02_NEO_Sizes & NEO_Orbital_Elements.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7962dae7-1d3b-499a-a540-7518ced890c4",
   "metadata": {},
   "source": [
    "### Import modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "816914f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pathlib\n",
    "import sqlite3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4e0d4c0",
   "metadata": {},
   "source": [
    "### Accessing the NEO database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "efbb82ea-03e9-4b93-bb40-c9fda8995ebb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Accessing the NEO database\n",
    "database_dir = pathlib.Path(\"../databases/neos/\")\n",
    "database_file = pathlib.Path(\"neodys.db\")\n",
    "database_filepath = database_dir / database_file\n",
    "\n",
    "# Establish a connection to the database and set a cursor\n",
    "neodys_db_con = sqlite3.connect(database_filepath)\n",
    "neodys_db_cur = neodys_db_con.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "13b73528-cb8e-421f-95e7-1b0be7c95e34",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Get all information from the DB. Since the DB is rather small, this won't cause any issues!\n",
    "neo_df = pd.read_sql(\"SELECT * FROM main\", neodys_db_con)\n",
    "\n",
    "# Close the database.\n",
    "neodys_db_con.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5934bab3-2dcb-43c0-b527-b10b51da4fd0",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Epoch_MJD</th>\n",
       "      <th>SemMajAxis_AU</th>\n",
       "      <th>Ecc_</th>\n",
       "      <th>Incl_deg</th>\n",
       "      <th>LongAscNode_deg</th>\n",
       "      <th>ArgP_deg</th>\n",
       "      <th>MeanAnom_deg</th>\n",
       "      <th>AbsMag_</th>\n",
       "      <th>SlopeParamG_</th>\n",
       "      <th>Aphel_AU</th>\n",
       "      <th>Perihel_AU</th>\n",
       "      <th>NEOClass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>433</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>1.458129</td>\n",
       "      <td>0.222782</td>\n",
       "      <td>10.827822</td>\n",
       "      <td>304.287024</td>\n",
       "      <td>178.926986</td>\n",
       "      <td>110.777664</td>\n",
       "      <td>10.91</td>\n",
       "      <td>0.46</td>\n",
       "      <td>1.782974</td>\n",
       "      <td>1.133284</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>719</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.636157</td>\n",
       "      <td>0.546780</td>\n",
       "      <td>11.575260</td>\n",
       "      <td>183.857164</td>\n",
       "      <td>156.215519</td>\n",
       "      <td>148.450677</td>\n",
       "      <td>15.54</td>\n",
       "      <td>0.15</td>\n",
       "      <td>4.077554</td>\n",
       "      <td>1.194760</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>887</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.472525</td>\n",
       "      <td>0.571093</td>\n",
       "      <td>9.398799</td>\n",
       "      <td>110.423003</td>\n",
       "      <td>350.474251</td>\n",
       "      <td>340.198429</td>\n",
       "      <td>13.43</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>3.884567</td>\n",
       "      <td>1.060483</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1036</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.665299</td>\n",
       "      <td>0.532826</td>\n",
       "      <td>26.686736</td>\n",
       "      <td>215.494967</td>\n",
       "      <td>132.496155</td>\n",
       "      <td>6.984966</td>\n",
       "      <td>9.47</td>\n",
       "      <td>0.30</td>\n",
       "      <td>4.085439</td>\n",
       "      <td>1.245159</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1221</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.920154</td>\n",
       "      <td>0.434718</td>\n",
       "      <td>11.868483</td>\n",
       "      <td>171.260813</td>\n",
       "      <td>26.717610</td>\n",
       "      <td>271.700798</td>\n",
       "      <td>17.43</td>\n",
       "      <td>0.15</td>\n",
       "      <td>2.754880</td>\n",
       "      <td>1.085428</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37411</th>\n",
       "      <td>2025BZ1</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.332160</td>\n",
       "      <td>0.186998</td>\n",
       "      <td>18.236821</td>\n",
       "      <td>308.499762</td>\n",
       "      <td>179.468173</td>\n",
       "      <td>295.799413</td>\n",
       "      <td>24.75</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.581271</td>\n",
       "      <td>1.083048</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37412</th>\n",
       "      <td>2025BZ2</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.547441</td>\n",
       "      <td>0.347306</td>\n",
       "      <td>12.393768</td>\n",
       "      <td>301.653113</td>\n",
       "      <td>217.970751</td>\n",
       "      <td>291.412078</td>\n",
       "      <td>26.29</td>\n",
       "      <td>0.15</td>\n",
       "      <td>2.084877</td>\n",
       "      <td>1.010006</td>\n",
       "      <td>Apollo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37413</th>\n",
       "      <td>6344P-L</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.821108</td>\n",
       "      <td>0.661803</td>\n",
       "      <td>4.678521</td>\n",
       "      <td>182.791071</td>\n",
       "      <td>235.006174</td>\n",
       "      <td>213.375870</td>\n",
       "      <td>20.40</td>\n",
       "      <td>0.15</td>\n",
       "      <td>4.688125</td>\n",
       "      <td>0.954091</td>\n",
       "      <td>Apollo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37414</th>\n",
       "      <td>2025BQ7</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.257766</td>\n",
       "      <td>0.500895</td>\n",
       "      <td>19.428948</td>\n",
       "      <td>134.964544</td>\n",
       "      <td>9.059571</td>\n",
       "      <td>325.461747</td>\n",
       "      <td>22.11</td>\n",
       "      <td>0.15</td>\n",
       "      <td>3.388669</td>\n",
       "      <td>1.126863</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37415</th>\n",
       "      <td>2025BR7</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.374864</td>\n",
       "      <td>0.410936</td>\n",
       "      <td>22.307244</td>\n",
       "      <td>309.646982</td>\n",
       "      <td>255.517583</td>\n",
       "      <td>262.288565</td>\n",
       "      <td>25.20</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.939845</td>\n",
       "      <td>0.809883</td>\n",
       "      <td>Apollo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37416 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Epoch_MJD  SemMajAxis_AU      Ecc_   Incl_deg  \\\n",
       "0          433    60000.0       1.458129  0.222782  10.827822   \n",
       "1          719    60600.0       2.636157  0.546780  11.575260   \n",
       "2          887    60600.0       2.472525  0.571093   9.398799   \n",
       "3         1036    60600.0       2.665299  0.532826  26.686736   \n",
       "4         1221    60600.0       1.920154  0.434718  11.868483   \n",
       "...        ...        ...            ...       ...        ...   \n",
       "37411  2025BZ1    60600.0       1.332160  0.186998  18.236821   \n",
       "37412  2025BZ2    60600.0       1.547441  0.347306  12.393768   \n",
       "37413  6344P-L    60600.0       2.821108  0.661803   4.678521   \n",
       "37414  2025BQ7    60600.0       2.257766  0.500895  19.428948   \n",
       "37415  2025BR7    60600.0       1.374864  0.410936  22.307244   \n",
       "\n",
       "       LongAscNode_deg    ArgP_deg  MeanAnom_deg  AbsMag_  SlopeParamG_  \\\n",
       "0           304.287024  178.926986    110.777664    10.91          0.46   \n",
       "1           183.857164  156.215519    148.450677    15.54          0.15   \n",
       "2           110.423003  350.474251    340.198429    13.43         -0.12   \n",
       "3           215.494967  132.496155      6.984966     9.47          0.30   \n",
       "4           171.260813   26.717610    271.700798    17.43          0.15   \n",
       "...                ...         ...           ...      ...           ...   \n",
       "37411       308.499762  179.468173    295.799413    24.75          0.15   \n",
       "37412       301.653113  217.970751    291.412078    26.29          0.15   \n",
       "37413       182.791071  235.006174    213.375870    20.40          0.15   \n",
       "37414       134.964544    9.059571    325.461747    22.11          0.15   \n",
       "37415       309.646982  255.517583    262.288565    25.20          0.15   \n",
       "\n",
       "       Aphel_AU  Perihel_AU NEOClass  \n",
       "0      1.782974    1.133284     Amor  \n",
       "1      4.077554    1.194760     Amor  \n",
       "2      3.884567    1.060483     Amor  \n",
       "3      4.085439    1.245159     Amor  \n",
       "4      2.754880    1.085428     Amor  \n",
       "...         ...         ...      ...  \n",
       "37411  1.581271    1.083048     Amor  \n",
       "37412  2.084877    1.010006   Apollo  \n",
       "37413  4.688125    0.954091   Apollo  \n",
       "37414  3.388669    1.126863     Amor  \n",
       "37415  1.939845    0.809883   Apollo  \n",
       "\n",
       "[37416 rows x 13 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neo_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e3e40fe",
   "metadata": {},
   "source": [
    "### Now we create a function to compute the size of the NEOs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "71298f8c-5755-4820-8f5a-6b2ac9e92bf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "def comp_neo_diameter(abs_mag : float, albedo : float=0.15):\n",
    "    \"\"\"\n",
    "    Function to compute the diameter of NEOs based on their absolute magnitude and albedo. If no\n",
    "    albedo is provided, a default value of 0.15 is assumed.\n",
    "    \n",
    "    The result is provided in km.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    abs_mag : float\n",
    "        The NEO's absolute magnitude.\n",
    "    albedo : float, default = 0.15\n",
    "        The NEO's albedo.\n",
    "    \"\"\"\n",
    "    \n",
    "    # Compute the diameter in km\n",
    "    neo_diam_km = ((10.0 ** (-0.2 * abs_mag))/(math.sqrt(albedo))) * 1329.0\n",
    "    \n",
    "    return neo_diam_km"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ca45c87e-5e95-405b-8637-921123fde2f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Known minimum NEO diameter: 0.0 km\n",
      "Known maximum NEO diameter: 3173.07 km\n",
      "Mean NEO diameter: 0.3370603485140047 km\n",
      "Median NEO diameter: 0.06 km\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Let's convert the absolute magnitude to the corresponding sizes\n",
    "neo_diam_array = np.array([round(comp_neo_diameter(k),2) for k in neo_df[\"AbsMag_\"]])\n",
    "\n",
    "# Print some statistics\n",
    "print(f\"Known minimum NEO diameter: {np.min(neo_diam_array)} km\")\n",
    "print(f\"Known maximum NEO diameter: {np.max(neo_diam_array)} km\")\n",
    "print(f\"Mean NEO diameter: {np.mean(neo_diam_array)} km\")\n",
    "print(f\"Median NEO diameter: {np.median(neo_diam_array)} km\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9e38da14-10de-4b6b-bef9-80c5d0c4d067",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>AbsMag_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7653</th>\n",
       "      <td>2010LF64</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7646</th>\n",
       "      <td>2010LB67</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1036</td>\n",
       "      <td>9.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>433</td>\n",
       "      <td>10.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1866</td>\n",
       "      <td>12.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36395</th>\n",
       "      <td>2024UQ</td>\n",
       "      <td>32.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25075</th>\n",
       "      <td>2021BO</td>\n",
       "      <td>32.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36770</th>\n",
       "      <td>2024XA1</td>\n",
       "      <td>33.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6524</th>\n",
       "      <td>2008TS26</td>\n",
       "      <td>33.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30804</th>\n",
       "      <td>2022WJ1</td>\n",
       "      <td>33.58</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37416 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Name  AbsMag_\n",
       "7653   2010LF64     0.17\n",
       "7646   2010LB67     0.17\n",
       "3          1036     9.47\n",
       "0           433    10.91\n",
       "14         1866    12.52\n",
       "...         ...      ...\n",
       "36395    2024UQ    32.90\n",
       "25075    2021BO    32.95\n",
       "36770   2024XA1    33.04\n",
       "6524   2008TS26    33.18\n",
       "30804   2022WJ1    33.58\n",
       "\n",
       "[37416 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Some values appear to be ... weird. We check now the corresponding absolute magnitude\n",
    "neo_df.sort_values(by=\"AbsMag_\")[[\"Name\", \"AbsMag_\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9a638bd3-3f38-40a4-8e03-e3d31a1bf331",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# Define a histogram bins array\n",
    "bins_range = np.arange(0, 0.26, 0.01)\n",
    "\n",
    "# Let's set a dark background\n",
    "plt.style.use('dark_background')\n",
    "\n",
    "# Set a default font size for better readability\n",
    "plt.rcParams.update({'font.size': 14})\n",
    "\n",
    "# Create a figure and axis\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "# Plot a histogram of the absolute magnitude distribution\n",
    "ax.hist(neo_diam_array, bins=bins_range, color='tab:orange', alpha=0.7)\n",
    "\n",
    "# Set labels for the x and y axes\n",
    "ax.set_xlabel('NEO Diameter in km')\n",
    "ax.set_ylabel('Number of NEOs')\n",
    "\n",
    "# Limit the xlim\n",
    "ax.set_xlim(0, 0.25)\n",
    "\n",
    "# Set a grid\n",
    "ax.grid(axis='both', linestyle='dashed', alpha=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13520555",
   "metadata": {},
   "source": [
    "### Compute a cumulative distribution of the absolute magnitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a56f3c79-ffe2-4733-a81a-de9664bd1a09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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t+C8zcobv+yovLw/UDpu5gna20c8u2tmVrnYjijwV5kmHuuJf/kanVJjXfT2kB/c72+hnVxDbBWcmAAAASKvWiNPhLmlIP1s6n5DfvVlfa4QX8QNAtmGxDwAAgLgammNa3xJVeTj+j4xlQ32t2x1VQ3P8l/kDADKHxT5yhnNOLS0tgdphM1fQzjb62UU7u9LVzkm6q75TrRGnypG+hhZIvicNLejenK814nT3mk4250sj7ne20c+uILZjN/4UsRs/AADIFTPHhrS4Jl+TS0IqzOt+6f663VHdvaZTqxujmR4eAOSMZNah/bwDCwgez/M0btw4bd++PVC/scsFtLONfnbRzq50t1vdGNUzjVFVl/oaUeSpNeLU0BzjGaNBwP3ONvrZFcR2vIwfOcPzPJWUlMjz2DHYGtrZRj+7aGfXYLRzkl5ujmnVtqheZqE/aLjf2UY/u4LYjsU+AAAAAAABw2IfAAAAAICAYbGPnBGLxdTU1KRYjI8HsoZ2ttHPLtrZRTu7aGcb/ewKYjt2408Ru/EDAICB8CQ2vAMAJCWZdSjP7CNneJ6nysrKQG26kStoZxv97KLd4Jk5NqSfv7dI979niJa8u/t/f/7eIs0cG0rL7dPOLtrZRj+7gtiOxb6kuro6Oee0aNGiTA8Fg8jzPBUXFwfqDpwraGcb/eyi3eCYOTakOy8q1PSykFoPxbS5NabWQzFNL+s+n44FP+3sop1t9LMriO1yfrF/2WWXaebMmdqxY0emhwIAAALOk7S4Jl8jijxt3BvTwU4p5qSDndLGvTGNKPK06Kx8BedHTQBApuT0Yr+0tFQ/+MEP9KEPfUidnZ2ZHg4AAAi46lJfk0tCamqPvwHUzgMxVZ0UUnVpTv+IBgBIg6x9JLn22mu1ZMkSrVmzRpFIRM45zZs375hfc+aZZ+qxxx5Ta2urDhw4oNWrV+uqq67q9/r33nuv/vM//1Mvv/xyuoePLBSLxbR169ZA7bCZK2hnG/3sol36jSjyVJgnHeqKf/kbnVJhXvf1BoJ2dtHONvrZFcR2WbvY/8pXvqLrrrtOFRUVampqesvrz5kzR08//bRmzZqlhx9+WEuWLFFZWZkefvhhffazn+1z/UWLFunEE0/Ut771rcEYPrLUnj17Mj0EpIh2ttHPLtqlV2vE6XCXNCQv/uUn5EuHu7qvN1C0s4t2ttHPrqC1y9rF/sKFC1VRUaHS0lItWbLkmNcNhUL68Y9/rFgsptmzZ+u6667TDTfcoKlTp+rVV1/VHXfcofHjx/de/7TTTtMtt9yiefPmyTk+5CZXeJ6nqqqqQG26kStoZxv97KJd+jU0x7S+JarycPwfwcqG+lq3O6qG5oE9s0Q7u2hnG/3sCmK7rF3sL1++XNu2bUvounPnzlVlZaUefPBBrV27tvd8W1ub7rjjDhUWFh71FoB3vvOdOumkk7Rx40Z1dnaqs7NTEyZM0Pe+9z09//zzaZ8LsoPneSoqKgrUHThX0M42+tlFu/Rzku6q71RrxKlypK+hBZLvSUMLpMqRvlojTnev6dRAn4qgnV20s41+dgWxXdYu9pMxZ84cSdKyZcv6XLZ06VJJ0nnnndd77je/+Y3OOOMMTZs2rffYsWOHvv71r+t973vfcRkzAADITasbo7ph2WE9vzOq4UW+Thnha3iRr+eaus+vboxmeogAgADo5x1jtkyaNEmStGHDhj6X7dq1S+3t7b3XkaT9+/dr//79R12vs7NTTU1N2rRpU9zvUVBQoMLCwt4/h8NhSZLv+/L97t+ZOOfknJPneUf9Rqhnk4dkz/fcbjrP94wx2fNBmFPP0TOuIMzpzeeDOqcj+wVlTkHs1N/Yk+lnZU5B7PRW/YI0p2zotLoxqmcao5pSlqcRRZ5aI04v74oqluY5Hfl96WRjTj2CNKcgdkpHPytzCmKneOf7+//ZNqdkBGKxP2zYMEnqs4Dv0dbW1nudVN1000269dZb+5w/44wzdPDgQUlSS0uLtm3bpnHjxqmkpKT3Ok1NTWpqatLEiRNVXFzce37r1q3as2ePJk+erKKiot7zGzZsUHt7u6ZMmaJQKNR7ft26dero6NC0adOOGsMLL7yggoICVVVV9Z6LRqNau3atwuHwUb/oiEQiWrdunUaNGqWKiore821tbdq4caPKy8tVXl7eez5ocxoyZIjGjBkTqDlJwesUb05DhgzRGWecEag59ciFOfX0C9KcegR5Tqeddlpvu6DMKZs6lZWXK6+8XO3q/oFsbEF651RQUNDb7njNKYidMjGnTZs2HdUuCHMKYqf+5rR9+/aj+gVhTkHsFG9OGzZs0IknnpjVc9q+fbsS5UkDflvYoLvxxhv19a9/XfPnz9d9993X5/KlS5fqoosuUmVlZdxn5hsbGzV06FANHz485THEe2Z/x44dGj58uNrb2yVl12+m+jufbb+ZYk7MiTkxJ+bEnJgTc2JOzIk5MSfmlNicTjzxRLW1tam4uLh3HdqfQDyz3/OMfn/P3hcXF6u1tXVA36Ojo0MdHR19zsdisd4QPY4MP5Dzb77dTJ4Pwpx839eUKVP00ksv9Y7P+pwSHaP1OXme19vuyPOW5xTETv2NPZl+VuYUxE7xzh/Z7sjbszynIHaKd/7Ix7w3fw+rcxrsMSZ7frDmdKx26Rp7f+fpNPA5HY9+dBqcOfm+r6lTp/bbLtnbH+w5JSL1NwBkkZ736h/5coseJ598ssLhcNz38yP3HPkSGNhCO9voZxft7KKdXbSzjX52Ba1dIBb7K1eulCRddNFFfS67+OKLj7oOAAAAAABBF4jF/vLly7Vp0yZ98IMf1NSpU3vPFxcX6+abb9bhw4d1//33p+V71dbWqqGhQfX19Wm5PQAAAAAA0i1rN+j76Ec/qlmzZkmSpkyZore//e166qmntHHjRknSU089pXvuuaf3+nPmzNHSpUsViUT00EMPqb29XVdeeaUmTJig66+/Xt/+9rfTOr5wOJzwxgjIHkVFRYpEIpkeBlJAO9voZxft7KKdXbSzjX52WWiX7DrUZeNx7733umO59957+3zNWWed5R5//HG3b98+d/DgQffMM8+4q6++elDGFw6HnXPOhcPhjP9dcSR++L6f8TFw0C4XD/rZPWhn96Cd3YN2tg/62T0stEtyHZr5AVs8WOzbO3zfdzNmzDBxJ+agXZAO+tk9LLXzJHd6qe/OHR9yp5f6zsuCMdGOg3a5d9DP7mGlXTLr0EB89B4AAMhdM8eGtLgmX5NLQirMkw53SetborqrvlOrG6OZHh4AABkRiA36AABAbpo5NqQ7LyrU9LKQWg/FtLk1ptZDMU0v6z4/c2ywPkYJAIBEsdgHAAAmeZIW1+RrRJGnjXtjOtgpxZx0sFPauDemEUWeFp2VLy/TAwUAIAOydjf+bFVbW6tFixbJ93297W1vYzd+Y3zfVywWy/QwkALa2UY/u7K53emlvu5/zxC1Hupe6L/Z0AJpeJGvD//mkF5uzs45DKZsbodjo51t9LPLQrtkduPnmf0k1dXVqbq6WjU1NZkeClJQUFCQ6SEgRbSzjX52ZXO7EUWeCvOkQ13xL3+jUyrM675eLsrmdjg22tlGP7uC1o7FPnKG7/uqqqqS7/PP3hra2UY/u7K9XWvE6XCXNKSf7YZPyO/erK81knsvYsz2dugf7Wyjn11BbBecmQAAgJzS0BzT+paoysPxf5wpG+pr3e6oGnLwJfwAALDYBwAAJjlJd9V3qjXiVDnS19ACyfe636tfOdJXa8Tp7jWdbE4EAMhJLPaRU6JRPm/ZKtrZRj+7sr3d6saoblh2WM/vjGp4ka9TRvgaXuTruabu86sbs3v8gynb26F/tLONfnYFrR278acomV0QAQDA4PIkVZf6GlHkqTXi1NAc4wccAEDgsBv/IKqtrVVDQ4Pq6+szPRSkIBwOZ3oISBHtbKOfXVbaOUkvN8e0altUL7PQl2SnHfqinW30syto7VjsJ4mP3rPL931NmjQpUDts5gra2UY/u2hnF+3sop1t9LMriO2CMxMAAAAAACCJxT4AAAAAAIHDYh85wzmnSCQi53gnpzW0s41+dtHOLtrZRTvb6GdXENuxG3+K2I0fAAAAAHA8sRs/0I9Ro0ZleghIEe1so59dtLOLdnbRzjb62RW0diz2kTN831dFRUWgdtjMFbSzjX520c4u2tlFO9voZ1cQ2wVnJsdJbW2tGhoaVF9fn+mhAAAAAAAQF4v9JNXV1am6ulo1NTWZHgoAAAAAAHGx2EfOcM6pra0tUDts5gra2UY/u2hnF+3sop1t9LMriO3YjT9F7MYPAAAAADie2I0f6Ed5eXmmh4AU0c42+tlFO7toZxftbKOfXUFrx2IfOcP3fZWXlwdqh81cQTvb6GcX7eyinV20s41+dgWxXXBmAgAAAAAAJLHYBwAAcXiSTi/1Nb0spNNLfXmZHhAAAEhKXqYHABwvzjm1tLQEaofNXEE72+hnz8yxIS2uydfkk/I09KR2HRhXpPW7u3RXfadWN0YzPTwkgPudXbSzjX52BbEdu/GniN34AQBBNHNsSHdeVKgRRZ6a2mM61CUNyZPKw75aI043LDvMgh8AgAxhN/5BVFtbq4aGBtXX12d6KEiS53kaP368PI8Xo1pDO9voZ4cnaXFNvkYUedq4N6aDXZ4KR43Twa7uP48o8rTorHxe0m8A9zu7aGcb/ewKYjsW+0mqq6tTdXW1ampqMj0UJMnzPJWUlATqDpwraGcb/eyoLvU1uSSkpvbY3854KgiXSH9b3u88EFPVSSFVl/LjQ7bjfmcX7Wyjn11BbMejNQAAkCSNKPJUmCcd6op/+RudUmFe9/UAAEB2Y7EPAAAkSa0Rp8N/e49+PCfkS4e7uq8HAACyG4t95IxYLKampibFYrG3vjKyCu1so58dDc0xrW+Jqjz8tx8PXEyRfTsl192ubKivdbujamimZbbjfmcX7Wyjn11BbMdu/CliN34AQBAduRv/zgMxvdHZ/Yx+2VB24wcAINPYjR+Iw/M8VVZWBmrTjVxBO9voZ8vqxqhuWHZYz++MaviQkE47dZKGDwnpuaYoC31DuN/ZRTvb6GdXENv18648IHg8z1NxcbE8z5NzvKDFEtrZRj97VjdG9UxjVFPK8nTWjEKteS6il3Z28VJAQ7jf2UU72+hnVxDbsdgHAAB9OEkvN8eUtzOql5tjLPQBADCGl/EDAAAAABAwLPaRM2KxmLZu3RqoHTZzBe1so59dtLOLdnbRzjb62RXEduzGn6Ta2lotWrRIvu/rbW97G7vxAwAAAACOC3bjH0R1dXWqrq5WTU1NpoeCJHmep6qqqkDtsJkraGcb/eyinV20s4t2ttHPriC2Y7GPnOF5noqKigJ1B84VtLONfnbRzi7a2UU72+hnVxDbsdgHAAAAACBgWOwDAAAAABAwbNCXomQ2RkD2CIfD9DKKdrbRzy7a2UU7u2hnG/3sstCODfqAfmT7nRf9o51t9LOLdnbRzi7a2UY/u4LWjsU+cobv+5o6dap8n3/21tDONvrZRTu7aGcX7Wyjn11BbBecmQAJCIVCmR4CUkQ72+hnF+3sop1dtLONfnYFrR2LfQAAAAAAAobFPgAAAAAAAcNu/CliN36bioqKFIlEMj0MpIB2ttHPLtrZRTu7aGcb/eyy0I7d+IF+dHR0ZHoISBHtbKOfXbSzi3Z20c42+tkVtHYs9pEzfN/XtGnTArXDZq6gnW30s4t2dtHOLtrZRj+7gtguODMBAAAAAACSWOwDAAAAABA4LPaTVFtbq4aGBtXX12d6KAAAAAAAxMVu/CliN36bfN9XLBbL9DCQAtrZRj+7aGcX7eyinW30s8tCO3bjB/pRUFCQ6SEgRbSzjX520c4u2tlFO9voZ1fQ2rHYR87wfV9VVVWB2mEzV9DONvrZRTu7aGcX7Wyjn11BbBecmQAAAAAAAElSXqYHAABA0HmSqkt9jSjy1BpxamiOsWEOAAAYVCz2kVOi0Wimh4AU0c62XO43c2xIi2vyNbkkpMI86XCXtL4lqrvqO7W6Mfv/XnK5nXW0s4t2ttHPrqC1Yzf+FLEbPwDgrcwcG9KdFxVqRJGnpvaYDnVJQ/Kk8rCv1ojTDcsOm1jwAwCA7MBu/EA/wuFwpoeAFNHOtlzs50laXJOvEUWeNu6N6WCnFHPSwU5p496YRhR5WnRWvrxMD/Qt5GK7oKCdXbSzjX52Ba1dSov9008/XQsWLDjqL6OoqEh1dXVqbGzUhg0bdN1116VtkEA6+L6vSZMmBWqHzVxBO9tytV91qa/JJSE1tcf/vN6dB2KqOimk6tLs/XvJ1XZBQDu7aGcb/ewKYruUZvLFL35RX/7yl4962cAdd9yh6667TuFwWOPGjdPdd9+tCy+8MG0DBQDAkhFFngrzpENd8S9/o1MqzOu+HgAAQLqltNivqanRE0880fvnUCikBQsWqL6+XqWlpTrllFO0e/dufepTn0rbQAEAsKQ14nT4b+/Rj+eE/O7N+lojbJ0DAADSL6XF/kknnaTt27f3/vmss85ScXGxlixZosOHD6upqUn//d//ralTp6ZtoMBAOecUiUTkHD9YW0M723K1X0NzTOtboioPx3+oLRvqa93uqBqa47/MPxvkarsgoJ1dtLONfnYFsV1Ki/2uri4VFhb2/nnOnDlyzh31bP+ePXtUUlIy8BECaeKc07p16wJ1B84VtLMtV/s5SXfVd6o14lQ50tfQAsn3pKEFUuXI7t34717TmdUfiZOr7YKAdnbRzjb62RXEdikt9rds2aLzzz+/989XXXWVNm/erG3btvWeGzNmjPbs2TPwEQJpNGrUqEwPASminW252m91Y1Q3LDus53dGNbzI1ykjfA0v8vVcU9TMx+7larsgoJ1dtLONfnYFrV0/7yQ8tgceeEDf/OY39cwzz+jw4cOaOnWqvvrVrx51nTPOOEMbNmxIyyCBdPB9XxUVFWptbVUslr0vm0VftLMt1/utbozqmcaoqkt9jSjy1BpxamiOZfUz+j1yvZ1ltLOLdrbRz64gtktpsX/XXXeppqZG73vf++R5nh5//HHdcccdvZdXVVVp6tSp+tKXvpS2gQIAYJWT9HIWvzcfAAAET0qL/Y6ODr3//e9XOByWc04HDhw46vJdu3Zp+vTp2rJlSzrGCAAAAAAAkpDSYr9He3t73PN79uzh/frIOs45tbW1BWrTjVxBO9voZxft7KKdXbSzjX52BbGdJ6X2tsHzzz9fM2fOVHl5uSSpqalJq1evPmpH/iALh8Nqa2tTcXFxv7/0AAAAAAAgXZJZhyb9zP4ll1yi73//+zrllFMkSZ7nSVLvb0Bee+01/eu//quWLl2a7E0Dg668vFxNTU2ZHgZSQDvb6GcX7eyinV20s41+dgWtXVKL/QULFuhHP/qRfN/Xn//8Zy1fvlzbt2+XJI0bN04XXHCB3vGOd+j//u//tHDhQt13332DMuhMqq2t1aJFi+T7KX1qITLI932Vl5dr165dgdlhM1fQzjb62UU7u2hnF+1so59dQWyX8GJ/4sSJ+sEPfqC9e/fqgx/8oJYvX97nOrfccovmzp2rBx98UEuWLNGqVav02muvpXXAmVZXV6e6urrel08AAAAAAJBtEn56+jOf+Yx839fll18ed6Hf449//KMuv/xy5eXl6TOf+UxaBgkAAAAAABKX8GL/wgsv1PLly1VfX/+W112zZo3+8Ic/6B//8R8HNDggnZxzamlpCdQOm7mCdrbRzy7a2UU7u2hnG/3sCmK7hBf7Y8eO1QsvvJDwDb/wwgsaO3ZsKmMCBoVzTtu2bQvUHThX0M42+tlFO7toZxftbKOfXUFsl/BiPxqNKi8v8f388vLyFI1GUxoUMBg8z9P48eN7P0ECdtDONvrZRTu7aGcX7Wyjn11BbJfwYn/z5s2aOXNmwjc8c+ZMbdmyJZUxAYPC8zyVlJQE6g6cK2hnG/3sop1dtLOLdrbRz64gtkt4sf+73/1O73znO3XZZZe95XUvvfRSzZw5U7/97W8HNDgAAAAAAJC8hBf73/72t3Xw4EE99NBDmj9/fr/Xmzdvnh566CEdOHBA3/nOd9IxRgAAAAAAkISE34Tf3Nys97///XrkkUf0k5/8RLfddptWrFih7du3S5LGjRunOXPmaMyYMers7NSVV16pXbt2DdrAgWTFYjE1NTUpFotleihIEu1so59dtLOLdnbRzjb62RXEdp6kpLYbnDFjhr73ve/p7LPPjnv5n/70J33qU5/Sc889l47xZa1wOKy2tjYVFxervb0908MBAAAAAARcMuvQpBf7PSZOnKizzz5bZWVlkqSdO3fqT3/6kzZt2pTKzZnDYt8ez/M0ceJEbdq0KVAfqZELaGcb/eyinV20s4t2ttHPLivtklmHJv5Zem+yadOmnFnYIxg8z1NxcbE8z8vqOzD6op1t9LOLdnbRzi7a2UY/u4LYLuEN+pJ10kknacqUKYN18wAAAAAAoB8JL/a7urr0xS9+8ahzV199tR555JG41//kJz+p559/fmCjAwAAAAAASUt4se95njzPO+rc2972Nl1xxRVpHxQwGGKxmLZu3RqoHTZzBe1so59dtLOLdnbRzjb62RXEdoP2Mn4gG+3ZsyfTQ0CKaGcb/eyinV20s4t2ttHPrqC1Y7GPnOF5nqqqqvq8QgXZj3a20c8u2tlFO7toZxv97ApiOxb7yBme56moqChQd+BcQTvb6GcX7eyinV20s41+dgWxHYt9AAAAAAAChsU+AAAAAAAB40lyiVwxGo2qpaVFLS0tvedKSko0atQovfrqq32u33NZXl5e2gabTcLhsNra2lRcXKz29vZMDwcJCofD9DKKdrbRzy7a2UU7u2hnG/3sstAumXVoUov9ZDnnWOwDAAAAAJAGyaxDE34ZfygUSvoI6kIfNvm+r6lTp8r3efeKNbSzjX520c4u2tlFO9voZ1cQ2wVnJkACQqFQpoeAFNHONvrZRTu7aGcX7Wyjn11Ba8diHwAAAACAgEn4dfbnnntuSt9g1apVKX0dAAAAAABITVIb9DmX0FV7OeeUn5+fyriyHhv02VRUVKRIJJLpYSAFtLMt3f08SdWlvkYUeWqNODU0xxJ7MEPSuO/ZRTu7aGcb/eyy0C6ZdWjCz+z/6Ec/Snixf+GFF2rixImJ3jRw3HR0dGR6CEgR7WxLZ7+ZY0NaXJOvySUhFeZJh7uk9S1R3VXfqdWNyX9yDI6N+55dtLOLdrbRz64gtnPpOt7+9re7P/zhDy4ajbqOjg5XV1eXtttO9/HpT3/avfzyy669vd21tra65cuXu5qamoS/PhwOO+ecC4fDGZ8LR2KH7/tuxowZzvf9jI+Fg3a5dKSz38yxIff0R05w62pPdMs/NMT93weGuOUfGuLW1Z7onv7ICW7m2FDG5xukg/ue3YN2dg/a2T7oZ/ew0i6ZdWhaNug75ZRT9Itf/EJ//vOfdf755+vRRx9VdXW1amtr03Hzg2Lr1q367Gc/q6lTp+rss8/Wxo0btXTpUo0cOTLTQwMAxOFJWlyTrxFFnjbujelgpxRz0sFOaePemEYUeVp0Vr68TA8UAAAgCwxosV9SUqLvf//7Wr9+va6++mo99dRTmjlzpt73vvdpw4YN6RrjoHj00Ue1bNkyvfbaa1q/fr1uuOEGDR8+XKeffnqmhwYAiKO61NfkkpCa2mNxL995IKaqk0KqLuWDZgAAAFL6ieiEE07Qf/zHf2jTpk2qra3VX//6V/3TP/2T5syZo/r6+rQM7Nprr9WSJUu0Zs0aRSIROec0b968Y37NmWeeqccee0ytra06cOCAVq9erauuuuotv1d+fr4+/vGPa+/evXrppZfSMn4AQHqNKPJUmCcd6op/+RudUmFe9/UAAACQ5PsYamtr3euvv+6i0ajbsmWLmzdv3qC8F2Hz5s3OOeeam5t7//+xvtecOXPc4cOH3f79+90Pf/hDd+edd/Z+3Wc/+9m4XzNr1izX3t7uurq6XGNjo5sxY8agvFeCI3uObH8PDgftgnqko9/ppb577uPd79X/n/f3Pf744SHuuY+f6E4v5d9KtrXjoB0H7XLpoJ/dw0K7QXnP/tVXX61XXnlF//mf/6mCggLdeOONOvXUU3XfffclehNJWbhwoSoqKlRaWqolS5Yc87qhUEg//vGPFYvFNHv2bF133XW64YYbNHXqVL366qu64447NH78+D5f9+yzz2ratGk6++yz9dvf/lYPP/ywRo0aNSjzQXYoKCjI9BCQItrZlo5+Dc0xrW+Jqjwc/6GrbKivdbujamiO/zJ/pIb7nl20s4t2ttHPrqC1S3ix/4tf/EL/8A//oE2bNunmm2/W1q1bdcUVV+iqq6465pGq5cuXa9u2bQldd+7cuaqsrNSDDz6otWvX9p5va2vTHXfcocLCwrhvAYhEItq0aZPq6+v1sY99TLFYTAsWLEh5zMhuvu+rqqpKvs/7ea2hnW3p6uck3VXfqdaIU+VIX0MLJN+ThhZIlSN9tUac7l7TKZeeYUPc9yyjnV20s41+dgWxXV4yV/Y8T5WVlaqrq0vous45/epXv0p5cImaM2eOJGnZsmV9Llu6dKkk6bzzztOXv/zlY96O53kqLCyMe1lBQcFRl4XDYUnd/yh6/kE45+Sck+d58ry/v2c0Fov13n4y59/8Dy0d53vGmOz5IMyp5+gZVxDm9ObzQZ3Tkf2CMqcgdupv7Mn0e6sx/vl1p3//Q6dqzwxpcklIJ4d9He6Snt8VVd2aTq1ujB6XOQWx01v1C9KcgtipvzkdeftBmVOqY7cypx5BmlMQO6Wjn5U5BbFTvPP9/f9sm1MyEl7s33bbbSl/k8E2adIkSYr7CQC7du1Se3t773V6fP3rX9f//M//qLGxUSNHjlRtba3Gjh2rRx55JO73uOmmm3Trrbf2OX/GGWfo4MGDkqSWlhZt27ZN48aNU0lJSe91mpqa1NTUpIkTJ6q4uLj3/NatW7Vnzx5NnjxZRUVFvec3bNig9vZ2TZkyRaFQqPf8unXr1NHRoWnTph01hhdeeEEFBQWqqqrqPReNRrV27VqFw+Gj5h6JRLRu3TqNGjVKFRUVvefb2tq0ceNGlZeXq7y8vPd8kObk+75OPfVUtbS0aMuWLYGYU48gdYo3p9LSUp166qmSpB07dgRiTkHs1N+chg8f3ttv8+bNA57TIUkf/s0Lmja2SNNOf5vaO5w27Y2pa0RU2kandM+pp10sFgvMnILY6c1zOnjwoCorKyX9/QdG63MKYqd4c3rllVfk+76mTZvW2876nILYqb85vfjiiyosLDyqn/U5BbFTvDn1LNzD4bAmTpyYtXPavn27EuVJ2f+KxxtvvFFf//rXNX/+/Lh7BCxdulQXXXSRKisrtWnTpj6XNzY2aujQoRo+fHjvufvvv19z5sxRaWmp9u7dqzVr1ujLX/6ynn322bhjiPfM/o4dOzR8+HC1t7dLyq7fTPV3Ptt+M3W8n9mfMmWKXnzxRUWj0UDM6c3ngzqnUCikKVOm6KWXXlJXV1cg5hTETv2NPZl+VuYUxE7xzodCIZ1xxhl66aWXFIvFAjGnIHaKd973fU2dOrW3XRDmNNCxW5mTJE2ZMkUNDQ1HLfYtzymIndLRz8qcgtipv2f2q6ur+3w6W7bN6cQTT1RbW5uKi4t716HHkrGdBBM9brzxRudc/7vxL1261Dnn3MSJE+Ne3tjY6Pbt25fWMbEbPwcHBwcHBwcHBwcHB8fxPAZlN/5stn//fknSsGHD4l5eXFzcex3ktp69FmAP7Wyjn120s4t2dtHONvrZFbR2gVjs97xX/83vy5ekk08+WeFwOO77+ZFbfN/XpEmTBrTJBTKDdrbRzy7a2UU7u2hnG/3sCmK7QMxk5cqVkqSLLrqoz2UXX3zxUdcBAAAAACDoArHYX758uTZt2qQPfvCDmjp1au/54uJi3XzzzTp8+LDuv//+tHyv2tpaNTQ0qL6+Pi23BwAAAABAuiX80XvH20c/+lHNmjVLUveOlpK0cOFCzZkzR5L01FNP6Z577pHU/dEPCxcu1NKlS/Xkk0/qoYceUnt7u6688kpNmDBB119/vbZu3ZqWcdXV1amurk7hcFhtbW1puU0cH845RSKR3l0zYQftbKOfXbSzi3Z20c42+tkV1HZvuYvfI4884q666qreP5977rlu3Lhxg7rL4L333uuO5d577+3zNWeddZZ7/PHH3b59+9zBgwfdM888466++uqM74LIwcHBwcHBwcHBwcHBwTHQI8l16FvfYDQadbfcckvvn7u6uo76cy4eLPZtHqNGjcr4GDhol4sH/ewetLN70M7uQTvbB/3sHhbapf2j9/bt26fi4uLeP3uel8iXAVnF931VVFQEaofNXEE72+hnF+3sop1dtLONfnYFsV1C79lft26dPvCBD2jNmjVqamqSJE2YMEHnnnvuW37tqlWrBjZCAAAAAACQlIQW+7fffrt+85vf6MEHH+w9N2/ePM2bN++tv0Fe1u4BmJLa2lotWrQoUL/xAQAAAAAES0Ir8d///veaPHmyLrzwQo0ZM0a33nqrVq5cmZOfXc9u/HY559TW1ha4HTZzAe1so59dtLOLdnbRzjb62RXEdp6637yflGg0qltvvVVf/vKXB2FINvQs9ouLi9Xe3p7p4QAAAAAAAi6ZdWhKr0U/5ZRT9L3vfS+lwQGZVF5enukhIEW0s41+dtHOLtrZRTvb6GdX0NqltNjftm1b70vYQ6GQqqqq9M53vlNVVVUKhUJpHSCQLr7vq7y8nP0WDKKdbfSzi3Z20c4u2tlGP7uC2C7lmYwYMUI/+tGPtH//fr344ot66qmn9OKLL2rfvn364Q9/qJEjR6ZznAAAAAAAIEEpbZU/YsQIPfPMM6qsrNTevXu1atUqNTU1qaysTGeeeaYWLlyo8847TzNnzlRra2u6xwwAAAAAAI4hpWf2b7nlFlVWVuqb3/ymKioq9K53vUsf+chHdOmll6qiokLf+MY3NGnSJH3hC19I93gzrra2Vg0NDaqvr8/0UJAk55xaWloCtcNmrqCdbfSzi3Z20c4u2tlGP7uC2C6l3fg3bdqkLVu26IILLuj3OsuXL9eECRM0ceLEgYwva7EbPwAAAADgeBr03fhHjx6t1atXH/M6q1ev1ujRo1O5eWBQeJ6n8ePHy/O8TA8FSaKdbfSzi3Z20c4u2tlGP7uC2C6lxf7+/ftVUVFxzOtUVFRo//79KQ0KGAye56mkpCRQd+BcQTvb6GcX7eyinV20s41+dgWxXUqL/ZUrV+qqq67q92X8c+fO1VVXXaUVK1YMZGwAAAAAACAFKe3Gf9ttt+myyy7T0qVL9fjjj2vlypXatWuXTj75ZM2ZM0fvete79MYbb+j2229P93gBAAAAAMBbSGmxv27dOl188cX62c9+pssuu0yXXXaZnHO9L3nYtGmT5s+fr3Xr1qV1sMBAxGIxNTU1KRaLZXooSBLtbKOfXbSzi3Z20c42+tkVxHYp7cZ/pHPOOUfTp09XcXGx2tra9Pzzz+vpp59O0/CyF7vxAwAAAACOp2TXoY4j8aO2ttY1NDS49evXO+ecC4fDGR8TR2KH53musrLSeZ6X8bFw0C6XDvrZPWhn96Cd3YN2tg/62T2stAuHwwmvQ1PaoC+X1dXVqbq6WjU1NZkeCpLkeZ6Ki4sDtcNmrqCdbfSzi3Z20c4u2tlGP7uC2I7FPgAAAAAAAcNiHwAAAACAgGGxj5wRi8W0devWQO2wmStoZxv97KKdXbSzi3a20c+uILYb8G78uYrd+AEAAAAAx1My61Ce2UfO8DxPVVVVgdp0I1fQzjb62UU7u2hnF+1so59dQWyX0mK/q6tLP//5z9M9FmBQeZ6noqKiQN2BcwXtbKOfXbSzi3Z20c42+tkVxHYpLfbb2tq0ffv2dI8FAAAAAACkQUqL/fr6ek2dOjXdYwEAAAAAAGmQ0mL/1ltv1dy5c/WhD30o3ePJerW1tWpoaFB9fX2mh4IkxWIxbdiwIVA7bOYK2g0uT9Lppb7OHR/S6aW+0v3iNfrZRTu7aGcX7Wyjn11BbJfSbvy33HKLzjnnHF144YV67rnntGbNGu3atUvOHX1Tzjl95StfSddYswq78QMIgpljQ1pck6/JJSEV5kmHu6T1LVHdVd+p1Y3RTA8PAAAAR0hmHZrSYj8aTewHQOec8vLykr15E1js2+P7vqZMmaKXXnopUL+xywW0Gxwzx4Z050WFGlHkqak9pkNd0pA8qTzsqzXidMOyw2lZ8NPPLtrZRTu7aGcb/eyy0i6ZdWhKK/Hzzz8/pYEBmRYKhTI9BKSIdunlSVpck68RRZ427v37A9rBTmnj3pgqR/padFa+nmmMJv8b4TjoZxft7KKdXbSzjX52Ba1dSov9J598Mt3jAAAcR9WlviaXhNTUHv831zsPxFR1UkjVpb5ebs7e324DAAAgvpQ26AMA2DaiyFNhnnSoK/7lb3RKhXnd1wMAAIA9KS/2Q6GQPv3pT+vPf/6z9u/fr87Ozt7Lpk6dqrvvvluTJk1KyyCBdIjFYlq3bl1WvwcH8dEu/VojTof/9h79eE7I796srzUy8Bfx088u2tlFO7toZxv97Apiu5QW+0VFRXriiSd05513qqKiQm1tbfK8vz/7s3nzZi1YsEAf/vCH0zZQIB06OjoyPQSkiHbp1dAc0/qWqMrD8R8Gyob6Wrc7qoY0vYSffnbRzi7a2UU72+hnV9DapbTYv/nmm3XOOefopptuUllZmX7yk58cdXlbW5tWrlypiy++OC2DBNLB931NmzZNvs+7V6yhXfo5SXfVd6o14lQ50tfQAsn3pKEFUuXI7t34717TmZbN+ehnF+3sop1dtLONfnYFsV1KM7nmmmv0xBNP6Jvf/Kak7o/Ye7PXXntN48ePH9joAACDZnVjVDcsO6znd0Y1vMjXKSN8DS/y9VxTNG0fuwcAAIDMSGk3/vHjx+vRRx895nXa29s1bNiwlAYFADg+VjdG9UxjVNWlvkYUeWqNODU0x9LyjD4AAAAyJ6XFfnt7u0pLS495nYkTJ2r37t0pDQoAcPw4iY/XAwAACJiUXsb/zDPP6PLLL+/3mfuxY8fq0ksv1ZNPPjmgwWWj2tpaNTQ0qL6+PtNDQZJisZheeOGFQO2wmStoZxv97KKdXbSzi3a20c+uILZLabH/zW9+UyNGjNDy5ct19tlnKy+v+wUCQ4YM0dy5c7V06VLl5eXp29/+dloHmw3q6upUXV2tmpqaTA8FKSgoKMj0EJAi2tlGP7toZxft7KKdbfSzK2jtUlrsr1q1SosXL9aUKVP05JNP6uabb5bU/fL+ZcuWqbKyUrW1tXruuefSOlhgIHzfV1VVVaB22MwVtLONfnbRzi7a2UU72+hnVxDbpfSefUlasmSJVqxYoU984hN6xzveoZEjR6qtrU1//vOfVVdXp3Xr1qVznAAAAAAAIEEpL/Yl6ZVXXtGnP/3pNA0FAAAAAACkQ3BeowAkIBrlc8Otop1t9LOLdnbRzi7a2UY/u4LWzpNS/zjl97znPZo/f76mT5+uYcOGaf/+/Xr++ed177336r//+7/TOMzsEw6H1dbWpuLiYrW3t2d6OAAAAACAgEtmHZrSM/uhUEi//OUv9etf/1qXX365ysrK9MYbb6isrEyXX365HnnkEf3yl79UKBRKaQLAYAmHw5keAlJEO9voZxft7KKdXbSzjX52Ba1dSov9m266Se973/u0atUqnXvuuSoqKtLo0aNVVFSk2bNn66mnntKVV16pz3/+8+keL5Ay3/c1adKkQO2wmStoZxv97KKdXbSzi3a20c+uILZLaSYLFizQK6+8ogsvvFB/+tOf5Fz3OwGcc3r66ad14YUX6q9//as+8pGPpHWwAAAAAADgraW02C8vL9f//u//9ruBQVdXl/73f/9X5eXlAxocAAAAAABIXkqL/e3bt2vo0KHHvM6JJ56obdu2pTQoYDA45xSJRHpfiQI7aGcb/eyinV20s4t2ttHPrqC2c8ken/vc51xzc7MrKyuLe/no0aPd7t273Q033JD0bVs5wuGwc865cDic8bFwcHBwcHBwcHBwcHBwBP9IZh2a0DP748aNO+p4+OGH9ac//UnPP/+8brzxRp1zzjmqrKzUOeeco89//vP6y1/+oqeeekq/+tWvErl54LgZNWpUpoeAFNHONvrZRTu7aGcX7Wyjn11Ba5eXyJW2bNkS9+UMnufpq1/9atzz//RP/6R3v/vdys/PH/gogTTwfV8VFRVqbW1VLBbL9HCQBNrZRj+7aGcX7eyinW30syuI7RJa7N9///2Be+9Cqmpra7Vo0aJAfSQDAAAAACBYElrsL1iwYLDHYUZdXZ3q6uoUDofV1taW6eEAAAAAANAHT08jZzjn1NbWxqtUDKKdbfSzi3Z20c4u2tlGP7uC2M5T9059SFLPM/vFxcVqb2/P9HAAAAAAAAGXzDo05Wf2zznnHD366KN67bXXFIlE1NXV1efo7OxM9eaBQVFeXp7pISBFtLONfnbRzi7a2UU72+hnV9DaJfSe/Tf7l3/5F/3sZz+T53l67bXXVF9fr66urnSPDUgr3/dVXl6uXbt2BWaHzVxBO9voZxft7KKdXbSzjX52BbFdSov9W265Ra2trbr00ku1Zs2adI8JAAAAAAAMQEov4x83bpweeughFvoAAAAAAGShlBb7W7duVUFBQbrHAgwq55xaWloCtcNmrqCdbfSzi3Z20c4u2tlGP7uC2C6l3fg/+9nP6vrrr9fpp5+u1tbWQRhW9mM3fgAAAADA8TTou/F/+9vf1qOPPqqnn35aH/zgB1VdXa1x48bFPYBs4Xmexo8fL8/zMj0UJIl2ttHPLtrZRTu7aGcb/ewKYruUP3rvueeeU1lZme6//36tXbtWmzdv7nO89tpr6RwrMCCe56mkpCRQd+BcQTvb6GcX7eyinV20s41+dgWxXUq78S9evFjf/e531dnZqSeeeEJNTU189B4AAAAAAFkipcX+Zz7zGe3YsUNnn322duzYke4xAQAAAACAAUjpZfxlZWV65JFHWOjDlFgspqamJsVisUwPBUminW30s4t2dtHOLtrZRj+7gtgupcX+xo0bNXz48DQPBRh8TU1NmR4CUkQ72+hnF+3sop1dtLONfnYFrV1Ki/3vfOc7uuKKKzR+/Ph0jwcYNJ7nqbKyMlCbbuQK2tlGP7toZxft7KKdbfSzK4jtUnrP/qZNm7Ry5Uo9++yz+u53v6u1a9eqra0t7nVXrVo1oAEC6eJ5noqLi+V5npxzmR4OkkA72+hnF+3sop1dtLONfnYFsV1Ki/0VK1bIOSfP8/TlL3/5mH8ZeXkpfQsAAAAAAJCilFbit99+e2B+2wEAAAAAQNCktNi/7bbb0j0OYNDFYjFt3bo1UDts5gra2UY/u2hnF+3sop1t9LMriO08STxFn4JwOKy2tjYVFxervb0908MBAAAAAARcMuvQlHbjz2W1tbVqaGhQfX19poeCJHmep6qqqkDtsJkraGcb/eyinV20s4t2ttHPriC2S2mxH41G1dXV9ZZHZ2dnusebcXV1daqurlZNTU2mh4IkeZ6noqKiQN2BcwXtbKOfXbSzi3Z20c42+tkVxHYpvWf/ySefjLtB37BhwzRp0iSdeOKJWrt2rfbt2zfQ8QEAAAAAgCSltNg///zz+71syJAh+vrXv65LLrlE//iP/5jywAAAAAAAQGoGbYO++vp6vfzyy/rIRz4yGDefcWzQZ1M4HKaXUbSzjX520c4u2tlFO9voZ5eFdlmxQd+qVat02WWXDdbNAynJ9jsv+kc72+hnF+3sop1dtLONfnYFrd2gLfZPOukkDR06dLBuHkia7/uaOnWqfJ8PobCGdrbRzy7a2UU7u2hnG/3sCmK7lN6zfyye5+naa6/VNddco2effTbdNw8MSCgUyvQQkCJL7TxJ1aW+RhR5ao04NTTHBuf9UoZY6oej0c4u2tlFO9voZ1fQ2qW02N+0aVP8G8vLU2lpqfLz89XZ2ambbrppQIMDAGtmjg1pcU2+JpeEVJgnHe6S1rdEdVd9p1Y3RjM9PAAAAOSIlF6j4Pu+PM/rc3R2durll1/Wj370I7397W/Xk08+me7xAkDWmjk2pDsvKtT0spBaD8W0uTWm1kMxTS/rPj9zbLB+WwwAAIDsNWi78Qcdu/HbVFRUpEgkkulhIAXZ3s6T9PP3Fml6WUgb98b6XF450tdzTVF96NFITv5HN9v7oX+0s4t2dtHONvrZZaFdVuzGD2Sjjo6OTA8BKcr2dtWlviaXhNTU3nehL0k7D8RUdVJI1aW5+Z/dbO+H/tHOLtrZRTvb6GdX0Nrl5k+dyEm+72vatGmB2mEzV1hoN6LIU2GedKgr/uVvdEqFed3XyzUW+iE+2tlFO7toZxv97Apiu5R34588ebIWL16ss846S8OHD4+7c6FzTpWVlQMaIABY0BpxOtwlDcmTDnb2vfyE/O7N+lojufgifgAAABxvKS32Z8+erd/97ncqLCxUV1eXdu3apa6uvk9neV7uPYMFIDc1NMe0viXa73v2y4Z2v2e/oTn+y/wBAACAdEppsf/1r39deXl5Wrhwoe677z7FYvzwCiC3OUl31Xfqzot8VY70tfNATG90dj+jXzbUV2vE6e41nTm5OR8AAACOv5R24z948KAeeeQRffjDHx6EIdnAbvw2+b7PL6eMstJu5tiQFtfka3JJSIV53S/dX7c7qrvXdGp1YzTTw8sYK/3QF+3sop1dtLONfnZZaJfMOjSlZ/YPHjyo5ubmlAYHZFJBQUHWf5wG4rPSbnVjVM80RlVd6mtEkafWiFNDcyznn9G30g990c4u2tlFO9voZ1fQ2qW01eDjjz+uc889N91jAQaV7/uqqqoK1A6bucJaOyfp5eaYVm2L6mUW+ub64e9oZxft7KKdbfSzK4jtUprJ5z73OQ0fPlzf+973NGTIkHSPCQAAAAAADEBKL+N/6KGHdODAAS1atEjz58/XX//6V7W1tfW5nnNOF1544YAHCQAAAAAAEpfSYn/OnDm9/3/o0KGaMWNG3Os5l+svXkW2iUZzd4M062hnG/3sop1dtLOLdrbRz66gtUtpN36wGz8AAAAA4PhKZh0anN0HgASEw+FMDwEpop1t9LOLdnbRzi7a2UY/u4LWjsU+cobv+5o0aVKgdtjMFbSzjX520c4u2tlFO9voZ1cQ2wVnJgAAAAAAQBKLfQAAAAAAAofFPnKGc06RSIRPiTCIdrbRzy7a2UU7u2hnG/3sCmK7nN2N//Of/7yuvPJKnXbaaXrjjTe0cuVK/fu//7u2bt2a0NezGz8AAAAA4HhiN/4EnHfeefr+97+vd7zjHbrkkks0cuRI/fa3v1UoFMr00DCIRo0alekhIEW0s41+dtHOLtrZRTvb6GdX0NrlZXoAmfKud73rqD9/7GMf0+bNm1VVVaWXXnopQ6PCYPJ9XxUVFWptbVUsFsv0cJAE2tlGP7toZxft7KKdbfSzK4jtUn5mPxQK6dOf/rT+/Oc/a//+/ers7Oy9bOrUqbr77rs1adKklAd27bXXasmSJVqzZk3veyfmzZt3zK8588wz9dhjj6m1tVUHDhzQ6tWrddVVVyX0/YYNGyZJ2rt3b8pjBgAAAAAgG6T0zH5RUZGWLVums88+Wy0tLWpra9OJJ57Ye/nmzZu1YMEC7d27V7fccktKA/vKV76iCRMmaPfu3WpqatKECROOef05c+Zo6dKlikQieuihh9Te3q4rr7xSDz/8sK6//np9+9vf7vdrfd/XnXfeqccee0w7duxIabwAAAAAAGSLlJ7Zv/nmm3XOOefopptuUllZmX7yk58cdXlbW5tWrlypiy++OOWBLVy4UBUVFSotLdWSJUuOed1QKKQf//jHisVimj17tq677jrdcMMNmjp1ql599VXdcccdGj9+fL9fv2TJEo0fP17z589PebzIfs45tbW1BWqHzVxBO9voZxft7KKdXbSzjX52BbFdSov9a665Rk888YS++c1vSlLcv5DXXnvtmAvst7J8+XJt27YtoevOnTtXlZWVevDBB7V27dre821tbbrjjjtUWFjY71sA6urqdOGFF+qCCy5QS0tLyuNF9nPOaePGjYG6A+cK2tlGP7toZxft7KKdbfSzK4jtUlrsjx8/Xs8+++wxr9Pe3t77PvjBNmfOHEnSsmXL+ly2dOlSSd2777/Z3Xffrcsuu0xz585VY2PjoI4R2aG8vDzTQ0CKaGcb/eyinV20s4t2ttHPrqC1S+k9++3t7SotLT3mdSZOnKjdu3enNKhk9WwEuGHDhj6X7dq1S+3t7X02C7z77rv1gQ98QJdffrkOHTqkk08+WVL3Bn1HbjbYo6CgQIWFhb1/DofDkrrf7+/73b8zcc7JOSfP8+R5Xu91e3ZzTPZ8z+2m83zPGJM9H4Q5+b6vMWPGqLm5WdFoNBBzevP5oM4pFAppzJgx2r17t7q6ugIxpyB26m/syfSzMqcgdop3/sh2sVgsEHMKYqd453se83raBWFOAx27lTlJ3QuOI9tZn1MQO6Wjn5U5BbFTvPO+76u8vFy7du066rrZNqdkpLTYf+aZZ3T55Zdr2LBh2r9/f5/Lx44dq0svvVSPPvpoygNLRs8rCOKNRep+Of+bX2VQW1srSXrqqaeOOj9nzhytXLmyz23cdNNNuvXWW/ucP+OMM3Tw4EFJUktLi7Zt26Zx48appKSk9zpNTU1qamrSxIkTVVxc3Ht+69at2rNnjyZPnqyioqLe8xs2bFB7e7umTJmiUCjUe37dunXq6OjQtGnTjhrDCy+8oIKCAlVVVfWei0ajWrt2rcLh8FG/6IhEIlq3bp1GjRqlioqKo/6ONm7cqPLy8qN+oxWkOfm+r1NPPVUtLS3asmVLIObUI0id4s2ptLRUp556qiRpx44dgZhTEDv1N6fhw4f39tu8eXMg5hTETv3NqaddLBYLzJyC2OnNczp48KAqKysl/f0HRutzCmKneHN65ZVX5Pu+pk2bdtRi0fKcgtipvzm9+OKLKiwsPKqf9TkFsVO8OfUs3MPhsCZOnJi1c9q+fbuS4ZI9zj33XNfV1eWeffZZd/bZZ7vbb7/ddXV1uSFDhri5c+e6hoYGd/jwYTdjxoykbzveceONNzrnnJs3b17cy5cuXeqcc27ixIlxL29sbHT79u0b0BgKCgpcOBzuPUaPHu2cc27YsGHO933n+77zPM9Jcp7n9Z7zfb/3NpI9f+S5dJ3vGWOy54Mwp7y8PHfmmWe6UCgUmDkFsVO8OfW0y8vLC8ycgtipv7En08/KnILYKd75UCjU2y4ocwpip3jnfd8/ql0Q5hTETvHG6Pu+mzFjxlHtrM8piJ3S0c/KnILYKd75vLw8N2PGjD7XzbY5hcNh55xz4XC49zr9HSk9s79q1SotXrxY3/ve9/Tkk0/2nm9vb5fU/Zue2tpaPffcc6ncfNJ6ntHvb4+A4uJitba2Duh7dHR0qKOjo8/5I1/W2OPIl3QM5PybbzeT54MwJ+ecmpube68ThDklOkbrc4pGo71vvzjyvOU5BbFTf2NPpp+VOQWxU39j72l35OWW5xTETvHO9zzmvbndYI+9v/N0SnxOnueppaUlbrt0jb2/83Qa+JyORz86Dc6cnHNqaWnp97aTvf3BnlMiUlrsS90fV7dixQp94hOf0Dve8Q6NHDlSbW1t+vOf/6y6ujqtW7cu5UElq+e9+pMmTerzC4aTTz5Z4XBY9fX1x208yE7OuYQ/4QHZhXa20c8u2tlFO7toZxv97Apiu9Tf7a/u9xR9+tOf1syZM3XaaafprLPO0uLFi4/rQl9S73vsL7rooj6XXXzxxUddB7nL8zyNHz/+qI0vYAPtbKOfXbSzi3Z20c42+tkVxHYpLfbnzp2b7nEMyPLly7Vp0yZ98IMf1NSpU3vPFxcX6+abb9bhw4d1//33p+V71dbWqqGhgVcKGOR5nkpKSgJ1B84VtLONfnbRzi7a2UU72+hnVxDbpfQy/t///vdqbGzUgw8+qP/6r//Syy+/nO5x6aMf/ahmzZolSZoyZYokaeHChZozZ46k7l3077nnHkndewQsXLhQS5cu1ZNPPqmHHnpI7e3tuvLKKzVhwgRdf/312rp1a1rGVVdXp7q6OoXDYbW1taXlNgEAAAAASKeUFvt33XWXrrnmGv37v/+7Pve5z+nFF1/UAw88oF/84hfauXNnWgY2a9YszZ8/v8+5nl8ASOpd7EvSihUrNGvWLN1222265pprlJ+fr5deekk33nijHn744bSMCQAAAAAAK95yy/54h+/77rLLLnMPPfSQO3DggItGo66jo8P97ne/c9dee60bMmRISrdr5UjmIw84sucoLy/P+Bg4aJeLB/3sHrSze9DO7kE72wf97B4W2iWzDvX+9n8GZOjQobrqqqv0oQ99SLNnz5YkvfHGG/rNb36jD3/4wwO9+azU8zL+4uLi3o8cBAAAAABgsCSzDh3Qbvw9Dhw4oHvvvVdz585VRUWF7rjjDhUUFOiDH/xgOm4eSAvP81RZWRmoTTdyBe1so59dtLOLdnbRzjb62RXEdim9Z78/F154of7lX/5F//zP/6z8/HxFo9F03jwwIJ7nqbi4WJ7nybkBv6AFxxHtbKOfXbSzi3Z20c42+tkVxHYDXuxPnTpVH/rQh/T+979fZWVl8jxP69at0wMPPKD/+q//SscYs0ptba0WLVok30/LiyIAAAAAAEi7lBb7Y8eO1bXXXqtrr71WVVVV8jxPu3bt0ve+9z098MADeuGFF9I8zOzBR+8BAAAAALJdSov9LVu2SJIikYgeeughPfDAA1q2bFlgXu6AYIrFYtq6datisVimh4Ik0c42+tlFO7toZxftbKOfXUFsl9Ju/H/4wx90//3365FHHtHBgwcHYVjZj934AQAAAADH06Dvxn/hhRfq/vvvz9mFPmzyPK/3bSewhXa20c8u2tlFO7toZxv97ApiO3aZQ87wPE9FRUWBugPnCtrZRj+7aGcX7eyinW30syuI7RJ6z/4999wj55xuvvlmNTc365577knoxp1zWrhw4YAGCAAAAAAAkpPQYn/+/Plyzukb3/iGmpubNX/+/IRuPIiLfT56DwAAAACQ7RLaoG/8+PGSpB07digajfb+ORHbtm1LeXDZjA36bAqHw/Qyina20c8u2tlFO7toZxv97LLQLpl1aEq78YPFPgAAAADg+Br03fhvueUWnXvuuce8zqxZs3TLLbekcvPAoPB9X1OnTuUtGAbRzjb62UU7u2hnF+1so59dQWyX0kxuvfVWzZkz55jXmT17tr70pS+lcvPAoAmFQpkeAlJEO9voZxft7KKdXbSzjX52Ba3doP3aoqCgQNFodLBuHgAAAAAA9CPlxb5z/b/VPz8/X+eee66am5tTvXkAAAAAAJCihDfo27RpU+//nzBhgvbt26d9+/b1uV4oFFJJSYmKior04x//WJ/85CfTNdaswgZ9NhUVFSkSiWR6GEgB7Wyjn120s4t2dtHONvrZZaFdMuvQvERv1Pf93mfznXPyPE+e5/W5XmdnpxoaGvTHP/5RX/7yl5Mcevarra3VokWLArVxQy7p6OjI9BCQItrZRj+7aGcX7eyinW30syuI7VyyRzQadbfcckvSXxekIxwOO+ecC4fDGR8LR2KH7/tuxowZzvf9jI+Fg3a5dNDP7kE7uwft7B60s33Qz+5hpV0y69CEn9k/0imnnBL3JfwAAAAAACDzUlrsb9u2Ld3jAAAAAAAAaZLSYr/HO9/5Tl144YUaPXq0CgsL+1zunNPChQsH8i0AAAAAAECSEt6N/0ihUEi/+MUv9N73vlee5/Vu2Nej58/OOeXlDej3CVmL3fht8n1fsVgs08NACmhnG/3sop1dtLOLdrbRzy4L7ZJZh6a0pfz111+vK6+8Uvfee6/OPPNMeZ6n7373u5o5c6ZuvPFG7du3T7/61a80ceLElCYADJaCgoJMDwEpop1t9LOLdnbRzi7a2UY/u4LWLqXF/rXXXquXX35ZH/vYx/T8889Lkvbt26f6+nrdeeedmj17tt797nfr4osvTutggYHwfV9VVVV8bKJBtLONfnbRzi7a2UU72+hnVxDbpTSTyspKrVixovfPzjnl5+f3/nndunX63//9X33yk58c8AABAAAAAEByUlrsd3R06I033uj984EDB1RaWnrUdbZu3apJkyYNbHQAcp4n6fRSX9PLQjq91Jf3ll8BAAAAIKXd87Zv365x48b1/vmVV17R7Nmzj7rOO9/5Tu3du3dgo8tCtbW1WrRoUaBe3pFLotFopoeAJMwcG9LimnxNPilfxRUhtY0bovW7O3VXfadWN9LSEu57dtHOLtrZRTvb6GdX0NqltBv/97//fV1xxRUaP368JOkzn/mM7rzzTv32t7/V448/rlmzZunqq6/WT3/6U3384x9P95izArvxA4Nr5tiQ7ryoUCOKPDW1x3SoSxqSJ5WHfbVGnG5YdpgFPwAAAHJKMuvQlJ7Z/+lPf6pQKKQxY8Zox44d+v73v685c+bo3e9+t971rndJkurr6/X5z38+lZsHBk04HOaXMwZ4khbX5GtEkaeNe7s//iRvSFgHD7Vr496YKkf6WnRWvp5pjCb/20pkBPc9u2hnF+3sop1t9LMraO1Sei36888/r9raWu3YsUOS1NXVpSuuuEI1NTX6wAc+oLPPPltnn312IF/GD7t839ekSZN4C4YB1aW+JpeE1NT+t8859XydWFYped3tdh6IqeqkkKpLaWkB9z27aGcX7eyinW30syuI7VJ6Zr8/f/nLX/SXv/wlnTcJIAeNKPJUmCcd6op/+Rud0slDu68HAAAAoK/g/NoCQGC0RpwO/+09+vGckC8d7uq+HgAAAIC+Enpm/5577knpxp1zWrhwYUpfC6Sbc06RSETOsUDMdg3NMa1viWp6Wehv79l3inZG1LOfaNlQX881RdXQHMvoOJEY7nt20c4u2tlFO9voZ1cQ2yW0G3+qH0HgnFNeXlrfKZA12I0fGFxH7sa/80BMb3R2P6NfNpTd+AEAAJCb0r4b/ymnnJKWgQGZNmrUKO3ZsyfTw0ACVjdGdcOyw1pck6/JJSGNPnmU3ti/R881RXX3mk4W+sZw37OLdnbRzi7a2UY/u4LWLqHF/rZt2wZ7HMCg831fFRUVam1tVSzGy78tWN0Y1TONUU0py9NZM07Wmude10s7u/i4PWO479lFO7toZxftbKOfXUFsF8zX2AMIDCfp5eaY8nZG9XJzjIU+AAAAkICUFvvnnntuwtddtWpVKt8ia9XW1mrRokWB+vxFAAAAAECwpLTYX7FiRcK7FAZtg766ujrV1dX1bowAO5xzamtrC9QOm7mCdrbRzy7a2UU7u2hnG/3sCmK7hHbjf7MvfelLcf8Shg0bphkzZmj27Nl67LHH9Oyzz+r2229PxzizDrvxAwAAAACOp2TXoS7dx5VXXuna29vd9OnT037b2XKEw2HnnHPhcDjjY+FI/CgvL8/4GDhol4sH/ewetLN70M7uQTvbB/3sHhbaJbMOHZQ3nj/yyCN64okn9LWvfW0wbh5Iie/7Ki8vZ78Fg2hnG/3sop1dtLOLdrbRz64gthu0maxfv14zZ84crJsHAAAAAAD9GLTF/vTp0wPz+YQAAAAAAFiS0lb548aNi39jeXkaM2aM5s+fr7lz5+o3v/nNQMYGpJVzTi0tLYHaYTNX0M42+tlFO7toZxftbKOfXUFsl9Ju/NFo9Jh/CZ7nadOmTbrgggu0ffv2gYwva7EbPwAAAADgeEpmHZrSM/v3339/3MV+LBZTa2ur1qxZo//+7//W4cOHU7l5YFB4nqdx48Zp+/btgfqNXS6gnW30s4t2dtHOLtrZRj+7gtgupcX+ggUL0j0OYNB5nqeSkhI1NjYG5g6cK2hnG/3sop1dtLOLdrbRz64gtgvO5woAAAAAAABJKT6zfyTP83TyyScrPz8/7uVBfc8+AAAAAADZKuXF/rXXXqsbbrhBVVVVCoVCca/jnOv3lwDA8RaLxdTU1MRHQhpEO9voZxft7KKdXbSzjX52BbFdSov966+/Xt/4xjfU2dmpJ598Uk1NTerq6kr32IC0a2pqyvQQkCLa2UY/u2hnF+3sop1t9LMriO1csseWLVvc1q1b3ZgxY5L+2qAc4XDYOedcOBzO+Fg4Ejs8z3OVlZXO87yMj4WDdrl00M/uQTu7B+3sHrSzfdDP7mGlXTLr0JQ26DvppJP0yCOPaMeOHal8uWm1tbVqaGhQfX19poeCJHmep+LiYnmel+mhIEm0s41+dtHOLtrZRTvb6GdXENultNj/61//qhEjRqR7LCbU1dWpurpaNTU1mR4KAAAAAABxpbTY/853vqMrrrhC48ePT/d4AAAAAADAAKW0Qd/999+v0tJS/elPf1JdXZ3Wrl2rtra2uNddtWrVgAYIpEssFtPWrVsDtcNmrqCdbfSzi3Z20c4u2tlGP7uC2C7lj94rLi7WsGHDdPvttx/7G+Sl/C2AtNuzZ0+mh4AU0c42+tlFO7toZxftbKOfXUFrl9JK/LbbbtPNN9+s3bt366GHHuKj92CC53maPHmy1q9fL+dcpoeDJNDONvrZRTu7aGcX7Wyjn11BbJfSYv8jH/mI/vrXv+qss87SwYMH0z0mYFB4nqeioiJ5nheYO3CuoJ1t9LOLdnbRzi7a2UY/u4LYLqUN+kaMGKHHHnuMhT4AAAAAAFkopcX+Sy+9pPLy8nSPBQAAAAAApEFKi/2vfvWres973qPp06enezzAoInFYtqwYUOgdtjMFbSzjX520c4u2tlFO9voZ1cQ26X0nv0RI0bo97//vf70pz/pgQceOOZH7z3wwAMDGiCQTu3t7ZkeAlJEO9voZxft7KKdXbSzjX52BbGdS/aIRqOuq6vLRaPR3qOrq+uoo+dcKrdv4QiHw84558LhcMbHwpHY4fu+mzp1qvN9P+Nj4aBdLh30s3vQzu5BO7sH7Wwf9LN7WGmXzDo0pWf2FyxYkMqXARkXCoUyPQSkiHa20c8u2tlFO7toZxv97Apau5QW+/fff3+6xwEAAAAAANIkpQ36AAAAAABA9vLU/Xr+pIwbNy7h627fvj3ZmzchHA6rra1NxcXFgdzIIaiKiooUiUQyPQykgHa20c8u2tlFO7toZxv97LLQLpl1aEov49+yZYuce+vfETjnlJ+fn8q3AAZFR0dHpoeAFNHONvrZRTu7aGcX7Wyjn11Ba5fye/bjLfaHDRumqVOn6pRTTtHKlSu1ZcuWgY4PSBvf9zVt2jS98MILgfr8zFxAO9voZxft7KKdXbSzjX52BbHdoOzGf/311+vf//3f9dGPfjSlQQEAAAAAgNQNygZ93/rWt9TQ0KBvfvObg3HzAAAAAADgGAZtN/5nn31Wc+fOHaybBwAAAAAA/UhpN/5EPPLII/rHf/xHFRcXD8bNZ0xtba0WLVok3/f1tre9jd34jfF9PzDvwck1tLONfnbRzi7a2UU72+hnl4V2yezGn9Zn9j3P09ixY/XFL35RV1xxhVavXp3Om88KdXV1qq6uVk1NTaaHghQUFBRkeghIEe1so59dtLOLdnbRzjb62RW0dikt9qPRqLq6uvocnZ2d2rJli2677Tbt27dP119/fbrHC6TM931VVVXJ9wft3SsYJLSzjX520c4u2tlFO9voZ1cQ26W0G/+TTz4Z96P3YrGYWltbtWbNGt17773avXv3gAcIAAAAAACSk9Ji//zzz0/3OAAAAAAAQJoE5zUKQAKi0Wimh4AU0c42+tlFO7toZxftbKOfXUFrl9Ru/DfffLNOPPFEfelLX1JXV1fc6+Tn5+vWW29VW1ubvvGNb6RrnFknmV0QAQAAAAAYqEHZjf+CCy7Q7bffrj179vS70Jekzs5OtbS06Ktf/armzJmT8KCB4yEcDmd6CEgR7Wyjn120s4t2dtHONvrZFbR2CS/2P/zhD6u1tVV33XXXW1737rvv1t69e7VgwYIBDQ5IJ9/3NWnSpEDtsJkraGcb/eyinV20s4t2ttHPriC2S3gmZ599tv7whz+oo6PjLa/b0dGhP/zhDzrnnHMGNDgAAAAAAJC8hBf7o0eP1muvvZbwDW/evFnl5eUpDQoAAAAAAKQu4cV+LBZTfn5+wjecn5+vWCyW0qCAweCcUyQSkXMJ70mJLEE72+hnF+3sop1dtLONfnYFsV3Cu/G/+uqr2rRpky699NKEbvjxxx/XP/zDP+htb3vbQMaXtdiNHwAAAABwPA3KbvyrVq3S3LlzVVFR8ZbXraio0Ny5c/Xkk08mevPAcTFq1KhMDwEpop1t9LOLdnbRzi7a2UY/u4LWLuHF/t133638/Hz9+te/PuZfwsiRI/WrX/1KeXl5+sEPfpCWQQLp4Pu+KioqArXDZq6gnW30s4t2dtHOLtrZRj+7gtguL9ErPv/88/rud7+rT3/601q3bp2WLFmiJ554Qo2NjZKkMWPG6IILLtDHP/5xnXTSSfr2t7+t559/ftAGDgAAAAAA4kt4sS9J119/vSKRiD73uc/pC1/4gr7whS8cdbnneYpGo/ra176mL37xi2kdKAAAAAAASExSi31J+sIXvqB77rlHCxYs0Nlnn62ysjJJ0s6dO/X000/rZz/7WVIf0QccL845tbW1BWqHzVxBO9voZxft7KKdXbSzjX52BbFdwrvx42jsxg8AAAAAOJ4GZTd+IAjKy8szPQSkiHa20c8u2tlFO7toZxv97ApaOxb7yBm+76u8vDxQO2zmCtrZRj+7aGcX7eyinW30syuI7YIzEwAAAAAAIInFPgAAAAAAgcNiHznDOaeWlpZA7bCZK2hnG/3sop1dtLOLdrbRz64gtmM3/hSxGz8AAAAA4HhiN34gDs/zNH78eHmel+mhIEm0s41+dtHOLtrZRTvb6GdXENux2EfO8DxPJSUlgboD5wra2UY/u2hnF+3sop1t9LMriO3yMj0AAMeXJ6m61NeIIk+tEaeG5hjv5QEAAAAChsU+kENmjg1pcU2+JpeEVJgnHe6S1rdEdVd9p1Y3RjM9PAAAAABpkrMv4//nf/5nLVu2THv27JFzThUVFZkeEgZZLBZTU1OTYrFYpoeSETPHhnTnRYWaXhZS66GYNrfG1Hoopull3ednjg1leoj9yvV21tHPLtrZRTu7aGcb/ewKYrucXeyfeOKJevLJJ/Uf//EfmR4KjqOmpqZMDyEjPEmLa/I1osjTxr0xHeyUYk462Clt3BvTiCJPi87KVza/QylX2wUF/eyinV20s4t2ttHPrqC1y9nF/s9//nN95Stf0YoVKzI9FBwnnuepsrIyUJtuJKq61NfkkpCa2uP/pnLngZiqTgqpujQ7/5OQy+2CgH520c4u2tlFO9voZ1cQ22XnT/aSrr32Wi1ZskRr1qxRJBKRc07z5s075teceeaZeuyxx9Ta2qoDBw5o9erVuuqqq47TiJHtPM9TcXFxoO7AiRpR5KkwTzrUFf/yNzqlwrzu62WjXG4XBPSzi3Z20c4u2tlGP7uC2C5rF/tf+cpXdN1116mioiKhl1PMmTNHTz/9tGbNmqWHH35YS5YsUVlZmR5++GF99rOfPQ4jBrJXa8TpcJc0pJ8tOU/I796srzXCvvwAAABAEGTtYn/hwoWqqKhQaWmplixZcszrhkIh/fjHP1YsFtPs2bN13XXX6YYbbtDUqVP16quv6o477tD48eOP08iB7NPQHNP6lqjKw/Hv8mVDfa3bHVVDc3A2JAEAAAByWdYu9pcvX65t27YldN25c+eqsrJSDz74oNauXdt7vq2tTXfccYcKCwvf8i0ACL5YLKatW7cGaofNRDlJd9V3qjXiVDnS19ACyfekoQVS5UhfrRGnu9d0Kluf18/ldkFAP7toZxft7KKdbfSzK4jt+nlRry1z5syRJC1btqzPZUuXLpUknXfeefryl7+c8vcoKChQYWFh75/D4bAkyfd9+X7370ycc3LOyfO8o97r0fMPJtnzPbebzvM9Y0z2fFDm1NraKs/zAjWnI88fa+x/ft3p3//QqUU1+XrbSF8nD5UORz09vyumujWd+vPrf1/qZ+OcWltb5ft+4DsFdU6J9rM0p0TPW59TT7sgzSmIneKdP7JdUOYUxE7xxrhnz57AzWmg5y3NKdF+luaU6Hnrc9qzZ0/WzykZgVjsT5o0SZK0YcOGPpft2rVL7e3tvdfpMWLECI0fP14TJ06UJFVVVWn48OHatm2bWltb+9zOTTfdpFtvvbXP+TPOOEMHDx6UJLW0tGjbtm0aN26cSkpKeq/T1NSkpqYmTZw4UcXFxb3nt27dqj179mjy5MkqKirqPb9hwwa1t7drypQpCoX+/tnn69atU0dHh6ZNm3bUGF544QUVFBSoqqqq91w0GtXatWsVDoePmnskEtG6des0atQoVVRU9J5va2vTxo0bVV5ervLy8t7zQZqT53k65ZRTtGbNGm3dujUQc+qRaKdDkr71mjTk5e3y3tirkRWT1XiwQK5EmlaSvXM66aSTdMopp2jz5s16/fXXA98paHMaNmxYb78tW7YEYk5B7BRvTlVVVZo8ebI2b94s51wg5hTETvHmdODAAb3nPe/R1q1be38YtT6nIHaKN6f169dr4sSJKiws7G1nfU5B7NTfnNauXaszzjhDvu/39rM+pyB2ijenWCymjo4ONTY2qrKyMmvntH37diXDZftx4403OuecmzdvXtzLly5d6pxzbuLEiXEvb2xsdPv27Tvq3Lx581w8/X2PgoICFw6He4/Ro0c755wbNmyY833f+b7vPM9zkpzneb3nfN/vvY1kzx95Ll3ne8aY7PkgzCkvL8+deeaZLhQKBWZOQewUb0497fLy8gIzpyB26m/syfSzMqcgdop3PhQK9bYLypyC2Cneed/3j2oXhDkFsVO8Mfq+72bMmHFUO+tzCmKndPSzMqcgdop3Pi8vz82YMaPPdbNtTuFw2DnnXDgc7r1Of0cgntlPxX333af77rsv4et3dHSoo6Ojz/lYLNbnfR1HvqRjIOf7e79IJs4HZU6xWKx3XEGZUyJjtD6nnvvZkZdbn1MQO/U39mT6WZlTEDsl08/6nILYqb85xfs5xfqcBmuMyZ4frDn5R7xtJt73tTinTJ4/3nM6Hv3oxJwSlbUb9CVj//79kqRhw4bFvby4uLj3OgAAAAAABF0gFvs979V/8/vyJenkk09WOByO+35+5JZYLKYNGzYM6LdjyAza2UY/u2hnF+3sop1t9LMriO0CsdhfuXKlJOmiiy7qc9nFF1981HWQ29rb2zM9BKSIdrbRzy7a2UU7u2hnG/3sClq7QCz2ly9frk2bNumDH/ygpk6d2nu+uLhYN998sw4fPqz7778/Ld+rtrZWDQ0Nqq+vT8vt4fjxfV9Tp04d0MdXIDNoZxv97KKdXbSzi3a20c+uILbL2g36PvrRj2rWrFmSpClTpkiSFi5cqDlz5kiSnnrqKd1zzz2Suj/6YeHChVq6dKmefPJJPfTQQ2pvb9eVV16pCRMm6Prrr9fWrVvTMq66ujrV1dUpHA6rra0tLbeJ4+fIj62ALbSzjX520c4u2tlFO9voZ1fQ2mXtYn/WrFmaP39+n3M9vwCQ1LvYl6QVK1Zo1qxZuu2223TNNdcoPz9fL730km688UY9/PDDx2vYAAAAAABkXNYu9hcsWKAFCxYk9TVr1qzRpZdeOkgjAgAAAADABk9S3w/zw1vqeRl/cXFx4DZyCLKioiJFIpFMDwMpoJ1t9LOLdnbRzi7a2UY/uyy0S2YdGpzdB4AEdHR0ZHoISBHtbKOfXbSzi3Z20c42+tkVtHYs9pPEbvx2+b6vadOmBWqHzVxBO9voZxft7KKdXbSzjX52BbFdcGZynNTV1am6ulo1NTWZHgoAAAAAAHGx2AcAAAAAIGBY7AMAAAAAEDDsxp8iduO3yfd9xWKxTA8DKaCdbfSzi3Z20c4u2tlGP7sstGM3fqAfBQUFmR4CUkQ72+hnF+3sop1dtLONfnYFrR2LfeQM3/dVVVUVqB02cwXtbKOfXbSzi3Z20c42+tkVxHbBmclxwkfvAQAAAACyHYv9JPHRewAAAACAbMdiHzklGo1meghIEe1so59dtLOLdnbRzjb62RW0duzGnyJ24wcAAAAAHE/sxg/0IxwOZ3oISBHtbKOfXbSzi3Z20c42+tkVtHYs9pEzfN/XpEmTArXDZq6gnW30s4t2dtHOLtrZRj+7gtguODMBAAAAAACSWOwDAAAAABA4LPaTVFtbq4aGBtXX12d6KEiSc06RSETOsSelNbSzjX520c4u2tlFO9voZ1cQ27Ebf4rYjR8AAAAAcDyxGz/Qj1GjRmV6CEgR7Wyjn120s4t2dtHONvrZFbR2LPaRM3zfV0VFRaB22MwVtLONfnbRzi7a2UU72+hnVxDbBWcmAAAAAABAEot9AAAAAAACh8U+coZzTm1tbYHaYTNX0M42+tlFO7toZxftbKOfXUFsx278KWI3fgAAAADA8cRu/EA/ysvLMz0EpIh2ttHPLtrZRTu7aGcb/ewKWjsW+8gZvu+rvLw8UDts5gra2UY/u2hnF+3sop1t9LMriO2CM5PjpLa2Vg0NDaqvr8/0UAAAAAAAiIvFfpLq6upUXV2tmpqaTA8FAAAAAIC4WOwjZzjn1NLSEqgdNnMF7Wyjn120s4t2dtHONvrZFcR27MafInbjBwAAAAAcT+zGD8TheZ7Gjx8vz/MyPRQkiXa20c8u2tlFO7toZxv97ApiOxb7yBme56mkpCRQd+BcQTvb6GcX7eyinV20s41+dgWxHYt9AAAAAAACJi/TAwAs8yRVl/oaUeSpNeLU0BxjEwwAAAAAGcdiHzkjFoupqalJsVgsLbc3c2xIi2vyNbkkpMI86XCXtL4lqrvqO7W6MZqW74Fu6W6H44t+dtHOLtrZRTvb6GdXENuxG3+K2I0/t80cG9KdFxVqRJGnpvaYDnVJQ/Kk8rCv1ojTDcsOs+AHAAAAkFbsxg/E4XmeKisrB7zphidpcU2+RhR52rg3poOdUsxJBzuljXtjGlHkadFZ+QrO1h6Zl652yAz62UU7u2hnF+1so59dQWzHYh85w/M8FRcXD/gOXF3qa3JJSE3t8V/is/NATFUnhVRdyt0rXdLVDplBP7toZxft7KKdbfSzK4jtWI0kqba2Vg0NDaqvr8/0UJAhI4o8FeZJh7riX/5Gp1SY1309AAAAAMgEFvtJqqurU3V1tWpqajI9FGRIa8Tp8N/eox/PCfndm/W1RtgOAwAAAEBmsNhHzojFYtq6deuAd9hsaI5pfUtU5eH4d5+yob7W7Y6qoTk4O3lmWrraITPoZxft7KKdXbSzjX52BbEdi33klD179gz4Npyku+o71Rpxqhzpa2iB5HvS0AKpcmT3bvx3r+nkYy7SLB3tkDn0s4t2dtHOLtrZRj+7gtaOxT5yhud5qqqqSsumG6sbo7ph2WE9vzOq4UW+Thnha3iRr+eaonzs3iBIZzscf/Szi3Z20c4u2tlGP7uC2K6fdx0DweN5noqKiuR5npwb+PPuqxujeqYxqupSXyOKPLVGnBqaYzyjPwjS3Q7HF/3sop1dtLOLdrbRz64gtmOxDwyAk/Qy780HAAAAkGV4GT8AAAAAAAHjSbzqOBXhcFhtbW0qLi5We3t7poeDBIXDYXoZRTvb6GcX7eyinV20s41+dllol8w6lGf2kVOy/c6L/tHONvrZRTu7aGcX7Wyjn11Ba8diHznD931NnTpVvs8/e2toZxv97KKdXbSzi3a20c+uILYLzkyABIRCoUwPASminW30s4t2dtHOLtrZRj+7gtaOxT4AAAAAAAHDYh8AAAAAgIBhN/4UsRu/TUVFRYpEIpkeBlJAO9voZxft7KKdXbSzjX52WWjHbvyDqLa2Vg0NDaqvr8/0UJCCjo6OTA8BKaKdbfSzi3Z20c4u2tlGP7uC1o7FfpLq6upUXV2tmpqaTA8FSfJ9X9OmTQvUDpu5gna20c8u2tlFO7toZxv97Apiu+DMBAAAAAAASGKxDwAAAABA4LDYBwAAAAAgYNiNP0Xsxm+T7/uKxWKZHgZSQDvb6GcX7eyinV20s41+dllox278QD8KCgoyPQSkiHa20c8u2tlFO7toZxv97ApaOxb7yBm+76uqqipQO2zmCtrZRj+7aGcX7eyinW30syuI7YIzEwAAAAAAIInFPgAAAAAAgcNiHzklGo1meghIEe1so59dtLOLdnbRzjb62RW0duzGnyJ24wcAAAAAHE/sxg/0IxwOZ3oISBHtbKOfXbSzi3Z20c42+tkVtHYs9pEzfN/XpEmTArXDZq6gnW30s4t2dtHOLtrZRj+7gtguODMBAAAAAACSWOwDAAAAABA4LPaRM5xzikQico49Ka2hnW30s4t2dtHOLtrZRj+7gtiO3fhTxG78AAAAAIDjid34gX6MGjUq00NAimhnG/3sop1dtLOLdrbRz66gtWOxj5zh+74qKioCtcNmrqCdbfSzi3Z20c4u2tlGP7uC2C44MwEAAAAAAJJY7AMAAAAAEDgs9pNUW1urhoYG1dfXZ3ooSJJzTm1tbYHaYTNX0M42+tlFO7toZxftbKOfXUFsx278KWI3fgAAAADA8cRu/EA/ysvLMz0EpIh2ttHPLtrZRTu7aGcb/ewKWjsW+8gZvu+rvLw8UDts5gra2UY/u2hnF+3sop1t9LMriO2CMxMAAAAAACCJxT4AAAAAAIHDYh85wzmnlpaWQO2wmStoZxv97KKdXbSzi3a20c+uILZjN/4UsRs/AAAAAOB4Yjd+IA7P8zR+/Hh5npfpoSBJtLONfnbRzi7a2UU72+hnVxDbsdhHzvA8TyUlJYG6A+cK2tlGP7toZxft7KKdbfSzK4jtWOwDAAAAABAwLPYBAAAAAAgYFvvIGbFYTE1NTYrFYpkeCpJEO9voZxft7KKdXbSzjX52BbEdu/GniN34AQAAAADHE7vxA3F4nqfKyspAbbqRK2hnG/3sop1dtLOLdrbRz64gtmOxj5zheZ6Ki4sDdQfOFbSzjX520c4u2tlFO9voZ1cQ27HYBwAAAAAgYFjsAwAAAAAQMCz2kTNisZi2bt0aqB02cwXtbKOfXbSzi3Z20c42+tkVxHbsxp8iduMHAAAAABxP7MYPxOF5nqqqqgK16UauoJ1t9LOLdnbRzi7a2UY/u4LYjsU+cobneSoqKgrUHThX0M42+tlFO7toZxftbKOfXUFsx2IfAAAAAICAYbEPAAAAAEDAsEFfitigz6ZwOEwvo2hnG/3sop1dtLOLdrbRzy4L7digD+hHtt950T/a2UY/u2hnF+3sop1t9LMraO1Y7CNn+L6vqVOnyvf5Z28N7Wyjn120s4t2dtHONvrZFcR2wZkJkIBQKJTpISBFtLONfnbRzi7a2UU72+hnV9Da5fRi/9/+7d+0ZcsWHTp0SKtWrdIZZ5yR6SEBAAAAADBgObvY/8AHPqBvfOMbuuWWW/T2t79dGzdu1NKlSxUOhzM9NAAAAAAABiRnd+Ovr6/X008/rc985jOSul+ysXPnTn3xi1/UD3/4w7f8enbjt6moqEiRSCTTw0AKaGcb/eyinV20s4t2ttHPLgvtArEb/7XXXqslS5ZozZo1ikQics5p3rx5x/yaM888U4899phaW1t14MABrV69WldddVWf6+Xn52v69On6wx/+0HsuGo1qxYoVmjlzZtrnguzR0dGR6SEgRbSzjX520c4u2tlFO9voZ1fQ2mXtYv8rX/mKrrvuOlVUVKipqektrz9nzhw9/fTTmjVrlh5++GEtWbJEZWVlevjhh/XZz372qOuWlJQoLy9Pu3btOup8c3OzysrK0jqPTPIknV7q69zxIZ1e6svL9IASMJhj9n1f06ZNC9QOm7mCdrbRzy7a2UU7u2hnG/3sCmK7vEwPoD8LFy7Uhg0btG3bNt144436+te/3u91Q6GQfvzjHysWi2n27Nlau3atJOn2229XfX297rjjDv3617/Wtm3bjtfwM27m2JAW1+RrcklIhXnS4S5pfUtUd9V3anVjNNPDi8vimAEAAAAgG2Xtry2WL1+e8OJ87ty5qqys1IMPPti70JektrY23XHHHSosLDzqLQAtLS3q6urSySeffNTtlJaWaufOnemZQAbNHBvSnRcVanpZSK2HYtrcGlProZiml3Wfnzk2+z5SwuKYAQAAACBbZe1iPxlz5syRJC1btqzPZUuXLpUknXfeeb3nOjs79fzzz+uCCy7oPRcKhTRnzhytXr16cAc7yDxJi2vyNaLI08a9MR3slGJOOtgpbdwb04giT4vOys+ql/RbHDMAAAAAZLOsfRl/MiZNmiRJ2rBhQ5/Ldu3apfb29t7r9PjOd76je+65R3/5y1/03HPP6YYbblBXV5cefPDBuN+joKBAhYWFvX/u+Yg+3/d739fhnJNzTp7nyfP+vjSNxWKSlPT5N79fJJHzp5f6mnxSvpoOxP5+Be/v19950KnqpJCqS32ta/n7VXrG/ubbPx5zqj5yzD1jdbHese88KFWV5mtKWZde3NnV7xgTOf/iiy/2nstkp7c6n8ycjjwf1DlJ3e2OZH1OQezU39ilxPtZmVMQO8U775zrbef7fiDmFMRO8c7HYrGj2gVhTgMdu6U5vfDCC30usz6ngZ63NKdE+1maU6Lnrc/phRdeUCwWy+o5JSMQi/1hw4ZJkvbv3x/38ra2tt7r9PjFL36hk046SXfccYdOPvlkPfvss7r44ov7/fiCm266Sbfeemuf82eccYYOHjwoqfvtAdu2bdO4ceNUUlLSe52mpiY1NTVp4sSJKi4u7j2/detW7dmzR5MnT1ZRUVHv+Q0bNqi9vV1TpkxRKPT3l6+vW7dOHR0dmjZt2lFjeOGFF1RQUKCqqipNLwtp2IQCHdjfJW15UXlDwjqxrLL3uq4zosI3XtWE8hIVjB171N/Rxo0bVV5ervLy8t7zx2NOo06IatiEM3Sg3WnY3z4Icv+WtfLzChQeO1meJw0Le3r7tEN68XfPKRwOH/XLm0gk0n07o0apoqLimHMqLCzUjh07Mt6pRzQa1dq1awc0p+PVKdNzKiws1OHDhwM1px65MKeefkGaU4+gz2nYsGE6fPhwoOYUxE7x5jRjxgx1dXUFak5B7BRvTr7v621ve1ug5hTETv3Nqbi4WP/wD/8QqDkFsVO8Ob366qvKz8/P6jlt375difIkuYSvnSE9G/TNnz9f9913X5/Lly5dqosuukiVlZXatGlTn8sbGxs1dOhQDR8+POUxxHtmf8eOHRo+fHjvLwiy4TdTp5f6+tkVQ9R6KKaDHX9/drzH0AKn4YWePvybQ1nzzP7ppb7u/+cTu8fc2fON/z72oQXS8CJf8//70ICe2e/ZYfP5559XNBrNmt8gBvG3oumeUygU0rRp0/TCCy/0/uBqfU5B7NTf2JPpZ2VOQewU73woFNL06dN7n+kIwpyC2Cneed/3NWPGjN52QZjTQMduZU6SNG3aNL344ou917E+pyB2Skc/K3MKYqd4533f1xlnnNH7yoxsndOJJ56otrY2FRcX9/tEdY9APLPf84z+m5+971FcXKzW1tYBfY+Ojo64n7t45A8/PY4MP5Dzb77dRM6/tDOm9bs7Nb0spI17e77B369fdqKv55qiamiO9ftbnni3P5hzamg+csxvutzF/jbmTr208+/PTqTyd9Pzvz3jymSnwTof1Dn13M+OvNz6nILYqb+xJ9PPypyC2CmZftbnFMRO/c0p3s8p1uc0WGNM9vxgzannB/t47dI19v7O02ngczoe/ejEnBKV+hsAskjPe/Xf/L58STr55JMVDofjvp8/iJyku+o71RpxqhzZ/ay470lDC6TKkb5aI053r+nMqpdzWBwzAAAAAGSzQCz2V65cKUm66KKL+lx28cUXH3WdXLC6Maoblh3W8zujGl7k65QRvoYXdT+jf8Oyw1n5mfXHa8zRaPbNHYmhnW30s4t2dtHOLtrZRj+7gtjOZftx4403OuecmzdvXtzLQ6GQ27hxozt06JCbOnVq7/ni4mL3yiuvuEgk4ioqKtIyltraWtfQ0ODWr1/vnHMuHA5n/O+nv8OT3Omlvjt3fMidXuo7LwvGFMQxc3BwcHBwcHBwcHBwHI8jHA4nvA7N2g36PvrRj2rWrFmSpClTpujtb3+7nnrqKW3cuFGS9NRTT+mee+7pvf6cOXO0dOlSRSIRPfTQQ2pvb9eVV16pCRMm6Prrr9e3v/3ttI4vHA4nvDECskc4HKaXUbSzjX520c4u2tlFO9voZ5eFdsmuQzP+24l4x7333uuO5d577+3zNWeddZZ7/PHH3b59+9zBgwfdM888466++uqM/0aFIzsO3/fdjBkznO/7GR8LB+1y6aCf3YN2dg/a2T1oZ/ugn93DSrtk1qFZuxv/ggULtGDBgqS+Zs2aNbr00ksHaUQAAAAAANgQiA36AAAAAADA37HYR85wzikSicT9/EpkN9rZRj+7aGcX7eyinW30syuI7bJ2g75sxwZ9AAAAAIDjKZl1KM/sJ6m2tlYNDQ2qr6/P9FCQglGjRmV6CEgR7Wyjn120s4t2dtHONvrZFbR2LPaTVFdXp+rqatXU1GR6KEiS7/uqqKiQ7/PP3hra2UY/u2hnF+3sop1t9LMriO2CMxMAAAAAACCJxT4AAAAAAIHDYh85wzmntra2QO2wmStoZxv97KKdXbSzi3a20c+uILZjN/4UsRs/AAAAAOB4Yjd+oB/l5eWZHgJSRDvb6GcX7eyinV20s41+dgWtHYv9JPHRe3b5vq/y8vJA7bCZK2hnG/3sop1dtLOLdrbRz64gtgvOTI4TPnoPAAAAAJDtWOwDAAAAABAwLPaRM5xzamlpCdQOm7mCdrbRzy7a2UU7u2hnG/3sCmI7duNPEbvxAwAAAACOJ3bjB+LwPE/jx4+X53mZHgqSRDvb6GcX7eyinV20s41+dgWxHYt95AzP81RSUhKoO3CuoJ1t9LOLdnbRzi7a2UY/u4LYjsU+AAAAAAABk5fpAVhTW1urRYsW9X7+YjgczvCIkCjf93XiiScqHA4rFotlejhIAu1so59dtLOLdnbRzjb62WWlXTLrTzboS9Ho0aO1Y8eOTA8DAAAAAJBjxowZo9dff/2Y12GxPwCjR49mJ35DwuGwduzYoTFjxtDNGNrZRj+7aGcX7eyinW30s8tSu3A4/JYLfYmX8Q9IIn/ByD7t7e1ZfwdGfLSzjX520c4u2tlFO9voZ5eFdomOjw36AAAAAAAIGBb7AAAAAAAEDIt95IzDhw/r1ltv1eHDhzM9FCSJdrbRzy7a2UU7u2hnG/3sCmI7NugDAAAAACBgeGYfAAAAAICAYbEPAAAAAEDAsNgHAAAAACBgWOwDAAAAABAwLPaR9a699lotWbJEa9asUSQSkXNO8+bN63O9vLw8vfe979XPfvYzrVu3Tu3t7Wpra9MzzzyjT3ziE/L95P65b968Wc65uMcTTzyRrukFWqLtJOlLX/pSv3/fzjlVVFQk9b0nTZqkX/7yl9q9e7feeOMNvfDCC/rEJz6RjmnlhGTaHatbzzF27NiEvi/3u4EbPXq0PvWpT2np0qXaunWrDh8+rKamJv36179WTU1N3K8Jh8P61re+pS1btigSiWjz5s36f//v/+nEE09M+vtfdNFFWrFihdra2rR//3798Y9/1Ny5cwc6rZyQTDse87JLsvc7HvOyR7LteMzLLoWFhfrWt76llStXaseOHTp06JCampr01FNPaf78+crLy+vzNbn0mNd39kCW+cpXvqIJEyZo9+7dampq0oQJE+Jeb+LEiXrkkUfU3t6u5cuX63/+5380bNgwXX755frBD36gSy+9VP/0T/+U1Pfet2+fvvvd7/Y5v2XLluQnkoMSbXekn/3sZ3H/fvft25fw9508ebL+9Kc/aciQIXr44Yf1+uuv67LLLtMPfvADVVVV6d/+7d8Sn0SOSqbdrbfeGvd8ZWWl/uVf/kUNDQ1qbGxM+HtzvxuYf/3Xf9XnP/95bdy4UcuWLdPu3bs1adIkvec979F73vMeffCDH9TDDz/ce/0TTjhBK1eu1PTp07V06VL94he/0PTp0/W5z31O5513nmbPnp3wxxBde+21+vnPf67m5mb97Gc/kyRdc801+v3vf6+rr75ajzzyyGBMOTCSacdjXnZJ9n7Xg8e8zEu2HY952WXo0KH65Cc/qfr6ej322GPavXu3RowYoXe9612699579f73v1/vete75Fz3B9Dl4mOe4+DI5uOCCy5w48ePd5LcjTfe6Jxzbt68eX2uN3r0aPfJT37SnXDCCUedP+GEE1x9fb1zzrn3ve99CX/fzZs3u82bN2d8/paPRNtJcl/60pecc86dd955A/6+K1ascM45d8kll/Sey8/PdytXrnTOOffOd74z43832X4k066/4z//8z+dc8595jOfSfhruN8N/Pjnf/5nN3v27D7nZ82a5Q4fPuz27NnjCgoKes/feuutzjnnvva1rx11/a997WvOOec+//nPJ/R9hw8f7vbu3euam5vdmDFjes+PGTPGNTc3u+bmZjd06NCM//1k85FMOx7zsutI9n7HY172HMm26+/gMS8zh+d5Lj8/v8/5UCjk/vjHPzrnnLv00kt7z+fgY17GB8DBkfCR6qLj/e9/v3POue9///sJfw3/AT6+7dL1g8+kSZOcc84tX768z2WzZ892zjl3zz33ZPzvw9KRyv2usLDQ7dmzx0UiEVdSUpLw13G/G9zjd7/7nXPOube//e295xobG11bW1vcRWNbW5vbuHFjQrf9sY99zDnn3C233NLnsv/4j/9wzjn3oQ99KON/B1aPeO36O3jMy64jXjse82wcid7veMzLzuNf//VfnXPO/du//VvvuVx7zONl/MgJnZ2dkqSurq6kvq6wsFDz5s3T6NGj1dbWpjVr1qi+vn4whoi/mT17tt7xjncoFotpw4YN+sMf/qCDBw8m/PVz5syRJC1btqzPZU899ZQOHDig8847L13DRT/e+973auTIkfrVr36llpaWpL6W+93gefN/CydNmqQxY8bod7/7nd54442jrvvGG2/o6aef1iWXXKKxY8e+5ctSj3XfW7p0qW677Tadd955euCBB9Iwk9yTzOMYj3nZ5Vg9eMzLbonel3jMyz6e5+mSSy6RJL388suScvMxj8U+csJHPvIRSfHvkMdSXl7e+x6cHvX19frABz6g1157LV3DwxFuv/32o/7c2tqqT33qUwn/x3LSpEmSpA0bNvS5LBaLafPmzaqqqlIoFFI0Gh34gBHXRz/6UUnST37yk6S/lvvd4Bg3bpwuvPBCvf7663rppZckHfv+0nP+kksu0aRJk97yB59j3VbPuZ7rIDnx2h0Lj3nZ463a8ZiXvZK53/GYl3n5+fm6+eab5XmeRo0apQsuuECTJ0/WT3/6U/3xj3+UlJuPeezGj8D72Mc+pksvvVTLly/Xb3/724S/7t5779XcuXNVWlqqE044QdOmTdP999+vmpoaLV++XEOHDh3EUeeetWvXasGCBTrllFNUVFSkCRMmaPHixXLO6Wc/+5kuv/zyhG5n2LBhkqT9+/fHvbytrU2hUEjhcDhtY8fRJkyYoPPPP19bt27V73//+6S+lvvd4MjLy9MDDzygoqIi3XjjjYrFYpISu78ceb1jOdZtJXM7OFp/7frDY172OFY7HvOyWzL3Ox7zskNBQYFuvfVWfelLX9LixYt12mmn6Zvf/KY+/vGP914nVx/zMv5eAg6ORI9k3zt82WWXucOHD7vNmze7srKytIzhvvvuS3oDFo7U91uYO3eui0ajbu3atQld/4c//KFzzrkLLrgg7uVPPfWUc8654cOHZ/zvxMqRbLvbb7/dOefcl770pbSNgftd6ofnee7nP/+5c865H/7wh0dd9oEPfMA559yXv/zluF/7la98xTnn3Hve8563/D6vvvqqc865UCjU57K8vDznnHMvvPBCxv8+LB3Hahfv4DEve45k2/UcPOZl/ki2HY952XV4nufGjBnjPvGJT7i9e/e6VatWuXA47KTcfMzjmX0E1rve9S79+te/1q5duzR37lzt3LkzLbf7wx/+UJJ0zjnnpOX2cGx//OMftWnTJp1xxhkJPTPR8xvW/n6bWlxcrFgspvb29rSOE908z9P8+fMVjUb105/+NG23y/0uNZ7n6ac//amuvfZaPfDAA30+dzuR+8uR1zuWY91WMreDbm/V7s14zMseybY7Eo95mZVsOx7zso9zTjt27NCSJUv08Y9/XLNmzdIXvvAFSbn5mMdiH4F06aWX6v/7//4/tbS06Pzzz9fmzZvTdts9G6+ceOKJabtNHFvP3/kJJ5zwltc91vukfN/XKaecos2bN/PexUFyySWXaNy4cfr973+v7du3p+12ud8lz/M83XvvvZo/f74efPBBzZ8/v/dzhnu81fsK3+r9jYneVjK3g8TaHYnHvOyRbLt4eMzLjFTa8ZiX3Xr2LenZTC8XH/NY7CNwLr30Uj3yyCPau3evzj//fG3atCmtt/+Od7xDkrRly5a03i7iO+GEE1RdXa0DBw4ktMPtypUrJUkXXXRRn8tmzZqloUOH9l4H6TeQTYqOhftdcnp+aJ03b54eeughfehDH4r7ntMNGzZox44dOuecc/osLE444QSdc845eu21195yoyLp2Pe9iy+++KjroH+JtuvBY172SLZdPDzmZUaq7XjMy26jR4+W9PdPVcjVx7yMv5eAgyPR463eO3zJJZe4Q4cOuddff92deuqpb3l7eXl57rTTTnP/8A//cNT50047zQ0ZMqTP9U877TT3+uuvO+ecO/fcczP+92HpOFa7oUOHukmTJvU5X1RU5P7rv/6r388JPu2009xpp53W5/yKFSucc85dcsklvefy8/PdypUrnXPOzZw5M+N/H5aORN+zX1JS4g4fPux27drl8vPz+70e97vBPTzPc/fee69zzrlf/vKXcd9PeORx6623Ouec+9rXvnbU+a997WvOOec+//nPH3V+yJAh7rTTTnPjxo076vzw4cNda2ura25udmPGjOk9P2bMGNfc3Oyam5vd0KFDM/73k81Hsu14zMueI5l2POZl15Hs/a7n4DEvO47JkyfH/XscMmSIe/zxx51zzt10002953PtMY+P3kPW++hHP6pZs2ZJkqZMmSJJWrhwYe9Lcp566indc889Ou200/Too4+qqKhIK1as0Ac+8IE+t7Vlyxbdd999vX8eM2aMXnnlFW3ZskWnnHJK7/n3v//9+uxnP6snn3xSW7du1cGDB3Xqqafq0ksvVUFBge644w6tWrVqEGcdDIm2GzVqlF555RWtWbNG69ev186dO3XyySfrwgsv1Lhx4/Tiiy/qc5/7XJ/bf+WVVyR1/0b+SLW1tXr66af1m9/8Rr/85S/V1NSkyy67TKeffrq+//3va/Xq1YM462BItN2RPvzhD6ugoEAPPPBA72/R4+F+N7j+4z/+Q/Pnz1d7e7v++te/6otf/GKf6/zmN7/R2rVrJUn/7//9P11xxRX6/Oc/r+nTp+u5557TjBkzdPHFF6u+vl7f/e53j/rampoarVixQitWrND555/fe37fvn1avHixfv7zn+u5557TL3/5S0nSNddco1GjRumaa67RgQMHBm/iAZBMOx7zsksy7XjMyy7J/jezB4952eHqq6/WZz/7WT311FPasmWL2traNGbMGL3rXe9SSUmJnnzySX3nO9/pvX4uPuZl/DcOHBzHOnp+29qfe++910ly55133jGv55xzTzzxxFG3XVFR4ZxzbvPmzUednz17tnvooYfcq6++6vbt2+c6Ojrc66+/7h599FH3j//4jxn/O7FyJNouHA6773//++7Pf/6z27Vrl+vo6HD79+93zzzzjLvhhhtcUVFR3NvvEe+yU0891T388MOupaXFHTp0yK1du/b/b+/eg6Iq3ziAf7mspCB4QTEF6WJpId4VdfQHYaXmNTVLs3Ahxhp1Gm8zpeZCeYlMYWgiKwIyLS0yAVFJEUUIzRzvo+QFROUiglxdFpTn94ftxrJnuaWh9P3MPDPrOe95z/ues7v47DnnfeWdd95p9mPysERDz13NOHPmjIiI9OrVq866+blr3nMnYnqXhr29vaxfv14uX74sOp1OMjMzZe3atYpXJfTftbW/T/UxevRoOXDggJSWlkpJSYkkJSWZHSmc0fRzx795D1Y05tzxb96DFU35zgT4N+9BiYEDB8qXX34pp06dksLCQqmsrJT8/HxJTEwUf39/xTs1/kt/8yz+ekFERERERERELQQH6CMiIiIiIiJqYZjsExEREREREbUwTPaJiIiIiIiIWhgm+0REREREREQtDJN9IiIiIiIiohaGyT4RERERERFRC8Nkn4iIiIiIiKiFYbJPRERERERE1MIw2SciInqAaDQaiAg8PT2buynIyMhARkZGczfjP01EkJSU1Gz7j4yMhIjA1dW12dpARERNw2SfiIgeSK6urhARiAh2796tWMbDwwMigsjISKPl+gSlrvDx8TGpz9LSErNnz8avv/6K69evQ6fTIScnB7GxsZgyZco/6s/IkSMN+542bdo/quth4unpCRGBRqP5V/YjIjhy5IjZcmPGjDGUa84k+p9gAk5ERA1h3dwNICIiqs/o0aPx3HPPNTo5Cw8Px9WrVxXXHT9+3OjfnTp1QkxMDIYNG4bs7GzExMTg+vXrcHZ2xrhx4zBhwgTExsZixowZuHXrVqP74OfnBwCorq6Gr68voqOjG10H1a+qqgqDBg2Cu7s7Tp06ZbLez88PVVVVUKlUzdC6xuvVq1eT3m9ERERM9omI6IGWkZGB7t27IygoCEOGDGnUtuHh4Th8+HC95aytrbF9+3YMGzYM4eHhmD9/PioqKgzrHRwcsGnTJkycOBGRkZF49dVXG9WOtm3bYtq0aThx4gTy8vLw4osvwtnZ2ewPEdR0CQkJGDt2LHx9fbFgwQKjdR07dsSECROwc+dOTJo0qZla2Djp6enN3QQiInpI8TZ+IiJ6oKWnp+O7777D4MGDMX369PuyDx8fHwwfPhzJycnw9/c3SvQBoLi4GK+88grOnz+P6dOn47nnnmtU/TNmzICtrS02btyIjRs3wsrKCrNnz653O19fX5w8eRJarRZXr17F+vXrYWdnZ1LOy8sLO3fuxLVr11BRUYHc3FxDX2obPnw4duzYgYKCAmi1Wpw9exYBAQFo3bp1g/pS1y3ktccb0Gg02L9/PwAgICDA6DGKmturVCosWLAAR48eRVlZGUpKSpCcnIwJEyY0qE01Xb16FXv27MHrr79ucvV+1qxZsLGxQUREhOK2Tz31FIKCgnD06FHcuHEDWq0W6enpWLNmDWxtbRW3cXd3R3x8PEpKSlBUVIT4+Hi4ubkpHicfHx/DIyQvvPACUlNTUV5ejhs3biAqKgodOnQwqb/24wYZGRmG905mZqbJIwn6x19qP9pirj69Z599FnFxcSb9qMvEiROxd+9eFBYWQqvV4tSpU1i0aBEsLfnfSyKiBwG/jYmI6IG3YsUKVFRUYOXKlbC2vvc3panVagDAqlWrzJapqKjAunXrANxNwhvDz88Pt2/fxubNm7Ft2zaUlpYa9mnOwoULERoaiiNHjiAkJAQ5OTlYsGABfv31V6Nj8NJLLyExMREeHh5ISEjAunXrEBsbCxsbG7zxxhtGdU6bNg0HDhyAl5cXtm/fjpCQENy6dQsajQb79u2DjY1No/pVn/379yMqKsrwOiAgwBBFRUUAgFatWiEhIQHr16+HhYUFvvnmG2zatAmurq6IjY3F3LlzG73fiIgIdOrUyeTHAl9fX5w+fdrs3R5TpkyBn58fLl26hG+//RYbNmxAYWEh3nvvPezZs8fkvdenTx+kpKRg9OjR2L17Nz7//HNYW1sjJSUFjz/+uNn2TZw4EXFxccjOzkZYWBguXrwIHx8fxMTE1Nu3kJAQwyMoISEhhuOpP85N4ebmht9++w1jx4419KNVq1ZITU3FE088objN6tWrERMTg549e2Lbtm0ICwuDVqvFp59+ii1btjS5LUREdG8Jg8FgMBgPWri6uoqIyK5duwSAfPLJJyIiMnfuXEMZDw8PERGJjIw02jYyMlJERL7++mvRaDSKYWNjIwDEyspKdDqdVFZWGpaZix49eoiIyIULFxrcj969exv1A4BERUWJiIi3t7dJeY1GIyIiFRUV4u7ubrRu06ZNIiKycOFCw7Lo6GgREenTp49JXR06dDC8btu2rdy8eVO0Wq1RvRYWFvLDDz+IiMjy5cuNts/IyJCMjAzFY+vq6mq27Z6enoZlnp6eIiKi0WgUj8/KlStFRCQwMNBouZ2dnfz+++9SUVEhjz76aL3HWb+fL774QlQqleTn58uOHTsM6wcNGiQiIgsWLBAnJycREUlKSjKqo2vXrqJSqUzq/uCDD0REZObMmUbLk5OTRURkxowZRssDAwNFr+Zx8vHxERGRyspKGT58uGG5paWl7Nu3T0REPDw8jOpSamdd50D/uan9mairvqSkJMX+rVq1SrEfzz//vOE93aZNG6NtwsLCRERkypQpjf7MMxgMBuOeR7M3gMFgMBgMk6id7Ldr104KCwslNzdXbG1tBag/2a+Lg4ODAJDOnTuLiEh2dna9bbKxsRERkfLy8gb3Izg42CQh9Pb2FhGRzZs3m5TXJ8xfffWVybru3btLVVWVnDx50rBMn+w/9dRTdbZj1qxZIiLy+eefm6xzcXGRyspKkx8x7neyb2FhIQUFBXL+/HnFNo8fP15EjH/gMRc1k30AEhISIlVVVYYfCsLCwkSn04mjo6PZZN9ctG/fXkREIiIijM6FiMixY8dMyrdp00YKCgpMjpM+2Y+KijLZRr9u3rx5RsuV2nkvk30XFxcRETl+/LhJWVtbWyksLDTZ1/bt20VExMXFxWQbe3t7uXPnjvz0008N/owwGAwG4/4EB+gjIqKHQlFRET7++GMEBQVh8eLFCAwMrHeboUOHNmiAvvulVatWmDVrFkpKSvDLL78YliclJSErKwsvv/wy2rVrZ7ilvaaDBw+aLMvKysKVK1fg5uYGlUqFqqoqbNmyBVOnTsWhQ4fw/fffIzExEQcPHkRBQYHRtv379wcAwzP0NV25cgWXLl1Cz549YWdnh7Kysn/W8Qbq2bMnOnTogOzsbMWp+Tp16gTg7oj0jRUREYF3330XPj4+CA4OxmuvvYYdO3bgxo0bcHJyMrudWq3G7Nmz0bt3bzg4OMDKysqwrmvXrobXffv2BQCkpqaa1HHr1i0cP34c3t7eivs4evSoyTL9YI3t2rVrUP/uFX0/UlJSTNaVl5fj+PHjJmNUDB06FGVlZWYfZ9FqtU06Z0REdG8x2ScioodGaGgo5s2bh0WLFiEsLOye1FlQUIDKyko4OjrCxsYGOp3ObFkXFxcAQE5OToPqnjx5MhwdHREREWE06J+IYPPmzXj//fcxc+ZMxb7k5eUp1pmXl4fHH38cbdu2RWFhIaKjozFp0iQsXLgQb7/9NubNm4fq6mokJSVh0aJFOHHiBADA3t6+znpzcnLQs2dP2Nvb/2vJvn5Aut69e6N3795my5kbHK8uJ0+exNGjR6FWq5GVlYX27dubHZhPLzQ0FPPnz0dWVhZiY2ORk5NjeD8EBAQYjWmgP57Xr19XrMvccQaAkpISk2W3b98GAKMfF/4NDg4OABrXjw4dOkClUiEgIMBsvU05Z0REdG9xgD4iInpoVFRUQKPRoG3btopXgpvizp07OHLkCFQqlWEUeXNGjRoFAEhLS2tQ3X5+fgDuDgwnNUaiFxG8//77RmVqM3f12cnJCdXV1SgtLTUsi42NhZeXF9q3b48xY8YgPDwcXl5e2L17tyGZ0yeY5urt0qWLUTlzqqurAUBxoET9vhpKv6/o6GhYWFiYjcYOiKj3zTff4Omnn0ZQUBCuXbuGXbt2mS3bqVMnzJ07FydOnECvXr2gVquxdOlSBAYGYsOGDWbb3rlzZ8X66rp74H6q6/zof6Coqbi4GEDj+lFSUoIbN27Uec7MDexHRET/Hib7RET0UPn2229x+vRp+Pv7o0ePHvekTv1I5voEXImNjQ0WLlwIAPVeIQaA7t27Y9SoUcjNzUV4eLhiXLp0CQMGDEC/fv1Mth85cqRinS4uLjhz5gyqqqpM1peVlSEhIQFz5sxBVFQUunTpAg8PDwDAsWPHANydpq82Z2dnPPnkk7h48WK9V/Vv3rwJAOjWrZvJOv2jAjXduXMHgPIV67Nnz6K4uBiDBg26L7MsfP/999BqtXB2dsbGjRsNibCSJ554ApaWlti7dy+0Wq3ROqVzob9jYvjw4SbrWrdubbg9/n6o65jqHwlp6PnR92PEiBEm62xtbRXfm4cPH4ajo+M9+/wREdH9wWSfiIgeKtXV1Vi6dClatWpV523EjREVFYVDhw7By8sLGzZsMJmCzt7eHlu3bsXTTz+NH3/8UXGe8trUajWsrKzw5Zdfwt/fXzE+/vhjAMpX99988024u7sbLVu9ejWsra2NplkbOXKk4rzm+iu1+scHYmJiUFRUBLVajWeffdaobFBQEFQqVYOmbzty5AgAGOZ615s6dariDwmFhYUA/n4EoqY7d+7giy++wGOPPYZPP/1UMeF3c3MzPLvfWMXFxRg9ejQmT56M4ODgOstevnwZwN3k3cLCwrC8W7duWLNmjUn5rKwspKSkoH///pg+fbrRuiVLlqBjx45NanND1HVMS0tLce7cOYwYMQJPPvmkYbmdnZ1iP65cuYIDBw6gb9++mDlzptG6pUuXon379ibbhIaGArj7o5f+UYyanJyc+Mw+EdEDgM/sExHRQycuLg4HDx5UvOJa01tvvYUxY8Yorjt06BASEhIA3H1eetKkSYiNjcWcOXMwfvx47Ny5E9evX0e3bt0wfvx4ODo6Ii4uDmq1ut72WVhYQK1Wo7q6us4EeuvWrQgJCcHrr7+OxYsXG40XkJCQgLS0NGzZsgX5+fkYNWoUBg8ejLS0NHz22WeGcqGhoejatStSUlKQmZkJEcGIESPg4eGBtLQ0w8BrpaWl8Pf3xw8//IDDhw9j69atyM/Px/PPP49Bgwbh8OHDWLt2bb19i4mJwYULF6BWq+Hi4oJjx47hmWeegbe3N+Lj4zFu3Dij8ufOncO1a9fw2muvQafT4erVqxARfPbZZygpKYFGo8GAAQPw7rvvYty4cUhOTjYcd3d3d/Tr1w9Dhw5Ffn5+vW1TojTQoZLc3FxER0dj2rRp+OOPP5CYmAgnJyeMHz8eiYmJilex58+fj+TkZGzevBlTp07FhQsXMGDAAAwdOhQHDhyAp6dnnXcTNNW+ffuwZMkSfPXVV/j5559RXl6Oy5cvY9OmTQCAdevW4euvv0ZaWhp++uknWFpaYuzYsYYfamqbO3cuUlNTsXHjRkyePBnnz5/HkCFDMHjwYCQnJ+N///ufUfmEhAR8+OGHWLFiBS5cuIDdu3fj8uXL6NixI3r06IGRI0di+fLlOHfu3D3vOxERNU6zTwnAYDAYDEbtqD31Xu0YNmyYYRq9pky9FxwcbFKnlZWV+Pr6yt69eyU/P190Op3k5uZKXFycTJ06tcFtf+GFFxo8tdt3330nIn9PzVdz+jo/Pz85deqUaLVauXbtmgQHB4udnZ3R9tOnT5ctW7bI+fPnpaysTG7evCnHjh2TJUuWGKYorBkjRoyQ+Ph4KSwslIqKCjl37pwEBgaazJcOKE+9pz8327Ztk+LiYiktLZU9e/bIwIEDFafeAyBDhgyRpKQkKS4uNhz/mlO5WVpair+/vxw8eFCKiopEq9VKZmam7Ny5U+bMmaPYttpRe+q9usLc1Hu2traydu1auXTpkmi1WklPT5dly5aJtbW12fPZt29f2bVrl5SUlEhxcbHEx8eLm5ubxMbGisjfUzwCf0+v5+PjY7b9tacoNLffxYsXS3p6uuh0OsUy77zzjmF9ZmamBAQE1NkPNzc32bFjh0k/6prmb9SoURITEyN5eXmi0+kkOztbUlNTZdmyZeLs7Nxs3x0MBoPBuBsWf70gIiIionvA0tISFy9eROvWrQ0DHxIREf3b+Mw+ERERURNYWVkpPpv/3nvv4bHHHsP27dv//UYRERH9hVf2iYiIiJrAwcEBeXl52LNnD/7880+oVCp4eHhgyJAhyM7OxsCBA5Gbm9vczSQiov8oJvtERERETaBSqRASEgJvb2907doVjzzyCHJycrBr1y589NFHyM7Obu4mEhHRfxiTfSIiIiIiIqIWhs/sExEREREREbUwTPaJiIiIiIiIWhgm+0REREREREQtDJN9IiIiIiIiohaGyT4RERERERFRC8Nkn4iIiIiIiKiFYbJPRERERERE1MIw2SciIiIiIiJqYZjsExEREREREbUw/wduBsCDIJdZEgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "neo_absmag_hist, bins_edge = np.histogram(neo_df[\"AbsMag_\"], \\\n",
    "                                       bins=np.arange(10.0, 31.0, 1.0))\n",
    "cumul_neo_absmag_hist = np.cumsum(neo_absmag_hist)\n",
    "\n",
    "# Create a figure and axis\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "# Create a scatter plot of the cumulative distribution.\n",
    "ax.scatter(bins_edge[:-1]+1, cumul_neo_absmag_hist, color='tab:orange', alpha=0.7, \\\n",
    "           marker='o')\n",
    "\n",
    "# Set labels for the x and y axes\n",
    "ax.set_xlabel('NEO Absolute Magnitude')\n",
    "ax.set_ylabel('Cumulative number of NEOs')\n",
    "\n",
    "# Set a grid\n",
    "ax.grid(axis='both', linestyle='dashed', alpha=0.2)\n",
    "\n",
    "# Set a logarithmic y axis\n",
    "ax.set_yscale('log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6f05e280",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import modules\n",
    "import pathlib\n",
    "import sqlite3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "98e53701",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Accessing the NEO database\n",
    "database_dir = pathlib.Path(\"../databases/neos/\")\n",
    "database_file = pathlib.Path(\"neodys.db\")\n",
    "database_filepath = database_dir / database_file\n",
    "\n",
    "# Establish a connection to the database and set a cursor\n",
    "neodys_db_con = sqlite3.connect(database_filepath)\n",
    "neodys_db_cur = neodys_db_con.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dca05db7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Get all information from the DB. Since the DB is rather small, this won't cause any issues!\n",
    "neo_df = pd.read_sql(\"SELECT * FROM main\", neodys_db_con)\n",
    "\n",
    "# Close the database.\n",
    "neodys_db_con.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "640a8abb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Epoch_MJD</th>\n",
       "      <th>SemMajAxis_AU</th>\n",
       "      <th>Ecc_</th>\n",
       "      <th>Incl_deg</th>\n",
       "      <th>LongAscNode_deg</th>\n",
       "      <th>ArgP_deg</th>\n",
       "      <th>MeanAnom_deg</th>\n",
       "      <th>AbsMag_</th>\n",
       "      <th>SlopeParamG_</th>\n",
       "      <th>Aphel_AU</th>\n",
       "      <th>Perihel_AU</th>\n",
       "      <th>NEOClass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>433</td>\n",
       "      <td>60000.0</td>\n",
       "      <td>1.458129</td>\n",
       "      <td>0.222782</td>\n",
       "      <td>10.827822</td>\n",
       "      <td>304.287024</td>\n",
       "      <td>178.926986</td>\n",
       "      <td>110.777664</td>\n",
       "      <td>10.91</td>\n",
       "      <td>0.46</td>\n",
       "      <td>1.782974</td>\n",
       "      <td>1.133284</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>719</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.636157</td>\n",
       "      <td>0.546780</td>\n",
       "      <td>11.575260</td>\n",
       "      <td>183.857164</td>\n",
       "      <td>156.215519</td>\n",
       "      <td>148.450677</td>\n",
       "      <td>15.54</td>\n",
       "      <td>0.15</td>\n",
       "      <td>4.077554</td>\n",
       "      <td>1.194760</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>887</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.472525</td>\n",
       "      <td>0.571093</td>\n",
       "      <td>9.398799</td>\n",
       "      <td>110.423003</td>\n",
       "      <td>350.474251</td>\n",
       "      <td>340.198429</td>\n",
       "      <td>13.43</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>3.884567</td>\n",
       "      <td>1.060483</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1036</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.665299</td>\n",
       "      <td>0.532826</td>\n",
       "      <td>26.686736</td>\n",
       "      <td>215.494967</td>\n",
       "      <td>132.496155</td>\n",
       "      <td>6.984966</td>\n",
       "      <td>9.47</td>\n",
       "      <td>0.30</td>\n",
       "      <td>4.085439</td>\n",
       "      <td>1.245159</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1221</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.920154</td>\n",
       "      <td>0.434718</td>\n",
       "      <td>11.868483</td>\n",
       "      <td>171.260813</td>\n",
       "      <td>26.717610</td>\n",
       "      <td>271.700798</td>\n",
       "      <td>17.43</td>\n",
       "      <td>0.15</td>\n",
       "      <td>2.754880</td>\n",
       "      <td>1.085428</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37411</th>\n",
       "      <td>2025BZ1</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.332160</td>\n",
       "      <td>0.186998</td>\n",
       "      <td>18.236821</td>\n",
       "      <td>308.499762</td>\n",
       "      <td>179.468173</td>\n",
       "      <td>295.799413</td>\n",
       "      <td>24.75</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.581271</td>\n",
       "      <td>1.083048</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37412</th>\n",
       "      <td>2025BZ2</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.547441</td>\n",
       "      <td>0.347306</td>\n",
       "      <td>12.393768</td>\n",
       "      <td>301.653113</td>\n",
       "      <td>217.970751</td>\n",
       "      <td>291.412078</td>\n",
       "      <td>26.29</td>\n",
       "      <td>0.15</td>\n",
       "      <td>2.084877</td>\n",
       "      <td>1.010006</td>\n",
       "      <td>Apollo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37413</th>\n",
       "      <td>6344P-L</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.821108</td>\n",
       "      <td>0.661803</td>\n",
       "      <td>4.678521</td>\n",
       "      <td>182.791071</td>\n",
       "      <td>235.006174</td>\n",
       "      <td>213.375870</td>\n",
       "      <td>20.40</td>\n",
       "      <td>0.15</td>\n",
       "      <td>4.688125</td>\n",
       "      <td>0.954091</td>\n",
       "      <td>Apollo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37414</th>\n",
       "      <td>2025BQ7</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>2.257766</td>\n",
       "      <td>0.500895</td>\n",
       "      <td>19.428948</td>\n",
       "      <td>134.964544</td>\n",
       "      <td>9.059571</td>\n",
       "      <td>325.461747</td>\n",
       "      <td>22.11</td>\n",
       "      <td>0.15</td>\n",
       "      <td>3.388669</td>\n",
       "      <td>1.126863</td>\n",
       "      <td>Amor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37415</th>\n",
       "      <td>2025BR7</td>\n",
       "      <td>60600.0</td>\n",
       "      <td>1.374864</td>\n",
       "      <td>0.410936</td>\n",
       "      <td>22.307244</td>\n",
       "      <td>309.646982</td>\n",
       "      <td>255.517583</td>\n",
       "      <td>262.288565</td>\n",
       "      <td>25.20</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1.939845</td>\n",
       "      <td>0.809883</td>\n",
       "      <td>Apollo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37416 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Name  Epoch_MJD  SemMajAxis_AU      Ecc_   Incl_deg  \\\n",
       "0          433    60000.0       1.458129  0.222782  10.827822   \n",
       "1          719    60600.0       2.636157  0.546780  11.575260   \n",
       "2          887    60600.0       2.472525  0.571093   9.398799   \n",
       "3         1036    60600.0       2.665299  0.532826  26.686736   \n",
       "4         1221    60600.0       1.920154  0.434718  11.868483   \n",
       "...        ...        ...            ...       ...        ...   \n",
       "37411  2025BZ1    60600.0       1.332160  0.186998  18.236821   \n",
       "37412  2025BZ2    60600.0       1.547441  0.347306  12.393768   \n",
       "37413  6344P-L    60600.0       2.821108  0.661803   4.678521   \n",
       "37414  2025BQ7    60600.0       2.257766  0.500895  19.428948   \n",
       "37415  2025BR7    60600.0       1.374864  0.410936  22.307244   \n",
       "\n",
       "       LongAscNode_deg    ArgP_deg  MeanAnom_deg  AbsMag_  SlopeParamG_  \\\n",
       "0           304.287024  178.926986    110.777664    10.91          0.46   \n",
       "1           183.857164  156.215519    148.450677    15.54          0.15   \n",
       "2           110.423003  350.474251    340.198429    13.43         -0.12   \n",
       "3           215.494967  132.496155      6.984966     9.47          0.30   \n",
       "4           171.260813   26.717610    271.700798    17.43          0.15   \n",
       "...                ...         ...           ...      ...           ...   \n",
       "37411       308.499762  179.468173    295.799413    24.75          0.15   \n",
       "37412       301.653113  217.970751    291.412078    26.29          0.15   \n",
       "37413       182.791071  235.006174    213.375870    20.40          0.15   \n",
       "37414       134.964544    9.059571    325.461747    22.11          0.15   \n",
       "37415       309.646982  255.517583    262.288565    25.20          0.15   \n",
       "\n",
       "       Aphel_AU  Perihel_AU NEOClass  \n",
       "0      1.782974    1.133284     Amor  \n",
       "1      4.077554    1.194760     Amor  \n",
       "2      3.884567    1.060483     Amor  \n",
       "3      4.085439    1.245159     Amor  \n",
       "4      2.754880    1.085428     Amor  \n",
       "...         ...         ...      ...  \n",
       "37411  1.581271    1.083048     Amor  \n",
       "37412  2.084877    1.010006   Apollo  \n",
       "37413  4.688125    0.954091   Apollo  \n",
       "37414  3.388669    1.126863     Amor  \n",
       "37415  1.939845    0.809883   Apollo  \n",
       "\n",
       "[37416 rows x 13 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neo_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "473e1e30",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_theme()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e550d8c2",
   "metadata": {},
   "source": [
    "### Creating quickly an overview plot with seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "56526f44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 35.0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use bins=... to set the number of bins or\n",
    "# bin_width=... to set the width of each bins. Quite easy!\n",
    "sns_plt = sns.displot(neo_df, x=\"AbsMag_\")\n",
    "plt.xlim(0, 35)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "46a1fd4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15.0, 30.0)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 597.625x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns_plt = sns.displot(neo_df.loc[neo_df[\"NEOClass\"] != \"Other\"],\n",
    "                      x=\"AbsMag_\",\n",
    "                      hue=\"NEOClass\",\n",
    "                      element=\"step\",\n",
    "                      stat=\"probability\",\n",
    "                      common_norm=False,\n",
    "                      binwidth=1)\n",
    "plt.xlim(15, 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "142be6da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.5, 3.0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 597.625x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(neo_df.loc[(neo_df[\"NEOClass\"] != \"Other\") & (neo_df[\"SemMajAxis_AU\"] < 3.0)],\n",
    "            x=\"SemMajAxis_AU\",\n",
    "            hue=\"NEOClass\",\n",
    "            kind=\"kde\",\n",
    "            multiple=\"stack\")\n",
    "plt.xlim(0.5,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3dacce19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 750x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Generate sample data\n",
    "np.random.seed(42)\n",
    "data = pd.DataFrame({\n",
    "    'Feature1': np.random.randn(100),\n",
    "    'Feature2': np.random.randn(100) * 2 + 1,\n",
    "    'Feature3': np.random.randn(100) * 3 - 2\n",
    "})\n",
    "\n",
    "# Create a PairGrid instance\n",
    "g = sns.PairGrid(data)\n",
    "\n",
    "# Upper triangle: Histograms\n",
    "g.map_upper(sns.histplot, bins=20)\n",
    "\n",
    "# Lower triangle: KDE plot with fixed parameters to avoid errors\n",
    "g.map_lower(sns.kdeplot, fill=True, warn_singular=False, levels=10)\n",
    "\n",
    "# Diagonal: Histogram with KDE\n",
    "g.map_diag(sns.histplot, kde=True, bins=20)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  }
 ],
 "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}