{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "thanks to -> https://stackoverflow.com/questions/49558464/shrink-polygon-using-corner-coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:28:36.727289Z",
     "start_time": "2024-10-23T09:28:36.365530Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "(np.float64(-0.8500000000000001),\n np.float64(6.85),\n np.float64(-1.3744678440936948),\n np.float64(11.065450849718747))"
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1500x1000 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.style.use(\"ggplot\")\n",
    "\n",
    "\n",
    "def shrink_polygon(coords, shrink_value_x, shrink_value_y):\n",
    "    \"\"\" \"\"\"\n",
    "\n",
    "    def det(a, b):\n",
    "        return a[0] * b[1] - a[1] * b[0]\n",
    "\n",
    "    def line_intersection(line1, line2):\n",
    "        xdiff = (line1[0][0] - line1[1][0], line2[0][0] - line2[1][0])\n",
    "        ydiff = (line1[0][1] - line1[1][1], line2[0][1] - line2[1][1])  # Typo was here\n",
    "\n",
    "        div = det(xdiff, ydiff)\n",
    "        if div == 0:\n",
    "            raise Exception(\"lines do not intersect\")\n",
    "\n",
    "        d = (det(*line1), det(*line2))\n",
    "        x = det(d, xdiff) / div\n",
    "        y = det(d, ydiff) / div\n",
    "        return x, y\n",
    "\n",
    "    # how much the coordinates are moved as an absolute value\n",
    "    # shrink_value_x = 2\n",
    "    # shrink_value_y = 2\n",
    "\n",
    "    # coords must be clockwise\n",
    "    # coords = [(0, 0), (0, 100), (20, 100), (30, 60), (40, 100), (60, 100), (60, 0), (40, 10), (40, 40), (20, 40), (20, 10)]\n",
    "\n",
    "    lines = [[coords[i - 1], coords[i]] for i in range(len(coords))]\n",
    "\n",
    "    new_lines = []\n",
    "    for i in lines:\n",
    "        dx = i[1][0] - i[0][0]\n",
    "        dy = i[1][1] - i[0][1]\n",
    "\n",
    "        # this is to take into account slopes\n",
    "        factor = 1 / (dx * dx + dy * dy) ** 0.5\n",
    "        new_dx = dy * shrink_value_x * factor\n",
    "        new_dy = dx * shrink_value_y * factor\n",
    "\n",
    "        new_lines.append(\n",
    "            [(i[0][0] + new_dx, i[0][1] - new_dy), (i[1][0] + new_dx, i[1][1] - new_dy)]\n",
    "        )\n",
    "\n",
    "    # find position of intersection of all the lines\n",
    "    new_coords = []\n",
    "    for i in range(len(new_lines)):\n",
    "        new_coords.append((line_intersection(new_lines[i - 1], new_lines[i])))\n",
    "\n",
    "    return new_coords\n",
    "\n",
    "\n",
    "# must be clockwise!\n",
    "coords = [\n",
    "    (0, 0),\n",
    "    (0, 10),\n",
    "    (2, 10),\n",
    "    (3, 8),\n",
    "    (4, 10),\n",
    "    (6, 10),\n",
    "    (6, 0),\n",
    "    (4, 1),\n",
    "    (4, 4),\n",
    "    (2, 4),\n",
    "    (2, 1),\n",
    "]\n",
    "\n",
    "# how much the coordinates are moved as an absolute value\n",
    "SHIFT = 0.5  # [m]\n",
    "\n",
    "up = shrink_polygon(coords, -SHIFT, -SHIFT)\n",
    "lo = shrink_polygon(coords, SHIFT, SHIFT)\n",
    "\n",
    "\"\"\"\n",
    "the last point is out of order for my needs\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "def rotate(l, n):\n",
    "    return l[n:] + l[:n]\n",
    "\n",
    "\n",
    "up = rotate(up, 1)\n",
    "lo = rotate(lo, 1)\n",
    "\n",
    "a = np.array(up)\n",
    "b = np.array(coords)\n",
    "c = np.array(lo)\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "plt.plot(a[:, 0], a[:, 1], \"b-\")\n",
    "plt.plot(b[:, 0], b[:, 1], \"r-\")\n",
    "plt.plot(c[:, 0], c[:, 1], \"g-\")\n",
    "plt.axis(\"equal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "now these edges can be used to compute the path as before! Plus outer and inner track"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:28:51.991289Z",
     "start_time": "2024-10-23T09:28:51.987250Z"
    }
   },
   "outputs": [],
   "source": [
    "from scipy.interpolate import interp1d\n",
    "from scipy.signal import savgol_filter\n",
    "\n",
    "\n",
    "def compute_path_from_wp(start_xp, start_yp, step=0.1, smooth_factor=7):\n",
    "    \"\"\"\n",
    "    Computes a reference path given a set of waypoints\n",
    "    \"\"\"\n",
    "\n",
    "    final_xp = []\n",
    "    final_yp = []\n",
    "    delta = step  # [m]\n",
    "\n",
    "    for idx in range(len(start_xp) - 1):\n",
    "        section_len = np.sum(\n",
    "            np.sqrt(\n",
    "                np.power(np.diff(start_xp[idx : idx + 2]), 2)\n",
    "                + np.power(np.diff(start_yp[idx : idx + 2]), 2)\n",
    "            )\n",
    "        )\n",
    "\n",
    "        interp_range = np.linspace(0, 1, np.floor(section_len / delta).astype(int))\n",
    "\n",
    "        fx = interp1d(np.linspace(0, 1, 2), start_xp[idx : idx + 2], kind=1)\n",
    "        fy = interp1d(np.linspace(0, 1, 2), start_yp[idx : idx + 2], kind=1)\n",
    "\n",
    "        # watch out to duplicate points!\n",
    "        final_xp = np.append(final_xp, fx(interp_range)[1:])\n",
    "        final_yp = np.append(final_yp, fy(interp_range)[1:])\n",
    "\n",
    "    \"\"\"this smoothens up corners\"\"\"\n",
    "    window_size = smooth_factor  # Smoothening filter window\n",
    "    final_xp = savgol_filter(final_xp, window_size, 1)\n",
    "    final_yp = savgol_filter(final_yp, window_size, 1)\n",
    "\n",
    "    dx = np.append(0, np.diff(final_xp))\n",
    "    dy = np.append(0, np.diff(final_yp))\n",
    "    theta = np.arctan2(dy, dx)\n",
    "\n",
    "    return np.vstack((final_xp, final_yp, theta))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:28:52.737070Z",
     "start_time": "2024-10-23T09:28:52.653026Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 0, 'x')"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1500x1000 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "track = compute_path_from_wp(b[:, 0], b[:, 1])\n",
    "track_lower = compute_path_from_wp(c[:, 0], c[:, 1])\n",
    "track_upper = compute_path_from_wp(a[:, 0], a[:, 1])\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "\n",
    "plt.plot(track[0, :], track[1, :], \"b+\")\n",
    "plt.plot(track_lower[0, :], track_lower[1, :], \"g-\")\n",
    "plt.plot(track_upper[0, :], track_upper[1, :], \"r-\")\n",
    "plt.axis(\"equal\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.xlabel(\"x\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:28:54.589399Z",
     "start_time": "2024-10-23T09:28:54.532313Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "[<matplotlib.lines.Line2D at 0x1369457f0>]"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjMAAAGdCAYAAADnrPLBAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAACDcklEQVR4nO29eZxjZZ3v/zknSyWpVFVSe7qW7q6mm3VYFAWEexkX1PG2Mj0ioI7IIPycoS9XvZdR+THowMhgOzPijDLjAoq0V4YWaWWQGRnhJyOIqKC00NBtd1V1LZ3ak6pKJalKcs7vj5PnZN9OzvIk9X2/Xv3qquTkPM9zTirPJ99VkGVZBkEQBEEQRIMiWj0BgiAIgiCIeiAxQxAEQRBEQ0NihiAIgiCIhobEDEEQBEEQDQ2JGYIgCIIgGhoSMwRBEARBNDQkZgiCIAiCaGhIzBAEQRAE0dCQmCEIgiAIoqEhMUMQBEEQRENjt3oCZhIKhZBMJnU/b09PD+bn53U/Ly/Q+hqfZl8jra/xafY10vq0Ybfb4ff7Kx+n+8gck0wmkUgkdD2nIAjquZuxzRWtr/Fp9jXS+hqfZl8jrc94yM1EEARBEERDQ2KGIAiCIIiGhsQMQRAEQRANDYkZgiAIgiAaGhIzBEEQBEE0NCRmCIIgCIJoaEjMEARBEATR0JCYIQiCIAiioSExQxAEQRBEQ0NihiAIgiCIhobEDEEQBEEQDQ2JGYIgCIIgGppN1WiSIAiCMJbXll7DgaMHkJSTVb9GgIDW1lasra1BRnWNCs/sOhNX7bpK6zSLEosJ+OpXWxEK1f49f2QkiQ9/OIp0z0VDsR0/jtYHHwQ2NiC3tCD6oQ8hNTxs/MAcQ2KGIAiC0I2//sVf42fTPzNlrEsHLkV/a79u5/vBD9z4+79v1/z6iy7awKmnVi/itNJ+111w//u/q7+Ly8tY/sIXDB+XZ0jMEARBELoxujwKALh619Xo8fRU9RoBArxeLyKRSFWWma8d+ho2pA1Ek9G65prP6KgNAPC6123g4ovXq37dt7/dipUVEZGICWYZAPZjxwAAiVNOgePYMQiRiCnj8gyJGYIgCEIXklISM2szAICbz78ZgdZAVa8TBAGBQADBYBCyXFnMfPvwt7GxsVHVsbUwMaFsie95Tww33LBW9et++EM3VlZE6Dyd4kgS7JOTAID1Sy9VxIwpA/MNBQATBEEQZXn5ZTtefNFR8biZtRmk5BQcogN9nj5dxrZNTsJ/ww1w/OpX6mMCFAtItfE11TI1pVhmhoZSNb2OxcmYoSnEuTkI8Thkmw2pwUHzBuYcEjMEQRCcceDoAfzH+H9YPQ0AgCQB73hHL9797h6EQuXdKFORKQDAgHcAoqDP9tLx6U/D/fjj6PnjP1YfEwyKsp2YYGKmtrgXM4J+GfaJCQBAamAAsqOywNwskJuJIAiCI+aj8/jE058AAJz4yAk4bNZuWMmsfX1szA6/P1Hy2Gwxoxe2uTndzlWOtTUBS0uKmBkcrM0yk8F4VWM7cQIAcrOXyDJDlhmCIAieyE5pXoovWTgThex9cnGx/JYxtaqImUHvoG7jS11dJZ/TM2ZmclIRMh0dEjo6tJ3XDE3BLDPJrVvN9W9xDokZgiAIjsh2z8zH5i2cSSFLS+W3jOnINAB9xUyqs7PgMSNiZpiYqdXFBJirKcgyUxwSMwRBEByRbW2Yj1ovZrL3yYUFW9ljVTdTm35uphzLTEpx/7CYGX0tM0rURa3Bv8p8kJ6PbtMpiY1ZZoaHzQ3W4RwSMwRBEByRbW3gwTKTK2bMt8xIWZYZMRwGYIxlZnpaEWoDA1rEjDIPU8TMyZMAgNSWLeRmyoLEDEEQBKcsxBasngKyg1orxczMRZVg3X6PflV5YctYg8QF5XqolhkdxczsrLK2/n6OLTOyrAZES4EAiZksSMwQBEFwRI6biTPLTLmYmVgyhtXEKgCg19NryATExUUAGcuMnszNKaKpt1eq+bVmeXvEUAhCQskmS/X0kJspCxIzBEEQHMGzm6mcZYbF97hsLngdXkMmoFpmoH/MzNycsrbeXn4tM+KMUl051dUFOJ1kmcmCxAxBEASn8OBmqlbMzMUU90ePu0ffonZFLDPqUzq6meqxzDCM1hS22VkAgNSXV12ZxAyJGYIgCJ7g2c20uFg6m4lZZqptLqkFm0ExM7EYsLzcAJaZtJhJMTGTHph6M5GYIQiC4IrsDZo3y0w8LmBjo/hxzDLT69YxXiZvAvluJr0MM/PzikhraZHh89V+UrPEjK2EmCHLDIkZgiAIrsi2zCzGF5GStJbWN4ZSQcDMiqS3ZUYo5mZStYw+mziLl+npSWmKqc28xtiA3Hw3k0xiRoXEDEEQBEdkb9CSLFne0iB/n2SxJfkwN5ORlhmWlqx3ALAe8TKAdW4mEjMkZgiCILgi39rAqupaRf4+yTpL52OUZSZHzKSr3+qdms0sM3192qxgZmVIq5aZfh3r+DQJJGYIgiA4Zmx5zNLxC8WMvehxhsXMZGGbn4cQjeoeADw7qwi0nh5tlhnTYmZYana+ZYYgMUMQBMET+a6TsRW+xMz4eHk3k5GWGSBjnQH0EzPz89ozmbIxVMzIshozJPX0FDy32SExQxAEwRH5G/T48rg1E1HJ/fZ/4kShZUaW5YybyW28mNE7ZoY10Ozu1mqZMb43k7C2BiGdSqb2q6KYGRUSMwRBEByRv0GPr4xbM5E0+fvkiROFlpm1xBrWU+sAgG53t6ETsI+P695okmVodXXx62YSl5RAcMnlgux2mzdwg0BihiAIgiPyN+jR5VGLZqKQv09OT9sKas2wjCuXzQW33W3oBGwTE5mYGZ028VBI2Qr9fo7FTCikjOH3mztwg1A8kosgCIKwFIfoQEJKILQewm+Cv0F0OQqn6MSAd8DUeWTvky6XhHhcxPPPOzEwkIkveW1lGQDQbu/E6GjpKsEAEAhIcLtr33wltxtiLAbHa69he18SzjXAMzEN25q/8osr4JtfxSkQMRBdhG00mfNcKhAA3OUFmqmWGeZiyhqYKgAbLGYOHz6MRx99FGNjYwiFQrj55pvxxje+UX3+nnvuwdNPP53zmp07d+LOO+9Uf08kEti/fz+effZZbGxs4KyzzsL111+Prq4uI6dOEARhCcza0OpohVN0Yi42h9d9/XXq8//vG/5f7D13ryVz27o1hSNHRFx9dZ4r6RQZ+FNgbrwX/+2WvuIvTtPXl8Kzz85VL2jS1yO1bRvEV19Fy3PP4afPpZ/78l/UuILivMB+uKbwueTgIOZ+9jOlsWMJzEgqYpYZqZhlhjBWzKyvr2Pbtm1485vfjH/4h38oesy5556LG2+8MTMhe+6U7r//frzwwgv42Mc+hra2NjzwwAP4/Oc/j3379kEUyUtGEERzwdxMAgR86PQP4d6X74UsyNhIbiCeiuPp6adNFTPsS78gyPjAB6K4++42pPKSfhKdc4gDsG10wdNW2lUTiQiYnbXhtdfsOO+8RE0T2Hj96yG3tMB+/DgiiQhkWYbH4YFNKG8Jqub0kYgiCtracgWWuLoK+9QU7KOjSJ52WslzWG2ZITeTwWLmvPPOw3nnnVd+AnY7fD5f0eei0Sieeuop3HTTTTj77LMBADfddBP+4i/+AocOHcK5556r84wJgiCshVlmBEHA/379/8b/Of//IBAI4Ecv/Qi7f7Abx8PHTZ5P5ufrr1/D9devFRzzjd+N4a9/Aex+ixf//LmZkue64oouPPdcC44fr17MMBeK7PFg4Uc/AgBc/NDFGF8Zxw/e/V28of8NNaymkGPHbLj00j60tUl47bXcuXf/j/8B529/W1HMmEFRMcMgMWN9zMzhw4dx/fXXo7W1Faeffjre//73o6OjAwAwOjqKVCqlChkA6OzsxPDwMI4ePVpSzCQSCSQSmT8UQRDgTvs8dW1Nn3U+vc/LC7S+xqfZ19hs61PXAwGCIKi/n+I7BQAwE51BJBFBm7PNrBml51X6GofXwwAAf4u/7H3YsSOJ555rweioPee4qu5h1rUQBcUqLwty3fc9FFIsO52dUsG5UiMjQFrMlBsnYyARih6nx3tUDIcBKG4m9TxFrqEV8PA3aKmYOe+883DRRRehu7sbc3NzeOihh3DHHXfg85//PBwOB8LhMOx2O7xeb87rOjo6EE7f2GIcPHgQDz/8sPr79u3bsW/fPvTkFxrSkf4mLy9N62t8mn2NzbK+RZtSGE0URQQCAfXxU7eein5vP2YiM1i2L2NXYJcp85HSXiNBEHLmk01cjAMAtvZsLXkMALzudcB3vgNMT7chECgUY0XvYWsrAMDb1gZv+twsHKGrs6vseNXA9t/eXnvhuc49F3jkEbQHg2gvMw4Lp/H7O1FuOnW9R6NRAEDb9u1oY4OkrTQtDkfd10EPrPwbtFTMvOlNb1J/Hh4exo4dO3DjjTfixRdfxAUXXFDydZXS8fbs2YPdu3ervzO1OD8/j2QyWeplmhAEAf39/ZiZmdEtTZAnaH2NT7OvsdnWN7ektAWQZRnBYDBnfSNtI5iJzOAXx36BQXHQlPnMzIgA+iAIMoLB4i6kqSWlf5Qj4UAwGCx5rp6eFgCdePnlBILBBfXxcvewbXUVXgCRSASr6XOnkkrQzsLiAoLO0uNVw7FjbgA+tLXFEQyGcp5z9fTAD2Djd7/DYpl1JRJdAJxYWlpCMLhe8Lwe79HOYBAtAEKiiHh6Lq5wGH4o8alLZeZnNEb+Ddrt9qoMEZa7mbLx+/3o6elR/xh8Ph+SySQikUiOdWZlZQWnnnpqyfM4HA44HI6izxn1YSfLclN8kJaC1tf4NPsam2V9UtoUIkDIWY8sy9jh24GfB3+O34d/b9paJYnF8JT+/FyMK9Ykf4u/7LxGRhT3/9iYHcmkDFte7G7Re5iJQM6JJwKUruL1XodQSDmXz1d4rsTICADANjpadhxm3ZGk8ntMPe9RtZVBZ6d6DvVMnLz3rfwb5CodaHV1FYuLi/CnU89GRkZgs9lw6NAh9ZhQKISJiQns2mWOiZUgCMJMsrOZ8mFxM8fCx0ycUSZmphQsZqbTVSQ4NYuhoRScThnr6wKmp6vMQmIbd3Z8iI7tDFj1387Owiys1PbtAABbKAQhHYBbDNbOwEgoNbs8hlpm4vE4ZmYyZsm5uTmMj4/D6/XC6/XiwIEDuPDCC+Hz+TA/P48HH3wQbW1tai0aj8eDt7zlLdi/fz/a2trg9Xqxf/9+DA8P5wQFEwRBNAuqmCmyUY10KJYCM1scZBlGSsIqAFcSMzYbsG1bEkePOjA6asfwcBWNHYtMoJjQ00q56r9yaytS/f2wzczAPjaGRLFMoqypGWaUkOWMmKHU7KIYKmaOHz+O22+/Xf39gQceAABceumluOGGGzA5OYn/+q//wtraGvx+P84880x8/OMfVzOPAODDH/4wbDYb7r77brVo3qc+9SmqMUMQRHPC9u4iG/bWtq0AgBMrJyDL9Wfy1EKpoWRZVsWM31W5Gu/WrSkcPerAxERtlpliE9CjN1M5ywwAJIeHYZuZgW1qConXv77suYzSFEIsBmFdicXJscwYPXADYaiYOfPMM3HgwIGSz996660Vz+F0OnHdddfhuuuu03NqBEEQXCJn1EwBQ21DEAUR0WQU87F59Hp6jZ9PJjCj6PORRAQJSYmFqWSZAYDhYSUJY2JC+/ajZ2+mSn2ZUoODwC9/CfvkZJn5ID2fuqdTFFZjRm5pgezxmDdwA0HmDYIgCI5Qg1yLqBmnzYktrVsAKNYZc+ZT/vlQXHF/VNtkcutWxbVUrPt22QkUi5kxwTKTGh4GANisFDPZ8TLZFirqzaRCYoYgCIJDSsWFDLcpm+uJVXPFTCk309J69S4mANi6VbHMnDhRo2WmSIE4PcRMJctMcmgIAGCbmqo4NaMtMwUuJrLMqJCYIQiC4IhKG/S29m0AzLfMlBIzzDJTjYsJyFhmJiZs1e3B5SZQ5x4uSRkxU9IyM6jU8ylnmTGaoplMAImZLEjMEARBcES5bCYA2NquBAGbldFU0TLDgn9bqrPMDA4qlpnVVVGt8VKOYi4UvdxMKysCJEk5V8mYmbRlxj41lSmHnD8fg+OwS/Vlkik1W4XEDEEQBEeUi5kBMmKGG8vMumI1qNbN5HYD/f0sbqYKV1OxmBmdNnEWL9PaKqGlpfgxqS1bIIsihPV1iPPzRY/J7s1kBCUtMwyyzJCYIQiC4IlyRfOATHr2xOqEOfPR2c0EZOJmqkrPLpeaXXf13/LxMgAAhwOpdN+jSq4mw2NmStS5IUjMEARBcEV+yf58htoUt8d8bB6xZMyE+SA9n+LP1+pmAoCBAcUyMzWl0TKjk5upUiYTI8fVVASjQ1eEYgXzzBi4gSAxQxAEwRGVLDO+Fh+8DqVX3XRk2rR5VXIz1WKZGRxUxMzkZPWWGdmAbKaqLDPIiJlSlhmjNYWNspkqQmKGIAiCIyoFAAuCoFpnplZLpwvrR/neTLVU/2UwMVNVf6Zylpk6N/FaLTOlxYycM1W9KelmIjGjQmKGIAiCJ6rYlwa9SrrwZMT4dOFqi+bV4mYaGmJupioL5+Whl5upWstMskJ6tmluJrLMlITEDEEQBIeUa6ZopmWmopjR4GYaGFACgKemqqw1AxQvmqdTAHDVMTMVxIxRkGWmMiRmCIIgOKIaa8OAdwCAuZYZ5krJR4tlhgUAR6NV1JoxsGt21TEzrKXB9HTRWjNGagohFoMYjwMoY5khSMwQBEHwRKVsJiBjmZlcNVPMFD4XS8YQTykbbS2WGZcL6OlhcTMVMprKKAS9spkqipn+fsg2G4SNDYizswXPGypmWJNJhwOy11v8GLLMkJghCILgiUrZTAAw5DXfzVRMzLDgX4foQKujtabzsiDginEzxSagk0GiWssM7HaktigNPkulZxtFySaTALmZsiAxQxAEwRGVspkAYLBNCUidi80ZXmumnJjJLphXa1XeTK2Z8mJG4CCbCaiuR5MRmqJswTwSMyokZgiCIDiiUjsDQIlPYZYQo2vNlLXMrNdeMI9Rj2VGj2wmWa7BMoPy6dlGtjMo18qAJEwGEjMEQRAcUY2bSRAEU11NypiFj6nBvzXUmGGwhpMVa82U6c1Uj2VmdVVAMqmcp7Oz8nlUy8x0oXg00kBSti8TWWZUSMwQBEFwRDUBwEDG1WR0RlM1biYtYqZaN5NRlhlmlXG5JLjdlc+THFAyyGwnTxY8Z2RSEYmZ6iAxQxAEwRHVWGYAc4OAS6GlLxOjVjeTrLOYqSVeBoAaAFzcMmNcBeCqYmYIEjMEQRA8wo9lpnQ7Ay0F8xhMzIRCNkSjVWzKOm/cmXiZ6hSI6maamipQLZa5mRhkmSExQxAEwRPVWhvMqjVTbp/UUjCP0d4uo71dsYqUtc4UmYAeMTM1W2YCAQCAGI1CCIeLHkPZTNZBYoYgCIInqtyXmJvJ0mwmDU0ms6k6biYPPWNmqslkAgC43Uh1dwModDWZYpkhMVMWEjMEQRAcUW3MDHMzzUZnEU/GjZtPmXYG9biZgCrjZgzKZqrVMgNkXE12M8UMs8xQAHBZSMwQBEFwRLXZTGbVmqkqm0mDmwnIpGdPTtYmZtSnzLTMoHQQsNWWGWpnQGKGIAiCK6q1zOTUmokYl9FUTdE80y0zOvQz0GSZYenZRTKaDCEeh7i2BoAsM5UgMUMQBMER1bQzYKgZTSY0nMyfznpqHWsJZaM1MmamaDsDHdxMmiwzTMzk9WcyKkOaWWVkmw1ye3vhAZSarUJihiAIgiOqaWfAYJYZI9OzS1lmmIvJJtjQ7iyy0VYBs8yUrQJczjRUB0zMaImZMcvNVLbJJLJixckyQ2KGIAiCJ6p1MwEZy4yRhfNK7ZMs+NfX4oMoaNtKmJiZnRWxsVFhAgZVANZkmSlSBRjQvzdT2bRsIgcSMwRBEBxSlZvJa7ybqZJlRquLCQC6uyW4XDJkWUCZZtTKPIq5mTSKGVmuM2ZmdhZYX8+aT+a8elI2k8nIgRsQEjMEQRAcUUscCCucZ2QAMFC8AjCrMdPZot1qIAjAwICS0XTiRImDyllmNG7ia2sCNjZYk8nqxYzU2QnJ5QIA2ILBzHwM0hS2hQVl3HR9mwJIzKiQmCEIguCIWtxMTMwYWWum1D65GF8EoD2TicFcTRXFTBb1upnm5pStr7VVgsdTwzkEoWhGk1G9mcT5eQCA1NNTcj6GDNyAkJghCILgkSrCL/wtfnjsHgDG1Zop5Waai84BAHo9vXWdv6KYKUK92Uzz80rAcU9P9VYZRnExo2kaFRHTlpkUWWYqQmKGIAiCI2rJZhIEwXBXk9FihqVna3Iz1WmZ6e1N1fzacmJGdzdTtZYZgsQMQRAET9TiZgKMDwIu1c5gNjoLAOjz9NV1/qrdTDpu3EZZZnR3M7GYGXIzVYTEDEEQBEdU286AoXbPNrDWDFDEMhMzyc1UrmiehZYZe5H0K6NiZlKlxIxRAzcgJGYIgiA4olbLjOpmMqjWTCU3k16WmclJQCpmKClnmdG4h8/PK1ufJsvM8DAAwFYpl7xeZLlqNxP1ZiIxQxAEwRW8upmySUkpzMeUjbZey0xfXwo2m4xEQimel0/RdgZ1x8wobqbe3trFTJKJmelpIJXKmZqemkJYXYWQrmVDAcCVsRt58sOHD+PRRx/F2NgYQqEQbr75ZrzxjW9Un5dlGd/73vfw5JNPIhKJYOfOnfjIRz6CoaEh9ZhEIoH9+/fj2WefxcbGBs466yxcf/316OrqMnLqBEEQllKrm8nMbKaF+AIkWYIoiOh2ldhoq8RuBwKBFKam7JiasqG/v4TrR8feTMzN1NNTu5tJ6u+H7HRC2NiALRhEanAwS1PoF9ejpmV7vYDbXfQYmQKAVQy1zKyvr2Pbtm247rrrij7/wx/+ED/60Y9w3XXX4a677oLP58PnPvc5xGIx9Zj7778fv/zlL/Gxj30Md9xxB+LxOD7/+c9DKmqPJAiCaGxq3aCZmJmJzmA9tV7haC3zUf7P3jeZi6nb1Q2bWKavUpVkXE1FzmWAZYYFAGuxzEAUMz2a0oE+RmiKigXzsiHLjLFi5rzzzsPVV1+NCy64oOA5WZbx+OOPY8+ePbjgggswPDyMvXv3Yn19Hc888wwAIBqN4qmnnsI111yDs88+G9u3b8dNN92EiYkJHDp0yMipEwRBWEKtbiaja80UEzMsk6leFxOjbMPJ9AT0ameQSgELC9otM0CWqykdN2OEt6eq4F+yzKgY6mYqx9zcHMLhMM455xz1MYfDgTPOOANHjhzBZZddhtHRUaRSKZx99tnqMZ2dnRgeHsbRo0dx7rnnFj13IpFAIpFQfxcEAe60ma5a0221sPPpfV5eoPU1Ps2+xmZdnyAI6j/2e6njhtqGcCR0BFORKezw7dB7JulxMnNgmUx9nj5drvvgoGIhmZqyl14nCq+BAKHm8cNhEamU8pqeHlnT/FkQsH1yMn2PlMdlufh90vIetWWlZZe8JqKoDmzl+5+Hv0HLxEw4HAYAdHR05Dze0dGBhfRNDIfDsNvt8Hq9Bcew1xfj4MGDePjhh9Xft2/fjn379qGnUnpbHfT39xt2bh6g9TU+zb7GZlmfb9EHAGhpaUEgEFAfL7e+U7pPwZHQEayKqzmv0QPWsNnhcKjnjh1VQgG2dW/TZbwzz1T+n5/3IBDw5D7pdAIAfH4/fOmx3C7ly2l7R3vN488qRiX09ADDwxrnftZZAIC2uTm0BQLwpKfc1taOQKC95Mtqeo9GIgAA98gI3KXWmLbe2ARB9/uuBSv/Bi0TM4x8JVeNv7jSMXv27MHu3bsLxpifn0cymdQwy9IIgoD+/n7MzMxoDkbjGVpf49Psa2y29S2FlAaOiY0EgsFgVevrcShf1F6eehnBLcGix2hlcdEJoAvJZALBoPJF89XgqwAAv+hHMFj/eG1tLQA6cfx4EsHgfM5z/ngcLgDh5WXE0mOtp7N8wuFwzeP/5jfKWIHABoLBRU3zdfl88APYOHIEi8EgYrEOAB6srKwgGFwrOF7Le9R35AjcAFb8fqyVWKN9YQE9AFKpFOZ0uA9aMfJv0G63V2WIsEzM+Hw+AMqb0Z/V3nxlZUW11vh8PiSTSUQikRzrzMrKCk499dSS53Y4HHA4HEWfM+rDTpblpvggLQWtr/Fp9jU2y/qy15D/c6n1qYXzVid1vwbZMTPs3BOrEwCUtHA9xtu6VfmSOTFhQyolQ8yO5mQxMyhs9SDJUs3jT00pcTmDgynNc09s3QoAsI2PQ5ZltTqyJJXfY2p5j4rpCsPJLVtKvkZ9lJP3vpV/g5bVment7YXP58sJ5E0mkzh8+LAqVEZGRmCz2XKOCYVCmJiYwK5du0yfM0EQhNHUGgAMAANepSqtEVWAi7UzYAX6htuGdRljYCAFhwNYXxdw8mReELDO2UwsY4oFHWshtX07AMC2uAghHDYkAJi1S2AVh4tCdWZUDLXMxONxzMzMqL/Pzc1hfHwcXq8X3d3deNe73oWDBw8iEAigv78fBw8eREtLCy655BIAgMfjwVve8hbs378fbW1t8Hq92L9/P4aHh3OCggmCIJoFVczUEExpZBXg/H0yJaXUrCk2br3Y7cDICHDkCDA6assVGsXSqdgerkHMsIypesSM3NqKVH8/bDMzsI+NQRC2aj5XUVIp2NJuo9SWLaWPIzGjYqiYOX78OG6//Xb19wceeAAAcOmll2Lv3r24/PLLsbGxgXvvvRdra2s45ZRTcOutt6qZRwDw4Q9/GDabDXfffbdaNO9Tn/oURJGKFxME0bzUYpkZ8ubWmmmxteg2j3wtEVwLIikn4RAd6G/VL+Bz505FzIyN2fHf//tG4QFFLDNayswwN9PQUH3xk8nt2xUxMzoK4A+V6eikKcTZWQipFGS7HVJvmfT3JsvgqwdDxcyZZ56JAwcOlHxeEARceeWVuPLKK0se43Q6cd1115UsvEcQBNFMaIk56HR1wm13I5aMYToyjZGOER3no/zP9k0WLzPgHYAo6PelcudO5f+xsdxtqVg7A3VuGtQMEzMDA9otMwCQHBlBy3PPwT46qrumUF1MgQBgK1OUkHozqZB5gyAIgiO0xMwIgqBaZ/R2NeVrCRaXo1e8DIOJmdHRvO/YZWJmaiUaFbC0VL+bCVDEDIAcMaOXprCdPAmgQrwMkYPlqdmNTjQSxbeu/QtszEw0pdtSEAC73YFkMmH5+gQA3diFVmirF2SzA2eemUCrJ7MQQRCA9na0rqyU/Uac6utD/D3vIbMuYThqxk6N77XBtkEcDR/FQ0cfwmuh13Sbz5FlO3BhK+YHkvj679bws+mfAdAvXobBcjpeftmBr3+9VX38mmkRIwCeeqoFv5tXHh+DAxCAZ551IPFsa5GzFWdpSfn+3t4uoaOjvg80JmYcL76Id/R9BV1w4r/9Oo7Wrxe2lKj2c4bh/MUvAFSIl0FuNtNmh8RMnTx51xfx/3z7q1ZPYxPxuCEvL13mKsNCdzc2Lr64vvEJogJaLDMAsL1dybD5wfEf4AfHf6DvpN4JnARw+y8Kx9OL005T/p+dteH22zPFVP87bBgB8PAjrfjXR9KPX+EEzgL+4z9c+I/nOwpPVgGWCl4PybQpyT41hQ9OfRofBICn0/9KUM3nTDas0nBJKABYhcRMnUjzSsT5RJsNv94yaPFsjEEUBEgW/7HIQgoxxxQEiBgMv6/m18djAuYXbOjqTOHSP8wEFwoA3G43YrFYSe+781e/gn1yEvajR0nMEIajJZsJAK4/63rEU3HEkrHKB9fAyaCIXzzXAr9fwpvfrFgd2p3tuOrUq3QdZ2AA+NznlvHii7k1wnr/KwUsAG94wwY2hqIAgF8OpjAF4Oyz13HKQLSmcQQBeP/7a3tNMVLbt2P5M5+B4+WX8dvfOjA6asdppyVwxhmFQqmaz5l85NZWrH3oQ+UPIjGjQmKmXlKK3/W3/QFc+NTPLZ6M/gjpMtnBYNDSokzrqXWMfHMEgITffeiv0OnqrOn1L7zgwIfe04NASwq//vKs+rggCHAHAgiXWV/7Zz8L7733wj6lf9orQRSg8c9suH0YX/hvX9B3LgB+/GMXfvFIJ7a/bgNfvmNB9/Nnc911UfzZn+VegK4rEsACcO2fRXH15WEAwN6nkpg6DvzJe6O44Q/Chs6pHGsf/SgA4Bu3duD+0VZ8/J2r+Mu/XC04rprPGU2QmFGhAOA6ESRFhUs6RvUThbTYWtDl6gKgpIbWCgv2m50VkdWDtCpSg4rFzUZihjABrW4moyiTTGTZBOopmmcErKCg6ZqCxIwK7cD1krbMpKjujeEEWpVGalrETE+PBKdThiQJmJkpk+pYBFXMpNMlCcJItAYAGwWPYibzFB+buGWagpP3CA/QDlwngqSIGYnEjOGwAl0zazMVjixEFIEtW5R7xepMVAuJGcIKeLPMWE62ZYazTdxyAwk3N8k6aAeuEyHF3Ey1bZBE7dRjmQEyRbJYOfNqSaZrPdjm5oB4XNPYBFEtvLhOGMV6M1k0gcKnOL1WpmG5iuIHEjN1QpYZ8+j3aLfMAJm4mVotM7LfDyndYoMVsyIIo9CazWQUPLqZeLFaWQ6JGRXagetFFTNkmTGagFcfy0xBV95KCAIFAROmocbMcLJhWy1mipXqZ0KPYmbS7QxMHpZHSMzUiZgWMzJZZgwn4FHEzExUq2VGcQnWapkBMnEzdoqbIQyGspkqT4C/bCaLB+ZE1FkJ7cB1IpJlxjTqjZkJBCQASoXRWkkFlLHFGW1CiiCqhbdsJgZXYoYsM8p46g98XAcrITFTJ4KkbJAyiRnD6fX0AgBWNlY0VTnt7laE59xc7W97qUfpB2Wbn6/5tQRRC7xaZiyfQANYZmTZ5HvGmeC1EhIzdUJuJvNod7bDISqlzpfiSzW/vrdXEZ5LS7baC+f1KkJKJDFDGIy6QXO2T1m9b8pWT6AMlnt7LFec1kM7cJ1kspmoM4TRCIKALrdSBXgxtljz6/1+CTab8ke/uFjbW59ZZkjMEIajahk+Nm9mbbDczZQFb5YZBqVmWweJmTphbiZKzTYH1tJgIV57jxibDejqUu7X/HxtbkEpbZkhNxNhFvyIGatnkIZiZjgamD9oB64TW7o3k2wjy4wZdLu6AWizzABKWwMAmJ+v7a2fYpaZuTlN4xJEtfBqbbDcMsN1zAz1ZrIaEjN1IkjpNxEFAJuC6maKaxUziluwVjGjupmiUQhra5rGJohq4C2biUsxw6llxrKBObkOVkJipk5EmQUAk5gxA9XNFKvdzQRkLDNzczVWAW5theTxACDrDGEsvGYzWd7OoNhT3FhmlP8tK5pHYobETL3YWDYTuZlMoV7LTG+vNssMQHEzhDlQO4PKE+BF6OVDXbOtg8RMnYjkZjIVFjOj1TLT3a0tABjIipshMUMYCG/tDBiWtzPgeOPmeGqbBhIzdZKpM0NixgyYZUZLnRkgU2tGk2WGxAxhAvy6mfiZAG8xMwxLLTOcXQuzITFTJ6KsbI6wO6ydyCah3pgZVgW4LjfT7KymsQmiGigAuPIE+MtmUv4nMWMdJGbqxMbEjI0upRnUn82k3K+FBQ1upm7FxSUuahubIKqBlw2aO4pZZji5Vla1M8hZPYkZoh5sam8mCgA2AxYzE0vGEE1Ea359Z6dyv5aXBaRStb1W8vsBAGIoVPO4BFErvLmZrCZ7GqplhpPJWZ6aDfBzoyyCduA6YW4mgdxMptDqaEWLrQXrqXUsxhfhcXhqer3PlxafsoDlZRFdXdV/AOgpZlJSCim5RjVV7DwpFBVldtEOUVC+qwgCsLGh/Mv/vLPJSdgEqfQAdjtA1a03Ndy0MyA3U+mBLRmcL0jM1AnLZhJsFABsBoIgwN/ix0x0BqF4CENtQzW93uEA2tslrKyIWFoS0dVVvaDQS8z8bPpn+LMn/kxT5++qWQ0AX3sRiPRnPRjIOeRG3IN/xMdgR+lrkOrqwsLjjyM1OGjQRIl8KGam8gR4CwDmQsxscugrV53YWcwMZTOZht+liIrQujZR4fcr9ywUqrEKcGcnAEBc0pZJxfjPE/9prJABgLYgsPW/yh7yPnyvrJABANviIlr+q/x5CH2hbKYSEyj2FDeWGYvaGWTDibCzCrLM1ImYjpmBg9xMZuFr8QEAwuthTa/v7JRw4gSwtFSjmMm2zMiy5k/3sZUxAMDtF92O9+18n6ZzAMDHPubDf/6nG5/4xAquuioTP3THC5/G45M/xCfu+C1uOP2/QRAE9Pf3Y2ZmJuebbOCNvwciwGcufgx/8Y2RgvO3f/7zaH3gAdh//3vNcyRqh1/LjMUVgKloXiHkZlIhMVMnNvbBQxWATcPfkrbMxOu1zNT2gSinLTNCIgEhEoHc1qZp/PGVcQDAaf7T0NHSoekcADB9vBuIO3DuaSkM9WTef6f17MDjk8BcYgIdHTIEAfD5gFhMzoiZWAy+yEkAwE9Dr8OfdxR+ECZOPx0AYD92TPMcidrhzTLDsNwykz0B5tbhxjKj/E9ixjrIzVQnLJuJYmbMQy8309JSjf2Z3G5ILhcA7XEzKSmFydVJAMD2ju2azgEon1snTijz37Yt11U03DYMADixcqLk6+0TEwCAMDrw4nhv0c/B5M6dyrHHj2ueJ1E7vIkZbtxMxSwzm3v/JjGTBYmZOlEtM+RmMg2rLDNA/XEzJ9dOIiEl0GJrQaA1UPkFJVhYELG2JkIQZAwNJXOe29q+FQAwsTpR8vX28XEAwDGcgrWoDbOzhR8FyVNOAQDYJiaAmMExPoQKv24ma8Yv1s6AspnyBgY4kb7WQWKmTkTVzURixixYzIxWywyrNVNrzAwAyHVmNLF4meG2YTV1Wgvj44pbaWAghZaW3OeYZWY6Mo2ElCj6eltazAQ9OwAAo6OFblKpuxtSRwcEWYZ9bEzzXInaIMtMCRogm8nSgTm5FlZBYqZOWDYTuZnMg7mZ6gkABmrPZgLqt8yML48DyFhPtDI2VtzFBAC9nl64bC6k5BROpuNi8mGWmeUexdV1/HiRmC9BUK0zFDdjPrxZZiyfAFlmSg9MkJipF1u6zozoJMuMWejlZtJimam31gwL/t3Wvk3T69XzpC0zW7cmC54TBVGtv3NitXjcDLPMJLYqompsrHgAe3KHYrmhuBnz4MXawA1lTEObXcxQO4MMJGbqxJZ+/4iUzWQa9QYAW2mZCa4FAQCD3vqK0AWDimVmcLB4nRjmappYKR43Ywsq83DsGAAATE4Wtywm02KHBQwTxsPLBs3gxc2U087A6smUwOzeTHmDWzc2B1i+Ax84cAAPP/xwzmMdHR34xje+AUD5lvK9730PTz75JCKRCHbu3ImPfOQjGBqqrfKrUajZTHbLL+Wmod46M1ZaZliDTNYwUyuLi8rcu7qKtyIYbFPE0nRkuujzrFmmd7uynlJiJrVtGwDAdqJ0ZhRhDPzEzHDczoCTDZwLNxMn18IquNiBh4aGcNttt6m/i1m9YH74wx/iRz/6EW688UYEAgE88sgj+NznPocvfelLcLvdVkw3B2aZsTmc1k5kE8HcTMvry0hJKdhqrL7MLDPhsAipTFuiYtRrmVmKK6/rctUnZpgQKyVmBloVi8tUZKrwyVRKFWPdpzMxU8LNxCwzJGZMg7KZSkwgC4qZyRvYksH5ggs3kyiK8Pl86r/29nYAyh/1448/jj179uCCCy7A8PAw9u7di/X1dTzzzDMWz1qBpWaLDi504abA5/IBUD7IljeWa349s8xIkoDl5do+oeu2zMTSlpk6xUw9lhkxHFbTXXtPV/7WwmERq6uF14KJGdvMDKVnmwRv2UwMy8VMA2QzkZixDi524JmZGXz0ox+F3W7Hzp078f73vx99fX2Ym5tDOBzGOeecox7rcDhwxhln4MiRI7jsssuKni+RSCCRyKSkCoKgWnH0/rZjTwcA2+x2br5J6QlbE09rc9qc8Dq8iCQiCK+Ha3bZtLQAXq+ESEREOKxYdapdn2qZCYVqviayLGcsM+6uuq5ptpgpdp5sMZN/D21pq5Lk86Gt0wG/X0IoJGJqyo4zzsgLKO7shNTeDnFlBY7JSSRPPVXznI2Cx/doPahiRhDUf+x3KxEE4+ZQdo3MUiWKRY+z+rooc8j8X2w+ht3DLC+GkD0Rk+HhPWq5mNm5cyf27t2LLVu2IBwO45FHHsFf/dVf4Ytf/CLC4TAAJYYmm46ODiwsLJQ858GDB3PicLZv3459+/ahp6dH9/nPpv/QfN3dCAS0F0Hjnf7+/soHmUh3azci4QhsXpum697dDUQigCAo74mq17drFwDAsbxc87ihWAhJWRELZ20/Cy32lgqvKE48DqytKT+feWYv0saiHF7X+joASsBxd283gKw1Hj0KABB7exEIBLBjB/DrXwNraz0ouqRTTgFefBE9KysofgAf8PYe1YrX61X+b/XmvMesWh/r2uHxuBEIGOvaL7rG9Ibd3dOjvv/avMqkPK0eLj532RblcnkQCHhKHqf7PUxmvnz09/ej6IeBiVj5N2i5mDnvvPPUn4eHh7Fr1y7cdNNNePrpp7EzXU49X+1VMi3u2bMHu3fvVn9nr5+fn0cyWZjKWg/OtJV/LRZFMJ0h0kyUalJoNe12xT3y++nfY5t9W82v7+joAuDEsWMhXHSRv+r12SQJvQDkhQXMnDxZ0zeh0eVRAIDX4cXSvPbO2ydPigD6YLfLiMVmEI8XOUgGHKIDCSmB3x7/Lc7feb66RtfRo/AD2OjowGIwiP5+HwA3XnppGW94Q7TgVL6BAbhffBErv/kN1t7wBs3zNgpe36NaWV1dBQBEo8pnitXrW15uBdCOeDyGYDBsyBjl1tiTSsEOYGFxEYn0Z2wkElH+X4tw8bm7uqpcI+WeFbq+DbuHqRSYlJsJBiEX/TAwHiPfo3a7vSpDhOViJh+Xy4Xh4WEEg0G8If3BGQ6H4c9SnCsrKwXWmmwcDgccJdoL6H2h1ZgZu70pPkhLIcsyV+tTqwDHQ5rmxeJmFhczvvdqzpPyKeMK6+tANArZU/pbWD4LMcWa2OXqqutasjkrgcxyUVe5AAFbWrfgxOoJTEWmcD7OV9copK2aqS5lHiy9e2LCVnReLG5GPHGCq/dAPry9R7WSHTOTvR6r1idJbEzjxy+6xvTvMop8fsu8xM2k51hhPrrfw+z3hyRZfi2s/BvkIgA4m0Qigenpafj9fvT29sLn8+HQoUPq88lkEocPH8apnPjuWTaTPb+mPGEoVtWakT0eyOl7XWtG01JMOb7T1VnT6/JZXFTifEoF/zK2eLcAAKZXc4OA2bylLiXWiPV2mpoqkZ49oGRG2aeKZEYRumP1hpSP1dlMjdCbiUG9mazDcsvMAw88gPPPPx/d3d1YXl7G97//fcRiMVx66aUQBAHvete7cPDgQQQCAfT39+PgwYNoaWnBJZdcYvXUAQD29H5ip2wmU7GsCrAgQPL7YZuZgRgKITVYffE7VmOmfjGjzJkJslKwwnz56dmsxgwLZh4aYpaZ4u9htkYbiRlT4DWbyTIom6nywJYMzheW78BLS0v4x3/8R6ysrKC9vR07d+7EnXfeqfrILr/8cmxsbODee+/F2toaTjnlFNx6661c1JgBAFt6PxGpaJ6p1NufKdM5W1vhPNvMTM2WGbMK5jFKpWfbmJhRLTOKmKlkmbGdLN7nidAX1drAiZax2jKjzoNjywyJGeuxfAf++Mc/XvZ5QRBw5ZVX4sorrzRnQjXC3EwOF7mZzKTeztlWVAHWv8ZM8VYGjFKF88Q8McNiZlZWRCwvC+joyP1QZJYZcXkZwuoqZJbeQhiDqmX4UDPcVADOQrXMcCZmLGWTixnuYmYaCSklZWJmyM1kKvW6mTIxM7V/CmmtAqxaZgyu/ssYaEuLmdU8MZMXM+PxyOjuVgRNsbYGcmsrpHTgM7majIdXNxNXYobbdgbmXySZCyVlPSRm6mBjfUP92eGidgZmopebyUzLDBNene76YmbYnKuNmZmOTOd86DMxk+rKiCrmairZ1oDFzUwX7/VE6Ae1M6h+ArxZZizRVpYOzg8kZuogkS1mqDeTqdTrZrKic/bKxgoAoMNZuqxAVedZUeac7w7KZ0urks0UTUbVTCoAEFaUecjptiFAxtVUsuEki5shy4zh8GaZ4VHM8HJtGIKQSc22DBIzhFY21jMtE+zO4nVtCGPQK5spFBJr/gxglhmhRstMNKkUpPM4qq9NU/Q8UeWD3OMpb5lx2V3ocSuB9CeW040iUymI6R5LcmureixLzy4pZsgyYxrZ7Qx4IKMlLN4sOc5mYpBlxjpIzNRBciMjZpxussyYCXMzRZNRrKfWa399WswkkwLShoqqYZYZW42WmciGUrXU6/DWNmD+eSLKh5fXW/nDi7maJpYnAABCNFPhV8oRM+XdTKplhsSMafBifbB8jyQ3E8eD8wOJmTpIbGTcTGSZMZd2ZztEQXn7aombcbsBt1sRNGXafBVFq2VmLak0VGq1t1Y4ssJ51pQPr9bWyh9erHDeibBimRHSTZ1km03puJmm2vRsKpxnPLxaG8jNxCkkZgCQmKmLZFbMjLOFLDNmIgqiGntSb0ZTOlO5arTGzEQTilWk1VGfmIlGlT/basRMgWWGiZnW1pzNYWBAETPT0+RmshqKmak8Ad7cTJZ6BEnMACAxUxfJDSXOQAKlZltBvS0NmKtJq2WmlmympJREPKU0gas3ZoZZZirFzAAZMcNiZsS0mym/pxQTMysrIlZWCj+Z1Vozs7NAlkWS0B/KZsqlEdoZ8OBm4uPdYh0kZuqAxcyk6CpaAgsCDsfDml5ft2UmFgPSwbSVWEusqT/XEzOzvg4kEtXHzAx4FfcQEzNCutuw5M2dQ2urDJ9PuR7FrDNSVxdklwuCLMPGQZfiZoY3ywzP8GaZsTRmZpND23AdJNPfUFP0XrIEZplZWq/N3aO+XqNlRvZ6IafbV1RrnWFixiE64LRpd0kyqwygFLurBCucV9TNlH9sOVeTICC1RYm/ofRsY+GtnQGDSzcTWWYycCLsrILETB2k0m6mJF1FS+h2dQPItAmoFa2WGQhCzXEzLC1br3gZl0tGNe3AmJtpbm0OsWQsI2Y8ha6uwUHl/VwqboYK55kEd+0MlP+tFjPZWzUv1yYfK/SEOiSJGUIrySS5mayENWxciNdoWknj9yt//LVaZoAsV1ONlhmP3bx4GUAp0McE1HRkOhMzU6tlBhQEbBa8uZm46c3UEDEzFlwkLsxC1kPbcB1I68zNxMeHzmaD9TjSbplRNu+aLTPICgKu0jITSSixKvVaZliNmWoymQDFHJ/d1kCNmdEiZsjNZAoUAFyCBshmojoz1kFipg5SacsMuZmsodutuJkWYhZYZmrMaGKWmXoL5jHLTDXBvwwmZqYiUxk3k7dwHlu2VGeZoVoz5sCPZYaTCTSAZcbSwS2/UdZC+cR1oGYzWf6VZXPCxAzrRl0rmmNmULuYYTVm6m9loCjnaoJ/GSyjaXp1GkJUec8Wj5mp0s1EYsZQeNmgGZZbZhqizoyFvZlIzAAgy0xdSEklYJKymayBxcxodTNpzWYCai+cp1b/rdPNlKn+W13MDJDJaJqOTEOsIptpZsaGRKLg6YyYOXkSkKofn6gN6s1UcgKFT3Ei/LhwM21ySMzUgZRg2Uz0ZrICNWYmvghJrn1zzbbMaG02WaubycxWBoyibqYiYqanR4LTKUOSBMzOFlpnUv39kEURwsYGxPl5LdMnqkCNmeHMzcSTZYYoAllmCK1ICQoAthImZlJySlN/JmaZ2djIrd9SDTVbZhJ6W2ZqdzNli5liAcCiWCFuxuFAqr8fALmajIS3bCaG5WImC96uDYPcTNZBYqYOpFS6nQGJGUtw2pxqfyYtria3W4bLpXwAhEK1/SlotszULWaq78vEYJaZYCQIpLOZillmgOqDgEnMGAev2UxWoV4FrmNmlP9JzFgHiZk6IDeT9dRTa0YQMtaZpaUaxYzllpnq3Wp9nj7YRTuSchKp1TCA0mKGxc2U7J7NMpqo1oxh8BIHko/llpkGyGai3kzWQWKmDqQEZTNZTb1VgOsWM1WmQuktZmrJZrKJNgy2KyIkFVkBUFrMUEYTP/DiSrE8ZKWB2hlYCllmCK3IKZbNxMM7eXOi1prRWAW4t1fZvOfmahQzvb0AlGaTrBBdOfSuAFyLmwkAtnZsVX6IrAIApCKp2UDGMnPyZAUxMzlZ0/hE9fDqZrJ6OsXaGZCbCZDJzQSAxExdyCw1W6TLaBWqm0lj4bzeXsUyMztb2z2UPR6187Q4O1vxeJaa7XXWWzRPmWctRfMAYKtPETO2qNLlu1jRPIBaGvAEP5YZq1VMI6VmW9jOYJNDu3AdyElyM1lNn6cPADCzNqPt9X1MzBTfvMvBrDO2asSM7qnZtaWiD7cPAwAcsXUA5WJmFIE+NWUr+kUvOaBkRtmmpjb9N0Gj4GWDZlhumSkXM8PJe5AL4wgn18IqSMzUAXMzSRQAbBlbWpV+QcG1oKbX9/VpczMBQKpPEVK2ubmKx+pXAbj2mBlAscyIEtCyoay3UjbT2pqIcLjwfZ1KixlxbQ1COFzTHIjqIDdT5Qnwcm3yoWwm6yAxUwdyUvngTwp0Ga0i0BoAUI+YUSwcMzO1W2ZSLG6mBsuMfl2za4+Zad3I/C653UWPc7szcUSTk0W6nbjdSHUrcUrkajIG3urMcClmKJuJk8H5gXbhekgpbiaJYmYso14xozUAGMhyM1VhmYmllFiVei0zsZg2MbPNtw2edIsCWRAAl6vksUNDyjWZmKCGk1bAm5hhWN7OIBu2f3MjZqg3k9XQLlwHckr50KeYGetgYmZlYwWRjcpZRfn09yuWmbm54jEi5WBuJrEKMRNPxgEALltpEVEN8bjyXmPF/qplm28bvCnlz11ytZT9mj08rLhPJyaK96GljCZjITdTLkIZywwnWsZaSMwAIDFTF2pqNllmLMPr9KLN0QYAmInWHgTc06MI0vV1oWiMSDlqCQCOJRXLjNte3L1TLcwy43bX9sHlsDkw4lRaESRbnGWPHR6uzjJDtWaMgTfLjNViRqUB3EyWDk5ihtBMOptJopgZS6nH1eRyAenOBJibqy1uRo2ZqWCZSUgJpGRFILjs2i0zsqzdMgMAIy3KdVp3ln+/MsvM5GTx65Gk9GxD4dUyY/ngxVKzOdnAuYiZ2eTQLlwHgqS4KChmxlrqjZvZoiRE1VxrRqoym4lZZYD6LDOJBJBKabPMAMB2uzLfqKP8cSxm5sSJEm6m7PRsQnd4sTbkY/me2QAVgDnRVpsS2oXrQa0ATJfRSuoVMwHl5TXXmlEtM8vLQCxW8jgWLyNAgFMs7+IpB7PKANosM4MOpcDgmi1V9ritWzOF86Qi5WzIzbS5sNTNVMIyw4sLjsGDmBE2uZKiXbge1DozdBmtJOBV1MjJyElNr0/vzSVL+JdC7uhQ2wLYTpYem1lmXHZXXa4DFi8jCDKcGjTRoKj0k1oRk2WPCwRSsNtlbGwImJkpfG+rYiYUqqqVA6ENXjZsXtxMOe0MOLPMMCibyTpoF66HdDYTxcxYy6BX2VwnVic0vX77duX/UgGvJREEpIaVyrr2Mpk9zDJTb/Avs8y43bKmb8kBmw8AEBLXIcmlKwjbbJmGk+Pjha4mub0dqXSgke3EidonQpSFv5gZJqItGTzzc0NUADb/IlFvJgXahetAUC0ztRdcI/Rje7uiRsaWx7S9XhUzxWNEypEaGgIA2CZKCylWY6betGxmmdHiYgKAbihVf9fsEqZWy7uIRkaU9/boaIm4mW3bAAD28XFNcyFKQ9lMRQbPmwBlMxUZnMQMoRVBSltmyM1kKds7FDUyvTaN9dR67a9Pi5lS2TvlSDIxY7JlRgu2uHJtog7gSOhI2WO3b1fEzNhYcTGTTF80EjP6o4oZTiwzDK7EjMCrZWazDc4PtAvXAyuaR5YZS+lx96DV0QpJljCxUruraWRE+f/kSRsSidpeyywz9nKWmayYmXqo1zIjxBVRFbMDR0NHyx6bscyUqDWTtszYSMzojupmIstMxQ2aN8sMpWZbR+12dYv48Y9/jEcffRThcBiDg4O49tprcfrpp1s6J+ZmkknMWIogCNjevh0vL76MsZUx7PTvrOn1/f1AS4uM9XUBJ0/a1GyeamAxM+Uye3ixzAjpjKtqLDOV3EyqZWZMm2uPKA2/biYLduqGyWaidgZW0xCWmZ///Oe4//778Sd/8ifYt28fTj/9dPzt3/4tFhYWLJ2XIJObiReYq2l0ebTm14piJuC11iDgpCUxM9per1pmHMDRcHnLzI4dmVozySLJT0kWM0NiRnf4CwBW/rfcMpM9AXX/3twbeA6b/Fo0hGXmsccew1ve8ha89a1vBQBce+21eOmll/DEE0/gAx/4gGXzElOsaB5ZZqyGBQE/e/JZDLcp1pIdHTtwauepVb1+eDiJ48ft+PGPXVhdrV6cOqI78WEAtqUluH74Q8BRWJFuaPpX2HMYOGd+BS7h8arPDQCy3Y6Niy6C3Namq2Xm96Hf4/ExZS4euwcXD1wMh5iZeyCQgsslIx4X8K//6kFnZ272U0vkNHwIgG1mBq/e/h+QbZm/AUEAdu5MwuvV/uGave7NBq+WGcvh2DLDIMuMdXAvZpLJJEZHR/HHf/zHOY+fffbZOHKkuKk8kUggkRX8IAgC3G63+rNeCFLGzcTLtyi9YevifX07fDsAAE9NPoWnJp8CADhFJ371gV+hx9NT8nVsXcy19K1vefGtb9UycifejU50YgmdN95Y9IjL0/+AQwBuqOXkAIDYe96D8Fe/mtPKoJb7od7DdSUAOOG0I56K44afZOZy2wW34S/O+Qv1d5tNCQJ+9VUHPvUpX5Gz+vE/4EcnQnjr1z9S85qqIXb55Qj/y79UPK5R3qPVom7UgrIm69enjCuKgmFzqGaNgiiqG7eYLocho7a/BaMQRRaQXHwNht5Ddm6jzl/VFKx+jzaAmFlZWYEkSejo6Mh5vKOjA+FwuOhrDh48iIcfflj9ffv27di3bx96ekpvalqQBk/BzyePIL5lBP39/bqemzd4X9+1ndfiZ3M/w0xEaTb50sxLWN1YxbQ0jbMDZ1d8/f/5P62YmQFqrQH3q18Bn1r/PL543n60tRb/ZjS5MoXx8Dj6Wnuxq2tX9SePRIDf/hbuV16BOxBQC+V1droQYGWLa8CT/uZ22Vnvwf83rLRgmInM4NjSMby2+lrBOT/3OeCf/kmNc89DwL0z+/D2uf0QsoIwZQlYjShi6KKLoO378+oq8NJLcB8+DHcN6+T9PVotLa4WAICvw5dzT6xaX/p7INra2hAIGGspK1jj2lrmuUAAaFXKC/jnlDpHzhanpr8FvelSimvD4Sg/H0PuoV3Zxru7ujLlzC3Cyr9B7sUMo5zazWfPnj3YvXt3wXHz8/NIFgsA0Mi7vvwPEIQv4k39/ZiZmWlK/60gCOhvkPX90yX/pP780Z98FP82+m947vhzONd7bsnXsPV1d8/gm9+sfX2XX96Fe391A153wxX44z+OFz3m7l//He5+8W58+Iw/wl2X3FX1ucVgEH2vfz3k8XHMTExgZsYHoB2yHEUwuFz1edga46EQXADODlyAA+/8EADgiRNP4NofX4vDs4cRDOa2g7joIuVfaXan/2WIRoHzTgkAKeCVr83A76/9mtomJtB74YWQT5zAzPS0EtRUxfoa4T1aDbG0O3BlZQXBYNDy9a2tdQDwIBJZRTBoTMXnUmsU1tbAtsfgzAyQrri9vKy8/+PxeMH71gpCoRYAndjY2EAwuFjwvJH3sEeSYAewMD+PhEXXwsj12e32qgwR3IuZ9vZ2iKJYYIVZXl4usNYwHA4HHEViFwDjAsZkWW6KD9JSNNr6TvWfin/Dv+FI6EhV89a6vpGRJH71KydGR20lX8+ymVw2V01jpHp7IblcEONxiJOTiMeVb6Nut8Z7kQ4AllyZeWQXHJQkqW4zsdsN9PamMDdnw4kTNvh8Nea6A0gGApBtNggbGxBmZiBV+W2z0d6jpVDTjeXczyur1pcZ0/jxC9aY1RxMVg7IPd6EOVVHJpup3HyMvodWXwsr/wa5T8Ox2+0YGRnBoUOHch4/dOgQTj21uuBOYvOxy6+4c44slU9BrpdKKcxAlpiptc6MKGYq7Y6N5cTMaIEFAMtZ6VDDbcMQBRHRZBRzsfLdv6uFdd2uuT0Ew25HKt3KvFybiGaFt2wmBlfZTOrTPAgZa2NwqZ2BAvdiBgB2796NJ598Ek899RSmpqZw//33Y2FhAZdddpnVUyM45VS/InSPho+W7UNUL5Uq5QKZonla6sxkV9plqdmas5nSlhnZnZmH0+bEkFdJL9faDiKf4WHlmkxOajf8VtMmolnhL5uJk95MWfDazsCK3kwqm1zMcO9mAoA3velNWF1dxfe//32EQiEMDQ3hlltu0T2gl2getrVvg1N0IpaMYWp1CsPtw4aMk22ZUTIZCo+JpzJuplrJrrSb1iK6WmYApUbPidUTGFsew4WBCzWdO5u6LTMAksPDaPn5z8u2iWhWeGtnwGOdGV6EXj6Umm0dDSFmAOAd73gH3vGOd1g9DaJBsIt27PDtwKtLr+Jo+KhhYmbbNkXMLC+LCIXEgnosQJ2WmSw3U6xNf8sMoMTN/BQ/xdiKPpaZrVuZZUa7mKmmTUSzQu0MigyeNwHqzcTL4PzQEG4mgtACqwo8vjJu2BhuN7BlS/k+RppjZpAlZsbHDYmZAYBtHcoYeomZjGWmDjcTaxOxmS0z3IkZizfLYjEznLmZLB2cxAxBNCcj7UoHSb1iQUrBNu/p6eJiRm00qcXNxDb16WnEo8qHVb2NJvPFzEDrAAAguKZPWmf29dD6+aq2iSjT84owBy4tM5wIvQwWCgkSMwBIzBBNzLb2bQCMFzOsr1OpgFcWM6PFzZQKBCCLIoT1dbhX55Xz6OxmCniV1Ge9xExfn3I91tcFhMPaNh0pXXzLNju76T6kectmsvTyk5up+sE3OSRmiKaFuZn0cp+UglkiSsWIqJYZDW4mOByQ+voAAF2rSvyIJstMMgkh3eIj3zITaFXEzHx0Hkmp/qKSLS2Az6fEDs3OaoubSaWD+4WNDQglKn03K7y5mawk5wo0gJuJYmasg8QM0bQwMTMVmcJGasOwcYaGFAEwNVU+ZkaLZQYAkoODAIDuNUXMaLLMpONlgELLTLerG3bBjpScwnxsXtMc82HWmbk5jUHALhcknw8AYJvTp/5Nw8GJluHZzUSWmSw4uRZWQWKGaFp63b3w2D2QZAkTq8ZlxWTcTCUsMyntMTMAkEqLmZ6YEgyryTITjQJIF9hqacl5yiba0NeqWH/0djXNzmr/iEn19gIAxNlZXebUKPCWzcTgSsxw6lqxUk/weUXMg8QM0bQIgmBK3Ewm4NVe9MOsXssMEzOB9fotM7LLVXRXYq4mvcRMb6/iZtJsmQEgpcXMZrPM8OZm4sYykwW/RfM22+D8QGKGaGpY2vGJ1ROGjREIpCCKMuJxAfPzhX9SdcXMIEvMJJQ11GWZcRWfg95iRk/LzKYTM5wGAJOYKQ2lZlsPiRmiqWGl+qdWjUvxdTqB/v7irqaN1AZSsvJcvZaZwVQdlpm1NQCF8TIM/cVMfQHAANTA503nZuLOMmN9OwM5b3DKZspAvZkUSMwQTc2gVxEC05FpQ8dhrqb8IOBIIqL+7HV4NZ2biZltGAcgw+vV8KEVUeYhe4vPQX83EwsAJsuMVsgyk0W+mOHUMmNJbyYSMwBIzBBNzmCbIgQmI8ZWkmVBwFNTubVmognFveOyuWAXtVXETQ0oRe3aEIEfIXg8dYiZ1taiT6tiJsKPZSbFLDObTMzwskEzLK0AXEFJ8XKtuIiZ2eSQmCGaGmaZMdLNBJSuNbOWUNw7HodH87lltxsJXxcA4DTXGEQtf7UVxEyvW7GC6JWazSwzs7Oi5g945maybTY3E2fZTFykG5dwM3GiZfgwjpBlhiCaF2aZCa2HVCuJEZSqNbOWVMRMq724iKiWaJ8S+7PTqTGQeXUVACCVEDNdbkUsLcYXtZ0/D2aZicdFrK5q25TV1OxNapnhTcxYGgBM1ofScKGkrIfEDNHUtDvb0e5sB6AUzzOKUrVmWMxMq6M+MRPpUsTMiH1c4wnKW2a63d0AgJWNFV0KDLrdMlpbFUGzsKDtY0ZKVwEW19Zyiv41O7xlM1lKKcsMZzEzzEREqdnWQWKGaHoGvErMyeSqcXEzmQDg3FozzBpUr5hZ8SliZjs0WmaYmPEUd3d1ODtgF5SYHr2sM11diphZWtL2MSN7vZDtypzEUEiXOTUC/GzQuVihrdQhGySbydLBObkWVkFihmh6htrS6dkGWmaya81kWyJYzEy9YibUrqxhSK5TzJTIZhIEIeNqiukjZjo76xMzEARInZ0AAHFpSZc5NRLkZkLJDZo3ywzpCeshMUM0PWakZ5eqNaOXmFloHQYADCQ0tmWoEDMDAF0uRcwsxBa0jZFH3WIGgOT3A9hklhnO3ExciJlSlhkSM+rgwiZXUiRmiKbHDDcTUDyjKZpU3Eweu/ZsJgCYcyuWmb51jWKmgpsJyMTNLMT1FTOLi3UUztuMYoYCgAsGL7VN8+ZmotRs6yAxQzQ9anq2gW4mABgYKKw1wwKAvU5tBfMYJx1bAQAdiUUIUQ1ZWRUCgIEsMaOTZabemBkAm9vNxMkmxUVCEecBwFy4mTgRdlZBYoZoeljMjNFVgFlG0/R0ETdTnanZiyk/wugAANimNIiyKsQMczMtxfURDuRm0gYv1gYGD+0MSooZTq4VF5YZTq6FVZCYIZoeZpmZjc5iPbVu2DjMMlNMzNRTNA8A1tYEnIBindEkZljMTIkAYCBTa0bvmJnFRRIztcCrm8nSwUsVzeMMK9oZUG8mBRIzRNPT6eqEy6Z0izbSOlPMMqNXanY0KmACShCwbVrDGqqJmXFx6GYiMWM5PMTMNIqbydLBScwQRHMjCIJaCdjIuJlilhk1ZkZjk0n1PBGxPstMNW4mnasAk5tJG/xmM3HUm4mPS6NCbibrITFDbAqGvOm4mVXjLDNMzKysiFhZUT5g9ErNznEz1WOZMTEAuLNTuR4UAFwbvFlmGFxaZjjZwC0RepnBlf85uRZWQWKG2BSw9GwjLTMejwy/P9c6o1dqdt1upnTMTDkx0+lShIPeAcCrqyLWNYYqbUrLDPiyzFhKhQ2aFzcTg1KzrYPEDLEpYG4mo2vN5LuaDLHM1Opm2thQ/qF80Tx/iyIcosmoLoHSHR0ybDbl0z0U0tifiVlmNpGY4Wx/tjRmpmQ7A+4sM8r/XARLb1JIzBCbApbRdHLtpLHjDLJaM3qLmayYmZkZIJGo+rXZdWnKBQC3O9thE5R5h+L1iwdRBPz++jKaVMvM6qoqyJod3txMXAYAUwXgQkjMEETzw9xMRteaYZaZkyf1t8zMog+SwwlBkmCbna36tcKaMgfZ6VT6LpQ6ThDQ0aLUsgmvh+uaL4OJGa2WGbmjA7KovFYM6zOnRoEXNxMXRfPy4EXo5UNuJusgMUNsCpiYCa4FkZJSho2zZUvGMiPLsq5iRoaI9d4tAGpzNYlMzJRxMTGYqym0ro9bp+6MJlGE5PMpP26SIGBeXCcMHiwzcoNYZqwcnHozEcQmoM/TB1EQkZASmI/NGzZOptaMHRvSBpJyEkB9YkaWFTEDAMkBxV1Wi5hhlhmpjIuJ4XelxYwObiagfssMsPmCgPlzM1k4j4bJZlL+p9Rs6yAxQ2wK7KId/Z5+AMa6mrIDgJlVBqgvmykeF9QNRR5MW2ZqyGgSLLTM6CJmNlkQMG/ZTDxYZhqlaB6JGesgMUNsGsyIm2GWmdlZEeGoUtvFZXPBLtrLvawsq6usN44MbE1bZmoRMywtu0wrA4avxQcACMfDtU2yBLpaZjaZm4kfy4zyP09iJvM0Hxu4lXoi3wW3WSExQ2wamJgxMqOpq0tCS4sMSRLw+5NhABnXjVZYvInPJyE1VLubiYkAJgrKobqZdLPM1JeaDQAyuZm4gCcxw2vMDBcuuU0KiRli02CGZUYUgUBAsc4cO6lsvqwbtVZYWnNXl4TUltrdTKqY6ao8D9XNxFPMzCarAkztDIoMngcJvSKDk5ghiM2BWenZzNV0Yt4AMTOYZZmp8sNLFTNpUVAO5mbiKmaGLDOWwkXtFM57MzEoZsY6SMwQmwaza81MhxURwRo4aoW5mbItM2I8XrWlQlxUGkdWZZlJu5l4qTMDbL4AYBXONmwurA/sV86ymSwt20xiBgCgPSpRB/bu3Yv5+dw02csvvxwf/OAH1d8XFhZw77334pVXXoHT6cTFF1+Ma665Bna7pVMnGhCzxcxcZAnozPQ80sriolKAr7NTAlpakOrthW1uDrbp6aoESk1ixiA3UzhMAcC1wptlhksxw13MzGYbnB8sVwRXXnkl3va2t6m/u1wu9WdJknDXXXehvb0dd9xxB1ZXV3HPPfcAAK677jrT50o0NkzMhNZDiCai8Djqa/5YisFBpbbMYlwREfWLGUUIsAJ0qYEBRcxMTSFx9tkVX1+LmPG5fAD0dzMtLwtIpQCbrfZzbDo3E2ebkqW9mUrFzAh8WWZIT1iP5W4mt9sNn8+n/ssWMy+99BKmpqZw0003Yfv27Tj77LNxzTXX4Mknn0Q0q98MQVRDu7MdbY42AMZaZ4aHFcvMSkoREXrGzABAamgIAGCbmKjq9VosM+H1sC4bhc+nzFmWBSwvU7PJaqCYmSKDl0rNJssMtTNIY7mY+eEPf4jrrrsOf/mXf4lHHnkEyWRSfe7o0aMYHh5GZ1bg4jnnnINEIoHR0VErpks0OGa4mpiYiYsLAPQXM8mtSsNJ+4kTVb3eVoOYYVakhJTIKfqnFYcDaGtjLQ20fegyy4ywvAykjGtFwQv8ZjNZN3hBOwNyMxWyyc1ClrqZ/uiP/ggjIyNobW3FsWPH8N3vfhdzc3P48z//cwBAOBxGR0dHzmu8Xi/sdjvCZZrOJRIJJLK6CguCALfbrf6sJ+x8vHzw6E2zrW/AO4DXQq/h5NpJCIJgyPoCAQkOh4yEOy1mPF11nZ8Fz3Z1SRAEAalt2wAoYqbSeYVoFEI8DgCQu7srHu9xeOCyuRBPxRHeCKOtpU3zvBl+v4TVVRHhsA2CINX8elZnRpBliMvLkPNEWbO9R9kGLQqiYe/R2lDGFUXBsDmUWqOQOSDnOVFQ/iZkWebivosic3sVv0+G3sOs3kxWXQvr36MGiJkDBw7g4YcfLnvMXXfdhR07dmD37t3qY1u3bkVrayu++MUv4oMf/CDa2pQP0WIXp9Ib+ODBgzlz2L59O/bt24eenp5al1M1/f39hp2bB5plfTt7d+LJySexjGUEAgH1cb3Xt20b8HuPEtx++tDpCHQHyr+gDMy7ctppXQgEALz+9QCAlqmpnDUUZXxc+b+lBX07dlT19brT04mTqydh89oqn78KenuBiQlAELqh+XQ+HxAOo99uR6mTNMt71GZXAou6u7oNfY9Wi8Oh/N/Z6dd+/6qkYI2TkwAAu92ecy2mZcWyKtpEXd6j9RKLsZ/Kz8eQe5j+ou7r6IDP4mth5d+g7mLmne98Jy6++OKyx5QSFbt27QIAzMzMoK2tDT6fD8eOHcs5JhKJIJVKFVhsstmzZ0+OUGLCZ35+PseNpQeCIKC/vx8zMzPcBKPpSbOtzy8q3/KPzBxBMBg0bH2BQQ9+71oBAKRWUwgmgprOI0nAwkI/AAGSNItgUILY1oY+APL4OGYmJjK7TREcr76KbgDo6cHM7GxVa+xwdOAkTuL307/HFmGLpnln4/X6Abhw/HgYwWCs4vHF6PH5YA+HsfDaa0jk/e0323uUWZWXlpYQbDHuPVot6+tdAJwIhZYQDK4bMkapNTrm59ENIClJmA9m/oYWFxTXaSqVQjCo7W9LT+bnbQB6IcsSgsHZgueNvIf+9XW4oHgyYhZdCyPXZ7fbqzJE6C5m2tvb0d7erum1Y2NjAAB/2qy8a9cuPPLIIwiFQupjhw4dgsPhwMjISMnzOBwOOEp8wBv1YSDLclN8kJaiWda3xatszlORqZz16L2+3m1zAABBtqHd2a753OGwgFRKEeN+fwqyDKR6eyG7XBDicYhTU6rbqRhCOl4GPT1Vr1EtnBcP6XJNWEbT0pKg+XyS3w+Mj0MMlZ5Ts7xH1TgQGYa+R6ueT1bMjNHj569RlqSc5wqOBy/3PB3bI5e/RkbcQzWeSJIsvxZW/g1aFgB89OhRPPbYYxgfH8fc3Bx+/vOf4+tf/zrOP/98dHd3A1CCfQcHB/GVr3wFY2Nj+N3vfof9+/fjrW99KzweY9JqieZmoNWcWjP+wRkAgDPZpfr3tcCCf9vaJLS0pB8URSSHhwFUDgIWs8RMtfDc0kDYBBlN/AYAW9jOoEQAMCfxv1nTsyJ/nYfoY+uxLADYbrfjueeew8MPP4xEIoGenh689a1vxeWXX64eI4oibrnlFtx777247bbb4HQ6cckll+BDH/qQVdMmGpzBNqUdwMnISSSlJBy20i6aenD1BIElQIj21nWeuTklfoJlMjFSW7fCcfQobOPjwKWXlny9bU6xEKG3+nno3WyS1cfRo6WBbRMVzuMlNZsLKDW78uCbHMvEzMjICO68886Kx3V3d+PTn/60CTMiNgP9nn44RSc2pA0E14IYbh82ZByp4ziwBKTmd9R1nhMnlD/RbdtyY72SLKMp7ZothY0FAO+ofh6qZYan/kybqNkkLxs0g4fU7FK9max2q2TIuJlMhywzADioM0MQZmITbap15sRKdXVatLDWotRBSszu1FxfBQDGxxXLzLZtufVVkqecAgCwHz9e9vV2JmbSx1eDapnh0M20GcSMCidfuK3cI0tdAqozUwQSMwSxudjaphSdm1ydNGyMybW0xWTpFBw/rt0AOjZWwjLDxExetl8+Ng1ihgUA69dsUvmQ1cPNtKliZjhRMzxaZngTMwwSM9ZBYobYdDDX0olV4ywz4yvjyg9Lp2B0VLuYGR8vIWZ27gQA2CYns4tc5BKLwX7ypPJzLZYZjgOAN0PMDG/tDBhciRnO4kR4asK5WSExQ2w6htsUMTOxWl1vo1pJSamM1acOMSPLwIkTiptp+/ZcN5PU2QnJ54Mgy7CXaO1hTxcck9rbgSpaGTD0DgDOFjNavzxuJjcTv9lM1g1esp0BJ9YILgKAObkWVkFihth0MDfTxIoxYia4FsSGtAEbHMDKoGY30+KiiEhEhCDIGBrKK/YoCBVdTczFlNq6taadSH83kyJmNjYERKP19WfaFGKGM8sMD2KGdzcTD2KmVIfxzYKlvZkIwgqYm+lI6Ag+8dNPwOPx6NqFfSGm9GTqdWxFULbh+eed+N//21fzecJh5UNqy5ZUpsZMFomdO+H89a/h/drX4Hr66YLnmchJbtuGWhLQmZtpeX0ZKSkFm2iree7ZeDwynE4ZGxsCQiERra21N4tU68ywZpO2+ubEM6qY4cYyw/ruWDJ4haf52MB5EDOb3TJDYobYdGxr34YWWwuiySgeOvqQYeOc0X0aZkUZS0s2PPSQ9iKPp51WvAVH4qyzAADOl16C86WXSr4+efrpNY3nc/kAKJvq8say2klbK4KgWGdmZ20IhUQMDmoQMz5lTqzZJBM3zQgFAFcenAk9/iwz5l+kfBfcZoXEDLHpaHW04jvv/A5+M/cbQADa29qxsrqiazVRu2jHu0fejSMPLOHwYe2F+Ww2Gbt3x4s+F73qKsBmg7iyUvL1Umsr4ldcgVp6XztEB7wOLyKJCELxUN1iBsgVM5pwOCC1t0NcWYG4tNTUYoZBYiaLUhWAOYELPUGWGYLYfLxpy5vwpi1vgiAICAQCCAaDhpist7x5HW9+szHN+eB2I1pFNWwt7oouVxciiQiW4kvYgfoK/wHZQcDaP/Wlzk5VzDQzvFgbCuGonQGzzHC4gcuyyeKG3EwAKACYIIgidLoVy8difFGX8+mSns2CgJu81gx/MTPK/zy5mXiDC6sViRmCIIhcul1Ks1cWzFwvrD/TwoL2wF01PXtBnzlxC9u/OXGlcFEIrkGymQALrheJGQAkZgiCKEKXS6lLo5dlpqdHETPz89o/clLpzt/i/Lwuc+IVOaNmuMIK60PJdgbcuZky87BsStxcC2sgMUMQRAHdbsUysxjTS8woGUwLC3W4mdJixtbsYoaymaoenCwz4N4FZxYkZgiCKIBlMOllmentVSwzc3N1uJl6ewFsHssMiZnSg5ObqcTgmxgSMwRBFMAsM3rFzHR312+Z2WxuJgoARkllwJubyVIxY/nAfEBihiCIAvSOmclYZuroz5S2zNjm5nSZE6+Qm6nIHMgyU3Hwzd7OgMQMQRAF6B8zo4iZeFxEJKJtV0x1K3NqdssMgx8xw0E7A86L5lkKZTMBIDFDEEQRutyKZWYpvgRJluo+n8cjo7W1vowmNWZmbQ2Cjr20eIMXawODCzcT50XzeLDMkJghCILIgwUAJ+UklteXdTlnJj1bWxCw7PVCcrkANLd1RnUzUcxMw1hmrBQzMokZACRmCIIoQoutBe3OdgB6xs0oQcCaa80IQsY608RxM7xlM1lKA6Zmm14giMQMABIzBEGUQE3P1ilupru7/sJ5m6XWDMCPZSYD9WYqBRdupk0OiRmCIIrS41aEw1xMHyuIHrVmUpvBMsPJBs3gIZupFDxaZig12xpIzBAEUZT+1n4AwMzajC7nY1WAZ2frKJzHLDOzs7rMiUd4czNZKWaECjEz/Ag/C9sZkJsJAIkZgiBK0O9Ji5moPmJmYEARMydP1mGZ2bIFAGCbntZlTjxCAcBFBs9DdTNxYpnJhiwz1kBihiCIogRaAwCA4FpQl/MNDipiZmqqDjEzOAigycUMWWYKaaBsps01OD+QmCEIoih6u5myLTOSxtI1qpiZmtJlTjxDlpnSg/NmmeEiAJgsMwRBEIXobZkJBFIQBBnr6wIWF7V99CQHBgAAtmAQSCZ1mRdv8LJBM3gQM/ntDDJP83GteBAz1M6AIAiiCEzMzKzN6LJpOBxAX59iktHqapL6+iDb7RBSqaYNAuavNxO/7Qx4EX48iJnNDokZgiCK0ufpAwBsSBtYii/pck4WNzM9rTFuxmbLBAE3qauJ15gZSwdvoJgZCgC2BhIzBEEUxWlzqg0ng1G9goAV11BdQcDM1dSsYoazbCYGV5aZrN95cDVxYZnh4DpYid3qCRAEwS/9nn4sxBbwfPB5SFqjdrNwbPUAgVb87FgcPc/FNJ3jbS1enA5g4t+fxKsxGwQAbW3tWF1d4cTpUBteWwc6nX3q7+dMSUjIwNxjx5ByrkIQgLDvJMLhkCn7ldcrIRDI3OuzE53YAhvajy3BIaeMGVQQgJMnYV9YQHJkBHJrq/J4FZYZGXKBpWZ1YxVjy2PGzLUIKQlAQBH8yxsedKIj5/loVMALLwALC3bd7+Hpiza0ApidFXHskCPnuW1bE/DPH4NodGPW9P0T7Xak0rWgzIbEDEEQJQm0BvDy4sv4zHOf0eeEfgAfBX4K4KcvazvFX8vAZwGc8+8/xDn//kN95sURv1B/+lMLZ5Hhx+yH/2n8WD0Aktu2Ye6ZZ5QNskKdmWJspDbwh9/7Q93qI1XNR5X/npv9Krb3v1t9WJaBd76zG8eOAcoK9eUf4cH/AvCvD7px24O55//Fn/0DTvvWzbqPWQr3Lbcg8j9NeKMUgcQMQRAl+cBpH8Dvw7/Hempdl/OlUgJCS6LyTVYjD29PYM8rS/Cv128psh4JEGQI6x0QE20AgJRXcZ+J0QAEKe2OE2BKayRJVjZfr1dGe5tyfWdmlVT6nm4JDodxk7DZbMDUFOzj4xAXFyF1d1f1OlmWc3o7Tq5OYiY6AwGCWl7ADILpYpBO0ZXzeDgs4NgxZasNBPS3bHmWAUSBttYUAu255+87/ksAgNTenrF2GYTNZoPs9Ro6RjlIzBAEUZK3b3073r717VZPo5A7Mz8KgoBAIIBgMMhF/EQtfO75z+FfDv0Lrj/rfbj9otsBADvu24aElMCv3v8otni3mLq+r/6zF3fe2Y4/eXsUX/5yGABw3rl9mJ+34T8fnMMZZxiTDs/WmNqyBbZgELapqVwxU8HNlM1URBGDu/y78NQVTxky32IMDCiB6X947QyAjNCemlK22d5e4IUX5nS/h+2fiQL3Adf9WQTvuyU3w6/rikkAwPLf/i1ie/boOm427P5Fg0HLYncoAJggCMIiBrxKMPPJyMmC56wIAB4YUMTK5GQmQNvMOjNqcPeksgmX6s2UTb6YmVidAAAMtQ0ZMMPK5O/lLNh92zaDBixzbWwnlfcVywBsZkjMEARBWAQTM9ORTHsGK61LmZYTGaO9qWJmSBEgarsKDdlMk6uKEBpuGzZolsURhHSBvxJiZutWU6cDSJJSXBIZkdjMkJghCIKwiC1e5Rvz9FqWmLGwzszQEOtsLiKRSM/HTDGTbldhT1tmqs1myoZZZga9gwbNsjilMqSZlcswMVNiYHFhAcLGBmRRRKqvr8gLmwtDY2YeeeQRvPjiixgfH4fdbsf9999fcMzCwgLuvfdevPLKK3A6nbj44otxzTXXwG7PTG1iYgL33Xcfjh07Bq/Xi8suuwzvfe97uavDQBAEUQsDrco35oXYAuLJOFx2V0bMWPD51t0toaVFaTkRDNowPJwyNQQiySwzeWImv51BOcvM1KoSM2O2ZYaRf71YgUizxQyzbkl9fUr57SbHUMtMMpnEhRdeiLe/vXgAoSRJuOuuu7C+vo477rgDH/vYx/D888/jgQceUI+JRqP4m7/5G/j9ftx111247rrr8G//9m947LHHjJw6QRCE4fhafHDb3QAyPbCsbGcgisCWLcW7m5tpmanoZipzbdSYmXZzY2ZKXR+zYmbyezOxa7gZXEyAwWLmyiuvxO7duzE8XFwhv/TSS5iamsJNN92E7du34+yzz8Y111yDJ598EtF0kZ9nnnkGiUQCe/fuxfDwMC644ALs2bMHjz32WMNlLhAEQWQjCEJB3IzV7QwycTPKJmxmbyZVzExOKkKmRjfTWmINi/FFAMCQ1xoxUxgzo3gZrLLMJDeJmLE0Nfvo0aMYHh5GZ2en+tg555yDRCKB0dFRnHXWWTh69CjOOOMMOLLMZOeccw6++93vYn5+Hr29vQXnTSQSSDCHL5QPDLfbrf6sJ+x8zeryovU1Ps2+xkZf34B3AMfCx3By7WTOGkRRhCAIpq8v0z/LnjOmIBg3B3ZeKS1mxLU1iOFwRrJkXQdAuTaZF2dezwRhh7MDPpfPkLmWIjO9zFwjEQHhsDLXrVuVSsCGDSzLOdfIns5kkrZsMfy9w8PfoKViJhwOo6Mjt+yz1+uF3W5HOBxWj+nJK4/MXhMOh4uKmYMHD+Lhhx9Wf9++fTv27dtXcB496e83rziTFdD6Gp9mX2Ojru+UnlPw9NTTWBVWc9bQ39ePntbMZ5ZZ69u1S/l/dbUNgUCb+nhfXy8CAWPH7t++HejsBJaW0A8A6c96l8uFQNbgkY1I5jV9/Wh1KgXhXo4qZaUHOwZzjjcDto/39vap1+m115T/29vZPwPuYZtyj7xeL7zZa15SmsN6Tz8993EDsfJvsGYxc+DAgRyhUIy77roLO3bsqOp8xZScnKcwa1V7e/bswe7duwtePz8/j2RS36JPgiCgv78fMzMzTen2ovU1Ps2+xkZfn1tWrMYTCxM4GczUm5mdm0XSlTR9fQ6HB0AHpqdjCAbDkKQ+ACLm5+fQ3m5Mb6bsNXb7fLAvLWHxyBHYwmH4AMTX1xEKZpqdRhOZXkPBmSBaHYqYeXXqVQBAp7MTwaA+zVGrRRD6AQiYmZmF3a4UzXvlFSeALvT0JAHYDbmHbZEIvAAikQhWs9bcNTkJJ4CQy4W4wdfCyPeo3W6vyhBRs5h55zvfiYsvvrjsMdVaQHw+H44pDStUIpEIUqmUan3x+XyqlYaxvLysPlcMh8OR45bKxqgPA1mWG/KDtFpofY1Ps6+xUdfnb/EDAJbiS7nzl3M/r8xaX2enIlgWF8X0mJkJGT2+LMtIdXXBPjoKYXGxYP3FkCRJfW52TamA2+vuNf29kB26wsaem1Me7O1NAbAbcg/VTK+s6wAA4vw8ACDV3W3atbDyb7BmMdPe3o729nZdBt+1axceeeQRhEIh+P3KH/ShQ4fgcDgwMjKiHvPggw8imUyq6dovvfQS/H6/oW4jgiAIM2BiJhQPcSHG/H7FqhAKKbEeZtaZAQApHUMpLi1BZl9Kq6wAPBtTxEyfx7q6Ktm3cG5OCaLu6TGwj1ipOjNZYmYzYGg208LCAsbHx7GwsABJkjA+Po7x8XHE43EASiDv4OAgvvKVr2BsbAy/+93vsH//frz1rW+Fx+MBAFxyySWw2+245557MDExgV/+8pc4ePAgdu/e3bABfwRBEAy/Ky1m1kM5G7NV2UydncrGu7RkvZgp1c6g1LWZi84BAHo9hbGUxlMoROfnlWvY22tCU9QsMSPEYhDX1gAA0ib50m9oAPBDDz2Ep59+Wv39k5/8JADgs5/9LM4880yIoohbbrkF9957L2677TY4nU5ccskl+NCHPqS+xuPx4LbbbsN9992HW265Ba2trdi9e3dOTAxBEESjkmOZyRYzFn1Zy7bMZGdHm4UqZhYXMxtxuaJ5WdfMSjFTzECSscwYE2uUM3AWzCoju1yQ29oKnm9GDBUze/fuxd69e8se093djU9/+tNljxkeHsbtt9+u59QIgiC4IMcyI/NgmVHmkEgIiERyU7PNQBUzoVDpCsDZdWayrtlsVHEz9XvMz6opJmZMscwUGTjHxbRJPBjUm4kgCMJCmGVmZWMFSSmTbWmVZcbtluF2Z1xNpruZ0vGT4tJSVT6uRrDMmCJmsrAtLADYPC4mgMQMQRCEpXS0ZGpthdZD6s9WWWaAjKvJEjGTFTNTS9fsyEYE0aSSsm1FAHBxMaNssYa6mRhFLDPSJgn+BUjMEARBWIpdtKPDqQiaUJwPMcOCgJWMJvPaGQBVipki7QyYi8nr8MLj8Jgw01zyxUwyqaS3A+ZYZoRibiayzBAEQRBmweJmluJL6mNWZmtmZzSZbpnp6gKQFjMlKCb05mJWZjIVihmlTo8AUZTR1WVuzIyNWWZIzBAEQRBmkV04j8GDZSZbzBRLPTYC1TITjUJIl/Goxs00H1U28B43Hxs4C/7t6pJgs1U4uB7KBQCTmCEIgiDMIjujiQestMzIbW2Q0wVSxcXFoscUE3rs2nW6OgueM4N8TbGwoCiY7m5ja8zIxcQMCwCmmBmCIAjCLHwtPgD8uJnya80o8zFpcEHIqTVTbPBidWbYtbNazLAYI1ZBmQlDwwfOFjNpFx1z2W0GSMwQBEFYTLGYGSvJrwJsNmp6dihtqSqXmp3exJllhrnsrIJpCnbtDBcz+QMjc93YddwMkJghCIKwGN5iZtra0unOEcF8ywwA2esFAIirqxUHZ5YZlgnGhKHZCEK6wJ/ZYib/2sgyxHRzZhIzBEEQhGm0OZWS86sbq+pjVrqZvF5lR15dtcDNBEBKixmhjJhhYo8fMaP8ny9mmMvOtHmsrEBIKXVtSMwQBEEQpuF1KJv3aiJLzFhomfF6lQ14bY0Py0x+OwNlPmkxI+fFzLTwEQBsVcyM6mLyeICWFmPH5ggSMwRBEBbT6mgFoFSxZfBgmVHcTOYWzQMyYqYmy8y6tZaZfEx3M+WLmU1klQFIzBAEQVgOs8xEEllixkLLTGursgFHIpktwgo3kxiJlDwm//rwks1kWcwMiRmCIAjCSngTM9mWGYYllpkSRfOUhzJupo3UhnrtrMpmstrNJOSJGZnEDEEQBGEmxdxMVsKymSTJGjEjtbXlPlAhm4m5mERBzGncaSbZYkaWyTJjNiRmCIIgLIZZZpJyUn3MypgZj0dWU40zmNPOAADk1taKx2Rbrlgmk6/FB1GwZlvL1hTRqICNDeUBs1OzScwQBEEQluB1egses9LNJAhAa6t54iUfuQrLTLabyep4GWU+mZ+ZVcblkuB2m3QdyTJDEARBWAlzM2VjpWUGyMTNMEx1M+VbZipkM/FS/RcAZFnIqjFjvJDJ781EYoYgCIKwhBZbCxyiw+pp5MBqzTBMDQCuJWaGE8tMNqa2MiAxA4DEDEEQBBdkW2esdDExrLTMsGymcoNnW67U6r8WWmayNYUl1X/TYkYgMUMQBEFYBQsCBqx3MQEWu5mqETNZbiYeLDPZvZlMS8tWBs75lSwzBEEQhGXkiBkuLDMWupnyxUy5Y7NjZiys/pttmbFEzJCbiSAIgrAa3txM+dlMVlpmKvVm4sMyg/R8THYzZV+b9XWI0SgAEjMEQRCEBWRbZnjASjcTXC7INlvZwXnLZipmmTE7Zkat/muzQW5vN29sDiAxQxAEwQGtzizLDAcxM21t1rmZIAi5GU3lxIwsqwHAvFhmrHIzqS4mn8/kG2Y9JGYIgiA4gLeYGSuL5gF5tWbKuZmQETO8dcw2080kZIuZTeZiAkjMEARBcAFlM+VSUGsmDyb4UlIKyxvLAPizzJgaM0NihiAIgrAa3gKA87OZzOzNBOT1ZypjmWHxMgIEdDitaTKpzEf5XxEzJvVlQm4FYBIzBEEQhKVQAHAuUoWYGQbLZOpo6YBNtJU8zixiMQHxuLWWGZnEDEEQBGEF5GbKRfZ4qhp8Mb4IwPq+TGyKzMXkcMimxx2RZYYgCIKwFN7cTB6PhdlMyBMzRWDXiIcaM0Dm+iwuKtahzk7J3GtGbiaCIAjCanizzFhZNA+oPmZGtcxYnMnE2hmY3pcp69qQmCEIgiAsxeMob4kwG4/H4piZSmImbZnhocZMNpaJGbLMEARBEFaTLWZ4cDNZbpnJcjOVa2ewGOMrZsZKMSNkF83bZJCYIQiC4ACPnS8xk2+ZMZtKAcBqzMw6XzEzZJmxBhIzBEEQHJATAMxBzIzLxY9lpprUbOtjZpT/rRIzgiRBDIcBkJghCIIgLKLV3lr5IBMR83YHSwOAi1CQzdTCl2XGlL5MWQMLKysQJGXMzShm7Eae/JFHHsGLL76I8fFx2O123H///QXHXHnllQWPXX/99Xj729+u/j4xMYH77rsPx44dg9frxWWXXYb3vve9XHx7IQiC0IPsmJn11LqFM8kgijIkKb1ZcmaZYZ//sWQMwCZ2M6URF5XYIcnrBVpaTB2bBwwVM8lkEhdeeCF27dqFp556quRxN954I84991z1d0/WmzgajeJv/uZvcOaZZ+Kuu+5CMBjEP//zP6OlpQXvfve7jZw+QRCEabjtbvVnXsSM2y1jbc2aL41SlTEzDF7cTImE8oPZbiZVzHR1mTMuZxgqZpjV5ac//WnZ4zweD3wloq+feeYZJBIJ7N27Fw6HA8PDwwgGg3jsscewe/duss4QBNEUiAJ/Xn+PR8bamjVjV3Iz5cdIW22ZyccsNxPL9LKx4N9Ovq6DWRgqZqrlm9/8Jr72ta+ht7cXb37zm/G2t70NYtphe/ToUZxxxhlwOBzq8eeccw6++93vYn5+Hr29vQXnSyQSSCQS6u+CIMDtdqs/6wk7X7OKKlpf49Psa2zW9eWvy4r1ZWc0GTl+0TVmixlRLBi/mGXGyvdA/tCdnbIp9zD/nFJXl+nXgYe/QcvFzFVXXYU/+IM/gNPpxO9+9zvs378fq6ureO973wsACIfD6OnpyXlNR0eH+lwxMXPw4EE8/PDD6u/bt2/Hvn37Cs6jJ/39/YadmwdofY1Ps6+x2dYXCARyfrdifdm9HvPnYwQ5a4zH1R+9Xi+8eePbbZnty+fyYWhgyPD5lSPr+zYA4PTTe5FvJDHkHuYF+7oGB025V8Ww8m+wZjFz4MCBHKFQjLvuugs7duyo6nxMtADAtm3bAAAPP/xwzuO1qr09e/Zg9+7dBa+fn59HMpms6VyVEAQB/f39mJmZgSxbW5fBCGh9jU+zr7GZ1icKIiRZcU8Eg0EA1q7P6ewC4MyZjxEUW6MYiaAv/XwkEsFq3vipVEr92ef0GTq/akgmuwEoikYUZcRiM2BTMvIeupeX4cv6PeJ2F1wrozFyfXa7vSpDRM1i5p3vfCcuvvjissfUYwHZuXMnYrEYwuEwfD4ffD4fwuncecby8jIAlIyzcTgcOW6pbIz6MJBlueE/SMtB62t8mn2NzbA+j92DSCICoPCzyor1ud2Z8cwYO3uN2QHAQixWMH72l1y/y2/5vWe9mQDA55MgCDLyp2TEPcw/m9TZadm1sPJvsGYx097ejvb2diPmAgAYHx+Hw+FAa9pfumvXLjz44INIJpOw25XpvvTSS/D7/Ya6jQiCIMzGbXerYoYHrKwCLLtc6s9CLFbwfHbMjNWtDIDcmBmz07KzSVE2k/4sLCwgEolgYWEBkiRhfHwcgOJXc7lc+PWvf41wOIxdu3bB6XTilVdewYMPPoi3ve1tqmXlkksuwfe+9z3cc8892LNnD2ZmZnDw4EFcccUVTRfwRxDE5ia7pQEPeDzWbcrZ6kCIRgufzhIzPGQy5YoZE0VgfgAwZTPpz0MPPYSnn35a/f2Tn/wkAOCzn/0szjzzTNjtdjzxxBN44IEHIMsyent7cdVVV+Ed73iH+hqPx4PbbrsN9913H2655Ra0trZi9+7dOTExBEEQzUB2rRkeyHYzWUlRy4zAr2WmszNV+kAjBwaJGUPYu3cv9u7dW/L5c889N6dYXimGh4dx++236zgzgiAI/nA7+BIzVjebZFRyM/FgmcnGUsvMJnUz8VeliSAIYpPCn5uJEzFTzM2UFwBsNZbFzJCYAUBihiAIght4EzP5nbOtopiYyabHbX0ySK6byRoxIzsckL1e88bmCBIzBEEQnJDdbJIHeLbMZMODmMmmp8e8mBk5S8xIXV3mdwTlBBIzBEEQnMCbZYZnMZMdM9PrKawEbzbZGqKvz5ossFSTVcGuBRIzBEEQnMBbNhM3YqZIAHB2PZ5ud7eZ0ylKtpjp7TUxmymLVJH2PpsFEjMEQRCcQJaZXFJ9SkODxOteV/DcfGxe/ZkHEZjdKcdUy0y2m6mvr8yBzY3ljSYJgiAIBR425WzOP38DAGC3WyNqFg4ehOc738Ha9ddbMn4tLCxkbANWZTOlSMwQBEEQVrO1favVU8ihp0fCr341A6/XGjGT2roVq7feasnYtTI/b1N/NjUGN9sys4ljZkjMEARBcMJ7Rt6D387/Fuf3nW/1VFS2bLGwpUEVdLn4qKuysWFRFhFZZgCQmCEIguAGm2jD7RdRtfNa4C0t23RIzACgAGCCIAiigeEhkykbv9/kTKasyOPN7GYiMUMQBEE0LLxZZnp7zXXL2eYzWV2S3/q2DlZBYoYgCIJoWM7qPsvqKeTQ02OumBHn5rJ+2bxb+uZdOUEQBNGwfPsd38Z1Z16Hj5z1EaunAgD4n/9zFaIo4zOfWTZ13OTOnaaOxysUAEwQBEE0HG8bfhveNvw2q6ehcsstq/jEJ1bhcpk7bmzPHgjr69h44xvNHZgzSMwQBEEQhA6YLWQAADYboh/8oAUD8wW5mQiCIAiCaGhIzBAEQRAE0dCQmCEIgiAIoqEhMUMQBEEQRENDYoYgCIIgiIaGxAxBEARBEA0NiRmCIAiCIBoaEjMEQRAEQTQ0JGYIgiAIgmhoSMwQBEEQBNHQkJghCIIgCKKhITFDEARBEERDQ2KGIAiCIIiGZlN1zbbbjVuukefmAVpf49Psa6T1NT7NvkZan3HnFGRZlnUfnSAIgiAIwiTIzVQnsVgMn/rUpxCLxayeiiHQ+hqfZl8jra/xafY10vqMh8RMnciyjLGxMTSrgYvW1/g0+xppfY1Ps6+R1mc8JGYIgiAIgmhoSMwQBEEQBNHQkJipE4fDgSuuuAIOh8PqqRgCra/xafY10voan2ZfI63PeCibiSAIgiCIhoYsMwRBEARBNDQkZgiCIAiCaGhIzBAEQRAE0dCQmCEIgiAIoqFp7kYRBvPjH/8Yjz76KMLhMAYHB3Httdfi9NNPt3paNXPgwAE8/PDDOY91dHTgG9/4BgClINL3vvc9PPnkk4hEIti5cyc+8pGPYGhoyIrpVuTw4cN49NFHMTY2hlAohJtvvhlvfOMb1eerWU8ikcD+/fvx7LPPYmNjA2eddRauv/56dHV1WbGkAiqt8Z577sHTTz+d85qdO3fizjvvVH/neY0HDx7EL3/5S0xPT8PpdGLXrl340z/9U2zZskU9ppHvYzXra+R7+MQTT+CJJ57A/Pw8AGBwcBBXXHEFzjvvPACNfe8YldbYyPevGAcPHsSDDz6Id73rXbj22msB8HUfKZtJIz//+c/x5S9/Gddffz1OPfVU/OQnP8GTTz6Ju+++G93d3VZPryYOHDiA559/Hrfddpv6mCiKaG9vBwD84Ac/wMGDB3HjjTciEAjgkUcewauvvoovfelLcLvdVk27JL/5zW9w5MgRbN++Hf/wD/9QsNFXs55vfOMbeOGFF3DjjTeira0NDzzwACKRCPbt2wdRtN6gWWmN99xzD5aXl3HjjTeqj9ntdni9XvV3ntd455134uKLL8aOHTuQSqXwr//6r5iYmMAXv/hFuFwuAI19H6tZXyPfw1//+tcQRRH9/f0AgKeffhqPPvoovvCFL2BoaKih7x2j0hob+f7lc+zYMdx9993weDw488wzVTHD1X2UCU3ccsst8te//vWcxz7+8Y/L//f//l+LZqSdhx56SL755puLPidJknzDDTfIBw8eVB/b2NiQP/zhD8tPPPGESTPUzvve9z75+eefV3+vZj1ra2vy1VdfLT/77LPqMYuLi/KVV14p/+Y3vzFr6lWTv0ZZluWvfOUr8r59+0q+ptHWuLy8LL/vfe+TX3nlFVmWm+8+5q9PlpvvHl577bXyk08+2XT3Lhu2RllunvsXi8Xk//W//pf80ksvyZ/97Gflb33rW7Is8/c3yI/0ayCSySRGR0dxzjnn5Dx+9tln48iRIxbNqj5mZmbw0Y9+FHv37sWXvvQlzM7OAgDm5uYQDodz1upwOHDGGWc05FqrWc/o6ChSqRTOPvts9ZjOzk4MDw/j6NGjps9ZK4cPH8b111+Pj33sY/jqV7+K5eVl9blGW2M0GgUA9Vtts93H/PUxmuEeSpKEZ599Fuvr69i1a1fT3TugcI2MZrh/9957L84777yceQL8/Q1SzIwGVlZWIEkSOjo6ch7v6OhAOBy2ZlJ1sHPnTuzduxdbtmxBOBzGI488gr/6q7/CF7/4RXU9xda6sLBgwWzro5r1hMPhAnMwO6ZR7u95552Hiy66CN3d3Zibm8NDDz2EO+64A5///OfhcDgaao2yLOPb3/42TjvtNAwPDwNorvtYbH1A49/DiYkJ3HrrrUgkEnC5XLj55psxODiobnTNcO9KrRFo/PsHAM8++yzGxsZw1113FTzH298giZk6EAShqsd4hwWsAcDw8DB27dqFm266CU8//TR27twJoHBdcoOHWmlZTyOt+U1vepP68/DwMHbs2IEbb7wRL774Ii644IKSr+Nxjffddx8mJiZwxx13FDzXDPex1Poa/R5u2bIFf/d3f4e1tTU8//zzuOeee3D77berzzfDvSu1xsHBwYa/fwsLC7j//vtx6623wul0ljyOl/tIbiYNtLe3QxTFAmW5vLxcoFIbEZfLheHhYQSDQfh8PgAoWOvKykpDrrWa9fh8PiSTSUQikYJj2OsbDb/fj56eHgSDQQCNs8ZvfvObeOGFF/DZz342J/uhWe5jqfUVo9Huod1uR39/P3bs2IEPfOAD2LZtGx5//PGmuXdA6TUWo9Hu3+joKJaXl/HpT38aV199Na6++mocPnwY//7v/46rr75avVe83EcSMxqw2+0YGRnBoUOHch4/dOgQTj31VItmpR+JRALT09Pw+/3o7e2Fz+fLWWsymcThw4cbcq3VrGdkZAQ2my3nmFAohImJiRx/eCOxurqKxcVF+P1+APyvUZZl3HfffXj++efxmc98Br29vTnPN/p9rLS+YjTaPcxHlmUkEomGv3flYGssRqPdvz/4gz/A3//93+MLX/iC+m/Hjh245JJL8IUvfAF9fX1c3UdyM2lk9+7d+PKXv4yRkRHs2rULP/nJT7CwsIDLLrvM6qnVzAMPPIDzzz8f3d3dWF5exve//33EYjFceumlEAQB73rXu3Dw4EEEAgH09/fj4MGDaGlpwSWXXGL11IsSj8cxMzOj/j43N4fx8XF4vV50d3dXXI/H48Fb3vIW7N+/H21tbfB6vdi/fz+Gh4cLguCsotwavV4vDhw4gAsvvBA+nw/z8/N48MEH0dbWpqZv877G++67D8888ww++clPwu12q9/+PB4PnE5nVe9LntdYaX3xeLyh7+F3v/tdnHfeeejq6kI8Hsezzz6LV155BbfeemvD3ztGuTU2+v0DALfbnRPDBQAtLS1oa2tTH+fpPlKdmTpgRfNCoRCGhobw4Q9/GGeccYbV06qZL33pS3j11VexsrKC9vZ27Ny5E1dffbUayCanCyP95Cc/wdraGk455RR85CMfKXij88Irr7yS45tnXHrppdi7d29V69nY2MB3vvMdPPPMMzmFnnipIVRujTfccAP+7u/+DmNjY1hbW4Pf78eZZ56Jq666Kmf+PK/xyiuvLPr4jTfeiD/8wz8EUN37ktc1VlrfxsZGQ9/Df/mXf8HLL7+MUCgEj8eDrVu34vLLL1c3sEa+d4xya2z0+1eKv/7rv8a2bdsKiubxcB9JzBAEQRAE0dBQzAxBEARBEA0NiRmCIAiCIBoaEjMEQRAEQTQ0JGYIgiAIgmhoSMwQBEEQBNHQkJghCIIgCKKhITFDEARBEERDQ2KGIAiCIIiGhsQMQRAEQRANDYkZgiAIgiAaGhIzBEEQBEE0NCRmCIIgCIJoaP5/T4TbPiFbdiwAAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.degrees(track[2, :]), \"b-\")\n",
    "plt.plot(np.degrees(track_lower[2, :]), \"g-\")\n",
    "plt.plot(np.degrees(track_upper[2, :]), \"r-\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "probably smarter to to save this in a file and load it in a notebook, so I dont have to carry over the code..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:29:05.534206Z",
     "start_time": "2024-10-23T09:29:05.527716Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"tracks/test.npy\", \"wb\") as f:\n",
    "    np.save(f, track)\n",
    "    np.save(f, track_lower)\n",
    "    np.save(f, track_upper)\n",
    "\n",
    "with open(\"tracks/test.npy\", \"rb\") as f:\n",
    "    a = np.load(f)\n",
    "    b = np.load(f)\n",
    "    c = np.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:29:06.705696Z",
     "start_time": "2024-10-23T09:29:06.699962Z"
    }
   },
   "outputs": [],
   "source": [
    "# matches perfectly!\n",
    "# plt.plot(np.degrees(a[2,:]),\"b-\")\n",
    "# plt.plot(np.degrees(b[2,:]),\"g-\")\n",
    "# plt.plot(np.degrees(c[2,:]),\"r-\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-10-23T09:29:07.582893Z",
     "start_time": "2024-10-23T09:29:07.568518Z"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "language": "python",
   "display_name": "Python 3 (ipykernel)"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}