From 35a1cd748e53ad5c939c796a80d89bef57ec53d5 Mon Sep 17 00:00:00 2001
From: Oleg Sheynin <osheynin@cryptovaltrading.com>
Date: Mon, 14 Jul 2025 05:15:47 +0000
Subject: [PATCH] notebook changes

---
 requirements.txt                          |    6 +
 research/notebooks/pt_pair_backtest.ipynb | 3204 ++++++++++++++++++++-
 sync_visualization.py                     |    1 -
 3 files changed, 3141 insertions(+), 70 deletions(-)
 delete mode 100644 sync_visualization.py

diff --git a/requirements.txt b/requirements.txt
index 52cee67..c1208f7 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -24,11 +24,14 @@ hjson>=3.0.2
 html5lib>=1.1
 httplib2>=0.20.2
 idna>=3.3
+ipython>=8.18.1
+ipywidgets>=8.1.1
 ifaddr>=0.1.7
 IMDbPY>=2021.4.18
 ipykernel>=6.29.5
 jeepney>=0.7.1
 jsonschema>=3.2.0
+jupyter>=1.0.0
 keyring>=23.5.0
 launchpadlib>=1.10.16
 lazr.restfulclient>=0.14.4
@@ -42,15 +45,18 @@ more-itertools>=8.10.0
 multidict>=6.0.4
 mypy>=0.942
 mypy-extensions>=0.4.3
+nbformat>=5.10.2
 netaddr>=0.8.0
 ######### netifaces>=0.11.0
 numpy>=1.26.4,<2.3.0
 oauthlib>=3.2.0
 packaging>=23.1
+pandas>=2.2.3
 pathspec>=0.11.1
 pexpect>=4.8.0
 Pillow>=9.0.1
 platformdirs>=3.2.0
+plotly>=5.19.0
 protobuf>=3.12.4
 psutil>=5.9.0
 ptyprocess>=0.7.0
diff --git a/research/notebooks/pt_pair_backtest.ipynb b/research/notebooks/pt_pair_backtest.ipynb
index a50eaaf..3727353 100644
--- a/research/notebooks/pt_pair_backtest.ipynb
+++ b/research/notebooks/pt_pair_backtest.ipynb
@@ -424,6 +424,120 @@
         "display(pair.market_data_.head())\n"
       ]
     },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Fixed draw_symbol_trades function created successfully!\n",
+            "This function correctly filters trades data rather than trying to filter price data with trade conditions.\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Fixed draw_symbol_trades function\n",
+        "def draw_symbol_trades_fixed(fig, symbol_name, color, symbol_data, colname):\n",
+        "    # Add Symbol price data to row 4 (subplot 4)\n",
+        "    fig.add_trace(\n",
+        "        go.Scatter(\n",
+        "            x=symbol_data['tstamp'],\n",
+        "            y=symbol_data[colname],\n",
+        "            name=f'{symbol_name} Price',\n",
+        "            line=dict(color=color, width=2),\n",
+        "            opacity=0.8\n",
+        "        ),\n",
+        "        row=4, col=1\n",
+        "    )\n",
+        "    \n",
+        "    # Add trading signals for Symbol if available\n",
+        "    if pair_trades is not None and len(pair_trades) > 0:\n",
+        "        # Filter trades for this symbol\n",
+        "        symbol_trades = pair_trades[pair_trades['symbol'] == symbol_name].copy()\n",
+        "        \n",
+        "        if len(symbol_trades) > 0:\n",
+        "            # Separate trades by action and status - filter the trades, not the price data\n",
+        "            buy_open_trades = symbol_trades[(symbol_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                            (symbol_trades['status'] == 'OPEN')]\n",
+        "            buy_close_trades = symbol_trades[(symbol_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                            (symbol_trades['status'] == 'CLOSE')]\n",
+        "            sell_open_trades = symbol_trades[(symbol_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                            (symbol_trades['status'] == 'OPEN')]\n",
+        "            sell_close_trades = symbol_trades[(symbol_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                            (symbol_trades['status'] == 'CLOSE')]\n",
+        "            \n",
+        "            # Add BUY OPEN signals\n",
+        "            if len(buy_open_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=buy_open_trades['time'],\n",
+        "                        y=buy_open_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{symbol_name} BUY OPEN',\n",
+        "                        marker=dict(color='red', size=12, symbol='triangle-up'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add BUY CLOSE signals\n",
+        "            if len(buy_close_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=buy_close_trades['time'],\n",
+        "                        y=buy_close_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{symbol_name} BUY CLOSE',\n",
+        "                        marker=dict(color='red', size=12, symbol='triangle-down'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add SELL OPEN signals\n",
+        "            if len(sell_open_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=sell_open_trades['time'],\n",
+        "                        y=sell_open_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{symbol_name} SELL OPEN',\n",
+        "                        marker=dict(color='blue', size=12, symbol='triangle-up'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add SELL CLOSE signals\n",
+        "            if len(sell_close_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=sell_close_trades['time'],\n",
+        "                        y=sell_close_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{symbol_name} SELL CLOSE',\n",
+        "                        marker=dict(color='blue', size=12, symbol='triangle-down'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "\n",
+        "print(\"Fixed draw_symbol_trades function created successfully!\")\n",
+        "print(\"This function correctly filters trades data rather than trying to filter price data with trade conditions.\")\n"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},
@@ -433,7 +547,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 6,
+      "execution_count": 7,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -486,7 +600,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 7,
+      "execution_count": 8,
       "metadata": {},
       "outputs": [
         {
@@ -561,7 +675,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 8,
+      "execution_count": 9,
       "metadata": {},
       "outputs": [
         {
@@ -674,13 +788,19 @@
         }
       },
       "source": [
-        "# Run\n",
-        "## Analysis\n"
+        "# Run"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Analysis"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 9,
+      "execution_count": 10,
       "metadata": {},
       "outputs": [
         {
@@ -812,14 +932,6 @@
             "\n",
             "================================================================================\n"
           ]
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "/home/oleg/develop/pairs_trading/lib/pt_trading/trading_pair.py:185: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
-            "  self.user_data_[\"trades\"] = pd.concat([self.user_data_[\"trades\"], pd.DataFrame(trades)], ignore_index=True)\n"
-          ]
         }
       ],
       "source": [
@@ -936,7 +1048,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 11,
       "metadata": {},
       "outputs": [
         {
@@ -945,12 +1057,14 @@
           "text": [
             "=== SLIDING FIT FIT_MODEL VISUALIZATION ===\n",
             "Note: Sliding strategy visualization requires detailed tracking data\n",
-            "For full sliding window visualization, run the complete sliding analysis\n"
+            "For full sliding window visualization, run the complete sliding analysis\n",
+            "Using consistent timeline with 391 timestamps\n",
+            "Timeline range: 2025-06-05 13:30:00 to 2025-06-05 20:00:00\n"
           ]
         },
         {
           "data": {
-            "image/png": "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",
+            "image/png": "iVBORw0KGgoAAAANSUhEUgAABv0AAAY1CAYAAAAB6xJcAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3Xd4FPXaxvF7Zje9QAgIUgSlBBQQ0KM0G2JBxYJH7OiriOVgxYJYAEGwi4qIBVGwAHaxcCzHhr0hKqgUG0VqgBRIdmfm/WPYTUKSTcgGtn0/18W1mdmZ3d8kzGyy9z7Pz3AcxxEAAAAAAAAAAACAmGVGegAAAAAAAAAAAAAAwkPoBwAAAAAAAAAAAMQ4Qj8AAAAAAAAAAAAgxhH6AQAAAAAAAAAAADGO0A8AAAAAAAAAAACIcYR+AAAAAAAAAAAAQIwj9AMAAAAAAAAAAABiHKEfAAAAAAAAAAAAEOMI/QAAAAAAAAAAAIAYR+gHAAAAYLd66KGHlJeXF+lh7HJ5eXl66KGH6u3xXn75ZeXl5WnFihX19pixbuTIkerXr1+khxG2FStWKC8vTy+//HJwXVXnSb9+/TRy5MjgcuD/xI8//hjW8+/4uAAAAABikzfSAwAAAACwe9Q2aJsxY4YOPvjgsJ5r69ateuKJJ3TQQQeF/Vj1aeTIkXrllVeCyxkZGWrZsqVOPvlknXPOOUpOTo7g6Hatc889V1999VVwOSUlRa1bt9app56qIUOGyDQj+5nQhx56SJMnTw4up6amKicnRx07dtRRRx2lgQMHxvXPBwAAAADCRegHAAAAJIi77rqrwvJrr72mTz/9tNL6tm3bhv1cW7du1eTJkzV8+PBKod+ll16qYcOGhf0cdZWcnKzx48dLkgoKCvTf//5Xd955p3788Ufdf//99fY8CxculMfjqbfHqw/NmjXTNddcI0nKz8/XG2+8oYkTJyo/P19XX311hEfnGjNmjNLT01VaWqo1a9Zo/vz5GjVqlJ5++mk9+uij2nPPPYPbjhs3To7jRHC09aNFixZauHChvN7Qf6LPmzdPhmHU+/PvqscFAAAAsHsR+gEAAAAJ4qSTTqqw/MMPP+jTTz+ttH5X83q9NYYbu/r5yx/zWWedpdNOO01vvfWWRo4cqaZNm9b5sW3bls/nU0pKilJSUupjuPUqKyurwrGfeeaZGjBggGbOnKkrrrgiKkLKY445Ro0aNQouDx8+XK+//rpuuOEGXXnllZozZ07wvqSkpEgMsd4ZhlGr/y/1WenoOI5KSkqUmppKBSUAAAAQJ5jTDwAAAECQbdt66qmndPzxx6tLly7q3bu3br31Vm3evLnCdj/++KMuvPBCHXzwweratav69eunG2+8UZI7P1mvXr0kSZMnT1ZeXl6F+e2qmqssLy9Pt912m9577z2dcMIJ6ty5s44//nh9/PHHlcb45ZdfatCgQerSpYv69++vWbNmhTVPoGmaOuiggyRJK1eulCSVlpbqwQcf1FFHHaXOnTvrsMMO01133aXS0tIqx/36668Hv2effPJJ8L4d5/RbtGiRhg4dqh49eqh79+4677zztGDBgkpjWrJkiYYMGaKuXbvq0EMP1ZQpU2TbdqXtCgoKtGzZMhUUFNTp2FNSUtS5c2cVFRVpw4YNwfW//PKLRo4cqSOPPFJdunRRnz59dOONNyo/P7/CNnl5eXr//feD63766Sfl5eXplFNOqfA8Q4cO1WmnnVanMUrSiSeeqNNOOy0YVAdUNaffm2++qUGDBql79+7q0aOHBg4cqKeffrpWz7NmzRrdeOON6t27d/D/4Isvvlhpu3/++UeXXXaZunXrpl69emnChAn65JNPlJeXpy+//DK4XXVz5Z177rk699xzg8tVzelXleoeb9u2bbr11lt18MEHq0ePHrr++usrnbP9+vXTxRdfrE8++USDBg1S165dNWvWrCoft7rzqap5JQOPGzgvu3btqoEDBwa/D++8844GDhyoLl26aNCgQVq0aFHIYwQAAABQd1T6AQAAAAi69dZb9corr2jQoEE699xztWLFCj377LNatGiRnn/+eSUlJWnDhg268MILlZOTo2HDhik7O1srVqzQu+++K0lq1KiRxowZozFjxuioo47SUUcdJanmOQW//fZbvfPOOzrrrLOUkZERrD774IMPlJOTI6ksNGvSpIkuv/xy2bathx9+uEJlWF38/fffkqSGDRvKtm1deuml+vbbbzV48GC1bdtWv/32m55++mn98ccfmjJlSoV9v/jiC7399ts6++yzlZOToxYtWlT5HEuWLNHZZ5+tjIwMDR06VF6vV7Nnz9a5556rZ555Rvvvv78kad26dRoyZIgsy9KwYcOUlpamOXPmVFkJ9u677+rGG2/UxIkTNWjQoDod+8qVK2UYhrKzs4PrPvvsM/39998aNGiQmjRpoiVLlmjOnDlaunSp5syZI8Mw1KFDB2VnZ+ubb77RkUceKUn65ptvZJqmfvnlFxUWFiozM1O2bev777/X4MGD6zS+gBNPPFGzZ8/W/Pnz1adPnyq3+fTTT3XNNdeoV69euvbaayVJy5cv13fffafzzjsv5OOvX79egwcPlmEYOvvss9WoUSN9/PHHuummm1RYWKjzzz9fkhuwnXfeeVq9erXOPfdc7bHHHnrttdf0xRdfhHV84bjtttuUnZ2t4cOH6/fff9fzzz+vVatWaebMmRXadv7+++8aMWKETj/9dA0ePFh77713vTz/n3/+qREjRuiMM87QiSeeqCeffFKXXHKJxo4dq/vvv19nnnmmJOmxxx7TVVddpXnz5kV8DkkAAAAgHhH6AQAAAJDkBjYvvPCC7rnnHg0cODC4/uCDD9bQoUM1b948DRw4UN9//702b96sadOmqUuXLsHtAnPCpaen65hjjtGYMWOUl5dX6/ahy5Yt01tvvaW99tor+LwnnXSS3nzzTZ1zzjmSpAcffFAej0fPP/98sA3ngAEDdNxxx+3UsW7cuFGSVFhYqLffflvvvfee8vLytM8+++i1117TZ599ppkzZ+rAAw8M7tO+fXuNHj1a3333nXr06BFc//vvv2vu3Llq165dyOecNGmSfD6fnn/+ebVq1UqSdPLJJ+vYY4/V3XffrWeeeUaS9Pjjj2vjxo164YUX1LVrV0nSKaecoqOPPnqnjrEqlmUFj33Tpk168cUX9dNPP+nwww9XampqcLuzzjpLF1xwQYV9u3XrpmuuuUbffvutDjzwQJmmqR49euibb74JbvPtt9+qf//+ev/99/Xdd9/p0EMPDQaA5b+XddGhQwdJZQFtVT788ENlZmZq2rRpO92q9P7775dlWZo7d24wZD7zzDN1zTXXaPLkyTrjjDOUmpqq2bNn648//tCkSZM0YMAASdLgwYN3e5vc8pKSkvTUU08F2502b95cd999t/73v/8FA1nJDeeeeOIJHXLIIfX6/L///rtmzZql7t27S5LatWunCy+8ULfccovefvttNW/eXJLUoEED3Xrrrfr6668rzfUJAAAAIHx8tA4AAACAJGnevHnKyspSnz59tHHjxuC//fbbT+np6cF2fVlZWZLcgMXn89Xb8/fu3TsY+ElSx44dlZmZGQx5LMvS559/riOPPLLCvHutW7feqRCjuLhYvXr1Uq9evXTUUUfpvvvuU7du3fTwww9Lcr8Pbdu21T777FPh+9CzZ09JqtC+UZL+9a9/1Rj4WZalTz/9VP379w8GfpK0xx576IQTTtC3336rwsJCSdJHH32kbt26BQM/ya2eLB/EBgwaNEi//vprrav8li9fHjz2AQMGaNq0aerXr58mTpxYYbvyAWBJSYk2btwYrET8+eefg/cdcMABWrRokYqLiyW5od+hhx6qjh076ttvv5XkhsmGYeiAAw6o1Rirk56eLkkqKiqqdpvs7Gxt3bq1QgvQ2nAcR++884769esnx3Eq/Nz79u2rgoKC4HF//PHHatKkiY499tjg/mlpaWFXMobj9NNPrzC/4Zlnnimv16uPPvqownYtW7as98BPckO+QOAnKfh/pWfPnsHAr/z6UMEtAAAAgLqj0g8AAACAJLcKqKCgIDgf344Cc74ddNBBOuaYYzR58mQ99dRTOuigg9S/f38NHDhQycnJdX7+Pffcs9K6Bg0aaMuWLcHn37Ztm1q3bl1pu6rWVSclJUVTp06VJCUnJ6tly5Zq1qxZ8P4///xTy5Ytq/H7ENCyZcsan3Pjxo3aunVrle0U27ZtK9u2tXr1arVv316rVq0KhiPl1UcrxhYtWmj8+PGybVt//fWXpk6dqvz8/EqtQzdt2qTJkyfrrbfeqnS85ecPPPDAA+X3+7VgwQI1a9ZMGzZs0IEHHqilS5cGKwC/+eYbtWvXTg0bNgxr7IFgMSMjo9ptzjrrLL399tu66KKL1LRpU/Xp00cDBgzQoYceKqlipWNAgwYNVFBQoC1btmj27NmaPXt2lY8d2G/lypVq3bp1hbaZUv38fOpqx///GRkZatKkSXCOyoDa/F+tix3P3cAHA8qfV5KUmZkpScFzGgAAAED9IvQDAAAAIEmybVu5ubm65557qrw/MG+eYRh68MEHtWDBAn3wwQf65JNPNGrUKE2fPl2zZ88OGcqEUl07Rsdx6vR4oZ6nd+/e1d5v27Y6dOigG2+8scr7dwwyylfFRbv09PQKx96jRw8NGjRI999/v26++ebg+quuukrff/+9LrzwQnXq1Enp6emybVtDhw6t8PPo3LmzUlJS9PXXX6t58+bKzc3V3nvvrQMPPFDPPfecSktLgy0/w/Xbb79JUoVq0B3l5ubq1Vdf1fz58/Xxxx/r448/1ssvv6yTTz5Zd955p1avXl2h3aUkzZgxQ/vss48kd97AU045pcrHrmlOyp1hWdZOtx+tD7X9v7pjoBlgWVaV66s7lt11TgMAAABwEfoBAAAAkOSGKZ9//rl69OhRq3CgW7du6tatm66++mrNnTtX1157rd566y2ddtpp1YYG4cjNzVVKSor+/PPPSvdVta6u9tprL/3yyy/q1atXvR1Ho0aNlJaWpt9//73SfcuXL5dpmsFqqebNm1d5PFXtG66OHTvqxBNP1KxZs3TBBReoefPm2rx5sz7//HNdfvnlGj58eHDbP/74o9L+ycnJ6tq1q7755hs1b948OG/fAQccoNLSUr3++utav369/vWvf4U91tdff12SamxPmZycrH79+qlfv36ybVtjxozR7Nmzddlll6lZs2aaPn16he0DbWQzMjJk23bIQFhyqyV/++03OY5T4f9HVT+f8pWq5a1atapCm9dw/fnnn8H2s5LbAnXdunXBCsedlZ2dLcmtyAt8LbnjBgAAABC9mNMPAAAAgCRpwIABsixLU6ZMqXSf3+8PhhebN2+uVKnTqVMnSVJpaakkd44zqX7b+AUq9N5//32tWbMmuP7PP//UJ598Um/PM2DAAK1Zs0Zz5sypdN+2bduCbSZ3hsfjUZ8+ffT+++9rxYoVwfXr16/XG2+8oQMOOCDY+vCwww7TggULtHDhwuB2Gzdu1Ny5cys9bkFBgZYtW1ah5ebOGjp0qPx+fzAMq6466+mnn65y/QEHHKCFCxfqyy+/DM7b16hRI7Vt21aPP/64JAXDwLqaO3euXnjhBXXv3r3atquSlJ+fX2HZNM1ghV5paalSUlLUu3fvCv8aNGggj8ejY445Rv/973+DFYXllW8Jeuihh2rt2rWaN29ecN3WrVur/P/SqlUr/fDDD8HzQpI++OADrV69uvYHXwuzZ8+uML/m888/L7/fX+fQL1BN+fXXXwfXFRcX69VXXw1rnAAAAAB2LSr9AAAAAEhy5+o7/fTT9eijj2rx4sXq06ePkpKS9Mcff2jevHm66aabdOyxx+qVV17R888/r/79+2uvvfZSUVGR5syZo8zMzGDIkJqaqnbt2untt99WmzZt1LBhQ7Vv314dOnQIa4zDhw/X/PnzdeaZZ+rMM8+Ubdt65pln1L59ey1evLg+vg066aST9Pbbb2v06NH68ssv1aNHD1mWpeXLl2vevHl64okn1KVLl51+3KuuukqfffaZzjrrLJ111lnyeDyaPXu2SktLdd111wW3Gzp0qF577TUNHTpUQ4YMUVpamubMmaPmzZvr119/rfCY7777rm688UZNnDhRgwYNqtPxtmvXTocddphefPFFXXbZZcrJydG//vUvPfHEE/L5fGratKk+/fTTCmFleQceeKCmTp2q1atXVwj3DjzwQM2ePVstWrSo1BI1lP/+979KT0+Xz+fTmjVrNH/+fH333Xfq2LGjHnjggZD73nzzzdq8ebN69uyppk2batWqVXrmmWfUqVMntW3bNuS+I0aM0JdffqnBgwfrtNNOU7t27bR582b9/PPP+vzzz/XVV19JkgYPHqxnn31WN9xwg37++Wc1adJEr732WpXVsaeddpr++9//aujQoRowYID++usvzZ07N2SL0rrw+Xw6//zzNWDAAP3+++967rnndMABB1RqZVpbffr0UfPmzXXTTTdp+fLl8ng8eumll5STk0O1HwAAABDFCP0AAAAABN12223q3LmzZs2apfvvv18ej0ctWrTQiSeeqB49ekhyw8Eff/xRb731ltavX6+srCx17dpV99xzT4WWhePHj9e4ceM0ceJE+Xw+DR8+POzQr3Pnznr88cd111136YEHHtCee+6pK664QsuXL9fy5cvDeuwA0zT18MMP66mnntJrr72md999V2lpaWrZsqXOPfdc7b333nV63Pbt2+vZZ5/Vvffeq0cffVSO46hr1666++67tf/++we322OPPTRjxgyNHz9ejz32mBo2bKgzzjhDe+yxh2666aZ6OcYdXXjhhfrwww/1zDPP6PLLL9e9996rcePG6bnnnpPjOOrTp48ef/zxKltrdu/eXR6PR6mpqerYsWNwfSD029kqvzFjxkiSUlJSlJOTo06dOmnChAkaOHCgkpOTQ+574oknas6cOXruuee0ZcsWNWnSRAMGDNDll18u0wzd6KZx48Z64YUX9PDDD+vdd9/V888/r4YNG6pdu3a69tprg9ulpaXpqaee0rhx4/TMM88oNTVVAwcO1KGHHqqhQ4dWeMxDDjlEI0eO1PTp0zVhwgR17txZU6dO1Z133rlT35Oa3HrrrZo7d64efPBB+Xw+HX/88br55pvr3J42KSlJkydP1tixY/XAAw+oSZMmOu+885SdnV3tXJcAAAAAIs9wmEEbAAAAQIy77LLLtHTpUr3zzjuRHgoS1JdffqkhQ4ZoxowZOvjggyM9HAAAAAAJiDn9AAAAAMSUbdu2VVj+448/9PHHH+uggw6K0IgAAAAAAIg82nsCAAAAiCn9+/fXKaecolatWmnlypWaNWuWkpKSKrVWBAAAAAAgkRD6AQAAAIgphxxyiN58802tW7dOycnJ6tatm6655hq1adMm0kMDAAAAACBimNMPAAAAAAAAAAAAiHHM6QcAAAAAAAAAAADEOEI/AAAAAAAAAAAAIMYxp18drVtXEOkhIIJM01CjRhnauLFItk2HXCDRcA0AEhvXACCxcQ0AEhvXACCxcQ0AEptpGsrNzYz0MEKi0g+oA9M0ZBiGTNOI9FAARADXACCxcQ0AEhvXACCxcQ0AEhvXACCxxcK5T+gHAAAAAAAAAAAAxDhCPwAAAAAAAAAAACDGEfoBAAAAAAAAAAAAMY7QDwAAAAAAAAAAAIhxhH4AAAAAAAAAAABAjCP0AwAAAAAAAAAAAGIcoR8AAAAAAAAAAAAQ4wj9AAAAAAAAAAAAgBhH6AcAAAAAAAAAAADEOEI/AAAAAAAAAAAAIMYR+gEAAAAAAAAAAAAxjtAPAAAAAAAAAAAAiHGEfgAAAAAAAAAAABHUt++B+vjjDyM9jBqVH+fq1avUt++BWrLkV0nSd999o759D1RBQYEk6a235urYYw+v0/MMHz5MDzxwb30MOaF4Iz0AAAAAAAAAAACAeHT77WP09ttvSJI8Ho+ysxuobdt26t//GB133ECZplub9dpr85SVlR3JodZKqHF26bK/XnttnjIzM8N+ngkT7pbXS4S1s/iOAQAAAAAAAAAA7CIHH9xbo0bdKtu2tXHjRn355Wd64IF79eGH7+uOO+6T1+tVbm7jSA+zVkKNMykpKezj8Pl8SkpKUnZ2g7AeJ1HR3hMAAAAAAAAAAGAXSU52w7AmTfZQXl5HDRlyge6441598cVnwSrA8m0zfT6f7rvvTp100jHq16+3Tj31BM2cOT3kc6xZ849uuWWkjj32cA0Y0E8jR16j1atXBe+3LEsPPXSfjj32cB133JGaMuUBjR8/WjfeOCK4zb//PVBz5jxX4XHPP/8sTZv2aHA5VBvSHdt7Bnz88Yc644xT1K9fb11zzXCtWfNP8L5p0x7V+eefpblzX9Vpp52ofv16S6rc3rOq5z322MP11ltzJZW1Gn3//Xd12WVD1a9fHw0dOkR//fWnFi/+WRdeeK6OOuoQjRhxhfLz80N+L2MZlX4AAAAAAAAAACAmrV5tqLDQ2C3PlZnpaM89nXp5rAMO+Jfateugjz76nwYOPLnCfS+8MEvz53+s2267Q02bNtOaNWu0du0/VT+QJL/frxEjLtd++3XRww8/IY/Ho6efnqYRIy7X00/PUlJSkmbNekZvvfWGbrzxVrVuvbdmzXpGH3/8oQ444MB6OZ7qbNu2TTNmPKmbbx4rrzdJ9957h8aMGaVHHnkyuM3KlX/rww//p9tvv0um6Qnr+Z588lFdccUINW3aTBMn3qaxY29Wenq6rrxyhFJTU3XrrTdq2rSpuvbaG8M9tKhE6AcAAAAAAAAAAGLO5s3S+eenybZ3z/OZpjRnTrEa1FPnydatW2vZsqWV1q9d+49atdpLXbt2k2EYatZsz5CP8/7778i2bY0ceYsMww1AR40arWOPPVzff/+tDjqop+bMeV7nnnu+DjusnyTp2mtv1FdffVE/BxKC3+/X1Vdfr/326yxJuvnmsTr77H9r0aKftO++7jqfz6ebbx6rnJycsJ/vzDPP0cEH95IknXbaGRoz5iY98MAj6tq1myTp+ONP0ttvzw37eaIVoR8AAAAAAAAAAPXgyy89OvBAS57wipVQSw0aSE89tXW3VvrVV+AnSY4jSZXHPmDAQF199X905pmnqmfPXurd+xAddFBPSdLdd0/QO++8Hdz23Xc/0dKlS7Ry5QodffShFR6ntLRUK1euUGFhoTZsWB8M2STJ6/UqL6+TpPqpXKyOx+NRp077Bpdbt26jzMws/fnnH8HxNGu2Z70EfpLUtm374NeNGuVKkvbZp125dY1o7wkAAAAAAAAAAKq3YYOhm29O0Z13blOPHrup9Azb223u2uBqV/nzz9/VvHnzSuvz8jrqhRde0xdffKZvvvlKt946UgceeJDGj79LQ4deojPPPLfC9lu3FqtDh44aPXp8pcdq2LD2YZphmHKcit9Lv99f6/3rKjU1rcZtDMOo1di83sqxV/l17uPE7/lJ6AcAAAAAAAAAQJh8Pve2tHT3VJ0htn377ddatmypBg8+q8r7MzIydeSRR+vII4/W4YcfqREjLteWLZuVk9NIOTmNKmzboUNHvf/+u8rJyVFGRmaVj5eb21iLFv2kbt16SHIDs19/Xay8vI7BbRo2bKgNG9YHl4uKCrV69cqwjtOyLP3yy6JgVd9ff/2hwsICtW7dZqcep2HDnApj+/vvv7Rt27awxhaPCP0AAAAAAAAAAAiTZbm3u2t+OcSO0lKfNmxYL9u2tXHjRn355WeaOfMp9e59iI499vhK28+a9YxycxurQ4eOMgxDH3zwnnJzc5WZmVXl4x999AA999xMjRw5QkOHXqImTfbQP/+s1scff6CzzhqiPfZoqtNOO0PPPPO0WrbcS61bt9GsWc+qsLCwwuMccMC/9Pbbc9Wnz6HKzMzSE09MlWmG16vW6/Xq/vvv1lVXXSePx6P7779L++3XpUKr0dro0eNAvfzyHHXu3EW2beuRRx6qsqov0fEdAQAAAAAAAAAgTIGwLxD+AQFffvmZTjrpWHk8HmVlZatdu/a66qprNWDACTJNs9L26ekZeu65GVqx4m+ZpqmOHffT3Xc/UOW2kpSamqqHH35MjzzykG666ToVFxerceMmOuCAg5SRkSFJOuOMc7RhwwbdfvtoGYap448/UYceeriKisqCv3PPPV+rV6/U9ddfpYyMTF100aVavXpVWMeempqqc845T2PH3qT169epa9duGjny1p1+nMsvv1oTJozVf/5zkXJzm+jKK0fo118XhzW2eGQ4OzZBjSGPPfaY7r33Xg0ZMkQ33XSTJKmkpER33HGH3nrrLZWWlqpv374aPXq0GjduHNxv1apVGjNmjL788kulp6fr5JNP1ogRI3YqFV63rqDejwexw+s1lZOTofz8Ivn9fHQHSDRcA4DExjUASGxcA4DExjUASGw1XQP++MPQRRel6aabSnT44SR/iH633z5GhYUFmjjx3kgPJSYErgHRrOpYOAYsXLhQs2bNUl5eXoX1EyZM0AcffKBJkyZp5syZWrt2rYYPHx6837IsXXzxxfL5fJo1a5buuOMOvfLKK3rwwQd39yEAAAAAAAAAAOJEoNKP9p4AIiUmQ7+ioiJdd911Gj9+vBo0aBBcX1BQoJdeekkjR45Ur1691LlzZ02YMEHff/+9FixYIEmaP3++li5dqrvvvludOnXSYYcdpiuvvFLPPvusSktLI3REAAAAAAAAAIBYFuipR+gHIFJick6/2267TYcddph69+6tRx55JLj+p59+ks/nU+/evYPr2rZtq+bNm2vBggXq1q2bFixYoA4dOlRo99m3b1+NGTNGS5cu1b777lurMZimIdM06u+gEFM8HrPCLYDEwjUASGxcA4DExjUASGxcA4DEVvM1wJBhSJIprzdmZ9VCAhk9+rZIDyGmxMLrf8yFfm+++aYWLVqkF198sdJ969evV1JSkrKzsyusz83N1bp164LblA/8JAWXA9vURqNGGTIMQr9El52dFukhAIggrgFAYuMaACQ2rgFAYuMaACS26q4BmZmSxyOlpXmUk7ObBwUAirHQb/Xq1br99tv15JNPKiUlJaJj2bixiEq/BObxmMrOTtOWLVtlWdTrA4mGawCQ2LgGAImNawCQ2LgGAImtpmvApk2GLCtFW7b4lJ9vRWCEAHalwDUgmsVU6Pfzzz9rw4YNGjRoUHCdZVn6+uuv9eyzz2ratGny+XzasmVLhWq/DRs2qEmTJpLcqr6FCxdWeNz169dLUnCb2rBtR7ZNiXaisyxbfj+/5AOJimsAkNi4BgCJjWsAkNi4BgCJrbprQGmpKceRSksdrhEAIiKmQr+ePXtq7ty5FdbdeOON2meffXTRRRdpzz33VFJSkj7//HMdc8wxkqTly5dr1apV6tatmySpW7dumjp1qjZs2KDc3FxJ0meffabMzEy1a9dutx4PAAAAAAAAACA+2HbFWwDY3WIq9MvMzFSHDh0qrEtPT1fDhg2D60899VTdcccdatCggTIzMzV+/Hh17949GPr17dtX7dq10/XXX6/rrrtO69at06RJk3T22WcrOTl5dx8SAAAAAAAAACAOWNs7ehL6AYiUmAr9amPUqFEyTVNXXHGFSktL1bdvX40ePTp4v8fj0dSpUzVmzBidfvrpSktL0ymnnKIrrrgigqMGAAAAAAAAAMSyQNjn90d2HAASV8yHfjNnzqywnJKSotGjR1cI+nbUokULPf7447t6aAAAAAAAAACABBEI/RwnsuNAfPv3vwdq8OAzNXjwWbXa/rvvvtEVV1yit9/+QFlZWbt4dIi0mA/9AAAAAAAAAACINNs2JEmWZUR4JIgGffseGPL+//u/i3ThhRfv9OM+/vgMpaWl1Xr7Ll3212uvzVNmZuZOP9fOCISLmZlZeu21eUpJSQnet3jxz7roovMkSfPnf7NLx5HoCP0AAAAAAAAAAAhToNIvMLcfEttrr80Lfv3+++9q2rSpeu65l4Lr0tLSg187jiPLsuT11hzZ5OTk7NQ4kpKSlJvbeKf2CUd6ero+/vgDHXXUscF1b7zxmpo2baY1a/7ZbeNIVGakBwAAAAAAAAAAQKwLhH2B8A+7h2fpkhr/VeDz1bi9+cfvFffZurXy49QgN7dx8F9mZqYMwwgu//nnHzr66EP1+eef6oILztERR/TSwoULtHLlCo0ceY0GDjxaRx11iIYOHaKvv/6ywuP++98DNWfOc8Hlvn0P1Ny5r+rGG6/VkUf20RlnnKL58z8K3v/dd9+ob98DVVBQIEl66625OvbYw/Xll5/r7LP/raOOOkTXXHO51q9fH9zH7/dr0qS7deyxh+u4447UlCkPavz40brxxhE1HveAASfozTdfDy6XlGzT+++/owEDTqi07Q8/LNBllw1Vv359NGjQ8Zo06W5t3bo1eP+8eW/qwgvP1VFHHaoTTzxGY8bcpPz8jZWO7ZtvvtKFF56rI4/so0suuUB//fVHjeOMV1T6AQAAAAAAAAAQpkDoR6Xf7pUx5qbQGxiGtsycXba4eXON+9iNm6hw0sPBZc9ffypj3K3a8sycsMa6o6lTJ2v48CvVvHlLZWVlac2aNerZs4+GDbtMSUnJmjfvTd1wwzV67rmX1KxZs2ofZ/r0x3XppZfrP/+5Ui++OFtjx96il16aq+zsBlVuv23bNj3//EzdcsttMgxT48bdoocfnqTRo8dLkp599mm988483XjjaLVps7deeOF5ffLJh+rRI3TLUkk65pjj9PzzM/XPP/+oWbNm+vDD/6lZs+bq0KFjhe1Wrlyha6+9XBdddKluvPFWbdqUr/vvv0v333+XRo0aLckNH4cOvUR77dVa+fn5mjz5ft1++xjdc8+DFR7rscemaPjwq9SwYY7uuWeiJk68TY888mSNY41HVPoBAAAAAAAAABCmQIUflX6oraFDL9a//tVTLVq0VHZ2A7Vv30Enn3yq9tmnnVq12ksXXXSpWrRooU8//Sjk4wwYcIKOOupYtWzZShdf/B9t3VqsRYt+rnZ7v9+v664bpY4d91VeXkcNGjRY3377dfD+l16ao3POOV+HHXaEWrduo6uvvl6ZmVm1OqacnEY6+ODeevvtuZKkN998Xccff2Kl7WbOnK6jjjpWgwefpVat9lKXLvvryiuv07x5b6qkpESSdMIJJ6lXrz5q0aKlOnfuoquuulZffPGZiouLKzzWsGGXqXv3A7T33vvonHPO048/Lgw+RqKh0g8AAAAAAAAAgDAxp19kFI25fae2dxo0qHEfZ4e59ay9Wu/089RGx477VlguLi7Wk08+ps8/n68NG9bLsiyVlJTUOBde27btg1+npaUpIyOjQhvMHaWmpqpFi5bB5dzcxsHtCwsLtXHjBu27737B+z0ej/LyOslxapdoH3/8iXrggXt19NED9NNPP2rcuDv0ww8LKmyzdOkSLVu2RO++Wzb3oeM4sm1bq1evUps2e+uXXxbryScf09Klv6mgoCD4/GvW/KO9996nyuMPzF+Yn58fsjoyXhH6AQAAAAAAAAAQJir9IsNq177mjcpLStr5fdLSdn6fWkhNTauw/PDDk/T111/qP/+5Si1btlJKSopuvvkG+Xz+kI/j3SGkNAxDjuPU2/Y7q2fP3rr77tt1xx3j1KfPIWrQoGGlbbZuLdZJJw3Sv/99RqX7mjZtpq1bt2rEiOE66KBeGj16vBo2zNGaNf/ommuGy+/3VXs8hmFIUq0DynhD6AcAAAAAAAAAQJjKKv2MyA4EMevHH3/QcccN1GGHHSHJrfz7559Vkg7YbWPIzMxUo0a5Wrx4kbp16yFJsixLv/32i9q371Crx/B6vTrmmOP13HMzKs2/F9ChQ0f9/vvvatmyVZX3L1u2VJs3b9YllwxX06Zuxd4vvyyqwxElFub0AwAAAAAAAAAgTIGwj0o/1FXLlnvpo4/+pyVLftWSJb9p7NibZNv1V4FXW6eeOljPPDNdn3zyof766w898MA9KijYIqn2gfZFF12qN954Twcf3KvK+88++zz99NMPuu++O7Vkya/6+++/9MknH+q+++6U5Fb7JSUl6aWXZmvlyhWaP/8jPfXUE+EeWtyj0g8AAAAAAAAAgDDR3hPhuvzyqzVx4m265JIL1KBBQ5199nkqKira7eM4++zztHHjBo0fP1qm6dGJJ56igw7qJdOsfR1ZUlKSGjZsWO397dq11+TJj+mxx6bosssukuSoefOWOvLIoyRJOTk5GjVqtB57bIpefHG2OnToqP/85yqNHHlNmEcX3wynPhu1JpB16woiPQREkNdrKicnQ/n5RfL7eRUHEg3XACCxcQ0AEhvXACCxcQ0AEltN14DXXvNq8uRkHXOMX9deWxqBEQK7hm3bOvvsf6tfv6N00UWXRno4ERO4BkQzKv0AAAAAAAAAAAhT2Zx+kR0HEK5//lmtr776Qt269ZDP59NLL83W6tWrdNRRx0Z6aKgBoR8AAAAAAAAAAGEKhH301kOsMwxDb789Vw8/PEmOI+2zT1tNmjRFbdrsHemhoQaEfgAAAAAAAAAAhCkQ+lHph1jXtGkzPfLIk5EeBuqg9rMuAgAAAAAAAACAKgUq/Aj9AEQKoR8AAAAAAAAAAGEKzOln20ZkBwIgYRH6AQAAAAAAAAAQJssytt9GeCAAEhahHwAAAAAAAAAAYSqr9IvsOAAkLkI/AAAAAAAAAADCFKjwo9IPQKQQ+gEAAAAAAAAAECbHcW+p9AMQKYR+AAAAAAAAAACEKRD2UekHIFII/QAAAAAAAAAACFMg7KPSD0CkEPoBAAAAAAAAABCmstDPiOxAACQsQj8AAAAAAAAAAMIUCPv8/ggPBEDCIvQDAAAAAAAAACBMgbaetPcEECmEfgAAAAAAAAAAhCkQ9jlOZMcBIHER+gEAAAAAAAAAEKbAnH609wQQKYR+AAAAAAAAAACEifaeACKN0A8AAAAAAAAAgDAFwr5AxR8A7G6EfgAAAAAAAAAAhKms0s+I7EAAJCxCPwAAAAAAAAAAwkR7TwCRRugHAAAAAAAAAECYLMvYfhvhgQBIWIR+AAAAAAAAAACEKRD2EfoBiBRCPwAAAAAAAAAAwuQ47i3tPQFECqEfAAAAAAAAAABhClT4EfoBiBRCPwAAAAAAAAAAwhQI+2jvCSBSCP0AAAAAAAAAAAhTWehnRHYgABIWoR8AAAAAAAAAAGGivSeASCP0AwAAAAAAAAAgTI7j3hL6AYgUQj8AAAAAAAAAAMIUaOtp22UBIADsToR+AAAAAAAAAACEybYlc/s77oR+ACKB0A8AAAAAAAAAgDBZluT1ul/7/ZEdC4DEROgHAAAAAAAAAECYbFtKSnKCXwPA7kboBwAAAAAAAABAmNzQr+xrANjdCP0AAAAAAAAAAAiTbZe197SsyI4FQGIi9AMAAAAAAAAAIEyWRXtPAJFF6AcAAAAAAAAAQJjKt/ek0g9AJBD6AQAAAAAAAAAQJts2yoV+RmQHAyAhEfoBAAAAAAAAABCm8nP60d4TQCQQ+gEAAAAAAAAAECbblpKTmdMPQOQQ+gEAAAAAAAAAECbLKqv0Y04/AJFA6AcAAAAAAAAAQJgsS+Xm9IvsWHaFH34wNXJkSqSHASAEQj8AAAAAAAAAAMLkOPE9p9/y5aa+/94T6WEACIHQDwAAAAAAAACAMFlWfM/p5/e7x+U4kR4JgOoQ+gEAAAAAAAAAECbbljzbC+Esy4jsYHaBQMtSQj8gehH6AQAAAAAAAAAQJssylJzsfh2PlX6BINPvj/BAAFSL0A8AAAAAAAAAgDCVn9MvUBUXTwJhXzweGxAvCP0AAAAAAAAAAAiTbUtJSfE7p18g7CP0A6IXoR8AAAAAAAAAAGFwnEDo5y7Hc+gXj8cGxAtCPwAAAAAAAAAAwuC4BX7B0C8eq+Fo7wlEP0I/AAAAAAAAAADCEAjCAu094zEY8/uNCrcAog+hHwAAAAAAAAAAYQiEfF5vYDn+gjHaewLRj9APAAAAAAAAAIAwBIKwQHvPQLvPeEJ7TyD6EfoBAAAAAAAAABCGHUO/eAzGAscUj8cGxAtCPwAAAAAAAAAAwhAI/bze+J3Tj9APiH6EfgAAAAAAAAAAhCEQhAUq/eJx3jvaewLRj9APAAAAAAAAAIAw2LYhKd7bexoVbgFEH0I/AAAAAAAAAADCsOOcfvFY6Ud7TyD6EfoBAAAAAAAAABCGstDPqbAcTwj9gOgXU6Hfc889p4EDB6pHjx7q0aOHTj/9dH300UfB+0tKSjR27FgdfPDB6t69uy6//HKtX7++wmOsWrVKw4YN0/77769evXrpzjvvlD/QjBgAAAAAAAAAgJ0UCPk8HvfW74+/FpiBt9HjMdAE4kVMhX7NmjXTtddeq5dfflkvvfSSevbsqf/85z9asmSJJGnChAn64IMPNGnSJM2cOVNr167V8OHDg/tblqWLL75YPp9Ps2bN0h133KFXXnlFDz74YKQOCQAAAAAAAAAQ4wLVbx6P+89xIjueXSFwjNTQANHLG+kB7Ix+/fpVWL766qv1/PPPa8GCBWrWrJleeukl3XPPPerVq5ckNwQ87rjjtGDBAnXr1k3z58/X0qVLNX36dDVu3FidOnXSlVdeqXvuuUfDhw9XcnJyrcdimoZMM/4+rYHa8XjMCrcAEgvXACCxcQ0AEhvXACCxcQ0AEluoa4BhGDIMKSnJ3B76GfJ64+taYdvuMRqGKW9MJQtA/YiF1/+YPTUty9K8efNUXFys7t2766effpLP51Pv3r2D27Rt21bNmzcPhn4LFixQhw4d1Lhx4+A2ffv21ZgxY7R06VLtu+++tX7+Ro0yZBiEfokuOzst0kMAEEFcA4DExjUASGxcA4DExjUASGxVXQM2bnQr/Bo2TFNKipSW5lFOTgQGtwsFqhgzMtLi7tiAeBFzod+vv/6qM844QyUlJUpPT9fDDz+sdu3aafHixUpKSlJ2dnaF7XNzc7Vu3TpJ0vr16ysEfpKCy4FtamvjxiIq/RKYx2MqOztNW7ZslWXRxBpINFwDgMTGNQBIbFwDgMTGNQBIbKGuARs3GrKsFBUWlsi2U1RQ4FN+vhWhke4axcUpsixDmzaVKj+fayAST+AaEM1iLvTbe++99eqrr6qgoED//e9/dcMNN+iZZ57Z7eOwbUe2HYeNmbFTLMuW388LHJCouAYAiY1rAJDYuAYAiY1rAJDYqroG+HymHEdyHEem6ai01Im764TP58hxDJWUxN+xAfEi5kK/5ORktW7dWpLUuXNn/fjjj5oxY4YGDBggn8+nLVu2VKj227Bhg5o0aSLJrepbuHBhhcdbv369JAW3AQAAAAAAAABgZ9jbMzCPx5Fpli3HE7/fvbXiq4ARiCvRP+tgDWzbVmlpqTp37qykpCR9/vnnwfuWL1+uVatWqVu3bpKkbt266bffftOGDRuC23z22WfKzMxUu3btdvfQAQAAAAAAAABxIBCEGYa2h37xNzVUIMiMx0ATiBcxVel377336tBDD9Wee+6poqIivfHGG/rqq680bdo0ZWVl6dRTT9Udd9yhBg0aKDMzU+PHj1f37t2DoV/fvn3Vrl07XX/99bruuuu0bt06TZo0SWeffbaSk5Mje3AAAAAAAAAAgJhUVunn/ovHaji/3w0y4/HYgHgRU6Hfhg0bdMMNN2jt2rXKyspSXl6epk2bpj59+kiSRo0aJdM0dcUVV6i0tFR9+/bV6NGjg/t7PB5NnTpVY8aM0emnn660tDSdcsopuuKKKyJ1SAAAAAAAAACAGJcYoZ97G4/HBsSLmAr9JkyYEPL+lJQUjR49ukLQt6MWLVro8ccfr++hAQAAAAAAAAASVCD0M03JNJ24bIEZCPsCFX8Aok/Mz+kHAAAAAAAAAEAkBQIxN/SLz3nvAscYj8cGxAtCPwAAAAAAAAAAwlA+9KO9J4BIIfQDAAAAAAAAACAMtu22vIzn0M+yjO23ER4IgGoR+gEAAAAAAAAAEAbHcW89Hmd7e8/4m/cuEPYR+gHRi9APAAAAAAAAAIAwxPucfrZdFmwS+gHRi9APAAAAAAAAAIAwBEK+eG3vGZjPTypr8wkg+hD6AQAAAAAAAAAQhkDI5/HEZ6VfxdAvcuMAEBqhHwAAAAAAAAAAYQi0vjRNyet14i4YKx9ixtuxAfGE0A8AAAAAAAAAgDCUb+9pGPFd6RdvxwbEE0I/AAAAAAAAAADCsGN7z3irhvP7jXJfR3AgAEIi9AMAAAAAAAAAIAyW5YZibntPybaNGvaILeVDTCr9gOhF6AcAAAAAAAAAQBhs223raRjxWelX/ngCASeA6EPoBwAAAAAAAABAGGzbDfsk5vQDEDmEfgAAAAAAAAAAhKF86Oe294zseOpboNLPMJjTD4hmhH4AAAAAAAAAAITBsiTTdCS5t/EWjAVCv+RkJ+5alwLxhNAPAAAAAAAAAIAwlK/083jir9LP73fn8UtOjr9jA+IJoR8AAAAAAAAAAGGwbbetp+SGf44T2fHUt7JKP1HpB0QxQj8AAAAAAAAAAMJg2+58d5Ib+gUq4+JFxfae8XVsQDwh9AMAAAAAAAAAIAy2bcR5e0/3NiVFcTdfIRBPCP0AAAAAAAAAAAiDZblhn+TexlsLzEDQx5x+QHQj9AMAAAAAAAAAIAyWpWCln2nGXzAWaOmZkuLEXaAJxBNCPwAAAAAAAAAAwmDbZZV+punEYejn3iYlxV8VIxBPCP0AAAAAAAAAAAiDbUuG4UiivSeAyCH0AwAAAAAAAAAgDLZd1t4zHkO/wPGkpjry+43IDgZAtQj9AAAAAAAAAAAIQ8X2nvFXDUd7TyA2EPoBAAAAAAAAABAGy9ox9IuvarhAdV9yMqEfEM0I/QAAAAAAAAAACINtG3Hf3tPjcf/FWxUjEE8I/QAAAAAAAAAACEP5Of1MMz5DP9OUvF4n7o4NiCeEfgAAAAAAAAAAhKF86OfxOHFXDef3u4FfPFYxAvGE0A8AAAAAAAAAgDBUntMvsuOpb5Yleb3x2boUiCeEfgAAAAAAAAAAhMFtf+lIis9gLBBquoGmEenhAKgGoR8AAAAAAAAAAGFwnIpz+sVbpZ/fb1DpB8QAQj8AAAAAAAAAAMJQcU4/ybLiqxrO73ePy+t15PdHejQAqkPoBwAAAAAAAABAGNz2nu7XHk/8Vfq57T2duKxiBOIJoR8AAAAAAAAAAGGwbUMej/u1YcRfMOb3S16vG2zS3hOIXoR+AAAAAAAAAACEwa2Ec7/2eh05TnwFf4HjY04/ILoR+gEAAAAAAAAAEAbHcSv8pLI2n/EV+hnb5/SLv/kKgXhC6AcAAAAAAAAAQBhsu6zSLxD6xVNFXKDSj/aeQHQj9AMAAAAAAAAAIAyWJZmmI6ks/IuncMyd08+Rx+MGnI4T6REBqAqhHwAAAAAAAAAAYXBDP/fr+GzvGZjTz0374unYgHhC6AcAAAAAAAAAQBgcp6zCL3AbT8FYWehXtgwg+hD6AQAAAAAAAAAQBsuSDMP9Oh6DMb/fkNdbdmx+f2THA6BqhH4AAAAAAAAAAITBto1gIBYI/yzLiNyA6tmOlX7xVMUIxBNCPwAAAAAAAAAAwlB+Tr94nPfOslSh0i+eqhiBeELoBwAAAAAAAABAGGw7vuf08/slr9ch9AOiHKEfAAAAAAAAAABhcJzylX7ubTwFY4H2nqbpbF+On9alQDwh9AMAAAAAAAAAIAxue083EAuEf/FV6efOWej1usvxFGgC8YTQDwAAAAAAAACAMNh2WdgXuI2nYMxt7xmfrUuBeELoBwAAAAAAAABAGALtL6X4DMbK2nuWLQOIPoR+AAAAAAAAAACEoapKv/gL/Zy4nK8QiCeEfgAAAAAAAAAAhMG2jWDY5/G4c/tZlhHBEdWvHdt7EvoB0YnQDwAAAAAAAACAMFhWfM/pF2jv6fXGX6AJxBNCPwAAAAAAAAAAwlBVe8/4Cv0M5vQDYgChHwAAAAAAAAAAYbDtsiq4QAtMx4nggOoZ7T2B2EDoBwAAAAAAAABAGMpX+sVjMOa293SCx2jbkR0PgKoR+gEAAAAAAAAAEAbblozt09zFYwvMsjn93GW/P7LjAVA1Qj8AAAAAAAAAAMIQCMUkxWU1nGW5gV88BppAPCH0AwAAAAAAAAAgDBXbe7qT+VmWEcER1S+/39hhTr/4OTYgnhD6AQAAAAAAAAAQBssygoFY4DbeKv08nrJAM56ODYgnhH4AAAAAAAAAAIShfKVfvLX3tG33nxv6ueto7wlEJ0I/AAAAAAAAAADCYNuSsb3jZSD08/sjN576FAj4vF4nGPrFy7EB8YbQDwAAAAAAAACAOgpU9O3Y3tNxIjOe+hYI+MpX+sVLFSMQb7x13XHBggWaN2+eVq9erZKSkgr3GYahRx55JOzBAQAAAAAAAAAQzQIBmGk622/d5XhpgRk4Dtp7AtGvTqHf008/rYkTJyo3N1etWrVSUlJSfY8LAAAAAAAAAICot2Oln3f7u+7xEoyVtfcsH2gakRsQgGrVKfR78skndc4552jUqFEyTTqEAgAAAAAAAAASUyAUC7xVHpjbz7bjIxgrX+lnmu6/eAk0gXhTp8Ru69atOvLIIwn8AAAAAAAAAAAJray9p3trGPEVjPn9bnjp8ZS1L2VOPyA61Sm1GzBggD7++OP6HgsAAAAAAAAAADFlx/aeUnwFY+Xbe0pu+BcvgSYQb+rU3vOmm27STTfdpBEjRqhXr17Kzs6utM3RRx8d9uAAAAAAAAAAAIhmO1b6Bb6Ot9AvEGp6PPFTxQjEmzqFfsuXL9d3332nlStX6s0336x0v2EYWrx4cdiDAwAAAAAAAAAgmu04p58UX9Vwfr97S+gHRL86hX6jRo1Senq6pk6dqjZt2igpKam+x1WlRx99VO+8846WL1+u1NRUde/eXddee6322Wef4DYlJSW644479NZbb6m0tFR9+/bV6NGj1bhx4+A2q1at0pgxY/Tll18qPT1dJ598skaMGCGvt07fDgAAAAAAAABAgrIsd867iqFf/ARjldt7xs+xAfGmTinXsmXL9NBDD+nQQw+t7/GE9NVXX+nss89Wly5dZFmW7rvvPl144YV68803lZ6eLkmaMGGCPvroI02aNElZWVkaN26chg8frlmzZkmSLMvSxRdfrMaNG2vWrFlau3atbrjhBiUlJemaa67ZrccDAAAAAAAAAIhtZe09neC6eGrv6fe7oabX6x6fG/oZkRwSgGrUKfTr1KmTNmzYUN9jqdG0adMqLN9xxx3q1auXfv75Z/3rX/9SQUGBXnrpJd1zzz3q1auXJDcEPO6447RgwQJ169ZN8+fP19KlSzV9+nQ1btxYnTp10pVXXql77rlHw4cPV3Jycq3GYpqGTJMLW6LyeMwKtwASC9cAILFxDQASG9cAILFxDQASW3XXANM0ZBhScrJZrhrOkGTK642H64V7fCkpprxeZ/sxGnFybEDtxcLrf51Cv9GjR2vkyJFq0qSJevbsGbG2mAUFBZKkBg0aSJJ++ukn+Xw+9e7dO7hN27Zt1bx582Dot2DBAnXo0KFCu8++fftqzJgxWrp0qfbdd99aPXejRhkyDEK/RJednRbpIQCIIK4BQGLjGgAkNq4BQGLjGgAkth2vAYWFbvVbTk6acnLcdampUmqqRzk5KREYYf1KT3ePr1GjdOXkuMeWkuKNi2MD4k2d0rqzzjpLfr9fF110kUzTVEpKxZPbMAx9++239TLA6ti2rQkTJqhHjx7q0KGDJGn9+vVKSkpSdnZ2hW1zc3O1bt264DblAz9JweXANrWxcWMRlX4JzOMxlZ2dpi1btsqy4qROH0CtcQ0AEhvXACCxcQ0AEhvXACCxVXcNyM83ZFkpKiwsVX6+u962U1RQYCk/3x+p4dab/HxTlpWswsIS5ec7cXVswM4IXAOiWZ1CvwsuuCDiVW5jx47VkiVL9Nxzz0Xk+W3bkW07NW+IuGZZtvx+fskHEhXXACCxcQ0AEhvXACCxcQ0AEtuO14CSEkOOIzlO2XrDkHw+Jy6uFSUlkuNIki2/35FhOCotjY9jA+JNnUK/yy+/vL7HsVNuu+02ffjhh3rmmWfUrFmz4PrGjRvL5/Npy5YtFar9NmzYoCZNmgS3WbhwYYXHW79+vSQFtwEAAAAAAAAAoDbs7dmXWW66L9N0gutjnWW5BUAej4K3lhXBAQGoVvTPOliO4zi67bbb9O677+rpp59Wq1atKtzfuXNnJSUl6fPPPw+uW758uVatWqVu3bpJkrp166bffvtNGzZsCG7z2WefKTMzU+3atdstxwEAAAAAAAAAiA/O9oZw5UO/eArGAsfh9boHapqSbTP1FRCN6lTpN2TIkBq3mTFjRl0eOqSxY8fqjTfe0JQpU5SRkRGcgy8rK0upqanKysrSqaeeqjvuuEMNGjRQZmamxo8fr+7duwdDv759+6pdu3a6/vrrdd1112ndunWaNGmSzj77bCUnJ9f7mAEAAAAAAAAA8ausEq5sOig3GIvUiOqXf/vUfVT6AdGvTqFfZmZmpTn9tmzZop9//lnZ2dnq3LlzvQxuR88//7wk6dxzz62wfuLEiRo0aJAkadSoUTJNU1dccYVKS0vVt29fjR49Oritx+PR1KlTNWbMGJ1++ulKS0vTKaecoiuuuGKXjBkAAAAAAAAAEL8CAVj5Sj+vtywMjHWB4wuEfu6xRW48AKpXp9BvypQpVa7fuHGjLrvsMh133HFhDao6v/76a43bpKSkaPTo0RWCvh21aNFCjz/+eH0ODQAAAAAAAACQgKqa088w4qfSr6y9p3vr8TjB6j8A0aVe5/Rr1KiRhg4dqgceeKA+HxYAAAAAAAAAgKhUVehnmvFTDef3B9qXusvx1LoUiDf1GvpJkmVZwbn2AAAAAAAAAACIZ1WFfl5v/ARjluUeW+D4mNMPiF51au/5888/V1rn8/m0bNkyPfzww+ratWvYAwMAAAAAAAAAINrt2P5SkkzTiZtgzLLKqvykQOgXH/MVAvGmTqHfqaeeKsOoeFI7jiNJ2n///TVu3LjwRwYAAAAAAAAAQJQLVPSVf8s8nlpg+v3uPH4BVPoB0atOod+MGTMqrUtJSVGzZs3UtGnTsAcFAAAAAAAAAEAsqKq9p8cTX6Ff+SpGj0fy+SI3HgDVq1Pod9BBB9X3OAAAAAAAAAAAiDm27Zb4la+GM03J74+PFpiV23s62rYtPo4NiDe1Dv02bdqk7OxsmaapTZs21bh9w4YNwxgWAAAAAAAAAADRL94r/SzLqGJOv8iNB0D1ah369erVS7Nnz1bXrl3Vs2fPSnP67Wjx4sVhDw4AAAAAAAAAgGgWCMDKB2PxNqdf+fae8XRsQLypdeg3YcIEtWrVSpI0ceLEXTYgAAAAAAAAAABiRSD0K18nY5rxM++d296zrHWp1xs/rUuBeFPr0O+UU06RJPn9fnXo0EF77rmnGjVqtMsGBgAAAAAAAABAtKu6vaejkpL4CMYqz+lHe08gWpk1b7LDDqap008/Xb/88suuGA8AAAAAAAAAADEjEPrFazC2Y3vPeDo2IN7UKfRr2bKlNm/evCvGAwAAAAAAAABAzKgu9IuXee8sy9hhvkInbo4NiDc7HfpJ0iWXXKIpU6ZozZo19T0eAAAAAAAAAABiRlXtPQ0jnkK/+K1iBOJNref0K2/evHnKz89X//79lZeXp8aNG1e43zAMPfLII/UyQAAAAAAAAAAAopVluXP3VZzTr2x9rKuqvaffH7nxAKhenUK/oqIi7b333hWWAQAAAAAAAABINLZdMfCT4qsazrIkr9cJLsdT61Ig3tQp9Js5c2Z9jwMAAAAAAAAAgJhTVehnmvEV+lWc0y9+qhiBeFOnOf0AAAAAAAAAAED1oZ/jVL19rPH7Deb0A2JEnSr9JGnJkiWaOnWqFi5cqHXr1qlJkybaf//9NWzYMHXo0KE+xwgAAAAAAAAAQFRyK+EqJnwejxM3wdiOc/p5vfFzbEC8qVPo9+GHH2r48OFq1qyZ+vfvr9zcXG3YsEHvvfeeBg0apMmTJ+vwww+v56ECAAAAAAAAABBdLCv+23smJ5ctx9OxAfGmTqHfXXfdpUMOOUQPP/ywzHJXs+uvv16XXXaZ7rrrLkI/AAAAAAAAAEDcc5zKoZ/H47b9jAd+v5SWVlbJSHtPIHrVaU6/FStW6Mwzz6wQ+EmSaZo666yztGLFinoZHAAAAAAAAAAA0ay6Of1s24jMgOqZZVVs70noB0SvOoV+eXl51QZ7K1asUPv27cMaFAAAAAAAAAAAscCyDHk8FdfFUzDmzllYtuweW3wEmkC8qVN7z1tvvVXXXHON0tLS1L9/f2VlZamgoEDvvvuupk+frnvvvbe+xwkAAAAAAAAAQNSpvtIvMuOpb26oWbG9Z7wcGxBvah36de/eXYZRlt77fD6NGjVKo0aNktfrld/vdx/Q69X555+v7777rv5HCwAAAAAAAABAFNmxEk6Kr0o/v79ye0/bducyNCj4A6JKrUO/Cy64oELoBwAAAAAAAABAonMcyTSdCus8HiduquEsq2IlY6Dqz7Yrh50AIqvWod/ll1++K8cBAAAAAAAAAEDMqaq9p2HETwtMy5K83ortPQPrCf2A6GLWvAkAAAAAAAAAAKjKjpVwktsOM17bewaOdfuMXwCiSK0r/S655BKNHDlSbdq00SWXXBJyW8Mw9Mgjj4Q9OAAAAAAAAAAAollVoZ9pSpYVH9NlWZZRoaIvEADGSyUjEE9qHfoVFRXJ2v7RhKKiol02IAAAAAAAAAAAYoVtG5XaXJpm/IRibnvPsuXy7T0BRJdah34zZ86s8msAAAAAAAAAABKVbbtz+JXn8cRP6Oe29yyb0y9Q1UjoB0Qf5vQDAAAAAAAAAKCObFvVVvo5TtX7xJId25d6PM729fHRvhSIJ7Wu9Js+fXqtH9QwDJ1//vl1GQ8AAAAAAAAAADHDsiqHfoFgrKpAMNa4lX5ly7T3BKJXrUO/O++8s9YPSugHAAAAAAAAAEgEti2ZZsWSvvLBWOyHfhXnLAwEgIR+QPSpdej3yy+/7MpxAAAAAAAAAAAQc6pr7ynFRzBm2xUr/QLzF8bDsQHxhjn9AAAAAAAAAACoI9suC8ICAqGfbe/+8dQnx6lcrUh7TyB61brS7+eff1bbtm2Vmpqqn3/+ucbt99tvv7AGBgAAAAAAAABAtHPbe1ZcFwjGYj30CwR7gTkK3a/d21g/NiAe1Tr0O/XUUzVnzhx17dpVp556qowdP7qwneM4MgxDixcvrrdBAgAAAAAAAAAQjSzLiNv2noHxl2/v6fW6AaDfb0hyKu8EIGJqHfrNmDFDbdu2DX4NAAAAAAAAAECis6z4rfTz+93b8qFmvASaQDyqdeh30EEHVfk1AAAAAAAAAACJynEqh36m6VbAWVZsV8OVtfcsW8ecfkD0MmveBAAAAAAAAAAAVCWeK/2qau8ZL8cGxKNaV/qV17Fjx2rn9AtgTj8AAAAAAAAAQLyzbcnjqVjNFwgBYz0Yc+ftq3h8VPoB0atOod/IkSMrhX5btmzRp59+qrVr12rIkCH1MjgAAAAAAAAAAKKZG/pVXBcvwVioSr9YPzYgHtUp9Dv//POrXH/55Zfr+uuv1+bNm8MZEwAAAAAAAAAAMaGq9p6B5VgPxvx+97Zi6Fd+vkIA0aTe5/Q78cQTNXv27Pp+WAAAAAAAAAAAoo7jSDvOhhVvoV/5UJM5/YDoVe+h3++//y6bsx0AAAAAAAAAkAAsy6i2vafjVN4+lgTe6qe9JxAb6tTec/r06ZXW+Xw+LVu2TPPmzdMJJ5wQ9sAAAAAAAAAAAIh2tl25vWfFFpixm/z5/W4Jo9dbdgyBYw1UAQKIHnUK/e68885K65KTk9WsWTMNGTJEl112WdgDAwAAAAAAAAAg2lmWKlX6xXN7z0DVHw3/gOhTp9Dvl19+qe9xAAAAAAAAAAAQc6qq9Assx3owFggtae8JxIZ6n9MPAAAAAAAAAIBEYduSYVRcFy/BWGD85SsZy6oYjco7AIioOlX6vfrqqzu1/cknn1yXpwEAAAAAAAAAIKrZdsU576SykCzWK/0C7T3LV/oZhhv8xXqgCcSjOoV+I0eOlLH9owuOU3Yxq24doR8AAAAAAAAAIB5ZVjy393Tf899xzkKPh9APiEZ1Cv1efPFFXXnllTrppJN0zDHHqHHjxlq/fr3mzZun119/XZMmTVKbNm3qeagAAAAAAAAAAESXUHP6BSrlYlVZe88dKxkdQj8gCtUp9Lv33nt1+umna9iwYcF1ubm5ysvLU2pqqu655x49/fTT9TZIAAAAAAAAAACikW0blUK/svaesT3vXSDY8+6QJNDeE4hOZs2bVPb9999rv/32q/K+/fbbTz/88ENYgwIAAAAAAAAAIBZUXennVsY5ThU7xJBApSLtPYHYUKfQr1GjRnrrrbeqvO/NN99Uo0aNwhoUAAAAAAAAAACxwLYrh2KByrh4ae+5Y6WfxxP78xUC8ahO7T0vueQS3Xrrrfrrr7/Uv39/5ebmasOGDXrvvff09ddf67bbbqvvcQIAAAAAAAAAEHUsq3Kln7G9q2esB2OB0LKq0M/vj+3WpUA8qlPoN3jwYDVp0kRTp07V3XffLb/fL6/Xq3333VdTpkxRv3796nucAAAAAAAAAABEHTf0q9jHMxACxnoLzECwZ+yQ79HeE4hOdQr9JOmII47QEUccIdu2tXHjRjVq1Ejmjh9nAAAAAAAAAAAgjjlO5Uq/QGVcrFf6WZZ7LJVDPyfmjw2IR2GndIZhyLIs2ZzhAAAAAAAAAIAEU1V7z8ByrL9tblluwLcj06TSD4hGdQ79PvnkEw0ePFhdunTREUccoV9//VWSdMstt+j111+vtwECAAAAAAAAABCtbNttd1leWXvP2J73zu+vfGySW/1H6AdEnzqFfm+88YaGDRumli1bavTo0RWq/Fq1aqWXX3653gYIAAAAAAAAAEC0siyjytDPMGI/GAu099wRc/oB0alOod+UKVN03nnn6b777tOgQYMq3Ne+fXstWbKkXgYHAAAAAAAAAEA0q2pOP8ldF/vtPSsHmlLg2GK7ihGIR3UK/f7++28ddthhVd6XlpamgoKCsAYFAAAAAAAAAEAssO34Df2qa+9JpR8QneoU+jVp0kTLly+v8r5ff/1VzZs3D2tQAAAAAAAAAABEO8epPvTzeJyYD8Zo7wnEljqFfieccIIeeughff7558F1hmHot99+0xNPPKETTzyx3gYIAAAAAAAAAEA0chz31jSdSvfFQzBmWW54uSOv15HfH4EBAQipioy+ZsOHD9eSJUv0f//3f2rYsKEk6aKLLtLGjRt1+OGHa9iwYfU5RgAAAAAAAAAAok4g+Kp+3rvdO5765vdXXekXD8cGxKM6hX7Jycl65JFH9MUXX+izzz5Tfn6+GjRooN69e6t37971PUYAAAAAAAAAAKJOIPiK1zn9LMugvScQQ+oU+gX07NlTPXv2rK+xAAAAAACQcGxbWrHC0F57VW6dBQAAoluo0M8NxozdO6B6Zlnxe2xAPKrTnH7l2batIUOG6I8//qiH4QAAAAAAkFg++8yjiy9OU0lJpEcCAAB2ViD0S8T2nlT6AdEn7NDPcRx99dVXKioqqo/x1Ojrr7/WJZdcor59+yovL0/vvfdepfE88MAD6tu3r7p27arzzz+/UiC5adMmjRgxQj169NCBBx6oUaNG7bbxAwAAAABQXn6+Ib9fhH4AAMSgUJV+Xm/sB2Nu6Fe5G0E8HBsQj8IO/Xa34uJi5eXlafTo0VXe//jjj2vmzJkaM2aM5syZo7S0NF144YUqKffX07XXXqulS5dq+vTpmjp1qr755hvdeuutu+sQAAAAAAAIKi52b30+WmQBABBrAsFXVZV+huHEfKVf9e09HUI/IAqFNadfJBx22GE67LDDqrzPcRzNmDFDl156qfr37y9Juuuuu9S7d2+99957Ov7447Vs2TJ98sknevHFF9WlSxdJ0s0336xhw4bp+uuvV9OmTWs1DtM0ZJr8QZaoPB6zwi2AxMI1AEhsXAOAxLYrrgHbtpkyDMlxzCo/SQ8gevB7AJDYqroGmKZkGFJSkiGvt+K1wes15DiV18cSxzGUnFz5GJKSYv/YgJ0VC6//YYd+Ho9HM2bMUJs2bephOOFZsWKF1q1bp969ewfXZWVlaf/999f333+v448/Xt9//72ys7ODgZ8k9e7dW6ZpauHChTrqqKNq9VyNGmXIMAj9El12dlqkhwAggrgGAImNawCQ2OrzGuA4bnVARka6cnLq7WEB7EL8HgAktvLXAJ/PfR1v0CCt0ut4WpqUmupVTk7Kbh5h/fF6pfR0KScnqcL69HRp8+bK6wFEVr1U+h100EHaunWr/vzzT+21114RC8PWrVsnScrNza2wPjc3V+vXr5ckrV+/Xo0aNapwv9frVYMGDYL718bGjUVU+iUwj8dUdnaatmzZKsuK8Rp9ADuNawCQ2LgGAIltV1wD1q9PkmV5tH59ibKyqPQDohm/BwCJraprwIYNhiwrRUVFpcrPr3hd8PtTVFBgKz/fF4nh1ovCwmR5vVJ+fmmF9T5fkoqLjUrrgXgWuAZEszqFftOmTdPWrVs1fPhwSdI333yjSy+9VIWFhWrZsqWmTZumvfbaq14HGm1s25Ft88dYorMsW34/v+QDiYprAJDYuAYAia0+rwGFhW6137ZtDtcVIEbwewCQ2MpfA3w+Q44jOU7l64JhOPL7Y/v13e93lJxc+RgMw5HPZ8T0sQHxqE4NSF944YUKc99NnDhR7dq105QpU5STk6P77ruv3ga4M5o0aSJJ2rBhQ4X1GzZsUOPGjSVJjRs31saNGyvc7/f7tXnz5uD+AAAAAADsLsXF7q0vdosAAABIWJbl3no8le/zeCQ7xjMxv7/6YwscO4DoUafQ759//lHr1q0lSWvWrNHPP/+sESNG6IgjjtCwYcP0zTff1Osga6tly5Zq0qSJPv/88+C6wsJC/fDDD+revbskqXv37tqyZYt++umn4DZffPGFbNtW165dd/uYAQAAAACJrajInTrC74/wQAAAwE4LBF9VzXhlmrH/+m5ZVYd+punEfKAJxKM6tfdMSUlRYWGhJOnzzz9Xenp6MFTLyspSQUFB/Y1wB0VFRfrrr7+CyytWrNDixYvVoEEDNW/eXEOGDNEjjzyi1q1bq2XLlnrggQe0xx57qH///pKktm3b6pBDDtEtt9yisWPHyufzady4cTr++OMrVC8CAAAAALA7UOkHAEDsCgRfZhXlNR5P7AdjlmXI6608zRWVfkB0qlPo17VrVz322GMyTVPTpk3ToYceKs/2uP+vv/7apeHZTz/9pCFDhgSXJ06cKEk65ZRTdMcdd+iiiy7S1q1bdeutt2rLli064IAD9MQTTyglJSW4zz333KNx48bpvPPOk2maOvroo3XzzTfvsjEDAAAAAFCd4mK3NMDnq6JEAAAARLVAqOet4p32eGnvWdWxeb2EfkA0qlPod8MNN+jiiy/WJZdcoubNm+vqq68O3vf2228Hq/52hYMPPli//vprtfcbhqErr7xSV155ZbXbNGzYUPfee++uGB4AAAAAADslUOkX6+2/AABIRLbtfminqko/w4j9YKz69p6xH2gC8ahOoV+7du30/vvvKz8/Xzk5ORXuu+GGG9SkSZN6GRwAAAAAAPHMtqVt2wKVfhEeDAAA2Gll7T2rboEZ68GYG/pV196TLgVAtKlT6BewY+AnSXl5eeE8JAAAAAAACSNQ5SdR6QcAQCwKVPJVPadf7Adj1bX3ZE4/IDrVOvQbP368LrjgAjVv3lzjx4+vcXvmyAMAAAAAILSiorI3ApnTDwCA2FNW6Vf5vngIxizLqLK9p8fjxPyxAfGo1qHf//73P/373/9W8+bN9b///S/ktoZhEPoBAAAAAFADKv0AAIhtgdCvqmDMMGK/vaffX/WxxUOgCcSjnQr9qvoaAAAAAADUTXFx+Uq/CA4EAADUSU2VfrH++k57TyC27PScfitWrNALL7ygBQsWaP369TIMQ40bN1aPHj102mmnac8999wV4wQAAAAAIO4UFZV9HetvCgIAkIhCz+nnxPycfrYteb1OpfWEfkB0quJSVL25c+fquOOO06OPPqo//vhDWVlZysjI0O+//64pU6bo2GOP1VtvvbWrxgoAAAAAQFwJVPqlpDjy+2P7TUEAABJRqNDPNOOjvWf18xXyuwsQbWpd6bds2TKNGjVKBxxwgG655Ra1bdu2wv1LlizRuHHjNHLkSHXq1El77713vQ8WAAAAAIB4Egj9srKo9AMAIBbZtvtaXtW8d/ER+hlVtveMh2MD4lGtK/2ee+45tWrVSo899lilwE+S2rdvryeeeEItW7bUs88+W6+DBAAAAAAgHhUXS2lpjpKTHfn9kR4NAADYWc72zpemWV0LzNiuhrPtqgNNr9eRbRP8AdGm1qHfV199pcGDBys5ObnabZKTkzV48GB99dVX9TI4AAAAAADiWXGxoYwMKSmJSj8AAGJRoL1ndZV+sTzvneO47T2rOrbAOkI/ILrUOvRbvXq18vLyatwuLy9PK1euDGtQAAAAAAAkgqIiKT3dkdcr5vQDACAGBUKv6ua9i+VQLFDF6PVWXcUoxXaoCcSjWs/pV1RUpIyMjBq3S09PV3FxcViDAgAAAAAgERQXG0pPd7+m0g8AgNgTCL2qCv1ifd67QOvxqub0M7Z/VonQD4gutQ79HKdymg8AAAAAAOquuNit9PP5CP0AAIhFZXP6Vb7P43FiOhQLhH5Vz+nn3sby8QHxqNahnySdd955MozQ7UYIBwEAAAAAqJ1ApV9RUdkbawAAIHaEau8Z65V+gUCvqko/2nsC0anWod/w4cN35TgAAAAAAEg4xcWGcnNtlZYa8vmY0w8AgFgTqhrO44ntUCzUsQVCTssyJFEIBEQLQj8AAAAAACKkqMht71lQYFDpBwBADLJt90M7Vbf3jO1KP7/fPbaqA0036IvlUBOIR1VcigAAAAAAwO4QaO+ZlOQwpx8AADHItiXDcP/tyDDKQsFYFAgsAwFfeYEgMJZDTSAeEfoBAAAAABAhxcVupZ/Xy5x+AADEItuuuhJOcufCi+VKuMDvJlXN6RdYF8vHB8QjQj8AAAAAACLAccpX+ok5/QAAiEGBSr+qmGZsh2K1m9Nv940HQM0I/QAAAAAAiICtW93gLyPD2R76RXpEAABgZ1lW1e0vJck0nZgOxQJjr3pOv4rbAIgOhH4AAAAAAERAUZFbFpCeLnm9Du09AQCIQbZdVvW2I4/H/YBPrLIs93eVqtp7MqcfEJ0I/QAAAAAAiIDiYvc2PZ1KPwAAyispifQIai/UnH6x3t4zMHavt3JyGahu9PtpTw5EE0I/AAAAAAAioLjYfZMsI8OR18ubZgAASNIffxg6+eR0rV0bG6+Loeb083hiO/QLdCGoqpKR9p5AdCL0AwAAAAAgAsoq/USlHwAA2/39tym/X/r771gJ/YyQ7T1tOzaOoypllX6V7yP0A6IToR8AAAAAABFQsdKPOf0AAJCkTZvc18c1a2LjrWvLSoT2npXvY04/IDrFxpUTAAAAAIA4U1Tk3qalUekHAEBAfr4b+sVKe0/Lqrr9peSuj+VQLPCBpKpCTSr9gOhE6AcAAAAAQAQUFxtKTnY/PZ+UxJx+AABIZZV+sRL62Xb1lX4ejxPcJhZZlvsz8HqdSvcFgk46FQDRhdAPAAAAAIAIKC42lJ7uvonm9bpvmjmV31MDACChxFqln21Lpln1C3ggGIvVarhQlX6BIDCW5ywE4hGhHwAAAAAAEVBc7M7nJ0lJSe4tn5YHACS6TZvc29gK/aq+L9bnvaO9JxB7CP0AAAAAAIgAt9LP/drrdW+Z1w8AkOjy8w2lpjpat86MibAsVHvPWK/0C3z/A7+nlBfrxwbEK0I/AAAAAAAioKhIwfaeSUnuOir9AACJLj/fUPv2tvz+slaf0cyyqPQDED0I/QAAAAAAiICqK/2i/81NAAB2ldJS9/WxfXs3JYuFFp+2bVQb+gXWx27o537/Cf2A2EHoBwAAAABABBQXl6/0Y04/AAAClX15ebEU+tVc6RerwVigdalRxY8h1o8NiFeEfgAAAAAAREBxsaGMDPfrQHtP5vQDACSyTZvcdKlVK0dpaU7Mh35l895F/3FUxe+P32MD4hWhHwAAAAAAEeC293Qr/Mrae0ZwQAAARFig0q9hQ0d77OFozZroD5Qsq+r2l5Jkmk5wm1jk90ter1PlfYbhBn+xemxAvCL0AwAAAAAgAoqKpIyMQHtPd11g7hwAABLRpk3ubSD0W7s2+t++tqyycG9HgTDQqfruqGdZZR9MqorHE7vzFQLxKvqvmgAAAAAAxBnHCVT6ucuBT9FT6QcASGSbNhnKynKUlKTtoV/0fxjGceJ3Tj/LMqqtYpQkj8eJ2WMD4hWhHwAAAAAAu1lpqfsGYKC9Z1mlXwQHBQBAhOXnG2rY0H1t3GMPW+vWRX/oZ9uh2nu6t7EajLntPau/3+OJ3WMD4hWhHwAAAAAAu1lxsXubkeHeBkI/Kv0AAIksP99QTk4g9HO0ZYuhrVsjPKgauO09q74vsD5WW2CGmq9QIvQDohGhHwAAAAAAu1lRkVu5EKj0C3yK3ueL/ooGAAB2lU2bylf6ubfR3uLTto0a23vGQujn80kPP5ykZcvKvt9u6Ff9hISmGRvHBiQSQj8AAAAAAHaz4uJA6OcuJyW5b6jR3hMAkMjc9p7u102bxkboF6oarmxOv+g+Bkl66qkkvfpqkqZMSQ6uq6m9p9cr+f3Rf2xAIiH0AwAAAABgNwu096xc6RehAQEAEAU2bSpr75mb68g0pbVro/stbMeRjGpyL9N0jyXaq+G++cbUnDlJOuggSwsXerRwofs99/sN2nsCMSa6r5gAAAAAAMShsko/983AwJx+VPoBABKVbUtbtpS19/R6pUaNnKiv9LPt6iv9Am0/o/n1PT9fuvPOFPXoYWncuBK1bWtr5kz3F5Oa5vQzTSfqA00g0RD6AQAAAACwmwUq/TIy3Fvm9AMAJLrNm90ArVGjsjnk9tjD0Zo10f3a6PeXVfTtKNrn9LNt6e67U+Q40g03lMg0pbPP9mnBAo9+/NGsMfSj0g+IPoR+AAAAAADsZkVFhrzesgo/wwjMixPZcQEAECn5+W6416BB+dDP1rp10R362XZZRd+OAuudqjPBiHvlFa++/tqj664rVaNG7ro+fSy1aWPrmWeSts/pV/3gCf2A6EPoBwAAAADAblZc7Lb2LD8HUFKSw5x+AICEtWmT+6JYvtKvaVMnJub0q64aLlDJH40f6lm50tATTyRr0CCfDj64LLkzTemcc3z67juPFi82Q1b6uR9Yiu5QFkg00X3FBAAAAAAgDhUXG0pPr7jO6xWhHwAgYVVd6edo/XojattjSm6lW3WVfoEP90Tj+L/+2k3zLrig8i8fhxxiqXVrWytXhg79TDM6jw1IZIR+AAAAAADsZkVFhjIyKrbL4tPyAIBEtmmToZQUp8KHYvbYw5HfL23YEL2vj7Zt1Nje07Kib/yLFplq395WSkrl+wJz+0ll1YpVob0nEH0I/QAAAAAA2M0C7T3LS0qi0g8AkLjy8w3l5FRct8cebhnZ2rXRF5oFWFao9p7ua300VsMtXuxRp07VJ3aHHWapVStbaWmh5vRzCP2AKBMipwcAAAAAALtCUVHl9p5JSU5UzvkDAMDusGmToYYNKwZMe+zhLq9da2i//SIxqprZdvXtPQProy3027hR+ucfQ/vuW/3ATFO6886SkI9DpR8QfQj9AAAAAADYzYqLpdzcyu09qfQDACSq/PzKoV9GhpSW5kR1pZ/jVB/6BSoAoy0YW7TIHVio0E+SmjSpvspPco872o4NSHS09wQAAAAAYDcrLq5c6cecfgCAROa296wYMhmG1LSpo7Vro/dtbMuSTLPqcKxsTr/dOKBaWLzYVOPGTo2hXk2o9AOiT/ReLQEAAAAAiFPFxVJGBnP6AQAQUFV7T8lt8RnNlX6x2N5z0SJT++4bflrnhn7R+7MBEhGhHwAAAAAAu1lVlX7JyQ6hHwAgITmOW+nXqFHVod+6ddEbLFlWWRvPHQXWR1Po5/NJv/7qqbG1Z22YZnQdGwBCPwAAAAAAdruiIkPp6RXf2PR4JL8/QgMCACCCiorc18AGDaoK/eyYrfSLxjn9li0z5fNJnTqFn9Z5vdF1bAAI/QAAAAAA2K18PvffjqGf294zet/UBABgV9m0yX39q67Sr6DAUHHx7h5V7di2UW3oZ2x/WY+mFpiLFpnyeqV27cIP/Tweh9APiDKEfgAAAAAA7EZbt7q3O7b39Hqp9AMAJKb8fDcUq25OP0lRW+0Xqr2nYeyaFph//WVo2rSkOgVuixeb6tDBVnJy+ONw5/QL/3EA1B9CPwAAAAAAdqPiYvdNy4yMim9sMqcfACBRBSr9cnJiL/QL1d5T2jWh32OPJWvWrCQ980zSTu+7aJFHnTrVT1LHnH5A9CH0AwAAAABgNyoqcm93rPRjTj8AQKLKzzfk8UiZmZXva9zYkWlKf/0VnW9l27bb5rI69d0C848/DH35pUf77mvrueeStHBh7b8v69cbWrvW0H771U9S51b6RWcYCySq6LxSAgAAAAAQpwKVfszpBwCAKz/fUIMGTpUVcx6PdMghfj3/fJLy83f/2Gqyuyv9XnghSY0bO7r77m3q3NnSxIkpKiio3b6LF7sD7dSpfgZEa3Ig+hD6AQAAAACwGxUVBUK/iuvd0C8CAwIAIMI2bTKqbO0Z8J//lEqSJk+uh4no6pltu3P3Vcfrrb9579atM/S//3k1aJBPycnSDTeUqqREuu++FDnVf/uCFi0ytccejho3rsXGtWCazOkHRBtCPwAAAAAAdqPiYve2cqWfw6flAQAJKT8/dOiXkyMNH16qjz/26uOPPbtxZDWzLLcasTqGEbrSb+NG6aGHkrV8ec3V/q++6lVysqPjjnN/YdhjD0dXX12q+fM9evNNb437L1rk0b771l9K5/E4zOkHRBlCPwAAAAAAdqPiYkOGIaWlVVzv9VLpBwBITJs2SQ0ahK4+O/xwS336WHrwwWRt3rx7xlUbtWnvGWreu+nTk/X6615demmaHnooudpWnYWF0htveDVwoF8ZGWXrDznE0vHH+zVlSrIeeSRJn3/uUWFh5f19PmnJErPeWntKgTn96u3hANSDmuN/AAAAAABQb4qK3Cq/HVuBufPiMKcfACDx5Ocb2nff0GGUYUhXXFGioUPTNHlysm66qXQ3jS40yzJCVvp5vdVX+v31l6F33vFq6NBSGYb0zDNJ+vDDNF1wgU8DBvgrhIlvvulVaamhk0+u3Bbgkkvc78X8+V69/LIh05TatbPVrZul/fe31LmzrT//NOXzqcbv884g9AOiD6EfAAAAAAC7UXGxUWk+P4k5/QAAiSs/36ix0k+SGjVy23xOnJiiww6z1Ldv5BOn2lX6VX3f9OnJatLE0Smn+JWcLB15pKXHH0/SpEnJev75JJ1wgk/HHutW9r3ySpKOPNJf5Xx8qanSVVeVynGk1asNLVjg0Q8/mHrvPa/mzEmSaUq5uY6SkqS2bes79IvdDywtWmQqJcXR3ns7FX6GPp/0zTceffihR4WFhq66qlRNmtTPPIjArkboBwAAAADAblRcXHk+P4k5/QAAiamkRNq61VCjRrULVY44wtJ//2vpxRe9MRP6VVXpt3ixqfnzPbr++hIlJ7vrcnMdjRxZqkGD/Hr1Va9mzEjWjBnJysuztGGDodNOC/3pIMOQmjd31Ly5X8cdJzmOtGJFWQjYrJkb/NWXWK70KymRrrkmVZYlpaU56tjR1r772tq40dD8+R4VFBhq3dpWUZGhK65I1cSJ29SmDcEfoh+hHwAAAAAAu9GmTUaFuXgCQs3p9957HqWnS717x+g7awAAVGPTJrdSrGHD2gUqhiH16GHpmWeSagzcdrVAmOfxVD92j8epFPo5jvTEE0lq08bWkUdWfm3v0MHW9deX6uKLSzVvnldvvunVEUf41br1zoVOhiG1auWoVSu/Bg7cqV1rJZZDv7VrDVmW2xrV55N+/tmjuXO9yshwdMIJfh1+uF/77ONo3TpDN9+coquvTtXYsSXq2rX+KiWBXYHQDwAAAACA3WTbNunLLz069dTKJX1JSdXP6ffyy0latszULbeUREVVAwBUxbalv/821KSJU2UbY6Aq+fnua19OTu0DrfbtbW3bZmjlSkOtWkWu+ioQ5tVU6bdtW8XX96+/NrVwoUfjxpWE3LdBA+n00/06/fTobAXg8TgxG/qtWeP+TPr0sdSsmSOp6u9xkyaO7r13m8aOTdENN6Rq5MgSHXZYjB40EkIEPwcRec8++6z69eunLl266LTTTtPChQsjPSQAAAAAQBybP9+jrVsNHXNM5TeWvF7J73c//b+jrVvdT9PffnuKvvsuof+UBxBlNm2S3n/fozvuSNbpp6dp6NA0DRmSplde8aq0NNKjQywoq/Sr/T7t2rlp29KlkX1NrE3o17ixo9df92rEiBS9955H27ZJTz6ZrM6dLR18cGyHR9W1Lo0Fa9aYMk1VOUfijjIzpQkTSnTIIX6NH5+iK69M1csve7VuXezOZ4j4lbCVfm+99ZYmTpyosWPHav/999fTTz+tCy+8UPPmzVNubm6N+3uWLqlxG6td+7IFn0+eP/8Iub3j9cpus3fZiq1b5Vm5IvQ+aWmyW7QMLhsFW2SuWRN6n6ws2U2ble2Tv1Hmhg0h97FzGskp930x1q6VuWVz6H2aNJHToGFw2Vy9SkZRUch9rD2bq3yfG/OvP2XU8Bui1WovKSUluOxZvlSyQ1+srX3alr0aW5Y8vy8Pub1MQ9Y+7cqWS0qkX1fI3Fwsj1X1cznJybL3al22orBQnn9Wh3waJyND9p7Ng8vG5k0y160LuY/doKGcJk3K9lm/Xuam/ND75ObKyWkUXDbX/COjoCD0Ps2aycnMKttnxd8ytm0LuY/VoqWUlla2zx+/y6hhkhKrzd7uux2S5DjyLFsacnupHs614mJ5Vq0MvU99nGsbN8jcuDHkPnU61/bYQ052g+CyuWqljOLikPvU6Vzbq7WCTea1a841xzRl79O2bMW2bfKs+Dv0PvVxrm3Kl7l+fch9djzXtG6dzN9XVHsNkKo41/5ZLaOwMPTz1OVca9nKnbU7sM/vy2XU8FG7nT7XDMlqW+5cKy2V568/Q+5SL+fals0y164NvU99nGtr1sgs2BJ6n+3nmmVJ331nKm3DSqU7RUpLc5SS4rY02bbNUGmpW8Xh9xsqbNhCpUkZsiz3VGha/LsapJUoK8u9PBYXS1u2GNqyxVBBgdt6xW7dRqnZSWWn6JKl2lbsaOtWqbTUUHq6s/2fO++AxyOVtG7v7iypeIul0sXLg4/r8xnKynKUmekoO9vd15JXm5u0lc8nlZQY8hVsU/Lqv1Raasjnc/9rZGU5atDA3SctTdqmVG1uuJeKiw1t2yZlqUC5JauUmSmlp7tvUBcWuv+KitzHSW2cqdS2eyoz01FGhmRurniuOY775nbgn21LynHPNcNwx5G6ZZ08WzaF/tmUO9ccRzJWr5YKCoN/fFY1Z0Wlc+3vv2SUlIR8nqrONU9J6Dk1InKuFRXJs3pV6H3qcK7ZWdlymjYt22fDBpn5u+5cCzBXrpCxdWvIfSq9rv35h4zqeiQG9tnhdc1cukSb8t1P/JaWuuGK1+ueu0lJ7qeYfXu3lzfJkGFIBfmW/L8uV0GBocJCQ0nJUnqao9RUd6625GTJMT3a1tJ9XTMMKdneqoz1f8nrdR/bsir/83nSVNR4L1mW+zh75WxRWv4/IY/FycyU3WzP4HKtfr/f8XfIdetkbt4Uep/6eF2ry7m2fJmMGt5N2i3nWlKS7NZtylYUFcnz907+vbZls76fla9j2kgtCn3SDsPMXW8q19dEPl928L9n4FxrvCFFJx5q6a+/DD1xnalrry1V+/bu7yERO9dq8/v9jr9DLlsi1fDemtW2XfB1TX6/PH/8HnJ7x+ORvfc+ZStq8ztkSorsVnsFl43CApn/RMm51rixnIY5weXa/C0dtefajn9L1/Vcq+l1LT1ddvMWweVd9rrWqJG0R9nPs1Z/S9flXGveQuXL5KLxXLNt6bvPSvXF7FVauNAj25b22svWGd1t5eXZ+vZbj96e5NEnz6bquEuaqV8/S6a5C8+1hjlyGjcu22cXnWtWsz3dd/8D+9Tmb+m6nGt77+P+MiJJti3P8mUht6/Tubbj39K1PNdWmS31zz/u7z+l6zbLXrVWGRmO8vJslf+TOcDObiBnjz2Cy1Wda9Yij1pvS1Lu+m3ybHLPNadR2etaVedajqTu6Sna+LklTyu/7KZN5WRll+2zi841td2nwqLx2xK13paqBv+UyrO06p/r+HHtNP9Tr956y6t77vDoZed3+UsNDb+xRN5llU/UOr1HnJoqu2WrsnHV5lyry3vEO5xrmcVr1bygUJ6l1b/m1Ok94rqcazv5HrHvJ68a5+QFX9ZqOtc8km4abKhnzzx98IFXjz+erCceLtHhbZapSxf32temTeU5E+t0rtXlPeJanGuV9qnLe8R1Odfq8h5x6zYV/piPljzGyEyXcjrWOJZIMhynqs8Qxr/TTjtNXbp00a233ipJsm1bhx12mM4991wNGzasxv1LjhkQegPD0JaZs8sW169X1lWXhdzFbtxEhZMeDi57fv1FGeNuDbmPlddJRbeMDS4nffqJ0h55KOQ+vt6HaOtllweXk19/Ralzng+5T8mJp6hk8JnB5dQnH1fy/94Nuc/WCy6Sr99RweX0uyfK+8P3Ifcpvu5G+ffvHlzOvOEamTWcaIV33FvhRS1r6HkytoW+0Gx5YkbZL1xFRcq++P9Cbu9kZKjg0enB5eRVf6vBzTeo1GepulPI2qu1iibcHVz2fv+t0u+9M+Tz+LsfoOIRN5Q9z7vzlPr0kyH3Ke1/jLadf2FwOWXWs0p547WQ+2w74xyVnnBicDlt8gNK+uLTkPtsHX6VfD17B5czxt4iz5JfQ+5TNHq8rPYdgstZl18io4YXm4IHHyn7xc5xlH3u6SG3l2lqy4xZwUVj3TplXf2fkLvYTfZQ4f2Tg8uexYuUcfuYkPtYHfdV0c1l2yTN/1hpUydXv4MkX59DtfXS4cHllNdeVsoLs0LsUcW5Nu0xJX/wXsh9tl4wTL5+/YPL6XdNkHfhgpD7FF8/Sv6u3YLLmddfLbOGMKbwzvsqvGmVfeEQqSR0GFX+XDMKC5R1yYUht3cyM1Uwtez/vPnH78q8+YYQe7i/BBTdfldw2fvt10q//+4Qe0j+Hgeq+Jrrg8vJ77yt1BnTQ+whlR49QNuGuNcKr9dUziuzVTrnxWqvAZK07cxzVXp8WdP8tAfvV9JXn4d8nuLhV8vfs1dwOWP0Te4f7CEUjbm9wi82WcMvllFD+F/w0NSyX+wsS9nnnRlye5kebZlR9lphrFmjrBGXh9hBsps2U+G9DwaXPYt+VsaEsSH2kPz7dlbxqLLXvqRPPlLaow+H2EPyHXKYtl5cdt6nvPqSUl6cHWIPqeTkU1Xy77LrS+oTU5X84f9C7rP1wovlO+JILVtm6LLL0nTxqtHquHVByH2mNBurX9O6BZdHrfiPmvpCv67d3nKK1iaVvWl19x+DleyEftNuROsX5DfdN3kyrC2a8Ne5ktz3CUxT8vsqvudTZGZrVOuZweWWJct03aprJLnbO3bl94j+Tm6re1rcF1zuUvSFhq6dKEkyVPV7SgvTe2pa0xvdbQzpsC1zNWj9EwrsVNXp81H2QL2cOzS4fEr+dPUvfFVejxtwOo5k2YZsy32zyXGkVxtfoA+yT5LjuMv/t+ZOdSv+LPgYhiF5PZLH67i3Hul/B12nNe16KSPDDST7v32DcjcsCX7PHLnfB9spu/3833dqfU472baprKwU9Xn0bKVszZdpuPuY2x/b45E8pjvejQ88ppSmDWWaUmmxX5lDzlJpqRsqObbk8ZaNzTQlS159f+ssbd1qaOtWKTV/tQ58/HIZ279ngdvAjWFIJblNtfiqye64Hcm76Ce1f2qs/JZk+Y0qfzbr9uyi+ceOkeTu0/LXD3TA/Mllx+xs//5u/x4bhrSkdT99cfBwpaZKKSmO9v9ljjovmCVz+/fMNCWPWe5rj6PNx52m4pMHKzXVDcezn3pEyR9/UDaQ7c9TFv4a+vWYS7WkTX8VFrrP2/e/Y9Vk1UJ5Pe7PxVeqYEDt87nfiP/2Ga21zfffHs5JJ749XA0KV8nY/v/M8mv798N9PsOQnjvsYRU3bC7DcPTPP6Yu+9/pMv2h30gY0eZF+Q33D89Ma7Nu/2uIpOrPm0KzgW5qPSO4vFfJEo1YdW3I5/gruZ3ubXFvcLlb8We6dNMdSkuXUlPc57Dtcv8s6dfcXnqx/Q3u/ytH6rnmdR3155MyDFX5z5sk/bH/CVpxzPnKyXHUpImjjvOnK+fjN4P/v6qy7ezzVDrg+OBy2gP3KunrL0MeT/EVI+Q/6ODgcsYtN8rze+g3Lotum1DhjcusS4fK2CHA2los/fGHKZ9PysqWFo96Qp16Zik315F8PmX/39khn0NJydoy/ZngovnPamVee2XIXexmzVV4zyT394CcDG35+HOl3H5byH38nbuoeOQtweUtL32gFTc8pnZtbTVuUvns3LDe0Mx/jtYZn10YfA8y5aU5SnnlRX3ztUfNW9hq1tTRL7+YKi42tO++ltIzpJJTB6vklH8HHyftsSlK+vjDkGPbOuwy+Q49PLicPvE2eX/+KeQ+RTfeKmu/zsHlzBFXyFwT+g3FwnsfrPCGYvZ5Z7knYwhbnnouGCwZmzcp6z+h/0Z3GjRUwcOPBZc9y5cq49ZRIfex9mmnotsmBJe9X36h9IfuC7GH5Duop7ZecU1w2Xz9DaU8O2N7aO/OC2T5y+Y28nqlTUcMVPEZ5yotzT1nG8yZrqwP3nKvF9uvt4HXQ8dxr9mrjv8/ret5nExTyshw1PrZu5X501fymKr2HC2+6lr5DzwouJxxy0h5lm//wF01+xSOu0NWm320aZO0erWpNjddICu/UJYlJSW5b1p6k9zjCLw+fHv1kyryZMvnk0oLfTr8oTNlO5JtGdtfo8u2NQzJ8qZozmnPy7v9da5B4UoNeO2Kctckx7013WXTkLbmttD3wx6Q1+te0xv+8YM6PjvOvd/jvr54PO7rp2G638eS/boq/6qbZZrue4rJH76vtGmPlh2sI/n8UmmJIcNwlJQs2Uf2U8mwS4KbpLw4WymvvhTcPvDa5PMbwWP6+9AztLLvaWrWLE3p6cVq9fKDSvvso5D/b7Ze/B/5DjksuJw+4TZ5F9Vwro0aLWvf/cp+ntdcIevvf9xKYBnB12cZUkqy+0GTgvseqhBiZg85032RCGHL088HgyUjf6OyLi/7ftiWW321YYMhvyWlJEt2To6+u+Ixbd5s6M03vUr+fYlu2Xyd9mjqqFGO+32tcOzF0jcFHXWt7lFKivu7QPei+Trz73vk9TjKbiDlNHSUleUEf5bFxdKiRn30aMPr5fFIBxxg6ajCV9TmfzODv3Ru2yYVFhnats1QZoaj7AaO/CcM1Lazzg0+d+qM6Up+5+2Qx79tyP+p9Oiy9/fS77tL3u++CblP8dXXyX/Av4LLGTddX+ObyoXj76zwpnLWJRfU+KGZgqnTyoL8bduUPXRIyO2Vkqot08p+5zBXrlDmDdeE2EGym7dQ4V33B5e9Cxco/a4JVW7r2NLGjYa+9B+gscaY4PpeW/6rszZOCeYqKSlSdrb7M01NlVJTHDnH9FfJ0GGybemffwzZT89Sw3dfluU33N9lHKmo0P0A5YH/cv/Plpx2hkpOGhR8nrRHJivp048rjevXX0zZjtSpk62tlwyXr++hwfsyxo+R55dFIb8HRTeNkdVp3+By5tXDZa4L/YGBrQ9NUcMOeys/v0h+v62Ms87Q118Zat/OVm41FWNbZs4OBuyrf9qo9MsukwypVauqQ0Inp5EKHpoaXPYs+U0ZY28OOS6rfZ6KRo8LLid98ZnSJk8KuY+vZx9tHV72+0/yG68rddYzIfaQSk44SSVnlP2e9ctV06U339FBISoWt513gUqPOja4nH7vnfJ+/23I5ykecYP83Q8ILmeMuq7GILtwwt0VwrWsi/8vZLi4dKmpew98RndO3p761eJcc1LTVPDE0+7zFUo/zF2lfe69Rlu2GLJs93UsK8u93vn97t8rq7x76a7WDwU/5Nd+y3e6aOVt2/9mkkyPI4/pvuamJEvJKVJhXnctO2eUNmwwtH69odyv39XB30xVUrKUmuooNcV9u800Hdm2ey6tPeAo/XXCMCUnu58B2fO959T4fy+7Ay/3N2Tg71bTkLadfqZKTzxFjiOVlkopkx9SyueflP096Liv7+b2v29Nj1Q47HIVH3SIiosNFRdLzSaNVuryxWW/10gVfsdxJC04Y5zy9+wk23Z/X+rz5CVK3bKuwjaG3IzP63Vv/5nwsDzNGgePp/EFp8txHPc1efu1I/gH2Pa/lf+e8oK2bXM/iOz/Z7063nVp8H2D8q+dgb9d/Q1z9evIqUpJcf/GzV75i5pPukU+vyFfqYJ/cxqmlJwk93WuY56aTC+7dkajhKz0Ky0t1c8//6yLL744uM40TfXu3Vvffx86lApw33AJ8RexYcjrLavrNryGjFDbSzJ32Mf01GIfs+I+nrrsY9a8j8dj7vTzeExTTvnjqeXzqPz3rTb7eE2Z5Z8n8A5YCF5vuefxmjU+h7Hjz2Z75ZJR/p23HVT+2dT8PDvuY9ZmH09dfp47Hk/t9tn5n6chYyd/nl5vuf83jlPj9rvrXDPq4Vyr7Tmw0+eaZzeda56K55qxs+daLf4/VzrXanF+7vjzrMu5trP7eDw1XwPc7Xb+/5rHa1T42eyWc82oxblm7niu1eZnox1+nrU5b1SHc80M/1yr5T6O11RenvTaa9uUOsFS8s+2+4v79hDBE/yl3T3+SdeWytl/W3By89RrLGmFLb/PDTe8XvcNtaRkKWn7b2XTbivRlqwSFRe7v5Dm3WwrybLl2f7GVuANxUCA4Ui6d2ypnCR3+wyrRPvebispafsbYdtZ2//g8PslO8vSU3eUKDnZ/cU2bVWJcsfZFbYP/IHi87n77t3KVttrS5Se7v4xb3zpU+6j7rH4/Mb2yjxHSV73jxXTkPbpZKnTqaXassX9pbv5t5b2/tD9rdyRu41hBm4dGZIaHuTX/keVyrYln89Q83mWmn/tBN9Edd/wc4LhkmFKxx/q1/4H+tz7TGm/uZaaLHGCYWT5N2ED3zefz9Dff5sqKjJUVCTtuchUi6Lqe/IYkl54IUn/ZCUrKWl75eZSUxmlZsgP0d98droKvelKTpasEr/u/d0T8v+ZZXh03XVlnwRv7EvRzX+Hblm0Psmr8TeU7dN+a7L+s9oM/n+s6r/279tMvfde2Z8CB27xqP1mw/2eGk65n4v7/9r9I9DQ6tWmSkrcak/jD48arTbdALaab8K8Fcn6f/buOzqKqo3j+G9LeiEhCQQIvXcEpImiIAIiggiCCjZQLNhRwIpKURQLYgEpIoIoIqKvCGIFqVJEuvQSIAkhpNfdff8YdsOSQoBI2vdzTs5mZ2fu3JnduTs7z9znLl2QfUfn7TGe6pBskdli7NOsrJzLfnHSQ+sDPeXvb/yY89prUb3Us9ofGT8CPT0lq4dDshs9ZiMdZqOnXKZJHWJMsqUaF0WdvUadQV+PM8eK1Wr0hM3KMqluXYeq73XIz8Mubx9jvzl/FDoc2cHfd17LUKYcstulYHO66o+1y8OafazZz/qM2R2Szd+maa8YQXu7XbIeyFCNyXZXeede6JZJql/NpsYj0mW1SomJUvLyLAXPNy6cnj5tch0Dzh+qFovkHyDVq+eQp6cxveZ2hwJOnfVD2+G+LWmp0r+7zZp3xFPODpG3xHrqugSLvLyNi/1nH59mi+TnKyUcNis43ezq6FXQ886zv9dS00xKizErIcEo19dX8vM1ehRbrM5lzHl/rzmkyGMmHT1ikpeXFBDoUEK8SW+/7aUki4/KlZO8zBkas9VypiypUUO7PLNv+nZ9kNy+1wp0LmAs4zwPKMj3zbnnKZs3WxRukUJClOuyZtcxa3bdde78TWCzG/vTYpUaNHBoxw6Ttm6zKDDQoVMbLArvaFGlSg63ujns7t8FZ7uY83ur1f29MZty3w739ZxzDmmWZD//emwms/HdWoBzjnPPU9x+RzmkjEwpI11Kz5AyM4yLTTEpFv3vfS+lpEgpKSZVPuipHlstRsDuzHe68/tGJuM7ZPsxD83b6KOUFOO7o+NJL/U5lX+7/tsJDy3+KbsdvCXWU53i81/mm+MeWrEgu12/L8pDzZItMumsm0usRvBLDsnuMOnL8V7a5u+j9HSjHXx4j1WVU88Ec5R9Q4bzZgiHQ5p0v48OWX1dPePHHbIoyGSSxWJ8t+eWOGLcOC8lW4wDymo3qdYRIzWa6wYY13ocxo0aJpO2b7e4LnQGp1jVJtbkulBnP3Mx0dXmSoo+YtGECdkHbb0UTz18Iv/vwt3bPPTRCiNSbrFInbO81P+ExeilnWVSRnrO75t1ezz148++8vd3KCtLuuaIp649YTHa76zcb2haEuWhn372OnNu5607Yzx1VbpFnh7ZNyPZz9wE4uVpBD12/GKV7B4ymx1KSjKp8U6zgo6YZbMb+8C1nrMulC6b46ljIV46edKkqCiT7ltnVUhG3p8bk0n6+DFveVT1dt2c88Aesyw6EyA9cxHVapVMcigry6SsLGnuVE+lpFvl7+9QqNlTPaLMMluk+NNGgMdmNzr3enk5lJIqnUwy6+23vWS1Stdea9PAwRlq+tlZV1zP4esndWxu14d3pGvrVrOyskwK3WVX2C8OZWRIsbEmHT9ufOYCAxxKSTEpPUPaVs6igF7GZ/Dzzz21P8pL/RIt8vZyKCU1+7NptUhZNpPMJml/hocy/TwUGGikQ66+yaKqR80ym+S6mOvlbZxzZ2QY7cHOf6zalmBEKr28HGq116Kwk2bje9aUfU7vPOasluzfHg6HlJwsmVNNMicb2+DllbPNdTikU6csis6wyMvLCEr7ZJpktZtkzqcpcPvNXpB28CK+10wmk9LTza52wxprljnN5HY+k5VlnPdFxxg3XKmG9MILmapf366AAIeC1mXKd5ZdWVlSYoIUn2BSQrxJJ2Oybzxbd8BTv63wUWysUUbPUx7qnmh2nUMZbYhDFStm/y4t6PUUf38jkGgymXJ8rxXsOofpnO+1Al5POevR+dk32r7cl7Vaza6T8mrVTPKtnvdxc6YiRXONuEDXe3Muk6X8zwfMlov7zX6h10asVrPs57yf+V23ysiQwsPPOnYKdI04e/6gIOna6xzyXWJ8sSYlOzP5GOcWHh7G90B4mEP9+9tc2UMqHMlSje+M4JXtzM2sxu8YKSVVijtt0pZTFk07YLS3oaEOXZdhtBmpqVJcnFm5dZJbddRDC1Zlnz/0POWprqfz+e6Q9PMRL/0+21fJyUY9Bkd7qFVS/ucpc17w0saA7B6yjx2zqFZa/t/TM2d6ar939nd78BGLQrLMZ64tnrmn48zNQ06vDPdRnDV7Pe/ut+h8XdifuCP7nCsoy1tjDudfr9NWi8aMyN5nNdO89fgx9+23WuX2m/fAfqvuybfUolcme/pFRUXpmmuu0fz583XFFVe4pk+cOFF//fWXFixYcN4yHLt2nf8Lt3797P8zMyXnXXZ58fCQatXKfp6aKh0+nP8yvr5S1exebkpIkI7nn9ZOgYFSpew0CTp1SjpP92CFhEhndd1WVJSRtD0/FSu6J+OOjDRugchPRIRbuhgdPGik0sxPjRpuXbe1Z8/5k0nXrauzUw5q7/lSkpiNZZzS04265cfLy6ibU1KSsQ/y4+8vVcnu3aHTp419nZ/gYOmsrtuKiTHe0/yEhUnly2c/P37c+Ozkp3JlKSA7XYwOHzY+o/mpVs2t67b275fOk2pLtWu7pYvRv//mP7906cdaSop0JP/0P4VyrMXGSudJIXlRx1p4uDGys9PRo8avj/xczLFWs6Zbupj/5FizWKQ6Z6UkSUuTDh3Kf5nCONbi4qTzpP8plGPt2DHjCm5+LuZYq17dLV2M9u1TrmeAZ7vQY81kkupl99xVRoZ04ED+yxTGsRYfL50nJUmhHGsnThjryk9hHGsHDui8A5tczLFWr172j5msLOMzkJ+LOda8vY3PmlNiovGZzk9hHGvR0cZy+SmMY+3QIWUlpSk11WgOrWeClx5n7jI0m5XnsWakdjWWS001/nf+nQqureR0q1JSjItZ1dL+VUiIUV0PD+OwSE42HtPTJW8fk6yN6snPz1iVKTNDjv0HsgM29pyPdouHsqrVck3zNyUrIP5ormlNXS7mWCtXzjgOnE6eNI43GfXIyDC2IS0t+/9k7xAl+4S69ofj+AnZ4+KVnmH8cAoIMD4mfn5n/V87XP5Vyrm+PhyHjyjtVIqrKSxXLjvblUthHGv//pt799OzFddjLSDA+Ew7FeT8PjhYjrAKSkoyTjditkfr1L44RUcbHwfnTQJZWcZX6+HDUpQ9TAnW8qpWzfgaaRx8TDVDExURYey648eNqp44YRy2np5SWvnKMgUGyG6XtmyR7AcOyVtpqlbNKPvYsezdHhwsVagoedWtrgrVvF3NbkjcXvn72JSRIc2caby9N98sDRyY/RbGBtXW5q1WHTwo2W0OlYv6V3a79O230l13ST17nrP9F/O95ulpfG6ckpON74L8nHWs2e3Sbd3idX2TE3rwwdxn37hReu6Ncpr7S3j219TJk8qKitWAAdLw4dJ112WvfsUK6a+/pFW7QhRrClWVKsamecSekCkhXjabUe0KFaWKFYzm1fkX0jhc4fXLZTeFR44YjdE5MjKy26jk4AilmPxksRib5R9dgPP7c461U+v+1cH9Dh09any2EhOzH5OTjf93ZNVTcopxI0I5vyzVt+5TYKDRNp/dbqalGe1GQLBVWdVrKzjYqG9ybJo8jx9SYqLxeT47eOXhYbwtVn9vJYdWl5+f0XwEWRJV0XZMPj7GZ9LZrqelGe+dr69kDQ6Qo1Jl1zLBjlMqlxEjX1+dSbtt/J2d9jrBEqw4jwpKTjaaBM/T0fJMjjurV7RcN604/1ShghQcLJvN2NaMA5FKO5l0JkCZ/Zeaaszv6Smlh1SWuVyA62744ATjWDObjWMt46y71S1W4/stPby6rP7eKl/e+LqOSNsrH8/snZWRYey/pCRjv3l4SNb6teXpa5WXl+Rhdci05zznkOf+lj7PsWa3S1lmT2VVrelK/W1LMI41m814T5zbnpKSfUOQzdtPmRUjlJVl/FRLPh4v29ETSkkx2pGwsOzTP5vN+IkVk1FOx+zhSkkxPlv+aSflmxpr/O9vNK3OPy+vM4GfiqGyVAhx/eSI3XZcpw4mKCEhu2eC8+N+8qTRLm4/Fa7IROMc0mSSalqPKMQnRZ5e2cHSc3tknw6oqkwPX4WGGu9NHfN+VQrNlJ+fXL3aLRbjvT150mjy99lr6nisp9LSjPe5XNS/yso0gnWJCcb76DwWTCbjFDqpcj35+JqMFO2nsxQQvU8Oh3F8d+wodejg/vUiq1UZVWsrK+tMRsSCfK/5+BjXBpzO+l5zOIyPw6bN0vZtxtd5q1ZSo7YB8qxR2fWR2b7ylLb/HqOTJ42ffrVqGX9+fkYzvHmz9OeO8lqxM0xZWcY+rWyNVpg1TpmZeZ8WnrJWcKX3TE+XgpIj5WvP/7rVKZ8qkr+/6wJ5pfSDrqwcJpNxGaxCBaMOMTHGqdIxj+rKMGefQ0ak7ZVFNplMxufF2zvnX1J4HVk8jbHf0lLsKhe9xzh+zwQXnce6w3EmWGAz67h/3ey0+WkZKp9wwHXzx9mfNWc7ejrVS5EeNVz18rYl58hK4vysdOggdesmVW3gZ7xRTnmcQ2ZkGKfx0dHSkcQgHUqrqLAw4yuhVuBJhZlj87+HODTUOGid8rhutX699MYb0rRpUkiTSkZlnfL4XnNTtapbes8CXbeqVcst5WD8+t267z7p2Weltm3zWOZCzyEv5hpxPsdani7mGnH58jo7j+sPs6I16+04ff11PstczDXiKlXc0nv+F9eIH3xQata3jh5+NDuVrvacJ4VkYVwjLsA5ZIanv1LLV1Fg4JmPzjnXiJOSjEPPea7n4SFZQ4NkD6t4ZhgPyRZ1UvaY2HOyCmR/l6akSnGWMGUFljduxPOTgtOOyzcrwXWjiHO4g7N/68X7VpI5KFB+fsbhExh/RN72FLdzm7PPa8xmyVyjmsx+PtnnOnkcaxkZcp2/xZarpdQsD9f2eB7Y7Wo3neclrnu8zmxjWvX6rvMyP89M+Ufvd91k7dwWZ6/GjAwpw+Gh5Iq1XNuWfjpVlsjDCgw0fpuUK3cm44HD2GenT0uxqT5q1rNajroXJwT9LjLoFxubJLP5PEE/lFoWi1mBgT5KSEiVzZb3lweA0ok2ACjbaANQFtls0uHDJv37r1n//mvSoUNmHT5spBs6W1CQVKWKXSEhDmVmmlwXCOx2ozfiFVfY1Ly53XVNLiPDKPfAAbOOHjV6fJw4YfzFxppyxGGrV3do5MgMNWhQsJ+xI0Z4ymqVXn/9PEHgC3CxbcD69WaNGuWpDz5IV8OGudd/40aznnnGU3Pnprt67UnGxY/evb318ssZ6tQp5zpTUqQNG8z65x+zPDx0JihlpC+OjzdSN544kb1/z75m5ucnlS/vUGioQ+XLOxQU5NDp08a8UVHG+5CXoCApIsKu8PCc49ecKzbWpD17TIqLM8rz9paCghxngiqOM+ngjLRwRsDFIZst+455Y5xa4/qfv78xj5eXQ/HxJsXHm3TqlNEb1tPTKKNcOeMxKMjoPRIW5lCFCsY6znf/LpCfi2kDnPeJ+fhk3xN5uTkcRtzAZjOOo9yOA2fA++x7d0sSZ5prT0/37UtJkaKjjXYtPt6kkBCjXQgNdbjFe+x2nen1Zjymp5tcF4KTkkxnxvGVUlNN8vNznGm7jDYpKcloM6OijPXY7VKlSsZ6wsONtsgY+9voOeccJzstTa607mlpxqPz/6wsI1bg7W30FvL0zK6b8f3qzLZhZNxwpsR1BqAtZzIDnJ2mz7iJIbud9fc3yj77Ar+np+PMzVjGfEX1mS2IqCiTbr/dS2PHZqhDh8tzXn5uG3DqlNSvn/dlrUNx8uOPFr35pod+/jmtWH9WzmWzSd26eeuxxzJ18835p0IGzuZsA4qzMpneMzg4WBaLRbHnDEwaGxur0LPv+s+H3e6QPZ+BQFE22Gx2ZWWVvS90AAbaAKBsow1AWVO1qlS1qk1dumRPS0qSjpxJ71elit3thuz8ODukm83Gjc81auS82GK3O3t+mZSUZFwcrV/fLk/P83dod2rdOkszZ3oqKcnu1lG3MFxoG7BkiVXVqtlVp44tz/o7Uy+mp9uVlZX9ezMpyQiAenjkvk5PT6lDB7s6dMjxUg4Oh7NjhlnHj5sUHW3SqVNGcC8qyqRdu8wKDnYoPNyuFi2Mx3Ll5Bqb09vbCOhGRpoUGWl2PZ6vU3pAgEPdutlUt65ddevaz6RxO399C1tuKSuBi3EhbYCz44lzPNai4uyFmN9x4OFR8Da2uDk7yczZPD2Nzmlnd1BzOndbnb1Hzg4GlmVF/Zk9n/LljeDk7t0mtWlzeSvqbAPS0503KZXV3wamMz2n7K5kQiVBVJSRKjg01FZG3zeUZiXoUCw8np6eaty4sdasWaPrr79ekmS327VmzRoNGjSoiGsHAAAAACWDv7/UsOF/c6HEbJarF9j5xu/Iy5VX2jR1qrRli0Vt2xZdtCcxUVq1yqr77svIN9DlvFh2brajtDTjsTB63zjTzwUF2dWgwcWW4jiTYZ8IGgCg6JhMUp06du3dW3RdzJxB0ZLUy60wOdPu22wqUUG/6GjjhKxCBTr1oPQpQYdi4br33ns1cuRINWnSRM2aNdPs2bOVmpqqvn37FnXVAAAAAACFoFo1I63a+vWXHvSz26W//zbrt988dOqUlJLiKZstu0eJM72ac7ylWrXsatjQrgYNbPrjD6scDun66/PvPuNMkZmVZdLZgc60tOyUmAAAIFudOnatWFF0l7idqcjLatAvrx62xV1UlHFuVbEiQT+UPmU26HfjjTfq1KlTmjx5smJiYtSwYUNNnz69wOk9AQAAAADFm8lk9Pb76y+zHI4LG8stM9NIXxoba9Iff1j1889WnTxpUtWqDrVoIWVkGD0Qz77DPSvLeExONmnJEqvmzTNWaLVKbdvaFByc/zo9PIwLTxnnDEGYmmo8+vhwYQoAgLPVqWPXggUmJSYaGQIulsMhbd9ujI/bt29WgW+0cQa7nOcDZc3Z50ElSXS0SYGBjhI7himQnzIb9JOkQYMGkc4TAAAAAEqxK6+06fvvrYqMNCkiIv+g2cqVFk2d6qm4OJNb4C0gwKFrr7Xp+uuz1LSpVL68VXFxmfmOAeNwGHeR79xp1t69ZnXpcv5Bspxpsc69cOZM7+kcFwwAABhq1za+i/fuNeuKKy485XhqqvTrr1Z9/71V+/YZ3dYOHjRr9Oj8U3I7lfX0nnmduxR30dFmUnui1CrTQT8AAAAAQOnWooVNVqu0fr1FERF5B95WrbJo3DgvtW5tU9++NgUEOOTvbwT86tWzy9PTmM9kKthVPZNJCg93KDzcpuuuK9iVMGd6z5xj+hlXHenpBwCAu6pVHfLyclxU0G/pUuNmn+Rkk9q2tem++9KUnGzS+PFeqlXLroED3c8bEhOlN97wVJ060tChxjRnsKusBv2y03u6pyYv7qKiTKT2RKlF0A8AAAAAUGr5+EjNmtn0118W9e2be9BvzRqLxo710lVXZem55zKKLEWX8275zEz3rgXO9J6M6QcAgDuzWapVy+HqpVdQS5daNGmSl66/Pkt3352p8PDsANChQ5maOdNT1as71L69EdWLjDTp+ee9dOyYWQcOSEOGGPOW9Z5+Foux3/Lr6XfqlHT0qFknT5p08qRJsbHGec5dd2XKz+9y1DKnqCiTWrcuYd0TgQIi6AcAAAAAKNXatLFpxgxPpaXlDJytXWvRq696qV07m0aPLrqAnyR5ehoXznLr6We1ZgcFAQBAtjp17NqyxT3qduKESS++6KWrrrJp4MBMt+//X36x6O23vdSzZ5YefzxnGs+77srUgQNmTZjgqcmT05SYaNKYMV4KCHBo+PBMffSRRZGRJoWHG+m8pbIc9DMe7Wd1sty926xVqyzau9dIcR4Xl72DfXwcCg116ORJk/bvN2vcuHRXNoVLlZlpnCudLy2rkYLdrIoVz596HSiJymhzBAAAAAAoK6680qbMTOnvv90jeuvWWfTKK1668kqbnnsuvciDas4LZ1nnXINKSyO1JwAAeald266jR82uMXBtNmn8eC/FxZn05ZceGjrUR6tWWeRwSH/8YdHEiV664YYsPfZY7uP2mc3SyJHpqljRodGjvfXss96qUcOu999P0/XXG73DduwwLqtnZRkFOHu8lTXnnrvExJj09NNe+vFHq0wmqXv3LL30UrqmT0/V4sUp+u67VM2cmaaxY9O1fbtFb7zh6RYwvFAOh/T330aAtndvXz3xhLeiovKP+sXHSxkZYkw/lFrcJwgAAAAAKNWqVnUoPNyhv/6yqF0742Ld4sVWffihp9q0semFF9Jd4+kVJWcdzg36paaaSO0JAEAe6tSxy26X9u83q1Eju+bM8dDu3Wa9806aAgMd+vBDT40Z46UmTWzaudOi667L0lNPZeTbO8/XV3rttXQ9/ri3unQxegR6eBg9yWrVkrZtM6tzZ9J7OoN+zvSeM2Z4yMdHmjUrVf7+eS/XrJldzz+frldf9dIHH0jDh2cHYOPipJ9/tioy0iyHQ64/s1ny8nLI21vy9nYoI8Ok336z6Ngxs6pUsWvgwEwtX27Vgw9666mnMnT11bmn74yKMt4sxvRDaUXQDwAAAABQqplMRm+/v/4yy2aTPvrIQ4sXe6hv30wNG5ZZbC7U5TWmn5GWlAtTAADkpmZNu8xmad8+s7KypC++8NDdd2eoUSMjIjduXLrWrrXoo4881KlTlp55Jv+An1N4uENffJGaY97mzaUNG4yJBP2MR5tN2r7drF9+seqppzLyDfg5XXWVTY8+mqH33vNUcLBD9erZ9OOPHlqzxiKTSapRw+7aryaTEfhLT5fS001KSzPW2aaNTU8/naGmTe0ymaS+fTM1aZKXXn3VSzffnKVhwzJypA+NjjbOsypWvIQuhkAxRtAPAAAAAFDqtWlj0/ffW/XUU97atcusxx7LUK9exWssF5PJCPzlNqYfPf0AAMidp6dUvbpdmzebNW+eh5o0sWngwOzveJNJat/epnbtbOcd7+1cuQXzmjeXFi40KSkpO+hXlGMCF6Xs9J4mffihp+rUsatbt4KfX910U5bi4kyaPdtDkodq1LBr2LAMdemSpcDAC6+Pv7/00kvp+t//rProI09FR5v02mvpbvNER5vk5eW4qPKBkoCgHwAAAACg1Gve3CYPD+nQIZPGj09Tq1bF8+5uDw8HY/oBAHCBate26+efrQoIcGjkyNx78l1owC8vzZoZvc527DDLy8uYVnZ7+hnnJ8uWWfXvv2a9/XbaBe+LQYMyVaWKXZUrO1S/vv2S3yeTSa4bu6ZM8VRiohQQkP16VJRJFSo4Cu3zABQ3ZbQ5AgAAAACUJT4+0muvpWnKlOIb8JNy7+nHmH4AAOSvXj3ju/3JJzNUocJ/e6NM1apSuXLS9u0W11h2ZbWnnzPA97//WXXttVlq2vTCz7FMJqlzZ5saNLj0gN/Z2rWzyW6XNm50f3OiosyM54dSjZ5+AAAAAIAyoTgH+5ysViNF1tnS0iR/fy5OAQCQl27dslStmv2yfNebTFLjxnbt2GFW06Y217SyyDkesdUqDR2amf/Ml1lYmEM1atj1118WXXutzTU9KsqkBg2K/zkhcLHo6QcAAAAAQDHh6SllZLhPS0szycenaOoDAEBJ4Ot7eW/uadLErl27zMrMNKJ9ZTW9p4eH8ThgQGax7D135ZU2/fWXRY6zqhYdbVKFCgT9UHqV0eYIAAAAAIDix2p1uFKFOaWlyTVmEAAAKHpNmtiVlmbS3r3G5XXn2HZlTYUKDo0Zk66BA4tXLz+n1q1tioszaf9+IzibkiIlJpqKZYASKCwE/QAAAAAAKCZyH9NP8vHh4hQAAMVFvXp2Wa3S1q3G5fWy2tPPZJKuusomT8+irknumjSxy9vbob/+Msb1i442gn//9biPQFEqo80RAAAAAADFT25j+qWmkt4TAIDixNPTCPzt2OHs6VfEFUKuPD2lFi3sBP1QphD0AwAAAACgmMhtTL/0dMnbm4tTAAAUJ40a2ZSeXrbH9CsJrrzSpu3bLUpOlqKizDKbpdBQzqtQetEcAQAAAABQTHh4OJSVlf3c4ZDS0kyM6QcAQDHTqJHd9T9Bv+LryittstmkzZstio42KSzMQc9MlGrWoq4AAAAAAAAwWCxyC/qlpxuBP19f7kgHAKA4adzY5vqfIFLxVamSQ1Wq2LVhg0UpKVLFivbzLwSUYNyDAAAAAABAMeHhIWVmZo/pl5ZmPHp7F1GFAABArsqXlypVMgJI9PQr3q680qa//rIoKsqssDBupELpRnMEAAAAAEAxYQT9sp+npRkBQMb0AwCg+HGm+CToV7xdeaVN0dEm/fuvWRUrck6F0o3mCAAAAACAYuLcMf1SU41HevoBAFD8tG5tU2Cgg6BfMde8uV0eHkYK9QoVCPqhdKM5AgAAAACgmDh3TD96+gEAUHx16WLTZ5+lFnU1cB5eXlLz5sYYjIzph9KOoB8AAAAAAMVEXmP6+fgUUYUAAECeTCbJz6+oa4GCuPJKZ9CPG6lQulmLugIAAAAAAMDAmH4AAACFr2vXLGVmSlWqcE6F0o2gHwAAAAAAxQRj+gEAABS+gABpwICs888IlHCk9wQAAAAAoJiwWnPv6eflVUQVAgAAAFBiEPQDAAAAAKCYsFqlrKzsMf1SU43UnmZ+vQMAAAA4D342AAAAAABQTHh6ShkZ2c/T00ntCQAAAKBgCPoBAAAAAFBMWK0O2WzZz1NTTQT9AAAAABQIQT8AAAAAAIqJc8f0S02VfHwcRVchAAAAACUGQT8AAAAAAIoJDw/3Mf3S0ujpBwAAAKBgCPoBAAAAAFBMGEE/yW43nhtj+tHTDwAAAMD5EfQDAAAAAKCY8PAwAnxZWcZzxvQDAAAAUFAE/QAAAAAAKCYsFuMxO+jHmH4AAAAACoagHwAAAAAAxYSHh/HoDPoxph8AAACAgiLoBwAAAABAMeEM+mVkmCRJaWmM6QcAAACgYAj6AQAAAABQTJw7ph89/QAAAAAUFEE/AAAAAACKCavVeMwO+jGmHwAAAICCIegHAAAAAEAx4Qz6ZWYaj6mpJvn4FF19AAAAAJQcBP0AAAAAACgmPD2NXn2ZmSbZ7Ubwz8uLnn4AAAAAzo+gHwAAAAAAxcTZPf1SU43/GdMPAAAAQEEQ9AMAAAAAoJhwBv1sNiO1pyTSewIAAAAoEIJ+AAAAAAAUEx4exmNmppSWZvzv40N6TwAAAADnR9APAAAAAIBiwsMje0y/9HRjmpdXEVYIAAAAQIlB0A8AAAAAgGLi7J5+KSlGek9vb3r6AQAAADg/gn4AAAAAABQTFovxmJV1dnrPoqsPAAAAgJKDoB8AAAAAAMWEs6efEfQzevoxph8AAACAgrAWdQUAAAAAAIDBeuZXekaGSZIR7GNMPwAAAAAFQdAPAAAAAIBiwmQyAn9ZWZLdbpLFkt37DwAAAADyQ9APAAAAAIBixMPDoawsyWaTvL0dMpmKukYAAAAASgKCfgAAAAAAFCNWq5SZaaT49PYu6toAAAAAKCnMRV0BAAAAAACQzcNDysw0KS3N6OkHAAAAAAVB0A8AAAAAgGLECPpJaWn09AMAAABQcAT9AAAAAAAoRqxWh2w2KSVF8vGhpx8AAACAgiHoBwAAAABAMeIc0y893SQfn6KuDQAAAICSgqAfAAAAAADFyNlj+nl5FXVtAAAAAJQUBP0AAAAAAChGnGP6paZK3t6k9wQAAABQMAT9AAAAAAAoRjw8HMrKktLSSO8JAAAAoOAI+gEAAAAAUIxYLDoT9JN8fOjpBwAAAKBgCPoBAAAAAFCMeHpKGRkmpaaaGNMPAAAAQIER9AMAAAAAoBixWunpBwAAAODCEfQDAAAAAKAY8fBwKDPTGNPP27uoawMAAACgpCDoBwAAAABAMWKxSCkpJtnt9PQDAAAAUHAE/QAAAAAAKEY8PaWkJON/evoBAAAAKCiCfgAAAAAAFCNWq5SYaJIkeXvT0w8AAABAwRD0AwAAAACgGPHwcCgpyRn0K+LKAAAAACgxCPoBAAAAAFCMWK2S40wHP8b0AwAAAFBQBP0AAAAAAChGPDyy/6enHwAAAICCIugHAAAAAEAxQtAPAAAAwMUg6AcAAAAAQDFitWan9CS9JwAAAICCKlFBv48++kgDBw5U8+bN1bp161znOXbsmB544AE1b95c7du31xtvvKGsrCy3edatW6dbbrlFTZo0UdeuXfXNN99cjuoDAAAAAHBeVmv2//T0AwAAAFBQJSrol5mZqe7du+v222/P9XWbzaZhw4YpMzNT8+fP1+uvv65FixZp8uTJrnmOHDmiYcOGqW3btlq8eLHuvvtuvfDCC1q5cuXl2gwAAAAAAPLk6Wk8enhI5hL1qx0AAABAUbKef5bi47HHHpOkPHvm/fnnn9q7d69mzZql0NBQNWzYUI8//rjeeustDR8+XJ6enpo/f74iIiI0atQoSVLt2rW1ceNGffrpp7r66qsv27YAAAAAAJAbZ08/UnsCAAAAuBAlKuh3Pn///bfq1aun0NBQ17SOHTtqzJgx2rt3rxo1aqS///5b7du3d1uuY8eOGj9+/AWty2w2yWw2FUq9UfJYLGa3RwBlC20AULbRBgBl2+VoA7y9TTKZJF9fyWqlrQGKE84DgLKNNgAo20rCsV+qgn4nT550C/hJcj2PiYnJd56kpCSlpaXJu4ADJpQv7yeTiaBfWRcY6FPUVQBQhGgDgLKNNgAo2/7LNiAoSLJYpMBAKTi4VP1sB0oNzgOAso02AEBxVeS/Ht566y198skn+c6zZMkS1a5d+zLVqGBOnUqmp18ZZrGYFRjoo4SEVNls9qKuDoDLjDYAKNtoA4Cy7XK0AenpZtlsnrJY7IqLy/hP1gHg4nAeAJRttAFA2eZsA4qzIg/63Xfffbrlllvynadq1aoFKis0NFT//POP27STJ09KksLCwlzzOKedPY+/v3+Be/lJkt3ukN3O+Aplnc1mV1YWX/BAWUUbAJRttAFA2fZftgEmk0kOh+Tp6aCdAYopzgOAso02AEBxVeRBv/Lly6t8+fKFUlaLFi308ccfKzY2ViEhIZKk1atXy9/fX3Xq1HHNs2LFCrflVq9erRYtWhRKHQAAAAAAuBQeHsYNpj7F+yZiAAAAAMVM8R918CzHjh3Tzp07dezYMdlsNu3cuVM7d+5UcnKyJKljx46qU6eOnn32We3atUsrV67Uu+++qzvvvFOenp6SpIEDB+rIkSOaOHGi9u3bp7lz5+rHH3/UPffcU4RbBgAAAACAwXrm9lxvb7LLAAAAACi4Iu/pdyEmT56sRYsWuZ736dNHkvTZZ5+pbdu2slgs+vjjjzVmzBgNGDBAPj4+uuWWW/TYY4+5lqlataqmTp2qCRMm6LPPPlN4eLjGjh2rq6+++nJvDgAAAAAAOXh4GI8XMAIFAAAAAMjkcDi4dfAixMQkFnUVUISsVrOCg/0UF5dM/m6gDKINAMo22gCgbLscbcDevSY99JCP+vTJ1COPZP4n6wBwcTgPAMo22gCgbHO2AcVZiUrvCQAAAABAaedM78mYfgAAAAAuBEE/AAAAAACKEcb0AwAAAHAxCPoBAAAAAFCMMKYfAAAAgItB0A8AAAAAgGLEw8Po4Ud6TwAAAAAXgqAfAAAAAADFiKen8Uh6TwAAAAAXgqAfAAAAAADFiL+/9Oyz6Wrb1lbUVQEAAABQgliLugIAAAAAAMBd164E/AAAAABcGHr6AQAAAAAAAAAAACUcQT8AAAAAAAAAAACghCPoBwAAAAAAAAAAAJRwBP0AAAAAAAAAAACAEo6gHwAAAAAAAAAAAFDCEfQDAAAAAAAAAAAASjiCfgAAAAAAAAAAAEAJR9APAAAAAAAAAAAAKOEI+gEAAAAAAAAAAAAlHEE/AAAAAAAAAAAAoIQj6AcAAAAAAAAAAACUcAT9AAAAAAAAAAAAgBKOoB8AAAAAAAAAAABQwhH0AwAAAAAAAAAAAEo4gn4AAAAAAAAAAABACUfQDwAAAAAAAAAAACjhCPoBAAAAAAAAAAAAJRxBPwAAAAAAAAAAAKCEI+gHAAAAAAAAAAAAlHAmh8PhKOpKAAAAAAAAAAAAALh49PQDAAAAAAAAAAAASjiCfgAAAAAAAAAAAEAJR9APAAAAAAAAAAAAKOEI+gEAAAAAAAAAAAAlHEE/AAAAAAAAAAAAoIQj6AcAAAAAAAAAAACUcAT9AAAAAAAAAAAAgBKOoB8AAAAAAAAAAABQwhH0AwAAAAAAAAAAAEo4gn4AAAAAAAAAAABACUfQD6XC3Llz1blzZzVt2lT9+/fXP//8k2OezZs366677lKLFi3UsmVL3XnnnUpLS8u33GPHjumBBx5Q8+bN1b59e73xxhvKyspyvb5u3TrVr18/x19MTEyeZaanp2vUqFHq1auXGjVqpIcffjjfOmzcuFGNGjVS7969z7MXgLKrtLUBF1MuUJaVtjZAkjIyMvTOO+/ouuuuU5MmTdS5c2d9/fXXBdwjQNlS2tqAUaNG5Vpuz549L2CvAGVHaWsDJOm7777TzTffrObNm6tjx44aPXq04uLiCrhHgLKlNLYBc+fOVY8ePdSsWTN169ZN3377bcF2BlAGlaQ2YN26dXrooYfUsWNHtWjRQr1799Z3332XY74ff/xR3bt3V9OmTdWrVy/98ccfF7BHJOsFzQ0UQ0uWLNGECRP0yiuvqHnz5po9e7aGDBmipUuXKiQkRJJxYA8dOlTDhg3Tiy++KIvFol27dslszjvubbPZNGzYMIWGhmr+/PmKjo7WyJEj5eHhoaeeespt3qVLl8rf39/13LnevMr18vLS4MGDtWzZsny3LSEhQSNHjlT79u118uTJguwOoMwpzW3AhZQLlFWltQ14/PHHFRsbq3HjxqlatWqKiYmR3W4v6G4ByozS2AY8//zzevrpp92W6d27t7p3716gfQKUJaWxDdi4caNGjhyp0aNH67rrrlNUVJTGjBmjF198UVOmTLmQ3QOUeqWxDZg3b54mTZqksWPHqmnTpvrnn3/0wgsvKDAwUJ07d76Q3QOUeiWtDdi8ebPq16+v+++/X6Ghofrtt980cuRIBQQE6LrrrpMkbdq0SU8//bSeeuopXXfddfr+++/1yCOP6JtvvlG9evUKtmMcQAnXr18/xyuvvOJ6brPZHB07dnRMnTrVNa1///6Od95554LK/f333x0NGjRwxMTEuKbNmzfP0bJlS0d6errD4XA41q5d66hXr54jPj7+ouo+cuRIx0MPPZTn60888YTjnXfecUyePNlx8803X9Q6gNKuNLYBl1ouUJaUxjbgjz/+cLRq1coRFxd3UeUCZUlpbAPOtXz5ckf9+vUdR48evaj1AKVZaWwDpk+f7ujSpYvbtM8++8xx9dVXX9R6gNKsNLYBAwYMcLz++utu0yZMmOAYOHDgRa0HKM1KchvgdP/99ztGjRrlev744487HnjgAbd5+vfv73jxxRcLXCbpPVGiZWRkaPv27erQoYNrmtlsVocOHbR582ZJUmxsrLZs2aKQkBANHDhQHTp00KBBg7Rhw4Z8y/77779Vr149hYaGuqZ17NhRSUlJ2rt3r9u8ffr0UceOHXXvvfdq48aNhbJtCxcu1JEjRzR8+PBCKQ8ojUpzG/BflguUFqW1Dfj111/VpEkTTZ8+XVdffbW6deumN95447zpR4CyprS2Aef6+uuv1aFDB1WpUqXQywZKstLaBrRo0UInTpzQH3/8IYfDoZMnT2rZsmXq1KnTJZcNlCaltQ3IyMiQl5eX2zQvLy9t3bpVmZmZl1w+UFqUljYgMTFRQUFBbutu37692zwdO3bU33//XeAyCfqhRIuLi5PNZsvRbTYkJMSVDvPIkSOSpClTpqh///6aPn26GjVqpHvuuUcHDx7Ms+yTJ0+6HdiSXM+duXnDwsL0yiuvaPLkyZo8ebLCw8N11113afv27Ze0XQcPHtSkSZP05ptvymolCy+Ql9LaBvxX5QKlTWltA44cOaKNGzdqz549+uCDD/Tcc89p2bJleuWVVy6pXKC0Ka1twNmioqK0YsUK9evXr9DKBEqL0toGtGrVSm+++aaeeOIJNWnSRFdddZX8/f310ksvXVK5QGlTWtuAjh076uuvv9a2bdvkcDi0detWff3118rMzGRsT+AspaENWLJkibZu3aq+ffvmu+6zt6kgiCag1HOOfzNgwADdeuutkqRGjRppzZo1WrhwoZ5++mkNHTrUFYmvXLmyfvjhhwKVXatWLdWqVcv1vGXLljpy5Ig+/fRTvfnmmxdVX5vNpqefflqPPvqoataseVFlAMhW0tqA/7JcoCwqiW2Aw+GQyWTSW2+9pYCAAEnSqFGj9Nhjj+nll1+Wt7f3RZcNlDUlsQ0427fffquAgABdf/31hVIeUNaUxDZg7969GjdunB555BF17NhRMTExmjhxol5++WWNHz/+ossFyqKS2AY8/PDDiomJ0YABA+RwOBQSEqI+ffpo+vTp+Y5BBiCn4twGrF27Vs8995zGjh2runXrXuim5YugH0q04OBgWSwWxcbGuk2PjY11RcTDwsIkSbVr13abp3bt2jp27Jgkady4ca6UWc6edaGhofrnn3/clnFG1J1l5qZp06batGnTxW6SkpOTtW3bNu3cuVOvvfaaJKOBcjgcatSokWbMmJGjiy9QVpXGNuBylwuUZKW1DQgLC1PFihVdAT9nfR0Oh06cOKEaNWpcUvlAaVFa2wAnh8OhhQsXqnfv3vL09CyUMoHSpLS2AVOnTlXLli01dOhQSVKDBg3k4+OjO++8U0888YQqVKhwSeUDpUVpbQO8vb01YcIEvfrqq4qNjVVYWJi+/PJL+fn5qXz58pdUNlCalOQ2YP369XrooYc0evRo9enTx+210NDQHL36zt6mguD2AJRonp6eaty4sdasWeOaZrfbtWbNGl1xxRWSpIiICFWoUEEHDhxwW/bgwYOucTEqVqyo6tWrq3r16q5pLVq00L///uvWcKxevVr+/v6qU6dOnnXatWtXvgf/+fj7++v777/Xt99+6/obOHCgatasqW+//VbNmze/6LKB0qY0tgGXu1ygJCutbUDLli0VHR2t5ORk17QDBw7IbDYrPDz8ksoGSpPS2gY4rV+/XocOHSK1J5CH0toGpKWl5ejNY7FYJBk3AwAwlNY2wMnDw0Ph4eGyWCxasmSJrrvuOnr6AWcpqW3AunXrNGzYMI0YMUIDBgzI8XqLFi20du1at2mrV69WixYt8i33bPT0Q4l37733auTIkWrSpImaNWum2bNnKzU11ZUL12QyaciQIXr//ffVoEEDNWzYUIsWLdL+/fs1efLkPMvt2LGj6tSpo2effVbPPPOMYmJi9O677+rOO+903Wn76aefKiIiQnXr1lV6eroWLFigtWvXaubMmfnWee/evcrMzNTp06eVnJysnTt3SpIaNmwos9msevXquc0fEhIiLy+vHNMBlL424FLKBcqi0tgG3HTTTfrwww81evRoPfbYY4qLi9Obb76pW2+9ldSewDlKYxvg9PXXX6t58+b8BgDyURrbgOuuu04vvvii5s2bp6uvvlrR0dEaP368mjVrpooVKxbGbgNKjdLYBhw4cED//POPmjdvroSEBM2aNUt79uzR66+/Xhi7DChVSlobsHbtWj344IO66667dMMNN7jGB/Tw8FBQUJAk6a677tLgwYM1c+ZMderUSUuWLNG2bdv06quvFni/mBzcJoRS4PPPP9eMGTMUExOjhg0b6oUXXsjRI27atGmaO3eu4uPj1aBBA40YMUKtW7fOt9zIyEiNGTNG69evl4+Pj2655RY9/fTTrq6+n3zyib766itFRUXJx8dH9erV0yOPPKJ27drlW27nzp0VGRmZY/ru3btznf/999/Xzz//rMWLF+dbLlBWlbY24GLLBcqq0tYGSNK+ffs0duxYbdq0SUFBQerRo4eeeOIJgn5ALkpjG5CYmKiOHTvq+eef12233VbQXQGUSaWxDZgzZ47mz5+vo0ePKiAgQO3atdMzzzxD0A/IRWlrA/bt26enn35aBw4ckNVqVdu2bTVixAi3scMAZCtJbcCoUaO0aNGiHNPbtGmjOXPmuJ7/+OOPevfddxUZGakaNWromWeeUadOnQq8Twj6AQAAAAAAAAAAACUciYABAAAAAAAAAACAEo6gHwAAAAAAAAAAAFDCEfQDAAAAAAAAAAAASjiCfgAAAAAAAAAAAEAJR9APAAAAAAAAAAAAKOEI+gEAAAAAAAAAAAAlHEE/AAAAAAAAAAAAoIQj6AcAAAAAAAAAAACUcAT9AAAAAAAAAAAAgBKOoB8AAAAAAAAAAABQwhH0AwAAAAAAAAAAAEo4gn4AAAAAAAAAAABACUfQDwAAAAAAAAAAACjhCPoBAAAAAAAAAAAAJRxBPwAAAAAAAAAAAKCEI+gHAAAAAAAAAAAAlHAE/QAAAAAAAAAAAIASjqAfAAAASqT3339f9evXL+pq/Ofq16+v999/v9DK++abb1S/fn0dPXq00Mq8HAp7P6xbt07169fXunXrCq1Mp9L02Tx3v+f2+Rk8eLAGDx7seu7ct0uXLr2kdZ9bbkl1IZ8H57ynTp36j2tV+AryWSlunHXcunVrUVdF0n9Tn1GjRqlz587nne/o0aOqX7++vvnmm0JbNwAAAC4/a1FXAAAAACVLQS9ef/bZZ2rbtu0lrSs1NVXTp09XmzZtLrmswjRq1CgtWrTI9dzPz08RERHq06ePBg0aJE9PzyKs3X/Lbrfru+++09y5c3Xo0CFlZmaqQoUKat68ue644w61aNGiqKtYqL755huNHj3a9dzT01PlypVT/fr11alTJ/Xt21f+/v5FWEOURB9//LHq1Kmj66+/vlDKW7dune66664Czbt79+5CWWdxdPToUXXp0qVA8/7yyy//cW0AAACAy4+gHwAAAC7IxIkT3Z4vXrxYq1atyjG9du3al7yu1NRUTZkyRcOHD88R9HvooYf0wAMPXPI6Lpanp6fGjh0rSUpMTNSyZcv0xhtvaOvWrXrnnXcKbT3//POPLBZLoZV3qcaOHau5c+eqS5cu6tWrlywWiw4cOKCVK1eqatWqpS7o5/TYY48pIiJCWVlZOnnypNavX6/x48fr008/1YcffqgGDRq45i3qz2ZhKsjnb8aMGf/Juv+rci+33D4PU6dOVbdu3Qot6Fe7du0cbfDbb78tX19fPfjgg4WyjgvVu3dv9ezZ87LeBFG+fPkc+2HWrFk6ceKEW/DeOS8AAABQ2hD0AwAAwAXp3bu32/MtW7Zo1apVOab/16xWq6zWojudtVqtbtt8xx13qH///lqyZIlGjRqlihUrXnTZdrtdmZmZ8vLykpeXV2FUt1CcPHlS8+bN02233abXXnvN7TWHw1EiUxIW1DXXXKOmTZu6ng8bNkxr1qzRgw8+qIcfflhLliyRt7e3pKL/bBamgnz+Cjuok5qaKh8fn1LTY/ZyfB5CQ0NztMGffPKJgoOD822bz25rCpvFYrnsNyz4+vrm2N4lS5YoISGh0L+jHA6H0tPTXcc9AAAAUBwwph8AAAAKnd1u16effqqePXuqadOm6tChg1566SXFx8e7zbd161YNGTJEbdu2VbNmzdS5c2dXb4yjR4+qffv2kqQpU6aofv36bmNG5TZOVv369fXqq6/q559/1k033aQmTZqoZ8+eWrFiRY46rlu3Tn379lXTpk11/fXXa/78+Zc0FpvZbFabNm0kSZGRkZKkjIwMTZ48WV27dlWTJk3UqVMnTZw4URkZGbnW+7vvvnPts5UrV7peO3csux07dmjo0KFq2bKlrrjiCt199936+++/c9Rpz549uuuuu9SsWTNdc801+vDDD2W323PMl5iYqH379ikxMTHfbTx69KgcDodatmyZ4zWTyaSQkBC3aQkJCRo/frw6d+6sJk2a6JprrtGzzz7rCg5mZGTovffeU9++fdWqVSu1aNFCd9xxh9auXZtvPZyioqI0evRodejQwfVef/311znmO3HihB5++GG1aNFC7du31/jx43O8Bxejffv2evjhhxUZGanvvvvONT23z9GqVat0++23q3Xr1rriiivUrVs3vf322wVaT0JCgsaNG6dOnTqpSZMm6tq1q6ZNm5bjvUxISNCoUaPUqlUrtW7dWiNHjtTOnTtzjNOV11h5uY39VZCxFPMqz2636+2339ZVV12lFi1a6MEHH9Tx48dzLHvTTTdp27ZtuvPOO9W8eXPXfjm33LzGiMttfEZnubt27dKgQYPUvHlzde3a1TXO4Pr169W/f381a9ZM3bp10+rVq/PdRofDobZt22rChAlu29e6dWs1bNhQCQkJrunTpk1To0aNlJycLCnn56F+/fpKSUnRokWLXO3aqFGj3NaXmJioUaNGqXXr1mrVqpVGjx6t1NTUfOtYEPm1NTNmzNDAgQNd7XHfvn1zHZcxIyND48ePV7t27XTFFVfowQcf1IkTJ3LMl9v71blzZw0bNkwbNmxQv3791LRpU3Xp0kXffvttjuWd793Z7dfChQv/k3ECMzIyNGHCBLVr104tWrTQI488kuMmBmfdV65cqb59+6pZs2aaP3++pIIfoz/88IP69u2rK664Qi1btlSvXr00e/bsi6qPJM2dO1c9e/ZUkyZN1LFjR73yyitun8W85NZW5Nb+x8TEaPTo0brmmmtc63jooYeK9TiNAAAAZV3puP0UAAAAxcpLL72kRYsWqW/fvho8eLCOHj2quXPnaseOHfriiy/k4eGh2NhYDRkyRMHBwXrggQcUGBioo0ePavny5ZKM1GtjxozRmDFj1LVrV3Xt2lXS+ccU3Lhxo3766Sfdcccd8vPz05w5c/TYY4/pt99+U3BwsKTsoFlYWJgeffRR2e12ffDBB5ec7u3IkSOSpKCgINntdj300EPauHGjbrvtNtWuXVv//vuvZs+erYMHD+rDDz90W3bt2rX68ccfdeeddyo4OFhVqlTJdR179uzRnXfeKT8/Pw0dOlRWq1VffvmlBg8erM8//1zNmzeXZFysveuuu2Sz2fTAAw/Ix8dHX331Va49epYvX67Ro0drwoQJ6tu3b57bV7lyZUnS0qVL1b17d/n4+OQ5b3Jysu68807t27dPt956qxo1aqS4uDj9+uuvioqKUvny5ZWUlKQFCxbopptuUv/+/ZWcnKyvv/5aQ4cO1YIFC9SwYcM8yz958qRuu+02mUwm3XnnnSpfvrxWrFih559/XklJSbrnnnskSWlpabr77rt1/PhxDR48WBUqVNDixYsLHFg8n969e+vtt9/Wn3/+qdtuuy3Xefbs2aNhw4apfv36euyxx+Tp6alDhw5p06ZN5y0/NTVVgwYNUlRUlAYOHKhKlSpp8+bNevvttxUTE6Pnn39ekhGUevjhh7Vx40YNHDhQtWvX1vLlyzVy5MhC2c6L8dFHH8lkMun+++9XbGysZs+erXvuuUeLFy926x11+vRp3X///erZs6duvvnmHMHjixUfH68HH3xQN954o7p3764vvvhCTz31lOx2u8aPH6+BAwfqpptu0owZM/TYY4/p999/z3N8RpPJpJYtW+qvv/5yTdu9e7cSExNlNpu1adMmXXvttZKMNqhhw4by8/PLtayJEyfqhRdeULNmzVyfmWrVqrnN88QTTygiIkJPPfWUduzYoQULFqh8+fJ65plnLnm/5NXWfPbZZ+rcubN69eqlzMxM/fDDD3r88cc1depU17ZJ0vPPP6/vvvtON910k1q2bKm1a9deUDrbQ4cO6fHHH1e/fv10yy23aOHChRo1apQaN26sunXrSjIC+nfffbck6YEHHpCvr68WLFjwn/X+HDt2rAIDAzV8+HBFRkZq9uzZevXVV/Xuu++6zXfgwAE9/fTTGjBggG677TbVrFmzwMfoqlWr9NRTT6l9+/YaMWKEJGn//v3atGmTa1svpD7vv/++pkyZog4dOuj222/XgQMH9MUXX2jr1q2u79ncXEhb8eijj2rv3r0aNGiQqlSpolOnTmnVqlU6fvy4IiIiLmGPAwAA4L9C0A8AAACFasOGDVqwYIHeeust9erVyzW9bdu2Gjp0qJYuXapevXpp8+bNio+P14wZM9zSJj755JOSjDRt3bp105gxY1S/fv0Cp2bbt2+flixZ4rqI3rZtW/Xu3Vs//PCDBg0aJEmaPHmyLBaLvvjiC1cazh49eujGG2+8oG119rxISkrSjz/+qJ9//ln169dXrVq1tHjxYq1evVpz5sxR69atXcvUrVtXL7/8sjZt2uTWY+7AgQP6/vvvVadOnXzX+e677yozM1NffPGFqlatKknq06ePunfvrjfffFOff/65JCO136lTp7RgwQI1a9ZMknTLLbfohhtuuKBtPFuFChXUp08fffvtt+rUqZPatGmjli1bqlOnTjnGcJwxY4b+/fdfTZkyxRWwlaSHH35YDodDklSuXDn9+uuvbhfyb7vtNvXo0UNz5szR+PHj86zLO++8I5vNpu+//94VzL399tv11FNPacqUKRo4cKC8vb315Zdf6uDBg3r33XfVo0cP1zoKK9VfeHi4AgICXAHf3KxatUqZmZn65JNPLjiwPGvWLB05ckSLFi1SjRo1JEkDBw5UhQoVNGPGDN13332qVKmSfvnlF/3111965plnNHToUEnG/rjrrrsuetsuVXx8vJYsWeIKpDVq1EhPPPGEvvrqK7d6xcTE6JVXXtHAgQMLdf3R0dGaNGmSbrrpJklShw4d1KNHDz399NOaP3++K0Beu3ZtDRkyRD/99FO+Qe/WrVtr0qRJSkpKkr+/vzZs2KAqVaooJCREGzZs0LXXXiu73a5NmzblW07v3r01ZswYVa1aNc/PYcOGDd0+/6dPn9bXX39dKEG/vNqaZcuWuQVj77zzTvXt21ezZs1yBf127dql7777TnfccYdefvll13xPP/20du/eXeD1z50719Uu9ujRQ506ddI333zjCjx98sknio+P16JFi1zB/759+6pbt26XtO15CQoK0syZM2UymSQZvTjnzJmjxMREBQQEuOY7dOiQpk+frquvvto17cMPPyzQMeoMKs+YMeO8aU/PV59Tp05p6tSp6tixoz755BOZzUYSp1q1arl6ct566625ll3QtiIhIUGbN2/Ws88+qyFDhrimDxs2rCC7FAAAAEWE9J4AAAAoVEuXLlVAQICuuuoqnTp1yvXXuHFj+fr6ulLwOS+k/v7778rMzCy09Xfo0MGt10yDBg3k7+/vCsrYbDatWbNGXbp0cRt3r3r16m4Xcs8nJSVF7du3V/v27dW1a1e9/fbbatGihT744ANJxn6oXbu2atWq5bYf2rVrJ0luqQgl6corrzxvwM9ms2nVqlW6/vrrXQE/yQjG3XTTTdq4caOSkpIkSX/88YdatGjhCvhJRu/JswOxTn379tXu3bvzDVQ4TZgwQS+99JIiIiK0fPlyvfHGG7rxxht19913KyoqyjXfTz/9pAYNGrgF/JycF7ItFosr4Ge323X69GllZWWpSZMm2rFjR551cDgc+umnn9S5c2fXWILOv44dOyoxMVHbt2+XJK1YsUJhYWHq3r27a3kfH588e+VdDF9fX1cqx9wEBgZKMi6255ZeNT9Lly5Vq1atFBgY6LadHTp0kM1mc/U8W7FihaxWq26//XbXshaLxRXoLgp9+vRx6znXvXt3hYWF6Y8//nCbz9PTs0CfvQvl6+urnj17up7XqlVLgYGBql27tivgJ8n1f36BW8kI+tlsNm3evFmScYODMz3ihg0bJEn//vuvEhIS3AL9F+PcAGjr1q11+vRp1/F9KfJqa84O+MXHxysxMVGtWrVyOxad79256VzP7amWnzp16rjtn/Lly6tmzZpu+3/lypVq0aKFW2/foKCgXNuvwuDsNezkfK+dqZqdIiIicnxPFPQYDQwMVGpqqlatWnXJ9Vm9erUyMzN11113uQJ+ktS/f3/5+/vnOMbOVtC2wtvbWx4eHlq/fn2O1NwAAAAovujpBwAAgEJ16NAhJSYmusbjO1dsbKwkqU2bNurWrZumTJmiTz/9VG3atNH111+vXr16XVIKt0qVKuWYVq5cOdc4R7GxsUpLS1P16tVzzJfbtLx4eXnp448/lmQELSIiIhQeHu56/dChQ9q3b99594NTQVKlnTp1SqmpqapZs2aO12rXri273a7jx4+rbt26OnbsmFtgwym3ZS+E2WzWnXfeqTvvvFNxcXHatGmT5s+frxUrVujJJ5/UvHnzJEmHDx8uUK/CRYsWaebMmTpw4IBb8De//XHq1CklJCToyy+/1JdffpnnPJIxvmL16tXdLqBLl74fzpaSkpJvSsobb7xRCxYs0AsvvKBJkya5AsXdu3d3XbCPiYlxWyYgIEDe3t46dOiQdu/enefn6OztDAsLy5FSsjC380KdezyZTCZVr149RyClYsWK/0naxvDw8Bzve0BAgNtx6pwm6bxjoTVq1Eg+Pj7asGGDrr76am3cuFGPPvqoQkNDNWfOHKWnp2vjxo2SpFatWl1S3Z2pdJ2cgeP4+Pg8U5AWVF7H1m+//aaPPvpIO3fudBvz8ux9GBkZKbPZnCMdaa1atQq8/rza6LMDS5GRkWrRokWO+c5db2HJa3+f+5nIbd8V9Bi944479OOPP+r+++9XxYoVddVVV6lHjx665pprLrg+x44dk5Rzv3t6eqpq1ao5jrGzFbSt8PT01IgRI/TGG2/oqquuUvPmzXXttdeqT58+CgsLy7N8AAAAFC2CfgAAAChUdrtdISEheuutt3J93Zne0GQyafLkyfr777/122+/aeXKlXruuec0a9Ysffnll3mOh3U+eaVNc6aULCwWi0UdOnTI83W73a569epp9OjRub5+buDh7F42JUVwcLC6dOmiLl26aPDgwVq/fr0iIyPzHI/wXIsXL9aoUaN0/fXXa8iQIQoJCZHFYtHUqVPz7XXl7C13880365Zbbsl1nvON/VhYTpw4ocTExHyDEd7e3po7d67WrVun33//XStXrtSSJUv05ZdfaubMmbJYLOrYsaPbMs7xFe12u6666ipXGr5zOdMJFgabzVZoZV2Ign72zw3gOeXVezKvtuBi2wgPDw81a9ZMGzZs0KFDhxQTE6PWrVsrJCREWVlZ2rJlizZs2KBatWpd8vigZ/feupA6FkRu+3vDhg166KGHdOWVV+rll19WWFiYPDw8tHDhQv3vf/+75HWe7XypLYtCQfd3bvuuoMdoSEiIvv32W/35559asWKFVqxYoW+++UZ9+vTRG2+8cVH1+a/dc8896ty5s37++Wf9+eefeu+99zRt2jTNnj1bjRo1uqx1AQAAQMEQ9AMAAEChqlatmtasWaOWLVsW6GJ+ixYt1KJFCz355JP6/vvvNWLECC1ZskT9+/fP8yL/pQgJCZGXl5cOHTqU47Xcpl2satWqadeuXWrfvn2hbUf58uXl4+OjAwcO5Hht//79MpvNrl40lStXznV7clu2MDRp0kTr169XTEyMqlSpomrVqmnPnj35LrNs2TJVrVpVU6ZMcdtHkydPzne58uXLy8/PT3a7Pd/AqyRVqVJF//77rxwOh9s6Cms/LF68WJJyBO3OZTabXelgR48erY8//ljvvPOO1q1bpw4dOmjWrFlu8zvTL1arVk0pKSkF2s61a9cqOTnZLWCe23aWK1cu16Cqs/dQYTn38+dwOHTo0KGLDsg6ezslJia6Tc+vV1Nha926tT755BOtXr1awcHBqlWrlkwmk+rWrasNGzZow4YNuu666y5bfQrLsmXL5OXlpRkzZrj1uly4cKHbfFWqVJHdbtfhw4fdepnt37+/UOtTpUqVXNuvw4cPF+p6CkNBj1HJ6D3XuXNnde7cWXa7XWPGjNGXX36phx9++IJ6mjt7Au7fv98t1XNGRoaOHj2ab10upK2QjO277777dN999+ngwYPq06ePZs6cmeeNPQAAAChajOkHAACAQtWjRw/ZbDZ9+OGHOV7LyspypSeLj4/P0WvBOX6TM7Wcj4+PpPOn3bsQzh56v/zyi9sYdIcOHdLKlSsLbT09evRQVFSUvvrqqxyvpaWlKSUl5YLLtFgsuuqqq/TLL7/o6NGjruknT57U//73P7Vq1cqV+q9Tp076+++/9c8//7jmO3XqlL7//vsc5SYmJmrfvn05ginniomJ0d69e3NMz8jI0Jo1a9zS/t1www3atWuXli9fnmN+5/vu7PFz9udgy5Yt+vvvv/Oth8ViUbdu3bRs2TL9+++/OV53ptOTpGuuuUbR0dFaunSpa1pqamqu78uFWrNmjT788ENFRETo5ptvznO+06dP55h27me9Q4cObn8VKlSQZHyONm/enOtnMyEhQVlZWZKM7czKytIXX3zhet1ms+nzzz/PsVzVqlW1f/9+t/20a9cubdq0qQBbXXDffvut2xh0S5cuVUxMTK7pDAvC+dlyjpEmGdtYGO9lQbVu3VoZGRmaPXu2WrVq5Qokt2rVSosXL1Z0dHSBUnv6+voWart2qSwWi0wmk1tvz6NHj+qXX35xm8/53s2ZM8dt+uzZswu1Ph07dtTff/+tnTt3uqadPn061/arqBX0GI2Li3N7zWw2uwLgZ6dTLYgOHTrIw8NDc+bMcWs/v/76ayUmJqpTp055LlvQtiI1NVXp6elu06pVqyY/P78Lri8AAAAuH3r6AQAAoFC1adNGAwYM0NSpU7Vz505dddVV8vDw0MGDB7V06VI9//zz6t69uxYtWqQvvvhC119/vapVq6bk5GR99dVX8vf3d11Y9vb2Vp06dfTjjz+qRo0aCgoKUt26dVWvXr1LquPw4cP1559/6vbbb9ftt98uu92uzz//XHXr1nW7yHwpevfurR9//FEvv/yy1q1bp5YtW8pms2n//v1aunSppk+frqZNm15wuU888YRWr16tO+64Q3fccYcsFou+/PJLZWRk6JlnnnHNN3ToUC1evFhDhw7VXXfdJR8fH3311VeqXLmydu/e7Vbm8uXLNXr0aFdKybycOHFC/fv3V7t27dS+fXuFhoYqNjZWP/zwg3bt2qW7777bldZwyJAhWrZsmR5//HHdeuutaty4seLj4/Xrr7/qlVdeUYMGDXTttdfqp59+0iOPPKJrr71WR48e1fz581WnTp3zBkWffvpprVu3Trfddpv69++vOnXqKD4+Xtu3b9eaNWu0fv16SdJtt92muXPnauTIkdq+fbvCwsK0ePHiC06numLFCu3fv182m00nT57UunXrtGrVKlWuXFkfffSRvLy88lz2gw8+0IYNG9SpUydVqVJFsbGxmjdvnsLDw88bIBoyZIh+/fVXPfjgg7rlllvUuHFjpaam6t9//9WyZcv0yy+/qHz58urcubNatmypSZMmKTIyUnXq1NFPP/2UayC3X79++vTTTzVkyBD169dPsbGxrv2enJx8QfslP+XKldMdd9yhvn37KjY2VrNnz1b16tV12223XVR5devWVYsWLfT2228rPj5e5cqV05IlS1xBlcuhRYsWslqtOnDggAYMGOCafuWVV7qCKK1btz5vOY0bN9aaNWs0a9YsVahQQREREbmOwXm5dOrUSbNmzdLQoUN10003uT6j1apVc2svGjZsqJtuuknz5s1TYmKirrjiCq1du7ZQe0lLRvv13Xff6d5779WgQYPk6+urBQsWqFKlSjp9+vR/0gv8YhX0GH3hhRcUHx+vdu3aqWLFijp27Jg+//xzNWzYULVr176gdZYvX17Dhg3TlClTNHToUHXu3FkHDhzQvHnz1LRp03xvQihoW3Hw4EHdc8896t69u+rUqSOLxaKff/5ZJ0+eVM+ePS9qXwEAAOC/R9APAAAAhe7VV19VkyZNNH/+fL3zzjuyWCyqUqWKbr75ZrVs2VKSERzcunWrlixZopMnTyogIEDNmjXTW2+95ZaubOzYsXrttdc0YcIEZWZmavjw4Zcc9GvSpIk++eQTTZw4Ue+9954qVaqkxx57TPv37y+0NHVms1kffPCBPv30Uy1evFjLly+Xj4+PIiIiNHjwYNWsWfOiyq1bt67mzp2rSZMmaerUqXI4HGrWrJnefPNNt6BBhQoV9Nlnn2ns2LGaNm2agoKCNHDgQFWoUEHPP//8Ra27Zs2aeu655/THH39o3rx5io2Nlaenp+rVq6exY8eqX79+rnn9/Pw0d+5cvf/++1q+fLkWLVqkkJAQtW/fXhUrVpQk9e3bVydPntSXX36pP//8U3Xq1NGbb76ppUuXuoJ2eQkNDdWCBQv0wQcfaPny5friiy8UFBSkOnXqaMSIEa75fHx89Omnn+q1117T559/Lm9vb/Xq1UvXXHNNnmNw5caZctTDw0NBQUGqV6+ennvuOfXt29fVuzIvnTt3VmRkpBYuXKi4uDgFBwerTZs2evTRRxUQEJDvsj4+PpozZ46mTp2qpUuX6ttvv5W/v79q1KjhtrzZbNZHH32k8ePH67vvvpPJZFLnzp01atQo9enTx63M2rVr64033tDkyZM1YcIE1alTRxMnTtT//ve/8+73C/Hggw9q9+7dmjZtmpKTk9W+fXu9/PLLrh68F+Ott97SSy+9pGnTpikwMFD9+vVT27Ztde+99xZavfPj6+urhg0bauvWrW4BW2egr1KlSgUa03LUqFF66aWX9O677yotLU233HJLkQb92rdvr3HjxumTTz7R+PHjFRERoREjRigyMjLHTQLjx49XcHCwvv/+e/3yyy9q27atpk2blm/vsgtVqVIlV/s1depUlS9fXnfeead8fHw0duzYfIPsl1tBj9Gbb75ZX331lebNm6eEhASFhYWpR48eevTRR/Mcwy8/jz76qMqXL6/PP/9cEyZMULly5XTbbbfpqaeekoeHR57LFbStCA8PV8+ePbVmzRp99913slgsqlWrlt59911169btgusLAACAy8PkuNwjQQMAAADF1MMPP6y9e/fqp59+KuqqAIXi6NGj6tKly3l7cQIlwbhx4/Tll19q8+bNrvTAAAAAALIxph8AAADKpLS0NLfnBw8e1IoVK9SmTZsiqhEAwOncNjouLk7fffedWrVqRcAPAAAAyAPpPQEAAFAmXX/99brllltUtWpVRUZGav78+fLw8LiglI8AgP/GgAED1KZNG9WuXVsnT57UwoULlZSUpIcffrioqwYAAAAUWwT9AAAAUCZdffXV+uGHHxQTEyNPT0+1aNFCTz31lGrUqFHUVQOAMq9Tp05atmyZvvrqK5lMJjVq1Ejjxo3TlVdeWdRVAwAAAIotxvQDAAAAAAAAAAAASjjG9AMAAAAAAAAAAABKOIJ+AAAAAAAAAAAAQAlH0A8AAAAAAAAAAAAo4axFXYGSKiYmsairgCJkNptUvryfTp1Klt3OsJhAWUMbAJRttAFA2UYbAJRttAFA2UYbAJRtZrNJISH+RV2NfNHTD7gIZrNJJpNJZrOpqKsCoAjQBgBlG20AULbRBgBlG20AULbRBgBlW0k49gn6AQAAAAAAAAAAACUcQT8AAAAAAAAAAACghCPoBwAAAAAAAAAAAJRwBP0AAAAAAAAAAACAEo6gHwAAAAAAAAAAAFDCEfQDAAAAAAAAAAAASjiCfgAAAAAAAAAAAEAJR9APAAAAAAAAAAAAKOEI+gEAAAAAAAAAAAAlHEE/AAAAAAAAAAAAoIQj6AcAAAAAAAAAAACUcAT9AAAAAAAAAABAmTJ8+AN6771Jl1TGkiXfq3v3awulPoVZ1n/p3HrOmDFV99xzh+v5uHFjNHr0067nF7ufjx8/po4dW2vPnt2XVN+yxlrUFQAAAAAAAAAAAHCKi4vTjBkfa/XqPxUXd0oBAYGqU6eu7rlnqJo1a1HU1bsgHTu2dv3v7e2t0NAwNW3aXLfeOkANGjR0vdalS1e1b39VUVTxgpyvno8/PkIOh+OS11OhQkUtXrxU5coFXXJZZQlBPwAAAAAAAAAAUGy88MKzyszM1AsvvKLKlavo1KlYbdz4lxIS4ou6ahfluedeVtu27ZWRkaEjRw7ru+++0bBh92jUqBfVo8dNkiQvL295eXkXcU3P73z19Pf3v+R1ZGZmysPDQyEhoZdcVllDek8AAAAAAAAAAFAsJCYmasuWzXrooUfVsmVrhYdXUqNGTTR48L3q2LGT23wTJ45Tr143qHPnDho8+DatWrVSkhQff1ovv/yc+vTpoS5drtJddw3Q8uVL811vRkaGpkx5V3369ND113fU/fffrU2bNrjNs2TJ9+rbt6e6dLlKo0ePUHx8wYKQ/v4BCgkJVaVKldWmTTuNHTtRXbt21zvvvKmEhARX2Wenzdyz5189+ugwde16jW64oZPuu2+Qdu3ake96Vq78Xffdd6c6d+6g/v17a+bMacrKynK9fuTIYT3yyP3q3LmDBg3qr7/+WquOHVtrxYrfJUmbNm1Qx46tlZiYeFY9dqtjx9Y6fvxYrvU817npPSXJZsvS22+/oW7dOqlnzy765JOP3HoD9uvXS59+Ol2vvfaSbrihkyZOHJcjvWdu612x4ne3npTOVKP/+99i9e3bU127Xq233npdNptNc+fO1s03d9NNN3XV7Nkz8t2PJRk9/QAAAAAAAAAAKEOOJx1TUmbSZVufv4e/KvlXLtC8Pj4+8vHx1cqVv6tx46by9PTMMY/dbteIEY8pJSVZL730qipXjtDBgwdkNhv9nDIyMlS/fkMNGnS3fH39tGbNnxo79mVVqRKhRo2a5Lred96ZqIMH9+uVV8YrNDRMf/zxm0aMeEyzZ89X1arVtH37Nr3++msaNuwRXX31tVq3bo1mzJh6sbtEAwbcoaVLf9Bff61Tly5dc7z+6qsvqF69+hoxYrTMZrP27PlXFkveIZ0tWzZr7NiX9cQTz6hZsxY6duyoJk4cL0m6774HZLfb9fzzzyg4OERTp36q5OQkTZ58aWMaFtSPP/6gm27qrU8+ma1du3Zq4sRxqlgxXDfffItrni++mKN77rlf9933wCWtKzLyqNauXa1Jk95XZORRvfjiSB07Fqlq1appypSp2rr1H02Y8Kpat26rxo1z/yyUZAT9AAAAAAAAAAAoI+LTT+uepXfIXgjjrhWU2WTSV72+VTmvoPPOa7Va9fzzL+uNN8bp22+/Uf369dWiRSt16XKD6tSpK0nasGG9du7crs8/X6Bq1apLkqpUiXCVERZWQXfcMdj1vF+/gVq/fq1+/fXnXIN+J06c0JIl32vhwv8pNDRMknTHHYO1bt0aLVnyvYYNe0QLFnyhtm3b684775YkVatWXdu2bdG6dWsuap9Uq1bjzLqP5fp6VFSU7rjjLlWvbsxXtWq1fMubOfMTDRp0jytdaJUqERo69EF9+OFk3XffA9qwYb0OHTqot9+e4trGBx54RCNGPHZR9b8QFStW1GOPPSWTyaRq1Wpo3769+uqreW5Bv5Ytr9Tttw9yPXf2LLxQDoddzz33knx9/VSzZi1dcUVrHTlySG+99Z7MZrOqVauhuXNna9OmDQT9AAAAAAAAAABAyVXOK0ifdp932Xv6FSTg53TttV3Uvn1H/fPPZm3fvk1r167WvHmfaeTIF3Tjjb20Z89uhYVVcAX8zmWz2TRnziz9+utyxcTEKCsrUxkZGXmORbd//17ZbDbdfntft+kZGRkqV66cJOnQoQO65prr3F5v3LjZRQf9JCPoajKZcn11wIA79Prrr2np0iVq3bqNOne+3hXY7Nr1atd8N9zQQ88885z27ftXW7du0WefzXS9ZrPZlZGRrrS0NB08eEAVKoS7An6S1KRJs4us+4Vp1KiJ23Y2adJU8+d/LpvNJovFIklq0KBhoawrPLyyfH39XM/Lly8vi8Xs6gVqTAvR6dOnCmV9xQ1BPwAAAAAAJO06tVPvbnxTkzt/LE9LzjRSAAAApUVBU20WJS8vL115ZTtdeWU73XPPUL3++muaMWOqbryxl7y8vPJddt68OVqw4As99tjTqlWrjnx8fDR58iRlZWXmOn9qaoosFotmzJgjs9ni9pqPj0+hbdPZDh48KEmqVCn392LIkGHq2rW71qz5U2vXrtbMmVM1Zsx4dep0nWbNmueaz8/PCHClpKRqyJAH1KlT5xxl5ZYiNTfOwNjZ4+2dPSbgf+l8+9lkMrnVS8q9blare9jLZDLlmCZJdvvl6+l6ORH0AwAAAABA0qrIldp3ep8ik46qZrlaRV0dAAAAnKVGjZpaufJ3SVLt2nUVExOtw4cP5drbb+vWLerYsZO6dbtRkjEG4OHDh1WzZs1cy65bt75sNpvi4uLUvPkVuc5TvXpN7dixzW3a9u1bL3p7vvpqnvz8/NS6dds856lWrbqqVauuAQPu1MsvP6clS75Tp07XKSKiao5569evr8OHD+X6mmTsv+joEzp58qRCQ0NzrX9QULAkKTb2pAIDAyVJe/b8e1Hbd7YdO7a7Pd++fZuqVq3m6uVXEEFBwUpJSVFqaqorQLhnz+5LrltpYz7/LAAAAAAAlH47Yo2LEceSIou4JgAAAGVXfPxpPfbYg1q2bIn27t2jY8ci9euvP2vevDnq2LGTJOmKK1qpefMr9MILz+qvv9bq2LFIrVmzSmvXrpYkVa1aVX/9tU5bt27RwYMH9Oab4xUXF5vnOqtVq64bbuihsWNf1h9//KpjxyK1Y8c2zZkzS6tX/ynJGBdw3bo1mjdvjo4cOayFC78scGrPpKRExcae1IkTx/XXX2v1wgvP6uefl+npp0crICAgx/zp6Wl6++03tGnTBp04cVz//PO3du3aoerVcw9aStI999yvpUt/0MyZ07R//z4dPHhAP/+8TNOmfShJat26japWra5x417Wnj3/asuWza7XnCIiqqpChYqaOXOajhw5rNWr/9T8+Z8XaBvzExV1Qu+//7YOHz6o5cuXauHCL9Wv38ALKqNx4yby9vbW1KkfKDLyqH76aal+/PF/l1y30oaefgAAAACAMs9mt2n3qZ2SpMiko0VcGwAAgLLLx8dXjRo10ZdfztOxY0eVlZWlChUqqlevPrrrrntd840bN1FTpryrMWOeV2pqmiIiIvTgg49Kku6+e4iOHYvUU089Km9vb9188y26+uprlZyc9ziGzz33smbPnqEpU95VTEy0ypULUuPGTdWhgzF+XpMmTfXss89r5sxpmjHjY7Vu3UZ33z1Es2dPP+82jR//iiTJ09NLYWFhatashaZNm6369RvkOr/ZbFF8fLzGjn1ZcXGnVK5ckDp1uk5DhgzLcx1t27bXxInv6tNPP9HcubNltVpVrVoN9erV50yZZo0f/6Zef/01PfDA3QoPr6QnnnhGTz/9qKsMq9WqMWPGadKk13X33berYcNGuv/+h/Tii6POu4356d69p9LT03X//XfLbLaoX7+B6t277/kXPEtgYDm9+OJr+vDD9/T994vUqlUb3XffA5o4cdwl1a20MTnOTYKKAomJSSzqKqAIWa1mBQf7KS4uWVlZ9qKuDoDLjDYAKNtoA4DSad/pPXpw+VBZzRZ1q3Gjnmg1Itf5aAOAso02ACjbaANQGnXs2Frjx7+la665tqirUuw524DijPSeAAAAAIAyb0fsdllMZrWqeKUiSe8JAAAAoAQi6AcAAAAAKPO2x25T7aC6qlmuto6R3hMAAABACcSYfgAAAACAMm9n7A5dGd5WVfwjFJMSrQxbhjwtnkVdLQAAAOA/9eefG4q6CihE9PQDAAAAAJRpp9PidCwpUo1CGquyf2U5JB0jxScAAACAEoagHwAAAACgTNt5aocknQn6RUiSjicfK8oqAQAAAMAFI70nAAAAAKBM2xG7XcHewaroGy5J8rJ4KZJx/QAAAACUMAT9AAAAAABl2o7Y7WoU0kQmk0mSVMW/iiITCfoBAAAAKFlI7wkAAAAAKLNsdpt2n9qphuUbuaZV9o+gpx8AAACAEoegHwAAAACgzDoQv1/ptnQ1Cm3imlbFvwpj+gEAAAAocQj6AQAAAADKrB2x22QxmVUvuL5rWmX/CEWnRCnDllGENQMAAEBJ169fL3311bzLvt6OHVtrxYrfL6mM4cMf0HvvTcp3noJsX2ZmpgYM6KOtW7cUeN1r167WPffcIbvdXuBlYGBMPwAAAABAmbXj1HbVDqorL4uXa1oV/yqyOxw6kXxc1QKrF2HtAAAAyq6oqBOaMWOq1q1bo/j40woJCdXVV1+re+8dqnLlgoq0buPGjdGPP/4vz9fDwyvp66+/v4w1Kr6+/XahKlWqrKZNm0uSjh8/pk8/na5NmzYoNjZWoaGh6tbtRt11133y8PCQJLVr10HTp3+sn376Ud279yzK6pc4BP0AAAAAAGXWjtjtahve3m1aZf8ISdKxpEiCfgAAAEUgMvKoHnzwPlWtWk1jxoxTpUpVdODAPn344Xtau3a1pk2bpcDAckVWv8cfH6EHHxzuet67d3c999zLatvWOK80my0XXXZWVpas1tIRunE4HFq48CsNHTrMNe3QoYNyOBx65pnnVKVKhA4c2Kc33hin1NRUDR/+hGu+Hj1u0tdff0nQ7wKVjk8OAAAAAAAXKC7tlI4nHVOjkMZu00N8QuRp8VRk0tEiqhkAAMB/K27vKUmST6ivvIO8XdNTYlKUHp8ms9WscjWCXNNtmTYlHIqXJPmF+8vT39P1WtLxRGUmZ8rq46GAKgGu6VmpmUqMTJQkBdcpf0H1e/vtifLw8NA770yRl5dRv/DwcNWrV18DBvTRtGkfasSI0ZKMFJM33dRbBw7s16pVK+TvH6DBg+/Vrbfe5iovMTFRH3zwrv788w9lZGSqQYOGevTRp1S3bj1J0owZU7Vy5R8aOPBOTZ/+sRITE9SuXQeNHPmCfH39ctTP399f/v7+50wLUEhIaI5509LSNH78K/rtt18UEBCgu+8eot69+0oyer3173+zXnllvBYt+lo7dmzTiBGjdeONvfT9999q/vzPdfz4MYWHV1K/fgPVt29/SUbKzPfff1t//PGrEhMTFRxcXn363KrBg+91rTc+/rRGjx6h9evXKCysgoYPf0IdO3Zyvb5580Z9+OF72rt3jwIDA9W9+026//6H8gw4xsWd0oQJr2nDhvUKCQnR/fc/dN73cffunTp27Kg6dOjomtauXQe1a9fB9bxKlQgdPnxIixYtdAv6XXXVNXrnnYmKjDyqKlUizrsuGBjTDwAAAABQJu06tVOScgT9zCazKvtVUWRSZFFUCwAA4D+3eswKrR6zQifWuZ/vHFy2T6vHrNDGd9e5Tc+IT3ctc2rXSbfXdn+1U6vHrNC2WX+7TU84nOBa5kIkJMRr/fo1uuWWfq6An1NISKi6du2hX35ZLofD4Zo+b94c1alTTzNnztWgQXdr8uRJ+uuvta7XX3xxpOLiTumttyZrxow5qlevgZ544iElJMS75omMPKqVK3/XxInvaOLEd/X335s0Z86nF1T33MyfP1cNGjTSrFlzdcst/TVp0us6fPig2zwffzxF/fsP1OefL1CbNu31008/avr0j/XAAw/r888XaNiwRzR9+seulKILFszXn3+u0Kuvvq558xbqpZfGKjy8kluZs2Z9os6dr9fs2fPVrt1VeuWVF13bGxMTrWeeeVwNGjTWp59+oaefHq0fflis2bNn5Lkd48aNUXR0lCZP/livvfaGFi1aoLi4U/lu+5Ytm1W1arVcA6dnS0pKUmBgoNu08PBwlS8foi1bNue7LNzR0w8AAAAAUCbtiN2u8t7lVcG3Yo7XKvtX0TF6+gEAAFx2R44ckcPhUPXqNXN9vUaNGkpMTNDp03EKDjZ6EDZt2lyDB98jSapWrbq2bt2iL7+cpyuvbKctW/7Wzp3b9f33y+XpafRQHD78Ca1c+bt+++0XV687h8Ou558f4wpQdet2ozZu/OuSt6d9+w6uHnqDBt2tr76ap02bNqhatRquefr3v12dOnV2PZ8xY6qGD3/CNa1y5So6cGC/Fi/+Rj163KTo6BOqWrWamjVrIZPJlCPgJxnpMbt27S5JGjbsEX399Xzt2LFd7dp10DffLFCFChX11FPPymQyqXr1Gjp5MkYfffS+7r33fpnN7v3FDh8+pLVrV+uTT2arYUPjhrlRo17SnXf2y3fbT5w4odDQsHznOXr0iBYu/FKPPPJEjtdCQ0N14sTxfJeHO4J+AAAAAIAy6XjSMVUPrCGTyZTjtYiACK08+kcR1AoAAOC/12HMNZKM9J5nq9Gttiq1qyKz1T3o41nOy7WMX7h7Wsv6tzVUrZ51ZPXxcJseWC3QtczFOLsn3/k0adLU7Xnjxs20YMEXkqS9e/9Vamqqevbs4jZPenq6IiOzb/IKD6/s1iMtJCRUcXFxF1N1N7Vr13X9bzKZVL58SI5yGzRo6Po/NTVVkZFH9frrr2nixHGu6TabTX5+xr7v0aOXnnzyEd1++61q1669OnS4Wm3atMtzvT4+PvLz83P1zDt06KCaNGnmdh7ctGlzpaamKDo6WuHh4W5lHTp0QBaLRfXrZ9ezevUa8vcPUH7S09NcgdbcxMRE6+mnH9V1112vm2++JcfrXl5eSktLy3cdcEfQDwAAAABQJsVnxCvIKyjX1yr5VVFUygll2jLlYfHIdR4AAICSKq8x9nzDfOUb5ptjusXDkucy/pVyD/xYfTwueCw/SYqIiJDJZNKhQwckXZfj9YMHDyogIFBBQcEFKi81NUUhIaF6//2pOV47O2h17lh2JpNJDof9wiqfi9zKtdvdy/Xx8XGrrySNHPmCGjVq4jafswde/foNtGDBYq1du1obNqzXSy+NUuvWbTR27MTzbE/BA6mFoVy5IO3fvy/X106ejNGjjz6oJk2a6dlnn891noSEhAK/zzAwph8AAAAAoExKSD+tQK9yub5Wxb+K7A6HolJOXOZaAQAAlG3lygXpyivbatGir5We7t7LKzb2pJYv/1FdunR166W2fftWt/m2b9+q6tVrSDICZKdOxcpisSgioqrbX1BQ0H+9OResfPkQhYaG6dixyBz1rVy5ims+Pz9/delyg0aOfEGvvDJBv//+q9sYhfmpXr2Gtm37xy0IuHXrFvn6+qlChQq5zm+z2bR7907XtMOHDyopKTHf9dSrV1+HDh3MEWyMiYnW8OHDVL9+Az333Ms50olK2T0x69WrX6BtgoGgHwAAAACgTIrPiFc5z9yDfpUDIiRJkUmRl7NKAAAAkPTkk88qMzNDTz31qP7+e5Oiok5o7drVevLJRxQaWkEPPPCw2/xbt27R3LmzdfjwIS1c+JV+//0X9e9/uySpdeu2aty4qUaPHqH169fq+PFj2rp1i6ZO/UC7du0ois07ryFDhmnOnFlasGC+Dh8+pH379uqHH77T/PmfS5Lmz/9cy5cv1aFDB3X48CH99tvPCgkJOW+6Tae+ffsrOjpK77wzUYcOHdTKlb9r5sypGjDgjlwDcNWq1VDbth305pvjtX37Nu3atVOvvz5WXl5e+a6nZcvWSk1N0YED2b39YmKi9eijw1SxYriGD39Cp0/HKTb2pGJjT7otu337Vnl4eKpJk2YF2iYYSO8JAAAAAChzHA6H4tPjVS6Pnn5hPmHyMHvoWNLRXF8HAADAf6dq1WqaPn2OZsyYqpdeGq2EhHiVLx+ia665Vvfee78CA93P4QYOHKRdu3Zq1qxP5Ofnp+HDn1Tbtu0lGWkt33rrPU2b9qHGj39Fp0/HqXz5ELVo0VLBwReefvRy6NWrj7y8vPXFF5/pww/fk7e3j2rXruMKZPr6+mnevM909OgRmc1mNWjQWG+++V6uAbvchIVV0JtvvqcPP3xP99xzuwIDA9WzZ2/dffeQPJd57rmX9MYbY/Xoow8oOLi87r//IU2fHpXvesqVC9I111ynn35aqgcfHC5J+uuvdTp69IiOHj2iW2650W3+P//c4Pr/55+X6YYbusvb27tA2wSDyXG5k7iWEjEx+XdbRelmtZoVHOynuLhkZWVdel5nACULbQBQttEGAKVDSmaKen/bQ8+1fUnXVeuS6zxDl92t5hWu0KNXPOGaRhsAlG20AUDZRhtQPPXr10u33Xa7brvtjqKuCnKxd+8ePfnkI/ryy2/l65tzvMjcnD59WnfccaumT//MLaVpUXO2AcUZ6T0BAAAAAGVOQoYx3klePf0kqZJ/ZR0nvScAAABw0erUqauHHnpUx48fK/AyJ04c09NPjyxWAb+SgvSeAAAAAIAyJz79/EG/CP8IrT626nJVCQAAACiVbryx1wXN36BBIzVo0Og/qk3pRtAPAAAAAFDmOIN+gZ5Bec5T2T9CJ5KPKcueJauZn88AAADF0ddff1/UVQCKDdJ7AgAAAADKnISM05KkQK/APOep4l9FdodDUcknLlOtAAAAAODiEfQDAAAAAJQ58enx8rZ6y8vilec8VfwjJEmRjOsHAAAAoAQg6AcAAAAAKHPiM+JVzjPv8fwkKcy3gswmk6JS6OkHAAAAoPgj6AcAAAAAKHMS0uMV6JV/0M9sMivEO1QxqdGXqVYAAAAAcPEI+gEAAAAAypz49HiVO0/QTzJ6+8WkEPQDAAAAUPwR9AMAAAAAlDkJBUjvKUlhPhUUkxJzGWoEAAAAAJeGoB8AAAAAoMyJT49XoFfQeecL8w0jvScAAACAEoGgHwAAAACgzIlPP12wnn5n0ns6HI7LUCsAAABciI4dW2vFit+Luhp5On78mDp2bK09e3Zf1vVu2rRBHTu2VmJi4iWVc779W9DtO3z4oG6+uZtSUpILvO5vv/1azz77ZIHnh8Fa1BUAAAAAAOBycjgcSsiIV2BBxvTzqaBMe6aRDrQAPQMBAABQOGJjT+qzz2Zq9epVOnkyWsHB5VWnTj3ddtvtat26TVFXT/369dKJE8fzfL1Hj5t0330PXMYaFV8ff/yBbr31Nvn6+kmS0tPT9dZbE7R7904dOnRQHTp01IQJk9yW6dmztz79dIa2bNms5s2vKIpql0gE/QAAAAAAZUpyZpLsDofKFSTo51tBkhSTEkPQDwAAlBrJhw9JkjyDg+UREOianhF3SpmJiTJZrfKtXMU13Z6VpdRjkZIkr9BQWc8EbyQpLSZattRUWby95V2homu6LT1NaVFRkiS/atUvqH7Hjx/TQw8Nkb9/gB555DHVqlVHWVlZWr9+jd5++w3Nm7fwwje6kH3yyWey222SpG3b/tHzzz+refMWys/P2DdeXt5KTEy44HJtNptMJpPM5tKRqPHEiRNavXqlnnzyGdc0u90uLy8v9es3UL///muuy3l4eKhr1+5asGA+Qb8LQNAPAAAAAFCmxKfHS1LB0nv6nAn6pUarTnDd/7ReAAAAl8u/H02WJEX06qOwDle7pkevWqmYVSvkGVxejZ993jU9KynRtUzNQfcqqHET12vHf/pRp7f9I/+atVX3gYdd01OPH9eeqVMkSVec04vrfCZNel0mk0mffDJbPj4+rum1atVWz56981xu3769eu+9t7Rt21Z5e3urU6fOevTRJ+Xr6yvJSHv50UeTdeDAflmtVtWsWUsvvzxO4eGVJEkrV/6uWbM+0cGDBxQSEqYePXrqrrvuk9WaM5QSHBzs+j/gTOA0OLi8AgICXNOdQb9jxyI1efLb2rFjmyIiqumZZ0arSZNmkqQlS77X5MmT9MILr+jjj6foyJHDmj9/kUJCQjVt2of6+edlSkpKVM2atfXQQ4+qZcvWkqQTJ47r7bcn6p9//lZWVqbCwyvrkUceU/v2HV3r3717pz766H0dPLhfdevW13PPvaRq1Wq4Xl+06Gt98cUcRUdHqVKlyrr77iHq3r1nnvt3x45tevPN8Tp06KBq1qytu+66L895nX79dbnq1KmnsLAKrmk+Pj4aMWK0JGnr1i1KSso9DelVV12tJ598ROnpafLy8j7vusCYfgAAAACAMiY+wwj6FSS9Z7B3sCwms2JSogtU9v74fer/XW9FF3B+AAAAuEtIiNe6dWvUt29/t4Cf09lBtbOlpqbqqaeGKyAgQNOnz9Zrr72uDRvW6513JkqSsrKy9NxzI9SiRSvNnj1fH388Szff3FeSSZK0ZctmjR37svr3v11z5nylZ58drR9//J8++2zmJW/TtGkf6vbbB2vWrHmqWrWaxox5XllZWa7X09LSNHfubI0c+YLmzPlSwcHl9c47E7V9+z965ZXxmj17vq677nqNGPGYjhw5LEl6++03lJmZoQ8++ESzZ8/XQw89Kh8f3xzrHT78CU2fPkcWi0UTJrzqeu2PP37Te++9pYEDB+mzz75U7959NWHCq9q0aUOu25CSkqJnn31SNWrU0vTpc3TffQ/ogw/ePe+2//PPZjVo0PAi9prUoEEj2Ww2bd++7aKWL4vo6QcAAAAAKFMSnD39ChD0M5vMCvUJU0xqwYJ4X+3+QqfTT+t4UqQq+FY4/wIAAABFoN5Dj0ky0nuercJVVyu4WQuZzunZZvUPcC3jFRrq9lqlG3qowtXXyuLt3hPLp1Il1zIX4ujRI3I4HG490gpi+fKlysjI0AsvvOoKFj711DMaOfIpPfTQo7JarUpKSlKHDh1VpUqEJKlGjZqu5WfO/ESDBt2jHj1ukiRVqRKhoUMf1IcfTr7ksfluv32QOnQweuANGTJMgwffpsjIo6pe3djGrKwsPfXUKNWtW0+SkRJzyZLvtXDh/xQaGiZJuuOOwVq3bo2WLPlew4Y9oqioE+rUqbNq167jqu+5HnjgYV1xRStJ0qBBd+uZZ55Qenq6vLy8NH/+HPXo0Ut9+/aXJFWrVl3bt2/TF1/McfUmPHf/Ohx2jRr1ory8vFSrVm3FxETprbdez3fbT5w4oQYNGl3EXpO8vb3l5+evqKgTF7V8WUTQDwAAAABQprh6+hUgvadkjOtXkJ5+J1NP6o8jxpgkiZm5pygCAAAoDvIaY88zuLw8g8vnmG62WvNcxjss9xudLF7eFzyWnyQ5HBe8iCTp0KEDqlOnrlvvwKZNW8hut+vw4UNq0aKlbryxl55++lG1bt1WrVu3UefOXRV6Joi5b9+/2rp1i1vPPpvNroyMdKWlpcnb++LTS9aunZ0mPiTEWF9c3ClX0M/Dw0N16mTPs3//XtlsNt1+e1+3cjIyMlSunHEO26/fQL311gT99ddatW7dVp06dXYrI+/1xik8PFwHDx4809MxW9OmzbVgwfxct+HQoQOqXbuuvLy8XNMaN2523m1PT0+Tp6fneefLi5eXl9LS0i56+bKmTAb95s2bpy+++EKRkcbAo3Xr1tXDDz+sTp06FXHNAAAAAAD/tfj00/L18JXVXLCfxGE+FRSTGnPe+b7bt0geZk9l2VOVlJF0qdUEAAAok6pWrSqTyaTDhw8WetnPPfey+vUboHXr1ujXX5frk08+0jvvfKAmTZoqJSVVQ4Y8oE6dOudY7lKCVpLcxgQ0mYx0ona73TXNy8vLNV2SUlNTZLFYNGPGHJnNFreynEHNXr36qE2bdlqz5k+tX79Oc+bM0vDhT6hfv4H5rtfhsOtyCgoKUmLixd8Ql5CQoKCgoMKrUClXJsf0Cw8P14gRI/TNN99o4cKFateunR555BHt2bOnqKsGAAAAAPiPJaTHq1wBe/lJUphv2Hl7+qVlpel/+xare82e8rH6KDEj4VKrCQAAUCYFBpZTmzbt9c03C5Samprj9bwCSNWr19TevXvcltm69W+ZzWZVO6vHYb16DTR48L36+OOZqlWrtn7+eakkqX79+jp8+JAiIqrm+DObL28opW7d+rLZbIqLi8tRF2ePPUmqWDFcffr00/jxb2rgwEH6/vtvC7yOGjVq6J9/trhN27p1i2rWrJnr/NWr19S+fXuUnp7umrZ9+9YCbcvBg/sLXK+zRUYeVUZGuurVa3BRy5dFZTLo17lzZ3Xq1Ek1atRQzZo19eSTT8rX11d///13UVcNAAAAAPAfi8+IV2ABxvNzcvb0s+dzV/TPh35ScmaSbqlzq/w9/EnvCQAAcAmeeupZ2e023X//3fr991905MhhHTx4QAsWzNeDD96b6zI33NBDnp6eGjfuZe3fv1ebNm3QO++8qW7dblT58iE6dixSH388Rdu2/aMTJ45r/fq1Onr0sKpXN4Jc99xzv5Yu/UEzZ07T/v37dPDgAf388zJNm/bh5dx0Scb4ejfc0ENjx76sP/74VceORWrHjm2aM2eWVq/+U5L03nuTtG7dGh07Fqndu3dp06YNrm0piNtvv0s//vi9Fi36WkeOHNb8+Z9rxYrfNHDgoFzn79q1u0wmkyZOHKsDB/ZrzZo/NX/+5+ddT5s27bVt21bZbDa36QcO7NeePbuVkBCvpKQk7dmzW3v27HabZ8uWzapcuUqu4xUid2UyvefZbDabli5dqpSUFF1xxRUFXs5sNslsNp1/RpRKFovZ7RFA2UIbAJRttAHA5Wd32PXR5g/Ut14/VfKvdMnlJWYmKMg7SFZrwY7j8ICKsjmylGxLkI+3cWf12W2A3WHXor0L1DHiGlUNilCgd6BSs5ILXD6AkoPzAKBsow24fKpXr6bZs+fp009naMqUdxUbe1JBQcFq0KChnn32ObfzLIvFJKvVLH9/X7333gd65503df/9d8vLy1vXXddZjz/+tKxWs/z8fHXkyCG98MKzio+PV0hIqPr1u0233tpPZrNZV111lSZNek8zZnyiuXM/k9VqVfXqNXTzzX3Oe17n/ExYreZz6pb9mXFOdz46pznjDOeu46WXxmjWrOmaMuVdxcREKygoSI0bN9XVV18jq9Ush8Oud955Q9HR0fLz81O7dh30xBPGtuZWn3Pr0rlzZ8XFPaN58+bovffeUuXKVfTCCy+rTZs252ybsX8DA/311lvv6o03xuu+++5UzZq19Mgjj2n06Gfctu9cHTt21KRJFm3e/Jfatevgmv7MM4/rxInjruf33nunJGnt2k2uab/8skx9+vQtNufVJeHYNzkcFzssZsm2e/duDRw4UOnp6fL19dWkSZMuaEw/h8PhlmMXAAAAAPDfOJV6SjfMuUHPdHhGA5oMuOTyhiweoojACL1y3SsFmn9nzE4NXjRYc26Zo4ZhDXO8vurwKj2+9HFNv3m6WoS30APfP6Aw3zCN6zLukusKAAAAlHRz587Vr7/+qhkzZhR4mT179ujuu+/WsmXLFBAQ8B/WrnQpsz39atasqW+//VaJiYlatmyZRo4cqc8//1x16tQp0PKnTiXT068Ms1jMCgz0UUJCqmy2yzvwKYCiRxsAlG20AcDlty/usGw2u/ZEHVBcleRLLi868aRqBdRTXFzByvLK8pfNZtfeEwdVxatGjjZg5oZPVadcPVXzrKO4uGR5Onx0MvFUgcsHUHJwHgCUbbQBwMW54YabFBV1UkePGr0SC2L//iN68cVXlJVlLjbn1c42oDgrs0E/T09PVa9uDN7ZpEkTbd26VZ999pleffXVAi1vtztkt5fJTpI4i81mV1YWX/BAWUUbAJRttAHA5ROddFIOh3Q86XihHHfxafEKsAYWuCw/S6AsJqtOJEa5LvA524D98fu08cRGjW77omw2hySH/Kz+Opx4iDYCKMU4DwDKNtoA4EKZNXjwfZJU4GOnZcsrL2h+GIp/AtLLxG63KyMjo6irAQAAAAA4x6m0WEnSieRjl1yW3WFXYkaCAr3KFXgZs8msMJ8wxaRG53jt10PLFeQVpGsirnVN8/f0V2JG4iXXFQAAAAAuRJns6Tdp0iRdc801qlSpkpKTk/W//wSAqAoAAQAASURBVP1P69evv6B8sgAAAACAyyM76HfikstKzEiQQ1K5Cwj6SVKYbwXFpMTkmL49dpuahbWQ1Zz98zrAI1BJBP0AAAAAXGZlMugXGxurkSNHKjo6WgEBAapfv75mzJihq666qqirBgAAAAA4x6m0U5Kk5MxkJWYkKMAz8KLLik+PlySV87zAoJ9PmKJSotymZdgytPvULg1p+oDbdH9PfyVlJsrhcMhkYix4AAAAAJdHmQz6jR8/vqirAAAAAAAooFNpsfL38FdSZpJOJJ+4pKBfQkaCJF1Qek/J6Om37eRWt2l7T+9Rpj1TTUKbuU0P8AxQlt2mNFuafKw+F11XAAAAALgQjOkHAAAAACjWTqXGqmFII0nSieTjl1RWwkX39Kugk6kxsjvsrmk7YrfJ0+Kp2kF13Ob19zCCkkkZSZdUVwAAAAC4EAT9AAAAAADF2qn0/7N332FxldkDx79TmaENvSQQWhJISO8xPTHG3l3ddYs/y9p1V9ey6uray1pXXXtfde1dY4lJNL0XCISElhB6GWAGBqb9/iAMDAwlCTADOZ/n8Vn3tjlX7jtz33vue95qkgzJ6NS6Y0761TbXooAjHi0Y6R+F3emg5nCpUYDMygzSwsa4zecHLeU9AeqtdccUqxBCCCGEEEIcCUn6CSGEEEIIIYTwWU6nk+rGKsJ04cT4x1LaUHpMx6ttMhKoDUKlVB3RfpH6KADKG8pdcWVW7WZs+LhO2wZpgwAwNdcfU6xCCCGEEEIIcSQk6SeEEEIIIYQQwmc12hppsje1JP0CYyk1Ffdqv/rmOu789Va3kXnQUt4z+AhLewJE+kcCUHE46VdqLqXGUkO6h6RfoKZlpJ+U9xRCCCGEEEIMJEn6CSGEEEIIIYTwWdWWKgDCdGFE+8dQ1lDWq/12V+xiU+lGNpZscFte21yLwe/Ik37BWgMapcaV9Muo3AXA2PD0Ttu2lg6tt8pIPyGEEEIIIcTAkaSfEEIIIYQQQgif5Ur66cOJDYil1FyC0+nscb+82lwAdlRsc1te11RL8FEk/RQKBVH+0ZQ3VAAt8/nFB43weCy1Uo1OrZPynkIIIYQQQogBJUk/IYQQQgghhBA+q6qxdaRfODEBsTTZmzA21fS4X2vSb2f5drckYW1zLYajKO8JEKGPdI30y6zM8DjKr1WgJpB6SfoJIYQQQgghBpAk/YQQQgghhBBC+KxqSxValRZ/tT8xATEAlJhLetwvz5jL8MA4KhsrKTG3zQNY23R05T2hZV6/8sZyzM1m8mvzSI8Y3+W2QdogKe8phBBCCCGEGFCS9BNCCCGEEEII4bNqLNWE68JRKBREB8QCUGYu7XYfi81CsamIM1LOQqlQsLNih2tdXVMtwUc50i/SP4qKhnIyyjNwOB2kh4/rctsgbTBmGeknhBBCCCGEGECS9BNCCCGEEEII4bOqLFWE6sKAlpKZQdogSnsY6VdYV4ATGBcxgZEho9lZ3jKvn81hw2Q1YfALOapYovTRVDVWsr10O0HaIOKC4rvcNkDKewohhBBCCCEGmCT9hBBCCCGEEEL4rBpLNWG6cNf/j/aP6THpl1ebiwJICE5kYuQkdlbswOl0Ut9cB3DU5T0j/CNxOB38nP8zYyPGoVR03aUO0gZhspqO6nOEEEIIIYQQ4mhI0k8IIYQQQgghhM+qtlQRpm9L+sUExLrN0edJnjGXYYFx6NQ6JkZNobKxkmLTIWqbagGOurxnlD6y5fg1ed2W9gQI1ATJSD8hhBBCCCHEgJKknxBCCCGEEEIIn1V1eE6/VjEBMZQ1lHW7T15tLskhKQCMixiPUqFgR8V26ppbkn5HO9Iv0j/K9e/jIyd0u22gNtA1slAIIYQQQgghBoIk/YQQQgghhBBC+CSbw0ZdU61bec+YgFjKG0pxOB0e93E6neTX5pJsaEn6BWgCGBkyml0V210j/Y426ReoCcJPpUOpUJIaltbttkGalvKeTqfzqD5LCCGEEEIIIY6UJP2EEEIIIYQQQvikGksNAKG6MNeymIBh2Bx2KhsrPe5T2VhJfXO9K+kHMClqMjsrdmBsMqJUKAjQBB5VPAqFgkj/SNIi0tCpdd1uG6gNxOaw0WRvOqrPEkIIIYQQQogjJUk/IYQQQgghhBA+qdpSBdCpvCdAaRfz+uXX5gG4ynsCTIycQlVjFXuqMgjSGlAqjr4rvCRhKeekndPjdoHaYACZ108IIYQQQggxYNTeDkAIIYQQQgghhPCkNekXpm8b6Rft35L0KzOXQmTnffJrc9Gr9UT5R7uWpUeMQ6lQsL54LeH6iGOK6U/j/o/Q0ABqaszdbhekCQLAZK0n0lOgQgghhBBCCNHHZKSfEEIIIYQQQgifVNVYhVKhIMQv1LVMp9YR4hdCibnE4z75tbkkGZLdRvMFaAIYFZqK2WrGoD26+fyOVKC2pYSoSUb6CSGEEEIIIQaIJP2EEEIIIYQQQvikmqZqDH4hncpxxgYOo7SLpF9eba7bfH6tJkZOAiDYb2CSfkHa1pF+pgH5PCGEEEIIIYSQpJ8QQgghhBBCCJ9U3VhFmC6s0/IY/1jKGko7LbfarRyoK3Sbz6/VxMgpAAM30q+1vKeM9BNCCCGEEEIMEEn6CSGEEEIIIYTwSdWWasJ04Z2WRwfEUGIq7rT8YH0hdqeDJA8j/cZFjEepUBDsF9wvsXakVWnRqrTUWyXpJ4QQQgghhBgYam8HIIQQQgghhBBCeFJtqSIhOLHT8piAWKoslVjtVjQqjWt5Xm0uAImGpE77+Gv8uX7yTYyLGN9v8XYUpA3C1CzlPYUQQgghhBADQ0b6CSGEEEIIIYTwSdWWKsL0nUf6xQbE4nA6qWgsd1ueX5tHTEAMgZpAj8c7PeVMjwnB/hKoCaJeynsKIYQQQgghBogk/YQQQgghhBBC+Byn00m1pZpwD+U9YwJiASg1l7gtz6vNJdGQPCDx9UaQNoh6a523wxBCCCGEEEIcJyTpJ4QQQgghhBDC55is9dgcNkJ1YZ3WReqjUAAlHZN+xlySfCjpF6gNwizlPYUQQgghhBADRJJ+QgghhBBCCCF8TlVjFQBhHkb6aVQaIvSRFJuKXMuMlhqqLdUkG1IGLMaeBGoCpbynEEIIIYQQYsCovR2AEEIIIYQQQgjRUbWlJennqbwnQKIhiQ/3/o+tZVs4YdhcDH4GAJ9K+gVpg9lnzfF2GL3mcDr4qfB75g5fgL/G39vhCCGEEEIIIY6QJP2EEEIIIYQQQvic1qSfp/KeAHfNupeNJetZX7yWT/d9hNlqRqvSMjwwbiDD7FbLSL/BM6ffB9nv8XrGK9RYargw7XfeDkcIIYQQQghxhCTpJ4QQQgghhBDC51RbqvHX+KNT6zyu99f4s2jEEhaNWILNYWN3xU4cOFApVQMcadeCtEGDprxnVtUe3sx8FZ1ax6+HVkvSTwghhBBCiEFI5vQTQgghhBBCCOFzqi1VhPp5HuXXkVqpZnL0VKZGT+/nqI5MkDYIq8NKs73Z26F0y2w18/DG+xgdmsZ1k//C3upsyhvKvR2WEEIIIYQQ4ghJ0k8IIYQQQgghhM+psVQTrvc8n99gEagJAvD50X7Pbn8KY5ORO2bezZxhc1ErVaw99Iu3wxJCCCGEEEIcIUn6CSGEEEIIIYTwOVWN1YTpBnnST9ua9PPdef1+KvyeFYU/cuOUm4gNHEagNojJUVNZI0k/IYQQQgghBh1J+gkhhBBCCCGE8DnVlqrBn/TTBAJgspq8HIlnpeYS/r3tKZYkLGVJwkmu5fPiFrK7Yic1lmovRieEEEIIIYQ4UpL0E0IIIYQQQgjhc2os1YTpejenn68K0gYDYPLR8p7fF3yHSqHi+sl/dVs+O/YEFAoFaw+tOeJjljWUcdn3f+T7gu/6KkwhhBBCCCFEL0nSTwghhBBCCCGET2myN2GymgZ90i9Q2zrSzzeTfuuL1zI9ZiYBmgC35SG6UMZHTGLNodVHdLzaJiO3/3IzB+oKeXfPWzicjr4MVwghhBBCCNEDSfoJIYQQQgghhPAprWUlw/SDu7ynn8oPjVJDvQ+O9KtoqCDXuJ9Zw07wuH5e3Hx2lG/r9XyEDdYG7lxzG6bmev4+8y5KzCVsLFnflyELIYQQQggheiBJPyGEEEIIIYQQPqWqsQpg0M/pBy2j/Xwx6behZB1KhYLpMTM8rp8zfD52p4MNxet6PJbNYeP+DXdzoK6Qh+b9i8UjljImfCyf5HzU12ELIYQQQgghuiFJPyGEEEIIIYQQPqXKUglA+BBI+gVpgzFZTd4Oo5MNxWsZFzHRNe9gRxH6CMaGp/NLDyU+HU4Hj29+mB3l2/nnCQ8wKnQ0AOeMPJ+dFdvJM+7v89iFEEIIIYQQnknSTwghhBBCCCGETymozcfgF0Kwn8HboRyzQE1gr0tkDpRGWyPby7cxu4vSnq3mDp/P1tLNNFgbutxmc+kmVhz4iVun38GU6Gmu5fPiFhChj+Cz/Z/0WdxCCCGEEEKI7knSTwghhBBCCCGET8mvzSPJkOztMPpEkDbI50b6bS/bitVhZVZs90m/eXELsDqs3c7Nt+rgCkYEJ7AwfrHbcrVSzZkp57Ci8EeMlpo+iVsIIYQQQgjRPUn6CSGEEEIIIYTwKUMp6ReoDcI0AHP6OZwOtpRuwuF09Ljt+pK1xAXFExcU3+12MQGxjAodzcqDKzyub7Y3s654DQviFqFQKDqtPy35DAC+zf+6F2cghBBCCCGEOFaS9BNCCCGEEEII4TOa7E2UmA8NnaSfJoj6AUj67arYwd9/vYVP933U7XYOp4MNxeuY3cMov1YnJ57KxpJ1VDZWdlq3tayl9Of8uIUe9w32M7A0YRlf5n6GzWHr1ecJIYQQQgghjp4k/YQQQgghhBBC+IzC2gIcTueQSfq1lPfs/6RfdnUWAK/vfoUDdYVdbpdTsxdjk5FZPczn12pxwlI0Si3L87/ptG71wZ9JCE4k0ZDU5f5njzqPqsYqfila1avPE0IIIYQQQhw9SfoJIYQQQgghhPAZ+XV5ACQEJ3o3kD4SqAnE1Nz/c/plV2cxJnwsUf7R/Gvzw12W+VxfvJYgbRDp4eN7ddxATSAL4xfzXf7XbsdssjexrngtC+IXdbt/kiGZyVFT+Dr3i96fjBBCCCGEEOKoSNJPCCGEEEIIIYTPyK/NJTYgFr1a7+1Q+kSQNogmexNWu7VfP2dvdRbjIyZwy/S/k1OTzUd7/+dxu40l65gRMxOVUtXrY5+echblDeVsLt3kWraldBONtkYWxHWf9ANYPGIpGZW7qLFU9/ozhRBCiO7UNdXK74oQQnggST8hhBBCCNGnlud/y40/X4PT6fR2KEKIQSi/No/EIVLaEyBIGwzQryU+qxqrqGysJC1sLOkR4zh/9IW8mfkaBbX5btuVNZSRa8xlZi/n82uVGppGSkgK3+R96Vq2+uBKkg3JjAhO6HH/2cNOQKFQsPbQmiP6XCGEEKIrT297gkuX/4Hdlbu8HYoQQvgUSfoJIYQQQog+lVG5iz1VmeTU7PV2KEKIQSi/Nm/IzOcHLeUxAeqb+y/pl1OTDcDosDQA/pR+GbEBw/jX5oepa6rlUH0Re6oy+Xzfx6gUSqbHzjyi4ysUCk5LPpONJeuoaKigyd7E+pK1LIhf3Kv9DX4hTIiczNriX47sxIQQQogu5FRn02Rv4rbVN7G+eK23wxFCCJ8hST8hhBBCCNGnSswlAKw++LOXIxFCDDa1TUZqLDVDK+mnDQL6N+mXXZ1FiF8IUfooALQqLbdM/zv7jTmc9+WZXLL8Ym78+Ro+zvmQ6bGzXInII7FoxIlolFq+L/iWTSUbsNgszI9b2Ov95w6fx/ayrZj68b+DEEKI44PJaqKsoYzrp/yVmbGz+ee6O1me/623wxJCCJ+g9nYAQgghhBBiaCk1F6NUKFhdtJIrJlyNQqHwdkhCiEEivzYPYGgl/TQtST+T1dRvn7G3Oou0sDFu37djwsfy1KLnqWgox+BnINjPgEEbQqgu9Kg+I1ATyKIRS/g27ytSw8aQEpJCXFB8r/c/Ydg8ntv+DBtK1nFiwrKjikEIIYQAyDfmApAalsayxFN4dttTPLHlUWqbjFyY9jsvRyeEEN4lI/2EEEIIIUSfsdqtVDZWsGjEiZQ3lLOnKtPbIQkhBpH82jw0Sg1xgb1PJvm6oMMj/UzNdf1yfKfTSU7NXldpz/bGhqezIH4Rk6KmkGxIIVwfjlJx9I8BTk8+i4rGCtYc+oWF8UuOaN9I/0jGhI9lzaFfj/rzhRBCCIC82lzUShXxgSNQKpTcMOUmzht9Aa/tfqlfX7IRQojBQJJ+QgghhBCiz5Q3lOFwOlmasIxQXSiri1Z6OyQhxCCSX5vHiOARqJQqb4fSZ/xUfqiV6n57CFlsOkR9cz2poWP65fjtjQ5NJSUkBeCISnu2mjNsHptLN9Joa+zjyIQQQhxP8mvzGBGUgEalAVrmnl2asAwnUFhb4NXYhBDC2yTpJ4QQQggh+kyJuRiA4YFxzI9bxC9FK3E4HV6OSgjRn3Kq91JQm98nxyqoyydxCJX2hJYHkZH6SHKN+7vcJqd6L3etuQ2bw3bEx99bkw1AaljqUcfYWwqFgj+lX8bpyWcyLHD4Ee8/d/h8mu3NbCnd1A/RCSGEOF7kGveTdPgllFbxQQkoFQpXqXAhhDheSdJPCCGEEEL0mRJzCSqFkkh9FAvjF1PVWEVG5S5vhyWE6Ecv7XqeF3c+1+02Tqezx+M4nA4KavNJCh5aST+AkxJP4ecDP1HfRYnPd/a8wcaSDd0mT2ubjDRYGzot31udTWxALAa/kL4Kt1uzh83hxqk3H9W+w4PiSDYks/bQL30clRBCiOOFw+kgvzaPZIN70k+r0jI8MJ6Cur55EUkIIQYrSfoJIYQQQog+U2ouJso/GpVSxdjwdCL0Eaw6KCU+hRjKTM31ZFdndTmqt8RUzJmfn9zjaMDyhjIabY0kdXiINxSclnwGdqed5fnfdlp3oK6QDSXrAciuzuryGP9Y+3ce3PDPTsv3VmeRGtb/pT37ypzh81lfsg6r3ertUIQQQgxCJaZimuxNnZJ+AImGpD6rPiCEEIOVJP2EEEIIIUSfKTGXEBMQC4BSoWRB/CJ+LVqF3WH3cmRCiP5itpoxW80crD/gcf3Wsi1YbBZ2Vmzv9jit5biShlh5T4BQXRgL4hfxZe5nnZKjn+77iFBdKCOCE9hXs9fj/o22RvZWZ7GpdCOZlRmu5XaHnX3GHEaH9n9pz74yN24+DdYGtpdv83YoQgghBqG82lwAUkJGdlqXZEgmvy6vVxUGhBBiqJKknxBCCCGE6DMlpmK3eZ4Wxi/B2GTs8WG/EGLwMlvNQNej1DKqWkr8ZlXv6fY4+bV5BGmDiNBH9G2APuLskedRai5l4+FRfQBGSw0/FCzn7JHnMTY8nb01nv8b7qvZi8PpJMQvhLcyX3MtL6zLp9neTNogGumXFJzMsMDhUuJTCCHEUcmrzSXEL4RQXVindYnBSdQ11WJsqvFCZEII4Rsk6SeEEEIIIfpMabuRfgCpoWnEBMSwupsSn422RjYUr2NvdfZAhCiE6ENOp5MGW0vSL6sq0+M2mZW7UUCPbTy/No8kQzIKhaKvw/QJaWFjSA1L44v9n7qWfZX3BQqFgtOTz2R0aBr5tXk02Zs67bunKhO9Ws/1U/7K9vJt7KrYAUB2dTZKhYKRoaMH6jSOmUKhYO7weawtXoPFZvF2OEIIIQaZPGNul1UBWpe3Vg8QQojjkST9hBBCCCFErzmdTj7d9xH1zXWd1tU312GymtySfgqFggVxi/j10Gp+PvAj64vXsq1sCxmVu/kk50Nu++Umzv3idP6x9u/csvovHKgrHMjTEUIco0ZbIw6nE3+NP9keRvJVNFRQai5l5rATKKo/6PG7o1V+bR6JQ7C0Z3tnjzyXrWVbOFh/gGZ7M1/u/4xliacQ7GcgNTQNh9NJrnF/p/0yqzJICxvDvOELSAkZyVuZr+N0OsmpyWZEUCJ6td4LZ3P0Tkk6nQarmdd2v+ztUIQQQvgoU3O9x+X5tbkkh3ie/3dY4HA0Sg0FdTKvnxDi+CVJPyGEEEKIIcrmsHX7gP1oHKw/wAs7nuPnAz91WldqLgUgNmCY2/ITE5bRbG/m4Y0PcPfaO7jtl5v568rreG33yygVSq6YcBUvLn2VSP8o7lt/Nw3Whj6NWQjRf1pLe06Omkp+bR6Ntka39ZlVuwG4YPSFAOR0MWdds72Zg/WFJAUP7aTf/LhFhPiF8Pn+T1lx4Edqm4ycO+oCoGV0glqpJqfDiEin00lW1R7GhKejUCi4JP0ydlXsZHv5VrKr95AaluaNUzkmcUHxXD7hSj7f/wnby7Z6OxwhhBA+Zkf5Ns7/8kxyjfvclputZkrMJaQYOs/nBy1zio8ITqCgVpJ+QojjlyT9hBBCCCGGqM/2fczVP17epxPZ7z/c8fY0d1eJuRiAYYHuSb9EQxJfnfM9X5/7Ax+e8Rlvn/I+L530Op+e9TUPz3ucc0ddQErIKO6efR9lDaU8s+3xPo1ZCNF/zFYTAFOjp+NwOtnXIamXUbmbYYHDGRcxgQBNANlVnuesO1hfiMPp7LJc11ChVWk5NfkMfixYzgfZ7zFz2AnEBcUDoFFpSDaksLfGPelXYi6mtsnI2PBxAMyMnU1qWBqv7X6Z/No8UgfRfH7tnT3yPCZGTubxLY9gOnwdCSGEEACf7/8Uu9PBV7lfuC1vTeZ1NdIPWl6ikZF+QojjmST9hBBCCCGGqNza/ZQ1lFFtqe67Y3aX9DMVE6AJIFAT1GmdQqHAT+VHqC6M2MBhJBtS0Kl1btskBCdy09Rb+fnACr7K/bzPYhZC9J/WkX5jw8eiV+vZ02Fev4zKXYyLGI9SoSQ1LI3sGs9Jv9a5dxINSf0bsA84Pfksmu1NHDIVuUZAtkoNG9NpNOSeqgyg5b8xtHyf/in9UnJq9uJwOkkbpEk/pULJLdNvp765nhd2POvtcIQQQviIioYK1hevYXhgHCsO/Oi61wDIq81FpVASH5TQ5f6JwUkU1ObjcDoGIlwhhPA5kvQTQgghhBiiSkwtI+88zQ91tPbV5KBWqj3OzVViLiYmIBaFQnHUx180YglnjjyHF3Y+6zGxKISvcTqdPLjhXnKqPZetHOoabC0P4oK0BkaHprm1W7PVTH5tLuMiJgAtCa3sqj0eR/Lm1+YR7R9NgCZgYAL3okj/SBaOWMLY8HTGR0x0Wzc6NJWDdYVuZY73VO0hLiieIG2wa9m06Bmkh49Do9QM6tGR0QExXDPpBn4oWM764rXeDkcIIYQP+C7/a7QqP+6d8yDN9ia3aQXya3OJD0pAq9J2uX+SIYVGWyPlDWUDEa4QQvgcSfoJIYQQQgxRxaZDAOTV9k3Sz+l0kmvcz/y4BUDnublKzSWd5vM7GldNuJaRIaN5YP092By2Yz6eEP3J2FTDqoM/s+LAj94OxSta37731/gzJnwse6oyXEm9rKpMHE4n4yLGAzAmbCzGJmOnh3BOp5N1xWsZFzlhYIP3or9Nu51/LXi600sSqWFpOIH9xhzXsj1VGYwNT3fbTqFQcNO0W7lp2i2oleqBCLnfLEs8hVnDTuDJLY9R22T0djhCCCG8yO6w813+1ywZsZSE4ERmxc7hm7wvXPcWucb9JId0/7JLa9UAmddPCHG8kqSfEEIIIcQQ1GBtwHj44WlfjfSraKygrrmOBXGLCdQEdpqbq8RcQmxA7DF/jkal4aqJ11HWUNYpsSiEryk1lwKwu3KnlyPxDrPVjALwV/szNjydGksN5Y3lQMt8fsF+BuICW+asay1DmVW9x+0YOTV7Kao/yNKEZQMauzeplWqPoxRGBCXgp/JzjZhstDWSX5vLmLD0ztsGJ3DiEPhvplAouGnqLTTYGlie/623wxFCCOFFG0rWUdlYyenJZwFwWvKZ5Bpzyareg8PpIL82jyRD1/P5AUTqI/HX+Mu8fkKI49ZxmfR76aWXOO+885g8eTKzZ8/mmmuuIS8vz9thCSGEEEL0mVJzS2nPkSGjjijp97/sd3lu+zMe17XO5zcydHTL3FztHtw7nA7KzCXEBh77SD9oGe2iV+vZWb79qI/hcDrYVbHDYylBIfpKqbkEaGkf7UsyHi/MVhN6jT9KhbItqXd4Xr+Myt2MCx/vGs0Wqgsj2j+avR1K9/5QuJxwfTiTo6YObPA+SKVUMSp0NPtqWkb65VRn43A6GRvROek3lITqwpgdO4eVB3/qeWMhhBBD1td5X5AWNoaRoaMAmBYznZiAGL7O/YLyhjIabY0kG0Z2ewyFQnF4Xj951iuEOD4N7jogR2nTpk1cfPHFjB8/HrvdzpNPPslll13GN998g7+/f6+OUbO/GgB9hD+6EJ1reUNFA021FpRqJYbEENdyu9VOXWEtAAExgWgD297qNJXUYzVbUes1BA0Pci23NVqpP1QPQFBcMGpd25+r/mAdtiYb2iAtAdGBruXN9U2Yy1pK7BgSQ1Cq2/K6tXk1OBxOdKF69OF613JLTSONVY0olApCkkNdy51OJ8bcGgD8owLwC/ZrO89yM011Tag0KoITDG3n2Wyn7kDLeQbGBqEJ0HQ6T42/hsBhbedpNVsxlbScZ3B8MCq/tvOsO1CLvdmOX5Af/tFt83s01TXRUN5yniHJoSiUbWVxjHk1OB1O9GF6dGFt59lY1YilphGlUoGh3Xk67A5q840ez9NcZqK5vhmVVkXwiLbztDXZqNxbSV1tI7roADT+bedZf6geW6MVTYCGwNh252lqxlRqajnPEQZUWpVrXW2BEYfNgZ9Bh39k2zXYVGuhoaLl4VFISqhb+R9jbg1OpxN9uB5daLvzrGzAYrSgVCkxJIW0nafNQW1By3l2vAZbz1OtUxMU1zZXiM1io76oZb6moOFBqPXtzrOoDpvFhjZQS0BMu2vQ1Iz58Hl2ugYPn6cuRIc+ou08W69BgNCRYa7l7a/Bo2lrgTGBaHrR1qwNVkzFntta6zXYbVtLCkGp6kVbq26ksdpDW3M4Meb10NY6XIPdtrXieqwNPbS1Dtegq60F++Ef1f9tLSA6AG1QL9pau2swcFjQkbe1BAMqTc9tzWK00Fjpua25vu87tDVzhZma/GocCtyuwW7bWqmJZpOHttbd931rW+t4DXbX1vKNOOxdtzWFQkFIShff95H++Bl60dbaX4NH0da6+r7veJ7tr8F+bWtlZprqPbS1Jht1Bw9fg121tY7XYHdtrbAWu7WHttbx+761rXX8vu+qrR2+BvPL8lA3qpk3bgFvZb5Gk70JW6W15fveT01QvOfv+5/3/USJrZgrJ1yDRqVxa2v7anII1gYTqY9ktC6NVTtWUB1dhSExhMrmCuxOBzEBsb1qa+2/76FzW1Mr1YyPmMDOfds5WXPqEd1btba1Two+5IOa93nhxFcZGTrq6O6tumlrxnwj1iZbn7a1bu+tetvWjvHeqmNba70GO7a11muwv9tal9/3R9PWjubeqrWtdXFvVZxXhNaioVlnZU9VBtNiZrTdW3XT1jrdWx0+z+7urXr9u9bFvRX0bT/GXGrClFtPaF3L3z9UF0ZMQAxZJZmMaxzPgT0FnD/3QrfPH2tLJzdjP+YYEwHRgdgcNlYd/JmTIpZRm2sE+rgf07Gt9Wk/phnj4eu2L/sxo1SpbKhumd9uT1UmwZZgQsoNGKtq3M6zu35Mr9ra0dxb9WM/Zn7QQp7a+i8yo3eTPmF823n6UD+mt23NF/oxffrMoKt7q948MxiofswAPTMIiA5A3b5P0F/9mF62te76MT0+M+hwDR5VP6Z9W+uqH9OHzwy6u7fqdVs7xn6Mzz0z6Or73hvPDLrqx/SyrR0yFpG9M4tLx19Bc30T2iA/lAolpyWfyQfr3iOtYQz6Kj3JIW0j/bpqa0mGZPbn5FATXt3nzwwiUsNpr6tnBl1dg/LM4NieGfRFP2ZQPjPo7t7qKJ8ZQNfP57zWjzmCZwatjrYf02xqPqp8jH+IjtBQ356H/LhM+r322mtu//+RRx5h9uzZZGZmMn369F4dY/0/fwEFjPvTRJJPbvuxOfBjHnnf7cc/wp8Tnz3ZtbzZaGH9vb8AMP2mWcROb3sLft/H2ZRsOkT4mAjm3D3ftbz2UL1rn/kPLSak3UOG3a9sx5hfQ9zcEUy5dppreWlmBdue3wLAspdOc7swtzyxgaa6JkadncqYC9veFC1ZW0TWB5motCpOe+ss13J7s931+RMum0ziiUmudQXf7afgp3yChgWx6ImlruWWcrNrn1m3nUDUpBjXur3vZVK2o5So8VHMumOua3nNgVrWP7QGgEX/OtHtR23nC1upL6ojYVEiE/88xbW8eGcZO17eBsCpb5yJut2X46aH12Kz2Ei7YCyjz01zLT/0SyE5n2ajDdRy8iunu5Zbm2yumCdfPY34+SNc6/K+3MfBXwoxJISw4JHFruWmUjNr7liJ1WZn9l1ziRgb6VqX9c4uKjMriJkay4y/zXYtr8qrYeO/1gOw5Oll+LX7gdrx3BbMZSaSlqUw/pKJruUHt5aw+42WUlGn//dstx+uDQ/8isPmIP3i8aScPqptn58L2P9VDrpQHSf951TXcoup2XWe026cwbBZca51+z/J5tD6IkJHhjHv/oWu5fWlJtc+8+5bSOioti/bzDd2Up1TxbBZw5l240zX8vLsKrY8sxGAk/5zCtp2X8LbntpIY3UjKaeNIv33bR35so3FZL67G4VSwRnvnuNa7nQ6XZ8//pKJJC1r19a+zyXv+1wCogJY8kxbWaPmmkbXPjNunk3MtLYyc/s+zKJkSzERYyM54R/zXMtri+pYf/+vACx4eDG6dj8QGa9sx1hgJH7eCCZf09bWSjIq2P6flrZ28sunow5qa2ub/7WeZlMzo89JI+03Y13Li9ceJPvDPaj91Jz65pmu5bZ21+DEK6aQsDjRtS7/2/0UrsgnaHgQix5va2uNZe3a2t/nEDUh2rUu+70MyneWETUxmlm3z3Etry40suHhlgdIix5f6vajtvM/W6g/VE/CkiQmXj7ZtfzQjjJ2vnK4rb15Jmp1u7b20FpsTTbSfjOW0ee0a2urC8n5rHNba25s19aumUb8vHZt7YscDv56gJDEEOY/3NbWzJUNrn3m/GMe4e3b2tu7qNxTQey0YUy/eZZreeX+GjY90dLWTvz3Mvwi27W1ZzdjLjeTvCyFce3aWsXWEna/2dLWznjvHLebpw33/4rT4XRrayqVkpzPstn9USa6UB1Lnz/Ftb2lvqldW5vJsFnDXev2fZJF8YZDhI0OZ+69C1zL60vb/p7z7l/odmOT8doOavZXM3x2HFNvmOFaXp5dyZZnNgFw0gunom3Xwd361AYsNRZGnjGasb8b51re2taUaiWnv3O2a7nD7mhra/83kaST2tpa4fe55H+fS0B0IEuePsm1vKmqra3NvGU20VPa2lrOB3so3VpCRHokJ9zV1taM7drawkeXuN0o7355O7WFRuLnJzD56raRHiUZFWx/oaWtnfLq6aj9PLS1c9NIu6BdW1tzkOyP9qDWqTn1jXZtzdJ2DU768xRGLEp0rcv/Zh+FKwsIigtm0b9OdC1vLG37/Z59x1wix0e51mX/dzflu8uJnhTDzNtOcC2vzq9hw6PrAFj8xFL8hnVoa8X1JJ6YxITL2tpa0bZSdr3WMqLttLfOQqVp+77f+OAa7M12xlyYzqizU9v2WVXAvs/34hfsx7KXTnMtb2qwsv7eXygxFRM9K5Lpw6bzZuarHDQV0PC5maI1BwhJCmX+Q4tc+5gqWtqa3WGjelYFTbEWcmqzmBg1iT1v7aQqq5LYGcPJnbqP0WGj0WhUJBkTKPjfCFav/InTXjiLCkcZCgXEG+LY/ugmGiobSD5lJOP+2DZHV/mWEjLeamlrZ75/Lu1tuO9XnE4n6X+YQMqpLW/vTomZyo9fLGfdh6vwDw9wa2vW2nb3Vn+ZSezMdm3t4yz2rM4gU7MTxbmQX7+ftMhU6orbftfmP7DIrSOb8dp2anJriDshninXt90Plu2pYOuzm4G2eyvV4d/jzf9aT2NNI6POHM2Y37a1tdL1h9jzfgYqjYrT3m67t3LY2trahEsnkbi0bT6SwuX7yf8hj8CYQBY/1a6ttfse7NjW9r6fSdn2UiLHRTH7zrZ7K2NRHesfONzWHltCcHxbW9v10jbqDtQyYmEik65su7cq2V3O9he3AnDKa2eg9mu7Bjc/ug5rg5XU88eQet6Ytn3WHCT74z1o/DWc8toZruW2RmtbW7tyKiMWJrjW5X29jwOrCggeYWDho0tcyxtK2r5TZt85l8hx7m2tIqOc6MkxzLy1ra1V5dWw8bGWtrbkqZPwa9fB3PH8Fkwl9SQuTWbCpZNcy4u2lbLr9R0AnP7O2W4PPzY+uAa71c6Yi9IZdVa7traygH1f7MXPoGPZi233Vq1tzWisIu2kMRxIPMCe6t3MiptF7md7KVp7kJDkUOY/2K6ttfv9nvvPBYS1e2i0540dVO2tInbGcKb/te3eqmJvFZufbrm3WvrcyfiFt3Wwtz+9iYaqBlJOHUX6H9rdW20uIfOdXSgUCs54r+3eCnB9/rg/TiD5lLY35bvqx7i1tb/OInZGWz8m56MsLD+aSYgYgfrSlv+WYyPSyc/J5eevvietYjSj545C3e6/87CfYmna08i+umymXT+DTYc2Ud9cy/TG6a7P6XU/Zl0RWf/L7NTW7NZu+jHLcyn4MY/A2CAWP9muH1PR0HU/pkNba/0OqCuodbW1jv2YXS9upe5gXae21l0/ZvMj67A2Whm+MJZSQwkN9nqya/Yw8eAENvywBm2AlpNf7aIfc9VU4he0a2tf5XBgdSGGBAMLHmnX1orb2toJd80jIr3t3qq1rcVMiWXGLV30Yzq2tdZ+zEnJjP+/Sa7lbm2ti37M2N+NY+QZo13LIzPDmfT5RNZuXMXE99vu05rMbf2YqTfMYPjsnvsxbm3t3gWEjW5ra73pxyx9/hS0Yb3ox2wqJvO/3fdjOj0z+CGPvOX78Y8M4MR/97If81EWJZuLPT8zuK9ln479mK6eGXTqx7Rva49voKm+c1vrqh/T/pnBxMsnk7Ckra111Y9xe2Zw+xyiJnrox0yIZtbf2/oxvXpmsDiRiVe0tTW3fkzHZwat/ZhePjNotrj3Y4IWJgItfYKunhmYq7rpx3TxzKAyt4ZNjx/uxzyzDL+ozs8Muu3HvHuOW3Jzw/2/4rB7eGawIp/9X+9DH6bvph/T4ZnBpy1tLWxUGHPvW+haXl/SzTOD13dQva+HfkwXzwxGnj6KsRd3fmagVCk5/b9nu5Y7Hb14ZtChH9Nc3a6t/W02MVN77se4PTN4ZDG6hBDXum77Ma1t7ZUj7Md0fGZg6e6ZwT4Kf/bUjzF13Y95N4PyXR6eGRQY2fBIyzMDj/0YT88Mtpey81XP/Ziunhm4+jFBfix7ua0f813OV0z6fAKKDQ6qrq1wPTM4beRp/PrMSna9v5WxkWOIvjbS1Wd3e2Zw93zCx0QAkBKawoFv81n3zWqGzRjO9Jt698xg+78301BhJvnkkYz7k+d+zNkfnAfguh9wPTP4/XhSTnNva7nfdG5rjXVH/sygrqS7foznZwZlWZVs/XdLW1v24qmodZ2fGXTqx2w4xJ73Mrp9ZqA+U8P/gt/n7dPeA9r6MZ2eGXTTj8n53x5Kt5V07sccbNeP6fTMYBu1hbWMWJDApKvatbX2/ZgOzwy2PLaeZnMzqeeNIfX8tn5M8a+H+zF6Dae83q4f080zA1c/Jj6YhY/17plB1jue+zFuzwyePAm/2F70Y7aXtT0zePssVO37MQ900Y/p4ZkBwJTrphM3J961rst+TLvf7zn3zCc8LcK1bs+bO6nKruzcj8mpZvNTGwAP/ZhnunhmsLmYjLd3Ab17ZgBw8Kd8cr/dh3+4Pyc+10U/psMzg5yPslryManhzPlnu7bWzTOD3a9ux5hXw4h5I4i7s+3+xRcdl0m/jurrW7K3BoOhhy3baLQqFCgIDPRzy+wGBPih1ajR+qndlmttoNW0/OcODta7rdPrNWg1anQ6jdtym6HBtY/B4L6Pn06NVqPG31/rtrw2SO/aJzTU/Y0ErVaNU2MnIKBDzIEtMau0Krfl9ma761hBQe4ZbH9/z+epami3T4fz1LWep9495qbgtpgNIf4Y2p+nn5omjRp9h/OsDtK5nWf7jopWq0Zpbzkvj38brXvMzVpNN+epRatR46dz30dRawVAo1Z1+nvqdC3H03c4z4Z25xkS4k9gh/O0evh7VgS6n2f7zrJWo8ahcHR5nn5a9+upEWW78+xwDR4+z47XoMNgabtuDb07z/pgXbvzDEDf7gZeq1Vj16i7vAYVSoXbcqfT6TpWYGCHv01Xbc1Ku2tQ5/ka7HCeVoO5XVvz79DWDp9nh7+Nsd01GBLqj1+Qe1tD4+h0noGH/57qDtegrcnW8zXo5x6zytzW1jp/p2g9/m0sHa7BYLdrUEOTh2uwU1vz69DWHJ3/Nl21tSa1usvz1Lvamvt5UtPc7hr093gN6vTu+5g7XIMB7a+P1rbW4W/Tsa21T/ppNWqcDmentgYt3wEdz7PRqezyGmz923S8Bu2Gxi6vQV0X12B9kPvfs31b89NqcGhsXbY1pVrp3tbtjq7bmusadD9PTZOz3Xl6vgY7nmdzsMntPEN68bvm3tYC0Aa0vZnVVVtrPc9Obc3S1tYCu7oGO5yn0mTrsq3pWs+zwzXY2OF3LbjDNdhynu4xV3Voa+3f9NNq1didil7/rjWpWj7D6mwmJiiGqYkT0KjVlFoPEuMf4/F3zVndhFajprqxDoVSgV6rY0/dThamzmn3fa+h0JzHspRlhIYGMC5uDCsVP2FxNBAS4k99dTVqtYrU4cnk+e3F5uH7PvDw36b1PNvTaFTgxO3easGoOXzPN1gcjYT6hbh/P9sVXV6DNmUTucb9xI+Kpy6kjtLmIkJDA9zurTr+rnX1fV/Xoa3p2r3VqtGosHv4TnG1NU2Htmbrrq15/l1TWxx929b8PLe1mg7XYPsRCVqtGoXV2WVb03S4Bq06ay9+1zrcW9VZu2lrnu85Ora1oA7n2ezhPCs7nGf7pJ9Wq8aOosvfNb8O52lRqlxtLdYQTXRcJHvr9hAaGnBU91Z+7dpa++Umt9/vAPxD296E1fqpsWnU+AdoPbc1Ree21tU12FU/xr2tdfxd0+BUONBp266N6SOm8Pq21xljT0WlUjEhbqzbPrGGaPLYTwN1hIYG8OvWlaRFpZIakUK1ptz1t+lNP6b13qpTP8baXT/G8zWobuxFW+vwtwlsd/9gMHTsx2g8trWe+jEKm5OEqHhUNiXF1kJyarM4Lfy0HvsxXf+uucesqO2mrXVxb9XQQ1uzevhdq+xFP6bjNRgc5E9UQCRlDaWEhPi77scsClWP95DdtbUu76267cf4u7U1Pz8Ndo21y2uw+36M+z7+AZ6vwe76MV1933ffj+nNvVXnfkx3ba3jvVX7ZwYdr8Eu+zENPfdjOl6DvXlm0PEa7PGZgeMInhlo3J8ZBAfrXfF39cwAY8/9mO6eGRi6embQUz+mXdJPo1HhVCo7nad/F+fp1o/p+MxA77m/1r4f0/XvWnf9GM/PDLq6t1KoOrQ1R8/PDDr1Y5qdPV+DfdzWQkMD3EaYHEs/pqvnc0fWj/H8t7F004/p6plBT/2Y3j4zaLY3s6poBfOC5qHTat3OM5QAUiNHU5lTSZh/KGFhbQkS92cGbec5MT6dnxU/YMfa6Ty7e2bg19O91eH/nu3/t/WZQZf3kB2+B/0c3d1b9fzMoMvnc536Me7n2X4kbOszg45trfX7vrtnBjX2akoaDmEI0aNUKLu8Brvrx3T1fK77fozn86zp6ZlBc9dtrWM/prtnBl39rinrj7ytNXZ4Ptebfkyntqbp8Mygm35MV88MoPf3Vk5DUy/urTr2Y9yvQU/9mK7uOVrPsz1Pzwyg7d6q+36M53xMx9+17p4ZtJ6nn66tr+yrFM7jfJITh8PB1VdfTV1dHe+//36v99u/4QBKpQJ9ZMfyAWaajE0oNR6Gkxa0G04a1G5Ic3HrkGYPQ7eLDg8nje9QPuBgLXbL4fIB7d60bKproqF9+YD2JajyanDanejCdOjDOwzdrjw8pLnj0O39h4c0R3so1VHbhFKrxNDuDSd7c7uSJMMC0QR4OE//jiWomjEVm1rOc0SwW1Kh7kAt9iY72mA/AjoO3S5rVz6gfamO3MNDt8P16N3KBzRgqbagUCk6l8XJM3o8T3Pp4VIdfu5Dt502B47qJkwmC/4xge6lOorqsDXaWoZut3srqtnUjLmk5TyDEzyU6rA68Avxw7/dG0ZNtRYayg8P3R7poeSgE/QRHYY0VzbQVGNBoVa6jQ512NqVJOlwDbaeZ6dr0GKj/mBrqQ4PZXEabWgCtQTGti9h0a58QJKHUh1WB36hOvw7lg+oPFwWp92bge2vwaNqa7EdSul20dasDVZMh7poa63XYHdtLdlD+QAPba2xuhFLlYe25mhXJqGLttbxGuyurdUfqsfW0H1b63gNtp6nn8FDqQ4vtrX212Dg8KAjb2uJHsoHeGhrFqOFxoou2tq+1jJobW1NpVKianJQcaAGlIrOpTq6aGumEhNWk4e21s33fet5drwGu2trxnwjTls3bU3hoQRV6/d9VMdSHV20tXbX4FG1ta6+773U1sxlZprrOrc1W5ON+gOt5WI8t7WO12B3ba220Iij2dF9WxvpoTSTw9np+77Ltnb4GvzXpofRRGq596QHueTb3zMleiqXDb+ipa3pVG6jv1rb2id7P+Q783dMjp/MIdMhXjjpFdc1aNFYuHjDhdw1+58sTlhCc30zV71/OVOip3L1qdfxZtZr/FDwPR+c+Umv2lr773vw3NYcTgcXvHk2p0WfyXljz+/VvZXVbuXmj2+k3ljPgyc+ygvFz9Foa+DxRU8f1b2Vp7amUikJDtZzYEcxtmZ737a1bu6tet3WjvHeqlNba/2+79jWWq/B/m5rXXzfH1VbO4p7K9d5dnFvdevqm5mYOpmYqBhe2fkSX533HdaK5m7bGhzdvVWvf9e6uLeCdm2tL/oxJSYeX/UIzdpmHjrvMQD2VGZww7fXMsKSQIQ+nIcu+JdbW6vIL+fyLy/hkpmXceKUkzj/87O5dPzlnD383P7px3Rsa33Qj2n9DqgqqaW29e/Zh/0YbZgfF606j3lxC1ie/y33TXiIdE16p/Ps9t6qN23taO6t+rkfs3P/dh7cfB+P/vYJ0iNaRh74VD+ml23NJ/oxffjMoMt7q148MxiofsxAPjPwD9UTHKynrq6RukN1/dOP6WVb67Yf08Mzg47X4FH1Y9q3tS76MX36zKCbe6tet7Vj7cf42DODrr7vvfLMoIt+TG/a2orCn3hozX38e+x/GBY4rNN5bty9ngd/vo+TRp/Cdafc4FreVVszWmq4+PXfcP24m5g7cm6fPjMITw3HYPCnrq4Ru93hsR8DXV+Dg/2ZwQdl7/Nh0f/46rzlBGgCBv6ZQV/0YwbjM4Nu7q2O9pmBx/NsfT7nrX7MET4zgKPvxxxpW2u9t9KF6Bg2um0Evy867pN+99xzD7/++ivvvfceMTExPe9wWEVFfT9GJXyd+vAbLzU1Zmw2h7fDEUIMMPkOEIPBH7/7LXOHzePPE6/hwQ33UtFQztOLn+92n1tW/xW9Ws+c4fN4YvMjfHTmFxj8QgDYVraF2365mddPfof4oJZSO+2P+9CG+6iyVPLEwn/36XncvfYOzFZTr4/7wo7n+DL3U55a9DxpYWN4M+M1vsn7ko/O/KLPYpLvANHK6XRy2qdLuXzClYwLn8C1K/7MU4ueY1zE+J53HiJuWf1XQvxCuHPWPUDLm/pnfX4KNoeN3435A/837vJO+1z146WMCk0lLWws/972BO+e9jER+oiBDv2oDcR3wK2r/0pG5W6sDiufnvUVQdrgnncaAhxOBxd/cwGzh83lhil/9XY4Qngk9wFC9L0ntzzG3uosXjrpDY/rnU4nT2x5lJOTTuv1fdYFX57F6Sln8af0S/sy1OP+O+DprY/zTd5X/O/0TwnXh/e8gxBDjLrDSFhfpOx5k6HrvvvuY9WqVbz11ltHlPATQgghhPBldoedcnMpsYHDAUgJGUlebS4OZ9edUrvDTnb1HtLDxzElahpOYFvZVtf6fTU56NQ6hge2ze+SFjaGnJq92Bw2ShtKiAmI9XDkYzMpajJ7qjJpsjf1uO2qgz/z6b6PuHLCtaSFtczZkGRIxthkpMZS3eexCVHTVI3VYSXGP5aUkJHo1XoyKnd5O6wBZbaaCNC0K1Go0jIypGU+m64eyqWFjSW7KosVhT8wKWrKoEr4DZTUsDSsDivxQSOOm4QfgFKhZFH8ElYXrcTmsHk7HCGEEAOkoC6fpJCULtcrFAr+Nv32I3qxKsmQTEFtfl+EJ9oxW1tG1TXaGrwciRCiK8dl0s/pdHLffffx448/8tZbbxEfH9/zTkIIIYQQg0R5Qxl2p4NhgcMASDaMpNHWSJm5tMt98mpzsdgspEeMJ9I/koTgRLaVb3GtzzXuJ9mQglLRdvuYGjYGq8NKfm0eJaZiYgOG9fm5TIqcjM1hY09lRrfbbS/byqObHmTxiCWcNbJtwu/kww8P8mvz+jw2IUoPt6nogGhUShVjw9PZXbHTy1ENLLPV7Jb0g5aknlKhYGz4OI/7pIWNpbAun92Vu1iasGwgwhx0RoemATA2PN3LkQy8JQlLqWuqdXvxRAghxNDldDopqM0nMTipT4+bZEiRPkA/MFlbqt812S1ejkQI0ZXjMul377338uWXX/LEE08QEBBARUUFFRUVWCzyZSWEEEKIwa/YfAiAYQFtI/0A9hv3dblPZuVu1Eo1o0NTAZgaPZ2tpZtprQS/37iPkaGj3fYZFToalULJtrItGJuMxPbDSL9EQzLBfga2V2zrcpuc6r3cs+5OJkZO4m/T/u42v8HwwDg0So10+EW/KHMl/Vqu/fERE8mo2t3tqNqhpiXpF+i27KyR53D95Js6JQNbpYWNwQn4qfw4Ydi8AYhy8Ek9PFq5q8TpUJZsGMmI4AR+PvCDt0MRQggxAMobymi0NZJoSO7T4yYakig2FfWqYojovbaRfvIcXQhfpe55k/6xY8cOli9fTklJCU1N7l++CoWCF154od8++/333wfgD3/4g9vyhx9+mHPPPdfTLkIIIYQQg0axqRiVQkmUfzQAYbowQvxCyKvNZV7cAo/7ZFZlMDo0Fa2qZXLrqdHT+XTfRxysP0CkfxRF9Qe4IPUit338VH4kGVJYXbQSgJh+GOmnVCiZGDmJneXbPa4vqj/IHWtuZURwAnfPvh+NStNp/4TgREn6iX5R1lBKkDaIwMNJr/GRE3gz8zXya3NJOVzicqhr8DDSLy4onrigrqupjAhOQK/Wc8Lwufhr/Ps7xEEpyj+KR+Y/zviIid4OZcApFAoWx5/I//a+S6OtEb1a7+2QhBBC9KP8upYSnEl9PNIvMTgJJ1BYW8DosNQ+PfbxzNRsAqS8pxC+zCtJv7feeouHH36Y8PBw4uPj0Wg0Pe/Uh/bu3TugnyeEEEIIMZBKTIeICohBpVQBLQ9Qk0NSehzptzB+sev/T4iciFqpZmvZZkaHpuEE1zxd7aWFjeHrvC8BiA3s+5F+0FLi8z87/k2DtcEtQVDZWMnff/0bwdpgHpz7aJfJg+QQKe0j+kepucSVXIeW0VlqpZrdFbuOi6Rfs70Zq8OKv/rIEndKhZIH5j7C8ECZZqE7U6OnezsEr1k84kTezHyN9cVrWTziRG+HI4QQoh8V1uajV+vd7qn6QpIhGa1Ky/byrZL060Ot5T0tMtJPCJ/llaTf66+/zu9//3vuuOMOlMrjssKoEEIIIUS/KTGXdCq1OTJkFKsPrvS4fXlDORWNFaRHjHct06l1jIuYwNayzagUKlSHR8x1lBY+lq/zvkSr0hLqF9an59FqUtQU7E4HmVW7mR4zE4CKhgpu//VmbA4bTyx8FoNfSJf7JxmSWXXwZxxOh9uchEIcq1JzCTHt2pqfyo/U0DR2V+7i7FHneTGygWG2trzp3bG8Z29MiJzUx9GIoSQ2cBhpYWNYeXCFJP2EEGKIy6/LI9GQ5Faivy/o1DpmxMzil6JVXJj2uz499vGsdaSfzOknhO/yylOPxsZGlixZIgk/IYQQQoh+UGI+5JrPr1WyIYWyhjJMzfWdts+s3A3A2PB0t+VTo6exs2IHWdV7SDQkuUp/tpd2eN6p2IBhfd5RbxUfNIJQXSg7ylvm9SuqP8hfVl6DxdbIvxY8TZR/VLf7JxmSabY3U2w61C/xieNXqbmUaP8Yt2XjIyewu3Knaz7Moax1Tpeu5u4T4lgsjF/MltJNmA4nl4UQQgxNBbX5JPZxac9WC+IXkVOzl1JzSb8c/3jTWuUBZE4/IXyZV7Jup5xyCr/88os3PloIIYQQYkhzOp0Um4qJDXSfX6+11GBebW6nfTKrMhgWOJxQnftIvWnRM7DYLKw+uLLLUoXxQSPw1/h3+ry+pFAomBQ5hR3l29lXk8NfVl6HXu3P04v+0+28Ya2SDMkAUuJT9CmH00F5QxkxAe5Jv3ERE6mx1HDIVOSlyAZOW9LvyEf6CdGTeXELsTlsbChe6+1QhBBC9BOH08GBukKPFUX6wszY2WhV2i4rnnjSbG/ul1iGAnO7F3FkTj8hfJdXkn533nknlZWV3HzzzXz88cf88MMPnf4RQgghhBBHzthUQ6OtkWGB7iP94oNGoFFqyDXu77TPnqoM0sPHdVqeHJKCwS8Eq8PKqJDRHj9PqVByevKZnDBsbt+cQBcmRU1hvzGHm1fdQGxALE8u/DeR/pG92jfULwyDX4gk/USfqrHUYHVY3cp7AqSHp6MAMg6PoD1aFpuFuqbaYzpGf2s4nPTraj5NIY5FlH8UY8PTWV20ytuhCCGE6CfFpkNYHVbXS3p9Ta/Wu0p89kZG5W7O/vxUysyl/RLPYNf6whfInH5C+DKvzOmXl5fHtm3bOHToEN98802n9QqFgqysLC9EJoQQQggxuBWbigEYFuA+8k6lVJFoSOqU9GuwNpBr3MepSWd0OpZSoWRK1FRWHlxBSqjnkX4AV0y4ug8i796U6Kk4nU7GhI/lntkPHFGSQaFQkGRIlqSf6FOtZaKiO4z0C9QGkRySwo+F37NoxBL8VH5HdfwXdz5Hfm0ezyz+zzHH2l/MNinvKfrX/LiFvLr7JUxWE4EyolQIIQZcfXMdb2S8yrmjLuhVhY0jVVCXD0CioX/Ke0JLic8HN9xLiYdqKB19X/AtVoeV3ZU7O93jCfekn8zpJ4Tv8spIvzvuuAN/f39efPFFli9fzooVK9z++emnn7wRlhBCCCHEoFdibpm3Liagc4c22ZDSKemXU5ONw+lkXMR4j8ebPWwOOrWOFMPIvg/2CMQExPLSSW/wwJxHj2pUUZIh2WNpUyGOVllDyxvgHef0A7h03JVkV+/hltV/wWipOeJjO51O1hev5ZCPz0Mp5T1Ff5sft0hKfAohhBf9fOAnvsr9gmtX/Jl1h9b0+fELavMJ1gYT6hfW88ZHqbXEZ0+j/ZrtzawpapmOKqtaBqN4YrK2zA8fpA2SOf2E8GFeSfrl5uZyyy23sHDhQhITExk+fHinf4QQQgghhDun09njNsWmYkL8QjwmxkaGjKKwrgCbw+ZallmZQaAmkBHBCR6PtzB+Me+e+qFPlO9LMiSjUWmOat9kQwolpkM02hr7OCpxvCozlxKkDfI4ym1G7EyeXPgsJaZibvj5ag7WHziiY+fV7qfaUk1tk9Gn55UxW01oVVrUSq8UkBHHgUj/yJYSn0cwF5MQQoi+s654Denh45gcNZV71t3J6xmv4HA6jvg4Xe1TUJtPoiEJhUJxrKF2Sa/WMzN2NquLuv8t2Vq2GZPVxKjQ0WRX7em3eAYzU3PLnH7hugiZ008IH+aVpN+YMWOoqqryxkcLIYQQQgxK28q2cP6XZ2Jqru92u2LzoU7z+bUaGToaq8PKH7+9iHvX/YP3s/7L+pK1jAkfi1Lh+bZQoVAQ7Gc45vi9LcmQjBM4UFfo7VDEEFFqLvE4yq9Valgazy55EY1Ky40/X8Ouih29Pvbm0k2uf6+xVB9LmP2qwdqAv9r7LwSIoW1+3EK2lG3u9Ptnaq7ns30f02Rv8lJkQoiB9GPBcp7c8pi3wziumJrr2Vm+nUUjlnDP7Pu5bPyf+SD7Xe749ZYe+yTtGS01nPvF6Wwt29xpXUFdPon9NJ9fe/PjFrKvJoeSw1MheLLywAoSghM5OfFUco375PfFA5PVhAII1YXKnH5C+DCvJP3uuece3nzzTdasWYPNZut5ByGEEEKI49yW0k3UNdexoWRdt9t1N1fF2PB07jnhfhaNWILJauJ/e99lb3U2k6Km9EfIPiUhOBEFyLx+os+UNpQQExDb7TYxAbE8s+h5UkJGceea23qdwNtcupGYw/PIVDZWHnOs/cVsNUlpT9HvWkt8rm9X4tNqt3Lv+rv5z45neWLzo70aCS+EGLxWHfyZf21+mO/yv5EXuNrp7+++TaUbsTsdzB42F4VCwUVpF/PwvMfJrMrg030f9/o428q3YLaa+Sr3C7flVruVovoDJAYn9nHknbWW+OxqtF+jrZF1xWtYPOJExoSnY3c62F+zr9/jGmzMVhP+mgACNIEyp58QPswrSb/f/e535OXlccUVVzBx4kSmTJni9s/UqVO9EZYQQgghhM/aW5MNwNoe5tIoNh1iWIDnkX5KhZK5w+dzxYSr+deCp/jsrG/476kfcO6oC/o8Xl+jU+sYFhgn8/qJPlNmLiM6ILrH7QK1Qdw9+15UChX/y36vx+3NVjOZlbs5OfE0AKotvlshxWw1eyxvKkRfivSPJD18nGsuJqfTyTPbniCjcie/Sb2IlQdX8MHentuWEGJw2ly6kUc3PcCC+MX4qfxYV9z388oNRla7lat/uoz3st7pt89YX7yWUaGjifKPci2bEj2NSVFTyKjc1evjtFYw2Fiyjtomo2t5kekgdqeDxOCkPou5K64Sn12Ui95QvI4mexML4xe3TCmg1JBdLSU+OzJZTQRqAvFT+8m0CUL4MK9MvnDppZf2a61mIYQQQoihxO6ws7c6mwh9BJtKN2CxWdCpdZ22a7Q1YmwyMqyLkX4dKRVKogO6Lk841CQZkmWkn+gTDqeDsoZSYvy7H+nXKkgbzPmjL+S9rHc4f/SFRPpHdrntjvJt2J0OFo84kXez3qbKp0f6SdJPDIz58Qt5ZdcLmJrr+Sr3C74v+I7bZtzBiQnLUCnVvL77ZRINycyKne3tUIUQfSizMoN71/2DqdHTuW3GnTy44V7WHvqVi9Iu9nZo3dpbnY3ZamJK9LR++4zVRT+Ta8wlz5hLalgaU6On9+nxm+3NbCxZz29Sf9tp3bjw8fw36y1sDluP8/o6nU62lm3mpMSTWVH4AysPrODsUecBLfP5ASQa+j/pB7AgbhEPbPhny0uSHaZDWHlwBalhaa7lo0NTya7OGpC4BpPWez+9Si9JPyF8mFeSftdff703PlYIIYQQYlAqrMunyd7Etek38uSWx9hStom5w+d32q7E3DJHRWwXI/2Od0mGZL7I/Qyn0ykvoIljUm2pxuaw9Vjes71zRp3PZ/s+5v3sd7hhyk1dbre5dCPDA+OIDRxGuD6cKovvJv0abGYp7ykGxLzhC3lhx3M8seUx1hz6hT+MvYQTE5YBcEn6ZeTX5vHQhnt5dsmLJAxAmTghRP/LNe7jrjW3MTo0lbtm3YtaqWbO8Lk8uukhKhoqun2BxpscTgcPb7yfJruF9077uF/uOZ1OJx/nfMDUw0nFhzc+wItLXyNCH9Fnn7GzYjuNtkZOGD6307pxEROw2CzkGveTGpbW7XHya3OpsdSwZMRSTM0mvi/4zpX0y6/LI1wfTpA2uM/i7s6M2FloVVq+yv2cKyde61puaq5nc+lGLh9/pWvZmPCx/Fq0ekDiGkzMVhOB2iB0ap3M6SeED/NKeU8hhBBCCNF7WdVZKBUKFsYvJjE4iTWHfvG4XevE9L0d6Xe8STIkU9dUS01T7+ZVE6IrZeZSgCMaKRugCeA3qb/l27yvKDWXeNzG6XSyuXQj02NmAhCui/DxOf1kpJ8YGJH+kYyLGM+aQ7+wJGEpfxh7iWudUqHk9hl3EeUfzd1r76C+uc57gQohjllebS6PbHqAa3/6M9EB0dw392FXhYuZsbNRKZRsKFnbw1G8Z2PJeg6ZiqhsrCSvdn+/fMauih3kGnM5f/SF3DbjTlQKJQ9vvB+H09Fnn7Hu0BpiAmJICk7utG5U6Gg0Sg2ZVbt7PM6Wss1oVVrGRUzgpMST2W/c5yq3X1CbPyClPVvp1Xp+l/YHPs75kDczXnPNibjm0K/YHTYWxC92bZsWNpayhjKfLrPuDebmljn99Gp/mdNPCB/mlZF+f/zjH3vc5u233x6ASIQQQgghfN/e6iwSg5PQq/XMjZvP5/s+wWq3olFp3LYrNh1Cp9YR4hfqpUh9W5Kh5aFFfm0eYbpwL0cjfJndYSfXuJ/dlTvZVbGTCP9Irpt0o+tt/bKGlqRdtP+Rlcc9a+S5fJzzAe/seZNbpv+90/oD9YWUN5S3Jf30EYOgvKeM9BMD46K03/Nr0SpumHJTp5EzAZoA7pvzENf8dAX/3fM2V0+6zktRCiGO1u7KXbyf9Q6bSzcRqY/k8glXcWrSGfhr/F3bBGmDmRA5iTWHfuGMlLO9EmeDtYGv877g9OSz3GJr9XHOB4wOTeVg/QHWF68jJWRUn8fw8b4PSQhOZGr0dBQKBXfOuodbVv+Fd/a8yZ/SLz3m4zucDtaXrGVB3GKPIxW1Ki1pYWPIqNzd49zgW0o3MTFyElqVlhkxswj2M/BjwXKunHgthXUFzB52wjHHeyQuHvtH1Eo1r+5+CZPVxDWTrufnAz8yPnKS20jJMeHpAGRXZXkc7Xi8MllNxATE4qeSOf2E8GVeGekXGBhIUFCQ2z9Op5OMjAwOHDhAcPDADOsWQgghhBgMsqv3kBY2FoC5w+dhsprYWbG903Yl5mKGBQyT0pVdGBY4HD+VH/tr9nk7FOHDXtz5HOd8cRrXrvgzr+1+mcrGCr7c/xkbSta5tik1lxKsDfb4sK87OrWOi8f8kZ8Kv+dg/YFO6zeXbkSj1DAxahJwOOnnw2+Ym60mGeknBszM2Fn8bfrtaFVaj+uHBQ7n9OQzWV7wDQ3WhgGOTghxLCoaKrhl1Y1UNlZw24w7ePvU/3H+6As9/s7OGT6PneXbMTXXeyFS+N/ed3ll14u8lvFyp3U51XvZVbGTC9N+x7SYGawv7vsRiUX1B9lYvI7zRv/Gdc8/IXISf0q/jHf3vMW2si3H/Bk5NXupaqxiTjfJrvSIcWRW7naNlvPEYrOQUbnbNd+gRqVhyYil/FT4A2armRLTIRI9jCTsbxem/Y4bp9zMl/s/5f7197CzYjuL4pe4bROpjyRMF0ZW9Z4Bj8+XmZpNBGgC0av1WCTpJ4TP8krS7z//+Q/PP/+82z/vvPMOP/30EzExMZx66qneCEsIIYQQwuc0WBsorCsgNWwMAMmGkcQExLD20K9u2zmdTvKMucQGynx+XVEqlIwNT2d35U5vhyJ82IrCH5kYNZmnFz3P52d/y3NLXmJ6zAye3/6Ma+6SUnPJEZX2bO/U5DMI10XwduYbndZtLt3IxKhJ+Kn8AAjXhfv0SL8Ga8MRJz6F6E9njDwHi62RHwuXezsUIcQRWHVwBUqFiqcWPc+JCctQK7suTHbCsHnYnQ42lqwfwAhbVDRU8PHeD0gMTuLL/Z+xu8L9nvLjnA+ICYhh7vD5zI49gZyavUddHvJAXSFf5X6O3WF3W/7pvo8J9gthyYilbssvSruYydFTeXDjfZQ3lHd53GZ7c4+fva54DcHaYNLDx3e5TXrEBKot1V2WLAfYVbETq8PKtJgZrmUnJZyMscnIJzkf4gQSDQNX3rO901PO5O8z72ZDyVoUKJgft8BtvUKhIC1sLFlVkvRrz2w1EXg46Wd3OrDard4OSQjhgU/N6RcWFsbll1/OM8884+1QhBBCCCF8wn5jDg6nk7TwlqSfQqFg7vD5rDn0i9u8HR/ufZ/MqgwWjzjRW6EOCpOiprC7clenByhCQEs5q7rmWmbEzCI9YhxalRaFQsG1k26kylLF+9n/BQ4n/Y6wtGcrrUrLxWP/xKqDP/N17peuN+QbbY3sqtjpKu0JEKGPwGw1+2T5JIfTQaOtUcp7Cp8S7R/NnOHz+WzfJ306t5UQon+tOvgzM2Nn92r0eKR/JKlhaawtXjMAkbl7I+MVAjQBPLXoWcaGp/PElsdcSbSyhjJWF/3MuaMuQKlQMiN2FgpgY8mGo/qsf297in9ve4pbVv+FioYKAOqb6/ih4DvOTDm706hnpULJHTPvRqfy4951d3lM7q0vXsvZn5/Kvev+QVVj18nIdYfWtMyfqFR1uU364fKXGZW7utxma9lmIvQRjAhKcC1LCRlJsiGZj3L+B+C2bqAtGrGER+Y9wV+m3kKwn6HT+jHhY8mpyZbfk3ZMVhOB2kB0aj0AFrvv3aMKIXws6Qdgt9upqKjwdhhCCCGEED4hq2oPOrXObZL7OcPnY2wysqcqE2jpwL+2+yV+O+b3zI9b6KVIB4eJkZNpsDaw3yglPkVnZqsJh9NJiF+I2/LhQXFcmPo7Ptz7PkX1BylrKCPmKEf6AZyceCqnJp3OM9ue4LZfbqLUXMLOih3YHDa3pF/44bllqrt5MOctZqsJQMp7Cp9zzqjzOWQqYkvpZm+HIoTohaL6g+TU7GVh/OJe7zNn2Dw2l26kyd7Uj5G521+zj58Kv+eP6ZcSqA3ipmm3UtZQyjt7Wkbuf77vY/zVASxLbKleZvALYUx4+lGV+MyuzmJnxXYuSvsdJeZirvrpMjaVbOSbvK9wOB2ckXKWx/0MfiHcM/sB8mvz+Pe2J91Kb6459Av3rruL9IjxZFTu4rLv/8DXuV92Smgdqi+isK6AOcPndRtjkDaYhOBEMqsyutxma9lmpsXMcJt6QKFQcFLiKVhsFmICYrxeMWBi1GROTvJccW5M2FgabY0U1hUMbFA+qv0LX34qHQCNh6tgCCF8S9fj5ftRZmZmp2VWq5Xc3Fyef/55JkyY4IWohBBCCCG859/bnmRW7BxmxM50W55dncXo0FSUirZ3tcaGpxOqC2XtoV/wV+t5aON9zBk+n0vSLxvosAed0aGp+Kn82FG+jdSwNG+HI3yMsckIgMHD294XpV3MigM/8Nz2pylvKCUmIPaoP0elVPHXabcwL24BT239F1f8cAnxQSOICYghLjDetV1r0q/KUsnwoLij/rz+YLaaAUn6Cd8zLnw8I0NG8fn+jzv9pgohjl19cx0FdQWMj+ibZ3erD65Er9YzM3Z2r/eZM3wer2e8wvayrcwadkKv96uxVPNN3lcsHnEiw46gJL7T6eSlXf8hLmgEpyadDkBCcCJ/GHsJb2W+xrToGXyb/zVnJJ/llsSaPWwO/93zFs325i7nI/Xkg+z3GB4Yx/+Nu4LzR1/IY5se4s41t6JT61g84kRCdWFd7js6LJUbp97M45sfIS1sLKennMnqgyt5aOO9zI9bxG0z7qTR1sDLu17gmW1P8POBH5kZO5uyhjLKzCUcqC9Eo9QwJXpaj3GOixhPRuVuj+vKG8oprCvg92P/1Gnd4hEn8vKu/5BoGPj5/I7EqNBUlAoFWVV7SOomVqfTiclaT5A2eACjG3itL3y1lPdsSfrJvH5C+CavjPQ777zzOP/8893+ueiii7jzzjuJjIzk/vvv90ZYQgghhBBe4XQ6+S7/G17Y+Wynt233VmeRdng+v1ZKhZI5w+ax+uBK/rH27wwPjOPWGXe4JQaFZxqVhvSIceyq2OHtUIQPak36BWs7J/10ah3XTLqBrWVbsDnsRB9D0q/VtJgZvHzSm5w44iT21eQwI3a229vw4bqWpF+lD87r13A46eevlqSf8C0KhYJzR53P5tJNHKgr9HY4Qgw5/8t+l7+tuqHLZM+RcDqdrDy4ghOGzUF3OInQGyOCE4gLimfNoV+O6PO+2P8Zb2W+zv8tv5gHN9xLbi8rP2wq3ciO8m1cMeEqt5KXv0n9LUmGZP7+6y002SycNfI8t/1mxZ5Ak72JHeXbex3jwfoDrD30CxekXoRSocTgF8L9cx/h8vFXolPpOH/0hT0eY1niKZyRcjbP73ia1zNe4aGN97Iofgm3z7gLtVJNkDaYm6fdxuMLnqa2uZb3st8hs3IXSqWKmbEncOese9AfLt/YnXER4ymsK6C+ua7Tum1lW1AAUz0kD0N1Yfxh7P9xUsLJvfpv4i3+Gn8Sg5PIru5+Xr/XM17moq/Po9h0aIAi8472L3zp1S3JbYuM9BPCJ3llpN/bb7/daZmfnx8xMTFER0d7ISIhhBBCCO8xWeuxOWwU1R/k16LVLIhfBEBVYxUVjRWkdkj6Qcsbzl/nfUmoLpT75zzSq465aDEpcgrvZ/8Xu8Pe7Vwl4vhTezjp17G8Z6tZsScwM3YWG0s2EHOUc/p1FKAJ4MapN3PmyHOI9I9yW+ev8Uev1lPlg0k/GeknfNmC+MW8vOsFPt//KTdM+au3wxFiSNlathmH08ljmx7kxaWv91iesdRcwnPbn8bpdHL/3EfcXlLLr8ujsK6AyydcdcRxzB0+j2/zv6G+ua5XI6ycTieri1ayMH4xEyIn8uHe97nqx8uZHjODG6f+jWh/z88j7Q47r+x6gQmRk5gV6z6qUK1Uc/O027luxZ9ZNOJEIv0j3dYnBCcSExDDhpK1vR55/OHe9wnVhbE0YZlrmVKh5MK033Fh2u96dQyAqydeR65xH+9n/ZelCcv42/TbO70gODFqMq+e9JbbC0dHYtzh0Z6ZlRmdRlxuKd3E6LC0Lv82nkYA+qK0sLGuKRU8yazM4IPs91ApVbyw8znun/PwAEY3sEzNrSP9glxJepnTTwjf5JXXwWfMmNHpn4kTJ0rCTwghhBDHparD83WF+IXwfvY7rvk39lZnAS2dzY4mRU3hjJSzeWDOo50eMIjuTYicRKOtkX3GHG+HInyM0WJEAQR7KO8JLSOIrp9yE2ePPI+4oHiP2xytJEMygZrATsvD9RFUWXw56dc5ZiG8TavScnrKWfxYuBxTc723wxFiyDBaasg15vL7sX+ipqmGl3Y+3+W2DqeDT3I+5PLv/8R+4z62lG3if9nvum2z8sAKgrRBTI3quZRkRwviFmNqruPcL87ggi/P4uZVN/LvbU9Rai7xuH1e7X6K6g+yNOFkzkg5mzdPfo+/z7yL/No87l5zOw3WBo/7fZTzPwrrCrhywjUek2OjQkfzzOIXuG7yXzqtUygUzIw9gQ3F69zm1+tKZWMlPxX+wLmjLjiicqCeaFQa7j3hQW6ZfrvHhF/7GI9WtH8M4fpwMip3uS13OB1sK9/CtOgZR31sXzEmPJ3CunyP10ejrZHHNj9EWvhYbp1+JxuK17GpZKMXohwYJmvL72mAJkDm9BPCxw1Y0s9oNOJwOFz/3tM/QgghhBDHi2pLS9LvsvFXkmvMZWPJegCya7II1YUSqe+c1FMr1dww5a+MDksd0FiHgtSwNHRqHTuPoNSSOD7UNdcS5GfotlRutH80106+AbVyYIqmhOsiXC8G+JLWeV1kpJ/wVWeknIXNYWV5wbfeDkUIn9FgbcBoqTnq/beXbwPgtOQzuXLCtXyb/zXri9d22i7XuI/rV1zFSzuf5+Sk03h92X+5MO1i3s58nb3V2UDLyLtVB1cwb/gCNCrNEccyMnQUry17hztm3s0ZKWcT6hfK6qKVPL/9GY/bry5aRZA2iCnRU4GW+XUXj1jKQ/P+RYm5hEc3PdipzP7XuV/y2u6XuSjt4m7vudPCxnh8cQdg9rATqGisIK92f4/n9Nm+j9CqtJyWcmaP2/ZGiC6UkxJP6bcpABQKBenh48msynBbvqcqk/rmeqbGTO+Xzx1IaWFjcILHEp+v7HyJysYKbp1+BwvjFzMxcjL/2fFvmu3NAx/oAGh94StQG4he01JlRub0E8I3DVjSb/bs2WRktPwIzJo1i9mzZ3f7jxBCCCHE8aI16bcwfjHp4eN4N+ttnE4n2VV7SAsbe0xv4IrO1Eo14yLGs7NCkn7CnbHJ2GVpT2+J0Ie7viN8SYOtAZVCiZ/Kz9uhCOFRmC6cucMX8FPhD94ORQif8fKu//DXVdd3OerM4XTw8s7/cKi+yOP6rWWbSQhOJEIfwWnJZzAzdhZPbnnMlUjMrs7in+vu4uofL6fJ3sRTi57nusk34q/x5w9jLiE5ZCSPbHoAi81CdnUWpeZSFsYvPurziQuKZ9GIJfwx/f+4a/Y/uXLC1WwoWc/B+gNu27UkGH9mzvB5nV7aSTIk8/eZ/2B98RrezHzNtfynwu/597YnOHPkOVw67oqjjnFCxCT0aj0bitd3u52puZ6vcr/gzJSzu0wg+qJxEePJrs5yJbp2V+7innV3EhcUzxgP1UoGmxHBCUTqI3lgwz/5Yv+n2Bw2ADYf2szn+z7hsvF/Ji4oHoVCwXWTb6TEfIjP9n3s5aj7h8n1wlcgetXhpJ9dRvoJ4YsGbE6/hx56iPj4lhI4Dz88dOsbCyGEEEIcqarGKvw1/ujUOn435o/cueZWtpVvYW9NNhem9n7uDtF7EyMn817WO9gctgEbsSV8X21Tjc8l/cL1EWQdLvXrS8xWM/6aAHkpQfi0GTEzWXXwZ2qbjBh8rG0L4Q0Zlbspqj9IRuUuxkdO7LR+a9lmPsr5gAZbA3+Z+je3dU6nk21lW5gXtxBoGeV107RbueL7S3hw4304nU52VmxneGAcN027jSUjlrqN4NOoNNw+4y6u/ulyXt71AhqlhlBdKBOjJvfZ+S2MX8Kru1/i05yPuHHqza7l+2pyKDEVc+OUmzzuN3vYHC4d/2de2/0yicGJqJUa/rX5YZYlncq1k244pt86jUrDtJgZrC9Zy8Vj/9jldp8fTiidM+r8o/4sbxgXMQGbw0ZOzV4OmYp4euu/GBs+nntm3zck7rGVCiXPn/gyb2S8yvPbn+HL3M+5fMIVvJL5AhMiJ3L2yPNc2yYakjhr5Hm8m/U2SxJOIkIf4cXI+56puR4/lZ/r76pWqmWknxA+asC+fc855xwAbDYbo0ePJjY2lrCwsIH6eCGEEEIIn1VtqSZMFw7A9JgZjAodzb+3PUWDtYG0sDFejm5omhA5idd2v8y+mhzGhA/+t5BF3zA2GQnWep7Pz1vCdOFUNlbgdDp9KsFmtpqktKfweZOiWsr4bS/fdkyjiYQYChqsDRysLwRgecG3HpN+3+R9BcDKgyu4auJ16NQ617oi00EqGiuYEt02/16YLpy/TP0b962/m1Gho7l79n3MGT6vy3KSI4ITuHLCNTy7/Wl0ah0nJ57Wp6UntSotZ488j//ueYtLxl3mSvavLvqZYD8DkyKndLnvham/o6Aun8c3P4rDaWdh/GL+OvWWPolv3vAFPLTxPu5ffw9/nngN0f7RrnVGSw0v7foPPxX+wDmjznf1CQaLZEMKOrWOp7c+TmFdAacmnc51k/9yVCVbfVWoLoybpt3KmSnn8MLOZ7ln7V0E6QJ5dO5Tna6PP469hJ8P/MSru17g9pn/8FLE/cNsNROobRuFqlfraZSknxA+acDKe7o+UKnkwgsvJDs7e6A/WgghhBDCJ9VYqgnTtbwMpVAo+G3a7yk2HUIBjA5L825wQ9To0FT0ar2U+BRuan2wvGe4PoJme7NrDj1fYbaaJeknfF6kfyQjghPYXrbV26EI4XW5xn04nE7mDp/PL0WraLA2uK2vbKxkffEazh11AQ3WBtYcWu22flvZFtRKFeMjJrgtnxe3gP+d/inPL3mZeXELekySnZFyNtNjZmCxWVg0YknfnFw7pyWfgUKh4OvcL4GWEYq/FK1i3vD5qJSqLvdTKBTcNPVWxkWMZ0H8Im6dfmefJSQXxi/mthl3kFG5i0uX/5539ryJxWbhu/xvuPT7P7CxZD03TbuVqyZe2yefN5BUShVjw9M5WF/I1ZOu4y9T/zakEn7tjQwdxeMLnuGBeQ/z1LKniA2M7bRNoDaIy8dfyYoDP5Fr3OeFKPuP2WomUBPk+v86lQ6LTcp7CuGLBnyctVKpJC4ujtra2oH+aCGEEEIIn1RlqXJ7q3fO8HkkBCfixDmo5vQYTNrP63dR2sXeDkf4iNqmWp8rARihjwRaHsYGaoN62HrgNFjNBMj3kxgEJkdNZWPJOm+HIYTX5dTsRaPU8OcJV7P2u1/4pWgVJyed6lr/Q8F3qJUa/jD2T+w37uP7guWcmLDMtX5L2WbGho/DX+Pf6djh+t6PTlMoFNw+4y42l27slznfDH4hnJRwMp/v/4QLUi8irza313MHalVaHlvwVJ/HpFAoODFhGScMm8d7WW/zXtbbfJD9Hk32JpYkLOXKCdcQqhu81dCun/xXzFYzqcfBy4oKhYIThs8lNDSAmhqzx21OTDiJZ7Y9QUblblJCRg1whP3HZK13e+FLJyP9hPBZAz7SD+Cqq67iP//5D2VlZd74eCGEEEIIn1LdIemnVCi5c9Y93DztNi9GNfRNiJxERuVubA6bt0MRPsDpdGL0wZF+rfPBVFuqvByJu9Y5/YTwdVOjp1FqLqXEVOztUITwqr3V2YwKHU1s4DAmR0/l+4JvXescTgff5n3FovglBGqDODnxFHaUb6PUXAKAzWFjZ/l2pkRN6+rwRyTYz8CShJP6rWz1uaMvwNhkZOXBFaw6uIIQvxAmRE7ql886Ev4afy6fcBWvnPQWp6ecyWPzn+T2GXcN6oQfQFxQ/HGR8OsttVLNiKAR5NfmeTuUPmVqNnVI+ulosstIPyF8kVdmVF2+fDk1NTWceOKJpKamEhHhPrGpQqHghRde8EZoQgghhBADrn15z1ZJhmQvRXP8mBQ1hdd2v8ze6mzSI8Z5OxzhZQ22BmwOm8+N9Gt9IaCqsdLLkbgzW81EBUT3vKEQXjY+ciJKhYKtZVs4PfBMb4cjhNfk1OxlesxMAE5OPI2HNt5HUf1B4oLi2VK6mbKGMk5Lbmkjc+MW8Oz2p/m+4Dv+lH4pe6uzabQ1us3n58vig0YwK3Y2n+R8gKnZxPz4RX06d+CxiguK56qJ13k7DNGPkgzJQy7pZ7aa3fqserUei4z0E8IneeUXz2w2k5SUxKRJk9Dr9ZjNZrd/TCbfmq9CCCGEEKK/NNmbMFvNR1QWSfSNUSGj0av17KrY4e1QhA+obTICYPAzeDeQDrQqLUHaIKp8bqSfScp7ikEhUBNIWthYtpfLvH7i+GVqrueQqYjUsFSgpZR8oCaQ7wu+A+CbvC9JNiSTFjYGaHmYvyh+CT8UfIfD6WBr2WYCNYGDajTXeaN/Q35tPhWNFSyIW+jtcMRxJtGQTEFdPk6n09uh9BmTtZ5Abdu9n06lo1Hm9BPCJ3llpN8777zjjY8VQgghhPA5NZZqALfynmJgqJQq17x+vx3ze2+HI7zMeDjp52vlPQHCdRFU+thIvwZbg1uJJyF82eSoqXyZ+xkOp8OnRvsIMVByavYCMDq0JWmnVWlZNOJEfixczhkpZ7OhZC3XTrrRrdzmsqRT+Tb/a3aUb2Nb2RYmRU0ZVO1nYuRkUkJSqLHUMC5igrfDEceZJEMKDdYGyhvKiA6I8XY4faLlhS/3Of3qm+u8GNHQtr54LT8ULOeeE+73dihiEBo8v9ZCCCGEEENQVWPL6J3BPpfHYDUuYgJZ1XtwOB3eDkV4WdtIv1DvBuJBuD7cJ8t7+qv9vR2GEL0yJXoq9c315Br3ezsUIbwip2YverWeuKB417JliadQ1VjFo5seQKPUsjhhqds+Y8LGEh80gk/3fURWdeagKe3ZSqFQcPuMf3D37PsHVbJSDA2tUzUMpRKfZqvZrcpDy5x+TV6MaOiyO+y8uPN51hz6xTW3qhBHwmu/evv27ePmm29m6dKlTJo0iaVLl/K3v/2NnJwcb4UkhBBCCDHgqg+X7AuXkX5ekR4+jgZrAwV1+d4ORXhZbVMt4HvlPQEi9JFUWXwn6ed0OqW8pxhUxoSl46fyY1vZFm+HIo5T28u2UlhX4LXP31udzajQVLfk1+jQVJIMSeyq2MnC+MUEdvhOVygULEs8hY0lG3A4nUwdZEk/gERDkszbLLwiUh9JgCZgyCT9Wu/9AjVBrmU6mdOv36w48APFpkMAMhWFOCpeSfqtWrWKc845h507d7JkyRKuvfZalixZwo4dOzj33HNZtWqVN8ISQgghhBhw1ZYq1EoVQdpgb4dyXBodloZSoWBPZaa3QxFeZmyqIVATiFrplRkQuhXmYyP9Gm2NOJxOKe8pBg2NSsOEyIlsK5eknxh4DqeDe9f/g+tWXMn64rVeiSGnJpvU0FS3ZS1JvVMBOD3lLI/7LU1chlKhICYghmGBw/s9TiGGCoVCQZIhecgk/Tzd++lVOhrtMqdfX7M77Pw3621OGDaXlJAUdkrSTxwFryT9HnvsMebNm8cPP/zA7bffzhVXXMHtt9/ODz/8wNy5c3nssce8EZYQQgghxICrslQR6hfmNoeKGDh6tZ5kw0j2VGV4OxThZbVNRgw+OJ8fQIQugmpLlc+UoTVbzQAy0k8MKlOip7G7YhfN9mZvhyKOM8WmQ5itZmL8Y7ln7R18uPd9nE7ngH1+jaWa8oZyRoeldVp3RsrZPDTvMdLCxnjcN0wXzmnJZ3Jy4mn9HaYQQ85QSvp5uvfTqfU0Whu8FdKQteLAD5SYivnD2EuYEDlZRvqJo+KVpF9RURG//e1vUSrdP16pVPK73/2OoqIib4QlhBBCCDHgqhurCNNLaU9vGhsxjj1VMtLveGdsMvpkaU+AcH0ENoedusMlSL2twdby4MdfI3P6icFjStRUrA4rGZW7vB2KOM7sq2mZxuZfC57iwrSLeWXXizy59TGsduuAfH7O4c9PDe2c9NOqtEyPmdnt/jdMuYmLx/6xX2ITYihLMiRzsL5wwNp6fzJZ6wEI1A6uOf2sdisNPpSYNFlNZFTu5uvcL3ll1wvkGve5rW8/ym9k6CgmRE6k1FxKWUOZlyIWg5VXatekpqZ2mdgrKipi1KhRAxyREEIIIYR31FiqCdWFeTuM41p6+Di+3P8ZRksNIbpQb4cjvMSXR/qF6yMAqLJU+sQ12va2t5T3FINHkiGFEL8QtpdvZcognJtMDF77avYS7R9NiC6Uy8b/mfigeJ7a+i/KzKU8MPdRtCptv35+Tk02QdogYgJi+/VzhBDuEg3J2J0ODtYXkhwy0tvhHBOT1QTgNvenTtUyp5/T6fTZqjVvZr7K1rLNvHDiawMaY3lDOesO/UpFYzmVjRVUNlZSYiqmorECAKVCQYAmkM/2fcINU27i5KSWUss/HR7ld8/s+wAYHzEBgN0VO4hOWDZg8YvBzysj/e6++27eeOMNPvvsM+rrW94UqK+v59NPP+WNN97gnnvu8UZYQgghhBADrspSRbhORvp5U3r4OACyqvd4ORLhTbVNtYT4atJP15L0q2ysOqL9NpVs5J/r7urzeMyHH/xIeU8xmCgUCqZET2Vb2VZvhyKOMzk1OYxqN5/eSYmn8Mi8J8isyuD+9Xdjc9g87lfRUNEnZZ1zqrMZHZrqsw/lhRiqkoKTAIZEiU9zc+d7P71ahxN8erRfdnUWucZcCusKBvRzX931Ii/ufI5fi1ZT2VhJhD6CJQlLuW3GHby49FW+OucH3j/9E05MOIkntjzKE1sepcHawLtZbzNn+DxSQloGRBn8QkgyJLGjfLvHz3k78w12V+wcyFMTg8SAjfSbPHmy2w2G1Wrljjvu4I477kCtVmOztdzkqNVqLrnkErZt2zZQoQkhhBBCeE21pYowSfp5VZR/NOH6cDIrdzN72BxvhyO8xJdH+oXpwlAAVY2VR7TfZ/s/YkvpZioaKoj0j+yzeGSknxisZsaewM8H7ue13S/xf+OuQKnwynvQwoflGffz2OaHuH/Oo33yvel0OtlvzOE3qb91Wz4xajL/POEB7l77dx7d9CB/n/kP1/XYaGvk9d2v8MX+T1icsJRbp99x1Neq0+lkb002JyfJnHxCDLRAbRCR+sihkfRrHemndZ/TD8Bia0Sn1nklrp4UHE72/VK0ikRD0oB8ptPpZFflDs4b/RuumHB1t9veNO1W0iPG88zWJ9hQvA5jk9E1yq/V+MhJbC7d2Gnfgtp83tnzJgV1+YyPnNin5yAGvwFL+l166aXyVpEQQgghRDsOp4PaJqMk/bxMoVAwJixd5vU7zhmbjD470k+lVBGiC6XK0vukn9FSw7ayLQBkVWcS6b+wz+JpnRvFXy1z+onBZVH8EiobK3ht90vk1+Zx+8x/uJUqE2LlwZ/JNeby0s7nuWv2P4/5eMWmQ5itZkaFju60bnrMTO6YeQ8PbLgHnVrHTVNvZXflTh7f8iiVDRWcknQ63+V/TaAmiGsn3XBUz9QqGyupsdR4nM9PCNH/kgzJQyLpZ7KaUCvVaJVt5Yj1rUk/u8VbYXWrxlJNXVMtwdpgfi1azR/T/29APrfUXEJVYxXjIyf1avtliacwKmQU962/h8lRU12j/FpNipzMl/s/6/QS35e5nwGwo3wbDqdDXmQSbgYs6Xf99dcP1EcJIYQQQgwKxqYaHE4n4XpJ+nlbesQ4Xt/9CjaHDbXSK9NeCy+y2Cw02Zsw+Bm8HUqXwnURRzTSb82hX4GWskB7qjKYH7ewz2IxW03o1Xp5uCAGHYVCwW9Sf0ticDIPbbyX61dcxf1zHiYuKN7boQkfsaV0ExH6CFYXreTk0lOZFjPjmI6XU7MXgNHtynu2Ny9uAbdM/zuPbnqIwroCsqr2kB4+jofmPkZcUDyjQlN5ZtsTBGuDe3xgXWYu5bXdL7NoxBJmxZ6AQqEgpyb78OdL0k8Ib0gyJPPzgZ+8HcYxM1vNBGoC3V4+8FO1jO6z2Hwz6XegrhCA80dfyOsZr3Cw/gDxQSN63O+FHc+Ra9zPzNhZzBp2AnGB8Uf00sWuyp0ogHGHp5DojeSQkbxx8n9x4uy0rnVev10V21mScBLQkoT9sfB7JkdNYXv5NnKN+z2+XCKOX9JLE0IIIYTwkurGagAZ6ecDxoaPw+qwkmvc7+1QfE6DtaHL+YaGitrmWgCfLe8JEKGPoMrS+zn9Vh5cweSoqUyOmkJWVd/OV2m2mqW0pxjUZsTO5LklL6FAwXUrriRPvvsFLaNC9hv3cem4K5gQOYlntz9Ns735mI65r2YvUf5R3f6+nJiwjBum3MTBugNcPek6nlz0rCsRfXrKmVw2/s+8s+dNPt33UZfHqGio4JbVf2Ft8a/cvfYObln9V/bX7GNvTTahulAi9BHHdB5CiKOTZEimorECU3O9t0M5JmarqdNczvrDJT0bbY3eCKlHBXX5qJUqzhp5Ljq1jl+LVve4z87y7Xy67yOa7BbeyHiVS5f/gUuWX8y7e97G6eyckPNkd8VOkkNSCNQGHVG8CoXC4wt1IbpQEoIT2Vmxw7Xsx4LlWO3N3DztNvxUfq7qHkK0GrDXmK+66ipuv/12EhMTueqqq7rdVqFQ8MILLwxQZEIIIYQQ3lFtaUn6herCvByJGBkyCo1SQ2bVblLD5G34Vg6ng2tX/JlZsbO5cuK13g6n39RajACE+IV6N5BuhOsjXCNGelLZWMnuih3cNO02Gmxm1h76Favdikal6ZNYWpJ+UhJRDG5xQfE8u+RFbvj5ap7d/jRPLny2xzf5nU4nqw7+zKqDP/O36bcRpA0eoGjFQNhathmAaTEzGBWaylU/XsqHe9/n92P/dNTHzKnJYVQXo/zaOyPlLE5PPtPjNXhR2sXUN9fxwo7nsNqtnDvqArfv86rGKm5Z/RfsTjuvL3uH/Lp8Xtn1Atf8dDkBmkDGRU6Q6XaE8JIkQzIA+XX5rhFbg5Gp2dTpha/2c/r5osK6AoYHxuOv8WdW7An8UrSK3435Q5fb2xw2nt3+NGPD03lq0XM025vZUb6NNYd+4c3M14j0j+SkxFN6/NxdlTuZETOrL0+FCZGTXIk9h9PBF/s/Y17cQqIDYpgQOZFt5Vu4MO13ffqZYnAbsJF+ZrMZu93u+vfu/jGZTAMVlhBCCCGE11QfHrUT6sOJhuOFVqVldGgqeyplXr/2Npduoqj+IL8Urer1262DkbHJCPj2SL8wXTiVjRW92vaXopWolCrmDJ/LmLB0rA4rebW5fRZLg01G+omhIUATwLWTbiCjcjc/H/ix220LavO5ZfVfeWjjfawrXsMPBcsHKEoxUDaXbmRkyChCdWEkGpI4b/RveC/rHUpMxUd1PKfTyX5jTpelPTvqLjF3+firOH/0b3g942Uu/f73/FT4PQ6ngxpLNbes/gtNdguPL3iG6IAYZsXO5uWlb3D9lJvQqXVMjz62EqVCiKMXH5SASqGkYJDP62eymgjUdhzp59tz+hXWFZAYnAS0lFLONe6n2HSoy+0/3/8JB+sLuWHKX1EqlOjUOmYNO4G/Tb+dExNO4vkd/6asoazbz6xoqKDEVMyEyIl9ei4TIydxyFREZWMl28q2cMhUxFkjzwVgctRUdlfsOuaR6WJoGbCRfu+8847HfxdCCCGEOF5VW6oI9jP02egbcWzSI8Z5nHOjyd5EUf0BCmrzKawv5JDpIOeNP5sJhmleiHJgfZX7GXq1nvKGcvLr8kg2pHg7pH5R12wEIMSHk34R+kiMlhrsDjsqparbbVcfXMm0mJkEaYNJCRmJWqkmqyqzz0axSnlPMZRMiZ7G3OHzeXnXC8weNhd/jb/b+gZrA2/veZ3P931CTMAwHpr3GN/nf8d3+d9w7qgLZATVEOFwOthStoXTks9wLbt4zJ9YeWAFz21/mgfmPnrEf+ti0yHMVjMjQ459niWFQsGVE69lWeKpvJHxKo9ueogPst/HiROTtZ4nFz5LbOAw1/YqpYozUs7ijJSzjvmzhRBHT6PSEB+UQP6gT/rVd6ry0Dqnn++W9yxg0sgpAEyPmYlWpeXXotUeR8RVNlbyduYbnJ5yNikhozqtv3bSDewo38bjmx/h0flPdDmvdUblLoA+H9XZmkTcVbGDlQdXkBKSQvrhOQOnRE/l5V0vsKcqg0lRU/r0c8XgJXP6CSGEEEL0s8rGSjaXbuy0vMpSRZiflPb0FWPC06lsrKS8ody1bEPJei748iyu+vFyHtn0ID8WLCezMoPXtr/mxUgHRqm5hE0lG7hs/J/RqXVsKF7n7ZD6jbHJiF6tR6vSejuULo0ITsAJfLD3vW63KzWXsKcqk0Xxi4F2o1ir+m4Uq5T3FEPNVROvxWQ18W7WW27Ly8yl3PDz1Xyd+yV/Sr+Ml096g+kxMzk1+XQK6wrIrMrwUsSir+2ryaGuqdZtVJy/xp+rJ13PptKNbCxZf8THbC3JPDr02JN+rRINSdw750GeWfwfDH4h1DfX8dj8p1xzAAohfE+SIXnQJ/3MVjOBHe79dIfn9LPYfG+kX42lmrqmWtdIP71az4yYWfxStMrj9i/v/A9alR//l36Zx/WB2iBumf53dpRv48v9n3X5ubsrdzE8MK7Pp+8I1YUxIjiB7wu+ZWPxOs4aeZ7rRZQkQwoGvxC2lW/t088Ug9uAjfR74403er2tQqHgkksu6b9ghBBCCCEG0HtZb/Nd/jd8dtY3rs4RQHVjFWF6Sfr5irHh6QDsqcogyn8xPxYs5/EtjzAz9gQuSruYEcEJBGoCWVn0E49tfpDyhjLCtJFejrr/fJX7Of6aAJYlnsr28m1sKFnX7TwYg1ltkxGDn8HbYXRrXMR4/pR+KW9kvIqfyo/zRv/G43arD65Eq9IyK3aOa1la2FjWFf/aZ7GYrSaGBw7vs+MJ4W3RATFclHYx72W9zclJpxEfNIKc6r3ctfY2/FR+PH/iyyQEJ7q2nxQ1hdiAWL7N+4pxEeO9F7joM1tKN+Gv8WfM4XuBVnOHz2d8xATe2fMmM2NnH9Fov/3GHKL8owjR9X0Z97Hh6Ty+8GkcTkeXI06EEL4hyZDMptINOJ3OQTs63NRs6pT0UyqU+Kn8sNh9b6RfYV0BgNtv9/y4hTy08T7KzKVEB8S4lu8s387Kgyv42/TbCdQGdXnMKdHTOHPkObyy+0Wmxczw+LLF7oqdfV7as9WEiIl8nfclQdogFsUvcS1XKpRMjprCtrItXDruin75bDH4DFjS79FHH+31tpL0E0IIIcRQ4XQ62Vy6EZvDRkblLqbFtL1BXm2pYpg8OPcZYbpwYgNi2VOVSXlDGa/sepFTkk7jxik3u5VTnDVsNmqlmjVFv3Jm8rlejLj/NNubWZ7/LcsST22ZzyL2BJ7c8ig1luo+f3PVFxibjARrfTvpB3DxmD/SZLfw4s7n0ar8PJZtW3lwBTNjZ7uVKBwTPpZP933UZ3+/BmsD/mr/njcUYhD5Tepv+aHgO17Y8SxnpJzNgxvuJcmQzH1zHurUbpQKJacknc5/s97imknXd/uQUAwOm0s3MjlqKmql+2MyhULB78b8gb//egvbyrcwNXp6r4+ZU5PDqF7O53e0JOEnhO9LMiRjtpqpaKwgyj/K2+EcFbPV5PG3TqfW++RIv8K6AtRKlVtfe2bsbDRKDb8eWs35oy+k2d7M+uK1vJbxMmPD01masKzH414+/kq2lG7i0U0P8vSi5936iHVNtRTU5XNh2m/75ZwmRE7i67wvOflw/6y9yVFT+WXbSkzN9XJPIoABTPplZ2cP1EcJIYQQQviMA/WFlJpLAdhevtUt6VdjqZYRAj5mbMQ4vsn7kmZ7M78d83v+L/3yTm/kBmmDmD5sOr8WrR6ySb9filZS11znSirNjJ0FwKbSjSxLPMWbofULY5PRp+fza6VQKLh03J9psjfz721P4qfSclK7v0dR/UFyjfu5eMwf3fZrHbmSXZ3F7GFzOFZmq0nKe4ohx0/lx5UTr+Xedf9gc+km5g6fz20z7uz0YK3VsqRTeCvzNVYc+JGzRg7N34LjRX1zHVnVmVw/+SaP66dGT2d0aCrvZb3T66Sf0+lkf00OF6Re1JehCiEGoSRDMgD5tXmDOOnneT5nvVrnk3P6FdYVEBc4wu1FDn+NP9NiZvBjwXLKzGWsOPAD9c31jAkfy83TbuvVSxR6tZ5bp9/BTauu45N9H/Kb1LYEX0blbgDGR/TPSL9pMdOZGTuLs0ed32ndlOipOJxOdlbsYM7wef3y+WJwGbCknxBCCCHE8WhTyQY0Sg2zhp3A1rIttBbccDqdLXP66cK9Gp9wNylyCj8X/si1k27g7FHndbndoqRFPLj6ocNlIUMGLsAB8sX+z5gSPdVVtiZUF0Zq2Bg2FK8bkkm/uqZahgfGeTuMXlEoFFw98Tqa7U08seVRvs77kih9NFH+URSbi1vmLDmcpG0VpY8iXB/OnqrMPkr6eX7wI8RgN2fYPE5LPgODXwh/Sr+02weAYbpwZg2bw7d5X3FmyjmDtmSbgO3l23A4nUxv92JWe62j/f657i52V+5icsykHo9ZYi7GZDUxMqTv5vMTQgxOUf7R+Gv8eSPjFT7c+z7VliqqLVWolRqmRk1jRuxMpkXP6JdSwH2h2d6M1WH1eO/np9L57Ei/RENSp+UL4xfx8MYHqLZUc0rSaZyUeIpbCdDeSI8Yx9kjz+etzNeZN3wBsYHDANhVuYMo/yi30qF9KUgbzANzPVdSjAmIJTZwGNvKt0rSTwADmPTLzMwkJSUFnU5HZmbPk8inp6f3uI0QQgghhK/bXLqRSVGTmRU7m8c3P+JKEjXYGmi2N0vSz8eclHgyk6ImExMQ2+12CxMX8sCqB1lfvI6Tk04doOgGRk71XrKrs/jnCQ+4LZ89bA7/y36XZnszWpXWS9H1D2OTkfTwcd4Oo9cUCgU3TLmJhOBE9hv3Ud5Qzj5jDuUNZZySdBp+Kr9O248JS2dPVc/9sJ60PvhpXz5UiKFCoVDwl6l/6/X2pyadwZ1rbmVvTTZpYWP6MTLRnzaXbmREcEK3D2pnD5tDYnAS72e906ukX07NXgBGh0rST4jjnUKh4PTkM8muziJMF8bIkFGE6cIw28xsLtnIyoMrUAAJwUloVBocTjs2hx0nTq6ZdP0RlRXuDyZrPQCBms5lI/Vqvc/N6ed0OimozWdy1NRO6xbGL2FYYBwjQ0Z1Kud8JP6UfilrD/3CU1v/xaPzn0ShULC7YhfjIyYcS+jHZErUVLaVbfHa5wvfMmBJv/POO48PP/yQCRMmcN5553X5FlzrpKZZWVkDFZoQQgghRL9osDawu3InV064lslR03ACO8q3syB+EdWWKgDC9ZL08yVKhbLHhB9AmD6M9IjxrD30y5BL+n2V9zmR+khmxZ7gtnxW7GzeyHiVXRU73MrUDgWDccSmUqHknA7lfVr7Up6khY3hv1lvYXfY3eYfOVJmqwloedtYiOPdtJjpRPlH8U3el5L0G6ScTidbSjcxP25Rt9spFUp+O+b3PLzxfvZWZzMrtPPD5Pb21ewlUh/psyN3hBAD64oJV3tcfum4K6i2VLGldJPr5SyVUo1KoWJr2WbeznzD+0m/5pZ7P08j/XxxTj9jUw11zXUeR/ApFco++b321/hzw5SbuXPNrfxYuJy5wxew35jDKUmnH/Oxj9bkqKl8k/cVFQ0VRPpHei0O4RsGLOn39ttvk5KS4vp3IYQQQoihbkf5NmwOO9NjZhLpH0l80Ai2l29tSfo1tiT9ZKTf4DU/fgEv73iRBmvDkBn1VN9cx88HfuLiMX/slBhKMqQQqY9kfcm6IZX0s9qtmK3mQZf086S78oJjw9Ox2CwU1OWREjLqqD/DZO36wY8QxxulQskpSafzv+x3uWriddIuBqHCugIqGyuZFtPzQ/WF8Yt5K/N13t3zDrNSekr65TAqNLWvwhRCDGFhunBOSjzFbZ5mgLWHfuWf6+4iuzrLqy+WmK1mAAK0nedz1ql1WHxsTr/CugKAIy7beaRmxM5kyYgTeXHn8ygVShxOJxMi+2c+v96YFDUZBbC9fAsnJZ6CzWHjQH0hpaYSgrRBhOhCCfELIVATJCXJjwMDlvSbMWOGx38XQgghhBiqNpVuYHhgHMODWuYKmxw9lc0lGwCotlQDkvQbzOYMn8fz255lU+kGFsYv9nY4feKbvK9wOp2cknRap3UKhYJZw+awqWQ9zkk3DpnOYm1zLQAhQyDp151RoamoFEqyqrKOKelX33y4xJO2c4knIY5HyxJP5Z09b/DzgR85I+Vsb4cj2mmyN/HZvo85LfmMLkcnbyxZj0apYULkpB6Pp1Qo+W3a73ly66Pk1eQRSrTH7ZxOJ/tqcjh/9IXHEr4Q4jg3e9gcYgNi+TTnI+6YdXefHz+vNpeP9v6PLaWbmBo9jSUJJzElalqnF/+6Le+p0rv6tb6isK4AtVI9IPN1XzXxOjaXbuLprU9g8AshPmhEv39mVwx+IaSEjOK9rP/y6b6PKawrwOawddpOrVQze9gczhl1PuPCxw+ZPp1w1/Ws1EIIIYQQ4qg5nU42lWxgRuws17KpUdMoMZdQai6h2lKFn8oPvVrvxSjFsYgNjCUlZCRrD/3q7VD6hNVu5fP9n7AkYSmhujCP28yKPYFScykFdfkDHF3/qW2qARgSI/26o1PrSA4ZyZ6qjGM6TmuJJ08PfoQ4HkX6RzIrdg5f5X6O0+n0djiinc/2fcxru1/mvax3PK632q18nfcFJwyb22ku1K4sGbGUSP8o/vr9X3lvz38pbyh3rbM5bKwvXss96+7EZDWRGpbWJ+chhDg+KRVKzh51Hr8UraSioaJPjul0OtlRvo07fr2FK3+4lJ3l21kYv4S9NXu549dbuejrc3lhx3PUtEvktd37dTHSz8fm9CuozSc+KP6Yytn3VogulKsnXUeTvYnxERO8nkA7LflMAjQBjAodzVUTr+XJRc/ywRmf8vrJ7/DEwmf4x+x7uST9MvKMudy08nqu+ekKfij4jmZ7s1fjFn1vwEb6tZeWltZjI5A5/YQQQggxmBXU5VPRWMH0dmUQJ0RNQqlQsK1sK9WWKsL04V7vGIhjM3f4fD7c+z7N9ma0Kq23wzkmq4t+pqqxivNG/abLbSZFTUan1rGheB1JhuQBjK7/1DYdHyP9AMaEp7OtbMsxHaN1Tj9PD36EOF6dNfIcbvvlZjIqdzHei6W9RJv65jr+l/0uIX4hfLH/M84ffVGneZS/L/iOMnMp9895pNfH1ag0PDjvEb4s+IS3M9/k1Z0vMTFqCiOCE/jl4EqMTUZSQkZyw5S/en0eLiHE4Hdy4mm8lfk6X+Z+ymXjr3Rb933Bd3yV+zl/m3Y7iYakXh3v/ez/8kbGqyQbkrltxh0sjF+CWql2jVBeceBHfixcTmbVbp5Y+G/8VH6YrWaUCoXHl1V9cU6/wroCEoJ799+jLywZcRL7jfuYFu39yoanp5zJ6Slndloepgt3G4V4QepFbCndzOf7P+Zfmx/hp8IfeGT+EygVMj5sqPBK0u/222/v9ICrrq6OtWvXUl5ezh//+EdvhCWEEEII0Wc2lWxAq9IyMXKya1mgJpDUsDFsL9+KSqkiXEp7Dnpzh8/nrczX2V6+jZntRnUONk6nk49zPmRazPRuHxpoVVqmRE1jQ8k6fjvm9wMYYf8xNhmBoT/SD2BM2Bi+3P8Z9c11XZa664nJWt/lgx8hjleToqYwPDCOL3M/l6TfAHp++79x4OA6DyWn38/6Lw6ng6cWPcd1K67kg73vcc2k613rm+3NvJf1NgviF/f6YXmrkaGjuD/5fq4cdz2rClfxY8H3rDv0K4tHLOWkxGXHVEJZCCHa89f4c3LiaXyT9xUXj/kTOrUOgA3F63hyy6Po1f7cuPIa/jHr3h7n3HY4HXyZ+xknJ53KTVNvdfveVCgUjA5LZXRYKotHnMhfV17Hk1se5fYZ/8BsNRGgCfT4sqqvzenndDopqMsf0JcuFAoFV028bsA+ry8oFUpmxM5kRuxMtpRu4o5fb/l/9u46PK4q/QP4d9wyk4m7NbXUUqPuSAuUUqyL6y4LLCw/dlls8WXxhV0cirsXp1AqWN29TePuMpbx3x9J7khm0iRNMpn2+3mefZaeO3fuOZn73rnvOXPOxaeHP8KyEReFumrUR0IyfHvllVfiiiuu8PnfTTfdhA8//BCTJ09Gc3NzKKpFRERE1Gc2V23ChPiJnWZ/TYifhO0129BgqQ+6hCKFjwxdJlIiUvFb+c+hrsox2V27E/lNR7r1/KHpyTNxoH4fmlobB6BmfetwwyH8d9uTcLldQlmztQkyseyEGMQaGT0KAJDXeLjX72G0GREh03KWMpEXsUiMJUOX4teydai31Ie6OieEbdVb8MWRz/DVkRX46ND7PtuqzdX44sjnuGDEhUjVpuH84X/AN/lf+iyP90PRd6iz1OLSUVf0ug4amQYLM0/Hk/P+iw8Wf4brx9/IAT8i6nPnDDsPJrsRq4p/AAAcqN+Pf228D9OTZ+HdMz7CmJix+Odvt+Hr/C+7fJ9t1VtQb6nH4iFnd3kfNyJ6JP5x0p1YU7IaHx58D0a7ERqZJuBrVRIVLM7BM9OvydoIg82AdF1GqKsSNiYnTsEFIy7EG3uX40hjXqirQ31k0M3ZXLJkCT766KNQV4OIiIio10x2E/bV7caUxM4zvyYlTEaLtRl76/YgmjP9wp5IJMKM5JnYVrUl1FU5Jp/mfYxMXRYmxk8+6munJE2FG8Dmqo39X7E+tqZ0Fb4t+Bo/l64VypqsTYhURJ4Qg1jJESmQiWUobinq9XsY7QZEyPk8PyJ/p2UsglQsw3eFX4e6Ksc9m9OGZ7Y/jXFxubg45zK8vucVbKxYL2x/e9/r0Mg0wnLV5ww7H0qpEh8eek/Y//0D72BB+inI0GWGoglERN2WqEnCjOTZWJH3KUoNJbj79zswTD8cd069BxFyLR6c+QiWZJ+LZ7Y/hRd3Pufz4zZvq4p+QLouA8OjRhz1mPPTT8alo67A63uXY33Fb0EH/QbbTL+i5rbnjvd0BveJ7orR1yBDl4WHNz046JZrpd4ZdIN+hYWFcLkCX5yIiIiIwsH26q1wul2YEmC5x5HRo6CQKGB32RHNmX7HhWz9UNRaamGym0JdlV4pM5RiY8V6nDd8WbcGvqKVMRgRPRIbKzcMQO36VscMt7f2vQ6nywmgbabfibC0J9A2Gyldl35sg342I5/nRxRAhFyLUzJOw7cFX8HhcgzYcd1uN6pMlfi5dC2W734Rv5f/OmDHDpWPD32AalMlbppwC64YfTWmJ8/Cw5seRFFzIQqa87GqaCUuHXUF1DI1gLYZectGXITvCr5Gtbka3xd+g4bWelw66srQNoSIqJvOHX4BSg0l+Ovq6xEpj8S/Zj0ChUQBAJCIJfjLhL/ixgk3Y0XeJ/gmwIw/o92I38p/wakZC7v9Q7fLRl2JWSlzUNJSDI0s8A++lFIVbE5b0IHG/uZ2u33+XdxSBKlYimRNSkjqE67kEjnunHoPqs1VeGX3C6GuDvWBkDzT74033uhUZrfbkZ+fj5UrV2Lx4sUhqBURERFR39hctRFp2nQkapI6bZNL5BgXl4stVZs50+840fGg+FJDCUZG54S4Nj33ed4n0Cv0WJB+Srf3mZ40Ex8deh92px0yiawfa9d3XG4X8hoPY17aAqwrXYNVxT9gUdYZaLY2Q3+CDPoBQLo2EyUtxb3e32g3IkLOQT+iQJZkL8W3BV9jfcVvmJM6r1+PVW2qwqt7XsaOmu1obn82qUKiwKriHzAtaQYkYkm/Hj9UKozleP/AOzh/+B+EmRy3T/knbl5zA+5b/08kqBOQGJGMM7LO8tlvSfY5+OTwR3hz76vYXr0VC9JPRao2LRRNICLqsTExYzEieiRqzTV4ZPYTAZ/NfPbQc3Go4SDe3v8mTslYKPzwAQB+KV0Hp9uBk9NP6/YxxSIxbptyF6rXVSFRkxjwNUpJ2zMGWx2tPsfrb2a7Ge8deAsr8j7DiOiRWJB+KuamzkNxSxHStenH7Xdgf8rQZeK63BvxzPancFLiVExPnhnqKtExCMmg32OPPdapTC6XIzExEZdffjluuOGGENSKiIiIqG/srNmOaUnBb5InxE/ioN9xJFWbBhHaflk6UIN+LrcL+U1HIBGJMUQ/NOBr3G43Xtr1PDIjs7Aw83SIRZ0X+WixNuOHou9x0chLOz1/sivTkqfjzX2vYXfdTkxKOKnX7RhIpYYSWBwWnJG1GE63E+/ufxML0k9Bs7UJ8er4UFdvwGToMrG1ejPcbnevljQ12FoCdjQRETBEPxRjYsfiqyNf9HjQz+FyQCKSHDUuXW4Xvi34Cst3vwSNTIPFQ5ZgRPRIjIgeicbWBly36o/YUrUJ05JnHENLBie3243nd/wPeoUel3g9i08tU+PBmQ/jL6uvRYWxHHdNvbfTD1LUMjX+MOIiLN/9EsQiES7N6f2z/IiIBppIJMK/Z7X1p3e1QsWVY/6IdaVr8NGh93HVmD8K5auKV2JC/CTEqeN6dFyVVIVnFrwIEQJ/N3U8E7vVaenRoJ/B1oL3D7wDuUQBnVwHnVyHSEUUxsdP6DIncbvd+LlsLV7e9TxabC1YMnQpSlqK8dyOp/HCzv9BJpZjWtLx9/03UBYPWYLNVRvx1NbH8d6Zn/QoP6TBJSSDfgcPHgzFYQVbtmzBa6+9hr1796K2thbPP/88Tjml+79sJiIiIgqm2lyNKlMVcuPHB33NtOQZeHv/G0jXpQ9cxajfKKVKJGgSUXIMSyb6M9hacO2PV0Er12JY1AgMjxqBofrhqLXUYEvVJmyu3IgmaxP0Cj0+OmtFwAG9KlMlPs/7BACwqmgl/jrxb8KsCLvTjpVF3+GDA+9AIpJg8ZAlParfkMihiFPFYWPFhrAZ9MtrPAQAGBY1HJePugrX/nglVhZ+iyZrE4Z149kmx4t0XQYMNgOarI2I6sUSwya7CUma5H6oGdHxYUn2OcJSk919ppDFYcFNq69DrCoW907/V9CO0wpjOf6z9XHsrt2JM4echT+Nu97nOUvRyhhk64diZdF3x+Wg32/lv2Bz1SbcP+MhoaO5Q1JEMv4181Gsr/gVc9PmB9x/SfY5WJH3KaYmTUeKNnUgqkxE1Ge6sxx9vDoe5w2/AJ8e/giLh5yNOHUcKozl2Fu3B3dOvbtXx5WKgw8fKKWemX49sbFiPT49/DHiVHFosbXA6rQCAMbGjsODMx8O+PzoCmM5/rvtSeyo2Y4ZybNw/fgbhZV1GlsbsK50DX4r/wWzUuf0qC7kIRKJ8OdxN+CqlZdibelqLMw8PdRVol4KyaBfqJnNZowYMQLnnXcebrzxxlBXh4iIiI4je2p3AmhLWIJJ06bjy6XfBxyoofCUocs8puek+dtTuxt1ljqMj5+IwuYCrClZBUf7M+gydVk4LXMR9IoovLL7RRQ25yNbP6zTe+yo2Q6xSIR7pj+IV3e/jOt/ugbLRlyMOFU8Pjj4DmrNNZiXdjIuHXUF9MqoHtVPJBJhWvIMbKz8HTeMv6lXM8YG2sGGg0iJSEWEXIsIuRYLMk7FewfehtVpRaQiMtTVGzAZukwAbTNTezPoZ7AbuLwnURdmpcyBXqHHszuexnnDlmFiwmShUzSY5btfQqWpAjXmatz+y9/w8OzHfWbUutwufHHkM7y+ZzmilFF4bM5/MDFhcsD3Oj3rTLy481k0tjb0KsYHK6PdiBd2PoNpSdMxI3lWwNeMjh2D0bFjgr6HUqrE8oVvQS0duCXoiIgG2h9GXoLvCr/FW/tew60n3YFVxT9AJVVhRvLsPj+Wsv0HGBaHuUf7HWk6gqSIZLx9+gcAAJvThgP1+/DAhnvwt3U34eHZTyJWFSu8/qfiH/DM9qcRqYjEQ7Mew9SkaT7vF6WMxjnDzsc5w84/xhZRqjYNUxKnYkXeJzgtY1FY5HnUWUgG/b744osevX7p0qV9evy5c+di7ty5x/QeppK252DIo6Ig03puxm2NDbAbDBBJpVAnex4a6nI4YKkoBwAoYmMhVXt+jddaWwOnxQKJUgllfIJQ7rS2orW6GgCgTEiERKEQtlmqKuGy2SDVaKCI8VwEHSYTrPV1AABVcgrEUs9HbC4rhdvlgkwXCbleL5TbW5pha2oCxCJoUj0zDtxuN8ylJW3tjI6BLMKT3Fsb6uEwGiGWyaBK8vzS12W3w1JZ0VbnuHhIVJ5f33naqYIy3rOEktNiQWttTVudE5MglnumDlsqK+Cy2yHVREAR41kCzW40wtZQDwBQp6ZBJPZ0mprKSgCXG7JIPeSRng4cW1MT7C3NEInFUKd61u53O50wl5cFbmd9HRwmU6d2Om02tBTWwNhigSw6DhKlJ4lrramGs7UVEpUKyjhPOx1mM6x1tW3tTEqGWOZZbsRcUQ63wwGZVgt5lCcxsxsMsDU2tLUzLd3nQmsqLQHcbsj1esh03u1shL2lBSKJBOoUz68XuzoHhXYqFFAleNbpdlqtaK2uAgAoExIgUXjaaamugstqhUSthjLWszyAw2yCtS7IOdjRTp0Ocr2nc1E4BwFo0jOEcp9zsFexFgep2pPQBY211la01gSJNeEcDB5r6pRUiCSe9cKDxZqtuRn25qbOseZywVxW2tbOvoi1mho4W48Sa37noNDOiAgoovs/1hQxsZBqApyD/rHmfQ7GJ/Q81oKdg51irQW2xsa2dvrHWsf13i/WWhsaYCytggvi7l/v62rhNJsDxFoX1/v2WOt0DnYVa+VlcDudwWNNJIImLcj1PioaMq3nV3VBY83rHOxNrAW/3vu20+cc7M9Yq6+HwxQg1mw2WKoqAXhird5SjxV5n+CihLMBq63TObinbBvG2JMhrW6GK0nT81jzPwfbY63z9T5wrPmcg8FiTS6HKtHzvMGurvfBY60b1/suYs37eg8Ej7Ve3Vv1JtaC3Vt10U5TeRkcVjtkOh3StRn4rfyXtnYeQ6x1nIP76vcgVhWLW8f/A61VlbC77KiWmxGlTxSWojRUleOL5lew8+DPyJ7mGfTruN4f3P8LhkcMxayUOZiSOA0fHHwX321+G7A7MSlrNpbNetwz86+LWBOu936xdpJmHH4vW4G8gxswPMczo6SvYk34PIOcg4G+15wuJyRiScBYy2s8hFGqIcK5dlnOlVhXshpOtwuRCn0X91btsdbVvVVfxlpv7q38Yy3IvRUA6BuciGsWobjyIMbHT/S0s5uxZrIZESFrO3c7Ym1Q5zF+sdaXeYzDYoGpsu3zHIg8plM7u8xjuhFrvbm3OtHzmG7Emkwiw00TbsHnv76E/x2+E/YIBcZkTMH8tJMxL20B7E2NPrG2tWozvs7/AjeOvRHZ9lg8tfVx3PbDjXjolKcRo4pBqaEEz61+EEU1h7B46Om4fPb/CTMBA+UxC9JPwUu7nseaHZ9hUcppfRJrQe+t+rrPoIs8ZvnqhyCvMeCGWX/xOZ96GmsRsohjz2Miva4p/ZXHdDvWushjjhZrfXJv5R1rgfOYPu0z6PLeqpt9BseYxwy6PoNg1/tQ9BkEyWO6G2vHfG81QH0GuqxMeAt5HuPXZxAhi8BlOVdg+eb/YbF6BjZv/wZzh8/1+QFKX/UZKCVKqM1uGIuLYTarux1rpSX7MAbJaK2phjI+AXKJHLnxE/Dk9Cfx2MrbcO+nf8IdZ/4HMdoEPLv9Kawu+QlnaGfhsuGXQSv3XaK0N3lMf/cZCJ9nR6x1I48RPs9gsdbVvVUf9xmcpZmFJw4/ib11uzE2LretzgOVxwxwn0Fv8hiFTgtEed5rMArJoN8dd9whnJhut1soD1bW14N+fSHvpWcBAGlLzkHCLM8vJSo3/obqX3+BIioKY++8Ryi3GkzCPtmXX4WoMWOFbdU/rUTjnt3QDsnGiOv+IpRbSquQ99JzAICcm/8GhVfiU/b5RzCVlSFm4iRkXXiJUN6cfxiFH74HAMi970FIlZ7Es/Dt12A3GpG04BSkLDpDKK/duQ3lK7+DWC7HxIceFcpddrtQ54xzL0DctOnCtvLffkbtxvVQxsdjzK13COWtjc3CPsOu/hMiR3qea1P5/ddoPngAuuEjMPyPfxbKzVXlyFv+EgBg9N9vhzzBE2glH78PS3UVYqdMReb5fxDKm/IOoOiTjwAAE/71CCReF42C116G02pFysLTkXTyqZ6/8/bNqPzpR0jVaoy//yGh3GG3CnXO+sNFiJnkWaKq9OfVqN+6BerkFIz6v78L5daaBuz933/gcLgw/Nrroc32PEun4usVaMk/Av2o0Rh65TVCubG8BEfeeBUAMPb2uyD1uhks+eAdtNbXIX7GLKQvPVcobziwByVffA4AmPTIExBJPJ0C+a88D5fTidQzz0LiXM/yJVWbN6Bq3RrIdTqMu/t+odxubhXaOeSSyxGdO95z/NU/oGHnDkSkZ2DkjTd72llRI+wz8sabofC62JZ/+SmMRUWIGpeL7Es9z0MwFBUg/923AADj7r4PUqXnIlz0zuuwNTcjYc48pC32LCNWt2cnyr79GiKxGJMefVIod7vdwvHTzz4H8TM9sVax/lfU/P4rFDExGHv7Pz11NhiFfYZecTX0oz2/9Kz68Ts07dsLbfZQjPiz59mhlppK5L30PABg1M1/hyLF8wVR+vnHMJeXIWbSZGT94WKhvDn/EAo/fB8AMP7+f0Gq8FzsC95cDofZjKSTT0XKQs9U+NqdW1H+w/eQyOWY4BVrTpvDE2vnL0PcFM8vlsp/XYfaTRugik/A6Ftv99S5ockTa3/8MyKHe5Ylq/z+KzQfOojIESMx7JprhXJTZRnyXn0ZADD61tsh9/pSK/noPVhqqhE3dToyzrtAKG88vB/Fn34MAJjw0KO+sfbqS3DabJ1jbdsmVK5e1TnWbBZPrF14MWImen6dXLruJ9Rv2wp1SipG3fw3odxW3SDsM+K6v0A7JNvzt/l6BQz5R6AfPQZDr7haKDeWFuHIW68DAMbeeTekXjcPxR+8DWt9PeJnzkb62ecI5Q3796DkyxUAgEmP/cfn5unIK8/D7XL5xJpEIkb5T+tQuPJHyHQ6jPvnfZ46mz3tzL70CkSNy/X8bX5aicbduxCRmYmRN/xVKG+tqBX2yfGPtRWfwFhSjOjxEzDk4suE8pbCfBS89zYAIPfu+yFVehLcondeh62lBYnzFiD1jMVCeUesiSUSTHzkCaHc7XR6Ym3puYif4fn1dMXvv6Bm/W9QxsRizO13CeXWZoMn1q76I/Q5o4RtVT98i6b9+6DLHorh3rFWXYG8l18AAIy65VaovW6USz/7COaKcsRMPglZyy4SypvzD6Hwo7Zf/41/4N+QKjw3w0KsnXIaUk5bJJQLsaZQYMK/HhHKnVbP91rmBX9A7ElThW1lv65B3eZNUCUkYvTfb/PUud7zvTb8T9dBN2w4mu0N+PjwBxj9ay1U5c2IHJmDYVf/yfNeedsxZ4sLeXufxZh/3AG518198UfvorWmBnHTZiDjXM+vEBsP7kPx523LME7892MQSz3tzH/1JbhsNqQsOgNJCzzLkVdv3YjKNT9BFhGB3HsfFMrtVptXrF2CmImTPH/ntatQv30bNKmpyPmrJ9as1fWeWLv+Rmizhgjbyr/6HIaCfESNHYfsy64Uyg0lRch/+w0AwNg774E0ypMsFr/3JqyNjUiYPQdpZy0Vyuv37UHpV22xNvnxp+DtyMvPwe12I+2ss5Ew2/PjrMpN61H9yzrI9XqMu+teodxmNHti7bIrETXWM7OyetVKNO4JEGtl1Z5Yu+n/oPBKZMtWfAJTaQmix0/EkIsvFcpbCvJQ8P67AIDce9vurSTt38f5b7zaFmvzFyBrRBY+y/sYDtjQvHsHyr77BmKpFBMfflx4L5fDc71PP+c8xE/3PPex4vefUbP+dyhj4zDmtjuxr2EvxsaNg9ts9I21dE/yX7fqB5y5RYHGsh8hneW53purK5D3youIrNqCSVeeBalUDKlUiWty/4hxP5TDWlWN1LgJyIzxXFObjhxE0ccfAgAmPPgwJF7nYOEby+GwWJB86kIkn7pQKM8od+DkDW7k5b2EUU97rhtOr3Mw84ILEXvSFM/f+Zc1qNuyCeqkJIy65R9CuaWusVOsCX+bb79ES95hROaMwrCrPM8mMZUXI+/1tnurpJuuxWc13+Pb/G/wjyl3IPGTrWitrUXc9BnIOOd8OF1OHGnKwyniTOE4Ex9+HGdkL8Y3+V8hRh2F/BdfhMtuR8rpZyJp/snCcaq3bEDl2tWQabXIvecBodze6mnnkIsvRfR4zwBa6ZpVqN+xDZq0NOTcdItQbq30XO9H3nATFJmepf/KvvgUxqLCzrFWXIj8d94EAIy7615IvTosit59E7amRiTMmYu0xWcL5fX7dqP06y8hEokw6bH/wFvBKy9gYY0EjcodkE7ynOvB8hjvWBty2ZUwOYyIVOkglYpRver7tjwmawhGXO9ZQcUnj/nrLVB4dTKUrfgYptJSxEyYhKyLvPKYgjwUftAea93NY3ZtR/n330Isk2Hivz3PjfeOtU55zO8/o3bDeijj4jDmH3cK5a1NLcHzmJXfoPnAfuiGDcfwP10nXANaK8qQ9/KLAIDRf7sN8kRPfJZ88gEsVZWIPWkqMi/oZh7z+itwtrYi+bRFSD7lNKG8ZvtmVPz0I6QqNcY/EDiPyVx2IWIne8Xaz6tRt3Uz1MnJGPV/twrl5lrPvdXwa6+HbqjnBwMV33yBliN5XeYxY267C/LYQHnMTKQvPU8obzi4FyUrPgPQgzxmywZUrQ2Qx1isXnnMZYjOneA5frA8xjvW/vJXKDIyhW3dymP+eS+kSr2wrejdN2BrauqUx9Tv3YXSb77qlMfMz5wP3YvfoNURg6opKVhnL8cjmx/EjtqtuKByGOrXr4ciOhoZt/wVT217HJMTJ+OM5JOx79GH8SdHFj4YVoq/rbsRp2YtxAf738O8nVIsNucgWRwF3WmeDshAeUyUVI85aXNR9cnnyJMdCtBn4JfHSD2xVvDWq3CYTAH6DALnMT59BuddgLipXrH2a+A8xqfP4JprETlipLAtWB6zbvvnUH76Cy6LGobYs5WQSj3nU0efQdzUacg4b5lQ7pPH+MdasDwmWJ+BrdUnj9G0f69JJGLUBOkzsNUEz2OC9hmUFePIm68BAMbe8U9IVZ7OXiHWuspjHn3S54cER155Dm6nq3OsbVqPqp/XQh4ZGTSP8e8zqFn9Axp27URERiZG/sU7j+miz+CLT2EsLkJ07ngMueRyodw7jwnWZ5A4dz5SzzxLKBf6DCRiTHrEq8/A5Tpqn0GnPKbF697qymugHzXa87cJlsd4x9r//R0Kr07lLvMYIdYe6lke499n4JXHdOoz+G0tajdtDJDHNAW9twraZ1BRirzXXgGATnlM0D6DQ/tQ/FngPCZorLXnMVKNBuPv+5dQ7rDZfWLNp88gSB7TZZ9BRx4zZiyyL79KKO+yz+D9t2BtaEDCrDlIW7JUKPfOY6Y8+TQACPcDHX0GaYuXIGHOPM/fOVgeY/LKY7rbZ1BeEzSPCdRncPbwpVi/7l1seOo+jHFaMXveAp9rp9BnMH8BUk/vYZ+BVx4TodRgeKELTbs/REnyUJ9Ya20K3Gfgdruh2XAQo40JqKj7AsOvvV7YJ9EswzX7MrC/fj/uE90EV4wOTdZG/HP6vUj+YhfKfnkVsZOnIHPZhcI+3nmMf59B4RuvwmExI/mU05DsFWs1O7ag4seVkCiVmPDgw0J5l30G7XmMKjEJo//mnccEj7WKb78IkseUIO/15QCAMbfdCbnXQFnxh+/45DEdGg/t9/QZPPw4xFLP4Gb+8iB5THf6DC66FDETfPMY5Y5tmGdX44vRn2FCUtt9l7WqLnifwZefwVBYEKDPoBD5b78JoHMeE7zPYDdKv/oCQE/6DH5H9S8/Q66Pwri7AucxnfsM2vKYiMwsjLzhJqG86z6DtjwmdtJkJA3z9AENRiEZ9Pv0009x88034+yzz8bChQsRGxuLuro6rFy5El999RX++9//IjMzMxRV6zaZrC2wIiIUiPIa2a1XKyCTSSBXyHzKW91WYR+dTuWzTaWSwyiTQKn03UdcrxL2idSpoPXaplDIYJNJoFLJffaxaZXCPlF6DWQRnm1yuRSQSaDR+NbZENG2j0Qm8Sl32mxB21mrlkMmk0Dh106zTd1lO80yCVR+7YRXnSMjVdD4tFMKh0wCtdr3+K0RXu2M0viMusvlUjhcjk7tbNK0fTYyudSn3KEQebVT6bOtWiVHi0wChV+djea2XzNIpWLodCrovbYpVXJYAnw2Lp92qqHy2iZXSOGUSaD2q7PZq536KA3EXr9WkcmlcDk617mx/bOR+7XTJnYI76XVKjt9NrIA7ZQ0q33OQZ13OxUyWGUSqP3a6fBqpz5SDYXe9xx0BzgHje3tFInFPuVutzvoZ1PfcQ76tbPV1eppZ4Bz0BQg1kQ6lc85GOHTTinsAdpp8/5s9BrINL7tFNk7t7OlI9b86uy0yTx19munJ9Z891FYg8easj3WlH51dnu1Ux+phjpgrMm7jjWvX7DL5FKI3U5o/OocLNbscgRtZ0esKf3aKTOqfNrpE2tKGVoDxJrTr51K73bKpXDJJND4tdPs107vQT+ZTAK3S9TpHKxF2zXAP9asInvQWFN3XO/9rp2SJq92Rqp9Yk2hbIs1/3bavWNNr4Y8MkCs+bWzI9bEUt86u5zOoLFWp+n4XvPdx+Iwe+oc4JpiCnAO+saa2ifWFEpZwFizen82erXPrwODxlp7naX+sWaVBm1nTfv3t3+syVtVndp5kn48knSJqCoqx3BZpM9nU2euQ11rLaLU2ZDJJIjsFGuytuu932djiVD4fJ7esSaXSeB0SzrVuSPW/M9Bu8wd9BysUgX+/pYafO85Insaa3rfWJMrZHAF+P42ebXT514A7bHmdndqZ0N7Oztd72EL2k6VShYw1sQNwWNNqWy7t/L/bOxa33bKtV7XKCHWFBiXNhTibSK0iOqgaa+zWOYXaw5H8FjzOgc1OhkKWvKwJOdM6PXq4LGmlCFaHYWS1kpoIxWe523oVHCIbLC77ZiRcZLPPtERkTCqjJ3aafVrp9TrF6oyuRQiR+dYa9ZqEKWKQmNrve+9QKsk6GdTE+QeUm7p4ntNKWu7t/L7/nZpVXCJHChtKcWja2+AW69BvDYWv1SuxmWKWDjbP5uoKA3y6vPgEjkwLD4bTlnbL4GjojS4aeYNKDLlY1JmLvJlK+GECxF+7WwMEms2qcurnb51rgrSTkmLbzv9Yy3Q9d773irSL9YUCs856Btr7fdWIlHAWItQRKDEVte9PMYr1hRqEURiICk6DlFRmmPLY9R9kMe0fzb+eYzLbveKNUWnWGsKlMfYTcHzGKWs7d7Kr50RGs81LXgec5R7K/88xhkg1oR7K992eucx/udgdZBzUGY+eqz5t9Pld88RMI9R9yKP8Y81dZBYkziDtjNoHtNVrHUnj9FrfPIYRS/zGJksAhNGnoY/zZ+P7/K+w79++RdkhbswW5IIhUKG1w68CDuseHjhQ9C1XztlMi3um38v7ix5Fu8ffBsXj7sY890KNO3e2zmPiVT7nIMd91bLcs/DJ+//AKvU3LnP4Gh5jK0neYx3n0H38piu+gyEPMarndXGanx4+F2cqolDki4xaKz5t7OrWBPymG72GfjnMTqdSqi/Okifgczk287u9Bk4u9FncNQ8xmvQTy6TwiV2Br236kke0xFr/uegdx7Tqc+gO3lMkD4D/74RIY+R+F4H3S5X0HOwo8+gUx7jtHTZzr7KY3xjTd29PoOO77Uu8hj/XLpGFTjWAuUxHZQd32td9Bl0zmMCf69Z/NrZX30GwfIYnz6DSPWx9xkIeYzvPt55jPc1APD0Gfi3M1ge05s+A3Fjz/sMlo1dhq3rn4VKpsSM7JOgCNhn4BdrHXlMN/sMRKoYiEVt94fd7TOoMFTA7rYjUqXrdE2BTgWNUo0JSeNRHG2GOVKO5fNfRoouBVu/3w97gHtI7zymc5+BJHAe06s+gyCxZuk61gLlMV3HmswnjxH+nt65tF7tMztQLpMEzGN61WfQ3s5RUTl4qup3tEpbkKRNgrSl530GDq/Pxj+PCdpnoOlFn0GQ/pyu+wyC5DFd9Bl05DFKpedvP1iJ3N7T6gbIVVddhenTp+Paa6/ttO3ll1/G+vXr8dZbbw1IXUaMGIHnn38ep5xyytFf7KVkxz6IxCIo9FGQ6TyzK6wdSzNJpFB7zRZyORwwt08nVQZY3tNhsUCiUEKV4Dud1NI+nVQVYDqp02aDVK2B0uuXlnaTEdb69inN/ktQtS8fIPef0tw+dVsUYOq2qX3qtiLAUh12oxHiAMskmL2WD5D6LYvjaF8mQeU1w8jht7yn9w2CuX1KsyzAcm/W9qnbGv9lcUpL4Ha7IY+MhDzSq51NTbC1T2nW+C3VYepYqsOvna11dXCY25bq8J6RAqcDEkMDjMZWyGPjfZYPsFRXw2lthTTA8gGt7csHqP2X6igvh8vZNqVZ4bcsjrV96rYmwJKDbrRNaZZ7TWm2NjbCbmhbFkfjtyxO0HOwvZ0SuQKqRN+lOiztU7dV/sviVFXBabNCGmDqdmv71G3/c9DTTh0UXjNCbF7L4kT4Le8pnIO9irXOS3UEjLXWVlhqAsdaxznYVaxpOi0fECTWmptga27uHGsuF0ztywcEjTW/c7CrWLN0TKvvItY6nYMdsRZgqY5+ibWYGMg0R481n3PQb6mObsVa0HPQL9ZaWmBtal8+wC/WjF7LB3TEmkQihtxhQUN5NdwiSfev93W1cJjNAWKtq+t9R6z5noNdxZqpY6mOILEmQueldIVY818GLViseZ+DvYm1INf7TrHmfQ72Z6zV18FuCnAO+i3V0RFr/9v6FPYc+g1Pz3oKMrVaOAfXlqzBoz/fi9emPge9MqpzrFWUtw38dBVrAZZmcrcvzST3W6ojUKx5n4PBYk0SYFmcoNf7oLHWnet98FiL8FuqI1CsAb28t+pVrAW+twrUTomk7Uc/lfvz4LDbIdPq4IiQ46zPFuHOafdgbvTU3seaVIp8WT1uXv0XvHTaqxiqHdJlrB2u2IN7Nt+Hfy99EWPi2laScFgs+HbLu3h3/zt447KvEKHRez6b7txb+cdaxznoH2tNTVi1dwXe2Pc6Xrvya0Qq2rb1ZawBwc/BguoDuPOL66GUKLBwysVYmnMBfij8Hs/veBYfTHsFKpFCiLXvC77Fk5sfw4qFn0BsaG1rZzfvrYRY6+Leqk9jrVf3Vr6xFuzeCmiLtRWHP8O3tWvw4UXfeD6bbsSaQe3CJT9djkfmPoGpSdM8sTaY85gAy3seax7TcQ1oqG6AqcqzvGe/5zH+7ewij+lOrPXq3uqEz2O6F2vB8ph9dXvx7x9uh9Ymw7whp2B55Ue4c9rdODVzYac8xixxoLG1ARmRmT3OY1xuF/747jmYGJ2LP07967HHWrB7q+70GRxDHuNyu3Dr2v9DVX0Jnprwb0TII4LnMQPVZxATA6VOB51OhZYWC0zVNf2Tx3Q31rrIY44Wa31zb+Uda8HymL7rM+jy3qq7fQbHmscMtj6DINf7kPQZBMtjuhlrx3xvNUB9BrrMTERGqtHSYoHT6RoEeUzgPgO7yYinVt2LUTFjcOb0y/ulz8DmtOHctxbgryOvw6yM+d2KtV9Lf8YTP/wTz89+FrH65B7HWp/kMQPQZwB4Yq3TOdhVrAXrM+jq3qof+gxsIieu2HwDFmcvwZ/H3+ATawXiOmTGDYNO0XbN7cs8ZsD7DHqRxyi0WsQP8fw9B6OQDPqNHz8ezz//PGbOnNlp22+//YYbb7wRO3fuHJC69HbQr7bW0E81onAglbb9krOx0QSHwxXq6hDRAOM1gLZVb8Edv9yKl059Fdl6z9Joz2x/Gturt+LN098LYe2ovwW7Blz0zXk4NXMRrh5z9KU+3tz7Ggx2A26a8H+dtn148D28d+BtfHH2d5CIJZ139uJyu3Dul4tx3vBluGzUlUL5gxvuRYOlHv9d8Hy329Ub9ZZ6XPjNubh9yl04JWPh0XfoQ9/kf4VndzyFz8/+FhpZWwJXa67Fxd+e36k+z2x/Crtrd+HVhQPzw8LB7ufStXho4/34dMmXwmBtdxQ05+PPP16NZxa8iJyYUUff4TjF+wA6FtXmatz3+53Ib8rHrJQ5uHf6gz4dd33lzb2vYcWRT/HR4hU+z3EKJ58c+hCv7H4Rj895ChMSJoW6OgJeA4hObLwGeLjdbiz6bD5umvA3LM5ecvQdALy173V8k/8lPj7ri375/qO+8/Ku57Gy8Du8v/hTqKQqWJ1WvLjzWXxb8DXOG34Brsu98ehvchzquAYMZuKjv6TvRUdH47vvvgu47dtvv0V0dHTAbURERESDwbjY8dDINPi9/Def8j21uzA2blyQveh4l67LQElLcbdeu71mK74v+AYmu6nTtn31e5ETPeqoA34AIBaJkRs3ATtrtgtlLrcLu2p3Ijd+Qhd79o0YVQyGR43Ahor1/X4sf2XGEiRqkoUBPwCIU8dhZHQOfiv/1ee1hxoOYljUcP+3OGFl6DIBAMUtRT3az2hr++FjhDziKK8komAS1Al4at5z+HPuDfjb5H/0W4fnwszTYbab8Vv5z/3y/v2tuKUIr+9djvOHLxtUA35EROQhEomgkCjR6rR0e58jTXnI1g/lgF8YOHvouTA7TFhdvAplhlL8dfV1+LFoJVIiUnGgfn+oq0ddCMmg33XXXYfPPvsMl112Gd566y188803eOutt3DZZZdhxYoVuO666/r1+CaTCQcOHMCBAwcAAGVlZThw4AAqKir69bhERER0fJBJZJiaNA3rKzwDC83WJhS1FCI3bnzoKkYhlaHL6vYgSqWxAnaXHRsqfAeO3W439tftxejYsd0+7sSESdhfvxcWR1uyXdRcgBZrMybETzzKnn1jWvIMbKnaBLvTPiDH61BuKENqRGqn8lkpc7ClapPw97A77ShozsfI6JwBrd9glhKRColIjOJuDlJ36BikjpBx0I/oWKhlapw//A/QynVHf3EvJUUkIzduAr4r+AYud/jNRHlr3+uIUcbgqm7MniciotBRSpXCfXd35DfmYajXajk0eCVqkjA9eRbeO/AWbvjpT7A6bXju5Jdw9tBzkNd4GDanLdRVpCBCMui3bNkyvPjii7DZbHjiiSdw66234oknnoDVasULL7yAZcuW9evx9+7di6VLl2Lp0qUAgEceeQRLly7FM88806/HJSIiouPHzJQ5yG/KR5Wpbf3+vXV7AABjY3NDWS0KoXRtBiqMZUcd/Gp1tKLJ2gSxSIS1Jat9tpUaStBia8GYHgz6jY+fCIfLib11uwEAO2t3QCaWYVTMmJ43ohcmxk+GxWHp8ayxY1VqKEWqNr1T+cyU2bA5bdhatRkAUNRSCIfLgWFRIwa0foOZTCJDijatx5+ZwdYCAIiQaY/ySiIaDM4ddj721O3GP3+7DY2tDaGuTrcVNB3Br2U/4+KcyyGXyI++AxERhYxKqkZrNwf9WqzNqLXU+jwigwa384ZdgDpLHaYlzcALpyzHEP1Q5MSMht3V9sNKGpykR39J/5g/fz7mz58Pl8uFhoYGREdHQywemDHIqVOn4tChQwNyLCIiIjo+TU6YAplYht/Lf8V5w5dhd+0uJKgTkKBJPPrOdFzK0GXA5Xaj3FiGzMisoK/rGCiekzofv5atg8HWIsz22Fe/F2KRCDnRo7t93HRtBqKV0dhRvQ0nJU7FjprtGBUzZsA6SjN0bQ9YLzEUY2jUwCTwDpcDVaYKpGo7P0A9VZuGrMgs/F7+C2anzsWhhoMQi0TI1g8dkLqFi3RtBkp6uryn3QiFRAGZRNY/lSKiPjUjZRYenv04Ht/8MP686mrcMeVuTEyYLGw32gw40LAfQ/XDEKUcPI9ZeWf/W0jUJOK0zEWhrgoRER2FSqpEq9PardceacoDgAHLGejYjY3LxQeLP0OMMkZYkjU7cihkYhkO1O/jaiqDVEhm+nkTiURwOp1wucJvuQkiIiI6callakxMmIT17csz7q7diTF8nt8JrbvPSasyVwEALhh+Idxw49eyX4Rte+t2IytyCNQydbePKxKJMCFhErbXbIPL7cKe2l0YPwDP8+sQIdciShnV7ecZ9oUqUyWcblfA5T0BYFbKXGyoXA+7047DjQeRFTkEColiwOoXDjJ0mb14pp+Rz/MjCjMnJU7Fy6e9jkxdFu745e94cedzeGnXc7h+1R9x7peLcdevt+GNva+GupqC/KY8/Fb+Cy7JuQJScch+p05ERN2kkChhsZu79dr8piNQSBRICXIPT4NTrCrW5xmMMokMw6KG87l+g1jIBv1+/fVXLFu2DGPHjsX8+fOFmXf33HMPvvrqq1BVi4iIiKjbZiTPxt663ag0VqCg+Qhy4wZuoIUGH50iEpEK/VEHUqpNlZCKpRgaNQy5cROwrtSzxOe+ur0YHdvzweMJ8ZNQ0HQE26q3wGQ3YfwAPc+vQ7o2E6WGkgE7XpmhFAACLu8JALNSZsNsN2NHzXYcbjzIpT0DyNBloqG1QViyszuMdiOX9iQKQ9HKGDw65z+4euy1+PLIZ/ildB0yIjPxt8m3Y27qfOyr3xvqKgre3vcmkiKScUrGaaGuChERdYNKqkKrs7Vbr81vykO2fijEopDPQ6JjNDJ6FA407At1NSiIkETYN998g2uvvRapqam47777fGb5paWl4fPPPw9FtYiIiIh6ZHryDLjdbry652W43G6M7cVgDR1fMnQZR53xVmGsQII6EWKRGPPSTsau2h1oaK1HY2sDyo1lGN2LZ/FNiJ8EN4C39r0OhUSBEVEje9mC3knXpQ/oTL9SQwkUEgViVbEBt2dFZiMpIhlrSlehqLkQwwf47xEOhGVZW7o/WGu0GRAh40w/onAkFolx4chL8PU5P+K9Mz/BHVPuxqKsMzAteTpKWop79AOA/nKkMQ/rK37DpTmXc5YfEVGYUEpV3X6m35GmI1xy/ziREzMKVaaqsHpm8IkkJIN+L7zwAq644go89dRTOPfcc322DRs2DHl5eaGoFhEREVGPRCmjMSpmDH4pW4doZTSXKSFk6DJRYijq8jVVpkoktj/7cXbqHIggwq9lP2N/fdsvJcf0YvA4Xh2PlIhUHGo4iDGxYwf8mWvp2gyUGUvhcg/Mkv3lxjKkalN9lpnxJhKJMDtlDtaW/ASn2zXgg6DhIFWbDrFIhKKWwm7vY7AbuLwnUZiTSWQ+185R7T802T8Iluh6e/8bSIlIxcnpnOVHRBQulFIlrN14pp/VaUWpoRhDIjnodzzIiWl7Bv3BhgMhrgkFEpJBv9LSUsydOzfgNpVKBYPBMMA1IiIiIuqdGSmzAADj4sYHHYCgE0eGLhOlhlI4Xc6gr6k2VyJRkwQA0Mp1mJRwEtaVrsG+uj2IU8UhXh3fq2NPaF/Sc6CX9gSAdF0GHC4HKo0VffaedZY6mIM8H6TUUIrUiMBLe3aYmTIHLrcbUrEUmZFZfVav44VcIkeSJqVHMzTNdhMi5Fzek+h4kqRJhl6hx776PSGtR17jYWyo+B2XjrocErEkpHUhIqLuU0qUQe/ZvRU1F8LldmNY1PABqBX1t3hVPKKV0cIPV2lwCcmgX1xcHAoKCgJuO3ToEJKTkwe4RkRERES9MzN5NoC2QT+iNG162+CXKfDgl9vtRqXJM+gHAPPTT8beuj34rfwXjI4d2+tjT0yYDKBtqc+BlqZtWyqyL5/rd+u6m/HmvtcCbiszlCBVm9bl/iOjcxCjisGQyGzIJfI+q9fxJEOXieIezPQz2gzQcHlPouOKSCRCTsxoHAjhTL+2pdJfQkpEKuannRKyehARUc9195l+eY2HIRaJ+GO848RguH+g4EIy6Ld48WI8++yz2LBhg1AmEolw+PBhvPrqq1iyZEkoqkVERETUYynaVDwx92kszDw91FWhQSBD15bEFrcUBdxutBtgtpt9Bv2mJ8+CTCxDpakSY45h0G9mymw8Nuc/GB41otfv0VuxqliopKqg7e6pFmszyo1l2FmzrdM2s92MhtYGpGq7Xk5XLBLjz+P+ggtHXtIndToeZURm9ugzM/CZfkTHpdExY3CwYX+Xs9T706bKDdhevQ1/zr2Bs/yIiMJMd5/pV9B8BGnaDCgkigGoFQ2EnOhRONR4YMAe8UDdF5JBvxtvvBETJkzAVVddhZkzZwIA/vSnP+Hss8/GmDFjcO2114aiWkRERES9Mj5+ImcSEQAgWhmNCFlE0CUTK42VANqWU+ugkWkwJWkaAGB0TO8H/cQiMSYmTA7JMrMikQhp2vQ+m+l3uPEQgLZlgAy2Fp9t5cYyAG3PpDua+eknY3Zq4McKEJChzUCdpQ4mu6lbrzfajdByeU+i486o2DFodbSisDnwikz9ye6046Vdz2NC/ERMS5ox4McnIqJjo5R075l+R5ryMFTP5/kdT3JiRqHV0YqiENw/UNekoTioXC7Hiy++iI0bN2L9+vVobGxEZGQkZsyYgRkzeJNHREREROFJJBIhXZeBYkNRwO1V5rZBv0RNok/5kuylaGxtQFbkkP6uYr9J0/XtoJ9ULIHD5cTeuj2YnjxT2NZxjNSIrmf60dF1zEwtaSlGTsyoLl/rdDlhcVgQIeOgH9HxZnjUCEjFEuyr34OhUcOO+vpWRysUEkWf/Mjkq/wVqDSV494ZD/LZyEREYUglVcHi6PqZfi63CwVN+Zidwh/jHU+GRY2AWCTC/vr9GMIB3UElJIN+HaZNm4Zp06aFsgpERERERH0qXZeBI415AbdVGiugkqqgk0f6lE9MmCw8ky9cpWszsKliA9xu9zF33B5uPITRMeNQbizF3rrdPoN+ZYZS6BV6RHDG2TFL1aZBhLblaI826GeyGwEAEXIu70l0vFFIFBiqH4799Xtx9tBzu3xtrbkWf151FRI1Sbhi9DWYkjj1qNd8s92MVcUrMTNlDmJVsUJ5U2sj3tn/Js7IOgtDIrP7pC1ERDSwlFIlHC4nHC4HpOK2oQa32w0AwvdDmaEUVqcV2RwYOq6opCpkRWbjYMN+LM7m49oGk5As7+nN5XLh8ssvR1FRUairQkRERER0zDJ0mSgxFAd8tkG1uQqJmsTjcjZDui4DRrsRTdbGY36vvMZDGBE9AmNix2FP3W6fbeXGUqRq0475GNTWSROvTkC5sfSorzV2DPrxmX5Ex6VRMWOwv37fUV/3yu4XIBFJoJAocPdvt+PmtTdgW/UWoYPX3966Pbhu1dV4bsf/cM0Pl+Hr/C+E78e3978BALhi9NV91xAiIhpQSqkKAITn+lWZKnHND5dj2ddL8e+ND+Cb/K+woeJ3AMBQ/dFnk1N4GRUzGgca9oe6GuQn5IN+brcbmzdvhsnUvedIEBERERENZunaTNicNlSZKjttqzJVIkGTFIJa9b90bQYABH2eYXc1tjagxlyDYVEjMDZ2HA43HESro1XYXmrgoF9filJGo7H16AO1BpsBALi8J9FxalTMaFSZqlBvqQ/6mh3V27CudA3+nHsDnpr3LB6Z/QTcbjfu+OVWXP/TNfjgwLsoN7Q9d9XutOP1vcvx93U3IUoZjedOfhnzUhfgme1P45a1N2Jd6Rp8W/AVLh11BfTKqIFqJhER9TGlpG3Qz+JoRZWpEreuuxkOtwMLM09HlakSz+54Cq/ueRnx6njoFJFHeTcKNznRo1DSUgxje65Ag0NIl/ckIiIiIjre5MTkQARgb91uJEek+GyrNFXipMSpoalYP0uOSIFEJEaJoQS58RN6/T557UujjogaCYvTAqfbhQP1+zAhYRLcbjfKDKWYmzq/r6p9wtMro9BsbTrq67i8J9HxbVTMGADA/vq9mJ3a+ZlLdqcdz+74L8bEjsXJ6adBJBJhcuIUTEo4CZurNuHHou/x3oG38fre5cjWZ8PtdqO4pQhXjL4GfxhxMSRiCUZEj8QpGafh6W1P4t8bH0BKRCrOzu56OVEiIhrcVFIlAKCwuQD/2/4kpGIZnpz7P8Sp4wAAJrsJe+p2QyfXhbKa1E9yYkYDAA42HMDkxCkhrg114KAfEREREVEf0sp1yIocgt21u3Ba5ulCucvtQrWpbXnP45FULEVyROoxz/TLazwErVyLRE0S3HBDK9diT91uTEiYhEZrAywOC2f69SG9Qo/C5oKjvs4z04+DfkTHozh1HOLV8UEH/T7P+wTlxlLcPf1+nyWqRSIRpiZNw9SkabA4LNhatRm/lK1DQ2s9nlnwEoZHj/B5n7FxuXjp1NfwbcFXGBUzBjKJrN/bRkRE/adjec9/bbwXMcpYPDH3v8KAHwBoZBpMS5oequpRP0uJSIVWrsWBhv0c9BtEQj7oJ5FI8PbbbyMzMzPUVSEiIiIi6hPj4iZgY+XvPmUNrQ2wu+xI0iSHqFb9L02bjhJD0TG9x6HGgxiqHwaRSAQRRBgdOxZ725/rV2Zoe/YcB/36jl7RvZl+RrsRIgBqmabf60REoRHsuX415hq8s/9NLB16PoZEZgfdXyVVYXbq3ICDht7kEjnOGXb+MdeXiIhCT9U+6BdowI+OfyKRCCOjc4R8jQaHkD/TDwCmTJkCsViM4uLioA9/JiIiIiIKF7nx41FlqkK1uVoo63jGX8JxOtMPANJ1GShtKTmm98hrPIThUZ6ZIWNixmJ//T44XA6UGkohFomO64HTgaZX6NHUnUE/mwEaWQTEokGRQhJRPxgdMwaHGw/B5rT5lL+06zmoZWpcPvqqENWMiIgGq+SIFFw5+ho8Oe9/HPA7QU1PnoWdNdsDPtOeQiMkGdtrr72G5557Tvj31q1bMWfOHCxatAinnXYaSkqOraOAiIiIiCiUxsaOAwDsqd0plFWZKgAAieqkUFRpQKRr01FrqYXZbu7V/g2t9aiz1GF49EihbGxcLqxOK/IaD6PcUIoEdSLkEnlfVfmEp1fo0epohcVh6fJ1RruRz/MjOs6NihkDh8uBvMbDANqew/T8jmfwa9nPuC73L9Bwpi8REfkRi8S4ZNTliFXFhroqFCKnZJwGjSwCXx75PNRVoXYhGfT75JNPkJCQIPz7kUcewdChQ/HCCy8gKioKTz31VCiqRURERETUJyIVemRFZmFnzQ6hrMpUBZ0iEmqZOoQ161/pukwAnmU4e+pwe0ez90y/YfrhkEvk2FO3C6XGUi7t2cf0yigAOOoSnya7ERo+z4/ouDZEnw25RI599XuwtmQ1rl55Kb4v/AZ/Gncd5qedEurqERER0SCkkqpwetaZ+L7w217/+LM7LA4LV4nsppAM+lVVVSEjIwMAUF1djX379uHvf/875s+fj2uvvRZbt24NRbWIiIiIiPrM2Ljx2F23S/h3lakSierjd2lPoO2ZfgB6/Vy/vMZD0Mq1SPD6O8kkMoyKGYM9dbtRZihFavsxqG/oFXoAOOoSn0abEREybf9XiIhCRiqWYmR0Dt7c+xoe3vQgRsWMwWuL3sGyERdBJBKFunpEREQ0SC0Zei4sDjNWFa/sl/dvdbTi6pWX4tU9L/XL+x9vQjLop1AoYDQaAQAbNmyAWq3GhAkTAABarRYGgyEU1SIiIiIi6jPj4yag0liBWnMtAKDSVHncP4tOLVMjVhWLEkPvlus/3P48P//O5bGx47Cvbg8qjeVIjUjti6pSO70iGgDQ1NrY5euMdgO0cg76ER3vZqfMRXJECh6a9Rjum/EvJKgTjr4TERERndAS1AmYnTIPK/I+g8vt6vP3X1X8A+osdfg871NUm6r6/P2PNyEZ9Bs3bhxeeeUVrFu3Dq+99hrmzJkDiUQCACgpKfFZ+pOIiIiIKBx1PNdvd23bEp/Vpkokao7vmX5A22y/0pZeDvo1HPR5nl+HMbFjYbAZ4HS7uLxnH4tURALoxkw/u5HP8yI6ASwddh5eXfgWpiZNC3VViIiIKIycM+x8lBvLsLlqU5++r8vtwmeHP8aUxKmIkEXgzX2v9en7H49CMuh3++23o7a2Ftdddx1MJhNuueUWYdv3338vzPojIiIiIgpXemUUMnSZ2FW7Ew6XA7WWGiQe5zP9ACBNl4ESQ3GP96uz1KGhtQHD9MM7bcuJGQ2JqC114fKefUsqlkIr16LJ2vVMP4PNgAg5n+lHRERERESdjYoZjeFRI7Ai75M+fd9NlRtQbizDJaOuwGWjrsTq4h9R0HSkT49xvAnJoN/QoUOxevVqbNiwAWvWrBGe7we0DQjefvvtoagWEREREVGfyo2fgN21u1BrroHL7T4hZvplaDNQYSyDw+Xo0X55jYcAIOBMP5VUhWFRIyCXyBGriu2TepKHXhGFxqMt72kzQCvTDVCNiIiIiIgonIhEIpw3/AJsr96GoubCPnvfTw9/hFExozEqZjTOGHIWEiOS8fre5X32/sejkAz6dYiKiupUNmLECERHR4egNkREREREfWtcbC7KjWXYV78HAJCoSQpxjfpfmjYdDpcTlaaKHu13uPEQdIpIxKviA26fmTIbuXHjIRaFNIU5LkUpo9B8lJl+JruJM/2IiIiIiCio2SnzEKOKwYq8T/vk/Q41HMTu2l04f/gfALStUnLV6D9iU+VG7Knd1SfHOB5JB+pADz30EK6++mokJyfjoYceOurr77777gGoFRERERFR/xkXlwsA+KFoJUQA4tXH/7Or03WZAIDSlhKk9WApzrzGQxgRNQIikSjg9gtHXoILR17SF1UkP5EKPRq7GPSzOq2wu+yIkHHQj4iIiIiIApNJZFiSfQ7e3f8WLh51ORKOMf/97PDHSNQkYmbKbKFsbtp8fHTofby652X8d/7zcMONTZUb8NnhT1DUUoi3T/8Aapn6WJsS1gZs0G/NmjU4//zzkZycjDVr1nT5WpFIxEE/IiIiIgp7UcpopOsysLNmO2JVsZBL5KGuUr+LVkYjRhWDrdVbMCNlVrf2cbvdONRwEGcMOaufa0eB6BVRqDCWBd1utBkBABq5dqCqREREREREYejsoefi6/wv8Nz2p/HgzEeC/qjzaKrN1fi5bA2uy73RZ7UXsUiMP427Dnf8ciue3fFfbK/einJjGTJ1WWi2NuFw40GMj5/YV80JSwM66Bfov4mIiIiIjme5ceNR0lKMJE1yqKsyIEQiEU7NWIhv8r/Cdbl/6dZAZ31rPZqsTRgeNWIAakj+9Ap9l8/0M9haAIAz/YiIiIiIqEsamQY3TbgF963/J34uW4t5aQt69T5f5H0KtVSDhZlndNo2KeEkTEyYhG8LvsSslLn4x0l3IidmFM758kwcqN9/wg/68YEYRERERET9aGxs2xKfCZrEENdk4CzMPANGuxG/l//ardcXt7Q96D1Tl9Wf1aIg2p7p1wS32x1wu8luAsBBPyIiIiIiOroZKbMwK2UOnt/xP+EHhD1htpvxXeE3OHPIWUGX6rxv+kP4YPFnuGf6AxgdOwZikRgjo3Owv2HfsVY/7A34oF9ZWRmefvppXHHFFTjzzDOxePFiXHnllXjmmWdQUVEx0NUhIiIiIupXufHjAeCEmekHAKnaNIyJHYuVRd926/UlLcWQiWVIijhx/kaDiV4RBafbBaPdEHC70d62vGcEl/ckIiIiIqJuuHHC/8HusuOV3S/2eN+9dXtgtpuxKOvMoK9Ry9SIVsb4lOVEj8aB+v1Bf8x4ohjQQb+vv/4aZ5xxBl5++WUUFRVBq9VCo9GgsLAQL7zwAk4//XR89913A1klIiIiIqJ+Fa2MwZ/GXYf56SeHuioDamHmGdhRvQ3VpqqjvrakpRip2lSfZzXQwIlURAIAmqxNAbcb23+dq+WgHxERERERdUOMKgZ/HHsdVhZ+h50123u075Gmw9DINEiJSO3Rfjkxo9FsbUKVqbJH+x1vBiyrzs/Px1133YWJEyfi22+/xc8//4wPP/wQH330EX7++Wd8/fXXyM3NxR133IHCwsKBqhYRERERUb9bNuIipGnTQ12NATUndR4UUiV+LF551NeWGIqRrs3s/0pRQHpFFACgKchz/Yx2I6RiKeTioz+fkYiIiIiICADOGLIYY2PH4eltT8LqtHZ7vyNNecjWD4NIJOrR8XKicwAAB07wJT4HbNDv/fffR1paGl555RVkZ2d32j5s2DC8+uqrSE1NxXvvvTdQ1SIiIiIion6glqkxN3U+fiz6Hi63q8vXlrQUI12XMUA1I39RyvZBv6Az/YyIkEX0OOkmIiIiIqITl1gkxi2T/4EqUwXWlqzu9n5HGg9jqH5Yj4+nU0QiJSIV++v393jf48mADfpt3rwZy5Ytg1we/Nehcrkcy5Ytw+bNmweqWkRERERE1E8WZZ2JKlMVdtXsCPoag60FTdamE24m5GCikUVAIhKjyRpspp+Bz/MjIiIiIqIeS9OmY0jkUOyu3dmt1xvtRlSaKjEsqueDfgAwMiYHB+o5029AVFZWYsSIEUd93YgRI1BeXj4ANSIiIiIiov40OmYMUiJS8UNR8Od2F7cUAwAyONMvZMQiMSIVejR2sbxnhCxigGtFRERERETHg3Fx47Gnble3XlvQdAQAMFQ/vFfHGh0zBvlNeT1aTrRDcUsRLvjqbFSbq3t17MFiwAb9TCYTNBrNUV+nVqthNpsHoEZERERERNSfRCIRFmWdgV/KfobRZgj4mpKWYohFIqRypl9IRSmjulzeU8uZfkRERERE1Atj48ahylSFGnPNUV+b13gYMrGs1yvB5ESPhtPtQl7j4R7v+0Phd2iyNgkDj+FqwAb93G73QB2KiIiIiIgGiVMzFsHpdmBt6ZqA20sMRUjQJEEuCf4YAOp/kQp9F8t7GqHhTD8iIiIiIuqFMTFjAQB7uzHbL6/pMLL1QyERS3p1rKzIIZBL5D1e4tPldmFN6U8AgEpTRa+OPVhIB/JgV1xxxVEf/s7BQSIiIiKi40eMKgaTEk7CutI1OCv77E7bS1qKkaHl0p6hFqWIQq2lNuA2g60FqRGpA1wjIiIiIiI6HuiVUUjXZWB37S4sSD+1y9fmNx7BmNixvT6WRCzByOgcHGjY36P9dtZsR72lHjKxDFWmql4ffzAYsEG/G2+8caAORUREREREg8ikhJPw2p5XYHPaOs3oKzWUYE7qvNBUjASRiigcDrIEjsluRASX9yQiIiIiol4aGzsOe+p2d/kaq9OKEkMRlg4775iONTI6B2tKfurRPmtKfkJyRApSIlI406+7OOhHRERERHRiGh8/AXaXHQfq9yE3foJQ3upoRbWpCmmc6Rdybc/0C7y8p8luQgSX9yQiIiIiol4aF5eLbwu+RmNrA6KU0QFfU9hcAJfbjaH6Ycd0rJyY0fj40IeoNdciTh131NdbnVb8UrYO5w//A5qsTdhTG3wZ0r21ezA7atox1a+/Ddgz/YiIiIiI6MSUFZkNrVyLXbU7fcrLDKVwA0jXcdAv1PSKKBhsBjhcDp9yl9sFo83AmX5ERERERNRrY2JzAQB76/YEfU1e42GIRSJkRQ45pmONjB4FADjYzSU+N1T8DovDggXppyBJk4Qqc2XQx9C9u//tY6rbQOCgHxERERER9SuxSIyxsbnYVbvDp7zEUASAg36DgV6hBwC02Jp9ys0OM9wAZ/oREREREVGvxavjkahJ7HKJz/ymPGTqsjo9EqKnYlWxiFfH40D9vm69fnXJKoyMzkGqNg2JmiS0OlqDroJS2lJyTHUbCBz0IyIiIiKifpcbPx4H6vfD5rQJZcUtxYhWRnNAaRDQK6MAAE2tvsmtyWYEAETI+RkREREREVHvjY3NxW6/1V+85TUeRvYxLu3ZYVTMGOzvxqBfs7UJWyo34pSM0wAASZpkAECVqarTa21OG6pMlX1Sv/7EQT8iIiIiIup3uXHjhef6dShpKUa6LjN0lSJBx0y/JmuTT7nRbgAARMi4vCcREREREfXeuLjxKGg6AqPd2Gmbw+VAYXMBhkUN75NjjYzOweHGQ7A77V2+7peydXDDjTmp8wAAiRFJAIBKU0Wn15YZS+FG4GU/BxMO+hERERERUb8L9Fy/UkMJl/YcJCKFQT/fmX7Gjpl+nI1JRERERETHYGzsOLgB7Kvb22lbiaEYdpcdQ/topl9OzGjYXXYUNOd3+bqfin/E5IQpiFJGA2jLe7RybcAZfeGwtCfAQT8iIiIiIhoA/s/1c7qcKDeWIl2bHuKaEQCopCooJAo0+i3vWWupAQBEKiJDUS0iIiIiIjpOJEekIFoZjb11uzpty2/MAwAM0Q/tk2MN1Q+DSqrClqpNQV9TaazA/vp9OLl9ac8OiZqkwIN+hpKwyIukA3Wgyy+/vEevf/vtt/upJkREREREFArj4yfgld0vwuq0osZcDYfLiXQtZ/oNFlHKqE7Le+6o2Y6syCxEyLm8JxERERER9Z5IJGp/rl/nQb+8pjykRKRCI9P0ybHkEjlmJM/E2tLVuCTncohEok6vWVX8A5RSJaYnz/QpT9QkoTLgoF8x0sIgfx2wmX4RERHQarXC/4qKirB161YYjUYoFAoYjUZs3boVxcXF0Ol0A1UtIiIiIiIaILlx4+FwOXCgfh9KWooBgM/0G0QiFXqf5T3dbje2V2/FxITJIawVEREREREdL8bGjcPhxoNodbT6lOc35fXZ0p4d5qWfgpKWYhQGWOLT5Xbhh6LvMC9tAVRSlc+2JE0SqgI806+kpQTpusG/Us2AzfR74YUXhP/+4osvUFhYiHfffRfp6Z4/UnFxMa6//nqcfPLJA1UtIiIiIiIaIJmRQ4Tn+snFcqhlakS3PzuBQi9K4TvTr8RQjDpLHSbGnxS6ShERERER0XFjbFwuHC4nDjbsx/j4iQDaBuDyGg/j4pzL+vRYk+InQyvXYm3p6k7Lhm6r3oIacw1Oz1rcab9ETTJqzNVwupyQiCVCHUsNJTg167ROrx9sQvJMvxdeeAE333yzz4AfAGRkZOCmm27yGSAkIiIiIqLjg1gkxri48dhduxPFhiKkazMCLrNCoRGp0KPJ65l+26u3QiqWYlxcbghrRUREREREx4tMXRa0ci2+LfgaRc2FcLvdqDRWwOKw9PlMP5lEhtkpc7GudA3cbrfPtu8Lv0WmLgs50aM67ZeoSYTL7Raebw4AdZY6WJ3WsJjpF5JBv6qqqqDJvUgkQnV19QDXiIiIiIiIBkJu3Hjsr9+H/MYjSNcN/uchnEjanunnO+g3OmYslFJlCGtFRERERETHC7FIjHOHXYDfy3/Fn368Ehd9ex6e2vY4APT5oB8AzE8/GVWmKhxo2C+UNbY2YEPFbzh9yJkBx6mSNMkAgEqjZ4nPUkPb4yn4TL8gxo0bh//+978oLS31KS8tLcX//vc/5Obyl6RERERERMej3PgJcLgcKGopRHoYJEwnEr3X8p4OlwO7andiYsKk0FaKiIiIiIiOK5eOugKfn/0NHpn9BOannQyjzYBRMaOhV0b1+bHGxY1HtDIaa0tWC2Wrin8AIMIp6YGX6oxXJ0AEoNJUKZSVtpRAKpYiKSKpz+vY1wbsmX7eHnjgAVx99dVYtGgRhg0bhpiYGNTX1yMvLw8xMTF47rnnQlEtIiIiIiLqZ5m6LOjkOrTYWjjTb5DRK/RodbTC4rDgSFMeLA4LJiXweX5ERERERNS3lFIlJidOweTEKf16HLFIjHlpJ2Nt6U+4fvyNEEGE7wu/xeyUudApIgPuI5fIEaOKRZXZM+hXYihBakQaxKKQzKPrkZDUMDs7G6tWrcLdd9+NnJwciEQi5OTk4O6778aqVauQnZ0dimoREREREVE/63iuHwDO9BtkOn5Z22xtwvbqrdDKtRgWNTzEtSIiIiIiIuq9eWkL0NjaiF01O7C3bjfKDKU4PevMLvdJjkhBldFrpp+hBGlh8Dw/IEQz/QBALpfjoosuwkUXXRSqKhARERERUQhMTZqO3XW7kBSRHOqqkBe9Qg8AaGof9BsfPzEsfslKREREREQUzMjoHCRpkrC2dDVsLhuSIpKRGz+hy30S1IkoNZQI/y41FGNh5hn9XdU+EdIMLj8/H1988QVeeukl1NbWAgCKi4thNBpDWS0iIiIiIupHCzNPxzunf8gBpUFGr4gGAFQYy3CwYT8mxk8OcY2IiIiIiIiOjUgkwrz0k/Fr2c/4pXQdTs8886i5aFJEMqran+lnsptQb6lHupYz/YKyWCy4++678d1330EsFsPlcmH27NmIi4vDf/7zH6SmpuK2224LRdWIiIiIiKifiUQiqGXqUFeD/ES2P9NibekauNxuTE7k8/yIiIiIiCj8zU87GR8ceBdikQinZZ5+1NcnaZLQZG2CxWFBmaEUAJAWJo+nCMlPax977DFs3LgRy5cvx7Zt2+B2u4Vtc+fOxa+//hqKahEREREREZ2wpGIptHIttlZtQpImCYmapFBXiYiIiIiI6JhlRQ5Btj4bM5JnI0YVc9TXJ2raHkVRZapEqaEYAJCqTevXOvaVkMz0++GHH3Dbbbdh1qxZcDqdPttSUlJQXl4eimoRERERERGd0CIVehhsBkxM4NKeRERERER0/Hh8ztOQimXdem3HDyCrTJUoMZQgVhUbNqvVhGSmn9lsRlxcXMBtFotlgGtDREREREREABCliAIATErg0p5ERERERHT80Ckiuz1wF62MhkwsQ6WpAqUtJUgLk+f5ASEa9BsxYgR+/PHHgNvWrVuHMWPGDHCNiIiIiIiIKFKhh1gkwvj4CaGuChERERERUUiIRWIkapJQZapCqaEEabrweJ4fEKLlPW+44QbccMMNsFgsWLRoEUQiEXbv3o1vvvkGn332GZYvXx6KahEREREREZ3QhuizYXGYoZXrQl0VIiIiIiKikEnUJKLcUIpyYynOyj471NXptpAM+s2bNw9PPfUUHn/8cXz99dcAgAceeACJiYl48sknMX369FBUi4iIiIiI6IR22agr4Xa7Q10NIiIiIiKikEqKSMGqopVwuJxhtbxnSAb9AGDRokVYtGgRCgsL0djYiMjISGRnZ4eqOkRERERERARAJBKFugpEREREREQhlahOhMVhAQCkabm8Z7dlZWUhKysr1NUgIiIiIiIiIiIiIiIiQqImCQCgkqoQq4oNcW26b8AG/d54441uv1YkEuHKK6/sv8q0e++99/Daa6+htrYWI0eOxD333INx48b1+3GJiIiIiIiIiIiIiIhocEqOSAYApGnTw2o1lAEb9Hvssce6/dqBGPT77rvv8Mgjj+CBBx5Abm4u3nrrLVxzzTVYuXIlYmJi+vXYRERERERERERERERENDgltM/0S9OFz/P8gAEc9Dt48OBAHapb3njjDSxbtgznnXceAOCBBx7AunXr8Nlnn+Haa6896v5isQhicfiM7lLfkkjEPv9PRCcWXgOITmy8BhCd2HgNIDqx8RpAdGLjNYDoxKGX6hCviceI6BGQSsMn9kP+TL9QsNls2LdvH/785z8LZWKxGDNmzMCOHTu69R67dm1GdXV1f1WRiIiIiIiIiIiIiIiIQmQZzoeiQIaVRV8JZRdddFEIa3R0IR30s1qtKC0thdVq7bRt9OjR/XbcxsZGOJ3OTst4xsTEoKCgoFvvkZs7hTP9TmASiRg6nQotLRY4na5QV4eIBhivAUQnNl4DiE5svAYQndh4DSA6sfEaQHRi40y/IGw2G+6//3589dVXcDqdAV9z4MCBAa5Vz7hcbrhc7lBXg0LM6XTB4eAXPNGJitcAohMbrwFEJzZeA4hObLwGEJ3YeA0gosEqJMOSzz//PH7//Xc8+uijcLvduOeee/DII49g+vTpSElJwUsvvdSvx4+KioJEIkF9fb1PeX19PWJjY/v12ERERERERERERERERER9LSSDfitXrsSNN96I008/HQAwbtw4LF26FK+//jomTZqENWvW9Ovx5XI5Ro8ejQ0bNghlLpcLGzZswIQJE/r12ERERERERERERERERER9LSSDflVVVcjKyoJEIoFCoUBLS4uwbcmSJVi5cmW/1+Gqq67Cxx9/jBUrViA/Px/3338/LBYLzj333H4/NhEREREREREREREREVFfCskz/eLi4oSBvtTUVGzatAkzZswAABQVFQ1IHc444ww0NDTgmWeeQW1tLXJycvDqq69yeU8iIiIiIiIiIiIiIiIKOyEZ9JsyZQq2bt2KBQsW4IILLsDjjz+OgoICyGQy/PTTT1i8ePGA1OPSSy/FpZdeOiDHIiIiIiIiIiIiIiIiIuovIRn0u+WWW9DY2AgAuPLKKwG0PefParXisssuw1/+8pdQVIuIiIiIiIiIiIiIiIgoLIVsec+4uDjh31deeaUw+EdEREREREREREREREREPSMOxUErKyuxb9++gNv27duHqqqqAa4RERERERERERERERERUfgKyaDf/fffjy+//DLgtm+++QYPPPDAANeIiIiIiIiIiIiIiIiIKHyFZNBv165dmDZtWsBtU6dOxc6dOwe2QkRERERERERERERERERhLCSDfmazGVJp4McJikQimEymAa4RERERERERERERERERUfgKyaBfdnY2fvrpp4DbVq9ejaysrAGuEREREREREREREREREVH4Cjzdrp9dccUVuOOOOyAWi3HeeechPj4eNTU1+Pzzz/HJJ5/g4YcfDkW1iIiIiIiIiIiIiIiIiMJSSAb9li5dirq6Ojz//PP46KOPhHKlUom///3vOOecc0JRLSIiIiIiIiIiIiIiIqKwFJJBPwD44x//iAsvvBA7duxAU1MT9Ho9JkyYgIiIiFBViYiIiIiIiIiIiIiIiCgshWzQDwAiIiIwe/bsUFaBiIiIiIiIiIiIiIiIKOwN2KBfQ0MDampqMHLkSJ/ygwcP4oUXXkB+fj5iY2NxxRVXYMGCBQNVLSIiIiIiIiIiIiIiIqKwJx6oAz311FO48847fcrKy8txySWXYPXq1VAoFMjLy8ONN96ILVu2DFS1iIiIiIiIiIiIiIiIiMLegA36bd++HWeddZZP2Ztvvgmz2YyXX34Zn3/+OdasWYPc3FwsX758oKpFREREREREREREREREFPYGbNCvuroaw4YN8ylbu3YtcnJyMGvWLACAUqnEpZdeikOHDg1UtYiIiIiIiIiIiIiIiIjC3oAN+olEIohEIuHfdXV1KCsrw0knneTzuoSEBDQ2Ng5UtYiIiIiIiIiIiIiIiIjC3oAN+mVlZWH9+vXCv9euXQuRSISZM2f6vK62thbR0dEDVS0iIiIiIiIiIiIiIiKisCcdqANddtlluP3229HS0oLY2Fh88MEHSE9Px4wZM3xe99tvv2H48OEDVS0iIiIiIiIiIiIiIiKisDdgg35LlixBdXU13n33XbS0tGD06NG47777IJV6qlBfX4+1a9fipptuGqhqEREREREREREREREREYU9kdvtdoe6EuGottYQ6ipQCEmlYkRFadDYaILD4Qp1dYhogPEaQHRi4zWA6MTGawDRiY3XAKITG68BRCe2jmvAYDZgz/QjIiIiIiIiIiIiIiIiov7BQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojDHQT8iIiIiIiIiIiIiIiKiMMdBPyIiIiIiIiIiIiIiIqIwx0E/IiIiIiIiIiIiIiIiojAnDXUFQuHFF1/Ezz//jAMHDkAmk2Hr1q2hrhIRERERERERERERERFRr52QM/3sdjsWLVqEiy66KNRVISIiIiIiIiIiIiIiIjpmJ+RMv7/+9a8AgM8//7zX72EqKQYAyKOiINPqhHJbYwPsBgNEUinUySlCucvhgKWiHACgiI2FVK0RtrXW1sBpsUCiVEIZnyCUO62taK2uBgAoExIhUSiEbZaqSrhsNkg1GihiYoVyh8kEa30dAECVnAKx1PMRm8tK4Xa5INNFQq7XC+X2lmbYmpoAsQia1HSh3O12w1xa0tbO6BjIIiKEbdaGejiMRohlMqiSkj3ttNthqaxoq3NcPCQqVYB2qqCMj/e002JBa21NW50TkyCWyz3trKyAy26HVBMBRUyMp85GI2wN9QAAdWoaRGLP+LWprARwuSGL1EMeGSmU25qaYG9phkgshjo1zdNOpxPm8rLA7ayvg8Nk6tROp82GlsIaGFsskEXHQaJUetpZUw1nayskKhWUcZ52OsxmWOtq29qZlAyxTCZsM1eUw+1wQKbVQh4V7WmnwQBbY0NbO9PSIRKJPO0sLQHcbsj1esh03u1shL2lBSKJBOqUVKG8q3NQaKdCAVVCoqedVitaq6sAAMqEBEgUnnZaqqvgslohUauhjI3zaqcJ1rog52BHO3U6yPVRnnZ2nIMANOkZQrnPOdirWIuDVK0WtgWNtdZWtNYEiTXhHAwea+qUVIgkEk87g8SarbkZ9uamzrHmcsFcVtrWzr6ItZoaOFuPEmt+56DQzogIKKL7P9YUMbGQagKcg/6x5n0Oxif0PNaCnYOdYq0FtsbGtnb6x1rH9d4v1lobGmAsrYIL4u5f7+tq4TSbA8RaF9f79ljrdA52FWvlZXA7ncFjTSSCJi3I9T4qGjKtVtgWNNa8zsHexFrw671vO33Owf6Mtfp6OEwBYs1mg6WqEkAXseZ3Dh5zrPmfg+2x1vl6HzjWfM7BYLEml0OVmOSpcxfX++Cx1o3rfRex5n29B4LHWq/urXoTa8Hurbpop6m8DA6rvU9jravrfbdj7VjvrfxiTbje+8da+znY/7EW+BzsVaz16t6qPda6urfqy1jrzb2Vf6wFubcC+jiPaY+1QZ3H+MVaX+YxDosFpsq2z3Mg8phO7ewyj+lGrPXm3upEz2O6GWuDIo/pw1gLem/V130Gx5LHDFCfgSImFtJIr2tKf+Ux3Y61LvKYo8Van9xbecda4DymT/sMury36masHWMeM+j6DIJd70PRZxAkj+lurB3zvdUA9RnosjLhLeR5zAnXZ9AHeUw49hl0dW81WPoM+uLeaoD7DHqTxyh0WiDK816D0Qk56NcX8l56FgCQtuQcJMyaLZRXbvwN1b/+AkVUFMbeeY9QbjWYhH2yL78KUWPGCtuqf1qJxj27oR2SjRHX/UUot5RWIe+l5wAAOTf/DQqvxKfs849gKitDzMRJyLrwEqG8Of8wCj98DwCQe9+DkCo9F8fCt1+D3WhE0oJTkLLoDKG8duc2lK/8DmK5HBMfelQod9ntQp0zzr0AcdOmC9vKf/sZtRvXQxkfjzG33iGUtzY2C/sMu/pPiByZ4/nbfP81mg8egG74CAz/45+FcnNVOfKWvwQAGP332yFP8ARaycfvw1JdhdgpU5F5/h+E8qa8Ayj65CMAwIR/PQKJ10Wj4LWX4bRakbLwdCSdfKrn77x9Myp/+hFStRrj739IKHfYrUKds/5wEWImnSRsK/15Neq3boE6OQWj/u/vQrm1pgF7//cfOBwuDL/2emizhwrbKr5egZb8I9CPGo2hV14jlBvLS3DkjVcBAGNvvwtSry/ikg/eQWt9HeJnzEL60nOF8oYDe1DyRdvg9KRHnoBI4klU8l95Hi6nE6lnnoXEufOF8qrNG1C1bg3kOh3G3X2/UG43twrtHHLJ5YjOHe85/uof0LBzByLSMzDyxps97ayoEfYZeePNUHhdbMu//BTGoiJEjctF9qVXCOWGogLkv/sWAGDc3fdBqvRchIveeR225mYkzJmHtMVLhPK6PTtR9u3XEInFmPTok0K52+0Wjp9+9jmIn+mJtYr1v6Lm91+hiInB2Nv/6amzwSjsM/SKq6EfPcbzt/nxOzTt2wtt9lCM+PMNQrmlphJ5Lz0PABh189+hSPF8QZR+/jHM5WWImTQZWX+4WChvzj+Ewg/fBwCMv/9fkCo8F/uCN5fDYTYj6eRTkbLwdKG8dudWlP/wPSRyOSZ4xZrT5vDE2vnLEDdlmufv/Os61G7aAFV8Akbferunzg1Nnlj7458ROXyEsK3y+6/QfOggIkeMxLBrrhXKTZVlyHv1ZQDA6Ftvh9zrS63ko/dgqalG3NTpyDjvAqG88fB+FH/6MQBgwkOP+sbaqy/BabN1jrVtm1C5elXnWLNZPLF24cWImTjZ83de9xPqt22FOiUVo27+m1Buq24Q9hlx3V+gHZLt+dt8vQKG/CPQjx6DoVdcLZQbS4tw5K3XAQBj77wbUq+bh+IP3oa1vh7xM2cj/exzhPKG/XtQ8uUKAMCkx/7jc/N05JXn4Xa5fGJNIhGj/Kd1KFz5I2Q6Hcb98z5Pnc2edmZfegWixuV6/jY/rUTj7l2IyMzEyBv+KpS3VtQK++T4x9qKT2AsKUb0+AkYcvFlQnlLYT4K3nsbAJB79/2QKj0JbtE7r8PW0oLEeQuQesZiobwj1sQSCSY+8oRQ7nY6PbG29FzEz5glbKv4/RfUrP8NyphYjLn9LqHc2mzwxNpVf4Q+Z5SwreqHb9G0fx902UMx3DvWqiuQ9/ILAIBRt9wKtdeNculnH8FcUY6YyScha5lnJn5z/iEUfvQBAGD8A/+GVOG5GRZi7ZTTkHLaIqFciDWFAhP+9YhQ7rR6vtcyL/gDYk+aKmwr+3UN6jZvgiohEaP/fpunzvWe77Xhf7oOumHDPX+b775Ey+FDiByZg2FX/0koN5WXIO/15QCAMf+4A3Kvm/vij95Fa00N4qbNQMa55wvljQf3ofjzTwAAE//9GMRSTzvzX30JLpsNKYvOQNKCU4Ty6q0bUbnmJ8giIpB774NCud1q84q1SxAzcZLn77x2Feq3b4MmNRU5f/XEmrW63hNr198IbdYQYVv5V5/DUJCPqLHjkH3ZlUK5oaQI+W+/AQAYe+c9kEZ5ksXi996EtbERCbPnIO2spUJ5/b49KP2qLdYmP/4UvB15+Tm43W6knXU2EmbPFcorN61H9S/rINfrMe6ue4Vym9HsibXLrkTU2HGev82qlWjcEyDWyqo9sXbT/0HhlciWrfgEptISRI+fiCEXXyqUtxTkoeD9dwEAufe23VtJ2r+P8994tS3W5i9A6ulesbZ7B8q++wZiqRQTH35cKHc5PNf79HPOQ/z0mcK2it9/Rs3636GMjcOY2+701LkpeKxVrvwGzQf2Qzd0GIZfe71Qbq6uQN4rLwIARv/tH5B7JWuln34Ac2UlYk+aiswLvO6tjhxE0ccfAgAmPPgwJF7nYOEby+GwWJB86kIkn7pQKK/ZuRUVP66EVKXC+Af+LZQ7vc7BzAsuROxJUzx/51/WoG7LJqiTkjDqln8I5Za6xuCx9u2XaMk7jMicURh21R+FclN5MfJeb7u3GnPbXZDHeu6tij98B621tYibPgMZ5/jF2opPAQATH34cYqmnUyD/1RfhstuRcvqZSJp/slBevWUDKteuhkyrRe49Dwjl9lZPO4dcfCmix0/0/J3XrEL9jm3QpKUh56ZbhHJrped6P/KGm6DIzPL8bb74FMaiws6xVlyI/HfeBACMu+teSL06LIrefRO2pkYkzJmLtMVnC+X1+3aj9OsvIRKJMOmx/8CbJ49ZioRZc4TyYHmMT6xdfiWixnjH2vdteUzWEIy4/kah3CeP+estUHh1MpSt+Bim0lLETJiErIu88piCPBR+0B5r3c1jdm1H+fffQiyTYeK/HxPKvWOtUx7z+8+o3bAeyrg4jPmHd6y1BM9jOmJt2HAM/9N1wjWgtaIMeS93xNptkCd6OudKPvkAlqoAsdZVHvP6K3C2tiL5tEVIPuU0obxm+2ZU/PQjpCo1xj8QOI/JXHYhYid7xdrPq1G3dTPUyckY9X+3CuXmWs+91fBrr4du6DBhW8U3X6DlSF6XeYx/rHnymJlIX3qeUN5wcC9KVnwGoAd5zJYNqFobII+xWL3ymMsQnTvBc/xgeYx3rP3lr1BkZArbupXH/PNeSJV6YVvRu2/A1tTUKY+p37sLpd981WUe06nPYMNvqP7tFyiiozH2jrs9de4ij6le9T0a9+7p3GfQRR4TvM/AL4+RemKt4K1X4TCZAvQZBM5jfPoMzrsAcVO9Yu3XwHmMT5/BNdcicsRIz98mSB7TnT6DuKnTkHHeMqHcJ4/xj7VgeUywPgNbq08eo2n/XpNIxKgJ0mdgqwmexwTtMygrxpE3XwMAjL3jn5CqPJ29Qqx1lcc8+qTP4OaRV56D2+nqHGub1qPq57WQR0YGzWP8+wxqVv+Ahl07EZGRiZF/8c5juugz+OJTGIuLEJ07HkMuuVwo985jgvUZJM6dj9QzzxLKhT4DiRiTHvGKNZfrqH0GnfKYFq9Yu/Ia6EeN9vxtguUx3rH2f3+HwqtTucs8Roi1h3qWx/j3GXjlMZ36DH5bi9pNGwPkMU1B762C9hlUlCLvtVcAdM5jgvYZHNqH4s8C5zFBY609j5FqNBh/37+EcofN7hNrPn0GQfKYLvsMOvKYMWORfflVQnmXfQbvvwVrQwMSZs1B2pKlQrl3HjPlyacBQLgf6OgzSFu8BAlz5nn+zsHyGJPXvVV3+wzKPbHmn8cE7zM4goL33gEA5N7zgM+9ldBn4J/HdKfPIFge4xdrXeUxQqz55zFV5UIe07nP4EOYKyoQO3kKMpddKJR75zH+fQaFb7wKh8WM5FNOQ7JXrNXs2IKKH1dColRiwoMPC+Vd9hm05zGqxCSM/pt3HhM81iq+/SJIHuPVZ3DbnZB7DZQFzWMO7ff0GfjnMcuD5DHd6TO46FLETOhGHlNVF7zP4MvPYCgsCNBnUIj8t98E0DmPCd5nsBulX30BoCd9Br+j+pefIddHYdxdQfKYTn0GbXlMRGYWRt5wk1DedZ9BWx4TO2kykoZ5+oAGIw769ZJM1hZYEREKRHmN7NarFZDJJJArZD7lrW6rsI9Op/LZplLJYZRJoFT67iOuVwn7ROpU0HptUyhksMkkUKnkPvvYtEphnyi9BrIIzza5XArIJNBofOtsiGjbRyKT+JQ7bbag7axVyyGTSaDwa6fZpu6ynWaZBCq/dsKrzpGRKmh82imFQyaBWu17/NYIr3ZGaXxG3eVyKRwuR6d2NmnaPhuZXOpT7lCIvNqp9NlWrZKjRSaBwq/ORnPbrxmkUjF0OhX0XtuUKjksAT4bl0871VB5bZMrpHDKJFD71dns1U59lAZir1+ryORSuByd69zY/tnI/dppEzuE99JqlZ0+G1mAdkqa1T7noM67nQoZrDIJ1H7tdHi1Ux+phkLvew66A5yDxvZ2isRin3K32x30s6nvOAf92tnqavW0M8A5aAoQayKdyuccjPBppxT2AO20eX82eg1kGt92iuyd29nSEWt+dXbaZJ46+7XTE2u++yiswWNN2R5rSr86u73aqY9UQx0w1uRdx5rXr6xkcinEbic0fnUOFmt2OYK2syPWlH7tlBlVPu30iTWlDK0BYs3p106ldzvlUrhkEmj82mn2a6f3oJ9MJoHbJep0Dtai7RrgH2tWkT1orKk7rvd+105Jk1c7I9U+saZQtsWafzvt3rGmV0MeGSDW/NrZEWtiqW+dXU5n0Fir03R8r/nuY3GYPXUOcE0xBTgHfWNN7RNrCqUsYKxZvT8bvdrn14FBY629zlL/WLNKg7azpv372z/W5K2q4O1UygJe791+7fSNNVnb9d7vs7FEKHw+T+9Yk8skcLolnercEWv+56Bd5g56DlapAn9/Sw2+9xyRPY01vW+syRUyuAJ8f5u82ulzL4D2WHO7O7Wzob2dna73sAVtp0olCxhr4obgsaZUtt1b+X82dq1vO+Var2uUEGt+91btdRbL/GLN4Qgea0HOwS5jTSlru97731v5nYMav3PQHqCdVr92Sr1+oSqTSyFydI615iCx5miVBP1saoLcQ8otXXyvdcSaXztdfnVWBYg1/8/GovW93nv/2lQuk8AJFyL82tkYJNZsUpdXO33rXBWknZIW33b6x1qg6733vVWkX6wpFIHPQVPHvZVIFDDWAHRqZ9A8xifW+jCPUfdBHtP+2fjnMS673SvWFJ1irSlQHmM3Bc9jgsRahEbhFWvB8pij3Fv55zHO4LEmk/u20zuP8f9sqoOcgzLz0WPNv50uv3uOgHmMuhd5jH+sqYPEmsTZ5TkYMI/pKta6k8foNT55jOKY8hj/WAv82RwtjwkUa6JItc85GBEo1nqax9h6ksd49xl0L4/pqs9AyGN60Wfg386uYk3IY7rZZ+Cfx+h0KqH+6iB9BjKTbzu702fg7EafwVHzGK9BP7lMCpfYGfTeqid5TEes+X823nlMpz6D7uQxQfoM/PtGhDxG4nsddLtcQc/BjljrlMc4LV22s6/yGN9YU3evz6Dje62LPMY/l65RBY61rvIYZcf3Wo/ymMDfaxa/dvZXn0GwPManzyBSfex9BkIe47uPdx7jfQ0APH0G/u0Mlsf0ps9A3NibPgO/PEbXOdb87yGNHXlMT/oM1D3vM1AqZQGvKf55jP/3mj3APaR3HtO5z0DSozym6z6DILFm6TrWAuUx3ekz6JTHeOfSerXP7MBgeUyv+gyC3KdIW3reZ+Dw+mz885igfQaaXvQZBMmlu+4zCJLHdNFn0HFvpVR6/vaDlcjtdrtDXYm+8OSTT2L58uVdvua7775Ddna28O/PP/8cDz/8MLZu3drj45Xs2AeRWASFPgoynWd2hbVjaSaJFGqvX9m5HA6Y26eTKgMs7+mwWCBRKKFK8J1OammfTqoKMJ3UabNBqtZA6fVLS7vJCGt9+5Rm/yWo2pcPkPtPaW6fui0KMHXb1D51WxFgqQ670QhxgKnbZq/lA6R+y+I42qduq7xmGDn8lqDyvkEwt09plgVY7s3aPnVb479UR2kJ3G435JGRkEd6tbOpCbb2Kc0av6U6TB1Ldfi1s7WuDg5z21Id3r8ugdMBiaEBRmMr5LHxPssHWKqr4bS2Qhpg+YDW9uUD1P5LdZSXw+Vsm9Ks8FsWx9o+dVsTYMlBN9qmNMu9pjRbGxthN7Qti6PxWxYn6DnY3k6JXAFVou9SHZb2qdsq/2VxqqrgtFkhDTB1u7V96rb/Oehppw4KrxkhNq9lcSL8lsURzsFexVrn5QMCxlprKyw1gWOt4xzsKtY0nZYPCBJrzU2wNTd3jjWXC6b25QOCxprfOdhVrFk6ptV3EWudzsGOWAuwVEe/xFpMDGSao8eazznot1RHt2It6DnoF2stLbA2tS8f4BdrRq/lAzpiTSIRQ+6woKG8Gm6RpPvX+7paOMzmALHW1fW+I9Z8z8GuYs3UsVRHkFgTofMSVEKs+S+DFizWvM/B3sRakOt9p1jzPgf7M9bq62A3BTgH/ZbqCBRrnc7BrmKtorxLJOyTAACTOUlEQVRt4KerWAuwNJO7fWkmud9SHYFizfscDBZrkgBLdQS93geNte5c74PHWoTfUh2BYg3o5b1Vr2It8L1VoHZKJG0/+qncnweH3d63sdbVvVU3Y+2Y7638Y63jHAywvKetZQBiLdg52JtY68W9ldDOLu6t+jTWenVv5Rtrwe6tAE+s9Uke0xFrgzmPCbC857HmMR3XgIbqBpiqPMt79nse49/OLvKY7sRar+6tTvg8pnuxNhjymD6NtWD3Vt3pMxioPGag+gxiYqDU6aDTqdDSYoGpuqZ/8pjuxloXeczRYq1v7q28Yy1YHtN3fQZd3lt1N9aONY8ZbH0GQa73IekzCJbHdDPWjvneaoD6DHSZmYiMVKOlxQKn0zUI8pgTq8+gT/KYcOwz6OrearD0GfTBvdWA9xn0Io9RaLWIH+L5ew5Gx82gX0NDAxrb13sNJi0tDXKvi8WxDPrV1hp6vA8dP6TStl9yNjaa4HC4Ql0dIhpgvAYQndh4DSA6sfEaQHRi4zWA6MTGawDRia3jGjCYHTfLe0ZHRyM6OvroLyQiIiIiIiIiIiIiIiI6zhw3g349UVFRgebmZlRUVMDpdOLAgQMAgPT0dGg0g3uUloiIiIiIiIiIiIiIiMjfCTno98wzz2DFihXCv5cuXQoAePvttzF16tQQ1YqIiIiIiIiIiIiIiIiod07IQb9HH30Ujz76aKirQURERERERERERERERNQnxKGuABEREREREREREREREREdGw76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOQ76EREREREREREREREREYU5DvoRERERERERERERERERhTkO+hERERERERERERERERGFOWmoKzDQysrK8MILL2Djxo2oq6tDfHw8lixZguuuuw5yuTzU1SMiIiIiIiIiIiIiIiLqsRNu0K+goAButxsPPvggMjIycPjwYdxzzz2wWCy4/fbbu/0+jUcaAACqWDWUeqVQbq41w9rcCrFUjMhMvVDutDvRUtwMANAkRkAe4RlgNFYaYDfZIVXJoE3RCuUOix2GcgMAQJuqg1Tp+bgMpS1wWB2Qa+XQJEQI5TaDFaZqEwAgMlMPsdQzmbO5oBEulxvKKBVUMSqhvLXRAku9BSKxCPohUUK52+1GU34jAEAdr4FCp/C0s8YEa4sVEpkEuoxITzttTrSUtLUzIkkLmUbWqZ0ytQwRyZ522k12GCvb2qlL00Gi8LSzpaQZTpsTCq0C6gSNUG5tscJc09ZO/ZAoiMQiYVtTQSPcLjdU0Soooz3ttNRb0NpogVgsQqRXO11OF5oLmwK201RthM1gg0QugS7d006H1YG6Q3VoabZAmaCBTO1pp6HcAIfFDplGhogkr3YabTBWGdvamR4JiVwibGsuaoLL4YIiUgl1nNrTzuZWmGvNbe3MjoJI5NXO/Ea43W6oYlRQRnm1s86M1qZWiCViRGbpPe10uNBc1NZO/3Owo51SpRTaVJ2nna0OGMpaAADaFC2kKq92lrXA0eqAPEIOTaLXOWi0wdTezk7nYHs7lXolVLGednacgwAQNTRaKPc+B3sTaxGJEZB1I9bsZjuMFYFjreMc7DLWsvQQS7oRaw0WWBoCxJrLjaaCo8Sa3znYZaxVGGA3HyXW/M5BIdZ0Cqjj+z/WNAkayLXdiDWvczAiWdvzWMuIhER29FhrbWqFpS5wrAnXe79YM9Wa0FjYAJcIPudgl7FWZYTNGCDWurred8Sa/znYVawVNsHlDB5rIpEI+uwg1/s4NRSR3Yg173OwF7EW7Hrv307vc7BfY63aBKshQKxZHWgpbT8Hg8Wa/znYVawVN8NpP0qs+V/vO2LN/3ofLNa8z8EgsSZVSKFN6+b1PkiseZ+DvYk17+s9EDzWenNv1atYC3Zv1UWsNRU2wW519GmsdXlv1d1YO8Z7K/9Y6zgH/WOt4xzs71gLer3vTaz15t6qI9a6urfqw1jr6t6q27EW5N4K6Ns8Roi1wZzH+Mdan+YxNjS1n7cDkcf4t7OrPKZbsdabe6sTPI/pbqwNhjymT2Mt2L1Vd/oMBiqPGaA+A02CBlLvnKC/8phuxlpXecxRY83vHOxVHuMda8HymD7sM+jq3qrbsXaMecyg6zMIdr0PRZ9BsDymu7F2jPdWA9VnEDsiBt56msewz+DY+gz6Io8Jyz6Dru6tBkmfQZ/kMQPdZ9CLPEatVyIqyvPZDEYn3KDfnDlzMGfOHOHfaWlpKCwsxAcffNCjQb8N9/8CiIAxV+RiyKJsobxkVQEKvj8Cdawapzy7SCi3NbViwwO/AABO+ts0JJ2ULGzL+/QgKjeXIyYnFjPv9dStudwg7DPn4QXQeyU+e5bvQFNhI1JnpWPiXyYL5VX7arH9+a0AgIUvn+lzYm79z0ZYW6wYtnQEcv4wWiiv/L0MBz7aB4lcgjPfOlsod9qcwvHHXTMBmadkCduKvj+Cop8KoU3WYv5/ThXKW2tMwj7Tbp+B+PGJwrZD7+9D9c4qxI+Nx7S7ZgnljSXN2PDwbwCA+U+c4vOltuvFbTCUtSBjfiZyr50olFfsqsbOV7YDAM54YwmkXhfHzY/8DkerAyMvGIXh544Uyst/Kcbhzw9CHiHHouWLhXK71SHUecL1k5E2J13YVvBVHkp/KUZkhh5zH10glBurTPjtrrWwO5yYfvcsxI6KE7YdeGc36vbVInFSEqbcOl0ory9oxKYnNgAATv7vQii8vqB2PrcVpmojshZmY+yVuUJ56bZK7HljFwBg8btLfb64Nj70K1wOF0ZfMhbZi4d59llThCNfH4YySonTXjhDKG812oR2Tr55CpKnpQrbjnx2EOUbyhA1NBqz/zVPKDdUGYV9Zj84D1HDPBfbfW/sQsPheiRPS8Hkm6cK5TUH67H1f5sAAKe9cDrkXhfh7U9vgqXBguwzh2H0pWOF8upNFdj33h6IxCKc9d45Qrnb7RaOP/bKXGQt9Iq1H/JR8EM+NPEanPy/hUK5rdEi7DPl79ORODlJ2Jb38QFUbq1A7Kg4zLhntlDeXNaCDf/6FQAw95EFUHp9QexdvgNNRU1Im52OCTd4Yq1yby12vNAWa4teWQyp1hNrW57YAJvRhuHnjMTIZaOE8orfS3Hw4/2QKqQ4480lQrnD6xzM/dNEZCzIFLYVfncExasLoU3RYv6TnlizVHvF2p0zET8uQdh28P29qNlVjfjcBEy7Y6ZQ3lDchI2P/A4AmP/kqT5farte2ApDuQEZJ2ch948ThPLyndXYtbw91t5cAqnUK9Ye/h0OqwMjl43C8HO8Yu3nYhxe0TnWbBavWLthMtJme8Xal4dR+msJ9Jl6zHnEE2umOrOwz8x7ZiPGO9be3o26/bVImpyMk/4+TSivO9KIzf9pi7VTnlkIRZxXrD27BaYaE4YszMYYr1ir3VaJPW+2xdpZ75/jc/O08V+/wu1y+8SaRCLG4RUHseeTfVBGKXHq86cLr281WL1ibSqSp6UI2/I+O4CKjeWIHh6DWQ/MFcoNVZ7Pc/a/5vnc2Ox9bScajzQgZXoqJv11ilBec7AOW/+3GQBw2otnQO6V4G57eiNaG1sx9KzhGHXxGKG8I9bEUjEWv7NUKHc5XZ5YuyoXWad5Yq34h3wU/pAPTUIETv7vaUK5td4Ta1P/MR0JEz2xdvij/ajaVonY0XGYcbcn1pq8Ym3eYyf73CjveWUHmoubkDYnAxOunySUV+6txY4X22Lt9FcXQ6oIEGvnjsTIC7xi7bdSHPxkP6RKKc54wyvWWj3n4PhrJyJ9fqawrfDbPBSvLYI2VYf5T5wilFuqPN/f0++ahbix8cK2g+/uQc2eGiSMT8TU22cI5Q2Fjdj42HoAwIL/nApFsl+sVRiQeUoWxl3jibWy7VXY/doOAMCZb50Nicxzvd/079/gtDmR84fRGLZ0hGefdUXI++IQFDoFFr58plBuNduFOk/8y2SkzvLEWv4Xh1H2Wwn0WVGY8/B8odxY6xVr981BzMhYYdv+t3ah/kAdkqak4KRbPNf72rwGbHlqIwDglGcXQRHruenf8b/NMNeZMeT0oRhz+TihvGZrJfa+1RZrSz44F942Pvgr3G43Rl82DtlnDBXKS1cXIv/bPKiiVT6xZm/2urf6v6lImuoVa58eQMWmzrHWUuH5Xpvz0HyfRHbvazvQmN+I1BlpmHjTSUJ59f5abHt2CwDPvZWk/ft4yxMbYGm0YNiS4ci5yBNrVRvKsf+DvZDIJDjzbc+9lcvhibVxV49H5qlDhG3FK4+g8McCRCRGYMHTXrHmdR30j7VDH+xD9Y4qxI2Jx/R/eu6tmspasOGh9lh7/GTo0jyxtvvl7WgpaUb6vEyM/7Pn3qpyTw12vLQNAHD6a2dBqvCcg1seWw+72Y4R5+dgxHk5nn1+K8XBT/dDppbh9NfOEsodFs85OP7Pk5A+L0PYVvBNHkrWFUGXHol5j50slJsrPdeU6f+chbgxvrFWu7cGCRMSMfU2T6zVFzRi0+NtsXby06dB4ZVg7nx+K4yVBmSeOgTjrh4vlJdtr8Lu13cCABa/s9Sn82PTv3+D0+5EzoWjMexsr1hbW4S8Lw9BEanEwpc891besTbpppOQMiNN2Ja/4hDKfi+FfkgU5vzbK9a8vr9n3T8X0V6dRvvf2In6Q/WdY+1QPbb8t+3e6tTnFkER4xVr/90Mc70Z2WcMw+jLvO6ttlRi3zu7IRKJcNb7nnsrAMLxx1w+DkNO98RasDzGJ9ZumYakKZ485vAnB9rymJGxmHlfkDzm3/N9OlP2vLoDTQWNSJ2Zhok3emKtan8dtj/nG2sdguYx68tw4MN9nWLNae8ij1mZj6JVBYhI0mLBU155jNd1sFMe4xdrHdeAlqJmIdb885jdL21Dy/+zd+dhcpVl3oB/VZXuJHRIIAsgogQFwr7IZkIwwzauKFsAZZMBBQWVD0RwZDEKAoKOCPqNH6Ky6IBhE0cEh8GdsERRBFEUEiCsISvpLN2pqu+PkCaddHcS0ulOdd33deXq1DmnznlO93mfrvc8/b7n2bkrtLWu+jEPXXJfWhe0ZpvDt8vWh73+2er53z6Tv9/yeBqbGvOe73bSjzllt7xl3DJt7adP5JlfP50hmw/JuEuWaWvPv97Wxpy7T4Zv//pnq6VtbZN3vCl7ntVJP2b5tra0H/Ovb8uOJ+zStrxdW+ukH7PdR3bIlgdt/fp7fjk1/7hjxX7MoubX+zG7fXrPvHn0yvsx7drahHEZuvXrbW1V+jEHfuu9aRy6Cv2YB5/PYzd03Y9Z4Z7BL57KU3f9M+uNaMoB31zFfszEx/PCQ893fM/gS0ves3w/prN7Biv0Y5Zta5ffn0WvrtjWOuvHLHvPYOeTds3m+7/e1jrrx7S7Z3DO3tlo5w76MTttnHd+/vV+zCrdM9hvZHb+2OttrV0/Zvl7Bkv7Mat4z6BlYft+zPr/MjLJkj5BZ/cMmmd00Y/p5J7BK0/OyoOXv9aPueLd6b/RivcMuuzH/PCQdsXN+7/821TKHdwz+N8p+ed/r/jZqn0/Zrl7BrcuaWtDtxqasV/6l7blr77QxT2D7/0pM/+xkn5MJ/cMtvzAVtnu6BXvGRRLxXzghoPbllcrq3DPYLl+TMvMZdraZ0dnk91W3o9pd8/gkv0yYPMN2tZ12Y9Z2tauXs1+zPL3DBZ2dc/gH3n63o76MfM678f88NG8/EgH9wymzs79lyy5Z9BhP6ajewYPv5g/f7fjfkxn9wza+jHr98+7/9/r/Ziu7hl01o9pd8/g/Hdl2LYd9GP22DR7nLFq9wwe/uZDmT+9OW97z5bZ4fiO+zEH33RYkrR9Hmi7Z3DMjnn7+9u3tY76MQvmrv49g7kvdNWP6fiewUuPv5I/fHNJW3v3f74v/QaseM9ghX7M/c/lrz96tMt7Bp31Y1a4Z9BFP+aJG/+aF//4wor9mGeX6cescM/gj5nz9Jy8ddzm2eWUZdrasv2Y5e4ZTP7qpLQ0t2TUYdtm1OGv92Oe/+1r/ZiBDXnv95bpx3Rxz6CtH/OWwfmXr67aPYPHr++4H9PunsHX/zX937QK/ZiHX3r9nsF1H0pp2X7MhZ30Y1blnsFpe2SzvVehH7PM7+8V7hn84M+Z8bcO7hk8MTMP/ceSewYr9GM6u2fw0PN59LpHkqzGPYN7puTJO/+R9YatlwOu6qQfs9w9g7Z+zKhh2fuLq3bPYGk/5q37vDWbfeH1zy/roror+nXk1VdfzZAhQ1a+4TIaGksppJBBg/q3q+w2NfVPY0O/NPbv12554+KksWHJt3vw4IHt1g0c2JDGhn4ZMKCh3fLFQ+a3vWfIkPbv6T+gXxob+mW99RrbLZ+z/sC292y4Yfu/SGhs7JdqQzlNTcvFPGhJzKXGUrvl5ZZy277WX799BXu99To+z9L8Zd6z3HkOWHqeA9vHvGjw6zEP2WC9DFn2PPv3y6KGfhm43HnOXH9Au/NctqPS2NgvxfKS8+rwZ9PYPuaWxoYuzrMxjQ390n9A+/cU5rQmSRr6lVb4eQ4YsGR/A5c7z/nLnOcGG6yXQcudZ2sHP8/pg9qf57Kd5caGfqkUKp2eZ//G9tfTghSXOc/lrsHXznP5a7AyZOHr1+2QVTvPVwcPWOY8mzJwmQ/wjY39Um7o1+k1WCgW2i2vVqtt+xo0aLmfTWdtrTXLXIMDOr4GlzvP1iHNy7S19ZZra6+d53I/m9nLXIMbbLhe+q/fvq2lobLCeQ567efZb7lrcPGixSu/Bvu3j7nU/HpbWzGnNHb4s1m43DU4uN012JBFHVyDK7S1/su1tcqKP5vO2tqifv06Pc+BbW2t/XlmVssy1+B6HV6DAwa2f0/zctdg07LXx9K2ttzPZvm2tmzRr7GhX6qV6gptLVmSA5Y/zwXVYqfX4NKfzfLXYHnIgk6vwQGdXIOvrt/+57lsW+vf2JBKw+JO21qxX7F9Wy9XOm9rbddg+/NsWFRd5jw7vgaXP8+WwfPanecGq/B7rX1ba0pj0+t/mdVZW1t6niu0tYWvt7VBnV2Dy51ncd7iTtvagKXnudw1uGC532uDl7sGl5xn+5hnLNfWlv1Lv8bGfilXC6v8e21Radm2NrDjn+dyv9eqMxet/Bpcoa21vwaXb2uLO8j3g1772Sw9z2U1NJSSajr9bLV8HuxfLqz2NbjsZ6vlf691lu/nLtfWBizzV60NDaWUO8gpbW2tYbm2trirttbx77V+Cyvd29b6d9zWZi13DS77V9KNjf1SaK122tYalrsGWwe0rsLvteU+W81t7aKtdfyZY/m2tv5y59nSwXm+stx5Llv0a2zsl3IKnf5e67/ceS4slrr1s1X/TtravHZtrSnrbfj6X8IubWvrNTV23NYKK7a1zq7Bzvox7dva8r/XVqUfs2q/1+Ys97NZlX7M0s9WK/RjWrvqx3R8DfZbsAptbbmfzaBlPj8MGbJ8P6ahw7a2sn5MYfGKnzlWpR/T+e+19jEX5nTR1jr5bDV/JW2ttYPfa6+sQj+ms8/3y/djFhZKnf48V6Wtdf57rat+zHrt2lr//g0pN7R2eg123Y/pv9x5dnwNdtWP6Szfd92PWZXPViv2Y7pqa8t/tlr2nsHy12Cn/Zj5K+/HLH8Nrso9g+WvwZXeM6isxj2Dhvb3DAYPHtgWf2efrTJ75f2Yru4ZDOnsnsHK+jHLFP0aGkqpFosrnOd6nZxnu37M8r/XBnbcX1u2H9P577Wu+jEd3zPo7LNVobRcW6us/J7BCv2YlurKr8FubmsbbtjUboTJmvRjOrs/t3r9mI5/Ngu76Md0ds9gZf2Y7rpn0Glba3fPYNXuW3V1z6D/yj5bvfb9XPZrY8OSewadfoZcvh9T6eqz1crvGXR6niv0Y9qf57IjYZfeM1i+rS3N96t3z6Dja7Crfkxn9+e67sd0fJ6zVnbPoKXztrZ8P6arewad/V4rvrr6bW3Bcn3pVenHrNDWGpa7Z9BFP6brewar9tmqOmT17xnMW66tddSP6ewzx9LzXFZn9wyWfrbquh/TcT1m+d9rXd0zWHqe/Qe83ldeVxWq1Wq1t4PoTU8//XQOPfTQnH322TniiCNW+X3/vP+ZFIuFDByx/PQBzVk0e1GKDR0MJ526zHDS9ZcZ0vz80iHNHQzdnvbacNK3LDd9wLNzUl742vQBmyw3Ddqy0wcsOwXVU7NSLVczYOiADBy23NDtV14b0rz80O1/vjakeeMOpuqYsyjFxmKGLPMXTuWWZaYk2XRQGpo6OM/1lp+CqiXznp+35DzfOrhdUWHuM3NSXlRO4+D+aVp+6PZLy0wfsOxUHU++NnR72MAMbDd9wPwsnLkwhVIH0+I8NbvD82x+8bWpOvq3H7pdXVxJZeaizJu3MOttMqj99AHT5mbxgsVLhm4v81dRLfNa0vzCkvMcvHkHU3W0VtJ/g/5Zb5m/MFo0Z2Hmv/za0O0tO5hysJoMHL7ckOZX5mfRrIUp9Cu2Gx1aWbzMlCTLXYNLz3OFa3Dh4rz67NKpOjqYFmfB4jQMasygNy07hcUy0wds0cFUHa2V9N9wQNZbfvqAV16bFmeZvwxc9hp8Q23tTctNpdtJW2ud35p5z3XS1pZeg121tbd1MH1AB21twcwFWTijg7ZWWWaahE7a2vLXYFdt7dXnXs3i+V23teWvwaXn2X9IB1N19GJbW/YaHPTm9Ve/rY3sYPqADtrawtkLs2B6J23tH0unQXu9rZVKxZQWVTL9mVlJsbDiVB2dtLV5L8xL67wO2loX+X7peS5/DXbV1mZPmZ3q4i7aWqGDKaiW5vuNlp+qo5O2tsw1+IbaWmf5vpfaWvNLzWmZu2JbW7xocV59Zul0MR23teWvwa7a2pynZ6fSUum6rW3ZwdRMleoK+b7TtrbMNdhpWxtQajf6a5Xy/fJtbZlr8I20tWXzfdJxW0ve4GerN9DWOvts1VFbK5WKGTx4YJ750/NZ3FLu3rbWxWerVW5ra/jZaoW2tjTfL9/Wll6Da7utdXINvqG29gY+W7WdZxefrbq1rXXx2WqV21onn62SZdpad/RjurGtrbV+zPJtrRv6MUtzwIwX5mTO0p9nT/RjljvPLj9brUpbeyOfreq9H7OKbW2d6Md0Y1vr9LPVKtwz6Kl+TE/eM1hvw4EZPHhg5s5dkLnPzV07/ZhVbGtd9mNW0taWvwbfUD9m2bbWST+mW+8ZdPHZapXb2pr2Y9axewad5fteuWfQST9mldvaGn626ql7BsNGDcuQIetl7twFKZcrq92Pcc9gDe8ZdEc/phbvGXTx2WqduWfQHf2YGrhnMGCDAdl069dH8K+L+kzR7/LLL8/VV1/d5TZ33nln3v7214f6v/TSSznmmGOy55575qKLLlqt402f/uobipO+od9rf/Eya1ZzFi+u9HY4QA+TA6C+yQFQ3+QAqG9yANQ3OQDqW7/lRsKui/qtfJPa8G//9m855JBDutzmLW95fX7al156Kccdd1x23XXXfPnLX17b4QEAAAAAAMBa02eKfkOHDs3QoUNXvmFeL/htv/32ufjii1MsFlf+JgAAAAAAAFhH9Zmi36p66aWXcuyxx2bTTTfN2WefnZkzZ7atGzFi3Z6LFQAAAAAAADpSd0W/3//+93n66afz9NNP513vele7dX//+997KSoAAAAAAAB44+qu6HfooYfm0EMP7e0wAAAAAAAAoNt4mB0AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI0rVKvVam8HAQAAAAAAALxxRvoBAAAAAABAjVP0AwAAAAAAgBqn6AcAAAAAAAA1TtEPAAAAAAAAapyiHwAAAAAAANQ4RT8AAAAAAACocYp+AAAAAAAAUOMU/QAAAAAAAKDGKfoBAAAAAABAjVP0AwAAAAAAgBqn6AcAAAAAAAA1TtGPPuGHP/xh9ttvv+y4444ZP358HnnkkRW2efjhh3Pcccdll112yTve8Y4cffTRWbhwYZf7ff755/Pxj388O++8c0aPHp1LL700ixcvblv/wAMPZNSoUSv8mz59eqf7XLRoUc4555wcdNBB2W677fLJT36yyxj+8Ic/ZLvttsuHPvShlXwXoH71tRzwRvYL9ayv5YAkaWlpyX/8x39k3333zQ477JD99tsvN9988yp+R6C+9LUccM4553S43/e///2r8V2B+tHXckCS3HHHHfngBz+YnXfeOWPHjs3nP//5zJo1axW/I1Bf+mIO+OEPf5j3vve92WmnnfLud787t99++6p9M6AO1VIOeOCBB/KJT3wiY8eOzS677JIPfehDueOOO1bY7uc//3ne8573ZMcdd8xBBx2UX//616vxHUn6rdbWsA668847c/HFF2fChAnZeeedc+211+bEE0/MXXfdlWHDhiVZ0rBPOumknHzyyTnvvPNSKpXyt7/9LcVi53Xvcrmck08+OcOHD8+NN96Yl19+OWeffXYaGhpyxhlntNv2rrvuyqBBg9peLz1uZ/vt379/jj322Nx9991dntvcuXNz9tlnZ/To0XnllVdW5dsBdacv54DV2S/Uq76aAz7zmc9kxowZueiii/LWt74106dPT6VSWdVvC9SNvpgDvvCFL+TMM89s954PfehDec973rNK3xOoJ30xB/zhD3/I2Wefnc9//vPZd99989JLL+WLX/xizjvvvFx11VWr8+2BPq8v5oAf/ehH+drXvpYLL7wwO+64Yx555JGce+65GTx4cPbbb7/V+fZAn1drOeDhhx/OqFGj8rGPfSzDhw/PL3/5y5x99tlZf/31s++++yZJ/vjHP+bMM8/MGWeckX333Tc//elPc+qpp+bWW2/N1ltvvWrfmCrUuMMPP7w6YcKEttflcrk6duzY6ne+8522ZePHj6/+x3/8x2rt91e/+lV1m222qU6fPr1t2Y9+9KPqO97xjuqiRYuq1Wq1ev/991e33nrr6pw5c95Q7GeffXb1E5/4RKfrTz/99Op//Md/VL/5zW9WP/jBD76hY0Bf1xdzwJruF+pJX8wBv/71r6u77bZbddasWW9ov1BP+mIOWN7//M//VEeNGlWdNm3aGzoO9GV9MQd897vfre6///7tll133XXVffbZ5w0dB/qyvpgDjjzyyOoll1zSbtnFF19cPeqoo97QcaAvq+UcsNTHPvax6jnnnNP2+jOf+Uz14x//eLttxo8fXz3vvPNWeZ+m96SmtbS05LHHHsuYMWPalhWLxYwZMyYPP/xwkmTGjBn585//nGHDhuWoo47KmDFjcswxx2Ty5Mld7vtPf/pTtt566wwfPrxt2dixYzNv3rz885//bLftwQcfnLFjx+aEE07IH/7wh245t1tuuSXPPvtsTjvttG7ZH/RFfTkHrM39Ql/RV3PAvffemx122CHf/e53s88+++Td7353Lr300pVOPwL1pq/mgOXdfPPNGTNmTN785jd3+76hlvXVHLDLLrvkxRdfzK9//etUq9W88sorufvuuzNu3Lg13jf0JX01B7S0tKR///7tlvXv3z9/+ctf0trausb7h76ir+SAV199NRtssEG7Y48ePbrdNmPHjs2f/vSnVd6noh81bdasWSmXyysMmx02bFjbdJjPPvtskuSqq67K+PHj893vfjfbbbddPvrRj2bq1Kmd7vuVV15p17CTtL1eOjfviBEjMmHChHzzm9/MN7/5zWyyySY57rjj8thjj63ReU2dOjVf+9rXctlll6VfP7PwQmf6ag5YW/uFvqav5oBnn302f/jDH/KPf/wj3/rWt/Lv//7vufvuuzNhwoQ12i/0NX01ByzrpZdeym9+85scfvjh3bZP6Cv6ag7Ybbfdctlll+X000/PDjvskL333juDBg3K+eefv0b7hb6mr+aAsWPH5uabb86jjz6aarWav/zlL7n55pvT2trq2Z6wjL6QA+6888785S9/yaGHHtrlsZc9p1WhmkCft/T5N0ceeWQOO+ywJMl2222XSZMm5ZZbbsmZZ56Zk046qa0Sv+mmm+ZnP/vZKu37bW97W972tre1vX7HO96RZ599Nj/4wQ9y2WWXvaF4y+VyzjzzzHzqU5/KFlts8Yb2Abyu1nLA2twv1KNazAHVajWFQiGXX3551l9//STJOeeck09/+tO54IILMmDAgDe8b6g3tZgDlnX77bdn/fXXzwEHHNAt+4N6U4s54J///GcuuuiinHrqqRk7dmymT5+er371q7ngggvyla985Q3vF+pRLeaAT37yk5k+fXqOPPLIVKvVDBs2LAcffHC++93vdvkMMmBF63IOuP/++/Pv//7vufDCC7PVVlut7ql1SdGPmrbhhhumVCplxowZ7ZbPmDGjrSI+YsSIJMnb3/72dtu8/e1vz/PPP58kueiii9qmzFo6sm748OF55JFH2r1naUV96T47suOOO+aPf/zjGz2lNDc359FHH83jjz+eL3/5y0mWJKhqtZrtttsu11xzzQpDfKFe9cUc0NP7hVrWV3PAiBEjsvHGG7cV/JbGW61W8+KLL2bkyJFrtH/oK/pqDliqWq3mlltuyYc+9KE0NjZ2yz6hL+mrOeA73/lO3vGOd+Skk05KkmyzzTYZOHBgjj766Jx++unZaKON1mj/0Ff01RwwYMCAXHzxxfnSl76UGTNmZMSIEbnpppvS1NSUoUOHrtG+oS+p5Rzw4IMP5hOf+EQ+//nP5+CDD263bvjw4SuM6lv2nFaFPw+gpjU2Nmb77bfPpEmT2pZVKpVMmjQpu+66a5Jks802y0YbbZQpU6a0e+/UqVPbnoux8cYbZ/PNN8/mm2/etmyXXXbJE0880S5x3HfffRk0aFC23HLLTmP629/+1mXjX5lBgwblpz/9aW6//fa2f0cddVS22GKL3H777dl5553f8L6hr+mLOaCn9wu1rK/mgHe84x15+eWX09zc3LZsypQpKRaL2WSTTdZo39CX9NUcsNSDDz6Yp59+2tSe0Im+mgMWLly4wmieUqmUZMkfAwBL9NUcsFRDQ0M22WSTlEql3Hnnndl3332N9INl1GoOeOCBB3LyySfns5/9bI488sgV1u+yyy65//772y277777sssuu3S532UZ6UfNO+GEE3L22Wdnhx12yE477ZRrr702CxYsaJsLt1Ao5MQTT8yVV16ZbbbZJttuu21uu+22PPXUU/nmN7/Z6X7Hjh2bLbfcMp/73Ody1llnZfr06fnGN76Ro48+uu0vbX/wgx9ks802y1ZbbZVFixZl4sSJuf/++/O9732vy5j/+c9/prW1NbNnz05zc3Mef/zxJMm2226bYrGYrbfeut32w4YNS//+/VdYDvS9HLAm+4V61BdzwAc+8IF8+9vfzuc///l8+tOfzqxZs3LZZZflsMMOM7UnLKcv5oClbr755uy88876ANCFvpgD9t1335x33nn50Y9+lH322Scvv/xyvvKVr2SnnXbKxhtv3B3fNugz+mIOmDJlSh555JHsvPPOmTt3br7//e/nH//4Ry655JLu+JZBn1JrOeD+++/PKaeckuOOOy7/+q//2vZ8wIaGhmywwQZJkuOOOy7HHntsvve972XcuHG588478+ijj+ZLX/rSKn9fClV/JkQfcMMNN+Saa67J9OnTs+222+bcc89dYUTc//t//y8//OEPM2fOnGyzzTb57Gc/m913373L/T733HP54he/mAcffDADBw7MIYcckjPPPLNtqO/VV1+dH//4x3nppZcycODAbL311jn11FPzzne+s8v97rfffnnuuedWWP73v/+9w+2vvPLK3HPPPfnJT37S5X6hXvW1HPBG9wv1qq/lgCR58sknc+GFF+aPf/xjNthgg7z3ve/N6aefrugHHeiLOeDVV1/N2LFj84UvfCFHHHHEqn4roC71xRxw/fXX58Ybb8y0adOy/vrr553vfGfOOussRT/oQF/LAU8++WTOPPPMTJkyJf369ctee+2Vz372s+2eHQa8rpZywDnnnJPbbrttheV77rlnrr/++rbXP//5z/ONb3wjzz33XEaOHJmzzjor48aNW+XviaIfAAAAAAAA1DgTAQMAAAAAAECNU/QDAAAAAACAGqfoBwAAAAAAADVO0Q8AAAAAAABqnKIfAAAAAAAA1DhFPwAAAAAAAKhxin4AAAAAAABQ4xT9AAAAAAAAoMYp+gEAAAAAAECNU/QDAAAAAACAGqfoBwAAAAAAADVO0Q8AAAAAAABqnKIfAAAAAAAA1DhFPwAAAAAAAKhxin4AAAAAAABQ4xT9AAAAAAAAoMYp+gEAAAAAAECNU/QDAABYDccee2yOPfbYttfTpk3LqFGjcuutt/ZiVCu3fNy9bdSoUbnyyiu7ZV+33nprRo0alWnTpnXL/lbHAw88kFGjRuWBBx5oW3bOOedkv/326/FYAACA+tavtwMAAABYHaNGjVql7a677rrstddeazma3jdt2rR861vfykMPPZSXXnopgwcPzsiRI7PXXnvl05/+dG+H94Yde+yxefDBB1e63WmnnZY3v/nNPRARAADAuk3RDwAAqClf/epX273+yU9+kt///vcrLH/729/eI/G8+c1vziOPPJJ+/Xq+e/X000/n8MMPT//+/XPYYYdls802y8svv5y//vWvufrqq9sV/a655poej29NnHLKKTn88MPbXv/lL3/J9ddfn1NOOSVve9vb2paPGjUqW221Vd7//vensbGxN0JdwZe//OVUq9XeDgMAAKgzin4AAEBN+dCHPtTu9Z///Of8/ve/X2H58hYsWJCBAwd2ezyFQiH9+/fv9v2uih/84AeZP39+br/99hVGu82YMaPd63WlILaq9t5773av+/fvn+uvvz5jxozpcARnqVTqqdBWqqGhobdDAAAA6pBn+gEAAH3Osccemw984AN59NFHc/TRR2fnnXfO17/+9STJPffck49//OMZO3ZsdthhhxxwwAH51re+lXK5vMJ+brrpphxwwAHZaaedcvjhh2fy5MkrbNPRM/3OOeec7LrrrnnppZfyyU9+Mrvuumve+c535tJLL13hOLNmzcpZZ52Vd7zjHdl9991z9tln529/+9sqPSfwmWeeycYbb9zh9JbDhg1b4Xuy/DP9nnvuuZxyyinZZZddMnr06HzlK1/Jb3/72xWeUbf0+/nPf/4zxx57bHbeeefss88+ufrqq9vtr6WlJVdccUUOPfTQ7Lbbbtlll13ykY98JPfff3+X57GmOnqm33777ZeTTz45DzzwQA499NDstNNOOeigg9rO6xe/+EUOOuig7Ljjjjn00EPz17/+dYX9Pvnkk/n0pz+dPffcs227//3f/11pPMs/02/pNXLNNde0XVM77LBDDjvssDzyyCPddlwAAKC+KfoBAAB90uzZs/Oxj30s2267bf793/+9bXTYbbfdlvXWWy8nnHBCvvCFL2T77bfPN7/5zVx++eXt3j9x4sScf/75GT58eFtR7hOf+EReeOGFVTp+uVzOiSeemA022CCf+9znsueee+Z73/tebrrpprZtKpVKPvGJT+RnP/tZDjnkkPyf//N/Mn369Jx99tmrdIw3v/nNefHFFzNp0qRV/K68bv78+Tn++OMzadKkHHvssTnllFPy8MMPr/B9WGrOnDk56aSTss022+Tss8/O2972tlx++eX59a9/3bbNvHnzMnHixOy555757Gc/m9NOOy0zZ87MSSedlMcff3y1Y1xTTz/9dM4888zst99+OeOMMzJnzpyccsopueOOO3LxxRfnoIMOyqc+9ak888wzOf3001OpVNre+49//CNHHnlknnzyyXzsYx/LOeeck/XWWy+nnnpq/ud//ucNxfPf//3fueaaa3LkkUfm9NNPz3PPPZdPfepTaW1tXavHBQAA6oPpPQEAgD5p+vTpmTBhQo466qh2y7/2ta9lwIABba8//OEP5/zzz89//dd/5f/8n/+TxsbGtLa25j/+4z+y7bbb5rrrrmubGnPLLbfMeeedlze96U0rPf6iRYvy3ve+N6eeemrbcQ455JDcfPPN+chHPpJkyajDhx9+OP/+7/+e448/vm27E044YZXO8dhjj81PfvKTfPSjH822226bPfbYI3vttVf23nvvlU5letNNN+XZZ5/Nt771rRxwwAFJkqOOOioHH3xwh9u//PLLufTSS9vWH3744dlvv/1yyy23ZNy4cUmSIUOG5N577203legRRxyR9773vbn++uvzla98ZZXOq7tMmTIlN954Y3bdddckS35+J554Ys4777z8/Oc/z6abbtoW9/nnn5+HHnqorTh80UUX5U1velNuueWWtvP5yEc+kg9/+MO5/PLLc+CBB652PM8//3x+8YtfZMiQIUmSLbbYIp/85Cfzu9/9Lvvuu+9aOy4AAFAfjPQDAAD6pMbGxhx66KErLF+24Ddv3rzMnDkzu+++exYsWJCnnnoqSfLoo49mxowZOeqoo9oVsA455JCsv/76qxzDhz/84Xavd9ttt3ZTUP72t79NQ0NDjjjiiLZlxWIxRx999Crtf6uttsrtt9+eD37wg3nuuedy3XXX5dRTT82YMWPy4x//uMv3/va3v83GG2+c/fffv21Z//7928WyrPXWW6/dcxMbGxuz44475tlnn21bViqV2r5flUols2fPzuLFi7PDDjt0OH3m2rblllu2FfySZOedd06SvPOd72wr+C27fOm5zJ49O/fff3/e+973tl0jM2fOzKxZszJ27NhMnTo1L7300mrH8773va+t4Jcku+++e48cFwAAqA9G+gEAAH3Sxhtv3K5gt9Q//vGPfOMb38j999+fefPmtVv36quvJlkyIitJNt9883brGxoa8pa3vGWVjt+/f/8MHTq03bIhQ4Zkzpw5ba+ff/75jBgxYoVReW9961tX6RjJktFil112Wcrlcv75z3/mV7/6Vb773e/mvPPOy2abbZYxY8Z0+L7nnnsub33rW1MoFFbp2JtssskK2w4ZMiR///vf2y277bbb8r3vfS9TpkxpN23lZptttsrn1F2WH5G5tGC7ySabtFs+aNCgJMncuXOTLHlWYrVazRVXXJErrriiw33PmDEjG2+88RrFs7QAuLaPCwAA1AdFPwAAoE9adkTfUnPnzs0xxxyTQYMG5dOf/nTe+ta3pn///nnsscdy+eWXt3um25oqlUrdtq9VPd6oUaMyatSo7LLLLjnuuOPy05/+tNOi3xvZ/8r85Cc/yTnnnJMDDjggJ554YoYNG5ZSqZTvfOc77UYE9pTOYu5sebVaTZK26+Df/u3fss8++3S47eoUZnv7uAAAQH1Q9AMAAOrGgw8+mNmzZ+eqq67KHnvs0bZ82Sk3k7RN/fj0009n9OjRbctbW1szbdq0bLPNNt0Sz6abbpoHHnggCxYsaDfa75lnnlmj/e6www5JljyHrzNvfvOb889//jPVarXdCL41Ofbdd9+dt7zlLbnqqqva7fOb3/zmG95nb1g6mrOhoaHbiqbr8nEBAIC+wTP9AACAulEsLukCLR1ZlSQtLS350Y9+1G67HXbYIUOHDs2NN96YlpaWtuW33XZb21SM3WHs2LFpbW1t9/y9SqWSH/7wh6v0/smTJ7ebQnOpX//610mWTP3Z1bFfeuml/O///m/bskWLFq30WYBdWTqSbdnv75///Of86U9/esP77A3Dhg3LnnvumZtuuqnDwunMmTP71HEBAIC+wUg/AACgbuy6664ZMmRIzjnnnBx77LEpFAr5yU9+0q5IlSwZaXX66afn/PPPz/HHH5/3ve99mTZtWm699dZVfqbfqjjggAOy00475dJLL80zzzyTt73tbbn33nvbnvu3/DP0lnf11Vfnsccey4EHHphRo0YlSf7617/m9ttvzwYbbJDjjz++0/ceeeSRueGGG3LmmWfmuOOOy4gRI/LTn/40/fv3X6Vjd+Rf/uVf8otf/CKnnnpq/uVf/iXTpk3LjTfemC233DLz589f7f31pgsuuCAf+chHctBBB+WII47IW97ylrzyyiv505/+lBdffDF33HFHnzouAABQ+xT9AACAurHhhhvmP//zP3PppZfmG9/4RgYPHpwPfvCDGT16dE488cR22x555JEpl8u55ppr8tWvfjVbb711/u///b+54oorui2epc+7u+iii3LbbbelWCzmwAMPzKmnnpoPf/jDbQW4zpx88sn57//+7zz00EP56U9/moULF2bEiBF5//vfn09+8pNdFiibmppy7bXX5sILL8x1112X9dZbLwcffHB23XXXfOpTn1rpsTty6KGH5pVXXslNN92U3/3ud9lyyy1z2WWX5a677sqDDz642vvrTVtuuWVuueWWXHXVVbntttsye/bsDB06NNttt11OPfXUPndcAACg9hWqy/9JKwAAAL3qnnvuyamnnpof/ehH2W233Xr02D/4wQ9y8cUX5ze/+U023njjHj02AAAAb5xn+gEAAPSihQsXtntdLpdz/fXXZ9CgQdl+++179NiLFi3KTTfdlJEjRyr4AQAA1BjTewIAAPSiL3/5y1m4cGF23XXXtLS05Be/+EUefvjhnHHGGRkwYMBaPfZpp52WTTfdNNtss03mzZuXO+64I0899VQuv/zytXpcAAAAup/pPQEAAHrRT3/603z/+9/P008/nUWLFmXzzTfPhz/84RxzzDFr/dg/+MEPcvPNN+e5555LuVzOlltumZNOOinve9/71vqxAQAA6F6KfgAAAAAAAFDjPNMPAAAAAAAAapyiHwAAAAAAANS4fr0dQK2aPv3V3g6BXlQsFjJ0aFNmzmxOpWKGXKg3cgDUNzkA6pscAPVNDoD6JgdAfSsWCxk2bFBvh9ElI/3gDSgWCykUCikWC70dCtAL5ACob3IA1Dc5AOqbHAD1TQ6A+lYLbV/RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI3r19sBAAAAAAAAtWXO1Nn5+8S/pnVeaxoGNWTU+O0yZOQGvR0W1DVFPwAAAAAAYJWUW8qZNOE3eWHy86mWqykUCqlWq3n6nil50+6bZvQF70qpsdTbYUJdMr0nAAAAAACwSiZN+E2emzQtqSSFQiHJa18ryXOTpmXShN/0coRQvxT9AAAAAACAlZo9ZVZemPx8iqWOSwvFUjEvTH4+c6bO7tnAgCSKfgAAAAAAwCp44ubHUy1Xu9ymWq7miYmP91BEwLIU/QAAAAAAgJVqndfaNqVnZwqFQlqaW3ooImBZin4AAAAAAMBKNQxqSLW6kpF+1Woamxp7KCJgWYp+AAAAAADASo0av10KpZWM9CsVsvX4bXsoImBZin4AAAAAAMBKDRm5QTbZ/U2plCsdrq+UK3nTHptmyMgNejYwIImiHwAAAAAAsIrGXDAubx69WVJM21Sf1Wo1KSZvHrNZRp//rl6OEOpXv94OAAAAAAAAqA2lxlLGXrRv5kydnScmPp6W5pY0NjVm6/HbGuEHvUzRDwAAAAAAWC1DRm6QPc4a3dthAMswvScAAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHH9ejsAAAAAAACgthRbWjJg9twUKpVUi8Us3GBwKo2NvR0W1DVFPwAAAAAAYNVUq2l66eU0zF+QVKtJoZBUq2mcNy+t6w1M88YbLVkG9DjTewIAAAAAAKuk6aWX09A8f8mLpcW91742NM9P00sv91JkgKIfAAAAAACwUsVFLUtG+HU2kq9QSMP8BSm2tPRsYEASRT8AAAAAAGAVDJgzd8mUnl2pVtN/ztyeCQhoR9EPAAAAAABYqUKlsvLn9RUKKZYrPRMQ0I6iHwAAAAAAsFLVYnGVRvpVSkoP0Bu0PAAAAAAAYKUWbjB4lUb6LRoyuGcCAtpR9AMAAAAAAFaq0tiY1oEDOx/tV62mdb2BqTQ29mxgQBJFPwAAAAAAYBU1b7JRWpvWW/JiafHvta+tTeuleeONeikyoF9vBwAAAAAAANSIQiHNm2ycYktL+s+Zm2K5kkqpmEVDBhvhB71M0Q8AAAAAAFgtlcbGLBgxvLfDAJZhek8AAAAAAACocev0SL+HHnoo11xzTR599NFMnz493/rWt3LAAQe0rR81alSH7zvrrLNy0kkndbjuyiuvzFVXXdVu2RZbbJG77rqr+wIHAAAAAACAHrROF/3mz5+fUaNG5bDDDstpp522wvrf/e537V7/5je/yRe+8IW8+93v7nK/W221Vb7//e+3vS6VSt0TMAAAAAAAAPSCdbroN27cuIwbN67T9SNGjGj3+n//93+z11575S1veUuX+y2VSiu8d3UVi4UUi4U12ge1q1QqtvsK1Bc5AOqbHAD1TQ6A+iYHQH2TA6C+1ULbX6eLfqvjlVdeya9//etccsklK9326aefztixY9O/f//ssssuOfPMM7Ppppuu1vGGDm1KoaDoV+8GDx7Y2yEAvUgOgPomB0B9kwOgvskBUN/kAGBd1WeKfrfddluampryr//6r11ut9NOO+Xiiy/OFlts0facwKOPPjo//elPM2jQoFU+3syZzUb61bFSqZjBgwdm7twFKZcrvR0O0MPkAKhvcgDUNzkA6pscAPVNDoD6tjQHrMv6TNHvlltuyUEHHZT+/ft3ud2y04Vus8022XnnnbPvvvvm5z//ecaPH7/Kx6tUqqlUqm84XvqGcrmSxYv9god6JQdAfZMDoL7JAVDf5ACob3IAsK5a9ycgXQWTJ0/OlClTVqtot9TgwYMzcuTIPPPMM2shMgAAAAAAAFj7+kTR7+abb87222+fbbbZZrXf29zcnGeffTYjRoxYC5EBAAAAAADA2rdOF/2am5vz+OOP5/HHH0+STJs2LY8//nief/75tm3mzZuXu+66q9NRfscff3xuuOGGtteXXnppHnzwwUybNi1//OMfc9ppp6VYLOYDH/jA2j0ZAAAAAAAAWEvW6Wf6PfrooznuuOPaXl988cVJkkMOOSSXXHJJkuRnP/tZqtVqp0W7Z599NrNmzWp7/eKLL+aMM87I7NmzM3To0Oy222758Y9/nKFDh67FMwEAAAAAgNpUnDolAybemMK8eakOGpSF449KZeQWvR0WsJxCtVqt9nYQtWj69Fd7OwR6Ub9+xWy4YVNmzWr20F6oQ3IA1Dc5AOqbHAD1TQ6A+laXOaClJU0TzkvD5AeSciUpFJJqNSkV07r7Xmm+4MtJY2NvRwk9YmkOWJet09N7AgAAAAAAvaNpwnlpmPT7pFJdUvBLlnytVNMw6fdpmnBe7wYItKPoBwAAAAAAtFOc8tSSEX6lUscblEppmPxAilOn9GxgQKcU/QAAAAAAgHYG3HzTkik9u1KupP/EG3smIGClFP0AAAAAAIB2CvPmvT6lZ6cbFVJsbu6ZgICVUvQDAAAAAADaqQ4alFSrK9momkpTU88EBKyUoh8AAAAAANDOwvFHJaWVlBBKxSwaf1TPBASslKIfAAAAAADQTmXkFmndfc+kXO54g3I5rXvslcrILXo2MKBTin4AAAAAAMAKmi+4MK2j906Khden+qxWk2IhrWP2TvP5X+7dAIF2+vV2AAAAAAAAwDqosTHNF12a4tQp6T/xxhSbm1Npasqi8UcZ4QfrIEU/AAAAAACgU5WRW2TBWZ/v7TCAlTC9JwAAAAAAANQ4RT8AAAAAAACocYp+AAAAAAAAUOMU/QAAAAAAAKDGKfoBAAAAAABAjVP0AwAAAAAAgBqn6AcAAAAAAAA1TtEPAAAAAAAAapyiHwAAAAAAANQ4RT8AAAAAAACocf16OwAAAAAAAGDdNXVqIRMnNmTevEIGDapm/PjWjBxZ7e2wgOUo+gEAAAAAACtoaUkmTGjM5MmllMuFFApJtZrcc08pu+9ezgUXtKSxsbejBJYyvScAAAAAALCCCRMaM2lSv1QqSwp+SVIoJJVKIZMm9cuECSp+sC5R9AMAAAAAANqZMqWQyZNLKZU6Xl8qJZMnlzJ1aqFnAwM6pegHAAAAAAC0c/PNDSmXuy7olctLnvUHrBsU/QAAAAAAgHbmzXt9Ss/OFApJc7ORfrCuUPQDAAAAAADaGTSommq1622q1aSpaSUbAT1G0Q8AAAAAAGhn/PjWlEpdF/RKpWrGj2/toYiAlVH0AwAAAAAA2hk5sprddy+nXO54fbmc7LFHOSNHGukH6wpFPwAAAAAAYAUXXNCS0aMXp1h8farPajUpFqsZM2Zxzj+/pXcDBNrp19sBAAAAAAAA657GxuSii1oydWohEyc2pLm5kKamJVN6GuEH6x5FPwAAAAAAoFMjR1Zz1llG9cG6zvSeAAAAAAAAUOMU/QAAAAAAAKDGKfoBAAAAAABAjVP0AwAAAAAAgBqn6AcAAAAAAAA1TtEPAAAAAAAAapyiHwAAAAAAANQ4RT8AAAAAAACocYp+AAAAAAAAUOMU/QAAAAAAAKDG9evtAAAAAAAAgO4xZ+rs/H3iX9M6rzUNgxoyavx2GTJyg94OC+gBin4AAAAAAFDjyi3lTJrwm7ww+flUy9UUCoVUq9U8fc+UvGn3TTP6gnel1Fjq7TCBtWidnt7zoYceyimnnJKxY8dm1KhRueeee9qtP+ecczJq1Kh2/0488cSV7veHP/xh9ttvv+y4444ZP358HnnkkbV1CgAAAAAAsNZNmvCbPDdpWlJJCoVCkte+VpLnJk3LpAm/6eUIgbVtnS76zZ8/P6NGjcoFF1zQ6Tb77LNPfve737X9+/rXv97lPu+8885cfPHFOfXUU3Pbbbdlm222yYknnpgZM2Z0d/gAAAAAALDWzZ4yKy9Mfj7FUse3/IulYl6Y/HzmTJ3ds4EBPWqdnt5z3LhxGTduXJfbNDY2ZsSIEau8z+9///s54ogjcthhhyVJJkyYkF/96le55ZZb8vGPf3yV91MsFlIsFlZ5e/qW0mu/PEud/BIF+jY5AOqbHAD1TQ6A+iYHQH1bl3PAP2/9e1Kpto3w60i1Us0/b/lb9jp7TA9GBn3Hutj2l7dOF/1WxYMPPpjRo0dn8ODBeec735nTTz89G264YYfbtrS05LHHHsvJJ5/ctqxYLGbMmDF5+OGHV+u4Q4c2dZlAqQ+DBw/s7RCAXiQHQH2TA6C+yQFQ3+QAqG/rYg4oLa6mX7+VP6+vWK5mww2beiAioDfUdNFvn332yYEHHpjNNtsszz77bL7+9a/nYx/7WG666aaUSismuFmzZqVcLmfYsGHtlg8bNixPPfXUah175sxmI/3qWKlUzODBAzN37oKUy5XeDgfoYXIA1Dc5AOqbHAD1TQ6A+rYu54Byv0IWLy53PdKvWk2lVMisWc09GBn0HUtzwLqspot+73//+9v+P2rUqIwaNSoHHHBA2+i/talSqaZSqa7VY7DuK5crWbx43foFD/QcOQDqmxwA9U0OgPomB0B9WxdzwFaHbZMpv3gy1a7CKhay5WHbrHOxA91n3Z+AdDW85S1vyYYbbpinn366w/UbbrhhSqVSZsyY0W75jBkzMnz48J4IEQAAAAAAutWQkRtkk93flEonIxAr5UretMemGTJyg54NDOhRfaro9+KLL2b27NkZMWJEh+sbGxuz/fbbZ9KkSW3LKpVKJk2alF133bWnwgQAAAAAgG415oJxefPozZLikqk8k9e+FpM3j9kso89/Vy9HCKxt6/T0ns3NzXnmmWfaXk+bNi2PP/54hgwZkiFDhuSqq67Ku9/97gwfPjzPPvtsLrvssmy++ebZZ5992t5z/PHH58ADD8wxxxyTJDnhhBNy9tlnZ4cddshOO+2Ua6+9NgsWLMihhx7a4+cHAAAAAADdodRYytiL9s2cqbPzxMTH09Lcksamxmw9flsj/KBOrNNFv0cffTTHHXdc2+uLL744SXLIIYfki1/8Yp544oncfvvtefXVV7PRRhtl7733zmc+85k0Nja2vefZZ5/NrFmz2l6/733vy8yZM/PNb34z06dPz7bbbpvvfve7pvcEAAAAAKDmDRm5QfY4a3RvhwH0gkJ16ThfVsv06a/2dgj0on79itlww6bMmtXswbdQh+QAqG9yANQ3OQDqmxwA9U0OgPq2NAesy/rUM/0AAAAAAACgHin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxvXr7QAAAAAAAIDuUWxpyYDZc1OoVFItFrNwg8GpNDb2dlhAD1D0AwAAAACAWletpumll9Mwf0FSrSaFQlKtpnHevLSuNzDNG2+0ZBnQZ5neEwAAAAAAalzTSy+noXn+khdLi3uvfW1onp+ml17upciAnqLoBwAAAAAANay4qGXJCL/ORvIVCmmYvyDFlpaeDQzoUYp+AAAAAABQwwbMmbtkSs+uVKvpP2duzwQE9ApFPwAAAAAAqGGFSmXlz+srFFIsV3omIKBXKPoBAAAAAEANqxaLqzTSr1JSEoC+TAsHAAAAAIAatnCDwas00m/RkME9ExDQKxT9AAAAAACghlUaG9M6cGDno/2q1bSuNzCVxsaeDQzoUYp+AAAAAABQ45o32SitTestebG0+Pfa19am9dK88Ua9FBnQU/r1dgAAAAAAAMAaKhTSvMnGKba0pP+cuSmWK6mUilk0ZLARflAnFP0AAAAAAKCPqDQ2ZsGI4b0dBtALTO8JAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGpcv94OAAAAAAAAilOnZMDEG1OYNy/VQYOycPxRqYzcorfDAqgZin4AAAAAAPSelpY0TTgvDZMfSMqVpFBIqtU03nN3WnffK80XfDlpbOztKAHWeab3BAAAAACg1zRNOC8Nk36fVKpLCn7Jkq+Vahom/T5NE87r3QABaoSiHwAAAAAAvaI45aklI/xKpY43KJXSMPmBFKdO6dnAAGqQoh8AAAAAAL1iwM03LZnSsyvlSvpPvLFnAgKoYYp+AAAAAAD0isK8ea9P6dnpRoUUm5t7JiCAGqboBwAAAABAr6gOGpRUqyvZqJpKU1PPBARQwxT9AAAAAADoFQvHH5WUVnKbulTMovFH9UxAADVM0Q8AAAAAgF5RGblFWnffMymXO96gXE7rHnulMnKLng0MoAYp+gEAAAAA0GuaL7gwraP3ToqF16f6rFaTYiGtY/ZO8/lf7t0AAWpEv94OAAAAAACAOtbYmOaLLk1x6pT0n3hjis3NqTQ1ZdH4o4zwA1gNin4AAAAAAPS6ysgtsuCsz/d2GAA1y/SeAAAAAAAAUOPW6aLfQw89lFNOOSVjx47NqFGjcs8997Sta21tzWWXXZaDDjoou+yyS8aOHZvPfe5zeemll7rc55VXXplRo0a1+/ee97xnbZ8KAAAAAAAArDXr9PSe8+fPz6hRo3LYYYfltNNOa7du4cKF+etf/5pPfOIT2WabbTJ37txcdNFF+cQnPpFbb721y/1utdVW+f73v9/2ulQqrZX4AQAAAAAAoCes00W/cePGZdy4cR2uW3/99dsV7pLkvPPOy/jx4/P8889n00037XS/pVIpI0aMWKPYisVCisXCGu2D2lUqFdt9BeqLHAD1TQ6A+iYHQH2TA6C+yQFQ32qh7a/TRb/VNW/evBQKhQwePLjL7Z5++umMHTs2/fv3zy677JIzzzyzyyJhR4YObUqhoOhX7wYPHtjbIQC9SA6A+iYHQH2TA6C+yQFQ3+QAYF3VZ4p+ixYtyuWXX573v//9GTRoUKfb7bTTTrn44ouzxRZbZPr06fnWt76Vo48+Oj/96U+7fN/yZs5sNtKvjpVKxQwePDBz5y5IuVzp7XCAHiYHQH2TA6C+yQFQ3+QAqG9yANS3pTlgXdYnin6tra35zGc+k2q1mgkTJnS57bLThW6zzTbZeeeds+++++bnP/95xo8fv8rHrFSqqVSqbzhm+oZyuZLFi/2Ch3olB0B9kwOgvskBUN/kAKhvcgCwrqr5ol9ra2tOP/30PP/887n22mtXa7RekgwePDgjR47MM888s5YiBAAAAAAAgLWrpot+Swt+Tz/9dK677rpsuOGGq72P5ubmPPvssxkxYsRaiBAAAAAAAADWvnW66Nfc3NxuBN60adPy+OOPZ8iQIRkxYkQ+/elP569//Wu+853vpFwuZ/r06UmSIUOGpLGxMUly/PHH58ADD8wxxxyTJLn00kuz7777ZtNNN83LL7+cK6+8MsViMR/4wAd6/gQBAAAAAACgG6zTRb9HH300xx13XNvriy++OElyyCGH5LTTTsu9996bJPnQhz7U7n3XXXdd9tprryTJs88+m1mzZrWte/HFF3PGGWdk9uzZGTp0aHbbbbf8+Mc/ztChQ9f26QAAAAAA0ImpUwuZOLEh8+YVMmhQNePHt2bkyGpvhwVQMwrValXWfAOmT3+1t0OgF/XrV8yGGzZl1qxmD+2FOiQHQH2TA6C+yQFQ3+QAWDtaWpIJExozeXIp5XIhhUJSrSalUjW7717OBRe05LWJ3XqVHAD1bWkOWJcVezsAAAAAAADq14QJjZk0qV8qlSUFvyQpFJJKpZBJk/plwoR1oOIHUAMU/QAAAAAA6BVTphQyeXIppVLH60ulZPLkUqZOLfRsYAA1SNEPAAAAAIBecfPNDSmXuy7olctLnvUHQNcU/QAAAAAA6BXz5r0+pWdnCoWkudlIP4CVUfQDAAAAAKBXDBpUTbXa9TbVatLUtJKNAFD0AwAAAACgd4wf35pSqeuCXqlUzfjxrT0UEUDtUvQDAAAAAKBXjBxZze67l1Mud7y+XE722KOckSON9ANYGUU/AAAAAAB6zQUXtGT06MUpFl+f6rNaTYrFasaMWZzzz2/p3QABakS/3g4AAAAAAID61diYXHRRS6ZOLWTixIY0NxfS1LRkSk8j/ABWnaIfAAAAAAC9buTIas46y6g+gDfK9J4AAAAAAABQ4xT9AAAAAAAAoMYp+gEAAAAAAECNU/QDAAAAAACAGtetRb/p06d3uf6xxx7rzsMBAAAAAAAA6eai30EHHZS77rprheWVSiVXXXVVjjzyyO48HAAAAAAAAJBuLvr967/+a04//fScddZZefXVV5MkTz31VI488shcffXVOeuss7rzcAAAAAAAAECSft25sy996UvZf//9c+655+aggw7KBz7wgdxwww3Zcsstc+utt+btb397dx4OAAAAAAAASDeP9EuScePG5eqrr87MmTNzzTXX5G1ve1tuvPFGBT8AAAAAAABYS7q96HfHHXfkuOOOy2abbZaPfexj+cc//pETTjgh06ZN6+5DAQAAAAAAAOnmot+nP/3pnH322fnQhz6U2267LWeccUYmTpyYOXPm5IMf/GAmTpzYnYcDAAAAqCnFlpas9/IraXrx5az38isptrT0dkgAAPQR3fpMv0cffTTf//738853vrNt2TbbbJNbbrklV1xxRb74xS9m/Pjx3XlIAAAAgHVftZqml15Ow/wFSbWaFApJtZrGefPSut7ANG+80ZJlAADwBnVr0e+OO+7IoEGDVlje0NCQz372s9l///2783AAAAAANaHppZfT0Dx/SWFvaXHvta8NzfPT9NLLad5k416MEACAWtetRb+lBb85c+bkH//4R1544YW8613vypAhQ7Jo0aLsvPPO3Xk4AAAAgHVecVHLkhF+nY3kKxTSMH9Bii0tqTQ29mxwAAD0Gd1a9KtUKvnGN76R66+/PgsWLEihUMjNN9+cIUOG5LTTTsvOO++c0047rTsPCQAAALBOGzBn7utTenamWk3/OXOzYMTwngsMAIA+pdidO7viiityww035Oyzz87dd9+darXatm6//fbLvffe252HAwAAAFjnFSqVlT+vr1BIsVzpmYAAAOiTunWk32233ZYzzjgjRx11VMrlcrt1b33rW/Pss8925+EAAAAA1nnVYnGVRvpVSt36t9kAANSZbv00OXv27Lz97W/vcF25XM7ixYu783AAAAAA67yFGwxepZF+i4YM7pmAAADok7q16Ddy5Mj8/ve/73Ddgw8+mK222qo7DwcAAACwzqs0NqZ14MAlo/06Uq2mdb2BqTQ29mxgAAD0Kd06vedHP/rRnHfeeenXr1/e8573JElefPHF/OlPf8r111+fiy++uDsPBwAAAFATmjfZKE0vvZyG+Qten+rzta+tTeuleeONejtEAABqXLcW/Q499NDMmTMnV155Zb7zne8kSU499dQMHDgwp59+et73vvd15+EAAAAAakOhkOZNNk6xpSX958xNsVxJpVTMoiGDjfADAKBbdGvRL0lOOOGEHHHEEXn44Ycza9asDBkyJLvuumvWX3/97j4UAAAAQE2pNDZmwYjhvR0GAAB9ULcX/ZKkqakpY8eOXRu7BgAAAAAAAJazxkW/22+/fbW2P/jgg9f0kAAAAAAAAMAy1rjod84557R7XSgUkiTVanWFZYmiHwAAAAAAAHS3NS76PfTQQ23/f/rpp/OZz3wmH/rQh/Lud787w4cPzyuvvJK77rord9xxR77xjW+s6eEAAAAAAACA5axx0W/99ddv+//Xvva1HHnkkfn4xz/etmzYsGEZNWpUBgwYkMsvvzzXXnvtmh4SAAAAAAAAWEaxO3f28MMPZ/vtt+9w3fbbb58///nP3Xk4AAAAAAAAIN1c9Bs6dGjuvPPODtf97Gc/y9ChQ7vzcAAAAAAAAEC6YXrPZZ1yyik5//zz88wzz+SAAw7IsGHDMmPGjNxzzz156KGH8qUvfak7DwcAAAAAAACkm4t+RxxxREaMGJH//M//zGWXXZbFixenX79+2W677fLtb387++23X3ceDgAAAAAAAEg3F/2SZN99982+++6bSqWSmTNnZujQoSkWu3UWUQAAAAAAAGAZ3V70W6pYLGb48OFra/cAAAAANWfO1Nn5+8S/pnVeaxoGNWTU+O0yZOQGvR0WAAB9QLcX/X73u9/l7rvvzosvvphFixa1W1coFHLttdd29yEBAAAA1mnllnImTfhNXpj8fKrlagqFQqrVap6+Z0retPumGX3Bu1JqLPV2mAAA1LBunXfzu9/9bk466aTcd999KRQKWX/99dv9GzRo0Grt76GHHsopp5ySsWPHZtSoUbnnnnvara9Wq7niiisyduzY7LTTTvnoRz+aqVOnrnS/P/zhD7Pffvtlxx13zPjx4/PII4+sVlwAAAAAq2PShN/kuUnTksqSP4pOXvtaSZ6bNC2TJvymlyMEAKDWdetIvx/96Ec55phjcu6553bL/ubPn59Ro0blsMMOy2mnnbbC+quvvjrXX399Lrnkkmy22Wa54oorcuKJJ+bOO+9M//79O9znnXfemYsvvjgTJkzIzjvvnGuvvTYnnnhi7rrrrgwbNqxb4gYAAABYavaUWXlh8vMpljr+2+tiqZgXJj+fOVNnm+oTAIA3rFuLfrNnz87+++/fbfsbN25cxo0b1+G6arWa6667Lp/4xCdywAEHJEm++tWvZsyYMbnnnnvy/ve/v8P3ff/7388RRxyRww47LEkyYcKE/OpXv8ott9ySj3/846scW7FYSLFYWM0zoq8ovdZRK3XSYQP6NjkA6pscAPVNDuCN+Oetf08q1bYRfh2pVqr55y1/y15nj+nByFhdcgDUNzkA6lsttP1uLfrtu++++cMf/pDRo0d35247NG3atEyfPj1jxrz+YXj99dfPzjvvnIcffrjDol9LS0see+yxnHzyyW3LisVixowZk4cffni1jj90aFOXH9apD4MHD+ztEIBeJAdAfZMDoL7JAayO0uJq+vVb+fP6iuVqNtywqQciYk3JAVDf5ABgXdWtRb/DDjssX/ziF7No0aKMGTMmgwcPXmGb7bffvluONX369CRZYUrOYcOG5ZVXXunwPbNmzUq5XO7wPU899dRqHX/mzGYj/epYqVTM4MEDM3fugpTLld4OB+hhcgDUNzkA6pscwBtR7lfI4sXlrkf6VauplAqZNau5ByNjdckBUN/kAKhvS3PAuqxbi37/9m//lmTJs/auvvrqdh9mq9Ul01g8/vjj3XnIXlOpVFOpVHs7DHpZuVzJ4sV+wUO9kgOgvskBUN/kAFbHVodtkym/eDLVri6ZYiFbHraN66pGyAFQ3+QAYF3VrUW/6667rjt316URI0YkSWbMmJGNNtqobfmMGTOyzTbbdPieDTfcMKVSKTNmzGi3fMaMGRk+fPjaCxYAAACoW0NGbpBNdn9Tnp/0XIodPAumUq7kzXttliEjN+j54AAA6DO6tei35557dufuurTZZptlxIgRmTRpUrbddtskybx58/LnP/85H/7whzt8T2NjY7bffvtMmjQpBxxwQJKkUqlk0qRJOeaYY3osdgAAAKC+jLlgXCZN+E1emPx8quUlsyFVq9UUSoW8ea/NMvr8d/V2iAAA1LhuLfp1t+bm5jzzzDNtr6dNm5bHH388Q4YMyaabbprjjjsu//f//t9svvnm2WyzzXLFFVdko402aivoJcnxxx+fAw88sK2od8IJJ+Tss8/ODjvskJ122inXXnttFixYkEMPPbTHzw8AAACoD6XGUsZetG/mTJ2dJyY+npbmljQ2NWbr8dsa4QcAQLdY46LfQQcdtMrbFgqF3HHHHau8/aOPPprjjjuu7fXFF1+cJDnkkENyySWX5GMf+1gWLFiQ888/P3Pnzs1uu+2W7373u+nfv3/be5599tnMmjWr7fX73ve+zJw5M9/85jczffr0bLvttvnud79rek8AAABgrRsycoPscdbo3g4DAIA+qFCtVqtrsoNzzjknhUJhlbdfWrirddOnv9rbIdCL+vUrZsMNmzJrVrOH9kIdkgOgvskBUN/kAKhvcgDUNzkA6tvSHLAuW+ORfpdcckl3xAEAAAAAAAC8QcXeDgAAAAAAAABYM4p+AAAAAAAAUOMU/QAAAAAAAKDGKfoBAAAAAABAjVP0AwAAAAAAgBqn6AcAAAAAAAA1rt+a7uDCCy9cre3PPffcNT0kAAAAAAAAsIw1Lvrde++9q7xtoVBQ9AMAAAAAAIBu1qNFPwAAAAAAAKD7rXHRDwAAgPo0dWohEyc2ZN68QgYNqmb8+NaMHFnt7bAAAADq0lop+j399NOZOnVqFi1atMK6f/3Xf10bhwQAAKCHtLQkEyY0ZvLkUsrlQgqFpFpN7rmnlN13L+eCC1rS2NjbUQIAANSXbi36zZs3L6eeemoefPDBJEm1uuQvPAuFQts2jz/+eHceEgAAgB42YUJjJk3ql1IpWdrdKxSSSqWQSZP6ZcKE5KKLWno3SAAAgDpT7M6dXXbZZXnllVfywx/+MNVqNVdddVWuv/76HH744dlss81y0003defhAAAA6GFTphQyeXIppVLH60ulZPLkUqZOLXS8AQAAAGtFtxb9fvvb3+aUU07JzjvvnCTZaKONsscee+TLX/5y9t9//3z/+9/vzsMBAADQw26+uSHlctcFvXJ5ybP+AAAA6DndWvSbOXNm3vSmN6VUKmXgwIGZPXt227px48blt7/9bXceDgAAgB42b14hhZUM4isUkuZmI/0AAAB6UrcW/TbZZJPMmjUrSTJy5Mjce++9besefvjh9O/fvzsPBwAAQA8bNKia1x7f3qlqNWlqWslGAAAAdKt+3bmzvffeO/fdd18OPPDAHH/88TnnnHPyyCOPpKGhIY888khOOOGE7jwcAAAAPWz8+Nbcc08plUrnI/lKpWrGj2/twagAAADo1qLfZz/72SxYsCBJcvDBB6epqSl33XVXFi1alPPOOy9HHXVUdx4OAACAHjZyZDW7717OpEn9UiqtuL5cTvbaq5yRI430AwAA6EndWvQbOHBgBg4c2Pb6wAMPzIEHHtidhwAAAKCXXXBBSyZMSCZPLqVcXvKMv2p1yQi/vfYq5/zzW3o7RAAAgLrTrUW/Zc2YMSOLFi1aYfmmm266tg4JAABAD2hsTC66qCVTpxYycWJDmpsLaWpaMqWnEX4AAAC9o1uLfrNmzcqFF16YX/ziF1m8eHG7ddVqNYVCIY8//nh3HhIAAIBeMnJkNWedZVQfAADAuqBbi37nnntuHnrooZx88sl5+9vfnoaGhu7cPQAAAAAAANCBbi36PfDAAzn33HNz8MEHd+duAQAAAAAAgC4Uu3NngwcPzoYbbtiduwQAAAAAAABWoluLfieeeGKuv/76FZ7nBwAAAAAAAKw93Tq951NPPZUnn3wyBx54YPbYY48MHjx4hW3OPffc7jwkAAAAAAAA1L1uLfr98pe/TKFQSJJMnjx5hfWFQkHRDwAAAAAAALpZtxb97r333u7cHQAAAAAAALAKuvWZfgAAAAAAAEDP69aRfrfffnun6wqFQtZff/1ss8022XTTTbvzsAAAAAAAAFDXurXod84557Q9069arbYtX3ZZoVDIAQcckK9+9asZOHBgdx4eAAAAAAAA6lK3Fv1uu+22nH766Tn44IOz//77Z9iwYZkxY0b+53/+Jz/5yU8yYcKETJs2LZdcckm+9rWv5dxzz+3OwwMAANCDilOnZMDEG1OYNy/VQYOycPxRqYzcorfDAgAAqEvdWvS7/PLLM378+Jx00klty4YNG5att946jY2N+c///M9ce+21mTVrVm644QZFPwAAgFrU0pKmCeelYfIDSbmSFApJtZrGe+5O6+57pfmCLyeNjb0dJQAAQF0pdufO/vCHP2TbbbftcN12222XP//5z0mSnXbaKTNnzuzOQwMAANBDmiacl4ZJv08q1SUFv2TJ10o1DZN+n6YJ5/VugAAAAHWoW4t+Q4cOzd13393hurvuuitDhw5NkjQ3N2fw4MHdeWgAAAB6QHHKU0tG+JVKHW9QKqVh8gMpTp3Ss4EBAADUuW6d3vPjH/94vvjFL2batGnZd999M3To0MycOTP/+7//m/vvvz8TJkxIktx///3ZaaeduvPQAAAA9IABN9/0+pSenSlX0n/ijVlw1ud7LjAAAIA6161Fv6OOOiojRozIf/7nf+bSSy/N4sWL069fv2y77bb59re/nf322y9Jctppp6Vfv249NAAAAD2gMG9e1wW/JCkUUmxu7pmAAAAASNLNRb8k2X///bP//vunUqlk5syZGTp0aIrF9rOIDhkypLsPCwAAQA+oDhqUVKtdF/6q1VSamnouKAAAALr3mX7tdlwsZvjw4SsU/AAAAKhdC8cflZRW0s8rFbNo/FE9ExAAAABJumGk34UXXph/+7d/y6abbpoLL7xwpdufe+65a3pIAAAAekll5BZp3X3PNEy6LymVVtygXE7rXnunMnKLng8OAACgjq1x0e/ee+/N4Ycfnk033TT33ntvl9sWCgVFPwAAgBrXfMGFaZpwXhomP5CUK0um+qxWk1IxrXvtnebzv9zbIQIAANSdbin6dfR/AAAA+qjGxjRfdGmKU6ek/8QbU2xuTqWpKYvGH2WEHwAAQC9Z46IfAAAA9akycossOOvzvR0GAAAA6Yai38yZM/Pyyy9nm222abf8b3/7W7797W/nySefzPDhw3P88cdnv/32W9PDrWC//fbLc889t8Lyj3zkI7ngggtWWH7rrbfm859v3yltbGzMX/7yl26PDQAAAAAAAHrCGhf9vv71r+exxx7Lbbfd1rbsueeey9FHH52FCxdm1KhR+cc//pHTTjst1157bfbYY481PWQ7N998c8rlctvrf/zjHznhhBPynve8p9P3DBo0KHfddVfb60Kh0K0xAQAAAAAAQE9a46LfH//4xxx++OHtlv3gBz/I/Pnzc/XVV2fs2LFZuHBhTjjhhFx99dXdXvQbOnRou9f/7//9v7z1rW/Nnnvu2el7CoVCRowY0a1xAAAAAAAAQG9Z46LfSy+9lK222qrdsl/+8pfZdtttM3bs2CTJgAEDcswxx+SrX/3qmh6uSy0tLbnjjjtywgkndDl6b/78+dl3331TqVSy3Xbb5YwzzljhHFamWCykWDRCsF6VSsV2X4H6IgdAfZMDoL7JAVDf5ACob3IA1LdaaPtrXPQrFArtCmyvvPJKpk2bluOPP77ddhtvvHFmzZq1pofr0j333JNXX301hxxySKfbbLHFFvnKV76SUaNG5dVXX833vve9HHXUUfnZz36WTTbZZJWPNXRok2lByeDBA3s7BKAXyQFQ3+QAqG9yANQ3OQDqmxwArKvWuOi3xRZb5L777msb1ffLX/4yhUIhe++9d7vtpk+fvsJUnN3tlltuybve9a5svPHGnW6z6667Ztddd233+n3ve19uvPHGnH766at8rJkzm430q2OlUjGDBw/M3LkLUi5XejscoIfJAVDf5ACob3IA1Dc5AOqbHAD1bWkOWJetcdHv2GOPzdlnn525c+dm+PDh+a//+q+89a1vzZgxY9pt97vf/S5bb731mh6uU88991zuu+++XHnllav1voaGhmy77bZ55plnVut9lUo1lUp1td5D31MuV7J4sV/wUK/kAKhvcgDUNzkA6pscAPVNDgDWVWtc9PvgBz+Yl156KTfccEPmzp2b7bffPhdccEH69Xt91zNmzMgvf/nLfOpTn1rTw3Xq1ltvzbBhw/Iv//Ivq/W+crmcJ554IuPGjVs7gQEAAAAAAMBatsZFvyT52Mc+lo997GOdrh82bFjuu+++7jhUhyqVSm699dYcfPDB7YqNSfK5z30uG2+8cc4888wkyVVXXZVddtklm2++eebOnZtrrrkmzz//fMaPH7/W4gMAAAAAAIC1qVuKfr3tvvvuy/PPP5/DDjtshXUvvPBCisVi2+u5c+fmvPPOy/Tp0zNkyJBsv/32ufHGG7Plllv2ZMgAAAAAAADQbQrVatWD6d6A6dNf7e0Q6EX9+hWz4YZNmTWr2fzdUIfkAKhvcgB9xZyps/P3iX9N67zWNAxqyKjx22XIyA16O6x1nhwA9U0OgPomB0B9W5oD1mV9YqQfAAAAq6bcUs6kCb/JC5OfT7VcTaFQSLVazdP3TMmbdt80oy94V0qNpd4OEwAAgNVUXPkmAAAA9BWTJvwmz02allSSQqGQ5LWvleS5SdMyacJvejlCAAAA3ghFPwAAgDoxe8qsvDD5+RRLHXcFi6ViXpj8fOZMnd2zgQEAALDGFP0AAADqxBM3P55quevHulfL1Twx8fEeiggAAIDuougHAABQJ1rntbZN6dmZQqGQluaWHooIAACA7qLoBwAAUCcaBjWkWl3JSL9qNY1NjT0UEQAAAN1F0Q8AAKBOjBq/XQqllYz0KxWy9fhteygiAAAAuouiHwAAQJ0YMnKDbLL7m1IpVzpcXylX8qY9Ns2QkRv0bGAAAACsMUU/AACAOjLmgnF58+jNkmLapvqsVqtJMXnzmM0y+vx39XKEAAAAvBH9ejsAAAAAek6psZSxF+2bOVNn54mJj6eluSWNTY3Zevy2RvgBAADUMEU/AACAOjRk5AbZ46zRvR0GAAAA3cT0ngAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxvXr7QAAAADoecWWlgyYPTeFSiXVYjELNxicSmNjb4cFAADAG6ToBwAAUE+q1TS99HIa5i9IqtWkUEiq1TTOm5fW9QameeONliwDAACgppjeEwAAoI40vfRyGprnL3mxtLj32teG5vlpeunlXooMAACANaHoBwAAUCeKi1qWjPDrbCRfoZCG+QtSbGnp2cAAAABYY4p+AAAAdWLAnLlLpvTsSrWa/nPm9kxAAAAAdBtFPwAAgDpRqFRW/ry+QiHFcqVnAgIAAKDbKPoBAADUiWqxuEoj/SolXUUAAIBaoycHAABQJxZuMHiVRvotGjK4ZwICAACg2yj6AQAA1IlKY2NaBw7sfLRftZrW9Qam0tjYs4EBAACwxhT9AAAA6kjzJhultWm9JS+WFv9e+9ratF6aN96olyIDAABgTfTr7QAAAADoQYVCmjfZOMWWlvSfMzfFciWVUjGLhgw2wg8AAKCGKfoBAADUoUpjYxaMGN7bYQAAANBNTO8JAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGpcv94OAAAAoFYVp07JgIk3pjBvXqqDBmXh+KNSGblFb4cFAABAHar5ot+VV16Zq666qt2yLbbYInfddVen7/n5z3+eK664Is8991xGjhyZz372sxk3btzaDhUAAOgrWlrSNOG8NEx+IClXkkIhqVbTeM/dad19rzRf8OWksbG3owQAAKCO9InpPbfaaqv87ne/a/v3ox/9qNNt//jHP+bMM8/M4Ycfnttvvz37779/Tj311DzxxBM9GDEAAFDLmiacl4ZJv08q1SUFv2TJ10o1DZN+n6YJ5/VugAAAANSdPlH0K5VKGTFiRNu/oUOHdrrtddddl3322ScnnXRS3v72t+f000/PdtttlxtuuKEHIwYAAGpVccpTS0b4lUodb1AqpWHyAylOndKzgQEAAFDXan56zyR5+umnM3bs2PTv3z+77LJLzjzzzGy66aYdbvunP/0pH/3oR9stGzt2bO65557VOmaxWEixWHijIVPjSqViu69AfZEDoL7JAQy49aYUKpXXR/h1pFLJwFtuyqKz/73nAqNHyAFQ3+QAqG9yANS3Wmj7NV/022mnnXLxxRdniy22yPTp0/Otb30rRx99dH76059m0KBBK2z/yiuvZPjw4e2WDRs2LK+88spqHXfo0KYUuurkUxcGDx7Y2yEAvUgOgPomB9SxxS1Jv05G+S2jX7kl623Y1AMB0RvkAKhvcgDUNzkAWFfVfNFv3Lhxbf/fZpttsvPOO2fffffNz3/+84wfP36tHXfmzGYj/epYqVTM4MEDM3fugpTLld4OB+hhcgDUNzmAAf0a07C43PVIv2o1LaXGLJrV3HOB0SPkAKhvcgDUNzkA6tvSHLAuq/mi3/IGDx6ckSNH5plnnulw/fDhw1cY1TdjxowVRv+tTKVSTaVSfcNx0jeUy5UsXuwXPNQrOQDqmxxQv+YfdlQG/+LupKv+QLGYBYcdmYprpM+SA6C+yQFQ3+QAYF217k9Aupqam5vz7LPPZsSIER2u32WXXXL//fe3W3bfffdll1126YHoAACAWlcZuUVad98zKZc73qBcTusee6UycoueDQwAAIC6VvNFv0svvTQPPvhgpk2blj/+8Y857bTTUiwW84EPfCBJ8rnPfS5f+9rX2rY/7rjj8tvf/jbf+9738uSTT+bKK6/Mo48+mmOOOaa3TgEAAKgxzRdcmNbReyfFQlJ9bcRftZoUC2kds3eaz/9y7wYIAABA3an56T1ffPHFnHHGGZk9e3aGDh2a3XbbLT/+8Y8zdOjQJMkLL7yQYvH12uY73vGOXH755fnGN76Rr3/96xk5cmS+9a1vZeutt+6tUwAAAGpNY2OaL7o0xalT0n/ijSk2N6fS1JRF448ywg8AAIBeUahWqx5M9wZMn/5qb4dAL+rXr5gNN2zKrFnN5u+GOiQHQH2TA6C+yQFQ3+QAqG9yANS3pTlgXVbz03sCAAAAAABAvVP0AwAAAAAAgBqn6AcAAAAAAAA1TtEPAAAAAAAAapyiHwAAAAAAANQ4RT8AAAAAAACocYp+AAAAAAAAUOMU/QAAAAAAAKDGKfoBAAAAAABAjVP0AwAAAAAAgBrXr7cDAAAAqFVTpxYycWJD5s0rZNCgasaPb83IkdXeDgsAAIA6pOgHAACwmlpakgkTGjN5cinlciGFQlKtJvfcU8ruu5dzwQUtaWzs7SgBAACoJ6b3BAAAWE0TJjRm0qR+qVSWFPySpFBIKpVCJk3qlwkTVPwAAADoWYp+AAAAq2HKlEImTy6lVOp4famUTJ5cytSphZ4NDAAAgLqm6AcAALAabr65IeVy1wW9cnnJs/4AAACgpyj6AQAArIZ5816f0rMzhULS3GykHwAAAD1H0Q8AAGA1DBpUTbXa9TbVatLUtJKNAAAAoBsp+gEAAKyG8eNbUyp1XdArlaoZP761hyICAAAART8AAIDVMnJkNbvvXk653PH6cjnZY49yRo400g8AAICeo+gHAACwmi64oCWjRy9Osfj6VJ/ValIsVjNmzOKcf35L7wYIAABA3enX2wEAAADUmsbG5KKLWjJ1aiETJzakubmQpqYlU3oa4QcAAEBvUPQDAAB4g0aOrOass4zqAwAAoPeZ3hMAAAAAAABqnKIfAAAAAAAA1DhFPwAAAAAAAKhxin4AAAAAAABQ4xT9AAAAAAAAoMYp+gEAAAAAAECNU/QDAAAAAACAGqfoBwAAAAAAADVO0Q8AAAAAAABqnKIfAAAAAAAA1Lh+vR0AAAD0FXOmzs7fJ/41rfNa0zCoIaPGb5chIzfo7bAAAACAOqDoBwAAa6jcUs6kCb/JC5OfT7VcTaFQSLVazdP3TMmbdt80oy94V0qNpd4OEwAAAOjDTO8JAABraNKE3+S5SdOSSlIoFJK89rWSPDdpWiZN+E0vRwgAAAD0dYp+AACwBmZPmZUXJj+fYqnjj9bFUjEvTH4+c6bO7tnAAAAAgLqi6AcAAGvgiZsfT7Vc7XKbarmaJyY+3kMRAQAAAPVI0Q8AANZA67zWtik9O1MoFNLS3NJDEQEAAAD1SNEPAADWQMOghlSrKxnpV62msamxhyICAAAA6pGiHwAArIFR47dLobSSkX6lQrYev20PRQQAAADUI0U/AABYA0NGbpBNdn9TKuVKh+sr5UretMemGTJyg54NDAAAAKgrin4AALCGxlwwLm8evVlSTNtUn9VqNSkmbx6zWUaf/65ejhAAAADo6/r1dgAAAFDrSo2ljL1o38yZOjtPTHw8Lc0taWxqzNbjtzXCDwAAAOgRin4AANBNhozcIHucNbq3wwAAAADqUM0X/b7zne/kF7/4RZ566qkMGDAgu+66az772c/mbW97W6fvufXWW/P5z3++3bLGxsb85S9/WdvhAgAAAAAAQLer+aLfgw8+mKOPPjo77rhjyuVyvv71r+fEE0/Mz372s6y33nqdvm/QoEG566672l4XCoWeCBcAAAAAAAC6Xc0X/a655pp2ry+55JKMHj06jz32WPbYY49O31coFDJixIi1HR4AAAAAAACsdTVf9Fveq6++miQZMmRIl9vNnz8/++67byqVSrbbbrucccYZ2WqrrVb5OMViIcWi0YH1qlQqtvsK1Bc5AOqbHAD1TQ6A+iYHQH2TA6C+1ULbL1Sr1WpvB9FdKpVKPvGJT2Tu3Ln5r//6r063e/jhh/P0009n1KhRefXVV/O9730vDz30UH72s59lk002WaVjVatVU4ICAAAAAACwTuhTRb8LLrggv/3tb/OjH/1olYt3SdLa2pr3ve99ef/735/TTz99ld4zY8Y8I/3qWKlUzODBAzN37oKUy5XeDgfoYXIA1Dc5AOqbHAD1TQ6A+iYHQH1bmgPWZX1mes8vfelL+dWvfpUbbrhhtQp+SdLQ0JBtt902zzzzzCq/p1KpplLpM/VS3qByuZLFi/2Ch3olB0B9kwOgvskBUN/kAKhvcgCwrlr3JyBdiWq1mi996Uv5n//5n1x77bV5y1vestr7KJfLeeKJJzJixIi1ECEAAAAAAACsXTU/0m/ChAn57//+73z7299OU1NTpk+fniRZf/31M2DAgCTJ5z73uWy88cY588wzkyRXXXVVdtlll2y++eaZO3durrnmmjz//PMZP358r50HAAAAAAAAvFE1X/T7r//6ryTJscce2275xRdfnEMPPTRJ8sILL6RYfH1Q49y5c3Peeedl+vTpGTJkSLbffvvceOON2XLLLXsucAAAAAAAAOgmhWq16sF0b8D06a/2dgj0on79itlww6bMmtVs/m6oQ3IA1LeuckCxpSUDZs9NoVJJtVjMwg0Gp9LY2EuRAmuDzwFQ3+QAqG9yANS3pTlgXVbzI/0AAKDXVatpeunlNMxfkFSrSaGQVKtpnDcvresNTPPGGy1ZBgAAALCWFFe+CQAA0JWml15OQ/P8JS+WFvde+9rQPD9NL73cS5EBAAAA9ULRDwAA1kBxUcuSEX6djeQrFNIwf0GKLS09GxgAAABQVxT9AABgDQyYM3fJlJ5dqVbTf87cngkIAAAAqEuKfgAAsAYKlcrKn9dXKKRYrvRMQAAAAEBdUvQDAIA1UC0WV2mkX6XkozcAAACw9rjzAAAAa2DhBoNXaaTfoiGDeyYgAAAAoC4p+gEAwBqoNDamdeDAzkf7VatpXW9gKo2NPRsYAAAAUFcU/QAAYA01b7JRWpvWW/JiafHvta+tTeuleeONeikyAAAAoF706+0AAACg5hUKad5k4xRbWtJ/ztwUy5VUSsUsGjLYCD8AAACgRyj6AQBAN6k0NmbBiOG9HQYAAABQh0zvCQAAAAAAADVO0Q8AAAAAAABqnKIfAAAAAAAA1DhFPwAAAAAAAKhxin4AAAAAAABQ4xT9AAAAAAAAoMYp+gEAAAAAAECNU/QDAAAAAACAGqfoBwAAAAAAADVO0Q8AAAAAAABqXL/eDgAAgO5XnDolAybemMK8eakOGpSF449KZeQWvR0WAAAAAGuJoh8AQF/S0pKmCeelYfIDSbmSFApJtZrGe+5O6+57pfmCLyeNjb0dJQAAAADdzPSeAAB9SNOE89Iw6fdJpbqk4Jcs+VqppmHS79M04bzeDRAAAACAtULRDwCgjyhOeWrJCL9SqeMNSqU0TH4gxalTejYwAAAAANY6RT8AgD5iwM03LZnSsyvlSvpPvLFnAgIAAACgxyj6AQD0EYV5816f0rPTjQopNjf3TEAAAAAA9BhFPwCAPqI6aFBSra5ko2oqTU09ExAAAAAAPUbRDwCgj1g4/qiktJKPd6ViFo0/qmcCAgAAAKDHKPoBAPQRlZFbpHX3PZNyueMNyuW07rFXKiO36NnAAAAAAFjrFP0AAPqQ5gsuTOvovZNi4fWpPqvVpFhI65i903z+l3s3QAAAAADWin69HQAAAN2osTHNF12a4tQp6T/xxhSbm1Npasqi8UcZ4QcAAADQhyn6AQD0QZWRW2TBWZ/v7TAAAAAA6CGm9wQAAAAAAIAap+gHAAAAAAAANU7RDwAAAAAAAGqcoh8AAAAAAADUOEU/AAAAAAAAqHGKfgAAAAAAAFDjFP0AAAAAAACgxin6AQAAAAAAQI1T9AMAAAAAAIAap+gHAAAAAAAANa5fbwcAAED3mzq1kIkTGzJvXiGDBlUzfnxrRo6s9nZYAAAAAKwlfWak3w9/+MPst99+2XHHHTN+/Pg88sgjXW7/85//PO95z3uy44475qCDDsqvf/3rHooUAGDtaWlJvvCFxpx88oDcfXe/3HdfKXff3S8nnzwgX/hCY1paejtCAAAAANaGPlH0u/POO3PxxRfn1FNPzW233ZZtttkmJ554YmbMmNHh9n/84x9z5pln5vDDD8/tt9+e/fffP6eeemqeeOKJHo4cAKB7TZjQmEmT+qVSKaRQWLKsUEgqlUImTeqXCRMaezdAAAAAANaKPlH0+/73v58jjjgihx12WLbccstMmDAhAwYMyC233NLh9tddd1322WefnHTSSXn729+e008/Pdttt11uuOGGHo4cAKD7TJlSyOTJpZRKHa8vlZLJk0uZOrXQs4EBAAAAsNbV/DP9Wlpa8thjj+Xkk09uW1YsFjNmzJg8/PDDHb7nT3/6Uz760Y+2WzZ27Njcc889q3zcYrGQYtENs3pVKhXbfQXqixzAuurWWxvajfDrSKVSyC23NObss1t7LrA+Rg6A+iYHQH2TA6C+yQFQ32qh7dd80W/WrFkpl8sZNmxYu+XDhg3LU0891eF7XnnllQwfPnyF7V955ZVVPu7QoU0pdHVHjbowePDA3g4B6EVyAOuaxYuTfqvw6a5cLmXDDU3zuabkAKhvcgDUNzkA6pscAKyrar7o11tmzmw20q+OlUrFDB48MHPnLki5XOntcIAeJgewrurXryGLF5e6HOlXrSalUjmzZhnp90bJAVDf5ACob3IA1Dc5AOrb0hywLqv5ot+GG26YUqmUGTNmtFs+Y8aMFUbzLTV8+PAVRvV1tX1HKpVqKpXq6gdMn1IuV7J4sV/wUK/kANY1hx3Wkl/8YkAqlc6rfsViNYcd1pLFi32OWVNyANQ3OQDqmxwA9U0OANZV6/4EpCvR2NiY7bffPpMmTWpbVqlUMmnSpOy6664dvmeXXXbJ/fff327Zfffdl1122WVthgoAsFaNHFnN7ruXUy53vL5cTvbYo5yRIxX8AAAAAPqami/6JckJJ5yQH//4x7ntttvy5JNP5otf/GIWLFiQQw89NEnyuc99Ll/72tfatj/uuOPy29/+Nt/73vfy5JNP5sorr8yjjz6aY445prdOAQCgW1xwQUtGj16cYrGa6mu1vWr1/7d350FVlX8cxz+AuOOo4FaO4oZKIFesVLr+HMhJzX1BnDEoxwW3lBEVcMk9NDUd0GYsNM10rDBNJ5epqewPRSfBxK1cG3evSGqOIuD5/dFwk0hCQOmc+37N8Md57uF7n/PM8JnR732e++cOv5CQPL3zzoOKnSAAAAAAAACeCtMf7ylJr7/+um7evKmkpCQ5HA61bdtWKSkpzuM6r1y5Inf3v/qbwcHBWrp0qVasWKH3339fvr6+WrVqlfz8/CrqEQAAAMpF5crSwoUPdP68m774wlN377qpRg1D4eG57PADAAAAAACwMDfDMPjfn1JwOO5U9BRQgSpVcledOjWUnX2X87sBF0QGAK6NDABcGxkAuDYyAHBtZADg2goy4L/MEsd7AgAAAAAAAAAAAK6Mph8AAAAAAAAAAABgcjT9AAAAAAAAAAAAAJOj6QcAAAAAAAAAAACYHE0/AAAAAAAAAAAAwORo+gEAAAAAAAAAAAAmR9MPAAAAAAAAAAAAMDmafgAAAAAAAAAAAIDJ0fQDAAAAAAAAAAAATI6mHwAAAAAAAAAAAGByNP0AAAAAAAAAAAAAk6PpBwAAAAAAAAAAAJgcTT8AAAAAAAAAAADA5Gj6AQAAAAAAAAAAACbnZhiGUdGTAAAAAAAAAAAAAFB67PQDAAAAAAAAAAAATI6mHwAAAAAAAAAAAGByNP0AAAAAAAAAAAAAk6PpBwAAAAAAAAAAAJgcTT8AAAAAAAAAAADA5Gj6AQAAAAAAAAAAACZH0w8AAAAAAAAAAAAwOZp+AAAAAAAAAAAAgMnR9AMAAAAAAAAAAABMjqYfAAAAAAAAAAAAYHI0/WAJGzduVFhYmAIDAxUeHq4jR44UuScjI0NRUVGy2WwKDg7WsGHDdP/+/WLrXr58WaNHj1ZQUJA6d+6sxYsXKy8vz/n6gQMH1Lp16yI/DofjsTVzcnIUHx+vPn36yN/fX+PGjSt2DocOHZK/v7/69ev3L6sAuC6rZUBp6gKuzGoZIEkPHjzQ8uXLFRoaqoCAAIWFhSk1NbWEKwK4FqtlQHx8/D/W7dWr1xOsCuA6rJYBkrR9+3b17dtXQUFBstvtSkhIUHZ2dglXBHAtVsyAjRs3qmfPnmrXrp26d++ubdu2lWwxABdkpgw4cOCAxo4dK7vdLpvNpn79+mn79u1F7tu1a5d69OihwMBA9enTR3v37n2CFZEqPdHdwH/Qzp07lZiYqLlz5yooKEjr16/XiBEjtHv3bnl7e0v68w975MiRio6O1qxZs+Th4aGTJ0/K3f3xfe/8/HxFR0fLx8dHmzdv1vXr1xUXFydPT09Nnjy50L27d+9WzZo1ndcF7/u4ulWqVFFkZKT27NlT7LPdvn1bcXFx6ty5s27cuFGS5QBcjpUz4EnqAq7KqhkwadIkZWVlaeHChWrSpIkcDocePnxY0mUBXIYVM2DGjBmKjY0t9Dv9+vVTjx49SrQmgCuxYgYcOnRIcXFxSkhIUGhoqK5du6Y5c+Zo1qxZWrly5ZMsD2B5VsyATZs2admyZVqwYIECAwN15MgRzZw5U7Vq1VJYWNiTLA9geWbLgIyMDLVu3VqjRo2Sj4+Pvv/+e8XFxcnLy0uhoaGSpPT0dMXGxmry5MkKDQ3Vjh07NH78eH355Zfy8/Mr2cIYgMkNHjzYmDt3rvM6Pz/fsNvtxurVq51j4eHhxvLly5+o7g8//GC0adPGcDgczrFNmzYZwcHBRk5OjmEYhpGWlmb4+fkZt27dKtXc4+LijLFjxz729ZiYGGP58uVGUlKS0bdv31K9B2B1VsyAstYFXIkVM2Dv3r1Ghw4djOzs7FLVBVyJFTPg77755hujdevWxsWLF0v1PoCVWTEDUlJSjFdffbXQ2CeffGJ06dKlVO8DWJkVMyAiIsJYtGhRobHExERj6NChpXofwMrMnAEFRo0aZcTHxzuvJ02aZIwePbrQPeHh4casWbNKXJPjPWFqDx480LFjxxQSEuIcc3d3V0hIiDIyMiRJWVlZ+vnnn+Xt7a2hQ4cqJCREb7zxhn766adiax8+fFh+fn7y8fFxjtntdv3xxx86ffp0oXv79+8vu92u4cOH69ChQ+XybFu2bNGFCxc0YcKEcqkHWJGVM+Bp1gWswqoZ8N133ykgIEApKSnq0qWLunfvrsWLF//r8SOAq7FqBvxdamqqQkJC9Pzzz5d7bcDMrJoBNptNV69e1d69e2UYhm7cuKE9e/aoa9euZa4NWIlVM+DBgweqUqVKobEqVaooMzNTubm5Za4PWIVVMuDOnTuqXbt2offu3LlzoXvsdrsOHz5c4po0/WBq2dnZys/PL7Jt1tvb23kc5oULFyRJK1euVHh4uFJSUuTv76+33npL58+ff2ztGzduFPrDluS8Ljibt169epo7d66SkpKUlJSkhg0bKioqSseOHSvTc50/f17Lli3TkiVLVKkSp/ACj2PVDHhadQGrsWoGXLhwQYcOHdKpU6e0atUqTZ8+XXv27NHcuXPLVBewGqtmwKOuXbumH3/8UYMHDy63moBVWDUDOnTooCVLligmJkYBAQF65ZVXVLNmTb3zzjtlqgtYjVUzwG63KzU1VUePHpVhGMrMzFRqaqpyc3P5bk/gEVbIgJ07dyozM1MDBw4s9r0ffaaSoJsAyyv4/puIiAgNGjRIkuTv76/9+/dry5Ytio2N1ciRI52d+Oeee05ff/11iWo3b95czZs3d14HBwfrwoULWrdunZYsWVKq+ebn5ys2NlZvv/22mjVrVqoaAP5itgx4mnUBV2TGDDAMQ25ublq6dKm8vLwkSfHx8Zo4caJmz56tqlWrlro24GrMmAGP2rZtm7y8vNStW7dyqQe4GjNmwOnTp7Vw4UKNHz9edrtdDodD7733nmbPnq1333231HUBV2TGDBg3bpwcDociIiJkGIa8vb3Vv39/paSkFPsdZACK+i9nQFpamqZPn64FCxaoVatWT/poxaLpB1OrU6eOPDw8lJWVVWg8KyvL2RGvV6+eJKlFixaF7mnRooUuX74sSVq4cKHzyKyCnXU+Pj46cuRIod8p6KgX1PwngYGBSk9PL+0j6e7duzp69KhOnDih+fPnS/ozoAzDkL+/v9asWVNkiy/gqqyYAc+6LmBmVs2AevXqqUGDBs6GX8F8DcPQ1atX5evrW6b6gFVYNQMKGIahLVu2qF+/fqpcuXK51ASsxKoZsHr1agUHB2vkyJGSpDZt2qhatWoaNmyYYmJiVL9+/TLVB6zCqhlQtWpVJSYmat68ecrKylK9evX02WefqUaNGqpbt26ZagNWYuYMOHjwoMaOHauEhAT179+/0Gs+Pj5FdvU9+kwlwccDYGqVK1fWCy+8oP379zvHHj58qP3796t9+/aSpMaNG6t+/fo6d+5cod89f/6883sxGjRooKZNm6pp06bOMZvNpl9//bVQcOzbt081a9ZUy5YtHzunkydPFvvH/29q1qypHTt2aNu2bc6foUOHqlmzZtq2bZuCgoJKXRuwGitmwLOuC5iZVTMgODhY169f1927d51j586dk7u7uxo2bFim2oCVWDUDChw8eFC//fYbR3sCj2HVDLh//36R3TweHh6S/vwwAIA/WTUDCnh6eqphw4by8PDQzp07FRoayk4/4BFmzYADBw4oOjpaU6ZMUURERJHXbTab0tLSCo3t27dPNput2LqPYqcfTG/48OGKi4tTQECA2rVrp/Xr1+vevXvOs3Dd3Nw0YsQIJScnq02bNmrbtq22bt2qs2fPKikp6bF17Xa7WrZsqWnTpmnq1KlyOBxasWKFhg0b5vyk7bp169S4cWO1atVKOTk5+uKLL5SWlqa1a9cWO+fTp08rNzdXv//+u+7evasTJ05Iktq2bSt3d3f5+fkVut/b21tVqlQpMg7AehlQlrqAK7JiBvTu3VsffPCBEhISNHHiRGVnZ2vJkiUaNGgQR3sCf2PFDCiQmpqqoKAg/g0AFMOKGRAaGqpZs2Zp06ZN6tKli65fv653331X7dq1U4MGDcpj2QDLsGIGnDt3TkeOHFFQUJBu376tjz/+WKdOndKiRYvKY8kASzFbBqSlpWnMmDGKiorSa6+95vx+QE9PT9WuXVuSFBUVpcjISK1du1Zdu3bVzp07dfToUc2bN6/E6+Jm8DEhWMCnn36qNWvWyOFwqG3btpo5c2aRHXEffvihNm7cqFu3bqlNmzaaMmWKXnzxxWLrXrp0SXPmzNHBgwdVrVo1DRgwQLGxsc6tvh999JE+//xzXbt2TdWqVZOfn5/Gjx+vTp06FVs3LCxMly5dKjL+yy+//OP9ycnJ+vbbb/XVV18VWxdwVVbLgNLWBVyV1TJAks6cOaMFCxYoPT1dtWvXVs+ePRUTE0PTD/gHVsyAO3fuyG63a8aMGRoyZEhJlwJwSVbMgA0bNmjz5s26ePGivLy81KlTJ02dOpWmH/APrJYBZ86cUWxsrM6dO6dKlSqpY8eOmjJlSqHvDgPwFzNlQHx8vLZu3Vpk/OWXX9aGDRuc17t27dKKFSt06dIl+fr6aurUqeratWuJ14SmHwAAAAAAAAAAAGByHAQMAAAAAAAAAAAAmBxNPwAAAAAAAAAAAMDkaPoBAAAAAAAAAAAAJkfTDwAAAAAAAAAAADA5mn4AAAAAAAAAAACAydH0AwAAAAAAAAAAAEyOph8AAAAAAAAAAABgcjT9AAAAAAAAAAAAAJOrVNETAAAAAAA8fa1bt/7XexITE7V161ZVr15dq1evfgazAgAAAACUFzfDMIyKngQAAAAA4Ok6fPhwoeuIiAhFRkaqd+/ezrEmTZro5s2bcnd3V/PmzZ/xDAEAAAAAZcFOPwAAAABwATabrchYo0aNiozXrVv32UwIAAAAAFCu+E4/AAAAAIBTZGSkoqOjndfJyclq3769jh8/roiICLVr104DBgzQ8ePHlZOTo9mzZ+ull17S//73P61bt65IvYyMDEVFRclms6lDhw6KjY1VVlbWM3wiAAAAAHANNP0AAAAAAMXKzc1VXFychgwZouTkZOXl5WnChAmaMWOGqlatqhUrVqhbt25KTExUenq68/cyMjIUGRkpLy8vLV++XPPnz1dmZqbGjRtXgU8DAAAAANbE8Z4AAAAAgGLl5uZqypQp6tq1qyTp4cOHGjNmjIKCgpSQkCBJ6tSpk3bv3q3du3crODhYkrRs2TIFBARo5cqVcnNzkyT5+fmpd+/e2rt3r7MeAAAAAKDs2OkHAAAAACiWu7u7Onfu7Lz29fWVJIWEhDjHPDw81KRJE129elWSdO/ePaWnp6tHjx7Kz89XXl6e8vLy5Ovrq0aNGikzM/OZPgMAAAAAWB07/QAAAAAAxapataoqV67svPb09JQkeXl5FbrP09NTOTk5kqTbt28rPz9fiYmJSkxMLFLzypUrT3HGAAAAAOB6aPoBAAAAAMqdl5eX3NzcFB0drW7duhV5vU6dOhUwKwAAAACwLpp+AAAAAIByV716ddlsNp09e1aBgYEVPR0AAAAAsDyafgAAAACAp2LatGl68803FRMTo169eqlWrVq6evWq9u3bp4EDB6pjx44VPUUAAAAAsAyafgAAAACApyI4OFibNm1ScnKyEhISlJubq4YNG6pTp05q2rRpRU8PAAAAACzFzTAMo6InAQAAAAAAAAAAAKD03Ct6AgAAAAAAAAAAAADKhqYfAAAAAAAAAAAAYHI0/QAAAAAAAAAAAACTo+kHAAAAAAAAAAAAmBxNPwAAAAAAAAAAAMDkaPoBAAAAAAAAAAAAJkfTDwAAAAAAAAAAADA5mn4AAAAAAAAAAACAydH0AwAAAAAAAAAAAEyOph8AAAAAAAAAAABgcjT9AAAAAAAAAAAAAJP7PzKm+bC4V76qAAAAAElFTkSuQmCC",
             "text/plain": [
               "<Figure size 1800x1600 with 3 Axes>"
             ]
@@ -1051,19 +1165,37 @@
         "    print(\"Note: Sliding strategy visualization requires detailed tracking data\")\n",
         "    print(\"For full sliding window visualization, run the complete sliding analysis\")\n",
         "    \n",
+        "    # Create consistent timeline - superset of timestamps from both dataframes\n",
+        "    market_timestamps = set(pair.market_data_['tstamp'])\n",
+        "    predicted_timestamps = set(pair.predicted_df_['tstamp'])\n",
+        "    \n",
+        "    # Create superset of all timestamps\n",
+        "    all_timestamps = sorted(market_timestamps.union(predicted_timestamps))\n",
+        "    \n",
+        "    # Create a unified timeline dataframe for consistent plotting\n",
+        "    timeline_df = pd.DataFrame({'tstamp': all_timestamps})\n",
+        "    \n",
+        "    # Merge with predicted data to get dis-equilibrium values\n",
+        "    timeline_df = timeline_df.merge(pair.predicted_df_[['tstamp', 'disequilibrium', 'scaled_disequilibrium']], \n",
+        "                                   on='tstamp', how='left')\n",
+        "    \n",
+        "    print(f\"Using consistent timeline with {len(timeline_df)} timestamps\")\n",
+        "    print(f\"Timeline range: {timeline_df['tstamp'].min()} to {timeline_df['tstamp'].max()}\")\n",
+        "    \n",
         "    fig, axes = plt.subplots(3, 1, figsize=(18, 16))\n",
         "    \n",
-        "    # 2. Raw dis-equilibrium\n",
-        "    axes[0].plot(pair.predicted_df_['tstamp'], pair.predicted_df_['disequilibrium'],\n",
+        "    # 1. Raw dis-equilibrium - using consistent timeline\n",
+        "    axes[0].plot(timeline_df['tstamp'], timeline_df['disequilibrium'],\n",
         "                 color='blue', alpha=0.8, label='Dis-equilibrium', linewidth=1)\n",
         "    axes[0].axhline(y=pair.training_mu_, color='red', linestyle='--', alpha=0.7, label='Training Mean')\n",
         "    axes[0].set_title('Testing Period: Raw Dis-equilibrium')\n",
         "    axes[0].set_ylabel('Dis-equilibrium')\n",
+        "    axes[0].set_xlim(timeline_df['tstamp'].min(), timeline_df['tstamp'].max())\n",
         "    axes[0].legend()\n",
         "    axes[0].grid(True)\n",
         "    \n",
-        "    # 3. Scaled dis-equilibrium with thresholds\n",
-        "    axes[1].plot(pair.predicted_df_['tstamp'], pair.predicted_df_['scaled_disequilibrium'],\n",
+        "    # 2. Scaled dis-equilibrium with thresholds - using consistent timeline\n",
+        "    axes[1].plot(timeline_df['tstamp'], timeline_df['scaled_disequilibrium'],\n",
         "                 color='green', alpha=0.8, label='Scaled Dis-equilibrium', linewidth=1)\n",
         "    axes[1].axhline(y=pt_bt_config['dis-equilibrium_open_trshld'], color='purple',\n",
         "                    linestyle=':', alpha=0.7, label=f\"Open Threshold ({pt_bt_config['dis-equilibrium_open_trshld']})\")\n",
@@ -1074,14 +1206,13 @@
         "    axes[1].axhline(y=-pt_bt_config['dis-equilibrium_close_trshld'], color='brown',\n",
         "                    linestyle=':', alpha=0.7)\n",
         "    axes[1].axhline(y=0, color='black', linestyle='-', alpha=0.5, linewidth=0.5)\n",
-        "\n",
-        "\n",
         "    axes[1].set_title('Testing Period: Scaled Dis-equilibrium with Trading Thresholds')\n",
         "    axes[1].set_ylabel('Scaled Dis-equilibrium')\n",
+        "    axes[1].set_xlim(timeline_df['tstamp'].min(), timeline_df['tstamp'].max())\n",
         "    axes[1].legend()\n",
         "    axes[1].grid(True)\n",
         "\n",
-        "    # 2. Trading signals if available\n",
+        "    # 3. Trading signals if available - using consistent timeline\n",
         "    if pair_trades is not None and len(pair_trades) > 0:\n",
         "        # Show trading signals over time\n",
         "        trade_times = pair_trades['time'].values\n",
@@ -1105,9 +1236,11 @@
         "        axes[2].set_ylabel('Signal Index')\n",
         "    else:\n",
         "        axes[2].text(0.5, 0.5, 'No Trading Signals Generated', \n",
-        "                     transform=axes[1].transAxes, ha='center', va='center', fontsize=16)\n",
+        "                     transform=axes[2].transAxes, ha='center', va='center', fontsize=16)\n",
         "        axes[2].set_title('Trading Signals (None Generated)')\n",
         "    \n",
+        "    # Set consistent x-axis limits for all charts\n",
+        "    axes[2].set_xlim(timeline_df['tstamp'].min(), timeline_df['tstamp'].max())\n",
         "    axes[2].set_xlabel('Time')\n",
         "    axes[2].grid(True)\n",
         "    \n",
@@ -1118,6 +1251,2980 @@
         "    print(\"No visualization data available - strategy may not have run successfully\")\n"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Visualisation-2 (plotly)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "        <script type=\"text/javascript\">\n",
+              "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+              "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+              "        </script>\n",
+              "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-3.0.1.min\"</script>\n",
+              "        "
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "=== SLIDING FIT INTERACTIVE VISUALIZATION ===\n",
+            "Note: Sliding strategy visualization with interactive plotly charts\n",
+            "Using consistent timeline with 391 timestamps\n",
+            "Timeline range: 2025-06-05 13:30:00 to 2025-06-05 20:00:00\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.plotly.v1+json": {
+              "config": {
+                "linkText": "Export to plot.ly",
+                "plotlyServerURL": "https://plot.ly",
+                "showLink": false
+              },
+              "data": [
+                {
+                  "line": {
+                    "color": "green",
+                    "width": 2
+                  },
+                  "name": "Scaled Dis-equilibrium",
+                  "opacity": 0.8,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T13:30:00.000000000",
+                    "2025-06-05T13:31:00.000000000",
+                    "2025-06-05T13:32:00.000000000",
+                    "2025-06-05T13:33:00.000000000",
+                    "2025-06-05T13:34:00.000000000",
+                    "2025-06-05T13:35:00.000000000",
+                    "2025-06-05T13:36:00.000000000",
+                    "2025-06-05T13:37:00.000000000",
+                    "2025-06-05T13:38:00.000000000",
+                    "2025-06-05T13:39:00.000000000",
+                    "2025-06-05T13:40:00.000000000",
+                    "2025-06-05T13:41:00.000000000",
+                    "2025-06-05T13:42:00.000000000",
+                    "2025-06-05T13:43:00.000000000",
+                    "2025-06-05T13:44:00.000000000",
+                    "2025-06-05T13:45:00.000000000",
+                    "2025-06-05T13:46:00.000000000",
+                    "2025-06-05T13:47:00.000000000",
+                    "2025-06-05T13:48:00.000000000",
+                    "2025-06-05T13:49:00.000000000",
+                    "2025-06-05T13:50:00.000000000",
+                    "2025-06-05T13:51:00.000000000",
+                    "2025-06-05T13:52:00.000000000",
+                    "2025-06-05T13:53:00.000000000",
+                    "2025-06-05T13:54:00.000000000",
+                    "2025-06-05T13:55:00.000000000",
+                    "2025-06-05T13:56:00.000000000",
+                    "2025-06-05T13:57:00.000000000",
+                    "2025-06-05T13:58:00.000000000",
+                    "2025-06-05T13:59:00.000000000",
+                    "2025-06-05T14:00:00.000000000",
+                    "2025-06-05T14:01:00.000000000",
+                    "2025-06-05T14:02:00.000000000",
+                    "2025-06-05T14:03:00.000000000",
+                    "2025-06-05T14:04:00.000000000",
+                    "2025-06-05T14:05:00.000000000",
+                    "2025-06-05T14:06:00.000000000",
+                    "2025-06-05T14:07:00.000000000",
+                    "2025-06-05T14:08:00.000000000",
+                    "2025-06-05T14:09:00.000000000",
+                    "2025-06-05T14:10:00.000000000",
+                    "2025-06-05T14:11:00.000000000",
+                    "2025-06-05T14:12:00.000000000",
+                    "2025-06-05T14:13:00.000000000",
+                    "2025-06-05T14:14:00.000000000",
+                    "2025-06-05T14:15:00.000000000",
+                    "2025-06-05T14:16:00.000000000",
+                    "2025-06-05T14:17:00.000000000",
+                    "2025-06-05T14:18:00.000000000",
+                    "2025-06-05T14:19:00.000000000",
+                    "2025-06-05T14:20:00.000000000",
+                    "2025-06-05T14:21:00.000000000",
+                    "2025-06-05T14:22:00.000000000",
+                    "2025-06-05T14:23:00.000000000",
+                    "2025-06-05T14:24:00.000000000",
+                    "2025-06-05T14:25:00.000000000",
+                    "2025-06-05T14:26:00.000000000",
+                    "2025-06-05T14:27:00.000000000",
+                    "2025-06-05T14:28:00.000000000",
+                    "2025-06-05T14:29:00.000000000",
+                    "2025-06-05T14:30:00.000000000",
+                    "2025-06-05T14:31:00.000000000",
+                    "2025-06-05T14:32:00.000000000",
+                    "2025-06-05T14:33:00.000000000",
+                    "2025-06-05T14:34:00.000000000",
+                    "2025-06-05T14:35:00.000000000",
+                    "2025-06-05T14:36:00.000000000",
+                    "2025-06-05T14:37:00.000000000",
+                    "2025-06-05T14:38:00.000000000",
+                    "2025-06-05T14:39:00.000000000",
+                    "2025-06-05T14:40:00.000000000",
+                    "2025-06-05T14:41:00.000000000",
+                    "2025-06-05T14:42:00.000000000",
+                    "2025-06-05T14:43:00.000000000",
+                    "2025-06-05T14:44:00.000000000",
+                    "2025-06-05T14:45:00.000000000",
+                    "2025-06-05T14:46:00.000000000",
+                    "2025-06-05T14:47:00.000000000",
+                    "2025-06-05T14:48:00.000000000",
+                    "2025-06-05T14:49:00.000000000",
+                    "2025-06-05T14:50:00.000000000",
+                    "2025-06-05T14:51:00.000000000",
+                    "2025-06-05T14:52:00.000000000",
+                    "2025-06-05T14:53:00.000000000",
+                    "2025-06-05T14:54:00.000000000",
+                    "2025-06-05T14:55:00.000000000",
+                    "2025-06-05T14:56:00.000000000",
+                    "2025-06-05T14:57:00.000000000",
+                    "2025-06-05T14:58:00.000000000",
+                    "2025-06-05T14:59:00.000000000",
+                    "2025-06-05T15:00:00.000000000",
+                    "2025-06-05T15:01:00.000000000",
+                    "2025-06-05T15:02:00.000000000",
+                    "2025-06-05T15:03:00.000000000",
+                    "2025-06-05T15:04:00.000000000",
+                    "2025-06-05T15:05:00.000000000",
+                    "2025-06-05T15:06:00.000000000",
+                    "2025-06-05T15:07:00.000000000",
+                    "2025-06-05T15:08:00.000000000",
+                    "2025-06-05T15:09:00.000000000",
+                    "2025-06-05T15:10:00.000000000",
+                    "2025-06-05T15:11:00.000000000",
+                    "2025-06-05T15:12:00.000000000",
+                    "2025-06-05T15:13:00.000000000",
+                    "2025-06-05T15:14:00.000000000",
+                    "2025-06-05T15:15:00.000000000",
+                    "2025-06-05T15:16:00.000000000",
+                    "2025-06-05T15:17:00.000000000",
+                    "2025-06-05T15:18:00.000000000",
+                    "2025-06-05T15:19:00.000000000",
+                    "2025-06-05T15:20:00.000000000",
+                    "2025-06-05T15:21:00.000000000",
+                    "2025-06-05T15:22:00.000000000",
+                    "2025-06-05T15:23:00.000000000",
+                    "2025-06-05T15:24:00.000000000",
+                    "2025-06-05T15:25:00.000000000",
+                    "2025-06-05T15:26:00.000000000",
+                    "2025-06-05T15:27:00.000000000",
+                    "2025-06-05T15:28:00.000000000",
+                    "2025-06-05T15:29:00.000000000",
+                    "2025-06-05T15:30:00.000000000",
+                    "2025-06-05T15:31:00.000000000",
+                    "2025-06-05T15:32:00.000000000",
+                    "2025-06-05T15:33:00.000000000",
+                    "2025-06-05T15:34:00.000000000",
+                    "2025-06-05T15:35:00.000000000",
+                    "2025-06-05T15:36:00.000000000",
+                    "2025-06-05T15:37:00.000000000",
+                    "2025-06-05T15:38:00.000000000",
+                    "2025-06-05T15:39:00.000000000",
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T15:41:00.000000000",
+                    "2025-06-05T15:42:00.000000000",
+                    "2025-06-05T15:43:00.000000000",
+                    "2025-06-05T15:44:00.000000000",
+                    "2025-06-05T15:45:00.000000000",
+                    "2025-06-05T15:46:00.000000000",
+                    "2025-06-05T15:47:00.000000000",
+                    "2025-06-05T15:48:00.000000000",
+                    "2025-06-05T15:49:00.000000000",
+                    "2025-06-05T15:50:00.000000000",
+                    "2025-06-05T15:51:00.000000000",
+                    "2025-06-05T15:52:00.000000000",
+                    "2025-06-05T15:53:00.000000000",
+                    "2025-06-05T15:54:00.000000000",
+                    "2025-06-05T15:55:00.000000000",
+                    "2025-06-05T15:56:00.000000000",
+                    "2025-06-05T15:57:00.000000000",
+                    "2025-06-05T15:58:00.000000000",
+                    "2025-06-05T15:59:00.000000000",
+                    "2025-06-05T16:00:00.000000000",
+                    "2025-06-05T16:01:00.000000000",
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:03:00.000000000",
+                    "2025-06-05T16:04:00.000000000",
+                    "2025-06-05T16:05:00.000000000",
+                    "2025-06-05T16:06:00.000000000",
+                    "2025-06-05T16:07:00.000000000",
+                    "2025-06-05T16:08:00.000000000",
+                    "2025-06-05T16:09:00.000000000",
+                    "2025-06-05T16:10:00.000000000",
+                    "2025-06-05T16:11:00.000000000",
+                    "2025-06-05T16:12:00.000000000",
+                    "2025-06-05T16:13:00.000000000",
+                    "2025-06-05T16:14:00.000000000",
+                    "2025-06-05T16:15:00.000000000",
+                    "2025-06-05T16:16:00.000000000",
+                    "2025-06-05T16:17:00.000000000",
+                    "2025-06-05T16:18:00.000000000",
+                    "2025-06-05T16:19:00.000000000",
+                    "2025-06-05T16:20:00.000000000",
+                    "2025-06-05T16:21:00.000000000",
+                    "2025-06-05T16:22:00.000000000",
+                    "2025-06-05T16:23:00.000000000",
+                    "2025-06-05T16:24:00.000000000",
+                    "2025-06-05T16:25:00.000000000",
+                    "2025-06-05T16:26:00.000000000",
+                    "2025-06-05T16:27:00.000000000",
+                    "2025-06-05T16:28:00.000000000",
+                    "2025-06-05T16:29:00.000000000",
+                    "2025-06-05T16:30:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T16:32:00.000000000",
+                    "2025-06-05T16:33:00.000000000",
+                    "2025-06-05T16:34:00.000000000",
+                    "2025-06-05T16:35:00.000000000",
+                    "2025-06-05T16:36:00.000000000",
+                    "2025-06-05T16:37:00.000000000",
+                    "2025-06-05T16:38:00.000000000",
+                    "2025-06-05T16:39:00.000000000",
+                    "2025-06-05T16:40:00.000000000",
+                    "2025-06-05T16:41:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T16:43:00.000000000",
+                    "2025-06-05T16:44:00.000000000",
+                    "2025-06-05T16:45:00.000000000",
+                    "2025-06-05T16:46:00.000000000",
+                    "2025-06-05T16:47:00.000000000",
+                    "2025-06-05T16:48:00.000000000",
+                    "2025-06-05T16:49:00.000000000",
+                    "2025-06-05T16:50:00.000000000",
+                    "2025-06-05T16:51:00.000000000",
+                    "2025-06-05T16:52:00.000000000",
+                    "2025-06-05T16:53:00.000000000",
+                    "2025-06-05T16:54:00.000000000",
+                    "2025-06-05T16:55:00.000000000",
+                    "2025-06-05T16:56:00.000000000",
+                    "2025-06-05T16:57:00.000000000",
+                    "2025-06-05T16:58:00.000000000",
+                    "2025-06-05T16:59:00.000000000",
+                    "2025-06-05T17:00:00.000000000",
+                    "2025-06-05T17:01:00.000000000",
+                    "2025-06-05T17:02:00.000000000",
+                    "2025-06-05T17:03:00.000000000",
+                    "2025-06-05T17:04:00.000000000",
+                    "2025-06-05T17:05:00.000000000",
+                    "2025-06-05T17:06:00.000000000",
+                    "2025-06-05T17:07:00.000000000",
+                    "2025-06-05T17:08:00.000000000",
+                    "2025-06-05T17:09:00.000000000",
+                    "2025-06-05T17:10:00.000000000",
+                    "2025-06-05T17:11:00.000000000",
+                    "2025-06-05T17:12:00.000000000",
+                    "2025-06-05T17:13:00.000000000",
+                    "2025-06-05T17:14:00.000000000",
+                    "2025-06-05T17:15:00.000000000",
+                    "2025-06-05T17:16:00.000000000",
+                    "2025-06-05T17:17:00.000000000",
+                    "2025-06-05T17:18:00.000000000",
+                    "2025-06-05T17:19:00.000000000",
+                    "2025-06-05T17:20:00.000000000",
+                    "2025-06-05T17:21:00.000000000",
+                    "2025-06-05T17:22:00.000000000",
+                    "2025-06-05T17:23:00.000000000",
+                    "2025-06-05T17:24:00.000000000",
+                    "2025-06-05T17:25:00.000000000",
+                    "2025-06-05T17:26:00.000000000",
+                    "2025-06-05T17:27:00.000000000",
+                    "2025-06-05T17:28:00.000000000",
+                    "2025-06-05T17:29:00.000000000",
+                    "2025-06-05T17:30:00.000000000",
+                    "2025-06-05T17:31:00.000000000",
+                    "2025-06-05T17:32:00.000000000",
+                    "2025-06-05T17:33:00.000000000",
+                    "2025-06-05T17:34:00.000000000",
+                    "2025-06-05T17:35:00.000000000",
+                    "2025-06-05T17:36:00.000000000",
+                    "2025-06-05T17:37:00.000000000",
+                    "2025-06-05T17:38:00.000000000",
+                    "2025-06-05T17:39:00.000000000",
+                    "2025-06-05T17:40:00.000000000",
+                    "2025-06-05T17:41:00.000000000",
+                    "2025-06-05T17:42:00.000000000",
+                    "2025-06-05T17:43:00.000000000",
+                    "2025-06-05T17:44:00.000000000",
+                    "2025-06-05T17:45:00.000000000",
+                    "2025-06-05T17:46:00.000000000",
+                    "2025-06-05T17:47:00.000000000",
+                    "2025-06-05T17:48:00.000000000",
+                    "2025-06-05T17:49:00.000000000",
+                    "2025-06-05T17:50:00.000000000",
+                    "2025-06-05T17:51:00.000000000",
+                    "2025-06-05T17:52:00.000000000",
+                    "2025-06-05T17:53:00.000000000",
+                    "2025-06-05T17:54:00.000000000",
+                    "2025-06-05T17:55:00.000000000",
+                    "2025-06-05T17:56:00.000000000",
+                    "2025-06-05T17:57:00.000000000",
+                    "2025-06-05T17:58:00.000000000",
+                    "2025-06-05T17:59:00.000000000",
+                    "2025-06-05T18:00:00.000000000",
+                    "2025-06-05T18:01:00.000000000",
+                    "2025-06-05T18:02:00.000000000",
+                    "2025-06-05T18:03:00.000000000",
+                    "2025-06-05T18:04:00.000000000",
+                    "2025-06-05T18:05:00.000000000",
+                    "2025-06-05T18:06:00.000000000",
+                    "2025-06-05T18:07:00.000000000",
+                    "2025-06-05T18:08:00.000000000",
+                    "2025-06-05T18:09:00.000000000",
+                    "2025-06-05T18:10:00.000000000",
+                    "2025-06-05T18:11:00.000000000",
+                    "2025-06-05T18:12:00.000000000",
+                    "2025-06-05T18:13:00.000000000",
+                    "2025-06-05T18:14:00.000000000",
+                    "2025-06-05T18:15:00.000000000",
+                    "2025-06-05T18:16:00.000000000",
+                    "2025-06-05T18:17:00.000000000",
+                    "2025-06-05T18:18:00.000000000",
+                    "2025-06-05T18:19:00.000000000",
+                    "2025-06-05T18:20:00.000000000",
+                    "2025-06-05T18:21:00.000000000",
+                    "2025-06-05T18:22:00.000000000",
+                    "2025-06-05T18:23:00.000000000",
+                    "2025-06-05T18:24:00.000000000",
+                    "2025-06-05T18:25:00.000000000",
+                    "2025-06-05T18:26:00.000000000",
+                    "2025-06-05T18:27:00.000000000",
+                    "2025-06-05T18:28:00.000000000",
+                    "2025-06-05T18:29:00.000000000",
+                    "2025-06-05T18:30:00.000000000",
+                    "2025-06-05T18:31:00.000000000",
+                    "2025-06-05T18:32:00.000000000",
+                    "2025-06-05T18:33:00.000000000",
+                    "2025-06-05T18:34:00.000000000",
+                    "2025-06-05T18:35:00.000000000",
+                    "2025-06-05T18:36:00.000000000",
+                    "2025-06-05T18:37:00.000000000",
+                    "2025-06-05T18:38:00.000000000",
+                    "2025-06-05T18:39:00.000000000",
+                    "2025-06-05T18:40:00.000000000",
+                    "2025-06-05T18:41:00.000000000",
+                    "2025-06-05T18:42:00.000000000",
+                    "2025-06-05T18:43:00.000000000",
+                    "2025-06-05T18:44:00.000000000",
+                    "2025-06-05T18:45:00.000000000",
+                    "2025-06-05T18:46:00.000000000",
+                    "2025-06-05T18:47:00.000000000",
+                    "2025-06-05T18:48:00.000000000",
+                    "2025-06-05T18:49:00.000000000",
+                    "2025-06-05T18:50:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T18:52:00.000000000",
+                    "2025-06-05T18:53:00.000000000",
+                    "2025-06-05T18:54:00.000000000",
+                    "2025-06-05T18:55:00.000000000",
+                    "2025-06-05T18:56:00.000000000",
+                    "2025-06-05T18:57:00.000000000",
+                    "2025-06-05T18:58:00.000000000",
+                    "2025-06-05T18:59:00.000000000",
+                    "2025-06-05T19:00:00.000000000",
+                    "2025-06-05T19:01:00.000000000",
+                    "2025-06-05T19:02:00.000000000",
+                    "2025-06-05T19:03:00.000000000",
+                    "2025-06-05T19:04:00.000000000",
+                    "2025-06-05T19:05:00.000000000",
+                    "2025-06-05T19:06:00.000000000",
+                    "2025-06-05T19:07:00.000000000",
+                    "2025-06-05T19:08:00.000000000",
+                    "2025-06-05T19:09:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:11:00.000000000",
+                    "2025-06-05T19:12:00.000000000",
+                    "2025-06-05T19:13:00.000000000",
+                    "2025-06-05T19:14:00.000000000",
+                    "2025-06-05T19:15:00.000000000",
+                    "2025-06-05T19:16:00.000000000",
+                    "2025-06-05T19:17:00.000000000",
+                    "2025-06-05T19:18:00.000000000",
+                    "2025-06-05T19:19:00.000000000",
+                    "2025-06-05T19:20:00.000000000",
+                    "2025-06-05T19:21:00.000000000",
+                    "2025-06-05T19:22:00.000000000",
+                    "2025-06-05T19:23:00.000000000",
+                    "2025-06-05T19:24:00.000000000",
+                    "2025-06-05T19:25:00.000000000",
+                    "2025-06-05T19:26:00.000000000",
+                    "2025-06-05T19:27:00.000000000",
+                    "2025-06-05T19:28:00.000000000",
+                    "2025-06-05T19:29:00.000000000",
+                    "2025-06-05T19:30:00.000000000",
+                    "2025-06-05T19:31:00.000000000",
+                    "2025-06-05T19:32:00.000000000",
+                    "2025-06-05T19:33:00.000000000",
+                    "2025-06-05T19:34:00.000000000",
+                    "2025-06-05T19:35:00.000000000",
+                    "2025-06-05T19:36:00.000000000",
+                    "2025-06-05T19:37:00.000000000",
+                    "2025-06-05T19:38:00.000000000",
+                    "2025-06-05T19:39:00.000000000",
+                    "2025-06-05T19:40:00.000000000",
+                    "2025-06-05T19:41:00.000000000",
+                    "2025-06-05T19:42:00.000000000",
+                    "2025-06-05T19:43:00.000000000",
+                    "2025-06-05T19:44:00.000000000",
+                    "2025-06-05T19:45:00.000000000",
+                    "2025-06-05T19:46:00.000000000",
+                    "2025-06-05T19:47:00.000000000",
+                    "2025-06-05T19:48:00.000000000",
+                    "2025-06-05T19:49:00.000000000",
+                    "2025-06-05T19:50:00.000000000",
+                    "2025-06-05T19:51:00.000000000",
+                    "2025-06-05T19:52:00.000000000",
+                    "2025-06-05T19:53:00.000000000",
+                    "2025-06-05T19:54:00.000000000",
+                    "2025-06-05T19:55:00.000000000",
+                    "2025-06-05T19:56:00.000000000",
+                    "2025-06-05T19:57:00.000000000",
+                    "2025-06-05T19:58:00.000000000",
+                    "2025-06-05T19:59:00.000000000",
+                    "2025-06-05T20:00:00.000000000"
+                  ],
+                  "xaxis": "x",
+                  "y": {
+                    "bdata": "AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh/eK9K+pck8D+WjVR9QWjqP2+V5QVt+PA/2braugEs9D8u/aiRcrTwPwsnQihYQfo/7MRSm85Y+D/Qlhhaf6v8P/Odar/gyfk/YePC8lbj+j/jgUn0MtEAQBZrdyPkq/w/UnaIKjJ8/D9yBZNln0AAQJV8eN7QIf0/llLBJxv3AEAZA24AY6D9P2QsnEXBTAJAC7RRh1PyAEATS7BM2OwAQBnMCIaNDgFA/u15Ntl1AECqi8mZ8FD9P6T1snbaKf4/QgHhABUr/z+9wOzWpzAAQKu/n6tYL/s/9EjrvXyG9z8TdUtLlHTzP76Idvv/SvQ/AHuN0Mlx9D8JKN46gI7xP0Z7Xc4g1ec/zhbFbcps4D/D56Xsk6/uP8wTdft2Uek/hiGkspqi8D89ru8fQHPwP8sLfHjMtvA/9jSpBeFo6j/VWS3eGszwPzTt8vnwOPA/zHnJyHCv8D/7eoElfL/yPyfPWqmY9vQ/nkqaRV3m8T83poHfb6XtP9qPisPXCuI/W23EXLR42j+/9BjvHqDHP/jx8o+/Z+E/riG6xNyE6j/XMkWQBdXiPx94HDlVHu8/eASgQ/AC8D91WwVIOkjqP99VvlKSqPE/j0c5GVnD7z8XP19HWxv7P+8sq20YVPs/HjnL623N+T+0li1kPJAAQAgJXrOFR/0/uSkQ6Ml7/D+sFQ1IrbP6P+6s6NXyF/o/t2739UpZ/T95X5/wolr0P9Ebys4uZvM/8ab88bFK8z+VY9bs5fn1P7OssB26yvE/JnPZzCZp6D8zcWAlzoK3P48T/DrgjtM/UfnI9gY+8z/wT9kKH5kBQIiA2wfK+P4/LUnV58JyAUAMaRLA+JP+P4kT8Al7jQBATL15ccgrA0C2DYSZ3PQHQDgq4Xo+XQRA+jK/82E5BEAcgkcQnMkGQM95xZ7q9ARAIdAw2zfaCkDzNt8h6eoMQO2qucTJrAlAybdV55OTBUAUG5eLT5gHQPyYst4PoghAdTW9rfCwAUA9cWBfTJwAQPQhettMowFAwFAUOqXM/j8zewCG9nYBQFxudkg5kABAT8+pnMvEAkD9ykf+nxUCQMI+807DHgJAs/u8kkymA0B+zMB4bEkEQCyjH0wy3QJA98ERS223AUDk5DcIwBQDQCrd6LVhlgNAHm6co7yHAkAIAPeMOxgBQGPGmFpHbABAqk/Nja09/j9y+Q4AmX37Pzz9al0Bj/w/H7lFljlv+z+lOGk6AU/5P3sFE+ux2fU/J7K45DAa9T+O/F4sBIvzP8eIHNU0VvQ/UOd6fdPi9D/HkDDHh5HyP9j/ATGzXfA/rIZDBJ8U8D/ta8azKqHuP05cp4kBqPA/Nbq9CyOZ7z8Ak58QnWXwP43Xi8SkAvE/2wggH34z8T+cQDuNxZntP/V8Xz2DQOw/kiAtm9m17D/mr2BAG5HkP3tlRN5osOU/DZ+0Bku96D8rrKM0xcznP9LufWXOMec/YaRrOgh66D+GmlCLNVHnPxtqZNbliOo/bXnCQsku7j9qSsT0eGbwPxuYSvon6PE/ivHL/DPI8D/uKuzS33zyP7oDBqC5rfA/nCc+r9h+8j/56if0xsX1P7er8QqvQvQ/IIBcHvNZ8j9BZcnJmgPyPzPSIVofXPI/59rAEH739j9XAeasOzH2P59SdX3LOPU/5bqLvzfV9T/vwfoJntj0P7O7UpFCXPQ/gEFgTnxN9T+3/lcEfsr0P4UKRGoDRvk/2IThOz7c9j9NWgTKdCf5Pxzk/myIvvY/oBSo9CAq+j/7UBYJbtb4P/4JiM3/RPk/3R2EDvzb+T9UPmaVjYz4P8+MIi9/Nfs/sCs62GKh+z9BIyQCNZ/8P/WmIvuzsvk/POSrxxiN+T+2kg2p9Hz3Py+OcgK9NPo/hNYhuIXG+T+djfit+an4P5y2DLpJn/k/27PFxeFH+z+fMZp5WN35PwvHrsce6fs/t9Zrrp/X+D+2f0DQwE34P7kdBDog4Pg/tHbUKbfY+j+1pmjE8Cj6PwVPuc+nO/w/98ypLFQB+z8nankr69f5P9uynowRv/o/Tdc1DKEp+j8pzBz8r0b6P+xUYxOsPP0/ynEw3N6D/D8QuH9lRJH4P1PNbqlaVfk/oSK/lN2r/D/wioYFezb6P7WkRP69lf8/W254kIDrAECC777IypL/P6tU0Td6VAJAyuaPX4DpAUB4XFmhmH/+P3CE01Euv/s/ei8DZZ3j+j8+eTNOKIr9P4ZiNOX4Svk/T02wWSrE+D/edfj6MB/6PyLK+CHij/g/sPK+mVJW8z9WaG2Nl23zP6ugimJLKvM/nuqbszYu8z/o0Ej6CxfxP5VMywf2HvI/B1iliW1X8T88NXNFVVbvP2+NyHTQJPI/jWIFp5+Q8j9ZCLTk6zvyP0fBYpIgIPE/QTKi6hcNAEByVC9a9XTmP1bSEt9mSOg/TL6mwlrQ5z8vqC+ancPwP5xUUychsvA/dW2w+Yy47z/fQrdFmYbwPwd6keIeFPE/w0fBZjDA8D8SGfnvpUD2P8MfD73LcvM/u5u16M3M8z+ju+ceAlX1P+lywvH7DvU/oinsacO28z8nQSe3f0byP49NRKhsFfY/lmBmZm0v9j/pPXMwnFj2P0qN0VPko/U/d5NdqxJ69z81CjBYFcTzPxdKvSNQ8fU/Q3WEB5938j9Y9Pl96qPyPzeR1z3Bj/I/aGdH8hcq8j8eKqaT+d7wP1yN7LV+fe0/h6ORO6ne7j8jDWRdNXbmP5Q8tlO4P+I/7DNvMFm53j9qxtGBcQzPPzVRbMTaDM0/3/pMGhnL4D++pJ75YOXkP3WL9vCyduE/6rVa6CdG4j+8lOIA7sXTPx3H6G5HVcI/lduIR5CJ0j88L8xmFczcPzlQFhFyI4M/tm0Iruck2D8=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y"
+                },
+                {
+                  "marker": {
+                    "color": "red",
+                    "size": 10,
+                    "symbol": "circle"
+                  },
+                  "mode": "markers",
+                  "name": "BUY OPEN",
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T16:46:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T19:15:00.000000000"
+                  ],
+                  "xaxis": "x2",
+                  "y": [
+                    1,
+                    5,
+                    8,
+                    13,
+                    17
+                  ],
+                  "yaxis": "y2"
+                },
+                {
+                  "marker": {
+                    "color": "pink",
+                    "size": 10,
+                    "symbol": "circle"
+                  },
+                  "mode": "markers",
+                  "name": "BUY CLOSE",
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T17:34:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:16:00.000000000"
+                  ],
+                  "xaxis": "x2",
+                  "y": [
+                    2,
+                    6,
+                    11,
+                    14,
+                    18
+                  ],
+                  "yaxis": "y2"
+                },
+                {
+                  "marker": {
+                    "color": "blue",
+                    "size": 10,
+                    "symbol": "circle"
+                  },
+                  "mode": "markers",
+                  "name": "SELL OPEN",
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T16:46:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T19:15:00.000000000"
+                  ],
+                  "xaxis": "x2",
+                  "y": [
+                    0,
+                    4,
+                    9,
+                    12,
+                    16
+                  ],
+                  "yaxis": "y2"
+                },
+                {
+                  "marker": {
+                    "color": "purple",
+                    "size": 10,
+                    "symbol": "circle"
+                  },
+                  "mode": "markers",
+                  "name": "SELL CLOSE",
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T17:34:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:16:00.000000000"
+                  ],
+                  "xaxis": "x2",
+                  "y": [
+                    3,
+                    7,
+                    10,
+                    15,
+                    19
+                  ],
+                  "yaxis": "y2"
+                },
+                {
+                  "line": {
+                    "color": "blue",
+                    "width": 2
+                  },
+                  "name": "COIN Price",
+                  "opacity": 0.8,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T13:30:00.000000000",
+                    "2025-06-05T13:31:00.000000000",
+                    "2025-06-05T13:32:00.000000000",
+                    "2025-06-05T13:33:00.000000000",
+                    "2025-06-05T13:34:00.000000000",
+                    "2025-06-05T13:35:00.000000000",
+                    "2025-06-05T13:36:00.000000000",
+                    "2025-06-05T13:37:00.000000000",
+                    "2025-06-05T13:38:00.000000000",
+                    "2025-06-05T13:39:00.000000000",
+                    "2025-06-05T13:40:00.000000000",
+                    "2025-06-05T13:41:00.000000000",
+                    "2025-06-05T13:42:00.000000000",
+                    "2025-06-05T13:43:00.000000000",
+                    "2025-06-05T13:44:00.000000000",
+                    "2025-06-05T13:45:00.000000000",
+                    "2025-06-05T13:46:00.000000000",
+                    "2025-06-05T13:47:00.000000000",
+                    "2025-06-05T13:48:00.000000000",
+                    "2025-06-05T13:49:00.000000000",
+                    "2025-06-05T13:50:00.000000000",
+                    "2025-06-05T13:51:00.000000000",
+                    "2025-06-05T13:52:00.000000000",
+                    "2025-06-05T13:53:00.000000000",
+                    "2025-06-05T13:54:00.000000000",
+                    "2025-06-05T13:55:00.000000000",
+                    "2025-06-05T13:56:00.000000000",
+                    "2025-06-05T13:57:00.000000000",
+                    "2025-06-05T13:58:00.000000000",
+                    "2025-06-05T13:59:00.000000000",
+                    "2025-06-05T14:00:00.000000000",
+                    "2025-06-05T14:01:00.000000000",
+                    "2025-06-05T14:02:00.000000000",
+                    "2025-06-05T14:03:00.000000000",
+                    "2025-06-05T14:04:00.000000000",
+                    "2025-06-05T14:05:00.000000000",
+                    "2025-06-05T14:06:00.000000000",
+                    "2025-06-05T14:07:00.000000000",
+                    "2025-06-05T14:08:00.000000000",
+                    "2025-06-05T14:09:00.000000000",
+                    "2025-06-05T14:10:00.000000000",
+                    "2025-06-05T14:11:00.000000000",
+                    "2025-06-05T14:12:00.000000000",
+                    "2025-06-05T14:13:00.000000000",
+                    "2025-06-05T14:14:00.000000000",
+                    "2025-06-05T14:15:00.000000000",
+                    "2025-06-05T14:16:00.000000000",
+                    "2025-06-05T14:17:00.000000000",
+                    "2025-06-05T14:18:00.000000000",
+                    "2025-06-05T14:19:00.000000000",
+                    "2025-06-05T14:20:00.000000000",
+                    "2025-06-05T14:21:00.000000000",
+                    "2025-06-05T14:22:00.000000000",
+                    "2025-06-05T14:23:00.000000000",
+                    "2025-06-05T14:24:00.000000000",
+                    "2025-06-05T14:25:00.000000000",
+                    "2025-06-05T14:26:00.000000000",
+                    "2025-06-05T14:27:00.000000000",
+                    "2025-06-05T14:28:00.000000000",
+                    "2025-06-05T14:29:00.000000000",
+                    "2025-06-05T14:30:00.000000000",
+                    "2025-06-05T14:31:00.000000000",
+                    "2025-06-05T14:32:00.000000000",
+                    "2025-06-05T14:33:00.000000000",
+                    "2025-06-05T14:34:00.000000000",
+                    "2025-06-05T14:35:00.000000000",
+                    "2025-06-05T14:36:00.000000000",
+                    "2025-06-05T14:37:00.000000000",
+                    "2025-06-05T14:38:00.000000000",
+                    "2025-06-05T14:39:00.000000000",
+                    "2025-06-05T14:40:00.000000000",
+                    "2025-06-05T14:41:00.000000000",
+                    "2025-06-05T14:42:00.000000000",
+                    "2025-06-05T14:43:00.000000000",
+                    "2025-06-05T14:44:00.000000000",
+                    "2025-06-05T14:45:00.000000000",
+                    "2025-06-05T14:46:00.000000000",
+                    "2025-06-05T14:47:00.000000000",
+                    "2025-06-05T14:48:00.000000000",
+                    "2025-06-05T14:49:00.000000000",
+                    "2025-06-05T14:50:00.000000000",
+                    "2025-06-05T14:51:00.000000000",
+                    "2025-06-05T14:52:00.000000000",
+                    "2025-06-05T14:53:00.000000000",
+                    "2025-06-05T14:54:00.000000000",
+                    "2025-06-05T14:55:00.000000000",
+                    "2025-06-05T14:56:00.000000000",
+                    "2025-06-05T14:57:00.000000000",
+                    "2025-06-05T14:58:00.000000000",
+                    "2025-06-05T14:59:00.000000000",
+                    "2025-06-05T15:00:00.000000000",
+                    "2025-06-05T15:01:00.000000000",
+                    "2025-06-05T15:02:00.000000000",
+                    "2025-06-05T15:03:00.000000000",
+                    "2025-06-05T15:04:00.000000000",
+                    "2025-06-05T15:05:00.000000000",
+                    "2025-06-05T15:06:00.000000000",
+                    "2025-06-05T15:07:00.000000000",
+                    "2025-06-05T15:08:00.000000000",
+                    "2025-06-05T15:09:00.000000000",
+                    "2025-06-05T15:10:00.000000000",
+                    "2025-06-05T15:11:00.000000000",
+                    "2025-06-05T15:12:00.000000000",
+                    "2025-06-05T15:13:00.000000000",
+                    "2025-06-05T15:14:00.000000000",
+                    "2025-06-05T15:15:00.000000000",
+                    "2025-06-05T15:16:00.000000000",
+                    "2025-06-05T15:17:00.000000000",
+                    "2025-06-05T15:18:00.000000000",
+                    "2025-06-05T15:19:00.000000000",
+                    "2025-06-05T15:20:00.000000000",
+                    "2025-06-05T15:21:00.000000000",
+                    "2025-06-05T15:22:00.000000000",
+                    "2025-06-05T15:23:00.000000000",
+                    "2025-06-05T15:24:00.000000000",
+                    "2025-06-05T15:25:00.000000000",
+                    "2025-06-05T15:26:00.000000000",
+                    "2025-06-05T15:27:00.000000000",
+                    "2025-06-05T15:28:00.000000000",
+                    "2025-06-05T15:29:00.000000000",
+                    "2025-06-05T15:30:00.000000000",
+                    "2025-06-05T15:31:00.000000000",
+                    "2025-06-05T15:32:00.000000000",
+                    "2025-06-05T15:33:00.000000000",
+                    "2025-06-05T15:34:00.000000000",
+                    "2025-06-05T15:35:00.000000000",
+                    "2025-06-05T15:36:00.000000000",
+                    "2025-06-05T15:37:00.000000000",
+                    "2025-06-05T15:38:00.000000000",
+                    "2025-06-05T15:39:00.000000000",
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T15:41:00.000000000",
+                    "2025-06-05T15:42:00.000000000",
+                    "2025-06-05T15:43:00.000000000",
+                    "2025-06-05T15:44:00.000000000",
+                    "2025-06-05T15:45:00.000000000",
+                    "2025-06-05T15:46:00.000000000",
+                    "2025-06-05T15:47:00.000000000",
+                    "2025-06-05T15:48:00.000000000",
+                    "2025-06-05T15:49:00.000000000",
+                    "2025-06-05T15:50:00.000000000",
+                    "2025-06-05T15:51:00.000000000",
+                    "2025-06-05T15:52:00.000000000",
+                    "2025-06-05T15:53:00.000000000",
+                    "2025-06-05T15:54:00.000000000",
+                    "2025-06-05T15:55:00.000000000",
+                    "2025-06-05T15:56:00.000000000",
+                    "2025-06-05T15:57:00.000000000",
+                    "2025-06-05T15:58:00.000000000",
+                    "2025-06-05T15:59:00.000000000",
+                    "2025-06-05T16:00:00.000000000",
+                    "2025-06-05T16:01:00.000000000",
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:03:00.000000000",
+                    "2025-06-05T16:04:00.000000000",
+                    "2025-06-05T16:05:00.000000000",
+                    "2025-06-05T16:06:00.000000000",
+                    "2025-06-05T16:07:00.000000000",
+                    "2025-06-05T16:08:00.000000000",
+                    "2025-06-05T16:09:00.000000000",
+                    "2025-06-05T16:10:00.000000000",
+                    "2025-06-05T16:11:00.000000000",
+                    "2025-06-05T16:12:00.000000000",
+                    "2025-06-05T16:13:00.000000000",
+                    "2025-06-05T16:14:00.000000000",
+                    "2025-06-05T16:15:00.000000000",
+                    "2025-06-05T16:16:00.000000000",
+                    "2025-06-05T16:17:00.000000000",
+                    "2025-06-05T16:18:00.000000000",
+                    "2025-06-05T16:19:00.000000000",
+                    "2025-06-05T16:20:00.000000000",
+                    "2025-06-05T16:21:00.000000000",
+                    "2025-06-05T16:22:00.000000000",
+                    "2025-06-05T16:23:00.000000000",
+                    "2025-06-05T16:24:00.000000000",
+                    "2025-06-05T16:25:00.000000000",
+                    "2025-06-05T16:26:00.000000000",
+                    "2025-06-05T16:27:00.000000000",
+                    "2025-06-05T16:28:00.000000000",
+                    "2025-06-05T16:29:00.000000000",
+                    "2025-06-05T16:30:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T16:32:00.000000000",
+                    "2025-06-05T16:33:00.000000000",
+                    "2025-06-05T16:34:00.000000000",
+                    "2025-06-05T16:35:00.000000000",
+                    "2025-06-05T16:36:00.000000000",
+                    "2025-06-05T16:37:00.000000000",
+                    "2025-06-05T16:38:00.000000000",
+                    "2025-06-05T16:39:00.000000000",
+                    "2025-06-05T16:40:00.000000000",
+                    "2025-06-05T16:41:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T16:43:00.000000000",
+                    "2025-06-05T16:44:00.000000000",
+                    "2025-06-05T16:45:00.000000000",
+                    "2025-06-05T16:46:00.000000000",
+                    "2025-06-05T16:47:00.000000000",
+                    "2025-06-05T16:48:00.000000000",
+                    "2025-06-05T16:49:00.000000000",
+                    "2025-06-05T16:50:00.000000000",
+                    "2025-06-05T16:51:00.000000000",
+                    "2025-06-05T16:52:00.000000000",
+                    "2025-06-05T16:53:00.000000000",
+                    "2025-06-05T16:54:00.000000000",
+                    "2025-06-05T16:55:00.000000000",
+                    "2025-06-05T16:56:00.000000000",
+                    "2025-06-05T16:57:00.000000000",
+                    "2025-06-05T16:58:00.000000000",
+                    "2025-06-05T16:59:00.000000000",
+                    "2025-06-05T17:00:00.000000000",
+                    "2025-06-05T17:01:00.000000000",
+                    "2025-06-05T17:02:00.000000000",
+                    "2025-06-05T17:03:00.000000000",
+                    "2025-06-05T17:04:00.000000000",
+                    "2025-06-05T17:05:00.000000000",
+                    "2025-06-05T17:06:00.000000000",
+                    "2025-06-05T17:07:00.000000000",
+                    "2025-06-05T17:08:00.000000000",
+                    "2025-06-05T17:09:00.000000000",
+                    "2025-06-05T17:10:00.000000000",
+                    "2025-06-05T17:11:00.000000000",
+                    "2025-06-05T17:12:00.000000000",
+                    "2025-06-05T17:13:00.000000000",
+                    "2025-06-05T17:14:00.000000000",
+                    "2025-06-05T17:15:00.000000000",
+                    "2025-06-05T17:16:00.000000000",
+                    "2025-06-05T17:17:00.000000000",
+                    "2025-06-05T17:18:00.000000000",
+                    "2025-06-05T17:19:00.000000000",
+                    "2025-06-05T17:20:00.000000000",
+                    "2025-06-05T17:21:00.000000000",
+                    "2025-06-05T17:22:00.000000000",
+                    "2025-06-05T17:23:00.000000000",
+                    "2025-06-05T17:24:00.000000000",
+                    "2025-06-05T17:25:00.000000000",
+                    "2025-06-05T17:26:00.000000000",
+                    "2025-06-05T17:27:00.000000000",
+                    "2025-06-05T17:28:00.000000000",
+                    "2025-06-05T17:29:00.000000000",
+                    "2025-06-05T17:30:00.000000000",
+                    "2025-06-05T17:31:00.000000000",
+                    "2025-06-05T17:32:00.000000000",
+                    "2025-06-05T17:33:00.000000000",
+                    "2025-06-05T17:34:00.000000000",
+                    "2025-06-05T17:35:00.000000000",
+                    "2025-06-05T17:36:00.000000000",
+                    "2025-06-05T17:37:00.000000000",
+                    "2025-06-05T17:38:00.000000000",
+                    "2025-06-05T17:39:00.000000000",
+                    "2025-06-05T17:40:00.000000000",
+                    "2025-06-05T17:41:00.000000000",
+                    "2025-06-05T17:42:00.000000000",
+                    "2025-06-05T17:43:00.000000000",
+                    "2025-06-05T17:44:00.000000000",
+                    "2025-06-05T17:45:00.000000000",
+                    "2025-06-05T17:46:00.000000000",
+                    "2025-06-05T17:47:00.000000000",
+                    "2025-06-05T17:48:00.000000000",
+                    "2025-06-05T17:49:00.000000000",
+                    "2025-06-05T17:50:00.000000000",
+                    "2025-06-05T17:51:00.000000000",
+                    "2025-06-05T17:52:00.000000000",
+                    "2025-06-05T17:53:00.000000000",
+                    "2025-06-05T17:54:00.000000000",
+                    "2025-06-05T17:55:00.000000000",
+                    "2025-06-05T17:56:00.000000000",
+                    "2025-06-05T17:57:00.000000000",
+                    "2025-06-05T17:58:00.000000000",
+                    "2025-06-05T17:59:00.000000000",
+                    "2025-06-05T18:00:00.000000000",
+                    "2025-06-05T18:01:00.000000000",
+                    "2025-06-05T18:02:00.000000000",
+                    "2025-06-05T18:03:00.000000000",
+                    "2025-06-05T18:04:00.000000000",
+                    "2025-06-05T18:05:00.000000000",
+                    "2025-06-05T18:06:00.000000000",
+                    "2025-06-05T18:07:00.000000000",
+                    "2025-06-05T18:08:00.000000000",
+                    "2025-06-05T18:09:00.000000000",
+                    "2025-06-05T18:10:00.000000000",
+                    "2025-06-05T18:11:00.000000000",
+                    "2025-06-05T18:12:00.000000000",
+                    "2025-06-05T18:13:00.000000000",
+                    "2025-06-05T18:14:00.000000000",
+                    "2025-06-05T18:15:00.000000000",
+                    "2025-06-05T18:16:00.000000000",
+                    "2025-06-05T18:17:00.000000000",
+                    "2025-06-05T18:18:00.000000000",
+                    "2025-06-05T18:19:00.000000000",
+                    "2025-06-05T18:20:00.000000000",
+                    "2025-06-05T18:21:00.000000000",
+                    "2025-06-05T18:22:00.000000000",
+                    "2025-06-05T18:23:00.000000000",
+                    "2025-06-05T18:24:00.000000000",
+                    "2025-06-05T18:25:00.000000000",
+                    "2025-06-05T18:26:00.000000000",
+                    "2025-06-05T18:27:00.000000000",
+                    "2025-06-05T18:28:00.000000000",
+                    "2025-06-05T18:29:00.000000000",
+                    "2025-06-05T18:30:00.000000000",
+                    "2025-06-05T18:31:00.000000000",
+                    "2025-06-05T18:32:00.000000000",
+                    "2025-06-05T18:33:00.000000000",
+                    "2025-06-05T18:34:00.000000000",
+                    "2025-06-05T18:35:00.000000000",
+                    "2025-06-05T18:36:00.000000000",
+                    "2025-06-05T18:37:00.000000000",
+                    "2025-06-05T18:38:00.000000000",
+                    "2025-06-05T18:39:00.000000000",
+                    "2025-06-05T18:40:00.000000000",
+                    "2025-06-05T18:41:00.000000000",
+                    "2025-06-05T18:42:00.000000000",
+                    "2025-06-05T18:43:00.000000000",
+                    "2025-06-05T18:44:00.000000000",
+                    "2025-06-05T18:45:00.000000000",
+                    "2025-06-05T18:46:00.000000000",
+                    "2025-06-05T18:47:00.000000000",
+                    "2025-06-05T18:48:00.000000000",
+                    "2025-06-05T18:49:00.000000000",
+                    "2025-06-05T18:50:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T18:52:00.000000000",
+                    "2025-06-05T18:53:00.000000000",
+                    "2025-06-05T18:54:00.000000000",
+                    "2025-06-05T18:55:00.000000000",
+                    "2025-06-05T18:56:00.000000000",
+                    "2025-06-05T18:57:00.000000000",
+                    "2025-06-05T18:58:00.000000000",
+                    "2025-06-05T18:59:00.000000000",
+                    "2025-06-05T19:00:00.000000000",
+                    "2025-06-05T19:01:00.000000000",
+                    "2025-06-05T19:02:00.000000000",
+                    "2025-06-05T19:03:00.000000000",
+                    "2025-06-05T19:04:00.000000000",
+                    "2025-06-05T19:05:00.000000000",
+                    "2025-06-05T19:06:00.000000000",
+                    "2025-06-05T19:07:00.000000000",
+                    "2025-06-05T19:08:00.000000000",
+                    "2025-06-05T19:09:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:11:00.000000000",
+                    "2025-06-05T19:12:00.000000000",
+                    "2025-06-05T19:13:00.000000000",
+                    "2025-06-05T19:14:00.000000000",
+                    "2025-06-05T19:15:00.000000000",
+                    "2025-06-05T19:16:00.000000000",
+                    "2025-06-05T19:17:00.000000000",
+                    "2025-06-05T19:18:00.000000000",
+                    "2025-06-05T19:19:00.000000000",
+                    "2025-06-05T19:20:00.000000000",
+                    "2025-06-05T19:21:00.000000000",
+                    "2025-06-05T19:22:00.000000000",
+                    "2025-06-05T19:23:00.000000000",
+                    "2025-06-05T19:24:00.000000000",
+                    "2025-06-05T19:25:00.000000000",
+                    "2025-06-05T19:26:00.000000000",
+                    "2025-06-05T19:27:00.000000000",
+                    "2025-06-05T19:28:00.000000000",
+                    "2025-06-05T19:29:00.000000000",
+                    "2025-06-05T19:30:00.000000000",
+                    "2025-06-05T19:31:00.000000000",
+                    "2025-06-05T19:32:00.000000000",
+                    "2025-06-05T19:33:00.000000000",
+                    "2025-06-05T19:34:00.000000000",
+                    "2025-06-05T19:35:00.000000000",
+                    "2025-06-05T19:36:00.000000000",
+                    "2025-06-05T19:37:00.000000000",
+                    "2025-06-05T19:38:00.000000000",
+                    "2025-06-05T19:39:00.000000000",
+                    "2025-06-05T19:40:00.000000000",
+                    "2025-06-05T19:41:00.000000000",
+                    "2025-06-05T19:42:00.000000000",
+                    "2025-06-05T19:43:00.000000000",
+                    "2025-06-05T19:44:00.000000000",
+                    "2025-06-05T19:45:00.000000000",
+                    "2025-06-05T19:46:00.000000000",
+                    "2025-06-05T19:47:00.000000000",
+                    "2025-06-05T19:48:00.000000000",
+                    "2025-06-05T19:49:00.000000000",
+                    "2025-06-05T19:50:00.000000000",
+                    "2025-06-05T19:51:00.000000000",
+                    "2025-06-05T19:52:00.000000000",
+                    "2025-06-05T19:53:00.000000000",
+                    "2025-06-05T19:54:00.000000000",
+                    "2025-06-05T19:55:00.000000000",
+                    "2025-06-05T19:56:00.000000000",
+                    "2025-06-05T19:57:00.000000000",
+                    "2025-06-05T19:58:00.000000000",
+                    "2025-06-05T19:59:00.000000000",
+                    "2025-06-05T20:00:00.000000000"
+                  ],
+                  "xaxis": "x3",
+                  "y": {
+                    "bdata": "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",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y3"
+                },
+                {
+                  "marker": {
+                    "color": "red",
+                    "size": 12,
+                    "symbol": "triangle-up"
+                  },
+                  "mode": "markers",
+                  "name": "COIN BUY OPEN",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T16:46:00.000000000"
+                  ],
+                  "xaxis": "x3",
+                  "y": {
+                    "bdata": "7FG4HoXTb0A=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y3"
+                },
+                {
+                  "marker": {
+                    "color": "pink",
+                    "size": 12,
+                    "symbol": "triangle-up"
+                  },
+                  "mode": "markers",
+                  "name": "COIN BUY CLOSE",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:16:00.000000000"
+                  ],
+                  "xaxis": "x3",
+                  "y": {
+                    "bdata": "YTJVMCo2cEAUrkfhehRwQHsUrkfhsm5AcT0K16NobkA=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y3"
+                },
+                {
+                  "marker": {
+                    "color": "blue",
+                    "size": 12,
+                    "symbol": "triangle-down"
+                  },
+                  "mode": "markers",
+                  "name": "COIN SELL OPEN",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T19:15:00.000000000"
+                  ],
+                  "xaxis": "x3",
+                  "y": {
+                    "bdata": "PQrXo3BHcEBSuB6F6zlwQHE9CtejuG5AcT0K16OAbkA=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y3"
+                },
+                {
+                  "marker": {
+                    "color": "purple",
+                    "size": 12,
+                    "symbol": "triangle-down"
+                  },
+                  "mode": "markers",
+                  "name": "COIN SELL CLOSE",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T17:34:00.000000000"
+                  ],
+                  "xaxis": "x3",
+                  "y": {
+                    "bdata": "w/UoXI+ab0A=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y3"
+                },
+                {
+                  "line": {
+                    "color": "orange",
+                    "width": 2
+                  },
+                  "name": "MSTR Price",
+                  "opacity": 0.8,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T13:30:00.000000000",
+                    "2025-06-05T13:31:00.000000000",
+                    "2025-06-05T13:32:00.000000000",
+                    "2025-06-05T13:33:00.000000000",
+                    "2025-06-05T13:34:00.000000000",
+                    "2025-06-05T13:35:00.000000000",
+                    "2025-06-05T13:36:00.000000000",
+                    "2025-06-05T13:37:00.000000000",
+                    "2025-06-05T13:38:00.000000000",
+                    "2025-06-05T13:39:00.000000000",
+                    "2025-06-05T13:40:00.000000000",
+                    "2025-06-05T13:41:00.000000000",
+                    "2025-06-05T13:42:00.000000000",
+                    "2025-06-05T13:43:00.000000000",
+                    "2025-06-05T13:44:00.000000000",
+                    "2025-06-05T13:45:00.000000000",
+                    "2025-06-05T13:46:00.000000000",
+                    "2025-06-05T13:47:00.000000000",
+                    "2025-06-05T13:48:00.000000000",
+                    "2025-06-05T13:49:00.000000000",
+                    "2025-06-05T13:50:00.000000000",
+                    "2025-06-05T13:51:00.000000000",
+                    "2025-06-05T13:52:00.000000000",
+                    "2025-06-05T13:53:00.000000000",
+                    "2025-06-05T13:54:00.000000000",
+                    "2025-06-05T13:55:00.000000000",
+                    "2025-06-05T13:56:00.000000000",
+                    "2025-06-05T13:57:00.000000000",
+                    "2025-06-05T13:58:00.000000000",
+                    "2025-06-05T13:59:00.000000000",
+                    "2025-06-05T14:00:00.000000000",
+                    "2025-06-05T14:01:00.000000000",
+                    "2025-06-05T14:02:00.000000000",
+                    "2025-06-05T14:03:00.000000000",
+                    "2025-06-05T14:04:00.000000000",
+                    "2025-06-05T14:05:00.000000000",
+                    "2025-06-05T14:06:00.000000000",
+                    "2025-06-05T14:07:00.000000000",
+                    "2025-06-05T14:08:00.000000000",
+                    "2025-06-05T14:09:00.000000000",
+                    "2025-06-05T14:10:00.000000000",
+                    "2025-06-05T14:11:00.000000000",
+                    "2025-06-05T14:12:00.000000000",
+                    "2025-06-05T14:13:00.000000000",
+                    "2025-06-05T14:14:00.000000000",
+                    "2025-06-05T14:15:00.000000000",
+                    "2025-06-05T14:16:00.000000000",
+                    "2025-06-05T14:17:00.000000000",
+                    "2025-06-05T14:18:00.000000000",
+                    "2025-06-05T14:19:00.000000000",
+                    "2025-06-05T14:20:00.000000000",
+                    "2025-06-05T14:21:00.000000000",
+                    "2025-06-05T14:22:00.000000000",
+                    "2025-06-05T14:23:00.000000000",
+                    "2025-06-05T14:24:00.000000000",
+                    "2025-06-05T14:25:00.000000000",
+                    "2025-06-05T14:26:00.000000000",
+                    "2025-06-05T14:27:00.000000000",
+                    "2025-06-05T14:28:00.000000000",
+                    "2025-06-05T14:29:00.000000000",
+                    "2025-06-05T14:30:00.000000000",
+                    "2025-06-05T14:31:00.000000000",
+                    "2025-06-05T14:32:00.000000000",
+                    "2025-06-05T14:33:00.000000000",
+                    "2025-06-05T14:34:00.000000000",
+                    "2025-06-05T14:35:00.000000000",
+                    "2025-06-05T14:36:00.000000000",
+                    "2025-06-05T14:37:00.000000000",
+                    "2025-06-05T14:38:00.000000000",
+                    "2025-06-05T14:39:00.000000000",
+                    "2025-06-05T14:40:00.000000000",
+                    "2025-06-05T14:41:00.000000000",
+                    "2025-06-05T14:42:00.000000000",
+                    "2025-06-05T14:43:00.000000000",
+                    "2025-06-05T14:44:00.000000000",
+                    "2025-06-05T14:45:00.000000000",
+                    "2025-06-05T14:46:00.000000000",
+                    "2025-06-05T14:47:00.000000000",
+                    "2025-06-05T14:48:00.000000000",
+                    "2025-06-05T14:49:00.000000000",
+                    "2025-06-05T14:50:00.000000000",
+                    "2025-06-05T14:51:00.000000000",
+                    "2025-06-05T14:52:00.000000000",
+                    "2025-06-05T14:53:00.000000000",
+                    "2025-06-05T14:54:00.000000000",
+                    "2025-06-05T14:55:00.000000000",
+                    "2025-06-05T14:56:00.000000000",
+                    "2025-06-05T14:57:00.000000000",
+                    "2025-06-05T14:58:00.000000000",
+                    "2025-06-05T14:59:00.000000000",
+                    "2025-06-05T15:00:00.000000000",
+                    "2025-06-05T15:01:00.000000000",
+                    "2025-06-05T15:02:00.000000000",
+                    "2025-06-05T15:03:00.000000000",
+                    "2025-06-05T15:04:00.000000000",
+                    "2025-06-05T15:05:00.000000000",
+                    "2025-06-05T15:06:00.000000000",
+                    "2025-06-05T15:07:00.000000000",
+                    "2025-06-05T15:08:00.000000000",
+                    "2025-06-05T15:09:00.000000000",
+                    "2025-06-05T15:10:00.000000000",
+                    "2025-06-05T15:11:00.000000000",
+                    "2025-06-05T15:12:00.000000000",
+                    "2025-06-05T15:13:00.000000000",
+                    "2025-06-05T15:14:00.000000000",
+                    "2025-06-05T15:15:00.000000000",
+                    "2025-06-05T15:16:00.000000000",
+                    "2025-06-05T15:17:00.000000000",
+                    "2025-06-05T15:18:00.000000000",
+                    "2025-06-05T15:19:00.000000000",
+                    "2025-06-05T15:20:00.000000000",
+                    "2025-06-05T15:21:00.000000000",
+                    "2025-06-05T15:22:00.000000000",
+                    "2025-06-05T15:23:00.000000000",
+                    "2025-06-05T15:24:00.000000000",
+                    "2025-06-05T15:25:00.000000000",
+                    "2025-06-05T15:26:00.000000000",
+                    "2025-06-05T15:27:00.000000000",
+                    "2025-06-05T15:28:00.000000000",
+                    "2025-06-05T15:29:00.000000000",
+                    "2025-06-05T15:30:00.000000000",
+                    "2025-06-05T15:31:00.000000000",
+                    "2025-06-05T15:32:00.000000000",
+                    "2025-06-05T15:33:00.000000000",
+                    "2025-06-05T15:34:00.000000000",
+                    "2025-06-05T15:35:00.000000000",
+                    "2025-06-05T15:36:00.000000000",
+                    "2025-06-05T15:37:00.000000000",
+                    "2025-06-05T15:38:00.000000000",
+                    "2025-06-05T15:39:00.000000000",
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T15:41:00.000000000",
+                    "2025-06-05T15:42:00.000000000",
+                    "2025-06-05T15:43:00.000000000",
+                    "2025-06-05T15:44:00.000000000",
+                    "2025-06-05T15:45:00.000000000",
+                    "2025-06-05T15:46:00.000000000",
+                    "2025-06-05T15:47:00.000000000",
+                    "2025-06-05T15:48:00.000000000",
+                    "2025-06-05T15:49:00.000000000",
+                    "2025-06-05T15:50:00.000000000",
+                    "2025-06-05T15:51:00.000000000",
+                    "2025-06-05T15:52:00.000000000",
+                    "2025-06-05T15:53:00.000000000",
+                    "2025-06-05T15:54:00.000000000",
+                    "2025-06-05T15:55:00.000000000",
+                    "2025-06-05T15:56:00.000000000",
+                    "2025-06-05T15:57:00.000000000",
+                    "2025-06-05T15:58:00.000000000",
+                    "2025-06-05T15:59:00.000000000",
+                    "2025-06-05T16:00:00.000000000",
+                    "2025-06-05T16:01:00.000000000",
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:03:00.000000000",
+                    "2025-06-05T16:04:00.000000000",
+                    "2025-06-05T16:05:00.000000000",
+                    "2025-06-05T16:06:00.000000000",
+                    "2025-06-05T16:07:00.000000000",
+                    "2025-06-05T16:08:00.000000000",
+                    "2025-06-05T16:09:00.000000000",
+                    "2025-06-05T16:10:00.000000000",
+                    "2025-06-05T16:11:00.000000000",
+                    "2025-06-05T16:12:00.000000000",
+                    "2025-06-05T16:13:00.000000000",
+                    "2025-06-05T16:14:00.000000000",
+                    "2025-06-05T16:15:00.000000000",
+                    "2025-06-05T16:16:00.000000000",
+                    "2025-06-05T16:17:00.000000000",
+                    "2025-06-05T16:18:00.000000000",
+                    "2025-06-05T16:19:00.000000000",
+                    "2025-06-05T16:20:00.000000000",
+                    "2025-06-05T16:21:00.000000000",
+                    "2025-06-05T16:22:00.000000000",
+                    "2025-06-05T16:23:00.000000000",
+                    "2025-06-05T16:24:00.000000000",
+                    "2025-06-05T16:25:00.000000000",
+                    "2025-06-05T16:26:00.000000000",
+                    "2025-06-05T16:27:00.000000000",
+                    "2025-06-05T16:28:00.000000000",
+                    "2025-06-05T16:29:00.000000000",
+                    "2025-06-05T16:30:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T16:32:00.000000000",
+                    "2025-06-05T16:33:00.000000000",
+                    "2025-06-05T16:34:00.000000000",
+                    "2025-06-05T16:35:00.000000000",
+                    "2025-06-05T16:36:00.000000000",
+                    "2025-06-05T16:37:00.000000000",
+                    "2025-06-05T16:38:00.000000000",
+                    "2025-06-05T16:39:00.000000000",
+                    "2025-06-05T16:40:00.000000000",
+                    "2025-06-05T16:41:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T16:43:00.000000000",
+                    "2025-06-05T16:44:00.000000000",
+                    "2025-06-05T16:45:00.000000000",
+                    "2025-06-05T16:46:00.000000000",
+                    "2025-06-05T16:47:00.000000000",
+                    "2025-06-05T16:48:00.000000000",
+                    "2025-06-05T16:49:00.000000000",
+                    "2025-06-05T16:50:00.000000000",
+                    "2025-06-05T16:51:00.000000000",
+                    "2025-06-05T16:52:00.000000000",
+                    "2025-06-05T16:53:00.000000000",
+                    "2025-06-05T16:54:00.000000000",
+                    "2025-06-05T16:55:00.000000000",
+                    "2025-06-05T16:56:00.000000000",
+                    "2025-06-05T16:57:00.000000000",
+                    "2025-06-05T16:58:00.000000000",
+                    "2025-06-05T16:59:00.000000000",
+                    "2025-06-05T17:00:00.000000000",
+                    "2025-06-05T17:01:00.000000000",
+                    "2025-06-05T17:02:00.000000000",
+                    "2025-06-05T17:03:00.000000000",
+                    "2025-06-05T17:04:00.000000000",
+                    "2025-06-05T17:05:00.000000000",
+                    "2025-06-05T17:06:00.000000000",
+                    "2025-06-05T17:07:00.000000000",
+                    "2025-06-05T17:08:00.000000000",
+                    "2025-06-05T17:09:00.000000000",
+                    "2025-06-05T17:10:00.000000000",
+                    "2025-06-05T17:11:00.000000000",
+                    "2025-06-05T17:12:00.000000000",
+                    "2025-06-05T17:13:00.000000000",
+                    "2025-06-05T17:14:00.000000000",
+                    "2025-06-05T17:15:00.000000000",
+                    "2025-06-05T17:16:00.000000000",
+                    "2025-06-05T17:17:00.000000000",
+                    "2025-06-05T17:18:00.000000000",
+                    "2025-06-05T17:19:00.000000000",
+                    "2025-06-05T17:20:00.000000000",
+                    "2025-06-05T17:21:00.000000000",
+                    "2025-06-05T17:22:00.000000000",
+                    "2025-06-05T17:23:00.000000000",
+                    "2025-06-05T17:24:00.000000000",
+                    "2025-06-05T17:25:00.000000000",
+                    "2025-06-05T17:26:00.000000000",
+                    "2025-06-05T17:27:00.000000000",
+                    "2025-06-05T17:28:00.000000000",
+                    "2025-06-05T17:29:00.000000000",
+                    "2025-06-05T17:30:00.000000000",
+                    "2025-06-05T17:31:00.000000000",
+                    "2025-06-05T17:32:00.000000000",
+                    "2025-06-05T17:33:00.000000000",
+                    "2025-06-05T17:34:00.000000000",
+                    "2025-06-05T17:35:00.000000000",
+                    "2025-06-05T17:36:00.000000000",
+                    "2025-06-05T17:37:00.000000000",
+                    "2025-06-05T17:38:00.000000000",
+                    "2025-06-05T17:39:00.000000000",
+                    "2025-06-05T17:40:00.000000000",
+                    "2025-06-05T17:41:00.000000000",
+                    "2025-06-05T17:42:00.000000000",
+                    "2025-06-05T17:43:00.000000000",
+                    "2025-06-05T17:44:00.000000000",
+                    "2025-06-05T17:45:00.000000000",
+                    "2025-06-05T17:46:00.000000000",
+                    "2025-06-05T17:47:00.000000000",
+                    "2025-06-05T17:48:00.000000000",
+                    "2025-06-05T17:49:00.000000000",
+                    "2025-06-05T17:50:00.000000000",
+                    "2025-06-05T17:51:00.000000000",
+                    "2025-06-05T17:52:00.000000000",
+                    "2025-06-05T17:53:00.000000000",
+                    "2025-06-05T17:54:00.000000000",
+                    "2025-06-05T17:55:00.000000000",
+                    "2025-06-05T17:56:00.000000000",
+                    "2025-06-05T17:57:00.000000000",
+                    "2025-06-05T17:58:00.000000000",
+                    "2025-06-05T17:59:00.000000000",
+                    "2025-06-05T18:00:00.000000000",
+                    "2025-06-05T18:01:00.000000000",
+                    "2025-06-05T18:02:00.000000000",
+                    "2025-06-05T18:03:00.000000000",
+                    "2025-06-05T18:04:00.000000000",
+                    "2025-06-05T18:05:00.000000000",
+                    "2025-06-05T18:06:00.000000000",
+                    "2025-06-05T18:07:00.000000000",
+                    "2025-06-05T18:08:00.000000000",
+                    "2025-06-05T18:09:00.000000000",
+                    "2025-06-05T18:10:00.000000000",
+                    "2025-06-05T18:11:00.000000000",
+                    "2025-06-05T18:12:00.000000000",
+                    "2025-06-05T18:13:00.000000000",
+                    "2025-06-05T18:14:00.000000000",
+                    "2025-06-05T18:15:00.000000000",
+                    "2025-06-05T18:16:00.000000000",
+                    "2025-06-05T18:17:00.000000000",
+                    "2025-06-05T18:18:00.000000000",
+                    "2025-06-05T18:19:00.000000000",
+                    "2025-06-05T18:20:00.000000000",
+                    "2025-06-05T18:21:00.000000000",
+                    "2025-06-05T18:22:00.000000000",
+                    "2025-06-05T18:23:00.000000000",
+                    "2025-06-05T18:24:00.000000000",
+                    "2025-06-05T18:25:00.000000000",
+                    "2025-06-05T18:26:00.000000000",
+                    "2025-06-05T18:27:00.000000000",
+                    "2025-06-05T18:28:00.000000000",
+                    "2025-06-05T18:29:00.000000000",
+                    "2025-06-05T18:30:00.000000000",
+                    "2025-06-05T18:31:00.000000000",
+                    "2025-06-05T18:32:00.000000000",
+                    "2025-06-05T18:33:00.000000000",
+                    "2025-06-05T18:34:00.000000000",
+                    "2025-06-05T18:35:00.000000000",
+                    "2025-06-05T18:36:00.000000000",
+                    "2025-06-05T18:37:00.000000000",
+                    "2025-06-05T18:38:00.000000000",
+                    "2025-06-05T18:39:00.000000000",
+                    "2025-06-05T18:40:00.000000000",
+                    "2025-06-05T18:41:00.000000000",
+                    "2025-06-05T18:42:00.000000000",
+                    "2025-06-05T18:43:00.000000000",
+                    "2025-06-05T18:44:00.000000000",
+                    "2025-06-05T18:45:00.000000000",
+                    "2025-06-05T18:46:00.000000000",
+                    "2025-06-05T18:47:00.000000000",
+                    "2025-06-05T18:48:00.000000000",
+                    "2025-06-05T18:49:00.000000000",
+                    "2025-06-05T18:50:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T18:52:00.000000000",
+                    "2025-06-05T18:53:00.000000000",
+                    "2025-06-05T18:54:00.000000000",
+                    "2025-06-05T18:55:00.000000000",
+                    "2025-06-05T18:56:00.000000000",
+                    "2025-06-05T18:57:00.000000000",
+                    "2025-06-05T18:58:00.000000000",
+                    "2025-06-05T18:59:00.000000000",
+                    "2025-06-05T19:00:00.000000000",
+                    "2025-06-05T19:01:00.000000000",
+                    "2025-06-05T19:02:00.000000000",
+                    "2025-06-05T19:03:00.000000000",
+                    "2025-06-05T19:04:00.000000000",
+                    "2025-06-05T19:05:00.000000000",
+                    "2025-06-05T19:06:00.000000000",
+                    "2025-06-05T19:07:00.000000000",
+                    "2025-06-05T19:08:00.000000000",
+                    "2025-06-05T19:09:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:11:00.000000000",
+                    "2025-06-05T19:12:00.000000000",
+                    "2025-06-05T19:13:00.000000000",
+                    "2025-06-05T19:14:00.000000000",
+                    "2025-06-05T19:15:00.000000000",
+                    "2025-06-05T19:16:00.000000000",
+                    "2025-06-05T19:17:00.000000000",
+                    "2025-06-05T19:18:00.000000000",
+                    "2025-06-05T19:19:00.000000000",
+                    "2025-06-05T19:20:00.000000000",
+                    "2025-06-05T19:21:00.000000000",
+                    "2025-06-05T19:22:00.000000000",
+                    "2025-06-05T19:23:00.000000000",
+                    "2025-06-05T19:24:00.000000000",
+                    "2025-06-05T19:25:00.000000000",
+                    "2025-06-05T19:26:00.000000000",
+                    "2025-06-05T19:27:00.000000000",
+                    "2025-06-05T19:28:00.000000000",
+                    "2025-06-05T19:29:00.000000000",
+                    "2025-06-05T19:30:00.000000000",
+                    "2025-06-05T19:31:00.000000000",
+                    "2025-06-05T19:32:00.000000000",
+                    "2025-06-05T19:33:00.000000000",
+                    "2025-06-05T19:34:00.000000000",
+                    "2025-06-05T19:35:00.000000000",
+                    "2025-06-05T19:36:00.000000000",
+                    "2025-06-05T19:37:00.000000000",
+                    "2025-06-05T19:38:00.000000000",
+                    "2025-06-05T19:39:00.000000000",
+                    "2025-06-05T19:40:00.000000000",
+                    "2025-06-05T19:41:00.000000000",
+                    "2025-06-05T19:42:00.000000000",
+                    "2025-06-05T19:43:00.000000000",
+                    "2025-06-05T19:44:00.000000000",
+                    "2025-06-05T19:45:00.000000000",
+                    "2025-06-05T19:46:00.000000000",
+                    "2025-06-05T19:47:00.000000000",
+                    "2025-06-05T19:48:00.000000000",
+                    "2025-06-05T19:49:00.000000000",
+                    "2025-06-05T19:50:00.000000000",
+                    "2025-06-05T19:51:00.000000000",
+                    "2025-06-05T19:52:00.000000000",
+                    "2025-06-05T19:53:00.000000000",
+                    "2025-06-05T19:54:00.000000000",
+                    "2025-06-05T19:55:00.000000000",
+                    "2025-06-05T19:56:00.000000000",
+                    "2025-06-05T19:57:00.000000000",
+                    "2025-06-05T19:58:00.000000000",
+                    "2025-06-05T19:59:00.000000000",
+                    "2025-06-05T20:00:00.000000000"
+                  ],
+                  "xaxis": "x4",
+                  "y": {
+                    "bdata": "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",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y4"
+                },
+                {
+                  "marker": {
+                    "color": "red",
+                    "size": 12,
+                    "symbol": "triangle-up"
+                  },
+                  "mode": "markers",
+                  "name": "MSTR BUY OPEN",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T15:40:00.000000000",
+                    "2025-06-05T16:31:00.000000000",
+                    "2025-06-05T18:51:00.000000000",
+                    "2025-06-05T19:15:00.000000000"
+                  ],
+                  "xaxis": "x4",
+                  "y": {
+                    "bdata": "FK5H4XrId0AAAAAAAJR3QGZmZmZmRndAmpmZmZkDd0A=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y4"
+                },
+                {
+                  "marker": {
+                    "color": "pink",
+                    "size": 12,
+                    "symbol": "triangle-up"
+                  },
+                  "mode": "markers",
+                  "name": "MSTR BUY CLOSE",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T17:34:00.000000000"
+                  ],
+                  "xaxis": "x4",
+                  "y": {
+                    "bdata": "AAAAAABwd0A=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y4"
+                },
+                {
+                  "marker": {
+                    "color": "blue",
+                    "size": 12,
+                    "symbol": "triangle-down"
+                  },
+                  "mode": "markers",
+                  "name": "MSTR SELL OPEN",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T16:46:00.000000000"
+                  ],
+                  "xaxis": "x4",
+                  "y": {
+                    "bdata": "PZtVn6uBd0A=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y4"
+                },
+                {
+                  "marker": {
+                    "color": "purple",
+                    "size": 12,
+                    "symbol": "triangle-down"
+                  },
+                  "mode": "markers",
+                  "name": "MSTR SELL CLOSE",
+                  "showlegend": true,
+                  "type": "scatter",
+                  "x": [
+                    "2025-06-05T16:02:00.000000000",
+                    "2025-06-05T16:42:00.000000000",
+                    "2025-06-05T19:10:00.000000000",
+                    "2025-06-05T19:16:00.000000000"
+                  ],
+                  "xaxis": "x4",
+                  "y": {
+                    "bdata": "5fIf0m++d0DhehSuR3l3QMP1KFyPKndA7FG4HoXzdkA=",
+                    "dtype": "f8"
+                  },
+                  "yaxis": "y4"
+                }
+              ],
+              "layout": {
+                "annotations": [
+                  {
+                    "font": {
+                      "size": 16
+                    },
+                    "showarrow": false,
+                    "text": "Testing Period: Scaled Dis-equilibrium with Trading Thresholds",
+                    "x": 0.5,
+                    "xanchor": "center",
+                    "xref": "paper",
+                    "y": 1,
+                    "yanchor": "bottom",
+                    "yref": "paper"
+                  },
+                  {
+                    "font": {
+                      "size": 16
+                    },
+                    "showarrow": false,
+                    "text": "Trading Signal Timeline",
+                    "x": 0.5,
+                    "xanchor": "center",
+                    "xref": "paper",
+                    "y": 0.7350000000000001,
+                    "yanchor": "bottom",
+                    "yref": "paper"
+                  },
+                  {
+                    "font": {
+                      "size": 16
+                    },
+                    "showarrow": false,
+                    "text": "COIN Market Data with Trading Signals",
+                    "x": 0.5,
+                    "xanchor": "center",
+                    "xref": "paper",
+                    "y": 0.47000000000000003,
+                    "yanchor": "bottom",
+                    "yref": "paper"
+                  },
+                  {
+                    "font": {
+                      "size": 16
+                    },
+                    "showarrow": false,
+                    "text": "MSTR Market Data with Trading Signals",
+                    "x": 0.5,
+                    "xanchor": "center",
+                    "xref": "paper",
+                    "y": 0.20500000000000002,
+                    "yanchor": "bottom",
+                    "yref": "paper"
+                  }
+                ],
+                "height": 1200,
+                "shapes": [
+                  {
+                    "line": {
+                      "color": "purple",
+                      "dash": "dot",
+                      "width": 2
+                    },
+                    "opacity": 0.7,
+                    "type": "line",
+                    "x0": "2025-06-05T13:30:00",
+                    "x1": "2025-06-05T20:00:00",
+                    "xref": "x",
+                    "y0": 2,
+                    "y1": 2,
+                    "yref": "y"
+                  },
+                  {
+                    "line": {
+                      "color": "purple",
+                      "dash": "dot",
+                      "width": 2
+                    },
+                    "opacity": 0.7,
+                    "type": "line",
+                    "x0": "2025-06-05T13:30:00",
+                    "x1": "2025-06-05T20:00:00",
+                    "xref": "x",
+                    "y0": -2,
+                    "y1": -2,
+                    "yref": "y"
+                  },
+                  {
+                    "line": {
+                      "color": "brown",
+                      "dash": "dot",
+                      "width": 2
+                    },
+                    "opacity": 0.7,
+                    "type": "line",
+                    "x0": "2025-06-05T13:30:00",
+                    "x1": "2025-06-05T20:00:00",
+                    "xref": "x",
+                    "y0": 1,
+                    "y1": 1,
+                    "yref": "y"
+                  },
+                  {
+                    "line": {
+                      "color": "brown",
+                      "dash": "dot",
+                      "width": 2
+                    },
+                    "opacity": 0.7,
+                    "type": "line",
+                    "x0": "2025-06-05T13:30:00",
+                    "x1": "2025-06-05T20:00:00",
+                    "xref": "x",
+                    "y0": -1,
+                    "y1": -1,
+                    "yref": "y"
+                  },
+                  {
+                    "line": {
+                      "color": "black",
+                      "dash": "solid",
+                      "width": 1
+                    },
+                    "opacity": 0.5,
+                    "type": "line",
+                    "x0": "2025-06-05T13:30:00",
+                    "x1": "2025-06-05T20:00:00",
+                    "xref": "x",
+                    "y0": 0,
+                    "y1": 0,
+                    "yref": "y"
+                  }
+                ],
+                "showlegend": true,
+                "template": {
+                  "data": {
+                    "bar": [
+                      {
+                        "error_x": {
+                          "color": "#2a3f5f"
+                        },
+                        "error_y": {
+                          "color": "#2a3f5f"
+                        },
+                        "marker": {
+                          "line": {
+                            "color": "white",
+                            "width": 0.5
+                          },
+                          "pattern": {
+                            "fillmode": "overlay",
+                            "size": 10,
+                            "solidity": 0.2
+                          }
+                        },
+                        "type": "bar"
+                      }
+                    ],
+                    "barpolar": [
+                      {
+                        "marker": {
+                          "line": {
+                            "color": "white",
+                            "width": 0.5
+                          },
+                          "pattern": {
+                            "fillmode": "overlay",
+                            "size": 10,
+                            "solidity": 0.2
+                          }
+                        },
+                        "type": "barpolar"
+                      }
+                    ],
+                    "carpet": [
+                      {
+                        "aaxis": {
+                          "endlinecolor": "#2a3f5f",
+                          "gridcolor": "#C8D4E3",
+                          "linecolor": "#C8D4E3",
+                          "minorgridcolor": "#C8D4E3",
+                          "startlinecolor": "#2a3f5f"
+                        },
+                        "baxis": {
+                          "endlinecolor": "#2a3f5f",
+                          "gridcolor": "#C8D4E3",
+                          "linecolor": "#C8D4E3",
+                          "minorgridcolor": "#C8D4E3",
+                          "startlinecolor": "#2a3f5f"
+                        },
+                        "type": "carpet"
+                      }
+                    ],
+                    "choropleth": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "type": "choropleth"
+                      }
+                    ],
+                    "contour": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "colorscale": [
+                          [
+                            0,
+                            "#0d0887"
+                          ],
+                          [
+                            0.1111111111111111,
+                            "#46039f"
+                          ],
+                          [
+                            0.2222222222222222,
+                            "#7201a8"
+                          ],
+                          [
+                            0.3333333333333333,
+                            "#9c179e"
+                          ],
+                          [
+                            0.4444444444444444,
+                            "#bd3786"
+                          ],
+                          [
+                            0.5555555555555556,
+                            "#d8576b"
+                          ],
+                          [
+                            0.6666666666666666,
+                            "#ed7953"
+                          ],
+                          [
+                            0.7777777777777778,
+                            "#fb9f3a"
+                          ],
+                          [
+                            0.8888888888888888,
+                            "#fdca26"
+                          ],
+                          [
+                            1,
+                            "#f0f921"
+                          ]
+                        ],
+                        "type": "contour"
+                      }
+                    ],
+                    "contourcarpet": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "type": "contourcarpet"
+                      }
+                    ],
+                    "heatmap": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "colorscale": [
+                          [
+                            0,
+                            "#0d0887"
+                          ],
+                          [
+                            0.1111111111111111,
+                            "#46039f"
+                          ],
+                          [
+                            0.2222222222222222,
+                            "#7201a8"
+                          ],
+                          [
+                            0.3333333333333333,
+                            "#9c179e"
+                          ],
+                          [
+                            0.4444444444444444,
+                            "#bd3786"
+                          ],
+                          [
+                            0.5555555555555556,
+                            "#d8576b"
+                          ],
+                          [
+                            0.6666666666666666,
+                            "#ed7953"
+                          ],
+                          [
+                            0.7777777777777778,
+                            "#fb9f3a"
+                          ],
+                          [
+                            0.8888888888888888,
+                            "#fdca26"
+                          ],
+                          [
+                            1,
+                            "#f0f921"
+                          ]
+                        ],
+                        "type": "heatmap"
+                      }
+                    ],
+                    "histogram": [
+                      {
+                        "marker": {
+                          "pattern": {
+                            "fillmode": "overlay",
+                            "size": 10,
+                            "solidity": 0.2
+                          }
+                        },
+                        "type": "histogram"
+                      }
+                    ],
+                    "histogram2d": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "colorscale": [
+                          [
+                            0,
+                            "#0d0887"
+                          ],
+                          [
+                            0.1111111111111111,
+                            "#46039f"
+                          ],
+                          [
+                            0.2222222222222222,
+                            "#7201a8"
+                          ],
+                          [
+                            0.3333333333333333,
+                            "#9c179e"
+                          ],
+                          [
+                            0.4444444444444444,
+                            "#bd3786"
+                          ],
+                          [
+                            0.5555555555555556,
+                            "#d8576b"
+                          ],
+                          [
+                            0.6666666666666666,
+                            "#ed7953"
+                          ],
+                          [
+                            0.7777777777777778,
+                            "#fb9f3a"
+                          ],
+                          [
+                            0.8888888888888888,
+                            "#fdca26"
+                          ],
+                          [
+                            1,
+                            "#f0f921"
+                          ]
+                        ],
+                        "type": "histogram2d"
+                      }
+                    ],
+                    "histogram2dcontour": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "colorscale": [
+                          [
+                            0,
+                            "#0d0887"
+                          ],
+                          [
+                            0.1111111111111111,
+                            "#46039f"
+                          ],
+                          [
+                            0.2222222222222222,
+                            "#7201a8"
+                          ],
+                          [
+                            0.3333333333333333,
+                            "#9c179e"
+                          ],
+                          [
+                            0.4444444444444444,
+                            "#bd3786"
+                          ],
+                          [
+                            0.5555555555555556,
+                            "#d8576b"
+                          ],
+                          [
+                            0.6666666666666666,
+                            "#ed7953"
+                          ],
+                          [
+                            0.7777777777777778,
+                            "#fb9f3a"
+                          ],
+                          [
+                            0.8888888888888888,
+                            "#fdca26"
+                          ],
+                          [
+                            1,
+                            "#f0f921"
+                          ]
+                        ],
+                        "type": "histogram2dcontour"
+                      }
+                    ],
+                    "mesh3d": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "type": "mesh3d"
+                      }
+                    ],
+                    "parcoords": [
+                      {
+                        "line": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "parcoords"
+                      }
+                    ],
+                    "pie": [
+                      {
+                        "automargin": true,
+                        "type": "pie"
+                      }
+                    ],
+                    "scatter": [
+                      {
+                        "fillpattern": {
+                          "fillmode": "overlay",
+                          "size": 10,
+                          "solidity": 0.2
+                        },
+                        "type": "scatter"
+                      }
+                    ],
+                    "scatter3d": [
+                      {
+                        "line": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scatter3d"
+                      }
+                    ],
+                    "scattercarpet": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scattercarpet"
+                      }
+                    ],
+                    "scattergeo": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scattergeo"
+                      }
+                    ],
+                    "scattergl": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scattergl"
+                      }
+                    ],
+                    "scattermap": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scattermap"
+                      }
+                    ],
+                    "scattermapbox": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scattermapbox"
+                      }
+                    ],
+                    "scatterpolar": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scatterpolar"
+                      }
+                    ],
+                    "scatterpolargl": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scatterpolargl"
+                      }
+                    ],
+                    "scatterternary": [
+                      {
+                        "marker": {
+                          "colorbar": {
+                            "outlinewidth": 0,
+                            "ticks": ""
+                          }
+                        },
+                        "type": "scatterternary"
+                      }
+                    ],
+                    "surface": [
+                      {
+                        "colorbar": {
+                          "outlinewidth": 0,
+                          "ticks": ""
+                        },
+                        "colorscale": [
+                          [
+                            0,
+                            "#0d0887"
+                          ],
+                          [
+                            0.1111111111111111,
+                            "#46039f"
+                          ],
+                          [
+                            0.2222222222222222,
+                            "#7201a8"
+                          ],
+                          [
+                            0.3333333333333333,
+                            "#9c179e"
+                          ],
+                          [
+                            0.4444444444444444,
+                            "#bd3786"
+                          ],
+                          [
+                            0.5555555555555556,
+                            "#d8576b"
+                          ],
+                          [
+                            0.6666666666666666,
+                            "#ed7953"
+                          ],
+                          [
+                            0.7777777777777778,
+                            "#fb9f3a"
+                          ],
+                          [
+                            0.8888888888888888,
+                            "#fdca26"
+                          ],
+                          [
+                            1,
+                            "#f0f921"
+                          ]
+                        ],
+                        "type": "surface"
+                      }
+                    ],
+                    "table": [
+                      {
+                        "cells": {
+                          "fill": {
+                            "color": "#EBF0F8"
+                          },
+                          "line": {
+                            "color": "white"
+                          }
+                        },
+                        "header": {
+                          "fill": {
+                            "color": "#C8D4E3"
+                          },
+                          "line": {
+                            "color": "white"
+                          }
+                        },
+                        "type": "table"
+                      }
+                    ]
+                  },
+                  "layout": {
+                    "annotationdefaults": {
+                      "arrowcolor": "#2a3f5f",
+                      "arrowhead": 0,
+                      "arrowwidth": 1
+                    },
+                    "autotypenumbers": "strict",
+                    "coloraxis": {
+                      "colorbar": {
+                        "outlinewidth": 0,
+                        "ticks": ""
+                      }
+                    },
+                    "colorscale": {
+                      "diverging": [
+                        [
+                          0,
+                          "#8e0152"
+                        ],
+                        [
+                          0.1,
+                          "#c51b7d"
+                        ],
+                        [
+                          0.2,
+                          "#de77ae"
+                        ],
+                        [
+                          0.3,
+                          "#f1b6da"
+                        ],
+                        [
+                          0.4,
+                          "#fde0ef"
+                        ],
+                        [
+                          0.5,
+                          "#f7f7f7"
+                        ],
+                        [
+                          0.6,
+                          "#e6f5d0"
+                        ],
+                        [
+                          0.7,
+                          "#b8e186"
+                        ],
+                        [
+                          0.8,
+                          "#7fbc41"
+                        ],
+                        [
+                          0.9,
+                          "#4d9221"
+                        ],
+                        [
+                          1,
+                          "#276419"
+                        ]
+                      ],
+                      "sequential": [
+                        [
+                          0,
+                          "#0d0887"
+                        ],
+                        [
+                          0.1111111111111111,
+                          "#46039f"
+                        ],
+                        [
+                          0.2222222222222222,
+                          "#7201a8"
+                        ],
+                        [
+                          0.3333333333333333,
+                          "#9c179e"
+                        ],
+                        [
+                          0.4444444444444444,
+                          "#bd3786"
+                        ],
+                        [
+                          0.5555555555555556,
+                          "#d8576b"
+                        ],
+                        [
+                          0.6666666666666666,
+                          "#ed7953"
+                        ],
+                        [
+                          0.7777777777777778,
+                          "#fb9f3a"
+                        ],
+                        [
+                          0.8888888888888888,
+                          "#fdca26"
+                        ],
+                        [
+                          1,
+                          "#f0f921"
+                        ]
+                      ],
+                      "sequentialminus": [
+                        [
+                          0,
+                          "#0d0887"
+                        ],
+                        [
+                          0.1111111111111111,
+                          "#46039f"
+                        ],
+                        [
+                          0.2222222222222222,
+                          "#7201a8"
+                        ],
+                        [
+                          0.3333333333333333,
+                          "#9c179e"
+                        ],
+                        [
+                          0.4444444444444444,
+                          "#bd3786"
+                        ],
+                        [
+                          0.5555555555555556,
+                          "#d8576b"
+                        ],
+                        [
+                          0.6666666666666666,
+                          "#ed7953"
+                        ],
+                        [
+                          0.7777777777777778,
+                          "#fb9f3a"
+                        ],
+                        [
+                          0.8888888888888888,
+                          "#fdca26"
+                        ],
+                        [
+                          1,
+                          "#f0f921"
+                        ]
+                      ]
+                    },
+                    "colorway": [
+                      "#636efa",
+                      "#EF553B",
+                      "#00cc96",
+                      "#ab63fa",
+                      "#FFA15A",
+                      "#19d3f3",
+                      "#FF6692",
+                      "#B6E880",
+                      "#FF97FF",
+                      "#FECB52"
+                    ],
+                    "font": {
+                      "color": "#2a3f5f"
+                    },
+                    "geo": {
+                      "bgcolor": "white",
+                      "lakecolor": "white",
+                      "landcolor": "white",
+                      "showlakes": true,
+                      "showland": true,
+                      "subunitcolor": "#C8D4E3"
+                    },
+                    "hoverlabel": {
+                      "align": "left"
+                    },
+                    "hovermode": "closest",
+                    "mapbox": {
+                      "style": "light"
+                    },
+                    "paper_bgcolor": "white",
+                    "plot_bgcolor": "white",
+                    "polar": {
+                      "angularaxis": {
+                        "gridcolor": "#EBF0F8",
+                        "linecolor": "#EBF0F8",
+                        "ticks": ""
+                      },
+                      "bgcolor": "white",
+                      "radialaxis": {
+                        "gridcolor": "#EBF0F8",
+                        "linecolor": "#EBF0F8",
+                        "ticks": ""
+                      }
+                    },
+                    "scene": {
+                      "xaxis": {
+                        "backgroundcolor": "white",
+                        "gridcolor": "#DFE8F3",
+                        "gridwidth": 2,
+                        "linecolor": "#EBF0F8",
+                        "showbackground": true,
+                        "ticks": "",
+                        "zerolinecolor": "#EBF0F8"
+                      },
+                      "yaxis": {
+                        "backgroundcolor": "white",
+                        "gridcolor": "#DFE8F3",
+                        "gridwidth": 2,
+                        "linecolor": "#EBF0F8",
+                        "showbackground": true,
+                        "ticks": "",
+                        "zerolinecolor": "#EBF0F8"
+                      },
+                      "zaxis": {
+                        "backgroundcolor": "white",
+                        "gridcolor": "#DFE8F3",
+                        "gridwidth": 2,
+                        "linecolor": "#EBF0F8",
+                        "showbackground": true,
+                        "ticks": "",
+                        "zerolinecolor": "#EBF0F8"
+                      }
+                    },
+                    "shapedefaults": {
+                      "line": {
+                        "color": "#2a3f5f"
+                      }
+                    },
+                    "ternary": {
+                      "aaxis": {
+                        "gridcolor": "#DFE8F3",
+                        "linecolor": "#A2B1C6",
+                        "ticks": ""
+                      },
+                      "baxis": {
+                        "gridcolor": "#DFE8F3",
+                        "linecolor": "#A2B1C6",
+                        "ticks": ""
+                      },
+                      "bgcolor": "white",
+                      "caxis": {
+                        "gridcolor": "#DFE8F3",
+                        "linecolor": "#A2B1C6",
+                        "ticks": ""
+                      }
+                    },
+                    "title": {
+                      "x": 0.05
+                    },
+                    "xaxis": {
+                      "automargin": true,
+                      "gridcolor": "#EBF0F8",
+                      "linecolor": "#EBF0F8",
+                      "ticks": "",
+                      "title": {
+                        "standoff": 15
+                      },
+                      "zerolinecolor": "#EBF0F8",
+                      "zerolinewidth": 2
+                    },
+                    "yaxis": {
+                      "automargin": true,
+                      "gridcolor": "#EBF0F8",
+                      "linecolor": "#EBF0F8",
+                      "ticks": "",
+                      "title": {
+                        "standoff": 15
+                      },
+                      "zerolinecolor": "#EBF0F8",
+                      "zerolinewidth": 2
+                    }
+                  }
+                },
+                "title": {
+                  "text": "Sliding Fit Strategy Analysis - COIN & MSTR"
+                },
+                "xaxis": {
+                  "anchor": "y",
+                  "domain": [
+                    0,
+                    1
+                  ],
+                  "range": [
+                    "2025-06-05T13:30:00",
+                    "2025-06-05T20:00:00"
+                  ]
+                },
+                "xaxis2": {
+                  "anchor": "y2",
+                  "domain": [
+                    0,
+                    1
+                  ],
+                  "range": [
+                    "2025-06-05T13:30:00",
+                    "2025-06-05T20:00:00"
+                  ]
+                },
+                "xaxis3": {
+                  "anchor": "y3",
+                  "domain": [
+                    0,
+                    1
+                  ],
+                  "range": [
+                    "2025-06-05T13:30:00",
+                    "2025-06-05T20:00:00"
+                  ]
+                },
+                "xaxis4": {
+                  "anchor": "y4",
+                  "domain": [
+                    0,
+                    1
+                  ],
+                  "range": [
+                    "2025-06-05T13:30:00",
+                    "2025-06-05T20:00:00"
+                  ],
+                  "title": {
+                    "text": "Time"
+                  }
+                },
+                "yaxis": {
+                  "anchor": "x",
+                  "domain": [
+                    0.7949999999999999,
+                    1
+                  ],
+                  "title": {
+                    "text": "Scaled Dis-equilibrium"
+                  }
+                },
+                "yaxis2": {
+                  "anchor": "x2",
+                  "domain": [
+                    0.53,
+                    0.7350000000000001
+                  ],
+                  "title": {
+                    "text": "Signal Index"
+                  }
+                },
+                "yaxis3": {
+                  "anchor": "x3",
+                  "domain": [
+                    0.265,
+                    0.47000000000000003
+                  ],
+                  "title": {
+                    "text": "COIN Price ($)"
+                  }
+                },
+                "yaxis4": {
+                  "anchor": "x4",
+                  "domain": [
+                    0,
+                    0.20500000000000002
+                  ],
+                  "title": {
+                    "text": "MSTR Price ($)"
+                  }
+                }
+              }
+            },
+            "text/html": [
+              "<div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
+              "        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-3.0.1.min.js\" integrity=\"sha256-oy6Be7Eh6eiQFs5M7oXuPxxm9qbJXEtTpfSI93dW16Q=\" crossorigin=\"anonymous\"></script>                <div id=\"4263a8ce-d351-4fe5-97dc-bf5209fc340a\" class=\"plotly-graph-div\" style=\"height:1200px; width:100%;\"></div>            <script type=\"text/javascript\">                window.PLOTLYENV=window.PLOTLYENV || {};                                if (document.getElementById(\"4263a8ce-d351-4fe5-97dc-bf5209fc340a\")) {                    Plotly.newPlot(                        \"4263a8ce-d351-4fe5-97dc-bf5209fc340a\",                        [{\"line\":{\"color\":\"green\",\"width\":2},\"name\":\"Scaled Dis-equilibrium\",\"opacity\":0.8,\"x\":[\"2025-06-05T13:30:00.000000000\",\"2025-06-05T13:31:00.000000000\",\"2025-06-05T13:32:00.000000000\",\"2025-06-05T13:33:00.000000000\",\"2025-06-05T13:34:00.000000000\",\"2025-06-05T13:35:00.000000000\",\"2025-06-05T13:36:00.000000000\",\"2025-06-05T13:37:00.000000000\",\"2025-06-05T13:38:00.000000000\",\"2025-06-05T13:39:00.000000000\",\"2025-06-05T13:40:00.000000000\",\"2025-06-05T13:41:00.000000000\",\"2025-06-05T13:42:00.000000000\",\"2025-06-05T13:43:00.000000000\",\"2025-06-05T13:44:00.000000000\",\"2025-06-05T13:45:00.000000000\",\"2025-06-05T13:46:00.000000000\",\"2025-06-05T13:47:00.000000000\",\"2025-06-05T13:48:00.000000000\",\"2025-06-05T13:49:00.000000000\",\"2025-06-05T13:50:00.000000000\",\"2025-06-05T13:51:00.000000000\",\"2025-06-05T13:52:00.000000000\",\"2025-06-05T13:53:00.000000000\",\"2025-06-05T13:54:00.000000000\",\"2025-06-05T13:55:00.000000000\",\"2025-06-05T13:56:00.000000000\",\"2025-06-05T13:57:00.000000000\",\"2025-06-05T13:58:00.000000000\",\"2025-06-05T13:59:00.000000000\",\"2025-06-05T14:00:00.000000000\",\"2025-06-05T14:01:00.000000000\",\"2025-06-05T14:02:00.000000000\",\"2025-06-05T14:03:00.000000000\",\"2025-06-05T14:04:00.000000000\",\"2025-06-05T14:05:00.000000000\",\"2025-06-05T14:06:00.000000000\",\"2025-06-05T14:07:00.000000000\",\"2025-06-05T14:08:00.000000000\",\"2025-06-05T14:09:00.000000000\",\"2025-06-05T14:10:00.000000000\",\"2025-06-05T14:11:00.000000000\",\"2025-06-05T14:12:00.000000000\",\"2025-06-05T14:13:00.000000000\",\"2025-06-05T14:14:00.000000000\",\"2025-06-05T14:15:00.000000000\",\"2025-06-05T14:16:00.000000000\",\"2025-06-05T14:17:00.000000000\",\"2025-06-05T14:18:00.000000000\",\"2025-06-05T14:19:00.000000000\",\"2025-06-05T14:20:00.000000000\",\"2025-06-05T14:21:00.000000000\",\"2025-06-05T14:22:00.000000000\",\"2025-06-05T14:23:00.000000000\",\"2025-06-05T14:24:00.000000000\",\"2025-06-05T14:25:00.000000000\",\"2025-06-05T14:26:00.000000000\",\"2025-06-05T14:27:00.000000000\",\"2025-06-05T14:28:00.000000000\",\"2025-06-05T14:29:00.000000000\",\"2025-06-05T14:30:00.000000000\",\"2025-06-05T14:31:00.000000000\",\"2025-06-05T14:32:00.000000000\",\"2025-06-05T14:33:00.000000000\",\"2025-06-05T14:34:00.000000000\",\"2025-06-05T14:35:00.000000000\",\"2025-06-05T14:36:00.000000000\",\"2025-06-05T14:37:00.000000000\",\"2025-06-05T14:38:00.000000000\",\"2025-06-05T14:39:00.000000000\",\"2025-06-05T14:40:00.000000000\",\"2025-06-05T14:41:00.000000000\",\"2025-06-05T14:42:00.000000000\",\"2025-06-05T14:43:00.000000000\",\"2025-06-05T14:44:00.000000000\",\"2025-06-05T14:45:00.000000000\",\"2025-06-05T14:46:00.000000000\",\"2025-06-05T14:47:00.000000000\",\"2025-06-05T14:48:00.000000000\",\"2025-06-05T14:49:00.000000000\",\"2025-06-05T14:50:00.000000000\",\"2025-06-05T14:51:00.000000000\",\"2025-06-05T14:52:00.000000000\",\"2025-06-05T14:53:00.000000000\",\"2025-06-05T14:54:00.000000000\",\"2025-06-05T14:55:00.000000000\",\"2025-06-05T14:56:00.000000000\",\"2025-06-05T14:57:00.000000000\",\"2025-06-05T14:58:00.000000000\",\"2025-06-05T14:59:00.000000000\",\"2025-06-05T15:00:00.000000000\",\"2025-06-05T15:01:00.000000000\",\"2025-06-05T15:02:00.000000000\",\"2025-06-05T15:03:00.000000000\",\"2025-06-05T15:04:00.000000000\",\"2025-06-05T15:05:00.000000000\",\"2025-06-05T15:06:00.000000000\",\"2025-06-05T15:07:00.000000000\",\"2025-06-05T15:08:00.000000000\",\"2025-06-05T15:09:00.000000000\",\"2025-06-05T15:10:00.000000000\",\"2025-06-05T15:11:00.000000000\",\"2025-06-05T15:12:00.000000000\",\"2025-06-05T15:13:00.000000000\",\"2025-06-05T15:14:00.000000000\",\"2025-06-05T15:15:00.000000000\",\"2025-06-05T15:16:00.000000000\",\"2025-06-05T15:17:00.000000000\",\"2025-06-05T15:18:00.000000000\",\"2025-06-05T15:19:00.000000000\",\"2025-06-05T15:20:00.000000000\",\"2025-06-05T15:21:00.000000000\",\"2025-06-05T15:22:00.000000000\",\"2025-06-05T15:23:00.000000000\",\"2025-06-05T15:24:00.000000000\",\"2025-06-05T15:25:00.000000000\",\"2025-06-05T15:26:00.000000000\",\"2025-06-05T15:27:00.000000000\",\"2025-06-05T15:28:00.000000000\",\"2025-06-05T15:29:00.000000000\",\"2025-06-05T15:30:00.000000000\",\"2025-06-05T15:31:00.000000000\",\"2025-06-05T15:32:00.000000000\",\"2025-06-05T15:33:00.000000000\",\"2025-06-05T15:34:00.000000000\",\"2025-06-05T15:35:00.000000000\",\"2025-06-05T15:36:00.000000000\",\"2025-06-05T15:37:00.000000000\",\"2025-06-05T15:38:00.000000000\",\"2025-06-05T15:39:00.000000000\",\"2025-06-05T15:40:00.000000000\",\"2025-06-05T15:41:00.000000000\",\"2025-06-05T15:42:00.000000000\",\"2025-06-05T15:43:00.000000000\",\"2025-06-05T15:44:00.000000000\",\"2025-06-05T15:45:00.000000000\",\"2025-06-05T15:46:00.000000000\",\"2025-06-05T15:47:00.000000000\",\"2025-06-05T15:48:00.000000000\",\"2025-06-05T15:49:00.000000000\",\"2025-06-05T15:50:00.000000000\",\"2025-06-05T15:51:00.000000000\",\"2025-06-05T15:52:00.000000000\",\"2025-06-05T15:53:00.000000000\",\"2025-06-05T15:54:00.000000000\",\"2025-06-05T15:55:00.000000000\",\"2025-06-05T15:56:00.000000000\",\"2025-06-05T15:57:00.000000000\",\"2025-06-05T15:58:00.000000000\",\"2025-06-05T15:59:00.000000000\",\"2025-06-05T16:00:00.000000000\",\"2025-06-05T16:01:00.000000000\",\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:03:00.000000000\",\"2025-06-05T16:04:00.000000000\",\"2025-06-05T16:05:00.000000000\",\"2025-06-05T16:06:00.000000000\",\"2025-06-05T16:07:00.000000000\",\"2025-06-05T16:08:00.000000000\",\"2025-06-05T16:09:00.000000000\",\"2025-06-05T16:10:00.000000000\",\"2025-06-05T16:11:00.000000000\",\"2025-06-05T16:12:00.000000000\",\"2025-06-05T16:13:00.000000000\",\"2025-06-05T16:14:00.000000000\",\"2025-06-05T16:15:00.000000000\",\"2025-06-05T16:16:00.000000000\",\"2025-06-05T16:17:00.000000000\",\"2025-06-05T16:18:00.000000000\",\"2025-06-05T16:19:00.000000000\",\"2025-06-05T16:20:00.000000000\",\"2025-06-05T16:21:00.000000000\",\"2025-06-05T16:22:00.000000000\",\"2025-06-05T16:23:00.000000000\",\"2025-06-05T16:24:00.000000000\",\"2025-06-05T16:25:00.000000000\",\"2025-06-05T16:26:00.000000000\",\"2025-06-05T16:27:00.000000000\",\"2025-06-05T16:28:00.000000000\",\"2025-06-05T16:29:00.000000000\",\"2025-06-05T16:30:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T16:32:00.000000000\",\"2025-06-05T16:33:00.000000000\",\"2025-06-05T16:34:00.000000000\",\"2025-06-05T16:35:00.000000000\",\"2025-06-05T16:36:00.000000000\",\"2025-06-05T16:37:00.000000000\",\"2025-06-05T16:38:00.000000000\",\"2025-06-05T16:39:00.000000000\",\"2025-06-05T16:40:00.000000000\",\"2025-06-05T16:41:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T16:43:00.000000000\",\"2025-06-05T16:44:00.000000000\",\"2025-06-05T16:45:00.000000000\",\"2025-06-05T16:46:00.000000000\",\"2025-06-05T16:47:00.000000000\",\"2025-06-05T16:48:00.000000000\",\"2025-06-05T16:49:00.000000000\",\"2025-06-05T16:50:00.000000000\",\"2025-06-05T16:51:00.000000000\",\"2025-06-05T16:52:00.000000000\",\"2025-06-05T16:53:00.000000000\",\"2025-06-05T16:54:00.000000000\",\"2025-06-05T16:55:00.000000000\",\"2025-06-05T16:56:00.000000000\",\"2025-06-05T16:57:00.000000000\",\"2025-06-05T16:58:00.000000000\",\"2025-06-05T16:59:00.000000000\",\"2025-06-05T17:00:00.000000000\",\"2025-06-05T17:01:00.000000000\",\"2025-06-05T17:02:00.000000000\",\"2025-06-05T17:03:00.000000000\",\"2025-06-05T17:04:00.000000000\",\"2025-06-05T17:05:00.000000000\",\"2025-06-05T17:06:00.000000000\",\"2025-06-05T17:07:00.000000000\",\"2025-06-05T17:08:00.000000000\",\"2025-06-05T17:09:00.000000000\",\"2025-06-05T17:10:00.000000000\",\"2025-06-05T17:11:00.000000000\",\"2025-06-05T17:12:00.000000000\",\"2025-06-05T17:13:00.000000000\",\"2025-06-05T17:14:00.000000000\",\"2025-06-05T17:15:00.000000000\",\"2025-06-05T17:16:00.000000000\",\"2025-06-05T17:17:00.000000000\",\"2025-06-05T17:18:00.000000000\",\"2025-06-05T17:19:00.000000000\",\"2025-06-05T17:20:00.000000000\",\"2025-06-05T17:21:00.000000000\",\"2025-06-05T17:22:00.000000000\",\"2025-06-05T17:23:00.000000000\",\"2025-06-05T17:24:00.000000000\",\"2025-06-05T17:25:00.000000000\",\"2025-06-05T17:26:00.000000000\",\"2025-06-05T17:27:00.000000000\",\"2025-06-05T17:28:00.000000000\",\"2025-06-05T17:29:00.000000000\",\"2025-06-05T17:30:00.000000000\",\"2025-06-05T17:31:00.000000000\",\"2025-06-05T17:32:00.000000000\",\"2025-06-05T17:33:00.000000000\",\"2025-06-05T17:34:00.000000000\",\"2025-06-05T17:35:00.000000000\",\"2025-06-05T17:36:00.000000000\",\"2025-06-05T17:37:00.000000000\",\"2025-06-05T17:38:00.000000000\",\"2025-06-05T17:39:00.000000000\",\"2025-06-05T17:40:00.000000000\",\"2025-06-05T17:41:00.000000000\",\"2025-06-05T17:42:00.000000000\",\"2025-06-05T17:43:00.000000000\",\"2025-06-05T17:44:00.000000000\",\"2025-06-05T17:45:00.000000000\",\"2025-06-05T17:46:00.000000000\",\"2025-06-05T17:47:00.000000000\",\"2025-06-05T17:48:00.000000000\",\"2025-06-05T17:49:00.000000000\",\"2025-06-05T17:50:00.000000000\",\"2025-06-05T17:51:00.000000000\",\"2025-06-05T17:52:00.000000000\",\"2025-06-05T17:53:00.000000000\",\"2025-06-05T17:54:00.000000000\",\"2025-06-05T17:55:00.000000000\",\"2025-06-05T17:56:00.000000000\",\"2025-06-05T17:57:00.000000000\",\"2025-06-05T17:58:00.000000000\",\"2025-06-05T17:59:00.000000000\",\"2025-06-05T18:00:00.000000000\",\"2025-06-05T18:01:00.000000000\",\"2025-06-05T18:02:00.000000000\",\"2025-06-05T18:03:00.000000000\",\"2025-06-05T18:04:00.000000000\",\"2025-06-05T18:05:00.000000000\",\"2025-06-05T18:06:00.000000000\",\"2025-06-05T18:07:00.000000000\",\"2025-06-05T18:08:00.000000000\",\"2025-06-05T18:09:00.000000000\",\"2025-06-05T18:10:00.000000000\",\"2025-06-05T18:11:00.000000000\",\"2025-06-05T18:12:00.000000000\",\"2025-06-05T18:13:00.000000000\",\"2025-06-05T18:14:00.000000000\",\"2025-06-05T18:15:00.000000000\",\"2025-06-05T18:16:00.000000000\",\"2025-06-05T18:17:00.000000000\",\"2025-06-05T18:18:00.000000000\",\"2025-06-05T18:19:00.000000000\",\"2025-06-05T18:20:00.000000000\",\"2025-06-05T18:21:00.000000000\",\"2025-06-05T18:22:00.000000000\",\"2025-06-05T18:23:00.000000000\",\"2025-06-05T18:24:00.000000000\",\"2025-06-05T18:25:00.000000000\",\"2025-06-05T18:26:00.000000000\",\"2025-06-05T18:27:00.000000000\",\"2025-06-05T18:28:00.000000000\",\"2025-06-05T18:29:00.000000000\",\"2025-06-05T18:30:00.000000000\",\"2025-06-05T18:31:00.000000000\",\"2025-06-05T18:32:00.000000000\",\"2025-06-05T18:33:00.000000000\",\"2025-06-05T18:34:00.000000000\",\"2025-06-05T18:35:00.000000000\",\"2025-06-05T18:36:00.000000000\",\"2025-06-05T18:37:00.000000000\",\"2025-06-05T18:38:00.000000000\",\"2025-06-05T18:39:00.000000000\",\"2025-06-05T18:40:00.000000000\",\"2025-06-05T18:41:00.000000000\",\"2025-06-05T18:42:00.000000000\",\"2025-06-05T18:43:00.000000000\",\"2025-06-05T18:44:00.000000000\",\"2025-06-05T18:45:00.000000000\",\"2025-06-05T18:46:00.000000000\",\"2025-06-05T18:47:00.000000000\",\"2025-06-05T18:48:00.000000000\",\"2025-06-05T18:49:00.000000000\",\"2025-06-05T18:50:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T18:52:00.000000000\",\"2025-06-05T18:53:00.000000000\",\"2025-06-05T18:54:00.000000000\",\"2025-06-05T18:55:00.000000000\",\"2025-06-05T18:56:00.000000000\",\"2025-06-05T18:57:00.000000000\",\"2025-06-05T18:58:00.000000000\",\"2025-06-05T18:59:00.000000000\",\"2025-06-05T19:00:00.000000000\",\"2025-06-05T19:01:00.000000000\",\"2025-06-05T19:02:00.000000000\",\"2025-06-05T19:03:00.000000000\",\"2025-06-05T19:04:00.000000000\",\"2025-06-05T19:05:00.000000000\",\"2025-06-05T19:06:00.000000000\",\"2025-06-05T19:07:00.000000000\",\"2025-06-05T19:08:00.000000000\",\"2025-06-05T19:09:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:11:00.000000000\",\"2025-06-05T19:12:00.000000000\",\"2025-06-05T19:13:00.000000000\",\"2025-06-05T19:14:00.000000000\",\"2025-06-05T19:15:00.000000000\",\"2025-06-05T19:16:00.000000000\",\"2025-06-05T19:17:00.000000000\",\"2025-06-05T19:18:00.000000000\",\"2025-06-05T19:19:00.000000000\",\"2025-06-05T19:20:00.000000000\",\"2025-06-05T19:21:00.000000000\",\"2025-06-05T19:22:00.000000000\",\"2025-06-05T19:23:00.000000000\",\"2025-06-05T19:24:00.000000000\",\"2025-06-05T19:25:00.000000000\",\"2025-06-05T19:26:00.000000000\",\"2025-06-05T19:27:00.000000000\",\"2025-06-05T19:28:00.000000000\",\"2025-06-05T19:29:00.000000000\",\"2025-06-05T19:30:00.000000000\",\"2025-06-05T19:31:00.000000000\",\"2025-06-05T19:32:00.000000000\",\"2025-06-05T19:33:00.000000000\",\"2025-06-05T19:34:00.000000000\",\"2025-06-05T19:35:00.000000000\",\"2025-06-05T19:36:00.000000000\",\"2025-06-05T19:37:00.000000000\",\"2025-06-05T19:38:00.000000000\",\"2025-06-05T19:39:00.000000000\",\"2025-06-05T19:40:00.000000000\",\"2025-06-05T19:41:00.000000000\",\"2025-06-05T19:42:00.000000000\",\"2025-06-05T19:43:00.000000000\",\"2025-06-05T19:44:00.000000000\",\"2025-06-05T19:45:00.000000000\",\"2025-06-05T19:46:00.000000000\",\"2025-06-05T19:47:00.000000000\",\"2025-06-05T19:48:00.000000000\",\"2025-06-05T19:49:00.000000000\",\"2025-06-05T19:50:00.000000000\",\"2025-06-05T19:51:00.000000000\",\"2025-06-05T19:52:00.000000000\",\"2025-06-05T19:53:00.000000000\",\"2025-06-05T19:54:00.000000000\",\"2025-06-05T19:55:00.000000000\",\"2025-06-05T19:56:00.000000000\",\"2025-06-05T19:57:00.000000000\",\"2025-06-05T19:58:00.000000000\",\"2025-06-05T19:59:00.000000000\",\"2025-06-05T20:00:00.000000000\"],\"xaxis\":\"x\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"AAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002fAAAAAAAA+H8AAAAAAAD4fwAAAAAAAPh\\u002feK9K+pck8D+WjVR9QWjqP2+V5QVt+PA\\u002f2braugEs9D8u\\u002faiRcrTwPwsnQihYQfo\\u002f7MRSm85Y+D\\u002fQlhhaf6v8P\\u002fOdar\\u002fgyfk\\u002fYePC8lbj+j\\u002fjgUn0MtEAQBZrdyPkq\\u002fw\\u002fUnaIKjJ8\\u002fD9yBZNln0AAQJV8eN7QIf0\\u002fllLBJxv3AEAZA24AY6D9P2QsnEXBTAJAC7RRh1PyAEATS7BM2OwAQBnMCIaNDgFA\\u002fu15Ntl1AECqi8mZ8FD9P6T1snbaKf4\\u002fQgHhABUr\\u002fz+9wOzWpzAAQKu\\u002fn6tYL\\u002fs\\u002f9EjrvXyG9z8TdUtLlHTzP76Idvv\\u002fSvQ\\u002fAHuN0Mlx9D8JKN46gI7xP0Z7Xc4g1ec\\u002fzhbFbcps4D\\u002fD56Xsk6\\u002fuP8wTdft2Uek\\u002fhiGkspqi8D89ru8fQHPwP8sLfHjMtvA\\u002f9jSpBeFo6j\\u002fVWS3eGszwPzTt8vnwOPA\\u002fzHnJyHCv8D\\u002f7eoElfL\\u002fyPyfPWqmY9vQ\\u002fnkqaRV3m8T83poHfb6XtP9qPisPXCuI\\u002fW23EXLR42j+\\u002f9BjvHqDHP\\u002fjx8o+\\u002fZ+E\\u002friG6xNyE6j\\u002fXMkWQBdXiPx94HDlVHu8\\u002feASgQ\\u002fAC8D91WwVIOkjqP99VvlKSqPE\\u002fj0c5GVnD7z8XP19HWxv7P+8sq20YVPs\\u002fHjnL623N+T+0li1kPJAAQAgJXrOFR\\u002f0\\u002fuSkQ6Ml7\\u002fD+sFQ1IrbP6P+6s6NXyF\\u002fo\\u002ft2739UpZ\\u002fT95X5\\u002fwolr0P9Ebys4uZvM\\u002f8ab88bFK8z+VY9bs5fn1P7OssB26yvE\\u002fJnPZzCZp6D8zcWAlzoK3P48T\\u002fDrgjtM\\u002fUfnI9gY+8z\\u002fwT9kKH5kBQIiA2wfK+P4\\u002fLUnV58JyAUAMaRLA+JP+P4kT8Al7jQBATL15ccgrA0C2DYSZ3PQHQDgq4Xo+XQRA+jK\\u002f82E5BEAcgkcQnMkGQM95xZ7q9ARAIdAw2zfaCkDzNt8h6eoMQO2qucTJrAlAybdV55OTBUAUG5eLT5gHQPyYst4PoghAdTW9rfCwAUA9cWBfTJwAQPQhettMowFAwFAUOqXM\\u002fj8zewCG9nYBQFxudkg5kABAT8+pnMvEAkD9ykf+nxUCQMI+807DHgJAs\\u002fu8kkymA0B+zMB4bEkEQCyjH0wy3QJA98ERS223AUDk5DcIwBQDQCrd6LVhlgNAHm6co7yHAkAIAPeMOxgBQGPGmFpHbABAqk\\u002fNja09\\u002fj9y+Q4AmX37Pzz9al0Bj\\u002fw\\u002fH7lFljlv+z+lOGk6AU\\u002f5P3sFE+ux2fU\\u002fJ7K45DAa9T+O\\u002fF4sBIvzP8eIHNU0VvQ\\u002fUOd6fdPi9D\\u002fHkDDHh5HyP9j\\u002fATGzXfA\\u002frIZDBJ8U8D\\u002fta8azKqHuP05cp4kBqPA\\u002fNbq9CyOZ7z8Ak58QnWXwP43Xi8SkAvE\\u002f2wggH34z8T+cQDuNxZntP\\u002fV8Xz2DQOw\\u002fkiAtm9m17D\\u002fmr2BAG5HkP3tlRN5osOU\\u002fDZ+0Bku96D8rrKM0xcznP9LufWXOMec\\u002fYaRrOgh66D+GmlCLNVHnPxtqZNbliOo\\u002fbXnCQsku7j9qSsT0eGbwPxuYSvon6PE\\u002fivHL\\u002fDPI8D\\u002fuKuzS33zyP7oDBqC5rfA\\u002fnCc+r9h+8j\\u002f56if0xsX1P7er8QqvQvQ\\u002fIIBcHvNZ8j9BZcnJmgPyPzPSIVofXPI\\u002f59rAEH739j9XAeasOzH2P59SdX3LOPU\\u002f5bqLvzfV9T\\u002fvwfoJntj0P7O7UpFCXPQ\\u002fgEFgTnxN9T+3\\u002flcEfsr0P4UKRGoDRvk\\u002f2IThOz7c9j9NWgTKdCf5Pxzk\\u002fmyIvvY\\u002foBSo9CAq+j\\u002f7UBYJbtb4P\\u002f4JiM3\\u002fRPk\\u002f3R2EDvzb+T9UPmaVjYz4P8+MIi9\\u002fNfs\\u002fsCs62GKh+z9BIyQCNZ\\u002f8P\\u002fWmIvuzsvk\\u002fPOSrxxiN+T+2kg2p9Hz3Py+OcgK9NPo\\u002fhNYhuIXG+T+djfit+an4P5y2DLpJn\\u002fk\\u002f27PFxeFH+z+fMZp5WN35PwvHrsce6fs\\u002ft9Zrrp\\u002fX+D+2f0DQwE34P7kdBDog4Pg\\u002ftHbUKbfY+j+1pmjE8Cj6PwVPuc+nO\\u002fw\\u002f98ypLFQB+z8nankr69f5P9uynowRv\\u002fo\\u002fTdc1DKEp+j8pzBz8r0b6P+xUYxOsPP0\\u002fynEw3N6D\\u002fD8QuH9lRJH4P1PNbqlaVfk\\u002foSK\\u002flN2r\\u002fD\\u002fwioYFezb6P7WkRP69lf8\\u002fW254kIDrAECC777IypL\\u002fP6tU0Td6VAJAyuaPX4DpAUB4XFmhmH\\u002f+P3CE01Euv\\u002fs\\u002fei8DZZ3j+j8+eTNOKIr9P4ZiNOX4Svk\\u002fT02wWSrE+D\\u002fedfj6MB\\u002f6PyLK+CHij\\u002fg\\u002fsPK+mVJW8z9WaG2Nl23zP6ugimJLKvM\\u002fnuqbszYu8z\\u002fo0Ej6CxfxP5VMywf2HvI\\u002fB1iliW1X8T88NXNFVVbvP2+NyHTQJPI\\u002fjWIFp5+Q8j9ZCLTk6zvyP0fBYpIgIPE\\u002fQTKi6hcNAEByVC9a9XTmP1bSEt9mSOg\\u002fTL6mwlrQ5z8vqC+ancPwP5xUUychsvA\\u002fdW2w+Yy47z\\u002ffQrdFmYbwPwd6keIeFPE\\u002fw0fBZjDA8D8SGfnvpUD2P8MfD73LcvM\\u002fu5u16M3M8z+ju+ceAlX1P+lywvH7DvU\\u002foinsacO28z8nQSe3f0byP49NRKhsFfY\\u002flmBmZm0v9j\\u002fpPXMwnFj2P0qN0VPko\\u002fU\\u002fd5NdqxJ69z81CjBYFcTzPxdKvSNQ8fU\\u002fQ3WEB5938j9Y9Pl96qPyPzeR1z3Bj\\u002fI\\u002faGdH8hcq8j8eKqaT+d7wP1yN7LV+fe0\\u002fh6ORO6ne7j8jDWRdNXbmP5Q8tlO4P+I\\u002f7DNvMFm53j9qxtGBcQzPPzVRbMTaDM0\\u002f3\\u002fpMGhnL4D++pJ75YOXkP3WL9vCyduE\\u002f6rVa6CdG4j+8lOIA7sXTPx3H6G5HVcI\\u002flduIR5CJ0j88L8xmFczcPzlQFhFyI4M\\u002ftm0Iruck2D8=\"},\"yaxis\":\"y\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"red\",\"size\":10,\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"BUY OPEN\",\"x\":[\"2025-06-05T15:40:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T16:46:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T19:15:00.000000000\"],\"xaxis\":\"x2\",\"y\":[1,5,8,13,17],\"yaxis\":\"y2\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"pink\",\"size\":10,\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"BUY CLOSE\",\"x\":[\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T17:34:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:16:00.000000000\"],\"xaxis\":\"x2\",\"y\":[2,6,11,14,18],\"yaxis\":\"y2\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"blue\",\"size\":10,\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"SELL OPEN\",\"x\":[\"2025-06-05T15:40:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T16:46:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T19:15:00.000000000\"],\"xaxis\":\"x2\",\"y\":[0,4,9,12,16],\"yaxis\":\"y2\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"purple\",\"size\":10,\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"SELL CLOSE\",\"x\":[\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T17:34:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:16:00.000000000\"],\"xaxis\":\"x2\",\"y\":[3,7,10,15,19],\"yaxis\":\"y2\",\"type\":\"scatter\"},{\"line\":{\"color\":\"blue\",\"width\":2},\"name\":\"COIN Price\",\"opacity\":0.8,\"x\":[\"2025-06-05T13:30:00.000000000\",\"2025-06-05T13:31:00.000000000\",\"2025-06-05T13:32:00.000000000\",\"2025-06-05T13:33:00.000000000\",\"2025-06-05T13:34:00.000000000\",\"2025-06-05T13:35:00.000000000\",\"2025-06-05T13:36:00.000000000\",\"2025-06-05T13:37:00.000000000\",\"2025-06-05T13:38:00.000000000\",\"2025-06-05T13:39:00.000000000\",\"2025-06-05T13:40:00.000000000\",\"2025-06-05T13:41:00.000000000\",\"2025-06-05T13:42:00.000000000\",\"2025-06-05T13:43:00.000000000\",\"2025-06-05T13:44:00.000000000\",\"2025-06-05T13:45:00.000000000\",\"2025-06-05T13:46:00.000000000\",\"2025-06-05T13:47:00.000000000\",\"2025-06-05T13:48:00.000000000\",\"2025-06-05T13:49:00.000000000\",\"2025-06-05T13:50:00.000000000\",\"2025-06-05T13:51:00.000000000\",\"2025-06-05T13:52:00.000000000\",\"2025-06-05T13:53:00.000000000\",\"2025-06-05T13:54:00.000000000\",\"2025-06-05T13:55:00.000000000\",\"2025-06-05T13:56:00.000000000\",\"2025-06-05T13:57:00.000000000\",\"2025-06-05T13:58:00.000000000\",\"2025-06-05T13:59:00.000000000\",\"2025-06-05T14:00:00.000000000\",\"2025-06-05T14:01:00.000000000\",\"2025-06-05T14:02:00.000000000\",\"2025-06-05T14:03:00.000000000\",\"2025-06-05T14:04:00.000000000\",\"2025-06-05T14:05:00.000000000\",\"2025-06-05T14:06:00.000000000\",\"2025-06-05T14:07:00.000000000\",\"2025-06-05T14:08:00.000000000\",\"2025-06-05T14:09:00.000000000\",\"2025-06-05T14:10:00.000000000\",\"2025-06-05T14:11:00.000000000\",\"2025-06-05T14:12:00.000000000\",\"2025-06-05T14:13:00.000000000\",\"2025-06-05T14:14:00.000000000\",\"2025-06-05T14:15:00.000000000\",\"2025-06-05T14:16:00.000000000\",\"2025-06-05T14:17:00.000000000\",\"2025-06-05T14:18:00.000000000\",\"2025-06-05T14:19:00.000000000\",\"2025-06-05T14:20:00.000000000\",\"2025-06-05T14:21:00.000000000\",\"2025-06-05T14:22:00.000000000\",\"2025-06-05T14:23:00.000000000\",\"2025-06-05T14:24:00.000000000\",\"2025-06-05T14:25:00.000000000\",\"2025-06-05T14:26:00.000000000\",\"2025-06-05T14:27:00.000000000\",\"2025-06-05T14:28:00.000000000\",\"2025-06-05T14:29:00.000000000\",\"2025-06-05T14:30:00.000000000\",\"2025-06-05T14:31:00.000000000\",\"2025-06-05T14:32:00.000000000\",\"2025-06-05T14:33:00.000000000\",\"2025-06-05T14:34:00.000000000\",\"2025-06-05T14:35:00.000000000\",\"2025-06-05T14:36:00.000000000\",\"2025-06-05T14:37:00.000000000\",\"2025-06-05T14:38:00.000000000\",\"2025-06-05T14:39:00.000000000\",\"2025-06-05T14:40:00.000000000\",\"2025-06-05T14:41:00.000000000\",\"2025-06-05T14:42:00.000000000\",\"2025-06-05T14:43:00.000000000\",\"2025-06-05T14:44:00.000000000\",\"2025-06-05T14:45:00.000000000\",\"2025-06-05T14:46:00.000000000\",\"2025-06-05T14:47:00.000000000\",\"2025-06-05T14:48:00.000000000\",\"2025-06-05T14:49:00.000000000\",\"2025-06-05T14:50:00.000000000\",\"2025-06-05T14:51:00.000000000\",\"2025-06-05T14:52:00.000000000\",\"2025-06-05T14:53:00.000000000\",\"2025-06-05T14:54:00.000000000\",\"2025-06-05T14:55:00.000000000\",\"2025-06-05T14:56:00.000000000\",\"2025-06-05T14:57:00.000000000\",\"2025-06-05T14:58:00.000000000\",\"2025-06-05T14:59:00.000000000\",\"2025-06-05T15:00:00.000000000\",\"2025-06-05T15:01:00.000000000\",\"2025-06-05T15:02:00.000000000\",\"2025-06-05T15:03:00.000000000\",\"2025-06-05T15:04:00.000000000\",\"2025-06-05T15:05:00.000000000\",\"2025-06-05T15:06:00.000000000\",\"2025-06-05T15:07:00.000000000\",\"2025-06-05T15:08:00.000000000\",\"2025-06-05T15:09:00.000000000\",\"2025-06-05T15:10:00.000000000\",\"2025-06-05T15:11:00.000000000\",\"2025-06-05T15:12:00.000000000\",\"2025-06-05T15:13:00.000000000\",\"2025-06-05T15:14:00.000000000\",\"2025-06-05T15:15:00.000000000\",\"2025-06-05T15:16:00.000000000\",\"2025-06-05T15:17:00.000000000\",\"2025-06-05T15:18:00.000000000\",\"2025-06-05T15:19:00.000000000\",\"2025-06-05T15:20:00.000000000\",\"2025-06-05T15:21:00.000000000\",\"2025-06-05T15:22:00.000000000\",\"2025-06-05T15:23:00.000000000\",\"2025-06-05T15:24:00.000000000\",\"2025-06-05T15:25:00.000000000\",\"2025-06-05T15:26:00.000000000\",\"2025-06-05T15:27:00.000000000\",\"2025-06-05T15:28:00.000000000\",\"2025-06-05T15:29:00.000000000\",\"2025-06-05T15:30:00.000000000\",\"2025-06-05T15:31:00.000000000\",\"2025-06-05T15:32:00.000000000\",\"2025-06-05T15:33:00.000000000\",\"2025-06-05T15:34:00.000000000\",\"2025-06-05T15:35:00.000000000\",\"2025-06-05T15:36:00.000000000\",\"2025-06-05T15:37:00.000000000\",\"2025-06-05T15:38:00.000000000\",\"2025-06-05T15:39:00.000000000\",\"2025-06-05T15:40:00.000000000\",\"2025-06-05T15:41:00.000000000\",\"2025-06-05T15:42:00.000000000\",\"2025-06-05T15:43:00.000000000\",\"2025-06-05T15:44:00.000000000\",\"2025-06-05T15:45:00.000000000\",\"2025-06-05T15:46:00.000000000\",\"2025-06-05T15:47:00.000000000\",\"2025-06-05T15:48:00.000000000\",\"2025-06-05T15:49:00.000000000\",\"2025-06-05T15:50:00.000000000\",\"2025-06-05T15:51:00.000000000\",\"2025-06-05T15:52:00.000000000\",\"2025-06-05T15:53:00.000000000\",\"2025-06-05T15:54:00.000000000\",\"2025-06-05T15:55:00.000000000\",\"2025-06-05T15:56:00.000000000\",\"2025-06-05T15:57:00.000000000\",\"2025-06-05T15:58:00.000000000\",\"2025-06-05T15:59:00.000000000\",\"2025-06-05T16:00:00.000000000\",\"2025-06-05T16:01:00.000000000\",\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:03:00.000000000\",\"2025-06-05T16:04:00.000000000\",\"2025-06-05T16:05:00.000000000\",\"2025-06-05T16:06:00.000000000\",\"2025-06-05T16:07:00.000000000\",\"2025-06-05T16:08:00.000000000\",\"2025-06-05T16:09:00.000000000\",\"2025-06-05T16:10:00.000000000\",\"2025-06-05T16:11:00.000000000\",\"2025-06-05T16:12:00.000000000\",\"2025-06-05T16:13:00.000000000\",\"2025-06-05T16:14:00.000000000\",\"2025-06-05T16:15:00.000000000\",\"2025-06-05T16:16:00.000000000\",\"2025-06-05T16:17:00.000000000\",\"2025-06-05T16:18:00.000000000\",\"2025-06-05T16:19:00.000000000\",\"2025-06-05T16:20:00.000000000\",\"2025-06-05T16:21:00.000000000\",\"2025-06-05T16:22:00.000000000\",\"2025-06-05T16:23:00.000000000\",\"2025-06-05T16:24:00.000000000\",\"2025-06-05T16:25:00.000000000\",\"2025-06-05T16:26:00.000000000\",\"2025-06-05T16:27:00.000000000\",\"2025-06-05T16:28:00.000000000\",\"2025-06-05T16:29:00.000000000\",\"2025-06-05T16:30:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T16:32:00.000000000\",\"2025-06-05T16:33:00.000000000\",\"2025-06-05T16:34:00.000000000\",\"2025-06-05T16:35:00.000000000\",\"2025-06-05T16:36:00.000000000\",\"2025-06-05T16:37:00.000000000\",\"2025-06-05T16:38:00.000000000\",\"2025-06-05T16:39:00.000000000\",\"2025-06-05T16:40:00.000000000\",\"2025-06-05T16:41:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T16:43:00.000000000\",\"2025-06-05T16:44:00.000000000\",\"2025-06-05T16:45:00.000000000\",\"2025-06-05T16:46:00.000000000\",\"2025-06-05T16:47:00.000000000\",\"2025-06-05T16:48:00.000000000\",\"2025-06-05T16:49:00.000000000\",\"2025-06-05T16:50:00.000000000\",\"2025-06-05T16:51:00.000000000\",\"2025-06-05T16:52:00.000000000\",\"2025-06-05T16:53:00.000000000\",\"2025-06-05T16:54:00.000000000\",\"2025-06-05T16:55:00.000000000\",\"2025-06-05T16:56:00.000000000\",\"2025-06-05T16:57:00.000000000\",\"2025-06-05T16:58:00.000000000\",\"2025-06-05T16:59:00.000000000\",\"2025-06-05T17:00:00.000000000\",\"2025-06-05T17:01:00.000000000\",\"2025-06-05T17:02:00.000000000\",\"2025-06-05T17:03:00.000000000\",\"2025-06-05T17:04:00.000000000\",\"2025-06-05T17:05:00.000000000\",\"2025-06-05T17:06:00.000000000\",\"2025-06-05T17:07:00.000000000\",\"2025-06-05T17:08:00.000000000\",\"2025-06-05T17:09:00.000000000\",\"2025-06-05T17:10:00.000000000\",\"2025-06-05T17:11:00.000000000\",\"2025-06-05T17:12:00.000000000\",\"2025-06-05T17:13:00.000000000\",\"2025-06-05T17:14:00.000000000\",\"2025-06-05T17:15:00.000000000\",\"2025-06-05T17:16:00.000000000\",\"2025-06-05T17:17:00.000000000\",\"2025-06-05T17:18:00.000000000\",\"2025-06-05T17:19:00.000000000\",\"2025-06-05T17:20:00.000000000\",\"2025-06-05T17:21:00.000000000\",\"2025-06-05T17:22:00.000000000\",\"2025-06-05T17:23:00.000000000\",\"2025-06-05T17:24:00.000000000\",\"2025-06-05T17:25:00.000000000\",\"2025-06-05T17:26:00.000000000\",\"2025-06-05T17:27:00.000000000\",\"2025-06-05T17:28:00.000000000\",\"2025-06-05T17:29:00.000000000\",\"2025-06-05T17:30:00.000000000\",\"2025-06-05T17:31:00.000000000\",\"2025-06-05T17:32:00.000000000\",\"2025-06-05T17:33:00.000000000\",\"2025-06-05T17:34:00.000000000\",\"2025-06-05T17:35:00.000000000\",\"2025-06-05T17:36:00.000000000\",\"2025-06-05T17:37:00.000000000\",\"2025-06-05T17:38:00.000000000\",\"2025-06-05T17:39:00.000000000\",\"2025-06-05T17:40:00.000000000\",\"2025-06-05T17:41:00.000000000\",\"2025-06-05T17:42:00.000000000\",\"2025-06-05T17:43:00.000000000\",\"2025-06-05T17:44:00.000000000\",\"2025-06-05T17:45:00.000000000\",\"2025-06-05T17:46:00.000000000\",\"2025-06-05T17:47:00.000000000\",\"2025-06-05T17:48:00.000000000\",\"2025-06-05T17:49:00.000000000\",\"2025-06-05T17:50:00.000000000\",\"2025-06-05T17:51:00.000000000\",\"2025-06-05T17:52:00.000000000\",\"2025-06-05T17:53:00.000000000\",\"2025-06-05T17:54:00.000000000\",\"2025-06-05T17:55:00.000000000\",\"2025-06-05T17:56:00.000000000\",\"2025-06-05T17:57:00.000000000\",\"2025-06-05T17:58:00.000000000\",\"2025-06-05T17:59:00.000000000\",\"2025-06-05T18:00:00.000000000\",\"2025-06-05T18:01:00.000000000\",\"2025-06-05T18:02:00.000000000\",\"2025-06-05T18:03:00.000000000\",\"2025-06-05T18:04:00.000000000\",\"2025-06-05T18:05:00.000000000\",\"2025-06-05T18:06:00.000000000\",\"2025-06-05T18:07:00.000000000\",\"2025-06-05T18:08:00.000000000\",\"2025-06-05T18:09:00.000000000\",\"2025-06-05T18:10:00.000000000\",\"2025-06-05T18:11:00.000000000\",\"2025-06-05T18:12:00.000000000\",\"2025-06-05T18:13:00.000000000\",\"2025-06-05T18:14:00.000000000\",\"2025-06-05T18:15:00.000000000\",\"2025-06-05T18:16:00.000000000\",\"2025-06-05T18:17:00.000000000\",\"2025-06-05T18:18:00.000000000\",\"2025-06-05T18:19:00.000000000\",\"2025-06-05T18:20:00.000000000\",\"2025-06-05T18:21:00.000000000\",\"2025-06-05T18:22:00.000000000\",\"2025-06-05T18:23:00.000000000\",\"2025-06-05T18:24:00.000000000\",\"2025-06-05T18:25:00.000000000\",\"2025-06-05T18:26:00.000000000\",\"2025-06-05T18:27:00.000000000\",\"2025-06-05T18:28:00.000000000\",\"2025-06-05T18:29:00.000000000\",\"2025-06-05T18:30:00.000000000\",\"2025-06-05T18:31:00.000000000\",\"2025-06-05T18:32:00.000000000\",\"2025-06-05T18:33:00.000000000\",\"2025-06-05T18:34:00.000000000\",\"2025-06-05T18:35:00.000000000\",\"2025-06-05T18:36:00.000000000\",\"2025-06-05T18:37:00.000000000\",\"2025-06-05T18:38:00.000000000\",\"2025-06-05T18:39:00.000000000\",\"2025-06-05T18:40:00.000000000\",\"2025-06-05T18:41:00.000000000\",\"2025-06-05T18:42:00.000000000\",\"2025-06-05T18:43:00.000000000\",\"2025-06-05T18:44:00.000000000\",\"2025-06-05T18:45:00.000000000\",\"2025-06-05T18:46:00.000000000\",\"2025-06-05T18:47:00.000000000\",\"2025-06-05T18:48:00.000000000\",\"2025-06-05T18:49:00.000000000\",\"2025-06-05T18:50:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T18:52:00.000000000\",\"2025-06-05T18:53:00.000000000\",\"2025-06-05T18:54:00.000000000\",\"2025-06-05T18:55:00.000000000\",\"2025-06-05T18:56:00.000000000\",\"2025-06-05T18:57:00.000000000\",\"2025-06-05T18:58:00.000000000\",\"2025-06-05T18:59:00.000000000\",\"2025-06-05T19:00:00.000000000\",\"2025-06-05T19:01:00.000000000\",\"2025-06-05T19:02:00.000000000\",\"2025-06-05T19:03:00.000000000\",\"2025-06-05T19:04:00.000000000\",\"2025-06-05T19:05:00.000000000\",\"2025-06-05T19:06:00.000000000\",\"2025-06-05T19:07:00.000000000\",\"2025-06-05T19:08:00.000000000\",\"2025-06-05T19:09:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:11:00.000000000\",\"2025-06-05T19:12:00.000000000\",\"2025-06-05T19:13:00.000000000\",\"2025-06-05T19:14:00.000000000\",\"2025-06-05T19:15:00.000000000\",\"2025-06-05T19:16:00.000000000\",\"2025-06-05T19:17:00.000000000\",\"2025-06-05T19:18:00.000000000\",\"2025-06-05T19:19:00.000000000\",\"2025-06-05T19:20:00.000000000\",\"2025-06-05T19:21:00.000000000\",\"2025-06-05T19:22:00.000000000\",\"2025-06-05T19:23:00.000000000\",\"2025-06-05T19:24:00.000000000\",\"2025-06-05T19:25:00.000000000\",\"2025-06-05T19:26:00.000000000\",\"2025-06-05T19:27:00.000000000\",\"2025-06-05T19:28:00.000000000\",\"2025-06-05T19:29:00.000000000\",\"2025-06-05T19:30:00.000000000\",\"2025-06-05T19:31:00.000000000\",\"2025-06-05T19:32:00.000000000\",\"2025-06-05T19:33:00.000000000\",\"2025-06-05T19:34:00.000000000\",\"2025-06-05T19:35:00.000000000\",\"2025-06-05T19:36:00.000000000\",\"2025-06-05T19:37:00.000000000\",\"2025-06-05T19:38:00.000000000\",\"2025-06-05T19:39:00.000000000\",\"2025-06-05T19:40:00.000000000\",\"2025-06-05T19:41:00.000000000\",\"2025-06-05T19:42:00.000000000\",\"2025-06-05T19:43:00.000000000\",\"2025-06-05T19:44:00.000000000\",\"2025-06-05T19:45:00.000000000\",\"2025-06-05T19:46:00.000000000\",\"2025-06-05T19:47:00.000000000\",\"2025-06-05T19:48:00.000000000\",\"2025-06-05T19:49:00.000000000\",\"2025-06-05T19:50:00.000000000\",\"2025-06-05T19:51:00.000000000\",\"2025-06-05T19:52:00.000000000\",\"2025-06-05T19:53:00.000000000\",\"2025-06-05T19:54:00.000000000\",\"2025-06-05T19:55:00.000000000\",\"2025-06-05T19:56:00.000000000\",\"2025-06-05T19:57:00.000000000\",\"2025-06-05T19:58:00.000000000\",\"2025-06-05T19:59:00.000000000\",\"2025-06-05T20:00:00.000000000\"],\"xaxis\":\"x3\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"rkfhehR2cEBcj8L1KJZwQPYoXI\\u002fCe3BAAAAAAACEcEBI4XoUrmNwQJqZmZmZYXBAFK5H4Xo4cEDD9Shcj0JwQFCNl24ST3BApHA9CtcrcEAAAAAAADBwQK5H4XoUPnBAy6FFtvMtcEDsUbgehTNwQOC+DpwzLnBAIv32deAIcECPwvUoXANwQFK4HoXr229AKVyPwvXIb0ApXI\\u002fC9bBvQD0K16Nw1W9A16NwPQq3b0AK16NwPcJvQKRwPQrXy29APQrXo3C9b0BI4XoUrrtvQOcdp+hItm9AEhQ\\u002fxtyrb0BLWYY41tNvQEjhehSu329AAAAAAADQb0Bj7lpCPsBvQHE9CtejwG9AFK5H4XrUb0A9CtejcOlvQMP1KFyP6m9A9ihcj8LZb0DVeOkmMeBvQHsUrkfh7m9A\\u002ftR46Sbrb0Cn6Egu\\u002f\\u002ftvQKg1zTtOAnBAcT0K16MEcEA9CtejcAVwQNejcD0KB3BAFK5H4XoEcECkcD0K1wNwQBZqTfOOAnBAH4XrUbj6b0BI4XoUrv9vQBSuR+F69G9ASOF6FK4FcEAzMzMzMxFwQDMzMzMzF3BAz\\u002fdT46UccEApXI\\u002fC9RpwQEa28\\u002f3UHHBAhetRuB4hcEDfT42Xbh1wQM3MzMzMIHBAuB6F61EYcEAzMzMzMxFwQIXrUbgeAXBAFK5H4XoGcEDFjzF3LQBwQOF6FK5H9W9APQrXo3AFcECF61G4Hg1wQKRwPQrXE3BAUrgehesXcEDhehSuRxFwQJtVn6utK3BAuB6F61EocEAK16NwPSpwQD0K16NwKXBA9ihcj8IlcEBI4XoUrjtwQJqZmZmZMXBAUrgehestcEAAAAAAACpwQOxRuB6FL3BAJJf\\u002fkH4ucECamZmZmSlwQHh6pSxDJXBAzczMzMwkcEBmZmZmZiZwQHE9CtejJHBAuB6F61EscEAAAAAAADBwQB+F61G4MnBAZmZmZmYucEAAAAAAAC5wQCcxCKwcNXBAzczMzMw0cEDD9ShcjzRwQBSuR+F6OHBAuB6F61E8cEAzMzMzMz9wQEjhehSuO3BAMzMzMzM9cEB7FK5H4TZwQAu1pnnHMXBAFmpN844zcEDXo3A9CjNwQGZmZmZmLnBAXI\\u002fC9SgwcEBI4XoUrjFwQB+F61G4MnBAZmZmZmZAcEB7FK5H4TpwQI\\u002fC9ShcO3BAMzMzMzM3cEC4HoXrUTxwQNejcD0KQ3BAUrgehetDcECuR+F6FEJwQFyPwvUoPHBA9ihcj8I9cEDD9Shcjz5wQHsUrkfhRnBASOF6FK5LcEDD9Shcj0ZwQIenV8oyQ3BArkfhehRGcEAAAAAAAEBwQFyPwvUoRHBAzczMzMxEcEB7FK5H4URwQKyt2F92Q3BAH4XrUbhCcEA9CtejcEdwQGZmZmZmPnBA9ihcj8I9cEAzMzMzM0dwQArXo3A9RnBArkfhehRAcEB7FK5H4T5wQPYoXI\\u002fCRXBAAAAAAABIcEAAAAAAAERwQJqZmZmZRXBAUrgehetJcEC4HoXrUUBwQI\\u002fC9ShcQ3BAZmZmZmZGcECamZmZmUVwQM3MzMzMTHBA16NwPQpLcEBcj8L1KEZwQM3MzMzMQHBAE\\u002fJBz2Y+cEC4HoXrUThwQGEyVTAqNnBANKK0N\\u002fgwcEAzMzMzMztwQAAAAAAAQHBARiV1AppEcEB1kxgEVkBwQBSuR+F6O3BAUrgehes1cECF61G4HjdwQDMzMzMzN3BAV+wvuyc0cECamZmZmTlwQLgehetROHBArkfhehQ2cEBcj8L1KCxwQJqZmZmZIXBAPQrXo3AhcEApXI\\u002fC9SBwQLgehetRKHBASZ2AJsIxcECPwvUoXCdwQNejcD0KN3BA7FG4HoUvcEBSuB6F6zNwQM3MzMzMMHBADXGsi9sxcECbVZ+rrTdwQLx0kxgEOXBAZmZmZmY6cEBSuB6F6zlwQK5H4XoUNnBAMEymCkY6cEDsUbgehTNwQNc07zhFNXBAYHZPHhY7cECkcD0K1y1wQPYoXI\\u002fCJXBAH4XrUbgecEDu68A5IxdwQDMzMzMzF3BAFK5H4XoUcECamZmZmQlwQEjhehSuAXBAVn2utmLjb0DsUbgehdNvQHsUrkfhvm9AKVyPwvWob0CF61G4HrVvQEjhehSux29AAAAAAACob0D3Bl+YTHlvQGZmZmZmhm9Aw\\u002fUoXI+Kb0CamZmZmYFvQOF6FK5HeW9A4XoUrkdZb0BI4XoUrkdvQMDsnjwsPm9A9ihcj8I9b0DXo3A9Ci9vQHZxGw3gPW9ArkfhehRmb0AfhetRuGZvQFK4HoXraW9APQrXo3Blb0AUrkfhenxvQOxRuB6Fi29AAAAAAACAb0B7FK5H4YpvQEjhehSuj29A4XoUrkeJb0CPwvUoXHtvQAAAAAAAgG9AMnctIR+Mb0BI4XoUrodvQHzysFBrem9AUrgehet5b0BMpgpGJXlvQPYoXI\\u002fCfW9AZmZmZmaOb0CuR+F6FIpvQOF6FK5HkW9AHVpkO9+Lb0D2KFyPwo1vQMP1KFyPkm9AA3gLJCiWb0A9CtejcJ1vQLgehetRkG9AmpmZmZmNb0C4HoXrUZBvQLbz\\u002fdR4m29AAAAAAACgb0DD9Shcj5pvQK5H4XoUlm9AuB6F61Gcb0DD9Shcj6JvQM3MzMzMnG9AodY07zidb0AAAAAAAKhvQJqZmZmZpW9APQrXo3Cdb0CPwvUoXK9vQPYoXI\\u002fCnW9AexSuR+GSb0BSuB6F64lvQD0K16NwhW9Aw\\u002fUoXI+Kb0CF61G4HoVvQG8Sg8DKeW9ANxrAWyBtb0B7FK5H4WpvQGZmZmZmbm9AJzEIrBxub0CqglFJnVpvQHWTGARWYm9A9ihcj8JNb0BxPQrXo0BvQBSuR+F6RG9A4XoUrkdZb0AzMzMzM1NvQD0K16NwVW9A4XoUrkdBb0DD9Shcj0JvQB+F61G4Pm9Aw\\u002fUoXI8ub0DRkVz+QyxvQOF6FK5HOW9AAAAAAABAb0CUh4Va0zZvQLgehetRLG9ArkfhehQub0DhehSuRwlvQM3MzMzMDG9AAG+BBMX5bkBfB84ZUeRuQArXo3A9+m5AmpmZmZn5bkDaG3xhMgtvQAAAAAAA9G5ArkfhehT2bkDgLZCg+PFuQJEPejarCG9AMzMzMzMTb0AfhetRuBZvQHE9CtejAG9A16NwPQoHb0CkcD0K1\\u002f9uQJqZmZmZAW9AcT0K16P4bkCF61G4Hv1uQGZmZmZm9m5AKVyPwvX4bkDBqKROQP1uQM3MzMzMBG9A7FG4HoUDb0BI4XoUrvNuQEjhehSu725AAAAAAADwbkApXI\\u002fC9eBuQH0\\u002fNV66225AKVyPwvXYbkBI4XoUrs9uQFyPwvUoym5AhetRuB7NbkCPwvUoXNduQHsUrkfh0m5AFK5H4XrMbkApXI\\u002fC9chuQFyPwvUovG5AcT0K16O4bkCF61G4Hr1uQEjhehSur25ApHA9CtenbkDXo3A9Cr9uQHsUrkfhum5A4XoUrkepbkAK16NwPaJuQDMzMzMzo25Aj8L1KFyvbkCF61G4Hq1uQKJFtvP9wG5AJJf\\u002fkH63bkAfhetRuLJuQLgehetRrG5AuB6F61GwbkDzH9JvX6duQFK4HoXrqW5A1JrmHaeqbkB7FK5H4bJuQAAAAAAAoG5AexSuR+GabkBmZmZmZpZuQPYoXI\\u002fCjW5AcT0K16OAbkBxPQrXo2huQAAAAAAAYG5AZmZmZmZObkCPwvUoXEduQAAAAAAAPG5AcT0K16MwbkAAAAAAADBuQB+F61G4Hm5AexSuR+EabkBI4XoUrhduQHsUrkfhRm5Aw\\u002fUoXI9ObkAzMzMzM0NuQLgehetRXG5Aj8L1KFxvbkCLbOf7qYFuQArXo3A9em5AAAAAAACAbkD2KFyPwoVuQFyPwvUojG5Aj8L1KFyPbkCkcD0K15tuQMRCrWnem25ArkfhehSabkA6I0p7g49uQPYoXI\\u002fCkW5ACtejcD12bkDXo3A9CnduQBniWBe3eW5ApHA9CteDbkAUrkfheoBuQJqZmZmZgW5A9ihcj8KNbkCuR+F6FJZuQBSuR+F6im5ACtejcD2SbkCPwvUoXJVuQKRwPQrXk25AMzMzMzOLbkAfhetRuJZuQBSuR+F6lG5A4XoUrkeJbkDNzMzMzIRuQI\\u002fC9Shch25A9ihcj8KNbkA=\"},\"yaxis\":\"y3\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"red\",\"size\":12,\"symbol\":\"triangle-up\"},\"mode\":\"markers\",\"name\":\"COIN BUY OPEN\",\"showlegend\":true,\"x\":[\"2025-06-05T16:46:00.000000000\"],\"xaxis\":\"x3\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"7FG4HoXTb0A=\"},\"yaxis\":\"y3\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"pink\",\"size\":12,\"symbol\":\"triangle-up\"},\"mode\":\"markers\",\"name\":\"COIN BUY CLOSE\",\"showlegend\":true,\"x\":[\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:16:00.000000000\"],\"xaxis\":\"x3\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"YTJVMCo2cEAUrkfhehRwQHsUrkfhsm5AcT0K16NobkA=\"},\"yaxis\":\"y3\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"blue\",\"size\":12,\"symbol\":\"triangle-down\"},\"mode\":\"markers\",\"name\":\"COIN SELL OPEN\",\"showlegend\":true,\"x\":[\"2025-06-05T15:40:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T19:15:00.000000000\"],\"xaxis\":\"x3\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"PQrXo3BHcEBSuB6F6zlwQHE9CtejuG5AcT0K16OAbkA=\"},\"yaxis\":\"y3\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"purple\",\"size\":12,\"symbol\":\"triangle-down\"},\"mode\":\"markers\",\"name\":\"COIN SELL CLOSE\",\"showlegend\":true,\"x\":[\"2025-06-05T17:34:00.000000000\"],\"xaxis\":\"x3\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"w\\u002fUoXI+ab0A=\"},\"yaxis\":\"y3\",\"type\":\"scatter\"},{\"line\":{\"color\":\"orange\",\"width\":2},\"name\":\"MSTR Price\",\"opacity\":0.8,\"x\":[\"2025-06-05T13:30:00.000000000\",\"2025-06-05T13:31:00.000000000\",\"2025-06-05T13:32:00.000000000\",\"2025-06-05T13:33:00.000000000\",\"2025-06-05T13:34:00.000000000\",\"2025-06-05T13:35:00.000000000\",\"2025-06-05T13:36:00.000000000\",\"2025-06-05T13:37:00.000000000\",\"2025-06-05T13:38:00.000000000\",\"2025-06-05T13:39:00.000000000\",\"2025-06-05T13:40:00.000000000\",\"2025-06-05T13:41:00.000000000\",\"2025-06-05T13:42:00.000000000\",\"2025-06-05T13:43:00.000000000\",\"2025-06-05T13:44:00.000000000\",\"2025-06-05T13:45:00.000000000\",\"2025-06-05T13:46:00.000000000\",\"2025-06-05T13:47:00.000000000\",\"2025-06-05T13:48:00.000000000\",\"2025-06-05T13:49:00.000000000\",\"2025-06-05T13:50:00.000000000\",\"2025-06-05T13:51:00.000000000\",\"2025-06-05T13:52:00.000000000\",\"2025-06-05T13:53:00.000000000\",\"2025-06-05T13:54:00.000000000\",\"2025-06-05T13:55:00.000000000\",\"2025-06-05T13:56:00.000000000\",\"2025-06-05T13:57:00.000000000\",\"2025-06-05T13:58:00.000000000\",\"2025-06-05T13:59:00.000000000\",\"2025-06-05T14:00:00.000000000\",\"2025-06-05T14:01:00.000000000\",\"2025-06-05T14:02:00.000000000\",\"2025-06-05T14:03:00.000000000\",\"2025-06-05T14:04:00.000000000\",\"2025-06-05T14:05:00.000000000\",\"2025-06-05T14:06:00.000000000\",\"2025-06-05T14:07:00.000000000\",\"2025-06-05T14:08:00.000000000\",\"2025-06-05T14:09:00.000000000\",\"2025-06-05T14:10:00.000000000\",\"2025-06-05T14:11:00.000000000\",\"2025-06-05T14:12:00.000000000\",\"2025-06-05T14:13:00.000000000\",\"2025-06-05T14:14:00.000000000\",\"2025-06-05T14:15:00.000000000\",\"2025-06-05T14:16:00.000000000\",\"2025-06-05T14:17:00.000000000\",\"2025-06-05T14:18:00.000000000\",\"2025-06-05T14:19:00.000000000\",\"2025-06-05T14:20:00.000000000\",\"2025-06-05T14:21:00.000000000\",\"2025-06-05T14:22:00.000000000\",\"2025-06-05T14:23:00.000000000\",\"2025-06-05T14:24:00.000000000\",\"2025-06-05T14:25:00.000000000\",\"2025-06-05T14:26:00.000000000\",\"2025-06-05T14:27:00.000000000\",\"2025-06-05T14:28:00.000000000\",\"2025-06-05T14:29:00.000000000\",\"2025-06-05T14:30:00.000000000\",\"2025-06-05T14:31:00.000000000\",\"2025-06-05T14:32:00.000000000\",\"2025-06-05T14:33:00.000000000\",\"2025-06-05T14:34:00.000000000\",\"2025-06-05T14:35:00.000000000\",\"2025-06-05T14:36:00.000000000\",\"2025-06-05T14:37:00.000000000\",\"2025-06-05T14:38:00.000000000\",\"2025-06-05T14:39:00.000000000\",\"2025-06-05T14:40:00.000000000\",\"2025-06-05T14:41:00.000000000\",\"2025-06-05T14:42:00.000000000\",\"2025-06-05T14:43:00.000000000\",\"2025-06-05T14:44:00.000000000\",\"2025-06-05T14:45:00.000000000\",\"2025-06-05T14:46:00.000000000\",\"2025-06-05T14:47:00.000000000\",\"2025-06-05T14:48:00.000000000\",\"2025-06-05T14:49:00.000000000\",\"2025-06-05T14:50:00.000000000\",\"2025-06-05T14:51:00.000000000\",\"2025-06-05T14:52:00.000000000\",\"2025-06-05T14:53:00.000000000\",\"2025-06-05T14:54:00.000000000\",\"2025-06-05T14:55:00.000000000\",\"2025-06-05T14:56:00.000000000\",\"2025-06-05T14:57:00.000000000\",\"2025-06-05T14:58:00.000000000\",\"2025-06-05T14:59:00.000000000\",\"2025-06-05T15:00:00.000000000\",\"2025-06-05T15:01:00.000000000\",\"2025-06-05T15:02:00.000000000\",\"2025-06-05T15:03:00.000000000\",\"2025-06-05T15:04:00.000000000\",\"2025-06-05T15:05:00.000000000\",\"2025-06-05T15:06:00.000000000\",\"2025-06-05T15:07:00.000000000\",\"2025-06-05T15:08:00.000000000\",\"2025-06-05T15:09:00.000000000\",\"2025-06-05T15:10:00.000000000\",\"2025-06-05T15:11:00.000000000\",\"2025-06-05T15:12:00.000000000\",\"2025-06-05T15:13:00.000000000\",\"2025-06-05T15:14:00.000000000\",\"2025-06-05T15:15:00.000000000\",\"2025-06-05T15:16:00.000000000\",\"2025-06-05T15:17:00.000000000\",\"2025-06-05T15:18:00.000000000\",\"2025-06-05T15:19:00.000000000\",\"2025-06-05T15:20:00.000000000\",\"2025-06-05T15:21:00.000000000\",\"2025-06-05T15:22:00.000000000\",\"2025-06-05T15:23:00.000000000\",\"2025-06-05T15:24:00.000000000\",\"2025-06-05T15:25:00.000000000\",\"2025-06-05T15:26:00.000000000\",\"2025-06-05T15:27:00.000000000\",\"2025-06-05T15:28:00.000000000\",\"2025-06-05T15:29:00.000000000\",\"2025-06-05T15:30:00.000000000\",\"2025-06-05T15:31:00.000000000\",\"2025-06-05T15:32:00.000000000\",\"2025-06-05T15:33:00.000000000\",\"2025-06-05T15:34:00.000000000\",\"2025-06-05T15:35:00.000000000\",\"2025-06-05T15:36:00.000000000\",\"2025-06-05T15:37:00.000000000\",\"2025-06-05T15:38:00.000000000\",\"2025-06-05T15:39:00.000000000\",\"2025-06-05T15:40:00.000000000\",\"2025-06-05T15:41:00.000000000\",\"2025-06-05T15:42:00.000000000\",\"2025-06-05T15:43:00.000000000\",\"2025-06-05T15:44:00.000000000\",\"2025-06-05T15:45:00.000000000\",\"2025-06-05T15:46:00.000000000\",\"2025-06-05T15:47:00.000000000\",\"2025-06-05T15:48:00.000000000\",\"2025-06-05T15:49:00.000000000\",\"2025-06-05T15:50:00.000000000\",\"2025-06-05T15:51:00.000000000\",\"2025-06-05T15:52:00.000000000\",\"2025-06-05T15:53:00.000000000\",\"2025-06-05T15:54:00.000000000\",\"2025-06-05T15:55:00.000000000\",\"2025-06-05T15:56:00.000000000\",\"2025-06-05T15:57:00.000000000\",\"2025-06-05T15:58:00.000000000\",\"2025-06-05T15:59:00.000000000\",\"2025-06-05T16:00:00.000000000\",\"2025-06-05T16:01:00.000000000\",\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:03:00.000000000\",\"2025-06-05T16:04:00.000000000\",\"2025-06-05T16:05:00.000000000\",\"2025-06-05T16:06:00.000000000\",\"2025-06-05T16:07:00.000000000\",\"2025-06-05T16:08:00.000000000\",\"2025-06-05T16:09:00.000000000\",\"2025-06-05T16:10:00.000000000\",\"2025-06-05T16:11:00.000000000\",\"2025-06-05T16:12:00.000000000\",\"2025-06-05T16:13:00.000000000\",\"2025-06-05T16:14:00.000000000\",\"2025-06-05T16:15:00.000000000\",\"2025-06-05T16:16:00.000000000\",\"2025-06-05T16:17:00.000000000\",\"2025-06-05T16:18:00.000000000\",\"2025-06-05T16:19:00.000000000\",\"2025-06-05T16:20:00.000000000\",\"2025-06-05T16:21:00.000000000\",\"2025-06-05T16:22:00.000000000\",\"2025-06-05T16:23:00.000000000\",\"2025-06-05T16:24:00.000000000\",\"2025-06-05T16:25:00.000000000\",\"2025-06-05T16:26:00.000000000\",\"2025-06-05T16:27:00.000000000\",\"2025-06-05T16:28:00.000000000\",\"2025-06-05T16:29:00.000000000\",\"2025-06-05T16:30:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T16:32:00.000000000\",\"2025-06-05T16:33:00.000000000\",\"2025-06-05T16:34:00.000000000\",\"2025-06-05T16:35:00.000000000\",\"2025-06-05T16:36:00.000000000\",\"2025-06-05T16:37:00.000000000\",\"2025-06-05T16:38:00.000000000\",\"2025-06-05T16:39:00.000000000\",\"2025-06-05T16:40:00.000000000\",\"2025-06-05T16:41:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T16:43:00.000000000\",\"2025-06-05T16:44:00.000000000\",\"2025-06-05T16:45:00.000000000\",\"2025-06-05T16:46:00.000000000\",\"2025-06-05T16:47:00.000000000\",\"2025-06-05T16:48:00.000000000\",\"2025-06-05T16:49:00.000000000\",\"2025-06-05T16:50:00.000000000\",\"2025-06-05T16:51:00.000000000\",\"2025-06-05T16:52:00.000000000\",\"2025-06-05T16:53:00.000000000\",\"2025-06-05T16:54:00.000000000\",\"2025-06-05T16:55:00.000000000\",\"2025-06-05T16:56:00.000000000\",\"2025-06-05T16:57:00.000000000\",\"2025-06-05T16:58:00.000000000\",\"2025-06-05T16:59:00.000000000\",\"2025-06-05T17:00:00.000000000\",\"2025-06-05T17:01:00.000000000\",\"2025-06-05T17:02:00.000000000\",\"2025-06-05T17:03:00.000000000\",\"2025-06-05T17:04:00.000000000\",\"2025-06-05T17:05:00.000000000\",\"2025-06-05T17:06:00.000000000\",\"2025-06-05T17:07:00.000000000\",\"2025-06-05T17:08:00.000000000\",\"2025-06-05T17:09:00.000000000\",\"2025-06-05T17:10:00.000000000\",\"2025-06-05T17:11:00.000000000\",\"2025-06-05T17:12:00.000000000\",\"2025-06-05T17:13:00.000000000\",\"2025-06-05T17:14:00.000000000\",\"2025-06-05T17:15:00.000000000\",\"2025-06-05T17:16:00.000000000\",\"2025-06-05T17:17:00.000000000\",\"2025-06-05T17:18:00.000000000\",\"2025-06-05T17:19:00.000000000\",\"2025-06-05T17:20:00.000000000\",\"2025-06-05T17:21:00.000000000\",\"2025-06-05T17:22:00.000000000\",\"2025-06-05T17:23:00.000000000\",\"2025-06-05T17:24:00.000000000\",\"2025-06-05T17:25:00.000000000\",\"2025-06-05T17:26:00.000000000\",\"2025-06-05T17:27:00.000000000\",\"2025-06-05T17:28:00.000000000\",\"2025-06-05T17:29:00.000000000\",\"2025-06-05T17:30:00.000000000\",\"2025-06-05T17:31:00.000000000\",\"2025-06-05T17:32:00.000000000\",\"2025-06-05T17:33:00.000000000\",\"2025-06-05T17:34:00.000000000\",\"2025-06-05T17:35:00.000000000\",\"2025-06-05T17:36:00.000000000\",\"2025-06-05T17:37:00.000000000\",\"2025-06-05T17:38:00.000000000\",\"2025-06-05T17:39:00.000000000\",\"2025-06-05T17:40:00.000000000\",\"2025-06-05T17:41:00.000000000\",\"2025-06-05T17:42:00.000000000\",\"2025-06-05T17:43:00.000000000\",\"2025-06-05T17:44:00.000000000\",\"2025-06-05T17:45:00.000000000\",\"2025-06-05T17:46:00.000000000\",\"2025-06-05T17:47:00.000000000\",\"2025-06-05T17:48:00.000000000\",\"2025-06-05T17:49:00.000000000\",\"2025-06-05T17:50:00.000000000\",\"2025-06-05T17:51:00.000000000\",\"2025-06-05T17:52:00.000000000\",\"2025-06-05T17:53:00.000000000\",\"2025-06-05T17:54:00.000000000\",\"2025-06-05T17:55:00.000000000\",\"2025-06-05T17:56:00.000000000\",\"2025-06-05T17:57:00.000000000\",\"2025-06-05T17:58:00.000000000\",\"2025-06-05T17:59:00.000000000\",\"2025-06-05T18:00:00.000000000\",\"2025-06-05T18:01:00.000000000\",\"2025-06-05T18:02:00.000000000\",\"2025-06-05T18:03:00.000000000\",\"2025-06-05T18:04:00.000000000\",\"2025-06-05T18:05:00.000000000\",\"2025-06-05T18:06:00.000000000\",\"2025-06-05T18:07:00.000000000\",\"2025-06-05T18:08:00.000000000\",\"2025-06-05T18:09:00.000000000\",\"2025-06-05T18:10:00.000000000\",\"2025-06-05T18:11:00.000000000\",\"2025-06-05T18:12:00.000000000\",\"2025-06-05T18:13:00.000000000\",\"2025-06-05T18:14:00.000000000\",\"2025-06-05T18:15:00.000000000\",\"2025-06-05T18:16:00.000000000\",\"2025-06-05T18:17:00.000000000\",\"2025-06-05T18:18:00.000000000\",\"2025-06-05T18:19:00.000000000\",\"2025-06-05T18:20:00.000000000\",\"2025-06-05T18:21:00.000000000\",\"2025-06-05T18:22:00.000000000\",\"2025-06-05T18:23:00.000000000\",\"2025-06-05T18:24:00.000000000\",\"2025-06-05T18:25:00.000000000\",\"2025-06-05T18:26:00.000000000\",\"2025-06-05T18:27:00.000000000\",\"2025-06-05T18:28:00.000000000\",\"2025-06-05T18:29:00.000000000\",\"2025-06-05T18:30:00.000000000\",\"2025-06-05T18:31:00.000000000\",\"2025-06-05T18:32:00.000000000\",\"2025-06-05T18:33:00.000000000\",\"2025-06-05T18:34:00.000000000\",\"2025-06-05T18:35:00.000000000\",\"2025-06-05T18:36:00.000000000\",\"2025-06-05T18:37:00.000000000\",\"2025-06-05T18:38:00.000000000\",\"2025-06-05T18:39:00.000000000\",\"2025-06-05T18:40:00.000000000\",\"2025-06-05T18:41:00.000000000\",\"2025-06-05T18:42:00.000000000\",\"2025-06-05T18:43:00.000000000\",\"2025-06-05T18:44:00.000000000\",\"2025-06-05T18:45:00.000000000\",\"2025-06-05T18:46:00.000000000\",\"2025-06-05T18:47:00.000000000\",\"2025-06-05T18:48:00.000000000\",\"2025-06-05T18:49:00.000000000\",\"2025-06-05T18:50:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T18:52:00.000000000\",\"2025-06-05T18:53:00.000000000\",\"2025-06-05T18:54:00.000000000\",\"2025-06-05T18:55:00.000000000\",\"2025-06-05T18:56:00.000000000\",\"2025-06-05T18:57:00.000000000\",\"2025-06-05T18:58:00.000000000\",\"2025-06-05T18:59:00.000000000\",\"2025-06-05T19:00:00.000000000\",\"2025-06-05T19:01:00.000000000\",\"2025-06-05T19:02:00.000000000\",\"2025-06-05T19:03:00.000000000\",\"2025-06-05T19:04:00.000000000\",\"2025-06-05T19:05:00.000000000\",\"2025-06-05T19:06:00.000000000\",\"2025-06-05T19:07:00.000000000\",\"2025-06-05T19:08:00.000000000\",\"2025-06-05T19:09:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:11:00.000000000\",\"2025-06-05T19:12:00.000000000\",\"2025-06-05T19:13:00.000000000\",\"2025-06-05T19:14:00.000000000\",\"2025-06-05T19:15:00.000000000\",\"2025-06-05T19:16:00.000000000\",\"2025-06-05T19:17:00.000000000\",\"2025-06-05T19:18:00.000000000\",\"2025-06-05T19:19:00.000000000\",\"2025-06-05T19:20:00.000000000\",\"2025-06-05T19:21:00.000000000\",\"2025-06-05T19:22:00.000000000\",\"2025-06-05T19:23:00.000000000\",\"2025-06-05T19:24:00.000000000\",\"2025-06-05T19:25:00.000000000\",\"2025-06-05T19:26:00.000000000\",\"2025-06-05T19:27:00.000000000\",\"2025-06-05T19:28:00.000000000\",\"2025-06-05T19:29:00.000000000\",\"2025-06-05T19:30:00.000000000\",\"2025-06-05T19:31:00.000000000\",\"2025-06-05T19:32:00.000000000\",\"2025-06-05T19:33:00.000000000\",\"2025-06-05T19:34:00.000000000\",\"2025-06-05T19:35:00.000000000\",\"2025-06-05T19:36:00.000000000\",\"2025-06-05T19:37:00.000000000\",\"2025-06-05T19:38:00.000000000\",\"2025-06-05T19:39:00.000000000\",\"2025-06-05T19:40:00.000000000\",\"2025-06-05T19:41:00.000000000\",\"2025-06-05T19:42:00.000000000\",\"2025-06-05T19:43:00.000000000\",\"2025-06-05T19:44:00.000000000\",\"2025-06-05T19:45:00.000000000\",\"2025-06-05T19:46:00.000000000\",\"2025-06-05T19:47:00.000000000\",\"2025-06-05T19:48:00.000000000\",\"2025-06-05T19:49:00.000000000\",\"2025-06-05T19:50:00.000000000\",\"2025-06-05T19:51:00.000000000\",\"2025-06-05T19:52:00.000000000\",\"2025-06-05T19:53:00.000000000\",\"2025-06-05T19:54:00.000000000\",\"2025-06-05T19:55:00.000000000\",\"2025-06-05T19:56:00.000000000\",\"2025-06-05T19:57:00.000000000\",\"2025-06-05T19:58:00.000000000\",\"2025-06-05T19:59:00.000000000\",\"2025-06-05T20:00:00.000000000\"],\"xaxis\":\"x4\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"uB6F61EMeEAf9GxWfex3QOF6FK5HvXdAcT0K16PAd0AK16NwPbp3QI\\u002fC9Shcs3dACfmgZ7Oud0AAAAAAALh3QB+F61G4xHdAZmZmZmaod0CuR+F6FL53QB+F61G4yndApHA9CtfHd0DsUbgehct3QOF6FK5HxXdAj8L1KFyTd0Bcj8L1KI53QGZmZmZmendACtejcD2Cd0DNzMzMzHR3QD0K16Nwg3dAFK5H4Xpud0CPwvUoXGd3QB+F61G4endAyxDHurh+d0BI4XoUrnt3QNPe4AuTeXdAcT0K16Nod0DNzMzMzIR3QPYoXI\\u002fClXdA7FG4HoWPd0AfhetRuIh3QBx8YTJVgndA9ihcj8KFd0BI4XoUro93QB+F61G4iHdApHA9Ctd9d0DD9Shcj4J3QJ\\u002fNqs\\u002fViXdAYhBYObSJd0BSuB6F64l3QKRwPQrXl3dALpCg+DGXd0CuR+F6FJ53QB+F61G4nndAUrgeheudd0DNzMzMzJx3QJqZmZmZoXdASOF6FK6fd0CPwvUoXJ93QClcj8L1lHdAMzMzMzOld0BxPQrXo6x3QMP1KFyPrndAPQrXo3Cxd0DHuriNBqd3QIXrUbgerXdAHVpkO9+xd0BmZmZmZrJ3QAAAAAAAuHdAzczMzMysd0DNzMzMzKR3QJqZmZmZlXdA16NwPQqrd0CamZmZmaV3QKRwPQrXl3dAUrgeheuhd0BI4XoUrr93QEjhehSuz3dAj8L1KFzPd0CuR+F6FL53QI\\u002fC9Shc7XdAKVyPwvXgd0A9CtejcOl3QOF6FK5H6XdAmpmZmZndd0DsUbgehfl3QGZmZmZm8ndA7FG4HoXjd0AfhetRuNp3QM3MzMzM4HdA7FG4HoXLd0Bcj8L1KMh3QDY8vVKWwHdAw\\u002fUoXI\\u002fMd0CVZYhjXc93QHsUrkfh1ndAhetRuB7ld0B7FK5H4eJ3QLgehetR4ndAmpmZmZnfd0DXo3A9Ctt3QDMzMzMzy3dAFK5H4XrMd0DhehSuR8V3QFyPwvUoyHdAj8L1KFzHd0B2Tx4Wasx3QGZmZmZmwndA4XoUrkfNd0BMN4lBYNJ3QD0K16NwzXdAcT0K16PQd0BI4XoUrs93QKRwPQrXx3dAcT0K16PKd0BxPQrXo9R3QFyPwvUo0HdAFR3J5T\\u002fOd0A9CtejcMl3QJqZmZmZxXdA16NwPQrLd0CitDf4wsh3QGZmZmZmzndAKVyPwvXYd0DsUbgehdd3QN9PjZdu13dAJuSDns3Xd0AUrkfhetB3QECk374O13dA9ihcj8LXd0DD9Shcj9Z3QBSuR+F6zHdA4umVsgzOd0DnHafoSM93QFjKMsSxyHdASOF6FK7Pd0C8dJMYBMp3QHE9CtejzHdAJLn8h\\u002fTKd0AUrkfhesh3QEaU9gZfwXdAn6ut2F\\u002fAd0BdbcX+ssd3QArXo3A9yndA4XoUrke5d0BE+u3rwLx3QFMFo5I6u3dA4umVsgzBd0D+Q\\u002frt67l3QMP1KFyPundAj8L1KFzBd0CkcD0K17d3QPYoXI\\u002fCuXdAj8L1KFy7d0DXo3A9Crd3QDMzMzMzyXdAdEaU9gbMd0CF61G4Hst3QOF6FK5HwXdA4C2QoPi8d0AUrkfherh3QOXyH9JvvndAcT0K16O8d0DsUbgehb93QM07TtGRyndAZmZmZmbKd0AAAAAAAMR3QAAAAAAAvHdAMzMzMzO5d0AibHh6pbR3QOF6FK5HtXdAS8gHPZuvd0BdbcX+srN3QJqZmZmZrXdA8kHPZtWud0ApXI\\u002fC9aR3QM3MzMzMnndACtejcD2id0DhehSuR6d3QLgehetRqHdAZmZmZmaud0DXo3A9CqV3QPYoXI\\u002fCsXdAmpmZmZmld0C4HoXrUbB3QK5H4XoUpHdAHOviNhqod0D2KFyPwp13QGZmZmZmnndAC0YldQKid0AAAAAAAJR3QOxRuB6Fk3dAUrgeheuZd0AK16NwPZJ3QIXrUbgelXdAMzMzMzOXd0DD9Shcj5J3QAAAAAAAiHdAmpmZmZl9d0D2KFyPwm13QHWTGARWdHdA4XoUrkd5d0C4HoXrUXp3QFyPwvUoeHdArkfhehR2d0A9m1Wfq4F3QAAAAAAAbHdAhetRuB5hd0AzMzMzM2N3QM3MzMzMdHdAmpmZmZlld0DXo3A9ClN3QCnLEMe6UndA7FG4HoVXd0BmZmZmZlp3QIGVQ4tsVndArkfhehRSd0D2KFyPwk13QAAAAAAAQHdARPrt68Azd0DD9ShcjzJ3QLgehetRRHdAXI\\u002fC9ShKd0CamZmZmUV3QClcj8L1QndAFK5H4XpYd0DD9Shcj2B3QFK4HoXraXdAObTIdr5td0DhehSuR3V3QI\\u002fC9Shce3dAcT0K16OAd0BxPQrXo3x3QFyPwvUofHdA0ETY8PSBd0BxPQrXo4h3QCBB8WPMhHdAHVpkO9+Bd0C4HoXrUXx3QMP1KFyPfndAmpmZmZmFd0Csi9toAHx3QMP1KFyPhndAKVyPwvWAd0A9CtejcH13QN9PjZdud3dARrbz\\u002fdR4d0AK16NwPXp3QFyPwvUodHdAhetRuB51d0CamZmZmXB3QBpR2ht8cndA9ihcj8J1d0AAAAAAAHB3QAAAAAAAcndAcT0K16N0d0Bcj8L1KHx3QHsUrkfhendAzczMzMx8d0DhC5Opgn13QArXo3A9endA9ihcj8J1d0CkcD0K13V3QI\\u002fC9Shca3dApb3BFyZpd0CamZmZmWF3QP5D+u3rXXdAcT0K16Nkd0CPwvUoXF93QIXrUbgeXXdAcT0K16Nad0AK16NwPV53QHsUrkfhZndAAiuHFtljd0AAAAAAAFx3QGFUUiegXHdAuB6F61FUd0DD9Shcj1Z3QJqZmZmZVXdApHA9Ctdfd0AzMzMzM1t3QNejcD0KX3dAcT0K16Ngd0B88rBQa2B3QIQNT6+UW3dAexSuR+FSd0CDL0ymCk93QLgehetRWHdA9ihcj8Jhd0BmZmZmZlp3QDMzMzMzY3dA9ihcj8Jdd0DsUbgehUt3QDMzMzMzR3dArkfhehRGd0BWDi2ynTJ3QArXo3A9RndAqoJRSZ1Jd0AAAAAAAFR3QJqZmZmZTXdAw\\u002fUoXI9Sd0DNzMzMzFR3QD0K16NwXXdACtejcD1md0ApXI\\u002fC9WJ3QI\\u002fC9ShcXXdArkfhehRid0CuR+F6FFp3QEjhehSuX3dAmpmZmZlfd0DXo3A9Cl93QI\\u002fC9ShcYXdAmpmZmZlZd0CPwvUoXFt3QBKlvcEXY3dAFK5H4Xpod0C4HoXrUVp3QEjhehSuXXdAZmZmZmZad0BI4XoUrkt3QKRwPQrXSXdA9ihcj8JFd0DNzMzMzD53QKrx0k1iQndA16NwPQpDd0CamZmZmUF3QOF6FK5HQXdAUrgehetFd0AK16NwPT53QP7UeOkmQ3dAZmZmZmZGd0AfhetRuEZ3QFyPwvUoTHdAmG4Sg8BGd0DhehSuR0x3QFyPwvUoRHdAE\\u002fJBz2Y2d0A9CtejcDl3QD0K16NwMXdA9ihcj8I5d0CuR+F6FD53QFK4HoXrPXdAj8L1KFwzd0B6pSxDHDF3QNejcD0KK3dA7FG4HoUvd0CRD3o2qyN3QKRwPQrXJ3dAAAAAAAAod0DD9Shcjyp3QAAAAAAAJHdACtejcD0ed0DNzMzMzBh3QM3MzMzMEHdAmpmZmZkDd0DsUbgehfN2QMl2vp8a7XZAKVyPwvXfdkCkcD0K1+d2QArXo3A94nZAAAAAAADYdkBSuB6F69l2QKRwPQrXz3ZAXI\\u002fC9SjMdkAK16NwPdp2QIXrUbge+XZAAAAAAAD4dkApXI\\u002fC9fR2QMP1KFyPCHdAH4XrUbgUd0DsUbgehR93QOY\\u002fpN++JXdAj8L1KFwrd0CF61G4HjF3QM3MzMzMNHdA4XoUrkc9d0AzMzMzMz13QAAAAAAARHdA9ihcj8I5d0B7FK5H4TJ3QClcj8L1NHdA7FG4HoUfd0AzMzMzMx13QAAAAAAAGndA9ihcj8Ijd0CuR+F6FBd3QOC+DpwzE3dAPQrXo3AZd0Av3SQGgRd3QM3MzMzMDndA7FG4HoUfd0DD9ShcjyZ3QArXo3A9IndAexSuR+Ecd0CkcD0K1x13QBKDwMqhF3dAAAAAAAAUd0CamZmZmRV3QDMzMzMzC3dA16NwPQobd0A=\"},\"yaxis\":\"y4\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"red\",\"size\":12,\"symbol\":\"triangle-up\"},\"mode\":\"markers\",\"name\":\"MSTR BUY OPEN\",\"showlegend\":true,\"x\":[\"2025-06-05T15:40:00.000000000\",\"2025-06-05T16:31:00.000000000\",\"2025-06-05T18:51:00.000000000\",\"2025-06-05T19:15:00.000000000\"],\"xaxis\":\"x4\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"FK5H4XrId0AAAAAAAJR3QGZmZmZmRndAmpmZmZkDd0A=\"},\"yaxis\":\"y4\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"pink\",\"size\":12,\"symbol\":\"triangle-up\"},\"mode\":\"markers\",\"name\":\"MSTR BUY CLOSE\",\"showlegend\":true,\"x\":[\"2025-06-05T17:34:00.000000000\"],\"xaxis\":\"x4\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"AAAAAABwd0A=\"},\"yaxis\":\"y4\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"blue\",\"size\":12,\"symbol\":\"triangle-down\"},\"mode\":\"markers\",\"name\":\"MSTR SELL OPEN\",\"showlegend\":true,\"x\":[\"2025-06-05T16:46:00.000000000\"],\"xaxis\":\"x4\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"PZtVn6uBd0A=\"},\"yaxis\":\"y4\",\"type\":\"scatter\"},{\"marker\":{\"color\":\"purple\",\"size\":12,\"symbol\":\"triangle-down\"},\"mode\":\"markers\",\"name\":\"MSTR SELL CLOSE\",\"showlegend\":true,\"x\":[\"2025-06-05T16:02:00.000000000\",\"2025-06-05T16:42:00.000000000\",\"2025-06-05T19:10:00.000000000\",\"2025-06-05T19:16:00.000000000\"],\"xaxis\":\"x4\",\"y\":{\"dtype\":\"f8\",\"bdata\":\"5fIf0m++d0DhehSuR3l3QMP1KFyPKndA7FG4HoXzdkA=\"},\"yaxis\":\"y4\",\"type\":\"scatter\"}],                        {\"annotations\":[{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"Testing Period: Scaled Dis-equilibrium with Trading Thresholds\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"Trading Signal Timeline\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":0.7350000000000001,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"COIN Market Data with Trading Signals\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":0.47000000000000003,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{\"size\":16},\"showarrow\":false,\"text\":\"MSTR Market Data with Trading Signals\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":0.20500000000000002,\"yanchor\":\"bottom\",\"yref\":\"paper\"}],\"height\":1200,\"shapes\":[{\"line\":{\"color\":\"purple\",\"dash\":\"dot\",\"width\":2},\"opacity\":0.7,\"type\":\"line\",\"x0\":\"2025-06-05T13:30:00\",\"x1\":\"2025-06-05T20:00:00\",\"xref\":\"x\",\"y0\":2,\"y1\":2,\"yref\":\"y\"},{\"line\":{\"color\":\"purple\",\"dash\":\"dot\",\"width\":2},\"opacity\":0.7,\"type\":\"line\",\"x0\":\"2025-06-05T13:30:00\",\"x1\":\"2025-06-05T20:00:00\",\"xref\":\"x\",\"y0\":-2,\"y1\":-2,\"yref\":\"y\"},{\"line\":{\"color\":\"brown\",\"dash\":\"dot\",\"width\":2},\"opacity\":0.7,\"type\":\"line\",\"x0\":\"2025-06-05T13:30:00\",\"x1\":\"2025-06-05T20:00:00\",\"xref\":\"x\",\"y0\":1,\"y1\":1,\"yref\":\"y\"},{\"line\":{\"color\":\"brown\",\"dash\":\"dot\",\"width\":2},\"opacity\":0.7,\"type\":\"line\",\"x0\":\"2025-06-05T13:30:00\",\"x1\":\"2025-06-05T20:00:00\",\"xref\":\"x\",\"y0\":-1,\"y1\":-1,\"yref\":\"y\"},{\"line\":{\"color\":\"black\",\"dash\":\"solid\",\"width\":1},\"opacity\":0.5,\"type\":\"line\",\"x0\":\"2025-06-05T13:30:00\",\"x1\":\"2025-06-05T20:00:00\",\"xref\":\"x\",\"y0\":0,\"y1\":0,\"yref\":\"y\"}],\"showlegend\":true,\"template\":{\"data\":{\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"white\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"white\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"#C8D4E3\",\"linecolor\":\"#C8D4E3\",\"minorgridcolor\":\"#C8D4E3\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"#C8D4E3\",\"linecolor\":\"#C8D4E3\",\"minorgridcolor\":\"#C8D4E3\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scattermap\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermap\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"white\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"#C8D4E3\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"white\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"#EBF0F8\",\"linecolor\":\"#EBF0F8\",\"ticks\":\"\"},\"bgcolor\":\"white\",\"radialaxis\":{\"gridcolor\":\"#EBF0F8\",\"linecolor\":\"#EBF0F8\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"white\",\"gridcolor\":\"#DFE8F3\",\"gridwidth\":2,\"linecolor\":\"#EBF0F8\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"#EBF0F8\"},\"yaxis\":{\"backgroundcolor\":\"white\",\"gridcolor\":\"#DFE8F3\",\"gridwidth\":2,\"linecolor\":\"#EBF0F8\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"#EBF0F8\"},\"zaxis\":{\"backgroundcolor\":\"white\",\"gridcolor\":\"#DFE8F3\",\"gridwidth\":2,\"linecolor\":\"#EBF0F8\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"#EBF0F8\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"#DFE8F3\",\"linecolor\":\"#A2B1C6\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"#DFE8F3\",\"linecolor\":\"#A2B1C6\",\"ticks\":\"\"},\"bgcolor\":\"white\",\"caxis\":{\"gridcolor\":\"#DFE8F3\",\"linecolor\":\"#A2B1C6\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"#EBF0F8\",\"linecolor\":\"#EBF0F8\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"#EBF0F8\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"#EBF0F8\",\"linecolor\":\"#EBF0F8\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"#EBF0F8\",\"zerolinewidth\":2}}},\"title\":{\"text\":\"Sliding Fit Strategy Analysis - COIN & MSTR\"},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"range\":[\"2025-06-05T13:30:00\",\"2025-06-05T20:00:00\"]},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.7949999999999999,1.0],\"title\":{\"text\":\"Scaled Dis-equilibrium\"}},\"xaxis2\":{\"anchor\":\"y2\",\"domain\":[0.0,1.0],\"range\":[\"2025-06-05T13:30:00\",\"2025-06-05T20:00:00\"]},\"yaxis2\":{\"anchor\":\"x2\",\"domain\":[0.53,0.7350000000000001],\"title\":{\"text\":\"Signal Index\"}},\"xaxis3\":{\"anchor\":\"y3\",\"domain\":[0.0,1.0],\"range\":[\"2025-06-05T13:30:00\",\"2025-06-05T20:00:00\"]},\"yaxis3\":{\"anchor\":\"x3\",\"domain\":[0.265,0.47000000000000003],\"title\":{\"text\":\"COIN Price ($)\"}},\"xaxis4\":{\"anchor\":\"y4\",\"domain\":[0.0,1.0],\"range\":[\"2025-06-05T13:30:00\",\"2025-06-05T20:00:00\"],\"title\":{\"text\":\"Time\"}},\"yaxis4\":{\"anchor\":\"x4\",\"domain\":[0.0,0.20500000000000002],\"title\":{\"text\":\"MSTR Price ($)\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
+              "                            \n",
+              "var gd = document.getElementById('4263a8ce-d351-4fe5-97dc-bf5209fc340a');\n",
+              "var x = new MutationObserver(function (mutations, observer) {{\n",
+              "        var display = window.getComputedStyle(gd).display;\n",
+              "        if (!display || display === 'none') {{\n",
+              "            console.log([gd, 'removed!']);\n",
+              "            Plotly.purge(gd);\n",
+              "            observer.disconnect();\n",
+              "        }}\n",
+              "}});\n",
+              "\n",
+              "// Listen for the removal of the full notebook cells\n",
+              "var notebookContainer = gd.closest('#notebook-container');\n",
+              "if (notebookContainer) {{\n",
+              "    x.observe(notebookContainer, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "// Listen for the clearing of the current output cell\n",
+              "var outputEl = gd.closest('.output');\n",
+              "if (outputEl) {{\n",
+              "    x.observe(outputEl, {childList: true});\n",
+              "}}\n",
+              "\n",
+              "                        })                };            </script>        </div>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "# Interactive Plotly Visualization\n",
+        "import plotly.graph_objects as go\n",
+        "from plotly.subplots import make_subplots\n",
+        "import plotly.express as px\n",
+        "import plotly.offline as pyo\n",
+        "from IPython.display import HTML\n",
+        "\n",
+        "# Configure plotly for offline mode\n",
+        "pyo.init_notebook_mode(connected=True)\n",
+        "\n",
+        "# Strategy-specific interactive visualization\n",
+        "assert pt_bt_config is not None\n",
+        "assert pair.predicted_df_ is not None\n",
+        "\n",
+        "if FIT_METHOD_TYPE == \"SlidingFit\":\n",
+        "    print(\"=== SLIDING FIT INTERACTIVE VISUALIZATION ===\")\n",
+        "    print(\"Note: Sliding strategy visualization with interactive plotly charts\")\n",
+        "    \n",
+        "    # Create consistent timeline - superset of timestamps from both dataframes\n",
+        "    market_timestamps = set(pair.market_data_['tstamp'])\n",
+        "    predicted_timestamps = set(pair.predicted_df_['tstamp'])\n",
+        "    \n",
+        "    # Create superset of all timestamps\n",
+        "    all_timestamps = sorted(market_timestamps.union(predicted_timestamps))\n",
+        "    \n",
+        "    # Create a unified timeline dataframe for consistent plotting\n",
+        "    timeline_df = pd.DataFrame({'tstamp': all_timestamps})\n",
+        "    \n",
+        "    # Merge with predicted data to get dis-equilibrium values\n",
+        "    timeline_df = timeline_df.merge(pair.predicted_df_[['tstamp', 'disequilibrium', 'scaled_disequilibrium']], \n",
+        "                                   on='tstamp', how='left')\n",
+        "    \n",
+        "    # Get Symbol_A and Symbol_B market data\n",
+        "    colname_a, colname_b = pair.colnames()\n",
+        "    symbol_a_data = pair.market_data_[['tstamp', colname_a]].copy()\n",
+        "    symbol_b_data = pair.market_data_[['tstamp', colname_b]].copy()\n",
+        "    \n",
+        "    print(f\"Using consistent timeline with {len(timeline_df)} timestamps\")\n",
+        "    print(f\"Timeline range: {timeline_df['tstamp'].min()} to {timeline_df['tstamp'].max()}\")\n",
+        "    \n",
+        "    # Create subplots with price charts at bottom\n",
+        "    fig = make_subplots(\n",
+        "        rows=4, cols=1,\n",
+        "        subplot_titles=[\n",
+        "            'Testing Period: Scaled Dis-equilibrium with Trading Thresholds',\n",
+        "            'Trading Signal Timeline',\n",
+        "            f'{SYMBOL_A} Market Data with Trading Signals',\n",
+        "            f'{SYMBOL_B} Market Data with Trading Signals'\n",
+        "        ],\n",
+        "        vertical_spacing=0.06,\n",
+        "        specs=[[{\"secondary_y\": False}],\n",
+        "               [{\"secondary_y\": False}],\n",
+        "               [{\"secondary_y\": False}],\n",
+        "               [{\"secondary_y\": False}]]\n",
+        "    )\n",
+        "    \n",
+        "    # 1. Scaled dis-equilibrium with thresholds - using consistent timeline\n",
+        "    fig.add_trace(\n",
+        "        go.Scatter(\n",
+        "            x=timeline_df['tstamp'],\n",
+        "            y=timeline_df['scaled_disequilibrium'],\n",
+        "            name='Scaled Dis-equilibrium',\n",
+        "            line=dict(color='green', width=2),\n",
+        "            opacity=0.8\n",
+        "        ),\n",
+        "        row=1, col=1\n",
+        "    )\n",
+        "    \n",
+        "    # Add threshold lines to first subplot\n",
+        "    fig.add_shape(\n",
+        "        type=\"line\",\n",
+        "        x0=timeline_df['tstamp'].min(),\n",
+        "        x1=timeline_df['tstamp'].max(),\n",
+        "        y0=pt_bt_config['dis-equilibrium_open_trshld'],\n",
+        "        y1=pt_bt_config['dis-equilibrium_open_trshld'],\n",
+        "        line=dict(color=\"purple\", width=2, dash=\"dot\"),\n",
+        "        opacity=0.7,\n",
+        "        row=1, col=1\n",
+        "    )\n",
+        "    \n",
+        "    fig.add_shape(\n",
+        "        type=\"line\",\n",
+        "        x0=timeline_df['tstamp'].min(),\n",
+        "        x1=timeline_df['tstamp'].max(),\n",
+        "        y0=-pt_bt_config['dis-equilibrium_open_trshld'],\n",
+        "        y1=-pt_bt_config['dis-equilibrium_open_trshld'],\n",
+        "        line=dict(color=\"purple\", width=2, dash=\"dot\"),\n",
+        "        opacity=0.7,\n",
+        "        row=1, col=1\n",
+        "    )\n",
+        "    \n",
+        "    fig.add_shape(\n",
+        "        type=\"line\",\n",
+        "        x0=timeline_df['tstamp'].min(),\n",
+        "        x1=timeline_df['tstamp'].max(),\n",
+        "        y0=pt_bt_config['dis-equilibrium_close_trshld'],\n",
+        "        y1=pt_bt_config['dis-equilibrium_close_trshld'],\n",
+        "        line=dict(color=\"brown\", width=2, dash=\"dot\"),\n",
+        "        opacity=0.7,\n",
+        "        row=1, col=1\n",
+        "    )\n",
+        "    \n",
+        "    fig.add_shape(\n",
+        "        type=\"line\",\n",
+        "        x0=timeline_df['tstamp'].min(),\n",
+        "        x1=timeline_df['tstamp'].max(),\n",
+        "        y0=-pt_bt_config['dis-equilibrium_close_trshld'],\n",
+        "        y1=-pt_bt_config['dis-equilibrium_close_trshld'],\n",
+        "        line=dict(color=\"brown\", width=2, dash=\"dot\"),\n",
+        "        opacity=0.7,\n",
+        "        row=1, col=1\n",
+        "    )\n",
+        "    \n",
+        "    fig.add_shape(\n",
+        "        type=\"line\",\n",
+        "        x0=timeline_df['tstamp'].min(),\n",
+        "        x1=timeline_df['tstamp'].max(),\n",
+        "        y0=0,\n",
+        "        y1=0,\n",
+        "        line=dict(color=\"black\", width=1, dash=\"solid\"),\n",
+        "        opacity=0.5,\n",
+        "        row=1, col=1\n",
+        "    )\n",
+        "    \n",
+        "    # 2. Trading signals timeline if available - using consistent timeline\n",
+        "    if pair_trades is not None and len(pair_trades) > 0:\n",
+        "        # Separate trades by action and status for different colors\n",
+        "        buy_open_trades = pair_trades[(pair_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                     (pair_trades['status'] == 'OPEN')]\n",
+        "        buy_close_trades = pair_trades[(pair_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                      (pair_trades['status'] == 'CLOSE')]\n",
+        "        sell_open_trades = pair_trades[(pair_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                      (pair_trades['status'] == 'OPEN')]\n",
+        "        sell_close_trades = pair_trades[(pair_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                       (pair_trades['status'] == 'CLOSE')]\n",
+        "        \n",
+        "        # Create y-values for timeline visualization\n",
+        "        trade_indices = list(range(len(pair_trades)))\n",
+        "        \n",
+        "        # Add trading signals with different colors based on action and status\n",
+        "        if len(buy_open_trades) > 0:\n",
+        "            buy_open_indices = [i for i, (_, row) in enumerate(pair_trades.iterrows()) \n",
+        "                               if 'BUY' in row['action'] and row['status'] == 'OPEN']\n",
+        "            fig.add_trace(\n",
+        "                go.Scatter(\n",
+        "                    x=buy_open_trades['time'],\n",
+        "                    y=buy_open_indices,\n",
+        "                    mode='markers',\n",
+        "                    name='BUY OPEN',\n",
+        "                    marker=dict(color='red', size=10, symbol='circle')\n",
+        "                ),\n",
+        "                row=2, col=1\n",
+        "            )\n",
+        "        \n",
+        "        if len(buy_close_trades) > 0:\n",
+        "            buy_close_indices = [i for i, (_, row) in enumerate(pair_trades.iterrows()) \n",
+        "                                if 'BUY' in row['action'] and row['status'] == 'CLOSE']\n",
+        "            fig.add_trace(\n",
+        "                go.Scatter(\n",
+        "                    x=buy_close_trades['time'],\n",
+        "                    y=buy_close_indices,\n",
+        "                    mode='markers',\n",
+        "                    name='BUY CLOSE',\n",
+        "                    marker=dict(color='pink', size=10, symbol='circle')\n",
+        "                ),\n",
+        "                row=2, col=1\n",
+        "            )\n",
+        "        \n",
+        "        if len(sell_open_trades) > 0:\n",
+        "            sell_open_indices = [i for i, (_, row) in enumerate(pair_trades.iterrows()) \n",
+        "                                if 'SELL' in row['action'] and row['status'] == 'OPEN']\n",
+        "            fig.add_trace(\n",
+        "                go.Scatter(\n",
+        "                    x=sell_open_trades['time'],\n",
+        "                    y=sell_open_indices,\n",
+        "                    mode='markers',\n",
+        "                    name='SELL OPEN',\n",
+        "                    marker=dict(color='blue', size=10, symbol='circle')\n",
+        "                ),\n",
+        "                row=2, col=1\n",
+        "            )\n",
+        "        \n",
+        "        if len(sell_close_trades) > 0:\n",
+        "            sell_close_indices = [i for i, (_, row) in enumerate(pair_trades.iterrows()) \n",
+        "                                 if 'SELL' in row['action'] and row['status'] == 'CLOSE']\n",
+        "            fig.add_trace(\n",
+        "                go.Scatter(\n",
+        "                    x=sell_close_trades['time'],\n",
+        "                    y=sell_close_indices,\n",
+        "                    mode='markers',\n",
+        "                    name='SELL CLOSE',\n",
+        "                    marker=dict(color='purple', size=10, symbol='circle')\n",
+        "                ),\n",
+        "                row=2, col=1\n",
+        "            )\n",
+        "    \n",
+        "    # 3. Symbol_A Market Data with Trading Signals (moved to bottom)\n",
+        "    fig.add_trace(\n",
+        "        go.Scatter(\n",
+        "            x=symbol_a_data['tstamp'],\n",
+        "            y=symbol_a_data[colname_a],\n",
+        "            name=f'{SYMBOL_A} Price',\n",
+        "            line=dict(color='blue', width=2),\n",
+        "            opacity=0.8\n",
+        "        ),\n",
+        "        row=3, col=1\n",
+        "    )\n",
+        "    \n",
+        "    # Add trading signals for Symbol_A if available\n",
+        "    if pair_trades is not None and len(pair_trades) > 0:\n",
+        "        # Filter trades for Symbol_A\n",
+        "        symbol_a_trades = pair_trades[pair_trades['symbol'] == SYMBOL_A]\n",
+        "        \n",
+        "        if len(symbol_a_trades) > 0:\n",
+        "            # Separate trades by action and status for different colors\n",
+        "            buy_open_trades = symbol_a_trades[(symbol_a_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                             (symbol_a_trades['status'] == 'OPEN')]\n",
+        "            buy_close_trades = symbol_a_trades[(symbol_a_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                              (symbol_a_trades['status'] == 'CLOSE')]\n",
+        "            sell_open_trades = symbol_a_trades[(symbol_a_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                              (symbol_a_trades['status'] == 'OPEN')]\n",
+        "            sell_close_trades = symbol_a_trades[(symbol_a_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                               (symbol_a_trades['status'] == 'CLOSE')]\n",
+        "            \n",
+        "            # Add BUY OPEN signals\n",
+        "            if len(buy_open_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=buy_open_trades['time'],\n",
+        "                        y=buy_open_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_A} BUY OPEN',\n",
+        "                        marker=dict(color='red', size=12, symbol='triangle-up'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=3, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add BUY CLOSE signals\n",
+        "            if len(buy_close_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=buy_close_trades['time'],\n",
+        "                        y=buy_close_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_A} BUY CLOSE',\n",
+        "                        marker=dict(color='pink', size=12, symbol='triangle-up'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=3, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add SELL OPEN signals\n",
+        "            if len(sell_open_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=sell_open_trades['time'],\n",
+        "                        y=sell_open_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_A} SELL OPEN',\n",
+        "                        marker=dict(color='blue', size=12, symbol='triangle-down'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=3, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add SELL CLOSE signals\n",
+        "            if len(sell_close_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=sell_close_trades['time'],\n",
+        "                        y=sell_close_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_A} SELL CLOSE',\n",
+        "                        marker=dict(color='purple', size=12, symbol='triangle-down'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=3, col=1\n",
+        "                )\n",
+        "                  \n",
+        "          # 4. Symbol_B Market Data with Trading Signals\n",
+        "    fig.add_trace(\n",
+        "        go.Scatter(\n",
+        "            x=symbol_b_data['tstamp'],\n",
+        "            y=symbol_b_data[colname_b],\n",
+        "            name=f'{SYMBOL_B} Price',\n",
+        "            line=dict(color='orange', width=2),\n",
+        "            opacity=0.8\n",
+        "        ),\n",
+        "        row=4, col=1\n",
+        "    )\n",
+        "    \n",
+        "    # Add trading signals for Symbol_B if available\n",
+        "    if pair_trades is not None and len(pair_trades) > 0:\n",
+        "        # Filter trades for Symbol_B\n",
+        "        symbol_b_trades = pair_trades[pair_trades['symbol'] == SYMBOL_B]\n",
+        "        \n",
+        "        if len(symbol_b_trades) > 0:\n",
+        "            # Separate trades by action and status for different colors\n",
+        "            buy_open_trades = symbol_b_trades[(symbol_b_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                             (symbol_b_trades['status'] == 'OPEN')]\n",
+        "            buy_close_trades = symbol_b_trades[(symbol_b_trades['action'].str.contains('BUY', na=False)) & \n",
+        "                                              (symbol_b_trades['status'] == 'CLOSE')]\n",
+        "            sell_open_trades = symbol_b_trades[(symbol_b_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                              (symbol_b_trades['status'] == 'OPEN')]\n",
+        "            sell_close_trades = symbol_b_trades[(symbol_b_trades['action'].str.contains('SELL', na=False)) & \n",
+        "                                               (symbol_b_trades['status'] == 'CLOSE')]\n",
+        "            \n",
+        "            # Add BUY OPEN signals\n",
+        "            if len(buy_open_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=buy_open_trades['time'],\n",
+        "                        y=buy_open_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_B} BUY OPEN',\n",
+        "                        marker=dict(color='red', size=12, symbol='triangle-up'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add BUY CLOSE signals\n",
+        "            if len(buy_close_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=buy_close_trades['time'],\n",
+        "                        y=buy_close_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_B} BUY CLOSE',\n",
+        "                        marker=dict(color='pink', size=12, symbol='triangle-up'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add SELL OPEN signals\n",
+        "            if len(sell_open_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=sell_open_trades['time'],\n",
+        "                        y=sell_open_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_B} SELL OPEN',\n",
+        "                        marker=dict(color='blue', size=12, symbol='triangle-down'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "            \n",
+        "            # Add SELL CLOSE signals\n",
+        "            if len(sell_close_trades) > 0:\n",
+        "                fig.add_trace(\n",
+        "                    go.Scatter(\n",
+        "                        x=sell_close_trades['time'],\n",
+        "                        y=sell_close_trades['price'],\n",
+        "                        mode='markers',\n",
+        "                        name=f'{SYMBOL_B} SELL CLOSE',\n",
+        "                        marker=dict(color='purple', size=12, symbol='triangle-down'),\n",
+        "                        showlegend=True\n",
+        "                    ),\n",
+        "                    row=4, col=1\n",
+        "                )\n",
+        "  \n",
+        "    # Update layout\n",
+        "    fig.update_layout(\n",
+        "        height=1200,\n",
+        "        title_text=f\"Sliding Fit Strategy Analysis - {SYMBOL_A} & {SYMBOL_B}\",\n",
+        "        showlegend=True,\n",
+        "        template=\"plotly_white\"\n",
+        "    )\n",
+        "    \n",
+        "    # Update y-axis labels\n",
+        "    fig.update_yaxes(title_text=\"Scaled Dis-equilibrium\", row=1, col=1)\n",
+        "    fig.update_yaxes(title_text=\"Signal Index\", row=2, col=1)\n",
+        "    fig.update_yaxes(title_text=f\"{SYMBOL_A} Price ($)\", row=3, col=1)\n",
+        "    fig.update_yaxes(title_text=f\"{SYMBOL_B} Price ($)\", row=4, col=1)\n",
+        "    \n",
+        "    # Update x-axis labels and ensure consistent time range\n",
+        "    time_range = [timeline_df['tstamp'].min(), timeline_df['tstamp'].max()]\n",
+        "    fig.update_xaxes(range=time_range, row=1, col=1)\n",
+        "    fig.update_xaxes(range=time_range, row=2, col=1)\n",
+        "    fig.update_xaxes(range=time_range, row=3, col=1)\n",
+        "    fig.update_xaxes(title_text=\"Time\", range=time_range, row=4, col=1)\n",
+        "    \n",
+        "    # Display using plotly offline mode\n",
+        "    pyo.iplot(fig)\n",
+        "\n",
+        "else:\n",
+        "    print(\"No interactive visualization data available - strategy may not have run successfully\")\n"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -1131,51 +4238,9 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 11,
+      "execution_count": null,
       "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "================================================================================\n",
-            "PAIRS TRADING BACKTEST SUMMARY\n",
-            "================================================================================\n",
-            "\n",
-            "Pair: COIN & MSTR\n",
-            "Strategy: SlidingFit\n",
-            "Configuration: equity\n",
-            "Data file: 20250605.mktdata.ohlcv.db\n",
-            "Trading date: 20250605\n",
-            "\n",
-            "Strategy Parameters:\n",
-            "  Training window: 120 minutes\n",
-            "  Open threshold: 2\n",
-            "  Close threshold: 1\n",
-            "  Funding per pair: $2000\n",
-            "\n",
-            "Sliding Window Analysis:\n",
-            "  Total data points: 391\n",
-            "  Maximum iterations: 271\n",
-            "  Analysis type: Dynamic sliding window\n",
-            "\n",
-            "Trading Signals: 20 generated\n",
-            "  Unique trade times: 10\n",
-            "  BUY signals: 10\n",
-            "  SELL signals: 10\n",
-            "\n",
-            "First few trading signals:\n",
-            "  1. SELL COIN @ $260.46 at 2025-06-05 15:40:00\n",
-            "  2. BUY MSTR @ $380.53 at 2025-06-05 15:40:00\n",
-            "  3. BUY COIN @ $259.39 at 2025-06-05 16:02:00\n",
-            "  4. SELL MSTR @ $379.90 at 2025-06-05 16:02:00\n",
-            "  5. SELL COIN @ $259.62 at 2025-06-05 16:31:00\n",
-            "  ... and 15 more signals\n",
-            "\n",
-            "================================================================================\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
         "print(\"=\" * 80)\n",
         "print(\"PAIRS TRADING BACKTEST SUMMARY\")\n",
@@ -1196,6 +4261,7 @@
         "# Strategy-specific summary\n",
         "if FIT_METHOD_TYPE == \"StaticFit\":\n",
         "    if 'is_cointegrated' in locals() and is_cointegrated:\n",
+        "        assert pair.predicted_df_ is not None, \"predicted_df_ is None\"\n",
         "        print(f\"\\nCointegration Analysis:\")\n",
         "        print(f\"  ✓ Pair is cointegrated\")\n",
         "        print(f\"  VECM Beta coefficients: {pair.vecm_fit_.beta.flatten()}\")\n",
diff --git a/sync_visualization.py b/sync_visualization.py
deleted file mode 100644
index 0519ecb..0000000
--- a/sync_visualization.py
+++ /dev/null
@@ -1 +0,0 @@
- 
\ No newline at end of file