docs/visualization/visualize_unit_responses.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "740a0b46",
   "metadata": {},
   "source": [
    "# Visualizing Neuronal Unit Responses\n",
    "\n",
    "Note: Some of this content is adapted from the [Allen SDK Documentation](https://allensdk.readthedocs.io/en/latest/_static/examples/nb/ecephys_session.html).\n",
    "\n",
    "After processing Neuropixels ecephys data with **[Kilosort](https://github.com/MouseLand/Kilosort)**, individual neuronal units have been identified and are stored in the units table, in the `Units` section of the NWB file. The units table contains information about hypothetical neurons determined by Kilosort. With this information and the stimulus information found in the stimulus tables of the `Intervals` section, this notebook helps examine the spiking behavior of these units in response to stimuli and their associated waveforms"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "4c83be96",
   "metadata": {},
   "source": [
    "### Environment Setup\n",
    "⚠️**Note: If running on a new environment, run this cell once and then restart the kernel**⚠️"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d820ef7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "try:\n",
    "    from databook_utils.dandi_utils import dandi_download_open\n",
    "except:\n",
    "    !git clone https://github.com/AllenInstitute/openscope_databook.git\n",
    "    %cd openscope_databook\n",
    "    %pip install -e ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "09650a3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3cc865a1",
   "metadata": {},
   "source": [
    "### Downloading Ecephys File\n",
    "Change the values below to download the file you’re interested in. Set `dandiset_id` and `dandi_filepath` to correspond to the dandiset id and filepath of the file you want. If you’re accessing an embargoed dataset, set `dandi_api_key` to your DANDI API key. If you want to stream a file instead of downloading it, use `dandi_stream_open` instead. Checkout [Streaming an NWB File with remfile](../basics/stream_nwb.ipynb) for more details on this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "faa81fb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "dandiset_id = \"000021\"\n",
    "dandi_filepath = \"sub-703279277/sub-703279277_ses-719161530.nwb\"\n",
    "download_loc = \".\"\n",
    "dandi_api_key = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b41929c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "A newer version (0.62.1) of dandi/dandi-cli is available. You are using 0.55.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File already exists\n",
      "Opening file\n"
     ]
    }
   ],
   "source": [
    "# This can sometimes take a while depending on the size of the file\n",
    "io = dandi_download_open(dandiset_id, dandi_filepath, download_loc, dandi_api_key=dandi_api_key)\n",
    "nwb = io.read()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "53919d11",
   "metadata": {},
   "source": [
    "### Extracting Unit Data and Stimulus Data\n",
    "Below, the `Units` table is read from the file. Individual units (putative neurons) are identified with the `id` column. Note that, while each id is unique, they are not perfectly ordinal; some ids are missing. In the cells below, the unit properties are listed and a slice of the units table is shown. More thorough descriptions of units and their properties can be found in [Visualizing Unit Quality Metrics](visualize_unit_metrics.ipynb)\n",
    "\n",
    "Additionally, the stimulus data is also read from the NWB file's `Intervals` section. Stimulus information is stored as a series of tables depending on the type of stimulus shown in the session. One such table is displayed below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "50a4d0b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('waveform_duration',\n",
       " 'cluster_id',\n",
       " 'peak_channel_id',\n",
       " 'cumulative_drift',\n",
       " 'amplitude_cutoff',\n",
       " 'snr',\n",
       " 'recovery_slope',\n",
       " 'isolation_distance',\n",
       " 'nn_miss_rate',\n",
       " 'silhouette_score',\n",
       " 'velocity_above',\n",
       " 'quality',\n",
       " 'PT_ratio',\n",
       " 'l_ratio',\n",
       " 'velocity_below',\n",
       " 'max_drift',\n",
       " 'isi_violations',\n",
       " 'firing_rate',\n",
       " 'amplitude',\n",
       " 'local_index',\n",
       " 'spread',\n",
       " 'waveform_halfwidth',\n",
       " 'd_prime',\n",
       " 'presence_ratio',\n",
       " 'repolarization_slope',\n",
       " 'nn_hit_rate',\n",
       " 'spike_times',\n",
       " 'spike_amplitudes',\n",
       " 'waveform_mean')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "units = nwb.units\n",
    "units.colnames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ce0e64b4",
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
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       "           waveform_duration  cluster_id  peak_channel_id  cumulative_drift  \\\n",
       "id                                                                            \n",
       "950921187           0.604355           4        850249267            481.80   \n",
       "950921172           0.521943           3        850249267            681.53   \n",
       "950921152           0.467002           2        850249267           1070.71   \n",
       "950921135           0.467002           1        850249267            253.42   \n",
       "950921111           0.439531           0        850249267            141.82   \n",
       "950927711           1.455946         482        850249273              2.46   \n",
       "950921285           2.087772          11        850249273            318.53   \n",
       "950921271           0.947739          10        850249273           1008.50   \n",
       "950921260           0.453266           9        850249273            175.00   \n",
       "950921248           0.439531           8        850249273            261.11   \n",
       "\n",
       "           amplitude_cutoff       snr  recovery_slope  isolation_distance  \\\n",
       "id                                                                          \n",
       "950921187          0.425574  2.209140       -0.118430           17.537571   \n",
       "950921172          0.390098  1.959983       -0.109729           14.677643   \n",
       "950921152          0.500000  2.522905       -0.109867           15.783665   \n",
       "950921135          0.500000  2.803475       -0.150379           26.666930   \n",
       "950921111          0.018056  4.647943       -0.328727           66.901065   \n",
       "950927711          0.000895  1.651500       -0.039932           39.400278   \n",
       "950921285          0.036848  1.379817             NaN           27.472722   \n",
       "950921271          0.001727  1.420617       -0.008204           30.027595   \n",
       "950921260          0.000081  4.969091       -0.184456           89.804006   \n",
       "950921248          0.065478  2.147758       -0.085677           84.145512   \n",
       "\n",
       "           nn_miss_rate  silhouette_score  ...  local_index spread  \\\n",
       "id                                         ...                       \n",
       "950921187      0.009496          0.036369  ...            4   50.0   \n",
       "950921172      0.003857          0.103446  ...            3   40.0   \n",
       "950921152      0.017776          0.027818  ...            2   50.0   \n",
       "950921135      0.023742          0.076530  ...            1   40.0   \n",
       "950921111      0.006595               NaN  ...            0   30.0   \n",
       "950927711      0.000033               NaN  ...          464  100.0   \n",
       "950921285      0.000903          0.291953  ...           11  100.0   \n",
       "950921271      0.000707          0.406673  ...           10  100.0   \n",
       "950921260      0.000000          0.223876  ...            9   60.0   \n",
       "950921248      0.005474          0.076346  ...            8   60.0   \n",
       "\n",
       "           waveform_halfwidth   d_prime  presence_ratio  repolarization_slope  \\\n",
       "id                                                                              \n",
       "950921187            0.357119  2.962274            0.99              0.381716   \n",
       "950921172            0.260972  2.067810            0.99              0.536663   \n",
       "950921152            0.247236  2.220043            0.99              0.566559   \n",
       "950921135            0.233501  2.339206            0.99              0.669090   \n",
       "950921111            0.219765  4.395994            0.99              1.261416   \n",
       "950927711            0.274707  5.557479            0.37              0.467365   \n",
       "950921285            0.288442  2.751337            0.89              0.372116   \n",
       "950921271            0.288442  3.847234            0.96              0.498618   \n",
       "950921260            0.192295  5.274090            0.99              1.140487   \n",
       "950921248            0.274707  3.022387            0.99              0.463570   \n",
       "\n",
       "           nn_hit_rate                                        spike_times  \\\n",
       "id                                                                          \n",
       "950921187     0.473829  [1.0439430431793884, 1.543311060144649, 2.7287...   \n",
       "950921172     0.445946  [10.406435026164546, 17.127986534673788, 18.48...   \n",
       "950921152     0.284058  [1.2775103414155262, 2.3915133536963493, 3.701...   \n",
       "950921135     0.590737  [9.473732504122962, 13.198542576065163, 18.302...   \n",
       "950921111     0.952667  [1.1677100445138795, 1.1707767194728813, 1.349...   \n",
       "950927711     0.000000  [2613.8652081509977, 2624.5193369599215, 2734....   \n",
       "950921285     0.258065  [39.04904580954626, 39.457346913598556, 40.495...   \n",
       "950921271     0.796491  [16.751918851114475, 26.127977537450867, 28.65...   \n",
       "950921260     0.997333  [0.9620761551434307, 2.092045877265143, 2.4040...   \n",
       "950921248     0.976667  [1.316477113448928, 1.779311698293908, 2.96088...   \n",
       "\n",
       "                                            spike_amplitudes  \\\n",
       "id                                                             \n",
       "950921187  [0.0001908626967721937, 0.00016134635752077775...   \n",
       "950921172  [0.00014485615850768024, 0.0001722424107984555...   \n",
       "950921152  [0.00014859435856024575, 0.0001531048673600236...   \n",
       "950921135  [0.00032386170367170055, 0.0004518112387675137...   \n",
       "950921111  [0.00015644521007973124, 0.000214412247939483,...   \n",
       "950927711  [0.00012946663895843286, 0.0001203425053985725...   \n",
       "950921285  [7.768399792002802e-05, 8.405736507197006e-05,...   \n",
       "950921271  [0.00016516929470324686, 0.0001501058102103845...   \n",
       "950921260  [0.0003836112198262231, 0.0004093908262843732,...   \n",
       "950921248  [0.00013780619334124896, 0.0001439873831056905...   \n",
       "\n",
       "                                               waveform_mean  \n",
       "id                                                            \n",
       "950921187  [[0.0, 0.5961149999999966, 5.378099999999993, ...  \n",
       "950921172  [[0.0, -1.341600000000002, -0.4586399999999933...  \n",
       "950921152  [[0.0, -0.6427199999999993, -2.836079999999998...  \n",
       "950921135  [[0.0, -3.2800950000000078, -6.087510000000009...  \n",
       "950921111  [[0.0, -0.9291749999999945, -6.120270000000007...  \n",
       "950927711  [[0.0, 6.3216435986159105, 10.324204152249129,...  \n",
       "950921285  [[0.0, 5.330324999999991, 2.4261899999999486, ...  \n",
       "950921271  [[0.0, -3.103230000000032, 5.680349999999983, ...  \n",
       "950921260  [[0.0, 1.9104149999999982, -7.270770000000016,...  \n",
       "950921248  [[0.0, -3.6761399999999953, 0.8334300000000014...  \n",
       "\n",
       "[10 rows x 29 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "units[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d61e1459",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['drifting_gratings_presentations', 'flashes_presentations', 'gabors_presentations', 'invalid_times', 'natural_movie_one_presentations', 'natural_movie_three_presentations', 'natural_scenes_presentations', 'spontaneous_presentations', 'static_gratings_presentations'])\n"
     ]
    }
   ],
   "source": [
    "stimulus_names = nwb.intervals.keys()\n",
    "print(stimulus_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aa347405",
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>start_time</th>\n",
       "      <th>stop_time</th>\n",
       "      <th>stimulus_name</th>\n",
       "      <th>stimulus_block</th>\n",
       "      <th>color</th>\n",
       "      <th>mask</th>\n",
       "      <th>opacity</th>\n",
       "      <th>phase</th>\n",
       "      <th>size</th>\n",
       "      <th>units</th>\n",
       "      <th>stimulus_index</th>\n",
       "      <th>orientation</th>\n",
       "      <th>spatial_frequency</th>\n",
       "      <th>contrast</th>\n",
       "      <th>tags</th>\n",
       "      <th>timeseries</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1290.883097</td>\n",
       "      <td>1291.133309</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3647, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1292.884817</td>\n",
       "      <td>1293.135016</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3648, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1294.886487</td>\n",
       "      <td>1295.136691</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3649, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1296.888137</td>\n",
       "      <td>1297.138344</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3650, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1298.889787</td>\n",
       "      <td>1299.140004</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3651, 1, timestamps pynwb.base.TimeSeries at...</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>1581.125517</td>\n",
       "      <td>1581.375726</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3792, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>1583.127217</td>\n",
       "      <td>1583.377419</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3793, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>1585.128807</td>\n",
       "      <td>1585.379029</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3794, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>1587.130507</td>\n",
       "      <td>1587.380724</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3795, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>1589.132187</td>\n",
       "      <td>1589.382401</td>\n",
       "      <td>flashes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>[300.0, 300.0]</td>\n",
       "      <td>deg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[0.0, 0.0]</td>\n",
       "      <td>0.8</td>\n",
       "      <td>[stimulus_time_interval]</td>\n",
       "      <td>[(3796, 1, timestamps pynwb.base.TimeSeries at...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      start_time    stop_time stimulus_name  stimulus_block color  mask  \\\n",
       "id                                                                        \n",
       "0    1290.883097  1291.133309       flashes             1.0  -1.0  None   \n",
       "1    1292.884817  1293.135016       flashes             1.0   1.0  None   \n",
       "2    1294.886487  1295.136691       flashes             1.0   1.0  None   \n",
       "3    1296.888137  1297.138344       flashes             1.0   1.0  None   \n",
       "4    1298.889787  1299.140004       flashes             1.0  -1.0  None   \n",
       "..           ...          ...           ...             ...   ...   ...   \n",
       "145  1581.125517  1581.375726       flashes             1.0   1.0  None   \n",
       "146  1583.127217  1583.377419       flashes             1.0   1.0  None   \n",
       "147  1585.128807  1585.379029       flashes             1.0  -1.0  None   \n",
       "148  1587.130507  1587.380724       flashes             1.0  -1.0  None   \n",
       "149  1589.132187  1589.382401       flashes             1.0  -1.0  None   \n",
       "\n",
       "     opacity       phase            size units  stimulus_index  orientation  \\\n",
       "id                                                                            \n",
       "0        1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "1        1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "2        1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "3        1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "4        1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "..       ...         ...             ...   ...             ...          ...   \n",
       "145      1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "146      1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "147      1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "148      1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "149      1.0  [0.0, 0.0]  [300.0, 300.0]   deg             1.0          0.0   \n",
       "\n",
       "    spatial_frequency  contrast                      tags  \\\n",
       "id                                                          \n",
       "0          [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "1          [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "2          [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "3          [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "4          [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "..                ...       ...                       ...   \n",
       "145        [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "146        [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "147        [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "148        [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "149        [0.0, 0.0]       0.8  [stimulus_time_interval]   \n",
       "\n",
       "                                            timeseries  \n",
       "id                                                      \n",
       "0    [(3647, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "1    [(3648, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "2    [(3649, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "3    [(3650, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "4    [(3651, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "..                                                 ...  \n",
       "145  [(3792, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "146  [(3793, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "147  [(3794, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "148  [(3795, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "149  [(3796, 1, timestamps pynwb.base.TimeSeries at...  \n",
       "\n",
       "[150 rows x 16 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stim_table = nwb.intervals[\"flashes_presentations\"]\n",
    "stim_table[:]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f2ca9341",
   "metadata": {},
   "source": [
    "### Getting Stimulus Epochs\n",
    "Here, *epochs* are extracted from the stimulus tables. In this case, an epoch is a continuous period of time during a session where a particular type of stimulus is shown. The output here is a list of epochs, where an epoch is a tuple of four values; the stimulus name, the stimulus block, the starting time and the ending time. Since stimulus information can vary significantly between experiments and NWB files, you may need to tailor the code below to extract epochs for the file you're interested in. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9fdc4f40",
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract epoch times from stim table where stimulus rows have a different 'block' than following row\n",
    "# returns list of epochs, where an epoch is of the form (stimulus name, stimulus block, start time, stop time)\n",
    "def extract_epochs(stim_name, stim_table, epochs):\n",
    "    \n",
    "    # specify a current epoch stop and start time\n",
    "    epoch_start = stim_table.start_time[0]\n",
    "    epoch_stop = stim_table.stop_time[0]\n",
    "\n",
    "    # for each row, try to extend current epoch stop_time\n",
    "    for i in range(len(stim_table)):\n",
    "        this_block = stim_table.stimulus_block[i]\n",
    "        # if end of table, end the current epoch\n",
    "        if i+1 >= len(stim_table):\n",
    "            epochs.append((stim_name, this_block, epoch_start, epoch_stop))\n",
    "            break\n",
    "            \n",
    "        next_block = stim_table.stimulus_block[i+1]\n",
    "        # if next row is the same stim block, push back epoch_stop time\n",
    "        if next_block == this_block:\n",
    "            epoch_stop = stim_table.stop_time[i+1]\n",
    "        # otherwise, end the current epoch, start new epoch\n",
    "        else:\n",
    "            epochs.append((stim_name, this_block, epoch_start, epoch_stop))\n",
    "            epoch_start = stim_table.start_time[i+1]\n",
    "            epoch_stop = stim_table.stop_time[i+1]\n",
    "    \n",
    "    return epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2afe14f6",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15\n",
      "('gabors_presentations', 0.0, 89.8968273815905, 1001.8917716749913)\n",
      "('flashes_presentations', 1.0, 1290.8830973815907, 1589.382401312724)\n",
      "('drifting_gratings_presentations', 2.0, 1591.1338573815906, 2190.634543106125)\n",
      "('natural_movie_three_presentations', 3.0, 2221.6604473815905, 2822.161967381591)\n",
      "('natural_movie_one_presentations', 4.0, 2852.1870373815905, 3152.4377773815904)\n",
      "('drifting_gratings_presentations', 5.0, 3182.4628573815908, 3781.963503106125)\n",
      "('natural_movie_three_presentations', 6.0, 4083.215117381591, 4683.716567381592)\n",
      "('drifting_gratings_presentations', 7.0, 4713.741627381592, 5397.312443106124)\n",
      "('static_gratings_presentations', 8.0, 5398.31325738159, 5878.714467381591)\n",
      "('natural_scenes_presentations', 9.0, 5908.739537381591, 6389.157337381589)\n",
      "('natural_scenes_presentations', 10.0, 6689.408117381589, 7169.809297381591)\n",
      "('static_gratings_presentations', 11.0, 7199.83431738159, 7680.268867381591)\n",
      "('natural_movie_one_presentations', 12.0, 7710.293937381591, 8010.54467738159)\n",
      "('natural_scenes_presentations', 13.0, 8040.56972738159, 8568.510620243858)\n",
      "('static_gratings_presentations', 14.0, 8611.04613738159, 9151.49746738159)\n"
     ]
    }
   ],
   "source": [
    "# extract epochs from all valid stimulus tables\n",
    "epochs = []\n",
    "for stim_name in stimulus_names:\n",
    "    stim_table = nwb.intervals[stim_name]\n",
    "    try:\n",
    "        epochs = extract_epochs(stim_name, stim_table, epochs)\n",
    "    except:\n",
    "        continue\n",
    "\n",
    "# epochs take the form (stimulus name, stimulus block, start time, stop time)\n",
    "print(len(epochs))\n",
    "epochs.sort(key=lambda x: x[2])\n",
    "for epoch in epochs:\n",
    "    print(epoch)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d1c90bcc",
   "metadata": {},
   "source": [
    "### Visualizing Unit Activity Throughout Epochs\n",
    "Below is a view of the spiking activity of a unit throughout a session, where epochs are shown as colored sections. Set `unit_num` to be the id of the unit to view. Set `time_start` to the starting bound in seconds of the session, you'd like to see, and `time_end` to the ending bound. You may want to use the output above to inform your choice. As mentioned above, if your file's stimulus information differs significantly, this code may need to be modified to appropriately display the epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8b1d9007",
   "metadata": {},
   "outputs": [],
   "source": [
    "unit_num = 950930672 # chosen from units table\n",
    "time_start = 0\n",
    "time_end = 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8197deec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unit index: 648\n"
     ]
    }
   ],
   "source": [
    "# translate unit id to row index\n",
    "unit_idx = -1\n",
    "for i in range(len(units.id)):\n",
    "    if units.id[i] == unit_num:\n",
    "        unit_idx = i\n",
    "        break\n",
    "print(\"Unit index:\",unit_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8eacf09e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make histogram of unit spikes per second over specified timeframe\n",
    "spikes = units[\"spike_times\"][unit_idx]\n",
    "time_bin_edges = np.linspace(time_start, time_end, (time_end-time_start))\n",
    "hist, bins = np.histogram(spikes, bins=time_bin_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6d11f911",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x116a86b6280>]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate plot of spike histogram with colored epoch intervals and legend\n",
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "\n",
    "# assign unique color to each stimulus name\n",
    "stim_names = list({epoch[0] for epoch in epochs})\n",
    "colors = plt.cm.rainbow(np.linspace(0,1,len(stim_names)))\n",
    "stim_color_map = {stim_names[i]:colors[i] for i in range(len(stim_names))}\n",
    "\n",
    "epoch_key = {}\n",
    "height = max(hist)\n",
    "# draw colored rectangles for each epoch\n",
    "for epoch in epochs:\n",
    "    stim_name, stim_block, epoch_start, epoch_end = epoch\n",
    "    color = stim_color_map[stim_name]\n",
    "    rec = ax.add_patch(mpl.patches.Rectangle((epoch_start, 0), epoch_end-epoch_start, height, alpha=0.2, facecolor=color))\n",
    "    epoch_key[stim_name] = rec\n",
    "    \n",
    "ax.set_xlim(time_start, time_end)\n",
    "ax.set_ylim(-0.1, height+0.1)\n",
    "ax.set_xlabel(\"time (s)\")\n",
    "ax.set_ylabel(\"# spikes\")\n",
    "ax.set_title(\"Unit Spikes Per Second Throughout Epochs\")\n",
    "\n",
    "fig.legend(epoch_key.values(), epoch_key.keys(), loc=\"lower right\", bbox_to_anchor=(1.12, 0.25))\n",
    "ax.plot(bins[:-1], hist)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "9684ec5b",
   "metadata": {},
   "source": [
    "### Probewise Activity Throughout Epochs\n",
    "It can also be useful to view the activity of an entire probe throughout epochs. The code below allows users to select a probe and a histogram is produced for the total of all unit spiking counts over time for one probe. To do this, the file's `Electrodes` table is used. To understand this, you need not know anything about the `Electrodes` table, except that it can be used to map channel IDs to probe IDs. Below is printed a list of the probe names to choose from. Set `probe_name` to one of these. Set `time_start` and `time_end` to the start and ending times, in seconds, to view in the session."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f0a1e4ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['probeA', 'probeB', 'probeC', 'probeD', 'probeE', 'probeF'])\n"
     ]
    }
   ],
   "source": [
    "print(nwb.devices.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "41fdd3fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "probe_name = \"probeC\"\n",
    "time_start = 0\n",
    "time_end = 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a1a02149",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27741944"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get list of channels on this probe\n",
    "electrodes = nwb.electrodes.to_dataframe()\n",
    "channel_ids = set(electrodes.index[electrodes[\"group_name\"] == probe_name].tolist())\n",
    "\n",
    "# get all spike times from units whose peak channel belongs to the selected probe\n",
    "probe_spike_times = []\n",
    "for i in range(len(units)):\n",
    "    if units[\"peak_channel_id\"][i] in channel_ids:\n",
    "        probe_spike_times += list(units[\"spike_times\"][i])\n",
    "    \n",
    "len(probe_spike_times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1f47732d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make histogram of unit spikes per second over specified timeframe\n",
    "time_bin_edges = np.linspace(time_start, time_end, (time_end-time_start))\n",
    "hist, bins = np.histogram(probe_spike_times, bins=time_bin_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8c6702d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1171e7db820>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate plot of spike histogram with colored epoch intervals and legend\n",
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "\n",
    "# assign unique color to each stimulus name\n",
    "stim_names = list({epoch[0] for epoch in epochs})\n",
    "colors = plt.cm.rainbow(np.linspace(0,1,len(stim_names)))\n",
    "stim_color_map = {stim_names[i]:colors[i] for i in range(len(stim_names))}\n",
    "\n",
    "epoch_key = {}\n",
    "height = max(hist)\n",
    "# draw colored rectangles for each epoch\n",
    "for epoch in epochs:\n",
    "    stim_name, stim_block, epoch_start, epoch_end = epoch\n",
    "    color = stim_color_map[stim_name]\n",
    "    rec = ax.add_patch(mpl.patches.Rectangle((epoch_start, 0), epoch_end-epoch_start, height, alpha=0.2, facecolor=color))\n",
    "    epoch_key[stim_name] = rec\n",
    "    \n",
    "ax.set_xlim(time_start, time_end)\n",
    "ax.set_ylim(-0.1, height+0.1)\n",
    "ax.set_xlabel(\"time (s)\")\n",
    "ax.set_ylabel(\"# spikes\")\n",
    "ax.set_title(f\"{probe_name} Spikes Per Second Throughout Epochs\")\n",
    "\n",
    "fig.legend(epoch_key.values(), epoch_key.keys(), loc=\"lower right\", bbox_to_anchor=(1.12, 0.25))\n",
    "ax.plot(bins[:-1], hist)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50eec819",
   "metadata": {},
   "source": [
    "### Regionwise Activity Throughout Epochs\n",
    "We can also break down our activity based on brain regions (with a bit of work). To do this, we must first be able to retrieve the brain region of each unit. The trick to do this lay in the `Electrodes` table, shown below. The `Electrodes` table contains the brain region for each electrode id, while the `Units` table (shown above) contains the `Peak Channel ID` for each Unit. These can be used together to get the brain region of each unit's peak channel. Once this is done, this information can be used just like the Probe selection above to get to get spike counts over time of each Unit in a selected region. Below, set `brain_region`, `start_time`, and `end_time` to view such a plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5d01b1be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "      <th>imp</th>\n",
       "      <th>location</th>\n",
       "      <th>filtering</th>\n",
       "      <th>group</th>\n",
       "      <th>group_name</th>\n",
       "      <th>probe_vertical_position</th>\n",
       "      <th>probe_horizontal_position</th>\n",
       "      <th>probe_id</th>\n",
       "      <th>local_index</th>\n",
       "      <th>valid_data</th>\n",
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       "    <tr>\n",
       "      <th>id</th>\n",
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       "      <th>850249265</th>\n",
       "      <td>7955.0</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>3766.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eth</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
       "      <td>probeB</td>\n",
       "      <td>20</td>\n",
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       "      <td>729445650</td>\n",
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       "      <td>False</td>\n",
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       "      <th>850249267</th>\n",
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       "      <td>3756.0</td>\n",
       "      <td>3756.0</td>\n",
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       "      <td>TH</td>\n",
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       "      <td>probeB</td>\n",
       "      <td>20</td>\n",
       "      <td>11</td>\n",
       "      <td>729445650</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
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       "      <th>850249273</th>\n",
       "      <td>7955.0</td>\n",
       "      <td>3727.0</td>\n",
       "      <td>3727.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TH</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
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       "      <td>60</td>\n",
       "      <td>43</td>\n",
       "      <td>729445650</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
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       "      <th>850249277</th>\n",
       "      <td>7954.0</td>\n",
       "      <td>3708.0</td>\n",
       "      <td>3708.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
       "      <td>probeB</td>\n",
       "      <td>80</td>\n",
       "      <td>59</td>\n",
       "      <td>729445650</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850249283</th>\n",
       "      <td>7954.0</td>\n",
       "      <td>3679.0</td>\n",
       "      <td>3679.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
       "      <td>probeB</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>729445650</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>850249289</th>\n",
       "      <td>7953.0</td>\n",
       "      <td>3640.0</td>\n",
       "      <td>3640.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
       "      <td>probeB</td>\n",
       "      <td>140</td>\n",
       "      <td>43</td>\n",
       "      <td>729445650</td>\n",
       "      <td>12</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>7952.0</td>\n",
       "      <td>3612.0</td>\n",
       "      <td>3612.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
       "      <td>probeB</td>\n",
       "      <td>160</td>\n",
       "      <td>27</td>\n",
       "      <td>729445650</td>\n",
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       "      <td>True</td>\n",
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       "      <td>7952.0</td>\n",
       "      <td>3593.0</td>\n",
       "      <td>3593.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
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       "      <td>17</td>\n",
       "      <td>True</td>\n",
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       "      <td>7951.0</td>\n",
       "      <td>3565.0</td>\n",
       "      <td>3565.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
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       "    <tr>\n",
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       "      <td>7950.0</td>\n",
       "      <td>3537.0</td>\n",
       "      <td>3537.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>APN</td>\n",
       "      <td>AP band: 500 Hz high-pass; LFP band: 1000 Hz l...</td>\n",
       "      <td>probeB abc.EcephysElectrodeGroup at 0x11968190...</td>\n",
       "      <td>probeB</td>\n",
       "      <td>240</td>\n",
       "      <td>27</td>\n",
       "      <td>729445650</td>\n",
       "      <td>23</td>\n",
       "      <td>True</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "                x       y       z  imp location  \\\n",
       "id                                                \n",
       "850249265  7955.0  3766.0  3766.0  NaN      Eth   \n",
       "850249267  7955.0  3756.0  3756.0  NaN       TH   \n",
       "850249273  7955.0  3727.0  3727.0  NaN       TH   \n",
       "850249277  7954.0  3708.0  3708.0  NaN      APN   \n",
       "850249283  7954.0  3679.0  3679.0  NaN      APN   \n",
       "850249289  7953.0  3640.0  3640.0  NaN      APN   \n",
       "850249295  7952.0  3612.0  3612.0  NaN      APN   \n",
       "850249299  7952.0  3593.0  3593.0  NaN      APN   \n",
       "850249305  7951.0  3565.0  3565.0  NaN      APN   \n",
       "850249311  7950.0  3537.0  3537.0  NaN      APN   \n",
       "\n",
       "                                                   filtering  \\\n",
       "id                                                             \n",
       "850249265  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249267  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249273  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249277  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249283  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249289  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249295  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249299  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249305  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "850249311  AP band: 500 Hz high-pass; LFP band: 1000 Hz l...   \n",
       "\n",
       "                                                       group group_name  \\\n",
       "id                                                                        \n",
       "850249265  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249267  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249273  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249277  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249283  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249289  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249295  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249299  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249305  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "850249311  probeB abc.EcephysElectrodeGroup at 0x11968190...     probeB   \n",
       "\n",
       "           probe_vertical_position  probe_horizontal_position   probe_id  \\\n",
       "id                                                                         \n",
       "850249265                       20                         43  729445650   \n",
       "850249267                       20                         11  729445650   \n",
       "850249273                       60                         43  729445650   \n",
       "850249277                       80                         59  729445650   \n",
       "850249283                      100                         11  729445650   \n",
       "850249289                      140                         43  729445650   \n",
       "850249295                      160                         27  729445650   \n",
       "850249299                      180                         11  729445650   \n",
       "850249305                      220                         43  729445650   \n",
       "850249311                      240                         27  729445650   \n",
       "\n",
       "           local_index  valid_data  \n",
       "id                                  \n",
       "850249265            0       False  \n",
       "850249267            1        True  \n",
       "850249273            4        True  \n",
       "850249277            6        True  \n",
       "850249283            9        True  \n",
       "850249289           12        True  \n",
       "850249295           15        True  \n",
       "850249299           17        True  \n",
       "850249305           20        True  \n",
       "850249311           23        True  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nwb.electrodes[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1a933448",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'', 'Eth', 'VISl', 'VPM', 'POL', 'CA1', 'NOT', 'VISam', 'LGd', 'DG', 'VISal', 'APN', 'VISrl', 'SUB', 'VISpm', 'grey', 'PO', 'CA3', 'VISp', 'LP', 'CA2', 'MB', 'TH', 'VL'}\n"
     ]
    }
   ],
   "source": [
    "# map electrode ids to brain region acronyms\n",
    "electrode_locations = {nwb.electrodes[\"id\"][i]: nwb.electrodes[\"location\"][i] for i in range(len(nwb.electrodes))}\n",
    "print(set(electrode_locations.values()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e54f5e08",
   "metadata": {},
   "outputs": [],
   "source": [
    "brain_region = \"VISpm\"\n",
    "time_start = 0\n",
    "time_end = 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9f107797",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4178172"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get all spike times from units whose peak channel belongs to the selected brain region\n",
    "region_spike_times = []\n",
    "for i in range(len(units)):\n",
    "    unit_channel = units[\"peak_channel_id\"][i]\n",
    "    unit_location = electrode_locations.get(unit_channel, None)\n",
    "    if unit_location == brain_region:\n",
    "        region_spike_times += list(units[\"spike_times\"][i])\n",
    "    \n",
    "len(region_spike_times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8f536548",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make histogram of unit spikes per second over specified timeframe\n",
    "time_bin_edges = np.linspace(time_start, time_end, (time_end-time_start))\n",
    "hist, bins = np.histogram(region_spike_times, bins=time_bin_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3d036599",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1173a0d3910>]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate plot of spike histogram with colored epoch intervals and legend\n",
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "\n",
    "# assign unique color to each stimulus name\n",
    "stim_names = list({epoch[0] for epoch in epochs})\n",
    "colors = plt.cm.rainbow(np.linspace(0,1,len(stim_names)))\n",
    "stim_color_map = {stim_names[i]:colors[i] for i in range(len(stim_names))}\n",
    "\n",
    "epoch_key = {}\n",
    "height = max(hist)\n",
    "# draw colored rectangles for each epoch\n",
    "for epoch in epochs:\n",
    "    stim_name, stim_block, epoch_start, epoch_end = epoch\n",
    "    color = stim_color_map[stim_name]\n",
    "    rec = ax.add_patch(mpl.patches.Rectangle((epoch_start, 0), epoch_end-epoch_start, height, alpha=0.2, facecolor=color))\n",
    "    epoch_key[stim_name] = rec\n",
    "    \n",
    "ax.set_xlim(time_start, time_end)\n",
    "ax.set_ylim(-0.1, height+0.1)\n",
    "ax.set_xlabel(\"time (s)\")\n",
    "ax.set_ylabel(\"# spikes\")\n",
    "ax.set_title(f\"{brain_region} Spikes Per Second Throughout Epochs\")\n",
    "\n",
    "fig.legend(epoch_key.values(), epoch_key.keys(), loc=\"lower right\", bbox_to_anchor=(1.12, 0.25))\n",
    "ax.plot(bins[:-1], hist)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "44250b4b",
   "metadata": {},
   "source": [
    "### Showing Spike Times\n",
    "Here, a histogram plot of unit spikes over time is created. In the second cell below, set `stim_time` to be the time of the stimulus you're interested in viewing. To get an idea of the stimulus times you might be interested in, access one of the tables in the `Intervals` section, discussed above in **Extracting Unit Data and Stimulus Data**.  The first cell below shows how to access these. Set `interval_start` and `interval_end` to the relative time bounds, in seconds, of the histogram around `stim_time`. Finally, `start_unit` and `end_unit` can be used to choose the slice indices of `selected_units` to display. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5569bac3",
   "metadata": {},
   "outputs": [],
   "source": [
    "stim_time = 1007 # arbitrarily chosen here\n",
    "interval_start = -0.5\n",
    "interval_end = 5\n",
    "\n",
    "start_unit = 100\n",
    "end_unit = 500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4cfaebe2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "400"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spike_times = [elem for elem in units[\"spike_times\"][start_unit:end_unit]]\n",
    "if len(spike_times) == 0:\n",
    "    raise Exception(\"There are no spiking units in this selection\")\n",
    "len(spike_times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d1488828",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(400, 275)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# for each unit, generate a histogram with 275 bins, where bins represent the number spikes per second\n",
    "time_bin_edges = np.linspace(interval_start, interval_end, 276)\n",
    "hists = []\n",
    "for unit_spike_times in spike_times:\n",
    "    hist, bins = np.histogram(unit_spike_times-stim_time, bins=time_bin_edges)\n",
    "    hists.append(hist)\n",
    "hists = np.array(hists)\n",
    "\n",
    "hists.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3fe22c0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Units Spikes Over Time')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# display array of histograms as 2D image with color\n",
    "fig, ax = plt.subplots(figsize=(16,16))\n",
    "img = ax.imshow(hists)\n",
    "cbar = plt.colorbar(img, shrink=0.5)\n",
    "cbar.set_label('# spikes')\n",
    "\n",
    "ax.yaxis.set_major_locator(plt.NullLocator())\n",
    "ax.set_ylabel(\"units\", fontsize=16)\n",
    "\n",
    "xtick_step=25\n",
    "reltime = np.array(time_bin_edges)\n",
    "\n",
    "ax.set_xticks(np.arange(0, len(reltime), xtick_step))\n",
    "ax.set_xticklabels([f'{mp:1.1f}' for mp in reltime[::xtick_step]], rotation=45)\n",
    "\n",
    "ax.set_xlabel(\"time since event (s)\", fontsize=16)\n",
    "ax.set_title(\"Units Spikes Over Time\", fontsize=20)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "34a45648",
   "metadata": {},
   "source": [
    "### Visualizing Waveforms\n",
    "The `Units` table can also be used to view the waveforms of a units with the `waveform_mean` property, which consists of the mean waveform of that unit as measured by each channel along the probe. One channel will contain the peak waveform. With a bit of legwork, the `peak_channel_id` of the unit and the `Electrodes` table can be used to get the single peak waveform as shown below. Just as in the sections above, you don't need to fully understand the `Electrodes` table except that it can be used to map channel IDs to probe IDs. There is also a timewise and channelwise view of all the mean waveforms and an average of the waveforms across all channels. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "32fd8345",
   "metadata": {},
   "outputs": [],
   "source": [
    "unit_num = 950952910"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ae1644bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unit index: 2513\n"
     ]
    }
   ],
   "source": [
    "# translate unit id to row index\n",
    "unit_idx = -1\n",
    "for i in range(len(units.id)):\n",
    "    if units.id[i] == unit_num:\n",
    "        unit_idx = i\n",
    "        break\n",
    "print(\"Unit index:\",unit_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8ede61b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29999.9995000281"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get sampling Hz for this unit's waveform\n",
    "peak_channel_id = units[\"peak_channel_id\"][unit_idx]\n",
    "electrodes = nwb.electrodes.to_dataframe()\n",
    "probe_name = electrodes.loc[peak_channel_id].group_name\n",
    "\n",
    "Hz = nwb.devices[probe_name].sampling_rate\n",
    "Hz"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "e4658307",
   "metadata": {},
   "source": [
    "#### Peak waveform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "32c543e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# use peak_channel_id of unit to fetch the peak waveform index from electrodes table\n",
    "peak_channel_id = units[\"peak_channel_id\"][unit_idx]\n",
    "electrodes = nwb.electrodes.to_dataframe()\n",
    "local_index = electrodes.loc[peak_channel_id].local_index\n",
    "\n",
    "unit_waveform = units[\"waveform_mean\"][unit_idx]\n",
    "peak_waveform = unit_waveform[local_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b01f1b67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "\n",
    "n_secs = peak_waveform.shape[0] / Hz\n",
    "time_axis = np.linspace(0, n_secs * 1000, peak_waveform.shape[0])\n",
    "\n",
    "ax.plot(time_axis, peak_waveform)\n",
    "\n",
    "ax.set_xlabel(\"time (ms)\")\n",
    "ax.set_ylabel(\"membrane potential (uV)\")\n",
    "ax.set_title(\"Unit Peak Waveform\", fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "cc66a18f",
   "metadata": {},
   "source": [
    "#### Waveforms\n",
    "Given the way Kilosort attributes spikes to specific units, most electrodes along the probe will detect nothing for a given unit. As the electrodes get closer to the actual source of the spikes, the waveform amplitude should increase and take shape. To get a very clear representation of a unit's activity through space, the waveforms for a unit from all probes can be plotted. It can be seen that as the electrode gets further from the peak waveform, the amplitude decreases until the unit is too far away to be detected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d30312a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(384, 82)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unit_waveforms = units[\"waveform_mean\"][unit_idx]\n",
    "unit_waveforms.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "c8dd3ee0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZzFVXXeW/7pNPPvFX+zpcOeUZM2b41/g88MADBxUpONDy5cv95Z6P1p133gl4XstbbrnFn8Fq7t1332XhwoUAXHnllYfdJ+hUkZ2dfcTXxPecALp06dLRQxJCiNOSrMERQnSYf//73yxevJiysjIeffRRlixZwrRp0+jZsydGo5GCggLmzp3L+++/j8vlQlVV3n333ZO66HvMmDG89957lJWVcd999zFt2jR/lTOTyXTQ/i9t1Tw48e1/0tr0NB/fudzcXP99rRUYiI6OZvLkycybN48ffviBSZMmcccdd5CamkpZWRlff/01M2fOpGvXrtTU1FBeXn7Esd5444289dZbWK1W7r//fsATsB4us2axWPjiiy+YMGECDQ0NnHvuuVx33XVcfvnldOnSBU3TKC4uJiMjg9mzZ7N161ZeeeUVfzbmaEyZMoWrr76aL7/8koULFzJq1Cjuu+8+evXqRXV1NZ999hnvvvsu4Fl788ILLxz1Y5wMeXl5nHPOOfTp04crrriCYcOG+TN8+fn5fP755/5iD4MGDTpimWwhhPi1kgBHCNFhEhMTWbZsGVdccQXbt29n4cKFLT6Bbi4iIoKPPvrIvxfLyXLdddfxzDPPkJ2dzYsvvujPtgCkpqaSk5NzTP2OHDkSi8XSYurb4QKcQYMGERIS0mLdzKE2+Hz99dc566yzyMvLY9GiRSxatKjF+c6dO/PNN98wefLkNo11/PjxpKSkkJ+f7y/8cN111x0x8Bw1ahRLlizhmmuuIT8/n48//ti/fqc1YWFhbRpPaz744ANcLhezZ89mw4YNTJs27aA2SUlJzJs375DTAE9VWVlZZGVlHfJ8r169mDVrVoesFxNCiDOBTFETQnSo9PR0tmzZwkcffcRVV11FamoqQUFBmM1mEhISmDhxIs8//zw5OTlMmTLlZA+XkJAQVq5cyd13303v3r0Pu5/J0QgICGD48OH+r6Ojo+ndu/ch2xsMBv+6HYDw8PBDFl9ISUlhw4YNPPjgg/Ts2ROLxUJ4eDgDBw7k8ccfZ9OmTUesYtecoihcf/31Le473PS05kaNGsXu3bt54403mDJlCklJSZjNZgICAkhJSWHSpEk89dRT7Nixg+nTp7d5TAcKCAhg1qxZzJkzhyuvvNL/OJGRkYwcOZJnnnmGnTt3MmjQoGN+jBNt3LhxLFmyhEceeYRzzjmH7t27ExoaislkIj4+nkmTJvHGG2+wadMmmZ4mhBCHoejtOclcCCGEEEIIIU4iyeAIIYQQQgghzhgS4AghhBBCCCHOGBLgCCGEEEIIIc4YEuAIIYQQQgghzhgS4AghhBBCCCHOGBLgCCGEEEIIIc4YstHnUdI0jaKiIkJDQ2WTNSGEEEKIU5Cu69TX15OUlISqnnqf59tsNhwOR4f07dt77NdMApyjVFRUREpKyskehhBCCCGEOIL8/HySk5NP9jBasNlsdEkNoaTM3SH9JyQksG/fvl91kCMBzlEKDQ0FPP/DhIWFneTRCCGEEEKIA9XV1ZGSkuJ/33YqcTgclJS5yc1IIyy0fbNLdfUaqUNzcDgcEuCItvNNSwsLC5MARwghhBDiFHYqLycICVUICW3f8Wmcus/3RJIARwghhBBCiBPMrWu49fbvU0gVNSGEEEIIIcQZRDI4QgghhBBCnGAaOhrtm8Jp7/5OV5LBEUIIIYQQQpwxJIMjhBBCCCHECaah0d4rZtq/x9OTZHCEEEIIIYQQZwzJ4AghhBBCCHGCuXUdt96+a2bau7/TlWRwhBBCCCGEEGcMyeAIIYQQQghxgkkVtY4jAY4QQgghhBAnmIaOWwKcDiFT1IQQQgghhBBnDMngCCGEEEIIcYLJFLWOIxkcIYQQQgghxBlDMjhCCCGEEEKcYFImuuNIBkcIIYQQQghxxpAMjhBCCCGEECeY5j3au08hGRwhxGlA13VyGyrYUp1/socihBBCiFOcZHCEEKekMlsdayv2sq4ym7WVeym11QHwl/6Xc0XKsJM8OiGEEOL4uDtgH5z27u90JQGOEOKUUWGv5+09S1hbsZecxooW51QUNHT+s/17xsT0ID4w/CSNUgghhDh+bt1ztHefQgIcIcQp5MENn7K5Og8ABYXe4UmMiO7KiOhuDIhM4fY175FZW8DT2+bw4tBpKIpykkcshBBCiFONBDhCiFPC9toiNlfnYVQMPD3oakbEdCPMFNiizeMDruD65f/ll7KdLCjewoVJA0/SaIUQQojjI0UGOo4UGRBCnBK+ylsDwMSEPpyX2O+g4AagW2g8v+t+NgDPZc2j2t54QscohBBCiFOfBDhCiJOuzmnl+8ItAFydOvKwbW/uNp7uofHUOJp4Luu7EzE8IYQQot1pKLjb+dCQqdsgAY4Q4hQwt2AjNs1J99B4BkemHratSTXyRP8rUVFYULyVpaXbT9AohRBCCHE6kABHCHFSabrGl7me6WnXdB7ZpsIBfSI6Ma3rWACezpxDvdPaoWMUQggh2pumd8whJMARQpxkayuyyWuqJNhoYXKnthcNuL3HRDoHRVNur+fFHT904AiFEEIIcTo5rQKcZcuWcckll5CUlISiKHzzzTctzuu6zl//+lcSExMJDAzkvPPOY/fu3S3aVFVVceONNxIWFkZERAS33HILDQ0NJ/BZCCGa+9JbXODiToMJMlrafF2AwcRfBlwOwOz8DNZU7O2I4QkhhBAdor3X3/gOcZoFOI2NjQwcOJDXXnut1fPPPfccL7/8Mm+88QZr1qwhODiYCy64AJvN5m9z4403sm3bNn788Ue+++47li1bxm233XainoIQopliaw1LS3cAcHXqiKO+fmhUF67u7ClK8OTWb7C6HO06PiGEEKKjSIDTcU6rfXAuuugiLrroolbP6brOiy++yGOPPcZll10GwAcffEB8fDzffPMN1113Hdu3b+eHH35g3bp1DBs2DIBXXnmFyZMn869//YukpKQT9lyEEDArbx0aOsOiu9A1JO6Y+vhTr0n8UraDQms13xVuPGIVNiGEEEKc2U6rDM7h7Nu3j5KSEs477zz/feHh4YwcOZJVq1YBsGrVKiIiIvzBDcB5552HqqqsWbOm1X7tdjt1dXUtDiHE8XNqLmbnrwc8xQWOVbDRwo1dPAUHvsnPaJexCSGEEB1N05UOOcQZFOCUlJQAEB8f3+L++Ph4/7mSkhLi4lp+Smw0GomKivK3OdAzzzxDeHi4/0hJSemA0Qvx67O4ZBtVjkZiLaGcHd/7uPqa3GkgRsXA9roidtQWtdMIhRBCCHE6OmMCnI7yyCOPUFtb6z/y8/NP9pCEOCN8kbsWgCs7D8ekGo6rr0hzMOckeIKkbwokiyOEEOLUJ2twOs4ZE+AkJCQAUFpa2uL+0tJS/7mEhATKyspanHe5XFRVVfnbHMhisRAWFtbiEEIcn111JWyqzsWoqFyZMuzIF7TBFcmefuYXbsbmdrZLn0IIIYQ4/ZwxAU6XLl1ISEhg8eLF/vvq6upYs2YNo0ePBmD06NHU1NSQkbH/E96ffvoJTdMYOVIWJgtxovg29jwnvg+xAe3zocGImK4kBkbQ4LLxU8m2dulTCCGE6Chu1A45xGkW4DQ0NLBp0yY2bdoEeAoLbNq0iby8PBRF4Z577uHJJ59kzpw5bN26lenTp5OUlMTll18OQO/evbnwwgu59dZbWbt2LStWrOCuu+7iuuuukwpqQpwg9U4b84s2A8dWGvpQVEXlsuQhgBQbEEIIIdri9ddfZ8CAAf5ZSqNHj+b777/3n58wYQKKorQ4br/99hZ95OXlMWXKFIKCgoiLi+PBBx/E5XKd6KfSwmlVJnr9+vWcc845/q/vu+8+AGbMmMHMmTN56KGHaGxs5LbbbqOmpoazzjqLH374gYCAAP81H3/8MXfddRcTJ05EVVWmTp3Kyy+/fMKfixC/VvMKN2F1O+gaEsfQqC7t2velyUN4c/fPrK/aR15jBZ2DY9q1fyGEEKK96B1Q9Uw/yv6Sk5N59tln6dGjB7qu8/7773PZZZexceNG+vbtC8Ctt97K3//+d/81QUFB/ttut5spU6aQkJDAypUrKS4uZvr06ZhMJp5++un2eVLHQNF1XT9pj34aqqurIzw8nNraWlmPI8QxuGPNe6yp3Mv9vSdzY5cx7d7/H9d9wIryXdzcdTx/7DWp3fsXQghx6juV36/5xrZwayrBoe07maqxXmNS/9zjet5RUVE8//zz3HLLLUyYMIFBgwbx4osvttr2+++/5+KLL6aoqMhfyfiNN97g4Ycfpry8HLPZfKxP5bicVlPUhBCnN03X2FZbCMDQqLQOeYzLU4YCMLdwAy7N3SGPIYQQQpzKDtzD0W63H/Eat9vNZ599RmNjo3/9OnhmP8XExNCvXz8eeeQRmpqa/OdWrVpF//79W2zTcsEFF1BXV8e2bSdvPexpNUVNCHF6y2+sosFlw6Ia6RYaf+QLjsH4uHQizcFU2BtYUb7ruPfYEUIIITqCW1dx6+2ba3B752UduG/j448/zhNPPNHqNVu3bmX06NHYbDZCQkKYPXs2ffr0AeCGG24gNTWVpKQktmzZwsMPP8zOnTuZNWsW4NljsrU9KH3nThYJcIQQJ8y22gIA0sMSj3vvm0MxqUYu7jSYD/ctZ3Z+hgQ4QgghfnXy8/NbTFGzWCyHbJuens6mTZuora3lq6++YsaMGSxdupQ+ffpw2223+dv179+fxMREJk6cyN69e+nWrVuHPofjIVPUhBAnjG96Wt+I5A59HN80teVlOymz1XXoYwkhhBDHQkNBQ23nw1Nk4MA9HA8X4JjNZrp3787QoUN55plnGDhwIC+99FKrbX3bquzZswfw7DHZ2h6UvnMniwQ4QogTJssb4PQJ79Shj9MlJJZBkalo6Mwt2NChjyWEEEKcSTRNO+SaHd9WLYmJiYBnj8mtW7dSVlbmb/Pjjz8SFhbmn+Z2MsgUNSHECeHU3OyoLQKgbwcHOODJ4myqzuXbgg3c3G08qiKf5wghhDh1uFFw075loo+2v0ceeYSLLrqIzp07U19fzyeffMKSJUtYsGABe/fu5ZNPPmHy5MlER0ezZcsW7r33XsaPH8+AAQMAmDRpEn369OGmm27iueeeo6SkhMcee4w777zzsFmjjiZ/8YUQJ0R2Qxl2zUWI0ULn4OgOf7zzE/oRbLRQ0FRFRlVOhz+eEEIIcbopKytj+vTppKenM3HiRNatW8eCBQs4//zzMZvNLFq0iEmTJtGrVy/uv/9+pk6dyty5c/3XGwwGvvvuOwwGA6NHj2batGlMnz69xb45J4NkcIQQJ8S2Gk+Bgd7hnU5INiXQaObCxAF8nb+Ob/LXMzy6a4c/phBCCNFWHVNF7ei2t3znnXcOeS4lJYWlS5cesY/U1FTmz59/VI/b0SSDI4Q4IXwFBvqFd2yBgeauSBkGwOKSLGodTUdoLYQQQpw4niID7X8ICXCEECeIv8BARMevv/HpHZ5Ej9AEHJqLH4q2nLDHFUIIIcTJIwGOEKLD2dxO9tR7ykaeiAIDPoqicFnyEADmSDU1IYQQpxANFXc7H5q8tQckwBFCnAA764px6xrR5hDiA8JP6GNf1GkgRsXA9roidtWdvF2VhRBCCHFiSIAjhOhwvgIDfSI6oSgndn5wpDmYs+N7AZLFEUIIcerwFRlo70NIgCOEOAF8BQZO5PS05i71TlObX7QJp+Y6KWMQQgghxIkhAY4QosNl+QOcE1dBrbnRMd2JsYRS42hiWdnOkzIGIYQQojnNu2amvQ8hAY4QooPVO63kNlYAJ7aCWnNG1cDFnQYBMk1NCCGEONNJgCOE6FBZtUUAdAqMJNIcfNLG4ZumtrJ8N+W2+pM2DiGEEALArSsdcggJcIQQHSyrdn+BgZMpLSSWAREpuHWNeYWbTupYhBBCiPYuEe07hAQ4QogOlllzctffNHdZylDAM01N1/WTPBohhBBCdAQJcIQQHcqXwTlZFdSaOz+hHwGqiZzGcrZ6S1cLIYQQJ4Omqx1yCAlwhBAdqMJeT6mtDgWFXuFJJ3s4hJgCmJjYF4BvCzJO8miEEEII0REkwBFCdJht3ulpXUNiCTZaTvJoPC7zFhtYWLwVq9txkkcjhBDi10rW4HQceRWEEB3GX2DgFJie5jMkKo1OgZE0uuz8VJJ1socjhBBCiHYmAY4QosNs823wGXHyCwz4qIrKJcmDAZmmJoQQ4uTRaP9S0drJflKnCAlwhBAdQtd1ttWcOgUGmrs4eTAKCusr91HYVHWyhyOEEEKIdiQBjhCiQxRaq6l1WjEqBnqEJpzs4bSQFBjJiOiuAMwt2HiSRyOEEOLXSEPtkENIgCOE6CC+AgM9wxIwG4wneTQHu9RbbGBu4UY0XZL6QgghTiy3rnbIISTAEUJ0kP3735w662+aOyehDyHGAIqtNWRU5Zzs4QghhBCinUiAI4ToEPsLDJxa6298AgwmzvfuifND0eaTPBohhBC/NhpKhxxCAhwhRAdw6xrba4uAU6/AQHMXJg0EYFHxNhxu10kejRBCCCHagwQ4Qoh2t6+hHKvbQaDBTFpI7MkeziENiUojLiCMepeNlRW7T/ZwhBBC/IrIGpyOI6+CEKLd+cpD9w5PwqCcur9mDIrKBYn9AfhepqkJIYQQZ4RT952HEOK0tb3u1J+e5uObprasdAeNLvtJHo0QQohfCzdqhxxCAhwhRAfIbagAoFto/EkeyZH1CkskLTgGu+bi55Kskz0cIYQQQhynU29zCiHEaa+gqQqA5KCoduvzzd2L+bYggy4hsfQKS/IfyUFRKMqxV41RFIULkwbwxu6f+L5oCxcnD263MQshhBCHoukKmt6+Vc/au7/TlQQ4Qoh25dTclNhqAUhppwDnm/z1/G/PTwCU2mpZXbHHfy7EGEB6WCIjorsxvcu4Y9pU9MKkgbyx+yfWVu6l0t5AtCWkXcYthBBCiBNPAhwhRLsqttbg1jUsqrFdAoUNVft4ZtscAG5MG0tacAw76orYUVfE7vpSGlw2Mqr2kVG1jzqnlft6Tz7qx+gcHE2/8GQyawv4sTiT69JGHfe4hRBCiMPROmDNjCarTwAJcIQQ7cw3Pa1TUBTqcVZQK2yq4sENn+DS3UxK7M+9vS5qMR3NqbnJaShnVcVuXtr5Ax/nrGBMbE9GxXQ/6se6MGkAmbUF/FC0WQIcIYQQHU7TVbR2Luvc3v2druRVEEK0q8J2Wn/T4LRxb8aH1Dib6BPeiYf6XEJmTSE5DeXUOJpw6xom1UCPsASmdx3HVZ1HAPDElq+ocTQd9eNNSuqPisKWmnx/kCaEEEKI049kcIQQ7ao9Cgy4dY3HNn/B3oYyYiyhPDvoeu5b/ykbqnL9bRQUwk2BhJsDiTQHkxocTeegaPKaKnkq8xueG3z9URUfiLGEMiKmK6sr9vJD0RZ+133CMY9fCCGEOBI3Cm7atyhAe/d3upIMjhCiXbVHgPPqzoX8Ur4Ti2rkhSHT+CJnLRuqcjGpBkKMFgB0dGqcTeQ2VrKpOo9vCzYSqAZiVAz8VLqNOQUZR/24vj1xvi/ajK7rxzx+IYQQQpw8ksERQrSrfG+Ac6wV1OYWbOCDfb8A8Hj/qVTYG5mZvRwFnfMS0+kfkUyoKRCzYsSgGtB1aHI5+Oe2+WyrLaJfRCI76gt5fvs8hkR1ISU4us2PfU58H55W57CvoZzd9SX0DEs8pucghBBCHImswek4EuAIIdqNrusUNlUDx5bB2VKdx1OZ3wBwS7cJ9I/ozLW//BcFnUAT/FS6lZ9Kt7Z6bUxAKLZGB5k1RXQOiaTIWs1jm7/k7VG3YlINbXr8UFMA4+LSWVyyje+LtkiAI4QQQpyGJMwTQrSbSkcDVrcDFYWkoIijvv7VXQtx6m7Oje/LLd3O5sENn1PvbMJi1HHrGmGmIAZHpjEiuhs9QxOJtYRhVDzBS4W9njCLAQXIa6ghQDWRWZvPO3t/PqoxXJg0AIAFRVvQdO2on4MQQgjRFm72r8Npv0OAZHCEEO2ooNEzPS0+MByTenS/XuqdVjZVe4oI3N3rQl7esYhtNfmYjRo6oOlQZbdSZc8jOSiSa1NHc1nyEIKNFqocDdyb8QE76goJt5ipsbtwuHVQ4J09Sxgd04OBkaltGsdZsT0JMQZQYqtlU3UeQ6LSjup5CCGEEOLkkgyOEKLdHE+BgdUVe3DrGmnBseysLeHjfSsxGTwZFE0HXYekwHCCDCYKmqr49/b5XPTz8/xr+3yaXA5eGjaDtOBYrG4H4WYjDs2NSTGhofOXzV/S5LK3aRwWg4mJCX0A+L5w81E/DyGEEKItfGtw2vsQEuAIIdpR/nEEOCvKdwEwKLIzf9n8FSaDhqJ4Aht0UBUotdVg1+xYVIVgo4kml41Pc1Zy+dIXeTpzLs8Mup6EgAhsmoMQk4rV5cSoGCi0VvPRvhVtHouvmtqikkycmuuon4sQQghxJG5d7ZBDSIAjhGhHBcdYQU3TNVZ6A5zlpbtw6rb9wQ2gKJAUGMllycNICozEpWvY3HZURceg6Ci4+akkk39v/4GXh/2GKHMwTt1FoFHF7vbMSP5o3/I2bwA6LLoLMZZQap1WlpXtPKrnIoQQQoiTS9bgCCHaTaE3wOl0lAHOzrpiKh0NGIAqZ12L4CYxMJIHel/M2Lh0DIqKruvsri9haWkWS8u2s7OuCEUBBZ21Fbv4IjeGl4f9ltvXvkWDy4ZJVXDrOo1uO+9nL+PuXhcecTwGReWS5MG8t3cZ3+RnMDGh79G+FEIIIcRh6Sho7bwxpy4bfQKSwRFCtKNjXYOzvHwnnq07dX9wo+lwWfIIvj37AcbH98ageH5dKYpCz7BEbu0xkY/G3sWcCQ9yT6/JmFUjigJf5K5kdflu/jN0BhbVhKL4ft3rfJa7ijJbbZvGdHnyUABWlu+m2FpzVM9HCCGEECePBDhCiHbR6LJT5WgEjj7A+aV0Jwr4gxu3Drd0P5f/63cZinL4T6MSAyO5sctZzBx9B8FGC4oCr+z6gZ21xTw3+EaMigGDCujg0Fy8vWdJm8aUEhzN8Oiu6Oh8m59xVM9HCCGEOBJZg9Nx5FUQQrQL3/S0CFMQoaaANl9XbW8kqy7fn1TXgVu6ncMdPSYeMbhprkdYIl+Nu5dQYyAAz2+fw/a6Qh7qcwngKVIAOt8UrCe/sbJNfV6R4snizCnYgFv2xBFCCCFOCxLgCCHaxbFWUPuucAOwP3sTbgzhth7nHlVw4xMTEMaX4+8lyOAJsF7f9SOZ1QVMiOuDonh+4bl1N2/uWdym/s6J70O4KZASWy2ry/cc9XiEEEKIQ9F0pUMOIQGOEKKdHMv6G7eu8X720hbZm+u7jMGkGo55HNGWEN4ffQdGxYSuw7eF66m2NxJpDvEWI4Afijazu77kiH1ZDCamdBoMwKz89cc8JiGEEEKcOBLgCCHaRUGjN8AJbnuA80H2MmqdTf7sjYKBK1OGHfdY0kJj+ffQaYCKrsOmmly6hsQCnqlqOjr/3fVjm/ryTVP7pWwHFfb64x6bEEIIAeBG7ZBDSIAjhGgnR5vB2VVXzJu7F/m/1oFJiQOIsoS0y3jGxPbgT70u9JfgXF+5j0ERaYDnF9+ysu1src47Yj/dQuMZEJGCS9f4rmBju4xNCCGEkClqHUcCHCFEuziaAMfhdvH4li9bLNzXdIUbu4w55DVuXaPK3oju2yCnDW7qMpaJCf38v/A3VecQaQr2r8d5cccPbervcm9WaXZ+xlE9vhBCCCFOPAlwhBDHzam5KfHuL5PShgDnzT2L2FNf4lkTo3j2vOkWkkCf8E6t9O3i69wMLv7pJSYs/CcXLn6Bv26azbyCzVTYDj9lTFEU7u19IUbFiKZ7skQOzeU9B5trclhbufeI452U2I9go4X8pkoyqvYdsb0QQghxJBpqhxxH4/XXX2fAgAGEhYURFhbG6NGj+f777/3nbTYbd955J9HR0YSEhDB16lRKS0tb9JGXl8eUKVMICgoiLi6OBx98EJfL1S6v0bGSAEcIcdyKrTW4dY0A1USMJfSwbTdX5/Jh9i+AZ92N799buo1v0c7hdvFFzjou/ukl/rblWwqbqr2PVcs3+Rt5ZOPXnPvj81yx5FWezZzPyrI9rWZXkgIjubHLGHQUTKqRBpedcFMw4Ck48PS2b46YlQkyWrggsT8As6XYgBBCiDNEcnIyzz77LBkZGaxfv55zzz2Xyy67jG3btgFw7733MnfuXL788kuWLl1KUVERV155pf96t9vNlClTcDgcrFy5kvfff5+ZM2fy17/+9WQ9JQCMJ/XRhRBnBN8eOJ2CIo9Y3vm1nQvQ0YkLCKPcXoeuQ4AawMTEfgDY3U5m523gnT2/UGqrAyDGEsLN3c5iSvJAsmqLWFORzZrybHbWlbC3voy99WV8sm8116QO58/9JmM8oArbzd3O5puCDGocjYQazdQ4GjGrRpy4KGqq4oeizVzUadBhx31lynBm5a9ncUkWDzmaCDcHHeOrJYQQQoBbV3C385qZo+3vkksuafH1U089xeuvv87q1atJTk7mnXfe4ZNPPuHcc88F4L333qN3796sXr2aUaNGsXDhQrKysli0aBHx8fEMGjSIf/zjHzz88MM88cQTmM3mdntuR0MyOEKI49bW9Td760vZWJ2DqihU2RsAz/S0q1KHY1INrCrfw+TFL/J05jxKbXXEBYTy536TmT/xXqZ1HY3VbSfQoNInIpbJKb24Oq0/g6LjiA8yEWB08VXeGu5d/xlNLkeLxw01BfD77ufiydkYMCgqDs3lqdymwLNZ3xxxI8/e4Un0DE3AobmYX7T5mF8rIYQQoqPV1dW1OOx2+xGvcbvdfPbZZzQ2NjJ69GgyMjJwOp2cd955/ja9evWic+fOrFq1CoBVq1bRv39/4uPj/W0uuOAC6urq/Fmgk0EyOEKI41bgz+AcPsCZnb8WgNTgGHIay/1T1KZ3HUeTy86jG2dRaW8gISCcW3qM4/KUwVgMJmxuBw9sfJ8V5TsP2beqQoDqZlXlNmasqOaNUb8hullFtis7D+fz3NXkNFYwKqYr6yr3+PffsbodvLJzAff0uuiQ/SuKwhUpw/hn1nfMzlvPdamjjmkzUiGEEALokKpnvv5SUlJa3P/444/zxBNPtHrN1q1bGT16NDabjZCQEGbPnk2fPn3YtGkTZrOZiIiIFu3j4+MpKfHsJVdSUtIiuPGd9507WSSDI4Q4bm3J4NjcTuYXesosl3unnmk6DIxII9oSwkfZq6i0N5AcFMncc//EtWkjsBhMNLrs3JsxkxXlO1FRCDMFEW4KwqyY0HTQNHBrnr4AjKpOnrWQq5a+xN66Mv/jm1QDd/e6AIANlbmcE98Xnf3rgD7NWU6No/Gwz3Nyp4FYVCN7GkrJrC04lpdKCCGE6HD5+fnU1tb6j0ceeeSQbdPT09m0aRNr1qzhjjvuYMaMGWRlZZ3A0bY/CXCEEMct3xvgHK6C2qLirdS7bESYgmh029G9Vc3+1OsCquyNvLd3BQB/6nUeFoMJgDqnlT+uf5uN1ftQUXFqOtV2K1V2K1a3C3SV1OA4LkgcSLwlErcGoKAoYNUbuHHly8zJ3+Afw/i4XgyL6oJDd2NQjKSHJQF4x6Jzz/r3D/s8Q02BnOddKzQ7T4oNCCGEOHa6rqK186Hrnrf2vqpovsNisRxyHGazme7duzN06FCeeeYZBg4cyEsvvURCQgIOh4OampoW7UtLS0lISAAgISHhoKpqvq99bU4GCXCEEMdF13V/hbPDZXBmeaenWQyembE6EGIMZFBUKm/tXkqjy06f8CQmJfUFoMrewJ3r3iKrtoAAgxmnpmFRzVyaPJQH+1zC26N+z5Lz/8qX4+/lyUHX8eHYuxgV0xO3pqP5ltMobp7a9iUPbPgQl+ZGURTu6X0hAAuKt/KbrmdjVr3j0SGrroBlpYf/1OoK7544C4q30uC0HdNrJoQQQrhROuQ4XpqmYbfbGTp0KCaTicWLF/vP7dy5k7y8PEaPHg3A6NGj2bp1K2Vl+2dM/Pjjj4SFhdGnT5/jHsuxkgBHCHFcKh0NWN0OVBSSgiJabbOnvoStNXmoikKZt3KapsO1nUdR0FTN5znrALin9/moikq5rY471v2P3fXFRJiCQVMAhTt6ns9f+k/lmtTRDIxMJci4/xOpCHMQLw6bwe+6T0RHwa2BigFFgeXlWcxY9Ro2t5M+4Z2Y4q2Y9nnuGv7Qc1KLsf5lyxfUO62HfL6DI1PpEhKL1e3gm4KM43rthBBCiJPpkUceYdmyZeTk5LB161YeeeQRlixZwo033kh4eDi33HIL9913Hz///DMZGRncfPPNjB49mlGjRgEwadIk+vTpw0033cTmzZtZsGABjz32GHfeeedhs0YdTQIcIcRxKWj0TE+LDwzHpLZet2RWnid7kxYc479PURRu63kOr+1YjEt3Mya2G6Niu1Fkreb2tW+S21hOXEA4vcKSaXQ76BWWxLWpow87FoOi8vse5/Hi0BmEmYJwahoqBnQd9jYUc+OKl2h02biz53lYVCMZVTkkBUYxJKoL4MniWN0Onsuac8jHUBSFG9PGAPBpzipcmrvtL5YQQgjhpen7Cw2033F0YygrK2P69Omkp6czceJE1q1bx4IFCzj//PMB+M9//sPFF1/M1KlTGT9+PAkJCcyaNct/vcFg4LvvvsNgMDB69GimTZvG9OnT+fvf/96eL9VRO6MCnCeeeAJFUVocvXr18p9vy26sQoijc6QCA1aXg/lFnuICjW5P+WYdSA6MZk99OfMKtwBwd+9J5DdWcMfaNym0VtEpMIrfdT2PFeW7UFH4v35XHLS/zaGMjUvngzF30issCaemedbY6FBoreS65S9iMRi5sctYAF7euZBH+15BoHfdj67DguLN/FK245D9T+40iAhzEMXWGn4u3d6mMQkhhBCnmnfeeYecnBzsdjtlZWUsWrTIH9wABAQE8Nprr1FVVUVjYyOzZs06aG1Namoq8+fPp6mpifLycv71r39hNJ7cQs1nVIAD0LdvX4qLi/3H8uXL/eeOtBurEOLo5R8hwPmxeAuNLjtxljDKbLX+4gKXdhrMS9t/BGBypwH0Ckvg75lfUmqrJTU4lheG/Ia39vwEwPVdxtIrvNNRjatTUBRvj/o9FyQOQEfBoBjRdSi313L98he5KGkAUeZgchsr+Lk0i/t7t9zs7MnMr6l1NLXad4DBxNWdRwLw0b4VRzUuIYQQAmj3AgO+Q5yBAY7RaCQhIcF/xMR4psTU1tbyzjvv8MILL3DuuecydOhQ3nvvPVauXMnq1atP8qiFOH0VHqGCmq+4gG+PHB1AV+gaksDK8j0YFQN3pZ9LRlU2W2vyMKtGXhl2C7Py11FiqyExMILfdz+v1b6PxGIw8df+V9E/ojNOzU2IIQhNhxpnI7eteYObunqmmr25+ycGR6YxOqaHZ4w6VDsaeWHHd4fs+5rUkZhUA1tr8tlcnXdM4xNCCCFE+zvjApzdu3eTlJRE165dufHGG8nL87zxaMturK2x2+0H7QYrhNjvcFPUdtYVsa22AIOikt9UAXgCHKNq4M3dSwG4Jm04ycFRzMz+GYBLOw2j0t7AZzmezMjDfS8j0Gg+5vGZDUb+OfgGoi2h1LmsJAfEounQ6Lbx7t7F9A/vhF1z8cy2ufyl35VYmlVV+75oE8vKWp+CFm0JYXLSQAA+liyOEEKIo6ShdMghzrAAZ+TIkcycOZMffviB119/nX379jFu3Djq6+spKSk54m6srXnmmWcIDw/3HwfuDCvEr93hApzZ3uICgyJTqXQ0+O8PMwWRVVtEsNHCbT3OJrMmj/VVezEoKtelnsVTmbPR0LkgcQBjY9OPe4yxAWH8c/ANnkDLWsGQiO64NQW75mRvYyFmVWVN5V7WVGXz1/5Xtbj22W3fUHeIqmq+dTw/lWT5M1lCCCGEOLnOqADnoosu4uqrr2bAgAFccMEFzJ8/n5qaGr744otj7vORRx5psRNsfn5+O45YiNNbo8tOlaMR2D8Frfm574s2AfgzMJ7qLgo2pxOA33QbS5QlmJnZSwC4KGkwS8qy2FlXRJgpkHt7T2m3sQ6MTOWB3hcDsLE6m4sSh+DWFFy6mwCDAui8kPU9w2O60S/c80GGrkOFvZ4Xd8xrtc/uofGMiumOhs4nOYfOBAshhBAHcutKhxziDAtwDhQREUHPnj3Zs2dPm3ZjbY3FYjloN1ghhIcvaxFhCiLUFNDi3IKizTS5HaQERbPVu0ZF95avrHXaibaEcFPX0eyuL2Z5+XZUFC5IGMSbuxcBcHf6RURbQtt1vFM7j+TS5KFo6Kys2M61KWeh62DTHAQZDNQ4m/jP9u95cdgM1GZp/u8KN7CyfGerfd7kzeJ8m59x2P1zhBBCiOakyEDHOaNfhYaGBvbu3UtiYmKbdmMVQhydw1VQm+0tLjAoKpU6lxWDooInUQIo3NJ9HEFGC+97szfnJvRnTuEGbG4nQ6O6cEny0DaNochazZ83fsSlS5/lzd0LqbTXH7Ktoig81OdS+oQnU+u0srFmL1OShgPgwomCzneFm9hRV8R9vTzZHl9Q9vS2b2hw2g7qc1RMd7qFxNHkdjA7Xzb+FEIIIU62MyrAeeCBB1i6dCk5OTmsXLmSK664AoPBwPXXX9+m3ViFEEfnUOtvsmoL2FFXhEkxUO8NCtzewMY3Te38xL7kNZazuGQrADemjeMX74L+P/S8AEU5fJrd7nby7t6fuH75Cywp20aZrZb3sn/msqX/5O9bv2R3XXGr11kMJv45+AaizMHsqi/GqbsYFNEVAKOqATpPbv2WSzsPJS4gAvAEOWW2Wl7e+f1B/SmK4l+L81nOKpyy8acQQog20GjvTT6lyIDPGRXgFBQUcP3115Oens4111xDdHQ0q1evJjY2FjjybqxCiKNT0OgNcIJbBjhzCzyZjPFxvVldsRsAl6YBngROj9B44gPD+GDfUnR0zortTYPLTqPLTpQ5mH4RyYd93JXlO7lxxYv8b8+P2DUXQyK78n99p9I/IhWX7mZ+0QZuWvUyd617m+Vl29F0rcX1CYERPOMtOvBD0SbOie9LjCUMRQGDolForeKt3T8zc/TtLa77pmAdayv2HDQe3546JbZafirZ1vYXUAghhBDt7uRuM9rOPvvss8Oe9+3G+tprr52gEQlxZmstg6PrOiu861USAiOwa07CTEFU2Zu85xXGxnWn2FrN90UbAfhN1wn8WJwJwJjYdFSl9c9eiqzVvLTjO5aWZQEQYwnlT+mTOT9hIIqicEnyMDJr8vgsdwU/l2ayvmov66v2khYcx1/7X0Wf8P1VEIdEdeGu9At4acf3vLLzB/4x8Boe2/IpqBq6pvN+9i9ckNifCxKH8EPRBgAUBZ7KnMUnZ91NsNHi78tiMHFN6kje2P0TH+5bwaTE/kfMQAkhhPh10zugrLMuGRzgDMvgCCFOrNYCnNzGCoqtNZgUA3sbPCXYVQz+N/y6rjAmtjsf71uGW9cYFtWNfhGdWV6+A4Bxcb1afazvizZw/fL/sLQsC4OickPaOD4/6z4mJQ5qEUz0i+jMkwOv5+txD3Jj2jiCjRZyGsu4bc2bfJazHN23qAa4IW0so2N6YtdcvLF7EXf1vAgAg6IDOrevncmf+1yMsdneOMW2Gl7b9cNB47u680gsqpGs2kI2Vece60sqhBBCiOMkAY4Q4pg4NTcltloAUpoFOL4paX0ikllflQ1AjcOXvYEAg5nU4CjmFK4H4Oau55DXWEFeYwVGxcCI6O4HPVZOQxnPbJuNXXMyOLILH4z+I39Kn0ywMeCgtj4JgRH8MX0ys8c/zIS4vrh0Ny/unMdDGz+k1jseVVF5YsBVRFtCyW4oI6e+nLGxvTxT1VSNWmcjt6x+m3t7TqZZXMRXeWvY4H1uPpGWYKZ0GgTAR/tWHs1LKYQQ4leo3dffeA8hAY4Q4hiVWGtw6xoBqomYZuWcfQFOpDkYt67RNSQOl3cNjK7DiJgufJW/Gofmon9EZ4ZEdWV5mWdK2+CoNEIOKDft1jWe2vY1Ds3FyOge/Hf4rXQLPXRp9wOFmQJ5ZtCNPND7UkyKgV/KtzN91cts8WZZoiwh/G3A1SgozCpYx9lxfYk2h6IqnkzO7oYSVlXuIdIchs7+qmpPZs6i0WVv8Vg3dBkDwJLS7WyrKWj7iymEEEKIdiMBjhDimPimp3UKivRPEXO4XWR4MxvF1moAwk0h/mt0XWFYVCqz81cDMKPLBBRF8U9POyv24Olpn+WuYGtNHkEGC4/0vfKY1rYoisJVnUfz9qg/kBIUTamtljvW/Y8Pspei6RojY7pzU9dxALy4fT53pXunqqk6BkVjadl2+oaleCvAeYKcgqYqntk2u8WUt64hcUxOGoiOzpOZ3+KSimpCCCEOQfbB6TjyKgghjklr6282VedgczuJ8JZgVlAotdb5z+u6QrWzlia3gx6hiYyN7UWD08aGqn3AwetvchvL+d/uhQDc3WsKCYERxzXm9LAkZo7+I5MSB+LWNf67+wfu2/A+9U4rd/Q4n37hKdS7bHydt5bbu08CPEGOUdVZWp5FnCXSH+QALCze4t/vx+e+3hcRbgpkZ10xn+SsOq7xCiGEOHPJFLWOIwGOEOKY7M/gHLz+JiEgHPBUKiuwVqMonqxHUkAkKyo82Zob0sahKAprK/fg1jU6B8eQEhzt78utazyZ+TV2zcWI6O5c2mlYu4w72Gjhb/2v5dG+V2JRTayu2MXta9+k0l7Pk4OuJdhoYXN1Lla3i/t7XQLsD3LK7DW4dVpMVXthxzx21hX5+4+yhHB3rwsBeGP3Yoqaqttl3EIIIYRoGwlwhBDHpNTmycwkNsuq+AKcJrdnbUqf8GT/HjQ6MCC6EwVNlVhUI+Pj+gDwS1nr09O+yF3J1ppcggwWHu07tV3LLiuKwqXJw3lr5O3EWELZ21DK79a8jtXt4NF+VwDw3t4ldA1J4PH+16CieIMcDRXQmgU5Ds3Fo5s+pcFl8/d/WfIQhkV1weZ28sy2uS2msQkhhBDg3eizAw4hAY4Q4hiVeQOcuIAwACpsdeyuL0EBCpoqPW2s9f72ug5G1fNGf2RMT4KNFjRd8++ZMy4u3d82r7GCN3YvAOBP6ZMPOzVN13V+Lt3KKzu/Y07BGnbUFeDQXG16Dj3Dknh75B9IC46j3F7H79e+QZQ5mMuSh6Gj85fNXzAiujvPDp6GUTGgKmA06Oj6/gwOOuQ3VfJU5ix/IKMoCo/2uxSTamBF+S4Wevf4EUIIIUTHO6M2+hRCnDgVdk+AE+utoLa6Yg8AiUGRFFur6R6awObqfH97Awb2Nnimcp0T3xeArNpCqh2NBBstDIpMA3xT077CrrkYHt2dy5KHH3IMu+uLeHHHHDbV7Gtxv0FR6RIcT8+wJHqGdqJveGd6hyW3mgVKCIzgfyNv5+GNH7Kxeh/3ZLzHw30uZ0t1Lvsay3low8e8PuJ3vDT0Zu7dMBOH5sJk0HG48fenAItLMvkqcjVXp44GIC0kllu6nc0bu3/iX1nzGB3bnTBT4NG+zEIIIc5QHbFmRtbgeEgGRwhx1HRdp8zmyc74MjirK3YBEGgwATAyujuF1ir/NT1C48lpLMeoGDgrtjcAy73T00bH9MCoGgD4MnclW2pyCTKYefQQVdNqHY38e/s3/Hb1y2yq2YdFNXFx0nCGR/Ug3BSEW9fY01DM/KIMXtw5h1vXvso1K57j7b0LyW+sOKi/MFMgLw69mYkJ/XHpbp7a9jVnxacTYrCwpSaPZ7d9y5Corrw54vdYVBOqAmYDuNx6i/U4L+6Yz/baQn+/v+k6nrTgWCodDby8Y8HxvORCCCGEaCPJ4Aghjlqt0+qfBhZjCcWta/4Mjm/qWpQpBB3dX2AgJiCIHCsMj+5GqDeTsdw7Pe0sb/W0vMYKXvdWTftj+mQSAyNbPK5b15hTsIb/7V1IndOzWee58QO4s8dkErxtdV2n1FbDrvoidtUXsrOukI3V2RRZq3gvezHvZS+mb3hnLkwcwsT4AYSbgwGwGEz8Y8B1xFrC+Cx3BZ/k/MJZsb35pXQHcwsz6B4azw1dzmLm6Dv5zarXsGtOzEZPkKOqCujgxM0jmz7hwzF3EWoKxGww8lj/y/jd6reZlb+eKZ0GMTgqraO+LUIIIU4jksHpOBLgCCGOWrk3iIkwB2E2GNlWU0Cts4kA1USDy0aIMYAddaX+9roOZXZPNbFz4vsBUGarZWddEQoKY2J6AvDSznnYNSfDo7tzefKIFo+5q66Qp7Z9yZ6GYgC6hSRwT/qlDInq1qKdoigkBEaSEBjJ+DjPVDir28Gysm0sKN7AusrdbKvNY1ttHi/tnMv4uL7c1+syIs0hqIrKPb0uJj4ggpd3zmd5+Xb6RCSTWVPASzu+p0tIHKNje/Lf4bfyuzWvoyqe4EbX8QdyRdZq/rb1K54ddANG1cCQqDSuSBnK7PwMnsqcw6dn/QGTKr96hRBCiI4iU9SEEEetzLv+Js7ScnpaQqCnPPSI6O5kVO1fFxNoNJPXVI5BUf3V01aUe67pF5FMpCWEnIYyVpTvQEHhwd6XtpiaVmGv476N77KnoZhQYyD39bqMd0f+6aDg5lACDWYuSBzMC0NuYfb4R/ljz4vpGZqES3fzU+kWbl79Ettq8/ztr087iye81dO21xXQOTgaDY1HN31GTkM5fSNSuL+3t4S0ogM6zQulLSvbzp83fYLN7QTg7l4XEmUOJruhjPezf2nz6yyEEOLMJfvgdBwJcIQQR63cu/4m1r/+xlMe2jdtbXBkmj8IAkgMCPXe34UI75Sw5QeUh/48b6X/687Bsf5r3brG37Z+RrWjgW4hCXw29kGmpozxr9k5WjGWMK5LHcd7o+7m3ZF/IjU4lnJ7HXeue4NvC9b4K6FdkDSIvw+8DoOiUmitJMoSTIPLyv0bPqTOaWVqyigmJQxEUcCogkbL6mrLyrbzp/XvUe+0EmYK5IE+kwH43+4lbKjKOaaxCyGEOHNIgNNxJMARQhy1cn+J6FAanDa21niqpRXbagAwKkbwrr8B0HAD+6en2d1O1lZ61uycFdeLWkcj8ws3AHBd2lktHmtm9mI2VO8l0GDmHwOm+QOk9pAe1om3RvyRs+P64dTdPLd9Fs9mfYXdm3k5L2EA/xhwPQZFpdbZSKDRRF5jOf+36TPcusaf+15BWnCcJ8hRwFNywLNPjoLCpuocfr/mLcptdVyQOIDzE/rh0t08kPEJ+Y2V7fY8hBBCCLGfBDhCiKPmKyQQYwljXeVe3LpGtDkEgPSwJFZX7vW31XWdYlsVCgoTvOWhM6r2YXM7iQsIp0doAt8UrMOuOekZmsiQyC7+azOq9vBe9mIAHux9JanNMjvtJdho4akB07ij+0WoKHxXtJ4/rH+DEqtnzdC5Cf14euANGBUDDs2JUVVZXbGLl3Z8T6DBzDODbiTQYEZVPet/PMENuHUdg6Kyp6GE3615k7ymSp4YeCV9wjtR42zi7vUfUe+0tvvzEUIIcXrQaf/NPmVbaQ8JcIQQR63cvr9EtG96WrDJAsCYmJ5sabb/TbDRDMDAyFSivXvm7J+elo5Ld/NV3ioArks9y7/2ptJezxNbP0VH5+Kk4VyQOLjdxu/QXJTZathZV0BeYzmKojCtywReGHIL4aYgdtQVcMuaV1jvzTKdHd+XZwbdiFExoKOhKvBZ7gqez5pL5+AYHu17JbB/I1PdG+Q4NQ2zaqTYWs1ta94kp6Gc/wydRnxAGDmN5Ty44VOcmrvdnpcQQgghpIqaEOIY+DI4sZZQPvAGOBXeoGd4dDfe3rPM39ZiUHG69k9P03Wd5eXeACeuF4tLtlJuryPaHMr5iQMAz7qbv2d+RpWjga4hCdzb69JjGmdOYylLyzLZUVdAjaOBakcD1Y5GGt22Fu2GRnVnWuoEhkX14N2Rf+LRzR+ys76Qeze8ze+6T+KmtAmMi+vNPwdP488bP8KJGxX4Mm8VpbZanhx4LVeljOKr/NUEGlUanRoGPJXVbG4XoUYL1Y5G7lj7Fs8NnsZLw27i5lVvsbYym39um8v/9bus1f1+hBBCnLmkTHTHkQyOEOKoVXgLCLh1N0XWaoyKitXtIMwUiEk1+teigE6DyzMNa4K3ZHN2QxnF1hosqpFhUV34LHcFAFM7j/KXT34/+yfWV+0hQDXxj/43EGAwt2lcuq6zoy6fN/d8zw0rn2faqn/z1t4F/FK+ja21uRRYK/3BjUFRiTaHYlBUMqr2cO/Gt7ll7ctsq8vj1WG/5+KkYWjo/G/PAh7e9D51zibGxvbiucE3YVaNKAoYVIVlZVncvvZtpnUZT5/wZFy6m6SgUNz6/kxOvctOhCmYJreDezLeJ7exnKcHXYOCwqz89Xycs7KdvjNCCCGEkAyOEOKoODU3lfZGAHIaygBPNbUSWw2jonuwsSoX8GQvfJ+g9A1PIT4wAtg/PW1YdDd21hexo64Qi2rkypSRAGRU7eW97EUAPND7CtJC4o84przGMmYVrGJZ2TbK7DX++02KgWFRPRgR3ZO4gHAiTCFEmoOJMIcQagxEURRKrNV8lreMuYVr2VVfyONbPyY5MJrrU8+md1gKL+2ay8qKHdy8+mWeHDCN0bHp/Gfozfx544fUu2wYVYWs2nx+v+ZtHut3JY9t+YRKRx1pIZHkNtagevfIqXI0Em0OodrZwGObP+f+3hdzb+8LeWH79/xn+w+kBEVzdnyv4/32CCGEOE1IBqfjSIAjhDgqlfZ6dHSMioHNNZ69Y9y6BsCY2HTmFW7xtzWpKhpu//Q0gHXeAgRjYnvyac5yAC5MGkyEOZgqez1/2/opGjpTkoZxUdJQwJOZ+TJvHQuKtgKe7IuqKKgo1LhqKbAWonmzRoEGM6Oie3F2XD9Gx/Qi2Bhw2OeTEBjJPemX8Zsu5/F1/gq+LlhJgbWS53fMItocyrWpZ7G4eAtFtiruWPdf7k6/hMuTR/HWyDu4f8P7FFqrMKoKRdYqHtn0CXf3msyru+ZTbKumc3Ak+Y014A1yKh0NhBoDaXRb+df2ufy26zlcmTyMWQXreXTTF7w7+lbSwxLb4bskhBBC/HrJFDUhxFHxFRiINgeTUZXtvc8zZW1UTA921hV7W+oHlYfWdI2s2gIAEgIiWFa2HYDrUscC8MKOb6l01JMWHMe9vS4DoM5p5b6MT3k6cy4ZVTlkVOWwtjKb1RV7yKjZTp61AA0dl6ZgdRqJNyUzPnYQfcM682PJZh7c+D63rvkvM7N/pqDp0KWZI8zB3NJtEl+NfYQ/9byUOEsElY56Psr5GU1xkx6WhFN38a8d3/C3zM+ICwjn7VF30D+iMzo6BhXqnE08u+1bpneZQKQ5hBJbNcnB4YDin65W57Ji8H629G72zyiqxoiorljdDu5Z/6F/jyEhhBBnNtkHp+NIBkcIcVR8BQaCTWYqHDWEGANodNvoE56MxWCiytEAeN7MA/QMTaJTUBQAeY2V1LtsWFQjayt3o6MzKroHXULi2VFXwM9lW1FQeKL/9QQazGytKeDhDZ9TZK3BpBr4fY9zSAmKothaxazCZVQ5HCgojInph1kP4oeSzeyoz+OxLR+hHvA7PrM2jzf3LKBPWArnJQ5gYvwA4gLCD3p+QUYL13Q+iyuSRzG3cC3v71tMqa2GUlsN0ZYQqh1N/Fiykd31RTze/3peGfY7/rH1SxaXbkVVwak7eWnH99zc9WzmF2+g1FZDYlA4JU31gI4KOHUXmu7ZIPTbgvWcFZtOalAMuU0V3LP+Q94e9TsCjW1bdySEEOL0JFPUOo5kcIQQR8WXYdB1z5SwUJNnCtiYmJ5sry0E71QxVfH823x62rZaT/noHmGJzC/KAPZv7Pn23h8BOD9hEN1DEvlo30puXvk2RdYakoMieX/MrdzSbTxWrZEPchdQ5agnzhLOq0N/z6CINDbUbsdocGAyeMo46zpomoKimxkc0YN+4amoKGTV5fPyznlcvuxZ7lj3Jl/lraLUu0FpcybVyJUpY/h87MPc0X0yocZAqhwN6GgYVQM5jaXcuuZVZuWv5G8DrmF6l7O9zxtQdN7NXsJZsX1ICIig3F5LfFAIvrBP8bZzeitELy/fSYTFTLgpkO11Rfxl81do3ml/QgghhDg6ksERQhyVcm8Gx645AKj2ZmzGxKazttIzZU1RdH8G59yE/QFOZo0nwDGrBprcDroExzEyugeZNbmsqtiBQVG5pvNZ3JvxCUtKPcUIzkvoy+MDLkdV4InMT1hcutnzeDG9eKjXVbyTvZhvCtYAEGSwMCqmJyOie1DrcDA7L4N9jRWsLM8BoHd4Cl1DoiizV5FZm8em6n1sqt7Hv3d8S4/QRMbG9uasmF70Dk9GVTyf/wQYzNyYNoFLO43k87xlfJ73C1a3A0UBl+7itd3zWFWxk8f6XUOnoGiey/oGvCuCvspbzaSEARgUlUJrFfGBobg1lXJbnacKmzfIMaqwrbaAToFRNLrt/FSaxas7f+RPvS7oiG+hEEKIU4CuK+jtnHFp7/5OVxLgCCGOSpm9DtCpdTYBYNdcRJiC6B3eif/uWgx4MhSKAl1D4kkNjvVfu622ANDJaSwF4NrUsSiKwlt7FwIwKroX92V8TrF3Str9vS/i2tQRuHQ3f8x4k8zaXAyKyu3dL+LSpJE8vvUzVlTsQEHhT+lTmJqyv9Q0wLQuY1hRvoev89bxS9kuttcWs722GItqZGxsf+ICg8huKCazNp/d9cXsri9mZvZPRJpDGBOTzjnx/RkTk46iKISaAvldtwuYmjKWD/b9xKyClbjxZFk2VO9h+sr/8GCfK/nP0Jt5dNPHNLhsqMDCki2MjO6BQVHJa6og0hzMhLjeLC3f7glyAJcbjAYotFYRoJpo1HRmZv9C5+BoLk8Z1tHfUiGEEOKMIgGOEOKo+DI4NrcT396Uo2N7YlBUdtQWAfunp/n2vgGwu53srisBoNbZRIQpmAuTBrOxKpv1VXswKioZFUVUOppICYriuSHX0js8CYD/7ppPZm0uIcYA/jX4FpICovljxttsryvArBr5W//rmNBsKpyPqqiMi+vJuLieVNobmFe4mW/yM8huKOcnb4YoJSiKR/tcg6porKjYweqKXVQ7GphXlMG8ogx6hiZxa/fzGRvTC0VRiDSHcHf6pVyRPIpXd3/HyoodKAo0uK08vvVjJiUM4eWhv+WvWz6jwFqFQYE1lbvpG55C15B4shtKWVW1g8uTh/JtwXpQFAwqODVPJsemOTGo4Nbg6cxvSQqMZERMt475ZgohhDhpNBQ02nkNTjv3d7o6qgBH0zSWLl3KL7/8Qm5uLk1NTcTGxjJ48GDOO+88UlJSOmqcQohTRFmzKl8mxYBTdzM6pifV9kZqvFkd36/XodH735jvrCvGpbuxGAy4dDdXpIzAohr92ZswYxj5jU10DYnl/TG3+df2LC7dzJf5nnLSj/W9lnBjMLet/S+F1irCTUE8P3gG/SNSjzjuaEsI07uO5aYuY8isLeTb/A38ULSF/KYqHts8i7Nie/Jw3yk80f9aNlXn8Et5FvMK17OrvogHN75P3/AUbu12PiOie6AoCp2D43hu0G9ZU7mTl3fOJbfJsyfQwpINrKncybS0CSwt3cHmmhwMKmTV5tM5KJaxsb1YUb6DuUXrOSehD0tLd+JGwwhoGugKGFQwqDqa7uaBjE/4YOztpIXEHv4JCiGEEAJoY5EBq9XKk08+SUpKCpMnT+b777+npqYGg8HAnj17ePzxx+nSpQuTJ09m9erVHT1mIcRJVG6v8wcwTt2NgsKomJ5k+QsM6N5NPhX6hCX7r/MUGNBx6Z6V9RclDWFd1W421+xDRaWgsZEAg4nnhlzrD27yGst4NutLAG5MnUCEKZRbvcFNUmAU/xtxR5uCm+YURaF/RDKP9b+UhRMf5LfdxmNUDCwv38XUZa/w1p6l9I9I5b5el/L1uIeZlnY2AaqJbbX53LPhXe5Y9yYbqvb6+xsZnc77o+7l3vTLCDZYUBSoczXy2u55FNvKGBjRGdBRVcizlpNZVcDkxCGoKCwty6JHWByBqtnzmnl/I7s1T5EEVQGrZuW2Ne9Q7Wg8hu+WEEKIU5WUie44bcrg9OzZk9GjR/PWW29x/vnnYzKZDmqTm5vLJ598wnXXXcf//d//ceutt7b7YIUQJ1ejy06jy47qrZQG0C8ihQhzEJk1nv1tfOWZe4Ymtih1vK0m3x8Y9QhNJCUomn9s+wwAh1tBR+HRfpfQPTQeAKvbwf9t+RCr28GgiK70C0/jzvX/w6G56B2WzL8GzyDKEkpRUw2f564hs7qAYJOFMFOg9wggzBREmCmAxMAIBkamYFQNLZ5PkNHCn3qdz6XJg3h22zxWV+zlf7uX8F3BJh7qO5mz43pxZ8+LuD71LD7Yt4TZBWvYXJPDnevfYmhkV27qMoER0T0wqgampozl/ITBvLVnAd8UrgZFp9JRT6WjnjBTIPVOO6oCNa4G5hZuYGhUV/Y0FLG7vphIczABmolqRyOKApruOVQ8a5mqHXVc+vO/eW3EzQyIlEy5EEIIcThtCnAWLlxI7969D9smNTWVRx55hAceeIC8vLx2GZwQ4tTiW3+jKgq6N8gZGd0dgI3VOYCnghpA/8iWmZXMmgL/mp1z4vuxsmIHWd6y0Q63ymXJQ7g0eTDgKUH9r+2z2NdYSrQ5lD/0mMLdGe/g0FyMienFPwZcz466Ep7a+h0/lWz31iw7vGhLCBcm9WdypwH0De+Eouz/lCstJJbXR8xgUck2/pX1PUXWGu5Z/wmjY7ozrcsYRsd2455el3BD2nje3/czcwrWkVGdTUZ1Nj1CE5mWdjbnxvcnzBTE/b2vYGrnMby0cw7rqnYD0Oi2+rMzmua5kVGVTagxkLiAcMpstRgUleHRXVlXudf7+oJb9xQhUBSw6zZ+u/p1zo7rx7ODrsFkkCWUQghxOpMqah2nTX8he/fuTWZmJv36HbyI90Amk4lu3WRBrBBnonK7Z7NKvVlA0Sc8GV3X2e4tMOD71Tqg2dSxansDhdZKf3bnnLi+/M2fvVHpFhrPn/tN8bf/tnANC0o2YFBU/trvel7dNZ8Gl40+YSmMi+3Pb1e96388gJExXbkoaQBuXaPOaaXOaaPOaaXeaaXWYWV7XSHVjjo+y13BF3nLCTcFEBcYgllVMRuMDI3szsjonkyI78VZsT15a88SPsheyaqKPayq2EOnwEimdh7G5SlDeLD35dyUNoFPc39hTsFadtcX8/jWz3hj9wKuTxvHJZ2GkRYcz3+G3Mqqiu28vGsu+U0VgHfamaqh6KDqBupdVupdVuICQql01LOhei9jY3uSWV1IrasJVQENPO0Vz7GsLJPxP+7iucHXMy4+vf2/yUIIIcRprs0fAQ4YMIDhw4fzu9/9juuuu47Q0NCOHJcQ4hRU5s3gAP5sTHpYEqW2WupdNmD//jfN18Zk1Ra2KB2d21TO7voidB2MBPL8kOsINHims+2oK+Clnd8CcFu3C9leW8jG6n2YFCN762p5vOIbACyqkSmdBnJDl1H0CEs4aKzF1ioWFG/kh+INaGo9Qftny2HTG8lr2r+mJas2nw9zfibQYGZYlCfYeX3kTfxcspO5BRsptFbz8s4f+e+un5iY0JurU0dwT/rF/LbruXydv5ov81ZSbKvmhR1zeGfvIq5KGc3lKSMZHdOb4VE9mVWwinezF9LgsjUboRuDqoBuoMxWj0U14sbF6spddA2Oo4sxlk3VuSjgz+b4pqy5cXBvxvv0j+jCayOmE2S0HNP3UwghxMnTEWtmZA2OR5sDnKVLl/Lee+9x//33c++99zJ16lR+97vfMW7cuI4cnxDiFFJuq2tRgDLSHEyMJZSfSrPwBTeKAuGmIBICI/ztMmvz/QHR2XF9eXnXdwA4NZUn+l9GF2+FsDpnE3/Z8iFO3c242L4MjezOrWtfB6DBqePWrMQFhHFd2giu7DyMSHNwi/E1uuwsKd3C98Ub2Fid7b9fQSHaEkp8QATR5lBsbjcFjdXsa6hER8eg6lgMnnU/v5Rn8Ut5FgCdg2K5setQLGogP5XsYGtNAQuKM1lQnEnXkFiuTxvF9anjuCFtHPMKM/gk9xeKrFW8k72Ymft+ZkJcP6amjOLqlLFMShjMzH2LmFO4BofmQlFA0XV03UWQGki907Nxqtmgkt1YRqgxgMlJA/mhaIt/Cl6LbI4KmbX7OPvHJ7k7/SJu6DLKvzmpEEKIU59MUes4bQ5wxo0bx7hx43jllVf44osvmDlzJmeffTbdu3fnlltuYcaMGSQkHPwpqhDizOGboubTMzQJRVHIqikE9hcYGBzZpcV1m73rcwB0NEpt1eg6XJgwjCmdBvrPvbRzDsW2apICo7g//Qr+mPEWLt2NS1Nwawo3dxvHnekTMR1QLGBXfRGf5ixjaVkmds0JeKbKJQfFkWCJIdIYSeeQKJKCIukUGEGnoAgizEFU2hv4NGc1n+asoc5uQ1VUogMCibEEUGSrJK+pnA9zfgYgPbQTN3cbSZmtiZ9KdpLdUM5TmXN5ecePTO08jGvTRnJZ8giWlG3jq7yVbK7JYXHpFhaXbqFrSDxTU0ZzW7cLubnLeXyVv4JPcpdi15ze9TVWgk0m3G4Vm9uFQYF6l40FJZuY3GkwK8v3UOVoQMET5DTP5oCbF3d+x8s7f2BCfB9u6jqWfuHJLdYYCSGEEL8miq7rR16dewh79uzhvffe48MPP6SkpIQLL7yQOXPmtOf4Tjl1dXWEh4dTW1tLWFjYyR6OECfUgxs+5eeSrZ7sgwI3dRnPH9Mv5Her32ZD1T6MqoaqwL29Luba1LGAp2DAhB+fwK47SAiIwKbZqXc1EmoM55vxDxJg8FRlLGiq4IaVz6Oh8+bwu/i+aCNf569C18HqNHJf74uY0W1si/Hous43BWv4z85vcesaAJqm4HAbcLoNh/0kK8hgJikogvSwBK5LG87qyr18vG8VdU4roBMXEEjfyARUdNZX7/X3r6DQPyKVcGMYW6qLKLLWAgoGReWc+N7c2GU0gyI7s6ehmK/zVrOgeCM2b9AVbLRwcdIwbkgbT4Q5mNd2zWNWwcoWa5qMGLG53Wi6guoNUoZGdkXBwJrKPd7n7d0vR/FNYPNVXlMAhWhzCJckD+bCpAH0CE2QYEcI8atzKr9f841tyFf3YQhu3ynG7kY7G6564ZR83ifScZXh6d69O48++qi/gtq8efPaa1xCiFNQmbW2xdfpYYlouuZd8N98/U1nf5v8pkpsmgNF8WR2FpZmoOvwRL+r/cENwMe5S9DQGR3di0p7A1/nrwLA6Tbxj4FXcmnK4BaPbXM7+NvWz1lWnultp2J3GtF0BZNqJDU4kuSgSFKCIwk2WihuqqXIWkNhUzVltnqa3A721Jexp76MH4o2MyquM5M6dWVj9V4q7DXYFTsbampAV+kblkb/iM5k1uazuWYfW2py/OOICwzAoJgotzWxuHQri0oy6RGawPi4dC5MHMbtPS7gh+KNzMpfTX5TBZ/nrWBW/mouSR7OTWkTuDF1AvdvfIfsxhIAXIoLowHQdTTdM90go3ovUeZQLkseyvyiTTg1N+jg9gY3Bm8BAgUdlwaVjgZmZv/CzOxfGBKZxt8HTiUpKPL4fwCEEEKI08AxBzjLli3j3Xff5euvv0ZVVa655hpuueWW9hybEOIUU2yt8WdvANJDk8hvrMLq9qwf8W3w2TM0yX/Nhsr9a2Fym8oBCDIEMiq2h//+MlsN3xdlAHBhwlD+b/PHAGiagX8PuYEJCS3L1Oc0lvHH9W9R5ahD18HtNnNL14kMiU4jJTiSuIDQw65HsbucLC3fxsKSDWyq3otDd5DVsJOsBm8DBYIMATS57KBobKvPZlt9NtHmcG5KG4+qGNhak0dmbS6Nbhtgw+L9barrkNdUyHvZxbyzdynhpiDGxPZgRtp5WAwqX+V7pq/Nyl/NnIJ1TOk0lGcGzmBV5Q7+t3sBTZpt/2upAOjouk6Nq5Z5RevoE5ZCtcNKflNVqwUIjKqOS9PRUVGADdU5XLH0RaZ3GcdtPc85aHqfEEKIk0PH8zejvfsURxngFBUVMXPmTGbOnMmePXsYM2YML7/8Mtdccw3BwcFH7kAIcdrSdI1qZ4P/6wCDieTgaBYUbQF0//qbTkHRLTbUXFK2DUWBIIOF3fWetToTEwY275rPcpfh0t30DUvlqW3f4NLdoCv8Z+gMxsT2bNk2ZwWv7v4OHQ1Nh9TAzjw/5HpSgqOO+BwKmypYULKBhSUZFFmr/PcrKJgUM3UONy63SrAhmBtSJ3BJ8kDe2LOQBSUZuLFT6ajlk7wlKMDAiK7c1OVswk3B1Dqa2FKTS2ZtLla3A6NBw2jQQFdpdDfwfdFmvi/agorCgIgULu80lr0NBWytzeXbgrV8V7ieCxMH89rw21lalsknuUtxeKe1gSdwUQAMGjsacgGVHmHx7K4rQ0EB75Q1dF+QA25dx63pqKg4cfNO9hJmZv/CuNhenJPQm7PiehBpkd/bQgghzjxtDnAuuugiFi1aRExMDNOnT+e3v/0t6emyB4MQvxY1jiY0XfMHMj1CEzEoKttqfQUGPJ8bDY/q3uK6bd7NPOMDwsmzloAOt3c/33++2tHAt4VrAMhvqMWqWQF4vP+1LYIbq8vOn9a/R1b9PgB0zcDt3SczvetY/xoTXddx6m5sbgdWtwOb99hZX8CC4gy21ub4+ws0WDgnbgDnxg+kX3gagQYzS0p38p+sH9nXUMHzWQuYuXcl4xN68nCva8lvKuezvOXYtAaMBp1NNdlsqvFkp8yqkT5hnbkudSzhpmB21hWzuHQzDs2FxQhhqopJsVBmtbGpJo9NNXn+1xDFSYG1gnlFGfxYspnfd5/EF2Mf4oN9P/NNwWo0bwbHx/NUNfKsxQSYVBTdgNXlxrcDke4LchRP0OnWNDTNs57Hrbj5uWwbi0qyUFAZEdOFq1OHc05CL8nsCCHECaaheD6kauc+j8YzzzzDrFmz2LFjB4GBgYwZM4Z//vOfLd7jT5gwgaVLl7a47ve//z1vvPGG/+u8vDzuuOMOfv75Z0JCQpgxYwbPPPMMRuPJ2ZS6zY9qMpn46quvuPjiizEY5A+hEL82ZQeUiE4PSwRgW00BsH+Dz9HNgpI6RxP1TisoUOv07DuTHBRHpCXE3+bLvOXYNSfR5nBKrLWoisK1ncdxYdIgf5tGl52py/5FvduzD0+cOZZXh91Cp2DPupIPcxbzWe5Smtx2fzGA1igopAbFEhcQgUvXyKjezcqKLLqGJNIjNIkeoZ14YfhUNlQW8PrOpZTb6/k6N4OvczMwKCr9I5KJNAewtW4fDa5GDKpGkEnFoblaBDyhxkBmdJmAjsK3BWsot9dhx0moRaVbSBI2l8L22lJ213s2AFUUA5FmE1bNxiu75rOsLIv/63cV16aO4+29C/mxZJP3Geho2v4pgigauuLAYvJM+2tyOnG4de+UB8WzLkf1bM2q6bo3+FEwGkDT3Kyp2MuaimxiLaFc2XkIU1OHkRAY3pYfByGEEGeApUuXcueddzJ8+HBcLhePPvookyZNIisrq8XsrFtvvZW///3v/q+DgoL8t91uN1OmTCEhIYGVK1dSXFzM9OnTMZlMPP300yf0+fi0OcA506ujCSEOr/kmn+ApEe3S3OyoKwZ0/5vu5gUGvilYB97pVTXOehQFrk89y3++wWVlVsFKAIobGzEYFAINZm7vMcnfpt5pY/qKN6h3e9bbXJUyjnt7TfFnbZaVbeWtvT8cNF6jYiDAYMKta9jdLjRPLoScpjJymspatN1QvYcN1Xv8X1tUEz0i40lX4ii11lDtbMSpucix7yDXAagQYAKX20CNDYLUECYmpWNQNTbV7KXCXse7+xaSEBDJHT0uxICBrwtWsaUmh131noDwnMSepAYlsrW6mA1VuVTZXRgUAyaDm801Odyw4j/c0nUif+13LTelTeCT3GUsLN6EpngCOF3X0XUFRfG89k1uK6hgVsGkGLG73bg1z4IpxRvs6Lon2NF1HVWFMGMQLjeU2+t4c/dS3tq9jPHx6VyTNpwxsd1kXx0hhOhAp8I+OD/80PLv58yZM4mLiyMjI4Px48f77w8KCjrkdjALFy4kKyuLRYsWER8fz6BBg/jHP/7Bww8/zBNPPIHZbG71uo501Hmjc84557AlR3/66afjGpAQ4tSU3VBG8//1e4Ylkt1Q5tm00ntfgGomotnmmz+VbAU8AYMTOwbFwMWdhvnPz85fRYPLhgEjeN+4X5kyyl9drdZh5bZVMylxFKMqcFHiUO7rfbH/+lJbDf/c/iUAV6eM4/rUs7GoZgINZirsdfx16wfsqPdlmBQSAiJJDY6jc3AcaUGefy2qid0NReypL2J3fSF7Goqxuu3+63wMB7zXVxQwGd2YjKBpjXxftJn0kM48P/A2dtTn8k72Akps1TyV9Rm9QpP5Q4+LsagWPs5ZwpKyTNZW7mJt5S6GRXXn30OvotxmZWFxJhurcjAaXKC6eXPvQj7KWc4NqWfzp56XcHv3i/g87xe+zl+JQ3MBvj+Q3qlpqqeSnRMXqgqq6snaaLqC1izYwRvsNLmb0HQIMZmJMoWT11TFktIdLCndQVJgBFd2HsKlKYMlqyOEEB1A0xWUdg5wNG9/dXUtP5S0WCxYLEcuSV1b66mWGhXVcl3rxx9/zEcffURCQgKXXHIJf/nLX/xZnFWrVtG/f3/i4+P97S+44ALuuOMOtm3bxuDBLaugnghHHeAMGjSoxddOp5NNmzaRmZnJjBkz2mtcQohTzK66YsDzxt6gqHQLiWd+0WY8BQY8a0TSguP87e1uJ7sbPNc4dRcoMDSyu78Agc3t4PO8XwBodOiYjJ4KbFNTRgNQbW/ktlUfkGPNx2yEOEs4D/W5wt+/W9d4atun1Lus9ApN5vbukzGpnl9payp38I/MT6lzNRFmDOLhPlczPKonAYbWP0VKD0v239Z0jUJrJbvqC6l1NBJmCiLUFEiocf+/JsXAazt/ZE7RGhTVjqrqBKgucmzZTF/9H0ZEpfOH7pewoy6fuUWr2VFfwJ82vMGYmN7c2vVCbu0+iY9ylrCgeCPrq/awvmoPfcJSuL7LOJ4YcDlLS3fyRd4KyuyVNLqb+N/e7/nfnkWMi+vN77ufy2+7ejYL/XDfEprc9v1PRFdwe6eweQ7d+/3SMTQLdtyagtIss+PUHZQ4yjEbFYINgVhdLoqs1by6czH/3fkzZ8X3YGrnoYyL69migIQQQohTU0pKSouvH3/8cZ544onDXqNpGvfccw9jx46lX79+/vtvuOEGUlNTSUpKYsuWLTz88MPs3LmTWbNmAVBSUtIiuAH8X5eUlLTDszl6Rx3g/Oc//2n1/ieeeIKGhoZWzwkhTn/5TRX+22nBsVgMpv3rb7wfQI2M3l/6eW3lHty65plKpXiWPd7c9Rz/+e8K11HjbPRmFjz3nRXXm8TASCrtDfxu5fvsaywh2OIG4LF+12Jptm/ORzk/sakmm0CDhb/0uwGTasSta7y/bxHv71uEjk6v0GT+3n86CYFt3wNGVVRSgmJJCYo9bLuH+l3C73tO5I1dS/g6fxUGgwOTQcOguMmoySKjJsvz2uCpINfktrOyYjsrK7bTKzSZyUnDubbzWcwpXMfcwrVk1eXz+NZPCFBNjIntxT29L8CiWPjXjm8osVWD4mR5xRZ+Kd9ChDmUc+L78d9ht5NZk8uHuUsptVUDYDB4p6L5gx0FVdFbDXY8U9b2f3qo6wo2rcE71c2TGUKHlRVZrKzI8gREKISZQugVlkTv8CS6hMTSJSSGtJAYgoztu2HdqUjXdRpcdmocjVR7jypHA7quMzy6G4mBERRaq9nXUMa+hjKyG8qocTQSYwklLiCc+IAwYgPCiQsIIz4gnHBTkGzEKsSvlO/3cHv3CZCfn99io8+2ZG/uvPNOMjMzWb58eYv7b7vtNv/t/v37k5iYyMSJE9m7dy/dunVrn4G3s3YrbTBt2jRGjBjBv/71r/bqUghxCmm+BqdnmGefG08Ftf1vkc9N6Otvs6B4k+eGN5sQYgyif0QaAE7NxUe5PwPgcKsEGBXcus5VKWMot9Xzu5Xvk91QRniAZyvLi5OGMzRq/y/RrTU5zNz3IwD3pl9OSlAsNY5Gntz2CWurdgFweafR3NXzUsxqx1VwCTcH8XC/yUzvOoZXd/7MvIINmIwujAYNVfFmthRaZlmAHfUF7NhZgEkxcFZsXx7pM5XshlIWl26hyFrFT6Vb+al0KxbVxOiYdEbF9GBnXTG76gpxKxq1znq+KVjFNwWrCDJYGBPbiyuTR7Omchebqvei+QIa3Rc7qmiahg7eYGd/lqflrgmt/6X1BEKArqADjVoN66pqWV25Hbeu+u8PNQbSJzyJC5L6My6uJyaDgXqnlTqnlUaXHbNqJNQUSIjRQogxgCCj+YSu83HrGkVN1RRbq/3BhRsNt67h0jRcuhtN11AUFdVb26jEVsvm6lw2Vuewu76UGnsjLtwt+lUOcbstjIqBMFMgoaYAggwWAgxmzKoRk2og0GgmOSiaxMBwwoyB2DUXTS47VrcT0An2vo7BxgBCTAH+ryPMQYfMVgohfh3CwsJaBDhHctddd/Hdd9+xbNkykpOTD9t25MiRAOzZs4du3bqRkJDA2rVrW7QpLS0FOOS6nY7Wbn/5V61aRUBAQHt1J4Q4xdQ7m/y308MSsbud7KkvRWF/BqeHt7KaU3OxvHwHAKr3TfPkxCH+T6oXFG+kwl6HpnveFNv0JroEx5EcGMPNK94jt7GSqEAjLuxEm0O5s+fkZuOw8o9tn+DWNc6LH8wFCUPJqs3j8cwPKbXVYFFNPNBrKhckDj0Br4pHYlAETw2+ghndxvDKjsUsK9mJho6ieMpqq6on2IkNCALFQaPbUwrbqbv5uWwLP5dtIcocyqCIrvQKS6TMVkteUwX1TitLy7ai45kW2Cu8E9HmMHIaK8lrLEdHp8ltZ1HJZhaVbPZUegvvQqDByLa6PBpcNrxbyfnLe+Odn+3WdBQU73dHx/fWXEH3F4aAZtPdABRfAKSDN1Ok6Rq6ruDSFJq0BtZX72Z99W6ULN+rc+i3/AqKJ9gxBRBmDCTUFOh/sx/mvR1mCiTOEubNfoQTagqg3mWjxtGE1eUgLSSWIOP+N/O6rmN1O6i0N7C3vpRN1Tlsqy0kr7Gcakej5/ty0Eh078+xNyL0ZsD0Q4z/SCGZfsgvWjx5FMClu6lyNFDlaN8ZENGWUDoFRpIUFEWnwEg6BUXRKSiKMFMgDs2Fw+3CrrlwaC6cmgu720W9y0qV3TOWakcjlfYGquwNVDsaMKtG0kJiSQ2OJS0klrRgz5EYFIlBilEIcUxOhSIDuq7zxz/+kdmzZ7NkyRK6dOlyxGs2bdoEQGKi52/+6NGjeeqppygrKyMuzjNV/ccffyQsLIw+ffoc3RNoJ0cd4Fx55ZUtvtZ1neLiYtavX89f/vKXdhuYEOLU0eiy49T3f2rdMzSRnXUluJvtixNsCPJ/Gr+uci82t8NfrQtgaucxgOdT9Lf2LgDA6TIQE2TCZocrUkZy97rPyG2sJCEwGLtSDTrc2+sywkyehYy6rvPvHV9TYqsmMSCKe9Mv5/O8Zby5dz5uXaNTYAxPDphOt5DEE/TKtNQzLJ5XRtxApb2BRUVZ/FC0jYzKHDRv6eqiRjugE2g0E2jScOMpFKCgUOWo56eyzS36U1u8b3Szsz7P/8bboKpEmUOpc9hpcjtRFA3Q2FSzz9teJzEgkiCjmVpHE/Uuq38tFICq+AKa/X8QdR3cuuovM60DmndfHbVZ4OML2HxT3kDH2GxqnOad+ub5470/eNK9//H9/dXRqXdZqXfZKKamTa9x8+kcvj1/LIoBVVFx4/JMi2zW/sA/9Yp3zZiqNgtqgNZmifkeyz+Vz/d1s+s8fTZ7fq2ME9/r0eJ+tUUfB494f1nvQzlwasv+K6HSXk+lvZ4t3j2XjleT28Gm6lw2Vee2uN+kGIg0B2NUDf7Mk1E1YFIMmFQDIcYAoi2hRFlCiDaHeP61hBJtDsGmOSm11VJqraXMVkuZrc7zr70Op+ZCVVQM3kNF8d+ODQjzB1mpwTGkBscSYpIPWIU4FnfeeSeffPIJ3377LaGhof41M+Hh4QQGBrJ3714++eQTJk+eTHR0NFu2bOHee+9l/PjxDBgwAIBJkybRp08fbrrpJp577jlKSkp47LHHuPPOO9s0Na4jHHWAEx7espqOqqqkp6fz97//nUmTJh3iKiHE6Wz7AWtteoYlMb9wE/vftkG3kP0LDH8uzfS3VxToHBRLclA0APMK11Hp8JR8PiuuN6srswg2Wsipq2N7bTFhpgCSQszsadAYH9uXCXH7Fzp+X7yen8o8mYp706/g79s+ZU2lJ1M0IW4AD/W+ihBjoL+9U3NR0FRDjb0Js8FIoMGExWAkwGDy3jZ1yKfP0ZYQru0ygmu7jKDcVs/Com3MK9jC1poCFAWsLgWrS8FkgACTy1+kQUUlzhJJ99AEwk1BNLkdNLlt1Dqb2FlXAN6pZyoKLt1NpaMW8PSjAEbFiNXtAu8b/2JbzWHH2TxL4/tXxbePjq8ogeeNtKoohBlDMBtMuHSNJqcdh+5AR8Og7l/j4xmf53of3xS35p8s+m5rOv6Ip1l+qNnlCjr7g5AW7/d9WRD0FtGFelBMoKMqmjcwa/210JsHL628LodOxRzpXOtt9MPs19Ta2HRdQQN0TfHnoPa/Fs1yTYon0dZ8fVXzTJSCp5iHUVUxqUbM3oBEQcGimoi2hBAXEE6MOZQgkwWXplHntKKhY1IMuHQXtY4m8puqyGssx665KLO3rNbUsXSoBUr3f18UIMhoJsIcRIwljM6BccQGhHszgEGEmQIJNwcRbQ4hJiDMX6URPB+aVDrqcWluVEXBoBi8/6qoiuItNy/T/UTHOBUyOK+//jrg2cyzuffee4/f/OY3mM1mFi1axIsvvkhjYyMpKSlMnTqVxx57zN/WYDDw3XffcccddzB69GiCg4OZMWNGi31zTrSjDnDee++9jhiHEOIUtrE6x387MTCSMFMgO71V1XxvGEfFeDb4dOsay8u2A/s/5fZVRgN4c89CAIINYeDNYAyP6smH2WsAuDC5Bz+UrCPYaOG+Xpf5P8HOayzjpV3feNokDOOf27+k0lGHWTXy+26TiTPH8U3eJnIbqshrrCS3sYriphq0I7z5DDSYiLIEE2UOJsoSTLQlxPtvMDGWUDoFRZAUFEGUOfiYFoPHBoRyY9dR3Nh1FKXWOrZWF7C4JIs1FXupdDTgdBswG91YjC5QNErslZTYKzFgpHdYKld3Hsv4uL5U2GuZV7SOeUVrKbfXel53RSfaHIpT06h2NOLUHRhV3xtZT5EBzTfdStFRUAkymrGoBnR0nLobh+b0Z5haD3jwBzz1Wj2+RF7zLI/LraJ790LyZUUU5YD1PtBsipunv7bwZWkOd96fGULxB2XgyTQZDgiKmgcyzeMipdl/fdP2fH0r+08d8OAHP5PWmh04/oMCtSPwvZE3ABj0gzM3h8s+sb+UePOxunQFl+bEpuktri+2l6HX7n8dPAFVK2Py/sf3/3+LzNpBtw7Oo/nON39tW3+JfZk2WhTLOJATG+UOG+WOKrbX56DpoGmKN6OotHjMYJOZQIMRRdGwuu2ezOZhBBsCiA+I8E6TjCA+IJL4gAhiLeFYDCaMiopRNWBUPIdBVbGoJiLNIYftV4hTgX6EKgcpKSksXbr0iP2kpqYyf/789hrWcWtTgKPrulR5EeIEqq2oIyQiGIPx1CjJu7220H+7Z6hn+ld2Qzl439TqOpyb4Mm0ZNbkUe1sRNd1DKrnjfZ5CYMAWFe5h1pXPboOd3Q/n+d3fOO5v6wIHZ1JSb1YWu6ZpvWHHpOJDfBkjN26xlNZn2F1O0gIiGResWcxY+egOEZFDeSVrJVUO/avEWou0GAmxhKCQ3Nhczuxe//1sbqdFDbVUNhUc9jXIMBgIinQE+x0Coqge2gc5yX2JiYgtM2vY3xgGPGBfTgvyTMneXddKZ/nrmFuwSbqbQ6MqobJ4MZk0HArLjLr9pKZuRd0lWhzBIkB0YyO7A+Kzo76PHY3FFDp8Hx67tunx6wacGue4MWgKv71IioGHG5ocDqp1dzNVqIYaZ47UdD9ldYMasvpWwe/0d+f7TmQgurZ30HXvauA3P6Lff35MzMHXqu0frs1+4On1scBLaeaea5R9mc7Dt1zq2NrpclRFhY4OEBp2aUni+CZHqih6bonc+c7f4jg6FBBT/PAcv/z94zjcGP0M7Tsv3kw2SJA9I9p/+B8vxugebbq4KDmoFVROi0CmVZ/BppHnjqe14n9r4+qgGrw/OQ1D1QVBVxYqW9WJ+JIAWOj20Z2YwnZjUdX7jYxMIrhUT0YHtWDoVHd/VNtT3fWBisNNU3EJkef7KGc9jpyH5xfuzYFOH379uWvf/0rV1555WF3I929ezcvvPACqamp/PnPf263QQrxa7Jj7W7uHvsYY68YwV+/uP9kDwfwbPLpkx6WiK7rZDeUNZvuo5Aa7Pljt+yA7M3QqG7+zT9f2en5dCfUGEK+1bNIPsoUTl59A52CIjEY7FjdDgZGdOHSTiP8jzkrfwXb6/JRUTwlk4EhET3ZU9PEm+UrAEgKjKBPRCKdg6PpHBxFiNFCrdPGvvoKCppqsLs9C6odmguby4lNc+FwO9F0nSCjGbPBiFH1zPXX0XFpbqxuJ3XeKmA2t5PshnJvYOfxzNb5DI9J48JO/TgvsQ8R5qN7A9MjLJ7H+l/K3b0mMa9wM5uqctldX8q+hnIUxYXJ4Al4FEWj0llFpbOKzPrdgG+9DKArzd7U6f4NQH0ZHh9dd2Eygsm7hkfFgKYbPJuA6ipOt+6ZAoWKSweXGzzFwnQUNIyqZypa8yleh89EHJA7azE9reW0qYPf4B745vvASVb77zswR3DgePZngJT9gZV/ylzLtq28R2/9/FHSm91QFGX/m+1WHkDHU3jAf9cBUeXhP21tlqlp1q61QOHAbloGP630fFCQe6hgsvUX9fCB6uE/QT5oLZSv4xaXKfvb+oIdDsgg0rIfg2JARUHzhtqarntuHeY19uezDuhT9QXN3v9qaBRbq5hTuIY5hWtQUOgVlsywqB4MiuyCQVE9H7i4Hdg0p/+2XXP6f085NTdObf/vLVVR6BqSQJ+wFNLDkk9awPTnC59i17o9PLvwLww8u++RLxCH1JFlon/t2hTgvPLKKzz88MP84Q9/4Pzzz2fYsGEkJSUREBBAdXU1WVlZLF++nG3btnHXXXdxxx13dPS4hThjzX9rMZpb45evVrP6uwxGXXziqoG1xqW5KWm2lqNnWBIV9gYaXXbvAnMINe7fy+OXsiw8ax487S/xBiol1lr2NhaiKHBZp5HMLlgFQGFjIypG7kwfz7M7PkdB4YHel/sLFpRYq3kr+wfA85Y5QDUTYYhjcaFnXVCkOYjbepxNWkgMWbXFbKkqYHbuZirsHbMvl+8NnklVcesaayr2saZiH09tmceo2G5c1KkfExLSCTMFHqkrv1BTANeljeS6NE/pTafmYl9DBbvrStlYlcvqyh3Uuxpw6U5Q3P6pX8YD3mj6puX4PsFTFR2jiicD4M90+D7Nd6EqLhTdk+UxGhTCTcF0DYmnc1AsjW47xU1VlNpqqHTU+7MtBzIqBm9AqB0UbPhfs1YCoZZvOI/0F1lp5Q1yGzIsNM8itBzLwdmottmfyVCahx34MzPK/vtbBAXNbhzP56uHml9/cBBzcLuWr3PL84fPCultD4AOcf7433Qd+P1uS4eK9w3kgW09vbh1N+7D9tTKa+i7T295nXZAJ7qu+KdrGlTPhybb6/LZXpfPhzltGPohLC7d7L+dHBRDn7AUeoWl0D0kAYNvE94DxuLWNW+Q5GwRQNndTgyKSpeQeLqFJLZpSt2+rblkrdwJ/D975x2nR1Xv//c5U566vSSb3kggJIReQwdRkSZ2bOj1ehVFBa/l6tWfomK5Yq8XFLlYsKEgKE1EpJcQCKSQXnezfffpM3PO748zT9uS7MZEAZ9PXk+eZ59n5pwzZ2bOfD/fCl9+27f54cr/IdGQ2PcDqqGGA4QJEZwzzzyTxx9/nL/97W/cdNNN/PSnP2XLli1ks1laW1s54ogjeOtb38oll1xCU1PTgR5zDTW8ZOF7Pn+7+ZHS39/70I858qyluNF/XpDrlnQPQUVA9KK6jtCiU3YhWZA0ee43p3azNdNjNNXSCL/L2w4B4JrVt4YB6BZt0TqG/RxoSaAk7zroZB7qexaAM6ccxrywPa0116z9LbmgAICFxe6UxS7dhytt3jLveJY1zeKLq/7EtnR/1bilMCmIs+kcvqPHijxHCoUlyzVrRPhefGkgUBI/sPCUGWtRaCoEZauCEBotfB7te44nB1bx+VWCtkgbx7Ys4Pi2+RzZPGtSrmyOtFlYP5WF9VM5d8Yy4PzSbxm/wHMDO3ioZx3PDGxlc7qLdJBCyqDKLcfMH/jaxFGgK913Kt1/ittqhvxhVvSnWNG/gZHCnSMtOqLNtEXqSflZdmb7GfazJWvDSC15cQwxy6XOjmFIr4XSioIKyPgFPO0RcoJR+42FkURlolRhtFWnmAGumO3LJiJtIpZD1LKxhIOnfHJBgWxQIBdq2SvbEqiqeKPKtiu99sq2BPOHLSRSmOTpngpK31vF+A1hYUvbWNgwMSIFlR/TGlFtwyqOy8AI3CPtRGMRxYnMW7X1bTT24na3N9PYyNbGaGuycUsj9h6vpzF+nai1bEQrIwhPUeGjEfiqop9R9wkIJLaQRKRbqmkUt8znhB2lzo5S58RwpM3WzG5WD21jZ7aP7Zketmd6uLNzxYTGuTe0uHXMr+tgQdK8psVbsIWpCCXD95t/fxdqtgOepqu3j29/4Ed89Pr3j9tmPvDozJnaU525PnZl+/m3+S/DOYD1yV5MKCYQ2d9t1jDJJAPLly9n+fLlB2osNdTwL48n736G4b4Uje0NWLZk54Yufn3NH3jTf716r/uu+PMzfPWd3+MNH7uIV7377P02pnVhMgEhICod2qMN3Nu1hkpnkRPbDwbK7mlFK8HxLYuIWiZN8d96nkNK893N2w2Jy/uCxQ3Tedm0Rbzz0TsRCN4+78xS33/uWsnDYZY0gKG8JNCCV05fyjsXLOenGx/lskd+DhiLihSCgjICt0lBnIMIgMDyYWZjIw0RiRAFUsEwQ356jCOucO0Z4xelBEEYtCzQodvW6MDnLNv5c88O/tT5AIXAQqgo7bFGZsWbmZNsYWH9VA5p6GB6opG6ESlus36B7nyK7tww3Tnz3uTGOa5tLm3ROo5uncvRrXPL49KavnyKR3vXs2JgA2uGtrEj242HN8rKU3U8Iy0b4bmzkDjSKtolCLQi0B47cl3syHWFcyNI2A6utEtZuBSanJ8nr/ySg1pB5+n18qP6RhjOaQmJK2x8bQptjmcpGnv8ZZuR+VfMgGXIQsKO0Ogkw4KikA/y9BSG2J0fCPfz8fDxVJ6MopjzAoAmN0mTk6Q5EsfXPkNelt78UOjOtAed/5jWocrtA1RYKLQ6xE6h8FCAK41AawmbgUIWgolnXCtCluZnBA0akbGuaowlFzARulyV3a0qj280JiigaRG6gYnQddCMTxbbFYRKhiJpEFV34+hMd7o0piIBrDia0QcpKBH9sY7FuK6VyZqs5Id6rGQLFValKnfQys7DbUZ0VnnvKTSBDsirLINeDrKV4yn3D4YIN0eStDot5II86SBTdX6KsCpSbFtCErEcItIharnEwlfCjqK0YnO6i+3ZXnoLw/T2DvNo77pR7ZVwPHB8uQjkrf5W/nLnf9Ne30SDk6DRTaA1dOb66cz10z9Gfafzpx/H9HgtfqeGA4saha6hhn8C/rr7Ga7beAfZoEC9E6fBSdDgxFm/cQP+WxqZdthCzph2ON++5If8/Au/5ay3nEL7zNZx23tm9QY+9I0fMvjKCF+/94+cfukpJNz9k3t+3fCu0udp8WaEECZGhLL7z9HN8wC4v7vaPe38GcY97Ufr/4oQRnpc3rqYq1f/Fq3BIsrVR76a60IXtNOnLGVumG560EuXsqaBydQ1I9rB5464iK7sMO966Ea6c+bhKQT4WoE2KXDnJFs4uGEqW29ew67nN2Md7MDBLhkxTKZQPjaBYHqshQYniRSQ8rP05AdIB7kx50JgLCT2WOJhxVdFAcySmpjrEcND6xxDwRArhnbwxIBEaUEQupMJbRGzIzjSJu0Vwkr1xR6rMb+ujRPa5nF821yOaZ1DnRNFCEFLtI5XTD+CV0w/AiAUXHazI9vDhuFOVg1sY0u6m57CIJ4qIOX4GvEARaD2LFRrNDlVIKcKe9xubwi0IqvHbkNgBLpif8GI1MrVaZI1GkXUirKofjoz461sSnexdmg7eeUxHmTJyqFLrQD0F1JjCmd7Q8KKmkQPaDJ+viqeZqJIB7lxr8HxUEx3rrUukcuqZA2lD3sjkBpHmBpLM+NtHFw/kyMa5zEj0U7Gz5Hxc+zI9rNuaBdb0j3syg5gCcmsRCsL6qZycH0H9W48TLMsSwVcO3P9rBveweO963huaBvd+UEKezgvo0mDHpNHjesyV3XQI3+oONoxSf5Y+411z1fQr3Fc/EbGmxW/H/PcUL7+gIqwtbAmEqAJ6PP6qvYtz1XZfc7XikCU75dhr3w9Fa22xXXaFjZT3EZaow3E7SiFoMCgnwmLO5cTchTyHkP9KYQURJqi5t63BcPkGU6Nn4AhbkXoiDUzJdJAMudiyxdG8pwXAl4IaaJfqqgRnBpq+AeiLz/MN9b9jnt3P136rhg0D8DBwMGNrGA3OyKPsvAVi1j3x7X88D9v4JO/uKKqrS2pPu7euZY/bX2OlQM74K2menAaOPrWr3BY83QunL2U49vmMiu579XGixYcgHkh+diU3l16QCstWFDXTm9+mFUD24CioCA4puUg0n6e32x/CCFharSZP4c1cvxA8uHF56Dx+cvuVQgEl1ZYb777/B8Y8IyFRWuYE5vN5w5/Ld9cfS937nyu1A9AwnZ554LlnNA+j4Pq2onZLk8+8ywfdu7B+o+GUptCw6L6mSxrms+cxBTygcfTgxt4rHdNtUCZU/BEHrEmT7QuyoUfPpeC8hj00vTmhxjwUhSUjy0s0OBpn5SXYzjIloRwXSGUFMfq2gp3DG2rOcZhtBbUOZAsaou1QAiJLWy0ctidVmwY3s2G4W5u3PgIlhAc2jiNY1rncFjTdA5rmsGUWD0AUkjmJacyLzmVk9uWVPU1UMjwaM9GVg1sZ0Oqk63pbrpzgyjhm3oxlVafsYRKyoJgkeiOPp7ye7laUsV8oKvcdcZsAyZNENJBjif71/Nk//oJba8oWzkqx15Mry1LbmFmvBKbuEzSaNdT5ySIWg5RyyFpR5kaa6QtWo+NJBuYejGbUl3szPWSVwVyQZ68LuApD1/7BDpAo6qymo20DkmM9j0mjbtS0o6RdGIkrCi2cFBakvY8+vJpuvPD9BRSZP08riWJWArw0DKYlHuXpwO68gN05Qd4vP95btzy573usyW3lft7zWdbyDCJhUBTLmj792BSrnWYOjYlC1QF6dNhIoE9xQyV7tu99Lm3eCMRWqRGZRoc51ofr8+xLE1j9z++pXZPy3+AT7fXT7fXX5WAQ4+wWkklUI4kIhwanXriVoSdz+wg15uloSnJomMXkFMeEsGsRBuH1s/giKb5NEfqWPfcZr5+xbWsHRzEuu2VUKvLWsMBRo3g1FDDPwBaa+7sfJJvrbuFIT+DJSRvnHUaJ7UtZsjLMOilWbliDX/6zX1EOuLUvbydrvwAzn82Ix6wuO+XD/Gqd69iwfKD+NHzD3PnjtWsGypn82KEG1KAZkXfdlb0mUB8V1oc2tjBuxadyFnTFk1q3OuGdpb+PrTBuCZsHN5dKk4Zt6K4ls39O1eXdOAA02ItuNLmZ5seJiCHBVww/Vi+9/xdYVtzef2cY/jUMz8F4PQpS0qxN4/3ruOPux4vaTqnRtp569xTeON91zLs56se7BfNOpwPHHImbWGMi6d8frb5Hn6064/oU+Kg4KjcXFZ8+VGSbQkWfW46j/Q+y6+23Vt1rE1uHSe0LKbzZ1tY8ZXHOeVVx/Lo7SvIZ4c587KlzF0ya0LzlQsKdOb62JTq5OmBzTw7uJUd2W6yyqSxHlM5LMrCUNhSxa8B4CFklrZ6yBRclJ9AI8j6Hk/3b+fp/u3Flpgaq+ewpuksbZrBsqYZzEw0kXQixC235CbT6MZ52bQlvGxamfhordmdG2bN0C7+1rUuTCRRIOPnyQQFsr6xLKX9ArnAqxirGa8UwrgJhvQnFCNLqY4rc6pJBMVUzSJkOcZNSVXUOtEIodDFHFdhTEllrzHLxdc+SgejYmFGnxtDxo1waGKpAiVK2eiMUCcqhLrRDooi/L+fHDuYmIVlfGFUMPYjeCy/KoB8+BqcUL+5QJELABwENrYV4FoKIXSYOS98qfJnAUhZzJinsKqSU0yoWyC0po5D5CXGOrSwbgaL6mbQ7NYRtyNhDJRLxLKJSIdAK7aku7lv9xoe6VlPNsiZ8ciwAK0SBFqWztmMeDNLG2fSHm3ElXZVsc5iCunWaB0tbpKmSBytFGuGd/BE30bWD3eyOzdMxi8UI6sw17QurXNQ6S5m4uSCwQJIhZN00DKAUDkwKqHGBOZuMjr3ibRXTbLG/31ku9XnewTxlxqZhACPrnz4/JkPYn6UIXwe6y+7Ez81uJ7f7yg2FN53HxFAIz9fdR/vP+OivR/EvwBGq1f2T5s11AhODS9S5HMendv7GOhJMdCXMu+95tXXPUxbRyOvf/dptHU0/lPGV8h7rHhwPU/8bR32FIunD93K07lNAByUnMZHDnkti+rLfsxKK+69817z4Dyqjq78AK602RH00fKDhQy/bQ1fvPon7P7QLLZnBhi5hI39ACtvU1ABK/q2896Hfsm/LTyBKw49A1vu3aLTnR9iwCvXlzmqeS5DXpa+Qgon3H1uwlh1jHta2e3h2OaF5AKP6zfeZ2qqCEl3NmMciZTg84e/hk3pLu4NLTpvn2usN2kvxyee/r/ScUWky2tnnMaVj//aaDnD9pc1zeDjS1/B0qbppfE90beOb6z7Ldsy3WZ1eybHy484ns0N3fDpFlJScGunyd4mECysm8GRTQs5sfVQDq6fxVDPMG/6ynsQec2rP/QqhtMZVtzxDCvvfXZCBEcIQcyOMDfZwdxkB6dPOZycKpDyc/Tnh1k1sJnd+UGygcfuXB/d+QG68wMM+WO7QhWFcqVlKU1zMlJAuQWynoOtHbSWJYHckJRB7to1yF27nqsKfBYCHGETtRxilkPSiTAlWs/cZCvtsTraonW0R+uYFmvksoPPpMGJjYobMGPSdOWGWNW/g1UDO1g1sJPnBnYy7OfCUJHKR/ZIu435XC366qrfQCARptiqm6TJjRPogExQIO3nSfk5Un6OgvIxV6ZN8VEWkRYx2yFmWUQtIzC7wsUStkkMEab+7smlGPSyo44tIm2mxRrpzA6SHeV6t2epspLwCUySCzUiLiRmOTQ4ceqdGA1OjPowcHzYM7EXw16WYS9Pys+PQSL30DdGkLcwBSeLqY/9gk+h4KGlQEdj5ANQQUDgBUghicQcrJBgFjX8Gk2gFPlAVbgEVhaCFaOOtUhILWHqMZVIakhy/UDgKYGvLLQW9GfzbBjcwO16w5jHo7UYI3mDE8ZZyTBRg4mBUwQhGRpgS3pgQvNVCUdaNLsJFiRn0B6tJ+d7PLNpI30qQ1BnoWSFm1nJqqHJA8RM8pesB6ZgkLn2pTC1pIokQQqNY5l4vb1ZfarjbihyrRLr0FpXJJCoJCWVhXbHfiYUrZIqJPZCVjnOUZXIYhLugGOhSJJKcWBl7znEtH9e0pwa/nVQIzg1vGjQ2zXEI39ZzSN/Xs1TD62nkN+z28NtP3+Yto4GDj9+AfMXT2PG3Famz2mjfXojMhTuBwYyPLd6J8+u3sHatbtI1kU57ZSDOf7Y+USjTqmt7s5BlB/Q3F6P446+bbTWDPSneeDuZ3noL2t4+onN5AoewYkK/ygPcoAPc9Z3cFrd0fSoLL3286TbUjyV3cAD3c/Sd14KaGTQPDopKB9X2vS2ZtHfn8WTiSRkyu5sI2taFP/UI34f6R5x7bqHuH3DKr5x+KspbMmwduU2tq7vpL4pSfu0RtqnNzElfK3RO6vaOqi+g1UD26FCcDumZT4ZP89jvRtK32sNr5x2FL/b9iSZIIVrw/K2Q/lj55MAzE9OZ0aiif9++qdoNKe1L2F+XQcZv8BbH/oWWZUrWW/ObDuaz6y8rURuWiNJrlh8FufNPKyUSro7P8h3nv899+1eCUA0b1P4eTexlzVzZ7ACUhjmtdWjaUeUD77rLSxrXEBe+TzUvYaHe57n1h2Pseq5dWS+1oI9xeWD+esIPqzgw7P4hrqb7/3lLybLFRIrTGhgC9u4woiyS4wQAl8FpPwsKT87Km7EHP80Tmtfxunt5zM93kouKLAz28uG1E7WDW9n3fB2nh/eQTbIG6ExrFCjdFF4hoTrEXdMFjKlBJ6y8ALzKmZ7Y8Q14muflO+T8rPszptirQ92j86YBhC1bDpiDUyNNdDiJpBSkAsKDHlZ2qN1LGmazglt83nzvONpcuNsy/SzZrCT3nyKIS8X1g/KMRx+LsYAVAc/i5Lr5EAhS28+RX8hg0LTk0/tIdV3RbxBBbJKk/UnFhNkIZhf385hjTNY0jSdJY3TmVfXZpIraE1vPsXmVC/PDuxk7VAnm1O9DBTSJJ0oTU6c5kiCRGgZi9kOdU6UWYkW5iZb6Yg1YEsLT/n05FNk/QJRyyEX+PQXMvTn0/QV0vQXMgwUMmFWNYnS4ClNPgjI4Zd86Y3LlRHvi7FI1fYz44blE5BXFS59EoiaeIdi8g0E4FoEQMbfm+tYcY4nGjOxJwk4pOGV5GiczcuZ/cI9S4kRjLQfjHJbFFX7TRRCmEx2XbkhunJD5R8SAIYUE5RJuhRFcjfecRatlyZ7YeVJKgTmF9cOsGWA0oKYjDIr0U5MOvQVsuzOD5ILCiWrZZX75ziHNrqOii6/Vbo+alGtsBBQGWY3up/K6lSq9FPRvlVJWopkpuqdsYmSANL+5OLLXsqoxeAcOEyI4AwNDe19oxD19fX7PJga/rWQyxbYubmHTDpPfWOchuYkyYYYllUOlt2weieP/Hk1D9y5ik1rTRCjloIg5oAbQeZ9RMEfO25WCLp3DXLXbx/nrt+agE3tWERbkjTPaiYdBHT3jBag7vvrWqJRh0Xz2kkKwa7ndrE+N4Cd07gDAY2tSeKtdYiEQx4YyhZIZfJVdRD0QTbqnBxMCwWI7Tbyj0m29XlcZz2APiqLPjELQxU7ZcF6FuxnBLoOCq/RFHwfLUDMFNTn8wznIlSpwhj9EBGEmv8g1NCNEHJBszMY5jWP/wR7hyax2ie+3ie+dfQ8Zl4m4VXmfNjaAgWbUrvLZErDkqaZPNL7fKnAJBg3lHo7yY/X/xXHMsLIQcnp/LnzWbSGyxe9nE2pLu7tegaAS+edRcbP844Hr2V3YXfpmKZH2/m/9U9B6M50zrTFXHX4BSScSOkauaPzMb79/O9J+zkkgpe1HsWff34/vK2BrFQk7Chvm3MOy8RcLn/FRxlQAY+fuIlvWn9id6Gr+gHcDKLZIUCBLjurYEGgCyVZp3KexkvJWRQGrLD9YmavvPLYmNrOxtR2frTxdqbH2ziu+WBObV/GKW1LOXuqqXuktGJ7ppu1IdnpyQ8a0uRl2Z3vZ9BLoUQ4RqmxpE/U9tGAJWziIokkwrDvMVjImtTIgJQaKYquSpK8b+EHFhViC2iT3nVLuoct6Z4xBdHbdjxT+mwLSZ0To9mNE7NcpBAEWpELTK2NXFhzwxY2MdshaUeocwwpqBNRhjb2smD+LKxWm0yQZ6CQoS+fpr+QZtDLoYpxTRqKOcxKsRSUM34V3d7K58DU5ymoYFQsT4Bm3VAXW1K9PNi9npZIktZIkoQdYWd2kF3ZAbpzw6G7lWlNCo3KmKvCEpJ6J0adHSFmu7jSMSl1RbnuSMYvMOzlGAhJ21hXiaBalBz7WtL4k8j96koL3w9QgUZIsGyr1PtYhHssONIiaUdwhIVCGzdDHZKr0OWw0vXQzEoxIF2UPmutwwx5Cl8pRqtiwJICS0pjTQK00KCNpW80mRkLhvrZUqG1IFByr3MKo1NbjyRIouyrVdxjZBPV9scRXY5sXyPIeWWLY1Yo+vKdpbaEEEjscG6D8l5CY0tjFVK6eL0U6+yUrTbFVUeUFq7y+IuKJ2MRLluiKi1yRXpm1t/Kek5lglvF20ay7BFHq7XJkCelcS0sttebzYzc+F8XNR+1AwahJ5DoXUo5pqtCJUxdAUEQTD5jzIsJQ0NDNDQ0MDg4WCNzE4DWmt6uIbas72L7xm52bOpm+6ZudmzuYffOgdE7CIHjWkYL7itUEIYAOxYqZhPEXXRkNC+P2hbtzUnmzmlh6ZKZRKIOjzz4PE89sZlMwUc5Fqbi4WjUxVwWLpjCgnntrH++k1Vrd5GvSMuabYauk2xkQTPtnjy2Z42retSOQp6Wwz88AxJEIGh9vhXn/hj9PSnys3OG+LSE7Q9JxPMuYr0LGy3s4QIyXSA3G/LvUEQaAwJFya87lXPJ5Kuzo43nSw1GQ6dUmegUH3LhVkZgVKBV6MsegMiBlQmYqYZZMm83M6cNM+hH2DUYZ+CmevqOaWR4Tg5bagIFid+3wFFZcrMyYQwF5AsWg8Nx6uszxFyfJidJo93M+vR26qwkd575ST799M+4u2slp7Yv4ZOHvo73PPxT1mXW4lhmbiSC3nQUpc15e/O84/joknNKVpve/BBfXfMrHuo1rnGL6mZySttSfrbuLrKO0eKf2X4k/7HgfBJ2nPu7nud/7riJoakpIhFVepCPFC+rtKal+Rwh+FTO/1jXwahUvBPXqElMPQxHukjtUFCCoXwA2mVatJ0ZiSZmJBrpiNXTXeji/p4n6cr3jWpnT9fFWNsqLfCVpOBbFAILpawK0bX6uqlyxZHKCF9h3IauiO8ItEApWRXjUXRnkiIkXOHfVfM1RipjPd73FXEzo+NnKuoaSYVEG2ELbeobKQu/aO2qnhFsqbAto20vxqRUWkXH0pIW0x9XBmdXHZOgJPBZQiGl+dUPLLSKIHQMR8SISRdHSuqcCPPq2pkWN+e7wY3hKVMbpy+foTM7SGd2iN25IXryKXrzqYoMfONDKCAbELNc6hsTCBGgKKDQ5D3BkOeFZH4i123ZwjFR7FmcMHMPEIzQbosxtovYPq4d4FjViRSKGQqLluCiu1z5e2FcZ8M6WFAk0GVrUPF6LV7TupIcaIEWVF3fJRew0pjFqFFXjr/YT2V/5XtKle6pYixUaU9t5iYIa3P5SpbutRJpKc2zaVdV3CNVo9A6zKhY7L/aglY8puJ3lqgcc/URVa2jYx626WNmdBq/PPXyceZl/+GFLK8VxzbvJ/+FFd+/GReCTI6Nb/vCC/K4/5GYkAXn3nvvPdDjqOFFjELe4/H717FtYzdSGMtM3+5htqzvYvO6LrKZPKEzbrXUJUDIMH6g4nvPC8yDI2ITxKKomDOKnIiCjwh0ibjk/ICtuwfZunuQ+x7dWN7QEhAru5oRKGQhQOR9ZN5H5gM8rXl2TRfPVrTvuhYq6eLHXfoOM/srV9B9XISpDwYIT5n9Cz4i74P28c7QqLM1Kixgr5QgQLDzoD5kQmG5Gky4CrYnad1ZT+uKBvq2+XQNZwimaoZfBv48sBPKmAm00dwpZR4wddEcEdtjOBvDV0artqcA0mIqYK0FWmlDukokxwiWLdE8091hDor1szAxwMHJXhYm+qizxxCUDgNfC7q9GF2FBDvyCZ55Yzu7ZIIN+Xoy2vhW5/IOkVihRFa29Pnsjm9HCogVmvm3P/2S1dZKAN44+xTe+8hPWTmwkfpYmVim8naJ3Fy5+GwuXXAiQhgf9Lu7nuRb625m2M/iCIuLZixnQ2o71226DRxgm8drreWcd+w5XPX07TzW9xSOnceaA3F06SE+FpmZLMbcfQQhKvrN61DTvCdhUBGQVVmyquzGYYcu612qi11D8PCAEWr8QKK0RBPBFhrHAksGyD1kzTLuTqagZEEVULpY9FJjyYCIXaGk0lVvpZGXXFVeoJ4QxTiGMWq7jrltEMYlAGEsSbVAOeo4S9ryUa3t03htKwArA2RQ2nhUAvR7sKX3WXRPSBhDYbpIpEZCSIhb5gelittVkj9zBdp2gB3V2FYe3xoozZMAojZEouAriRcY654ljFKloAqjBG9LGiVU0T2yuE+xVtRYc1S0bEYti4hl4VhWmEAgT0AWLcrW4GLMiKeKxy+xrYCI5TMyjLDowimESdFujTof5h7ZM8aa2LHa2ksrukyYilbRKmsPZeK1p4xuRShtig7bIdG2hcaWASYJSbnlknIl7LtIUIp9UtHnRPou3kuVRC4ICdXYyoHSiMM+y2UDilahBnviRY9f8jgALmrs7/ZepJgQwTn11FMP9Dhq+AdBKc1XbrmP21es4eLjlvL204+iPrZn7cFQf5o1K7ex5qkt7NjUQy7nkc8W6O8Zpq97mNRw3miNqiIczbsGcG3QGqHClbLiyVxUEmoh0K6FitioiIOOjLCSaG0IRc4QE1HhD6aFQDuSwLHQUcuQnlCKr+yzuI8WGhyJEjbKtRBK4UclqXkuaE18m4+b1ohCwPBBAV6di8xptAX5ZsHwzIDGVXmC6RpvsSJYqBBTVelhq7XRHqIF0tcIVyFmUOZ4QN5S7Jo1QOf0fuQA6EaN5WjiJecDQz5KorAsuxm4VkDCLeArSSoXYSgTIVDlp7Zl6aqxCAH1do4j67qYERlmRnSY6bEU0yMppkVSxK2x/fB9LegsxOjxo0RlQIP0aHOy2FLT4WbocDMcnuzm3JbNpX26CnGezzby7EArm4J6dvlxdnkJRKglVRpW7h6kqWEX8QT46Sjv/9tv6FWD1EfLgnWgBFnPBBVffeSFnDdzGb27+tnSuYubrUf4W49JTLAgOY2D62fyux334+sAW0m8mwYR2QQ3v2UrP3/oKhwrIB7ZO6EpWrMQkiA8hxqBUphsTYiiGaHkhx8oMcLFyDzMLamxpY9jKayQVFqi0hdhzySnSECLWytt+jbtGBJTTDc9Ec+lkpASPkzzYWYzX9kEAbi2IGYTavLNeah0c6nUR1e+j3bBqf69EtUxYROHHvePcmelcVUIa5Vj1KG7k42Fa7nYQpJV2VL2NVuE5H+8/jU02nmmOinygU1GmVdW2RSUPcKiV7wmCImuLk2mKBETVdFZ2eZU1KCPPL7ygVd7SIyejn0TbEY6cgghcCwVKig8CDPGJcbZXwARewQ5hlDQMmNSocvSaG8Qc537jL5GRKiIsCyNZcGo49cj5yDM3ldxPKNnZKQdqPoPXTGOPWFPm1QH6lcUSR1j2+qnoagiQqWUzRRJinELLDrgVbunFffTqNJ3InT7myw5q5i/kJRIq9K1sdripZQhO76SFAILrWWYKVGXLLSWACkMKW60xruSaqhh/2FCLmpjIZPJsHXrVgqF6oDOww47bL8M7IWKF7LJc28IlOJTN93FLY8/V/quPhbhHWccw5uWH07MdQj8gC3Pd7H6qa2sXrGF557YzK5txv1Fg/GvwJjmdcRGRWy0a6MiFqPUaWNBaYSRGA3hkAG6TqBsyzzZQ0EOjbG25IPQUuIRumUbSNAeyJxARR2CmIOK2iAFCw7fhhPxWffELAJ/z+q6fAMMz5GkOwQyorBdHyk1bk7hegF+u8ZyFZG8j3A1OqkRoQZtLH9rpQTFgmsjBWpDfIxwaouyq4wc8ZCC8R+wAo0rPTwlcYQiIn0i0sMWCkspXKlQ2mhfO9wMS+L9LIn3MScyXIoFGQmtIacFKS1JKUk6/JwJNcUjtiaCJirMKyY0SamoE4q4HHspCTR0eQm25uvYXqhjWy7J9kIdG3INpAOnLKBWmAbMXEpadR2JlM3A1mEylgcLFbjGfe2U9qWsGdpSqkrfaDexaUse3ahojGWxrbIb1Mj59AJJzrPI+bZxz8NYyhzLuCM5VoAlyyliR8Y4Vc/I6Pkcz3ogxtiupOUN5WBZyr403p7l/ccfg9neFiaYWTHCAlpyQSlrl1Xp7+q+VIWrT9EigAChQ7cvUZnxajziVj3Cyn5L/Wmg4nxN3jqkqz6LEd8JICp8Don3MysyzFDg0uNF6Q3i9PpRPF2hJEAxNzLIIbE+Do71c3CsjynO6KxrYK7vrLLJKztMBTHSXc6MwtcyfAl8wnct8bQkrSxyWpLTkoI2YnyAIggXveo2zZH5WpIOXDJBhLRyyfouGeWQCRx8ZRk3JxEQFX64Tiii0scWAbaAqDTfx6QXfvYItGTQjzDgx+jzo6SUi0YipSHHQ56LFzhEhCJhedTLAkm7gNaCgrYoKIu8tsgrCw/zPhi4peuv6poNLxVzvsvnq3idFb8vn0WzMJSusBH7jhT2x7xCdNkSYhQYRRfJYl8VZFOMuF/DX0qJD4oj1qJqv6oaO+G+I/823ylsoYhYfulcRCwfRwb4ysyledkUlGWSiOhybZ+93R9F0S4mPRpkHkuE8TChhVIKQ5RsoXFFQEQGRCrfRYArA1yhcIR5d0WAK827AHLKIqdtcsoiq2xyynweVi6dhThdXpxePxam3i72CXJ4Jn8878N7PoD9gBeyvFYc29wffwK5n13UVCbHpks//4I87n8kJp1Frbu7m0svvZQ//vGPY/7+Uo/BeaHAVxlWbPsauzJ3Eo3VEXWaca0GXNmIazXiykZsGcdTKTw1SNbr5+lt65kyq48PLMwTcTWpbJTBVISN6b/wyd/GUV0RUpss0ukY2gflg5oG7mwbL2rhxySecCgMOKiUhZ0V2DltiEc4LiPjjCF5hU8MHQU1LUDN8FGzC9TPTJFwCygdmr8J/fa1xAndFPq8BGMLTaCzAjEAYjBApDWnH/4cRx60CYCTX/8kK9bM5amn5pMbiBCzPdpn9qPykq35JtKzBHazx8zEMEsbd3BwsosBL8Yfug/D1xPNGkQpeFtpENIs4EW/bhk+NLUnsWyFcMx3jU6aVjeFLXQoFBU1uOUHjyUVNhpL+LhWgCsC47df3TsCRUwE1EuPBukx3ckxw86RkNXBxHkNWWXeC0BBgY8CYYpPBgh84zxiCAwmd5IA0lpS0DYKEQoECk1AAUWPEnSFmlpXCGICYgLiAmKh5m6am2aamwaqq13v9qJsytexNtvM2kwT63NNDARRhBBEbA8hu5DxPLM7POpsQ+T6PZf+IMpDPU/iacsQNM8iWxigZUYwBqnRJK0YU6LNSCTpQpZdqR7ceEBDdGIZt0afc/M+Uggqfjeh/SqJXSgClEdc+oFKEa9o2UlYHu1OlnY7Q7uTJSF9nJIAEpCwCiSkR8QKGAwcns81sirbysZsI76uWPbHcKWLCJ+pTgZfCwb9CIOBW7ZgjTlKVSGgUhp5nczRZOdpsgs02zka7TypwKHXj9HrR+n1o6QCZ8Rxlo973Dkc51tTR6c6Va4jAhZF+1ka62FJvJeF0X6ccTJtDfouvX6UvLaYFxkkMuL+URqGlY0UGheNK1TJopa0fJLjWEL/HihtLBsFLfAQ5l0LPAzhsIXGQeMIcITGRuMIjUUY6zNpkjgaQTgGgREYJtumpyTbCwm25OvZUqhjW6GOLfk6urx4BUnZcxuOCGhwctTbWertXClGJ6R9Zr0UJq5JIcgFDlll4ysbX1t4SuJpK/xsUVCGWAZaYoX00dMjYyv3RtQnpxu2RHhf2gXiVoGI5YdW3WJviojwiIgAJcLzh1lrZXiMGsgFDhnlGnLruUgECRnQbOVotfO0OxnanCztTpY2O3NArsvJwLg0R+nyEuz2Den5bXo/XJg11LAXTJrgfPCDH2RgYIBHHnmE0047jZtvvpmuri4+97nP8dWvfvVAjLGGCmit2dzzJ1bs+gJWchgikFWDZPPb97pvawu0VvxdnxhmWuu4m+8RvpJkfYeM7+JriZAQIBjw4gwWTHyIEEbgN65WgpyyKWgLWyrilkeDnSVqFxff4oJnFvw6mWWKM4RE0+Mn2FVoJKdC07fQuNIQ6VzgkJtmE2jBkuRO2l3jvZ4NHBLRAssPX8sJy9bR5ydIqQh+eMkfqRU2AQ1WjmannNGlxU3zavkkf9i9lIKyTfBmWBTQJiBh56lz8iTtHHVOgaSdJ2nnSw/9cpanYqyFOTaNwkIbTZj0qZM5psgsEalwhMYRhqQkpUdUBDihISvQZl59LQkw8SNRqZGYCusSEQp2Y2n4NQEme1EQ5jqyQuIRh7DuhdnfrkoDGwoPFU0q7RPg4aHwtcZHlzy/NaOdMHJAToNWEGgLMDEfDoKIgIQ0FqB2J0e7k+O4ZLloaUGbh7s9gWdgKnDo8yP0+VH6gwgDQYQBP2I+e1H6ggiDfoR0oNmULmvgRTKco6oJq/6owyB5MxeVlhxNk53BkQG7CwlMWgBzlqtco4rvYfBx0X+d0FpUGTw8WmjUNMkcHW6aDifNNCdNu52lzcnSZmdJTFJoOSHeDTzPcGCzqVDHmlwTz6RbQUtmuCmmh68Zboo2Z3QK1+HAYShwGQ5chgI3vJY0DkYLbYXXsC0U9VaBeis/rsWwEnklGVYOKWWzLV/HlnwDnV6CnYUEuwrx0IJQRlEJYIswCFsoXBkQlR5TnCzT3BRT7AxTnCxT7Qwz3fQoQtPrR9jlxXCFotEq0GTncYSmwS7QYJcJr6dhUEkGlcWglgwpSTCC4JkrO4xfokzVSpr7qrGbNUGGVlsLwvciYTIkxQUiQpn7XIALuFXujfuOksduxQvK9NqoN8JjCQdvidFJoovEy9NFpQihEG62l5RJliMVc6PDzI0OV7Xha8hpE6ujKFoIy/eapwVp5ZDTFgUt8bQwli0tyGpJSjmklEtWW+RDmlJE1PJpmMB0Fe9nRwTlRBvawlPGNTUqfaKWR08hyVAQx9NWqQaNLQOill8ulorEEgFJK88Md4BWN2USa2iz3iWlol4GNEifOhmUroPivFWuAYEGD4Efvnta4IXPgojQ5Rd6QoTTC100KXpBFM2nIrRqYdouPnMUIjzHhlircN6L5VuL14sVjt0OLTM2GleELyASun92uFk63PL6+8zAv65VYSRqaaIPHCZNcP785z/z+9//nqOPPhopJbNnz+bss8+mvr6eq6++mnPPPfdAjHO/4zvf+Q5f+cpX6OzsZNmyZXzrW9/i2GOP/WcPa48Yymzlz099BDF1DVYS8oFFT1BPQUssrYgJn7j0SEiPpGUEZVV6eIiSabqo9cpph6yS5LDIK4kOFyNZ2qb4gFa0yBwz7SwxocgoQUZLfNsiCJNa1kkfR2hyWpLWFn1BhLw2vumuCNAIuvw43UEShUUY3YCxCWiMjsos9i12moRVDnBvc9I02lkG/Dh5bYf6trAFO4dEMdUZJCIDlIZuv46ssokHBRrsHBHp0+YM06pTpFUEpQVJK1+VOcfTEhdNQnosivcwa9b99PpxCtqmoCV+KMIWNYUS4/4RET6u8M3oiyZ/AuNuQIATmveTIiApjUuXGwoMe8tMWDwBRU2e8Wke3w1Qh+4b5drvRaFclAiMhSkGKEXoI42Y2DhG9AOVloWyi0bxiim2aB6cRVJkaJavNVmlyQuBjcQWAgcZCkaCmBAVreuQ5BmBM68sHKmIChVqzs21PisyXr0UA18L+vwo3V7ZetDjGwKUCdxQU2oCiWV4H9goItLDFYq4DIhZHm1OmunuEAnL1J9JBzbbC/VsyDXT6SVDchWloGTJlcOtcBOqsz1zzZR+U6Grodmu2cozxckwxc6OsiCMxFBg0x9EQquDRAlRcoHKKpuU71LQkg4nw4LIILPcNHWWz2Gxfg6L9fO6po3jtp0PA+4jodthneVRZ3lAeo9jqoTWkNEWqcAQmKy2iAufeqtAUvpEpSYiFRGZp5U8c9w0J9dVW/gK2qw1gS7aKoGSoGXux5jQ1El/XEEvrSx2Bw4DSjKsoIBGCENktgUSgig2EA2FRhvNcNFFsyprWzE9RNFCGArcaKzwngiKFEFDQVvkQ7cdgJhl1mYZmrwF2rgBYQiNg8LV5npwUTiBsdbmtI2nbXwECqtEegQ6FILFKGE4wJAQFc6ZhaJOFmiUZq1Ka5u0shlSDgUsgtCCboVWQBEKrIa8KSIYy0hey3AcRXe5MrEL5f6qJwcYRUZCaJJCkZCKhFAkhMYWkBTVHh9ixL6avWeEK54gQ44qiFtJ2VTapIIChS5wlLONFUlFQRuX3YwSZEOrWRDfjR/OdRCSLQ/zXIgRkJA+MamIioCE0MSFJirAlXpSQlZxrFZIfEOXiD3vo8tHaIiILq2XntZm/GiiUhhrH+AIiRPW9JJ7YUiBVnjFNN9h+yJ0nfSh5FrrFK/LiuZ8HSrpwvuoSOyTdu8kZqWGGvYNkyY46XSa9vZ2AJqamuju7mbhwoUsXbqUJ598cr8P8EDgpptu4oorruD73/8+xx13HF//+tc555xzWLt2benYXkgoeDl+f//HsWbdQ1tHjhZZoE6awGmb7rASdTlnvaRcDyIItfeqYqEfqWEuQeuSwGshQyuBKLVn0lMVNw1rUYRCazEFZehtDs5YGuahCv9l83/lw6do+SjVuaBIPgQ5LSjYMrQamAe/FuArUbJKxAS4QuBEBwAjeARao0InsOIDG8yDvxiEaQgElU+/cFy9FQ9BU9fDR4eCQxizgEZqwqKPmmJFcRnuV3yvpIzlh66m+KAtdl/yPcfYBeQI8lGsP1Hc3pznsL63GJuslHy2GftBNqq2wzj7l/4WlWLIWLrqMkLbDe6kFUrlHYqWgFjYYKAFOQ1pFVAIz4npxxRDNCSO8ufw3LSHbhv7FVbAPLebUyosUPsLSsOQchhQFmllkVKSIeUyqGzyStBoZWiysyTtYYSW9AUxMthICbZUNDuKSOjeskNrOgsWSaGpl5o6oUhI00cmjLkqaMICkj6RUCmR9YvE3sylcYMr3uUSHVrbjNBkrDieFmS0cWs0yQwKaJEnIhTDQjCswFFGyxsTimio8RWhPVIicATYQoTa4Im5PSttrH8+ZcHKuGMGWCjaLc00K8w+JXTFfaFLa4CsuP/K0R7lu9UoECrqI1WgtK4KI/yX1mNRJEmVi58u7TSWiiC00aKBmNYoChXro1kXAyiRjQBDanSoECmus044tzbVWeGaCMDKownX1zAGSAmIoErubuW4jQoyEM6VjQyz8YVqMK0p/qucleKxaYoWZ1FSsMCeFT06ZC6V7RZjd4pzJcbyE608IROEFQroibBnqE5WMN6nkatr9fFMZBB732bkGl41xyN239N6vrdnwVgoFuXdWx97e45U4m1TVk9425c8tGC/Zz2rWXCAfSA4ixYtYu3atcyZM4dly5bxgx/8gDlz5vD973+fjo6OAzHG/Y5rrrmGd73rXVx66aUAfP/73+e2227jRz/6ER/72Meqts3n8+Tz+dLfkyl6uj/g7ZyPJSSvPqTyWwch3Ant74TX+chcEiMf3gAjgjtGC7aVf4s9L7KTRfWDZOSjRJdlAiEo5oUpifYTtEAUSdlokaIS4z2oKtuobGeClphxxlPqVYye6zEfGHvrSlc8xCY4rok87MY7P2O2N8axTK79UKDRunS8ZeHKEJaEsEmEy5fWGg+FpwPyOiCr/dDNwuxptMwCOxybFZLBIvmpvOyLV0aZnFa68ZS3qdxD67J7yUiXwbIiYKQ2uXxNF7+1wjReqmKfqAjosMCyhLF+mRKk4fhEhUucRpCqmu3icZT71ght7hcjzJv+YgJaw6xepl23+jrTlSK+HOPurIRV1R+64qhFubESKccO7+ly9istyscvAKFFxXVQiWqKbQlwZOWvE78vJ7MtlM/ZRIW68dqvvM8n2lblOla+K8L2Ku69sqW1vGaNPGOlT1U+aCXqUSI0lf2UFRwjjqlKQTT6WCY7x6V9xOhnTyUmmiepmGJ+T2Mc2fde6/+hRx/XxOX8UW0V+4U9r997msuRvxWPeeS1YZSeRvkpR15HY7RfOa49/T4RNE1a8nzpYmT1jP3VZg37QHA+8IEPsGvXLgA+/elP8/KXv5yf/vSnuK7L9ddfv7/Ht99RKBR44okn+PjHP176TkrJWWedxUMPPTRq+6uvvprPfOYz/8ghlqC1Rorxi6yOXKD3uOiNK3TuOzPZlwfWuG39vXk5J9hHtUg0AcG7LN2ZB+0Yi/tkEhFWCnvjnZPK90ohZSQqx1Fqay+HVOleVilYVQo+ExUBRj6QK36oGkpxxmRIJSqPe6yHeekcVQpMlcKaHi0IuFi4wiJBmYT6KAKl8EIrY1mDTMkyWbSSFTXL+0pWR46zONZqoa/6U6XwNpl+R56Via4D+3y/iopzMgmMPP7q9sZpa5ztX2jYF03439NW6boaZw0as92xFDSTkL731kflPTmelXeiGO32OvZYxrRQT6KvsdaevwdjtrHPt9mBudArlS2V31nhqvzPQFCzMNTwD8CkCc6b3/zm0uejjjqKLVu2sGbNGmbNmkVr6z5GrP8D0dPTQxAETJkyper7KVOmsGbNmlHbf/zjH+eKK64o/T00NMTMmTMP+DjBLEK+CrCErBJC1RiC08hH5EiBpPhpLCFzbyhbLSrd3EY/lsezeFSOcWybyYi/J2qRGau1CjKyJ4z1MKkUIqq+LwYp6+qHeUmTOZkH7CQfYuNqS8dAtca2mrhoCF31xthvLwKyCULVYXBt+Uowgnn5WivF9ITjrrRWAATFGha6+nqt+jyOADKZeSgKgC4SLOPaNqamdR+wN/eP/S1Alfqt0MLu0bK6D21WtfV3Eryqtl6IzGQcVFpFRhPIMqo13OOvfaMt5sX1r7q1Mfnc3ynE7wkHQim1x7U0hKpQqYxcl6r2q/hmrDtJaFGyL+nqHUtEvDTXOrRfivK3Y9kdqFgbdNW34/DtPT7nqq1mI49kvOMa+Y0eo6UJWZxK7+Xrc0/PqbEsWpVnam/j39PxVD+Hqo/hmXSMqXs8mn8hVE71/myzhskTnJGIx+MceeSR+2MsL0hEIhEikcg/r//pG9k+NMj5v/g/YtEdnDRnNcs7NjLLTdMoPWKSMNOrDANDRSmjT1E3UxREDUIhV49eECsfV8Ug9cpg9b1BK/OgKPpYC0TJ/7yaeE0MYz80Kr/Z086jGkNXUazQqlARwzKeEFFatsf4udrtbWxMxOVgtPtc+UD2tL8OM5rltY+nTYhzgCCvBJ6W2GFq6WK8kMZoz4aVSbU8qKLklU1B22htY2tBneUx1Ukz1UnTID2T5YuiG1aZkqgwmFWhEWGsk0CghUaOqGJeef4r44yqjklXarMrj7HsNGOup5HX1IjzU+Sp+0A29mSNm6jm/O/tR5fuvfJnUf4xvMeKdHLvwm/ZTW4C93Sp/co5rqKaI67O8v/V35VReZ7GshVWbl+2ClYKauXfRhL24r5ylFuVqLrbxxpxpdpGjdyypOsYf10oulAWrbxlwXuMXoty9ojvRp8JgaWFiXsIz3GlcFh9PkZc8BV/jSXIj/xu7HOgx/1cbGfUV1QKs+UfxnfxLW9fLP5ZsrAKKq7scptCl91KVehqZtY9RV4rghEjLRflJUylLXHC8RRdT6sVNOVjq7xex7y/Ko678hpT4XGoMHtlpatpaVzaxIYW60mZtPuUXGWNe2tF67o8TpMAReCHiQPy2iSW8NF4oRLKFhJXQBRFQmoionysYJRUWSVIKxmmGlcEAob8CAhBk+VTLwPiUpWyWPpaMxBYDAU2njYJK+otn5gMsMJkERZjFXCtPO+E6YTMNr9ZfRRnLx538xpq2C+YEMG54ooruOqqq0gkElXWjLFwzTXX7JeBHSi0trZiWRZdXV1V33d1dTF16gtTpzCjvoGbXvNGXv+bX/Crla3c8ugpzBY9LJq3naltfQyl4/QN1tEzWEd3PkGuUTN3ejfTkoMM+jEKgW3y/QtNRAZELY9GK4cWkqgVEBcmE1XC8kjIAg1WHjvM6uOEQb5umOkpIoIw3bEJKHYrMj0VFziTxausrZdjPG7BCNpBqM0v1n6p3LRSm4UuZwQyi7pZsCOCUQG0I2FcgcYSncuaxeJYy1uMFvBG6iArH1xjH5/JZANmDlypyw/N8J8RrkaJVwDklCilpx1UpsbMNEvTZinSSrAzkKzINLEm284ur4FA20RljpxySyPXQFzmmeP2Ms0dYmehgdXZKXjaKT1wtTaFW4Mw2LEoaAjMOZ7iZJjmppjuDjPDSTHLHaTVzpWSKZRUp3vA6FgUHQou1YJEtQa3TOyKMzRypqpI8EhiM4LEl8Tjin2qk2+MvkJK7h2V7VdspylfHSPbqcRoUjA5jCQBpftrkg1WiayhZXYsweTvqWZWDjYvjk2UFAnVBKM8otL9pStGGN6zlWSr2EqR6BZHrrQqZVZTutxDoMPaMeExmdXKRDGZIoeY9MzoUjrkyqD1yju9aj0qDgiT6S0IhdsgFGBVGEuEVoQJ6bAROMLcx25InMaizBoTa+VpY/Mcq55N5V5Km8yExeyJKmylmpZWZ24MirFRIQ+QhIVmQ4HbtGvWMCFAajNr6UAy4DuklUOAJCo9opZPgCQX2KSVS1q5FLSFEJpmO4eFJh8WrAwUWNpk1mxw8mQCh935JLvzSfr9KFltoyRYjmLYj5Dyowzmo6S9CJ6SJO0C8+L9bE438dxAB4EW1EeyzKgbYHrdAEm3gBdIujJ1dKUb6ErVkQ8cknaOZQ3b6Ssk2JhqIWb7tDgZGp0szU6GBifHzlw9GzLNSEuzpKmTZfW7WBjrZrqbIqttMsrB0xLQxKXJWBoXvsm4FtbUKecoNdfigB9jdyFJbz5BOnBxbI+2eLpqjofzMQZyMTIFh7jj4do+67qnsGLbXLKZqGnNBe0qtKVBC4QqrmOauniGeS09tMXS9OdjdKfr6UvFyeajOFpxULKfVifDpv4mtg82oKWFthXSDbAiAUgoZG0IJASGTDbHhzh7/nO0xtL85NETSKeTmDA9YYpsC41QAjyNkAJlB7S3DTJ/ShdzGvtxLY/t2Ua2DTeRzkdAm9TdMdsjEcuz8rGZcDE1QC1N9AHEhAjOihUr8Dyv9PnFDNd1Oeqoo7jnnnu48MILAVBKcc899/C+973vnzu4PeCg5hZ+fP7FXHLzL0njkYvM5d4HWkELbCm54OjFzDvI5bpVT+D3a/p2N7Pp6YDmAYsWN0Lf1j58ATru4EclQUSC1vjNkJ0hyLUrLFvjuHmciE8mFSeftUFblEowaBAKrDzYWRABBBFN1A6IWQExr4DrBFhJH6ehgFvnEYsViEfySEsxUIiTyrsMFVyGfZeCkDgRHyk1fsFCFDRHtW/lhCkbmRkfxBUKNGQpV2JPeRH6Cgn6Ckny2iLp5Km3s0xz0kx1cjRZHklpas5klc1g4DLkR1Ghc54lTEHLdOCQ9l1SvsOQFyGjbPKBjRKCiAywPU3M8klEC8RtjxY3YwpKhoUJBcUMQ+Z9yHfp9BJ0FhJ0enF2FhIMqgi20CZtb8Ehk4vQ5OaYEktTJwtENtuIQQvVZTMcdUk7DqrRQy3KkfMt0o82YB+apqU5RVwWkGlo2uqTzHh0b2ti0+kx/Jig/aEOtlkZGo7vJmJFDTmpWN+GidGZb6y4msZY/Cq1sVrjK/OAzgtFRjWwOd8QkhCzjYWiwxlmbnSAelmg3i7QZOVosnM0WHmS0iMmA+xS/ZjRjlV7w0h73Uht/viHUq2DHhVkO5JE6/G1j6NJUXUPldxCVLyPqfn9J6KYLS2jNCZBssIVCh0qC4TWWMII4I4wWdFkxXRV0gmBIQt5JRhWNr1+lJ1egh4/CiJgfa6ZvI4x2x5kQbSX+dE+Gu3q2jqDXoSd+Xp6/DhDOspQEKHTq6PbSzIURAmwCJQgLvLMj3XRX0iwLdtMqhAh79ugoV541FkFdhcSdHtxNAIpTbFHU2PIZygXR4+KMzB1TzzfhrxA5ARNOsfslh5mtPfSlhzG920CYZKzR8LUyQnLI2oFdOUT7MzVsT1Xz+5CnLyyUUoQBJJs4FBZitcWAW2RFPV2lryyw2r0Fie1Ps8F09fQaheIADktGQxcHumdzV93z2dnvo6efAylTSKIyor3McsnKnyUEnRlk6QLkRJ7c62AuQ27ibkFugp1dOeSeNhYQjE9PsiCZDcx6dNTSNBbSNDiZnh5+zrObluPKw3d78rHuW7rMdzadXBYw2o0tAICgSgICAQUQEkLfIGdklg5gW37xOJ5fM8mk3XAEmhXEcQDiCtUxCgNhC8QAeCHwrOrIGIYlfCM0I3UYIO2NKvk9OJpRCjBUC7Bc/1JVgfTidse+ZyD8ixEIEGBpQTZIMIjqjFMfSlIaUipFrYAWoKf1Ggb0BorI+j2p3KvPBwtNUiwbJ9IS454Ik/SypNwC8RjBaKRAnnPJltwyeYdsp5rPnsO2YKDTjvIYQsK4c0kwXYLtDYNkypEGCrECCyJLhdRCm9YcIYEjjfGGlI0ToWmqLyIsXpDCyPzklkalIK1OsFaSt2HbViAU0q25YTzWZzXod5mfrN1eenvkcMrK7UEBCA9m75tLfRta+FRqdEWCG8PlvP8P7f4aA3/GhB6MhHSLxHcdNNNvO1tb+MHP/gBxx57LF//+tf55S9/yZo1a0bF5ozE0NAQDQ0NDA4OUl//jy9W9dD2rbz9lt9SCALOnDmPo+JTOWxBB1994kFWdJrkD6fPnstnTj4DmVF0dDQhpWDzs9v44Mn/TTqdZ+k5R3D+5edCNscNH/s/tq3egZ+0mfKuY+g+rIGNQwOTH1jRkDNSlgjA8kDmBbIwcVehtvoBli99lvpolm2729jR1cKuHS3kByNYObBz4YMpAX6jhhYfK+GTrM/Q0jhExnPp62/ATzv4aZsga4EDIh4gogG4ChFREAkQEWXW+6IgHQ4xGHDwN8QRAiIdWSIzM6bOgjaFTssOI6osDIZs0Jaq1E5xH5Fx6fctIlEfS2r8gkRtNam3tQA/YaGFJtmYxY4rPF+Szrsk3QKuG5Dsj3NBz0kcvKiDZYfP5lf9f+VnW+7l2OaFfGz+m3jdLd/A7+hHDzu8Zt5R3Nb3N6RQTIs1opVPnz+I1hC1ovTnQBNgWyYdMJpQMKwuHFfM8KK0oFgl3hyzma9KF49Ked4SpvhiTHpGILA84rJAo5Wn0c6RlJ5Jthu6shmLoLEU2iIIq44LpFBYYV2OIBxnRPgkpEdMBERlgIspMCkxKW/zYSHAtLIZDGyGtRMKng51VkCj8GiUBVrtPHWWccHzlKC/EKE7G6cnFyelbHJIUr5D13Aduwcb6R6qp3Ownr5UkkDZSKlwXJ/6+jQN9cPM6ehmQWsnU6ODWCIg50VJp5JkhxK4AXTEU8yoH8S1AgZyMQZyUQZyMQZz0fAVw1eSiO0TtX0j0No+kfCz1oKs55DzbXK+Xfqc90y1dhFq5IUwV6a0AuLJHF3pOp7eOg0vcBBomuLDzGrpYUZLD5lClK19LfSkG/CxcCMedU0Z6uozCKXJZV0KGZdsOkIu5SBdRXPTMNu7WslnoxUXStivGxAUJELJ0vcIzczGfg6ZspP+TIIN3W3055KlXYWtcGKe0WQGEuVLggCjtY4qtKvLcXCMELSkEXq1rcE2ghW2Lq9DCigIREEiwvfi3/h7Xo80Gp1UqBYPnRgjfk2BSFnIIQuRthAqtBI62oy74jWWKrE9OsQb5z5GR2yQ+3cfxD2bF5FLRxG+RAeUMpuJtET6Ah1T5hVX4I7z2C4IRM7YvFQiGKNCJ+AJhCfAF4hAgIImO8s5M9bgaYvbtywmK2ywNFpiJGVLgy+QaQuRsvAtjUqYfd1+gR/XqBiIAri9ouhrNhE9xpgWSF2qFTRaKaHliN/2BSP61ELj1Wl0mJzUSgusbLmPIKLx63TpeEXRLFc0P052KMX9KvrXFigbkBorV9HHnpoptlOZ8jGsYTBKv1JUUlb+XQFR+m/yGHUKxdjfFRHrLrDiex/dt84mgX+2vLYnFMc264efQsaie99hElDZHFv//bMvyOP+R2LSBOcd73gH3/jGN6irq6v6Pp1O8/73v58f/ehH+3WABwrf/va3S4U+Dz/8cL75zW9y3HHH7XW/F8INc9fG9bzn9lsItGb5zNk8tnMH+cCnznX51Cmnc/HBh46pPV5537N8/JzP4RV8Fp+4iDUPr0MpTdOUBj7wvX/npAuPRWvNcKFAIQjwVYAXKDwVsHtXH4/e8RRbdvbgzaijPw7bcyl2exkyTsXDP9DYabAzIalRgBDmQVl8JoQPBF1cmDUIH2QA0tcI3/wdRM3GsW6FFex55dUC/Dh4cfCSwmiQNKHJ3ViepBYkIw6N9THa2+qJRh3SeY+ntuzAEwHJdkF+xiCEbndCQMR3mT88F9eL4Eez7GjaRE7mjC+1EhQrOsuisF8kR0pjSbBlUPV9nR1jutvByoEtIASZvGO0tBWQQlEXyyMEDG9IEt0dp3F5P1lV4AOLzuN1s4xmbWe2lzc8+EUAfnHix8hnFe948qsEIuDLy95JX2GQ/1nzKzSai2acxBlth3PFyu8QaM25U0/l2jVPEXEKtCazVKrvJIbo2KLa9U/rohsR4fxUnpOxBVA94kFetAJJAmxpSI0tg/K7VFhC4ytJXlnkPJu+nfVEg4DZ7d00JTJkci6pbJThdJxUKkomFyXr2XiBzWBfEjcSEIvniSXyxGIFYnEzl927G+je3YDnles5xawCccejNxdn0k/3EXNThOUYQuZ7dpVWVFRPU9VvJYXoCNPQmEKH1sUiTGGH1e3okoueuZe0TbmY0Iiuqw6l2G6xbcHYgqoeo4FRjY0x7vG+K7VbPICKMVQKZMpcj0bbvWdiUgpoGEFiVLGfYrBDZTPjNalBxQJUq4+OKkRGGlKTskwK6/EHMmI8ukTIKBIHqbFQqLRryMaIfUtzUFlATAiwNapIeKIKFQutHiMRhCQsLRAZG5GvcIqrsMyPPHxd/GIc4V2j8Ro0yjV9YJmd3H6BLITOiCG5HX9eKF1no55XKtxIiupLbeS1tY8Eqgql6dAECU0QD7vOgT1srpFCkzFjWCmwc2NkHhvrPh+x9o25y1jX31j7jFg3RPEeqdi81N1k5mbcgY34ongdBsVntdlIuaAcwagHRQnle6zyVpm2ucA9N9YITo3gHFhMmuBYlsWuXbtGFcTs6elh6tSp+P5L2/T4Qrlhbl7zHFfc9cfS36fMmsPVZ5zNtLo9j+neXzzAF9709dLfZ775ZN779Uupb64bf6e9IF0o8PTWnWze1oPTE7Bjcy9bNvewZVM3g4PZ0gIoC6r6ISpAudL486bzLDx4GiefuZTZc1vxhGZr5wBdPcPk8h7pTIHhdI5MNk8m65HOFQiCYqUTStqrog9/XSLCIQs6mDezlbkzW5g3q5VpUxqxrdEPpztWruPDN9yGJQWiMcBfPIiwNY608HVAzHK5atlFnD1tCSkvx5eeu5m7Op8GIFAQaInAWD60Bimh0UnQW0hjCY1jKbSuJkBJK0ZfPs+ceAfvnH82AJ4f8MXf/4X+VJZZR2gGrH68bTHePfsVtB2s+Mrqm4lKh/878QqmxZoBuHLF//JY3zoumX06717wSr7z/K3ctPWvLG2Yw7ePei9/2vUYX1nzyxLJaY808L8bbyMqXc5oPZVr1z2KawXMbPDJqixWVRyMITu2NG54eyI7ZYgRsqcunaPi90qbAq1hPfjSFkoBQhMoU3ox3xtlcFUL2h9DoKh8qivKUkXFU1TLMCxbjNi++KFSwhhDGBClgxQI30gu2gKkGNWcrhQqippUXW6jIhFfdXdVAs4eJBKljXChzRi0tYdtx0CVMDVqLsbBZAnKBGBLSdJycLWkkPEopHyUp5BKIHKGT2lZVn5oaQRPO6exshrpm4ktNEhyzZIgHkaB+RqroLF9gasFDiZIv74pRrQhQlYGdKcyDFXUNANwlMANrRgeCs+BwKke8xiXMyiNzGnsIY2b1dgZhZ0JEIHGSti0HdxKr+XRHWTxx7BklKZ+bB0BAnAty8TXKDX+PhU/SFtT3xTBrZf0pNL4QyDyYenS0jnXxrXM10R6ywWTtQyvKymq/kaCCoOTtKi4joW5v/KtlAi2lQUnVWG5KxKnCUgYE+HLe9yv8toeo7FRbeyhQz+m8erN/S48kB4EcSPYu73jJBrRGlG5pJTWHDG20mIvxzOmAmK8YxmzoVBZUZ21YM/bhwpBc4+BtgV6lDnfKCJF2L5QgNIoW6BdYZQp4/WndUmH8W/t87jygxdO5Ej+LrxQ5LWxUBzbzB98+oAQnG3v/swL8rj/kZhwFrWhoSEjPGrN8PAw0Wj5hARBwO233z6K9NRw4HDRwYspBAE/XvkkbzvsCN5w6NIJ+fyf/oaTyAxluPOG+3jDRy/khPOO/rvHknBdTlgwhxMWzKn6XmvNQH+azZu6GRrIEk9EiCdc4okIG1ds4stv/gYib2K7OuZN4TvXfhrLHtvn+0DinGULuWvZ89yxch30SY4eXszGKZvpL6SJWQ7ZoMCHn7yJ96a6effC0/nsYW/guNaD+OKzvwMZILUyArum5I424KWZEWthe7YXR0uEMCQnUCZOIBVkcW3YntvF8va5JJwYAGK5w8d++kd2Pl4gfhw403NccOIiWmN13N25khX9G/nSc7/h60f+G0IILph+PI/1reO2nY/yjnkv4/WzTuW32x7gmcHNrBzYxCumHYsQ8OXVv+Tm7Q9wztSjObxxAU8NrOf5zGrOnbGE27avoicVZUFzPTuyu4nJCPlAY3wKLQoKCCMLrNDCIkX5+V2EDlWyJeVlSPaKMMRGVtWBF0haZTtbcz24doBWppBkdnuSoXWN1Wq/SlQyBYuyZFEh6JREkZEWB1HetpLvjNm4MAeiI2Owu2JbReJaef+ViI4oc6kJCDjjQopQ2C+PwcqDlTMvBASu0agGLminupeSRr1yAHsqgTGe9jlsw5ICx7JwbQvHkhWEV9PRUMfctmam1ifpaKhjakOdea+vozkRG7VOpdM5/nTHM2QyefxCwHAqz9BAht7eYZ556Hm0ZYGAaDJKoiFu5jOlCYYVvtQctWwOrzjnMI48cg72XtaPTMFj58AQg5kc89tbaIyPFiwyBY/t/YOs7+ph1dZOntvRzcbePvpzWfyitG4JVELgNDrMi9Wz7ZZnsHakaWmM8qnvfQgr5lDwAwpBQOdAime3d9E5PMy63T1s6x0ce3CVlxiQV2GqBzn697GgtEBnBa2RevJpGCzkRikChG+s6u1OnHibZKhQIKM8CkITOOxRQK28381tIYj0a/ItRti1hyp/pHTR6YkI2ONtose7R8feVRtDCzEliASgBrLkdw3hZnym1NfRMq2RhnltZOsddqQzdA4Ok8oXqtqzsgLhG6uNriC8dipcUbQxiBaNTEUFTclLYeSxjCS3I83aYx3THn7We7C8VTZQFT61N6VG0ZppQeCOo/QpJqgY60c9xudRAyuvz4tPOmicgfwLYuTzaX+1WcPELThSjl9wEkAIwWc+8xk+8YlP7LfBvRDxQtYIvNhw+//ezdfe/QMArrz2Pbz8HWf808bSn8ry7h/+lua6ONe89VV0eYP8+0PX05UbJGlHSAdG8/vdY9/KSe1mcd6c2s3lj/+Y3fmBMC7HZHcqWnFKQh/Q6EpyykMpQdazcawA1zbua0sa5vCto/4dR9oopbnkmz9n1bZOYsf3YTX4vHvBObx93ulsz/Twloe+RkH5/Nfi13Du9GPwVcDrHvwCPfkhPr3kEs6ccjhfXfMbfr/jYY5tXsj/HPEuAGPJWX0TCs2S+jlsy3Yy7Ge5eMap/HVHDyv7txO3bQ5tddmW7URryAcWllBEw3ECIYkzFMUWGinLdGWs5aGYHtQPiQuIkqB9ZtvxbBrwWJV5mogdoDXYwuaDiy7mFR3HMpzLs3rHbm5/4Dn+9sxGegpZlC2QvkZ6RlDwkwIVHctlZGwhokrjW2Q/+ysZwFgr6Shte2jRUZS0pdIHUQCrYIai7FCbbhuhSVnmb6FCQpM15EZUELVRQ5Eh4XEMx1KOcfnUdnljmTdWIW2ZPkqubiNSdxMorL4cHTnBh999HmccuxjH+scoIr5wyde59+cPMGV2G//7zFeJJWP/kH7Hw+7hFA+s38L9z2/mwQ1bGMzm977TfkRbXYJ5rc3MbW0iEXHZOTDEjv4htg8M0pfOVm3bXpfgvGWH0BKPc9vKNTy3c/ek+7OlxLEktjQvIQSWMBngLGnelYB612WKGyfqSTLDOTYMDdDp5NF7ItHjwA2Jc7pQmFBFdksKXMsm5tjEIw6HTpvCqQvncpAd5yPHfgIv7/Hxn36AM964fMz9857Pml3dPLVtJ/et28QzO7tI5QsoadzwtG10Pc5gtfVmWkMdtpR0DafI++W8g1IIEq5D1LJpjEdxbItCoOjPZOlNZyY/IXvCSOtQoE2GNblnslqEY5lCx5Xj3xOKRZEDpcpL7GSXTw3ffuN5nLl4wSR3nDxeyPJayYLz/QNkwfmPmgVnwgTnvvvuQ2vNGWecwW9+8xuam5tLv7muy+zZs5k2bdoBG+gLBS/kG+bFiN996490buri3770Zmzn7y7L9HdBj8imtTMzwLsf/glb0r1ELZu88miL1PHrU99Ho2sctfOBx0V//R/6CkMobbLWFItcylDLpxG8euaR3L7r0TB2xyKdt4m5XonkTI+28+Pj30/cjrByyy7+7Xu/5ojjGngm8RytkXp+e/JHcKTNTzffx3efv532SAO/XG6++9HGO7h+090c0TSfbxz5H+zM9nLJQ18m0Ir/PeYDLKqfAcAjvav57Kr/IxPkaY3U01cwmuRPLn47P1r7JI/3bgE0B7c4DPh9AOR8i6ioY15dPZszW5AydF8IyZvxnhEIEWCJML200KXnXqAFQtjMjk3l+dROQ/iUxHt+BsOtKRqbBkMXPlB5m/RzUwkyDk2JOK2JOC3J8JWI0xiN0ts5RE/nMLt2DrBzSz/Z4Ty+A9lpFn5M4Axr3AGFk9L4cYGXNK/ANaKJcqqFfABCoUCoIlETiArXDuFrtK/DOk9UCRVFFw2pRXXArwbpaWPAsSGICIKoGN33CMi8xs5q7Ix5WVmN7cG0aQ3Mm9PGIQdNo6kjST6i2TowyJrOblbv6iZb8Ez9EA1aaQJf4XkBQaBMLFvxWBTUeTZtRKl3Ikxra+Dg2e142/u544u/Y3D3IP4hLUw5dylDazrJP7oVtyvDGz9yAW/9f6/7h9+jOzd0ct1//YzXffh8Fh1z4AWiycAPFM/s6OT+5zfzt/WbWdfVU7JqGSHdLn12LAvbklhCYEmJJc07gcLLejQ0J7GlDH+T2FJgWxYJ12FuaxNzW5uZ19ZMXXT8mmzpfIEdA0Ps6B8k5jocPXtGySVXa81jm7bzkweeZOfAEB0NdbTVJ5kSvtrqEkxpSNIQixJ1bDP2cMz7ir50hp89vJJUPk99PEpdNELCdbj+wzfSv7mb13zkAk479xja6hLEXZeYY+aruAYXfJ8tfQNs6u5nU08/G3v62NzTz6befoZzEyOWzs4Uc5XDVZ99G0umTUUIGMjm2N4/yLa+8NU/yLqubp7ZUS4dEXcdzl68gLMPOYiHd2zllQsX0pPK8tjmbTyyaTvrunqq+qmLRjjz4Pm8fMlCTpg3C3ccS2I6X2BTTx/b+gdxLIuobRN1ii8nnHsLR1pIachkNlPg6We388STW1i1eRfDts+Q4zNgeWTEnolJxLaY39ZCe12CTMFjIJtjIJNlIJujUEFqhID2uiQzGuuZ3tTAzKYGZjTVM7WhjqZ4jIZYlMZ4jGh4/3tBQCpboDERxQsCuofTdA2l6BpO0TWUJu/51MciNMSixF2HbMFjMJOjJ5VmZ/8wn7norH+IkuSFLK+VCc7/O0AE5/+9II97Tzj88MO5/fbbmTZtGtu3b2fatGlIue9r0KRjcLZs2cLMmTP/rk5fzHgh3zA17H/05lP8x8M3sHZoF7aUBFpxdsehfOXI15cexGuHdvK2B78FwlhxBMLUe5DmwRFoaLTrObJ1Kg/2rEZrWFp3MA/1bCTqeDiWybjmBxbL6g/htbOP4ajm2cQdh4vv/zK9hWH+39I3cE7H4eQDj9f+7Uv0Fob55KGv4xXTjqIrN8DrH/gCCs3/Hf+fzE6087lnf86dnU9yStsSPnfY20rHszG1i/9aeR1d+X5caeFrnxa3nu8dfSU3bniMH6y9Hyl9GmJ5XNs8ACMiSUTU0ZXvwRIK1/ax5djLhiE+0sQmKUmcDr5x7Gv54IrvkFeesQztamY4kae1Po0ljV92ridK/3OtMIHMQWPBFjKs1WEKAO4RSuOmITKkiQ5rREpN2H1sTx4etiWxHYuIY4S0fMGn4AX4fjmGIohCEBOG8Lgh8XEFKsK4cTVRx2bhlFa8QLGhu7dKMJkoDp3WzhuPXcYrlywi5jpjbtPfNcDX3v0DHrrl8dJ3zR1NfPSG93PkmUsn3WcNNYyFG/7fL/m/z/6KY15+OF+4fd88PrTW5P2ArOeR93yynk/O8xjO5Xlk0zb+8PAzbM1VW0sa41ECpcclR1IITpw/i/OXHcKZhywgPs59Aoa8Pb55B2s6u1k6fQonLZiNa//jFXQP3L+K/3zfd/EPambe2YcyNR7n8R/9FXYO84FPvp6LLzkDObKIEmb+sp7PQCaLFyg6GpL/lPEfaLyQ5bUawTG48cYbWb58OXPmzKGpqYmnn36amTNnUl9fz1NPPcW8efP2ue19ShM9MDDAo48+yu7du1GqOn3mW9/61n0ezIsBL+QbpoYDg6FClnP//HUGvQyWFCit+fzhF/OqGYeXtvnPJ37K/T2rwpTKhFWqwQ5d1XwtWJycS5e/hWxQoNFJ8olDXs8HnrweIVSJ5HiBJJ1zEULSGqlDyBxZPUxURlmSXETSjdKZ72RdajNJK87xTUeg0Tw9/Cx9Xj/TIh28duZpHNLQxn888U0Abjjuw8xJltOf9+WH+MTTP2LN8NZSSugTWw/ls0vewYO7N3Ll4z8jkFkcyycSkpxAWRQCiQ7TRdsywJYKV5dLPARahLFIFpbUBH6ELx35Or685udkApN5TooIg1lNQ5glDuBlTSdx3pSTS64pAH3pLL2pDL3pND2pTPg5Q186y3Auz1Auz1A2N8p/fiQitkXUcWhNxjl+3ixOWjCbY+fMIBFxS9v4gWJgIE1Pb4revpR5703R05eiUAhoaozT2BCnsTFOY0OMxoYEjQ0xkskojmPhOhaWNb4Lr1Iaz/MpFAIGhzIMDmUxrnoKFZiYpSBQDOZy5B1FdyHH2q4e1nZ28/zunlHuI3HXYeGUVhZNaWXh1DYWtrdQH4uS931ynk/e88n5Pnk/oOD7LJzSyqHT9pz+vgitNXf/31+59mM3csjxB/HBH7ybxraGCe1bQw0TwfZ1O7n04A8gLckvdvyQpvb9e32lBtK845AP0JPOcOSVL6OwqIUHN2wlXbFWtNcljJWiuYGZTY3MbG7g+Hkzaa9L7qHlFx6UUrxx5n/Qt6ufq//0Se7+v/u456f3s2T5wVxz32dfULW4/hl4IctrJYLzvQNEcN7z4iA455xzDg899BDJZJKenh6uvvpq3vCGN3DwwQezcuXKfyzBufXWW7nkkktIpVLU19dX3UBCCPr6+vZ5MC8GvJBvmBoOHL646nZ+tulhFtS1sSG1mzo7yq9OvYyOWCMAvgo4+a5PoVEhwTFppG2rnNAml3dY0NBIj98JwLvmvYxfbHmU3vww715wBjdsuRuFwg8kqZxLMSVQMlpACEjnXQJlMrbVx3IIAamci68sHMunPpZHaehPx4lIh9kNFr1eH+dMPYpPHPqGquPJBQW++NzPua97ZSl+5u1zXs5b5r6MT6/8FbfvXBHGnSrijgfCBDEXfBsNWFITlTFcEaXPGyi5mQVKYIWk7r0LXs5Pt95JTlX60utSIVKJ4FOHvo2T2w/b5/MSKMVwrsBwLkfO94mFbh7Fd+tFbmn2A8WWvn7Wdhr3p4OntjK9sWFMrez+xEh3zRpq2J+47NiPse7xDVz2zXdw4fteMeH9tNY8cdfTJBvjHHTUPKwx3Jy+edm13Pq9O5i5aBrff+p/cCMm4cPqXbtJRFymN9aPa8V8MeKad32fP153D4eetIhnH1iLEILvPPZFDjpy3wXDlwpeyPJajeCUoZRixYoVnHrqqRx33HE89thjpNNp3vzmN/PKV76SU045hY6Ojkm3O+mn/5VXXsk73vEOUqkUAwMD9Pf3l14vdXJTw78uLpx5BACbU70sbpjGsJ/jv5/6LUobC6YtLS6ZfUpopQgT0shiUL5pI+FYPD84iI2xHvx40z0sbTTxMRrBd47+D2KWi22pkNQYIdPG+N0vaWrhisVn8e8LT+XgujkAzG1I8P6DT+fUtiUoJZACXMsnr3w2DBoXjT/teoJ3P/QTHuhaT1GfEbVcPrXkLbxp9lklt6vrN/+JLz73M3rzw6Xj9pTFYC6C0iCFJmJ7WKHf95z4VLpzQ0hRjMspp+qZn2zj+s23l8iNCGNziuQmKl2+eeTlfxe5AbCkpDEeZWZzIwe1tzKjqYHWZIJExH3Rkxswbm/z21p45dJFnL14ATObGw84uQFq5KaGA4piwP8t372Dob7hvWxtoLXmex+6no+//HO8//j/4nVT38Xn3/R17rj+Xnp39QOw5tHn+cP37wTg8u++CzdiiIxrWyyb2cGC9paXFLkBOP68owB49oG1AJzz9tNq5ObFBH2AXi8S3H333WSzWY466igcx+HHP/4x3d3dxGIx6urq+OEPf8hBB+1b1r1JSwA7duzg8ssvJx6P71OHNdTwYsTBDR0cXN+BrxXL2xYStRwe693ETzc9XNrm3w46AxGmohJhNLosBncDCxtbaXBi9KRF6LYWsD1rMhs92beJpY1z+OaR7yZpx7AtxfzGGAk7wrDJ08zG9C4e6XmeQxs7+Oyy12ELi+58P3fsXMldu9aQ9YwPdVPM1ADxA4uCLxECVgyu4V0P3cipf/ofVvRuBUAKybvmv5KPHPwGZDjuu7oeZ01qDUKUXU8t4ZD3HJQyNW4cSyGF4ome7SFpCQkOGksqbBmwPbeLgHLBVK01rrQRAuqdBN848v0c0jD7wJysGmqo4QWNMy45mfqWOrat2cGVp32anp17Vo4qpfjWZddy8zdvByBeH2Ood5i//OIB/ucd3+UN0/+ddx/+YT7/xq+jteast5zC4acv+Uccyj8dR551GG7UkLZ4XYxLP//Gf/KIaqhh4vjgBz9Ic3MzRx55JJlMhnvuuYcgCBBCcMUVV3DPPffQ39+/T21PmuCcc845PP7443vfsIYaXmK4cJax4tzXtY4PLzZuFd9ccxfrh032najlcOGMY1GhxcJkUSsXI10ztJMfn/hWmtwked8Qim2Z3YDmmYGtFAKfQxpm8vUj34UtLHoK/Xzl6Av57LKLickYQsAT/ev54GO/4Px7vkOgDKHZnttF3HK4dO6ZSAQ+OX535r/zu9Pfw+tnngpAxPaRUtFbSPPmv/2Iyx/5BVnf+KS/Ytqx3HjCf7GobpZJEiB8km4B1woAzZxkMwhBzrfxQ5JjS0XcLSCFCrOmKVwrwLVUKa6nGI8UaJNu1tc+DU6C/zn8PSyom/4POGM11FDDCxFN7Q38z73/j+aOJjav2saHTv5vdm7oHHNbpRRff/cPufX7dyKE4Mpr38Nvun/E1/76WS75xMUsOmY+Qgg2Pr2Fzk27qWtK8O9feWnHAlciGo9w3LlHAnDJJy+meWrTP3lENUwKWhyY14sEq1atYvfu3XzhC1/Atm2uueYaWltbyWazfPe73+Wvf/3rqFj/iWLSMTjXXXcdn/3sZ7n00ktZunQpjlNt7j3//PP3aSAvFryQfTprOLAYKGQ4866v4KmAX5z8H3x33T3cv3sdi+qn8tPl78aRNhuGu3jt/d/EkSZpgFKYomthPZhzO47irfOW87YHrkNbA8Z1S9nkleaHx72LI5rnAvD1tb/n19seYEGyg+uO+wAPdq/hI0/dgCNsPC9GyjfkIhk1LmCZfISDG6bji352F3p54+zTeM+Cc9Fac9kT32HV4BaObz6Ue3fsJBMYYhOVDp9adi4XzDq8dIzff/4P/HLbn0sFS30lcEiGdYAEggDb0lgiPD49ugaOUpDKu8QiHlKAHW5bJDfzki/9dPI11FDD3rFrUxcfPfsqdm3sonlqI1+845PMXVq27AZBwFff+T3uuuE+pBT85/Xv46w3nzKqncGeIZ6462mefWANJ198/L+M9aaIod5h1j62nqPPObzmXlqBF7K8VhzbjG9/5oDE4Gx/36dfkMe9JzQ1NbFy5Upc12X+/Pm86lWv4umnn2bz5s1ks9m9NzACk7bgvOtd72Lbtm189rOf5bWvfS0XXnhh6XXRRRdNegA11PBiQaMb5/QpBwNwy/YV/L/DLqTRibN2qJPvr7sXgPl1Uzi8aTZBqEEpumcVXdZu3fEkCsWNy/8NHVbB8/EB+NmmhwhCi8/b555F0o6yPrWLO3c9yfRYOwkrhqd9sipLoKDVbaLOqjNuY7bPswM72Thk/Nlv2nI/v9u6Ak8FvGXOmQCsHFzP7WddxjnTFgOQUx4ff/J3vOYvP6AzY2riHNV8CJmCU4qbsaVGyWGitkfULuDaAVJolLLL8UYVFhvftzmu4SSOa59dRW7qnQRfPfy9NXJTQw01lNAxdwpfu/8q5i6dRV/nAFec+mmee8jEkgR+wJfe+i1DbizJx278wJjkBqChtZ4z3ric93/73/7lyA1AfUsdx7z8iBq5qeFFjVmzZmHbNlOnTkVKydVXX83q1avZvHnzPrU3aYKjlBr3FQSTr89QQw0vJlw4y7gC3Lb9aeqdGJ9ceh4AP9v0MJ4yROXVM49BaVHlqlaC0Lz3kRtoj9VzTMt8oPi75p7OZ7n43u9zX+c6Gpw4b5p9GgBfeu63vOqeb9GT9QCIO5r/Puxc7nzZB/nKkW8Ov4NPLH0FZ0053PRNwGef+TVn33UNj+7ezuz4FLJBnpu3P8g1x7yOn578TloiCYSA1YO7OPuur/OJJ3/Hqv5tBNoi47lhSuiihUaXkgRIobEsv8pqEyiTkOCrR76TSxYczqqh9SVy40qHrx1xGXOTk8+CUkMNNby00dLRxFf/8hkWn7CQ1ECaj559FY/c9gSff9PXuffnD2DZFp/8xYc4/Q0n/bOHWkMN+x//4kkGKrFy5UqmTTNK0De/+c0l69OUKRMrczASf1eaoVwu9/fsXkMNLzqc0Daf9mg9g16Wv3St4cyOxTS7CTJBgaf6tgFwVscS6uwYgaq8vbQhCkB3fohPPXUzJ7UeUrKUSKGxhGbdUBfvefhnvPGv13Ld2icJlMDHJ+b4HNu8kIh00CJgTl0DlpAsbZzDYY1z8HVAn9/Hl49+LRfNOB6Auoigr5Dm2vV/Y3W/sdD8dMu93LbjCQ5pmMq951zJ2+efgECg0Pxu21N8Y/XdACgtGc67BGHMTTEznNbg+YJM3sYPBEoLvEASaIvZ8RaeHFjDR1Z+v+SipzV85tC3Mycx9R93kmqooYYXFeqaknzxzv/mqJctI5fJ88nzvsj9v34Yx7X59G8+zMkXH//PHmINNdTwD8T3vvc9Wltb/642Jk1wgiDgqquuYvr06SSTSTZu3AjAf//3f3Pdddf9XYOpoYYXOiwhOT8s8Pm7bSuQQnJi2wIA/ta9DjDJBs6dfjgaUZUmWorQIiLg7s5n6cylSqmVHcswiPNnLsGVFk/376A7l8JSpvBcc1zwpaNfzatnHgfAjZvvK43pkjkmkcDvtj9Mysty8Uyj6RTS4zPLzuOYljnkfUnBt9BovvDcTRx/++d57V++T38hzbsOOon5yVbAWGmKKJKcQmCVrFGW1EQcRSLiYUlTpNKWiojl01Xo4lfb/oKvfQgTDBzZdAjHth5yIE5FDTXU8BJCLBHlqls+yimvPQEAJ+Lw/27+CCecd/Q/eWQ11HAA8S+eZOBAYtIE5/Of/zzXX389X/7yl3HdcjXwJUuWcO211+7XwdVQwwsRxWxqD+5eT1d2iJPaDwr/fr60zatnHQOY4phAyXpTtOQA/GTDA0RlxGQuQwGaRY1t/PGsy7li8Vl89ejXcPfZH2VR3XSyQYEfbbyL181aji0snuzfyJN9RrlwYuvBzEm0k/bz/H7HI8xJTOHQhtkorcjqYX500qX89rT3ctH0U7CwsaTGcfI8P9zFrdtXcu36+9mU7i65nxWhw9F6gU3Wc8j5Fr6SWNglsuNIhSVNjFHMigASXwkUNoG2ePu8sw/YeaihhhpeWnBch//62Qf4yE/exzcf+jzHvuKIf/aQaqihhhcpJk1wbrjhBn74wx9yySWXVFURXrZsGWvWrNmvg6uhhhciZiVaOLJ5NgrNrduf4oS2BQgE64a76MoOAbCgbgrLmmYRhHxBiCKJgahlCEKgNX6Fr6wUmif7NtERb+DfFi7nFTOWELVcLjvoVQDcsuMR8qrA+dMNebp2w13hfpI3hVacm7b8jYLyOXfasQDcvusxtNYcVD+Fjy55JV88/G1mDI7PhxafymWLTuesjkM4qG4Kr5i+hFg4ttKYSs68ApDU242c2XJaSHaMi5qvJOd3nMLC5Fw8JZgabSXQmsX1s1jSMGc/z34NNdTwUoZlWZz9llNZcPjcf/ZQaqjhgEPoA/OqYR8LfS5YsGDU90opPM/bL4OqoYYXOi4Kkw38btuTNDpxljSaui4PdJetOBfNPBpCN7UiBCAlgMYSgozvl9zUpNQ83b8FX1Un6ziyeT7LWxcTaMX31/+Rt807HUdYrOjfxBN9GwB42dTDaYvU01sY5k87n+SM9sOIWS7bMt08PbCp1NZxLQdzwXTjz35b54NcMu84vnbMG/jt6e/lk4e9irw2iRIanQQgwrGa8QIc27KQ32x/CBAE2qIQWNTZDSyqn8Hj/c/jCItMkAfgtTNP/rvmuIYaaqihhhpqqGFfMGmCs3jxYu6///5R3//617/miCNq5uQa/jVwdsdiYpbL1nQfK/q2sjx0U3tg97rSNkc0zcYQnLKbGkAu8JgabUChCZQo2UikgEyQZ83QzlH9veegV2IJyf3dz7Iz28sFM4yF5n/X34XWGkfavGG2IRTXbrgTpTWnty8DjBWnEu896Dymx1rozg/yzXW/K32/I1OuJt7gxivGrEuZ4DrTaaRVMFaecOAXTD+O72+4DYDjWw5h0EvTFmng1PalE5vMGmqooYYaavhXRC2L2gGDPdkdPvWpT/G2t72NHTt2oJTit7/9LWvXruWGG27gD3/4w4EYYw01vOAQtyO8fNoSbt72JL/b9iSvmX0031t3Lw/3bMBTAY60mBprRCIItDZmYwFCazSCo1pmc9uOZ4jaDloHpVo5RTe1JY0zq/qbnWjnvOnH8bvtD/Gd52/jc0vfyi07HmPlwGYe61vPsS0HcdGME/jd9kfYlunhhxvu5Nxpx3L7rse4t2slly+8gIRtionFLJf/WvwG3v/Ed7mj80lOajuU09oPqyI4cSsClKsHCwESwSO963Eds3pqYEq0kX5vkL5CipmxVnblTBsXzTgRW5ZdWGuooYYaaqihhhE4EEkBXiRJBq644ooJb3vNNddMuv1JW3AuuOACbr31Vu6++24SiQSf+tSnWL16Nbfeeitnn10LKK7hXwcXzDQWyzt2PsvcZCuNTpyUn+eZfpMu2pCcBnTFbVa0iPTkh2l04uQCH1vYJSuPJTVP9G4cs793zD2LmOWyemgbKwc3cmFoxbl2w91orYlYDh8+2BTb/e22h7CQzIq3k1Mef+5aWdXW0sY5vGn26QB8dc1v6M0Psb2C4FhCItBV8ThRGcO2fCqXzvOnH8ttO42F6MIZJ7A+tZOIdDhv+nGTmssaaqihhhpqqOFfBytWrJjQ66mnntqn9idtwQE4+eSTueuuu/apwxpqeKngiOZZzE60sCXdyz27VnNi2wJu3/k0f+t+niNb5gAwPd7Mzmx/KV100bXrqf7NXDj9WG7a+ijt0UZ25bpL2zw1sAlfBaMsIM2ROt4853T+d8Md/GTjPXztyHfxu+2P8szAFh7tfZ7jWhdydMsCzuk4gjt2reAra27m5R1H8cMNf+S2nY+OIh2Xzjubh3tXsz61i6+s+TVJ2Vj6bVdmsOSWVkwdPeRlkZJSfZtD62ZxX/fTaDQv7ziKp8JYn3M6jqLBSRyQOa+hhhpqqKGGlwwOhEvZi8RF7d577z2g7U/agjNv3jx6e3tHfT8wMMC8efP2y6BqqOHFACFEyYrz+20rOLEUh1NONDAj3gQILGGXa+Joja8VdY5xGduZGQLKsTh5lWfd8K4x+3zNzJNIWFG2ZHbz/PAOXj3TJAz43w0mFgfg/QtfRZ0dY93wTgpBgCUkzw1tZVOqs6otR9p84tA34giLB3tW80T/GoorY1duKLTelNNaS1lZJ0fTGI2xIbWLejvOq6efxN+6nzVjnLF8H2azhhpqqKGGGmr4R+Pqq6/mmGOOoa6ujvb2di688ELWrl1btU0ul+Oyyy6jpaWFZDLJxRdfTFdXV9U2W7du5dxzzyUej9Pe3s5//ud/4vv+pMayfv167rjjDrLZLEBJrtkXTJrgbN68mSAIRn2fz+fZsWPHPg+khhpejDhn2hIAVvZv55hmk9Z0zdAuenLDAEyPNQOQDONfAFzL3Ha/37aCuck28irAEVbJb1aK8d3UEnaU80PXtF9s/StvmXMqEenw7OA2Hu4xCQ6a3CTvPegVAPxsy185sslkPbxt56Oj2puf7ODdC14JQK/XT8TxEUKhKxILFC025WQDGkdKHu5dg0DwgUUXcnfXCjSaY5sXMic5ZbLTWEMNNdRQQw3/engBJBm47777uOyyy3j44Ye566678DyPl73sZaTT6dI2H/rQh7j11lv51a9+xX333cfOnTt59atfXfo9CALOPfdcCoUCDz74ID/5yU+4/vrr+dSnPjWhMfT29nLmmWeycOFCXvnKV7Jrl1HyvvOd7+TKK6+c3AGFmDDBueWWW7jlllsAuOOOO0p/33LLLdx8881cddVVzJkzZ58GUUMNL1bMiDfR6MTxdUB3fphDG6rTRU+PG4LjSqeULrpY1LOnMMS8ZDsgcKVr1qXQyvOH7U+M2+drZi7HEpIV/Rvpzg+OacV51fRjOKxxDtmgQMozaZvv6HwST43Wprxu1il8+tBL0NpkcnOtgKgTAJUWG/ObCEmOQjEt1sw3jvwPTmw9hD+E5Om1s2qpoWuooYYaaqjhxYI//elPvP3tb+fQQw9l2bJlXH/99WzdupUnnjByyODgINdddx3XXHMNZ5xxBkcddRQ//vGPefDBB3n44YcBuPPOO3nuuee48cYbOfzww3nFK17BVVddxXe+8x0KhcJex/ChD30Ix3HYunUr8Xi89P3rX/96/vSnP+3TcU2Y4Fx44YVceOGFCCF429veVvr7wgsv5A1veAN33XUXX/3qV/dpEDXU8GKFEIIlTYbUPDuwgxPbjbWkSHCMixpkA69EYIAwgF9zX+fzCGCgkAcEEekCsCXbRW8+NWafU6KNnDnFpID+xda/8uY5pxKVDquHtvNgjzErSyH5z0MuwhKSVYNbqbNjDHppHuh5bsw2F9bNJOfZBEogBDiWwrGCCsc5jRTlpAPndhzLj4+7ksOb5vHHXY+TCfLMirdzTPPCfZzJGmqooYYaavgXwwG04AwNDVW98vn8hIY0ODgIQHOzUdA+8cQTeJ7HWWedVdrm4IMPZtasWTz00EMAPPTQQyxdupQpU8oeHOeccw5DQ0M8++yze+3zzjvv5Etf+hIzZsyo+v6ggw5iy5YtExr3SEyY4CilUEoxa9Ysdu/eXfpbKUU+n2ft2rW86lWv2qdB1FDDixmHhkU+nxnYwfI2I+A/1L0BXwUlC86Al0FU0AVXWggBBeUhkahiFjVhbkkpNB967EZywdjFc98w6xQA/tz1NJ72ec2sEwG4tsKKMy85lTfOPgUQ+Mp895NNd48qJArw/HAnIPACm7ioL1mSbEsjhcK2dMlVLSHr+eji1xKzXAKt+M22vwHw2pnLkWLSXq811FBDDTXUUMN+xsyZM2loaCi9rr766r3uo5Tigx/8ICeddBJLlhgX/M7OTlzXpbGxsWrbKVOm0NnZWdqmktwUfy/+tjek0+kqy00RfX19RCKRve4/FiYtjWzatInW1tZ96qyGGl6KWNJYtuAsaZxOvRNjyMuyamAHDU6MpB0BBC2ROsrxckbN0hGvw1O6RHxSfh6JsaI8O7SFyx65gZSXG9XnwvrpHNk0n0Arfr3tb1wy5xRilsuaoR38tbtspbl03pl0RJtI+XlcabMhtYtfbL1vVHs/2VAu3rsgOQ0vkKiwDE7RaqM1BBpOaFlc2vbBnufYke2lzo5xTsdR+ziDNdRQQw011PAviGIdnP39ArZt28bg4GDp9fGPf3yvw7nssstYtWoVv/jFLw70kVfh5JNP5oYbbij9LYRAKcWXv/xlTj/99H1qc5/Urffddx/nnXceCxYsYMGCBZx//vncf//9e9+xhhpegigSnE2pHvLK5/jW+YBxUxNClKw4M+NGMaC1iWERwOxkE7PjbWgtCJQABK2RRgBcCx7v28y7Hv4x/YX0yG55w2xjxbll+6M40uK1oRXnc6t+xbODphZP1HK58pALAUEhMIzl+k13sT3TU2rnTzuf4ZmBbaW/1wxvBwRKSwIlCBQEyuRTU8piWdPs0ra/3mqsN+dPP56o5e77JNZQQw011FBDDfsN9fX1Va+9WULe97738Yc//IF77723ylVs6tSpFAoFBgYGqrbv6upi6tSppW1GZlUr/l3cZk/48pe/zA9/+ENe8YpXUCgU+MhHPsKSJUv461//ype+9KWJHO4oTJrg3HjjjZx11lnE43Euv/xyLr/8cmKxGGeeeSY/+9nP9mkQNdTwYkZLJMnUaAMazXMDO1k+Il309JiJw5kSbYCKMplCaLame/jfE99KzHJLbmqJMOOalJoGJ8pzgzt5x4PX0ZUdqur3+JZFzI63kw5y/GHHo7x97hksa5xDys/xgSeuZdXAVgBOaD2YM6YsJdAaraGgfL7w3E1orXmkZyOffOo3pWQCAk3KzyJE0SXNkC4hhLHgKMGyplkAPD+8gxUDG7CE5KIZJx6Yya2hhhpqqKGGlyiEPjCvyUBrzfve9z5uvvlm/vznPzN37tyq34866igcx+Gee+4pfbd27Vq2bt3KCSecAMAJJ5zAM888w+7du0vb3HXXXdTX17N48WL2hiVLlrBu3TqWL1/OBRdcQDqd5tWvfjUrVqxg/vz5kzugEJMmOJ///Of58pe/zE033VQiODfddBNf/OIXueqqq/ZpEDXU8GJHMdHAqoEdnNhmCM6zgzvozaeYkTAWHBHGp4ThMEigOz9EgxPjE0vPKxGcTanuUlrm9y46lSnRejamunn7g//L1nS5BpUUktfPNlnLfrXtARxpcc2Rl3J401zSfp4PPHEdK/s3A/Cfh7ya09sPQ2lDVFYNbubfH/02H3zs//BUQMJykUKVat0UaZgo8zG0FjQ4CWYn2sgHHl9bezMAp7UfRnu0cb/OZw011FBDDTW85PECSBN92WWXceONN/Kzn/2Muro6Ojs76ezsLNWiaWho4J3vfCdXXHEF9957L0888QSXXnopJ5xwAscfb7K4vuxlL2Px4sW85S1vYeXKldxxxx188pOf5LLLLptwDE1DQwOf+MQn+OUvf8ntt9/O5z73OTo6OiZ3MBWYNMHZuHEj55133qjvzz//fDZt2rTPA6mhhhczim5qqwZ20BatY1G9Mck+1L2eGWEtnKFCFlfaQDkdtAC2Z/o4d/phNLt1YZyLQmIB8Hjf81x/4ruYFW9mZ3aAtz94LeuGygF750w9kkYnQWeun/t2P0PcjnDNEZdyVNM8MkGeDz35I57q30S9E+dzy97MtcdezvSYcZVbM7wVYaWZmYjjkTPkJkwDXSQ2SpuCoGCsN4eF1puvrPk1qwa3kLSjvGPeyw7s5NZQQw011FBDDQcE3/ve9xgcHOS0006jo6Oj9LrppptK23zta1/jVa96FRdffDGnnHIKU6dO5be//W3pd8uy+MMf/oBlWZxwwgm8+c1v5q1vfSuf/exnJzyOgYEB7rzzTm688UZuuOGGqte+wJ7sDjNnzuSee+5hwYIFVd/ffffdzJw5c58GUUMNL3YcWpFoAGB5+0LWDnXywO7nOX/m4QDsyPZzUF1HGB9jVCxSaLZmejiofiqvnnUUP9l0DwLI+xrXgUd61/HzjY/whtkn8IstD7M108s7HrqOjx16LqdOWYTSmtPbl3Hzjgf5wfo76MkWSDhRXjPzFLKBx3ND2/jQEz/iq0e+nSOb5zMn0c575l/IJ1f9CBFabPr9AUO2KpIJgPk774ElfQQCpQXLGmdz45Y/c2fnk1hC8tmlb2FmvO0fONM11FBDDTXUUMP+gtZ7N/lEo1G+853v8J3vfGfcbWbPns3tt9++T2O49dZbueSSS0ilUtTX1yNEpTu/4K1vfeuk25w0wbnyyiu5/PLLeeqppzjxRON3/8ADD3D99dfzjW98Y9IDqKGGlwIWN0wDYGd2gL58muVtB3Hd+r/yYPd63r3wNAB2ZPp505zjeHZwGxpjvRHA1pRxO3vVjCP48cY/h/VmjCuZEoobNv0NpSWm8CYMezk+8dRvQIc0SUNdDHbmern62VsIlBWOShN1BDk83vvY/xIV9fTns9hWgGuBbZninYEq91dc56Q0n21LALpkUVLC47oNdwDwgYUXcHSt7k0NNdRQQw011PB34Morr+Qd73gHX/jCF8ZMF70vmDTBec973sPUqVP56le/yi9/+UsADjnkEG666SYuuOCC/TKoGmp4saHOiTIn0crmdA/PDuzg+Lb5JO0IA16G/nwGiSCnPObUtZf2KbqprR42Vp/ZiRbmxKewPddJwnHIBQFCwLKWKTgkWT+0m75CiqL1p+jihgAvkLi2ojVmM8WdRsbzGPAyDBTSQAHbUuT0EPGSK6xAYAEBScelL+cjBEghEJhsa0prHMv0lfUVtrD42ZY/A3DxjJO4sJZYoIYaaqihhhr2GYLJJwWYSJsvNuzYsYPLL798v5Eb2AeCA3DRRRdx0UUX7bdB1FDDSwFLGqezOd3DqoEdnDxlIce3zufuzud4pHcDU2IN7MoOUG+bm1drUcpctmF4V6mNi2cdy9fX3kI2KGDjoPHIqQw3LH8fAP35NFvSfUSkxUAhw2N9G7ln12q2ZHbj2oqsyvDs0BbQFlOi9RzRMpP2aB1rU5vpzP3/9u48Psry3v//655JZrKvZCFsYQn7qlbEFSsVlWP1VK1bFavSU+tSgbp9bbVqrdXWpS5H2tMiXbRo69HzcymKCLiBioICIhC2ECD7PlkmM3P//piZOxkSkAkZMkneTx/3w8y9XPc1mcdM+Mznuj5XlT+ows7NY87lP/Kmcd2nT1DaXEOM3YbP15YlgsAHrwHZznT2ttYS5/TS4vMyPXMMNxZ0nIcnIiIiEq7Zs2ezbt06RowY0W1tdinAAVi3bh1btmwBYPz48Rx/vBb5k/5tYvogXt/3BZtqigE4JXs075R8xUflhQxKSOdAUw31nmYyHEmBTIxfWXOt9fOcwVN5YutrgEmGM4kKdzX7miopbqxgcMIA0p2JpDsTrfNnZI/i5jHfobC+jJ9/+Vf2NZeTEAsut0lJcy0lVtsmNsNOrBHLounXcFxmPgALxnyPO75YTIzNh5dgVslfTtoWKEEyOC6LsuZqvKZJfmIO9068khibHRERETkK7Rbm7NY2e5k5c+Zw22238dVXXzFp0iRiY2NDjn/3u98Nu82wA5zi4mIuv/xyPvzwQ9LS0gB/5YOTTz6ZpUuXhiwOJNKfTLAqqe3HNE2Oz8gHYGttCecNnsg6drGvsYop6cNYWbrZmofj9rXS5HETH+MgJTaeoQlZ7G0qo8nbag1je69sM1fkn9HpfQ3DoCAlh19M/D4/XvcMdpuHP5x0HQn2ePa6qihurKK4sZqy5jquHnGKFdwAzBgwjrSYFGo8dcTY/UPTzGDHANO0saV+DzabSYLdyW+mXEtSTHxkfoEiIiLS78ybNw+g06prhmHg9XrDbjPsMtHXX389ra2tbNmyhaqqKqqqqtiyZQs+n4/rr78+7A6I9BVjU3KJMWxUu10caKplcGI6cfZYmn2tJMb4J7/sobkIYgAAWa5JREFUa6xmSvow65pgALMhsF4NwOy8qQDUe5qstXHeK9v8jfefmDaM7+ROxcTkuV1vMzFtEHMGT+G/Rp/JA1O/xx9OuoZTAouQthdjJtDqteHztStfHdhsNh8tZjOmCXePv5y8QMlrEREROUpRsA5ONPD5fIfcuhLcQBcCnNWrV/Pss88yZswYa9+YMWN46qmneO+997rUCZG+wGmPZVRyDuBfD8du2CgIPA4u7lncWMWE1GCWsy2N/FHFVuvn7w+bHvjJtK7bVFtEZUv9N/bhxoI5xNsdbK4t4q0Dn3/j+aZpUtpcg89nw+Oz4zMNvD5/f70+iLPFYZqQYk/ltOwJ39ieiIiIHCEFOBHTpXVwWltbO+z3er3k5eV1S6dEequJaYP4uu4Am2v2cXbeBEan5LKxppiG1mbAvxbO2NQ8DNqyJQAba4qsNlJiExjgTKGipQ67YcdnerAZJu+Xb+bCwScd9v4DnKlcM3wWzxa+yX8Xvslp2RMOO6SstrURt+kJLO4Z/FT0d6rRHcPIhDy21O3lrOyxXf6diIiIiBzOihUrWLFiBWVlZfh8vpBjixcvDru9sDM4v/3tb7n55ptZt26dtW/dunX89Kc/5Xe/+13YHRDpSyamB+fh+AsNjE7JBaCsuT7w/zoMDPKT/OWigyHF3saKkHZOyxoHgNf04fMd+TA1gO8PPZUhCQOodjfw3M53Dnvu7oZyIDAcLRDYGAaBLI6d8pYaAKZnjjpUEyIiItIFhhmZrbe57777OPvss1mxYgUVFRVUV1eHbF0RdgbnmmuuobGxkenTpxMT47/c4/EQExPDtddey7XXXmudW1VV1aVOifRWEwOFBr6qPYDP9FkBzs76chJjnLg8LexvqmFK2jB2NZQB/kyOy9NMZUs9mc5kAE4cMIpXij/GMAjMwzH5rGoHDa1NJMUefpJ/rC2Gn46+gJ9t+DP/2vsh/5F3IsOTcjo99819GwJZJBMMH4bh74/HawdMKlrqsRs2Ts7Sgp4iIiLS/RYtWsSSJUu46qqruq3NsAOcJ554ottuLtLXjEjKIs4Wi8vTwu6GSmsOTmlLHWNSsilsKGVfYxWT0ofyavGn+IeD+b9u+aJ6N9/OnQTA1PR8AGwGeE2wYcNjevmo4mvOHjjtG/tx0oAxnJY1gffLN/PEtv/jiWnzMIzQ0pGmafJuyVf+9W5C9ht4fQa2wNdAU9KHkerovsW3REREhMjMmemFGRy3283JJ3fv4uFhBzhz587t1g6I9CUxNjvjUgeyvrqITTX7+O6QqeTFp7G/qYbkQOaluLGaSWlt5dSDVZk/rdxhBTjpjiSGJWaxx1UOJrT6TOw2/zC1IwlwAG4q+A8+rtzKZ1WFrC7bxMycSSHH11bsoLq1gVg7Idkbr8/AB9gDAc7p2eOO9tciIiIi0qnrr7+eF154gV/84hfd1maXF/oUkc5NSBvE+uoiNgcCnNEpuexvqsFu+Ke87Wus4ty8ye2uaBuC1t7U9Hz2uMr9w9R8BnabydrKrbR4W3HaQxfB6syghEyuGHYGS3at4Kntr3HSgDHE2R3W8X/sXhvI0pjYrHVvgv3B2neaCgyIiIh0P2VwAGhubuaPf/wj77zzDpMnT+6w0Odjjz0WdpthFxkQkcMLFhrYeFChgRavB/CXik51JBBr2IG24WF7Gyuoa22y2pmaPhwAm83ABGKNGJq8bj6t2n7EfflB/pnkxKVR2lzD33evtPbvrC/jw/Kvsdt82ALZGwCfabMySgD5iVkMTRwQxrMXEREROXJffvklU6dOxWazsWnTJtavX29tGzZs6FKbyuCIdLNgoYGtdSW0+jyMDszDqXY3Av7FPgEGxCVT0lzj/7IlEFV8Ub2b0wJDwoLzcIzA1zEen/+c98o2c2rW+CPqS5zdwc0F5/PzjX/jhT2rqW1tZFv9PrbUFhPvCC3DGG+Lo97bimm2ffOh4WkiIiKREYmqZ72xitrKlSu/+aQwKYMj0s2GJGSQEhtPq8/L9royRqcMBOBAUw0AxU1VmKZJfmKWdU3w82hD9S5r38D4dHLj0qxjLV5/QPJB+Vd4fEe+su8Z2RM5PmMUbp+HV4rXsLm2CB8+TNO/oKcZ2GJMh9WXYEbn9BwFOCIiIhFhGpHZpOsZnMLCQnbs2MHpp59OfHw8pml2qNIk0h8ZhsGE1DzWVOxgU80+Lh52PHH2WJq9bmJs0OxtpcrtoiB5IGsqtgdKQfvnvKxvF+AATEnPp+TABuyGgdc0sRt2alsb2Vizh2kZI464P3eOu5hFhf8m05FMdUsLrxZvICnGjpcWMCA9Nplqt394nBnoS7zdwcS0Id3++xERERFpb926dbz00ksUFRXhdrtDjv3v//5v2O2FncGprKxk1qxZjB49mvPOO48DBw4AcN1117Fw4cKwOyDSF00IDFPbXLMPm2ELlIs2SI31l1subqxiSGKmdX4wS7O1bj+NnhZrf3CYWnxMLGDg9vrPXFW2Maz+DIzP4L5JV3LT6P/gs6p9mKaBD491fETSQLxm6JC1iWlDrMIIIiIi0s3MCG29zNKlSzn55JPZsmULr7zyCq2trWzevJl3332X1NTULrUZ9r9e5s+fT0xMDEVFRSQktK2Ncemll7Js2bIudUKkrwnOwzm40EBcoPrZvsYqBidkWOcbGP4SzaaPjTVF1v5goQG3zwOY/nk4wJv7P6OutTHsfn1YXkiRq5KEmFh8eK3sUVpsEuDP3hiBEgOnZWl4moiIiETWr3/9ax5//HFee+01HA4Hv//97/n666/5/ve/z9ChQ7vUZtgBzttvv83DDz/M4MGDQ/YXFBSwZ8+eLnVCpK8JVlLbWV9Oo8dtBTi+wDcr+xqrGdQuwLFZpQRC5+HkJ2aRFpvYll0xwcBOo7eFfxZ9GHa/Xti1BoChCSlWpTSfz0az1x1s3loPZ3ZIKWsRERHpTsEiA9299TY7duxgzpw5ADgcDlwuF4ZhMH/+fP74xz92qc2wAxyXyxWSuQmqqqrC6XR2qRMifU12XArZccn4MNlSu98KcBoCw8+KG6vIjkvFFpi3ZhgGvsDEwA3Vu612DMNgilVNzf+4qdV/7J9FH9LQrqz0N9lZX8aaikIMoNxdbWVvTKDS3QAE18GBGFsMGc6kLj13ERERkSOVnp5OfX09AIMGDWLTpk0A1NTU0NgY/mgV6EKAc9ppp/HXv/7VemwYBj6fj0ceeYQzzzyzS50Q6YsmpLbNwykIlIpuaG0GYF9TNXbDRkpsPAA+02dlcDbX7qXF22q1E5yH47THBM41sGGn3tPEy3vXHHF//rH7YwCOyxhKk9cfaPl8BmBQ3lwbcm6mI+XIn6iIiIiET3NwADj99NNZvnw5AJdccgk//elPmTdvHpdffjlnnXVWl9oMu4raI488wllnncW6detwu93cfvvtbN68maqqKj78MPwhMyJ91YS0Qaws/ZpNNfu5euQp5MWnsb/JvwbOvsYqAPLi06ltN5fGYYvB7fOwpa7Ymn8TDHB8+ACTNEcCdZ5G4mLgxaL3uWToKSTEHD57WtfaxGv71gNgt3msMtBmYKBatdvlf2z6h6iNDARkIiIiIpH09NNP09zs/wL47rvvJjY2lo8++oiLLrqIn//8511qM+wAZ+LEiWzbto2nn36a5ORkGhoa+N73vseNN97IwIEDu9QJkb4oWGhgS+1+AMak5FoBTllzPS3eVoYnZbGlbp91TZzdidvnYX3VbivAKUgeSILdQWNgnsyE1DzWVe3FZzZS29rIK8VruTL/jEP2w+31cP+Xr9LsbWVUUjbb6/2FD3w+G2DgNGJoNf0Zo+D8mxFJCnBEREQiKhJzZnphBicjo92cZJuNO++886jb7NI6OKmpqdx9991HfXORvqwgxR8kFLmqaPa2UpCSy8rSLcQYNjymjwNNNYxMyrWyJpjg9voX8PQXGvAP+Yyx2ZmUNoyPK7djAEWNFTww5SLu2vACzhgvS3au4KIhM4izOzr0ocnjZsFn/2BNRSGxNjun54zkxb3FmCZ4fP61q9KdiZS11ATm3xj4gLyEtGPwGxIREenHIjGkrBcGOAA+n4/CwkLKysrw+UKXrTj99NPDbq9LAU5NTQ2ffPJJp524+uqru9KkSJ8zwJlESmw8da1N7GqoYExKLmBgN+x4TB/7GqsZmpgVck29p4VYG3xZswePz0uMzQ74y0V/XOlfFPRAUw3HZQzjqvwzWLr3XRq9Lfyx8G1uGfMfIW3VtTZx86d/54vqIuLtDh4/4Qoe/9q/WFZyTAJVgXk4zkDp6uBnos9nMCg+PXK/GBEREZGAtWvXcsUVV7Bnzx5MMzRCMwwDb+DL33CEHeC89tprXHnllTQ0NJCSkoIRHMwf6IQCHBE/wzAYmZzF+qoidtSXMSnNX1rdv6aNv5LaCZnDrfPt2PDiI8HupNHbwrb6/YxPHQK0zcOxGzZ8po9NNcXcNPY7rK38mqKm/bxU9CHfH3oqufFpAFS2NHDDx0vYVl9Kckwcz5x4NTbDR3FTBaYJE1KH8X7ZNgBafW0LfgY/VwYpgyMiIhJZyuAA8OMf/5gTTjiBN954g4EDB4bEFl0VdhW1hQsXcu2119LQ0EBNTQ3V1dXWVlVVddQdEulLRiVnA7CjvowhienE2WPxBqKI4sYqBiW0z5SYgMHQhAEArG9XLnp86mBiDXug0AB8VbsXu2Hj6W9diw0bJj5+8umfafV52ddYzTUf/Q/b6ksZ4Exi8YzrmJw+hOd3r7buMjhwD4AGT5N1e/9nrWEFSiIiIiKRtH37dn79618zbtw40tLSSE1NDdm6IuwAZ9++fdxyyy2droUjIqFGBaqRFdaXYTNs/nLRwcU+m6qJszuICwwRCxaKTnX4159ZX9W24KfTHmtlcwzg44pCADKdyVyV75+rc6C5jLs3/JMfrvkTexuryItPY/GM6xmVnMO6ykLeL98MQEpMIr7giqOYuDzNgZ/8wU1abLzVJxEREYkMLfTpN336dAoLC7u1zbCHqM2ePZt169YxYsSIbu2ISF80Mtk/x2ZHfRkAo1Ny2VizF/BncAAynUnsb6omUGcAu+H/3uHLmt34TB+2wOOp6fl8UbMbm2GwubaYnfWljEjOYe6IM/nf4o+o9zTxbumXeHx2RiRl8fgJV7C+upBffLmGwoYDgH8I2unZEyhtaVv3xgzsDw5Py4lLi+wvRURERPq1L7/80vr55ptvZuHChZSUlDBp0iRiY0O/ZJ08eXLY7Ycd4MyZM4fbbruNr776qtNOfPe73w27EyJ91cjAELV9jTU0edyBQgME9lVjmiYD49Ot8tEAte5mnLZY6lqb2O0qt0o2T03P5y+7IM4eg8vj4bV9n/PTsefitMfywxFn8eS214m1e8lPzOWEAYOY98mTuDz+QgIOWwx27DR43JyaNZY/Fa7spLf+RT8HJ6rAgIiIiETO1KlTMQwjpKjAtddea/0cPHbMigzMmzcPgPvvv7/Dsa52QqSvynQmke5IoNrdyK6GCgraBThNXjfVbhf5iVl8VrXT2l/cVMXEtCF8VrWTL6p3WwHO5PRh2DBo9vnXrHlz3+fcOPpsYmx2Lhg8nb/tXkW1u4EDLft4bZ9/bZ1B8Zl8b8hJTEgZxrxPFhFrxPCtzFE88OX/YhgQnMZnmviXETVhWGLb/BwRERGR7rZr165vPukohB3gHFwWWkQOb2RyNusqd1NYX8aZuWOB4LcSUNxYzehk/wK5/rVwTCpa6rlg8FQ+q9rJhurd/OeQ6QAkxsQxKnkg2+r3kxQTR5XbxYfl2zgjZxxxdgc/yD+Dp7a9gYHByQPGctGQGXwrswCbYePprf8G4LiMERgY1Hqa/AFOIMJpX5UxtPCBiIiIREQ/rqI2bNiwiLbfpXVwROTIBQOcHfVlfHfIVPLi0yhp9g9J29dYxcikHGuxT7thw2ua1jyYL9pVUgOYlp7Ptvr95CWksa2ulNeK13FGzjgALh16GkMTshmelM3A+LZVgQ80VfNS0UcAXDT0JEqbawJH2j4F/XlX/1yfPAU4IiIiEReJogC9scjAQw89RE5OTsgQNYDFixdTXl7OHXfcEXabYVdRA3C5XLz55pssWrSIJ598MmTrSfn5+RiGEbL95je/CTnnyy+/5LTTTiMuLo4hQ4bwyCOP9FBvpb8Y2a5UNMCYlFwrtNjXVMWQxEzr3OBY1DibE7tho6S5htKmGuv4SQNGA7DHVQ6YfFC+lYqWesA/RPTkrLEhwQ3As9vewu3zcFz6CE7LGkdJU23Icf8t22rO56lEtIiIiBwjf/jDHxg7dmyH/RMmTGDRokVdajPsDM769es577zzaGxsxOVykZGRQUVFBQkJCWRnZ3PLLbd0qSPd5f7777fmCQEkJydbP9fV1XH22Wcza9YsFi1axMaNG7n22mtJS0vjRz/6UU90V/qBUUn+SmqFgQCnICWXVaVbIDBELc2RiN0w8GHiC6RySlvqKEgeyNd1+/iiZjdnx08F/AHOjAGjWVOxjaRYJw2tLfx73wauGnFap/feVFPE2yVfYGBwy9jzMAyDA1YGx88fUrUFOAPju1ZzXkRERMLUCzMu3a2kpISBAwd22J+VlcWBAwe61GbYGZz58+dz/vnnU11dTXx8PGvXrmXPnj0cf/zx/O53v+tSJ7pTcnIyubm51paYmGgde/7553G73SxevJgJEyZw2WWXccstt/DYY4/1YI+lrwtmcPY31dDoaQmppFbcWIVhGCTFxANtc2L2uiqYmp4PwIZ2w9QMw+D28RcSb3fQ5G3BAF4rXhdShSTINE1+v/UNAM7LO46xKYMAKAlkhNoXGDACj+LssTi1Bo6IiIgcI0OGDOHDDz/ssP/DDz8kLy+vS22GHeBs2LCBhQsXYrPZsNvttLS0WEO9/t//+39d6kR3+s1vfkNmZibTpk3jt7/9LR6Pxzq2Zs0aTj/9dBwOh7Vv9uzZbN26lerq6s6ao6Wlhbq6upBNJBzpzkQyHP5Ae0d9OaPbDVGraPYPL8t0JoVcs7exislp+QB8Ub0n5NjA+HR+XHA2ADYb7HKVsSmwtk5775ZuYmNNEXH2WP6r4DvW/uLGStp/ZWRiWGvvpMZqAV8REZFjwozQ1svMmzePW2+9leeee449e/awZ88eFi9ezPz580NGZYUj7CFqsbGx2Gz+fwxlZ2dTVFTEuHHjSE1NZe/ejv/IOpZuueUWjjvuODIyMvjoo4+46667OHDggJWhKSkpYfjw4SHX5OTkWMfS0ztOrn7ooYe47777It956dNGJmdTVbnLKjQQZ4ullVaq3A2AP2jZ5SqzFvssaqxgSrq/wsjOhlLqWptIiY232rt46AzeOrCBr2qLsRnw/+37jEnpQ63jLd5Wntnmr5x2Zf7pZMe1DTvbWFME+LNFpum/X4xhx2P6rEBMRERE5Fi47bbbqKys5Cc/+QlutxuAuLg47rjjDu66664utRl2BmfatGl8+umnAJxxxhncc889PP/889x6661MnDixS504nDvvvLND4YCDt6+//hqABQsWMHPmTCZPnsyPf/xjHn30UZ566ilaWlq6fP+77rqL2tpaa+vpIE56p4IU/zC1wvoybIaNEUn+xw2eFjw+L8MTs0LOr2xpIN7uYEhCJiYmG2tCszh2w8ZdE76HzTAwDFi2bz1NHrd1/J9Fa9jfVM0AZzI/yD/d2u/ytFhD1IJMs23+TY7m34iIiBwTwSpq3b31NoZh8PDDD1NeXs7atWv54osvqKqq4p577ulym2FncH79619TX+8fVvPggw9y9dVXc8MNN1BQUMDixYu73JFDWbhwIddcc81hzxkxYkSn+6dPn47H42H37t2MGTOG3NxcSktLQ84JPs7Nze2sCZxOJ06nM/yOi7QzMim0ktrY1IF8Xb8Pw4Da1iZGp7SNMbXhX3Rzb2MlU9OHs7exkg3VuzklK7TCSEHyQK7OP4Mlu1bhNlt5c//nXDT0JKrdDTy3810Aflwwm/iYtiGZL+35CBOwBWKa4KpWXtP/06CDKrCJiIiIHAtJSUl861vf6pa2wgpwTNMkOzvbytRkZ2ezbNmybunIoWRlZZGVlfXNJ3Ziw4YN2Gw2srP9/7icMWMGd999N62trcTG+idSL1++nDFjxnQ6PE2ku7SVii4H/AEOxf5j1W4X41MHWWvheE0TMChyVTIlfRiv7VvXYT2coB+O/DavFH9CbWsjf97xLhcNPYk/F67A5WlhdHIe5+VNs85t9LTw910fhFwfzN54TP9KOPlJA7rxWYuIiMgh9eOFPiMtrCFqpmkyatSoqBymtWbNGp544gm++OILdu7cyfPPP8/8+fP5wQ9+YAUvV1xxBQ6Hg+uuu47Nmzfz4osv8vvf/54FCxb0cO+lrxsVCHBKmmtpaG1mVHKOdaza7WJQQoZVQS1YEG1vYxVTAoUGttQW0+Jt7dCu0x7L7eMuBKDKXc/iwnd5pfgTAH465jxsRttb/OWiT6hrbSK0wEDo/4P9FBERkcjSELXICSvAsdlsFBQUUFlZGan+dJnT6WTp0qWcccYZTJgwgQcffJD58+fzxz/+0TonNTWVt99+m127dnH88cezcOFC7rnnHq2BIxGX4ogny+lfk2lHQzlD2y3uWdlST4zNjsPmT6gGZ8TsdVUwOCGTDEcSraaXLXXFnbZ91sBJZDn9c2f+uGM5XtPHaVnjOD5zpHVOQ2szf9/1nvU4WGAAsO4LUNAu8BIRERHpjcKeg/Ob3/yG2267jWeffTYiRQW66rjjjmPt2rXfeN7kyZN5//33j0GPREKNTM6ivKWeHfVlTE4bjN2w4cPHrgb/sLXkmDgq3Q3tKqlVYhgGU9Pzebd0ExuqdzM1fXinbf9o1Hf41aZ/YRj+AgQ3jj6HwvoS1pRvZ23FdjZU78bt85ASG099ayPQtsBnamwC5S31GEBibNwx+E2IiIiIhqhFTtgBztVXX01jYyNTpkzB4XAQHx8fcryqqqrbOifSl4xMzmZtxU521JcFFveMo87TSJHL/57JdCZT6W6wUjh7Xf5M6ZRAgHOoeTgAswdO4dEtr9HkbSEnPp0bPvkzFS31IefkxqUxJmUg75V/Ze0zTUiJiae8pZ5YW9gfByIiIiJRJ+x/0TzxxBMR6IZI39dWaMBfSS3DmUidp9Eq2zwwPp1t9QesDE6lu4GG1mampOcD8GXNHrymz1qUsz2HPYb/GHQ8L+75KBAYGThtsRyfOZyTBhQwY0ABwxKzWPj536whcMEhasF5OvF2R4d2RUREJEKUwYmYsAOcuXPnRqIfIn1ecAJ/YSDAyYlLZbernIoW/2KfwxOzWY0/u2JgYGKyt7GSguRcEuwOXJ4WdtaXUpAysNP2rxk5kxq3i+y4VE4aUMDU9Hwc9tC3+P7GauvnYIno1kAFtfYLiYqIiIj0Vl0ak+L1ennllVfYsmULAOPHj+eCCy4gJkZDXEQOZUSyv9x5WXM9da1NDEpIh0oClc1gTLvAxWeaGIZ/LZxxqYOYlDaMjyu3s6F61yEDnAHOZH419bLD9mF/Y1VIgQHAWiA0w5F4NE9PREREwhCJqmeqouYXVhU1gM2bNzN69Gjmzp3LK6+8wiuvvMLcuXMpKChg06ZNkeijSJ+QEhtPdlwK4B+mNjzJH/A0elsAmJQ+FCBQLtr/CVXUbh4OwBc1e7p8/4bWZpp97nZ7/IPVXB7//bMCfRMREZH+4b333uP8888nLy8PwzB49dVXQ45fc801GIYRsp1zzjkh51RVVXHllVeSkpJCWloa1113HQ0NDcfwWXQUdoBz/fXXM2HCBIqLi/n888/5/PPP2bt3L5MnT1a5ZZFvMKrdgp/Bkswen49mbyvZcakdzi9qPCjAqd6NaXbt65nS5lqrgIG/CYNEuxOX1x/0DIzveH8RERGJEDNCWxhcLhdTpkzhmWeeOeQ555xzDgcOHLC2f/zjHyHHr7zySjZv3szy5ct5/fXXee+993o8Jgh7TNmGDRtYt26dtXgmQHp6Og8++CDf+ta3urVzIn3NqORsPiovpLC+jFOzRln7ixoqGJ06EKctlhZfa7u1cPwBzoTUwcQYdspb6jjQVE1eQkbY9y5pqmkrMBD4/8D4NLbXl2EYMCg+/DZFRESki6KgyMC5557Lueeee9hznE4nubm5nR7bsmULy5Yt49NPP+WEE04A4KmnnuK8887jd7/7HXl5eeF1qJuEncEZPXo0paWlHfaXlZUxatSoTq4QkaD2ldTSnf45L4YBW+tKgLaJ/sFApMhVAUCc3cHYFP+HxIbDlIs+nJ0NpYHhb4HPVBOynG3D0jKdSV1qV0RERKJLXV1dyNbS0tLltlatWkV2djZjxozhhhtuoLKy0jq2Zs0a0tLSrOAGYNasWdhsNj7++OOjeg5H44gCnPa/oIceeohbbrmFf/3rXxQXF1NcXMy//vUvbr31Vh5++OFI91ekVxsZKDSwo74Mpz3WKvm8vd4f4AxwJvtPDAQiNa2N1AeKEEwJLPLZ1QDnq9pioG14GoQu7JnqUBU1ERGRYyVYZKC7N4AhQ4aQmppqbQ899FCX+njOOefw17/+lRUrVvDwww+zevVqzj33XLxefwXWkpISsrOzQ66JiYkhIyODkpKSo/r9HI0jGqKWlpaGEfzqFzBNk+9///vWvuCcgPPPP996wiLSUTCDU9HSQK27kQS7g3pPM7sb/N+G5MVnsKVun7UWDvgLDUxIG8yU9GE8vxu+qNndpXvvdpV12Nd+TZ2U2IQutSsiIiLRZe/evaSktI3ScDqdXWrnssvaqrNOmjSJyZMnM3LkSFatWsVZZ5111P2MlCMKcFauXBnpfoj0C4kxTgbGp3KgqZbC+jJSHQnUe5rZ11QF4K+sFhgBapr+4Wt7XBX+ACdtGAB7XOVUuxtId4Q3pKy8pc7fLm3Bk9vrsY6nORTgiIiIHDMRnIOTkpISEuB0lxEjRjBgwAAKCws566yzyM3Npaws9AtUj8dDVVXVIeftHAtHFOCcccYZke6HSL8xMjmbA0217KgvJ9OZRHFjlb/CGTAmZVC7M03AYG+gklqqI5HhidnscpXxZfUezsiZcMT3NE0Tl6e5w/5ad5M1L0cLfYqIiMjhFBcXU1lZycCB/jX5ZsyYQU1NDZ999hnHH388AO+++y4+n4/p06f3WD+7tDJnc3MzX375JWVlZfh8vpBj3/3ud7ulYyJ91cjkbD4o286O+jJy49L4giIaWltweVoYk9zx247gWjgAU9Pz2eUqY0P17rACnCJXOSZmyAKfiTFOSpr9WZ1Ym504e2zXn5SIiIiEJRoW+mxoaKCwsNB6vGvXLjZs2EBGRgYZGRncd999XHTRReTm5rJjxw5uv/12Ro0axezZswEYN24c55xzDvPmzWPRokW0trZy0003cdlll/VYBTXoQoCzbNkyrr76aioqKjocMwxDc3BEvkFwLZzC+jImpvu/AcHwBzLBtXGMdpNw9ja2vdeOyxjJK8Wf8PaBL/ivgrOPOChZU7Hd+tk0/SmbIQmZbK8rB5S9ERER6Y/WrVvHmWeeaT1esGABAHPnzuXZZ5/lyy+/5C9/+Qs1NTXk5eVx9tln88ADD4TM6Xn++ee56aabOOuss7DZbFx00UU8+eSTx/y5tBd2gHPzzTdzySWXcM8995CTkxOJPon0ae1LRZ+W024tHFcl41LzOqyFU+SqxDRNDMNgZs54cuPSKGmu4ZW9H3N5/qnfeD+f6eN/964N2WeaBoMSMthccwC7DdJjE7vt+YmIiMgRiIJ1cGbOnHnYBcTfeuutb2wjIyODF154IbwbR1jY6+CUlpayYMECBTciXTQiaQAAVW4XDpv/OwYD2BMYinbwWjj1nmZqWhsBiLXFcO3IbwPw112rafK4v/F+K0o2UtRYgWmGfu4lx8RZ90hzqsCAiIjIMWVGaJPwA5yLL76YVatWRaArIv1DQoyTQQnpADS2C1CCc22Ca+HYDMOaM7O33Tyc8/KOY1B8BtXuBl4+KDNzsFafh0Xb3wba1r8JfvY5bW3D21JVIlpERET6iLCHqD399NNccsklvP/++0yaNInY2NA5ALfccku3dU6krxqZnMW+xmrqAot4QluAMzgh078WTrt5OEWNlUxOHwpAjM3OtSO/zQOb/sXfdq3mP4dMJzGm8/r2r+79hH1NVThsMTT5PBjtjrX/kidVc3BERESOKQNC/i53V5vShQDnH//4B2+//TZxcXGsWrUqZAFQwzAU4IgcgVHJ2bxXuo2y5nprXzDAGZ08kOUlX7YbE2tQ5Aot6jF74FSW7FzJ3sZK/lW0hrkjZna4h8vTzOKd7wKQEpNAk6c+5HiTx219EiqDIyIiIn1F2EPU7r77bu677z5qa2vZvXs3u3btsradO3dGoo8ifc7IJH+hgX2NNYC/alq120Wdu4nRKf7Kau0zLMG1cIJibHauG+lfQfj5Xe91usbNC7vfp9rtYnBCJpUtLmu/CSTGxFHpbtuXqkU+RUREji3NwYmYsAMct9vNpZdeis0W9qUiEjA21R/EbK0rIcawW/v3uCoZmjjAety+ktrBvjNwCsMSs6jzNPHing9DjlW21PPC7g8AuGToyXjMtvWqTBOGJmSyr7Haal9lokVERKSvCDtKmTt3Li+++GIk+iLSb4xMziIpxkmzt5Xk2Dhrf5Grktz4NAwM2o3+ZG+gVHR7dsPG9SNnAfDC7g+obzefZ/GOd2nyuhmfOpgsRwpASHtDEzPZ31RjPU5TBkdEROSYCi702d2bdGEOjtfr5ZFHHuGtt95i8uTJHYoMPPbYY93WOZG+ymbYmJg2iLUVO4ltl8EpclViN2ykOxKpcjdgM8BrgsvbQpXbRaYzKaSds3In8tzOHHY2lLJ0zwfMG/UdilwVvFr8CQA3jT6X9VW7rfODMVJ2XArN3lZs1hwcZXBERESkbwg7g7Nx40amTZuGzWZj06ZNrF+/3to2bNgQgS6K9E1T0ocA4A1EHf61cPzFBAbFZwD+LE3QwYUGwB8oBbM4/9j9IbXuRv6w/W28po+TB4zhuIwR7GwoO+gqgwS7M3C9f4+KDIiIiBxjmoMTMWFncFauXBmJfoj0O5MDAU7oWjhVABSk5LKxtgifNXfGYG9jJdMy8ju0MzNnPAXJA9lef4D7N/2TD8u/xsDghtGzAdjVIcAJBk6m9TmoIgMiIiI9QAFJRHS5UkBhYSFvvfUWTU3+cf8Hzw8QkcOblD4YAJenxb/D8A9RM02TMcl5QOjn3p5OMjjgz+LMG+XP4nxY/jUA5+ZNpSB5IB6fl90N5da5wfY8Pl9IGynt5gGJiIiI9GZhBziVlZWcddZZjB49mvPOO48DBw4AcN1117Fw4cJu76BIX5XmSGBYYiZmu2W56j3NVLsbGZbUsZLa3k4qqQWdljWOMSn+oMhhi+FHo84GoLixilbTG3Jugj0upGx0YoyTWFvYyVwRERE5CioyEDlhBzjz588nNjaWoqIiEhLahrVceumlLFu2rFs7J9LXBYepAcTZ/QU79rgqGJowoMO5RY2dZ3DAv8juT8fMIc4ey7Ujv01ufBrQcXiaacKwxEwONNdY+1QiWkRERPqSsL+2ffvtt3nrrbcYPHhwyP6CggL27NnTbR0T6Q+mpA/h9eL1ADhsdprwUOSqZGr6UGINO614sQE+2oavGe3rPbdzXMYIVs26P2TfzobSkMcm/hLRW+vaAh8VGBAREekBkSgKoAwO0IUMjsvlCsncBFVVVeF0OrulUyL9xeT0wR0+i4pclRiGQU5cKuAvCGCa0OLzUN5SF1b7W+v8Q0gNo61E9JCETPY31lhD31QiWkRERPqSsAOc0047jb/+9a/WY8Mw8Pl8PPLII5x55pnd2jmRvm5UcrY1NM3t8wD+AAdgeFI2QKCSmhly7Eh9Xbv/oD0Gmc4kmrxtldtUQU1EROTY0xycyAl7iNojjzzCWWedxbp163C73dx+++1s3ryZqqoqPvzww0j0UaTPirHZGZsykE11e6wAZ08giClIHsj75V+HZHiKGis5IXPEEbXt8XkpbTfXJtiOw+YPqBJiHDT73BqiJiIiIn1K2BmciRMnsm3bNk499VQuuOACXC4X3/ve91i/fj0jR46MRB9F+rRpGcNoX2W9yFWFaZoMTexYaOBwldQOVtxYha/Twbj+fQkxDgBSHRqiJiIicsxpoc+I6VJt2NTUVO6+++7u7otIvzQ1Yyh/3eX/2YZBk9dNeUt9SIATnC9TdIi1cDrzRXVo0Q/ThKSYOGrd/rWrHDY7oCIDIiIi0rd0KcBpbm7myy+/pKysDN9BCwZ+97vf7ZaOifQXk9PbKhJmOBOpaHFR5KqkIDkH8BcICFZS23lQ2efDWVNRaF0P/i91Bidksr+pFvAvEAoqMiAiItITIjFnRnNw/MIOcJYtW8bVV19NRUXHb5INw8Dr9XZylYgcSqYzCYcthlbTQ7zdAfgDnBMyh5MY48TlacFu2PCZJgeaavCZPis4OZwttfs67BuamMn+pmogWLxARQZERER6hMpER0zYc3BuvvlmLrnkEg4cOIDP5wvZFNyIdE26IxHAmjOzp8E/12ZIQqZ/v+nDNE1aTS+lzUdWKrqsfYEBE8Bgavow9jf597f6/O9XLfQpIiIifUnYAU5paSkLFiwgJycnEv0R6Zdy4/1r3gTLNwcrqY1M8r/P2n8hcySFBopdVVYA08bglKwC9jfWhNwrTXNwREREjj0VGYiYsAOciy++mFWrVkWgKyL9V36Sv6BAfWsz4C8HDTA0MavDuUWN31xo4O0Dm6y5N+D/vMtPHEBSbFwgsDFpDAQ4KaqiJiIiIn1I2HNwnn76aS655BLef/99Jk2aRGxsbMjxW265pds6J9JfjEjyBzIenxcw2Ouqwmf6GJqYaZ0TjFf2NHxzgPNh2baQa0wTTskabWVvMh1J1HgaAA1RExER6QkqMhA5YQc4//jHP3j77beJi4tj1apVGO2+JjYMQwGOSBcMcCb7fzDAjoHb56GkqY4hCe1KRRv+TExhQ+lh2zJNk631+/0/0xbknJo9mgOB+TcD4pKpaWggOSYO+xEULBARERHpLcIOcO6++27uu+8+7rzzTmw2/cNIpDsEiwwYQILdSb2nmSJXJVPSh/j3G/41cjwm7HaVH7at3a5KGj0t2Nu9PZ02J9PS8/nH7o8D9/PPu1EFNRERkR6iKmoRE3aE4na7ufTSSxXciHSjYIAD4POXPKPIVUl8jMPK7pim/5Owork+MJStcx9X7MQI5KgNwz88bfqAkTjsMVaJ6OTYOEAFBkRERKTvCTtKmTt3Li+++GIk+iLSb6W1y6S4PP5CA8FKavmBQgMm/mDFh0lJc+0h2/q4fAfGQftOzR4DYM3B8a+3owIDIiIiPcUwzYhs0oUhal6vl0ceeYS33nqLyZMndygy8Nhjj3Vb50T6C2uImtE2b2aPy19MYEjiANZV7Qw5v8hVyeCEjA7t+Ewfn1TsDGnHBE7NGg1gZXBibXYAUpXBERER6RkaohYxYQc4GzduZNq0aQBs2rQp5Fj7ggMicuSc9lgS7A6rdDPAjvoyAIa2LzQQ+H+Rq4KTswo6tLO1rhSXt4lYe9u5mY5kcuJTMU3TyuDYAgdTVUFNRERE+piwA5yVK1dGoh8i/V66I5HGprYAZ39TDQ2tzQxN7FhJbVv9gU7b+Lii4/C0KenDAKhtbbICqOA8HxUZEBER6RkqEx05qhQgEiWC83CMwH8AhfVlIQGOLZAlXVO+nWZva4c2PqnYZRUYCDozZzwA+xv9w9MGOJNoCMzzUQZHRERE+hoFOCJRIjgPx26zWRmW7fWlDIpPx4aBYQCmiWmalLXU8d/blodc3+rz8lnlnpAKatAuwAmsgZMXn05taxOgOTgiIiI9xozQJgpwRKJFMMDJjku29m2vKyHGZicvUFCg/efWC7s/4vOqXdbjTTXFNHlbrPk14F9TJy7GXzFtX2D+TV5CGrXuRkBV1ERERKTvUYAjEiWCQ9TS282L2V5fCsCwdsPUwMCGgYnJL798mUZPC6Zp8ufC9635N8FAaEhipnVVsIJaXnwadYEMjtbBERER6RnBOTjdvYkCHJGoEczgJAYyLgBb60owTZMh7SqpDU3IwGuaxBg29jVV88TXy1hRsoX3SrdhD4xLCwY6U9Pyrev2WxmcdGpa/RkcFRkQERGRvkYBjkiUSAsEOHExsYxPHYRpgsvTwoGmGoa2y8QUJOcwwJlCq88HwMt7P+GBL18FYGL6wJA2x6bmWT8HMzhZzmSrQIGKDIiIiPQQzcGJGAU4IlEimMGpdTfy0LSLrLk0i3d8ELIWTnFTFQ9OvQQDG8EFi+u9LgYnpGHiC2kzPzELIGQNnJRYJwB2w0ZSTFwEn5GIiIgcioaoRY4CHJEoEZyDU+12MTw5y8q+/O+ez7C1e6vubihjWvowrh81EwDT9FdMG5acRnFjJdBWQW1Ykj/Aab8GjtPuHwKXHBunxXlFRESkz1GAIxIlghmc6kCFs1m5/vLOHtPLo1+9jcMWg2GAx/RR3FjFD0ecRpzNaV3/SWWhtb4N+IeiBTM07dfAaQ4EOiowICIi0oM0RC1iFOCIRIlggNPkddPsbWV0Si4AdsNgc+1+Eu1tw8l2NZTx0p5PaWhtBQxrqBpg/TwsMDwN2tbAGRifZhUYSNH8GxEREemDYnq6AyLilxTjJMaw4zG91LhdVoDjZ1LZ4sIW+EpiZelX/HvfZmyGybiUgXxdt88/7tZoG56Wn9QW4Ox1VQH+NXCCJaJVQU1ERKRnac5MZCiDIxIlDMNoNw+nkZy4FJJj4/BhMmPASHztPgT/vX89GG5i7T621e/D1i6wCWqfwfmqdj8AY1JyrUU+VUFNRERE+iIFOCJRpG0ejgvDMChIzgHg2wPHkRiYT2MY/mFopmlwYuYoLht2MjePmc2g+AF4TQOn3Z+YzW8X4Gyu3QfAxLTB1AYzOJqDIyIi0nP8f8y7fxMFOCLRJD2QwalxuwAoSPYPU9vfWBNSNc3tjWHuiDN55sRrWTj+P7h6xBksmn4tc/Km4TH9paLzk7IBqGpxsS9QZGBcal5bBkdD1ERERKQPUoAjEkUOrqRWkOLP4GyrL+H8wdOs8wbHpzOv4IyQa3Pj07hu1On4TB/xdgfZzhQANtf4szf5iQNIiY1vl8HREDUREZGeonVwIkcBjkgUSWs3RA1gdCDA2V5XSrojkaSYOAwD7px0LnH22A7X73ZVAP75N8E1bjbXFgMwIW0QALWtyuCIiIj0OJWJjhgFOCJR5OAhaqMCc3DKW+qpbW1iaOIAALx4O71+j6scCJ1/s6mmbf4NQJ1bGRwRERHpuxTgiESRg4eoJcY4GZSQDvizOEMSMgEoCmRqDra7wR/gDEvyB0KmabYLcPwZnOA6OCoyICIi0nMMX2Q2UYAjElXSDxqiBjA6uW0eTjCD82nlDqtYQHsHZ3D2N9VQ7XYRY9gYk5KLaZrWOjgpDmVwRERE+rP33nuP888/n7y8PAzD4NVXXw05bpom99xzDwMHDiQ+Pp5Zs2axffv2kHOqqqq48sorSUlJIS0tjeuuu46GhoZj+Cw6UoAjEkXSDhqiBjAqMA+nsK6UsSn+LMwnlYVcsPoRnt66jKoW/4eIaZrstgIcfwW1TTX++TejU3Jx2mNp9rbi9nn891IGR0REpOdEwRwcl8vFlClTeOaZZzo9/sgjj/Dkk0+yaNEiPv74YxITE5k9ezbNzc3WOVdeeSWbN29m+fLlvP7667z33nv86Ec/Cq8j3azXBDgPPvggJ598MgkJCaSlpXV6TlFREXPmzCEhIYHs7Gxuu+02PB5PyDmrVq3iuOOOw+l0MmrUKJYsWRL5zoscoWAGp6ZddmZ0oFT0tvpSTs0aw2+mXkFB8kAavW7+uus9Llj9Wx7b8jpb6vbR4GnGhsGQRP9Qts0Hzb8JDk+LMezE2x3H7HmJiIjIsVNXVxeytbS0dHreueeey69+9Sv+8z//s8Mx0zR54okn+PnPf84FF1zA5MmT+etf/8r+/futTM+WLVtYtmwZf/rTn5g+fTqnnnoqTz31FEuXLmX//v2RfIqH1WsCHLfbzSWXXMINN9zQ6XGv18ucOXNwu9189NFH/OUvf2HJkiXcc8891jm7du1izpw5nHnmmWzYsIFbb72V66+/nrfeeutYPQ2RwwoGOLWtTXgD69kES0UX1pdiYvLt3In8/eSbePS4q5iQOpgWXytL93zENWv+G4BBCRk4bP7FPoPzb4IV1ILD09Ic8VaVNRERETn2IlkmesiQIaSmplrbQw89FHb/du3aRUlJCbNmzbL2paamMn36dNasWQPAmjVrSEtL44QTTrDOmTVrFjabjY8//vjofkFHIabH7hym++67D+CQGZe3336br776infeeYecnBymTp3KAw88wB133MEvf/lLHA4HixYtYvjw4Tz66KMAjBs3jg8++IDHH3+c2bNnH6unInJIKbHxGBiYmNS6G8lwJjEkIQOnLYZmbyvFjdUMTczEMAxOyx7HqVlj+bRyB4t3rOTz6l0ADA8s8Ok1fXxV6//2xCow4FaBARERkb5u7969pKSkWI+dTmfYbZSUlACQk5MTsj8nJ8c6VlJSQnZ2dsjxmJgYMjIyrHN6Qq/J4HyTNWvWMGnSpJAXYfbs2dTV1bF582brnPZRaPCcYBTamZaWlg5pPpFIibHZSYmNA9oKDcTY7IxM9n94bKsL/bAwDIMTB4xi0fR5/OHEeVyRfyo3FJwNwM76cpq8buLtDoYn+YsOWAUGVCJaRESkZ5lmZDYgJSUlZOtKgNOb9ZkAp6SkpNMIM3jscOfU1dXR1NTUabsPPfRQSIpvyJAhEei9SJvO5uEE18MprC895HXTMoZz69jzGBk4N1hgYEJqHnbD/1YPVl5L0yKfIiIiPSqSQ9S6Q26ufw5waWnovz1KS0utY7m5uZSVlYUc93g8VFVVWef0hB4NcO68804Mwzjs9vXXX/dkF7nrrruora21tr179/Zof6TvS+usVHRKoNBA3aEDnINtrg0tMABQGygyoAyOiIiIHM7w4cPJzc1lxYoV1r66ujo+/vhjZsyYAcCMGTOoqanhs88+s85599138fl8TJ8+/Zj3OahH5+AsXLiQa6655rDnjBgx4ojays3N5ZNPPgnZF4w420eZnUWhKSkpxMd3/g8+p9PZ79J60rPSA9mV9gFOQSArs/0wGZyDHVxgAPzFCwBSlcERERHpWV0o63xEbYahoaGBwsJC6/GuXbvYsGEDGRkZDB06lFtvvZVf/epXFBQUMHz4cH7xi1+Ql5fHhRdeCPjns59zzjnMmzePRYsW0drayk033cRll11GXl5eNz6x8PRogJOVlUVWVla3tDVjxgwefPBBysrKrMlOy5cvJyUlhfHjx1vnvPnmmyHXLV++3IpCRaJBZxmcYCW1va4qGj1uEmIOX+K5xdvK9sB8nZAMjlVkQBkcERGR/m7dunWceeaZ1uMFCxYAMHfuXJYsWcLtt9+Oy+XiRz/6ETU1NZx66qksW7aMuLg465rnn3+em266ibPOOgubzcZFF13Ek08+ecyfS3u9popaUVERVVVVFBUV4fV62bBhAwCjRo0iKSmJs88+m/Hjx3PVVVfxyCOPUFJSws9//nNuvPFGKwPz4x//mKeffprbb7+da6+9lnfffZeXXnqJN954owefmUiozubgZDqTyHAkUuV2saO+jEnpgw91OQBb60rwmD7SHYkMjE+19lsZHFVRExER6VHdPWcm2GY4Zs6ciWke+iLDMLj//vu5//77D3lORkYGL7zwQng3jrBeU2TgnnvuYdq0adx77700NDQwbdo0pk2bxrp16wCw2+28/vrr2O12ZsyYwQ9+8AOuvvrqkBdk+PDhvPHGGyxfvpwpU6bw6KOP8qc//UkloiWqpHeSwYG2eThHMkxtY6DAwMS0QSHr3dS1qky0iIiI9G29JoOzZMmSQ66BEzRs2LAOQ9AONnPmTNavX9+NPRPpXmmdzMEB/zC1tRU7rKFnh7O5pmOBAYAad3AOjoaoiYiI9Kh2ZZ27tU3pPRkckf4iI5DBqTo4wAmj0MCmdhmc9mqVwREREZE+rtdkcET6i0xnEgBVLQ0h+60hanWlmKYZMvSsvbrWJva4KoHQCmqmaVoLfaqKmoiISM+Khjk4fZUyOCJRJiMQ4NS4G/GaPmv/8KQsbBjUtDZScVDw095XNfsBGJyQbs3nAWjwtFjtaR0cERGRHmZGaBMFOCLRJi02AQMDH6ZV1hkgzh7LsKRMALYdZh5OcHjahIOGpwULDMTZYomzx3Z3t0VERESiggIckSgTY7NbRQAONQ+n8DDzcDYdosBArQoMiIiIRI3gELXu3kQBjkhUynD4h6lVHjQUrSAwD+ej8sKQ4WvtWQUGUjsvMJCiAgMiIiLShynAEYlCGc7gWjihAc5p2aOxYbC2Ygf3fvFKhyCntKmO8pZ6bBiMTc0LOWZVUFMGR0REpOf5zMhsogBHJBq1ZXBCh6iNS83jN8ddgt2w8VrxBn6+/mU8Pq91fHOtP3szKjmbhBhHyLXWEDVlcERERKQPU5lokShklYp2d6yWNjtvEnbDxh2fv8Sb+7/Ei49fT72YGJvdmn8z4aD5N9B+DRxlcERERHpcJKqeKYEDKIMjEpWC5Z0PXgsnaNbACfzu+MuIMey8tX8Td67/J60+L5utAgODOlxT26oMjoiIiPR9yuCIRKFgBufgIWrtnZk7jsdOuJyFn/2D5Qc24zV9VoBzcIlowCo5rUU+RUREep5BBBb67N7mei1lcESiUHAOzsFFBg52Rs4YHj/+Chy2GN4t2UK9pxmnLYZRgXLS7bVlcDRETUREpMeZZmQ2UYAjEo2CVdQOLhPdmdNyRvPECVfgtPkTsuNS84i12Tuc11ZFTRkcERER6bsU4IhEoUwrg+PCPIJvY07JLuCpE3/A6OQcLs0/sdNz2qqoKYMjIiLS07TQZ+RoDo5IFEoPZHBafB5cnhaSYuO+8ZrpA0byzzNuOuTxOquKmjI4IiIi0ncpgyMSheLtDhLs/nVsqtyHLjRwpLymj7rWZkBD1ERERKKCGaFNFOCIRKvgPJxDlYoOR0NrM2bgUy/lCLJBIiIiIr2VhqiJRKkMRxLFjdVUfkMltSMRLDCQGOMk1qa3vYiISE8zTBOjm6uedXd7vZUyOCJRKiOwFk71YdbCOVLBEtEpKjAgIiIifZy+yhWJUhmOQKno7sjguFVgQEREJKr4Alt3tykKcESiVWYgg1PVDRmcmsAQtTSHMjgiIiLRQEPUIkdD1ESiVHpgLZyqbsjg1LmDQ9SUwREREZG+TRkckSjVlsE5+gCnMtBGsE0RERHpYZEo66wEDqAMjkjUCs7B6Y51cMpb6gDIciYfdVsiIiIi0UwZHJEoFayiVtkNGZyy5kCAE5dy1G2JiIhINzBN/9bdbYoyOCLRKpjBafA04/Z6jqqt8pZ6QBkcERER6fsU4IhEqZTYeGIM/1v0aAsNlDcHAhxlcERERKKCYUZmEwU4IlHLMAzSu2EeTpPHTYOnGVAGR0RERPo+BTgiUaw7KqkFCwwk2B0kxcZ1S79ERETkKAXn4HT3JgpwRKJZsNDA0WRwNDxNRERE+hNVUROJYlap6G7I4Gh4moiISPQwfP6tu9sUBTgiUa07SkW3ZXAU4IiIiEQNlYmOGA1RE4liGY6jH6KmNXBERESkP1EGRySKZTi7Y4hacA0cBTgiIiJRwwxs3d2mKIMjEs26I4NTbmVwNERNRERE+j5lcESiWHeWiVaRARERkehhmCZGN8+Z6e72eitlcESiWDCDU+124TPDL41imqZVZCBbc3BERESkH1AGRySKpTkSAPBhUutuIj0wJ+dI1XuaafF5ABigDI6IiEj0UBW1iFEGRySKxdrspMX6g5xKd/jD1ILzb1Jj43HaY7u1byIiIiLRSAGOSJRLP4pKalaJaFVQExERiS4m4OvmTQkcQEPURKJepiOJXZRT1ZUMTrBEtObfiIiIRBUVGYgcZXBEolxbBif8UtEqES0iIiL9jTI4IlEuM1BJrUtzcKxFPhXgiIiIRBWTCBQZ6N7meitlcESiXEYgg1N9VBkcDVETERGR/kEZHJEol3E0GRytgSMiIhKdVCY6YpTBEYlymU5/gNOVKmrlLcEqahqiJiIiIv2DMjgiUS49kMGpcoc3RM1n+qgIBEUaoiYiIhJlfIARgTZFGRyRaJfZbh0cM4zUc5Xbhdf0YcMgw5EYqe6JiIhIL/XLX/4SwzBCtrFjx1rHm5ubufHGG8nMzCQpKYmLLrqI0tLSHuzxkVGAIxLlgnNwWnweGr3uI74uOP8mw5lEjM0ekb6JiIhI1wTXwenuLVwTJkzgwIED1vbBBx9Yx+bPn89rr73GP//5T1avXs3+/fv53ve+152/hojQEDWRKBcf4yDe7qDJ66aypYHEGOcRXWdVUNP8GxERkegTJUUGYmJiyM3N7bC/traWP//5z7zwwgt8+9vfBuC5555j3LhxrF27lpNOOumouxspyuCI9ALBIWbVYczDsdbA0fwbERGRfqWuri5ka2lpOeS527dvJy8vjxEjRnDllVdSVFQEwGeffUZrayuzZs2yzh07dixDhw5lzZo1EX8OR0MBjkgvkBGopFYZRiW1MmVwREREolcwg9PdGzBkyBBSU1Ot7aGHHuq0C9OnT2fJkiUsW7aMZ599ll27dnHaaadRX19PSUkJDoeDtLS0kGtycnIoKSmJ9G/nqGiImkgvEMzghFMquiJQIlpr4IiIiPQve/fuJSWl7e+/09n58PZzzz3X+nny5MlMnz6dYcOG8dJLLxEfHx/xfkaKMjgivUAwg1MVxmKfwSIDWXHK4IiIiESdCGZwUlJSQrZDBTgHS0tLY/To0RQWFpKbm4vb7aampibknNLS0k7n7EQTBTgivUCmNUStC3NwnMrgiIiIyDdraGhgx44dDBw4kOOPP57Y2FhWrFhhHd+6dStFRUXMmDGjB3v5zTRETaQXaCsy0IU5OMrgiIiIRJ8oWOjzZz/7Geeffz7Dhg1j//793Hvvvdjtdi6//HJSU1O57rrrWLBgARkZGaSkpHDzzTczY8aMqK6gBgpwRHqFcIsMtPo8VsU1VVETERGRzhQXF3P55ZdTWVlJVlYWp556KmvXriUrKwuAxx9/HJvNxkUXXURLSwuzZ8/mv//7v3u4199MAY5ILxBumeiKQCAUY9hJi02IWL9ERESka7q6MOc3tRmOpUuXHvZ4XFwczzzzDM8888zRdOuYU4Aj0guEm8FpX2DAMLo7/y0iIiJHLUoW+uyLVGRApBfIcPgDnHpPM26v5xvPL9caOCIiItJPKYMj0gukxMYRY9jwmD6q3S5y4lMPe3651sARERGJbj4TjG7OuPiUwQFlcER6BZthIy0wD6fyCCqptQ1RU4AjIiIi/YsCHJFeIrgWTvURrIUTzOBoiJqIiEiUiuBCn/2dAhyRXiI4D+dIMjjBNXAGaA0cERER6Wc0B0ekl8hw+oeoVR1RBsc/RC3bqSFqIiIi0SkSGRdlcEAZHJFeI5jBqdIcHBEREZFDUgZHpJcIZnC+aS2cJo+bBk8zoDk4IiIiUUvr4ERMr8ngPPjgg5x88skkJCSQlpbW6TmGYXTYDl6hddWqVRx33HE4nU5GjRrFkiVLIt95kW6QGcjgVH9DBidYYCDe7iAxxhnxfomIiEgX+MzIbNJ7Ahy3280ll1zCDTfccNjznnvuOQ4cOGBtF154oXVs165dzJkzhzPPPJMNGzZw6623cv311/PWW29FuPciRy/dyuAcfg5OcHhadlwKhmFEvF8iIiIi0aTXDFG77777AL4x45KWlkZubm6nxxYtWsTw4cN59NFHARg3bhwffPABjz/+OLNnz+7W/op0t3AzOBqeJiIiEsVMn3/r7jal92RwjtSNN97IgAEDOPHEE1m8eDFmu7GIa9asYdasWSHnz549mzVr1hyyvZaWFurq6kI2kZ5grYPjbsR3mA+wtgIDCnBERESk/+k1GZwjcf/99/Ptb3+bhIQE3n77bX7yk5/Q0NDALbfcAkBJSQk5OTkh1+Tk5FBXV0dTUxPx8fEd2nzooYes7JFIT0pz+IeoeU0fta1NpAceH8xaA0clokVERKKXigxETI9mcO68885OCwO0377++usjbu8Xv/gFp5xyCtOmTeOOO+7g9ttv57e//e1R9fGuu+6itrbW2vbu3XtU7Yl0VazNTmqsPwivOkwlNWsNHJWIFhERkX6oRzM4Cxcu5JprrjnsOSNGjOhy+9OnT+eBBx6gpaUFp9NJbm4upaWlIeeUlpaSkpLSafYGwOl04nSqEpVEh3RHErWtTVS5XYw8xDnlgQyOhqiJiIhEMZ9Jty/MqSpqQA8HOFlZWWRlZUWs/Q0bNpCenm4FKDNmzODNN98MOWf58uXMmDEjYn0Q6U6ZzkR2u8qPKIOjIgMiIiLSH/WaOThFRUVUVVVRVFSE1+tlw4YNAIwaNYqkpCRee+01SktLOemkk4iLi2P58uX8+te/5mc/+5nVxo9//GOefvppbr/9dq699lreffddXnrpJd54440eelYi4ckIVFI71GKfpmm2y+BoiJqIiEjU0hyciOk1Ac4999zDX/7yF+vxtGnTAFi5ciUzZ84kNjaWZ555hvnz52OaJqNGjeKxxx5j3rx51jXDhw/njTfeYP78+fz+979n8ODB/OlPf1KJaOk1MgKV1Krcna+FU+9ppsXnAZTBERERiWomEQhwure53qrXBDhLliw57Bo455xzDuecc843tjNz5kzWr1/fjT0TOXYyApXTDjVELZi9SY2Nx2mPPWb9EhEREYkWvSbAEZG2tXC21h3AZ/qwGaGFEK01cFQiWkREJLppiFrE9LmFPkX6slOyRhNnj2VL3X7+r/jzDsfLWgJr4KiCmoiIiPRTCnBEepGc+FR+UjALgCe2LKMiUDEtKDhETWvgiIiIRDmfLzKbKMAR6W0uyz+JsSl51Hua+d1XoWXPVSJaRERE+jsFOCK9TIzNzi8mXYjdsPH2gY28X7bVOmbNwVEGR0REJLoF5+B09yYKcER6o3GpeVyRfzIAD236/2j0tABtQ9SUwREREZH+SgGOSC/144JvkxefRklzLc9uWwFAeYvm4IiIiPQKyuBEjAIckV4qPsbBXRO/C8A/dq9hU00xFYH1cTRETUREJMr5zMhsogBHpDc7JWs05+ZNxofJ/9vwEl7Th4FhLQgqIiIi0t8owBHp5RaOO4+U2HiKG6sAyHQmEmOz93CvRERE5HBM0xeRTRTgiPR6Gc4k5o89x3qc5dTwNBEREem/FOCI9AHfHXwcJ2QMB1RgQEREpFcwIzD/RkUGAAU4In2CYRjcN+Uizs2bzFUjTu3p7oiIiIj0mJie7oCIdI+B8Wk8OPX7Pd0NERERORKmCXRzxkUZHEAZHBERERER6UOUwREREREROdZ8PjC6ueqZqqgBCnBERERERI49DVGLGA1RExERERGRPkMZHBERERGRY8z0+TC7eYiaFvr0UwZHRERERET6DGVwRERERESONc3BiRhlcEREREREpM9QBkdERERE5FjzmWAogxMJyuCIiIiIiEifoQyOiIiIiMixZppAdy/0qQwOKIMjIiIiIiJ9iDI4IiIiIiLHmOkzMbt5Do6pDA6gAEdERERE5NgzfXT/EDUt9AkaoiYiIiIiIn2IAhwRERERkWPM9JkR2brimWeeIT8/n7i4OKZPn84nn3zSzc/22FKAIyIiIiLST7344ossWLCAe++9l88//5wpU6Ywe/ZsysrKerprXaYAR0RERETkWDN9kdnC9NhjjzFv3jx++MMfMn78eBYtWkRCQgKLFy+OwJM+NlRkIEzB6hR1dXU93BMRERER6Uzw32nRXFXMQyt0c/c8tAId/53qdDpxOp0dzne73Xz22Wfcdddd1j6bzcasWbNYs2ZN93buGFKAE6b6+noAhgwZ0sM9EREREZHDqa+vJzU1tae7EcLhcJCbm8sHJW9GpP2kpKQO/0699957+eUvf9nh3IqKCrxeLzk5OSH7c3Jy+PrrryPSv2NBAU6Y8vLy2Lt3L8nJyRiGEfH71dXVMWTIEPbu3UtKSkrE7yfh0esTvfTaRC+9NtFLr0300msTHtM0qa+vJy8vr6e70kFcXBy7du3C7XZHpH3TNDv8G7Wz7E1fpgAnTDabjcGDBx/z+6akpOgDLYrp9Yleem2il16b6KXXJnrptTly0Za5aS8uLo64uLie7gYDBgzAbrdTWloasr+0tJTc3Nwe6tXRU5EBEREREZF+yOFwcPzxx7NixQprn8/nY8WKFcyYMaMHe3Z0lMEREREREemnFixYwNy5cznhhBM48cQTeeKJJ3C5XPzwhz/s6a51mQKcKOd0Orn33nv73djJ3kKvT/TSaxO99NpEL7020UuvjUTKpZdeSnl5Offccw8lJSVMnTqVZcuWdSg80JsYZjTXzxMREREREQmD5uCIiIiIiEifoQBHRERERET6DAU4IiIiIiLSZyjAERERERGRPkMBThR45plnyM/PJy4ujunTp/PJJ58c9vx//vOfjB07lri4OCZNmsSbb755jHraP4Xz+ixZsgTDMEK2aFjIq6957733OP/888nLy8MwDF599dVvvGbVqlUcd9xxOJ1ORo0axZIlSyLez/4o3Ndm1apVHd4zhmFQUlJybDrcjzz00EN861vfIjk5mezsbC688EK2bt36jdfpb07kdeW10d8bkUNTgNPDXnzxRRYsWMC9997L559/zpQpU5g9ezZlZWWdnv/RRx9x+eWXc91117F+/XouvPBCLrzwQjZt2nSMe94/hPv6gH+V6QMHDljbnj17jmGP+weXy8WUKVN45plnjuj8Xbt2MWfOHM4880w2bNjArbfeyvXXX89bb70V4Z72P+G+NkFbt24Ned9kZ2dHqIf91+rVq7nxxhtZu3Yty5cvp7W1lbPPPhuXy3XIa/Q359joymsD+nsjckim9KgTTzzRvPHGG63HXq/XzMvLMx966KFOz//+979vzpkzJ2Tf9OnTzf/6r/+KaD/7q3Bfn+eee85MTU09Rr0T0zRNwHzllVcOe87tt99uTpgwIWTfpZdeas6ePTuCPZMjeW1WrlxpAmZ1dfUx6ZO0KSsrMwFz9erVhzxHf3N6xpG8Nvp7I3JoyuD0ILfbzWeffcasWbOsfTabjVmzZrFmzZpOr1mzZk3I+QCzZ88+5PnSdV15fQAaGhoYNmwYQ4YM4YILLmDz5s3HortyGHrfRL+pU6cycOBAvvOd7/Dhhx/2dHf6hdraWgAyMjIOeY7eOz3jSF4b0N8bkUNRgNODKioq8Hq9HVaKzcnJOeT485KSkrDOl67ryuszZswYFi9ezP/93//x97//HZ/Px8knn0xxcfGx6LIcwqHeN3V1dTQ1NfVQrwRg4MCBLFq0iJdffpmXX36ZIUOGMHPmTD7//POe7lqf5vP5uPXWWznllFOYOHHiIc/T35xj70hfG/29ETm0mJ7ugEhfMmPGDGbMmGE9Pvnkkxk3bhx/+MMfeOCBB3qwZyLRacyYMYwZM8Z6fPLJJ7Njxw4ef/xx/va3v/Vgz/q2G2+8kU2bNvHBBx/0dFfkIEf62ujvjcihKYPTgwYMGIDdbqe0tDRkf2lpKbm5uZ1ek5ubG9b50nVdeX0OFhsby7Rp0ygsLIxEF+UIHep9k5KSQnx8fA/1Sg7lxBNP1Hsmgm666SZef/11Vq5cyeDBgw97rv7mHFvhvDYH098bkTYKcHqQw+Hg+OOPZ8WKFdY+n8/HihUrQr6VaW/GjBkh5wMsX778kOdL13Xl9TmY1+tl48aNDBw4MFLdlCOg903vsmHDBr1nIsA0TW666SZeeeUV3n33XYYPH/6N1+i9c2x05bU5mP7eiLTT01UO+rulS5eaTqfTXLJkifnVV1+ZP/rRj8y0tDSzpKTENE3TvOqqq8w777zTOv/DDz80Y2JizN/97nfmli1bzHvvvdeMjY01N27c2FNPoU8L9/W57777zLfeesvcsWOH+dlnn5mXXXaZGRcXZ27evLmnnkKfVF9fb65fv95cv369CZiPPfaYuX79enPPnj2maZrmnXfeaV511VXW+Tt37jQTEhLM2267zdyyZYv5zDPPmHa73Vy2bFlPPYU+K9zX5vHHHzdfffVVc/v27ebGjRvNn/70p6bNZjPfeeednnoKfdYNN9xgpqammqtWrTIPHDhgbY2NjdY5+pvTM7ry2ujvjcihKcCJAk899ZQ5dOhQ0+FwmCeeeKK5du1a69gZZ5xhzp07N+T8l156yRw9erTpcDjMCRMmmG+88cYx7nH/Es7rc+utt1rn5uTkmOedd575+eef90Cv+7ZgaeGDt+BrMXfuXPOMM87ocM3UqVNNh8NhjhgxwnzuueeOeb/7g3Bfm4cfftgcOXKkGRcXZ2ZkZJgzZ84033333Z7pfB/X2esChLwX9DenZ3TltdHfG5FDM0zTNI9dvkhERERERCRyNAdHRERERET6DAU4IiIiIiLSZyjAERERERGRPkMBjoiIiIiI9BkKcEREREREpM9QgCMiIiIiIn2GAhwREREREekzFOCIiIiIiEifoQBHRCRKrVq1CsMwqKmp6ZH7r1ixgnHjxuH1eiN2j5NOOomXX345Yu2LiEj/Y5imafZ0J0RE+ruZM2cydepUnnjiCWuf2+2mqqqKnJwcDMM45n06/vjjWbBgAVdeeWXE7vH6668zf/58tm7dis2m79xEROTo6a+JiEiUcjgc5Obm9khw88EHH7Bjxw4uuuiiiN7n3HPPpb6+nn//+98RvY+IiPQfCnBERHrYNddcw+rVq/n973+PYRgYhsHu3bs7DFFbsmQJaWlpvP7664wZM4aEhAQuvvhiGhsb+ctf/kJ+fj7p6enccsstIcPKWlpa+NnPfsagQYNITExk+vTprFq16rB9Wrp0Kd/5zneIi4uz9v3yl79k6tSpLF68mKFDh5KUlMRPfvITvF4vjzzyCLm5uWRnZ/Pggw9a15imyS9/+UuGDh2K0+kkLy+PW265xTput9s577zzWLp0aff8MkVEpN+L6ekOiIj0d7///e/Ztm0bEydO5P777wcgKyuL3bt3dzi3sbGRJ598kqVLl1JfX8/3vvc9/vM//5O0tDTefPNNdu7cyUUXXcQpp5zCpZdeCsBNN93EV199xdKlS8nLy+OVV17hnHPOYePGjRQUFHTap/fff58rrriiw/4dO3bw73//m2XLlrFjxw4uvvhidu7cyejRo1m9ejUfffQR1157LbNmzWL69Om8/PLLPP744yxdupQJEyZQUlLCF198EdLmiSeeyG9+85uj/C2KiIj4KcAREelhqampOBwOEhISyM3NPey5ra2tPPvss4wcORKAiy++mL/97W+UlpaSlJTE+PHjOfPMM1m5ciWXXnopRUVFPPfccxQVFZGXlwfAz372M5YtW8Zzzz3Hr3/9607vs2fPHuv89nw+H4sXLyY5Odm619atW3nzzTex2WyMGTOGhx9+mJUrVzJ9+nSKiorIzc1l1qxZxMbGMnToUE488cSQNvPy8ti7dy8+n0/zcERE5KjpL4mISC+SkJBgBTcAOTk55Ofnk5SUFLKvrKwMgI0bN+L1ehk9ejRJSUnWtnr1anbs2HHI+zQ1NYUMTwvKz88nOTk55F7jx48PCUza3/+SSy6hqamJESNGMG/ePF555RU8Hk9Im/Hx8fh8PlpaWsL8bYiIiHSkDI6ISC8SGxsb8tgwjE73+Xw+ABoaGrDb7Xz22WfY7faQ89oHRQcbMGAA1dXVR33/IUOGsHXrVt555x2WL1/OT37yE37729+yevVq67qqqioSExOJj48/3FMXERE5IgpwRESigMPhiMh6M9OmTcPr9VJWVsZpp50W1nVfffVVt/QhPj6e888/n/PPP58bb7yRsWPHsnHjRo477jgANm3axLRp07rlXiIiIgpwRESiQH5+Ph9//DG7d+8mKSmJjIyMbml39OjRXHnllVx99dU8+uijTJs2jfLyclasWMHkyZOZM2dOp9fNnj2bv/zlL0d9/yVLluD1epk+fToJCQn8/e9/Jz4+nmHDhlnnvP/++5x99tlHfS8RERHQHBwRkajws5/9DLvdzvjx48nKyqKoqKjb2n7uuee4+uqrWbhwIWPGjOHCCy/k008/ZejQoYe85sorr2Tz5s1s3br1qO6dlpbG//zP/3DKKacwefJk3nnnHV577TUyMzMB2LdvHx999BE//OEPj+o+IiIiQYZpmmZPd0JERKLPbbfdRl1dHX/4wx8ido877riD6upq/vjHP0bsHiIi0r8ogyMiIp26++67GTZsmFUwIBKys7N54IEHIta+iIj0P8rgiIiIiIhIn6EMjoiIiIiI9BkKcEREREREpM9QgCMiIiIiIn2GAhwREREREekzFOCIiIiIiEifoQBHRERERET6DAU4IiIiIiLSZyjAERERERGRPkMBjoiIiIiI9Bn/P4Xz+MatelYBAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "colors = plt.cm.viridis(np.linspace(0, 1, unit_waveforms.shape[0]))\n",
    "ax.set_prop_cycle(color=colors)\n",
    "\n",
    "n_secs = unit_waveforms.shape[1] / Hz\n",
    "time_axis = np.linspace(0, n_secs * 1000, unit_waveforms.shape[1])\n",
    "\n",
    "ax.plot(time_axis, np.transpose(unit_waveforms))\n",
    "\n",
    "norm = mpl.colors.Normalize(vmin=0, vmax=len(colors))\n",
    "cb = fig.colorbar(mpl.cm.ScalarMappable(norm=norm), ax=ax, label='channel #')\n",
    "\n",
    "ax.set_xlabel(\"time (ms)\")\n",
    "ax.set_ylabel(\"membrane potential (uV)\")\n",
    "ax.set_title(\"Unit Waveforms\", fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f670a848",
   "metadata": {},
   "source": [
    "#### Waveform Image\n",
    "Below is an image of the waveform means for each channel of a unit. The further in space from the real neuron, the weaker the measurement of the response waveform, so it is usually only useful to view a subsection of the channels at once. Set `start_channel` and `end_channel` to be the bounds of the channels you want displayed. Because on neuropixels probes the channels are arranged into two rows along the length of a probe, typically a unit is only strongly detected by every other channel. The data shown below displays every other channel to avoid the resultant striping effect. If the waveform looks too dim, try incrementing `start_channel` by 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b9289e8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_channel = 230\n",
    "end_channel = 280"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9b949dab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1a5326baf50>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = unit_waveforms[start_channel:end_channel:2] # step by 2 to remove striping effect\n",
    "n_channels = end_channel - start_channel\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, n_channels // 15))\n",
    "\n",
    "n_secs = unit_waveforms.shape[1] / Hz\n",
    "time_axis = np.linspace(0, n_secs * 1000, unit_waveforms.shape[1])\n",
    "\n",
    "norm = mpl.colors.Normalize(vmin=np.min(data), vmax=np.max(data))\n",
    "cb = fig.colorbar(mpl.cm.ScalarMappable(norm=norm), ax=ax, label=\"membrane potential (uV)\")\n",
    "\n",
    "ax.set_xlabel(\"time (ms)\")\n",
    "ax.set_ylabel(\"channel #\")\n",
    "ax.set_title(\"Unit Waveforms Image\")\n",
    "\n",
    "ax.imshow(data, vmin=np.min(data), vmax=np.max(data), extent=[0, n_secs*1000, end_channel, start_channel], aspect=\"auto\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}