Graph Theory Discussion.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Week 3 Discussion - Searching for Solutions\n",
    "\n",
    "Below, we will walkthrough one way to solve exercise 3.3a as described in Artificial Intelligence 2nd Ed as found [here](http://artint.info/2e/html/ArtInt2e.Ch3.S11.html)\n",
    "\n",
    "# Setup\n",
    "\n",
    "First we import the required packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "import pprint\n",
    "\n",
    "pp = pprint.PrettyPrinter(indent=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are asked to \"Consider the problem of finding a path in the grid shown in Figure 3.14 from the position `s` to the position `g`. A piece can move on the grid horizontally or vertically, one square at a time. No step may be made into a forbidden shaded area.\"\n",
    "\n",
    "Below, we'll print the figure referenced above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 114,
     "metadata": {
      "image/png": {
       "width": 250
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "Image(filename='grid-environment.png', width=250) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setup\n",
    "\n",
    "First, let's create a very barebones `Point` class. This class will enable us to compare locations with `(row, col)` combinations and aid in printing the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Point():\n",
    "  def __init__(self, row, col):\n",
    "    self.row = row\n",
    "    self.col = col\n",
    "\n",
    "  def __eq__(self, other):\n",
    "    try:\n",
    "      return (self.row == other.row and self.col == other.col)\n",
    "    except:\n",
    "      return False\n",
    "\n",
    "  def __str__(self):\n",
    "    return \"Point(%s, %s)\" % (str(self.row), str(self.col))\n",
    "\n",
    "  def __hash__(self):\n",
    "      return hash((self.row, self.col)) \n",
    "\n",
    "  __repr__ = __str__\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below are several global variables to store our board boundaries and moves (deltas from a given point)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "MAX_ROWS = 8\n",
    "MAX_COLS = 8\n",
    "\n",
    "UP    = [-1,  0]\n",
    "DOWN  = [ 1,  0]\n",
    "RIGHT = [ 0,  1]\n",
    "LEFT  = [ 0, -1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we're ready to create our board complete with start and goal coordinates.\n",
    "\n",
    "*Note: There are several ways we could tackle this. I feel the below approach is the most explicit, but it is not the most efficient or scalable. If scalability were a concern, it would likely be better to hold each dimension (x,y,z, ...) in parallel lists*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "BOARD = [\n",
    "  ['o', 'o', 'o', 'o', 'o', 'o', 'o', 'o'],\n",
    "  ['o', 'o', 'o', 'o', 'o', 'o', 'o', 'o'],\n",
    "  ['o', 'o', 'o', 'o', 'o', 'o', 'o', 'o'],\n",
    "  ['o', 'o', 'f', 'f', 'f', 'f', 'f', 'o'],\n",
    "  ['o', 'f', 'o', 'o', 'o', 'o', 'o', 'o'],\n",
    "  ['o', 'o', 'f', 'o', 'o', 'o', 'f', 'o'],\n",
    "  ['o', 'o', 'o', 'o', 'o', 'o', 'o', 'o'],\n",
    "  ['o', 'o', 'o', 'o', 'o', 'o', 'o', 'o']\n",
    "]\n",
    "\n",
    "START = Point(5, 3)\n",
    "GOAL =  Point(2, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finding a Path using Depth First Search\n",
    "\n",
    "In this section we will find a path using a depth-first search from `s` to `g`, given that the order of the operators is `up`, `left`, `right`, and `down`. Below, we create our moves list representing the precedence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "MOVES = [UP, LEFT, RIGHT, DOWN] \n",
    "\n",
    "# Order matters, but naturally is not generalizable. For reference:\n",
    "  # MOVES = [UP, RIGHT, DOWN, LEFT] # solves in 25 moves\n",
    "  # MOVES = [LEFT, RIGHT, UP, DOWN] # solves in 13 moves"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are ready to perform our search. The below codeblock is heavily commented to describe the depth-first search process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 total moves\n",
      "29 moves in the final path\n",
      "\n",
      "visited\n",
      "[   Point(5, 3),\n",
      "    Point(4, 3),\n",
      "    Point(4, 2),\n",
      "    Point(4, 4),\n",
      "    Point(4, 5),\n",
      "    Point(4, 6),\n",
      "    Point(4, 7),\n",
      "    Point(3, 7),\n",
      "    Point(2, 7),\n",
      "    Point(1, 7),\n",
      "    Point(0, 7),\n",
      "    Point(0, 6),\n",
      "    Point(0, 5),\n",
      "    Point(0, 4),\n",
      "    Point(0, 3),\n",
      "    Point(0, 2),\n",
      "    Point(0, 1),\n",
      "    Point(0, 0),\n",
      "    Point(1, 0),\n",
      "    Point(1, 1),\n",
      "    Point(1, 2),\n",
      "    Point(1, 3),\n",
      "    Point(1, 4),\n",
      "    Point(1, 5),\n",
      "    Point(1, 6),\n",
      "    Point(2, 6),\n",
      "    Point(2, 5),\n",
      "    Point(2, 4),\n",
      "    Point(2, 3),\n",
      "    Point(2, 2)]\n",
      "\n",
      "path\n",
      "[   Point(5, 3),\n",
      "    Point(4, 3),\n",
      "    Point(4, 4),\n",
      "    Point(4, 5),\n",
      "    Point(4, 6),\n",
      "    Point(4, 7),\n",
      "    Point(3, 7),\n",
      "    Point(2, 7),\n",
      "    Point(1, 7),\n",
      "    Point(0, 7),\n",
      "    Point(0, 6),\n",
      "    Point(0, 5),\n",
      "    Point(0, 4),\n",
      "    Point(0, 3),\n",
      "    Point(0, 2),\n",
      "    Point(0, 1),\n",
      "    Point(0, 0),\n",
      "    Point(1, 0),\n",
      "    Point(1, 1),\n",
      "    Point(1, 2),\n",
      "    Point(1, 3),\n",
      "    Point(1, 4),\n",
      "    Point(1, 5),\n",
      "    Point(1, 6),\n",
      "    Point(2, 6),\n",
      "    Point(2, 5),\n",
      "    Point(2, 4),\n",
      "    Point(2, 3),\n",
      "    Point(2, 2)]\n"
     ]
    }
   ],
   "source": [
    "visited = []\n",
    "path = []\n",
    "\n",
    "def do_the_thing(orig):\n",
    "  # add the incoming Point to the visited nodes (path) list\n",
    "  visited.append(orig)\n",
    "  path.append(orig)\n",
    "  for m in MOVES:\n",
    "    move = Point(orig.row + m[0], orig.col + m[1])\n",
    "    # confirm move is valid\n",
    "    if (move.row < 0 or move.col < 0): continue\n",
    "    if (move.row >= MAX_ROWS or move.col >= MAX_COLS): continue\n",
    "    # get location value and check that the current location is not forbidden\n",
    "    # or in our list of previously visited nodes\n",
    "    if BOARD[move.row][move.col] == 'f' or move in visited:\n",
    "      continue\n",
    "    # if the current move is the goal, then add it to the path and exit\n",
    "    if move == GOAL:\n",
    "      visited.append(move)\n",
    "      path.append(move)\n",
    "      return True\n",
    "    # if `do_the_thing` has found a valid path, exit\n",
    "    if do_the_thing(move): return True\n",
    "\n",
    "  # if we haven't returned yet, then the current path has exhausted all valid\n",
    "  # moves, but did not reach the goal, remove the point from the path and \n",
    "  # return false\n",
    "  path.pop()\n",
    "  return False\n",
    "\n",
    "# kickoff the recursive search\n",
    "do_the_thing(START)\n",
    "\n",
    "# Print the results\n",
    "print(f'{len(visited)} total moves')\n",
    "print(f'{len(path)} moves in the final path\\n')\n",
    "print('visited')\n",
    "pp.pprint(visited)\n",
    "print('\\npath')\n",
    "pp.pprint(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the given order of operators (`up`, `left`, `right`, and `down`), we found a path that requires 29 moves. Below is an updated image of the board detailing the steps taken to reach the goal. \n",
    "\n",
    "*Note: the above algorithm included a visit to `Point(4, 2)`, which is not part of our final path.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gICAgICAgICAgICB4bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iPgogICAgICAgICA8dGlmZjpZUmVzb2x1dGlvbj4xNDQwMDAwLzEwMDAwPC90aWZmOllSZXNvbHV0aW9uPgogICAgICAgICA8dGlmZjpSZXNvbHV0aW9uVW5pdD4yPC90aWZmOlJlc29sdXRpb25Vbml0PgogICAgICAgICA8dGlmZjpYUmVzb2x1dGlvbj4xNDQwMDAwLzEwMDAwPC90aWZmOlhSZXNvbHV0aW9uPgogICAgICAgICA8dGlmZjpPcmllbnRhdGlvbj4xPC90aWZmOk9yaWVudGF0aW9uPgogICAgICAgICA8ZXhpZjpQaXhlbFhEaW1lbnNpb24+NjY2PC9leGlmOlBpeGVsWERpbWVuc2lvbj4KICAgICAgICAgPGV4aWY6VXNlckNvbW1lbnQ+CiAgICAgICAgICAgIDxyZGY6QWx0PgogICAgICAgICAgICAgICA8cmRmOmxpIHhtbDpsYW5nPSJ4LWRlZmF1bHQiPlNjcmVlbnNob3Q8L3JkZjpsaT4KICAgICAgICAgICAgPC9yZGY6QWx0PgogICAgICAgICA8L2V4aWY6VXNlckNvbW1lbnQ+CiAgICAgICAgIDxleGlmOlBpeGVsWURpbWVuc2lvbj42NjQ8L2V4aWY6UGl4ZWxZRGltZW5zaW9uPgogICAgICAgICA8eG1wOkNyZWF0b3JUb29sPlBpeGVsbWF0b3IgUHJvIDIuNC41PC94bXA6Q3JlYXRvclRvb2w+CiAgICAgICAgIDx4bXA6TWV0YWRhdGFEYXRlPjIwMjItMDctMDhUMTI6MDA6NTMtMDY6MDA8L3htcDpNZXRhZGF0YURhdGU+CiAgICAgIDwvcmRmOkRlc2NyaXB0aW9uPgogICA8L3JkZjpSREY+CjwveDp4bXBtZXRhPgovSbapAABAAElEQVR4Aey9eYwk133nGWdm5H3UXV3VdzebbF7mIVmkaUm0RFumRxRsC5YxGA+8xsCeAcaYxf412D8WGGANDPaaNXYH/mM9Hnj+WC1srUXLPVqJGpkiLWooUhTJ5tHsbnZ33XfeR9yx38isrsrMyqqMrMojIuMXKrEjI15EvO/n9+L93hXvsXp+kaGNCBABIkAEiAAR8DIBzsuRp7gTASJABIgAESACNgFy55QOiAARIAJEgAh4ngC5c8+bkAQQASJABIgAESB3TmmACBABIkAEiIDnCZA797wJSQARIAJEgAgQAXLnlAaIABEgAkSACHieALlzz5uQBBABIkAEiAARIHdOaYAIEAEiQASIgOcJkDv3vAlJABEgAkSACBABcueUBogAESACRIAIeJ4AuXPPm5AEEAEiQASIABEQnCOwTMswjGpVLpRKiiw7v5BCEgEiQASIABEgAl0RkEJSIhaXpCDHcSzHdry2C3de9+Wraxsf3vhka3vHsjrenAIQASJABIgAESACXRNgWWZqcuLRq1dmZ6ZFUeQ5vuMtunDnlUp1eWXt1qd3Pvr45k42JwUDPN/F5R2j4qYAFjZZVnL5AmKViMckSeJAF3+juJmmoWqaqmqKovI8F41EAoHAKArd1aSqaqlcQfFUFAUoDQaQkju/Kt4EYpkmUrKczReQdtOpJFKyN4U4ijVsqiAda5qu67BpJBxGPujoSm8GQkouFEuGaYSCkp2ORYFzkOl7UauFhGyaVVkpFkssyyaTcSk42ilZlxU1k8mFai/s1ORkJBruaLgu/HGuUPj5+x98fOPWxtY2HFs0EsZfxwd4MYCJtGOY+ULx5u07FmM9evXBVDIhCHhVRtOdo+CCPhSUXba3d5DdX7wQiTlIOl60bD3Omay6vrlVqVRgVni4GNJxaDSzBvhy3TCyudzHn9xC6n3qFx6bGE9713AdY15BV2CxiJSMTD8cDkWjI56St3eU5dU1FNdmpqfGx9LBaAS1rI6UvBhA1w1UNrYr2U9uf4qs+BceuRobG03vU7cO6hulTA6Wxc+qLH8mJPXYnctVeX1jE/mgYZrpZOLU7MxYOunFlNExzigG1lNPuVJBNT2ZSJw5PSei6DuidbhSqSyIAhINsn6W46YnJ+bnZjtS8m4AUQx8encRFThUzeHR50/NJBJx78o5IuaGYaICh4JLsVhEbXU8nTp/7swR4b1+Kp8v7I7vYRjUy2emJmdnprwu6oj4oy7+4Y2baI9A9+rEWHpmehIlmCPCe/cUNJbKZWTI+D9eW5RdRjsl72SyaA4vlMqb2zvpzSScrxPbdVE7x+3g24LBYDwWhXt78vFHZkb0VbEbnxUNow/+4b/+FJIffODi0088LoWCKBU6Yeq5MNls/s69BVEQKxUZ7u2xRx564PJFz6lwHuF06vbC0jIyhbPzc5cvnX/oyuWJiTHnl3soJIosaHpB8TQWjSL1PvTg5V/8zJMein+3Ud3a2pFCIVgWYifHxx5/9OqF82e7vYmHwsdjsRs3b2eD+fNnTl998PK5s2dSqYSH4u88qnK1mssXkRv/7L3rUjB49aEHnnriMeeXey7k2toG4ryyuo5X2Pkwte78E+4rCDzaJsfHUvDlc6dmPIfJSYQN3UD3273FJbQ8IytESfDU7HQoJKEK6+Ryz4VBU3OpXNra2o5EwiiroZ9mVC1bN00+V4BMNMyiUo7G59nZKQw58ZzVnERY13R0oyABo2NVFISJ8bHRtiw0bm5tZzJZVNMTidj01Iin5O3tDKrjGC6QTCYmJ8ZPzU6l0yknCcNzYaoVORTOpRdS8OXoTp6cGPGUDAONLaaQjIulinNj0XfnzllRSCJABIgAESACLiVA7tylhqFoEQEiQASIABFwToDcuXNWFJIIEAEiQASIgEsJkDt3qWEoWkSACBABIkAEnBMgd+6cFYUkAkSACBABIuBSAuTOXWoYihYRIAJEgAgQAecE3PjllT0ZfFcTwmP2VeeKKSQRIAJEgAgQgZEj4Dp3rplsXhVVAxMGYH5VBo665qoxTe++y67t3j/AMgLHRjhZcp2UkUssJIgIEAEiQATcSsB1PtCwuFdXrW/fKDbWz+sevc6w5uKbcP7uo6nnp7GEhtF0lH4QASJABIgAEfANAde5c6xykpI43TxogUb/3nQ2LvGM1eaCpkD0gwgQASJABIjA6BJw3VA4lrGSwe5WLosFUDU/1NmPru1IGREgAkSACBCBXQIudOdMLNDd2LaQgP51cueUpokAESACRMC/BFzozq0gx3QVLZG1yJ37NwmTciJABIgAEWC685sDAWaPVGe4hnHsHZ/KMybXXfN8x1tSACJABIgAESACXiLQVTV4EMIwiJ1jrK68M2cZXYUfhAx6BhEgAkSACBCBARJwnztnbV/O739k3gGG7f5td+74gg73o9NEgAgQASJABLxHwH3uvFY75x1XtxGSxxfn5M29l/YoxkSACBABItAzAq5z51DGs5aIT8+cbZLAIjx5c2e0KBQRIAJEgAiMJgE3unMMhQsJTh10PMjxLM0hM5qpk1QRASJABIiAQwJudOdwz7GA04iNhXjnHe0OoQwlmOWnDgNfiW1MTr4S7iuxsLJ/9PpHaf3l9Ypep16zMUvq9z4azzExnMOnjIfhzj0/h4zOCNkKGhkc9zE4pOPKYL4S22gBXwn3lVhY2T96/aO0/vJ6SK9Tr9mYK/V7n2OtdMhpxCYjWFCt3zHq4/2x5Eymyv/4bvXOdtUc9TEAvhLbmGhqwrl/ICs3QhmVff+kav8oradNz+l13RIs4Aj3PCY5ddETYeej4N2Vf1gMV1L5W1uV7y4Y1zPMH1xxKtldMpzFxldiG5Ggma6kCmTlRiYjs++fVO0fpfXE6VG9bnTnmLE15cydwwGi7xy1eXtddC9trGwGlrZLL9813t1mdM/3FRyN3ldiG1HsCa+SlRu5jMT+nnFH/hX2j9J6wvSwXpe680TAnrbV7OTnMHlMNMB6agoZVjaE1Zz8yoL81pZV0hpzNm+VSBpjfti+r8Q2QqgJz8rfX6y+vcWQlRvReH/fP6naP0rrqdLzet3pzpmIyDpx5zzLSlwnn++a/EM1hc2C/uOV0utr1rbcGi1vlUpaY3/gt6/ENqqvCdd+vFx6fZ2sPGolVP+kav8orb+8o6HXje6cYa0gj4VYWL1T9ZznENZ0f56hW3ymYr2zUv7+srVaacz89/dPqAKFGsvaHeJf27H3wc+ek4cb6Hf5vhK7bz+MbR6klS37syjb6Axbs7IpDrZcO1Cxu2l7aEkaVvaPXv8orb+8o6TXle7cnhiOETnmQA22MfO09+HyTdNwc2O7yXC5KvfJevFbC+xyqTX+zb8PXeW91v5gu3trNxO3c3AMgzfsP043GeyYtWwd/8VPxWSKqpVTzKxsfmGWHZPUE5YVmuN56C9fiW2kYFpcTuZurBf/XydWbrzy/n7NxLUftTJZzVV3ZWWerHyfZY//9U+q9o/SehIZPb0udedoaQ/ybBF1jyM3zB9nGro73bk9pFkT7myWvn3XupmH3z1SiV38Z3SDszgRLtkw4KHtP9OE27bgvLGvGExZY/KqBSe9I1uZqgmHXVTNqm5pCG9adnj7z7Ir47bjt5eafXYq1uHBvTjtK7GNwI4j3Gy2sm3iFitbNStbzq38DKwMe/e51HYcsZ5N0rV3yC+vMFm28aU+uO+VzNmN7hyZElZICziYUkVE7dwwDq3VHjTLQI7g3aho/NJO9dpC5YMsW9UdPfXle8aWUjVQsdassm7hKkW3UM9WDThySzMZdD3U8n1Hd6sHQg4P797FBd0H9ZXYRjw14dzSjtytlTeVKkppvbWyRVZutM2J9/2Tqv2jtJ4oRluvG905uNu1cwcTydgrtaDvnHUQ9MRvuJMbIK3IOreSVV9brryxiaJ9F9WljGz93d2mke5Ontg5TN+8ua/ENnKuC1/Oqq8vq8ew8jWyciPNY+z3LUkjLv5J1f5RWk9iftDrUneOMW5BB6uwYKWW2kfnx8gSen4JqxrsRtF8e6X4yiqXUbpw5D2PStMN+xIRX4ltwqkaHKz81krxB2TlJjAD/NGXJI34+ydV+0dpPVn6Ra9b3TmLRdU6ZxCR2uqoncP1OQTGo22VrI/XCt+8J+RVtzQV7CbkXmv3ldhGeL4S7iuxsLJ/9PpHaf3l9ZVeBz6zMUsb1D7PM3DVHZ+G1VFVvZgpGx1DdhXA0A1d10payRQM0zSxk61kZUvihdb+fJblq1r4zrb2nSV2qSygb9tVGwiiwz1bztmNiIdvuWq+qJaqZlXjNJVRC0ohU84cDO4Rsdn7Yg9NPwWlCJk6p8mWXNLKkC+WW16EJly2cDV8Z8fVVs5VILx10zVDluWyVraQNgWjpJay5TbBGi+D2IoWcnmSzh2iIl/NQ6xsyhqjKqZckAujrbeoFDXUPJGSjWpJLUI+U2pKui2Wrepuz6wOs6xcVaCuolfsPJnXRyMlM70exd2SizVaf5j7HGPFxEOz472YJYNsvprJV6t7R3qyYximrus5OWeIumWaeSW/WdwKqkGhwZ1znChw6UxVeGVZu5Hn1IF+2u1cJYvyyHph7egL8oVCppIpakWVlatWZae8s56LNl7CcQGR94rY9caYt93fLm9DpsopZaOUk7ObhU1DaD9qwUPCN4qbENsyGRGSsSKrBbXABE2LZ+2UXNhqZNKY9yNJ81wqW+G/7/okvVFqUrGnKFPKQmPFKCusUrEqSNWbhQjONsrcC+wlvTXj7sV8bwcCVVbReK1slLPVHIwL4fa4yOa800OZVdtkDL2yrBTKReRRlmggW0bmXE/JbQeB7lq26vaU3PNB3EN251gStO0yYobJcg4arfEhFscG6p60OQHjE218XKDupfujdg6860gi9a1+FfZNVHLtbf8hAWF8Nc/95R2+2N4RHPXAgZ7DDPj28w6IbIiEfQ5TdNRGR9v/1LaG84zAe0esLaYmdt9WjVLq+/ZEO7VP+WpB7+/b55o5eUU4Svm7cvA6NRT5ayIhyTZt7R/btAdx1I/w7NhqjnV/krb1HaLCVrerz96xfx0SEpI9pHdPVYvtama1nTcC1L5QtTMqO0yzkQXOG+/vbjJujnxdsp1wbbU1c9bMWjvSWnCpB+a5MW9kzvXo9u6/w3TnMEWuYt3ZrmR33S4yonpWxMIV/2StcxP6q0vq9JV5AXO9IkXXizq1O0yE+LBVsMzt44EydUPT9YgY5XS7tBERI8lwQgoGhYDYcEPlTDr8z0X92jJ/q8C6tXaO4g6XDCcbot1ml1W5jJiT+LBgiQEmGAvGk5FUczj5dDriDbGRDmKhKxbIBqygYAaCrATjxqVEMtyid099Xbh2bVlwt5V5W4I9bVrTZqCxnVNCYoTVMWaUg9hEOFEL0RqydlD2SJLmE6HEQbGQoJX1sBgKskGk5CAbiAWjiXC8iUjTD8/o3TNuS+EkGoyKVoA3hCAnYT8ZSiYidfs26WQYr2RW7ZMxxARZhdHYkBBGnszxQiQQ3VPawqSm3Bt6W4x08p/DdOcoU8bDfMng/vxG3XO3zWKO0piTzT97t9wSAmX3f/V0dDbJh4MzLacc/kTfuaZp6dAirwmYdi4lpWYS06GQJIituObSzERMWcnr31rgl1oj4vBpfQwGoCInTKVmjqqpMkzIkvLhUlzcDppSmA1PRMdPpdqgmx8JscCdixYgM2hWonw0LaWm41NTqYkjzOB+4cjhpqNT9bJwoxBd06sBORlIsArHCXwqlJpJTjcGOLjv/iQtcPxUarptkuYUYVXaiggZiQmF+eh4dHwm2SYlN6r2ht7YVFu9m+GdoCWJRjUmxMZC6an4ZDp5WMGU8bTSqiijCB4PxDmN53khjZSc8HxKbmvTxsTZ7X6rf+r2+hOGFxj90engI2sVLPjdq+0zs8ELUSPs5Lv1Ez8S38fPjQXHY+JERLlbYF5eZLd63I9/oijayaV3ScZXYhu5u1/4QUfeGP+u9t0vtodJGmT8o9c/SusJ3m96oXrI7hwxSEjMV87wH2cNNLCffIMJvzQvRER0aDvoez/582ruMhTgzk+GJuL6mZj2foZ9dY1xk1PvnT/3mdjG1AGINStLEzGDrNxIZhj7vUzSiP99447+K+wfpfVk6Te9w3fnPGtemgg/Pl7EytAn356bD86ENOS8J79VV3dA9SgeEmKSMBbRHk4bb2ywP9mwCs6G4nX1oG4D97DetvdoX4ndU40dDMyIh4VYiKzcSGXQ+/1I0jXj+uUV9tv76x+9w3fneJGiAf2lc/yNnFE62ShxrJL+4lkxIZ3sLifInZBu0jExGRFSIe3ZafbaIvPetil3HtJnPzIpcV+YD2A9tJxiFRSzNm27vbaKZlo4iAnbMZ27URve2YtWjBOIvH+pr8TeF23/6yvhvhLrK+OSZUcvc3aFO8eYuPnx6FMT+VdXG7PNrvd/eS4QZmRRGLIojmMnE4HxuPU7ovqVeeGv75of7HT+LP0bV0KPpVTMQq/p9jd2+FQP6/ehy4Dj7ZGc+MdiOdlkS6q1UzW2KsZmWd+uGNiH75d1OPt2Azzt/KlrjF1d4CuxjWR6ILy+sq3FMfgqk6zsmiQNK/fAuB55hf2jtP7yHlvvKWG1KGeTY2OxUMq1mfOQPd9e/ihx6gunxQ8y2nbHRc73rmnemQxzz89x6UEsB9r84EN+YVG42XRwTDN/P2gtlcRrC8bt3FGzxuFzu4DARppH8MFF24ujwr/XvzzlWUuwzoVYM4Xp3uyZKe//sQa+4GftP4PhNMtexq2oGgXZELjOJYlDFHRx2FdiG7n0TjhMvGdlxhKYrq3c53IbVPdOrAeStK/0kmU7Zs74ClI3SzwfnojtfgXjwszZLe4cEwTMpqTnpvW/uXfMtuTPzwlRXuNY9yiys/2gyM0m8eW3MR/lPsoJryzpi4X2/rXtDEFoELNzafyzvzXu11lhoXPwQ3t8bQVV055DwsKcemGExGQ8WEB2QJuvxDYy3RUeOomV29q//pC2VkZmwtpWDrFMEgNAycqNBunlvn9StX+U1tPH6Ol1kfOTeP3ZucCbm8pqpeu38XSc++wkg07rrq/s/wXwxZEgHwky0aDxYEp4c5P50bK+WTng1I/IzztF0nbYLGa5Yu055ffnlYcbcNZv3+n+zs/7SmwjFlu4xEekzlZuvKqr/WYr7xXSyMpdUTxOYP+kav8oracD53qPk25q1zS/tnu36ctr6yr/Z03GxRfm1P94s14d2VPeYQe8vjwvxAKY3rJDyOGeToT5eIh5XtQ/MxX84Yr52pJa1vaVujvuXZPzldhGOrvChZqVl83XllutPEqG9puV/aPXP0rrL+9o6HWVO2cCnP7EqdAPVivLpcYcssP+xST3UNJMhN2lpW2kUeBIRYSEZb7IGV+ci1y7p72+pOz2qLu8MNJWz5EHfSW2kYQtPFqz8rzxxXmyciMbz+/7J1X7R2k9UXbQu1/zcm8aHvT32R1JpMPsb57B4k8dA+4HePEMn0QPonc2DDwZjwkzYe3r561//ZnIZ2eDiL2XBHSD2ldiG8HYwuNk5UYko7Pvn1TtH6X11Olpva6r0QqscWU6dnml9DEW6XawPTzGzUfNcLBxcRQHl7kgiCiw41E2GtRmwvwzp6Jjof1ObxfErsdR8JXYRnZ14ZEAWbmRyojs+ydV+0dpPWke1Gt1P6Jr8Kncde4cCJKS+bVz7L3rFr62OnqTeOa3z3HjUZSojg7o3rOSyEmiFRbUqmHyXTVKuFfToTHzldhGCpimMBSoW9kgKzeSGYF9/6Rq/yitJ8s9vWVdz1mdvJELkrIb3TnHmucnow+nCm9tdfDSj41z8YARPLDQmQvAdhcFLBgTZjDWvYPe7m7q1tC+EttohJpwdMGRlRupjMi+f1K1f5TWkyb0CpyaY4c22ajzN8R1fef1qEdF/cUzQvTIFvR4gHnxNDOdCjhXSyGJABEgAkSACIwkAZe6c3va1zHpmcmjRhN+bopNSvZMVSNpGBJFBIgAESACRMA5AZe6cwgIi+Zzc4F0sL2WiRDzzJSFhcbbn6ajRIAIEAEiQAT8RMC97hwV9LlU4EuzB2ZPq5nnCzPMRITHfPp+MhZpJQJEgAgQASLQnoB73TniKwnm06fCiQOd46iaP5q2Ukd3rbfXS0eJABEgAkSACIwgAVe7c1TQp2LcN87qLZXwl05bU3GROs1HMD2SJCJABIgAETgWAVe7cygK8OaDM7H5yP6YuPkIcy7OxEZ60pVjmZIuIgJEgAgQAf8ScLs7h2UmouxXT1uBWkzx3986Y8ymgizVzf2baEk5ESACRIAItBLwgDvnWfPyROhKwh4TdyluTcdYqe7bW7XQbyJABIgAESACPiXgAXcOy4zHuBfmGXyV9utz+ljMouHsPk2tJJsIEAEiQAQOIeANd44xcTMx5vfOa/GQRq3sh5iSDhMBIkAEiIB/CXjDncM+AUGeimm6seNfW5FyIkAEiAARIAKHEPCMO7csoyDftbywrM0hqOkwESACRIAIEIF+EfCMO+8XALovESACRIAIEAHvEyB37n0bkgIiQASIABHwPQFy575PAgSACBABIkAEvE+A3Ln3bUgKiAARIAJEwPcEyJ37PgkQACJABIgAEfA+AXLn3rchKSACRIAIEAHfEyB37vskQACIABEgAkTA+wTInXvfhqSACBABIkAEfE9A6JaALCvrG1sMywiCsLi03O3lxw6fk/Nblc0gF1yPbkuCdOz7OLnQNExN1z/8+GYunzdN6+NPbkFsMBgQBN7J5Z4Lky8Ul5ZX79xb3Njcqsryu+9/UCgWPKfCeYShdHl1PZPJhqQgx7GqqqXTSeeXeyikrhuqqt64ebtYLPE8/8FHn4hi16+8h/RmMrlbn8K6K+sbm7KivvPe9Z1MxkPx7zaqt27fXVvfzBcKSNKwbzafT8Rj3d7EE+EVRS0Uijdv3UGeXK3K1z+8Mcho64a2Ud4saeVVaWMlsjGAR29u7UDs9k6G78bpsHp+0WHkbt789OVr33/75++vrK1pmp5KJkJSf91qY8QMQdcCCmfyghbgjP42KmBxddM0kd3fubdgWcy5s6fH0ikeGf+IzhevalqpXEaOD78eEMXZ2el4NNoIf8T2C6XS6uo6MohoNBKLRRLxeDAQGDGNdTkWJlM0zZ2dzO0795B8L186P5ZOj6TSuihFVeHbSqVKtVpF+Xt6ajIaiYywXohFQbxeHo3HYxCL93ck9SIZo2CayeaWlld4jr9w/mw6NcAiOGvB+xi8yeuCqA4ir0C1KpvLh0LSxXNnn3risReef+78+bMdLdt1Ud20TF3XQVZWlI5372EAUzQMRmUNTldN/LeHdz54K2SCcOfIGgzDXpUVYpE7oPA7qu5c0zT4NvzXgGlZVpGVqtB1wjiI0bVHFEWBUMOAXA1ZId4cmNu1sT1JxOruHCkZAi1YFilZlk9yQ5dfC4HYdNQ2dJ3jOORReG1dHueTRA+vbT0l119hgeeRqk9yQ9deC10wqp1H1fJkRVUGmpJZS7c0SzQ51dCVQeQVSLpIyWhLwyvs3Chd59qotz14+RJKRpcunkunU86fdMKQRa2YVTIiF0hLaTS5n/BuR1+OvA+5PVoj/u57PwDNF57//JXLF0RR7Krd4+hHuOpsqVheW99YWlm9u7AUjUaf/eyTc3OzrophbyOzvLz6xk/fyefzszPT86dmz54+FU/Ee/sIl9zNzgRVDb1Ff/ufvw/H9usv/MqDVy65JG79iEYuV0AP4Oraxtb2TjKReOqJR2dmpvrxIJfcc2Fh6e9f/0mpVH7g8oWzp+dnpycj0dFsjUCxGzJv3r7z96/9GFnxb/zal9HUNDArGKa+o2SqRiUmxtPBQbRvoW0YPSloaIqEw85ldu3OJSkYj8XOnpl78vGBvio75cxqfhW95qeSs+FAFwqds9gLaRoG6qoCz/34zbfg2h+8cvEzT/yCFAqiB30vzCjtZLP5O3fvBQKBSlVGH8rjj1594PLFURLYouWTm7eR50uBwLnT88gUHrpyeWJirCXMaPxE1Q2DXVAk/fvX3xB44eqDD3zus0+OhrS2Kra2diKRELpOUK2ZGB/7hceuXjh/rm3I0TiYjMc+uXUHrbIXzp556MHL58+eSaUSoyGtRYVcrebyRRzEeAgpGHzkoQeeevLxljD9+6np2nJupaAUxqPjpxKDqOqsrW2gMXhlZR2Pdq6ra/+Efgt4dHQ6JhPxdHJwvRfoOy8a+ZAYTiUSkWB/S6CmiQFEWiwWRTEQ7jwWjabSiVBQGlV3juQS34khH8R7gvEQ6EsepGWdJ9ZehYRASZICwUAoLMHKyAFHVa/tzhUFLS5IutjQuzqqSutpA3rxtobDSMlSOBRKxEfWsnW9GPgWxBiBgAjJ2B/hlCzXxmnB74iCgIoHBgoMMiWrulo0CpZgJgeVN1YrFYyEgG0Ns4vek67dOcux6KFBCpJCEnLDXuWwHe8j6cGgFJDEgBRGPbm/zzV0Ay2T0IjuN0QMO3giRiUIIzoqOCTX8wQRqvG24McgLdvR9D0PgFILPlKoiRWDARHF01HVq2t6LQGLSMkYy4ncYVSV1hMJLGs7N9TNBR7/GWHL1vUiT9xNySJScgClmBG2L7Jg2NZ+bweeknmNk0KBoBWADxoM4bpYGJdluxgo1kXQnueqdEMiQASIABEgAkSgJwS85M7ZniimmxABIkAEiAARGDkCXnLnXQ3ZHzlLkSAiQASIABEgAocS8JI7P1QEnSACRIAIEAEi4G8C5M79bX9STwSIABEgAiNBgNz5SJiRRBABIkAEiIC/CXT9oZq/cZF6IkAEiICPCNhTjHYxzSiD1blozPKw0ge582GRp+cSASJABFxNQDPZvCqqBkYhW7ZT33XVmK9s32XXdu8fwEqbHBvhZGm0HAsWPOD5KYGvutpaDDNa1F0Om6JHBIgAEfAOAcPiXl21vn2j2Fg/r3nyXXdec/FNen730dTz01j2pou5zJqud+WPfJVZybET0WmGcfUKRtR37srkQ5EiAkSACAybAMcyKYnTTQbLmO394aduWvU/4/7O3pG4xDPWINYcGxgb02JWc8pf3hGLaoTjXF0BJnc+sFRBDyICRIAIeIkAy1jJIHx6F1ssgKp5Y2W+i2tdGBRKVjLK3y3xRY15ZRk8BrGc2rE5kDs/Njq6kAgQASIwygTgyGOB7sa2hQT0sI+OO5dVcyWv3yrYRZobeW4ha6ADwrUmd2/MXIuMIkYEiAAR8AMBOOYgx3TlJETWGhl3jvF/q1nlWwu8Wus9wH+/s8RtlQ4OGHBLWujKUm6JNMWDCBABIkAE+k7AHqnOcA3j2Ds+kWdMrrvm+Y63HFqAoqzfLTBL5f0ILJXZj9eKqtFV/8P+5f3eI3feb8J0fyJABIiAJwnAa3GM1ZV35iyjq/Cu5YKq+UZee3mxyXNjWNw37wkbRfzbdNwlKsidu8QQFA0iQASIgLsIsKzty3nHnst2/7Y7d3yBu+Q2xSZb0t7PsFsHPjXPq8zbKxVZd6PrdGOcmqDSDyJABIgAERgGAds9MxbvuLqNkDy+OPe+NzdNa6tsvLrWHvorq9xKVnVhBZ3ceXuD0VEiQASIABHgWUvEp2fONklgEd773pzZLmpvbLSpmtcxZBTmtWW1ojnm4ozeyUOROz85Q7oDESACRGA0CWAoXEhw6qDjQY5nPT+HjGlZOZn5ycZRn9u9scku7VTdVkEndz6aLyGpIgJEgAicnADccyzg1E2MhXjnHe0nj1uf7rCeVa8tMgX1qNuXNObagl7S3DVJnFM7HaVsUOc4VoqGzyraoJ7ngucourVTYSuK5wu8zln6R7J/lML6vhI7SnrReI6J4Ry+v+NhuPOjKrUO7zPEYIpmFlT+ve3OWe4HWfbOZsns7rP8/ipzaqf+xsLZ3XkuoPLp26XEdpmt1j/sd3ahd0NhCqKsLl3PBUiyd414WMx9ZVxfiYXFR0Yvx1rpkFM3MRnBgmqHpXcPHMfHadsl46/vmrKDFWSqOvPtu1au6hTOAPS7KCpO1G5VjX/3duk/fWLezovbJVPTvV0SdCr5LZLsBJX3wtjp2TfG9ZVYpMXR0Av3PCY5ddETYeej4N34tlZUY6nEfbDTuWpej/3NPPPJelG33DImzl1N/50sjMKTPR3wm6vKW2vKc/PBF8+KYUZOx5CGnCa4To9w3XmSPMJW9pVxfSUW+cho6MWMrSln7hxZMPrOUZu310X35parWNcWnPpySDQs5lsL7IVJazLiCsFecudIJozt0O0Ns/L8aFF5e0395bnA83NclNeSEWE0fTpJHmEr+8q4vhKLTGok9MKdJwL2tK3Ico/ekP1GA6x3M+F8xfgox93O6UfLbDm7XGLeWak+fzES4Lq7sOU+PfnpJXeO4m5Liipr1nfvKj/b4D4/J3x2EiMwrUTYLe0ePTEP9JLkUbWyr4zrK7F490dGLyraEZF14s55lpW4luyqJ7ngIG6ColdRZV9ZOk737feXrYcn9bkkUA1Zfr/cuaxDWX0de3uBHfyhgIc0YbeKd7fgXrMt2+HarJh/dVN9c5378rzwUFJPhthwEEmr+cL+/yLJI2xlXxnXV2KRMfhNb3d5IWsFeSzEwuqdquc8x7CWOfB8tzs1h4XOVfQ3N7nFQhct7Xu3Wq0wP15RXopFJX7In131xZ3D55ZN6b9ucnGJx2r2WAEXq+bZK+1gOl/LwCyA+JgBnzPiC0Xs1Hw83LxVd8BIDbbHrzn9gy75QP18DykDS/yHD9WLSe7FM/x8VBuP8kFxcAP9SPIIW9lXxvWVWGQfftO7n2M63kNGjaxU7hQeLt80jYOZdqfrhn8e88aUdPFHy8qxo/L6mvX0tHx+DP4UCWpoW1/cORShKPd/v589WKCDt8ZgCcwFiPmDMG4C3yni2waMh8Q++l3QVoPyHdKEaeimYTCWCTcPl4+ZiTSd5zlJx9iDwzecu5Uz/13OfHiM++1zZjygTacCAxol1wfJosBqBkOSWww+BCv7yri+Eou05Te9La+Tg5+ocaG5s9jJUSGXRr7tRXeeKRk/XGHQyusARvsg2zLzyoL+T1NhiTt+maD9rbs52h93jhgc4nZxGD6+pOLPXC3ujx2oV8rRRI4WG5TykDJEjsVcwZhfEEPc4PuTwbTApV9dOrDATTu1+NLgds58bJx78bSWlJjxmDiIJXh7L9nmQJLbWdg+NlAr+8q4vhKLlOQ3vYe9Ue2OI2dGjSjgYEgScmzUwU7Sldru+X0/hq+dK5b0WuOq5sd65ltb1vPbpYuTQYwaPNYNenBR39x5l3HDC4XBCGj00GwUh7xe3dwT8wC8uWF+nGU+N8U+M6VMRPhUVHRVyZEkd2PP9mFda2VfGddXYuvZk68yK7t27qDf0l6pBX3nrIOg7d/m4RzNy9a1exrG257w8Zj29eW7xh8m0b88cu78/jcaJ0R00ssx7+73lqx3tpkvzBiPpvWpuBgLoQkAJc7ebyS590yd3XEAVvaVcX0lFknMb3qdvVX7odBiGnSwCgtaUmsfne9f6P49WTPXquLrJ66a15W+u83c2qo8NouuieF49P6VpE5a2OlhUsAS9H91h/nTD9mfrmh3NmVMENufyPXnrscCQZJ7bWVfGddXYvGC+U1vd3kKhsJhoGvHDb2inpuwvaTyP1g6OMSro9b2AfCV23cXjLzcl+pi+0c2H3VgpeYLHP5CgddFr0gt0vBw/9cn7HyE+a0z1VMJ4VQ6iEakHm4kuYcwj32rPlnZV8b1lVikNJfrnY6x6Sg+/GmToVa0is7qBmeoplrVqiWlLMrisd+dwy60uChc9WFn945jhJPAOZjrfO+CYe9gaatPS4Gfrjoaj+UwstczzPV1+dlzKP/sjwxzeO3Jg/XLnSNmne1/8uh3fwc0q/z7G/yluPniXHEsxgp8GVPMtdzG1A1N1zNy1gig4GZmlexaYV1Sgrx4OC50/AunvCAZIw2bJCOTyOfz25Wdgl5QOLnCVDbLW8vZWAuTNj9RYhPnXC751+eK47FWyVtlOP2Kystlo5iVM+uFDV088oNRGNcjSvlm4xq6LssKErApGfgwdKe6s5xdbWPKxkNeMGvt5W01K0RsFzIwaMkoymy1bJY2S5vRbKhRXJt9DxjX+vU5IxnWsQy3aTUl1J3yjsJWNV4pGgUYN1oIyWyljcaTHZKC6ZiY6niPZJDFxzgdg7knQNUQxkLiHz8dtwtKFgp1djMN/oePib55o5qTW/1CS8zTEvvSWb6m2L62dgP7HhHeLFTMVBh9uvbPQW6H+6dBxmKwz8JibB/m2MWy+HvntZl4UFaXW55vGKau62WlaPF4hayyWsqWskEtIAiHj+9k2Vh8puU+7vnZLFmqqkuNcStUikWlUDUqGquqllyQ89nSTmOAQ/bZeHz2kFPDP3yE5LxcUCxFY7WqJRfVcq6SYwP7EbbfwgOvYSLhSaW6biiKWtZKjGBYAlNSiw4s6xmzTselqtL08mbL2aJaqhpVlVFkU4ahM6XMvmnb73lFLzMTT6lak17NwNBh0569BZ+IGbqqq6p25DLd7QnUj7KiiPVNA+0cssA56JW1Pyc2mPL91Zwb74NlU530vh8Vuz6ciwaMEF+eDe7fuv7eq7q1Ph/49q0OX9o/MyN8HrVw3jzote1pVA7UEvcf07c9P7rzAMdcSZhfnrPSYd0wc4LQkJfXQLMMPnlnOV6wsJatZfKcIAoBUYQ738VVL8m1GuWAD2gNMLzf+5JDkJwV+SbJAieKnMjbHwnigz4e+wGhIY0PL9onefIRkgX7A0AWcxxAL/r7BE4ICL1vojxJ5Lu6dk/pWC09N9qOY3RLx2RNgj1dk4m2UM9bdk9supaSWwwnogENLW71lGwbV8CRrmC6LXBd7wtzzEQUH4xVRL6p2SwSCIuYlcPkA1wgJIaiwUhUih5PAkaki+L0at7K7pYHMGK4PmaYRZfwT9Y6Nx2/uqROR+DecFX9f/aMYHDqEyE+JchB5KYu2+wSRrvmBMvCtCed42qYmEMFhWTdPQ3R/XLney0PnakMMAQ6y+cj1j+aty6MB8IBGTPPMkz64PPtgq6uLwRXBJU3TTYZSEzFJiQpCK9+MPDekSLmuztYTts7PaSdPcnnx8WaZLxfu5L3vhANWVIxVInxOwEzGLJCY+Gx6cSUk/i6XPK+ldmxxhJYPlKU2JBoVSN8JCklJuMTE8mxo/WWDCQV1+VHe8bdV3rfuHU5uqbLAQUJmFUwmQOfkpJOLOtysx5MyXu24zVhU9rZ5rNBRgrzkfHo2HSyc0p2s3G/etq6PBEaj8HUSH5Nvhyqs7GSZEUCupoQU1PRqfn0fDrduVV8D1fLjs4INzPVP79R7//uOrWjdfrP3kVHXtOG7OZfPR2dTeKeDir4TZcO7Qe+RM8pneUXNQsNI0OLZbsHH+Wf2oV3fuxgg6Xza/sSMhFgvnFWf3AmNhHFCEyUvg4txsKda5oWFsMspqM1kfGH46F4KCQd4c6htlxuN1ilL1Kc3vSA5PY1FUM2I4FIkJcESxTZQDQYTYQTHZ/hEcltrBwNxgL49MYUg6wUFiNxKZ4MJ4/QC6WVsusWlzhg3DZK4c4DrIwEzOjwBxzEdrSsR8zaPiUrEl7bSJCTRCsQZIOxYOxoy8LoHjFuZ+9yRAJ2eAoVzUeng4+sVTCeq1fbZ2aDF6JG2Ml367165Invg9aIwv0ugyNuVtYtzFzK9M+FHvHsQ071Ky6DSH2HSDp4OB1kvjRrPn0qPBXjAujq6E81iyQfJD/II321sq+M6yuxSKJ+03vEW5mQmK+c4T/OGsdZWezAfVGE/NK8ELHHmXqmag4RhsnCVR9Q03qgqtvrnbtq65c7d8krEhWZZyat5+YCc6mAJGC1HwddIse2jztMS5L7YmVfGddXYvG++03v4VkcWiMvTYQfHy++vXV4IMdnnpsPzoS0EPr/PbWhCb3qoPNcQe3cHSlnj27f3Hn3fQp2ayCGJmCqdkxCxNuzBKOFBqMV8AUfvnqMYc1dzh6RkZEdIcRVD6esF88I82NoUIUj7/8HkSR5L1kdvuNVK/vKuL4Si7TqN72Hv544Ew3oL53jb+QMzFp6kg2rpL94VkxIJ7vLSWJwrGvR+YK2BM1uRu+woT3e7Gf1sMPj253ulzu/Pyqy9qbAT9fm8UdWbi+Ken9tlVgAC6tw6RA3JrEpiU0EWKQArK2LMLVM314fHYOt7Ut4e4g52kAmg5W/uNFhjCXCX04wXzvHnp+MRUV9EI68RpYkj7CVfWVcX4nFu+s3ve0cwf4xjLmbH48+NZF/tdMMBfvXtNv75blAmJHF+18DtQvixmPw5hzPa2bn7/1Uw15kxFUa+uPOWSbAs1+7EktJtsOOBVjUs/FtEFyy7aeZ3TVP0bBTW+/cPog0hDZSu5R8fzzZwRIzywntPito4jkXZX7zjHVlOpaUsLjqAAuGJHmErewr4/pKrJ3h+C+zasoy2/yQOPWF0+IHGQ3rfh5vmwxzz89x6daR+Me72UCvwicw+ETZQVs7oxgWZguHPz/oqgYa44aH9cWdQ14ioP3GGXzEDA8NP217a/zf3rG/rz/JdmhpaDbMvDDHPnEqlA7jM9sONfiTxKDttSR5hK3sK+P6SizeZb/pbZt9HThozaak56b1v7l3aH574JKmA5+fE6K8ho8jm4564Qfq2xzHO5nGHTP41PrOkYKOSannPPqFW+QssQ/d1W2xjUvMc9Pss3OBybgY4AbtyPdMQpL3UJxwx4VW9pVxfSUWadVvep28nhKvI0d9c1NZ7X7S2NNx7rOTTDLSL+fiJP7HDoPMB/NLYYqYjhtcvtK5h73jbXoZwGPEGycDAQaM4n5qgkG7EMqSSH/MMGa976U12t2LJI+wlX1lXF+Jxavscb0WakcvzKn/8Wbb0nW7rKp2DHXVL88LsQDWjDk0jLtPsLLJGg46xdHSXtbseQvco9Rj7nyvWQOd6I+PMxiBiVEb6OlhmAF2kw86Me6+TiR5FK3sK+P6SiyyCW/rRUsn+i5/sFpZLnWR5V1Mcg8lzUTYc55lVyMKYSW1pSTWXj7ceR4h7e6aXUO3DzfAo56E/kjanusA30fimwqWUQaIa2iPIslDQ9//B/vKuL4Si7Tjab0Yh4SRxf/nR6itOn0NXjzDJzstYuf0XsMIZ1pYeNCp3KwMn+6iVgiPufNUgPmjqzxmIsTsRfwgB64PI2HVn0mSh8e+70/2lXF9JRZJZwT0CqyBr4Qur5Q+zjl6Fx4e4+ajZjjYfgpeR7cYdiD4562K0y7xHRmD2/fWvhh21N014WwnGlh17vx4KB7mhrIyfKfY9eU8Se4LVnfc1FfG9ZVYpK+R0YsvfjGHx73rFuY0PXqTeOa3z3HjUc49fclHR7jtWbjzzXInqfevzFRN0zp81ez7wQb2r5em3+MYIxWuLUg3MDzDfhBJHrYF+vh8XxnXV2KRaEZGLz42Pj8ZxQybHd+Ex8a5eMAIYlJPL2+GxW47rp3nFBPh3SPXY+jt79d9tpHkETa4r4zrK7FItCOjF3NrYrZsfGByxBYPMC+eZqbRweDxDd3m6Dt3KKKowp27yIe6KCoOCVIwIkAEiAARGBgBlEuw8gXWsjriiZ+bYpMSuhhcVFU9IrZHnIJ7drI6av0OVd1yMn/cEY/r7Sly573lSXcjAkSACIwaAaxihXUpsQZx220ixDwzZY3Hjqy/t73SZQdRYEHjuexgddR6xDXDDu8eEeTO3WMLigkRIAJEwI0EUEHHGtNfmm0/WdoXZpiJCI85vd0Y9a7iZGEqU97AcDhnG0JiNVWnoZ3d8yShyJ2fhB5dSwSIABHwBQFJMJ8+FU4c6BxH1fzRtJU6umvdI4SwQprJ8s7dMzra4fot11TQyZ17JKFRNIkAESACwyOACvpUjPvGWb2lEv7SaWsqLnq/09wmC98Md+6csR2eaufOeVFIIkAEiAARcAOBAG8+OBObj+xXX+cjzLk4Ewt14QLdIOSwOJhYJA3fGDreUJunoXCOaVFAIkAEiAARcA2BiSj71dNWoOby8N/fOmPMpoLsaNTNa3Ova920nGMogWJSY7trUidFhAgQASJABBwS4Fnz8kToSsIeE3cpbk1FGanu2x1e7+5gmIC94+R3TQospri7CkvT4WH96KJhYVhRpOcSASJABIiASwiMx7hfnWfwVdpX5rRkBItgjdDGskXV6RwykI1eB0wMt9/3MGwSHluCZdi46PlEgAgQAV8TwJi42QT3e+e1WFBhWc9/a95sS64gG0LzYD9464YiS9NC6DiORdXc48/JnTdbk34RASJABIjAkQRCojYd1yvKBsPMHRnQYycx0/4vTppPPR+vTyZec934EA3D1y3d0A3T4Dle4GpfstWcPGbBE3mWd82X5+TOPZbgKLpEgAgQgWETMErVhWHHoffPDwpMgJEP3lfT1IWdxWwlN5WYmhmbbwnQUHdvOTPon+TOB02cnkcEiAARIALuJHC4b653kXcz8H3gCmko3MCR0wOJABEgAkSACPSaALnzXhOl+xEBIkAEiAARGDgBcucDR04PJAJEgAgQASLQawLkzntNlO5HBIgAESACRGDgBMidDxw5PZAIEAEiQASIQK8JdD2y3TBMWVFKpXIumw+HpF7HxxX3M0xTU7VCsaRpGibZx04mlwvJQUHoGpcr9HSKRCaTK0BkuaIoSkWW8/l8JpPtdJGHz+cK+aqMVKxUKhXozmby4ohaVtcNKC2USrquw2B2Sh5py2az+VpCrlRlGLeaG/WUjFfVTsiqipQM5ZlsbjCvZaGKpxXxrKyYM+VBzIoGg8K45VIZeTLP87bYAaZkTVfzeGS1KDFShh1E3gixcLKyoppmF7PUde2fQDOXL6ytb965t1AqlweTegb8FBPuXNeXV9bKlSoWwF1dW7/96d1gMCjwI7JwUAtPJNSl5dXNre1coYhX897SMl6YljCj9HNhcaVegtnaycRW18OhEPL9URK4p0U3DJRa1tY2qlUZhdHlldWbt+7snR29nZ1sbmV1bWsL/+Y5jr23sGy5Z8quPuBeXF5Bblwslja2thPLq3jCdjzTh+e03rKsltZK6ziq5YxoINZ6ug+/UWSB0NX1TeTJSNVLy2upRKIPz2l/S93QNsqbJbVUzsiViNI+UE+PIjeGk4Vxu8qKu3bnwIryLwqEmPhuZQ2zAo3gBheOas2ndxfwnliWhR2IDAREjhtNJ4eiPbKD1bWNnZ2MLMuf3Py0UCiNoF3vS1pb39jY3EIyFkQR9kVijsWi90+O1L92wVTT7txbhImRem9/eq9pwsqR0mqLKRaLyyvr61tbqLohp7rxya2BVViHwhJVjq3t7XKlsry8hgjkC4VwODyAmMimnNPsSuqWkJP40ACeiGSM5pZ7i0ulEryPeOvTu4bRRbX1hDE0LCOv5WRLjvDbK8LWCe/m5PJcLn93cQlNL12VWrp253jA+ubmypq5vZMJhwdhSCfiexsGWTzm4cV7AqaY4u+jGze3tjMoJaG839sHueRuyPhQcEFJEHqDwQB0wgG4JG79iAbazZZX15CS0RCdzWZRjpGkYD8eNPR7IiWjd2xzyy67sCx3/aMbKLcNPVb9iwBsms2hjamErB8VdHQxxEe0oFZnCI3rG5t25Yph0CGIUmkwEOgf3r07G5yuivbsaQFN4s2uncjefZzvwHmrqra1vQPzIit+/4OPUCh3fvkJQ8ILqELVEAxBFwP6ILqYkYDhYVGH7Cpr6toScGpSMAigqWQiGo2cEJM7L7fduWGilVIUBTQ+x2OxdCopCHBzozlyEJkgVixG3ocmWaSeRCIxlk660zQ9ihUrbe/AyiiPwrhIyaNaMEXtHPkgSi1oaedYDmLH0qkeMXTjbZAJQi82CIdNk4k4jOvGiPYoTqh1oBMQN4uEw4l4HHq7yv2PHQudVSu1xVfCVliwBlGAQHMpMmSkZOTJ2CB2kCkZs7ZDr8ZpQUsKmYNo/0CxDIMi4HEwS7xzM3XtzmPR6OT42KnZ6UeuPjg1OeH8SR4KWW+i/Pn7H6IwaFrml7743OOPXkUhBsnIQyqcRxUDahaWVm7fuXfj5qeJROxXf+XzF8+fc36550JC6ff/y492MtlzZ+YvnD9z+eL5sXTacyqcRBjrRqDq9rOfv49ec5RHv/LlLz75C486udCjYXYymU9u3VlYXF5d3xhPpz7/3OfOnm6dYduj0tpG+8at2ziONvbHH7l65fL503OnUBZvG7K3B9GLvFqwu+pn47PRwCA6qhRFRt/5e9c/QtMaWhBf/NXnH3vkam9FHXE39J2vFdeLamkslJ6KTR0Rslen0Bv4/gcfowcdFS3n9+zaPwHl+Fj67Jn5qw89MHdqxvmTPBQSa+egq6ZYKqHxCq79wrkzjz38UCgkCWLXuDyhGh2NgWBAVVX0KSATvHL50sNXH/BEzI8XSZTv37v+IdpdZmemYdyHr14Z1YKprtktLtlsLhIJQ/XFC2cff2xwmeDxrHOSqzY2tlCNQzsTtumpiQcfuPTA5QsnuaH7r/3J+M/QCYis+NKF85cvnU8PpPUlV8lFNu1WgXOTZ5PhQbTkVSsyehPQj4I8OSRJly6eG2RKVjU1mYlmyrmp+OSZ8dMDSBUYFYEhjmhcQ8eR88eNZuuxc/0UkggQASJABIjAEQQG8SneEY93fIrcuWNUFJAIEAEiQASIgFsJkDt3q2UoXkSACBABIkAEHBMgd+4YFQUkAkSACBABIuBWAuTO3WoZihcRIAJEgAgQAccEyJ07RkUBiQARIAJEgAi4lQC5c7dahuJFBIgAESACRMAxAXLnjlFRQCJABIgAESACbiVA7tytlqF4EQEiQASIgAsImBbLc1MCP4jpbE8il9z5SejRtUSACBABIjDiBPJVZjnHhAPTLtdJ7tzlBqLoEQEiQASIwNAImBazmlP+8o5YVCMc5+p5vsmdDy2V0IOJABEgAkTAzQQwvetKRrm2xBc15pVlrIbi6rWayJ27OS1R3IgAESACRGBoBGTVXMnrtwr2smY38txC1jAs9zpN98ZsaAakBxMBIkAEiIADApblldVJHIg5EATiVrPKtxZ41bTP4b/fWeK2SpDcxaKlB+7axwPkzvsIl25NBIgAESACHiVQlPW7BWapvB/9pTL78VpRNcid7zOhPSJABIgAESAC7iWAqvlGXnt5sclzY1jcN+8JG0X823TcJTKodu4SQ1A0iAARIAJEwC0EsiXt/Qy7VW2NT15l3l6pyLobXacb49TKj34TASJABIgAERgUAdO0tsrGq2vtn/fKKreSVV1YQSd33t5gdJQIEAEiQAT8SWC7qL2x0aZqXqeRUZjXltWKxrsNDrlzt1mE4kMEiAARIAJDI2BaVk5mfrJx1KD9NzbZpZ2q2yro5M6Hlmjowf4k4LYsoK9W8JVYkPSPXpbjXTkarAfJeT2rXltkCupRtyppzLUFvaS5a5I4cudH2YzOEYHeEtAZIVthTcZ1zXS9lVm/m6/EQrJ/9LJ8KBW9EBQj/Ug2w72nopkFlX9vu/al+ZFR+SDL3tksmYyLfKiLonIkOjpJBLxNAJNJZar8j+9W72xXsUCTt8V0ir2vxAKGf/TWlf58FbOp8Dwf7JQQPHYeH6dtl4y/vmvKRueYV3Xm23etXNVFPtRdbQWdEVIIIuA1AhbDlVT+1lbluwvG9QzzB1dG2Zf7SixSon/0HlQaGzVvzlRUY6nEfbCjOcxjbuaZT9aLT5+NCqwD/+/wpicIRu78BPDoUiLQgQArm4GljqfOHQAAQABJREFU7dLLd413txn9qLE1HW7khdO+EguD+EevX5TmKta1hc7N7Hsvo2Ex31pgL0xak+7odiB3vmca2iECPSTAyoawmpNfWZDf2rIwcKZhG73aua/EwpL+0esfpUy+YnyU427n9IZXtfPucol5Z6X6/MVIgOvuws637j4EufPumdEVzQSwDMNiwVooWgsFc7NsjYfZqTB7KcVdSA6oV+nGjqli1kWGmY5wk+HhO0vVFDYL+o9XSq+vWdtyMyy4Anb4MWyN0wl++0osOPlHr3+UwqzoNS+q7CtLx2lB+/6y9fCkPpfEez3k9jdy5yfIyehShsG3l//+XfXDnTbp+Ikp7nevCPOxvjt1RGCzNhcjHvfSxWEmad3iMxXrnZUy3vDVSvv0cUJnDtCWxdZx13bsfRRmeNYSuS7aCdtHrpujvhILMP7R6x+le+k9V9Hf3OQWC8d5g/Cm/3hFeSkWlfimVri9mw9sZ5h538BE0oP6RODtdePP3tOaW5L3H/XOhvnBlvo/PBu4kOi7R99/6pD28L0KxrhiXAz60tD+duTGHvbBbs1J2+4edQV8wYw/+GkMgzfsP043MYIaH7nVDjIsfiomqhRWTjGzsvmFWXZMUk9YVjgy2vsnfSUWsv2jtzul+ymiac8ryXgv0pg3pqSLP1pW9o50u4N2uKen5fNj8Kf1kna3N+hNeHLnveHow7tsVKz//Weadj/1PpjmUB2fibArJfP9LbNeX8cKwf/LT9X/8blgShqMoxmCHeB0MZsEvkDFVys38/C7HeKA5jzd4CxOhGM2DHho+8804bYtOG/sKwZT1pi8asFJ78hWpmrCYRdVs6pbGsKblh3e/rPsqoTt+BmBY56dinV4cC9O+0psja5fjHsMywbFKMtHFCvguWTc8ipkSsYPV5jNynGq5vVboU/tlQX9n6bCEnf8MkFLrI7xk9z5MaDRJTaB//TRvi//xgNo5ebrvcJPMfxLF5m/uaX/P5/YY0Mwv/HfLxm/ealNSkOn+7ZshQU2InZ29opuBTAPlZs6npEDYt5mzPV4baGCOSXwHaqT7eV7xpZSNVCx1qyybuEqSEM9WzXgyC3NZHTT9uv4c74hLLy78/DHCOkrseDjH73HVvqMkqgl44qHkvHBlK/pVsWSXmtc1fxgIAdHMOL1+e3Sxckgi9acIW1tMtkhxYQe6yUCH2wbb6/vptonp7ivHfDWX7vIv76ir9aand9ab3Xnry/r37tnLhcN2bAd+ZjEnk+w/+SqeHAg2/fv6W+smqslTNWEOqg1HuKenuK/fJY/GHKQ+JADYoVErKr02nIFszeXtM7Fkb3oZWTr7+72oY+tb97cV2JhJv/o9Y/Svbfv4E5etq7d08p7zYwHQzg7gj5HfI/6h0k+FiB37gwZhXIJgXc395Ps1y+3KRSiGv1vng1Way9Jo6/TDOs/XNf/frk+68LuGTQp4+/DHeVfPC4+Nb07ASpalf+nt7XGB+kmu162vnNHR0Hhv//FwAAG2bWjzaoGu1E0314pYp3EjNIorl3wgR3rS0R8JRam8o9e/yg96g2UNXOtKr5+4qp5/RmYWwKzRT02G+QxxGUYW5uMeBjRoGd6jMBaebcyGBaYs4eMdIuKLP5ahF27Y9z35Uw8wJ5PshjMdTdvNy9XdOZP39H+ty9yYyH7qo8z5p4vj4rM1TFus2rdy9ttyjnFbsz/4ycCLTfv90+MR9sqWR+vFb55T8ir7hrf1wr6xCx8JRa0/KPXP0o7vgSYrvEHS+jd6hjQUQAMi8HMj2fTbDrkKHzPA5E77zlSX9xwrbT7BtRd755mdAN/km1TMoUz5jnbc//tp7s9zFfH2P/uaTGMQVwM8+GO8W/f1DBuDn9/dVP/o8dEHHxjZXfeRDTm/7dPigJnOyx8k/basn3/O7kevYK4l4MNzZLbRevmVulvF9mlstCr99/Bkx0FsdH0blSBr8SCnH/0+kepk9emopiflgI/Xa195OrkAgdhMIvz9XX52XMhASvyDHwjdz5w5CPxwK3KrjdtGbKeUaw/ebNNx/Bf/FowxDE/XTNQBccG9/PfPLLry/Hz6hj/xdPm9+7Z/vsfVvR/9ogA3//kFH9lzG54v5Ri674cpejN+x9z55UBuXN8J5atmPd2qt9bsm7kORQ4XLnBmfegfu4rsbCjf/T6R6nz17NqCGMh8Y+fjttZCcbl2v+1/6cb1jdvVHNyh1c9LbEvneUF+7Wzr63dwL5HhDcLFTMVxitp/xzkRu58kLRH51molK/XPDoGkjhXtXq/iX48xJyKNjVWPzLO1d05OsjxCdxslH2y1ol+J2/+bN1cLOroNUdLe8+9qWqouUpOLB/6IlTU8N1t9S/viMVuxrs5Z9KrkPh+LVvO2hlSw2boRrUql7WSJRqWwJbUYqacaTjfvIv+Dg1iNS+JbZLLwJQltSQbVZVRZFMuVPM1Js0yG37BuHc8YtycbdzWraggVaoGp0EyjJuv5tlya5j6b68obR/7/hyNBowQX55tWEimnppU3VqfD3z71oEJHZuj8cyM8HnUwnmz+Z2zA3Es1kzsUBpovllvfh2ai/Xm9nSXESUwE91155v3q+l1oehK/+Lc7li2gmb9bKMpTcNP14MlD3yGjqLuHircczZqf771P7+tXW9eeDjI2XOn9GrTLR2ubqu0rQnqYfdkWWEqNv5HDzD/eVm4VWB7Xp447LndHtdNY6243uLOdd1QFDWn5q2gafJGRs6u5RCmtjU7wvoxiJ2OjXlDbKFVLEZf7pSyOSVXMssKK1fM8nZlJ5Jr042597kj9M7E057Qu17a2DVcwz87FYzFlDVBKxmlTDUbLYRltr0T8orSBnF93w2iZl2rXLc8ybIMzNHUccNHejxn2Y3q+1lXx4v6G4DceX/5jurdUXv++aYtrmowqECfvz8aLhHk/vDx3Wr3d+8aLe48GdhN+Ac/Cyk1fCiSqJWX/9ef7fpydJo/NMY+NsFfTnGLRfPPr9vt9b3oKbY0S5N1xTCNektbzVjwcojkvq+zLFUxVwMC//Vz0zkl+K0FvkfDYGtP69F/7Ojac9Ggt2I/5jiGI/irzTeDblOoNGth7KfuuTT7x/3NFquvBUX+6+encrJ7xdYshBy3QSwaSfFn1ibXsefXqf/a1dsitmHoA9ov1oIw7vlJl+uFIet6G7XUpyfYlQ71jIXEfN+Y9r/7gS3VMNcl27ITLlfaGP+h7ONL9JyDvjzMG4GZoIYSw8MeSu78MDJ0/CgCj0/yGKNeD/EXH+j/5hlxP+OoHa3o5vfutg4GQZ2+fgm6wOG/G8e9Y3D73vNmIhzOvre1W0LGNOy/88BuQv1wZ/fgXuBj76A5jGe4kBhKR9Lj8bSD+2jRkPEHUnC5LL68yG71cgCNg4cfGQRYeZ4fj47bM8M2bIZmyIISFWOsim9n+HggPh4bbzjftNtsQS0muVcsx/FjkTG2qbumpkXh4sHtEJ8NMBirEUqFk+PxQ/XWxd8fc6DFQuYfSAGXGpeDcccOFmE3pZ2gFRANMcyHk8H4WCSVjCWgCw7+vq4mE9d+uFqpG/wjBqgXHLQBYvIcTIfHuMmFuikuBxMeHXErAXR1f2aa/+m67dFvZU20iv/Bw2K69oEZjqC1/M/e1eud640KHh7fzYDRloUvzf7JQ/YIdmwFxdrz/Rj4JgksxrrXT+G/vzS7exVql9fv+/jawJW9IMfZQfdWgAsmg8nJ2MRUYsLhLfDcWVk/E9Pez7CvrjHuceoCJ0ylplsqC7qmo+8cGuHOOVNIhdIzyRmHShHMW2IRYVbmE8HNCA8nFwpzkbHI+HRiugu9SZcal4dxk1MtxoWutdB2wJIEoxrho0kpNRGdSCdSTvRablVaaxtzoqCPYQyThavu+ADM54jpll21kTt3lTm8FJnfe4h/b9Ool2LRqH59SzmbsJdGhYf7NGvW287RTt7QsMmciXO/PMfVvzRD5R6j21AsQJvVjxYNzAVb3/7xFdvHpzBV4v3tO58av3WZWS5aP1o28DF6/XDjbe8HHMS/qCHFQ0JMEsYi2sNp440N9icbFmasG/p2sOp28ij5Sixw+Uevf5Qe4y1AE3rVQec5BveQOz8GXrrEjQTGw9y//mzg//i5hnnXET+MEbuZtfC3F9cXzvDotv0vi03N47/zgHgrq9ZnoUEhoKVz/dfP4eM0uy4+HWHPJdh6C/yrywb+6rc9FWNXiruPw+tkD2YZxobcMB0TkxHUd7Vnp9lri8x726a836BwVJySEveF+QCyC/TPoU2vNt+1vbaKZlo4iI/xMMTG7sxHg+lRtxncOV+JBVb/6PWPUudvS63Zj9PsZvQOG2oy9ngGN21UO3eTNbwWF7jef/v5ACZtfXNdxwdme9HHJG5fvSB89aLw/9nd501JHl+4/clzgb/4QKvX0fcuwZD4f/ao+LnZ3VHxHMv+8RMiJonb61PHPV+8IKDh/V/+0K4Lw9X97R3965d3m+v37jPIHY5jJxOB8bj1O6L6lXnhr++aHzjo2v/GldBjKVXkGYy4QZMeWvawKiW+beF4nuMF/GOxnGziozJrp2psVYzNsr5dMbAP3y+jQnDYWiv7+PvCwFdiQdA/ev2j1MmLgYwFb6Jmdm5ww5pJh72LTh7UjzDkzvtB1Uf3xGJo//IJ8Z+bwlLRWihgrlasksJeSXMB3nYvv3ZOwF8LjpDA/ovHA7//sLVcxCosFu4wF7Nb6TF1TGNIDIj7k18K3MlbaJPHQPozcRY+HgG++RtSYzDs/+mvtB5pCdDXn4jVbDo4ppm/H7SWSuK1BeN27qiuAIFnA1hEDp/cNWy1ujjq5PpupZxnLcE6F2LNlN1bgVk57/+xBsObrP1nMJxm2cu4FVWjIBsC11Rsarh3L3d9JRbg/KPXP0qPfh/QLIZStYO2dnv9Q7ybcP9N2dbRd+/z2dasts+Po9uPJgHM2oa28XP2oFqnG5z6pRR/6ciBOxhrfSGJP6f3HGK4oMjNJrlk2JiPch/lhFeW9MVCe//adsgxCip2plArr9xX0ZhL1Nvda111aJKvrYyOhj4ctTArfhghOY6pLU53/+K+/usrsSDpH73+UXrYC4LyNFrInEzjjrWMay8k3r7663nYLQd3nNz54FjTk0abAHxxJMhHgkw0aDyYEt7cZH60rG9WDjj1tv7cGZqay2ewsLzdJ7HbL4E95Cadu/qcPcFpKF+JBRT/6PWP0rZp3S4isxzGr3Tc4PKVQb92HSJF7rwDIDpNBLolkAjz8RDzvKh/Zir4wxXztSW1cdqcxkp3t3d2YXhfiQV//+j1j9Lm14rFyBX0ezUfbPMLLe1lzf6YEwUgl2zkzl1iCIrGSBHAG56KCAnLfJEzvjgXuXZPe31J2e1Rd8/b3yPkvhILZv7R6x+le68C+s4xCtWBN7cHteQR0u4l6+z79+7f1x1y533FSzf3NQEMLxqPCZquff289UszEays/NNVxTVF+R6bxldiwc4/ev2jFGbF0nP4isShf87K8OkueqHJnfc4U6PbEYEWAqLAjkfZaFCbCfPPnIqOhfY7vVtCjsBPX4mFvfyj1ydK4Z/xdajDN3FHxuD2E4yFcfgYx8HInTtGRQGJwAkISCIniVZYUKuGyde+4jvBzdx+qa/Ewhj+0TvySuHOMdODwxcsU8WaPy4qnZM7d2g4CkYEekAgHOTC9rw6Lmqg64GqQ27hK7Fg4B+9I6zUsFjM2nRIim49nFOwXqGL3uWmuSxaI0u/iQARIAJEgAj4hgC6zdF37lBuUYU7d5EPdVFUHBKkYESACBABIkAE+kEA7tnJ6qj1R1cxT7ODL9T7Ec+29yR33hYLHSQCRIAIEAF/EcCAdjSeY2UEh7KxchI1tjtkRcGIABEgAkSACAyKANZHYHiscuTweQiJ1VSdhnZ40xMEo9r5CeDRpUSACBABIjAqBOzVEFjeuXtGRztcv+Wa0XDkzkclJZIOIkAEiAAROAEB+Ga4c+c3sMNT7dw5LwpJBIgAESACRGAABLBKIdYddv4g1OZpKJxzXBSSCBABIkAEiMAgCKCZXeum5Ryj2hWsU9zNJX2V0UVJpK/xoJsTASJABIgAERgiAUzAXnU6I1wtmhZT3F2FZYix3n80ufN9FrRHBIgAESAC/iXAskXV6RwyoITaPCaGcz50rt9gaZLXfhOm+xMBIkAEiIAnCHAF2RC4pnlb4a0bfjctnYrjWFTNPf6c3LknEhlFkggQASJABPpLgGOMX5w0n3o+Xl/BvOa68SEahq9buqEbpsFzvMDVvmSrOXksHSvyLO+aL8/Jnfc3fdDdiQARIAJEwBMEggITYOSDUdU0dWFnMVvJTSWmZsbmWwI01N1bzgz6J7nzQROn5xEBIkAEiIA7CRzum+td5K4Zxd4OHw2Fa0eFjhEBIkAEiAARaCHgnmFvLRGr/SR33o4KHSMCRIAIEAEicJ8Ayx5eb78fZuj/kjsfugkoAkSACBABIuBeAu6uk+9zI3e+z4L2iAARIAJEgAh4lAC5c48ajqJNBIgAESACRGCfALnzfRa0RwSIABEgAkTAowS6/lBNVbVcvrC6tvHpnXvlcsWjso+OtmmYmqYtLa9BoGVZSytrN2/fkSRJELpYO+/oR7jqbC6XX4DIjS3sQO+nd+9x3CiX827fvbe9k4HYjc2teCwCy+7s5FxlkV5FRtd1RVEWl1crlaogCAuLyx99fKtXN3fhfbZ3dpCS1ze2YF6MXbp9565hYJmMkd3u3F3IZJEfF9c3Nu8uxLHAVzKRGEm1siznC4WVlbVSuWwYBqw8lk4PTKlqaBuFtbxSrIRlOaMN4LkwKJxsNl+wuplzrmt3XqlUtrZ31je3Nje3E4nYAIQN/hGYtQ8p5t7i8tb2Ntzbm2+/g3xfhDPnR9PJlSvVre0MEtDy6pokBaHzvfc/HDz2gT1xc3vn409ulcqVYqm0trF58/bdaCQ8sKcP8kGmaWq6fm9xZSeT5Tnu1dd/cm9haZARGPCzYFP48u1MJpfPr65HVE0bT6cGHIdBPg5FcBRZqlV75pPV9c2xVDIckgYZgYE9C8kYMlEwhd8JBgP/8MZby8urA3u6YRklsyBbSpgNx/j4AJ6bzxcXlldQqxwf66LU0rU71w0DHl1R1ZAkVeU2E+gMQGq/H4FCLtw5ir2KguVyrGw2H5ZC8OajWmeFHXeyuZ1sNpPJQrgsK5FwqN+Qh3j/WvFlR1XVQq1acycaCYjiEOPTv0cj9cKj5/JFKEVt9d3rH95bHGV3Dv9dKpWR78uKApsWiqVRdW/1NIPiy8bGFlwd2mDW1jdCIQm1jv4lpyHe2S6YajrK30jJ8Xgsk81KwcDA4mMyZpUtq4xWtuQyowzgucVSGa0u+DbOSHaxJEzXtkdyicVikUh47tRMMjGIcsoA2LU8AkkHXg0bmmGxmO3kxPj83KwootY6mo3tyAEhDf/FC4NCDFLSqHYr1A2t6wYKaqZl2kp5Hq3QXPOiCy3pwcM/7QmnLZi1Uq1iIYlFdKmsb3hYTqeoo10N/Qv2q2uaHMuhFXpUW9TqJKAVJRdUP2Bfgc/gLR7VlIzp01EyhVlh3alQaHpq8szpuU7JoWfndcsoGnnZkCN8NC4MwuvBl9s9ZaqK3Mm5jC6C1m8qimIwGJycGLtw7kxX7QDO4zT0kPUmSmSCKLWgeoOCy6WL54KBwKi6cyQd+G/0wSEvQL5Qy/qHbgSKQO8J5PKD6PbrfbyPe8dyZTQH9xzkgdr5wYOjdwQ5MFrao9Hw6blTD1y6MDCBmqnvVLfLajkpJcZC4wN4LkZ/oPkQeTIcrvPHde3OQTMRj509PffQlcuzM1POn+ShkFg5B74cxd5YLIoi4bmz84889EAohPb2rnF5QvX2tl2u39zaQUHNExGmSBIBIuBDAugwQvtDIh6/dOHs449eHRgBVVdX86v5amEiOj6bnB3AczEOTq5WkS1j7Lnzx3Xtn/CAcCiUSMQnJsampiacP8lDIbEUHsYgpFMJ1MhRU08nk1OTk+iXEsSucXlCNSrlG1tbGA422m3snrAFRZIIEIHDCKAvGR4d2XI6nRyk91E0VRGqXJkbS6Snxgbh9TAeAk4WI1i7+jRjNIdqH5Ya6DgRIAJEgAgQgZEkQO58JM1KoogAESACRMBfBMid+8vepJYIEAEiQARGkgC585E0K4kiAkSACBABfxEgd+4ve5NaIkAEiAAR6JYAy9B6590yo/BEgAgQASJABIhA9wSodt49M7qCCBABIkAEfEPAtFiOmxT4wU0rezy05M6Px42uIgJEgAgQAV8QyFeZ5RwTDk67XC25c5cbiKJHBIgAESACQyOAFUpXc8pf3hELSpjjXD2TGLnzoaUSejARIAJEgAi4mYDFMCsZ5doSX9SYV5ZZy3L1ervkzt2clihuRIAIEAEiMDQCsmqu5PVb9lKlzI08t4BJVy33Ok33xmxoBqQHEwEiQASIgO8JYFXW1azyrQVeNW0W+O93lritEmrsLv1ojdy579MsASACRIAIEIEDBIqyfrfALJX3TyyV2Y/XiqpB7nyfCe0RASJABIgAEXAvAVTNN/Lay4tNnhvD4r55T9go4t+m4y6RQbVzlxiCokEEiAARIAJuIZAtae9n2K1qa3zyKvP2SkXW3eg63RinVn70mwgQASJABIjAoAiYprVVNl5da/+8V1a5lazqwgo6ufP2BqOjRIAIEAEi4E8C20XtjY02VfM6jYzCvLasVjTebXDInbvNIhQfIkAEiAARGBoB07JyMvOTDYxgP3R7Y5Nd2qm6rYJO7vxQg9EJIkAEiAAR8BuB9ax6bZEpqEfpLmnMtQW9pLlrkjhy50fZjM4RASJABIiAfwgomllQ+fe2a1+aHyn7gyx7Z7NkMi7yoS6KypHo6CQRIAJEgAgQgT4SwMdp2yXjr++astH5KVWd+fZdK1d1kQ91UVQ686MQRIAIEAEiQAT6Q6CiGksl7oOdzlXz+vNv5plP1ou65ZYxceTO+5Mu6K5EgAgQASLgKQK5inVtwUHF/L4ow2K+tcBmKkcNmrsfdhD/kjsfBGV6BhEgAkSACLiZQL5ifJTjbuecVs3rWpZLzDsrVdV0xZg4cuduTmAUNyJABIgAEeg7AfSaF1X2lSX9GBXt7y9bmwXdDeuykDvve0KhBxABIkAEiICbCeQq+pubzGKhu6p5XdFqhfnxiiIbw6+gkzt3cxqjuBEBIkAEiEB/CWDemJIu/mgZNexjbq+vWauYembY67KQOz+m/egyIkAEiAARGAECmZLxwxVzs3Kcqnld/rbMvLKgy2ZguDTInQ+XPz2dCBABIkAEhkZA062KJb22dOQkcA5i99aWtbRdsoY6qwy5cweGoiBEgAgQASIwigTysnXtnlbWjjEGrgkHpn19+a5RUof5DTq58yaT0A8iQASIABHwCQFZM9eq4utLSk/0vrvN3NqqGNbQvOrQHtwTfHQTIkAEiAARIALHI4DK9A+WdPOkNfPdh+Mrt+8uGHmZPV5kTn4VufOTM6Q7EAEiQASIgMcIVBTz0xL/09XeVM3r4q9nmOvrss4M56O14TzVY2an6BIBIkAEiMBoEagawlhI/OOn43bl3MJEMviv/T/dsL55o5qTOwx0T0vsS2d5wa6K29fWbmDfI8KbhYqZCrMsbjbYjdz5YHnT04gAESACRMAFBKIBI8SXZ4P7Uam7X1W31ucD376F78iP2p6ZET5/LiTw5kGvzbEWy3QoDRx16+OeI3d+XHJ0HREgAkSACHiWQBA161rlukWBZRm6A19smAzPWQKjD3vymP3oU9/5PgvaIwJEgAgQAZ8TwJfoOaVzO3lRs0z3ePKazcid+zzpknwiQASIABHYJ4AB6gWlc/W8rFtGF4up7t+/f3vkzvvHlu5MBIgAESACHiNgmCxcdcdIV3UG6527aiN37ipzUGSIABEgAkRgmATQhF514M4V1M7JnQ/TUPRsIkAEiAARIAKHEKh9r8ZpDlrR0R5vdm6SP+Qx/TlMtfP+cKW7EgEiQASIgNcIoL7N8bzmYKI41WCwsqqr9JE7d5U5KDJEgAgQASIwNAKYDYbjBScfqimGBafvKn9O7nxo6YYeTASIABEgAq4igPo2x/FOpnHXzPpQuKHN0H6QG7nzg0zoCBEgAkSACPiRAGrbFsthipiOG1y+4qCLveN9ehiA3HkPYdKtiAARIAJEwNMEWNlkDQed4mhpL2u16dpdI5fcuWtMQREhAkSACBCBoRJA33lJra/H0iEecOd5hHTTxHDkzjvYjE4TASJABIiATwiYFrtTdfo9eVaGT6e+c58kDZJJBIgAESAC3iEA/7xVcdolviPbg9vds1Ht3D22oJgQASJABIjAMAnAPW+WdYcxyFRN1OYdBh5AMHLnA4BMjyACRIAIEAEPEDAsdttx7TynmAjvHlXkzt1jC4oJESACRIAIDJMAus3Rd+4wBkUV7txFPtRFUXFIkIIRASJABIgAEegHAbhnJ6uj1h+NlVqczB/Xj3i2vSe587ZY6CARIAJEgAj4iwCGtaHxXHawnFqdC1ZqocZ2fyURUksEiAARIAIeIGAxBsMbjkerIyRWU3XP2HaqnXsgjVEUiQARIAJEoN8EsEKayfLO3TM62uH6LdeMhiN33u8UQvcnAkSACBABDxCAb4Y7dx5ROzzVzp3zopBEgAgQASJABAZAwMQiaUwXVVzU5mko3ADsQo8gAkSACBABItAFATSza920nGPdNcWkxvYuCFNQIkAEiAARIAJ9J4AJ2KtOZ4SrReb/b+/MYyu77vt+l7cv3MmZ4ZCzrxppJFlSZNlW7MiJm9RO7SzNgrYp2gZogaJp+0fRogWK/JO2aNMgQYEAXYOmQePEcePYUdx4qXfLm2zJo9Hsw30n377frd/7HjVDcki++zh85L3nfJ/p0VvOvfd8P7/fPd9zzt0cpeinp7B0MLHQdZbcAAmQAAmQAAkcFgFVLTa83kMGdcRoHjeG837qXLdlhbq9Aa6fBEiABEiABIJAQCvUrJC26b6tcOsNnzc9CB3f46Fq/vFz2nkQcox1JAESIAES6DIBTbHePWI//0qPO+7G4Nv9Fxei4fR1x7RM27Y1TQtpzSvZmiavqWpYV3XfXHlOO+9ygnD1JEACJEACQSAQDSkRpfZoTRtGYzYzk63kjvQeOTYwtqXAhrH7ll8O+iPt/KCJc3skQAIkQAL+JLCrN7uj9V0LHLImngp3yAHg5kmABEiABEjg8QnQzh+fIddAAiRAAiQgNIHm0XSfK6Sd+zxArB4JkAAJkIAPCKh+nmh3+dDOfZAlrAIJkAAJkAAJPB4B2vnj8ePSJEACJEACohPA/Vz9/6Kd+z9GrCEJkAAJkMBhElAx0+77w+e088NMEW6bBEiABEiABPaFAO18XzByJSRAAiRAAmIScIfmQXh1fBuZarU2v7Bk4cGwijI8NBgEjR3XETfzM03z2vWbmWzOcRy8wSqi0Yiud/Bk+463engL5HL5iamZyZm5SqV6eLXglkmABEhgNwJojS3LWstkfvDmdcPo6Nlnu6227W+mba5UVsuNUl98/n58pm35xy+wsrp24+ad1Uw2Eg57X1vHdp7N5admZmu1Wk86DYfzvqUAlUTS4JUvFGfnFvDmf3/iU72fS+sabtAbjD5ap6gbhlEuV/L5wspaptNlWZ4ESIAEDoYAhpH1euP2nfu/9wd/1NuTPpiNYiuO6tgx0wnZWkPX6h2b5h7qCZmFYjGVSl46f8774h3XDPaGwatl2bglvWaKOVfvarRswzDQEyyWyrl8Ad94ZxrQkiFdR//s2JGRoaGBRCIeUBVeqo0ZprVMFvGNx2LxeBxiw+GOdwQvGzr0Mkhb7K3FYml+YRGd0bHjx9Lp1KHXqnsVwIitUqnUanW0hohpf39fLBbt3uYOfc2YTsMwDlOJ6VQKaRyLxUIhMWcQ8dgyyCyVysura3ZzjG6YBzc6d3AanGk5qq1Zinogm4VYuA9Ud2Q8HbdifX29z/b1Dg0OXLpwdnCg/9ATuhsVAEg0B2/fvP3pv/jczdt3QVUGO4eX4+jJ5UsX3v/ed588cbwbYH2yzpnZhde+83ounx89dvTE8VGI7e3t8Und9rcaSF30Wt6+eQeZrOvaz3/0w5cvnd/fTfhqbZhhmpyexdFANPp9vb0vvOvq6LEjvqrh/lZmcmr2y19/rVgqYQx36sTYsaMjGM/t7yZ8srZGwyiVyxiXf+lr34xFoz/7137q0oUOhq2PqcK0rUxtrWyUe6O9A7GBx1ybl8VX1zK37tzDSBJ9NC/lW2U6tvN4LDrQ33fuzKkfee5ZUXcV9IwqtSom17/6zW/jiXhoE70DDW7JUCiUTCbHRo899+xTV564GFwhbWt+89bduYVFjNvOnj558cLZJy9dHB4R8ywQy7QwUkUOo9HHuO3qU0+8593Pt+UT3AIry2uYfojHY5FoZGRo8IXnnj539nRw5bSt+eDAzTv3JnAA9PzZ008+cfHM6ZP9/b1tlwpiAcy45LJ5zCC+ce16IpF45uqVF59/14EJaVjGXHYuV8mN9Iwc7xs9gO2igcJuOzUzh6lE75vr2M4xZYd2PxwJx2IR7DbetxSgkpiysx07EongeHmAqv2YVUVkMYCLRsKpZLI3fXDHpR6z2ntYHDOTkIlzTODoyUQi3ZMSVS9m7CKRMKZh0Q7iL5VMiKq0lQZo9BFQDGiikQj+TafSYuvFror4hkMhN5OTiR5xMzkajmDyGcfGcD4ymmU0zgfpPrqJA5HRqBUB54PZbjOFI9hnMar03sTtxc5xShg2o7uu3vHi3mt2iCUxtR5yW7/WuW8d0DzEOu/LppuOrmNXiQp9xBENoNsmuA4XioRDOMogql4dHVPbRnOvaio6++FwWFSlrfyHi0MjWibsvfg/Pomt1x1yuJmsQTGUQ76oenEUGWIRW6Rxc0ipH6T72KrjGkLz72C220xhV2tHT2SVaPS5L4bHlZAACZAACZCADwnQzn0YFFaJBEiABEiABDojQDvvjBdLkwAJkAAJkIAPCdDOfRgUVokESIAESIAEOiNAO++MF0uTAAmQAAmQgA8J0M59GBRWiQRIgARIwC8EbEfRteGQ7vc7DNLO/ZIxrAcJkAAJkIAPCeSrymxOiUf8fodB2rkPk4dVIgESIAES8AUBDM3ns/Xfvx8u1BOa6utbrdDOfZExrAQJkAAJkIDfCOAJKHOZ+p/P6EVD+fysait9fqvhxvrQzjfS4HsSIAESIAESWCdQa9hzefNOwb036M28NpWxLMe/punfmjGhSIAESIAESOCwCODppJhm/+SU3mg+hAv/fmZGWylhxO7TO3/Tzg8rVbhdEiABEiAB/xIo1syJgjJTfljDmbJ6Y6HYsGjnD5nwHQmQAAmQAAn4lwCG5kt548+mNzk3Tov7+GRoqYj/bvreJzI4OvdJIFgNEiABEiABvxDIlowfZtSV6tb65BvK9+YqNdOP1unHOm3lx88kQAIkQAIkcFAE8DzWlbL15YXtt/f5eW0u2/DhAJ12vn3A+C0JkAAJkICcBFaLxjeXthmat2hk6spXZxsVQ/cbHNq53yLC+pAACZAACRwaAdtxcjXltSWcwb7j65vL6sxa1W8DdNr5jgHjDyRAAiRAArIRWMw2Xp1WCo3ddJcM5dUps2T46yZxtPPdYsbfSIAESIAE5CFQN+xCQ39ztXml+a6y38qq95dLtuIjD/VRVXZFxx9JgARIgARIoIsEcHHaasn6kwm7ZrXfStVUPjXh5Ko+8lAfVaU9P5YgASEI1E1nraJW6u1HAELIdUXII1kepa3kFElvpWHNlLS31rzumLfzyq3Foun45Zw42rkwDSaFBIYA7vucNWPXcpHVslpt3UAyMHXfY0XlkSyP0lYqiKQ3V3FenfIwMH9nJ7Ac5ZNTaqay20lz75Q9iP/Szg+CMrdBAlsIrFSt3/5u6X/dsu/mw6sl2zD90iJsqec+fpRHsjxKW+khht58xXo7p93NeR2at7TPlpTvz6FP7otz4nxRiX1sMrgqEggEAbg3/r49X//uQv3l8eiHT4UTSm0grWuqH28euS9I5ZEsj9JWYgigF0fNiw318zN76VZ/btZ5csQc68OeCxKH+aKdHyZ9blteAmg/mi/c/fkr0/XvLTR+dCzyypiW0o2+ZEhMT5dHsjxKW0kcfL25ivntZW260NnQvKV+vqJ8Y67+0XQqphutbw7rX9r5YZHnduUl0BrNbNRfNpzPTtRfX9LePxZ6ccROR5zehF/Or9lYzz2/l0eyPEpbySCAXtw3pmSGvzJb33N6f23BeeFo7cwg/BQ8Du1FOz809NxwIAjUTOyguuKg2+6ozT9NUzVVcWfF3f/t9bXdXr9csT9xu/HtRe0nxkNP9Jl9cTUR1Q9+pC6PZHmUttJUNr0ed85Myfp/cwr2Po/lHy22WlM+P2X+7f5ETNt7n+DR1Xb6De28U2IsLxEBeG7Zjn1rWeuJ6emIHg8pYRVXpdiaY+FPVywdH1VbVxW8aXo8bN5pGTCc3nX8puk/asnOzr14zPj9j+uNc33ah0/q4yljKKVHwwd3yqo8kuVR2tpjZdPrsZ3CWagVJ/bVjU8197jk5mLfXXFeWS2dG4mqyt67BZtX2fEn2nnHyLiARAQcxbSdP/xhFv9uUQ23xnlrsZDaE9UG4/pQQh9JhoYTOt6nImpMc1THtm3LtkzbsjC4h83D8kOaEg6phqWYuMZl5xd+u5OzfztnPzmo/fxpuydiHO2PHNBZcvJIlkdpK9Nk07vz/rXxl3zNeXXSwNGujV/u4T1u+/pnE9bf70O/n3a+B35chAQOgMAOuzm+hseXGviz54vmg4q0BuWYItc1JaSprn9ralhX4iEVp7jB+/ui7pdfnnnkQcoPVrHhDe5ogStnnh7SPnzC6IspQ+kwpvo3/N6dt/JIlkdpK1Nk09tu/6gZ9kI1/LXHHpq3tvPGqnJnpfL0KI6QHY6jc3TeLuD8nQQ6IYAGE+f54uQaw92jd2g+O1kh7jf57SX7RlZ56Yj6niP14aTenwo/OnvfySr3uaw8kuVR2koR4fWWGvoXZh6detvjDoKr3D47ZZ0aUAfie1zDYy5GO39MgFxccALvXINzyDLxfKe/nHG+v6p84Jh1dcA80hNOxzEF0JWRujyS5VHaSl/Z9O6+0+Iuy/dKke/Me5on231VD369llGuLdbeexqn2TycsXvwa7ff0M67TZjrDzqBfRhh7xeClaryifvKlxfUj54wTvcYo/3RGA6p79faH65HHsnyKG1FVza9D3P60XdVKzQYD//aCz0uFKfZ1XHPUHVwXsvHb1ZztTYT5gMx9aOn9JC7+7nLNlfgrimp24WK3Z9AX/ugadPOH40yvyGBhwSwpx70Tvlw49u/g6n/t1vqeFL5uZPV472h4wPR/bV0eSTLo7SVSbLp3X7/eefbVMSK6+XR6Duf3zk21jCdxfHIp+7UHv6w3bv3HAu9H6Nw3X60gXAvbzmM89tp59sFit+RwAYCXRj+blj7Xt/i9J3fvamf77E/PF462hNKRk1V3drxMA2zVqtXzaqjO45u402xVmqzQffAv3u/Sh++tpe8oa6legka607DUI26Uy81SvlqYRchtjOwYeldCh70T5uU9m4fXNSpbFRM1bQ0C2IrZqVYL4VqOzfpbmT7/a/3iJvMxpZkRhpDXdWq2rpt6xaE7x7ZxwmYYammnW67BsvGtS2OO6nuG6Y7x76tGhYgARI4VAJ4GNv1nDpdDv3KGeN4n2NZSxurgyPrpmHV6/VCo6BELVwvn6tml/KLG8s8+t5x1GiifVv26IIH880Wyaa1Sc5qIZet5cpmqa7UKlZltbSWyiV2qVg82bvLr4f70yalvY6xObituq2V12pKzdAbJaO0Vs6k8gl83KXa8WTPLr8e7k+764WdF4rFQr1gh00zpGcr2cXcpmzfz8o7yVw91XaFRQP3lvKNkzerSztvGzUWIAGfEohoyqVe+yfGnP64UTfWLLuxpaKmadVNzB2ajubgz3BMfNxS5tGPEczJ+vW1QXKjBsnWpptwofdiwfgc01Zwsb/VsIBlU4EtsqLuzf58+nqgtC8GpauPBhf1NuyGo5qOCrGGaRuQ3zB3sXM1FhC9Vei1Nt3/vGFAmpvJCjJZtQ27TWQfI6hOONRTqLdPjLKJDrSi+MlC/VSXx4gAFyWBLhF4cIZLl9a/t9XiYPl40vnpcfvUQEhX87ZjxsJJnIWzZW2Wadb0eiKUUEz3NjbJcLI30belzNaPOFfAPWHed47+QPLJAV1XmpJDWyVbVSURTsb0WFiJxLRobyzdn9pNr6PidnsBUBoPbz9Y7ImshZ1oyKrFtUQ6ku6L9/XuOt/gf72aknsnmTclZl2vq7aWDCdUS9NtPR1N7R7ZTQt3+MG0k7DqtgtVTWXXe0G1XcH+F6Cd7z9TrlEsAr4bq/ZGlF86ZV4+lh5Oqc0bVozsBBzHzqvVWn90UqvpWgh3rBsc6x/dqXDre6hdKOvtG7Pd17Lfvz4iObbtFsJGZCm2tqrn4k4hpaWPpI+MD4xtWxJfBlppS9RqKhdz4mGrlg71DCWHjvUdGxjoD7jeo9vWv1qpxdVkX2RWr+O2ipGhxNAukd12Dd6/nM/jLBOMu9u86hid+2w/oZ23iRl/lpyAr3bYgajy46P2C8cTR9JaBKfUdmdkKY9keZS29mLZ9O6h7Wp23jXDnUZv88J8vN1+Sr7NSvb3Z9r5/vLk2oQj4I8mMBVW3jPivDwWGeuPxEJ2dy+DkUeyPEpb+6VsejtvjUBI03WclNB20Ybl3vyxbbGDLEA7P0ja3FYACXR+7iqO8uIPN2zHg9Bw++aIrkTxJqTiTlG4bXs6rGqa8tqCmal5aguw1JP9zodPhsYHY4kwjLz9uOFxKcsjWR6lrZyQTW/newLOldH0EM6lbPvCWZd4MBP24c6htl33HgvQzvcIjotJQgCXe7V2V/df+DQ676r7vHP3oajvPFslHcGDVbSBuDYYU/tjam9ETYbVqO6WaVp7s7zWXETHGpxSvTYS1X/vZpvbQGLxC73Kx06rZ0bSqbB5EEbeDGo3JFu2OhKt+E2yPEpbe6tsevfQRmG8rWm6l9u446EMzWPnaBg89cv3UJlOF6Gdd0qM5WUioCoRXf3YpXR/zDXsdETFOBvPQ4Mluz6trD/ztPnIc3zjfok7O2ImvOn96zt5qzewkZqqmCFV3/jNo+/HUsrPnnQuHU33xfBw1U0X7TxaeD+/6ZJkLdS8HeZuNT1oyfIobVGXTe9uubbjb9hpcf4/bhHT9gXLr3d/pqxtNTYWoJ1vpMH3JLCJAJy4N2J85CSeSgqHhk+7bo3/u2/c+zju+eU2GjstPJpQPjSmvut4fCChhtQ2I/idVrLn77smGTXyl2R5lLaSQTa9e90F1JqtWh4OimOmvWy410d050FIe6k+7Xwv1LiMPATCmhPuwuHqbZ1tKKa8fFR971hkpCcc0Q7ayB/EVB7J8ihtBVc2vQ9S2vsbHDsvNZo3m2i3DOw8j5Ju337bvbnd8l34nXbeBahcJQm0I7ClwcCJ688PKx86ER7tj8V0GPmheXm7iu/9d3kky6O0lQ0i6bUdda3q9XrybA2eDjv3y4t27pdIsB6SEVjv0eOI8jNDykdP6+NDqZiGy2MO8DD5QROXR7I8Sls5JI5e+PNKxesh8bUaTm5vHns76F1p++3Rzrfnwm9JoIsE1ls/5akB5adO6ueHE6kITlzf7e7iXazMwa5aHsnyKG1lkBh6YefLZa9zY5mqbePRRr550c59EwpWRBoCcPP+iPIPruiXh0NDSV0/yBPXDw9yS/LVo7iVOq7ZE3gSYj24MihtZZNIkbUcddXz6DxXt1H+8HaprVumnW8lws8k0H0CFm633meuxPVeXfXv00j3kQOu4jszFO9JaO7zoYV+yaO0FUbB9OKwOY6de8zQYgN2jltR+OVFO/dLJFgPeQg4tpErzSp4WmXav8/b3t9waIrVn8AVPYJ7OaDJo7SVIYLphT17eTpqS3sVT2z1cIX6/u5Ku6zNRz2LXWrJn0hALAI4F9hPzcCBwHUv2ZfjJY/SVjyF0YsExeR5zcPTUVvCDcst75+kpp37JxasCQmQAAmQwOERcHCLCd3C6XDeXihpK6rX0t7W+TilaOePQ4/LkgAJkAAJCEIAT0izVd27PeNAO6zf8c0AnXYuSCJSBgmQAAmQwOMQgDfDzr2vwS3P0bl3XixJAiRAAiRAAgdAwMZD0nAuo+cXRvM8Fc4zLRYkARIgARIggQMhgGl2o5OZc5zOWrc52X4gseFGSIAESIAESMAjAdyAvdrRpZSOUlx/CovHLXS3WAcTC92tCNdOAiRAAiRAAodIQFWLDa/3kEE1MZrHjeG8nzrXbWW8jUy3CXP9JEACJEACgSCgFWpWSNt0KTncesPnTQ9Cx/d4qJp//Jx2HogkYyVJgARIgAS6SwB3uHv3iP38Kz2tOx41rRsXoj28/1Hzw/rXMHlNVcO6qvvmynPaeXfzg2snARIgARIIBIFoSIkotU6rumHs3umi+1yedr7PQLk6EiABEiCBgBLwjzfvASBPhdsDNC5CAiRAAiRAAv4iQDv3VzxYGxIgARIgARLYAwHa+R6gcRESIAESIAES8BcB2rm/4sHakAAJkAAJkMAeCNDO9wCNi5DAPhDwz90n9kEMV0ECJHDYBGjnhx0Bbp8ESIAESIAEHpsA7fyxEXIFJEACJEACJHDYBDq+7tyyrEq1ms8XVlbWwuGOFz9svZ62bxhmtVLN5gqNhoHH5XhaJviFcK9CCC+VK8srq/MLi8EXtKMCCCyWyghxsVTK5PIry2s7Fu3OD7lqPpPNYd1pdbUa6/i2Fd4rZZpWrVrN5guGYTi2g40uLa94XzxwJZdX1rK5fBHRdYNbXl1b61vuCZwK7xVey2QqaI6rNbdBXsuk06lave598QCVrFVraJCz2Vy9Xtc0LZMRPJNhr4hppVqD4XoPU8d+XK83VteyABqLx1ZWV71vKUAl0QhC5uTUTKlcxhNtA1Tzx6kq8gYNw+LyyvUbt8qVyuOsyufLTs/MzS8uYW9JJOKRcBi1HVjsPcg6l4zyasXdd4oL5Xg43r1NW5Zdb7iZXC5XdV27PzGVTHRxc90T4nHN6Jzdn5yaW1iEtyGfb92+Vy6LnMl3709BaT6fn5qZQ5ucy+fTqZRHVsEq1mg0SqXyvftThWKpYRh3709GIu6eK+prZTUzOT2Lvmk0GvWusWM7B0r0B9EHRPYsLYlp57ZtQSYafbQFuqZFIxE0hS5TNdC3DNoxKxwItm1d19HRn5tfeP0H19A67Fg6+D+sZbLTM7OYegmH3PxHrA+4Eaw5tYJZwKYzejGiRbpH1LZtw3QzGR017LATkzOqKvLxNUy3zC9gAmIV7SAM4M69CYzVu4f30NeMjssa7LxQuHt/IpfLT0z1xmIdtP6HXn/vFTBNs1ZvLDR74YaRuD857aMnn3iX4bkkBhszcwvI4cGBfs8LKZ3becPI5nLZfB4Ts8lkwvuWAlTStTfLwjgV9oY+4NDgAIZxavMVIBXeq+ruKrU6puzK1SpGcplMNhrtosd4r1iXStYbBnr6rUNFhmmiexo/2DGrqRk1rQp1y1ZGdzreB71jaXXUFheXkMmaqk3NztUNw/vigSuJXgsOKKApxLxarV67NxFbzbgHNUR9wcsz2Swk4w9903A4vD7wEE4wzBt9U8y0F8sVvJ+ansWYUjiVDwVhJLm8shIKhXrS6YfftnvXcVMS0vVEPB6JREaGBnCopt36A/m74ziwczT0sWgUO8mVJy6NHj0SCmGgLubIBo0gDqDMLSxgLgvtQi7vDhyFfw3096Gv1tvbM4RMTiUPUm9DaZScEraYVtJhtYtzhmj4LMvtq+GYArJ3oK/36MjQQSo94G2hEcTOi3YfjX8ymURHfHCg74DrcJCbg1RMxmJkhUkInB5xkJs+lG0hh9ELx2BjYKBf7Ex2jyk0GjjUi0lT76g7tvNUKjEyPDh2/NjVJy8fHRnxvqUAlcTMM/aNH7z5FmYp0TL8+Afe98zVK7B29JUCpMJ7VdHBv3d/8ns/uLa25vb0vS8Y6JKpVPLCubPPP3v1qScujQwfqMkV6sXFgnuy4fHe0WSkiz0J08JZIPXv/eDNO/fuoz/6yvvf+/yzTwc6artXfjWTuXn73tT0DKbcBwcHfuzll06fPLH7IoH+9a0bt3C6AHZbnOsjh52rGF+Njh794Afe++xTTwY6drtXfnF5+c1rN5aWlzs6d6tjf8K4HMOa8bHRixfOwdR3r1NAf7VMC/sGhqlo8WHnZ06duHrlcjweCwl6Jv/KyirGNLNzC2LPsW/JxmgkjONSJ8aPX7x4dvTY0S2/dvVjppyNr7qHM86MnO6JdzCZ1mmtTFyjUa3hWDKOFqEdPHVy/MqVi52uJEDll5ZWMBXRfDUwejt/7szFC2cDVP9Oq1qt1fp7ezBg1TQxT+vZAkRVVAzQe1IptMliZ3JvXw9GVobRKJY6OJdTzNnjLUnAjyRAAiRAAiQgNgHaudjxpToSIAESIAEpCNDOpQgzRfqNAK6T8FuVWB8SIIFAE6CdBzp8rDwJkAAJkAAJuARo58wDEiABEiABEgg8Adp54ENIAcEigCtPMpWo2HdnC1ZEWFsSEIMA7VyMOFJFYAisFI3fv4HrbQYCU2NWlARIIAgEaOdBiBLrKBCBT921bhfUry+K/KQvgcJFKSQQGAK088CEihUVgMB8tvHtZVfH91b1eOy4AIoogQRIwCcEaOc+CQSrIT6Bhun88R27bLpKS4by5xMJ2+EOKH7cqZAEDoYAW5OD4cytkIByd838VnNo3mLx/TV1oSzyk+sYchIggYMkQDs/SNrclrwEqg37MxPORv2Wo3zyttWweD+ZjVT4ngRIYI8EaOd7BMfFSKAjAm8u22+s2lsWuZ5V3liytnzJjyRAAiSwBwK08z1A4yIk0BmBct3+v1P2prF5cwX45s/vNWomB+id8WRpEiCBRwnQzh9lwm9IYJ8JfGfRuZndOjRvbeN2Xvn6jLHP2+PqSIAE5CNAO5cv5lR8sARKNfvT93ebUX91wqzb+sFWilsjARIQjQDtXLSIUo+vCNi28rUFbbGy/dC8VdXFivLq7Rpu/soXCZAACeyZAO18z+i4IAm0J7Badf7oVn13q4aPvzplZWs8gt6eJ0uQAAnsRIB2vhMZfk8Cj0vAspW3MqF0RBtKaENxLfzI3hbSlMGYOhhTYrryrdmG7dDRH5c5lycBaQmEpFVO4STQbQKq4rw4Yrw4omP87djOpyfDn7lX37jRv3Ii/EtXYk0Pd6faVXW3Q+wbF+R7EiABEthCgHa+BQg/ksC+EdA0NRldH3CbllN/xKyrlqOrpqbwsPm+MeeKSEBaAo9M/0lLgsJJoJsEcNV5obF1A7m64nCCfSsVfiYBEtgLAdr5XqhxGRLolICjqPn61vPbc3XMwXe6JpYnARIggW0I0M63gcKvSGDfCcDOYd5bVptvOLuf9L6lPD+SAAmQwE4EaOc7keH3JLCfBGDnhUcOnhcbjrnV4vdzo1wXCZCAPARo5/LEmkoPk0DDVquPWLfhnh/Hi9MOMy7cNgkIQ4B2LkwoKcTXBCqm8uhhcozMq6avq83KkQAJBIUA7TwokWI9g02gYmw/q77T98FWy9qTAAkcOAHa+YEj5walJFAytp9Ux6idLxIgARJ4fAK088dnyDWQQHsC5Z1G57Tz9vBYggRIoD0B2nl7RixBAo9PoLyDbVf4rPPHh+RewMEAAB9ESURBVMs1kAAJKArtnFlAAgdBoLyDbe9k8wdRJ26DBEhAIAK0c4GCSSk+JrCTnZceufOrj0WwaiRAAv4lwEew+Dc2rJkwBHDrt6sj4eFEunkPuPV/Wv8ZS4ccpbH9aXLC6KcQEiCB7hOgnXefMbcgPQFVVZ7qrz/Vvy0IDs+3xcIvSYAEOiPAyfbOeLE0CZAACZAACfiQAO3ch0FhlUiABEiABEigMwK08854sTQJkAAJkAAJ+JAA7dyHQWGVSIAESIAESKAzAjwVrjNeLC0zgZWq/a15e7niLFWcsKYcTaqne9WXjum6xjPTZc4LaicBXxCgnfsiDKyEzwngSaZ/fMv67KRp2ltr+olb1t+4HPqRY/rGH+5m8fg095krR5NaOrKfZp+pOms1txIRTT3Zy9m1jdT5ngSkJkA7lzr8FO+RwB/cMP9y0tq2MEbqv/1945+/oDw98tDRf/21Rsv4/8lz4XdvdvptV+L9y6/OWh+/5d4w9nha/Y/vj3pfkCVJgATEJkA7Fzu+VLcPBG6u2Q+8fDylvuuodqlfy9ScOznnKzMWxuAYif/O943/9EEtGd7Pgfg+VJ2rIAESkIYA7VyaUFPoXglcW12fYcfB8t94ORLR1z37gyeVi/3qf/6hO1bGc05vZ+xnjzwcoLfdWt10Irqi4hYzHl4oHA15KulhZSxCAiQgIAHauYBBpaT9JTBbXLfzsbT6wMtbm3jf8dBn7ptGcxp+oew8qyh/ctuYKzrWO4fYX71vfnveeuVk6Kmh9ePcn5s0vzlvz5fsQkMJac5QXHvhiP4Tp/SRxLpbY8T/hWl3jRf61V+6GP78lPmdRXumaP/6eyL/57Y5W3IPyeOVqTi/83ojGVZ+9Wqk9Q3/JQESkJkA7Vzm6FO7JwJD7xjtWyv2G8vWMxuOkYd15bc+ENu4luurzo3MO2auKHeyzh3FeWLIeWpIsWznP3zPeGP54a+mrS6WHXQIvjZn/qt3R8bTruVn6s6drFsmGdb+67XGV2fd93FdKdad1xYeLlu1FHzsiyq/unHzfE8CJCArAdq5rJGnbs8EzvXBZd3hcs1S/t13jJG48dSwdnlQuzygDca3nlt+pk8N69q1FRxPd18n0mpfTB1sOj5s/oGXp8LKlUFtuepM5t1HseTqyp/eMX/tXZvG2TD1jc9hw4H5q8MaLpNDDwBrjmrKxUEN6+GLBEiABECAds40IIE2BF48pj13RHt9aX1kvFxVvjht4w+LjSSU547o7xvTz75zzdjfesI12L/5F7XWme0/eyH04Mz2b86tnxuPtf3T58Kh5tXqv/vG+vj7fm59Fv1BbVpe/qNj2oUBvS+i4LK0f/li5FN3zNaZ7UNJFR8fFOYbEiAByQnQziVPAMpvT0BT1X/0bPgPb5pfmrYaD2e73QWXK8pnJyz8/fgJ/Vevthkpw/gvDbrnyp3vV1tebtoO1tB65etb7Rzf//Il/aPn2qx2fXn+hwRIQG4CtHO540/13gjEQurfeTL8CxdDb61Yb67YNzPOfHPG+8HSOHntSFL96bO77VDPHXW9/H7efn3Rni6amDPHTPuW/sGDFbbevOd4B6fKb1mWH0mABKQisFvrIxUIiiWBtgRw9PrF0dCLo27BYsN5a9X+6qz5g+X1UfVn71u72zkuNvvN7xkPLntrbQ6HwOubR/wPqhHTlaEYL057wINvSIAEdiNAO9+NDn8jARD4zsL6dWfHU2rr5HN8iVu3vjSq4+83vtVoOTTOSC/UnZ7ojgb8W6+vezkOmj8xqD49rF/o16aL9n+/5l65/uj15+g9eLwqnWEiARIgAdo5c4AE2hD4+C1jvuSWeWJA+9fv2Xr2Gc5rezDgDukYqW9v5yXDwSx9a0sfPRf6xYvru971tR3G5m0qxZ9JgARIYBOBrZfZbPqRH0iABBTlwVnrb2fs7y+tn53eApOv21+ZXf9mNKUkQlt3KDy7pVVyqvDQtt83ul7McRxc0tYq4F6v1snL3FSRTpZkWRIgAREJcHQuYlSpaV8J/OTp0GsL649U+fffNS4PWONpXFyu4OEruJ17yVjf2E+eerg34d7t7gS6ouAmMLZj4VT2/g2T8J+5Z/3cBWW26KAr8OCeM+sXqq+vbMf/YLutFy5Axxn1/THlwYVwOy7DH0iABCQg8LABkkAsJZLAXgic7dP+7pOh/9K8NzuWhwHfyGxdz/uO6x/aYOdPDmvfXXSH3ZiHx9/feyr0wRM6Ho4+kXfH4F+etfDXWgUejIabwuI9TnH3cmP2JwffGdkryv+8bvRGaectkPyXBGQnsHVuUHYe1E8C2xF45UTo374cxmHyR388mlD/8bvC//CZTT3jj50L4QbvGwvj4vVfe1cYjv7gS9zQ7Rcvhf7FC+uXlcPSP32/NaR/UGSbN7iZzF89reNm79v8xq9IgAQkJrCpDZKYA6WTQBsCp3v1f/aCjoPlS2Vnpeo+Qu1IQhlOqCNxVW/e323j8hjQ/+b7o2XDPdcdxtvfvN7sWFL7N++L3M+7d2kdTakne1R4PJb6+Ec23fX9Z86F8LdxbVve/8qV8C9fChcaTtVUoiH6+hY8/EgCkhLYrdWQFAllk8DOBHqjGua3L+xcYOMvuNIMfxu/wYVnZ/vwt/G7vbzHEfTBeGvNm9a/l3VxGRIgASEIbDN5KIQuiiABEiABEiABiQjQziUKNqWSAAmQAAmISoB2LmpkqYsESIAESEAiArRziYJNqSRAAiRAAqISoJ2LGlnqIgESIAESkIgA7VyiYFMqCZAACZCAqARo56JGlrpIgARIgAQkIkA7lyjYlEoCJEACJCAqAdq5qJGlLhIgARIgAYkI0M4lCjalkgAJkAAJiEqAdi5qZKmLBEiABEhAIgK0c4mCTakkQAIkQAKiEqCdixpZ6iIBEiABEpCIAO1comBTKgmQAAmQgKgEOn5AaqPRWMvmZmbn+/t6c7mCkFxs2zYMY3JqtlQq2449OT070N8Xi0b1UMe4AsEnk81OTs0sr67V641AVHhfKlmvG2uZ7PTMXE86lcnk92WdfluJZVm1em1qZq5SqYZCOqI8ODDgt0ruY33WMhnsrQuLy6uZrKIqd+7eNwxzH9fvt1Xdm5jM5gtorGxbisfeO4qDxrlQKt2fmO5J9/gtHPtYn6XlZZgsrFbpJLAd+1OxVJmdX0QDgd2mJ5XaRwH+WRUs3LLsmbmFxaVlx3G++o1vTUxOh9AcamJOZpQrlZXVzNTsbKFY9E8Uul2TYql06869Wq1+f2IqLWgmW7ZtmubU7NzqakbTtS9+5Rt37012G+whrr9UqSyhW4reWaE4N5+oVmuD/f2HWJ9ub3p+aXlicqpUrpiWyL2WBxjRazFMc35+8Qtf/vqt2/cefC/em0KxhG4pOi9Hjwx7V9exndu2VavVMEbPZvONhuF9SwEqCQu3bAve1hTogCx6Sa6bq2LaOQIKb8M4JhKJDA3296TT0WgkQPHqtKqYhEBww6EwBq+lchnjm7qgmex2TE2rWCzB1DVbLRSK7rBV3Fe1WkVk0T1FSquqms0VnE4GN4EDg4BiaI69NZVMhMNh7L+6LmYb5bbJmGqq1dEaNwzDzeRYLHDx8l7hcrlSLBZDuo6BpfelOrbzaCQyPDSE+cmzp09gvt37lgJUsjmmse4lJ6emZ5BG586cwh/2Fhh6gFR4rypmXJaWV5LJBBaByicvXxwZGvS+eOBKYvx2/cbtWr0+dnx0fPTY+Nix3p504FR4qbBpuYeNEvH4/YlJTdMvnDtz4dxpLwsGtEy+UJqdm19cXsFhlJ6e9JVL5zsa3ARO9TTmYzMZuPjxY0dHRoYH+/sScTFNDoNyzLVgYvjNa9fRUl04f+bc6ZOBi5f3Cmey+UQiVqnWOhpZdWznSJ1UKnnsyMiF82eRP97rF6CSNhpB00RnMJVM2o5zcnzs8sXzsWhED+kBUuG9qvl8MZmMozy6hJh2fv7Zq6dOjntfPHAlp6Zni6VyLl84fuzIqZNj58+eHhjoC5wKLxVGDmMqAq94PK7rOsJ65YmLXhYMaJlMJofhKcbliqIODvSdQ5M/fjygWrxUG63xzdv3cE7PubOnz54+OXb8GAZaXhYMXBlkMSaZ0AufnJ6Jx2NnTp0QO5PRIzVMA8fIOjKdju0cg9S+3p5jR4+cOXXy+OiRwKWFlwpjfgPzOWga0A3EmRfHR4+eP3c6FouGRT0VrjkBWy5XMUbHjAuahssXz3kBFdAyOA3irbdvofKYhEALePb0qZERMTummGOv1upLK6toAUN6aPz4sYvnzwY0al6qvby8hgFNFVPt9cbw4MDpE+PYc70sGNAy6Kv19/VgBnH06Ajs/MzpkwP9Ys6YIo1xeBeOjsMK6JuOj42KncmpJM7PzZqGiX6M9+Ts2M7R+cU53ul0sr+/d2BAzNNMcLgRU5Q9PSn0XWDn6PAO9PW5DWK4Y1zeI3G4JXvXMulUIhaLJROJgf7+4eGhw61PV7eORj+BSclYLJFIILj9A8JmMpoDTFHilFX0YNAZxfyzqPtsK2Fw/gcCihyOx6L4p69P2Mi29Pb19iKNo9FqKpVCR3x4aEDU+FYrNUwvpXvSmJCIhMM4Oiaq0lZk0SvFLDhia5iW98ZQzIPB3vWzJAmQAAmQAAkIQIB2LkAQKYEESIAESEB2ArRz2TOA+kmABEiABAQgQDsXIIiUQAIkQAIkIDsB2rnsGUD9JEACJEACAhCgnQsQREogARIgARKQnQDtXPYMoH4SIAESIAEBCNDOBQgiJZAACZAACchOgHYuewZQPwmQAAmQgAAEaOcCBJESSIAESIAEZCdAO5c9A6ifBEiABEhAAAK0cwGCSAkkQAIkQAKyE6Cdy54B1E8CJEACJCAAAdq5AEGkBBIgARIgAdkJ0M5lzwDqJwESIAESEIAA7VyAIFICCZAACZCA7ARo57JnAPWTAAmQAAkIQIB2LkAQKYEESIAESEB2ArRz2TOA+kmABEiABAQgQDsXIIiUQAIkQAIkIDsB2rnsGUD9JEACJEACAhCgnQsQREogARIgARKQnQDtXPYMoH4SIAESIAEBCNDOBQgiJZAACZAACchOgHYuewZQPwmQAAmQgAAEaOcCBJESSIAESIAEZCdAO5c9A6ifBEiABEhAAAK0cwGCSAkkQAIkQAKyE6Cdy54B1E8CJEACJCAAAdq5AEGkBBIgARIgAdkJ0M5lzwDqJwESIAESEIAA7VyAIFICCZAACZCA7ARo57JnAPWTAAmQAAkIQIB2LkAQKYEESIAESEB2ArRz2TOA+kmABEiABAQgQDsXIIiUQAIkQAIkIDsB2rnsGUD9JEACJEACAhCgnQsQREogARIgARKQnQDtXPYMoH4SIAESIAEBCNDOBQgiJZAACZAACchOgHYuewZQPwmQAAmQgAAEaOcCBJESSIAESIAEZCdAO5c9A6ifBEiABEhAAAK0cwGCSAkkQAIkQAKyE6Cdy54B1E8CJEACJCAAAdq5AEGkBBIgARIgAdkJ0M5lzwDqJwESIAESEIAA7VyAIFICCZAACZCA7ARo57JnAPWTAAmQAAkIQIB2LkAQKYEESIAESEB2ArRz2TOA+kmABEiABAQgQDsXIIiUQAIkQAIkIDsB2rnsGUD9JEACJEACAhCgnQsQREogARIgARKQnQDtXPYMoH4SIAESIAEBCNDOBQgiJZAACZAACchOgHYuewZQPwmQAAmQgAAEaOcCBJESSIAESIAEZCdAO5c9A6ifBEiABEhAAAK0cwGCSAkkQAIkQAKyE6Cdy54B1E8CJEACJCAAAdq5AEGkBBIgARIgAdkJ0M5lzwDqJwESIAESEIAA7VyAIFICCZAACZCA7ARo57JnAPWTAAmQAAkIQIB2LkAQKYEESIAESEB2ArRz2TOA+kmABEiABAQgQDsXIIiUQAIkQAIkIDsB2rnsGUD9JEACJEACAhCgnQsQREogARIgARKQnQDtXPYMoH4SIAESIAEBCIQ61eA4ju3YpmWZeBlmp4sHorxlWYZhQiPE4oU3+BQSVCwi4mp1/2cjsvjHDa24YqEXAbVdrXhBtciZ7Kaxm8jrmYw3gke2KRYy3dBatpvXYmeyabpZ7Oay4Jns5nGzmVpvkyWIbLOZchTH8W6ae7FzUG3UG7VqvVqted9SgEqiOWiYRr3eaLWDjUajVnOVwtMDpMJ7VWu1eq3eMJpdGOwztbqwkW0xQTRbNgfFiHK1UhM1kxHNah0SDdfebNsVK+g+24pstVqtN5DJbsuPfxBosfViV4VSt71qoL2qV2vC7rnVOmJZRxvlqpUgk12xDTeP7a7aOZr+hcVlbEZV1YmpAe+eEaCSSBcIfPvm7Vw+j87g2zfvoPKRSCSk6wFS4b2qhWJpbn5xamZ2cWm5Uql8/823Mtmc98UDV3JyenZmdiGby4UjYfgcWvz+vt7AqfBSYTT1aOhv3LpTLJY0Tb92/aaXpYJbJpPLTUzOzM4tLK+sopP2+hvX8Ca4ctrW/N7E1MLiUqFYxBsUXl3L9qRTbZcKYgH00oql0s3b93L5QqVau3b9BproIArxWOfVtUxTbD4WjXpcBMVUMz/tsfTt2/f+7NXPfef1N7C7AG5fb0+0ky153IpPiqGVh5dPT89hpuPE+Ghfb6+maejB+KR6+1sN9HnLlWq5XEajHw6HjxwZTiWT+7sJX62tVC4vLa1g0iWRSKRSyXQqib6ar2q4X5VBZxSZnM3lJ6dmkL1nTp8UtePSIoaYotGvlNFDq0WjkeGhoUQivl8wfbgeiJ1fWML+iwYqnU4in8MhMWcQkcaQCS+HXjTFJ0+MwYB8GJH9qhLmWiA2mUxcPHf2heee+dArL585c6rtyjuPPRwNDUPzBaxtNxDEAmgEWwIVVVGddbkC2zmkuV0Vt7Pi/qup7hdBDJzHOkOgK9bV2ny5csXU6x5ofLi/umJFVdoKPeRB4sPIiq7XzWTE90ETJbRepC4SGIHGP3greCY3WyZE1mOb1irWsZ2jTzTY3z8yPHj54vnhITEn25s9QfP6jVuf/PRfoD382Ed+8srli+jsCzvZXijNzi9gAHfn/mRPOv1jL7906uRYR2kUrMJT07Nf+tq3MNk+fnwUSjFmHRB0sh3HGXHg/Idv3fjEn35G1/Vf+JmPXH3ycrCC1VFtM9n8/Ympmbn5peXVgf6+l37kufGxYx2tIViF796f+twXv4LJdjRQZ0+fHDt+TOTJ9mLp7Rt3PvuFL0Ujkb/+Mx+5cvlCsILVUW1XVjM3bt7BwSOI9b5gx3Yej8YGB/vPnT31wnNPj42KuavgXAvM2gHiF7/yDdj5E5cuvPTicxAeDneMy3skDrHkWjY3cPc+mvtiuYy+2rNPPyn2rtLf14d2MBIJnz41juDC4Y4MDx0i/+5tGieFuWdLGWY6ncI07FNXLr3vpR/p3uYOfc1LK6uxWBT7KZL56Mjwc888deH8mUOvVfcqkE6l3rp+Ewc94eVPP/XE+bOn0Ynp3uYOcc04fAJvw9U3r3339Xg8jn0WfbVDrE+3N43zPzCqxBCrUq1631bH/oQ5AF3TQqEQDjfiOKv3LQWopKbZqC0aBcznwM5dsaEw5OJNgFR4r6obSGhDG6ihGdTwCS/viweuJNRBJl5QjJa/KVdMvdhb0Sggsq2DKYix6JENIZORxK2XwJFt7XQQqLmZrEI0hOPUTlHji3kmiHMzuflyxQrdRkWiTbHNHdd7A9u5PzUP1LSg6iExz/QGPtt2swatIewcYtebB0H1ut4GJ2/qbR04FziyCG5LafPglBtltxcjaGSRva5CnBnwjlpRlbaavGYWNwW7R5FVN6sFjWxLL6Q2A4t/XNXufiyo3mYLBX1NvYoiQWRdsVDrnhrh+SXmGUCe5bMgCZAACZAACYhAgHYuQhSpgQRIgARIQHICtHPJE4DySYAESIAERCBAOxchitRAAiRAAiQgOQHaueQJQPkkQAIkQAIiEKCdixBFaiABEiABEpCcAO1c8gSgfBIgARIgAREI0M5FiCI1kAAJkAAJSE6Adi55AlA+CZAACZCACARo5yJEkRpIgARIgAQkJ0A7lzwBKJ8ESIAESEAEArRzEaJIDSRAAiRAApIToJ1LngCUTwIkQAIkIAIB2rkIUaQGEiABEiAByQnQziVPAMonARIgARIQgQDtXIQoUgMJkAAJkIDkBGjnkicA5ZMACZAACYhAgHYuQhSpgQRIgARIQHICtHPJE4DySYAESIAERCBAOxchitRAAiRAAiQgOQHaueQJQPkkQAIkQAIiEKCdixBFaiABEiABEpCcAO1c8gSgfBIgARIgAREI0M5FiCI1kAAJkAAJSE6Adi55AlA+CZAACZCACARo5yJEkRpIgARIgAQkJ0A7lzwBKJ8ESIAESEAEArRzEaJIDSRAAiRAApIToJ1LngCUTwIkQAIkIAIB2rkIUaQGEiABEiAByQnQziVPAMonARIgARIQgQDtXIQoUgMJkAAJkIDkBGjnkicA5ZMACZAACYhAgHYuQhSpgQRIgARIQHICtHPJE4DySYAESIAERCBAOxchitRAAiRAAiQgOQHaueQJQPkkQAIkQAIiEKCdixBFaiABEiABEpCcAO1c8gSgfBIgARIgAREI0M5FiCI1kAAJkAAJSE6Adi55AlA+CZAACZCACARo5yJEkRpIgARIgAQkJ0A7lzwBKJ8ESIAESEAEArRzEaJIDSRAAiRAApIToJ1LngCUTwIkQAIkIAIB2rkIUaQGEiABEiAByQnQziVPAMonARIgARIQgQDtXIQoUgMJkAAJkIDkBGjnkicA5ZMACZAACYhAgHYuQhSpgQRIgARIQHICtHPJE4DySYAESIAERCBAOxchitRAAiRAAiQgOQHaueQJQPkkQAIkQAIiEKCdixBFaiABEiABEpCcAO1c8gSgfBIgARIgAREI0M5FiCI1kAAJkAAJSE6Adi55AlA+CZAACZCACARo5yJEkRpIgARIgAQkJ0A7lzwBKJ8ESIAESEAEArRzEaJIDSRAAiRAApIToJ1LngCUTwIkQAIkIAIB2rkIUaQGEiABEiAByQnQziVPAMonARIgARIQgQDtXIQoUgMJkAAJkIDkBGjnkicA5ZMACZAACYhAgHYuQhSpgQRIgARIQHICtHPJE4DySYAESIAERCBAOxchitRAAiRAAiQgOQHaueQJQPkkQAIkQAIiEKCdixBFaiABEiABEpCcAO1c8gSgfBIgARIgAREIhDoSoaqKaVqlcmUtk11YWOpo2QAVtm270WisrGZqtZrjOKtrmbn5xVg8Ggp1hisokrPZ/PLKWjaXL5crkUh4aXm5r68nKJXfQz0Xl5eLxRLE5guFlbXM/PySYZh7WI//F7FMs1ZrYG9FPtuWvbK6Nju34P9q77mGKytrCGguX0B447HY4tJyMpnY89r8v+DS8koJzXGlmstjF15NJZOVas3/1d5DDWvVGsKayWRr9ToWR3sldibDXpHIiK1lddA0dexP9Xp9qVo1DANMB2dm9xAY/y9i2bZpmrdu30MCwc5v3r6LfyPRSEjX/V/5PdSwWCwvLC5Nz84vrayUq9UfvnUD1r6H9QRlkZnZ+dn5xVyhEA6H0HVDS9HbK2b3xbQso2HcvH0PIdZ17e2bd4ISo73VM5crTE7PzC8swdSrtdqb195GD2ZvqwrEUpNTM4vLK8VSaWJyxrEdGEA6nQxEzTutZL3RQMflzt2JfL5QjUSu37iFJrrTlQSo/Opa9s7d+4VSOZVMYBTt8dWBnUdj0SMjw9jMEsat2dzk1OzqasbjZoJVDOYNR0cHMBKJKI4DuRiXh0K6pop5bAIdXnRcMKJpTUvMzC2gvx+skHVUW2QvRquILGQiylCdiMc7WkNQCtuOg1YP00vxeEzTtKWlFV0TM4dbEalUqxCLMQ1UV6s19NswDROUYO2hnhBrWRYiC5kLS8vowcSi0T2sx/+LoGNaq9Wx50YxrAqFFhdXFMf/td57DZHDmGXCAHJwoH94aDAai3lZl2rmp72UQ5l8rjAxNXPj9p03f/g20igaxeSzmKNVJAocvVp3p3fwvq+3JxaLqs2XR1bBKmZZNqZb4HDoAmuank4l3H6MuC8oLZUqaCBwZCESDqOB0AWdd0Eau5lcq+dyeeRvf18vfF3cwCqWaSGHGzh2YppoChMJZHJYYL31egNDc+y/aKCikBoOYw5GSL2Ye7Bs19ELpRKGVa02WUilLVE4qI2J8KNHhl947plLF84dP3YklU611dvB6BwNwfj4KNZoGiaO2eCNI3T/qC07FiABEiABEiCBfSeACXb0v48eGTl/9szo0SOxfR+d41Sa1hQWDjrWa+75CHyRAAmQAAmQAAl0g0AsHuvvdWfUMH2oau0PoXcw2d6N6nKdJEACJEACJEACj09AzAMtj8+FayABEiABEiCBABGgnQcoWKwqCZAACZAACWxPgHa+PRd+SwIkQAIkQAIBIkA7D1CwWFUSIAESIAES2J4A7Xx7LvyWBEiABEiABAJEgHYeoGCxqiRAAiRAAiSwPQHa+fZc+C0JkAAJkAAJBIgA7TxAwWJVSYAESIAESGB7ArTz7bnwWxIgARIgARIIEAHaeYCCxaqSAAmQAAmQwPYEaOfbc+G3JEACJEACJBAgAv8f6uLF6vGjPFoAAAAASUVORK5CYII=",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 120,
     "metadata": {
      "image/png": {
       "width": 250
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='depth-first-path-u-l-r-d.png', width=250) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Greedy best-first search \n",
    "\n",
    "In this sections, we perform a greedy best-first search from s to g using manhattan distance as the evaluation function.\n",
    "\n",
    "We'll import distance from scipy so we may use the `cityblock` function rather than handrolling our own (admittedly trivial) manhattan distance calculator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.spatial import distance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And, for laughs, let's set `MOVES` to a more standard arrangement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "MOVES = [UP, RIGHT, DOWN, LEFT] \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below are 2 reusable fns\n",
    "- `unzip_points` enable us to extract the row and col data from a list of points.\n",
    "- `get_sorted_moves_by_heuristic` is our greedy heuristic fn, which returns a list of moves sorted by the manhattan distance from a given point to the GOAL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "def unzip_points(points):\n",
    "  a = []\n",
    "  b = []\n",
    "  for point in points:\n",
    "    a.append(point.row)\n",
    "    b.append(point.col)\n",
    "  return [a,b]\n",
    "\n",
    "def get_sorted_moves_by_heuristic(orig):\n",
    "  h_scores = []\n",
    "\n",
    "  for m in MOVES:\n",
    "    move = Point(orig.row + m[0], orig.col + m[1])\n",
    "    point_vectors = unzip_points([move, GOAL])\n",
    "    h_score = distance.cityblock(point_vectors[0], point_vectors[1])\n",
    "    h_scores.append(h_score)\n",
    "  \n",
    "  scored_moves = list(zip(h_scores, MOVES))\n",
    "  scored_moves_sorted = list(sorted(scored_moves, key = lambda x: x[0]))\n",
    "  _, sorted_moves = zip(*scored_moves_sorted)\n",
    "\n",
    "  return sorted_moves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 total moves\n",
      "29 moves in path\n",
      "\n",
      "visited\n",
      "[   Point(5, 3),\n",
      "    Point(4, 3),\n",
      "    Point(4, 4),\n",
      "    Point(4, 5),\n",
      "    Point(5, 5),\n",
      "    Point(6, 5),\n",
      "    Point(6, 6),\n",
      "    Point(6, 7),\n",
      "    Point(7, 7),\n",
      "    Point(7, 6),\n",
      "    Point(7, 5),\n",
      "    Point(7, 4),\n",
      "    Point(6, 4),\n",
      "    Point(5, 4),\n",
      "    Point(6, 3),\n",
      "    Point(7, 3),\n",
      "    Point(7, 2),\n",
      "    Point(6, 2),\n",
      "    Point(6, 1),\n",
      "    Point(5, 1),\n",
      "    Point(5, 0),\n",
      "    Point(4, 0),\n",
      "    Point(3, 0),\n",
      "    Point(2, 0),\n",
      "    Point(1, 0),\n",
      "    Point(0, 0),\n",
      "    Point(0, 1),\n",
      "    Point(1, 1),\n",
      "    Point(1, 2),\n",
      "    Point(2, 2)]\n",
      "\n",
      "path\n",
      "[   Point(5, 3),\n",
      "    Point(4, 3),\n",
      "    Point(4, 4),\n",
      "    Point(4, 5),\n",
      "    Point(5, 5),\n",
      "    Point(6, 5),\n",
      "    Point(6, 6),\n",
      "    Point(6, 7),\n",
      "    Point(7, 7),\n",
      "    Point(7, 6),\n",
      "    Point(7, 5),\n",
      "    Point(7, 4),\n",
      "    Point(6, 4),\n",
      "    Point(6, 3),\n",
      "    Point(7, 3),\n",
      "    Point(7, 2),\n",
      "    Point(6, 2),\n",
      "    Point(6, 1),\n",
      "    Point(5, 1),\n",
      "    Point(5, 0),\n",
      "    Point(4, 0),\n",
      "    Point(3, 0),\n",
      "    Point(2, 0),\n",
      "    Point(1, 0),\n",
      "    Point(0, 0),\n",
      "    Point(0, 1),\n",
      "    Point(1, 1),\n",
      "    Point(1, 2),\n",
      "    Point(2, 2)]\n"
     ]
    }
   ],
   "source": [
    "visited = []\n",
    "path = []\n",
    "\n",
    "def do_the_thing(orig):\n",
    "  # add the incoming Point to the visited nodes (path) list\n",
    "  visited.append(orig)\n",
    "  path.append(orig)\n",
    "  # get heuristic scores\n",
    "  sorted_moves = get_sorted_moves_by_heuristic(orig)\n",
    "  for m in sorted_moves:\n",
    "    move = Point(orig.row + m[0], orig.col + m[1])\n",
    "    # confirm move is valid\n",
    "    if (move.row < 0 or move.col < 0): continue\n",
    "    if (move.row >= MAX_ROWS or move.col >= MAX_COLS): continue\n",
    "    # get location value and check that the current location is not forbidden\n",
    "    # or in our list of previously visited nodes\n",
    "    if BOARD[move.row][move.col] == 'f' or move in visited:\n",
    "      continue\n",
    "    # if the current move is the goal, then add it to the path and exit\n",
    "    if move == GOAL:\n",
    "      visited.append(move)\n",
    "      path.append(move)\n",
    "      return True\n",
    "    # if `do_the_thing` has found a valid path, exit\n",
    "    if do_the_thing(move): return True\n",
    "\n",
    "  # if we haven't returned yet, then the current path has exhausted all valid\n",
    "  # moves, but did not reach the goal, remove the point from the path and \n",
    "  # return false\n",
    "  path.pop()\n",
    "  return False\n",
    "\n",
    "# kickoff the recursive search\n",
    "do_the_thing(START)\n",
    "\n",
    "# Print the results\n",
    "print(f'{len(visited)} total moves')\n",
    "print(f'{len(path)} moves in path\\n')\n",
    "print('visited')\n",
    "pp.pprint(visited)\n",
    "print('\\npath')\n",
    "pp.pprint(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interestingly, the first path found using a greedy search also contains 29 moves. Below is an updated image of the board detailing the steps taken to reach the goal. \n",
    "\n",
    "*Note: the above algorithm included a visit to `Point(5, 4)`, which is not part of our final path.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 125,
     "metadata": {
      "image/png": {
       "width": 250
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('greedy-manhattan-path-u-r-d-l.png', width=250) "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "e7e5d1bb7fa01062e060b31ae7befa618a51e6950cccea635f55e1ba98ae294d"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}