 = fig1.add_axes([0.12, 0.1, 0.78, 0.8])\n",
    "ax11.set_title('intensity')\n",
    "ax11.set_aspect('equal')\n",
    "plt.sca(ax11)\n",
    "plt.imshow(im_intensity, cmap=\"gray\", origin='upper')\n",
    "plt.gca().invert_yaxis()\n",
    "plt.colorbar(orientation='vertical')\n",
    "plt.tight_layout()\n",
    "#plt.show()\n",
    "ax12.set_title('lifetime')\n",
    "plt.sca(ax12)\n",
    "plt.imshow(lifetime2,vmin=.8,vmax=1.8,cmap=\"nipy_spectral\") # This sets the scale for the colormap to 0.8 ns - 1.8 ns\n",
    "plt.gca().invert_yaxis()\n",
    "ax12.set_aspect('equal')\n",
    "plt.colorbar(orientation='vertical')\n",
    "############################################################################\n",
    "# SAVE PLOTS #########the following formats can be also used .pdf, .eps. .svg\n",
    "#intensityNamePNG=basename + 'intensity.png'\n",
    "intensityNamePDF=basename + 'intensity.pdf'\n",
    "#plt.savefig(intensityNamePNG, format='png')\n",
    "plt.savefig(intensityNamePDF, format='pdf')\n",
    "#plt.show()\n",
    "#plt.savefig('intensity.eps', format='eps')\n",
    "######################################################################\n",
    "#######\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set a Low counts Threshold Limit and /or a High counts Threshold limit for your image.\n",
    "#### apply a simple INTENSITY  threashold. Show all pixels with intensity value equal or more than LOW threashold \n",
    "#### or equal or fewer than the  HIGH threashold\n",
    "\n",
    "### OUTPUT: ROI mask , Intensity/FLIM image with ROI mask applied , Histogram of lifetime for all pixels within ROI, mean lifetime per ROI, Area of ROI as percentage of the field of View"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x230.4 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##########################################################################################\n",
    "LOWthreshold=500 #threshold given in photon counts\n",
    "HIGHthreshold=15000 \n",
    "thresNAME='_L_' + str(LOWthreshold) + '_H_'+ str(HIGHthreshold) # Name used for automated saving\n",
    "##########################################################################################\n",
    "thres_image_ROI_mask=np.ones(im_size)\n",
    "for i in range(im_size[0]):\n",
    "    for j in range(im_size[1]):\n",
    "        if im_intensity[i,j] < LOWthreshold or im_intensity[i,j] >HIGHthreshold :\n",
    "            thres_image_ROI_mask[i,j]=0\n",
    "        \n",
    "ROI_pixels = np.nonzero(thres_image_ROI_mask)\n",
    "N_ROIpixels = len(ROI_pixels[1])\n",
    "ROI_area = 100 * N_ROIpixels / TotalPixels   #ROI AREA as a percentage of the FULL IMAGE\n",
    "    #    ax87.title.set_text('ROI_mask,No of Pixels: ' + str( N_ROIpixels2))\n",
    "######SAVE ROI MASK AS ASCII\n",
    "roimask = basename + thresNAME + '_ROI_Mask.dat'\n",
    "np.savetxt(roimask, thres_image_ROI_mask, fmt=\"%12.6G\")\n",
    "#########################################################\n",
    "fig2 = plt.figure(figsize=(6, 3.2))\n",
    "ax21 = fig2.add_subplot(121)\n",
    "ax22 = fig2.add_subplot(122)\n",
    "ax21.set_title('Ph.Counts' + thresNAME )\n",
    "ax21.set_aspect('equal')\n",
    "plt.sca(ax21)\n",
    "\n",
    "plt.imshow((im_intensity*thres_image_ROI_mask),cmap=\"gray\")\n",
    "plt.gca().invert_yaxis()\n",
    "plt.colorbar(orientation='horizontal')\n",
    "plt.tight_layout()\n",
    "#plt.show()\n",
    "# SAVE PLOTS #########the following formats can be also used .pdf, .eps. .svg\n",
    "THRESIntenNamePNG = basename + thresNAME +'_intensity.png'\n",
    "THRESIntenNamePDFF= basename + thresNAME +'_intensity.pdf'\n",
    "#plt.savefig(intensityNamePNG, format='png')\n",
    "plt.savefig(intensityNamePDF, format='pdf')\n",
    "#plt.savefig('intensity.eps', format='eps')\n",
    "######################################################################\n",
    "ax22.set_title('ROI_MASK'+thresNAME+ ' \\n No of Pixels in ROI:' + str( N_ROIpixels) + ' \\n ' +  str(ROI_area) +'% of FoV area')\n",
    "ax21.set_aspect('equal')\n",
    "ax22.set_aspect('equal')\n",
    "plt.sca(ax22)\n",
    "\n",
    "plt.imshow(thres_image_ROI_mask)\n",
    "plt.gca().invert_yaxis()\n",
    "# SAVE PLOTS #########the following formats can be also used .pdf, .eps. .svg\n",
    "THRESROIMASKPNG = basename + thresNAME +'_ROI_Mask.png'\n",
    "THRESIntenNamePDF= basename + thresNAME +'_ROI_Mask.pdf'\n",
    "#plt.savefig(THRESROIMASKPNG, format='png')\n",
    "plt.savefig(THRESIntenNamePDF, format='pdf')\n",
    "plt.show()\n",
    "######################################################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define Lines across the image and get the profile of the mean Lifetime.\n",
    "###After executing the following block you can draw lines by using the mouse in the image. Hint: If the figure is not expanded just click on the left side of it.\n",
    "One can make multiple selections. For each selection the corresponding profile is drawn and saved automatically. The name includes the pixel co-ordinates of the start and end of the line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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1KjsQYabrIVLwbf0CDeMCzXfxY9HH320uLnL/7766qtzg3D/5OHO9RdddJEsDvXg4dL9TT3Cjd3Cpejhkflmw8KN5/xj3rx5Vny8YVAffpGxpUf4RUGokS9+FK9bHPM3AggggAACaRRggJ7Gs8I+IYAAAgiUC4GRI0fmjjMMaMOgcmuPk08+Odcl1Frvrke4E/uWHsX1+KFPjRo1LHNJ/pa65+r3Q6fMJfcb9X3llVds1apV2eXnnHOO1a5de6M+fkGbNm0sUz6QXbw7rfx+ESOAAAIIILA5AW4StzkZliOAAAIIILCTBcKN34ofof1f//VfxeFm/w7fMBc/CgoKipu7/O9wyfqWHvXq1culw9UBxZew5xa6Rtw/3DzOP2KrcNO872IVthGmhguPhQsXWriTfLgKgQcCCCCAAAJpFWCAntYzw34hgAACCJR5gdmzZ+eOMVzqXny5e27hVhph0Lm7HuEy8y094gH51vqG7cT9i+9mH28/tgp3sA9/tvURvBigb6sa/RFAAAEEdqUAl7jvSm2eCwEEEEAAgUjg22+/jaJtb/r5x7d9C9u/RvE3099lC9vSd3Pb21GrsN0wTR0PBBBAAAEE0izAAD3NZ4d9QwABBBAo0wLxt7nPPPNM9gZp4RL2bflTpoGig4utBg8evE1GxZ5hXnkeCCCAAAIIpFmAAXqazw77hgACCCBQpgXCdGDFjxkzZhQ3+XsTAlhtAoVFCCCAAAJlToABepk7pRwQAggggEBpEQh3GS9+vPjii8XNHfq7JC4n36Ed2Ekr7wyrnbSrbBYBBBBAAIHtFmCAvt10rIgAAggggMCOCYTpwoofr776qk2dOrU43O6/47nGN3Wzte3e8G5e8fTTT8/dSO6TTz6x5557bjfvEU+PAAIIIIBAyQswQC95U7aIAAIIIIDAdxI4/vjjrX379tm+oU76F7/4hW1qirFNbWz16tXZqcN8rm7dulax4oYf73PnzrWyMkhv3Lhx1qf4eK+++mr78ssvi8Mt/r1+/XqbN2/eFvuQRAABBBBAIA0CDNDTcBbYBwQQQACBcitw9913W+3atbPHP2XKFAuD9ldeeWWzHuHb4wEDBtgBBxxgb7311kb9qlWrZmHe8fAIdy1/+umnN+pTWhfcfvvtts8++2R3PwzOW7dubSNGjLAwAN/UI/T5y1/+YoceeqgNGzZsU11YhgACCCCAQKoEmAc9VaeDnUEAAQQQKG8CRxxxhD3++OPWsWNHW758uU2fPt1OPfVUy8/Pzw5A99xzTwvflodvgN977z0rLCzcKtFPf/rT7CA+dAzfyj/88MN20EEHWZUqVXLr/vGPf8y1S0sjDM7/8Y9/2FlnnWXz58+3r776yi666CLba6+9LNSohxvJhcH6N998Y++//77NnDkze7f30nJ87CcCCCCAAAIM0HkNIIAAAgggsJsFQi362LFj7YorrrBJkyZl96agoMDCn809wpRhTZo02WT6lltuyX5z/sEHH2QvcR85cuRG/UrjAD0cRPjWfOLEiVmrULcfHuFS/meffTbb3tT/wsC9efPmm0qxDAEEEEAAgVQJMEBP1elgZxBAAAEEyqvAUUcdlR14vvTSSxbmRA+Xr8+ePdsWLVpk4bL1hg0bZi9db9u2rYUbpp1wwgm2uTu25+Xl2YQJE+yee+7JDlw//PDD7HbKSj36/vvvny0DGDdunD355JP2+uuvZ3+ZsXDhwuyN5Bo0aJAdkLdq1cpOO+20bJ1/5cr8k6e8vrc4bgQQQKA0CVTI3JSmqDTtMPuKAAIIIIAAAggggAACCCCAQFkU4CZxZfGsckwIIIAAAggggAACCCCAAAKlToABeqk7ZewwAggggAACCCCAAAIIIIBAWRRggF4WzyrHhAACCCCAAAIIIIAAAgggUOoEGKCXulPGDiOAAAIIIIAAAggggAACCJRFAQboZfGsckwIIIAAAggggAACCCCAAAKlToABeqk7ZewwAggggAACCCCAAAIIIIBAWRRggF4WzyrHhAACCCCAAAIIIIAAAgggUOoEGKCXulPGDiOAAAIIIIAAAggggAACCJRFAQboZfGsckwIIIAAAggggAACCCCAAAKlToABeqk7ZewwAggggAACCCCAAAIIIIBAWRRggF4WzyrHhAACCCCAAAIIIIAAAgggUOoEGKCXulPGDiOAAAIIIIAAAggggAACCJRFAQboZfGsckwIIIAAAggggAACCCCAAAKlToABeqk7ZewwAggggAACCCCAAAIIIIBAWRSoXBYPimPatMDKlStt6tSp2WTDhg2tcmVO/6alWIoAAggggAACCCCAQNkWWLt2rc2bNy97kC1btrTq1auX7QMuJUfHCK2UnKiS2M0wOD/++ONLYlNsAwEEEEAAAQQQQAABBMqIwIQJE6x169Zl5GhK92FwiXvpPn/sPQIIIIAAAggggAACCCCAQBkR4Bv0MnIiv8thhMvaix/ht2T77LNPNpw0e6Wd/8Sc4pTZmqSZbR08M1nwebOkvalWFbew7npdUKNQ42X7aVwj2o+QWdQoydc8OWmH1rejNN73YYmv/vH/Stz9bQltiTuUw/M0/9voKp/ZmrLHvnQLFrv4Qxf7sIFbMNdd2VB7QtLB7af5nWmZdM22XqqqC/IGaFx0s8Z+35e9meT7LU/aoXVPtF8hXnlY+H/yWH1x0g6tKk9qvOYijZuu1nj+/0viZeck7dCqtuESrNzCej/PNbONJdG6YUGVv2h+bw3tQ+fU1e2L606IwC4RGORel5Xc6/K30fszu0PuffGXobqbaz/WeNLfNI6jE1+MI7OC0zXOd+//Vf/Q/Kr3NK5ysMY3uvU1S1QCAs8//rhsZb+Lk8/kllMkZfaKO3/P6g+mQ0dPkhU++lNTie1G7W/2fc0TIYBAqRKIxwmlasfL4M4yQC+DJ3VzhxTXnIfBeZMmTbJdC4pWmuVVTFbzA/QGS5Lcog2D+mSBa/kBej03QK+1Sleo6rZXs0jzFuVrVdBchSgXMg3qSL7OhsPLLWuyV66ZbSzeV2Orq/Ee0QDdj2HNHZbV0HVtrot9mPyuZENmbTXtEf+ywA8s3b/XzR9HPedUt75u2xNX0rRViV2XarJBPY1XONRV7rmruvxql/cORdGBV3MHHp2P7E64w7Kq0bqhgxvnWPS7nuz6X7t9yS7kfwjsZgH//t3op3T8/gz76l7HDWrpAaxxb4Tafv2oewP3IbjE9W3g3nQr3ZtyVfRzJGy2ivtci56K5s4RaBT9Ij48Q+P4afzPivru87mGxlXMDcB9f9P+8VPRRgCB0icQjxNK396XrT12P03L1sFxNAgggAACCCCAAAIIIIAAAgiUFoGNfjdfWnac/SxBgcLMtvpG23NXRNvSg3LJ63qNzrVD4+6uJ0lsx72k8SunaXxcU42vyXx7Hz8u1V/x1xn6Ti67pPcHuXa2sd9ijSsdLfEd7lvsy1tJ2k6rqfGHyzU+bFoU+296F0W50Jzl4vWn64IKt2r8bXJc2USltzU/P/7maZXmDtTQ3nJxZdd/6RXawX0pYtVO1Hy9aN+Gu/Oz8p/at4Y7B1U6a77yDI1r/knj0Wdo3DI6mKIfau71aL9C5vipms/7t8by1VEmNUvTG0VxxYS7UMCO2ag3CxDYKQJTf6Hv35a/+1Sf5wH3nqvsLudZ0kf7f62htYnWr+M+d+45XztfpZ+5y4/tLPma7w6R2Co3lbjg7Hslzu8sIcHOEKirV0HMPCcqFfryOX3Gb9w34O7l0NTWSv8TOj8l8SumP3NnSpYAAQQQQGB7BfgGfXvlWA8BBBBAAAEEEEAAAQQQQACBEhRggF6CmGwKAQQQQAABBBBAAAEEEEAAge0VYIC+vXKshwACCCCAAAIIIIAAAggggEAJClQoyjxKcHtsKsUChYWFlp+fn93DgoKC3F3cx41fae1Omp3subv7udzI9dSkW7Z1ULReWFDD1QHPOFtX2N9Vqc1ppvmoPDKbaBHVJC88QfvWe0Hjhddr3FTDgrYaz3I16Cvd3cwPjW5eP9HdIPyCZbotG3mnLvh2gMb7LNDYlXabP+74UL/QVV3Zn9kbLt/axbNcXMvFM//gFsQd/O/wqmrfyq6+3aVt+V3av6Y7Rz5v0XOvi28CkNlMxT/ptio484o3aX69e+793XPP0+52YBK3OzRph9bYhw7RBZdP15gIgZ0lcJarQb8veqGG5xx7jz7zymc0LuqhccWorriWu4fI6p7ad417D1Zrr/mK+p5a0VLTPqrh3kY+T7xzBSZOnChP0OrD2yW2T+7Q2M/oUkXT5l4eNsK9Nl13QgQQSLdAPDZI956W/b3z//ou+0fMESKAAAIIIIAAAggggAACCCCQQgEG6Ck8KewSAggggAACCCCAAAIIIIBA+RNggF7+zjlHjAACCCCAAAIIIIAAAgggkEIB5kFP4UnZ5btUO/OMcX12DbcHK6J4TtQOzfo6b7nd4Obk7er6X99MFwx0/fMnaP5P30vit6PaybD0trOTXGgd7IqKW/STfL6rp3vHPfV89274bV6y+jBfMz4jyWVbzVz98ySXb+hiX6s93dV+WrTv3/5ZV/70Bo39thdp2qbHc6pncvVXaYcmt2gcMy7+ieaqnaqxj5a5BUXxxjK55Y9oh2+7aFxpQRJXPj1ph9ZaV8Ca58xX/1r6512s9bGLn3xA8mbVNZ6SnJSx0y7SXANXc/7QsZr/5bsaEyFQUgJ/0Lreos91wxUsed2GzDsdX5QOrR/V2GpE92Y4Rbqaveg+z6vVlw7tLtL31NjJkrYVDTSe2TmagzubcvNwa3einSzQqlUreQZfk17tp/pae67m36R/t7bu8/9t7S+dCRBAAAEEtluAb9C3m44VEUAAAQQQQAABBBBAAAEEECg5AQboJWfJlhBAAAEEEEAAAQQQQAABBBDYbgEG6NtNx4oIIIAAAggggAACCCCAAAIIlJwA86CXnGXqt7TZedDHrbB27QqS/b/HFWPXm5LkfrZf0g6t4dM0Xu+Ks5f8XPOPab2k/WKx5n+fp/HVUdhgbhRkmt/spbHPVzhB82domOdW/2qW5mt8k8QV6yTtbMvtpsuaveSWuHJnqzBEO1TuLPHDFyRhp78n7WxLy0LNGru8q7W3j1x+tYt9GJ+ivV2y4EZdUOSKzmvdq/mGGtoCFy93czgvvibpUDdpZlvrXS3+/q4W3+3KzW6K5zuevEs3uFDraSXpn/vbapK22qs0di9zTRIhUHICRU3dtrpp/HUHjffR0F7eI1nwo05JO7Q++R+Nm87UuIr7PJhYoPNqa++NI18DvXEPluxOgaJX9dkrfOo+9yq6H5pXRv9u0FWJEECgFAowD3p6ThrfoKfnXLAnCCCAAAIIIIAAAggggAAC5ViAAXo5PvkcOgIIIIAAAggggAACCCCAQHoE3LXM6dkx9mQXCuRXMBsQvRSu+USfvO2RSTz0i6QdWvE0aNnM9zR/w7sajz5W46vdczV3+ZuiqdWGv6Prfnq2xvlu/qHDNV3krsac+CPNx5e0h8yceAaZL7WvfepiH9ZyC/JdvLKzLnCXwHeKLq/XjpnIXya+UewuSzzcXY7d1G3RX4YeX1LvL4/Pc51X/0k3tuo+jQvdgdW+TPO2XOO8PyTxyluSdmgVHa3xrCc1XnW/xHfcP1hiq3S+xvX8tGsro7y7xr3q36Jcpln5LI0/cdcZH6RpIgRKSmDSCPdB5jZcuZ5OpVXk3oIfRS/zFe7jd5Ur5Vnvtj1jiS74VsOtRvG0Xmm+3D3ez3BQad7XraJvS4eOrvN/P6ELfnmkxhb/kHQpQgQQQACB7RbgG/TtpmNFBBBAAAEEEEAAAQQQQAABBEpOgAF6yVmyJQQQQAABBBBAAAEEEEAAAQS2W4AB+nbTsSICCCCAAAIIIIAAAggggAACJScQFR6X3EbZUikTKMjMy9X962Snu7oC2kGTk9zbhybt0Hp4tsadXE3x+nGa9zXmFRZqvq2G9pNoTrA1zTXZcozG5ubZmqJpP+ta0c80v6afxhK52kyrJFmzZi6e6mJfqlfT5SPibCaucW/p+vrQT6s2wdWcu1Nm89wG3PoPX5zkO01K2tnWh+/ognoa2sqrdMHanhpHL7NsotZNmo/qY62Kpmy9mzfN5/d2/T/+ni5o7Ir1m16heXdokqx4uoQ3X6Q153c84G8yUCD9CRDYVQJrJ2qNun8Lx/vxwaI4Mjv8E61fX+x+FHx78Tm6QvsxLm6v8RYiX+e9ha6bTJVkXbjfF79tn/c75Pv7fGmJK8zXPW3XMZrvM5Ma635mam8iBBBAAIGSEuAb9JKSZDsIIIAAAggggAACCCCAAAII7IAAA/QdwGNVBBBAAAEEEEAAAQQQQAABBEpKgAF6SUmyHQQQQAABBBBAAAEEEEAAAQR2QIAa9B3AKzurhmLeqID3Lj2yipbMRe7nxW3W6QvpPHPovhJbpeM0viWqKQ+ZDj/U/P/N1HhltF9F7uX6UXvt+2Mt9J7RTNMHjdL4/Uc1bllJ47yqSfzyHkk7tGonJNnECZ9pPt8ddsE0zdvHLvbTy74RzQd/7Lva2ddK5/1V8wdeq/HrGtp5Lh6jcaeodj/f9S1Y9pR2dvXr9s0bmm94osZL6mtc9IDGNZYk8bLBSTu0anXReK07YXO+1HyNqRrXHarxe9Gc6yGz9tkkv6c7jsVNk1ymdcdbEprVLNAFw922O7g53bU3EQKbFdha/fNmV9yOxDpXc77neN3I55X66IJdGO3MOm+/bW/u87vwsHfrU42tsFufnidHAAEEyq0A36CX21PPgSOAAAIIIIAAAggggAACCKRJgAF6ms4G+4IAAggggAACCCCAAAIIIFBuBRigl9tTz4EjgAACCCCAAAIIIIAAAgikScAV9aZp19iXXSYQpnC+LXq2XrOiwGy9NU3i4VrXO/PrtkkutJZqaB/vpwvqamgPLdAFVb/QuPLrSby+X9IOrTYa2kqNz6+t8f1natz2aY0Xtte4qFISV3fzBS9zpdQ2I+kbWgW1NG7XQuOxfnLiTzVvcd35PM0tPkPjfo215vyOJ139c2VX/+yOZdwPdHt1o7rywyZrztw85nd10Pz1w13N+VK3L+e4fZmm8+xag2h771SLgkzz2y4S51+pr52CVyVtNiu8sKNHdE+B7NIity8HR32/6BkFmeYyV+e/TNMWvVaymYvctl13QgTSKOA+tsx/ptpGHbb/KEq6rntb6sa3pW84wm3tv/0qrIkAAggggIAZ36DzKkAAAQQQQAABBBBAAAEEEEAgBQIM0FNwEtgFBBBAAAEEEEAAAQQQQAABBBig8xpAAAEEEEAAAQQQQAABBBBAIAUC1KCn4CTs9l0INc5D471wxdwXNk2SHVxhtyvNtWvcBOGPuwm/K32VbCu0OsRFx5n44bgQOBPPbJ/5338eLaI50cOiWlp7XXBocccNfzeZoPEK91S2p+b/ey+Nz4kYmrhfZU2uq33Nx+s0P3b4k7qg6UUau+e2D6O0q/vM+yLKheZYV+e90NU/V3C13P/qIBs44ady8s3iOd2rS1ez4zS+3tXxm++/SPdltDvOk974s25wflRXnhfNBR96VdRC/4InHYy5wvCa+tw2TZ/KPvhUF8yOwsZ/j4JM84Rov0JmrqatSGvWO1o/6TBMIgIE0ilQwc17fsvxup+3T2klC95bM1Hi3RlsraY9riPfWt+t5XfncfLcCCCAAAJlX8ANO8r+AXOECCCAAAIIIIAAAggggAACCKRRgAF6Gs8K+4QAAggggAACCCCAAAIIIFDuBBigl7tTzgEjgAACCCCAAAIIIIAAAgikUaBCUeaRxh1jn0peoLCw0PLz87MbLigosCZNmmTb475eae2eiQtw3XPX8AW3Ub6aq62u1CJKZprrXNFxJVcnrL0z8+4+pEvW/D6JjzomaYeW21RRf02bK3e3Oi7vStrtSpePwqJGUZBpXu1qsX//jebrL9LYfN24OxTztdxHRuvPdDXmi11t9eFR39D82sU+XOIW+Nr8o6P8hKidaXZ005b/TNM21sX+sIe50m5bfrquUe3FJF79k6QdWsuf0jjez5BxJeVWUevCrYbWhdvXWtNuVc5Jtl/j7KQdWpXck7W+TPOva2jL3c5cc6DrQIjApgXiWulN9yi5pZVbaU35wnW67faDNf70Jo0XTdy2GvS4tntrxxn31WclQgABBBDYGQLx2GBnbJ9tfncBvkH/7lb0RAABBBBAAAEEEEAAAQQQQGCnCTBA32m0bBgBBBBAAAEEEEAAAQQQQACB7y7AAP27W9ETAQQQQAABBBBAAAEEEEAAgZ0mwDzoO422FG14dWZfC6L9bebqZRdG9bR1lkcdM83F12q896sar3cvMT8P+jfnaf/Wrqo5ngc9X7u+UV/jtX/UeKmrMa/o6sjzTtD+vs784qjO/Peubvsid+eG+vN0WxvNB+7WNzc9vLl9tY/i7U2Ng0w9tJsffKar+993qPafpaHVHqgLludp/GZUxL5Y69+HPb9K+g6LumYT+0rarjpTY3Pn0JZFNeeh69yoGL/Sv3Tl6HxkEx//WvP73atxoYa2/EZd8K37/WSDJ6K8MzR3gt95JOqbaVadrPEP3HtIs0QIbFbA115vrVZ7sxv6Dolq7j4e7fvrSv17aXzmTRpvLdqWY/F9t7Zt8ggggAACCJRVAfcv1LJ6mBwXAggggAACCCCAAAIIIIAAAukWYICe7vPD3iGAAAIIIIAAAggggAACCJQTAQbo5eREc5gIIIAAAggggAACCCCAAALpFmAe9HSfnxLdu83Og/7NHGs36p/Jc71yStIOrcOisPHzURCaVVy8XuNPz9B4X1ebu+4Qza+frnH7JJzq6psPrpnkQiuU0seP2g/Ekdn8KzTe432NK6/UuEK0/uQ/aa7ZIo33WKyxVXLxGhePc7EPq0f11VVdbbWfO/wsV8ftT0ktt/Gn7tIFza/XOD4WV6Nq+2hXm1hfF7RaoLGvtW+o6Y3mbD8+yo92267ktl3xxKhzpnnCGxp78w/+qnn/2q18VZJfe2fSDq3arvg2fk+EvHvt2NywMHr8MGrTRGAHBEqyJv24aToPeoXz3I651/Eq9/E+dZnOg+7ryP2++rx7NkIEEEAAgd0owDzouxHfPTXfoDsQQgQQQAABBBBAAAEEEEAAAQR2hwAD9N2hznMigAACCCCAAAIIIIAAAggg4ATcHFguS1g+BCrONKsZXd57izvsN6PrsVe6S9xXuMur60SXZofN7NlTN3a2hmu+nC4LHjtSQvv5lCSufE/Szrb21LjiqxrPz9e4rrvEvfI0zU92l3fu+fskX3tt0g6tPfyl226/zV0Cb1/q+lbhWF2w+l2N149M4nU/SdqhdexTGrtTYg01bfPcpd+rfqQd3nOXiteI+seXnIe1Xq6m69bto/GMPI2/da8H+z/Nr3tc47HLkvhH7rXlDWf/LOkbWrOi/Q5xtKkQ2rIHsn/l/lfxL7lmthFP4zZugOaWamj7uXicXo5ftHiBdKggEQEC313AXyb+3dfces8K7jOyX11dp+fftUPV/ALt0EDDnbmv+kxECCCAAAIIlF0BvkEvu+eWI0MAAQQQQAABBBBAAAEEEChFAgzQS9HJYlcRQAABBBBAAAEEEEAAAQTKrgAD9LJ7bjkyBBBAAAEEEEAAAQQQQACBUiTANGul6GTt6K5ubpq1r2ycjbB2uc1f/0WumW3cFdXbXv+65jaqtW6v+XauJHmQq+U+Qkt1re75ur51SeL5HZN2aO3ZVONJv+ghCxr17y/xXhKZVX3VLXDhmkbJgvYtknZoxaXSIc53U5m5w7Zpvmbd1XraO2Er0WNd1J6ndaDWVutAW7h9m/b3aN3Q9LXY7V1+kovjqZQWu5yvna//rnbw+5rXT/NtOmv8tYYW17TGBqFbvF8h/ir8L3rE64bF/z4xSmaa+7ga9aaatjFR7M9P9SgXmi7OO03zi6dpbEe4mBCB7RTY0Trvhq1a5Z55f39vheGH5HKh8fAv9R4hnR69VPITD/1/Em8tYJq1rQmRRwABBHafANOs7T57/8x8g+5FiBFAAAEEEEAAAQQQQAABBBDYDQIM0HcDOk+JAAIIIIAAAggggAACCCCAgBdggO5FiBFAAAEEEEAAAQQQQAABBBDYDQLUoO8G9N31lJurQV8/bpytapfUoNe4V/dw8XlJnHdf0g6thddqXMfNVb3kKM3X+4fG5mt9n3D5T5J47R+TdmhVbqOxuZLjlf+t+eoTNTZX/3z3jZpvvSaJH6qStEPrPldjfLOrA7/jIe1vTV1cycVuX+yUKD/KoTRz83+7Wu08N3f54kejbYVm1SG6oGZnjVdGoTtu+ybKhWbtgbpg/XKNK/fTeP2fNV7s5mRfUzPJu01Z/ltJLrSWDtC4di+N13+k8XK3L7Xdi1kOLrrxQthK60t0W+N+rfF5+qb50E18flgt7U5UtgR8XfiurLX2z7012eOGJTXoFVq7zxabq6vveb3G8/8g8ZIOt0g8faL/kJW0BLvSSJ6YAAEEEEBgkwLUoG+SZbcs5Bv03cLOkyKAAAIIIIAAAggggAACCCCgAgzQ1YMIAQQQQAABBBBAAAEEEEAAgd0iwAB9t7DzpAgggAACCCCAAAIIIIAAAgioQGUNiRDI1JX/VBXqtY9iV+e9Zs8ol2lWvkBjH330Y12yr5vLetE9mo+n4T7ib5pbP07jT47RuOYhGtf9XOPBrsy4x+uaf/uEJP7jl0k7tO7bW+M7XH6jmvMC7W/rj9UFZ7n5xJ+J0nV/FgWZ5hca2nKdm3jxe8O1Q93/1dhPXj/P7cvaWUn/FguSdmjV0dAWddMFUd1+SFzlXkv3PXCD9neHZiPvTPLVH03aobXUTehedbrmXZ34mU01/cLjGtviq3TB96LQvbbMzxVfVWvOff6wH0bbopl6AV/H7eujfd4fkO/v82mKKwyM9uZx91lRwd0s4XP32eDSdd6PtpVpTlypMRECCCCAAAIIbLsA36BvuxlrIIAAAggggAACCCCAAAIIIFDiAgzQS5yUDSKAAAIIIIAAAggggAACCCCw7QIM0LfdjDUQQAABBBBAAAEEEEAAAQQQKHEBatBLnLT0bbBiZg7vGq8l+73I1ZXH9dTvuRrxGslq2Vbdp3WBq2C2Q7Vc2iY1ry0r1LClEleJomnuuVtEc6SHbsOLos6ZZo+XNPbznl+Zp/kKB2tscQH8Ipf7yMWrXRzXM4fU/L9qh/Vu4vN3XA16lTeS/vmu8P+znkkutPZ183v7OtCCy7R/vQc0ruVOSs2oTny6r0G9Wtdd6Oq4NWv3PeRuBJB3hfYYGZ/hTGpdVKxfyz2XVdJ1Vz2v8TtnS/zCNPdcle+SvFW5XuO3ovDQqB2a7nTZemd4tHsutzph+gTiunJfQx7nNrXnvv+m+qRl2XHdWumuXBy9J2tdrLm1+nlsC9yHov9Ab6PzoLc8Qp9r6jbMi647QoQAAggggED5FeAb9PJ77jlyBBBAAAEEEEAAAQQQQACBFAkwQE/RyWBXEEAAAQQQQAABBBBAAAEEyq8AA/Tye+45cgQQQAABBBBAAAEEEEAAgRQJUIOeopOx23Yl1HJ3Sp599hFHJEGmNXvw4CTu0ydpZ1pLJk+WePFSrSFfK9lM8KRb8NsusqBq//4SH9Q3CnXTZgdFuUyz6zSNrVDjN0/WuMkKjcc10PipqDz6jnmaa+fm9x47RfP2sovbXqsLmmtor7q4xYnJgg9OT9qh1aSfxgdoaK+N0wX1XH27Zs0OiWrOQ+6dqEPVhlGQaX57q8a+Vvtzt69rX9T+65dovHKMxjV/lsS1XX17iySVbelLz6zhU9ph1q81znM15xbNuR56Nrwp6R/ffyAsXfGTJBdavpben2/tTVTKBEpTjflWaX/helQ9O1nwybFJO7TqamiN+uiCtb/R2H3mVj1B00QIIIAAAgggsO0CfIO+7WasgQACCCCAAAIIIIAAAggggECJCzBAL3FSNogAAggggAACCCCAAAIIIIDAtgswQN92M9ZAAAEEEEAAAQQQQAABBBBAoMQFKhRlHiW+VTaYSoHCwkLLz8/P7ltBQYE1adJkw37OzdQsP9cut8/T3ZTOS6O5bI+bo/Pc+jpvG5jbTLYxd5bGizS06i6e7+Jj49rsji55ncZL3H43aax5rW7X3Kai6z+NljaI2qHp51hf5/J5Ll7+qC5Y+YjGjVyt9tFR2qO990SUzDRXRHXbIVOtp+bN1Zm6rC13deU1OyQ91iWvi+zCKjOSXGitOEbjqk9rvMefNJ6noVVwNet7RA51XN/59+iCpddo7M/Rqrs0v9YVzK7urPm9ogLa9ZqyuYfIgn9fPF3iY2pISIDAThPY2hztFxynn9EFTz6g+7J6vySuGm5AEj0Wfz8KMs2iyhrv8Z7GqxppXO8kidecI6G9F/0s0czGUZm6D8DGh8cSBBBAIHUCMjZI3d6Vrx3iG/Tydb45WgQQQAABBBBAAAEEEEAAgZQKMEBP6YlhtxBAAAEEEEAAAQQQQAABBMqXAAP08nW+OVoEEEAAAQQQQAABBBBAAIGUCrgCs5TuJbu1UwVWZGqtv4jqtw92zzalVVLT6CoQbW1jLfRu9uWXsvZXEpnt5eK5Li5yNYpfRc+9jyul/CDa57CZir/VjS2crPHMgzQurKlxk+Ua28oonhC1Q3O1mxe72vdch2hO7ZA5+RLN+1rsvTVt/zgxWbDXG0k7tKq5mvOVro57cGft3+tAjedG2w6ZH2g9tX3UL+m/fGDSzrbcXQPWXan5ClH9esj454rnOQ/51deG/yeP45OmPZF5YcaPWofHUWYu8p4aL3he4+Zu3vPZroZ9WTQfdFhz6X3R+kuidqZZ8RmJj6nhzCRLsCsEfC321mqWt7X/rjiG7/Icfr9tsn6wHVdP34MFq91WF7oPynrR67xoT+1cYa3GeS9ovO4wjVdpzbnN18+W+QvdZ5d7S8cb29r5i/vSRgABBBBAoCwL8A16WT67HBsCCCCAAAIIIIAAAggggECpEWCAXmpOFTuKAAIIIIAAAggggAACCCBQlgW4xL0sn93veGw1DjU7JL46+Dld8agno9jNqmW/1Uva/bxpVX4YrZtpzl+s8SHuGvhPD0kupw8945m2JrkrNY9zM5fZRN22uas1m7t43rfav+GzGlvF6DL2C56SZH4tjQue1Es7bd470t9GjdO4tbv8+pljNd8oujT02xs1V+lIjatM0fjGtzSOZlXKJpb+XPNPDdF4v2h7fu66Qndc+/9N1/XTso3trPl2Lq7oLs9/45dJf39JewW9tNdWXpX0Da3KTTX+orXGld1caHvcoXn7JonXu0vcO0fnI+lFaxcK+Eu9/SXRW8vvwl3doafyx+E3dsxxekl7hRnRJeuh82f5ukr12hovjOpp/uh+Rz9gjPYtOkDjm12ZycDRml+oHzb7PD9T8hMzP2t4IIAAAggggMCWBdxP5y13JosAAggggAACCCCAAAIIIIAAAjtHgAH6znFlqwgggAACCCCAAAIIIIAAAghskwAD9G3iojMCCCCAAAIIIIAAAggggAACO0egQlHmsXM2nY6tzp071yZMmJD9884771j48803G2pNO3XqZEOGDNnijs6aNcsOOMDV4W1xDbP999/fwnr+0b59e3vttdf84k3GO+O0FBYWWn7+hvrEgoICa9KkSfa5V40bZ/PatcvtR1ShmF1WOZ6J56+5btnG6o4ar9RwoyjvAV30kasrX+amWTskmmat9hG6rrl9+dqVZi+qqv2bfaHxQa4e8jFXo37i+Kj/4qgdmm7b9vWl2uHEoRp7mDdcnagVaP+8Pyfx6huSdmhVfUTjuHY6m9lH86saabze3XqixoeabxbVdv/b5ap10b4F/6Nx879rbOs0XtxN4zx3Epc/keSrunrXyickudBq1lnjmc5l6WWaX6+hnaJxXtMkXlwhadNCYFcK+Br0VsfpfTk+c7dHOGDk07p7fqq0wmM1vywKe82Pgkyza/xhn4lradq/nW2ay3/s4l9ovLDTgbkF9dzHUi5BAwEEEEBgtwjEY4PdsgM8aU7A/Us9t7zMNBo12vX/CjjkkEPKjB8HggACCCCAAAIIIIAAAgggsGsEyvwAPWYM3x4fdthh9tJLL8WLt9hu3LixTZ06dYt9QnLgwIH22GOPZfuFb+a39Ah3H37ooYe21IUcAggggAACCCCAAAIIIIBAORMo8wP0Xr16WevWrbN/wrfp23rJepUqVeyII/y11foqWbdunY0ZMya7sE6dOnb++edrBxfVqlVrq9t0qxAigAACCCCAAAIIIIAAAgiUcYEyP0Dv27fvTj+Fr7zyis2ePTv7PBdeeKHVrFlzpz9nST5BtcPMmry4hS1eEuXuj9qZZpWJGq/UcsmNShbNrX+oOz2fRTXnYctfR5tf+34UZJrzk7L5bKLpcs03ceWVy+trvsDVS554sOaltPsHLvdiT12wcojG/9LQ6rla67yKrkNVjatdEcUDo3amOe97Go/Q0Bq4+Jy5uuDDvTRu6QrkL/80l28zZWyuHRrju7ia88HxGQo9jgv/Sx4P/iZpZ1onX/mwxKOGu8noKzXM5Vv+/MRcOzSmTnQFraslbbZ0gC7w52yMuxLmgJbS399mQJIECOwigeOGuQ/RKfrEB9yXvD+zGfc5ZgvcB19zXd9mTM4t6C+fsGY9Bh2Ry21ouJr0s6prXt9CdvmIMZJ/cK8hEtd7+dJc3KJoaK4dGtO474N4ECCAAAIIlF8BP0oovxI7cOSPPJLcnGprl7fvwNOwKgIIIIAAAggggAACCCCAQBkWYIC+gyd3yZIl9swzz2S3Eu7e/oMf+K/tdvAJWB0BBBBAAAEEEEAAAQQQQKBcCDBA38HTPGLECFu+fMO11ZdddplVqLD16/Q++uijbE18qFevXr16drqzH//4xxa+iV+zZs0O7hGrI4AAAggggAACCCCAAAIIlEaBMl+DvrNPSnx5exigf5fHnDlzLPwpfnz55ZcW/vzzn/+0QYMGWRj0h7vNb+sjzHO+pcdXX321pXSSW5Q0Q+vtDeX12YVt79bcdFcu6SeYm67dbfY4XdCitsYLNLT8KPa57w+PkqHpXs1FyZS72Y77u/Lo0a688m9uc8PiUu8qLnlhP13wkCtwd6Watse12n9eUouZTTTTekwr/EPSf1HPpB1aDQ7VuNPeGnfO0/gnQzR+9BaNezbVOIIeb4drLqnm2LD8ibmav/1IietcrjcZGHVpa8mbP4cXJmc83x6TvlNf/FRi+607we38q027m7mCWZ8mRiAFAhVa36d7scoVkZ+raavp4ur6wVbxmonSYX3b5EO7h9tWx+6vS98PrEDimiOLJD51pL7/XzZ3f4ua7gmiu5JMWyebIkAAAQQQQACB/wi4IQ0u2yLwxRdf2GuvvZZdpV27dnbQQQdtcfWKFSvaKaecYmeddZYdddRR1qBBAwuXyL/77rt277332ocffmgffPCBnXTSSTZhwgTbb7/9trg9nwzTyPFAAAEEEEAAAQQQQAABBBAonQIM0HfgvP3f//2fFRVt+Ebhu3x7/tRTT1ndunU3esYTTzzRfvOb39ivfvUre/jhh7Pfrnfp0sVCfx4IIIAAAggggAACCCCAAALlQ4AB+g6c56FDN1yWXK1aNevYseNWt7SpwXnxSmG+9fvvv9/Gjx9voUb96aefzl723rhx4+IuW/27oEAvR/QrhEvcjz/+eL+YGAEEEEAAAQQQQAABBBBAIAUCDNC38ySES9DDQDo8zjvvvE1+M76tm65cubJdccUVdvPNN2dXDZfP//znP//Om2nSpMl37ht3nJT5Uv+C05Iln2w4rNyCtk/nmrb8J0k7tA79vsb2vsaHPqex+SqA9po/7miNbXIS1385aYfWoh9p/L4rA/+5e3UPd/ff6+Dqygte0u3JPOgrXXX9Ka7e+cCocDts5svRurH/cuUKNx+u+UJX3L0kqpeu4+Yar6hzh/fvHN0kILPVHuZgerua87P0qe3Xur6dFL2OCtdq5zvdcf7sAsn3sj9JfJvdKLFt+J2WLoujEUkwMmluaHV/Upd015AIgTIh8Mopehh+avLGWvdtnd0HX3394FvfO6k5z264b2Fu+33ejj5gM0v7uA/oZrYo1zc0pg44QeJTuz8j8XjTXwAP6PCq5LvXPz2JV72TtLMtrhhzIIQIIIAAAuVUgLu4b+eJ356bw32Xpzr88GTgFm4cxwMBBBBAAAEEEEAAAQQQQKB8CDBA347zHKZCGzZsWHbNvfbay84444zt2MqmVymuad90lqUIIIAAAggggAACCCCAAAJlVYAB+nac2eeff97mz5+fXTNcgh4uTS+pR7iLe/Fj3333LW7yNwIIIIAAAggggAACCCCAQBkXKLmRZRmHig8vvry9U6dOcWqH2mvXrrUHH3wwt40f/OAHufbObByz0mx6dDV91eR3BNmnfTsqM/bzoNvRumfzr9C4qoaW93ddsPhsjWdoaJWi+OgNpfm5JXX75JrZRrurNH7M1W7unTnO+FHwTRxl2p779Sjf2NWcuym5zZVm28qfRitnmve4Dp//W/Mrlmpc6fok/mhI0g6tFlos32N4Lc130LpRW7Gn5h1yI9Ma9DmnRTXorpTeKriact2y3dblx7pksPavbw0lf32mYj5+9LH/F4dbbg8Zp/nOWh+rSSIEUirwvu7XbUe8Igtmmf6YXmb6e/WRVkP6LzmqtcRX9f2bxPfVuDoX9/lT9F7PLO1/zb9yudAYbkMk7tddf949ZHtLvo7p59pqWy35gQtezsXdLu2aa29oUIPuQAgRQAABBMqpgP6kL6cI23LYCxYssPANeni0bNnSjj7ajVA3s7HRo0fbokVu4BT1DZfNX3nllbkbz9+1XXQAAEAASURBVJ177rnGvOYREE0EEEAAAQQQQAABBBBAoIwL6K/my+DBvvnmm/bJJ5/kjqz40vSwICwfMmRILhcanTt3ltgHTzzxhK1eveFbgW359jzMbx7u9h7+tG/f3g455BDLy8uzpUuX2qRJk+zee++1Dz/8MPt0oa79L3/5i39qYgQQQAABBBBAAAEEEEAAgTIsUOYH6GFu8TA43tTjrbfesvAnfmxtgF58eXulSpXskksuiVfdajsMxh977LHsn811Dt/Kh18CHHDAAZvrwnIEEEAAAQQQQAABBBBAAIEyKFDmB+glec5mzJhh48ePz27y1FNPtb331vq7LT1X165ds5fDjxs3zsKN4ObNm2fhcvlq1apZo0aNrFWrVnbhhRfaBRdcYGHwvysf49eYtYum1s37iT57fhS+40qMpzeOkpnm0S9q7KbRtbmuNHuve7V/tUs1PnRGFLvpwJcfHOUyzQ/cPfWGulf3W3W0v8xznkndXF3zd8QVCW4ac/vqBe2855kaV3c15wv+qvm/52k8xcXNhyT585JmtlVwmiy47iYtFL/bVkq+R+EzEvfve7LEc0YfKfHvuiU3CqhhNSX3SGct3P/UNsxmUNxp/WBXUFuc+M/fC+xtWdJHS2DN+kY3Alh7jPS1ta7wv2iB5oc/qnGHbfsFmq5MhMBOFOiavJZ7HKHvz7+afhY0tbWyI36u8X72suR7jk6uGAuJ++5Kas6zHa8/MOl/jd5bY4WtSHKZ1md2k8RzTe+VMfPItpJvM2WsxH3NfS7G9fR3SVezdxKTbGZotJ+uKyECCCCAAAJlWcANYcreoYZL2P1l7Nt7lM2bN7ftnQbtsMMOs/CnS5cu2/v0rIcAAggggAACCCCAAAIIIFCGBbhJXBk+uRwaAggggAACCCCAAAIIIIBA6RFggF56zhV7igACCCCAAAIIIIAAAgggUIYFKmQu2S4qw8fHoUUChYWFuanbCgoKrEmTDQXAS9ePs4/Wtsv1bD0z18w2Hj40iS+elrRDq3sLjbtpibK91kDz5/t73z2g+THtNW7/XBTXjdqhGecyYWEPzU/UUk4347aZLyt/we2LNY2291n9KMg093H1z76+/Ujtbhtm5ksWVv1D0g6tb1xxfsX1SX6t+z1aw3eSXGh1aC3xyfamxKMGfl9i6zZf4oFu7uJul56a5IdqPav94aAkF1r/q6HdovMe2ydVtcOgyRo/NEDjBU8mcf6rSTu0xp6i8WBqVBWEKK0CA+1vsmsf2JRcfKgdkWuHRndrJHEbWy7x+ObJZ3VInDxD3+8/tG+lf287SuL+ltwn4kHTD1U/x/p/uRt19LzL1ZRfr58l5mrUrUZTeW5bkbz/m7l7Zcx0+2Jtox88YStv835XTCIEEECgZAXisUHJbpmtbauA+5f/tq5OfwQQQAABBBBAAAEEEEAAAQQQKAkBBuglocg2EEAAAQQQQAABBBBAAAEEENhBgTJ/F/cd9CkXq1fLXE3ddFlyqPnuysJO/1stl+z0k1W5dmhcJZFZ/Qm6YLG/1NtNST/GXX190le6/oLvJfE57nL5v7ttf1096RtaOuGP2TS3b9NmaX+rerou+HqvJD5naNIOrbc0tOXukvWPb9EO7upse8MdjPY2m5P87qxrr1GS/R/T6+l/666f/73dKv1rdJPQ2lp7WfCBXMtv1mZorVx+vEUGYakrYbAZOu2SPV07t2628eutXJb6S+1utpX+vjsxAqkUGO/26t8SD7X/kTgOrrP749DuvuokiQfc96LE3e03Eo86Sacru260TsM4yJLPntamn+enWPSDILPV7hfqJe2NrtcP0ePd+q1ssezLiBX6gT512C9y+ZkdvVGbXC40bn17kMTj7SyJR9tIiQkQQAABBBAoKwLJKKCsHBHHgQACCCCAAAIIIIAAAggggEApFGCAXgpPGruMAAIIIIAAAggggAACCCBQ9gQYoJe9c8oRIYAAAggggAACCCCAAAIIlEIBatBL4Ukr6V1elfk1zayk7NgKtAzRLK471/JG2yMpZ9ywWy4e0lj39sqVGl/mfkX0tOv/edR/7Me67kduxq+jFmr+Dl8vPU/z5p7LVmttpy2J+r9wSBRkmqdN13iSqzn//E7Nv/c7jav8VeO6rta7++G5/CBrlmtnG/8XTcGWWdB7YmvJ9xq8VuKFlifxv+xPEo9ucrfEFQsnJvG97rm7JKls63F3U4HDddsL99b+9TQkSpvApe4NPlTvCVDHnpA9XmI/k7jcBsMfkEPv0UGnPutuTSTfK3oPfmafSO7uu7Tm/OTr/bb8DS3+Luv3G/2CxD2tucRmyQfnKJcaMyN674e1DtZVj7OndIGdLXElqyTx1D+fIHH/jsnn3gp7Q3JfmRpOc9v6oek9Qnzcx/6fbK/cBsP1PWrPRj8fhurPhh5urtL+w90HdodLyi0jB44AAgjsTgE3PNqdu8JzI4AAAggggAACCCCAAAIIIFB+BRigl99zz5EjgAACCCCAAAIIIIAAAgikSIABeopOBruCAAIIIIAAAggggAACCCBQfgUqFGUe5ffwy9eRFxYWWn5+fvagCwoKrEmTDXWR4xaOs3Zj2yUYbh50W5SkzM017qet1tl+zY6ZG62baT69n8Y9NLRprn+7qDT7CNe3b7xfmdw+dV2Hh1zs6inv+p7mr39cY4vq8l05pG3ksMDV/dV3tbkL7tONT3N1pK9resDopB6+ux2nyTv31PgmrWE1V6vZ1+6S/r3NPbec4EzXe2OYGbKu1bpN48pNNf5ZP42JUicw0P4m+9St56m5+Hf9tJ55vemPh2pWLdc3NL41vfHDYOsr+Y3m9O6p9dV28BdJ/0tdLsmkrnWWXST7VNNqSjzCrpLYLH5PmV1onXL5Ec175drZxozJGpu+37ua3ozjU9Ma9emWnE+3oWw41Y7JLb7Nrdur649yuWzjUQ3l/hSZ1Nm2QjrUdK+Xz22I5A+3yySOg5dMP1uutW5x2mZbZYn3yLz64kd/OzoOM23/OefSpTacpnt+lf5QbnnfOMl3jJwG2M2S8/cBMP+zRnoTIIBAWReIxwZl/VjTfnwV076D7B8CCCCAAAIIIIAAAggggAAC5UGAAXp5OMscIwIIIIAAAggggAACCCCAQOoFGKCn/hSxgwgggAACCCCAAAIIIIAAAuVBgBr08nCW/3OMm61BX5SpQZ8Q1aB/daKqHPVGEn+WNEPrrgs0vt7Vhd/l6sLv1e42zc1V/rCbR73T19EKcTuz+GlXcniBTqNrdka0bmhWcbGW7pm50j77IOp/btQOzVd/rQsqH6/xquc1rqY1qLb6SMm3+YUe3Kyo3nJODbftFYpcx7RO/FZbINvu3uR0ia1Q58I1m6/53tFcuC1e0tys0zT+8YEaH6IhUQoEhmhNap/OE2SnZlthLr7P7si1Q+NWGyTxcDef90y7RPK9bbDEM129dANrKPl7o+db8YQreH5b3yM22L3WZEu7OnjNPaF7D0Xv39Cxq+nNNQZZ9Hl7j34Q9bnmOdl2n5POkdhGz5K4o30h8bAaP5DYVuhni1ntKK+fBW3kQ89svLlzUD9e16zigonRtszW39ZK4ut6jZZ4L1uZiz+zGrl2aDzYtb3EzQfph+5i6yn5Oa7u35y59TxU+lu/NL1+dNc0ek9DZ375gjGSf9C+L3FfS+5fEhJ9rVEuv17OfVis59NqNMn1zTZWlBYz3W0iBBDYPgFq0LfPbWesxTfoO0OVbSKAAAIIIIAAAggggAACCCCwjQIM0LcRjO4IIIAAAggggAACCCCAAAII7AwBBug7Q5VtIoAAAggggAACCCCAAAIIILCNAtSgbyNYae6+2Rr0xZka9MlRTeQ6d5T7uDgOv4qDTNuXO65x+UqX6oLvDZX4DVcC99/R1LfDnpauZm5O9Y2mwR3i+ue7uLGLK7k4Lhv9TOt4be0J2tnVw9u0NzT/yb4atxwjcZ8OSyVeEdVXfuCK55dZBek7qrnWINoMfxIixLBmfZ1X2frI5sz2/ley4NMzknZodaMmUUHSF/Wz/5admuDqTOua1qAX2qxc/6Osda4dGnEuxCPaujm739bXw8n2cOiWe5xiy3Lt0Ohuv5G4oz2Ui490c2p3tza53IbGcRo3/1Rj99FivXTftPNWokdf0A6XrJb4VvtI4lpWS+J1tk7iKu49HDv0t79K3x4b3TxjvuQb2UyJ59jFEltXdbl00J2SHyrzgzeVXEX7ROKbbbHEg8x9jkk2BPpZc67pD4ijLLnpSP8m58vafQqfk/hRu1fiGa4+/lL3Whp65E3S36ZMlrhZVP/u750gHXd2MPwefYYOatrGmTewf0r/NnaixL3teom9y2h7PpdvbP1z7dAYbwdLbH92PxvqLNf8lS01JkIAgTIlQA16ek4n36Cn51ywJwgggAACCCCAAAIIIIAAAuVYgAF6OT75HDoCCCCAAAIIIIAAAggggEB6BBigp+dcsCcIIIAAAggggAACCCCAAALlWEALxsoxRLk+9PWZo0+mpzXztdlxLXbcL6C5aXLN1av3O1Rle04Yqgu0VNNOXKrp1V8m8bBvj02C0Pr6XY2f0lpLq/yM5r+YprGbL9xauHR+FBe4mnMX2htR39Cs5Qrmm12sHbq3l7iPvS+xWVILeK6b53yMVde+M7RGdaBNlXy3gadKbI9raHUW6IJl0bzr+Vrvqh2J0ijQs+uZslu9Bz0rcV/7fxKfZDfk4kbuDfyAHZbLZRtv62vtLLtI8iNr6P0Q2q94RfI1onsrhETz6D3YfYDWJHftPkrWvcOGSbx+hqsx76W1112st/T/p6u3nXlX2yR//dqkHVpf6o/Gk+1NyU+wvSVuZ+oyw+pLfph7brPpufx0+0uuvaGh932oGN0jIOTnWFXp38x0/viZgxZJfuhVrjb7vsIor317Z7YePz5xtfYWz98eOg50n0XdZsWr27NWz8VJ/XTLwnGS+7s1kHjG7/R12/t2jd+1utK/5RTd3tE2VvKP2g+jeFLUDk093z1MX7f97z9N+ne9MqnrDompptsbedbvpX98f5TLO4yR3POmdd7nuhr0Hna19N/bvR4G2t8k74Oh9tNo0eVR26yr9ZC42g1LJL7tyB9LTIAAAgggsGsE+AZ91zjzLAgggAACCCCAAAIIIIAAAghsUYAB+hZ5SCKAAAIIIIAAAggggAACCCCwawQYoO8aZ54FAQQQQAABBBBAAAEEEEAAgS0KaOHVFruSLLMCNTNHFteSa2mf1qR/7BS01NKiaW6zHXtqWaj1i8qbQ4eefntVdPuf75/EeS205nzx60ku21rsNrbKFYbXcf0L4iLzTO7zuNg+E9e9N1qhc9TONMe6evi8KzS/+AcaF7m32gxXbG9a6xfPD73ERsq22ts5ErfwNedtXc25TtFsdtNsWf+2Th9I3Gt4VJPeoZvkCFIocKG+ya4bNFp28gH7s8T1bYDEDeysXNytub52Os7QN9kw05rlka6GdcCKF3PbCo2Kmf/ixwp3A4S/RHOfd+3+ZNw1M7O41i/XsiLJ/9bukri3qwOv6eYmb2jrpf+869/JxeebHuehtxyRy4XGs67+/Uyp6w3zSb8t/UeaHssA+x/J/9OSD6PJrq77OtPzN8vVRzd0c6w/aE1l23XcPStuuk/ryitZpVz/nn5O7d+dncuFRpvb9RyYuVr9z6R75mxrLX5fmycdKkfzoq+xCpJbYPq5dN7tX0v+KVf37x3OM+0/wK6V9W+153LxeHs41w6N0fXvlnj2AvdDcHn4IZk8htj+SZBprbE7Je4+8mmJvxg5Mxc/6F4Lvoa8mx2U67uhcYrE+7vXfTc7RPKZH1wSH2n/lYun2Oe5dmgsNP2Z+Q9zP9fOlO5mU1xMiAACCCCwUwT0X0875SnYKAIIIIAAAggggAACCCCAAAIIbE2AAfrWhMgjgAACCCCAAAIIIIAAAgggsAsEGKDvAmSeAgEEEEAAAQQQQAABBBBAAIGtCVQoyjy21ol82RAoLCy0/PwNddcFBQXWpEmT7IGNKxpn7da3Sw5y+K+TdqY1umNSi32SL52OypWzK2lJm86vHjocmO2V/M/3PzhJhVa/Fknc86WknW0lpZQbEq6k/OXm2v/U9zSOyiGziZfP0PypIx5JFhRdlrRDq8JAje0AFy/WeIjWEfYb+YLmXdTTjsktudTNczzU1av7mkMbPj63brbRSetKNZmJbnBLakVxd3/CohzNdAjU1xr0Xgv+Ifu10PIkvttOkriOvZOLa7o676au5vgDq5LrGxpLLmwtsY1wNcrN9d4LPWY8I/3XZKp3ix+DXD202feKU9m//Rzq3Vxt/WrTD6f/tX1l/cNtqMSnWPK+6GGtJOc/uC63TyTfzFZK3MM2fJYmC2snzWyrqcTNopr1mab17napW9d9jpn76Dl5xZuy7VEnfV/iW0ePkLi2JdufY9Uk5+u6q7jXwwx3/vdz5n2anCPbs0I9J3Zk8txtpoyVvuN7tpO4Ub8JEtdy9xCY6Wqt7axDpX/FkRMlPsL+mIsvtity7dBYnfkvfvS26+Mw09Z7K1zl5kn/xJ3DU6N7K4QNzY7uIzDc3RthsduXHtF+hnW7W4vwV+5xa/TaCQurunOy1r1nn4vuhzDlwidy2wmN20a8InEv05/9Zm9J3r8nXZIQAQRKuUA8Nijlh1Lqd59v0Ev9KeQAEEAAAQQQQAABBBBAAAEEyoIAA/SycBY5BgQQQAABBBBAAAEEEEAAgVIvwCXupf4UfvcD2Owl7t/MtXajnks2VFsv/7N4xrDJSbdsy13Jbf6Sd9fdmrkF7pL2ja6oOy3p/4ZeLWsn6hWSG03xttHl9N8k28q2Grv4bRcfF8WTonZo6hWuZvUe1Q6fttVYZzqyywePkby/lLhXkx8l+Z46PZR96H6vNtjtzP16SaR9q5dAW7470MVHJs8VWle21JgoZQL6Ymzkpkr6lZuuqoq7BDa+rDwcWP+Tzk+Ob7QvaXg+yWVaXd2UfnXdZcZzXN3IYOsr6/dw01ENiaaMWmO/l75z7GKJfXCrDZJF06yRxIe7abc+tQ8lPyqavvC6zIXE8eMj2yMObdil8Yeg2aVD75T8x3aCxONl3srMdGVufqrx9aPLuW+SVTPXNOv7eaC9IR26mb4/K1qh5M+wERKPtC4SW3SJu7l1/fkdNLSNrNvs0tkSz/SX9tdwl/rfIt2tf99/5Rb0aH5Grp1tfKNhxwWvy4LPbYjEp7lSn+luWj4/Pd15tiS3/jzTD+RqViOXC408VxbipwvsZldLf38JvNmekq8YlUisb6LlFB0L9TiHddHXWv/BiVnY6HDncKZdJc/lgzFWPbdovF2aa4fGkaYlKh3tl5J/JZqaLiRGR+8Z6UiAAAJlQoBL3NNzGt2/9NOzY+wJAggggAACCCCAAAIIIIAAAuVJgAF6eTrbHCsCCCCAAAIIIIAAAggggEBqBRigp/bUsGMIIIAAAggggAACCCCAAALlSYAa9HJ0tjdfg/5VpgZ9WCLRzs27FdcGTv9r0i+0VlyrcRU3TcvxyRRt2Y6VtLstcrHOdmMyw4yWw7oVM2FSapfNPX2edrngiRt1weI/aVzJzdNWu3OSr+hqcxdGudCr7pNJ30yrTUetIx1vx0u+omkx/3q3833t81z/3vXPzrVD4/IFYyR+sGd7ia2l5m3hFZpf4GrSH9e0TXHH6tKEu1ighp6v21bo1EjL3ZuoyOrLDn5qOg1XgUX3N8j0HH9bVA/d6yNZd6Ogy6Gy6LbBui9Ftkry862mxLUs/jDRKaKquffAq246qu+7dW9r8mPZdp3CdyTe226T+GvrJXEreyQXf+Bqc8+25blcaDxobSW+3E111cS+lXylaFqtkPAOcy35IIxrhEPfOXZs+Cv36Gh6s40DbG4uFxoTbG+J/f0sHrywveQvHzEmFx/gpgPr6WqSu7ra+TtcbXYf99qrZOty2w6N7keeLrFsTmf7s0ajdVq1H9u7su4/nMs80+8X1rup8hplZOJH3N8bzXTrmr0fr2q/M30P3m37SX7JWVrL3X3k05KPp7ZbFJ370GmQRe+/THyp6c/YoXaKbOsq99q7zzpLvof9S+I10Tnzz3VuNMViWOlZty27TY/beh0o2yZAAIGyJUANenrOp/6ES89+sScIIIAAAggggAACCCCAAAIIlCsBBujl6nRzsAgggAACCCCAAAIIIIAAAmkVYICe1jPDfiGAAAIIIIAAAggggAACCJQrAWrQy9Hp3mwN+uJx1m5yVAf3udYNXnXpizml7+VaGxqdvnYLXnfxGhdriaJZQ5fX6YTN4rpzLbU0V95qrrRv4/hj91yV/6ALlp+ocaU7knjdzUk7tGq+ofGkn2qspbjWe/Czkl/pJlIf5OY2zhS15/o3s1m5dmjMvErrYd20x2YLdF5knfc4bOG48D8eqRV4y+2Zvuva2g8lf6a5155kzXrb/rKkonvttbDkTTrNzZl+tqtRfraGvkd8Pbyfe/rB6HUcdqKNq+2uZetl3+JglMzXbZkK8uS+DKHf07ZX3N2mNtEPj+sKR0v+bvdh0zWq5R7kaoqbm96HIz8zA3z88HXj65vr3NY2Q+8xcbItjVfPvKMr5+IfuftR3Gfn53Kh0c/+LXHPrmdK3HdQ/CFpmS0n2w4dP7Vq0j8+JxvVM590tfQ9efSbEo+69PsSu9sCmI10Ncquhrl3r+RzsMid+9syr474UccK4tDau9dtTSuS/DDT+cP7uDm874leL3Pa6j1BGr2t9er+uYZFddzZJx14tDz3ud3050HL6LUVOt5ut+T6X24P5Nqh8eCR7SUeOOVliT9z9e8NrZHka7ofhB+5+vl97Zhc/6n2Uq4dGsebns8v3HvuwebtpX+XGY9IPNj6SkyAAAKlW4Aa9PScP75BT8+5YE8QQAABBBBAAAEEEEAAAQTKsQAD9HJ88jl0BBBAAAEEEEAAAQQQQACB9AgwQE/PuWBPEEAAAQQQQAABBBBAAAEEyrGAFquVY4hyfeihlC8pQ83UVyc158HloqjU76UKTmq1j7Xu09a4yW6r/ERXOO0pjf+poa3MTxbsrTWJbtpka+fKH8dOSlbNtjYqvU7qArP5sTr/sFW7JNnAl1rvajUbJ7nQGvSJxG1cDWLf3udKvn9fnat2gKuv7T4gmW+6aXfd9swpsimzAS6+prYuODKpZ88m/Pram2g3C/R2cxP7Ks/2dpbs4R+j2tqQ8HMy9x6Z1P2GfF+L3lOZ+PCoLtzXoD9vNcIqyaNH0gytv3bPkwVzHjpIYvvlconH254Sd7cXcvGAIy/ItbONKToXdWU3L3pDN+e2ddfVG12jN4IYYF9KB63NXim5GfZnjeu741owS/I2Y77E/U1vztGj+RmSbzbj7VzcxHTbbWxmLhcaPe89XeLf/frvEvc298H3O1cffbvWR9uRSf6+O9z9C06/ULY96iStUbbkY2lDv8XS3TqOfEgWDBssYeaMrcst6O9q7VvauFwuNKZ20XsKPD94ouTXu/nf3VT21ue9c6S/3Tg3iTsnzdCaM/B4WTCsuoTW9wat8+/dTfNHuWL8/m7ucrPXcis8eGmTXDvbcD8yuw04VfLXddd/pjlyG/BX/Rnb8Vp9zw6yg6PtnRy1zY50NzDZ19ZK3mboa+sr0/OrnYkQQAABBEpKgG/QS0qS7SCAAAIIIIAAAggggAACCCCwAwIM0HcAj1URQAABBBBAAAEEEEAAAQQQKCkBBuglJcl2EEAAAQQQQAABBBBAAAEEENgBAS1u2oENsWopFgh15HF5ZgM9lssrJHHBrKS9yVZlrXe1yjdqtyp/kji/koRW4J7borlwv3Jl30vdq7e5lgmaLdc6UnO1urYsrs3L7MdarfW0yecnO9cwaWZbQ3Qu8kam8+jOM/3d13V9tdCwh6+ftCP0CZondaajfqd1ohVvd7WYP26l67r6V+sxWfMdNCRKg0Byw4S+br7n3qaFvO+6ucVvsNlyALfpS9O+HblQ8hVtH4nj12otN7f0kttaS1/r/rXEG81j/suqkq/j5nBe0lzrbx+fkeyLn/95pXPoZSfKts+1qRLbNVpH7t9jfi7yUZa8b/rbGN2Wi5Ys+EKW/I/VkXiJuyHGalsl+Yoz9D37K1uSyy8y/RDcyHSSfpbcfpJ+HtitWidsp7+Y23ZoPFtf3bpOeTKXHzTx01w7NNrYWIn3Gv2hxM9+X7cV3UIg2+8DqyL9bYG+XvpfGH2mak+bNcJ9oL+tHdYfmZyvkLl1ygjp8PsRWj9/8oo3JT+rc7L9FjZdcs92S+YKzyauqi35jYILj5ZFa0YskLiNfSDxOfZtLu45VF+n10U/40KnvO6Lcn1DY8BJ7t4MoydL3npqOMuS4wyZy+2jXId8d3+Lv9l+uVxo5Fk/ia2Lvj4OHfys5okQQAABBHaKgP7k3ylPwUYRQAABBBBAAAEEEEAAAQQQQGBrAgzQtyZEHgEEEEAAAQQQQAABBBBAAIFdIMAAfRcg8xQIIIAAAggggAACCCCAAAIIbE1Ai5W21pt82RRokDmsqC75ZjcH7B1JCZu5UsuN42VaY277OrKld8qCgid9YXlvydsJSa3gPiPqa656e40rPKXxRTdo/HA1jQ/XOlGbPVDzcWnoW5qymhrP8QtcjfneltQYZ9d0NYw2Qms1+3VInqDn7/S5NqoT3lMnoz/X5skKz3a4QmKCFAhcqrWd1w1N7lHga0gruvsZPNtF64Cf/dgdTy+tcR3c/DLt8DMNR/0xittG7dBMdus/Ca2PvSiaQz10qGNa99vDT5z9zX8285+/lkXHtsrVbfe98FztPKJQYj9Hex97RfJ97EcSj7L/z965wPdc73/8bS4Z5pZbGi2sSFsKYd1s3V26HY1OiVSrToejOshtw0J0Koe/Oq0SqRPS1aUTMkVM6Ghzq6HFwtDCMNft//18nX6fz+s916Jme/160Pv1fb8/n+/3+/xefr7b9/X5ZIDuJtbkPGDoLZCr2R/HlMiqivNkC1rpJTQ1BtqfI31AD1bX5G7HXz9ioPIYKxuw3DAF+pKkSND9kkeCHtavAej2ah70EVPCbD4W/cyL5QqbO1qUiPUhchCqqsm/QUvVMaidKboHTZwOuWVSCXSB8zobz71n26DnPGTmEmg/t8PVoF2xXp1Lg515yk3dP5JquOWSIGp8EnXNlRQc50HUOA8DpY7trzMenzET1RduHzy5Ekd8Ytt6EfTl6UHZyPGgOiZlxI4L8ZLUhL6ypB7oR+Qh0ENG1Qf9vrwFWl5LQ/1QBGoqEiABEiCBX0WAv0H/VdjYiARIgARIgARIgARIgARIgARIgAROLwE+oJ9enuyNBEiABEiABEiABEiABEiABEiABH4VAT6g/ypsbEQCJEACJEACJEACJEACJEACJEACp5dAiXzvc3q7ZG+FlUBmZqbUqXPEC7dx40YJDT3idVt0aJFE7Y6ym13Zhn7k2DETlRVz4AdYW1HZKXdtwLyyYkpUU8wvdP3umBJZ1hmXNJ2IWufbq/yEdVhfaxbqhTehHuV4ecPRJ9gtfR7UjgtvDVraopRRGbjgNfQ4dnvIgexVjmvZOlBfL8V6Zc3CrrI7kDNB/GTlze94N+QpCiGBYHUuTrD+2ZhYHBuhpWTBDgwL/hPoQbnoQV2n5ng+V6pD/agOypPunD4tknAe7MXiJL1e4lXfQzrfDn27XnqTKKfmVR/ROQbq5RtHpm5xhBcG11IapfaBS+ohKBgsn4LOkzzQg8Otxz06vTvkrlcX8ICBt0B+aCL2PUfwGHwuXaA+T9B3HCMrAvm5U/D4yjQ8vqLHBahuzxW/k5fVXPUuU6+gfzbepIeKc5PuGdiMI8FcpVPRgxwjE6BAj5ewXvT84XhMZLJzDEpshr4k9irUSsUrn3im8qzrsTnGSCPooYWsD2g9X7s+Tx+TrYHaowWDpB0sbi/zQW9Vc9u7nLLUNfWMrIW2A+Rq0PKiYvqEYhpcCur75L4LeoTY74N6zrgLpmi93Au1kYLnUqz3beN+BsThddAnSa/rabecMQmQwFlGwH02OMs2vchtLn+DXuQOKXeIBEiABEiABEiABEiABEiABEjgbCTAB/Sz8ahxm0mABEiABEiABEiABEiABEiABIocAT6gF7lDyh0iARIgARIgARIgARIgARIgARI4Gwmgeels3ANu828ncNjrYpfTjbLfjXZ85z2WOXVeWMexM5rMRmUjFZw2Vxbdiu1bfYY67nrUSe58s4cnYhJt255n9QrMf6nqa32I+Vxnx0wmHNM1JTWwICsd5x52PeJ+kbWzHmnT33pMzYJ4Qc/x/ocOHKn7398jJij/ZUnrl1z/JB6Q+HJPQFv5BvvGJFWhIPDONLUZq0DHx24K6FfUHMpz5fie5EEp6IcNykXvdp6o2/zUHYF1HQnKBvRiuSQQ+8HAyqDfSlRtUyAtY+RCXKA9yeoSlYnLbf3wJjb2om5954EelxsGWhKVnor7mZDbFupjUhaA7pz+fEDXlmsDsQkGTMHrU6ZAWvq/ciMuWK/myUZs0rPvm1A/KvJ+R6uboJp7vs1E9PXOjHvWaSvSMxn73iV1IX9IebVDJSaQz9w7NxCboFvqPNDj3kC/+9yBVSEvcSil4cew4JnYMqAH5Nl7Vc170O98oTwJtSlDxoFeFY/m+qkSC3lp2RC1up8vDnOui7FYmnMR6kHXoQ4asRQWdBc8SGOkCuRFn/fi+MarNoDaAdn2+juS2A55Kak86LIF8y1DQe9Nrga6hSwM6GwZHohN0E1eBz3DGzXC/ZSUna6UiKRFoMvr/cbTSZxTDdpRkAAJkAAJHJ9A0PHTzJIACZAACZAACZAACZAACZAACZAACfweBPiA/ntQ5jpIgARIgARIgARIgARIgARIgARI4AQE8J3AExQzXUQJmLcQz7f7tuSwjU3UPMPR5zqxF16KUjbiG3Ki3hyVVitVg62PwIKkRa+Aln2OvMOJTfil0rvL44ItF6Ou4OykycypjXn3dVsvkyU1bD5SvYbovnpvqvS2DEEyL8bn2r68qLfga4wRXX6AfNrYVgGd+Pi3gdgEA6e8DFrGo6QqhARKOK+4ms0bhpaJPLEnFJx3Xmm04BRgrZNvgR0spV5h19OJJahp1vLc1229nhJkdqC/wdrnMRvf1V4veB3o6QYvFDzPB3ZWnpYn8PXcCKc+LSewGX4Qql6vxaz3GvrjH8IizWGQujvNVdNXDXfW/b2yoLSPbQx9T5syD7R0aY26L0qFSUZ1vh8KIid2CuiOsQ8EYhP0V68wt5QbID8zCc+lUeom20/Qh7RI5kH7TLHvIQclLYXcuMjWoCUdZZ/Md2HBiHjt7bGvz5vCAS0rQL04rqOsKZ9BLiu2B2jBU08iJQryX8sO0NtS8HX8nJTqkBexr34PF3xVu29KHaitl4J9r49uCflyyZahnwhvAnlJ343aud+HZKvtfB2/p0IexPt9WI/N0FeaXA46JhmtG2MioyE/IPXDgH5VBgZiE8wAZZxuD8KSsere8aj3zeV+DsthV4p8vg611FeakgRIgARI4GQI8DfoJ0OJNSRAAiRAAiRAAiRAAiRAAiRAAiRwhgnwAf0MA2b3JEACJEACJEACJEACJEACJEACJHAyBPiAfjKUWEMCJEACJEACJEACJEACJEACJEACZ5hAiXzvc4bXwe4LCYHMzEypU+eI127jxo0SGnpkepZFuxZJ1HLH31dabbBjx4yqiLmFqag3hqGusxd1AWWtt0dSB1WFa3lFW2CBadFk8c3YuOwdqPdbr62f2P0c5Ic8Ngd0vDi+w6rKS4lWW5ER0FSUPVI6xn8BBZM9RyV8Xq4M0t0W2A6/Sg8d4Rwg6IXiDyMQp7yYUVthUzp0/Rfoqc4UU4Plc8glCB7fmoJ9Zb3aBOplsxlUwn7qxadY4UXaRy6hTvtB6oJ9CPuSkXju1euNfd/meOnNSkeradsGqQsjPs7xVydlmCb2845yyN7zuM35EXqx5U3lYU58Cet/QhmXbY9BtmL6qaB3Pkd787ErkQ54/YpaV4fkIdBiani81Y/a0I+eWqEWqHtPaBjmj9zGA8sGpyC3BEGPs/RpEKiV923oR5mog3KXwoKh8jPovtIctAh6r58R3JcBI2+x9V/Z0I/QWi0SugkLdtdGvQulqFNXPlL51C12wfO1bGyiCSgldR8uCC+L+s8oBW/vIoqjpK91GqhzpU01J+eFM91aT79aF/MfqGtypl6Z6t+55oLU+AbVJQ/6bg2DvohskyDIz5UuoKOlDegoNa/aUGnk5Ns6MUMSIIHCSMB9NiiM21ectgnvvsVpz7mvJEACJEACJEACJEACJEACJEACJFCICPABvRAdDG4KCZAACZAACZAACZAACZAACZBA8SXAB/Tie+y55yRAAiRAAiRAAiRAAiRAAiRAAoWIQJH3oG/dulW++uor/8+SJUvE/PnppyMGwS5dusj48eNPeDhMzQMP4Fy1x2r0xhtvSNeuXY+V9pfv3btXxo4dK++++66sXbtWDhw44HvD27ZtKz169JC6dZXn7Li9nXzyWB70nLxFsvKw9aC30j+2yXDWscOJTfgj6qjbUC9cg7piQ9S73kAt5QbigosTrVa2QZmtPOdlrrS1JvquK+r6yvB+bz3MS4bSrsdVbXg/Var9j9+ovPKkippPXpKV5zHY8Twqa62M4Nyyim6hkz292cXdz+vgxRTJiUPv7vAkOz7CKKnkNpVHZDPoYCkHuu/LN4KWx9zzVqSbLID8PDVJ992OefdzeQtqt0oc6K7KY/yc2tact9SJfZ8yCic0gf66DZ4X0DPUfl0p+wM5E8yRv4DuL8+BHjAdPer92o2E/GHltx0RfncgH5oeE4hN4M4VfiSBXmpRc8/HybwjZf/7W3vap6r5owfLZ4H6VRISiE1QXm3nOGkGeRHlUVbZ/vI9LMlX/ZUX62nvXxXvof2zP4C2ep7rZ9W21DuBpznXG4XA/aTC+VXKTUm8Mo0PmYDXiHSpAfUFOYSq/GVKr3P0bif2wldU7QK31svPwPI+2XNhwYgEPH+UlVtCRiwJ1OdI6UDsB5F4TUg2piXz+Odee88p7n7KSb4rZaYEB3SOVAnEJuimzPLvemef+8mRTq70HOf2mjGJy6UF5FOdueZN4hLn/BghT0MtBQmQQOEjQA964Tkm+A1ZeLbrtG1JzZo1T1tfp6OjdevWiXkQ//bbb6G7NWvWiPnz2muvyb///W9p0wYHX4FiChIgARIgARIgARIgARIgARIggSJHoMg/oLtHzIxg3qhRI5k1a5a7+JTiTz/9VGrXrn3MNr+MjH60gt27d0u7du0CD+cPP/ywdOrUSYKDgyU5OVmGDx8uO3fulLvvvlsWLVokkZGRR+uGy0iABEiABEiABEiABEiABEiABIoggSL/gB4fHy/Nmzf3/5jfpmdkZMiFF174qw/lRRddJGFhYb+q/T/+8Q//t+Sm8ciRI6VXr16Bflq1aiXR0dFy7bXXinkFvmfPnjJ3Lr5GFyhmQAIkQAIkQAIkQAIkQAIkQAIkUOQIFHkPuj5i7gP6r/Ggf//997/qAf3gwYNSo0YN2bFjh/9b/BUrVkhQkDZ7izz66KPyyiuv+Ju9dOlSadq0qd6FX62P5UFftMebB31dlO13iw39yLVIKpu3rFS1y1DHKet+krL2idY7h2MH5fpaXdWGfrTiHFxQcRLqTtpjfqKfRylfojN/rCQ0gL5DBltPoUnkSATkZaDjIfcyfRLxhy0jXr0a6x9Wc/6C11fPa3sdtqX64wn0UyfyRVuPv00H8ZgmPPxpoH6w9AzEftBG9a3nSVbnZoFrcip6WPuoOb9HuHMXo2VYuvdIhm0Z0yYatCj7u6zGdHwSTkY9pM3tWHDngYCu+fDyQGyCrPEvgZbp41FPRdld1LaOVtvaQ1/fzo1uKF7fMg37lpQ1sKCP4PXq+nxNYZoacyBGzQfeWA4G+stQfvZpfa4J5PxAW6+f0vuBnvT23t3I/WyVkq6EeLGot8H6hUE+ZJi6zz3fHPL9n0LPekk1b/aQaHW8k51t7aCY74WuRVKV1vf/1ENYEI7396B0nMM9L7KZrdd9S4bN+VEY6rfWo96ovlsQuch2LJcUR3e357y/9GH174CRuB8hvdUxaIPHQNKdvk3YVulRltMQNVbCNnVuVHPGozC9lPH+cz/pyj8fKjvdtDfaAfrfdzpjVIx5Xl2PT3EsFYBHQQKFgAA96IXgIPxvE9Q3Q+HZsKK2JfPmzfMfzs1+mR8MHO3h3OTcAebef/99s4gfEiABEiABEiABEiABEiABEiCBYkCAD+i/00GeP39+YE3XXXfs34A2a9ZMypcv79cuWLAg0IYBCZAACZAACZAACZAACZAACZBA0SbAB/RTPL7mN9zGy16mTBmpVq2atGzZUgYMGCA//qjmG1P9rl5t3/1s2LChylpZqlQpqV//yKtfbhtbwYgESIAESIAESIAESIAESIAESKAoEkCzU1Hcw9O8T59//nmgRzOfuvmzePFief7552XUqFHyyCOPBPJuYHwd5mN+O165MvpP3ToTm9HmU1NTZdu2bbJ//3455xzltdYN/qeNx/x4n82bNx89XcJbXNJJXeTEJtzh6AwnNqGavlvCMJ/0HmplURTZpfyWh5Tv9PCTtoNNY21sonLTQcd02gR6brSd79ckhiZbn6/R/SNvNv+zny7oG5d3q9ncYBuaqI/8BAsOO/Mam8QPiUfegvilaMSUkF/CI/+P3YV6eBjqsFVW33PsNy5sEaMzSmCs8oHvUWurrTyq96mffYaGYYM4lAfF9aXieSoz8boOkZ+hcbnBX4HeK+aCtp/ussEKLxojdUG780l364HrGuPNdOx+Bs+c4UpJuBNN6CFJ30B+yFD0IIf2j4F85swfAjrrVftDTLNwcNe7AzkTbNce88hoyFdMdW9UXuo/kJYB3kzq7ucZaRCQ3frPC8QmqK7mDl+ivLgjRuJ+SG/k1l9t61DF8UbHODymJe6HHpdj6Ag8Hwrct1JDYdun6ZvyFLzvB8Xi+QGNhzm+fC+R8w7ex+QeqJZ35DxY8LDyv4ckL4F8jlwY0IOn4rk0Qc4N5EzQDb54RCZnVoL8HnWer49uCXkHsb+8Xqo1gq8X/CF5VTXfdzbM1y6ScB+emyUFr/f452/AdSts7ra4402YRi9ILWib0xuZ9lI+74yZ86B+nJqbXkbhuShiPejxcim0FTVvuTbP9xHne8hr+b3gF3qo4H6XhH9IiLjjK3R7Crd7i5pTfaa8q7aNkgRIgASKL4FSxXfXT23P69WrJ3fddZeY0dbNA7T5rF+/Xt577z2ZOnWq7Nu3zx/grUSJEhIXp/717dXm5BwZRaZCBXxo9DtSf/3yirtZbKZmO9kH9F+2S3VHSQIkQAIkQAIkQAIkQAIkQAIkcBYQ4AP6SRykO++80x/YzTx8ux8zfVvHjh1l+vTp/sO7Gan9iSeekNtuu01q1cKfipsHePMxr8af6OM+kOfm5p6onHkSIAESIAESIAESIAESIAESIIEiQEC9h1kE9ugM7EKlSpVEP5y7q2nXrp0kJCT4i8wc5q+//rqb9uOyZY+8Pn3ggPsqa4Eyf4F5rf2XT3Bw8C/hCf9vXqM/3p+vvsJXYU/YIQtIgARIgARIgARIgARIgARIgAR+NwKcB338+NMCe+vWrf5vzfPz8+XGG2+UWbNmQb9mMDnjVTevr5vX1o/3MQ/8M2Yc8eeZ37y7v1E/XrsT5Y45D3q2Nw/6gijbHK2AIkfGrDuSR9ugKPucKGu2yPm2Wz9S1mvZk4wF51ifoJ8I72vz+ucLWetszkRJKOV+pYetxQVtGqCOQBkywvonC8xzLluweGQYau1JTquHeVUu59p1+YU7utj6OPsDG7uQ0Zkl8CV2XxXfiJHsI2/EBIre2hQI/WBvO9RxX6Du54xvYDLLnXTX/zjCC6fcgnouSsm2HlM/o+aDTkz/BBrsFrz/jAi/2+b7ZdvYRA+oHyhOfB7yNTs7bb1M1tArIS/91XUyXv1MuGuerZ/iQhCJiEXPcZryO8uUbbatifZegLqr2vZw9GpLut227moC9zFSBfoKcny8JuHOY2502istzP/sZ7faz/PVxNupkba2sg39SJ1KUlPlz9uKC8r9gFr2oD5QV2ln3IAKkzCX3hx1qNqYMjswnz8d9d6ZqLfNQ13RkaorKefkTFhW6aFK6/v7dpVPUgtCnWsuM0MVq2tIHW8RPHdC5TZon/nO/4GWtEtQX/a11Qec7TBLD8fbnIkWjkedtAZ0kLp+8wY2g7yoQ9ov3frGh8mfsBZ3SyRzBeZfvBS1ui3GTF0A+Ri1bfnOvOh5alyHhNFtoW29Himg109xB8YRGRSbBflB2k8/53rIS5rz74PaDn9T9a8rsFarbhtwyaEKqMuvRh2rT0ZMU5HA2UKA86AXniOl/hVReDbsbNuSGjVq+KO6m+0+2ojuoaFHvgn37NkTmA/9WPv4y4By1atXP20P58daF5eTAAmQAAmQAAmQAAmQAAmQAAkUDgJ8QD+Nx8H89vxYn0susT9RX7MGfyLutjl06JCsW3fkJ7+NGjVyU4xJgARIgARIgARIgARIgARIgASKMAE+oJ+mg2tecTdTrplP7dq1C/R69dVXB5a5U7UFFv4vWLp0qZjfspvPVVdd9b+l/B8JkAAJkAAJkAAJkAAJkAAJkEBRJ8BR3E/TEU5KSpJffoN+3XXXFei1devWYgab27lzp0yYMEF69+591IHnxo8fH2hrRo//XT5mHLqLnDWFOLEXNq5l9UrHvugvRduoSBNb60dHfmZhF+61oR+VjFYL1AB76W/afBXlrUy0KT/SfQ/bjQVvqZ9HlfgO80tcCN7UeG0cP2ZH5cXMCoO2Ib3RQ54z1GlrKpsqX3EstpfxY6E/oe8ceZwO1cHxJJr+2teHXut1eTug1ysvZQGf94LGgVo/WJMGumbceNBZr5cBLQ9mohZ7z4if+QLkhoh+4+YQ5PsIepJH/BQD+a8E/ZPTnr8V8mBZfrEq5mQt6r89BzprymegZRlKb6JIWBDd9Z+glzoDReTE4s0jLcG58ZhWg/dBW4nFvqVPDcyrebQHpU+HvDtn80Bnfu4jRdWgNq8q6jRtOUV7rHc/VZ7zPWHQnzSZZ/XukTY2UdhTqA/jvNhSUp07e5GblN6B7ctsUNpZ30H0+UtdVXuO8rcfUIOKNH4F+15yDupq6j5YaaDNl3rCxiYq3xl1mZaoX9iF+uVY1MkoZSAes5BEe49252P3W6njK9nqvFfncRfpDisbeg+eey29WdzdT4y0Dch1qq/J/cYHcn4wE+Vw2QgL+oarL+HqkBZ5GjlNetA5ZkNUbfxyWBAuzvHxMlWfcMaA8fTi8Cio157zf4lzbnmVD4s9lw/KQWg7qMd01Mrnnxi7GfKHQXm7KUthybM3gBSZ5FyDP1yByWR1L3ktD/N966LW3nxpCvma8g7orIFXWp2I3zM2wYgESIAEjk0g6NgpZgyBjIwM+e9//3tcGGaatcTERL/GjNb+wAMPFKg306v16NHDX7569Wr5xz/+UaBm0aJFgRHgzUO+mcaNHxIgARIgARIgARIgARIgARIggeJBoMj/Bn3BggWydq39afj27dsDR9Ysd39jbRJdu3YN5E1gHtCjo6OlVatW0r59e2nSpImYAeHMb8vXr18vU6dO9f/88ttz8+B9/vnOT6yd3nr16iWTJ0+W7777zv8Null/p06dxEyllpycLMOGDRPjQTd61KhRTkuGJEACJEACJEACJEACJEACJEACRZ1AkX9Af+211/xXyo92IL/88ksxf9yPfkD/JWd+u23+HOtTrlw5efHFFyUuLu5YJRISEuJPn9amTRtJT08X81q8+eN+KlasKG+//bb/gwB3OWMSIAESIAESIAESIAESIAESIIGiTaDIP6D/1sPXtGlTeeutt/yHczOA2+bNm8X8Ft78prtKlSrSuHFjuf766+Whhx7yf7N+ovU1aNDAf2V+7Nix8u677/q/3T9w4IDUqVNHzIP73/72N7ngggtO1M3pzed4pvPF1wT6rNNlfiA2wcpZjkSbtohjtfKr8OcdIofQ0yZNjlgBAj0uqhoI/aACevmk5M82H6t8ZHou8qHKszoHvbfyhdJJW2zfJnrjbtQXv2t18Dobm2hTbdAFPI397ZsafuHwW6BeXmsNenSXjaB7dAVJcTIEOqtjZMZWcD6RSZ0cJZJaH+vXj3e83FPwPBw0E/2SG65+HfoaJ9mg90oJ0PLgLtQJoajX220ZMnEF5oY0RF0W5Yjea3CBmqO9nDMXsSms+dRXUJ+V4FzEmZASeVV5McuosRh+uh4blEQZJ3NgQVLPMaA7jvoioCe3wes3aPDSQM4EeaK/rhBExAj8AWqamst8UHQ76E9SHKnOFfnXe07SC3cMRF22Nep981Dv3o8aN1XkQGebb/itjU20fj7qWyainjscdcdWqD94BPUe6732E/l7bP56te7F6CGW0N621kR5KGW1Wlf+K1hQaj/q3Y7vvNIHmNupxlwpqczVETg2g9wUi+0f+xC1nAs6Z8pPjlbXY5o6j2c3cGq9MOUQ6KGTdoKWdeh3Tyk7DvIpT+22OlR9D4XjvSMiE49J34HKc37YduVH536HC3bhl3SYM6f7+vgtUFtP9oFOlzdAeyc+6JrpeO9wx3EwhQflWagPEsv8GbkaclLA949++IFV1VgZLbG5zFTfsVXtPdRUBnWy9488dVrLeHX8y62HziMy80H/WY0b0DfyUshnpap/m0RMgTwFCZAACZwqAf0vnlNtX+jrzSvs+jX2U9lo81vve++91/9zKu2OV1u+fHn/FXczUBw/JEACJEACJEACJEACJEACJEACJGAIcJA4ngckQAIkQAIkQAIkQAIkQAIkQAIkUAgIlPAGN8N3eQrBRnETzgyBzMxM/1V60/vGjRslNPTIa7aL9i2SqC1RdqX4FpvANEzqFVZRbwbKrIttPya6CF/Xk02TML+/JuiQzjhfUY44756G42tl6g1GkTbQlYh6E1T0jG76dd52qn1kql0QlGNjE225CvWPKKWG0hXViPxBn2HBg5ejpjoKATyXOsgwqKmvXqHcpn7+OC6yNdR3SMU5h6bKk4F8iKwOxCa4UJ4HnTqlO2j9KqgUOAG+x/ou6vXcUc67w7PVz01TsKncq7SWIzLUEnz9VqQs5t9xXpHdE4a5fPWS1aEymN+CsoBSb1eLelu3+xPJgSbnwo1GZIOaHu4dNbVV7pShgbYmSIhFW8HgF9tDXirjq8Syt6rNt6hvYxMpKbPVO7J54VhfQ72enXkz5i/4FLXLDWdsEsE3dUVaY1OZpHT+NbigVBjqffNAz+62MaBvnBgIjwRhSjdRGmfKkgLT6un8drVtHebbDqeqnPvqvak6vM3Wmqiz3W4/8cFAzB9KRF0apeTZ61tK1sfk3itQl8PXrUVPZTdA3eDVNFwRgt8XW6Uk9u+orLgrHeWFScqyglmR0Q1xib7GpmJach0d6cQmTFXrisS+B6R+CA3+LbVAr5dmoIfIPNDxYi0Qz8hYyA1Q06qJ3A55kRmgI2UQ6Fx1v0iXMZCX6LCA7pM8NxCbYMSLMaBlL8qa/fEfQVmCljaZoO7RXZx7iemqTVnb4Ux1rtkMIxIodATcZ4NCt3HFbIPUXaaY7T13lwRIgARIgARIgARIgARIgARIgAQKCQE+oBeSA8HNIAESIAESIAESIAESIAESIAESKN4E+IBevI8/954ESIAESIAESIAESIAESIAESKCQEKAHvZAciN++aN00AABAAElEQVRjM47pQd+6XKJmdLKbEIleX5hpZav1lPkN9r1i25no0DmoQ5QhbtMlmK94APUY5XF1bWmJa7E2tAHqzAzUncNQq02Rf23C/HblM6vkGNM+L4e1aI8TeSlV5ZXZ7wa1rgPKF/xwI2xfRFU3eR32bNzkiqBlb1hA13wAj3eW1Avk/GAgMoxL/Bfkk9o8ClpmKr/l6+p4/+hsi2Mh9Dupno19lVfHW5Th9Uc1RsH5X2L7WOVLnOLkX/gT1nZBKY8hF+mA10G3qfOgwTiYXspLpav+XXt9dga0lX5hqM9HKX9XWsvc3bikXwXUww45OtOJvTA4DPQzuf8BPU2c4+VlFneOgrxcvxV1uTTUW663OlQdj72dbc5EB75CfSgDdakw1CXKo670NepajnSG2XCW2vAnG/qR/rH6uSqvrNuy4WIsqOzc3/XxVJsN937Tyy7sqsA4IDtU/qDSrlVXWa8LeO+1t1p1JRFqwUVK60vUPcSzn8Ri7UmXw5jf0Qt1uemoP1T3JnUqP5Niz90BLW/Btvr4d3LGozCVPdUBH9Ma2+fMQ11OtZ9k28ckL4Da6mrevMlvhUK+4324I+6UbaZwRM8YqI8Zhf3PlYY23xLv10EpS23Oi5oL/ltgsb7fqzEpRN9LmuCX8tDYUoH+fxAcAyRJ1DHoEBao9YOpuN9DZSXk+8t1oKVfWdTD3JMNU1QkUJgJ0INeeI6OvXMXnm3ilpAACZAACZAACZAACZAACZAACZBAsSPAB/Rid8i5wyRAAiRAAiRAAiRAAiRAAiRAAoWRAB/QC+NR4TaRAAmQAAmQAAmQAAmQAAmQAAkUOwL0oBejQ35MD/pPmyRq7tsOiRAn9sLcx6zW1qpN6CmWJ1vbWhNFogyaib4z7YHLmpKDDZZfb/Uw5WdNUH7WUPSwycPq508vWk+a32lV5QvfqzzJwY6HdUMNux0mKo1S6qfgggP3om6KUhopfZbIDoKG6KnB8bjlucrnLa7HWCRc+kL9ffIo6ITQtlZnYl+Jykc40Ovt+J8GmJ6Cptb2sfsgP809KKPRLylYKtJbnYud1bnYZhX0LffURR2q6ns76R5O7IVDZA4siFfzvYcIeqtzqjaHeolBKd8pnWrnfI6ASZPF6/lyLA5VXks8nCKPr4X6boJeznFyKeQl0uGcugVz4uRUxpdD1fUcPh+rDtZEXXIh6oqJVuvr8fNrbM5E1VTfe1/EfNQTqBeORJ3rHmAvVcdJl3RiE16p9I9KK3u0KGxR12L9wimoxbnExB76I0XqlimZL2Pjas53gcmo66LxrVi+8t3RuGCXc3Lr/bgfS9U02KKm4BZRp6JkqPZ5r+OCcg9avdcdeMFbXPMpmzNR5ieo815F/fNzqCup75Jp6rtkrlP+tBN74dDen8KCdYLjuIxLaA152YlSotS5OecaLChnZbdR86zwonHBrUFLLl6/Eoz30Hq5KVD/oNqY/qE3Q979/n9m5n8gN0DNoZ4oeH/erTiMUDeyEFWfU+BL2bnX6HtFDfVvhUrfwLbJFHUPDcW0jFoDC4bKD6D7v32h1feqi8JmGJFAoSNAD3rhOST667jwbBm3hARIgARIgARIgARIgARIgARIgASKEQE+oBejg81dJQESIAESIAESIAESIAESIAESKLwE+IBeeI8Nt4wESIAESIAESIAESIAESIAESKAYEaAHvRgd7GN60LetlahZQyyJMsrD5hoN88+zdSYqsRn1AWXmfL0e5pOVd1fPbdoZyyXM0RlObEI9P7DebJz6VOQ6Zb7doCbOrT8LVxB7hdXDlR+2/sc2Z6JDyoN6LqZl6124oPP7qAurCl8HWxaaHgM6c6xrrhQZ/PgMyCfEuYZXkeFJsyH/quB4Bzc4ptgk5bWW19S5dFiZUH8Igr5FzYsbE1sJ8nNHXw1aQrKtfmCXjU0UHWb+th+0Vhc8FzvYUj/S9TOV+TeuiWrgyFQn9sKIlEWwoJOanPpjxXTxFLUv2ryb1tr2p8dWwMNTwHMsfVfYtiYa4vg+jZ5o/nI+6ap+pFPfG32doudv15Ny56gLvsXlzoq8cNVY1IfxXJZKL9j8z8pzXE35RnNsqR/haS2ijpGsvBgbtPoWtcM52bGrmqK/qtN4pbotiT5V9mHXUllp5VHfn2fzkxra2ERdVK1swLyaDlrkesyvVrfJRv/FfOJVVg9Ul0CBde2wtX50h9LK9i3OkCF+pbo9SBmnfW0nNqHelgyVr/I6LIi62/Gze5mFSZAWOV/pvU7BYfUd+t4lWDxVXQdx6iAlZWD9i2GoV6MUx4Murb6GZFzHr0AnBT8KusA891UxLanKs65OviDJCDTope5Tq5RnfBoMzGCa4YmdIOmBvkwwWG4ELX3UAXe/g3urk6lPZWyrLn9JVfepCWrHu1SE9kGCxyxPOkKeggTOFgL0oBeeI6X+KVB4NoxbQgIkQAIkQAIkQAIkQAIkQAIkQALFiQAf0IvT0ea+kgAJkAAJkAAJkAAJkAAJkAAJFFoCfEAvtIeGG0YCJEACJEACJEACJEACJEACJFCcCNCDXoyO9jE96D9t9eZBn+6QOODEXpjT0ur30Hsl9yiTYucattZE/ZQvDC3LBb276cqsO9qZgFTZwgpMk6x9hMpiXmDa7MO4qXJQaffHV+fjHK1SqhMU97oTpDyn5y52dgMrC7mqir7doOylsMF5egwBmGRZJEFGQX1JCQa9EoyhIpPFev1CpQfUZk7+B+hBHdGE+qY6IaqLY7b1Wi7uEwXtpek81LmOr7TLZ5gTPIAdZSHkM6QU6MWiroPIBpAv4O1MtifvcNkGtX2lOmhp2QR1Z5QyXOlMdU2pfRHZ7jRwY8/vLj87OZG7ZQ/oeD2veYHJqtFHWk+Zfde3dO4tKeoCn4THTwT9sxKkvLm7h8C2SZn/Qy1voq7tGOS3YEpKvYwLqj6GWte7Pl9TWRLLRW2qLHPyuvZ6J+eFia6X1tMFvNuOn920HN3Y/G0/7ZV/frgzrkCS8s7vd33aXhfn4OEW0fc1na9l1+tH2Uq726p9/Pp+PFu1VZdBgVNtlr13+C3LqJXXcfpr6sQm/I/SeltKjcaC5nhvkpRpmD/0BupzrrJ6Zxsbm6jEIdSj8WR6JhU3bsDIW6C+e+9k0GNejgad+Jg1WA8MVWMrZOL1LlWrQdtB2dNBv6zua1lSF/LeYCxK2/tiPcePboo6q/uc/m4IUn19qwZAmBj5FKyrACfn3pQgOBjC++q7Iu35VtCXPKXumeF4/5f0tVgfre7vyfUxT0UCZwkBetALz4FyH0EKz1ZxS0iABEiABEiABEiABEiABEiABEigmBHgA3oxO+DcXRIgARIgARIgARIgARIgARIggcJJgA/ohfO4cKtIgARIgARIgARIgARIgARIgASKGQF60IvRAT+mB33rbomaucaSWKO8fJ/blMQ4sReGDENvdk5wcyzItd5aPxGp/LNotxNJ2YHt+1W2uqwN/Uj5J+U7lX9AaeXFLDB38e0bsME5KVYf6GtjE4WjjLsS9SSUsquEWnC2yA7rcEvVVNOD+qNHMUjNsa19hAPkcexPzbMu6a53zzXqes2inXPB9JKcYf52PugT7C/oCx06VA0U0N85571eYhwv9tyhVzv9euE2lDIqAxf0C0ONWArOky27sX5kBavTbOhH3yh9mdKut9aktFf3Cbymuikf+Li41rZDZdtVQwZI4kTrZzWNBgYrT2sH25UfOZeQr/upFSxy7jWNVFs97sPh8liwfyTqgytRVxqKOg/HLJA7E20ebb7e2BhqHvNDGbb2KNGEh/fD0i4fgJQCY1Q4Huc0NeQHtvRmgy6JSw6pe8kW19ftlaqzXJR7Wm51Tr1w5Tn/GU8VqaKGUhA8/JJ+DW5b+CHUynYs2y6w+WpqrIRVz9mciS5EKcGLccHySNQN1e07WO2buPumagv42fV3zUFcV4ExBhxfv1/prsss2OW0X+ec82ZxRXVNlHjbKfbCA+ogfFoP8i0mLgS9TYJAr+/Q0mo1BkxI9hKb86IcqQJa1P1clHdbWipQKRnYPjjM6twtNvaioYI3ttFq3X9RN918yYf2BfzwPdWX8Cj7XRLkjW7ifs4R/MfBefKqm/ZG2kCGWXIR5CNkNei0AjfdmyFPQQJnCwF60AvPkcK7UOHZLm4JCZAACZAACZAACZAACZAACZAACRQrAnxAL1aHmztLAiRAAiRAAiRAAiRAAiRAAiRQWAnwAb2wHhluFwmQAAmQAAmQAAmQAAmQAAmQQLEiQA96MTrcx/SgL8qVqKiNlkSwnbvUX9jWpupNTbHCi9YHO/42kxkAaVHTj4pMVfmBSju2UJOJkEWBgjTBuUpbqLmoF8slgVoT1BP0GK+foOZsLaOMgvsSoH3jrl8H9MovA6EfLFJ2t5bKc1qiI9afrWqovASbnuO5FN3Ps3KDK73YMbj6mX0qj3q4bIZ835Y3Wp2SaWMvipPpoJPaPApaZuK6a8oqyGepOXxldBjkZYwj07WZFvt2Kv1QexL3CBqF1/dR18mlG6CLmM5W67nhs15pBrXyiPq5qrJiKzulSJ+92P4HNfCDa6cMxVI9dbhkZ6gCLSvjgglq3fvV+RLs3FzOUYbmff/Bvsr+CfWB+agPx6Eu8QzqA5+iPucuq+9738Ymevd51Jc9hXobSlE+cPnmHCy4Cz3q4njQ9yhE3cKwaSeUcqk6FeutxYI9agyCf56P+RscP3Ws2m5FUFvOZSFeviLrsO8l4aibO+symXznMlg2ag4Ul78Bz42Gl0Ja1q5AXesH1FuUtbua4lplk1O/VBWXVD7wa51aL6xYH/WuNajlK6XVMZBIJ79wuCO8cMcg1EHqXKn4JuZzlTu/pDooSre4x37PLdb3wKoNoO+ns/EL+tm4DpBvkbQQ9GK5ErTElUI905EuA29xxEz73W6q7nLGADF6sDjfBWbB8LLmb/sZZ0MTDU6fAQsS5GKrg3E/JTfD5kwUHAa6Te7ToCOlGehn34gBPfgB3JcE6QF5ChI4WwjQg154jpT6l17h2TBuCQmQAAmQAAmQAAmQAAmQAAmQAAkUJwJ8QC9OR5v7SgIkQAIkQAIkQAIkQAIkQAIkUGgJ8AG90B4abhgJkAAJkAAJkAAJkAAJkAAJkEBxIkAPejE62sf2oO/1POgZDolMJ/bCfo5/a9gWzBWYQHY35oc48zt7mW7x8yA/bnhr0NJXtRfHCxyp/K2p26FtTVkPOguMf16qjfKwDVDGwjWOZ830lGdNjKMf3Ah9q+mA5UO0HMs5UH32ij7yLGz8CEFvXrjy/acr33eITIL2d3szzLqfJYqU691eL+p4t2noNpWWM7uBbiexoPW8uQNfvhXy8tgW1O4cvx2Ul3LqclWrtk1l5R177vipe9T4B6+pn426vnA9L3aTVdj7JhxrQULVedxVGYMfweai52yu5eQf3+cILxxdFnUPlQ9V+QewXC5W25ajtq20kw95FxuXUObqffMwX015yndgWvYon3HZ1lhQ0jEK71HrbqU8yWqzG9+GXa18G7UoTL0exPwKR3ZyYhO2/wkXVNqI+mt1+MsexvxVwah3Kn903SttfmaujU10ybeoS6rDW8BrXxrr89HCLAfaYD6tkaOXLnXESYS33w5FwT/+CDrcheplSj8MabnUsU+vfB1z0lxpJaOUf3qh+gLoqG4tk/WtxeX4pep8K+rNaiL7877AfIGv3PXTsOCAujflOSsfpq6JcGwqM9eoBaFKO32ZzBT0Xsuuplj/UBlHq4tCMpycSAxMVC9eFu/Bem7yMPffBl5P2g/f0RmjZrLUhnWJ/m4Jrob5y1DGp3wEC4aIc9/yM86/UzzdzdmXcaIufuiJggQKFwF60AvP8VD/Siw8G8YtIQESIAESIAESIAESIAESIAESIIHiRIAP6MXpaHNfSYAESIAESIAESIAESIAESIAECi0BvuJeaA/N6d+wk37FPVi9xua+Mvm8evXzAfXK3BDc7prx+H5lVmfn/UpT6vZtdBXzl/NxZ5wZpd5hfVG9ynf+EqehF16mXh5Vu5Ws3t6LXozNc5zpic7JwdyMxqjvVK+4Y/YsU9HO+7zt1LZPRx2cHIELlOoh/4Qlq9Q7stNCr4F8+8z5AT0tHHM109W59DyeSxFP4euWlwjO8TS56rWBvk3QJ3su6BFykaPxlUUJDXNyXjhyJOrevVFnov1CBE++EHHnNhNv8jrnQpg4Afvq3Af1UPU65hxMy327cMGuiqirr0d9396AHiw/BGITJAxpC1oaTkG9PBb1I+rVzzn/xfzhlqhLL7A6W91LKqp3/a9sZGtNpG4Hgm88S4G3UFOx/zoP2XvZRv0acUlclTptpQ6eeqIIy0q1baPVrepy5/Q6pH5Mrl9Zb5mM23LpTahXvI963h2oWz+Nesffra64ycYmKlkO9Wz1CvRqdZ/TjodFitvF6lTc5Jy6+071FXfcNGl6SzNYslfd/stD1hOH7YIC06a9aXN+5LgffF0X88nqVIxWbgtR+QK2Erc7xUz0K/D69fsZF7utvTnglC8h70XMp99mdX/nxDNLh+Br5JJuS/1o4nK1IExp1V62qHyFgB4q3wRiE/SfoL47uuD12V7wgG4VBKVfgc+C+7eZ8XVeYH3PyNWB2ATt1f33crH3ApPfrw7YiPAYs/jYH/VKvNx0ia2Nc/8RYxczIoHCSICvuBeeo6L+aVB4NoxbQgIkQAIkQAIkQAIkQAIkQAIkQALFiQAf0IvT0ea+kgAJkAAJkAAJkAAJkAAJkAAJFFoCfEAvtIeGG0YCJEACJEACJEACJEACJEACJFCcCGgDUXHad+7rLwQu8H5OM9J6ZGN6O75Qr2buI45/6y/oExNRXtskx2Tota3hGv88nTVx9y9rPfL/l61HzV/wmMpHu3m7jX6t8oXLNmXWm74O1/W3+qBbrgUps5U9do7jt6zz2RworrNPmUoF/ZBQfLaJZIfTT8iwXmoK7M1V0hX0xOCnQK/KnQ+6vnwPuk8mehZHiONLTHe2w2v1iLwAbYc8lQE6TQ1gkKan0kGbYYFpfCJkY6C/tPBWgdgP0pUXc7vynCsp+6pB+0G9p6Me2w60hPzF6s5ObJa+oq45nPFH5F7k1O3B121fXjRD0FicVVUZqMVeCAlTzoW2sn8D6lznXmAyDdW2KsZSsge2L/c46l3ONVtnJOaUb19ZTEXeUeWxSn+odKXnYEGUM/3RZByuQKJwuAJZmARNZaZzmprMM84QAkavzDB/288rTWxsorrON28cpqTJHrXgXtRXbUO9Kwr1SPVj99ZqSrDKu516dVrn/93JeWG+use+0FTlU1FrC3Lv2zB/P8pTU/PmQf1u9dVT0vGYQ+EvotYvgciuGTb2ozClledcn4qtp2L9ojtRV1bnU6OtTj7Mib1QjTghXdTxE3VJJj6AnvOBeAsVwVuuSCPn/pB0Dq68hDoBSpfBvJrqTIIrYz43E7WeX/D1GoF8/3/eHIj9IEjdW17G7/dpm67B+gyUosZmaJG5EAqekdYBnSiLArEJ9JSb0x7LgLyEh6EORdkv+T1YMCz4T6CfmfpCQA8Qdc8LZBiQAAmQwLEJ6K+CY1cyQwIkQAIkQAIkQAIkQAIkQAIkQAIkcMYI8AH9jKFlxyRAAiRAAiRAAiRAAiRAAiRAAiRw8gT4gH7yrFhJAiRAAiRAAiRAAiRAAiRAAiRAAmeMAOdBP2NoC1/Hx5wHfetuiZq5xm7wIuV5rWlT0vA7R3jh3jDUn2oPG6bd6Z79jPJmaq8fzG2svHhScz12HnQj6ltRpju+T5Mpm4f5UDVf8LIHlwYKajdrFohNUBtUURboQdfHLzgXzbgdpCvAmBj9FOgOyUNAN5RI0K5vUKQC5CQaD2BQsj0+pjCvMx4jmYj+yCHinONefXzLG7D/xzYFdEQXnA88TeoEckeC61C3UZy6zsJ87EWop6j69Ottvn+Gjf3IMc8aPRS9mqpYJDwFF8UqLsHIMSR3SaA+553ygdgP2rdHvQylGmJCRF/+O1T9LqVLOXM2X/YEJtX1KQvUfSkvG+uvRSkKm6hDAvcaZa0tMIf67Cuw85CvQUehBVUqQVbkk7dxwf6mVg9oaGMT7UQpScqTnv88FpRQFtd8PY92NazPucDqkJU2PmqkuOwIw6oq+hipQxSlzocvv3Daq+1eNh6vZ1H33KYfOW1NqLatkzr+fz2E9W2d074TpgpMPf7hbiw4V01lvac05mtloC5dF7X8ZPV8h79ZGrnd5kw0QZ23PdRXroRhvTfIBH4OjUbtqvzzXCWyXp3XmvGDB6B+yMPuAfTuodHqHnoTlIv0zbAL3lInS496Nmei+1Hqi6jb4HlQMG5sa9D9Hn8P9HdiT+5IiYJctmwC/aa8BPpJGQR6seB9cZr6npO3oFzkPmdbhjfBZF9nTADMUJHAH06A86D/4YcgsAFBgYgBCZAACZAACZAACZAACZAACZAACZDAH0aAD+h/GHqumARIgARIgARIgARIgARIgARIgAQsAT6gWxaMSIAESIAESIAESIAESIAESIAESOAPI0AP+h+G/vdf8TE96Cv3SVR3x5OlpjoWx4bWfUQybPiYqtGg5UWnH5PZWRvzPVagbnkpaq2edAyV+Wqy4c+Uf66p8nZFYGf/vRx1CdXdofvuw4KePQO6mfJDBhJFPRh3Mexhh24tQWdKBui2cjfoIMGfAe6SXZAvC0ZgM4VvlUA+Q83B21hwcuFpQ68J1Jqgff/5oMMETahj4tS5es0GqB/e2c4v3LfPjZCTn1FK9CpYkHgPetZnyLuQT+kwDrTc7FxUJhO0z+bzlMf8izI2ZyI8BDLk8TmQjxflC53yGeRlzvWomzdH7aqKyud94C43K3LQ+jz9RIVHMR/xBOq011FXetBqZdXsZadQ9mueU7uhpncXPQWzqMO9c4tdlYlSHW/2n0thbuMHqOV81IlXor4jF/UYdW9JOoz5NOfwR6jDK3uwNl9ZszObYf7vFVFP+hi1OPtpMgeusvkyb9vYRCvuRH3pc6g7xaN+2jltTeZZdeoO2ov1F2y2+nADG5so6HvU5VVfUbUw/3YO6pdCUDvfHH7iy4U23ybKxiaamYR6WVMFHdMSor4PwlS+zGBc8KbD7TZ3TnSvrIq6xER1lp+KfX2ozr07v8K8qOsGBkxJV7XqvJaP8R4qX9bGBpkopa3SFdT3/7dOe+W1F2WHl8G7dWeow1FKogLTqa4qUCcnZPFmkCjOienVDSywcQ2hdXc1r/oMNTjLegkN1Meo78i5U9R+xj4eqGVAAn80AXrQ/+gjYNeP/3q2yxmRAAmQAAmQAAmQAAmQAAmQAAmQAAn8jgT4gP47wuaqSIAESIAESIAESIAESIAESIAESOBYBPiAfiwyXE4CJEACJEACJEACJEACJEACJEACvyMBetB/R9h/9KqO6UHf4nnQP3S8YwfVlrpev/7KSBanDI4zVdveSrt9mVS4MkxWUJ7VLRfbDsq2trGJbnoFdUmU+Y7n0GSW1Ty+rxBbizcNbzO9iFrNGPy0LAAm5dTkxPEdboC8fIdyaOqnsKC/1AzoIOUhz6uqjof2brYJND0SpKCumY1mzayRyszZ2/ElTtoKjUM67Qed81on0PLQR6j1HO4vh2H+sTWoQ63HMSYTmc7tfDXW4jAQIpnotZfXDmD95+VQt1XezXaO8diZvtdvpG2ctbAr+cm5Pk0qqAYWVFCe1h11MB+x0WrVdJHyx7ZCm6iMVpbTHs7h8zudYbv2I4v4SKKlze/cZmMTVdL7/SPmRfth1bm4pyzWl1f+6uTrbH6D+jH53etszo8aoH43H3UXtW2LFMdLFbd9F9j2lb+xsYnmqXE7muzAfEZ51M3moc5T6/6qMearOZfRFsXokOLg1ppeKqvvpfPVZPPr1HdLg69x3eJYfzupe8WkF1TtVNTLxpzad0fT/Xiv2t7I9rdCbXcLdW4Eq2NS4nbb1kQb1RgFddT3nqRgvbjjH2SonLoc5edPsGD/rajLqcEZOl2E+dHqoC5x0vp6HOjkTPhEplpQDXQ9WQ56fbRzAXuZxGTc9oHSPFBfU9YHYhNkdbgStEzdAjpG1oK+UXCQib5tboR8vZkIfY8z9spN3sgq7mei3OtKL75KaUoS+OMI0IP+x7HXa1ZfiTpNTQIkQAIkQAIkQAIkQAIkQAIkQAIk8HsQ4AP670GZ6yABEiABEiABEiABEiABEiABEiCBExDgA/oJADFNAiRAAiRAAiRAAiRAAiRAAiRAAr8HAXrQfw/KhWQdx/SgL/I86FGOB10ycItDw6zWNjE9+bD2oJW2Tf0oKA8XlOuDulQY6nzHcFcDPecHb8DSg2gbk1U70Dd4ifKUr1qK+RIq3xS7p/IJoJEwXHoBl5bSGrQWDaQhLMoXNNSWFnvCpKq5ZSeLMh1PWQZ9SWwL1FpFh8KSAp7F4Y7f8h0o9SbNVqbkccpc2w25yIu4n6o3z2+p+hte1pYor63EZ9icFw1R/sh4PXHyaGVarlYf2kupF1Gn32b1Bar2bpvyI+W1jquF+SR1SGQD5kc7dneTWeGkk153hAlbK602TbaovJIT1LZ1mYUFvW6y+rk1NjZRmuPTNjpCzWsuK81S53O+E3vhIuXVbvUW5us8YPUKtR+3qu3+XA0ZUCrFtjVR3TjUzlnsJwYrH3mmMyTB38pg2wmOT9tkwn/AfLriMqkC5jeiFL0tC538Xeo8b6DW/cPXc5xqL6xcGfWJ1A7c8aY/2i+MvEhsnH056h8GDMAFd9yB+gTq3IuaQcXuUlaWwlueBKlz5SK0N8vK2batiSrtRF0Hd1N+dm4lpnKfc4zP+xLbRrVFvVBdIxKCecl8HhekKy791ZewOxbHcHViP4ddiXNe+plMlYe7hUiM4I7PHXs1Nki3ssOoIVZ4UbbX2v00FjwZa6vxT/pKK7fcc5jjDSNvOB7vkL5LAvWt1b+RfpCxgZwJUl+cBDrxCe2l/yvkKUjgTBKgB/1M0j21voNOrZzVJEACJEACJEACJEACJEACJEACJEACZ4IAH9DPBFX2SQIkQAIkQAIkQAIkQAIkQAIkQAKnSIAP6KcIjOUkQAIkQAIkQAIkQAIkQAIkQAIkcCYIOM6oM9E9+zwrCJizoKqzpdnKxHavkxuhjIIDlQmxlvVeHWn1o9PYC3f0Q13SmRjXy2y7GdPVXI9cV8wtUx5yZUnDYk9pzznnOS+A6MQL+jSEmvQRw1ELTtpbU9DMfZH8BPXfK5/5SrGGyRskC2pFrkX9chjoRNHevQshL8noG0yQ6pjve8jqkerW2DvD5kw0dR3qKSmo9bzKD6q5ydvgNdair3XnLpba2Fd0GOg9yTinr0gDyMsVyqyd0RnzB/EYyvldMe8qtGZ616+bFElSGETtpj5klzuITU+TXMzufcYklfda1DzXtzYxRfbzyVt3WeFFUXe8D1oao3zusKMV8oiSTs4LK6KUXqqvSir/htIb/4QLQu+3uu6bNjbRxl2o9bAdcinmv/4Z9V+roN5hLyk/Ud/h2OlcrF2hbueiODRIwvquD6HWc5s3UOfLQmee9Bbq+H6HNl6RdqOw80GDUJ9IKc/6sspLAy3qXY4rq/BtIOUHTf/0DCxYdgIPeogav0TUMYxwjkH+R9C1yKeov1PfgeqSkaXqZMxW12gVxVwq2/4rut+n3uICnvOdI22xiZTfXQ5egvlwZWqXyzAvzn1O3c4jshdBbdrj6PPW13vMKNyx6pIH7eVxzIvjI98oN0Dt4ugo0HOTsW095THvKF9DfQP1PVa27zbI5znblhCpoD+l7s9dUA+ciPcxUbdvWBEFCZBAkSXA36AX2UPLHSMBEiABEiABEiABEiABEiABEjibCPAB/Ww6WtxWEiABEiABEiABEiABEiABEiCBIkuAD+hF9tByx0iABEiABEiABEiABEiABEiABM4mApwH/Ww6Wr9xW096HvQ2uKKgmda7l+d6ykxZT2WIjJqFjXf0RH0Nes71PMm7lLfTbfyT8t4FKe243fxmG7VH3e3Mi+lBV0BOi0Qz52BlsJwKgx0UXGFHx/Q4Qc0Xu0XiocElau7axQUm0g2DegmtjBrt8CKPOOlmyud9Xz0naUL0LMqkDZgP2os6ty7qbGV63mfT7hy6ZmlOZHObNNGAFNQZLVHXVtteS02svBXLpcSTgQW9Or0QiE2g56pupXZT2/ij1DW50PV5mw6VX/YD56K9c4opcD45dRzhhU03olaHc6fTlynsVAvL1abJ5C1Ofo8Te+FGNTxBZjDmh5RG/YnyHP/X8RybysbrsH63s23DlQ/8SXVqnafWtboE9tVwOeoSNVGvPg91BcfUfIuCsuJjrN2hTq0VVTHfchXqkur4BjXFfHKe1ZUP2NhETdRpviysHRacqgcdW4O6WHnGn1Jzkw9SjM+bAM1FnkO94zPUlVugTvnO6pb9bexH6vjpec/rZmJ9yD9R7/g76jLq1lPeOWYV1fHelYFtJQx1HEpJWqYWrOmMC/LVhXS4l82XUuPXZKl7qrq8JUqdjOm32b5M1H8f6mB1A8hdYfMj8d8p7XvPtzkvmjbkGtCSjlImoh4ic2DBu1IedFqC46dX9ylRA1R0T02GtmN6RoMW59zxEzPrY56KBE4jAc6Dfhph/saugn5jezYnARIgARIgARIgARIgARIgARIgARI4DQT4gH4aILILEiABEiABEiABEiABEiABEiABEvitBPiK+28leBa1P+Yr7t/sk6j7N9k96WJDP6rzH7ugwuM2NpF6ldOd0sWkdzmvchr98Pnmb/t51Hnl0SwNuR1faywxfXqgOF+/sq5eeWzm1AYaMTijBIJkMvSfJx1Bi6wE3UcWgh4xOgZ0TI8FAT1XKgTiowcNcPEQVa9eU+w/8QOoHyrhoCUUX4OE5HPqXd5/4nRDLVJwv9qreZYGhN4C3cmDKMEJkKJeBR2t9ku9RSr1P8TO9iqNWZESw2BJr/vt653PqbdGV6vrc1A5aCp6erECr8Cuvgsb1HgfdMebrNxoQz9aqF4FFfWGa5ralgg1jZOoe49sVSs4aHWUemsUj6ZX574Ob5qpt2k326786Dz1WuvBVCwonWF1nNovnCxQ5FZb6kdJX6oFyha0X21rdEOsH+sc48ud2FQlqu2ui02lyw5ckF4Kdbh6vXqP0gecY1YlG9vmq0ts2QVLseA0qkrqFfcLnLehzWoOqeMbfAeufC3OECbnKudWVdX+A+cN6LZ4SxRtC8A1iWi3jKjbw0H1naq3/U/Ouf3JBHut++u5bj6u7nOVr6Hy12O56HNx++tYsLK11YO329hEkdVQ34NS+qqTLRxPzu7p6tXwzurV8Ainv8NObEJ3Sk2jQ9WJnLnGLHU+eDMJFbyvZcosp1ZkuNht6yuKqX4VvwM0lRYT8e6zWPRVeB02oCKB00iAr7ifRpi/sSv+Bv03AmRzEiABEiABEiABEiABEiABEiABEjgdBPiAfjoosg8SIAESIAESIAESIAESIAESIAES+I0E+ID+GwGyOQmQAAmQAAmQAAmQAAmQAAmQAAmcDgL0oJ8OimdJH8f0oC/aLldHzQ3sRV54s0DsB0Pfs3rPJBubqOvXqNU0LHmqq//Lx/Lmjg/UZEpfoXzA48djA0dxmjQHxh8UtlDzzyyWzsfdkgL1kVFQ3z7Veh5bCJqtB8jVUKunOouQjZBPk+agparyGWavxbw7x9Crynz9RRmsba+mAIq9BPMSqrRad0vUMSkLAvVzRV0DY9F7KdWV8fNg9UBbPyjxIep9r6CWi1GX+dbq1jb0I7WqxFjM36Cu31rK03yh9n0vx/bi+kS11VL/+Fj1LSmqL5U/UB/zZfR0Ra65W+2nnkWv4p+wr11foY66EvXCA6hnl0b9QgmrR+ba2EShOagrbEG9QJ0eVUpivtFq1N9dgPrSd6xu083GJvpYeeUz6mF+QAXUk3eh3qk85xVnYj7vCqsLeKvfsjk/srcCXy4bv1QVnKKcNy/QoMTf/x6ITXBFGEg59BHqtQ1Q62n3SqnvtX+pc/dZ55geco696bXGbuy7F9qdJUkd/4PqmiqVge1X3IjanVYPMyIXqvNU3XJlfm1scc1s1LJJafd6NilnvyX7TSyedhXqGSjlaaV7qwu8T1ks0PePqU463Im9sGPSF7Bgcty1oEOSloDOaam+S1IyIS/ReL/vkzw3kC+roB6SQ4GcCYZG3wl6cDKCSHixLeTliRWo5XalKUng1xOgB/3XszvdLdXXyOnunv2RAAmQAAmQAAmQAAmQAAmQAAmQAAmcDAE+oJ8MJdaQAAmQAAmQAAmQAAmQAAmQAAmQwBkmwAf0MwyY3ZMACZAACZAACZAACZAACZAACZDAyRCgB/1kKBWRmmN60H/aJFFzJ9m9PPSUjb1o2y1WVs+zsYk2VUN9LkpJ03OXq7yW9JVrIme3HiLof44feAPsUEii8vpNON/ms5QBsrf23qE3u5ugp3zckNa2LxPFq/YvKzPvFKdcTakr8di3TFHavUhMN8on2nEweh7DlA9xRJ8Yu/Kmynyr5lQXwf2WA8oY2n6i7ctE09S4AHdgfoIzR3N3bCm7ZqkFatVpynP6SDDWd0Ip0cpv3dupH3IAi5tvRF1gzuX7VR6tmyIhKq984rLGyesfVTunoV/1YR2nWOT7WNy43aUgLRGrUCdfjvrKDVZ/HWpjE13zOepbr0et1XTl699dCyvKqXPxtkib/0T5m3PUMcgvaWtNtLIG6pbDUe+KQz1abcsAx5O+oxnWVv476tyJqFed4ncJtvZOB2fu83BlZ/+oKVZf9xNqPa/55oOYX1EJdVM1x3tVp35jOayto45BGp5q0sm5RkzL6a6v29Pt1HmuNkXe22HXp7fTHQvBVE1xzkujK2SYv+2nxD4b+5Hadjms8u7QHWUmYXK58nW/iOkCw3goK7aM2o4NXndX5qUedA7C0DCs7Y87MlTwovtY3TzuUD7yvpFo9E9M/QT6LyX2hrBKcGCH+moMkBKCgxIkBOOOVs1tCX03kX+Anht5NWhJrY+aigROgQA96KcA6wyX6n+WnOHVsXsSIAESIAESIAESIAESIAESIAESIIGjEeAD+tGocBkJkAAJkAAJkAAJkAAJkAAJkAAJ/M4EivwD+tatW2X69OkSHx8vt956q1SrVk1KlPBeKvL+dO3a9aRw79u3Tz766CPp3r27tGjRQqpWrSqlS5f2/9+qVSsZNGiQbN68+YR9tW7dOrDuX7bhWP8/YWcsIAESIAESIAESIAESIAESIAESKFIEirwH3TwAH+vTpUsXGT9+/LHS/vLU1FS5+uqrJSdHGb9Uq5CQEHnttdckNjZWZaw0D+iff45eJ5vFKD9fTayK6V+ljulBz1okUR9F2T7vtaGJ8p+3une8jU00DO1Vsu0yzCt7nHyrfIT0nCOvoqb6yKuwSyGCJtfJgo7JVvJNoH6tmg98rpoHPUSWBGpNkCNo9E2U2ZCfrta1uLNzzpvKZFuekDnNCi8a/GJ70DIZpaSsUQtOIPs1xALXR3xXa8xV7Im6gNFTGYVLPYX1jv/VT6iLcvYttnyWul22UWNOhO2xtSb6QvXVRfmdZR3WSxWlXb9teZU7kZyiCq5S+lyltT+2rJNHS6oo26jIeU6tF9YJQ70RpagzS3qp/J3Otuzagsk9isO7lTHfWTFeWh3z9dWP3evtxLw4G7v5fMwlqHU9jJerXKLmvc5T69pdEfurkYF6vXOJ7qxQAZKNl+0GvXLMX0HLvHmgK6zAMSX04VZYRfba5o1X2fhoUVBTXDr/EGo9t3iTjzG/oSPqbGfsBV0rj2Nt/n9Qf9MYdVl1Tep51S/6Aes3OGMchDu2bL9KnWsHf8S2j0eiTlLX3K3qnzufvI31cq+j33NiE+Yp03leGBasVitXt7kCt8El2Fyc+5oEqxM5F/3qMT0WQOOVgvmsuCsh3z3J+bLwMiulNOTngoF+B+T0GCIDZLnKo3xJnoUFPeUZ0PHSBLRM+drq2MdszIgEToIAPegnAel3KrEjWfxOK/wjV1OnTh1p1KiRzJo166Q3Y9euXYGH86uuukratWsn5qHy3HPPlW3btsn777/vP5ibB/g///nPYh7UzW/qj/cx7d94443jlTBHAiRAAiRAAiRAAiRAAiRAAiRQzAgU+Qd082p78+bN/T81a9aUjIwMufDCC0/6MAcFBfm/FU9ISJBLLrmkQLubbrrJfyC/88475fDhw/5r8Onp6f6r7AWK/7egfPnycumllx4rzeUkQAIkQAIkQAIkQAIkQAIkQALFkECRf0AfPHjwbzqsUVFRYv4c73P77bfLXXfdJe+9956sW7dOli9fLpdf7rzLd7zGzJEACZAACZAACZAACZAACZAACZCAR6DIP6D/Xkc5Ojraf0A36zMP6WfVA7rxoTk2pjxlp13WdmkAY8f3MgKxCUp36AD6hMKZi/aEtSw46wgMkn/CNg8SfOukvyyCfAkZDzrp5UlW97ehHyn/ZE5nNY/uRDQS5wmaNRc/jz9oq/nUV7AC12d4MEl5Fp9Af2yIrIa2OWreXJG2kJc3lEHygQzMjy9n9SHHJGyWRihPeeq7ttZE9e9GXRklzPft12P+xv1WNy5rYxM9pzzGgsjk5wisr1gD9WdqW5ovx7y469MeVdef7jWbfwW2vca5Z/mZnzDvGUPhU+cmkPK+c4hrOZ5wU6VWLWroBNmJXRXwmD+ntuXObdhgcy2rKzqxWRqnvLbqbJAeaI+V/zrHz7R/Nt/8bT/5s2xsooxWVlf73sYmen4X6hDlUc9fj/l5rVFfp7b98DeYb9DZ6lUT8ZpamWO/Z0xV5f9rZou9qP6dIL0J45W+A3VlxfVZZz7x7Zdj7aXqgO7JwHwpvLXIPnVeb1eeczUsgITssf3lXWRjEy1U48s2VttSSh3PLe4147Wv7JzHpr9dNc3f9hPuYv7sYpsw0QPfgi4dAlIaoxQpjws++Qy1RCi9xdFo0/ZukU84SS98dxrqL1D2SZ4LC5Yon/hcqQB5SXduED3VRaOO51zBA1pPXGjYrVFj1B3iGVkLRdvEHtSL1VgolwreyJYJjp4wTUFMELyoMtW6RB6BddeMfSegH5EXArEJ3hI8OdbDIAFQSkECJPAHE9D//PqDN+fsXf3+/fZfSea1eH5IgARIgARIgARIgARIgARIgARI4FQI8EnyVGgdp9Ydnb1hw4bHqRRZs2aN74k3A8qVLVtWQkNDxbwm/+abb8rBgweP25ZJEiABEiABEiABEiABEiABEiCBokmAr7ifhuP6zTffyIwZM/yeGjdufNTB5NzVZGVlifnzy+fHH38U8+fjjz+WESNGyNSpU/3R5n/Jn+z/zTRqx/uczFztx2vPHAmQAAmQAAmQAAmQAAmQAAmQwJkjwAf038jWvNr+0EMP+SO4m66GDRt2zB7Nq+/XX3+9tGnTRi677DJ/qjYzPdvXX38tr7zyiqxevVpWrVolxs/+1VdfSd26dY/Z19ESZhq5X/Np6nnaNju+uK/XoRewvOMbb/RrVsA2xYbAIGkJ+1pV2oE+LH8HnSuOOdNkhtp0SPYSK7zoHlkG+oKJOBtD/9CbIZ+QWR+0PLUGdJbyMEpT61k/rCfsjkZ/Y05yFeirj2wAXVJGgh72gO3bT0xZCXlZ09bq8/9rYxMteRp1EPolNUJlWRRx7O1+R4uRkyz7NND/M/cEQj9w5+s2C3LCMR9SEbW+A5U9jHk9d/Eex2Bd/nqsHa1288+YFknBBXXuR/2t8suWU6dac2fdHfVLT+dhX2qaY9m1FfPPbUEt6ta9WunzVjj1KrexlpPzwpnKQ56Jl5gkevdv9/OJK0ysOGU7hz9MeYgr/Asb59+HWv6DusUFqPX04o3xcpfM2bY+dyl+z9jMkWiHyuPVL1Lp4mbQpB7agAv4xAe+Z8tzlVc6s7bNmahkCOpyL6Eusxv1MrWtmPVUhl1ygfN9apbiDNsiryjPeff3bVsTzbsD9eWpqDuqDlfvtflG939rhRdtVGMO1FkOaZFrlW6itBqjQH5UeYdjegzmwtW5J+XaY0HX+aBHtFIdOH37hR9Bucjtjp7oxCb8Sem4S2HB+hu+BB0Ruwh0mjgDGniZAdIa8iKHAjpNLg/EJvhW8P6eNhEhDumM10UJNVRUisyD/iKlOWj7qx+zFXY7TFEXteNTPVe6+6kjCLG+ODcLr3CMPOSWF4w7r7PLJta3MSMSIIFTJsAH9FNGhg3++te/ytL/fTl36dJFbrvtNixwlJkzvXJl9a9OL3/NNdfIX/7yF3n44YdlwoQJ/m/Xe/bs6c+x7jRnSAIkQAIkQAIkQAIkQAIkQAIkUIQJ8AH9Nxzc4cOHy2uvveb30LRpUxk7duxxezvaw/kvDUqXLu33tXjxYt+j/sEHH/ivvZ9/Pv509Zf6o/1/40bnV0JHKTCvuF95pfrx+lHquIgESIAESIAESIAESIAESIAESOD3J8AH9F/J3LyS3q9fP7/1xRdfLJ988omUL6/eqTzFvkuVKiUPPvig9OrVy29pBp77858LvNh5zF7NYHP8kAAJkAAJkAAJkAAJkAAJkAAJnJ0E+ID+K47bO++847+SbppecMEFMmfOHKlevfqv6Klgk0suuSSw0Awc93t8lnlW36god03o7XMzjEngeARi1KTbVyrP+T5xDJFeR+kyHLp7OnNqQD8rNwRiEySpuWclTpl1k5SBcvwoaC/fjQcdNAy9fnmPWEPmiEj0O/ZP/gDalpQg0MHK6N236p8gL/ejlAzHc25SoY5fT/+cb+c52Pga6xn3E3azj9St7Iz1bdGAOToa2/dw/NNdsKVIGi6YozyoSw5gXs8X3hutmvJBK6wv/7bV89Vc0ujU9PyyaAOVn2+xbU1U5TDqng5Sk1F2ednl1E+ehW3FYeJnlO87yhmzw+QXljl++0Z6HACn/cEN2La0+iopURrzixTToT9j/sWdqOcNQN36aqtTrrGxiVoqb/WuepiviFZdCV6G+cZoYZVDYZgPdfzwrlcWq46uSinvdoMjP8cOFB+6LxD6wRvK25/v3B4ecfibYrVbEqGOV9hA7DtMXReYPYpablf+g/KrV1D79ejKo7R3Fv0Lbz3y30gn6YXoeBZ51jnPxW6G36hOZWx7q/Kcf6LuLb3UC33PJWF7UdecbLg4UBBeEf3vBcbOKPNkoNYPDqqTs/w6zPfdgXoI7kxM3wWB/Nyqzklvlv7rvUDOD+ao+/XLV0FeH+4+MhfypQRHfqjgzMneV3nEb1M3l7TOjaCvkmqgjvHyEuQvU/19J6sgf6XsD+ggNSDJXvX9myY9ArUmuF2eB/2S9AVdUKgL3vGdx8gEKJ/bQR2DqfpkgXIKEij2BNStvtjzOCEAM9L6/fffL3l5eXLeeefJZ5995k+TdsKGJ1mQn69GiDnJdiwjARIgARIgARIgARIgARIgARI4uwnwAf0Ujp95GI+NjZVDhw75I7DPnj1b6tc/vT8FNKO4//KpXbv2LyH/TwIkQAIkQAIkQAIkQAIkQAIkUMQJ8AH9JA/wwoUL5fbbbxczrVrFihXl008/FTPn+en8mAf/cePGBbq89lr1vlkgw4AESIAESIAESIAESIAESIAESKCoEaAH/SSO6HLPP9a2bVvZs2ePPxDczJkzxYzafiqf5ORkufzyy486zZrp5+DBg/40a2vWrPG7bd++vfzaec1PZbtYSwKnk0BLQWfpMOkD3XeWv4AeJBlKu/WLIddHee1GiPKgSxjUR3R9BHSaMmDmSSjkI2R1QIelHgrEJpgjNUHXUD7BadIV8v2yR4IeFnUu6AIT8bovy2yahLWhnVCnYd9SrTfma01EvQHlc2jVlPyFNl/iMhubKP871CVCUN+qXiCaotb1idrtT37C9o3vtbqxylULtjk/Uuuqko355Gqooz9BLWq/Kzp++E7qZ61Je1TbI7flwMKFyg6rh0fQ86ZrA3wvZ1sWaHO88pQnXxdYrR80WYv6VeWn7q7M+1crH/FSxwo6R/nb378N+x6WilpdYiJlMb+9BepqM1Afaml11ctwrJMwm/KjjUoXkO1wyUE1dsMD6lyUB239UHVeV1Pnypg/21oTNVPHRE0fLW7ffkvHc+7rJk38/x3tr93Kk551KXIJ/RxbjVfbfkCdP/nqmO262bbP/9LGJipREvWTymE3fT3mw9RuNI7D/Eq1bRLh+M7TsVbUeSmNX8CC2XVQ1x+Peoq6IaShZ31uP+dE34tNJdaBYlJtVP5e1SC3HBSMSKkNWtrEoL7RypgnrBfeLB0afKdNelFC7jTQqVIJdPpozKf3wIEiOghy+9S5KKcNvwP6iui7CHRVqQ66pPKsZ8s2yHfwZlJ3P5lq3Sliv7Pnyna3VGRqJugCHnVxbg5eZYQsgfrq6jsXkp64RuxFOrhne0yHoxz0+HRYMOiHv4GWC1BSkcAfQaDIP6AvWLBA1q61/6LZvt3eNMzy8ePHA/euXbuCXrdundx8882yY8cOf/kzzzwjlSpVkhUrVkCdK2rUqCHmj/sx85ubOdLNn9atW4sZ+d38Jn737t2ybNkyMaPCr1692m9i2v7zn/90mzMmARIgARIgARIgARIgARIgARIo4gSK/AO6mafcPBwf7fPll1+K+eN+9AP6/PnzZevWrYGSJ554IhAfK0hISJBBgwYVSJuH8X//+9/+nwLJ/y2IiIiQSZMmyYUXXnisEi4nARIgARIgARIgARIgARIgARIoggSK/AN6YTlmffr0kSbea26LFi0SMxDctm3bJDs7W8455xypWbOmNPOmWunQoYPceef/s3ce8FVVWRffSeidAIKQYKQJBJAWmqKAoIKDigUYG02D4wyIOoD0DgLjyICjkhEUsdAEFEHHAgwdQzMQQQMYISC9JIRQk++dmy/vnLWC1CgY9vOH2evufc6993/Ly8s76542EhRE486ulZ3Q7VACFyAwUnC49WDBkSCfSzD0UFp2gXaH3B2KLA65+Ci8XZWM+hbye/vWA72xCs0J9GVZyMvtqaBLdLUjbeZlmqwoHmoLSgpoERzzPHIi9i3J7bD+oXWo3fIjNKR9zy1YewcyzjS8mm4foaRnn8LuAtzRnjSUm1wAmUbm96K/IxbciH2H34c6lqaQij3k5GlEaxU83EKjL0Vo2GIYD0unw02nmnziMP8o0NkOXziMhktH1cH8UZRCR0yiiHmK/Ruv1zJvTtvBclrXV3iJSAjtV9Bp29ZE3Wkodzc61TbgJSYRx237tPdtbKLFHVGn5kKdSMPpvy+G+RACE0BD4A8l2fqzTmyWHqO2ZfHWISeetm1NNIG2pVsU5o/g6F6Zu9/mSxHDPM5oaFPV+IStNVFbOpfeGI15eWwwLli8+PzazVJtETfni7fWxgUVcYSz9CyF+TELURdcY3UAXftC+1ncztDlNQqqadt6Ed7mJJOVIwzr2+Wyerpz3nlLt9AFf3qnLTZRoR6oT1dF/RydAIfs/dsrzFvB1tN5KhUL2JwvKrfAmf/Pp7e3boD5VZQXfG+SBfFQL3+2NxR36LUpWpiSALWxsh70f6Ul6MHdP0MtOBx7qXwE+cKOrezlPr0hlyR40b2SF/drdgoOgReZD+2DZTHoylIDdA2Z5dc3Cb45nJEz/ty5grvkG1jcj2xlIg9DnofI7xTrvwoZ1wxqmwq+EQ2mqesG34Q3m8HEGDpToQR+JwI5smo9Q4cO9bqqX7++NyQ8q/q90n7MEHYexn4pfZpv1Plb9Utpn1FbpUoVMf969KA3nYwC/akElIASUAJKQAkoASWgBJSAElAC1zWBLPuAh+QEygAAQABJREFUboZ0BwQEyJw5c65roLrzSkAJKAEloASUgBJQAkpACSgBJaAELoeAHYdzOa2dNsWKpY8hKluWxoI5NRoqASWgBJSAElACSkAJKAEloASUgBJQAucmEJDme507dWlLGzZsKN9++63Mnz9f7r333ktrrNW/C4GEhAT/1G07d+6UkJAQb73GF9+oUaPfZRt0JdmMQDCaEnsfmgk7OFpeBj1IxoEe4ptMxX2NEjsXTz8p6qaEp0Vr7dSawnjBAUEbezvzaJmC0XvM//2vZoKexRqy3Z/7RcL88bmC6VIaFw+tgPqm3ahzkHH0GPoMJZdjNA0kf/rZW7CvOs7URSZTCNNCPtPj5IduXh7rV2xxNPmd29Vxcr5wE0qJJZ0cjwu+pb/XViAMocttfSNC0t6mvOhJ8nEXTf+bsK3ijaH9FPIdg/8WT2MR6nsR2V1vJaZ7iVuZw3azTNSwDOqVji88jfrKR/uZk9adsgP7qkT5JUmYL0n9DXK4DHePva/ZbtrOIvSohSJoWZWtaPWUCg/hugPeQX04p9UH8tnYRP3RFixv0rR7AWexfuQNqJ+ibS1AltcjzrrD6XjHOkxMrzVjsG8hZ9qyJZi/vS3qtf0c4zemLlnVGVEX29CvV60iMc3qY2dfD5bAbCgdfwnHPF8z0XTMvs+F9e2pv9xhTn6RE5uwFmnaNvmU8gdy44IiU1C/GIE6/deb9GWr8N4vDUph7T0o5UPU1eNWwoKN9N4kfStDXkYmWF3R3RDf4oo2ZaLABXiuDJYjUHBG8OYy9NUHIC8vHQDd2blL30zPShlAKw+kdT0tuC0ptO6peV+CddVPWQF6tZRzNG6XkG+/pOCNbK/QySQFnL5MeII0vt/Lk84xyIul7aLwgp0eeQcWRNENALPXlXI/G1xXO34N7mxgVm1Tu3btxHzWnzFjRlZ1qf0oASWgBJSAElACSkAJKAEloASUgBK4bghk2Qf05557Tm699VZ57733fnVas+uGqu6oElACSkAJKAEloASUgBJQAkpACSiBSyRAY0QusbVTvmfPHjFzjnfp0kU6d+4sH3zwgTz22GNSo0YNKVq06AWnDlPvugNTQyWgBJSAElACSkAJKAEloASUgBK47ghkmQc9MDDQe4q7IWiGupsnul/sy9SeOUOGsYttrHUXTUA96BeNSgsvlsAIx+DoazO432fQ8jSZGEeQB264OF49X8sR0tPfvqcM98cmSBV8XMbwBg9CXlbFo+Z5V915cU3lC1S+0OoRq/5rhS/qJ8+Blve/Qp1rH+qTH6PO3Rh1C1p5Hps+ihZEKYyIJZl8wvlt0/RoMy4IJ2832cLlk1hb/yR5UKcn2pwXxaFO64g6YTnqUKqPxkcOiOsLbnEa24o7R7ovFUq20Z1oC5WlZEFtTO1lP/afVNBqnuf6c7QsSkuyLPalt6t6W21fJlpRCfXfaKzaXMeLX5Hmnj58FtsWdc4NL0P7FRmG9aEo5QnypIf91RZ8TTbe5jQJSwB5ysfbpl60k/SLdO4W34EFOZ3nJRwmP3OBPVh7nDzmiVRfnOoDU7F9bvL6pn3i5Is4sS9MugV1HtqPXNQXn5tpMdg+7R7U69agtxezpI7gyuscbQ4FreiYvEfPOyhO10XAfufe024p9CXTaqNusQ51PMpMis7VdnSduA7lnV9S65qkg0hzfY5JWHC8Kuq36IT5zkmPw5OjdVe8UcXShO4dBB+AsIA85+H0oI9oye2sTGSj82yV+oInx73U9xf0wIsHyfc9UvBkTaL30G40j/q3zrZ8T/v1nMTDduag57YECP7eHifBUL9A0Nz9oOCN8qBzky0l90LbEk7OJLYJvlHtFDzPV2d6uAp0J1KjGi6IsdfNcFkFuRTy4o+Qv0NehSWgHnTL4mpHObJyA9znzblxVq5D+1ICSkAJKAEloASUgBJQAkpACSgBJZAdCWTZB/R33qHHtWZHWrpPSkAJKAEloASUgBJQAkpACSgBJaAEfiMCWfYBvUOHDr/RJmq3SkAJKAEloASUgBJQAkpACSgBJaAEsj+BLPuAnv1R6R4qASUggt7spv26AZTBsgB0a3kX9Cj5BXSfMehTk0FWT0z5Fmrvk+Ogh676GvRMQTf2RiFTclcoFxlpPWuU8bnd0e8eLCWg5NCH5UDLY++hzv0g6uRxoDeiZVGOOHfiKeS1hoY+kY9sonITVdxMmmR70g84vvPPP6akk/Myjm/b6ACytEbnofZo5ZQIqh92l62fQtPgPuUaWH1lvch7u7yhbWsinrM7lCyp2/dgfU5nW9m3LWFYy1x2PIz5wpVRr0hGLeTVrfiNzf/S1MYmKoL2WJEmmI8rjro7SvnHLlywrRjqNW9b3eKQjU2U9j7qjfT8gvDvMR9wL+pe+1EfLYLa5bwBbcFyOx0ffubANvJa59mCfZ8i338acTx9i63PudbGJir4Lmq5HXXaUdQbyLp9nNb9I5aLzJ1rlzxI94a6dW3OF9Vxzg2TSGgOaXHnNTcZnts8vjHWr8xjL7qGpzDHN5Nh9HyLRNI81/x7aEmWidR9ogvibkwmx6POj7d7KfRnzCfGdsEF309C3f1d1DncC+ss5OY9QpAWQlrSDn0GC1b3aIR63BnQQl5uGWTTq/NT217YtrpE22Jf1IcmiC8p2yGfJHlATxjg7qcvNcydfxwvwNHkSRfhN5tj0Hdmgdtemra1nOOfH8I3UZoHXYRuLj1o3vNxvHZc97CYz6Egxfn9IImeGVBEgqBWhRL4IxAI/CNspG6jElACSkAJKAEloASUgBJQAkpACSiB7E7A+d4m63Y1NTVVFi9eLCtXrhQz/drx48dl+PDhcuONN/pXcurUKe/J7UFBQZI7N32d5K/SQAkoASWgBJSAElACSkAJKAEloASUwPVBIMs/oM+fP1+6d+8u8fHxQPCll16CD+iTJk2Sv/3tb1KgQAHZvXu35M+fH+pVKAEloASUgBJQAkpACSgBJaAElIASuJ4IZNk86Aba22+/LV27dvXmQTe6ePHicuDAAW9O9I0bN0rVqnbeSvMNuvlG/Yhvzs8pU6bIE088YZro6zckoPOg/4Zws1PXM17z7027tuhhq+74vExRpvlFQ9r423rBUyhlZDwsKCdoPN3etIE/P2TRfH9sgkFD7wNNdneRVeyfS8D6HpVRsxq31VlS3Il94SRyAxWvBflC94OUxJmjcEGOPqALEaZvHG9oGPmXg8irW7QudCVJy1Dn3496BU0XG4ZWfgnZZOvXUN8P5bI5E+2Yjboa+cJj3w6GgvVPoMm55kBIy6YhVlffa2MvIuRfhWK+cwDqneR3P4Wnluwqi/U3r3d0ISc2IR2Dr9BGKjWPYP0GvEzkrnWYTyMLZJBzKu50jr1pFUrbLeQDnkJ/y+5A7b/KietuQZzkRye/7kVHiByP+CfovOTjPnIvpOVYHtR7SNf9AvNbm1ldIcbGXkRMJ7TCfLf3UEsI6j21UW8lS+vtM5w8tRXys299zKn1heXp2QsH8bSW4v2wXjqSnmX1mbE2NtGZH1DnLY/6K7oOGv2M+fx07p3egfmc7rMY6PkEEoa1cgJ1OJ17G+iY5XgL6wNeRg12abydC9mXRcpR23lf0YIWqOm8lxz3YH7LG1bT9dd32Mc254uO0wU/7jV84yr5Ahrk9/LGtqL3C/f8qAGrEpmKul3KElgwXUqDLicHQN8PF7D4ZgsvDPmh4x+wujud2HLG5kzUA98c+o2bA/kd5H/fJfUh34i2zZ03fbrY3/dNoydlCrSdKl1A95fFoFkMz3Sy1oSSl8VeZIuI4epHGkGtzKKLDLPXtdJ50K+dw0+3/svfsK1bt8pf//pXr4NmzZrJ999/L/v27fvVDnPlyiUPP/yw92H+yy+//NU6TSgBJaAElIASUAJKQAkoASWgBJSAErgeCGTZB/Rx48bJ6dOnJTw8XBYsWCCVK1e+IL/GjdOfpLlhw4YL1mqBElACSkAJKAEloASUgBJQAkpACSiB7Ewgyz6gf/PNN95Q9h49eoj5dvxiXuXLpw8z2bFjx8WUa40SUAJKQAkoASWgBJSAElACSkAJKIFsSyDLPOjmYW8pKSkSHR0ttWtbM1hgYOA5PeiG6HfffSe1atWSHDlyiPGk6+u3JaAe9N+W7x+196bSCjb9brnfr/vIs/74XMEIcXx+voJ+gt6u1jTv+TzB+WfrywrotrlYI/IIqQ45aVoB9IhF/wXdrwZ5EDtBWjq/sBgW5Ke5zieAKXIP1IrgumXGGsonog75C+joOiAl4gvUaY7/9gxa62RPGNbmQcuhPIVTtsvnTl+m5Zwi2L4A1bse5XZYKsOP4YKKq1HPuQv1NJQynd1LJ6jA4TKe/K4TqTSW/45L83sLee97hmEHY7eh3nyj1VXo8PUsZXMm4rZT8DSXDmexXnaiTqI/hR9xjknhJKzlecufyIP5WPby0rYL9ZeGNlMJyOH05/A3S0/HOjlfuKEy6hn0t/cX6Vw7kBvrzwSgruRcVvmJcRzZY4+52+nrpuZC7GttJJ0wn3wCBbWC8IEKgd/bdLXHbGyiL4hhcWc7Tf4AbWvIFrPUvlLQmit5G9qcF/3i6IpObELq+/hQzOdD+7N8/Sjm69lbppcIpF+lCjqYwoOw7btUW5dua6sisJ6fj3FjPsz3pPOjkZNuk+wIE9J+ZZqquibVR5OmYySBXbEgj3MHOT0Tc1Nqg262YBnoxWCeF0ltgOeSvIgedml7C7SXinTRudm4E67yxXQy9aAdH0cXWUgRbJ9AF06wc+G4XnjTagQ2lX5bcUHeCqhT6A1AEjCfl24QzrkdGIMnU2owMUx3xNr+hsXb2EQjwkC37rcUdLLgzWVh3tttnk4FGUc3bFupERFQDzoBuYqSfm24/C0JCEi/WNLS6Le/83S5f3/6b1SFChU6T5WmlIASUAJKQAkoASWgBJSAElACSkAJZH8CWfYBvXTp0h6tH3/88aKp/e9///Nqw8LCLrqNFioBJaAElIASUAJKQAkoASWgBJSAEsiOBLLsA/odd9zhPZH9ww8/vChOZvq1iRMnesPfzVPf9aUElIASUAJKQAkoASWgBJSAElACSuB6JpBlHnTjPa9fv773gdvMh96pUyeP67k86MYL/dBDD8maNWs8/7mZkq1CBfK+XM9H5Tfad/Wg/0Zg/2Dd9pdXYYvzS37Qa2WlX89y/OhmYTNBT1qsoOlwr7iT7oqMkjh/Xyb4jxQE/SjNq15QrClyNW3XvAHoX5dh6OUbIekjcjJW0G/EPRlh+k/2CQ9EE+NQ2eSvHzi0uT/2AvY7F9qB+YCmqHNNQl26C+jEMJCyq6jVk8nXOTje5kyUbztqIRthwN2YP0Xez1zEYWUVW9/wJxubaEol1M3Iqxv6BeYLtUU9HKV0t4fXy7R0Tp/PCdlXnbFxi42o5SBp2tZMnlY8XUQcK2c7Jza9TqfDu9Lxq9NaPdkwBZem4mkvR8Iwvzev1VXY10+nUiuyqPYn2+fY5bYvLypFGi9vkc0235PW5bh2vaJ4YrwNL18pftL2ZaIc5HDLfxrzwc51FIkpmUge8y0NsKA8nZvsrU8+gPVrg1HXcfy4o5ztMFXDiXEuOv7HiHmBp7Fv6UG6N+mejqbjs49uUyWPOrW+MNnZbpPJH4j5OWVRV8NbtMBzI8Kw9jAdT+c25BU2wtu5rCAu/KyF47Rv+fI461vixCbk63XrACwIGIaaz2M6vsL3B7f+jH1P8zr9DHds0Kx5sK4TNCH86BqPQl7+hJIs6yJRTj6BDgj1LQ2KO8UirVeh13qeODdor9KFahbQG4AU8Pc3SvCi6QPPWRHfrOY44rWJ7PK3NcHoENzvJxNehXxFuRW0693fTzfgfaT3Cr7RNZB/Ql93SWvQI6QhaJHbUL8TbXWnCBtrdEkE1IN+Sbh+02K61V/+uiIiIuTZZ5/1vkV/+umn5dFHH5UZM2b4O4yJiZHp06dLly5d5JZbbpG1a9d6H+Zfeukl/XDup6SBElACSkAJKAEloASUgBJQAkpACVyvBHJk5Y5PmDBBkpOTZerUqTJ79mzvX8bD4x5//HH/qjIeJNexY0cZOXKkf7kGSkAJKAEloASUgBJQAkpACSgBJaAErlcCWfYNugEYFBQkU6ZMkZkzZ3rTp5kP4uf6V7VqVTFe9cmTJ3vfol+v8HW/lYASUAJKQAkoASWgBJSAElACSkAJZBDIMg96Rofuz927d3s+83379snZs2elWLFi3gf38uXLu2Ua/04E1IP+O4G+2qt5ZBtuwXyUQ1O+hgUDpStod170RbIAciKxoNvRZLZnZTHkq0sd0IPkFtAiaMAcLv/25+cJTr+YX1L9OROEyRnQJSi/Ub6E/EHy00eTf7609PLXJ1QkQyx5VuV5u51eo/bon5OZ6NWTO1/y9+0FG1Eerm51jpI2NlGBKagdi6GX2Pcw5reTz7vhesxLTdS/HLf6Rq4lu+PKurbWRA35T7w8t3ES1rNtsJHjE13xKdU6OS9TEPNT6qHu8A6dW3V+gIKlVUHKdmf8WH9MCXvnd1B+ADFulwsLph9E3bIY6vlrrf6mto1N1DkAdSRKeTkGF+QMQr2/NOp44hjh1tPxiXOYmF7CtmNfPC96BKalEHFI/AYLTpaxOtduG3vREdJzST+CetsDqMvTMwxkGuaPvG91/v02NlHOn1HTozbkQAvMJ5H/+Wa+RmnbtzjrrvwF9pXYCPXZnKiPEtOwaMzTbRCerWAqTzvHP1c4tv2Jjv8bdI11du4NpmV9tA3LBOxO+HEInzv5lk5swlDSA07Qgo9JVyZN1wG9XfjM+049PQtB6BqR1+k98wF8r+ndFTdm9IzCTue+8HBz1MucG+O9P2JuRyXUk1FKXDwtIJk3DBcMRCml7YVVsAN6ypMeoSvWeRaG18tUPgj4His0D3p9wQckrA6xJ/PLCbNgw16Re0HL2w4jk3kaOY2QvVD/iuBFlyT8xAT8XQIaq7hoAupBv2hUv3khvR1n7frM1Gv3339/1naqvSkBJaAElIASUAJKQAkoASWgBJSAEsiGBOhPWNlwD3WXlIASUAJKQAkoASWgBJSAElACSkAJ/AEI/GbfoJ8+fVrWrVsnmzZtkkOH0ofBBAcHS7Vq1aR27dqSMyeN4/oDwNJNVAJXg0BreRdWO086gq4vU0HfMGsp6PI01cpxmt5EKuLwvkVxm/ztu8lD/tgEEyrmAR0edwr0wKY43u6HRSshzyJQpsOi/qOcMdR94iHXW7aDHv1IM9DSMhF1l3Kox4ShtiPaveUJU5xxqLloCPvpWGjbrv1/QU9/G4ffSWG8v222M9947arQDDFFnPGeuCaRE+FrYF2yYQPqNTVBN7jTYejLpNIhCEDkIk73aTSMOICGkYcQYlixT0yhmXCmUUFfGjF5wpmWq0UYFRch7QyPNpkOiygfhkPaKSuN7WmdnnL6HxaG1R1iUNPsgcLTKpWlYchyFtu/QUOJn61j81FUu9RhYqpuxZGekrOsbetFdExKrMD8YRrV6u4LTy/HiCoWwr72J6Pe6Q6X96VCaPh2gLOfpmUJ5xgm0HDqNOqr0Fxc11a63EvRsPS0/Vj/TSfUzT+yOuAxG3sRDf1OI4b9aDTtC8TBvYa8/uKw/zMBVqfSbalwCZszURKOSpaw7zAv8agDOqBefxr1/c4tO5H6HuYcD9Oqz0Fsy1PVHYjFfK5SqHkGMXcqw6i1VLt7Hi4o3Zo0SuH2RcdgQR26oe9w0vgW5/PmODlfWL8VHvDWC/CiCqDx883a4lj/poLvBwOebOlfQb/HEdoIev/tTNOkrZG3/G1NENMU76K9F82E/O4+7o6KlJGb/PlXpIk/NkH9Wbif+yUQ8vkFbz6P0BD272ma1E/lr9B+eMJYvw6g2uGyzJ8zQf+nse0o2u+jgjfNJHkO2qtQAtmdQJZ/QD927JgMGzZMJk2aJIcPHz4nv6JFi3rTrfXv318KFix4zhpdqASUgBJQAkpACSgBJaAElIASUAJK4HoigH8+u8I937x5s4SHh8s//vEP71vzcz3B3Swz36ibmurVq8sPP5z/W48r3CRtrgSUgBJQAkpACSgBJaAElIASUAJK4A9BIMu+QT9y5Ig0b95cfvnlF2/HzVD2Dh06SL169aRkyZLedGvmae7R0dHeVGwbN26UHTt2eG3MMPjChempmH8IfLqRSkAJKAEloASUgBJQAkpACSgBJaAEsoZAlk2z1qdPHxk9erQ3r/nQoUOlb9++vzrHufkWfdSoUWKGuAcEBEjv3r1l5MiRWbNH2suvEtBp1n4VzVVPVJSqsA2PSaRfD6EJaVrR/EHlaaqyYjC/jEiQ7z/3dVrQN55Lcrtp36w91ig8WvpALkUcI6cvM1T2QD6VTIg5BP8G2F/QtDhM0v+gl9HJAGmcEfp+HnFiEx5Anbcm6IIp0aDvEXeSH5Hjvv/cV02JcKWMfPVhq0ui311O/c3mTJSfRv6cegjymx+aDbrK1yBFiqFOvd3qZBt60Q9rHJM45Tw5bhwsrfOX90ELGYuPdcV0gdWoQd0JStYcRV3qBOrQ9MeN2IVovxSyX4q4fmrHK+t1wJ5TtCRmmk5Kfgm26zXRI7QxOIuPSLhTjpeISLyT84WNKqNe8S1qmrFP6HKWObmwvtoxqyvayy19IfmE6ZKS/eVsWxMtI3+0dYGm19HhlkqOR3kPPipB3O0yrSviJZPJe78zfRX+/88hz/pyfyY9cKefS6bjmZ8OXxyN7ytJ594u2u/KzWll/VHHu7cWTElxcuO95J6XvtqJ1anBCNIbSONtTo48aPNFttjYRMfCUOci5tPo3HtqIdZPaIY6FKUUSbULmhLT9XT91tpna88VHaZrtCgd77O0bwtvtb3kQHuzTfx/1BRt376Hb1AJvm1lvv7n05l+YrHtgJ9P8XNtmzPRmQ9Qd6cLtjumM6nRzgVtkgMK2JLwGBubKLYGar7P8bk2G8vlWdIvHYEFJcXe6PbSDbczvYdOfrIJtKW3RJHuCZh/NQR0v5fmgM7t+M4HNqALchUyqi/IZZfgBdtVekLfAybdBlq61EKtKksI6DRrWYIxSzqh2/Xl9zl37lzvw3a7du2kX79+v/rh3KzBfCg3H+BNrfmwPmcOXuSXvxXaUgkoASWgBJSAElACSkAJKAEloASUwB+TQJZ9QP/55/RHqpph7Rf76tixo1ea0fZi22mdElACSkAJKAEloASUgBJQAkpACSiB7EYgyz6gZzyN/YYbbrhoRhm1BQo4w4EuurUWKgEloASUgBJQAkpACSgBJaAElIASyD4EcmTVrpgnsi9atEji4uKkVq2L84aYWvMybfWlBP7YBL7BzZ8Rj7ptE9RkDG5M3rCljnd7iOyCtmdpEtez5NXeIWjODKX5RIeGPAD9ST+U8hfH05Z3IyYrohwbkwILkqQaaJ/DEvWACqAHxNcELVOddfdGv5uMLoK1jr/RJJJaR0B+Vj+6D4Xg7W7BI1AuUsAxazZpgcmvycD6MHrQQ4PQKFjlS2wud6A+G4/atePGXchzjk1FevSAJVvrvg+a7dVs9TwTdB6P+zLoSoqfrAsLQun0OF4K0pLvLtSLyNr5gPMn4sSDWCs5Sd9Lmn3gNx7CAt5R9rSucsrZ30o20RV4CUrPek5bX/gY9V1rP+arFUa9wv2b9A7M+SYyhldPOu03OaepKSx+BsplNEopQPnPHB9x89NY3N3dLl8qmo7XCed4mZZbSdeidU3ES07GF7Pry59sYxNtptqQBMzndi8SX6osbXuvFVjfmbzck/PZ/DQbetEOGvg3sSMV3Ij6SAPURei8P50f83scrjfRveDIWqxl9Ug8LgmojZo955GYlgEHnAV0idQq6ORM6JwbRm52ttvooni7lzg63kHEAd566LwlC7KMJy7dZ75mVmlfp16wsYmqo/Q9KYAXWM3rPrvO5s4VpWzFpaPDQNcXvPmsFjooVcrb+n3bbGyiYe4BEelNIEYfagb1Q+Lmgx7U/z7QBSUOdA856tc/Ce7nd4I3tqFTv/bXmiBt6knQu2Qn6LIvhYFeIfgAkwWRr/jz7aKW+GMTTJdg0LfSfq+W9FG4GUUD6Nk76jnPIKM/rxcC9PZ6+bvdtWtXz08+zvfAotRUvhtm7tfUvPbaa54fPTKS31Iy1+sSJaAElIASUAJKQAkoASWgBJSAElAC2ZlAln1Af/TRR6VTp06yatUqefDBB2XPnj2/ym3v3r3y0EMPyerVq8X40M3D4vSlBJSAElACSkAJKAEloASUgBJQAkrgeiZAg8oujOK999771aI777xTzJzmn332mZQrV07uvvtuiYiIEOM1N09uNx/MzTzoX375pZw8edLLmTamz6eeeupX+9WEElACSkAJKAEloASUgBJQAkpACSiB7E7gkudBDwwMPO8UahnAzPRp5kP5uV6cM3VnzpCZ6VwNddkVEdB50K8I3/kb90Cf2Yhx/4X6fvIc6AuJgs5c50nSHspr0GSle+VFyJ+W7qBzynjQLLrSXORD5RanJMyJRUbJUtB9yA/Pc5uurtEI6iUE5aAF82DBkInWX9e5K3rYJvdoArUybgPoEbIXdDL531dJScgvfKcqaAk4zz0ozwKsrTIMNftIyYPari2WP0suoCbjbP7Hl2xsoqRL9aTTvOh53n8fOjxxnv7q9EGPOZ0avomxoSvpOhs1OhZF/kk+4PqOD9i0TPzRaU8+byeTHm6nJSVIky84/AbMx858Fxe07mj1IhuaKLIl6qh9qCWINB1v2YL50JqoZzj+6YYHMcdqJzHjfEmCHuT0bWq3V8AW8c627qa36A50DFqWwbYL6DIIaI55ng+ex8Y9nWbrZ9K6O9F218ZbqqTSeL+BlWxfJqqGUjrQcwXS5joFJ5zYF379JOriaMWVUlR/IDfWl7W2Xy/xLd5qpIFzjDbdiG3rxaJe3+12WHDTp8tA7yGfeHk6Pzo5jE3DaR/a5qdq29hEuYlRKh2DE0WwflB51C8eQc0qwdm273NhlpBJ90TMy3LSdD3zPOmnaFtzOYM4w+/CvmLp3BK+l8z7ChvsLIea95vOF3HPjzqLse27TVAvoJPrgx2Y/4BO9AXoYS8nW6F+e40GVqfY8JxRMVq6yoHmSxUkD3pSqwhssCAedCt5y68XyBP+OD3AE7evfAf5kdILtIqrQ0DnQb863M+11hznWnihZeYD9sW8zld3vtzF9K01SkAJKAEloASUgBJQAkpACSgBJaAEshOBS/6A/tNPP2Wn/dd9UQJKQAkoASWgBJSAElACSkAJKAElcE0QuOQP6DfddNM1seG6EUpACSgBJaAElIASUAJKQAkoASWgBLITgUv+gJ6ddl73RQlcLIHq8j6UbiTTWsFx0ZBPFDTUDZJxkB8iPUA3kymgF1Z0vF5xP0Au5hG8bEvO+hbyPWUY6D6D6oFm797Q0eSBi3S8YlGYmyuOgdX0+hpOlLv6EHnOl+GqhbyAQ1a1xoKum/x68oe4XyMeQ6Nfv6H3+GtNMGngKtARkhd0fiFrzu5gyMuNrazOj8zD29qUifDoiuxkD7pjAzT1O83/nFees44woVNf6S+Y21IXfeHJX3+NBYMHg67zKkHfAGnhTXWzP5H1kq2ZBSa61SLsG346J+bvdjyoJoNnuUgb51STcGwrhVA3aoqaphaXkXiqSq0lWC/lOsKCns66x9aCFM/AK8Ke0zisl32kb0O9E09laVjG5ns6sVk61vXl+3ToSltrov1NUMeWR101HnUzvERl3WGbb3HIxl50EDV70A80xPxp12vrS71Jl9hf6dwLck6o/XRulCiKfUsp1FOKoB6zAPWEVqiTd6OWNVYHDLexFx1HfYjOpaJol5WHm2H98o2o6Y4rs8vaPDmMpWFVmzPRobl4/e4lxtXexPpTm1FH7UENzwlgz3ES1gbyfakg5tcTlxvJy92uDtZPj3U0nadC55rg7VskleZB3/OC05kvLID5XAl0Mp+8218fG9/YH3sBnVsyszbmU4uDrt9nBegUeq5LS4mE/Oi8zglSsQnkhM57kQTI93vchSYyokclyJdbgJ7zZ2CyeZE+Me5FFwJt28n3oKfHlQZdXfaDbkM3ttcW4O85/HycSjLI3/4gvUuulgf8ORP8KB1Ad5O3QU+Qp0GrUALXG4HA622HdX+VgBJQAkpACSgBJaAElIASUAJKQAlciwT0A/q1eFR0m5SAElACSkAJKAEloASUgBJQAkrguiOQ5R/QN2/eLC+88ILU9Q3LDA4Olpw5c0pQUNB5/+XIkeO6A687rASUgBJQAkpACSgBJaAElIASUAJKwCVwyfOgu405fuWVV2TgwIFy9uxZuZRp1Mw86KaNvn5bAjoP+qXyne9v0FT+7Y9NsEjIAAlZkSdp3vOp8gZUNBU0TDYlf1agnPHXb5Bv/bEJagj6vEcJevNSgtEQOfDQJ9B+qNxJ2jFn+jIBctqfH9AbJ4QuORq3Za+Qj1vQuydChsjgyv6+TdDt0CLQE+RmR5Ph0cl44Qw06/Zoi0bhcTIEWtSXqaBXj0eOUnKdzQeQyzyNDNEBp2ytidIeR30vSvn0IVgQ3XY26JW5rJxmQy9a/iUumHA36q5bUP94E+pw8jzSEYGpzmuTx5htgO07Y9/Tea7iEpjvifZJGfsR5uGZBIvPkzOpuaFYkI+c/UGYFvIsC83xLU859auc2ITk1W1UGfMr8FQTice80J++F1XDfFPHB+6bbBhe+5NBSu2iqNnP3pMMzzuwXKZTfy2dx0jQWZ3pWQm8n+2IaQ97q/DWeg89g+Doh7gxAe7jFIgh78fYtdiW/c3T6Ba89Q6s57nKzwTY/O2f2tiLyJO8qRbm1+HjLOQpvA2KbML6VnSdTHMuukLVsfY2tP3Kf+kAFiArbgp50PMSp/faYv9VnVtVBWKen9Z9jDgUjcW+ltEts/EhzH9F138Lx+O+khjyczhi8mBfhFTGxmOer+d2t2F+unO9R5bBXNQk1FKONN1aJO94KGjdFq+cxYIbnzQgwtYPs+/l3sKJgTZnot2kw+mm2hZ3rJksg/YL3QeYmEyw84VXDyiVIQPnw4IpdKN7kjzos+n9PMz5vcR09DP9XhSTd5q//0Ep8/yxCYZIRdAyoDLqYeVRq7oqBHQe9KuC/Zwrda7kc+YveuHMmTOlb9++Xn1gYKA0btxYbr31VilSpIgYrS8loASUgBJQAkpACSgBJaAElIASUAJK4NcJZNkH9H/961/eWsqUKSMLFiyQ6tXpz8S/vg2aUQJKQAkoASWgBJSAElACSkAJKAElcN0TyLKvtmNiYsQMVR82bJh+OL/uTysFoASUgBJQAkpACSgBJaAElIASUAKXSiDLPOjFihWTI0eOyNq1a6VmzZqXuh1a/zsQUA/6+SH3llegYPQU6/0a1uE7yCVLMuhdPjeW+6osaDoNJFNqH0GTY3/ylf1LrGkuSaq4XUt/+Rr0cMHrrb7shvxqqQpaahQBPTDmE9BDxe639CVP+UIoNZOZ4usZlGSf95n3j2HBmAKow760um0zG5uoBw34ScC0zKIFE0tjwTL6e+Tt5HlzLc6IUCRfV+gr+mGcEPyuXJCWxCWoJSdpx5vpZY44+TpObELHM2zk2T3m//YVhIc/05zd0eRBvzXOtjVRk3Cr2e+e0MDmTBRKntPwMMzH7kAdTZ5Wx5npFYY63H4mL21gQezrvBO4m1K8TIQuUck077JjgYwOw3VFsAeVt2UL1meaw909nr7ScDrVlu2z7deUsLGJejheaaOdq9FImTjD++H/X1nyHL+X6k95wQ467V1PcmU6lwqSJzmSzsWW2LW02YYLQmk/Y3dh/l57W8u0X2PpmmlJnvLPaV3jaV3LcVU0C7PIDOfcdOclN8060PHiaybiOHVOMrQILth5CvUc5zy/h/YjH+1HGnnrYR5zX7eHaVuL5sF1tUR7tLhcPqFzoynNoX6c+soXhn3zI0V4rnr2hfO9C3rja+o0ZEWmkS5Huizpxe4N3Jdrv9MWLLahF/G646htbrpTPfkSdUCggukEeMSWd4ui56xUbGqTJnoRZbO/LIMFCyUEdDk6CB3oxvY/Keyvj5bc/tgEScG4X/UPrYD8aqkHWshzXkM6Qv5B+TNoVyTKUVf6nlaD78eD6SEhqdIO6lVcHQLqQb863M+1VnrrPlfJxS2rVKmSV3jw4MGLa6BVSkAJKAEloASUgBJQAkpACSgBJaAElICfQJZ9QO/QoYP35Pa5c+f6O9dACSgBJaAElIASUAJKQAkoASWgBJSAErg4Aln2Ab1Lly7ek9ujoqJk3rx5F7d2rVICSkAJKAEloASUgBJQAkpACSgBJaAEPAJZ5kE3vRkPuvkmff78+dK+fXtp27atmKHv+fLluyDusmXZUHTBJlpwiQTUg36JwEKsWfDlhFnQOIegH3qdrIL8FnkQdGdB4+BZOQv5BVIU9Ooajfy6esxKf2yCh8lztk1+gHwl8pwPkMaQf1LQP32EfGf1HfPudMfPZjrZJ0HQV3dxJ3QW6Sc4CfdA2rZlNO/qfupvY3BD2/9b0TY2UVs0GdeXGMjHCPrEU/JuhHxgyhrQqVOng5YTi63O6RizzdLmS23ORD+ilHjUPTuhHnsCtXxEuryj2d98n5MzYTLqTHONx2NewkhTvpCTz+RRnUNtW6COJL9rFO8nnvYi5M0t5Nz2M/n22Q75AflES+zEjcFTU3h6YPkSzw854VwHj2NXQl77TIbmUheoz0l5sqy6c58XcvzJplUiMeJtSaM5vOdG4rqIinR7CPMBbzm6iBP7wqO034WDMb8Rb1tyhPazAE35XIPO5e0VbH8VvrSxiVrRdrrzWJv8z7Qt7fOapfYVm2hjE7Wjc7N/is2XovO0OHmxk/A2JmdpP4vSMUubbPs2UcoDqPM5nuc0YiIHsPY94oDZTFOuy5jnsOLwMNRFl1sdQLe1/cT0AXwbksWxtq2J9tIlGDoX80lNUB9w+gtbjzmyNwu9pUrAHVQ/nzRtS3gNzMe6x5icl9ElsDYCpchiWrCb3oty4LNU6j+Jzz9Z/Voj28F+G3pRTTrx4+7Ggpu2o36Cfn8eUwrzs1HKi85DKtpS3/R7iLyDF0mDTn+HzvJJZ9ARdAMvQr/H9HHnOg8Og7blDuHvSNuFb7pQruIqEVAP+lUCf47V4qeMcxRcyiIz53n37t1l1apV8tFHH3n/Lqa9efr7mTP0zn4xDbVGCSgBJaAElIASUAJKQAkoASWgBJRANiGQZUPcDY8ePXrI3XffLQcOHPD86GlpaRf9M5vw1N1QAkpACSgBJaAElIASUAJKQAkoASVwWQSybIj7+++/L0899ZS3EYUKFZI2bdpIjRo1xHyrHhh44b8DmKHx+vptCegQ9yvh+w02HhUGelSfr0D3GdoC9JMDXwU9VXAMZCt5G/ILxA41q0/jqVcLjeWTrdC2JA1DyzwMvTzUixRHHemMe43ag7kZMaC7tcWxnyVoyNvAAc2hPnAYDTMPqQv51glL/XpeSGN/7AUNUMosHj+NA4IGCU5vM+SDW7CD5AdRlz7p19F4+CQi1Z9KD+JJ0yjE9Tdg/kgu1E1pGHNPZwh0NSyVMaR5KG8jHKVI1SJTjuGicni6SJB7e66MteG03bE05L1RG6xfsQ21LMIxtDvbHoKCUHc0J5YKuSEkGk81ueBUaHQMMk0BddZuyviyNjZR90TU4hwfL7Ob8lxPQ4MlCesXPW31Ay5/32I+/jQwX0qn2bYmqrcXdU8aARuFaZiGb2V+TDYkxjRaWgbQeYutMw+RD6T6XMdti3V0G2pIHOhWIuK0Nb1szG37MtEEGvI+gI7JQuc6qe0Mdzdtq7vnoVkQav5nX9F0/I/hrUaK21uH16g6nubgkFhd2vZrolU0rd4ATMv+w7igxFHUx53z2GReJa7TnPLYGEf4wkY1UK/gWyoN/ReHodfSeaswerMzpN3oynPN/9NfqVUzovSfyTTM/CTdQ0t8HIwNGhLUTUQqL52tyU7zOk5swjjSYaRp22Q+vXf8vAAbEAd5YZM/3448KtMr3uHPmaBH3HugJ9F8kcmCJ0i4nIb6JuKO5ffNCOp4JsbKzVCbWgPfb1vFvAz5fL7W7mu2tHKlb4rXXaCH8hxxTnYoWelyCt64+sizTrWG1woBHeJ+rRyJTK6fy9+wCRMmeI0rV64sixYtkpIlS15+Z9pSCSgBJaAElIASUAJKQAkoASWgBJTAdUaA/2Z92bu/ZcsWMV7ywYMH64fzy6aoDZWAElACSkAJKAEloASUgBJQAkrgeiWQZR/Qc+ZMHxtnntquLyWgBJSAElACSkAJKAEloASUgBJQAkrg0giQk+rSGrvVZmj7ypUrZc+ePe5ijZVANiGAswwU7IPTrvSRG2E/mw7sBvqUPApa5B7Q9eRfoEuJ9bBVJM/ZfidnGuUnbxd71paTF3s41X9D6y4Q1da/LfOkuj82Qeu2aPSMJX/cXeR/7zxsMbQPo7l1Biagf66IfGvrIxvb2EQDN6CuWBN077iZoE+wiXkw/fGwFxlwz1ojacQnY6AvadQLNflbJRqPZ8yT/4X6DnxbJG/n2CpOeUEnNiH5RiUe8z3/jHoFSqmIh0xWhlOB+2faeMzBVEUmdRfmV3yAWsi72fJp9I2GLsH6no4dc+ynmGMVQT5xwcMvzEXWUg8VSeeyuvt/cltxrijYnhteGq2aIk2pUR7SB1E3/Qy1q3be7yrf9GPkQc6BFlSpRp7zHbOxfdSfUKf96OgDTuwLD9VHHRyEOpS8tjvpOlhI20JpuX+f7a8uXQNC3ulfaD+L77BtTZTjCOo/347a9ZybjOvdr462XkmLxbar6FaRkP79g79omj9KD3rQb1JzymBBwYVWN9tvYxM1ca8/n/68BuafIl/3Tjom+cibH4nNxfWdD6O+C1MtH99x7n3JV3sj3q4llI73mRTqsABpRxbEW6QUxLdYie54yKkWKU/PcQguNgzyEowSnvvA1yNr517g9ULngxT7ATsvsBx13G2gh8jPfv29O6eiWfqcP+UF4164GxYESgLoVEGIG5tWhvzG70CKuOfuKrzAA2PWQHFB8phPp4cM8PNs9sgv0D6EplV93OdSz3jFyLKM0Ps5S6aAVqEElMD5CdBbw/mLz5ft1KmT98R2M72avpSAElACSkAJKAEloASUgBJQAkpACSiBSyOQZR/Qu3TpIn/605/EPM399ddfv7St0GoloASUgBJQAkpACSgBJaAElIASUALXOQEamHX5NJYsWSLdu3eX/fv3y/PPPy8ffvihtG/fXownPV8+Hg+YeT133OGMdcyc1iVKQAkoASWgBJSAElACSkAJKAEloASyNYEsmwfdzHVunuJ+OS/T7swZMiBdTkfa5rwEdB708+K5smSNbdi+AcqmUd1gQT3BP0jlFDQ5DncMtq1lJ7SdJxGghSdpDqE0efPaxSyBgukTbwctw+zAmpIJ30Ju74B6oOUfKGU06Q9Jd0VfoXQqhAUVnb8ZxtE9wc2ZVrdiU5m1hxYcQz2DzXqYDn3U+sx3xmBuDnk328zBvJA/elEtzDdFK6CAP9KUut5t8pguIg95U9qtQoQwkXyisgO3ZeXNqN05nCuSFzOU9E7yUocWw76WkE90VEHMRxFX8EtyjuZ3FmIq7BPFS0jkBlw3XyZwya2iWpbxtOAu0u7x86UudMy+criUouPF+m9FcV3odhXphpeoBJA3P3k3tnfnJt8UhrlKdHkeosc0/MnZbtNy3RZsf6gU6hvpklxZ3ua/puP1NHnKbyG/e+Ii29aL6pAmb7dQ+0XE0W3dZJarRAq3RV0NpczfhwuK0jV4Mh7zuRyuW+j4VPkJa9mLPz4P5rvTW00jh6mp/Jg4uscgtDL2tfMb1DBhu0nRee6etybdYqn5v32dJQ5BzjHYWNLWmSj8e9RT6Xh24PsBnYs8V728i/0Ni7R6wKRQK84VNdmJS5c1Rl2cdvQXfIBC/WfWQH2KjPfrluJsiG/pAsEb+sa8Df21XlARpTxB2nadnkjAA15S7EMmnhO8KD6Xj6Gz43IcdCt5BPQr0hs0e84TghdCvvehmX49Wl72xxr8cQjoPOjXzrFyfhu+8o1KS0u78k60ByWgBJSAElACSkAJKAEloASUgBJQAtchgSz7gL5oEf95+zqkqbusBJSAElACSkAJKAEloASUgBJQAkrgMglk2Qf0O++88zI3QZspASWgBJSAElACSkAJKAEloASUgBJQAlnmQVeU1z4B9aD/dseoH5mxR0wi814X6+s2WzGI5iYPoPnE14qdoba2oMfsEM2LWojyiWS+3CSzYccbS3PQQ+UW0O3EGizjBf+Gd4Ochdo6chT0e1IcdBfK96txD+TLxaD5d7vUtflHcN0yK8HmfFGgoMF1hByGfB95FrTId6gHFUD9aHmrE23oRWjVyzzndr6u2KDIRNQtUbIv3PWwR5/C2trk1RxZE/MDEIPwtLvh5N2M/RTbi+P9DKX5m3dy3+Qb/iUI+yo1GXVABdRyN+pCeayOP2hjEwVvQy3xpJ22XuZ+ytOgrkJNMZ/4paMbOLEJ+Xj/hPmeZBvFrMhYXsDn0wmngBnT8TpKutB2p60vTCFv7/JymK+7H7WriqxylcjhB1AH/4xayGOe9jXmy7ZC3QilvOkc46LfYDKgMuq0LajpNifvobVXNlH5WGddXso5X0KJ6Tq8dUjx9djZ4VtRH8yNuiTeBiWZ+i+1zqk/5sS+cBkxC0nB/M107glxWp+K9WF0rr1+g80PoFwoecb5eE1Hy7KcDLd9mag2bUsvTEsjZ18r0H2scD0snoJSHliLC04WRM3PT7grF+aPLrH6QHUbm2gMPY9gLL7Finz1JjY40gP1ftqZ2533DlN5pwXXTBwIvtRC5/kyXqf/wQ0PfCbGW5zxv9RWdTPC9J/5UMos92Yi0k6+9RdM73uHPzZBs5HLQC8Uev4M3SPlT1AuzjTn6YkUXLf0cC6yccSEulJ5bRJQD/q1c1zwU8O1s126JUpACSgBJaAElIASUAJKQAkoASWgBK4rAvoB/bo63LqzSkAJKAEloASUgBJQAkpACSgBJXCtEqAxpJe/mc2aNbvsxmaatW++ofFul92bbbhv3z759ttvvX/R0dFi/h08eNAr6NChg7z77ru2+CKiL774QqKiorz+zHzvJUqUkHr16klkZKTce++9F9GDeNPJTZo0ST744APZvHmzHDt2TMqUKSPNmzf35pGvWrXqRfWjRUpACSgBJaAElIASUAJKQAkoASWQvQhkmQc9Yx708021xvOkZ9Sa5WfPorc1KzDz+tw+L+UDutnOZ5991vtw7vbhxuZD+ltvvXXeueDNHwfuu+8+Wb16tdvUH+fOnVveeOMN6dy5s39ZVgbqQc9KmpfY1wefY4NdlVCHfQH6kbbWR1bdNQn7qgJ9/7mvAYLGsSfl325apspfQbeWaNDznmwMesTU//p1v7zoGZcUMutVLOKv9QKew5W8fyNG275Nfb83qf8cjgE7Eb158tIeXBd58TPNB0/+eXn7OLYvMIP0MKtr2tCL0v+uZxfeYMNzRY1K4dIVzm55GTwEEulMbh0Vi22jiWkI7cYB8sNWP4ntnWlx0xO87fls/XrypOYhf2t9p9a0Wov2SuFt2UOe9TCyLLr9V77JboeJqu1HTfZZ2bkS8zTlr/B80jDvuWnqHNN25Cmf/iP1HUZ6LurN5NXcQpzaoK1UxPHuTwnHvlzfrsl0oEclrCCGaRHY/vQ01EdLo85/yOqZZBOtR+fWa7Qf/9hl25qoAF2StzvPMzB5fvTCvc51wHOum3r3taOwq0Sq07mYTOdHfiwX9ss7j9aQw3mweAt5khtEYz6hGmr2bkdiWugQyNF/2oK0O21sIvZW5y2GecdS7CV6ElT2T8+hW/KdznkevAH7PkT3ueCCmBdiTtNoi9yL9ZG07Z1O23zDX2xsojQ6d9Kca8LkA2nb6PEnIjMeMmX2df9sG5vIPT/4+x+6p8pObCoNSG+YiQuO0cM1Ci6FfN+29iJdJfiQiBIEdXoD9Im79yXTabM49I3HCr4v7nUfYOKrLyfxppn32i4hGaH3s5wkgI4Q54L0ZcJJD8z0vBp86MQqQb1AiBOsTcUfgYB60K+do5Rl36Dfcccd5/1wanY5OTlZ4uLi5OjRo15tpUqV5MYbb/xdaISGhkqVKlXkyy+/vOT19e/f3//hvFatWtKrVy8pX768bNu2TcaMGSPr16/38uYb9eHDh5+zf/MHiIceesj/4dzEzzzzjAQHB3vLTDvzjb/5oG++Ub/nnnvO2Y8uVAJKQAkoASWgBJSAElACSkAJKIHsSSDLPqAvXrz4ogiZb6Pnz58vzz//vBw6dEjefvttuf12epLkRfV04aKBAwdKRESE969kyZISHx8vN99884UbOhVbt271PoSbRXXr1pUlS5ZI3rx5vQrT9/333y9mirk1a9bI6NGjpVOnTt6Hd6cLL5w6darX1ojnnntO/v1v+y2nGSbfsmVLqVOnjiQmJkq3bt3k+++/lxw5suzw8OaoVgJKQAkoASWgBJSAElACSkAJKIFrjACOlf0dNs4MO//Tn/4ky5Ytk6CgIGnTpo3s2kXj5rJoO4YMGeKty3w4v9zXa6+95vnGTfsJEyb4P5xn9JcvXz5vudFnzpyRcePGZaTg59ixYz1dtGhRyYjdggoVKkifPn28RWaUwSeffOKmNVYCSkAJKAEloASUgBJQAkpACSiBbE7gqn1Fa4a2v/jii9K7d2/vG+p//etf1xxq821/xgflypUrS4MGbExK32Sz/JZbbpEffvhB5s6dK+PHj4fh/uYDt/lG3LzatWsn5kP9uV4dO3b0f0ifPXu2PPzww+cq02V/RAKPo3Gws0yCvZhMPvE68pY//72ggfU78pBLCPZ9JKGev60JXpbPQO+jucoHT8V8P6ngr6+fssIfm2D1qEagC/aJBp0UVwt05wXLQPcTsm7shrTIsO12QY3KNvZF1QUnBH6M5pddKyuh/iCYEEUWfTEB8vJoDdTHo6xeHGljE526BXWuH1CnLQK9ogw+FyASpUSFQzlaIEtgLiL91uFfGE7ezF7+zP8HjsfYW4KngxxyPKkm39jxjdba9v99/P+PnuVRrz6OumwC6hV4yKTDcsyPd7z2JtM6yeYDZtjYi8g32vIuzO+8AbXw4Cj+u+8RrF/k+M6b0nZm8i/TeTqlLfb1CEp52/Heeini6m5rK5qD+wHyQ7envpevwwVbN6EuG4Sa+1u+2eZb2EvdW7iNtnsiOcLa323bmmhTGdRk1RaykUues7Z+Sikbnyt6mpgtpWcU1AvDVmnfoi5L+SUOV9/f0uFV50eQspje6qsdxTzeBUWi8PKXw3R9y1bbPuCYjU2Uh3SjMZj/gm5TsXSMpAjWt9qCOtm5nyyi+1BRtBDLerJDL82DfTUl23f1AMyHopSGp+yC1P02NlESnTvPkF5E/vdSdMxmPTEbOhxA97X1Tn9v0u2cL/cN+BYra+he0nAdgciB73Mio2BbRlZ0bhC9HAi+qqHPLIFaWUU79l53yC985w3QsgqlvJ4IC7Z3ca9CPLn2uw+/8LWaLnjAy2Xq/AT0PVDcvn2p8c0hL91nolalBJTAZRP43b9Bd7c0Y2i7GfJ+Lb5++ukn/7f7Zhj7+V4ZefMgNjOU3n0tXbrULzPq/AucoFSpUmJ8+eZlRhjoSwkoASWgBJSAElACSkAJKAEloASuHwJX9QN6rly5PNK7d+++JombadAyXuYb9PO93LzbzrRxtVt3rv4y8uZJiuahevpSAkpACSgBJeFd7osAAEAASURBVKAElIASUAJKQAkogeuDQI6ruZsZ3xL/2pDvq7ltZt3mQ3LGKyQkJCM850/zlPiMl9vOLHP1xfZjhtebb+PN0PmLfZn6871++eWX86U1pwSUgBJQAkpACSgBJaAElIASUAJXkcBV+4C+cuVKGTp0qOfVNk8xvxZfSUnWIFmgQIHzbmL+/Pn9+WPH0PeTVf34V/ArgftHgl8p0cXXCIHJ0uW8W9KnRgt/vlsMXqYx8rg/Z4LeCej7Gj30UcjnG4ietzDZC/kTQkbCoXa0yGqo9Al7SXiZJKlCFQdAT36kCWhJd3DYZf+2YXrkGFP7fwzJjf0eBp3+SEVnUdyNjhDf7LPHQcu9pI+jb1BKO+be8ti0UXn0nK9wvLRe5WI0d/ZEKQuwO0kmP3R+x0fa6AYsnk72x3sxLeXIwsie1HZUH0ze7LjctuCI/TujtzAC7Y0yNt7WmqgQ+WOPrMX8o87hNJnlaZgP+cnq42VtbKLmdAw+J4+x7MF63yS++HKYegnatqYuN8evamrX03Y/QcdgE65JYmnb7qlHBWjlFIm1+RLBNvai06i/IN2LDNBjXsX6M2h5lW9+xLzrh76xOOYK0mC2PbQf9k/W6e020YkdQE6w6fHYf6rDYXgdzA3Ht03JOxHzJ0ajHkfn0tcRmJ9B3G5eb/NpeJuSw7TdIcdtrYmKbUe9grZd6DooQtsa8IZtv5+eOXAiyOZMtIKOV6FimN+Zgnos6bvpb/otHA5zaMzksmbYV+OfUfP9XuhcjabrpO6n1P5+q/fS9Wwz6VEPZzvNkobO8fIqbkivy/j/UvrOZBhx+mtGoe/nCnwLFKnnJH1hztiuuMC5Pr1EDroR5qT6r9tC++FxX/j1iWeck963NEjy+nPpAb0Z7HJOFlNA+9kj5T1ov63LzaCrigWZR5IhxyKX/BcWpQieTEHyFeSnSgnQ7bujm38kZFUoASVwJQTwN/8r6Ml82L7QKzU1VQ4fPuxNSbZ69Wox2jzV/YUXXrhQ06uSP3HC3lgzhuP/2obkzm1/y01JwZtcVvXza+vW5UpACSgBJaAElIASUAJKQAkoASXwxyeQZR/QBw8eDE8uvxAaM4TbzPM9ZswYadHCflt4oXa/Zz5PHvu1yalT9LUEbcjJkyf9SzLmSc9YwP24OqMm4+f5+smo+bWf7lD6c9WYIe7X6miFc22vLlMCSkAJKAEloASUgBJQAkpACVxPBLLsA7qBZj50n+9lvi0vWLCg3HzzzWKeZh4ZGSlVq1Y9X5OrmjPbmvHiYesZyzN+ug904+Hw3M/5PqCfr5+Mdf3azwv523+tnS5XAkpACSgBJaAElIASUAJKQAkogatPIMs+oJvh6tnt5X7gvdAD2Nxvr9kLzv0UL07GPwdcRj/mjxluO6dEw+uBQEyCfy8/kD7+2AT9fTObu69UCXSlyEA0524W9LRN53nUsbUEDgzzL+kvaFg+I65xVySH7z/39YM4kw2bxCw0VIZR+9F5m7nNZZgzl/mAZx+GnByKR019Cem7ZSnUT32a/hg4bQDk5XvHSHp0BuRWbMNjgBOX+0rt3/K8dtOgte9BkXhIJIA87C2d+jHokJFhhZykL4xdiXp9Q9Tj8ZDIWEwLHVLZ5Oz2Cq49TgviUCfSMwUC2fdNek4Ati/mrHsteZCXbsDaIGIolTEv5EEVPISSyaO+32n/kxP7wlrW3eQlVpJ/tuE+rI+shzoqBrW0Qe3aa8PI3lpkDdZ+7Z4cvtQYtIHKe+5++PIPEWMhX3GqwzzwY1xXfuqrwCzMryDr7QE691K3YP1Jui7E4doKS6WItc6mZ27Hgpm0XyPIy50nCes3lEa93jlGc/Ng7kE68ZOrYf5IXdTRJ1F/T+feMjbjfmPrt+LU05n3ez3dl9oMs419UaNcIDNdz2H0dtCogK2vRtdYhS9tzkSb70Xdhc776XSuHqBf+ybcj+03ObIz3Qt6Udu3aLs3Vnca+8Lqs1Gvfxx1czp/+r/j5MOc2BfGU+3Lf54IBdPxbUtkG+bl2JtQLzQtev/XHJBo0xZpSRC7FMK++uxB3aMU6HHBT4Em27jMS7EX2RBxTjxfq58lP7SdPKgJ6HJDVoGOkFOgSwgetJEzsD9pC+UqlIASuAICdEu8gp6yYVP32/0tW+g3D9pfN1+lShXIXk4/5kO+++A56FCFElACSkAJKAEloASUgBJQAkpACWQ7AvoB/TyH1AzFL106/c/w//vf/85TKbJkyRIvX6ZMGQkLC4Pa22+3XwWcr589e/bIjz+m/+n2tttugz5UKAEloASUgBJQAkpACSgBJaAElED2JkCDIbP3zl7q3plh5g888IC8+eabYr4hX7VqlTRo0CBTN2Z5xjfopt60c1+VKlUS86365s2bZcaMGfLqq6/KueZ+f/fdd/3N2rShMZH+jAbXB4E7/bt5yB+lBzysfLA0gYpBNLR7CU2NUl3eh/oIwfGak98p588P3UljOxf5U17QedFiWDA9+A7Qch9KoSGznVOw/YBgZzzvI9S23g2woPXTa0HPk4agp46qCVr60Jjp08GYL+OMiT71PebyoJRQ0jSUdx0Nvz1AoxiPUn+f21GJMiEf9o0DXEX+fBbzTWkmnTT6W2L3qlj/C2KC4Z7Lc2ItuyfSaL+TDmJ9gSOof8ZDJjfTtrcLsvUVd9vYi2iIq1BbIYa8rXI39VcK9WZntGaVeMwJHa9xzIVGdvKfU6PCqD/6U/iHzjDlSHSNSNFm2Pb0RtRHYlHfTcxzu+OKfaU5cdSqpNSx7U8Tk0I7bM5E1V5EvZKGBhfYhfnvwlHfROfmVuf8qUR9FZ+DbVt1Rv35PtRjneNnMi+VxfwzODpXKjjtQ+h67doI2/47BvX9aag/oPM+gvZzYwmsj7zL6qE29KLP6V4hxemKp/107pBe+6hvscNm9KvDeCddDG/10vUhJ+kL36Rb5KRKmA/9BvUwWtcKTMNl9Dldv5uca98025n+3YS/h+nR/tAL0vaiPkDcitN1kuLYMb6jc4GvZ7pkRJzr01vrnltw5YfvRh2I8pEX7FEuJHdAcvIsvOhGyWrIb5DcoKePc94cfJmB8h3kh4r9XcFLNC3iz89aFOyPTbAxGG/+fYd8DPlX5CbQnQQhHxfHL2Eqk+tBvQoloASyjgDdVrKu4+zSU48ePbynzZv96datm/AUakab5eZlnkpv6s/1+vvf/+4tPnTokPTq1StTybZt22TUqFHe8vLly4t+QM+ESBcoASWgBJSAElACSkAJKAEloASyNYHL+ga9XLlyWQrFfONsPqBm9WvZsmWydetWf7cHDhzwx2a5+421SXTs2NGfzwjMt9/mw/Urr7zizd9uhp737t1bzIdos82jR4+W9evXe+U9e/aUihUrZjSFnx06dJDJkyfL8uXL5d///reY4ezPPPOMFC1aVL799lsZNmyYJCYmSmBgoEyYMMH/RwHoRIUSUAJKQAkoASWgBJSAElACSkAJZFsCl/UBPT4+PkuB8JDwrOr87bfflilTppyzO/NB2fxzX+f6gG7yI0aMkH379nkfsM2H8fbt27vNvLhLly4yfPjwTMszFgQFBcncuXOlVatWEh0dLR9//LH3LyNvfubKlUtef/11admSB7G5VRorASWgBJSAElACSkAJKAEloASUQHYkEOCbu5zcVRfezSZNmmTyWV+4FVbExsbKwYMHvbnTzQf0s2fJoITll6XMB+5f+4B+rg4vhGLBggUSFRXlfcA238ab6dIiIiKka9euF/2h+syZM/Kf//xHPvzwQ8+TbuY9Nw+iu+uuu+T555+X8HAy8Z1rQy9zmZkqLmMKODOdW8Y0bitXrpRGjciEd5nr0Ga/P4GB8k9YaV7JB7oPedCHih1JYgrHSmGob+XM21JB0Gw5QiKgtregcTCepl3LNK1axWbQvmAcGg2TnGnaOksC1E7O2wS0vICy38g5sGCEpNtK/As/mucPveDP6M+TqY5R8cTDWJsjDPXpWNR570NdbzboSPJyvoJYZZdzyMo7sekk7SfoSn65GXWFY6gL5UedSL7RTNOTOR7WX5pi239aO6OX6L8H85Fop5S/OwhN5fPk5cQzTWSH0x3/2ZMsxZJuJLINEm2YHvEgrCNYkES+4DLOChJpu2U3tuVp9DJNsxeG9b+glE20480d03rAAiqm4y+0H+Hk659Lx7/UIewvlY5BT+eYvXAcawuQH75wEuYLTkd9pjnqv9ZAXQ2l/PmwXTCmqI1NNPYE6p/Io76HnjlwJgDrG+MlJ5FtMd/Nmb7wJmK0i7ZlMB2Dl2nbYmhbOlA+zbmmzFbc5tiQV1DtSvJil6J8CF3/fYnxU85+mXXloN/oKjvPILgNb7+yyTRwXoc3OMIXrquK+kQg6sZ0DBaRDnHOr3J2MKPXyQo6ORrj25KkrcB1namA+rvTa3ABq8GD7RI3tkv9UZ2Odf2xCSaQn30aZEVW7KEFS6NwQapzsxlAB+wZLJVe8bSgOOoaBVAXQym3om42bpl/wULB/SopMf6cCfb2rQeafjUQieIdzQH1w2jK1gHyN8ir+OMRcD8b/PG2PnttMV5tF7lvixcvvsjKzGXmG+iBAwd6H84zsr/VdGJmCDsPY89Y5+X8NN9+m39X8jI+9b/85S/evyvpR9sqASWgBJSAElACSkAJKAEloASUQPYiQH8P/e12btOmTfLwww9L3bp1xXwTbb6tzpMnj7z00kuyffv2327F2rMSUAJKQAkoASWgBJSAElACSkAJKIE/AIHL+gb9Uvbrhx9+kMGDB8vMmTO9D+Xmg3nu3LklMjJS+vbtKyVLlryU7rRWCSgBJaAElIASUAJKQAkoASWgBJRAtiTwm31AN084HzJkiHz00UeSmprqfTjPmTOnmIep9evXT8qUKZMtgepOKYHfm8BQeZFWOR90O9kH+l2ayzRJbob89AHWAzd42GeQk1YhoEfHoB6cgPWD3ybTI3k/k3rhuuVVu+7Jb1WAdWXyq5eIgPwIqQ5a+pIpeRGmZSjpE7a/lk/jhn5+CrWwKbHabOgsbRVIYZ+gTMR8UbvbIv/D3Npuf4IFJY8i43bkOZ9G3s1ld0JzaZyAWtpYfYD8rLSZMtaxVppWPC/2F+R37mq79iLGFuucmoVvwOIO5AtvR32z2agsnUrLaHxYwY+x/6Wlrc4RYGMTDQ1D/fkW1PSYB0qK3EjrlplYsnSJo8n3vZTahuR1an0h2YSluOPzNZVbSmF9XTx9ZOJwm29PFtSpsTZnom3EtApZTOfQMeHjS9Z7aeicq5twVSL0UIGb46iAntuwuTnl70cdRfvygrMvhcjfnnQA244rhHpmEdTd6bkASwtgPqAmanF85Y3yYK4h7depPZg/TtdFL8fHbypL0PkxhXQV55pOjse+89P1/GMlzEeQP17wubqS6hxP0zIwJ7ZPG2z1qZE2NtHtfVEnPo/69C2oc9LtXC70K6TzMOObfCM33ddeV/ji1PW4IBSlrKB7hyRFY8XCYNS1rRwV95UVvuhYr2OgPxW8YDfO2An5Zm3x5lSBnhwQtegJqC8hqX49WL72xyaYLe+D3j/y76CryT9At5WOoFfIYtADnnwFtFR0DtLA8phTpQSUwCURyHFJ1RdR/PPPP3tThr333nveg9/MN+bGd/3UU0/JgAED5KabbrqIXrRECSgBJaAElIASUAJKQAkoASWgBJTA9UUgyz6g79q1y5tm7J133pHTp09735ibqcUee+wxGTRokGT13OnX12HSvVUCSkAJKAEloASUgBJQAkpACSiB7E7gij+g7927V0aOHOlNP3bq1Cnvg3lgYKC0bdvW857fcguNU8ruRHX/lIASUAJKQAkoASWgBJSAElACSkAJXAaBy5oH3azHzAP+yiuvyJtvviknTpzwPpib+czbtGnjec9/y/m8L2M/tYmPgM6Dfn2eBk2F3brI4aDshwV15Vm/ThY0xIYLGoN5DvVkQb9cag30/vWLmePv2wQFyA/fRxrafAgZOxPibc6LyLxLWSFvXzny7m0f0ABbVJ9v9cnFNjbRjegxl12YFvKojic/LFk3ZVovbJ/WzuqAjjb2IjKCr0GkUpk8q18783ub9lHU3ednacE3js7jxCYkL24h8ta2pPKn03BBc5pOPuANzLvT8q5sirm6m1HnJH+s6+v1Ki9wTMLJsxq70vY/xzntzNKxNuVFK37EBRvJpFr9JObpspF2xHG6470/ai2jXieF6ICdaI99r6qAmtUOvGTlybVYMbWO1U8ttLGJTpVGnbsg6v35UBcnK25AE8yfikO91jmGL5FfuRqWSqfTuKBhDGqpiHoKMe6PafnROYYpNJf0WrIQ307b/R9nu0233eOx86/IudeCtt2xBUs7usbeJA/60VzY9yg6Bv9y9sNU5pmG9YUHok7cYnXaOhubKOAh1MfpGjpB97U8R7A+r3vv8KVWdcJ87W1WJ1axsYl+XrMGFtS5nW5sUyAtx5x7pMn8QO2x+hLVhg3QoE7o06BvuxukrPgItUhXXHDUucEX2IG5fXSDJobuPdFrmEDvc+8kYn+v0cnbf5XNx9F73HSb8qI/o+7cZzEsmCyVQfvONtDdBM37E8R5qEEIXdF/haYifdSjTkSuCanzoF8Th8HbiMv6Bt08ff3111+X5ORk74O56al169YydOhQufXWW6+dvdMtUQJKQAkoASWgBJSAElACSkAJKAEl8AchcFkf0M035+bbcvMAuBIlSkivXr0kIiJCjh49KkuWLLmsXb/jjjsuq502UgJKQAkoASWgBJSAElACSkAJKAElkB0IXNYH9IwdNx/SzVB38wH9Sl6mnzNnaBjPlXSobZWAElACSkAJKAEloASUgBJQAkpACfzBCFz2B3Tz7bm+lIASuPYJLJIFuJE1HGOgyZDfsmWKNaa6c6qa0v0SZH74X03ICFxV0Hy5P2axv9YEI/5zH+huzywHLU0d33mXwZjbiXpIH8cz7qucJejF2yj4R7/8QvesYXuw/3dnWp2DjJxlZtuciUJRMsOGpzBPFmeRzzEf4G5KN8wdIO9mBKaFDomQVTPTpu4nC2Nxx1a4hiyLOVJxZX1RyuDjuKAKeZTT/o75pcVRf+p4O3MQsxwHsLZdDdR/o3evxeGYH0De3tswLbH77YI2yTb2oljUofVQHyAuJ3/GfP/KqNvSvr3lpNfd4AhfWI2OP2ZFbiNv/tHSWNFkJWpxPMgmU7uqzR+oZWMTJeRFLT+iPlIYdYkmqFcGoM5VCnW0cwlOonOnC507Ven4RVfHviodQl3oC9TT2qI+nd/qHCdsbKKQFNRBeBuT7oswv9Px8ZtMKG1LJHnco5xj0IOst7dS7ZfEJeosrjsKpUhjWkDnrmsLXvMI1dK68pHnfFFRrB9D21qI9uVl4prLsV///PXX2BmptX/vD0vqHBsOOks959CzSJ2/PQ1LAuh6lo8h7TPvv4gLCv4TdQ57t6neFh8K0YZ823PkBmi7MQTfLYbIfyE/6KX7QMshvFGWc8777WOwdHDMZ7BgcAzeqCZLTcizx/yk/AD5ZPKoDxELbtBB8qCr5xzYqVACFyJAv+JcqDw9b6ZS05cSUAJKQAkoASWgBJSAElACSkAJKAElkHUELusDeocOHbJuC7QnJaAElIASUAJKQAkoASWgBJSAElACSoAng1EiSkAJKAEloASUgBJQAkpACSgBJaAElMDVIHDZ86BfjY3VdV4ZAZ0H/cr4ZdfWI+QN2LUUsYbMd2U85B6RjqDHi2No9WX6yE7IbxUyLUJWhOdVH1ixub9iVNxX/tgEGyQ36O8FJ1LeKAUhL5HogesdZb31pnAsTfKdOt3xCh59AvtK24S6Dk3C7Pi4vULyckaWweYDyAceGmfzK8lr7c4lbKqmoW1QnsApfOVTtBHS7O+Z50Xf+Y1d92Hy+RbdZnMmWkoG+MYrMN/uDtTTyT8rBzG/uYDVg8mDTMRlnONfNq1a4Kkm8lWo7cwXteuCBXg2iAyYb8t7kq1zLO33+PK21kTolhVZbi8Zr/A28nJvO4ztizun9poHMZdA82DzuhZTX/3IJ9wSu5N7yUfuzqPeZBYWBzj+VS+zD/N0yUgS5ROKYz0/k0Acf/ypQli7qyzq9+lybkDHv7nTl2k5txG253F+ic41F0nrnjgD2waEoz5cAnUgPYOgsHPr8CqTsF6W1vYvSCu9zh+bIICu1yloSZYOznlq6iPpXH2UuLRYZarsq5FjaeZzY0C8rTNRWmvUAWtR7ySPechwzG8Yivps7Br/gjo/1PXHJjjwOMhM86LnqYv1pbFctl9gHvSCTvskrn3gAextF04A/zkxZU7yDd5rpFAP7O/4XKsPv2tjE71wDLUcIV2ENOVbhWC+o7Muk9nyoM077yveQnrvkH5nbK0vGkQPRxlSg04IwibDEqB9def9/y56MMs3gu+ZrZzfM0wn+QUvqoE8tzysScVvRUDnQf+tyF56v/y2cuk9aAsloASUgBJQAkpACSgBJaAElIASUAJK4IoJ6Af0K0aoHSgBJaAElIASUAJKQAkoASWgBJSAErhyAvoB/coZag9KQAkoASWgBJSAElACSkAJKAEloASumIB60K8Y4R+nA/Wg/3GO1dXc0mYyxb/6hYI+wHI+J7j74nnQJ0c2cdM+w/NW1I9UQD0rHnXFMKtftKEX/YW8e2McA7Mp6EVePSFjeF/SI9F/J1N32xWeftbGvqhQJ5z/NfFTSMuU+1F3mDkNFoQ+2h70zliQIkUcTbuxqIqT84VNJ6EXP7HVSSj4ORikdCU/9IpTmE/cb/XJfDY20TLyN3+OaeE5moU8qj+hrVAeJ1/xiuW2w43WpustrIrIJSjR1noReXWjy2H+WA7UTTejhil80YIqchxrfyqDuhhty9obMd8kP+pM8ygfsPnFT9jYRE2WoRY6TXs1w/zQH1E/VAn1SDomNbbY/Ms1bWwinq89YjHmJQx1I1rXFLpEV9Al+n/snQucTuX6/u8ZY8YMBoMcMhrnwyCRnFKGVJQOttDBocMetYufXRsJ41wNu/Lnpx07Eto7h9KRJEaRc9FMg5piMsqxwQwzTjPzX8/r532e66JQ1DD3uz9b97Xu+3nWWt/1rPXOmlnXeho429LwY+yrG51D4+k8eNE9R7ymsbSuGnS82R9/wjn9izpj3mzFF7QfIwvjtr3jMDOZEP7TBo1FWYLtxTnnNpOPtw5dIqUQta1Nei3paNK0b+4xSwjA2hjyWsfSuv9O50Htj7B9wPWoJRh1inP9qF4Pc1u+Rn34AToR+vWDgsZ9rgVNFmeRSZj+4kl70jaewSc41vJ1K4BWJe9TfXnSWVNwwVELqmn3uyHHXmv+jh0jn0L94A63gB6+4APUUh20RDgDBhHKwLilUBsfixeTflNmQH68NAAdI1NBJ8gC0H3kVb+eSJ5zOc1rjycCvwtnsPzN35cGfxwB9aD/cazPtib+mjlbveaVgBJQAkpACSgBJaAElIASUAJKQAkogYtAQG/QLwJU7VIJKAEloASUgBJQAkpACSgBJaAElMD5EtAb9PMlpvVKQAkoASWgBJSAElACSkAJKAEloAQuAgH1oF8EqPm1S/Wg59cjk9+2y04CHSN9fnXjbpCbIb9V0BBbk+ZJHyrNoV5eRdNix0fsxLt1ZRfUjpMqoIfJbtTP3Qa6zSA08y6VZpAX6l/muPMTkxmTTYp1B2BfdrNPLi/cG/NBZHJt8xTmNzpyG5nIr013kl5IU/AKeU6jHQuiaZj8Wi1sfzeau/c7/tgd5BEveRybRv6EOpbWdZonPQ3rpSLpLY6OcmITFiG9ifR+0teRziHt+N19maJO3tpVTy6s5uRMmEqa/NAbaFvZX52FVk7ZU9r2V+yEjU0UdhC16502mfDPMB9wF2qh4ZKXiPkMZ1tK/Iy5dTVQRx1GXWYD6oCrUEtZ1OuIS6Usm3+IGC7cY3MmGnUF6r67UJeg0yST8rsov8vZlkfJr/4mzWNf3z0fzWr5cuCOHZNfbf6xn/4P29hE49xjsOlJTGa/iDoKpeybAAvC7+kLOoPO7w334vm9L8SWt7PWaN/CcJoYPYPG1mbyYtem/cwrYfs2UWBt1MuddV9Hvn6+NFTFpqedcuW2YUFRug6m0DGN+srW78CvDqlC3vvT/OzONdHXyzW2L1/0/lhccGgA6kLLrf6BLnpHbMoXPXuIFtCONHMGrql88h2oH9glHHT8sDZWV8UL9kM9v7U5L5pWozVoSdkBuqlsB71XAkFv5e/U7jb90MxlVnjRVYIXk0Dqayh9scXKCmh/kH6WqCX4BTBS6LyC1irOlYB60M+V1MWvw7Pt4q9P16AElIASUAJKQAkoASWgBJSAElACSkAJnIGA3qCfAYouUgJKQAkoASWgBJSAElACSkAJKAEl8EcTOO9H3GfMmHFRtrFHjx4XpV/t1BLQR9wtC41+mcBDzlQqV4gzH5TXZJL3oJr7yazUxJUiO75DPQcfmRveBR/nGz6bHv/7oJFtf6PzPKxZ+kOYzZkoE6W0WIcLutDzts9EYR53TaSJfa6x6yM4t9nsH7EpP8orSZRPRR35F9T8eKe4/TuPP/taZWDbw4SlaBTm5UPUsbeh5sfQlzuPe5anxy8rMiPsStIjaAHJIJpmbS491tznPdsgoLWNfREd3xb0GDpPF9ce3RLSjbq7LxEXFHYex02j/Y5Mx9rN9Lh1eRzGklEO63PpmF2FT6FKQJStz/7ExiYK/QH1lmaoo/CUkiJ0ykkxrO99A+p/OmNtCTG9+3us5Ue7EypjPmYVammMOpyezv3QeZx/QxDW9qXH7feTRaFkU6wPWIg60jmeJpNKj6kXqmvr9x+wsYl2EbM6dPyEto2e/BX5iZ63LvQ2ruCEs4Ki4zEXPhk1bZsE/wvzPAdg3lOYJw6SmGDzN8XY2ER0iRS+MJHl5XW6NvWk8wY795SzaqFz6CCNvQnlsfWALajL0n59QedgDT4Pkp32DZ3YhGxRWOw8i2/ygbSx4f3MUvs5gY+KS6GbbM5EPzRC7aoBvKG4I/Ul2632vlroINAJHkFXunSZ5bQv6cQiwwRP2BFkOSsu26C+A21LbSH/DVSLjBDLqbP0hGy0oE/ArTWFsdIf6ksJ2sLi5a+QbyBNQCcKff9DVsW5EtBH3M+V1MWvo6/Is6+wV69eEhAQcPbC86gw/ekN+nkA01IloASUgBJQAkpACSgBJaAElIASuOwInPcNuiGQl5d32YHQHVICSkAJKAEloASUgBJQAkpACSgBJfBnEjjvG/Rt2/ARmD9z43XdSkAJKAEloASUgBJQAkpACSgBJaAELhcC5+1Bv1x2vCDuh3rQC+JR/w37PNIaUR+KWwYdVJQDoEcL+h+HyXjIjwjtCFqysf1pU52NtEbDcnFroW20WI84JP5PLJUysDhQ0NuXS/mmglPQrBnYwrYnz7BcX83mTMQeRvJPyvInsb7di6jZVpjppI84sQkZ2XHMRzZEnbYd9WnteVud/rqSL5RmUZL4Pdj3fWTVXEi+YXH69rUsgu2jHZlMhzeL/LBhhZxiE/J+kG84lrZtih3WJztyt+Vn7Lt9A9RP0kNjjdMxX+pd1BJFegXqE3dZvetqG5toB3FoRNt9lz1FfA3rYXOarEik5y4seN3h1vdbzB2j4xXM4zwK6yWRNOfJFtq1ra2fTfvZn94hcIfjVzetWk2PsI29KPoRPAjJWyAtaRVRR4ejdtXBAa4SCRiLWlJJbya9cwMuCH0FdZA70mkg5+IBiu46CtomfwhSJGsqLaCDdOQ1zOeMtrroZzY2UcZ41KyConBJheWg83aAlIwOqEsUdjT519nX/wNevuVROufY/TyG3m/RgsZydec84XNkYYKzXSZsTPoDesHBCZqP7gjVlxiKC3JaWJ0da2MvqvrI86AfoOlCR469E/IyAL/HpJnzPgNT2Q7L5Z9W189Gz3mS1LBJX0R914jCfAr75atDvjj5vjMbOL7wRBzXVekkiqYvh7qk46URrGukrAcdJ71Bu6KpzHSlrJHuoL3JR0m75yelCphUD3r+OeD6Fvf8cyx0S5SAElACSkAJKAEloASUgBJQAkqgABPQG/QCfPB115WAElACSkAJKAEloASUgBJQAkog/xAIuhibkpGRIfPmzZNVq1bJrl27JCsrS6ZNmyZXXXWVf3U//fSTHDhwQIoUKSJVq1b1L9dACSgBJaAElIASUAJKQAkoASWgBJRAQSRwwW/QJ02aJIMHD5bMzJOmSvPGdzON2uHDh4Hvp59+Kvfff7/vBt14oyMi0F8GxSqUgBK4eAQmkcn18X2/uK4U4fMU224R8jhWoq5SuG/0tLnVuztf50rZ/RVIkT6k+6KfrqigUXQA6aFCcwK7czyXno6dk0dZtrXCfA56M6XFi5j/CGXX+1HPdr2aOZgTN+elVuH0sNL8R6wPd/fDS2UUwnx78mYv3G7zb1axsYkyV6A+THbXGTTjZpk1WB9A1r7+mJYhjk0xgPb7pmpYPAGlsH96AnFpj8NBJpK/OsThOqoBdj6UfP8LS2I+m8cDjfO8tlh/cDfqmc4x6DMbc/uIw7EwzL9NXtv/of0eSfldFbB9HdfbSz7en6/EWn7tw+FUzBd19sOXycK81Ef9iLPuesGY+xql3EY/nUSy5xx/pBD2NH9HXNzueRxOZM85e5TpUiEJtdzuvEnXyeAeOADzFR3QIXQNvKI51CbPfQ605OxFfYi2fv86zBdvgrqEu3MEJTANa2ncSmXKv4fl3R5CPXsjanf8tCAPehrpsHRsu/B71KxinPPXlwukCuedBGlVKUcY5C06ns583r6WRcjvHEVz16eMwhUUco5JyjLMyWrQI2dHghb6nnuIvNcfrsYLwu7VdaH9EPnEr0cPvMsf+4J4NM/zvOgzU5wLstegkIyB9l0ED/h/BS8umYnV/PWVxP5BzixsJK39ORPMC40DHZb9GWh+MQBWU6kn3XnXvxX+tsD6gbISFsR3p8E20+4HFKpQAn8ggcALua7hw4dL3759xfwFPTg4WBo35jdv2LV17dpVKlSoIEePHpW33nrLJjRSAkpACSgBJaAElIASUAJKQAkoASVQAAlcsBv0DRs2yKhRJ3+L+MADD/gebV+7du0vIg0MDJR77rnHN6f64sWLf7FOE0pACSgBJaAElIASUAJKQAkoASWgBAoCgQt2gz5x4kTfzXbz5s1lxowZUqIET9BzOk5Taz5JSUmnJ3WJElACSkAJKAEloASUgBJQAkpACSiBAkTggs2DXq1aNUlNTZU33nhDunXr5kdo/lJuPOjmJrxuXfTKrFmzRsxNerFixXyPxfsbaXBRCOg86BcF6yXf6XD5f7AP8TLIr7Nlrj82wUDBX6b9W16A/GNehfvZKaVcKRnkUX9bOkC+v1dx6hMm2adC33+HjbkNdNPB6CNrLWjG3itloX6aRIFuIztAu2LpnBOuFNnbGvSqv6JHrfk8SJ8+Rzd5nOWDVtBg7x3L/bqs4500C9eRU6haiL/UF0Sg1V5SyA9dg3YllvzUUw7Y/uZT7m6yBcbeYGtNNAUtjRJeBPMZh1HTVLfS31nfCLIBsgd9JeU3o/1R6uzEdeWR7zugHOZhwnCL/2TRHqxd9xfU0Wmoc8gPe4I4nKB8WceyHF4I+xqNUvrm4IKdmaiL2VMGE/+nRlbGxePc/thLT9studiWTl/JIzv1ih5Yzz7yjGNO/icn9sIN5VFfQ176CXQO9aXzJLY2tp9Cx1Cc+iSyaR+g49OK9/t1OulCP8KVHS2DutAR1KGOeTsXNyz83slQm5EIUuTrhbgg99+oQ+5CfeQN1LnOiwGC4jB3sCrq0rTyIy9i/k48UfLwEiw7rsfyLcWtvo7OxxJ4eZY0ulYE0TE4EGz7MlFNGh/3NcT8m862BbTA3HK6JraicTyhPNb3TUYt6xrhguJfos5wZN4GR3hhIK38pQjMJ36H+rnqoOsPWgU6qdnJP3T5F97jj0QqbnKESNN7D4Be04DA9DkGefmrM3ZMpoZzwTaa50mPcbaVvPTPpeOTsin0cpVpQn0LHoSH3BPYW/U0ocEm9pxj3/40wfOzmeC4riHRZm/8n5nysj82Afvpd8QshbwkuMe0FuYuMaXzoOefA3bB/oK+c+fJn45q1Tr3wRkSEuIjYXzo+lECSkAJKAEloASUgBJQAkpACSgBJVCQCVywG3TzUjjzOX78+DnzPHVTX7Ik/+bsnLvQQiWgBJSAElACSkAJKAEloASUgBJQApcFgQt2g16pUiUfkORkfhbolzl9/PHHvmT16s5jMb9crhkloASUgBJQAkpACSgBJaAElIASUAKXLYGgC7Vnbdq0kU2bNslrr70mDz744Fm73bp1q0ydOtXnT2/Xrt1Z67VACSiBi0Mgm7ze/WW0f0UjHV+XWcie83R5x19rggmC5tzMfk0gL+PJKDoUfWbxrk1tdSq2jfoW9JoO6J+7a4HbWCT+pdZQL5iWpQuiMA8et12YK/430M3J9y1B5PtMvR/qJ9A8yjFd0MtZdqtTXtSJvbAJeTFfd+aSNpVHt2B99WKo0V0n0hLTMs5a96TEYUzurY96I637BbTTSgj5o4NdL6bXVQuyS45z5pseVw3X5c6h7MtEUZ6cUasqU/4H0uSvznQOcXHaT54rvonDyPS67Qrs+zPHa2syPWZgvl4P1O0dufCAI7zwID1QdnAv5tm7KzwWt5DN7I5voIOdhaysQOsSHJayrpWtNVGTm1Fn0LaXIQvrW866TMvrU237UDpey+n4CI3FybbpyYjeSTCF8uG1cUHGF1Z3C7WxiV49jlrodJYc9PJK4URssI925sq1mJcwqzOm29iLMuZOAC1BfVFXckeLl/qWPMvhb2M9/1SX4RzE4O1YO68q6lhqHPYw5hd3Ah3Q5u+gw8NBSobDcQO9x0HoWrGUxmJPGkv9yYPepS6ua/q3qEe3cDSN01ZznJwJa6Du61yXfJk6mD9tbvpcOuGDK9gGD+yxsYlGVgddNXE16Nb0nTvtXaxPehPPZ+l2DbSX1YccjdD2SqCTE+mTiDu67K94EiYJ9v1MylvQfrWUA7004Ra/jqB3wGQ777YxReFy0F9rglj4/hXvDTGpkK8iN4IeLO+DzhH7co1k2q5+8iXUlhQcx8PlfyDPYofQl0lCNSgZKM/7dbw/OhmEuue+tyibfxA57RuZOlBZYAng2fo7MDzxxBMSFBQkn3/+uZj50H/ts379ern55pvl0KFDYnzovXv3/rVyzSkBJaAElIASUAJKQAkoASWgBJSAErjsCVywG/SaNWvK0KFDfVOtmfnQmzZtKmPHjvUD/OijjyQ+Pl7atm3ry23bts331/Pnn39eKlRwftvob6GBElACSkAJKAEloASUgBJQAkpACSiBgkOAnmf6fTtubtDNS+KeffZZWbdunZi/lJsp1synf//+/s7z8vJ8y+Pi4qRvX3qcy1+lgRJQAkpACSgBJaAElIASUAJKQAkogYJD4ILNg+4iMzfm5i/j5q/mWVk4j6J527v5K/rgwYOlRQvXJOT2oPHFIKDzoF8Mqpdfn+686MMr3Q47OHzHB6BDJAT0IHkUdB95FfREeQS0/IuMpI+5Zl+cnLa47IS2ZR3PGST+T2w9bV5VnAu1qaBpMVI+8Xczr0OcP/YFt6GUsh/SgtKo26EHXWgqXKFycTySLW7ArlaiTVCE/ZDlsZ4sjNICbYXy7n6sd+cqbrUGc9IE9aqTv2/1L7yW/M/radtKkre3c5i/qS9IXuvoRPbWpjtJbz74u0AK+8LTaV0RpNsTp0inu/ZOfKbwa1r4BNlKbyNPej2qH5qBC1o4Xt3RmJKedLw3N8WCOsdQy+ek+bm4GMp/5mhixF5cHqeL6RC1S3L68sI8ZxybTG8ay5MSbf131W1sojq03dnbMb++KuqZ9OeFKe6lwyuNpHE/x9nX5j9iX7IYr2NS8lksuPEp1J/apwN9iWPo1ZWO7bD+rVpWlyYP8W5ad4ujttZE6x0PudGV6EUBPB7wRy6RdKf/ktYra7qSow19//H/c4L2MwS9u+wbl7b+lieDVZ1gwagH3vbroVPdM07k9YfT/DkT9FwCUqQ16vmFUNem/axI59g7zvl+M43Lj0tiXz1RisynBY1Js8ylBZ84F8bSdFHc5xwPr1nH2MnQ+P2ReLwD49ZDPrfztaCF3mciGXZjOz7ivHjBa9WUXuwwpNmt0FfH1Ti23icfuVSqDfVVd6wGfY/YgxIvlSEn4s4VLlKcBlN/8qTH0dzl8hyN1Uzqfq7VHVN4P+glIRHY15j0RbaxFw1udgtoaYNSnq0GC4bJeL9Opi/7CMEvhyndH/XX+oKO9LNEl76Y/4OVzoP+BwP/ldXRV9yvVJ5H6tprr5V58+bJiRMnfC+O27Nnj+Tk5Ejp0qUlOjpaQkNDz6M3LVUCSkAJKAEloASUgBJQAkpACSgBJXD5E7goN+insJmXxjVo0OCU1P8qASWgBJSAElACSkAJKAEloASUgBJQAr9AIPAXlv+hi3Nz+fmgP3T1ujIloASUgBJQAkpACSgBJaAElIASUAJ/OoEL5kE3L4gz06sVKkRGobPs4vfffy/du3eXlStXnqVS07+XgHrQfy/By6P9M4L+ycKCc6XOdyYBTox4E3c6nYye08n4l4F+K1qVN7kpu3krYf+drTkwcB5572LQe1c8YR22JZU5B7ftoS54bZom6EOTBnbdMgQ9bBLRC3t3/I2+xC5Ms3VPkiiPNkNJKmvz9X+ysS9yfdregvSbMX8Ud0vKfY/5L+qjvrY16hnOpZe9mhUOYy0S9eayLY35FLQZCtktpXke1qc5w+m7Ypirfgh1JO3nXvLehlj7o6/hVzhFr2yl58V69LD9l5hh4zNFX5Hf8TmyNE6hbTmYjr2spW0JcjjwfqaGYdtHabuTEzG/rjbqJjR+MunX8MW32PpV5E9vvtPmfFER0nR696f0UPJ2V7oSC37YY3UpYhpezeZMlEFjjyyr0pXOwdlO36Z9C9rWlTlm6f993p5wKjr534PDUQcuQV38I9QH70LtQjWZWndj3j2mn0VgrsRw1MfIg5pLfths9MtKUWwuwVNogbPjyXTxiKbrHL/XI7MR9lX4adRX0bbsfg7ztwyymsalVLUpE+2l410mBfMB9DDm6zQ2e6LdWlwu7ekcWUjjVJY/iSvL/hA1q0AaXIenY4W7L8swJXRteHr1PCgoJnghZC82z5NeVJyLidfTYbEvClna+Xro+7Tv1IH4nVoufi3U7xaE3k/mQD5E8Ps7vkYbm0/B7/oOMsvmvGiBOKZxTzegF57cLvdAfZh7QL3MNHrHjMtlmeDgcL3xptMi5MWfKGNgXenyCmiRv5BGWUPq+hfEyG3+2ASr5GrQSfIA6Pwm1IOef44IfXX/9g0bM2aMtGzZUswN97l+pk6dKtdcc42sWbPmXJtonRJQAkpACSgBJaAElIASUAJKQAkogcuSwAW7QTd0zNRqDRs2FHPj/Wufn3/+WTp16iSxsbFy6NAhKVIEf9v1a201pwSUgBJQAkpACSgBJaAElIASUAJK4HIkcMFu0F966SUJCQmRw4cP+268zQ24uRHnz6JFi6R+/fry7rvvipkP/eqrr/bd2HOdaiWgBJSAElACSkAJKAEloASUgBJQAgWJwAXzoBtomzZtkvvuu08SExMlICBAypcvL9OnT5d27drJ0aNH5R//+Ie8/PLLvhvzwMBAefLJJ8U8Gl+4cOGCxPxP21f1oP9p6P/kFX9D668Feoy8DPqoM5H2SPJPPS3oC39eBkLbhwSfnqksaCQuLHiuLyFf2VL2hTu9j5BPHSUyQtDYm9sM/XQPrV4G9dMGtgbdNN4xX3uZNdLd5iuRVeeFL23ORAF7UJPnDQyQprJuN6z/EaVEO/qjSEd4YdU00C3INzw1C9JSJxu10O9Jd5J9MiTH1kdstLEvaoh6WzDqKmGoW5BPHLdcJO1jrHfnf998O+bqkB96VDXM8yy7PckHvv8A1pcqidr1vJZJwFwAbYuQH5bsj7K4IrYvRl78t3HYy7hEp5525OARJ+eFJdhbWxzzp21bfcrT8Y92Jn1PpuOR1ArbXkljK8L11nql4bTtTte+jl6h06SUO/b4HKDjxXZod6yYziNv8K3C/w+ve8rn/tTJoLGjP3NiE35J53sV9wB5+Qw6f0v+Gzs4+g7qBm+jdscePzC4iDzmJ1KxbdjzqLOeRl2eru87QjAPc7rT4Hm/Lda2SUdd9BPUQif4/gGYJ6vu8hI23eo7G5sogzZlyZWYb7MLdQZda3YRxyarsX6xM5b7WVu2ryj51QgsDqX9pv0QHqs8fq7D7mTTJLtg8K029qLhKR+A3izhoGf3o4FN++1MNX6yXYs50F62dLE6Dn3gzwiOlWcFx15VwfomghfVKJrLvKjk2nV50VHnRRFj5BrIDZR1oPlngUI0torQd+qgiHbQ/jTR2VkyZYcjTFge9ChZDHqyjAN9vwwBHV+pDWjZgV9Go8Ue7yHyONZeYko96PnngF2wv6CbXapbt67vr+FPPfWUbw937twpt956q/Tu3VsaNWrkvzmPjIyUTz75RMaOHas35/lnLOiWKAEloASUgBJQAkpACSgBJaAElMCfSOCC3qCb/TB/DR83bpzvBtzciJvH2F999VXZvHmzbzfvvfde31/YW7du7dP6jxJQAkpACSgBJaAElIASUAJKQAkoASUgQhO4XDgkNWrUkKuuukrMY9XmYx55Dw8P9/nTS5Rwnnu6cKvUnpSAEjgTgRp4msem9IeqLHpmbsybzuNb3aKgNlnSQMtIfDS0aBw+KzxcbsL6CHouMf0Q5LvKl37d0HtgDj/4fHXu5K6YnoTbMu0/azF/n/ucqXh7Tc89uo//NcCmEoCP+gk/f1vsYWywcwPqPSjlZtILrR71MDJGJdKHHmHnx6kTStm+TBRDjyXz1GldnUdLt9GjmlEnf6/q73Ai5RfjDD9CM/7ITfgkoRyq7e/KFwQ6T0gWXYS5zfj0pdSehvllvVC7U7aZTAkCd5SeYg3eZNsfuN7GJlpcGHWZaqgbbEFd6AhqcnKc5ngQp7/De7FtUXpcPvo2zCfnoA6nJ2IzvsC8OMeXMiJtcUl92o/2pTEv9Nh4y8qYn51Kmh/PdU9RYkxPocpp45gekU4jDjwNnzTGbZEMR+/p5AgvrDIddfNRqOe5G+6lAp0DaCrLYjnNXCmypJYtuA4fM5ZyNPBt5cnoJ9qWQtQ+ixqUxMd1xbEsSXYdKiZZFC1M8kkXLLhhK+pSU1F//DDoSq5VhJ4qD98FpUJPOEssPpUsU9zj5zXNW0HtK6Fud9TRdDmWe+lisMypNSGdB/LldCwoRhuzjvKF3rP1ffAR99y+OHC/pMerB44/Ydt60RsyGvRpj1+XoGMEh+ROaPtsMxrHq3FHy9Ij67VkP7QfKdifkO9ksNjv/3KCX3olyRc0iB6B7yD/hHWlSDLoh9LxgjGdpqPrO8Ve0JdIDWhbVOJAZ9NUaM2kNeT/Lc+A7ryjA+h5c2aAHtKlB2gVSuBCELjgf0E3GzVnzhzfy98+//xz31/Qzc26+Ut6RkaG3HTTTTJo0CA5cQIvQhdiZ7QPJaAElIASUAJKQAkoASWgBJSAElAClyqBC3qDbqZM69mzp5jH2Pfv3y9BQUHy/PPP+x5v/+CDD+SKK66QnJwcn/e8adOmsmXLlkuVm263ElACSkAJKAEloASUgBJQAkpACSiBC0rggt2gr1y50vdX81mzZvn+Wl6rVi1ZtWqVDBgwwPd4e4cOHSQpKUluv/12X37jxo3SuHFjmTRp0gXdIe1MCSgBJaAElIASUAJKQAkoASWgBJTApUjggk2zZv5abh5jN/+PjY0VMy96aGjoGZm88sorvinXsrI8F6jnTb/llltkwYIFZ6zVhReOgE6zduFYXko9dZTpsLnvk2HyaZpaZY+U8ddPi2jtj01QP30V6C7kQRvajCY7Wg3lUl+wfZI0wQKYlo1MijG1sfYOlBJOvsCH0QP3nGyDBj/RKzg+khf9+U7yd39sgnhpBFpm0rpC1mE+Fz1wp03T1N01SHpNP3aa834hMhnV3Kn1wqHbUdNsNiLtML8BrfxyjWOJjC2KtVPQoihC6wqvifUZNKVXLHmY//kj1oc7+fZFKIdS3lyLCwJ429hzvBfrZSfqdGfbS5E1cz9ZjCOIC1tarzmMfZ+mqH2Ccwxi9lH1FaijUZIz00ta2+fJypbUIJO0s68J12Iuhp1n3JYfemPmTt+m53Da+GTntJkejuse+iFqaU2atwVfKSFClwuaIUpGOcd76AzqO5QWHBqDBdeQ73tDLcz/hfIfYRpeWVGacjx2Dt0CBZHdF4FOm07XoqLdIC/ZA1AHOgMkZDXmfuyC+kr3QuSl8ux3ga8w8x6sD+mEuvnbqJ1jtIqOd220N0sq5aNpLP1I7zuoQtca+RZXPeFmq9vjq06kbzGbM9FYeq9H/bmYd98Z4cvwuvfTRTpsne1gy202NlEcn2Q0cKc7FwevvGmv76D9GqkImqc+3Sb2AjJbIqBWhtVD/R+Uz6XgS0MGed/Y8OlcHmSbefgigKUS5c8/JLjd7BnnKdw20Ys7ysJJI7L1hWb+vk1Q/ylk7k4B14h+LjlIXvoJUhf6yiV/vND0c1B8mQudZi3/HODAC7Upubm5Urp0aXn33XfF3ID/0s25Wd+jjz4qX375pe8v6OaGftEi/AK6UNuk/SgBJaAElIASUAJKQAkoASWgBJSAErhUCFywG3TzV3DzCHvHjh3Pad9r1qzpewTevDDO/BVdP0pACSgBJaAElIASUAJKQAkoASWgBAoygaALtfMLFzrzBJ1jp+ax+DFjxojxp+tHCSgBJaAElIASUAJKQAkoASWgBJRAQSZwwTzoBRnipbLv6kG/VI7U79zOadT+oTWwgOcbbSBoRHU9bHMlDNrGkdFzhuNXN4VbJ18H9dLvLA/pkD1P5jm+tdDq2Fc2mXU7kD8yHcvl4WO4YD96+6T83zDf72WraX52iSDT4qO21BfVIG9m5JdYsI28gM1pYx2vprC/kbyXr7u13lp6puKqIqNQt0Aps1NxwSpnnuxbCmPui7N4NxduxPpt5N0+RL8CrnwQ67OKWM3zs4uT81XRfvO812nk5c1bYvs20b5WqMtmWT3fYWCW3kH7tTba1proNeI0hWyk6+hwN07C9msaWN2AfPlhMTZnomXkxb2TTqkM2u/wotj+4FLUuxpZXeGIjU2USadMXRp7aRlYL7Qunst61XGsH+lwW0jjfGchrK1QHPV8yt+9HfOLI1G3S0MtXzh6M0GtTudr5pNOsReGzCBNB/RQX8w3Rgnn9Pc0OIr1wuLiL6Km8SE893h2TazP/R/URftZnXGNjU1UiAZACm3bt1gut+/BBSFzUdenbU9yOHaknDMWfJ0swa4kHXVmK9TFlzbCBTW+RO2es2sxJTeQfo80jT059AYV5JAm+WhLu6CNDU1Ubh5ujDe3ERR0kwzQg+VG0N6VjDReKEPFXkAGyUtQGyfXgx4p6CGPk4aQF9kBejR9/6+UZZA/Irf7dQPZ6o9N8LPsBT1TnO9bLzNQ/g35/fRSgURBbhGO1940dNddRD6AvhYIjVP5FPJyGmNKFyCpHvT8c7Dpqz7/bJhuiRJQAkpACSgBJaAElIASUAJKQAkogYJEQG/QC9LR1n1VAkpACSgBJaAElIASUAJKQAkogXxLgB5APPt2Fip08jkz82K3EydO+BucWu5fcB4B93UeTbVUCSgBJaAElIASUAJKQAkoASWgBJQoNrI6AABAAElEQVTAZUHgvD3ogYEn/+hubqpzcqx35tTy30KF+/otfWibsxNQD/rZGV0OFaNlEuxGLs33HSdRkA+kOUNvlNf9efaNbZOn/DkTZNLcpeVo8mF3blJTv4bmH5UGZCxOdDzoYn8BaNpWpe3sCcZOb8pe73/uZ/gY64czy4cNft9NS5qg0bCyMwf7cUHz7Bi5G9oKbZv8l8yaxTtiPVk9CZNIaVsefrONTZTBHtSymJfFpKuRrkqavJ0wBewGrD0Wjrqa6+v0Ummur9fTm+tgfZ0Q1LHkI57i2Ar31sDa1KKom5AvfAK97qCv/TryNWSP+vaV2F+A64dvgDn2Um+jbYnCKXgltTm2r0jHLDgR8xvvsLrhxzb2RWgplUO1Mb++Euon6Dm4ROJ0mMbL985Y43cEXIu2UQn9HtcV2x61i9Bk/kEe9mqZWP+Dw7EYnt4yhF7zMJt8/fQ6DJlAY7PvFlyXEDe3PGMq1YY/hwsOjkNdKh11Og3sq45inrz74H8PHou1dA2Vg6MwX/Qe1EFsoD6Mec+NC5+suVaG3WdjEx1sjTqIXjpxJALzYT+hznkEdbVvUH9r23d9BBn2w0usNJ+FTaUl6rTyqCPTUJM9WjY47a+ha8MoZxyaXoby2KHroETTutYl4YLC9VEfSbF6K56gw+LftzkvGjGJviuGQlrkr6iLx6+DBZmxTUDLlFRH48WiKfm4z/Z9HJi43ulLhH+WkA7oWX9uwWJ//X8ET+iOgmOnsAT7a03A38dVBCenDxTkmE350fSzCXSu4pwJqAf9nFFd9MLz/gv6sGHDzrhRv7T8jMW6UAkoASWgBJSAElACSkAJKAEloASUgBIAAnqDDjhUKAEloASUgBJQAkpACSgBJaAElIAS+HMI4DMjf8426FqVgBJQAkpACSgBJaAElIASUAJKQAkUeALn/Rf0Ak9MASiB/Ebgme9hi4Y0nAO6eJcqoEXQl5ZLXrGEV+P99cMeWeKPTTACuxaZgx603eR/3j0BmouQz1gSyYj6r+r+BoGPof9ta+dm/pwJhoWCFJl5ABf8gHLEWPL65WBeKuyxC16/wsYm6paLujd5NdPrYj6nO+osAteKPKsVbXkGbVfklTZnonooZQD5glt/ggUB1gbqS+wl++xgx/M8GW38EkD+5bybse9lH6GuQ1iOf4f5oFTUaXdY/V8b+qLPSR8j32jyESxo4eyHyawkP3QAWiJlseMbv2439lWcPOSZdAxWtMH6BvtQbyUPck3a1jLutq3Atll/Q72vFOqmhVCvoG3/koZiXbR+ShFnKJdx5oI3vYbWxL7h/QReqjudrkdoWxptwvaT8PIgk500j+PZbzhJL5x/P+q7v0cd6ZrKvdRhOv5F6f0I7nzx0Q9jX8lz6YCVGI4FudR5uVjMk9deNj6J+YgXrS45wMYm2otSSrxJC3aiziMwATjXtZkRGj5hf7UyqaWNTeSOQ6Or00lilrmf0G2u8kzJz6PeQu/quMH6zme/h6WzUYoU+xcuWf4Y6Epk815M1ut2JaFcrtnjaPpqGEqHWz5zak3YjfR7CbggHOfZlhdpcD7qrDw+A9pupfm9ZTWkRdLpIhqfCgWZk2jHP4S0POO88CBMtkByt+DFP5W2pV8ivlUih+Zonyj4ZdLP8ZybFQ2KaOdf3+j0j/yxCTIFL2TPkrk+RjpA/TRZALqSXAW6p/QBHSH2yyr9tJMKSlUogUuCwO+6QT969KhMnTpVFi5cKD/88IPvpXEVK1aUmJgY6d27t5QuXfqSgKAbqQSUgBJQAkpACSgBJaAElIASUAJK4M8m8Jtv0FNSUqR9+/aybRv+RnXLli2ydOlSGTdunLz99tu+m/U/eyd1/UpACSgBJaAElIASUAJKQAkoASWgBPI7gd/kQTd/Ob/jjjtk69atkpfnTW50hv8fPHhQOnXqJGZqr0v907p1azFTwZ3P/5ctWwa7PX369HNub2r1owSUgBJQAkpACSgBJaAElIASUAIFi8Bv+gv6rFmz5JtvvvHdcDZp0kTGjBkjzZo1k6CgIElMTPTp9957TzIyMuSFF16Ql15ij9TlDdnMCV+jRo3Leyd17/IPgWer4bY0Qz/cCSHznsyF+s4yB3T4Izf49WfysT/2BV0eBz1KFoL+X3dCby+zWypCXhLJX1ejNuTHPLbIrwc/d4s/9gVkUi6euA7yvZx5zE3i+ym2L6MXyKPmP/Yzk34/2d0xZI68wtZ50eDe74IeI+jrb/p4FuTXTEGmEnQU8rICvXxSrJc/H9nN8at6S9Pm+1O+oBvZPF+h3YhpjPWjyGnUGtOSvMoumPKNjX0RWhYlYCzlN6DuSusu/EUtLLgfV5Cz0aYLkfc+nPoK/tzW+iIa9uGUjg7GBcnkr27nbMo28pgHEbPQn7GvVmGo2ddfm94DcOJOrL9yvdWHnrCxiYqhdVMOdcf87XmovyZv77/vwLxEoZ681uotZATflmlzvigUdSqNtSDalkJ1sZ5V9rd2yT/peMxua3MmehOl7C+OC0p9hrqrvWz5EtFRmE/eZXUyWnNFMsjXHeScFKbZsda2sYmCaFw756+vsOogrHfXt4NOqk5HsXbpYdTe7NPwKQJKZCsd8Lp0YuxwTlI6x/gdA7KOTpoB1NeSFFx5Sfo5pzamxcEY/iDm+F0b7Quh55zP53ewudxI56QkUsHNpB2ZvccRXhhaHjV9RYq0jcGCddNRP7kctWRY3eA2G3vRzMSuoCUB5Qj5FBYMi8X2Qp5z6YXfg88ucOvxD2TlJB363i34PTdIGkBehF4iItUhf1DIi59uzf5DIm6F2g7pT4OOkxdBT5P/B3q0TAI9RB4HPUb+AVqFErjcCPymG/R33jl5qaxTp458+umnEhJiv3DMDbvJm7+wf/DBBzJ//vxL/gb9tddek8OH+UsTh8KmTZuka9eTF962bdvKlVfST3xO+aJFi8R49X/pU6lSpV9K6XIloASUgBJQAkpACSgBJaAElIASuEwJ/KYb9K+++sr31/N+/frBzbnL6JlnnvHdoKelpYl53L1EiRJu+pKKq1SpctbtnTlzpr+mR48e/vhMQc2aNSUqKupMKV2mBJSAElACSkAJKAEloASUgBJQAgWUAD2wdm4U9u3b5yts2LDhLzZwcz//zM8i/WKzSzKRm5srb7zxhm/bixUr5vPeX5I7ohutBJSAElACSkAJKAEloASUgBJQAn8agd/0F/QjR474/oIeFhb2ixtepIg1Spn6y/mzZMkS+fHHH3272LlzZ/k1LpczB923P4jAGPSYlxu8Flb8+Go0wM6VKZDfL38DPU9eBl3cm7H01CdTnjsV+v47UHBdQ6Ud5KUZXVLuw7T0PfnLPf/SFNRTxXnSZtBGf9nJoCTozGFNQE8kT6qEkm8wG8pFxqF+Thb7FxyLcwzK3tJhA9H43ScejYMTB9K6Sr7u78sXFOuGuih6AeW49eOl/RdLR92L+n9OXmr8C4vt8oe+YHYk6gFbUA9xfMAm0+0Om59WwcYmejEK9VBmTL+jnU59T2mPHBPpV8IrXQ80WW3TaL/6x+K2PHgcNY56kdvpa+caHLoi5W37qJ42NtGBV1Bn4NATISvuCvLLX98K25clr/Zm55UFO8jnfZ1zPEwvQWHY1ywax4foGLTEcmlAHAIc7/c6Ol2LkEeZt60HHb/EPbiyCWhplebHMH+8qNVv2tAX5W3CBTOc42Myh+yPFCcLaXw8Tft5zfsvQYdd7/m7X8/+wh+eOQhvjsvJii3fxGE+hzr8biHmg+21RYLpWrHgf7G2zMOof9yMOnQj6r0o5VP8fpCGjmk55zYstpf6k8tvWof55aTDBmI+YAbqI/T0oHPeZDib4WtETBd+TheuovdA37PL2mukL4GXfxH29mcete1pP0OL2pQvOngLLshZhHolHc/CNFhz6KJ8r7utfaGv5wQvLsd3bIF83Eg8Rh3jlkN+Lc1lvncBnpTDZYW/Pm7YTf7YBA+PeAt0UdkPerCgvXIwXejGSBTUJ0s50DEy1K/bpuN+DDnN2O8v9QWVqO/jQhd4LFelBC57AnhmX/a7e3F2cMYM+yV1tsfbL84WaK9KQAkoASWgBJSAElACSkAJKAElcKkT0Bv033kEDx065HsRnummcuXKYqZkO9unV69eUq5cOQkODpYyZcr43oA/ZMgQ/1/hz9Ze80pACSgBJaAElIASUAJKQAkoASVw+RGgB9zObwdffvllueIKeqbtDF2cS11cHD0ydoZ+8uOit956y/+G9+7du/se/T/bdpo335/6GH+++f+aNWt8U9KNHz9eevfufSp9Xv8925zzO3fuPK/+tFgJKAEloASUgBJQAkpACSgBJaAE/jgCAXne53xXZ+b5DggION9mv1qfk0Pmt1+tzj9JM6Xa0qVLfRtk5oY3b2g/02f69OkyatQo3wvkmjdvLpGRJ/1WW7duFXOTP2/ePDl1KCZPniyxsWS4PFOntOx8jol5u/6p6dxWrVolLVq0oN5U5hcCoYIm1IHkC8+mfLxUhk2vL3tBH5FnQadEvA/anSo1QppB7kkZDjpA8DowWKIhX05+At1a0Cg6Wx6EfB951a8nNojxxyZ4KHEZ6PKCL58MEHwg6L9SAeq3dsd9kY5zIC9dbnA0Gly7yxIn581lK38BLTyh8DOO+dJUNnwH6482Qn2zs6/pmKLDK9F4eCX5e6xvQd7OlbjpQlPVC/QfjH2NikJNTkxZ+Rnml9Nl5PpnMD96LOqhn1u9v4aNTVSKtkVoP1c1wPoTOBSlFf/6GYeLwOsUHPy+XvEVA/J6e1xXTxweMr885oeglOW07gjXskr+2Oyy2LjI16gD7kR9OA31MbxcSHAW5tc64yfqMObKoCVViu3AfG86vuPpmHxfEesnkr9+ipOOdGITjib9AFmtD1KDqNLYIAMvLSKpmO9a2+rZW2zsi4iDHKM8rUto2yQA/e7C/tmqA2yHG2lHIugAZrSytSbKmYA6+ADqgBOog/eg3uhc93i7u/TC2lxqW6wf5p33k/gSFZ39Mgto7IozzlOaYFc1aFym0LjdF4L1V29HfaII6vBvUbd3zumFH2Nu53WoK3yIWrqR5vGyaSwWbMTvg4HPLvXn58IF1pu2PtQ5HqYKrdpCX6FSbsRaf18m2E39NXXnXPfya15oYesP29AX0VzxI+d9AgVx3W8CXXXmatAPkmd9aHe6MM78zl//kODF47h84c+ZYKbwH6KuhryKP4eAe2/w52yBrvUUgaBTwfn+99TN5Pm2O1P9+dxYnqn9n7XM/MV62bJlvtU3a9bsF2/OTcHdd98tPXv2PO0XG2beeDN/upkzvlOnTnL8+HH5+9//7ptHvnz58r6+9R8loASUgBJQAkpACSgBJaAElIASuPwJ/KYb9IQE+vPC5c/pjHs4a9YsMVOsmY+5+f61z9nmgb/99ttl2LBhYrzoWVlZMnXqVBk8ePCvdXlazvzm69c+5hH3666jXx3/WgPNKQEloASUgBJQAkpACSgBJaAElMAfRuA3PeL+h21dPl9RdHS0bNq0SUJCQsTc/JYqVep3bfGePXvE/NXcPJ3Qrl07+fhjei7rd/XuzULi/cX/1KP17mMs+oj77wR70Zu/RWvg36s5z256lSNlGdQnCz4rPPu0R+Dx3QRJQ50phlKhK++5NHzetqv7PLxXeoXkQIOJMc5zhiaTcAjyIjjNmkRE2XxNG/oiegRaZlLboWWwQeVjqEPxkTt5uirmOzvy2uGO8MKxqNskroD8UsFjEEjP1+bO+gDqJZueqSzh/DKu0lNQu/ksT/7V/BbKhR9x/idxHPI3rA8Y7uiSTuyF4Th0JIMf9eRHKBtjezQ8iNADsdLjRVufd6ONTRTwDeqvcaY7mUGPT3ehw32gMLY/RI/ANztg8xWK29hE8wuhvpv6lpO/l/UXzafHbe92+jZFi0v4S32Buy0lqa+kQKzlX7uOwydeZQL9zrUvHxPSefYpVMnGWZIkAE9fCa2M25JNjxmHXkl555FmkwlNxvzyjlaXpFmUetPx/Pw9W2uiiXeg7vsz6tdLo56MUla6x5DHMW231KHGCbVwQbGHUR+airpYLOojH1udO9zGJlp5Beo29Bxyt4qYf40GSDBdB4/TSRzkXHPT6ZpXfgn2nUujLWsO5lkFRcGSvFqLQAc446O9E5uihR9CqfCMnfTVIpvDsb7OZtTsMgIrD50zkDPdbIjAzq5MR83q0HOwJK5LCOiRUs2vO9Jj4cmCF6atZCMTsoENlJX+vkxQiPrLEfy5M75DG3993IJ3/bEJVtCOL33meshXfRYfaU8V/FkjV7pCvdBj613Fjl22rxWXN6FtEzkKeqn8+h+5oFjFRSPg3htctJVox+dEgK7059RGizwC69ev992cGxjmr9+/9+bc9GNeuGfe6m4+p+ZV9wn9RwkoASWgBJSAElACSkAJKAEloAQuewJ6g/4bD7E79/nZHm8/n1VcSG//+axXa5WAElACSkAJKAEloASUgBJQAkrgzyWgN+i/gb95kdubb558XKds2bLSvj29yfI39GmamEfczZRr5lOxIj3W5luq/ygBJaAElIASUAJKQAkoASWgBJTA5UoADSaX615e4P1auHCh7N17cuqq++67T4KCLgzGKVOm+Kdau/FGMmRe4H3Q7vI3gTHysn8DB88mk2rXO/05E8RKf9BxchNoFnHyFSwaKdhf01HW8xYpOA1LY2kObQdJJOg25Clvk7AC8s1pyjfvzQ2Qn1Yzymq2u31pUybqJwtgQcQo/KVWXARxaFYV6r2XMqD+uZJfP/dAS39sgkFz0JsX0WUp5KUBevmeIY/66KNPYn2JJqiz5lq94yUbe1GdHWTWbTEA8mRpFHrFgNAMcTKU7LFgI6yAXWdsoe2+9UUsIB/wcWtB9NUVLorl260105cIeMLJf+TEXrj5LtTsKf9bJuaPFELdhHzgZO2UvPW2fj8ePilVxOZM1IL8rwcxLXcfpgVoM5V2Myl/m6Npu6PJQpyc6tR64evXoeYp3/bTr90HXoH1JRw9GlPy4HZcsBittTKnJuZboJTQLFrg7qeXKnbC5utT7fEUmzNRxnWoH9+Iug9t6zHeNns6+xrWCLLtRzWwsYmG0ikmS/C6JuH4Xgg58QV2UGww6v09UAevs7roJzY20U1knp/TFvMvoJSi7+AC199uMkHOATb6eLL59+QnbO+p6OR/D9LArZKO+fQJqG/pC7pF+Deg6TUPIs6qF9I4b0FjoyX0JDKOPObz6HUm4Y2xwRoaT3W2OfloJ/bCBLrO1auK+132B6yXFDoIK++CgpEdQMrgBfP9C8bMutof+4IHMlATYpmIF5/4+9pA/WnTroXSibLggL9+pDT1x74gBmcGinsWPeojY/FngWFT3of2IwSP9zBZCPkT4pzgUzdALvPha0DTNyjkVCgBJSA0cbASOScC7uPtPXrQF/EZekhNTZUNG/BixWVmmjUzT7r5FClSRB588EEuUa0ElIASUAJKQAkoASWgBJSAElAClzEB53fKl/FeXsBd279/v2/OctNlvXr1pFGjRmft3dygx3hvs27evLl07NhRGjZs6HshnPGbb926VebNm+f7/yn/+T//+U+58sorz9qvFigBJaAElIASUAJKQAkoASWgBJTA5UNAb9DP81jOnj1bjh496mt1Ln89d7s305mZ///SJywsTF566SWJjeVnUH+phS5XAkpACSgBJaAElIASUAJKQAkogcuFgM6Dfp5HsmXLlrJy5UopVKiQbN++/Zxe5paZmSnvvfee7+bcTM9m5kzft2+fnDhxwjc9m5lPvW3btvLII4/4/rJ+npt0zuU6D/o5o/rjCyd8D+sc0fdDv36d5i7dGtHMn/MFL6B/Th5E3VT2QP2aBugcrZqI/uqHxHrYhpzmZ7e5k52iX66+JMG6kl5F/125R76G/G5pAFqaOf2txtpAMhHndr8W2+JuiNTAtJBHNXC8Y0L2Soc7+x0XehM2njYJ9b1okG8q30J+zUwywB49OX2ivyiwsz/0BcXirG56v41NlIJSyKK6kw7JjjCs/59g1N1QSpqjB+x3hBeW3YiaDoHQ0BTJpPqGqPNo2uVP7rH5mwba2EQH/oG6JNkpu7keU6/0FRzmUoS4hIZjfwmOVbfxTsxF0wNMae9hfjMNj9rvYD6gE+r+zrA2mclOep/j0zWLg6s5SS88jkNLGtIps4yO2S5aV1Ae9nelUz+d9rMjHb8q1Fao7/QQ7LsV1SfTOwqiS9t6d9yZpQfftjkTfU3vXh1N86TzOG77I7YvTlw73GzzC4/Y2BeRpbxFS8yv/DftaMkXseAoDeygKMwf+qvVi+iEvGu4zZkomMzZe5tg/iuUctPHuOBnZ0dNpnBrmw9/0sYmKvd31FtQ0itGRGi88HjY6ZxTpqcKzvFPK4t9R+JXhawiK3XzRKyXoqTxK1PkJzpGd578Q4qv1cJW2LjSctRbqW2Q09ZUFpuC9V+0BR0b/wroq6SKXw8WMsCPpO+GuO/8tSaoSu9xuUeyIB9PX2RjXKO/VzlYbvHXPyTL/LEJPhT8cmglH0G+oeBB2C3IpThNTv8mDYitcr+/v1BaVzbth79Qg3xFQOdBzz+HQ/+Cfp7H4vPPPz/PFiLFixeX+++/3/f/826sDZSAElACSkAJKAEloASUgBJQAkqgQBCg970WiH3WnVQCSkAJKAEloASUgBJQAkpACSgBJZDvCOgNer47JLpBSkAJKAEloASUgBJQAkpACSgBJVAQCagHvQAddfWg59+DPUr+FzYuQAL8eog87o9N0F3+BjpbDoOOFpxvdITUgfwYQfNeBk2kHSbZ/vokmCRbpBr1FS/oj6whffxtTZAiE0E/Q/3tIhPztIjW/vo+6Qn+2AQTx8aAlgFfo46ohzodTcjPyTrIryQD5fvOvgQK9p0rtaHtSFkNei4ZJJOkAuS7Ck7aPNtzGsJn1qtWHptpYxOFDUV9yyjUq1AK+UBpN4V2RY45vtPWZJdcOYf6RqTeRJ2bsSCvIepa6OV8/QZM93R94+mYSyfP6lelMM/qFfp18+zPsOKY4382mcLf2HwA+dtfJ69tz7dsrYnm/wX1XeSfDuiA+a7k3Z7tpJPs6eZb2pK81hk5TrEXti+Eeiy1n0jtS2C5hDv61mOO8MIm5AtOj8L8LGLInnWsFilB/UcUdyrIip030sl54cYBqMtQX5FozZWu5bF+CHFJcLgwk8q52DbG8en7Muxsy6Zz8gSdk3S84b0RNJb4fJSfcVvkJ7xeS/HhWBBG1wsau5Jcy9ZXcwa9WbrLpnxRJuroh1EnZ6DeS2OzrMPYV/mtU89j61Yn54URznXIZCa0xHzfJaiF1s1W/bIrnXq6NsBJYMp+muQUe2EefufKEjwGgVPw/SW5oddi+2xnZ2JqYy4F5WnW7PQdWDDVPWO91MN0Irhzj5uWLzknQin3Auvlvscvh6ajXEgie2nm5b2CF5tMoYtwRHWzRvtJr2ZjjS5JAupBzz+HjS9b+WfLdEuUgBJQAkpACSgBJaAElIASUAJKQAkUIAJ6g16ADrbuqhJQAkpACSgBJaAElIASUAJKQAnkXwJ6g55/j41umRJQAkpACSgBJaAElIASUAJKQAkUIALqQS9AB1s96PnnYDcV9A2uoflHRQ75N7a+bPbHJkgSNvqVgXx9mNnaqx/YHPLF49GL3Zomt35/ZCtbP96GvmgM6cfQqy0jyQceZ/eDWvrkafOmu5OXD8T9Cown39+bZGL9sQGugjyK8m9MSwoZqqc6v6/8lnx/n1LbGqQ7LsEFXRzfpy+D+yLTH8X6JdOt7kB+yEJkxr5qkK01UWWU7DnfTJhqur5Qr2mhMKe9Y1/0LS3i5Ex4nPRq0leSjiSNlkaBoZeMtQk4bKXeQczvwyl65SV3P7zSyZ9hfW/yv09xDv/8klhLVlvptB3zxdHKKctpwtJW9hUSJxu+FgEdHL4p3a/D0AYqJe7zp3xBxmHUq+h4Nvoe88E0f/TquzHvzoveifrqj6XSl0Dk4SkoX9Mxqv8TdUAW2KSGNl89zcYmCiZP+Z4ozLvbbTJlqV7oNJFUbJ/nWHt3XIu5InStKEtcRhXF+qHUt7jeelP6MdbDOcnnEPm+hScfL9IaOwvE7w7JXYx5mYG6I9W72Xdc4cW3kv64Ey44/jbqe1F6E23jJ8qRdA7JwUZO0gt7fYmajolMxfRpX5k0VmX3G7bBwT42NlEJGukl6JqamoL1vXFgVxVnMHmVW4UunMOi/O2Hj/jAH5sgm+YHj5c2kBfZgjq0NursfaA7y8ugK0grvy4vx/yxCXYJDuwSghfV43SBj5d20L6zTAA9r0McaFlQDbWqS46AetDzzyELzD+boluiBJSAElACSkAJKAEloASUgBJQAkqg4BLQG/SCe+x1z5WAElACSkAJKAEloASUgBJQAkogHxHQG/R8dDB0U5SAElACSkAJKAEloASUgBJQAkqg4BJQD3oBOvbqQf8TD/YL3+PKn0Kv1hjykf0g2/z1V5In8SgYdz3vpqAZd7igDzxQ0LOWG0EGzHT0vNUQ688rIs/4t8MESfIA6IHyPOi5tK1NyAMHxZ6YS368QY5/fkwHNM+WW7AWmj9Ic4snSznINyZ/3XCJgrw0QE6SaH2FA+VbqI3vjj7Bh2YugzzPgw5JT2Q6c6ybXD/yiY6XBrbJ1Ko2NlHQIdT3W4+hLzEd06d5WKPSoGDbdSBlluOfHToDcwl4uCVmA+ZHNUY99NUIXBBjvda+xBJMJ3W3uhu9WiE52eZMlEE+8fAjmAefr5c6TvNJP+4gNi37OPNks589iX513Z4OQQ3yP4+6Ardl6ELUvG1S2ubDabt2ptqcibbisJZdRTB/UwLqABrWebMwL44PPI8mBH+XjmdParqG9nsfWlql1XfYYDO9H8Hd9pgVWJsZhfqIMy5NpuxWzK+rj/rftC1vYlp6O7qHc+zN4gE09lo4tSYcegAXHCZddCfm3dPZl3Ev/7uotjBpGg/exQM/dIrxnN4b6Ly4xr28R2FXPA96elnMf0Hr+pjerbAAyyUZLc+S7mx7BHvvy2PjWJQyha4V7jnjK61IDb4gvauWs+AbJ/bCIu5o8HSQc1KYyjk3m3/t5ysbmujplHmw4PkanUHLfY4c4R4Ab/m/ajtJL3yMLy7FIN80ZSXo2+l77X8JzG5n8JWTRGi7m19YMpkuXIEnoF4K00DPoPq++HMMNlZ1KRJQD3r+OWr0Y0j+2TDdEiWgBJSAElACSkAJKAEloASUgBJQAgWJgN6gF6SjrfuqBJSAElACSkAJKAEloASUgBJQAvmWgN6g59tDoxumBJSAElACSkAJKAEloASUgBJQAgWJgHrQC9DRVg/6H3iw5/wLVja4y2HQY6a3BD2iF85NPkzaOnnyqDUo4+RE4hLfBT2yw52gZQF54F5FY2i5R76G+qKS69fRNC/q+w1a+XO+oD1KiUfPWnHB+WSfkt3QYHjM7aAlYZ+jg5zYC2eRn3lRVcgPm/k+6K3kI58Z+xTkZQpxlVSbH1jPxiaqmYF6WDjqSihl9RFcMJkMspPod6OdnfLaqx3hhZl1URfqCzqy53LQaWjVl/DrIC0Z21Hvdby+1UphbhH5RpvPiMSCXuhvlxxMSxbq6JKok53TYgLNNd33M6xtfwPqBT1QH3sG9VFnv0zmZzpkVzt5HsazcRhjx55aF4aLeB5t1jXIu+u8auG0VwbIXuw7j47XEfLuFrka67uRv/oJspW2dPy0Yxpj21vJQ9yEjh8f3xw6/JMaYn99adsPOqdBAI2VLypg2xj3UuClNhfDfFM6Bpj13llAl7085/IRQN77UdHY+vGfUUfQtvK4jozC+jTa7xbOJXclbdcosiQPdc4JX69FsG/3MmUyec7xNPprGsxljpqlJz8V6DJ2arn/v0n+6GTA24JfW5JCHGvgpUiinW1J3kh91ydNY0l43UlPYoP6L6Lm/qOc9E/OnOhmcVZVJ+mFj5G3+h+YfmjUMlhQWfC7I4TeAzNImvvrhwu2HS6t/TkT9BH87i9DgyuA+o6DtymIDJEXoL/Rcr2j8SQqJzgAdo+hLwc+p750ujJhx49wQZfHUau65AmoBz3/HMLA/LMpuiVKQAkoASWgBJSAElACSkAJKAEloAQKLgG9QS+4x173XAkoASWgBJSAElACSkAJKAEloATyEQG9Qc9HB0M3RQkoASWgBJSAElACSkAJKAEloAQKLgH1oBegY68e9It5sNEHLoKm5MGCkxUfpslts8h3tkqssbQTzWOeQ0bQYEFz5gky722QCNjxCpIMeqZMAp0trpcbfeB9yFM+UcpC21jByY2nyDjIj5TJoGfK/wOdIUP9OprmUF/azPXWeWU1/KW+oOpM9G5vdSd89iqKe7O4u58BxPUDsYbKNULePLehLz6BS0LJKErT7Mp49CyKYHt3fIzhHZPquK5/0bo6VcM8ezm/x7QEoGdRwp6yBVkv2dhEIX9Hvb8V6upkOt16C+arLkJNm55wjU1Hkee0yrudbNKLJjzwNug6eSBlM/m8Y8iL3SEU6//jHIJW9rULJ4vYgx6ObVcVQt18D2pvsMFnOXk7WznrXke/Jm+SDk0lBU9v+Zr0LXR8Q3/E9u+Qd/+utTZ/iPzsxb6zORMF0FzTKZUwf4K2/RBeLiSIuDaMte0DBtrYF9EwziGv9gkaO2VrY/uMHNQpdPxTi9p8JcoVc46HqYr83NaaKIWGfRHar0gsF3G89r6Ue/mPxuLIyqjZv56JaSlOYzHvPSwIaIu665VW96N3Spygc+Z6eo9DAF3H9tO4XkbW7b52Vb7oq5/tgmR7efUtvP5jmzNR7w6op/A5lYV5+Qx1eA/UGYmOTuruCC8MJkg/4wEe+dgnUD/O+W4wicxhTSAvUXTSpjrfuSPwYlKO3o3ivvPFdNpN8AR+dk5JWFfVLs5A9jJbhU6EkU79VT9BWyl0BPWt7VDjqkXWhGA+1nmhAWZUXSYE1IOefw4kfb3mnw3TLVECSkAJKAEloASUgBJQAkpACSgBJVCQCOgNekE62rqvSkAJKAEloASUgBJQAkpACSgBJZBvCdADafl2O3XDlEC+IvCMjIXteXYmPXcYhI+Wjcm4E+o79sZnKBsJPgbX1nmUPF3wAcqJrzaFvuTtMNBNF6wE3UH2gx4mD4CWSo+i3mEfg+PHwidKHagdLKtAJwo9vyn4iHMcPY4vHdzH6UW6LrDPLW6Wl6FvWV0GdP3VuF9JzZpDfuDquaDDBDkdFnzOdY24jy2mQlt5gR4zD6dnXHFTRIZhc+lAzyXfhvnEx+2+NaWpcNYMpWd7H6PH5UvjWJQsfFxTKiMXEeeRdm8zljvljwbhI+3J3+J2SvnlsCCdHpmNOILHe29dKJct9Ihsq09tfkKMjU2UcN/bsOC/oLzppOjx3HvpkNS7HxukYXeyzPn2W0yPy7ejJ1b3Fsa+wg6ipqElSVRffzfWby5l9SH6Nfmq0jZnonJ7UO+jp04x6z1+S4+K32VPKV/poSjbovj3NvZF16PeQEwrp2J+Mj1duxDTsmAGLXjC6uW1bGwifuycp8kLo/2iK660KIT9LaRT7tFkm88mxoHHbM4X4VPEUvU7zAduR728A2p+ZH65M91YL3qMOPxDbLv8FtSvOePUZNKdx8aNrkyPdnc1C51PhhN3oXHZwsmZ8Eg8LaDz4D3i1pPHD53fEU5+XWPsO+Aq1A6ikwk6BvLpFGxwHK9rGXM/wHzeIKuDm9nYRF2ci54nh8g7kI/rfhfoBjO7gb5qxOOg35/l+Ai8TNwIe51cRDawNVIT2tZ3vutNIknIN9ClCtQ38R5qdz9bxX5f+5a73IrscktFrrwH9UfdUZeciTqsC2qhPGVVKgElcOEI0I8GF65j7UkJKAEloASUgBJQAkpACSgBJaAElIASOHcCeoN+7qy0UgkoASWgBJSAElACSkAJKAEloASUwEUjoDfoFw2tdqwElIASUAJKQAkoASWgBJSAElACSuDcCeg0a+fO6pKv1GnWLuQh/Ao6qypfg94q14KuL+tAJ/3HetRMYth9dSA/QvpZHeMY+czShGo2d06RY/T16ofIemgVKGjmHdnB+uUDF2BtrpSHtqGCzsFsmi6uvsyC+iTyvz8taHp8HqYU+wu0Pb12IORF0MzZhqZROyz4+8i9pN1p2QYLumnHzCQDZWxlWPfo7I9Az6ZpeZJeJ8NlTzQWl3OmlOtC0+SFCRqk4yPawLpkbGvUudh3wsNHIX8nYpCMBCd9gxOfKdyLC7MOox5GQ3NcDublTdQpdqhJjW8wF0vIcaSJ8PRiYeSHP1wE+1uLh0xqO+bcV0ti7YAtqBfURl2PXgOwi9bV6gesp1kVpX9Dm38GD5ccor6uTLG1Jgo8gHpCW9SseDq6kg6nJplYHVsa9WNkb72Dti2NvNur8FIi0bRvPzvG8SvIS52INl5pRJe94G9x2+rdgfrrOagTyYx9fMgQf0GJ0aP9sQlo1bLbGRsmX4W81WaZ+4l0hRcvyMYF7vRztajvCGK+gZhfnYx9BUahnk/t3Wn0TGWAM+63uf5kL/c32q9Y7FruTqUFm1HPp5My6le2/frG2HYlefHTaFsiV2O9/EgvLQgZjwWlaGNci/riGVh7sAnq5GDQI8d/AjrutUagZW8E6p9QyjxHD6OT5D+4rqoJuKP30Hdo/OTWTmde2DsLdQN82UKLr+xFeOWM5VAb3aMV6A8yQcqV21EH01iVFphXdfkR0GnW8s8xpR/V8s+G6ZYoASWgBJSAElACSkAJKAEloASUgBIoSAT0Br0gHW3dVyWgBJSAElACSkAJKAEloASUgBLItwT0Bj3fHhrdMCWgBJSAElACSkAJKAEloASUgBIoSATUg16AjrZ60AvQwb5UdnUgGU0bv+Pf8q5d0Of3njzuz5ngJpon/f3u6K/rN3MG1JcSNGt+Sj7xpVLJXz9YNvhjEyRKGdDvC65LQiHtTepMegx6AaXLNVgw1vERRn2EuV23gi7eF99nkBlKfsoBUC5CHlbpZz2KvsryTv1hJzYh+URHkc1z6OvE4QHaz2k0aTfPq9t6pl3hEhuaaFQP1L3IDznf8TObyu7kd/7fK7D9UPI8Zzle7vKEZP9GbPt0Q9T4xgmRhbTuBBwusoJ+Ff4Px0/9z5rYd2eymBbJwXxJ8jc/SvvZAcvlvkRcUNj1ndLQyU7F2h0VUVf/DPWKm1FH0bZPoGM09j+2PvNGG5voH2QEn4Jp2bsfF5SZj/qLDU/ggl69UC9bZvU//mFjL7oalEjQW7jgRHXUhVNRp7VGHXkcdX/n0jOOjge9ckLoMiWb6VpSG+3Rso9OwRWlcN1DHJlMHnF6DYd0DXaKvfDfdP7fSsfoU9qXIDoxTtSz/e2oYmMTpZIfPua1SCwIS0N9jHb0RCrmuf67720+zjnZvaWhdP0eJC/ZWi8qJDmgB4/EyemHx30A+cKCE8wPbubUr0YosbIC2k6JeRS0JOBB6iOrID9R6oAWeteKfHqnzW+xoS+id4zE1sb8FOe65Mvgppx+omBzVZcBAfWg55+DSD825J8N0y1RAkpACSgBJaAElIASUAJKQAkoASVQkAjoDXpBOtq6r0pACSgBJaAElIASUAJKQAkoASWQbwnoDXq+PTS6YUpACSgBJaAElIASUAJKQAkoASVQkAioB70AHW31oBegg3057uocdKU+1yUX9nKQoK+7nyyA/PgYMjWT188tZt9fcUl30/Ks/AW0dEYp876jBSgfkh2wYFpMa6vdecm9pcPkfZvzoo/IpLqGJ6clz6rwPLwlsD856hiRq8XAuuQnlNIWdRJZzOu/WQsLcsmUXJ58pe6viBGxCPkjZZPj6/TWknD/IljXAbcvL+N6b01hMlo55XVnnuQWh6ArqfEV6hYtUa9Ei6oc3Iv5yPKo1xCGOmE2z/Ne31jE5kz0BW3bXc7rCkw+ebv51/mQj5jnqv/G8RFfg9Zc6UrbPZs8qOG0bRnkWU2j9uVTne3ywmcaWB1L+1WJxtqWyrbWRA3Xov6SPOx569djAavWre2SZcts7EWFrr0WdJmDIKXSMtQB9E4CWYx5aUbasSgnkJ+d30+AVzmRNHr3wk687EkFZyyZtSYE4bpjXM7k+xYat0klsG01OiahazC/ogvqBvtQv+6Mh74bMZfgjAWTWUDn7zi6DkbTpSn5c+xP1jiec5P6wMnf4MReWH8EXgySpCwUdJb/gK4vjUEP63wbaIlGCc3/irmmA1bCgjVSFbT0c6CZzHhMy5z3cEHKHairjLW6/GQbm4iYC42HrB+xPOzLSbigy+OoVV12BNSDnn8OKV0S88+G6ZYoASWgBJSAElACSkAJKAEloASUgBIoSAT0Br0gHW3dVyWgBJSAElACSkAJKAEloASUgBLItwT0Bj3fHhrdMCWgBJSAElACSkAJKAEloASUgBIoSATIrVSQdl33VQkogUuKQJdY2NxBoE4X44UMk2TVezrBNSma6cLL+TspJ0f9sQmGCPqfi8s6yGfOo0l+Y8homoDmzGkRlL/O6S7hhCNERkg70FKJjMA7XJOpV7oDyyWMjKTTyT/v+mVDXsDGbZ4CPb8kSKl/GPVpqht5zv8TAiWj/mo5D90CqdPmYE/qvAgK6m8HKdFRqHujlMjmuOC2ZKsLY9cy/0mbM9GbKCUnCRcUovmgw+l1B/uCsV4OWM0+8G2lbc5EnxVH7Wy2L7G8IuZbWaS+xEEaLlWddefRsB1Ac6xLKva9g7YlnPbr1nCs523NW2DzR+gU4PngH3G207QKcMepp/NG2L5M9AXK09WyZacv+78lOQ88ALlK62eBPs1zTl5dfjcDzy8ux213zb6zsS8iDm/yn002Yv1c8lPLx5g/cDNqd92ryL/enMbGjFBsO64a6vSSqFv9gHoC1Ue6aXpvQ8xb092sd0DJEF37HsgnTwUpfFmUHdhfYEI9f4NRCT/7YxOsFjTu76F3jMxrEAf18+iclA8hLfXnrYIFhyXAr2+jk2qPN8u6+1kzh86SLng9Hyh4oYvv0sZtLjIT83LFZJuvbENf9F4tWND/wW9Ah34OUuS4es6JiEol8IcR4K+CP2zFuiIloASUgBJQAkpACSgBJaAElIASUAJKwBLQG3TLQiMloASUgBJQAkpACSgBJaAElIASUAJ/GgG9Qf/T0OuKlYASUAJKQAkoASWgBJSAElACSkAJWAI6D7plcdlHOg/6ZX+IdQddAhNoXly0/ok8jl7vOMdYGEg+wc8EzZctBD3l7zr+dbMJSSObu1sigXHrQec2uxa0rE7166qyyx+boKygcXRNjRaQF7RXCk2TLpJC5u4OtbH9/d9a/WlNG5vopjmgW9wzCPTKmbeAlkqLUJPHVRCLiHuIyKO6uRJ2VYf90bRbwv5omvM3g7y82xy/bJVtuK5tVVBHLUQdQO8zGEX72SwP6+vRvNrhB2y+KP+avLzNmSgrDfWDznabzOxUzK9y5jk3mV2FMX9zqtVh5J3fcpPNmagzWnXlaxwOsqIT1rP//fBezM+LsronWW/X1bA5E9X9CXUi7VezmZiXgai/+AjPOcyiql8Uz8fgvpgPmIE6nI5RhjuOTenyRtig7peoHZVF/ubydHy/ynSKvbAyrSswA/MTb0B9736r/1vKxia6m9ruIA96c+fSYOoT6ph/7eeEtVr7Frb7weZMtMHhdA0db2mItd5LQPBD+y0/PYf5T2gS9htpY3c517I92PS5eJy4fpA0wYKZBCYYr/eBXfGanCtlsH33KKv5+rzDpkzUMXE5LHh/WCvQQpdUeXw75qeR0fyvY20+a7KNTXQrymg6p5J3YV4+I92VtMrLjoDOg55/Din/aJB/tky3RAkoASWgBJSAElACSkAJKAEloASUQAEioDfoBehg664qASWgBJSAElACSkAJKAEloASUQP4loDfo+ffY6JYpASWgBJSAElACSkAJKAEloASUQAEioB70AnSw1YNegA627uoZCPAkr1zS0r8gVvr7YxOECM4fO1HIzClkQpYgaC8873n6Ecz3c9qTl1qOYWmb+BWw4DBNurxGwiEvUh10fdkAOinUMYa/ToyORkKtBOEcvXLiNcyH3IE6oxfq3BDUZY5aTf7W0ya2LmtLfRFZL1+vjfmehLirg9hUjnZ25eti2Pau/6AOIKt9Ah3+67/G+vW0L+VpW6ISbP0xxyprloYQ8r10/MsutW1NlEVe3oPkaa5APvLoYNt+9XYbm+gRYvoEvqZBWv2E9Qn0noD/0q/848n7W9KxhbfsgH19SLWl6HjlfYL1HTqh/vAL1F9di7qkYyuOmou5XdTXLlr386Rp06Uqc5qJ1wtp8I1/hceor2DS9LoLEfLx96/t78oXjEMpQlbs9s74WkhjKSkHG9c/iPq0y9pcOn+7O+ev13Q+7cvdPzr9rXZiEzr+dF+Gjj+9BkRk/PfYQbdc1K/h4KuxuqM/nyIv+WMTPCf40olt8DIMkSmxj0L9yCk4+PiaGy8OZF9L5/o/gXa0r3Ph8WqbSiKsqyi9c2Sp0En2TBTUn8ap1nCbb4cvathG7xgoQsc/YpdtaqIQuo5hVtXlSEA96PnnqOIVLf9sl26JElACSkAJKAEloASUgBJQAkpACSiBAkVAb9AL1OHWnVUCSkAJKAEloASUgBJQAkpACSiB/EpAb9Dz65HR7VICSkAJKAEloASUgBJQAkpACSiBAkXAMcoUqP3WnVUCSqCgERhLXsBhBMCZZ3u1LINkYgR6EvukOyZir7I8GcXzJA/aD0kvArqcoJm37njrFbya5uQd370HtG0mu0E/KzeCHi2O0dfLDImoB/mkdDQiNs1e6c+v6VLUH/uCZmRKfnI15gO6o6b9Inu8SPhkrD+yyuq1lKPDJWmRttaLut6cBrqnM7e4SSwnX3l1yldw/ZdfQVeSh7Z9EcLC3s3CeHhFtmN/6SVRr7/V6nqpNjbRzuOo2Q8t7nZ7pcOqYf04yuckYT7Ayf9/9s4Evqrqat+LmSCDUhWHUCOKxQE+rTKIWgG1Kop1QNRaHFBxoFqs1cgYZoxD5ZNaKyqitFWRqv2jqLUCDhUQnIIDiiIVHKKIyoxA+N9z+XLOflcIBAghw3P9YdZ71tr7nPPsc2/Y3POe/dIRmntshdPuvL0/OsvVn+uY/789tb+LAy//j+9pbo179sKy1Zr3nvNHv9J8tW9V+7/cNA6OdWUnrd1rrNPuPA7rqfmLVdpDfmdHJJ7zdOmsxLtd2y0W/8He2tnceqo7BOMVZWov0Pwv91O9u3vLPh2khwRxFLasrRtOde+5Z5/R/F1XrJEN14Ue81TmLLVTm52QlE89K4mjqONU1bb6St3wzk2qnRXbrtTPUDN9EEAPSxaz7+OeAdLn9iQX7aRTj76yr6FjnhU9oOepom3MYtFNbL7ofGucaPe5k23ad665vlu5i89hscbvJ31H0SGJ1z6dCN8HbnyzJmnTVW1Vf+SuJc2iIACBsiTAN+hlSZt9QQACEIAABCAAAQhAAAIQgAAEiiHABL0YMGyGAAQgAAEIQAACEIAABCAAAQiUJQGWWStL2jt5X8Uts7Zg+kL73/YPxEc3ygbHMQEEKg2B4Z/oqfTTe2ib2dtxfr5bA6iL6e3Uk1odF9dGwc15E0XXtlqih9iRooeZrsvV3zok+Vvd/dJPJKl05G/1PMfd8nhBQ2lQ3fRe4AJzt1CGt4bee4i0tXz3b7jN3b5qfKr139+oeoPeEmu73a15W5ro5eOSOIrauNuEHZYb/a3df+su7TdkjBd909kiRUwWZdbI6Rfd0lUZ+2rBk+5W8LPman69XmqWdXiS/7vemWvuDmiz95LaKPr0YNV7fal6sbtNebZeDjYmKD8siDcV+tvll7jbdXdzb6kZ7pb5tu6W52UBt0bBXcDRvl9xl9rh7g7mBm75uFeSu8bTh56lbznL799fT2natFjXevXVOI6CVg+JNPur6hnuVu8hbl9NtdzGuOXMwvRD7rbji92t3j+48W20Pmxt9pbjcMQKzftl2ax5kp/jjqvlsiSXjv6fG5RLl2jBiyrN2TFs5R1asN8NiZ6ThOmohdP/1Vu/bdZBWjDKvVFaqa8gI6+l1J9hyWfNY+1+ITmbobKLvSIb2pu+YdeYfo4Nyjxd6ocs+rfogUNOTPTA5PdKtLGZ63u+X0ZtSGbSNoo844Nu1Pz+7hdE+D5y18oqbWl1Q/9DKlfNXXvm1xN07ZGVjwDLrJWfMQ3fyuXnqDgSCEAAAhCAAAQgAAEIQAACEIBAFSPABL2KDTinCwEIQAACEIAABCAAAQhAAALlkwAT9PI5LhwVBCAAAQhAAAIQgAAEIAABCFQxAmriqWInz+luJFDNalsd74MCDgQqG4F+zrScqQbaixYtjs94kPNpH+KMgHPzdGmbDLsqbhsFOcESP5FuZn+LfsSvZan3XLEvZ8XMmTFJSge30n3bBQWSN+dxPNQdu9l3Ur/Akl8DN1/5guT+Y84gK1mzya1u0S0XnKb6gKdUf3uK6hqB5/1n6vP0S5vZv9Ufe1tT9ce+8Gv1nFebprvyS59Z2Nz5eJdmaduMGqrXz1PdKvCUR5lTW2g+ccNu3L4wGONdO2it9xD3bKP5r5wn9WVn1T3ja63f1T1y4NnlSf7ZhkkcRbOcR/nX7tJq/JXWTz1KdcfPVL91qOqn66oO1Z9CkYpHuWOb7t4y7cZqgzd++1vZ0HjYMNFLZs+Ode2j9MDfmKd+9Z/8Q9t6z/mzeXFX6eC8VqoPdce6UNOinuwo0vKc1foVTVtNN/7+7T3VXQ+HJx9rtqtapc3aauc3Xh6+Kczu1bQtXeY2BP72dOabG7Qg/IjN0pS9EiZTuTdcfqJebNVtkRQU5OnDFlbZHMk/Fj7nQ5ua3acX+qSCY6TtJP/sjYHqSbcLpdwG7nuibrg1kOP1c2v+Iz8NkqnQjZe5a8u6uc/Q6k9o+/Uqpx6d6I5uvN8bfXqSTEWNHnlatL2kEgUBCOw8AnyDvvPYs2cIQAACEIAABCAAAQhAAAIQgEBMgAl6jIIAAhCAAAQgAAEIQAACEIAABCCw8wgwQd957NkzBCAAAQhAAAIQgAAEIAABCEAgJlAzjgiqLIEvbL7l2hVV9vw58apBoIuNkxOddLVI+6JfaFQ8RZK5dpjowaYrytYu4in/h9S3Dtf7lsz/ieaBOXfqXKl4wnYXbXmab2lqDJ2Tqcc65+oDtX0/bW+tWsT5tXnqSZxsw+JcFAy1F0TPzZshev4F7UTbnDNVZy1VXSfwnX9+peY+dWuuN3Ru3PFaflKAMJ05R/MrP1edcVaipzk7bP7KJJeOXD7P+cL/4nzDx7n2z6q11wr2TPqvXi2Jo2iZ+2fzt13fP3MIn/iJtr+4hmr/GIGFrYO866upO25rENRG4WeqOzqP+V1Zmj/iSdUWPKKgp/Npj1mttY8tUO2stvaGu1x2sT9Jg31FmT5yIPCju7K03KehXvftN2jVs475Yx9p3g5wOhiTa13KDYHZO1rwpevr4/qan9NItVuy23bbNck/9OskTkcLVLvhtaUuf6N7T93217Olg4a/UX/00jC/q+Ys631p27bP96JPtHzR60xP9HHTN8Yx9pjUj78vIO2vw3Xu4hsuTc0aO53hPlxy39aCWw9X3SeRnbor1SkZ6kHvMXlaUpyKxmZ3EG0rfiH6yUtE2pkPq163a6I3LE/iKFp6n36+f+vf31qOggAEdiKB6jtx3+waAhCAAAQgAAEIQAACEIAABCAAgf8jwASdSwECEIAABCAAAQhAAAIQfnKxMgAAQABJREFUgAAEIFAOCDBBLweDwCFAAAIQgAAEIAABCEAAAhCAAARqggACEIBAVSBQz9RIOrzf83La/ey2ROdclcSpaORg9V7/0/4h+V/ar0QPscWiw7XGo0Q952FvMG9WXL/C1JT8K+fFjAv/L5hjTWVT9UWzRQ/pp8fSf4L7d9k5LeL6mnn6K6GBvRXnoiDH9hBd0Pwo0dZHvZldnD9+Ut/jtP6Q7olef34SR1HtR1X/qPu2ds7TqtVmwVrjUareMa4gPLWHNNfzUtV+TfYjnI3fnAXVvtf2G75QPaN1oPOCOBU+caTqi15WXa2V6qEqzQIPajrl/NLLgyE+WB+lYLaX68z5wu0EzX/gPeuatqGBzz9KvRvkx7wXiFQ43a0HndlM869nqHZXnr1z2GFSMGfcONFbI7wv/Hfu+QW9nSF+X3fszh5vnQuSvdcM4mjrcfr2tLvc+Nf/LGkbRT9319abmZofH4xvOvNGkr/V9b3e9VXjgaQ2Hbn629y1aHXCCznlcR6/QjuoE7xH3z9Zcw8eInpmjkhrM3iqbGggTxGw1FtSL4ha5g620StJ+9buwm38ZpJLRW0X6YU+c3iW5O1id6FnHq75OSptfDKoU+45VpMfqhw7Kvn8TWeOfE4LftSL68z2mvbv2R8Dy3rNv2htowNVoyAAgfJLoHr5PTSODAIQgAAEIAABCEAAAhCAAAQgUHUIMEGvOmPNmUIAAhCAAAQgAAEIQAACEIBAOSbABL0cDw6HBgEIQAACEIAABCAAAQhAAAJVh0C1DalX1Tndqn2mixYtsqZNm6YhLFy40DIzN5rXpk+fbu3be2NT1WbF2VdCAg8mPu/02V1aW06yp/011qtMvZT7m5r3hrRSz/nAvH/GbaNgiB0v2qyu6rud7rUgyffMSuIoGvO26jud//H6RZq/VU2p592kxtEW9oPUD+7ZJdHHfJHEUXSxMrL7Gmr+ih9VD6+v+huVLUdNlw1zuh6d6NOWJHEUrXeM1tTT/B5uPL87X/PO2mn5d2q+0/WJXpiE6ehbp5fcKhuannuT6IV6WvZCO0nbSbrks73ysyTvPcNjXF/m7K+ftknaRtH+urSxveV830es1nr7KNBZQRyF+qgFc48csLV7aX0td3m8laX5Xm4IX/tPkHe+bjszyKVCN7p2u9vXo2pBtjdenS0dND5KXerLguza3/wmUGZHnpS899OJLEnbgiNU7++O3Z/3Ee5t8UKDpP1Ja5I4ipo6Rnlfa/6qPVU/5sfTGeY/dVz2/zRo/0kQp8L1+6uu8YHqcN36KNPQvf2XPunq192hG8YFgzo58WVHRW3lQtRmkTrJFMQ6t+75LXa6NhrgQLZ8KslXvyGJo6jrS6r953PX3TU/ca7qCd+r7tZOtQX1ffWDaMiIf0vtQDtRdBEx+QDZNPRUkfab8MJOpUYG19q9r2nt2z9XfYS7VjSLqooEwrlBVTz/8nTOfINenkaDY4EABCAAAQhAAAIQgAAEIACBKkuACXqVHXpOHAIQgAAEIAABCEAAAhCAAATKEwEm6OVpNDgWCEAAAhCAAAQgAAEIQAACEKiyBPCgV6Ghx4NehQabUy1CoGXgMY+Sc0x9qGYzgzbqMWxugV85VTXPhga1UXiO6B6mCwqPtQ6SH+oW6S6wZHHkVW6N9Ay33u//un3va+qt9uu9z+yoz5foMXWaHMsuwfrwn9jzkptsN4tuFnorU5n53rt5z+FSbx+qtHdUN5s6I96Q5TymUxofG+fSwZLVqieEhuZUap5f61jLrbF6OWXtcufjdI8gMFvo+uri9Dyn8wKTeZT6hQOxS1DvPecrzg6SqbDVE6qdj9icz9/qHKf19TqL/vSUPrFurI9asEZ7xKmNQWClTW/Qt4X59d6tuWvvhuyFlkn+pCVJnI7WOh165aNUK80P3VX16W5f/+P8tW8em1xPzZ56VRrXchxW7ydpq/tf1Q2cF9u+1fyp7lJ79qsg778WWRDkUuHSfVWf5/QQ529v7Tgeupe2PyaQY9xx2oIgGYVeH+rynzn9ubvO61+mBW8kn4s5uZMkN7idexPNCCGlSjP1RJosel3a509YINq6/VJ1z+ACcZZyO8AZ9//qBnSqu5g8mEz1lbuP6NRnUdK+ieXJceWb25fzqNsIx+F+V39aS+lvyd4i7YtAHvp8IFJhtZNVoyDgCeBB90R2nva/KnbekbBnCEAAAhCAAAQgAAEIQAACEIBAFSbABL0KDz6nDgEIQAACEIAABCAAAQhAAALlhwAT9BKMRbVq1awkfzp06LDF3p577jk7++yz00uc1alTJ/0z0tF2XhCAAAQgAAEIQAACEIAABCBQdQngQS/B2EeT85K8jj/+eJs2bdomS6Pl5q+66iobM2bMJvPRxp49e9pf/vKX9D8GFFu0HQk86NsBj6YVn0BjNe9mLFEv36p7E4N0jytflvNtZomnMEqsTf0Xvl6x3UJpU0Ymftd0YqykUx5FXRPYwv5HZmpxn3dFd3LG3ym9dV9NRqlXs5szVI/u2VH6szEfqw5V5oGhKuIDthmatl5OP+r0zc77eUvgr7zJmWtn1dbG/jgfqqf5DD1vW/ELzduVqte/mejArpre2CBJpSPvxZ3izJwHOrOna37e0brhsemqRTlPqb0lWbPQVBylvAd9F63/oa7qRlMDnRXEUZg8CmFjopbLz3W6g9M+77z7Uy9N6juqNdc+db7t/b9LaqNoXmPV/eur1neJ2WvOyvvQXkl996+TOIp2dcf9VSvNN/pWdT23DvqXrn5v79UPm7u+iqw179rWmhM2TsXnq17hGO/ivfvtgvrn3RtyzYQgmQqrPaHaefPtyg81/+j7qs8/SPQwmxbr1NcccRwFK1P/ha911iiUqazWjx7gPrdavij1zbuNEn2c3RDrae5ZGfOHh1BSZf3ejms3BjVF3+yevXGrZUm+IOMo0d1X3RHrFnZYHEfBo86DPqej+3BYJOVmg9yAttWF0F9xz0vIeGd20oH7++hRf/hDkiOCwCYI4EHfBJSdtEk/hXbSQVSU3V599dV2zTXXFHu4u+zi/mYUVPbv3z+enB9xxBF200032QEHHGCffPKJ3XrrrfbWW2+l83vssYcNGzYsaEkIAQhAAAIQgAAEIAABCEAAAlWBABP0rRjlPffc0w47TP81tCTNP/744/QkPKo96qij7OWXX7aMjI2PmG3durWdccYZFn37Pnv2bMvNzbVLL700PXkvSd/UQAACEIAABCAAAQhAAAIQgEDlIIAHvQzG8c4777R169al9zR69Oh4cl6463r16lm0PXpFdaNG6a1ahXX8hAAEIAABCEAAAhCAAAQgAIHKSwAPegnGttCDnpOTY4MGDSpBi6Qk8p43bdrUPv/8c2vRooV98MEHSdJFUf7DDz9MPzjus88+K3UvOh50BxxZtQjcp++9YVdMkfPvH/gKW9kgyWXYdaJPtx9E5zgjaWtTP/VMqyf1nWy56Cl2cay72Lg4joK3LEf0IvuzaLPdVWeqHrnoBcmvt/Wi+98feLXX6HFm91JGue06SVs7W6Xt96ZuOO8Q1XeoIXroDc/G+QGm3soiawufFpduDCYu1g0POM/6fQ01P2OB6gnBMwkK3ALg1ZdpbcuLVK9WeePhqm9z/mpnOzV7NQB3lPp+e7bQvsZ8rdo9/sDsOZf3/nl3bBaemrfeHuf68nKO2+A96l87o3irJdrgp4lcqJeaNXalE7OS2ii62Pn2px+l+VnuWC4PhjeqrBdwXBocR5Rbp5el1dBHTFgj58We7tofHdh+o/7siPT/k/+9mIR+rfiGatu2Zzb+W37c4LiX4nBj8JnqJy9VPUalPfu3YIP/SubgIBeF8x5wG5xhfk1rzX/nQLyraX2+xV6SbG4XiJ53/2OiO13+pugpY5PPyHRCm5v9xQ14+HF/onuTdMuUvi3T3Rnp0jbje613zwGRZ4ikKttacjHPzG6vbQ/U3w3W6CnNLztFde2hor/75ROiNzQRaTUC6S5b2yfIEUJgUwTwoG+Kys7Z5j+ud85RVOK9fvrpp+nJeXSK0W3sm3sV5qOJ9IIFCzZXSg4CEIAABCAAAQhAAAIQgAAEKhkBJuhbMaCPP/64/exnP0vfot6gQQNr3ry5XXzxxTZ16tRiewm/MY++Id/cK8yH7TbXhhwEIAABCEAAAhCAAAQgAAEIVA4CPCRuK8bx/fd1SZHo4W/Rn4cfftjOPPNMGzdunDVqpEuFRLeLFL4yM/19U4WZjT+jW+ELX2G7wm1b+hl9876515dffrm5NDkIVC4CE+7U8/mj3gLd/+lemv98XqzzarvbyC/VWztnTng0ro2Cvt3+K3qhLRA9060/tsL09s1suyWuz7WWcRwFbW2Y6LNM38ejB7h/+HtQyq1Pq5N0g7u12C5fHuTnBrFZ7shOotv2eU30zO7u9s3lB0re3C3tdoPeKjrgbwck9RcmYRSNXKW35n86UW9hHdP5KmnQ9jJ3bJnu2AILQ7pht+C8R7pbXP8pXafWwHS62s9lw23vZom2XfQ2VPtB6y38zburNh3zleoid9PODm6Pj0rrutVDfjLedeBk3s+SDZe5ZbMeSH4HpYvOT35/RfrUg5KmUfTs66ptdXJrb5Rp30bzrwX1TVtpztyuzd1d/UI7rT88ebumE0PcsR3cTOstL9EN3Z3Z5m6P9/uW+4ZT3Yzy9YrJFh6a7CuKmu4baGcTWFo3yKXC49aqNn89uL7PeuxJbeDtGQV/S/K1nk/iKProcdVevd9Bt/hje1jTzRbNkA0/t3/F+lB33//g3pPiXDq4XOWUu4/VDfVHqv77KapD60aUGbMuyY9xfckbMFXmri1zt/43mfFR0lcqamNrRE+yvUXP7J189rTNdZ9LE5ZKrc3pptpdD7bf1ZLfbaF+tnzquvu2YVJ+VBISQQACFYxA+NeECnboZXe40UPcoietn3DCCWkfef369e2bb76xl156Kb1u+bfffmtPPfWU/epXv7IXXnjBatVKfnsvW5b81ojabe4VLtO2fHnwl8fNNQpy4QQ/2EwIAQhAAAIQgAAEIAABCEAAAhWAABP0EgxS9IC3XXd1X3Ok2p100kl27bXX2qmnnppexzyasN9zzz123XXXxb2uXr06jmvXrh3Hmwrq1KkTb161alUcE0AAAhCAAAQgAAEIQAACEIBA5SfABL0EY7ypyXlhsyZNmtjEiRPt4IMPth9//DG9XFo4Qa9bN7lfKcpv7rVmTXLbVOE66Zur97kt3RYf3eLepo2759B3goYABCAAAQhAAAIQgAAEIACBnUKACXopYG/WrFn62/Rnnnkm7Un/4osvbJ999kn3HD1MrvC1pdvWV6xIFsXY0u3whX2GP7fkcQ9riSFQ6Ql0u15OcbAzkuac/ozkzT5LdKusJE5HWju026eSH5BzjuhrB/sHRy6SfJYF/shUZmWwVFoPe1tq97BvRL9ve4luMHSW6GV9W4tuNkJ9oX7fUyz0Xyf/oJjuxHmxved8ZK8XZF8/uOXnbuneVfL21yWiR16YePf7TPhBcn0WnCTa9g6801Gm+wLJz8xIfJ/pxKJ3JT/Ykn1FiRw7OckfoAytkzK0D9X/brk6nnbfWUlf6ciNf+OOml/8QKLfU0+pLQlyUdX31yS1UbS7q199pebdodr85M6sqPCuKz6M669zzyuwds5MXSMuTQf/UWn2X3esx1wmFa99JdKaBv8+3FNTdnpys1k6c8RHWnCS9z8fqnm3eqB95o5d3jaBFz7dywna15POz36WviXtscDPnm7pjqXp99qfHNseLveN07s4XXOAbvivu5uv+jzNL79J9ZGB/PCOQKTC1fervv3PojvlvSp6ygD1cg9dlCyTGBUO6Hmq1M8/MTFIH9btR8nZ4Zeo7jlOdZ0OqtfrsdnFR2i+5nuqM4PPsq7OXqgfiVZkScehOoD52cGFm9rLpC90V/75CV1GvBIXTOp9XByngwkqizzv4HSX39V9Drprbb8Mrd81P9BuCbYgQwgBCJRzAtXL+fFVmMM75JBD4mONbokvfIWT5i09xC38Bhw/eSFBfkIAAhCAAAQgAAEIQAACEKgaBJigl9I4b9iwYZM9hRP3uXPnbrKmcGOYj26Z5wUBCEAAAhCAAAQgAAEIQAACVYcAE/RSGutwCbbC29ujrvfff//4dvfoIXKbe7388svp9L777mtZWVmbKyUHAQhAAAIQgAAEIAABCEAAApWMQLXUN7+b/uq3kp3ojjyd+fPnp5dfW7t2rUV+9E8+URPgNddck366e3QM06dPt3bt2hU5nBkzZtjRRx+d3h7V33333UVqtndDdIt94a3z0e30hbffR8fUvr3zb27vzmgPgZ1MYKj9SY7gQdtNdA+3wPRKWxHnX3Tr2p4Z5KKiPs50WN10WcSbbEHcVxTcct8ZortecYvoKTY51kvaqUFy5Az1efexq+LaKKhuj4nua+qPHiYec7PBlniQpWFKTLTGsuk85ynv7/oyt55wJ/tY2k/JUc+q7f+15O3qPRPdJwnTkdrVo4OTl19zef7d+rnat9c/pH7EAH1OwMihCdcia8VfLk3NrlugG8Zeo3pgMn7pxPWadpeaiR+6buLTTbdq8I5r7PLfnqb5nzhTa8FKzRcMVb1vIL8K4ij8hdNvOL0k8O1HqZbPS0HTw0XawuQtpYlIrXebFjqd53S13+uGVX9U7bAUWT88XPvc971Wu7JjnP7MaeeXN39zXJarnxdo7ylfpr/rT71cL/xn/b6/CfqKwvnOV16g/mmr1ippsPjnSRxF4XGlZJdRiXc6Sk9yn5mWET6vIlXgrvNOI5xnPTt4/+cqtPPs9WgX8Wu9TYvjKHjFThGdb7VF+8+e1MMZJD/IZsd6kF/ovKfWNhmjx5Lft03cNh2MWCy6rekDEg6y6ZIfb+fFupP7XTBlQrU4lw7ecxfbe5q2Uw7QDe46L9hb03zrpjxQW0cgnBtsXUuqS5sA7+UtEJ00aZKtW7eu2Kr8/Hzr2rWrRZPz6NWrV68itb1797aaNWumt0fLsvkl1CIdbY9eUV1UzwsCEIAABCAAAQhAAAIQgAAEqhaBjbPGqnXOW3W20cQ5mnyfc8456W+4o1vPoyXQFi9ebNOmTbO//OUv9u2336b7PPbYYzc5QT/ooIPsD3/4g91yyy02e/ZsO+aYYyw7O9sOOOCA9Lftubm56XXUo05uvPFGa968+VYdI8UQgAAEIAABCEAAAhCAAAQgUPEJMEEvwRhGy6aNHj06/ae48mgCf//991udOnU2WTJ8+HD7+uuvbezYsenJ+Pnnn1+k7rLLLrNhw4YV2c4GCEAAAhCAAAQgAAEIQAACEKj8BPCgb2GMowe7RX8in3bkNY++OV+6dKlF65RHfu7Iu33xxRfH/vEtdGeTJ0+2MWPG2KxZs9J97b777ta6dWu78sor7dRTT91S8+3K40HfLnw0rnAE1B/b0/4tZzDGbhPdO7UyduHrAdNVFG50Xuyp9s/C0vTPGc4/uSq1svm2vprYI9K0ja0R7dcxb+gMzsM7nyX1N09W8/YG08eO7BL4TN9zPs/HrKH0NdKtye7P88Ogr6jhYz2dqXmM+mMbBCbY6+0L2deQO34l2pxHucGoWZJfYertLLj1KMlbowLVDwYOr5M1VUQ9WWSLbuivzw2wq9pJvu2S10TPzAye+ZF6Noi8mmeKtJxBqmuNV11tpOoial/dsvtFif7qyiSOogPuFf2Bsxwf7Dl4H3kDaW62srtuqF4v0UfqvkyH06y281av/lfSNorW6fvbjtC0+RvRXg7yC+cFIhVWcyd6mL7nrIaWe/1QuNZ4qvRi91gAWxNcYI3dca9UD7rbU0qqd9vMQV7jTvRfodk+1VwuF/VSm3t2hlld3X32Xqprq+w3VC+I4T31syd8bkTOkknSePDdXUSHtenEVPeAhCHuWLKu0fZz/6x6xMeB1meEmH+Wxj3uu6qG6jG3C/Vz0Bq7Y/lJsKsonBd8znXdVZP6cWyWrWlrOV83rBui+leviN7wvkirdoxqFAS2hgAe9K2htWNr3afSjt1ZRez9+OOPt+hPab06d+5s0R9eEIAABCAAAQhAAAIQgAAEIACBkEDwFUK4mRgCEIAABCAAAQhAAAIQgAAEIACBsiTABL0sabMvCEAAAhCAAAQgAAEIQAACEIBAMQTwoBcDpjJuxoNeGUeVcyopgR72gJTu4fzUuZ3PjfNDJqtffWDzE+NcOpj3tup7g7WGo0yB+7fPRgdIfdtfizHUZo4MPMnOU2jj35W2ZupRHurW4M2xPaS+oKPzYr8jaWu5ZHq8YY61jOMoyHZrFecO6CT5JkNfF51v+4g2855X590UD6z3iR7u+nJe7d7Kwdo7E/P6XbT95ENUjw98ot57e5fz4l7nj80dy90ttO9e61S79eGteVLfY940V6vyfXtYNsww57XNccfq/bDe4xpalq/T69JsjuzLaun14C6t1HWu5Zb/lm6ofpnqGsG1WetQl3PXRvObNP+JSlt+nG7o+orqSW7d9EP+mOSzkjAdzXB6YVPd0HCQ6vruvL7StGW4fe8T7Dv/Vi1+4xzVzrJsznpvR2u5/UX14CXPyIacjNNi3XHVtXEcBZmWJfod9yCADfY7yc+570jR9rGa0pvkus+DCSvj+pxuy+I4CkbbcNFLMnUQ2i5yz224K/iMjFr692Tz+tKf/U8gtWvrtOjVIGk2pfGxom3JAtHD3EL3j1kjyc/proPSbHyyw/nmP8fqSlvrrbLIR+i+H2lBLf0FsaHGDZKv5i4nSSIgsAUCeNC3AKgM0+5vkWW4Z3YFAQhAAAIQgAAEIAABCEAAAhCAQEyACXqMggACEIAABCAAAQhAAAIQgAAEILDzCDBB33ns2TMEIAABCEAAAhCAAAQgAAEIQCAmUDOOCCAAgcpJoJWaN3vkTZPz9Otqj7Tr47xf5zpOVMBggenH3d5Oh/brgd2cp/ySt90ZO6Pobs9qvpv39mp6pjk/dJ8k39+eSkQqGnbvGaLtlNBEbDbgObemc8ZvtX6uetCHTP235Ad2PjHWQyfreSy0/8a5dPDPTqKPs+dET7Rfi/Z+eeu4u+av/k+sq3erE8dRUGALRFvPLNVHv6n6961VD16qWq25Zt2TMRw0/mmpHfT96aLtLudvve5AyTfrlXhOo8R8c+c5rrHUW/9Eju3YIRFR5Nd/bj5W8r3nPSx698F7iu7vfMWW3ULy2blTYp17v3422O8nxLl08LbLL9e09VqtG+5z/+bfwPnIv784qV89LYmj6Bv11lpN17bgTq23J1T/Q6Xt8kfZ0LBVIpeOSeJ0lHGybtgwSrVNU/3DJNX57v28zxea/6Jjom90tZlJKh1dqsb+ZlNfl4LuU78RvcT02szpnnjO04XjkzGa6jzl55ke5zmm18r7tlb2NefL2qKb5brrvmM7yTfoNivWg+2oOE4Hfh30Xoslf6atED2z3krRZl+pztT3ZJOJCbdvTK/LIp7zq7SrHiMWyIb+fz1ItF3XTHWGyvl9Aw6HJwzSVV+5z6n6nbVx7T+p/trte59TJY/nXHAgIFBpCOinVqU5LU4EAhCAAAQgAAEIQAACEIAABCBQsQgwQa9Y48XRQgACEIAABCAAAQhAAAIQgEAlJcAEvZIOLKcFAQhAAAIQgAAEIAABCEAAAhWLAOugV6zx2q6jZR307cJXcRr/1R1qF9XDGt0tG/o7b2BbS9Zd/Tw0y6ZaLfKeZOmpgokHnTfw0sBfOWG2nsy3HVT/5EXR/d0av8NM16aV4p0tMtVX3HvRw/ERPeI8qFfb13EuCgZ1P120jVdTsl83/XGrJ/Xz3bVmnWsm+ckfJ3EqamDfiV52p/NuNlBParPL86R+vgU+0CgzYYLk7buuif6v+7fq5C2wsabbv5LaKJr0S9XHqm/42itfkvzoB44UbSsaJvrdJExHY9a5DcrFLPHOpwv77qX1isXcMupmS5LykfZCIlLRCuf7HWaHSd7aqc/XTtK0HTpON0y5RPWiQPZwz2lY3T1IpsLap6j+8ULVz+t1bO7yMO/trXdL0v78Q5I4iu4IrsNIN3IQn9Dr2E6IioLX40G8qTC8npa8rRX3HK76NZWDxz8jG3JMuWU7H/ltFlxbqZaH2e1x+7x7/x7HUdDgyjdEd7ZVoh8b10J0s0vmi25tP4r27/eCzKPi/M2LJsZxFNxiZ4q2djoGTWa8Lvl891liPd21ubuUm4WPLLjO5fSjxUwPzfyuWi6aLh3MsT1EW4Z7X6xaneTvqJvEUdRQmVn1oDbK1x4a/T953X1bEkfR2SrtJr0eXBYJga0iwDroW4Vrhxa7v5Xs0H3ROQQgAAEIQAACEIAABCAAAQhAAALFEGCCXgwYNkMAAhCAAAQgAAEIQAACEIAABMqSABP0sqTNviAAAQhAAAIQgAAEIAABCEAAAsUQwINeDJjKuBkPemUc1aLn1N2ukY3jb3V+aOdZK1Jvf5b2oWhnx4fSZph6bSVZ0cRdgaf1fnfw1wfG3Sh1qTe8uvoKJDvZQ/HRvmeBDz+19SrLj3NRUDf1X/j6u1uDeYVVC9Op9cATD+rGhPpMzRI/bnZojk4V5z7qTKWftpK+rU/SdmMiS/PNd1U9T73dnYPnK0y2y7XWnadN0evepgbXStSy5TRtv/491f/opbpNIG96NxCpsLfz1jbRdPU+s2VDgWWJru7Wj+9lyyQ/2lomurFjvGRRkouiWzNV37RA9EibJ3qe1RI9tnkH0TZveayb2PtxvKkgf0gIKVUxylW5RwzY5KTvqLKHKaexjyZr0Tc4f410tuwu934eJOmUb98/B8Bfx1naoK9KGxFee19JcqR9ILpPtjP2t/CfPf57Fe2vh1sffGxwfVS3xbKvggFHiTZnfzZTpn3teanfxb3/b7GEcVS4LPUkifjVrkUcRsHQGc+KHtBO1/e2zpI2G+h0jtMNnW76/5IN3doncRRl7q7avT3dW8bsaS23rk67t40dHOT3fSYQqXBtc9W19D1kX52m+X2cx/x999kz0OW1NQoCW0UAD/pW4dqhxf6TfofujM4hAAEIQAACEIAABCAAAQhAAAIQ2DQBJuib5sJWCEAAAhCAAAQgAAEIQAACEIBAmRLgFvcyxb1zd8Yt7juX/07be293S9wUPZJOea/Khimdj4310MnuNkT7bZwjqBwEwlvcp7lbuwvsPDnJ/naH6GF2ouhs0+slt/e5krdRejuutQqWCMubq7UW3hbsUik52C35l2Pu1lDfZIDbMHRBvKGHuy18bEaHOJcORukyav2u/Kfkhw84S3TO0EmiB1tH0dUtOdcCv5TZPXWl1q7+XnR/myZ6WO8zRRdZVu0nmrZ5wW3OXfVW3/4Tn5LiYW6pupE2R/L59qXoUbdeJHrITf8WPVCW8asvOeu7q+jhI/R26vVWQ/Lr3JJwQ/4W3lecKs09SOplBbHgVvuoqK3lSe3M4XpLdHY//dDM7dlJ6m0/ldbP3fOckZkUrErCKKrubsU/TQ40taKf7S8Nmrhl1fLvdFaA6xdIvbXLivWQGToeM0z1ZLs5rt0YuPPoeJjkB03Ve79rOYvDXbZbXJ8/LiuOo6DJJQtE59s+oju59+SUvsdKXm0Dqf7sTcnnB3adTu5W/Snuuva38g+yV6WvQYFNYGNC3zfWPPgciwrODpq7X792rh6nrcwKilPhfLUJOJdRdKL6Gsot7goEtT0EuMV9e+iVblu+QS9dnvQGAQhAAAIQgAAEIAABCEAAAhDYJgJM0LcJG40gAAEIQAACEIAABCAAAQhAAAKlS4AJeunypDcIQAACEIAABCAAAQhAAAIQgMA2EcCDvk3YKmYjPOgVc9x2+FHf94Hu4oovAn1CEBNWRgJdbFx8WpPskjjeVNDTbpTNu5k3OEvacrOdB/0lzduMwJPe3fk439HaLnmvyIZJ1lS0mXqYi+iOWt5latLfcpsgyZfsYtFFlyo7WvJ2h/OND9d09SWzZUOBhefqj/tjqbXGh4vutET9sX5pvHzbU+qtZ5bqzECOCeIo7Oe0YjG7cKUWzKsneljuc6L7T1gq2r7pFuvqvZTJIPs+zkXBwLtPFG295qp2y3bZjHc1P0D90j2GTovzYzt2iON04Hzh186YKvnRzgduXbMk32Ti66LzM9uIDpcM6zImue6iokntjtPa389Q3c1dW3LtpFb4s0+lvpvj+LpbCi0sfs95xuffq8fd8sqZYXnKFV5T9B62XvT87Haiq+cmY1zkWQs93XlNlKZm7hEC1sXl+7nroXMLKWgyORmT/FZ6Xpb3ttSaPBshlbrPfXeVXVvr/0el6SMozOqtdAWBHKTvmZaLpgdJSz3lQZ+lMNJmSb5PavFLXhDYUQTwoO8oslvfr/sU2voOaAEBCEAAAhCAAAQgAAEIQAACEIDA9hNggr79DOkBAhCAAAQgAAEIQAACEIAABCCw3QSYoG83QjqAAAQgAAEIQAACEIAABCAAAQhsPwE86NvPsML0gAe9wgwVBwqBMiPQz26P91XXrYO+zq1FPtgZQbuY+mkPcH7YJrZ33HcU9PFe3kcDr+ZbraTWcherdmsZD7b3JJ9jh4q2zCzVi74S3cAWxrqzW3u6ldP9sk+Oa9PBfSptifONP7CnFtRx5zKnWZLP1eMyW53kosh7yMcsl3wzU+/1N2698GX3qWG25RVvxO3nFPHx141zUdDAjeey3q0lX2TNdbXXWui9Tjc8IVgD+jwd7/72tPS9wTaInm57iJ7ivNjW90DJu0vZeg98OM5/4q7DSQ8dEOfSwTBdk3vovGclP6D3qaJtkUoLff5Rqv1/koKlRyRxFNXU8bRL1Lffw3U+1vSZBNXNXXvauw21b+Mt/bq663jigjiXDvx7xj2TYOjVymGCe+7DnIf20/7GBRwdo8HznpHaHDtNdJH3gS3QfOMWoocu0WMbEH72dFdmliFNbciYf8uGgb1PFD1y1Aui+4R9pzI9TN/f4XMhZma3l7bu7Wk2RdPnzXhZNjxu+qbqE3xuRYXD7Q9Sj4DA9hDAg7499Eq3Ld+gly5PeoMABCAAAQhAAAIQgAAEIAABCGwTASbo24SNRhCAAAQgAAEIQAACEIAABCAAgdIlwAS9dHnSGwQgAAEIQAACEIAABCAAAQhAYJsI4EHfJmwVsxEe9Io5bhw1BHYoge6fJN2P935W9aw2s78ltamovo0SnTf8UdHm1yoeor7RlgOnx/VznMfYRqqnuEefaXFtFDS1ZaIH93ULJast1Jyt3OzYgqT9lV8kcRTlOBOxW+59yHXqWV1h+m/dudZJ+3MeVeu4u8sH0nl1bd5XQTJ1aG5d5MFd9bz7TvyH1I/ofo5oC9eXz3P+5671pbbLRH3GwKSM4yRvq75X/ehnoq89P/E/R4nRlvivvXe6YMIabdvtR9E/sRWiB3U9XbRN1GNpYPMkv+yuwD/v16l2a1NbY2lqlrdAN9yTJTr7ajUST3MG+JkTkoXWb+72nbS925xvW7Jmy/oGx+1yaZm8hdKy09RXpWqKHRvot4M4CvcSPchmO61ebDO9Fps57ddRtyt1DKXznLoi7UuVNkb3ZW59d+vbQhs8rNIWrUs2PKi+fqsW5KKqenOS2ij6wV3ni9066Pq2MLvkRW1/zwmJPiMJ09H1uu9B9pwU+Gcv/GB6vezqLs5B9jtpj4DA9hDAg7499Eq3rf6tonT7pjcIQAACEIAABCAAAQhAAAIQgAAESkiACXoJQVEGAQhAAAIQgAAEIAABCEAAAhDYkQSYoO9IuvQNAQhAAAIQgAAEIAABCEAAAhAoIYGaJayjDAIQgAAEKiOB8cm6237N5aecL3wPC3zbaRbXKZHmzotpzrw9UH3C59kPcfuz7Os4joIhfUTaAtNfV2Nbqfdaq1NrE4+ZJpvGpRzz4atg1VGx7JTqPXxN+TIzlGaD3xU90C10PcStVW3NpdwsQz3nPaf+JS7YzQ6K4yjINV0f3DLUJ/zKqt2k3o5WOeKks3TDlc53PPzwOD8wT8dryMRj4lwUTOrrvLhPS9rsoF1lQ5PzPxI9ulVH0c3yZsR6fvd2cZwOvtNra3RX9/3BmfOlvvtv7hA93n4l+gbLFz0oGMJOY96U3JTmx4oekvdv0QObOy/21Qskn9u8k+iceZNEz+yW+Mhvcb7t6rZOarOcXjbiY8nbrQeKbjY1YRolptzXRvLDr3g+1jPcmtrPuH0NaqW+/mF5z8Vto6CGW8R7lDWSvF2pYxR+nuznniGQM/hIaTvU3hL9J/fZ0cFWS37yiGWil3VOGKcTjYPPi3fcQwVGLZC2Znrd2wO6LzPnQXcfa0U861cHz4F47xy3L5We6Uf2vhS84545car1lDwCAhConATcb8DKeZKcFQQgAAEIQAACEIAABCAAAQhAoLwTYIJe3keI44MABCAAAQhAAAIQgAAEIACBKkGACXqVGGZOEgIQgAAEIAABCEAAAhCAAATKOwHWQS/vI1SKx8c66KUIk64gUEkIDLF74zMZaIk/eePGtnFuU0EPe0A2L7WXRb9ip4jOt31ERyupF77627TCMP1zhPN5H2prJX+I04+Zem8ts67U91v0pOj7bd9Y5zsfuHVVb7VNXB7Xbgy+dzo5jyjR0j6Q/OH2mujxnW9I9MXqh7bznN81+7CkNoqc/3XYTeoTLnBe/YEZzj+9KjBj33eQ9F39ijzRBaYchpn6ofu76+Vad96je6sHPWfUpLj/1c5TnGvnxrkoaOuYzRyn3utOl6jffYpb09ucvzrb5sT95wbrsW/cqJ7jvvZhXBsFI+44R3TbG3Q8Z05YL/ke3VS/F3iYT7OVUvuN83WPds99sOY6/t7fvtAaSH+P2y6ilwXnmu3en7l2iNS2NfWQzyzyfpVys8ZZumGJcsyxF+L8YGsaxxsDPa8upgu6P2MZUl9wx1Gi7YavVN+7p+oXgu+fDtBU8NbfmKinY2K1WmqDOvrZYef/VPN99X1i+wfrv1/n3s+rtKmZHtx59qAUtHTXy5TgMzMqnGIXSz0CAttDgHXQt4de6bYNPsFKt2N6gwAEIAABCEAAAhCAAAQgAAEIQKDkBJigl5wVlRCAAAQgAAEIQAACEIAABCAAgR1GgAn6DkNLxxCAAAQgAAEIQAACEIAABCAAgZITwINeclYVvhIPeoUfQk4AAjuUQD+7Xfofbn8QPdjuEv2QM0TPtyzJZ9sror9x/trQmzvT2kutqX3ZbOpczZt6zLOdf/Y2ayj1Be7YLFy7vOvhUlt94mzRBZnO/7oo8HGnKvvZPKkfbl1EW0awJnOUOS1Iq9XWbHyQi8JH3tcNI9U33CBvluSXOe/uQPtE8kOyf5XoxJad3pY9eUqSS0V+7fh8c+tJd1Vf+JCJun743W4M8kPPc/P6si/vrR7sFpPPcYwH/+1n0r75hTeI7mY9RA/PTNaHH7roWckN6Hqq6MyJnUQfY4NEH2qBx1gyG4U/7+vsu7hqrXt2wiD3nIZr3XtmdIZ7I4TXTtxrEnSa+GoiUtEUS7zeXQIfflTkn+NQz4oYpKWvNe65AQ84X3l+1zZSbxOT92xPmya5em5N9hfdeM9x3vph4fs11VP/dvp8C5vxtvRvDzRL9IYzkjiKGt6i+pN2qpuqF9/+HvQVVU52/vf73Pvi1sB3Pk+Pq4d9L/tqastE32p9Ra9yHvSh9ifJD7DfikZAYHsI4EHfHnql27Z66XZHbxCAAAQgAAEIQAACEIAABCAAAQhsCwEm6NtCjTYQgAAEIAABCEAAAhCAAAQgAIFSJsAEvZSB0h0EIAABCEAAAhCAAAQgAAEIQGBbCOBB3xZqFbQNHvQKOnAcNgR2IIHudk3ce4vArxpt7Nf85DgXBW3n6frPp9sPkn/aGol+32qJvs75SOsGPvIBjdUH3HKJrovc2tZIX2M7dxBtk3WNbjM9dstRL7YNXhS3b2JfxHEU5Dd2XtolyyVvph7UbPtM8rnZnURb7mLRw+2NWPcbqceZ3Ud94N+Y/jv62qBt1Mn4juq9tm/jrjcGebo2tVniC27g/NDLbG9tPEHXAx/SbYPkB1oL0XZrpuonVNpHifbjO8d55y1DnwswbNVzSeNU1D/zFNGNF6mPuJZ7XkK4/vjYIuu763guC9Ytj3aywK0t38j0uQBjsq+SYxmc+4zoHDs00XdnJXEqatZrhuj57fQ8qs+YLfkCU8ZN3LWX385duzOS8ZaOUuJa+1I2jbajRY90fvh+tpvks9xa8/Ob67HbvHVJffOaSRxFYS7SE6ZH/09ey/4niaOoQbKmejqx7CSXf0f1hksS/UOdJI6i2o5R3d9r/ojkeQXpxPTjNF9LfeItL9Q3XTX737g+z/QZEdl2S5yLgly7WbQXGc6r7z3pbd1DK2Zad98FGgIlJoAHvcSodnih/ubf4btjBxCAAAQgAAEIQAACEIAABCAAAQhsigAT9E1RYRsEIAABCEAAAhCAAAQgAAEIQKCMCXCLexkD35m7K/YW9zdWW/szk1s8uyzSpZEm2SU787DZNwQgUEYEcmyU7Km6u706R9YHS5Xq3bZmF0lz6zpiiGyYaGeLzrYPYl3NqsVxFNxyn1saaXCwdFEq32/Rk1I/vLO7LXWJpIuIJjNej7ddY9/EcRQUpP4LXzXc7dfTglvzo7pdTG/9bmV6S/tSd0t1uHzZMjs43JW1tTzRfkmvn5rebv+9bf5Ep9uB0t/Mxu1jnb1Eb6fPtT3jXBQ0cUs8hbeJR3l/LIPcLe/nOevAYx1/ETXb+Jq6oDDa+LN5lujh854X3c/2FW1uX51MbxWf4s67k30ctz/U3do/+m63lFmvBXFtFAwLbAGR7n/HKdGP5LUwCdPRqNW6oXvdRI/XZbesud7KP3Ke3sr9vdVI2qaihu7Yl9pSyde3+qI/Cm7HP8RaSa5Pd3eb+HhJWyd7VTZMMT3WbEveQ1Fhrh0k9dYz+IAYo+8Je6it1hboreD2eGPNXzRO9YxLVB81SPScs5OTaamOBPvUHeakBtLUrpur2t7QMbE/NZOCZjP02rskeI+ud0vXPWB3SttF9l/RWxKtrLWU+FvoJYmAwFYS4Bb3rQS2A8v5Bn0HwqVrCEAAAhCAAAQgAAEIQAACEIBASQkwQS8pKeogAAEIQAACEIAABCAAAQhAAAI7kAAT9B0Il64hAAEIQAACEIAABCAAAQhAAAIlJYAHvaSkKkFdsR70z1Ie9HsTD7o97E520QFuAxICEKicBGbKaXW220V/a+oL7+L8r/2d77eIB9maSX/WOPGo9l3yD8mtd0s6+eXG9rMVUj/R1LO6wnnaz3V+avHLtkuOI93pjEXSd1u3lNVM+7nkq9u7oguGHCV64MB/ih5iyRJSg1zb5+wJqZ1huqRTkeXjpDolOupyci2n6vJVcwYkS2k1Gaoe4vxxWdrbJfpv+G3DddJSlTPdeBZZ8svlrfHuSf+DkjAd3eq0s4XbeOfrNq9rug50DJsE12r+cF1mK6ffJGk72HqLNtNl08zte7jlS30/O0a0tUp84YPynpbcENtLdIFb6nC4vST5r7awBNwkU0P1wMDjPMQfl1su0NyzEizDvS/ayaFYk6nu+rn/Ai14KbgWO6sRvMEF+v5dNkGb3nju+bLhtkd1jKxBF8nb984n/hvnr9fqHasyg/PWy9AGmv8s+L0eS9g2yvD3L+WD2qEE8KDvULxb1bn+9t2qphRDAAIQgAAEIAABCEAAAhCAAAQgUFoEmKCXFkn6gQAEIAABCEAAAhCAAAQgAAEIbAcBJujbAY+mEIAABCAAAQhAAAIQgAAEIACB0iKAB720SFaAforzoC+anm8Ptk98USvtezmbusGav4M6ni45m4o/XYGgIFB5CAy1P8nJPGx/Fj3PkrWGo0Q7Uz9lFztP6m9xPvFl1jzIq1mzi30X5MwmNT9OtM3TzylNptQdu+qmG75S3Tzx/vq1p7XQbE3qv/BVPfhMjLaPsv5hOrVa/Lmi9zP9nPxnaoXxwtcctw66OV9wpl1TWJr+uZsNFz3n0V1E2/m6hvtIt8b72sCbP8ZGSNurLVt0nlv//eDAxx0VDhrpfh/0WSztza3J3dLeivPnu75mWL04FwWTTMd7kKl3e1Bj3ffNSyZK+4+D9b+jxMTQyz8hOY50o266Fr01ri992U9UNpun617P995tLbfBlniSc2w/zbY7THTLGfrMgNbu2hs7soPUW5+5onu462ds96S+0/hXpXaW1RGt78dUqp17D12n17FV0/e71VBvv/2+ddL/ZUmYjg79l9ug163Zjy6/m+i7zr1E9HXVRFYg8aE71p85rXKw3SUbcuw60QgIbA8BPOjbQ6902/INeunypDcIQAACEIAABCAAAQhAAAIQgMA2EWCCvk3YaAQBCEAAAhCAAAQgAAEIQAACEChdAkzQS5cnvUEAAhCAAAQgAAEIQAACEIAABLaJAB70bcJWMRsV50H/b8qDfk/7ZI3RDLde8CD7XcU8YY4aAhDYSgLPu/qTRV9r94v2Yhf7VjatcObd0dm6uPWw3Ofi+v52bBxHQY5NFT24p657fO0YzY+2PaR+uH0uup/3/gbrT/e3aVL7H3tRdBs7S3SuXSE62+4T/YTdKXqePSm6c+BZn2tnSm5+73aibx6l3uoH7aeSb+M8ypMaq3fblki5XRtw3c35wKuZ/pv9Euch9+N7ix0unVd3zy/JceuDrwnWDx9h3mt7oPTV1t4UPdMaih4Y+LqjxJB2v5L84BnPiK5pNWNd5FkIXQOvdKqqx8RpcW0UjLUOos+zl0U/ZgeJrm76PIWCzkfF+QaTZ8VxFBxq94huZerj/qllSb5/q1NEW967qifomuwWjklBc639vJXo7BumiPbXuTVPvPTpwnnOky6tERCAQEUjgAe9/IyY/jYuP8fFkUAAAhCAAAQgAAEIQAACEIAABKoUASboVWq4OVkIQAACEIAABCAAAQhAAAIQKK8EmKCX15HhuCAAAQhAAAIQgAAEIAABCECgShHAg16Fhrs4D/r06d9a+/YvxSQGO+8m62zGaAggUKkJdLKH5Pza22LRtayW6LW2VvQwc/5YtyazBT7gjQ2Xx+3Ps6/jOAqaO/P0MOd3NkvaRvW9nWd5j2Ct8Si/IfVf+OrfMTjWqc7H69a17m+zw6aps9bzHuf87fl2iNRb9/qiu44fEuufWcs4joLhbv3vm50/Ps8dSz23fvj/mPqpB9j+rv//xtqvPb4iWCM9Kppiu8e1UTDQdM3m2m4d7RpWQ+qHmK6TvSrw4ve0f0ttEa+1HSZ5a5wpevgSfV6CP5dJ7ryb2Bdx+/x26vMeOeOFOBcFT5muLT/Laks+9JRHibaTX5N8lq0THa4f/4ljON5Ok9oMO1d0yGxjoq7kPRdb8pXmLaxXb7yZ+vZdQyQEIFDFCOBBLz8Dzjfo5WcsOBIIQAACEIAABCAAAQhAAAIQqMIEmKBX4cHn1CEAAQhAAAIQgAAEIAABCECg/BBggl5+xoIjgQAEIAABCEAAAhCAAAQgAIEqTCBZGLQKQ6jqp9405accal/GGEbYzXEcBd3tmlh/ZEfHcRTMnJC0Sye63SR5BAQgUL4JNLFH4gPMspVxHAXD7AbRrZy/Oc9GSd7c+s+9Tb2575iuAf1LO8O1T+Qa51e/1j5NkqloL/tR9FLLEN0vtcK0vJyHufHUZL3xJfaqlJpbo3uY6Zra5rzZg2yGtB80dpDovj0uE13bfh7rO5xX3iYkzwOJim5x/vZ23SbHbaNg8gT1ME/86lTJD79Ovdp5AadJHd2a6bqMvfXImyZ9DclQz/LwVdr3C0HfUcN21kHat7c5sR7u1r3vFK7XHVVlque8y6JX4rZR8KLziXcI1liP8pNM2x+XWs288DXxZPWgfzpD1/eeaacXlqZ/DrQ3RN87uUD0TLcO+knueqoWPLthP9O1w4e663qAvSV9n+feQ49l/0Lylqv9aRIFAQhAAAIVkQDfoFfEUeOYIQABCEAAAhCAAAQgAAEIQKDSEWCCXumGlBOCAAQgAAEIQAACEIAABCAAgYpIgAl6RRw1jhkCEIAABCAAAQhAAAIQgAAEKh0B1kGvdENa/AkVtw76O9O/se7t/xU3PNreieMoGGO3iUZAAAKViMDwwH97h57XzUsmyoZPbU/Rjex90R+7tatbB8+2iArruPWkh9gJSfu+ula4HTI/yaWi4b+ZJ/ou2030ac4/v9RelvwBdrDoXNHqre5rt0rtCLtJ9E4VA4Lxig5kqPcga76t8zB3saXx4efaT+I4Ci5wXusx4ztL3rrreuDZ9orkd3Xrx/cRxmbZNj2uz7Uucbwx+F50W9PxP8OWSb5fzsmibbCu8T3SPpD8KGsU66ssP46j4E133JPsCMmb87cPtpmSf8hxvNS+k/wAa5rodm59d+f7rz5vdlKbigp6HiXaxvjx1jQKAhCAwLYSYB30bSVX+u34Br30mdIjBCAAAQhAAAIQgAAEIAABCEBgqwkwQd9qZDSAAAQgAAEIQAACEIAABCAAAQiUPgEm6CVg+uabb9qIESPs1FNPtaZNm1qdOnWsfv36dtBBB9kll1xir7yit/ltqstx48ZZtWrVSvQnquUFAQhAAAIQgAAEIAABCEAAAlWLAOugb2G8jz/+eHv5ZfUyRk1+/PFHmzdvXvrPQw89ZN27d7f777/fatdWj94Wui8X6d2twH5ty+NjWWV7xzEBBCBQyQn0Wx2c4LogjtbgTtYK35hYLPlopWt5NT5cZKclz4nOT7nQw1dX+2MsJ464Lo6joK19JbqfWw/cTNf/3sfUQD/27oHSvkevaaItO/AC52qqXHnO9dA24Tn3BepRVre0qXu6t/rVxxzm1o6v9bHr/BDR9znmft1zs6ukvpqFoN2+Uiubh6/T7YdQWj87SXSDwbNEL8tuLTo/d4rqvkn7v4x4XXLdbIXookL98d5zfoF71sJa8999tEi6nBG+38x62rgkl4qKPPNljKQREIAABCBQBQgwQd/CIH/++efpin322cfOPfdcO+644+ynP/2prV+/3qZPn2533HGHRTXjx4+3devW2d///vct9Gj2/PPPW9Rfca/MzMziUmyHAAQgAAEIQAACEIAABCAAgUpKgAn6Fga2RYsW6dvbzznnHKtRo4ZUt2vXLv3N+THHHGMfffSRPfLII3b11VenJ/FS6ER0a3xWVpbbioQABCAAAQhAAAIQgAAEIACBqkyACfoWRv/pp5/ebMXuu++e/ha9S5eNS8ZMnDhxixP0zXa4E5KrrZrNs1rxnsembi4NX4Ptrljm2PFxvDH4H6eREIBARSLQ2ybEhzvqnoviOB1crbc4N7EfJX+dW06q35IFkk89dUP0nm65qtH2+zjf3/4dx1EwzG4QvSWxwTZoSS+91XusZk3utva5qqJHKaMip+2WdBtsz0jJRLtT9Fw33gPtaMk/YveLVqG3fn9r30h6sD0vuiBlzQpfa3P/EUobYd1EW/Cr/JduebjRdp7WOnuFmf5V6UR7W+o/Nr31v7ktkbwKtW4UuaVdi1EQgAAEIFAFCXijVBVEsP2n3KFDh7iTTz5RT1+cIIAABCAAAQhAAAIQgAAEIAABCGyGABP0zcApaSp6YFzhq3p1kBay4CcEIAABCEAAAhCAAAQgAAEIlJwAs8mSsyq28qWXXopzkWd9S69oabYmTZqkn/ge3SIfedn79++fftjcltqShwAEIAABCEAAAhCAAAQgAIHKSaDahtSrcp5a2ZxVQUGBHX300fb66xuXbZk1a5YdddRRRXYerW1+6aWXFtkebqhbt66NGjXKrrzyynBzieNFixZtttLus3AAAD/SSURBVPbLL7+0Nm3apGsWLlxohU+LXzT9K3u4/ZNx20etYRxHQTdLlph513aR3GO2+XOSYgQEIFD+COQEthy1AVv/3KfkeGs6L+4d1kTy57rlqhraZ5KfbgeK7hx42FfaSsn5fQ23IyRvdoLTyFIn0DG4NqLOpzrP+oM/113ucoXoLt0yRE9qdVys2+a9FsdRcJob/4GWJfkGwbUSJbJsneRb2xrRY0d2EN2yz/RYz7GmcRwFXexT0e3dsxLW23rJz7F6og+0b0XXtbqiw/aD7HeSQ0AAAhAoLwTCuUF5Oaaqehz65JOqSmE7zvvOO++MJ+dnnXXWJifnhd03a9bMzj777PSEvmnTjX9BmD9/vv3jH/+w6OFyq1evtquuusqqVatmPXv2LGxW4p+FfZa4AYUQgAAEIAABCEAAAhCAAAQgUG4IMEHfjqGIbm2/+eab0z3sueeeds899xTbWzR5v/jii9OT77CodevWdt5551n0tPho8r527Vq7/vrr7YwzzrC99torLCWGAAQgAAEIQAACEIAABCAAgUpMAA/6Ng7ue++9Z9Gke926dVanTh2bMGFC2ldeXHeNGjUqMjkPa08//XTLyclJb1q5cqU98MADYbpEcXRryub+FN6GX6LOKIIABCAAAQhAAAIQgAAEIACBMiXAN+jbgPvTTz+1X/7yl/bdd99ZjRo17JFHHrHjjz9+G3rSJldccYUNGDDAoscCRN/O9+vXTwu2oAo95VsoK5KO1pt9zB6Mty9w6w8PGH5qnLN+zoOYZIggAIGKSKBp4v1ud/lv5QyG2Uuib3aLhy+z3ST/U8sXXdP2FH2oW0c99Jnn9jxXam0MnzUKZCco7zn3h3Dpm27L1aIX2F9FW/CrZGafXSV32gXJdRgl2qVWMg9fJ6Sc4uHrIRsdypQnva9oZwO3ObZHnM+2j+I4CnZ1HvPvg+euRPnHnWd9ft920eb4NXiErg8/wDrGuXQwIPCkD8WDrnBQEIAABCDgCfANuieyBf3FF1/YiSeeaNHPyCs+duzY9DfpW2hWonR0m3z0VPfo9fnnn5eoDUUQgAAEIAABCEAAAhCAAAQgUDkIMEHfinFcvHixnXTSSRY92C16jR492i666KKt6GHLpTxUf8uMqIAABCAAAQhAAAIQgAAEIFAZCTBBL+Go/vDDD3byySfb+++/n25xyy23WK9evUrYumRlX3/9tX377cblWvbZZ5+SNaIKAhCAAAQgAAEIQAACEIAABCoFATzoJRjG6KFtp512mr355ka/XeQNz87OLkHLrSsZM2ZM2n8etSoNT3tJ977SlluezYrLG8TR/wVv+Q1oCECgshAYefl/4lNZa7+O4yg4xc4W/bBttOAUbuxkXxWG6Z+DrINoy6ivetVi0dVtQaLxnCcsKkk0x36jZ3JwshZ5dec5v80aSW22dRP9tE0QfbFdK/obqyE6+/rHRb9vyaoouXd2kly/658U/Z1b13y+bVytJS5Se7xNdF77gfZ8XBoFQ4b+XjQCAhCAAAQgsDkCfIO+OTqp3I8//pj2mP/nPxv/Evu73/3Ohg0btoVWml6wYIG99dbmZ7nRMmtDhw5NN6xbt65deuml2gkKAhCAAAQgAAEIQAACEIAABCo1Ab5B38LwXnDBBfavf/0rXdWpUye77LLL7N133y22Ve3ate2ggw6SfDRB79ixox199NHWpUsXO/zwwy16IFzkN4/87BMnTkz/KfSf33777bbvvvtKHwgIQAACEIAABCAAAQhAAAIQqNwEmKBvYXyfeOKJuGLKlCnWqlWrWG8q2G+//SyakG/qNX36dIv+FPeqV6+e3XnnndazZ8/iStgOAQhAAAIQgAAEIAABCEAAApWUABP0MhjYI4880v7617+mJ+ezZ8+2L7/80qInwq9bt8522203O/TQQ+2EE06wyy+/PP3Nehkc0mZ3sczO1/xElSgIQKDyEFieegZF4auO6RMonrXGhan0z0NtrejXrY7okab/APn9qu8ln+u8vAWSRVR6ApccHZ9iQeNP4jgKblryrOg5tovodu75BsPtLMmbzRXd1l2bn1v/JH/9XUmcil6zKaLbm3rUB9n/Sn5Q59NFzzlBpM254QDdgIIABCAAAQhsBQEm6FuAVXjb+RbKNptu0KCBXXjhhek/my0kCQEIQAACEIAABCAAAQhAAAJVlgAPiauyQ8+JQwACEIAABCAAAQhAAAIQgEB5IsAEvTyNBscCAQhAAAIQgAAEIAABCEAAAlWWALe4V9mh58QhAIEqSWCken+Hv5FQGDjxn4lIRWfaBtGvWV3RlwT+9SjRZ8hJkreBeHEVCComsESvjQFxYmOQY6Nky1zLEm33uicYXLla8m1sjejR4jPXfU9tpe8Jy9M11qfaSOlr2OTnRPef3Es0AgIQgAAEILA9BPgGfXvo0RYCEIAABCAAAQhAAAIQgAAEIFBKBJiglxJIuoEABCAAAQhAAAIQgAAEIAABCGwPASbo20OPthCAAAQgAAEIQAACEIAABCAAgVIigAe9lEDSDQQgAIGKQCC7j675PM7qx4ddy2rHcRR8aurNnWS3SX6SqJQY6DegIbBtBBZaA2l4uPOUP9Z7898vjLbLpb3Zf2J9rd0fx1EwOm+R6Kk2WXSmvSd6jg0SbfaS08c7jYQABCAAAQiUnMDmf8OVvB8qIQABCEAAAhCAAAQgAAEIQAACENgOAkzQtwMeTSEAAQhAAAIQgAAEIAABCEAAAqVFgAl6aZGkHwhAAAIQgAAEIAABCEAAAhCAwHYQwIO+HfBoCgEIQKCiEci1K/SQcxKf+YDBuj60FqIgUHYExtplurPmyXWaTszTdc/NrZNexGdudeP+Rttucbwx0L6G2p8kP8B+K/ox21O0GZ5zBwQJAQhAAALbQYBv0LcDHk0hAAEIQAACEIAABCAAAQhAAAKlRYAJemmRpB8IQAACEIAABCAAAQhAAAIQgMB2EOAW9+2AR1MIQAACFZ4At7VX+CGsEicwT+0Xray1nHaezRI92maKbmVXxTov49E4Tger3ha93OqIvtlyRd9ip4lGQAACEIAABEqTAN+glyZN+oIABCAAAQhAAAIQgAAEIAABCGwjASbo2wiOZhCAAAQgAAEIQAACEIAABCAAgdIkwAS9NGnSFwQgAAEIQAACEIAABCAAAQhAYBsJ4EHfRnA0gwAEIAABCEBg5xDIs9t1x30zVY9YLjrPxsV64Kp/xnEUvG/viH7cfil6frtOom1GtmoUBCAAAQhAoBQJ8A16KcKkKwhAAAIQgAAEIAABCEAAAhCAwLYSYIK+reRoBwEIQAACEIAABCAAAQhAAAIQKEUCTNBLESZdQQACEIAABCAAAQhAAAIQgAAEtpUAHvRtJUc7CEAAAhCAAAR2EoHjdb/7fyC6h80Wvb+tivUqWxfHUdDQfiH6XFsoOvfkdqJthkoUBCAAAQhAoDQJ8A16adKkLwhAAAIQgAAEIAABCEAAAhCAwDYSYIK+jeBoBgEIQAACEIAABCAAAQhAAAIQKE0CTNBLkyZ9QQACEIAABCAAAQhAAAIQgAAEtpEAHvRtBEczCEAAAhCAAATKB4EmV7wtBzI2o4Pom1dNjPVU2yeOo2Bmq/aiB+U9LdoGH6AaBQEIQAACENiBBPgGfQfCpWsIQAACEIAABCAAAQhAAAIQgEBJCTBBLykp6iAAAQhAAAIQgAAEIAABCEAAAjuQABP0HQiXriEAAQhAAAIQgAAEIAABCEAAAiUlgAe9pKSogwAEIAABCECgXBLItwvkuNqt0nXSpwXZmRljA2XWLE8XNh9kHSSPgAAEIAABCJQlAb5BL0va7AsCEIAABCAAAQhAAAIQgAAEIFAMASboxYBhMwQgAAEIQAACEIAABCAAAQhAoCwJMEEvS9rsCwIQgAAEIAABCEAAAhCAAAQgUAwBPOjFgGEzBCAAAQhAAAIVk8AMe0kOvJ/dHusNq16L4yiYZbVFm33sNBICEIAABCBQdgT4Br3sWLMnCEAAAhCAAAQgAAEIQAACEIBAsQSYoBeLhgQEIAABCEAAAhCAAAQgAAEIQKDsCDBBLzvW7AkCEIAABCAAAQhAAAIQgAAEIFAsATzoxaIhAQEIQAACEIBAZSBQzarFpzHTDonjKLjW3hI92i4XjYAABCAAAQiUJQG+QS9L2uwLAhCAAAQgAAEIQAACEIAABCBQDAEm6MWAYTMEIAABCEAAAhCAAAQgAAEIQKAsCTBBL0va7AsCEIAABCAAAQhAAAIQgAAEIFAMATzoxYBhMwQgAAEIQAAClYPAMLshPpFB9r9xHAW1Uv/xggAEIAABCJQXAnyDXl5GguOAAAQgAAEIQAACEIAABCAAgSpNgAl6lR5+Th4CEIAABCAAAQhAAAIQgAAEygsBbnEvLyPBcUBgGwn0s9ul5T2WK3qVrXBalxQy+5nkERCAAAQqM4FB9rvKfHqcGwQgAAEIVHACfINewQeQw4cABCAAAQhAAAIQgAAEIACBykGACXrlGEfOAgIQgAAEIAABCEAAAhCAAAQqOAEm6BV8ADl8CEAAAhCAAAQgAAEIQAACEKgcBPCgV45x5CyqMIHhj/6gZ3/+N6K72sWia9hroh8ThYAABCAAAQhAAAIQgAAEdhYBvkHfWeTZLwQgAAEIQAACEIAABCAAAQhAICDABD2AQQgBCEAAAhCAAAQgAAEIQAACENhZBJig7yzy7BcCEIAABCAAAQhAAAIQgAAEIBAQwIMewCCEQIUkcP7QzR72xI4DJd9v6pOiM20/0Yvsv6IREIAABCAAAQhAAAIQgEDZEOAb9LLhzF4gAAEIQAACEIAABCAAAQhAAAKbJcAEfbN4SEIAAhCAAAQgAAEIQAACEIAABMqGABP0suHMXiAAAQhAAAIQgAAEIAABCEAAApslgAd9s3hIQqACEuj7iR70iANE32N7iF5ium56K2sd5/NsVhwTQAACEIAABCAAAQhAAAI7lgDfoO9YvvQOAQhAAAIQgAAEIAABCEAAAhAoEQEm6CXCRBEEIAABCEAAAhCAAAQgAAEIQGDHEmCCvmP50jsEIAABCEAAAhCAAAQgAAEIQKBEBPCglwgTRRCoQASc59wf+TV2s2z6r6lnfbz9Ocg/H8RReLLTSAhAAAIQgAAEIAABCECgtAjwDXppkaQfCEAAAhCAAAQgAAEIQAACEIDAdhBggr4d8GgKAQhAAAIQgAAEIAABCEAAAhAoLQJM0EuLJP1AAAIQgAAEIAABCEAAAhCAAAS2gwAe9O2AR1MIVEQCw+yGzR52tt0X53PxnMcsCCAAAQhAAAIQgAAEILCjCfAN+o4mTP8QgAAEIAABCEAAAhCAAAQgAIESEGCCXgJIlEAAAhCAAAQgAAEIQAACEIAABHY0ASboO5ow/UMAAhCAAAQgAAEIQAACEIAABEpAAA96CSBRAoGqRCDXrqhKp8u5QgACEIAABCAAAQhAoNwQ4Bv0cjMUHAgEIAABCEAAAhCAAAQgAAEIVGUCTNCr8uhz7hCAAAQgAAEIQAACEIAABCBQbggwQS83Q8GBQAACEIAABCAAAQhAAAIQgEBVJsAEvSqPPucOAQhAAAIQgAAEIAABCEAAAuWGABP0cjMUHAgEIAABCEAAAhCAAAQgAAEIVGUCTNCr8uhz7hCAAAQgAAEIQAACEIAABCBQbggwQd9JQ/HZZ5/ZH/7wBzv44INtl112scaNG1ubNm3s9ttvt5UrV+6ko2K3EIAABCAAAQhAAAIQgAAEILCzCLAO+k4g/8wzz9iFF15oP/zwQ7z3aFI+a9as9J/777/fJk+ebM2aNYvzBBCAAAQgAAEIQAACEIAABCBQuQnwDXoZj+8777xj3bp1S0/O69evb8OHD7fXXnvNXnzxRbviiivSR/Phhx/aaaedZsuXLy/jo2N3EIAABCAAAQhAAAIQgAAEILCzCPANehmT7927d/oW9po1a9q//vUvO/roo+Mj6NSpkzVv3txuuukmmzt3rv3xj3+0gQMHxnkCCEAAAhCAAAQgAAEIQAACEKi8BPgGvQzHNrqFfdq0aek9XnbZZTI5LzyMG264Ie1Lj/SoUaNs7dq1hSl+QgACEIAABCAAAQhAAAIQgEAlJsAEvQwH96mnnor3dumll8ZxGFSvXt0uuuii9KbvvvsuntCHNcQQgAAEIAABCEAAAhCAAAQgUPkIMEEvwzF95ZVX0nuLntp+5JFHFrvn448/Ps69+uqrcUwAAQhAAAIQgAAEIAABCEAAApWXAB70MhzbDz74IL23Aw880CIPenGvFi1axKnCNvGGHRAcdthh6QfV7YCu6RICEIAABCAAAQhAAAIQKIcEvv76azvzzDPL4ZFV7UMqfpZYtbmU+tmvXr3aFi9enO43MzNzs/3vtttu6bXRV6xYYQsXLtxsbZhctGhRKIvEX375ZZFt0YYGDRps0g+/yWI2QgACEIAABCAAAQhAAAIVnsCW5g4V/gQr6AkwQS+jgVu2bFm8p2h5tS29otvgown61iy11rRp0y11Sx4CEIAABCAAAQhAAAIQgAAEyikBJuhlNDDRN+iFr9q1axeGxf6sU6dOOrdq1apia7YnUdy36dvTJ20hAAEIQAACEIAABCAAgYpBIJwPrFu3rmIcdBU4SiboZTTIdevWjff0448/xnFxwZo1a9KpjIyM4kqKbN/S7fBvv/22denSJd2uTZs2RdqzAQIQgAAEIAABCEAAAhCoegS++eYby8rKqnonXg7PmAl6GQ1K5PMufJXktvXo9vboVZLb4Qv73ZK3PfxXssI2/IQABCAAAQhAAAIQgAAEIACB8kGACXoZjUP0Dfruu++eflDclh7IEK1/XjhBL01fecuWLe3111+3/Pz8+Jv0SO+9995lRIHdFBKI/rGk8C4GxqCQStn+ZAzKlvem9sYYbIpK2W2Df9mxLm5PjEFxZMpuO2NQdqyL2xNjUByZHb89uq09+uY8ekXzBF7lgwAT9DIch4MPPtiitdA//vhji94QxS21Nnfu3Pioojal9Yr+kaB169YW/gNBNDnf0jfvpbV/+tk0AcZg01zKcitjUJa0N70vxmDTXMpqK/zLinTx+2EMimdTVhnGoKxIF78fxqB4Njsqw23tO4rstvdbfdub0nJrCRx77LHpJtG342+88UaxzV966aU4d8wxx8QxAQQgAAEIQAACEIAABCAAAQhUXgJM0MtwbM8888x4bw8++GAch0FBQYE9/PDD6U3/v737AJeiuvs4/rdgwYKKBbGhIooVFQuigg1Exd57w4IiMRp7F1FUosRgoQiKUbBEjaKCGisgNmJBFGOJJdgL9rrv+Z28M8zundk2y713d7/neeDuzpw5M/M5O7tz5rQllljCttlmm+hqXiOAAAIIIIAAAggggAACCNSoAAX0RsxY9Tneaqut/B5HjhxpU6ZMabD3wYMH24wZM/zy/v37W4sWLRrEYQECCCCAAAIIIIAAAggggEDtCdAHvZHzdMiQIaZm65rfvEePHnbWWWf5WnK9Hzt2rA0bNswfUYcOHeyUU05p5KNjdwgggAACCCCAAAIIIIAAAk0lQAG9keU33HBDGzdunB188ME2e/ZsX0DPPQQVzsePH2/Rqdly4/AeAQQQQAABBBBAAAEEEECgtgRo4t4E+dm7d297+eWX7eSTTzYVxlu2bGnqb965c2cbNGiQTZs2zdq3b98ER8YuEUAAAQQQQAABBBBAAAEEmkqAGvQmkl9llVXsz3/+s//XRIfAbhFAAAEEEEAAAQQQQAABBJqRwDwZF5rR8XAoCCCAAAIIIIAAAggggAACCNSlAE3c6zLbOWkEEEAAAQQQQAABBBBAAIHmJkABvbnlCMeDAAIIIIAAAggggAACCCBQlwIU0Osy2zlpBBBAAAEEEEAAAQQQQACB5iZAAb255QjHgwACCCCAAAIIIIAAAgggUJcCFNDrMts5aQQQQAABBBBAAAEEEEAAgeYmQAG9ueUIx4MAAggggAACCCCAAAIIIFCXAhTQ6zLbOWkEEEAAAQQQQAABBBBAAIHmJkABvbnlCMeDAAIIIIAAAggggAACCCBQlwIU0Osy2zlpBBBAAAEEEEAAAQQQQACB5iZAAb255chcPp733nvPTj31VOvYsaMtssgittRSS9mmm25qV155pX3//fdzee+1mfyLL75oAwcOtF69etlKK61kCy64oC266KLWoUMHO/zww+2pp54qeOKjR4+2eeaZp6h/ikvIFijWrnv37tkbxrx76KGHbM8997QVV1zR56X+6r2WE+IF5FpsHgTxHn/88azEuAayOBq8+eSTT+z++++38847z3/XLL300qG5vmdKDZX4nP/66692ww032NZbb23LLLOMLbzwwta+fXs77rjj7LXXXiv1kJp9/ErkwY8//mj33nuv9evXzzbbbDP/G9yiRQv/t0uXLnbBBRfYrFmzClqUcs0VTKyKIlQiDyr9XaN7pyuuuMLfS+meSr//usfSvZbuuWotpM2Dd999N/zuCn4PCv1t165dLGO9XgexGCysLYEMoW4E3M1dplWrVhn3CY79t+aaa2beeuutuvGoxIm6G9NYy1zjQw45JPPTTz8l7nLUqFFFpaN0FZeQLZDrnfS+W7du2RtG3v3++++ZY445Jm8+aL3iEbIF5JpkHrd83nnnzXzwwQdZiXANZHE0eBPnGCw77LDDGsRPWlCpz/lnn32WcQXMxHx3DyozI0eOTDqMqlweeMf9LSYPXnrppcxiiy2WaBakqzjjxo3La1TKNZc3oSpbGRjF/S0mD3S6lfyu+fe//53RvVPc8WiZ7rnGjx9fZcr5DzfpXLW8mDx45513Er2S0u7Ro0fsQdXrdRCLwcKaEpjfXQyEOhBwNwa27777+lpyPd0988wzbZtttrEffvjBxo4da8OHD7c33njDdt55Z3vuuef8E+A6YEl9ih9++KFPo23btrbPPvvYVlttZSuvvLL99ttvNmXKFBs8eLApzpgxY0y1TbfeemvBfU6YMMGUXlJQjS4hXuD444+3vn37xq90S9VqJCmcc845NmzYML96ww03tNNOO81WX311cw+t7PLLL7dp06b59aopHDBgQFIydbnc3fDad999l/fcVaO63377+TjbbbedrbDCConxuQYSafwKtdRRDd3EiRPzR4xZW4nPub7f1Kpk6tSpfg963adPH18LrGW6PlTL5h5o+Xzu2bNnzJFU96Jy8mD27Nn2zTff+BPv2rWr7bLLLta5c2dr3bq1ffrpp/b3v//dRowY4eMceOCB5grqvrVEPiltr+uvHkM5eZDrlOa75ttvv/V5qHsnBV0D+++/v29J8thjj9mll15qX3/9tb830P3A+uuvn7v7qn9fTh7ou/+VV14peO7yC+6ZXME/b/x6vg7ywrCyegVq6nEDJ5Mo4JoB+SeW888/f2by5MkN4rkCSPhE88ILL2ywngXxAu6Bhq/pcIXv2AjupivjmrqHtk8++WRsvOgTfT1dJpQm4L6BvfH5559f2ob/H/vNN9/M6NpQOu6HPuOaLGal4wqffrnWK55qTQilCbgHHuF14B5YNdiYa6ABSdYC17Q9c99992U++ugjvzxaC1VMrZU2qtTnPJpX7oFY1nEG+1l88cV9fq+xxhqZX375pUGcalyQNg8mTZqUcQ/KM9OnT088/XvuuSfjmvt6O/eAMLHFTlBzqL/1FNLmgayin980v7f6vQl+e3QPlRt0rxX8rrgKkdzVVfu+EnlQ6OR1T+UqKryvWpToNzgu1Ot1EGfBstoSsNo6Hc4mTuDZZ58Nf0SOPfbYuCgZVyOScTUyPt6SSy6Z+fnnn2PjsbB0Ad1UBz/iJ510UmwClbphiE28DhYGvuUW0FXICNJwNR2xYloexDnxxBNj47AwXkDfL67WxPu5FjyxN1tcA/F2SUvLKaBX6nO+9tpr+7zUb0XSjbOr/QqvlzvvvDPpNKp6eTl5UMwJ77XXXqGdG+MkdhMKJv9jKScPKvFdo3ukJZZYwueT7p30HRcXdM8V/G48//zzcVGqflk5eVDopN0YGaHbEUcckRid6yCRhhVVLsAgce6bs9aDeyIfnqL7ogtfR1+4PqF26KGH+kVffvml5Q7gFI3L69IENIhJENRcmtC8BNx3uB+0SUe11lpr2eabbx57gFru+hr6dbqmtB2hOIFHH33Ud/VQ7L333ttatmxZ3IbEqphApT7nrhY+HABOXRaS8jI6cJ2abhOKF1D3syDwmxFINK+/ukf66quv/EGp+bXuoeIC10GcSuFlN998cxhJvgQE6k0g/hul3hRq/HyDUcTV/3bjjTdOPFv3JDJc9/TTT4eveZFOwD1pDxNI+hEPI/Ci0QXc0/+w8Bi9BuIOJFjvBjgzjURLKE4gerMVPAgsbktiVUqgUp/z4PdExxVcD3HH2KZNGz+ThdbxexInlLzMDSgaruQ3I6RoVi+KvQ7UNzoY+4TroLgs1DgNQcXSKqus4meJKG5LYiFQOwIU0GsnLxPPZMaMGX6dpr9x/aES46n2MAjBNsF7/pYv8MQTT4QbR43DhTkv9MR9ueWWswUWWMA0lZJqbjWwUzAgXU503kYE7rjjDl/LremeNMCS6/9qevquAXuSQvSzXih/ouuj2yWlzXIzDaR09913ewoNoBhtUZLkwzWQJFP+8ujnNfo5jksxuj66neJG30fj5Uvn/fffLziIYNz29bqslN+M119/3TbZZBP/fbfQQgv56SF3220300Mx1/e/XgmLPu9yv2uKvQ50z6XBRhWi2xR9gHUY0XWJCaf91QNdTcFWKHAdFBJifbUJUECvthwr8Xg156qbDsdvVWj0b9efMHzSqxsqQnoBN6WRXXbZZWFCGkm/UNDNmUZA1s3V559/7kdKvuSSS/z8wppzmJAsoJHCZ86cafrcq2DoBnPzN6rbbrut7bHHHn5E3dyto5/1QteIRqwNQnS7YBl/GwrcddddYeHMTTdY1M0W10BDx7RLop/XNJ/zctJR83q1OiEUFtCMK25aLh9xnXXWMdffP+9GH3/8sbm+zf77TjXvepD7j3/8wz+Y7NSpE4XCvHpm5X7XBNeBasddX/S8ewl+NzRSf7R1RN6N6nhlOS2uuA7q+ANTo6eeXJ1aoydcb6cVTOmi89b0aoWCfmw0XZIKN4T0AldddZW5Qfp8QiogqrlbUlhttdX81EVdunSx4Af97bffNhVw9ERZhc7jjjvOF3A0fRFhjoD6we66666m6btUq6fPum6GdPN1/fXX+wcdajKnmqWHH37YWrRoEW5cyjUSNFXUxlwjIWHeF6XcbHEN5KVMtbJSn/NKpZPqZGp0YxXejj76aD9Np05x4MCBiWeqpu/6vttpp51sgw028FO1KW/coHKmB7mqrdUDS/Vn12+QWq8Q5gik/a4JroNi76uCPet3Y8EFFwze8jdH4L333vO/21q8xRZb+IqJnChZb7kOsjh4U0sC7sk2oYYF3JedRrLy/1ztVcEzdQVDH1fTuxDSCbhBZMIpVpZddtlweqS4VN1gM4nT6Si+RoJ3hUqfN64wmpk1a1ZcMnW7zA1smHjumpbKzWseXgdDhgzJinvRRReF69xgZlnrct9ofXA9XXzxxbmreZ8j4GqZMu4Gypu5rho5a7Pfcg1kexR6V+rIyZX6nLvWKOE1kDRydXDs5557bhjX9dkNFtfM31LzoNCJu8J56OW65uSNnu87TyOMa/vgu8o9HM6bVjWvLCcPKvFd4wr43lf3TIWC7r2CvNB3Yq2FcvIgycC1Fgyt3MP1pGjhcq6DkIIXNSZAE3f3rVnLQX3SghAdrCxYlvs3aH6lPryE8gXcPLe+SbWby9M/Lb/99tt9v/KkFFu1apW36e8uu+xibgoxv7mbo9tGjhyZlFRdLs/XxFD9+dUCQX36Fa655poso1KukeD6UAJcI1mMsW9uueUWUzcPBVdgiI0TLOQaCCTmzt9Kfc4rlc7cOcvqTdVNS2cjRozwJ6DBXIcOHZr3ZPJ956mFkNIKxgjQGBCMYTKHsxLfNcF1UMp9lY6A3405+RD3asyYMX6xWhlolohCgeugkBDrq1WAAnq15lyRx62BsoJQTJNcNW9XKKbZVpAuf7MF3NNk69Gjh2m6uvnmm89uu+22vKMdZ2+d/K5Pnz5hIV5NtwnFC6g54w477OA3UL/0//73v+HGpVwjwfWhjblGQsLEF6XebCUm9P8ruAYKCSWvr9TnvFLpJB9p/a1Rk/SzzjrLn7imcnzwwQfD8WDK1dDgZEcddVS4Ob8ZIUVRLwp91wTXQSn3VdoxvxvJ/OqKocHeFNRlLV/hOzmV7DVcB9kevKseAQro1ZNXZR2pnvJqJHCFQoP0qEAZFECCPtBl7bSON1LBb/vtt/cFQI08euONN/qa9EqQuGbyYV5SG1K6aHSwpahfdMCsQtdIMDCQ9s41kj8PNHCV+sAqqAWIBqFMG7gGyhes1Oe8nHT0XRjdrvyzqL0t9QC3b9++/sQ0pdQjjzxiyyyzTEVONOk7ryKJ13gihb5rgs+z7pmC+dCTSILfDeUr/c+TlMwP6BqsreR0nFwHgSp/q0mAAno15VaZx9qxY0e/pWoO1eQ6KQRPLrU+2CYpLssbCmi0fNXSamA3BTWlruSPjNJ0XWz0h1CGQJJd9Mc7eg3E7SK6nmskTmjOsujgcIWat8/ZqvCrpHwsvGV9x6jU57ycdPQwKzrAYn3nxJyz12jr+o1QN5Dll1/e3BgXFX2QwbUyx7qcV/n8ir0OdM/11ltv+d3zm5GcC5q1Zty4cT6CHo7suOOOyZFLXJMvH0tMiugINJoABfRGo266HW255ZZ+53rS+8ILLyQeSLQJXNeuXRPjsaKhwNdff209e/YMaww1tdoJJ5zQMGKKJZp6TdOuKbRt2zZFSvW5aVCbm+u36qqrhp7RayBO6cknn/SLV1hhBWvXrl1cFJY5Ad1sjR071luo1qhXr14VceEaKJ+xUp/z4PdER5LvenGDM/opDxWP3xMpZAcVxjXtpgpwrVu39rNLBPNlZ8cs/13Sd175KdbPloW+a4q9DtSSKGiZyHWQ/PnR1ILBlMAHHnigqWl6pQLXQaUkSacxBSigN6Z2E+1r9913D/c8atSo8HX0hZ7gBzVe6vejqVkIxQlo0Ladd97ZT2+jLc4++2w7/fTTi9u4hFjDhg0La9C7detWwpZEVasGTa+moP7oKmAHQc1vNf2agmrIn3nmmWBV1l8tD2rQFV/bEeIF1IdW09wpVPJmi2sg3ruYpZX6nHfo0CFsYaXBL/X9FxdGjx4dLtYUk4Q5ApMnT/bfORp0cvHFF7cJEyaY5jyvZFDBX12sgrD11lsHL/lbhECh75ru3bubBptTuOmmm8Lf5tykuQ5yReLfB/efWlvJFldcB/HeLK0CAdf0g1AHAltttZXaRvtpv9zNQYMzvvzyy/16xXGjhTdYz4J4AXeDlXEDwoV2/fv3j4+YZ6mmKHFz1+aJ8b9p1two5H4/blyBjOsrnTd+Pa10zUQzrsY28ZRzp1kbPHhwg7hvvPFGOCWem6s+4wodWXH0XsuDa2jmzJlZ63mTLbDXXnuF14RrtZO9MuYd10AMSoFF5UxtVKnPuZtFIsxf11KowZG67lQZV/D0cTRlZ77rs8HGVbSgnDyYNm1axj0E9zau2X/m6aefLvmM//nPf2ZKmV6qd+/eJe+jWjYoNQ8q+V0TnUZQ91C5QfdaribY57V7qJ67umbel5oHuSfuWgZmgvub9dZbL3d14nuug0QaVtSAQOXakFTBw4h6PkQ397NvZvjDDz/4EcY1YqxqyfVeTVH1tFhBtSOnnHJKPVOVdO4HHHCATZw40W/j5gf2o+a++uqriWloqi8ZR8O7777r86JLly7mbqSsU6dOpj5Y7vvF92fXFGH6p/cKV155ZVYNcDStenzdr18/36TaFQpNhmp6rqls1FzOzUVvbi7VsGuAmiXGdT1Qnpx66qmmrglqkqimiGoFoSan6j84aNAgczfWnvdPf/qTrbHGGvVIXdQ5a7DJ+++/38ddd911baONNiq4HddAQSJzBTnTOCJBCJqD6r2WR2vqtOzwww/Xn6xQqc+5arhUOztp0iQ/HZias2vUaw0EqJGYL774Yps9e7bNO++8fiyOSjZXzTqhRn6TNg/0XaKuUMGgYgMGDPC1sPl+M/RboH/RoBpbjXKtf6rJ1cjvqonXiOLqxqZR4WfMmOE30bb6/a+VkDYPKvldo98C9Zt2D2zttNNO89fh/vvv739/HnvsMRs4cKDvwqDfo6uvvrpWsqAi30VRDN2DBtPVlVJ7Xs/XQdSP1zUqUAMPGTiFIgVU0xjUariPs3+qG/3rbt4yb775ZpGpEU0CUb9iXrtRehvAuR/yotJp2bJlxt14Ndi+3hfItBh71ermq3X67bffMkceeWTetNy0RRnFIyQLXHfddaFhXK1S3JZcA3Eq2cvcjWvoWsznPXvrOe8q9Tl3XRgym2yySeIxqUbMPfids+MaeJU2D1wXs0SvpDyNa9FW7HGoNnL69Ok1ID/nFIo998Bzzpb/e1Xp7xrdM7kHton5qnuu++67L/cwqvp92jzIPfnNNtvM+7lpaTOzZs3KXZ34vtjjqMXrIBGFFTUjQA26+xavl6Da2Zdfftk/TdeAHJpSSjW67du3t3322cdOPPFEc4XAeuFoNue58cYb2y233GJTpkzxtbfuB8rX/qrvlGqk1Ddxu+22s6OPPrpBTUqzOYkmPBA9RddgVfJTX3PVLKr2TvPNavToLbbYwvdpU+16vqDaPtd011QTrxYlzz33nE9L0xS6gogde+yxFRvsLN9xVPu6YO5zd7NlBx10UFGnwzVQFFNFIlXqc67rQn2phw8fbrfeequvsdVgWBrAUt9XrrtPxftVVwSgBhJR6x61tNJ3ngbA0ngPX3zxhZ/Ca7nlljPXHcf23ntvP8WnrkPCHIFKf9fo/kmtq4YOHWp33HGHr0VXbbB+e3baaSd/HWj6PEK8gHvAYVOnTvUrNQtOmzZt4iPGLOU6iEFhUc0IzKNHDTVzNpwIAggggAACCCCAAAIIIIAAAlUqwCjuVZpxHDYCCCCAAAIIIIAAAggggEBtCVBAr6385GwQQAABBBBAAAEEEEAAAQSqVIACepVmHIeNAAIIIIAAAggggAACCCBQWwIU0GsrPzkbBBBAAAEEEEAAAQQQQACBKhWggF6lGcdhI4AAAggggAACCCCAAAII1JYABfTayk/OBgEEEEAAAQQQQAABBBBAoEoFKKBXacZx2AgggAACCCCAAAIIIIAAArUlQAG9tvKTs0EAAQQQQAABBBBAAAEEEKhSAQroVZpxHDYCCCCAAAIIIIAAAggggEBtCVBAr6385GwQQAABBBBAAAEEEEAAAQSqVIACepVmHIeNAAIIIIAAAggggAACCCBQWwIU0GsrPzkbBBBAAAEEEEAAAQQQQACBKhWggF6lGcdhI4AAAggggAACCCCAAAII1JYABfTayk/OBgEEEEAAAQQQQAABBBBAoEoFKKBXacZx2AgggAACCCCAAAIIIIAAArUlQAG9tvKTs0EAAQQQQAABBBBAAAEEEKhSAQroVZpxHDYCCCCAQLzABRdcYPPMM4//Fx+j6Ze+++674TGOHj266Q+oSo8AxyrNOA4bAQQQQCBRgAJ6Ig0rEEAAAQQaW+Dxxx8PC65BITv4u/DCC9tKK61ku+yyi40YMcJ+/PHHxj68ZrU/FewDG/0944wzCh5f9+7d/Tbt2rUrGJcICCCAAAIIIND4AhTQG9+cPSKAAAIIlCGgAvkHH3xg48ePtz59+linTp1s5syZZaRUm5v89a9/tU8++aQ2T46zQgABBBBAoE4EKKDXSUZzmggggEC1CRx//PH2yiuvhP+mTp1qN9xwg3Xs2NGfyhtvvGE77rij/fDDD1mnpibumUzG/8taUeNvvvvuO7vssstq/Cw5PQQQQAABBGpbgAJ6becvZ4cAAghUrcCyyy5r6667bvhv0003tWOOOcZeeOEF02uFd955x0aOHFm151ipA1966aV9Utddd53NmjWrUsmSDgIIIIAAAgg0sgAF9EYGZ3cIIIAAAukE1Bf9kksuCRN58MEHw9f1+uK0007zp65uAAMHDqxXBs4bAQQQQACBqheggF71WcgJIIAAAvUnsPnmm4cn/Z///Cd8rRdJo7ir2buaxGtAtfnmm8+efvrprO2ib4YMGRIOwHb22WdHV2W9VjP7k046ydZZZx1r1aqV6eHBaqutZkcccYS9+OKLWXHn5ptNNtnEevfu7XcxbNgwe//998vaXTDonAzzhWCwOf3NDdGB/vRa7mrlsOWWW1rr1q1t8cUX9y0gxowZk7Xpzz//bNdff70pb5daailbbLHFrGvXrnb77bdnxSv05o477rDtt9/e1AJD+bHWWmv5AfS+/PLLQpv69c8++6wf46BDhw626KKL2iKLLOLTOOGEE+zNN99MTCM6aJ9Gl//pp5/s6quv9uejFg6yLeSamDgrEEAAAQTqRoACet1kNSeKAAII1I7A/PPPH57Mb7/9Fr7O90IFJBWiVFj6/fff7ZBDDrHZs2c32OS1114LR0Tv3LlzYqHq4osv9s3vr7nmGtM2Sks12Gp2r/1o2/PPP79B+nNrwUUXXeQLgSroDhgwYG7tpqR0f/nlF9ttt93s6KOPtkmTJtkXX3xh33zzjT333HN26KGHWv/+/X16KjzvsMMOpnEHNNaA3n/77bc2efJk22+//YpuFXDUUUfZvvvua48++qh9+umnPj/0EGXQoEH+IYryKSn8+uuv1rdvX9tss838LAEqjKtf//fff29K49prr/VpDB8+PCmJcPlnn33mC+Ynn3yyP5/PP/88XMcLBBBAAAEE8glQQM+nwzoEEEAAgWYp8PLLL4fH1bZt2/B1oRdt2rQJ+6yrllO1otGgwu2BBx7oC3YtW7a0v/3tb9aiRYtoFP/6vPPOM/1ToW6LLbbwBbopU6bY888/77fp0qWLrzlWoVkF+MYIGtV+jz328LsaNWqUf1DQGPvNt49zzz3X7rvvPjvooIP86PsaP+C2226zNddc02/2l7/8xR555BE7/PDDfWFcBfSJEyf6cQZU6x7kraynT5+eb1e+AH3jjTf62nntQ3nxwAMP+AK+NlTf/J49e8Y+lNF6Fe7Vh1+hV69edsstt5hq0/UwQYVytZLQAweNg6BzyheU1ksvveQfQmjWAZ333Xff7Qv/+bZjHQIIIIAAArqBICCAAAIIINAsBB577LGM+2n2/1ztc+IxuVrZMJ4rBGfF03ZBGlkrIm9cISuM4wpz4ZpTTz01XO5GjA+XR1+4Qltm3nnn9fHOOeec6KrwtavVzxx88ME+jmuqnXE1wuE6vXC17OF+XGE6a12xb7RdcJ5yU3Cj3ofH5prZ+2XR/7p16+a3WWWVVaKLw9dBevnsFTlIR39zQzQPlZ5r5p0bJeMKyxnX1N0fyzLLLJNxrRsyrgDbIJ4r5Ibn47oSNFgfddS+dtppp4wrRDeIp89IcG7K49xw5513hutdYTx3tX/vZgvIbLvttj6em0e+wX6i+aF9uQcMsemwEAEEEEAAgXwC1KC7X1ECAggggEDzF9B0aqql3nXXXe3ee+/1B6z+zMcdd1zJB3/VVVeFtbiqtX3vvffMFSxt8ODBPi3tQzWlcUHNpdVEfuONNzbVkMcFV4D3NecLLrigb9LtCoBx0Sq+TKPe77PPPj7dm2++OW+f6YrvPCZBNRcPmrFHV6slQ1Dbr6boasa+++67R6P41+uvv77vu643Tz31VIP10QWyVk13tPtDsF7jCMhGQTXz6h8eDZdeeql/q2NSc/y4sNBCC5nmmldQ6wv1r08KriBvRx55ZNJqliOAAAIIIJAoQAE9kYYVCCCAAAJNKXDhhReGA7Wp/7ianKs5edC8WIXzu+66y1wNbMmHGW2+/tVXX/km2Icddphvlq7C44gRI2LTVBPnYNT4vffe2x9fbES3cIkllrD11lvPr9aDhcYKGohMg+Cpb74MmzLsv//+ibtX4TsIKqAnhQ022MCvevvtt5Oi+OU9evQIm8TnRtQDE+Wvgvq3Rwfw+/DDD30TdK1T//V8oWPHjn4MA8XJl6dq0k9AAAEEEECgHAEK6OWosQ0CCCCAQJMJrLTSStavXz9zzbn9aN3lHki0Blwjugcjn6v/dlKhX4OMadAwhTPPPDPrAYIeIuT+Uz9ohY8++sj/bYz/NGq5+tErqC/2jBkzGmO3sfvQSOhJQQ8wglBMPA0uly9oJPt8YdNNNw1Xv/rqq+HrII+04IADDmiQh7l5qgHgFPLlafThg4/MfwgggAACCBQpQAG9SCiiIYAAAgg0roCanqsQHvzTqNoaBVzN0TW42Morr5z6gDR/eLRwqObNmootKXzyySdJq/IuDwr1eSNVcKXrQ+6beqspvmrUmyqopUJSUK12EIqJp3PJFzStWr6w3HLLhav1OQrC3MjTJZdcMkievwgggAACCJQkMH9JsYmMAAIIIIBAIwmowBX0G55bu3zooYds5syZYfKqSVdfd82fHReiU7pdccUVeQvz0e01l3ZjhtVXX92PIK5RzTUvuPpg13qtrmq68wU3IE/s6mieatT+Yp3yFcLVxYCAAAIIIIBAOQIU0MtRYxsEEEAAgaoX0OBkwUBe6s+uecxff/11c6N829ChQ2PPr3Xr1uFy9Uef2w8Qwp2V8UJTnI0ZM8ZPDaYadU3zVSiokKuCbKHaas0P3tzCxx9/nPeQojXlSy21VBg3mqc6/+acp+FB8wIBBBBAoGYF5rQvq9lT5MQQQAABBBBoKKC5qlWoU1Pre+65x4IBza699tpwILjcrTQX9gILLOAXa77u5hzatWvn5/bWMer8ogOjJR23mxLOr9JAaklBhXd1N2huQfOV5wvR9dFC+IYbbhhu1tzzNDxQXiCAAAII1KwABfSazVpODAEEEEAgSeD6668PR4M/5ZRTbJtttrHrrrvONACdgptD3FTDnhvUV3q77bbzizXNlpsTPTdKs3qvpu2afkzhvPPOK3hsq666qo8THTgtd6MHHnjAvv7669zFTf5ehWs3v3rsceihwk033eTXqWn6RhttFMZr3769rb322v792LFj/RgH4UpeIIAAAggg0MgCFNAbGZzdIYAAAgg0rYD6nKtQrqApvAYMGOBfa1RxFeJUo66a9T59+vjluf+p0Bv0d1at+1tvvZUbJXyv/s233nqrffDBB+Gyxnyx4oorhvO5jx8/3qZPn5539926dfPrp06dapMmTWoQVwXgk046qcHy5rBAc5sfe+yxfnq53OO57LLL/GCDWq5uDcFDiyDeOeec41/++OOPtueee8Y+nAniaj9qZaG4BAQQQAABBCotQAG90qKkhwACCCDQbAXUb1xzVGtU9YUWWsg0KFjQZF0HrZr0P/7xj/747733Xhs+fHiDc+natWtYG/3OO+9Yp06d7A9/+IOpZnnatGn2zDPPmGpi+/fv70ea1/4013pThbPOOisc9C6YIizpWI455hg/+rv6offu3duuvvpqU2365MmTTYPiqTm4+uqvscYaSUk02fLOnTv7VhHKn3Hjxvkm/RoEUFOn6aGKgh5YqG9+blCcYJ70F154wdeoq9D+8MMP27/+9S//sOLmm2/2D23atm1rJ5xwgv3666+5yfAeAQQQQACB1AIMEpeakAQQQAABBKpFQFOOBc23Bw0aZOpTnhsuueQSXzB76aWX7OSTT/aFdjWDjgaloxr3M844w7799lsbMmSI/xeNE7zWAwA9DGiq0KZNG+vbt68NHjy44CHI4/LLL/cPKdQPXecfDWoerv7sai7f3Pqhq9D8xBNP2OjRo8PxBKLHvvzyy9uECROsVatW0cXh65EjR5qmYpOTHmToc6B/cUGj8jNSe5wMyxBAAAEE0gpQg55WkO0RQAABBKpCQFOoqamzQo8ePaxfv36xx60CtWrWVajWaOUHH3xwbG2pas3VvF01sptvvrktvfTSvvZZhTfNrb7XXnuZ+rp/+OGHllvAj93xXFx4+umnW7FTvalQrprnnj17mgrkag6uvukqAKs2eeutt56LR5ou6VGjRvkuBd27dzeNzq5jV15ovns17w/6msftRQVuPbR57bXXfBcItRbQ+Wu5Bs/Twwu1hlA3CDX1T5qKLy5tliGAAAIIIFCswDyuGVv8xKDFpkA8BBBAAAEEEEAAAQQQQAABBBBILUANempCEkAAAQQQQAABBBBAAAEEEEAgvQAF9PSGpIAAAggggAACCCCAAAIIIIBAagEK6KkJSQABBBBAAAEEEEAAAQQQQACB9AIU0NMbkgICCCCAAAIIIIAAAggggAACqQUooKcmJAEEEEAAAQQQQAABBBBAAAEE0gtQQE9vSAoIIIAAAggggAACCCCAAAIIpBaggJ6akAQQQAABBBBAAAEEEEAAAQQQSC9AAT29ISkggAACCCCAAAIIIIAAAgggkFqAAnpqQhJAAAEEEEAAAQQQQAABBBBAIL0ABfT0hqSAAAIIIIAAAggggAACCCCAQGoBCuipCUkAAQQQQAABBBBAAAEEEEAAgfQCFNDTG5ICAggggAACCCCAAAIIIIAAAqkFKKCnJiQBBBBAAAEEEEAAAQQQQAABBNILUEBPb0gKCCCAAAIIIIAAAggggAACCKQWoICempAEEEAAAQQQQAABBBBAAAEEEEgvQAE9vSEpIIAAAggggAACCCCAAAIIIJBagAJ6akISQAABBBBAAAEEEEAAAQQQQCC9AAX09IakgAACCCCAAAIIIIAAAggggEBqAQroqQlJAAEEEEAAAQQQQAABBBBAAIH0AhTQ0xuSAgIIIIAAAggggAACCCCAAAKpBSigpyYkAQQQQAABBBBAAAEEEEAAAQTSC1BAT29ICggggAACCCCAAAIIIIAAAgikFqCAnpqQBBBAAAEEEEAAAQQQQAABBBBIL0ABPb0hKSCAAAIIIIAAAggggAACCCCQWoACempCEkAAAQQQQAABBBBAAAEEEEAgvQAF9PSGpIAAAggggAACCCCAAAIIIIBAagEK6KkJSQABBBBAAAEEEEAAAQQQQACB9AIU0NMbkgICCCCAAAIIIIAAAggggAACqQUooKcmJAEEEEAAAQQQQAABBBBAAAEE0gtQQE9vSAoIIIAAAggggAACCCCAAAIIpBaggJ6akAQQQAABBBBAAAEEEEAAAQQQSC9AAT29ISkggAACCCCAAAIIIIAAAgggkFqAAnpqQhJAAAEEEEAAAQQQQAABBBBAIL0ABfT0hqSAAAIIIIAAAggggAACCCCAQGoBCuipCUkAAQQQQAABBBBAAAEEEEAAgfQCFNDTG5ICAggggAACCCCAAAIIIIAAAqkFKKCnJiQBBBBAAAEEEEAAAQQQQAABBNILUEBPb0gKCCCAAAIIIIAAAggggAACCKQWoICempAEEEAAAQQQQAABBBBAAAEEEEgvQAE9vSEpIIAAAggggAACCCCAAAIIIJBagAJ6akISQAABBBBAAAEEEEAAAQQQQCC9AAX09IakgAACCCCAAAIIIIAAAggggEBqAQroqQlJAAEEEEAAAQQQQAABBBBAAIH0AhTQ0xuSAgIIIIAAAggggAACCCCAAAKpBSigpyYkAQQQQAABBBBAAAEEEEAAAQTSC1BAT29ICggggAACCCCAAAIIIIAAAgikFvg/hIHQh0LQI6kAAAAASUVORK5CYII=\" width=\"500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from skimage.measure import profile_line\n",
    "import matplotlib.patches as patches\n",
    "import scipy\n",
    "from __future__ import print_function\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from cycler import cycler\n",
    "x0=[0] \n",
    "y0=[0]\n",
    "x1=[1] \n",
    "y1=[1]\n",
    "xx0=-2 \n",
    "yy0=-2\n",
    "xx1=-2\n",
    "yy1=-2\n",
    "# 1. Setting prop cycle on default rc parameter\n",
    "plt.rc('lines', linewidth=2)\n",
    "plt.rc('axes', prop_cycle=(cycler('color', ['r', 'g', 'b', 'y','k','c'])))\n",
    "\n",
    "l1=im_size[0]+1\n",
    "x, y = np.mgrid[1:l1:1, 1:l1:1]\n",
    "z = im_lifetime*thres_image_ROI_mask\n",
    "#-- Extract the line...\n",
    "#-- Plot...\n",
    "fig77 = plt.figure('Lifetime image ',figsize=(5,5.2))\n",
    "ax77 = fig77.add_subplot(111)\n",
    "plt.ylabel('Pixel Number ');\n",
    "plt.xlabel('Pixel Number');\n",
    "ax77.set_title('lifetime')\n",
    "ax77.set_aspect('equal')\n",
    "plt.imshow(z,vmin=.8,vmax=1.8,cmap=\"nipy_spectral\")\n",
    "plt.gca().invert_yaxis()\n",
    "fig5 = plt.figure('Lifetime across selected line ',figsize=(5,2.2)) \n",
    "class drawline(object):\n",
    "    def __init__(self, ax):\n",
    "        self.ax = ax\n",
    "        self.lx = ax.axhline(color='w')  # the horiz line\n",
    "        self.ly = ax.axvline(color='w')  # the vert line\n",
    "       \n",
    "        # text location in axes coords\n",
    "        self.txt = ax.text(0., 0., '', transform=ax.transAxes,color='white')\n",
    "       \n",
    "    def mouse_press(self, event):\n",
    "        global x0\n",
    "        global y0\n",
    "        global xx0\n",
    "        global yy0\n",
    "        if not event.inaxes:\n",
    "            return\n",
    "                   \n",
    "        x, y = event.xdata, event.ydata\n",
    "        # update the line positions\n",
    "        self.lx.set_ydata(y)\n",
    "        self.ly.set_xdata(x)  \n",
    "        x=round(x)\n",
    "        y=round(y)\n",
    "        x0=x\n",
    "        y0=y\n",
    "        xx0= np.asscalar(np.array(x0))\n",
    "        yy0= np.asscalar(np.array(y0))\n",
    "        #plt.plot([x0], [y0], 'ro')\n",
    "        #plt.draw()\n",
    "        #return (x0,y0)\n",
    "        \n",
    "    def on_release(self, event):\n",
    "        global x1\n",
    "        global y1\n",
    "        global zi\n",
    "        global xx1\n",
    "        global yy1\n",
    "        global fig5\n",
    "        if not event.inaxes:\n",
    "            return\n",
    "            \n",
    "        xend, yend = event.xdata, event.ydata\n",
    "        # update the line positions\n",
    "        self.lx.set_ydata(yend)\n",
    "        self.ly.set_xdata(xend)  \n",
    "        xend=round(xend)\n",
    "        yend=round(yend)\n",
    "        x1=xend\n",
    "        y1=yend\n",
    "        self.txt.set_text('x=%1.2f, y=%1.2f' % (x1, y1))\n",
    "        plt.sca(self.ax)\n",
    "        plt.plot([x0,x1],[y0,y1], 'o-')\n",
    "        ann1=ax77.annotate('(%1.0f, %1.0f)' %(x0 , y0) , xy=(2, 1), xytext=(x0, y0) ,  color='white', fontsize=10, weight='bold')\n",
    "        ann2=ax77.annotate(' (%1.0f, y=%1.0f)' %(x1 , y1) , xy=(2, 1), xytext=(x1, y1), color='white', fontsize=10, weight='bold')\n",
    "        NAME='Profile_%1.0f_%1.0f_%1.0f_%1.0f_' %(x0,y0,x1,y1)\n",
    "        \n",
    "        xx1= np.asscalar(np.array(x1))\n",
    "        yy1= np.asscalar(np.array(y1))\n",
    "        ax22 = fig5.add_subplot(111)\n",
    "        plt.sca(ax22)\n",
    "        aa = skimage.measure.profile_line(z, [xx0,yy0] ,[xx1,yy1], linewidth=1, order=1, mode='constant', cval=0.0) \n",
    "        np.savetxt(NAME,  aa, fmt=\"%12.2G\")\n",
    "        plt.plot(aa,marker='o', markersize=3)\n",
    "        plt.ylabel('Average lifetime [ns] ')\n",
    "        plt.xlabel('Pixel number along profile')\n",
    "        #plt.show()\n",
    "\n",
    "#plt.scatter(xx0,yy1,'r.-')\n",
    "\n",
    "drawline= drawline(ax77)\n",
    "cidpress = fig77.canvas.mpl_connect('button_press_event', drawline.mouse_press)\n",
    "cidrelease =fig77.canvas.mpl_connect('button_release_event', drawline.on_release)\n",
    "#cidmotion =fig.canvas.mpl_connect('motion_notify_event', drawline.mouse_move)\n",
    "#plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "############Save Overview Figures\n",
    "plt.savefig('Profiles_Overview', format='pdf')  \n",
    "plt.sca(ax77)\n",
    "plt.savefig('Lines_Overview', format='pdf') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Go back to initial directory and be ready to start again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "######RETURN  TO INITIAL DIRECTORY , in which the original tiff file was saved. \n",
    "\n",
    "os.chdir(InitDir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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