diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..17ec257
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,5 @@
+.idea
+.ipynb_checkpoints
+data/
+test/local_node/state/
+
diff --git a/0x85Cb0baB616Fe88a89A35080516a8928F38B518b_df.pkl b/0x85Cb0baB616Fe88a89A35080516a8928F38B518b_df.pkl
new file mode 100644
index 0000000..7289de8
Binary files /dev/null and b/0x85Cb0baB616Fe88a89A35080516a8928F38B518b_df.pkl differ
diff --git a/README.md b/README.md
index 4b860d9..fe2ef47 100644
--- a/README.md
+++ b/README.md
@@ -8,4 +8,24 @@ using [The Graph](https://thegraph.com). Using a node to pull events was very sl
 to  complete prior to me wrapping up the code to pull indexed data from The Graph.
 
 Much of main flow of code was hacked together in test files. More work is required to make this a 
-finished production product.
\ No newline at end of file
+finished production product.
+
+## Load Notebook
+
+This repo uses [Poetry](https://python-poetry.org/) to manage dependencies within a python virtual
+environment. You can install the dependencies and run [jupyter-lab](https://jupyter.org/) with the
+comands.
+
+```bash
+poetry install
+poetry run jupyter-lab
+```
+
+from jupyter-lab you can navigate to the [notebook](data-analysis.ipynb). 
+
+## Constructing data for a new pair
+
+Code to scrape data is not production quality, it was assembled quickly and a testing framework was
+used to execute the process. Data can be recreated using the tests in 
+[test_scanner_with_node.py](test/local_node/test_scanner_with_node.py). You will need to fill in
+the node url, uniswap v2 pair address, and the block the pair was created (to save on time). 
diff --git a/data-analysis.ipynb b/data-analysis.ipynb
new file mode 100644
index 0000000..e7c3a14
--- /dev/null
+++ b/data-analysis.ipynb
@@ -0,0 +1,1480 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "39921289",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pickle\n",
+    "from pandas import DataFrame\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "import ipywidgets as widgets\n",
+    "from ipywidgets import Layout\n",
+    "import pathlib\n",
+    "\n",
+    "plt.rcParams[\"figure.figsize\"] = (14, 7) # (w, h)\n",
+    "pair_address = \"0x85Cb0baB616Fe88a89A35080516a8928F38B518b\"\n",
+    "cache_df_path = f\"data/{pair_address}_by_block_df.pkl\"\n",
+    "sync_swap_df = f\"test/local_node/state/{pair_address}_df.pkl\"\n",
+    "\n",
+    "state_df = pickle.load(open(sync_swap_df, \"rb\"))\n",
+    "state_df.head()\n",
+    "\n",
+    "def index_by_block_and_cache(state_df: DataFrame) -> DataFrame:\n",
+    "    block_df = (state_df[['block', 'amount0In', 'amount1In', 'amount0Out', 'amount1Out', 'reserve0', 'reserve1']]).groupby(\n",
+    "        state_df.block, as_index=False).agg({\n",
+    "            'block': 'first', 'amount0In': sum, 'amount1In': sum, 'amount0Out': sum, 'amount1Out': sum, 'reserve0': 'first', 'reserve1': 'first'\n",
+    "        }).copy(deep=True)\n",
+    "    block_df.block = block_df.block.astype(int)\n",
+    "\n",
+    "    block_df = block_df.set_index('block').reindex(np.arange(block_df.block.min(), block_df.block.max() + 1)).reset_index()\n",
+    "    block_df.reserve0 = block_df.reserve0.fillna(method='bfill')\n",
+    "    block_df.reserve1 = block_df.reserve1.fillna(method='bfill')\n",
+    "    block_df = block_df.fillna(value=0)\n",
+    "    block_df.to_pickle(cache_df_path)\n",
+    "    return block_df\n",
+    "\n",
+    "# block_df is 172M due to intoducing a row for each block, build it and cache it to run cell faster on future runs.\n",
+    "block_df = pickle.load(open(cache_df_path, \"rb\")) \\\n",
+    "    if pathlib.Path(cache_df_path).exists() \\\n",
+    "    else index_by_block_and_cache(pickle.load(open(sync_swap_df, \"rb\")))\n",
+    "\n",
+    "rates_df = DataFrame({\n",
+    "    \"block\": block_df[\"block\"],\n",
+    "    \"y_per_x\": block_df[\"reserve1\"] / block_df[\"reserve0\"],\n",
+    "    \"x_per_y\": block_df[\"reserve0\"] / block_df[\"reserve1\"]\n",
+    "})\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "568c7020",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>block</th>\n",
+       "      <th>amount0In</th>\n",
+       "      <th>amount1In</th>\n",
+       "      <th>amount0Out</th>\n",
+       "      <th>amount1Out</th>\n",
+       "      <th>reserve0</th>\n",
+       "      <th>reserve1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>11876000</td>\n",
+       "      <td>172168679926519706</td>\n",
+       "      <td>1000000000000000000</td>\n",
+       "      <td>17216867992651970607</td>\n",
+       "      <td>29238993545300586</td>\n",
+       "      <td>25851205000000000000</td>\n",
+       "      <td>500000000000000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11876001</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13596682010212464215</td>\n",
+       "      <td>2270761006454699413</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11876002</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13596682010212464215</td>\n",
+       "      <td>2270761006454699413</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11876003</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13596682010212464215</td>\n",
+       "      <td>2270761006454699413</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11876004</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13596682010212464215</td>\n",
+       "      <td>2270761006454699413</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      block           amount0In            amount1In            amount0Out  \\\n",
+       "0  11876000  172168679926519706  1000000000000000000  17216867992651970607   \n",
+       "1  11876001                   0                    0                     0   \n",
+       "2  11876002                   0                    0                     0   \n",
+       "3  11876003                   0                    0                     0   \n",
+       "4  11876004                   0                    0                     0   \n",
+       "\n",
+       "          amount1Out              reserve0             reserve1  \n",
+       "0  29238993545300586  25851205000000000000   500000000000000000  \n",
+       "1                  0  13596682010212464215  2270761006454699413  \n",
+       "2                  0  13596682010212464215  2270761006454699413  \n",
+       "3                  0  13596682010212464215  2270761006454699413  \n",
+       "4                  0  13596682010212464215  2270761006454699413  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "block_df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "920a283f-e5ac-4688-99ef-70436c3c6614",
+   "metadata": {},
+   "source": [
+    "# Reserve based price vs Volume weighted average price\n",
+    "\n",
+    "Price is usually measured by the state of the reserves at the end of a block. Another way to meausre price is considering the rate each swap executes at. This can be chaotic with multiple swaps in either direction in a block, but we might group these rates within a block using a volume weighted average. Lets compare how these values would differ from a reserved based price"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "6fc4b53a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prices_df = DataFrame(block_df[\"block\"])\n",
+    "\n",
+    "# Add reserve based price\n",
+    "prices_df[\"reserve0/reserve1\"] = block_df[\"reserve0\"] / block_df[\"reserve1\"]\n",
+    "\n",
+    "# Add Volume based price, use last price if no volume exists\n",
+    "prices_df[\"volume0/volume1\"] = (block_df[\"amount0In\"] + block_df[\"amount0Out\"]).divide(\n",
+    "    (block_df[\"amount1In\"] + block_df[\"amount1Out\"]).replace({ 0 : np.nan })).fillna(method='ffill')\n",
+    "\n",
+    "# seperated volume values\n",
+    "prices_df[\"volume_sell_0_0per1\"] = (block_df[\"amount0In\"]).divide(\n",
+    "    (block_df[\"amount1Out\"]).replace({ 0 : np.nan })).fillna(method='ffill')\n",
+    "prices_df[\"volume_sell_1_0per1\"] = (block_df[\"amount0Out\"]).divide(\n",
+    "    (block_df[\"amount1In\"]).replace({ 0 : np.nan })).fillna(method='ffill')\n",
+    "prices_df[\"volume_sell_0_1per0\"] = 1 / prices_df[\"volume_sell_0_0per1\"]\n",
+    "prices_df[\"volume_sell_1_1per0\"] = 1 / prices_df[\"volume_sell_1_0per1\"]\n",
+    "\n",
+    "prices_df = prices_df.set_index('block')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a186b047",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>reserve0/reserve1</th>\n",
+       "      <th>volume0/volume1</th>\n",
+       "      <th>volume_sell_0_0per1</th>\n",
+       "      <th>volume_sell_1_0per1</th>\n",
+       "      <th>volume_sell_0_1per0</th>\n",
+       "      <th>volume_sell_1_1per0</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>block</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>11876000</th>\n",
+       "      <td>51.70241</td>\n",
+       "      <td>16.895043</td>\n",
+       "      <td>5.888324</td>\n",
+       "      <td>17.216868</td>\n",
+       "      <td>0.169828</td>\n",
+       "      <td>0.058083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11876001</th>\n",
+       "      <td>5.98772</td>\n",
+       "      <td>16.895043</td>\n",
+       "      <td>5.888324</td>\n",
+       "      <td>17.216868</td>\n",
+       "      <td>0.169828</td>\n",
+       "      <td>0.058083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11876002</th>\n",
+       "      <td>5.98772</td>\n",
+       "      <td>16.895043</td>\n",
+       "      <td>5.888324</td>\n",
+       "      <td>17.216868</td>\n",
+       "      <td>0.169828</td>\n",
+       "      <td>0.058083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11876003</th>\n",
+       "      <td>5.98772</td>\n",
+       "      <td>16.895043</td>\n",
+       "      <td>5.888324</td>\n",
+       "      <td>17.216868</td>\n",
+       "      <td>0.169828</td>\n",
+       "      <td>0.058083</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11876004</th>\n",
+       "      <td>5.98772</td>\n",
+       "      <td>16.895043</td>\n",
+       "      <td>5.888324</td>\n",
+       "      <td>17.216868</td>\n",
+       "      <td>0.169828</td>\n",
+       "      <td>0.058083</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         reserve0/reserve1  volume0/volume1  volume_sell_0_0per1  \\\n",
+       "block                                                              \n",
+       "11876000          51.70241        16.895043             5.888324   \n",
+       "11876001           5.98772        16.895043             5.888324   \n",
+       "11876002           5.98772        16.895043             5.888324   \n",
+       "11876003           5.98772        16.895043             5.888324   \n",
+       "11876004           5.98772        16.895043             5.888324   \n",
+       "\n",
+       "          volume_sell_1_0per1  volume_sell_0_1per0  volume_sell_1_1per0  \n",
+       "block                                                                    \n",
+       "11876000            17.216868             0.169828             0.058083  \n",
+       "11876001            17.216868             0.169828             0.058083  \n",
+       "11876002            17.216868             0.169828             0.058083  \n",
+       "11876003            17.216868             0.169828             0.058083  \n",
+       "11876004            17.216868             0.169828             0.058083  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "prices_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "20750698",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: xlabel='block'>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "prices_df[[\"volume0/volume1\", \"reserve0/reserve1\"]] \\\n",
+    "    [(16300150 <= prices_df.index) & (prices_df.index <= 16300450)].plot(linewidth=2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ef1a1c72",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "price_compare = prices_df[[\"reserve0/reserve1\", \"volume_sell_0_0per1\", \"volume_sell_1_0per1\", \"volume0/volume1\"]] \\\n",
+    "    [(16300300 <= prices_df.index) & (prices_df.index <= 16300450)]\n",
+    "plt.plot(price_compare[[\"reserve0/reserve1\"]], label = \"reserve0/reserve1\", linewidth=5)\n",
+    "plt.plot(price_compare[[\"volume_sell_0_0per1\", \"volume_sell_1_0per1\"]], label = [\"volume_sell_0_0per1\", \"volume_sell_1_0per1\"], linewidth=4)\n",
+    "plt.plot(price_compare[[\"volume0/volume1\"]], label = \"volume0/volume1\", linewidth=2)\n",
+    "plt.xlabel(\"block\")\n",
+    "plt.ylabel('price')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bb3a784d",
+   "metadata": {},
+   "source": [
+    "# 30 Minute Oracle Comparison on ETH-POOL Uniswap V2 Pair\n",
+    "\n",
+    "Here we look at the ETH-POOL pair, a low liquidity trading pair, to understand how variout price calculations for our oracle would work. \n",
+    "\n",
+    "## Construct Oracles\n",
+    "\n",
+    "Our dataframe starts with swaps and reserves prior to swaps. Using this data we crunch some numbers to build build various oraclse. Since we do not have time which our scanner does not grab, we use blocks thus BWAP rather than TWAP. If every block was 12 seconds exactly, this would be the same, but since that is not the case, there are some minor erorrs. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "6153bcec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class OracleBuilder:\n",
+    "    tick_log = math.log(1.0001)\n",
+    "\n",
+    "    def __init__(self, block_df: DataFrame):\n",
+    "        self.block_df = block_df\n",
+    "        self.df = DataFrame(block_df.loc[:, (\"block\")])\n",
+    "    \n",
+    "    @staticmethod\n",
+    "    def new_builder(block_df: DataFrame) -> 'OracleBuilder':\n",
+    "        return OracleBuilder(block_df)\n",
+    "    \n",
+    "    def add_reserve_price(self) -> 'OracleBuilder':\n",
+    "        self.df[\"current_price\"] = (self.block_df['reserve0'] / self.block_df['reserve1'])\n",
+    "        return self\n",
+    "    \n",
+    "    def add_shifted_reserve_price(self, minutes) -> 'OracleBuilder':\n",
+    "        half_blocks = int(self.minutes_to_blocks(minutes) / 2)\n",
+    "        current_price = self.df[\"current_price\"] if \"current_price\" in self.df.columns else self.block_df['reserve0'] / self.block_df['reserve1']\n",
+    "        self.df[f\"shifted_price_{half_blocks}\"] = current_price.shift(periods=half_blocks)\n",
+    "        return self\n",
+    "    \n",
+    "    def add_twap(self, minutes) -> 'OracleBuilder':\n",
+    "        blocks = self.minutes_to_blocks(minutes)\n",
+    "        cumsum_x_per_y = self.block_df.loc[:, ('reserve0')].divide(self.block_df['reserve1']).cumsum()\n",
+    "        cumsum_y_per_x = self.block_df.loc[:, ('reserve1')].divide(self.block_df['reserve0']).cumsum()\n",
+    "        self.df[f\"twap_{minutes}_x_per_y\"] = (cumsum_x_per_y - cumsum_x_per_y.shift(blocks)).divide(blocks)\n",
+    "        return self\n",
+    "    \n",
+    "    def add_geom_twap(self, minutes) -> 'OracleBuilder':\n",
+    "        blocks = self.minutes_to_blocks(minutes)\n",
+    "        tick_sum = (np.log((self.block_df['reserve0'] / self.block_df['reserve1']).astype(float)) / self.tick_log).cumsum()\n",
+    "        self.df[F\"geom_twap_{minutes}_x_per_y\"] = np.power(\n",
+    "            1.0001, (tick_sum - tick_sum.shift(blocks)) / blocks\n",
+    "        )\n",
+    "        return self\n",
+    "    \n",
+    "    def add_vwap(self, minutes) -> 'OracleBuilder':\n",
+    "        blocks = self.minutes_to_blocks(minutes)\n",
+    "        cumsum_x_in = self.block_df[\"amount0In\"].cumsum()\n",
+    "        cumsum_y_out = self.block_df[\"amount1Out\"].cumsum()\n",
+    "        cumsum_y_in = self.block_df[\"amount1In\"].cumsum()\n",
+    "        cumsum_x_out = self.block_df[\"amount0Out\"].cumsum()\n",
+    "        self.df[f\"vwap_{minutes}_x_per_y\"] = (\n",
+    "            cumsum_x_in + cumsum_x_out - (cumsum_x_in + cumsum_x_out).shift(blocks)).divide(\n",
+    "            (cumsum_y_in + cumsum_y_out - (cumsum_y_in + cumsum_y_out).shift(blocks)).replace({ 0 : np.nan }))\n",
+    "        return self\n",
+    "    \n",
+    "    def add_proposed(self, minutes) -> 'OracleBuilder':\n",
+    "        blocks = self.minutes_to_blocks(minutes)\n",
+    "        geom_0In_1Out = (np.log((self.block_df[\"amount0In\"] / self.block_df[\"amount1Out\"].replace({0: np.nan})).fillna(method='ffill')) / self.tick_log).cumsum()\n",
+    "        geom_1In_0Out = (np.log((self.block_df[\"amount0Out\"] / self.block_df[\"amount1In\"].replace({0: np.nan})).fillna(method='ffill')) / self.tick_log).cumsum()\n",
+    "        self.df[f'proposed_0In_1Out_oracle_{minutes}'] = np.power(1.0001, (geom_0In_1Out - geom_0In_1Out.shift(blocks)) / blocks)\n",
+    "        self.df[f'proposed_1In_0Out_oracle_{minutes}'] = np.power(1.0001, (geom_1In_0Out - geom_1In_0Out.shift(blocks)) / blocks)\n",
+    "        return self\n",
+    "\n",
+    "    @staticmethod\n",
+    "    def minutes_to_blocks(minutes):\n",
+    "        return minutes * 5 # minutes * 60 second / 12 second per block\n",
+    "\n",
+    "    def build(self) -> DataFrame:\n",
+    "        return self.df\n",
+    "\n",
+    "\n",
+    "oracle_df = OracleBuilder.new_builder(block_df) \\\n",
+    "    .add_reserve_price() \\\n",
+    "    .add_shifted_reserve_price(30) \\\n",
+    "    .add_twap(30) \\\n",
+    "    .add_geom_twap(30) \\\n",
+    "    .add_vwap(30) \\\n",
+    "    .add_proposed(30) \\\n",
+    "    .build()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "2ec711b9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: title={'center': 'POOL per ETH Reserves Based Price Uniswap V2 Pair'}, xlabel='block', ylabel='POOL/ETH'>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "oracle_df[[\"block\", \"current_price\"]].plot(linewidth=.75, x=\"block\", ylabel=\"POOL/ETH\", title=\"POOL per ETH Reserves Based Price Uniswap V2 Pair\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f1a51b64-faf9-4365-a48f-30ad0a5425f2",
+   "metadata": {},
+   "source": [
+    "# Proposed oracle calculationsin comparison to twap and geometric twap\n",
+    "\n",
+    "Our proposed oracle calculation tracks what assets are tracking rather than what the state of the reserves in the pair are. Below we show each oracle calculation along with the price based on the reserves shifted forward to overlay with what the oracles which lag. The twaps break from the reserves briefly until the opposite direction trades occur at which point the twaps start decreaeasing towards the new reserve prices. The rate at which the swaps execute at are higher than the values the twaps track. The proposed oracle more closely follows the actual price, not the reserve based price. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "ff41527d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: xlabel='block'>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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zDAZT6PPwcSqlcQCXdxERNVw+Pj7WnkK55HI5WrRoYe1pUD1UoS3biYiIiBoCXWHoI5WWvkmFianSJ5eVPkRERFQPMfQhIiIim2Oq9JGXE/rYc3kXERER1WMMfYiIiMjmmHr6SCXlVPooC0MfLu8iIiKieoihDxEREdkcndjTx7LlXaz0ISIiovqIoQ8RERHZHEuXd7GnDxEREdVnDH2IiIjI5ugtbORsr2SlDxEREdVfDH2IiIjI5ugrWOnDnj5ERJYJDg7GzJkzrT2NMsXExKB///7w8PCAvb09mjVrhoULF6KgoMBs3Jdffok2bdrA3t4eHTp0wI8//milGRNVDUMfIiIisjkWN3IWl3cZanxORERU8xQKBSZOnIhffvkFMTExWLduHf7zn//gzTffFMccO3YMTz/9NF544QWcP38eo0ePxujRo3H58mUrzrzyBEGATqez9jTIShj6EBERkc3RW9rImcu7iKiuEAQgP6v2H4UhuSVCQ0Nx6NAhrF+/HhKJBBKJBI0bN8bq1avFMaNHj4ZCoUBmZiYA4H//+x8kEglu3LgBAPj000/RvXt3ODo6wtPTE+PHj8fdu3fF86OioiCRSLBnzx507NgR9vb26Nmzp8WBTLNmzTBp0iR06tQJfn5+eOyxxzBhwgQcPnxYHLN+/XoMHToU8+bNQ2BgIJYuXYquXbtiw4YN5V7/jz/+gFqtxo4dO8TnvvjiC6hUKly5cqXc80NDQzF69GgsWbIEbm5u0Gq1mDp1KvLz88UxBoMBK1asQEBAAFQqFTp16oSvvvqqxHv0008/oVu3brCzs8ORI0fKvOetW7cglUpx5swZs+fXrVsHPz8/GAz8h4/6TG7tCRARERHVNotDHy7vIqK6oiAbWO5d+/d9LR5Qaiwaun79ely7dg3t27fHW2+9BQB49913ERUVhblz50IQBBw+fBjOzs44cuQIhg4dikOHDsHHxwctWrQAABQUFGDp0qVo3bo17t69i9mzZyM0NLTE8qp58+Zh/fr18PT0xGuvvYaRI0fi2rVrUCgUFXp5N27cwM8//4zHH39cfO748eOYPXu22biQkBB888035V6vTZs2WL16NaZNm4Z//OMfkEqlmDp1Kt599120bdvWojkdOHAA9vb2iIqKwq1btzBp0iQ0atQIy5YtAwCsWLECn332GTZv3oyWLVvit99+wzPPPAM3Nzf069dPvM6CBQuwevVqNGvWDC4uLmXez9/fH4MGDUJERAS6d+8uPh8REYHQ0FBIpawVqc8Y+hAREZHNsTT0sS+2ZbsgCJCUsxyMiMiWOTk5QalUQq1Ww9PTEwAwYMAAREREQK/X4/Lly1AqlXjyyScRFRWFoUOHIioqyiyoeP7558W/N2vWDO+//z569OiBzMxMODg4iMfefPNNDB48GACwdetWNGnSBLt378a4ceMsmmuvXr1w7tw55OXlYcqUKWJIBQCJiYnw8PAwG+/h4YHExESLrj1t2jT8+OOPeOaZZ6BUKtGjRw+8/PLLFp0LAEqlEp988gnUajXatWuHt956C/PmzcPSpUtRUFCA5cuXY//+/QgKCgJgfJ+OHDmCf//732bv5VtvvSW+R+WZPHkypk6divfeew92dnY4d+4cLl26hG+//dbieVPdxNCHiIiIbI4Y+pTX06dweRcA5OkMYghERFTrFGpj1Y017lsFffr0QUZGBs6fP49jx46hX79+CA4OxjvvvAMAOHToEObNmyeOP3v2LBYvXowLFy4gJSVFXFoUFxdnViljCjwAwNXVFa1bt8bVq1ctntfnn3+OjIwMXLhwAfPmzcPq1avxyiuvVOm1FvfJJ5+gVatWkEql+P333yv0jwadOnWCWl30vgcFBSEzMxO3b99GZmYmsrOzS4Q5+fn56NKli9lzxat2yjN69GiEhYVh9+7deOqppxAZGYn+/fvD39/f4mtQ3cTQh4iIiGyOqZFzuZU+8qKS9px8PUMfIrIeicTiZVZ1ibOzMzp16oSoqCgcP34cgwcPRt++ffHkk0/i2rVruH79ulidkpWVhZCQEISEhGD79u1wc3NDXFwcQkJCzHraVAdfX18AQNu2baHX6zFlyhTMmTMHMpkMnp6eSEpKMhuflJQkVi9Z4sKFC8jKyoJUKkVCQgK8vLyqZd6mXkh79uyBj4+P2TE7OzuzjzUay79elEolJk6ciIiICDz++OPYsWMH1q9fX/UJk9Ux9CEiIiKbY7BweZdcJoVSJkW+3oCcAj3K7ohARESAMTzQ6837oPXr1w8HDx7EqVOnsGzZMri6uiIwMBDLli2Dl5cXWrVqBcDYBPn+/ft45513xFDmwebCJidOnEDTpk0BACkpKbh27RoCAwMrNWeDwYCCggIYDAbIZDIEBQXhwIEDZlvP79u3z6y66GGSk5MRGhqK119/HQkJCZgwYQLOnTsHlUpl0fkXLlxATk6OOP7EiRNwcHCAr68vXF1dYWdnh7i4OLOlXNVh8uTJaN++PT788EPodDqzPkdUfzH0ISIiIpujKwx9pOWEPgBgrygKfYiI6OH8/f1x8uRJ3Lp1Cw4ODnB1dUVwcDA++OADuLm5oU2bNgCA4OBgbNiwAWPHjhXPbdq0KZRKJT744ANMnToVly9fxtKlS0u9z1tvvYVGjRrBw8MDr7/+Oho3bozRo0eXO7/t27dDoVCgQ4cOsLOzw5kzZ/Dqq6/iySefFJtAz5gxA/369cOaNWswYsQI7Ny5E2fOnMFHH31k0XswdepU+Pr6YuHChcjLy0OXLl0wd+5cbNy40aLz8/Pz8cILL2DhwoW4desW3nzzTYSHh0MqlcLR0RFz587FrFmzYDAY8I9//ANpaWk4evQotFotnnvuOYvuUZrAwED07NkT8+fPx/PPP29xSEV1G9twExERkc0x9fSRWxD6iNu2cwcvIqJyzZ07FzKZDG3bthWXZ/Xp0wcGg8GsMiU4OBh6vR7BwcHic25uboiMjMSXX36Jtm3b4p133jHb7r24d955BzNmzEC3bt2QmJiI77//Hkqlstz5yeVyvPvuu3jkkUfQsWNHLFmyBOHh4diyZYs4plevXtixYwc++ugjcTv0b775Bu3bty/3+tu2bcOPP/6ITz/9FHK5HBqNBp999hn+85//4Keffir3fAAYOHAgWrZsKS6De+yxx7B48WLx+NKlS7Fo0SKsWLECgYGBGDp0KPbs2YOAgACLrv8wL7zwAvLz880aalP9JhGEwkXtDUx6ejqcnJyQlpYGrVZr7ekQERFRHTJk7SFcS8rEjsmPoleLxg8dG7zqIG7dz8ZXU4PQ3d+1lmZIRLYsNzcXsbGxCAgIgL29vbWnU6dERUWhf//+SElJgbOzs7WnU+1CQ0ORmppq0fbwNWHp0qX48ssvcfHiRavcn8w97HuBpZkHK32IiIjI5ugs7OkDmG/bTkRE1BBlZmbi8uXL2LBhQ4W2l6e6j6EPERER2RxLGzkDXN5FRFSfDBs2DA4ODqU+li9fXuXrHz58uMzrOzg4lHv+w849fPhwledXlnbt2pV53+3btyM8PBzdunVDcHAwl3Y1MGzkTERERDbHtGW7JY2cVaz0ISKqM4KDg/GwDiVbtmxBTk5OqcdcXau+RLd79+6Ijo6u9PkPO9fHxwd9+vSp9LUf5scff0RBQUGpxzw8PDBhwgRERkbWyL3Juhj6EBERkc3R6yvQyLkw9Mll6ENEVOf5+PjU6PVVKhVatGhR6fOrcm5V+Pn5WeW+ZH1c3kVEREQ2R6z0kVjQ04fLu4iIiKieYuhDRERENkdfkZ4+4vIuQ43OiYiIiKi6MfQhIiIim2MKfSqyvIs9fYiIiKi+YehDRERENscU+ljUyFnJnj5ERERUPzH0ISIiIpsjLu+ypKePgj19iIiIqH5i6ENEREQ2x9TIuWI9fRj6EBERUf3C0IeIiIhsjqGwJ7NloY/xxyWGPkREDVNkZCScnZ2tPY1yvfTSS2jevDlUKhXc3NwwatQo/PHHH2Zj4uLiMGLECKjVari7u2PevHnQ6XRWmjHVBQx9iIiIyOboClMfi0IfU08fLu8iIiIr6tatGyIiInD16lXs3bsXgiBgyJAh0OuN/3/S6/UYMWIE8vPzcezYMWzduhWRkZF44403rDzzysvPz7f2FOo9hj5ERERkUwRBQGFLH4tCH3su7yIislhGRgYmTJgAjUYDLy8vrF27FsHBwZg5cyYAIC8vD3PnzoWPjw80Gg0effRRREVFmV3j66+/Rrt27WBnZwd/f3+sWbPG7Li/vz/efvttTJw4EQ4ODvDz88N3332He/fuYdSoUXBwcEDHjh1x5syZcucbFRWFSZMmIS0tDRKJBBKJBIsXL8aGDRvQvn17cdw333wDiUSCzZs3i88NGjQICxcuBADcvHkTo0aNgoeHBxwcHNCjRw/s37+/xLyXLl2Kp59+GhqNBj4+Pti4caPF7+2UKVPQt29f+Pv7o2vXrnj77bdx+/Zt3Lp1CwDwyy+/4MqVK/jss8/QuXNnDBs2DEuXLsXGjRvLDU8EQcCgQYMQEhICoXAJdHJyMpo0aWJRaBQVFQWJRII9e/agY8eOsLe3R8+ePXH58mWzcUeOHEGfPn2gUqng6+uL6dOnIysrq8R7NHHiRGi1WkyZMuWh9x0wYADCw8PNnrt37x6USiUOHDhQ7rxtAUMfIiIisimmwAewrJEze/oQUV0gCAKyC7Jr/WEKACw1e/ZsHD16FN999x327duHw4cP49y5c+Lx8PBwHD9+HDt37sTFixcxduxYDB06FNevXwcAnD17FuPGjcNTTz2FS5cuYfHixVi0aBEiIyPN7rN27Vr07t0b58+fx4gRI/Dss89i4sSJeOaZZ3Du3Dk0b94cEydOLHf+vXr1wrp166DVapGQkICEhATMnTsX/fr1w5UrV3Dv3j0AwKFDh9C4cWMxoCooKMDx48cRHBwMAMjMzMTw4cNx4MABnD9/HkOHDsXIkSMRFxdndr9Vq1ahU6dOOH/+PBYsWIAZM2Zg3759FXqPASArKwsREREICAiAr68vAOD48ePo0KEDPDw8xHEhISFIT0/H77///tDrSSQSbN26FadPn8b7778PAJg6dSp8fHwqVCk0b948rFmzBqdPn4abmxtGjhyJgoICAMZgbOjQoXjiiSdw8eJFfP755zhy5EiJ0Gb16tXie7Ro0aKH3m/y5MnYsWMH8vLyxOc+++wz+Pj4YMCAARbPuyGTW3sCRERERLXJtLQLAGQyy5d3cfcuIrKmHF0OHt3xaK3f9+T4k1Ar1BaNzcjIwNatW7Fjxw4MHDgQABAREQFvb28Axn4zERERiIuLE5+bO3cufv75Z0RERGD58uV47733MHDgQPGX/VatWuHKlStYtWoVQkNDxXsNHz4cL730EgDgjTfewKZNm9CjRw+MHTsWADB//nwEBQUhKSkJnp6eZc5ZqVTCyckJEonEbFz79u3h6uqKQ4cO4Z///CeioqIwZ84crF+/HgBw6tQpFBQUoFevXgCATp06oVOnTuL5S5cuxe7du/Hdd9+ZhRq9e/fGggULxNd29OhRrF27FoMHD7boPf7www/xyiuvICsrC61bt8a+ffugVCoBAImJiWaBDwDx48TExHKv7ePjg3//+9+YOHEiEhMT8eOPP+L8+fOQyy2PDd58803xtWzduhVNmjTB7t27MW7cOKxYsQITJkwQq75atmyJ999/H/369cOmTZtgb28PwFi9M2fOHIvu9/jjjyM8PBzffvstxo0bB8DYoyk0NBQSC/5hxxaw0oeIiIhsSrHMp0KVPrms9CEieqg///wTBQUFeOSRR8TnnJyc0Lp1awDApUuXoNfr0apVKzg4OIiPQ4cO4ebNmwCAq1evonfv3mbX7d27N65fvy72rgGAjh07in83BRsdOnQo8dzdu3cr9VokEgn69u2LqKgopKam4sqVK5g2bRry8vLwxx9/4NChQ+jRowfUamMglpmZiblz5yIwMBDOzs5wcHDA1atXS1T6BAUFlfj46tWrFs9rwoQJOH/+PA4dOoRWrVph3LhxyM3NrdRrLM3YsWMxZswYvPPOO1i9ejVatmxZofOLvz5XV1e0bt1afH0XLlxAZGSk2ec+JCQEBoMBsbGx4nndu3e3+H729vZ49tln8cknnwAAzp07h8uXL5sFhLaOlT5ERERkU/TFSv3Z04eI6guVXIWT409a5b7VJTMzEzKZDGfPnoVMJjM75uDgUKFrKRQK8e+mio7SnjMUT/orKDg4GB999BEOHz6MLl26QKvVikHQoUOH0K9fP3Hs3LlzsW/fPqxevRotWrSASqXCP//5z2pvROzk5AQnJye0bNkSPXv2hIuLC3bv3o2nn34anp6eOHXqlNn4pKQkAHhotVNx2dnZ4ufHtOSuumRmZuKll17C9OnTSxxr2rSp+HeNRlOh606ePBmdO3fG//73P0RERGDAgAHw8/Or8nwbCoY+REREZFP0+oqFPlzeRUR1gUQisXiZlbU0a9YMCoUCp0+fFn+JT0tLw7Vr19C3b1906dIFer0ed+/eRZ8+fUq9RmBgII4ePWr23NGjR9GqVasSQVF1USqVZlVEJv369cPMmTPx5Zdfir17goODsX//fhw9etRsCdLRo0cRGhqKMWPGADAGHKYGy8WdOHGixMeBgYGVmrcgCBAEQexnExQUhGXLluHu3btwd3cHAOzbtw9arRZt27a16Jpz5syBVCrFTz/9hOHDh2PEiBEV6o1z4sQJ8XOfkpKCa9euia+va9euuHLlClq0aFGRl1muDh06oHv37vjPf/6DHTt2YMOGDdV6/fqOy7uIiIjIpphV+lRoeVfl/7WYiMgWODo64rnnnsO8efNw8OBB/P7773jhhRcglUohkUjQqlUrTJgwARMnTsSuXbsQGxuLU6dOYcWKFdizZw8AY+hw4MABLF26FNeuXcPWrVuxYcMGzJ07t8bm7e/vj8zMTBw4cAB///03srOzARiXkLm4uGDHjh1moc8333yDvLw8s2VoLVu2xK5duxAdHY0LFy5g/PjxpVYZHT16FCtXrsS1a9ewceNGfPnll5gxY0a5c/zzzz+xYsUKnD17FnFxcTh27BjGjh0LlUqF4cOHAwCGDBmCtm3b4tlnn8WFCxewd+9eLFy4EGFhYbCzsyv3Hnv27MEnn3yC7du3Y/DgwZg3bx6ee+45pKSkWPI2AgDeeustHDhwQFxi1bhxY4wePRqAsc/SsWPHEB4ejujoaFy/fh3ffvttiUbOlTF58mS88847EARBDN7IiKEPERER2ZTijZylllT6FIY++XoDdHoGP0RED/Pee+8hKCgI//d//4dBgwahd+/eCAwMFJv0RkREYOLEiZgzZw5at26N0aNHm1UGde3aFV988QV27tyJ9u3b44033sBbb71Voz1aevXqhalTp+LJJ5+Em5sbVq5cCcBYXdWnTx9IJBL84x//AGAMgrRaLbp37262DOm9996Di4sLevXqhZEjRyIkJARdu3Ytca85c+bgzJkz6NKlC95++2289957CAkJKXeO9vb2OHz4MIYPH44WLVrgySefhKOjI44dOyZW9chkMvzwww+QyWQICgrCM888g4kTJ+Ktt94q9/r37t3DCy+8gMWLF4vzXrJkCTw8PDB16tTy38RC77zzDmbMmIFu3bohMTER33//vdhoumPHjjh06BCuXbuGPn36oEuXLnjjjTfEpt5V8fTTT0Mul+Ppp58Wv9bISCJUdA++eiI9PR1OTk5IS0uDVqu19nSIiIiojkhMy0XPFQcgl0pwY/nwcsfnFujRZtHPAIDLS0LgYMfV8URUs3JzcxEbG4uAgIB6/wtsVlYWfHx8sGbNGrzwwgvWno5V+fv7Y+bMmeLuVQ1JVFQU+vfvj5SUFDg7O9f6/W/duoXmzZvj9OnTpYZt9dXDvhdYmnnwpxYiIiKyKablXZZU+QCAnbyoMDonX8/Qh4joIc6fP48//vgDjzzyCNLS0sQqk1GjRll5ZtQQFRQU4P79+1i4cCF69uzZoAKf6sLlXURERGRTTI2cLennAxjL+7ltOxGR5VavXo1OnTph0KBByMrKwuHDh9G4cWOrzWfYsGFm24QXfyxfvtxq8ypu+/btZc6xXbt21XKPdu3alXmP7du3P/TcqVOnlnluRZZ/VdTy5cvLvO+wYcNw9OhReHl54fTp09i8eXONzaM+4z9VERERkU0xVfrILaz0AYw7eOUU6LltOxFRObp06YKzZ89aexpmtmzZgpycnFKPubq61to8StvNy+Sxxx7Do48+Wuqx4lvRV8WPP/6IgoKCUo95eHg89Ny33nqrzGbaWq0W7u7uqInOMVOnTsW4ceNKPaZSqeDj41Mj921IGPoQERGRTdEbKra8Cyhq5sxt24mI6h8fHx9rT6Fcjo6OcHR0rNF7+Pn5Vfpcd3d3sWF0bXJ1da3VYK4h4vIuIiIisimm0EdWgdDHXmH8kYmVPkRERFSfMPQhIiIim1KZ0EelLKz0YehDRERE9QhDHyIiIrIpBqFijZyBouVduVzeRURERPUIQx8iIiKyKbpKLe9ipQ8RERHVPwx9iIiIyKZUankXQx8iIiKqhxj6EBERkU0Rl3dVpqcPl3cRERFRPcLQh4iIiGyKTl/5Sp9cVvoQETUYu3btQvfu3eHs7AyNRoPOnTvj008/NRsjCALeeOMNeHl5QaVSYdCgQbh+/bqVZkxUcQx9iIiIyKZUppEze/oQETU8rq6ueP3113H8+HFcvHgRkyZNwqRJk7B3715xzMqVK/H+++9j8+bNOHnyJDQaDUJCQpCbm2vFmVdefn6+tadAtYyhDxEREdkUUyNnaaWWdxlqZE5ERA3BRx99BG9vbxgM5t8rR40ahUmTJkEmk+HMmTMAAIPBAFdXV/Ts2VMc99lnn8HX11f8eP78+WjVqhXUajWaNWuGRYsWoaCgQDy+ePFidO7cGf/+97/h6+sLtVqNcePGIS0tzaL5BgcHY8yYMQgMDETz5s0xY8YMdOzYEUeOHAFgrPJZt24dFi5ciFGjRqFjx47Ytm0b4uPj8c0335R7/W3btsHBwcGsMmjatGlo06YNsrOzyz3f398fS5cuxdNPPw2NRgMfHx9s3LjRbExqaiomT54MNzc3aLVaDBgwABcuXCjxHm3ZsgUBAQGwt7cvd86NGjVCXl6e2fOjR4/Gs88+W+6cqe6pUOizYsUK9OjRA46OjnB3d8fo0aMRExNjNiY4OBgSicTsMXXqVPH4hQsX8PTTT8PX1xcqlQqBgYFYv3692TWioqJKXEMikSAxMbEKL5WIiIgIMBSGPnI2ciaiekQQBBiys2v9IRRWR1pi7NixuH//Pg4ePCg+l5ycjJ9//hnPPPMMOnfujKioKADApUuXIJFIcP78eWRmZgIADh06hH79+onnOjo6IjIyEleuXMH69evxn//8B2vXrjW7540bN/DFF1/g+++/x88//4zz589j2rRplXp/Dxw4gJiYGPTt2xcAEBsbi8TERAwaNEgc5+TkhEcffRTHjx8v95oTJ07E8OHDMWHCBOh0OuzZswdbtmzB9u3boVarLZrXqlWr0KlTJ5w/fx4LFizAjBkzsG/fPvH42LFjcffuXfz00084e/YsunbtioEDByI5OVkcc+PGDXz99dfYtWsXoqOjH3q/sWPHQq/X47vvvhOfu3v3Lvbs2YPnn3/eojlT3SKvyOBDhw4hLCwMPXr0gE6nw2uvvYYhQ4bgypUr0Gg04rgXX3wRb731lvhx8S/os2fPwt3dXUxxjx07hilTpkAmkyE8PNzsfjExMdBqteLH7u7uFX6BRERERMXpK1Ppw54+RGRlQk4OYrp2q/X7tj53FhILAwoXFxcMGzYMO3bswMCBAwEAX331FRo3boz+/fsjODgYUVFRmDt3LqKiojB48GD88ccfOHLkCIYOHYqoqCi88sor4vUWLlwo/t3f3x9z587Fzp07zcbk5uZi27Zt8PHxAQB88MEHGDFiBNasWQNPT89y55yWlgYfHx/k5eVBJpPhww8/xODBgwFALDrw8PAwO8fDw8PigoR///vf6NixI6ZPn45du3Zh8eLF6NbN8s9j7969sWDBAgBAq1atcPToUaxduxaDBw/GkSNHcOrUKdy9exd2dnYAgNWrV+Obb77BV199hSlTpgAwLunatm0b3Nzcyr2fSqXC+PHjERERgbFjxwIwVmA1bdoUwcHBFs+b6o4KhT4///yz2ceRkZFwd3fH2bNnxTQUMIY8Zf0H9mA62KxZMxw/fhy7du0qEfq4u7vD2dm5IlMkIiIieijT8i6Z5ZkP7Ll7FxGRRSZMmIAXX3wRH374Iezs7LB9+3Y89dRTkEql6NevHz7++GPo9XocOnQIQ4YMgaenJ6KiotCxY0fcuHHDLFj4/PPP8f777+PmzZvIzMyETqczKwoAgKZNm4qBDwAEBQXBYDAgJibGotDH0dER0dHRyMzMxIEDBzB79mw0a9as2gIOFxcXfPzxxwgJCUGvXr3EAMdSQUFBJT5et24dAOMqmszMTDRq1MhsTE5ODm7evCl+7OfnZ1HgY/Liiy+iR48euHPnDnx8fBAZGYnQ0FBIKtALj+qOCoU+DzKtlXR1dTV7fvv27fjss8/g6emJkSNHYtGiRQ8tX0tLSytxDQDo3Lkz8vLy0L59eyxevBi9e/cu8xp5eXlm6w7T09Mr+nKIiIjIBpgaOcullq9y5/IuIrI2iUqF1ufOWuW+FTFy5EgIgoA9e/agR48eOHz4sLgkq2/fvsjIyMC5c+fw22+/Yfny5fD09MQ777yDTp06wdvbGy1btgQAHD9+HBMmTMCSJUsQEhICJycn7Ny5E2vWrKnW1yeVStGiRQsAxt8/r169ihUrViA4OFgMjZKSkuDl5SWek5SUhM6dO1t8j99++w0ymQwJCQnIysqCo6Njtcw9MzMTXl5e4pK54ooXTxRflWOJLl26oFOnTti2bRuGDBmC33//HXv27KnibMlaKh36GAwGzJw5E71790b79u3F58ePHw8/Pz94e3vj4sWLmD9/PmJiYrBr165Sr3Ps2DF8/vnnZl9EXl5e2Lx5M7p37468vDxs2bIFwcHBOHnyJLp27VrqdVasWIElS5ZU9uUQERGRjSha3mX5OQx9iMjaJBKJxcusrMne3h6PP/44tm/fjhs3bqB169bi73DOzs7o2LEjNmzYAIVCgTZt2sDd3R1PPvkkfvjhB7N+PseOHYOfnx9ef/118bm//vqrxP3i4uIQHx8Pb29vAMCJEycglUrRunXrSs3fYDCIxQQBAQHw9PTEgQMHxJAnPT0dJ0+exL/+9S+Lrnfs2DG8++67+P777zF//nyEh4dj69atFs/nxIkTJT4ODAwEAHTt2hWJiYmQy+Xw9/e3+JqWmDx5MtatW4c7d+5g0KBBZg22qX6pdOgTFhaGy5cvi53NTUzrBgGgQ4cO8PLywsCBA3Hz5k00b97cbOzly5cxatQovPnmmxgyZIj4fOvWrc3+I+3Vqxdu3ryJtWvX4tNPPy11Pq+++ipmz54tfpyens4vTCIiIipBb6hEpY/SOJY9fYiIyjdhwgT83//9H37//Xc888wzZseCg4PxwQcf4J///CcA46qRwMBAfP7552Y7U7Vs2RJxcXHYuXMnevTogT179mD37t0l7mVvb4/nnnsOq1evRnp6OqZPn45x48ZZtLRrxYoV6N69O5o3b468vDz8+OOP+PTTT7Fp0yYAxqBt5syZePvtt9GyZUsEBARg0aJF8Pb2xujRo8u9fkZGBp599llMnz4dw4YNQ5MmTdCjRw+MHDlSfP3lOXr0KFauXInRo0dj3759+PLLL8WCiUGDBiEoKAijR4/GypUr0apVK8THx2PPnj0YM2YMunfvbtE9SjN+/HjMnTsX//nPf7Bt27ZKX4esr1JbtoeHh+OHH37AwYMH0aRJk4eOffTRRwEYO4YXd+XKFQwcOBBTpkwxa9BVlkceeaTENYqzs7ODVqs1exARERE9qDKNnO0V7OlDRGSpAQMGwNXVFTExMRg/frzZsX79+kGv15v1zAkODi7x3GOPPYZZs2YhPDwcnTt3xrFjx7Bo0aIS92rRogUef/xxDB8+HEOGDEHHjh3x4YcfWjTPrKwsTJs2De3atUPv3r3x9ddf47PPPsPkyZPFMa+88gpefvllTJkyBT169EBmZiZ+/vnncrc+B4AZM2ZAo9Fg+fLlAIxFEcuXL8dLL72EO3fuWDTHOXPm4MyZM+jSpQvefvttvPfeewgJCQFgDKV+/PFH9O3bF5MmTUKrVq3w1FNP4a+//irRfLqinJyc8MQTT8DBwcGigIvqLolQgT34BEHAyy+/jN27dyMqKkpcb/kwR48exT/+8Q9cuHABHTt2BAD8/vvvGDBgAJ577jmsXLnSonsPHjwYjo6OZS4Te1B6ejqcnJyQlpbGAIiIiIhEX5y5jVe+uoj+rd0QMekRi845H5eCMR8eQxMXFY7MH1DDMyQiW5ebm4vY2FgEBARYFC7YqsWLF+Obb74pdxvy+srf3x8zZ87EzJkzrXL/gQMHol27dnj//fetcn96+PcCSzOPCi3vCgsLw44dO/Dtt9/C0dFR3KbOyckJKpUKN2/exI4dOzB8+HA0atQIFy9exKxZs9C3b18x8Ll8+TIGDBiAkJAQzJ49W7yGTCYTO4qvW7cOAQEBaNeuHXJzc7Flyxb8+uuv+OWXXyoyXSIiIqISTJU+sgot7+KW7UREZBtSUlIQFRWFqKgoi6umqO6qUOhjWtv44PZ1ERERCA0NhVKpxP79+7Fu3TpkZWXB19cXTzzxhNnyra+++gr37t3DZ599hs8++0x83s/PD7du3QIA5OfnY86cObhz5w7UajU6duyI/fv3o3///pV8mURERERGRaGP5eeouLyLiKjecXBwKPPYTz/9hD59+lTp+suXLxeXbj2oT58++Omnn8o89/Dhwxg2bFiZxzMzM6s0t7LExcWhbdu2ZR6/cuUK+vbti5SUFLz77ruVbohNdUeFlnfVJ1zeRURERKXZeuwW3vzudwzv4IkPJ3Sz6Jy76bl4ZPkBSCXAzeXDIZFY3g+IiKiiuLyrejysJ6yPjw9UFdyO/kHJyclITk4u9ZhKpYKPj0+Z5+bk5Dy0r49pG/nqptPpxGKL0vj7+0Mur/R+T1TNan15FxEREVF9V5nlXfaFy7sMApCvN8BOLquRuRERUfWpqeDExNXVFa6urpU6V6VS1fj8SiOXy61yX7KeSu3eRURERFRfGQqLnGUVKNYxLe8CgNx8Q3VPiYiIiKhGMPQhIiIim6KrxJbtCpkU8sLxOWzmTERERPUEQx8iIiKyKablXfIKhD5AsWbODH2IiIionmDoQ0RERDbFIPb0qVjoY+rrwx28iIiIqL5g6ENEREQ2RVzeVcEduFjpQ0RERPUNQx8iIiKyKaZGzpVd3pXL0IeIiAr5+/tj3bp11p4GVYJEIsE333xj7WnUOIY+REREZFP0lWjkDHB5FxERVU1ubi7CwsLQqFEjODg44IknnkBSUpJ4/NatW5BIJIiOjq6W+yUkJGD8+PFo1aoVpFIpZs6cWeq45ORkzJw5E35+flAqlfD29sbzzz+PuLi4Ct/TVoKUB+3atQvdu3eHs7MzNBoNOnfujE8//dRsjCAIeOONN+Dl5QWVSoVBgwbh+vXrNT43hj5ERERkUyrfyNn4YxOXdxERVZ/8/HxrT6HWzJo1C99//z2+/PJLHDp0CPHx8Xj88cdr7H55eXlwc3PDwoUL0alTp1LHJCcno2fPnti/fz82b96MGzduYOfOnbhx4wZ69OiBP//8s8bmV1kFBQXWnkIJrq6ueP3113H8+HFcvHgRkyZNwqRJk7B3715xzMqVK/H+++9j8+bNOHnyJDQaDUJCQpCbm1ujc2PoQ0RERDalspU+7OlDRFS+4OBghIeHIzw8HE5OTmjcuDEWLVoEoXBprb+/P5YuXYqJEydCq9ViypQpAICvv/4a7dq1g52dHfz9/bFmzRqz65rOe/rpp6HRaODj44ONGzeajYmLi8OoUaPg4OAArVaLcePGmVXSXLhwAf3794ejoyO0Wi26deuGM2fOiMePHDmCPn36QKVSwdfXF9OnT0dWVpZ4/O7duxg5ciRUKhUCAgKwfft2i9+XtLQ0fPzxx3jvvfcwYMAAdOvWDRERETh27BhOnDhR6jlRUVGQSCQ4cOAAunfvDrVajV69eiEmJsaie/r7+2P9+vWYOHEinJycSh3z+uuvIz4+Hvv378ewYcPQtGlT9O3bF3v37oVCoUBYWJjZ9R5cyta5c2csXrxYPA4AY8aMgUQiET8uz6ZNm9C8eXMolUq0bt26RIWMRCLBpk2b8Nhjj0Gj0WDZsmXQ6/V44YUXEBAQAJVKhdatW2P9+vUlrv3JJ5+IX1deXl4IDw8vcx63b9/GuHHj4OzsDFdXV4waNQq3bt2y6DUEBwdjzJgxCAwMRPPmzTFjxgx07NgRR44cAWCs8lm3bh0WLlyIUaNGoWPHjti2bRvi4+NrvDKKoQ8RERHZFH3hLx6yijZyVrKnDxFZjyAIKMjT1/rDFNZUxNatWyGXy3Hq1CmsX78e7733HrZs2SIeX716NTp16oTz589j0aJFOHv2LMaNG4ennnoKly5dwuLFi7Fo0SJERkaaXXfVqlXieQsWLMCMGTOwb98+AIDBYMCoUaOQnJyMQ4cOYd++ffjzzz/x5JNPiudPmDABTZo0wenTp3H27FksWLAACoUCAHDz5k0MHToUTzzxBC5evIjPP/8cR44cMQsJQkNDcfv2bRw8eBBfffUVPvzwQ9y9e9ei9+Ts2bMoKCjAoEGDxOfatGmDpk2b4vjx4w899/XXX8eaNWtw5swZyOVyPP/88xbdszwGgwE7d+7EhAkT4OnpaXZMpVJh2rRp2Lt3L5KTky263unTpwEAERERSEhIED9+mN27d2PGjBmYM2cOLl++jJdeegmTJk3CwYMHzcYtXrwYY8aMwaVLl/D888/DYDCgSZMm+PLLL3HlyhW88cYbeO211/DFF1+I52zatAlhYWGYMmUKLl26hO+++w4tWrQodR4FBQUICQmBo6MjDh8+jKNHj8LBwQFDhw6tcDWaIAg4cOAAYmJi0LdvXwBAbGwsEhMTzT7/Tk5OePTRR8v9/FeVvEavTkRERFTHVHZ5l72CPX2IyHp0+QZ8NONQrd93yvp+UNjJKnSOr68v1q5dC4lEgtatW+PSpUtYu3YtXnzxRQDAgAEDMGfOHHH8hAkTMHDgQCxatAgA0KpVK1y5cgWrVq1CaGioOK53795YsGCBOObo0aNYu3YtBg8ejAMHDuDSpUuIjY2Fr68vAGDbtm1o164dTp8+jR49eiAuLg7z5s1DmzZtAAAtW7YUr71ixQpMmDBB7HvTsmVLvP/+++jXrx82bdqEuLg4/PTTTzh16hR69OgBAPj4448RGBho0XuSmJgIpVIJZ2dns+c9PDyQmJj40HOXLVuGfv36AQAWLFiAESNGIDc3F/b29hbduyz37t1Dampqma8hMDAQgiDgxo0beOSRR8q9npubGwDA2dm5RIhUltWrVyM0NBTTpk0DAMyePRsnTpzA6tWr0b9/f3Hc+PHjMWnSJLNzlyxZIv49ICAAx48fxxdffIFx48YBAN5++23MmTMHM2bMEMeZPncP+vzzz2EwGLBlyxZICv9RKCIiAs7OzoiKisKQIUPKfS1paWnw8fFBXl4eZDIZPvzwQwwePBgAxM+xh4eH2TmWfP6ripU+REREZFO4vIuIqGb17NlT/MUZAIKCgnD9+nXo9cbvn927dzcbf/XqVfTu3dvsud69e5udY7pOcUFBQbh69ap4DV9fXzHwAYC2bdvC2dlZHDN79mxMnjwZgwYNwjvvvIObN2+KYy9cuIDIyEg4ODiIj5CQEBgMBsTGxuLq1auQy+Xo1q2beE6bNm1KhDg1oWPHjuLfvby8AMDiCiNLVKaaq7qU9bk3fc5MHvyaAYCNGzeiW7ducHNzg4ODAz766COx+fTdu3cRHx+PgQMHWjSPCxcu4MaNG3B0dBQ//66ursjNzTX7OnkYR0dHREdH4/Tp01i2bBlmz56NqKgoi86tSaz0ISIiIptiCn0qvLyLoQ8RWZFcKcWU9f2sct/qptFoqv2alli8eDHGjx+PPXv24KeffsKbb76JnTt3YsyYMcjMzMRLL72E6dOnlzivadOmuHbtWpXu7enpifz8fKSmppoFRUlJSeVWxZiWoAEQwzSDwVCl+QDGypziodiDrl69ColEIi6JkkqlJQKi2mqq/ODXzM6dOzF37lysWbMGQUFBcHR0xKpVq3Dy5EkAxuVpFZGZmYlu3bqV2qfJVMFUHqlUKr5XnTt3xtWrV7FixQoEBweLn+OkpCQxuDN93Llz5wrNtaJY6UNEREQ2RQx9ZJXs6cPlXURkBRKJBAo7Wa0/JBUMyAGIv3ibnDhxAi1btoRMVvoyscDAQBw9etTsuaNHj6JVq1Zm5zzY8PjEiRPi0qTAwEDcvn0bt2/fFo9fuXIFqampaNu2rfhcq1atMGvWLPzyyy94/PHHERERAQDo2rUrrly5ghYtWpR4KJVKtGnTBjqdDmfPnhWvFRMTg9TUVIvek27dukGhUODAgQNm58fFxZWoYKotUqkU48aNw44dO0osMcrJycGHH36IkJAQuLq6AjCGHwkJCeKY9PR0xMbGmp2nUCjMqrPKU9bnvvjnrDRHjx5Fr169MG3aNHTp0gUtWrQwq8hxdHSEv7+/2fv9MF27dsX169fh7u5e4vNfVhPs8hgMBuTl5QEwLj/z9PQ0m096ejpOnjxZ459/hj5ERERkUyrbyNmelT5ERBaJi4vD7NmzERMTg//+97/44IMPzPqqPGjOnDk4cOAAli5dimvXrmHr1q3YsGED5s6dazbu6NGjWLlyJa5du4aNGzfiyy+/FK87aNAgdOjQARMmTMC5c+dw6tQpTJw4Ef369UP37t2Rk5OD8PBwREVF4a+//sLRo0dx+vRpMTSaP38+jh07hvDwcERHR+P69ev49ttvxUbOrVu3xtChQ/HSSy/h5MmTOHv2LCZPnmxxRYmTkxNeeOEFzJ49GwcPHsTZs2cxadIkBAUFoWfPnpV5my0SHR2N6OhoZGZm4t69e4iOjsaVK1fE48uXL4enpycGDx6Mn376Cbdv38Zvv/2GkJAQFBQUmO2QNmDAAHz66ac4fPgwLl26hOeee65EkGcKWhITE5GSklLu/ObNm4fIyEhs2rQJ169fx3vvvYddu3aV+Nw/qGXLljhz5gz27t2La9euYdGiRSUaRy9evBhr1qzB+++/j+vXr+PcuXP44IMPSr3ehAkT0LhxY4waNQqHDx9GbGwsoqKiMH36dPzvf/8r93WsWLFCbB5+9epVrFmzBp9++imeeeYZAMbQdubMmXj77bfx3Xff4dKlS5g4cSK8vb0xevTocq9fJUIDlZaWJgAQ0tLSrD0VIiIiqkOm//ec4Df/B+E/v92s0HkfH/5T8Jv/gxC+41wNzYyIyCgnJ0e4cuWKkJOTY+2pVFi/fv2EadOmCVOnThW0Wq3g4uIivPbaa4LBYBAEQRD8/PyEtWvXljjvq6++Etq2bSsoFAqhadOmwqpVq8yO+/n5CUuWLBHGjh0rqNVqwdPTU1i/fr3ZmL/++kt47LHHBI1GIzg6Ogpjx44VEhMTBUEQhLy8POGpp54SfH19BaVSKXh7ewvh4eFm7/GpU6eEwYMHCw4ODoJGoxE6duwoLFu2TDyekJAgjBgxQrCzsxOaNm0qbNu2rczXU5qcnBxh2rRpgouLi6BWq4UxY8YICQkJ4vHY2FgBgHD+/HlBEATh4MGDAgAhJSVFHHP+/HkBgBAbG2vRPQGUePj5+ZmNuXfvnvDyyy8Lvr6+gkKhEDw8PITQ0FDhr7/+MhuXlpYmPPnkk4JWqxV8fX2FyMhIoVOnTsKbb74pjvnuu++EFi1aCHK5vMR9yvLhhx8KzZo1ExQKhdCqVSth27ZtJV7D7t27zZ7Lzc0VQkNDBScnJ8HZ2Vn417/+JSxYsEDo1KmT2bjNmzcLrVu3FhQKheDl5SW8/PLLZV43ISFBmDhxotC4cWPBzs5OaNasmfDiiy9alCm8/vrrQosWLQR7e3vBxcVFCAoKEnbu3Gk2xmAwCIsWLRI8PDwEOzs7YeDAgUJMTMxDr/uw7wWWZh6Swhfb4KSnp8PJyQlpaWnQarXWng4RERHVEeE7zuGHiwl4c2RbTOodYPF5/z0Vh1d3XcKgQA9sea5kQ0kiouqSm5uL2NhYBAQEVHmHptoWHByMzp07Y926ddV6XX9/f8ycOVPcXYvIFjzse4GlmQeXdxEREZFNMZiWd1Vy965cLu8iIiKieoKhDxEREdkUnb5yoQ97+hARUVm2b99utt178Ue7du1q5J7t2rUr856l7UJlDfVhjpYo6zU4ODjg8OHD1p7eQ3HLdiIiIrIphko2cjbt3pXD3buIiMoUFRVVI9e9detWjVy3ujz22GN49NFHSz1WfMv16vTjjz+WuWW6h4dHjdyzourDHC0RHR1d5jEfH5/am0glMPQhIiIim2Lasl3K5V1ERFRNHB0d4ejoWKv39PPzq9X7VUZ9mKMlWrRoYe0pVBqXdxEREZFN0RWGPvJKhj5c3kVERET1BUMfIiIisimVbuSsNP7YxNCHiIiI6guGPkRERGRTTI2cpRXs6SM2cmZPHyIiIqonGPoQERGRTTFV+lR2eVeezgBD4RIxIiIiorqMoQ8RERHZlEo3ci7cvQsAcnWs9iEiIqK6j6EPERER2RRT6FPRLdvt5UWhD5d4ERERAPj7+2PdunXWngZVgkQiwTfffGPtadQ4hj5ERERkU/SmRs6yioU+UqkEdnI2cyYiosr56KOPEBwcDK1WC4lEgtTU1BJjqjuIuHjxIvr06QN7e3v4+vpi5cqVJcYkJydj5syZ8PPzg1KphLe3N55//nnExcVV+H62EqQ8aNeuXejevTucnZ2h0WjQuXNnfPrpp2ZjBEHAG2+8AS8vL6hUKgwaNAjXr1+v8bkx9CEiIiKbojcY/6xopQ9QtMQrl6EPEVG1yM/Pt/YUak12djaGDh2K1157rVbul56ejiFDhsDPzw9nz57FqlWrsHjxYnz00UfimOTkZPTs2RP79+/H5s2bcePGDezcuRM3btxAjx498Oeff9bKXCuioKDA2lMowdXVFa+//jqOHz+OixcvYtKkSZg0aRL27t0rjlm5ciXef/99bN68GSdPnoRGo0FISAhyc3NrdG4MfYiIiMim6A3G1KeiW7YDRc2cc/IN1TonIqKGIjg4GOHh4QgPD4eTkxMaN26MRYsWQSissvT398fSpUsxceJEaLVaTJkyBQDw9ddfo127drCzs4O/vz/WrFljdl3TeU8//TQ0Gg18fHywceNGszFxcXEYNWoUHBwcoNVqMW7cOCQlJYnHL1y4gP79+8PR0RFarRbdunXDmTNnxONHjhxBnz59oFKp4Ovri+nTpyMrK0s8fvfuXYwcORIqlQoBAQHYvn17hd6bmTNnYsGCBejZs6dF42/dugWJRIJdu3ahf//+UKvV6NSpE44fP27R+du3b0d+fj4++eQTtGvXDk899RSmT5+O9957Txzz+uuvIz4+Hvv378ewYcPQtGlT9O3bF3v37oVCoUBYWJg4trSlbJ07d8bixYvF4wAwZswYSCQS8ePybNq0Cc2bN4dSqUTr1q1LVMhIJBJs2rQJjz32GDQaDZYtWwa9Xo8XXngBAQEBUKlUaN26NdavX1/i2qbXbmdnBy8vL4SHh5c5j9u3b2PcuHFwdnaGq6srRo0ahVu3bln0GoKDgzFmzBgEBgaiefPmmDFjBjp27IgjR44AMFb5rFu3DgsXLsSoUaPQsWNHbNu2DfHx8TVeGcXQh4iIiGyK2NOnKqEPK32IqJYJgoCC3Nxaf5jCmorYunUr5HI5Tp06hfXr1+O9997Dli1bxOOrV69Gp06dcP78eSxatAhnz57FuHHj8NRTT+HSpUtYvHgxFi1ahMjISLPrrlq1SjxvwYIFmDFjBvbt2wcAMBgMGDVqFJKTk3Ho0CHs27cPf/75J5588knx/AkTJqBJkyY4ffo0zp49iwULFkChUAAAbt68iaFDh+KJJ57AxYsX8fnnn+PIkSNmIUFoaChu376NgwcP4quvvsKHH36Iu3fvVvj9qajXX38dc+fORXR0NFq1aoWnn34aOp2u3POOHz+Ovn37QqlUis+FhIQgJiYGKSkpMBgM2LlzJyZMmABPT0+zc1UqFaZNm4a9e/ciOTnZonmePn0aABAREYGEhATx44fZvXs3ZsyYgTlz5uDy5ct46aWXMGnSJBw8eNBs3OLFizFmzBhcunQJzz//PAwGA5o0aYIvv/wSV65cwRtvvIHXXnsNX3zxhXjOpk2bEBYWhilTpuDSpUv47rvv0KJFi1LnUVBQgJCQEDg6OuLw4cM4evQoHBwcMHTo0ApXowmCgAMHDiAmJgZ9+/YFAMTGxiIxMRGDBg0Sxzk5OeHRRx+1OMSrLHmNXp2IiIiojjHttl6Z0MeeoQ8RWYkuLw/vP/fPWr/v9K1fQWFvX6FzfH19sXbtWkgkErRu3RqXLl3C2rVr8eKLLwIABgwYgDlz5ojjJ0yYgIEDB2LRokUAgFatWuHKlStYtWoVQkNDxXG9e/fGggULxDFHjx7F2rVrMXjwYBw4cACXLl1CbGwsfH19AQDbtm1Du3btcPr0afTo0QNxcXGYN28e2rRpAwBo2bKleO0VK1ZgwoQJmDlzpnjs/fffR79+/bBp0ybExcXhp59+wqlTp9CjRw8AwMcff4zAwMAKvTeVMXfuXIwYMQIAsGTJErRr1w43btwQX0dZEhMTERAQYPach4eHeCw/Px+pqallvobAwEAIgoAbN27gkUceKXeebm5uAABnZ+cSIVJZVq9ejdDQUEybNg0AMHv2bJw4cQKrV69G//79xXHjx4/HpEmTzM5dsmSJ+PeAgAAcP34cX3zxBcaNGwcAePvttzFnzhzMmDFDHGf63D3o888/h8FgwJYtWyApXP4dEREBZ2dnREVFYciQIeW+lrS0NPj4+CAvLw8ymQwffvghBg8eDMD4fgNF77+Jh4eHeKymsNKHiIiIbIquKsu7lKblXQx9iIjK0rNnT/EXZwAICgrC9evXodcbv3d2797dbPzVq1fRu3dvs+d69+5tdo7pOsUFBQXh6tWr4jV8fX3FwAcA2rZtC2dnZ3HM7NmzMXnyZAwaNAjvvPMObt68KY69cOECIiMj4eDgID5CQkJgMBgQGxuLq1evQi6Xo1u3buI5bdq0gbOzc2Xeogrp2LGj+HcvLy8AqNYKo8pUc1WXsj73ps+ZyYNfMwCwceNGdOvWDW5ubnBwcMBHH30kNp++e/cu4uPjMXDgQIvmceHCBdy4cQOOjo7i59/V1RW5ublmXycP4+joiOjoaJw+fRrLli3D7NmzERUVZdG5NYmVPkRERGRTDFVp5KxgI2cisg65nR2mb/3KKvetbhqNptqvaYnFixdj/Pjx2LNnD3766Se8+eab2LlzJ8aMGYPMzEy89NJLmD59eonzmjZtimvXrllhxkamJWgAxDDNYCi/t5ynp6dZTyMA4seenp5wcnIyC8UedPXqVUgkEnFJlFQqLREQ1VZT5Qe/Znbu3Im5c+dizZo1CAoKgqOjI1atWoWTJ08CMC5Pq4jMzEx069at1D5Npgqm8kilUvG96ty5M65evYoVK1YgODhYrHxKSkoSgzvTx507d67QXCuKlT5ERERkU6rS04fLu4jIWiQSCRT29rX+kFQiIDf94m1y4sQJtGzZEjKZrNTxgYGBOHr0qNlzR48eRatWrczOOXHiRInrmpYmBQYG4vbt27h9+7Z4/MqVK0hNTUXbtm3F51q1aoVZs2bhl19+weOPP46IiAgAQNeuXXHlyhW0aNGixEOpVKJNmzbQ6XQ4e/aseK2YmJhSt12vK4KCgvDbb7+ZBTP79u1D69at4eLiAqlUinHjxmHHjh0llhjl5OTgww8/REhICFxdXQEYw4+EhARxTHp6OmJjY83OUygUZtVZ5Snrc1/8c1aao0ePolevXpg2bRq6dOmCFi1amFXkODo6wt/fHwcOHLBoHl27dsX169fh7u5e4vPv5ORk8espzmAwIC8vD4Bx+Zmnp6fZfNLT03Hy5MkSFWzVjaEPERER2RRdVRo5c3kXEVG54uLiMHv2bMTExOC///0vPvjgA7O+Kg+aM2cODhw4gKVLl+LatWvYunUrNmzYgLlz55qNO3r0KFauXIlr165h48aN+PLLL8XrDho0CB06dMCECRNw7tw5nDp1ChMnTkS/fv3QvXt35OTkIDw8HFFRUfjrr79w9OhRnD59WgyN5s+fj2PHjiE8PBzR0dG4fv06vv32W7GRc+vWrTF06FC89NJLOHnyJM6ePYvJkydXqKIkMTER0dHRuHHjBgDg0qVLiI6OtrhRckWNHz8eSqUSL7zwAn7//Xd8/vnnWL9+PWbPni2OWb58OTw9PTF48GD89NNPuH37Nn777TeEhISgoKDAbIe0AQMG4NNPP8Xhw4dx6dIlPPfccyWCPFPQkpiYiJSUlHLnOG/ePERGRmLTpk24fv063nvvPezatavE5/5BLVu2xJkzZ7B3715cu3YNixYtKtE4evHixVizZg3ef/99XL9+HefOncMHH3xQ6vUmTJiAxo0bY9SoUTh8+DBiY2MRFRWF6dOn43//+1+5r2PFihVi8/CrV69izZo1+PTTT/HMM88AMIa2M2fOxNtvv43vvvsOly5dwsSJE+Ht7Y3Ro0eXe/0qERqotLQ0AYCQlpZm7akQERFRHdLlrV8Ev/k/CDGJ6RU+d96X0YLf/B+EDb9er4GZEREZ5eTkCFeuXBFycnKsPZUK69evnzBt2jRh6tSpglarFVxcXITXXntNMBgMgiAIgp+fn7B27doS53311VdC27ZtBYVCITRt2lRYtWqV2XE/Pz9hyZIlwtixYwW1Wi14enoK69evNxvz119/CY899pig0WgER0dHYezYsUJiYqIgCIKQl5cnPPXUU4Kvr6+gVCoFb29vITw83Ow9PnXqlDB48GDBwcFB0Gg0QseOHYVly5aJxxMSEoQRI0YIdnZ2QtOmTYVt27aV+XpK8+abbwoASjwiIiLEMQCE3bt3C4IgCLGxsQIA4fz58+LxlJQUAYBw8OBBi+554cIF4R//+IdgZ2cn+Pj4CO+8806JMffu3RNefvllwdfXV1AoFIKHh4cQGhoq/PXXX2bj0tLShCeffFLQarWCr6+vEBkZKXTq1El48803xTHfffed0KJFC0Eulwt+fn4WzfHDDz8UmjVrJigUCqFVq1bCtm3bzI4Xf09McnNzhdDQUMHJyUlwdnYW/vWvfwkLFiwQOnXqZDZu8+bNQuvWrQWFQiF4eXkJL7/8cpnXTUhIECZOnCg0btxYsLOzE5o1aya8+OKLFmUKr7/+utCiRQvB3t5ecHFxEYKCgoSdO3eajTEYDMKiRYsEDw8Pwc7OThg4cKAQExPz0Os+7HuBpZmHpPDFNjjp6elwcnJCWloatFqttadDREREdUTHxXuRnqvD/tn90MLdoULnvvntZWw9/hdeHtACc4a0rqEZEpGty83NRWxsLAICAmBfwZ2zrC04OBidO3fGunXrqvW6/v7+mDlzpri7FpEteNj3AkszDy7vIiIiIpti2rJdXpmePlzeRURERPUIQx8iIiKyKVVp5KxiI2ciIirF9u3bzbZ7L/5o165djdxz2LBhZd5z+fLlNXLPimrXrl2Zcyxtp6y6qqzX4ODggMOHD1t7eg/FLduJiIjIpphCHylDHyKiahcVFVUj171161aNXLe6PPbYY3j00UdLPVZ8y/XqtGXLFuTk5JR6zLTjlrX9+OOPZW7r7uHhUcuzqbzo6Ogyj/n4+NTeRCqBoQ8RERHZFH1hO8PKLO8y7d6Vy9CHiIiKcXR0hKOjY63es66HDQDg5+dn7SlUixYtWlh7CpXG5V1ERERkMwRBKKr0kVSip4+CPX2IiIio/mDoQ0RERDbDUGzPUvb0IaK6zmAwWHsKRGRF1fE9gMu7iIiIyGboi6U+VQt9+IsYEdUcpVIJqVSK+Ph4uLm5QalUQlKJ6kQiqp8EQUB+fj7u3bsHqVQKpVJZ6Wsx9CEiIiKbYRCqGPqYevpweRcR1SCpVIqAgAAkJCQgPj7e2tMhIitRq9Vo2rQppNLKL9Ji6ENEREQ2Q1es0qcyjZztubyLiGqJUqlE06ZNodPpoNfzew6RrZHJZJDL5VWu8mPoQ0RERDaj+PKuyjRyZk8fIqpNEokECoWixrb8JqKGj42ciYiIyGYYqtrTh8u7iIiIqB5h6ENEREQ2Q2dW6VPx81npQ0RERPUJQx8iIiKyGaZGzjKppFJr5E2hj84goEDPHbyIiIiobmPoQ0RERDbDVOkjq2RTRHtl0Y9OrPYhIiKiuq5Coc+KFSvQo0cPODo6wt3dHaNHj0ZMTIzZmODgYEgkErPH1KlTzcbExcVhxIgRUKvVcHd3x7x586DT6czGREVFoWvXrrCzs0OLFi0QGRlZuVdIREREVMjU06cy/XwAQCmTiueyrw8RERHVdRUKfQ4dOoSwsDCcOHEC+/btQ0FBAYYMGYKsrCyzcS+++CISEhLEx8qVK8Vjer0eI0aMQH5+Po4dO4atW7ciMjISb7zxhjgmNjYWI0aMQP/+/REdHY2ZM2di8uTJ2Lt3bxVfLhEREdkyfRVDH4lEwr4+REREVG9UaMv2n3/+2ezjyMhIuLu74+zZs+jbt6/4vFqthqenZ6nX+OWXX3DlyhXs378fHh4e6Ny5M5YuXYr58+dj8eLFUCqV2Lx5MwICArBmzRoAQGBgII4cOYK1a9ciJCSkoq+RiIiICEDR8q5KZj4AAHuFDJl5OoY+REREVOdVqadPWloaAMDV1dXs+e3bt6Nx48Zo3749Xn31VWRnZ4vHjh8/jg4dOsDDw0N8LiQkBOnp6fj999/FMYMGDTK7ZkhICI4fP17mXPLy8pCenm72ICIiIirO1MhZLqv8j0Cqwr4+OVzeRURERHVchSp9ijMYDJg5cyZ69+6N9u3bi8+PHz8efn5+8Pb2xsWLFzF//nzExMRg165dAIDExESzwAeA+HFiYuJDx6SnpyMnJwcqlarEfFasWIElS5ZU9uUQERGRDdCLlT6VL/Xh8i4iIiKqLyod+oSFheHy5cs4cuSI2fNTpkwR/96hQwd4eXlh4MCBuHnzJpo3b175mZbj1VdfxezZs8WP09PT4evrW2P3IyIiovrHFPrIq7C+yxT6/Oe3P/HjpYRqmVd946xS4sW+zeCkUlh7KkRERPQQlQp9wsPD8cMPP+C3335DkyZNHjr20UcfBQDcuHEDzZs3h6enJ06dOmU2JikpCQDEPkCenp7ic8XHaLXaUqt8AMDOzg52dnaVeTlERERkI6rayBkAGjsYf944GHOvWuZUX3k62eOZnn7WngYRERE9RIVCH0EQ8PLLL2P37t2IiopCQEBAuedER0cDALy8vAAAQUFBWLZsGe7evQt3d3cAwL59+6DVatG2bVtxzI8//mh2nX379iEoKKgi0yUiIiIyoy/s6SOtQlfDRf/XFl2aOotNoW3N3t+TcDUhHVl5OmtPhYiIiMpRodAnLCwMO3bswLfffgtHR0exB4+TkxNUKhVu3ryJHTt2YPjw4WjUqBEuXryIWbNmoW/fvujYsSMAYMiQIWjbti2effZZrFy5EomJiVi4cCHCwsLESp2pU6diw4YNeOWVV/D888/j119/xRdffIE9e/ZU88snIiIiW1K0vKvyqY9/Yw3CB7SsrinVO/GpObiakG6zoRcREVF9UqGfeDZt2oS0tDQEBwfDy8tLfHz++ecAAKVSif3792PIkCFo06YN5syZgyeeeALff/+9eA2ZTIYffvgBMpkMQUFBeOaZZzBx4kS89dZb4piAgADs2bMH+/btQ6dOnbBmzRps2bKF27UTERFRleirYct2W2daGmdg6ENERFTnVXh518P4+vri0KFD5V7Hz8+vxPKtBwUHB+P8+fMVmR4RERHRQ1VHTx9bZ3rvWOlDRERU91VhRTsRERFR/VIU+vBHoMqSFW53byjnHwOJiIjI+vgTDxEREdkMUyNnGX8CqjRTYMZKHyIiorqPP/IQERGRzdDrC0MfCZd3VZYpMGNPHyIiorqPoQ8RERHZjKJKH4Y+lcVKHyIiovqDoQ8RERHZDAMbOVeZqdJHz9CHiIiozmPoQ0RERDZDJ27ZztCnskxL4xj6EBER1X0MfYiIiMhmmHackssY+lSWaXmXnrt3ERER1XkMfYiIiMhm6FnpU2Xi8i49Qx8iIqK6jqEPERER2QzT8i45e/pUGit9iIiI6g+GPkRERGQz2Mi56tjImYiIqP5g6ENEREQ2w1SdwuVdlSdW+jD0ISIiqvMY+hAREZHNMAUVbORceaa3jqEPERFR3cfQh4iIiGwGGzlXnUzGSh8iIqL6gqEPERER2Qw9e/pUmawwMGMjZyIiorqPoQ8RERHZDIY+VWfa+YyVPkRERHUfQx8iIiKyGabqFBmXd1WalKEPERFRvcHQh4iIiGyGXs9Kn6pipQ8REVH9wdCHiIiIbIZY6cPQp9JY6UNERFR/yK09AaKGLGP/fsTPXwBDXp61p2I1UqUSXm8vhXb4cGtPhYgIBvb0qTJW+hAREdUfDH2IalDq17tgyMqy9jSsyqDTIWP/foY+RFQn6Bj6VJmUu3cRERHVGwx9iGqIIAjIiY4GAPj+ezPs2rSx7oSsIGPvXiQtXwF9eoa1p0JEBICNnKuDqdJHx0ofIiKiOo+hD1ENKfjrL+hTUiBRKqEJCoJEqbT2lGqdokkTAIA+Pd3KMyEiMuLyrqozvXcGhj5ERER1Hhs5E9WQ7PPRAAD79u1tMvABAJlWCwAwMPQhojqCy7uqTspKHyIionqDoQ9RDck5fx4AoOrS2boTsSKpozH0YaUPEdUVrPSpOjkrfYiIiOoNhj5ENcTUz0fVubNV52FNMq0jAECfkQGBDT+JqA4w9fSRsqdPpZneO53BYOWZEBERUXkY+hDVAH1GBvKuXwcAqG069DFW+qCgAEJurnUnQ0SEom3G5az0qTS5rLDSh1k+ERFRncfQh6gG5Fy8CAgCFL6+kLu5WXs6ViNRqwGZDACXeBFR3WAKfaQMfSqNlT5ERET1B0MfohqQU9jE2ZaXdgGARCKBzNG4xIvNnImoLmAj56or6ulj5YkQERFRuRj6ENUANnEuInUqbOackWHlmRARFTUf5vKuypNJWelDRERUXzD0IapmgsGAnAsXANh2Px8TmWkHr7Q0K8+EiAjQF/ahYSPnyjOFPnpmPkRERHUeQx+iapZ34wYMmZmQqNWwa9XK2tOxOlMzZwMrfYioDtAXVqdweVflmd47A3dlJCIiqvMY+hBVM7GfT4cOkMjl1p1MHSDVmip92NOHiKxPz54+VSYu72KpDxERUZ3H0IeomuVERwNgPx8TUyNnfQZDHyKyPlNOwdCn8mQSbtlORERUXzD0IapmpibO6i5drDyTukFW2MjZkM7lXURkfVzeVXVs5ExERFR/MPQhqka6lBTk37oFAFB16mTdydQRUlMjZ27ZTkR1gKmRs4yNnCtNxi3biYiI6g2GPkTVyLS0S9msGWTOzladS10h0xqXdxm4vIuI6gADe/pUmZyVPkRERPUGQx+iaiQ2ceZW7SI2ciaiukTH5V1VJpUW9fQRuIMXERFRncbQh6gasYlzSaYt2/Xcsp2I6gADGzlXmbzYe6dnN2ciIqI6jaEPUTURCgqQc+kSADZxLs4U+hjY04eI6gBTpY+UPX0qTVo89GGlDxERUZ0mt/YEiOo6Q34+hJyccsflxsRAyMmBVKuFslmzWphZ/cBGzkRUl5gaOctZ6VNpxZtgs9KHiGpCfq4OBj2/v1DNkiulkCtk1p5GjWPoQ1SOjJ9+Qvz8BRaPV3XqBImURXQmYiPnzEwIBgPfGyKyKjZyrjoZl3cRUTXJz9UhOSELyfFZSL6Thfvxmbgfn4Wc9HxrT41sQO9/tkDnQU2tPY0ax9CHqBpJFAo4jRpl7WnUKaZGzhAEGDIyIHNysu6EiMim6QpDCilDn0pj6ENEFaXXG5CamI3k+Czcv2MMdpLjM5H+d661p0bU4DH0ISqHduRIaIcPt2ywVAqJrOGXCFaEVKmExN4eQm4u9Ax9iMjKTJU+XN5VeVzeRURlEQwCMpJzcb8w3DGFPKlJ2WUu11JplWjkrUEjbwe4+hj/dPFUQ6ZkdTjVLImN9Pdj6ENUDolUCnBJUpXIHB2hy81lM2cisjpT42E2cq48qVQCiQQQBIY+RLYsOz0f9+MzxWVZyfHGZVoFefpSxyvsZWjkrYGrtwMa+RT+6a2BylFZyzMnsi0MfYioxkmdtMC9e2zmTERWp2dPn2ohl0pQoBe4exeRDcjP1YmBTvGlWTkZBaWOl8okcPHUwNVbg0Y+RRU8jq72NlNZQVSXMPQhohon4w5eRFRHMPSpHsZKKQE67q5D1GDodQakJmUbmynfKQp5Mu6X0XdHAmgbq4xLs3wcjCGPtwOcPFSQyVglT1RXMPQhohonK2zmbMjIsPJMiMjWMfSpHnKpBHkADKz0Iap3BIOA9Pu5RT13CpdmpSZmi33PHqTWKouWZBX+6eqlgcKOvSyJ6jqGPkRU40w7eOnTWOlDRNalZyPnamHa/Yw9fYjqLkEQkJNRYNZQ+X58FpITsqAro++O0l5m3nPHx7hMS+XAvjtE9RVDHyKqcTJHRwCAPoOhDxFZFxs5Vw85Qx+iOiU/R4fkBPOeO/fvZCE3s4y+O3Jj3x2x507hEi0HFzv23SFqYBj6EFGNkzoVLu9ipQ8RWZmBy7uqhen9YyNnotqlLzAgJSnbfGnWnSxkJJfdd8epsaqo507hn87uKkjZd4fIJjD0IaIaJzZyZk8fIrIyHUOfamF6/9jImahmGPvu5BQ2VDZW7dyPz0JaUtl9dzROSrj6OJhti+7ipYFCyb47RLaMoQ8R1TiZ1ri8y8Ddu4jIyljpUz1khcs/2MiZqGoEQUB2ej6S7xirdu7HZyH5Tqax706+odRzlCq5MdgpDHga+Wjg6uUAewdFLc+eiOoDhj5EVOPERs4MfYjIysRKH/asqBKZrLDShz19iCyWl6MTGyoX/zM3q/S+OzK5FC5eamPPnWK9d9h3h4gqgqEPEdU405btbORMRNZm6kFjCi2ocsRKH4Y+RCUY++5kPbA0KxOZyXmljpdIACd3tbHnTrGlWU5u7LtDRFVXodBnxYoV2LVrF/744w+oVCr06tUL7777Llq3bl1irCAIGD58OH7++Wfs3r0bo0ePBgBERkZi0qRJpV4/KSkJ7u7uiIqKQv/+/UscT0hIgKenZ0WmTER1gCn0YSNnIrI2Ayt9qoXY04ehD9kwg0FA+r0cYzPlYpU7qXdzIJTVd8fZrmg79MLGyi6easjZd4eIakiFQp9Dhw4hLCwMPXr0gE6nw2uvvYYhQ4bgypUr0Gg0ZmPXrVtXatnhk08+iaFDh5o9FxoaitzcXLi7u5s9HxMTA23hL4sAShwnovpBXN7FRs5EZGWmkELKfzyvElPow0ofsgWCICArNQ/3iwU7yfFZSE7Igr6g9L47dmp5YeWOgxjyuHprYK9h3x0iql0VCn1+/vlns48jIyPh7u6Os2fPom/fvuLz0dHRWLNmDc6cOQMvLy+zc1QqFVQqlfjxvXv38Ouvv+Ljjz8ucT93d3c4OztXZIpEVAfJHI2NnIXcXBjy8yFVKq08IyKyRcUDCjlTnyqRSljpQw1TblZBse3QjcuzkuOzkJetK3W8XCGFi5fGrLGyq7cDNM5K9t0hojqhSj190tLSAACurq7ic9nZ2Rg/fjw2btxo0VKsbdu2Qa1W45///GeJY507d0ZeXh7at2+PxYsXo3fv3mVeJy8vD3l5Retk09kwlqjOkDo6GhesCwIM6emQNm5s7SkRkQ3SF9tpisu7qkZe2BNJz927qJ4qyNMjOaGw507hjln347OQnZZf6niJVAJndxUa+TiIFTyuPhpoG6sg5W6ARFSHVTr0MRgMmDlzJnr37o327duLz8+aNQu9evXCqFGjLLrOxx9/jPHjx5tV/3h5eWHz5s3o3r078vLysGXLFgQHB+PkyZPo2rVrqddZsWIFlixZUtmXQ0Q1SCKVQurgAENGBvTpGZAz9CEiK9AXq0phI+eqMYVmej1DH6rb9HoDUpOyzXfNis9C+t85QBlfvo6N7MWKHVdT3x0PNWQKVggSUf1T6dAnLCwMly9fxpEjR8TnvvvuO/z66684f/68Rdc4fvw4rl69ik8//dTs+datW5s1h+7Vqxdu3ryJtWvXlhhr8uqrr2L27Nnix+np6fD19a3ISyKiGiRzdIQhIwOG9DRrT4WIbJRZ6MNKnyox9fRhpQ/VFYJBQEZyLu4XVuwkFy7NSknMhqGMcFLlqDBrqOzqrYGrlwZKFTc4JqKGo1Lf0cLDw/HDDz/gt99+Q5MmTcTnf/31V9y8ebNEH54nnngCffr0QVRUlNnzW7ZsQefOndGtW7dy7/nII4+YBUwPsrOzg52dXYVeBxHVHqmTExAfz2bORGQ1xQMKtvSpGjH0YU8fqmWCICAno3jfHeOW6MkJWdDl6Us9R2EnEyt2im+LrtayxyARNXwVCn0EQcDLL7+M3bt3IyoqCgEBAWbHFyxYgMmTJ5s916FDB6xduxYjR440ez4zMxNffPEFVqxYYdG9o6OjSzSFJqL6w9TMWc9+W0RkJcWXIrGRc9Uw9KHakJejEyt27t8p6r+Tm1lQ6nipXAIXT1OoUxTyOLras6kyEdmsCoU+YWFh2LFjB7799ls4OjoiMTERAODk5ASVSgVPT89Smzc3bdq0RED0+eefQ6fT4Zlnnikxft26dQgICEC7du2Qm5uLLVu24Ndff8Uvv/xSkekSUR0iczJu225g6ENEVmJW6cPf/6qEoQ9VJ12BHimJD/bdyURmcl7pJ0gAJzeVsZlysXDHyV0FmYyBLhFRcRUKfTZt2gQACA4ONns+IiICoaGhFbrxxx9/jMcff7zULdnz8/MxZ84c3LlzB2q1Gh07dsT+/fvRv3//Ct2DiOoOqaMx9NGnc3kXEVmHKaCQSsB/9a8iWWGlFEMfqgiDQUD6vZxifXeMFTxpd7NRVnsojbPdA9uha+DipYFCKavdyRMR1VMVXt5VUWWdc+zYsTLPeeWVV/DKK69U+F5EVHcVLe9iI2cisg5TQMGlXVVn2vyMjZypNIIgIDMlT6zYSb5j/DMlMRv6AkOp59ip5eY9d3wc4Oqlgb1GUcuzJyJqWNianohqhVRc3sVKHyKyDrHSh5lPlbHSh0xyMwuKminHF22Jnp+jK3W8XCE17pJl1ljZAWonJSvwiIhqAEMfIqoVMtPyLu7eRURWYgoouF171ZnapjD0sR0FeXokJxT13DEtzcpOzy91vEQqgbOHGo18inbLcvXWQNtYBSmbahER1RqGPkRUK2Ra4/IuA5d3EZGVmJYiyfgLZ5XJWenTYOn1BqSamioXq+BJv58LlPHp1ja2F0OdRoUVPM7uasgULKsjIrI2hj5EVCukWjZyJiLrMhgY+lQXKXfvqvcEg4D0+7kltkNPTcqGQV/651WlVZbYDt3VSwOlPX+lICKqq/gdmohqhcwU+mRwy3Yisg4dQ59qI2foU28IgoDs9PwHtkPPQnJCFnR5+lLPUdjLHtgxy/inylFZy7MnIqKqYuhDRLXCFPoY0hj6EJF16Bn6VBtpYV8k7t5Vt+Tl6JAsbodeFPLkZhWUOl4ql8DVSyM2UzZV8Di42LGpMhFRA8HQh4hqhbi8KyMDgiDwh0kiqnUGgY2cqwsrfaxLV6BHSkK2uCTLtDwrMyWv1PESCeDkri7aNcvbAY18NHByU0EqY98dIqKGjKEPEdUKmaOxkTP0ehiysiFz0Fh3QkRkc8TlXTKGPlXFnj61w6A3IO1eTomlWWl3s1FWkZWDi11R5Y6P8U8XTzXkSlntTp6IiOoEhj5EVCskKhWgUAAFBTBkpDP0IaJaZ+CW7dXGVByiY+hTLQRBQGZKXrHt0I07Z6UkZEOvM5R6jp1GbqzYMeu9o4GdWlHLsyciorqMoQ8R1QqJRAKZoyP0ycnQp2dA4eVl7SkRkY0xVaVI2dOnykxbthsY+lRYTmY+ku8UNlMutnNWfm7pTZXlSqmx705hsGOq4FFrlVwqTURE5WLoQ0S1RqbVQp+cDEN6mrWnQkQ2yBT6yBn6VJmpkTMrfcqWn6tDSkI27sdnFoY8xiqe7PT8UsdLpRI4e6ofaKqsgbaRChJ+zRIRUSUx9CGiWlO8mTMRUW0z7TQlZXVElckL+yIZuHsX9DoDUpOKhzvGyp30v3PLPEfb2F7cBt3Ud8fZQw2ZnE2ViYioejH0IaJaY2rmrOe27URkBTpu2V5txEofve2EPoJBQPr9nMLlWFnizlmpidllLnNTa5Ulmyp7qaG054/gRERUO/h/HCKqNTInY6WPIYOhDxHVPgOXd1Ub03vYECt9BEFAdnq+uCTrfnwWku9kIjkhC7r80psqK+1lcC0W7JiaKqsclbU8eyIiInMMfYio1kgdC5d3pXN5FxHVPjZyrj6m91BnKD0EqS/ysgvEbdCT7xQGPPFZyM0qKHW8TC6Fi5da7Llj7LvjAAcXOzZVJiKiOomhDxHVGpm2cHkXGzkTkRXouWV7tTFV+ujrSeajy9cjJbFk353MlLxSx0skgJO7WqzYaeRjDHmc3FSQyth3h4iI6g+GPkRUa0yNnA2s9CEiKzA1cmZPn6ozvYd1bct2g96AtHs54jbopsqdtLvZKGslmoOLnbGpso+mMORxgIunGnKlrHYnT0REVAMY+hBRrZGJy7vY04eIap+ejZyrjUxq3S3bBUFAZkoe7t/JLFyeZfwzJSEbel3p5Uf2GgUa+RhDHWNzZQ1cfRxgp+KPw0RE1HDx/3JEVGvERs4MfYjIChj6VB/TErnaaOSck5lvXrlT+Pf8XH2p4+V2Mrh6aUoszVJrley7Q0RENoehDxHVGrGRcwaXdxFR7WPoU31qotInP1eH5ITC7dCL7ZyVk55f6nipVAJnT7VYsWNamqVtZA8JP8dEREQAGPoQUS0qauTMSh8iqn2mqhQ2cq66qvT00esMSE0yNlU2VvAYK3fS/84t8xxtY3uxYse0c5azhxoyOZsqExERPQxDHyKqNTItl3cRkfXoWOlTbWQWbNkuGASk3y/ZVDk1MbvMsEjtpBQrdkxLs1w81VDa80dWIiKiyuD/QYmo1oi7d2VlQdDpIJHzWxAR1R4DQ59qIyu2ZbsgCMhOzy/WVDkLyXcykZyQBV1+6aGQUiUv0XPH1VsDlYOyNl8GERFRg8ffuIio1sgcHcW/6zMyIHdxseJsiMjWmHr6SBn6VFpedgHux2chPyYNg7IVaHE5Ex/PPYy8LF2p42VyKVy81CWWZjm42LGpMhERUS1g6ENEtUaiUECiVkPIzoYhIwNg6ENEtci0vEvO0Kdcunw9UhKL990xVvFkpuSJY7pADuQbkAcDJBLA2UNdWLHjgEY+xoBH66ZiyEZERGRFDH2IqFbJHB2hy86GPo19fYiodrGRc0kGvQFp94x9d+4XBjv372Qi/V4OytqN3cHVDjoHOQ4lpcLFW4OF4zvBxVMNuUJWu5MnIiKicjH0IaJaJdNqoUtKgiGDoQ8R1S6dDS/vEgwCMpJzC3vuFPXeSUnMgkFXerpjr1GgkY/5duiu3hrYqeT4/kI8fvvv3+jpIoObr2Op5xMREZH1MfQholplauasT8+w8kyIyNYYbGB5lyAIyMkoMAY7xap3kuOzUJCnL/UcuZ2sqKmytwNcC5dmqRwVZfbdKWrkXPEt24mIiKj2MPQholplauasT0+z8kyIyNboCzeSaiiVPnnZBUW7ZcUXbYuem1lQ6nipTAIXT9OOWRq4ehl3znJ0tYekgu8JQx8iIqL6gaEPEdUqmVPhtu0ZrPQhotqlNxhTn/rW06cgX4+UhKxiAU/JpsrFSSSAk7ta3AbdtGOWk7sKMpm0WuZkeg8Z+hAREdVtEkEoq01f/Zaeng4nJyekpaVBW7ichIisL/HtZUj57DNI7O0htbe39nSIyIbkFOiRU6CHvVwGtbLuNR02QIps+8bItPcoeqjckaN0BSSlhzX2+SlwyLkLh9wkaHKTCv+8B5lQ+hbq1aVALyAjrwByqQRae0WN3ouIbI9ErYL3smXQBAVZeypEdZalmQcrfYioVqk6dkAKACE3F/rcXGtPh4hsiLLwgXxAn229eQiQIMe+EbI03sjSeCGz8M9stQcEaek/minyM6DJiodDVkLhn/HQZCVAri/9+2jp3XuqjxSAk+le/FZORNUtNRVpe/Yw9CGqBgx9iKhWOT32GNQ9esCQlWXtqRCRjfn3oZv46uz/MK67L17s26zG7ycIArIz9Uj5uwDJfxcgpfCRer8AujJ2zFIoJXBprCh8KOHaWAGXRgqoNDIA7Wp8zpY6H5eCV766CL/GamyZ2MPa0yGiBiTj4EHcW/MedPEJ1p4KUYPA0IeIap3Cy8vaUyAiG5R6NR9xWh2yvJvCrkWLar12bmYBkhMycf+Oed+dvOzSl1nJ5FK4eKnFfjvG5soOcHCxK3PHrDpFeh9x2rtQOGmq/b0kItumu58MACiIj7fyTIgaBoY+REREZBMMhW0Mq9LIOT9Xh5SE7GJboRt3zMpOyy91vEQqgbO7Cq7eDsYdswobK2vdVPV6FzE5d+8iohqi8Db+42BBQgIEQagfQThRHcbQh4iIiGyCzrR7lwVhi77AgJSkbDHUMQU86X+X3cBG29geroWVO428NXD1doCLhxoyRfXsmFWXmAIrfcPcD4SIrEjh4QFIJBDy8qBPSYHc1dXaUyKq1xj6EBERkU3QGzMfs9DHYBCQfi9HrNy5f8cY7qTezYFQRhWLWqsUl2OZKndcvNRQ2tvOj1VipY+eoQ8RVS+JUgm5mxt0d++i4E48Qx+iKrKdn06IiIjIZgmCAGQXIKBACllMBvbHXcH9+EykJGZDX2Ao9Rw7tbyw345DYeWO8aFyUNby7OseqYSVPkRUcxReXsbQJyEeqg7trT0donqNoQ8RERE1KNnp+SWWZSXHZ6FJrh7/hB1wMRUxxcbLFVIx0CkKeBygcVayl0QZ5DL29CGimqPw8UbOhQts5kxUDRj6EBERUb2Ul6Mza6ZsCndyMgpKHS9IgL8lBnj4OqJHJ4/CJVoaaBupIKnHTZWtwdQMm6EPEdUEeeFOr7oEbttOVFUMfYiIiKhO0+XrkZJY1FTZ1HcnMyWv9BMkgFNjlVnfHVdvDRYfvIbvLyVgUZ/m6P4P/1p9DQ2NqS+SjqEPEdUAhZc3AKAgnqEPUVUx9CEiIqI6Qa83IO1ujrGhsrglehbS7majrNYxDi52JfruuHhpoFDKSow1de6Rs6qnykyhj4GhDxHVAIW3KfTh8i6iqmLoQ0RERLVKMAjISM4Vl2QZK3eykJKUBYOu9BDBXqMo2grdp2hbdDu1wuL7mpYiSRn6VBkrfYioJim8jcu7Cri8i6jKGPoQERFRjRAEwdhU+U5R5c79+CwkJ2RBl6cv9RyFnUxcjtXIu2hpllpb9abKpoBCxubMVSZW+nD3LiKqAYrCnj765GQYcnMhtbe38oyI6i+GPkRERFRluVkFDzRVNgY9eVm6UsdL5RK4eGrEJVmmgMfR1b7GmiqbAgou76o6U3DGSh8iqglSrRZSjQaGrCwUxCfArlmAtadEVG8x9CEiIiKLFeTpkZxgHu4k38lEVlp+qeMlEsDJXS2GO67eDmjko4GTmwpSmbRW587lXdXHVOkjCMa+PnxPiag6SSQSKLy9kHf9BgoS4hn6EFUBQx8iIiIqQa8zIDUpW6zYMe2YlX4/FyijuMPR1R6uPqbqHWPljounGnJFyabK1mAKfVjpU3WyYu+hXhAgBd9TIqpecq/C0IfNnImqhKEPERGRDTMYBKT/nVNiaVZqYnaZOzOptMoSy7JcvTRQqur2jxWs9Kk+ZqGPQUAdyfWIqAEx7eClYzNnoiqp2z+dERERUbUQBAFZqXnGUOdOUcCTkpAFXYGh1HOU9jJjxU6x6p1G3hqoHJW1PPvqoRfYyLm6PBj6EBFVN4WXadt2hj5EVcHQh4iIqIHJyTTtmGUMd0y7ZuXnlN5UWaaQwtVLU2LXLAcXuyrvmFWXmMIJGSt9quzB5V1ERNVN3Lady7uIqoShDxERUT2Vn6srXJZlviV6TnoZTZWlEjh7qEsszdK6qWxiyRNDn+pTvFqqrGWARERVYVreVcDlXURVwtCHiIiojtMV6JGSmG3ed+dOFjKSc8s8R9vYXlyOZVye5QBndzVkitrdMasuKQp9rDyRBqB4cMZt24moJii8Cit9EhMhGAyQSPnNm6gyGPoQERHVEQa9AWn3csSKneQ7xoAn7W42ylpBo3FSwtXHobByx9h3x8VTDaU9/xf/oKLQh784VJVEIoFUAhgEVvoQUc2Qu7sDMhlQUADdvb+h8HC39pSI6qUK/US4YsUK7Nq1C3/88QdUKhV69eqFd999F61bty4xVhAEDB8+HD///DN2796N0aNHi8dK6w/w3//+F0899ZT4cVRUFGbPno3ff/8dvr6+WLhwIUJDQysyXSIiojpJEARkJOeWWJqVkpANva70psp2arnZkqxGhUGPvUZRy7Ovvwxs5Fyt5FIp8vUGVvoQUY2QyOWQe7hDF58AXUI8Qx+iSqpQ6HPo0CGEhYWhR48e0Ol0eO211zBkyBBcuXIFGo3GbOy6dese2vwxIiICQ4cOFT92dnYW/x4bG4sRI0Zg6tSp2L59Ow4cOIDJkyfDy8sLISEhFZkyERGR1QiCgJyMAmOoU2zHrOSELBTk6ks9R64sbKrs42DWe0ftpGxQTZWtQSdu2W7liTQQUikAPXfvIqKao/Dyhi4+AQUJCVB17mzt6RDVSxUKfX7++WezjyMjI+Hu7o6zZ8+ib9++4vPR0dFYs2YNzpw5A6/CtZgPcnZ2hqenZ6nHNm/ejICAAKxZswYAEBgYiCNHjmDt2rUMfYiIqE7Kyy4oWpZVrPdObmZBqeOlMglcPNXGLdGLLc3SNrKHhI2Ga4RpGZKcqU+1ML6PBoY+RFRjFF5eyAF38CKqiiot+E9LSwMAuLq6is9lZ2dj/Pjx2LhxY5mhDgCEhYVh8uTJaNasGaZOnYpJkyaJ/4J5/PhxDBo0yGx8SEgIZs6cWeb18vLykJeXJ36cnp5emZdERET0UAX5eqQkZBULeIxLszJT8ko/QQI4uanEZVmmyh0nDxVk7Chcq0xbi/Ntrx6mbJJbthNRTRF38IrnDl5ElVXp0MdgMGDmzJno3bs32rdvLz4/a9Ys9OrVC6NGjSrz3LfeegsDBgyAWq3GL7/8gmnTpiEzMxPTp08HACQmJsLDw8PsHA8PD6SnpyMnJwcqlarENVesWIElS5ZU9uUQERGZ0esNSE3KLuq7c8cY7qT9nQOU8Tuug4tdyR2zPNVQKGW1O3kqlU7PRs7VSV6YnrHSh4hqisK7cAcvVvoQVVqlQ5+wsDBcvnwZR44cEZ/77rvv8Ouvv+L8+fMPPXfRokXi37t06YKsrCysWrVKDH0q49VXX8Xs2bPFj9PT0+Hr61vp6xERkW0QDALS7+cW2wrd+GdqUjYM+tJ/mbV3UKCRj6Yo4PF2gKuXGnZqNlWuy9jIuXpJC99Hhj5EVFPESp8EVvoQVValQp/w8HD88MMP+O2339CkSRPx+V9//RU3b940a8oMAE888QT69OmDqKioUq/36KOPYunSpcjLy4OdnR08PT2RlJRkNiYpKQlarbbUKh8AsLOzg52dXWVeDhER2QBBEJCdli/ulGUKeJITsqDLL33HLIWdzKzfjql6R+WoYFPlekjPRs7VSi5l6ENENUtR2B+WoQ9R5VUo9BEEAS+//DJ2796NqKgoBAQEmB1fsGABJk+ebPZchw4dsHbtWowcObLM60ZHR8PFxUUMbYKCgvDjjz+ajdm3bx+CgoIqMl0iIrJRuZkFSE7IxP075lui52XrSh0vk0vh4qU22xLd1VsDR1d7hjsNiJ6NnKuVjKEPEdUwuZex0seQlgZ9ZhZkDppyziCiB1Uo9AkLC8OOHTvw7bffwtHREYmJiQAAJycnqFQqeHp6ltq8uWnTpmJA9P333yMpKQk9e/aEvb099u3bh+XLl2Pu3Lni+KlTp2LDhg145ZVX8Pzzz+PXX3/FF198gT179lTltRIRUQOTn6tDSkK2GOqYlmhlp+WXOl4iAZw91IWhTtGW6E5uKkjZ3bfBYyPn6mXKznQMfYiohsgcNJA6OcGQlgZdQjxkLVtae0pE9U6FQp9NmzYBAIKDg82ej4iIQGhoqEXXUCgU2LhxI2bNmgVBENCiRQu89957ePHFF8UxAQEB2LNnD2bNmoX169ejSZMm2LJlC7drJyKyUfoCA1KSsov67hQGPOl/55Z5jmMj+6JlWd4aNPLRwNlDDbmCTZVtlb6wR5OU1VvVwlQxZeDuXURUgxReXshLS0NBQgLsGPoQVViFl3dV1IPnDB06FEOHDi33vODg4HIbQhMRUcNiMAhIv5dT1HfnjjHcSb2bA6GMagK1Vlm0LMvHWLnj6qWB0r7SexVQA2Wq9OHyruph2rJdV0bDcyKi6qDw8kLeH39wBy+iSuJPxEREVOsEQUBmSp64Dbqp705KYjb0BaU3VVaq5OJyrOLboqsclLU8e6qv2Mi5erHSh4hqg7iDVzybORNVBkMfIiKqMYIgIDs9Xwx2xOVZCVkoyNWXeo5cIYWL14M7ZmmgcbZjU2WqElPoY2pATFUjLXwf2dOHiGqSwps7eBFVBUMfIiKqFrlZBebBTuEjN6ug1PFSqQTOnmpxOVYjH2PvHW1jlfjLJFF1KmrkzK+v6mDast3A0IeIapC4bTuXdxFVCkMfIiKqkNJ2zEqOz0JWGTtmQQI4uanMtkJ39dbA2V0NmZzrbKh2GAwCTKuQZKwYqxZSbtlORLVAXN6VwNCHqDIY+hARUal0BXqkJGaXWJqVcb/sHbMcXO3EcMe0PMvFUw25kjtmkXXpi/WdYaVP9ZBzeRcR1QK5lzH00SXdhaDTQSLnr7BEFcH/YoiIbJxeb0Da3RyxmbIp5Em7m42y+rOadswSd80y7Zil4v9WqG4qXo3C0Kd6mCqm2MiZiGqS3K0xoFAABQXQ3b0rVv4QkWX40zkRkY0QDALS75vCnaLqnZTEbBjK2HLZTi03D3YKH9wxi+obAyt9qp2MlT5EVAskUikUnp4ouH0bBQkJDH2IKoihDxFRAyMIArJS84zBzp0sJCcUVu8kZEGXX/p26HI7mbGZcvHqHR8N1Fold8yiBkHHSp9qJ2MjZyKqJQovLxTcvo2MX36B7u7dh46VNWoEdY8e/PmFqBBDHyKieiwnI7+wasfYbyelsIonP0dX6niZXAoXr2I7ZhVW8Di62kPCX4SpASseTLCRc/VgpQ8R1RaFjw8AIHnrNmDrtnLHN/3kY2h69arpaRHVCwx9iIjqgbzsArFa536xHbNyMkrfDl0ilcDZXQVXbwc08tGIIY+TmwpSGXfMItvDnj7Vj5U+RFRbXJ99Brr7f0PIzXvouLybN6G/fx95f8Yy9CEqxNCHiKgOKcjTIyUxC/fvFAY7CcbeO5kpZfyQIwG0jVVFS7N8jNU7zu5qyBQMd4hMTKGPVAKW/FcTVvoQUW2xb9sWTT/6qNxxCYsXI3Xn59AnJ9fCrIjqB4Y+RERWoC8wIPVutnG3rDtF1Tvp93OBMn5/cnCxK2yk7CD23nHx1EBhx+3Qicpj2rKdVT7Vx7RMTs/du4iojpC7ugIAdCkMfYhMGPoQEdUgg96AtHs5RUuzCit4Uu/mQCjjX8dVjooHwh0HuHqpYadW1PLsiRoOnd5U6cPQp7rIZIWhj770BvFERLVN5uwCANCnpFp3IkR1CEMfIqJqIBgEZCTnFm6HXrRbVkpCNvS60n8hUqrkYsWOqxjuGHfMIqLqZdqyXc5Kn2pTVOlj5YkQERWSFVb6cHkXURGGPkREFSAIArLT8s3CnfvxWUhJyEJBnr7Uc+QKqVmwYwp6NM527C1CVEvEnj4MfaqNaamc3sBKHyKqG+Supkofhj5EJgx9iIjKkJtZUFS1UyzkycsufTt0qUwCF8+iyh3T0ixtI26HTmRtptCHPX2qT1HoY+WJEBEVMlX66JJTrDwTorqDoQ8R2bz8HJ24S1bxkCc7Pb/U8RIJ4OSuLrY0ywGu3ho4uasg43boRHWSnsu7qp24vIuVPkRUR8hcCit9UlMhGAyQSPlzGRFDHyKyGbp8PVISs5Ecn1m4W5Yx5MlMLmM7dADaxvZw9SoKdhr5aODsoYZcwR2ziOqToi3bGfpUF7GRMzMfIqojTKEP9HoY0tMhc3a26nyI6gKGPkTU4Oj1BqQmZYsVO6ZwJ/1eDsraWVjjpISrjzHYcfXSoJG3A1y81FDa89skUUNgCn1Y6VN9WOlDRHWNVKmE1MEBhsxM6JJTGPoQgaEPEdVjBoOA9Hs5hUuziqp3UpOyYShjOxl7jaKo306xkMdew+3QiRoyNnKufmJPn7LSdCIiK5C5usKQmVnYzDnA2tMhsjqGPkRU5wmCgMyUPNy/kyn23jFtia4vKP1fmBX2MmOwY1qa5WOs3lE5KrhjFpENMm3ZzkbO1YeNnImoLpK7uKAgLg46bttOBIChDxHVIYIgICejcMesO8bqneQE45boBbmlb4cuU0gLgx1N0dIsHwc4uHA7dCIqotMz9Klucm7ZTkR1kNjMOYU7eBEBDH2IyEpyswqKqnbuFC3Nys0qKHW8VCqBs6fabCt0Vy8NtG4qLtcgonKZliDJGAZXGykrfYioDjJt267ntu1EABj6EFENy8/VISUh21i9UyzkyUorfTt0SAAnNxUaFe6WZXo4u6shk3PbTSKqHFMxCit9qg8rfYioLpK7mip9uLyLCGDoQ0TVRFegR2pSNu7fMfXcMYY86X/nlnmOg6udGO6YqnecPdVQKLkdOhFVL11hMMHQp/pIJWzkTER1j8zFWOmjY6UPEQCGPkRUQQa9Aal3c4qCnXhjz520u9llboeu1irFih2xgsdLA6WK34KIqHawkXP1K6r0YehDRHWH2NOHjZyJADD0IaIyCAYB6fdzzbZCT47PQkpSFgy60n/At1PLzYOdwofKQVnLsyciMmdq5CxlT59qI2XoQ0R1kMyVjZyJimPoQ2TjBEFAVmp+sXAnU9wOXZdfep8GuZ3MuEvWA9U7aicld8wiojrJVOkjZ6VPtTG9lzqGPkRUh8gLGznrGPoQAWDoQ2RTcjLyi1XtFC3Nys/RlTpeJpfCxUtdtBV6Ybjj6GoPCX9xIqJ6xLTDFHf7qz6mpXIGhj5EVIcU7d6VDEEQ+A+SZPMY+hA1QHk5OjHYKR7y5GSUvh26RCqBs7sKrt4OaORjDHhcvTVwclNBKuOOWURU/4mNnPnDf7WRsdKHiOogeWFPHyEvD0J2NiQajZVnRGRdDH2I6rGCfD1SCrdBL740KzMlr/QTJIC2sapoaZaPsXrH2V0NmaJmwp3s9DQIBgOkcjlkhQ+pTM5/dSGiWiUu75Lxe091ESt9uHsXEdUhErUaEqUSQn4+dCmpUDL0IRvH0IeoHtDrDMbt0E39dgpDnvS/c4AyftZ2cLErbKTsYAx5fDRw8dRAYVez26ELBgMSb17HzbMnceP0Cdz/X1yp46QymTEIkslLBEIyubz0Yw88J33gHNNzZh+bHVNAKpcZP5YV+7tcUXieDDK5ovC8Yn8v/JhBFVH9JS7v4n/H1cb0XpqaZBMR1QUSiQQyV1foEhOhT0kGmvhYe0pEVsXQh6gOMRgEpN/LEcOd+3eMDZXTkrLL7JmgclSI4U4jMeRRw06tqLV5F+TnIe7SBdw8exJ/nj2FrNTyG+cZ9HoY9HroUEZVUh1UFEjJxKCoRLAkK3ZMJoO0MDgqEWjJix17MMiqaBBWWiAmY1BFVJy+cHkXGzlXHzkrfYiojpK5uhhDH27bTsTQh8gaBIOAjORccZcsU8iTkpANva70HbOUKjkaeWvg4q0pFu5ooNZaZzv07LRU/HnuNG6cOYm/Lp6HLr8ovFGq1Ajo3A3Nu/9/e3ceH0V9/w/8NTt7ZHPfFzl2cnLLHQiKqBjwqHj061FbtdZ6FA+0th6tdxWqtdpfD+33q6LVqnghKIoglyKXIAG5ISeQhASS7ObO7O7n98dmN5kkQBKS7CZ5PR+PPCQzs5PPMA6bvPL+vD9ZUMZNgikgAMLphMNhh9Nuh8Nuh8Ouwml3wGG3w2lX4XA4Wvaprm2O0+yzO1peb2/Zp7ac0w6no+W/7fa5zqd69nnG4Wh3vjbnaM/pcO0bQDmVp8JJdldWuaud5E6qn/SGltBK7wmk3J+fep/h7IKwdqGVpNMxqKI+wUbOvU/Hnj5E5KP0YeFoAmCv5ApeRAx9iPqQEAL1tmZUHmsJdkrrPNOz1CZHp6/RG3QtlTstwU5LyBMQavLqD8NCCFSWHEXeti3I27YFJYf2A21+uxsUGYXUiVlInZSFxJGjIeu1lUaSLEMny4DR1N9D7xEhREs1UpsQqU0gpNnW2T5N+NQu7GobaNkdp97XzSDM6egYVLnH03kLbx8kSV2rcJLbhUZy59VPbbe3D65aA60255ZPHYR1Og1QL0On69spk9Q7HC3/XrGRc+9xV/o4GPoQkY+RW5o5s9KHiKEPUa9prFVRWVrrmpJV0hryNNV1vhy6TpYQFhvgCXjc1TvBEb6zHLrT4UDJgX04vH0L8rdvQVVpiWZ/TEqaJ+iJSlYGVYWG1CZ8MAyMnKolqLJ7Kqgc7aqcnB0qnhxwODqpfuok3DploNUm2OpJEOZ0ONpfBByqCoc6YGIqSJKuNWTSn6LCqSfVT+2CrW4HYacIu2RZhqQbeqvyOVpKfWQ2cu41MkMfIvJRcnhL6NOFlgNEgx1DH6Juam60e6ZleSp4SupQb2vu9HhJAkKi/VtCndbqnZBoM2QfXA69ubEBhTt/QN62LcjfsQ2NNTbPPlmvR+Loc1xBz8QpCIqI9OJIqT1XUGWArDeg/zo6nR3XtL9OKqq6Vf3knprXfqpf59MAO0z10wRcLa9xtB9H6+uEUzsFUwgn7GozoHb+b4AvknS6dk3L3dP25JbwqG21U/vKqDNM9Wu/T9+xQXrnQdipQqveWfHP3WuYlT69h6EPEfkqfXg4AMDOSh8ihj5Ep2JvdqCqrB6VJbWu5dBbQp6aysZTviYowq+13068a8Ws0Bh/6A2+Pf2jpvIE8rdvRd62LSjevVPTz8YvMAgp4ychdfJUWMaOh9Hs78WR0mAj6XTQ63SAYaDEVIDT6fBMpztt9dMZp/p18jpHm7Crpz2v2uxz2h2w21XNVEzAFbbZm5s0vbh83dmu+Fd7sgEXnKhBxK5grFO3aV532mmAXPHvlNwBGhs5E5GvkcNcoY+DPX2IGPr4ss//udPbQxiShFPAWtEAW0VD+5+TPAJCjAgf5mqk7JqaFYiwOH8Y/QbGIyWEQEVRAfK2b0Hetq04nn9Isz80Jg6pk7KQNmkq4jNHuHrxEBEAQKeToTPKALzTRL0nnE6HtpKpfcVTZ43OO6t2OsWUvc6rpjoPtroUhHUyva83VvwbDQA1wPb8nv9ddke3V/zravVTH6z4J+sN3W6kLrORMxH5KM/0Llb6EDH08WVFP5709hCGPL8AQ2u/nTYhj1/AwKlKcHPYVRzdu8cV9GzfAltFeetOSUJceiZSJ7qCnvBhCYP+N9REQ4knqBogOZUQotdX/NtwoAzfHjiOsfGBuCA9vNOwiyv+db7iX/tpe+6KJ2ujE5eX1SHIZsRnL2/QHNdrK/6139f+v2ykTkSd0Lc0crazpw8RQx9fduFNw709hCErMNzPsxz6QA4/GutqUZC7HXnbtqAwdzua6us8+/RGE5LHjkPqpCykjJ+MgNAwL46UiKiVJEm9vuLfBtMhbCs/iPQxSTjv6jG9cs62ur3i3+mm+g2gFf8UAGgADm46dKZD+4aXVvzz9L3qZMW/9sEVV/wj6n9yOKd3Ebkx9PFhI7LjvT0EGoCs5WXIa+nPc3Tfbs3qSP4hoUiZMAVpk7OQNPocGEx+XhwpEVH/cS/Zru+j1REHy4p/7qCoKyv+7T1ahf9ddwjxwQbcfb5y9iv+dSEI44p/pwmtuOIfkYd7yXZnTQ1EczMk4wApdSXqAwx9iAY44XTieP5hHN7mmrZ1orhQsz8iIQmpE6cgddJUxKVl8Bs3IhqSnC19Z+Q+Cn0GorNd8e9k3gns2y7DHhWI8XPO7/XxdaavVvxrH3ZxxT+trqz41zptr+OKf+7XDaQV/2hgk0NCAJ0OcDphr6qGISba20Mi8hqGPkQDkL25GcV7diLv+y3I+2Er6qpam9RJkg7DRoxE2qSpSJk4BWGxrBgjInI3G9bxB8Fe4169y9GPq3dxxT+u+NdVnhX/zhQWta+aat8ovZPXdXXFv/b9q9qGXR3POfhX/OtPkk4HOTQUjspKOKoqGfrQkMbQh2iAqLdZUbBjGw5/vxlFu3ZAbWpdOt7gZ4ZyzgSkTp4KZdxEmIOCvThSIiLf415WXC/zh6re4v67dHD1rtMaqCv+aab9ta94Gkgr/jUNpKCqn1b8624Q1ukUwe6v+Nff5PCwltCHfX1oaGPoQ+TDKkuOIW/bZuRt34KSA/shRGuJeGBEpGu1rYlTkDBqLPQD6LeeRET9zcFKn17n/rtk6DP4uIMq/QDpg9IXK/51ZaofV/zr3op/p57qp28Nsk41DbAbQZgpIABB4ZHQh4WjGXmwc9l2GuIY+hD5EKfTgZKD+5G3bQvytm9FVclRzf5oSypSJ01B6sQsRCupPv3bFSIiX+IOJvqqkfNQpG/pEcfQh7ytL1b862sDacU/T3jWCyv+9ZeoJAtijECYycAVvGjIY+hD5GVqYyMKd/2AvG1bkf/DVjTU2Dz7dLIeiaPGIHVSFlInTkFwJOcjExH1hKfSh6FPr3GvC8DQh6j7huKKf52FVn2x4l9jbQ0qigtRAQDDk7Br9WcYYQIysqYjMsnCX5rSkMPQh8gLaqsqkb99K/K2b0HRj7maueimgACkjJ+M1ElZsJwzASb/AC+OlIhocHA3G5b5zX6vca+ExtCHaGg42xX/+ktDbQ3ytm3B7vffQenJClgb6rD54/ex+eP3ERYXj/Ss6cjIms6qeRoyGPoQ9QMhBE4cKWqZtrUFZYcPavaHRMcgddJUpE7MwrDhIyHr+WgSEfUmh4ONnHube6pcf67eRUR0JubAIIyeOQvxR8pwdMEC2M6dipMZCgpyt6OqtARbP/0QWz/9EMFRMciY6gqAYtMyGADRoMWfLIn6iMNux7H9ezxBj7X8uGZ/XFqmZ9pWRGIy32iIiPqQO5hgI+fe42nk7GDoQ0S+Rw4Pg8HpRGKDinMf/COaG+qRv2MbDm3ZiPwd38NWcRzbPvsE2z77BIERkciYko30qdMxLGMEJPf8VaJBgKEPUS9qqq9DQe525G3bgoId29BUX+fZpzcYkTTmHKROykLKhCkIDAv34kiJiIYW9xQkmd/H9xpPI2dW+hCRD9KHu77Xtle5Vu8ymv0xPHsGhmfPgNrUiMLcH3Bwy3fI274VtSdP4Icvl+GHL5chICwcaZOnISNrOhJGjHI1CCcawBj6+LAXr7vc20Ogs2QODkHKhJb+PGPGw+Dn5+0hERENSa2hD1Of3uL+q7Szpw8R+SA5LAwAOl29y2DyQ3pWNtKzsmFvbkbhrh04tOU75G3bgrqqSuxcuRw7Vy6HOTgE6ZOnIX3qdCSOHMMWDDQgdev/2gULFuCTTz7B/v37YTabkZ2djT//+c/IzMzscKwQApdeeilWrFiBJUuW4MorrwQA7Ny5EwsXLsSGDRtw4sQJWCwW3Hnnnbjvvvs8r123bh0uuOCCDucsLS1FbGxsNy+RqH+Fxye0TNvKQlxGJnQ6/naAiMjbWhs5e3kgg4i70sfJ0IeIfJDcUlXvqK6GcDpPOWVLbzQibVIW0iZlwWFXUfzjThzc8h0Of78ZDTYrdq1egV2rV8AvMAipk7KQMXU6kseMg6z35XbWRK26FfqsX78e8+bNw+TJk2G32/Hoo48iJycHe/fuRUCAdoWhl19+udMeJdu3b0d0dDTeeecdJCYmYuPGjbj99tshyzLuvvtuzbEHDhxAcHCw5/Po6KG1XPWd/37b20OgbtLJMsxBwWc+kIiI+pW774zMJdt7jWfJdk7vIiIfpA8Ldf3B6YTDaoW+pfLndGS9Acr4SVDGT8Ks2+bh6N7dOLhlAw5t3YQGmxV71n2NPeu+hsk/AKkTpyA9azos50yA3mjs24shOgvdCn1WrFih+fzNN99EdHQ0tm/fjhkzZni25+bm4sUXX8S2bdsQFxenec2tt96q+TwlJQWbNm3CJ5980iH0iY6ORmhoaHeGOKgEhJ75HyYiIiI6M0+lD6d39Rp3pY8QrmofHQM1IvIhktEIXVAQnDU1cFRVdSn0aUvW65E8dhySx47DRb+6C8f278XBzd/h0NaNqKuqxN5v12Lvt2th8DMjZcJkZEydDmXcRBhMbOdAvuWsJiVarVYAQHh4a0Pa+vp6/OxnP8M///nPLk/FslqtmnO4jRs3Dk1NTRg9ejSefPJJTJ8+/WyGS0REREOUk42ce53cpqLbIQR0YOhDRL5FDgtzhT6VlUBKSo/Po9PJSBw5Bokjx+DCW25HycH9OLjlOxzashE1JytwYOM3OLDxG+hNJijjJiIjazpSJkyG0ezfi1dD1DM9Dn2cTifmz5+P6dOnY/To0Z7t999/P7KzszF37twunWfjxo1YvHgxli9f7tkWFxeHV199FZMmTUJTUxNee+01zJw5E1u2bMGECRM6PU9TUxOampo8n9tsth5eGREREQ02djZy7nVymwZJDqeAgS3siMjH6MPCoBYXw17VsZlzT0k6HYYNH4lhw0di5k23oSzvoKsCaMt3sJYfx6EtG3Foy0bIBgMs50xERlY2UiZOgV9AYK+Ngag7ehz6zJs3D7t378aGDRs825YtW4Y1a9Zgx44dXTrH7t27MXfuXDzxxBPIycnxbM/MzNQ0h87OzkZeXh5eeuklvP12531uFixYgKeeeqqHV0NERESDmVOw0qe3aSp92MyZiHyQ3DKbpLMVvHqDJEmIS8tEXFomZtz4S5QX5OHQ1o04uHkDqkpLkLdtM/K2bYZOdk0Vy8iajtTJU2EODOqT8RB1pkehz913343PP/8c33zzDRISEjzb16xZg7y8vA59eK655hqcd955WLdunWfb3r17cdFFF+H222/HH//4xzN+zSlTpmgCpvYeeeQRPPDAA57PbTYbEhMTu35RRERENGi5QwldJ4tMUM+0bYrNZduJyBfJ4S3LtldV9vnXkiQJMSlpiElJw/TrfoETR4o8FUAnjxajYMc2FOzYBt3//QOJo8YiI2s60iZPhX9IaJ+PjYa2boU+Qgjcc889WLJkCdatWwdFUTT7H374Ydx2222abWPGjMFLL72En/zkJ55te/bswYUXXoibb74Zzz77bJe+dm5uboem0G2ZTCaYTKZuXA0RERENFe5QQs/pXb2mbejDZduJyBfpWyp97JV9H/q0JUkSopIsiEqyYPq1N+Lk0SM4tOU7HNzyHSqKClC0aweKdu3A16/9CwkjR7sCoCnTEBjWsc8t0dnqVugzb948vPvuu1i6dCmCgoJQVlYGAAgJCYHZbEZsbGynzZuTkpI8AdHu3btx4YUXYvbs2XjggQc855BlGVFRUQBcy70rioJRo0ahsbERr732GtasWYOVK1ee1cUSERHR0MRGzr2v7WJdrPQhIl8kt6yG3FfTu7oqIiEREQnXY+o116Oq9BgOtvT9OZ5/CEf27MKRPbuwetGrGJY5oiUAykZwZJRXx0yDR7dCn1deeQUAMHPmTM32RYsW4ZZbbunSOT766CNUVFTgnXfewTvvvOPZnpycjMLCQgBAc3Mzfvvb3+LYsWPw9/fH2LFj8fXXX+OCCy7oznCJiIiIALQu2c7pXb1HkiTIOgkOp/D0TCIi8iWenj692Mj5bIXFDUPWlf+DrCv/p6Xxs6sCqPTQARzbvxfH9u/F2rf+D3HpmUjPmo6MrGyERHdtVWyizkhCDM53aZvNhpCQEFitVgQHB3t7OERERORFV/xjA3YdteKNWybhwuEx3h7OoJHxxy/RbHfiu4cvxLBQs7eHQ0SkUbt+PY7ccSdMI0cg5ZNPvD2c06o5eaKlCfR3OHZgL9Dmx/SYlDRPABQWN8yLoyRf0tXMo8erdxERERENFGzk3DfcK3ixpw8R+aK+Xr2rNwVFRGLCJVdgwiVXoLaqEoe3bsKhrd/hyJ7dOJ5/GMfzD2PDe28hKsmC9KnTkZF1LiISuHARnRlDHyIiIhr0HJ6ePgx9epP775M9fYjIF8lh7p4+lRBCQBogwX9gWDjGzb4M42ZfhnqbFYe/34SDm79D8e6dqCguREVxITZ+8F9EJCQhPSsbGVnTEZlkGTDXR/2LoQ8RERENegx9+ob779PB0IeIfJC+JfQRzc0Q9fWQAgK8PKLu8w8OwdiL5mDsRXPQUFuDvG1bcGjLdyjcuQMnjxbj5NFibP74fYTFxbdMAZuOaCWVARB5MPQhIiKiQc/dyFnmN8G9iqEPEfkyyd8fkskE0dQEe1UVjAMw9GnLHBiE0TNnYfTMWWisq0X+D9/j4ObvULhzO6pKS7D10w+x9dMPERwVg4yprgAoNi2DAdAQx9CHiIiIBj1W+vQNhj5E5MskSYIcHg57aSkq/t//gz48wttD6lURAKbBgEkjJuGYrQrF1SdwzFYJW8VxbPvsE2z77BP4G0yIDw5DQEoK9NHR3h6yT0mdlIXEkWO8PYw+x9CHiIiIBj2GPn3DXTnF0IeIfJUhLg720lLYln3m7aH0qWAAowGMkCRUBPujNCQA5cEBqEcTDp8sA06WeXuIPicwPIKhDxEREdFg4GTo0yc8lT6CoQ8R+abYJ56A7YsvAKfD20PpN9EARgFwOB0osVbhRK0VBouFlT7txKame3sI/YKhDxEREQ16doY+fYLTu4jI1/llZsAvM8Pbw/CaOG8PgLxO5+0BEBEREfU1p2Do0xf0DH2IiIh8GkMfIiIiGvQ8PX24gkmv0jH0ISIi8mkMfYiIiGjQ4/SuvsFKHyIiIt/G0IeIiIgGPTZy7hs6iY2ciYiIfBlDHyIiIhr03JU+Ok7v6lV62V3p4/TySIiIiKgzDH2IiIho0HM3cnaHFNQ7PJU+zHyIiIh8EkMfIiIiGvTYyLlvtPb0YepDRETkixj6EBER0aAmhIC7z7COPX16VevqXV4eCBEREXWKoQ8RERENam1XltIz9OlV7r9POyt9iIiIfBJDHyIiIhrU2q4sxUqf3uVeDc3J1buIiIh8EkMfIiIiGtTaVvqwp0/vcjdytjsY+hAREfkihj5EREQ0qGlCH1b69Co9K32IiIh8mt7bAyCiIUIIoDQX9h8/Qv6RDYgMiEVYRCakqEwgMt31YQ7z9iiJaBBq226GoU/v0nl6+jD0ISIi8kUMfYio7wgBlP0IdfdH2HrwU6wSNVjtb0a1QQaaKxFy9EcoBXYoqur6kPyhBCdhWEQm9FHDgcgMICINCE0GZP5zRUQ907bJMKd39S5PpQ9DHyIiIp/En6KIqHcJAZTvhfrjR9hycAlWOq1Y42+GNVAGEAgAMOsMaHCqsMoycmUZuX6mNic4Dn1VGZLLv4aitgRCdgHFPwaWsHQERraEQZHprkDIHOqNqySiAcTdyFmS2Mi5t7HSh4iIyLcx9CGi3lG+H+ruD7H5wBKsdFRhjb8ZtoDWoCdcH4CLLbNxccqlmBgzEapTRbGtGAXWAtdH1UEUVB1EYW0JGmFHntGIPKOxzRdoApp2I7ooF8phOyzu6iBdIFJCLIiOyIQuKhOIaJkqFpoE6GSv/FUQkW9xF/qwyqf3uSt9HAx9iIiIfBJDHyLquROHoO7+CJv2f4yV9pNY4++PGn8d3EFPhD4AsyyzMTv1ckyIngC5TQij1+mRGZ6JzPBMzSmdwomyurLWMMiaj4KT+1FgK8QJtQblej3K9XpsMfu1eVUJzCePwlL2VWsY5AAU/zgkh6XDL2p4a9+giHTAL7gf/nKIyFe4p3exn0/vcwdpbORMRETkmxj6EFH3nMzzBD1fqRVY6++PGnNr0BOpD8QsSw5yOgl6ukIn6RAfGI/4wHhMHzZds8/WbEOhtbBNddAhFFQdwpH642jQAftMRuwzta0OaoDUuBPxBT9AOai29g7SB0MJURAekQkpMqNlulgaEJIE6LioIdFg46n0YejT62RO7yIiIvJpDH2I6MwqC9C852Ns3PcRVjUfdwU9fjrAzxX0RHmCnp9gfPT4bgc9XRVsDMbYqLEYGzVWs111qjhacxQF1gIU2gpRUJ2PgsoDyLcVocbRgGMGPY4Z9NgAc5tXHUVwRRGUki9awyCHBCVwGBLCMqBvu6pYRBpgCuqTayKivuep9OH0rl4ns5EzERGRT2PoQ0Sdqy5G048fYeOBj7CyqQzr/M2oNekAkyvoiXYHPWlXYHz0eOgk71XIGHQGKCEKlBBFs10IgcrGSldVkK1tdVAeShorYJNl7JRl7NQ0kq6DvuEHJOVthbLfXR1kh2IIgSU0BUGRw1v7BkWmA8EJrA4i8nHuqUeyzNCnt7HSh4iIyLcx9CGiVtajaNr9Mb7b/yFWNpZgnb8ZdQYdYAgA4Ap6LrbMRk7aFRgXPc6rQU9XSJKECHMEIswRmBQ7SbOv0d6IIltRaxhUnY/CyoMorD2CBqeKfKMB+UZDuzMWI6osH8oRdyNpOxSnBCUwEbHhGdBFZbQuMx+R5gnIiMi7HGzk3GdY6UNEROTbGPoQDXW2UjTu/hjf7f8AKxuOYr2/GXV6HRDoCnpiWoKe2elXYmzUWJ8PerrKT+93ykbSx+uOt6sOOoiC6nxUNFtRodejQq/HVk0j6Rr41X0PS/UmKHvbVAcZw5Acmgq/yMzWvkGRGUDwMNfa0UTUL9zTu7hce+9jpQ8REZFvY+hDNBTVHEfjnk+wYd9irKwvxnp/M+rl1qAn1l3RM8iCnq7QSTrEBcYhLjAO2cOyNftqmmtQaC109Q2yFqCgOg8FVYdQVFeCRh2w32TEfk0jaUASBYgvPQxL8aetYZBTByUoCRERGZCiMl1VQe4KIaN/f14u0ZDgbuSsZ+jT69zVUw6u3kVEROSTGPoQDRV1J9Cw+6PWoMfshwZda9ATpw/ExZYc5GRcjTGRY4ZU0NNVQcYgjIkagzFRYzTb7U47jtUea7PMvKt3UL41HzZ7vaeR9HeaRtI2BNVshVL5XWsjadUOxRSJhLA0GCIzWvsGRWYAQXGsDiLqIXcgoeMz1OvcfZIcDoY+REREvoihD9FgVl+Jhj0f49u972NlXSG+cQc9Aa5qknhP0HMNxkSOgcQfiHpEr9MjOTgZycHJmJk407NdCIGqpiptGFSdj4LqQzhWX44aWYddsgm7NI2kAb3zMBKP7YelsE0YJPRQgpMR7J4q5qkOSgUMZhDRqTlaSn30bOTc61jpQ0RE5NsY+hANNg1VqN+7BN/ueQ8ra/PxbbugZ5g+EBcn5yAn86cYHTmaQU8fkiQJ4X7hCPcLx8SYiZp9TY4mVyNpTXXQYRTaCtHgbEaB0YACowFrNa+qRkT1RigV61vDINUOxRyFuNA06KIyW/sGRaQDQbGsDiICGzn3JfeUOQd7+hAREfkkhj5Eg0GjFfV7PsU3e9/Fypo8fGs2obFd0JOTnIPZw6/FyIiRDHp8gEk2ISMsAxlhGZrtTuFEeX058q35KLS29A6y5qOg+jDKGytxUi/jpF7GNk0jacDPcRDJR/ZCyXeHQSoUGJEcYoE5MlO7zHx4KmDQvp5oMHMHEmzk3Pt0DH2IiIh8GkMfooGq0Yb6fcvwzZ7/YmXNYXzrZ2wJelxTfRL0gchJvhg5I67DyHAGPQOFTtIhNiAWsQGxyI7XNpKuba5Fka0I+dZ8FFgLUGgtQEH1YRTVHEWjzo4DJiMOtGskDVQivvJbKMfXtKsOikZEeEsj6bbVQYHRrA6iQccdSLCRc+/zTO9i6ENEROSTGPoQDSRNtajbtxTr9/wXK22HsMHPiCadDvB3VW0k6gORk3QxckZejxHhIxj0DDKBxkCMihyFUZGjNNvtTjtKaktap4nZXCuL5VfnwarWosSgR0mHRtJAkLofStGPsBxuUx0k+SExVIEhss2qYpHpQHgKoNf2HiIaKNjIue94Gjkz9CEiIvJJDH2IfF1zHer2f4Z1u9/BSutBfOdn0AQ9SfpA5CTNQs7In2F4+HAGPUOQXqdHUnASkoKTcH7i+Zp9VY3tGkm3VAcdqys9ZSNpWVQg8UQpLKWrWsMguwOKfyxCIjJbp4lFtKwsFhDJ6iDyae5GzjIrfXodK32IiIh8G0MfIl+kNqDWE/Tsx3cmI5p1EuDv+uE8uU3Qk8mgh04jzC8MYX5hmBAzQbO9ydGEYluxa5qYraV3UHUeCqwFqHc0otBoQKHRgHWaVzkR3rQbSsEOKAfbVAfp/BAXlgY5ot0y82EKoG8/3Yyo/3kaOTP06XXuv1Ou3kVEROSbGPoQ+Qq1ETUHlmPd7rexsnofNpoMrqDH7Ap6LPpA5CRdhJxRv0BGWAaDHjorJtmE9LB0pIela7YLIVBeX+6aIqapDsrD8YYKVMoyKs0ytrdrJG1yliG54iiUkq/aVAc5kRwQD3/3FDF3ZVBkBhAQ0Z+XS0OcuwqFoU/vc/+d2lnpQ0RE5JMY+hB5k70JtgNfYN3u/7QEPXqokgSYXdURitwS9Iz+BdIZ9FA/kCQJMQExiAmIwdS4qZp9dWpda1WQJwzKR5GtCE06Ow6ajDjYoZG0HXENu6DkbYeyvyUMUlUocgAiw9MgdagOsgCyod+ul4YGT+jDf0N7nbs5tpOhDxERkU9i6EPU3+zNsB1agbU/voWVVXuw0aSHXZIAP9cPuilyIHKSLkTO6JuRFpbOoId8RoAhAKMiRmFUhLaRtMPpcDWS1lQH5aOgOh9VzVaU6vUo1euxsf35nCVQyougHP2yNQxyCCQFJsDQoTooHfAP77+LpUHFPfWIlT69j0u2ExER+TaGPkT9wWGH9dCXWLvrLays2o1N7YKeVDkQOYkXIGfMLUgLz/DyYIm6R9bJSAxORGJwImYkzNDsq2qsQqGtEIXWthVCeThScxR1Oh12m0zYbWrfSLoJCXU7oFRthbK3TXWQPggh4enayqCI9JbqIL6d0ak5Ob2rz+gZ+hAREfk0fpdM1Ifqj/2ArzYtwMrK3dhslDVBT5ociJzEmcgZcytSw9PPcCaigcndSHp89HjN9mZHM47UHOm4spg1H3X2ehQZDCgytG8kDYQ7jsBSlg+leHmb6iAgPjgRcvtl5iPTAXNYv10r+S53vxkdQ59ep5PYyJmIiMiXMfQh6gP1pbl4f+3DeKuxGJWyDJhcj1q6HIichJnIOedWpIQx6KGhyygbkRqaitTQVM12IQQqGio6DYPK6o+7GknLMn7wa3c+ZyOSa7ZBObkJyp7W6iCLIQT+ERlAZFprZVBkOhCazOqgIcRd6aNn6NPr9DIrfYiIiHwZv+Ml6kW1pbvw/rqH8VZDIaplGZBlJEhGXJl4MXLOuQ1KeJq3h0jk0yRJQrR/NKL9o5EVl6XZV6/Wd2wkbS1Aka0QzVBxyGjEIWPHJeJj7IVQSg5BKfxMUx0UHWqB1HZFsch0V6WQObSfrpb6i7sKRcceab3OU+nD0IeIiMgnMfQh6gW24z/i3bWP4O36AthkHSDLSJaMuH3Ur3Dp+Nuh1/FRIzpb/gZ/jIwYiZERIzXbHU4HSupKUGAtcPUOsrWuLFbZVIXjej2O6/XYbG53PmcdFNv3ruqgH1vCINWOJGMYjJGdVQclATq5H6+YeoudlT59Rq/TAeCS7URERL6KP4kSnQXr8T3477qH8E59AWp0OkDWQYERt4++FXPG38Gwh6gfyDoZiUGJSAzq2Eja2mRtrQpqCYMKrQU4UnME9Tpgj8mEPe0aSeuEQII9D8rRA1DyP22tDnLqEBqW0rFvUEQ64Bfcn5dM3cRGzn1HdmU+XLKdiIjIR/EnUqIeqK7Yi/+sfQjv1uWjTqcDdDqkwYg7Rv8KF4+/AzKrAYh8QogpBOOix2Fc9DjNdtWhtjaSbrfUfK1ah2KDAcUGA9b7a8uDwhxWKNWboVRsgNLcWh0U7xcJuW0I5K4UCkkCWiohyHscbOTcZ2RW+hAREfk0hj5E3VBZsQ//WfsQ3qvLQ31L2JMOI+4cdStmTbwLOok/3BENBAbZgJTQFKSEpmi2CyFwouFEh+qgAmsBSutKUSXLqOqkkbRBCCSrh6AU74MlT4XSrCJFtcMiZASEpbRbZj7N9WdTUD9e8dDm4PSuPuOp9OHqXURERD6JoY8Pa25u8vYQqEVV1WG8/c2jWFybh0adBOh0GC4MuH3UrZg5wRX2CMEla4kGg3C/SIT7RWJizGTN9ga1HkU1RZ6+Qe7/FlkL0ORsxmGjEYc7aSQdba+CUrkRyvH1muqgaP8YSBFpEC1BkPu/CEkAGCD3KtXpBMBGzn3BU+nj4PsfERGRL2Lo48MmvjfJ20Og9nQSkhsliBPn4/ua2fh+vwR8vMLboyKifmdp+ZgJwAnJUA2dscL1YaqAzlju+q++FuV6Pcr1emwxa8uD/J1OWJoPQCnaA+Ww2hII2RGlSihxxiFPxCFfxCPPGY88EYcCEYd6+HUYCXWdzCyt18ktQRorfYiIiHwTQx+iLkpplIATM7CzZjYA/uRARG46CDUcDjUcjrrMdrvqoTOegM5U3iYQqoBsPIF6nQ57TSbs7aSR9DB7MxQ1D4q6H+c3q7hFtUNRVTQ4QpHnjEe+iEOeiPeEQqUIB8AqltPRScBkS7i3hzHouFtWsacPERGRb2Lo48M+v/hjbw+BWuh0BgQGDfP2MIhokFCdKkpqj6K4phBFNYUobvNRq9biiMGAIwYDvoG2kXSIwwFFrYCilkBRN+PCZlcYFC8ZIYWlwhmeBkd4OhzhaS1/TgUM/l66St9i0OsQaOK3Pb3NvWQ7V+8iIiLyTd367mfBggX45JNPsH//fpjNZmRnZ+PPf/4zMjMzOxwrhMCll16KFStWYMmSJbjyyis9+4qLi3HXXXdh7dq1CAwMxM0334wFCxZAr28dzrp16/DAAw9gz549SExMxB//+EfccsstPb7QgSg5PsPbQyAioj5hRHRQJsbFad8/hRA42XiyzWpiBZ7+Qcdqj8Eqy8iVZeT6aauD9EIgWa2AUlkK5fgaV9+gZjssqorA4ISOy8xHZgBBcQB73NBZklnpQ0RE5NO6FfqsX78e8+bNw+TJk2G32/Hoo48iJycHe/fuRUBAgObYl19+GVIn30w6HA5cdtlliI2NxcaNG1FaWoqbbroJBoMBzz33HACgoKAAl112Ge68807897//xerVq3HbbbchLi4Os2fPPovLJSIi8l2SJCHSHIlIcyQmx7ZrJG1vQLGtuNNAqNHRiDyjEXmdNpK2Q6nfA0teLpT9rjAoRVURI5shuVcS86wqlgFEpAIGc4fzEHXG3cjZwdCHiIjIJ0lC9LzzXkVFBaKjo7F+/XrMmDHDsz03NxeXX345tm3bhri4OE2lz5dffonLL78cJSUliImJAQC8+uqreOihh1BRUQGj0YiHHnoIy5cvx+7duz3nvP7661FdXY0VK7rWNNdmsyEkJARWqxXBwcE9vUQiIiKf5hROlNWVdQiDCqwFONFw4pSvMzudsLT0CnJVBrkaSSfb7TCFJAIRLWFQpDsMSgeCYlkdRBo/HrXiJ//YgNhgP2x+9CJvD4eIiGjI6GrmcVaT261WKwAgPLy1MWJ9fT1+9rOf4Z///CdiY2M7vGbTpk0YM2aMJ/ABgNmzZ+Ouu+7Cnj17MH78eGzatAmzZs3SvG727NmYP3/+KcfS1NSEpqbWJc5tNltPL4uIiGjA0Ek6xAfGIz4wHtOHTdfsszXbXEvLtwuEjtiK0aAD9pmM2GfSVgdJQiDebodSuwtK1XYoe11hkNKsIlwfAKltCOSeLhaeChi4sthQJOtcIaCDq3cRERH5pB6HPk6nE/Pnz8f06dMxevRoz/b7778f2dnZmDt3bqevKysr0wQ+ADyfl5WVnfYYm82GhoYGmM0dy84XLFiAp556qqeXQ0RENOgEG4MxNmosxkaN1WxXnSqO1hxFgbUAhbbWUCjfmo+a5hocM+hxzKDHhnaNpIMdDlcT6ZIiKEVfQFFdfYMSVAcMoUnavkHuSqHAaFYHDWLu0IeNnImIiHxTj0OfefPmYffu3diwYYNn27Jly7BmzRrs2LGjVwbXHY888ggeeOABz+c2mw2JiYn9Pg4iIiJfZ9AZoIQoUEIUzXYhBCobKzVTxNwfJbUlsMkydsoydnbSSDpRbYZi2wHLya1QdrumjVlUFSGGoI59gyLTgfAUQK89Dw087tCHjZyJiIh8U49Cn7vvvhuff/45vvnmGyQkJHi2r1mzBnl5eQgNDdUcf8011+C8887DunXrEBsbi61bt2r2Hz9+HAA808FiY2M929oeExwc3GmVDwCYTCaYTPzmkYiIqKckSUKEOQIR5ghMip2k2ddob0SRrag1DKp2VQkV2grQYG9EgdGAAqOhwznDHQ4ozUegHM2HpaC1h1C8Q0AOTe68OiggktVBAwQrfYiIiHxbt0IfIQTuueceLFmyBOvWrYOiaH9D+PDDD+O2227TbBszZgxeeukl/OQnPwEATJs2Dc8++yzKy8sRHR0NAFi1ahWCg4MxcuRIzzFffPGF5jyrVq3CtGnTund1RERE1Cv89H7IDM9EZrh2mXmncKK8vhz51nzXdDFroScYKq8vR6Uso9IsY7tZ2/PH6BRIsjdAsW6H5cRmKM0qUlqmiwWYgjv2DYrMAMIUQN9xhTLyHj0rfYiIiHxat0KfefPm4d1338XSpUsRFBTk6cETEhICs9mM2NjYTps3JyUleQKinJwcjBw5Er/4xS/w/PPPo6ysDH/84x8xb948T6XOnXfeiX/84x/4/e9/j1tvvRVr1qzBBx98gOXLl5/t9RIREVEv0kk6xAbEIjYgFtnx2Zp9dWqdpmeQOxAqshahGc04bDTi8KmWmVeLYDl6GErBMk8j6RgnoAuzdKwMikwH/CNYHeQFOjZyJiIi8mndCn1eeeUVAMDMmTM12xctWoRbbrmlS+eQZRmff/457rrrLkybNg0BAQG4+eab8fTTT3uOURQFy5cvx/3334+//e1vSEhIwGuvvYbZs2d3Z7hERETkRQGGAIyKGIVREaM02x1OB0rrSlvDoDbB0MnGkyjX61Gu12NLu+ogs9OJZLUOStX3UMo3epacT1btMPuFdlxmPjIDCLMAcsdpZ9Q73JU+Dlb6EBER+SRJiMH5q5murllPREREvqP9MvPuQKjYVgy7sJ/ydfEtU8MUtbVvkEW1I0pIkMKUU1QHhffjlQ1OFTVNmPzs1wCAggWXQmK1FRERUb/oaubR49W7iIiIiHrb6ZaZP1ZzTFMV5F5lzNpkRYlBjxKDHhvbnS/A6YSi2mCp3AKlbIMnDEpWVRj9Izr2DYpIb6kO4rdIXeGu9AEApwBkZj5EREQ+hd/REBERkc8z6AywhFhgCbFgZuJMzb6qxqoO08QKbYU4UnMEdTpgt8mE3e1W+NQJgWF2O5TmPFiK9kM5rEJpdlULhUOGFK50XGY+Mh0wh/XjVfs+XZvQx+EUntW8iIiIyDcw9CEiIqIBLcwvDGF+YZgQM0GzvdnRjCM1RzoEQgXWAtSqtThiMOCIwYBvYNa8LtjhgKJaoZzYCEvpes+UsQTVDoN/pLZvkLtSKDR5SFYH6duFPkRERORbht53J0RERDQkGGUjUkNTkRqaqtkuhMDJxpMdpokVWgtRUlsCmyxjpyxjp5+2OkgvBBJUO5TGg1AK9sBysLV/UAj0QERqu8qglkohc2g/XnX/alvZwxW8iIiIfA9DHyIiIhpSJElCpDkSkeZITI6drNnXaG9Eka0IBbY2y8y3VAo12BtQaDSg0GjA2nbnDHc4YFEroVRshFKyviUMsiPeboccEN2xb1BkOhCaBOjk/rvwPqBr07jZ4WDoQ0RE5GsY+hARERG18NP7ITM8E5nhmZrtQggcrz+uqQ5yTxk7Xn8clbKMSlnGD9pV5mEQAsmqCqXhACz5u6Hsd4VBFlVFoM7YSXVQywpjfgNj5VE9K32IiIh8GkMfIiIiojOQJAmxAbGIDYjFtPhpmn31an2HnkGFtkIU2YrQ5GjCYaMRh43GDueMttthUU9AKS+FcmyNJwyKtTugC4ztZJn5NCAk0aeqg9o2crY7nV4cCREREXWGoQ8RERHRWfA3+GNkxEiMjBip2e5wOlBaV9ppIHSi4QTK9XqU6/XYataWB/k5nbCodljq9kKp3gVln6tvULJqh1k2AeGp7aaLpbn+bArqz8v20Osk2J0CzHyIiIh8D0MfIiIioj4g62QkBCUgISgB5w47V7PP1mxDobWwQyBUXFOMRtix32TEflPH6qA4ux1KczksZSVQjnwNRVVhUe2IdjggBcW1qwxqCYaCEwCdrs+uU6eTAKdgpQ8REZEPYuhDRERE1M+CjcEYGzUWY6PGarbbnXYcqz3W2kS6TUPpqqYqlOr1KNXrsbHd+fydTlfz6No9sFTlQtnr6h2UZFdhks2t1UBtq4Mi0gBT4Flfi14noRlgpQ8REZEPYuhDRERE5CP0Oj2Sg5ORHJwMJGr3VTVWeSqD3KuKFdgKcLTmKOp1wB6TCXtM2mXmdUIg3m6HopZBKT0CS/FXUFQ7lGYV4U4npOBhHfsGRWYAQfFdrg6SW1bwYqUPERGR72HoQ0RERDQAhPmFIcwvDOOjx2u2qw4VR2qOeEKgtqFQjVqDowYDjhoM+BZmzeuCHQ5YVDsU2y4oJ7fDsscORVWRqNphMPi3qQ7KaF1hLCINMPprziPLrtDHydW7iIiIfA5DHyIiIqIBzCAbkBKagpTQFM12IQRONp7sdJn5ktoS2GQZu2QZu/y01UF6IZCg2mFRS6AcK4ZSuMI1dUy1I8TpdK0g1maZ+amwIRdRcDgY+hAREfkaSYjB+WsZm82GkJAQWK1WBAcHe3s4RERERD6j0d6IIluRppG0+88N9oZTvi7c4YClJQBSmlVPI+l4ux2SIQCye3qYpjooFTCYT3lOIiIi6r6uZh4MfYiIiIgIgKs66Hj98U6XmS+rKzvl6wxCILklAHJVBalQmu2wqCoCBYDQxI59gyLSgaBYoKUnEBEREXUdQx+GPkRERES9pl6tR6GtULOqWIG1AAcrCwBJPeXroux2KKq9tUKoJRSKtTugMwZpQyD3CmPhqYDBrx+vjoiIaGBh6MPQh4iIiKjPzXhhNY7YSvD4VZHQ+53QhEInGk6c8nV+TieSW0KgthVCyaod/gJAaJKnb5BmhbHAaFYHERHRkNfVzIONnImIiIiox/Q6GUINx8jQKchKidDsq2mu8YRAnmXmrQUoqilCI+w4YDLigMnY4ZyxdjsUtR5K5TZYjm/yNJKOdjggmYLbhEDprSuMhacAelOHcxEREQ1lDH2IiIiIqMfklqobRyfF40HGIIyJGoMxUWM02+1OO0pqSzo0kS6wFqCqqQplej3K9Hpsatf/2d/pdE0Tay6EUnwIlsOuMCjZrsIEHRCa3Hl1UEAkq4OIiGhIYuhDRERERD0m61pCH2fXOwbodXokBSchKTgJ5yeer9lX3VitbSTdUiV0pOYI6nXAXpMJe03aih5JCAyz22FRa6Gc3AKlbINryliziginE5JfSMe+QZEZQJgC6DtWGhEREQ0WDH2IiIiIqMd6EvqcTqhfKMb5jcO46HGa7apDxZGaI5om0oW2QhRUF6BGrcFRgwFHDQZsgLY8KMjhdPUNasyDUngAyiFX76BE1Q6DJANhlo6VQZHpgH8Eq4OIiGjAY+hDRERERD3W26HPqRhkA1JCU5ASmqLZLoTAycaTHaaJFVoLcaz2GGpkHXbJJuzy01YHyUIgUbXDolqhVGyGUvKtp6l0qNMJmMM6X2Y+XAFkQ59eKxERUW9h6ENEREREPdZfoc+pSJKESHMkIs2RmBw7WbOvydGEIluRJwRyVwkVWgtRb69HodGAQqMB69qdM8zhcDWPbjwMS/4+KAdcvYPi7XbodfqW6qAMIKIlDPJUB4X312UTERF1CUMfIiIiIuoxTyNnL4U+p2OSTcgIy0BGWIZmuxAC5fXlmhDI3T+orK4MVbKMKlnGD37a8+mFQLKqQlGroZR/B8ux9VCaVVhUFUFCuKaEte8bFJHuColkfttNRET9j+8+RERERNRjnkqfTlbv8lWSJCEmIAYxATGYGjdVs69erfdUB7Vdar7QVogmRxPyjEbkGTs2f460t1QH1R+AJW8PlP2u3kFxdgd0OoNrWpimOqglGDKH9ddlExHREMTQh4iIiIh6zNvTu3qbv8EfIyJGYETECM12p3CirK6sdVWxNj2EKhoqcEIv44RexvdmbXmQSQgkN6tQ1JNQyr6F5cgaT+8gfyEA/8iOfYMi013Lz7M6iIiIzhLfSYiIiIioxwZb6HMqOkmH+MB4xAfGY/qw6Zp9Nc01rdVBbcKgIlsRmpwqDpqMOGjqWB0Ua7fDoqpQavdBqdoFy15X76AYhwOSzgBEpLarDGqpFDKH9tNVExHRQMfQh4iIiIh6zB362Ad56HM6QcYgjI4cjdGRozXb7U47SmpLNKuKuUOhysZKlOn1KNPrsVm7yjz8nU5YVBUWtQJKWQmU4tVQVDuS7SpMAkBAdCfLzKe5qoN0cv9dOBER+TyGPkRERETUY/qW0Mc5hEOfU9Hr9EgKTkJScBJmJMzQ7KturG4Ng9o0lD5ScwT1OmCvyYS9Ju0y85IQiG/pHWSp2QOlcqerj5CqIsLhhCSbOqkOagmG/IL789KJiMhHMPQhIiIioh7TSQOvkbMvCPULxTi/cRgXPU6zXXWoOFJ7pMOqYgXWAtQ01+CYQY9jBj02QFseFOR0tqwkVgal5CiUolVQVBWJqh0GAAiM7bw6KCSR1UFERIMYQx8iIiIi6jG9PDR6+vQXg2xASkgKUkJSNNuFEKhsrOywqliBtQAldSWo0QG7/EzY5aetDpKFQILdDqVZhWL9EZYTP7RUB9kR6nQCej8gPLXdMvNprj+bgvrz0omIqA8w9CEiIiKiHvNU+jD06VOSJCHCHIEIcwQmxU7S7GtyNKHYVtyhkXSBtQD19noUGQwoMhiwrt05Qx1OKGozLGoplGPFsBR+BaVZxTB7S3VQUFzHyqDIDCA4AdDp+unKiYjobDD0ISIiIqIe0w+R1bt8mUk2IT0sHelh6ZrtQghUNFR0usx8aV0pqmUddsh+2KFdZR56IZCotqwsVr0TlortnuqgEKcT0Jtbq4HaVgdFpAGmwH68ciIiOhOGPkRERETUYzqGPj5LkiRE+0cj2j8aWXFZmn31aj2Ka4o1vYMKbYUotBWiwd6AAqMBBUYD1rY7Z7jD4QqD1GOwHCmEkv8FLKodw+x21w8WwcM6rw4Kimd1EBGRFzD0ISIiIqIe03PJ9gHJ3+CP4eHDMTx8uGa7UzhxvO64ZkUxdw+h4/XHUSnLqJRl/NBJdVCSaoeiNsFStQNK+fct4ZCKYKcADP5tqoMyWlcYi0gDjP79eOVEREMLQx8iIiIi6jGZS7YPKjpJh7jAOMQFxiE7Pluzr16t90wP8/zX6qoOanI0Id9oQL7R0OGc4Q5Hy8piR6EUF0DJWw5FtSPebocMuFYQ62yZ+eB4oKVnFBER9QxDHyIiIiLqMZmVPkOGv8EfIyNGYmTESM12p3CirK6sQxhUYC1AeUO5qzrILGO7dpV5GIRAsqpCURtgqfoBSvkWWJpdvYSChACMgUBEaktFUHqbQCgNMLQ7GRERdYqhDxERERH1mNxSieEUDH2GKp2kQ3xgPOID4zF92HTNvtrmWhTZijpMFyuyFqHZ2YzDRiMOG40dzhlpd0BRVViai6EU5cNy+DMoqoo4uwMyJFd1UGS7vkER6UBQLKuDiIjaYOhDRERERD2mY6UPnUagMRCjIkdhVOQozXaH04HSulJtZVBL76CKhgqc0Ms4oZfxvVnbPMjYUh1kUeuhnNwGS9kmpLSsNBYgBGAM0oZA7uqg8FTA0K4RERHREMDQh4iIiIh6TM+ePtQDsk5GQlACEoIScO6wczX7apprXNVB7ZaZL7IVodmp4pDRiENGIxCgPWe0vWVlsaZCWAoPQzmkwtJSHaSDBIQmdewbFJkBBEazOoiIBi2GPkRERETUY6z0od4WZAzC6MjRGB05WrPd4XSgpK6kQ2VQgbUAJxtPolwvo1wvY2u76iA/IZDUrEJRa2E5sRVK6XctK4vZ4S8EYApuEwKlt04bC08B9Kb+vHQiol7H0IeIiIiIesxd6eNg6EN9TNbJSAxKRGJQImYkzNDsszXbPAFQ2yljRTVFaHTacdBkxEFTx95B0XY7FNUOS2M+lMIDUA7ZoTSriHE4oJN0QGhyx2XmI9OBgChWBxHRgMDQh4iIiIh6zN3ImaEPeVOwMRhjo8ZibNRYzXa7046S2hJNGOT+c2VjJcr1epTr9djSvjrIKWBRVVhUG5SKLbCUbICiqkh2Vwf5hXTsGxSZAYQpgL5juERE5C0MfYiIiIiox2SdDgDg4Opd5IP0Oj2SgpOQFJyE83G+Zp+1ydpxmXlbAY7YjqBRZ8d+kxH7O6kOirXbXSuL1R+GYt0HywHXVLEYhwOSJANhlo59gyLTAf8IVgcRUb9j6ENEREREPSa7Mh84HAx9aGAJMYVgXPQ4jIsep9muOlUcqznWGga1CYWqmqpQptejTK/HJrP2fGZPdVA1lPKNUI59A0VVkaTaYRYCMIe1CYHarDAWrgCyof8unIiGFIY+RERERNRjrPShwcagM8ASYoElxIKZiTM1+6obq1unidkKPGHQkZojaNA5sM9kxL5OqoPiW5aVV+oPwZK3F8p+FRbVjmiHA5JO31Id1K5vUGQG4B/ePxdNRIMWQx8iIiIi6jF3pQ+XbKehINQvFOP8OqkOcqg4UnukQzPpAmsBbM02lBj0KDHosbHd+fydAha1GYpaBcvxDVCOrIVFtSPZboefEIA5XFsZ5K4OCrMAMn+UI6Iz478URERERNRj7kofLtlOQ5lBNiAlJAUpISma7UIIVDVVdVxZzFaIozVHUa9zYK/JhL0m7dLwkhCItztc1UF1+6FU74ZlnwpFVRHpcELSGVzTwtpXB0WksTqIiDQY+hARERFRj8ktfWk5vYuoI0mSEO4XjnC/cEyImaDZpzpUHKk5op0q1hIK1TTX4JhBj2MGPb6DtnlQoNPZ0jvoJJTSb2ApXg1FtSPJrsIkAPhHduwbFJnuWn6e1UFEQw6feiIiIiLqMbllfhcbORN1j0E2ICU0BSmhHauDKhsrO1QGFVgLcKz2GGp1wG6TCbvbVQfphEC83Q6LaodSuxdK1U5Y9tqhNKuIcLZUB0WkduwbFJEGmEP78cqJqD8x9CEiIiKiHpNblqBmpQ9R75AkCRHmCESYIzApdpJmX7OjGcW24g5hUIG1ALVqLY4aDDhqMGBDu+qgIKcTSrMKi1oOpbSkpTpIRaJqhxEAAqI7WWY+zVUdpJP77+KJqNcx9CEiIiKiHtPrWkIf9vQh6nNG2Yi0sDSkhaVptgshcLLxpCcAarvM/LHaY6jR6bDLz4Rdfh2rgxLc1UE1e2CpzIXS7FppLNzphCSbgPCU1kDIM10sDfAL6c9LJ6IeYuhDRERERD2mY+hD5HWSJCHSHIlIcyQmx07W7GtyNKHYVtwxELIVok6tQ7HBgGKDAd+0qw4Kdrh6BynqcVhKjkEpWuWpDjIAQGBs59VBIYmsDiLyId0KfRYsWIBPPvkE+/fvh9lsRnZ2Nv785z8jMzPTc8wdd9yBr7/+GiUlJQgMDPQcM3z4cADAm2++iV/+8pednv/48eOIjo7GunXrcMEFF3TYX1paitjY2O4MmYiIiIj6ECt9iHybSTYhPSwd6WHpmu1CCFQ0VHS6slhJbQlssg675I7VQXJLdZDSrMJi/RHKiR9clUKqijCnE9D7AeGp7aqD0lx/NgX156UTEboZ+qxfvx7z5s3D5MmTYbfb8eijjyInJwd79+5FQEAAAGDixIm48cYbkZSUhMrKSjz55JPIyclBQUEBZFnGddddhzlz5mjOe8stt6CxsRHR0dGa7QcOHEBwcLDn8/b7iYiIiMi7WOlDNDBJkoRo/2hE+0djStwUzb5GeyOKbEUosBV0CIUa7A0oMhhQZDB0OGeIwwlFVWFRS6EcK4al8CsoqooEd3VQUFzHyqDIDCA4AdDp+ufCiYaYboU+K1as0Hz+5ptvIjo6Gtu3b8eMGTMAALfffrtnv8ViwZ/+9Cecc845KCwsRGpqKsxmM8zm1tLBiooKrFmzBq+//nqHrxcdHY3Q0NDuDJGIiIiI+pGnkTNDH6JBw0/vh8zwTGSGZ2q2CyFQXl/eaRhUWlcKq6xDrmxCbrvqIL0QSFBdvYKU6l1QKra3hEN2hDqdgN7cUg3Ubpn5iDTAFNifl0406JxVTx+r1QoACA8P73R/XV0dFi1aBEVRkJiY2Okx//nPf+Dv74+f/vSnHfaNGzcOTU1NGD16NJ588klMnz79bIZLRERERL1M1nH1LqKhQpIkxATEICYgBlPjpmr21av1KK4p9oRB7mCo0FaIBnsDCo0GFBoNWNfunGEOR0vvoGOwHC2Ekr8CiqpimN3u+mE1eJgr/IkeCUy9Ewiz9M/FEg0SPQ59nE4n5s+fj+nTp2P06NGaff/617/w+9//HnV1dcjMzMSqVatgNBo7Pc/rr7+On/3sZ5rqn7i4OLz66quYNGkSmpqa8Nprr2HmzJnYsmULJkyY0Ol5mpqa0NTU5PncZrP19NKIiIiIqIvcoY+dlT5EQ5q/wR/Dw4djePhwzXancLqqgzppJF1WV4YqWUaVLGOHn/Z8eiGQqNqhqE2wVOcirfx7XPzDf+A360lg8m2cDkbURZIQPfu1zF133YUvv/wSGzZsQEJCgmaf1WpFeXk5SktL8Ze//AXHjh3Dd999Bz8/7ZO8adMmZGdnY9u2bZg4ceJpv97555+PpKQkvP32253uf/LJJ/HUU0912G61WjV9gYiIiIio96zdX45fvvk9xgwLwWf3nOvt4RDRAFKv1rt6B7WpDCqwFqDIVoRGR2OH4xNVFU+eqMSUmEnA3H+4lpMnGqJsNhtCQkLOmHn0KPS5++67sXTpUnzzzTdQFOW0xzY3NyMsLAyvvfYabrjhBs2+X/3qV/jhhx+wY8eOM37N3/3ud9iwYQM2bdrU6f7OKn0SExMZ+hARERH1ofUHK3DzG1sxIi4YX953nreHQ0SDgFM4UVZX5gqBbK4KobXFa1DeUAEAuLqmFg9YGxFy0ePAlDtY9UNDUldDn25N7xJC4J577sGSJUuwbt26MwY+7tcIITSBDADU1tbigw8+wIIFC7r0tXNzcxEXF3fK/SaTCSaT6ZT7iYiIiKj3uZdsd3J6FxH1Ep2kQ3xgPOID45E9LBsAcN+E+/C3H/6GxQcW45OgQKw3m/HoN0/h4j1LIM39l6sJNBF10K3QZ968eXj33XexdOlSBAUFoaysDAAQEhICs9mM/Px8LF68GDk5OYiKisLRo0excOFCmM1mXHrppZpzLV68GHa7HT//+c87fJ2XX34ZiqJg1KhRaGxsxGuvvYY1a9Zg5cqVZ3GpRERERNTbdJK7p4/TyyMhosEsyBiEP079Iy5VLsUTG59Aoa0Qv42JwgV1efjD/52HmPMfBab+BtDJ3h4qkU/pVh3cK6+8AqvVipkzZyIuLs7zsXjxYgCAn58fvv32W1x66aVIS0vDddddh6CgIGzcuBHR0dGac73++uu4+uqrO12Svbm5Gb/97W8xZswYnH/++di5cye+/vprXHTRRT2/UiIiIiLqdXq5pdKHhT5E1A8mxEzAR1d8hDvG3gG9JGNtgD+ujA3HB5sWwvlGDlBx0NtDJPIpPW7k7Ou6Or+NiIiIiHpue1EVrnllI5LC/fHN7y/w9nCIaAg5WHUQT218ErtO/AgAmNDYiCcra6Gc9xAw7W5A7vFi1UQ+r6uZBzteEREREVGPuXv6OFjqQ0T9LCMsA/+55G08POVhmGU//ODnh2viIvC/378I9Y2LgfL93h4ikdcx9CEiIiKiHpMZ+hCRF8k6GTeOuBGfXrkU0+OnQ5Uk/D08FNehBD8uuhD49kXAYff2MIm8hqEPEREREfWYO/SxM/QhIi+KD4zHK7NewcLzFiLMGIJDRiNujAnHn3f8P9S/dgFweDUwODubEJ0WQx8iIiIi6jF36OPkD1NE5GWSJOGylMuw9KrPcHnK5RCShHdCgnGl/gQ+XPoLNL92EXBwJcMfGlIY+hARERFRj3kqfRxcsp2IfEOYXxgWnLcAr8x6BfH+MSjV6/F0ZAQu0ZXiP5/fivr/PR/Y/wXDHxoSGPoQERERUY/JEpdsJyLfdO6wc/HpVZ/hockPIdovEuV6PV6ICMNswwn8e8UdsL16LrB3KeBkaE2DF0MfIiIiIuqx1p4+/KGJiHyPWW/Gz0f+HF/+9Cs8Me0JJATEo1qW8Y+wUOT4VePlVffg5KvTgN0fA06Ht4dL1OsY+hARERFRj3l6+jDzISIfZpSN+GnGT/HZ1cux8LyFSAtWUKfT4fXQEMwx12Lhmt+i7JUsYNcHXO2LBhWGPkRERETUY6z0IaKBRK/T47KUy/DxlZ/ibxf8DaPDR6BRp8N/Q4JwSUAjnvjmIRS/MhnIfRdwqN4eLtFZY+hDRERERD3WunoXINgUlYgGCJ2kw4VJF+Ldyxfjfy/+X0yOHg+7JOGToED8JFDF77/7Iw7+ayLww38Ae7O3h0vUYwx9iIiIiKjH3I2cAcDBbs5ENMBIkoRp8dPwxiX/wduXvI0Z8dlwShK+DAzANcEC92x+Crv+NQH4/nXA3uTt4RJ1G0MfIiIiIuoxWW4T+rDSh4gGsHHR4/DPi/+ND3/yIWYnXQQJwLoAf9wYIuG27Qux5V/jITb/G1AbvT1Uoi5j6ENEREREPcZKHyIabIaHD8dfLngZS69chitTfgI9dNhi9sNtITJ+vvNFrHtlHMTGfwLN9d4eKtEZMfQhIiIioh5z9/QBGPoQ0eCihCh45rznsPyaL3FDxrUwSTJ2+ZlwT4gBP939//Dlq+Ph2PAS0FTr7aESnRJDHyIiIiLqMYY+RDTYxQfG49Fpj2HF/3yNW0feDH+dAQdNRvw+xIi5+/+NJf8eD/Wb54FGm7eHStQBQx8iIiIi6jFO7yKioSLSHIn7Jz+IldeuxW/G3okQ2Q9FBgMeD/HDpYcW4b//OwENa58DGqq9PVQiD4Y+RERERNRjOp0Ed+7DRs5ENBSEmEJw1/h5WHndejw44X5E6gNRptdjYYgZcwrewWuvTUbt6qeA+kpvD5WIoQ8RERERnR19yxQvVvoQ0VDib/DHzWNuxYrr1+GxrD9gmDEUlbKMvwX7IafoA/z99Smo+upRoO6kt4dKQxhDHyIiIiI6KzqJoQ8RDV0m2YRrh1+Pz65bg+em/wkpflGokXX432AzZpcsxfOLslD+5YNAbbm3h0pDEEMfIiIiIjorrPQhIgIMOgN+kjYXS679Gi+d/yJG+A9Dg06Ht4PMmHN8BZ5+KxtHPr8PqCnz9lBpCGHoQ0RERERnRcfQh4jIQyfpMMuSg8U//RKvXPQvTAhSoEoSPgw04ycnVuORt8/F4WV3AdZj3h4qDQEMfYiIiIjorLDSh4ioI0mScG7CeXjr6mV4c/YiTA8dDock4fMAM66q2oD5787Enk9/BVQXe3uoNIgx9CEiIiKisyK7Qx+u3kVE1KmJsZPw6twP8f5l7+PiiHGQBLDa3w/XW7fijvcvwraPfwFxMt/bw6RBiKEPEREREZ0Vd+hjdzD0ISI6nVGRo/DXy9/Gkis/xRUxWZABbDT74Ze1ubj5ozn49sPrIU4c9vYwaRBh6ENEREREZ0VuWb3LyUofIqIuSQ1NxbNzXsPnV3+Ja+PPhwESdviZ8Jv6Pbjuk8uwcvE1cJTv8/YwaRBg6ENEREREZ8XdyNnOnj5ERN2SEJSAxy7+B1b8z9e4OWkOzJCwz2TEbxsP4qqlV2Hpez+BWrrL28OkAYyhDxERERGdFXcjZydDHyKiHon2j8aDF7yAldd9gztTrkQQZBQYDfhjcyEuX34d3v/vJWg6tt3bw6QBiKEPEREREZ0VVvoQEfWOUL9QzDvvGay8YQPuz7gB4dCjxKDHs/ajmLPiF1j0zsWoK97o7WHSAMLQh4iIiIjOCit9iIh6V6AxELdOexRf3bgJj468FXGSESf0Mv7qKEPO17fhlbcvgLVgnbeHSQMAQx8iIiIiOis6iZU+RER9wU/vhxsm34/lN27G02PmwSL5wSbL+JfzBHLWzcNf35qBE4e+8vYwyYcx9CEiIiKis6KXXaGPg6t3ERH1CYNswFUT7sSnP9+MFyY8iExdAOp1OixCFWZv+C3+9FY2SvYv9fYwyQcx9CEiIiKis+Jest3hYOhDRNSXZJ2MOWNuxoc/34R/Zj2Oc+RgNOskLEYNLtv8B/zhzSzk734fYAhPLRj6EBEREdFZkXWs9CEi6k+SJGHG8P/B2zduwBvTF2KqIRx2ScIyqR5XbvsTHnhzCvblvsnwhxj6EBEREdHZkdnImYjIKyRJwuS0y/B/P1uPd8//Gy4wxkBIElbpGnHtzhdx16KJ2LHtFYY/QxhDHyIiIiI6KzKXbCci8roxlgvx/274Gh9f9L+41G8YdEJgg6zipj3/wi8XjcfGzX+FcDi8PUzqZwx9iIiIiOiseCp9+JtkIiKvy0iYhj9ftwKfzXkH1/hboBcC22QH7jiwCDe8NQGrNzwHp8Pu7WFSP5GEGJzvzjabDSEhIbBarQgODvb2cIiIiIgGrZve2IpvDlYgLsQPIWaDt4dDRERtmFGMMMNb2OVfiqaWkD7a7oTZObRrQGaFXID51/4/bw+jx7qaeej7cUxERERENAglh/sDAEqtjSi1Nnp5NEREpBUGYD6C5eM4J/I9HA4tQbl+aAc+AGBrOuntIfQLhj5EREREdFYe/8lIXD42DiqXbCci8nFXoKmhDBVlq+AUTm8PxqtGWrK8PYR+wdCHiIiIiM6KQdYhKyXC28MgIqIuiQTGjvb2IKifsKaLiIiIiIiIiGgQYuhDRERERERERDQIMfQhIiIiIiIiIhqEGPoQEREREREREQ1CDH2IiIiIiIiIiAYhhj5ERERERERERIMQQx8iIiIiIiIiokGIoQ8RERERERER0SDE0IeIiIiIiIiIaBBi6ENERERERERENAgx9CEiIiIiIiIiGoQY+hARERERERERDUIMfYiIiIiIiIiIBiGGPkREREREREREg1C3Qp8FCxZg8uTJCAoKQnR0NK688kocOHBAc8wdd9yB1NRUmM1mREVFYe7cudi/f7/mGEmSOny8//77mmPWrVuHCRMmwGQyIS0tDW+++WbPrpCIiIiIiIiIaAjqVuizfv16zJs3D5s3b8aqVaugqipycnJQV1fnOWbixIlYtGgR9u3bh6+++gpCCOTk5MDhcGjOtWjRIpSWlno+rrzySs++goICXHbZZbjggguQm5uL+fPn47bbbsNXX311dldLRERERERERDRESEII0dMXV1RUIDo6GuvXr8eMGTM6PWbXrl0455xzcPjwYaSmprq+qCRhyZIlmqCnrYceegjLly/H7t27Pduuv/56VFdXY8WKFV0am81mQ0hICKxWK4KDg7t3YUREREREREREPqqrmcdZ9fSxWq0AgPDw8E7319XVYdGiRVAUBYmJiZp98+bNQ2RkJKZMmYI33ngDbbOnTZs2YdasWZrjZ8+ejU2bNp1yLE1NTbDZbJoPIiIiIiIiIqKhqsehj9PpxPz58zF9+nSMHj1as+9f//oXAgMDERgYiC+//BKrVq2C0Wj07H/66afxwQcfYNWqVbjmmmvwm9/8Bn//+989+8vKyhATE6M5Z0xMDGw2GxoaGjodz4IFCxASEuL5aB8yERERERERERENJfqevnDevHnYvXs3NmzY0GHfjTfeiIsvvhilpaX4y1/+gmuvvRbfffcd/Pz8AACPPfaY59jx48ejrq4OL7zwAu69996eDgePPPIIHnjgAc/nNpuNwQ8RERERERERDVk9qvS5++678fnnn2Pt2rVISEjosD8kJATp6emYMWMGPvroI+zfvx9Lliw55fmysrJw9OhRNDU1AQBiY2Nx/PhxzTHHjx9HcHAwzGZzp+cwmUwIDg7WfBARERERERERDVXdqvQRQuCee+7BkiVLsG7dOiiK0qXXCCE8gU5ncnNzERYWBpPJBACYNm0avvjiC80xq1atwrRp07o1VgDs7UNEREREREREg4o76zjT2lzdCn3mzZuHd999F0uXLkVQUBDKysoAuCp7zGYz8vPzsXjxYuTk5CAqKgpHjx7FwoULYTabcemllwIAPvvsMxw/fhxTp06Fn58fVq1aheeeew4PPvig5+vceeed+Mc//oHf//73uPXWW7FmzRp88MEHWL58eZfHWlNTAwCc4kVEREREREREg1JNTQ1CQkJOub9bS7ZLktTp9kWLFuGWW25BSUkJbrvtNmzfvh1VVVWIiYnBjBkz8PjjjyMzMxMAsGLFCjzyyCM4fPgwhBBIS0vDXXfdhV//+tfQ6Vpnm61btw73338/9u7di4SEBDz22GO45ZZbujpUOJ1OlJSUICgo6JTj9nXuvkRHjhzhdLVBjvd6aOH9Hjp4r4cO3uuhhfd76OC9Hjp4r4eOwXKvhRCoqalBfHy8Jktpr1uhD/Uvm82GkJAQWK3WAf0/I50Z7/XQwvs9dPBeDx2810ML7/fQwXs9dPBeDx1D7V73eMl2IiIiIiIiIiLyXQx9iIiIiIiIiIgGIYY+PsxkMuGJJ57wrGpGgxfv9dDC+z108F4PHbzXQwvv99DBez108F4PHUPtXrOnDxERERERERHRIMRKHyIiIiIiIiKiQYihDxERERERERHRIMTQh4iIiIiIiIhoEGLoQ0REREREREQ0CDH06WcWiwWSJHX4mDdvHgCgsbER8+bNQ0REBAIDA3HNNdfg+PHjmnMUFxfjsssug7+/P6Kjo/G73/0OdrvdG5dDp3G6e11ZWYl77rkHmZmZMJvNSEpKwr333gur1ao5R2evf//99710RXQ6Z3q2Z86c2WHfnXfeqTkHn+2B4XT3urCwsNN9kiThww8/9JyDz/bA4HA48Nhjj0FRFJjNZqSmpuKZZ55B2zUwhBB4/PHHERcXB7PZjFmzZuHQoUOa81RWVuLGG29EcHAwQkND8atf/Qq1tbX9fTl0Gme616qq4qGHHsKYMWMQEBCA+Ph43HTTTSgpKdGcp7N/HxYuXOiNS6LT6Mqzfcstt3S4l3PmzNGch8+27+vKvT7V+/YLL7zgOYbP9sBQU1OD+fPnIzk5GWazGdnZ2fj+++89+4fse7agflVeXi5KS0s9H6tWrRIAxNq1a4UQQtx5550iMTFRrF69Wmzbtk1MnTpVZGdne15vt9vF6NGjxaxZs8SOHTvEF198ISIjI8UjjzzipSuiUzndvf7xxx/F1VdfLZYtWyYOHz4sVq9eLdLT08U111yjOQcAsWjRIs15GhoavHRFdDpnerbPP/988etf/1pzjNVq9byez/bAcbp7bbfbNftKS0vFU089JQIDA0VNTY3nHHy2B4Znn31WREREiM8//1wUFBSIDz/8UAQGBoq//e1vnmMWLlwoQkJCxKeffip27twprrjiCqEoiuZ+zpkzR5xzzjli8+bN4ttvvxVpaWnihhtu8MYl0Smc6V5XV1eLWbNmicWLF4v9+/eLTZs2iSlTpoiJEydqzpOcnCyefvppzbNdW1vrjUui0+jKs33zzTeLOXPmaO5lZWWl5jx8tn1fV+51+/ftN954Q0iSJPLy8jzH8NkeGK699loxcuRIsX79enHo0CHxxBNPiODgYHH06FEhxNB9z2bo42X33XefSE1NFU6nU1RXVwuDwSA+/PBDz/59+/YJAGLTpk1CCCG++OILodPpRFlZmeeYV155RQQHB4umpqZ+Hz91Xdt73ZkPPvhAGI1GoaqqZxsAsWTJkn4aIfWm9vf7/PPPF/fdd98pj+ezPXCd6dkeN26cuPXWWzXb+GwPDJdddlmHe3f11VeLG2+8UQghhNPpFLGxseKFF17w7K+urhYmk0m89957Qggh9u7dKwCI77//3nPMl19+KSRJEseOHeuHq6CuONO97szWrVsFAFFUVOTZlpycLF566aW+Gib1kq7c75tvvlnMnTv3lOfgsz0w9OTZnjt3rrjwwgs12/hs+776+nohy7L4/PPPNdsnTJgg/vCHPwzp92xO7/Ki5uZmvPPOO7j11lshSRK2b98OVVUxa9YszzHDhw9HUlISNm3aBADYtGkTxowZg5iYGM8xs2fPhs1mw549e/r9Gqhr2t/rzlitVgQHB0Ov12u2z5s3D5GRkZgyZQreeOMNTTkq+aZT3e///ve/iIyMxOjRo/HII4+gvr7es4/P9sB0pmd7+/btyM3Nxa9+9asO+/hs+77s7GysXr0aBw8eBADs3LkTGzZswCWXXAIAKCgoQFlZmeZ9OyQkBFlZWZr37dDQUEyaNMlzzKxZs6DT6bBly5Z+vBo6nTPd685YrVZIkoTQ0FDN9oULFyIiIgLjx4/HCy+8wGm6Pqir93vdunWIjo5GZmYm7rrrLpw8edKzj8/2wNDdZ/v48eNYvnx5p+/bfLZ9m91uh8PhgJ+fn2a72WzGhg0bhvR7tv7Mh1Bf+fTTT1FdXY1bbrkFAFBWVgaj0djhm4eYmBiUlZV5jmn7Q6F7v3sf+ab297q9EydO4JlnnsHtt9+u2f7000/jwgsvhL+/P1auXInf/OY3qK2txb333tsPo6ae6ux+/+xnP0NycjLi4+Oxa9cuPPTQQzhw4AA++eQTAHy2B6ozPduvv/46RowYgezsbM12PtsDw8MPPwybzYbhw4dDlmU4HA48++yzuPHGGwG0PpudPbtt37ejo6M1+/V6PcLDw/ls+5Az3ev2Ghsb8dBDD+GGG25AcHCwZ/u9996LCRMmIDw8HBs3bsQjjzyC0tJS/PWvf+2vS6Eu6Mr9njNnDq6++mooioK8vDw8+uijuOSSS7Bp0ybIssxne4Do7rP91ltvISgoCFdffbVmO59t3xcUFIRp06bhmWeewYgRIxATE4P33nsPmzZtQlpa2pB+z2bo40Wvv/46LrnkEsTHx3t7KNTHTnevbTYbLrvsMowcORJPPvmkZt9jjz3m+fP48eNRV1eHF154gT8Y+rjO7nfbQG/MmDGIi4vDRRddhLy8PKSmpnpjmNQLTvdsNzQ04N1339U8x258tgeGDz74AP/973/x7rvvYtSoUcjNzcX8+fMRHx+Pm2++2dvDo17UnXutqiquvfZaCCHwyiuvaPY98MADnj+PHTsWRqMRd9xxBxYsWACTydQv10Jn1pX7ff3113uOHzNmDMaOHYvU1FSsW7cOF110kbeGTt3U3X/H33jjDdx4440dqkX4bA8Mb7/9Nm699VYMGzYMsixjwoQJuOGGG7B9+3ZvD82rOL3LS4qKivD111/jtttu82yLjY1Fc3MzqqurNcceP34csbGxnmPar+bl/tx9DPmWzu61W01NDebMmYOgoCAsWbIEBoPhtOfKysrC0aNH0dTU1FfDpbN0uvvdVlZWFgDg8OHDAPhsD0RnutcfffQR6uvrcdNNN53xXHy2fdPvfvc7PPzww7j++usxZswY/OIXv8D999+PBQsWAGh9Njt7dtu+b5eXl2v22+12VFZW8tn2IWe6127uwKeoqAirVq3SVPl0JisrC3a7HYWFhX04euqurt7vtlJSUhAZGal53+az7fu6c6+//fZbHDhw4IzfwwF8tn1Vamoq1q9fj9raWhw5cgRbt26FqqpISUkZ0u/ZDH28ZNGiRYiOjsZll13m2TZx4kQYDAasXr3as+3AgQMoLi7GtGnTAADTpk3Djz/+qPmf0f1Nx8iRI/vvAqjLOrvXgKvCJycnB0ajEcuWLevwG4XO5ObmIiwsjL9R8GGnut/t5ebmAgDi4uIA8NkeiM50r19//XVcccUViIqKOuO5+Gz7pvr6euh02m+VZFmG0+kEACiKgtjYWM37ts1mw5YtWzTv29XV1ZrfMq5ZswZOp9MT/pL3neleA62Bz6FDh/D1118jIiLijOfNzc2FTqfrMF2AvKsr97u9o0eP4uTJk5r3bT7bvq879/r111/HxIkTcc4555zxvHy2fVtAQADi4uJQVVWFr776CnPnzh3a79lebiQ9JDkcDpGUlCQeeuihDvvuvPNOkZSUJNasWSO2bdsmpk2bJqZNm+bZ717WOScnR+Tm5ooVK1aIqKgoLuvso051r61Wq8jKyhJjxowRhw8f1iz/aLfbhRBCLFu2TPzf//2f+PHHH8WhQ4fEv/71L+Hv7y8ef/xxb1wKdcGp7vfhw4fF008/LbZt2yYKCgrE0qVLRUpKipgxY4bnGD7bA8vp/h0XQohDhw4JSZLEl19+2WEfn+2B4+abbxbDhg3zLPX7ySefiMjISPH73//ec8zChQtFaGioWLp0qdi1a5eYO3dup8u/jh8/XmzZskVs2LBBpKenD/jlXwebM93r5uZmccUVV4iEhASRm5ured92r7C4ceNG8dJLL4nc3FyRl5cn3nnnHREVFSVuuukmb14adeJM97umpkY8+OCDYtOmTaKgoEB8/fXXYsKECSI9PV00NjZ6zsNn2/d15d9xIVzfm/v7+4tXXnmlwzn4bA8cK1asEF9++aXIz88XK1euFOecc47IysoSzc3NQoih+57N0McLvvrqKwFAHDhwoMO+hoYG8Zvf/EaEhYUJf39/cdVVV4nS0lLNMYWFheKSSy4RZrNZREZGit/+9reaZb7Jd5zqXq9du1YA6PSjoKBACOFaHnDcuHEiMDBQBAQEiHPOOUe8+uqrwuFweOFKqCtOdb+Li4vFjBkzRHh4uDCZTCItLU387ne/E1arVXMcn+2B43T/jgshxCOPPCISExM7fV75bA8cNptN3HfffSIpKUn4+fmJlJQU8Yc//MHzQ74QrmXbH3vsMRETEyNMJpO46KKLOvx/cfLkSXHDDTeIwMBAERwcLH75y1+Kmpqa/r4cOo0z3euCgoJTvm+vXbtWCCHE9u3bRVZWlggJCRF+fn5ixIgR4rnnntOEBOQbznS/6+vrRU5OjoiKihIGg0EkJyeLX//616KsrExzHj7bvq8r/44LIcS///1vYTabRXV1dYdz8NkeOBYvXixSUlKE0WgUsbGxYt68eZp7OlTfsyUhuEYsEREREREREdFgw54+RERERERERESDEEMfIiIiIiIiIqJBiKEPEREREREREdEgxNCHiIiIiIiIiGgQYuhDRERERERERDQIMfQhIiIiIiIiIhqEGPoQEREREREREQ1CDH2IiIhoyJs5cybmz59/yv0WiwUvv/xyr3293j4fERHRUPPss88iOzsb/v7+CA0N7fLr9u3bhyuuuAIhISEICAjA5MmTUVxcDACorKzEPffcg8zMTJjNZiQlJeHee++F1WrVnGP16tXIzs5GUFAQYmNj8dBDD8Fut2uO+eqrrzB16lQEBQUhKioK11xzDQoLC7s8zsLCQkiS1OnHhx9+2OXzMPQhIiIiIiIiIp8zc+ZMvPnmm53ua25uxv/8z//grrvu6vL58vLycO6552L48OFYt24ddu3ahcceewx+fn4AgJKSEpSUlOAvf/kLdu/ejTfffBMrVqzAr371K885du7ciUsvvRRz5szBjh07sHjxYixbtgwPP/yw55iCggLMnTsXF154IXJzc/HVV1/hxIkTuPrqq7s81sTERJSWlmo+nnrqKQQGBuKSSy7p8nn0XT6SiIiIiIiIiMgHPPXUUwBwylCoM3/4wx9w6aWX4vnnn/dsS01N9fx59OjR+PjjjzX7nn32Wfz85z+H3W6HXq/H4sWLMXbsWDz++OMAgLS0NDz//PO49tpr8cQTTyAoKAjbt2+Hw+HAn/70J+h0rlqbBx98EHPnzoWqqjAYDACApUuX4qmnnsLevXsRHx+Pm2++GX/4wx+g1+shyzJiY2M141+yZAmuvfZaBAYGdvmaWelDREREBMBut+Puu+9GSEgIIiMj8dhjj0EI0emxxcXFmDt3LgIDAxEcHIxrr70Wx48f1xzz2WefYfLkyfDz80NkZCSuuuqqU37t1157DaGhoVi9enWvXhMRERG5OJ1OLF++HBkZGZg9ezaio6ORlZWFTz/99LSvs1qtCA4Ohl7vqplpamryVAa5mc1mNDY2Yvv27QCAiRMnQqfTYdGiRXA4HLBarXj77bcxa9YsT+Dz7bff4qabbsJ9992HvXv34t///jfefPNNPPvss52OY/v27cjNzdVUHXUFQx8iIiIiAG+99Rb0ej22bt2Kv/3tb/jrX/+K1157rcNxTqcTc+fORWVlJdavX49Vq1YhPz8f1113neeY5cuX46qrrsKll16KHTt2YPXq1ZgyZUqnX/f555/Hww8/jJUrV+Kiiy7qs+sjIiIaysrLy1FbW4uFCxdizpw5WLlyJa666ipcffXVWL9+faevOXHiBJ555hncfvvtnm2zZ8/Gxo0b8d5778HhcODYsWN4+umnAQClpaUAAEVRsHLlSjz66KMwmUwIDQ3F0aNH8cEHH3jO89RTT+Hhhx/GzTffjJSUFFx88cV45pln8O9//7vTsbz++usYMWIEsrOzu3XdkjjVr7CIiIiIhoiZM2eivLwce/bsgSRJAICHH34Yy5Ytw969e2GxWDB//nzMnz8fq1atwiWXXIKCggIkJiYCAPbu3YtRo0Zh69atmDx5MrKzs5GSkoJ33nmn06/nPl9paSnefvttrFq1CqNGjeq36yUiIvJFzz33HJ577jnP5w0NDTAYDJ4qG8D1npuUlOT5/M0338T8+fNRXV192nOXlJRg2LBhuOGGG/Duu+96tl9xxRUICAjAe++9pzneZrPh4osvRnh4OJYtW+ap0AGAv/71r3jqqadQV1cHk8mExx57DI888gjef/99XHfddSgrK8OMGTNw5ZVX4oYbbkBNTQ0ef/xx6PV6rFq1CpIkISoqCrW1tZBl2XNeh8OBxsZG1NXVwd/fX/P3EBcXh8ceewy//e1vu/4XCvb0ISIiIgIATJ061RP4AMC0adPw4osvwuFwaI7bt28fEhMTPYEPAIwcORKhoaHYt28fJk+ejNzcXPz6178+7dd78cUXUVdXh23btiElJaV3L4aIiGgAuvPOO3Httdd6Pr/xxhtxzTXXaBogx8fH9+jckZGR0Ov1GDlypGb7iBEjsGHDBs22mpoazJkzB0FBQViyZIkm8AGABx54APfffz9KS0sRFhaGwsJCPPLII57383/+858ICQnR9A565513kJiYiC1btmDq1Kmora3FU0891Wlz5/bTxz766CPU19fjpptu6vZ1M/QhIiIi6mVms/mMx5x33nlYvnw5PvjgA82KH0RERENVeHg4wsPDPZ+bzWZER0cjLS3trM9tNBoxefJkHDhwQLP94MGDSE5O9nxus9kwe/ZsmEwmLFu2rEMA4yZJkieAeu+995CYmIgJEyYAAOrr6z0NnN3cFT1OpxMAMGHCBBw4cKBL1/b666/jiiuuQFRUVBevthVDHyIiIiIAW7Zs0Xy+efNmpKena8quAddvBI8cOYIjR45opndVV1d7fns4duxYrF69Gr/85S9P+fWmTJmCu+++G3PmzIFer8eDDz7Yy1dEREQ0eBUXF6OyshLFxcVwOBzIzc0F4FpNy7261fDhw7FgwQLPYgq/+93vcN1112HGjBm44IILsGLFCnz22WdYt24dAFfgk5OTg/r6erzzzjuw2Wyw2WwAgKioKM/3BC+88ALmzJkDnU6HTz75BAsXLsQHH3zg2X/ZZZfhpZdewtNPP+2Z3vXoo48iOTkZ48ePBwA8/vjjuPzyy5GUlISf/vSn0Ol02LlzJ3bv3o0//elPnus8fPgwvvnmG3zxxRc9+nti6ENEREQE1zePDzzwAO644w788MMP+Pvf/44XX3yxw3GzZs3CmDFjcOONN+Lll1+G3W7Hb37zG5x//vmYNGkSAOCJJ57ARRddhNTUVFx//fWw2+344osv8NBDD2nOlZ2djS+++AKXXHIJ9Ho95s+f3x+XSkRENOA9/vjjeOuttzyfu8OUtWvXYubMmQCAAwcOwGq1eo656qqr8Oqrr2LBggW49957kZmZiY8//hjnnnsuAOCHH37w/BKofQVOQUEBLBYLAODLL7/Es88+i6amJpxzzjlYunQpLrnkEs+xF154Id599108//zzeP755+Hv749p06ZhxYoVnmrg2bNn4/PPP8fTTz+NP//5zzAYDBg+fDhuu+02zdd94403kJCQgJycnB79PbGRMxEREQ15M2fOxKhRo+B0OvHuu+9ClmXcdddd+NOf/gRJkjSNnAFXQHTPPfdg9erV0Ol0mDNnDv7+978jJibGc85PPvkEzzzzDPbu3Yvg4GDMmDEDH3/8MQB0ON8333yDSy+9FAsWLMA999zT35dPREREgxRDHyIiIiIiIiKiQUh35kOIiIiIiIiIiGigYehDRERERERERDQIMfQhIiIiIiIiIhqEGPoQEREREREREQ1CDH2IiIiIiIiIiAYhhj5ERERERERERIMQQx8iIiIiIiIiokGIoQ8RERERERER0SDE0IeIiIiIiIiIaBBi6ENERERERERENAgx9CEiIiIiIiIiGoQY+hARERERERERDUL/H1m8GWRzlHwTAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "oracle_df.drop('current_price', axis=1)[(16298700 <= oracle_df.block) & (\n",
+    "    # oracle_df.index <= 16300600\n",
+    "    oracle_df.block <= 16298900\n",
+    "\n",
+    ")].plot(x=\"block\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "2f4c3c12-e783-4c8f-a5b6-8a35e7570f09",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: xlabel='block'>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "oracle_df.drop('current_price', axis=1)[(16300300 <= oracle_df.block) & (\n",
+    "    oracle_df.block <= 16300600\n",
+    ")].plot(x=\"block\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2cbc87a-0857-47d2-81e5-a4074ed31531",
+   "metadata": {},
+   "source": [
+    "# Largest price moves in one block\n",
+    "\n",
+    "Below we look at the largest moves in one block. Our first list has 17/20 in the first 24 hours of the pair getting created. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "366692bc-eb5c-429a-a254-64863aad874f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>block</th>\n",
+       "      <th>amount0In_per_reserve0</th>\n",
+       "      <th>amount1In_per_reserve1</th>\n",
+       "      <th>amount0Net_per_reserve0</th>\n",
+       "      <th>amount1Net_per_reserve1</th>\n",
+       "      <th>max_amountIn_per_reserve</th>\n",
+       "      <th>max_amountNet_per_reserve</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>11876000</td>\n",
+       "      <td>0.00666</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>-0.659339</td>\n",
+       "      <td>1.941522</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.941522</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11876001</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11876002</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11876003</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11876004</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      block amount0In_per_reserve0 amount1In_per_reserve1  \\\n",
+       "0  11876000                0.00666                    2.0   \n",
+       "1  11876001                    0.0                    0.0   \n",
+       "2  11876002                    0.0                    0.0   \n",
+       "3  11876003                    0.0                    0.0   \n",
+       "4  11876004                    0.0                    0.0   \n",
+       "\n",
+       "  amount0Net_per_reserve0 amount1Net_per_reserve1  max_amountIn_per_reserve  \\\n",
+       "0               -0.659339                1.941522                       2.0   \n",
+       "1                     0.0                     0.0                       0.0   \n",
+       "2                     0.0                     0.0                       0.0   \n",
+       "3                     0.0                     0.0                       0.0   \n",
+       "4                     0.0                     0.0                       0.0   \n",
+       "\n",
+       "   max_amountNet_per_reserve  \n",
+       "0                   1.941522  \n",
+       "1                   0.000000  \n",
+       "2                   0.000000  \n",
+       "3                   0.000000  \n",
+       "4                   0.000000  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "big_moves_df = DataFrame({\n",
+    "    \"block\": block_df[\"block\"],\n",
+    "    \"amount0In_per_reserve0\": block_df[\"amount0In\"] / block_df[\"reserve0\"],\n",
+    "    \"amount1In_per_reserve1\": block_df[\"amount1In\"] / block_df[\"reserve1\"],\n",
+    "    \"amount0Net_per_reserve0\": (block_df[\"amount0In\"] - block_df[\"amount0Out\"]) / block_df[\"reserve0\"],\n",
+    "    \"amount1Net_per_reserve1\": (block_df[\"amount1In\"] - block_df[\"amount1Out\"]) / block_df[\"reserve1\"],\n",
+    "})\n",
+    "\n",
+    "big_moves_df[\"max_amountIn_per_reserve\"] = big_moves_df[[\n",
+    "    \"amount0In_per_reserve0\", \"amount1In_per_reserve1\"\n",
+    "]].max(axis=1)\n",
+    "big_moves_df[\"max_amountNet_per_reserve\"] = big_moves_df[[\n",
+    "    \"amount0Net_per_reserve0\", \"amount1Net_per_reserve1\"\n",
+    "]].max(axis=1)\n",
+    "\n",
+    "\n",
+    "big_moves_df.sort_values(\"max_amountNet_per_reserve\", ascending=False).reset_index(drop=True)\n",
+    "big_moves_df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f68d1a15-56a4-4c68-88e5-982c15feed7b",
+   "metadata": {},
+   "source": [
+    "Lets drop the first 24 hours to look at the largest moves after the market has found some equilibrium after initialization"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b1be09da-3b84-4e91-8ff4-ea5bd73a8108",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>block</th>\n",
+       "      <th>amount0In_per_reserve0</th>\n",
+       "      <th>amount1In_per_reserve1</th>\n",
+       "      <th>amount0Net_per_reserve0</th>\n",
+       "      <th>amount1Net_per_reserve1</th>\n",
+       "      <th>max_amountIn_per_reserve</th>\n",
+       "      <th>max_amountNet_per_reserve</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>13845789</td>\n",
+       "      <td>0.297619</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.297619</td>\n",
+       "      <td>-0.228827</td>\n",
+       "      <td>0.297619</td>\n",
+       "      <td>0.297619</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12215728</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.180044</td>\n",
+       "      <td>-0.152186</td>\n",
+       "      <td>0.180044</td>\n",
+       "      <td>0.180044</td>\n",
+       "      <td>0.180044</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11950780</td>\n",
+       "      <td>0.164481</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.164481</td>\n",
+       "      <td>-0.140884</td>\n",
+       "      <td>0.164481</td>\n",
+       "      <td>0.164481</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11892712</td>\n",
+       "      <td>0.143585</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.143585</td>\n",
+       "      <td>-0.125227</td>\n",
+       "      <td>0.143585</td>\n",
+       "      <td>0.143585</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11913006</td>\n",
+       "      <td>0.141817</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.141817</td>\n",
+       "      <td>-0.123876</td>\n",
+       "      <td>0.141817</td>\n",
+       "      <td>0.141817</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>11900698</td>\n",
+       "      <td>0.134465</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.134465</td>\n",
+       "      <td>-0.118214</td>\n",
+       "      <td>0.134465</td>\n",
+       "      <td>0.134465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>15442876</td>\n",
+       "      <td>0.134218</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.134218</td>\n",
+       "      <td>-0.118022</td>\n",
+       "      <td>0.134218</td>\n",
+       "      <td>0.134218</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13032464</td>\n",
+       "      <td>0.001424</td>\n",
+       "      <td>0.130006</td>\n",
+       "      <td>-0.113319</td>\n",
+       "      <td>0.128197</td>\n",
+       "      <td>0.130006</td>\n",
+       "      <td>0.128197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>15684118</td>\n",
+       "      <td>0.010373</td>\n",
+       "      <td>0.140461</td>\n",
+       "      <td>-0.112464</td>\n",
+       "      <td>0.127171</td>\n",
+       "      <td>0.140461</td>\n",
+       "      <td>0.127171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>11892713</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.122017</td>\n",
+       "      <td>-0.108457</td>\n",
+       "      <td>0.122017</td>\n",
+       "      <td>0.122017</td>\n",
+       "      <td>0.122017</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      block amount0In_per_reserve0 amount1In_per_reserve1  \\\n",
+       "0  13845789               0.297619                    0.0   \n",
+       "1  12215728                    0.0               0.180044   \n",
+       "2  11950780               0.164481                    0.0   \n",
+       "3  11892712               0.143585                    0.0   \n",
+       "4  11913006               0.141817                    0.0   \n",
+       "5  11900698               0.134465                    0.0   \n",
+       "6  15442876               0.134218                    0.0   \n",
+       "7  13032464               0.001424               0.130006   \n",
+       "8  15684118               0.010373               0.140461   \n",
+       "9  11892713                    0.0               0.122017   \n",
+       "\n",
+       "  amount0Net_per_reserve0 amount1Net_per_reserve1  max_amountIn_per_reserve  \\\n",
+       "0                0.297619               -0.228827                  0.297619   \n",
+       "1               -0.152186                0.180044                  0.180044   \n",
+       "2                0.164481               -0.140884                  0.164481   \n",
+       "3                0.143585               -0.125227                  0.143585   \n",
+       "4                0.141817               -0.123876                  0.141817   \n",
+       "5                0.134465               -0.118214                  0.134465   \n",
+       "6                0.134218               -0.118022                  0.134218   \n",
+       "7               -0.113319                0.128197                  0.130006   \n",
+       "8               -0.112464                0.127171                  0.140461   \n",
+       "9               -0.108457                0.122017                  0.122017   \n",
+       "\n",
+       "   max_amountNet_per_reserve  \n",
+       "0                   0.297619  \n",
+       "1                   0.180044  \n",
+       "2                   0.164481  \n",
+       "3                   0.143585  \n",
+       "4                   0.141817  \n",
+       "5                   0.134465  \n",
+       "6                   0.134218  \n",
+       "7                   0.128197  \n",
+       "8                   0.127171  \n",
+       "9                   0.122017  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sorted_net_moves_df = big_moves_df.iloc[7200:].sort_values(\"max_amountNet_per_reserve\", ascending=False).reset_index(drop=True)\n",
+    "sorted_net_moves_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4cecbe74-d57e-4359-b0ce-118bb61347d2",
+   "metadata": {},
+   "source": [
+    "## Examining some of the largest moves \n",
+    "\n",
+    "Below is a chart of the largest moves. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "765fac9b-ca2b-446e-8446-07976590e785",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: >"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_net_moves_df[(sorted_net_moves_df.index  <= 25)][[\"max_amountIn_per_reserve\", \"max_amountNet_per_reserve\"]].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8ab83a5b-ba0f-4381-9787-aecf4d44a5da",
+   "metadata": {},
+   "source": [
+    "#### Looking at how the market and oracles behave after the largest shift in price"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c0c1ec4f-4876-432c-a436-370e4ed646a1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>block</th>\n",
+       "      <th>amount0In</th>\n",
+       "      <th>amount1In</th>\n",
+       "      <th>amount0Out</th>\n",
+       "      <th>amount1Out</th>\n",
+       "      <th>reserve0</th>\n",
+       "      <th>reserve1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1969784</th>\n",
+       "      <td>13845784</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>153212210186396951314993</td>\n",
+       "      <td>238716385955530719051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969785</th>\n",
+       "      <td>13845785</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>153212210186396951314993</td>\n",
+       "      <td>238716385955530719051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969786</th>\n",
+       "      <td>13845786</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>153212210186396951314993</td>\n",
+       "      <td>238716385955530719051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969787</th>\n",
+       "      <td>13845787</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>153212210186396951314993</td>\n",
+       "      <td>238716385955530719051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969788</th>\n",
+       "      <td>13845788</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>153212210186396951314993</td>\n",
+       "      <td>238716385955530719051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969789</th>\n",
+       "      <td>13845789</td>\n",
+       "      <td>45598914832797630699516</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>54624835640149345578</td>\n",
+       "      <td>153212210186396951314993</td>\n",
+       "      <td>238716385955530719051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969790</th>\n",
+       "      <td>13845790</td>\n",
+       "      <td>4930032061697182061256</td>\n",
+       "      <td>12071084298563895296</td>\n",
+       "      <td>12227918575556074800253</td>\n",
+       "      <td>5005352062942556724</td>\n",
+       "      <td>198811125019194582014509</td>\n",
+       "      <td>184091550315381373473</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969791</th>\n",
+       "      <td>13845791</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>191513238505335689275512</td>\n",
+       "      <td>191157282551002712045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969792</th>\n",
+       "      <td>13845792</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6636305260866285568</td>\n",
+       "      <td>6406902276717032296170</td>\n",
+       "      <td>0</td>\n",
+       "      <td>191513238505335689275512</td>\n",
+       "      <td>191157282551002712045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969793</th>\n",
+       "      <td>13845793</td>\n",
+       "      <td>5379873916932590788066</td>\n",
+       "      <td>15270927886500831959</td>\n",
+       "      <td>13229504248002106402496</td>\n",
+       "      <td>6420108745716013110</td>\n",
+       "      <td>185106336228618656979342</td>\n",
+       "      <td>197793587811868997613</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969794</th>\n",
+       "      <td>13845794</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>177256705897549141364912</td>\n",
+       "      <td>206644406952653816462</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969795</th>\n",
+       "      <td>13845795</td>\n",
+       "      <td>332166678408919642610</td>\n",
+       "      <td>2204986233670493184</td>\n",
+       "      <td>1865882334299188750566</td>\n",
+       "      <td>393602925405286658</td>\n",
+       "      <td>177256705897549141364912</td>\n",
+       "      <td>206644406952653816462</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969796</th>\n",
+       "      <td>13845796</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3901151799213780841</td>\n",
+       "      <td>3218652312887786605207</td>\n",
+       "      <td>0</td>\n",
+       "      <td>175722990241658872256956</td>\n",
+       "      <td>208455790260919022988</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969797</th>\n",
+       "      <td>13845797</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>172504337928771085651749</td>\n",
+       "      <td>212356942060132803829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969798</th>\n",
+       "      <td>13845798</td>\n",
+       "      <td>0</td>\n",
+       "      <td>275947058460000000</td>\n",
+       "      <td>223198976410456758357</td>\n",
+       "      <td>0</td>\n",
+       "      <td>172504337928771085651749</td>\n",
+       "      <td>212356942060132803829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969799</th>\n",
+       "      <td>13845799</td>\n",
+       "      <td>391811678424399155226</td>\n",
+       "      <td>3900000000000001700</td>\n",
+       "      <td>3093834627989030657712</td>\n",
+       "      <td>498800693606030358</td>\n",
+       "      <td>172281138952360628893392</td>\n",
+       "      <td>212632889118592803829</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969800</th>\n",
+       "      <td>13845800</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>169579116002795997390906</td>\n",
+       "      <td>216034088424986775171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969801</th>\n",
+       "      <td>13845801</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3700000000000002000</td>\n",
+       "      <td>2847041201773387626234</td>\n",
+       "      <td>0</td>\n",
+       "      <td>169579116002795997390906</td>\n",
+       "      <td>216034088424986775171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969802</th>\n",
+       "      <td>13845802</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>166732074801022609764672</td>\n",
+       "      <td>219734088424986777171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969803</th>\n",
+       "      <td>13845803</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1204255672555673600</td>\n",
+       "      <td>906085166102727564276</td>\n",
+       "      <td>0</td>\n",
+       "      <td>166732074801022609764672</td>\n",
+       "      <td>219734088424986777171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969804</th>\n",
+       "      <td>13845804</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>165825989634919882200396</td>\n",
+       "      <td>220938344097542450771</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969805</th>\n",
+       "      <td>13845805</td>\n",
+       "      <td>0</td>\n",
+       "      <td>677592088322756234</td>\n",
+       "      <td>505497578245424541794</td>\n",
+       "      <td>0</td>\n",
+       "      <td>165825989634919882200396</td>\n",
+       "      <td>220938344097542450771</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969806</th>\n",
+       "      <td>13845806</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>165320492056674457658602</td>\n",
+       "      <td>221615936185865207005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969807</th>\n",
+       "      <td>13845807</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>165320492056674457658602</td>\n",
+       "      <td>221615936185865207005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969808</th>\n",
+       "      <td>13845808</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>165320492056674457658602</td>\n",
+       "      <td>221615936185865207005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1969809</th>\n",
+       "      <td>13845809</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>165320492056674457658602</td>\n",
+       "      <td>221615936185865207005</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            block                amount0In             amount1In  \\\n",
+       "1969784  13845784                        0                     0   \n",
+       "1969785  13845785                        0                     0   \n",
+       "1969786  13845786                        0                     0   \n",
+       "1969787  13845787                        0                     0   \n",
+       "1969788  13845788                        0                     0   \n",
+       "1969789  13845789  45598914832797630699516                     0   \n",
+       "1969790  13845790   4930032061697182061256  12071084298563895296   \n",
+       "1969791  13845791                        0                     0   \n",
+       "1969792  13845792                        0   6636305260866285568   \n",
+       "1969793  13845793   5379873916932590788066  15270927886500831959   \n",
+       "1969794  13845794                        0                     0   \n",
+       "1969795  13845795    332166678408919642610   2204986233670493184   \n",
+       "1969796  13845796                        0   3901151799213780841   \n",
+       "1969797  13845797                        0                     0   \n",
+       "1969798  13845798                        0    275947058460000000   \n",
+       "1969799  13845799    391811678424399155226   3900000000000001700   \n",
+       "1969800  13845800                        0                     0   \n",
+       "1969801  13845801                        0   3700000000000002000   \n",
+       "1969802  13845802                        0                     0   \n",
+       "1969803  13845803                        0   1204255672555673600   \n",
+       "1969804  13845804                        0                     0   \n",
+       "1969805  13845805                        0    677592088322756234   \n",
+       "1969806  13845806                        0                     0   \n",
+       "1969807  13845807                        0                     0   \n",
+       "1969808  13845808                        0                     0   \n",
+       "1969809  13845809                        0                     0   \n",
+       "\n",
+       "                      amount0Out            amount1Out  \\\n",
+       "1969784                        0                     0   \n",
+       "1969785                        0                     0   \n",
+       "1969786                        0                     0   \n",
+       "1969787                        0                     0   \n",
+       "1969788                        0                     0   \n",
+       "1969789                        0  54624835640149345578   \n",
+       "1969790  12227918575556074800253   5005352062942556724   \n",
+       "1969791                        0                     0   \n",
+       "1969792   6406902276717032296170                     0   \n",
+       "1969793  13229504248002106402496   6420108745716013110   \n",
+       "1969794                        0                     0   \n",
+       "1969795   1865882334299188750566    393602925405286658   \n",
+       "1969796   3218652312887786605207                     0   \n",
+       "1969797                        0                     0   \n",
+       "1969798    223198976410456758357                     0   \n",
+       "1969799   3093834627989030657712    498800693606030358   \n",
+       "1969800                        0                     0   \n",
+       "1969801   2847041201773387626234                     0   \n",
+       "1969802                        0                     0   \n",
+       "1969803    906085166102727564276                     0   \n",
+       "1969804                        0                     0   \n",
+       "1969805    505497578245424541794                     0   \n",
+       "1969806                        0                     0   \n",
+       "1969807                        0                     0   \n",
+       "1969808                        0                     0   \n",
+       "1969809                        0                     0   \n",
+       "\n",
+       "                         reserve0               reserve1  \n",
+       "1969784  153212210186396951314993  238716385955530719051  \n",
+       "1969785  153212210186396951314993  238716385955530719051  \n",
+       "1969786  153212210186396951314993  238716385955530719051  \n",
+       "1969787  153212210186396951314993  238716385955530719051  \n",
+       "1969788  153212210186396951314993  238716385955530719051  \n",
+       "1969789  153212210186396951314993  238716385955530719051  \n",
+       "1969790  198811125019194582014509  184091550315381373473  \n",
+       "1969791  191513238505335689275512  191157282551002712045  \n",
+       "1969792  191513238505335689275512  191157282551002712045  \n",
+       "1969793  185106336228618656979342  197793587811868997613  \n",
+       "1969794  177256705897549141364912  206644406952653816462  \n",
+       "1969795  177256705897549141364912  206644406952653816462  \n",
+       "1969796  175722990241658872256956  208455790260919022988  \n",
+       "1969797  172504337928771085651749  212356942060132803829  \n",
+       "1969798  172504337928771085651749  212356942060132803829  \n",
+       "1969799  172281138952360628893392  212632889118592803829  \n",
+       "1969800  169579116002795997390906  216034088424986775171  \n",
+       "1969801  169579116002795997390906  216034088424986775171  \n",
+       "1969802  166732074801022609764672  219734088424986777171  \n",
+       "1969803  166732074801022609764672  219734088424986777171  \n",
+       "1969804  165825989634919882200396  220938344097542450771  \n",
+       "1969805  165825989634919882200396  220938344097542450771  \n",
+       "1969806  165320492056674457658602  221615936185865207005  \n",
+       "1969807  165320492056674457658602  221615936185865207005  \n",
+       "1969808  165320492056674457658602  221615936185865207005  \n",
+       "1969809  165320492056674457658602  221615936185865207005  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "b = sorted_net_moves_df[\"block\"][0]\n",
+    "block_df[(b -5 <= block_df[\"block\"]) & (block_df[\"block\"] <= b + 20)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "eb2c5f5a-e202-4859-b07a-feb6f0def7e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: xlabel='block'>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "oracle_df[(b - 5 <= oracle_df.block)&(oracle_df.block <= b + 300)] \\\n",
+    "    .drop([\"vwap_30_x_per_y\"], axis=1) \\\n",
+    "    .plot(x=\"block\", figsize=(12,6))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "712e3be2-6522-4a85-a680-5b3a74b73063",
+   "metadata": {},
+   "source": [
+    "#### Interesting series of trades to come back to and look at\n",
+    "\n",
+    "price fluctuates betwee 0.01 ETH / POOL to 0.026 ETH/Poool "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "bce7bac7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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mvu+99x5//vOfOe644zCZTJx55pk888wzLfB0Dl/llW4Ky10AxIU2v1GyX4g1hAv6XcBLq1/i2Y7RvNwnn+w14WQ99TRhxx+PyWZrsccSn+rtV/tWQz341TqW7cyrdV2wzcydJ/djQFJEm6xPRERERERE2of9DnUmTZrU4NhrwzC4//77uf/+++s9Jjo6mvfff39/H/qI5u+nY7OYCA/a7z+2Bl3c/2LeX/8+Wyhi+TAPPTa7qUxJIf+DD4i+9NIWfSypuf2q9vXZxU5enb+9zvu8sWAHj509pLWXJiIiIiIiIu1Iu5h+JbX76RiG0cjR+yfCHsGlA3zhzX+TuxA9qAiA7Oefx11Q0KKPJTW3X9VOdcoq3IAvuHvlkhG8cskIbpnSC4A1e/TnICIiIiIiIrUp1GknMgurQp2wluunU9NF/S8i0h7JDncJ88d2wB5RibugkOz/Pt8qj3cks5h8/+z2bpTsdPlCniCrman9E5jaP4Hzj+4MwObMIkorXG27UBERERERETmktew+HjlgXq+XF37dyqpd+XXenpJfBkB8K4U6IdYQrhh4BU8sf4IXYqL4aHg6qT9FkPveu0Sedx727t1a5XGPRFWZzj6hTkVVqGO3VGetCeEOEsLtZBQ6WZtayMiu0W22ThERERERETm0KdQ5RKxPK+LR2RsbPa57XGirreG8vufx1tq3SCnL5OvTz2TChq8oTnWQed8Mkt/6sNUe90hTf6VO9farmgZ1jCSjMIPVewoU6oiIiIiIiEiAQp1DxKzVqQCM6BLFGcM61XmMw2pi2oDEVltDkCWI64Zcx78X/5vnc1dy/FkjKH52DcWLf6f4h28JnXJiqz32kaS+keZ1VeoADOkUwQ/rM1i9J79N1iciIiIiIiLtg0KdQ4DX62XW775Q54rx3ThpUIeDtpazep/FRxs/Ykv+Fl4ZOo3LB28g93cXGffOIOSY4zA04rzZzIZ/+lXdPXVsFnOt6wcnRwKwWs2SRUREREREpAY1Sj5INqQX8uumLH7dlMX7S3axJ6+MEJuZyX3iD+q6LCYLt428DYAPN39G8Yz7Mds9VGQ7yXv4+oO6tsOF2VR3qFNfpc6gjhEAbM8uUbNkERERERERCVCoc5C8Mnc7l76+hEtfX8KdM/8AYGr/BIJs5kbu2frGJI1hUvIk3F43/8meQ+wFJwCQ/b/5uNfMOcira/8s5sYqdWr/s4wKtgYulzjdrbw6ERERERERaS8U6hwkHSMd9O8QHvga2TWK6yb1ONjLCrh1xK1YTBYWpCzgj3NPxxYfjLvCRPZ9N0Nx5sFeXrtWb08dty+w2btSxzAMbGZT1TGeNlihiIiIiIiItAfqqXOQ/G1aH/42rc/BXka9uoR34aJ+F/Hm2jd5ZMXjvHfvv0m74a/kroXIVy7FfvNXYDr4VUXtUXVPndoBjbOy7u1X/usq3B6clarUERERERERER9V6hwm3C4PRbnllJdU4na1TDXHdUOuIy4ojl1Fu/g4dhehY4aD1yBz1gaY+58WeYwjUXVPndrX+6tw7JZ9wzL/lixV6oiIiIiIiIifKnXaudy0EtbNT2XDojScJdVNdE1mA6vDTHznMLoOjqXroFjCY4P269wh1hD+PuLv3DHvDl5Z/Qon/f05OPcKilMdFL3/JGHJR0OPY1v6KR32/D11XPVU6uzdU6fmdRUtFNiJiIiIiIhI+6dQpx1yVbjZuiKTtfNTSdtSPebaMMBb1abF4/biLHGxe30eu9fnMe+jzUQnhdB1UCxdB8WQ2D0Co6pipCEndTuJTzZ9wvKM5TyR/RG3X3oZua+/TsbycEI+uBzT9T9BzKHTC6g9MJt8Ac0+06/c9W+/UqgjIiIiIiIie1Oo047kpBazbl4qGxen4yz1VeUYJoOug2LoPz6JzgNi8Hq8VDrduCrclBVXsmd9HjvWZJO2tYDc1BJyU0tYMWcnnftHc9INgzHXESDUZBgGM46ewblfncv3O7/nrDOeIu6rWVRmZpH7eymxH14I184Fi60tfgSHhapCnX0aJfv75dRZqWNWqCMiIiIiIiK1KdQ5xBVklbFleQabl2WSs6c4cH1YtIP+45PoN7YDIZH26juYDF9QE2IlNMpBXHIYQ6d1prykkl3rctixOoftq7LYtS6XX9/fyOSL+2IYDVfs9Inuw3l9z+O99e/x0JqneOvWv5Nx2x1krwsjousmrItfgHE3t9aP4LDjr9Tx7B3qNKFSx6meOiIiIiIiIlJFoc4hqCi3nC3LM9myLIPMnUWB600mg65DYhkwPolO/aIxNWH7lJ8jxErvkYn0HpnIjjXZfPP8atb/lkZEfBDDT+ja6P1vOOoGvt3+LTsKd/D5sGyOGzmS0qVLyVgZTqeoR2HwuRCWeCBP94hjqWekuXrqiIiIiIiIyP5QqHOIKClwsnVFJpuXZpK+rXafnI59oug1IoHuR8XhCLU2+7G6Doplwrm9mfvhJhZ9vo3w2CB6jUho8D7htnD+Nvxv3LXgLl5c/RLH/+NpOH8FRXuCKM8owjH7Djj7zWav7UhQPf2qvp46+06/sivUERERERERkb0o1DmIyooq2Loyiy3LMkjZnA/+z/gGJPWMpOfweHoMiyc4vOX71Qya1In8zFJW/7SHH99cT1i0g8TuEQ3e59Qep/LJpk/4Pet3nsr7jFuOn0bhN9+SuymMpKiZMPBM6Hdqi6/1cFNfqNNwpY4v6HEq1BEREREREZEqCnUOkp/eXs+GRel4a3ywT+gWTq8RCfQYFk9olL2Be7eMcWf1ojC7nB2rs/nmhdWcdfuIBseemwwTd466k3O/OpfZO2Zz7skzCPnmWwp3hxA/uADL13+HLuMgOLrV196eWRqt1FGjZBEREREREWlcw6OPpNXYQ6x4PV7iOocx5oweXPzvMZx1+wiGHJfcJoEO+Hr0TL2iP7HJoZQVVfLVc7/jLK1s8D79YvpxTp9zALg7/x3sQwbjdXnI3Z0MxRkw5862WHq7Zq63p07906+qt1+5W3l1IiIiIiIi0l4o1DlIhhzbiQvvH805/xzJsGldCI+pv0KmNdkcFk6+YQghkXby0kuZ/fIfuBuZsHTLsFtIDElkT/Eefpnkq8rJXWfgKjPD7+/Dpu/aYuntVvX2q9o/54Z66gQaJWv6lYiIiIiIiFRRqHOQhEY5iIwPPtjLACA0ys7JNw7GYjezZ0Mev76/Ea/XW//xtlDuG3sfAE8HL8A8uD/e8gqyc8b4DvjiBijKaIult0vVoU7t6xvsqaPtVyIiIiIiIrIXhToCQFxyGMdfNQDDgPUL0lgxZ2eDx49NGsuYDmPw4GXhqd0ByFu0iwp7XyjJgpnXgkdbhepiabRSp47tV1aFOiIiIiIiIlKbQh0J6DoolvHn9AZg0efb2LQkvcHjz+97PgCvWhcRNG4suFxkpQ0FSxBs+1n9dephNvn+2e3TU8dVf08df6WOU9uvREREREREpIpCHall8OROHDUlGYAf31rPno159R57TKdjSApJIt+Zz7qzhgJQ+P1cyof9y3fA4hdg8cutvub2piqf2Xf6lauB6VdV1/m3aImIiIiIiIgo1JF9jD2jJz2GxeFxe/n2xTXkpBbXeZzZZA5U6/y37FtCj58GXi8ZHy/Be+w9voNm3w6b5rTV0tsFf6XO3qGOswmhjholi4iIiIiIiJ9CHdmHYTKYcnl/OvSIoKLMxVfP/U5JgbPOY8/pcw5R9ih2Fe1i9dlHYTgclC5aRGFuTxh6MXg98MnlkLa6jZ/FoctSz0jz6kqdBqZfqaeOiIiIiIiIVFGoI3WyWM2cdP1gIuKDKM518tVzv1NR7trnuGBrMJcNvAyA/2Z+QvQN1wGQ8cgjuMb/C7pNhMoSeP9cKExty6dwyKqeflV3pY6mX4mIiIiIiEhTKNSRejlCrZx60xCCwqxk7y5mzitr8dSx/ee8PucRZY9id9FufjsmFnuvXrjz8sh84ik4522I7QNFqfD+OeCseyvXkSQQ6nib3lPHrkodERERERER2YtCHWlQRFwwJ90wGIvVxK61Ofz6wSa8e4URwdZgLh94OQAvr3uNuHt9/XQKPv2MkjWb4MKPISQO0tfAp1ce8aPOA6GOu+nTr/xbstRTR0RERERERPwU6kijErtFMPXKAWDAuvmprJizc59jzu1zbqBa54fw3USeey4A6ffehyckCc7/ECwO2DQb5vyzrZ/CIaWunjoej5fKqpBHPXVERERERESkKRTqSJN0PyqOCef0BmDR59vYuDi91u3B1mCuHHQlAM+sfIbQm67FHBtLxbZt5L72GnQaAX96yXfw4hdh4fNtuv5DSXVPneqApmYFTp09dfwjzV1HdpWTiIiIiIiIVFOoI002eHInjpqSDMBPb68nbWtBrdvP73s+yWHJZJdl8+rOD0mYcQcA2S+8SMWOHTBgOky5z3fwnBmw+pM2XP2ho7qnTvV1zhoVOHWONFejZBEREREREdmLQh3ZL2PP6EmPoXF43F7mfrgRb40tRDazjX+M+AcAb697m7TRPQgZNw5vRQVp993n68Uz7mYY5ZuQxefXwe8fHoyncVBZ6qjU8VfgGEb17TVVV+oo1BEREREREREfhTqyXwyTwcQL+2BzmMneXcympRm1bp+UPInJyZNxeVzcMe8Oou68HcNup3ThIgq++MKXWhz/EBx1IXhcMPNaWPA07NV8+XBmNvn+2blqlOrUnHxlGPWHOmqULCIiIiIiIn4KdWS/BYXaGH5iVwAWfb4VV0V1nxfDMLh37L3EBsWytWArz2R+TOwNNwCQ8eC/qdi9G0wmOO05GHuT707f3wNz7gTPkRFYVO2kwl2jyslfgePfZrU3NUoWERERERGRvSnUkQMyeHInQqPtFOc5+f2n3bVui3ZE8+C4BwH4cOOHrD2+J0HDhuEpLibl1lvxVlb6gp1pD/q+ABb9F2ZeA66Ktn4qbc5fqeP21lGpY9138hVU99lRqCMiIiIiIiJ+CnXkgFhsZkaf3gOA5bN3UlZUO4wZ13EcF/W7CIB7Ft9H0AMzMIWHU/77arKeeab6wLE3wRmvgMkCaz6BV4+DnQvb7HkcDNU9dZpeqWPX9isRERERERHZi0IdOWC9RyYQ1zmMynI3S7/avs/ttwy/hd5Rvcktz+Vf258j8YH7Ach55VWK5y+oPnDwOXDBR2CPgPTV8MYJ8MnlkL97n3MeDvzTr+rsqWOtZ/uV2VzrOBERERERERGFOnLADJPB2DN7ArB2Xip56SW1breb7Twy4RHsZjsLUhbwVedsIs89F4CUW26hfMOG6oN7ToG/rIDhlwMGrP0MnhsBPz8ElWVt9ZTaRPVI85qVOr6+RI311NH0KxEREREREfFTqCPN0qlPFF0Hx+LxeFk4c+s+t/eM6snfhv8NgCeWPUHR9WcTPGIEnuJidl19ta9xsl9ILJz6FFw7F7qMB1c5/PowvDAOts9ro2fU+sx1bL9qrKeOP9Rxe7y17iciIiIiIiJHLoU60mxj/tQDw2Sw/fdsUjfn7XP7+X3PZ0LHCVR4Krh98V3EPPM49j59cGdls+uqq3Dl5NS+Q4fBcNlXcPZbENYBcrfCW6fAF3+Gsn3P3974e+q46uipY2+kUge0BUtERERERER8FOpIs0V3CKH/+CQAFvxvC969KkkMw+D+cfcT7YhmS/4W/m/tUyS//DLWjh2p3LmL3Vdfg7u4mL3uBAOmw42LYcSVvutWvgPPHQ3rvmiDZ9V6TIFKnepwpvGeOgp1REREREREpDaFOtIijj6lG1a7mcydRWxZnrnP7bFBsfznmP9gNszM2jaLj3O/p/Nrr2KOjqZ83Tr2/PkmPKWl+57YEQGnPAFXzIHYPlCSCR9fAp/fAM6iNnhmLa96+lX1dY311LGaDQyj6li3u1XXJyIiIiIiIu2DQh1pEcHhNoYd3wWAhTO34qrcN3g4usPR/HX4XwF4bOljrAnKIfmllzAFB1O6aBE7LryIytTUuh+g82i4bh5MuBUME6x6D14cD7uXtNpzai3mA6jUMQwjEPioUkdERERERERAoY60oCFTkgmJtFOUW86an1PqPOaS/pdwYtcTcXld/O2Xv5HZJYzkV30VO87169l+9jmUrlhZ9wNY7HDc3XDZ1xDRGfJ2wOsn+CZkuV2t98RamMXk+2dXV0+d+ip1oLqvjkIdERERERERAYU60oKsNjOjTusOwLJvd1BeXLnPMYZhcO/Ye+kT1Yfc8lyumH0FmT2i6PbJx9j79sWdk8OuSy8lf+bn9T9Ql7Fw/XwYfC543b4JWW+cALnbWumZtSx/buOuq1Gype7pV77bNNZcREREREREqinUkRbVZ3QiMZ1CqShzsfSb7XUeE2wN5qWpL9EzsieZZZlcMecK9oRW0PW9dwmbOgVvZSVpM2aQ8eh/8NbXP8YRAWe8DGe+BvYI2LMUXpwAK98F76E98ttsqh5P7heo1LE0UKmj7VciIiIiIiJSg0IdaVEmk8G4M3sC8MevKeRn1tH8GIgJiuG141+jV1QvssqyuHLOlex0ZdLx6aeJveF6AHJff53dN9yw72SsmgadBdcvgC7joKIYvrjR10i5NLfFn1tLqW6UXB3qBHrqNBTq+LdfuRXqiIiIiIiIiEIdaQXJ/aLpPCAaj9vLwplb6z0u2hHNq9NeDQQ7V8y5gi0FW4n7y19IevwxDLudkl/nsuO886jYtav+B4xMhktnwXH/ApMF1n8JL4yFrT+3wrNrPn+j5No9daqmXzUl1FGljoiIiIiIiKBQR1rJ2DN7YhiwbWUWKZvy6j0u2hHNa9Neo3dUb7LLsjnnq3N4cvmTWKdNpsu772KJj6diy1Z2nH0OJYsW1/+AJjNM+Btc9QPE9IKiNHhnOvx4P3gOrRHg/lAnq8hJ1zu+pusdX/PGgh1AYz11fLf5Q53U/DI2ZRRR7Gw/TaJFRERERESk5SjUkVYRkxTKgAkdAZj/yWY8nvr73EQ5onht2mtM6DgBl8fF63+8zqmfn8ovobvp8snHOAYNwl1QwK6rriLvww8bfuCkoXDtrzD8ct/38x6Hd8+AkpyWemrNlhwVTIcIxz7XW80Gw7pE1ns/W41GybP/SGfswz8x7cm5THjkJ0orFOyIiIiIiIgcaQyv9xDvKluHwsJCIiIiKCgoIDw8/GAvR+pRVlTBu/csoqLMxeSL+9J/XFKDx3u9Xn7d8ysPL3mYlGLfSPSRiSO5+6jbsf3nVQq/+gqAqAvOJ2HGDAyrteEFrP4EZv0FKkshvBNc/BnE9WmR59ZclW4PBWW1p4MFWc2E2C313uf8lxexcFsOz5w/lCXbc3h3UfWWtF9unUTX2JBWW6+IiIiIiIi0jf3JPFSpI60mKMzGyJO7ArDoi21UlDdcTWIYBpOSJ/HF9C+48agbcZgdLE1fytnfX8iPlw0k9pabAch7/wN2XX0N7vz8hhcw+Gy46keI7gGFe+CTy6CyvPlPrAVYzSZiQ+21vhoKdKBGpU6lm00ZtZtHt7tkVkRERERERJpNoY60qkGTOhERF0RZYQUrZu9s0n3sZjvXDbmOz6d/zugOo3G6nfxn+WP8vctv2P7zL4zgYEoXLWL7uefi3Fp/I2YAEvrDFXMgJB4y18GP97XAszo4ak6/2pK5V6jT/gruREREREREpJkU6kirMltMjK0acb7qh90UZpc1+b4dQzvy8tSXuWfMPQRbglmZuZJzCx5j7f9dhLVjRyp37mLHuedRPHduwycKjYPT/+u7vOh52PrTgT6dg8of6qQXlJNbUoFhgM3su66BlkUiIiIiIiJymFKoI62u25BYOvaJwu3yNDjivC6GYXB277OZefrMQNXOvRmv8/otfbAPG4qnuJjd111PzhtvNlyt0nsajLzKd/nzG6A0txnP6OCwVwU4a1MLAegUFUSw3T8tS6mOiIiIiIjIkUahjrQ6wzAYf3YvDAO2LM8kdUv+fp8jKTSJl6e+zB1H34HFZGFW7lxumZ4Pp04Fj4fMRx4h7c678FRU1H+SqQ9AbG/fuPNZN0M727Jkt/r+uf6RUgBA7/gwjKrb2tlTERERERERkRagUEfaRGynUPqN902/WvDJZrwHsF/IMAwu7Hchb53wFokhiWwv283FgxeQcfXJYDJR8Nln7Lrsclw59YwvtwXDGa+AyQLrv4RV7zfnKbU5/1arzCInAD0TQjEMX6yjTEdEREREROTIo1BH2syoU7tjdZjJ3FnE2vmpB3yewXGD+eSUTxjfcTxOTwU3xc7hp7+MwQgLpWzFCraffTblGzbUfeeko2Dynb7L394GOfu3Hexg8vfU8esdH4apqlTHo1IdERERERGRI45CHWkzweE2RpzUFYBfP9jIH3NTDvhckY5I/nvcf/nL0L9gMky8GLSYJ66Nx0juiCs1jR0XXEjh99/XfedxN0OX8VBRDP+7HFzOA15HW9o71OmVEApVG7CU6YiIiIiIiBx5FOpImzpqSmf6T0gCL/z6/kaWfLX9gMdxmwwTVw++mlemvkKMI4aF1l3ccF4RZcP64C0tJeWmv5Dz2ut13NEMZ7wMQVGQ9jv80D7GnI/oGo3V7AtxusYE0zshjKrdVwp1REREREREjkCtEuoUFRVxyy230KVLF4KCghg7dixLly4N3O71ernnnnvo0KEDQUFBTJkyhc2bN7fGUuQQYzIZTLqgDyNO7grA0q+28+v7G/E0Yyb30R2O5pNTP2F4wnCyLKVcPnULW6f2BSDzP/8h45FH8Xo8te8U0RGmv+C7vOi/sGnOAT9+W5ncJ55V90xjxd1T+eFvE3FYzdp+JSIiIiIicgRrlVDnqquu4vvvv+edd95hzZo1TJs2jSlTppCS4ttu8+ijj/LMM8/w4osvsnjxYkJCQjj++OMpLy9vjeXIIcYwDEad2p2J5/cGA9bOS2XOK3/gqnQf8DnjguN4ddqrXDnwSjwmgxkjtvD9Kb7GzLlvvEHqHXfgraysfac+J8Ko63yXZ14HWZsO+PHbSojdQnSIDUtV02QjMP9KREREREREjjQtHuqUlZXx6aef8uijj3LMMcfQs2dP7r33Xnr27MkLL7yA1+vlqaee4q677uL0009n8ODBvP3226SmpvL555+39HLkEDZwYieOv2ogJovBtpVZzHrmd5yllY3fsR4Wk4Vbht/Cc8c+R7gtnFcGZfL69FC8JhOFX85i9/U34CkpqX2nqfdD0jAoy4W3T4e8nc18Vm1L269ERERERESOXC0e6rhcLtxuNw6Ho9b1QUFBzJ8/n+3bt5Oens6UKVMCt0VERDBq1CgWLlxY5zmdTieFhYW1vuTw0HN4PKfedBQ2h5nUzfnMfHwlJQXNa1w8MXkiH5/6MQNjBjK7XzkPn2XgtlsomT+fXVddjdflqj7YYocLP4HYPlCU6gt2itKb+azajr9Ox6uh5iIiIiIiIkecFg91wsLCGDNmDA888ACpqam43W7effddFi5cSFpaGunpvg/MCQkJte6XkJAQuG1vDz30EBEREYGv5OTkll62HESd+kQx/e/DCAq3kZNSzKePLGfPhtxmnbNjaEfeOvEtzu1zLit7GNx9rhdXsJ2ylSvJ//Sz2geHxMIln0NkF8jbDu/8CcrymvX4bcWoKtVpRksiERERERERaadapafOO++8g9frpWPHjtjtdp555hnOP/98TKYDe7gZM2ZQUFAQ+Nq9e3cLr1gOtrjkMM78x3Ai4oIoyi3ni6dW8d1ra5tVtWMz27hr9F3cPvJ2tnQ0+HC87/qsZ57BXbzXNqzwJLjkCwhNhMx18OGF7WLUefX2K6U6IiIiIiIiR5pWCXV69OjBr7/+SnFxMbt372bJkiVUVlbSvXt3EhMTAcjIyKh1n4yMjMBte7Pb7YSHh9f6ksNPRFwQZ88YwaCJHcGAzUszeP9fi1j9855mTce6sN+FDI0fytdHuSiMD8Gdk0POq6/se2B0N7joU7CFwc4FMPNa2Htq1iEmEOoc3GWIiIiIiIjIQdAqoY5fSEgIHTp0IC8vjzlz5nD66afTrVs3EhMT+fHHHwPHFRYWsnjxYsaMGdOay5F2wB5s5Zjz+3D2HSOI7xJGRbmbeR9t4n8PLyNjx4H1UjIMg9tH3o7bbPDShDIAct94k8q0tH0PThwI570LJiusnQnf392cp9PqTFWpjip1REREREREjjytEurMmTOH2bNns337dr7//nsmT55M3759ufzyyzEMg1tuuYUHH3yQL7/8kjVr1nDJJZeQlJTE9OnTW2M50g7FdwnnzNtHMPH83tiCLGTtKuJ/jyxj0Rdbcbv3v3pmQOwATu9xOkt7GezsHorX6STzySfrPrj7JJj+vO/ywudg4fMH/kRaWaBRsjIdERERERGRI06rhDoFBQXceOON9O3bl0suuYTx48czZ84crFYrALfddhs33XQT11xzDSNHjqS4uJjZs2fvMzFLjmwmk8HAiZ248L7R9D46Abyw/NudfP74Cgqzy/b7fDcPu5lgawgvHOO7b+GXsyhbs6bugwefA1Pu9V2e809f1c4hyN8oWZmOiIiIiIjIkcfwtsN9G4WFhURERFBQUKD+OkeQzcsy+OW9jVSUubA5zBx3aX+6D43br3O8uuZVnl7xNH//xsqo38sIGjGcLu+8EwhHavF64Zt/wNJXwGzzjT7vPqllnkwLOfaxX9iWXcJH14xmVPeYg70cERERERERaab9yTxataeOSEvqNSKBc+8cSWL3cCrK3Xz70hp++2wLnv3YjnVx/4vpGNqRN8dX4LaaKVu2nKLvvq/7YMOAEx+B/qeDu8I3EStlRQs9m5ahRskiIiIiIiJHLoU60q6ExwYx/e/DGDIlGYCV3+3ii6dWNXn0ud1s5+8j/k5OuMGsUb6//hkPPoi7sJ4mzCYznPEKdJsIFcXw3lmQvblFnktLCGy/UqojIiKNcHu8fL06jbd+28Fbv+3g3UU7ySwsP9jLEhERkWZQqCPtjtlsYvxZvTj+6oFY7WZSN+fz8f8tJW1LfpPuP6XzFEYljuKT0R7y4oNxZWWR8fAj9d/BYofz3oMOR0FpDrzzJyhIaZHn0lyBRsmq1RERkUb8sjGTG99fwb++XMu/vlzLXZ//wT1frD3YyxIREZFmUKgj7VbP4fGcPWMEUYnBlBZU8PkTK/n9x92Njvc2DIN/jvonXruVJ4534jUMCj77jOJ58+u/kz0MLvoUYnpCwW549wwozmzhZ7T/TKrUERGRJkor8FXlJIY7GNElCoCs4qZVuoqIiMihSaGOtGtRiSGcdccIeo2Ix+PxMv+TzXz36loqyl0N3q97ZHcu7X8pGzsZzB0dAkDaPffgLi6u/04hsXDxTAhLgqwN8PoJkL+7JZ/Ofgv01FGoIyIijSivdAMwuns0N07uCUDlfvSlExERkUOPQh1p92wOC1OvHMCEc3thMhlsWZ7J/x5eRm5aSYP3u2bwNXQI6cCrY8sojQ/HlZZG5n8ea/jBIjvDZV9BRDLkboUPLwB3wwFSW9D2KxERaUxZhS/UCbKZsZp9bwErXAp1RERE2jOFOnJYMAyDwZOTmf73YYRE2MhLL+WTh5exeVlGvfcJtgZz+9G347QZPD6tDID8jz6iZNHihh8spgdcMRsckZC+2jfy/CDxb7/yKNMREZFGlFVV6jisZqxm3+uHKnVERETaN8vBXoBIS+rQI4Jz7jya7177g5SN+Xz36lqydhUx5k89ApOiajo2+VhO7Hoi3/Itv4ywM2mZk7S776b7F59jCg6u/4EiOsGUf8FXf4Wf/u0bex6e1IrPrG7V26+U6oiISMP8oU6Q1YzV4vu9XqW7/tcPr9fL2wt3siu3tEnnD7VbuGJcNyKCrc1frIiIiDSJQh057ASH2zjtL0ex+MvtrJizk5Xf7SIs2sGgSZ32OdYwDO4fdz97ivfwxjGrGbLZQtTu3WQ9/TQJM2Y0/EDDLoNV78OepTB7BpzzVus8oQYEQp02f2QREWlvymuEOjazP9Spv1JnyfZc/vXl/k3HsllMgX49TeVye/hhfQaF5S56xocyrHPUft1fRETkSKZQRw5LJrOJMX/qgT3EwsLPtjL/483EdAwlqVfkPsc6LA6eOfYZzv/6fJ4/PpU7P4bct98h7PgTCB42tIEHMcHJT8DLE2Hd57D5B+g1pdWeU10MlOqIiEjT1NVTp6FQZ8WufAD6JoYxqU98g+dem1rAvM3ZrEst3O91fbh0N3d9/gcAJgMWzTiO+HDHfp9HRETkSKRQRw5rQ6d2JmtXEVuWZTL75TWc88+RhEbt+0YxNiiW5459jkucl/DzoCImr/GS9s9/0m3mZ5iCgup/gA6DYdT1sOi/8M3f4YZFYG3g+BZmqsp0PNp+JSIijSitFer4XkAaapS8ek8+ANOHduS6iT0aPPcvGzOZtzmbjRlF+72ub/9IC1z2eCGj0KlQR0REpInUKFkOa4ZhcOzF/YjpGEpZUSXfvvQH7sq638D2ie7DI8c8wjvHmckNhYodO8h88snGH2TyDN+Y87wdMO/xln0Cjanaf6VMR0REGlOrp4658Z46q/cUADC4U0Sj5+6TGAbAjuwSnC53k9dUWF7J4m25QPWW4vL9uL+IiMiRTqGOHPasdjMnXjcIe7CFzB2F/PrhxnobC09KnsSV427mxZN8/zTy3n6Hoh9/bPgB7GFw4sO+y/OfgqyNLbj6hvlbPyvTERGRxtTqqVPVKLminu1X2cVOUvLLMAwY1LHxUCcx3EGY3YLL42V7dkmT1zR3UxYuj5fucSH0TQyvtU4RERFpnEIdOSJExAUx7aoBGAasX5DG2nmp9R575cAr6TDlZL4d7otM9tx6K+UbNjT8AP1Og17TwFMJX/4FPG0zIlbbr0REpKkCI81r9NRxe7y4Pfu+hvi3XvWICyXM0fg0K8Mw6F1VrbMpo7jR411uDz+uz+CDJbsAmNovAYfVtyZ/7x8RERFpnEIdOWJ07h/D6Om+ngDzPtpE2pb8Oo8zDIP7x97P0nMGsrqrAWXl7LruOlzZ2fWf3DB8TZNtobB7ESx7rRWeQd1rBW2/EhGRxgUaJVure+pA3c2Sf9/d9K1Xfr0TQgHYlN54X51Plu/hyreWsWBLDgDH9UvAYTEDUN5Anx8RERGpTaGOHFGGTutMj2HxeNxeZr/8B8V5zjqPc1gcPDnlGd46P47UaHCnZ7D7zzfhcdZ9PACRyTDlXt/lH+6F/F0tvv69Vb8lV6ojIiINK6/qKVezpw7UHeqsTa0KdZqw9cqvd4KvUqcpzZJ/350PQNeYYK4a340RXaIClTrafiUiItJ0mn4lRxTDMDj2kr7kZ5SQk1LCty+u5k+3DsNiNe9zbGJIIg+d9Awz8i7lvjedsGoV6ffcQ4eHHw5UyOxjxJWw5n++ap2v/goX/q+682OrPB/ff+uonBcREakl0CjZtneos++LSH5pJQCJEU2fQtWnKtRZsj2Xmz9cWecxDouZ6yf1YFtV351bpvRm+tCOgXUBOBXqiIiINJlCHTni2BwWTrxuMJ88vJTMnUX88MZ6pl01AJNp3/BlSNwQrjv1fp7Mn8E/P/JQ8MWX2Lp2Jfb66+s+uckEpz8HL4yDLT/Ayndg2CWt9ly0/UpERJqq5vYrs8nAbDJwe7x1Vur4r6sZ/jSmb4dwrGaDgrJKvlhVf+86t9fLtixfqNM9LiRwvX/7VZlCHRERkSZTqCNHpIi4IE64ZhCznlnF1hWZzP/YxjHn9a7z2NN6nMbmUzbzRu7rXPWdh6ynn8FwBBFz+WV1nzy2F0z+J/zwL/j2DugyDmJ6tMrzqJ5+pVRHRETq5/V6qxslV1WnWs2+UKeijh42zqrr/FOymiI6xMY7V47ij5SCOm/fmVPKO4t2smBLNtnFvu3M3WKrQx171br828RERESkcQp15IjVqU8UUy7vz3evrWXNL3tI6BZOn1GJdR57y7BbuDF/Mx+VzePceR4yH3kES2wsEaeeUvfJx94Em7+HnfPhs6vhijlgbnx6yP7yb79SpY6IiDTEWSO48W9zsppNlFd6WqxSB2B09xhGd4+p87asIifvLNpJWkE5APFh9lqTtdRTR0REZP+pUbIc0XqNSODoU7oB8OsHGynIKqvzOLPJzKPHPMryk7rzxShfkpJ2112Urfmj7hObzHDGS+CIgJTl8OujrbJ+U1Wqo5HmIiLSkNIaY8KDqipibFWBTV09dfzX7W+o05C4MDsdI4MC39es0qm5Lm2/EhERaTqFOnLEG35iVzr0jKCy3M33r6/FU8dvLAHCbeE8e+yzzJoWwfIeBl6nk91//jOurKy6TxzRCU550nd53mOwa1GLr70VezCLiMhhxB+U2CwmzFU95KyBUGff1z3/liz7fmy/aoqaI9K7x4XWus2h7VciIiL7TaGOHPFMJoMpl/fHFmQhY3shS7/eUe+xXSO68tzU53ntzDD2xIA7I4M9f7kZb0VF3XcYeCYMPg+8Ht82rPK6+wwcKAM1ShYRkcbVbJLsZ7X4XkMqWnD7VWOGJEcGLveIq12p499+pelXIiIiTadQRwQIjwli0gV9AFj+7Q5SN+fXe+zQ+KE8ccqLPHamhRI7lK1cSd5HH9d/8pP+A5FdIH8XfHNbi667eqS5Uh0REamfv09NzVAnsP2qjkbJFYFQp2VLQmtX6uwd6lRV6rgU6oiIiDSVQh2RKr1GJtB3dCJeL3z/xlqcpZX1Hjs0figDh03j/Um+f0LZL76Ip7S07oMd4XDGy2CYYPWH8MenLbZmjTQXEZGm8G+/8jdJhprbr/Z9EfFvv2rpSp1BHSOo2v1Fj723X/lHmlco1BEREWkqhToiNUw4rzfhcUEU5zr58a31eD31pyXXDL6Gn4YYpEeCOyeH3Hferf/EnUfDhFt9l2f9FfJ3t8h6q0eai4iI1M8flDhqVupY6u+p47+upXvqhDms/N+fBnHHiX3pErNXpY5NPXVERET2l0IdkRpsDgvTrhyA2WJi++/ZLP5yW73H9onuw8Sux/HJBN8/o5zXXsNd0EDPnIm3QccR4CyA/10B7vorgZqqeqS5Yh0RkSNBsdPFrN9TKXa69ut+gUoda/VbP38Vzt49ddweL/7fabR0pQ7AeUd35rqJPfa53lEVIGn7lYiISNMp1BHZS0LXcCZfVNVfZ/ZONi5Or/fYa4dcy/z+BrviDDyFheS8/kb9JzZb4azXwB4Be5bAj/c1e60mbb8SETmivPXbDm76YCVv/bajzts/X5nCje+t4JYPV3Lb/37nzplr+L9v1rM+rRDYe/uV7zVk70qdmt9bW7hSpyGafiUiIrL/LAd7ASKHoj6jO5CbVsKKObv4+Z0NRMQHkdgtYp/j+sf0Z0LniXx4zC/c9qmX3LffJvrii7DExtZ94qiuMP2/8NFF8Nuz0GUc9DnxgNdZvf1KqY6IyJEgo7AcgJT8sjpvv3PmGkoa6ElTa/pVPSPNnTUaJ9taoVKnPtWhjip1REREmkqVOiL1GH16D7oOjsXt8vDtC2soziuv87jrBl/Hsl4GW5IMvGVlZL/0csMn7ncqjLred3nmdb6pWAeoevvVAZ9CRETaEX9vnKLyfbdfOV3uQKDzj+P7cNsJfThreKdaxwTZqn+f5w9sKlwNVOq08PSrhgQp1BEREdlvCnVE6mGYDKZe0Z+YjiGUFlbwzQtrqHTu+0ZzUNwgpnadxvsTfW988z/8kMqUlIZPPvV+SBoG5fnwyeXgqjiwNValOg30cxYRkcNIeVUAU1S+b1+2mkHPdRN7cMOknlxzTPdax9TdU6f2i0hljXHm/teZtuCoWptCHRERkaZTqCPSAJvDwknXD8YRaiVrVxE/vrWuzolYNw+7mQ3dbKzpYuCtrCTruf82fGKLDc5+AxwRkLLsgPvraPuViMjh7cnvN3Hxa4u54b3l7MopDQQexXVU6hSW+YKeMLsFc9Xc8I6RQbWOqbX9yj/9aq9KHX/lTltuvQL11BERETkQCnVEGhEeG8SJ1w3CZDbYuiKLpV9v3+eYLuFdOKv3WXww0fdPqmDmTMpWrWr4xFFd4fTnfZcXPgcbvt7vtWn7lYjI4SuryMnTP25m3uZsvlmTzqcr9gRCnbq2X/mvC3NUb7EKsVuIDLYGvnfsR6PktmySDGCvqtQpq3RrqqOIiEgTKdQRaYKknpFMvMA3EWvp1zvYvCxjn2OuG3IdqV1C+Hmw701y2n3343U1MnK23ykw+kbf5c+v3+/+Ogb+6Vd68ysicrjZe2x5sdOFs7Lx7VdhDmut62tW69Ss1LHV0yi5wuV7TWmNceYNcdRYm9Olah0REZGmUKgj0kT9xyUxZEoyAD+9tZ6clOJat8cExXDFwCt4d7KJkiATzvXryXv/g8ZPPOVe6Dgcygvg+3/t15pMVf+CFemIiBx+9u4tU1bppqzBSp2q7VeO2sNNk+oJdRrrqdPW269qrs2pLVgiIiJNolBHZD+MPaMnnftH46r08P3r63Dv9abz4v4X44iJ572Jvu+znn6ayszMhk9qscGpT/sur/0M0v9o8nqqK3WafBcREWknyvYKdcor3NU9dSpcePbq8VZYT6hTq1LH1vhI8wp/qNPG26+sZlOgF1C5S82SRUREmkKhjsh+MJkMjr20H45QKzkpxSz+clut24Otwdxw1A38OMRgW0cLnpISMh9+uPETJw6CAX/yXf75301fUKCnjlIdEZHDTXlF7WCjtMIdCDu8XiipqF2t46/eCQ+qvf2qU1R1qOOo1Si5qqdOja1OHo838H1bjjP3c1QFSWUVCnVERESaQqGOyH4KibAz+aK+AKz8YRd7NubVun16z+l0i+rBS9O8eA2Dwm++peiXXxo/8eQ7wTDBxm9g+9wmrcWkkeYiIoetvSt1yirdtSZD7b0Fq7CORsnQ9J46j87ewLAHv2d7TgnQ9j11oMYELFXqiIiINIlCHZED0P2oOPqPTwIv/PjmOspLqhtWWkwWZoyawfZEg69G+kKX9Hvvw11cXN/pfGJ7wYgrfZe/vR3cjTRZpuZIcxEROdzsPdq7rMb2K9g31KnuqbNXo+SopvXU+XVTFvmllSzf6ftlRVtvvwKNNRcREdlfCnVEDtC4s3oSERdEcZ6TuR9uqnXb6A6jOa3HaXx0jEFOtBVXejpZTzzR+Ekn/xOCoiBzHSx7vdHDDW2/EhE5bNVVqeOsValTewJWXSPNoXaljrnGlqq9e+r4tzwVlrlq3d6WHFVjzfduEi0iIiJ1U6gjcoBsDgtTLu+PYTLYvDSDTUvSa91+64hbCQ6N4r/H+96Y5r3/AaUrVjR80uBoOPYu3+Wf/w0lOQ0e7t9+pUxHROTw4w91IoN9lTfFTlegiTFA0V4jzwvL6q7UiQ6xVd+nRnWPv2eOP9Qp9Yc6VWFRW0+/gupKnb0DLREREambQh2RZkjsHsGIk7oC8OsHmyjKLQ/cFuWI4raRt/FHVxO/DvH91jTtrrvxOJ0Nn3T45ZAwCMrz4acHGjy0evuVUh0RkcONv1GyP5TJK62odfu+26+qGiXvValjGAanDO5AXJidib3jAtf7t1dVhzq++/vDoYO5/cqpUEdERKRJFOqINNOIE7uQ0C2cijIXP7yxrtaI2VO6n8KoDqN4c7KX4nArFdu2kf3iiw2f0GSGEx/xXV7+JuxeUv+xge1XzXsOIiKyf16eu5Vr31m2zzjwluSvVokO9oU6BWV7b7fa63un7/vwvSp1AJ49fygL7ziWiBqTsQI9dVzeWo/nD3UOxvSrIPXUERER2S8KdUSayWQ2MeWy/ljsZlI357Pqh12B2wzD4J7R9+AKdfDScb43yzmvvEr5hg0Nn7TrOBhyPuCFL26EyvI6DzOqUh1lOiIibevluduZszaDdamFrfYY/r4y/kqdvQP8+ip19u6pA77XI8te26lqTr/yffkewD9FSz11REREDn0KdURaQGRCMBPO7gXA4i+2kb2nKHBb5/DOXDfkOhb3NbGinw1cLlL/cVvj27CO/z8IiYfsTTD30ToPMVX9EtWjUh0RkTblr5LZO1hpSf7KmahgW523712pU19PnfpYa2y/8vfTAV/vHjg426/s6qkjIiKyXxTqiLSQfuM60HVwLB63l+9fX4erxhvkSwdcSu+o3jw/1U1ZmA3n5s1kPflUwycMjoaTH/ddnv8UpK7a5xBD269ERNpcpduD0+XbHlTsrGzk6APnr1aJCqk71CmuESh5vd7qnjpB+1bq1MVWo1FyWcW+IcpBaZRs0fYrERGR/aFQR6SFGIbBsRf3JSjcRm5qCQs/3xq4zWqycv/Y+ykONfP08b433blvvknJokUNn7T/adB/Onjd8MWfwV37w4NB2/c7EBE50pXUmDpV2JqVOoFGyXVX3tSsEiqv9OCq6unW5EqdQE8dT6BJcl23t6WDsf1q+c5czn7xN057bj6nPTef815eyNrUgjZ7fBERkeZQqCPSgoLCbBx7cV8AVv+0h93rcgO3DYgdwKX9L2VFLxNzhzsASL1jBu6CRt44nvQfCIqGjDW+ip0aTFX/gms2ZxYRkdZVXCPUKW6D7VfBNgv2OrZC1QyU/FuxTAaE2MxNOn8g1HF7a22/8jsY268CjZJd+65n+c48vl+XwZo9+xe4lFe6+dPzC+h392yGP/A9v23JDtzm8Xi5c+YfLN2Rx+o9BazeU8Cibbl8ujyleU9ERESkjSjUEWlhXQfFMvCYjgD8+NY6yourq2v+PPTP9IvuxyuTKsmLdeBKTyf9/obHlhMaXz0Na+6jkLm+xo1qlCwi0tZKnPv2n2kN/i1IQVYzwXUENTV76hRWXQ61WzCMplVxWms0Sq6rh83BqdSpCnX2Cpm+XZPGmS/8xtVvL+PU5+bz++78Jp9zbWoBK3flU1bpJqekgls+WkVeiW88/Jy16WxILyLUbuGVS0Zw5rBOQO1qLBERkUOZQh2RVjD2rJ5EJgRTUlDBL+9twFvV9MZmtvHIMY9gCg7mPydV4jUZFH79NQVffd3wCQedDb1PAHeFbxuWx/dmVz11RETaXs0+Oq0Z6viDFofVHKhgqanm9qvCwOSrpm29ArBZqnvq1FmpcxBGmldvv6ruqeP2eHn8+00AgYql79dlNPmcWzKLARjRJYoecSFkFjk59bn5nP7fBfxz5hoArhjXlan9E+ifFA5AqRo1i4hIO6FQR6QVWG1mpl7RH5PJYOvKLNYvSAvc1i2iGzOOnsGWjgafjvP9E0y/7z4q9uyp/4SGAac8CfZwSFkGi17wXV11s6ZfiYi0neIalTp7T6BqSf6+MkE2E44alTr+keU1A6XqJslND3UClTouD2V19NQ5GNuv/JU623NK+G5tOt+tTefZnzazJbOYcIeF20/wbXGeX2MLVWO2ZpUAMLBjBE+fNxSr2WBPXhm/784nr7SSyGArV47vDhCoiKqrcbSIiMihqGnjEURkv8V3CWfU6d1ZOHMr8z7aRGKPCKI7hAAwved0fkv9jf95vmXkTgdddhWR8re/0/XddzBsdU85ITwJpj0Is/4CPz0AvU/AZGj7lYhIWyupI0xpDf5gwbHX9qu4MDtF5a5agZL/sj/waYrGeuocjO1XwTbf+pdsz2XJ9txat109oTsnDkrk/q/WsXpPPgWllUQENx5iba2q1OkRH8rAjhF8e/Mx7MwpCdzet0N44DyBUKdS269ERKR9UKWOSCsaOrUznfpG4ar08N1ra3FV+rdNGdw56k6igmN55JRKKoNtlK9eTe7bbzd8wmGXQPdJ4CqHz6/DRNWbcFXqiIi0mZrNkdti+1XQXtuv4kLtgC9Q2pJZxJbMIrZVVaOEH0CoU9/2q4MR6kzpH8+UfvEM7RxZ6+vkwR24Ynw3OkQE0SMuBI8XFm5rWrXO1qyqUCfO94uVnvGhHNcvIfDVMTIocKy/Uqiun4eIiMihSJU6Iq3IMBlMubw/Hz6whJw9xSycuZUJ5/QGINIRyV2j7+Kvv/yV1ya7ue5ryH3rbaIuuQRTfdU6hgGnPQcvjIU9Sxnv+YC3mKBKHRGRNtTc6VdOl5u1qYW465hcGBlkpVdCGFCjUbLNTJCt+i1bXJgv1HF5vEx5Ym6t++9XT52ajZLrCnUOwvar+DAHr146ssFjJvSKY2tWCU/9sJk5a6t768SG2vj7tD6BYAZ8P+tduaUA9IwLbfTxtf1KRETaG4U6Iq0sJMLOcZf04+vnV7P6pz0k94um66BYAKZ0mcL0ntOZ5Z7JufNMRGVlUTjrKyLPPKP+E0YmwwkPwxc3MDntVfoYXfB4e7TRsxERkeZuv7r9f6v5fFVqvbe/fPFwpg1IDPTUcVjMBFmrA5bYUDvTj0ri101Zte7nsJo5ZXCHJq/D2kijZPtBqNRpikl94njztx1sSC9iQ3pRrduGJEdyyuCkwPc7c0rxeCHMbgmEYQ2p3n6lUEdERNoHhToibaDr4FgGTe7Emp/38NPb6zn3rqMJifC9ufznqH+yLmcdXw3fwMU/Q87rrxPxp+kYpgbeTB91AayfhWXTtzxufZHZ7vFt9Eya5v++Wc9PGzJxWE3869QBjOwafbCXJCLSYmpV6jhd7MwpYe6mrEDVZEK4g6n9EjCZ9p0elVXk5KvVvub53WJDqHlEdrGTwnIXa1MLmdo/oXr7la329iu71cRT5w1t9vOo3n7lpbSORsn+0OdQM7F3HM+cP5TMwvLAdV/+nsrqPQWkF5TXOtbfT6d7fGiTRr0HWX1vjbX9SkRE2guFOiJtZOwZPUjdlE9OSjE/vrmOU286CsNkEGQJ4h8j/8Ff0q7izN+ArVsp/OZbIk45uf6TGQac+jSlTy1gIDsoSHkDeKKtnkqDKt0eXp67LfD9h0t2K9QRkcNK7alTldz4/gr+SCmsdcyUfvFcPaE7sWF2etTY9vPZij24PF6Gdo5k5g3jat3nie838cyPm8kudlLp9ga2ZzmstbdfOSz7jjc/EDV75hTWMcXrYPTUaQrDMDhtSFKt61Lzy1m9p4CsYmfguvSCchZs9fXd8ffTaUyQtl+JiEg7c2i+WoschixWM9OuHIDFamL3+jxW/bA7cNuoxFEkJnTny1G+f5LZzz6L19VISX9YAt92+QcAY1LehJQVrbX0/eJy1+4RkVlUXs+RIiLtU8lelTpbqqpBjusbz4kDE7FZTPywPpNzX17ElCd+5beq8dter5ePlvr+33/eyOR9zhsb6uunll3spNxVHSrs3Sg5yNYyoY6tRmhTULZvqGM7REOdusSG+X52OcUVgO+155j//My7i3YB1ArWGuLfflVa4cKrIQQiItIOtJ9Xa5HDQHRSCOPO7gXAoi+2krnT95tdwzA4v+/5fDPCoDjERMXOneTPnNno+TbETGGWe7RvCtbM66Dy4AcolR5Pre+zipz1HCki0j7VrNTxeKsbGv/3wmG8cNFwPrt+LEd3iyY+zI7XC//37Xo8Hi//W76HbdklhNjMtfq++MVWTbXKKa6gvKpSxGSA1WzUGmnuaKEGxlZz9XakukKdg9Eo+UD5f3bZVZU6G9KKqHB5sFlMHJUcyal1/Lzr4g/MPF6ocHsaOVpEROTgaz+v1iKHiQETkug+NA6P28t3r62loqrJ5mk9TsMaGs6no33HZT3zDO7ikgbPZRgGd1deTrE1BrI3ws8PtvbyG7VvpY5CHRE5vNQ1xjwmxBaYujSwYwQfXzuGb2+eQKjdwh8phdz/1Tru+vwPAK6b2IMQ+7474GsGEzXHmRuGUas6p+Z0p+Ywmwz8bWbafaVOjSonINBbZ0z3GD6/cRydY4KbdJ6aFVHagiUiIu1B+3m1FjlMGIbB5Iv6EhplpyCzjB/eWIfH4yXEGsJF/S9i9nCD7Bgb7qxscl5+ueFzAfmE8XXXO3xX/PYcpK5q9efQENdev9nMLamgwqXfdorI4aPEue+H/cQIxz7XxYTauXpCdwDe/G0HTpeHSX3iuHFyzzrPGxNavYWoZpNkqB3ktFSoYxhGoG9OnaFOe6zUKfJtv0qrCnU61PHn0hCr2RSoYFKzZBERaQ/az6u1yGHEEWLl+KsHYraY2P57NotmbgXgwn4X4nCE8tpk32+Bc998k4o9e+o9j3+Sx6aI8TDwLMAL398NB7EPQGVVY0+b2YSlavJLdrGqdUTk8FFXpU594cE1x3TnotGdmdo/gcvGduWpc4+qcyoWVAcTRU4X+aW+kMUf4NTafmVtubdv/mqcgtL20yi5LoGtayVOvF4vaQVlAHSICNrvc/mrdRTqiIhIe9B+Xq1FDjOJ3SM49tK+AKz8fhfp2wuIsEdwQd8LWN7TYEvPYLwVFWQ+9ni95/CXzXu9wHH3gNkG2+fC5u/b4BnUzV+pYzUbxIX53mRrC5aIHE78oU7NbKa+8CDIZubB6YN45ZIR3HvaACKDbfWeN9xhCYQsKXm+UMIfMAS1QqUOVPfVKSyvY6S5+dAcaV4Xf5VTpdtLYZnrgCt1AIKrJo2VVyrUERGRQ1+Lhzput5u7776bbt26ERQURI8ePXjggQdqTRDwer3cc889dOjQgaCgIKZMmcLmzZtbeikih7zeIxPpMzoRgHkfbsLr8XLZwMuIcETy4kQnXpNB0ezZlC5dWuf9/W+3vXghqguMutZ3xff3gLuR6VmtpLKqp47FbCLeH+oUHvwGziIiLcU//cofXEPd26/2l2EYgXBid14pUB3gtEZPHWh4i5W9HW2/slvMhDl8YUxWsTNQqXMgfy7VE7AU6oiIyKGvxV+tH3nkEV544QWee+451q9fzyOPPMKjjz7Ks88+Gzjm0Ucf5ZlnnuHFF19k8eLFhISEcPzxx1Nerg9+cuQZ86ceWB1mMncWsX5hGuG2cK4edDW74g0WDPf95jf9/gfwVu5bGm+qKtUJZKYT/g6OSMhaD6vea6NnUJvLU7NSx/dmWpU6InIweTxeyivdVLbANCO3xxv4sJ8YXh0YHEhFSF38oc6eNqvUqf1WMCLIWu9th7q4Go2m/ZU6SZH7/+fisFaPNRcRETnUtfir9W+//cbpp5/OySefTNeuXTnrrLOYNm0aS5YsAXxVOk899RR33XUXp59+OoMHD+btt98mNTWVzz//vKWXI3LIC4mwM/LkbgAs+nwrztJKzut7Hh1DO/L6WCcVYQ6cmzeT88ab+9y3evtVVaoTFAUTb/Nd/vn/oKLh6VmtwT/9ymwyiA9XpY6IHFxOl5tpT82l792zGXLfdyzZntus85XU+KBfswqkJSp1oLo3zO7cqkodW12VOi3fU8cvJqR6e1h7C3X8P7tdOaUUVW0nSzyAnjr+Sh1NvxIRkfagxV+tx44dy48//simTZsA+P3335k/fz4nnngiANu3byc9PZ0pU6YE7hMREcGoUaNYuHBhned0Op0UFhbW+hI5nAye3ImoxGDKiipZMms7drOdO46+g+Jgg1cn+d5UZv/3v1Ts3l3rftXbr2oYeRVEdoHidN80rDbmqmqUbDHV2H6lSh0ROUh255axJbMY8G2nWbQtp1nn82+9spoNokOqt18dSEPeusRUnbO6UsdU9d8aoY6l9Sp1ottzqBPmW/ualAIAwhwWQusYHd8Yf4BWpp46IiLSDrT4q/Udd9zBeeedR9++fbFarQwdOpRbbrmFCy+8EID09HQAEhISat0vISEhcNveHnroISIiIgJfycnJLb1skYPKbDEx4ZzeAKz5NYWclGImJU9iUvIkfhngYWevcLxOJ+n33V+rP5W/VMdT8zqLHab8y3d5wdNQlNFWTwOo3Sg5XtuvROQgq3DV3nJV1+Sq/VFcVQESYrcQ7qgODFpq+5U/mEjJ32v7VY1KnZqXm6trbHCt72uGOu1ppDlUB2L+UOdA/0zUU0dERNqTFn+1/vjjj3nvvfd4//33WbFiBW+99RaPPfYYb7311gGfc8aMGRQUFAS+du9VrSByOEjuH033o+LwerzM+2gTXq+XO46+A4cliCcml+CxWiiZP5/Cb74J3MdUc/pVTQPOgKRhUFkCvzzUdk+CeholF2n7lYgcHBXuFg51qu4faq+uAokKtrZYn5vYGtU/UM9I8xas1BnRJTpw2TAgqsZ0rr23Zh3q/Nuv/qgKdQ5k6xVUB2nafiUiIu1Bi79a/+Mf/whU6wwaNIiLL76Yv/71rzz0kO+DZWKib9JPRkbt6oGMjIzAbXuz2+2Eh4fX+hI5HI07qydmq4mUTflsWZ5Jx9COXD34atJiDL6e4PuNY8ZDD+Ou2oJoVG3A2jvTwTBg2oO+yyvehqyNbfQMqhslW2r11FGljogcHHtX6pQ0M9Qpcfo+6IfaLYFpSwcaHtTFX6nj5w91QqoCJMMAh63l3r4N7xpV/VgWc60qoPY00hyqf3b+bcBJB1ipE1Q10lyVOiIi0h60eKhTWlqKyVT7tGazGU/VB71u3bqRmJjIjz/+GLi9sLCQxYsXM2bMmJZejki7Eh4bxLBpnQH47dMtVDrdXDbgMrqGd+WD4WUUdQjHnZ1N5hNPADUbJddxsq7joM9J4HXDD/e2zROgulGy1WwKbL/KLnby5e+pzPo9lfVp6oklIm3H6ar9wdy/fepAFTt9kwhD7BY6RPrCnB5xIc06Z00xe1Xq+EOWcIeVfxzfh3+e2A97C1bqDEyKCFwuq3QHQiST4au4bE/8lTp+B9q8Olg9dUREpB1p8VfrU089lX//+998/fXX7Nixg5kzZ/LEE0/wpz/9CQDDMLjlllt48MEH+fLLL1mzZg2XXHIJSUlJTJ8+vaWXI9LuDDu+C2ExDorznCyfvQOb2caMUTNwWQyeONY3DSX/w48oXbmyxvarulIdYMp9YJhh4zewY0GbrN8/MthiNogNtWE2GXi88JcPVnLTBys57bn55JVUtMlaRERasqfOOwt38Ph3vkEQoXYLx/WN578XDOOeU/o3a4017R1M1GyQfOPknlx9TPcWeyzw9c2pWZHjf7z21iQZoFNU7YqpbrEHFrZVT7/SSHMRETn0tfgr9rPPPstZZ53FDTfcQL9+/bj11lu59tpreeCBBwLH3Hbbbdx0001cc801jBw5kuLiYmbPno3D0TJNBkXaM4vNzPizegGw8vtdFGSVMjZpLNO6TGNtZ1g1MgaA9Hv+hcnj+y1ifZkOcb1h+KW+y9/dBR5PPQe2HH/Zu9VkwmI2cedJ/RjTPYYx3WOwmU1Uur2kFajHjoi0jZYKdUorXNz/1To2V03S6hITjMVs4uTBHYgPb7n3L93jQgLhhM1sYljnqEbu0Xz9O1Rvaw+q2trV3vrpgO95PHrmYG6Y1IO7Tu7HCQPr3tbfGH+1krZfiYhIe7D/cx4bERYWxlNPPcVTTz1V7zGGYXD//fdz//33t/TDixwWuh0VS3K/KHavz2P+J1s4+YbB3H707SxIXcAzY/N5eWMwbN5M8g+fA4Pw7ttVp9qkGbD6Y0hdAWs/g0Fnteraa1bqAFwxvhtXjO8GwOTHfmF7dkmzG5WKiDSVv1Gy3WLC6fIccE+dJdtzqXR7SQx3cO9pA5jQK7YllxngsJr5+dZJFJZV4rCaA710WtMV47tx84er6B4XEqjUaW+Tr8D3/vKckc2fkBqYfqXtVyIi0g60v1dskSOAYRhMOLc3JpPBjtXZ7Pwjh/jgeG4edjPFwQZvTvaFON2+/pDEkhw8DWQ6hMbDuJt9l3+8D1yt27TY31PHbNq3waZ/UkxzG5WKiDSVs9IX6sRUjeo+0FB5wZZsACb2juOEgYmtGrZYzSZiQu1tEugAnDYkidcuHcF7V40KVKm0x+1XLcUf6pSrUkdERNqBI/cVW+QQF5UYwuBjOwEw7+NNuCs9nNP7HAbHDua7fhWk9o7GXOnkht8/w9tgqgOMuRFCEyF/Fyx5pVXX7fZUN0reW4jd90a5SKGOiLQRZ1WlTlQzQ535W3IAGNdKFToHk2EYHNcvgQ4RQdWhjqV9Tb5qSZp+JSIi7YlCHZFD2MiTuxEcbqMgs4zff9qN2WTmnjH3YDZZeGRSAW6zmZGZG+m18ueGT2QLgWPv9F2e+x8ozW21NVfWGGm+t1C7FVCljoi0HX9PneiqUKe80oPLvX/9xTKLygOT+8b2iGnZBbYWz4EFEoHtV0dwpY7/Z6DtVyIi0h60TV2viBwQW5CFMWf04Mc317P0mx30PjqBPtF9uGTAJbzxxxt8NtHB2T8VM+abt6m48SxsyQ30EjjqQlj0ImSu9W3DOvXpVllzzZHmewutqtRp7khhEZGm2jvUAShxuokIblpocc3by/huXQYAfRPD9plOdVC4KmDrT5CyDHK3QVk+OAuhvLDqvwVQWQq2UN8W3NBE6DAYEgaAyeq7LqorRHQCS91jwA+J53mQaPqViIi0Jwp1RA5xfY5OZO3cVNK3FbDg0y0cf9VArh9yPd/t+I7/jdxD/3URDEgvIPX2O+jyztsYZnPdJzKZ4eTH4I0TYfmbMOR86Dy6xde7d6PkmkIdvv/lqFGyiLQVf6gTYrdgs5iocHkornAREWxt9L6F5ZWBQAfg7BHNb8J7wEpzIWU5rJ8F676A8vw6D3MB+SYThVYLka5SonK3YeRug12/1XG0AWEdIKoLRHaBhP4M6Dic1y/oT69OCa35bA5pQf5QR5U6IiLSDijUETnEGSaDY87vzSf/t5QtyzLpPz6X5L7R3DX6Lq7/4Xr+O72EJ1+3w4oV5Lz6GrHXXlP/ybqMhaEXwcp34au/wrVzwdz4B5v94R9pbjHV1VNHoY6ItC2ny/fB3GY2EWq3kOuqaHK14Naq8eVxYXZ+vnVSoNl7q3G7IHsjpK6C/J1QnAFFGZC5zvd9FacBP8UksSK2M9vNBoW4KPRUUuguo8hVVuuUVsNCvDWUwYaDIZUerB4PCWVFdC5Ip1NZEdaiVChKhV0LATCAYw0zhCdVVfkkVFf7hMb7wp+43hDeCer4//zhwL/9anduGRMe/Yl7Tx3Acf2O3JBLREQObQp1RNqBuOQwBk7qxJqf9zDvw02ce9fRjO84nt6hE9jEPN6dFsGVX2WS9eyzhIwfR9CAAfWfbOoDsPFb34eEhc/B+L+26Fr9vSqsdVTqhGn6lYi0MX+ljt1iIsRuJrek6cHylqpQp1d8aOsEOh43ZK6H7b/Chq8hZQXsFcr4uYD1cd35OiaBWe48SstLiE1PIabQS3g5JDoh2Am2SvCYoSzcQVpQOblhlWRG5PGt1eBb/8mCgKAozEYMSY5YuljD6YqVAWUlHJ2xlfiCNCjY7fuqjyUIYntCbB+I7Q2xvSC+H8T1BaN9N1n2b78CX7Dz6OyNCnVEROSQpVBHpJ0YdWo3tizLIC+9lN9/2s2waV2YHHsVGwuWMmdgDn/K7k30ok2k3nY73T79HyaHo+4TBUfDtH/D59fBL4/AgD/5eiu0kMqqnjp1bb/yV+po+pWItJUKd3Wo42vWXtb0UCfLF+r0iAtt2UWV5cOy12HR81CSVesmjy2MrR36sSs8jgyrjXSTwcaKQvK37qDbunL67d7FI2leYooae5DSWt85I4PJiXeQ0iuSTfEuVgXnsCu0nN1lmewuy2S+/8BoK906j6NXcCIJJjsJXhMJbg+JFeUklBUSn7cHc85WX/iUvsb3VVN0d+h9gi/ciesLcX0gKPLAf1YHQZCt9jbm+PAjt7+QiIgc+hTqiLQT9mArY8/oyY9vrWfp1zvoOSyeUEsUzsyTcHT4jBmjd/Lipkgqtm4l69lnSfjHP+o/2ZDzYNV7sGMefH0rXPhJi/1m1RWYflVXo2RV6ohI2/JX6tgspkCz9qb+P2hrZgkAPeNbKNTJ3uKbQLjuc3CV+66zhZLacQizYzqyPr+Q/O3bKN2RSkxRKl0yvXTJ9DI5DRyV+57OCArC2qED5qgozGFhmMLCMDkceCucuLKycGVlUZmahqekBHt+KUn5pSRtymUkcCGAzYa7UwLFSRGkx5pZHZrHEnsqe1y72F5cd5WOI8JBry5T6R3Sgd6mYPpUuOhdnEdYzjZfwJO7zRdW1RTZGXpNgwFnQOcxh/y2rWBb7bfHR/IkMBEROfQp1BFpR/qMSmT9b2mkbs7np3c2wNGRVOaPpFPSbrKDlvLSSSauexfy3n2P6EsvxRofX/eJDANOeRJeGAtbvvd9wBjwpxZZo3/6Vd0jzat66mj6lYi0EWetUGf//h+0tapSp9mhTkEK/PowrHwPvL4eP7nx/Xir6yC27Eyh8087GLduO2Maqr4JCyVk+HBCRowgaOhQbN26YY6KwmgkkPd6vbjz86nck0L5unWULluGc/NmKrZvx+t0Yt62m4htu4kA+gBnA16TgTM+koIOoWTG2diYbGJxspOUykzK3eWsyfmDNTl/1HqcjlEd6dftbE61JjCxpBhz9kbI2giFKZC/C5a+6vsK6wDdjoHko30BT3z/Q267VpDVTHSIjdySCgBKNAVLREQOYQp1RNoRw2Qw+eK+fPTAElI25mGPNAMGPY0rCApN56dOu7igTxLhG1PJfe01EmbMqP9ksb1g/N98HzS+vR16HAuOiGavMdAoua6R5pp+JSJtLFCpYzbtV7N2p8vNzpxmVOqk/wGbvoXNP8CepYEwJ7vXVD4N70LGtz8y6v35nJBdfRePxYSR3BG71YElJgZHn77Y+/TBMaA/9p49MQ6gwsUwDCxRUViioggaNJCoc88BwOt2U5mainPrViq2bsO5zf/fbXgKC3Gk5+FIzyMBGAScExJCyKRjKR/el50drawNyWdjwWY25m4kozSDlOIUUopT+AEIt4XTN74vvftcSv+wLgyqcNFl63yMjd9AURqs/sj3BZA4CMbdAv2ng/nQeFtqNhl8ev1Y5qxN5+FvN1BWoSlYIiJy6Do0Xj1FpMki44MZ/acezP94M87lOUQEGZgJ4oajbmDGvBm8NrKIv26EvA8/Iuaqq7DExdV/svF/hTWfQO5W+PEB38jzZmqoUbKmX4lIW/NX6tit5v3aArojuxSP19fgPT6siT1VPG5fI/qFzwWmSfmVdx3H2x0Gk/XpN5y4aC1BviIQvFYL9onjif/TWYSMH4/J3jb9WwyzGVtyMrbkZJg0KXC91+vFnZ2NsyrocW7aRPEvv+JKT6fo62/g629IAjoFB3Nav37Ye0/A270zaR3sLLDv5qM9X1JYUciS9CUsSV8SOG+vqF5MP+VeTrHEEJ2+FnYtgt1LfFu2Pr0SfrwfjroQ+p92SDRb7hYbwuBOvl90lCjUERGRQ5hCHZF2aPCkTmxbmUXq5nyOL7NS4PVwQtcTePH3F1nYaQdX9U4ibFMqOa++RsKMO+o/kdXh24b19mm+svgh50On4c1aW2UDI801/UpE2pq/UbJ/pDk0LVj2T77qER/a6BYnADbOhu/uhJwtvu9NVug1FVePY/nFEcRv777A1Ge/INJX/IOzVzKdL7maiOOPxxwevt/Py1XhJntPMdl7iqkod+Gq8OCqcONxe7HazUR3CCE6KYTI+GDM1qZX+BiGgSUuDktcHCGjRwHg9XgoX7OGou+/p3TVKsrXrsNTWkrZ8uWULV8OQDAw1TA4dcgQykcPZPugWFaH5rI2Zx1rc9ayOW8z/8l7kicNC4PjBjNi8FSOnvgXhu9YhmXJy76R7b/8n+8rtjf0O9W3LThx0H7/bFpKSFVvHVXqiIjIoUyhjkg7ZJgMjr2kL+/et5guLjN70iqxmCxcM/ga7px/J6+PKuHmTZD34YfEXHVlw9U63SfC4PNg9Yfw1c1w9S/NKoH3V+o0NP1KlToi0lwut4cN6UV4vF76JoZjs9QdXDgrfR/IbZb92361McPX4KbRrVd5O+DbO3xbrQAcEXiGX8H8LkfxXcZSCr96mdN/KObsXN/NlUmxdPnHPwk/4YQ6wyKvx4uzzEVFmQtnqQtnmQuX001FuYuCrDLyM0rJTSshN6UET1WI3hDDZBARF4TFZsJqMxOVFEJMUigxSSHEdAzFEWptwjlMBA0ZQtCQIb41ut04t27FuXEjzo0bKd+4CefGjbgyMylftQpWraIb0LtTJy6fOhXzaX/nR2MjM7fMZG3OWlZkrmBF5gpeBrqGd+X66Y9zQnEJpvVfwrafIXsTzHvc99VlHIy5EXqf2OYNlv2jzWv21Lntf78zc2UKNrOJB6YP5Ixhndp0TSIiIntTqCPSTkXEBRM8IobSRdl02FlOYXYZJ3U7iRdWvcCCjru5ok9HwjamNF6tAzDtQdg021cGv/hFGPvnA16Xv1FyXduv/D11Kt1enC43dot5n2NERJpixmdr+GT5HgCO6xvPa5eNrPO4QKWOxUTYfvT1WrkrD4AhyZF1H1BZDguehvlP+CZZmSy4R9/IdzG9WTjrNRJe+Zjjd3iJLaxaR7iDxD/fTPx5F2DYbIHTlJdUsvOPHNK3FpC2tYDc1GK8jWc1AASFWYnvEo4j1IrFZsZiNWG2GJQXV/qCn9QSKsrd5GdUjzdP21pQ+xzhNqI7BBOVGEJ0hxCiOoQQlRhMcLit3golw2zG0bs3jt694dRTq38kaWkU//ILRT//TOmixVTu2UPuG2/AG28wokcPJk2YQOmI81mV5GRxzgrm7ZnHjsId3L7wHl6J7MmFIy9k2qlPEr7jN1j/hW8r284Fvq+YXnDas9BlTNN+OC3AP9q8tEalzuerUql0e6l0u5n9R7pCHREROegU6oi0Y45+EWxYmkFnt5mf3l7P6bcM5ZrB13DPb/fwxtEl/GVjE6t1QuNg2gPw5U3w87+h3ykQ1fWA1tTQ9quQGmNii8td2EMV6ojIgVmXVhi4vDa1sN7j/I2S7TUqdRrbAur2eFm5Kx+A4Z2j9j1g03fw7W2Qtx0Ab5cJLA09hj/e+5ShKz7h/Brjx70OOzGXX07slVdhDg3xXef1kr61gLXzUtmyIhN3pWefh7DYTNiDLNiCLFgdFqw2E2GxQUTGBxGZEEx8l3BCo+wNbg3zer2U5FeQn1GCx+2lvLSS3JQSclJLyEkppiinnLLCClIKK0jZmF/rvmaLieBwG8ERNqISg0nsHkFi9wiiOoRgqmO6IYC1Qweizj+fqPPPx1NaSvGCBRTM/JziX3+lYutWcrduhTehX3AwIycew+1XP8/HlYt4a+1bbMnfwn0L7+Mhk41JyZM4ZcyVjD/+31iXvQHLXoeczfDGiTDsEhh3M8T0qP8PsIX4X7MqXB5cbg8ujzfw9wmgrFLbskRE5OBTqCPSjplMBrODK7myxEzKpnzW/JrCKRNP4cXfX2R+xxSu6N2R0E0p5Lz2Ogl33N7wyY66CH7/CHbOh1k3w8WfH1CjyoYaJZtNBsE2M6UVbkqcbmKaOSVYRI5cheXVyUlBWWW9x1XUGGnuD3WKGhlpvjmziGKnixCbmT6JYdU35O2E2TNg49e+78M6kJ5wAdtf/4rI1Dfw15CUdowm/rgTiZowieARwzEFBQHgLK1k4+J01s5LJTe1JHDa6KQQkvtF06FHBAndwgkKs2GuZzvZ/jAMg9AoO6FRNZov1yhoqih3kZdeSl56CXlpJeSmlZKXVkJhdhlul4ei3HKKcsvJ2F7IhoXpAFjtZmKTQ4nvEk58lzDiOocRGR+MsVfQYwoOJnzqVMKnTsVdUEDJb79RPHcexfPn4c7Kpujb2RTNnsMpJ5/MWde8xBcVS5m1dRZb8rfw3c7v+G7nd0Q7orly4JWc8+dlOH64F1a9Byve8n11nQBHXw19T221bVn+Sh2A0ko3zr3CN/WHExGRQ4FCHZF2zDAMCsxe9iTb6LKzgoUzt9B1UAxXDb6K+xfez1ujyrjR31vnyisartYxmeC0Z+CFsbDtF9+b56EX7feaKt31jzQHX1+d0go3Rc76P4SJiDSmsKz6A3VZpZsKl6fOvjr+7Vd2i6m6WXtFwx/Gl+/0bb06qnMkZpMBLif89gzMfRxcZWCyUNHrEn7/fhehr3xAJFBih5yRPRh+2a3EjJsYqKDxer2kbytg7bwUtizLxFUVDFisJnqOTGDAhCQSuoY3rRlzC7M5LCR0DSeha+1Gze5KDyWFTkoLKijJd5K1u4j0bQVk7Cii0ukmbUsBaVuqt3FZHWbiksOI7xpOct8oknpHYrFWByLmiAjCTzyR8BNP9DVdXruOnFdfpWjOHAq/+orCr79myjETOPfau9k1PohZ22bx7fZvyS7L5j/L/sNba9/i2iHXctZRF2Ba8DRs/g52zPN9xfeHQWfBoHMgMrlFfz52iwmzycDt8VLqdFO619+bUjVQFhGRQ4BCHZF2zP8RIDPByhhbMKmb8/n53Q2c9ufTeHn1y/zaMY3L+nQiZOOeplXrxPSAyf+E7++BOf+EnlMhLGG/1uTy+D6wmOspzw+zW8gqclLi1JthETkwHo+XovLawXBBWSVxdYwe91dX2MxmQqpubuz/P/5QZ1jnKEhZDp/fCFnrfY/dcSzbMwdS8n/fEFrpwW3A4rFRHH3n4xzfvbrfi7PMxaaqqpyclOLA9dFJIQyY0JE+oxKwBzfepPhgMFtNhMcEER7jqzDqMSweAI/bQ156KVm7isjcWUTWrkKydhdTWe4mdXM+qZvzWfX9Liw2Ex37RNFlQAzJ/aOJiAsKhFaGyUTQoIF0evopytauJfvZ5yj+5RdKfp1Lya9zCTvhBG664nL+etZf+XLLl7y4+kXSS9J5YNED/NrpGP595itElhfCirdh0YuQuc43Dv3nh2D4ZXDMrRCW2CI/B8MwCLaaKXK6KK1w7VPh1Vg4KCIi0hYU6oi0Y4HfBGMw+aK+fPjgEvZsyGPbkhyuHHgl/178b94aVcYNG5tYrQMw+kb44zNIWwXf3ArnvrNfa3J76m+UDDUnYKlSR0QOTEmFC//gJ5vZRIXbU2+oE6jUsZoCYXNj269W7MzDTgVn5b0Cr74GXg/eoFjyYy5mx9uzcWR+hRVY39lE+V8u4pKTbsVqsuL1esncWcTaeSlsXpqBq6Iq5Laa6Dk8ngETOpLY/eBU5bQEk9lETMdQYjqG0ndMB8AX9OSmlZK1q5C0LQXsWptDSUEFO9fksHNNDgDB4TY69IygQ89IknpGEtspFMNkEDRgAMkvvkDFzp3kvPoq+f/7lKLZsymaPRvHoEFMueRiTjntSz7a/AlPr3iauXvmcsJnJ3B+3/M5d9RVJI6+AdZ9AWv+59s6vPQVWPmub1vW+L9CcHSzn3Ow3R/quPf5e6NR5yIicihQqCPSjvk/FniByIRgjj6lGwtnbmXB/7Zw5l0n80rQK/ySlMFlvTsRvGlP0yZhmS1w+nPw8iRY/6XvDXP/05u8pkr/SPN6ehyEBkIdvRkWkQNTWPXh2mY2ER9uZ09eWb19dQI9dcwmHBaj6v6VlDhdgZC5pl82ZhKdu4rX7C/TZX0qAM7Ek9k6vwJj2Uc4gOwwWHRGb8654Rm6RHShotzFH0tSWDsvhezd1VU5UR1CGDAhiT6jEnGEHJpVOc1lMpuI7RRKbKdQ+o1Nwuv1kpNSzM4/cti1Npf07QWUFlawdUUWW1dkARAW7aDXyAR6H51ATMdQbF260OGBB4i68EJy33iTwm++oXzNGlL/cRv2V3pz5p13MvKkd7lrwV1sytvEq2te5fU/Xuf4rsfz12F/pcOIy2H7XPjxAdizxLdVbtkbMO4vMPoGsB94A7dgmwVwVoU6vr9jCeF2MgpVcSoiIocGhToi7Zg/N/FWzb89akoyW5ZnkrWriMX/28EVE67g4SUP8/ZoJ9dV9daJvuIKrAnxDZ84cZDvt5xz/wNf3wrdjoGgOibA1KGhkeZQo1Knkd+Ui4jUp7AqwAkPshARZGVPXlngur3VbJQcF2anQ4SDtIJy/jlzDfefPrDWsV5nEbmf/o3/2b7CZHjxOBJJK5hM/rNzMbm9VJrhu7FB9L55BrcOOAuvx8sfc1NYMmsbZUW+xzdbTPQYHseACR3p0COi3VblHCjDMIjtFEZspzCGn9AVV6WbzB1FpG7JJ21LPmlbCijKLWfFnJ2smLOT+K7hDJrUkZ7D43H07UvSIw8Tf9s/yP/4Y3LeeBPnpk3suvRSIs48g/dveo75znW8t+E9lqYv5dvt3/LDzh8YlzSOc/uey/grv4PN38NPD0D6at80xyWvwMTbfFuzzPsfrAUHxppXb79KDHeQUeikrNKN2+PFZHDE/TmLiMihQ6GOSDtm4G/E6fveZDYx+eK+fPLQMrauyOK44ZOIDXqVn5KyuLhvMiEbdpPz8ssk3n1X4yc/5h++Kp3sTTDnLpj+3yatqaGR5gBhjqaNFBYRqU8g1HFYiQjyfVCvq1LH4/EGtl/ZLCasZhPPnD+U815exBerUvliVWrVkV7ONM3jduuHnGHkgwGFUaew+5s0TDt/xQQs72mw8/Jjue6k+4gJimHn2hwW/G8LeWm+KVbhcUEMmtiRvqM74Ag9PKtyDoTFaiapVyRJvSIBcFW42bEmh01L0tn5Rw6ZOwr58c1CFnyyhcHHdmLIscnYYmKIvf56Is87j6ynnyb/w48o+PQzCr+cxYBzzuGlax5iiyWXR5c+yrKMZfyy5xd+2fMLEztN5LaRt9H5ml9h3ee+Xjt5231biZe8Asf/H/Sasl/rrw513IGJawnhDsDXKHrV7nyue3c5Nx3bk0vGdG2hn5qIiEjTtc4MSBFpE/5fDHrxBq6LSw5j6LTOACz8aDtX9LoaDIPXx5QBkP/xx1Smpu5zrn1Y7HDas4ABq96FrT81aU3+keaWeit1fG+QixTqiMgB8m+/CguyEhlcf6jjD3TAN8kIYGTXaO4/fQAOq+/7TkYm71gf4nHbi8Qb+exwJbA0+xz2vLQS08408kPg1Qtj6frSy9x55nOQa2fWM6v46tnfyUsrwR5iYcK5vbjg3lEcNaWzAp1GWGxmeg6P56TrB3PpQ+MYdXp3QqPslJdUsmTWdt6+6zdWzNlJpdONJSqKDvfeS5f33yNoxHC8lZXkvfceW6dOI/aDn3h10gt8dtpnXNTvIiyGhV/3/Mr0L6bz5MqnKe1zAty4BE56DIJjIHsjvHcmvHsWZG1q8np926+o1VMnLsyOfxbATxsyyCpy8sP6zBb/WYmIiDSFKnVE2jF/ubfHU/v6kSd3ZdvKLPIzSum9ZjAJwQnMS8zgsoFdCPtjJ9kvvkSH++9r/AE6j4ajr4ElL8Gsm+GGRWALafAu1duv6uup4/vAU7NS5+W5W/l42Z7ANrKakiKDeOGi4YFePCIi1ZU6lgYrdWqGOjXHnV84qgvnjUiGJS9j+uk+jMpSvBYHZd2vwvnBKkI3zwdgQT+D3decwL3H3Ye53M7P721g/fxUvF4wmQ0GT+7E8BO7Hrb9clpbcLiNESd2Zdi0zmxdkcWSr7aTn1HKwplbWfXjboYf34UBxyQRPGwYXd55h9LFS8h67lnKli0n+7nnyP/kE2KuvJJ/nHMzZ/c5m0eXPMqC1AW8/sfrfLX1K/424m+cNPIqjEFn+7YTL34Jtnzv+yXF0VfDxNsbbaZc1/arMIeVEJuFIqeLtPxy3+37+YuK1XvyeXfRTtweOO2oJCb2bmSIgYiISD1UqSPSjlU3Sq4dhlisZiZf1BeATb9lcnnUjQC8dHQhAPmffUbF7t1Ne5Dj7oGIZMjfBT892OjhlR5/o+S6K3VCqyp15m3O4p2FO/B4vDz9w2a2ZBazNatkn695m7NZtDWnaWsVkSOCfxtMeJCV8KpQJ7+0jlDHVSPUqRk0l+Zi/uh8zHNu9wU6yWPJDv0rO/7vCzybt1EYBP89K5iExx7h7uP+w8Yfc3j37oWsm+cLdHoMi+OCe0cx7qxeCnRagMlsotfIBM6/52iOu7Qf4bEOygormP/JZt69exF/zE3B4/YSMnoUXd55h45PPoElMRFXRgYZ//d/bJkylahvFvP8sf/lmcnP0Cm0E5llmdwx7w4um30ZG8rS4fh/w42Loc/J4HXD4hfh2WGwflaDa6tdqeP7OxbmsBBUFfakFfhCneL9DHUe+24THy/bw6cr9nDvl2v390cmIiISoFBHpB0LbL/at8CFpF6RDJzYEQD3Lwl0DurKkoQi8o/qCi4XWc8+27QHsYfCqU/5Li96AXYvbfBwf6WOpZ5KnfhwBwCbMoq5+4u1fL4qhZIKNw6riQ+vGc1HNb6GJEcC1R/gREQACst8H6Ab66njrDH5KtDIdudCeHE8bJoNZhsVI+5k85wQsl98C8PlZmkvg9duH8Tf//oZSZsH8c5dC1n8xTYqnW7iu4Txp1uHccI1g4iIC26bJ3sEMZlN9B3TgQvuG83EC/oQGmWnJN/Jr+9v5J07f+Ond9aTsimfsBNOoMd3c0i8919Ykjrgzs4m/b772XXRxYytSObz6Z9z09CbCLIEsSJzBed+dS6PL3uc8oiOcP77cMkXEN8fyvLgo4vg54fAXXcoE6jUcVZX6oQ7LIGm/xmFVZU6+znePK+kInA5u9i53z8rERERP4U6Iu3Y3o2S9zZmeg9Co+wUZZdzbqGvWue5kXlgGBR+OYuSRYub9kA9p8CQ8wEvfPlncNX/BjTQU6eeSp1TBydx9yn96ZsYBsDLc7cBMDApgtHdYxhV46tTVBBAvVNtROTIVFRee/oV1LP9qsbkKzwemPc4vHkyFKZAdA+KBz/Opvs+xL16LaU2eOU0B96HbuOuYc8z/6lUFn2+jdLCCkKj7Uy9oj9n3T6CpJ6RbfY8j1Rms4mBx3TkwvtHM+HcXgSF2ygpqGD9gjS+eHIlnz66nJ0bCok891x6zp5Nwp13YgoOpmzlSrb96QwK//sSV/W6mC+nf8kJXU/A4/Xw5to3OXvW2azMXAndJ8G182DUdb4H/PVheH1anb12ajZKLnL6K3WsgetTC3z96va3+X9RjV9WFDtdeDz1vJCLiIg0QqGOSDtmqqNRck22IAsTL+gDQPFyG0MYzerYErZP7g1A+r/+hcfZxN8QHv9/EBIHWRt8H4zq4fJPv6qnUXKQzcyV47tx1vBOAGxILwJgYMeIfY4Nd/g+rBVq/LmI1BDYflWjUqeu8Ncf6nQwF8K7Z/imIXndeAeeTYpxITvveAhzURlbOsBbtw/hpn98Qbc1Y5j1xGoKs8oIjbIz5bJ+XHT/GHofnYhRT1gtrcNiNTN4cjKXPDiGU24awoAJSZgtJjK2F/LN86v5+P+WsmtTEVEXXUj3r78idOJEqKwk+/kX2HbyKQT/toZHj3mU5459jvigeHYU7uDSby/lkSWPUOathBMfgT+9BPYISFkOL02A354DT3XVjX/7VUmNRslhDgshVdeXV3qqbt+/16ma27W8Xg0PEBGRA6dQR6Qda2j7lV/XQbH0GpmA1wvH7bgAvHD/UdvwxkRRsXMnOS+91LQHC46Gk/7juzzvCciouweAP9Spr1Gy39HdajenHNypjlAnyPemWZU6IlJTYPtVUMPbrypcHkab1vGB51bY9jNYgnBPe4JNP3gp/O+rmLzw01Fmsh67hb8NeZa5T+xmza8pAPQb24Hz7hlFn9EdMFv0dulgstjMdBkQw6QL+3Lxv8cw7PjOWO1msncX89VzvzPz8RVklwTR6cUX6PjUU1g6dKAyNZWUm/7C7iuvYnRlMjOnz2R6z+l48fLu+nc5deapvL/+fSoHnQk3LIQex4KrHL6701fNlbMVqK7UKdurUXJwVX84v/JKD+79qLbZ+5cVep0TEZEDpXcpIu1a1farRo4af3YvLHYzpWlezrBcSondyycn+0KU7FdexbllS9Merv906HsKeCrhiz/X+m2mX2Uj268Cp+oQXmuiVZ2hTqBSR292RaRadaVOA9uvPB6iVzzNe9Z/E0s+xPXFefw7rP3XO3h++Q2XCT44LZJjnv6Afrun8PVzayjOcxIe6+C0m4/i2Ev6YQ/S1L1DTUiEnTF/6snF/x7DUVOSMVtMpG0p4LPHVvD186vxDJ1Aj6+/Iua6azGsVkp++41tp51O+XOvcd+wf/L8cc+TGJJIRmkGDy15iGu/v5Z8ewhc9Bmc8hTYQmHXQnhhHCx+iWCb77WsZK9Gyf5KnZqaWq3jdLlrbw1Er3MiInLgFOqItGP+3MTTUKkOvrGxQyb7tjv13DKGMEsY/0vaTcHI3lBZSdrd9+Ddey56XQwDTnrMV6qeusLXOHkvjY0097OYTQzvEgVAiM1Mt9jQfY4JD2yrUFm6iFSrOf2qzlCnJBveO4uOKx7HbHiZYz2O/G53sumav2PdnUFOGHx480CuvXUmW993sWL2TgAGTezIeXePIrlfw2Ou5eALCrUx7qxeXPTAaPpPSMIwGexck8MHDyxm6Q/pRN9wk29L1qRJ4HKR8/LLbDv1NIZuh6/+9BV3jrqTEGsIS9OXcuE3F7KtcDuMuByu/w26HQOuMvj2NqYtvZpkI4OyCneguqbm9KuaSp1Na5ZcXKNKJynCNzxAr3MiInKgFOqItGP+aS6NZDoAHDW1M7YgC4XpTq4J+QcYBvePTccIDqJs5Ury3nu/aQ8a3gGOrxpt/tODkLut1s0u/0jzenrq1DSqu++D04COEZjrqOwJd1Rtv9JvMEWkhurpVxYig2wAlFVWVT/sWgQvToCtP+I2O7jdeRXbV8eR9rfbsZRVsi4Zlj90Ptcf+yLfP7GVlI15WOxmpl01gGPO74PVvu+HdTl0hUY5mHxhXy741yg6D4jB4/Ky7JsdfHD/YlILgkl+8QU6PfcslsREKvfsYffV15D9jxmcGX0s75z4DkkhSewq2sVFX1/ET7t+gqgucPEXvl9gWIOJy1nKbNsdjMn9nEpX9farkDpCnWKniz15pYGBAfXx99MJtpmJCvH9/dXrnIiIHCiFOiLtmD8GacoufkeIlaFTOwNgXp7IwKiB7A4u5bfpPQHIfPJJKvbsadoDD724+jeZX/4lkCp5vV4q/SPNTY3/7+XCUV04d0Qytx3fp87bA5U6erMrcsRauSuP+2at5b5Za1mzpwCo3Sg5zGHBMMDAQ8XcJ+GNk6AoFWJ6seSoFxn96wom/j4XgG9GW7E/9wiTTJcz68nVlOQ7iUoM5uw7RtBrRMJBe47SfJEJwZzy58GccO1AQqPsFGaX8/V/V/P186txDxpL96++IvrSS8FkovCbb9l28inEzl7Geye+y1FxR1FUWcTNP9/MPQvuocRdBkdfDdf/RkH8SEIMJzeWPs871ofoSBahdgvB9n23X83bnMX4R37m7i/q7jnn5+/NE2q3VG8zVk8dERE5QAp1RNoxf27ibUqpDjD42E4EhVkpzCrjCtvfMBkmnuq8jsrBvfGWlpJ+z/+zd97hUVRvG75ntu+m95AAoffei2ABFFRAEQRFRfFn77333v3sFXsHFcEuIKD03nt678n23Znvjy3ZNAid4Lmva2GTzJ6ZSbacec7zPu9DTRtLkuDcV0FrgvQlsPYTgFohkbomOHUiTTqevaAn/dMaLnWomewKW7pA8F/loR+3MOufdGb9k85t36xHVdXgBXCESYcsS6QYHLyre4mwxb7uVvSYTHWXJzA98jidS/OpNsIHF8dz1tNfo1vSlqXf7EJRVNr3T+CCe/oTk2w5zmcpOBJIkkS7PglMe3gQvUe3QpIl0jcW8+WjK/hnXg4RN95G2rffYOzeHaWqivxHH6P6iht5M+1uLu9+ORIS3+/+nklzJ7GhaAPEtGH3uK95xH0pdlXPcM0WfjfcjWbdx1h09afQqzPKANhVULXf4wztolWzeCE+5wQCgUBwaAhRRyBoxkg0vfwKQG/U0vfM1gDk/u1iWoeLUCWJF0fZkQwGrP8uo2L27KYNFtMWTn/Ad//3B6EyL9j5CnyZOYdLpKmm/Gr2mmwufn85ZVbXYY8rEAiaD6Uhr/ldhdVszK4g8FYTYdRBRTafSQ8yWrMWRaOHc16m2HkamTfeisFqZ3cSPD6jCzdd9i0b3qlg9+pCZFli+JQOjJnZDb1RhCGfbOiNWoZNas/UBweS1iMWRVHZtCibzx5YxrbsMFI//ZzE++9Htliwb9hA9oUXcdmGaD4c/T4pYSnkVOcw49cZfLX9K4x6DR95z2Ks62lWKR2xSA746WYmbrmJZEpq7TenzA74QpX3R6D8KsyoqykzFk4dgUAgEBwiQtQRCJozgZbmTSrA8tF9ZAqWKAPVZU7OqJ5EvCmetYY8dl3QH4CCZ5/DXVDYtMEGXwsp/cBZAfNvx+2pmcgeqPtVUwi1pd/+7Qb+2V3CrH/TD3tcgUDQfAh0FEqJMgHw7ZoswOcGNFbuhQ/PIk3NIVeN4eWWrzPny3SKHnsCSYU/e0vcPe4M2nMHv720nbJ8G5ZIPRNv70uv01sGc8kEJycxyRbOvr4XE27pTVzLMFwOL8u+38MXj62iqMMZtJk3j7DTTwe3m8LnniPxsVl8M3IWo1qNwqN4eHLFkzyy6lpkQz7pajIXuh7iHeMVoDWSWrqM3wx3M1FeSqAIOjsg6jj377qpCuneJsqMBQKBQHC4CFFHIGjGBDN1mq7poNVp6D8uDYBNf+RzZ++7AXi01Rqkrh39lvRHm1aGJWtg/Osg62DHfORtP9bs50iIOv7JbogBCHEJJhD8t7D5XQ/n9UkB4JvVvuyv/oZspFljoSKLfG0qU+wPIX0zhy7zvwVg9hAtr3a7lK6559J2uwOXw0ty+0im3D+Q5HaRx+dkBMeF1M4xTLl3AGfM6EJYtG9R48+PtvH9h5kY732GpEceQdLrqV60iMKLZvBU8tXcNeAuzFoz28s3Y057HV30UhTg98jJcM1SyqJ7EiHZeEX/Jm/qXiWGSoqrnQDYDtDaPOjUqZWpI8qvBAKBQHBoCFFHIGjGyP5VZuUgRB2ALkOTiYgzYq90YVrdmuEpw3Hi4b1z9KDTUr1gAZXzf27aYIld4ZTbADD9eQ9R+LIEGupmdbAYtDL6OmVcSf72rwKB4OTH41V8Ha2AiX1aIEng8igMkLbznvIwWIsgqSeV53/DPTu+Y+zejSjAp2Mi+aTVrYwq6stpDh0S0HVYMhNu6YM5Qn9cz0lwfJBkic6Dk7n40cEMOa8deqOG4qxq5jy/htKOp9H6yy/QpaTgzswkY+o0ztls4McJPzKsxSlIsgdj0jxMLWdhNFohrgPrRn3F8+4puFUN4zQr+c1wF2fIa4Aa0aYxamfqiC6PAoFAIDg8hKgjEDRjApUDTQ1KDqDRypx6UWcAtizOZWbYLZi1Zn7XbCdv0jAACh5/HE9RUdMGPOV2iO+MbCvmQd1n6DTSESlrkCQpOOENYG6gjaxAIDg5sblrSjpbxpgZ0SGeU+V1fKp/mjBs0Goo7nM+pvyO62i3Yy8uLcy7sgu3PDKfiyrT6OHSoqBS1snCqdM7o9GKac9/Ha1eQ98zWzP9iSG07BKNx6Xw67ubWb5OQ8oXX2EZPhzV4SD/oYdx3/kYr/Z8BEfeRFRFhzZsFzvkJ9hRugOT0cgb3olMdD3ODiWVeKmSD/Qvcpf2K1xuT63GAXWp6X6lE92vBAKBQHDYiNmNQNCMkQ6jGKll15hgi/P13xZwU8fbAbi/7RrkTu3xVlSQ19QyLK0Bxr+OisQkzRJGyhsP+bjqEpjwBjhI/UogEDRjbE6fqKOVJfQamXf77ONDw8sYJTfe9mNwjniFDdMuJHxvIZUmWHn/OVw5/WP+eHUX8XZwoTLH4sLd1iLycwS1MIXpOeeGXr7PQQm2Ls3lh3f2EP7EyyTcdReSTkf1woVknHce13o74M26GdwJOCnl4p8v5tecT0Bys0VNY7zrCd73jAXgOu1cPtM9ha0ovdF9Vzt9Ao7ofiUQCASCI4EQdQSCZkygwkk5RKVj0IS2JLQOx2n1YF7cjn4J/alWHXw0MdxXhvXnX00vw2o5gMpeMwF4TPMeOPff0rWphJtqizr7W/0UCAQnF4FsEpNeg7T6Aww/Xo2seqDHZJy9H2TLRVOxFFWTHwVZL1zH2QPu54fn11NeYAOzhi/CnezTKeiFQ0fQALJGZuik9ky4uTemCD2luVa+e3YtVf3PJe277zB06oS3tJSxnz3DkiQXS6bPZljKMJxeJ3P2fYi5zWvIhlxckp4nPJdwk+sGbKqBoZqtWD44BdZ/0eBKRK3yK9H9SiAQCASHiZjlCATNmWD51aE9XKOVGX1FN3QGDbm7KpjuuBmDxsA8eRNFU04FDq4Mq3DAXWQp8bSgGP56/NAOqg4RddoNH6qAJRAImh++kGSV6zQ/wPzbARUGXEll66vYeel0TJUO0hMkqv7vXnqETebHV9bhsLpJaB1O10s6UqTxvV8IUUewP1I7x3DhfQNIahuJy+5h/psbWbNJIvWLr4iaMgVUlaKXXqL67kd4Y/ALPD/yeWIMsWgMhZjT3iAqaRmgMFcZyjjXU6xROiC7quCHa+HTiZC9utb+qmtl6ojuVwKBQCA4PMQsRyBoxgTKrw5H5ohKNDNiWkcAdv5RxrWJvtDj+9NWo+nc4aDKsFyykXs8V/q+WPkupP9zGEfmI6KOU0eIOgLBfwerw8192i+41vuF7xsj7qQs7BzSr7gcg83NjlQJ6Y0nScwfzp+ztqJ4VNr2jmfi7X3p2SEmOI7HK943BPvHEmVg4m196HFqKgDr/8ziuxc2oJl5O0mPPgo6HVW//Ub6pAsYWZXCJ2d9g7uqC5LsxRP1I6aWs5C0laSryUx2PUxe/7t9nSH3LoL3z4C/nwuuwDSUqVPt9KAIJ6pAIBAIDgEh6ggEzRjpMMuvAnQalETHgYmoiop2YWt6R/ajXKnmi/Njasqw5s0/4Dger8o/Sg/makYBqm+V0ll9WMdWN1NHzHkFgv8IipeW/9zNVVr/e8+YJymy9yTnuuvRuRQ2ttUQ9dqryCs6sPrndAD6ntmKs67qjk6vITbMEBxqT5H1OJyAoLmh0cqMmNqRcdf1xBShpyzPyuxn17AnYiAtZ32ENikJV0YG6dMuwvjV97iypuPIOw8ZPdqwXZjbvIrGlI6CzL4uV8ENq6DHFN/gC5+E764Al40qZ41TJ9zvRlVVgt8XCAQCgeBgEKKOQNCMkYPtrw5vHEmSGDmtExFxRqpLnUzMvQatpGW2uoayC0cBUPDEEwcsw/IovtbDbxmugMhWUJ4Bfzx4WMdWt/uVyNQRCP4DeD0w5ypa7P0OryrxVuSt5GVFUXjH3Wi8Kiu7aGn16ruU/RzLrtWFyLLEaZd0Zsh57ZHk+oHICRGGBnYiEDRMm55xTHtoIO36JqAoKit+3MufiyHhk28IP+ss8HgofeUVnv3nHaJyOzIq8mm8jmRkrRVTq/fQRq72lVjFtIFJ78G5r4KshS1zYNZZRNnSAQgzajHqNBj85YEiV0cgEAgEh4IQdQSCZswR0nQA0Ju0jJ7ZDVmWyN9o43/6OwG4r80qtF06+sqwHtl/GVagxMGpscDEN3zfXP0h7P7rkI+rfvcrIeoIBCc1Xg/M+R9s/g5F0nKD60a8OxyUP/wksgqL+xjo+uzHpH+pIXdXOXqjhnNv6kXXYS3qDTX3hmFMG9iSW0d1PA4nImjOmML0nPm/bpxxWRe0Bg05O8v59tVtuGbcS/JTTyGbzXQv3subC15k2J4cbOnX4q7shiR7MbX4jo93P0mVy98woN8MuHQumGMhbwOznLdyieZ3IgwaAJGrIxAIBILDQog6AkEzJrAefaSEjqQ2kQwc3wYAzb8t6K0bSImngq8uSPCVYf31F5Xz5jX6eI/fRaOTZWgzAgZe7fvB3BvBXn5Ix1Q3U0c4dQSCkxivG2bP9DkaZB2LejxHq02ZnLHoRwB+G2am/0OfsnWWndJcK+ZIPefd0ZfUzjENDtczNYqnz+9JfLhw6ggOHkmS6DwkmQvvG0B8K1+nyF/e3swGZ1dafvMdFWkdCfM46PLec9y+ejZy+iSchaNRVZmN5YuY/NNkluUu8w2WNgyu+hu17akYcfO47iNa/PMgeJwhHbBE+ZVAIBAIDh4h6ggEzRjJb9U5kjpH3zGtSekUjcelMGrXZRhUI994llM21VeGlf/Ek42WYbm9vvIrrcYvN416GGLaQmUO/HrvIR1P/e5XhzSMQCA40fG6fZkjW38AWYdy/iyUbxcxcfdKAOaMjWTETZ+z7r0yqsucRCWamXRnP+JSw4/vcQtOeqISzUy6qx+9R7cCYPPfOXz/aQFpr88i7rprQZYZlbWG1xe+Sttd7bClX0OENpGc6hyu+uMq/vf7/yiwFkBUSxwXzuYp9zQUVcK88SN4ZwQDtLsA4dQRCAQCwaEhRB2BoBlTU3515JQOSZYYfXlXjGE6qvM8XF51DwD3tF6BpnNHlIoK8h5+pEF3UKD8Sqvxv7XoLTDxbZBk2PAFbP/5oI8nKcJY62vR/UogOAnxeuC7y2HbXNDo8Z77Pjuf/oyUdavxyPDWxBjOvPBjVr6fj9PmIbFNBJPu7EdEnOl4H7ngP4JGKzNsUnvG39QbS6Se8gIbc17aQHq7c7G88S4FpmiSbSW8sORNpq3bxoToZ7io80VoZS3L85Yzbf40thRvocrl4V3vuVzluQ3VEg9F23mq7E4e1c7CWll2vE9TIBAIBM0QIeoIBM2YmvKrIzuuJcrAqMu7+r7YEs0pzrMp81bx2aRoXxnWggVUzPm+3uMCQcm60KDSVoNgyA2++z/dDLbSgzqWAWkxPDepJz1TIwEh6ggEJx2qCvNugW0/gUaPe8xb7HroPdQ1G7Hp4YnzYklu+QwrP87B61ZI6xHLhFv7YAzTHXBogeBI07JrDFMfGkT7/gmoisrKn/axap2J2067nQWpfdGoCtN3/MGwVx7jtoSp/DjhR9pFtqPIXsSMX2fw677fAFihG4R0/UroPR0Zlcu0f3Dmogmw45fjfIYCgUAgaG4IUUcgaMYEul8dDZ2jdbdY+p7ps5r32nImMc4kvlfWUHSxvxvWU0/hys6u9Rh30KlTp/vMafdDfGewFsL82w/qOGRZYsqAlnRM9JVY+Cu8BALBycJfj8G6T0GScQ17nj33vIa6ay/lFnh+egu0tnuI2ORGVaHrsGTGXtMDnV5zvI9a8B/GaNFx5pXdGXV5V7R6mfyd5UyxR/F57+m8MewyqnQmYjJ3se+88wmbt5RPx37K8JThOLwOnl/3AIbEHwk3qmCOgYlv8H6bl8lQErA4C+DLqfD1JVC9/26TAoFAIBAEEKKOQNCMCZZfHSX3ysDxbUlqG4nHqXJh1m3IioZ7Upeh7dMTxWol9557UL3e4PZBp46mzluLzgjnvQ2SxheAunn2QR+LJpgfJJw6AsFJw7I3YOlLALgHP8rex2ah5hWSGw3vXdeObrYHGGo3A9D/7DROnd4Zue77i0BwnOg0KIkL7ulPVKKZcFViarUepfUQrjv9dva16orqcFDw2OOUXXsLL3e5n8u6XgaAPmYZjoRXyKvOA6AgbjBnup5lWfIlvs/JbXPh7eGQvvR4np5AIBAImgliZiQQNGMkfwHW0ZI5NBqZMVd2w2DRohYZOKfoCqq8Vt4db0A2m7GvXkPprFnB7YNOHVmqP1iLPjDiDt/9+bdDVcFBHYvsf7dSRFKyQHBysOp9+O0+ANz9bmfP8z+i5heSGwMfX92Jc62PEJOvoqBiHhrPoHPbBsPhBYIThdgWYUy+tz97TQoaJLrlehmoxHNb7xm81WMiLq0O67//kjHhPK7Mbs/I8HtRPGG4NTlMmz+NxdmLCTPocGDgp4Sr4eq/Ia4TVOfDx+fC4udBERZVgUAgEDSOEHUEgmZMjVPn6O0jPMbIqMt8+Tot9nanQ3lffnWtI3PmGAAKX/0/HNu3Aw0EJdfllDsgqSfYy3wZGgdx4Eej05dAIDhOrP00WIrp6XEV+974BzU7l4Io+OyKLozLu4fcrZV4JfjR7CKmZ8MtywWCEwG9UcuedkYWm3zdq7q5tcyoMrOp1QjuH3cPpl69UKqrybv3Xk5//ycM22aQaGxDiaOE6/+6niUVryBpqql2eCCpB1y1EHpNA1WBBU/AZ+eLciyBQCAQNIoQdQSCZkxA1DnaJUlpPePoPaolAGfsvYRwRwz3R/6JduRQcLvJvfMuFKczWH7VoFMHQKv3lWHJOtjxM2z4ssnHECi/8oryK4GgebN5Nsy9EQBvjytJ/3gH3vRMisPh40s7c1rm7ZRk2DCYtaxpo2O3XsGs1x7ngxYI9s+7l/Xn/tsH0WpyG0plhXBV4gKrgVRHHHHvfEj8bbeBVkuXvet58/d3eY1LmdFtBrIks6N6MZa2L5Hu/NtXTq23+D4rJ7wJWhPsXegvx/rneJ+mQCAQCE5AhKgjEDRjjnb5VSiDz2tHYpsIcMpMSL8Op9vNK6OcaGJjce7aRdGr/3dgpw5AYjc4zVdywS/3QEV249uGIB/l/CCBQHAM2PELzLkKUFF6XkLG11m4d+6i3AKvX5rIGcV3UFXoJCzawPl39CNP5xOKLSIYWXCCkxBupGdqFPFtIvg43MlqgwcVlR4uLd88vZbqIefhfP1D9kS0INJlg4cfZOrXBXwx4j1amNohaW3skz7g6j+uJrc61zdon4t9rp1gOdY5sORFUY4lEAgEgloIUUcgaMYci/KrABqNzJiZ3TCYtYSVxTMseyKLbRvYefUZAJTOmoVl23qgTkvzhhh6E6T0B2eFb8W+CScgyyIoWSBo1uxdBN9cBooHtdsF5C7W4ty4iSojPHuRmfOUJ6jIdWIM0zHxtr7EtLBgc/mC2E1C1BE0Eyx6LR4JFprcfBnmokxWsFe4mP/GRpatULhnxM0sGzoeZJnKn35CP+NuHlJm4iw8C1Qdy/KWcf7c8/l257e+RYyELj5hp+dUXznWX4/BF1PAWnK8T1UgEAgEJwhC1BEImjE1Lc2PjdAREWfi9Eu7ANAtZwStyrrxiDwfafwYUFU6znoZi8tev6V5XTRan7Vca4Q9C2DNrP1vT825ipbmAkEzJHMFfDkNvE7UTmdTsD2Nql9/wyPDS5O0TI19npJtLjRamXHX9iQy3gQQFHUsBlF+JWgemA01AmSOVuHjcCfGblGogLLPyqVWC/aRF9H688/QtW6FJz+fmEfu4obf80nKuYHe8b2xuq08tuwxrvnzGopsRTXlWONf831u7v4D3jnF97oSCAQCwX8eIeoIBM2YoFPnGO6zbe94ep6eCsCYvZehtZl4pH862tRUjKVF3LBhduOZOqHEdYAzHvbd/+0BKN2338018rEVsAQCwREidz18PhncNtS2p1GwqxNln38BwDvjNEzo/hwly32bnn5pZ5LbRQYfanN5ADDphFNH0DwIqyNAuiX4SbbzeZiDYlnBokqwrITFq3Skfvkt0dOngyQxOms1j3/zFv/nmcyd/e7AoDHwb+6/TJo7ib+z/vZ94Pe9FK78C2LaQWUOfDQO/n3t2Nh1BQKBQHDCIkQdgaAZE5BOjrXQMfT89iS0DkfrMjB295Vss6bz5rjWeCWZU3PW02H9kqYNNOgaaD0c3Fb48fr95gQEBCyvaH8lEBx1dhZU8fbfe3B5DtMaV7jd17nHWYHacjD5e3tR9sVXKMBb42SGj32K8j+MAAw4O42OA5OCD/UqKg63P1NHOHUEzQRzA6WCG7PLydOqVIyIpceYlsiyxJ61hcx+dSvyJTcS9t4s0sMTiXRWk3/X3Zz66j983fc1OkV3osxZxg0LbuCpFU/h9Dohqbuv7Xn3SaB44PcH4KuLoLrwOJytQCAQCE4EhKgjEDRjarpfHdv9arQyY67sjt6oIa6yJQOyzubP2BV80bMXAP1/fB9XZuaBB5JlmPgG6CyQ8Q+seLvxfYqW5gLBMeOSD1bwzC/befH3HYc+SOk++HQi2EpQk3pRkDGA8q++QQHeGSczdMrjVM+PQlFUOgxIZMA5bWo93O72Bu83dKEsEJyINNSpLfC51ScthhHnd+C8O/oSFm2gvMDGd8+uIb0olptPvZWPu5wFOh3WJUtwX3w9b5aM45LOFwPw5fYvmTpvKrvKdoEhHCZ9AGe/CBq9r5vkKz18zQcq847l6QoEAoHgBOCIizppaWlIklTvdv311wPgcDi4/vrriY2NJSwsjEmTJlFQUHCkD0Mg+E8gHeNMnVAi42vydfrkjqJlWRd+G7uXwjYd0Dod5Nx5J6rbfeCBotPgzCd89/96FIp3NbiZLImgZIHgWFFQ6QTgo3/TD22Aihz4ZDxU5aHGdSY/Zzhl38z2OXTOlhk4/QHc85Nx2jwktY3g9Es7B9/PAticvtIrWQKDVqxBCZoHGlkKlgtGmnS1ftYxIQyApLaRTLl/AO36JqAqKht/y2SqzcJf7UcT/eW3mPv3R7XbKXn2eaa8vIF3Oj5EjDGG3eW7mTZ/Gl9t/8pXdj3gSpj5u6/xgMcBK96CV3vCb/eDo+IYn7lAIBAIjhdHfJa0atUq8vLygrc//vgDgMmTJwNw66238tNPP/Htt9/y999/k5uby/nnn3+kD0Mg+E8QLL86Tvtv1zeB8hQDAKP2XIbOpWXOpeHI4eE4Nmyk6M03mzZQv8uh3em+Sen314DXU28T0f1KIDj2OD0KysHa46qL4JMJUJ6JGt2G/LxTKf/2+6Cg0+uSWzEv6EhlkZ3wWCNjr+mJtoHMHGsgJFmvrSf4CAQnMoFywX6to2t9v2NiePC+KUzPWVd1Z8yV3TBadCR6ZS6pMrBxK7R4/0OSHnkE2WLBvn49MVc/wafF5zE8aShOr5MnVzzJTQtuosxRBi36wJV/wiXfQ6sh4HXBstfh//rCmo9A8SIQCASCk5sjLurEx8eTlJQUvM2bN4927doxcuRIKioq+OCDD3jppZc4/fTT6devH7NmzeLff/9l+fLlR/pQBIKTHul4JCXXIae1gQKNgsFtYszuy1no3MyWmacAUPLOu9hWrTrwIJIE418HQyTkrIZ/X623iSwydQSCY0aLSGPw/vb8qqY/0F4Gn54HJbtQw1PIzz+D8tlzUYA3z5FpP+1/tFk/lLzdFeiNGs6+vifmCH2DQwVDkkXplaCZEebvgBUq6sSFGYi21H+ud+ifyNSHBpJlUtEgsWtBDl88tpLi9qfS5qe5WEacgupyYX3tHe58t4SHEy5HJ+tYlL2ISXMnsSx3me8ztN3pcPkvcNG3ENsBbMXw083w2STf61IgEAgEJy1H1c/scrn47LPPuOKKK5AkiTVr1uB2uxk1alRwm86dO9OqVSuWLVvW6DhOp5PKyspaN4FAUCN0HE/3it2rMNfsQtLJJFa2oX/WWTxm/gvvWSNAUci+7TbcBU0IcIxMgbHP+u4vfBoKttT6scjUEQiOHe6QF9q/e4qb9qCqAvj0fCjYhGpOIL9gDOXf/4wCvHGOTIsLLmJ44QR2LM9HkkE7PJ4vt+fx+oJdwdsvm/KC5aSinbmguTJ9cGsGt41hQu8Wwe91TAxrdHtLpIHVqRrmml3ownVUlzr5/f0tzPsiD+P9L5D89NPIERE4t2yh+10f8UXJJNqHtaHIXsRVf1zFi6tf9IUoSxJ0HAPXLYMznwadGfYuhPfOaLS0WSAQCATNn6M6U/rhhx8oLy9nxowZAOTn56PX64mKiqq1XWJiIvn5+Y2O8/TTT/Poo48exSMVCJonkr8A63jqHA63QrlGJebUJEr+yKVvzhjyIvZw78C9vLSnPZ5du8m5+WZaffIxsr7hFfkgvabCtrm+0Mfvr4YrF4DW95hg+ZVQdQSCo47DVVOy8frC3cxem7Pf7S9uVc70vXf6MnSM0eQXnEn5/N9QJJ+gEz1hIlO0M/l97lYADAPjeHT1vgbHumpEW+4d2zko6oh25oLmxpWntOXKU9qiqip6jYzLq9QqvWqIMKOO9Xorrae1JybbwdpfM8jbXcG3z6ymx8iu9Jv9A6VPPU71woXw9me80LM7c6eexYdVv/LRlo+Yt3cel3W9jCmdpmDWmWHIdZA23NcZq3SPT9iZ8Dp0HX+MfgsCgUAgOFYcVafOBx98wNixY2nRosWBN94P9957LxUVFcFbVlbWETpCgaB5E6y+Oo46h8Pju/CK6RxFt1NaICExevdlFFptfH5pCnJEBPb16yl48qkDDyZJcM4rYIqB/E2w+Pngj0RQskBwbFBVFVtI56lym5tteZWN3sry9jF6/Q3+UORO5BWPp3z+XygSvH6OjGHcGK5vcTt/fbwdgJ6np1KQ4AuQ7ZIcwbSBLZk2sCXje/nmCu8u3kvPR37nmk/XAGAxCFFH0DyRJImECF/uXIf9OHUAwo2+dVab4mXA2W246NHBdBiQCCpsWpTNd2/uxXPtoz7XTlgYro2bGfvoH7xXOp5kUyLF9mJeXPMio78bzYebP/Q5d5J7wv8WQsvB4KyAby6Br6eLEGWBQCA4yThqTp2MjAz+/PNP5syZE/xeUlISLpeL8vLyWm6dgoICkpKSGh3LYDBgMBiO1qEKBM0W6QQov3K4FQCMOg1DJ3cgf28lJTkwatelzOn6BkNunUarxz6l/OuvMXbrSvSUKfsfMDwRznkJvp0BS16ETmMhpW9Npo4QdQSCo4rbqwazq76/bihVjvrB5QFkj43oryeQKJXjjOlESc5pVMybiyLBa+fKMPoUHuz+KD88vxGvW6F1j1iGXdCB77/dAMCE3i24ZmS74Hj906J59KetVDlr9tkzNeronKhAcAwYmBZDQWUuQ9vF7Xe7MH+ZYbX/9RYeY2TMzG50GZrMos+3U1ns4Oc3N9G+f3vy734N7f89Td+inUS+M4d3+vVly1VTeaf0R9Ir03l5zct8vf1rbu57M2e1OQv5srnw97Pwz6uw7Sco3A4XfQ2x7fZ3SAKBQCBoJhw1UWfWrFkkJCRw9tlnB7/Xr18/dDodf/31F5MmTQJgx44dZGZmMmTIkKN1KALBSUuwpflxPAanf0XfqNOg1Ws483/d+Pbp1bSo7EC/rLN4sO33fHbNJXjf+oSCx5/A2LEjpt699z9ot/Ng61zYMsfXDevqxWjkQPv2o3xCAsF/HHtI6VX3lEh0mkZMvYoC390O0j6K1QhyC0aj+35OUNCxn9af/xv8PL+8shV7pYvYlDDGzOyGLEsUW10AxNYJjr10SBpn90im3O4GQCtLtIoxH50TFQiOAS9M7sUjE7oRYdTtd7uAqBMqaAK07BLD1IcGseqnfaz/M5PdqwtRdBK/9b8Gr3E7A3/7DMeatbS/aQsfXPU/VpyayCtb3yLXmsvdS+7mp70/8fTwp4k64yHoci58NR1KdsF7p8Hkj3wBywKBQCBo1hyV8itFUZg1axaXXXYZWm2NbhQZGcnMmTO57bbbWLhwIWvWrOHyyy9nyJAhDB48+GgcikBwUhNs8ns8y6+Coo7v7SQ6ycKpF3cCoF/OmcQVpXFf2mrMo85AdbvJvulmPEVFBx747BfBkgDFO+CPB4MCluh+JRAcXez+17RWlhoXdAD+fga2/ogHLW/vPhvdbJ8z952xMuUjevDaqa+zaNYeSnKsGMN1nH19T/T+EpPiKicAceH1XbixYQbaxYfRLj6M1rEW0c5c0KyRZemAgg5AmLG2UycUnV7D0EntmXzvAOJahiG7VcbaDRR5+2F6/UssQ4egOp2UvPY6na55la8013BT7xsxaAwszVnKhfMuZEvxFl/78/8tgNSBvhKszy6AVR8c8XMWCAQCwbHlqIg6f/75J5mZmVxxxRX1fvbyyy9zzjnnMGnSJEaMGEFSUlKtEi2BQNB0ajqaH8fyK09N+VWAjgOT6OrP1xmz8wpKsx18OzkJfbt2eAoLyb7lVlSXa/8Dm2Ng4lu++yvfJa1oISAydQSCo02TWolv+s5XzgH8zqWMX7cEgO+HSGSf2om3R73Nhrl5ZG8txY1KUe8IwmNq2qQXV/tFHYsorRYIAMID5VfOxssd41uFM/me/hS3M+FCxVjpYd4n2WwecAuWR15El5qKt6iY4vse4sw3VvNZ31doGd6SXGsul/xyCR9s+gCXORpmzINe00D1wvzbYP7t4LYfq1MVCAQCwRHmqIg6Y8aMQVVVOnbsWO9nRqORN954g9LSUqxWK3PmzNlvno5AIGgc+QRo8x0o1TBqa18AjpjSkdTO0egUPeO2Xc0P2xaS98ClyGFh2NesIf+pp4KtixulwygYcgMAg3c8gx73ERV1XB6F5XtLcHq8B95YIPiPcMCuU8W74MfrAXB3nknK3CXoFIVlnSUyp53Cx2d9TNbyajYuzAbgZ7OL2ek17jxFUSn1l1/FhR+gI55A8B9hf06dUGSNTGELA+9HOMiL0yLJEvs2FDNvsYnM6a9guOZOJJ0O6+IlSNNv5gP3RZyWeipuxc0ra19h4o8T2VK+27docvoDvkFXvQ/vnQ4FW472aQoEAoHgKHBUu18JBIKjS6Ao4YDiyFFCVdVg96tA+VUAjU5m7DU9iG8VjskTxjnbruGRHR9iePQukCTKv/qass8+P/BOTn8QwltgcRRwgWYxinLkjv/zFRlMfXc5Hy5NP3KDCgTNnEBJpbkhp46qwk+3gMeBmjaS7J8K0Nus7E6G98elcXWXJ5j7cy6Lv94JwGKjm516hbiwGkdOhd2Nx69ExwqnjkAAQJjBV6JVN1OnIZweL1YZNiTKTHtoIG16xaEqKtuWF/DL9jTSr3wP+g5Hsdkof/hJ7pqn45lu95BgSiCrKotLfrmEr3d8g3rKHXDxbF+pc+FWePc0WPmeCK8TCASCZoYQdQSC5kyw/Or44PIqwbmfoYFVfb1Ryzk39CIiwUi4M5YRG6Zzn/NHYm69CYCCp5/Gunz5/neiM8LwWwC4TvsjKO4jdvx7iqp9x1HpOGJjCgTNnYBTx9iQU2fF25CxFLQmSsqG4FizFpseXj7XSHXRdK57Yw0Fv2aDCpt1HlYYfBeo2WW24BCB0qsIoxa9VkxDBAJoulMHwOkve65yuIlOsjDu2p6cf2c/2vSKAwn2bLOyOPZiCqY+jldnpOqXX2h/zSt85r6E01NPw624eWLFE9y95G5saUPh2n+h41ngdcLPd8AP14pyLIFAIGhGiNmUQNCMCZRfHa9FtUA7c6jv1AlgjtAz4aY+GMI1xNpb0HbZSN7qVEDkhAmgKOTcfgfugoL976jvpdj1saRKxQyq+v2IHX+5zScQiZwegaAGe0NOHUWBvx6HX+8BwNnpWgo//AKAD8bIZDouQKmI5NwKLQYkKsNlHL0jufY0X8vkKoeHCn9Hq+LqQOmVcOkIBAGakqkTwBUUdWq2TW4XybhrezL5nv4kt4/E41bYkh/D2rEvY+0zBqW6mvLHn+X2b1zc2+4aNJKGX/b9wvRfppOp2GHaVzDmCZBk2PAlfHgmlGcenZMVCAQCwRFFiDoCQTMmtCfM8SjBCrQzlyTQ76dLTkSciYk390NjgOSqdlh/jWLZRb0wdOqEt6SEnFtvQ3Xvx4GjM7GjvS94/ezyL8B74ElvUxCijkBQn0BOllnv717pssK3l8KSFwBQh91G1uytSG4Pa9tJxEw4D3NVXyZXG4hUZdQwLbc+PIxZMwdx91mdg23LA26dYEhymBB1BIIAQadOk8qv6os6ARJaR3De7X0583/dCYs2UFWpsCJyApvHv0hlTHusf/9N/zs/5yPLdcQaY9lVtotJcyfx0ZaP8Qy+Fi75AcyxkLcB3hkJe/8+oucpEAgEgiOPEHUEgmZMaKvf46FLBJw6Rq3mgG2H41LDGH9DH9AopJX14O/Z6RTff4UvOHntWgpffGm/j9/XegrFagQJnjzY9O0ROf5yu88x4D2COT0CQXMn4NQx6jRQnuVbsd/2E2j0MOFNyoo74l6/EYcOfr2gFXf0uovJNgNxikyVpDJ0ZheMYTUtnFOjTQDklPnKOUqCoo4ISRYIAkSafK+ZoionngN8KAWcOi6v0mDQvyRJtO+XwNSHBtF9RAqyLFFYaWR1z1vZ2/9KXBVWDPe/zIdr+zEsqh8Or4MX17zIRfMvYkdUElz1NyT3BnspfDoRlr4icnYEAoHgBEaIOgJBMyZURjkebpNASPJ+Wx+H0KJDNGf9ryeqpNKpcBAf/bEG/UO3AVD60UdU/vJL4w/Wm3nPc7bv/uLnjohbp8zqc+ocr6BpgeBEJJCp0827Dd47DfI3gSUeLvsJd4tR5D3va2X+zWk67h33Cove302ME2ySyuIWEn06x9UaLzXaDEC2X9QJll8Jp45AEKRtnIUIo5Zqp4cN2RX73dYVIvo05NYJYDBpGXlRJ6Y/MYSOgxIBSA/rw+rTn6E0uhPOH3/mjtdzeT7yCsL14Wwr3ca0+dP4PG8x6uW/QO+LQVXgz4fhu8vBLfLnTgS+WZXFL5vyjvdhCASCEwgh6ggEzRg51KlzHPYf6JJjPIiw03a9EzhlWnsAumWN5PX0vURdcTkAuffdj2PHzgYfJ0sSn3pHUylHQule2PjVYR49wYwP7/HsCS8QnGA43F4u0PzNjVm3grUIEnvA/xbgsEeTcfnlyDYnO1tA6qVXsW+2i5yd5Sgaie8sTgb3Tqrn2gs4dWpEHZ9TR3S+Eghq0GpkhnfwCaKLdxbtd9tQd87+RJ0A4TFGRl/ejXNu6EVYtAGrx8D6Xjexu9dlOHLyaX3Pu3y+dSSjEk7Brbh5ZuUz3LDkTkrPfBzOeRlkHWz5Hj49D6oLD+9EBYdFhc3N3XM2csvX61HE3EUgEPgRoo5A0JwJuXY6ruVXDXXJ2Q+9RrSm69h4ANpuHcJXqTFYhg5FtdvJvuEGvOXl9R4jSxI2jMwNm+z7xt/Pgsd1yMfu8ijB7AIxLxII/CgKA3a+xAu6d9CqbuhyLurlv1D681LSJ0/BvXcfpWHw9fkJtNswgvSNxWh0MiNnduHCM9tz86gO9YasEXUCmTqBoGRRfiUQhDKig+9zcfGu/Ys6gfIr8HXAaiqtu8cy7eFBdDulBQCZ0QNZc9qTVISn4fj2B254LYPH4i9HL+tZnL2YC36azMqU7nDJHDBEQua/8NZQ2HnkGhYIDo5KhxtV9eUqORoovRMIBP9NhKgjEDRjQhfE1ePg1Qk4dRpqZ34gTh3fnej+vvuaJa3ZfMFkdKmpuLOyyLn9DlRv7clKwJX0q/kcCEv0deVY/9khH3vApQOi/EogAHwi6ZwrGZj3OQD/pMxEGf8eufc9QsFjj6O6XKxpJ3HnTA1jzfexZ1Uxkixx1v+607NvEreN7hjMBQklpRGnjii/EghqM6KjT9TZkFVOVqmNMqsreAt1ZYSKOk1pgR6K3qjl1Is7c86NvbBE6qn2Wljb/072dbsQx74MutzzMZ/bL6ZNRBpF9iKu/P1KXi1bh/vynyGhm8+998VkmH+HaHt+HHCG/O0DpbICgUAgRB2BoBkjH/eg5ECg6sG/lUiSxLQrTsPdtgSNqmHXPLDe8QCS0Yj1n38oeuXVWtsHmms5McBwXw4Pi1845Br/cluNy8crRB3Bfx2XDb66CDbPxouGm1zXszlmCpmXX0Hlzz/jleGjM2RenWrm+pjnqVzpE29Om96ZtJ5x+x06kKmTVWrjty355JT7LgRFULJAUJsWUSbaJ4ShqHDKcwvp8/gfwdvkd5YFFyBCL+wrD1LUCdC6WyxTHxpEhwGJqCrsix/B2pGPUqWLRX3pPf7v9xSmJp+Nisr7m97nirXPUjz9Wxh8vW+AVe/5umPlbTzs8xY0ncC8C2o6FQoEAoEQdQSCZkztlubHfv8OT033q0NBkiWuvvlcSuOz0Cp6FsyvRnfXIwCUvPdereDkQE6HV1Gh3wyISIHKHFj78SHtuzzEqSPKrwT/aaoLfVkZu/8ArYl3U58iMz+ewc/cgn39eqqN8MRUmc1npPFC6nuUL/Q5bAZPbEuXockHHD4lyufUqXJ6uPrTNRRV+Zw68WHGo3dOAkEz5bIhrdHK9btJrskoY3dhNXDo5Vd1MVp0jJnZjTP/1x2DRUsl0aweeD+ZaWdiW7iYKU+t4LXY6wjXhbO+aD3Tfp/Byl4TYfpsn2O2eAd8MBrWfX7IxyA4OIRTRyAQNIQQdQSCZsyJUn51KE6dACaDkctvHU1peA56t4mfVmswXHoVALl334NtzRoANP6TVVRAZ4RTbvcN8PdzYCs96P2W20JFHaHqCE4eqhxuXvx9Bw/+sJlPlqU3uI2iqMzfmMfvP3yC87VBkLUcjJGoF3+PfkUWT/77HvqqCtIT4N7LNCQOH8XLHd5l63flAPQ4LZW+Z7Zu0vFYDFpuH92Rfq2jg7fLh6XRMsZ0hM5YIDh5uGRIGjufGMuep8YFb6f4A5QX7ShCUVQ8ISsRTQlKPhDt+yUw7aFBtO4Ri6JK7E4bz4ZBd2IttZN41+t8nHc2bcJak2/NZ+bvM3m4cAkVM3+DDmPA44Afr4OfbgGP87CPRbB/QkOyra7D/9sLBIKTAyHqCATNmNDyq+PhNnEGRZ1Dc+oESI1pwdjre1BhLERnM/NzZUf0p52J6nKRde11OHfvRva/WwUFmD6XQHxnsBXDn48c9D7LQsqvRAcJwcnEj+tzeW3Bbj5dnsFDP24Jru6HsmJXLoXf3MyY9TdicJZii+6E5/xvyXriA4YumYOMyl+9JB68TMdFZ9zO5crtLHx/N4pXpX2/BE6Z3KFel6v9ceMZHZh97dDg7eFzux3U4wWC/xKyLKEJuZ3aKQGARTsLa7UzhyMj6gBYIg2cfV1PTpveGa1BQ6mpNSuHPUJRdHc8733GK3MimBF/LgBzds1hwu+X8/vQK1FPvQ+QYM0smDUWKrKPyPEIGsbprvn7i/IrQXMkv8JBYeWhRScIGkeIOgLBScLxCPs91O5XDdE/rTddLwvHqitHKjexMGkc+t79UCoryfzfVWhLfN1AgqKOVu9rtQq+EqzM5Qe1vwrh1BGcpORV1A4vzS2vE2ZasJUu8yZwufY3AD70nMWC6PvZ97+7sf7zD04tvHG2zOfjY3ll2HtE/tqDf77bjcfppVXXGEbN6IrUQHmIQCA4OpzayRegvGpfWa0FCYBq56GXX9VFkiS6Dm/BhfcNIL5VOG5Vz6YeV7Ozy8XY1m3m3EcX8KnhOtpEtqHEUcLti+/gFiWX0ikfgTEKctbAOyMgY9kROyZBbUKdOqL8StDcsLu8nPXqYsb931JfnILgiCFEHYGgGVO7/OrYcyTKr0KZ2OdsDBMKcWpsOPO0LO81E7ltRzx5eUS9+DioKrUWKVsPhT7Tfffn3Qrepk9uQyfGdRY+BYJmTXFV7Yu+Equ/JEJVYeV78N5pRFXtokiNYKb9djI2xtHmmfvwFBSQGytx3wwNC9q34eaI/2P7e07y91aiN2k59eJOnHNDLzRH6PUuEAiaRts4C6nRJlxehb931G53fqScOqFEJZqZdFc/+oxuBUB24lDWDH2ICo8FwyP/xxtLO3Bd55loZS0LshZw/qZXWDLxRUjqCbYS+GQCbPruiB+XoGYxDcAmyq8EzYyteZWU29wUVztr5iaCI4KYmQkEzRiJ49z9yr9iZDjEoOSGuPGMqygYuQa37KQ8Q2Xt4NtQzBHotm5kYMG2+o6k0Y+DORYKt8Ky15u8n3LR0lxwklJ3olRc5QJFgZ/v8N08DvZGDeGqwtuYvGABU3cuQFYUlnSVuOcymWLLAAZtv4GS+WU4rR4SWocz5b4BdDslRTh0BILjgCRJDGkbC8DqjLJaPzsaog6ARiszdFJ7xt/UG3OEnmptDKsH3kt62lgq5//Gmc8s5su+r9Iush0ljhKuW/EoT/Ychb3TOPA6YfZM+P4asJcfleP7rxLq1BHlV4LmxtbciuD9QNMEwZFBiDoCQTMm9PqquZdfBZAlmYfPu5ONg+bh1NgozfWSfsatAFy29RcUb51JjDkGxjzhu7/oWShLb9J+Qluai/IrwclEUbXvud0qxtdKvKKiDGZfAaveByTUUU/wT9ZIHv37A1pXFVBm1vDC+TKvTdAwNeVaJm6ZTn+nr914r9Nbcv6d/YiMF6HGAsHxJNrie02WWWs78SoPo/tVU2jZNYapDw4krUcsiiqzN+0cVg+8j7L0EuSZdzMr/jamd/E5Zr/a9R0XGq3sHHwlSDJs+BLeGgp7Fh7VY/wvIbpfCZozm3Mqg/eFqHNkEaKOQNCMCQ0aPS5OnSNcfhXArDPz5KQHWNbjWwDSqxIobNGftpV59N69uv4Dek2DtFPAY4ef72zSLyO0+5VXaDqCk4iSat9EqXNSOC2lAqZvuhy2fA+yFs/pL5P10Ub6z/8EneJlTTsNd/wPVrc3cbPnSUzzuhDpkaiWVPpd0pHhUzqg0YqpgkBwvDHrfYsnoS5TgGrn0S/BMYXrGXddT0bP7IopXEe1KYlVA+4lR9+O3CuvJeFLheeGvUa8KZ59lfuYXrKEeWMfQY1Og8oc+HQi/HwXuGxH/VhPdgLzLgC7W4g6gubFljzh1DlaiJmaQNCMCS2EOB66RGBCYTqCTp0AyWHJPDTpDrakLAZgS6epuHThnL3mJ1R3nZVJSfKFJmv0sOt32PrjAccvs4nyK8HJh6qqFPtFnSGRpXyjf5wkVwaEJ1Pd/Vn23vM+1qVLcWkl3h8j8+xkwNGP89c9gXNVGKoK2/VeZoU7aNUt9viejEAgCBIQdeoGJR+t8qu6SJJExwFJXHj/QFp0iMIr69na9Qp2dpjCgN++JOzJb/luzBcMSR6C3WPn3m3vc1O3oeT39eferXwH3jkFshtYmBE0GafI1PlP4vEqTHt3OT0f+Y3hzy5gc07FgR90guHyKOzIrwp+XVQtRJ0jiRB1BIJmTGhQ8vEoIXIehfKrUHrE92Dy9FMpMeeiqiY2drmU+Moiyud8X3/juA4w3Femxa/3gKOy/jYhVIjyK8FJiNXlxeFW6CBlc9HWa0mWSkmXW1KsvZKs+1/CW1pKVqKGe2bI/NbbwIWu+5iy41Li3HoMFi2jZ3blJ7MLh1xzESkQCI4/Zr0WqO0yBag6QPnV8r0lPP3ztuDtm9VZh3UcligDE27pTfSAOFRUclucwuq+d2Bev5mKK67n/7o+xHW9rkMra1mUs5SJ1Wv46oxbUcKToWQ3fDAaFjwBHle9scUCy4ER5Vf/TfYWW1m2t4RKh4fsMju/b8k/3od00OwqrMIdYo0XTp0jixB1BIJmzMlafhXKaW1OpWToRrySh8qYruQmD6f49ddRbA3YuIffBjHtoCrPN2ncD6FOHdFWUXCyUFLtpI+0i6/1j2NwFrPV0YpViztQ9NYHoKr81UvinkuhJKw9p294lOi1SeiQSNd6GXBNN5J71LhzjpZYKxAIDp5g+ZV/QSLgkD2QU+emL9fxzuK9wdtd321kd2H1YR2LrJGxdwrnW4sLq6RiDUtlZf97yCg2kTnlQi519ePbc76lZ3xPrG4rT+6dzWWd+rCn2zmgKrD4eXj/DCjYGhxzXWYZA578k+/WZB/WsZ3s1Cq/EqJOs6Tc5mJDVvlBPabu6zyQndec2JJTe7FViDpHFiHqCATNnICuox6HAqxA96ujffF3yfAprGj1EwA720+islqi9JNP6m+oM8LZL/rur3wXctY2OJ7D7a1Viy40HcFJgarC6ll8rX+MGKmKam1X8v6MpHv2drxambfGybwzTsNFiddy/qYb6eS0IMkSWxNkvrW4KPV6gxcJsgQGkaUjEJwwBJw6gc+r2DBfcLLN5aXC3rBbR1VVSvzBytMHtyIuzABATrn9sI8nt9xOhk7h43AHmRovisbAlq5XsDV2DPuuvIaY+Sv4+MyPuXfgvZi1ZtaXbOYCx1beHHopLlM05G+Ed0fCP/8Hipfle0sprnaxaEfhYR/byYxw6jR/bv16PRPe+IdN2U0voarryCtuhqVLOwp8pVeJEb73ISHqHFnEjE0gaOYEvDrHx6njm1wcyZbmDdE/qT+uLmVkR+5A1ejZ0uUyit7/EE9JSf2N250GPaYAKsy7Bbz1VzEr60yAFaHqCJo7HifMvZHWy+5HL3lZWdiHnO/dtKguoShcw33TJRb30nGb9BTmn7sS7pUolxVGXtcNR1sLSJBbYa+VkxXqBBQIBMcXi6H252xCuIGUKF9Xuks/WMEXKzL5YkUm36/LDoYnOz1K0Il691md6ZIcDhyZi6mcMp8wFBNn4pswFyWtjSBBTsoprO51O7tf+YjCBx5iattJ/DjxR0amjsSjeHgrbxGTO3RjXftTwOuCPx6Ej85BX5UJ1MwrBA0T6tSpK+oUVjpYtKOQFXtL8HjF7/FEZUuuz7Gyq7DqAFvWUM+p0wwFEav/falDgv99qBkKUycyQtQRCJo5sv/C62QtvwowrePVLGz3OU6NjaqINPbGjaDwueca3vjMJ8EYCXkbfI6dOpTVySQQmTqCZo2jAj6bBOs+xavKzN48jLAFhShWK9tStNx7OdiTWnNb/ivY/rWgKipbdR4+DnfSpmMMyVFGAPIrHMGLBJPfFSAQCE4M6mZcmfQa3ru0P9FmHRuyK7jv+03c9/0mbv16A28t2g3Uvug367XEhx25FfLcCp+o0ykxHFWCjGQd597YC3OEHqslmdV972TDGiv7pkwlOt/Ka6e/xvMjnyfGGMPeqkwu9WbwRL/xVBvCIPNfpq+7iAs1C3G6Rfjv/qjt1Kn5XSmKyjmvLWXGrFVc+O5y3lm893gcnuAAONxeCv2vv4N5HQZEnTi/Q685ijou/3M3IEY3x3M4kRGijkDQzDmu5VfuY1N+BdA1phflrhQWt/0GgPTWZ5G5cBPWf/+tv3FYAox61Hd/wRNQXjsYsrxO9xBh1BE0WyrzYNY4SF+CIoezeutpdN28DwmVv/sZeOxiFb2jL5M23knVPgWtXqbPBe2Yb3ajaiVMOg3Jkb4J1msLdnPndxsAEZIsEJxomOsIrXqNTNcWEXx99RDO75PC6K6JdEr0rYAHXDSBlXGjTkYjS8SH+0SdI1G6EdhHB/8+q50eWnWNZepDA2nbJx5V1rK37QSWmcex9eKrqZg9mzNbn8nciXM5r/15AHxdup4JbTuwsFUfDIqNZ3XvcUvhg1DV/EJgjxVOT8NOHavLExQLAPYUHV5ukuDokFfhCN4/mNdhoPyqTZwl+NjmFizu9LvHUqJ9c44qh6eW80xweAhRRyBo5kgcT6fO0e1+FYosSbgKz2JP7AZ2xq0CSWZLl8vIevRpFIej/gP6XgathoDbCj/fUesXJJw6gpOCop2+TjIFm3FLiWSs6knEpm14JIkPzjLwxhgvnUvGMXHnZXhtCjEtLEy5bwBRXaNBgkiTHkmSSI40Bofc7A8ybBljOl5nJRAIGqCu0Booe+6YGM5LF/bmvUv7M2NYGgDVTt+FUuCi3+IXhOKOkFPH4fYGs3oCQpLV7xoxhek566runHFZF3QGmYrIdqzofhtrXv+ZrGuvx1xm59Ghj2LLuBLFFUuho4SbNCVc1GoQGbKefq6V8OZg2NJAl0tBrfK00KDkuqVYlXbheDoRyS6rafJRfBBhxwGnTkDUcXoUqpzN62/s9jt1YsP06P2ZfcKtc+QQoo5A0MwJOHWOS0tzz7Erv5IlCcWVgFQ9iKVtvsNprMJhimercRDFb73dwANkOPdVkHWw81fY+mPwRxV23wepRvb98oSoI2h2ZK2ED8dARRYObxvS/0jAsWsf1SY9j18k83tvhfNLruGUPWehRUKTambSXf2ITrIEQ1UjTb4Lvd4to9BrZFrGmHjyvO68c0k/3rio7/E8O4FAUId6Tp0GgswtBt82AYdOoDzH7M/jOVinztJdxdw7Z1O9LkuBoGWLXhNcda8OyfyQJInOQ5KZ+uAgkttH4tUa2d55OsuK2rN9woUUf/4FirUt1r23MDR2MhpJwyZNHue2TOWlyDS89jL4dgZ8ezlYi5t0rP8Vajl1QkrV6ok6B2h1Lzg+BBxucHBOnUBOVny4gTD/67y4mQkiLr9TR6+Ra0pBRa7OEUOIOgJBMydYfnU8nTpHOSgZfN14ANSy0WiMEr+2mwWo5CUPZfsPq3Bs317/QfGd4JTbfPd/uQvs5UCNUyfa7KtNVkSeoKA5seNX+Hg82MuodnYjfZ6Mp7iEkiQzd8/wsjvFyLR9D5CwswsAywxuqvtHoTf6JoI1oo4OgLbxYax6YBQLbz+Viwe15sxuSUT5XxsCgeDEoG5QckOiTph/m+qgqHN4Tp3pH6zgy5WZvPD7jlrfz/WLOi2iTMELzIA7KJSIOBMTb+vLkPPaIctQHN+b5d1uZfub3/PM0rdJqq4kxjWRr8/5mgg6oMoeZsUoXNGpL5k6PWyZA68PgI3fHp9JzlHG4faSVWo78Ia1HtOwU8dax7VRtyGE4MQgtPPcwbhUAiJduFEXFGebm8slkKmj18rN9hxOZISoIxA0cySOX4eaY5mpE3DVqJ4ILut2GXkRe9jTZhUA29tfyJ47HsRbba3/wOG3QWx7qC6Av3w5O+V+USfW4hd1TsLJouAkZe0n8NVF4LFTWtGPrB8rUO12drUzcfs0JzZjAuPXPUxEQRwanYwyKIalJg+Ldxfzyp87eX3BLjbn+NqoBkSdwH2tRkwJBIITlbqLJ4aGnDr62k6dwP8m/aE5dQIs21O702RA1EmJDhV1GhYRZFmi75mtmXzfAGJaWHDpI9jY8zoMMf15bdH/YfzlRzpGd6STeg+OvPNAMbDWVcykVq34KKUDbnspzLkSvrnUFwp/EvHI3C2c8txCft2cx86CKm76ch0TXl/Ke/sJOW6spXldp07dbkmhZJfZOP/Nfzj1+YVcPmtlLfeP4OiSfYhOncDfM9yoDYYlH0z51olAUNTRCFHnaCDaWwgEzRz5OJVfebwKHn/C8LEqvwLwKiozus3gmx3f8FfCV3Sq6IW7NIwN5lOJfPgRUl54rnYrZp3RV4b10dmw+kPoeSHlNjMAMULUEZzAOD1eZn60mtgwPa9e2BsWPQN/P4OqQmHuIEqX+ALA/+lj5PXRLtrTh4GrL8GiaNGH6Rh/Qy+WlFTCjhw2ZlewMbv2BVGoqCMQCE5sZFnCrNcEL973V37VmFMncCFVZnPj8ijBMX5Yl8MXKzKDn4XJUSaem9QzOG5WWW03SaCEpEWUKbhPh1vB41UaFYfjUsOZfG9/lv+wlw1/ZZGTMpKy6M6M2fg5e2dcgbHnJNzlgzC4uzB44F+syF/Bi3qY27EnD2btps+2uZC/ES6YBSknR3noV6t87+HXfLaW1GhT8IJ/b5GVmcPb8NTP22iXEMa0ga2CjwkVYOxuL6qqIklSMNPIotdgdXn369RZtKOItZnlAKSX2NiQVcHANjFH+vQEDRBaflVqdeFV1OCi5f6oatCp00Ce5AlMsPwqxKlTKESdI4ZYlhMImjnScWhpnl5s5YEfNge/PiZBySH5NxadhWt6XYMie/m+7dvIGpWymC5s2Wjn64dfq19LnjYc+kz33f/pZqqsvglqjH+1wyvaXwlOQH5Yl8PS3cXMW5+F98cb4e9nUDwSOTtqBJ2vRuh49Uw3Q5SxnL72CiyKljKtygV39SMxLYJxPZK46YwOTB/ciin9U2uNL0QdgaB5ERqW3JCoE26s49QJZOr4Hxdl0gUvIEusNRdTL/+5k5XppazOKGN1Rhk/bchl+b4ad05d10dOue9iMiXKVKsszOoXkb5YkcnPm/LqHZ9Wp2H45A4MmNGJKknBZk5kbZ/b2FTaiis+fYIz01fgsEXw7ph3eXToo0QaItnlLufSpDieSG6FozwDPhgDK94JTno+X5HBlHeWUWFrfuVGlpC/Z3aZnYRwA5IEVU4Pf+8q4v2l+3jml9ql5c6Q8itVrSnHsvnL35L8wfdVTk+jc5u6HYcKm5k40JwJLb9SVJ+w0xRqO3Vq59GUVDtrBTCfqISWXyWG+56nhZXiuXekEKKOQNDMCej7x1KWeG/J3uAKU4RR26AN/EhT15F0QccL6BHXgxzdXnZ187U139NmPC1//YVX3ppXf4DRj4M5Doq2M6Lwc6Cm/EoYdQTHi805FTz4w2bKbfUndnPW5mDCwXu6F9Gs/xSPQ0vGur5Urc9C0Wp4dbyGOcNUumZMpvuasagelX1aL+rpiUQn+NxoZr2W20Z35ImJPXh2Uk9ahHS6EqKOQNC8CA1LNjSQZRcMSnZ5URQ1eKEf+L4sSzWlG1W+9xxVVcnzizRPn9+DDglhQI1IEMAVUvaTVxFw6hgxaDXo/e6caqeHwkoH932/iVu/Xt+oqBCRFs6scCcb9b4L1ZyUkazvfQeXZG7hoX/ew5mbz/kdzueniT8xqcMkAL42wkVtOrBXo/oy8r65BKwlfLkyk5X7SlmZXtq0X+IJhNlQu2DijjGdaBHpC57+Y2sB4MtAC/091i2VCoRhB/5PCnmPr26kBKueqFMp3BLHArdXCb52tP5JbVPLjwLuuwijNhgyXFzlosLmZvTLixn+7EJOfX4hG7PLD/n4vliRyTmvLWHC60v5dXP+IY/TGKFByUmRvnPIF6LOEUOIOgJBcycYlHzslImAXXJcjyQ+vmJg7XKno0Sg/Cowt9HJOp4b8RzhunD+MH+DklaOKmvZ0flShn75Ot7q6toDmGPgrGcAOK/6S9pIeTVByULVERwnXvx9B58uz+Ctv/fU+n56sZXd+/bxpf4JTtesx241k/5vZxx78nBZDDwyFf7tqmHItusYkXcKqLDJ6GWOxcV5g1o2uC9JkhjaPi74dYQQdQSCZkWoU6ehxZSwEJHA6vLUc+pASFhyte9iqtTqwuVVkCSY1Dc1KAo4PV6izDXvEZmlNZl1Bf4LscQI37YBt47V6SG3wuF/vNJoZojTreCU4Tezm28sTtxGGacxhg09r8cSM4jd519E+fc/EGWI4pGhj/DOqHeIMcawS3UwtWUrvoqIxLvtJ3hzEP2ti4PH29wIFV26p0QwqV8qaXE+Qf6vbQXBn4WWUoU6daCmxC7wf5RJHyyJb6wDlr2OqCM6EB0b8iscKKpP1Ggb72tN3tRcnRqnTkj5VbWT2Wuzg26f9BIb8zfWd8g1lTcW7mZzTiUbsiv48J99hzxOY4Q6dZL84mV+xZEXdVRVpaDSQW65/T/lQhOijkDQzKkrdhwLyvwfIOf2bEGfVtHHZJ+hmToBUsNTeWToIyDBx3HPUi07sZsTqUw+jbwHH6wvdPW4ANqdgR43T2o/INbim7B6hagjOE5sy6sC4Kf1uSghz+3fli5jtv4Rest7ySuIIn1BC9yFpVTEm7jzYg+7WxiYtPMhepV3AmCR0c2vBhftk8Lo1iKi0f0Nax8bvC+cOgJB8+JAoo5BKwfLq6xOb02mTojYEwxL9jt18vwXVXFhBvRaOegAcriVWu6c3YU1CyUBZ0dA1Anzl31VOTy1nAeNXbCFhv1m6BR29A5jeySoqOQnDWJZt1tZ9/Icsq69DndhIUNThjJ7/GwGJw/Grnp4MjaSS1qlsc1dziOO53hD9wqStWg/v7kTD49XCYor824czldXDUEjS6TF+i72C0LcMxUhoo6jjngVGCNUwIsw+t7bGxN1HHWEIeHUOfq8+PsOxr66BPA53BL85UdNEXVUVQ1m6oQZtLW62H2xMhOAaL8AW1ewOxhCHcONubwOh8D7iU4jk+R/7zgaTp0Hf9zMoKf+YugzC7j0g5VHfPwTFSHqCATNnBqTzLETJkr9b/yBoOFjQWiOXKhYMyZtDBd2uhCnzsafHT5B9bc53726kPKvvqo9iCTBOS9hV/UM1WylZ8nPgGhpLjg+VNjcwQlNboWDVf7yASVvMxesn0maXMCevYkULwoDq42s1mZuu8iFPSKe69KfJa40GjcqP5qd7ImVSYo0cvMZHffrnBvarsapI6RMgaB5ESrONJSpI0lSMKel2ukJZus07NTxXUwGhJfARZbB7/Jwery1xJeAqGN1eqjyjxt06oR03QpdGc9rVNSpfeFpVRSWRyh8HuakWPbi1oeztesMlpZ2Z/OkGVT8NI9YYyzvjH6Hewbeg0VnYZNGYWpKC56KiWakdhWjFoxvVq3Pq0NakHdKCg+6rAKiTijlflHHq6i4vb7zC/xNg06dkFK7gAuz0r7/8qvUaJ9b4r/kZjgeOD1e3l+yL/g3H9IuLqSD1YFFHadHCf7dw43aoDC7KaeC3YXVmHQapgzwOXTrOrmaiturBDOxoEYkPJIEyq8MWjnoCCy3ueuVAx4ui3cWA74SN63m+HUIPtaI7lcCQTMnmKlzDOcxAavnsRR1QrsDeBW11hv1nQPuZH3henawmdUJqxhQOJAdnaYR+eLzGHv2xNStW3BbR1hLXvZM4j7dl3Tb9BwxPIOqGhEIjjU7Cqpqff3Goj24M1cw6N9riFEr2LY5FbYoaFFY3dXIy+OcpKhdGL/zOlyVKm6txNdGB7dO7cGU/g2XXNUlcBEG0CWpcUePQCA48TCFNCXQN9JlKsygpdLhE3Tqdr8C6rUSzvMLy4GLrEDrdGudoN21meVkl9mCq+0WvSYoRAT+tzprO3UKGlmFD3UAAdicHpxuL0ValY/DXbzVrz37/s6hLKYLyyPbkf/aL3T77XdaPPIQF3e5mNGtR/P8quf5Nf1XvowM51dLOPeVFnPmnCuRtsyBc16G8KTGf5EnAIFyGqNORhfyt0yLqy/qBJw6oWJYtFmPzWUPydTx/cyk1wQDsw/k1GkVYya7zC7aSh9lVqeXYXd7iQ83MOfaoaRGm3hy/raan7l24fWvLsZY9Fw8uHWt50Tg7yhJvtdycmTtOev4Xi2COTuHWoZYt1ua1Xloos6P63PYGTK3GdkxIdhZLbT8KsKoxaTTYHd7ya9wNPi8PxS8ihrMLfr7rtNIiTAckXGbA0LUEQiaOce6/MrjVYITjOhjKOqEug/qnqtBY+D5kc9z7pwLWNfmS1Ir2pNMDFs6TMdyy220m/MdmvBwAMpsLj7wjmOi5l+6ujJ4QPcZz6q3HrPzEAgC7MivBHyB3SVWF+7di+iT8QJaxcnmVa3QpvsmVT8M0vHlaW76u05n4ObzcLlUopMt/BLlJi/PVitHoyn8c8/pZBRb6ZEaecTPSSAQHD1CnToBR01dwoxaqMAv6vidOoYGnDpVAaeO7wIocKFoCOax1L6oW7C9kAXbC7ljTEcAEkMuLIPlV3VEnfxKR60LuQDOuqKOy4vD/z1FghZDkxh0akv+/mw72TvL2dt2AgXlOXSdcj2d75xBwtixPD/yeca3ncA1vz5Amb6EOxPi+MHu4P49v9PyjYG+DL1e00LtzCcUAVEnzFC7DLaNP1MnlKCoE+LCiLboyCm3Bx06tpCW5sHyq0bamgdKuFrFmPl3T4loK32UWbzTVxo4okM8LWN8f9+AuPr71gJ+31pQa/uYMAPje7UIfl0dfK5okWWJhAgjT57XnQ1Z5Zj1Wq47rR2/+YON65bWNZWKOs+V6kMQdTJKrNz81fpa3/t6VTarHxgF+NxA4HsvkCSJ5Egje4ut5B2qqKN4oSIbtSKbirI9FJTuIr10H5eE7cbgtDL7WQ8RhjBmPLLq4MduhghRRyBo5gTmK+oxKqaosLuDrqCoY5jJEerUaSjYuE1kGwzlk3HFfM5fXd7g0q0PUhHZjt2l3THfdz8p//cqkiRRbnPjRcMzumv5WLmP8zVL+ct7OjDqmJ2LQACwPd+3mjW5f0u6VCxm3I7nkF0eNi5pjb7QjSJLvDdG5q8+KqeUXEj3XcPwqiqpnaM566rufPrecqD2hV5TSIkykRJlOuLnIxAIji61Wppr6ne/gpr3g6pGnDqB135mqa8FcqBEqq5TJ7RF+MC0GLbkVmB1eflxfS5AsCVx6D7rOnUyS22c/uIizHoNv90yIrg4E3ATGHUyDreCzeWp5d6xu71EpUYy/tY+7FxZwNKvtmMlhVUdryb3zSX0+m0BLR++j97xg7DuvQV97CJM8X/zj8nIxNQWXFlezswfrkW/eQ6c+wpEph74l3uMCe1mFEpqtBlJqu2+rnHqBDJJpKCYbwtm6vj+N+tDyq8ayUVx+h8TEBhKrS7cXqWWO0TQOF5FrTUnPRB/B0SdjjXlzwFxFaBDQhhD28WyJrOMzTmVbM6pqCXqBATAgFgHcPGg1lw8qHXwa4PfxXeoTp1AiZ9Fr8Hq8uJwK3i8CtqDeE4E3lNiLHrGdE3kq1VZlFqdqKqKqhIsIQu4DBMjfKJOY46+eqgqatEO9m3/gTU7/iQ9IxtXOVjKJGIqJWIrVeIqYXJN13iyE6vhkSafQrNGvHoFgmaP74PlWJVflfnzdCJNuoN6sz9cQj8/G+tWFcdQ3OX9qDYV82/77wHYlzaWrJV7Kf3wQ6Dm+HMtXSnrfjkA93rfAZftKB69QFCfHX5RZ7RnIRN23ANWL3sXt0Ff6Mah0/DsJIkFvWUG7biKbjuHoarQZVgy59zYC4NZF7RHhxkavrgTCAQnF7VEnQYydaB2KVRDmTodEn0ty3cXVqMoajBTJ+DUqds5Sa+R+eaaIdx4RgcAdvmzdRJDyhrC/fusdnhquT7+2FpAdpmdnQXVtVb+A46TQAfKMlttl0AgY0OSJDoNSuLix4fReXAiADkpp/BnxVD+vegeSmd/j6RocBWPZmL8SwxOHoxLgjejo5iU2oLl2YvhjcGw8j3wNuxaOV5UO/3Bt3VEHaNOE2xrHqDCP28J/F4MWk2wvb09UH7l//1aDJqgUNSoU8f/+0+ONAZbaze1C9N/nSW7iuhw/898vSrzgNtuzqnglT93sj2/CkmCUzrEB3/WJr7GmfLRFQN5dEJ3pg1sBdTMDQLUdL5qfAEnEJxe1wXXVALCYYuQBR+r8+AEokDgdpfkcO4d1wXwOetdXiWYpwOg8x9r4D2nsewtAG/eTvZ++QC/3zOSb6Z3Zc6l55F/68d0fzGHc76TOP9PiTPXwIBdKm0LIMIv6Dj0MtaUSKI79zqoc2jOCKeOQNDMCTh1jlVb7lKr743/WObpQE2ZGdTugFUXR/4EZFMW6yMX0aFlL2Kz2rKlywwsrzyDsUsXKsLbAD6XUenAO3Fs/J5UqQD+fhZGP3rUz0Pw30NRVDx1nrMqKjsKqrhI8xf91nyAs0JL5r+t8FQ4sEUYePR8D1kJRs7bdTcJpb7VvcET29L3zNbB1W5rcBIvPsoFgv8C5hDHTUPdr6B2aHFD3a9ax5jRa2Tsbi855faQoGSTf1y/U8d/kRfYT4eEsFr7Cc3nCoxf7art1Al131Q6PIT7nQaBC7xos568Cke90o+6wanGMB1nzOhG56EtWPjhRirKI9nU+kIKZq/m+cJ/eKfbWIyM5N3R7/Jr+q88t+o50inmf8mJDLI7uGrB/QxY8RbSGY9Al3NPiJKsqpCSmrq0ibOQU25Hp5Fwe9V6Th2jTsZUJyi5pvtVqFOnMVEn4OrREBdmIL/SQWGlk+RI4eA8EE/9vB1Fhbtnb+LCAa0a3a7C5uaSD1YEBcueKZG15s19WkbxziX96JocEXTPdU7yxQTUF3V8Y+xf1Al0rTu8TJ24MAMZJTZcXoVql4dIc9Md+YHw9YRwY1Ac9h2TUuslF3TqRBqRVIXKrBxsKwpw796KY99OKtJ3UZmViVpqw1zlc6C09N9CscdZ0LZrh7lDRyLbdsLYIpVvM9y8v76KMzq2ZFrPFLSNlKmejIiZoEDQzAk4WI6VUycQkhx9EG/0RwJ5P5k6AdyKAqoeR/Z0Yjq8xQ/Jb3NFxeM4iWFHhwsx3HY71Q/+HwBRZj0YwnnQfTkf6F+Ef1+DHpMhqfuxOB3Bf4Tiaidn/9+SWu1pA0zT/MVTug+wFujJXpaE4nBSlmjmgfOd2C3RXJP+IJ4SLR5UlIEx9DsrrdbjAyvfoaUVAoHg5KUpTp2gwOL01mpzHUCrkWkbb2F7fhU7C6qCq+R1nTpBUcf/dcfE8Fr7aVDUcXiCF3Z1qbS7gxevQaeOpeF5RGNtmVM6RjPt8VNYPX8Pa37NpDChP7qojtyz/Qds9s14Bz/G2DZjGZ4ynNfWvca3O75lhcnICpORXo5qbpx7JYMWd4LB10L3C0Crb3LZUaXDjdujEBt2ZIJX9+e+mDE0Da+i0ibewhcrMoN/i1pOHV1tUcfuqhFqajJ1Gi6/Cvx+DToNCRF+UUfk6jSJxAgD2/J89/Mq7I0KYf+3YBdlNjep0SZO7RTPhf1rC0CSJHFmt9ph3h38r7H8SgcVNndQUNmfABjAqDsyTp1Ikw6LQYPLpjQpLFlVVdw5OTi2bSN23jJu2r6Xnhkaiv/V8+j2fCSg9K45qJLKU7vz0aoesq55D2txIacVVjCuUkH7I2TUGTc0YafKCGVJeuQ2KcT1OYW2A0ajT+1AeSWUF1gpzLexs8BG2Q4btkKFi9Uo2FDFwg3biU0No+PAEzs0/UghZoICQTNH4tiuOB2PzldQJ1OnEVXH46/XVVwJTEi9lW8yn+L7Vq9z/tbbKEzoR3bZdpJeegRd36uIMuuQJfhL6cfv6iDGsAJ+uglm/gGyKGcRHBnWZZY3KOhM1Szgad0HVGYbyV0Wh+r1kNUmjIfH2wmT2jBjx614qkDVy3ylt3FWfO3Xm9urBCdvBxuULBAImifmA7Q0hxqRwOr0BEN0zXWE3/YJYWzPr2JNRlnwAj+QqRNw5gRcHgEHQEqUKditBmqLOoHyq7wKR73OVgGqQvJdArkfUaaG5xH7a8us0ckMmtiBtF6JzH9nPfbyCLZ3uZTI8t1smDiDNlddSPTUC7lv0H3M6DaDWZtnMXvXbDYY4crkRPo68rnwj9sZvehp1rS6isvXtuHtSwcxsmN8o/sEGP/aUspsblbcdwZG3eHPERoLSgYY1TWRUV0T+Wy571K33FbbqWPQyiHinW+c2pk6/lylAzh1jFoNCSHd0KqdHl79cyend05kSLvYwz7Hk5HQBdRX/9zF3iIrN5zenhH+58+sf/Yxe2022/N8bpunzusR/NmBiDDqSIkykVNuZ0dBVbBrVGXQqdP4YmrgdXrIoo7/ORZl1mExaCmzuRsMS1YcDmyrVmP9Zyn2dSux79wDdt91QXf/jQyoBAb6H+PwKzZ9/F979oEB3w3AK0FxJBRGShRGQXGkhMNswB7eigsmXEb/Xmdhd8i8M3srap4d4xdWDFVrGjwPCXChYo4xkNIinKik+sHjJytiJigQNHOkY+zUCWTSBGrhjxVNydTxhNTsJmkGMb3LdD7b9hnrWv9On31nsqPDFPqvfYHLtv2CdOpNQaHoKXUGY4zbIGcNrHofBl19NE9F8B+ixL9qPbJjPK9d5JvS6DZ9jWn++9iK9OQuj0P1KmzqEc4zZ9loa+/PGTsvxeOC6CQzZf2iyPtnT/DiLEDoCpoovxII/htYQhw3jZZf+TO2qp2eBp06AB0SwoE8Fu/yBbhGm3VBoSLwf+AiL7AfWZbokBjGxuwKoHamTuA9aF+xFfCt9ktSjRgBtfNdAheeUY04fh1NCHtNbBNB+xmdef3tdQyza6iIas+KyBvJ+XIRnb67iJTbbiB5+HDuH3w/GXuG8Hfx15hiVrDWaGSt0cgrHg+XpT/DbE04cz89nZF33NdooLLLo5Be4svdK652khp9+BeKgUyd/ZXURPrLqOq2NDfoNPVa09fO1DlQ+VVNGVdgnMIqB8//up2Pl2UwZ20Oi+86TXy2NECJtWaR5qtVWQC8/feeoHDz2oLdwcXPUV0SmizoBOiYGFZP1AmIK/stv/I7dQ61/Ko8xKkTmsvlrarCvnEj9nVrsS1bjHXjNqQ6+/DIkBkPWfESBVESDj3IKshKzf8aRUWRwKuRkDQgm3VYElqw0hZGZUQqaSld+G2bhOKJQPKYiVBkom0Sw7a34s9/d5CxvZSIOnpVpaRQqlEplVWI0PLwRb245seNbC238+XM3v85YVK8WgWCZk5NS/Njlanjd+qEHVtRR5KkYEeIxsuvan5QXO3kjmG3sbl4MyvUX2hR1ZHE4jZs7nYl49c8i+zJRpbSAMhXo2HUwzD/dvjrMeh89gnZLUPQ/AiETyZFGH0T7czl8MstuKo0ZC9PRvW42dTFxBPjbAwsG0ufXWNRVEjpFM3Yq7vz5bpswJdVEUpgkqfXyI2u2AsEgpMLc5NEnZqQ3MDFe92L80BY8uacSgCSQkpIAheHVYH3mJD9dEgIDxF1QsuvfMcVEHXiww1oZam2qBMiMATcPBaDFr1WrufuCZQSHQinorLS6GGb3svFujDCSyCr5RkUOPvR9uGPSdU/Q9yFk6E6FWfBeK7ofgUR8Wv5esdX5DlKeSY2hugoL2OsP7Pyre/om9gPbfcLoOtEsNRcENpC3n+bemwHoroJ4bcB0aum/KrGqZMQFGN8nzENdr9qpPyqpvuYhnh/F7PFO4tYn1UOQInVxYdL9wXDsQU1lFS76n0v4F7zKmpw4fPt6X0Z2THhoMfvlBTBwh1F7MivDH6vplSvcaeOsQlOHbdX4Y+tBVTY3bRPCGNAWkzwZxV2N7KqkFyaw8idq5iweyPRy59lR0ERUsicWwJKwmF9W4ntqRJ5STKahDCSLXFkFBgpro5nxsjTGdmpF5e8t46CSi+fXTGMCIORc19bTrTZyLqHxqCqKtn51cx5cSnRlRLWTIlzFZke4Wbc1S4Uv/O+aGlBcL/Vkoo+xYw+1QyJRiJNGiKBXxbuodppZ6ZeZXe1AyRIjf7v5UMJUUcgOEk4RkYdygKizjF26oBPwPKqapOcOkVVTnQaHS+MfIEp86bwc9q7nF9xPxDPtk7T6f3C49Dza8AvEvW7AjZ+A1kr4Oe7YNoXx+CMBCc7xf4JYGyYHsoy4OvpeOwespan4bU62ddCy3NjXYzJv4w2Gf0A6DI0mZEXdUKjlYPlFrY6NuhAVwqL6HwlEPxnCC2jaqyleWCVPTTbpq5Tp2Ni7dDj7i0igvcDF4eBj1lDSKlRh5DHJYR2v6ojTMSHGTDoZLaHBL425NTRa2TMek09Ucexn/KrUAJiS5WssreTmfv7tWHxF9upLIlie6eL2eOqJOWbJVyb+zZnhMfhMp3NxXdfwRU9ruCHXT/w+JLXKdOX83VEOF9HhBPjzeD05Y8zeuGDDEgegq7nFOg8Dqur5vway/s5WJqSk9KYU8eok0nwi2qF/nbQoZk6gb/HgZ06NeVXazPLAWgdayajxMa7i/dy6ZC0gwrKPdlRVTUo6iRGGIKl1YHfZ4XdHXzdjOqSeEgdYjsl+V5jc9fnsiXXJ+xk+VuFN8Wp49zP8/P7dTnc9d1GALQoLJqUhGHT7xSsX8HELVlcWuhA92P9x+VHwa4UiZ0tJDJaaYhvnUKfpAHMbH82PZL6oUFDaZ6Vq175lzYulfiNyezZ6GBMXhxel8L2D7KQJYnLK81oqyW+eGQ5tkoXTpuHi6idUeUs9b9vyRJFeHGbZTQJRn4uKqdb51g+njmo3vFlldr5cmUmry3YjcurIEs15aT/JYSoIxA0c2rKr46RUydQfnWMM3UANJKEl/2JOjXfD0xoEy2JPDfiOa787X/82fltzt98G8XxvdlXmU67Jx5GihuPqkogy3DOK/DOKbBjPmz7ydclQyA4DAJOnVS9FT67GKWyiOwVrXCVOCmOlHjqApWR9ouCgk7dDlc1NujaE7Vq0flKIPjPUcup00hXl0BweqAsRyNL9Vw9rWMttb6+e2znRscNfWxADIo264IZHqH7DBAfbqh3AVrZQKaOQStj1mkop073qyaUX0Ft14zLq9C6WyzTHhnMpkU5bPwrk+ryCNLTziaj1RgSC1bTZu4cdv38CVETJzLxwincvedONJbdaCM2ER+/g1Kq+C4inO8iIMq9jdOX3MPoP+6ga8JwxsidWKT0DgYTHy5VzgO7L+qJOkGnjqaWU8flqWkZbdFrQ4KSD5Cpo5MZ2TGetFgzxdUukiONfDJzINPeXU56iY3VGaWc0SXxcE/1hMftVbj4/RVsyq7AYtDy5sV9g6VPoVQ5PcHf86I7TmNbfiXnv/lvcLEz4GSPNOkOSdAB6NsqGlnyvV7W+YW2AG3jLA0/iJrXqaOuU0dV8WRsonTpPCIWL+KNvHwiy9xElqlU/SBRBWiAgC/NrofdyRK7UmBnC4nSFD1dktvTv+WpXNN2DG2j2oECRVnV5G4p57cftpK3uxynzcPpflkhe20xAL5njoyjxPdeFIcMCpTl24KHZ4k2YI41EhFvIjnVl4ETnWjGa9TQ78k/fIuupXYkLdwV8j4VyrSBLflyZSbL9pYAkBxpalL4+cmGmA0KBM2cmvKrY7O/4+nUCQhYjbU0dys1H2Y5ZXY25/hs4j3j+0PZWRTF/MI/bb9n+J5J7Gk7nrBNb3FB0iJmdzrd96DErjDsFljyAvx8J7QZAcbIo3lKgpOckmoXJhyM3XQzaulu8tamYM/1YDNKPDlFpl/EeNr9MxgVOOXCjvQ8rXbZX+Aizuqq69Q58CqvQCA4uajt1Nl/+VWgLMes1wRF4gA6jczQdrGsTi/jo8sHEBfS0cmore3qCRV1BraJpUdKZL2sirricny4gUsGt8ao01BS7eSH9bm1nToBcSKkNXcoTS1xCnXNBMbU6jT0Gd2KnqensnddERv+yqJgXyX5yUPITx5CdNkOWs5bQOzHn/B8fDvmtR7Ev8kTWXjjOFblr+KPjD/4K/13ylyVzAkPY044hHs2clqL5bxq/ZDkJaeDZ5pvfqA7cInH+qxy2sRZggJNgECIcdj+yq/8QdI2lxeXRwmKXQatHCx/K7W6arWEN+k1NUHJTg+KoiKHhBK6vQoe/xzKpNMQFaln0Z2n1dpv2/gw0ktstdrTNxcURcXh8dYLB98fO/KrWLmvFPA9p2avyW5Q1Am4dCx6DSZ9jbBWanOhqjWlV4fcSMReRmtPLr9f0YYsqw5FY0DnLEPvLMWiFBFjn8uWBbmUWvMpc5TgVbzoNQaMWiMqeqaEF2P0VDP/qReQsiow5Dqw5HmIrPT9/VvX2pmEUwtZcVCYqCE73sDeuHBa9upKblUs/2aEc+mgIdw7ejguu4f8fZXkL61gy54NFOyrxF1noUmjl9mruKnUwZWjO6A3aXn7373sKLVyw+iOhBm1PPbTVpKjjLw8pTcGi5bIBDO6Bl7/AXqkRrHBXxJ42ZA0urVoeD7eIyWSXi1rtu2Z+t+ct4vZoEDQzKmZqx0bVafEehydOv6JSWOmpFCnzt5iK+e8tjTkp6dg0WeyOX4xKfa2tMntw5aulzN5zQvsikoFzvZtNuJO2PI9lO6Bvx6Hs184Oicj+E9QVmXlTd2rRJdtonBbApV7VLwyPH+eRExqP3qsPAun6qHzkCR6nJpS7/GhgYWhCFFHIPjvEVpueaDuVwHXQF0XTYAPLhtApcNdKxsHGnLq1OwzzKDlpxuH1xsrMcKILNUsLqXFWUiLs/DgOV15fcEuoE73K29N+VVDbkNnE506tjpOnVA0GpkO/RPp0D+RcQ/9SbsyhU5uLWXRnSiL7oTJVkjL7IXcse47qjf+QEn0VnqPHsWQAfdz/6D7WVuwlt8zfufPfb9S4qpgbngYc8MhTFnFkD+XcIrTy/CkgcT3nAadxoG2fqvzT5dn8OAPmxnePo7PrqxdNhIMv93Pe3i4URvMEqywu4PClVGnIdqsQ6eRcHtVMkqswd+nXisHnTqqCqNf/ju4+KfXytxwWvvg+I118YoPqx3C3Jx4aO5mPlueyYC0aDolhRNrMXDtqe3227FsR0iZIMCazLIGtyutrCaJErqbHFRv+QFb6R4mhy1Hp63gu6/eptLh4eIYKxadlh++eQ3wZcFIkoSEhN1jJ99RQoGrimo8xMgGTLIOl6qSo9jJlhTKNDIWRSVMUdCjUiZrKNPI2GQZrUcl3A5hdoiwq4TbINwOETZoUaJyZp5Ki3qH7vvb50VDToKGgmgjhTGx7DInkdh1AI9MuIAkSxKDn/qL/EoHP/YfytwlmRSU5mFeo+Or5SspzbPWu8QwmLUkt4+iRfsoWnSIYp/XzTPvLyct1kz/cWkAlO/OZk9VFXKSEaNFT5ZOwRKuIaVTdJP+liM6xLEhq5yUKBN3nNmp0e0kSeLDy/qzLrMci0FLn1ZRTRr/ZEPMBgWCZk5A0zlm3a+OU0tzqHElNeTUUVU1uPrUMzWSQn+tc7XT4588ybSXrkSJfJU/Wn7KRY5Uwkrj2dL9f9y57g1cOVPQp6SAzgjnvAyfjPd1wuo5BVoOrLc/geCAqCrXV7/KaZoNlKZHULLR95H79liZ0k6pzNh9NWVWB/Gtwhk5rVO91XSoWZm3ukT5lUDwX8fShJbmdd8TzI3kbpn8boO6GOo6dRop8wolPtzAZzMHsT2/igiTjnN6Jgd/FgztdTTk1NFgauBiu6mZOqGOnv0JQVmSl60WD5kxeu5ul8qWpbnYSWBnxwvZ03Y8KblLMXwzn7JPPkETFUXYaafR5YzT6TfoZu4deC8frFrAi/9+izl8PdU6O39YzPxhAVzb6LP0Lsb9dRdj2p9LeO/LSdekoQLFVU6emLcVgKW7i9mUXUGPEAdBU4KSZVki3KCl0uGhwu6u5dSRJImEcCM55fZgQHXg72nUaYLZOHuKrLXGnPVPevB+Y2HbgY5YxdXNS9RRVZX5G/MAWJVexqp0n8LRNt7ChN51Fk0UhaqSbDSVOVi3LmO8aTNt460UWAtQqOaZDyQ8qhen6sGlKthVD6UoRLXXsEEjM2S1/3fX0vffTy5AJlBzBPaChg9SBowSGq+WcLuXcJvXL9BIdLBrCLfjF2sC91XCHQrhNgVz/YzmBqmI1lLeMgx7Whyazh1oMewc+rfpz4tvb2BLbiXn9Exm3cY8hlbGIBeb2bo+l55FCqe49ax8eRMxNg/j0EOGjVL/mJHxJpLaRpLULpKktpHEtrAghTjAVm3MBWqeO1AjGjrc3mBuVmPPuYa4Ylgbymwupg5odcAFrNgwA6O6nvylgvtDzAYFgmZO4ELwaGg6DreXZXtKgqGGiqoGLy6PZ/lVQ5k6nhCh55MrBhLlP76CSgcjnluI06NwaodWTBjwKlPnT2V2m1e51PEwNpLJbjeFpJtups3nnyEbjdB2JPS+GNZ/Dj/dDFf9Ddpjf74nEwWVDl79axeXDUmjU1L48T6cY4Ly+0Ocq/5NRZ6RgpURgMJ3wyRW9w3n7qpHyc2yYbToOOvq7mgbsSALp45AIAgQa9EzdUBLwgzaRjMjwuqIOI05dRrDuJ9Mnf0xtH0cQ9vH1ft+Q+21a2XqHKHyq7phywFUVcXm3y7P7WHopPb0PzuN7cvy+WXOTsIwkdlqNJmtRhNuyyY+fy3xv/2L5fvvQZbRp6XRNyKW8a54Vib9j3EXtCQsejdL0/9gS+Ve1hmNrDPCM4W/M+THuXSvNuGytyLH2Ym2Snv2yC1xKTIfLN3LK1P7BI8rGJS8H1EHINKsC4o6oU4d8F1A55TbSfc7dUJb3s+9fjhb82o6KC3bU8z/LdhNQZUvWDkgDDVEnL+7aVEzE3XSS2yU2dwYtPDYabGs27iOqvKtlK79ltnbyyhylqKqKsUeK1leG1kaiQKtFq8K4fGw2wphDpAVlaxKkFTfTe8Fo1NDkktDGyeYXComp5dwl4TZCZKiwWTQ4VFVHF4FWSejNWvwaGVQVYx2LyargtmuYrGDweZF6zjEbCaNBk1UlO8WHYU2OhpNVBTaFi24dpWdnZGp/Pno+GCQttejUFXqoHy3neg8JyPsWnpkuImvNBCz3sa361cD0Avfc8fl8YAM2ZIXS4qFi8Z1IKltJOaI/c+BAwupCeE1zj9jsM26Enx9Hky3zmiLnicm9mjy9v91xGxQIGjmBIWOoxCq88wv2/no3/R639dppP2uLh0tAuVXDYo6IaVXoQF1iRFGFt15KvM35jFlQEsijDruH3Q/D/zzAD+0e43xm26hOK4n2zJyMNx9Dykvv4QkyzDmCdj5KxRuhX9ehZF3Hv0TPIm5+tM1rM8q59fN+ax9cPTxPpyjz7I3kZf9H45yLen/JKBXPCzuJjFnhJ6Hzc+Rs8SGJMGYmd2IiG08lyGwym5zeWtlIwTEVdH9SiD47yBJEs9M6rnfbeo5dfaTWdEQ9Zw62sN7jwnku4S213Z6agJ/G8o+aWpQcq3yq0ZEHbdXDbp7A9kzeqOWnqelcu3ynRiLnfR1aknzaqgyp1LVNpW9bcdjcRUTl7eK2JJthGVs5Aqvkyu2/oxjfTzJZ43i0hG3Yhuexm8Fi/h5+zdssWax1GxiqRkgE4OSTifXPIa4vYTZI/DubkHGH8No1aIrUlgiXV0b2EHSAYX5KJOeLOxU2F0hvzffHCeQ6ZJe7AueNYeMFWnW1co+CoQjBy6+91eOFGhzfiKUX61KL+XPbQXoZJkL+qWSFmOC6gLU8kwKclayJXcFla4K7F4nxTYb05PLcGmd/LpLYme4Dkkvk1UE0VUq0dUQU+37v02VhuhqlZhqLxFWn4Hm4AnMOxWg4VDq/SLLfnEmuo5IE13z/RDhRhMdDZYw3E4FrV5G4xfmPG4vZfk2lD3LGOCCvz/Yimr3Yqt0YatwBp38Q5ABGU+G1RdaDL5sm2QL87OKKZFV3rlhMH/ml/PlT1s4s2U0bXvHN+lUAhlejTp1/OWR/8UA42OFEHUEgmZOsPzqKIwdaKOYFmuuFaR4VvekWsF7x4r9hUKHhiRr6xxbcqSJK09pG/x6QvsJrMxfydw9c1mU9j1npE8io/VYtFu/R//yyyTcfjuYY+CsZ2HOlbD4Oeg6HuIbr+kV7J/1/gC7QM7DSUt5Jvz5CGyejdsus+Xvlpg9Tra29JVd3So/Rc5vvoubQRPa0rJr/TDGUEIn/Da3N/i1KL8SCAQNUfc94WDfI/bX/epQaMipE7pqHyo6mXQa7G5vUIA4EHZXfaGo/jbeWts43N7gxabTq5CjU9ijc/Hi+O50UXTsWVdI9vYyrPo4rK3HktF6LACSq4LoygwiqrMp/3MnYT/+jcVZxIge3Rk75Cw2JMVx356/McXswmkqwyp72Gg0sNEIhHuATD7JzcSYrRCtKHjToLvbw7xvX6ZLVFuSIloTZUkkKjwFQ1gC6MNQ7RWMVpbTSZ9P2cqNRFh1jJBdtHFYIddJb20mmVIB3oIy2kk2OmgioXQvyFowhIPHBRXZ4KompaiI0fIG9IoDrd5JtM5LxqKVoKqEmWOJSR2MlNwbZDmk/OrYfV7vLqzGVVFImmczW9L/osJeSrQpjh/X23F7yjGY9/LuLisVWhe5GpliVUN4hRwUaaKrfIJNh2qIrtIRUw1R1SoatWnPJQUJTVQkdoOFApsHg05LQqQJk0GLZNCjsYSxvUphW4WX9m0SGdA1FdkSxifrSthXYmd8j0Qyi61szalgRNsoeidaUJ0+oUOOiESOjARLBG5DOIboCEwJ0ahGE4oCHpeCw+rGZnXjsHpwWN04qt04Stw4Mt247G5cjnxc9mzs1W5U/yRY1khotHIwtPgM/2V94Y7yWuem1clYYo2sKa6iQla5YXxnHl6wg30eF1/dPAyjTsOdL+UTYdTSol0U4ZXVQP2umw3h9HiZ+dFq1vpziBIi6os6drc3+Po8GKeO4OAQs0GBoJkTLL86CqpOYLXs1tEd69cjHwf2l6kT6tRpykrA/YPuZ0PhRnaxmDBbKoMKB7Gn3Xmov81lcMtviJ4yBXpcAJu+gV2/w9yb4PJffK3PBYIGcG36Ht28m5CclVRlG8nZ2AKz3UFODLw80cyVZQ9Stce3Atp/XBp9z2x9gBF9F1SBAFKb01OvHEuUXwkEglDqllsdrFOnroOjKZk6+yOYqRPa/SrEcRJ6fFFmHfYKL/amZuo0Un4V6mq0uWuXrpbb3CRF+kWdEEdQmddL11Na03V4C5w2N+mbSti7voiCvRVYK1yo+khK43pSGlfjlNJ47ERW7iNy/h4iK/7ivcoMqqJjSBtyBo62yWQlathsyWNh4Xpy3IXYtB4cskyefx5RqNWyChfYt/tufkyKgklVqZJl3FESRMFvKmAGQweF9EqVD39RkQFNO8hAxRQBOSpMnK2iUSFMVXBKEnlaLXZJwilJKJ1qFrw0XpU56aD651UJm1+jp8tDpKTDJGm5PEFGq1hY8n07YkwJ6HUmqh1lFNsKKXaUUuKqwKa4SdJHEaY1Y1ecZNtLMMlaWllaoKLi8rpwKm7cqge34sGtev3/K777qoIbBZeq4FC85Gtldul1KAELehVoElWSyiC1WCW1GPoU6xhfpJJS0jTBxotEpSmc5LYt0SYkIMcn4o5OZlWZnkXZXrz6cGSNmQidkcGtY7A6PGzJrkBGQgZizXriLXoURaWowokjzkO6QUd+lozL4cHgbUPnKNiZ5dtf2xjILvfdGqbKf8s54LEfCMWronj9pYxmLRleN1l4uHh0ezq09pVMWaIMmCP07Cyo5oFXFhNt1tF3VCv0u7KpznCRXmIjOdI3L4k0+16rgfeQ6jpl3w2xOaeCpbuLg1/3To0K3g900nO4Fdwh4eiCo4OYDQoEzZyAKUU9CqpOIKzwcO3XRwp5f5k6/g8MSaop09ofZp2ZZ055nqnzLmJduy/olZKKcV0Ke9uOR531MyNSUggbNgzOfgneHAxZy2H1BzDwf0f0nP5rWA7yAqNZ4LJS8cOdRG79HLdVJn9bW6p3OwAH+VESr09I5oKMW6DSgixLnHJhB7qPTD3QqIBPtLUYtFQ5fIHfCf7vC6eOQCBoCI0s0Ss1kg3ZFQD0CrnIagr1W5of3nt2oFS7yuFBVVUkSaqVqWMKEaEiTTryKhw4m+jUsdVx4YCvmcNZry5mVJdEnjyvR61tAMrtLpL8F7Gh7p7QUiODWUenQUl0GpQEwHM/buGnxZnEKxJDYyNoazRQnFWNGxOlMV0pjekKgKR6CavKpmT7HiJWriOiKpMz7MWckZjIStpQFhHNOaM7U2DW8ezaEgwRBfRpX8J2qYBMrY1K3HgAuyxjb+ScnbJMaFGUpKpIKsiKv9MSvn8kFSwOSCiExDKVhHKFhApILFdJKIeYav94WnDqAjctDp1KWbiH0nBwaV0s2bIajwYcegmNF4xuFaMLTC6IcYOLQuxO3/fjLRLFES5WWvYAIPuPS1ZBVtWQ+6BXwOCfynk1Mh5ZJk4j0VVSiXfJtKiSiS5wE1+qoG1E45MjI9ElJSHHxVNhiWROhpNyUzyXjx2ILjyOMreeD//JJVzVMKxFFNZyJ7YiFxT6Ht81EBPj9d1y/A6XFEKe81Ueyqp8n7d6QI8MDi8Oaj+v1OD/PkExsAiJBJLvHzRaGaNFi8et4HJ40fidNlq9jMGswximw2jWYrToMITpMFp8N4NZi96oQWfQYgrXY4rQ4XUpuBwePC4FY5hvm1NfWERGiYcbe0ST1rq2CzgQeh1w3beJs7Amo4zle0toExcG+F5/0HiWX0OU23xibYeEMD6cMYCWMebgz2oydbyHlKkjODjEbFAgaOZIHN2gZKgfnHi8CGbqNPAB7/a7d3QH4aTpEN0BR+5kTKlf8JHxOe4Z8Tzli/Xsaz0Onp3P6S/EY+zYEc54GH6501dW0/EsiGp5JE7npODjf9OJMGk5r0/TRIrYsPptX5s1OWthzv+IKNpNyS4LeZui0XgcoNHw02ADKzp15dT06egUHZYoA2dd1Z2ktpEHHjcEi94n6oRenFiFqCMQCBrhu2uHklVqw6DTkBLVeGZXQ+g0UrCNNhy58iuPomJ3ezHrtbW6X9V16gAHUX5V36kzb1MeBZVOPl+RyZPn9agXuhy4CFVVtZa7Z3+hwDYJsnQKWUC7ThbumNwLxatQkmMlb08F+XvK2bC+ELNHQ1VEa6oialyYWo+NsKosoq05JDqryfh+JwZXOU9W7EHnqZFuJL0eTVwCcmwM3kgLXpMefXgUBr0JjQpejxt3VSXu8jK85eVQUoZaWo50mAt6Bo/vVktFym9ozKbsR63z/8ESmlFTg0tnoCypLRv0qUS260zX7l2oUCOx2nylS+kF1bjtHuKSJRKQ+GcZgC8kuh/+0OeMmrblGq2MXQv5HjdVkkqlrNKzYyznDWyJJEvIGglZlvh6TRY/b87HqNfwxPk9eOGPHaSX2njy/B70TYtBa5D5cE0mryzYzcWDWrFkVzGZpXa+u2YI/dP2X1p9uGhMMnpT7c//wGu1oe5xAdEyVNQB+Gx5ZnCbgKhjOQhRJ5BTlRRprCXoAMHOdk6PEHWOBWI2KBA0c6SgU+fIj10j6pwY7oqaTJ3GnTpaTdOzfjSShKeqJ87iPAxxC3lZeYAnRr/Gnj/s7GsxigUPfM3oN65BN+BK2PwdZK2A+bfBRd/U/OJDKLO62FtspW+rqEa7SpxMFFY6eHjuFvRamYm9Uxo951AXWWzYSdJFTPHCP6/AwqdwV6lkrkzCVSCjQUHt3on/O92NWtiP0/eeCkBKpyjGzOx+wA4SDREIQw61Qgdq3et2uhEIBAKdRqZtfNghPVaSJIxaTbC06XBFHbNeg0aW8CoqlXYPZr02GJqq19QpvzL53h/th+DUcXkVVFUlIqSJQ4XNXW+sgKgTOIYA+wsFtoVk9wTGkzUy8a3CiW8VTvthSVyzJwOLV2LW2T2w5dkpzKikOLsaD2bKoztRHl0nk09V0LkqMXmq0NtLMTgr0bsqMBRXoM+pwOCqQO+qxOmqQmpEJGlslqECqiTjsMRjS+2JNb4jdlM8+6waFI0JJC0arZYosw5ZBqNRwqAHg05BJ3vRuqpZtz0Lt9tD16RwzBpQXB5KHQr5tQP1qAAAbFdJREFUdlC0YURY9MREaFifVYRdUrBLKha3jUhnNRa3nbRYMy1iI/FIOlyqHjc6PGjRygp6jYJOq7I1r5SiSgcooMHnbkkIM5GSGIvHEM4eq4ECq0yU1oDGraIFrC5YtVYFyoPnawJMgahjCcKiDYRHGwmLNvDL3iLS7U4uH9Wewd0TCIs2YgrXccHby1iTYeWMzglsTC/ltnPb0aFVdK3f461dY1j5np01GWXcvnA7ZU4XVVqV1LaRxCT5RJFov0hSZnNR5s8MjLYcn3mOUVe/rDBAwKkTyEs6p2cyv27Op8zmO2adRmbawFZAjajTlPKrwOspIAg1dDx216G1NBccHELUEQhOEhoSOg4XR532mcebgAnH28C5uv2ZOnVDkvc7nl+EcBWN5tQeHpblLeEF5UEePfN51v9Wxr6YYfxx52ec+dY1aMa/Bm8P9+XrbPoOek6uN97I5xdS6fDw6cyBnNKhaR0DmjO5Fb7WqC6PgtOjNPo8Ce16EnucJjtHlMpcmHMVpC+hIsNI/rp4FIcXu0bPx8OSWNG/iNG7Liepyh/O3SWC8Tf0Rj7EWvLABCv0wqIq4NQ5yHbFAoFAcCAMOrlG1DnMz39Jkogwaimzual0uEmKNAbLqww6uVb3qxqnTtMydeo6euqGJWeUWuuVX1XYXQ1uuz9RxxoyRkPt1rfmVqKoYIrU039kjZPX61Uoy7NSmFHFv+vyWfX/7d13fBv1/T/w12kP723HdvbeiySEVQiEFCiUFFpGWza0lFKgQPProAUKLe23UPplpuxRCu0XCgUSVtghJCGQRYaznOERb9myNT+/P053OsmSLMlyLMWv5+PhR2LpdD7JZ+nufe+xowlWv4QCv4RCvw4ecx485jzAHj37V4KAxeiF3eSF1QzozQZ4YITLZ0CPW0J9ew90QoIegEmng16S4PdFOB50A2btebcPcAbKijrbwxfOgsk2ESYA+7QZPDpAbwf0ALq9wMEWoNiuCYRoksJqAdR2Rn1aMsMI2MMSWtoAtLUFvy8EAI/8fLolgXadwMwJRRg2PAd5pTbsd/Tgjje/hsVmwL9uPB72XHPIII8Xn1qHDV87cW6BASXDc9Tb6wPHLz85eQxmhgVzFCaDDo9+fza+/eCnqA0MDgFCx3YrAZyGDpf6uVxgG5zjHCVg4oqUqRNWfjW80I7Xrjsu4nrU8iu3Ty2ZjEbJ1FH+drVCRppz+tWA49EgUYZTAhMDUX6lRPvTpfxKfa6RMnX8iX9gBD/4dVg25w789INLsLdjLx4tuQ/XnXI91rzbhj2W6Xjr5uew+K+XQnfCzcCq3wMrbgVGnwzYC0PW19Ejf6B/sP3wkAjqNHb0qP/vdvuiBnUOdwaXy/gP9J1vAy9fDV9bC+q/LELHbhMAH3YVl+Les9wwWrKwdNOPYfNkwyX58YbNg6sWliYd0AG0TQt7l1+xUTIRpZrcV0c+WUvFlfUcq1EO6gROAKM1Ss5NsPwqPGDj9vlDJvbsa3bCGJa9q2QWhJ/4xpr05HT1ztTR2lYvl/ZMrsgJuV2v16GoMhtFldmonlOCDf/eiEMdLnTbjTjjmBGoNJnQ1e6Cs8Mt93tpd6Grww1nu/x9t8MNISR0e4zo9hiBLu3aA58B2v4vfsCvORrUGSQUVWajZHg2CsrtuOf9ndjT2QM3BBaMLsSvz5oEr8cvT1rq9KC70wOX0wOX04sPtzbiYHs3Zg3Px7iybLR1e/Dqxjp4JYFOnYDVoMc3x5bgk00NKDMbMaEgC0IIHO5w4bDDhXybEcMKbTDbjTBbDTDbDDCa9fC4fHB3e+FwuPFFTQskAFOr8+DTAWtqW6EzSDhr5jCYbQY8v/kQvnY4ccPZE7H4mEqc/r8fY3dTF846sxrHjJSjQR9+uBv7jH4sGpOP7HwLwlUHSoL2twajUz6/QEPg+EXprxRNYZYZz10xD49+uBuOHg9mD89HgebilBLA2X1YjmDppGBz8CNN6X/VEyFT53CEkePRKNnBPr+IecEOCAZ1ImXqKAHhHm35VaYfA6YxHg0SZbhg+VXiYR2vz48/rdyOBaMLcdL4kl73q5k6adIoWa9Ov+p9nzL9KpHyKwDqZCG7wY77T74fF75+Ib5o/AL/GfMyvr1gMVavdmO3dxTe+tX/YfHvroe05WWgcSuw4hfA0uUR15kumU0DTduDoNvjQ+RrXUCj5gpopMllGcHnAd69Hfj0fjgbTTi0dhg8Dj+g02HLmZNx99idmHvwW5i6+0QAQKPOj//Y3WjTC4wtSa4MQqEcYDlDyq/YU4eIBoZ24lVKgjqBvjpKs+RgUEcPqzaoEzgxdHn9IROsotFmLwJyoEZ7W21LcLKPoq07cvlVc5crZNx56M/xRfy/QrnAMSw/ev+iLLMBD1w4K+r9kfj9At0ONzpbXeg43I2eLg98Xj/MSjNduxEGow56g04db63TS9Dp5X+NFj30mpPorq37cKAnkHGSb0JRZXbUn73yZTdWrOnA+Gm5OOnUcXjw/Rq8V+PBtMpcbDzQDp3kw7mzC/HG7gM4fmwufnP5XADAE5/swZ9f24ozpxXgZzGeb01jJ276ywfIsRhw561z0O324Ze3rYAQwC/PHYVCuwlXb9qNTqMfE8YXwmQxwBb4LOzS/I7X7WsBAMwZEfkIpKpA/p3UNgczbZo7XfD6BXQSUBxHn7+qAhvuOGdKxPvy7fI+2+pUMlZMcQ3rGAjK32p9uwuPfrgL35o+TA1aKUHLojhK4LUZwI4eb8xj2rZA+ZZSOqml9NTp8fiCJZcsvxowPBokynBqUCeJx76wdj8e+XA3HvlwN/b+4Yxe96dbTx3luUYqNVPGJRoSHDmukyT4hYBPCIzMHYk/n/hn/PjdH+OVmlcwcvZIzG8rwmdbbdjVWoi3/vQ+TvvB3yA9fqo86rx6HjD3il7rTJfMpoHW2BEa1IlGm9aekTEdRz3wwkUQB9ahaUsWmrbkAMIPf0UJ/naWDjuNTpy75Rbk9ZQCAL40ebHK6sHi6eW44riRUVO74xWpvl35f5aFH+NElFraCzmpmH6pTMDq6PGopdKAfIKnPYHUnhi6vP6QgE8k4WVabp8/JOiyr7mrVwZBMFPHp26bQSeh1elBTWMnpgzr3cheu85IWUTKhYvirNhZH4nS6STYc82w55pROiKn7wf0QZtB0tfFOiXYofRiWbVNHhl15rRybDzQDr+QA2FAaMZodiCAp2QuR+Po8YQsbzXpUZVvQ22LEzsbOiFKstDp8kKSgOpCOdvGZpR/jlICJ4TA+n2tAIA5wyN/ziqZOtryqfpAEK4k2wJDPzNHCsJKyvMjlCEdKcqx+mMf70FTpwt3vbENX/7mVOTZTMFGyXFk6uh0EmwmPZxuH7pcXhRnm7G3qQs/++eX6usoAbjk2BExM3XUnjoePxslHwF8ZYkyXKySpL5sr3dEvc/r88MbOANPlyBFcPpVpPKrwPSrRDN1lHUGVrlw2EL84phfAADuW38f2s6xY25pLSD8qNlvxNsvdcN/wjJ54dd/LvfXCZMuI+AHmjYDJ1KfAYU2qJPMfjqoOg8DT50F7+4vsP+jEjRtzgEEsP+4Mbjsu21wdx6Dczb/DHk9pXBIAi/ZXXjb5oFXAs6ZMazfAR0Aas+JP67Yhsm/WYHJv1kBRw/Lr4hoYIRk6qTg81/J1Ono9oQ0cZVHmveefgX0XYLl9fl7Zdu4vf6QLI59zc5e6wnvqWM26DGuVM5YiXZMpF1npEwd5TOuJCe9pzsqvweg7+M65eR/y6EOPL16rxo8WTKlXL3AVt8uP29txqjSqFoptYtG+QzL1lyYULJaV+9qwsc1hwEAw/Ks6jGVmqkTuKixr9mJpk43THpdxGAcAPV3u6PBgY5AIKmuPb7Sq3jkh/XPCQ/yHElKpk6TJov69Ps+whn3f4SaRnnfjiczCQj+Tve3OlHb7MRlT63Fl/vb0NLlRkuXG81dbjzz2T418y03Rk8dF0eaHxF8ZYkynBLCSOZcOVZn+x5NE8F0ydQJTr/qfZ+aqZPgVRclS1YbKLpgwgW4YMIFEBBY9vEyZF13DGYb1gPCj507PHh7y0nwz7kSgABevhrY+U5IWVG6BMEG2mFHsFdOrANwbVAnUpPrtOVsAZ45B93b9mDPW2XoOmQAzCa8dH45fjn/ME7Z9SPMPrgYOuiw1ejFaxUCe43Bv5vZUa4cJmpWdR4AuRl4l9unNu2sKrAO6gEkER2dQjN1UtFTR8nU8YY0KA7vqWM16dULM31NwHJq7s8OnIC6vL6QCwz7mp1qEMYe+Dlqpo6mr8+EskBQpyFyUEe7zkjbFczUSe+gjjaboq/jutJAUOfL/W34zX+2wC+AieU5qCqwqRcT6jvkPjXaiwtKNpASQIlGCepoA01jSuWgzv3v1eCGf34FIDh6G4C6ryi/gyc/3QsAmF6VG/X5VBXYMKrYDq9f4JOdTfJ2B4I64aV5ybAY9er+BwCF9sHbByIFYOs7erDlUAc8PgGbSa9mPfVFeU7ff+xznPCnVdh9uAvluRa8cu1C/POq+QDk4FFLl1J+FT1TJ6T8ij11Bgwv8RFlOjVTJ/GHOmKkx2pP0tNlBGHskeaJT7+Ktc5b5t6C2o5afHLoE1y36no897vH4L/uIXyZswg1mzsB3YU4dVIbdFtfAv55MXq+92/1sf2dFpIptJk6ka5eRlouY8qvetqBZ89Fy8e70bChCPAD3RUF+N0ZXWizGvGdzTcjqycfBrMee0ea8Xp9M86bUImX1h8AAIwutqcs4HLenCqcOL4YPe7Qq9KluebMbzxNRGkntKdO/z/PlGBCa5dbDaaYDDpIkhQS1LEY9LAY9fD4vCGfKV6fv9cFm57A/TpJLkN1uLxypo6mUXJ9R486srk8z4qaxk61XEQdsWzUYVxZH5k62kbJMTJ14mlCO5iU4BrQd1Dn+LHFOGdGBerae2Az6TG9Kg/nzqwEIAdxHD1eNTii9H0DQvsnxRIsvwpu07emV+DtrQ3qxEyTXsL35lar9ytZq10uHzYdaMfTq/cCAK47eWzMn/WN8SXYfXgPVm1vxJKp5SnN1AGA/3fGRLy+sQ4mgw5XnjAqJetMRvjf6h3nTFHLzwD5uEQbRIvljGnlePiDXeoxW1W+Ff974SxMGZYLn1/AoJPg9QvsD5RjRcrUCfbUYfnVkTAgQZ2DBw/i1ltvxZtvvgmn04kxY8bgiSeewJw5cwDI6fe33XYbli9fjra2NixcuBAPPfQQxo6N/UdJRL3pYvSZ6UunK/qVFCWoYw4ceKWDWCPNk5l+BQSbL4cHGww6A/504p/w/Te+j13tu/DT1bfg73/+E/w/+iM2ln0bNRvbgOnX4tTR7dDtegvWly7AeGkZtovqhEvAMlUyPXUyovzK3QXx7Hk4/GYNmr/OAwBsm1GIu09uQ1nnDHxnyw+g8xlgzTdjuXCgrl6eenH8uGL834aD8PkF5gwviPEDEqcdoUpENJDMKc7UUYIdhztdwWBK4LNaO9LcYtShNMcCR08nGjp6MKYkCx/sOIxrnlmPK08YhRtPHacuqwR9rEZ9cJSz19+refKOQPZNea4FNY2dOOxwwe8XahmY2aAPZupECeo4wzJ1tGOe/X6hlruke/lVIpk6VpMe931vZsT7lMychg6lp05wvWpWVhLlV5MrcvHeTSdFfYyaqeP24p6V2+AXciDohHGxp41+Y3wJHvt4D1ZtP4xOlxcf7ZRLu1KRqQMAFxxTjQuOqe57wQEWnqkzusiOY8cUJbWum04bj5tOGx/xPr1OQmmOBQfbutVj50iNkpWs9W6PT82mZ6bOwEn5K9va2oqFCxfCaDTizTffxNatW/E///M/yM8PpqHfc889uP/++/Hwww9jzZo1sNvtWLx4MXp6emKsmYgiUcuvknhszPIrZfJVGmWd6GP0D/IkOf0qVvPlbFM2/nbK35BvzsfXLV/jth33Yfa9N2La3n9A8ntR81Ur3u76f/BXzofO1Y5nTH9AldQAf4TpXEcb7YEskED5VTqn6vi8co+kx09H43+/RvPX8oH+m6cV4DeL2zG96VtYvOMy6HwGVE7Ih39RKeoQLIU6fkwRhuXJkzaiTeIgIkp32pPDVJQTK0Hpxg5XMJhiVII6oU2ZKwMTpA60OtHU6cJNL36Jbo8Pz6+phd8vUN/eA4+mIbLVZFCDUG6vv1fW6LY6OVAzqTwHFqMOjQ4XHvt4jzrS3GTQqX1X6jt60O4MDUa4vcH+goD8Gabt5dPqdKv3D2bpTTwS6akTi9KgXxkLnqXJ1FEaH7u8/pDjgtW7mnH+w6ux5VA7gN6NkuOhZuq4fdh9WJ7vfsnCEX0+bu7IfNhMehx2uLDkrx9iy6EO5FgMOH1yedw/OxOEZ+rkD2B5dmlYADMvQqaOOmLd4wvJ0KOBkfJX9o9//COqqqrwxBNP4JhjjsHIkSNx2mmnYfTo0QDkk7H77rsPv/rVr3D22Wdj2rRpePrpp3Ho0CG88sorqd4coqOe1I/yq844yq/SpfQKCD7XWCPNE87UidF8GQCqsqtw3zfug1FnxDu17+DR9tcx+0/XY+rOp+XAzpeteM15J5z5k1AiteFZ490w9DQntA0Kn1/g/IdX46f/2JDU448k7YEsEExJr2l04LIn1+K7j6xWv/Y0danLJZNRNuD8fuDr/wIPLYD/n1eg8a09aNkm1/a/eHYBnpnRg2/t+TFm1C4CAEw/pQpnXTcdB51ysOrqE0fho1tORr7dhJ+cPAanTSrFkqlH18EiEQ0dqZ5+VRLI1Gl09KjBFGW9Vs2FI4tRpwnqdOO3r25RRzE3dbrw0Ae7cOwf3sVPnv8C3R75+MVm0qsniu4ImTrNgZ4fZbkW/PrMSQCAe1Zuw6aD7YHt0CHbYlQD8uF9dcLXByCkFPZw4OJGgd2U9iesiWTqxKJk6ijHANpGydlmg3qxTMnG6XJ5ccHyz/D53hYs/3A3gOB0rOwEJjgqAUCn26sGhSJNXQpnNujxjQklAID9Ld3INhvwzOXz4u4vkynCA3WFAxjUKc+1qv83GXQR9yflNpfXz6DOEZDyV/bVV1/FnDlzcN5556GkpAQzZ87E8uXL1fv37NmD+vp6LFq0SL0tNzcX8+bNw+rVqyOu0+VyoaOjI+SLiGTBvJTET5Zj1TwrV9PSKVMnVqlZsPwq2Z460ZeZVToLvzv2dwCAv2/6O1ba9yD3Jxdh0tbHIPm9OLDVgX8678EeXxmG6xox74ubAX/sJo+R1Hf04PO9LfjvxkMJP/ZI0/bJAYLp6f9cux/vbWvEmj0t6pf2qmZaJeq4ncDax4AH5sL3zMU4/P4h1LxWhuat8lXbN75ZjDdHSzjv65+jonE8dHoJJ/9gAo47byx0eh0OtMpNIivzggc358+pwqM/mMOpVESUsUJ76qQgUydHm6kTbFAMyBMoK3ItMOl1KLSbUZkvn2jva3bi7a0NAIBxgQa6f35rO/wCWLmlAa99VQdADgqZ1PIrn9pTZ1RxsMEuIAcELjymGgtGFcLjE1i5pT5kO8YHSrAueeJzXP9C8MKK8tlm0uvUnn2f7mrCqu2N6nMC0r9JMhA20rw/mTphn2/aoI5OJ6n3K4GX+9/dqd6vHAMEy68SydRRpl/51Ezz7Dg/a+86Zyr++r0Z+Mv507HyhhMwvSov7p+bKcIDsHm2gczUCZauRWqSDCBksp1yEZnlVwMn5a/s7t271f44K1euxI9+9CP89Kc/xVNPPQUAqK+X30RLS0tDHldaWqreF+7uu+9Gbm6u+lVVVZXqzSbKWPEEJaJxxFV+lT5vwLGyatTyK11i2xvM/on9Ap41+ixcOfVKAMDvPv0d3iz04pnqSZi6ZTkkvwfOfR4sb/sTOvw2lDWvAd67M6HtAOSxj4D8u0zX3jNKBld4UEfpqaNMFjlnRgUeuHCW+nXzYrk2O1pG1BG3axXwt9nwvXITmj6sR81/y9C0OQc+lwRD5TD89/zheGd4Cc7bdAtyHaWwZBlx9g0zMfHYCnUValAn/+i62kdEQ1tIpk4KLuwovWYcLq/aqFh7xf7ZK+bhxWsWINdmVDN1Pt3VDJfXD4tRhyuPl5vPaj8WlclH2RZDSE8d5bNodHFWyDZYTQZIkoSxgQCRkgGknAifGOjL4nT78J8vD6lBAyVTx2bWqyepP3ruC1z25FrsaerKmHHmQFimTj8ysMKDOuGBFXWEfY/8+378kz3qfcoxRKRGyX1Ryq+aOl3qMW+8QaFcmxFnzxiGc2dVokJzIeZoog3AZpsNA5oVo+1HFC1byqL5+crfvZGZOgMm5a+s3+/HrFmzcNddd2HmzJm46qqrcOWVV+Lhhx9Oep3Lli1De3u7+rV///4UbjFRhgskpiQTA3B7ozd/UT540ylTR4oRwPL6ksvUUS4axFMW9JOZP8HpI06HV3jx0v7f4/3xhXilbDimbpYDO8M8WXiw9T74hAH4+C/AttcT2pa0zWgJ+PtHuzHltpVYvasZjR2hPdCU/UUZYzp7RAHOmFaufo0tkQ+kB738yuUA3rgZvse/jabPOlDz33Ic3pQDv1uCcdQo1N9yIX77k2JsN8zCmV//GBZPFg7r/Tj+x1NQMSYvZFUHWuWpD8pJCBHR0cCS4kydbLNBXacyLUe73lHFWZgRyJxQguRKz7Zxpdk4ZWKpWtJzzowKtZ9HVYEVN502XpOp41cnVY0pCQ3q2ALHMkoQoaVLXr+SlfTDY0fg41u/oR5DKEEHJfPHZtSHlIoJAXy083DGjDMHwnvq9COoY4meqQNoxpp3e7DpQLt60Q0A2gIn95EaJfdFmbKl9PLR66S0uvA42LS/04HspwMApZqgTqR+OgBg0GS3KceGZmbqDJiU54eXl5dj0qRJIbdNnDgR//63PO63rKwMANDQ0IDy8mDPgYaGBsyYMSPiOs1mM8zm9H+zJBoMwUbJqT1ZVjN1UlBPnypKo+RI0688/uQydXQJ9CTSSTrcedydaHQ24ovGL2Ct/jv+Y/gO8j8txEmbHsGmKVchG8V4sedvOM9yPQwvXwNc9T5QODqubVF6DQBy5pA+wfHsA+3zPS3w+gU+39PSqyG10lNHOVDLCTtQ609GWcrsfAfi1evRur4VhzeXwu+W9xXDyBGo+fZM/CV3Dbra3sGij3+I0s4RAIANJi/et3owy9GNcQg2P27v9qjPdRiDOkR0FEn19CtJkqfl7Gt2olYN6kQ+tggPko8vzUaB3YQzppbj013NuOm08fD5BTYfasepk0phNujx5KdyJoi2UfKYXpk68s9TAhvKZ5H2JLMy34YcixHNXW60d3twx3+34r1tcpmVzWxQLx4pPqlpwrA8OQhVnGGZOuGTkhIRq/wKCAZqOno86u8732ZEq9OjNqJ2BKavxjtiGwhm6iglb9kWQ9pMZ00H2r/VgQ7qhGbqRP9ZFqMenS6verzEnjoDJ+Wv7MKFC7F9+/aQ23bs2IHhw4cDAEaOHImysjK8++676v0dHR1Ys2YNFixYkOrNITrqJXuyHGtakfb+/nzwp5oSr4lUmqQcbCU6/UoXI1AUiVlvxsOnPoxqyzxIOh+slf/EMydmYX1ZKaZtegg6nwst7WX4r/OP8HS7gBd/IPduiYM2Uycdp0QpV1oaHT1qyrlyPOUMy9QJP1DTJZARlXLOFuD/rkb3X7+Hvf/qQcMXuXJAZ/gwfHrVfFx8YRPuEJ+iesdcnLfpVpR2joDRqkPlGVV4x+aBVwK+2t+GFZvr8cgHuyCEwMFA6VWB3RQykpeIKNMp2Q8mgy5lJ81Ks2SlbDXayV2h3RSSfaH0uvnfC2dh7S8XoarAhhFFdpw5rUINDJkMwYasSrlUeKaOEtQJL9cJP8ZRAhIHW7vxxqZ69QKX3aTvld3y2e4WNWskEzJ1tBk21hQ0So72vVp+1e3FpgNyQ+rjx8rlbW3dctlbMpk6Sk8dpXUAe9eF0gZ1CqJkz6RKWU7f5VdA7xYODOoMnJS/sjfccAM+++wz3HXXXaipqcHzzz+PRx99FNdeey0AOVr/s5/9DHfeeSdeffVVbNq0CT/4wQ9QUVGBc845J9WbQ3TUk9Tyq8ROlju6PTHv70nLRsnR+98kO/0qmWCD1WDFfPvP4G4+DgBgKn0LD5/Yg/9UjMKMjQ9A7+3GQccIvNZ+B9x1NcDrN8aVChSSqTPYZUoRKAdhhx0u1LfLB7IVgQkIPYGrox3dgUwda7RMnSP8vGrehffP83Bo+QrsfacYPa0mSFlZ+OqH8/C97zXgMftuzN3xbVzw5a8w6+BpMHktKBuVg+/9ah7qc4L70ic1Tbj+hQ24+81tWL2rmaVXRHTUUk4OUzn9Uhlrrrx3Rlu3JEkhfcqUoA6AqNmrSvPVjm6PeoFrRKE9ZHmbKbT8ShGeMaSUDillYgqrSR8yfh2QMzbfDzRMLtGc5KYrvU5Sn38qy6/Cv1c+/x09HmwMBHWOG1sEINh3rz+NkhWJPHYoOJLlV9oeUtHKr8K3CWBQZyClPMQ5d+5cvPzyy1i2bBluv/12jBw5Evfddx8uuugidZlbbrkFXV1duOqqq9DW1objjjsOK1asgMWS/m+IROkm2YtobWFBHb9fQKc5AAo2Sk6/oE6kJBZPYPqVIcGSJXWdCWbG9HgEXI1nQvIVwlD8Kgz56/DaKWPR9slUXLrxAWyc9mPUYSxebfktztpwO8yVc4G5l8dcp9sXzJ5Kx0wd5SCs0eFSi/1GFdtxsK1bbU4ZbH4Ylqmjvs5HZlvh80C8ezs6nl+O+vW58Hvkk4Tuxcfi9zP34pB7NxbuPQ+TDh8LyS8fZBSOysGcU6oxakYRdHoddjR0qqvbVh8cc7tySz2GF8qTVRjUIaKjjfK5n4px5grlJFAtv4qRBVyZb0VNo/z+O740O+pyCmVdbU63eluWxYDSbDMOBS5A2IzyKU/voE7odihZJvsDGUUKu8kAva53hnNX4IJGJmTqAMBlC0di08F2tc9dMsIzZGxhx4nKa7i32YmDbfLreNwYOajj8vrR7fb1q1GyIt7JV0NFaKbOwAZ1zAY9irJMaOp0R51+BUQI6rCnzoAZkL+GM888E2eeeWbU+yVJwu23347bb799IH480ZAiIbkMCOVqicInBHTQBnUCmTppFFWPNf1KydQxJPiBoU+yfE3pIVPkPxl1B3JhHfYPGLJ24uMTHTh+3vmY+dKj2DD+SjRgPP7T9Dt86407YCmfAVTOjrrO8J466UY5CDvscKkj5EcXZ+GjnU3o9vgghECH2lMnSlDnSGTqtOyB99lLUf/aXjj2B/rgjB2Jf5yZjbelnZi551Sc1DgfOiEfbOw1+PCJxYv2ziZ8Nnk6dIF9aEeDI+LqV25pwOlT5P5wnHxFREcbJUgyEJk6Ss+bWAEjJViebzOiOLvvYIlyotgaOK6xGHXQ6ySU51nVoI7FJC8TfsEhPHNAyTKpDcvUae/2hIyIPn5sET7a2QQA0EnAyKLQEerp6oZTx/V7Hdqgjt2kD7kgCASznT7dJb8+o4rsKM+1QK+T4PMLNHT0qM2Tkym/UiTy2KHAfAQzdQB5rHlTpxu5MTN1Qv++Es2mp/jxlSXKcMHyq8Qep72iBfQOIrjScPqVctwQKTCQ7PQrKcY6Y1EOTMtyLPB1ToJz39Xwe7Oht9TjkaKXUHH/LZhb+wyMbgcO+8fg5bpfo+v5a4Gu5qjrHJCeOl4X4Is+uj5e2oBNo6NHnfihHMh2u33o9vjU7Q4/2DpiPXU2/xudv/4Gdj9+CI79VkCnw67vzMU1Z3aj+eAUXLDhV5jcsBA6ocewcXl4pwx4KcuNQwY/utw+NVXc7xfqleJhmvGnJr0O9R09eHNzHQBm6hDR0UcZkJDKnnolYcGZWFfslWD5uNLsuHr6KNvZGjiuUTI6tM1cldvCm/iHB66yzZHLr9bta1X78gDAz08bj4cvnoV7lk7DS9csQFnu0Kk2CAnqRMiWUV7jfc3yazhlWC4kSVIzOvYHSvAkSc6AiheDOrFpAygFRyCoM3VYLoDe/atCtikseJvKQDGF4l8DUYaTEpjepNUeVn4VHkTo8SrlV+nzBhyrqXF/p18lWn6llBspYx39PZVw7v0RbNWPoh11uHLP77H84T9g3i1/xZrcb6HFNBIv7roJZz7xcxRf/SBg7B0M0GbqJB38EAI4sBb4fDmw92PAcUi+XW8GTHb5CxLgbAaED5D0gE4P5FYCxROA3GFAdgVQMAoYcwqgN6rPV9lHPGr/IkkNeHR7fGo/Hb1O6nXwNeDTr9xO+P9zExqefB1tu+RAk7+qBA+fXgR/+zgs/fL70Acyc4aNz8cxZ45AnQnY8NCnsJv0WDC6CO983YANta1YOKYIB1rlkjKTQYezplfg4Q92YUJZNkaXZOH1jXVoCEzf0AZ8iIiOBgNRflUa1nMm1rHF6ZPLsHJLPS45dkRc61YmWCkZyMrnT4Xm/dmqjjQPa5Tcq6dO5EydmxePx9a6DvX7kcV2TA+MYR9qtD10wvvpAL0zdWdW5wEAcm3yZLH9LXJJVpbZ0CvLJ5bwAFKknz2Uaffl/AEuvwKA335rMq44fiTGlEQvkbSa2FPnSOFfA1GGC440T0x4UMcbHtRJy0yd6IGBZDN11JKuJMuvtBMAhKcAzn1Xo3zCkzjQeQCXb7gFf3/gbzju1w9jjXMOnLYy/HvT+Tj5/l9j3E/v6BXYcfUnU0cIYPO/gU/+CtRvhLdHB49TD+EzQfgA4Qf8Pie8PT3y5CdJgqTTQ2cQMFhdMNp2wFC7DXqTH5LymZs/EjjxVmDqeWo/Ha2yXAtsZr36emhr5MOvriYbPIv4VN1uuLesg2f75/A3H4R7fx16Nn0F50EXfD12+CUddi8+Gx9aizC2ZqoazKkcn4+5Z45Exdg8AMAj/9kMADhtchkmV+Tgna8b8OX+NgDA9kDp1ZjiLFw8vxobD7Th6hNHwy8EXt8oZ+mYDTpMCVypIiI6WswdWYDjxhThjGnlKVtnSdjI79OnRF/3iCI7Xv7xwrjXrZSdKJk69rBMHbNBp37WhzfxD89GUgISSjbud2ZX4vvzh2NyRQ4u/PuaXssNRdpMnUgTqMJf48WT5XJlJVNHCZgl+hqaDTpIUvAiJhslhwrpqXMEMnUsRn3MgA7QO2jKoM7AYVCHKMPFKkmKJbynTvjJdjoGdWL11PGoPXUSLb9KrteL0yMHOUrDDlSFNx/fLLoDn3X/Hvs69uGyj6/F3//4KE6571l8+nUzmgsn4+2d30TzXX/F/F9cD8kcDOy4PAk0Svb7gba9QMMWoGErsHMlejZ/hbbddjgOlsLrjP178xhsaCqcgm5rEbI6DyLHUQuzqxWSBJhLbMgqdSCr6CCszddA+vBPELOuhw4F8GuqdstzrGpKe7fHF3WcOQDokyy/El4Pej5+E46Vr8O1Yydch5rhaXMBovfvudNehfopJ2BP2Szoe+wYIbdSQNn4bCw4aywqxuSpy/Z4fHh9kxyc+db0CrUHwIbaNggh1F4A48uyUZlvw/NXzlcf++HN30B7twfleRYUZUhzTCKieGWZDXj2inkpXWdpdvACyNUnjsKC0YUpW7cpLFNHyQ4oD0xn1GYLWI16tbcLEKFRcljT10K7Sc3IaQqUHQ91oT11YmfqzKrOUzOmlJ5ESvlVouVTkiTBbjKgkyPNI9IerxfY0yPg1WukOXvqDBj+NRBlODUjop/lV70zdeSskXSqf43V/8arTr9KsFFyYPFER4grV/HCU8oBwKYrwOOLH8cVb12BPe17cNk7V2D5jcux6LXVWP3Pd1BbuQhf1B2Dpv/3DBb/7iKYsuRyoag9dZwtcvCmcSvQsFkO4jR+DeHqQk+bET2tRnTVmeE4UBJ8jCTBUFwMyWqBzmSGMFnQYatAW/YoHNYPQ5MnFyKsrZrR7UCOoxbZjn3IPrgfWTsOwuZvQlZpC7LW3Yq3SvPwkPFsvOZfADeMKM+zqCntPR6f2nMn0oGaFE/5lc8L7HkfonE7XBvXoePTTejY2gFPZ3iASoLO4Icx1whPViEaSufhQPYctPrk6Rp6L9Bt7ETeFAlnLzkRxdU5vX7Ug+/vQlOnG2U5Fhw3tgg+v4BRL6G5y42NB9rxwuf7AQBnz6jo9djqQjZHJiJKRK7NiKtPGAWHy4ubTxuf0nUrV/+Vk317IIN0dLH82aqdTCVJ8lhvJQAUnjkQ/vmlbQI7LN+K3U1dKd32TKQte4rYU0cTGPvm1GBGlpKpc6AluaAOIAfolN9zeH+koU57vH4kyq/iod0Om0mf8DATih//GogyXLD8KsFMnfCR5iJzMnUiZbF4NX1eEqFTexIl2FMnQvmVwicESmwleHzx47jyrStR01aDy1Zehr+f+XcsmjYFn//yEWytOBu1XWPw4i3/xbSl81AxvhCuwDqN8MK4/2NgwydAzXtAwyYIAXidOnQ3mwJfFvS05kD4NM9XkpCz5HTYvnUGPsxrwcZdtejZr0N2cynsLUXQ+QyAH/IXgJ7cdrjz22Fuz4GpLQceUzaaCyejuXCyukpzTwvKGtaibPPnsH9ej2vz/o3ry1/ChuKx8LjOhg1VAOQgV0d39EwdtR9SxHn03RDrnkb3K39DV00bOmotcDuUdegh6QWsY/PgGTcDnUXT0JE1Fm3ufDTX9cDZHmj47QN8khf78rfAM6YJPz/3GlTnVak/orGjB/9cux9unx8+v8DfP9oDAPjNWZNg1Otg1AOTynPw1YF23Pyvr9Dt8WHqsFycOK449o5ARERxWfbNiQOy3vCLT0oG6djSbDx40SyMKAydTKUN6vTqqRP2+ZVnDZ6U3vXtqfjDim246vhRKdv2TGQ26GHUS/D4RMTAjPY11AZ1lACZMi4+mfIpu0mPw4H/s6dOKLvZgHNnDoNPiCNSfhWPq04YBYtRhx6PHyfweGpA8a+BKMPFlQGh0e704J6V2/BJTVPI7b0yddRGyekT1NHFaArtSXKkuaQGGxLbFiVTpzDLpB7cKJSXsshahMcWP4ar3roK21u347KVl+GRUx/Bwmd+j7yf/hKfGxah3VyMj17aDWA3LHovfquvxRjjJrQ83wSHywGp1QDRNAH+Jg/g6EZ4yEqXmwvr5MkwjZ+A5tnz8e/aWhxeuRtFbdUoEDNDlu0xdKEuexfqcnZhb8EmdFgCk7jKAb3fgMKuChR3VaO4swpFXZUo6CmDy1KAfcMXY9/wxchy1KKs4XOU7lqPcV/XAh/fD9/f/4J/52djY9ZoGNedgxyXCdnmEoTTRwqedbfB98GDaH3mSbRuAbw9egByfbbXbIdz1iloGb4Qhz0FcLS4gQ7IX4D2P2i012J78efYVfQFLpr5Pfxk5u9g0IV+vP36P5uxcktDyG0njS/GksBocgCYWZ2Prw60Y0eDPPXqJyePiWvyChERDZ7wbBtto35tUEEhT7iSAwt9lV/laTJ1qgpseODCWf3d3KNCltmAVqdHzYrSqiqw4srjR6IwyxzSrFoJkLV0yRdjksnUsWnKvZRJZRT0l+/OGOxNCFFVYMMvz5g02JsxJDCoQ5ThEhlp7vcL3PDil3hvW2PE+7SCmTrpkyqpi9H/xuNTyq8SbJScZE8iZfqV1WRAjkWe6KDQvpYFlgI8tvgxXP321djSvAU/XPFD3L7wdix+6n9RcOdvsPkTB9pyx6I9dxR8sKDLNx5fuTWp6fbA13BA8nthFt2wmAFrnhVZpXmwluWgsakN9Ts6gH95oEc5lDCFsHlgHy7BUumHVN4Nd24nsn02jBGTcZZ5IQw6A/zCD6/fi6buJtR11eFQ5yHs7v4EH3UeBHwShrdOwcTm+RjWMh6d2dWoya5Gzehzkde+HeV1nyOvfResh5sxH1uAL7bgnwDEWxJ2PZ4DY3kpjFUjYRgxFjpbAaYdboTeXwBvYz3EuqfR+vijaN2mh8dvQZe9HK7iCjhGTURj9mg4u/Lkvjn1ACC/tk6jAy3WOrTa6tAS+OqwN8FsNaDQUoj/mXMPTqg8odfv6mBbN97eKgd0LppXDaNeB7NRh8uPGxkStPnhsSOwv8WJTpcXkypycOrE0oT2CSIiOvLCs21sfYzJ1gYTok2/UuRZGTiIJMuiBHUil1tHOpHXBsiAZIM6wd8XM3WIgvjXQJTh+iq/emXDQbywthZCyNklmw62w2TQ4bazJmFkkR1XP70eDpe3V6aO0rTXksKRpv2lxGsi9b9ReuoYE8zUSab8yucXcAcymWxGPXKsoUGd8BKjXHMulp+2HDe8fwPW1K3BzR/cjE2TNuGGX/0WBa88joO3/w88LgM6syrRmjce3dYiuI1Z8Jhz4c0uhFtvh8evh9AZ0INs9HiBtiYATZ3Als7ATzHAo3Ohs7gR46dV4qT5c1FUkZ10pslh52G8UvMK/r3z33i98GFYPHaMbp6JsQ0LUeasQFveRLTlyan0kr8bOd0HYO1uhbHbAZPbAbO7Dea9bTBv/wJm13vQ+z34IwCfzoB1q56HI7sKjuxL4ZhRhS57BYSk+b0FnlKrtR778rbgQN529OS1Y1hxKUbnjcaC3FEYm78YY/PGotBaCJ0U+3f+3Gf74BfAsaML8ftvT4263MgiOx67ZG5SrxcREQ2O8Ewduyn2cYs2G6d3T53QwEOujUGdSLIC2U5ZfQTQtMKDOiOLshL+uTZNECmZoBDR0Yp/DUQZrq9MnT+u2Ia69p6Q2+44ezK+O7caAKDXR+51ojRKTqfyK6WnTuzyqwR76ugSL79yuoPjva0mfa9mfZFK4bJN2Xh40cP424a/4fHNj+PprU9ja/NW/GnJnzBy9jdw8Be/hm7DVzA667G+ZDymXnUuGqcb8GX7Rmxt3opdzbuhd5lh9WTB6smGzZMd+H8OJKOAvrIHp807HmeP+0FKSoaKbcW4ctqVuHzq5Vh9aDXu+uhxbDZ8ii1lHyOnuwjjmuZgVNt05DvLAFjRbh+Ldnv09Rm9nTB6u9BtKoLQ9d6nug2daLXWw23pgqnCD+soH0ZWD8OivLMwOvdnKLIWxf28PD4/Ln9qHbbXyyVaSqr3DxYMT/h1ICKi9GYzhWfqxD5uCc3UCR9pHtYomZk6EWUFyq4SyZYJfy1Pm5R4NqxNc0w6lMfKE4VjUIcow8XKNOl0edWAzl/Onw6zQY/hhTZMGZarLqOP0sC2x5t+5VdSjGa73kBUxpjg9KtkRsIrTZIlST4gDK/Bj7Yug86AG2bfgKlFU/HLj3+JdQ3r8N3Xvos/nfgnzHjuedzw0FN4q/MrSLk7YHDfBbE2dD32LB0q8gowOnc0RueNxpi8MRidNxqlttIB6/2ik3RYOGwhZltzsXXzJkwbvwc7/J9j7bB3sK5qBXR+PfK7y1DgLIfdXQBTdxmGGUpQqiuAwWmFv1MHvwfwGLLgMchX5cxmD9wFXdho2ICDtl04bN+P/IIsXDz5Ynx7zMWwGfs3XWp7vQMf7jgcctuoIjsWsZyKiOioM7M6D9lmAxyBqUi2PkZda4MBZmN4lo8BOil4cSYvTaYIpZuSwIj64mxzH0sGaV/LSeU5qCpI/LPepunhw5HmREH8ayDKcLEmmu85LI/eLLSbcO6syoiPjzZRKh2nX8UKwCjlYwln6sTo0xON0iTZZtRDkqReV4v6Wtei4YswKm8UfrbqZ/LI85WXodBSiMasRgTiHhAAJhZMxPyK+ZhcOBmTCiehMqty0Br3Onq8EN4cfLP6u5jZfjbK842YN96JLxq/wF8/WYmmgk2Q9K7eDxSAyWdFtjsfxu4SOIw+SAV70OmVa6xG547GbdP/H04bfhr0ETJ4knG4U96O0cV23H+B3Cx6RKGdozSJiI5CNpMB584ahqdW7wt8n0imTuiyOp2EbIsR7d0eGHRSn6VcQ9UvlkzAgtGFODWBbBttf6LFk8tiLBkde+oQRca/BqIMJyF6SdLupsCJc3H0uuXoQR2l/Cp9ToSVbQ1v6gxoGiUneOKurjOJoI41UEse3lgx4tjuMKNyR+EfZ/wDd352J/67+79o7G6ETpjg6hwNX+dE3H/2BVgycULc2zTQHD2BceVWI64+cbR6+4ySGXj6zZHY2+yAzlIHnakR58y1wm534FDnIbX5crPhEGA7JD/IC4zJG4Nrpl+DU4ef2mdPnEQ1OeSgzrB8GyZX5PaxNBERZboL5w1XgzpKNm00scqvlPvbuz3Isxk5ATGKqgIbLp6fWElzviZTJ5FgkJY9cNxlMeoS7qFIdDRjUIcow0kxsld2NcpBnVHF0ZudqEEdETlTJ/wq1mDSxRjf7g301DEmOP1KHQmfQE8dZfKVcsWod6ZOfOuxG+2467i7cP748+H0OPG/b/qw+oADAJBrLIp/g46Ajh45rT1SY0I5uKWHv6cS/p5KnDtyHo4dE9x+v/Djq0P7sXT5G7Da2vHoRcdjQcWClAdzFE2dcg+doiymzRMRDQXjy7JRlGVGU6cLs4fnx1xW2ww5vFEyoHymd7OfTorl2oz48Umj4RMCE8uzk1qHNXDcFd7QmmioY1CHKMNJUvRMnV1NcvlVfJk6waiGEAIub/o1SlaCOpGmX3nU8qvkeupEWmc0ylVANagT3lMn3qgO5N/fzBK5ROhez6fq7Ylsz5HgUIM6vQ+krMbY00N0kg5F1mL4e6rh9+mxcNjCgdtQAE2B8qvirPhr/YmIKLO9e9OJ2F7vwJwRBTGXC+mpEymoE8i+ZT+d1Lvl9P5lICuZOtnsp0MUgnlrRBkuONK8t92BnjpxZepoMlWUgA6QXuVXMXvqqOVXiWXq6JMYaa5Mv7KqmTph5VdJBmTcml9CPCVcR1JHt1x+FTlTJzTwF16OBgSnjCVS5pYsJahTxKAOEdGQkWs14piRsQM6QOyeOkAw6JPHTJ20E8zUYVCHSCt9ztaIKCnBkeahJ8t+v8CeeHrqBFbg1WTqKKVXQHpl6sTqqRMsv0rsbU2KUdIVjVJ+ZTVGydRJMnDh8qRvUEftqRMpqBO2j0TK5klmyliy1KBONq+yEhFRKCUgIEmAMcKFIOUzPdfGoE66KbCbQv4lIhnDnEQZThel/OpQezd6PH4Y9RIq861RHx8MlARvU5ok63VSWjWiixWA8fiTzNQJPL1EgijOsPKryRW5MOoleAKBpUTKr7TSNVNHCIHOwKjY8P5BQGjgz27SRwz8xOqHlGpNDqWnDjN1iIgolBK0MRt0ERshK7108qwMHKSbkyeU4IZF47BoUslgbwpRWmFQhyjDBcuvQs+WldKr4X2MclaCOpEydSwRas0HU6wAjJqpk+RI88TKr0KnX40pycIXvz4VL647gDv+uzXpwIVLkyF1JDJa4tXl9qnPKVIWTnugNAsAln1zYsT9LZnR8ZH4/AJ/fXcnDrV1ozjbjOtPGdsrm6y5i+VXREQU2chCO06bVIqRUUrTl86qxJ6mLnxnduUR3jLqi8Wox/WLxg72ZhClHQZ1iDKdWn4VevPBtm4AQHWBLebDDRF6nfR4A0GdNCq9AmIHYNSeOgmWXyWTQdId6Klj07w+2RYj9Ek0XdbSZup40yhTR+mnY9BJEXssHTOiAB/tbMKxowtx0bzqiOvQafZTIUTSY2I/2nkY97+7U/1+emUeTp9Spn7v8wu0dMmZOoWcfkVERGF0OgmP/mBO1PsnVeTg8UvmHsEtIiLqHwZ1iDJctKBEq1M+se2r7lhpYKtkugBAl0sO6tjTbLpAfNOvEszUURtFJzD9SumpE9YgOFbPn3ika0+d1zfWAZAzXyIFY648YRRmD8/HMSMLogZr9JpR834BJPhrUn1d5wj5XgngaL/3C7lXQgEnlxARERHRUS69ztiIKGHRyq9au+IL6kTK1FH6p2SlaVAnUrxDydRJtAdQMg18w3vqKKR+lhi5NJk6g11+JYTAU5/uxY7GTvxz7X4AwI9OGh1xWYtRj2PHFMVcnzbY4xcCeiQX1dnREBrU6XR5Qr5XmiQX2EwJj7cnIiIiIso06XXGRkQJk6KUX7V0ySe7+X1kK+jU6VeaoE5PIKiTZiMjlXP0WNOvDLrkeuokEkTpdodOvwpuX+/x8PESQsCtGSWvzZwaDNvqHfjta1vV7781vQI/WDA86fVpfy0+v0CylX3b6uWgTnmuBXXtPeq+quA4cyIiIiIaSngZkyjDReszEyy/ij2SUylX0pb7KNkP2WmWqRMrE0aZfpV4pk7iPXWCjZJDIxPBvjGJB2TcYZGgwc7UqWuXezKV5Vhw5zlTcM93piXdBwcILb9K9ql5fX7sauwEAMwang8AcLiiBHU4zpyIiIiIhgAGdYgyXLRMHSWokxdnpo42qONI20yd6JkwaqZOwtOv5H+TK78KfX1i9fzpi8sb+qSSyfZJpeZOef8ZV5aNi+cP73fTbF1Y+VUy9jY74fb5YTPpMbEsGwB6Z+pwnDkRERERDSEM6hBlvECmTtitifbUCc3USdeeOvK/4ZkwQgi1fCzR6VfJNDfu9gSmX0VrlJxEzMLdK6hzZKM6b26qw5VPr0O7U87SUidI9bH/xEub5JPsdDCln87Y0mzkWOUMtM5omToM6hARERHREMCgDlGGi95TRz4p76unjj5SUCdNM3WiZcJo+wEZE8zUkZIaaR6t/Cr56Ve9M3WObPnVX9/dibe3NmDl1noAwf2nr6BgvPSaqI5IMl6l9NMZX5qlBhyVoI7T7cW5D36CJz7ZC4BBHSIiIiIaGtLrjI2IEhapfMjj86MjEJjp66RcCep4I2TqpFtPnWj9b7RNhROdeBRv+dWhtm6s3dsCAGjokLNBwjN1khmPruiVqXMEYzoenx+7D3cBAPY2yf82pziok0j51dOr9+L5NbW9bq9r7wEAjCvNVoM6Sqngmt0t+KK2DYAc6JxZnZeCrSYiIiIiSm/pdcZGRAmTIpRftQVKaCQJyLXGbpSsjzDS3JHm5VfhQQGPplQp0elX8ZZf/eDxz1ETaNKrCH99kunPo3B5fSHfJ5Ptk6y9TV1qo+Y9gaCOkqlTlHVky6+EELjvnZ3qz4/kmJEFauBR+XfzwXYAwGmTSvH7b09FcTYzdYiIiIjo6JdeZ2xElDD1ZFlzotwWaJKcazWGTB2KRB/oQaPNdgmWX8UOCB1p0QIw2m0fiOlXzZ0uNaBz3JgiAMCIIhumVeaFbl8S49EV4Zk63iMY1Nke6FUDBIM6zYHeNAX21ARHJEmCTpJf51ivz2GHCy1dbugk4MlLj+m1/5ZkmzG2NBubDshBHGVf3XxI/v6YkQUM6BARERHRkMGgDlGGixSUUPuh9NFPBwD0EbJL0rVRcrSR5t5Alokkoc8gVrh4JlZtPtQBABhVZMezV8yLY/sS2gQAvXvqHMmR5tvrg0Gdfc1O+P0i5eVXgPxa+4WIOdJc6ZszssiOE8YVR11O6fcUzNSRf0eTK3JTtLVEREREROmPjZKJjhJCU4CljDPPj+OEXM3UidAoOTvNGiVHG2nuCWy7McHJV0B8JVNKac/kYbEDBpGaTser9/SrwQnqdHt8aHD0pHz6FaAJoMV4btvq5eDMhLKcmOvSNkpu6XLjYFs3AGBSRezHEREREREdTdLrjI2IEhZp+lVLl9xTJ9/Wd/mUUq2kPdF29MiPT7dMnWgjzZVMHUOCk6+AYHPjWNkjWwKlPVP6CBgor2WsAJEQArubutSSsRyrAeW51l49dQar/AoAttU54AxM+CpIUU8dANDpAPhivz7b6uRtmVCWHXNd2oDj53vkBtbDC2199pAiIiIiIjqapNcZGxElTGmUrI0BqJk68ZRfBbJbQoI6rvTM1IlUKiWEwGGH3P8l0SbJIeuMEURRSnum9pGpE608TOuPK7bj4Q92hdz25KVze2XqHKlGyU63F7UtTgDAtMpcbDzQjvX7WgHI4+FTOQFNea3jKb8a30dQx2zQwaiX4PEJfLa7GQAwhaVXRERERDTEsPyKKMOp2Sva8qsE+qGEZ+oIIYI9ddI0qKONd9z5+tf4zsOrASTeJFleJwLrjBxpaHd61KBHX/1a9FLk8jCt9fvkrJJsswEWo7y9q3c19+qpE6vHTyrtaOiEEPKUq9nD8wEA6wLbWGA3qYGqVOgrgObx+dWG1BPLY2dFSZKkZpIpQZ3Jw1h6RURERERDC4M6RBkuOP0qeFtLAj11DGGZOk63T82kyDanVylL+PSrQ23deHr1XgCASa/DmdPKE16nGiiKEmhQSq+qCqzI7aOcLZiJEj0gU9/RAwB44tK5WLZkIgBg1+Gu3kGdI5Sp80lNEwBgemUeRhbZAQBf7GsDkLrJV4pYAbQ2pxv/Wn8Abp8fdpMew/Ksfa5PCTruDASCxhRnpW5jiYiIiIgyQHpdhieihCmZFNrTZCVTJ56eOuElTUqWjl4nqZkk6UIKCwos/2g3PD6BeSML8M+rFyS1TqWnTrQYyo5Av5mJfTTuldcl/xstICOEQEOHXCpWmmNBt0fuW7O7qRMub+ikp/4GdXo8Pri8/j57zLy3rREAcPLEElQX2AAA7kCqUSqbJAOxX+tLn1yLDbVtAOTSK10cpXRZZiOAbvW1qgpsPxERERHRUMGgDlGGUwMdgRPbmkaHOgkonp46SnNh5cTY0RMcZ57K0ptU0E6Xau1y4x+f1wIAfnLymKTX2Vf5VX0gCDMsv+/MEV0fPXXanB61d05Jjll9PrXNTjgDwTRFf4M6lz+1FpsOtGPFz05ARZ4Vfr/Ayi31aHXKTbD1OmB6VR421Mr9c74xvgS5ViOsRr0abErlOHMg9uuzv0XeZ6cMy4n79xne7yee3xERERER0dGEQR2iDKc0ShYAPtp5GN9/7HP1vnhOysP7nKj9dNJs8hUQ2mh37d4W9Hj8GF1sx3FjipJep76PQExjoFyqNMfS97r6yPppcMjryrcZYTboUZZjUYMoSi8ZRX+COp0uLz7d1QwhgNc31uHKE0bh4Q934Z4V23ttr1/Ik6YqAuVOiyeX4pUvDwEAClM4+QqIHdTx+uVg133fnYExJbGbJCu0PZ9yLAbkWNKrXJCIiIiIaKClV20FESVMO9L86zp5SlO22YBTJpRgWmVen4836MKCOj3pOfkKCC0V2xp4rjOq8vuVUaSWBEVpbqwEYkpz+u4v01cj4Pr20ACRTiepfWy+ru8IWbY/jZK3HupQ+yKt2FKPzQfbce/bOwAAx48twmmTSjGyyK5u5ykTS9THfntWpfr/VAdJ1KyoCK+1J5DBpPR4ioc28FiZz9IrIiIiIhp60u+sjYgSoi0fag700jl/bhV+feak+B4fHtRxyeU56ZmpI//rFwJbD8lBkEkV/Zt4FN6nJ5zaAye770ydvkq5GjX9dBSjiu3YWteBr+scIcv2Z6T5poPt6v/X72vFj5/7Ah6fwOmTy/DQxbMgSRLauz247Mm12HigDd+aPkxdfuHowuA2pHgCV6xMHU/g+SrlgPHQZupUsvSKiIiIiIag9DtrI6KEKOVXQGKjzBVKpo43vKdOGmbqaKdfKZktE8vjK9WJus6wRtHhGgLlVyWJlF9Fy9QJrKtMs67RgYlNSlBNkuSsq/6UX23RBHUAoLbFiYpcC+46d6qa1ZRrNeKlqxfA4fKGNFM26HW477sz8Oxn+/CDBSOS3oZIguVpEcqvAs2ZTQmMpc9mpg4RERERDXHpd9ZGRAkJll8JtHTJWTbxNEhWhAciMqGnTlu3R22sO6m8f5k62j494brdPjXIlUj5VdSeOh29S7lGFdtDlrEa9XC6ff0K6iiZOseMLMDne1qQZTbg8Uvn9gr26XRSxOlY58wchnNmDut1e38Fs6JCb/f5hXqbIYGgjnYfZZNkIiIiIhqK0u+sjYgSouTpCACtTiVTJ/5eKPqwTJ207qkT2NZ9zU4AwLA8K/ISCGBFogQaIgVRGgP9dGwmfVxBrvDx8OHUoE5u70wdhc1kkIM6SZY+Od1e7DosN12+Z+k0PLdmH06fUo4JcYxkH2jReg55fMEmOyy/IiIiIiKKX/qdtRFRQiRNn5IWtfyq76wShSGsJCa9M3VCv5/YzywdIHZJkNJPpyTbHFcz5r7KryL155lUnoNzZw3D1kMdyLUaMbE8B09+ujfpTJ2v6xzwC3mbRxTZ8csz4uutdCQor48Ie629mueaSPlVaKNkBnWIiIiIaOhJv7M2IkqIdvpVMKgTf6aOkj2h9tRRgzrpNx5aFxZY6W+TZO06IyXGJNJPR16X/G+0BsNqTx1Npo5OJ+Ev589Qv39m9V4AyfXUEULg8U/2AACmVeYm/PiBFq38yqvN1AmP3MWQbWFPHSIiIiIa2jjSnCjDKY2SvT6B9u7Ee+oo5S7+sPKrdGyUXBV24j5/VEG/1xk+/Usr2AMnzqBOjHV5fX40dQYyf2L054m1jr78/aM9eH1jHQw6CT86aUzCjx9o0cuvgt/rEwjqKIHHbIshYm8gIiIiIqKjXfqdtRFRQpRz4JZAPx1JQkJ9ZoKZOnK2hBIYSseeOtWFNqz6+Uk40OpEod2cokwd+d9I2TWNDqVcKr5ytmhZP/tbnPjn2v0QQg5aFMUoj9PHGPsdS4/Hh3vf2QEAuO2sSZg9PD+hxx8Jeily+ZXSU8eol+Iqc1OMK82CxajDvJGFfS9MRERERHQUSr+zNiJKiHIO3BzIAsmzGhPKdjComSHy93Xt8lSp8tz4slOOtJFFdowssve9YJxiTaxKNFMn2nj0O1/fipVbGgDIzZ11MX4/4Y2r4/VJTROcbh+G5Vlx8fzhCT32SIlefiXfYEygnw4gl8V9/stFsJv4UUZEREREQxOPhIkynJLZoPTTybcnNg0qWO7jhxACB1vloE5F3tBoPBsrMybYUye+TB0pStZPXbu8nlMmlOCK40fF3p4ky6/eCgSNFk0sSSjb5UiKNh3ME8gSS6SfjiLHwrIrIiIiIhq6GNQhOko0dwaaJCc44lvN1BFAR7cXXW4fADmjZCiIFogBgEZlWlW8mTrq9KvQ25WStmtOGo25I2L3AYo1jSsan1/g3W1yUOfUSWVxP+5Ii/bcguVXbPNGRERERJQIHkETZTgl+0GZWlWQYKaOXpOpc7BNztIptJtgMepTuJXpK1ZmjNJTpzjOnjrqusKCFkpQJ55mvmr5lS/+oM6G2lY0dbqRbTFgXgqaRw8UJRGn10jzwHNVmnYTEREREVF8GNQhynDhlTbJB3WEGtQZlj80snSA6M2NXV4fOgOBsliNjbUiZf34/QIdiQR1EmyU7PL6cPt/twIAFk0sTetsF0kK7d+kYKYOEREREVFyWH5FlOHCcxsS7amj14yZPtjqBABU5A6doE608qvWLjkQo9dJyLHG91ap1wSIhBCQJAmdbq/aGDieoE68I83r23vwp5XbUdPowMYD7cizGXHTaePi2s7BEq38SmkKzaAOEREREVFiGNQhynC6sFSdRHvqaDN1DgUa+g6lTJ1o5VfNXXLpVb7NFHfjYe3vwi8AvQS0O+XgkMmgi6ukTdvjKJb/23AA//7igPr9vd+dgcp8W1zbOViilV95vMk3SiYiIiIiGsoY1CHKcCktvxpik6+A6OVXSqZOYQKvp3ZUuc8voNdJCfXT0a7DF95tOUxHt1wadvzYIvxiyQRMrsiNezsHS9TyK2bqEBERERElhUfQREeZpIM6QtNTZ0gFdeR/w0uC1Ewde/wjs7WJJsr6OnoSC+roowQ+wnW75aDOjKq8jAjoANH7BXnVnjrM1CEiIiIiSgQzdYgyXHj5VcI9dTTTlho6hmJQJ/LEqtYueUR8YZxNkoHgawlogjoJZuoEx6LHrr9yBkbPW02ZM6VMF7iM0HukuTL9itcZiIiIiIgSwSNoogw3d0QBcixyfHZ0sR3jS7MTerwSROjx+HA4MMJ7KPXU0anZI6G3twSCOoll6oSWXwGJjTMHNEG2PsqvnB45qGPLoNHzuiiZOsr0K/bUISIiIiJKDDN1iDLc1MpcfPmb0yAgl//E29RXoZTEHAj007EYdci3xR/IyHTRMmNanHJQpyCBTJ3wRslAMKijBN7i3p4+GiV3BzJ1bKbMeRtXgzph8SolgGUy8DoDEREREVEiMudsgIii0vUjw8GgVzJD5ChCaY4l4cBQJutrpHlBAgGukPKrJDN1dJoR87E4Az11Mqr8KsprrZZfMVOHiIiIiCghvCxKNMSF9+SxZ1DmRypEK78KNkpOYPpVhEbJiQZ1DFFGrIcLZupkUlCnj/Ir9tQhIiIiIkpIyo+gf/vb30KSpJCvCRMmqPf39PTg2muvRWFhIbKysrB06VI0NDSkejOIKE4GXejbQCZlfqRCtPKr4Ejz+Muv5Pc8+f8+NagjZ9TkJNhTp+9MnUxslBw5gOb1KSPNmalDRERERJSIAbksOnnyZNTV1alfH3/8sXrfDTfcgNdeew0vvfQSPvjgAxw6dAjnnnvuQGwGEcUhLKaTUZkfqRCt/Ko5iUbJQO++MUmXX4n4gjqZ1VNH/jdapo6RmTpERERERAkZkLMBg8GAsrKyXre3t7fjsccew/PPP4+TTz4ZAPDEE09g4sSJ+OyzzzB//vyB2BwiiqFXpk4GTVNKBX2EkiAhBFqdiY80V9bng0i+/EofZ/mVJ4PLr8Kem9LPKXxfJCIiIiKi2AbkCHrnzp2oqKjAqFGjcNFFF6G2thYAsH79eng8HixatEhddsKECaiursbq1aujrs/lcqGjoyPki4hSIzw5IpOCBKkQqSSoo9urBlUSztQJvJ7K4x0D3Sg5g4Jw0cqvPF4lU4flV0REREREiUh5UGfevHl48sknsWLFCjz00EPYs2cPjj/+eDgcDtTX18NkMiEvLy/kMaWlpaivr4+6zrvvvhu5ubnqV1VVVao3m2jI0vfqqZM55TypEKkkSBlnnmU2wGxILGiiBGVE2Ejz3DinaEXr8aPl9wv0eORASCYF4aI2SvYrPXWYqUNERERElIiUn70tWbJE/f+0adMwb948DB8+HC+++CKsVmtS61y2bBluvPFG9fuOjg4GdohSRB82/SqTggSpECkzpkWdfJVYlg4QfD19QkAIkXD5lT6OnjpK6RWQYY2SlSbS4eVX6vQrZuoQERERESViwC+L5uXlYdy4caipqUFZWRncbjfa2tpClmloaIjYg0dhNpuRk5MT8kVEqaHXM6gDBDNrAKAlMPmqIMF+OkCw8bLPL+B0+9R+MTmWOIM6gd+HN0amjjaoY0kwk2gw6SO81kDwuTJTh4iIiIgoMQN+BN3Z2Yldu3ahvLwcs2fPhtFoxLvvvqvev337dtTW1mLBggUDvSlEFEF4po4lg3q0pEJ4SdArGw7iwfdrAAAFcZZMaSnlU9osHYNOijtYpo/STFirWxlnbtSrfWoygRSl/Mod6KljyKDnQkRERESUDlJefvXzn/8cZ511FoYPH45Dhw7htttug16vxwUXXIDc3FxcfvnluPHGG1FQUICcnBxcd911WLBgASdfEQ0SvW6IZ+poGhsLIfCL/9uo9qsZXmhPeH3K6+kLK72SpPgCFur2xCi/Co4zz6zflVp+JcKnX3GkORERERFRMlIe1Dlw4AAuuOACNDc3o7i4GMcddxw+++wzFBcXAwDuvfde6HQ6LF26FC6XC4sXL8aDDz6Y6s0gojgN+aCOFJzI5HB51YDOnedMwZnTyhNen5qN4gc6ehLrpwMEx3oLIWfrRMrEUSdfZdjvKpjFFHq716eUXzFTh4iIiIgoESkP6rzwwgsx77dYLHjggQfwwAMPpPpHE1ESwoM6Q236lTptSgi0dslTr+wmPS6ePzy59WlKjJRMnZwEgjracjifENChd6CjO0MzdaQopWVutVEyM3WIiIiIiBLBI2iiIa5Xps6Q66kj/+sXAi2BoE6ezdTv9fn8iU++AoLlV8o6IlHKrzItABe1/CqQqcOeOkREREREiWFQh2iICz+RzrTsj/7SZo+0OuWgToG9H0EdTeZPRxJBHYMmqhM1qBOYfpVpAbhgVlTo7UpPHZOBH0lERERERIngETTREKeTwsuvMitQ0F96TU8dZZR5fn+COlL/gjohmTpRmiV3B3rqZFoALjg+PvR5edRMHX4kERERERElgkfQRENceKbOUAvqaIMwbUqmThKjzBXabJRkyq+0PXWijTUPll9l1u9K0pSmaXnUnjosvyIiIiIiSgSDOkRDXPh0JZsxs/q09Jd0BHrq5Fjjf021PY68fQR1Mi1TR5sVpaX01DGxUTIRERERUUJ4BE1E0MZ1Mi37o7/UzBo/UtNTJ8L0q0QydSRJCjZvjhLUCU6/yqwAnE4XrfyKmTpERERERMlgUIeIQjInMi37o7+0QRglU6c/PXW0QaJkgjradUTrqXO0lV8pGUnsqUNERERElBgeQRNRCGuGTVTqLyWO4BMCrYFGyQX9KL9Spmn5hLb8KrGgjhJoijb9qtsTaJScYb+raOVXSqaOkZk6REREREQJYVCHiEKE99g52gUnMgEtTiVTpz+NkuV/5fIrOfiSaKaO0rw66kjzDM3U0WZFaSnTr4zsqUNERERElBAeQRPRkKYd6a6WX/WrUbJSfpXcSHMgGFjrK6iTcT11NE2ptbzsqUNERERElBQGdYhoSNNHCOqkolGy0+2DOxCsSLanTnjwQ9GdodOvdFGeV7D8ih9JRERERESJ4BE0EQ1pUoR3wTxbf8qv5MBFW6CUS6+TkGVOLKNGKb+KPtJcLuuyZFhPHV3UnjpKo2Rm6hARERERJYJBHSJSDcVzam2mDgBkmQ0wG5IPliivYUug6XKOxaA2T45/HfGWX2VaUEf+N3xUu9fPTB0iIiIiomTwCJqIVCbD0HtL0IUFXPqTpaNdX2sgUyfRyVdA6Fj0SLo9GRrUiVJ+5WWjZCIiIiKipPAImohU/clQyVThSTT96acD9A7qJNpPBwgGdbxRojqZP/0q9HY3GyUTERERESWFQR0iUg3FTB19WM1ZfyZfadenNF3uT1Cn70bJGTr9Krz8KpCpY2KmDhERERFRQngETUSqoXhSHV5+1e9MHbVRcqCnTjJBHbWnTu/7hBBqo+SMK7+SopRf+ZmpQ0RERESUjKF3BkdEUZmHYKaOTgIWjikEIE9fOmFcUb/XB/QvU0cXo/yq0eGCX8jZPP0NQB1pkcqvhBCa6VdDb/8jIiIiIuqPzMrdJ6IBNRTLryRJwrOXz4PT7YNeJ/V7TLiSZdPWj546hhiNkvc1OwEAFXmWjGssrAS8fJpMHe3YdiMzdYiIiIiIEsKgDhGphmKmDiAHduzm1LwdKuPLuwJ9b5LK1FHKryL01KltkYM6wwvsyW7ioFF6BQltUMenDeoMzf2PiIiIiChZPIImItVQnH6VauFxiX41Sg4fEwWgtrkLAFBVYEt84waZpPYKCj4vjyYdiT11iIiIiIgSw6AOEamGYvlVqoU3Xs6x9GekeYxMncLMC+pE6qnj8QaDOkb21CEiIiIiSgiPoIlINVTLr1JJFzYi3WZOPPtJCer4IgR19gWCOtUZmKmjZDGJCD11dFLv146IiIiIiGLjGRwR4fpTxsJu0uMXSyYM9qZkPH1Ypo41icbL+iijvwFgfwYHdSKWXwXmtrOfDhERERFR4tgomYhww6njcN3JY2DgiXW/hSebJBXUiVJ+1enyoqlTnqpVfZSUXymNkhnUISIiIiJKHI+iiQgAGNBJkfASIqsp+aBOeKPk2sA483ybMalePYNN2cW0GUhKpg6bJBMRERERJY5ncUREKRTeKDmZTB1dlJ46SpPk6sLMG2cOaDN1tEEdZuoQERERESWL5VdERCkU3lPHklRPHflfJajj9wtc9Pc1WL27GUBm9tMBgj11NFPM4Q18Y2STZCIiIiKihPHSKBFRCoVP5U6u/EpeiS+Q0bJhf5sa0JEk4MRxxf3byEESqQG0kqnD8j8iIiIiosQxU4eIKIXCy68sSYyJV+IbSqbO21sbAACnTy7DH5dOQ64t8/rpAMEm0uypQ0RERESUGrw0SkSUQnpNGZFJr0sqA0Uf1lPn7a31AIBvTivP2IAOEOwVFGn6lYmZOkRERERECeNRNBFRCmkzdSzG5N5i1fIrv8Duw53YdbgLRr2Ek8ZnZtmVImKjZD8zdYiIiIiIksWgDhFRCmmDOsn00wGCjZL9QmDFFjlLZ/6owowcY66lll9pUnU83kBQJ7wZERERERER9YlH0UREKaQd4pTMOHMgWKbk9vnx/JpaAMCZ08r7vW2DLWL5lV8Zac5MHSIiIiKiRDGoQ0SUQtqeOsmMMwcAQ2Adb21pwIHWbuTZjPjW9GEp2b7BFLH8KtAo2cieOkRERERECeNRNBFRCkmpKL8KBHW+3N8GALjgmOqk15VOlHiXT5Oq4+VIcyIiIiKipPEomogohbSxiWTLr3Kswd45Bp2E788f3t/NSgv6QMBLSdT5z5cH8cxn+wAARh3Lr4iIiIiIEmUY7A0gIjqa6DWZOrYks2uuPH4Ucq1GdLt9mD08HxV51lRt3qCSNOVXB1qduOnFr9SeOkVZ5sHcNCIiIiKijMSgDhFRCklS/3vqFGWZ8eOTxqRqk9KGWn4lBB58fxe8foHplbn4zpwqfHNK2eBuHBERERFRBmJQh4gohbSNkpMtvzpaKa/NwdZuvLRuPwDgl2dMwjEjCwZzs4iIiIiIMhaDOkREKRQy0vwoaG6cSkoWk8srT7yaOyKfAR0iIiIion5go2QiohTSMVMnqvBeyGNLswdnQ4iIiIiIjhIM6hARpZA+BT11jlb6sKhOtpnJokRERERE/cGgDhFRCuk0QR2WX4XSvjYAYGdQh4iIiIioXxjUISJKIZZfRRcW02FQh4iIiIionxjUISJKoZBGyQzqhAgvv8oy8/UhIiIiIuoPBnWIiFJIG7iwsPwqRHj5VZbZOEhbQkRERER0dGBQh4gohSSJ5VfRhE+/sjNTh4iIiIioXxjUISJKIT2DOlH1ztRhTx0iIiIiov5gUIeIKIX0mndVq4lvsVqcfkVERERElFo84yAiSiFt+ZWFmTohmKlDRERERJRaDOoQEaUQy6+i04V94jCoQ0RERETUPwzqEBGlkC6k/IpBHS2WXxERERERpRaDOkREKeT3B/9vMzJooaUN6pj0OpgM/AgiIiIiIuoPHlETEaWQ2xeM6ljYKDmENouJ48yJiIiIiPqPZxxERCnk8vjU/5v0fIvV0mbqZFmYxURERERE1F884yAiSiFtpo4U1kNmqNMGdewmBnWIiIiIiPqLQR0iohRyefx9LzRE6TnunYiIiIgopRjUISJKIW2mDoWSNJ84Nk4GIyIiIiLqNwZ1iIhSyOVlUCcabfkVgzpERERERP3HoA4RUQqdOa0cADCmJGuQtyT9aMuvrOypQ0RERETUbzyqJiJKoWmVefjolm+gONs82JuSdrR9o23sqUNERERE1G8M6hARpVhVgW2wNyEt6UIydRjUISIiIiLqrwEvv/rDH/4ASZLws5/9TL2tp6cH1157LQoLC5GVlYWlS5eioaFhoDeFiIgGkV7HoA4RERERUSoNaFBn7dq1eOSRRzBt2rSQ22+44Qa89tpreOmll/DBBx/g0KFDOPfccwdyU4iIaJBpYjqwM6hDRERERNRvAxbU6ezsxEUXXYTly5cjPz9fvb29vR2PPfYY/vKXv+Dkk0/G7Nmz8cQTT+DTTz/FZ599NlCbQ0REg0xio2QiIiIiopQasKDOtddeizPOOAOLFi0KuX39+vXweDwht0+YMAHV1dVYvXp1xHW5XC50dHSEfBERUeayslEyEREREVG/Dcil0hdeeAFffPEF1q5d2+u++vp6mEwm5OXlhdxeWlqK+vr6iOu7++678bvf/W4gNpWIiAaBjeVXRERERET9lvJMnf379+P666/Hc889B4vFkpJ1Llu2DO3t7erX/v37U7JeIiIaHGyUTERERETUfykP6qxfvx6NjY2YNWsWDAYDDAYDPvjgA9x///0wGAwoLS2F2+1GW1tbyOMaGhpQVlYWcZ1msxk5OTkhX0RElLnybabB3gQiIiIiooyX8vKrU045BZs2bQq57dJLL8WECRNw6623oqqqCkajEe+++y6WLl0KANi+fTtqa2uxYMGCVG8OERGlkZtOHYfaFifmjsjve2EiIiIiIoop5UGd7OxsTJkyJeQ2u92OwsJC9fbLL78cN954IwoKCpCTk4PrrrsOCxYswPz581O9OURElEauO2XsYG8CEREREdFRY1Bmyt57773Q6XRYunQpXC4XFi9ejAcffHAwNoWIiIiIiIiIKCNJQggx2BuRqI6ODuTm5qK9vZ39dYiIiIiIiIjoqJFIzCPljZKJiIiIiIiIiGjgMahDRERERERERJSBGNQhIiIiIiIiIspADOoQEREREREREWUgBnWIiIiIiIiIiDIQgzpERERERERERBmIQR0iIiIiIiIiogzEoA4RERERERERUQZiUIeIiIiIiIiIKAMxqENERERERERElIEY1CEiIiIiIiIiykAM6hARERERERERZSAGdYiIiIiIiIiIMhCDOkREREREREREGYhBHSIiIiIiIiKiDMSgDhERERERERFRBmJQh4iIiIiIiIgoAzGoQ0RERERERESUgRjUISIiIiIiIiLKQIbB3oBkCCEAAB0dHYO8JUREREREREREqaPEOpTYRywZGdRxOBwAgKqqqkHeEiIiIiIiIiKi1HM4HMjNzY25jCTiCf2kGb/fj0OHDiE7OxuSJA325iSlo6MDVVVV2L9/P3JycgZ7c+gow/2LBhL3LxpI3L9ooHDfooHE/YsGEvevoUcIAYfDgYqKCuh0sbvmZGSmjk6nQ2Vl5WBvRkrk5OTwD5MGDPcvGkjcv2ggcf+igcJ9iwYS9y8aSNy/hpa+MnQUbJRMRERERERERJSBGNQhIiIiIiIiIspADOoMErPZjNtuuw1ms3mwN4WOQty/aCBx/6KBxP2LBgr3LRpI3L9oIHH/olgyslEyEREREREREdFQx0wdIiIiIiIiIqIMxKAOEREREREREVEGYlCHiIiIiIiIiCgDMahDRERERERERJSBGNQhIiIiIiIiIspADOr008GDB3HxxRejsLAQVqsVU6dOxbp169T7GxoacMkll6CiogI2mw2nn346du7cGbKOnp4eXHvttSgsLERWVhaWLl2KhoaGkGVqa2txxhlnwGazoaSkBDfffDO8Xu8ReY40OEaMGAFJknp9XXvttQBSt9+8//77mDVrFsxmM8aMGYMnn3zySD1FGiR97VuPPvooTjrpJOTk5ECSJLS1tfVaR0tLCy666CLk5OQgLy8Pl19+OTo7O0OW2bhxI44//nhYLBZUVVXhnnvuORJPjwZZrP2rpaUF1113HcaPHw+r1Yrq6mr89Kc/RXt7e8g6+N5F0fT1/nX11Vdj9OjRsFqtKC4uxtlnn41t27aFrIP7F0XT1/6lEEJgyZIlkCQJr7zySsh93L8omr72r5NOOqnXfddcc03IOrh/UUSCktbS0iKGDx8uLrnkErFmzRqxe/dusXLlSlFTUyOEEMLv94v58+eL448/Xnz++edi27Zt4qqrrhLV1dWis7NTXc8111wjqqqqxLvvvivWrVsn5s+fL4499lj1fq/XK6ZMmSIWLVokNmzYIN544w1RVFQkli1bdsSfMx05jY2Noq6uTv16++23BQCxatUqIURq9pvdu3cLm80mbrzxRrF161bxt7/9Tej1erFixYoj/XTpCOpr37r33nvF3XffLe6++24BQLS2tvZax+mnny6mT58uPvvsM/HRRx+JMWPGiAsuuEC9v729XZSWloqLLrpIbN68WfzjH/8QVqtVPPLII0foWdJgibV/bdq0SZx77rni1VdfFTU1NeLdd98VY8eOFUuXLlUfz/cuiqWv969HHnlEfPDBB2LPnj1i/fr14qyzzhJVVVXC6/UKIbh/UWx97V+Kv/zlL2LJkiUCgHj55ZfV27l/USx97V8nnniiuPLKK0OWaW9vVx/P/YuiYVCnH2699VZx3HHHRb1/+/btAoDYvHmzepvP5xPFxcVi+fLlQggh2trahNFoFC+99JK6zNdffy0AiNWrVwshhHjjjTeETqcT9fX16jIPPfSQyMnJES6XK9VPi9LU9ddfL0aPHi38fn/K9ptbbrlFTJ48OeTnfPe73xWLFy8+As+I0oV239JatWpVxKDO1q1bBQCxdu1a9bY333xTSJIkDh48KIQQ4sEHHxT5+fkh71G33nqrGD9+/MA9EUpL0fYvxYsvvihMJpPweDxCCL53UWL62r+++uorAUC94Mb9ixIRaf/asGGDGDZsmKirq+sV1OH+RYkI379OPPFEcf3110ddnvsXRcPyq3549dVXMWfOHJx33nkoKSnBzJkzsXz5cvV+l8sFALBYLOptOp0OZrMZH3/8MQBg/fr18Hg8WLRokbrMhAkTUF1djdWrVwMAVq9ejalTp6K0tFRdZvHixejo6MCWLVsG9DlSenC73Xj22Wdx2WWXQZKklO03q1evDlmHsoyyDjr6he9b8Vi9ejXy8vIwZ84c9bZFixZBp9NhzZo16jInnHACTCaTuszixYuxfft2tLa2pvZJUNqKZ/9qb29HTk4ODAYDAL53Ufz62r+6urrwxBNPYOTIkaiqqgLA/YviF2n/cjqduPDCC/HAAw+grKys12O4f1G8or1/PffccygqKsKUKVOwbNkyOJ1O9T7uXxQNgzr9sHv3bjz00EMYO3YsVq5ciR/96Ef46U9/iqeeegpA8CR72bJlaG1thdvtxh//+EccOHAAdXV1AID6+nqYTCbk5eWFrLu0tBT19fXqMto/XuV+5T46+r3yyitoa2vDJZdcAiB1+020ZTo6OtDd3T0Az4TSTfi+FY/6+nqUlJSE3GYwGFBQUMD3LQrR1/7V1NSEO+64A1dddZV6G9+7KF7R9q8HH3wQWVlZyMrKwptvvom3335bDTBz/6J4Rdq/brjhBhx77LE4++yzIz6G+xfFK9L+deGFF+LZZ5/FqlWrsGzZMjzzzDO4+OKL1fu5f1E0hsHegEzm9/sxZ84c3HXXXQCAmTNnYvPmzXj44Yfxwx/+EEajEf/3f/+Hyy+/HAUFBdDr9Vi0aBGWLFkCIcQgbz1lksceewxLlixBRUXFYG8KHWW4b9FAirV/dXR04IwzzsCkSZPw29/+9shvHGW8aPvXRRddhFNPPRV1dXX485//jPPPPx+ffPJJSOY0UV/C969XX30V7733HjZs2DDIW0ZHg0jvX9oLHFOnTkV5eTlOOeUU7Nq1C6NHjx6MzaQMwUydfigvL8ekSZNCbps4cSJqa2vV72fPno0vv/wSbW1tqKurw4oVK9Dc3IxRo0YBAMrKyuB2u3tNl2loaFDTOsvKynpNNVK+j5T6SUeXffv24Z133sEVV1yh3paq/SbaMjk5ObBaral+KpRmIu1b8SgrK0NjY2PIbV6vFy0tLXzfIlWs/cvhcOD0009HdnY2Xn75ZRiNRvU+vndRPGLtX7m5uRg7dixOOOEE/Otf/8K2bdvw8ssvA+D+RfGJtH+999572LVrF/Ly8mAwGNSS0aVLl+Kkk04CwP2L4hPv8de8efMAADU1NQC4f1F0DOr0w8KFC7F9+/aQ23bs2IHhw4f3WjY3NxfFxcXYuXMn1q1bp6Ztzp49G0ajEe+++6667Pbt21FbW4sFCxYAABYsWIBNmzaFnES9/fbbyMnJ6RVUoqPPE088gZKSEpxxxhnqbanabxYsWBCyDmUZZR10dIu0b8VjwYIFaGtrw/r169Xb3nvvPfj9fvUAZMGCBfjwww/h8XjUZd5++22MHz8e+fn5qXkClNai7V8dHR047bTTYDKZ8Oqrr/bKnuB7F8Uj3vcvIQ8FUfsccv+ieETav37xi19g48aN+PLLL9UvALj33nvxxBNPAOD+RfGJ9/1L2cfKy8sBcP+iGAa5UXNG+/zzz4XBYBC///3vxc6dO8Vzzz0nbDabePbZZ9VlXnzxRbFq1Sqxa9cu8corr4jhw4eLc889N2Q911xzjaiurhbvvfeeWLdunViwYIFYsGCBer8yvu60004TX375pVixYoUoLi7mSPMhwOfzierqanHrrbf2ui8V+40y9vDmm28WX3/9tXjggQc49nCIiLVv1dXViQ0bNojly5cLAOLDDz8UGzZsEM3Nzeoyp59+upg5c6ZYs2aN+Pjjj8XYsWNDRpq3tbWJ0tJS8f3vf19s3rxZvPDCC8Jms3Gk+RARbf9qb28X8+bNE1OnThU1NTUhY1vDR07zvYuiibZ/7dq1S9x1111i3bp1Yt++feKTTz4RZ511ligoKBANDQ1CCO5f1LdYn4/hEGWkOfcviiba/lVTUyNuv/12sW7dOrFnzx7xn//8R4waNUqccMIJ6jLcvygaBnX66bXXXhNTpkwRZrNZTJgwQTz66KMh9//1r38VlZWVwmg0iurqavGrX/2q1xjy7u5u8eMf/1jk5+cLm80mvv3tb4u6urqQZfbu3SuWLFkirFarKCoqEjfddJM6/pWOXitXrhQAxPbt23vdl6r9ZtWqVWLGjBnCZDKJUaNGiSeeeGIgnxKliVj71m233SYA9PrS7hvNzc3iggsuEFlZWSInJ0dceumlwuFwhKznq6++Escdd5wwm81i2LBh4g9/+MNAPy1KE9H2r1WrVkXctwCIPXv2qMvxvYtiibZ/HTx4UCxZskSUlJQIo9EoKisrxYUXXii2bdsWshz3L4ol1udjuPCgjhDcvyi2aPtXbW2tOOGEE0RBQYEwm81izJgx4uabbxbt7e0hy3H/okgkIdixl4iIiIiIiIgo07CnDhERERERERFRBmJQh4iIiIiIiIgoAzGoQ0RERERERESUgRjUISIiIiIiIiLKQAzqEBERERERERFlIAZ1iIiIiIiIiIgyEIM6REREREREREQZiEEdIiIiIiIiIqIMxKAOEREREREREVEGYlCHiIiIiIiIiCgDMahDRERERERERJSB/j8enY6TleEZ9gAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1400x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "r = (11882900 <= oracle_df.block) & (oracle_df.block <=11883550)\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(1, 1, 1)\n",
+    "ax.plot((oracle_df.drop(\n",
+    "    [\n",
+    "        'block',\n",
+    "        'current_price',\n",
+    "        # \"shifted_price\", \n",
+    "        \"vwap_30_x_per_y\"], axis=1))[r])\n",
+    "b = 2900\n"
+   ]
+  }
+ ],
+ "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": "3.8.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..e1cf545
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,2061 @@
+[[package]]
+name = "aiohttp"
+version = "3.7.4.post0"
+description = "Async http client/server framework (asyncio)"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+async-timeout = ">=3.0,<4.0"
+attrs = ">=17.3.0"
+chardet = ">=2.0,<5.0"
+multidict = ">=4.5,<7.0"
+typing-extensions = ">=3.6.5"
+yarl = ">=1.0,<2.0"
+
+[package.extras]
+speedups = ["aiodns", "brotlipy", "cchardet"]
+
+[[package]]
+name = "anyio"
+version = "3.6.2"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+category = "main"
+optional = false
+python-versions = ">=3.6.2"
+
+[package.dependencies]
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["packaging", "sphinx-rtd-theme", "sphinx-autodoc-typehints (>=1.2.0)"]
+test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "contextlib2", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"]
+trio = ["trio (>=0.16,<0.22)"]
+
+[[package]]
+name = "appnope"
+version = "0.1.3"
+description = "Disable App Nap on macOS >= 10.9"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "argon2-cffi"
+version = "21.3.0"
+description = "The secure Argon2 password hashing algorithm."
+category = "main"
+optional = false
+python-versions = ">=3.6"
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+[package.extras]
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+[[package]]
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+[[package]]
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+[[package]]
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+[package.extras]
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+
+[[package]]
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+[[package]]
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+[metadata]
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+backoff = []
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+bitarray = []
+bleach = []
+certifi = []
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+eth-hash = []
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+typing-extensions = []
+uri-template = []
+urllib3 = []
+varint = []
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diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..3f4a82a
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,25 @@
+[tool.poetry]
+name = "data-analysis"
+version = "0.1.0"
+description = "analyze swaps in AMMs"
+authors = ["Your Name <you@example.com>"]
+license = "n"
+
+[tool.poetry.dependencies]
+python = "^3.8"
+gql = {extras = ["requests"], version = "^3.4.0"}
+pandas = "^1.5.3"
+tabulate = "^0.9.0"
+web3 = "^5.31.3"
+tqdm = "^4.64.1"
+notebook = "~6.4"
+matplotlib = "^3.6.3"
+pip = "^22.3.1"
+install = "^1.3.5"
+jupyterlab = "^3.5.3"
+
+[tool.poetry.dev-dependencies]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/local_node/__init__.py b/src/local_node/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/local_node/event_scanner.py b/src/local_node/event_scanner.py
new file mode 100644
index 0000000..b1acda0
--- /dev/null
+++ b/src/local_node/event_scanner.py
@@ -0,0 +1,527 @@
+"""A stateful event scanner for Ethereum-based blockchains using Web3.py.
+
+With the stateful mechanism, you can do one batch scan or incremental scans,
+where events are added wherever the scanner left off.
+
+Modifed from https://web3py.readthedocs.io/en/v5/examples.html#example-code
+to scan for swaps and syncs from uniswap v2 pair.
+"""
+
+import datetime
+import json
+import time
+import logging
+from abc import ABC, abstractmethod
+from typing import Tuple, Optional, Callable, List, Iterable
+
+from web3 import Web3
+from web3.contract import Contract
+from web3.datastructures import AttributeDict
+from web3.exceptions import BlockNotFound
+from eth_abi.codec import ABICodec
+
+# Currently this method is not exposed over official web3 API,
+# but we need it to construct eth_getLogs parameters
+from web3._utils.filters import construct_event_filter_params
+from web3._utils.events import get_event_data
+
+
+logger = logging.getLogger(__name__)
+
+
+class EventScannerState(ABC):
+    """Application state that remembers what blocks we have scanned in the case of crash.
+    """
+
+    @abstractmethod
+    def get_last_scanned_block(self) -> int:
+        """Number of the last block we have scanned on the previous cycle.
+
+        :return: 0 if no blocks scanned yet
+        """
+
+    @abstractmethod
+    def start_chunk(self, block_number: int, chunk_size: int):
+        """Scanner is about to ask data of multiple blocks over JSON-RPC.
+
+        Start a database session if needed.
+        """
+
+    @abstractmethod
+    def end_chunk(self, block_number: int):
+        """Scanner finished a number of blocks.
+
+        Persistent any data in your state now.
+        """
+
+    @abstractmethod
+    def process_event(self, block_when: datetime.datetime, event: AttributeDict) -> object:
+        """Process incoming events.
+
+        This function takes raw events from Web3, transforms them to your application internal
+        format, then saves them in a database or some other state.
+
+        :param block_when: When this block was mined
+
+        :param event: Symbolic dictionary of the event data
+
+        :return: Internal state structure that is the result of event tranformation.
+        """
+
+    @abstractmethod
+    def delete_data(self, since_block: int) -> int:
+        """Delete any data since this block was scanned.
+
+        Purges any potential minor reorg data.
+        """
+
+
+class EventScanner:
+    """Scan blockchain for events and try not to abuse JSON-RPC API too much.
+
+    Can be used for real-time scans, as it detects minor chain reorganisation and rescans.
+    Unlike the easy web3.contract.Contract, this scanner can scan events from multiple contracts at once.
+    For example, you can get all transfers from all tokens in the same scan.
+
+    You *should* disable the default `http_retry_request_middleware` on your provider for Web3,
+    because it cannot correctly throttle and decrease the `eth_getLogs` block number range.
+    """
+
+    def __init__(self, web3: Web3, contract: Contract, state: EventScannerState, events: List, filters: {},
+                 max_chunk_scan_size: int = 10000, max_request_retries: int = 30, request_retry_seconds: float = 3.0):
+        """
+        :param contract: Contract
+        :param events: List of web3 Event we scan
+        :param filters: Filters passed to getLogs
+        :param max_chunk_scan_size: JSON-RPC API limit in the number of blocks we query. (Recommendation: 10,000 for mainnet, 500,000 for testnets)
+        :param max_request_retries: How many times we try to reattempt a failed JSON-RPC call
+        :param request_retry_seconds: Delay between failed requests to let JSON-RPC server to recover
+        """
+
+        self.logger = logger
+        self.contract = contract
+        self.web3 = web3
+        self.state = state
+        self.events = events
+        self.filters = filters
+
+        # Our JSON-RPC throttling parameters
+        self.min_scan_chunk_size = 10  # 12 s/block = 120 seconds period
+        self.max_scan_chunk_size = max_chunk_scan_size
+        self.max_request_retries = max_request_retries
+        self.request_retry_seconds = request_retry_seconds
+
+        # Factor how fast we increase the chunk size if results are found
+        # # (slow down scan after starting to get hits)
+        self.chunk_size_decrease = 0.5
+
+        # Factor how was we increase chunk size if no results found
+        self.chunk_size_increase = 2.0
+
+    @property
+    def address(self):
+        return self.token_address
+
+    def get_block_timestamp(self, block_num) -> datetime.datetime:
+        """Get Ethereum block timestamp"""
+        try:
+            block_info = self.web3.eth.getBlock(block_num)
+        except BlockNotFound:
+            # Block was not mined yet,
+            # minor chain reorganisation?
+            return None
+        last_time = block_info["timestamp"]
+        return datetime.datetime.utcfromtimestamp(last_time)
+
+    def get_suggested_scan_start_block(self):
+        """Get where we should start to scan for new token events.
+
+        If there are no prior scans, start from block 1.
+        Otherwise, start from the last end block minus ten blocks.
+        We rescan the last ten scanned blocks in the case there were forks to avoid
+        misaccounting due to minor single block works (happens once in a hour in Ethereum).
+        These heurestics could be made more robust, but this is for the sake of simple reference implementation.
+        """
+
+        end_block = self.get_last_scanned_block()
+        if end_block:
+            return max(1, end_block - self.NUM_BLOCKS_RESCAN_FOR_FORKS)
+        return 1
+
+    def get_suggested_scan_end_block(self):
+        """Get the last mined block on Ethereum chain we are following."""
+
+        # Do not scan all the way to the final block, as this
+        # block might not be mined yet
+        return self.web3.eth.blockNumber - 1
+
+    def get_last_scanned_block(self) -> int:
+        return self.state.get_last_scanned_block()
+
+    def delete_potentially_forked_block_data(self, after_block: int):
+        """Purge old data in the case of blockchain reorganisation."""
+        self.state.delete_data(after_block)
+
+    def scan_chunk(self, start_block, end_block) -> Tuple[int, datetime.datetime, list]:
+        """Read and process events between to block numbers.
+
+        Dynamically decrease the size of the chunk if the case JSON-RPC server pukes out.
+
+        :return: tuple(actual end block number, when this block was mined, processed events)
+        """
+
+        block_timestamps = {}
+        get_block_timestamp = self.get_block_timestamp
+
+        # Cache block timestamps to reduce some RPC overhead
+        # Real solution might include smarter models around block
+        def get_block_when(block_num):
+            if block_num not in block_timestamps:
+                block_timestamps[block_num] = get_block_timestamp(block_num)
+            return block_timestamps[block_num]
+
+        all_processed = []
+
+        for event_type in self.events:
+
+            # Callable that takes care of the underlying web3 call
+            def _fetch_events(_start_block, _end_block):
+                return _fetch_events_for_all_contracts(self.web3,
+                                                       event_type,
+                                                       self.filters,
+                                                       from_block=_start_block,
+                                                       to_block=_end_block)
+
+            # Do `n` retries on `eth_getLogs`,
+            # throttle down block range if needed
+            end_block, events = _retry_web3_call(
+                _fetch_events,
+                start_block=start_block,
+                end_block=end_block,
+                retries=self.max_request_retries,
+                delay=self.request_retry_seconds)
+
+            for evt in events:
+                idx = evt["logIndex"]  # Integer of the log index position in the block, null when its pending
+
+                # We cannot avoid minor chain reorganisations, but
+                # at least we must avoid blocks that are not mined yet
+                assert idx is not None, "Somehow tried to scan a pending block"
+
+                block_number = evt["blockNumber"]
+
+                # Get UTC time when this event happened (block mined timestamp)
+                # from our in-memory cache
+                block_when = get_block_when(block_number)
+
+                logger.debug("Processing event %s, block:%d count:%d", evt["event"], evt["blockNumber"])
+                processed = self.state.process_event(block_when, evt)
+                all_processed.append(processed)
+
+        end_block_timestamp = get_block_when(end_block)
+        return end_block, end_block_timestamp, all_processed
+
+    def estimate_next_chunk_size(self, current_chuck_size: int, event_found_count: int):
+        """Try to figure out optimal chunk size
+
+        Our scanner might need to scan the whole blockchain for all events
+
+        * We want to minimize API calls over empty blocks
+
+        * We want to make sure that one scan chunk does not try to process too many entries once, as we try to control commit buffer size and potentially asynchronous busy loop
+
+        * Do not overload node serving JSON-RPC API by asking data for too many events at a time
+
+        Currently Ethereum JSON-API does not have an API to tell when a first event occurred in a blockchain
+        and our heuristics try to accelerate block fetching (chunk size) until we see the first event.
+
+        These heurestics exponentially increase the scan chunk size depending on if we are seeing events or not.
+        When any transfers are encountered, we are back to scanning only a few blocks at a time.
+        It does not make sense to do a full chain scan starting from block 1, doing one JSON-RPC call per 20 blocks.
+        """
+
+        if event_found_count > 0:
+            # When we encounter first events, reset the chunk size window
+            current_chuck_size = self.min_scan_chunk_size
+        else:
+            current_chuck_size *= self.chunk_size_increase
+
+        current_chuck_size = max(self.min_scan_chunk_size, current_chuck_size)
+        current_chuck_size = min(self.max_scan_chunk_size, current_chuck_size)
+        return int(current_chuck_size)
+
+    def scan(self, start_block, end_block, start_chunk_size=20, progress_callback=Optional[Callable]) -> Tuple[
+        list, int]:
+        """Perform a token balances scan.
+
+        Assumes all balances in the database are valid before start_block (no forks sneaked in).
+
+        :param start_block: The first block included in the scan
+
+        :param end_block: The last block included in the scan
+
+        :param start_chunk_size: How many blocks we try to fetch over JSON-RPC on the first attempt
+
+        :param progress_callback: If this is an UI application, update the progress of the scan
+
+        :return: [All processed events, number of chunks used]
+        """
+
+        assert start_block <= end_block
+
+        current_block = start_block
+
+        # Scan in chunks, commit between
+        chunk_size = start_chunk_size
+        last_scan_duration = last_logs_found = 0
+        total_chunks_scanned = 0
+
+        # All processed entries we got on this scan cycle
+        all_processed = []
+
+        while current_block <= end_block:
+            self.state.start_chunk(current_block, chunk_size)
+
+            # Print some diagnostics to logs to try to fiddle with real world JSON-RPC API performance
+            estimated_end_block = current_block + chunk_size
+            logger.debug(
+                "Scanning token transfers for blocks: %d - %d, chunk size %d, last chunk scan took %f, last logs found %d",
+                current_block, estimated_end_block, chunk_size, last_scan_duration, last_logs_found)
+
+            start = time.time()
+            actual_end_block, end_block_timestamp, new_entries = self.scan_chunk(current_block, estimated_end_block)
+
+            # Where does our current chunk scan ends - are we out of chain yet?
+            current_end = actual_end_block
+
+            last_scan_duration = time.time() - start
+            all_processed += new_entries
+
+            # Print progress bar
+            if progress_callback:
+                progress_callback(start_block, end_block, current_block, end_block_timestamp, chunk_size, len(new_entries))
+
+            # Try to guess how many blocks to fetch over `eth_getLogs` API next time
+            chunk_size = self.estimate_next_chunk_size(chunk_size, len(new_entries))
+
+            # Set where the next chunk starts
+            current_block = current_end + 1
+            total_chunks_scanned += 1
+            self.state.end_chunk(current_end)
+
+        return all_processed, total_chunks_scanned
+
+
+class JSONifiedState(EventScannerState):
+    """Store the state of scanned blocks and all events.
+
+    All state is an in-memory dict.
+    Simple load/store massive JSON on start up.
+    """
+
+    def __init__(self, file_name):
+        self.state = None
+        self.path = "state/" + file_name
+        # How many second ago we saved the JSON file
+        self.last_save = 0
+
+    def reset(self):
+        """Create initial state of nothing scanned."""
+        self.state = {
+            "last_scanned_block": 0,
+            "blocks": {},
+        }
+
+    def restore(self):
+        """Restore the last scan state from a file."""
+        try:
+            self.state = json.load(open(self.path, "rt"))
+            print(f"Restored the state, previously {self.state['last_scanned_block']} blocks have been scanned")
+        except (IOError, json.decoder.JSONDecodeError):
+            print("State starting from scratch")
+            self.reset()
+
+    def save(self):
+        """Save everything we have scanned so far in a file."""
+        with open(self.path, "wt") as f:
+            json.dump(self.state, f)
+        self.last_save = time.time()
+
+    #
+    # EventScannerState methods implemented below
+    #
+
+    def get_last_scanned_block(self):
+        """The number of the last block we have stored."""
+        return self.state["last_scanned_block"]
+
+    def delete_data(self, since_block):
+        """Remove potentially reorganised blocks from the scan data."""
+        for block_num in range(since_block, self.get_last_scanned_block()):
+            if block_num in self.state["blocks"]:
+                del self.state["blocks"][block_num]
+
+    def start_chunk(self, block_number, chunk_size):
+        pass
+
+    def end_chunk(self, block_number):
+        """Save at the end of each block, so we can resume in the case of a crash or CTRL+C"""
+        # Next time the scanner is started we will resume from this block
+        self.state["last_scanned_block"] = block_number
+
+        # Save the database file for every minute
+        if time.time() - self.last_save > 60:
+            self.save()
+
+    def process_event(self, block_when: datetime.datetime, event: AttributeDict) -> str:
+        """Record a ERC-20 transfer in our database."""
+        # Events are keyed by their transaction hash and log index
+        # One transaction may contain multiple events
+        # and each one of those gets their own log index
+
+        # event_name = event.event # "Transfer"
+        log_index = event.logIndex  # Log index within the block
+        # transaction_index = event.transactionIndex  # Transaction index within the block
+        txhash = event.transactionHash.hex()  # Transaction hash
+        block_number = event.blockNumber
+
+        # Convert ERC-20 Transfer event to our internal format
+        args = event["args"]
+
+        # transfer = {
+        #     "from": args["from"],
+        #     "to": args.to,
+        #     "value": args.value,
+        #     "timestamp": block_when.isoformat(),
+        # }
+
+        # Create empty dict as the block that contains all transactions by txhash
+        if block_number not in self.state["blocks"]:
+            self.state["blocks"][block_number] = {}
+
+        block = self.state["blocks"][block_number]
+        if txhash not in block:
+            # We have not yet recorded any transfers in this transaction
+            # (One transaction may contain multiple events if executed by a smart contract).
+            # Create a tx entry that contains all events by a log index
+            self.state["blocks"][block_number][txhash] = {}
+
+        if event["event"] == 'Sync':
+            sync = {"reserve0": args["reserve0"], "reserve1": args["reserve1"]}
+            # Record ERC-20 transfer in our database
+            self.state["blocks"][block_number][txhash][log_index] = sync
+        elif event["event"] == "Swap":
+            swap = {'sender': args['sender'],
+                    'to': args['to'],
+                    'amount0In': args['amount0In'],
+                    'amount1In': args['amount1In'],
+                    'amount0Out': args['amount0Out'],
+                    'amount1Out': args['amount1Out'],
+                    }
+            self.state["blocks"][block_number][txhash][log_index] = swap
+
+        # Return a pointer that allows us to look up this event later if needed
+        return f"{block_number}-{txhash}-{log_index}"
+
+
+def _retry_web3_call(func, start_block, end_block, retries, delay) -> Tuple[int, list]:
+    """A custom retry loop to throttle down block range.
+
+    If our JSON-RPC server cannot serve all incoming `eth_getLogs` in a single request,
+    we retry and throttle down block range for every retry.
+
+    For example, Go Ethereum does not indicate what is an acceptable response size.
+    It just fails on the server-side with a "context was cancelled" warning.
+
+    :param func: A callable that triggers Ethereum JSON-RPC, as func(start_block, end_block)
+    :param start_block: The initial start block of the block range
+    :param end_block: The initial start block of the block range
+    :param retries: How many times we retry
+    :param delay: Time to sleep between retries
+    """
+    for i in range(retries):
+        try:
+            return end_block, func(start_block, end_block)
+        except Exception as e:
+            # Assume this is HTTPConnectionPool(host='localhost', port=8545): Read timed out. (read timeout=10)
+            # from Go Ethereum. This translates to the error "context was cancelled" on the server side:
+            # https://github.com/ethereum/go-ethereum/issues/20426
+            if i < retries - 1:
+                # Give some more verbose info than the default middleware
+                logger.warning(
+                    "Retrying events for block range %d - %d (%d) failed with %s, retrying in %s seconds",
+                    start_block,
+                    end_block,
+                    end_block-start_block,
+                    e,
+                    delay)
+                # Decrease the `eth_getBlocks` range
+                end_block = start_block + ((end_block - start_block) // 2)
+                # Let the JSON-RPC to recover e.g. from restart
+                time.sleep(delay)
+                continue
+            else:
+                logger.warning("Out of retries")
+                raise
+
+
+def _fetch_events_for_all_contracts(
+        web3,
+        event,
+        argument_filters: dict,
+        from_block: int,
+        to_block: int) -> Iterable:
+    """Get events using eth_getLogs API.
+
+    This method is detached from any contract instance.
+
+    This is a stateless method, as opposed to createFilter.
+    It can be safely called against nodes which do not provide `eth_newFilter` API, like Infura.
+    """
+
+    if from_block is None:
+        raise TypeError("Missing mandatory keyword argument to getLogs: fromBlock")
+
+    # Currently no way to poke this using a public Web3.py API.
+    # This will return raw underlying ABI JSON object for the event
+    abi = event._get_event_abi()
+
+    # Depending on the Solidity version used to compile
+    # the contract that uses the ABI,
+    # it might have Solidity ABI encoding v1 or v2.
+    # We just assume the default that you set on Web3 object here.
+    # More information here https://eth-abi.readthedocs.io/en/latest/index.html
+    codec: ABICodec = web3.codec
+
+    # Here we need to poke a bit into Web3 internals, as this
+    # functionality is not exposed by default.
+    # Construct JSON-RPC raw filter presentation based on human readable Python descriptions
+    # Namely, convert event names to their keccak signatures
+    # More information here:
+    # https://github.com/ethereum/web3.py/blob/e176ce0793dafdd0573acc8d4b76425b6eb604ca/web3/_utils/filters.py#L71
+    data_filter_set, event_filter_params = construct_event_filter_params(
+        abi,
+        codec,
+        address=argument_filters.get("address"),
+        argument_filters=argument_filters,
+        fromBlock=from_block,
+        toBlock=to_block
+    )
+
+    logger.debug("Querying eth_getLogs with the following parameters: %s", event_filter_params)
+
+    # Call JSON-RPC API on your Ethereum node.
+    # get_logs() returns raw AttributedDict entries
+    logs = web3.eth.get_logs(event_filter_params)
+
+    # Convert raw binary data to Python proxy objects as described by ABI
+    all_events = []
+    for log in logs:
+        # Convert raw JSON-RPC log result to human readable event by using ABI data
+        # More information how processLog works here
+        # https://github.com/ethereum/web3.py/blob/fbaf1ad11b0c7fac09ba34baff2c256cffe0a148/web3/_utils/events.py#L200
+        evt = get_event_data(codec, abi, log)
+        # Note: This was originally yield,
+        # but deferring the timeout exception caused the throttle logic not to work
+        all_events.append(evt)
+    return all_events
diff --git a/src/local_node/process_state_to_df.py b/src/local_node/process_state_to_df.py
new file mode 100644
index 0000000..b435e4a
--- /dev/null
+++ b/src/local_node/process_state_to_df.py
@@ -0,0 +1,100 @@
+import time
+from logging import error, info
+from typing import Callable
+from unittest import TestCase
+
+import pandas as pd
+from pandas import DataFrame
+from tqdm import tqdm
+
+
+class ProcessStateToDF:
+    RESERVE_KEYS = {'reserve0', 'reserve1'}
+    SWAP_KEYS = {'sender', 'to', 'amount0In', 'amount1In', 'amount0Out', 'amount1Out'}
+
+    @staticmethod
+    def get_progress_callback(blocks: int) -> Callable:
+        with tqdm(total=blocks, ascii=True) as progress_bar:
+            def update_callback(current, chunk_size):
+                progress_bar.set_description(f'Current block: {current}')
+                progress_bar.update(chunk_size)
+        return update_callback
+
+
+    @classmethod
+    def process_state(cls, data: dict, test_self: TestCase) -> DataFrame:
+        swaps = []
+        reserve0 = 0
+        reserve1 = 0
+        start = time.time()
+        blocks = sorted(data.keys())
+        progress_callback = cls.get_progress_callback(len(blocks))
+
+        for block in sorted(data.keys()):
+            current_block = block
+            progress_callback(current_block, 1)
+            txns_list = [data[block][hash_key] for hash_key in data[block]]
+            for txn_dict in txns_list:
+                reserve0, reserve1 = cls.process_txn(block, reserve0, reserve1, swaps, test_self, txn_dict)
+        duration = time.time() - start
+        info(f"Scanned blocks in {duration} seconds")
+        return pd.DataFrame(swaps)
+
+    @classmethod
+    def process_txn(cls, block, reserve0, reserve1, swaps, test_self, txn_dict):
+        txns = sorted((txn_key for txn_key in txn_dict), key=int)
+        while len(txns) > 0:
+            if len(txns) > 1:
+                if txn_dict[txns[0]].keys() == cls.RESERVE_KEYS and txn_dict[txns[1]].keys() == cls.SWAP_KEYS:
+                    txn1 = txns.pop(0)
+                    txn2 = txns.pop(0)
+                    reserve0, reserve1 = cls.process_swap(
+                        block, reserve0, reserve1, swaps, txn_dict, txn1, txn2)
+                elif txn_dict[txns[0]].keys() == cls.RESERVE_KEYS:
+                    reserve0, reserve1 = cls.process_reserve(reserve0, reserve1, txns.pop(0), txn_dict)
+                else:
+                    msg = f'Unknown txns {txn_dict[txns.pop(0)]}'
+                    error(msg)
+                    test_self.fail(msg)
+            elif len(txns) == 1:
+                if txn_dict[txns[0]].keys() == cls.RESERVE_KEYS:
+                    reserve0, reserve1 = cls.process_reserve(reserve0, reserve1, txns.pop(0), txn_dict)
+                else:
+                    msg = f'Unknown txns {txn_dict[txns.pop(0)]}'
+                    error(msg)
+                    test_self.fail(msg)
+        return reserve0, reserve1
+
+    @classmethod
+    def process_reserve(cls, reserve0, reserve1, txn, txn_dict):
+        reserve = txn_dict[txn]
+        reserve0, reserve1 = cls._process_reserves(reserve0, reserve1, reserve)
+        return reserve0, reserve1
+
+    @classmethod
+    def process_swap(cls, block, reserve0, reserve1, swaps, txn_dict, txn1, txn2):
+        reserve = txn_dict[txn1]
+        swap = txn_dict[txn2]
+        swap['block'] = block
+        swap['reserve0'] = reserve0
+        swap['reserve1'] = reserve1
+        swaps.append(swap)
+        reserve0 += swap['amount0In'] - swap['amount0Out']
+        reserve1 += swap['amount1In'] - swap['amount1Out']
+        reserve0, reserve1 = cls._process_reserves(reserve0, reserve1, reserve)
+        return reserve0, reserve1
+
+    @classmethod
+    def _process_reserves(cls, reserve0, reserve1, entry):
+        _reserve0 = entry['reserve0']
+        _reserve1 = entry['reserve1']
+        if _reserve0 > reserve0 and _reserve1 > reserve1:
+            info(f"Mint {_reserve0-reserve0}, {_reserve1-reserve1}")
+        elif _reserve0 < reserve0 and _reserve1 < reserve1:
+            info(f"Burn {reserve0 - _reserve0}, {reserve1 - _reserve1}")
+        elif _reserve0 != reserve0 or _reserve1 != reserve1:
+            error(f"Not sure what this is, "
+                  f"\n\treserve0: {reserve0} -> {_reserve0}"
+                  f"\n\treserve1: {reserve1} -> {_reserve1}")
+        return _reserve0, _reserve1
+
diff --git a/src/local_node/scanner_runner.py b/src/local_node/scanner_runner.py
new file mode 100644
index 0000000..c0a2fcd
--- /dev/null
+++ b/src/local_node/scanner_runner.py
@@ -0,0 +1,50 @@
+import json
+import time
+from typing import Union, Type
+
+from tqdm import tqdm
+from web3 import Web3
+from web3.contract import Contract
+
+from src.local_node.event_scanner import JSONifiedState, EventScanner
+
+
+class ScannerRunner:
+    @staticmethod
+    def run_scanner(file_name, first_block, node_url, abi, uni_pair_contract_address):
+        provider = Web3.HTTPProvider(node_url, request_kwargs={'timeout': 60})
+        provider.middlewares.clear()
+        web3 = Web3(provider)
+        abi = json.loads(abi)
+        pair_contact: Union[Type[Contract], Contract] = web3.eth.contract(abi=abi)
+        state = JSONifiedState(file_name)
+        state.restore()
+        scanner = EventScanner(
+            web3=web3, contract=pair_contact, state=state, events=[pair_contact.events.Sync, pair_contact.events.Swap],
+            filters={"address": uni_pair_contract_address}, max_chunk_scan_size=10000)
+        chain_reorg_safety_blocks = 10
+        scanner.delete_potentially_forked_block_data(state.get_last_scanned_block() - chain_reorg_safety_blocks)
+        start_block = max(state.get_last_scanned_block() - chain_reorg_safety_blocks, first_block)
+        # TODO(WF): add arg to overwrite
+        end_block = scanner.get_suggested_scan_end_block()
+        blocks_to_scan = end_block - start_block
+        print(f"Scanning events from blocks {start_block} - {end_block}")
+        start = time.time()
+        with tqdm(total=blocks_to_scan) as progress_bar:
+            def _update_progress(start, end, current, current_block_timestamp, chunk_size, events_count):
+                if current_block_timestamp:
+                    formatted_time = current_block_timestamp.strftime("%d-%m-%Y")
+                else:
+                    formatted_time = "no block time available"
+                progress_bar.set_description(
+                    f"Current block: {current} ({formatted_time}), blocks in a scan batch: {chunk_size}, events "
+                    f"processed in a batch {events_count}")
+                progress_bar.update(chunk_size)
+
+            # Run the scan
+            result, total_chunks_scanned = scanner.scan(start_block, end_block, progress_callback=_update_progress)
+        state.save()
+        duration = time.time() - start
+        print(
+            f"Scanned total {len(result)} Transfer events, in {duration} seconds, total {total_chunks_scanned} chunk "
+            f"scans performed")
diff --git a/src/uniswap_v2_pair_abi.py b/src/uniswap_v2_pair_abi.py
new file mode 100644
index 0000000..ba7af24
--- /dev/null
+++ b/src/uniswap_v2_pair_abi.py
@@ -0,0 +1,3 @@
+UNISWAP_V2_PAIR_ABI = '''
+[{"inputs":[],"payable":false,"stateMutability":"nonpayable","type":"constructor"},{"anonymous":false,"inputs":[{"indexed":true,"internalType":"address","name":"owner","type":"address"},{"indexed":true,"internalType":"address","name":"spender","type":"address"},{"indexed":false,"internalType":"uint256","name":"value","type":"uint256"}],"name":"Approval","type":"event"},{"anonymous":false,"inputs":[{"indexed":true,"internalType":"address","name":"sender","type":"address"},{"indexed":false,"internalType":"uint256","name":"amount0","type":"uint256"},{"indexed":false,"internalType":"uint256","name":"amount1","type":"uint256"},{"indexed":true,"internalType":"address","name":"to","type":"address"}],"name":"Burn","type":"event"},{"anonymous":false,"inputs":[{"indexed":true,"internalType":"address","name":"sender","type":"address"},{"indexed":false,"internalType":"uint256","name":"amount0","type":"uint256"},{"indexed":false,"internalType":"uint256","name":"amount1","type":"uint256"}],"name":"Mint","type":"event"},{"anonymous":false,"inputs":[{"indexed":true,"internalType":"address","name":"sender","type":"address"},{"indexed":false,"internalType":"uint256","name":"amount0In","type":"uint256"},{"indexed":false,"internalType":"uint256","name":"amount1In","type":"uint256"},{"indexed":false,"internalType":"uint256","name":"amount0Out","type":"uint256"},{"indexed":false,"internalType":"uint256","name":"amount1Out","type":"uint256"},{"indexed":true,"internalType":"address","name":"to","type":"address"}],"name":"Swap","type":"event"},{"anonymous":false,"inputs":[{"indexed":false,"internalType":"uint112","name":"reserve0","type":"uint112"},{"indexed":false,"internalType":"uint112","name":"reserve1","type":"uint112"}],"name":"Sync","type":"event"},{"anonymous":false,"inputs":[{"indexed":true,"internalType":"address","name":"from","type":"address"},{"indexed":true,"internalType":"address","name":"to","type":"address"},{"indexed":false,"internalType":"uint256","name":"value","type":"uint256"}],"name":"Transfer","type":"event"},{"constant":true,"inputs":[],"name":"DOMAIN_SEPARATOR","outputs":[{"internalType":"bytes32","name":"","type":"bytes32"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"MINIMUM_LIQUIDITY","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"PERMIT_TYPEHASH","outputs":[{"internalType":"bytes32","name":"","type":"bytes32"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[{"internalType":"address","name":"","type":"address"},{"internalType":"address","name":"","type":"address"}],"name":"allowance","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"spender","type":"address"},{"internalType":"uint256","name":"value","type":"uint256"}],"name":"approve","outputs":[{"internalType":"bool","name":"","type":"bool"}],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[{"internalType":"address","name":"","type":"address"}],"name":"balanceOf","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"to","type":"address"}],"name":"burn","outputs":[{"internalType":"uint256","name":"amount0","type":"uint256"},{"internalType":"uint256","name":"amount1","type":"uint256"}],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[],"name":"decimals","outputs":[{"internalType":"uint8","name":"","type":"uint8"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"factory","outputs":[{"internalType":"address","name":"","type":"address"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"getReserves","outputs":[{"internalType":"uint112","name":"_reserve0","type":"uint112"},{"internalType":"uint112","name":"_reserve1","type":"uint112"},{"internalType":"uint32","name":"_blockTimestampLast","type":"uint32"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"_token0","type":"address"},{"internalType":"address","name":"_token1","type":"address"}],"name":"initialize","outputs":[],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[],"name":"kLast","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"to","type":"address"}],"name":"mint","outputs":[{"internalType":"uint256","name":"liquidity","type":"uint256"}],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[],"name":"name","outputs":[{"internalType":"string","name":"","type":"string"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[{"internalType":"address","name":"","type":"address"}],"name":"nonces","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"owner","type":"address"},{"internalType":"address","name":"spender","type":"address"},{"internalType":"uint256","name":"value","type":"uint256"},{"internalType":"uint256","name":"deadline","type":"uint256"},{"internalType":"uint8","name":"v","type":"uint8"},{"internalType":"bytes32","name":"r","type":"bytes32"},{"internalType":"bytes32","name":"s","type":"bytes32"}],"name":"permit","outputs":[],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[],"name":"price0CumulativeLast","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"price1CumulativeLast","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"to","type":"address"}],"name":"skim","outputs":[],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":false,"inputs":[{"internalType":"uint256","name":"amount0Out","type":"uint256"},{"internalType":"uint256","name":"amount1Out","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"bytes","name":"data","type":"bytes"}],"name":"swap","outputs":[],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[],"name":"symbol","outputs":[{"internalType":"string","name":"","type":"string"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[],"name":"sync","outputs":[],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":true,"inputs":[],"name":"token0","outputs":[{"internalType":"address","name":"","type":"address"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"token1","outputs":[{"internalType":"address","name":"","type":"address"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":true,"inputs":[],"name":"totalSupply","outputs":[{"internalType":"uint256","name":"","type":"uint256"}],"payable":false,"stateMutability":"view","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"value","type":"uint256"}],"name":"transfer","outputs":[{"internalType":"bool","name":"","type":"bool"}],"payable":false,"stateMutability":"nonpayable","type":"function"},{"constant":false,"inputs":[{"internalType":"address","name":"from","type":"address"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"value","type":"uint256"}],"name":"transferFrom","outputs":[{"internalType":"bool","name":"","type":"bool"}],"payable":false,"stateMutability":"nonpayable","type":"function"}]
+'''
diff --git a/test/__init__.py b/test/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/test/local_node/__init__.py b/test/local_node/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/test/local_node/test_scanner_with_node.py b/test/local_node/test_scanner_with_node.py
new file mode 100644
index 0000000..baed3a6
--- /dev/null
+++ b/test/local_node/test_scanner_with_node.py
@@ -0,0 +1,64 @@
+import logging
+import sys
+import unittest
+from unittest import TestCase
+
+from eth_typing import Address
+from pandas import DataFrame
+from web3 import Web3
+
+from src.local_node.event_scanner import JSONifiedState
+from src.local_node.process_state_to_df import ProcessStateToDF
+from src.local_node.scanner_runner import ScannerRunner
+from src.uniswap_v2_pair_abi import UNISWAP_V2_PAIR_ABI
+
+this_log = logging.getLogger(__name__)
+this_log.setLevel(logging.INFO)
+this_log.addHandler(logging.StreamHandler(sys.stdout))
+
+
+class TestScannerWithNode(TestCase, ScannerRunner):
+    ETH_POOL_UNI_V2_CONTRACT_ADDRESS: Address = "0x85Cb0baB616Fe88a89A35080516a8928F38B518b"
+    FIRST_BLOCK = 11876000
+    NODE_URL = "http://1.1.1.1:1111"
+    ABI = UNISWAP_V2_PAIR_ABI
+
+    def test_web_3_sync(self):
+        w3 = Web3(Web3.HTTPProvider(self.NODE_URL, request_kwargs={'timeout': 60}))
+        self.assertTrue(w3.isConnected())
+
+        contract = w3.eth.contract(address=self.ETH_POOL_UNI_V2_CONTRACT_ADDRESS, abi=self.ABI)
+
+        print(contract)
+        event_filter = contract.events.Sync.createFilter(fromBlock=16478475-1000, toBlock=16478475)
+        events = event_filter.get_all_entries()
+        self.assertEqual(len(events), 2)
+        self.assertEqual(set(events[0].keys()), {'address', 'args', 'blockHash', 'blockNumber', 'event', 'logIndex',
+                                                 'transactionHash', 'transactionIndex'})
+        self.assertEqual(events[0]["event"], 'Sync')
+        self.assertEqual(set(events[0]["args"].keys()), {'reserve0', 'reserve1'})
+        print(events[0]["args"])
+
+        event_filter = contract.events.Swap.createFilter(fromBlock=16478475 - 1000, toBlock=16478475)
+        swaps = event_filter.get_all_entries()
+        print(len(swaps))
+        print(swaps[0]["args"].keys())
+
+    @unittest.skip("Using as a work space, runs in 12 hours for ETH-POOL pair")
+    def test_scanner_runner(self):
+
+        ScannerRunner.run_scanner(
+            "test-state.json", self.FIRST_BLOCK, self.NODE_URL, self.ABI, self.ETH_POOL_UNI_V2_CONTRACT_ADDRESS)
+
+    @unittest.skip("Using as a work space")
+    def testReadJsonState(self):
+        json_state = JSONifiedState("test-state.json")
+        json_state.restore()
+        state = json_state.state
+        state_df = ProcessStateToDF.process_state(state["blocks"], self)
+
+        self.assertTrue(isinstance(state_df, DataFrame))
+
+        # store file as needed.
+        # state_df.to_csv("state/0x85Cb0baB616Fe88a89A35080516a8928F38B518b_df.csv")
+        state_df.to_pickle("state/0x85Cb0baB616Fe88a89A35080516a8928F38B518b_df.pkl")