{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cf948b94",
   "metadata": {},
   "source": [
    "### Make figure S15 - effect of Lagrangian reference frame of GNSS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "034446ee",
   "metadata": {},
   "source": [
    "# Load necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7d8baa9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib \n",
    "import numpy as np\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "from scipy import stats\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9df15ab1",
   "metadata": {},
   "outputs": [],
   "source": [
    "figure_folder = '/home/ram21/notebooks/brunt-is2-rifts/figures/'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe579fb8",
   "metadata": {},
   "source": [
    "### Figure S15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c1010e0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MzCQnJ4fjx4+TmJhIRkYGa9euZeXKlSVXO8vq06cPaWlpAKSmpnLFFVfgnCMtLa3kmY3ly5eTk5PD8OHDATh16lTJ1YuFCxeWtEfftWsX27ZtIy0tjfvuu4+f/exndOvWjbFjx1ba7ltvvRU0zwoKCpgyZQoLFiygdevWAHzwwQd069aNgwcPMmHCBAYOHMjx48fp1KkTmZmZZGdnB11nVcuPGTOmxvkRaL/bt29f5Xbbt2/PokWLgqbtfNRn+QpWFsoKd7maNGkSo0ePrrTdUOUqkLNnz7JkyRIefvjhknHVKS/+K3mhyl9DLFcSu5577jlmz55d8n39+vVMmjSJtm3bhmV7sRYDv/nmG4YOHQqE71ylGNjwxVps7tmzZ6ONza+88gr/9m//Vm6/o6W8N9pmnLfccgsff/wxeXl5nDt3jgMHDjBr1izAe+iztoWuulJTU1m3bl3J96eeeorly5dz6NChcvPdfffdPPvss5w4caLc+Li4OMaOHcu8efP43e9+x9/+9reg48tq2rQpffr04bnnnuPyyy9n9OjRZGVl8eWXX5KcnFxpfn/TAIAmTZqUfG/SpAmFhYWAd4d4xowZrF+/nvXr17N161YefPBBsrOzWbZsGatWreIf//gHQ4cO5fTp0/Tv359169aRlpbGs88+y7//+7/XKP/OnTvHlClTmD59OjfeeGPJ+G7dugHQqVMnJk+ezJo1a/jwww9ZsmQJvXv35uabb2bFihXceuutVa63quVrkx+B9ru+RLJ8BSoLFYW7XP385z+vcbkK5u233yYjI4POnTuXjKtOealu+WsI5Uoah+LiYv6//+//K/n+wgsvcPz4cX7zm99UOofUVqzHwBdeeCGs5yrFwIYp1mPz+vXrG21szsnJidry3mgre126dOHJJ59k6NChtGjRgs6dO/Of//mfJdO3bt0a1u2PHz+e06dP8/vf/75k3MmTJyvN165dO2666aZyvfZs3bqVbdu2lXxfv349vXr1Cji+KqNHj+bRRx9lzJgxjB49mkWLFjF06FCcc7XanyuuuIKXX36ZgwcPAt5VzZ07d3Ls2DHatm1LixYt2LJlC6tXrwZg7969tGjRgltvvZWbb7653MkvFDNj9uzZJCcnc++995aMP3HiBPn5+SWf33nnHQYNGsTDDz/M7t272bFjBy+99BLjx4/nxRdfrLTeQMvXRqD9ri+RLF+BykJtnE+5+slPflKjchXKX//6V6ZNm1byvbrlpbrlrzoiXa6kcdi6dSt79+4FYOjQoXz3u9+lVatW3HPPPfTo0aNOthHrMfD48eNhO1cpBjZcsR6bCwoKGm1sbtWqVdSW90ZZ2Tt27BijRo3ixRdfZNeuXZw7d67SPKdOnQprGpxzvPbaa7z33nv06dOHESNGMGPGDH79619Xmve+++4jLy+v5HtBQQEzZswgJSWFwYMHs2nTJh588MGA46syevRo9u3bx2WXXUbnzp1p1qxZlbfVqyslJYVf/vKXXHnllQwePJgJEyawb98+Jk6cSGFhIcnJydx///1ceumlgNdDkf/B3ueff56f//znAFx99dUlPzLKfi7rww8/5E9/+hMrVqwo6XL3rbfe4sCBA4waNYohQ4YwYsQIrrnmGiZOnBgy7f7t1Hb5qgTa7/oSyfIVqCzUxvmUq3nz5pWUq/vvvz9kuQKYNm0al112GVu3bqV79+4lgfbEiRO8++675a6ghyovwbZTW5EuV9I4HD58uORz9+7dy03zXzE/X7EeA3/84x/X6lylGBjbYj02jxgxos7LOzSM2FxUVBS95T3Qw3wNYajtw+evvvpqyQPmV1xxhe3bt8/MzBYuXFgy3v9AbG1Ea+cG0Ur5VTPKr5pTntVMtOYX6qClXmLk5s2bS2Lh0KFDy03r0aNHnXTQEusa8/435n03a9z7r32PnGDxsVHe2YuPL+2XplmzZiQlJfH555/z5JNPRjBVIiIikde/f/+Srts//fRT/vSnP5Gfn8/jjz/Orl27Ipw6ERGpiUZZ2Rs5ciQdO3YE4M0336R169a1bpcuIiISS5o0acJDDz1U8v22226jdevW/PjHPw5bb5wiIhIejbKy17ZtW95++21GjRpFixYt6Nq1Kw8++CD3339/pJMmIiIScTNnzuTZZ5/loosuIiEhgbS0NF555RUGDx4c6aSJiEgNNNr37GVmZrJy5cpK47/3ve9FIDUiIiLR5Xvf+16lmHj99ddHKDUiIlIbjfLOnoiIiIiISKwLW2XPOdfMObfGOfcP59znzrl5vvHPOedynXPrfUO6b7xzzi10zn3pnNvgnMsIV9pERERERERiXTibcZ4BxptZgXOuKfCBc+5t37SfmNnLFea/CujnGy4Bfu/7KyIiIiIiIjUUtjt7vtc+FPi+NvUNFmSR64EXfMutBto457qEK30iIiIiIiKxzHnv4QvTyp2LA3KAi4GnzOxnzrnngMvw7vwtB+43szPOuaXAI2b2gW/Z5cDPzGxthXXOAeYAdO7cOfOll14KW/prq6CggJYtW0Y6GQ2G8suzd+9eXnzxRU6cOMG8efMCzqf8qjnlWWXBylu05te4ceNyzGxYpNMRzaIlRkZrGaovjXn/a7vv1Y2B0U7HXvt+Pmr7fxA0PgZ623pdDkAbIAsYBHQBHJAIPA/8wjfPUmBUmWWWA8OCrTczM7NuXjtfx7Kysqo13/79+23atGnWp08fy8jIsEsvvdReeeUVMzMD7N577y2Zd/78+TZ37tyS77/85S8tJSXF0tLSbMiQIbZ69eqg46PF3Llzbf78+eXGVcyvpKSkkOv5+uuvbezYsZacnGwpKSm2YMGCkmm9evWyQYMG2ZAhQ6xiGSksLLT09HS75pprAq472PL1YcqUKUGnq3xVVlW5KisrK+u8ytWpU6ds+PDhNnjwYEtJSbFf/OIXQcdXZ51+0VjeqlvG6huw1uohZsXKEMkYWZ0yFMvnqED7H+pcZdbwY+D5nj9CxcBoF2r/G1O5D3d5D/Z/MGvWLOvYsaOlpqYGXfdvf/tbS0lJsdTUVLv55pvt1KlTtmXLFhsyZEjJ0KpVK3v88ceDrqeu42ZN/w+Cxcd6efWCmR11zmUBE83sUd/oM865/wR+7Pu+B+hRZrHuvnExycy44YYbmDFjBn/5y18A2LlzJ0uWLAEgMTGRV155hQceeIAOHTqUW3bVqlUsXbqUdevWkZiYSF5eHmfPng04PhbFx8fz2GOPkZGRQX5+PpmZmUyYMIGUlBQAsrKyKuUbwBNPPEFycjLHjx8Puv5Ay9eFzz77jAceeKDcuD/+8Y906tSpzrah8lU7gcpVcnIyK1asoGXLlpw7d45Ro0Zx1VVXcckll1Q5/tJLLw25Tn9ZhYZf3kRqSueo86MY2DCp3NdOoPLetm3bgP8HM2fO5Ic//CG33XZbwPXu2bOHhQsXsmnTJpo3b85NN93ESy+9xMyZM1m/fj0ARUVFdOvWjcmTJ9f5ftXX/0I4e+Ps6Jxr4/vcHJgAbPE/h+ecc8ANwEbfIkuA23y9cl4KHDOzfeFKX6StWLGChIQEfvCDH5SM69WrFz/60Y8Ar2DPmTOHxx9/vNKy+/bto0OHDiQmJgLQoUMHunbtGnB8RfPnz2fhwoUA3HPPPYwfP74kTdOnTy83744dOxg4cCAzZ86kf//+TJ8+nWXLljFy5Ej69evHmjVrSub97W9/y6BBgxg0aBALFiwoGf/QQw/Rv39/Ro0axdatW0vGv/jii4wYMYLbb7+dO+64g6KiomrnX5cuXcjI8DpsbdWqFcnJyezZE/zawO7du3nzzTe5/fbbq72dqtQkT2644QYyMzNJTU1l8eLFAKSlpbF06dJyQ13/Y0eyfEHpsU1PT6/y2NZHuQq07WAClSvnXEnzjHPnznHu3DmccwHHV2ed1dUQyptITcV6DHz55dI+6OrzXBVMfcXAzZs3l8yrc1J5is11W96D/R+MGTOGdu3ahVx3YWEhp06dorCwkJMnT1bKu+XLl3PRRRfRq1evSsuWza/vfve7AfOrqv8DqMf/hUC3/M53AAYDnwIb8Cp0/uaaK4DPfONeBFr6xjvgKeAr3/SgTTitgTfjfOKJJ+zuu+8OOD0pKcmOHTtmvXr1sqNHj5a7lZ+fn29Dhgyxfv362Z133mnZ2dlBx1e0atUqmzp1qpmZjRo1yoYPH25nz561Bx980BYtWlRu3tzcXIuLi7MNGzZYUVGRZWRk2KxZs6y4uNhee+01u/76683MbO3atTZo0CArKCiw/Px8S0lJsXXr1pWMP3HihB07dswuuugimz9/vm3atMkmTZpkZ8+etaysLLvzzjvt+eefL9l3v6uuusr27NkTNC9zc3OtR48eduzYMTMz6927tw0dOtQyMjLs6aefLplvypQptnbtWsvKygrahCXQ8jXNEzOzw4cPm5nZyZMnLTU11fLy8gJuNy8vz+644w7r27ev/epXvwo4X7SXr7LH1szKHVu/+ihXZbddsRlnbcpVYWGhDRkyxJKSkuynP/1pyXyBxldnnWbRWd7UjDM2hmhuxhnrMbBXr161Olf5992vIcbAkSNHlswbjhgY7YKV/ViPzYsWLar38h5sfG5ubshmnAsWLLCkpCTr0KGD3XLLLZWmz5o1y5588smAafHn1/LlywPmV338HwSLj2FrxmlmG4ChVYwfH2B+A+4KV3qi3V133cUHH3xAQkICn3zyCQCtW7fmtttuY+HChTRv3rxk3pYtW5KTk8PKlSvJysriO9/5Do888ggzZ84MOL6szMxMcnJyOH78OImJiWRkZLB27VpWrlxZcrWzrD59+pCWlgZAamoqV1xxBc450tLS2LFjBwAffPABkydPJikpCYAbb7yRlStXUlxczOTJk2nRogUA1113HeBdKcnJyWH48OEUFBQQFxdX5dWMt956K2i+FRQUMGXKFBYsWEDr1q1L0tKtWzcOHjzIhAkTGDhwIMePH6dTp05kZmaSnZ0ddJ1VLT9mzJga5wnAwoULefXVVwHYtWsX27Zto3379lVut3379ixatCho2mqrPstX2WMLcOrUqSqPbbjLVdlt9+zZs9y2a1Ou4uLiWL9+PUePHmXy5Mls3LiRQYMGBRxfnXX69zHWyptITcVaDBwzZkytzlUVNcQYuH///pL5dE4KLtZi8xdffFHv5T3Y+FCOHDnC66+/Tm5uLm3atOHb3/42L774IrfeeisAZ8+eZcmSJTz88MMB1+HPr+zs7ID5Fen/g3p5Zk8qS01N5W9/+1vJ96eeeoq8vDyGDSvfkc7dd99NRkYGs2bNKjc+Li6OsWPHMnbsWNLS0nj++eeZOXNmwPFlNW3alD59+vDcc89x+eWXM3jwYLKysvjyyy9JTk6ulFZ/0wCAJk2alHxv0qQJhYWFtdp/M2PGjBk8/PDDZGdnM3bs2Bqv49y5c0yZMoXp06dz4403lozv1q0bAJ06dWLy5MmsWbOGw4cPs2TJEt566y1Onz7N8ePHufXWW3nxxRcrrbeq5SsGuurkSXZ2NsuWLWPVqlW0aNGCsWPHcvr06RrvZ21EsnyVPbbBhLtclRXqx01ZgcqVX5s2bRg3bhx///vfy1XqAo0Ptc5YKG8iNaUYWL3zZDDRGgP9zfN0TqpMsbnuy3uomB3MsmXL6NOnDx07dgS8SutHH31UUtl7++23ycjIoHPnzgHXESq/ouH/IGzP7Elw48eP5/Tp0/z+978vGXfy5MlK87Vr146bbrqJZ599tmTc1q1b2bZtW8n39evX06tXr4DjqzJ69GgeffRRxowZw+jRo1m0aBFDhw6t9LxRdY0ePZrXXnuNkydPcuLECV599VVGjx7NmDFjeO211zh16hT5+fm88cYbAFxxxRW8/PLLHDx4EIBvvvmGnTt3Vnt7Zsbs2bNJTk7m3nvvLRl/4sQJ8vPzSz6/8847DBo0iIcffpjdu3ezY8cOXnrpJcaPH19lkAu0fG0cO3aMtm3b0qJFC7Zs2cLq1atrtZ7aiGT5Ot9jW1a0lKtDhw5x9OhRwLsi+e677zJw4MCA46uzToid8iZSU7EeA1euXKkYqHNSJbEemwcPHlyv5T1YfK2Onj17snr1ak6ePImZsXz58nIXfP76178ybdq0Gq+3rGj4P9CdvQhxzvHaa69xzz338Jvf/IaOHTuSlJTEr3/960rz3nffffzud78r+V5QUMCPfvQjjh49Snx8PBdffDGLFy9m586dVY6vyujRo3nooYe47LLLSEpKolmzZowePbrW+5ORkcHMmTMZMWIEALfffjtDh3qteL/zne8wZMgQOnXqVHILPyUlhV/+8pdceeWV5Ofn06ZNG5566qlKJ6irr76aP/zhD5UemP3www/505/+RFpaGunp6QD86le/YuDAgSU9JhUWFnLLLbcwceLEkOn3b+f06dO1Wr4qEydOZNGiRSQnJzNgwIByPTSGWyTLV9ljW1xcTNOmTas8ttVxPuWq7LYrqmm56t69OzNmzKCoqIji4mJuuukmJk2axIYNG6ocX3Y7999/f5XrvPrqqzlw4EBMlDeRmor1GHjNNdfU6lylGBjbYj02Hzt2rF7Le+vWrQPG12nTppGdnU1eXh7du3dn3rx5zJ49u9x2LrnkEqZOnUpGRgbx8fEMHTqUOXPmAN7FjnfffZenn366xvlTVjT8H4T1perhNmzYMFu7dm3oGetZbZslNlbKr5pRftWc8qxmojW/nHN6qXoNRDJGRmsZqi+Nef8b875D495/7fvYiG0/WHxUM04REREREZEYpMqeiIiIiIhIDFJlT0REREREJAapsiciIiIiIhKDVNkTERERERGJQarsiYiIiIiIxCBV9kRERERERGKQKnsiIiIiIiIxSJU9kQZg+/btzJ49m6lTp0Y6KRIjVKZEpKHQ+Uoai3CUdVX2Iuh73/senTp1YtCgQSXjduzYUe57tLn88ssBWLhwIcnJyUyfPp2jR4/yH//xH/Wajl27djFu3DhSUlJITU3liSeeKDe9d+/epKWlkZ6ezrBhw8pNKyoqYujQoUyaNCnoNirOF2qb4dS3b1+effbZGi2j8lUzwY7v6dOnGTFiBEOGDCE1NZW5c+eWTPv73//OgAEDuPjii3nkkUcqrTfYslu3biU9Pb1kaN26NQsWLAjrfvrVpkyJ1CWdo2qvNjEw2LmorGDzPfHEEwwaNIjU1NR6O1dBbJ2vVO5rJlRZryo/AR5//HFSU1MZNGgQ06ZN4/Tp05XWffToUaZOncrAgQNJTk5m1apV1dpmOIWlrJtZgx0yMzMtGmVlZVVrvvfee89ycnIsNTW1ZFxubm6579GguLjYioqKyo0bMGCA7dq1y8zOP83Vza+y9u7dazk5OWZmdvz4cevXr599/vnnJdN79eplhw4dqnLZxx57zKZNm2bXXHNN0G1UnC/UNuvKhg0b7Jprrik3HDhwwMzMpkyZovJVC9XJs2DHt7i42PLz883M7OzZszZixAhbtWqVFRYWWt++fe2rr76yM2fO2ODBgyuViUDLVlRYWGidO3e2HTt2nM+uVhKsPJl5Zaqi2vxP1gdgrUVB7GkoQyRjZHXKUCyfo8L9P1SbGFjdc1Gg+T777DNLTU21EydO2Llz5+yKK66wbdu2VVr+fPc9VAyMdqH2X+W+ZkKV9aryc/fu3da7d287efKkmZl9+9vftv/8z/+stO7bbrvNnnnmGTMzO3PmjB05cqRa26xKTfe9NrE5mGDxUXf2ImjMmDG0a9cu4PTt27czdOhQPvnkE3bs2MHAgQOZOXMm/fv3Z/r06SxbtoyRI0fSr18/1qxZU2n5ileKHn30UR588MGSdU2fPp3k5GSmTp3KyZMnKy07YMAAbrvtNgYNGsSuXbsAaNmyJT/4wQ/Yvn07V111FY8//jj3338/X331Fenp6fzkJz+po9wJrkuXLmRkZADQqlUrkpOT2bNnT8jldu/ezZtvvsntt99e4/mqu83qHqsbbriBzMxMUlNTWbx4ccnyaWlpLF26tNzQqVOn0JlSgcpXzQQ7vs45WrZsCcC5c+c4d+4czjnWrFnDxRdfTN++fUlISODmm2/m9ddfL7feQMtWtHz5ci666CJ69epVbnxNjk1VZaquypNIXdM5qvZqEwOrey4KNN/mzZu55JJLaNGiBfHx8XzrW9/ilVdeqbT8/v37oyIGRiuV+5oJVdYD5WdhYSGnTp2isLCQkydP0rVr13LTjx07xvvvv8/s2bMBSEhIoE2bNtXaJlSOzb/85S+jNzYHqgU2hKGh39kzq3xlxP99y5Ytlp6ebuvXry8ZHxcXZxs2bLCioiLLyMiwWbNmWXFxsb322mt2/fXXh1z3/Pnzbe7cuZabm2uAffDBB2ZmNmvWLJs/f36lZZ1zla76JSUlmVn5q4ZVXd256qqrbM+ePdXKg/O9EpSbm2s9evSwY8eOlYzr3bu3DR061DIyMuzpp58uGT9lyhRbu3atZWVlBb2zF2q+qrZZdlp1jtXhw4fNzOzkyZOWmppqeXl5AdOTl5dnd9xxh/Xt29duv/32kHlSNi2NvXyZ1byMVXV8CwsLbciQIZaUlGQ//elPzczsf/7nf2z27Nkl87zwwgt21113VVpfVctWNGvWLHvyySerTEt1j01ty9SvfvWrctN0Zy82hmi/s2cWu+eoSy65pEbnqPNRkxhYnXNRoPk2bdpk/fr1s7y8PDtx4oRdeuml9sMf/rDSsn/961/DGgMrnq+iTXXKvsp97QT67VVVWhYsWGBJSUnWoUMHu+WWWyqt69NPP7Xhw4fbjBkzLD093WbPnm0FBQU12mbZY9OvX7+wx+ZggsVH3dmLQocOHeL666/nz3/+M0OGDCkZ36dPH9LS0mjSpAmpqalcccUVOOdIS0tjx44dNdpGjx49GDlyJAC33norH3zwQaV5evXqxaWXXlqrfXjrrbcqXUUJh4KCAqZMmcKCBQto3bp1yfgPPviAdevW8fbbb/PUU0/x/vvvl1w1yczMDLrOUPMF2mZZ1TlWCxcuZMiQIVx66aXs2rWLbdu2BUxT+/btWbRoEV999RXTp08PkSvBqXwFF+j4xsXFsX79enbv3s2aNWvYuHFjtdcZatmzZ8+yZMkSvv3tb1e5fHWPTW3L1AMPPFDtfREJt1g4Rz3yyCNRFwOh+uexquZLTk7mZz/7GVdeeSUTJ04kPT2duLi4KpcPZwyM1fOVyn1w1fnt5XfkyBFef/11cnNz2bt3LydOnODFF18sN09hYSHr1q3jzjvv5NNPPyUpKanSc/ehtln22PTu3TtqY7Mqe1HoggsuoGfPnpX+CRMTE0s+N2nSpOR7kyZNKCwsrLSe+Ph4iouLS76XfTi1YtONqppyJCUl1W4H6sm5c+eYMmUK06dP58Ybbyw3rVu3bgB06tSJyZMns2bNGj788EOWLFlC7969ufnmm1mxYgW33nprpfUGmy/YNssKdayys7NZtmwZq1at4h//+AdDhw6t8uHhcFD5Cqw6x7dNmzaMGzeOv//973Tr1q2kmQt4zX/9ZS/UsmW9/fbbZGRk0Llz5yqXq86xiWSZEqlLOkdVT01jYFmBzkUVVZxv9uzZ5OTk8P7779O2bVv69+9f5XLRHAOjlcp9YNX97eW3bNky+vTpQ8eOHWnatCk33ngjH330Ubl5unfvTvfu3bnkkksAmDp1KuvWravRNhtKbFZlLwolJCTw6quv8sILL/CXv/yl1uvp3LkzBw8e5PDhw5w5c4alS5eWTPv6669Leh36y1/+wqhRo2q9nVatWpGfn1/r5WvDzJg9ezbJycnce++95aadOHGiJD0nTpzgnXfeYdCgQTz88MPs3r2bHTt28NJLLzF+/PhKV3qAgPMF22ZNHTt2jLZt29KiRQu2bNnC6tWrz2t9NaHyVbVgx/fQoUMcPXoUgFOnTvHuu+8ycOBAhg8fzrZt28jNzeXs2bO89NJLXHfdddVatqy//vWvTJs27bzSH8kyJVKXdI4KrTYxsDrnIgh+zjp48CDg5d8rr7zCLbfcUqv063xVmcp91Wrz26tnz56sXr2akydPYmYsX76c5OTkcvNceOGF9OjRg61btwLec/MpKSm13mYg0VDWVdmLoGnTpnHZZZexdetWunfvXq6r1aSkJJYuXcrjjz/OkiVLarX+pk2b8otf/IIRI0YwYcKEcif1AQMG8NRTT5GcnMyRI0e48847a70f7du3Z+TIkQwaNKjkId2rr76avXv31nqdoXz44Yf86U9/YsWKFSXd1r/11lsAHDhwgFGjRjFkyBBGjBjBNddcw8SJE4OurzrpDbbNmpo4cSKFhYUkJydz//3317rJRDAqXzUT7Pju27ePcePGMXjwYIYPH86ECROYNGkS8fHx/O53v+Of//mfSU5O5qabbiI1NbVcGgMt63fixAnefffdal2tDKY+ypRIXYrlc9T9998fdTEw2Lmo7Dk12HxTpkwhJSWFa6+9lqeeeqqkQ4uaasznK5X7mgn126uq/LzkkkuYOnUqGRkZpKWlUVxczJw5c4DyZf3JJ59k+vTpDB48mPXr1/Ov//qv1dpmTURFWQ/0MN/5DkAzYA3wD+BzYJ5vfB/gY+BL4L+ABN/4RN/3L33Te4faRix00BIJ0dbFb7TnV7SJ9vyKtvJlFv15Fm2iNb9QBy0x10FLJNTHOSqa9z/cGvO+m0Xv/qvch1ek9z1YfAznnb0zwHgzGwKkAxOdc5cCvwYeN7OLgSPAbN/8s4EjvvGP++YTERERERGRWghbZc9X0SzwfW3qGwwYD7zsG/88cIPv8/W+7/imX+GqenJUzlvv3r1r1JOgSE2ofIlINNM5ShojlfvGy3l3/sK0cufigBzgYuApYD6w2nf3DudcD+BtMxvknNsITDSz3b5pXwGXmFlehXXOAeYAdO7cOfOll14KW/prq6CgoOSFpBKa8qtmlF81pzyrmWjNr3HjxuWY2bBIpyOaRUuMjNYyVF8a8/435n2Hxr3/2vfI7Xuw+Bgfzg2bWRGQ7pxrA7wKVO72qebrXAwsBhg2bJiNHTv2fFdZ57Kzs4nGdEUr5VfNKL9qTnlWM8qvhitaYmRjL0ONef8b875D495/7fvYSCejSvXSG6eZHQWygMuANs45fyWzO7DH93kP0APAN/0C4HB9pE9ERERERCTWhK2y55zr6Lujh3OuOTAB2IxX6Zvqm20G8Lrv8xLfd3zTV1g425iKiIiIiIjEsHA24+wCPO97bq8J8N9mttQ5twl4yTn3S+BTwP+CkWeBPznnvgS+AW4OY9pERERERERiWtgqe2a2ARhaxfjtwIgqxp8Gvh2u9IiIiIiIiDQm9fLMnoiIiIiIiNQvVfZERERERERikCp7IiIiIiIiMUiVPRERERERkRikyp6IiIiIiEgMUmVPREREREQkBqmyJyIiIiIiEoNU2RMREREREYlBquyJiIiIiIjEIFX2REREREREYpAqeyIiIiIiIjFIlT0REREREZEYpMqeiIiIiIhIDFJlT0REREREJAapsiciIiIiIhKDVNkTERERERGJQarsiYiIiIiIxKD4SCdAREREYsj+/fQ+cQI+/9z77lz5oeI4//e4OGjSxBuq+lxxXHy891lERAJSZU9ERETqzoED9D55EjZtCv+2mjTxKn3VGZo2hYSEyn8TErzKo7/iKSISQ1TZExERkbpz4YXk7t5Nn969wcwbZ1Y6VPzuH4qLvaGoqPLniuP8Q3ExnD3rDefDucqVwGbNIDGx/FB2XLx+QolI9NOZqq7t30/n06dh587QTVf846pqplLxr644iohIQ9C5MzuTkuiTmhre7fgriIWF1RvOnoVz58r/9X8uKqp5pTEurnwlsHnzkqHd2bNw9Kj3PSFBMVxEIiZslT3nXA/gBaAzYMBiM3vCOfcg8H3gkG/WfzWzt3zLPADMBoqAfzGz/w1X+sJm82aS8/NhzZq6XW/Z5xmqappS3WYr/s8KPCIi0pD546K/0nU+iooqVwTPnIHTp72/ZQf/uKIiOHnSGyoYDPDuu96XJk28Sl/ZCmGLFpCUVPpXcVlEwqRalT3n3DBgNNAVOAVsBN41syNBFisE7jOzdc65VkCOc8535uNxM3u0wjZSgJuBVN92ljnn+ptZUY32KMLmvf8+AHMnTqyymcq85cu96ePGlZ9WsalKxb9m3pVJOP/mKlB1JTAhoXJTFf9fXZkUEZFY5a80NmtWvfn9MblsBfDUKTh1inmvvALA3Esu8cafOwcnTjDvk0+88SkpldcXH1+5Auj/m5SkGCwitRa0suecmwX8CMgFcoCtQDNgFPAz59xG4N/M7OuKy5rZPmCf73O+c24z0C3I5q4HXjKzM0Cuc+5LYASwqsZ7FQ0uuaTq8b7KHmPGVH9dZSuE/qGw0AsgwZqs+Kf7m6b4r1iWHarLucrPLVRotkKLFt449Y4mIiKxzP+MX9Om0LJl+Wm+yh4TJ3p/Cwu9iqC/w5rBg+HECe+OoP9vYSEcP+4NVfFvp6ohMVEVQREJKNSdvRbASDM7VdVE51w60A+oVNmrMF9vYCjwMTAS+KFz7jZgLd7dvyN4FcHVZRbbTRWVQ+fcHGAOQOfOncnOzg6xC5ERKl31nm5/UAIwI96MpmbEFxd7n8v8TfANTc28v77PnD7tDUEYcM45zsTFcaZJk9IhLo7TTZpw2je+bGAqKCiI2uMYjZRfNac8qxnlV8MVLTFSZShwnM/et6/0i6/lTLwZzYqKaFZcTLOiIhJ9f5sVF9O8qIj4c+fgyBFvqKDQOU7FxZUMJ+LiOBkXx8n4eIojUAls7Me+Me+/9j070smoUtDKnpk9FWL6+lAbcM61BP4G3G1mx51zvwf+H1694P8BjwHfq26CzWwxsBhg2LBhNnbs2OouWi/y8/PZt28fgdKVn58PEHB61CouLv+sgr/i52u2wqlTcPIk7vRpEsxIKCykVaB1OVeuecr2Eyfo26dPaXOVZs10lTKI7Ozshld+Ikx5VjPKr4YrWmJkYy5DgX4H1Dr+m3ktcwoKID/f+1tmiD93jlaFhbTyP+pRVlIStGoFrVuXH/wXf8OgMR97aNz7r30fG+lkVKm6z+z1wWvO2bvsMmZ2XYjlmuJV9P5sZq/4ljlQZvozwFLf1z1AjzKLd/eNa1CuvfbaoDX7a6+9tv4SU5f8D5g3bx58Pn+l0Ff5K1sRLGmycvq09/fECQD6QvkObZo0KW2e0qqVN/g/q7mKiIhEsUC/A2od/8s+RtG+fflpVVUE/c1BCwpKY+3+/eWXa9bMq/RdcAG0aeMNrVp5zy2KSEypbm+crwHPAm8AxdVZwDnnfMtsNrPflhnfxfc8H8BkvM5eAJYAf3HO/Ravg5Z+QB13aSlhV7ZS2K5d1fP4ezDzBaGvN2+mZ/v2pc8unDkT+NmF+PjSip//r/9KpYKUiIg0JsEqgsXF5St//iE/v7R1zsGD5ddVtgLo/1vdTmtEJCpVt7J32swW1nDdI4HvAp8559b7xv0rMM33rJ8BO4A7AMzsc+fcfwOb8HryvKuh9cQJsHfv3pKmGoGmA3Tt2rW+khR94uJK79gB23ftoudll5VOP3eutImK/0plfr43nDvnvbvo6NHK601K8oKTv/J3wQW6UikiIvUq0O+Aeo//TZqUxsOyzLyLq8ePe7H02DHvb0GB9/nYMfi6TFcMiYlepa9tW29o1867oKtWNiINQnUre0845+YC7wBn/CPNbF2gBczsA6CqM8FbQZZ5CHiommmKSs888wwQuLmGf/rcuXPrLU0NTtOmpUGlrIrNVfxDxeYqvoBaomXLys1VkpIUqEREpM4F+h0QNfHfudJHJcpWPAsLSyt7/ouqx455rW0OHPAGv8TE0oqf/6/uAIpEpepW9tLw7tKNp7QZp/m+i9SPYM1ViopKr0qWba5S9kH2spXA+PjSip//imXr1npthIiINE7x8V5sLRtf/XcBjx4t7Q30yBGvArh/f/lnAZs3h7Zt6XnihNc8tF07b50iElHV/S/8NtDXzOrgbd4iYRAX5925u+CC8uOLikrv/pW9Wnn6NOTleYOf/3mFsk1VLrhAzUBFRKRxKnsXsHt3b5yZ93z9N994FT//X1+HbH0B3nvPm7dNm9IKZPv2alUjEgHVrextBNoAB0PMJxJd4uJK796Vdfp0acXPf8Wy7PMKO3Z48znnLduuXenQqpWClYiINE7Olb4qqYevE3UzL4YeOcLuDRvo3qxZ+Rj71VfefP6WOR06eH/bttUFVZEwq25lrw2wxTn3CeWf2Qv66gWRqNWsGVx4oTf4+Z9X8DdT+eYb746g/7s/WMXHl6/8tW+vZxVERKTxcq6k47Uvt2+n+9ixXkw9cgQOH/aGvDyv+efevaWPVTRp4sXQjh29oX17Vf5E6lh1K3vqTURiX1XPK5w7V1rx8w+nTjHP9w6luSkp3nwtW3pXKv1XK3X3T0REGrP4+NJKHJQ+/5eXV1oBPHYMDh3yBvDiZsXKn577EzkvQf+DnHPOPO+FmqfukyYSBZo2hU6dvMHv1CnYtMn73KmTF7D8ncD4m38mJJRW/jp08JqC6mqliIg0VmWf/+vd2xt39mxpZe/QIa/Jp/95+s2bvWXatfMqfp07686fSC2EulyS5Zz7G/C6mZW8dMU5lwCMAmYAWcBzYUthA/P973+fnJycoNOlgWvevPQ4du3qvbj26NHSZip5eew9cgSOHaNrxaYq/opju3bq+VNEJAYF+h2g+F+FhATo1s0bwKv85eWVVv7KNgPdssWr6Pkrfp07e52qqRWNSFChKnsTge8Bf3XO9QGOAs2BJnjv3FtgZp+GNYUNTNeuXfniiy+CTpeGr9xxbNKk9Pm9fv3AjK5lm6rk5XnP/vmD1+efewGrQ4fSyl+bNqr8iYjEgEC/AxT/qyEhwbuI6s+rc+e8GHrwoPeev2PHyr/yoVmz0opfp07e6x9EpJyglT0zOw38B/AfzrmmQAfglJkdrYe0iTRMVTVVOXPGq+gdPOgN+fnlX1Lrf7ahUyddrRQREQHvUYouXbwBvJ60/bHzwAHv+86d3gDe65IuvNCbv317XUQVofodtGBm54B9YUxLTHjjjTfYt28fY8eODTgd4Nprr63HVEldC3UcK01PTPTeUeR/T9GpU+UrfydOwL593gDe1ckLLyy9YpmQENb9ERGRuhHod4Difx1o1gx69fIGM6/VjL/id+hQ6euTtm71Kor+it+FF3pxWKQRUhdHdWzdunXVmq6TfcMW6jiGPM7Nm0PPnt4A3gtq/RW//fu9ymBurjeAd4XSX/lTf0giIlEr0O8Axf865px3J++CC6B/fygq8pp8+i+cFhTArl3eAF4c9d8lvOACtZ6RRkOVPZFo0KKF1+Szd2+vMnf0qHelcv/+8t1Uf/45I52D1au9ZxouvFB3/UREROLiSlvDpKd7j0v4Kn7lXpe0caMXc/0dw3TooIqfxDRV9kSijXPQtq03DBzoPaDufzh9/36anjhRerXSOS9Q+R9ob9ky0qkXERGJPN9L3unfH3yVPXr39i6injwJ27Z5Q2KiFz+7dfOem9erHSTGVKuy55y7Efg10AlwvsHMrHUY0yYi4D134L8CacbHy5dzSc+esHdv+S6q//EPr2MXf8WvXTtdrRQREfEbPtxrPfPNN7BnD+zZw7w1a+DTT727fvHxXjPPbt28ljNNm0Y6xSLnrbp39n4DXGtmm8OZGBEJwTlOxcd7Vyr79/feSbR/v1fx27fPe1j9+HHvfUT+q5U9eng9fapXMhERaeyc857fa98e0tJgzRpvfJs23iMU/pYzTZp4Fb8ePby/8WoMJw1TdUvuAVX0RKJQQkJpRy/Fxd4dvn37vMrfiROlnbz4313Uvbv3PIMqfiIi0tiVbf0yYYLXqcvevd5dv7y8krt/xMWVXjy98EI19ZQGJWhlz9d8E2Ctc+6/gNeAM/7pZvZK+JLWMHXp0oX8/Pyg06XhC3UcI3KcmzQpfTh9yBCv++k9e7wrlPn5sGOHNzRtWr7ip6AlIlJnAv0OUPyPnGB5X25ay5alLWdOnYLdu+Hrr71mn/47fv5HK3r08J7x08VTiXKh7uyV7R/4JHBlme8GqLJXwZw5c8j2PwgcYLo0fKGOY8SPs3Nek5Q2bSA11WvauXu3Nxw7VvoS2vh4L2j17KmgJSJSBwL9Doh4XGjEguV9wGnNm0O/ft5QtmO0o0dLL54mJHiVvt69vU7V9Jy8RKGglT0zmwXgnBtpZh+WneacGxnOhIlIHWrdGlJSvCE/v7Tid/RoacUvMdELWr16KWiJiIj4JSV5vWMPHOhdPPVX/PLz4auvvKFVK+jdm8SiokinVqSc6j6z9ySQUY1xIhLtWrWC5GRvyM/3mqh8/bX3rMKXX3pDy5alzwK2ahXpFIuIiESH1q29FjMpKaUXTL/+2ounn33GpQDvvefd7evWTR27SMSFembvMuByoKNz7t4yk1oDetCnCvPmzQNg7NixQafPnTu3vpIkYRDqODaY49yqVWnQOnKkfMVv0yZvaNvWC1o9e+oF7iIiIQT6HdBg4kIMCpb3tT4uZd+JO3iw1zP2zp3Y7t24gwe99+PGx3vPx/fp4/X+qRYzEgGhLjckAC1985W9vH8cmBpsQedcD+AFoDPe832LzewJ51w74L+A3sAO4CYzO+Kcc8ATwNV4zwfONLN1Nd0hEakF57z38rVr5wWtQ4e8q5V79niVwCNHvPf4devmBa1OnRS0REREwHve3feO249WrGBUr15eDD18uPT5vlatoG9f71GJxMRIp1gakVDP7L0HvOece87MdtZw3YXAfWa2zjnXCshxzr0LzASWm9kjzrn7gfuBnwFXAf18wyXA731/RaQ+le3Vs6jIq/Dt2AEHDpQ+p9C8uXe3r3dvr8mniIiIUNikCVx0kTf4e8LOzfU+/+Mf8Nln3t2+vn2hQwddOJWwC9WM8w28u3K4KgqjmV0XaFkz2wfs833Od85tBroB1wNjfbM9D2TjVfauB14wMwNWO+faOOe6+NYjIpEQF1f67N7Jk6VXKE+cgM2bvaFjR+9uX/fueo2DiIiIX6tW3ovbU1O9d+Bu3+419/Q/MtGypVfp691bd/skbEI143zU9/dG4ELgRd/3acCB6m7EOdcbGAp8DHQuU4Hbj9fME7yK4K4yi+32jStX2XPOzQHmAHTu3Dnoaw4iKVS6ojXdkVBQUNBg8yMSxzni+dW8OW3i47nw9Gk6njlD3KFDcOgQZz/5hP3NmrG3eXNOR1mlL+J51sAovxquaImRKkOBz/+xni/RfOyDpauu0hxq/5u1a8eFp0/T5fRpEgsKYMMGijds4GBiInuaNye/adM6SUckRPOxD7do3vfqNOPEOfeYmQ0rM+kN59za6mzAOdcS+Btwt5kdL3uH0MzMOWc1SbCZLQYWAwwbNswCdYQSKe+99x4QuIOWUNMbo+zs7AaXH5E8zlGVX+fOeVcnt28n4ehRep46Rc9Tp+DCC70mLF26REUTlajKswZA+dVwRUuMbMxlKND5v7HE/2g89sHyvq6PS7X3v7jYu8u3fTtN9u3jwjNnuPDMGe/Z+X79vNYyDezdt9F47OtLNO97dfuDTXLO9TWz7QDOuT5AUqiFnHNN8Sp6fzYz/wvYD/ibZzrnugAHfeP3AD3KLN7dN05EolXTpl6lrm9f+OYb711Du3Z5AWz/fu/Zvosu8pp5NmsW6dSKiIhEhzKdulBQ4MXP3Fwvln78sfd8X9++XgxV/JTzUN3K3j1AtnNuO+CAXsAdwRbw9a75LLDZzH5bZtISYAbwiO/v62XG/9A59xJexyzHGuLzepMmTWLr1q1Bp0vDF+o4Nrrj7JzXrXT79jBkiPdc31dfec/2bdwIn3/uPffXr5/XTbWISIwK9Dug0cWFKBIs76PiuLRs6cXO1FSvF88vv/Re3r5pk/dsfI8e0L+/4qfUSrUqe2b2d+dcP2Cgb9QWMzsTYrGRwHeBz5xz633j/hWvkvffzrnZwE7gJt+0t/Beu/Al3qsXZlV3J6JJZmYm+fn5QadLwxfqODbq45yYCAMGeIHpwAGv0rd3rxfAdu70eh/r39+7mhkFTTxFROpSoN8BjTouRFiwvI+q4xIfX9pa5tAhr9K3Z09phy6dOnnxtXNnxU+ptlC9cY43sxXOuRsrTLrIOUeZppmVmNkHeHcBq3JFFfMbcFeoBItIA+Gc9+zehRd6d/i2bfOaqOTleUNSknenr3dvrzmoiIiIePGzUydvOHHCq/Rt3+69qP3gQbjgAu+iac+eDe65Pql/oe7sfQtYAVxbxTQDAlb2GqucnBz27t0bdDpE2ZUkqbFQx1HHuYKkJEhP95qo5OZ6gevECVi/3mvi2aePF7iaN490SkVEzkug3wGKC5ETLO+j/rgkJXlNPJOTvQrftm1w7Bh88on3mES/ft6dQF00lQBC9cY51/e3QTapjISlS5dWa3rUnlSkWkIdRx3nAJo29Sp1/fp5TVO2bfPu8n3xhVcB7NXLa6LSqlWkUyoiUiuBfgcoLkROsLxvMMclIQEGDvRi6Ndfw9at3nN9GzZ4z/b16+cNel+fVFCtZ/acc18Bq4GVwEoz+zysqRKR2Oac16109+5ez2Nbt8Lu3d5dv9xcb/zAgXoYXUREpKwmTbzHH3r18nq93rrVe75v82bvwunFF3sVQvXgKT7V7Y0zBa+HzNHAfOfcAGCDmU0OW8pEpHFo1w4uuwzy82HLFq8Tl927veHCC71KX4cOehhdRETEzznvXbZdungtZDZvLq38ffml17RzwAA9HiHVruwVAed8f4vx3o13MOgSIiI10aoVDB/uPdf3xRfeswn+9/V16OCN79Qp0qkUERGJLh06wOjRXkuZzZu9HrC3bfN6w+7Tx7to2qJFpFMpEVLdyt5x4DPgt8AzZnY4fEkSkUatRQuvM5fkZO/qpP+5vvfeg44dvUpfx46RTqWIiEh0adcORo6Eo0e9St/u3aUva7/oIq/Sp+adjU51K3vTgFHA/wFud859BLxvZsvDljIRadwSE72KXf/+XoXviy+85xKys707fKmp3tVMERERKdWmjfd4xLFjXqVv1y4vjm7f7sXU/v29Dl+kUajuS9VfB153zg0ErgLuBn4KqCGwiIRX06aQkuL1MvbFF17A8r9rqHNnr9LXvn2kUykiIhJdLrgALr3Uu6O3cSPs2+dV/r780nuer18/70XuEtOq2xvn34AhwFfA+8BtwMdhTFeDNXfuXLKzs4NOl4Yv1HHUcQ6Dpk29il3ZSt+BA97QrRukpemVDSIScYF+ByguRE6wvG8Ux6VNGxg1Cg4fhs8+81rJbNzoxdGUFK8zF72cPWZVtzr/MPCpmRWFMzEiIiElJMCgQV4zlK1bvWC1Z4/3QHqfPl7gUu9jIiIi5bVvD9/6ltcyZuNGr0OXTz/14ujgwdC1q3q+jkHVbca5NtwJERGpkYQE727exRd7L5TNzfWeR9i506sIDhjg3Q0UERERj3PeIxCdOnkXSTdsgIIC+Ogjr/OzIUP0jtsYo3u2dWzx4sXk5OQEnb548eJ6TJGEQ6jjqONcj5o3h8xMuPJK76pkUZH3TMLbb3vPJRQXRzqFItKIBPodoLgQOcHyvtEeF+e8RyD++Z+9HrATErzmncuWwccfw8mTkU6h1BE9lVnH9u3bd17TpWHQcY5CrVt7XU7n5XlXKg8f9pqnfPUVbdUsRUTqSaDzv+JC5ATL+0Z/XJo08Z6F79ULtmzxmnR+/bX32oYBA7zOXdSJS4NWrTt7zrlKr1ioapyISMR16ADjxsHll0NSEhw/zpBjx+DDD72mKiIiIlJeQoL33N7EidCjh9cqZvNm+N//9Sp+ZpFOodRS0Kq6c64Z0ALo4JxrC/gvj7cGuoU5bSIiteNvnnLhhbBtG4UbNxK/dy/s3+9dwUxO1vN8IiIiFSUlea9ruPhir3XM0aOwapX3nN/Qoer1ugEKdWfvDiAHGOj76x9eB34X3qSJiJynuDgYOJA1bdtC797elcqtW+Hvf/c6ctGVShERkco6dIB/+ievgte0qfeao//9X+8xicLCSKdOaiBkI1wz6+Oc+4WZ/Xt9JEhEpK6djYuD4cPhoou8K5XffANr1ng9eGZm6kqliIhIRc55d/h69PDez5eb610w/fprr1OX7t0jnUKphlB39mb5/t4Q5nSIiIRfu3YwfrxX8fP3PPbOO/D5514vniIiIlJeYiIMGwZXXOG9luHUKa9p50cfeZ8lqoW6s7fZObcN6Oqc21BmvAPMzAaHL2kNU0ZGRtCenTIyMuoxNRIuoY6jjnMUc85r0tmli9ccZccO7z19X38NGRnecwkiIrUU6HeA4kLkBMt7HZcaaNfOq/B99ZV3p2/PHq955+DB0LdvpFMnAQSt7JnZNOfchcD/AtfVT5IatmuvvZbs7Oyg06XhC3UcdZwbgMRE7w5f796wbh0cPw7vvw89e3rNUxITI51CEWmAAv0OUFyInGB5r+NSQ/6mnV27erFz3z7v79df00ItZKJSdZ7Z2w8MqYe0iIjUv44dYcIE7zkE/x2+Awe8u3x6HkFERKSyFi28d9vu3u09C5+XxzDwXtcwYID3/j6JCkGPhHPuv31/P3PObSgzfFahWWdVy/7ROXfQObexzLgHnXN7nHPrfcPVZaY94Jz70jm31Tn3z+e7Y5Gyd+9e8vPzg07fu3dvPaZIwiHUcdRxbmCaNPFex/DP/+xV/s6c8Z5HWL3a+ywiUk2BfgcoLkROsLzXcTkPznmdt0ycCH36eJWKjRshK8trLSNRIVS1+//6/k4Cri0z+L8H8xwwsYrxj5tZum94C8A5lwLcDKT6lvkP51xctfYgyjzzzDOsW7cu6PRnnnmmHlMk4RDqOOo4N1AtW8K3vuV1NR0XB7t2eV1N79oV6ZSJSAMR6HeA4kLkBMt7HZc6kJAAw4ax/oILoHlzr8frd9+Fbdv0iqMoELSyZ2b7fH93lh2AXcCoEMu+D3xTzXRcD7xkZmfMLBf4EhhRzWVFROqO/3mEK68svcu3erV3p+/s2UinTkREJCodTUjwWsj432u7fj289x6cOBHppDVqQZ/Zc861Bu4CugFLgHeBHwL3Af8A/lyLbf7QOXcbsBa4z8yO+Na/usw8u33jqkrTHGAOQOfOnYN2hhJJodIVremOhIKCggabH5E4zg05vyKl1nlmRteWLbmooIC43bs5s3cvm1u18gJaDFMZa7iiJUaqDAU+/8d6vkTzsQ+WrrpKczTvf7gVFBSQ/eGHALRv3ZoB+fkkHDpE4dtv82XLluxPTPQuqMagaD7uoTpo+RNwBFgF3A78K95rF24ws/W12N7vgf8HmO/vY8D3arICM1sMLAYYNmyYjR07thbJCJ/33nsPgEDpCjW9McrOzm5w+RHJ49wQ8yvSzjvPCgpgzRoSDx8m/dgx7+Hz1FSvqWcMUhlruKIlRjbmMhTo/N9Y4n80HvtgeV/XxyUa97++VNr3M2dg3Trid+9mYH4+A9u29To/a9o0YmkMl2g+7qEqe33NLA3AOfcHYB/Q08xO12ZjZnbA/9k59wyw1Pd1D9CjzKzdfeNERCKvZUsYO9brZWzzZq/nzgMH4JJLoHXrSKdOREQk+iQmwqWXws6dJa9n4PBhb1y7dpFOXaMRqoOWc/4PZlYE7K5tRQ/AOdelzNfJgL+nziXAzc65ROdcH6AfsKa22xERqXNNmnh388aNg6QkOHoUli2D7dv1ALqIiEhVnPOe4ZswAdq08Z7fW7HCu2iq2FkvQt3ZG+Kc8/ed6oDmvu8OMDMLeEnbOfdXYCzQwTm3G5gLjHXOpeM149wB3IG3os99r3nYBBQCd/kqlyIi0aV9ey9offqpd7UyJwfy8rymKfEhX10qIiLS+LRqBePHw2efeb10bthQ2kImMTHSqYtpQX+ZmFmtH0gxs2lVjH42yPwPAQ/VdnvR4vvf/z45OTlBp0vDF+o46jjHuKZNYcQI6NzZq+zt3AlHjsBll6lZp0gjF+h3gOJC5ATLex2XehQXB+np0KkTfPKJV9l79124/HI16wwjXYauY127duWLL74IOl0avlDHUce5kejVC9q2hY8+8l4gu2wZZGZ640WkUQr0O0BxIXKC5b2OSwR07eq93uijj7x38mVlee+37dMnZnvrjKRQz+yJiEgwrVvDP/0T9OwJRUWwZo13t6+4ONIpExERiU7Nm3vPwF90kRcvc3Jg7VovjkqdUmWvjr3xxhtB7+y98cYbvPHGG/WYIgmHUMdRx7mRiY/3mnVmZHgduWzfDtnZcLrW/VmJSAMV6HeA4kLkBMt7HZcIatLEi5sjRnhNPHfs8Dpv0UvY65Qqe3Vs3bp17Nu3L+j0devW1WOKJBxCHUcd50bIOe8K5bhx3hXLw4e9Zp1HjkQ6ZSJSjwL9DlBciJxgea/jEgV69fI6b/H3dL18udfxmdQJVfZEROpSu3ZwxRVer52nTnnPInz9daRTJSIiEr3atPEeiejc2XsZ+3vveZ2fyXlTZU9EpK41bw7f+pb3bqGiIvj4Y6+7ab1TSEREpGoJCTBqVOlzfGvWKHbWAVX2RETCIS4Ohg3zupl2DrZs8Sp9evhcRESkav7n+IYOLY2dq1ZBYWGkU9ZgqbInIhIuzkG/ft6Vyvh42LUL3n8fzp6NdMpERESi18UXl8bOPXu8Zp1nzkQ6VQ2SKnsiIuF24YVexy3NmnkPnau3MRERkeAuvNB7Br5Fi9L38Sl21pheql7HunTpQn5+ftDp0vCFOo46zlJJmzZe0Fq50nsB+/LlMHq091J2EYkZgX4HKC5ETrC813GJcq1bez11rlwJx455F0vHjIELLoh0yhoMVfbq2Jw5c8jOzg46XRq+UMdRx1mq1KKFF7Q++ggOHvTexTdqFHTsGOmUiUgdCfQ7QHEhcoLlvY5LA9C8OYwdCx9+6LWOycqCkSMVO6tJzThFROpT06beHb0ePbwHzt9/H4K8m1NERKTRS0jw7uh16wbnzil21oAqeyIi9a1JE7jkEujTx+te+sMPvc5bREREpGpxcXDZZdC3b2ns3LMn0qmKeqrs1bF58+bx3nvvBZ0+b968ekyRhEOo46jjLCE5B5mZ0L+/9w6h1ashNzfSqRKR8xTod4DiQuQEy3sdlwbGOe/VDP36ebFz1SpdLA1BlT0RkUhxDgYPhtRU7/vatbB9e2TTJCIiEs2cgyFDYMCA0oulO3dGOlVRS5U9EZFIcg5SUrzABZCTozt8IiIiwTgHaWle/ARYswZ27IhokqKVKnsiItGgf3/vLh94d/h0lVJERCQw57yWMYMGed8/+URNOqugyp6ISLQYMMC7UgneVcqvv45sekRERKJdcnLpHb6PP1YvnRWosiciEk0GDix9hu/jj9XTmIiISCgpKaUdnn30ERw4EOkURQ1V9kREok1KinelErwHzw8dimx6REREopm/w7OLLip9LcPhw5FOVVSIj3QCYs2kSZPYunVr0OnS8IU6jjrOct5SU+HMGa93zg8/hLFjoU2bSKdKREII9DtAcSFyguW9jksMcQ6GDoXCQu+59w8+gPHjoVWrSKcsosJW2XPO/RGYBBw0s0G+ce2A/wJ6AzuAm8zsiHPOAU8AVwMngZlmti5caQunzMxM8vPzg06Xhi/UcdRxlvPmf5fQmTNeU86VK72glZQU6ZSJSBCBfgcoLkROsLzXcYkxzsGwYV7s3L+/NHY2axbplEVMOJtxPgdMrDDufmC5mfUDlvu+A1wF9PMNc4DfhzFdIiINg3NwySXQsSOcPg3vvw9nz0Y6VSIiItGrSRO47DKvNcyJE94dvsLCSKcqYsJW2TOz94FvKoy+Hnje9/l54IYy418wz2qgjXOuS7jSFk45OTns3bs36PScnJx6TJGEQ6jjqOMsdSYuDkaOhAsugIIC78Hz4uJIp0pEAgj0O0BxIXKC5b2OS4yKj4fRo6FFCzhyxHv+3SzSqYqI+n5mr7OZ+ftD3Q909n3uBpR9McZu37hKfac65+bg3f2jc+fOZGdnhy2xtfHee+8BBEyXf3qwpp6NTUFBQdQdx1BCHcdwHueGmF+RFgt5lhgXR6ZzJBw6xN433+SLli29O39hEAv51VhFS4xszGUo0O+AxhL/o/HYB8v7uj4u0bj/9SUa9715YiIZp07RdN8+vn7zTba3bBmW7UTjvvtFrIMWMzPnXI2r2Ga2GFgMMGzYMBs7dmxdJ+28+E8agdIVanpjlJ2d3eDyI5LHuSHmV6TFTJ4dPgzZ2XQ9fZquAwZ43UyHQczkVyMULTGyMZehQOf/xhL/o/HYB8v7uj4u0bj/9SVq9/3gQXj/fXqeOkXPtDTo1avONxG1+079v3rhgL95pu/vQd/4PUCPMvN1940TERG/9u1h+HDv8z/+oRfHioiIhNKpE6Sne5/XroVvKj5lFtvqu7K3BJjh+zwDeL3M+Nuc51LgWJnmniIi4tezp/cePvBeun7iRGTTIyIiEu0uugj69PGeef/oI6/Ts0YibJU959xfgVXAAOfcbufcbOARYIJzbhvwT77vAG8B24EvgWeA/xOudImINHgpKdClC5w7B6tWQVFRpFMkIiISvfyvM2rfHk6dalQdtoTtmT0zmxZg0hVVzGvAXeFKi4hITHEORoyAd9/1ehlbvx70rigREZHAmjSByy+Hd96BQ4dg0yZITY10qsKuvptxiohIXUhI8IJWkyawfTvs3BnpFImIiES3Zs2899eCV9k7eDD4/DEgYr1xxqq5c+cG7Xp17ty59ZcYCZtQx1HHWepF27YwdCjk5MC6dV7zlDB1Ky0i1RPod4DiQuQEy3sdl0aoc2dITobNm71n3ydM8CqBMUp39kREGrI+faB7dygshDVr9MJ1ERGRUFJToWNHr6OWTz6J6ef3VNkTEWnInPOe12ve3HsP35YtkU6RiIhIdHPOa87ZtCns3w+5uZFOUdioslfHFi9eTE5OTtDpixcvrscUSTiEOo46zlKvEhJK37+3aVOje4eQSDQJ9DtAcSFyguW9jksj1ry510MneB2dFRRENDnhomf26ti+EC85DjVdGgYdZ4k6nTtD//7wxRdec84JEyAuLtKpEml0Ap3/FRciJ1je67g0cj16wJ49sHu315xz7Fjvrl8M0Z09EZFYMWgQtGoF+flqzikiIhKK//17iYmQlwdffhnpFNU5VfZERGJFXFzp+/Y2b4ZjxyKbHhERkWiXmFgaOzdu9F66HkNU2RMRiSUdO0Lfvl7PYmvXxnQPYyIiInWiWzfo2tXr2Xr9+kinpk6psiciEmsGD/beGfTNN94L10VERCS4oUO9FjK7d0MMPcupyp6ISKxp2hTS073PGzfC2bMRTY6IiEjUa9HCe/8ewKefQlFRZNNTR9QbZx3LyMgI2rNThr+LV2nQQh1HHWeJuO7doUMH74HzTZtKK38iElaBfgcoLkROsLzXcZFy+vWDHTvg+HHYtg0GDox0is6bKnt17NprryU7OzvodGn4Qh1HHWeJOOe8Jinvvuv1Lta3L7RuHelUicS8QL8DFBciJ1je67hIOU2aeBdH33/f6+isTx+vA5cGTM04RURiVZs2pZ21bNgQ6dSIiIhEv86d4cILvc5aNm2KdGrOmyp7dWzv3r3k5+cHnb537956TJGEQ6jjqOMsUSM1FeLjvYfN8/IinRqRmBfod4DiQuQEy3sdF6nS4MHe36++8t5d24CpslfHnnnmGdatWxd0+jPPPFOPKZJwCHUcdZwlajRr5j2DAF5nLSISVoF+ByguRE6wvNdxkSpdcIHXhNMMPv880qk5L6rsiYjEuv79vR46Dx2CgwcjnRoREZHol5LiPf++a5fXYUsDpcqeiEisS0iAAQO8zxs36kXrIiIiobRo4d3dA6+zlgZKlT0Rkcbg4ou9St/hw3p2T0REpDoGDvTu7n39dYN9dk+VPRGRxqBpU7joIu/z1q2RTYuIiEhDkJQEvXt7nxto7FRlT0Sksbj4Yu8dQvv2NejnD0REROqN/zGInTvhzJnIpqUWIlLZc87tcM595pxb75xb6xvXzjn3rnNum+9v20ikTUQkZjVrVnqF8osvIpoUERGRBqFVK++9e8XFsH17pFNTY/ER3PY4Myv74Mj9wHIze8Q5d7/v+88ik7Ta+/73v09OTk7Q6dLwhTqOOs4Stfr394LVzp3ee4QSEiKdIpGYEuh3gOJC5ATLex0XqZZ+/WD/fu+9ewMGeK1kGohIVvYquh4Y6/v8PJBNA6zsde3alS+CXDHv2rVrPaZGwiXUcdRxlqjVqhV06uS9gmHnztJ38IlInQj0O0BxIXKC5b2Oi1RL585e/MzPhz17oEePSKeo2pxFoAtu51wucAQw4GkzW+ycO2pmbXzTHXDE/73CsnOAOQCdO3fOfOmll+ot3dVVUFBAy5YtI52MBkP5VTPKr5pTnpXX8cwZUo8fpyAujrVt23o9jZURrfk1bty4HDMbFul0RLNoiZHRWobqS2Pe/8a879C49z/W973bqVP0Kyjgm6ZN2dCmTblpkd73YPExUpW9bma2xznXCXgX+BGwpGzlzjl3xMyCPrc3bNgwW7t2bXgTW0NvvPEG+/btY86cOQGnA1x77bX1mayolp2dzdixYyOdjBoJdRzDeZwbYn5FmvKsguJiWLrUe9B8/Hho377c5GjNL+ecKns1EMkYGa1lqD4E+h3QWOJ/NB77YHlf18clGve/vsT8vp8548XO4mKYNAmaNy+ZFOl9DxYfI9Lg1Mz2+P4eBF4FRgAHnHNdAHx/D0Yibedr3bp17Nu3L+j0devW1WOKJBxCHUcdZ4lqTZqUdtSyY0ckUyIScwL9DlBciJxgea/jItWWmAj+Zr87d0Y2LTVQ75U951ySc66V/zNwJbARWALM8M02A3i9vtMmItJo9Orl/d2927tKKSIiIsGVvVAagdaRtRGJDlo6A696j+URD/zFzP7unPsE+G/n3GxgJ3BTBNImItI4tG5d+rD5wYNet9IiIiISWOfO3h2+/Hw4dgwqPLsXjeq9smdm24EhVYw/DFxR3+kREWmUnPN6E9u0CXbtUmVPREQklCZNvKacubler5wNoLLXcF4SISIidcvfdfSePWrKKSIiUh3dunl/9+yJbDqqSZU9EZHGqnVraNkSzp2Db76JdGpERESiX6dOEB/vNeMsKIh0akKKppeqx4QuXbqQn58fdLo0fKGOo46zNBhdusC2bbBvH3ToEOnUiDR4gX4HKC5ETrC813GRGouL82Lnrl2wfz9cfHGkUxSUKnt1bM6cOWRnZwedLg1fqOOo4ywNxoUXepW9/fshLS3SqRFp8AL9DlBciJxgea/jIrXSubNX2TtwIOore2rGKSLSmHXs6F2lPHoUTp+OdGpERESiX6dO3t9Dh6L+FQyq7ImINGZxcdC+vff58OHIpkVERKQhSEryhnPn4MiRSKcmKFX26ti8efN47733gk6fN29ePaZIwiHUcdRxlgbFX9nLy4tsOkRiQKDfAYoLkRMs73VcpNbK3t2LYqrsiYg0dv6OWVTZExERqR7/hdIo781alT0RkcbOH7COHIGiosimRUREpCFo1877q2acIiIS1Zo29d63ZwZBXh0jIiIiPq1aec+9nzhB0+LiSKcmIFX2REQELrjA+3vsWGTTISIi0hA0aQJt2gDQsrAwsmkJQpU9ERFRZU9ERKSmWrcGoEUUPwKhyp6IiKiyJyIiUlP+yl4U39mLj3QCYs2kSZPYunVr0OnS8IU6jjrO0uC0auX9LSiA5s0jmxaRBizQ7wDFhcgJlvc6LnJefLEzmu/sqbJXxzIzM8kP0sFBZmZmPaZGwiXUcdRxlgYnKcn7e/IkNGsW2bSINGCBfgcoLkROsLzXcZHz4qvsNY/iyp6acYqICMTHQ0ICFBeTEMW9iomIiEQNX0uYhOJir0frKKTKXh3Lyclh7969Qafn5OTUY4okHEIdRx1naZB8d/eaqbInUmuBfgcoLkROsLzXcZHzEhcHCQleherMmUinpkpqxlnHli5dWq3pajbQsIU6jjrO0iAlJgIQr8qeSK0F+h2guBA5wfJex0XOW/PmcPYsnDoVlY9B6M6eiIh4EhIAaBqlTVFERESiju9CabTe2VNlT0REPP7Knu7siYiIVI8vdnLuXGTTEYAqeyIi4vE349SdPRERkepp2tT7q8pe9TjnJjrntjrnvnTO3R/p9IiINBotWsAFF1DoXKRTIiIi0jCosld9zrk44CngKiAFmOacS4lsqkREGoneveHKK9ndokWkUyIiItIwDBzIR+3awcUXRzolVYqqyh4wAvjSzLab2VngJeD6CKdJRERERESkssREzsbFea9hiELOoujZDOfcVGCimd3u+/5d4BIz+2GZeeYAc3xfBwBb6z2hoXUA8iKdiAZE+VUzyq+aU57VTLTmVy8z6xjpRESzKIqR0VqG6ktj3v/GvO/QuPdf+x45AeNjg3vPnpktBhZHOh3BOOfWmtmwSKejoVB+1Yzyq+aUZzWj/Gq4oiVGNvYy1Jj3vzHvOzTu/de+R+e+R1szzj1AjzLfu/vGiYiIiIiISA1EW2XvE6Cfc66Pcy4BuBlYEuE0iYiIiIiINDhR1YzTzAqdcz8E/heIA/5oZp9HOFm1EfEmNA2M8qtmlF81pzyrGeWXnK/GXoYa8/435n2Hxr3/2vcoFFUdtIiIiIiIiEjdiLZmnCIiIiIiIlIHVNkTERERERGJQars1THn3ETn3Fbn3JfOufsjnZ5o45z7o3PuoHNuY5lx7Zxz7zrntvn+to1kGqOJc66Hcy7LObfJOfe5c+7/+sYrz6rgnGvmnFvjnPuHL7/m+cb3cc597Pu//C9fB1Di45yLc8596pxb6vuu/JJaa2xxsDHHtcYcoxRvGnfscM7tcM595pxb75xb6xsXleVelb065JyLA54CrgJSgGnOuZTIpirqPAdMrDDufmC5mfUDlvu+i6cQuM/MUoBLgbt8ZUp5VrUzwHgzGwKkAxOdc5cCvwYeN7OLgSPA7MglMSr9X2Bzme/KL6mVRhoHn6PxxrXGHKMUbxQ7xplZepn360VluVdlr26NAL40s+1mdhZ4Cbg+wmmKKmb2PvBNhdHXA8/7Pj8P3FCfaYpmZrbPzNb5PufjnVS7oTyrknkKfF+b+gYDxgMv+8Yrv8pwznUHrgH+4PvuUH5J7TW6ONiY41pjjlGNPd4odlQpKsu9Knt1qxuwq8z33b5xElxnM9vn+7wf6BzJxEQr51xvYCjwMcqzgHzNStYDB4F3ga+Ao2ZW6JtF/5flLQB+ChT7vrdH+SW1pzjoaXTn6MYYoxp5vFlA444dBrzjnMtxzs3xjYvKcq/KnkQV894FoveBVOCcawn8DbjbzI6XnaY8K8/MiswsHeiOd5dhYGRTFL2cc5OAg2aWE+m0iMSqxnCObqwxqrHGG8UOAEaZWQZek/W7nHNjyk6MpnIfVS9VjwF7gB5lvnf3jZPgDjjnupjZPudcF7wrZOLjnGuKF0T/bGav+EYrz0Iws6POuSzgMqCNcy7ed8VR/5elRgLXOeeuBpoBrYEnUH5J7SkOehrNOVoxqlHGm0YfO8xsj+/vQefcq3iV/ags97qzV7c+Afr5eiNKAG4GlkQ4TQ3BEmCG7/MM4PUIpiWq+NrAPwtsNrPflpmkPKuCc66jc66N73NzYALeMyRZwFTfbMovHzN7wMy6m1lvvPPVCjObjvJLak9x0NMoztGNOUY15njT2GOHcy7JOdfK/xm4EthIlJZ7591llLriu8qxAIgD/mhmD0U2RdHFOfdXYCzQATgAzAVeA/4b6AnsBG4ys4oPuzdKzrlRwErgM0rbxf8r3jMRyrMKnHOD8R6KjsO7mPXfZvbvzrm+eB1FtAM+BW41szORS2n0cc6NBX5sZpOUX3I+GlscbMxxrTHHKMUbT2OMHb79fNX3NR74i5k95JxrTxSWe1X2REREREREYpCacYqIiIiIiMQgVfZERERERERikCp7IiIiIiIiMUiVPRERERERkRikyp6IiIiIiEgMUmVPREREREQkBqmyJyIiIiIiEoNU2RMREREREYlBquyJiIiIiIjEIFX2REREREREYpAqeyIiIiIiIjFIlT0REREREZEYpMqeiIiIiIhIDFJlT0REREREJAapsiciIiIiIhKDVNkTERERERGJQarsiYiIiIiIxCBV9kRERERERGKQKnsSMc65IufceufcRufcG865Nr7xXZ1zL5eZ76/OuQ3OuXucc3c751rUcnv/7pz7pyrGj3XOLS3z+fIy055zzk2tzfZqyzm3wznXoTbzOM8K51xr3/d/cc5tds792Tk30zn3uzpMZ0m+RZpzboJzLsc595nv7/gy05Y559pGMn0iIjWlGBkwnYqRNaQY2bipsieRdMrM0s1sEPANcBeAme01s6kAzrkLgeFmNtjMHgfuBmoVyMzsF2a2LMRsY4HLQ8wTza4G/mFmx33f/w8wwcymRzBN9SEPuNbM0oAZwJ/KTPsTXj6IiDQkipF1TzFSMbLRUWVPosUqoBuAc663c26jb/w7QDff1c25QFcgyzmXVXZh59xw59wrvs/XO+dOOecSnHPNnHPbfeNLrkA65yY657Y459YBN/q3C/wAuMe3vdG+1Y9xzn3knNte1RVMX3q3+Nb/he8K4T855z50zm1zzo3wzdfOOfea7wrsaufcYN/49s65d5xznzvn/gC4Muu+1Tm3xpeep51zcSHycTrwum/ZRUBf4G3n3D1VpHmFLy3LnXM9nXNxzrlc35XPNr6rymN887/vnOsXaKPOuRHOuVXOuU99eTXAN/7NMvv5qXPuF77P/+6c+34VadrsnHvGlxfvOOeah9hfAMzsUzPb6/v6OdDcOZfo+74EmFad9YiIRCnFSMVIxUipFVX2JOJ8J+cr8E44FV0HfOW7ujkP2AuMM7NxFeb7FEj3fR4NbASGA5cAH1fYXjPgGeBaIBO4EMDMdgCLgMd921vpW6QLMAqYBDwSYDcuBh4DBvqGW3zL/Bj4V98884BPzWywb9wLvvFzgQ/MLBV4FejpS2cy8B1gpJmlA0V4gSqYkUCOb39+QGl+PV5hvieB531p+TOw0MyKgK1Aii/t64DRvoDQw8y2BdnuFmC0mQ0FfgH8yjd+pW8dFwCFvvSBd4zer2I9/YCnfHlxFJjiy4uf+IJ5xWFhFeuYAqwzszO+fDgCJDrn2gdJv4hIVFKMVIwsQzFSaiw+0gmQRq25c2493tXKzcC7tV2RmRU6577ynfxHAL8FxgBxeCfTsgYCuf4Ts3PuRWBOkNW/ZmbFwCbnXOcA8+Sa2We+9X0OLDczc859BvT2zTMK34nZzFb4rla29qXzRt/4N51zR3zzX4EXaD9xzgE0Bw6GyIp2ZpYfYh6Ay/zbxGvC8Rvf55W+9PQBHga+D7wHfBJifRcAz/uubBrQtMz6/gXIBd4EJjjveZI+Zra1ivXkmtl63+ccfHlnZvOB+aF2yjmXCvwauLLCpIN4V7wPh1qHiEiUUIxUjKxIMVJqTHf2JJJO+a7G9cJrlnHXea7vfeAq4BywDC9wjKJyIKupM2U+u2rMU1zmezG1v6ji8K4spvuGAWb2YIhlCp1z5/N//T7eFcURwFtAG7xnNELl4f8DsnzPllwLNPON/wQYRulVyk/xgmNOgPWUzccifHlXnauWzrnueFd9bzOzryqstxlwKsQ+iIhEE8XI4BQjFSOlGlTZk4gzs5N4V7buc86FOunnA60CTFuJ93D6KjM7BLQHBuA1VylrC9DbOXeR73vZturB1n++VuJrYuKcGwvk+R4Sfx+vSQvOuasAf69Yy4GpzrlOvmntnHO9QmxjK94zCKF8BNzs+zyd0kC1Bu/h+2IzOw2sB+6g6uYkZV0A7PF9nukfaWZngV3At/GeOVmJ12wn1PrKMbP5ZQJ62eFfAJzXS92bwP1m9mHZZZ13yfdCYEdNtikiEg0UIxUjQ1GMlGBU2ZOoYGafAhsI/ZDwYuDvrsLD5z4fA50pPUluAD4zM6uwrdN4TVLedN7D52WbfbwBTHblHz6vKw8Cmc65DXjPNczwjZ+H94D753jNRr72pXMT8HPgHd8y7+I9GxHMm3hXGUP5ETDLt97vAv/Xt80zeIFntW++lXiB/bMQ6/sN8LBz7lMqX6VdCRw0s1O+z905/yvJFf0Q75mQX5S5otnJNy0TWG1mhXW8TRGReqEYqRh5nhQjGzFX4X9cRBow51wX4AUzmxDptEQL59wTwBIzWx7ptIiISOQoRlamGBn7dGdPJIaY2T7gGd9D7eLZqCAmIiKKkVVSjIxxYb+z5+syeC2wx8wmOef6AC/htRXPAb5rZmd9Xde+gHc7+TDwHV83vyIiIiIiIlJD9XFn7//idRns92u8d7RcDBwBZvvGzwaO+MY/7ptPREREREREaiGslT1fN6/XAH/wfXfAeOBl3yzPAzf4Pl/v+45v+hW++UVERERERKSGwv1S9QXATyntprc9cLRMjz+78V4Wiu/vLih5+ecx3/x5ZVfonJuD7+WezZs3z+zRo0c4018rxcXFNGmixyGrS/lVM8qvmlOe1Uy05tcXX3yRZ2YdI52OaBYtMTJay1B9acz735j3HRr3/mvfI7fvweJj2Cp7zrlJeF3J5vjel1InzGwxXtfCDBs2zNauXVtXq64z2dnZjB07NtLJaDCUXzWj/Ko55VnNRGt+Oed2RjoN0S5aYmS0lqH60pj3vzHvOzTu/de+j43Y9oPFx3De2RsJXOecuxpoBrQGngDaOOfifXf3ulP6ksk9QA9gt++loRfgddQiIiIiIiIiNRS2+41m9oCZdTez3sDNwAozmw5kAVN9s80AXvd9XkLpCzSn+ubXSwBFRERERERqIRKNS38G3Ouc+xLvmbxnfeOfBdr7xt8L3B+BtImIiIiIiMSEcHfQAoCZZQPZvs/bgRFVzHMa+HZ9pEdERERERCTWNc4uc0RERERERGKcKnsiIiIiIiIxSJU9ERERERGRGKTKnoiIiIiISAxSZU9ERERERCQGqbInIiIiIiISg1TZE4kC27dvZ/bs2UydOjXSSZEYonIlIg2BzlXSmNR3eW+0lb2ZM2finMM5x44dOyKShgMHDnDLLbfQt29fMjMzueyyy3j11VcBcM5x3333lcz76KOP8uCDD5Z8f+ihh0hNTWXw4MGkp6fz8ccfBx0fS3bt2sW4ceNISUkhNTWVJ554omRa7969SUtLIz09nWHDhpVbrqioiKFDhzJp0qSA6w62fDj17duXZ599tk7XqfJVc9/73vfo1KkTgwYNKhm3detW0tPTS4bWrVuzYMECoGblpTrlr66Fo1yJ1BWdo2pHMbBhU7mvOcXm81MvL1WXysyMG264gRkzZvCXv/wFgJ07d7JkyRIAEhMTeeWVV3jggQfo0KFDuWVXrVrF0qVLWbduHYmJieTl5XH27NmA42NNfHw8jz32GBkZGeTn55OZmcmECRNISUkBICsrq1KeATzxxBMkJydz/PjxoOsPtHxd+Oyzz3jggQfKjfvjH/9Ip06d6nQ7Kl+1M3PmTH74wx9y2223lYwbMGAA69evB7yg0K1bNyZPnlwyvbrlpbrlrzbqq1yJ1BWdo2pPMbDhUrmvHcXm89No7+xF2ooVK0hISOAHP/hBybhevXrxox/9CPBO5nPmzOHxxx+vtOy+ffvo0KEDiYmJAHTo0IGuXbsGHF/R/PnzWbhwIQD33HMP48ePL0nT9OnTy827Y8cOBg4cyMyZM+nfvz/Tp09n2bJljBw5kn79+rFmzZqSeV988UVGjBhBeno6d9xxB0VFRQDccMMNZGZmkpqayuLFiwE4ceIE11xzDUOGDGHWrFn813/9V7XzrkuXLmRkZADQqlUrkpOT2bNnT9Bldu/ezZtvvsntt99e7e1UpSb5UdV+p6WlsXTp0nJDOP7pI1m+IHBZ8KuPcjVo0KAalSuAMWPG0K5du4DTly9fzkUXXUSvXr1qtN5Q5a+hlCuRuhLrMfCxxx4L27lKMbDhUmyO3dj885//PHrLu5k12CEzM9Nqa8aMGQYYYB9//LHdcsstdsEFF1jLli3t29/+tu3du7fW687Kygo5zxNPPGF33313wOlJSUl27Ngx69Wrlx09etTmz59vc+fONTOz/Px8GzJkiPXr18/uvPNOy87ODjq+olWrVtnUqVPNzGzUqFE2fPhwO3v2rD344IO2aNGicvPm5uZaXFycbdiwwYqKiiwjI8NmzZplxcXF9tprr9n1119vZmabNm2ySZMm2dmzZ83M7M4777Tnn3/ezMwOHz5sZmYnT5601NRUy8vLs5dfftluv/32kvw6evRopXReddVVtmfPnqD5mJubaz169LBjx46ZmVnv3r1t6NChlpGRYU8//XTJfFOmTLG1a9daVlaWXXPNNQHXF2j5muZHoP0OJC8vz+644w7r27ev/epXvwq6z9FevoKVBb/6KFdmVlKuyuZZqHKVm5trqampVU6bNWuWPfnkkyXfQ5UXv1DlLxrKVVnVKWORAKy1KIg9DWU4nxhp5sWKG264wTp16mTx8fHWpUsXmzFjhuXm5oZcNlQZivUYeN1119XqXFVWQ42B/mNfH+eqaBSs7Md6bM7KygpbeY/22Pz6669X2u9AwlHeg8VHNeMEJk+ezN69e0u+/8///A+fffYZOTk5tGjRol7ScNddd/HBBx+QkJDAJ598AkDr1q257bbbWLhwIc2bNy+Zt2XLluTk5LBy5UqysrL4zne+wyOPPMLMmTMDji8rMzOTnJwcjh8/TmJiIhkZGaxdu5aVK1eWXO0sq0+fPqSlpQGQmprKFVdcgXOOtLS0kucdly9fTk5ODsOHDwfg1KlTJVcvFi5cWNIefdeuXWzbto20tDTuu+8+fvazn9GtWzfGjh1babtvvfVW0DwrKChgypQpLFiwgNatWwPwwQcf0K1bNw4ePMiECRMYOHAgx48fp1OnTmRmZpKdnR10nVUtP2bMmBrnR6D9bt++fZXbbd++PYsWLQqatvNRn+UrWFkoK9zlatKkSYwePbrSdkOVq0DOnj3LkiVLePjhh0vGVae8+K/khSp/DbFcSez67//+b2655ZZyV/737dvH888/zxtvvMFHH33EgAED6mx7sRYDv/nmG4YOHQqE71ylGNjwxVps7tmzZ6ONza+88gr/9m//Vm6/o6W8qxkn3i30nTt3snv3bkaOHAnAli1b+MMf/hC2baamprJu3bqS70899RTLly/n0KFD5ea7++67efbZZzlx4kS58XFxcYwdO5Z58+bxu9/9jr/97W9Bx5fVtGlT+vTpw3PPPcfll1/O6NGjycrK4ssvvyQ5ObnS/P6mAQBNmjQp+d6kSRMKCwsB7w7xjBkzWL9+PevXr2fr1q08+OCDZGdns2zZMlatWsU//vEPhg4dyunTp+nfvz/r1q0jLS2NZ599ln//93+vUf6dO3eOKVOmMH36dG688caS8d26dQOgU6dOTJ48mTVr1vDhhx+yZMkSevfuzc0338yKFSu49dZbq1xvVcvXJj8C7Xd9iWT5ClQWKgp3ufr5z39e43IVzNtvv01GRgadO3cuGVed8lLd8tcQypU0DidPnuTOO++kqKiIjIwMtmzZwpkzZ8jKyiIhIYFvvvmGn/zkJ+e1jViPgS+88EJYz1WKgQ1TrMfm9evXN9rYnJOTE7XlXZU9YN68efTs2ZNu3boxd+7ckvHvvvtu2LY5fvx4Tp8+ze9///uScSdPnqw0X7t27bjpppvK9dqzdetWtm3bVvJ9/fr19OrVK+D4qowePZpHH32UMWPGMHr0aBYtWsTQoUNxztVqf6644gpefvllDh48CHhXNXfu3MmxY8do27YtLVq0YMuWLaxevRqAvXv30qJFC2699VZuvvnmcie/UMyM2bNnk5yczL333lsy/sSJE+Tn55d8fueddxg0aBAPP/wwu3fvZseOHbz00kuMHz+eF198sdJ6Ay1fG4H2u75EsnwFKgu1cT7l6ic/+UmNylUof/3rX5k2bVrJ9+qWl+qWv+qIdLmSxuHDDz/km2++AWDdunUMHDiQxMRExo0bV9Lxw/nGx1iPgcePHw/buUoxsOGK9dhcUFDQaGNzq1atora8q7IH9OzZs8rPeXl5Ydumc47XXnuN9957jz59+jBixAhmzJjBr3/960rz3nfffeXSUlBQwIwZM0hJSWHw4MFs2rSJBx98MOD4qowePZp9+/Zx2WWX0blzZ5o1a1blbfXqSklJ4Ze//CVXXnklgwcPZsKECezbt4+JEydSWFhIcnIy999/P5deeing9VDkf7D3+eef5+c//zkAV199dUmT2rKfy/rwww/505/+xIoVK0q63H3rrbc4cOAAo0aNYsiQIYwYMYJrrrmGiRMnhky7fzu1Xb4qgfa7vkSyfAUqC7VxPuVq3rx5JeXq/vvvD1muAKZNm8Zll13G1q1b6d69e0mgPXHiBO+++265K+ihykuw7dRWpMuVNA7+H3DBnD59utJdh5qI9Rj44x//uFbnKsXA2BbrsXnEiBF1Xt6hYcTmoqKi6C3vgR7mawhDXXXQ8s4775SMf+edd0rGT5o0qVbrjtbODaKV8qtmlF81pzyrmWjNL9RBS73EyLJxsGynCmUVFxcHXUe0lqH60pj3vzHvu1nj3n/te+QEi4/qoAWvGWdycjLOOebNm1cyfsKECRFMlYiISP27/PLLadu2LUeOHOGFF15g3LhxXHfddTjn2LhxIy+//DJnz54t9zJvERGJTqrsAbm5ufTo0aPcuIEDB573+2hEREQamqSkJJ566iluvfVWzp49W+ndcwAzZsyIQMpERKSm9Mwe8Oqrr3LLLbdwwQUX0LJlS6ZOncqKFSvq7bULIiIi0WTatGl88MEHTJkyhc6dOxMfH0/Hjh0ZNmwYP/vZz7jvvvsinUQREamGRntn77nnnuO5554r+f7nP/85cokRERGJMpdddhkvv/xypJMhIiLnQXf2REREREREYlDYKnvOuWbOuTXOuX845z53zs3zjX/OOZfrnFvvG9J9451zbqFz7kvn3AbnXEa40iYiIiIiIhLrwtmM8www3swKnHNNgQ+cc2/7pv3EzCq2DbkK6OcbLgF+7/srIiIiIiIiNRS2O3u+1z4U+L429Q0WZJHrgRd8y60G2jjnuoQrfSIiIiIiIrHMee/hC9PKnYsDcoCLgafM7GfOueeAy/Du/C0H7jezM865pcAjZvaBb9nlwM/MbG2Fdc4B5gB07tw586WXXgpb+muroKCAli1bRjoZDYbyy7N3715efPFFTpw4Ue59jxUpv2pOeVZZsPIWrfk1bty4HDMbFul0RLNoiZHRWobqS2Pe/9rue3VjYLTTsde+n6/a/C8EjY+B3rZelwPQBsgCBgFdAAckAs8Dv/DNsxQYVWaZ5cCwYOvNzMysm9fO17GsrKxqzbd//36bNm2a9enTxzIyMuzSSy+1V155xczMALv33ntL5p0/f77NnTu35Psvf/lLS0lJsbS0NBsyZIitXr066PhoMXfuXJs/f365cRXzKykpKeR6vv76axs7dqwlJydbSkqKLViwoGRar169bNCgQTZkyBCrWEYKCwstPT3drrnmmoDrDrZ8fZgyZUrQ6SpflVVVrsrKyso673I1a9Ys69ixo6WmppaMO3XqlA0fPtwGDx5sKSkp9otf/KLSOrds2WJDhgwpGVq1amWPP/64mZn99re/tZSUFEtNTbWbb77ZTp06VYO9rhtVlbfqlrH6Bqy1eohZsTJEMkZWpwzF8jkq0P6HOleZNfwYeL7nj1AxMNqF2v/GVO7rqrybVR2DzcwWLFhgqamplpKSUhJbqxOby6r4fxHs/yuQcMTNmvwvBIuP9fLqBTM76pzLAiaa2aO+0Wecc/8J/Nj3fQ9Q9s3m3X3jYpKZccMNNzBjxgz+8pe/ALBz506WLFkCQGJiIq+88goPPPAAHTp0KLfsqlWrWLp0KevWrSMxMZG8vDzOnj0bcHwsio+P57HHHiMjI4P8/HwyMzOZMGECKSkpAGRlZVXKN4AnnniC5ORkjh8/HnT9gZavC5999hkPPPBAuXF//OMf6dSpU51tQ+WrdoKVq5kzZ/LDH/6Q2267rWT+xMREVqxYQcuWLTl37hyjRo3iqquu4tJLLy2ZZ8CAAaxfvx6AoqIiunXrxuTJk9mzZw8LFy5k06ZNNG/enJtuuomXXnqJmTNn1uk+1Ud5E6kpnaPOj2Jgw6RyX3tVxeCNGzfyzDPPsGbNGhISEpg4cSKTJk3ioosuChmby6r4fxHq/6uu1Nf/Qjh74+zonGvj+9wcmABs8T+H55xzwA3ARt8iS4DbfL1yXgocM7N94UpfpK1YsYKEhAR+8IMflIzr1asXP/rRjwCvoM2ZM4fHH3+80rL79u2jQ4cOJCYmAtChQwe6du0acHxF8+fPZ+HChQDcc889jB8/viRN06dPLzfvjh07GDhwIDNnzqR///5Mnz6dZcuWMXLkSPr168eaNWtK5v3tb3/LoEGDGDRoEAsWLCgZ/9BDD9G/f39GjRrF1q1bS8a/+OKLjBgxgttvv5077riDoqKiaudfly5dyMjwOmxt1aoVycnJ7NkT/NrA7t27efPNN7n99turvZ2q1CRPbrjhBjIzM0lNTWXx4sUApKWlsXTp0nJDXf9jR7J8QemxTU9Pr/LY1ke5CrTtYIKVqzFjxtCuXbty8zvnSpptnDt3jnPnzuGd2qq2fPlyLrroInr16gVAYWEhp06dorCwkJMnT1aZnw2hvInUVKzHwLLvJ6zvc1Ug9RUDN2/eXDKvzknlKTbXrrxD1TF48+bNXHLJJbRo0YL4+Hi+9a1v8corr9QoNlf1f1Hd/6+y+fXd7343euNzoFt+5zsAg4FPgQ14FTp/c80VwGe+cS8CLX3jHfAU8JVvetAmnNbAm3E+8cQTdvfddwecnpSUZMeOHbNevXrZ0aNHy93Kz8/PtyFDhli/fv3szjvvtOzs7KDjK1q1apVNnTrVzMxGjRplw4cPt7Nnz9qDDz5oixYtKjdvbm6uxcXF2YYNG6yoqMgyMjJs1qxZVlxcbK+99ppdf/31Zma2du1aGzRokBUUFFh+fr6lpKTYunXrSsafOHHCjh07ZhdddJHNnz/fNm3aZJMmTbKzZ89aVlaW3Xnnnfb888+X7LvfVVddZXv27Amal7m5udajRw87duyYmZn17t3bhg4dahkZGfb000+XzDdlyhRbu3atZWVlBW3CEmj5muaJmdnhw4fNzOzkyZOWmppqeXl5Abebl5dnd9xxh/Xt29d+9atfBZwv2stX2WNrZuWOrV99lKuy267YjLM25co/rmITksLCQhsyZIglJSXZT3/606DrnDVrlj355JMl3xcsWGBJSUnWoUMHu+WWWwKmo77Lm5pxxsYQzc04Yz0G9urVq1bnKv+++zXEGDhy5MiSecMRA6NdsLIf67F50aJFYS3vFWPwpk2brF+/fpaXl2cnTpywSy+91H74wx+aWfVjc6j/i6p+C1SVX8uXL6/334NlBYuPYWvGaWYbgKFVjB8fYH4D7gpXeqLdXXfdxQcffEBCQgKffPIJAK1bt+a2225j4cKFNG/evGTeli1bkpOTw8qVK8nKyuI73/kOjzzyCDNnzgw4vqzMzExycnI4fvw4iYmJZGRksHbtWlauXFlytbOsPn36kJaWBkBqaipXXHEFzjnS0tLYsWMHAB988AGTJ08mKSkJgBtvvJGVK1dSXFzM5MmTadGiBQDXXXcd4N3hyMnJYfjw4RQUFBAXF1fl1Yy33noraL4VFBQwZcoUFixYQOvWrUvS0q1bNw4ePMiECRMYOHAgx48fp1OnTmRmZpKdnR10nVUtP2bMmBrnCcDChQt59dVXAdi1axfbtm2jffv2VW63ffv2LFq0KGjaaqs+y1fZYwtw6tSpKo9tuMtV2W337Nmz3LZrU64CiYuLY/369Rw9epTJkyezceNGBg0aVGm+s2fPsmTJEh5++GEAjhw5wuuvv05ubi5t2rTh29/+Ni+++CK33nprrfIKoqe8idRUrMXAMWPG1OpcVVFDjIH79+8vmU/npOBiLTZ/8cUXYS3vFSUnJ/Ozn/2MK6+8kqSkJNLT04mLiwOqF5v9d9IC/V9U57eAP7+ys7OjNj7XyzN7Ullqaip/+9vfSr4/9dRT5OXlMWxY+Y507r77bjIyMpg1a1a58XFxcYwdO5axY8eSlpbG888/z8yZMwOOL6tp06b06dOH5557jssvv5zBgweTlZXFl19+SXJycqW0+psGADRp0qTke5MmTSgsLKzV/psZM2bM4OGHHyY7O5uxY8fWeB3nzp1jypQpTJ8+nRtvvLFkfLdu3QDo1KkTkydPZs2aNRw+fJglS5bw1ltvcfr0aY4fP86tt97Kiy++WGm9VS1fMdBVJ0+ys7NZtmwZq1atokWLFowdO5bTp0/XeD9rI5Llq+yxDSbc5aqsUD9uygpUrkJp06YN48aN4+9//3uVlb23336bjIwMOnfuDMCyZcvo06cPHTt2BLxg+dFHH1VZ2Yv28iZSU4qB1TtPBhOtMdDfPE/npMoUm2tf3gOZPXs2s2fPBuBf//Vf6d69e7npwWLzhx9+GPD/orq/BRpCfA7bM3sS3Pjx4zl9+jS///3vS8adPHmy0nzt2rXjpptu4tlnny0Zt3XrVrZt21byff369fTq1Svg+KqMHj2aRx99lDFjxjB69GgWLVrE0KFDgz5vFMzo0aN57bXXOHnyJCdOnODVV19l9OjRjBkzhtdee41Tp06Rn5/PG2+8AcAVV1zByy+/zMGDBwH45ptv2LlzZ7W3Z2bMnj2b5ORk7r333pLxJ06cID8/v+TzO++8w6BBg3j44YfZvXs3O3bs4KWXXmL8+PFVBrlAy9fGsWPHaNu2LS1atGDLli2sXr26VuupjUiWr/M9tmVFS7kK5NChQxw9ehTwrlS+++67DBw4sMp5//rXvzJt2rSS7z179mT16tWcPHkSM2P58uVV/tCsrkiWN5GaivUYuHLlSsVAnZMqifXYPHjw4LCU92D86/z666955ZVXuOWWW6odmwP9X9T0t0Aokf5f0J29CHHO8dprr3HPPffwm9/8ho4dO5KUlMSvf/3rSvPed999/O53vyv5XlBQwI9+9COOHj1KfHw8F198MYsXL2bnzp1Vjq/K6NGjeeihh7jssstISkqiWbNmjB49utb7k5GRwcyZMxkxYgQAt99+O0OHeq14v/Od7zBkyBA6depUcgs/JSWFX/7yl1x55ZXk5+fTpk0bnnrqqUonqKuvvpo//OEPlR42/vDDD/nTn/5EWloa6enpAPzqV79i4MCBTJ48GfA6v7jllluYOHFiyPT7t3P69OlaLV+ViRMnsmjRIpKTkxkwYEDAXqDCIZLlq+yxLS4upmnTplUe2+o4n3JVdtsV1bRcXX311UybNo3s7Gzy8vLo3r078+bNY/jw4cyYMYOioiKKi4u56aabmDRpUqXtXHDBBbz77rs8/fTTJdMuueQSpk6dSkZGBvHx8QwdOpQ5c+bUOI/8IlneRGoq1mPgNddcU6tzlWJgbIv12Hzs2LGwlHegyhg8e/ZspkyZwuHDh0vW2aZNGzZs2FCt2ByoI5tgvwVqI9L/C2F9qXq4DRs2zNauXRt6xnpW22aJjZXyq2aUXzWnPKuZaM0v55xeql4DkYyR0VqG6ktj3v/GvO/QuPdf+z42YtsPFh/VjFNERERERCQGqbInIiIiIiISg1TZExERERERiUGq7ImIiIiIiMQgVfZERERERERikCp7IiIiIiIiMUiVPRERERERkRikyp6IiIiIiEgMUmVPpAHYvn07s2fPZurUqZFOisQIlSkRaSh0vpJYU59lWpW9CPre975Hp06dGDRoUMm4HTt2lPsebS6//HIAFi5cSHJyMtOnT+fo0aP8x3/8R72mY9euXYwbN46UlBRSU1N54oknyk3v3bs3aWlppKenM2zYsHLTioqKGDp0KJMmTapy3adPn2bEiBEMGTKE1NRU5s6dW6Plw6Fv3748++yzNVpG5atmQpWpv//97wwYMICLL76YRx55pGT8448/TmpqKoMGDWLatGmcPn260roDlcdQZS2calOmROqSzlG1V5sYGGqZUPNs3bqV9PT0kqF169YsWLAgrPvpF0vnK5X7mqsqz/yqisHVLavVid/hUq9l2swa7JCZmWnRKCsrq1rzvffee5aTk2Opqakl43Jzc8t9jwbFxcVWVFRUbtyAAQNs165dZnb+aa5ufpW1d+9ey8nJMTOz48ePW79+/ezzzz8vmd6rVy87dOhQlcs+9thjNm3aNLvmmmuqnF5cXGz5+flmZnb27FkbMWKErVq1qtrLn68NGzbYNddcU244cOCAmZlNmTJF5asWqpNnwcpUYWGh9e3b17766is7c+aMDR482D7//HPbvXu39e7d206ePGlmZt/+9rftP//zPyutO1B5DFXW6kKw8mTmlamKavM/WR+AtRYFsaehDJGMkdUpQ7F8jgr3/1BtYmCoZao7j5l3TuzcubPt2LGj0rTz2ffanK+iTaj9V7mvuaryzMyqFYMDldXqxu/qCrTv9VWmg8VH3dmLoDFjxtCuXbuA07dv387QoUP55JNP2LFjBwMHDmTmzJn079+f6dOns2zZMkaOHEm/fv1Ys2ZNpeUrXil69NFHefDBB0vWNX36dJKTk5k6dSonT56stOyAAQO47bbbGDRoELt27QKgZcuW/OAHP2D79u1cddVVPP7449x///189dVXpKen85Of/KSOcie4Ll26kJGRAUCrVq1ITk5mz549IZfbvXs3b775JrfffnvAeZxztGzZEoBz585x7tw5nHPVXr66x+qGG24gMzOT1NRUFi9eXLJ8WloaS5cuLTd06tQpdKZUoPJVM8HK1Jo1a7j44ovp27cvCQkJ3Hzzzbz++usAFBYWcurUKQoLCzl58iRdu3at9jaDlTW/mhybqspUXZUnkbqmc1Tt1SYGVmeZ6q53+fLlXHTRRfTq1avc+B07dnDbbbfpfBWEyn3NBcuzUDE4UFmtzrIQIzE4UC2wIQwN/c6eWeUrI/7vW7ZssfT0dFu/fn3J+Li4ONuwYYMVFRVZRkaGzZo1y4qLi+21116z66+/PuS658+fb3PnzrXc3FwD7IMPPjAzs1mzZtn8+fMrLeucq3SXISkpyczKXzWs6urOVVddZXv27KlWHpzvlaDc3Fzr0aOHHTt2rGRc7969bejQoZaRkWFPP/10yfgpU6bY2rVrLSsrK+iducLCQhsyZIglJSXZT3/60xotX91jdfjwYTMzO3nypKWmplpeXl7A9OTl5dkdd9xhffv2tdtvv71a+eJPS2MvX2Y1L2MVy9T//M//2OzZs0umv/DCC3bXXXeZmdn/z959x0d13fn/f31UAdGb6B2D6AiMscG2sEOCYzuuydrB67JOcPJN8k3b3Tj57oawm+JdJ3HJeuPgzSZOnMS7v8QFEzsxTdhgipGMaaYXA6KbItElnd8fZ0YSoCkSGk17Px+P+9DMvXNnzj33aM587j3lySefdHl5ea5z587us5/9bL3vF6o8Ohe6rNVNS7TnprFl6oc//OEF23RnLzWWRL+z51zqfkddddVVDfqOuhwNqQPD7dOQ1zz00EPuZz/7Wb37ZGRkNOv3VaKJpuyr3DdcqLufkergUGU1mn2DnxvNOVi0aFFcy3S4+lF39hLQoUOHuO222/jd737H6NGja9b379+fkSNHkpGRwfDhw7nxxhsxM0aOHMnOnTsb9Bm9e/dm0qRJANx3330sWbLkktf07duXiRMnNuoYXn/99Qbd4WisiooK7rrrLp588knatm1bs37JkiWUlpbyxhtv8Mwzz/DWW2/VXE0ZN25cxPfNzMxk9erV7Nmzh5UrV7Ju3boG7R/NuXr66acZPXo0EydOZPfu3WzZsiXk+3Xq1Ilnn32Wbdu2MX369MgZE4bKV3ihylR9jh49yquvvsqOHTsoKyvj5MmTvPDCC5e8rr7yGFRfWbtYtOemsWXq29/+dhQ5I9I8UuE76rHHHku4OjDSPtG8L8C5c+eYM2cOn/70p+vdt3v37vq+agSV+4aLVAeHK6vR1t+Q/HWwgr0E1K5dO/r06XPJP2Fubm7N44yMjJrnGRkZVFZWXvI+WVlZVFdX1zyv2/H04qZiFz8HyMvLa9wBNJPz589z1113MX36dO68884LtvXs2ROArl27cscdd7By5UqWLl3KnDlz6NevH/fccw8LFy7kvvvuC/sZ7du3Z8qUKfzlL39p0P6RzlVxcTHz589n2bJlvP/++4wdO7bZOgarfIUWqkz17NmzpjkL+Oa8PXv2ZP78+fTv358uXbqQnZ3NnXfeyTvvvHPJ+9ZXHi9Wt6xdLJpzE88yJdKU9B0VnYbWgZH2ieZ9Ad544w0KCwvJz8+vd//s7Oyax/q+ip7KfcNFqoPDldVo62+I7hysXr06Ycu0gr0ElJOTw8svv8xvfvMbfv/73zf6ffLz8zl48CBHjhzh7NmzzJ07t2bbhx9+yLJlywD4/e9/z+TJkxv9OW3atKG8vLzR+zeGc46HH36YgoICvvGNb1yw7eTJkzXpOXnyJG+++SYjRozgRz/6EXv27GHnzp28+OKL3HDDDfVexTl06BDHjh0D4PTp08ybN4+hQ4dGvX80jh8/TocOHWjVqhUbN25k+fLljXqfxlD5ql+4MnXllVeyZcsWduzYwblz53jxxRf51Kc+RZ8+fVi+fDmnTp3COceCBQsoKCi4YN9Q5RFCl7XGiGeZEmlK+o6KrDF1YLh9onnfoD/84Q/ce++9l5V+fV9dSuW+4SLVweHKajT1d0NUVFQkbJlWsBdH9957L1dffTWbNm2iV69eFwzBmpeXx9y5c3niiSeYM2dOo94/Ozub7373u0yYMIGpU6de8CNyyJAhPPPMMxQUFHD06FG++MUvNvo4OnXqxKRJkxgxYkRNJ91PfvKTlJWVNfo9I1m6dCm//e1vWbhwYc3Quq+//joABw4cYPLkyYwePZoJEyZw8803M23atLDvVze9+/btY8qUKYwaNYorr7ySqVOnNvk0C9OmTaOyspKCggIeffTRRjeZCEflq2HClamsrCz+4z/+g0984hMUFBTwmc98huHDh3PVVVdx9913U1hYyMiRI6murmbGjBkXpDFceWzKstYcZUqkKaXyd9Sjjz6acHVguH2C31fhXgM+eJw3b17Iu4LRSufvK5X7hguVZ+Hq4FBlNVjWw+3bGBMmTEjcMh2qM9/lLkALYCXwPrAemBVY3x9YAWwF/gfICazPDTzfGtjeL9JnpMIALfGQaEP8Jnp+JZpEz69EK1/OJX6eJZpEzS80QEvKDdASD83xHZXIxx9r6XzsziXu8avcx1a8jz1c/RjLO3tngRucc6OBMcA0M5sI/BvwhHNuEHAUeDjw+oeBo4H1TwReJyIiIiIiIo0Qs2AvEGhWBJ5mBxYH3AD8MbD+eeD2wOPbAs8JbL/R6us5KpetX79+9Y74J9IUVL5EJJHpO0rSkcp9+jJ/5y9Gb26WCZQAg4BngMeB5YG7d5hZb+AN59wIM1sHTHPO7Qls2wZc5Zw7fNF7zgBmAOTn54978cUXY5b+xqqoqKiZKFkiU341jPKr4ZRnDZOo+TVlypQS59z4eKcjkSVKHZmoZai5pPPxp/OxQ3ofv449fscern7MiuUHO+eqgDFm1h54GWjcMHMXvudsYDbA+PHjXVFR0eW+ZZMrLi4mEdOVqJRfDaP8ajjlWcMov5JXotSR6V6G0vn40/nYIb2PX8deFO9k1KtZRuN0zh0DFgFXA+3NLBhk9gL2Bh7vBXoDBLa3A440R/pERERERERSTcyCPTPrErijh5m1BKYCH+CDvrsDL3sAeDXweE7gOYHtC10s25iKiIiIiIiksFg24+wOPB/ot5cB/K9zbq6ZbQBeNLPvA+8BwQlGfgn81sy2Ah8B98QwbSIiIiIiIiktZsGec24NMLae9duBCfWsPwN8OlbpERERERERSSfN0mdPREREREREmpeCPRERERERkRSkYE9ERERERCQFKdgTERERERFJQQr2REREREREUpCCPRERERERkRSkYE9ERERERCQFKdgTERERERFJQQr2REREREREUpCCPRERERERkRSkYE9ERERERCQFKdgTERERERFJQQr2REREREREUpCCPRERERERkRSUFe8EiIiISApZt45Jhw/Dq6+CWe2SkXHh88zM2iUr68K/wcc5OZCd7f8Gl+Bzs3gfqYhIwlOwJyIiIk2nspJs5+Dcudh+TlYWtGhx6ZKbW/u4ZUv/V4GhiKQpBXsiIiLSdEaOZMlHHzF50iRwDqqr/d+6S3W1X6qqoLLywr/Bx5WVPmA8f97/rfv4/Hm/vaLCL+GYQatWtUte3qXPM9SrRURSk4I9ERERaTqZmVRmZPg7bLHinA/4zpzxy9mztY/rLqdO+eDw5Em/1MfMB3ytW0ObNhf+bdVKdwVFJKkp2BMREZHkYlbbh69t2/Cvraz0QV99y8mT/m/wDuH+/Rfum5HhA7927fzntGvnFwWBIpIkFOyJiIhI6srK8oFaqKCwqqo22Csvv/DvmTNw/Lhf6nvPYPDXvj106ODXi4gkEH0rNbXNmxlUXg6rV1846tjFo5HVN/pY3b/Z2X5RPwIREZHYycysDdoudv48nDjhl2DQd+KEDwI/+sgvdbVpAx060OvUKTh0yAeB2dnNchgiIvWJWbBnZr2B3wD5gANmO+eeMrPvAZ8HDgVe+h3n3OuBfb4NPAxUAf/XOffXWKUvVmb94Q8AzDxzpmneMDj09MXDT9cdbazuokpFRESkaWRnQ6dOfqnr7NnaAPDYMTh61D8uL4fycgYBFBf717ZpAx07QufO/n3atlUTUBFpNlEFe2Y2HrgW6AGcBtYB85xzR8PsVgl80zlXamZtgBIzmxfY9oRz7scXfcYw4B5geOBz5pvZFc65qgYdUaIYPfrSkcecY9af/gTAzFtvvXDUsYv/BkccC45IdupUdJ+bmVk73PTFo44FH2dmxvDARUREUlxuLnTp4pegqiof8B09StmGDfRo0eKCAJBdu/zrsrJqA8jOnX0gqAu1IhIjYYM9M3sI+AqwAygBNgEtgMnAt8xsHfDPzrkPL97XObcP2Bd4XG5mHwA9w3zcbcCLzrmzwA4z2wpMAJY1+KgSwRVX1L8+EOxRWBj5PYKjjdUddjq4hBp5rKoq/Khj4CupvLwLRx0LPlZ/AxERkYbLzISOHZn1s58BMHPmzNoA8MgRZv3+9379sGFw4IBfgtq1g65dawPInJx4HIGIpKBIv+xbAZOcc6fr22hmY4DBwCXB3kWv6weMBVYAk4Avm9n9wCr83b+j+EBweZ3d9lBPcGhmM4AZAPn5+RQHm0kkmEjpatJ0Z2T4O3YtW5LpHDnV1eRWV9OiupoWVVW0qKryzwN/M86e9cHixX0NgLMZGZzKzOR0ZiYns7KoCPytjGHfwYqKioQ9j4lI+dVwyrOGUX4lr0SpI1WGQtfzyzp2pG1lJW3Pn6fd+fO0rqwkI9gfcMsWHFCRlcWx7OyapSqJ+u+n+7lP5+PXsRfHOxn1ChvsOeeeibB9daQPMLPWwJ+ArznnTpjZz4F/xffj+1fgJ8DfRZtg59xsYDbA+PHjXVFRUbS7Novy8nL27dtHqHSVl5cDhNwec87B6dP+zl9wxLHgqGMVFeQGAsUO589fuF+LFrUd2INL27ZN0iS0uLg4fvmRhJRfDac8axjlV/JKlDoynctQqN8Bwfr/6htvvHCHqio4csQP6HLwIPbRR7SprKRNZSW9TweutXfoAPn50K2bb/6ZwMFfOp97SO/j17EXxTsZ9Yq2z15/fHPOfnX3cc59KsJ+2fhA73fOuZcC+xyos/05YG7g6V6gd53dewXWJZVbb701bGR/6623Nl9i6mNW24evbl8D8IFgMAi8ePSxYDPRus1OzGqHm+7Qwfc7aNs2oSshERGRWAr1OyBk/Z+Z6Ztwdu0Kw4f7fvp1gj8++sgPAHP0KGzc6LtbdO3qA79u3Xy3DBGREKLtoPUK8EvgNaA6mh3MzAL7fOCc+2md9d0D/fkA7sAP9gIwB/i9mf0UP0DLYGBllOmTpmDm++21bu0rkKBgEBgM/IJLeXltBRSUkVEbAAZHH8vL08hjIiIi0cjK8nfx8vP988pKOHzYT/h+4IC/EFtW5hfwfe7z86F7d38RV4OwiUgd0QZ7Z5xzTzfwvScBfwusNbPVgXXfAe4N9PVzwE7gEQDn3Hoz+19gA34kzy8l40icZWVlNU01Qm0H6NGjR3Ml6fLVDQJ71ulGef68H3K67lXHiorauYe2bfOvy82tHXK6c2cfCOrun4iIpKBQvwMaXf9nZdXexQM/Ovf+/bXBX7A7xtatta/t0cMHfxroRSTtRRvsPWVmM4E3gbPBlc650lA7OOeWAPXdznk9zD4/AH4QZZoS0nPPPQeEbq4R3D5z5sxmS1PMZGdfOvT0uXO1gd+RI/5q5NmzsHevX8AHesG7fl27kuFcfNIvIiLSxEL9Dmiy+r9VKxgwwC/V1f7i6v79sG+fvwC7Z49fzHw926OHX1q3vrzPFZGkFG2wNxJ/l+4GaptxusBzkVo5ORc2P3HO3+07fLg2+Csv938PH4aNG5kMsGiR36drVx8I6s6fiIhIeBkZPqDr3BlGjPBdLvbt8xdXDx2qXd5/3/ep79kTevfWxO4iaSTaYO/TwADn3LlYJkZSkFntPH79+/t1Z8/Wdj4/dAg7erQ2+Fu/3vc3CNz1Iz/f9wFUpSQiIhJeXh4MGuSX8+d94FdW5u/8BQde++ADXyf36qXATyQNRBvsrQPaAwdjlxRJG7m5tc1KgKULFzJ5yBA/6tjBg74yCk44u3atn/Yh2F8hP199EERERCLJzoY+ffxSXe0vsAabeJaX+6BPgZ9Iyos22GsPbDSzd7mwz17YqRdEolGZkeGblgQHfzlzpjbw27/fzwu4c6dfzPxAL8HgT3f9REREwsvIqO1iMXasD/x27/bNPS8O/Pr0gb59NaWDSIqINthLgdFEJGm0aFF7NdI5f6dv3z4f+AWbex4+DOvW+df26OEDxa5d1ddPREQknLqBX2HhpYHf+vV+6dzZB329eqlFjUgSCxvsmZk5b3Gk1zR90kTwd+3atfPL0KG+D8KBA7XDTp8+Ddu3+yUryw813bOnv+uXnR3v1IuIiCSuiwO/Awfgww994Be8sPree75u7dvX162ax08kqUS6s7fIzP4EvOqc+zC40sxygMnAA8Ai4NcxS2GS+fznP09JSUnY7XIZsrP9VcZevfxdv2PHfOfzvXv9RO+7d/slI8Pf6evZ09/5a9Ei3ikXEZE0EOp3QMLX/xkZPqjr3t1fWN27F3bt8l0qgtMnZWf7vn0DBqgbhUiSiBTsTQP+DviDmfUHjgEtgQz8nHtPOufei2kKk0yPHj3YvHlz2O3SRMz8BO0dOsDw4X6Kh2Dgd/hw7d2/0lIf+PXu7YM/NUcREZEYCfU7IKnq/+xs6NfPL6dP+7t9u3b5i6rB1jTt2vmgr08f1asiCSxssOecOwP8J/CfZpYNdAZOO+eONUPaRBqmdWu44gq/nDnj+/nt2VM7sueBA1BS4pur9Onj7/ipqaeIiEhoLVvCkCF+OXbMD5YWDPzee8/P4derl59eqUuXeKdWRC4S7QAtOOfOA/timJaU8Nprr7Fv3z6KiopCbge49dZbmzFVaahFC1/x9O/v5/Xbu9c37wyO8Ll/v2+y0q1bbeCnfggiInKZQv0OSIn6v317GDMGRo70LWl27Kjt5/fhh5CXRx/n/N3Ali3jnVoRoQHBnkSntLQ0qu1J/WWfbHJzfVOTAQP8Hb89e3zgd/iwr6zKymr7IfTt66d2UD8EERFphFC/A1Kq/s/M9HVm795w8qS/27djB5w8yQCAP//Zd5sYNMiP6qk6VSRuFOxJemnRwlc+gwb5K4+7d/urkUeP1vZDyMvz/RQ0z5CIiEh4eXm+3/ywYXDgAIdWrKDL+fO1E7i3bQsDB/o6VV0nRJqdgj1JXy1b1vbxO37c90HYtctfpaw7z1C/fv7qZZb+XUREROplBt26sb5dO4omTPB3+rZv93PlvvcerF3rA76BA/3gLiLSLKL69WpmdwL/BnQFLLA451zbGKZNpPm0awejRvl+CAcO+KCv7jxDq1f7vn0DBvjRP0VERKR+rVr5u30FBb4u3brV16XbtvmlSxcYPNj3l1cTT5GYivZWxb8DtzrnPohlYkTiLnBlkm7d/DxDe/b4q5NHjtQ282zfvna4aTVJERERqV9GRm3fvuPHfaC3axccOuSXvDwf9PXvr9YzIjES7X/WAQV6knays2tH9Dxxwgd6u3b5oadLS/1w08HJZTt21NVJERGRUNq1g8JC34Jm507YssV3m1i92nebGDDA96dv1SreKRVJKWGDvUDzTYBVZvY/wCvA2eB259xLsUtacurevTvl5eVht0sSatu2drjpvXuZ/f/9f1BZyYyqKl9ptWvnK6k+fXR1UkQkjYX6HaD6PyA729/NGzTIN/HcssU38dy0CTZv9nP2XXGFv4gqIpct0q/SuuMDnwI+Xue5AxTsXWTGjBkUFxeH3S5JLDMT+vRhxje/CeXlvonnjh2+eUpJCaxZ4+8EDhqkkTxFRNJQqN8Bqv8vYuYDu1694KOPfKAXnBpp924/QNrQob5bhVrOiDRa2GDPOfcQgJlNcs4trbvNzCbFMmEiCa9NGz+oy/DhvoLaurW2wtq82Xc8HzQIunZVRSUiIhJKx44wcSKcOuXr0u3b/d2+JUt8y5mhQ31QmJER75SKJJ1o25v9DCiMYp1I+snM9MNJ9+3rg72tW/1VyeCE7W3a+KCvXz818RQREQmlVSt/EbWgwAd8mzf7ljMrVsC6dTBkiK9LMzPjnVKRpBGpz97VwDVAFzP7Rp1NbQH9p9Vj1qxZABQVFYXdPnPmzOZKksRAyPPYsSNMmMCsN97w2wsLfXPP997zFdXAgT7wa9myuZMsIiLNINTvANX/DZCd7QO7QYP8wGibNkFFhR8cbf1636dv4ECNiC0ShUj3w3OA1vigsE2d5QRwd7gdzay3mS0ysw1mtt7MvhpY39HM5pnZlsDfDoH1ZmZPm9lWM1tjZrprKMnv5pt905ROnfxUDhs3wuuvw7vv+quVIiIiUr/MTD9K57Rpvi5t3x7OnvUTtM+d6y+inj0b8W1E0lmkPnuLgcVm9mvn3K4Gvncl8E3nXKmZtQFKzGwe8CCwwDn3mJk9CjwKfAu4CRgcWK4Cfh74K5K86s4xdPiwb5Kyd68fwXPnTt/xfMgQP8Gs+vWJiIhcyszXo716wYED/sLpoUPwwQd+NM9Bg/zdvtzceKdUJOFEasb5Gn7UTayeH6LOuU+F2tc5tw/YF3hcbmYfAD2B24CiwMueB4rxwd5twG+ccw5Ybmbtzax74H1Ekl/nzn6pqPBB386dsH+/X9q390GfOqCLiIjUz8xfJO3WzV9A3bChNvjbulVBn0g9Io0W8ePA3zuBbsALgef3Agei/RAz6weMBVYA+XUCuP1AfuBxT2B3nd32BNZdEOyZ2QxgBkB+fn7YaQ7iKVK6EjXd8VBRUZG0+XE55zm7fXt6nD5Nz9OnyTl2DFas4PS77/Jhq1bsb9ECF+JOXzLnV7wozxpG+ZW8EqWOVBkK/f2f6vnS3Oe+bfv29Dt5ko6BrhKVmzaxt2VLdrdsSWUcLp6mc9nXsRfHOxn1iqYZJ2b2E+fc+DqbXjOzVdF8gJm1Bv4EfM05d6LuHULnnDMz15AEO+dmA7MBxo8f70INhBIvixcvBkIP0BJpezoqLi5Ouvxo0vNcVeU7oG/cSMuTJxlSUcGQqip/p2/AgEtGHUvG/Io35VnDKL+SV6LUkelchkJ9/6dL/R+3c3/kCGzYQNb+/fQ9dYq+587F5U5fOpd9HXtRvJNRr2jHgc8zswHOue0AZtYfiDhjtJll4wO93znnghOwHwg2zzSz7sDBwPq9QO86u/cKrBNJbcEO6P36+fn6PvgATpyA1av9Y406JiIiEl6nTnDttTVBH/v31zbvHDLE16Wa/kjSULSl/utAsZltBwzoCzwSbgfzt/B+CXzgnPtpnU1zgAeAxwJ/X62z/stm9iJ+YJbjydhf75ZbbmHTpk1ht0vyi3QeG3WeMzKgTx/fCb2szAd6R4/6Ucc2boTBg/0iIiIJK9TvANX/zaRu0Ld+ve/Tt369D/oKCuptMSOSyqIK9pxzfzGzwcDQwKqNzrlIY91OAv4WWGtmqwPrvoMP8v7XzB4GdgGfCWx7HfgksBU4BTwU7UEkknHjxlFeXh52uyS/SOfxss6zGfTsCT16+Erqgw9qO6Jv3ky/nBw/jYPu9ImIJJxQvwNU/zezTp3guuv8qJ1r1/rgb/VqP0DasGHQt68GRJO0EGk0zhuccwvN7M6LNg00M+o0zbyEc24J/i5gfW6s5/UO+FKkBIukjbqjjh065IO9gwfpV1kJf/5z7YSzCvpERETq16ULTJkC+/b5efmOH4dVq/xE7SNG+IurmvpIUlikO3vXAwuBW+vZ5oCQwV66KikpoaysLOx20BW+ZBfpPDb5ee7SBa6/Hg4d4tjSpbQ/f95XWps31wZ96osgIhJ3oX4HqP6Pn5LSUgDGTZ0KH37om3WWl8OyZdChA4waBV27xjmVIrERaTTOmYG/SdmkMh7mzp0b1XZ92Se3SOcxZue5SxdWt2tH0bBhvrI6csQ3T9m8GYYO9QO5qC+CiEjchPodoPo/fi7I+759fd/4HTtgwwZmLV0KS5cy88YbfdDXtm2cUyvStKK6FWBm24DlwNvA28659TFNlYiEZgb5+f4q5IED/g7f0aPw/vu+Wcrw4X5kT/VFEBERuVRGhr842rcvBO76sW+fXwYM8PVoixbxTaNIE4n21+Aw4BdAJ+BxM9tmZi/HLlkiElGwT9+NN8KkSdC+PZw5AyUl8OabfhoH16BpLEVERNJH3e4PAwf6enX7dnjjDd9PvrIyfmkTaSLRdvKpAs4H/lbj58Y7GHYPEWkeZn7kzu7dfYC3dm1tX4SOHX2zlC5d4p1KERGRxFVY6Pu/r1nj7/CtX+8DvxEj/B1ADeIiSSraYO8EsBb4KfCcc+5I7JIkIo1i5vsh9OzpK6gNG+Cjj6C42N8BHDnS3/0TERGRS7VtC5Mnw8GDvmvEsWPw7ruwZQuMHq1BXCQpRRvs3QtMBv4P8Dkzewd4yzm3IGYpE5HGycjwVyf79fMDt2zaBPv3+6VvX98XIS8v3qkUERFJTF27wsc+5kfuXLvWB32LF0OvXr61jOpQSSLRTqr+KvCqmQ0FbgK+Bvwj0DJ2SRORy5KV5SeOHTDAT8y+bRvs2gW7d8MVV/jROzVHn4iIyKXM/AXSXr38RdONG31XibIyX38OHarRryUpRDsa55+A0cA24C3gfmBFDNOVtGbOnElxcXHY7ZL8Ip3HhDrPLVrA2LEweLAfuXP3bl9p7djh+yL076++CCIiTSTU74CEqhfSTLi8j3heMjP9hdN+/Xx/vt27fTeJnTt9005Nyi4JLtpmnD8C3nPOVcUyMSISQ61bw8SJPuhbvdr35yspga1bYcwY9UUQEREJpVUrX4cOHAjvvQfHj/uB0Lp08RdU27WLdwpF6hXV1AvOuVUK9ERSRKdOcMMNcNVV0LKlr7AWL4alS/0oniIiIlK/Ll1g6lQ/emdODhw65Kc7Ki2Fc+finTqRS2jW5SY2e/ZsSkpKwm6fPXt2M6ZIYiHSeUz482wGffrATTf5ppyZmb4fwl//6u/6qcISEWmUUL8DEr5eSGHh8r5R58XM3+G76SY/IJqZ7xf/l7+Qf+aM5riVhBJtM06J0r59+y5ruySHlDnPmZlQUOD7Iqxb5/sgbNniB3IZNcqvV18EEZGohfr+T5p6IQWFy/vLOi85Ob4J54AB/s7e4cMUnD3rW8sUFvqpHETiLKo7e2Z2yRQL9a0TkSTVsiVceaUfarpzZ39nb9UqWLjQ9+0TERGR+rVrB0VFcOWVnDOrbdq5Zg1UVsY7dZLmwgZ7ZtbCzDoCnc2sg5l1DCz9gJ7NkkIRaT4dOvgK66qr/CieH30ECxb4gVzOno136kRERBKTGfTrx8qOHf2dPuf8lA1//avvJiESJ5GacT6Cn1OvB1ACBNtznQD+I3bJEpG4Cfbn697dDy+9ZQts3+7nFxoxwldiatopIiJyicqMDBg3zneDKC31E7IvXerr1LFjNSG7NLuIffacc/3N7LvOuX9pjgSJSILIzvZzCPXv74eZPnjQV1w7dvgKq1OneKdQREQkMXXqBDfe6AduWbcO9u3z9ejw4X4KpAyNkSjNI1JJeyjw9/YYp0NEElXbtnDddX5+oZYt4ehR35dv1SqN2ikiIhJKRoYP7KZNg969oarK9+NbsMDXpSLNINKdvQ/MbAvQw8zW1FlvgHPOjYpd0pJTYWFh2JGdCgsLmzE1EiuRzmPKnWczX1F17w4ffOD7IezY4fshjB7tm32qaaeISMjfASlXLySRcHnfLOelZUt/wbRfP98H/tgxH/BdcYW/05eZGfs0SNoKG+w55+41s27AX4FPNU+Sktutt95KcXFx2O2S/CKdx5Q9z1lZMHIk9O3rK6zDh2HlSj9VQ2EhtG4d7xSKiMRVqN8BKVsvJIFwed+s56VbN/jEJ3yzzi1b/IXTPXtg/Hjo2rX50iFpJWKDYefcfufcaOfcrouX5kigiCSgtm39qJ3jx/t5hg4c8COOffABVFfHO3UiIiKJKSsLxoyBG27wdenJk35evnffVdcIiYlIUy/8b+DvWjNbU2dZe1Gzzvr2/W8zO2hm6+qs+56Z7TWz1YHlk3W2fdvMtprZJjP7xOUeWLyUlZVRXl4ednuZhuBNepHOY1qcZzM/eMu0af5OX3W1v1o5b56/4ycikoZC/Q5Ii3ohQYXL+7idl06dYOpU34wzIwN27oS//MXf6XOu+dMjKSvSnb2vBv7eAtxaZwk+D+fXwLR61j/hnBsTWF4HMLNhwD3A8MA+/2lmSdmA+bnnnqO0tDTs9ueee64ZUySxEOk8ptV5zs2FCRPg+ut9M84TJ2DRIg3gIiJpKdTvgLSqFxJMuLyP63nJyIBhw3zQ17mzn8922TK/nDkTnzRJygkb7Dnn9gX+Xtx8czcwOcK+bwEfRZmO24AXnXNnnXM7gK3AhCj3FZFE0LUrfPzjUFDg7/rt2OGbdu7dG++UiYiIJK5g14jCQt/Mc+9eX3/u3q27fHLZwg7QYmZtgS8BPYE5wDzgy8A3gfeB3zXiM79sZvcDq4BvOueOBt5/eZ3X7Amsqy9NM4AZAPn5+WEHQ4mnSOlK1HTHQ0VFRdLmRzzOczLkV6v27RlSXk67M2fgnXc4mJvLltatOR+neYWSIc8SifIreSVKHakyFPr7P9XzJZHPfbh0NVWaL/f4c9u2ZUh5OR3PnYPlyzmUk8PmNm3iVn82RCKf+1hL5GOPNPXCb4GjwDLgc8B38NMu3O6cW92Iz/s58K+AC/z9CfB3DXkD59xsYDbA+PHjXVFRUSOSETuLFy8GIFS6Im1PR8XFxUmXH/E8z0mTX87B1q2wdi1dz56lq3N+MvbevZt9moakybMEofxKXolSR6ZzGQr1/Z8u9X8invtwed/U56VJjt853zrm/ffpcu4cXcrL/V2/3r2bJI2xkojnvrkk8rFHCvYGOOdGApjZfwH7gD7OuUY1JHbOHQg+NrPngLmBp3uBuiW4V2CdiCQrMz+ZbPfufpqGgwdhxQrfLKWw0M87JCIiIhcygwEDID/f938/eBCWL/eDtxQW+r7yIlGKdE/4fPCBc64K2NPYQA/AzLrXeXoHEBypcw5wj5nlmll/YDCwsrGfIyIJpHVruO46GDfO90UoK/N9EXbsUF8EERGRUPLyfP1ZWOgnXt+zx9efe/bEO2WSRCLd2RttZicCjw1oGXhugHPOtQ21o5n9ASgCOpvZHmAmUGRmY/DNOHcCj+DfaH1gmocNQCXwpUBwKSKpIHiVsls3f5dv/35/tXL3bj9XX6tW8U6hiIhI4jGDgQN9/fnuu3DokB+ts3dvHwTm5MQ7hZLgwgZ7zrlGT3/gnLu3ntW/DPP6HwA/aOznJYrPf/7zlJSUhN0uyS/SedR5DqFVK5g8GT78EFavrp2MfexYP1dfM/flExFpaqF+B6heiJ9weZ805yUvz09xtG0brFnjL5YePgxXXumbe4qEEOnOnjRQjx492Lx5c9jtkvwinUed5zDMfGCXn+/v8pWV+auVe/f6pp4tWsQ7hSIijRbqd4DqhfgJl/dJdV7MYNAgf5dvxQr46CN46y3fP37kSN/UU+QiiT+Oq4ikphYt4Jpr/FXJun351BdBREQktNatYcoUGD7cB4BbtsD8+XDsWLxTJglIwV4Te+2118Le2Xvttdd47bXXmjFFEguRzqPOc5TMoF8/+MQn/KTs5875vggrVvjHIiJJJtTvANUL8RMu75P2vGRkwLBhcMMNPvg7cQIWLIBNmzT4mVxAwV4TKy0tZd++fWG3l5aWNmOKJBYinUed5wZq1cqPODZ2rG+G8uGH8OabfiAXEZEkEup3gOqF+AmX90l/Xjp2hKlT/SBo1dW+P9/ixXDyZLxTJglCwZ6IJIZgX4SpU33ldfo0vP02lJZCZWW8UyciIpKYsrJ8n/fJk/0cfIcO+Qumu3bFO2WSABTsiUhiadPG90UYMcIHgNu2+b4IR4/GO2UiIiKJq3t33y2iRw9/kXTlSt8t4vz5yPtKylKwJyKJJyMDCgrgYx+Dtm2hvFx9EURERCLJzfWDn40bV9stYv58P3KnpCUFeyKSuNq39wHfoEE+yFuzxg8zffp0vFMmIiKSmMx8H76PfQzatYOKCli4UBdM05SCPRFJbJmZfuCWYF+Egwd9X4S9e+OdMhERkcTVti3ceOOFF0yXLIEzZ+KdMmlGmlS9iXXv3p3y8vKw2yX5RTqPOs8x0L07fPzjfgL2/fvhnXf8lcvRo33ndBGRBBDqd4DqhfgJl/cpf16CF0zz82vrzzffhAkT/OTskvL0C6mJzZgxg+Li4rDbJflFOo86zzHSooW/w7d1q79CuX27H3XsqqugQ4d4p05EJOTvANUL8RMu79PmvPTo4S+Yrljh682334YhQ/xgaBlq6JfKdHZFJLmYweDBlw7esnmz+iKIiIiE0rIlXH997WjXmzb5vnwVFfFOmcSQgj0RSU7t2l04eMv778PSpXD2bLxTJiIikpjM/GjXRUXQqpWf1mj+fPWDT2EK9prYrFmzWLx4cdjts2bNasYUSSxEOo86z80k2BfhmmsgOxv27YN58+Dw4XinTETSVKjfAaoX4idc3qfteencGaZO9c07z5/3/eDffx+qq+OdMmliCvZEJPn17OkrrY4d/bQMxcWwcaOadYqIiISSk+Mvlo4e7e/4bd7s689Tp+KdMmlCCvZEJDXk5cGUKb7DuXOwdq3vgK4hpkVEROpnBldc4Zt1tmwJR474FjL79sU7ZdJEFOyJSOrIyIBRo/yInTk5cOAAzJtHu3Pn4p0yERGRxBVs1tmtG5w75+fjW7tWzTpTgII9EUk93bv7SqtzZzhzhjHHj8OGDWrWKSIiEkpurr9YOmKEf75xI7z1lu8eIUlLwZ6IpKZWrfwQ0wUF/vn69b7S0midIiIi9QuO1nn99X5u20OHfLPOgwfjnTJpJAV7IpK6MjJgxAjWtGvnr1gePOgrrSNH4p0yERGRxNW1q28h07Wrv0i6eLGfl08tZJJOVrwTkGpuueUWNm3aFHa7JL9I51HnObEczcmBa6+FZct8oLdoEYwZAwMH+quYIiJNJNTvANUL8RMu73VewmjRAq67Dtat800616yBjz6C8eP9dEeSFGIW7JnZfwO3AAedcyMC6zoC/wP0A3YCn3HOHTUzA54CPgmcAh50zpXGKm2xNG7cOMrLy8Nul+QX6TzqPCegli39aGNr1sCWLfDeez7wGzcOsnTdS0SaRqjfAaoX4idc3uu8RGAGI0f6qY1WroQ9e+DECT9lQ5s28U6dRCGWzTh/DUy7aN2jwALn3GBgQeA5wE3A4MAyA/h5DNMlIukqI8Pf0Zs40U/I/uGHsGABhLlAIyIikvZ69oSPfQzatvXB3vz5sHdvvFMlUYhZsOecewv46KLVtwHPBx4/D9xeZ/1vnLccaG9m3WOVtlgqKSmhrKws7PaSkpJmTJHEQqTzqPOc4Hr39pVWmza1ldaePfFOlYikgFC/A1QvxE+4vNd5aYA2beCGG6BXL6ishHfe8U081Y8voTV326V851xwlsb9QH7gcU9gd53X7Qmsu2RGRzObgb/7R35+PsXFxTFLbGMsXrwYIGS6gtvDNfVMNxUVFQl3HiOJdB5jeZ6TMb/iLVSeZebkMCQ3l65nz8KyZexu2ZLteXm4NO/HpzKWvBKljkznMhTqd0C61P+JeO7D5X1Tn5dEPP4m5xy98/IYcPIk9sEHfLR1KxvatqXi1KnUP/YQEvm8x62jinPOmVmDLwU452YDswHGjx/vioqKmjpplyX4pREqXZG2p6Pi4uKky494nudkzK94C5tnzsHWrfD++/Q+fZreeXm+mWeLFs2axkSiMpa8EqWOTOcyFOr7P13q/0Q89+HyvqnPSyIef8wcPAjLltHx3Dkmnz7NqtxcxqfLsV8kkc97c0+9cCDYPDPwNzhpx16gd53X9QqsExGJLTMYPNgP3tKiBRw+7Jt1Hj0a75SJiIgkruD0DB06wKlTjD12zPeFl4TS3MHeHOCBwOMHgFfrrL/fvInA8TrNPUVEYq9zZ19pdeoEp0/DwoWwa1e8UyUiIpK4WrWCKVOgf38yAVas8KNeqx9fwohZsGdmfwCWAUPMbI+ZPQw8Bkw1sy3AxwLPAV4HtgNbgeeA/xOrdImIhNSihb/DN2AAVFf7YaZXr/aPRURE5FKZmTBuHFtat/atZTZtgqVL4fz5eKdMiGGfPefcvSE23VjPax3wpVilRUQkahkZfu699u39XHxbtsDx474fX25uvFMnIiKSeMzY27Ilg8eNg2XLYN8+P7XRpEmajy/OmrsZp4hIchg40N/ly831ndDnz4djx+KdKhERkcTVtSvceKOfj6+83Ad8+/fHO1VpLW6jcaaqmTNnhh16debMmc2XGImZSOdR5zlFdO7s5+N75x0/YMvChXDllX6ePhGReoT6HaB6IX7C5b3OSwy0bu3n41u5EsrK4O23YfRoPxhamk9tFA+6syciEk6w83nfvlBVBcuXq/O5iIhIONnZcM01UFDgn7//Prz7rq9HpVkp2BMRiSQz09/RGzNGnc9FRESiYQYjRvg+75mZfoTr4mI/4rU0GwV7TWz27NmUlJSE3T579uxmTJHEQqTzqPOcgoLz8V13HeTk+M7nCxfCyZPxTpmIJJBQvwNUL8RPuLzXeWkGvXv7FjItW8JHH/l+fOoD32zUZ6+J7dsXfnrASNslOeg8p7Fg5/MlS+DECV9pXXON798nImkv1Pe/6oX4CZf3Oi/NpEOH2j7wR474i6UTJ0KPHvFOWcrTnT0RkYYKdj7Pz4ezZ2HxYti5M96pEhERSVwtWsD110OfPr7v3tKlsHmz+sDHmII9EZHGyMmByZNh0CA/6fq778Lataq0REREQsnMhAkTYPhw//z996G01NejEhMK9kREGisjA8aOhcJC36dv40bfRKWyMt4pExERSUxmMGyYb8aZkQHbt/vpGc6di3fKUpKCPRGRyzVwIFx7rR9quqzM90U4dSreqRIREUlcvXtDURHk5sLBg77urKiId6pSjoI9EZGmkJ/vB25p3RqOH4f5830ndBEREalfp06+7mzbFsrL/aBnhw/HO1UpRaNxNrHCwsKwIzsVFhY2Y2okViKdR53nNNWmja+0li3zVymLi+Gqq6BXr3inTESaSajfAaoX4idc3uu8JIC8PD/o2fLlsH+/H/Rs/Hjo2zfeKUsJCvaa2K233kpxcXHY7ZL8Ip1Hnec0lpPjm3SWlsKOHT7wGz3az9FnFu/UiUiMhfodoHohfsLlvc5LgsjOhkmT/IAtW7fCypV+HtuCAtWdl0nNOEVEmlpGBowbByNH+ufvvw/vvafRxkREREIJDno2dqx/vn49lJSo7rxMCvaaWFlZGeXl5WG3l5WVNWOKJBYinUedZ8EMhg71zTgzMmDbNo3UKZIGQv0OUL0QP+HyXuclAQ0a5O/yZWb6FjJLl8L58/FOVdJSsNfEnnvuOUpLS8Nuf+6555oxRRILkc6jzrPU6NPHTyKbkwP79sGiRXD6dLxTJSIxEup3gOqF+AmX9zovCapHD1935ub6fnzFxao7G0nBnohIrHXu7Duf5+XBsWN+tLHjx+OdKhERkcTVqZOvO1u39nXnwoVw4kS8U5V0FOyJiDSH4EidnTr5q5MLF8KBA/FOlYiISOJq3doHfJ06+flrFy70o11L1BTsiYg0l9xc3yylVy/fd+/tt31/BBEREalfsO7s2dP33Xv7bfjww3inKmko2BMRaU6ZmTBxIgwZAs7BqlWwYYN/LCIiIpfKzISrr/bTGFVXw4oVsHGj6s4oKNgTEWluZjBqFAQn812/3s/Lp0pLRESkfmYwZoyfuxZg7Vo/rZHqzrDiEuyZ2U4zW2tmq81sVWBdRzObZ2ZbAn87xCNtIiLNZuBAf6UyIwO2b/cTsFdVxTtVIiIiieuKK3wLmeC0Rqo7w8qK42dPcc4drvP8UWCBc+4xM3s08Pxb8Ula433+85+npKQk7HZJfpHOo86zRK1XL98fYelS2LsXFi+GyZP9VA0iknRC/Q5QvRA/4fJe5yVJ9e4NLVrU1p1vv+3n5svOjnfKEk4iNeO8DXg+8Ph54Pb4JaXxevToQZs2bcJu79GjRzOmSGIh0nnUeZYG6dIFpkyBli3hyBE/F9+pU/FOlYg0QqjfAaoX4idc3uu8JLEuXaCoyAd9hw75ufjOnIl3qhKOuTi0czWzHcBRwAG/cM7NNrNjzrn2ge0GHA0+v2jfGcAMgPz8/HEvvvhis6U7WhUVFbRu3TreyUgayq+GUX41XLLkWW5VFaOOHyevqoqzGRm8364dp7KavwFGoubXlClTSpxz4+OdjkSWKHVkopah5pLOx5/Oxw7pffzxOvYWgbqzVVUVpzMyWNO+PaczM5s1DfE+7+Hqx3gFez2dc3vNrCswD/gKMKducGdmR51zYfvtjR8/3q1atSq2iW2g1157jX379jFjxoyQ2wFuvfXW5kxWQisuLqaoqCjeyWiQSOcxluc5GfMr3pIqz86d881SDh/2zVEmTfJXL5tRouaXmSnYa4B41pGJWoaaQ6jfAelS/yfiuQ+X9019XhLx+JtLXI/97FnflPPoUd814tproUPzDf8R7/Mern6MSzNO59zewN+DwMvABOCAmXUHCPxNyhkTS0tL2bdvX9jtpaWlzZgiiYVI51HnWRotJweuu652PqG33vL9EUQkKYT6HaB6IX7C5b3OS4oIzsXXtasP/IqLNfl6QLMHe2aWZ2Ztgo+BjwPrgDnAA4GXPQC82txpExFJCMH5hAYM8PMJvfOOH61TRERE6ped7e/o9e4NlZX+Tt/u3fFOVdzFYzTOfOBl3y2PLOD3zrm/mNm7wP+a2cPALuAzcUibiEhiMPPz8LVs6efhKynxTTyHDo13ykRERBJTRgZcdZW/07d1Kyxf7u/0DRoU75TFTbMHe8657cDoetYfAW5s7vSIiCQsMxg2zFdapaV+Atlz52DkSL9NRERELhScfL1FC1i3zk+8fvasr0/TsO5MpKkXRESkPgMH+iuVZrBpk7/LF4fBtURERJKCGRQUwLhx/vmGDfD++2lZdyrYExFJBn36+JE5MzNhxw7fNKWqKt6pEhERSVwDBvg+8GawZQusWpV2AV88+uyltO7du1NeXh52uyS/SOdR51liont3P1LnkiWwZ48frfOaayAOc/GJSP1C/Q5QvRA/4fJe5yUN9OoFkyf7wc527vSDt1x1le/flwb0C6GJzZgxg+Li4rDbJflFOo86zxIznTtDUZGfkuHAAVi82I8+lpMT75SJCKF/B6heiJ9wea/zkia6dfMXS99+218sraz0d/zS4GJpeoS0IiKppH17mDIFWrWCjz6CRYvg9Ol4p0pERCRxBS+W5ubC/v0+8Dt/Pt6pijkFeyIiyahNGx/wtWkDJ074gK+iIt6pEhERSVwdOviAr2VLOHzYT75+9my8UxVTCvaa2KxZs1i8eHHY7bNmzWrGFEksRDqPOs/SLFq18gFfhw5w8qQP+E6ciHeqRNJaqN8BqhfiJ1ze67ykobZtfd3ZujUcO+brzlOn4p2qmFGwJyKSzHJz4frroUsXOHPGV1pHj8Y7VSIiIokrL88HfO3aQXl5SreOUbAnIpLssrP9IC3duvlJ1xcvhiNH4p0qERGRxNWihW/S2bGjv7O3aBEcPx7vVDU5BXsiIqkgM9NPw9Czp+9w/tZbcOhQvFMlIiKSuHJyfOuYrl1965ji4pRrHaNgT0QkVWRmwsSJfgL2yko/0tiBA/FOlYiISOLKyvLz8HXvXts65qOP4p2qJqNgT0QklWRkwIQJ0L8/VFX5CdjLyuKdKhERkcR1ceuYxYv9aJ0pQMGeiEiqMYNx42DQIKiuhnfegd27450qERGRxJWR4VvH9O7tW8ekSHeI1J82vpndcsstbNq0Kex2SX6RzqPOs8SdGYwZ469WbtoEy5f7wK9v33inTCSlhfodoHohfsLlvc6LXCDYOiYjA3bt8t0hJk2C/Px4p6zRFOw1sXHjxlFeXh52uyS/SOdR51kSghmMHOkDvg0bYOVK37RzwIB4p0wkZYX6HaB6IX7C5b3Oi1wiIwOuvNL/3bHDd4e45hrfpy8JqRmniEgqM4Phw33QB1BSAlu2xDdNIiIiiSzYHWLgQN8qZulS2Ls33qlqFAV7TaykpISyMIMhlJSUUFJS0owpkliIdB51niXhDB0KY8f6x6tXw+bNcU2OSKoK9TtA9UL8hMt7nRcJyczXm4MHg3OwbFlS9n9XM84mNnfu3Ki2q9lAcot0HnWeJSENGuSbpZSUwPvv+8pryJB4p0okpYT6HaB6IX7C5b3Oi4RlBqNH++4QGzcmZf933dkTEUknAwb4pikAa9b4yktERETqZwYjRvguEeD7v+/YEd80NYCCPRGRdDNgAIwf7x+vXQsffBDf9IiIiCQyMxg2rLb/+6pVSRPwKdgTEUlH/fv70cYA1q3zo3WKiIhIaEOHXhjwbd8e3/REIeGCPTObZmabzGyrmT0a7/SIiKSsfv38fEIA69cr4BMREYlk6FAYNco/LilJ+IAvoQZoMbNM4BlgKrAHeNfM5jjn9AtERCQWgp3MV670AZ9zfhEREZH6BQc3W7MGSkro3rp1fNMTRqLd2ZsAbHXObXfOnQNeBG6Lc5pERFJb375w1VX+8YYN9Dt1Kr7pERERSXRDhviROoEhFRWwbVucE1Q/cwl0BdfM7gamOec+F3j+t8BVzrkv13nNDGBG4OkQYFOzJzSyzsDheCciiSi/Gkb51XDKs4ZJ1Pzq65zrEu9EJLIEqiMTtQw1l3Q+/nQ+dkjv49exx0/I+jGhmnFGwzk3G5gd73SEY2arnHPj452OZKH8ahjlV8MpzxpG+ZW8EqWOTPcylM7Hn87HDul9/Dr2xDz2RGvGuRfoXed5r8A6ERERERERaYBEC/beBQabWX8zywHuAebEOU0iIiIiIiJJJ6GacTrnKs3sy8BfgUzgv51z6+OcrMaIexOaJKP8ahjlV8MpzxpG+SWXK93LUDoffzofO6T38evYE1BCDdAiIiIiIiIiTSPRmnGKiIiIiIhIE1CwJyIiIiIikoIU7DUxM5tmZpvMbKuZPRrv9CQaM/tvMztoZuvqrOtoZvPMbEvgb4d4pjGRmFlvM1tkZhvMbL2ZfTWwXnlWDzNrYWYrzez9QH7NCqzvb2YrAv+X/xMYAEoCzCzTzN4zs7mB58ovabR0qwfTuV5L5zpK9U161x1mttPM1prZajNbFViXkOVewV4TMrNM4BngJmAYcK+ZDYtvqhLOr4FpF617FFjgnBsMLAg8F68S+KZzbhgwEfhSoEwpz+p3FrjBOTcaGANMM7OJwL8BTzjnBgFHgYfjl8SE9FXggzrPlV/SKGlaD/6a9K3X0rmOUn2jumOKc25Mnfn1ErLcK9hrWhOArc657c65c8CLwG1xTlNCcc69BXx00erbgOcDj58Hbm/ONCUy59w+51xp4HE5/ku1J8qzejmvIvA0O7A44Abgj4H1yq86zKwXcDPwX4HnhvJLGi/t6sF0rtfSuY5K9/pGdUe9ErLcK9hrWj2B3XWe7wmsk/DynXP7Ao/3A/nxTEyiMrN+wFhgBcqzkALNSlYDB4F5wDbgmHOuMvAS/V9e6EngH4HqwPNOKL+k8VQPemn3HZ2OdVSa1zdPkt51hwPeNLMSM5sRWJeQ5V7BniQU5+cC0XwgFzGz1sCfgK85507U3aY8u5Bzrso5Nwbohb/LMDS+KUpcZnYLcNA5VxLvtIikqnT4jk7XOipd6xvVHQBMds4V4pusf8nMrqu7MZHKfUJNqp4C9gK96zzvFVgn4R0ws+7OuX1m1h1/hUwCzCwbX4n+zjn3UmC18iwC59wxM1sEXA20N7OswBVH/V/WmgR8ysw+CbQA2gJPofySxlM96KXNd7TqqLSsb9K+7nDO7Q38PWhmL+OD/YQs97qz17TeBQYHRiPKAe4B5sQ5TclgDvBA4PEDwKtxTEtCCbSB/yXwgXPup3U2Kc/qYWZdzKx94HFLYCq+D8ki4O7Ay5RfAc65bzvnejnn+uG/rxY656aj/JLGUz3opcV3dDrXUelc36R73WFmeWbWJvgY+DiwjgQt9+bvMkpTCVzleBLIBP7bOfeD+KYosZjZH4AioDNwAJgJvAL8L9AH2AV8xjl3cWf3tGRmk4G3gbXUtov/Dr5PhPLsImY2Ct8pOhN/Met/nXP/YmYD8ANFdATeA+5zzp2NX0oTj5kVAX/vnLtF+SWXI93qwXSu19K5jlJ946Vj3RE4zpcDT7OA3zvnfmBmnUjAcq9gT0REREREJAWpGaeIiIiIiEgKUrAnIiIiIiKSghTsiYiIiIiIpCAFeyIiIiIiIilIwZ6IiIiIiEgKUrAnIiIiIiKSghTsiYiIiIiIpCAFeyIiIiIiIilIwZ6IiIiIiEgKUrAnIiIiIiKSghTsiYiIiIiIpCAFeyIiIiIiIilIwZ6IiIiIiEgKUrAnIiIiIiKSghTsiYiIiIiIpCAFeyIiIiIiIilIwZ6IiIiIiEgKUrAnIiIiIiKSghTsSdyYWZWZrTazdWb2mpm1D6zvYWZ/rPO6P5jZGjP7upl9zcxaNfLz/sXMPlbP+iIzm1vn8TV1tv3azO5uzOc1lpntNLPOjXmNeQvNrG3g+f81sw/M7Hdm9qCZ/UcTprMm3+LNzCYEytJqM3vfzO4IrM8xs7fMLCveaRQRaQjVkSHTqTqygVRHpjcFexJPp51zY5xzI4CPgC8BOOfKnHN3A5hZN+BK59wo59wTwNeARlVkzrnvOufmR3hZEXBNhNcksk8C7zvnTgSe/x9gqnNuehzT1BzWAeOdc2OAacAvzCzLOXcOWAD8TTwTJyLSCKojm57qSNWRaUfBniSKZUBPADPrZ2brAuvfBHoGrkbNBHoAi8xsUd2dzexKM3sp8Pg2MzsduGLVwsy2B9bXXIE0s2lmttHMSoE7g58LfAH4euDzrg28/XVm9o6Zba/vCmYgvRsD7785cIXwY2a21My2mNmEwOs6mtkrgSuwy81sVGB9JzN708zWm9l/AVbnve8zs5WB9PzCzDIj5ON04NXAvs8CA4A3zOzr9aR5YSAtC8ysj5llmtmOwJXP9oGrytcFXv+WmQ0O9aGBq4bLzOy9QF4NCaz/c53jfM/Mvht4/C9m9vl60vSBmT0XyIs3zaxlhOMFwDl3yjlXGXjaAnB1Nr8SyBcRkWSlOlJ1pOpIaRQFexJ3gS/nG4E59Wz+FLAtcHVzFlAGTHHOTbnode8BYwKPr8VfxboSuApYcdHntQCeA24FxgHdAJxzO4FngScCn/d2YJfuwGTgFuCxEIcxCPgJMDSwfDawz98D3wm8ZhbwnnNuVGDdbwLrZwJLnHPDgZeBPoF0FuCvtk0KXI2rIvIX8iSgJHA8X6A2v5646HU/A54PpOV3wNPOuSpgEzAskPZS4FozywV6O+e2hPncjcC1zrmxwHeBHwbWvx14j3ZAZSB94M/RW/W8z2DgmUBeHAPuCuTFP1htE5S6y9PBHc3sKjNbD6wFvlCnYguWBRGRpKM6UnVkHaojpcHURlfiqaWZrcZfrfwAmNfYN3LOVZrZtsCX/wTgp8B1QCb+y7SuocCO4Bezmb0AzAjz9q8456qBDWaWH+I1O5xzawPvtx5Y4JxzZrYW6Bd4zWQCX8zOuYWBq5VtA+m8M7D+z2Z2NPD6G/EV7btmBtASOBghKzo658ojvAbg6uBnAr8F/j3w+O1AevoDPwI+DywG3o3wfu2A5wNXNh2QXef9/i+wA/gzMNV8f5L+zrlN9bzPDufc6sDjEgJ555x7HHg8XAKccyuA4YEy8LyZveGcO+OcqzKzc2bWJsq8ERFJBKojVUdeTHWkNJju7Ek8nQ5cjeuLb5bxpct8v7eAm4DzwHx8xTGZSyuyhjpb57FF8ZrqOs+rafxFFcNfWRwTWIY4574XYZ9KM7uc/+u38FcUJwCvA+3xfTQi5eG/AosCfUtuxTcTAV8Bjqf2KuV7+MqxJMT71M3HKgJ5F81VyyDn3AdABTCizupc4EyEYxARSSSqI8NTHak6UqKgYE/izjl3Cn9l65sWeUSocqBNiG1v4zunL3POHQI6AUPwTRTq2gj0M7OBgef3Rvn+l+ttAk1MzKwIOBzoJP4WvkkLZnYT0CHw+gXA3WbWNbCto5n1jfAZm/B9ECJ5B7gn8Hg6tRXVSnzn+2rn3BlgNfAI9TcnqasdsDfw+MHgykDn793Ap/F9Tt7GN9uJ9H4XcM49XqdCr7v8XwAz6x8sO4E8GgrsDDzvhM/r8w35TBGRRKA6UnVkJKojJRwFe5IQnHPvAWu4sFKpz2zgL3ZR5/OAFUA+tV+Sa4C1zrm6HZEJfEHPAP5svvN53WYfrwF32IWdz5vK94BxZrYG36/hgcD6WfgO7uvxzUY+DKRzA/BPwJuBfebh+0aE82f8VcZIvgI8FHjfvwW+GvjMs/iKZ3ngdW/jK/a1Ed7v34Efmdl7XHqV9m3goHPudOBxLy7/SvLFJgPvB5o8vQz8H+fc4cC2Kfh8ERFJSqojVUdeJtWRacwu+h8XkSRmZt2B3zjnpsY7LYnC/Ah0jzrnNsc7LSIiEj+qIy+lOjL16c6eSApxzu0Dngt0ak97ZpaDHzxAlZiISJpTHXkh1ZHpIeZ39gJDBq8C9jrnbjGz/sCL+LbiJcDfOufOBYau/Q1+ZKUjwN8EhvkVERERERGRBmqOO3tfxQ8ZHPRv+DlaBgFHgYcD6x8GjgbWPxF4nYiIiIiIiDRCTIM9M+sF3Az8V+C5ATcAfwy85Hng9sDj2wLPCWy/MfB6ERERERERaaBYT6r+JPCP1A7T2wk45pyrDDzfg58slMDf3VAz+efxwOsPU4eZzSAwuWfLli3H9e7dO5bpb5Tq6moyMtQdMlrKr4ZRfjWc8qxhEjW/Nm/efNg51yXe6UhkiVJHJmoZai7pfPzpfOyQ3sevY4/fsYerH2MW7JnZLfihZEsC86U0CefcbPzQwowfP96tWrWqqd66yRQXF1NUVBTvZCQN5VfDKL8aTnnWMImaX2a2K95pSHSJUkcmahlqLul8/Ol87JDex69jL4rb54erH2N5Z28S8Ckz+yTQAmgLPAW0N7OswN29XtROMrkX6A3sCUz82A4/UIuIiIiIiIg0UMzuNzrnvu2c6+Wc6wfcAyx0zk0HFgF3B172APBq4PEcaifQvDvwek0CKCIiIiIi0gjxaFz6LeAbZrYV3yfvl4H1vwQ6BdZ/A3g0DmkTERERERFJCbEeoAUA51wxUBx4vB2YUM9rzgCfbo70iIiIiIiIpLr0HDJHREREREQkxSnYExERERERSUEK9kRERERERFKQgj0REREREZEUpGBPREREREQkBSnYExERERERSUEK9kQSwPbt23n44Ye5++67450USSEqVyKSDPRdJemkucu7gr04OnDgAJ/97GcZMGAA48aN4+qrr+bll18GwMz45je/WfPaH//4x3zve9+ref6DH/yA4cOHM2rUKMaMGcOKFSvCrk8lu3fvZsqUKQwbNozhw4fz1FNP1Wzr168fI0eOZMyYMYwfP/6C/aqqqhg7diy33HJLyPcOt38sDRgwgF/+8pdN+p4qXw33d3/3d3Tt2pURI0bUrNu0aRNjxoypWdq2bcuTTz4JNKy8RFP+mlosypWknxdeeIHRo0fTunVrzAwz49ixY5f9vvqOahzVgclN5b7hVDdfnmaZVF0u5Zzj9ttv54EHHuD3v/89ALt27WLOnDkA5Obm8tJLL/Htb3+bzp07X7DvsmXLmDt3LqWlpeTm5nL48GHOnTsXcn2qycrK4ic/+QmFhYWUl5czbtw4pk6dyrBhwwBYtGjRJXkG8NRTT1FQUMCJEyfCvn+o/ZvC2rVr+fa3v33Buv/+7/+ma9euTfo5Kl+N8+CDD/LlL3+Z+++/v2bdkCFDWL16NeArhZ49e3LHHXfUbI+2vERb/hqjucqVpJ8NGzbwwAMPUF1d3aTvq++oxlMdmLxU7htHdfPl0Z29OFm4cCE5OTl84QtfqFnXt29fvvKVrwD+y3zGjBk88cQTl+y7b98+OnfuTG5uLgCdO3emR48eIddf7PHHH+fpp58G4Otf/zo33HBDTZqmT59+wWt37tzJ0KFDefDBB7niiiuYPn068+fPZ9KkSQwePJiVK1fWvPaFF15gwoQJjBkzhkceeYSqqioAbr/9dsaNG8fw4cOZPXs2ACdPnuTmm29m9OjRPPTQQ/zP//xP1HnXvXt3CgsLAWjTpg0FBQXs3bs37D579uzhz3/+M5/73Oei/pz6NCQ/6jvukSNHMnfu3AuWWPzTx7N8QeiyENQc5WrEiBENKlcA1113HR07dgy5fcGCBQwcOJC+ffs26H0jlb9kKVeSft57772aQG/WrFlUVVXhnKN9+/aX9b6pXgf+5Cc/idl3lerA5KW6OXXr5n/6p39K3PLunEvaZdy4ce5ylZSUuHvuucf16NHDZWdnu06dOrmioiK3YsWKRr/nokWLIr7mqaeecl/72tdCbs/Ly3PHjx93ffv2dceOHXOPP/64mzlzpnPOufLycjd69Gg3ePBg98UvftEVFxeHXX+xZcuWubvvvts559zkyZPdlVde6c6dO+e+973vuWefffaC1+7YscNlZma6NWvWuKqqKldYWOgeeughV11d7V555RV32223Oeec27Bhg7vlllvcuXPnnHPOffGLX3TPP/+8c865I0eOOOecO3XqlBs+fLg7fPiw++Mf/+g+97nP1eTXsWPHLknnTTfd5Pbu3Rs2H3fs2OF69+7tjh8/7pxzrl+/fm7s2LGusLDQ/eIXv6h53V133eVWrVrlFi1a5G6++eaQ7xdq/4bmR6jjDuXw4cPukUcecQMGDHA//OEPwx5zopevcGUhqDnKlXOuplzVzbNI5WrHjh1u+PDh9W576KGH3M9+9rOa55HKS1Ck8pcI5aquaMpYPACrXALUPcmyXG4def311zvgkqVv374R941UhlK9DvzUpz7VqO+qupK1Dgye++b4rkpE4cp+qtfNixYtill5T/S6+dVXX73kuEOJRXkPVz+mdTPOl19+mc985jNUVlbWrDty5AjFxcVs2LCBCRMmNFtavvSlL7FkyRJycnJ49913AWjbti33338/Tz/9NC1btqx5bevWrSkpKeHtt99m0aJF/M3f/A2PPfYYDz74YMj1dY0bN46SkhJOnDhBbm4uhYWFrFq1irfffrvmamdd/fv3Z+TIkQAMHz6cG2+8ETNj5MiR7Ny5E/BXVUpKSrjyyisBOH36dM3Vi6effrqmPfru3bvZsmULI0eO5Jvf/Cbf+ta36NmzJ0VFRZd87uuvvx42zyoqKrjrrrt48sknadu2LQBLliyhZ8+eHDx4kKlTpzJ06FBOnDhB165dGTduHMXFxWHfs779r7vuugbnR6jj7tSpU72f26lTJ5599tmwabsczVm+wpWFumJdrm655RauvfbaSz43UrkK5dy5c8yZM4cf/ehHNeuiKS/BK3mRyl8yliuRppJqdeBHH33E2LFjgdh9V6kOTH6pVjf36dMnbevml156iX/+53++4LgTpbynbbB3+vRpPv/5z9cEev/yL//CI488QmZmJosWLYr5bdbhw4fzpz/9qeb5M888w+HDhy/pSPq1r32NwsJCHnrooQvWZ2ZmUlRURFFRESNHjuT555/nwQcfDLm+ruzsbPr378+vf/1rrrnmGkaNGsWiRYvYunUrBQUFl6Q12DQAICMjo+Z5RkZGTf4553jggQcu+GcDKC4uZv78+SxbtoxWrVpRVFTEmTNnuOKKKygtLeX111/n8ccf59ixY3z3u9+NOv/Onz/PXXfdxfTp07nzzjtr1vfs2ROArl27cscdd7By5UqOHDnCnDlzeP311zlz5gwnTpzgvvvu44UXXrjkfevb/+IviGjyI9RxN5d4lq9QZeFisS5X//RP/8SNN97YoHIVzhtvvEFhYSH5+fk166IpL0uXLo2q/CVDuZL0UlxczK9//eua74df/epXl/y/N1aq14HFxcUUFRXF7LtKdWBySvW6+cknn0zburmkpIQVK1YkZHlP2z57S5cu5ciRIwAUFRXxz//8z3Tt2pVOnTpx9913X1IomtoNN9zAmTNn+PnPf16z7tSpU5e8rmPHjnzmM5+5YNSeTZs2sWXLlprnq1evpm/fviHX1+faa6/lxz/+Mddddx3XXnstzz77LGPHjsXMGnU8N954I3/84x85ePAg4K9q7tq1i+PHj9OhQwdatWrFxo0bWb58OQBlZWW0atWK++67j3vuuYfS0tKoP8s5x8MPP0xBQQHf+MY3atafPHmS8vLymsdvvvkmI0aM4Ec/+hF79uxh586dvPjii9xwww31VnKh9m+MUMfdXOJZvkKVhca4nHL1D//wDw0qV5H84Q9/4N577615Hm15ibb8RSPe5UqkqaR6HXjixImYfVepDkxeqV43V1RUpG3d3KZNm4Qt72kb7B04cKDmcXAEq+ZkZrzyyissXryY/v37M2HCBB544AH+7d/+7ZLXfvOb3+Tw4cM1zysqKnjggQcYNmwYo0aNYsOGDXzve98Lub4+1157Lfv27ePqq68mPz+fFi1a1HtbPVrDhg3j+9//Ph//+McZNWoUU6dOZd++fUybNo3KykoKCgp49NFHmThxIuBHKAp27H3++ef5p3/6JwA++clPUlZWdsnjupYuXcpvf/tbFi5cWDPk7uuvv86BAweYPHkyo0ePZsKECdx8881MmzYtYtqDn9PY/esT6ribSzzLV6iy0BiXU65mzZpVU64effTRiOUK4N577+Xqq69m06ZN9OrVq6aiPXnyJPPmzbvgCnqk8hLucxor3uVKpKmkeh3493//9436rlIdmNpSvW6eMGFCk5d3SI66uaqqKnHLe6jOfMmwXE7n83nz5tV0Np8yZUqj36c+iTq4QaJSfjWM8qvhlGcNk6j5hQZoabY6MuhXv/pVTV35q1/9Kur9ErUMNZd0Pv50Pnbn0vv4dezxE65+TNs7e5MmTarpOLlo0SJ++MMfcujQIY4ePcorr7zCW2+9FecUioiIiIiINF7aBnstW7bkueeeIyvLj1Hz//7f/6Nr16507NiRO+64g+3bt8c5hSIiIiIiIo2XtsEewB133MGKFSu455576NGjB1lZWXTs2JHrr78+Lv34REREREREmkraTr0QVFhYyB/+8Id4J0NERCThPPjgg0023YKIiDS/tL6zJyIiIiIikqpiFuyZWQszW2lm75vZejObFVj/azPbYWarA8uYwHozs6fNbKuZrTGzwlilTUREREREJNXFshnnWeAG51yFmWUDS8zsjcC2f3DO/fGi198EDA4sVwE/D/wVERERERGRBorZnb3AtA8VgafZgcWF2eU24DeB/ZYD7c2se6zSJyIiIiIiksrMz8MXozc3ywRKgEHAM865b5nZr4Gr8Xf+FgCPOufOmtlc4DHn3JLAvguAbznnVl30njOAGQD5+fnjXnzxxZilv7EqKipo3bp1vJORNJRfXllZGS+88AInT55k1qxZIV+n/Go45Vn9QpW5RM2vKVOmlDjnxsc7HYksUerIRC1DzSWdj7+xxx5tHZjodO517JerMf8LYevHULOtN+UCtAcWASOA7oABucDzwHcDr5kLTK6zzwJgfLj3HTduXNNMO9/EFi1aFNXr9u/f7+69917Xv39/V1hY6CZOnOheeukl55xzgPvGN75R89rHH3/czZw5s+b597//fTds2DA3cuRIN3r0aLd8+fKw6xPFzJkz3eOPP37BuovzKy8vL+L7fPjhh66oqMgVFBS4YcOGuSeffLJmW9++fd2IESPc6NGj3cVlpLKy0o0ZM8bdfPPNId873P7N4a677gq7XeXrUvWVq7oWLVoUVblyzrmHHnrIdenSxQ0fPvyC9U8++aQbPny4GzZsmHviiSdq1kdbXurb//Tp0+7KK690o0aNcsOGDXPf/e53o0pjU7u4zEVbxpobsMo1Q52VKks868hoylAqf0eFOv5I31XOJX8deLnfH5HqwEQX6fjTqdw3VXl3LnTdfPToUXfXXXe5IUOGuKFDh7p33nnHOefcT3/6Uzds2DA3fPhwd88997jTp0/X+7717R/u/yuUWNSbDflfCFc/NsvUC865Y2a2CJjmnPtxYPVZM/sV8PeB53uB3nV26xVYl5Kcc9x+++088MAD/P73vwdg165dzJkzB4Dc3Fxeeuklvv3tb9O5c+cL9l22bBlz586ltLSU3NxcDh8+zLlz50KuT0VZWVn85Cc/obCwkPLycsaNG8fUqVNr5kdctGjRJfkG8NRTT1FQUMCJEyfCvn+o/ZvC2rVr+fa3v33Buv/+7/+ma9euTfYZKl+N9+CDD/LlL3+Z+++/v2bdunXreO6551i5ciU5OTlMmzaNW265hUGDBgGRy0uo/QcOHMjChQtp3bo158+fZ/Lkydx0001MnDixSY+pOcqcSEPoO+ryqA5MTir3jVdf3Qzw1a9+lWnTpvHHP/6Rc+fOcerUKfbu3cvTTz/Nhg0baNmyJZ/5zGd48cUX651Gpr79T58+Hfb/q6k01/9CLEfj7GJm7QOPWwJTgY3BfnhmZsDtwLrALnOA+wOjck4Ejjvn9sUqffG2cOFCcnJy+MIXvlCzrm/fvnzlK18B/Bf5jBkzeOKJJy7Zd9++fXTu3Jnc3FwAOnfuTI8ePUKuv9jjjz/O008/DcDXv/51brjhhpo0TZ8+/YLX7ty5k6FDh/Lggw9yxRVXMH36dObPn8+kSZMYPHgwK1eurHntT3/6U0aMGMGIESN48skna9b/4Ac/4IorrmDy5Mls2rSpZv0LL7zAhAkT+NznPscjjzxCVVVV1PnXvXt3Cgv9gK1t2rShoKCAvXvDXxvYs2cPf/7zn/nc5z4X9efUpyF5cvvttzNu3DiGDx/O7NmzARg5ciRz5869YGnqf+x4li+oPbdjxoyp99w2R7kK9dmRXHfddXTs2PGCdR988AFXXXUVrVq1Iisri+uvv56XXnop6vcMtb+Z1TT7OH/+POfPn8d/NV4oGcqcSEOkeh34xz/WjkEXi++qRK4DP/jgg5rX6vvoQqqbm7ZuPn78OG+99RYPP/wwADk5ObRv3x6AyspKTp8+TWVlJadOnao3T0LtH+3/V938+tu//dvErZtD3fK73AUYBbwHrMEHdMHmmguBtYF1LwCtA+sNeAbYFtgetgmnS/JmnE899ZT72te+FnJ7Xl6eO378uOvbt687duzYBbfyy8vL3ejRo93gwYPdF7/4RVdcXBx2/cWWLVvm7r77buecc5MnT3ZXXnmlO3funPve977nnn322Qteu2PHDpeZmenWrFnjqqqqXGFhoXvooYdcdXW1e+WVV9xtt93mnHNu1apVbsSIEa6iosKVl5e7YcOGudLS0pr1J0+edMePH3cDBw50jz/+uNuwYYO75ZZb3Llz59yiRYvcF7/4Rff888/XHHvQTTfd5Pbu3Rs2L3fs2OF69+7tjh8/7pxzrl+/fm7s2LGusLDQ/eIXv6h53V133eVWrVrlFi1aFLYJS6j9G5onzjl35MgR55xzp06dcsOHD3eHDx8O+bmHDx92jzzyiBswYID74Q9/GPJ1iV6+6p5b59wF5zaoOcpV3c++uBlnpHK1Y8eOC5qKbNiwwQ0ePNgdPnzYnTx50k2cONF9+ctfds5FLi+R9q+srHSjR492eXl57h//8R9Dpqc5y5yacabGksjNOFO9Duzbt2+jvquCxx6UjHXgpEmTal4bizow0YUr+6leNz/77LMxLe8X183vvfeeu/LKK90DDzzgxowZ4x5++GFXUVHhnPNdJ/Ly8lznzp3dZz/72XrfL9z+dT+z7v9XqPxasGBBs/8erCtc/RizZpzOuTXA2HrW3xDi9Q74UqzSk+i+9KUvsWTJEnJycnj33XcBaNu2Lffffz9PP/00LVu2rHlt69atKSkp4e2332bRokX8zd/8DY899hgPPvhgyPV1jRs3jpKSEk6cOEFubi6FhYWsWrWKt99+u+ZqZ139+/dn5MiRAAwfPpwbb7wRM2PkyJHs3LkTgCVLlnDHHXeQl5cHwJ133snbb79NdXU1d9xxB61atQLgU5/6FAALFiygpKSEK6+8koqKCjIzM+u9mvH666+HzbeKigruuusunnzySdq2bVuTlp49e3Lw4EGmTp3K0KFDOXHiBF27dmXcuHEUFxeHfc/69r/uuusanCcATz/9NC+//DIAu3fvZsuWLXTq1Knez+3UqRPPPvts2LQ1VnOWr7rnFuD06dP1nttYl6u6n92nT58LPjtSubpYQUEB3/rWt/j4xz9OXl4eY8aMITMzsyaNkcpLuP0zMzNZvXo1x44d44477mDdunWMGDGiUfkFiVPmRBoi1erA6667rlHfVRdLxjpw//79Na/T91F4qVY3b968Oabl/WKVlZWUlpbys5/9jKuuuoqvfvWrPPbYY3zjG9/g1VdfZceOHbRv355Pf/rTvPDCC9x3331R7f+v//qvQP3/X6Hyq7i4OGHr5mbpsyeXGj58OH/6059qnj/zzDMcPnyY8eMvHEjna1/7GoWFhTz00EMXrM/MzKSoqIiioiJGjhzJ888/z4MPPhhyfV3Z2dn079+fX//611xzzTWMGjWKRYsWsXXrVgoKCi5Ja7BpAEBGRkbN84yMDCorKxt1/M45HnjgAX70ox9RXFxMUVFRg9/j/Pnz3HXXXUyfPp0777yzZn3Pnj0B6Nq1K3fccQcrV67kyJEjzJkzh9dff50zZ85w4sQJ7rvvPl544YVL3re+/S+u6KLJk+LiYubPn8+yZcto1aoVRUVFnDlzpsHH2RjxLF91z204sS5XdUX6cRONhx9+uKapx3e+8x169eoFRFdewu0f1L59e6ZMmcJf/vKXeoO9RC9zIg2hOjC678lwErUODDbP0/fRpVQ3N76816dXr1706tWLq67y03LffffdPPbYY8yfP5/+/fvTpUsXwAej77zzziXBXqj9IfT/18WSoW6OWZ89Ce+GG27gzJkz/PznP69Zd+rUqUte17FjRz7zmc/wy1/+smbdpk2b2LJlS83z1atX07dv35Dr63Pttdfy4x//mOuuu45rr72WZ599lrFjx9bbXyga1157La+88gqnTp3i5MmTvPzyy1x77bVcd911vPLKK5w+fZry8nJee+01AG688Ub++Mc/cvDgQQA++ugjdu3aFfXnOed4+OGHKSgo4Bvf+EbN+pMnT1JeXl7z+M0332TEiBH86Ec/Ys+ePezcuZMXX3yRG264od5KLtT+jXH8+HE6dOhAq1at2LhxI8uXL2/U+zRGPMvX5Z7bupq7XIUTfM8PP/yQl156ic9+9rMNKi/17X/o0CGOHTsG+Cud8+bNY+jQoY1OYzzLnEhDpHod+Pbbb6sO1PfRJVK9bh41alSz1s3dunWjd+/eNX0DFyxYwLBhw+jTpw/Lly/n1KlTOOdYsGBBvRdyQu0f6v+rseL9v6A7e3FiZrzyyit8/etf59///d/p0qULeXl5/Nu//dslr/3mN7/Jf/zHf9Q8r6io4Ctf+QrHjh0jKyuLQYMGMXv2bHbt2lXv+vpce+21/OAHP+Dqq68mLy+PFi1acO211zb6eAoLC3nwwQeZMGECAJ/73OcYO9a34v2bv/kbRo8eTdeuXWtu4Q8bNozvf//7fPzjH6e8vJz27dvzzDPPXPIF9clPfpL/+q//uqRj7dKlS/ntb3/LyJEjGTNmDAA//OEPGTp0KHfccQfgb89/9rOfZdq0aRHTH/ycM2fONGr/+kybNo1nn32WgoIChgwZ0uQjLIYTz/JV99xWV1eTnZ1d77mNxuWUq7qffbFQ5Qrg3nvvpbi4mMOHD9OrVy9mzZrFww8/zF133cWRI0dq3rN9+/Zs3749bHmp+zn17b9mzRoeeOABqqqqqK6u5jOf+Qy33HJLg/MpKJ5lTqQhUr0OvPnmmxv1XaU6MLWlet18/PjxmJR3CF03/+xnP2P69OmcO3eOAQMG8Ktf/YoOHTpw9913U1hYSFZWFmPHjmXGjBn1fk59+4f6//rkJz/Z4LyC+P8vxHRS9VgbP368W7VqVeQXNrPGNktMV8qvhlF+NZzyrGESNb/MTJOqN0A868hELUPNJZ2PP52PHdL7+HXsRXH7/HD1o5pxioiIiIiIpCAFeyIiIiIiIilIwZ6IiIiIiEgKUrAnIiIiIiKSghTsiYiIiIiIpCAFeyIiIiIiIilIwZ6IiIiIiEgKUrAnIiIiIiKSghTsiSSB7du38/DDD3P33XfHOymSAlSeRCSZ6DtL0kUsyrqCvTj6u7/7O7p27cqIESNq1u3cufOC54nmmmuuAeDpp5+moKCA6dOnc+zYMf7zP/+zWdOxe/dupkyZwrBhwxg+fDhPPfXUBdv79evHyJEjGTNmDOPHj79gW1VVFWPHjuWWW25p8PseO3aMu+++m6FDh1JQUMCyZcua/uDqMWDAAH75y182aB+Vr4arL8+CnnjiCYYPH86IESO49957OXPmTNj1QZs2bWLMmDE1S9u2bXnyySeB5CpPIk1N31GN19g6MNx3XF31vS7cd1mspdJ3lsp9w4Urt6Hq0Uhl/cyZM0yYMIHRo0czfPhwZs6cGdW2WItJWXfOJe0ybtw4l4gWLVoU1esWL17sSkpK3PDhw2vW7dix44LniaC6utpVVVVdsG7IkCFu9+7dzrnLT3O0+VVXWVmZKykpcc45d+LECTd48GC3fv36mu19+/Z1hw4dqnffn/zkJ+7ee+91N998c4Pf9/7773fPPfecc865s2fPuqNHjzY47eGsWbPG3XzzzRcsBw4cqNl+1113qXw1wuXkmXPO7dmzx/Xr18+dOnXKOefcpz/9aferX/0q5PpQKisrXX5+vtu5c6dzLvblybnwZequu+6qd5/G/E82B2CVS4C6J1mWeNaR0ZShVP6OivX/UGPrwFDfcQ193cXfZXVd7rE35jsrkUQ6fpX7hgtXHkPVo5HKcHV1tSsvL3fOOXfu3Dk3YcIEt2zZsojbQmnosUfze68hwtWPurMXR9dddx0dO3YMuX379u2MHTuWd999l507dzJ06FAefPBBrrjiCqZPn878+fOZNGkSgwcPZuXKlZfsf/GVoh//+Md873vfq3mv6dOnU1BQwN13382pU6cu2XfIkCHcf//9jBgxgt27dwPQunVrvvCFL7B9+3ZuuukmnnjiCR599FG2bdvGmDFj+Id/+Icmyp3wunfvTmFhIQBt2rShoKCAvXv3Rtxvz549/PnPf+Zzn/tcg9/3+PHjvPXWWzz88MMA5OTk0L59+wv2b8h5uv322xk3bhzDhw9n9uzZAIwcOZK5c+desHTt2rVhmROg8tVw4fKssrKS06dPU1lZyalTp+jRo0fY9fVZsGABAwcOpG/fvlGVJ4i+TNVXnqBpy5RIU9J3VOM1tg6MlOfRvq7ud9nF9u/fr++sMFTuGy5UnoWrRyPls5nRunVrAM6fP8/58+cxs4jbgi4+N9///vfj9nsvolBRYDIsyX5nz7lLr4wEn2/cuNGNGTPGrV69umZ9ZmamW7NmjauqqnKFhYXuoYcectXV1e6VV15xt912W8T3fvzxx93MmTPdjh07HOCWLFninHPuoYceco8//vgl+5rZJVcy8vLynHMXXjWs7+rOTTfd5Pbu3RtVHlzulaAdO3a43r17u+PHj9es69evnxs7dqwrLCx0v/jFL2rW33XXXW7VqlVu0aJF9d7ZC/e+7733nrvyyivdAw884MaMGeMefvhhV1FRcck+0Z6nI0eOOOecO3XqlBs+fLg7fPhwyLQcPnzYPfLII27AgAHuc5/7XIPyJt3Ll3OX9z8Z9OSTT7q8vDzXuXNn99nPfjbi+vo89NBD7mc/+5lzLrryFExPNOemseXphz/84SXbdWcvNZZEv7PnXOp+R1111VUN+o66HA2pA0OlN9T7hnpd3e+yi/3hD39o9u+sRBJN2Ve5b7j6Pi9SPRqprFdWVrrRo0e7vLw894//+I9Rbwu+d91zM3jw4Cb/vdeQsh6uftSdvQR06NAhbrvtNn73u98xevTomvX9+/dn5MiRZGRkMHz4cG688UbMjJEjR7Jz584GfUbv3r2ZNGkSAPfddx9Lliy55DV9+/Zl4sSJjTqG119/PewdjqZSUVHBXXfdxZNPPknbtm1r1i9ZsoTS0lLeeOMNnnnmGd56662aqybjxo1r1PtWVlZSWlrKF7/4Rd577z3y8vJ47LHHLtk32vP09NNPM3r0aCZOnMju3bvZsmVLyPR06tSJZ599lm3btjF9+vQG5NClVL4a7ujRo7z66qvs2LGDsrIyTp48yQsvvBByfX3OnTvHnDlz+PSnPw1EX54gunPT2PL07W9/+/IyR6SJpcJ31GOPPZZwdWBTufi7rD76zmo4lfuGa0g9Wp/MzExWr17Nnj17WLlyJevWrYtqW1Ddc9OvX78m/73XVGVdwV4CateuHX369LnknzA3N7fmcUZGRs3zjIwMKisrL3mfrKwsqqura57XHTji4tvRFz8HyMvLa9wBNJPz589z1113MX36dO68884LtvXs2ROArl27cscdd7By5UqWLl3KnDlz6NevH/fccw8LFy7kvvvui/p9e/XqRa9evbjqqqsAuPvuuyktLb1k/2jOU3FxMfPnz2fZsmW8//77jB079pKBPWJF5avh5s+fT//+/enSpQvZ2dnceeedvPPOOyHX1+eNN96gsLCQ/Px8IPryBJHPTTzLk0hT03dUdBpaBzaVi7/L6qPvrIZTuW+4htSj4bRv354pU6bwl7/8pUHbEv33Xk3amvXTJCo5OTm8/PLL/OY3v+H3v/99o98nPz+fgwcPcuTIEc6ePcvcuXNrtn344Yc1Ixb9/ve/Z/LkyY3+nDZt2lBeXt7o/RvDOcfDDz9MQUEB3/jGNy7YdvLkyZr0nDx5kjfffJMRI0bwox/9iD179rBz505efPFFbrjhhkvuwoR7327dutG7d282bdoE+D4Lw4YNa1T6jx8/TocOHWjVqhUbN25k+fLljXqfxlD5arg+ffqwfPlyTp06hXOOBQsWUFBQEHJ9ff7whz9w77331jxPlfIk0tT0HRVZY+rApnLxd1lj6DvrUir3DXc59eihQ4c4duwYAKdPn2bevHkMHTo04raGSoSyrmAvju69916uvvpqNm3aRK9evS4YajUvL4+5c+fyxBNPMGfOnEa9f3Z2Nt/97neZMGECU6dOvaCgDhkyhGeeeYaCggKOHj3KF7/4xUYfR6dOnZg0aRIjRoyo6aT7yU9+krKyska/ZyRLly7lt7/9LQsXLqwZBvr1118H4MCBA0yePJnRo0czYcIEbr75ZqZNmxb2/YLpDfe+AD/72c+YPn06o0aNYvXq1XznO99pVPqnTZtGZWUlBQUFPProo41uMhGOylfDhcqzq666irvvvpvCwkJGjhxJdXU1M2bMCLn+4jSePHmSefPmXXL1PZnKk0hTS+XvqEcffTQh68BQeX7xd2qo14X6LmuodP7OUrlvuHB5FqoejVTW9+3bx5QpUxg1ahRXXnklU6dOrZmSK9y2hkqIsh6qM9/lLkALYCXwPrAemBVY3x9YAWwF/gfICazPDTzfGtjeL9JnpMIALfGQaEP8Jnp+JZpEz69EK1/OJX6eJZpEzS80QEvKDdASD83xHZXIxx9r6XzsziXu8avcx1a8jz1c/RjLO3tngRucc6OBMcA0M5sI/BvwhHNuEHAUeDjw+oeBo4H1TwReJyIiIiIiIo0Qs2AvEGhWBJ5mBxYH3AD8MbD+eeD2wOPbAs8JbL/R6us5KpetX79+9Y4qJNIUVL5EJJHpO0rSkcp9+jJ/5y9Gb26WCZQAg4BngMeB5YG7d5hZb+AN59wIM1sHTHPO7Qls2wZc5Zw7fNF7zgBmAOTn54978cUXY5b+xqqoqKiZjFEiU341jPKr4ZRnDZOo+TVlypQS59z4eKcjkSVKHZmoZai5pPPxp/OxQ3ofv449fscern7MiuUHO+eqgDFm1h54GWjcUDYXvudsYDbA+PHjXVFR0eW+ZZMrLi4mEdOVqJRfDaP8ajjlWcMov5JXotSR6V6G0vn40/nYIb2PX8deFO9k1KtZRuN0zh0DFgFXA+3NLBhk9gL2Bh7vBXoDBLa3A440R/pERERERERSTcyCPTPrErijh5m1BKYCH+CDvrsDL3sAeDXweE7gOYHtC10s25iKiIiIiIiksFg24+wOPB/ot5cB/K9zbq6ZbQBeNLPvA+8Bwckyfgn81sy2Ah8B98QwbSIiIiIiIiktZsGec24NMLae9duBCfWsPwN8OlbpERERERERSSfN0mdPREREREREmpeCPRERERERkRSkYE9ERERERCQFKdgTERERERFJQQr2REREREREUpCCPRERERERkRSkYE9ERERERCQFKdgTERERERFJQQr2REREREREUpCCPRERERERkRSUFe8EiIiISAo5dIiep0/Dtm1g5peMjNq/GRmQlVW7ZGfXPjaLd+pFRFKKgj0RERFpOmVlDK6ogNLShu+blQW5ufUvLVv6pVUr/zdDjZNERCJRsCciIiJNp1Mn9rRoQa8ePcA5v1RX1/6trobKSr+cP1/7uO5y8mTkz2nRwgd+rVpB69Z+adPGLzk5uksoIoKCPREREWlKvXqxdetWeo0b17D9nPPB39mz9S+nT8OpU/7v6dNw5oxfPvro0vfKzq4N/tq180v79j5AVBAoImlEwZ6IiIjEn5m/I5eT44O0cKqra4O/U6egosIv5eV+OX8ejh71S105ObWBX7t20LEjtG2rAFBEUpaCPREREUkuGRmQl+eXiznn7wRWVMCJE3D8uF+OHYNz5+DQIb8EZWb6oK/u0qpVsx2KiEgsKdgTERGR1GHmm2u2aAGdO9eud87fDQwGf0eP+iagp05dGgC2bOn37dLFL23a6O6fiCQlBXsiIiKS+sxqB3Tp3r12fbDfX93l9GnYvdsv4EcDDQZ/Xbuq6aeIJA0FeyIiIpK+WrSAHj38Av4OYHl57d2+Q4d8QLh3r1+C++TnQ7du/m9ubvzSLyIShoI9ERERkSAzf+eubVsYONAHfxUVtYHfwYM++Nu1yy8AHTrUBn+dOsU3/SIidSjYa2olJRQePQoLF/oKIyPjwr+ZmX7S2KwsPzR08HF9E8lmZsb7aERERNKbWe38fQMG+ODvxAnYv98vhw/Xjvy5cSPk5DDUzN8FzM/39buISJzE7BvIzHoDvwHyAQfMds49ZWbfAz4PBHtCf8c593pgn28DDwNVwP91zv01VumLlVlz5wIwc9iw+rdv2BB2+wXqBoDBfgatWvmO48HHubnqNyAiItJczGrn7hsyxE8CuiUcCAAAQTZJREFUf+gQHDgAZWVw8iTdAN55x1/o7dattpmomnuKSDOLKtgzs/HAtUAP4DSwDpjnnDsaZrdK4JvOuVIzawOUmNm8wLYnnHM/vugzhgH3AMMDnzPfzK5wzlU16IgSxZQpfh4g5/xSXe2XQLDHqFG+gggu9U0kG9x28mT9k8aCv/sXnDi2TZsLH+fkNN/xioiIpKOsLD/gS/fuMHo0nDjB9iVLGNCiha+7y8r8An5wl969oWdPBX4i0izCBntm9hDwFWAHUAJsAloAk4Fvmdk64J+dcx9evK9zbh+wL/C43Mw+AHqG+bjbgBedc2eBHWa2FZgALGvwUSWCusM912fIkPDbnfOB3tmzvm9AcOLYi5fz52uHkb5Ybm7txLHBv23b+iuNIiIi0rTMmPXkkwDMnDnTj+oZCPZmLVwIGzb4lj2lpb6JZzDwy86Ob7pFJGVFurPXCpjknDtd30YzGwMMBi4J9i56XT9gLLACmAR82czuB1bh7/4dxQeCy+vstod6gkMzmwHMAMjPz6e4uDjCIcRHpHRddrpzciAnh6zqalpWVdGqqoqWgSX4OOvsWd+s5MCBmt2qgVOZmZRnZ3MiK4vy7GxOZmbi4tgUtKKiImHPYyJSfjWc8qxhlF/JK1HqSJWh0PX8R9nZdDh/Hgv0+at+910+ysnhQIsWHM7JiWt93BTS/dyn8/Hr2IvjnYx6hQ32nHPPRNi+OtIHmFlr4E/A15xzJ8zs58C/4vvx/SvwE+Dvok2wc242MBtg/PjxrqioKNpdm0V5eTn79u0jVLrKy8sBQm5vMs75O3/Hjvm7foG/GRUVtK6qonVVFTWzDGVm+pHEOnb0o4h17uyHlW4mxcXFsc+PFKL8ajjlWcMov5JXotSR6VyGQv0OCNb/HW+91bfa2bMHdu8m49AhOp87R+dz5/wdvj59oF8/Xy8nYeCXzuce0vv4dexF8U5GvaLts9cf35yzX919nHOfirBfNj7Q+51z7qXAPgfqbH8OmBt4uhfoXWf3XoF1SeXWW28NG9nfeuutzZMQM8jL80vPOjdIKyt98BecOPbIEd8n8PBhvwS1aeMnjw0uLVs2T7pFRESSWKjfARfU/7m5flqHgQNrJ3DftctfmN22zS9t2/qgr08f1cEi0mjRjsb5CvBL4DV8S8CIzMwC+3zgnPtpnfXdA/35AO7AD/YCMAf4vZn9FD9Ay2BgZZTpk2hlZfm7d3XnATp79sLg7/BhP6FseTls3+5f07q1D/ry8/2iwV9EREQuX8uWcMUVfjl2DHbu9IHfiROwZg2sXetH9BwwwA8Ck4R3+0QkfqIN9s44555u4HtPAv4WWGtmqwPrvgPcG+jr54CdwCMAzrn1Zva/wAb8SJ5fSsaROMvKymqaaoTaDtCjR4/mSlJkubm1I4mBHzX06NHaCWQPH/YTylZUwI4d/jWdOvnKp1u3pG1qIiIi0tRC/Q6Iqv5v3x7GjPEjdu/b5wO/fftql1atoH9/v+hun4hEIdpg7ykzmwm8CZwNrnTOlYbawTm3BKgvAng9zD4/AH4QZZoS0nPPPQeEbq4Z3D5z5sxmS1ODZWTU3v0bOtQHf8eOwcGDtRPIHjnil/Xr/V2+/Hw/h1D37hpVTERE0lao3wENqv8zMnwXjJ49feubnTt9086TJ329u2GD3zZggJ/OQRdcRSSEaIO9kfi7dDdQ24zTBZ5LqsvI8IO3dOzog7/z5/0dv8BIYpw86fsb7N7tK5yuXX0l1KOHrjyKiIhcjtxcP13TFVf4i67btvnpHPbs8Uvr1jBokO/fp4utInKRaIO9TwMDnHPnYpkYSRLZ2T6Q69HDj/pZUeGbl5SV+SAwON1DaakPEHv2hF69fIUkIiIiDWdW22/+9GnfrWL7dl8Hr14N69b55p2DB/vB2UREiD7YWwe0Bw7GLimSlMz8yJ1t2virjmfP+sBv714f8AUHflm71vft693bL61axTvlIiIiyallSxg2zLe2KSuDLVt8F4stW/zSs6cP+jp3VhNPkTQXbbDXHthoZu9yYZ+9sFMvSBrKzfVNSfr189M8HDjgm5mUlflBX44e9aOLde7sg75eveKdYhERkeSUkeHr0V69fP26ZQt8+KG/4Lp3rx/w5YorfH2bkRHv1IpIHEQb7CXwaCKSsLKyajuYV1X5O367d/vALziv3+rVjMzO9ut79PATvIuIiEjDdOgAEybAyJG1c/UdOwYrV/omnldc4Zt5ZkX7009EUkHY/3gzM+ctjvSapk+apJTMzNqrj+fP+4Bv927Yv59O587B8uW+L2CfPr4yat9eTU9EREQaqmVLGDECCgr8Xb5Nm/y8uatX+1E8Bw/2A7povlyRtBDp8s4iM/sT8Kpz7sPgSjPLASYDDwCLgF/HLIVJ5vOf/zwlJSVht6e97Gzo29cvZ8+yZcECBmdn+yuQwauR7dr5pqB9+kCLFvFOsYiISFRC/Q5o9vo/M9NfPO3Xz19g/eAD39Rz/XofAA4Y4O/2adRskZQWKdibBvwd8Acz6w8cA1oCGfg59550zr0X0xQmmR49erB58+aw26WO3Fz2tmrF4KIiH+zt3Am7dsHx4/D++75/X69eMHCgOpqLiEjCC/U7IG71v1ntdEiHDsHGjb4//ebNvo9fv37+LqBG8BRJSWGDPefcGeA/gf80s2ygM3DaOXesGdIm6aZ9exgzBkaN8v37duyo7ee3eze0beuvRGouIRERkYYJzoPbtau/w7dxox9AbccOf6FVQZ9ISop6aCbn3Hnn3D4FeuG99tprYe/svfbaa7z22mvNmKIklJHhr0JOngw33+wrnxYt4MQJ3+fgtddg1SpfWYmIiCSQUL8DEqr+79ABrr4apk3z3SWc80HfG29ASQmcPBnvFIpIE9GQTE2stLQ0qu233nprcyQn+bVq5TuaDxvmh5Hets03Q9mxwy+dOvk+Bz17qomniIjEXajfAQlZ/7dpA1dd5evYDRv8gC7bt/v6tX9/P4+f7vSJJDUFe5IcMjJqJ2Q/ccJXRjt3wpEjsGyZDwoHD/aVk5p4ioiIRC8Y9BUU+IFc6gZ9Awb49RrIRSQpKdiT5NO2re/bN2KEr4i2bPFNTt5/348y1r+/D/x0NVJERCR6bdteGvRt2+Yvrg4eDEOGaMoGkSQTVbBnZncC/wZ0BSywOOdc2ximTSS8rKza+YLKynzQd+iQ/7tlix/Fc+hQ3zdBREREolM36Fu3znej2LjRB35Dh/q6NzMz3qkUkShEe2fv34FbnXMfxDIxIo0SHFa6Z08/aMuWLf5q5J49fsnP95VTly7q1yciIhKttm3hmmt8l4m1a/0F1bVrfT07fLgfwTMj6rH+RCQOog32DijQk6TQoQNMmAAjR/o5hLZt8/MJHTgAHTv6q5TduyvoExERiVanTnD99b4uXbvWz4tbUuInZx85UoOkiSSwsMFeoPkmwCoz+x/gFeBscLtz7qXYJS05de/enfLy8rDbpRm0bAmjR/vgbutWfxXyo49g6VJ/pXLoUD/Yi65IiohIEwr1OyDp638z6NbNt5bZs8c376yo8IOkderk+9J37BjvVIrIRSLd2as7PvAp4ON1njtAwd5FZsyYQXFxcdjt0oxycvyQ0ldc4UcW27zZj+a5cqUfzGXYMD/HkII+ERFpAqF+B6RM/W/mL5b27OkHSVu/3jfzXLAA+vQht6oq3ikUkTrCBnvOuYcAzGySc25p3W1mNimWCRNpUllZPuAbOND359u40V+RfPddP+JYMOhTMxQREZHIMjJ8ndqnj69TN2+GDz9kAvi7fkOGaCokkQQQ7e2Mn0W5TiSxZWb6qRk+8Qm48ko/PUNFhb/T99e/+kDQuXinUkREJDlkZ/t+e9OmQe/eZIK/iPrGG75FjepUkbiK1GfvauAaoIuZfaPOpraAxtytx6xZswAoKioKu33mzJnNlSSpT0aGH0WsTx/YtctXTOXlsGIFbNjgRxnr1Ut3+kREpEFC/Q5I+fo/Lw8mTqS0vJzCjAzfT76kxPebHzMGunaNdwpF0lKkO3s5QGt8UNimznICuDvcjmbW28wWmdkGM1tvZl8NrO9oZvPMbEvgb4fAejOzp81sq5mtMbPCyz04kYgyMvydvmnTYNw4aNXKB33Ll8O8ebBvn65KioiIROlEdjbccANMnOjr1OPHYfFiX6+eOhXv5ImknUh99hYDi83s1865XQ1870rgm865UjNrA5SY2TzgQWCBc+4xM3sUeBT4FnATMDiwXAX8PPBXJPYyMmDAAH+3b+dOf3fv+HFYsgQ6d4ZRo/xoYyIiIhJecBCXHj389AwbN8Lu3VBW5kfJvuIKTcou0kwiNeN8DT/qJlZPczbn3KdC7euc2wfsCzwuN7MPgJ7AbUBR4GXPA8X4YO824DfOOQcsN7P2ZtY98D4izSMY9PXt65uebNwIhw/DwoV+5LERI/zUDSIiIhJeZqYfAK1fP3j//dopG3bu9E07k306CpEkEGnqhR8H/t4JdANeCDy/FzgQ7YeYWT9gLLACyK8TwO0H8gOPewK76+y2J7DugmDPzGYAMwDy8/PDTnMQT5HSlajpjoeKioqEzY/MNm3oc/o0vU6dInPvXtzevexv0YKdrVpxNk5XJRM5vxKV8qxhlF/JK1HqSJWh0PV8qudLuHPfvl07BldUkFdRAUuWcDgnh62tW3Mmhe7ypXPZ17EXxzsZ9YqmGSdm9hPn3Pg6m14zs1XRfICZtQb+BHzNOXei7h1C55wzswZ1iHLOzQZmA4wfP96FGgglXhYvXgyEHqAl0vZ0VFxcnPj5cfo0bNiA7dhB9zNn6H7uHAwe7JujNPPQ0kmRXwlGedYwyq/klSh1ZDqXoVD1fLrU/xHPfXW1bzmzfj2dz52j87FjfpqGgoKUaNqZzmVfx14U72TUK9qpF/LMbEDwiZn1B/Ii7WRm2fhA73fOueAE7AfMrHtge3fgYGD9XqB3nd17BdaJxF/Lln4Al098Anr1Yta6dcx6+WU/tPS2bb7yEhERkfAyMnyfvZtu8l0mqqv9iNh//Svs3x/v1ImknEjNOIO+DhSb2XbAgL7AI+F2MH8L75fAB865n9bZNAd4AHgs8PfVOuu/bGYv4gdmOZ6M/fVuueUWNm3aFHa7JLE2beDqq7nl/Hnf2fzsWSgtrR1aOj8/4luIiEjqCvU7QPX/RVq0gAkTfD/5khI4cQLeftsP7DJmjN8uIpctqmDPOfcXMxsMDA2s2uicOxtht0nA3wJrzWx1YN138EHe/5rZw8Au4DOBba8DnwS2AqeAh6I9iEQybtw4ysvLw26X5Dfuuuv8lAx79sCaNb6Seust6NYNRo/WIC4iImkq1O8A1f8hdO4MU6fC5s1+JOzdu/0dvpEjfSCo+W5FLkuk0ThvcM4tNLM7L9o00Myo0zTzEs65Jfi7gPW5sZ7XO+BLkRIskjDqDi29ZYtvhrJ/Pxw4AAMH+hHIcnPjnUoREZHElpEBQ4f6OrW01NelpaV+1M5x46B9+3inUCRpRbqzdz2wELi1nm0OCBnspauSkhLKysrCbgdd4Ut2F5zHzExfSfXrB+vXw/btvlnnrl1+qoaBA3VlUkQkTYT6HaD6Pwp5eTB5MuzdC++9Bx99BPPn+wHRhg+HrGh7H4lIUKTROGcG/iZlk8p4mDt3blTb9WWf3Oo9jy1a+CuQgwYx68knAZh5/jzs2AFjx/qmKiIiktJC/Q5Q/R8lM+jVy/eBX7fOXzzdvNl3mxg3zneXEJGoRTUap5ltM7PfmdkXzGx4rBMlktTatat93KoVHDsGixbBypVw5kzckiUiIpI0srP9hdIbb/TNOE+d8gO4rFwJ587FO3UiSSPaqReGAb8AOgGPB4K/l2OXLJEU8YlP+LmDMjJ8s8433vBXKDVVg4iISGQdO/qAb+TI2rr0L3/xd/pEJKJog70q4HzgbzV+bryDYfcQEd+/YMQIH/R17w6VlfD++zBvHhzUv5CIiEhEwQFcPv5x3yXi7FlYtgzeeQdOn4536kQSWrQ9XU8Aa4GfAs85547ELkkiKah1a9/pvKwMVq/2UzUsXqz5hERERKLVpg0UFfmB0Nas8QO5HDzopzzq10+DoYnUI9o7e/cCbwH/B3jRzGaZ2SXTJ4hIBD16+Lt8w4f7UTx37/bNUbZv9/P2iYiISGhmfpTrT3zCD9Zy/jysWuXnuj15Mt6pE0k4UQV7zrlXnXP/ADyCn/z8QSD8sJMiUr/MTD8HX92KqqTED+Jy/Hi8UyciIpL4WrXyLWYmTICcHH+H769/9aN36uKpSI2omnGa2Z+A0cA2/B2++4EVMUxX0po5cybFxcVht0vyi3QeozrPwfmE9uzxTTuPHPF9+YYM8YO6aD4hEZGkE+p3gOr/GDCDvn39NA2rV/vWMu+955t3XnmlDwhF0ly0vyZ/BLznnKuKZWJE0o6Z77fXrRusXQvbtsHGjb7CKizUfEIiIiKRtGgBEyf6+flKSmrv8o0Zo758kvaibca5SoGeSAxlZ/vg7oYb/Dx9J0/6+YSWL9dIYyIiItHo1ct3kejZ049+vWoVLFmielTSWrQDtEiUZs+eTUlJSdjts2fPbsYUSSxEOo+NPs+dOsHHPgajRtUO4PLXv8KOHeqDICKSBEL9DlD930xatICrr/Z9+bKzYf9+X4/u2qV6VNKSOgU1sX379l3WdkkOMT3PGRm+316vXlBa6iuqVat84DduXOPfV0REYi7U97/q/2YU7MvXtauvP/fvh5UrfV++wkJNdyRpJao7e2a2IJp1ItKEggO4BEcaO3AA/vpXep4+rauTIiIikbRsCZMnM2vDBmZt2OCDvb/+1Q+MJpImwgZ7ZtbCzDoCnc2sg5l1DCz9gJ7NkkKRdBa8OvmJT/g7fVVVDK6o8NM0lJfHO3UiIiKJre7gLF27wrlzsGyZv9N3/nz80iXSTCLd2XsEKAGGBv4Gl1eB/4ht0kSkRrAPwjXXcDYjw0/T8OabfuTO6up4p05ERCTxXXcdjB3r+8Tv2uXr0UOH4p0qkZiK2IzTOdcf+IFzboBzrn9gGe2cU7An0tx69uTdDh38UNLV1X66hgUL4NixeKdMREQksZnBoEEwdSp06ACnTkFxsa9LdeFUUlSkYO+hwN/bY5wOEYlSZUaGnyz22mv9hLHHjsH8+bB+vSorERGRSNq08VMdFRT4/nwvveQvnJ44Ee+UiTS5SKNxfmBmW4AeZramznoDnHNuVOySlpwKCwvDjrhVWFjYjKmRWIl0HpvlPHfr5vvyrV0LW7fChg1QVuYHdGnXLvafLyIilwj1O0D1f/zUm/cZGTBiBIUffOCbch47BvPmwejRMHCgJmKXlBE22HPO3Wtm3YC/Ap9qniQlt1tvvZXi4uKw2yX5RTqPzXaes7J8/4OePeHdd2vv8g0f7qdvUGUlItKsQv0OUP0fP+Hy/tZPf9oP1LJ6NezcCe+9B/v2wfjxfjRPkSQXTZ+9/YE+ersuXpojgSISha5d4eMfhwEDavvyLVyoETtFREQiyc723SOuvtpPdbR/vx+8Ze/eeKdM5LJFmnrhfwN/15rZmjrL2ouadda373+b2UEzW1dn3ffMbK+ZrQ4sn6yz7dtmttXMNpnZJy73wOKlrKyM8jA/sMvKyigrK2vGFEksRDqPcTnP2dl+0vVrr/VXIz/6yDdJ2bJF8/KJiDSTUL8DVP/HT7i8v2Bbr17+wml+vp+i4Z13/KTslZXNmFqRphXpzt5XA39vAW6tswSfh/NrYFo9659wzo0JLK8DmNkw4B5geGCf/zSzzKiOIME899xzlJaWht3+3HPPNWOKJBYince4nudu3Xxl1bcvVFX5pimLF8PJk/FJj4hIGgn1O0D1f/yEy/tLtrVs6S+ajhnj+/Xt2OG7R2jUa0lSYYM959y+wN+Lm2/uBiZH2Pct4KMo03Eb8KJz7qxzbgewFZgQ5b4icrGcHD9QyzXXQG6u73z+5puwfbvu8omIiIRjBoMHw8c+Bm3b+i4RCxaopYwkpbADtJhZW+BLQE9gDjAP+DLwTeB94HeN+Mwvm9n9wCrgm865o4H3X17nNXsC6+pL0wxgBkB+fn7YwVDiKVK6EjXd8VBRUZG0+RGP89zQ/Mpu3ZornKPLuXNQUsKRtWvZ1KYN5zIidtlNGclcxuJB+ZW8EqWOVBkK/f2f6vmSyOc+XLpCbcvIyWFgixb0PHMGVq/myIYNbGzThvMh6tBEPv5Y07EXxzsZ9Yo09cJvgaPAMuBzwHfw0y7c7pxb3YjP+znwr4AL/P0J8HcNeQPn3GxgNsD48eNdUVFRI5IRO4sXLwYgVLoibU9HxcXFSZcf8TzPjcov52D3bigtpdO5c1xTXu5HGutZ7zWVlJOMZSyelF/JK1HqyHQuQ6G+/9Ol/k/Ecx8u76M+L3v3wrvv0uncOSadPOlbz+TnX/KyRDz+5qJjL4p3MuoVKdgb4JwbCWBm/wXsA/o458405sOccweCj83sOWBu4OleoHedl/YKrBORpmAGffpA585+ioaDB33H8/79fb+ErEhfBSIiImmsZ0/o0AFWrIDDh+Gtt2DoUD/VURq1lJHkE6l0ng8+cM5VAXsaG+gBmFn3Ok/vAIIjdc4B7jGzXDPrDwwGVjb2c0QkhFat4Lrr/KSxwY7n8+bBkSPxTpmIiEhia9UKiop8gAewcSMsWgQVFXFNlkg4kS7njzazE4HHBrQMPDfAOefahtrRzP4AFAGdzWwPMBMoMrMx+GacO4FH8G+0PjDNwwagEvhSILgUkaZmBldc4ZufrFgBx4/7ymrYMH+VUlcoRURE6mfm68uuXX0dGpzmaNw434JGJMGEDfacc42e/sA5d289q38Z5vU/AH7Q2M9LFJ///OcpKSkJu12SX6TzmBTnuV07uPFGWLcONm+G9eth3z646ipo3TreqRMRSUqhfgckRb2QosLlfaPPS+fOMHUqlJTAnj0+8Nu/n0yN1ikJRh11mliPHj3YvHlz2O2S/CKdx6Q5z5mZvklnt26+L1/wCuWYMdCvn7+CKSIiUQv1OyBp6oUUFC7vL+u85OTAxIm+S8Tq1bBrF+MyM/2cfO3bN/59RZqQ2muJiG/S+fGPQ69eUFkJq1bBsmVw9my8UyYiIpK4zGDAgJo5+VpVVfk5+TSvrSQIBXtN7LXXXgt7Z++1117jtddea8YUSSxEOo9JeZ6DVygnTPCjc+7d6ydiP3gw3ikTEUkaoX4HJGW9kCLC5X2TnZe2beHGGylr0QKqq33zzhUr4Pz5yPuKxJCCvSZWWlrKvn37wm4vLS1txhRJLEQ6j0l7ns2gb19/l69TJzhzBhYvhrVrfeUlIiJhhfodkLT1QgoIl/dNel6ystjcpo3v+56V5ee3nT8fjh5tmvcXaQQFeyJyqbw8P7z0sGH+eXB46ZMn45osERGRhNenj2/W2a6dn5Zh4ULYtk3NOiUuFOyJSP0yMvxcQkVF0LKlH7zlzTfhww/jnTIREZHE1qaNH/F6wADfMqa0FJYvV7NOaXYK9kQkvC5dfLPOnj394C0rVviROysr450yERGRxJWZ6effCzbr3LPHj3itZp3SjBTsiUhkOTlw9dVQWOjv+O3cqQrr/2/vzqOkOs87j38futm72QS0oFmFENqF2ATaDMhSsC3F9omPnYwTy9mYzNiJlYmTKMschZk4UTbH2SYxcjyycxw7niSKJcULIKkRspCAbjWbEDtCrC0QCJDYeeaP57a61HRVd0N33dtVv885dai6t5bnvm/RT733vouIiEhHNHfrHDIkhkM8+yxs3apunVIUauyJSMeYwaRJ700vzYkTMb30li1KWCIiIoVUV8P8+ZFHL1yIdflWroQzZ9KOTEqcFlXvYqNGjeL48eMF90vP1149lnQ9Dx4cDb61a2PA+dq1cPAgzJwJ/fqlHZ2ISKry/Q4o6byQcYXKvqj1UlERPWRGjozhEHv3Rg+ZOXNg2LDixSFlRY29LrZw4ULq6uoK7peer716LPl6bk5YNTWxAPuBAzF5y6xZcOWVaUcnIpKafL8DSj4vZFihsk+lXsaMiS6dL70Ujb1nn4WpU+Oqn1nx45GSpm6cInLpamvh3ntjEpfTp2HFCli3TmvyiYiIFFJVBfPmwdVXx1CIV17RbJ3SLdTYE5HLM2AAfOADcOONcUZy82aoq4N33007MhERkeyqqIBbb4XZs1tm61y2DN5+O+3IpISosdfFFi1axPLlywvuX7RoUREjku7QXj2WXT2bwXXXtazJd/hwdOvcty/tyEREiirf74CyywsZUqjsM1EvY8dePPnZrl3pxiQlQ409Eek6w4dHt85Ro6Iryo9/HDOOqVuniIhIfs2LsE+YAOfPxwQua9bEfZHLoMaeiHStvn3hjjvg5pvjit/WrTH4/MSJtCMTERHJrsrKmNl6xoxY03bnzrjKV2CWd5H2qLEnIl3PDKZMicHnAwbEbGNLl8Z4BBEREclv4sS4yldVFeP3li1T/pRLpsaeiHSfK66Ibp21tXDuXCwg29CgbikiIiKFDBkS4/hy86eGRcglUGNPRLpXnz6xYOytt0a3lO3b1S1FRESkPb17R/6cOrVlWIRmu5ZOUmNPRLqfWawlNH8+DBzY0i1l9+60IxMREckuM5g8OYZFNM92vXQpHDiQdmTSQ1SmHUCpuf/++9m8eXPB/dLztVePquc8hg6Nbp319fDGG/Dyy9DUFGctK/XnSER6vny/A5QX0lOo7HtMvTQPi3j5ZTh4EFasiCWPbrghGoQieXTbrysz+zpwP9Dk7jcm24YB/wJMAHYBn3T3I2ZmwF8BHwbeBT7r7g3dFVt3mj59OscLdE+bPn16EaOR7tJePaqeC+jdG267DUaOhFdeidnGDh+OriqDBqUdnYjIZcn3O0B5IT2Fyr5H1UvfvnDXXbBpE2zcGP8ePhw5tV+/tKOTjOrObpyPAwtabXsYeMbdJwPPJI8BPgRMTm4Lgb/vxrhEJG1mcNVVMdtYdTUcOxbdOnfuBPe0oxMREckmM7j+erj77mj8NTVFt85Dh9KOTDKq2xp77v488FarzR8FvpHc/wbwsZzt3/TwEjDEzEZ1V2zdqb6+nn379hXcX19fX8SIpDu0V4+q5w5qnm1s/PiYoXPNGli1KmYeExHpgfL9DlBeSE+hsu+x9VJTE906hw+HU6di4pbNm3XCVC5S7EEyNe6+P7l/AKhJ7tcCb+Q8b0+ybT+tmNlC4uofNTU11NXVdVuwl2L58uUAeeNq3l+oq2e5OXHiRObqsT3t1WN31nNPLK+OuLK6msnHj1Oxezfv7t3LxkGDeKeLxvGVapl1F5VXz5WVHFnO36F8vwPKJf9nse4LlX1X10uxj9+Aif37M+7kSVi3jkOvvcZr1dWc61X8ORizWPfFkuVjT21GBHd3M+v06Qd3XwwsBpgxY4bPnTu3q0O7LM1/NPLF1d7+clRXV9fjyiPNeu6J5dVhx47BypUMOHaMmW+/Hcs1TJx42YPPS7rMuoHKq+fKSo4s5+9Qvr//5ZL/s1j3hcq+q+sltePfuxdWr2b4mTPceepUjIMfOrSoIWSx7osly8de7Gb/webumcm/Tcn2vcDYnOeNSbaJSDkZNCjG8U2YEAvH1tfHzGNnz6YdmYiISHbV1sawiCFD4J134NlnY11bdesse8Vu7D0JPJjcfxD4Xs72z1iYDbyd091TRMpJZSXMnAmzZkFFRSzRsGwZHDmSdmQiIiLZVVUV69ledVWcMG1o0Dh46b7Gnpl9G1gJTDGzPWb2i8CjwL1mthX4YPIY4PvADmAb8Bjw37srLhHpIcaPj8HngwfDiRNxlnLbNp2lFBERyaeiAqZPj+UYKipg9+44YXrsWNqRSUq6bcyeu/9Mnl33tPFcBz7XXbGISA9VXR3dOhsbYceOWJfvzTdhxoxYr09EREQuNm5cdOlcubJleaPp0+NEqpSV4k/VIyLSGblnKSsrYc+eWFPordYru4iIiMh7msfBjxsXyxutWhVj4c+fTzsyKaLUZuMsVY888kjBqVcfeeSR4gUj3aa9elQ9d4Nx42JmsZdegqNHo1vnLbfA1Vdf9mydIiJdJd/vAOWF9BQq+5Kvl8rKGAM/YkT0jtmxI06WzpkTY/yk5OnKnoj0HNXVMfh80qQYu9fYCC++CGfOpB2ZiIhINpnFpC3z58PAgXHCdNmyWK5BSp4aeyLSs1RUwLRpcVayshL27YtunYcPpx2ZiIhIdg0dGsszjB4dSxq9+CKsXRszd0rJUmOviy1evJj6+vqC+xcvXlzEiKQ7tFePquciGDMmZuscOhTefReeew62bNFsnSKSqny/A5QX0lOo7MuuXvr0gdtvj2EQZpE36+oij0pJ0pi9LrZ/f+HlAdvbLz2D6jkjqqpg3jxYvx62bo0zlE1NsU5f375pRyciZSjf33/lhfQUKvuyrBczuOYaGDYsxsEfPhw9ZGbPhpqatKOTLqYreyLSs1VUwNSpcaayd2/Yvz+S1qFDaUcmIiKSXcOHRw+ZmpoY+/7887Bxo3rIlBg19kSkNNTWRtIaNgxOnoxuKa+9pqQlIiKST9++cNddcMMN8fjVV6PRd+pUunFJl1FjT0RKx8CB0a3zmmuikbd+PbzwAr01+FxERKRtZnD99XD33dH4a2pSD5kSosaeiJSWXr1i4Pkdd8RA9AMHmHHkCLz5ZtqRiYiIZFdNTfSQueKKuLJXVwebN6uHTA+nxp6IlKbRo99LWn0vXIiktWmTkpaIiEg+/fvD3LktPWTWrdN6tj2cZuPsYtOmTSs4s9O0adOKGI10l/bqUfWcEQMGwNy5vP797zP+5EnYsCGu8M2aBf36pR2diJSgfL8DlBfSU6jsVS9taO4hM3w4rF4d69kuWxbr2w4dmnZ00klq7HWxBx54gLq6uoL7pedrrx5VzxnSqxc7q6oYP2MGvPwyHDwYYxFuuw1Gjkw7OhEpMfl+BygvpKdQ2ateCqithcGDYeVKOHoUnn02Zr++6qoY5yc9grpxikh5uPJKuO++OFN56hQsX64ppkVERAqpqoL586OBd+ECNDTAqlVw9mzakUkHqbHXxfbt28fx48cL7t+3b18RI5Lu0F49qp4zqn9/+MAH4Lrr4vGrr0aj7+TJdOMSkZKR73eA8kJ6CpW96qUDKipg+vToEVNRAbt3R7fOI0fSjkw6QI29LvbYY4/R0NBQcP9jjz1WxIikO7RXj6rnDOvVC268sWWK6TffjG6dBw+mHZmIlIB8vwOUF9JTqOxVL50wbhx88IPRtfPEiejWuXWreshknBp7IlKemqeYHjECTp+ORWQ3bIhuKiIiInKxQYPgnntg0qTIl42Nmq0z49TYE5Hy1dyt84Yb4vGmTerWKSIiUkhFBUybFrNz9u4ds3UuWcJgjePLJDX2RKS8mcH110ejr18/OHQIliyJ5CUiIiJtGzMmesgMGwYnTzL16FGtZ5tBauyJiEAsw3DvvdG988wZ+PGPY9axc+fSjkxERCSbBg6EefNgyhQMYjjE88/HrNeSCWrsiYg069cP7rorFpM1g+3bY8axo0fTjkxERCSbevWCm29m7eDBMfFZU1P0kDlwIO3IhJQae2a2y8zWm1mjma1Jtg0zs6VmtjX5d2gasYlImTODa66JGceqq+H4cXjmGdiyRV1TRERE8jjSp0/0kBk5MiY+W7EC1q3TxGcpq0zxs+e5+6Gcxw8Dz7j7o2b2cPL4t9MJ7dL98i//MvX19QX3S8/XXj2qnkvAkCHR4Fu7FnbsiH8PHICZM2NiFxGRNuT7HaC8kJ5CZa966WL9+8fSRq+9Bhs3wubNscTRrFlxAlWKLs3GXmsfBeYm978B1NEDG3ujR49my5YtBfdLz9dePaqeS0RlZSwke+WVsGZNrMW3ZEk0+FTHItKGfL8DlBfSU6jsVS/dwAyuuy6WNnrpJXjrrVjP9tZbYcKE2C9FY55CtyQz2wkcARz4qrsvNrOj7j4k2W/AkebHrV67EFgIUFNTM/073/lO0eLuqBMnTlBVVZV2GD2GyqtzVF6d1xVl1uf8ea49fpxhydTSe/v1Y3tVFRdKMGll9Ts2b968enefkXYcWZaVHJnV71CxlPPxl/OxQ3kff1vHXnnhApNPnKDm9GkA3uzTh83V1ZzrVVrThqRd74XyY1qNvVp332tmI4GlwK8CT+Y27szsiLsXHLc3Y8YMX7NmTfcG20lPPfUU+/fvZ+HChXn3AzzwwAPFDCvT6urqmDt3btphdEp79did9dwTyyttXVZm7jF2b/36uD9oENx2W3T5LCFZ/Y6ZmRp7nZBmjszqd6gY8v0OKJf8n8W6L1T2XV0vWTz+Yil47K+/3jLDdb9+0a2zpqao8XWntOu9UH5MpVnt7nuTf5uAJ4BZwEEzGwWQ/NuURmyXq6Ghgf379xfc39DQUMSIpDu0V4+q5xJlBlOmwD33xNiDY8dits5NmzQAXUSA/L8DlBfSU6jsVS9FMn483HcfDB8eyzI8/zw0NsL582lHVvKK3tgzs4FmVt18H7gP2AA8CTyYPO1B4HvFjk1EpEOGDo3JWyZNiit8GzbAc8/FzJ0iIiJysYEDYe5cuPHGOHm6dWvMdv3222lHVtLSuLJXA7xgZmuBVcB/uvsPgUeBe81sK/DB5LGISDZVVsK0abEuX//+LQPQt23TEg0iIiJtaZ68Zf58qKqKht6yZVreqBsVfTZOd98B3NLG9sPAPcWOR0Tkslx5ZXRNeeUV2L07/t27N2bsHDAg7ehERESyZ9iwWJOvsRF27ozljZpzZ5lOcNNdSmsqHBGRNPTpExO1zJkT95uaYomGXbt0plJERKQtlZUwYwbccQf07QuHDkXu3L5dubMLqbEnItJVxoyBn/iJWIPv7FlYvRpWrozB6CIiInKx0aMjd44dGxO2NDTEBC7vvpt2ZCUhS4uql4RRo0ZxvMAkDaNGjSpiNNJd2qtH1XMZ69cPbr89pplu7tLZ1ARTp8ZsZCW4Lp+ItMj3O0B5IT2Fyl71khF9+8Ls2VBbG429pib40Y8id2oh9suixl4XW7hwIXV1dQX3S8/XXj2qnsucWSSnESOgvh4OHoyrfG+8EZO6DByYdoQi0k3y/Q5QXkhPobJXvWTM2LGROxsa4mTpmjWwZ0909+zfP+3oeiR14xQR6S4DB8ZsnTNnQu/ecOBAjEfQjJ0iIiJt69cvxsDfdltL7vzhDzWW7xKpsSci0p2ar/ItWBBj+s6di+6ddXVal09ERKQtZjBuXIzlGzUqcmdDQ+TOY8fSjq5HUWOviy1atIjly5cX3L9o0aIiRiTdob16VD3LRZrPVM6Z8/5ZxzZtggsX0o5ORLpIvt8BygvpKVT2qpeM698/ZuucPbsldy5dChs3xmQu0i419kREimnMmLjKN2FCNPI2bIhGX1NT2pGJiIhkj1mM5VuwACZOjNz56qvR6Dt0KO3oMk+NPRGRYuvTJ8bx3X13LB57/DgsXw4vvwwnT6YdnYiISPb06RMTtcyd25I7n3suJnE5fTrt6DJLjT0RkbTU1MB998GNN0KvXrB7dwxC37pVg9BFRETaMmJE5M7rrourfjt3agKXAtTYExFJU0VFJKwFC1oGoTc2wrJl6p4iIiLSloqKOFF6330wciScORMTuCxbBocPpx1dpqixJyKSBQMHxiD022+HAQPg6NHonrJyJbzzTtrRiYiIZM+gQTEkYs6cmMzl6FF49llYtQpOnUo7ukzQouoiIllhBrW10b1z8+a47dkD+/bB5MlxBbB377SjFBERyQ6zmPzsyivhtdcid77+eizKPmUKXHMNVJZvk6d8j7yb3H///WzevLngfun52qtH1bNclspKuOGGmHVs/foYy7d5M+za1bK9lzpmiGRRvt8BygvpKVT2qpcSUlkZXTsnTIjhEPv3xxIN27e35E6ztKMsOjX2utj06dM5XmCh5OnTpxcxGuku7dWj6lm6xIABcNttcVWvsTHGITQ0wJYtcP31seBsGSYukSzL9ztAeSE9hcpe9VKCqqrgzjtjSaN16+DIEaivj8nPbr45rgCWUe7UqWERkawbNgzmzYtFZauq4MSJGI+wZEl0U9HsYyIiIu83ciTcc0+cNB04EI4dgxdeiPHwBw6UTe7Ulb0uVl9fz759+wruB51J6unaq0fVs3S55kVla2tjLMKrr0bievFFGDo0xvONHl1WZytFsijf7wDlhfQUKnvVS4kzi14wtbXRnXPTpugls2JFnEi94YYYJ1/CuVONvS729NNPd2i//qj0bO3Vo+pZuk2vXjHuYNy4WFto06boovLii1BdHYPRx42LaalFpOjy/Q5QXkhPobJXvZSJioqYqOWqq2DbthgH/9ZbLY2+KVOiQViCjT419kREeqKKCrj66hiIvnNnjOM7fhzWrIENG2Kc38SJ0Ldv2pGKiIhkQ2UlXHtt5M/t22P2zrfeimWOBgxoyZ0lNPO1GnsiIj1ZZWUkp0mT4I03InEdOxazeG7cGNNRT5oEV1xRkmcsRUREOq2yMq7mTZoUM11v2RJr2q5dG7lzwoS4DR2acqCXT409EZFS0KsXjB8fXTgPHIhuKgcOxLINu3fHwrPjxsW4v6qqtKMVERFJX2VlXOWbNCnWtN26Fd58M3Lotm0wZEg0+saOhX790o72kmSusWdmC4C/AiqAr7n7oymHJCLSc5jBqFFxe+cd2LEjunkeOxbdOzdsiPEJzYu3DxmiK34iIlLezCIv1tbC0aORN3fvjvuNjXEbPjwmQhs9Ok6a9pDcmanGnplVAH8H3AvsAVab2ZPu/mq6kYmI9EADB8JNN8VsYwcORDfPvXtjfMJbb0VXzz59IoENGQKDB8OAAfS+cCHtyEVERNIxZAjcemusybdvX8yAffAgHDoUt3Xr4irf8OHRzbOqiuqzZ+H06UyOk89UYw+YBWxz9x0AZvYd4KOAGnsiIpeqV6+Ws5HnzkXD78CBSF7vvhvJLGeq+PH9+6cYrIiISAZUVET3zbFj4ezZyJt790buPHUK9uyJGzAdYuzflClpRtwm8wwtKGhmnwAWuPsvJY9/DrjN3T+f85yFwMLk4RRgc9EDbd9w4FDaQfQgKq/OUXl1nsqsc7JaXuPdfUTaQWRZhnJkVr9DxVLOx1/Oxw7lffw69vTkzY9Zu7LXLndfDCxOO45CzGyNu89IO46eQuXVOSqvzlOZdY7Kq+fKSo4s9+9QOR9/OR87lPfx69izeey90g6glb3A2JzHY5JtIiIiIiIi0glZa+ytBiab2UQz6wP8NPBkyjGJiIiIiIj0OJnqxunu58zs88CPiKUXvu7uG1MO61Kk3oWmh1F5dY7Kq/NUZp2j8pLLVe7foXI+/nI+dijv49exZ1CmJmgRERERERGRrpG1bpwiIiIiIiLSBdTYExERERERKUFq7HUxM1tgZpvNbJuZPZx2PFljZl83syYz25CzbZiZLTWzrcm/Q9OMMUvMbKyZPWdmr5rZRjP7QrJdZdYGM+tnZqvMbG1SXouS7RPN7OXk/+W/JBNAScLMKszsFTN7Onms8pJLVm55sJzzWjnnKOWb8s4dZrbLzNabWaOZrUm2ZfJ7r8ZeFzKzCuDvgA8B1wM/Y2bXpxtV5jwOLGi17WHgGXefDDyTPJZwDvgNd78emA18LvlOqczadhqY7+63AFOBBWY2G/gT4C/d/WrgCPCL6YWYSV8ANuU8VnnJJSnTPPg45ZvXyjlHKd8od8xz96k56+tl8nuvxl7XmgVsc/cd7n4G+A7w0ZRjyhR3fx54q9XmjwLfSO5/A/hYMWPKMnff7+4Nyf3jxB/VWlRmbfJwInnYO7k5MB/412S7yiuHmY0BPgJ8LXlsqLzk0pVdHiznvFbOOarc841yR5sy+b1XY69r1QJv5Dzek2yTwmrcfX9y/wBQk2YwWWVmE4BbgZdRmeWVdCtpBJqApcB24Ki7n0ueov+X7/cV4LeAC8njK1B5yaVTHgxl9ze6HHNUmeebr1DeucOBJWZWb2YLk22Z/N6rsSeZ4rEWiNYDacXMqoB/Ax5y92O5+1Rm7+fu5919KjCGuMpwbboRZZeZ3Q80uXt92rGIlKpy+BtdrjmqXPONcgcAd7r7NKLL+ufM7O7cnVn63mdqUfUSsBcYm/N4TLJNCjtoZqPcfb+ZjSLOkEnCzHoTSfRb7v7vyWaVWTvc/aiZPQfMAYaYWWVyxlH/L1vcAfykmX0Y6AcMAv4KlZdcOuXBUDZ/o5WjyjLflH3ucPe9yb9NZvYE0djP5PdeV/a61mpgcjIbUR/gp4EnU46pJ3gSeDC5/yDwvRRjyZSkD/w/Apvc/cs5u1RmbTCzEWY2JLnfH7iXGEPyHPCJ5Gkqr4S7/467j3H3CcTfq2fd/dOovOTSKQ+GsvgbXc45qpzzTbnnDjMbaGbVzfeB+4ANZPR7b3GVUbpKcpbjK0AF8HV3/1K6EWWLmX0bmAsMBw4CjwD/AXwXGAe8DnzS3VsPdi9LZnYnsAJYT0u/+N8lxkSozFoxs5uJQdEVxMms77r7/zKzq4iJIoYBrwA/6+6n04s0e8xsLvBFd79f5SWXo9zyYDnntXLOUco3oRxzR3KcTyQPK4F/dvcvmdkVZPB7r8aeiIiIiIhICVI3ThERERERkRKkxp6IiIiIiEgJUmNPRERERESkBKmxJyIiIiIiUoLU2BMRERERESlBauwJZnbezBrNbKOZrTWz3zCzXsm+GWb21wVeO8HM/kvxou0YM9tlZsOL/Jkv5tz/s6Q8/8zMPmtmo/O85tqk7F8xs0nFi/bymNnvdvP7LzCzVWb2WlI+/2Jm45J9j5vZXjPrmzwebma7kvu9zOyvzWyDma03s9VmNjHZ9wvJtnXJ/o/m+eyHzOwzyf06M5txicdwk5k9fimvFZHyo1zcZZ+Z2VycxOBm9sGcbR9Ltn0iefxe3knKrzlvLTez8Xne18zsWTMblHwXNlxGjH9uZvMv9fWSPWrsCcBJd5/q7jcQi4J+iFgnCHdf4+6/VuC1E4DMJZhiMrNKAHe/PWfzQuBmd/9N4LNAmwkG+Bjwr+5+q7tvz3lPa07yGdXpxp6ZVXTweTcCfwM86O7XuvtU4FvEd63ZeeAX2nj5p4iyvtndbwI+Dhw1szHA7wF3uvvNwGxgXRufXZm87z938LDycvf1wJjmRqqISDuUiy9DD8rF64mFyJv9DLC2wPPnJXmrDvj9PM/5MLDW3Y91QXx/AzzcBe8jGZHlH5OSAndvIv44fj75IzfXzJ4GMLMPJGe+ms9+VQOPAncl2349OaO0wswaktvtyWvnJmer/jW5WvMtM7Nk30wzezE5k7nKzKrNrCI5E7c6OaP1X9uK18z+w8zqkzN3C/M8538kV3I2mNlDybYJZrbJzB5LXrvEzPrnxLMuOaY/a+sMWXI8K8zsSeDVZNuJ5N8ngSqg3sw+BcwAvpW8X/+c9/gw8BDw38zsuSSmzWb2TWADMLb585Mze5/K+ezlZvY9M9thZo+a2aeTslvf1lnJZPuQpE4PW8uVq2+a2b35ytvMRpnZ80nsG8zsLjN7FOifbPtW8ryfTT6/0cy+2tywM7MTZvYXZrYWmJM8/lJS1y+ZWU0bVfbbwB+5+6bmDe7+pLs/n/OcrwC/3pzcc4wC9rv7heR1e9z9CDASOA6cSLafcPedbXz2fKDB3c+1Kr9eFlcU/zDnuJrPGC8zs1nJ93uHmf1kzkuf4v1JXUSkXcrFpZmLEyuAWWbW28yqgKuBxjzPzbUSqM2z79PA99oon6uS78hMi6uK/2FmSy2uGH4+qZNXknw8DMDdXweuMLMrOxCT9ATurluZ34ATbWw7CtQAc4Gnk21PAXck96uAytz9yfYBQL/k/mRgTXJ/LvA2MIY4ybASuBPoA+wAZibPG5S870Lg95NtfYE1wMQ24hyW/Nuf+KN8RfJ4FzAcmE6cRRuYxLwRuJU4C3oOmJo8/7vAzyb3NwBzkvuPAhva+Ny5wDu5MeWWY6v7dcCMPGX/B8AXk/sTgAvA7OTxTwFLgYqkLnYTjZm5Sf2MSspmL7Aoec0XgK+08Tn/AHwEuBFYDTyWbN+alE2b5Q38BvB7yfYKoLqN47su+W70Th7/H+AzyX0HPpnzXAceSO7/afNntoq1AbilwPf1ceATwNeBn0/qeVeyb0xS943AXwC35sT+o6QM/29zDG289yLgV1vV3Wzg283lkHMcH0ruPwEsAXoDtwCNOc+7A3gq7f/juummW/ZvKBdD6efizwJ/C3wZuJ9opD1Cktdax9lcfsn9rwAL88T/Oi35eUJSdlOAV0jyafLZ24BqYETyPfiVZN9fAg/lvN9jwE+l/X9Ct6656cqedMaPgS+b2a8BQ7zV1Y9Eb+AxM1sP/D/g+px9qzyutFwgfoxPIP4Y7Xf31QDufix53/uAz5hZI/AycAWRsFr7teSq0UvA2DaecyfwhLu/4+4ngH8H7kr27XT3xuR+PTDBzIYQfzBXJtsLdedb5W1fHbocr7v7S8n9O4Fvu/t5dz8ILAdmJvtWu/t+dz8NbCcaGxDJdEIb77sCuDu5/T1wk5nVAkfc/R3yl/dq4OfN7A+Am9z9eBvvfQ+RyFcnr78HuCrZdx74t5znngGeTu7X54n1PWZ2RXIWdouZfbHV7j8GfpOcHgruvof4Tv0OkayfMbN73P08sIBoJG4B/jI5ptZGAW+22vZV4kfGl1odxw+T++uB5e5+lovLv4n83YZERC6FcvH79aRc3Ow7RK+PnyZOJhbynJntJbr15nvusFb5eQRxpe/T7p7bRfQ5dz/u7m8Sjb2n8sSr3FVC1NiTi5jZVcSP9Kbc7e7+KPBLxJm7H5vZtW28/NeBg8QVjhnE2cJmp3PunyfOGuYNg7jCMjW5TXT3Je97gtlc4IPEmb9biDNY/do9wEuLpy3vdPL5XfmeubFfyHl8gbaP43kisd5FnDV8k2j4rEj2t1neHl0n7ybOWD5uSffPVgz4Rs5rp7j7HyT7TiUNrWZn3eO0IfnLfCMwDcDdD3uM2VtMnA1+j7tvJX6ofLLV9tPu/gOPMRp/RIzFwMMqd/9jIsH+VBuffZKLv0MvAvPMLHd77nG8V/7Jj6fcY+qXvKeISKcoF3dYT8rFALj7KuAm4qrdlnY+Yx4wnsh3i/I855y9f2zh28QVyDsvMV7lrhKixp68j5mNILr8/W3Oj9nmfZPcfb27/wlxxedaYhxUdc7TBtMyZurniG4PhWwGRpnZzOQzqi3GYf2I6D/fO9l+jZkNbPXawcSVqXeTZDe7jfdfAXzMzAYkr/84LQ2ci7j7UeC4md2WbOqK8Vaty6ijVgCfSsZMjCAaXasuJQB3f4PoSjPZ3XcALwBfJBqBkKe8LWb+OujujwFfI2mEAWebnws8A3zCzEYmrx1meWYM66A/BX7PzK7L2TYgz3O/lBwHyWdPs2S2tSTx3Qy8bmajzWxazuumEt1eWttEjJ/I9Y/A94Hv2sVjBNtzDdGdRkSkw5SLSzMXt/IwHZzsLLnK+hBxlXVYG0/ZTEuPGojeJx9Pnn8pE/cod5WQzv5wkdLUP+mi0ZvoO/9PRH/y1h4ys3nEGaCNwA+S++eT7huPE+O1/i25AvRD2jk75u5nksHOf5MMmD5JnCH8GtGloMHMjLgS9bFWL/8h8Ctmton4Q/dSq/24e4PF9PfNf5i/5u6vmNmEAmH9ItH95QLRXePtQsfQAY8D/2BmJ4kznx09W/YEMIeYpcuB33L3A3nO4nbEy7Qk/BVEN8gXksf5ynsu8JtmdpaY3KT5yt5iYJ2ZNbj7p83s94ElSQPrLPA52m5Mtcvd15vZF4Bvmtkg4BBxhvKRNp670cwaaGmEjiTqrm/yeBUxPqIG+POkIXgqOb5faePjf0B8/1t/zpfNbDDwT2b26U4czjzgPzvxfBEpX8rF71equRgAd/9BJ5+/38y+TeTX/91q938S+XpbzvPfMbP7gaWWTFrTEUnD/mpifKaUAGt1wkik7JlZVTKmADN7GBjl7l9IOSwpEjN7gkjmWy/zffoSP1DuzDOmRkRE8lAu7jgzGwV8093v7YL3+jgwzd3/5+VHJlmgbpwiF/tIMinIBmKM2x+mHZAU1cPERC2XaxzwsBp6IiKXRLm4g9x9P3EVdFAXvF0lMZu1lAhd2RMRERERESlBurInIiIiIiJSgtTYExERERERKUFq7ImIiIiIiJQgNfZERERERERKkBp7IiIiIiIiJej/Aw/SHpeQim1ZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ftsz=10\n",
    "\n",
    "fig = plt.subplots(3,2,figsize=(15,15),sharey=True)\n",
    "\n",
    "#-----------------------------------------------------\n",
    "ax1=plt.subplot(3,2,1)\n",
    "   \n",
    "rift_len = 40\n",
    "xx = np.arange(0,rift_len,0.01)\n",
    "w1 = 254.5 #rate m/yr\n",
    "r = np.sqrt(rift_len**2 - xx**2)\n",
    "\n",
    "n=1\n",
    "\n",
    "pl_t1 = ax1.plot(xx,(w1 * ((r/rift_len)**n)),'-',linewidth=2,color=(1,2/3,2/3),label='1 year')\n",
    "    \n",
    "ax1.plot([0,0],[0,w1],'--',color='0.5',linewidth=2)\n",
    "ax1.plot([1,1],[0,(w1 * ((r/rift_len)**n))[100]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "#test fit at GNSS\n",
    "ax1.plot([16,16],[0,(w1 * ((r/rift_len)**n))[1600]],'--',color='0.5',linewidth=2)\n",
    "ax1.plot([17,17],[0,(w1 * ((r/rift_len)**n))[1700]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "ax1.set_xlim(-5,45)\n",
    "ax1.set_ylim(0,400)\n",
    "ax1.grid('on')\n",
    "    \n",
    "ax1.annotate('GNSS w meas.: 254.5 ma$^{-1}$',(1,365),fontsize=ftsz)    \n",
    "ax1.annotate('GNSS w model: '+str(round((w1 * ((r/rift_len)**n))[0],2))+' ma$^{-1}$',(1,335),fontsize=ftsz)\n",
    "ax1.annotate('1km up rift:       '+str(round((w1 * ((r/rift_len)**n))[100],2))+' ma$^{-1}$',(1,305),fontsize=ftsz)\n",
    "ax1.annotate('GNSS e meas.: 175.4 ma$^{-1}$',(21,365),fontsize=ftsz)\n",
    "ax1.annotate('GNSS e model: '+str(round((w1 * ((r/rift_len)**n))[1600],2))+' ma$^{-1}$',(21,335),fontsize=ftsz)\n",
    "ax1.annotate('1km up rift:      '+str(round((w1 * ((r/rift_len)**n))[1700],2))+' ma$^{-1}$',(21,305),fontsize=ftsz)  \n",
    "    \n",
    "ax1.set_ylabel('Rift width (m)')   \n",
    "ax1.set_title('Rift width model (flow law n=1)',fontsize=ftsz)  \n",
    "\n",
    "#-----------------------------------------------------\n",
    "ax2=plt.subplot(3,2,3)\n",
    "\n",
    "n=2\n",
    "\n",
    "pl_t1 = ax2.plot(xx,(w1 * ((r/rift_len)**n)),'-',linewidth=2,color=(1,2/3,2/3),label='1 year')\n",
    "    \n",
    "ax2.plot([0,0],[0,w1],'--',color='0.5',linewidth=2)\n",
    "ax2.plot([1,1],[0,(w1 * ((r/rift_len)**n))[100]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "#test fit at GNSS\n",
    "ax2.plot([16,16],[0,(w1 * ((r/rift_len)**n))[1600]],'--',color='0.5',linewidth=2)\n",
    "ax2.plot([17,17],[0,(w1 * ((r/rift_len)**n))[1700]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "ax2.set_xlim(-5,45)\n",
    "ax2.set_ylim(0,400)\n",
    "ax2.grid('on')\n",
    "    \n",
    "ax2.annotate('GNSS w meas.: 254.5 ma$^{-1}$',(1,365),fontsize=ftsz)    \n",
    "ax2.annotate('GNSS w model: '+str(round((w1 * ((r/rift_len)**n))[0],2))+' ma$^{-1}$',(1,335),fontsize=ftsz)\n",
    "ax2.annotate('1km up rift:       '+str(round((w1 * ((r/rift_len)**n))[100],2))+' ma$^{-1}$',(1,305),fontsize=ftsz)\n",
    "ax2.annotate('GNSS e meas.: 175.4 ma$^{-1}$',(21,365),fontsize=ftsz)\n",
    "ax2.annotate('GNSS e model: '+str(round((w1 * ((r/rift_len)**n))[1600],2))+' ma$^{-1}$',(21,335),fontsize=ftsz)\n",
    "ax2.annotate('1km up rift:      '+str(round((w1 * ((r/rift_len)**n))[1700],2))+' ma$^{-1}$',(21,305),fontsize=ftsz)  \n",
    "\n",
    "ax2.set_ylabel('Rift width (m)')\n",
    "ax2.set_title('Rift width model (flow law n=2)',fontsize=ftsz)\n",
    "\n",
    "#-----------------------------------------------------\n",
    "ax3=plt.subplot(3,2,5)\n",
    "\n",
    "n=3\n",
    "\n",
    "pl_t1 = ax3.plot(xx,(w1 * ((r/rift_len)**n)),'-',linewidth=2,color=(1,2/3,2/3),label='1 year')\n",
    "    \n",
    "ax3.plot([0,0],[0,w1],'--',color='0.5',linewidth=2)\n",
    "ax3.plot([1,1],[0,(w1 * ((r/rift_len)**n))[100]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "#test fit at GNSS\n",
    "ax3.plot([16,16],[0,(w1 * ((r/rift_len)**n))[1600]],'--',color='0.5',linewidth=2)\n",
    "ax3.plot([17,17],[0,(w1 * ((r/rift_len)**n))[1700]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "ax3.set_xlim(-5,45)\n",
    "ax3.set_ylim(0,400)\n",
    "ax3.grid('on')\n",
    "    \n",
    "ax3.annotate('GNSS w meas.: 254.5 ma$^{-1}$',(1,365),fontsize=ftsz)    \n",
    "ax3.annotate('GNSS w model: '+str(round((w1 * ((r/rift_len)**n))[0],2))+' ma$^{-1}$',(1,335),fontsize=ftsz)\n",
    "ax3.annotate('1km up rift:       '+str(round((w1 * ((r/rift_len)**n))[100],2))+' ma$^{-1}$',(1,305),fontsize=ftsz)\n",
    "ax3.annotate('GNSS e meas.: 175.4 ma$^{-1}$',(21,365),fontsize=ftsz)\n",
    "ax3.annotate('GNSS e model: '+str(round((w1 * ((r/rift_len)**n))[1600],2))+' ma$^{-1}$',(21,335),fontsize=ftsz)\n",
    "ax3.annotate('1km up rift:      '+str(round((w1 * ((r/rift_len)**n))[1700],2))+' ma$^{-1}$',(21,305),fontsize=ftsz)  \n",
    "\n",
    "ax3.set_ylabel('Rift width (m)')\n",
    "ax3.set_xlabel('Distance along rift from western GNSS (km)')\n",
    "ax3.set_title('Rift width model (flow law n=3)',fontsize=ftsz)\n",
    "\n",
    "#-----------------------------------------------------\n",
    "ax4=plt.subplot(3,2,2)\n",
    " \n",
    "rift_len = 50\n",
    "xx = np.arange(0,rift_len,0.01)\n",
    "r = np.sqrt(rift_len**2 - xx**2)    \n",
    " \n",
    "n=1\n",
    "w1=259.75\n",
    "   \n",
    "pl_t1 = ax4.plot(xx,(w1 * ((r/rift_len)**n)),'-',linewidth=2,color=(1,2/3,2/3),label='1 year')\n",
    "    \n",
    "ax4.plot([10,10],[0,(w1 * ((r/rift_len)**n))[1100]],'--',color='0.5',linewidth=2)\n",
    "ax4.plot([11,11],[0,(w1 * ((r/rift_len)**n))[1100]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "#test fit at GNSS\n",
    "ax4.plot([26,26],[0,(w1 * ((r/rift_len)**n))[2600]],'--',color='0.5',linewidth=2)\n",
    "ax4.plot([27,27],[0,(w1 * ((r/rift_len)**n))[2700]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "ax4.set_xlim(-5,55)\n",
    "ax4.set_ylim(0,400)\n",
    "ax4.grid('on')\n",
    "    \n",
    "ax4.annotate('GNSS w meas.: 254.5 ma$^{-1}$',(1,365),fontsize=ftsz)    \n",
    "ax4.annotate('GNSS w model: '+str(round((w1 * ((r/rift_len)**n))[1000],2))+' ma$^{-1}$',(1,335),fontsize=ftsz)\n",
    "ax4.annotate('1km up rift:       '+str(round((w1 * ((r/rift_len)**n))[1100],2))+' ma$^{-1}$',(1,305),fontsize=ftsz)\n",
    "ax4.annotate('GNSS e meas.: 175.4 ma$^{-1}$',(31,365),fontsize=ftsz)\n",
    "ax4.annotate('GNSS e model: '+str(round((w1 * ((r/rift_len)**n))[2600],2))+' ma$^{-1}$',(31,335),fontsize=ftsz)\n",
    "ax4.annotate('1km up rift:      '+str(round((w1 * ((r/rift_len)**n))[2700],2))+' ma$^{-1}$',(31,305),fontsize=ftsz)  \n",
    "    \n",
    "ax4.set_title('Rift width model (flow law n=1)',fontsize=ftsz)    \n",
    "    \n",
    "#-----------------------------------------------------\n",
    "ax5=plt.subplot(3,2,4)\n",
    "\n",
    "n=2\n",
    "w1=265.1\n",
    "   \n",
    "pl_t1 = ax5.plot(xx,(w1 * ((r/rift_len)**n)),'-',linewidth=2,color=(1,2/3,2/3),label='1 year')\n",
    "    \n",
    "ax5.plot([10,10],[0,(w1 * ((r/rift_len)**n))[1100]],'--',color='0.5',linewidth=2)\n",
    "ax5.plot([11,11],[0,(w1 * ((r/rift_len)**n))[1100]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "#test fit at GNSS\n",
    "ax5.plot([26,26],[0,(w1 * ((r/rift_len)**n))[2600]],'--',color='0.5',linewidth=2)\n",
    "ax5.plot([27,27],[0,(w1 * ((r/rift_len)**n))[2700]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "ax5.set_xlim(-5,55)\n",
    "ax5.set_ylim(0,400)\n",
    "ax5.grid('on')\n",
    "    \n",
    "ax5.annotate('GNSS w meas.: 254.5 ma$^{-1}$',(1,365),fontsize=ftsz)    \n",
    "ax5.annotate('GNSS w model: '+str(round((w1 * ((r/rift_len)**n))[1000],2))+' ma$^{-1}$',(1,335),fontsize=ftsz)\n",
    "ax5.annotate('1km up rift:       '+str(round((w1 * ((r/rift_len)**n))[1100],2))+' ma$^{-1}$',(1,305),fontsize=ftsz)\n",
    "ax5.annotate('GNSS e meas.: 175.4 ma$^{-1}$',(31,365),fontsize=ftsz)\n",
    "ax5.annotate('GNSS e model: '+str(round((w1 * ((r/rift_len)**n))[2600],2))+' ma$^{-1}$',(31,335),fontsize=ftsz)\n",
    "ax5.annotate('1km up rift:      '+str(round((w1 * ((r/rift_len)**n))[2700],2))+' ma$^{-1}$',(31,305),fontsize=ftsz)  \n",
    "\n",
    "\n",
    "\n",
    "ax5.set_title('Rift width model (flow law n=2)',fontsize=ftsz)\n",
    "\n",
    "#-----------------------------------------------------\n",
    "ax6=plt.subplot(3,2,6)\n",
    "\n",
    "n=3\n",
    "w1=270.575\n",
    "   \n",
    "pl_t1 = ax6.plot(xx,(w1 * ((r/rift_len)**n)),'-',linewidth=2,color=(1,2/3,2/3),label='1 year')\n",
    "    \n",
    "ax6.plot([10,10],[0,(w1 * ((r/rift_len)**n))[1100]],'--',color='0.5',linewidth=2)\n",
    "ax6.plot([11,11],[0,(w1 * ((r/rift_len)**n))[1100]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "#test fit at GNSS\n",
    "ax6.plot([26,26],[0,(w1 * ((r/rift_len)**n))[2600]],'--',color='0.5',linewidth=2)\n",
    "ax6.plot([27,27],[0,(w1 * ((r/rift_len)**n))[2700]],'--',color='0.5',linewidth=2)\n",
    "    \n",
    "ax6.set_xlim(-5,55)\n",
    "ax6.set_ylim(0,400)\n",
    "ax6.grid('on')\n",
    "\n",
    "ax6.annotate('GNSS w meas.: 254.5 ma$^{-1}$',(1,365),fontsize=ftsz)    \n",
    "ax6.annotate('GNSS w model: '+str(round((w1 * ((r/rift_len)**n))[1000],2))+' ma$^{-1}$',(1,335),fontsize=ftsz)\n",
    "ax6.annotate('1km up rift:       '+str(round((w1 * ((r/rift_len)**n))[1100],2))+' ma$^{-1}$',(1,305),fontsize=ftsz)\n",
    "ax6.annotate('GNSS e meas.: 175.4 ma$^{-1}$',(31,365),fontsize=ftsz)\n",
    "ax6.annotate('GNSS e model: '+str(round((w1 * ((r/rift_len)**n))[2600],2))+' ma$^{-1}$',(31,335),fontsize=ftsz)\n",
    "ax6.annotate('1km up rift:      '+str(round((w1 * ((r/rift_len)**n))[2700],2))+' ma$^{-1}$',(31,305),fontsize=ftsz)  \n",
    "\n",
    "ax6.set_title('Rift width model (flow law n=3)',fontsize=ftsz)\n",
    "ax6.set_xlabel('Distance along rift from MIR (km)')\n",
    "\n",
    "\n",
    "ax1.annotate(\"a\",(-5+2.5,400-40),ha='center',fontsize=16,fontweight='bold')\n",
    "ax2.annotate(\"b\",(-5+2.5,400-40),ha='center',fontsize=16,fontweight='bold')\n",
    "ax3.annotate(\"c\",(-5+2.5,400-40),ha='center',fontsize=16,fontweight='bold')\n",
    "ax4.annotate(\"d\",(-5+3,400-40),ha='center',fontsize=16,fontweight='bold')\n",
    "ax5.annotate(\"e\",(-5+3,400-40),ha='center',fontsize=16,fontweight='bold')\n",
    "ax6.annotate(\"f\",(-5+3,400-40),ha='center',fontsize=16,fontweight='bold')\n",
    "\n",
    "output = figure_folder+'/figS15_upstream_1km.png'\n",
    "plt.savefig(output, dpi=100, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba4ee2dc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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