{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This script plots up meteorological weather station data from the August 10th Derecho event that impacted the Midwest. This is the programming 2nd programming assignment for **Atmos 5340**. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from datetime import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          Station_ID  air_temp_[C]  relative_humidity_[%]  \\\n",
      "Date_Time                                                                   \n",
      "2020-08-09 12:00:00+00:00      IA061         22.01                   95.0   \n",
      "2020-08-09 12:10:00+00:00      IA061         22.01                   95.0   \n",
      "2020-08-09 12:20:00+00:00      IA061         21.91                   95.0   \n",
      "2020-08-09 12:30:00+00:00      IA061         22.01                   95.0   \n",
      "2020-08-09 12:40:00+00:00      IA061         22.11                   95.0   \n",
      "...                              ...           ...                    ...   \n",
      "2020-08-11 11:20:00+00:00      IA061         17.41                   95.0   \n",
      "2020-08-11 11:30:00+00:00      IA061         17.51                   95.0   \n",
      "2020-08-11 11:40:00+00:00      IA061         17.61                   95.0   \n",
      "2020-08-11 11:50:00+00:00      IA061         17.81                   95.0   \n",
      "2020-08-11 12:00:00+00:00      IA061         17.91                   95.0   \n",
      "\n",
      "                           wind_speed_[m/s]  wind_direction_[degrees]  \\\n",
      "Date_Time                                                               \n",
      "2020-08-09 12:00:00+00:00              3.33                     190.0   \n",
      "2020-08-09 12:10:00+00:00              2.78                     185.0   \n",
      "2020-08-09 12:20:00+00:00              3.61                     170.0   \n",
      "2020-08-09 12:30:00+00:00              3.33                     165.0   \n",
      "2020-08-09 12:40:00+00:00              5.00                     205.0   \n",
      "...                                     ...                       ...   \n",
      "2020-08-11 11:20:00+00:00              0.83                     265.0   \n",
      "2020-08-11 11:30:00+00:00              0.56                     320.0   \n",
      "2020-08-11 11:40:00+00:00              1.39                     260.0   \n",
      "2020-08-11 11:50:00+00:00              1.39                     300.0   \n",
      "2020-08-11 12:00:00+00:00              0.56                     300.0   \n",
      "\n",
      "                           wind_gust_[m/s]  \n",
      "Date_Time                                   \n",
      "2020-08-09 12:00:00+00:00             5.00  \n",
      "2020-08-09 12:10:00+00:00             5.83  \n",
      "2020-08-09 12:20:00+00:00             6.38  \n",
      "2020-08-09 12:30:00+00:00             7.50  \n",
      "2020-08-09 12:40:00+00:00             6.66  \n",
      "...                                    ...  \n",
      "2020-08-11 11:20:00+00:00             1.94  \n",
      "2020-08-11 11:30:00+00:00             1.67  \n",
      "2020-08-11 11:40:00+00:00             1.67  \n",
      "2020-08-11 11:50:00+00:00             1.94  \n",
      "2020-08-11 12:00:00+00:00             1.94  \n",
      "\n",
      "[282 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "#Lets read in our meteorological data\n",
    "stat1 = pd.read_csv('./class_files/pHW2_IA061.csv',sep=',',skiprows=6,index_col=1,parse_dates=True)\n",
    "\n",
    "#Check our data\n",
    "print(stat1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#And lets convert our time from UTC to Central \n",
    "stat1.index = stat1.index.tz_convert('US/Central')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          Station_ID  air_temp_[C]  relative_humidity_[%]  \\\n",
      "Date_Time                                                                   \n",
      "2020-08-09 07:00:00-05:00      IA061         22.01                   95.0   \n",
      "2020-08-09 07:10:00-05:00      IA061         22.01                   95.0   \n",
      "2020-08-09 07:20:00-05:00      IA061         21.91                   95.0   \n",
      "2020-08-09 07:30:00-05:00      IA061         22.01                   95.0   \n",
      "2020-08-09 07:40:00-05:00      IA061         22.11                   95.0   \n",
      "...                              ...           ...                    ...   \n",
      "2020-08-11 06:20:00-05:00      IA061         17.41                   95.0   \n",
      "2020-08-11 06:30:00-05:00      IA061         17.51                   95.0   \n",
      "2020-08-11 06:40:00-05:00      IA061         17.61                   95.0   \n",
      "2020-08-11 06:50:00-05:00      IA061         17.81                   95.0   \n",
      "2020-08-11 07:00:00-05:00      IA061         17.91                   95.0   \n",
      "\n",
      "                           wind_speed_[m/s]  wind_direction_[degrees]  \\\n",
      "Date_Time                                                               \n",
      "2020-08-09 07:00:00-05:00              3.33                     190.0   \n",
      "2020-08-09 07:10:00-05:00              2.78                     185.0   \n",
      "2020-08-09 07:20:00-05:00              3.61                     170.0   \n",
      "2020-08-09 07:30:00-05:00              3.33                     165.0   \n",
      "2020-08-09 07:40:00-05:00              5.00                     205.0   \n",
      "...                                     ...                       ...   \n",
      "2020-08-11 06:20:00-05:00              0.83                     265.0   \n",
      "2020-08-11 06:30:00-05:00              0.56                     320.0   \n",
      "2020-08-11 06:40:00-05:00              1.39                     260.0   \n",
      "2020-08-11 06:50:00-05:00              1.39                     300.0   \n",
      "2020-08-11 07:00:00-05:00              0.56                     300.0   \n",
      "\n",
      "                           wind_gust_[m/s]  \n",
      "Date_Time                                   \n",
      "2020-08-09 07:00:00-05:00             5.00  \n",
      "2020-08-09 07:10:00-05:00             5.83  \n",
      "2020-08-09 07:20:00-05:00             6.38  \n",
      "2020-08-09 07:30:00-05:00             7.50  \n",
      "2020-08-09 07:40:00-05:00             6.66  \n",
      "...                                    ...  \n",
      "2020-08-11 06:20:00-05:00             1.94  \n",
      "2020-08-11 06:30:00-05:00             1.67  \n",
      "2020-08-11 06:40:00-05:00             1.67  \n",
      "2020-08-11 06:50:00-05:00             1.94  \n",
      "2020-08-11 07:00:00-05:00             1.94  \n",
      "\n",
      "[282 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "#print our times again...\n",
    "print(stat1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets convert our variables to English units from Metric for each station\n",
    "stat1['wind_speed_[m/s]'] = stat1['wind_speed_[m/s]']*2.23694     #m/s to mph\n",
    "stat1['wind_gust_[m/s]'] = stat1['wind_gust_[m/s]']*2.23694       #m/s to mph\n",
    "stat1['air_temp_[C]'] = (stat1['air_temp_[C]']*(9/5)) + 32        #C to F\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "85.1\n",
      "2020-08-10 13:50:00-05:00\n"
     ]
    }
   ],
   "source": [
    "#Determine time and speed of maximum wind gust\n",
    "max_gust = str(round(np.max(stat1['wind_gust_[m/s]']),1))\n",
    "max_gust_t = str(stat1.index[np.argmax(stat1['wind_gust_[m/s]'])])\n",
    "\n",
    "print(max_gust)\n",
    "print(max_gust_t)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lets subset data for day of derecho\n",
    "stat1 = stat1[(stat1.index >= '2020-08-10 00:00:00') & (stat1.index < '2020-08-11 00:00:00')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa185c8c7f0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SSy/x7bffcsYZZ/D777+zfv16+vTpQ2xsLA89dOS9uZNdd4IbyPTp0znrrLOYP38+u3fv5o477mDUqFGsWbPGU2fcuHEsWbKEyZMn07NnT1asWMEVV1xR7vhFRKQCUlMhLw8KCpxjamq19uKGJoYS3j2c3LW5RPSJUHIrUl7uX1Ll5UFYGKxaVa1/h8vqzTff5JJLLmH48OEsXLiQgoICpk+fTnJyMt9//z3x8fGeuv/5z3+YNGkSDzzwABEREdx5550MGzaMgQMHEhYWxiuvvML333/PfffdR3x8fLEhwA899BA9e/bklVdeITMzk/vuu48//elPfPfdd4SEhAAwceJE5syZw8SJExkwYABbt27lL3/5C//5z39Ys2YN9eod6dubN28eHTp04Nlnn/Ukw9nZ2Rw6dIgpU6bQokUL9u7dy6xZs0hKSuLHH38kNjaWm2++mczMTBYuXMinn34K4NNueXzwwQd89dVXTJs2jdjYWE488UTy8vIYOHAgv/zyC5MmTaJTp0589tlnPPDAA+zfv59HHnnkqJ5VlyjBraXcyWpaWhpnnHEGa9euJTw8nO7duxMbG8vWrVvJyMggMTGRtLQ0YmJi6NatW4lttm7dmoULF3rO9+zZw1133UVmZiYJCQn8+OOPLFy4kEceeYR7770XgEGDBnHw4EHmzp1bdW9WRER8paQ4H4rdH45TUo5c8zd0uZKHM+dn5HPom0NE9Ing0DeHqJ9YX0muSHkE+ZdUZVFYWMiECRM499xzeeONNzzlffv2pW3btsycOZPHHnvMU/7bb7/xxRdfcMIJJwBOT+pll13G3r17effddwE499xzWb16NUuXLi2W4MbFxbFs2TLPXq9t2rRh4MCBLF68mFGjRrFp0yaee+45HnvsMe6++27PfYmJiQwcOJCPP/6Y8847z1Nev359Pvzww2JDgufNm+f5c0FBAYMGDaJZs2a8/vrrjB8/nhNOOIGEhASg+HDu8jpw4ADfffcdcXFxnrIXXniBr776ivT0dHr16gXAwIEDOXz4ME8++SR33XUXjRs3rtBzazsluCU4mp7TmqJt27a0bNmStLQ07rzzTtLS0ujVqxdhYWG0b9+e5s2bk5aW5klwzz77bM9vvwIZPHiwz3nXrl0B+PXXX0lISOCLL76gsLCQSy+91KfeyJEjleCKiFSnpCSnx8dfIlu0VwgqtafIe85taGIo9RPra5iySHmV9EuqGuKHH35g27ZtzJgxw2dKXExMDD179iy2Fkznzp09yS3gWQvm3HPP9anXsWPHYvcCXHLJJZ7kFmDAgAHExcWRnp7OqFGj+Oijj7DWMmrUKJ94kpOTCQ8PJy0tzSfBHTx4sN/5rn//+9959tln2bRpEwcOHPCU//jjj6V+TcqrT58+PsktOMOc27dvT/fu3X3ex6BBg3j44Yf58ssvGTRoUKXHUpsowa3FkpOT+eCDD7DWkpaW5vMPiHsebv/+/cnIyGDcuHGltte0aVOf8/DwcMD5DRzAjh07AIptQ+RvWyIREaliSUnFE1V/vUJQqT1FBZkFPsmse05uQWaBElyRsgr0S6oaZPfu3QCMGjWKUaNGFbvevn17n/MmTZr4nLuTS3/l7s+W3vx9nmzRogXbt2/3iadly5Z+4/3f//7nc+49fNpt6dKlXHnllVx33XVMnTqV2NhY6tWrx8CBA/3GVFH+Yti9ezc//vgjoaH+/70s+j6kOCW4tVhycjILFy5k3bp1fPvttzz88MOea3369GHOnDme+bPurYUqwv2XdNeuXbRt29ZTvmvXrgq3LSIilSBQr1Al9hRFnBVRrCw0MVTJrUh5+fslVQ0SGxsLwFNPPeV3HRf3wkuVxd/nyV27dpHi+jfLHU9qaipRUcVXbW/WrJnPuXdvsNvixYvp3LkzL7zwgqcsOzvbZ5Gqkrjfc15enk95oKTUXwyxsbF06NCB1157ze893p+xq4wxZwOTgW5ABPATMAtr53vVCbTi1WlY+68qj7EESnBrMXfS+thjj2GtJcnrH8nevXszceJEXn/9dRo0aECPHj0q/LxevXpRr149Xn/9dc8cXHD+sRARkUpSkTm0gXqFanhPkYjUPF27diUhIYENGzbw5z//ucqf98Ybb3Dfffd5ksJVq1axd+9ez+fbQYMGYYxh27ZtfnuUyyI7O7tYz+mCBQuK1QsPD6egoID8/Hyf+q1btwZg/fr1Pkn/+++/X+YYzjvvPD788EOaNGkSnK07jTkFWAmsA64HsoGLgRcxJhxr/+pVewEwr0gLm6ojzJIowa3FOnbsSPPmzVm+fDndu3cnOjrac+20004jOjqa5cuX069fv4DDIMqjQ4cOXHHFFTz44IMUFhZ6VlEuz19qEREpQWXMofXXK1TDe4pEpOYJCQlh1qxZXHLJJWRnZzNixAhiY2PZuXMnn332Ge3bt+eWW26ptOft2bOHESNGcN1117Fjxw7uu+8+OnfuzMiRIwE4+eSTuf3227nhhhs8O4eEh4fz66+/8vHHH3Prrbdy1llnlfiM8847j9tvv5177rmHQYMG8cUXX/DXv/7V5zO0+1kATzzxBAMHDqR+/fqcfvrptGnThl69ejF16lQaNWpE06ZNWbBggWcYdVlcffXVvPzyy/Tr14877riDLl26cOjQIX766SfeeecdPvroo1LXzamgkUAIMBRrD7rKVmDMqcBowDvB3Y6164o2EGxKcGu55ORk3njjDfr06eNTHhISQlJSEitWrCh1e6DymDdvHtHR0Tz55JPk5eXRv39/Fi5cSO/evSvtGSIidVY1zKEVESmr4cOHs3r1ah599FGuvfZacnJyiI+PJykpiSuvvLJSnzV58mS+++47Ro8eTXZ2NgMHDmT27Nk+yd7TTz9Nly5d+Otf/8rMmTMJCQmhVatWDBgwgDZt2pT6DPcWQK+88gqzZs2iV69evP/++5xzzjk+9UaMGMH111/P008/zQMPPOAzb3jJkiWMHz+em266iQYNGnDDDTeQnJxc5mQ/PDycVatW8eijjzJ79my2bNlCdHQ0J554IoMHDz7qLYnKIQzIB3KKlP8ONCleveYxdWXD4KioKJuVlRXw+oYNG+jUqVM1RiTHMv28iEhQVMMqyD7P0rBlkTLR54Kqs3HjRjp16sSrr75a6UlzbVTaz6IxJttaW3yS8pEKXYAvcIYfP4IzRPkSYA5wFdYudtWzwG9ANFCAM6R5MtaurYz3URHqwRURETlWVNccWn+JtJJcEZHaoL4x5muv8+ettc97zqxdjzEpwFvATa7SfOBGT3LreA14F8gEWgN3AZ9gzDlYm1p14ZdOCa6IiMixpDrm0PobCq0EV0SkNjhsrQ28uqwxJwHLgB+AG3GGKl8AzMWYXKz9OwDWXuV111qM+QewHngYCOrcRCW4IiIi4ivQdkIiItWsY8eO1JUplTXEozg9tkOwNt9VtgpjYoGZGLMIawuL3WXtHxjzHnBt9YXqnxJcERER8RVoKLSIiNR2XYHvvJJbty+BK4DmwM4A9xog6L+NUIIrIiIixWnrIJFysdZ69mgVCYZK6uneCXTDmDCszfMq7wXk4iwsVZwxMcBgnAWqgkoJroiISE2kVYxFjhmhoaHk5OTQoEGDYIcidVhOTg7h4eEVbWYWsBRYjjFzcObgDgMuB57B2jyMuRPoAKzmyCJTdwLHAaMqGkBFKcEVERGpabSKscgxpXnz5mzfvp3jjz+eyMhI9eRKtbHWcvjwYf744w/27t1LixYtKtrgGxhzPnAP8DcgAvgZuBmY56r1IzDc9WoEHAA+A67F2i8rFkDFKcEVERGpabSKscgxJSYmBoDMzEzy84tOXRSpWvXr1yciIoJWrVoRERFR8Qat/QD4oITry4HlFX9Q1VCCKyIiUtNoFWORY05MTIwn0RWR4FGCKyIiUtNoFWMREZGjUi/YARhjzjbGfGyM2W2MOWCM+dYYc02ROhHGmCeMMTuMMTnGmHRjTHKwYq7pFi1ahDGGtLQ0n/Jdu3ZhjPE7Nn/27NkYY1i/fj0AY8eOJTExsdJiysjIwBjDggULylQ/PT2dkSNH0rJlS8LCwoiJiaFnz55MmjSJHTt2VFpc3hYsWMD8+fOrpG0RkXJLSoL77lNyKyIiUg5BTXCNMacAK4FQ4HpgBPAV8KIxZrxX1Rdd1x8EhgA7gI+MMd2qN+JjQ9++fQGKJbhpaWk0aNCA3bt3s3HjxmLXYmNj6dy5MwCTJk3irbfeqp6Ai3jqqac4++yz2bNnDw8//DArV65k8eLFnHvuuTz//PNcc801pTdyFJTgioiIiIgc24I9RHkkEAIMtdYedJWtMMacCowG/ur68xXANdbalwCMMWuAH4CpOMtW1yi5n+cSkhBCaGKopyw/I5+CzAIizqqEid+lSEhIoG3btn4T3P79+7NhwwbS0tLo2LGj59ratWvp06ePZ9W/du3aVXmc/qxevZq77rqLCRMm8Mwzz/hcO//887nvvvtYunRpUGITEREREZGaLdhDlMOAfJz9lbz9zpHYhrnqLHFftNYeBhYD5xpjKrzZU2ULSQgha1kW+RnOKnr5GflkLcsiJCGk2mLo27cv6enpHD582FOWlpZGnz596N27t0/yu3nzZnbs2EFy8pFR30WHKLuHGM+bN48HH3yQ+Ph4GjduzNChQ9m2bZvPs7Ozs7npppuIjY0lOjqaYcOGFasTyIwZM4iLi2PGjBl+r0dFRTF27FjPeWpqKsYYUlNTfeotWLAAYwwZGRmesoULF3LaaacRHR1No0aN6Nq1K/PmOaudp6SksGbNGj777DOMMRhjSNGiLiIiIiIix5RgJ7gLXMfnjDEJxpjGxpjrgQGAu/uuM/CLtTa7yL0/4CTIJ1ZLpOUQmhhK1IgospZlkZOaQ9ayLKJGRPn06Fa15ORkDh48yLfffgvA77//zvr16+nTpw99+vTxSXDdf/ZOcAOZPn06P/30E/Pnz2fmzJmkp6czapTvfs7jxo3jb3/7G3/+859588036dChA1dccUWpbR8+fJg1a9ZwzjnnEBYWVp63W6pPP/2UK6+8kr59+/L222+zdOlSrr/+en7//XcA5syZw2mnncYpp5xCeno66enpzJkzp1JjEBERERGRqhXUIcrW2vXGmBTgLeAmV3E+cKO1drHrvCmwz8/tv3ld98sYcwNwA1DpCVNpQhNDCe8eTu7aXCL6RFRrcgtHktW0tDTOOOMM1q5dS3h4ON27dyc2NpatW7eSkZFBYmIiaWlpxMTE0K1b6VOaW7duzcKFCz3ne/bs4a677iIzM5OEhAR+/PFHFi5cyCOPPMK9994LwKBBgzh48CBz584tse3//e9/5Obm0qpVq2LXvHuiwdnvqzzWrVtH48aNefbZZz1lgwYN8vz55JNPJiYmhsOHD3PmmWeWq20REb/S0/2vguyvPFBdERERKZdgLzJ1ErAMpzd2KDAQmAvMNca4uwUNYP3dXlr71trnrbU9rLU9ypsQVVR+Rj6HvjlERJ8IDn1zyDNcubq0bduWli1benpn09LS6NWrF2FhYbRv357mzZv7XDv77LMJCSl9CPXgwYN9zrt27QrAr7/+CsAXX3xBYWEhl156qU+9kSNHltq2tf6+zbBz505CQ0N9XkUT3tL07NmTffv2ceWVV/Luu+96em5FRKpEejoMGACTJjnH9PTA5YHqioiISLkFe4jyozg9tkOste9aa1dZa28DXgdmGmPq4fTU+uulbeI6/ubnWlC559xGjYgiMiXSM1y5upPc5ORkPv30U6y1nvm3bu55uNu2bSMjI6NMw5MBmjb1/VaEhztToHNzcwE8W/gU3YrI39ZERcXFxREREeFJlr3Lv/rqK7766iuuv/76MsVZVN++fVm6dClbt25l+PDhNGvWjIEDB/L9998fVXsiIiVKTYW8PCgocI7udQL8lQeqKyIiIuUW7AS3K/CdtbZo5vclEAs0x+ndbWOMaVCkzslAHvBTlUdZTgWZBT5zbt1zcgsyC6o1juTkZPbt28e6dev49ttvfRJc9zzcNWvWAEe2Fqqo+Ph4wNlz11vRc3/q169PcnIyK1asIC8vz6e8R48e9OjRg4SEBJ97IjNiNVcAACAASURBVCKcVam964Mz3Lmoiy++mDVr1rBv3z7eeustduzYwXnnnUdhYWHZ3pyISFmlpEBYGISEOEf3onX+ygPVFRERkXILdoK7E+hmjCk6QbYXkIvTO/sOzj65l7gvGmPqA5cBH1trD1VTrGUWcVbxObehiaHVskWQN3fS+thjj2GtJclrXlfv3r3ZvHkzr7/+Og0aNKBHjx6V8sxevXpRr149Xn/9dZ/yxYsXB7jD1913383evXu55557ylS/devWAKxfv96n/P333w94T3R0NEOGDGHcuHHs2LHDkwyHh4eTk1N0QW8RkaOQlASrVsG0ac7R/e+vv/JAdUVERKTcgr0P7ixgKbDcGDMHZ7ugYcDlwDPW2jzgX8aYJcCzxphQ4BdgPNAGGOW/WQHo2LEjzZs3Z/ny5XTv3p3o6GjPNfd2OcuXL6dfv36EhlbOIljuFZMffPBBCgsL6dmzJytWrCgx4fQ2YMAAHnvsMe69916+//57Ro8eTZs2bcjNzWXTpk0sXryYqKgoz3698fHx9O3bl+nTpxMXF0fz5s157bXX+Pnnn33affDBB9m1axf9+vUjISGBbdu28dxzz9GtWzeaNWsGOAtNzZkzhyVLltCuXTsaNmxIhw4dKuXrIiJ1kDt5LUt5oLoiIiJSLkHtwbXWvgGcD4QDf8NZcKo3cDNwl1fVq4GXgIeB94ATgPOstd9Wa8DHoOTkZKy1PsOTAUJCQkhKSsJaW+b5t2U1b948rr32Wp588kmGDx/Oxo0bfVZeLs3dd9/N2rVriY2N5f7772fgwIFcfPHFvPzyy1x22WVs3rzZZ0Gs1157jTPPPJPbbruNsWPH0qpVKx544AGfNnv16kVGRgYTJ07knHPO4Z577qFv37689957njr33HMPAwYM4LrrrqNnz56MGzeu4l8MERERERGpNibQyrW1TVRUlM3Kygp4fcOGDXTq1KkaI5JjmX5eRERERORYY4zJttZGBTuOqhTsObgiIiIiIiIilUIJroiIiIiIiNQKSnBFRERERESkVlCCKyIiIiIiIrWCElwvdWXBLakY/ZyIiIiIiNRMSnBdQkNDycnJCXYYcgzIycmptH2DRaSWSE+H6dOdo4iIiARN/WAHUFM0b96c7du3c/zxxxMZGYkxJtghSQ1jrSUnJ4ft27fTokWLYIcjIjVFejoMGAB5eRAWBqtWQVJSsKMSERGpk5TgusTExACQmZlJfn5+kKORmio0NJQWLVp4fl5EREhNdZLbggLnmJqqBFdERCRIlOB6iYmJUeIiIiLlk5Li9Ny6e3BTUoIdkYiISJ1l6sqCOVFRUTYrKyvYYYiISG2Unu703KakqPdWRERqLGNMtrU2KthxVCUluCIiIiIiInVAXUhwtYqyiIhIeWjFZBERkRpLc3BFRETKSismH7Xcz3MJSQghNPHINmv5GfkUZBYQcVZEECMTEZHaRD24IiIiZeVvxWQpk5CEELKWZZGf4exUkJ+RT9ayLEISQoIcmYiI1CbqwRURESkrrZh81EITQ4kaEUXWsizCu4dz6JtDRI2I8unRFRERqSgtMiUiIuJPoJWRtWJyheSk5pC7NpeIPhFEpkQGOxwRkTqlLiwypQRXRESkKM21rRLuYcnqwRURCY66kOBqDq6IiEhRmmtb6dzJbdSIKCJTIj3Dld1zckVERCqDElwREalbyrLNj3uubUiI5tpWkoLMAp8eW/ec3ILMgiBHJiIitYmGKIuISN1RnqHHmmsrIiK1TF0YoqxVlEVEpO7wN/Q4UPKalKTEVkRE5BijIcoiIlJ3BBp6XJZhy1Lpcj/PLTYHNz8jn9zPc4MUkYiIHOvUgysiInVHUpIzLNl76LFWTA6akIQQz8JToYmhPgtRiYiIHA0luCIiUrcUHXpcnmHLUqncC01p6yAREaksGqIsIiLHFn/Dicta5o9WTA6q0MRQwruHk7s2l/Du4UpuRUSkQtSDKyIixw5/w4mhbGUlLSZVdNiyVJv8jHwOfXOIiD4RHPrmEPUT6yvJFRGRo6YEV0REjh3+hhND2cpKSly1YnJQeM+5DU0MpX5ifZ9zERGR8lKCKyIixw73cGJ3z6x7OHFZy6RGKcgs8Elm3XNyCzILlOCKiMhRMdbaYMdQLaKiomxWVlawwxARkYpKTy8+nLisZSIiInWYMSbbWlurl6pXgisiIiIiIlIH1IUEV6soi4iIiIiISK2gBFdERKpXWbfvKW9dERERqfO0yJSIiFQff9v8BJofW566IiIiIqgHV0REqlOgbX4qWldEREQEJbgiIlKd3Nv8hIT4bt/jbyhyoLoiIiIiAWgVZRERqV5Ft+8paSiytvqpMXI/zyUkIcRnf9r8jHwKMguIOCsiiJGJiEhZ1YVVlDUHV0REqldSkm+y6m8osvt60boSNCEJIWQtyyJqRBShiaHkZ+R7zkVERGoKJbgiIhJc7qHI7h5cDUWukUITQ4kaEUXWsizCu4dz6JtDnmRXRESkptAQZRERCT4NRT5m5KTmkLs2l4g+EUSmRAY7HBERKYe6MERZCa6IiIiUiXtYsnpwRUSOTXUhwdUqyiIiIlIq7zm3kSmRnuHK+Rn5wQ5NRETEQwmuiIhUHX/b/8gxqSCzwKfH1j0ntyCzIMiRiYiIHKEhyiIiUjVK2v5HREREqp2GKIuIiBwtf9v/iIiIiFQhJbgiIlI13Nv/hIRo+x8RERGpFhqiLCIiVUfb/4iIiNQYdWGIshJcERERERGROqAuJLgaoiwiIhWn1ZJFRESkBqgf7ABEROQYp9WSRUREpIZQD66IiFSMVksWERGRGkIJroiIVIxWSxYREZEaQotMiYhIxWm1ZBERkRqvLiwypQRXRERERESkDqgLCa6GKIuIiIiIiEitoARXREREREREagUluCIiIiIiIlIrKMEVERERERGRWkEJroiIiIiIiNQKSnBFRERERESkVlCCKyIiIiIiIrWCElwRERERERGpFZTgioiIiIiISK2gBFdEREREREQcxpyNMR9jzG6MOYAx32LMNUXqRGDMExizA2NyMCYdY5KDFLEPJbgiIiIiIiICxpwCrARCgeuBEcBXwIsYM96r5ouu6w8CQ4AdwEcY0616Ay7OWGuDHUO1iIqKsllZWcEOQ0REREREJCiMMdnW2qgSKjwK3Ak0xdqDXuXrAIu1SRhzKvAv4Bqsfcl1vT7wA/Aj1g6rundQOvXgioiIiIiICEAYkA/kFCn/nSO54zBXnSWeq9YeBhYD52JMeNWHGZgSXBEREREREQFY4Do+hzEJGNMYY64HBgDPuK51Bn7B2uwi9/6AkyCfWC2RBlA/mA8XEZEaIj0dUlMhJQWSkoIdjYiIiFSN+saYr73On7fWPu85s3Y9xqQAbwE3uUrzgRuxdrHrvCmwz0/bv3ldDxoluCIidV16OgwYAHl5EBYGq1YpyRUREamdDltrewS8asxJwDKc3tgbcYYqXwDMxZhcrP07YAB/CzmZyg+3/JTgiojUdampTnJbUOAcU1OV4IqIiNRNj+L02A7B2nxX2SqMiQVmYswinJ7aVn7ubeI6/ubnWrXRHFwRkbouJcXpuQ0JcY4pKcGOSERERIKjK/CdV3Lr9iUQCzTH6d1tgzENitQ5GcgDfqryKEugBFdEpK5LSnKGJU+bpuHJIiIiddtOoBvGhBUp7wXk4vTOvoOzT+4lnqvONkGXAR9j7aHqCdU/DVEWEREnqVViKyIiUtfNApYCyzFmDs4c3GHA5cAzWJsH/AtjlgDPYkwo8AswHmgDjApO2EcYa/3ND659oqKibFZWVrDDEBERERERCQpjTLa1NqqUSn8C7sHZDigC+Bl4HpiHtQWuOpHAI8AVQGPgO+AerE2tqtjLSgmuiIiIiIhIHVCmBPcYpzm4NcCCBQswxmCMYdOmTcWup6ameq6vXLkyCBGWjzGGKVOmVFp7U6ZMwZgaseq4j4yMDKZMmcJ///vfan/2//73PyZMmEDbtm2JjIykTZs23HLLLezZs8en3tixYz0/O96v22+/vdRnrF+/nnHjxtG9e3fCwsJq5PfA/Xfnp5+CupaBiPix6/tdpD+dji2sG79IFxGRmkFzcGuQhg0b8uqrrzJt2jSf8ldeeYWGDRvyxx9/BCmy8klPT6dly5bBDqPKZWRk8NBDD9G7d2/atm1bbc+11jJs2DA2bdrE1KlT6dSpE//5z3+YNGkS33zzDZ9//rlPMtqsWTPeeecdnzbi4+NLfc4333zD+++/T48ePQgPDyc9Pb3S34tUovR0Z3uflBTNpZUaYeW9K/npg5+I6xjHSeefFOxwRESkjlCCW4NcdNFFvPbaa0ydOtWToOTk5LBs2TJGjBjBggULghtgGZ155pnBDqFW27x5M59//jnz5s3jhhtuACAlJYV69eoxfvx4Nm3aRIcOHTz1w8LCjup7ctVVVzFmzBgAHnjgASW4NVl6OgwY4OxhGxamlZClRsjekw3A9i+3K8EVEZFqoyHKNchVV13Fli1b+PTTTz1lb731FgUFBYwYMaJY/a+++oqLL76Yli1bEhkZSYcOHbj//vvJycnx1Fm/fj2RkZFMnDjR597777+f8PBw/vnPfwaMp0uXLlx33XWe8/379xMSElKsd/bss8/m0ksv9ZwXHaLsHmK8efNmBg8eTHR0NK1bt2bq1KkUFhb6tPXPf/6TPn36EBERwfHHH8+0adMo6zzx7Oxsxo8fT2xsLA0bNmT48OGe3kzvXw6kpKSQ4mefz8TERMaOHes537lzJ2PGjCEhIYHw8HDi4+MZMmQIu3fvJjU1lX79+gFwzjnneIb+pqamlinWisjLywMgJibGp7xx48YAxb6mR6tevaP/58E9rP7tt99m3LhxNG3alCZNmjBx4kQKCgr46quv6N27N1FRUXTu3JmPPvrI5/6xY8fSsmVLPv/8c3r27ElERASJiYn83//9n9/n7d27l1GjRhETE0NCQgK33XYbubm5Rx3/MSc11UluCwqcYzX8HIqU5tAfzi4RO77ZEeRIRESkLlGCW4O0bt2a5ORkXn31VU/ZK6+8wvDhw4mOji5W/9dff6Vbt27MnTuXDz/8kAkTJjB//nyuvvpqT50uXbrw1FNPMXPmTD744AMAVq9ezYwZM5g+fTqnnXZawHj69+/PJ5984jlPTU0lPDyc7du3e+YKZ2Vl8dVXX3mSvZIMHz6c/v378/bbb3PhhRcyefJkXn75Zc/1vXv30r9/f/bu3cvLL7/M7Nmz+fDDD5k/f36pbQPccMMNzJ8/nzvvvJM333yTDh06MGrU0a9UftVVV5Gens4TTzzBihUreO6552jZsiXZ2dmcfvrpzJ49G4DnnnuO9PR00tPTOf300wO2V1hYyOHDh0t9lZagdu7cmeTkZKZNm8bXX3/NwYMH+fLLL5k6dSp/+tOf6NSpk0/93bt3ExcXR/369Wnfvj0zZsygoKDgqL8u5XH77bcTFRXFkiVLuOWWW3j22We5/fbbGT16NNdccw1vvvkmTZs25aKLLmLv3r0+9x44cIDLLruMMWPG8Pbbb5OSksJtt93mdyTDVVddRbt27XjzzTcZP348s2fPZvr06dXyHmuElBSn5zYkxDn6+QWOSHXL+8P5ZVzm15ll/kWliIhIhVlr68SrQYMGtqZ66aWXLGA3b95sX3zxRdu4cWObk5NjMzMzbUhIiP3444/t6tWrLWBXrFjht43CwkKbn59vX331VWuMsXv37vW5fsEFF9jmzZvb9evX24SEBHvuuefawsLCEuN68803LWAzMjKstdZOmDDBDh061J544ol27ty51lprP/jgAwvYDRs2eO4D7OTJkz3nkydPtoCdP3++T/tdunSx55xzjuf8/vvvt6GhoXbLli2esoMHD9rY2Fjr/KgGtnHjRmuMsTNmzPApv/XWWy1gX3rpJU9Z3759bd++fYu10bp1aztmzBjPeVRUlJ05c2bAZ5b2PSnK/XUo7eX9tQvk4MGDdvjw4T73DR482GZnZ/vUe+aZZ+xzzz1nV61aZd977z173XXXWWOMvfbaa8sUs9tf/vKXUr8H3txfm6uvvtqn/LTTTrOAXbt2rafsu+++s4BdsGCBp2zMmDEWsIsWLfK5f+DAgbZVq1aen133350HH3zQp97gwYPtSSedVOZ4a4XPP7f20Uedo0gN8GjDR+0UptgpTLH7t+0PdjgiImKtBbJsDcjNqvIVcA6uMaZVJeTPv1trD5RWyRhzPnAvcDpQCGwC7rbWfuK63gR4ArgQiATSgYnW2n9XQow1yiWXXMItt9zC8uXL2bJlC8cddxwDBgwgLS2tWN0DBw7wyCOP8MYbb7B161by8/M91zZv3kxsbKzn/MUXX+TUU0+le/fuNGrUiJdffrnUVXH79u1LvXr1+OSTT7j66qv55JNPuOaaa4iPj+eTTz5h3LhxfPLJJ8THx9OxY8dS39vgwYN9zrt06eIzRDo9PZ0zzzyTVq2O/OhFRUUxdOjQUucff/HFF1hrueSSS3zKL7744oDDWkvTs2dPnnjiCay19O/fny5dulRoJeEbbriBIUOGlFovISGh1DrXX38969atY+7cuXTq1IkNGzYwefJkLr74YpYvX+4ZXlx0teTzzz+f6Ohonn32We655x5OOqlq58X96U9/8jnv2LEjmzZtonfv3j5lAFu3bvWpGxISUmxo/siRI7nuuuvYvn27z1D5oj9bXbt2PSZWHK9USUmadys1hi20nh5ccIYpxxwfU8IdIiIilaOkRaYycHqGKuIhYGpJFYwx44BZrtc0nGHT3YAGrusGeAdoA9wK7APuA1YbY7pZa7dVMMYapWHDhlx44YW8+uqrZGRkMGrUqIBzIa+++mpWrlzJ1KlT6datG1FRUXz55ZfcfPPNxeYfxsbGMnjwYJ5//nkuv/xyWrRoUWosTZs25dRTT2X16tUMHTqU9evX069fP4477jgmTJgAOMOdyzI82d2et/DwcJ84d+zYQZcuXYrdV5ZYd+xw5ng1b9683PcGsmTJEh566CEef/xxbr/9duLj47nxxht54IEHjmp+6nHHHVcsPn9Ka/u9995j0aJFrFy5kgEDBgCQnJxM27ZtGTRoEMuXL+eCCy4IeP/ll1/Os88+y9dff13lCW6TJk18zsPCwjxzhb3LgGI/s02aNCE0NNSnzP39LJrg+vvZOnToUMWCF5GjlpeV53Oe+XUmHYZ1CFBbRESk8pS2ivL3wL+Ool0DjC61kjGJwLPAXdbaZ70uea84MwzoDfS31q523ZcO/ALcDdx2FPHVaKNHj2bw4MEUFhayaNEiv3Vyc3P5xz/+wZQpUzzJJsC//+2/U3vlypW88MIL9OjRgzlz5nDllVfSo0ePUmPp168fS5YsYfXq1cTGxnLKKacQHx/P7t27+eyzz/jnP//JuHHjju6NFhEfH8+uXbuKlfsr83cvOPNN27RpU+K9ERERHDhQfGDBb7/95nPevHlzZs+ezezZs/nxxx95+eWXmTx5Ms2aNWP8+PGlxlTU1KlTeeihh0qtN3ny5BL3EXZ/j3v27OlTfsYZZwCwYcOGEhNc65oLVxP3tfW2b98+8vPzfZJc9/fz+OOPD1ZYIlIG3r23oIWmRESk+pSW4L5lrS2xBzYQY0ypCS5wDc6Q5Lkl1BkGZLqTWwBr7X5jzHLgAmphgnvOOedw6aWX0rhxYzp37uy3zqFDhygoKCjWw+VvKO/evXsZPXo0559/Pm+99Ra9e/fmiiuu4Ntvv/W7eJW3fv368fTTTzNv3jxSUlIwxtC8eXM6d+7M5MmTKSgooH///kf9Xr0lJSXxxBNPsHXrVk444QTAWcRq+fLlpd7bq1cvjDEsXbqUu+++21O+dOnSYnVbt27NsmXLyMvL8/QepqWllbjPcIcOHXj00UeZO3cu69evB5xeQsBn1eqSVNYQ5eOOOw6AL7/8koEDB3rKv/jiC6D05G/hwoUYY4olyDVNQUEBy5YtY+TIkZ6yxYsX06pVKyW4IjXcoQPOCIrQBqHkZ+d7Fpqq6b9YExGRY19JCW4WkFfC9dKU5f7ewEZgpDFmEtAaZ2j0M9ba2a46nYH1fu79ARhtjIm21h6sQJw1TkhISMCeW7dGjRpx5pln8tRTTxEfH09cXBzz589n+/btxepec801WGt56aWXCA0NZeHChZx22mnceuutvPTSSyU+Jzk5mZCQEFatWuVZNRicxHfWrFm0atWKtm3bHt0bLWLixInMmTOHQYMGMWXKFMLDw3niiSeIjIws9d4OHTpwxRVXMGnSJAoLC+nevTuffPKJJzn2HvY7cuRInn/+ea655hrGjh3LL7/8wtNPP02jRo08dfbv38/AgQMZNWoUHTt2JDQ0lH/84x/s27ePQYMGAdC+fXvq16/P/Pnzadq0KeHh4XTo0IGGDRv6jTEhIaFM82tLc9FFF/GXv/yF0aNHM2nSJDp27MjGjRt56KGHOOGEExg+fDgAW7Zs4aqrrmLkyJGceOKJHDp0iLfeeosFCxYwbtw42rVr52lz6tSpTJ06lZ9//pnWrVsDzrZL77//PgAbN24E4I033gCcLZXKMgKgIho2bMjdd9/N3r17OemkkzzDshcsWKAPySI1nHuLoLiOcfye8TtZu7M4sO0AjU5oVMqdIiIiFRMwwbXW+v+UXkZlvD/B9XoCuB/4GbgEmGWMqW+tnQk0xUl6i3KPJ20C+E1wjTE3ADfAkXl+tcmiRYsYP348N998M5GRkVx66aXMnDnTp5dw1qxZvPvuu3z00Uc0a9YMgHbt2jFnzhyuuuoqzjvvPC677LKAz4iJiaF79+58+eWXPj21/fv3Z9asWWWef1sWcXFxrFq1igkTJjBmzBhiY2O58cYbOXz4MFOnlj6Q4Pnnn6dhw4Y8/vjj5OXl0b9/f2bPns2QIUN8ktd+/foxd+5cnnzySZYtW8Zpp53Ga6+95rOgUUREBKeffjovvPACW7ZsoV69enTo0IG///3vnuG/sbGxzJo1ixkzZtC3b18KCgpYvXq13z12K1NMTAzr1q1jypQpPP744+zYsYP4+HiGDh3KlClTPL3yDRs2pGnTpsyYMYNdu3ZhjKFTp04899xz3HTTTT5tFhYWUlBQ4LOVx+7du4st2uU+HzNmTKkLf1XG+1y8eDETJkzg3//+Ny1atGDmzJmMGTOmSp8rIhXnHqIcHhNOfPd4/rviv+z4ZocSXBGRusqYwHtpll0m1u4s9VHeH2iLx2FaUcaVkI+GMWYTcBIwwlr7plf5B8BpQDzOispfW2svL3Lv9cDzQCtrre/yq35ERUXZrKysygxfjgFPPPEE99xzDxkZGT6rM0vNNnbsWFauXMm2bbVqDTmROmPjPzay5MIltB/anuZdmvPp9E/p85c+9H+4cqa0iIjI0THGZFtro4Lw4EIqYwHjMkyfLW0O7i/AFJzVjavC/3AS3BVFyj8GzsNJcH/D6cUtyr08674qik2OMe+++y7r16+nW7du1KtXj7Vr1/Lkk09y6aWXKrkVEalG7jm44Q2dHlxwVlIWEZE6bR3w+VHcZ4A/l7VyaQmucb2qyg/AmQGeC84CVD8Ag/zUORn4tbbNv5Wj17BhQ95++20ee+wxsrKyOP7447ntttvKtHKxiIhUHvcQ5bCYMBJ6OGsP7PhmhxaaEhGp2z4qSw+sX8ZUWoJb1d4CrgXOBd7wKj8X2Gat3WmMeQe42hjT11q7BsAYEwMMBRZWd8BSc/Xt25d169YFOwypBFU9v1dEqpZ7kanwhuE0atWIBnENyN6bzf5f99O4deNS7hYRkVpoC/B7ddwf7AT3fWA1MM8YEwf8F7gYp8f2aledd4B04DVjzF04Q5Lvw+nlfbzaIxYREZESuYcohzUMwxhDfPd4fv7oZzK/zlSCKyJSF1nbprrur1d6lQpPBg7csLPC1YXAYuAh4F2cIcujrLULXHUKgSE483Tn4PT6FgD9yrK4VK2Qng7TpzvHyqwrIiJSBbxXUQZ8himLiIhUpbL04E40xlxdejUPa61tV3o1T+UDwM2uV6A6vwHXuF51S3o6DBgAeXkQFgarVkFSUsXrioiIVBFPgtvQN8HVQlMiInWYMU2BbKzNrcrHlKUHtzGQWM6XVJbUVCdhLShwjqmplVNXRESkirjn4IY1dPag915JuaTtCUVEpFbbA9zlU2JMUnkWkCqLsvTgPgvMrMyHSjmkpDi9se5e2ZSUyqkrIiJSRby3CQKIaRlDVPMosnZn8XvG7zRp06Sk20VEpHbyt0PPIOBB4OnKekhZEtzfrbVbKuuB4iU93ellTUk5MpS4aFlSkjPUuGi98tT195yyPr+k+0VERPwoOgfXGENCjwQ2v7+ZzK8zleCKiEiVCfYqynWXv/my4H8OrftV2v3+6gaqV9bnB4pJREQkgKJDlMEZprz5/c3s+GYHnS/pXO42cz/PJSQhhNDEUE9ZfkY+BZkFRJwVUfGgRUSkVijLHFypCv7my1bFfNtA9cr6fM3rFRGRcio6RBkqvtBUSEIIWcuyyM/IB5zkNmtZFiEJIRWMVkREahP14AZLoPmylT3fNlC98jw/0HM0dFlERPwoOkQZjiw0teObHVhrMaboNKyShSaGEjUiiqxlWYR3D+fQN4eIGhHl06MrIiJSWoLbD8iohjjqnkDzZQPNty3r/WWtV57nB5rXq6HLIiJShLXW7xDlhgkNiT4umoM7D7Lvv/to2q6p3/tLG4oc3j2c3LW5RPSJUHIrInLsuQJjenidtwfAmHcC1LdYe0F5HmAqsly/MWYY0B9nNaw0a+2yo26sikVFRdmsrKxgh1F7TJ8OkyY5Q5dDQmDaNLjvvmBHJSIiQZafk8+jDR4lJDyEB3If8Lm2aOgiNr27iRGLR9Dlsi7+73cNPXb3znqfA+rBFRGpAGNMAvBuRQAAIABJREFUtrU2KkgPLzyKuyzWlmsuSok9uMaYoTh7FU2y1q4pcu0lYDRHlnq+xRjztrV2RHkCkGOUtiQSqR6aCiDHGH/zb93iu8ez6d1N7PhmR8AEN9BQZMAn8a2fWN/nXEREaryh1fGQ0oYoDwNOB77wLjTGDAHGAFnAM8AfwA3AhcaYy621i6ogVqlJyjpEWkSOnqYCyDHI3/xbt9j2sQDs37K/xDZCE0OLDUXO/TzXJ5l1J8IFmQVKcEVEjgXWvlcdjyktwT0DSLf2/9m79/hI6/L+/68rk8lhk+wBlmU3LJAFLCByctGyK4flpCiC5aT4q6VKv7bVVv3RVr9Fq1SpXWs9tFqt0qIooJSKVATFysJycKPAAgusnIQNe8ieD9kku5lMJp/vH/fM7CS5ZzL3HO+ZeT8fjzyyueeez/2ZyWSSaz/X57rcyKTj1wAO+IBz7kcAZnYL8Arwh4AC3Ebg175IRErHr4q5fuYk5Pz236Z0dXcBMNg/mHOMeF+c2OoYbWe2EVsdo7mn2bcVULQnquBWREQmmK5N0Hy8oHWys4A9QHrPrXNuC3AvcGrJZici0shSWwEiEW0FkJqRK0U5nwA3c89t+7L2dLpyqj2QiIhILtMFuHOAXZkHzOwI4CDgUTe1QtU64ODSTU9EpIGltgLccIPSk6Vm5EpR7lzQCcDg5kGyFblM9CeypiKLiEiNMnsMs/9TiftPl6I8CCycdGxx8vNTWe4zOZ1ZREQKpa0AUmNypSi3drXS0tnC6NAosYEYbbOnph0rFVlEpC6dBtxTiftPF+A+C1xkZp3OuaHksUvx9t8+6nP+ImBzvrMUERGR+pJawfULcMFLU9750k4G+wd9A1wREalbSzH7q3JfZLoA9zbg28BDZvY9vEa8fwhsAR7MPNHMDDgD6C3DPKWWqc2JiEjDyLUHFyYGuIe8/pBKTk1ERKrrrcmPspouwL0JuAx4G3AKXs/bOPAx59zkzTDn4RWlur/Uk5QapjYnIiINJZWi7LcHF/KvpCwiInWlFD1wX8rnpJwBrnNu3MwuAt4LLAV2Aj92zj3tc/pc4F+BuwNOVOqZ2pyIiDSU6VKUO7sPFJoSEZEGUaEeuDD9Ci7OuXG8VOXbpjnvduD2Es1L6kWqzUlqBTfV5qTW05azzb/WH5eISAAjq0aIdEcmFIBqi7XxxjPemDNFGbSCKyIi5TFtgBuEmX0DuMo5p1ZB4km1OckM+mo9bTnb/Gv9cYmIBBTpjqR71kZ7osT74hw39zju2XQPi2Yu8r1P1wIvwB3qH/K9XUREpBjT9cENagYwu8RjSq1bsgSuu+5AsOeXtlxLss2/1h+XiEhAqR61w3cOs3/lfobvHObJF59k47qNOasog1ZwRUSkPEod4IpML5W2HIlMTFsGbxV0+XLvc1hMnlO2+Wc7HsbHJOGj14nUqGhPlNbFrYw8MkLr4la2bNoC5K6iDApwRUSkPEqaoiySF7+0ZQhnim+2OfnNvx7TsaUy9DqRGhbvixNbHaPtzDZiq2PMap0F5CgytSBZZKp/EOccXpdBERGR0lCAK9WxZMnUP+DDWHE525z85g9Tj4fxMUn46HUiNSreF5+wB7e5p5klu5aw+9XdWdsEtXS00DqrldhAjJHdI7Qf1F7hWYuISD1TirKER67U5Wopdk5KWxY/+aa9i4Rcoj+RDm7BS1de8bMVzDtsXtYUZThQaEppyiIiUmpawZXwyJb6W03FzklpyzJZkLR3kZBrW9o25Vjfb/tIjCa4sOvCrPfr6u5ixws7GOwfZN4b5pVziiIiEmZmTcBS4HigE+e+mjweAVpxbl/QIXMGuGb2asDx5gadgMgE2VJ/q6nYOSltWTIFTXsXqSGJ0QSJ0QQWMZrbsv+JUapCU359eON9cRL9Cd/gW0REQsTsLOC7QA9ggAO+mrx1CfAQZlfh3H8HGXa6FdyeYLOE5MREJJtUOmpqBU/pqI1F33+pY7HBGACtM1tzFo/q7D5QaKoYfn14U1+LiEiImZ0M3AcMAZ8GTgEuT9/u3KOYrQcuBUoa4Pp3aReppN7eyqVuVuJaudJR/a6f7zGpDUpHljo2OjgKZG8RlJJewd1cXICb2Ye3dXErsdWxCXuCRUQktD4DxIHTcG49ZteTGeB6HgPeGHTgnAGuc+61oAOKlFQl96tW8lp+6ah+14f8jilIqi1KR5Y6FdvrreBmaxGUkgpwh/qHir5mZh/etjPbFNyKiNSGs4C7cG59jnPWA9kLOmShKsoSbn77FevhWvleP99jIiIhkJminEspqyhP7sMb74sXPaaIiJRdF7B1mnNaKaAosqooS7iVa7+iX4pvtfdGZrt+vsdERKoscIpykQGuXx/ezK9FRCS0NuNVTs7lJKAv6MBZA1wz2wfc4JxbHnTQUtxfBCjPfsVsqcjV3huZ7fr5HhMRqbJ8U5Q7FySLTG0exI07rCl7Qapc/PrwdlzeQaI/oQBXRCTc/he4BrPFOLd6yq1m5+ClMX8p6MC5VnDbgGJ+OxR7fxFPqfcr5mrTU+29kX7Xz/eYiEiVpVOUp1nBjbZHaZvTxsjuEfbt3EfHIYVVPfZrBRTtiSq4FREJv38E3gM8iNk/A8cAYHY2XmD718AO4MtBB54uRfkPzKwn6KBJahck5ZOtinA+FYernYpcTqquLCJVlEpRbpmZewUXvDTlkd0jDG0eKjjAFRGRGuXca5i9A7gD+Cxe7GjAA8nPm4DLcG66fbpTTBfgnpL8EAmPbCnG+VYhrnYqcrlUsgq0iIiPfFdwwSs0tX3tdgb7Bzn0pEPLPTUREQkb51ZhdjRwBXA6cDAwAPwa+C+cGylk2FwBbil64O4pwRgiE2VLMc5WXdjv3HpM8c2Vei0iUgH57sGF0hWaEhGRGmR2EDCGc3uB25IfJZE1wFUPXAmtbCnGQaoQ16Nsjz+ftG0pHz3X0kDSVZSnaRME0NmdLDSlAFdEpBFtB24B3l/qgdUmSGpPthTjIFWI65Hf4w+Sti2lp7RxaTD5tgkCreCKiDS4Aabvg1sQBbhSm7KlGDd6xeHJjzVI2raUntLGpcEUkqI8tHmorHMSEZFQegyvz23JKcAVqWeNnrZdbfVcsVvER6AiU1rBFRFpZDfgtQi6CuduL+XACnBF6lnQtG3tFy2c33NXrxW7RbIIsge3a4ECXBGRBvb7wC+B2zD7c+BxYAt+rWad+0qQgRXgitS7fNO2tV+0cLmeu0ZKkZeGl1rBzSdFuXNBssjU5kHcuMOarKxzExGRUPlSxr/PSn74cYACXBEpgPaLFk7PnQhwYA9uPinKza3NtB/czv6d+xnePkznoZ3lnp6IiITHxeUaWAGuiHi0X9RfPmnbeu5EgGApyuDtw92/cz+D/YMKcEVEGolz95ZraAW4IuLRftGp8k3b1nMnwnhinPi+OBhEO6J53aeru4ttz27zKimfWuYJiohIQ8ga4JrZqwWO6ZxzRxd4XxGpJu0XnShI6rGeO2lwqdXbls4WzPLbT6tCUyIiUmq5VnCbmFrFqgVYkPz3GLATODhjnM3AaCknKCJV5peimy1tN8i5YeM3z2ypx7XymEQqKEiLoJTO7mShKQW4IiKNxWxvnmc6nJsVZOisAa5zrmfiHGwmcD/wGnAd8IhzbtzMmvCqXi3HC4rPDzIBEQkxvxRd8E/bDXJu2GRLRfZLPVa1aRFfQfffgnrhiog0sJfwawkEs4EeIAK8AAwHHTjIHtzPJy/4BudcepXWOTcOrDSzc4Bnk+d9NOhERCSE/FJ0wT9tN8i5YZMrFXly6rEqJov4CtIiKEUBrohIg3LutKy3mR0MfB04Hjg36NBNAc69FPhJZnCbyTk3AvwEuCzoJEQkpFIpupHIgRRdv2NBz+3theXLvc8pfsdyHZ8syP0nH8s2z3yfExEJ1CIoJRXgDm0eKsucRESkBjm3E7gaaAX+Iejdg6zgHgxMVxYxmjxPROpBturAfsfyPbfYtGe/1dJs5wW5Vr5VkFUxWcSXUpRFRKRknBvDbAVwOfCxIHcNEuC+AlxhZtc75wYm32hmc4ArgEKrL4tIGPlVB85WMTifc4tNe/a7brbzglwrSBVkVUwWmaKQFOVU79uhLUOMJ8ZpigRJLBMRkToXAeYGvVOQ3yTfArqBx8zsajPrMbP25Oc/Bn4DzAe+EXQSItJAik17znfMoNcSkaKkUpSDBLiRlggzDpmBG3cMbwtcR0REROqVWQ8FLp7mvYLrnPs3M3sd8BHgu37TAL7unPtm0EmISAMpRdrz5DY92c4Lci0RKUo6RTnAHlzw0pT3bd/HYP9gui+uiIjUObOvZbmlGTgcOA9vD+71gYd2zq86c6652BLgGuBUYBYwADwJ3OycWxV0ApXS0dHhhof1v8MiNU9tekRC6f7r7udXX/gV537+XM785Jl53++2d9zG737+O666+yqOvfjYMs5QRETMbJ9zrqPa88BsfJozNgL/jHNfDzp0kD24ADjneoFpypmKiJSJ2vSIhFJqBTdIijKokrKISIM6McvxcWA3zm0pdODAAa6ISFWl9tCmVnC1h1YkFAppEwTQucArNKVKyiIiDcS5teUaOnC5QjO72MxuN7M1Zva7jOPHm9knzOyw0k5RRCRDal/tDTcoPVkkRAppEwRqFSQiEipmKzFzWT7uS57Tk+Oc2Xle52uYXTjNOW/NsVc3q7xXcM3MgJuB9yUP7QfaM07ZDfwjXrGpfwo6ERGRvKlNj0joFNImCBTgioiEzIeBmZOOLQG+Atw96fhyn2P5vpn/JbADuC/HOW8C/gL4aJ5jAsFSlD8M/BHwHeCvgWuBT6dudM5tMbNfARehAFdERKShFJqirABXRCREnPvtlGNmHwRGgdsn3fIqzv26jLOJAomgdwqSovwnwBrgg865AcCv/PLLwKKgkxAREZHaVmyRKQW4IiIhZNYOXAn8FOd2lXj07O18zCLAW4BtQQcNsoJ7LPBtl7uv0DbgkKCTEBERkdqWSlEOuge3c34nFjGGtw4zFhujuVX1L0VEQuQyoAv4ns9tyzH7FjAMPAR8CueezTqS2TOTjvwFZlf6nBkBFuC1pL0p6ISD/BYZA9qmOecwQHX+RUREGky6yFTAFOWmSBNd3V3s3bCXwU2DzDlqTjmmJyIinmYzeyLj6xudczfmOP9qvEXMn2cciwHfBv4X2A4cB3wSWIXZm3Hu+SxjdXNg1dbhBc4Rn/MSwGbgVuDvcj+cqYIEuL8FlpmZ+a3imlkbcC7wVNBJiIiISO1yzh0oMtUZLEUZYNbhs9i7YS8DGwaKDnBHVo0Q6Y4Q7Ymmj8X74iT6E7Qtne7/6UVE6t6Yc+60vM406wbOB/4V58bSx53bDPx5xpmPJCssrwU+xYGixBM5Nzdj7HHgn3Duc8GmP70ge3BvwYvOv2pmE+5nXo70V/Ci8ptLNjsREREJvfhwHBxEZ0Rpag7cgZCZh3sFO/du2Fv0XCLdEYbvHCbeF/fm1hdn+M5hIt1+iwQiIpLD+/DiRb/05Imc2wA8ilf5OB8XAz8seGY5BFnB/TZwCV6Z5itJloA2sx8Bp+MFtz9xzt1W6kmKiIhIeBXaIiglFeAObBgoei7Rnigdl3cwfOcwrYtbia2O0XF5x4QVXRERycvVwBqcW5Pn+UauwlGZnLu30ElNJ+8A1zmXMLN34uVB/wXwe8mbLgP2ADckP0RERKSBFNoiKGXW4bMAGFhffIALXpDburiVkUdGaDuzTcGtiEhQZqcBJwB/lef5R+BVPb4r4HWagJPwajn5/xJx7sdBhgxUqtB5udd/b2afxQtwDwYGgBecc4F7FImIiEjtK7RFUEopU5TBS0uOrY7RdmYbsdUxmnuaFeSKiARzNV6R4R9MucXsy3ipy714RaaOBa4DxoF/zPsKZu8BvoxXMdn3DLwV4UB7TAqqxZ8sMvViIfcVERGR+lJoi6CUWUd4K7ilCHBTe25TacnNPc0TvhYRkWmYRYH3Avfh3FafM9YCHwLej1cJeQfwAPBZnMsvRjQ7Fy94fhX4e+CzeJWanwLOxlsNvhNYGXT6gQNc8x7wecDxQKdz7obk8TZgJrDDOTcedFwRERGpTYW2CEpJpyiXYA9uoj8xIZhN7clN9CcU4IqI5MO5OHBIjtu/A3ynyKt8HC8T+M04txsvQ/g36arKZh8Dvpj8CCRQqUMzuxDoA+7FW07++4ybT8HrV/SeoJMQERGR2pXag1toivKMQ2YQaY0wsnuE0eHRoubStnTqnttoT1QtgkREwuVNwN04tzvj2IHY1Ll/BR4HPhN04LwDXPM2Gv8PXh70tUzKx3bO/RpYB1wadBIiIiJSu4qtomxmzFxY2n24IiISap3ApoyvY3jpzpl+AywNOnCQFdxPA/uA05xzXwNe9jnnceDkoJMQERGR2pVOUS5wDy6UNk1ZRERCbyswN+PrzcDrJp3TCQTeWxIkwH0L8D/OuS05ztlA9ipYIiIiUoeKbRMEpa+kLCIiofY8B9rOAqwCzsfsjQCYHQNcmTwvkCABbidehaxcZgQcU0RERGpcsSnKcCDA1QquiEhD+DlwBmaHJr/+El4c+Rhm6/AqNc8GvhB04CDB6Ca8Zr+5nIJX6llEREQaRClTlLWCKyLSEL4NHIdXSRmcexp4O/AoXqefx4ArcO6uoAMHaRP0c+DPzewM59yjk280s7fjbQIOHGWLiIhI7Sq2TRAoRVlEpKE4NwK8MunYg8CDxQ4dZAV3ObAH+F8z+yfg9QBmdlHy6//G2xz8lWInJSIiIrWj2DZBkFFkar1SlEVE6p7Z3Zj9XTmGznsF1zm3yczeCtyB15g35W7A8CLwy5xz0+3TFRERkTqS2oNbihXcgQ0DOOcws5LMTUREQukC4LlyDBwkRRnn3JNmdixwEbAEOBgvb/rXwE+cc2Oln6KIiIiEWSn24LbNbqOls4XRoVFG9ozQPqe9VNMTEZHweQU4rBwDBwpwAZxzCbxV27tLPx0RERGpNaWoomxmzDx8Jjue38HeDXsV4IqI1LfvAn+L2QKc21zKgQtu6WNmM83scDObWcoJmdl9ZubM7B8mHZ9jZv9pZjvMbNjM7jezE0t5bREREQmuFH1wIWMfrloFiYjUu+8DvcAjmL0fsxMwOxizg6Z8BBRoBdfMWvD2314D9GQc7wO+A/yzc2406CQyxnkvcLLPccNbMV4EfATYDVwHPGhmpzjnNhZ6TRERESmccy6dolzMCi6okrKISAPZCji8Wk435TjPETBmzftkM+sCVgCLkxdaD2wB5gNHAp8DLjGz85xzQ0EmkRx/NvBV4FrgB5NuvgQ4AzjXeeWjMbNeYB3wCeCjQa8nIiIixRsbGWN8bJxIS4Tm1sA7nybILDQlIiJ17cd4MWXJBflN9FngtORkPu6cW5e6wcwWAV8CLk2e99cFzOWLwFrn3A/NzC/A7U8FtwDOuQEz+ynwLhTgioiIVMWWp7cAMHvR7KLHSqUoawVXRKTOOXdFuYYOsgf3SuBp59wVmcEtQPLrK4A1wLuDTsLMzgCuBj6c5ZQT8C8jvRY4wsw6g15TREREirfuAe9PgkXnLip6LKUol1lvLyxf7n0WEalTQQLcucAvst3onHPJ2w8OMgEziwLfBr7knHsxy2kH4e27nWxX8vOcLGP/qZk9YWZPjI2pg5GIiEiprVtRugB3uiJTrz38Gl+Y/QWe//HzRV+r4fT2wnnnwac/7X1WkCsiYWG2ELMLMLu0FMMFCXD7gOnyj2Ylzwvi/wLtwOdznGP452jn7ALvnLvROXeac+605ubi9gWJiIjIRPH9cTas2gBAzzk9RY+XXsHduBfv/80neuqmp4gNxHjpnpeKvlbDWbkSRkchkfA+r1xZ7RmJSKMzOw6zh4DXgPuA/8647WzMtmF2YdBhgwS4/wG828wW+s/PjgDekzwvL8n7fAr4NNBqZrOTxabI+DqCt1LrVyI6tXLrt7orIiIiZbRh1QYSsQTzT5nPjINnFD1eS0cLbXPaSMQS7Nu+b8JtzjleXfEqAIObBou+VsNZtgxaWiAS8T4vW1btGYlII/NqOD0KvBmvivIKJi5ePgok8LbJBhJkWfPHwFnAk2b2L8DDeOWdDwXOBj4GPATclQxc05xz67OMeRTQBtzqc9vfJD9Oxdtr+1afc14PrC+karOIiIgUJ52efF7x6ckpsw6fxcjuEQbWD9AxryN9fNfLu9KB7d6N2qMb2JIlsGKFt3K7bJn3tYhI9VwPdAJLcO4pzK4Hzkvf6lwCs18BpwcdOEiA+yoHehXd4HO74VU7vmTS8Vy9i54GzvE5/iBe0HsT8Du8HrgfMLOznXMPAZjZTOBiprYUEhERkQpIF5gqZYB7xCy2PrOVgQ0DdJ/WnT6eWr0F2LtJAW5BlixRYCsiYfFW4C6ceyrHORuAc4MOHCTA/T4l7lXknNsDrJx83MwAXnPOrUx+fTfQC9xqZh/HS0m+Di+o/mIp5yQiIiLTGxkYof/xfpqamzjyzCNLNm62Ssp9D/Sl/x0biDE6NEpLZ0vJrlt3envzX60Ncq6ISGkcjLf3NheHl+0bSN4BrnPu/UEHLxXn3LiZvROv1+438R5oL3COc25DteYlIiLSqF57+DXcuGPhkoUlDTRTAW5mJWU37lj3oLdaHJ0RJb4vzt5Ne5l77NySXbeupComj456+21XrMgeuAY5V0SkdLYD06X/HA9sCjpwkCJTFeOcM+fc3006tss5d41z7iDn3Azn3HnOuTXVmqOIiEgjK2V7oEypVkGZK7hbn9nK/p37mXXELBYsXgCUptDUyKoR4n3xCcfifXFGVo0UPXZVBamYrOrKIlIdDwGXJItNTWV2EnAB8MugAxcd4JrZcWZ2rZn9mZnNKnY8ERERCb9y7L8F/xTl1P7bRecuYubCA62EihXpjjB853A6yI33xRm+c5hId6TosasqSMVkVVcWkepYnvz8CGZ/BHgpOWZHJr++F9gPfDnowHmnKJvZZ4APASc453Ylj50P/BRI5SZ9wsze7JzbGXQiIiIiUgN6exm9539peXYDze2LWHi6b/fAgqVWcDNTlFP7bxedt4gta7YApSk0Fe2J0nF5B8N3DtO6uJXY6hgdl3cQ7YkWPXZVBamYrOrKIlINzj2H2f+HV+fp5uRRwytsDLAPuArnXgk6dJAiU28HXkgFt0nL8Tb/Xg/MBz6M1y7oM0EnIiIiIiGX3K8ZjcW4mibuf8N1NLcG+VNiel2HdQEw2D/IeGIcN+547WGvDsmicxexb6fXH7dUvXCjPVFaF7cy8sgIbWe21X5wmxKkYrKqK4tINTh3F2bHAP8Hrx3QwcAA8GvgRpzbXMiwQX4r9QB3pb4ws8OAxcBXnHP/kDx2HPAHKMAVERGpP8n9mjY+ThOO4w/aWvJLNLc203FoB8NbhxnaPMTA+gFGh0aZe9xcurq7mHlY6VKUwUtLjq2O0XZmG7HVMZp7musnyBURCTvntgKfL+WQQfbgzgEyV2/fgrd6e0/GsdXAESWYl4iIiIRNcr/mOE2ME6HjyovKcpnMNOXU/tuec3sA0ntwS7GCm9pz23F5B+3L2tPpypMLT4Veby8sX+59Dsv18z1WSdW+vohURJAV3O3AYRlfnwPEgd9kHGshpJWZRUREpEhLljB46//w2OVfZFPH63jf+99ZlsvMPHwm/U/0s3fD3vT+26POOwo4kMJcihXcRH9iwp7b1J7cRH+idlZxq93mx+/6kN+xas9Tadki1Wf2LuAa4FRgFl6K8lPAd3DuJ4UMGSTAfRq4xMzeAIwA7wEedc7tzzinBygoV1pERETC73d7DuFRzuTY84+lKVKe/9NOVVLe8eIONqzaAAY9y3oA6JzfCQZDW4dIxBNEooVXPG5b2jblWLQnWjvBLfi3+alk4JatzVA+x6o9TwW4ItVjFgFuwYspLXl0GFiY/HgnZv8FvA/nxoMMHeQ30xfxouo1wIvJf6fLNptZG7AMeCLIBERERKR2lKs9UKZZR3gpymtvX0tiNMGCUxfQflA7AJFoxAtyHQxtGcp7zLrteVvJNj9+Kb5+18/3WK5xS51OHPT6IlJufwNchRdbXgx04VwX0AVcAjyDF/z+TdCB817Bdc49YmbvBD6It/f2NufczzNOWQr0kVGISkREROqHc451K7wAN5UyXA6pPbjbf7sdOLD/NmXmYTMZ2jzE3o170+dOJ9XzNpWSnLn/tqZVqs1PthTfbNfP91i+Kc7FPq5s81Tqski1/Ale7HgGzu1LH3VuGLgHsweAtXgVlr8YZOBAtf2dc/cB92W57QG83GkRERGpQzte2MHQliE653cy9/i5ZbtOKkU5ZXIwPXOht0c3SKGpuu15C5Vp85Mrxdfv+vkeyzfFuRSPL9/rK8AVqYQjgG9MCG4zObcPs7uADwUduLTN60RERKRubXpsEwBHnHkEZjbN2YXLXJVtam7iiDMmNmgotNBU3fa8LYfe3omrnakU39RKZ6lSobON63ds8pzKeX0RKbctHNh7m40BgfvRKcAVERGRvMQGYgB0HFretN7OBZ1YxHAJx8LTF9LS2TLh9nSAuylYgKuet3nKlrZbjlTofFOcy5VKXKkUbxGZ7A7g3Zj9ne8qrlkncBlwe9CBFeCKiIhIXkaHRgGmBJyl1hRpoqu7i70b9voWsyqkF27mnttoT5TmnuYJX0uGbGm75UqFzieduZypxJVI8RaRya4HTgFWYfYZ4GGc24PZbOBs4LN4hY2vDzqwAlwRERHJSyrAbe1qLfu15r1hHns37OWYtx8z5baZh3kBbpAU5broeVspYUzbDeOcRKQYW/FSkDtIFSk2G+NAfGp4bYO2MXFLjMO5nNUFFeCKiIhIXmKDXopyuVdwAS6+8WJ2/W4XC39/4ZTbClnBrYuet5USxrTdoHONXWPkAAAgAElEQVQqdr9uOfb7ikiml/A685ScAlwRERHJS3zI6yNbiQB35sKZ6UB2ssw9uM65sha8alhhTNvNd07F7tdV6yCR8nPutHIN3VSugUVERKS+VGoP7nRaOlpom91GIpZg/879VZ2LhFC21kOVur+IVJUCXBEREclLOsDtqm6AC4VXUq5pvb2wfLn3WQ6Y/Lyk9utGIoXt1812fz3/IjUha4qymb1a4JjOOXd0gfcVERGRkKrkHtzpzDxsJtvXbmfvxr3MP3l+tadTfkqb9VeOlkZ+99fzL1IeZufgVVNeCPgVRXA497EgQ+bag9vE1I2/LcCC5L/HgJ3AwRnjbAZGg0xAREREakNYUpQBuhZ6K7hBCk3VtHK2yall5WppVMk2RSKNyKwb+DHwJryKydk4oDQBrnOuZ+IcbCZwP/AacB3wiHNu3MyagLOA5XhB8flBJiAiIiK1IUwBbiGtgsrGr+Juqavwqk2Ov0o9L7muo4rLIoX4GvBm4A7g+8AmvAXUogWpovx5YDbwBudcepXWOTcOrDRvefnZ5HkfLcXkREREJDwq2Qd3OqkKy1Xfg+uXugqlT2cNY+ueMKjU85LtOkpdFinUBcADOHdVqQcOEuBeCvwwM7jN5JwbMbOfAFehAFdERKTuhGkFN1VkanBjlVOUs1XcLUc6axhb94RBpZ4Xv+sodVmkUOPAk+UYOEiAezD+G38zRZPniYiISB1x4474sNcHNzpjuj8Hyi+dolztFdxsqavFps0q7bU2KHVcpFC/AY4rx8BBAtxXgCvM7Hrn3MDkG81sDnAFUGj1ZREREQmp0WFv9TbaEcWactUDqYxUinLVi0xlS10tJm1Waa+1Q6njIoW6HngQs4tx7qelHDhIgPstvM3Aj5nZ54GHga3AocDZwKeA+Xh7cEVERKSOhGn/LUD7we1EWiOM7BlhdHiUlo4qpk37pa4WkzartNfaotRxkeCc+w1m7wB+hFkvXrrylEXU5LlfCTJ03gGuc+7fzOx1wEeA7/qcYsDXnXPfDDIBERERCb8w7b8FMDNmHjaT3a/uZnDTIAf/Xh3tkFLaq4jUO7MO4K+Ag4CLkh9+HFCeABfAOfcxM7sduAY4FZiFF2k/CdzsnFsVZDwRERGpDaOD4QpwwSs0tfvV3ezduLe2A9zJ+22V9lr7tIdaZDpfAt4JrAJuA/qpQpsgAJxzvUBvKS4uIiIitSFsK7gQolZBxci231Zpr7VLe6hF8nEp8DhwJs65Ug7cVMrBREREpD6lA9yu8AS46VZB1S40VYxsbYakdul7KpKPTuChUge3UMAKrplFgGOBOUDE7xzn3MNFzktERERCJJQruKlWQRtrZAXXL21V+23rT7bvqd/3P1sqs1Kcpf49AxxZjoEDBbhm9mngWry9t7n4Br4iIiJSm2KDMSBkAW5YWgXlI1cqsvbb1he/76nf9x/8XxNKcZbGsBy4A7PFOLe6lAPnHeCa2SeAz+IVlboF2ECJNgKLiIhIuIVxBTeVolwTK7i5Wv9ov239mfw9zZa27PeaUJsoaQxR4F7gUcxuAlaTvU3Qj4MMHGQF94PAJuCNzrntQS4iIiIitS2MAW5NFZlSKnJjy/b99zsW5LWiVGapXT/CawFkwIeT/57MkscDZQcHCXAPB/5Dwa2IiEjjCWORqc75nWAwtGWIRDxBJBriHVJKRW5s2b7/fsfyfa0olVlq20fKNXCQAHdrwPNFRESkToSxD24kGqHz0E6GtgwxtGWIWYdPVyKkypSK3Nj8vv/ZXhP5vFaUyiy1zLlvlGvoIG2C7gAuMLPWck1GREREwimMKcpQ4UJTvb2wfLn3WaTaUqnMkUjhae96TUsdCrIi+xngdOBHZvZR59y6Ms1JREREQiasAW7XYV3wRAUKTSkdVMKm2LR3vaYlDMxmApcAxwOdOPex5PHZQDfwO5wbDTJkkAB3LV61q27gHWY2AOzxOc85544OMgkREREJt1SA29oVrkSuihWaUjqohFExae96TUu1mV0FfAvo4kBBqY8lb+3Bq6x8DfC9IMMGSVFuwmsLtD75MZCcyOSPIGOKiIhIDQj1Ci4VSFEuRTqoSJjoNS3VZHY2cCuwGfgj4KYJtzv3NPAicGnQofNewXXO9QQdXEREROpDGItMQcYKbqlTlCe3X1EVZKk3ek1LdV0H7ACW4txuzF7nc85TwJuDDqyqyCIiIjKtsK7gzjysDEWmsu1NVBVkqTd6TUv1vBn4Ec7tznHOBuBdQQdWOrGIiIhMK4x9cAFmHeG1Btr85Ga2/3Z7aQb125soIiKl1A5Ml3ozE29fbiBZV3DN7OrkP+9yzg1mfD0t59z3g05EREREwiusK7hzjp7DcX9wHC/8zwvceuGt/MmqP0mnLRdiZNUIzceeQXNLS3oFd+zYMxhbNULb0rYSzjycRlaNEOmOEO2Jpo/F++Ik+hMN8fhDbXLafDnv73dusdcXmeg14JRpznkT8HLQgXOlKN+MFzH/GhjM+DqXVPUrBbgiIiJ1YjwxTnxfHAyi7dHp71BBZsZlt13GLRfcwoZVG7j1wlv5wCMfoH1Oe0HjRbojDPWeSOetv6D5xUcZO/YMhtadSMcbIyWeeThFuiMM3zlMx+UdRHuixPvi6a+liopt6RPk/n7ngloKSandA1yL2UU4d++UW70Ky4uB64MOnCvAvQYvWN2c/PoDQQcXERGR2hcfjgPQ0tGCNVmVZzNVdEaU9/70vXznjO+wfe12bn/X7bzvF+8rKBiP9kTpuLyDoTtPpHXJacRWx9LBXiNIPf7hO4dpXdzacI8/tIpt6RPk/tlS9NVSSErrC8BVwF2Y3QLMA8Dsj4GzgPcB64B/DTpw1gDXOXfzpK8D9R8SERGR+hDW/beZ2g9q5333vY+blt7E+kfW8+M//DFX/veVNEXyKDcyKfUy2hOldXErI4+M0HZmW8MFd43++EMp1dIntYIatKVPkPtnO7eY64tM5twOzM4FbmPiQup38LKCnwSuxLnAJfLNuexZx2YWdc7Fgw4aRh0dHW54eLja0xAREak5O1/ayb8d+28c9LqD+MhLH6n2dHLa9tw2vnvmdxnZM8LiP1/MO//9nbnv4JOOGV9wWkOvYKbSkhv18YeW9uBKCZjZPudcuPYcmC0FlgAHAwPAr3HuoYKHmybAHQIeAR4AVjjnniz0QtWmAFdERKQw/av7+Y/T/oP5p87nz578s2pPZ1qvPfIat1xwC4lYgg8+8UG6F3dnP3n5cvj0p73Uy0iExF/9PYOH/qXvHtRGCPImP95Ge/wi9a6qAa5XtPhpnHumnJeZLm+nGXgbXo7042a208x+ZGYfMv9mvCIiIlJnwlpBOZsjzzySk//4ZABe+d9Xcp+cSseMRLyKycecMSGYS+1JTfQnyjzrcEj0J/J+/COrRoj3TUz0G753mOF7Ji4oxPvijKwaKd+kRaRW3Az8QbkvMl2AOxu4AC/AfQyvF9FlwL8BL5jZejP7rpm9z8wWlHeqIiIiUg2pALe1q7XKM8nfonMXAdD3QF/uE5cs8SrC3nADrFhB658um7JSGe2JNkyLnLalU/fcZnv8qYrLqSA33hdndO0oo78dnXBs+M5hIt2NUYVaRKovVxVlnHMjwIrkB2bWBZwNnJv8OBH4Y+Dq5O0vAvc75z5axjmLiIhIBdXaCi4cCHDXP7qesZExmtty/MmzZIn2FBbAr+Jy57s7AbSHV0SqJo/Sggc45wadc/c45/7KOXcKXjnn9wA3An3AccBflHyWIiIiUjWpADfaWTtBSschHRx60qGMjYyx8dcbqz2dupVZcbl1cSvRnqjvMRGRSgkU4Po4IuNjXvHTERERkbAZHay9FVx6ezm38zcsZAOvrni12rOpW/G+OLHVMdrObCO2Oka8L+57TOpUb69XqK23t9ozkVIxW4mZy/JxX8Z5czD7T8x2YDaM2f2YnZjHFWZjdkSgj4BypihPfbx2HAfSk5cBc/D6FG0G7gYeTH6IiIhInai5FOVk65/XxWIsoon7fjIPbji32rOqWSOrRoh0RyasxMb74ow+N0r8xXg6Bbm5p5mhO4YA6Hx3Z/qYqjDXKZ8WW0r1rwsfxqu7lGkJ8BW8eA/MLPnvRcBHgN3AdcCDmJ2Cc7nSZj6W/MiXI2DMmvNkMzuSAwHtOcACvIB2G3A/sBJ40Dn3YpCLioiISO2ouSJTK1fC6Cg2Pk4Tjo61jxMbjNXO/EMmVUxqcuug6HHRKRWXW05oAYdvFWYFuHUm+XNGIuF9XrlSAW49cO63U46ZfRAYBW5PHrkEOAM4F+ceTJ7TC6wDPgHkqse0F9hTuglPNV00nMrp2Qk8THKF1vk9cBEREalLoVrB7e31/pBetiz7H9Op1j+jozjXxLrxI1n48Gv83kW/V8GJ1g+/YlLZVmQ7LpraXjO1L1fqTMbPGS0t3tcp+fycSm0waweuBH6Kc7uSRy8B+tPBLYBzA5j9FHgXuQPcr+Lc58o1XZg+wDW8ZeFngNXAE8AL5ZyQiIiIhEto9uDmmxKZav2zciVPvdDJxu/vYt0D6xTgFiGzcFTbmVNbCUkDyvg5mxDIKnW53lwGdAHfyzh2AvCcz7lrgasx68S5oUpMzs90Ae4fciBF+fN4we6QmT2Ct5r7gHPuqfJOUURERKopNCu4QVIik61/5j6wDr7/fdatWFfJmdadyYWjmnuaFeSKf4stpS6HXbOZPZHx9Y3OuRtznH813vbUn2ccOwivg85kqRXeOUA4A1zn3A+BH0J6P+75HCgw9Q7Amdke4CEOBLxryzlhERERqax0gNtV5QA3V0pkFocvPZxIa4Sta7ayb8c+ZsydUfZp1pvUntvMYlIqHCVZFfBzKhU15pw7La8zzbrx4r9/xbmxzFvwFj6n3KP46RUv74pUzrnXgJuSH5jZ8cB5eAHvWXj51pjZdufc/NJPVURERKohNCu42VIic2hua+aItxzBugfWse7BdZxw5Qlln2a9SfQnphSTUuEoyaqAn1MJrffhtZX93qTju/BWcSebk/y8u5yTmk6gksuZnHPPA8+b2V3ABcC1wInAISWam4iIiIRAbDAGhCDABf+UyGksOm+RF+CuUIBbiLalbVOOqXCU5FTAz6mE0tXAGpxbM+n4WuCtPue/Hlifdf+tc02lnZ6/wBcxs4PN7Aoz+6aZvQisx1vVPZEDBalERESkToRmBTeb3l5Yvtz77GPRuYsAWPfAumnPFZEy0c9ebTE7Da+Y1OTVW/B64B6G2dkZ588ELibVK7eKpl3BNbNO4Gy8VOTzgDfg5VencqxfAVYAD+Dtwd1RnqmKiIhINYS6D24eFVu7T+umpauFGS+vwZ37f7G4qruKVJQqK9eiq4Ex4Ac+t90N9AK3YvZxvJTk6/Diwy9WbIZZ5FzBNbNVeDnWd+OlIJ8EbMF7oNcARzrnXuec+3Pn3B0KbkVEROpPqFdw/Sq2TtLU3ETP2T300AexWM5zRaQM8vg5lRAxiwLvBe7Dua1TbnduHHgn8Evgm8BdQAI4B+c2VHCmvqZbwT0dLyJfSXKV1jmnPrgiIiINYnxsnLH9Y2DQ3F5w6Y7yybNi66LzFrH2nh4STc00k1B1V5FKyvZz2tvrX4zK73i2c6X0nIszXV0l53bhLXheU4kpBTHdb6rTgKecc35loEVERKTOjQ4fWL01C0UHiInyrNi66LxF/ILD+e85f8ZV187HzjlHfySLVIrfz2m2tGW/46AUZ8nbdH1wn6zURERERCR8Qr3/NiWPiq3zTpjHjENm8NJ22Hn5nzL32LkVmpyIAFN/Tv3SlpcsyZ7O7HeuiI8Q5hqJiIhIWIR6/20A1mQsOncRa/9rLd884ZtY04HVaDPjTX/5Jt725bdVcYYiDSZb2nK243lsRRABBbgiIiKSQ70EuAAn//HJvPA/L5CIJXCJibuvnr3t2cAB7siqESLdkQn9YON9cRL9Cd/esSKSIdv2gmzH/Y4F2cMrDcMaZXttR0eHGx4ervY0REREakrfyj6+d873OPKsI3n/Q++v9nSKNj42jhs/8LePG3csn7mc8fg4nxz+JNEZ0Rz3nijeF2f4zmE6Lu8g2hOd8rWIlFGQPbwKctPMbJ9zrqPa8yinnG2CREREpLGlV3C7an8FF7yWQZGWSPqjua2Z2UfOBmBP355AY0V7onRc3sHwncPsX7lfwa1IJWXbq6uWRA1PAa6IiIhkVU8pytnMXuQFuLtf3e17+8iqEeJ98QnH4n1xRlaNEO2J0rq4lZFHRmhd3Oob3Oa6v4gUKLVXNxLx38M7+bg0DAW4IiIiklVDBbjr/APcSHeE4TuH00FqKhU50h0h3hcntjpG25ltxFbHpgSy091fRAqU2qt7ww0T05CzHZeGoSJTIiIiklVsMAbUd4A756g5AOxZ55+inJmK3Lq4ldjqGB2Xe1vYMtOSm3uafdOUs91fqcwiRcrWIiyP1mFSv7SCKyIiIllVbQW3txeWL/c+l9mcRbkDXMA3FTnRn5gQqKYC2UR/Iq/7i0gFVfA9RapLK7giIiKSVVWKTFW4Cup0KcrAlFTk5p5m31ZA0Z6ob/Dqd38FuSIVosrKDUUruCIiIpJVVVZwK1wFNXMF1699Ymb7n/Zl7el0Y7/9tn6Kvb+IFEmVlRuKAlwRERHJanSwCgFuhaugth/cTktnC7G9Mfbv2j/l9iCpyH4Vk0fXjhI9NprX/UWkDFRZuaEoRVlERESyqsoKbqoK6sqV3h+iZU4lNDPmHDWHrc9sZc+6Pcw4eMaE24OkIqcqJqcC4nhfnPgL8XRRqunuHxZDW4fAQef8zmpPRaR4FX5PkepSgCsiIiJZpQLc1q7Wyl64wlVQZy+azdZntrJ73W66T+sueJx6qJjsnOPGxTfiEo5rN15LU0QJf1IHVFm5YVT1HcvMrjCzO83sNTPbb2YvmtlyM+uadN4cM/tPM9thZsNmdr+ZnViteYuIiDSKRuiDCwcKTeWqpJyvWq+YHNsbY3DTIENbhti3Y1/R4/mlbcf74oysGil6bBGRyar9X3J/AySATwIXAv8OfAj4pZk1AZiZAXcnb/8IcDkQBR40s4XVmLSIiEijaJQAN1VoKlcl5XxNrphca8WkMoPawf7BosdLpW2nnodU0a1Id6TosUVEJqt2ivLFzrntGV8/ZGa7gO8By4AHgEuAM4BznXMPAphZL7AO+ATw0YrOWEREpIFUpchUFaRXcF8tbgU3s2JytCdKc0/zhK9rweQAd8GpC4oarx7StkWkdlR1BXdScJvyePLzYcnPlwD9qeA2eb8B4KfAu8o7QxERkcZWlT64VVCqFdwgFZfDKjPAHdo8VJIxaz1tW0RqR7VTlP2cnfz8fPLzCcBzPuetBY4wM5X3ExERKZNGSVFOreAOvDaAG5/aCzdfbUvbpgRv0Z6obyXmsNq3vbQpylD7adsiUjtCFeCa2WHA54D7nXNPJA8fBPj9d+qu5Oc5Ocb7UzN7wsyeGBsbK+1kRURE6tz42DhjI2NYk9HcVu1dTeXV0tFCx7wOEqOJkgV1tarUe3Az07bbl7Wn05UV5IpIOYQmwE2uxP4EGAM+kHkT4PdfqTbdmM65G51zpznnTmturu9fzCIiIqWWuXrr1Xysb6lV3FIUmqplpQ5w6yFtW0RqRygCXDNrw6uUfBTwNufcxoybd+Gt4k6WWrlt7N9CIiIiZdIo+29T0vtwX23sPy1KHeDWQ9q21KneXli+3Pucz3GpCVVf1jSzKHAn8GbgfOfcs5NOWQu81eeurwfWO+dKU/1AREREJmiU/bcppeyFW6iRVSNEuiMTAsJ4X5xEf6JiAWE59uD6CcNjlQbW2wvnnQejo9DSAitWwJIl2Y9LzajqCm6y1+1twHnAu5xzv/Y57W7gMDM7O+N+M4GLk7eJiIhIGTRagDvnKG8Ft5oBbhh6xmau4A5vHWY8MV6W64ThsUoDW7nSC2ITCe/zypW5j0vNqPYK7jeAK4HPA8NmdnrGbRuTqcp3A73ArWb2cbyU5Ovw9uB+scLzFRERaRixwRjQOAFuGPbghqFnbGaA68Ydw9uG6VrQVfLrhOGxSgNbtsxboU2t1C5blvt4b68X7C5bphXdkKt2gPv25OdPJT8yfRb4e+fcuJm9E/gS8E2gDS/gPcc5t6FiMxUREWkwqRXc1q7WKs+kMlJ7cKu5ggsTe8a2nTl1/2q5pQLcrsO6GNw0yGD/YFkCXKj+Y5UGtmSJl348OWj1O6605ZpS1QDXOdeT53m7gGuSHyIiIlIBjZaiPPPwmViTsXfTXsZiYzS3VufPpMk9Y5t7misW+I2PjbN/934wmHfCvHSAy+LyXK+aj1WEJUv8A9XJx/3SlhXghlYoqiiLiIhI+KQC3GhnYwQckWiEmYfPBAcDrw1UZQ7V7hm7f9d+cNB+ULv3XFC+QlPVfqwieUulLUciE9OWJZQU4NaJkVUjU34hxPvijKwaKepcERFpXKODFVrBDVFLjnSroCrtw612z9hUevKMuTPo6vbSkssV4Fb7sYrkLZW2fMMNSk+uAdXegyslkqpEmPpFkfm/osWcKyIijasiKcoh29s2+6jZsLJ6+3D92uNEe6IVS9tNBbgdh3TQuaATgKHN5enIWO3HKhJItnRmCR2t4NaJzEqE+1funxDAFnOuiIg0rooUmQpZS45qr+BWWyVXcEVEykEBbogFTSXOrETYurg1Z8Aa5FwRkXqlLRtTZT4nqQB3Vuus8j0nIdvblmoVVO1KytUyvH0YgPa57QpwRaaTbXtFiLZdNCKlKIdY0FTiIJUIVbVQRERbNvxkPiejQ6MsXLSQ+UPziXRHynPBbK06qiS9gvuqVnAV4IrkkG17Rci2XTQireCGWJBU4iCVCFW1UETEoy0bU2U+J4d3Hs7b3/12Bo4YKO9zsmQJXHddKP4IbPQV3Al7cA/tBIPhbcMk4v6Fn/bv3s8dV9xB38q+Cs5SJASyba8I2baLRqQAN+TyTSUOUonQ79zocVFGnxudcF6jp+mJSGNolC0bQdKxU8/J0QuO5pnHn4H5lZpl9XXO76S5rZn9u/YT2xsr67XCmCK/f8d+wFvBbWpu8oJcB8Nbh33Pf+6Hz/H8nc/z0OceKtucwvg8iWTdXhGybReNSAFuyE1OJc62ytq2tG3KH2XRnqhvhUK/c1tOaCH+Yjw9fmqVt2wpaSIiIZHv+2ytS6Ue5/M+n3pOnn/5eU5600m0j7ZXerpVY2bpVdxyF5oK8j2plMwUZSBdSXlws3+a8vbfbgdg0282MT42XpY5hfF5EsnaOkgthapOe3BDLDOVONoTpbmnuWzpc5kpaa2LW4mtjjV8mp6I1L9Kvs9WW77v85nPyZqb1/D8o89z6ZxLiZ8Qr7vnJJs5i+aw4/kd7Fm3h/knl2/5Ooy/e1NFplIBbld3F1ue2pJ1H24qwI3vi7P12a0sOHVByecUxudJBMjeOkgthapKK7gh4Zd+M7p2lOix0bzSjkuhUdL0RERSgmzvqAf5vM9nPiexwRgb123EzrK6fU78VGoFF8L3u3fyCu50haa2r92e/veGVRvKNq+wPU8iEl4KcEPCL/0m/kKclje0TDgvW9pxKTRKmp6ISEqQ7R31IJ/3+cznJN0H93Wtdfuc+EkHuBWopBy2373pAPeQ6QPcfTv2MbztwN7cjas2lm1eYXueRCS8lKIcEtVOv2mkND0RkUZUyPt8KsBt6Wzxvb1epVoFlbuScth+98b3x4kPx4m0RNLf81wB7vbnvdXb1lmtxAZiZVvBDdvzJCLhphXcEKlm+k2jpemJiDSaoO/ziXiCRCyBRYxIa2MV85lzVGUC3HL87i2m4nBmerKZAQcC3KH+oSnnp/bfHnvxsbR0tbCnb09ZeubqbxQRCUIBbohUM/2m0dL0REQaTdD3+czV21Sw0yjSvXD79uCcK9t1yvG7t5iKw5P330LuKsqpAHfeifNYePpCADb0ln4VV3+jiEgQCnBDIjP9pn1ZezpdWXtMRESkGtL7b7taqzyTymub1UbbnDbi++IMbir9imQ5ZW552r9yf6BU3sn7byF3ivKO3+4A4JDXH8LhSw8HyltoSkQkHwpwQyJI+k2+6UfFNkZXY/Xw0fdEaoVeq7WvUfffphy+xAvYHv78w1WeSXbZfs4S/YmCtjz5reB2zOvAmox92/eRGJ34N8m2tdsAOOSEAwFuOQtNTab3GRHxowA3JIKk3+SbflRsY3Q1Vg8ffU+kVui1WvsaPcA9/4vn09TcxOpvr2bT45uqPR1f2X7OXJMraMvTvu1TA9ymSBOd87005aEtB/bh7t+9n6HNQzS3NzP7yNkc9vuHgUH/6n7GRsZK9RBz0vuMiPhRgFuD8k0/KiZNqRT3l9LT90RqhV6rtW90sLED3HknzOP0a08HB/d+6F7GE+PVntIUfj9nrW9pJfarWEFbnvxWcME/TXnH88n05OMPwZqMtlltzHvDPMbj4/Sv7i/VQ8xJ7zMi4kcBbo3Kt+JysZWZ1Vg9fPQ9aQz1kHpXrddqPTx3YZBewe1qzAAX4OzPnM3MhTPZvHozq7+9utrT8TX558zGreCKw357cCGj0FRGgJsqMHXI6w9JH1u4xCs0tbG3cmnK+p0oIpMpwK1R+VZcLrYysxqrh4++J42hHlLvqvVarYfnLgwaPUUZvMf+tn95GwArPrmCoa1TW+VU2+Sfs0h3pOCKw9Ou4G6eGuDOff3c9LFqFJrS70QRmUwBbg3Kt+JysZWZVdk5fPQ9aRy1nnpXzddqrT93YaEA13P8ZcdzzIXHEBuIcf8n7q/2dCYo9c9ZkBTldIugE+alj2UGuOVsr5Si34ki4kcBbg3Kt+JysY3Rs91/pLcyVZxlKjW7byy1nHpXqddqkCqyek8KRgGux8x4+9ffTqQ1wprvr+G1h1+r9uiA3/gAACAASURBVJTSSv1z5ldkCg4EuEP9B1awt6+dmqJ80DEHMWPuDIa3DrNn3Z6C5hCEfieKiB8FuDUo34rLxTZGz3r/JW0VqeIsU6nZfWOp5dS7Sr1Wg1SR1XtSMLHBGKAAF7zA7Yy/PQOAez98L4l4OAKoUv+cpVZwOw7pmHB88gpubG+MvRv3EmmNMHvR7PR5ZlbRNGX9ThQRPwpwJbBKVXEWaWRKvctPkCqygN6TAlCRqYne8n/fwpyj5rB97Xaeuumpak+n5Jxz6QC3/eD2CbdNDnC3P5/cf3vcXJoiE/+UXLjUKzRVyX24IiKZFOBWQT2kyVWqinMjq4fXiRSuVlLvwvA6DVJFNp/3pHI9Jr9xh+8dZvie4YKvVc7nXynKE0Xboyz73DIAnvpO/QW4sb0xxsfGaelqobm1ecJtk6so+1VQTil2BTcM7ymV0CiPU6QaFOBWQT2kyVWqinMjq4fXiRSuVlLvwvA6DVJFNp/3pHI9Jr9xR9eOMvrb0YKvVc7nPz7kjakA94DjLz2elq4W+h/vZ8eLO0o27sCGAcZGxko2XiGy7b8FL2XZIsb+XfsZi40dCHBPmBrgdp/WTVNzE9ue3UZsb2zCbWMjYwxtyV2JOgzvKZXQKI9TpBoU4FZBrafuVqqKc6Or9deJNIZqv06DvM/ke265HpPfuJ3v7qTz3Z0FX6ucz//IgLeSpAD3gOiMKK+//PUAPHPrMyUZs391P1876mv84KIfVKTycDbZKigDWJPRtSBZaGrzEDt+6wX3fiu40fYoC964ADfu2PTYJgDGE+M8ffPTfO3or/HVw7/K1me2Zp1Htd9TKqVRHqdINSjArZJaTt0tpopz9Lgoo8+NTjivXCk59ZD+k+/rpB4eq9Suar6fBUnlDnJuuR6T37jFXqtcc9354k4A5iyaU5Lx6sVJf3QSAM/e+ixuvPiA9Fdf+BXjY+Ose2Ada76/xvecYt/j87l/tgJTKZn7cLet3Qb4B7gAC5cc2If76v2vcuPiG/nJB37CYP8g42PjvLri1ZzzreW/kYJolMcpUmkKcKukllN3i6ni3HJCC/EX4xVJyamH9J98Xyf18FildlXz/SxIKneQc8v1mPzGLfZa5ZhrfF+cnS/vpKm5ibnHzy16vHrSs6yHmQtnsqdvD+t/tb6osXa9sovnf/x8+utffvyX7N+9f8p5hbzHD28fTu+Zzef+uVZw4UCAu/OlnQy8NkBTtImDjj7I99zUPtxHv/Aot1xwC1vXbGXm4TM5/vLjAdj2zLas807Nr1b/RgqiUR6nSKUpwK2CRk7drWRKTq2n/wR5ndT6Y5XaVY/vZ+V6TH7jDt0xxNAdQwVfq1xz3fbcNnBeldzJBYd89fbC8uXe5zpnTcaJf3giAM/cUlya8q//5de4ccfJV5/MkWcdyb7t+3jgUw9MOS/oe3x8f5wbF9/It075FvF98bzuP7zdK3bWPrfdd8zObq/Q1LoH1gEw99i5NDX7/xmZCnDH9o/R0tXCecvP4y9f/EtOv/Z0ALas2ZL1OanH9xQ/jfI4RapBAW4V1Ep11HKpZEpOMdcqR9pvkDGDvk6U6iTVUOz7WbaficEfDpa84nC+sj2mkd7i3hP8xm05oYWW17cU/PwVuxUk2/O//1feKuKhJx06/SR6e+G88+DTn/Y+N0CQm0pTXnvH2oKLQ+3buY+nv/M0AEs/vpR3fOMdNDU38cS3nmDT45umnB/kPX7N99ewd8Ne9m3flx5ruvtPu4Kb3IO7boUX4GZLTwaYuXAmF3zpAt7yt2/ho7/7KGf87RlE26MceqL3etq+dnvWXsLlek8J25adRv9bUKScFOBWQTmro25YtSHdn64Qrz38Gjtf2ln0PHKpZEpOMdcqR9pvkDGDvk6U6iTVUOz7WbafieZFzSWvOJyvrI9pSVtR7wl+43Zc1EHHOyfueQzy/BW7FSTb879lg7fCdujJeQS4K1fC6CgkEt7nlSvzmnstm3fCPOafOp/YQIyX7n2poDGe+PcniO+Lc8yFxzDvDfOY94Z5/P7///vg4Gcf/hnjifEJ5+f7Hj+eGKf3ywf+kyHVrme6+wfZgwv+FZQzLf3rpZy//Hw65h0Yr3VmK7MXzSYxmsj6t0bQ95TxxDgv3v1iuq1VrWzZqZVK+SK1SAFuHRncPMjNy27mpiU3MbQ1dxl+P5uf3MzNy27m5mU3MxYrT7uCSqbkFHutcqT9liuVWKlOUquy/Uy0n94+5XixFYfLNdewZUsEmWe2c19+4mUgzwB32TJoaYFIxPu8bFlpH1BIpVZxC0lTHhsZ47GvPwZ4q7cpy65fRtdhXfQ/0c/qG1enjwd5j3/ppy+x6+VdYN7XG361Ia/779/hrdpPtwc3JdcKbi7zT54PwNY12SspB/HMrc9w+7tu56EbHgJq5+dURMpHAW4dWf/oesbj48QGYqz42xWB79/75V5wXguAZ3/wbBlmGCwlxy/NKEiKYinSf8qR4pzoT5Q8lVipTlLLsv2claPicLnmGjZB5jn53OYjm9NtXPJKUV6yBFasgBtu8D4vWVKqhxFqJ773RKzJePlnL7Nv575A911zyxqGtw0z/9T59JzTkz7e0tnChf9yIQAPfPIBhrd5v++CvMev+tIqgPR+1429GxnbNDbt/fMtMpVSaIA776R5ADlbBQXR/0Q/ABtXbUwfC9v2JBGpLAW4dSSVhgTw9M1PT/h6OgPrB3juv55Lf9375d6y9OMLkpLjl2YUJEWxFOk/5Uhxdk2u5KnESnWSWpbt56wcFYfLNdewCTLPyefueWwPsYEYMw6ZQef8zvwuuGQJXHddwwS3AJ3zOzn6rUczHh9n7X+tzft+btylU4iX/s1SzGzC7cdffjxHv+1oRvaM8Itrf8F4Yjzv9/gNvRvY8KsNtM1u45zPnkNXdxf7d+1n+ODhae+fKjKVT4Db1NzEQcf4V1CeTqlXcFPtrLY+szX9d0vYtieJSGUpwK0jqf+9PPKsIwH42V/8jPGx8Vx3SfvN136DSziOv/x4urq72L52O6/84pWyzTUffmlG2VIUE/2Jkv+Pq2/F09uH/h975x0Wxbn24Xt2WToiCNgAK6DYu6ixN2zRWGJNYnpi2kk7Jck5SU6+k5OcVI0lPbHHEnvvDbCDIDZUVCwURTossPP9MezKwi4sUpby3te1l7I75Z3Z2Zl55vk9v4essKxi05kyxAHQBGiMxmrX146cIznFZGIZW4pLzerKE2NrPy2v6+u3Nuakk1lhWcV/f+V0HK6MsZo7J1jz+yuLnNXUtLo9OrxbeNOoU6NiwZfAmIeRKV/ccpG7F+7i6utK4OTAYp9LkkTwvGDUtmoil0fyQ9cfuLzLsutx6BdK4Nz9pe7YOtsa3IzNtTMqfP7RZ3DttfYmj1+HBg6oNMpto7ufO2rbhwv49KqAkpyUy4I+wM1JzSHlWkq1LE+q6+d5gaCqEQFuLSE3K5fbp24jqSQmrZqEazNX7oTf4cSiE6XOm5Oaw6kfTwHQ7+/96PlqTwAjkwprYalEsTKeuJqShNkPtCd7f3ax9ZgyxMlYm4Fte1ujsUo6yaRMDJk6+8TY2k/L6/r6rY056WXe1eKSyvI6DlfGWM2dE6z5/ZVFzmpq2tj8WLyaehmkpALztBnfBltnW+LC4rh7yTKDxpD/KRLiXm/0Qq0xfZw08GvA5DWTcfV1Jf5MPEuHL2VZ8DKlfZMZ7sXc49y6c6ht1YbruE9fJcA1p+jSn3+0l7VkJ2fj3dKbvJ15Jo9fSZIMTspe7R7+2HBr6Yatsy3pt9MNWeOHJTczl5TrKYa/48/EW708yRR1/TwvEFQ1FjS3E1Ql59ef59bJW8Xed2nsQvcXuyOpTD9Nv3XiFro8HY06N8K5oTMjvx3JH+P/YO/7ewmcHIhzQ/Mys1M/nSInNYfmA5vTpFsT3Fq6cfCTg1zZfYU7EXcMciJrUFRmZNNcOWSLvlf4iatdNztyTuaU+4mrKXmvQ28HbBrZmFyPqfeLjtXUmPRBe2773Aodf02hMr47sf6ag6nfmf43URSn0cXdXc1NWxmU9ZxQlcTujyU/N59Ww1qVaZ+amvbKmStEH45m/HPjK2WstQmNo4a2E9sS8XsEp38+zdD/Di1x+tgDsVw/dB07Vzu6Ptu1xGkDxgbQcmhLjs49yuH/HCZmewyXd16myzNdGPjRQEOwqSf0K8VHo8PMDobP9BncG0dMB7j680/66nR6De5Fx14dcZpk/vh1aeJCyvUUPAI9Shx7SUgqCa8OXsSFxhF/Jp6WQ1o+9LLuxdwz+jv+TDwB7wcUm66s5wlT9x4VZTBZF8/zAkFVIzK41Yj0+HRWTVzFoU8OFXttnbOVi5vNtyLQX7y8+3gDEDAugNbBrclJyWH3X3ebnS8/N5+wb8IACHpLqZ1ycHOgyzNdAOtmcU3KAUuQKFaV+YulhjhAmWRSFT3+8kqiqlJSVRnfXVnGX1WGJFVpPFYdqa0yvaLHT2WUTJSENkPLsuBlLBu5jHuX75U+QynopaMWGUwJ6PRkJwCOfHaEZaNMZ1kzEjLYMmcLi4csBqD7i92xc7ErddkaBw39/tqPV2NepccrPUCCUz+eYp7fPA58fABthtIaJyMxg/BflZ66QW8+qINu1KURNg423L1w1yBBLraO5hrym+fTa2AvYmJiSjz/uLV0U5bbuXwPvvXHVnmNppIuJAEgqZWH/xVR11tZpQg1xaDOFLX13C2ovYgAtxpxI+QGsk7Go40HAz8eaHj5j/UH4PyG8yXOCw+e1kqSRPBcpYYn4vcIs/U30WuiSb2RSoOABviN8jO83/uN3kgqiagVUaTeTK2Q7SsrpmRGJUkUq8r8xVJDHO1ZbZlkUhU9/vJKoqpSUlUZ311Zxl9VhiRVaTxWHamtMr2ix4+skqt0O68fuk5edh6yTibs67ByLUuboeVezD1UNio82j58lq5EQkPh00+Vf2sBLQa1YMTXI7CrZ0fMthgWdVrEpuc3kXY7jdysXA59eoi5redyYsEJkKHr810Z8M8BZVqHk6cTo+aN4uWzLxPwaAC5Gbns/9d+5vnN4/Qvpzn23THysvPwG+VnJB9Wa9Q07dEUUAyoTJEbm4t0WeLo/qP4B/iXeP4Z8ukQxv40loBxxbOkZUHffqq8Aam+/rbF4BbK8irAmbmyShFqikGdKWrruVtQexES5WqEPgsbODmQAR88uPjFR8ZzcdNFLm2+hKyTi8mUZVkuFuACuLd2p8+7fZQM8MtbeXL/kzi4ORjNp8/QBr0ZZLRctxZutH2sLdFrojk271ipsqvKwJR0zpxEER5kSzXNNdg0t6mU3neFn+wWXk9h86jC79u2sy02VlPjMbfc8oy/vJKoqpJUVca2g+XjL+/6y7KfTE1r7tipjfK12iDTk2WZkz+cxLuXN406NyrxnGBqO3X5Oo5+exSv9l60Gt6qQsZ0de9Vw/9P/3KagR8NxLGBaSfc0kiISgAZPNp6YGNXCbcIoaEwZAhotUrP3FrSVqj3G73pMKMDBz46wIlFJzj14ykil0diX9+etJtpAPiN8mPo50PLVb/qEeDB1PVTiT0Qy663d3HrxC02PrPR8Hnhnrp6vPt4c+3gNW6E3CBgrHFgqj9+k5skc3TvUVRNVfRc29Ps79LV15Wuz5QsrbaEisrg6gPcNuPbELsvlruX7qLN0GLrZFvKnOax72OPLMtELInAvZU7Pn18yl2KUFnXuaqiNpy7BXULkcGtRpgKUgG82ntRv3l9MhIyuHnsZrH57l26R9bdLJwbOVO/eX2jzx75+yO4NlNMKua2mkvYN2Hka5UM4rWD17h98jaOno4GJ8jCBL2t3HSc/P4k2nRthWxjZWGpqUR5ZTZlMcQpi6lFZfWxLa900tL5TblIW9qz2Ny2Z4da1ge5pPVYMn7tWS2aAM1Dr7+sEuOiYzJnPFZbexjXZJkeQMz2GLa8uIXVk1cjy7LZ41fSSSa3M3ZfLDvf2snSEUtZOmKpyRt8c+cpU7+z3NhcbK8pN/POjZzJy8rjxMLSzQXNoc+oVZo8ef9+JbjNz1f+3b+/ctZjBZw8nRj1nXGWNe1mGg07NWTWrllM3zK9XMFtYZoPaM6zR5/lsWWP4errCkCT7k1oNqBZsWl9+/oCxn1i9eiP3/tZ9wHIsc+pkvOP/vhKPJtIfu7Dr0svUfbq4KUoDmRlmeXl6p6rrH9iPWseX2NoPWTpucvU79fcdaYmnedr+rnbUoQcu3YgAtxqQl52HrdP3gYJvHt7G30mSRL+4xSZ8oWNF4rNWzgwLtrSQeOoYeaOmbQY3ILsZKWn3vzA+USviTa0E+gxpwcah+InKu9e3vj09SH7fjanfzldIdtZWVjaI7C8Mhtz63GZ5mLR+ss7/rJSXumkpfObcpG2tGex2W0PsrdomSWtx5Lx557PxbZ98Uy7pesvq8S46JjUTdSV8t1XV2qyTA/gwgblHHwv5h5xYXFmj191E7XJ7Uw6n2SY7vLOyyzqvIgNz2wg7Vaa4X1z5ylTv7P01enEHI9Bbatm7I9jATg2T5GrPgz6gFsvIa1wBg5UMrdqtfLvwIGVsx4ros+yPn3kaab8OYXnTz5Py6EPb6RkDkkl0WF6B1658AqTV09m6oapJts6eQcp9xQ3j900PODWoz9+9fW5jh6OVXL+sXOxw62lG/nafEMWtqzIsszdi8q8HgEeFdp+6MjnRwBIjUsl5Zri0mzpucvU79fsdaYGnedr+rnbUoQcu3YgJMrVhNunbpOvzcervRf29Yuf8ALGBnBs7jEubLzAkP8MMfrMEOD29Sk2Hygn/lm7Z3Fp6yV2vbOLpHNJrJ68GgAbext6vNzD7LiC3grixpEbhH0dRvup7XHyKi4RrknUJZlNWaWT5Z2/qHzLeYri3F2REmlTyzS3Hv17D7v9lq6/LBLjmi5TKy+Vuf2Xtl3i9snbdH+xO44eDyfPLQ1ZJ3Nx0wOzvzNLzuATVPy8W9J26l1f+/61L7lZuZxYcILwX8I5u/Isg/49iKA3g0o8TxX9nd1rdI+4q3E0G9AMv9F+NOrSiDun7xCxJIJuz3Ur8zbqM7iV5p4fFKTIkvfvV4LbWiBPNkdRNVZlYWNvQ+Ck4v109Tg2cMSjjQdJ55O4E36Hpj2bFpsmM7EgwPWsnN+OKRp2bEjylWTiz8Tj1b54Zjv8t3AcPRzxH+Nvcv6MhAxyUnKwc7XD0dORhh0bErksstyy5zvhd7iy64rh7xshN3DCyeJzV228z6hL167a+P3VRUQGt5qgD1L1LshFada/GXb17Eg8m1jMJVNfu1vSxVSSJPxH+/PSmZcYvWi0IVDtPLszTp7mg9aAcQE08G/A/dj7fNvyW/Z/uJ+ctJwybVt1o67IbMoinSyLpMqc9NLUfq1oibSpZZp7r6zS0Yddf1kkxpUlRa8pVNb2X9h4gRVjV7Dvg33MbTWXQ58eIjez4rMLt0/dJu1WGrYuSiYmamUUeTnFM6Ulbac+wG3aqynB3wbzcvTLtH2sLbmZuex8aye3TtwyzGPJ7+zCUSWj3GJICyRJos/bSg1m6JehyDq5TNsny/KDDG5lOigHBcHf/16rg9vqhv7ewpzhZOEMblWhVwmYyrjGHY1jw+wNrHl8TbGssx595tcjwANJkh7KuMrUtS96fjRd+3XF3k1JNtwIuVGmUpra6Ixvavs1bTRoo4zL12qSlLckKXJduU+szYgAt5pgrv5Wj9pWTevg1gBGGYSs5CwSoxNR26lp1KX0J+4qGxXdX+jOqzGvMnXDVEZ8NaLk6dUqpm+djv9Yf3Izcjnw0QHmtprL0blHTd7Y1QTqisymLNLJskiqzEkvTe3XipZIm1qmuffKKh192PWXRWJcWVL0mkJlbP+1g9eUOrl8Gc9AT3JSc9j7j73M85/H6V9Po8vXlXfYBvQlIh1ndaRhp4ZkJ2dzaeulYtOVtJ36ANe9tTsADfwaMGXtFEObtpD/hQCWu7VnRCo14XoX2cDJgbj6unL3wt0SW8uZIuVaCjmpOTh5OeHcyHzvdEHNo6Q6XLBSgFvwECXhTPG2SobfQWYud8JNS4719bcNAhoYLS/+TLyhbrY0il77ko8m06ZBGxJuJzDy25GAcn9WllKa2uiMb2r7bdvZknsht8ZKeUuSIteV+8TajAhwqwHmXJCLorflL1yHGxemXKyadG9SJsdLOxc7AsYFYGNf+jzurdyZtnEasw/NxqePD5mJmWx/fTvz28xnz3t7uHbwWrlMIqqSwjIbS3rT1jbMbT9g+H/W/iyLJLaF588Kyyr2vqmexTlHcgwS4ZLWY25dppZZUm9kS7ff0mnLsi5B5XMn4g4rxq4gLzuPbi9046Wol5i1axaNujQi7WYaG5/eyPedv+fS1ksW3/CWhP7cGzAugE5PKL1Pzyw+Y/H8unwdyVeSgQf9RPX0/ktvVBoV0WuiSQ5Jtuh3Jg2Q6BvUl2Ztmxlkp2qNml5v9AIg5IuQYmO4uvcqq6es5sruK8U+M/S/raz6W4HV0N9bXD9y3eRvoTplcO9eusu5P88Z/jaXddbX3+oDXOdGzjh6OpKTkkPqDcvaGxaWo2btzyJ3ey7bVm3DrbcbgRMDkdQS8RHxZpVrRecv2lWhNl8nTG17TZLymhs/UKfvE2sLIsCtBiRfSSYjPgNHD0fDU31TtA5ujaSWuHbwGlnJSsNxSwLjisK3ny+zD89m6oapeAZ6cj/2Pof/c5jfBvzG5w0+Z+X4lRxfeNxwA1cWqsq1TkhEzW+/JZKcsrhIm+tZbKlE2NI+yCX1Ri7L9j/s+s3NX1OcGGvKOIty7/I9lo5YSk5qDoGTAhk1fxSSJNFyaEueP/G84i7bzJWEqASWj17O4sGLDfLfhyHlegrxEfHYOtvSfGBz2k9rj6SSuLjlIpl3My1aRuqNVHS5OlyauBRrY1KvaT06TO+ArJO5tv6aRb+za+evsW3VNgL6BKDWPMiadH22K3audlw/dJ24o8pD0MRziawYu4LFQxYTvTqatdPWknUvy2gMVSJPFliFBv4NcHB3IP12usE0qTCGGtwqDHDdWrhh62xL+u10MhIfuNOHfhUK8oN6YHNZZ71EuYG/EuBKkvRQRlOFr30RoRHEXY2jzzt90DhqaNylMbJONtnBwtT8FeGMb+1zclnWX9OlvGUpb6or94m1BRHgVgNKckEujIObA80eaYacLxOzPQZ4cOKvKjMLSZIIGBfAi2deZMa2GfR6oxcebT3Qpmm5sOECW1/eytxWc5nnN4+tr2zlwqYLFrUYqirXOiERNb/9lkhyyuIi7TTaCacxTsWmtVQibGpdppZpbj3llQhbun5z89cUJ8aaMs7CpN1OY+nwpWTEZ9BiSAsmLJ2ASv3gclbYXXb4l8Oxd7Mndn8sP/b4kbXT1j7UQ7gLm5TsbasRrbCxs8GlsQuthrdCl6vj7B9nLVpGUXlyUfT1s1u+20Kus/HvwtTv7Oqeq8RdjUNua5yRs3Oxo/uL3QE48NEBNr+0mYUdFnJx80VsnW1x93MnMymTPf/YYzSfoUWQyODWOiSVZLhP0N9zFEafwS3Jk6MyxuTVQTGX0j9cyUjIIPzXcADGfD8GUMZrKutcuAZXz8P019Vf+xKkBNp1bkfPyT0NJmt6805T+6zo/BXljG/tc3JZ1l/TpbxlKW+qK/eJRkjSKCTpIJKUjiSlIkknkKTBBZ81R5JkM6/6JS+48hEBbjWgNIOpwujbBV3ceBFdns7wdF7fBqCqUKlVtB7ZmpFfj2RO9BzeuPYGY38cS+CkQOzrK3Vmx+cfZ+W4lXzm/hkrx68kO8X808eaLnWp6VSVdLs6S8SvHbzGsuBlDxX8mKKsx/SlrZdYNmoZ0WujK0ROW1njtDZxYXEsGbaE5CvJNOnehMfXPW62PMPGzoagN4N47fJr9Hm3D2o7NVEro/iuzXd83/V7fuj2g9Fr7bS1Zr0FLm5U6ln1pSKAoX94xOIIi8auD3DdWruZ/NyrvRd+o/zIy8rj2PxjJS5LlmWu7r0KPKi/LUzPV3ui0qiI2RbDyUUnAej+UoH/wvqpqGxUnPzhpFFmqtJ74AqsijmjqdzMXHIzc1HbqdE4Ve3vvqgx1LHvjpGfk4//WH/ajG+Dg7sDabfSimWd83PzlXO1BO5+7maXVxr6a5L9WHs2fbeJbau20bNLT8M1Sf9QwFwWuTKuadY+J1u6/up8PbeEmj7+SkeSXgA2ACeBCcBkYDVQVObxKRBU5JWGlREBbjVAf+LUm0CUhP7m6tK2S9w6eYvcjFzcW7vj3NC6hiCuvq50fbYrk1dP5p3Ed3g65GkG/GsA3r29kfNlLmy4wMpxK8nNMn/iqOlSl5pMVUlyqqv0R5uu5c8ZfxKzPYbDnx2usOVaekxnJGbw58w/idkWw+pJq/m5989c3Xe1wsZRUeO0JonnEvljwh/8HPQziWcTaRDQgOlbp2PnYlfqvA5uDgz7bBivXnyVTk92Qpen487pO9w+ddvoFbUyymTdak5qDlf3XUVSSfiN8jO832Z8G2ydbbl59KahHrAkDBncVuZLUfq8q2Rxj393vEQn6OTLyaRcT8HB3cFkS596TevR7QWlTZD/WH9einyJ0QtG49zQGc9AT3q/2Rtk2PLSFnT5OrTpWu5dvodKo8KzrWep2yKoeZgzmtJL7B09HEtUkVUGhTOu2gwtx+cfB6DPO32QJPNZ5+QryejydLj6uqJx0JhcXmHMym5Ds3Ga6MTZA2fJiM8gzzUPl6kuhmuSYf2hN0y6klfWNc3a5+TylCyVd9tNfVcZWzLI2Jxh9F55ZdtlGb+1ZeNVjiQ1B74B3kGW/4Is70KWdyDLnyHLm4tMfQVZDivysrqeWwS4ViYnNYf4yHhUGhWNuzUudXr3Vu6KU2hKDkf+qzQiryp5sqWo1jyFdgAAIABJREFUbFT4BPkw8MOBPBP6DK9eehWXJi5cO3iNtVPXossz7Wpa06UuNZmqkuRUV+nPgY8PkBqnmJJEr4omL7tiHMItPaZ3/2032cnZeHXwwqmhEzeP3WTx4MUsC15m1kG0IqnOv72UGylseGYDC9sv5Pz682gcNTzy3iM8e/TZMsspXX1dGf/beN649gbPnXjO6DVh6QQADn1yiOSrxln8mB0x6HJ1+PT1MapR1DhqCJys9B+NWFJ6Fjf5srLckrwWmvVvRpMeTchMyiT893Cz0+mzt80HNUdSmQ5KRn4zkjdvvcm0jdOKBa0DPhhAPZ963D51m5PfnyQhKgFk8Gzridq2+srTBQ9Pk+5NUNmoiD9jbJpkjfpbPfqHM/ER8Zz+5TRZ97Lw7u2Nbz8lGDeXddY/UCosTwbwDPREUkvcu3TP6AGROdmtfZA9Nr42hH4RCigPmGxb2BquSfW861HPpx45KTkknkssNv7KuqZZ+5xcnpKl8m67qe9Ke1aLNlpbobLtsozf2rJxK/A0oAMWWXsgD4vltruCSiHuaBzI0LhrY6OnkCXhP9afxOhEzq8/D1gmbbYmbi3dmLlzJr8+8isXNl5g0/ObGPfzOKMnxXWpiXjK9RT2vr+Xm0dvMv738Xj3Lvv3d+TzI4T/Fs6MrTOo39zqpQ7VgvDfw9n97m60GcY135JKosvTXRjx1QiTgUDC2QTCvg4DCVyauJB2M42LWy4SODGwXOOx9Ji+EXKD8F/CUWlUTF49mXpN6xH2TRhHPj9CzPYYYrbHEPxdMD3n9CzXeMo7zpKQZZld7+7iyq4rPLbsMbzaeZV5HLv/tpvj848Xk2fnZeUh62QktUT3l7rT/4P+uDR2KfPyC+Pq44qrj6vRe026NSFmawyRyyPZ/vp2pm2cZvhM35qtsDxZT8dZHQn/NZzIpZEM+miQ2WATSq/BBcXnoM87fVgzZQ2hX4bS7fluRvXFeq7uKZAnDykuT9ajUqvM7itbZ1tGfjOSVRNXsecfewxtioQ8ufaicdTQqEsjbh2/xRcNvzAcq3K+8puryvpbPfoa3MToRMK+CgMeZG/BfNZZX3/r7m/8W7Kxs8GjjQeJZxNJOJtA0x6Ku3hh2a1dNztyTuYYznHnN5zn7sW7uDZzpd3kdsXG6NPHh7N/nOVGyA2Lz21ZyVn8NuA3kyUv7q3deXLfkzi4OZic19r3Q+bWbzfKjnVvryM/N58ZW2egsqmcHJmp78p5iqJSNPX9VQUlHT+1lH7AeWAqkvQB0AyIBb5GlucXmfZTJGkRkAEcAN5DliOrcrCmEBlcK3PjSNldkIveZFW3DK4pvNp5MX3LdGwcbAj/NZzdf9tt9Hl1la5WJNkp2ez+227m+c/jzJIz3L14l+Wjl5N0PqlMy0mISmDPP/aQdC6JI58fqaTR1izObzjPxqc3kpGQQW5GrtFLm6bl6LdH2f333cXmk2WZrS9vRZeno/uL3Ql6U7nJP7PE8tYv5rDkmNbl6djy0hYA+r7bF48AD2ydben/fn9ev/I6vV5X2r3s+2BfscC9oqiI397e9/cS+kUo8RHxLBu5zJANt5SU6ymEfBGCNl1b7PuTZZl2U9ox59wcRi8YXe7gtiSGfTEMu3p2XNx00dASSJen49IWpdet/1j/YvM0H9Ccej71uB97n+uHTbczAZB1MvcuF9TgtjJdg6un7WNtcWvpRvLlZM6vO29yWXoJu6n6W0tpM6ENrYNbk5OSw8GPDwLCYKq203FmR5CUB0f635hesdJyWMsqH4+dix1uLd3I1+ZzP/Y+7n7uBDz64B7HXNZZ3wO3aAYXjLPChTEnuw3/RVFK9Hy1p8mgzSBTPmLeaKooJxaeICEyodj5LDcjl/iIePa+t9fsvKbOyZo2GrRRxteA8kpkS5NtF16/w6MOhH8ZzqWtl7iy6wrn1p0ztUizyzUlMS5Jdmzquyr6Xv6t/CqVDVu6/rQVaTVBzmwjSdKJQq/ni3zeBPAD/gf8FxgO7AK+Q5JeL5gmB/geeAEYBLwNdABCkKS2VbERJSEyuFbmYdr8NO3VFEdPRzITM7GrZ4dnYM2ol/IJ8mHK2imsHLeSkM9DcPJ0MriGmpKE6E9oNZ383HxO/nCSAx8eMDhVtp/Wnuz72cRsi2HpiKU8E/oMLk1Kv3GXZZmtc7YanriH/xrOoI8HWUVaVl24fuQ6a6euRdbJ9P9nf/q+09fo89gDsfwx/g9CPg/BpbELvd/obfgsclkk1w5ew9HTkcH/N5i87Dx2vbOLS1svkXk3E8cGD79fLTmmj80/RvyZeFybufLIPx4xmtbRw5GR34zk1vFbSpb313B6vlLxWdzy/vaOzj3K4f8cRlJLhszJ0pFLmX1ottkMRVHCvg1Dzpdp93g7xv00zugzlY3Kon7dFYFLYxcG/XsQ21/fzrbXttFyaEtunbhF1r0sGvg3MHkzLakkOs7syOFPDxOxJIJm/ZuZXHba7TTysvJw9HTE3rVkCZ9KrSLorSC2ztnKkc+P0HZiWyPFS0JUApmJmbg0dTG0SHkYJEkieF4wC9otID9HeaAhAtzaTa/XetH1ua6Ga4geSS1ZrCKraBp2amjIdAa9FWSkWNA4amjctTE3j93k5tGbtByqBOGGFkEBxY9/r45esLx4HW5R2a1NcxtynXO5tPWS8jue0dHk+CxxUi5MXk4ex+YpJnHTNk+j+YDmhs/uXrrLTz1/4sSiE3R5pgtNujUpNr+pc7JtO1tFIts+F01zjVGW9WHRy271wWzRzK0eWZbZ/p/thP8ajqSSkHUyoV+EEjgp0GTNtqnlas8qwblte9sS39PPZ+q7Aozes+trZ3b8lUHRMZlbf1WP6yHJk2W5ewmfqwAX4Clk+c+C9/YW1Ob+HUmaiyzfBl4sNM8hJGk7cBZ4D5hZ8cO2HJHBtSK6fB1xYWVv86NSq/Afo2QSvHt7m5SvVVf8gv149LdHAdj1zq4SnwKCcmJd98Q6fuj2AynXi/fuq0xkWebS1kss6rSIj6SPir3+6/pf9n6w12wDeFmWOb/hPAvbL2TbK9vITMrE9xFfnj36LBOXT2TKmil49/Ym5XoKS0cuJft+6U/3olZEKQGZhyPN+jcjLzuP4wuPl3nb9n+4n3l+87h/7X6Z560ItszZwoJ2C4x6Hz4MCWcTWDFmBXnZeXR9visDPxyIrbOt0ct/tD/jflGCph1/2UHUyigAsu9ns/OtnQAM+98wHNwccGnsQsthLcvU+qUkEqMT+bbFt6wYt4LEaOP6rbRbaez7YB8AwfOC0TiavrkMelvJKod+FYou33T9urWI+iOK7W9sB2Dcz+OYfXA2noGeJJ5NLNVUTk92SjanfjwFKNLEot9fVQW3enq83INGnRuRci2Fg/930JDJ1TvYm0LvplxS/bYl8uTCdH6qM44ejtw6fovdf9ttdJ65sucKAC2HtCy3KZB7K3f6/b2f4W8hUa79aBw0xX5n1gpu4cEx5+jpSKcnOhX73FQdrrka3MLLKxzgmnPMvbz0Mro8Ha2Gt8K5kWmzzoYdG6Jx1HDv0j2LrlmRyyNJv5NOw44N8RvlZ7SfG3dpTK83eoEMW1/eatK4yhSV4axs6TL3vr+X8F/D0ThqmLV7Fg4NHLh57KbZjLap5TpPccZ5inOp7+mDwKLfVfqqdNJXpRu9l3PkQZBZ2W7Tpo4fc+t36O1Q4d+VFdC7Ju4q8v5OoCFg2jRIlm8Ah4EelTYyC6k5kVEtJPFsIto0La7NXC3K3hWmx8s9cGnqQpdnu1TS6CqPjjM6MvTzoQBse2Wb2QARlIDuzJIz3D51m6UjlhrcHiubO+F3WDJsCctHLzfbTy8nNYdDnxxint88Tnx/wsg86+bxm/w+8Hf+GP8Hdy/exd3PncfXPc5TB56iac+CmiBHDdM2T6NBQAMSIhNYOX5lieZGOak5hoBs6OdDGfCvAYDitloWUyRthpaQL0K4F3PPpGNsZZN0PokTC06QGJ3Ise9KboVSEqlxqSwbuYzs+9m0Gd+G0QtGm73Z7zSrk+GYW/fEOq7svsLeD/aSkZCBbz9fo5sqfbByZmn5ZMqyLLP5xc3cj73PxU0XWdhhIZtf3Ex6fDoAO9/eiTZNi/9YfwLGFq/t1BMwLgC3Vm7cv3rfpFzVWlzZfYV1s9aBDEM/G0rnJzvj4O7AjO0zqOddj+uHr/Pn9D/NmsrpOfXTKbRpWpoPbG4ym1HVqGxUjFowCoCQ/4UQuUwpJTJVf6vHs60nnu08yUnN4dbJWyanKWuAq3HUMPCjgco4Pg9hXut5nFiknGdi98YC0Hxwc4uWVRr9/toP30d88R/jb3VHfkHdI3BSIM6NnRn62VCTgXbRVj3ZKdlkxGdg42BDPe96xaYvLFHW1/SbK8VIPqZkjvXnfVOoNWrDdTsu1HS7ID2yLBP6pWJYFfRWkMlr0oB/DsCliQs3j93k1M+nSlxeYSpDoluaW/LReQ8UOpNWTaLFoBb0eFmJXfTbaelyLX3P1Hdl284W20DbYt+fpJOKzV8ZLszmjh9T67dkv9YAzD3h1x/QJV3YJaDqeh2aQQS4VuRh5Ml6mnRvwptxb5o0RKgJBL0ZRJMeTUi7lcbBfx80OU3hgM6hgQNJ55NYMXZFia0zdHk6tBnaYi9Ln5KmxqWy/qn1fN/1e67uuYp9fXuGfzmc97Le45+6fxq9Zh+ejXdvbzLiM9jy4hYWdlxI5IpI/pzxJz/1/IlrB6/h0MCB4HnBvHz2ZdqMb1PsYufYwJGZO2YqLtMHrvHnzD/NZun2f7if9DvpePf2pvOTnWk+qDmNOjciIyGjTMHY+XXnyc1Q9mH4L+GlPjSo6J6sIV8+CKqPzy+5FYo5spKzWDpyKalxqfj28+Wx5Y+VqmTo83Yfev+lN7pcHSvHr+TEghNIaolRC0YZfS9txrdB46QhLjTOEJQURZblUo+pyGWRXD90HUdPR6VdiwQnvz/JvNbz2PTCJqJWRGHjYMPIb0eWuByVWmWoDQ75IqRKe+Sa4/ap2/wx4Q90uTp6/6U3fd7pY/jM1ceVGdtnYF/fnvPrz7NlzhazY87Pzefot0cBDCZH1QGfIB+6PNsFXa6O9DvpODRwwCeo5PO03vXVnIzR0AO3lPrbwvR4uQdPhzyNTx8fMhIy2PLSFhZ2WEjs/ligfPW3hbGxt2H2wdlM2zSt9IkFggrGq70Xb916iy6zTT+wNxhNhcWhy9c9kCf7NTBp6ubc2BmHBg5k3882+AGYcsxN1aayb8U+bJ1taTO+TYlj1GeRS5MpX95xmcSzibg0caH91PYmp7FzsWPE1yMA2PO3PYbSpdIoKpGVVXK5nX1Lcks+u+os218vUOj8NA7/0YqKpcecHqjt1Io51yXT7dFMLbek9+z62RneM/VdOY12wmmMk3LtLbieaJprUDdRF1tmZbgwm3NcNrX+0vZrDWFdwb8jirw/AohDlk23d5AkX6AvcLTyhmYZIsC1IoYAt2/1N4mqaFRqFaPmjwIJwr4OM2m/Xzige+H0C9TzqUdcaBxrHl9TLCukzdBy4OMDfOb+GZ86f1rstaDdglIlzrEHYvmuzXdE/B6BykZF77/05rXLrxH0ZhA29jZIkmT08u3ry9MhTzNp1STqt6hP0rkk/pz+J5HLI1Hbqenzbh9ei3mNnq/0RK0xfxKt36w+M7bPwM7VjnNrz7EseJnSsqMQCVEJHJ17FEklMWr+KCSVMgZ9UBD6VajFQbzeQEnjpCE3M5cTC0+YnTYzKZOFHRaydOTSCjE5Sr+TzpnFZ0BSbvSz7maV2ArFFLIss3ryahLPJuLZzpOpG6daJK+TJInhXwyn/bT2inmRTqbX671o2MFYkmnrZEvbxxR/BFMPDrJTsvltwG8s7LCQlBumj6nslGx2vl0gf/58GGMWjeGlyJfwH+uPNl3LqR+Up/aPvPcIbi1KD3g6P9VZkYUdvWlxHVhlcS/mHsuCl6FN19JhegeGfzG82IMbr3ZeTNs0DRt7G079cIoDHx8wuazo1dGk3kjFo42HUX/Z6sDQT4fi4K7UEPuN8ivVMbQ0I5rkmNJbBJlcbpAPsw/PZvKaybi1ciPpfBLadC3ufu7FnKAFgtqISxMXXJu5kpOaQ+LZRIPBlKn6W1DO9eaMpgqjP7+3ndjWbImIHnP9eIuiz2r2fK1nie22AicH0nJoS7LuZZk0QCxKWSSylmYLzcm2M6Mz2fv+Xv6c+SfIMOTTIXR+qrNhPueGzopZmazcv1myXFMS4/RV6aStSCMkNIR5j80jxTfFKDAtStqtNBZ1WsQvfX8hKznL7PgBiyTS5vZV+p10Nr2wiU9dPi3x/sTc+rPCsky+X8OC3K3APuB7JOlFJGk4kvQDitnUBwBI0pdI0tdI0hQkaRCS9CJwCCW7+x9rDVyPCHCtyMM4KNcmmvZoStfnuqLL07HtlW1GWZ6iAZ2rjyszd8zEwd2Bi5svsvnFzciyjC5fx+lfT/Od/3fs/9d+tGlabBxs0DhqDC+1rZqk80klSpzjz8QrNYMZufiP9WfOuTmM+GqE4QbXHJIk0W6y4vA6/KvhuPq60mF6B145/wrDPhuGfX3L+sE17NCQaRunYVfPjiu7rrCo0yI2PreRtNtpRsZS3V/qTuOuD0of2j3eDpemLiSdSyJme0yp60m7ncaV3VdQaVQ8+qtSC31s3jGzEufdf9tN4tlELu+4zOrJq8nPLZ+r9bH5x8jX5hMwLoAhnw4BIOyrsDLVlp5Zeoare67i6OnIzO0zLTYyAsUQaPxv4+k4qyPNBzZn4IcDTU5XWKZc+LjMy8njj/F/cP3QdRKjE1k6YilZ97KKzb//w/1kxGfgHeRtkD97tvVk2sZpPLH3CXz7+dJqeCuDyVppaBw1D2RhX5iXhVU26XfSWTpiKRkJGbQa3opHf33UbFsc336+TFwxEUklceDDA5z84aTR54WlfL3f7F1iex1r4OjhyJgfxlC/eX16zCm9nKjwDbCpjLXeQbmsAS4o55nAiYHMiZ7DiG9G4NHWw+JjRyCoDeizuDdCbhjqb80FuFBgNEVxoyk9siwbAtyS5Ml69AqOW8dvka81fR28E3GHK7uvoHHS0O35biUuT5Ikgr8LRqVRcfqn0wY/FnOUVSJrCUWXqfZWE6eJ49Cbhzj0f4fQ5eoIejuIvn/tW2xevaoo/LfwYhloSyTGWTZZ3Eq4RVRoFMfXHif7fjbLZi8ju322SQf/7JRs5eF/ZAJxoXGsHLcS7TWt2Q4AlsqhC5ObmcvBTw4yz28ep344hTZdy9739pr9vs19J3lX82p+VxDlIjYeWAl8BGwGegMzkOXfCqY6i9JO6HuUWt0PgSNAL2T5QhWPuBjCRdlKpN9JJ/lKMhonTbEMUl1iyH+GcG7NOa7uvcrZVWdp/3h744Du5QcBnWdbT6ZtnsbiIYs5/fNpZJ3M7ZO3DRewJt2bMOyLYUaOhaCYCf3a/1cSIhVDoif2PGH0tPZ+7H2WjlxKTmoOgZMCmbhyYpmNu2zsbAj6SxBBf3l4mWWz/s14NeZVDnx8gBMLT3D6p9NErYjCb5Sfwel30L8HGc2j1qjp9Xovdr+7m5AvQkrNgkWtiELWyQSMCyBwUiCNujTizuk7nFl6hq7PdjWa9kbIDU7/fBqVRoVdPTtitsWw6blNSlDzEMY22gwtJxYo2eI+b/fBu7c39VvU517MPS5suGDImpZE9v1sdr2teB4M+98wk/VXpaG2VTNh8YQSp2kxuAUuTVxIvpxMXGgcPn180OXrWDdrHbH7YxUJnJsDidGJrBi3glm7ZhmyyPFn4jk275hRtt1o2YNa0OJQ2aWlPeb04MjnRww9G8vjnvsw5KTmsCx4GclXkmnSowlT1k4pMUMBitx79MLRbH5hM1te2oKTl5NBCnjtwDVun7qtGMvMKm4sUx0InBhocT9kt1ZuBnf75MvJRoGsLMtlrsE1hdpWTe/Xe9P79d6lTywQ1CK8+3gTuTySG0dukJejPJA1ZTClx2A0ZSaDeyPkBvev3selqQvNBzYvdf0O7g54tPUg6VwSt0/fxrtX8f71+gd2XZ7pYtGDV48A5UHV4U8Ps3XOVp499qzZew+9s7KsU8pjVDYqQwCVsTbDyG3Y0iDXsMwCQ81d7+wi6ZySHfcO8mb4l8PNlmZ4BnriN8qPS1svcXzhcQZ8MKDYcgvjNFoxj8pJy+HIZ0cI/SqUvKw8VBpFLZcRn0Hk8kiWzFrC00eexp4Hy8jLzmPloyuJPxNPA/8G5Gbmcv3wdTZ/s5nJayYbrUcfyFriwqzfV7p8HWeWnGHve3tJu5UGKJ4LSReSuHvhLlF/RJm8RpXWgSDuaByNOjfCxs6mZnYFkeVUYE7By9TnvwC/VOWQyoLI4FqJG6FK9ta7l3elNcuuCTg2cGTIf5VM3s43d5KTlkPk8kiDU/DgTwYbTe8T5MOkPyYhqSTCfw1XWqz4uvLYssd49uizxYJbAPv69szYNgNXX1fiwowlzplJmSwduZT02+k0H9icCUsmWNWV2snTiVHzRvHy2ZcJeDSA3IxcoldHA4qRj6mLZrfnumHrbEvsvlhun75d4vL18uSOszoiSZIhCxTyRYiRxFmXp2PLy0p/1j7v9GHG1hloHDVE/B7Bnn/seahtC/81nKx7WXj39sanr49BBq5fvyXsfb/AGOoRX5NumxWFSq2i/XSlfipiSYTSJuGN7USvjsaunh0zts1g5o6Z1POux40jN1g7dS26PF3xhzNdTBsNPgzODZ2VTIMMoV9XbRY3LyePleNXcif8Du5+7kzfMh1bZ1uL5u32fDcGfDgAWSezdtpaQ69Yg5TvlZ5V7pRcGejLFqC4jDEzMRNtmhb7+valqkIEAkFxCiskDDW4JTzk00uUrx++brJDgf5a2GF6B4uv+SXJlFNvphK1IgpJJRm1oiuNR957BFdfV26fus2JRebLhUDpvPHbwN/4ptk3pN9JNyuRLasU9sDHB1gxZgVJ55Jwa+nG5NWTefrI06X6DuhLpCw1ukyNS2VRp0Uc+r9D5GXlETg50KCWe/S3R2k1ohWZiZksHbGU9Dvphm1eN2sd1w5cw7mxMzN3zjTyeNg6Z2sxxYylEmn9vtr8wmY2zN5A2q00GndrzJP7nmTqhqmGzHXI/8rmfXHv8j1WT1nNz71/5vj8sne5EFQMdTeysjI5KTk4eTkZjAvqMl2f6UrTnk1Ju5XGrnd3GTJ0Qz83HdAFjA1g/O/j8Qz0ZOhnQ3nlwit0mN6hRIljvab1jCTOm17YhDZDy/Ixy7l74S4NOzbk8fWPV5sbbY8AD6aun8pTB56ixeAWdJzZkc5PdjY5rX19e7o+p2RfS3I1TIhK4E74Hezd7PEbrWR6AycHUs+nHncv3OXilouGaY/NP0Z8hNKftf97/WnasymT10xGZaPiyH+PcHRu2fwDdPk6Qr8qcJZ8+4GzZJenu2DvZk9caFyptU23Tt7ixMICY6j5ox4qi1wW9E9sz/5xlgMfH+D4d8dR26qZumEqjTo1op63ckzZu9lzYeMFtry8hTNLz3D9sGIsNfjfg0tZQ9nRy8IifoswtKsw5RhZkU3ldfk61s1cR+w+JXM9a+csnDzL1s9vwD8H0O2FbuRl57Fi7Aqi10ZzcfNFbOxt6P5SSa34ahbmjGgKZ28r+7gVCGojDTs0xNbZluQryYaWayVKlDt44RnoSdqtNMWcslDLsrycPM6uUkxiLZEn6ynq5lyYY/OOocvT0XZiW4t8FfTYOtky4hvFx2fve8oDXHOcWHiC64euK/dK7+wyK5E1KfE1c51IWpfEoU8OgQTDvxzOnHNzzPa3LYqR0eWyko0uM+8qgev9q/dp2KkhTx95msmrJuPeSlG0qDVqpqyZQpPuTbh/9T7LRi0jJzWH7a9vJ3pNNHaudszcPpP6zeobeTyc/P5kMY+Hsrgwp0WmEf5rOCqNiglLJvDcsecMGf0O0zvg3NiZhMgEruy6Uur+yLqXxY43dzC/7XyiV0djY29T7rIuwcMjAlwr0fmpzrx15y36v9/f2kOxOnopJxKcXHRSMZYK8jYb0AF0nNmRl8++TN93+1oclHq08WD6lunYONgQ/ks4CwIXcPPoTVybuTJj2wzsXS2rl61KmvVvxhN7nmDCkgklBvC9Xu+FpJaIWhll1vgoYkkEAO2mtMPGTtlnao3akEXV13am3Tbdn9Uv2I9xPyv9ZLe/sZ2oP6Is3o7z685z/+p93Fq5GblV2jrZGmpLQ/5nPosr62RDz0BTxlCVQcOODWnYsSHZydkc+PAASDBh6QQjOZtnoOcDM6UfT7Hp2U2AYixlaf11WfBs64n/GH/ysvMM5mCmHCPL6qRpDlmWH9xg1Cu4wWhev8zLkSTlN95mfBuy72ezetJqADo92anMwXJ1xlyG52EclAUCwQNUNiqa9lJa9ejydDg1dCrxmq3WqJmxbQYuTV24fvi6kXLr0pZLZCdn07BTwzJdS/S/7+tHrpN8JdnwSjqfZMi+PowbfJvxbWgd3JqclBx2vVu07ahC+p109r63FwBJLXFm6RnuaO+YdPY1JZ01d50IWxyGLk9Ht+e7EfRmUKllJ4UxMrr80rzRpTZDy4oxSi94z3aePLn3SZPeM7bOtkzfMh331u7cOX2HhR0Wcnz+gwfLhXt0F/V4ODr3qOH7yGqURbounZTrKYbMq96Fuei+CtsRhqyT6TijIx1ndjS6z7Kxs6HXa72AklVmeTl5hH4dytzWcwn7WtmfnZ7sxKuXXqXfX/uZnU9QuYgA14pIkmQINOo6Tbo3MZgymKtdrAi8e3szedVkJLVEyvUUHBo4GNr01GTqN6tPu8ntkPNldr+7u9iFRpevM/Tz7DjT+Il112e7Yudqx7WD17h57CY73zLfn7XTE50Y+tmTdGQTAAAgAElEQVRQkOHPGX+yZc4Wg5TIHLIsG4LXoDeDisnBer6iuE3qa0tNceqnU9w8dhOXJi5mjaEqgw4zOxj+Hzw32GRbLt++vgbZfL42H58+PpUqnw56W7mhOPbdMXKzcg1Poiujqfyh/zuk3GDYqZm60fgGo6yo1CoeW/6YoZ0OEoaHK7WFJt2aoNKoSIhKIDvlQQa9IupvBYK6TuGOEyXV3+px9XVl1s5ZinJr00U2PrtRMZdaYrm5VGEa+DfAwd2B9NvpzG011/Ca33Y+OSk5+PbzNVmbWxqSJBE8Nxi1nZqI3yMMZRyF2fXOLnJSc/Ab7ceAfyr1rlvnbDVrgFQUU9eJeNd4Tq4/iaOHI0P+M6TM4wZjo8s1j68p1jYoX5vPqomriAuLw7XZA7NQczh5OTFzx0ycGjopnS8keGzZYybLz/QeDwDbX99u9J3MbTWXb5p9U2JJVebdTE7/chow/2Ci2wvd0DhpuLLrCnciinfG0WZoWTx4MTvf3El2cjYtBrfg+ZPPM/638Q/lESKoOESAK6g2DPnPEFoNb8WQT4dUaO1iUfzH+PPYssdo1r8ZM7bOsOhCWRN45P1H0DhqiFoZxc53dhrVjMTujyXtZhr1W9Qv1pbKzsVO6dMKbHh6Q6n9Wfu804dH3nsEZDix4ARzW81l7wd7yUnNMTn9jSM3uHnsJg4NHIxaDehxbuRMxyfM15ZmJGaw+29KG4URX4/AzsXOsh1SAXR5ugvNBzZn6OdD6flKT7PTBYwLYMLSCbQc2pJxP4+rVEfgZv2b0bhbYzITMx+0fKqEpvInfzypZPIlmLh8oskbjLKicdAwdeNU/Eb70e/v/WrNb0+Pjb0NTbo1ARluHr1peF8EuAJB+Smc9XP3t+y35BnoyfQt0w0eElte2sLFLReRVBIdpncofQGFkFQS/f7eD7eWbtRvUd/o5RnoaegM8DC4t3Y31HxunbPVqBVi7P5Yziw9g429DcFzg+n7bl/cW7uTGJ1I2DfF2/SYo/B1Qt1ezab3FcXR0M+HPrQ3gFqjZsRXI1DbqYleE82CwAVsfmmz0gFCJ7P+qfVc3nEZRw9HZu2cRb2mpQd9bi3dmLl9Js0HNmf8b+MJnGTe6K/b890YOXck7n7uxb4TJEUZFh9p2mjsxMIT5GXl0Tq4NV7tvUxO4+DmYDDgLNrBID83n9WTV3Mj5Ab1vOsxfct0Zu2eVan3rwLLkcpSOF2TcXJykjMyzNc2CAS1gZgdMawYuwJdro4h/x1ikMdsmL2B8N/C6f9BfwZ9PKjYfKk3U/m2xbfocpWL6qBPBtH/vZLl8wlnE9j73l4ubFDc4B0aONDvb/3wbOdpNF3ol6Fc3XOV/v/sz6CPiq8bIPFcIgsCF2Bjb8PElRONZFLhv4YTvTqalsNaMnPHTFHDCEStjGLttLU08G/AnHNzyLueR8baDOy62ZFzMqfcGdzz68+zauIqZJ3M6IWj6f5i7amTrWx2vLWDsK/CGPCvAQa1wY89f+TW8VvMPjT7QQZbIBCUieyUbD5z+wxkxUW/LK2yYnbEsGLMCkPg2Gp4K2bumFlZQ30ocrNyWdBuAfev3mfE1yPo/UZv8rX5LOq8iKRzSQz8eKDBrThmRwzLRi5D46hhzvk5FvXE1suS7brZkXYgjU2/b0JqLDH70OxyP5RNuZHC/g/3E/FbBLJORuOooWnPpsTuj8XW2ZYn9z+pPPyrQra+spXj84/j28+Xpw4+ZXTvkJedxzfNviEjIYMn9jxBi8HmOxvcj73P3NZzkSSJ1668hquPK7JOZt2sdUQuj8TRw5Gnjzxd5Z0NyoMkSZmyLNee+iATiAyuQFCLaD2itdICR4I9f9vDqZ9PkZuZS/QaxYnZnCSrXtN6hqfZDfwbWHTj4NXOi6nrpzL7sHLTnnU3i13v7GL5qOVGr6t7rqK2U9NzjvkMaOHa0j/G/2E0f/TqaNS2akZ9V/nGUjWFwEmBuPq6cvfiXa6uvFqhTeWvHbzGmqlrkHUyAz4cIILbMmKowz3yoA5XZHAFgvJj72pvyLR5tCmb+qP1iNaMXzweCi4hZZUnVwUaBw3Bc4MB2PfPfaTdTiPsmzCSziUpGd53HvSjbT2iNYGTAsnNzGXHGztKXXZhZ+H7rvfZtHgTwVOCGfPxmApRHLn6uPLoz4/yUuRLSgeIzFxi98ca6merOrgFGPzJYJy8nLh++DoRiyOMPotYEkFGQgaNujSi+aDmJS6nfnOlBEyXp+Po3KOKN8VfthO5PBJbZ1tmbJ9Ro4LbuoIoABUIahntp7Yn824m217ZxubnN3P94HW06Vqa9mpKAz/zJ+HB/zcYZKUusiy14b59laejl7Zc4vQvp8nLKt4uoN3j7XDyKvlh4bD/DUOlURWfX4L209qLC0gh9C2WdvxlB7e238LnYx+zze7LQnxkPCvGrSA/J59uL3Yz1HoJLMfgtBoWhy5fR05KDtnJ2WicNDg1rNUPzAWCSmfkNyO5uPkirUa0KvO8HaYpD3GvH75O4GTL+ltXNf5j/AkYF8CFjRfYMHsD1w8p9bij5o8qZqg54usRXNp2iXN/nuPStkv4BfuZXa7eWdjG14YtU7dw88pNYvNj6erQtULH7xnoydT1U7kRcoOT35+k/fT2JWZHKxP7+vYM+2IY659Yz653dhEwLgAHNwdknWzoONHnnT4WPTgPeiuIqJVRnPz+JCq1imNzj1k1eBeUjpAoCwS1lP0f7ufARw/s84O/Cy4xiyqoWeSk5fC1z9fkpOTw7NFnadqzabmWl3Qhid8H/U767XTaPtaWSasmWbUndE3m25bfcv/qfV4If4F8bT4/9fyJhp0a8mL4i9YemkAgqOYkX01mQeACQ2/ZwMmBTF412eS0IV+EsOudXbi1crOoBvj2qdsc+e8RnBs788r5V7CrV3WeFtZAlmV+H/g71w5eo/tL3Rm9YDQXNl1g5biVuPq68mrMq6g1ljlH/z7od2L3xyp/SDB51eQS64OrM3VBoiwyuAJBLWXAvwaQmZTJ8fnHUdmoaP94e2sPSVCB6M3BQj4PIfTLUCb9ManMy9Cma4leE03E4ghi98UC0GxAMx5b9pgIbsuBTx8f7l+9z42QG4Z2Ufp+jwKBQFASbi3ceOS9R9j3wT40ThpGfDXC7LS9Xu9F+G/hJJ5NZM2UNRavY8RXI2p9cAsFLeoWjOL7zt9zYtEJOs/ubOjq0OuNXhYHt6Bke/UB7phFY2pscFtXEAGuQFBL0bcecG7sTD3vejh6OFp7SIIKptdrvQj7KozoNdEkX03GrUXpfVZ1+Tpi98cS8XsE59aeIzdTqdW1sbchcHIgwfOCLe4tLTCNTx8fIpdFEhcSZ3B7dWsteuAKBALL6PNOH7QZWnz7+ZbYbkatUTNx+USOfHbE4pZBXh29aPd48ZZ3tRWvdl70/ktvQv4XwurJq0m5loKdq53BHdlSWge3ZtC/B1HPu57JjhCC6oWQKAsEAkENZv2T64lYHEHP13oS/G2w2emSLiQR8XsEZ5acITUu1fC+bz9fOj3ZicDJgdi72lfFkGs9d8Lv8H2X73Fr6YZvP18iFkcw5ocxdHuum7WHJhAIBHUObbqW+W3nG659ff/al6H/HWrlUVkPIVEWCAQCQbUm6K0gIhZHcPrn0wz8cCAObg/6GWbdyyJqZRQRiyOM+rLWb1GfTk90ouOsjkI6Wwl4tffC1tmW5CvJBtdW4aAsEAgE1sHW2ZaR345k1cRVqDQqer4q/EhqOyLAFQgEghpMw44NaTmsJVd2XeHk9ycJeiuImO0xRPwewcVNFw2yNVsXWwInB9L5yc749vOtkNYQAtOobFQ07dWUq3uuknw5GRABrkAgEFiTNhPaEPxdMM4NnanX1LzsW1A7EBJlgUAgqOFc3nmZpSOWYl/fHpVGRWZipvKBBK2GtaLTk51oM74NGseytQ0SPDz7/rmPg/8+CIDaTs17me+JhwoCgUAgsDpCoiwQCASCak/LYS3x6uBFQmQCAB5tPej0ZCc6zuwonlRbCX0/XAC3lm4iuBUIBAKBoIoQAa5AIBDUcCRJYtLKSUSvicZvlB+NuzW2qHm9oPLw7u2t1N/KdVieHBoK+/fDwIEQFGTt0QgEAoGgjiACXIFAIKgFeAZ6MuCfA6w9DEEB9vXt8WrnRUJUQt0McENDYcgQ0GrB1hb27BFBrkAgEAiqBJW1ByAQCAQCQW2kxZAWADTq0sjKI7EC+/crwW1+vvLv/v3WHpFAIBAI6gg1JsCVJMlHkqQ1kiSlSJKUKknSn5Ik+Vp7XAKBQCAQmGLwJ4N5fN3jdJjewdpDqXoGDlQyt2q18u/AgdYekUAgEAjqCDXCRVmSJEcgAsgB3gdk4BPAEegoy3Kp9sjCRVkgEAgEgipE1OAKBAJBtaMuuCjXlAD3deArIECW5ZiC91oAl4B3ZVn+qrRliABXIBAIBAKBQCAQ1GXqQoBbUyTK44AwfXALIMvyVeAI8KjVRiUQCAQCgUAgEAgEgmpDTQlw2wFRJt4/CwRW8VgEAoFAIBAIBAKBQFANqSltgtyBZBPv3wPczM0kSdLzwPMAtra2lTMygUAgEAgEAoFAIBBUC2pKBhcUY6miSCXOIMs/yLLcXZbl7jY2NSWWFwgEAoFAIBAIBALBw1BTAtxklCxuUdwwndkVCAQCgUAgEAgEAkEdo6YEuGdR6nCLEghEV/FYBAKBQCAQCAQCgUBQDakpAe5GoLckSS31b0iS1BzoW/CZQCAQCAQCgUAgEAjqODWlD64TEAFkAe+j1OP+G3ABOsqynF7aMkQfXIFAIBAIBAKBQFCXEX1wqwmyLGcAg4GLwBJgGXAVGGxJcCsQCAQCgUAgEAgEgtpPjcjgVgQigysQCAQCgUAgEAjqMiKDKxAIBAKBQCAQCAQCQQ1BBLgCgUAgEAgEAoFAIKgViABXIBAIBAKBQCAQCAS1AhHgCgQCgUAgEAgEAoGgViACXIFAIBAIBAKBQCAQ1ApEgCsQCAQCgUAgEAgEglpBnWkTJEmSDsiy9jhMYAPkWXsQdRSx762L2P/WRex/6yL2v3UR+996iH1vXcT+ty7VYf87yLJcq5OcdSbAra5IknRCluXu1h5HXUTse+si9r91Efvfuoj9b13E/rceYt9bF7H/rYvY/1VDrY7eBQKBQCAQCAQCgUBQdxABrkAgEAgEAoFAIBAIagUiwLU+P1h7AHUYse+ti9j/1kXsf+si9r91Efvfeoh9b13E/rcuYv9XAaIGVyAQCAQCgUAgEAgEtQKRwRUIBAKBQCAQCAQCQa1ABLgCgUAgEAgEAoFAIKgViABXIBAIBAKBQCAQCAS1AhHgCgSCGoskSQ6SJE2QJMnZ2mMRCAR1B0mSnCVJmmTtcQgE1kKSJBFDCKotNtYegODhkSTJAZgAuAEpwHogQxbOYVWCJEn2wESgLXAP+EWW5fvWHVXdQZIkF2APYAfkAZusO6K6RcHxHwzUB1KBzYBWnH8qH0mS7ID+QCsgDVgu9nvVIUlSPSACOClJ0mZZlrOtPaa6hiRJEmBf8Ge2LMuyJEmS+B1UPpIkaWRZzpVlWSdJklqW5Xxrj6kuIUmSI/AU0BDl3n8zcEWW5Txrjqu6IVyUaygFN/ehgAZwRbnJPA/8CPwky3KOFYdX6ynY/7sAF8AT5SHDNmCCONlXPgUn+DDgNvAvIFzcZFYdBcf/AZTj3wtwBE4BPwG/y7KsteLwajUF+34ryjmnJcpN/kbgeVmWE6w5trpAQXAbDlwFZsmyfEsEVlWLJElOwGdABxQl4hbgG3ENqHwK9v0RIEyW5RcL3hNBbhVRcP4/Ckgox35jIBFYC3woy3KmFYdXrRDyghqIJEk2wCqUg3o00B3oCWiBvwP/K8juCiqBghP8YSAD5SlaD2AqMBIYb72R1SmeRMlcvQ4ck2U5W5IkV0mSPCRJsi14ui+oBCRJskV5mJOGctz3ACahPE3+FvikILsrqGAKHuzsA7KBF1H2/WxgOPAPKw6tTlBwc3kKuAI8gfKADRHcVh0F5ShhQC8gBrAF3kb5PgSVSMF5fQ3QEXhckqSvAGRZzpckSW3VwdUBCvbxb0ACMALoBgSgPHCbAfxRcH8qQEiUayr1gKbAfFmWYwrei5MkaQiwAEU2q5Ik6S2Rya1YCh4ufIciC3lJlv+/vTsPk7Oq0z7+vZMoYQkg4BAQZVNEmGERUGRHFgFhGGSMwrCruCGbLwPqBAOI4sruhijwCsKIryLKoAiyDaICIiIIDAOyrwIhQIQkv/eP36nkoel0eqmuU125P9dVV6Wfquo+ffdJ1TnPc5a4sxwfD9wPPCZpyYiYXrGYC4N1yEb+PWWY1LuBI4A3AY8AV0j6rM9mjop1gMnAwRFxYzl2p6SHgf8HfBQYL+lTvpLbPmW+21TyxNohEXFbOX4vsBmws6TPAX+LiDnVCtqjynv/xcAbgK0j4sFyfDNyqtD6wB3lOZdFxEu1ytqryt/gPLKBv39E3FeO30IO2f9247m+qt5G5aTxB4H1gC+TJzT3Lzkf1urk+kruqBoPvB64KCLuK9nPkLQ3cBT597lA0hS3fXwFd6xahJx7NfcqiaQJEfEs2bi8nLyS+DEvAtB2K5BDQ84G/qeR74vl+FeBuyX9l6RdfVazvRp5LwM8HhF/L53bi8mrKWeQ86EPAH5UrnhZey0BrAr0bcDfSF7dWpS8ojulw+XqdcuSV2pvIaejABARzwFXA6sAi7pzO2qWJodmziZPpiHpPcClwDbkMP3dge8Bh5XOmLXX64A3Av9ZGvit9/cryM/jTSVtIGlimZPrz9/2mUhOR/lTRBxJXjX/CbCfpBPBV3I7YCKwMvleQ6njE0pn9vNk+2d94POSXlWvmN3BnZ8xppxFe4r8oN1V0ioAETGrnD2bARwE3At8iGwUWZtExP3A18hFXeaUq4cTgV+SV1YuB6YBa5fnbVSrrD2qdUb+SmAbSTsA7yOz3i8ippHD9k8nh7B9skIZe910snO7raSlYO7VktnAX4FTgRnk2WRrk4h4nKznp5b3neYw/AfIz/OFvlEzWiLiCeAksiH5MUmXku8zXwV2iYiNyTmh9wKHAptWKmovWwxYg3kN/OfLdKzdgQPJdQF+CVwtaVLpcHm6ShtExAvA98mTl63/D9OAH/PKTq4zbzNJ48rIwJ8Du0l6K7ys7T+TnJd+FXmB65/qlbY7uIM7xkSaSc7B3YqcB7F4eWx2OZsznZyXtSrw3mqF7VERcUtEvNC4mvjv5NCRf4mIT0XE6eRwqWXwnNy2agw5+wPZydqHPInwl3I1d0IZFnsseZVrizol7V0RcRM5FPAT5BC1FcqZ5HXJESS/Jt9/NpC0XsWi9gQVABFxbkTc2c/wy4fL/Wsbr5soaQ03NkemmV85yfBN4BjyBNrFwFfKiU8i4lGys7UosFPnS9vzHicXdzxU0jRJU8hRI/czr81zPLn42vlltV8PU26TiLgzIqZLGlfeg/5K/l9odXJPKs8LSStL2tIjGdqjMTLnYvIq7gclva481mr7Pw8cTI6yWujbnq54XU65HcTbyWHJT0XEDQAR8R1JG5BvLk9KOi8inm8sE/4IcB85Xt+GaX75N0XEsZJO6bNF0IPk32D5zpS0Nw1Q/6+XdCrZmIF572WteUCzJN0KrFsaOZ4PNwwD1P+pwOLkFcUPSnoU2Bz4QUT8VNLK5JD9SRWK3RNa89lKY3Ec80YvLHBRo7IQz2nksNp/I0eX2BD0zb/VwIyIxyV9B3gIuLNMDWrO+XwCeJKczmIj1DyZExFPSDqZHB1yEHAdeSJ5D+DW0v75mqQ1gZ3J9s//1in52FY6piuQJ82eiYi7y3G1/i+0OrmSjikv21dSAF8iFxxcBtiVHHVoQ1BGBm5HrrnzOHBlRLwYET+W9CVy94i/Sfp6RDzUuJL7hKQ7cNvfHdxuplyx8QqykfI6cuGWHwBnRcSV5PDLpcmGzFKS/rN1Jpkcq/8c+R/DCy4MwwD5nxkR15RhghMiYla8cv/btwDPk0Npnf8wLKj+R8QXyjyTaeTKvfdHxM/JTu5ryHnqfwE8J3EY5pP/+cAZEXEt8AFJ1wGbkFvWHBERJ5eXr0UOm32w8yUf+8qonPMlXRQR3ynvNXM7WX2eO478LJ9D1v1Xk8Nm3w9sVubo2hAsKP+IeFjSBWVKEH3+NmuQo0tuLI/5vX8Y+jvBU1wq6SpyOP6ewMoRcXN5zYTSyb2f/PydUe0XGMPKCbJzySviawOPSDo6Is5s1uXyt2l1co8mT8LtTa6/8Bry/ced2yEqn73XkFdilyVPFF8h6ZyI+H5EHKOcHvRpsu1/RhlZOFvS0uTo3PvL91po33/cwe1SpZFyKbla70FkhV0HOAHYSNIXI+IcSR8i38S/DGwl6QLgaXKY1BvIRQC8jcEQLSD/DSV9OSLOLmfNBIyLsnqgpH8gt6+ZSM7Jdf5DNIj8vxoR3ytXz2eW42dK+ib5/+Ft5PZZnwiv6jhkg8j/KyX/M8nc536ISlqWHDr+DD5zP2TlzP0l5BXx1STNLI2afju55fiz5ctVyatbewPviIg/dLTwPWCw+Tc6t61OFZJWAA4nhyj7s3eY5neCgTKKIXI+6AuSZgNLS1qnNPBnSVqOnLZyGx65MGQl++vIkQgnkplPAc6Q9HBEXNJ8fuPq+gOSziKv2E4E3hYRt3ay7L2gnLS/iMx/L+Dv5Mn6rwPHSFo9Io6JiMMlzQCOBN4h6Txygc13AmuSWyku3O8/EeFbF97IKyB/AXboc3xN4HbgLnJRndbxj5F7w71EbkD/R2Dd2r/HWL0NIv87yW0K+r7u3eQ+ZU8C69T+PcbqbZD5f6BxfDfgfPLkzt3kPNB/qv17jNXbUPNvPL4V8APyg9b5Dz33ceRZ+b+SCxjdWLLep/mcfl63fMn8NvLK1Vtr/y5j8Tbc/MvxfwUuKO/969X+XcbqjewcXUWOSPgzsNf8sif3An0J+BG5D/1O5fP3EWCt2r/LWLuRF72+B/wKWLVxfCNyyttJ/f0dyrHVyPmhTwP/WPt3Gas3clj47cCefY6vQi4w9QBwTOP4+8i9iWeQ+0Jf57Zn3rzIVPdqrRbYuiqoMmTnL8Au5Jv6kZK2A4iIrwM7kg3QrYGtIuKPVUreGxaU/yzgCOXew5Tn7AB8gxyevGVE3NL5YveMweT/SUnbA0TEj8nhaquR+/TtHBF/qlLy3jDY/Jv1f3nyqvkyZP13/kO3DHml/M8R8XFy0a5ngf+QtA/MvWI797O7jCCZRA4lfz155eSmjpe8Nww5f5i7F+6x5FD+LaIMmbWhKbkeTjbmv0HudX70/LKPiF+QU7W2I6+6f4tcPXa7KPtE25C02o8Xk6uBAxARvyc7TlvMb6oEsCKZ/TbhK7cjsQTwZl752Xsv8GHgZmAfSQcARMQF5HSUVcmRa+9y2zOpnAGwLqNcpOUq8szk0VHmUbXmpUhaA/gNcHlETCmPLbRj7dttCPn/KiLe13jdJsA9EfFwf9/XBmc4+Q/wwWtDNIL6/w/Ai/HKOek2SJK2BW6MMndN0pbknNolgc9FxDnzed2BwPVu3IzMCPJ/K/BARDzWscL2mDK8+DRgyYjYSdLbyI7uJBrZtzq5MW+xo43IkwuPAXdFrnZtQ1Tmfk4DvhwRj5Rj48qJhRPIxbxW6a+dqdyuaRG/949M+Rv8ipxD+/HIldmbn72rkNOHHiNP5E9vPVarzN3KHdwuJul0ci7VrhHx68bxVkXfk9yX7J2Ri05ZGzn/upx/Xc6/s/qeoOwzt7PZyTo+Is4uxycDkyLirhpl7iXOvzsM5QSDT+q3n6TFIvcXbnVsFREh6QPkHtBvAp4rnwHeoWAUSJoKHE3u7Xxu5NaHzc/ezckT0FMi4sKKRe1qHqLchRpDcD4D3AKcJWmdxlNaV6luIBdyWeiXA28n51+X86/L+dfRt6Ee8xawIyKuIodiPgt8WtLe5Wr5t4FPlasnNgLOv65G1r+KiKdU9k9tZD+dHCq+b+Nly0tavfOl7V2Re6nOvTre+H8R5NSVWaWTtQS58NThdUraexr/B46j7LEN7KhceArmffbeTu5Q4Lo/AHdwu1DjjeVp4N/JSfsXS9pC0sTGG84ccqW15+uUtDc5/7qcf13Ov3s0O12loX8o2cmaClxGLqxzauSqstZmzr9zRnCC4TM+wdARKrc5khYj97rdB7i6aql6SLlSrvLlwcBNwHeBPSQt1/g/sgh5wufJCsUcMzxEucuVqymbkNsAvQU4iTyzM4dcOXkHcjuIB6oVsoc5/7qcf13Ovzs0h2JKej9wHnniYcvwYl6jzvl3hzI080RyuPIL5HvS28PbYY06Se8h98ZdBziKnI+7SXhBtVEj6Q3AqeQCsueRU4JmA/8G7AxsHLn4lPXDHdwusaAFcpQrlB4P/DOwHLkV0DhgN7/BjJzzr8v51+X86xnK4mhlOOaXyL0ON4uIP49q4RYCzr/7+QTD6Bls/Ze0E7kN1hXA9mTn1icWOkDS8cC/kCd07iNXF3+/P3sH5g5uBWV4x+7AyuSenTcMdpEKSf9ILsf+PPA/UVa6s8Fz/nU5/7qcfz0jzH48eeb+FHJhL28FNETOv/v4BEPnjLD+70auqv8M3oZyWMpc2tdGxEODfH7zxM5kcqXwF4DHIuKJ0Stpb3AHt8OUS4BfT179WIac07AIcATww9bKgf28zlugtIHzr8v51+X86xlu9n2+x6rAzPA2ZEPm/OvzCYZ6Rlr/JS0LfI3cQsj73A5RWZTrYuAO4PMRcd8gX+fP3mHyIlMdVN6gvwc8CrwnIpYH3gP8kNzrbaqkflckdQUfOedfl/Ovy/nXM5LsmyLiHneuhs7511c6WL8HPg18AjgZuEHSgZJes6DXR+7zeQ3wFnduh6Yd9T8innMAoXYAAA/MSURBVAQOdOd26CQtQg7v3pLceu9gSSsN5rX+7B2+CbULsJCZBLwZODsibgeIiGsl3UiezTyeHJVwvIcfjArnX5fzr8v51+Ps63L+FfXpYH08Im6XtBmwH9nBWlPSiRFx/0DfJyLuGfXC9qa21P+I+HtHSttDyqrIBwBrA4eQ+wgfXh460Qs0jh53cDvr1cCi5TZ3I/nILQa+ICnIN5q7gdM8NKHtnH9dzr8u51+Ps6/L+dflEwx1uf5XEhFRVkP+G3BGRMwseR8G4E7u6PEc3A6T9AtgBWD9yM2yJ0TErPLYq8ltOPYF3uYFFNrP+dfl/Oty/vU4+7qcfz3KPWuvIzu4xzWzL48fRXawDokId7BGget/XZImRcSzja9PJK/ongi4kzsKPAe3Q5T7SQIcC6xCDtdpbWY+ofz7RXJT56eAbSsUs2c5/7qcf13Ovx5nX5fzry8iHiOvDr5X0vhm9sXXgG8BX5S0tju37eP6X1cr/4h4VtK4xteHkfPQDwMOl7Rief5qkt5ercA9xB3cUaI0N9/GG/afyEq9u6RTymOzlMuHExE3kFtwrNnhIvcU51+X86/L+dfj7Oty/t3FHazOcv2va4D8iYg5ETGnTyf3FOBQ4JOSNgVOBS6RtGSHi95z3MEdBcrlwM8BNpek5mMRMR34Znl8f0lnleMvlddOJsfq393JMvcS51+X86/L+dfj7Oty/vW5g1WP639dA+Xf1KeTeyj5/+IQclXrTYDty9/LRsCLTLWZpInAfwGbAusAHwF+03hcEfGgpOPJDbM/IWkt4EzyzX1rcpW1izpd9l7g/Oty/nU5/3qcfV3Ov77SwP8G8B1JV0djkZeImC7pm8ByZAdryYjYzx2s9nD9r2tB+ffVZxj+ccAUYCKweXgrprbwIlNtVM7IfJbc5+pCYEdy1bq9I6LvG01IWhp4W3nNqsBs4H7goxHxx06Xf6xz/nU5/7qcfz3Ovi7nX19p4F9GNvD/BHxkPtmvBBxE7oX7Z17ewdoV2Dgi7up0+ccy1/+6Bpv/fF67MrnQ1I7ARu7cto87uG1Uzl5eBCwGbAesDJxPnpXZp783msbXbwJmAs9GxNMdLXiPcP51Of+6nH89zr4u51+XO1h1uf7XNZT8+3nt9uQK4gdGxB86UNyFhju4bSZpTeDRiHhKuYDCuuSiCouygIpuI+f863L+dTn/epx9Xc6/Hnew6nP9r2sk+UtaNiKe7FBRFxru4I4SvXyPsQ2YV9H3jYjryvEVgeci4pl6Je1Nzr8u51+X86/H2dfl/OtwB6s7uP7X5fy7hzu4HdKnou8NPAF8tXy9IzAn/McYNc6/Ludfl/Ovx9nX5fw7yw387uL6X9eC8o+I2RWL19Pcwe2QMkdlXeBschjPo+RKa1t43P3oc/51Of+6nH89zr4u51+XO1h1uf7X5fzrcQe3A5pzTiT9M/ATckPzrSPilqqFWwg4/7qcf13Ovx5nX5fzr88N/Hpc/+ty/nWNW/BTbCDSyzdzljS+3E+StBRAo4KvCuwHzCD3unIFHyHnX5fzr8v51+Ps63L+3a808OeUjux/AKsBawKbunM7Mq7/dTn/7ucO7hBIerWkTSTtWIbdEBHRquiSxkfEbElrAP8NbNDnW+wJ7EKeubyto4XvAc6/Ludfl/Ovx9nX5fy7jxv4neP6X5fzH6MiwrdB3IBJwK+BO4E55DySAxuPjyv3qwOPk0MRlujzPRYDVqv9u4zFm/N3/gvzzfk7+4X15vzr34BXA5uQc2Y3aBxvTXMbX+7XAG4B3tnn9Z8BXgLWq/27jLWb67/z9214N8/BHQRJi5FnZf4GfIV8s98bWJ8cS39fed5k8j/Bz4CPRMT0xvcYH14tbVicf13Ovy7nX4+zr8v51ydpEvBT4HXAG8m/xacj4tvl8XERMUfS6sD15N9rr4iY0fgeiwGTI+J/O/4LjGGu/3U5/7FtQu0CjBFHAAF8qPUGLWlxYFvghdaTIuIRSZ8Cvt+s4OUxV/Dhc/51Of+6nH89zr4u519RaeBfTTbwD2FeA/9ISZdGxH2lczsZ+APzGvjNzu34iHgecOd26Fz/63L+Y5g7uIOzJvAMcI+kV0XES8BdwB3A0ZKWBG6KiJMj4vSaBe1Rzr8u51+X86/H2dfl/OtyA78u1/+6nP8Y5kWmBmcmWdEXi4iXypCdc4AVyDknKwAnSvpG6wV9F2CwEXH+dTn/upx/Pc6+Ludf18sa+OVYs4F/tqRDACLi9Ih4plI5e5Xrf13OfwxzB3cArVUByf3bXgQelnQJcCswHdg+It4F/CtwFPBhSbvDvNUDbficf13Ovy7nX4+zr8v5dw038Ctw/a/L+fcGd3D7aL45N4bWXAdMAb4OXEiuBvh18kwmZUjOz8gPgzd3sry9xvnX5fzrcv71OPu6nH/3cAO/81z/63L+vcdzcBskLQF8UdLrgSWB84GrIuJ24LfAbyWtBJwI/Cly36sJETELWBx4kFLxbeicf13Ovy7nX4+zr8v51ydJrc5pPw383chVYtegTwNf0s+AabiBP2yu/3U5/97kK7hFWTjhJmBDcs7JS8DxwAWStmk89RngMeAzytUBZ0laHvhoec1/d7bkvcH51+X863L+9Tj7upx/faWBf5qkn0q6UtJHJL0lIl6MiN9GxFHAL4HX0mjgl5e7gT8Crv91Of/e5Su480wFngV2jYhHACTtTVbeSyTtFhGXkBX5YnKp/Gsl3QasDKwF7BARD1Up/djn/Oty/nU5/3qcfV3Ov6JGA/8p8irtomQD/0FJh0XE5eWpzQb+FDfw28b1vy7n36N8BXee1wMPRS53Px4gIv4vcCRwDfATSe+KiJnkcJzTyRMEGwL3k5s+31Kl5L3B+dfl/Oty/vU4+7qcf13NBv7eEbEdcCgwg2zg71Se12rgb0E28M8EzgV2AN7vBv6wuf7X5fx7lLweQJJ0PrBWRKxTvm6Nr0fSZsAJwHLAlIi4RdI4ctNzAS+1nmvD4/zrcv51Of96nH1dzr8uSecCS0bELmXo5exyfHPgs2SHdpeI+IVy38/DgXeTf4ObgBMi4o5KxR/zXP/rcv69a6G/givNXTntQmBFSf8HoAy/mVD+fS1wGrAUsGPrtRExMyJecAUfPudfl/Ovy/nX4+zrcv5dYzw51JJozK2NiGvIK1a/A06WtE7kqrHHApsDGwMfcud2eFz/63L+vW+h7+DGvEvY15BL4B8gadfyWLOinw9cC+xRvp5Tobg9x/nX5fzrcv71OPu6nH9dbuDX5fpfl/PvfQt9B7clIh4FPkYORThG0s7l+NyKDtwNzCpDFKyNnH9dzr8u51+Ps6/L+dfhBn53cP2vy/n3Lv+xGiLiNmA7YCVyT6yDy/FZypUG3ww8AExonP20NnH+dTn/upx/Pc6+Ludfjxv49bn+1+X8e5MXmeqHpLWB7wCrk8vm30ZW/E2BTSPi1orF63nOvy7nX5fzr8fZ1+X865G0LnA58CjwrYg4pRxfHPg+uajOFHJhHTccR4Hrf13Ov7e4gzsfklYk55y8F5gI3EeuFnhb1YItJJx/Xc6/Ludfj7Ovy/nX4wZ+fa7/dTn/3uEO7iCpsXy+dZ7zr8v51+X863H2dTn/znIDv7u4/tfl/Mcud3AHIEmtoTjNf1tnOP+6nH9dzr8eZ1+X8+8ebuB3nut/Xc6/N7iDa2ZmZmaAG/hmNva5g2tmZmZmZmY9wUu+m5mZmZmZWU9wB9fMzMzMzMx6gju4ZmZmZmZm1hPcwTUzMzMzM7Oe4A6umZmZmZmZ9QR3cM3MbEyTdKWkMbMlgKToc5tcu0xDIWlyn/LPql0mMzOzFndwzcysK/TT8VvQbb/aZR6BvwLHlNuM1kFJW5Xf7cr5vVDSKuU595av9xtqdv18z7UknSbpVknPSHpR0kOSLpa0v6RFGk+f0Sj7/W1Jw8zMrE0m1C6AmZlZcUw/xw4FlgJOBp7u89jN5X4fYLFRLNdouDciprXpe93MK7NbBdiX7EifNb8XShIwDZgKCLgOuILsxE4GtgJ2Bj4MbAwQETPKa5C0LbBiW34LMzOzNnAH18zMukJ/Hb5ylXYp4KSIuHc+r7tvVAvW5SLiZuZ19oG8Ekx2cBfUkZ4KHE12hN8bEb/v+wRJu5AnGszMzLqehyibmdmY1t8c3MZQ32mSNpR0aRl6+5SkH0l6fXneapLOl/S4pBck/VrSuvP5OYtJ+pSkmyU9J2mGpN9I2qMTv2e7SVqd7OD+Hdixv84tQERcDOzUybKZmZkNlzu4ZmbWyzYCrin/PgP4HfAe4HJJa5avVwLOAX4ObAlcJmmJ5jeRtDRwLfB5YDbwXeBs4LXAeZI+N/q/StsdQI7k+mFE3D7QEyPi750pkpmZ2ch4iLKZmfWynYC9IuLc1gFJZ5Kdu+uAr0bE8Y3HpgLHAh8g5/22nASsDxwZEV9qPH8i8BPg05IuLMOFx4rNyv3lVUthZmbWRr6Ca2ZmvezaZue2OLvcPwOc0Oexc8r9eq0DkpYF9gJuaHZuASJiJnAkuUDTnu0qdIesUO4fqFoKMzOzNvIVXDMz62U39HPsoXJ/c0TM7vPYg+V+pcaxjYDxQEia1s/3e1W5f8twC1mJyv2Y2UPYzMxsQdzBNTOzXvZMP8dmze+xiJiVO+fM7bQCLFvuNyq3+VligMcGa065H2iEVeuxOQM8ZzAeAt7IyzvzZmZmY5qHKJuZmQ2s1RE+MSI0wG3rNv6sZQd4znLlvu++wEN1bbnfZoTfx8zMrGu4g2tmZjaw35FXSzfvwM+6g9y2Z40y97c/7yj3fxzhz/oueTV7SllRer4kLTLCn2VmZtYR7uCamZkNICIeA84FNpQ0VdIrpvdIWl3Sqm34WTOB88kpRF9WGS/d+DkrAUeUL88a4c+6GzgOWAS4RNJb+3uepJ2An43kZ5mZmXWK5+CamZkt2EHAm8gthPaWdC3wKLAiubjURsAewD1t+FmfLN9vf+Adki4DpgMrA7sCk4AvRsRVbfhZx5ELaE0FbpB0Hbkw13PA8uS+wG8Erm/DzzIzMxt17uCamZktQERMl7QlcCC5HdDuwESyk3sXcBhwWZt+1pOS3g4cDOwG7AcsCjwJXAV8IyIuadPPCuCzki4APg5sRe4RPLH8vD8AXwC+346fZ2ZmNtqUn21mZmbWCZICuCoitqpdlpEqV7I3jgifMDczs67gDq6ZmVkHlQ5u0woR8UiVwgyDpMnAw41Ds93BNTOzbuEPJDMzs846ps/XM6qUYvhm8PLfYaT78ZqZmbWNr+CamZmZmZlZT/A2QWZmZmZmZtYT3ME1MzMzMzOznuAOrpmZmZmZmfUEd3DNzMzMzMysJ7iDa2ZmZmZmZj3BHVwzMzMzMzPrCf8fi8TwVi9hCwQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Matplot lib bad about honoring time zone, need to manually change it with \n",
    "#this command. Dumb.\n",
    "plt.rcParams['timezone'] = 'US/Central'\n",
    "\n",
    "#Lots plot our data up on a double axis\n",
    "fig, ax1 = plt.subplots(figsize=(15,8))\n",
    "\n",
    "ax1.plot(stat1['wind_speed_[m/s]'], color=\"purple\", linestyle = \"-\",linewidth=2,label=\"Wind\")\n",
    "ax1.plot(stat1['wind_gust_[m/s]'], color=\"violet\", marker=\"x\",linewidth=0,label=\"Wind Gust\")\n",
    "ax1.tick_params(axis='x',rotation=45,labelsize=16)\n",
    "ax1.tick_params(axis='y',labelsize=16)\n",
    "ax1.set_xlabel('Time [UTC]',fontsize=20)\n",
    "ax1.set_ylabel('Wind speed [LST]',fontsize=20) \n",
    "ax1.set_title('Severe storm',fontsize=22)\n",
    "ax1.legend(loc=\"upper left\",fontsize=16)\n",
    "ax1.text(stat1.index[0],60, 'Max wind gust = '+max_gust+' mph', fontsize=16)\n",
    "#ax1.xaxis_date('US/Central')\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(stat1['air_temp_[C]'], color=\"red\", marker=\".\",linewidth=0,label=\"Temperature\")\n",
    "ax2.set_ylabel('Temperature [F]',fontsize=20,color=\"red\")\n",
    "ax2.tick_params(axis='y', labelcolor=\"red\",labelsize=16)\n",
    "ax2.legend(loc=\"upper right\",fontsize=16)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}