{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a2f07f51-25b6-4ddf-942e-2ff98bf19781",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "78420221-7a8d-48ab-806a-84021b506641",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1280x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting Figure 7\n",
    "\n",
    "path = './'\n",
    "\n",
    "# structure function file names\n",
    "names = [\n",
    "    \n",
    "    ['SF.mex.Yg.09.10.2021', 'Oct 9$^{th}$', 'k', '-'],\n",
    "    ['SF.mex.Yg.10.10.2021', 'Oct 10$^{th}$', 'k', '-'],\n",
    "    ['SF.mex.Yg.11.10.2021', 'Oct 11$^{th}$', 'k', '-'],\n",
    "    \n",
    "        ]\n",
    "\n",
    "v = 400 # velocity scaling factor (km/s)\n",
    "trunc = 8000 # truncation scale (samples)\n",
    "\n",
    "plt.figure(figsize=(16, 8), dpi=80)\n",
    "\n",
    "for name in names:\n",
    "    \n",
    "    ls = name[3]\n",
    "    color = name[2]\n",
    "    label = name[1]\n",
    "    name = name[0]\n",
    "\n",
    "    df = pd.read_csv(path + name, delimiter = ' ', index_col=None, usecols=None).values # import data\n",
    "    df = pd.DataFrame(df) # convert to a dataframe\n",
    "\n",
    "    plt.loglog(df[0][1:trunc]*v,df[1][1:trunc], color=color, label = name, ls=ls) # plot on loglog plot\n",
    "    plt.fill_between(df[0][1:trunc]*v, df[1][1:trunc]-df[2][1:trunc], df[1][1:trunc]+df[2][1:trunc], alpha = 0.4, color='grey') # add uncertainty fill\n",
    "    \n",
    "    plt.annotate(label, (df[0][8000]*v +3000,df[1][8000] -10), fontsize=15) # add epoch annotations\n",
    "\n",
    "# add plot axes\n",
    "plt.xlabel('Scale (Km)', fontsize=18)\n",
    "plt.ylabel('D(s)', fontsize=18)\n",
    "plt.xticks(fontsize=18)\n",
    "plt.yticks(fontsize=18)\n",
    "\n",
    "# set figure limit sizes for manuscript\n",
    "plt.xlim([8,2*10**5])\n",
    "plt.ylim([10**-2,10**6])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c785595b-3d52-4bca-a30b-ec54f65fd511",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hs9l47LHHePjhhwFIS0tD0zQ0Tbvo1h29Xk9CQsIl1/v2229TVlbG73//e/z8/DCZTLhcru+cZ7PZOHz4MJmZmUDzBKOoqChPo1NoDkYGDRp0ycf0Jqn4EEIIIYQQQohLUEqxefNmXnvtNd577z1mzpzpeZP5n//8hxEjRhAZGenjVQpvMRgM/OMf/2D+/Pncd999PPzww7z77rusWrWqRUHBpeTm5pKamkpWVtZ5j48bN47U1FTWrFnjua64uJgRI0ZQW1vL/fffT79+/SgqKuK9997DbDYzZ84cDh06xLJly3j++eeJiYkB8MqUoE8++YSwsDCKioqYNWsWhw4dwmg0snDhQp5//nmCgoIAaGhoAJoDEKPRSH5+/lkhR0NDA0VFRfTv3/+q13Q5JPgQQgghhBBCiAuor6/nX//6Fy+99BL79u0D4JprruGaa64hPDyctLS0VusBIXzvpptuYv/+/Tz44IN89dVXHD9+nJiYGPz9r/ytdF1dHcXFxcycOfOi5w0aNIhVq1bR0NBAaGgojzzyCKWlpWzbto1hw4Z5zlu6dClKKQYNGsTQoUNZtmwZs2bNIjU19YrXeK7Dhw/jcDiYOXMmixcv5sknn2Tjxo28+OKL1NbWsmzZMgCio6OZP38+3bt3Z8CAAUyePPms4CM/P58+ffoQGBjotbW1hAQfQgghhBBCCHEBW7Zs4Yc//CEhISHMnz+f2bNnc+ONN7aocaToHIxGI//6178oKyujsLCQb7/9lhUrVrBw4cIr6v3hrooIDQ296Hnu4/X19RiNRlasWEFOTs5ZoYdba2+pamxsxGw28+CDD3qmuMyZMwebzcYrr7zC0qVL6d27NwBvvvkmb7755nnvZ/To0ezZs6dV13o+0uNDCCGEEEIIIWguz//Pf/7D+PHj+eCDD/j666+JjY3ld7/7HZs3b+af//wnc+fOldCji4qPj2fo0KEUFRXx+9//nkGDBrFkyRKsVutl3Y870HAHIBdyZkBSUVFBfX29p3dGWwsODgZg/vz5Z11/++23A7B169Y2X9PlkOBDCCGEEEII0aUVFhby29/+lh49enDbbbexdetW8vLyAEhPT+d//ud/GDx48FVtbxCdg6ZpzJgxg7Vr15KYmMhjjz1G//79+eyzz1p8H+Hh4SQmJrJ79+6Lnrd79266detGWFjY1S77qiUlJQHN4c+Z3E1La2pq2nxNl0OCDy/TNG2upmnvNjU1+XopQgghhBBCiEt49dVXSU1N5Xe/+x2apvHDH/6QTz75hN///vdce+21REdH+3qJoh2aMmUKBw8e5Kc//SlFRUVcf/31LF26tMW3z87O5vjx42zZsuW8xzdv3syJEyfIzs4GmhuUhoWFkZ+ff9H7ba0tL9deey3QPFXmTMXFxZ71tWcSfHiZUmq5UmqeuxRICCGEEEII0X6YzWZef/11rFYrJSUlhIeHM2LECJ577jm2bt3KCy+8wLhx49q8+aLoeAIDA3nuuefYtWsX48ePJyMjg507d+JwOC45+vbhhx8mODiYBx54gKqqqrOOVVdX8+CDD2IwGDyTg/z8/Jg1axa5ubns2LHjO/enlAKa+5EA1NbWeuEZ/p958+YB8Prrr591/d/+9jf8/f2ZMGGCVx/P26RWSwghhBBCCNHpFRQU8Je//IXXXnuN6upqioqKmD59Or169eKjjz66ZKNJIS6kX79+bNy40dP89KmnnvKMlL3xxhvPe5vevXvz5ptvcscddzBw4EAWL15MWloaJ06c4PXXX6eyspJly5bRs2dPz22eeOIJ1q9fz/jx47n//vvJyMigpKSE5cuXs2XLFiIiIjyVGb/+9a+57bbbCAgIICcnxxOInM+f//xnamtrPdUbubm5FBYWAvCjH/2I8PBwhgwZwj333MPf//53HA4H48ePZ+PGjSxfvpxHHnnEsxWmvdLcyZDwruTkZOX+yyKEEEIIIYTwje3bt/Pss8/y3//+F6fTSUpKCrfddhu33nor11xzjfTtEF7lcrn4+c9/zl/+8hdsNhv33Xcfr7766gXP37Nnj2c0bGVlJdHR0UycOJFf/epX521keurUKX7zm9+wbt066uvr6datG1OnTuW5557zVCk9/vjjvPzyy5SUlOByuTh+/PhFR9umpqZy8uTJ8x4787Z2u50nnniCN954g+LiYnr06MEPfvADHnrooRb//rQWTdOKlFLJFzwuwUfrkOBDCCGEEEII31BKeXod/OIXv+CZZ55hxIgR3H777dx8880kJ1/w/ZEQXnHo0CF+9rOfcdNNN5GTk3PR4EFcPQk+fESCDyGEEEIIIdpWRUUFr776Km+88QZvv/02Op2O2tpaqqqqmDp1qmxnEW3ObDYTEBBAQECAr5fSqV0q+JC6LiGEEEIIIUSHtmfPHv70pz/x1ltvYbVaiY+PZ+/evYwYMYJx48bJm07hMwaDwddLEEjwIYQQQgghhOjAvv/97/PXv/4VgEGDBjF//nzmzp1Lenp6q432FEJ0LBJ8CCGEEEIIITqMxsZGPv30U2bMmEFBQQHx8fFMmTKF2267jRkzZhAZGenrJQoh2hnp8dFKpMeHEEIIIYQQ3lNYWMiLL77IK6+8Ql1dHe+99x6pqalomkb//v0JCgry9RKFED4iPT6ukKZpjwGPnnN1mVIqwQfLEUIIIYQQokvauXMnzz33HO+88w4Oh8MzQrN3794MGDAAnU7n6yUKIdo5CT4u7iAw4YzvnT5ahxBCCCGEEF3Sww8/zKeffsqwYcO44447uPnmm0lJSfH1soQQHYhsdbmA0xUftyilMq/k9rLVRQghhBBCiMvT1NTEW2+9xSeffMLTTz9NZWUlhw4dwuVyMX36dCIiIny9RCFEO9Rpt7pomnYLMB4YDFwDhAL/VkotuMhtkoGlwBQgGigBVgBLlFI157lJuqZpxYAV2Ab8Sil1zItPQwghhBBCiC6vvLycl156iZdeeomKigpCQkK44447SE5OZvbs2dK/QwhxVTps8AH8D82BRyNQCPS72MmapvUE8oA4YCVwABgB/ASYomnadUqpqjNusg1YdPq8uNOPl6dp2oBzzhNCCCGEEEJcoR//+Me8+uqrWK1WkpKS+P/+v/+P+fPnM3jwYOnfIYTwio4cfPyU5sDjCM2VHxsucf5LNAcYP1ZKvei+UtO0507f1++BB93XK6XWnXljTdO+BI4BdwHPeWH9QgghhBBCdDlKKQoLC0lJSaG2tpaCggJ69+7NggULuPXWW+nRoweapvl6mUKITqRT9PjQNG0CzcHHebe6nK72OAKcAHoqpVxnHAulecuLBsQppUwXeZwNwAGl1PcutSbp8SGEEEIIIcT/sdlsvPPOOzz33HOUlJSwYsUKAgMDsVqt9OvXj6ioKF8vUQjRQXXaHh+XaeLpr+vPDD0AlFINmqZ9AUwGRgGfnu8ONE0Lonk7zaUqS4QQQgghhBCn1dbW8vLLL/Piiy9SXFxMcHAwM2bMwGq1cs0112AwGHy9RCFEJ9dVgo++p78eusDxwzQHH304HXxomvYskAuconmLzG8AI/Dm+e5A07SfAT9zfx8eHu6NdQshhBBCCNFhuVwuhg0bxtGjR4mNjeWHP/wht912GyNGjCAgIMDXyxNCdBFdJfhwpxB1Fzjuvj7ijOuSgWVADFABfAmMUkqdPN8dKKWe44zeH8nJyR1/D5EQQgghhBCXKT8/n127djFnzhz279/P7bffjk6n49Zbb6VPnz74+fn5eolCiC6mqwQfl00pdZuv1yCEEEIIIURHoJRi8+bNPP3006xZswa9Xk9ycjKhoaF873vfIzEx0ddLFEJ0YV0l+HBXdFxo/4n7+tqrfSBN0+YCc6U5kxBCCCGE6OxcLhcrVqzg6aefZtu2bWiaxqRJk7jzzju55ppriIyM9PUSxUW4XC7sdjt2ux2Hw+G5OJ3Os37tcrlwD8XQNA0/Pz90Oh3+/v7fuQQEBBAYGIi/f1d5qyk6gq7yt/Hg6a99LnC89+mvF+oB0mJKqeXActnqIoQQQgghOjulFI888ggnTpxgzpw5LFiwgJtuukkalrYTLpcLi8WC1WrFarVisVgwmUw0NTVhsViw2Wy4XK7v3E4p5Qk43KOF3V/dAYhS6ju31TTNc9uAgACCg4MJCQkhJCSE4OBgz0W2O4m21lWCD/cklsmapvmdZ5ztdYCZ5j4eQgghhBBCiPOoqanhr3/9K0ePHuXnP/85ZrOZ3/72tyQlJTF27FhpWOojTqcTi8VCU1MTZrOZhoYG6uvraWpq+k444a7M0Ol0hISEoNPpvL4el8uF0+nEarXS2NiI0+n0HNPpdISFhREZGUlYWBihoaHo9Xqvr0GIM3WJ4EMpdVTTtPU0T275AfDiGYeX0Dyt5RWllOlqH0u2ugghhBBCiM7m1KlT/PGPf+TVV1/FZDKRmJjIXXfdRUJCAvPnz5dP8NuQ3W7HbDZ7Ao7a2loaGxvPCjjcW05aK9i4FD8/P/z8/DxVH2dyOByYzWZqamo814WEhBAXF0dERARhYWGyTUZ4neYuVepoNE2bBcw6/W0CcBNwDNh8+rpKpdTPzzi/J5BH82jalcB+YCQwkeYtLmOUUlXeWl9ycrIqLCz01t0JIYQQQgjR5hwOB/fccw/Lli3D4XDQu3dv7rzzTubPn096erpn+4NoHXa7HZPJhNlspq6ujtraWsxms2e7iU6n8/TU8EXA4Q0ul8uzFUcphU6nIzo62hOEBAUF+XqJogPQNK1IKZV8weMdOPh4DHj0IqecVEqlnnObFGApMAWIBkqAD4AlSqma79zDVZDgQwghhBBCdERKKaqqqoiJiaGmpobs7Gzsdjt33nknc+fOJT4+3tdL7JScTqcn5KitraW2thaTyYRSCqUU/v7+BAYGEhgY2KkrbBwOB01NTdjtdvz8/AgPDycxMZGoqKjvVI8I4dZpg4/26oytLnOrqrxWQCKEEEIIIUSrcjqdfPDBBzz99NOYzWb+8Y9/oGkaFouFzMxMwsMvNCBRXC6lFE1NTZhMJurr66murqahoQGn04mmaeh0ui4RclyKy+WiqakJq9WKpmlERERICCLO61LBh2ye8jKZ6iKEEEIIIToSi8XCP/7xD5599lmOHj2KXq8nJycHq9XKkCFDZEKLFzgcDkwmE42NjVRXV1NTU+N5M69pGoGBgT7rx9Ge+fn5YTQaMRqNuFwuzGYz+/btkxBEXDap+GglstVFCCGEEEK0dzabjT59+nDy5EnCw8OZN28et912G2PHjiUwMNDXy+uwbDYbDQ0NNDQ0UFVVRV1dnaeaw9/fH71eT0BAgPRIuUIXqgSJjo6WniBdlFR8CCGEEEIIITzKyso4ePAgo0eP5tChQ0yePJnQ0FBuv/12Bg8eLFUHV8BqtXomrFRWVtLY2Agg1Ryt5EKVIH5+fkRFRZGUlERUVJSMVxYeUvHhZdLjQwghhBBCtEfHjh3j2Wef5e9//zshISGsWrUKvV5PZGQkaWlpUn1wGS4WdOj1evR6fZfuzeEr7hDEZrPh7+9PXFwc8fHxREZGSvDUyUlzUx+RrS5CCCGEEKI92L17N0899RTvvPMOLpeL/v37c/fdd3PrrbeSkpLi6+V1CHa73RN0VFRU0NDQADQHHUFBQV2+CWl75HA4MJvNOBwOAgICSEhIID4+nvDwcPmz6oQk+PARCT6EEEIIIYSv2e12kpOTKS8vZ+TIkdx9993Mnj2buLg4Xy+tXXM6nTQ2NlJXV0dFRQV1dXW4XC6p6Oig7HY7ZrMZp9NJcHAwKSkpxMXFSVPUTkSCDx+R4EMIIYQQQrQ1l8vF2rVrOXr0KLfddhuFhYVs3LiR+Ph4cnJyZCTtBbjHy9bX11NRUUFVVRV2u/2soEO2SnQOFouFpqYmNE0jPj6e5ORkwsPDZatXByfBh49I8CGEEEIIIdqKw+HgnXfe4amnniI/Px+j0ciHH35IcHAwGRkZMpL2PBwOB/X19dTU1FBWVobZbEYpRUBAAEFBQdIYs5NzV/U4nU6ioqJITU0lKipKApAOSoKPNibNTYUQQgghRFtxOBy88sorPPvss5w4cYLg4GBuvvlmFixYwIQJE9Dr9b5eYrtiNpupq6ujvLycqqoqXC4XAMHBwej1ennT2wUppTCZTFitVmJiYujZs6dURnVAEnz4iFR8CCGEEEKI1ma328nMzKSsrIz58+ezcOFCRowYgb+/v6+X1i64XC7q6+uprq6mvLycxsZGlFIEBgYSFBQkv0/CQylFQ0MDDoeD7t27k5aWRmBgoK+XJVpIgg8fkeBDCCGEEEJ4W0lJCc8//zynTp3il7/8JU6nkxMnTtC7d28yMzOl4SbNYZC7KWl5eTk2m80zfSUoKEiqOi7AYrFgMpmwWCxYrVbPxWKxeH4PNU1Dp9OhaRoBAQEYjUZCQkIIDQ3FaDR2iiDJ6XRSV1dHcHAw/fv3JyoqytdLEi1wqeCj4//NFEIIIYQQopM7cuQIzzzzDP/4xz+w2Wykp6fT0NBAjx49GDp0aJd/M2+xWKitraWsrIyqqiqcTic6nY7g4GBCQkJ8vTyfMJvNVFRUeC7u7T0NDQ3U1dVRX1/vuTQ0NGC1Wq/6McPCwoiJiTnrEhcXR2pqKj169CA+Pr7dh3M6nY6oqCjMZjNff/01aWlppKWlSXPbDk6CDyGEEEIIIdoph8PBwoULeffdd3G5XAwcOJBFixZx2223kZSU5Ovl+ZTZbKa6uprS0lLPuNnAwEBCQkK6xJtUi8VCYWEhRUVFFBYWen5dUlJCeXk5JpPpgrfV6XSEh4cTGhpKUlISoaGhhIWFERISQlBQkGeSzZkXaK6GUErhdDqx2+00NjZiMplobGyksbGR6upqKisr2bt373kfX6/X07NnTzIzM8nMzGTgwIEkJye3y+DOYDCg1+s5duwYdXV1DBgwgKCgIF8vS1wh2erSSmSrixBCCCGEuBJKKaqrq4mOjqa6uppZs2bhdDq56667uPnmm4mOjvb1En3C3YSyurqakpIS6uvr0TSNwMBAgoOD230lwZWw2+0UFBRw4sQJTpw4wcmTJz1BR2Vl5XfODwwMJDExkbi4OGJjYz2XuLg44uLiiI6OJjw8nODg4FYPG5qamqisrKSkpISTJ09y8uRJjh8/zsGDB6mtrfWcFx0dzYgRIzyX+Pj4Vl3X5VJKUVdXR2BgIAMHDiQiIsLXSxLnIT0+2phMdRFCCCGEEFfC5XKxevVqnnzySWpra/nXv/6FpmnYbDYyMzMJDQ319RLbnDvsqKqqoqSkhMbGRoBO16+joaHBE24cP37c8+uioiKcTudZ54aHh5OcnExycjLdunU769exsbHtPgBSSlFUVER+fj579uzh66+/5siRI57jqampjBo1irFjx3Lttde2m7HCZrMZm81GRkZGl6+2ao8k+PARqfgQQgghhBAtYbfbWbZsGU899RT79u0jICCAnJwcfvrTn3LttdcSHBzs6yW2qc4cdlgsFo4fP87hw4c5cuQIR44c4ejRo5z7galOpyMlJYXU1FTS0tLo0aMHqamppKamdsqeJZWVlezYsYNt27bx1VdfUVZWBoDRaGTUqFFkZWUxduxYn1db2Gw2GhoaSE9PJz09vd2HTF2JBB8+IsGHEEIIIYS4FIfDQWZmJgcPHsRoNHLzzTezYMECxo8f3+VGabq3sRQVFXX4sMPlclFcXOwJN9xBR0FBAS6Xy3NeUFAQ6enpngaa7nAjOTm5U0xIuRJKKY4ePcqmTZvYvHkz+fn5KKXw8/Nj4MCBZGVlkZWVRXp6uk/+XjidTmpra0lKSqJfv35d9s+pvZHgw0ck+BBCCCGEEOdTU1PDvn37GDVqFAcPHuT5558nMDCQhQsXMmzYsC71RqqpqclT2VFXVwd0vLDDZrNx9OhRDhw4wIEDBzh06BBHjhyhqanJc46maaSkpNCrVy969epF79696dWrF926dZOqgUuorq5my5YtbN68mS+//NLz+9qtWzfGjh1LVlYWQ4cObdOg0OVyUVtbS2RkJJmZmdL09BKUUoSGhnL06NFW6+EiwYePSPAhhBBCCCHOVFRUxPPPP88rr7xCYGAgq1atIigoiPDw8C5VNm+1Wqmurqa4uJiamhqUUgQFBbVJw82rZbFYOHz4sCfkOHDgAEePHsXhcHjOiYiI8AQb7pAjPT1d3hx7gc1m4+uvv2bz5s1s3ryZkpISoHkCy8iRIxk3bhyjR48mJiam1dfibnoaFBTEoEGDumQPngtxBx3Hjh0jLi6OY8eOMWzYMKqrq1vtMSX48BEJPoQQQgghBMChQ4d45pln+Oc//4nNZqNnz54sWrSI+fPn+6xcv63Z7XZqamooKSmhsrISl8uFXq9v19NYmpqazgo4Dhw4wPHjx8/aqhIXF0ffvn3p168f/fr1IyMjg9jY2C7xZ+pr7i0xW7ZsYdOmTezZswf3e9u0tDRGjBjB8OHDGTZsWKv2RWlsbMTlcpGZmUlsbGyrPU5HcuzYMUaNGkV5eTkAq1at4qmnnuKLL75otceU4MNHJPgQQgghhBAOh4Pu3btTUlLCoEGDuPvuu5k7dy7dunXz9dJanbsXQllZGWVlZTgcDgICAjAYDOh0Ol8v7yxOp5Pjx4+Tn5/P3r17yc/P5+jRo2eFHImJiZ6Aw33pqqOF26Pa2lq++OILvvrqK7Zv3+550+3n50dGRgYjR47kuuuuIzMz0+t//ywWC2azmZ49e5Kamtpuw7y2sH//foYMGYLT6USv15ORkcHs2bPZtWsXBoOBFStWkJSURG5uLj179vTa40rw4SMSfAghhBBCdD1KKTZt2sTevXuZP38+x44d49NPPyUqKopZs2a1SQm+LymlqK+vp6KiguLiYqxWKzqdDqPR2K56l1RUVJCfn+8JOvbt24fZbPYcj42NJTMzkwEDBpCRkUHfvn19PlFEtJxSipMnT3pCkB07dtDQ0ABAWFgYo0eP5oYbbmDMmDHo9XqvPKbD4aCuro6EhAT69evX4p4je/fu5cknn2TDhg1UVlYSHR3NxIkT+dWvfsWAAQMuex15eXmsX7+ehx56qEV/ZxsbG3nmmWc8E3Vqamp44403WLRo0Vnnbdy4kYkTJ573PrZu3cqoUaM83z/55JOUlJTwwgsvAHD77bezadMmli9fzogRI5g/fz69e/fm97///WU/vwu5VPDRfn76dBKaps0F5kZFRfl6KUIIIYQQoo0opVi7di1PPPEEeXl5BAUFMWDAAEJCQnjggQcIDw/39RJblclkorKyksLCQsxmM35+fhgMBoxGo6+XhtPp5PDhw+zcuZNdu3aRn5/vGZcKEBwcTEZGBpmZmZ5LXFycD1csrpamaZ4JOfPmzcPpdLJv3z6++OILvvjiCz766CM++ugjjEYj48aNY8qUKYwaNeqqKkH8/f2JioqivLychoYGBgwYcMng4f3332f+/PlERUWxePFi0tLSOHHiBK+//jrvvfce77zzDrNnz76sdeTl5bFkyRIWLVrUouCjsrKSpUuX0r17d6655ho2btx40fN//OMfM3z48LOu69Wr11nf7969m0mTJnm+z8/P5/HHH2f06NEA9O7dm7YuwJDgw8uUUsuB5cnJyVJKI4QQQgjRyblcLpYvX84TTzzB7t27CQgIYPbs2dx1110MGzasXbzxby3uJqVFRUXU1tYCzSFCZGSkT3tcWCwW9u7dy65du9i1axe7d+/GZDIBzW+Ie/bsyejRoz0VHenp6e1u643wLp1Ox8CBAxk4cCAPPvggpaWlfPLJJ3z88cesW7eOdevWkZSUxOzZs5kxY8YVb2HSNI3IyEhMJhM7duwgNTWV7t27n7f64+jRoyxcuJD09HQ2bdp0Vn+Qn/zkJ2RlZbFw4UJ2795Nenr6FT/3S0lMTKSkpISEhAR27NjxnVDjXFlZWdxyyy0XPWf37t089NBDQHMlzMGDB5k2bZrn+N69e5kzZ85Vr/1ySPAhhBBCCCHEVViyZAnHjx/njjvu4I477mDixImddoKH0+mkpqaG0tJSysrKPE1Kw8PDfdbXwGKx8O2337Jjxw6+/vpr9u/fj91uByAwMJABAwYwePBghgwZwqBBg1q10aXoGBISEliwYAELFiygsLCQVatWsXLlSv7yl7/w6quvMmvWLO666y4SEhKu6P6NRiN6vZ4TJ05QUFDAkCFDvlN98cwzz2A2m3n11Ve/0xQ1JiaGV155hfHjx/P000/z8ssve44VFRXx29/+lnXr1lFVVUVSUhJTpkzhT3/6E0888QRLliwBmhu8uh0/fpzU1NTzrlWv11/282xoaCA4OPi829dsNhuHDx8mMzMTaG7uHBUVdVYV1e7du3nssccu6zGvlgQfQgghhBBCtJDJZOJvf/sbe/bs4f/9v/9HfX09jz76KAkJCYwZM4aAgABfL9HrlFI0NDRQXl7u6dvh7+9PaGioTyolHA4He/fuZfv27Wzfvp3du3d7gg6j0cjw4cMZMmQIQ4YMISMjw2s9HETnlJyczPe//33uv/9+Nm7cyFtvvcXy5ctZsWIFt9xyC4sXL76i/i7+/v5ERkZSVVWF2Wz+zn3k5uaSmppKVlbWeW8/btw4UlNTWbNmjee64uJiRowYQW1tLffffz/9+vWjqKiI9957D7PZzJw5czh06BDLli3j+eef9/QU8ua0mbvvvpvGxkZ0Oh1ZWVk888wzDBs2zHPc3UvFZrNhNBrJz89n0KBBZx0vKiqif//+XltTS0jwIYQQQgghxCXU1tby5z//mT/+8Y9UVVURHR3N7bffTmJiIrfcckun3CphtVo9fTvcb2aMRmObb99xuVwcPnzYE3Ts3LnT04g0KCiIYcOGMXz4cIYPH06fPn065Z+FaH3+/v7ccMMNXH/99WzdupWXX36ZZcuWkZuby6JFi7jtttuuqJLrfJVQdXV1FBcXM3PmzIvedtCgQaxatYqGhgZCQ0N55JFHKC0tZdu2bWeFDUuXLkUpxaBBgxg6dCjLli1j1qxZF6zyuBKBgYHcfPPNTJs2jZiYGPbt28ezzz5LVlYWeXl5DBkyBIDo6Gjmz59P9+7dGTBgAJMnTz4r+MjPz6dPnz4tbv7qLRJ8CCGEEEIIcQFKKX7961/z5z//mYaGBhITE/nlL3/JggULyMjI6HRjK10uFzU1NZSUlHi2sgQFBREREdGmfTtqamr48ssvycvL48svv6SmpgZofnM6cOBAhg0bxogRI8jMzOyUVTbCdzRNY8yYMYwePZqPP/6Yv/zlL/z5z39m+fLlfO9732PatGlX/e/eHSSGhoZe9Dz38fr6eoxGIytWrCAnJ+es0OPMdbemMWPGMGbMGM/3M2bM4JZbbmHQoEE88sgjfPjhh55jb775Jm+++eZ572f06NHs2bOnVdd6PhJ8CCGEEEIIcQ673U5AQABWq5UvvviCmJgYfv7zn3PHHXeQnp7u0+adrcFkMlFWVkZRUREWi6XNt7I4nU727t1LXl4eeXl57N+/3zP1oU+fPmRnZ3u2sAQHB7fJmkTXpmkakydPZsKECbz33nu8/vrrPPbYY7z99tv8+Mc/Pmt86+VyBxruAORCzgxIKioqqK+v9/TOaA969erFzJkzef/993E6ne262kqCDyGEEEIIIU47cOAAf/jDH9i5cyd/+9vf8PPz49FHH6Vv375069bN18vzKofDQVVVFYWFhZ6KCoPBQFRUVJs8fmVlJVu3biUvL49t27ZRX18PNL/Ju+GGGxg9ejSjR4/2an8CIS5XYGAgt99+Ozk5Obzxxhu88847/PCHP2TUqFH86Ec/om/fvpd9n+Hh4SQmJrJ79+6Lnrd79266detGWFgYTU1NV/oUWlVKSgo2mw2TyURYWJivl3NBEnwIIYQQQogu75tvvuGJJ57g/fffRynFtddeS319PYMGDepUb7zdjUrd1R12u53AwMA2mcricDjYvXu3p6rj0KFDnmP9+/f3bC8YMGDAeadFCOFLoaGh/PjHP2bevHn89a9/Ze3atWzbto0pU6awYMGCyw5AsrOzee2119iyZQtjx479zvHNmzdz4sQJHnjgAaC5QWlYWBj5+fkXvd+2rkY7duwYQUFB7X5akvxEEUIIIYQQXZZSiptvvpkPPvgAgKysLBYtWsTs2bOJjIz08eq8x2azeRqV1tfXo2kaRqPxkj0GrlZtbS1ffPEFW7ZsIS8vD5PJBEBERARTp05l9OjRjBo1qs2qTIS4WgkJCSxZsoQ77riDF198kXXr1rFu3TquvfZa5s+fz9ixY1sU3D388MO89dZbPPDAA2zatIno6GjPserqah588EEMBgMPP/ww0NwkddasWbz11lvs2LHjO30+lFKef9fQ/G/PmyoqKr4TAn/77besWrWKqVOntvt+R5p775zwDk3T5gJzo6Ki5lZVVfl6OUIIIYQQ4hxKKU6cOEFaWhrl5eU89NBDVFVVsWjRIrKzs1s9DGgrSinq6uooKSmhpKQEp9NJUFAQwcHBrfapsFKKo0ePsmXLFjZv3syePXtwuVxomsaAAQMYO3Yso0eP7pSNYUXXtH//fpYtW8b69etxOBzExMSQnZ1NTk4OPXr0oKamhv79+5OUlPSd2y5fvpw77riDmJgYFi9eTFpaGidOnOD111+nsrKSZcuWMWfOHM/5RUVFDBs2jPr6eu6//34yMjIoKSlh+fLlbNmyhYiICLZv386IESOYNm0at912GwEBAeTk5Fx0GtOf//xnamtrKS4u5q9//Stz5szxTGn50Y9+RHh4OJMmTSI4OJgxY8YQFxfHvn37ePXVVwkICGDr1q1kZGR4/zf3MmiaVqSUSr7gcQk+WkdycrIqLCz09TKEEEIIIcRpTqeT//73vzz55JOcOnWKVatWERQUhFKK/v37YzAYfL1Er7BarVRUVHjG0Pr5+RESEtJq20dsNhtff/01mzdvZsuWLRQXFwPN/UJGjRpFVlYW1113nVR1iE6tsrKSFStWsGrVKs+/gX79+jFw4EB++MMfMm7cuPPebs+ePTz55JNs3LiRyspKoqOjmThxIr/61a/O28j01KlT/OY3v2HdunXU19fTrVs3pk6dynPPPecZEfv444/z8ssvU1JSgsvl4vjx4xcdbZuamsrJkyfPe8x92xdeeIF///vfHDlyhPr6emJjY7n++ut59NFH6dWr12X+bnmfBB8+IsGHEEIIIUT7YLfbeeutt/jDH/7AoUOH0Ov1zJkzh/vuu4/Ro0cTFBTk6yVeNaWU5xPb0tJSXC4XwcHBBAUFtUp1R21tLZs2bWLz5s18+eWXnsaLSUlJZGVlkZWVxdChQz1vxIToKlwuF19//TWrVq0iLy+Puro6/vOf/zBv3jxfL61Tu1TwIT0+hBBCCCFEpzZ+/Hi2bt1KSEgI99xzD3fccQdjx47tFG/KLRYLFRUVFBQUYDKZ0Ol0rTaGtry8nI0bN7Jhwwa++eYbnE4nfn5+DBo0iLFjxzJu3DjS0tI63ahfIS6Hn58fw4cPZ/jw4bhcLnbu3Pmdfhyi7UnwIYQQQgghOhWz2cyXX37JhAkTOHLkCJMmTWLIkCEsWLCA4cOHd/iJIS6Xy1PdUVZW5qnuiIyM9HroUFBQwIYNG9iwYQN79uwBmsd7jhkzhkmTJpGVlUVERIRXH1OIzsLPz4/09PROUVXW0XXsn/pCCCGEEEKc1tDQwEsvvcT//u//Ultby8qVK4mLi2PBggX07t27Vaog2pK7uuPUqVOYzWb8/f29Xt3hbk762WefsWHDBg4fPgw09+uYPHkykyZNYvTo0RdtlCiEEO2NBB9CCCGEEKJDq6mp4YUXXuBPf/oTNTU1xMfH89Of/pTu3bt3+Okh51Z3KKUIDg72eqPQEydO8PHHH7N+/XqOHz8OQHh4ODNmzGDSpEkMHz4cvV7v1ccUQoi2IsGHEEIIIYTo0GbOnMnmzZvp1q0bP/jBD1iwYAF9+vTp0L0m2qK6o7i4mPXr17N+/XoOHToEQEREBDfffDM33ngjgwcP7vDbgoQQAiT4EEIIIYQQHUxxcTG5ubksWrSI/Px8br31Vm688UYWLFhAWlqar5d3xS40mcWb1R3l5eV88sknrF+/nvz8fABCQ0OZMWMGkydPZtiwYRJ2CCE6HfmpJoQQQgghOoSTJ0/y9NNP8/rrr2O1WgkLC6NPnz7Mnj2bpKQkXy/vilmtVk91R2tMZqmpqeHTTz9l/fr17Ny5E6UUBoOBqVOnMnnyZEaNGkVAQIBXHksIIdojCT5aQNO0R4AngL8opX7o6/UIIYQQQnQlR44c4cknn+Sf//wnDoeD/v37c++99zJx4kQSEhJ8vbwropSirq6O4uJiSkpKUEoRFBTktcks9fX1bNiwgfXr17Njxw6cTid6vZ5JkyYxefJkrrvuOpk0IYToMiT4uARN00YB9wO7fb0WIYQQQoiu6Kc//SmrV69m8ODB3HvvvcybN4/Y2FhfL+uK2Gw2KioqKCgooKGhwavVHWazmU2bNvHRRx+xdetWHA4H/v7+jBkzhptuuomsrCyZxiKE6JIk+LgITdPCgX8D9wCP+ng5QgghhBBdwq5du3jzzTf5zW9+w/Hjx1m4cCE5OTnMnTuXyMhIXy/vsimlqK+v91R3OJ1OgoODvVLd4XA42LZtGx9++CEbNmzAYrGg0+kYPnw4kydPZsKECYSFhXnpmQghRMfUYYMPTdNuAcYDg4FrgFDg30qpBRe5TTKwFJgCRAMlwApgiVKq5jw3eRV4Tym1QdM0CT6EEEIIIVrRtm3b+P3vf09ubi4AmZmZDB48mJtuuonw8HAfr+7y2e12T3VHfX09fn5+hISEXHXzUKUU+/btY926daxfv57q6moABg0axNSpU7nhhhs6ZEAkhBCtpcMGH8D/0Bx4NAKFQL+LnaxpWk8gD4gDVgIHgBHAT4ApmqZdp5SqOuP8+4BewAWDFCGEEEIIcfW2bNnC0qVL+fjjjwGYNGkS99xzDzNnziQkJMTHq7s8SikaGhooLS2lqKgIh8Phtd4dhYWFrFu3jnXr1nHq1CkAunfvzrx585gyZQrJycneeApCCNHpdOTg46c0Bx5HaK782HCJ81+iOfT4sVLqRfeVmqY9d/q+fg88ePq6vjQ3Mx2rlLJ7f+lCCCGEEMLtn//8J59++ilTp05l0aJFZGdnYzAYfL2sy+JwOKisrKSgoIC6ujo0TcNoNF71tJSamho+/vhj1q1bx549ewCIjo5m/vz5TJ06lYyMDK80QxVCiM5MU0r5eg1XTdO0CTQHH+fd6nK62uMIcALoqZRynXEslOYtLxoQp5QyaZq2CHgDcJ5xNzpAAS7AqJSyXmxNycnJqrCw8MqflBBCCCFEJ6SUYs2aNbz00ku88MIL1NXVUVVVhdls5qabbiI4ONjXS7wsZ1Z32O129Ho9BoPhqsIIi8XC559/zocffkheXp6nJ8iECROYNm0aw4cPv+rtMkKItlFTU0P//v079MjtjkDTtCKl1AXL3rrKT8yJp7+uPzP0AFBKNWia9gUwGRgFfEpz348d59zHG8BhmitBbK26WiGEEEKITsblcvH+++/z+OOP8+233xIYGMjHH3/MiBEjGD9+PHq93tdLbDGHw0FVVRWFhYXU1NR4qjtCQ0Ov+D6dTic7duxg3bp1fPbZZ5jNZnQ6HSNHjmTatGmMHz++w4VCQgjRXnSV4KPv6a+HLnD8MM3BRx/gU6VULVB75gmappmAaqVU/vnuQNO0nwE/c3/fERtwCSGEEEK0hpUrV/LII4+wf/9+9Ho9t99+O3fddRcTJkwgMDDQ18trMZPJRGlpKYWFhdhsNgIDA4mIiLji6g6lFAcPHmTdunV89NFHVFZWAjBgwACmTp3K5MmTiYqK8uZTEEK0sc6ww6Iz6CrBhzuFqLvAcff1EVf6AEqp54Dn3N8nJyfL33AhhBBCdFlKKTRNQynF9u3bOXnyJIsWLeLOO+9k7NixV937oq04nU6qq6spLCyksrLSU91xNU1Xi4uL+fDDD1m3bh3Hjx8HIDk5mfvuu48pU6bQo0cPby1fCOEjDoeDhoYG/Pz8OlRFW2fVVYKPq6aUmuDrNQghhBBCtHcWi4W///3v/PGPf+T111/HYDAwdepUpk6dysiRIztMb4qmpibKysooKCjAYrF4qjv8/Pyu6P4aGho8TUp37twJQEREBHPnzmXatGlkZmZKk1IhOgH3ZCeXy0VaWhrdunUjKCjI18vq8jrG/zxXz13RcaH9J+7ra6/2gTRNmwvMlbJEIYQQQnQlJpOJV155hWeffZaSkhIiIiLYvXs3kyZNYvDgweh0Ol8v8ZJcLhc1NTUUFRVRXl4OgMFguOLtJg6Hgy+//JI1a9bw+eefY7PZ0Ov1TJ48mWnTpjFq1KgOEwQJIS7N6XRSW1tLVFQU/fr163DjuDuzrvKT9uDpr30ucLz36a8X6gHSYkqp5cBy2eoihBBCiK7iX//6Fz/72c+orKwkJiaGn/3sZyxYsIBrrrnmiisk2pLFYqGiooJTp05hNpvx9/cnLCzsisOaQ4cOsXr1aj766COqqqoAGDp0KNnZ2UyaNEneDAnRCTkcDurq6ujRowe9evXqEGFvV9JVgo8Np79O1jTN7zzjbK8DzMCXvlicEEIIIURHYzKZMBqNOJ1Oqqqq8Pf355e//CULFiwgIyOj3QceSilqa2spLi6mtLQUl8t1VdUdlZWVfPjhh6xZs4bDhw8DkJKS4tnKIqMshei8nE4ndXV19OrVi7S0NNm21g51ieBDKXVU07T1NE9u+QHw4hmHlwBG4BWllOlqH0u2ugghhBCiM6uqquL555/nxRdf5K9//St9+/bluuuuY8OGDfTt27fdv+C32WxUVFRQUFBAQ0MDOp2O0NDQK/p01mq18vnnn7NmzRq+/PJLnE4noaGhzJkzh+zsbAYOHNjufz+8weVy4XQ6z/rqvnhjooW7Ue6l+Pn5odPpPBd/f/92H8CJjs/lclFbW0vPnj0l9GjHOmzwoWnaLGDW6W8TTn8drWnaP07/ulIp9fMzbvJ9IA94QdO064H9wEhgIs1bXH7tjXXJVhchhBBCdEbl5eX87//+Ly+99BKNjY306NGDhoYGoqOj6dGjR7t+se9uNlhSUkJxcTEOh4Pg4GAiIyMve91KKb799lvWrFnDxx9/TGNjIzqdjtGjR5OdnU1WVlanm+DgdDpxOBzY7XZPsHEmTdPQ6XTo9XoMBgN6vZ7AwEACAwPx9/dHp9N5Qgk/Pz80TfN8Pd/FfZ9nUkp5Lu5Qxb0up9OJ3W7HYrFgtVqxWCw0NTVhNpvPCl4CAgIICAggMDCwXf99FR2HUoqamhq6d+9Oenq6/L1qx7SOOldY07THgEcvcspJpVTqObdJAZYCU4BooAT4AFiilKrx5vqSk5NVYWGhN+9SCCGEEMIn3nzzTb73ve/R1NREeno6ixcv5vbbbyc1NdXXS7soh8NBZWUlBQUF1NbWotPpMBqNV9RQtKioiLVr17JmzRrcr/H69OnD9OnTmTJlCtHR0d5efptzOp3YbDZPwOHm5+dHUFAQRqMRo9GIwWDwBBvuMKE9Nmm12+2eIMRsNlNXV0d9fT1NTU1Ac7ii1+vR6/VSGSIumzv0iI+PJzMzU/4O+ZimaUVKqeQLHW9/P6FaSCn1GPDYZd6mALi7NdYjhBBCCNGZFBcXk5CQgM1mQ6fTkZKSwuLFi5k/fz4pKSm+Xt5FNTY2UlpaSmFhIXa7Hb1ef0XVHY2NjXzyySesXbuWb775BoDo6GgWLFjA9OnT6d279yXuoX1SSuFwOLDZbNhsNs/1fn5+hISEEB0dTVhYGEFBQZ5LR2zU6A5lzm0ma7VaaWxspK6ujsrKSurqmgdAappGcHCwVISIS3KHHrGxsfTv319Cjw6gw1Z8tFdn9PiY6+7iLYQQQgjRUZw8eZKnnnqK119/nd/97ndcf/31ACQmJrbrBp3uJquFhYVUVVWhaRohISEEBARc9v189dVXrF69mo0bN2K1WgkMDGT8+PFkZ2czcuTIdlndcDF2u/07IYe/vz/h4eFEREQQEhJCcHAwwcHBHTLguFo2m436+npqamooLy/3VIQEBgZ22NBHtB536BEXF8eAAQM63M+DzqrTVny0V9LjQwghhBAd0bFjx3jyySf5xz/+gcPhIDMzk8jISFJSUoiLi/P18i7IbDZ7qjvcIUVERMRlfwJ75MgR1qxZw7p166isrATgmmuuITs7mxtuuIHQ0NDWWL7XuberWK1WT38Ld8gRGRlJSEgIBoOB4OBgqWo4LTAwkJiYGGJiYujVqxcmk4m6ujrKysqoqanB5XIRGBjYZYMh8X9cLhc1NTUkJCQwYMAA+fvQgUjFRyuRHh9CCCGE6Cjefvtt7rzzTpxOJ4MHD+bee+9l3rx5xMbG+npp5+VyuaiurqawsNATUhiNRgIDAy/rfmpqajwjaA8cOABAUlIS06dPZ/r06SQnX/DDw3ZBKeXpY+FwOIDm7RqhoaFERUURFhaG0WgkODhYSvGvkNVqpba2ltLSUiorKz0hiMFgkN/TLkYpRXV1NUlJSWRkZEjo0c5IxYcQQgghhPiO/fv3k5KSglKKqKgohg8fzqJFi7jlllvabaPOpqYmysvLKSgooKmpiYCAAMLDwy/rDajNZmPz5s2sXr2avLw8nE4nRqORmTNnMn36dAYPHtxu39AqpbBarVitVs9klcDAQKKjo4mMjCQ0NPSKm7eK89Pr9cTHxxMfH4/VaqWmpobi4mKqq6tRSnmm2Ej1TOfm3t6SkJAgoUcHJRUfXiY9PoQQQgjRnu3Zs4fHH3+c5cuX8+Mf/5iFCxcCkJ6eTmRkpI9X910ul4va2lqKi4spKyvD5XJhNBove2TsgQMHyM3N5cMPP6Surg4/Pz9GjhzJ9OnTmTBhAkFBQa30DK6cy+XyBB3u1+wGg4GYmBjCw8M921bkTXfbM5vNnolBZrMZnU5HSEiIvCHupGpqaoiJiWHgwIHyZ9xOScVHG5MeH0IIIYRoj3bu3Mnvfvc7PvjgAwCuu+46hg4dSq9evQgPD/fx6r7LarVSUVHBqVOnMJlM+Pv7ExoaellvOmpqali3bh2rV6/m0KFDAKSmpnLnnXcybdq0dreVx+VyYbPZsFgsnqAjJCSEhIQETxPS9hjQdEUGg4Hu3buTkpLiCeZKS0vPqgIRnUN9fT0hISH0799fQo8OTCo+Won0+BBCCCFEe/HBBx8wZ84cAMaPH8/ixYuZOXMmYWFhPl7Z2ZRS1NXVUVJSQnFxMS6Xi+DgYIKCglpc1eBwOMjLyyM3N5fNmzfjcDgwGo3cdNNNzJgxgwEDBrSbCokzt644nU78/PwwGo3ExMQQERFBaGiovIHuQCwWC2VlZZw8eRKr1UpQUJA0ke3gmpqacDqdDBs2DKPR6OvliIuQig8hhBBCiC5o69atdO/enaCgIOLi4sjJyeG2224jJyen3U0osdlsVFRUUFBQQENDAzqd7rKrO44dO0Zubi5r1671jLMdPnw4M2bMaDdbWdzNSC0WCw6HA03TCA4OJjk52dOjoz2sU1yZoKAgevToQXJyMhUVFZw8eZKamhoCAgIICQmRAKSDsVqtWCwWhg4dKqFHJyAVH61EKj6EEEII4QubNm3id7/7HZ988gnz5s3jF7/4BQD9+vVrVy/elVLU19dTUlJCSUkJDofjsqs7Ghoa+Oijj8jNzWXv3r0AJCcnk52dTXZ2NgkJCa35FFrkzKADmt8cx8TEEBUVRWhoKMHBwT5eoWgt7ikgJ0+epKqqCn9/f0JCQtpt81zxfywWC01NTQwcOJD4+HhfL0e0gFR8tLEzmpv6eilCCCGE6CKUUmzYsIGlS5fy+eef4+fnx9SpU5k3bx4ZGRkYDAZfL9HDbrd7qjvq6+vx8/MjJCSkxZNInE4n27dvZ9WqVWzcuBGbzUZwcDA5OTnk5OQwZMgQn36y7nQ6sVgs2Gw2APz9/YmOjiYmJoawsDBpRtqFaJpGdHQ0UVFR1NXVcfz4cSorK6UCpJ1ramrCarUyePBgYmJifL0c4SVS8dFKpOJDCCGEEG3ls88+4/rrr0en0zFt2jTuuecebrrppnZTTaCUoqGhgdLSUoqKinA4HJfd/6CgoIDc3FzWrFlDWVkZAEOHDiU7O5sbbrjBZ+GOUgqbzUZTUxNKKTRNIyIigtjYWMLDwwkNDZVP+AXQ/HeltrbWE4Do9XqMRqMEIO2I1WqlqamJwYMHt9ux3uL8pOJDCCGEEKKTUUqxZs0aUlJSiI+PJzQ0lPvuu4/s7GxuvPHGdhN4OBwOz8jPuro6NE3DaDQSEBDQotubTCY++eQTcnNz2bVrFwDx8fEsXryY7OxsUlJSWnH1F+Z0OmlqavJUdbgnfLi3rwQGBvpkXaJ90zSNyMhIIiIiqK6u5ujRo1RXVxMSEiJNbNsBm82GyWRi4MCBEnp0QlLx0Uqk4kMIIYQQ3qaUIjc3lyVLlvDNN98wYcIEnn32WQAGDBjQbhpjNjQ0UFZWRmFhIXa7Hb1e3+ItHkopvvnmG3Jzc/n0009pampCr9czYcIEcnJyGD58eJuPlHRPX3FXdeh0OqKjoz1VHbJ9RVwJl8tFaWkphw8fxm63Ex4eLtVBPmK326mvr2fAgAF069bN18sRV0AqPoQQQgghOjh34PHYY4+xc+dO9Ho9t912G3feeSeZmZnt4tNip9NJVVUVBQUF1NTUABASEtLiCTIlJSWsWbOG3NxcioqKAMjMzCQnJ4fJkye3+SSaM6s63NNXUlNTiYqKIiwsrMU9SYS4ED8/P5KSkoiOjubo0aMUFhZiMBjaTcVWV+FwOKivrycjI0NCj05MKj5aiVR8CCGEEMJb9uzZw6BBg9Dr9cyZM4e77rqLCRMmtIvAw2w2U1paSmFhIVarlcDAQAwGQ4s+ubZYLGzYsIHc3Fy2b9+OUoro6GimTZtGTk4O6enpbfAMmp3Zq8PlcqHT6YiKiiIuLk6qOkSbqKioYN++fTgcDsLDw+XvWxtwOBzU1dXRt29fevTo4evliKtwqYoPCT687IypLnOrqqp8vRwhhBBCdEAul4uVK1cSGhpKv379KCsr44MPPiArK4uJEyf6vIeEy+WipqaGwsJCKioqADAajS1al1KK/Px8Vq1axfr16zGZTPj7+zNu3DhmzJjBqFGj2qyawuVyYbFYsFqtKKUIDg4mLi6O6OhowsLCWtyLRAhvaWpqYt++fVRVVREREdHm27q6Enfo0bt3b9LS0ny9HHGVJPjwEan4EEIIIcTlcrlcrFixgqVLl/Ltt9+SmZnJP/7xD/z8/BgwYIDPAw+LxUJ5eTmnTp2iqamJgIAAjEZji6o7KisrPVtZTpw4AUCfPn2YMWMGU6ZMISIionUXf5rD4cBsNuNwONA0jfDwcBISEoiIiJARo6JdcDqdHDt2jOPHj0uz3FZyZuiRmpoq/+47AenxIYQQQgjRzrkDjyVLlrB79270ej0LFixg0aJFDBo0yKeVB+4RnMXFxZSWlnoqI6Kioi55W4fDwdatW1m5ciWbN2/G6XQSHh7O/Pnzyc7Opm/fvm2yfpvNhtlsBsDf35/Y2FhPY9L20hBWCDedTkfv3r0xGo3s27cPp9MpfT+8yOl0SqVHFyQVH61EKj6EEEII0VIlJSWeF+Dz5s1j0aJFZGVl+TTwsNlsVFRUUFBQQENDAzqdjpCQkBaV3hcWFrJy5UpWr15NRUUFmqYxevRoZsyYwfjx41v9eZ25hQUgKCiIhIQEoqKiCA8Pl+0DosOorq7m22+/xc/Pj5CQEF8vp8NTSlFdXU1qaiq9e/eWSo9ORLa6+IgEH0IIIYS4EJfLxfvvv4/FYiErK4vKyko2btzIkCFDfBp4KKWor6+npKSE4uJizyfNQUFBl3yDYLVa2bBhAytXrmT79u0AJCYmMmPGDHJyckhISGjVtZ87hSUsLIyEhAQiIyNlC4vo0Orr69m1axdOp5OwsDBfL6dDq6mpIS4ujszMTBkd3MlI8OEjEnwIIYQQ4lwul4v//ve/LF26lPz8fLp168YHH3yAXq+nf//+PhuRarfbPdUd9fX1nk+XW7KeQ4cOsWLFCj788EPq6+sJCAhgwoQJzJw5kxEjRrTqm4sz+3X4+fkRHR1NfHw8ERERsjVAdComk4ldu3Zhs9kk/LhCDQ0NBAUFMXToUOmb0glJjw8hhBBCCB9zBx5Llixh7969BAUFceedd7Jo0SKGDBnik8BDKUVDQ4OnusPhcBAUFERkZOQlqyMaGxv58MMPWbVqFfv27QMgPT2de++9l2nTprVqo9JzR87GxcURGxtLRESEvJkRnZbRaGTo0KHs3LmT+vp6CT8uk8PhwOl0tosm0cI3pOLDy2ScrRBCCCHOZTKZ6NGjB2azmXnz5nH33Xdz3XXX+STwsNvtVFZWUlBQQF1dXYurO5RS7Nq1ixUrVvDJJ59gtVoxGAxMnjyZWbNmMWDAgFbbTuJuTqqUIiAggISEBGJiYggPD/dZlYwQvmA2m/n6669xuVzS8+MyVFdX07NnT9LT0329FNFKZKuLj8hWFyGEEKLrcjqdvPfee5w8eZJ58+ZRVVXFN998Q58+fXwSeLirO0pLSykqKvJUdwQHB18yrHCPoV25ciWnTp0CYNCgQcycOZMbb7wRg8HQKmt2hx0ul8vTnNQddsjefNGV1dfXs2PHDvR6vUwlaoGmpiYARo0aJUFpJyZbXYQQQggh2ojT6WT58uUsXbqU/fv3ExERwXXXXUdYWBh33313m7/ottvtVFVVcerUKU91h9FovGTzVIfDwZdffsmKFSs8Y2gjIiK44447mDlzZqt9anpu2NGjRw9iYmIICwuTsEOI08LCwhg4cCC7du3C399f3sxfhFIKs9nM4MGD5fepi5M/fSGEEEKIq+RyuXj33Xc9gYfBYODuu+/mnnvuYeTIkW36gts9maWsrMxT3aHX61vUu6OwsJBVq1aRm5vbZmNoJewQ4vLFxsbSs2dPjhw5QlRUlEwtugCTyURkZCSxsbG+XorwMdnq0kpkq4sQQgjRdbib5hUWFnLrrbdy9913M3r0aHQ6XZutwWazeXp3uCeztKS643xjaBMSEpgxYwYzZsxolTG054YdiYmJEnYIcZlcLhe7d++mqqqqVRsKd1Qul4va2lquvfZaoqKifL0c0cqkx4ePSPAhhBBCdF5Op5N33nmHr776ioceeojq6mqOHDlCt27d2jTwcFd3lJSUUFJSclm9Ow4dOsTKlStZt24d9fX1+Pv7M3HiRGbOnMnw4cO9/hwk7BDC+ywWC9u2bcPf31/6fZyjvr6eqKgorrnmGl8vRbQB6fEhhBBCCOElDoeDd955h8cff5yDBw9iNBrJzs4mMTGRW265pc0CD6vV6qnuaGhoaPFklsbGRj766CNWrlx51hjaxYsXM336dK9/amy32zGZTCilCAwMpHv37tKgVAgvCgoKIiMjg127dhEYGCj/rk5zuVw4HA5SU1N9vRTRTkjwIYQQQgjRAm+99Ra/+93vOHToEEajkXvvvZdFixYxatSoNgk8XC4XdXV1nuoOl8tFcHDwJXt3uMfQrly5ko8//hir1UpwcDCzZs1i5syZZGZmerU/gMPhwGQy4XQ6CQwMJCUlhdjYWAk7hGglsbGxdOvWjZKSEiIjI329nHahsbGR+Ph4wsPDfb0U0U5I8CGEEEIIcQlKKd544w2Kioq47777uOuuu9os8LBYLJSXl1NQUIDZbEan0xEaGnrJx66qqmLNmjWsWLHirDG0M2bM4MYbb8RoNHptjU6nE5PJhMPhwN/fn8TEROLi4oiIiGjTPidCdEWaptGrVy8qKyuxWCxdfsuLUgqHw0H37t19vRTRjkiPj1YiPT6EEEKIjsvhcPD222+zcuVKnn76aWpraz2fprZF4OFyuaiurqa4uJiKigqUUgQHB6PX6y9aneEeQ7ty5Uo2bdrkGUM7ffp0r4+hdblcmM1mbDYbOp2OuLg44uPjiYyMlLGRQvhAaWkpu3fv7vJTXhoaGggLC2PIkCFd+vehq5EeH0IIIYQQLeRwOPj3v//N448/zpEjRwgJCeH222+nb9++TJ06tdUDD5PJRHl5OYWFhVgsFvz9/VtU3VFUVOQZQ1teXo6maYwaNYqZM2cybtw4AgMDvbI+pRRNTU1YrVYAoqKiSEpKIioqymuPIYS4MvHx8cTGxlJbW0tYWJivl+MTSinsdjupqakSeoizSPDhZZqmzQXmysgkIYQQomN5++23+e1vf8vRo0cJCQnhgQce4M4772TkyJGtGng4HA6qq6spLCykuroaAIPBcMnxi+4xtKtWreKrr74CmsfQ3n///eTk5JCYmOi1NVqtVsxmMwChoaGkpaURHR1NcHCw1x5DCHF13Ftetm3bhtPp7JLbzEwmE1FRUdLrRHyHBB9eppRaDixPTk6WPURCCCFEB6GU4sMPP6S8vLzNAo+GhgbKysooKirCZrMRGBjYogaghw8fZsWKFWeNob3hhhuYOXMmI0aM8Nqa3RNZ3E1U09PTiY2NJSQkRD5JFaKdCg0NJSUlhYKCgi735l8phdVq9XrDZtE5SI+PViI9PoQQQoj2y+FwsGzZMl577TVeeeUVzGYztbW1BAcHt2rgYbfbqaqqoqCggLq6OgCMRuMlt4lcaAztzJkzmTZtmtfe4DidTsxmM3a7nYCAAE+TUpnIIkTH0dTUxNatWzEYDAQEBPh6OW2mvr6e8PBw6e3RRUmPDyGEEEKI05xOJ8uWLfOMpQ0JCeHLL79k+PDhjB8/vlWaciqlqKuro7S0lJKSEhwOB3q9noiIiEuOof32229ZsWIFn3zyCRaLheDgYGbOnMnMmTMZOHCgV17cu/t2WCwW/Pz8iI2NJTExUZqUCtFBBQcH06NHD44dO3bJLXOdhcPhwOVy0bt3bwk9xHnJ/2ZCCCGE6BJWrFjBL3/5Sw4ePIjRaPSMpR05cmSrvMG3Wq1UVFRQWFhIQ0MDfn5+hISEXPKx3GNoV65cycmTJwEYOHAgM2fO9OoY2jP7doSHh5Oenk5MTAx6vd4r9y+E8B33dhf3NrrOrr6+nvT0dEJDQ329FNFOSfAhhBBCiE5PKcX27dspLCxk8eLFLFq0iFGjRnk98HC5XNTU1FBSUkJZWZmnP0ZkZORFP4V0Op1s3br1rDG04eHh3H777cycOZOePXt6ZX0OhwOTyYTT6SQ4OJiePXt6+nYIITqPwMBAUlNTOXLkSKcPPhobGwkNDaVHjx6+Xopox6THRyuRHh9CCCGE77hcLt577z2efvppXnrpJXQ6HRaLBZfLxejRo70eeJxvDK3RaLyiMbQjR45k1qxZXhtD63K5MJvN2Gw2/P39SUhIICEhQfp2CNHJ2Ww28vLyCAoK6rS9Pmw2G2azmeHDh3fZEb6imfT4EEIIIUSX4XK5eP/991myZAn5+fkEBwfzxRdfcP3113PNNdd4NfCw2+2eMbQ1NTVAy8fQbty4kZUrV3rG0MbHx3PfffcxY8YMr4yhdU83aGpqAiAqKopu3boRFRXVad8ACSHOFhgYSPfu3Tl27FinnPDidDppaGggMzNTQg9xSRJ8CCGEEKJT+PTTT/nZz37G7t27CQoK4s4772TRokVkZWV5LfBwNyotKyujuLgYh8NxWWNoV65cydq1az1jaK+//npmzZrltTG0DoeDxsZGXC4XBoOB3r17Exsbi8FguOr7FkJ0PElJSRw/fhyn09mq47nbmtPppLa2lrS0NK+ExaLzk+DjAjRN+wHwAJB6+qq9wONKqTU+W5QQQgghzqKU8vTOOHz4MAcPHmThwoXcfffdjB071mvVDU1NTVRWVlJQUIDJZMLPzw+j0XjJ+29sbGT9+vWsWLHCM4Y2LS2Ne+65h+nTp3vlU9hzt7J069aN+Pj4S06NEUJ0fkFBQSQmJlJaWkp4eLivl+MVSilqa2vp0aMHvXr1kp9zokWkx8cFaJo2E7ABhwE/4C7gF8C1Sqndl7q99PgQQgghWo9SitzcXJYsWcLjjz9OXFwcLpeLhoYGsrKyvBJ4OBwOampqKCoqoqqqCqUUQUFBBAUFXXIM7a5du1i5cuVZY2hvvPFGZs2a5bUxtBaLxbOVJTIykuTkZNnKIoT4jtraWrZv337JJssdgVKK6upqEhISyMzMlD5FwkN6fFwhpdTKc676taZp3wNGA5cMPoQQQgjhfUop1qxZw2OPPcbXX3+NXq/nyy+/ZPbs2QwaNOiq3/Qrpaivr/dsZbHb7QQEBBAWFnbJF9iVlZWsXr2aVatWcerUKQAyMzOZNWuW18bQnjuVpXfv3sTExHhtxK0QovMJDw8nLCyMpqamDr3tzT01KyEhgf79+0voIS5Lhw0+NE27BRgPDAauAUKBfyulFlzkNsnAUmAKEA2UACuAJUqpmovcTgfMBUKAPO88AyGEEEJcjm3btvGjH/2I7du3ExgYyG233cbdd9/NxIkTrzrwuNBWltDQ0IvezuFwkJeXx8qVK9myZQtOp5OIiAivjqFVSmE2m7Fareh0OhISEkhMTJSpLEKIFtE0jeTkZPbt29dhgw93T4+kpCQyMjI6Vb8S0TY6bPAB/A/NgUcjUAj0u9jJmqb1pDm0iANWAgeAEcBPgCmapl2nlKo65zYDga1A0OnHma2U2uPl5yGEEEKIC3BvydU0jcrKSr799lvmzZvH3XffzaRJk65q3KvD4aC6uvqsrSzBwcEtKgc/deoUq1atYvXq1VRWVqJpGqNHj2bGjBmMHz/eK9tNbDYbJpMJaP7Etnfv3kRHR3tlxK0QomuJiYnBz8+vQzY5dTgc1NXVkZqaSs+ePTvc+kX70JGDj5/SHHgcobnyY8Mlzn+J5tDjx0qpF91Xapr23On7+j3w4Dm3OUhzRUk4cAvwpqZpE5RS+d54AkIIIYQ4P6UUH3/8MY8++ij33nsvgwcPJiEhgXXr1jF27NgrfvPvcrk8U1lKSkouayqLxWLhk08+YdWqVXzzzTdA88SEBx98kOzsbBISEq5oTeeuz2QyYbfbCQwMJC0tjbi4uEtWngghxMXo9XpiY2Oprq7uUD9PnE4ndXV19O3bl+7du3f4HiXCdzps8KGU8gQdl/oHcLraYzJwAvjLOYcfBe4HFmqa9v8ppUxnPIaN5mAF4GtN04bTHJIsvtr1CyGEEOK7lFJ8+umnPProo+Tl5eHv78/w4cMZPHgwAwcOvOLAw2QyUVFRQVFREWazucVTWZRS7Nu3j5UrV/LRRx9hMpkIDAzkpptuYubMmQwbNswr200sFgtmsxlN04iJiaFbt25ERUXJJ5tCCK9JSEigrKzM18tosTOnt0joIa5Whw0+LtPE01/XK6VcZx5QSjVomvYFzcHIKODTi9yPH6BvnSUKIYQQXdu+fft44IEH2LJlCzqdjtmzZ3PPPfdw4403otdf/n+/VquVqqoqiouLqa2tBSA4OJioqKhL3ra2tpZ169axcuVKjhxp/gykT58+zJgxg6lTp3plLKTT6aSxsRGn04nBYKBPnz7ExcURHBx81fcthBDnioiI6FDbXerq6oiNjZWRtcIrukrw0ff010MXOH6Y5uCjD6eDD03T/gCsAQpobpx6OzABmN6aCxVCCCG6GpfLhZ+fH1arla+//ppZs2Zxzz33MHny5MsOPNwjaEtKSqioqMDlcqHX64mIiLjkC2eXy8VXX33FypUr2bhxI3a7nZCQEG655RZmzpxJv379rvrFt1KKpqYmLBYLfn5+JCYmkpCQ4HlDIoQQrSUwMJDo6Gjq6uoICQnx9XIuyl1dJ41Mhbd0leDD/bFM3QWOu6+POOO6BOCt01/raB5hO1Up9dH57kDTtJ8BP/M8oBc+CRJCCCE6s02bNvHoo48yceJEpk9v/lxh7dq1jBo1iqCgoBbfj7tvR3l5OSUlJZ4RtKGhoS16wVxSUsKqVavIzc2ltLQUgGuvvZaZM2cyadKky1rLhdjtdsxmM06nk7CwMNLT04mNjZVGpUKINhUfH09lZaWvl3FRjY2NKKUYMmSIV37+CgFdJ/i4bEqpRZd5/nPAc+7vk5OTlbfXJIQQQnQGW7Zs4dFHH+Wzzz5Dp9ORkpICwIABA1r8IlcpRWNjo6dvh7uCoiUjaKF5Ysrnn3/OypUr2bZtG0opYmNjufvuu5kxY4ZnTVfjzDG0/v7+dOvWjYSEBMLCwqRsWwjhE+4PZ5VS7ernkMVioampCQCj0ciAAQMICwvz8apEZ9JVgg93RceFyjDc19e2/lKEEEKIrunUqVMsXryYTz75BD8/P7Kzs1m8eDFTpkxpceBhNpupqqqiqKiIxsZGAAwGQ4v6dgAcOXKElStXsnbtWurq6tDpdEyYMIGZM2cyatQo/P2v/qWR3W7HZDLhcrmIiIigT58+REdHe2XErRBCXI3g4GCCg4OxWq0+r6ZwuVyecNhoNNK7d2/CwsJaNGVLiMvVVYKPg6e/9rnA8d6nv16oB0iLaZo2F5jb0hdgQgghRGfnbqSnlGLnzp1MmzaNe++9lylTprSokafVaqW6upqioiJqa2tRShEcHNyivh3QXDb90UcfsXLlSvbt2wdAamoqixYtYtq0aURHR1/1czyzuiMgIIDu3buTkJBASEhIu/pUVQjRtWmaRlxcHKdOnfJ68KGUwul04nK5UEp5vrovZ55jNptRShEREUGPHj2IiYkhICDA0+9Jp9Ph7+8vAYjwGs39l7Aj0zRtArAB+LdSasF5jvekeSztCaDnmZNdNE0LBUoADYg7c5zt1UhOTlaFhYXeuCshhBCiQ/rqq6947LHHSElJ4f777weaKzaGDRt2ycDDbrd7mpRWVlZ6mpQGBwe36IWwy+Xim2++YdWqVXz66adYrVaCg4O54YYbmDVrFoMGDfJKIOGu7nC/gE9JSSE6OtorlSNCCNEaKisr2bVrF5GRkZc81x1UuC8OhwOn04ndbsdut+NwODzXuYOOi3GfHxoaSmhoqKeB9flu5+fnh7+/P0FBQQQFBWEwGDAYDJ7/C4KCgiQYER6aphUppZIvdLxL/K+slDqqadp6mie3/AB48YzDSwAj8Iq3Qg8hhBCiK9uxYwePPvooa9euRdM0srOzUUrRv39/DAbDBW/ndDqpra2lrKyMsrIyHA7HZTUpBSguLiY3N5c1a9ZQXFwMwMCBA5k5cyY33ngjRqPxqp/fudUdPXr0ID4+vkW9RYQQwtdCQ0PRNM0zUcsdbrjDDLvdjtVqxWq1YrPZcLmaPzPWNM0TUGiahp+fH35+fmiahr+/v+e6C3E4HACkp6df8mexu2LE6XRis9loamryhOBuOp2OsLAwIiMjCQ8PJzQ0VBpGiwvqsBUfmqbNAmad/jYBuAk4Bmw+fV2lUurnZ5zfE8gD4oCVwH5gJDCR5i0uY5RSVV5Yl3ury9yqqqu+OyGEEKLDqK6u5q677mL16tVomsYNN9zAvffey/Tp0y/4Itc9kaWiosIzkUWn02EwGFpcNdHU1MRnn31Gbm4uO3bsACAmJobp06eTk5NDamqqV57fmb07IiMjpbpDCNHhWK1Wmpqa2L59u+fnmdVqxel0nnWen58fOp3O8/VqKaUwmUwkJSW1qNKkJRwOBzabDavVCjSHMREREcTHxxMREYHRaJSthl3IpSo+OnLw8Rjw6EVOOamUSj3nNinAUmAKEE3zFpcPgCVKqRpvrk+2ugghhOgq3ONjq6qqGD16NN27d+e+++4jOzv7vIGHUor6+noqKyspLi4+ayJLSxuAKqX49ttvyc3N5ZNPPsFkMhEQEMD48ePJyclh5MiRXgkkzp3MkpycTEJCglR3CCHaNaUUTU1NmM1mzGYztbW11NfXY7FYAKipqaG+vh6j0YhOp/NKuHEx7gq51NTUVgsjXC4XTU1N2Gw2Ty+ohIQEoqOjCQsLa/XnKHyr0wYf7Z0EH0IIITq7b7/9lsceewy73c6SJUuA5pGE11xzDSEhIWed6/60r7KykqKiIpqamtA0jeDgYM8e75YoKytjzZo1rF69mlOnTgGQkZFBTk4OkydPJiIiwivPzeFwYDKZcDqdhIeH0717d5nMIoRot6xWKyaTicbGRmpqaqitrcVms3lChoCAAAIDAwkICEDTNBobGykoKLjo9kNvMplMpKSktFlorJTybJFxuVwEBgaSmJhIbGysTI3ppKTHRxuTqS5CCCE6u927d7NkyRLef/99ACZOnIjD4aB///7feVHrHj9bXFxMQ0MDwGVNZIHmF/QbN25k9erVbNu2zbPV5I477iAnJ4devXp55XkppbBYLDQ1NeHv70+3bt1ISEggLCxMyqWFEO2GuxKtsbGRuro6qqqqMJn+r1VhQEAAer3+ols93BNdlFKt/vPN4XDg7+/vlR5LLaVpGnq93hOs22w2CgoKOHXqFHq9npSUFOLj41s0WUx0DlLx0Uqk4kMIIURnY7PZuP322/nvf/8LwPjx47nvvvuYMWPGWYGHxWKhqqqKkpKSs8bPBgUFtfgFtlKKffv2kZuby0cffURDQwM6nY6srCyys7MZO3as13prOJ1OGhsbcTqdhIaGkpKSQmxsrDTJE0K0C+6go6GhgerqaqqqqrBarSil0Ol06PV6AgMDL7uK4dixY7hcrlavZDObzcTExBAbG9uqj9NSVqsVs9mMpmkkJCSQnJxMeHi4r5clrpJUfAghhBDiqlitVvR6PVarldLSUrKysnjggQfIyckhLCzMc05NTQ3FxcXU1NR4xs9ebklxZWUl69atIzc3l2PHjgHQq1cv7r33XqZOnYo3Kyrd1R2appGYmEhSUhLh4eFS3SGE8DmLxUJ9fT3V1dVUVlZisVhQSnnGuwYHB1/1z6qQkBCqq6tbNfhwf8h+7vZHX3JXgjidTsrKyiguLiY6OpoePXoQFRUl/wd0UlLx0Uqk4kMIIURHd+DAAZYsWcKBAwd47bXX0DQNm81G//79CQ8Px263U11dTWlpqWfMYGBgIAaD4bLCDrvdzubNm8nNzSUvL8/TV+Omm25ixowZ9O3b12svRF0uFyaTCbvdjsFg8JQ7X06fESGE8Da73U59fT21tbVUVFTQ2Nh4VtDh7s3hTQ0NDRQWFrZqnw+73Y6maaSnp7fbQEEpRWNjI3a7nYiICNLS0oiOjm636+2IlFKEhoZy9OhR4uPjW+UxpOKjjUmPDyGEEB3d4cOHWbp0KW+//TYul4sxY8bQ0NDAkCFDCAkJoaamhvz8fMrLy3E6nQQEBBAaGnrZHfMPHjxIbm4u69ato66uDj8/P0aPHk1OTg7jxo3z6lYTm83m2QMfExNDSkoKkZGR0uBOCOET7i127nHe7m2B0Nx/43L6IF0pd+Dr7vPhDoZNJhNms/mSXx0OB06nE5fLhcvlQtM0/P398ff3JyAgwBPWREdHExcXR1hYGKGhoYSFhXl+HR4e7vNKO03TCA0N9TTh3rlzJxEREfTs2ZPIyEgJQK6AO+g4duwYcXFxHD9+nMDAwFYLPVpCgg8vU0otB5YnJydLKY0QQogORSnFgw8+yOuvv47T6WTkyJGeLS2aplFcXExZWZmnUV1ISMhlhx21tbV8+OGHrFq1ikOHDgGQmprKnXfeybRp07y6B/zMUbSBgYGkp6cTHx/fpg32hBAC/u/nUX19PRUVFVRXV3uqIQIDA68oPG4Jl8tFdXU1FRUVVFVVUVNTQ1VVFdXV1VRXV1NYWEh9fb3n4nK5WnS/fn5++Pv74+fn57kopXA4HNjt9hbfDzQHMHFxccTHx5OQkEBqaippaWn07NmTpKSkNguoNU0jJCTEE4Ds2LGD+Ph4evbs2a626nQEx48fx2AwEBcXB0B+fj4ZGRk+XZNsdWklstVFCCFER+Hu4WE2m1m0aBEnTpzg/vvv5/rrr8dms1FaWorNZsPf3x+DwXDZTUUdDgdbt25l1apVbN68GYfDgdFo5KabbiInJ4fMzEyvfqJ25ijaiIgIzyhabzVDFUKIlrBardTX11NTU0N5ebmnT0dgYCBBQUFe+Znk7lNRUFBAQUEBpaWllJWVeS7l5eXY7fYL3j44OJiwsDAiIiIIDw8nLCwMo9GIwWDAaDR6Lmd+bzAYLtms2ul0YrPZMJvNxMXF0djYSENDA3V1dTQ0NFBfX09DQwO1tbWUl5d71tvY2HjW/ej1elJTU8nIyCAzM5OBAweSlpbWJmGIy+WioaEBl8tF9+7d6dGjh2yLbIH9+/czZMgQnE4ner2ejIwMZs+eza5duzAYDKxYsYKkpCRyc3Pp2bOn1x73UltdJPhoJRJ8CCGEaO8KCwt54oknWL16NcuWLUOv19PQ0EB4eDgmkwmr1YqmaRiNxitqfnf06FFWr17N2rVrqaqqQtM0RowYQU5ODhMmTPCMU/QWi8WC2WxGp9N5mpXKKFohRFtxv1F2v5mvr69HKYWfnx9BQUEEBgZe8c+j2tpajh49yvHjxz1jWQsLCyksLDxvsBEeHk58fLynkiIuLo7o6GiioqLOulgsFkpKSlqlz4fFYiE0NJSkpKQW36ahoYETJ05w9OhRjh07xvHjxzly5AgVFRWec0JDQxk+fDhjxoxh1KhRJCQkeH3tZ3I6ndTX1+Pv70+vXr28XoWyd+9ennzySTZs2EBlZSXR0dFMnDiRX/3qVwwYMOCy7y8vL4/169fz0EMPERERccnzGxsbeeaZZ9i2bRtfffUVNTU1vPHGGyxatOis87Zv386bb77Jhg0bOHHiBNHR0YwaNYrHH3+cPn36nHXuk08+SUlJCS+88AIAt99+O5s2bWL58uWMGDGC+fPn07t3b37/+99f9vO7EOnxIYQQQoizFBcX8+STT/Lqq69is9kYMGAAhw8fJjExET8/P2pqajAYDFf0Qti9lWXNmjXs378fgOTkZB588EGys7O9/gL13Gal/fr1Iy4uTj6VE0K0CavVSl1dHZWVlVRUVGCz2dA0Db1eT1hY2GW/QTabzRw7doyjR49y9OhRjhw5wtGjR6mqqjrrPJ1OR7du3RgxYgTdu3cnJSWFlJQUEhMTiY+PJzg4uEWP15ofgjudzsveWhgaGsrAgQMZOHDgWdeXl5eTn59Pfn4+X3/9NRs2bOCzzz4DoE+fPowbN46srCwyMjK8Xg2i0+mIjIzEZrOxb98+iouL6d27N5GRkVd93++//z7z588nKiqKxYsXk5aWxokTJ3j99dd57733eOedd5g9e/Zl3WdeXh5Llixh0aJFLQo+KisrWbp0Kd27d+eaa65h48aN5z3vqaee4osvvmDu3LkMGjSI0tJS/vznPzN06FC+/PJLMjMzPefu3r2bSZMmeb7Pz8/n8ccfZ/To0QD07t27Vf/unY9UfHjZGc1N5577A0oIIYTwtd/97nc88cQTWCwW+vTpw5w5cxg5ciQhISEYDIYrCgzsdjtffPEFq1evZsuWLZ6tLDfccAPZ2dkMHjzY61UXdrvdUxIdExNDcnIyUVFR0qxUCNGq3BNAamtrKSsro66uDpfLhb+/P8HBwS2ujrPb7Zw8edITbLgvRUVFZ52n1+vp2bOn55KWlkaPHj1ISEjw2laZw4cPo9frvfrz093TpGfPnq0SRNfW1vLVV1/xxRdfsGXLFurq6oDm/w+ysrIYN24cw4cP93plobv/h81mIzExkfT09Cuuljl69CiDBg2ie/fubNq06aweV5WVlWRlZVFQUMDu3btJT09v8f0+++yzPPzwwxw/fpzU1NRLnu8eR5+QkMCOHTsYPnz4eSs+8vLyGDZs2FmNxw8fPszAgQO55ZZbeOuttzzXDxgwgL///e+MHDnS85qgoKDA0/Nj1qxZzJkzhzvvvLPFz+tSZKuLj8hWFyGEEO2Fu4dHdXU1/+///T8+/fRTZs2axbhx44iJibnkXu3zUUpx4MABVq9ezYcffkhdXR2apjFy5Eiys7NbZSuLUgqLxUJTUxP+/v6kpKSQkJAgTeeEEK3K4XBQV1dHdXU1ZWVlWCwWoDmUCAoKumRgYDabOXToEAcPHvRcjh49isPh8Jyj0+lITU09K+RojW0V53P8+HEcDodXJ2k5HA5cLhe9evVq9e2GTqeTPXv2sGnTJjZt2sSJEyeA5j+fUaNGkZWVxdixY4mJifHaY7pcLurr69E0jR49etC9e/fL3hL64IMP8sorr7Bp0yaysrK+c3zTpk2MHz+eBx54gJdfftlzfVFREb/97W9Zt24dVVVVJCUlMWXKFP70pz/xxBNPsGTJku/cV0tDkIsFHxdy7bXXAvD1118DzVPU3BPgjEYj+/bt4/rrr6ekpMRzm/T0dN5//30GDx7cosdoCdnqIoQQQnRRVVVV/OEPf+Dvf/87Tz31FEFBQYwZM4bZs2cTFxd3RS9GKyoqWLduHatXr+bYsWMApKWlsXDhQqZNm+b5NMebXC4XjY2NOBwOQkND6d+/P3FxcVfUd0QIIVrCYrFQV1dHWVkZVVVVOJ1ONE0jODj4oqNma2trPeHGgQMHOHjwIKdOnTqrrD8uLo7Ro0fTu3dvT8jRo0cPn/1MMxqNVFdXe/U+7XZ7m42C1el0DB48mMGDB/PjH/+YU6dOeUKQLVu28PnnnwPQv39/srKyyMrKom/fvle1Nj8/PyIiInA4HBw7doyioiJ69uzp2TLaErm5uaSmpp439AAYN24cqamprFmzxnNdcXExI0aMoLa2lvvvv59+/fpRVFTEe++9h9lsZs6cORw6dIhly5bx/PPPe8Ieb05MO5NSirKysrN6kTQ0NADNAYjRaCQ/P59BgwaddbyoqIj+/fu3ypouRIIPIYQQopMpKSnh6aef5tVXX8VsNtOtWzfKy8sZOXJki/b7nstisbBx40bWrFnDtm3bcLlchIeHM3fuXLKzs+nfv3+rvLi12WyYTCag+Y1CcnJym72QFkJ0Le6tGTU1NZSWllJbW4tSioCAgAtOs7Lb7Rw6dIg9e/awd+9e9uzZw7kV3ykpKVx//fX069ePvn370rdvX6KiotrqabVIUFCQ1/stKKV8Njq8e/fuLFiwgAULFlBXV0deXh6bN28mLy+PV155hVdeeYW4uDgmTJjAtGnTGDBgwBX/v+Lv709UVBRWq5V9+/ZRUFBAz549iY6OvmgAUldXR3FxMTNnzrzo/Q8aNIhVq1bR0NBAaGgojzzyCKWlpWzbto1hw4Z5zlu6dClKKQYNGsTQoUNZtmwZs2bNalGVx9X497//TVFREUuXLvVcFx0dzfz58+nevTsDBgxg8uTJZwUf+fn59OnTx6sVRi0hwYcQQgjRCbj36L700ks899xzmEwmEhMTuf/++5k6dSrR0dGXdX9KKb799lvWrFnD+vXrMZlM6HQ6xo4dS3Z2NmPHjm2VFy1KKZqamrBYLAQEBJCWlkZiYmKrTBwQQnRtSikaGhqorq6mtLSUxsZGlFLo9XrCw8PPeuPq/mR7z5497Nmzh/z8fA4cOIDNZvOc0717d6ZNm0ZGRgZ9+/alT58+HWIrnrd/lrtcLk91jK+Fh4czdepUpk6disPhYNeuXWzevJlNmzbx7rvv8u6773r+3KZNm3ZZE2jOpNfr0ev1mEwmdu3aRXh4OD179iQqKuq8oYq7KiI0NPSi9+s+Xl9fj9FoZMWKFeTk5JwVeri19YcCBw4c4Ac/+AGjR4/mrrvuOuvYm2++yZtvvnne240ePZo9e/a0xRLPIsGHEEII0UHZbDZqamo4efIkDQ0NOBwO6uvrCQ0N5Z577mH69OmXvae5uLiYtWvXsmbNGgoKCgDo27cv2dnZ3HTTTa32SaXT6cRkMuFwOAgLC6NXr17ExsZ6pXmfEEK4uUeTVlVVUVpa6unXERQUdNYWFqUUJ0+e5JtvvvFcysrKPPcTGhrKtddeS2ZmJpmZmQwYMOCKKuraA/eYXZfL5ZV+Iu4pWzqdzgur8x5/f3+GDRvGsGHDeOihh9i/fz9r167lo48+4uWXX+bll19m6NChTJ06lUmTJhEeHn7Zj2E0GjEYDJhMJr755htiYmLo2bMnYWFhZ53nDjTcAciFnBmQVFRUUF9ff9b0FF8pLS1l+vTphIeH895777W7P+vzkVcTXnbGVBdfL0UIIUQnZLfbPaXYBQUFrFixgvfee4/f/va39OjRg7FjxzJlypTL2s9rMpn47LPPWL16tac5WXR0NAsWLCA7O5tevXq11tM5aztLfHw8ycnJF90/L4QQl8vpdFJbW0tFRQVlZWXY7XYADAaDZySpy+Xi6NGj7Ny50xN0nDmhMS0tjTlz5jBo0CAyMzPp3r17p5ki5efnh16vx+l0euU5OZ3OS1Yy+JqmafTv35/+/fvz0EMP8eWXX7JmzRo2bdrEN998w1NPPcWYMWOYOnUqWVlZl9WsW9M0QkJCUEpRW1vLtm3bGDJkyFkfRISHh5OYmMju3bsvel+7d++mW7duhIWF0dTUdMXP15vq6uqYOnUqtbW1bN68+YqrZNqaBB9eppRaDixPTk6WcTlCCCG8wuFwUFNTQ1lZGRUVFZhMJtatW8eyZcuoqakhJiaGmpoaBgwYcMGy2nO5XC527NjB6tWr+eyzzzxbS9wjaEeNGtVq1RZnbmcJDAwkPT2dhIQE2c4ihPAah8NBbW0t5eXllJeXY7fb0el0GAwGz/aTmpoaPvvsM/Ly8vjyyy+pqakBmt+49urVixtuuIGhQ4cyZMiQdteXw9sMBgM1NTVea7DaHra5tJS/vz9jx45l7NixNDY2snHjRtatW8eWLVvYtGkTBoOBYcOGMWrUKEaOHEn37t1b9P+spmmEhYVRXV191pYot+zsbF577TW2bNnC2LFjv3N88+bNnDhxggceeABoblAaFhZGfn7+JR+3tVgsFnJycjh06BCffPJJmzcovRoSfAghhBDtkPtFe1lZGeXl5TgcDvz9/fn666/5wx/+QFVVFVFRUdx3333k5OSQmJjYohc7J06cYM2aNaxdu9ZTtj1o0CCmTZvG5MmTv1OO603nbmfp3bs3MTExsp1FCOEVZ4YdZWVlOBwOT9gRGhqK0+lk7969bN26lS+++IL9+/d7mnr26dOHadOmMXToUAYPHnxF2xw6Mm81OHU6neh0OvR6vRdW1fZCQkLIzs4mOzubyspKPvnkE9avX88XX3zBpk2bAEhISGD48OEMGjSIgQMHkpaWdtGtHhf6v/nhhx/mrbfe4oEHHmDTpk1n9eKqrq7mwQcfxGAw8PDDDwPNlTmzZs3irbfeYseOHd/p86GUQtM0T1PZ2traq/mt+A6n08mtt97K1q1bWblyJaNHj/bq/bc2zdsdfEWz5ORkdW5XZyGEEOJizn3R7n4BGRAQ4HlRunnzZh5//HHmzJnDjBkzSEpKumTgUV9fz/r161mzZo2noVh8fDzTpk1j+vTprd71/cztLAkJCXTr1k22swghvMJut3tC4oqKCk9I7J7EUlVVxdatW8nLy2Pbtm3U1dUBzT0TRo4cyZgxYxg9erTXx30qpXC5XOe9uI8ppTxvVq/0MTRNO+/Fz88PPz8/dDqd5+vFmM1mTp48edWVdxaLhdDQ0A6z/aGlGhsb2bFjB9u2bWPbtm2cOnXKc8xgMDBgwAAyMzMZOHAgmZmZZ1UI1dTU0L9///P+nixfvpw77riDmJgYFi9eTFpaGidOnOD111+nsrKSZcuWMWfOHM/5RUVFDBs2jPr6eu6//34yMjIoKSlh+fLlbNmyhYiICLZv386IESOYNm0at912GwEBAeTk5Fx0ys6f//xnamtrKS4u5q9//Stz5sxhyJAhAPzoRz8iPDychx56iD/96U/k5OQwb96879zHggULruj31ls0TStSSiVf8LgEH61Dgg8hhBAtcaGww/3iMzc3l9dff517773X8yLE39//koGHw+Fg69atrF69mk2bNmG32wkKCmLSpElkZ2czbNiwVt2ffu52lpSUFNnOIoTwCnevI/c2FpfLddbPzfz8fPLy8sjLy+PAgQOe2/Xr148xY8YwZswYMjMzr6jaTCmFw+HA4XDgdDo9l/P9PPbz88Pf35+AgADPxf29v78//v7+nmDizNACvlsl4H7P5g5L3OGJ0+n0fHVf7HY7DocDm82G1Wr1nHM+Op0OnU6Hy+Xi1KlTGAyGq/q/wWw2k5SU1OkrZiorK8nPz/dM+dm3b5+nUS40NzmNjY0lPDycoKAgfvvb3zJt2rTz3teePXt48skn2bhxI5WVlURHRzNx4kR+9atfnbeR6alTp/jNb37DunXrqK+vp1u3bkydOpXnnnvOM6Hn8ccf5+WXX6akpASXy8Xx48cv+iFHamoqJ0+ePO8x920nTJjA559/fsH78HWuIMGHj0jwIYQQ4kIuFnb4+/vjcDhYu3Ytf/vb3yguLiY0NJS7776bm266ibi4uIsGHocPH2b16tWsW7eO6upqAK699lqys7OZNGnSRT/x8YZzt7P06NFDtrMIIa6aO+xwV3Y4nU5PZUdNTc1ZVR3uSRjh4eFnVXW0dKy3UsoTINjtdpxO51nHAwICCA4OJjg4GIPBQFBQ0EVDDV9zOp04HA7P83EHN3a73RNQm81mDh48iE6nO+//MeerJnH/2s0deKenp3fYrS5XyuFwcPToUfLz89m3bx8lJSWUl5dTX19PQ0MD//rXv7j11lt9vcxOTYIPH5HgQwghxJnOt/f8zHLs/5+9/w6P6zrPtfF7D/oMBpiCDhAkWMDei9gAEABRWFQoiRJpWYkcOZbz+3KSnJTzncSfI7fEcZLLPsmJI8ndx3ZsSz62LFMs6IVgJ8UqihJJsaEDM2jTZ/b6/QHtbYAVBFHJdV8XLoozG7PXUDN7r/Ws930ejdOnT/Pqq69y/fp1YmNjefLJJ3nyySeZNm3aHSfQDoeDvXv3smvXLj788EMAMjIy2Lp1K5s3bx6TkmOtnUVRFJKTk2U7i0QieWAGVnZobSwRERFERkZy9uxZXezQrnuKojB37lzWrVvH2rVrmTdv3j1bPFRVxe/34/f7CQaD+jUrLCyM2NhYzGYzZrOZqKgo/SciIuKhvLYdPXoUt9tNZGQkwWBwUEWJVuGiiSbaz8C1pNZ6M3v27Akh+EwUnE4nc+fOJT09fbyH8lBzL+FDbr+MMDLOViKRSCQaQxU7QqEQQgjCwsIIDw+np6eHHTt28NRTTzF9+vTbTiD9fj/19fXs2rWLAwcOEAqFMJlMbNu2jS1btrB48eJRn5jfLp0lNTV1Urn5SySSiYXf76erq4uWlhY6Ojr0yo6+vj6OHDlCQ0MDR44c0X2DLBYLmzZtYu3ataxevVqPp70dA0UOrYpDM4NMSUkhLi5Or+SIjo5+KMWNuxEbG0tfXx+RkZF6y8TdEEIMaqvp6OggMjJS91ExGAxER0cTGRn5yP1b3syj/v4nAlL4GGFknK1EIpE82oRCIV3saGlpuaPYAf2T8KqqKt544w1KSkooKirCZDLxgx/8gClTptwieAghOHXqFLt376aiooKenh4MBgOrV69my5Yt5OXlER0dPSbvUaazSCSSkcLv9+N0OnWxQ/Oj+Oijjzh06BAHDhzg0qVLQP8CcsGCBXr7yty5c+9Y1REKhfD5fPj9fr0ywWQykZqaSnx8PCaT6bbX5keV2NhYgsHgkI9XFEUXSYxGI0IIFi9ejNlspre3V6/WcTqdKIpCVFQU0dHRshpEMi7Ib7lEIpFIJA/IQLFDq+wwGAwYjUYiIiJuOV4IQU1NDW+88QYXL14kOjoaj8dDeHg4qampt0wKr169yp49e9izZw+NjY0AzJgxg5deeolNmzaNeBrBnRiYzpKcnExGRoZsZ5FIJMNCa2NpaWmhvb0dVVXp6urixIkTHDx4UG+7ALDZbGzZsoU1a9awevVqLBbLLa+nVR/4fD69BSMsLIz4+HimTJmC2WwmNjb2kfOeuB8epMpFM3iNj48nMjKS6OhoEhMTmTVrFn19fXryjhaxqigK0dHRREVFyXuIZEyQwodEIpFIJMPgfsUOjatXr/J3f/d3XLhwgaioKJ566im2bdvGnDlzBu1aOp1OysrK2L17N+fOnQMgISGBF198kU2bNpGdnT3q7xH6FxNerxePx0NERARZWVmkpqbKdBaJRHLfBINB3aC0ra2NYDDI1atXOXr0KPv37+f8+fNAf4vEwoUL9QSW23lGCCHw+/14vV69QiQyMhK73Y7dbsdkMhEbG3tPjw/J73mQikGPx4PVar2lRUZRFN0nZcqUKfj9fnp6evT7pyaEREZGEhMTI6tBJKOGFD4kEolEIhkimtjR3t5OS0sLgUBAT2O5m9ih7URqJcGdnZ08/vjjPP3004PM97xeL/X19ezevVv37YiJiWHLli1s2rSJlStXjtkkXlVV+vr6CAaDmM1m5s+fT2Ji4l3fp0QikdzMzV5HbrebM2fOcPToURoaGmhtbQXAbDZTWlpKTk4Oa9asIS4ubtDrCCHw+Xy60KEoCjExMbqRcmxsLEajUVYPPABaNYxmUno/+P1+kpOT73lcZGQkCQkJJCQkMHPmTNxuN93d3TQ3N+tJZCaTaUgeI5MB7f4vGX+k8CGRSCQSyV24m9hhNpvv+rtCCA4fPswbb7xBdnY2n/rUpwD49re/zbRp0wgLC0NVVY4dO8bu3buprKzE5XLpvh2bNm1iw4YNY2oWGggEcLlcCCFISkoiIyMDq9UqFxMSiWTI3Ox11N7ezrFjxzhy5AhHjhzB4/EAMGXKFF544QVycnJYsmTJIK8NzYjU6/UO8ufIzMzEYrFgNpvHxNPoUUJLzNHSc4aKJpTcrgXpXhiNRoxGI6mpqbjdbtra2rh69Sq9vb2YTKZJ/f84GAzS3d1NWloaCQkJ4z2cRx4pfEgkEolEchMPInZoHDt2jNdff52TJ08SHh7O1KlTAUhPTyc8PJzLly/rvh0tLS0AzJ49m82bN1NSUjKmk6Sb21mmTp1KamoqJpNpzMYgkUgmN6FQiO7ubtra2mhububSpUscOnSIw4cPc+7cOYQQGAwGFi1aRG5uLrm5uUydOlUXVVVV1VOiNGJjY5k6dSrx8fFS6BgDFEXBaDTq94Kh4vP5dAHjQTAajUybNo2MjAxaW1v5+OOPcTgcky5lRwihV0xmZ2eTmZkpW3gmAFL4kEgkEomEkRE7oN+b42//9m85duwYYWFhbNy4kWeeeYYlS5bQ3d3Nm2++ye7du/nggw+AfpNQzaR0xowZo/X2bouqqrhcLgKBACaTiXnz5pGUlCTbWSQSyZBQVZWenh7a29tpbGzkvffeo6GhgYMHD9LU1AT0V2kUFBSQk5PD+vXr9aoAVVXxer34fD69YiA2NpbU1FS9dUUakY49sbGx9Pb23tfveL3eQSLWgxIeHk56ejopKSl6BYjT6SQqKmpCtzMJIXC73fh8PqxWK7NmzSI+Pn68hyX5BCl8SCQSieSRZaTEDujvb46MjMRgMNDR0UF+fj7PPvssc+fO5cCBA/zVX/0Vhw8fJhQKYTKZeOKJJ9i8eTPLli0b852gQCBAX18f0G+YOmXKFKxWq9yRkkgk90TbzW5vb+f69eu6MWlDQwMdHR0ApKam8txzz5Gbm8uyZcuIjIzUPTq6urr01pXY2FhSUlL01hUpdIw/JpOJUCh0X78jhBhWm8u9CAsLIzU1lZSUFDo7O7l06RIOhwOj0TimLaD3YqAnVlxcHHPnziUhIWHCCjSPKop24ZGMLBkZGeLGjRvjPQyJRCKR3MRwDUrvxLlz53jjjTcICwvjL/7iL4D+st/29nbKysqorq7G7XYTFhbG2rVr2bx5Mzk5OeNSsu3xePTY3IyMDFJTU4mNjR3zcUgkksmHy+XC4XBw9epV9u/fr4sdWipHZmYmhYWFFBYWMnv2bKBfZPV6vfpC2mg0kpiYiMViIS4uTgodE5D29nZOnTqF1Wod0vGqqtLd3U1ubu6oG5KqqkprayuXLl3C4/FgNpvHtUIxFArR29ure2Klp6fLTYRxRFGURiFExp2elxUfEolEInnouTl69kEqOzQ++OAD3njjDerr61EUhXXr1nHp0iVOnjxJeXk57e3tAMyfP5/NmzdTXFw85InkSKKqKm63G7/fj9FoZO7cuSQlJT00jvkSiWT08Hq9dHZ2cvXqVaqrq6mvr+fgwYP09PQAMH36dLZv305hYSEzZszQfTqcTieKohAZGUlKSgo2m424uLgJtUsvuT33e2/wer3Ex8ePyT3FYDCQmppKYmIi169f5/LlyxgMBsxm85hWVwgh6O3tJRQKkZmZSVpamtxEmATIio8RRlGU7cB2m822vbOzc7yHI5FIJI8sdxM7HmSHyO/384UvfIHq6moAli1bRlpaGh988AEXL14E+g1MN23aRGlpKdOmTRuJt3PfBINB+vr6EEJgs9nIzMzEZrPJnSiJRHJXAoEATqeTjz/+mH379lFfX8+hQ4f09rjs7GwKCgooLCxk2rRp+P1+PB6Pbl5qtVpJTEwkPj6e2NhYWe4/yfB6vezfvx+LxTKk/3dOp5OZM2eOy72ur6+P8+fP43Q6sVgsYxL37vf76e3txWazMXv27GFvnkhGHlnxMcYIId4C3srIyJCKkkQikYwxN4sdwWAQg8HwQJUdGpqHRygUwuFwMH36dMLCwnjvvfc4ceIEcXFxPP3002zevJnFixeP22RfS2cxGAxMmTKF1NRUOTGTSCR3Rbt23rhxgz179lBZWcmBAwdwu90AzJs3Txc70tPTdVPSrq4uoqOjdWE1Li5OmiNPcqKioggLCyMUCg2KF74To+XvMRRiY2NZtmwZH3/8MR9//DERERGjJrZpRr6KojB37lzS09PlRsIkY9jCh6Io84BcIBNIADxAG3ASqBNC3J8dsEQikUgkw+BuYsdITMCvXLnC9773PT7++GOeeeYZ6uvref/99wkEAoSHh7NhwwY2b97MunXrxq19ZGA7S0xMDLNnzyY5OVm2s0gkkjsihKCnp4fW1lb27t1LWVkZ9fX1ehvLvHnzKCoqorCwkOTkZDweD36/n+7ubuLj45k6dSpWq1VWdTxkKIpCTEwMwWDwnsKH3+8nKiqKuLi4MRrdrYSFhTFz5kwSExP56KOPcDqdREREYDQaR6QCZGD1ZGpqKllZWQ8c2ysZH+6r1UVRlAzgc8AfAanawzcdJoAQUAG8BuwSj2A/jTQ3lUgkktFjtNpYBnL9+nW+973vsXv3boQQhIeHEwwGAVi8eDGbN29m48aN4xpVp03IVFXFbrczZcoU7Ha73IWSSCR3xOVy0d7eTmVlJXv27KG2tlZPY5k+fTrFxcWUlJSQmpqK2+3WxWS73U5ycjIWi0V6dTzknDlzBofDcU/fiu7ubtLT03Uz2/FGCIHD4eD69et0dnYycAmqKIp+bxwo1CmKgqqq+rGKoiCEIBQKoSiKniyTkZEhfTwmOCPS6qIoig34EvAKEAFcAf4LOAq0AA4gBrADc4A1wAagBLigKMpfCSH2DPdNSCQSiUQymm0sAxFC8Pd///fs3bt30KQpJSWFrVu3UlpaSkbGHe+rY4LP58PtdqMoip7OMp47bhKJZGKjmZTW19eza9cuqquraWpqAvo9iT7zmc9QUlLC1KlTcbvdehVZYmIiSUlJWCwWWUH2CBEbG0tra+s9jwuFQthstjEY0dBQFAW73Y7dbicQCOByufB4PASDQQKBAMFgECEEqqqiqirQf8+PiIjQq0NCoRBhYWFER0djNBqJi4sbUsuPZOIz1P+LF4Eo4HvAj4UQR+71C4qixAE76K8Q2aUoyn8XQvz7sEcqkUgkkkeO0W5jGUhHRwe1tbXs3r2bU6dOAf3RiyUlJTz55JPMnz9/XMu5hRC4XC78fj/R0dFkZ2eTnJws4yAlEsltCQQCOBwOjh49ym9+8xuqq6v5+OOPAUhISGDnzp2UlJSQnZ2Nx+NBVVW8Xi8pKSm62CEXfI8mQ6noEUKgKMqErYKIiIjAYrGMm/+IZOIx1KvZT4B/FELcW/r7BCFED/Ad4DuKojwFRN//8CQSiUTyqDGWYofX62X37t386Ec/0nc/IyMjWbNmDY8//jgFBQXjPvEPhUL09vaiqipWq5W5c+dit9vHxL1eIpFMLrTr59mzZ3nrrbeorKzkgw8+ACAuLo5t27ZRUlLCggUL8Pl8qKqKz+cjNTVVFzvktUUyFEFdE+Gjo+USTzI5GNJsTgjx5w9yEiHE2w/y+xKJRCJ5uAkGg3R1ddHe3j7qYkcoFOLYsWP89re/paqqSvftMBqNPPvsszz//PMkJyeP6DmHg8/nw+VyYTAYSEtLIy0tjbi4OGkiKJFIBqGZlH744Ye8+eablJeXc/r0aYQQGI1GNm3aRElJCcuXL9fL/QOBgBQ7JHdkqMJHYmKivCdJJg2yfk0ikUgk44Imdgys7Bhpg1INIQQXLlxgz5497Nu3TzfyA7DZbLzwwgs89dRT42pUCv3jdLvd+Hy+Qe0sckdNIpHcjMvl4sqVK7z55pvs27ePY8eOEQqFiIyMZMOGDZSUlLB69WpUVdXFjuTkZNnGIrknUVFRuunnncyyA4HAuN8zJZL7YVhXPEVRwoAoIYT7pscLgCcBN/AdIcTHDz5EiUQikTwsBINBnE4nbW1ttLW16SZiRqNxVCbhjY2N7Nmzh71793LlyhWg38hv4cKFdHR08OlPf5ri4mKsVuuIn/t+uLmdZc6cObKdRSKR3ILP5+PGjRv86le/4t133+Xw4cP4/X7CwsJ47LHHKC4uZv369RgMBoLBIKqqSrFDct+EhYURFRVFMBi8o6mtoiiYTKYxHplEMnyGe/X7V+BPFEVJFkJ0AyiKsgP4Gb+Pt/2soijLhBDXR2CcY46iKH8LPA3MBnzAIeBvhRBnx3VgEolEMskIBAJ0dXXR2tpKe3s7wWCQ8PDwURM7urq6KC8vZ8+ePZw+fRpA70P+67/+a5YsWUIwGMRisZCQkDDi578fZDuLRCK5F36/n9bWVn7zm9/wzjvvcODAATweD4qisHTpUoqLi9mwYQORkZGEQiEMBgOJiYkkJydjtVql2CEZFjExMbjd7tsKH1oiihQ+JJOJ4V4Jc4FqTfT4hFeBLuDPgRTg68BfAv/9QQY4jmwA/pP+yF4F+ApQoSjKPCGEYzwHJpFIJBOdQCCgV3a0t7ePemWH1+ultraWvXv3cuDAAUKhEFFRUWRnZ9PY2IjL5SI5ORmTyURcXNy4xu/JdhaJRHIv/H4/7e3t/O53v+Odd96hvr6evr4+ABYuXEhxcTH5+fmYTCYCgQBhYWEkJCToYsdItwtKHj1MJhM9PT23fS4QCBATEyMjjiWTiuHOPqcAB7S/KIoynf7KiK8IIX76yWO5QCmTVPgQQpQM/LuiKC8C3cA64HfjMiiJRCKZwPj9frq6umhpaaGjo4NQKERERMSoiR3BYJCjR4+yZ88eampqcLvderl3WloalZWVfPjhhyQkJPDiiy/y+OOPk5SUNG7VFLKdRSKR3A2/309nZyd79+7l7bffpra2lu7u/j3G7OxsiouLKSwsxGKx6GKHzWYjJSVFih2SEcdkMhEKhW77XCAQGNcNBIlkOAx3JhoHDJQA1wEC2DvgsXNA/jBf/54oivIskAcsARYDZuBnQohP3+V3Muiv3CgF7EAz8DbwZSGE8x6nNAMG4F7HSSQSySOD3+/H6XTqYoeqqkRERBAbGzsqC3ohBO+//z579+6lrKyMzs5OABYsWEBxcTGlpaVYLBZ+9atfUVlZyWc/+1meeOIJUlNTx03wkO0sEonkTvj9fhwOBxUVFfz2t7+lpqZGN1+eNm0aO3bsoLCwkKSkJN3LQxM7LBaL3HGXjBp3S3aRxqaSychwhY9mIGvA3zcCHuD4gMdigeAwX38o/H/0Cx59wA1gzt0OVhRlBv1VKknAb4EPgFX0t+aUKoqyTgjReZeX+DfgJHDwgUcukUgkkxifz4fT6aS1tXWQ2GE2m0eteuH69eu6Sem1a9cAyMzM5JlnnmHjxo2cPn2aH/zgB0ybNo309HRWrlzJmjVryMjIGBeBQQiBy+XC7/fLdhaJRDIIr9eL0+mkvr6et99+m+rqalpaWoB+8+XPfOYzbNy4kbS0NAKBAAaDAYvFold2SLFDMhZoyS53Qvp7SCYbwxU+DgFPKIqyFfACzwKVQojAgGOygMYHHN/d+O/0Cx4X6a/8qL7H8f9Jv+jxZ0KI/609qCjKNz95rX8APn+7X/zkmPXAeiHE7Wu+JBKJ5CHG6/XS1dVFc3MzDocDIcSoix0Oh4OysjL27t3L2bP9vtI2m42dO3dSWlrK7Nmz2bdvH3/5l3/JjRs3iI2N5caNG8yYMWPcWlpubmeZO3eubGeRSCS43W6cTieHDx/WKzs0ETcpKYkXXniBoqIisrKy8Pl8KIpCXFwcaWlpWK3Wu+6+SySjQWRkJEKIWx4XQiCEICYmZhxGJZEMn+EKH/9If2ztbz/5u0q/cACAoijRQA7wqwca3V0QQuhCx70mt59UexQDV4Bv3/T0q8DngBcVRfkrIYTrpt/9FrADyBdCXH7wkUskEsnkwOPx3CJ2REZGjqrY4Xa7qa2tZc+ePRw+fJhQKITRaGTz5s1s2rSJlStXEh4ezrFjx9ixYwdXrlzBaDSyY8cOnn76aaZNm4bBYBiVsd0Nn8+H2+1GURTS0tJIT0/HbDbLdhaJ5BFFq/pyOp289957/O53v6O6uppLly4B/SLu9u3bKSoqYs6cOfh8PqB/l3369OnY7Xa5sJSMK1FRURgMBt2cXEOLuJWfT8lkY1jChxDijKIojwF/+MlDvxRCHB1wyFKgCvj5A45vpNC8RsqEEOrAJ4QQvYqiNNAvjKwGKrXnFEX5N+B5+kWPD8ZqsBKJRDJeaLuSzc3NdHV1IYQgKiqK+Pj4URMUgsEghw8f1k1KvV4vYWFhrFmzhk2bNpGXl0d0dLS+8ySEwOv10trayrPPPsvTTz/NzJkzx1zwuFM7i9yZlUgeTYQQ9Pb24nA4OH36NPv27aOmpob3338fALPZzBNPPEFJSQkLFy4kEAjo8bMzZ84kISGB2NjYcX4XEkk/BoMBo9GoG+lq+P1+4uPjpbAvmXQM22ZfCHEG+Os7PHcQ2Dbc1x4FZn/y54d3eP4j+oWPbD4RPhRF+TbwIvAU4FQUJeWTY/uEEH03v4CiKH9Jf3wvgDT8kUgkkwaXy4XD4aClpYXu7u4xETtUVeX06dPs3buXiooKurq6AFi0aBGbNm2iqKgIi8UC9C8m9u/fz+uvv87OnTtZsGABU6ZM4Qc/+AHTp08f8zaSYDCIy+UiFAphs9nIzMzEZrPJdhaJ5BFEVVV6enro6OjgwoULlJeXU1tby6lTp/R2gE2bNlFcXMzKlSvx+/2EQiFUVSUjI4OkpCS5iJRMWMxmM+3t7YP8qfx+P1ardRxHJZEMj5HPF5yYaCpE9x2e1x63DHjs//fJn5WDD+XLwJdufgEhxDeBb2p/z8jIuLUpTiKRSCYAQgj6+vpwOBw0NzfT19eHEILo6OhRFTuEEHz44Yfs27ePffv20draCsD06dPZsWMHpaWlZGRkDDr+8OHDvPHGG5w5c4aIiAiuXLnC4sWLSU1NHXOhYWA7S3p6up7OIpFIHi1CoRDd3d10dHRw6dIlampqqKmp4fjx44RCISIjI9mwYQMlJSWsXbsWVVXx+/34fD6Sk5NJTk7GarVKsVQy4TGZTDQ3N9/yuKxMkkxGhiR8KIryrBBi2H4diqKkAtM+qQSZFAghpPQukUgeGgaWYDc1NeFyuVAUhejoaCwWy6juNl6/fl0XOz7++GMAUlJS+MM//ENKS0uZOXPmLee/fPkyX//613nvvfcIDw+ntLSUZ555hkWLFo3pYmFgO0tMTIxsZ5FIHlGCwSBdXV20tbVx7do1GhoaqKmp4ciRI3rM7OrVqykuLiY3N5fw8HC8Xi8+nw+73a6blMpEFslk4mYfj1AohKIomM3mcRqRRDJ8hlrx8aaiKO8B/wy8LYTwDeWXFEWZTX9SyueAf2L8omC1io479Z9oj3c96IkURdkObLfZbA/6UhKJRPJAaCXYnZ2dNDc34/F4UBSFmJgYrFbrqIodHR0dlJWVsW/fPs6dOweAxWJh+/btlJSUsGjRottWlgghUBSFYDDI+++/z8aNG3nmmWdYunQp4eFjV6Qo21kkEonf79fFjqamJg4fPkxtbS0HDhzQr6crVqyguLiY/Px8YmJicLvdBINBoqOjmT17NgkJCdIEUjJpuTmC3efzYbFYpIAnmZQMdRZZCHyLfrPSbkVRfgs0AMeAZsAJRAN2YA79JqElwAogAPwb8L9GcuD3yYVP/sy+w/OzPvnzTh4gQ0YI8Rbwlmx1kUgk44FWgq2JHT6fD4PBMCZiR09PD1VVVezbt49jx44hhMBoNLJlyxZKSkpYtWrVHcWL999/n9dff50VK1aQl5dHVFQU3/nOd8jOziYiImLUxnwzXq8Xt9tNWFgYaWlpsp1FInnE8Pv9OJ1OWltbaW1t5cSJE9TV1VFfX09vby/Q70VUXFzMxo0biY+Px+VyoaoqoVCI6dOnk5iYSGxsrPTtkEx6NOFD25Tw+/1MmTJlnEclkQyPIQkfQohqRVGWAjuB/wf4A/qNP++EQn/1xL8B/y6EuPJgw3xgtOjbYkVRDAOTXRRFMQPrADdwaDwGJ5FIJA+CVoLd3t5OW1sbfr9fd2M3mUyjem6v10t9fT179+6loaGBYDBIRESE3t++fv36W3aMBvLRRx/x+uuvU1tbi6IoWCwW8vLySE1NHbMdJVVVcbvdejvL7NmzZTuLRPIIoYkdLS0ttLW1cfbsWerq6qitrcXpdAIwe/ZsiouLKSoqIjk5Wa8I83q9g0xKxyNOWyIZLaKiooiKiiIQCBAZGYkQQra5SCYtQ64bFv05gv8F/NcnLSwbgfVAJv2VHh6gDTgN1ABVQgjPSA94OAghLimKUkZ/csv/A/zvAU9/GTABbwghXA96LtnqIpFIxoKBJdjt7e0Eg0HCwsIwGo2jbjoWDAY5dOgQ+/bto7a2FrfbjcFgYOXKlZSUlJCfn3/PiVFHRwf/+q//SkVFBQCPPfYYzz//PKtXrx4zwSMQCOByuRBCDGpnkQsXieThR7uGtrS00N7ezgcffEBdXR01NTW0tbUBMHXqVLZv305xcTGZmZm6QNrb20tycjIpKSlYLJYxbcOTSMYai8WCw+EgLCwMg8FwSxWkqqoEg0H9JxQK6clF2p9CCFRVRVX79561ChKDwaD/3Px37XxhYWGEh4frf0okw0Xp1zMmH4qiPEV/1CxACv2tNZeB+k8e6xBC/PWA42cAB4Ak4LfAeeAxIJ/+Fpe1QojOkRpfRkaGuHHjxki9nEQikeDz+fQS7M7OTkKhEOHh4RiNxlGfDKiqyqlTp/T42e7ufuukhQsXUlJSwsaNG0lISLjn62iTnc7OTrZv386sWbPYsWMHa9euHbMKC4/Hg8fjITw8nPT0dFJTU+UOlkTyCBAIBPTKDi2Rpb6+nurqarQ5W1paGsXFxRQXFzNz5kx8Ph9erxcAm81GWloaNptNehxIHlqEELqIEQgEaGpq4sKFC4SFhREREUFmZqZu3Ov3+3WxQ2vt0v4cuMbU7v13ev5mFEW55XlFUQgLCyM6OpqYmBhMJhNGo5GYmBiMRqOs0pSgKEqjECLjjs9PYuHjS8CrdznkqhBi2k2/MwX4ClBKf5VKM/Ab4MtCCOdIjk8KHxKJZCTweDw4HA5aW1txOBwIIYiMjCQmJmbUjTaFEFy4cIF9+/ZRVlY2KH62tLSU4uLiQfGzd6OpqYnvfve7mM1mnnnmGQC6u7vJzs6+ayvMSKGqKi6Xi0AggMlkYurUqSQmJsrFi0TykHOz2HHt2jX2799PTU0Nly5dAiAhIYGioiJKSkqYP38+fr8ft9sN9Md2pqenS5NSyUPDwHhlTdjzeDy43W5d0AiFQrrwEAgEaGxsRFVVkpKSsFgseiWGVpWhVWyM9ri1apJQKHSL4BITE4PNZsNqtWI2mzEajdJn5xFjVIUPRVGmAomAANqFENeG/WIPGVL4kEgkw0GLT9Um6lplhSZ2jEUbxrVr1ygrK2Pv3r1cuXIFgNTUVEpKSvT42aHS2trKD37wA95++21CoRBLly7lC1/4AsnJyWOyiBjYzpKQkMCUKVOwWq2ynUUieYjRxI7W1lba29tpaWnRxY7z588DEB8fT2FhIcXFxSxdulS/9oZCIaKjo0lPT5cmpZJJTTAYxOPx6MJGb28vvb29eDweQqHQoGM1EUNrKQkLCxv0ub9+/Tper5fp06dPyHQzIYQu5mjvLSYmhuTkZGw2G/Hx8RNy3JKRZcSFD0VREoC/o9/oNOmmp1uBnwFfF0I47nOsDwUDPD62d3aOWOeMRCJ5iBFC0Nvbi8PhoLm5GZer324oKiqK6OjoMVmkNzU1UVZWRnl5ORcu9AdhWa1WfRd00aJF9zX593g8fPvb3+bXv/41fr+f2bNns3PnTjZs2DDqHiRCCH2iFx4ezpQpU0hNTR11o1eJRDJ+BAIBurq6aG1tpa2tjY6ODg4cOEBtbS0nT54EwGQykZ+fT3FxMatWrcJgMOi+HeHh4aSkpJCcnKzvaEskkwEhBD6fD7fbjcvloqenh56eHtxu96B2kfDwcCIiInRx437u6VoFyGTx2NCEEI/Hg6qqREZGkpaWRlJSEnFxcVLMfEgZUeFDUZRZQDkwhf7kliDQ+cl/2+g3SxXAVWCjEOLy8Ic+uZEVHxKJ5G6oqkpPTw8dHR20tLToPeTR0dFER0ePyU25tbWViooKysvLOXv2LABms5kNGzZQXFzMypUrhz3J8Xq97Nixg6ioKHbu3ElhYeGo+2iEQiFcLhfBYBCz2UxmZiaJiYljGocrkUjGjoFiR3t7O11dXRw8eJDa2lqOHTuGqqpERUWRm5tLcXExa9euJTIyEq/Xq19z7Xa77tshrxWSyYDP58PlctHX10dXVxddXV34/X79eU3giIyMlALeJ2jta6qqYjabmTJlimx3fQgZMeFDURQD/XGvK+hPbfkasF8I4f/k+SggB/gCkAccEkKsfaDRT2Kk8CGRSG4mGAzS3d1NR0cHra2t+Hw+DAYDMTExREZGjonY0dnZSWVlJeXl5bz33nsAGI1G8vLyKCoqGnaqSnd3Nz/96U9pbW3l5ZdfBsDpdDJ9+vRbHOBHGr/fr1fJJCcnk56ejtVqlTs6EslDyM1iR19fH4cPH6a2tpZDhw4RDAYJDw9n7dq1FBcXk5ubi9FovGXhI307JJOBYDCIy+XC5XLR1dWF0+nE4+kPzdQ8vyIjI4mIiJD3vCEwsCI0LCyMtLQ00tLSRn2eIhkb7iV83M9WXjH9osebwE5xk2IihPABFYqiVAK/BJ5RFKVICFE+jHFLJBLJQ4E2SW9ra6OtrY1QKKSLHWPVetHV1UV1dTVlZWUcP35c3wXduHGjvgs6XIPRvr4+/uu//ouf/exnuFwuMjIy8Hq9pKamMnXq1BF+J79HCKEbsUVFRTF9+nRSUlIwGo2jdk6JRDI+3Cx2eDwejh07Rl1dHfv378fn8xEWFsbKlSspLi5mw4YNxMXF6VVgDoeDqKgopk6dSlJSEmazWS4SJRMO7b6mtas4HA56e3tRVVVPNImKisJisUy6z68WZTvwR2u7Gcv3oigKMTExxMTEEAwGaWpq4vr169hsNqZMmYLdbpdeIA8x91Px8V3g00CmEKL9HscmAdeAHwshXnngUU4ipMeHRCLxer36JH2sY2c1ent7qampoby8nMOHDxMKhYiIiGDdunUUFRWRk5PzQCKBqqr8+Mc/5ic/+Qk9PT2kpKTw/PPPs3nzZux2+wi+k8GEQiH6+voIhULEx8czdepU7Hb7pOk7lkgkQyMYDOJ0OnXR2Ov1curUKerr66mtrdWrvJYuXUpxcTGFhYXYbDZUVcXj8ehiSFJSEqmpqVgsFrmgkUwogsEgfX199Pb24nQ6cTqdBAIBoH+BHhUVRWRk5IT53IZCIXp6enA6nTgcDrq6unA4HPrYNaHG5XLpAo7b7b7Fa+RmIiIiBv1ERkbqcyaz2UxsbCxms5m4uDgSEhJISkoa9POg93/N2Njv9xMdHU1GRgZJSUnSF2wSMpKtLscBpxBi4xCPrwDihRArh3SChwzZ6iKRPFq43W49icXpdI5p7OzAMdTV1VFWVsbBgwcJBAKEhYWxevVqioqKRtRYNBQK8corr9DU1MT27dt5/PHHSUhIGJHXvh1aT7PBYCA1NZW0tDTi4+Mn3a6XRCK5MzdXdvh8Ps6fP09dXR3V1dV6ytW8efMoLi5m48aNpKSk6OaOWguAxWIhPT0du90ue/glEwav10tfXx/d3d04HA56enp0QSAiIoKoqKhx8Znxer20tLTQ2tpKS0sL7e3ttwgampeIqqp3fB1FUTCZTLf8xMTEEB4ersfeaj/BYBC/308gENB//H6//vjAJJo7rVcjIiLIyspixowZzJw5kwULFjBv3rxht7BpJrHQb/CekZEhN1cmESMpfLQBPxdC/PkQj/83+ltibk5+eSSQwodE8nAjhKCvrw+Hw0FLSwu9vb3A2MbOQv+EZf/+/ZSXl+sl3waDgRUrVugl3xaL5YHP4/f7+fWvf82hQ4f4m7/5G303NjU1leTk5Ad/I7dBVVU9cSE6OprMzEySk5OH3ZYjkUgmHjeLHYFAgI8++oj6+noqKyvp6OgAYMaMGRQXF1NSUkJGRob+uy6XC1VVMRqNZGRkkJCQIHdqJeOO5iXR29tLV1cXHR0d+oIa+o3Mx6qaQwiBw+Hg2rVrXL16levXr3Pt2jUaGxtpbW3VBcXbYTabsVqt2Gw2rFbrLT8DH4+Pjx8VgUCbC3R3d9Pe3k57ezttbW20trZy7do1Ll68SEtLi358WFgYM2bMYOHChSxcuJDly5eTmpo6rHP6/X4iIiIGJcJIw9iJy0gKH17gG0KIV4d4/JeB/yGEeCRdo6TwIZE8fKiqSm9vL52dnTQ3N+N2u1EUZUyTWKBfhDh48CBlZWXU1dXh8XhQFIWlS5dSVFREQUHBiLWbBAIB3nnnHb7//e/T1taGxWLh61//OllZWdjt9lF5z1r5rxACq9VKZmYmNpttwpT7SiSSB0MTTjWxIxgMcu3aNerr6ykvL6epqQmAKVOmUFxcTFFRETNnzgT6q83cbrduYqotSGQFmGQ8GSh0OBwOOjs78Xg8CCF0b46oqKhR/4x2dnZy8eJFPvroIy5evMjly5e5evWq3hqmERYWRnJysh7hPPAnKSkJu92OxWKZNElHfX19XLhwgbNnz3L27FlOnz7NQMuBrKws1qxZw/r161m2bNl9CTQDBdaYmBjS0tJITEwkNjZWXnMmGCMpfKjAl4QQXxni8a8Cfy+EeKRmqtLjQyJ5uAiFQnoSS0tLCz6fTzfHGotJjEYwGOTIkSOUlZVRU1NDX18fAAsXLqSoqIiNGzeSlDSyBXa7d+/m9ddfp6mpibi4OLZt28aTTz7JlClTRvx9D3RaDw8PJz09ndTU1FGPwJVIJGNDMBjUKzva2toIBoO0t7frYselS5cASEpK0is75syZg6IoCCHweDx4vV4MBgOJiYmkpqZitVplCbpk3NBaMbq6unTTXU3o0Co6RmuOIITgxo0bnD17lg8++EAXOhwOx6DjEhMTmTp1KpmZmYN+0tPTJ42oMRyEELS2tnLq1CkOHTrEwYMH9eoxm81GYWEhRUVFLFmy5L4qOLRWGCEEcXFxpKWlyXSoCcRICx+vCiG+OsTjH0nhQ0NWfEgkkxet9ForpwwGgyiKgtFoHNN+8VAoxPHjxykvL6eqqkovR50zZ46+C3q/5ZtDRQjBq6++Sl1dHU8++STbtm1j6tSpIz6JU1WVvr4+gsEgJpOJzMxMkpKSZF++RPIQoIkdWlm6JiQ3NDRQUVHBmTNnAIiPj2fjxo2UlJQMWohoYqh2jLbIiIqKGrf3JHl0GU+ho7e3l3PnznHmzBm9qmFgi0pUVBQzZ85k1qxZg/6Mj48flfFMNoQQfPTRR1RXV1NeXs6VK1eAfmFo48aNbNmyhTlz5tzX63m9XrxeL9AvpqSlpWG32x9qQWmiM9LCx9AOHoAUPiQSyWTg5iQWVVUJCwsjJiZmTG9ioVCIU6dO6WKHVjmm9bcXFRWRmZk54udVVZWqqip+/etf84UvfIFgMEhPTw9Go5GsrKwR72n1+/166W1SUhIZGRlYLBbZOyuRTHJCoZB+LW1tbSUYDOL1ejl8+DDl5eUcO3ZMLxnfsGEDJSUlrF69Wq/cuNm3Iz09nYSEhBEzZpZIhorWuuJ0Ogd5dBgMhlFtXQkGg1y8eFEXOM6cOcPVq1f158PDw5k9ezYLFixg4cKFzJ07l4yMDNkOOkSEEFy8eJGysjLKyspobGwEIDs7m8cff5zS0lKsVuuQX2+gH0hYWBgpKSmkpKTIOc04MNLCx/0ipPAhkUgmKhMhiQX6FwonT56koqJikNiRmZlJSUkJRUVFTJ8+fVTOLYSgrq6ON954gw8//JDo6Gi++MUvsnDhQlJSUkb0pi2EwO124/P5iIyMZMqUKaSkpDxQrK5EIhl/tEqOtrY2Wlpa9FSGEydOUFlZSUNDA4FAgIiICNauXUtpaSk5OTm6UbHm26Edo5kmS98OyVhysxmpy+UaE4+OtrY2Tp8+rVd0nD9/Hp/Ppz+fnp7OggULdKEjOztbVkWOEEIIzp07xzvvvENZWRl9fX2Eh4eTk5PD448/ztq1a++rnS4YDOJyuQiFQrrhcmJiopznjBEjJnxI7g8pfEgkE4+JksQC/RP99957j4qKCqqrqweJHYWFhWzcuJHs7OxRnfQfOXKE//iP/+D9998nMjKS0tJSnnnmGebMmTOiwk8oFKK3txdVVbFYLGRmZsp4OIlkkjNQ7GhtbSUQCKCqKufOnaO8vJza2lrcbveglKmCggLi4uIApG+HZNzx+XyDWlc0ocNgMBAdHT0qQodWzXHq1ClOnz7NqVOnBiWSmEwm5s+fz8KFC3Wx436qDyTDx+v1UlNTw+9+9zuOHDmCEAK73c7mzZt56qmnmDp16n2/3sBWvdmzZ+vXP8noIIWPcUIKHxLJxEBVVXp6enA4HOOaxAL9E56BYodmQpaZmcnGjRvZuHEjs2bNGrMxvfbaa/z4xz+muLiYZ555hgULFoyo4OH1evWFT1paGmlpacTFxckdXIlkknI7sQPg4sWLVFRUUFFRofsOLFiwQK9YS0hI0F9D+nZIxouBQkdHR4duEq7NCUZD6Ojt7eXMmTO6yHH27Fn98w8wffp0Fi9erEevTp06VbZHTABaWlrYtWsXu3btQlvPrVmzhueee461a9fe11xJVVXa29tZsmQJaWlpozVkCVL4GHNkqotEMv5MlCQW6Bc7Tpw4oYsdTqcTgGnTpulix4wZM8ZkTCdPnuQHP/gBf/mXf4miKHg8HlwuF4sXLx6xHVZVVXG5XAQCAYxGo25WKhc1EsnkRFVVfUe8paWFQCCAoijcuHGDyspKysrKaG1tBfoXcSUlJZSUlJCR8fu5581xkBkZGdK3QzLqBAKBQRUdWpWnoih668pIiwzNzc0cP35cr+i4fPky2lorOjqa+fPns3jxYhYtWsSiRYtkBcAERwjB8ePHeeutt6ipqSEUCpGWlsazzz7LE088gcViGdLrOJ1O5s2b90gLH0IIzGYzly5dIjk5eVTOIYWPcUJWfEgkY8tESWKBfrHj+PHjVFRUUFNTo4sdWVlZbNy4kcLCwjETOwDOnj3L66+/zqFDhzAYDPzZn/0ZOTk5pKWljZhx60Cz0oSEBDIyMrDZbHLnSiKZhKiqSnd3ty52+Hw+wsLC6OzspLKykr179+pmi6mpqbrYMXPmTP26diffjri4OHldkIwKqqrS29urf3a7u7tRVXXUhA4hBE1NTRw/fpwTJ05w/Phxmpub9eeTk5NZtGgRixcvZvHixcyaNUu2cU1iWltb+c1vfsOvf/1rHA4HUVFRlJSU8Nxzz90zEeZRFD40oePy5cskJSVx+fJlVqxYcUvk8kgihY9xQgofEsnoM1GSWKBf7Dh27BiVlZVUV1fT1dUF9O+Aap4dM2bMGNMxXbx4kW9/+9vU19ejKAo5OTls376d5cuXj4gYNNCsNCIiQjcrNZlMIzB6iUQylmhtge3t7TQ3N+Pz+TAYDLhcLqqrqykrK+P9998H+qMbtfjZRYsW6WLHzb4dCQkJpKWlSd8Oyajh8Xjo7u6ms7OT9vZ2gsEg0O/dFR0dPaLtm0IIGhsbOXbsmC50aNVO0N+2unz5cpYvX86SJUtISUkZsXM/LAxcdw7c/NEenwytsH6/n6qqKt58801Onz4NwKJFi/jUpz5Ffn7+bT9zj6LwcfnyZVavXk1bWxsA77zzDt/4xjdoaGgYtXNK4WOckMKHRDI6TJQkFvi92KG1sWi97dOnT9fbWEYrjWUovPPOO3zlK19hzZo1PP/886xatWpEBI+BZqXx8fFkZmaSkJAgFzYSySRDEzs6Ojpobm7WBYtgMMj+/fvZu3cvx48fRwiByWSioKCAkpISVqxYMej77vP5cLvdCCGIi4vTI2i11BaJZKTQota7urpoa2ujr68PIQQRERFER0eP6KaHEILr168PqujQFnHQ37K6fPlyli1bxvLlywd52TzMCCFQVZVQKHTLz92ECyHEPYWN2x2jKAo3r1cNBgNhYWH6T3h4+LhUkn3wwQe8+eab7Nu3D5/PR2ZmJn/4h3/Ili1bBl0jHzXh4/z58yxdupRQKERUVBRz585l27ZtnDx5EqPRyNtvv01aWhq/+93vRnRTUAof44QUPiSSkeHmJJaenh4URRmXJBbon3QdPXpUb2PRxI4ZM2boYkdWVtaYjknjypUrfOc732Hnzp3ExcWhqio3btxg5cqVI7IAkWalEsnkRwgxSOzweDwYDAYMBgOHDh1i3759NDQ0EAwGiYyMZP369ZSUlLB+/fpBXj0DYxujo6NJT08nMTGR2NhYeU2QjBhaFZFmqqtVd46GIakQgqtXrw4SOjo6OvTnp0+frgsdy5Ytw263j8h5JwKakBEMBu8pZGgRv5rYpP1ERUURGRlJeHg44eHhuihhMBhQFEV/rdsJGTe/viauDBRYtLEFAgH8fj9er1c3S/b7/bdUkwwURUZbGHE6nfziF7/gl7/8JX19faSlpfFHf/RHbN26lfDw8HsKH+fOnePrX/861dXVdHR0YLfbyc/P5+/+7u+YP3/+fY/nwIEDlJWV8Rd/8RdD8iHp6+vjX/7lXzh8+DBHjhzB6XTywx/+kJdeeumWYz/66CO++MUvsn//fhwOB5mZmXzqU5/ir//6rwfF9n7961+nubmZf//3fwfgU5/6FHV1dbz11lusWrWKnTt3MmvWLP7hH/7hvt/fnbiX8CG35yQSyYRD24Xs7OykpaVFd0CPjo7GarWO+aQ6GAxy5MgRKioqqK2t1cWOmTNnsnPnTjZu3Mi0adPGdEwDuXHjBt/97nfZs2cPqqpit9t59tlnSUlJeWARRlVV+vr6CAaDGI1G5syZI81KJZJJhiYgd3Z20tjYqF9TIyMjOX/+PHv37h0UP7tq1SpKS0vZsGHDIANSVVVxu934/X7Cw8NJSUkhJSUFi8UifTskI0YoFNLT2FpbW3G73QBERERgMplGrLpQCMGVK1c4fvy4LnYMDCaYMWMGBQUFutBhs9lG5LzjgRCCQCBAMBjUfwbOpRRF0YWMmJgYYmJiiIyMJDIyUhcPBooI41VhcSeCwSA+n0//0QQR7UerSNOIiIggMjKSiIiIEZlTWq1W/uRP/oQXX3yRX/7yl/zsZz/ja1/7Gj/84Q95+eWXWbNmzR1/99e//jU7d+7EZrPx8ssvk5WVxZUrV/j+97/Pr371K37xi1+wbdu2+xrPgQMH+PKXv8xLL700JOGjo6ODr3zlK2RmZrJ48WJqampue9z169dZtWoV8fHx/Omf/ik2m42DBw/y6quvcvz4cX7729/qx54+fZqCggL972fPnuVrX/ua/m8xa9asuwpgo4EUPiQSyYQgGAzqhmStra34/X4MBgMxMTFYLJYxFzsCgcAgsaOnpwfov1BPBLED+o22vvvd7/K73/2OUCjEwoUL2blzJ+vXrx+kug+HgWalSUlJpKenY7VaJ9RERyKR3B2Xy0VnZydNTU309vbqJo9Xr15l3759lJeX635ECxcu1ONnB+5kCyHw+Xy6WGKz2UhPT8dms425l5Lk4cXr9epzgI6ODn1hHh0dPaJzgKamJo4ePcqxY8c4evTooIqOWbNmUVRUpAsdQ03smEioqkogENB/BhIZGYnJZCI2Nhaj0ahXaGg/k7ldVRNj7uQxFgqF9AoRl8tFV1cX3d3d+jxHuzZGR0c/0GctNjaWl19+meeff55f/OIX/OxnP+MrX/kKaWlp/Pu//zvPPPPMoOMvXbrEiy++yPTp06mrqyMxMVF/7s///M/JycnhxRdf5PTp06PaOp2amkpzczMpKSkcO3aMlStX3va4n/zkJ3R1dbF//369EuVzn/scqqryf/7P/8HpdGK1WoF+4eMv/uIvgP45/oULF9i8ebP+WufOnePpp58etfd0OybvJ1wikUx6fD4f3d3dtLa20t7eTigU0s1JxyPmMBAIcPjwYSorK6mpqdGj77Kzs3nhhRfYuHEjU6dOHfNx3YkbN27w9ttvM3fuXHbu3EleXt4DGYsONCuNjIxk+vTppKSkPLCIIpFIxg6Px0NnZyfNzc16dVp0dDSdnZ3s27ePffv26ckTWVlZ7Ny585b4WRgcQWsymcjOziYhIUFeDyQjghACl8ule3Z1d3frXh0xMTEjtgjv6Ojg2LFjutDR2NioP6e1qK5YsYIlS5ZMOqEjGAzi9/v1Ng8hhL5hZLPZiIuLIyYmRm9FGeuEu4lEWFgYJpMJk8mE3W4nMzMTIYQuhGiiW1dXl/45NBqNw/aOi42N5bOf/Sw7duzgF7/4Bf/1X/81SNTQ+Jd/+Rfcbjff+c53bnk+ISGBN954g7y8PP75n/+Z119/XX+usbGRv//7v2fPnj10dnaSlpZGaWkp//Zv/8Y//uM/8uUvfxlgUNXvxx9/fMcNu6ioqCGZ8WqbgDfH0aampmIwGPTPmN/v56OPPmLBggUAfPjhh9hsNpKSkvTfOX36NF/60pfuec6RRAofI4yiKNuB7ZO5HE4iGU08Hg9dXV20tLTgcDhQVXXEy1fvB7/fz+HDh/XKjr6+PqBf7HjxxRfZuHEjmZmZYz6u2+FwOPjRj37EihUrmDp1KgkJCfzzP/8zK1euxGw2D/t1g8EgfX19qKqK1Wpl9uzZ2O32Sb37I5E8Sni9Xl3s0Co4oqKicLlclJeXs3fvXi5dugT0T1j/4A/+gNLSUmbNmjVod1NVVVwulx5Bm5GRQXJyMvHx8dK3Q/LAaG2sDoeD5uZm3G63vtMeHx8/IhWFPT09nDhxgqNHj3L06FEuX76sPzdlyhS2bdvGypUrWb58+aTy6FBVFb/fj8/nQ1VVoH8xbzabSU1NxWw2ExMTg9FolPfuIaIoit7Wk5CQwIwZM3Q/mdbWVjo6OhBC6NUxw0ETQB5//HFmzpx5y/O/+93vmDZtGjk5Obf9/dzcXKZNm8a7776rP9bU1MSqVavo6uric5/7HHPmzKGxsZFf/epXuN1unn76aT788EN+/vOf861vfUs33b2d8HK/bNiwgW984xu8/PLLfPnLX8Zut3PgwAFee+01/uzP/kzffNM2Dv1+PyaTibNnz7Jo0SL9dXp7e2lsbGTevHkPPKb7QX4zRhghxFvAWxkZGdI1ViLh973lTqeT5uZm/WIYERGB2Wwe8yQW6F8kHDhwgMrKSvbv36+XOs6ePVs3KJ0yZcqYj+tOdHV18ZOf/IRf/vKXeL1empqa+G//7b9htVoH9U/eD9pOh8fjITw8nIyMDH3yJBc4EsnEx+fz4XQ6aWpqwul0oqoqUVFRhEIhKisr2bdvnx61GB8fzzPPPENpaSmLFy8etMDUrgVerxdFUbDb7aSlpWGz2eQCSvLAaG2sHR0dtLa26jHJI+XZFQgEOHPmDAcPHuTw4cOcP39e9w1ITExk8+bNrFy5khUrVpCamjoSb2lMCIVC+Hy+QaadsbGxZGRkEB8fj8lkwmg0yvbTEUYTQlJSUvB6vbS1tXH16lUcDgdGo3HYRvG3q7bp7u6mqamJJ5988q6/u2jRIt555x16e3sxm8387d/+LS0tLRw+fJgVK1box33lK19BCMGiRYtYtmwZP//5z3nqqadGtC27tLSUr371q/zjP/4j77zzjv74F77wBb72ta/pf7fb7ezcuZPMzEzmz59PcXHxIOHj7NmzZGdnj3kVkryjSSSSEedmc1LNmCw6OnrEdnXuF5fLxf79+6mqqqKhoQGv1wvA/PnzKSgooLCw8JZS7/Gmr6+Pn/70p/zXf/0XbrebzMxMduzYQXFx8bBLckOhEH19fYRCIcxmM/PmzSMxMfGRLoGVSCYLfr9fF5G1dIvIyEgMBgP79+9n3759HDlyhFAoRExMDKWlpZSWlvLYY4/d4sfh9/txu92oqorZbGb27NkkJCQQExMzTu9O8rAQCATo6urSPbuCwaDexvog7ZjQL9Rdu3aNQ4cOcejQIY4fP67PMeLi4sjPz2fVqlWsXLmSzMzMSSHkCyF0c07Nl0NRFOLi4pgyZQpxcXHExsbK+/QYEx0dTWZmJmlpabS2tnL58mU6OzuJjY0dEYN3bSPwXhW72vM9PT2YTCbefvttHn/88UGih8ZYfN6nTZtGbm4uzzzzDHa7nXfffZd//Md/JCUlhT/90z/Vj/vxj3/Mj3/849u+xpo1azhz5syoj/VmpPAhkUhGhIHmpG1tbSO+qzMcenp6qKuro6qqikOHDuH3+1EUhcWLF1NQUEBBQcGQehrHC6fTyY9+9COSkpJ45ZVXKC0tHXZp7sAo2pSUFNLS0sbFNFYikdwfgUBAFzs6Ojp0sSMqKorDhw+zd+9e6uvr8fl8hIWFsXbtWkpLS8nNzb1FxAiFQnoEbUREBFOnTiUpKUlWekkeGJ/PR1dXl94ioKoqYWFhI9J60dPTw9GjR3WxQ/OoCQsLY9GiRTz22GOsXr2auXPnjksV6f2ieXP4fD79sYiICKxWK1arFbPZTGxsrKy4miCEh4eTnp5OcnIyLS0tXL58mb6+Psxm8wOJUZqgoQkgd2KgQNLe3k5PT4/unTHW/OIXv+Bzn/scH374ob5Z+PTTT6OqKv/v//v/snPnzgndQia/URKJZNhoE522trZbzEkfdFdnuHR1dVFTU0NVVRWHDx8mFAphMBhYvnw5BQUF5Ofn6/2OEw2Px8Obb76J1WplxYoVqKrKV7/6VZYsWTKs3syB/foxMTFkZ2eTnJw87FJNiUQyNmg75q2trbS1telChdFo5OTJk+zbt4/Kykrdk2jZsmWUlpZSUFBwSzWYqqp4PB5djE5OTiYlJQWr1TopFomSiYvX66Wrq4vm5uZBnl2xsbEP9NkKBoOcPXuWw4cPc+jQIc6dO6f7WkyZMoXt27fz2GOPsWLFinExQr8fQqGQLnJoBqTh4eHExcWRnp6O2WzGZDIRExMjxccJjtYWnJKSQlNTE5cuXcLlchEXFzesz3t8fDypqal6S+KdOH36NOnp6cTFxenpWuPFf/7nf7J06dJbKqSfeOIJfvSjH/Hee++xcePGcRrdvZHCh0QiuS/cbjdOp5PW1la9r3w8zUmh37W9urqaqqoqTpw4oQswjz32GAUFBeTl5enxWhMRn8/H//2//5cf/ehHOBwOsrOzWbRoEbGxsWzcuPG+J0MDo2gTEhLIyMjAZrPJXmCJZAITDAZvETu0JIILFy6wd+9eysvL9fjN2bNnU1paSlFR0S2VazdH0FosFmbNmoXNZhuREm3Jo4tmUK6JHUIIIiMjH9izq6WlhYaGBg4ePMjRo0f1e1hsbCx5eXmsXr2axx57bMK1pA5ECEEgEMDn8xEMBgEwGAyYzWZSUlKIi4vDaDRKb45JTnh4OJmZmSQlJXH16lWuXbumC373O1/bunUr3/3ud9m/fz/r16+/5fn6+nquXLnCK6+8AvT71sTFxXH27Nm7vu5oiWitra23nU9rLVra536iIoUPiURyVzRzUofDQUtLC729vQghiIqKIi4ubtxu3i0tLVRVVVFVVcWpU6f0yde6desoKCggNzeXuLi4cRnbUAkEAvz2t7/l+9//Pu3t7VitVv74j/+YrVu3kpaWdl83LlVVcbvd+P1+oqKiZBStRDIJ0MSOtrY2WltbdbHDaDRy48YN9u3bx969e7l+/ToAGRkZfPazn6WkpGRQTKHGQN8Ok8nErFmzSEhIGLcKPMnDgcfj0ZNYtLjPB01iCQaDnD59mv3799PQ0KCnDhkMBhYsWKC3r8yfP3/CtnyoqorP59OTVhRFITo6msTERKxWK7GxsZhMJllZ9ZASHR3N7NmzSUlJ4aOPPsLhcNy3/8ff/M3f8NOf/pRXXnmFurq6QW0iDoeDz3/+8xiNRv7mb/4G6P9+PPXUU/z0pz/l2LFjt/h8CCFQFEW/5mspXyNFdnY2ZWVlfPjhh2RnZ+uP//znP8dgMAwyMJ2IKJpTsGRkycjIEDdu3BjvYUgkwyIUCg0yJ/V4PPoNPTo6etzKMW/cuEFlZSVVVVWcO3cO6L/xaGLH+vXrJ9UEv7e3lyeeeAKDwcC2bdt44oknmDJlyn39+wYCAb3c3Wq1MmXKFOx2u5xoSSQTlJvFjmAwSHh4OEajkZaWFioqKvSJJfS74xcXF1NSUsL8+fNvuT4Eg0FcLpfu/ZGWlqbvCsrSeclwuZPYERMTM2yxo7OzkwMHDtDQ0MChQ4f0e5fNZmPt2rWsW7eOxx57bMJuWtwpaSUhIYH4+HhiY2PHdY4kGT+EEDQ3N/Phhx+iquot11+n08m8efNIS0u75XffeustXnjhBRISEnj55ZfJysriypUrfP/736ejo4Of//znPP300/rxjY2NrFixgp6eHj73uc8xd+5cmpubeeutt9i/fz8Wi4WjR4+yatUqNm/ezI4dO4iIiODxxx+/6xz5P/7jP+jq6qKpqYnXXnuNp59+mqVLlwLw3/7bfyM+Pp66ujoKCgqw2+386Z/+KXa7nV27drFnzx4++9nP8t3vfncE/1XvH0VRGoUQdywLk8LHKCGFD8lkIxAIDDInDQQCesZ5ZGTkuN3Ir1y5QkVFBVVVVfpCwGQysX79egoLC1m7du2k8awIhULs3bsXp9NJaWkpLpeLDz/8kJkzZzJ16tQhTyaFELjdbnw+HxEREXrP6UTvdZZIHlXuJna0t7dTUVFBeXk577//PtBvYrdhwwZKS0tZsWLFLULmwAqv8PBwkpOTSU5OxmKxSNFTMmy8Xq9upOt0OvVKyuGKHaFQiPPnz9PQ0EBDQ4P++VYUhXnz5rF+/XrWrVvHnDlzJmTrRygUwuv14vf7gd8nrWjCokxakdyM2+3m/fffx+FwDLoe3034ADhz5gxf//rXqampoaOjA7vdTn5+Pn/3d393WyPTa9eu8cUvfpE9e/bQ09NDeno6mzZt4pvf/Kb+mfza177G66+/TnNzM6qq8vHHH9812nbatGlcvXr1ts8N/N0jR47wpS99iffee4/Ozk6ysrL4wz/8Q/7H//gf416dJYWPcUIKH5LJgGZM1traSmdnJ6FQiPDwcGJiYm6JPhwrhBBcvHiRqqoqKisruXz5MtC/EMjLy6OwsJBVq1ZNqj51VVWpqKjgO9/5DleuXMFqtfLaa68RExNDamrqkCd8gUBA39kdWN0x3jcaiURyK3cTOzo7O6moqKCiokKP9DOZTOTl5VFcXHzb+FkhBB6PB6/Xi8FgwGazkZaWhs1mG7frtWTyc7PYoarqA1V29PT0cPDgQRoaGjhw4IBeam82m1mzZg3r1q1jzZo12Gy2EX4nD04wGMTr9RIIBBBCEBYWhsViwW6360KH/K5J7kUoFOLixYtcvXpVT365l/AhGRnuJXzI2fIIoyjKdmD7RLygSyRCCFwuF06nk5aWFnp6evTy6Ad1YX/QcZ0/f14XO7R+dqvVyrZt2ygsLGTFihWTboEvhKC2tpY33niDjz76iOjoaJ555hm2bdtGVlbWkP69B1Z3aIZaKSkp98x9l0gkY48WPaslXQ0UO7q6uti9ezcVFRWcPHkSgJiYGEpKSigqKmLNmjW3FXR9Ph9utxvoXzxmZWVht9tviaqVSIaKz+fTxY7Ozk69smO4vl2NjY3U1tZSV1fHe++9RygUAvr9ALZt28a6detYsGDBhLuHa0KHFnUfFhaG1WodJHTICirJ/RIWFkZ2djaxsbGcP39+wht+PkrIio9RQlZ8SCYKqqrS29ur+3W43W6EELpfx3iVl6qqypkzZ3SD0ubmZqA/hSQ/P5/CwkKWLFky4SZK90MoFGL79u20tLSwadMmtm3bxty5c4c0kdKqO4QQxMfH69UdcrdJIplY+P1+Pemqo6NDr5wzGo309PRQVVVFeXk5J06c0H0ScnJyKCoqYt26dbdt1RtY3RUTE6P7dgwnNUAigf7PqebZoUXPRkZGDithRFVVzp8/r4sdFy9eBCAqKopVq1aRm5vL2rVrSU5OHo23Mmxubl2RQodktHE6nZw5cwaHw8GqVatkxccoI1tdxgkpfEjGk2AwSHd3ty52+Hw+3a8jKipq3CbOoVCI9957j6qqKqqrq2lvbwcgJSWFgoICCgoKWLRo0YTs9R0KQgiOHDnCyZMn+dSnPoXD4eDSpUvYbLYh7XbdXN2Rnp6uV3fIxY5EMnHQdsw1sUOL9TYajfT29lJdXU15eTnHjh3TF5jr1q2jqKiInJyc21ZrhEIh3G43gUCA8PBwUlNTSU5OfqDkDMmjjSbKtbS06J9TzbPjfhf4Pp+PY8eOUVtbS319vX7/tlgs5OTkkJeXx2OPPTahKpFUVcXr9eLz+YB+jw6r1UpCQgJxcXEPHMErkQwFj8fDyZMnmTZtGqmpqeM9nIcaKXyME1L4kIw1Pp+P7u5uvcQ6FAphMBh0c9LxIhAIcOzYMaqqqqitrcXhcAD9sYyFhYUUFBQwb968Sb+wP3HiBK+//jonTpwgPDyc1157Te/Bv1eVxsDdXYvFIqs7JJIJyO28ELRFpMvloqamhvLyco4cOUIoFCIiIoI1a9ZQVFREbm7ubd30VVXF4/Hg8/kwGAwkJiaSmpqK1Wqd1NVukvEjEAjQ1dVFc3OzXoGkiXL3u8jv6uqioaGB2tpaDh06pLdcZWZmkpeXR15eHgsXLpww4oEWL+v1eoHBZqTx8fGYzWb5vZKMC9p6e7LPdSc60uNDInlI0aoDNHNSzYE9LCwMo9E4rjd3j8fDgQMHqKmpob6+Xo+sy8rK4umnn6agoIBZs2Y9FDeAs2fP8tprr3H48GEMBgMFBQVs376d+fPn31Vwurm6Y8qUKbK6QyKZYLjdbhwOBy0tLXqkp+aF4Ha7qa2tpby8nEOHDhEMBgkLC2P16tUUFRWRl5d3Wy8eIQRer1dfnFksFmbNmoXNZptUps2SiYNmpNva2kpbW5vebjWc1o0bN25QU1NDXV0dp06dIhQKoSgKixYtIjc3l7y8vLsmQ4wlmtDh8/kGxctmZWVhsVh0Y0mJZLyR87qJgRQ+JJJJhObXoZWuaoLCg5iSjRTd3d3U19dTXV3NoUOH9NLSuXPnkp+fT35+PllZWeM2vtHi29/+NseOHSM3N5ft27ezbNmyuy5ebq7uyM7OltUdEskEYaABdFNTE729vUD/NTY+Ph6Px0N9fT3l5eUcPHgQv99PWFgYK1euZOPGjeTn5xMfH3/b1/b7/bpvj8lkIjs7m4SEBIxG41i+RclDQigU0qs8W1pa9Bap+934UFWV999/n9raWmpra/UktaioKNavX09ubi45OTkTIoXlTkJHSkqKLnRI8VAikdwJ2eoySshWF8lIcSe/Ds2cdDxV5Pb2dmpqaqiurub48eN6e82SJUsoKChgw4YNpKSkjNv4RoOLFy+yZ88ePvvZz9LW1qYn0KxYseK2JoXQP1lzu934/X4iIiJ07w5pVCiRjD9CCPr6+nTjR01Q1iI9vV4vDQ0NlJWV0dDQoLelLF++nKKiIvLz87Farbd97UAggNvtJhQKER0drZuUysouyXBQVZWenh7a29tpbm7G5/PpVZ73I577fD6OHj2qm5N2dnYCYLPZdL+OVatW3fGeNlYIIfTWlYFCR0JCghQ6JBLJLchWF4lkEuL1eunu7h5knKf5ddyuT3wsuXbtGtXV1dTU1HDmzBkAvZd9w4YN5OXl3XERMJm5cuUK3/nOdygvL0cIwZw5c8jOzmb58uV3NHPTdnihP5o3IyMDu90ue4wlknFGCEFPTw+dnZ00Nzfj8XgAiI6OxmKx4PP5OHDgAOXl5dTX1+P1elEUhaVLl+piR0JCwm1fOxQK4XK59HaDtLQ0kpKSsFgs0qRUct8IIejt7aWjo4OmpiY8Hg8GgwGj0Xhf8wGPx0NDQwNVVVU0NDTo96asrCy2bt1KXl4e8+fPH1e/DiEEfr8fr9ert9jExMQwZcoUrFYrZrN53MUYiUQyeZGzb4lkAqCVV3d1dem95ADh4eGYTKZxXSgLIfjwww+pqamhqqqKS5cuAWA0GvUFwNq1a4mNjR23MY4mN27c4Hvf+x67d+9GVVWWLl3Kjh07WLNmzW1L1FVVxeVyEQgEiIqKIisri+Tk5If230cimSxou+UdHR20tLTg8Xj0hZXFYiEQCHDw4EEqKiqora3VjRwXLVpEcXExhYWFJCYm3vG1taqusLAwkpKSSE5OlialkmHjcrno6OigsbERl8uFoigYjcb7ajnp7e2lvr6eqqoqDh48qLegLliwQK/KzMzMHK23cE+0ig6fz4eqqgDExMSQnp4+SOiQ1VESiWQkkHdjiWSc0CbhmnGe2+1GCEFUVNS4xxeGQiHOnDmjV3Y0NjYC/SZ8TzzxBAUFBaxcufKRKDH94Q9/yK5du1i4cCE7d+68o8jj9Xr1XeOEhATS09Ox2WwTxu1eInkU0XwQNLFDa1OJiYnBZrMRCAQ4fPgwFRUV1NTU6G0u8+fPp6ioiI0bN96xXU8Igcfjwev1YjAYsNlspKamYrPZpKGiZFh4PB46Oztpamqip6cH6K9CslqtQ178O51Oamtrqaqq4siRIwSDwUEtqPn5+SQnJ4/m27gjdxI6MjIy9NYVKXRIJJLRQnp83AFFUXKBvwaWA2nAZ4QQPxrq70uPD8ntCAQC+iS8tbUVv9+PwWAgOjqaqKiocb3ZD4ydHdjzm5ycTH5+Phs2bGDJkiUP/e5lR0cHv/jFL/jMZz5DR0eHvmDKzc29JaFBK2kPBoN6OW5iYqI0K5RIxhHNF6m9vX3QddZoNBIZGUkwGOTYsWOUlZVRU1OjLzDnzJlDUVERRUVFpKWl3fa1tYWbx+NBCEF8fDxpaWnY7fY7trxJJHfD5/PpZroOhwMhBNHR0cTExAx5TtDW1kZ1dTXV1dWcOHECVVUJCwtj1apVFBQUkJeXNy7mpLczIzWZTNjtdqxWK7GxsfJ7I5FIRgzp8TF8YoGzwP/55EciGRYej0f36+js7Bzk1zHe7Q93ip2dNm0aTzzxBPn5+cydO/eR2H1xOBz8+Mc/5le/+hU+n4+4uDjy8vKYNWsWy5cv148bGEWpKArJycmkpaXJ/n2JZBzR4jzb2tpoa2vTd7mNRiOxsbGEQiFOnDhBWVkZ1dXVejthdnY2n/70pykqKmLKlCl3fH2fz6dX5ZlMJmbNmoXdbh/3a7hkchIIBPR0tvb2dlRV1ZODhnofaWxspLq6mqqqKk6fPg30G/Lm5ORQUFBATk4OcXFxo/k2buFeqSuxsbHSo0MikYwbUvi4A0KI3cBuAEVRfjS+o5FMJrSEAM2vo7u7G+g3AI2NjR331odHNXb2TnR1dfHTn/6UX/7yl3g8HrKysnj++ecpLCwcZNI6MIbWbDYzZ84cEhMTH4l2H4lkIhIIBOjq6qK1tZX29nZCoRBhYWHExMQQERGBqqqcPHmS8vJyKisrcTgcAEyfPp3nn3+eoqIipk2bdtfX177z0dHRZGVlkZCQQFxc3CMhBktGllAopH9eW1tbdfNbs9k85HnBlStXqKyspKqqigsXLgC/99sqKChg3bp1Y1pxqKqqbkYqhEBRFEwmE6mpqcTHx8vUFYlEMqGYtMKHoijPAnnAEmAxYAZ+JoT49F1+JwP4ClAK2IFm4G3gy0II5ygPWfIQo/WRa34dXq8XYEL4dcCjGTs7VH7zm9/wox/9iClTpuiLIbvdDvRP6jweDz6fj/DwcDIyMkhJSZELH4lknPD7/YPEDq2k32g0Eh4ejqqqnDlzhvLycioqKujo6AAgMzOTp59+mqKiImbMmHHH1x/YvhYREUFGRgZJSUkT4joumXxoXl5tbW00Nzfr5rdDNS3XzMWrqqqoqqri448/BsBsNrNlyxYKCgpYvXr1mIkLt/PoiI2NZerUqTJeViKRTHgmrfAB/H/0Cx59wA1gzt0OVhRlBnAASAJ+C3wArAL+HChVFGWdEKJzVEcseajw+Xx6H3l7ezvBYHBQQsB4L4wf1djZe+FyuXjzzTd5/PHH8fv9rFmzhoiICIqLi0lMTERRlFtiaGfPno3NZiMiImKcRy+RPHpoHggD470HVtAJITh37pwudrS2tgKQnp7OZz7zGYqKipg1a9Ydr8m3S2TRSvMfdk8jycijVX22t7ffEj87lNYoVVU5d+6cLnZo5uI2m41t27ZRWFjIihUrxuSzKYQgEAjo8bLwezNSGS8rkUgmG5P5jv7f6Rc8LtJf+VF9j+P/k37R48+EEP9be1BRlG9+8lr/AHx+dIYqeRgQQuB2u/UJeFdXF6qqEh4eru82jvf4HuXY2Xvh9Xp56623+PGPf0xXVxcdHR0899xz2O12XnjhBVRVpbe3l2AwSHR0NNOnTycpKemR/feSSMYTj8dDV1cXzc3NOJ1O3QNBawsQQnDhwgXKysqoqKigqakJgNTUVP7gD/6AoqIi5syZc0exQ0tk8fl8KIqCzWYjLS0Nq9UqE1kkw8LlcumJLJpf1lDjZ0OhEO+99x5VVVXU1NTQ1tYG9JuL79ixg4KCAhYvXjwmrbKa0BEMBoH+ytWUlBRsNhtxcXHSjFQikUxaHopUF0VRNtAvfNy21eWTao+LwBVghhBCHfCcmf6WFwVIEkK4bvP7fcCfylSXR4+bI2ddLheKohAZGUlMTMy4lz4Hg0FOnjxJbW0tdXV1+s5QfHw8eXl55Ofns2rVqke69NTn8/Gb3/yGH/7wh3R2dmK323n22WfZsmULKSkpekKDwWAgMTFRX/yMtxeLRPIooQnL2rW2u7sbIQSRkZEYjUYMBoMudlRUVFBRUYF2j01OTmbjxo0UFRUxf/78u4odmjExMCiRRe5aS4aD1+vVxY6uri4URSE6OnpIkayBQICjR4/qlZlOZ3/HdUZGBgUFBRQUFDBv3rxRn2eEQiG8Xq/u9xUREYHdbichIQGz2YzJZBr3ClaJRCIZCjLVpZ/8T/4sGyh6AAghehVFaQCKgdVA5VgPTjKx0AzzOjo6aGtrGxQ5a7Vax30C4HK5OHjwILW1tTQ0NOhRjCkpKTz//PPk5+c/ErGzQ6W2tpZ//dd/xWKx8PLLL+uCh9vtpqurC7PZzNy5c0lISJCLH4lkDNFaAhwOB83NzfT19elRnpqnhiZ2VFZWUl5erosdCQkJuifPokWL7ro4HJjIEhsby6xZs0hISMBkMo3VW5U8RPj9fv0z63A4UFWVqKioISV7eb1eDh06RFVVFfX19fT29gL9hrvPPvss+fn5d23LGgk0AVBLXjEYDFgsFrKysoiPjyc2NnbcN3UkEolkNHhUVkazP/nzwzs8/xH9wkc2nwgfiqLEAjM/ed4AZCqKsgRwCCGujd5QJeOB2+3WI2e1iYyWDjARWh3a29v1qo6jR48SCAQAmD17Njt27CAvL4/s7OxxF2UmAsFgkN27dzNv3jysViszZ87k85//PAUFBSQkJBAMBvH5fEyZMoXk5GRpVCqRjCFCCHp7e+no6BhURRcdHa17Iw0UOyoqKrh+/Tpwf2LHwESWmJgYpk+fru9gy++75H4JBoM4nU6am5sHxc/GxcXdUyRwuVw0NDRQVVVFQ0MDHo8H+H2SWkFBwV3ThUYCLXlF8yKLjY3VY9jNZrP0r5JIJI8Ej4rwEf/Jn913eF573DLgsRUM9g358ic/PwZeuvkFFEX5S+Av9RPGx998iGQCoaoqfX19OJ1OWlpa9F2XiRI5K4Tg0qVL1NbWUltby/vvvw9AWFgYy5cvJy8vj7y8vEc2ieV2hEIhysrK+O53v8u1a9fIzc3lz//8zzEYDGzbtk3f1UpPT8dms8mKGIlkjNBaBjs7O2lubtZbTWJiYvQqOs2jSGtjuVns2LhxI4sXL77rIjMYDOJ2uwkGg0RGRjJlyhQSExNlIotkWGjxs21tbbS0tOhJP0OJn+3p6aGuro7KykoOHz6M3+8HYNGiRXobS1pa2qiO3ev14vf7EULoPh12u524uDhZ3SiRSB5J5Mz/Dgghauj3/Rjq8d8Evqn9PSMjY/KbpzxkBINBuru76ezspLW1Fa/Xe8tO43iP79SpU7rYofl1mEwmioqKyMvLY926dZjN5nEd50RDVVWqqqr4zne+w+XLlzEajTz33HMUFxdjMpmIjY0lIyODxMREjEbjeA9XInkkUFVVv95qYofBYBiUejUSYkcoFMLtdhMIBAgPDyc5OZnk5GQsFsu4C9iSyceDxM92dnbqsfFHjx4lFAoRFhbGsmXL9Nj4xMTEURm3FjOrVZMYDAasVqsu/JlMJin+SSSSR55HRfjQKjruVIahPd71oCdSFGU7sH0oLt6S0cfr9eo7NloMojb5ngj/j9xuN4cOHaK2tpb9+/fT3d3/UU1OTmb79u3k5eWxfPlyWYZ6F86fP8///J//k+joaJ544gk2bdrEzJkzSU9PJyUlRe72SiRjRCgUoqenh/b2dlpaWvD5fHqMp3a9FULw0UcfUV5eTmVlJdeu9XeOJiQk8Nxzz1FUVHRPsWNg/KxmSpySkoLVapXXSsl9M7D96n7jZ9vb26mqqqKyspL33nsPIQTh4eGsXr2agoIC8vLysFgsozLuYDCIx+PR01eMRiNZWVl6zKz8LkgkEslgHhXh48Inf2bf4flZn/x5Jw+QISOEeAt4S1Z8jA+aWV5XVxctLS309PSgqioRERFD2rEZCzo6Oqirq6Ouro4jR47oJbDZ2dk899xz5OXlMXv27HGvQJmoCCE4dOiQ3rcfFRXFZz7zGZYvX87KlSuZOnUqNptNTvokkjEgFArR3d1NR0eHvkOuLRo189CbKzs0scNut/Pcc8/plR13q9DQ4me1yhGbzUZqaio2m03Gz0qGhcvloqOjg8bGRt1rZijxsy0tLbrYcerUKaA/8nXDhg0UFBSQk5MzKt5gqqri8/n0VrHw8HDsdjuJiYl6zKycN0gkEsmdGf9V4NigeXUUK4piuE2c7TrADRwaj8FJHgxtl1FrYXG73SiKQlRU1JCMx0YbIQQff/yx3sJy9uxZAL0ENi8vj9zc3FHt931YOHbsGK+99hqnTp1i1qxZfPGLXyQyMpL/+T//JxkZGbKVRSIZAzTvg/b2dlpbWweJHdqCb6TEjpvjZ6dPny7jZyXDZmD8rFZhOZTEtqamJqqqqqioqNDv4dHR0RQVFVFYWMjatWtH5f4TCATweDyEQiEAzGYzGRkZuimpbOeSSCSSofNICB9CiEuKopTRn9zy/wD/e8DTXwZMwBtCCNd4jE9y//j9/kGRs4FAQG9hmQiRs6FQiNOnT+tih9a7bjQa2bhxo+7XERcXN67jnCycOnWK1157jWPHjhEWFkZBQQEvvvgiRUVFJCcnj/v/b4nkYScYDA4SOwKBAGFhYbeIHVoby81ix/bt2/U2lnuJHZpXgRACs9lMdnY2drtdxs9KhkUgEMDhcNDU1KSntg3F2+vGjRtUVFRQVVWlG4wbjUZKSkrYuHEja9asGXEBbmBVhxCCiIgIkpKSSEhIID4+Xgp+EolE8gAoQkzOjgxFUZ4CnvrkrylACXAZqP/ksQ4hxF8POH4GcABIAn4LnAceA/Lpb3FZK4ToHIFxaR4f2zs7H/jlJANwu904nU5aW1txOp2oqkp4eDgxMTEToq3B4/Fw+PBhamtrqa+vp6urC4CkpCRyc3PJzc1lxYoVsiz7PhBC0NjYyLPPPksoFGLDhg28/PLLbNmyZdT6piUSST+a2NHW1kZrayvBYFAXO7RrrhCCixcvUlFRQXl5+SCxo6CggI0bN7JkyZJ77kz7/X7cbjeqqmI0GklPT8dutxMbGyuFTcl9o1UltbS00NraSigUIjIyEqPReNcq0KtXr1JZWUllZSUXLvR3SZtMJvLy8igsLGT16tVERUWN6Fi1qg4tatZsNusGvROhalUikUgmC4qiNAohMu74/CQWPr4EvHqXQ64KIabd9DtTgK8ApYAdaAZ+A3xZCOEcyfFlZGSIGzdujORLPnJokbMOh2NQ5GxUVBTR0dETosSzs7OT+vp6amtrOXLkCD6fD4CZM2fqkbNz586VE/f75Ny5czQ2NrJo0SJcLhdHjhxh5cqVbN68WabaSCSjSCAQ0MWOtrY2PZnCaDTqHkla3LZW2XH16lXg/sWOQCCAy+XSd+BTU1N1vwJ5zZTcL0IIuru7ByWyhIeHD/rs3o6PP/6YyspKKioquHjxItDfUrJhwwYKCwtZtWrViG5YqKqK1+vV5wsREREkJiZit9tlVYdEIpE8AA+t8DHRkcLH8AgGg/T09NDR0XFL5Gx0dPSEmAxfuXKFmpoa6urqOHPmDEIIwsLCWLJkie7XkZFxx++c5A6EQiHOnTvHD3/4Q+rr67Hb7fzqV78iNjaWWbNmER9/p1AmiUTyIPj9fr2aTku/upPYoVV2DFfsCAaDuFwufQdeEztk+pJkOAghBpmUut1u3W/mTmKF9lnWKjsuX74M9HvI5OfnU1hYyIoVK0a0ktTv9+P1evWqjvj4eJKSknSvDvnZl0gkkgfnXsLHI+HxMZbIONv7x+fz6b3j7e3tBIPBWyIQx5NQKMSZM2d0vw6tlDsmJob8/Hzy8vJYv369XJgPAyEEbreby5cv89Of/pSqqiqEEKxfv57Pf/7zLF68GKvVOt7DlEgeOrSo75aWFjo7O/X0q9jYWF28GNjGUlFRwZUrV4Dfe3YUFhaydOnSe4odoVAIl8tFMBgkPDyclJQUvZR/IlTuSSYfHo+Hzs5OGhsb9WrQu8XUa2a7mtihCXdWq5Wnn36awsJCli9fPmLJb6FQCK/Xi9/vRwhBVFQUKSkpelXHSLfLSCQSieTeyIqPUUJWfNwZbbGr7TB2dXXpk+6YmJgJETnr9XoH+XU4nf2dUAkJCbpfx8qVK+XkZZh4vV48Hg/Qbxb3xBNP0NnZyerVq/n85z/P1q1bsdvt4zxKieThwuPx4HA4aG1txeFwIIQgMjKSmJiYQWKHVtkxUOyw2WwUFhYOWexQVRW3243f7ycsLIzExERSUlKwWq0T4hovmXxolUlNTU10dnYihCA6OvqOMa6a2FFeXk5lZaVuMq5VKQ31s3w/4/N4PKiqiqIoWCwWkpKSiI+PJzY2VlZ1SCQSySgjW13GCSl8DEZVVXp7e3E6nTQ3N+Ny9QfoaJPuiTAhcDqdul/HoUOH9P7b6dOn634d8+bNmxBjnYwM7OfX2pm2b9/Oxx9/TFlZGYmJiTz55JMkJiaO91AlkocGt9uNw+GgublZj++8+bo7sPS/vLx8kNihtbEMVezweDz4fD4URcFut5OWlobVapWmzpJhEQqFcDqdtLS06J4z9zIpvXz5MuXl5ZSVlemVHUlJSbrYsWjRohEROwZ6dWgiTGJiIgkJCcTFxcnPvEQikYwxUvgYJ6Tw0d/L3d3drft1aJPhmJgYoqKiJoRfx9WrV/UWltOnTyOEwGAwsGTJEnJzc9mwYYP063gAQqEQbrebQCBAeHg4YWFh/OxnP+NHP/oRiqKwa9curFYrGRkZJCcnj/dwJZJJjxCCvr4+XWTu6elBURTdFHqg2PHBBx9QVVVFVVWVvkC8X7FDCKGLHQAWi4W0tDRsNps0aZQMCyEEPT09tLW10dTUpEcnm0ymO34er1+/TllZGWVlZVy6dAnor+woLCykuLiYRYsWjcimxUCvDoPBQHx8vN62JROIJBKJZHyRHh9jzKPu8eH1eunu7tZN8rREgJiYGEwm03gPD1VVOXv2rC52aDub0dHRbNiwQffrkFGpw2fgrq/BYCAxMZGIiAi+973v8dprr+HxeJg3bx6vvPIK8+bNIy0tbbyHLJFMaoQQ9Pb24nA4aGpqwuVy6abQVqtVX4ypqsrJkyepqqqiurqa5uZmoH+B+Oyzz96X2KG1q2nxm1lZWdhsNoxG46i/X8nDidvtpr29ncbGRlwul+71FRsbe9vjm5ub9cqODz74AOg3KN22bRvFxcUsW7bsgSs7VFXF5/Ph9XoHeXVoVR2y3VUikUgmD7LiY5R4VCo+NEf1gX4dQogJ59dx9OhR3a+js7MT6J/s5+TkkJeXx8qVK+Xu5AOgLYS8Xi/w+11fu91OVFQUK1as4Pjx48yaNYtXXnmF559/XlbSSCQPgNYy1tnZSXNzsy5C3FxRFwwGOX78ONXV1VRXV+vXv9TUVAoKCsjPzx/SbrgQAp/Ph8fjQQiB2WwmNTWVhISECSFqSyYnfr8fh8NBY2Oj7qV1t6rQtrY2PVnozJkzAMTGxpKfn09RURGrVq164HlHMBjE4/EQDAYBZAKLRCKRTBJkq8s48TALH9qE2+Fw0NLSgtvt1vtbB5ZSjyddXV3s37+f2tpaDh48qC/Is7KydL+O+fPnT4ixTmb8fj9utxtVVTGZTGRkZJCQkEAgEKCsrIynn36a8+fPU1VVhcfj4fnnn2fatGnjPWyJZFISCoX09sGWlha9qiomJobIyEh9oejz+Thy5AhVVVXU1dXp3h5Tp07VfQ5mz549pLJ8n8+nX+ONRiPp6enY7XZZ1i8ZNqqq6olCLS0thEIhoqKi7uj35XA4dP+Z9957T/8s5ubmUlRUxJo1ax7IT0MT9bSqjvDwcBISEvSYZbkpIpFIJJMDKXyMEw+b8BEIBAb5dfj9fgwGA9HR0RPGr+P69evU1tZSV1fHyZMnUVUVg8HAokWLdLEjMzNzvIc56QkGg7pJaWRkJGlpaSQlJWE2m3G5XPzHf/wH//zP/4zT6eQXv/gFM2fOxG63M3Xq1AnxOZFIJhOBQECP+25rayMQCOgtAAMXe263mwMHDlBVVUVDQ4NuIJ2dnU1BQQEFBQVMnz59SOccKGjGxMSQlpZGQkICZrNZfoclw0LzntFaWbxeL+Hh4RiNxttWaHR3d1NdXU1ZWRnHjh1DVVWioqJYv349xcXFrFu37oEEiZvjZk0mE8nJydhsNuLi4mTMskQikUxCpMeHZNh4PB7dr6Ozs1MXEmJiYu7YczuWqKrK+++/r/t1XL58GYCoqCi9hSUnJwer1TrOI538DIymDA8PJyUlhZSUFOLj4wkLC8Pj8fCtb32Lf/qnf6K9vZ3U1FS++MUvsnTpUmbNmiUXSxLJfeDz+fQdce3aGxYWhtFoxGw268f19vZSV1dHVVXVoCSqhQsX6m0sQ20pGyh2REdHM3XqVBISEoiPj5ffX8mw8fl8dHR00NTUpFceGY1GbueD5na7qampYe/evRw+fJhQKERERAQ5OTkUFRWRm5v7QB4ygUAAj8dDKBRCURSsVqtuTGo0GuXnXCKRSB5yZMXHCDPA3HS71ks9WdB2ZLQJtzZJ0fw6JsIOiM/nG+TX0dHRAfQnEeTk5JCbm8tjjz0mS1NHgJtNSgdGU0ZERAw6dufOnfziF78gKSmJP/qjP+LFF19k7ty5ciIpkQwRj8eDw+GgtbUVh8OBEEKPnR147XU4HNTW1lJVVcWRI0cIhUIYDAaWLVtGfn4++fn5JCUlDemcA8UOzbRRK++XbYCS4TIwgra1tVUX02JiYm65JwSDQQ4dOsSePXuora3F6/USFhbGY489RnFxMXl5eYPEvvvhZl+ayMhIkpKSdEFPxs1KJBLJw4VsdRknJkurSygUusWv43bRh+NJd3f3IL8Oj8cD9Peray0sCxYsmBDCzGTn5rQGi8VCamoqdrt9kJgUCAT47W9/y9NPP83HH39MQ0MDp0+f5g/+4A9YsGDBhPjcSCQTHZfLpV97NaFZEzsGfodaW1uprq6mqqpKb+MLDw9n1apVFBQUkJeXN+TKttuJHQkJCVgsFvm9lQwbLVlIi6D1+XyEh4ffNoJWCMHp06fZu3cv5eXldHV1AbBo0SI2bdpEUVHRsJPVBgr2iqJgNBpJSUnRW1jkZ1wikUgeXqTwMU5MZOHj5p7xYDCoRx9OFL+OGzduUFdXR21tLSdPntRLUxcuXKiLHdIkc2QYuCsGYDab9USWm8uKQ6EQP/vZz/jyl7/M5cuX+da3vkVOTg5Go5HZs2fLSaVEche0qjpN7Ojt7b2jMfSNGzeorKykurqas2fPAv1tfGvXrqWgoICcnJwhtxzeLHZoaSyyskPyoHi9Xjo6OmhsbKS3txcAk8l022qKjz/+mD179rBv3z4aGxuBfsPx0tJSSktLSU9PH9YYQqEQbrebQCCgC/YpKSlYLBZMJtOEmNNIJBKJZPSRHh8SoL+MuqurS/frEEIQFhZGTEzMLW0L44Gqqpw/f17367h06RLw+4m+5tdht9vHeaQPDwPTGkwmE7NmzcJut992oqiqKm+++SZf+tKXuHDhAmazmT/5kz9h7dq1LFmyRFbbSCR3YGAKlhY7CxAdHY3FYtG/a0IILl68qFd2fPTRR0D/IrK0tJT8/HzWrl1LTEzMkM57O88Ou90uxQ7JAxMKhfTPc3t7u26CO/DzrNHe3s6+ffvYs2cPFy5cACAxMZFPf/rTlJaWDjld6GY0v45gMEhYWBh2u13365CtrhKJRCK5HbLiY5QY74oPrexU67PVdhZv1zM+Xvj9fo4dO6YnsbS3twNgsVh0c9LHHntsyBN9yb0ZblrD3//93/PVr34Vk8nEzp07eemll3jsscdu68YvkTzq3Cl29uaqOiGEHvdcVVXFtWvXAIiPjycvL4+CggJWrVo1ZC8CrXJLEzu0yg5Z4i95UAa2sjQ2NuL3+4mIiMBoNN4yn+jr66OyspK9e/dy7NgxXVwvLCxk06ZNLFu2bFhzkIH3r4iICJKTk3VPmomwgSORSCSS8UW2uowT4yF8aJNtrYxa82nQJtsTYeLb09NDQ0OD7tehRS5mZmbqLSwLFy6cEMLMw0IgEMDtdhMKhfQy98TExLsuhoQQ7N69m40bN9LZ2cmJEyf41a9+xUsvvcS6devkJFMiuYk7tRDeHDsbCoU4c+aM3sbS0tICQEJCAvn5+RQUFLB06dIhi4oDxY6YmBjds0OKHZKRQGtluXHjBr29vbeNUoZ+k9KGhgZ2795NfX29LoysX7+e0tJS1q9fT1RU1H2d+2Zz0ujoaFJSUvTKJTlPkEgkEslApPAxxox1qovf76erq4uOjg7a2toIBAJ65GxkZOSE6G1tamrS/TpOnDih+3UsWLBgkF/HRBjrw0IwGMTtdhMMBvWdseTk5HtOFoUQ7Nmzh1dffZVjx47xN3/zNzz//PP6/y/pgi+R/B4tdra1tZWOjg49dvbmFsJgMMixY8eorq6mpqYG7d6Qlpamx84uXLhwSELFzYvBmJgYvbLDbDZLsUPywGipLE1NTYNaWaKjowfdp4UQXLhwgXfffZe9e/fidDpRFIVly5axadMmCgoKiIuLu69zawbbXq8XQP982+12+fmWSCQSyV2Rwsc4MZoVH263G6fTSWtrK06nU3f4nyh+HUIIPvjgA92vQ+tVj4yMZNWqVbpfR0JCwjiP9OFioMFbeHg4iYmJusHbvXaPhRCUlZXx6quvcvjwYSIiInj66ad56aWXyM/Pv++dOonkYUXzS2pubtavv7cr+ff5fBw+fJiqqirq6uro6ekBYNq0aRQUFFBQUDBkf4OBi0EhBEajUV8MxsXFSdFYMiIMbGW5WypLR0cHe/fuZdeuXVy8eBHor9rcunUrmzdvJiUl5b7Oe7PYERsbS2pqKjabjdjYWPn5lkgkEsmQkMLHODFawsfJkyd1L4yJ5NcRCAQ4fvy47tfR2toK9Peq5+TkkJuby+rVq29JCZE8GAPFDoPBQEJCAqmpqVit1vsSwX7wgx/w8ssvEx4ezrZt23jppZcoKCiQJnGSRx4hBG63e1Ds7J38ktxuNw0NDVRVVdHQ0IDb7QZg9uzZ5OfnU1hYSFZW1pDPOzBa2mg0kpaWhs1mu6cnj0QyVPx+v57KokUq3y6VxefzUVdXx65duzh06BChUAiz2UxxcTFbt25lwYIF9/WZFELg8Xjwer0oiqKniVmtVpnEIpFIJJJhIVNdHjK6urowm80TorKjt7dX9+s4cOCA7teRkZHBCy+8QF5eHosWLZIGmCNMKBTC4/Hg9/t1sSMlJQWr1XpfrSi1tbXMmzcPg8HAzJkz2bFjB5/+9KcpKCiQhrKSRxrNyHFg7Cz0J7HcnIrS09NDXV0d1dXVHDp0CJ/PB8CiRYsoKChgw4YNZGTc8R48CFVVB+18x8XFkZmZic1mk4tByYihqipdXV20tLTQ0tKi+z/dnMoihODs2bPs2rWLsrIyent7CQsLY/Xq1Tz++OPk5OTcVzWgJnZo35G4uDimTZumf74lEolEIhlN5IpUcl+0tLToLSzHjx8nFAoBMH/+fN2vY/r06XKCPsKMlNgBsH//fl599VWqqqr49Kc/zV/8xV9gMpn4/ve/LytyJI8sqqrS3d1NZ2fnLebQVqt10DWtvb2d2tpaampqOHr0KKFQCIPBwPLly8nPzyc/P5/ExMQhn1dbDCqKQnx8PFlZWfrOt0QyUrhcLtrb27lx4wYej4ewsDBiY2NvqRptaWlh9+7d7Nq1S08amjlzJi+//DKlpaX31aZ6c2WH9vm22WzyfiORSCSSMUUKH5K7opmXaS0sFy5cACAiIoLHHnuMvLw8cnNzhzzJlwydkRQ7AA4dOsSrr75KWVkZBoOBrVu38uyzzzJnzhy5wJI8kgSDQd0curW1Vf+uxcTE3CJ2XLlyhZqaGmpqajh79iwA4eHhrF69mvz8fDZs2IDFYhnSeW/+blssFmbMmIHNZpPVVpIRJRAI4HA4aGxsxOFwAP2GoTabbdBxHo+Hqqoq3n33XY4ePYoQAqvVys6dO9myZcuQ/WjgVs8Os9nMtGnTsNvtUuyQSCQSybghhQ/JLQSDwUF+HVrcYlxcHJs2bSIvL481a9bIxfIocCexw2KxPJDBaEVFBUVFRSiKwqZNm/jsZz9LcXExsbGxIzh6iWTic7skFk3sGPh9UFWVs2fP6mLH1atXgX7/g+LiYjZs2MDatWuH/B262Y/HarXqfjzSS0cykggh6O7uprW1laamJoLBIJGRkbe0aamqyokTJ3j33XeprKzE7XYTHh7Ohg0b2Lp1K+vWrRtyq+rAtCHoNyjNzs7GbrfLuYJEIpFIJgRS+BhhBsTZjvdQ7ou+vj4OHDhAbW0tDQ0N9PX1AZCens7OnTvJy8tjyZIl0q9jFLhZ7LDb7Xplx4OIHe+99x5ms5nk5GTi4uL41Kc+xbZt2yguLr7viEGJZLKimZMOTMKC/mqNm8v8/X4/R48epaamhrq6Oj12NiEhgWeffZYNGzawfPnyIXssabHSWitMQkICycnJDyxkSiS3w+v10tHRwY0bN+jt7cVgMGAymW75vF6/fp13332X3bt309TUBMC8efPYunUrxcXFQ65cgn4h0e12I4TAZDIxa9YsXeyQLa8SiUQimUjIVJdRYrRSXWpqaoiOjh4Rc9PW1lbq6uqora3l2LFjBINBoH8ClJuby4YNG5gxY4acvIwCoyV2AJw+fZovfelL/OY3v6GwsJBvfOMbQH+Pdnx8/EgMXyKZ0NxsTqoJuVoSy8Bd776+Pvbv33+LSXNWVhYbNmwgLy9PNwEeCoFAQBc7wsPDSUpKIikpCYvFMiFMqSUPF6FQCKfTSVNTE+3t7aiqSkxMDNHR0YPu3X19fZSXl7Nr1y5OnToFQGJiIps3b2bLli1Mnz59yOf0+/243W79XGlpaSQkJMi0IYlEIpGMKzLVRaIjhOCjjz7SzUk/+OADoH/nc+XKlbpfR1JS0jiP9OHkZrHDZrPppe4jsft77tw5vvzlL/PWW28BkJ+fz2c/+1lmzJhxXzt4EslkJBQKDTIn1cwUo6Ojb0mraGtro66ujpqamkGi76JFi3ST5mnTpg353AMXgpGRkaSlpZGYmEh8fLyskpOMCn19fbS1tXHjxg18Ph/h4eGYzeZBFUyhUIgjR46wa9cuampq8Pl8REVFUVpaytatW1m5cuUtxqZ3YqCgFxUVRWZmJomJicTFxQ1ZFJRIJBKJZDyRM7KHnGAwyHvvvaf7dWhlrWazmU2bNpGbm8uaNWuk18Mooaoqbrd71MQOjQ8//JCFCxcihCAnJ4dXXnmFTZs23WJgJ5E8TPj9ft2ctK2tjWAwiKIot5g3CiH4+OOPdb+Oc+fOAf0mzatWrWLDhg3k5uYOOa1C8zPwer2oqkpUVBRTpkwhISGB+Pj4IS8mJZL7IRAI0NnZyY0bN+jq6gL6PWdu9tC4fPkyu3btYs+ePbS3twOwdOlStmzZwsaNG+/Ll8blchEMBgkPDyc1NVVv1ZJih0QikUgmG1L4eAhxuVwcPHhQ9+vo6ekBIDU1lR07dpCXl8fSpUvlTuQoMdqVHRofffQRvb29zJ07l97eXl5++WVycnLYvHnzfcUNSiSTiZv9OlRVJTw8nJiYmEGtJKqqcubMGWpqaqitrdVjOU0mEyUlJWzYsOG+RN+BSRVCCIxGo55UIXe9JaOFZlTa0tJCc3MzwWCQqKioW6qYurq62LdvH++++y7vv/8+AGlpafzxH/8xW7ZsISPjjpW/gxh4/woLCyMpKYnk5GSsVqucM0gkEolkUiM9PkaJsfb4aG9v16s6jh49SiAQAGDOnDl66fasWbNk/+0ocXNig2ZiONJiB/Tv5n31q1/lJz/5CbNnz+bHP/4xiqLopccSycOEqqr09vbidDppaWmht7cX+L1fx8DqCp/Px9GjR/VroWZOmpiYqPt13I85qaqqeDwefD4fiqJgNpt1ETM2NlZeTyWjhtfrpb29nevXr+NyuTAYDMTGxg4SH4LBIPv37+fdd9+lvr6eYDCI0WiksLCQrVu3snTp0iEJcjd/zu12O2lpacOOTpdIJBKJZDyQHh8PKUIILl26pPt1aDs84eHhLF++XPfrSElJGeeRPrzcnNiQmJiolwGPxmTxypUr/MM//AM//OEPCYVCrFy5kldeeYXMzEzpyyJ5qND8Ojo6OmhtbR3k12G1WgcJDj09PRw4cICamhoOHDiA2+0GYPr06TzxxBNs2LCBuXPnDrkiIxgM4vF4BsXOzpgxA6vVitFoHJX3K5HArUalQohbPvNCCC5cuMCuXbvYu3cvXV1dKIrCypUr2bp1K/n5+cTExNzzXAMrmAAsFgszZszAbrfLeGWJRCKRPJRI4WMSEQwGOXnyJIcOHWL//v00NjYC/aXbxcXF5OXlsW7dOunXMYrcnNiQnJxMYmLiqCc2dHV1MX/+fNxuN8uWLeNzn/scTz31FMnJyaN2TolkLNH8Otrb23W/DoPBgNFovMWr5sqVK+zfv5+6ujpOnTpFKBRCURQWLlyoV3ZMnTp1yOcOBAJ4PB5CoRBhYWEkJibqSSxyx1sy2mhGpY2NjXi93tsalXZ0dLBnzx527drFpUuXAJg6dSovvPACmzZtGvImh8/nw+PxIIQgNjaW2bNnY7fbpagnkUgkkoceKXxMIh577DFOnDgBQHJyMs899xx5eXksW7ZMxiSOIlpigxBCN3hLSkoa9cSGxsZGLl26xOrVq7l06RKf+9znyM7O5qmnniI1NXXUziuRjBUul4uurq5b/DqMRuMtJf0nT56kvr6e+vp63a8jKiqKdevWkZOTQ05Ozn2Zk2rfa0AXMTWxQ3oZSEabYDCoG5U6nU6gfxNjoMjn8/moq6vjd7/7HYcOHUJVVeLi4nj22WfZunUr8+fPH1K7VSAQwOVy6fGzWVlZJCYmynYtiUQikTxS+fQXPwAAWCZJREFUSI+PUWI0PD6++c1vcvr0afLz84c84ZEMD21XTEtsSElJGbPEhubmZv7pn/6JN954g/j4eN5++209IlMKHpLJzM1+HX19fUC/X0d0dPSg75bWwlJfX8+BAwd0b4+kpCTWr19Pbm4uK1asGHJZvqqqeL1efD4fANHR0aSkpOjmpDKJRTLaCCHo6emhpaWFpqYmgsEgkZGRGI1GvRVLCMGZM2fYtWsX5eXl9Pb2EhYWxtq1a9myZQu5ublDqkIamMgSGRlJamqqHrEsjXglEolE8jByL48PKXyMEmNtbip5MLR4Sq0EODo6mtTUVBISEsYssaGtrY1vfOMb/Od//ider5e5c+fyyiuv8Oyzz5Kenj7q55dIRoNAIEB3dzednZ20trbqBorR0dFER0cPEnCvXr2qV3WcPHmSUCgEwLx583SxY/bs2UMWfQcmVEhzUsl44fP5aG9v58aNG7qQYTQaB93HW1paePfdd3n33Xf1iqZZs2axZcsWNm3ahN1uv+d5Bsana4ksKSkpWK1WKexJJBKJ5KFHmpuOMYqibAe239yTLpl43C6ecvr06djtdsxm85juigWDQZYvX86NGzfIzs7mlVde4bnnnhtyBKFEMpHweDx0dXXR1tZGZ2cnqqpiMBiIiYnBZDLpxwWDQU6dOkV9fT11dXWDWljWrl1Lbm4u69evv6+0Ir/fr1drGQwG7HY7ycnJxMfHD8n0USIZCVRVxel00tzcTGtr622NSt1uN1VVVbz77rscO3YMIQRWq5WdO3eydetWZs+efc/zCCHweDx4vV49Pj0tLQ2bzSY3SCQSiUQiGYCs+BglZMXHxORmJ3uTyURqaio2mw2z2TymO8AOh4OjR49SWFjIuXPn+M1vfkNsbCzPPfccmZmZYzYOieRBGdjC0traSm9vL0KI20bO9vb2Dmph6enpAfojZ7WqjpUrVw65hUWr1vJ6vaiqSmRkJMnJyXprmrxWSsYSl8ulx9BqRqUmk0n/DqiqyokTJ9i1axeVlZV4PB4iIiLIyclh69atrF27dkgeMz6fT/eeiouLIz09HbvdLsU9iUQikTyyyIoPySOP1tuvRWKazWYyMzOx2WyYTKYxL3d3Op1861vf4n/9r/9FIBDgnXfewWaz8fLLLzNlypQxHYtEMlz8fr/ewtLW1jaohcVisQz6Xl27do26urpbWljmzp3Ljh077ruFRVVVPB6Pfs6YmBimTZum+3VIDwPJWBIIBHA4HNy4cQOHw4GiKLekEV2/fp1du3axe/dumpubAZg/fz5bt26luLiY+Pj4IZ1noEnp9OnTpUmpRCKRSCRDRAofkocSbWHk9/sBiI+PJysrC6vVOqjUfizp7u7m3/7t3/jmN79Jd3c3U6dO5Y//+I+ZOXMmWVlZ4zImiWSoCCH0FJa2tjacTidCiDu2sJw+fVpvYbl69Srw+xaWnJwc1q9fT1JS0pDPPzByVlEULBYL06dPx2KxjIuAKXm0uZNRqcVi0YW33t5eysvL2bVrF6dPnwb6zXlfeukltmzZMqTrfigUwu12EwgEiIiIICMjQ08VkwKfRCKRSCRDRwofkoeGm40MbTYbycnJ2Gy2CVH+W1JSwuHDh5kyZQp/9Vd/xac+9SmmT58uF2ySCUswGKS7uxuHw0FraysejwfoFzDMZvOgFhan08nBgwdpaGjg0KFDdHd3A5CQkMC2bdvIyclh1apVw2ph0aKkk5KS9GSKqKiokX/DEsk98Hq9dHR06EalBoMBk8mkt1QFg0EOHjzIrl27qKurw+fzERUVxaZNm9iyZQsrV668p9HowIomg8FAYmKibsoro5YlEolEIhke8g4qmdQM3A3TjAxTUlKwWCxDXmCNFn19fVRUVPD4449z4cIFnn/+eUpLS3nhhReYOXOmFDwkEw4hBG63m+7ubtrb23VjUq2dZKAxo6qqnDt3joaGBhoaGnj//ffRPKPmzJnDc889p7ewDHVnWhMvA4EAAEajkWnTpmGz2WTkrGTcCIVCOJ1OmpqaaG9v11tNBn4fLl26xK5du9izZw8dHR0ALF26lK1bt1JYWEhsbOxdz3Gz/5TFYmHWrFnY7fYhxddKJBKJRCK5O1L4kEw6gsEgbrebUCiEwWAgISGB5ORkrFbrhJggulwu/vM//5N/+Zd/oaOjg5///OfMnDmTJ598kqysLCl4SCYUwWCQnp4enE4nLS0teqRzZGQksbGxg8SG7u5uDh06RENDAwcPHsTpdAIQGxtLYWEh69atY82aNSQkJAzp3EIIPYVFa5ux2Wx6Kb/RaJTfF8m40dfXR2trK42Njfh8PsLDwwdVOnV1dbF3717effddzp8/D0B6ejp//Md/zJYtW4aUyuX3+3G73aiqSmxsLNnZ2SQkJGA0Gkf1vUkkEolE8qghhY//f3t3Hh13fd/7//nRaB0tI412WfImW7KxsQ1ewAtggwEZOylJC01ZSmh/TdMmbZOUnqanS5amoe1JITRJe9P09HJvm3vbpDcpCQYTQjEkNmAg8YLxKi8g2Za1jaTRMqOZ+fz+mJlvZmRJlm1Jo+X1OGfOxJrvfOcjha+keen9eb9lWkj85TAjI4Py8nJKS0spLCycMlMb/H5/UuBRXl7OH//xH7NixQqWLFmiN3AyZfT19dHd3e2Mm403G83JyUlqTGqt5ejRo+zZs4e9e/dy6NAhIpEIAIsXL+aXfumX2LBhAytWrBhzCX44HGZgYIBAIOC8Zk1NjdOYdKpczzI7BYNB2tvbaW5uxufzOY1K4z1sBgcH+clPfsKzzz7LT3/6U0KhELm5uXzwgx9kx44drFq16rIVTonhfWZmJvPmzaOsrGzSJ4uJiIjMJgo+ZEoaOqIyKyuLmpoaZ0TlVCx5f+SRR/je975HeXk5n/3sZ3n44YdZunSpfpGVlAuHw05VR0tLC729vU5Vh9vtTgot/H4/r7/+Onv37mXv3r1O2b7b7ea2225jw4YNbNiwgfLy8jG9dryqI34tp6WlqTGpTCmRSASfz8eFCxe4cOEC4XCYrKwsJwS01nLkyBGeffZZXnjhBScQWbduHTt27GDLli2X3VoZiUTo6+sjGAzicrkoLy+noqKCoqIiNSkVERGZBAo+ZMoYusd5qo+o7Onp4Tvf+Q6PPPIIJ06c4IMf/CD19fU89NBDCjwk5eJVHa2trbS1tTnTUIaOm7XWcvLkSadXx4EDB5wKkAULFtDQ0MDGjRtZtWrVmKsxhk5Vys7Oprq6Gq/Xi8fjUVWHTAm9vb20trbS1NREf38/LpeL3NxcJwhsa2vjueee49lnn+XUqVMAzJ8/n4ceeoht27ZdNvwb+jOtuLiYqqqqKbMtU0REZDZR8DEKY8zvAn8EVAKHgU9Za3+S2lXNLEPfIOXl5bF48WK8Xi95eXlTMjzo6enhG9/4Bl/5yldob2+nv7+f9evXs2nTJn791399Sq5ZZr6RqjoyMjIuqero6enhjTfe4PXXX+e1116jpaUF+MW42Y0bN7JhwwaqqqrG/Prxqo5QKORUdSxYsIDCwsIpey3L7DM4OEhHRwfNzc10dHQA0ZDd6/UC0aktL730Ejt37uT1118nEolQUFDAfffdx/bt21m2bNll/1sOBoP09vYC0Z9p9fX1lJSUTInpYiIiIrOVgo8RGGN+FXgK+F3gp7H7540x11lr30vp4qa5xMkNxhg8Hg8LFy6kqKjI2Uc9FfX09PD1r3+dr3zlK3R0dFBZWcmf/umfsnXrVurr6/XGTiZdf3+/M4Glra3NCR2GVnWEw2HeeecdXnvtNV577TUOHz7sVHXMnTuXX/u1X2PDhg3ceOONYx4TG4lEknp1ZGZmUlFRQUlJCQUFBRo3K1OGtZbu7m4uXLjAuXPnCIVCZGZm4vF4SEtLw1rLgQMHePbZZ3nxxRfx+/24XC42btzIjh07uOWWWy5boREKhejt7XW2Zi5YsIDS0lL17RAREZkiFHyM7DPA09bab8X+/XvGmAbgd4A/Sd2ypqd4M7f4G7OpNHZ2rP7kT/6Eb3zjG07g8dBDDynwkEmVWNVx8eJF/H4/AOnp6ZdUdbS1tTlBxxtvvEFXVxcQ7dWxadMm1q9fz/r165kzZ86YXz+xqiMeWs6dO5fCwkLy8/On3HY0md36+/tpa2ujqakJv99PWloaubm5zlar8+fPs3PnTp577jneey/694y6ujp27NhBQ0ODUwUyksRx6unp6VRWVlJeXk5hYaGuBRERkSlm2gYfxphfAW4DVgErgXzg29bah0Z5TjXwRaABKAbOA/8FfMFa25lwXCawGvjKkFP8CNgwbp/EDDc4OOh0rk9PT6e0tJSysjIKCwunxf7m7u5u/vmf/5mPf/zjnD59mrvuuouioiIefPBBBR4yKay1SVUdiRNYhlZ1BINB3nzzTSfsOHHihHOe+vp6PvzhD3PzzTezYsWKK+rVEa/qiDdDLS8vd5oMq6pDpppwOExHRwfnzp2jra0Nay3Z2dkUFRVhjKGvr48XXniBZ599lrfeegsAr9fLAw88wI4dO6irqxv1/PFrcmBgwBmnXllZidfrHfNkIxEREZl80/mn9J8RDTz8QBOwZLSDjTG1wF6gDHgGOAqsA/4AaDDGbLTWtscOLwFcQMuQ07QAW8frE5iJAoEA/f39Tm+BqqoqSktL8Xg80+aXwu7ubr72ta/xd3/3d3R2duLz+filX/olrr/+ej7wgQ8o8JAJNTg4mFTVEe8VMFyvjvfff98JOt566y36+/sBKCoqYtu2baxfv56bbrqJ4uLiMb320AksxhgKCwuZP38+Ho+HvLw8/SVbphxrLT09PVy8eJHm5maCwSAZGRlOU+xIJMJbb73Fs88+y3//93/T399PRkYGd9xxBzt27GD9+vWX/fk0MDDgXF/x7ZnFxcXTpmJRRERktpse70SH92migcdJopUfL1/m+H8gGnr8vrX2a/EPGmOeiJ3rr4CPT8xSZ66hXeuzs7OZN28excXFzv7p6aKrq4uvfe1rPPHEE3R2djJnzhw+8YlP8NBDD7F48WIFHjIhIpEIfr/fqerw+XxEIhEg2nQx/pdqiE6h2LNnjzNutrm5GQCXy8WKFSuc7Sv19fVjvvYSe+5A8gSWgoKCaVGdJbNTIBBwtrL09PRgjMHtdpOXlwfAe++9x7PPPstzzz3HhQsXAFi+fDk7duzgzjvvxOPxjHr+wcFBp2+H2+1m0aJFlJSUOOcXERGR6WPaBh/WWifouNwb0li1x13AGeAbQx7+HPAx4GFjzB9aa3uBNiAMDJ1VVw5cuKaFzwBDmxrm5uayaNEivF7vtG7k9vWvf50///M/Z86cOXzyk59U4CETpr+/n+7ubtrb22lra3OmGmVmZpKXl4fL5QKiweLx48edqo4DBw4QCoUAqKys5MMf/jAbNmxgzZo1Y34zFolECAQCTliZlpaG1+t1KrNyc3P137xMWeFwmM7OTi5cuEBLSwuRSCRp21dPTw8//OEP2blzJwcPHgSgvLycRx99lO3btzN//vzLnr+3t5dQKERGRgY1NTWUlZVNyZHqIiIiMnbTNvi4Qlti9z+y1kYSH7DW9hhj9hANRm4GXrLWBo0xbwN3At9NOPxO4P9NxoKnmkgk4jRxg2ip7/z5851JLNPxjVK8wuM3f/M3aW9vZ9OmTXzuc5/jgQceUOAh4ypx+0pra6uzfcXlcpGdnZ00zai1tZU333zTGTfb3h7dgZeVlcW6devYsGEDN998M/PmzRvTf6NDt68AFBQUUF1djcfjIT8/f9psQ5PZq6enh9bWVpqamggEAqSnp5Ofn4/L5SIUCrF3716effZZXnnlFYLBIFlZWWzbto0dO3awZs0aJ0wcTnyseiAQIC0tjdLSUqqqqigqKhr1eSIiIjJ9zJbfdutj98dHePwE0eCjDngp9rEngH81xuwD9hDdBlMF/I/hTmCM+QzRSTAAly2hnQ4SO9anpaVRVFREZWUlhYWF5OTkpHp5V83n8/H3f//3PPnkk/h8Ps6dO8dv/uZvMm/ePD73uc8p8JBrFg6HL9m+Yq3FGHNJU9Kenh727t3Lvn37ePPNNzl9+rRzntraWqdXx6pVq8bcTDQUCjEwMHDJ9pWioiKNmpVpIxgM0tbWRnNzszOVKDc31wkKT5w4wc6dO3n++eedgPDGG29kx44d3HHHHaOORx+6TbOwsJDFixfj9Xp1fYiIiMxAsyX4iKcQXSM8Hv94YfwD1tr/MMYUE22iWgm8A9xjrT073AmstU8QDUsAqK6utte45pQYHBykv7+fUCiEy+WipKTEGc833X8Z9Pl8PPXUUzz55JN0dXVRXV3Npz71KR588EFqa2sVeMhVs9bS29tLd3c3bW1tdHR0MDg4iDGGrKws5y/TEO1L8Oabb/Lmm2+yb98+jhw54lRilJWVsX37dtauXcu6desoKysb0+sP3b7icrmc7SsFBQXTtipLZp9wOIzP5+P8+fPDbmVpb29n165d7Ny5k+PHo3/LqK6u5mMf+xjbt2+/7HjmYDBIb28v1lry8/Opq6ujpKQEt9s9GZ+eiIiIpMhsCT6uirX2H4g2RZ3RgsEgfX19WGtJT0+noqLC2e8/1rGX08EPfvADPv/5z1NTU8OnP/1pBR5y1eJ/Le7u7qajo4PW1lanT0dGRgY5OTnk5+cD0TdyR44ccSo6Dhw44Bybn5/Pbbfdxrp161i7dq22r8islTiVZehWlkAgwI9//GN27tzJa6+9RjgcJi8vjw996ENs376dlStXjnrdJI5Wz87OZsGCBZSWlk7rnlQiIiJyZWbLb8bxio6R9p/EP+671hcyxtwH3Of1eq/1VBPGWuuMnYVo74CamhpKSkrweDwzZk9zZ2cnX/3qV/nQhz6Ey+Wivr6eL3/5y9x///0sXLhQv/DKFRkYGKCnp4fOzk7a2tqSwsLEPh3WWk6fPu0EHW+//TZ+vx+IXms33HCDU9FRX18/5uttcHCQgYEBQqEQ1lpycnK0fUWmtfhUlubmZrq7u4FfbGWx1nLgwAF27tzJiy++iN/vx+VysX79erZv384tt9wy6ijZxK2a6enpVFVVUVZWRmFhoZqUioiIzEKzJfg4FruvG+HxxbH7kXqAjJm19rvAd6faVpfE/czWWtxuNwsXLqS4uJj8/PwZ9YtgPPD46le/Snd3N8ePH+exxx6joqKCz372swo8ZEwCgQA9PT34fD7a2tqcsZYul4usrCyn9D4edLz99tvOrbOzE4huOVm2bBlr165l7dq1rFixYszjYcPhMAMDAwSDQay1ZGRkUFxcTElJCQUFBbjdbv23LNNOfCrLuXPnaG1tvWQrS1NTE8899xzPPfccTU1NANTV1bF9+3YaGhooLi4e8dzDNSmtrKykqKhIFVAiIiKz3Gz5TSA++vYuY0xa4mQXY0w+sBHoA15PxeImSvyXwMSy+rlz51JUVEReXt6Me9PU2dnJk08+yVNPPUV3dzdz587lscce44EHHlCFh1xWMBikp6fHaUjq9/uTGpLGx1laazlz5gxvvfUWb7/9Nj/72c/o6OgAoqO16+vrueeee1i9ejU33njjmMfMhsNhAoGAMybaGENRUZGz7SwvL29GBZQye1hrk7ayBIPBpK0sfr+fZ555hp07d/Lzn/8cgOLiYh566CG2b9/O4sWLRz33wMAA/f39zjVTV1eH1+sdc8goIiIiM9+sCD6stY3GmB8RndzyCeBrCQ9/AcgFvmmt7b3W10r1VpdwOOyEHfFfAmtraykqKprxzdsOHDjAX/7lXzJv3jz+6I/+iAcffJD58+cr8JBhJQYdbW1tTqk9MGzQkVjRkRh01NXV0dDQwOrVq7nhhhsoKCgY0+sPF3QUFhYyd+5cCgoK1KdDpr3+/n7a2tpoamrC7/eTlpaG2+0mLy+PUCjE66+/zs6dO3nllVcIBAJkZWVx1113sWPHDtatWzfqf/+JTUrz8vJYsmQJxcXFM/7nnIiIiFwdY+2U2pExZsaYe4F7Y/+sAO4GTgE/iX2szVr7WMLxtcBeoAx4BjgC3ARsIbrFZYO1tn281lddXW3jZbrjaffu3WRnZyc1HQ2FQvT19TmTWIqLi51JLKPtgZ7uOjo6eOKJJ9i0aROVlZXOL9L33HMPCxYsSPXyZIqJb12JV3TE3zRBNOjIyspygo6zZ886FR1Dg47FixezevVq1qxZc81Bh8fjcXrr5OXlzahmwjI7DQ4O0tHRwblz55wRs9nZ2c7PoqNHj/L888/zwgsvJI2gveeee9i6deuoFVKhUIje3l7C4TBZWVnMmTNHTUpFREQEAGNMs7W2esTHp3Hw8Xngc6McctZaO3/Ic2qALwINQDFwHvg+8AVrbed4rm+igw9rLf39/U7PgbKyMqdx20x/83Tu3DmeeOIJvvnNb+L3+2loaOBLX/oSpaWlzJ07N9XLkyliYGAAv9/v9OiINxiNj5iNBx2RSITTp0/z85//3Nm6En9Dlhh0xCs6PJ6ReiQnS+zRET9XYWGh06NDQYfMFJFIhM7OTlpaWmhpaSEUCpGZmYnb7SYtLY3333+fXbt2sWvXLs6ejU6Er66uZvv27Wzbto3q6hF/R3GalMaD/YqKCifY19YvERERiZuxwcdUlbDV5b74m6fxFC8Jzs7Opry83Plr8WwoiW9ubuaLX/wiTz/9NMFgkNraWh599FFnS4vMXvF9/n6/n87OTtrb2+ntje5cGxp0BAIBjhw5wv79+zlw4AAHDhxI2uZSV1d3VUFHKBQiEAg4QUdaWppT0aGtKzLTWGvx+/20trbS3NzMwMAALpeL3Nxc0tPTaW9v58UXX+T555/n8OHDAHi9Xu688062bdvGsmXLRqzSsNbS19eX1KS0oqICr9era0hERESGpeAjRSaq4qOlpYWsrCyn/8BsEG8w+e6777JixQqWLVvGRz/6Ue67775R/1IoM1e84ik+Xra9vd0Zz5yWluYEHcYYfD4fBw8eZP/+/ezfv58jR44wODgIRKeuLF26lFWrVjm3wsLCMa1hcHCQQCCQdK6ioiJnUlJeXp7epMmM09fXR1tbG+fOnXOqqNxuN1lZWfT29vLyyy/zwgsvsG/fPsLhMG63m82bN7Nt2zbWrl074jUxdMy6x+OhqqqKkpISjWoWERGRy1LwkSITFXzMJnv27OHxxx9ny5YtbN68GYAzZ85wyy23UFZWltrFyaSy1tLb24vf76ejo4P29nYCgQDWWtLT08nKynImODQ3NzvVHPv37+f06dPOeXJzc1m5ciUrV65k1apVLFu2bEx9cKy1DA4OMjAwQDgcBiAjIyMp6MjNzcXlck3MF0AkhYLBIB0dHTQ3NzujmuN9O0KhEHv37mXXrl28+uqrBAIBXC4XGzZsYNu2bdx6662jXmPBYJC+vj4ikQhut5vq6mpKSkrIzc2drE9PREREZoDLBR/6c6RMKdZadu3axeOPP85PfvITjDEUFBSwefNmamtrWb16daqXKJMgEolcEnQEg0En6MjOziYnJ4dwOMzx48eTgo7ELWYVFRU0NDQ4QcfChQvHFE5EIhGCwSCBQMAJOnJycigvL3fGQefm5s6aqiuZfcLhMJ2dnVy4cIGWlhYikQhZWVnO1q/9+/eza9cuXnrpJbq6ugC44YYbuPvuu9m6deuolVOJDbmzsrKYN28epaWlFBQUqEmpiIiITAgFH+Ms1eNsp7MjR47wwAMPsH//flwuFx/4wAd45JFHuPvuu0ft9C/TXyQSwe/34/f7aW9vp6Ojg8HBQay1ZGRkkJWVhdvtpq+vj0OHDjkhxzvvvOOUxscbkd5+++2sWrWKlStXUlFRMabXj09ciYcrEK0Oqa6uprCwkLy8PHJycvSmTGY0ay1dXV1cvHiRc+fOMTg4SHp6Ovn5+bhcLk6ePOlMZLlw4QIAtbW1PPzww9x9991UVlaOeO7EUevp6emUl5c7TUpVKSUiIiITTVtdJoi2uoxN/K/qeXl5vPvuu2zZsoU77riDhx56iNtvv52cnJxUL1EmQDgcxu/309PTQ3t7O52dnU6vjMzMTLKyssjIyODChQscOHDA6dFx4sQJIpEIAFlZWVx//fVONcf1118/poAsvm0lEAgQCoWAXzQi9Xq9zsQV9RWQ2SC+jaytrY2mpib6+/tJS0sjNzeXjIwMzp8/zwsvvMDzzz9PY2MjAOXl5TQ0NLBt2zYWLVo06rn7+/udEc4lJSVUVlbi9Xo10UhERETGlXp8pIiCj9H19vbyrW99i6985Sts376dj33sY0D0L/8rV650+jXIzBAKhS4JOkKhEMYYMjIynB4Ax44d4+DBg86tpaXFOYfX603qz7FkyZIxNQ+NV3PE33xBtD9BUVFR0rYV/dVZZpOBgQHa2tpobm6mp6cHiG7nys7Oxufz8eMf/5hdu3axf/9+INps9I477mDbtm2sXLlyxG1eiU1KrbV4PB7mzJlDcXHxmPrpiIiIiFwN9fiQKaWzs5Ovf/3rPPXUU7S3t1NcXExhYSE5OTnU1dVpCsYMEQgE8Pv9dHV10d7eTnd3t7OFJDMzE7fbjd/v59ChQxw8eJADBw5w+PBhJ5wwxrBw4UI2bNjAypUrWbFiBTU1NZfdahKJRJxqjnhvjng1x5w5cygoKCA3N5fs7GxtW5FZJxgM0tnZyblz5+jo6CASiZCdnU1hYSGBQIBXXnmFXbt2sXfvXsLhMFlZWdx55500NDSwYcOGUas0hjYpXbRoESUlJdqmKCIiIlOC3mXKpDlw4ACbNm3C7/czZ84cPvvZz/Lggw9y3XXXqUnkNBYvZ/f7/fh8Ptrb2+nt7XUez8rKIjc315m2Eq/mOHPmjHNMTk6OE3CsXLmS5cuXk5+ff9nXDYVCSSNl4+eqqKigsLCQ3NxcVXPIrJbYpPTixYuEw2EyMzMpKCggEomwb98+du3axe7du+nr6yMtLY1169bR0NDAli1bRp2uMjg46IQdalIqIiIiU5mCj3Gm5qbJGhsbMcZQVVVFIBDgxhtv5K677uJXf/VXqa2t1S/H01A4HE6auNLR0UEwGASi1RVZWVlkZWVx5MgRpz/HoUOHnMkPAFVVVTQ0NDhBR21t7WWrfYbbshIfKRtvQJqbm6veHDLrxZuUtra2cu7cOaehaF5eHmlpaRw+fJjnn3+eF198kY6ODgCWLVvGtm3buPPOOykuLh7x3IkTWTIyMqiqqqK8vByPx6MAW0RERKYs9fiYILO9x8fBgwf567/+a/7jP/6DO+64g8cffxyAyspKqqqqUrw6uRLBYJDe3l6nP4fP53P6c6Snp5OVlUVHR0dSb45jx445W03S09NZsmQJK1ascIKO0tLSUV8zcZxsvJlpfMtKUVER+fn55ObmatKKSIy1Fr/f74Qd/f39uFwucnJyyMzM5MyZM+zatYtdu3YR/9k0d+5ctm3bRkNDAzU1NSOeOxwO09fX50x5KS0tdaqqtD1RREREpgL1+JBJtXfvXr785S+zc+dOAG666SZ++Zd/mblz5172za6kXvwNTm9vLz6fj87OzqRtK5mZmWRmZtLc3MyBAwecio7EJqSFhYVs3LjRCTmWLl06alNDay3BYJBgMOhMWTHGOONk43053G63tqyIDNHX10d7e7vTpNQYg9vtxuv10trayg9/+EN27drF0aNHgehklQceeICGhgaWLl06YnAYiUTo6+sjGAySlpbmTGQpKirSRBYRERGZdhR8yLg5dOgQGzduxBjDli1bePTRR9mxYwdFRUWpXpoMI96bI17N0dHRQXd3t1Nh4XK5nOk6hw8fdkKOw4cPMzAw4Jxn4cKFfOhDH3IqOubOnTvim6mR+nJkZ2dTWlpKUVERbrfbGaUpIpcaGBigs7OT5uZmfD4f1lpycnIoKiqit7eXXbt28cILL/Dmm29irSU3N5cPfOADNDQ0sGbNmhEDxEgk4oyfTUtLw+v1UlVVRVFRkSZtiYiIyLSm4EOuWjgc5nvf+x5lZWXU19cTDAb55Cc/yebNm7nrrrsu25xSJlcgEHB6c/h8Pnw+n9ObwxhDZmYmxhhOnTrFkSNHOHz4MEeOHCFxy1Z2djbLly93GpFef/31FBQUjPia8b4cwWDQmeqSkZFBYWFh0ihZ9eUQGd1wE1mysrLweDwMDg6yZ88edu3axU9/+lOCwSAZGRncdtttNDQ0sGnTphGrruIB6MDAAMYYCgsLqa2t1fhZERERmVHU42OCzOQeH8FgkH/7t3/jb/7mbzh+/DirV6/mm9/8JgDXXXcdOTk5KV6hxBsQxresdHR00N/f7zyekZGBtZbGxkaOHj3Ku+++y7vvvsvZs2dJ/J4wb948li5dyvXXX8/KlStZtGjRiHv643054ltWjDGkpaWRn5+P1+t1tqyoL4fI2IRCIXw+3yUTWXJycgiHw7zxxhu8+OKLvPLKK/T29mKM4cYbb2Tbtm3cfvvtI4aS1loCgYDzPcHj8VBZWUlxcbG+f4uIiMi0pB4fk2wmT3Xp6+vjW9/6Fl/5yldoamoiLy+P3/iN3+DBBx/k+uuvVyl0isT7cvT19dHT00NnZyc9PT1JW1aMMTQ3Nzshx5EjRzh16pTTgBRgzpw5bN26laVLl3LdddexZMkS8vLyhn3NxC0rwWDQCTLcbrdGyYpcg3A4jM/n4+LFi7S0tDgNRfPy8pyw48c//jGvvPIKfr8fgKVLl3LnnXdy9913U15ePux5E8OO+PaXxYsXU1JSMurIWhEREZGZQBUfE2QmVnycOnWK+vp6PB4PDzzwAA8++CCrV69WV/9JFAqF6O/vp6+vj+7ubnw+Hz09PU6AkZaWhsvlckKOI0eOcOTIEU6cOJHUU6O8vNwJOOIhR2Fh4YivGw6HnSkr2rIiMr4ikYgTdly4cIFQKERaWhputxvACTt2796dFHbccccdbN26lerq4f+4MTTscLvdVFZWUlJSQn5+viqvREREZMa4XMWHgo8JMhOCj/Pnz/Pkk0+yaNEibr75ZgYHB9m3bx8bN25k+fLlpKWlpXqJM1p8u0piyOH3+5PGuxpjaGpq4uTJkxw7dowjR45w7NgxAoGAcx6v18t1113H0qVLWbZsGUuWLKGkpGTU1x0cHCQYDCa9lrasiIyfSCRCd3c3ra2tnD9/nkAggMvluiTseOWVV+jp6QFgyZIlbN26VWGHiIiIyBDa6iJX7NSpU/zt3/4tTz/9NIFAgA0bNrB69WqKi4v5+Mc/rl+cJ8Dg4KATcnR1deHz+ejt7XWqK9LS0hgcHOTMmTNOyHHs2DFOnTrljICF6F79G264Iamao6ysbNj/z+LbVeJ9Oay1SX05KioqyM/Px+12k5OTo8oekWtkraWnp8cJO/r7+53KjszMTN544w1eeukldu/e7YQd9fX13HnnnWMOOwBycnJYtGgRXq9XYYeIiIgICj4kwfnz53nsscf493//dyKRCMuXL+fRRx/lvvvuo6amJtXLmzGCweAlIUdfX58TcrhcLrq7uzl9+jQnTpxwQo6hFUTl5eWsX7+e+vp651ZZWTliyBGv4kjc8pKeno7H48Hj8ZCfn09OTg5ut1vVPCLjJB52tLW1OWEHRPvh5Ofns2/fPmcbS2LYEa/sGOl773CVHbW1tZSUlJCXl6ewQ0RERCSBtrpMkOm01SUUCpGenk5zc7OzJeLRRx/l3nvvHbFRnoxNIBBwQo74CNnE6SrGGFpbWzl16hQnTpzg+PHjHDt2jPb29qRj5s2b54QbdXV11NfXU1RUNOxrWmuTpqvEZWZm4vF4nMaj8UoOvUESGV9Dw46+vj6MMeTk5OByuXjzzTedaSzd3d0A1NXVOZUdo4UdAwMDDAwMANHKDm1jEREREVGPj5SZ6sGHtZYf/ehHPP74405lB0B7eztr164d8U21jCwecvT29jqVHIkhRyQSobm5mVOnTjkBx4kTJ+jr63OOyczMZNGiRUlVHIsWLRpxxGS86ejg4KAzQhYgOzubwsJCPB6PE3JkZWXpjZHIBBku7EhLSyM7O9sJO+KVHYlhR7yyY+7cucOeNxKJMDAw4DQWLigooKKiAq/Xq8oOERERkRj1+JAk4XCY73//+zz++OP87Gc/w+VyUVZWBkR/Cc/Pz0/xCqeHeMjh9/udkCP+V9j442fPnqWxsdHZrjK0H0d+fj7XXXedU8FRX1/P/Pnzh+2lEd+qEt+uEpeWlkZeXh4lJSUUFBTgdrudfgEiMrHiDUrb29s5f/58UiVGTk4O+/btY/fu3bz66qt0dXUB0e+zDz300KhhRzgcpr+/3xkV7fF4WLBgAV6v12l+KiIiIiJjp+BjnBlj7gPu83q9qV7KJc6ePctdd93F8ePHycrK4v777+fhhx/mjjvuGLGiQKIhRm9vL729vfh8Prq6upw3ONZaurq6OHPmDKdOnXL6cTQ3NyedI96PY8mSJU7QMVI/jsQqjviYWohWgxQUFDhbVeJvrlwu18R+AUTEEYlE6Orqcio7AoEAaWlp5OTkkJaWxp49e3j55Zd57bXXnO8Tixcv5oEHHmDr1q3Mmzdv2PMmhh1paWl4vV4qKiooLCzU92cRERGRa6TgY5xZa78LfLe6unpK7CGKN9CsqKggEAiQnp7Oo48+yoMPPsgtt9yiyoAE8WaB8e0qQ0OOSCRCS0sLZ86cobGx0dmu0tHR4Zwj3o/j7rvvTtquUlhYOOzrxQOOeBWHtdYZaRmv4ogHHNqqIpIaoVDICTsuXLjghBNut5ve3l5eeeUVXn75Zd5++23C4TDGGFauXMnmzZvZvHnziNNYQqEQ/f39DA4OkpaWRklJiRN2ZGVlTfJnKSIiIjJzqcfHBEl1j4/Ozk6+8Y1v8NRTT7FmzRq+9KUvAZCVlcWSJUtm/WjSy4UcwWCQ5uZmTp8+7YyPPXHiRFLPjqysLGpra8fUjyMcDjsBR2IvjngVR2IvDlVxiKTe4OAgPp+P1tZWWlpaCIVCuFwucnJyOHfuHLt37+bll1/m8OHDAGRkZLBu3Tq2bNnCrbfeykhVf/GpTpFIhPT0dEpKSigvL6ewsFBBtIiIiMhVUo+PWebChQs8+eST/OM//iM9PT1UVlayatUq8vPzWbRo0awcUzo05Ojs7KSrq4tAIABAb28vZ86ccUKO48ePc+rUqaRtJgUFBSxbtixpsspw/TiGjo2NB4vGGHJzc6moqHB6caiKQ2RqGRgYwOfz0dLSQnt7O5FIBJfLRXZ2NsePH2f37t3s3r2bM2fOAJCbm8vdd9/N5s2b2bBhA7m5uZecc+jY2ezsbGpqaiguLsbj8cz6EFpERERkMug3rhnkvffeo66ujkAgwMKFC3nsscf4yEc+wuLFi2fNm+v4m4yhPTniExHa29udfhzxkGO4fhwbN25MquSoqKi45GsYn7YQn6gSl5GR4VRx5OXlOVtV9AZHZGqx1jph6IULF+jq6sJaS2ZmJtnZ2ezfv5/du3fzyiuvcPHiRQCKi4v58Ic/zObNm1mzZs2wVRrWWvr7+53vO263m4ULF1JcXEx+fv6sDKBFREREUknvxKa5d955h/7+fpYtW0Zraysf/vCHWb16Nffffz81NTWpXt6EstYyMDBwyXaVQCDgjI49ffp00naVzs5O5/lpaWnMmzePhoaGpEqOof04rLWEQiGnkiOxisPtdlNaWorH43GqOLKzs2dN0CQy3UQiEXp6eujs7OTcuXPOOOl4T4033niDV199lb1799Lb2wtATU0NDz/8MJs3b+b6668fNrgIhUJOEArRqU3z58+nsLBQY2dFREREUkw9PibIRPf4eP311/nyl7/MD3/4Q5YtW8bTTz+NMYaamhpnPO1MEv8L6tCQIxgMEgwGna0q8UqO4fpxLFq0yJmosmTJEhYtWkR2dnbS60QikaStKsYYrLVkZGSQn5/vvInJycnB7XarikNkGgiHw3R1ddHe3s6FCxcYGBjAGENOTg4XLlzgpz/9Ka+++ioHDhxwtrgtW7aMW265hc2bN1NbWztscBEMBunv73e2xBQXFycFoSIiIiIyOdTjYwax1vLiiy/y+OOPs3v3bgA2b97MRz/6UWpraykqKkrtAsdJJBJJCjk6Ozvp7u4mGAzS29tLY2OjE3KcOHGC06dPX9KPY/ny5UlVHPPmzbskpAiFQvT19TE4OEgkEgGiVRzZ2dmUlJQ4b17cbreqOESmmcTmpBcvXnSaCmdkZHDq1Cn27NnDq6++ytmzZ4FoOLpx40ZuvfVWNm3aRElJySXnjEQiBAIBBgYGsNaSlZVFVVWVE3YoCBURERGZmlTxMUEmouLj3LlzzJs3D2stDQ0NPPLIIzQ0NJCfnz+urzOZIpEIfX199PX14ff76ezspKenh8HBQdrb2zl58qQTchw/fpxz584lPb+iosIJN+KVHOXl5UkhRbyKI36Lc7lcSVUc8a0qGRkZk/b5i8j4sNbS19dHd3c3LS0tdHR0OJUYPT097Nu3j71797Jv3z5nC0tpaSmbNm3itttuY82aNZdUgEHyyFljDPn5+ZSXl1NUVKR+HSIiIiJThCo+ZpCqqir+4i/+glWrVnHHHXdMu1LqcDjshBzxPfbxkKO5uZlTp05x6tQpGhsbOXHixCX9OObPn8+2bducSo7Fixdf0o8jHA4zMDBAMBh0qjgAsrOz8Xq9l1Rx6E2LyPQVDofp7u6mo6ODlpYWp1+HMYbjx4/z+uuvs3fvXk6ePAlEv48sX76cjRs3Og2Mh1ZyWWudLSzWWlwuFyUlJZSVleHxeIYNR0RERERkalPFxzgzxtwH3Of1eu9rb29P9XJSJr6NJP4XWJ/Ph9/vZ2BgwKngSAw5BgYGnOdmZWWxePFip4qjvr7+kn4cw42NNcaQlpZGfn4+Ho+H/Px8p4pjuMkLIjL9DAwM0NXVRVtbG62trc4Wlp6eHt5++2327NmTVNXh9XpZv349Gzdu5KabbsLj8VxyzviEpviI6+zsbCoqKpyw1OVyTernKCIiIiJX5nIVHwo+JshENzedSgYHB52Qo6urC5/PR29vL93d3TQ2Njohx8mTJzlz5kxSPw6Px5M0Nrauro65c+cm7ZUPh8NOwBF/kwPRgMTj8eDxeMjNzXXGxqqKQ2TmiEQi+P1+fD4fLS0tzshZgJMnT7Jv3z727NnDiRMngF9UdWzYsMGp6hj6PSFe1TEwMEAkEsEYQ0FBgbOFRVNYRERERKYXbXWRcRUMBocNOVpbWzl58qQTcpw4cYLz588nPbeyspJbbrklqZIjsR9HvIojcSRkvNQ8Ly+P0tJSCgoKnIkqquIQmZkGBgbo7u6mra2NtrY2AoGAU9Xxs5/9jNdee43XX3/dqeooKirinnvuYcOGDdx8882XbIGDX/TqCIVCAOTk5FBdXY3X6yU/P98ZZysiIiIiM4+CDxlW/C+i8ckq8ZDD7/fT1NTkVHI0NjZy8uRJfD6f81yXy8W8efOS+nHU1dUllZjHqzh6enouqeIoKipSFYfILBIKhZy+PxcvXsTv92OtJRwOc+zYMX72s5/x+uuvc/z4cSDawyNe1bFhwwaWLl16yfeIxAksgNOro6SkhIKCAtxut6o6RERERGYJBR+CtZaBgQEn5PD5fHR1ddHT08Pp06edSo7GxkYaGxsv6cdRV1fHHXfc4YQctbW1Tj+OxF4c8WalI1Vx5OTk6K+uIrNAfPtKvFdHZ2cnkUiEcDjM2bNn2b9/P2+++SYHDx4kGAwCUFhYyLZt29i4ceOwVR2J21fC4TBpaWnk5eVRVVVFUVERBQUF6tUhIiIiMksp+JhlrLX09/dfEnK0t7c71RvxfhzvvffeJf04VqxYkdSTY+7cuc6biXgVR7xSZLgqjvhEFVVxiMwuw21fsdZy/vx5Dh06xNtvv81bb72F3+8Hot83Vq9ezbp161i7di11dXVJ3zMSt8Ylbl+pqqrC6/VSUFCgCSwiIiIiAij4mNEikUhSyNHZ2YnP5+PcuXNO9UY85Lhw4ULSc6uqqrj11luT+nGUlZVhjEmq4uju7gZUxSEiyQYHB52JTq2trfj9fiKRCBcuXODw4cP8/Oc/5+2336ajowOINiVdtmyZE3SsWLHikj4+iRUd8IvpK0VFRc4UJ21fEREREZGhFHzMEJFIxGk62tPTg8/no7Ozk7Nnz15SydHV1eU8z+VyMX/+fO65556kfhwFBQVA8kSVzs7OS6o4CgoKyM3Nxe12k52drVJykVlqcHDQ2b7S3t6Oz+fDWusEHQcOHODtt9/m4sWLznPq6upoaGhg7dq13HDDDeTl5SWdMxQKMTAw4Gx3ycrKoqysjJKSEvLz88nJyVHQISIiIiKXpeBjGgqHw0khR2dnJ21tbU7Akdh4NBAIOM/Lzs6mrq4uqYqjtraWrKyspCqOeMgBOPvkVcUhIoniDUnj21d8Ph+RSITW1laOHDniBB3nzp1znrNw4UJuu+021q5dy4033pjUpyPeoyMQCDhTnTIyMvB6vU7QkZubqy1yIiIiInLFFHxMMwcPHnTGxcZDjsbGRt577z0ikYhzXGFhIatWrXIqOJYsWUJNTQ0ulyupiqO3t5e+vj5AVRwiMrJQKITf708KOgYHB2lsbOTYsWO8++67HDx4MKmio6amhg996EOsWbOG1atXU1JS4jyW2Iw0PtkpMzOT4uJiiouLycvLIy8vT0GHiIiIiFwzBR8jMMbcCjwGrAaqgEettU+nck2/8zu/w/e//31aWlqSPj5nzhxuu+22pKajpaWlAElVHPF+HKriEJHLiW9diQcd8UlP7777LkePHuXw4cMcPnzYmfJkjGHhwoVs3LiRVatWsXr1aioqKpzzWWud8bKRSARrLTk5OerRISIiIiITTsHHyPKAd4D/HbulXGtrK7m5uWzbto2lS5c6W1by8/OTqjhCoRA+nw9QFYeIjE0gEEjautLd3c358+d55513OHr0KO+++y6NjY1Ya4Ho1rnly5ezYsUKVq5cyYoVK8jPz3fOF2+uHAgEiEQiGGOcqSvxoEM9OkRERERkMpj4L7EyMmOMH/jklVR8VFdX26ampnFdh7WWV155BZfLRSQScfbBwy+qODwej6o4RGRU8WbIvb29Sc1IT548yeHDhzl69CjvvPMO7e3tznNKS0tZuXKlc6urqyM9PZqdx3sExftzGGMwxpCfn4/X68Xj8ZCXl0d2draCDhEREREZd8aYZmtt9UiPT5mKD2PMrwC3AauAlUA+8G1r7UOjPKca+CLQABQD54H/Ar5gre2c4CVPuvhfTIPBoKo4RGTMAoEAvb29+P1+Ojo66OzspLm5mRMnTnDixAmOHDnCkSNHnGbIaWlpLFq0iNtvv90JOioqKpzQIh5y9PT0OK+RnZ1NaWmpE3Lk5uaSkZGRks9XRERERCTRlAk+gD8jGnj4gSZgyWgHG2Nqgb1AGfAMcBRYB/wB0GCM2WitbR/lFNPS2rVrnb+miogMFQwG6e3tpbe31xlrfebMGY4fP+40RT5x4oTT8wfA7XYnVXMsX77cGS0b30bX1dXlbHNJT0+nsLCQoqIiJ+TIysrS9yURERERmZKmUvDxaaKBx0milR8vX+b4fyAaevy+tfZr8Q8aY56IneuvgI8nfPxLwJ9e5pxbrLW7r3jlk0gTDkQkzlrrbFnx+Xy0t7dz7NgxJ9yIBx2JlRlZWVnU19ezZMkSli5dypIlS1i4cKGzhS4YDBIMBpNGWufn51NZWemMlM3JydH3IhERERGZNqZM8GGtdYKOy/3VMFbtcRdwBvjGkIc/B3wMeNgY84fW2t7Yx78K/NtllvHe2FcsIjK5wuEwfr+fnp4eOjs7OXnyJIcOHeLYsWPOze/3O8dnZ2dTX1/vBBxLlixh/vz5pKenJzVE7urqcirJcnNzqaqqwuPxOFvptI1ORERERKazKRN8XKEtsfsfWWsjiQ9Ya3uMMXuIBiM3Ay/FPt4GtE3qKkVErkG8N0d3dzdnz57lrbfe4siRIxw7dozjx49z8eJF59h4JceyZctYunQpS5cuZe7cuaSlpSWNtY5Xf6SlpZGbm0txcXFSyKG+HCIiIiIy00zX4KM+dn98hMdPEA0+6ogFH1fKGJMHLIr9Mw2Ya4xZBXRYay+pDDHGfAb4TPzfHo/nal5WRGYhay0DAwP09/fT29vLxYsXOXDgAAcOHODo0aMcO3aM9957z+mxkZaWxsKFC1m/fj3Lli1j2bJl1NbWYoxJGmsd7+ORnZ1NUVERHo8Ht9uthsgiIiIiMqtM1+Ajnip0jfB4/OOF1/Aaa0juM/KF2O1/AR8derC19gngifi/q6urNSdYRC4RCoXo7++nv7+f9vZ2Dh48yOHDhzl58iRnz57lzJkzXLhwgUjkF8VsVVVVbN261Qk56urqyMzMdEIOay09PT1OFUdJSQkFBQW43W6NtRYRERGRWW+6Bh8TLtbkVCMKROSqRCIRp4rD5/Nx6NAhDh06xPHjxzlz5gxnz56lubk5KeBwuVzU1NSwefNmamtrWbZsGddddx25ubnOdpV4VYe1loKCAmd8bE5OjvpxiIiIiIgMY7oGH/GKjpH2k8Q/7pv4pSQzxtwH3Of1eif7pUUkReJVHF1dXRw6dIiDBw/y7rvvcvr0aSfgCIfDzvFpaWlUV1dz2223sXDhQhYuXMiCBQuoqqrCGEMoFEoKRCKRCF6vl8LCwqStKhofKyIiIiJyedM1+DgWu68b4fHFsfuReoBMGGvtd4HvaquLyMxjrSUYDNLT08O7777L/v37OXToECdOnODs2bM0NTURCoWc440xVFdXs2nTJifgmDdvHlVVVbhcrqRjIRqI5OXlJY2N1VYVEREREZFrM12Dj3jvjbuMMWmJk12MMfnARqAPeD0VixOR6S8UCuH3+zl69CgHDhxwxsaeOnWK999/n8HBwaTj58yZw/r1651wo6amhqqqKjIyMpIqMzIyMnC73eTl5TnhRnZ2NtnZ2ZqoIiIiIiIyAaZl8GGtbTTG/Ijo5JZPAF9LePgLQC7wTWtt72SvTVtdRKYPay2Dg4P09vZy8uRJDh48yKFDhzhy5AiNjY28//77BIPBpOdUVlaybt06FixYkBRw5OTkYK0lLS2NrKwsCgoKnBGxmZmZZGVlkZWVRXp6uraoiIiIiIhMIhMfj5hqxph7gXtj/6wA7gZOAT+JfazNWvtYwvG1wF6gDHgGOALcBGwhusVlg7W2fTLWPpzq6mrb1NSUqpcXkZhwOIzf7+fUqVM0NjZy+vRpTp06xXvvvUdTUxMtLS20trYm9dQAKC8vp7a2lvnz5zNv3jzmzp1LVVUVbrfbCTiys7PJz89PmqCiyg0RERERkclljGm21laP9PhUqvhYBTwy5GMLYzeAs4ATfMSqPtYAXwQagHuA88BTwBestZ0TvWARSb2BgQHef/99zp49y3vvvcf777/P+++/T3NzM83NzZw/f5729naGC3kLCgqorKxk6dKlVFZWMnfuXGpqaqiuriY3NxeI9t3IyckhLy+PgoICp++GAg4RERERkelhylR8zDSq+BC5dpFIhLNnz3Ls2DHOnDlDU1MTTU1NTqDR0tJCR0fHJdUacYWFhVRVVVFRUUF5eTllZWWUlZVRWlpKeXk5brfbOTY9PR23201+fj55eXnO5JTs7GyNiBURERERmcKmU8XHjKAeHyJXpqenh2PHjnH8+HEaGxud7Shnz57l3LlzlzQRhWgVhtfrpbS0lOuuu47S0lKKi4udW0lJCSUlJc40FJfLRXZ2trMdJScnh8zMTOeWkZFxSRNSERERERGZGVTxMUFU8SESFQwGef/992lsbOTEiROcPHmSU6dOcebMGd577z18Pt8lz8nIyKCysjKpWqO8vJzi4mLKysooKioiPT0dl8tFZmamU5mROB0lPT2djIwMJ9hQqCEiIiIiMjOp4kNEJlRfXx9nz55Nah6a2G+jtbV12P4aXq+XOXPmsGbNGioqKqiqqqKyspKKigqKi4vJzMzE7XbjdrvJzc0lKyvLqcyI3zQhRURERERELkfBh4iMKBwO4/P5aGpqcqahnDp1ygk2mpqa6OjoGPa5Ho+HsrIyFi9eTHl5uRNuVFRUUFFR4TQKjY98jY97Tdx+IiIiIiIicq0UfIwz9fiQqai/v5+Ojg46Ojro7Oykra2Njo4O2traaG9vdx7r6OjA5/M5t56enmGrNYwxeL1eysvLuf76651gI74tpbKyksLCwqSeGvGKjXi4kZ6ubz8iIiIiIjLx1ONjgqjHh1yrSCRCX18ffr9/2Ft3dzc9PT10d3fj9/vp6emhq6vLCTd8Pp9zHwwGx/Sa8QqM/Px85z4/P5/i4uKkao2amhqnYsPtdic1ClVPDRERERERmUzq8SEyicLhMO3t7bS2ttLa2uqEEvFbT0+Pc4v/2+/309vb69zHb/39/Ve1BpfLRV5eHnl5eRQVFVFTU+MEGAUFBc59/FZUVERRURHFxcXOtJN4U9B4A9H09PSkUCMtLW2cv3IiIiIiIiITQ8GHyCgikQgdHR1cvHiR1tZW576lpYWLFy/S0tLihBzx7SNXUkVljCE7O5ucnBxnIklZWZnzsaG3xK0j8cafeXl55ObmkpeXh8fjobCwMKn6wuVyOeHFcP9bIYaIiIiIiMxkCj5kVolEInR2djoBxtAwIx5oJAYZkUhk1HPm5+dTWFhIZWUlS5YsobCwkMLCQoqKisjLy0sKKPLz8/F4PE7VRW5uLhkZGUkhxGi3ocdoO4mIiIiIiMjoFHyMMzU3nVyRSASfz5cUYCTeDw0y2tvbCYfDo54zHk6Ul5dTX1+Px+NxtoMUFRXh9XqprKx0bm63m/T0dGe8auJN1RQiIiIiIiKppeamE0TNTa+OtZaurq5hQ4yhW0taW1tpb28nFAqNes7ELSCFhYVOkFFYWEhxcTFFRUVUVlZSVVVFVVWVE2QMDTNcLpcqLERERERERKYYNTeVlLLW0t3dPeLWknigkRhkDA4OjnrO3NxcJ7Sora1N2lri9Xqdiow5c+ZQVVVFbm5uUhVGPMxQNYaIiIiIiMjMp+BDroi1lp6enmG3liRuK4nft7e3X3aUqtvtdqowFixY4AQZXq/XmTZSXl7OnDlzmDNnDvn5+cNuK1E1hoiIiIiIiAyl4GOWs9bi9/svqcYYurUkMcgIBAKjnjMnJ8cJL+bNmzdsRUY8yKiurqagoGDYrSUKMkRERERERORaKfiYgXp7e4fdWjJcmNHe3s7AwMCo58vOznZ6Y9TU1AwbZJSVlTFnzhxqamqcIGNoVYa2loiIiIiIiMhkU/AxziZyqsuhQ4d4//33k0KNoX0y2tra6O/vH/U8WVlZTpAxZ86cYYOM0tJSJ8jweDxJIYZ6ZIiIiIiIiMh0oakuE2Qiprps3LiRvXv3XvLxzMxMp0dG4vSSeJBRVFREWVkZlZWV1NTU4PV6R5xaIiIiIiIiIjKdaKrLDPKZz3yGrVu34na7KSkpoaqqiurqaoqLi8nIyLikKkNBhoiIiIiIiMx2qviYIBNR8SEiIiIiIiIiyS5X8aEmDSIiIiIiIiIyYyn4EBEREREREZEZS8GHiIiIiIiIiMxYCj7GmTHmPmPMdy43UlZEREREREREJp6Cj3Fmrf2utfb+nJycVC9FREREREREZNZT8CEiIiIiIiIiM5aCDxERERERERGZsRR8iIiIiIiIiMiMpeBDRERERERERGYsBR8iIiIiIiIiMmMp+BARERERERGRGUvBh4iIiIiIiIjMWAo+RERERERERGTGUvAhIiIiIiIiIjOWgo9xZoy5zxjznf7+/lQvRURERERERGTWU/Axzqy137XW3p+Tk5PqpYiIiIiIiIjMego+RERERERERGTGUvAhIiIiIiIiIjOWgg8RERERERERmbEUfIiIiIiIiIjIjKXgQ0RERERERERmLAUfIiIiIiIiIjJjKfgQERERERERkRlLwccojDF/Yox50xjTbYxpNcb80BizPNXrEhEREREREZGxUfAxus3APwAbgNuBEPBjY4w3lYsSERERERERkbFJT/UCpjJr7d2J/zbGPAx0ARuBH6ZkUSIiIiIiIiIyZlOq4sMY8yvGmK8ZY34S215ijTH/dpnnVBtj/sUYc84YEzDGnDHGfNUYUzQBS8wn+jXrnIBzi4iIiIiIiMg4m2oVH38GrAT8QBOwZLSDjTG1wF6gDHgGOAqsA/4AaDDGbLTWto/j+p4C9gOvjeM5RURERERERGSCTKmKD+DTQB1QAPzOGI7/B6Khx+9ba++11n7WWns78CRQD/xV4sHGmC/FqkhGu20e7oWMMU8Am4BfttaGr/ozFBEREREREZFJY6y1qV7DsGIBxMvAt621Dw3zeC1wEjgD1FprIwmP5QPnAQOUWWt7Yx8vAUou89LvWWv7hrzWk8BHgC3W2qNjWX91dbVtamoay6EiIiIiIiIicpWMMc3W2uqRHp9qW12uxJbY/Y8SQw8Aa22PMWYPcBdwM/BS7ONtQNuVvIgx5ingV7mC0ENEREREREREpoapttXlStTH7o+P8PiJ2H3d1b6AMeYbwKPAA0CnMaYidsu72nOKiIiIiIiIyOSZzhUfnth91wiPxz9eeA2v8bux+5eGfPwLwOcTP2CM+QzwmYQPRYwx56/gtXKA/jEcl0e0+atEjfXrliqTvb6Jer3xOu+1nOdqnnslz7mSY3UdJpvK16GuwfE7z0Rfg1dyvK7BZFP5GgRdh+N5Hv0snLqm8nWYirVNxGvOhmvwSo7XNZisfLQHp3PwMeGsteYKjn0CeCL+b2PMd6y194/1+WM93hjTNNrepdnmSr/Ok22y1zdRrzde572W81zNc6/kOVd4rK7DBFP5OtQ1OH7nmehr8EqO1zWYbCpfg6DrcDzPo5+FU9dUvg5TsbaJeM3ZcA1eyfG6BpMZY74z2uPTeatLvKLDM8Lj8Y/7Jn4pw/ruBB8vUVP96zbZ65uo1xuv817Lea7muVfynKn+39JUNpW/droGx+88E30NXu1ryNT/uuk6HL/z6Gfh1DWVv3apWNtEvOZsuAav9jXkMl+36TzV5f8DvgX8k7X2t4d5/AWizU23WmuHblWZtpTsiaSerkOR1NI1KJJ6ug5FUkvX4JWZzhUfL8fu7zLGJH0esXG2G4E+4PXJXtgEe+Lyh4jIBNN1KJJaugZFUk/XoUhq6Rq8AtM2+LDWNgI/AuYDnxjy8BeAXOBfrbW9k7y0CRXrJSIiKaTrUCS1dA2KpJ6uQ5HU0jV4ZabUVhdjzL3AvbF/VgB3A6eAn8Q+1matfSzh+FpgL1AGPAMcAW4CthAdc7vBWts+GWsXERERERERkalnqgUfnwc+N8ohZ62184c8pwb4ItAAFAPnge8DX7DWdk7MSkVERERERERkOphSW12stZ+31ppRbvOHec771tpHrbWV1tpMa+08a+2nZnPoYYy51RjzA2NMszHGGmM+muo1icw2xpg/Mca8aYzpNsa0GmN+aIxZnup1icwmxphPGGMOxq7DbmPMa8aY7alel8hsFPu5aI0xX0/1WkRmE2PM52PXXuLtQqrXNdmmVPAh4yYPeAf4A6A/xWsRma02A/8AbABuB0LAj40x3lQuSmSWaQL+GLgRWAP8N/BfxpgVKV2VyCxjjLkZ+BhwMNVrEZmljgGVCbfrU7ucyZee6gXI+LPWPgc8B2CMeTq1qxGZnay1dyf+2xjzMNBFdOLUD1OyKJFZxlr7zJAP/akx5neA9egNmMikMMZ4gG8Dv8HoW9pFZOKErLWzrsojkSo+UsAY8yvGmK8ZY34SK721xph/u8xzqo0x/2KMOWeMCRhjzhhjvmqMKZqsdYvMJCm4DvOJfs+dtdvwRIaazOvQGOMyxnyEaFXk3vH8PESmq0m6Bv8J+E9r7cvj/xmITH+TdB0ujB172hjz78aYhRPwqUxpqvhIjT8DVgJ+omW4S0Y7eJjpNUeBdUS3sjQYYzZqeo3IFZvs6/ApYD/w2jWvXGTmmPDr0BhzPdHrLjv2Oh+y1h4a589DZLqa0GvQGPNbwCLgoQlZvcjMMNE/C98APho7riz2enuNMctm03tIVXykxqeBOqAA+J0xHP8PRP8j/X1r7b3W2s9aa28HngTqgb+asJWKzFyTdh0aY54ANgG/bK0NX/PKRWaOybgOjwGriI67/0fgf6nRsIhjwq5BY0w98GXgAWvt4LivXGTmmNCfhdba562137HWHrTW/hjYQTQHeGQ8P4mpbkqNs52NjDGbgZeBb1trL0nDY4neSeAMUGutjSQ8lk90fK8Byqy1vcM83w980lr79AQsX2RGmMjr0BjzJPARYIu19ugEfQoi095E/zxMOPbHwFlr7W+O5/pFprvxvgZNdKrg/wQSA38XYIEIkGutDUzE5yIyXU3iz8KXgaPW2rEELTOCKj6mvi2x+x8l/ocNYK3tAfYAbuDmyV6YyCxyVdehMeYp4NeA2xV6iFyz8fp5mAZkjf/yRGa8K70G/4vo5IhVCbe3gH+P/e/gxC5XZEa65p+Fxphsottpzk/UIqciBR9TX33s/vgIj5+I3dfFP2CMyTPGrDLGrCL6//Hc2L/nTtwyRWa0q7kOvwE8CjwAdBpjKmK3vIlbpsiMdjXX4V8bY24xxsw3xlxvjHmc6Kjpb0/cMkVmrCu6Bq21PmvtO4k3oBfoiP1bZeciV+5qfhZ+xRhzmzFmgTHmJuA/gVzgf03cMqceBR9Tnyd23zXC4/GPFyZ8bA3w89gtB/hC7H9/cQLWJzIbXM11+LtEJ7m8RDRRj98em4D1icwGV3MdVgD/RrTPx0vAWmCbtfb5iVigyAx3NdegiIyvq7kOq4H/S/Rn4feAAHCztfbsRCxwqtJUlxnIWrub6N4uEUkRa62uQZEUs9Z+NNVrEJFfsNZuTvUaRGYba+1HUr2GqUAVH1NfPLXzjPB4/OO+iV+KyKyl61Ak9XQdiqSWrkGR1NN1eJUUfEx9x2L3dSM8vjh2P9I+LxG5droORVJP16FIaukaFEk9XYdXScHH1Pdy7P4uY0zS/1+xkUUbgT7g9clemMgsoutQJPV0HYqklq5BkdTTdXiVFHxMcdbaRuBHwHzgE0Me/gLRjrz/OtqcZhG5NroORVJP16FIaukaFEk9XYdXz2iS1OQzxtwL3Bv7ZwVwN3AK+EnsY23W2scSjq8F9gJlwDPAEeAmonOcjwMbrLXtk7F2kZlC16FI6uk6FEktXYMiqafrcHIo+EgBY8zngc+NcshZa+38Ic+pITqOtgEoJjoW8/vAF6y1nROzUpGZS9ehSOrpOhRJLV2DIqmn63ByKPgQERERERERkRlLPT5EREREREREZMZS8CEiIiIiIiIiM5aCDxERERERERGZsRR8iIiIiIiIiMiMpeBDRERERERERGYsBR8iIiIiIiIiMmMp+BARERERERGRGUvBh4iIiIiIiIjMWAo+RERERERERGTGUvAhIiIiM4Yxxhpjdk/C62yJvdb9E/1aV8IYszq2rv8v1WsRERGZKhR8iIiIyFUzxriMMb9ljHnFGNNhjBk0xlw0xhw0xvyzMeaDqV7jeDPGpAFPAgeA7w55bHcseNg8zPNyjTHPxR5/wRiTN95rs9a+DfwX8JcTcX4REZHpKD3VCxAREZHpyRjjAp4FGgAfsBNoAjKBZcADwBLgByla4kT5CLASeNBaa8fyBGNMCdGvzzrg28Cj1trBCVrf48AbwO8DX56g1xAREZk2FHyIiIjI1fo1oqHHAeA2a21X4oPGGDdwUyoWNsE+AXQD3x/LwcaYecALQD3wBPDYWAOTq2Gt3WeMOQr8tjHmr621kYl6LRERkelAW11ERETkam2I3T89NPQAsNb2WWtfHu6JxphfNca8FNseM2CMOWOM+b/GmDUJx3iMMX9kjPlvY0yTMSZojGk1xvzAGLP+ShZqjEk3xvyuMeZ1Y0y3MabPGPNzY8wnY1tXxnqeJbHP+wfW2v4xHH89sBeoA/7IWvuHQ0OPhO0xGcaYvzDGNMa+JseMMb+VcNzHjTGHjDH9sa/HF0ZZ+78Dc4E7x/q5iYiIzFSq+BAREZGr1R67rxvrE4wxBvifwCNAG/A9oBWoBrYAx4C3YocvBf4KeJXoNpFOom/mPwhsM8Z8wFq7awyvmQH8ELg7dv7/AwzEXu9rRKtSHh7jp7A1dv/TMbzurUS3+biBR6y1/3qZp/x7bC3PAYPArwD/ZIwZBFYQ/Zo9C7xE9GvwF0Af8DfDnGtP7P5OotUmIiIis5aCDxEREbla3wP+GPi4MSaf6NaPt621Z0d5zm8RfQP/JnBnYqVIrGdIWcKxR4Aqa21b4gmMMdXAPqINRi8bfAB/SjT0+DrwKWttOOH1/gn4DWPMf1prnxnDuTbF7t8a9Si4F/htIAx8cCwBDdFQZ7m11hdb398BR4l+nj5ghbW2OfbY54GTwGPGmL+z1oaGnOvN2P2tY3hdERGRGU1bXUREROSqWGt/DjwEtMTu/x9wxhjTboz5vjHmA8M87fdi9789dHuMtTZsrT2f8O+uoaFH7ONNwH8CS4wxc0dbY2wryO8BF4BPx0OP+OsBfwhY4MHLfsJR8dc7P+pR8AdANvDxMYYeAJ+Nhx6x9Z0iWllSCPxlPPSIPeYjWsVSAswZeqLY13YgYb0iIiKzlio+RERE5KpZa79jjPk+0W0jm4AbYvf3AvcaY/438FFrrTXG5ALLgZZYaHJZxpiNREOE9USrQTKHHDIHeG+UU9QBXuAE8GfRnTaX6Ce6rWYsimP3nZc57gWiVSZPGGMOWmsPjuHcw1WRnIvdvz3MY/EgpBoYrsqmAygfw+uKiIjMaAo+RERE5JrExrL+KHaLbyH5ZeBfgF8nugXmv4hWLsAv3rCPyhjzIaKVHQPAi0Aj0AtEgM3AbUDWZU4TDyoWA58b5bi8sayJaEgC0WqO0Zqb/jWwm+ho2ZeNMXdba0fdHjNcg1ggvoVltMcyRjhlzmXWKCIiMiso+BAREZFxFdtC8p3YRJM/A24nGnz4YodcsjVjBH8JBIE11tojiQ8YY75JNPi4nHhg8H1r7YfH+LqjuRi7L+YyVR/W2r82xvQDXwVeMsZss9buHYc1XFZsi08hcHoyXk9ERGQqU48PERERmSg9sXsDYK3tBd4Byo0xN4zh+YuAd4cJPdL4RZPRyzlKNHC5OTbd5VrFt6wsGcvB1tqniDY5zQd+ZIzZMg5rGIt6ol/3/ZP0eiIiIlOWgg8RERG5KsaYXzPG3BkLIoY+VkF0ggtEx9HG/X3s/pvGGM+Q56QZYyoTPnQGWGyMqUo4xgCfB64byxpj006+BlQCf2+MyRlmrZXGmDGdj+j2FYCbx3g81tp/IjrJJhvYaYxpGOtzr0F8fS9PwmuJiIhMadrqIiIiIlfrJqKNRy8YY37KL7ZVLAC2E+0x8QzRPh1x/wzcAjwMnDDGPAO0AlVEt8T8C9FgA6JjXP8H8HNjzP8DBoGNREOPHwLDTY0Zzl8CK4GPAx8wxvw30T4jZUR7f2wkOvL23TGc67+JVpDcTXQbz5hYa//VGDMAfBt4xhhz/xjH516tu4iO0p3I1xAREZkWFHyIiIjI1fo7otNStgIriIYB2UA70cqI/wP8H2utjT8h9r9/3RjzAvAx4H6iDUrPAz8BfpBw7DeNMQHgU0QrJvpjxzxKtHnqmIIPa+2gMeZeoiN3PwrsINrMtJVoWPPnRAOJsZyrzxjzNPApY8zSodtwLvPc78bCj+8C/2mMecha+x9jff5YxSpp7gWetda+P97nFxERmW5Mwu8iIiIiInIZxpgFRHuH/A9r7R+kej1DGWN+j+iWolustT9N9XpERERSTcGHiIiIyBUyxvwt8HvAImvtmMbzToZYD5NGYK+19ldSvR4REZGpQFtdRERERK7cl4BeYD7RfiFTxXzgn4CnU7sMERGRqUMVHyIiIiIiIiIyY2mcrYiIiIiIiIjMWAo+RERERERERGTGUvAhIiIiIiIiIjOWgg8RERERERERmbEUfIiIiIiIiIjIjKXgQ0RERERERERmLAUfIiIiIiIiIjJj/f8wYBz0xLCDSAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1280x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting Figure 9\n",
    "\n",
    "path = './'\n",
    "names = [\n",
    "\n",
    "    ['SF.mex.Yg.12.10.2021', 'Oct 12$^{th}$', 'k', '-'],\n",
    "    ['SF.mex.Hb.15.10.2021', 'Oct 15$^{th}$','k', '-'],\n",
    "    ['SF.mex.Yg.16.10.2021', 'Oct 16$^{th}$','k', '--'],\n",
    "    ['SF.mex.Yg.18.10.2021', 'Oct 18$^{th}$', 'k', '-'], \n",
    "\n",
    "        ]\n",
    "\n",
    "v = 400 # velocity scaling factor (km/s)\n",
    "trunc = 8000 # truncation scale (samples)\n",
    "\n",
    "plt.figure(figsize=(16, 8), dpi=80)\n",
    "\n",
    "for name in names:\n",
    "    \n",
    "    ls = name[3]\n",
    "    color = name[2]\n",
    "    label = name[1]\n",
    "    name = name[0]\n",
    "\n",
    "    df = pd.read_csv(path + name, delimiter = ' ', index_col=None, usecols=None).values # import data\n",
    "    df = pd.DataFrame(df) # convert to a dataframe\n",
    "\n",
    "    plt.loglog(df[0][1:trunc]*v,df[1][1:trunc], color=color, label = name, ls=ls) # plot on loglog plot\n",
    "    plt.fill_between(df[0][1:trunc]*v, df[1][1:trunc]-df[2][1:trunc], df[1][1:trunc]+df[2][1:trunc], alpha = 0.4, color='grey') # add uncertainty fill\n",
    "    \n",
    "    plt.annotate(label, (df[0][8000]*v +3000,df[1][8000] -10), fontsize=15) # add epoch annotations\n",
    "\n",
    "# add plot axes\n",
    "plt.xlabel('Scale (Km)', fontsize=18)\n",
    "plt.ylabel('D(s)', fontsize=18)\n",
    "plt.xticks(fontsize=18)\n",
    "plt.yticks(fontsize=18)\n",
    "\n",
    "# set figure limit sizes for manuscript\n",
    "plt.xlim([8,2*10**5])\n",
    "plt.ylim([10**-2,10**6])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ed2d98d7-20ad-4a87-aa5b-3db8792ccc53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd9f80335b0>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sample code to calculate a structure function from the Phase file output of SDtracker\n",
    "\n",
    "# Declarations and Definitions\n",
    "\n",
    "# Import Modules\n",
    "import pandas as pd # data analysis\n",
    "import numpy as np # data handling\n",
    "import math # mathematical tools\n",
    "import csv # handling csv files\n",
    "import matplotlib.pyplot as plt # plotting\n",
    "from pysctrack import handler\n",
    "import re # to search filenames for date and station\n",
    "import statistics as st # for statistical analysis\n",
    "import os\n",
    "import scipy.signal as sps\n",
    "import scipy.stats as spstat\n",
    "from scipy.ndimage import shift\n",
    "\n",
    "import matplotlib\n",
    "\n",
    "# search file name for date and station, this is used when plotting to denote days and stations\n",
    "#############################################################################\n",
    "def PhaseSearch(filename):\n",
    "    m = re.search('Phases.(.+?).txt', filename)\n",
    "\n",
    "    regex = '[a-zA-Z0-9]\\w+' # set the regex search terms\n",
    "    match = re.findall(regex, m.group(1)) # search the filename\n",
    "    craft_date = re.match(r\"([a-z]+)([0-9]+)\", match[0], re.I)\n",
    "    \n",
    "    # splitting the craft name from the year\n",
    "    if craft_date:\n",
    "        items = craft_date.groups()\n",
    "        match[0]= items[0]\n",
    "        match.insert(1, items[1])\n",
    "        \n",
    "    if m:\n",
    "        found = m.group(1)\n",
    "    else: \n",
    "        found = \" \"    \n",
    "    return(match)\n",
    "\n",
    "#############################################################################\n",
    "\n",
    "# search file name for date and station, this is used when plotting to denote days and stations\n",
    "#############################################################################\n",
    "def FdetsSearch(filename):\n",
    "    m = re.search('Fdets.(.+?).r2i.txt', filename)\n",
    "    \n",
    "    regex = '[a-zA-Z0-9]\\w+' # set the regex search terms\n",
    "    match = re.findall(regex, m.group(1)) # search the filename\n",
    "    craft_date = re.match(r\"([a-z]+)([0-9]+)\", match[0], re.I)\n",
    "    \n",
    "    # splitting the craft name from the year\n",
    "    if craft_date:\n",
    "        items = craft_date.groups()\n",
    "        match[0]= items[0]\n",
    "        match.insert(1, items[1])\n",
    "\n",
    "    if m:\n",
    "        found = m.group(1)\n",
    "    else: \n",
    "        found = \" \"\n",
    "    return(match)\n",
    "\n",
    "#############################################################################\n",
    "\n",
    "# convert the scan seconds to hours, minutes and seconds\n",
    "#############################################################################\n",
    "def sec2hmi(seconds):\n",
    "    hours: int = int(np.floor(seconds / 3600))\n",
    "    minutes: int = int(np.floor((seconds - 3600 * hours) / 60))\n",
    "    secs: int = seconds - hours * 3600 - minutes * 60\n",
    "\n",
    "    return hours, minutes, secs\n",
    "#############################################################################\n",
    "\n",
    "# convert scan times in HH:MM:SS to seconds \n",
    "#############################################################################\n",
    "def get_sec(time_str):\n",
    "    \"\"\"Get seconds from time.\"\"\"\n",
    "    h, m, s = time_str.split(':')\n",
    "    return int(h) * 3600 + int(m) * 60 + float(s)\n",
    "#############################################################################\n",
    "\n",
    "def convert_times(date_times):\n",
    "    \n",
    "    seconds = []\n",
    "    \n",
    "    for i in date_times:\n",
    "        seconds.append(get_sec(i[11:]))\n",
    "    return seconds\n",
    "path: str = './structure_function_data/'\n",
    "\n",
    "phase = [\n",
    "\n",
    "    'Phases.mex2021.10.10.Yg.txt',\n",
    "    \n",
    "        ] # check phase and fdets are same length\n",
    "\n",
    "fdets = [ \n",
    "    \n",
    "    'Fdets.mex2021.10.10.Yg.r2i.txt',\n",
    "    \n",
    "        ] # check phase and fdets are same length\n",
    "\n",
    "FileNum = len(phase) # Number of compiled files (should be same for phase and fdets)\n",
    "\n",
    "# global data structures\n",
    "FDETS = [] # is a list of pandas dataframes\n",
    "PHASE = [] # is a list of pandas dataframes\n",
    "\n",
    "i = 0 # set iterator\n",
    "\n",
    "while i < FileNum:\n",
    "# iterate through the list of file names and append them into their respective list of dataframes\n",
    "    FDETS.append(pd.read_csv(path + fdets[i], skiprows=4, delim_whitespace=True, names=['Scan', 'Time', 'SNR', 'Spectral_Maximum', 'Frequency', 'Doppler_Noise'])) # import data into FDETS\n",
    "    ########################################################################################\n",
    "    column_check = pd.read_csv(path + phase[i], skiprows=4, delim_whitespace=True)#delimiter=' ') # imports csv to count number of columns\n",
    "    cols = len(column_check.axes[1]) # counts number of columns in the csv\n",
    "    names = ['Time'] # set the list of column names to add to\n",
    "    n = 1 # again set iterator\n",
    "    while n < cols:\n",
    "        names.append(\"Phase\" + str(n))\n",
    "        n += 1 # increase iterator\n",
    "    ########################################################################################    \n",
    "    PHASE.append(pd.read_csv(path + phase[i], skiprows=4, delim_whitespace=True, header=None, names=names)) # import data into PHASE\n",
    "    #general import command is: DATA = pd.read_csv(path + phase, skiprows=4, delimiter=' ', names=['Time', 'Phase1', 'Phase2', 'Phase3', 'Phase4'])...\n",
    "    \n",
    "    i += 1 # increase iterator\n",
    "\n",
    "for ex in FDETS:\n",
    "    \n",
    "    ex['Time_sec'] = convert_times(ex.Time)\n",
    "\n",
    "# check the Phase residual resolution - related to the Bandwidth 20 Hz or 100 Hz\n",
    "# resample to match lower resolution\n",
    "\n",
    "if len(PHASE[0].Time) == 214000:\n",
    "    samples = 5\n",
    "else: samples =1\n",
    "\n",
    "# create lists to store the values\n",
    "structure_functions = []\n",
    "structure_functions.append(PHASE[0].Time[::samples].values-15)\n",
    "data = []\n",
    "\n",
    "\n",
    "for (columnName,columnData) in PHASE[0].items():\n",
    "\n",
    "    if columnName != 'Time':\n",
    "        data.append(PHASE[0][columnName].to_numpy()[::samples])\n",
    "\n",
    "    else: continue\n",
    "\n",
    "# conduct the structure calculation\n",
    "for index in range(len(data)):\n",
    "    \n",
    "    struct = []\n",
    "    s = 0\n",
    "    while s < len(data[index]):\n",
    "        \n",
    "        \n",
    "        delta_phi_squared = np.square(np.array(data[index][s:]) - np.array(data[index][0:len(data[index])-s]))\n",
    "        struct.append(np.mean(delta_phi_squared))\n",
    "        \n",
    "        s = s + 1 #increase offset to next sample\n",
    "        \n",
    "    structure_functions.append(struct)\n",
    "\n",
    "plt.loglog(structure_functions[0][1:],structure_functions[1][1:])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bfd064bc-596f-424c-b875-e71a1e2f7870",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "small scale gradient is 1.1290190066307753\n",
      "fitting boundary scales are 10.000000000000119 and 100.0\n",
      "sum of the squares of the fit errors is [0.00047901]\n",
      "##############################\n",
      "The fitting boundary scales are 100.0 and 1200.0\n",
      "The large scale gradient is 1.127307611559252\n",
      "The sum of the squares of the fit errors is [0.00330353]\n",
      "##############################\n",
      "The fitting boundary scales are 1200.0 and 16000.0\n",
      "The large scale gradient is 0.9052026202037183\n",
      "The sum of the squares of the fit errors is [0.35723343]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "##############################\n"
     ]
    }
   ],
   "source": [
    "# Sample code for determining the structure function gradients\n",
    "\n",
    "path = './'\n",
    "names = [\n",
    "    \n",
    "    'SF.mex.Yg.10.10.2021',\n",
    "    \n",
    "        ]\n",
    "\n",
    "plt.figure(figsize=(15, 8), dpi=80)\n",
    "\n",
    "# import data\n",
    "for name in names:\n",
    "    \n",
    "    df = pd.read_csv(path + name, delimiter = ' ', index_col=None, usecols=None).values#, index=None)\n",
    "    df = pd.DataFrame(df)\n",
    "\n",
    "lin_fit = np.polyfit(np.log10(df[0][1:]),np.log10(df[1][1:]),1)\n",
    "\n",
    "fit_x = np.linspace(0.001,1000,1000)\n",
    "fit_y = lin_fit[0]*np.log10(fit_x) + lin_fit[1]\n",
    "\n",
    "fitline = 10 ** fit_y\n",
    "\n",
    "plt.loglog(df[0][1:]*v,df[1][1:], '.')\n",
    "##################################################################################################\n",
    "# SMALL SCALE\n",
    "\n",
    "# set sample scale range\n",
    "low = 1\n",
    "high = 10\n",
    "\n",
    "model = np.polyfit(np.log10(df[0][low:high]*v),np.log10(df[1][low:high]),1, full=True)\n",
    "\n",
    "print(f\"small scale gradient is {model[0][0]}\")\n",
    "print(f\"fitting boundary scales are {df[0][low]*v} and {df[0][high]*v}\")\n",
    "print(f\"sum of the squares of the fit errors is {model[1]}\")\n",
    "\n",
    "x = np.linspace(df[0][low]*v,df[0][high]*v,100)\n",
    "p = np.poly1d(model[0])\n",
    "y=p(np.log10(x))\n",
    "\n",
    "plt.loglog(x,10**y, '-')\n",
    "print(30*'#')\n",
    "\n",
    "####################################################################################################\n",
    "# MEDIUM SCALE\n",
    "\n",
    "# set sample scale range\n",
    "low = 10\n",
    "high = 120\n",
    "\n",
    "model = np.polyfit(np.log10(df[0][low:high]*v),np.log10(df[1][low:high]),1, full=True)\n",
    "\n",
    "print(f\"The fitting boundary scales are {df[0][low]*v} and {df[0][high]*v}\")\n",
    "print(f\"The large scale gradient is {model[0][0]}\")\n",
    "print(f\"The sum of the squares of the fit errors is {model[1]}\")\n",
    "\n",
    "x = np.linspace(df[0][low]*v,df[0][high]*v,100)\n",
    "p = np.poly1d(model[0])\n",
    "y=p(np.log10(x))\n",
    "\n",
    "plt.loglog(x,10**y, '-')\n",
    "print(30*'#')\n",
    "####################################################################################################\n",
    "# LARGE SCALE\n",
    "\n",
    "# set sample scale range\n",
    "low = 120\n",
    "high = 1600\n",
    "\n",
    "model = np.polyfit(np.log10(df[0][low:high]*v),np.log10(df[1][low:high]),1, full=True)\n",
    "\n",
    "print(f\"The fitting boundary scales are {df[0][low]*v} and {df[0][high]*v}\")\n",
    "print(f\"The large scale gradient is {model[0][0]}\")\n",
    "print(f\"The sum of the squares of the fit errors is {model[1]}\")\n",
    "\n",
    "x = np.linspace(df[0][low]*v,df[0][high]*v,100)\n",
    "p = np.poly1d(model[0])\n",
    "y=p(np.log10(x))\n",
    "\n",
    "plt.loglog(x,10**y, 'r-')\n",
    "plt.show()\n",
    "print(30*'#')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b1e1b15-1505-47ed-86fb-6ec70348fb8f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53299433",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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