From 0b64e948ba41b86a8afa0ca578507a3a5223f012 Mon Sep 17 00:00:00 2001
From: Laurin Luttmann <laurin.luttmann@gmail.com>
Date: Mon, 25 Nov 2024 15:41:47 +0100
Subject: [PATCH 1/2] [BugFix] fixed taillard instances in scheduling nb

---
 examples/other/2-scheduling.ipynb | 437 +++++-------------------------
 1 file changed, 74 insertions(+), 363 deletions(-)

diff --git a/examples/other/2-scheduling.ipynb b/examples/other/2-scheduling.ipynb
index ffe6782b..4b2423de 100644
--- a/examples/other/2-scheduling.ipynb
+++ b/examples/other/2-scheduling.ipynb
@@ -13,47 +13,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Requirement already satisfied: torch_geometric in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (2.5.0)\n",
-      "Requirement already satisfied: tqdm in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (4.66.1)\n",
-      "Requirement already satisfied: numpy in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (1.26.3)\n",
-      "Requirement already satisfied: scipy in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (1.11.4)\n",
-      "Requirement already satisfied: fsspec in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (2023.12.2)\n",
-      "Requirement already satisfied: jinja2 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (3.1.3)\n",
-      "Requirement already satisfied: aiohttp in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (3.9.1)\n",
-      "Requirement already satisfied: requests in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (2.31.0)\n",
-      "Requirement already satisfied: pyparsing in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (3.1.1)\n",
-      "Requirement already satisfied: scikit-learn in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (1.4.1.post1)\n",
-      "Requirement already satisfied: psutil>=5.8.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from torch_geometric) (5.9.7)\n",
-      "Requirement already satisfied: attrs>=17.3.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from aiohttp->torch_geometric) (23.2.0)\n",
-      "Requirement already satisfied: multidict<7.0,>=4.5 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from aiohttp->torch_geometric) (6.0.4)\n",
-      "Requirement already satisfied: yarl<2.0,>=1.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from aiohttp->torch_geometric) (1.9.4)\n",
-      "Requirement already satisfied: frozenlist>=1.1.1 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from aiohttp->torch_geometric) (1.4.1)\n",
-      "Requirement already satisfied: aiosignal>=1.1.2 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from aiohttp->torch_geometric) (1.3.1)\n",
-      "Requirement already satisfied: async-timeout<5.0,>=4.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from aiohttp->torch_geometric) (4.0.3)\n",
-      "Requirement already satisfied: MarkupSafe>=2.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from jinja2->torch_geometric) (2.1.3)\n",
-      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from requests->torch_geometric) (3.3.2)\n",
-      "Requirement already satisfied: idna<4,>=2.5 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from requests->torch_geometric) (3.6)\n",
-      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from requests->torch_geometric) (1.26.18)\n",
-      "Requirement already satisfied: certifi>=2017.4.17 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from requests->torch_geometric) (2023.11.17)\n",
-      "Requirement already satisfied: joblib>=1.2.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from scikit-learn->torch_geometric) (1.3.2)\n",
-      "Requirement already satisfied: threadpoolctl>=2.0.0 in /Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages (from scikit-learn->torch_geometric) (3.3.0)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! pip install torch_geometric"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!conda info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -78,7 +56,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -96,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -121,24 +99,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "jupyter": {
      "source_hidden": true
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x600 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Create a bipartite graph from the adjacency matrix\n",
     "G = nx.Graph()\n",
@@ -213,7 +180,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -236,18 +203,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "torch.Size([1, 60, 32])\n",
-      "torch.Size([1, 5, 32])\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "encoder = HetGNNEncoder(embed_dim=32, num_layers=2)\n",
     "(ma_emb, op_emb), init = encoder(td)\n",
@@ -264,20 +222,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "tensor([[ 0,  4, 10, 15, 21, 27, 33, 39, 45, 49]])"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# next operation per job\n",
     "td[\"next_op\"]"
@@ -285,17 +232,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "torch.Size([1, 51])\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "decoder = L2DDecoder(env_name=env.name, embed_dim=32)\n",
     "logits, mask = decoder(td, (ma_emb, op_emb), num_starts=0)\n",
@@ -305,7 +244,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -334,47 +273,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Figure size 640x480 with 0 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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Ozl1pEzCW/PwEo+Xh4e9hbe3Cb789Q6lWjZ/fA3SN+JBf40dTUHCqSet2vYBb3Di5N5X0i/kolAp6j+7AA1MiWf/6AcpK/yx6ft93mV+3XTA81paWmzSPxqpP/r7tXRg5JZIjO5LZtzERnU6PV6ATer2+SbEL1SUc2JrEvoM/sOXgp3w0/xVGR7/CullTQaHA0d2DvetWk3U5BY2dI0P+8Tze3t6mWG2TOl1QzN+OJxkel1fZLr/lF7M5Tc1ljRY3ayteau/Hhls70uuXUzS+JBbCMhr8Napt27Zs2LCB4uJiw7KSkhLWr19PUFCQSZOrDw8PD5ydnS0Wb+LEiXTr1q3J/fyjX3s2/HqJrw6nci69gLlbT1BcWs6Ynm1NkGXdYhMzWLIrkZ2/t6BRuuvpyqAg/c9/RdmWidtvGuRerhihu3wEcpIhaQ+oL9T50qZSqVQ8/PDDbNu2rdpo3IEDB9i/fz+pqakWi5uens5//vMfEhMTUavVXLhwgd27d3PLLbc0ahTGysqBiC5LSTj9MmVlxqPTri7dSU39nLz83ygpucTFix9RVpaHi3NEk9fvets/PM7pX66RfbWQrMsF7I5JwNnTDu8gF6N2ZaU6ivJKDf+0JS2jsKtP/v3+1onf9lziyM5ksq8WkpNWxLnD6ejKmlbYXTyRRfLJLNIuZ3H27Fm+W7uC0pIS/DuFknUpmW3/fJvzR34lN+0a544dYe7cubi6ujZ1lU2uTA8ZpWWGf9naP/ftF1ezOJBbyKWSUk4UFLPo/FUC7VS0tVM1Y8ZC1E+D/zJ3796dtm3bsnnzZsOyzZs3ExQUxG233WbUdseOHfTr1w83Nzc8PT0ZMWIESUlJRm1SU1MZO3YsHh4eODo60rNnTw4ePGjUZt26dbRr1w5XV1ceffRR8vPzDc8NGDCAadOmGR63a9eOhQsXEhUVhbOzM0FBQXz22WdG/V26dIkxY8bg5uaGh4cHo0aN4uLFi3Wu+/Lly8nJyeGll16qs21tbKwURLRxJe5cpmGZXg9x5zLpHuzWpL5bFY+OMOM0TD0OD60A10DLxA0dWnHI9W8xEH0Ont0H3Z+0SOhhw4aRmJjI+fPnLRKvMXHt7OzQaDTodA0fuwi95XUyM39Erf652nO5eUfw9RmOtbUroMDXZwRKpS3qnIPVOzIxW/uKgxeaIq3R8lt6+RL1Xj8efbUXvUd3wNqmZR1SrHR9/vbONvh1cKU4X8tD0T146t1+jJ5+G/4dTVtgKZVKbhtwLza2dlxJPF1jG1dXV8rLW0ZBXFUHBxXH7uzCwd5hfBQWRBvbmo/8OCiVPOrvQXKxhisabY1thGhJGvVXKioqijVr1hger169mqeeeqpau8LCQqZPn86hQ4fYvXs3SqWSBx980PCBUFBQQP/+/bl8+TLffvstx48fZ+bMmUYfGElJSWzdupXt27ezfft29u7dy6JFi2rNb8mSJfTs2ZOjR4/y3HPPMXnyZM6cqTgvRqvVMnjwYJydndm3bx9xcXE4OTkxZMgQSktvfAj01KlTLFiwgM8//7zJ54u4O6iwtlKSWWB8vkZGgQZvJ9sm9d1qpB6Crc/BFw/D9ungHgxP/Q9UTuaP7d4Obp8I2Umw7iE4tAqGvgO3jjVr2IiICPz9/dm9e7dZ4zQlroODA3fffTeHDx9ucBxfnxE4O3ch6fziGp8/efL/UCis6X/3EQYOSKBz5zf57cRkiouTGxyrQRQVo1tXzuWQfaXQsDjx1zS+X3OKrf88ypGdyYTe4cd9UeHmzaUxasjfxcsegF4j2nNq/xW2fXiMjEv5jJp2G64+9k0O6RHgyCf/nYdGo+FvU2bw7XtvkX35UrV2ji6uvPrqq2RlZTU5pikdyStkakIKY48nMSsxlSB7W77p3glHqz//tk8I8CTprq6c79+NezxcGHMsCW0TD2MLYQmNunhi3LhxzJkzh+Tkij+4cXFxbNiwgdjYWKN2Dz/8sNHj1atX4+3tzalTp4iIiGD9+vVkZGQQHx+Ph4cHACEhIUav0el0rF271nC4dfz48ezevZu33nrrhvkNGzaM5557DoBZs2axdOlSfvzxR0JDQ9m4cSM6nY6VK1eiUCgAWLNmDW5ubsTGxnL//fdX60+j0TB27FgWL15MUFBQvUY1NBqN0cnleXl5db5GVHHuhz9/TvsdLh+CaSegy4NwdJ15YyuUFSN2uxdUPL72G/iEQc8oOP5vs4R0cXFhyJAhrFu3jrIyC51L2MC4tra2PPbYY2RkZFT7Xa+Lra0/t9zyKkePPoFOV/MXqA7tp2Nt7cKRo+PRarPx9hpERJcPOXzk7xQWJjYoXkP0f/QWPNo4snnxEaPlp/ZfMfycfaWQwtxSRr94Gy5e9uRlFl/fTbOpKf8//rTx+77LnP7lKgCZl84RGOpB2J3+HNjatBHhnLQiXnv6Q3Yn/Jt3ol9kyPMvsnH+bKPiTmVvz9OzX+fUqVP4+vri5+dXS4+WtSf7z6M+CYUlHMkr4lCfcB7wcePfVytO+diUpmavOh9flQ2Tg3z4LKIdDxw5i0YnxZ1o2RpV2Hl7ezN8+HDWrl2LXq9n+PDheHl5VWt39uxZXnvtNQ4ePEhmZqZhJC4lJYWIiAiOHTvGbbfdZijqatKuXTujc+j8/f1JT0+vNb+q58ApFAr8/PwMrzl+/Djnzp2rdl5eSUlJtcPElebMmUNYWBjjxo2rNW5Vb7/9Nq+//nqNz6mLSikr1+F13eict5MtGQVy1VWNSnIhKwk8Opg/Vv41yLjuyseMRAh7wGwhAwICcHJy4tlnnzUsUyqVBAcH06tXL954440mn/TelLgqlYpx48ZRWlpq+HLUEM7OEahUXtx++7dV4ljj5taLwDbjOXBwEG3bPsGBg0MoLDwLQEHBadzcbicwcDxnzrxqmhW+zl2P3kJwVy+2LDlCYU7tv3tpFyrOCXT1aTmF3Y3yL8ytKJ6zrxYatVdfK8TZw67JcXXletKvZHPkyBH+u/pTOnWJoPuwB/hhxUcA2NjZ8/CcBRQUFvLggw/y88/VD723JHll5Zwv0tDe/s+/yfnlOvKLS7lQXMrhkxc5c1cEQ71c2Zqe03yJClEPjZ7uJCoqihdeeAGAjz76qMY2I0eOJDg4mBUrVhAQEIBOpyMiIsJwyNPevu5DAtdf8apQKOr8UKntNQUFBfTo0YMvv/yy2utudOXWnj17OHHiBF9//TWA4QPWy8uLuXPn1ljAzZkzh+nTpxse5+Xl0bZtxYUR2nI9Jy/ncmeIl2GKEYUC7gzx5POfzXzY6WalcgSP9vDbBvPHunQQPI1HjvHsCLnVDzWZyvnz5/n444+Nlo0aNYrMzEzi4uLMUtTVN66trS3jxo2jvLycf//7340aUVSrf+bAwaFGy8LD3qGwKInk5M9QKiuKDb3e+Hdbry9HYabpNu969BY6RHqz9Z9HyM+qe9oYr7YVXwaLclvGl6/a8s/PKqEgR4Obr4PRcjcfB1J+N/1hUYVCgZV1xd9dlb09D7/8BuVaLSvnzW7StDiW4mClJNheRdq1ms+hU/zxv20Lm7ZFiJo0urCrPCdNoVAwePDgas9nZWVx5swZVqxYwV133QXA/v37jdp069aNlStXkp2dXeuonSl1796djRs34uPjg4uLS90vADZt2mR0FXB8fDxRUVHs27ePjh071vgaW1tbbG1vfL7cyv0XWPK3WzmRmsOxS7lM7NcOB5U1Xx02X/FQlYPKinaejobHbT0cCPd3IaeolCu5pp0brVHufxPO/K+imHL2gwEvg64cTnxt/ti/fAwTd8FdM+D3LdCmO/SYANummi1kaWlptZForVZLcXGxYbmTkxNOTk6G3xUfHx9KS0vJzc01en+aMq6trS3jx4/HxsaGDRs2GL2vCwsL611wlpcXVjucWl5ehFabQ2FhIgqFNUVFF+nc+U3OnX0bbVkO3l6D8PDox/Hfnm7UutXm7rG3cMvtvny3/ATaknIcXCqudtQUl1Gu1eHiZc8tvXxJPplFSaEWzzZO9PtbJy4nqsm6XFhH7+ZXV/4AR3cl02tkB7IuF5B5qYDQ3n64+zmw47OTTYrde3QHkk9m45XrRkREBMOjnqVteFc2LXytoqib+wY2Klu++9d72Dk44uvri7V1y5oydV7HAHZl5ZJaosVXZU10e390etiaribITsUoHzf2ZueTpS3D39aG/wv2pUSnY3eWnFIjWr5G/7ZZWVmRkJBg+Pl67u7ueHp68tlnn+Hv709KSgqzZ882ajN27FgWLlzI6NGjefvtt/H39+fo0aMEBATQp0+fxqZWq8cff5zFixczatQoFixYQGBgIMnJyWzevJmZM2cSGFj9ysvri7fMzIqrWcPCwho9j932367i4ajixUG34O1sS8KVPJ5c/SuZBeafww6gW6ArG575cxu/OqLipPCvD1/ipa9+s0gOtXIJgEdWgb0HFGVCygFYeR8UWeAk7CtHYOPjcO886D8T1MmwYw6c+Mr8sWvRs2dPBgwYYHgcFRUFUOck3k3h7+9v+J2YOtW4sH3//ffJyckxSRy9voxjxycS0jGaW29dgZWVA0VFyZxKiCYrK9YkMarq2r9inR6c0d1o+e6YU5z+5Rq6ch2Bnd259Z62WNsqKVBrSDqazqHvLpo8l8aoK3+A3/akYm1jRd9HOmHnaFMxOfEHx5p8GNneWcV9T4Uxcko3ZuZMICc1hU0LXyP5xDECw7sS0KkzAP9YthKABU2KZh7+tjYsD2+Hu40VWaVl/JpbyLDDiWRpy7FWKOjt5sQzbb1xtbYio7SMAzkFjDx8lkyt5c5/FaKxmvQ1qrYRL6VSyYYNG5gyZQoRERGEhoaybNkyow8mlUrFrl27mDFjBsOGDaOsrIzw8PAbHto1BQcHB3766SdmzZrFQw89RH5+Pm3atOHee++t9wieqXz+SzKf/9I8h14PnM+m3ez/Nkvsevk6qnnjJ+6s+NeMrp/oOzY2tsEXLTQ17sWLF5k/f75Z4hw5+rjR4+Lii5w4+bxZYl3vo0l7an2+QK1h6z8tc5eRxqgr/0pHdiZzZKdp/8b8uK5iWpP4xB+I+fFtpg3qR6B7xTQqqadOsOTvIwxtU9W5vP/9fg4fPkz37t1r7K85TDp1422SVlrG479ZdrohIUypQYVdXXeU2Lp1q9Hj++67j1OnjGeMv/7QTXBwsOHctevNnz+/2ofKtGnTjOatu/6Drqb56K4fzfDz8yMmJqbGmPUxYMAAs53zJIQQQgjRWHImqBBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEK2Hd3An81WizU1Gq7OpsV5abVtE+65K5U7KIyvVJyNBZLOYFtd7iMWuKn5GR0Szxq1Kr1YBlcqmMlZJSatY4lf1nFVzjUkaiWWM1VVbBNQCu5aQ0cyamU7lO6XkFN2xT23PmUJZywaLx6tLS8hF/DQq9Xq9v7iT+CvLy8nB1dW3YixRK0DdPUWIOSgXoLPxus1JAeTO+wxUKBS3lV8ySuSiVoLPAW9dScUxBoVCib0W/z1C/95S9vR2nT58hKCjIbHmkpKQQGhZGSVGR2WI0lp2DA2cSEsy6/s2h8jMtNzcXFxeX5k5HVCEjdha2d+9enJyc6tVWo9Fga2tr5owspznWp7m3YXPHr8qSuVgqVkvavnW5mXKtr/qsk5eXl9mLmqCgIM4kJJCZmWnWOI1hifUXoioZsbMQ+XYjhBCitZDPtJZLLp4QQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglpLATQgghhGglrJs7ASGEEEK0TuXl5Wi12uZO46ZmY2ODlZVVvdtLYSeEEEIIk9Lr9Vy7do2cnJzmTqVVcHNzw8/PD4VCUWdbKeyEEEIIYVKVRZ2Pjw8ODg71KkhEdXq9nqKiItLT0wHw9/ev8zVS2AkhhBDCZMrLyw1FnaenZ3Onc9Ozt7cHID09HR8fnzoPy8rFE0IIIYQwmcpz6hwcHJo5k9ajclvW53xFKeyEEEIIYXJy+NV0GrItpbATQgghhGig2NhYFApFi7tARM6xE0IIIYRFXM4pRl1YarF47o4q2rjZ17v9hAkTyMnJYevWrWbLqaSkhBkzZrBhwwY0Gg2DBw/m448/xtfX1yT9S2FnYceOHcPJyam50zArjUaDra1tq49pDrIeN1dMU6ia982wDvXJ0cvLi6CgIAtldPNISUkhMzOz2eI39365nFPMPe/FoinTWSymrbWSPS8NaFBxZ24vvvgi//3vf/nqq69wdXXlhRde4KGHHiIuLs4k/UthZ2H9+/dv7hTMTqkEneV+b5stpjnIejQhpkKJTn/zbbyqed8M61CfHB3s7Ug4fUaKuypSUlII6xxGUXFRs+XgYO9AwumEZtsv6sJSixZ1AJoyHerC0kYVdhqNhujoaDZs2EBeXh49e/Zk6dKl3H777Ubt4uLimDNnDomJiURGRrJy5UoiIiJq7DM3N5dVq1axfv167rnnHgDWrFlDWFgYBw4coHfv3g1fyetIYWdh06d70qmTXXOnYTYpKaW8/XYGQyJuobO/j0Vinr6azo6TicyZ401QkMoiMc3h118LWbMm56Zfj8r3wBQvL+52tMzo9E+FBSzLzGTZiFcI8Qy2SExT+PH8ARbvW8WyEa9wKfeq4eeWug7nspKZsv1N3hhoy7BONX98JGToGLelmMzMTCnsqsjMzKSouKjZ9m/lvpP9Un8zZ85k06ZNxMTEEBwczLvvvsvgwYM5d+4cHh4ehnbR0dF88MEH+Pn58fLLLzNy5EgSExOxsbGp1ufhw4fRarXcd999hmWdO3cmKCiIX375RQq7m1FgoIpOt7TsQy2m4OHoQKC7q0VipecVABAUdHNv25SUivNObvb1qBRobUO4nWW+xJzXaAAI8Qymq1+oRWKawrmsZACjD/qbYR3auyvo7l//WxyJP90M+1dAYWEhy5cvZ+3atQwdOhSAFStW8P3337Nq1Sqio6MNbefNm8egQYMAiImJITAwkC1btjBmzJhq/V67dg2VSoWbm5vRcl9fX65du2aS3OWqWCGEEEKIKpKSktBqtfTt29ewzMbGhl69epGQkGDUtk+fPoafPTw8CA0NrdbGkqSwE0IIIYSwAD8/P0pLS6tNkZKWloafn59JYkhhJ4QQQghRRceOHVGpVEZXqmq1WuLj4wkPDzdqe+DAAcPParWaxMREwsLCauy3R48e2NjYsHv3bsOyM2fOkJKSYjTy1xRyjp0QQgghRBWOjo5MnjyZ6OhoPDw8CAoK4t1336WoqIiJEycatV2wYAGenp74+voyd+5cvLy8GD16dI39urq6MnHiRKZPn46HhwcuLi783//9H3369DHJhRMghZ0QQgghBAA6nQ5r64rSaNGiReh0OsaPH09+fj49e/Zk586duLu7G71m0aJFTJ06lbNnzxIZGcm2bdtQqW48s8HSpUtRKpU8/PDDRhMUm4oUdkIIIYQwO3dHFbbWSotPUOzuWP/po9LT0wkJCQHAzs6OZcuWsWzZshrbDhgwAL1eD8CIESPqHcPOzo6PPvqIjz76qN6vaQgp7IQQQghhdm3c7Nnz0oAWeUsxtVpNXFwcsbGxTJo0yQKZmY8UdkIIIYSwiDZu9i3q9l6VoqKiiI+PZ8aMGYwaNaq502kSKeyEEEII8Ze2ZcuW5k7BZGS6EyGEEEKIVkIKOyGEEEKIVkIKOyGEEEKIVkIKOyGEEEKIVkIKOyGEEEKIVqJFXxU7f/58tm7dyrFjx27YZsCAAURGRvL+++9bLK+WLDj4WUI6ziTl0hrOnn0TgO63fYm7u/GtSlIvr+fMmVctnl+v0X+jU68+eAQEUlZaypXEBH76ci3qq5cNbVx9/eg/biJtOodjZW3DxeOH2bPmU4pycyyaa03bEsDF5TY6dpyBq8ut6PXl5BckcOzYBHQ6jUXzq6/r18POrg197/ypxrYnTrxAesb/zJqPfc+eeE6Mwq5LF2x8fLj0/AsUVLlvopWnJz4vzcCxb1+snJ0pOnSIa2++hTY52Ww5Od7hj2Nvf6zdbQHQphWRvzuFkkR1tbZeT3XBLtSDzM9PUXIqq0kxgtdcgO0Vzz+4MIr/2/aG0WsKDlwlZ+u5JueuCnLGZXA7VG2dQadHe7WQjFUnoSkTxaqc4J650HkEOHrDtd/gf7Phanzj+/yLq2tfKp1scB3WHrtO7ihsrSjLKCb/xxSKT9b/fShavwYVdhMmTCAmJoZnn32WTz75xOi5559/no8//pgnn3yStWvXmjLHWm3evBkbGxuzxsjKyuLxxx/nt99+IysrCx8fH0aNGsXChQtxcXExa+yGcHbuSpuAseTnJ1R77vLlDZy/sNTwuLy8xJKpGQSGRXBs53+5lnQWpZUV/R59gkfmvsGaGZMp02iwtrXlkZffICPlAl8teBmAvn8fx+iZr7H+lRnwxyzf5najbenichu3Ra7hYvJyEhNfR68vw8kpzDD7eEtT03qUlFxl3/47jNq1CXiUoKCnycrea/aclPb2aE6fIXfTZgL/9WG15wM/+hdoy0h97nl0hQV4TJhA8OrVJI0Ygb642Cw5ledpyNtxgbLMYlAocOjug+cT4aQtO0pZepGhnVO/gEa/BWuKMXzuY4R/9Y6hzWeffUbH3x0J8+4IgF5bd+FVV+6qIGe8oiLI//ESOd8kgU6Pjb9j03+XHvgQfMJgy7OQfw26jYEntmKT1BOovRgVNatrX3qMCUVpb01mzO/oispwiPTG47Ew0v91FO2VwuZO/y8nNjaWgQMHolarcXNza+50DBo8Yte2bVs2bNjA0qVLsbevmGSwpKSE9evXExQUZPIE6+Lh4WH2GEqlklGjRvHmm2/i7e3NuXPneP7558nOzmb9+vVmj18fVlYORHRZSsLpl2nf7vlqz5friiktzWyGzIxtfnue0eMdHy/luZXr8e0QwuWE32kTGo6Ljw/rZk+h9I8P8f99tJQXVm8gKKIbKSeOmz3H2rblLZ3mculSDMnJnxqWFRVdMHtOjXHj9dBVey94e99Pevp3lJcXYW6F+/ZRuG9fjc+p2rXDITKSpBEjKT1XURxcm/86nfbvw3X4cHK+/tosOZUkZBs9ztuVjFNvf1RBzobCzsbfEae7Akn/8Cj2rzT8Zt01xVDd7lVx4+/yimVFRUWU5irR2WtNlrvriA4UxF0hf2+qoU1ZZtMKZCuVHYQ/AP8eC8k/VyyMXQS3DMWr/9Pw7qwm9f9XVde+VAW7kLP1HNrUAgDy91zCqW8bbNo43TyFXc4lKLLgCKODJ7i1rXfzCRMmkJOTw9atW82W0meffcb69es5cuQI+fn5Ji8MG1zYde/enaSkJDZv3szjjz8OVIyaBQUF0b59e6O2O3bs4M033+TkyZNYWVnRp08fPvjgAzp27Ghok5qaSnR0NDt37kSj0RAWFsZHH33EHXf8OaKwbt06Xn31VdRqNUOHDmXFihU4OzsD1Q/FtmvXjmeeeYZz587x1Vdf4e7uziuvvMIzzzxj6O/SpUvMmDGDXbt2oVQqueuuu/jggw9o165djevs7u7O5MmTDY+Dg4N57rnnWLx4cUM3n9mE3vI6mZk/olb/XGNh5+f7AH6+oygtzSQzczcXLv4Lna55Ru2qsnVwBKCkoOIPlZW1DeihXPvnB1u5thS9Xk+b0C4WKexutC1tbDxxdb2Na2nf0qPHVzjYB1FYmETS+SXk5h42e14NVdd7opKzcwTOzl04c2a+5ZK7AYWqYvRdr6lyWFuvR19ain2P7mYr7IyTAPuu3ihUVpSm5FcsslHi8Whncr45h66g/kVXXTFs7FT88ssvPNKrDwCPP/44rhOdURSWU5yQTf6elHqN2t0od6WjDbZBLhQdy8B78q1Ye9hRllFM7s6LlCbnNT59pTUoraHsutMPyopx6tin0f2KKmp4H5Ym52HfzYvi09noS8oqnrdRojmf28zJ1lPOJfhXj+rvG3OytoUXDjeouDO3oqIihgwZwpAhQ5gzZ47J+2/UxRNRUVGsWbPG8Hj16tU89dRT1doVFhYyffp0Dh06xO7du1EqlTz44IPodBV/qAoKCujfvz+XL1/m22+/5fjx48ycOdPwPEBSUhJbt25l+/btbN++nb1797Jo0aJa81uyZAk9e/bk6NGjPPfcc0yePJkzZ84AoNVqGTx4MM7Ozuzbt4+4uDicnJwYMmQIpaX1u3/dlStX2Lx5M/37969Xe3Pz9RmBs3MXks7XXGheS9vG76dmcOTo41xMXo6f32i6hP/TwlnWQKFgwJNPc/n072Rdqjh/6urZ02g1Jdz1+FNYq2yxtrWl//iJKK2scHR3N3tKtW1Le/uKPwwd2k/hypUNHD32FPn5v9P9tnXY27cze24NUdd7oqoA/79RWHiW3LwjFsisdprzF9BevoLP9BdRuriAjQ2e//gHNv7+WHt7mzW2ta8DAa/fSZs3++H+YAhZ604ZRutcR3SgNCWPklPZdfTSsBj/fWs9CQkVh8kT9/7GuHHjOPjOf8mLvYRDdx88/h7apNytPewAcLk3iMJfr5G55iSlVwrwfror1p52jV6PspICuHQQ+keDsx8olBWHYgN7YePq2+h+Re3vw6z1CSislLSZ14c2b/bF/aGK58uzmv9Ler0UZVm2qIOKeI0cIdRoNEyZMgUfHx/s7Ozo168f8fHVzyGNi4ujW7du2NnZ0bt3b06ePFlrv9OmTWP27NkVo/Vm0KjCbty4cezfv5/k5GSSk5OJi4tj3Lhx1do9/PDDPPTQQ4SEhBAZGcnq1as5ceIEp06dAmD9+vVkZGSwdetW+vXrR0hICGPGjKFPnz+/8el0OtauXUtERAR33XUX48ePZ3eVE61rMmzYMJ577jlCQkKYNWsWXl5e/PjjjwBs3LgRnU7HypUr6dq1K2FhYaxZs4aUlBRiY2Nr7Xfs2LE4ODjQpk0bXFxcWLly5Q3bajQa8vLyjP6Zg62tP7fc8iq///4iOl3NhemVKxvIzt5HYWEiaWnfciohGh+fwdjbW/7QeVX3Rk3Gq20w2z9417CsOD+PbUsX0bF7L6bEfMX/rfkPtg6OpJ0/h15n3vPY6tqWij9+XS5f/jdXr26ioOAUZ8+9RWHRBQL8HzFrbg1Rn/dEJaXSFl/fB7hy5SsLZVeHsjJSp/wfqnbtCP31IJ2PHsHhjl4U7P0JdE040b8+oTOLSVt2hPSPj1Fw4CrufwvF2scBuzAPbDu6kbMtyeQxBr34MGFhYQD8vvMQu3btoiBVTfGxDNT/OYN9hBdWHnUXYDfKHUXF84W/XqXocBraK4Xkbj+PNqMYh55+TVuZzc8CCphxBl7NgDsmwcmvLXYebGt1w30JuN7fDqWdFRkrTpD+r2Pk77uM52NhWPs6NHPWrdPMmTPZtGkTMTExHDlyhJCQEAYPHkx2tvEXvOjoaJYsWUJ8fDze3t6MHDkSrdYEI/uN1KirYr29vRk+fDhr165Fr9czfPhwvLy8qrU7e/Ysr732GgcPHiQzM9MwEpeSkkJERATHjh3jtttuq/U8uXbt2hkOuwL4+/uTnp5ea37dunUz/KxQKPDz8zO85vjx45w7d86oT6g4TzApqfY/3EuXLmXevHkkJiYyZ84cpk+fzscff1xj27fffpvXX3+91v5Mwdk5ApXKi9tv/9awTKm0xs2tF4FtxvNjbBhg/IGYm3sMAHv7YIqLU8yeY03ueWoSHbvfzob5synINv42lfzbUVZNfRp7Zxd05eVoigqZ9Ok6ctOvmTWnurblgYODACgsND4xvKgwCTu7ALPm1hANeU/4+AzFysqOq9dazn0SS34/xYUHH0Lp5ITCxoZytZp2GzdQfPJ38wYu11OeVUI5oL1cgCrQCae+Aei1Oqw97AiYd6dRc89xYZRezCXjsxONjqF3L2Xq1KnwS/WmlYffrD3tKM+uY0TmBrnnx14CoCzN+NzJsvQirN1s6593TdQXYO1wsHEAW2coSINH1qDJbJnnnN40brQv96bidGcA1/552DCCp71aiG07F5z6BNR59bRomMLCQpYvX87atWsZOnQoACtWrOD7779n1apVREdHG9rOmzePQYMqPh9iYmIIDAxky5YtjBkzpllyb/R0J1FRUbzwwgsAfPTRRzW2GTlyJMHBwaxYsYKAgAB0Oh0RERGGQ56VF1/U5vorXhUKhdGh2oa+pqCggB49evDll19We513HYd6/Pz88PPzo3Pnznh4eHDXXXfx6quv4u/vX61tZeFXKS8vj7ZtTX+MX63+mQMHhxotCw97h8KiJJKTP+P6og7A2TkcgFJN7QWyudzz1CRCevXhP6/PIS8j7YbtivMrRjnbdumGg4srSYcOmjWvurZlcXEKJZprODh0MGrj4NCOrCzzX01aXw15TwT4/43MzN1otU07xGgOuj/Ou7QJDsYuIoKMZcssm4BSgcJaSd73yRTGG3+p8HuxB7nbz1Oc0MSTwBUKbG1tgbJqT9kEOAGgy6/fKSJG/si9XK2hPFeDtbfxiI61tz0lZ0y0z7VFFf/s3CDkHnK+tvw0Sq3aH/tSYfPHAbbrR0T1GEZmhekkJSWh1Wrp27evYZmNjQ29evUynD5RqepRRg8PD0JDQ6u1saRGF3aV56QpFAoGDx5c7fmsrCzOnDnDihUruOuuuwDYv3+/UZtu3bqxcuVKsrOzLXJ1K1Rc/LFx40Z8fHyaNFVJZaGo0dR8voCtre0ff7DNq7y8kMLCxOuWFaHV5lBYmIi9fRC+vg+QlRWLVqvGyakznTrNRa0+SEHhGbPnd717J06mc9/+fLP4TUqLi3BwdQOgtKiIMm3FB1iXAfeRffkSRXm5BHTqzMAJz3D4u2+M5rozh7q2JUBK8go6dJhGQUEC+QUJ+Ps9hINDR06cfMGsuTVEfdYDKkZs3dx6cez4RIvmp3BwQFXlCnpVYCC2nTtTnptL2dWrOA8eTLk6G+2Vq9jecgu+c18mf/duCuN+NltOLoPbUZKYTXmOBoXKCodIH2zbu5K5+iS6Am2NF0yU5WgoV9f/fKGaYjh3bcOXLz3LK5H/4Pb7BtD9ynfYezlhF+aB24gOaM7nor1W+5XKteUOkP9TKi6DgtFeLaT0agGO3X2x8bYn64sbf6mql473VhQUmefAowPcvwAyz5IVt65p/f6F1bYvyzKK0WYW4/5QJ3L+ex5dURn2XTyxDXGjIMbMo9niptLows7KyspQkVpZWVV73t3dHU9PTz777DP8/f1JSUlh9uzZRm3Gjh3LwoULGT16NG+//Tb+/v4cPXqUgIAAowrYlB5//HEWL17MqFGjWLBgAYGBgSQnJ7N582ZmzpxJYGBgtdd89913pKWlcfvtt+Pk5MTvv/9OdHQ0ffv2veGVtC2FTqfFw/1OgtpOQKl0QKO5Skb6Ti5crHmU1dwi7x8OwN/nG18As+Pjpfy+t+LcSQ//Ntw19knsnJzITU/n4Jb/cPi/Wy2dao0upa5FaWVLp06vYGPjSn7BaY4ee6LZDmk3RYD/I2g018jOrnnqEXOxj+hC8OefGx77zqn4u5CzZQtX57yMtY83vrNnYe3pSVlGJrnffEPG8uVmzcnKyQaPMaFYOavQlZShvVpI5uqTaM7lmDXGN/M+54cffuDlrlG0jezArl27cHNxRZerpfhkJnl7LjU594K4KyislbiO6IDSwbpicuKVJ+s+vFsXOxe4dx64BECxGhK+hd1vgK766KOon7r2Zdaak7gMbY/Xk10qJijOKkb9VSIlZ6pPpC2apmPHjqhUKuLi4ggODgYqLr6Mj49n2rRpRm0PHDhgmO5NrVaTmJhoOHe2OTTpzhO1jXgplUo2bNjAlClTiIiIIDQ0lGXLljFgwABDG5VKxa5du5gxYwbDhg2jrKyM8PDwGx7aNQUHBwd++uknZs2axUMPPUR+fj5t2rTh3nvvveH62Nvbs2LFCl588UU0Gg1t27bloYceqlaothRHjj5u+FmjucqRo481YzbGlvx9RJ1t9v07hn3/jrFANnWrui0rJSd/ajSP3c2gpvVIOr+EpPNLLJ5L0a/xJHS+8R899bovUK/7woIZgXrT2Qa1T53d8GK4phiXfq84r7cku5DNc1YzZfubfPfkCrr61e9q2Bv1e738valG89iZxO9bKv4Jk6lrX5ZllZD9RfMd4vsrcXR0ZPLkyURHR+Ph4UFQUBDvvvsuRUVFTJxofJRjwYIFeHp64uvry9y5c/Hy8mL06NE37PvatWtcu3aNc3/M1XnixAmcnZ0JCgoyydHLBhV2dd1R4voJ/e677z7DFbCVrp+hPzg4mK9vMDfV/PnzmT9/vtGyadOmGVXL11/JevHixWr9XH9LMj8/P2Ji6l84DBw4kJ9/Nt9hICGEEEI0P51Oh7V1RWm0aNEidDod48ePJz8/n549e7Jz507cr5t6a9GiRUydOpWzZ88SGRnJtm3bUKlUN4zxySefGF1ceffddwOwZs0aJkyY0OR1aNH3ihVCCCFEK+HgWTFhsKUnKHbwrHfz9PR0QkJCALCzs2PZsmUsu8GFWwMGDDAMVo0YUffRqEo1DVqZkhR2QgghhDA/t7YVd4FogbcUU6vVxMXFERsby6RJkyyQmPlIYSeEEEIIy3Br26Ju71UpKiqK+Ph4ZsyYwahRo5o7nSaRwk4IIYQQf2lbtrSeC4EadUsxIYQQQgjR8khhJ4QQQgjRSkhhJ4QQQgjRSkhhJ4QQQgjRSkhhJ4QQQgjRSkhhJ4QQQgjRSsh0J0IIIYSwiKsFV1Fr1BaL527rjr+Tv1n6jo2NZeDAgajVatzc3MwSozGksBNCCCGE2V0tuMqIrSMoLS+1WEyVlYrto7fXu7ibMGECOTk5bN261Sz5ZGdnM2/ePHbt2kVKSgre3t6MHj2aN954A1dXV5PEkMJOCCGEEGan1qgtWtQBlJaXotaozTZq11BXrlzhypUrvPfee4SHh5OcnMykSZO4cuUKX3/9tUliyDl2QgghhBDX0Wg0TJkyBR8fH+zs7OjXrx/x8fHV2sXFxdGtWzfs7Ozo3bs3J0+evGGfERERbNq0iZEjR9KxY0fuuece3nrrLbZt20ZZWZlJ8pbCTgghhBDiOjNnzmTTpk3ExMRw5MgRQkJCGDx4MNnZ2UbtoqOjWbJkCfHx8Xh7ezNy5Ei0Wm294+Tm5uLi4oK1tWkOosqhWAtLTS3F3r711tMpKRXD7NmFRaSqcy0SM7uwyCj2zeratYo/BDf7elTmn1qm5VRJiUVippZVbLtzWckWiWcql3KvAhV5V/25parM7YJaz5Gr5TW2ScjQWTKlm05z7d+W/L5qiQoLC1m+fDlr165l6NChAKxYsYLvv/+eVatWER0dbWg7b948Bg0aBEBMTAyBgYFs2bKFMWPG1BknMzOTN954g2eeecZkuUthZ2H//GdWc6dgdkol7DiZyI6TiRaN+fbbGRaLZy6taT2WZWayLDPTcjEVSqZsf9Ni8Uylat43wzooFUpe/VHDqz9qbtjGwd4OLy8vC2bV8nl5eeFg79Cs+9fB3kH2Sz0lJSWh1Wrp27evYZmNjQ29evUiISHBqG2fPn0MP3t4eBAaGlqtTU3y8vIYPnw44eHhzJ8/32S5S2FnYXv37sXJyam50zArjUaDra1tq49pDrIeN1dMU6ia982wDvXJ0cvLi6CgIAtldHMICgoi4XQCmRb8snM92S8tR35+PkOGDMHZ2ZktW7ZgY2Njsr6lsLOwyMhIXFxcmjsNIYQQFhYUFCSF1U2iY8eOqFQq4uLiCA4OBkCr1RIfH8+0adOM2h44cMCwX9VqNYmJiYSFhd2w77y8PAYPHoytrS3ffvstdnZ2Js1dCjshhBBCiCocHR2ZPHky0dHReHh4EBQUxLvvvktRURETJ040artgwQI8PT3x9fVl7ty5eHl5MXr06Br7zcvL4/7776eoqIgvvviCvLw88vLyAPD29sbKyqrJuUthJ4QQQggB6HQ6w9WpixYtQqfTMX78ePLz8+nZsyc7d+7E3d3d6DWLFi1i6tSpnD17lsjISLZt24ZKpaqx/yNHjnDw4EEAQkJCjJ67cOEC7dq1a/I6SGEnhBBCCLNzt3VHZaWy+J0n3G3d6274h/T0dEPBZWdnx7Jly1i2bFmNbQcMGIBerwdgxIgR9eq/6mvMRQo7IYQQQpidv5M/20dvb5H3ilWr1cTFxREbG8ukSZMskJn5SGEnhBBCCIvwd/JvMbf3qioqKor4+HhmzJjBqFGjmjudJpHCTgghhBB/aVu2bGnuFEym9d4CQQghhBDiL0YKOyGEEEKIVkIKOyGEEEKIVkIKOyGEEEKIVkIKOyGEEEKIVkIKOyGEEEKIVkKmOxFCCCGERWivXKFMbbkJiq3d3bEJCDBL37GxsQwcOBC1Wo2bm5tZYjSGFHZCCCGEMDvtlSskDRmKvtRytxRTqFR03PG/ehd3EyZMICcnh61bt5otp2effZYffviBK1eu4OTkxJ133sk777xD586dTdK/HIoVQgghhNmVqdUWLeoA9KWlFh0hrI8ePXqwZs0aEhIS2LlzJ3q9nvvvv5/y8nKT9C+FnRBCCCHEdTQaDVOmTMHHxwc7Ozv69etHfHx8tXZxcXF069YNOzs7evfuzcmTJ2vt95lnnuHuu++mXbt2dO/enTfffJNLly5x8eJFk+QthZ0QQgghxHVmzpzJpk2biImJ4ciRI4SEhDB48GCys7ON2kVHR7NkyRLi4+Px9vZm5MiRaLXaesUoLCxkzZo1tG/fnrZt25okbynshBBCCCGqKCwsZPny5SxevJihQ4cSHh7OihUrsLe3Z9WqVUZt582bx6BBg+jatSsxMTGkpaXVee/Zjz/+GCcnJ5ycnPjf//7H999/j0qlMknuUtgJIYQQQlSRlJSEVqulb9++hmU2Njb06tWLhIQEo7Z9+vQx/Ozh4UFoaGi1Ntd7/PHHOXr0KHv37uWWW25hzJgxlJSUmCR3uSpWCCGEEMKCXF1dcXV1pVOnTvTu3Rt3d3e2bNnC2LFjm9y3jNgJIYQQQlTRsWNHVCoVcXFxhmVarZb4+HjCw8ON2h44cMDws1qtJjExkbCwsHrH0uv16PV6NBpN0xNHRuyEEEIIIYw4OjoyefJkoqOj8fDwICgoiHfffZeioiImTpxo1HbBggV4enri6+vL3Llz8fLyYvTo0TX2e/78eTZu3Mj999+Pt7c3qampLFq0CHt7e4YNG2aS3KWwE0IIIYQAdDod1tYVpdGiRYvQ6XSMHz+e/Px8evbsyc6dO3F3dzd6zaJFi5g6dSpnz54lMjKSbdu23fBCCDs7O/bt28f777+PWq3G19eXu+++m59//hkfHx+TrIMUdkIIIYQwO2t3dxQqlcXvPGF9XSFWm/T0dEJCQoCKImzZsmUsW7asxrYDBgxAr9cDMGLEiHr1HxAQwHfffVfvfBpDCjshhBBCmJ1NQAAdd/yvRd4rVq1WExcXR2xsLJMmTbJAZuYjhZ0QQgghLMImIKDe9221pKioKOLj45kxYwajRo1q7nSaRAo7IYQQQvyl1TWh8M1ECjsLO3bsGE5OTk3qQ6PRYGtrW+eym1Fzr0dzx28oU+fb0P4a0v5m2LZeXl4EBQVZNGZKSgqZmZktIv7NrDm2nRAtkRR2Fta/f/8m96EEdNctUygUhpM4b2bNvh4KJeiv37otmAIw4eZSKpToGrL+SiXo6tm+IW2biZ2DA2cSEixWIKSkpBDWOZSi4ooZ5x3s7Ug4fcai8UPDwigpKrJIPHOy9L4ToqWSws7CXvf1pYudfaNfn1SqYdbVq7wx0JZhnSp233dny3j1Rw0PPvgg3t7epkrV4jIyMtiyZQuud43DvkNPi8cvPn+I3H1f4DliBjaeprkZszlV5hv4TCC2AU0fCcv/LZ/0zeksG/EKIZ7Bdbb/8fwBFu9bhcvLb2Ed1L7Wtppf91O4+uN6tW0uZSkXyFs4l8zMTIsVB5mZmRQVl/DFgxV/E8ZtKbZ4/JKioha9X+qjOfadEC2VFHYW1l5lS7idXdP7cVfQ3d8KgITMcgC8vb3x9/dvct/NzdrVF1u/EIvH1WZdAsDGs22zxG+oynxtA2yxb9f4LwuVNFcqZj0P8Qymq19one3PZSUDYB3UHptbap9lvSzlQr3b/hWFeTfvTYBkvwjResgtxYQQQgghWgkp7IQQQgghWgk5FCuEEEIIi8jPLqGkQGuxeHZONjh7NP30p5rExsYycOBA1Go1bm5uZonRGFLYCSGEEMLs8rNL+PK1A5SXWe7qeCtrJY8v6F3v4m7ChAnk5OSwdetW8yYG6PV6hg0bxo4dO9iyZQujR482Sb9yKFYIIYQQZldSoLVoUQdQXqaz6AhhQ7z//vsoFAqT9yuFnRBCCCHEdTQaDVOmTMHHxwc7Ozv69etHfHx8tXZxcXF069YNOzs7evfuzcmTJ+vs+9ixYyxZsoTVq1ebPG8p7IQQQgghrjNz5kw2bdpETEwMR44cISQkhMGDB5OdnW3ULjo6miVLlhAfH4+3tzcjR45Eq73xKGFRURGPPfYYH330EX5+fibPWwo7IYQQQogqCgsLWb58OYsXL2bo0KGEh4ezYsUK7O3tWbVqlVHbefPmMWjQILp27UpMTAxpaWm13nv2xRdf5M4772TUqFFmyV0unhBCCCGEqCIpKQmtVkvfvn0Ny2xsbOjVqxcJCQlGbfv06WP42cPDg9DQ0GptKn377bfs2bOHo0ePmidxZMROCCGEEMIi9uzZQ1JSEm5ublhbW2NtXTG+9vDDDzNgwACTxJDCTgghhBCiio4dO6JSqYiLizMs02q1xMfHEx4ebtT2wIEDhp/VajWJiYmEhdV8i77Zs2fz22+/cezYMcM/gKVLl7JmzRqT5C6HYoUQQgghqnB0dGTy5MlER0fj4eFBUFAQ7777LkVFRUycONGo7YIFC/D09MTX15e5c+fi5eV1wznp/Pz8arxgIigoiPbt25skdynshBBCCCEAnU5nODy6aNEidDod48ePJz8/n549e7Jz507c3d2NXrNo0SKmTp3K2bNniYyMZNu2bahUquZIH5DCTgghhBAWYOdkg5W10uJ3nrBzsql3+/T0dEJCQgCws7Nj2bJlLFu2rMa2AwYMQK/XAzBixIhG51jZh6m06MJu/vz5bN261XAMuiYDBgwgMjKS999/32J5NZV9z554TozCrksXbHx8uPT8CxTs3m143v/thbg9+KDRawr27ePS089U76zfizw+fz4Z779/w6tw6qtnz57cfvvthnvepaens3fvXs6dOweAu7s7999/P0FBQVhbW3Pu3Dm+++47CgsLmxS3qZ4b0JHBXfzo6ONEibacI8lqFv3vNOczmy+vcXcE8XjvYALd7QE4m1bAst1niU3MMFvMHr49mNBlAuGe4fg4+DB1z1T2XNoDgLXCmv+77f+4K/Au2ji1oUBbwIGrB3j/8PtkFGcwJnQMj9z7CG0Wt8HBxo7y9BLyd6dQkqgGwO3BEOxC3LByUaHT6ChNycP9wyMATI0M47U7IvnsUgavnbsMQLCdinkhAdzh6oRKqeAHL1smrfyAsgau00vt/HipvfFhi7OFJdz162kAbJUK5ncMYJSvO7YKBT9m5zM7MZVMbUMjNQ9/f3/Onz9PcBs/tLlXecXHNOfYWFpt+8nN2oro9n7093Cmja2KLG0ZOzJzeef8VfLLLXsXAtG8nD3seHxB7xZ5r1i1Wk1cXByxsbFMmjTJApmZT4MKuwkTJhATE8Ozzz7LJ598YvTc888/z8cff8yTTz7J2rVrTZljrTZv3oyNTf2r8cY4fvw4ixYtYv/+/WRmZtKuXTsmTZrE1KlTG9Wf0t4ezekz5G7aTOC/PqyxTcFPP3Hl5bmGx/rS0uqNArpDj6dQX/ytUXlcLy8vjx9++IGsrCwUCgW33norY8eO5ZNPPiEnJ4fx48eTlpZGTEwMAPfccw+PPfYYK1euNPk3joa4o70H6w4kc/xSDtZWCqIHd+bzib0Y9M+fKNaWN0tOV/NKeGfHaS5mFqJQKHi4eyCfPdGT4cv2cTa9wCwx7a3tSVQnsuXcFj4Y+IHRc3bWdoR5hvHp8U85oz6Di8qFWb1m8eE9H/Lofx8lrTCNt7e8zS/LfmHlQ29x2+DeeD4RTtqyo5SlF6G9XEDRsXTKczQo7a1xuS+YUQuepNeR9TwZFsLvBcWGWA5KJRsjO/J7QTEPH6v4UvCSk5Jt27Yx7GhSg9frdEExfzv+5+vKq7zXFoS04V5PF54+eZH8snIW3hLI6q7teODIuQbHaQ7e3t6MGjWKd269gENwd2bOXE5OTk5zp9UoN9pPfrY2+KpseP3cFRILSwi0U/FuaCB+Khv+8fvFZspWNBdnD7t637fVkqKiooiPj2fGjBlmm1/OUho8Yte2bVs2bNjA0qVLsbevGI0oKSlh/fr1BAUFmTzBunh4eJg9xuHDh/Hx8eGLL76gbdu2/PzzzzzzzDNYWVnxwgsvNLi/wn37KNy3r9Y2+tJSyjMzb/i8tZ0jPLwCtk2htPuMBudQk8TERKPHe/bs4fbbbycwMBAXFxfc3Nz49NNP0Wg0AGzZsoXZs2fTvn17zp8/b5IcGuPJNca3eHnpq+MceXUQXQNd+fVC9g1eZV67E9KNHr+36wzjegdxW5C72Qq7/Zf3s//y/hqfK9AW8Mz3xiO+Cw8uZMOIDfg5+rE3dS85J3NIPZdKUVoeebuScertjyrImbL0Igp/vWZ4XblaQ96ui/hO68GGDRt48adfealvL8Pzt7s60tZOxX3xZyj4Y0Rm8o7dJL/yInenF/BzA9erTA8ZpdVH4JytlIz19+C5U8nE5VRs02mnU9h/RxjdXRw4klfUwEiWl5OTw3fffccbgY6UZqVw1OtBBg4c2NxpNcqN9tPpwhKjAi65pJRF56/yr/BgrBRQ3nzfCYUwqG1C4ZtNg6c76d69O23btmXz5s2GZZs3byYoKIjbbrvNqO2OHTvo168fbm5ueHp6MmLECJKSjL+xp6amMnbsWDw8PHB0dKRnz54cPHjQqM26deto164drq6uPProo+Tn5xueGzBgANOmTTM8bteuHQsXLiQqKgpnZ2eCgoL47LPPjPq7dOkSY8aMwc3NDQ8PD0aNGsXFixdvuM5RUVF88MEH9O/fnw4dOjBu3Dieeuopo21gag69etEpbj8d/vcdfvPmYfXH4dFKt//jfUjcCedjzRJfoVAQERGBjY0NqampWFlZAVBW9ucf7rKyMvR6fbMU9LVxtqv4vpJTVMMoZzNQKmBkN3/sVVYcSVE3dzoGzipndHod+aX5xk8oFNh380ahsqI0Jb/a6xQ2Shx6+lFarOHbb79l7+U0o+dVSgV6PZTq/vzELikrQ6fTcYefd4Pz7OCg4tidXTjYO4yPwoJoY1sxQt/N2QGVUslP6j8L5XNFGlJLSunp4tjgOM3B2dmZTp06AWAfGEG/fv3Izc1t5qwa50b7qSbO1lYUlOmkqBPCDBo1j11UVJTRfCurV6/mqaeeqtausLCQ6dOnc+jQIXbv3o1SqeTBBx9Ep6v4Fl9QUED//v25fPky3377LcePH2fmzJmG56Fi9uetW7eyfft2tm/fzt69e1m0aFGt+S1ZsoSePXty9OhRnnvuOSZPnsyZM2eAinloBg8ejLOzM/v27SMuLg4nJyeGDBlCaU2HO28gNzfXbKOFhfv2c2XWbFKeeor095bgcHtP2n72KSgrdtff//53PDpEwu7XTR7bx8eHl19+mVdffZURI0awceNGMjIySE1NpbS0lEGDBmFjY4ONjQ33338/SqUSJycnk+fRWAoFvDYinPiL2SSmmWdkrL5CfZ35/fXBJL45lLce7Mqz6w5zzkyjdQ2lUqp4sceL/O/C/yjUVpyL2DmgM/n5+Qxe+RTuD4aQte4UZel/jno59vYn4PU7afNGX+y7elGYlc+sWbOq9X0kr5AinY5XOgZgr1TgoFTy5tB7sba2xtfBvkF5HskrZGpCCmOPJzErMZUge1u+6d4JRyslPiprNDodeWXGh9szSrX4qFr06cMGarWa06dPc9vHajrP/Zn3338ftbrlFP/1Vdt+up6HjRXT2/mx7sqNj0gIIRqvUX/9xo0bx5w5c0hOTgYgLi6ODRs2EBsba9Tu4YcfNnq8evVqvL29OXXqFBEREaxfv56MjAzi4+MNRVLl1SiVdDoda9euxdnZGYDx48eze/du3nrrrRvmN2zYMJ577jkAZs2axdKlS/nxxx8JDQ1l48aN6HQ6Vq5ciUKhAGDNmjW4ubkRGxvL/fffX+f6//zzz2zcuJH//ve/N2yj0WgMhyyh4vy1+sr77rs/+0k8i+bMGUJ++B6HXr2wP3OGDz74gLh3RjDcRVNLL42TlZXFJ598gq2tLeHh4YwePZq1a9eSkZHBV199xfDhw7njjjvQ6/WcOHGCK1euNOv5ddd7Y1QEoX7OPLL8l+ZOhfOZBQxbtg9nO2uGRfiz5G+38vfPDjR7cWetsOa9Ae8B8MaBNwzLk9KSiIyMJObxxXQd0BP3v4WS8dlvhuKu6Gg6mrNqrP0d8Xy0M7rcms9fzNKW8/TJi7wTGsg/Ar3Q6eHr4yc5fPgwejuXBuW6J/vPEcOEwhKO5BVxqE84D/i4UdIKTrz38PDgscce47WwCzi07cpLL71jdETiZlHbfvr31T9Ph3CyUvJFtw4kFpbw3sVrNXUlhGiiRhV23t7eDB8+nLVr16LX6xk+fDheXl7V2p09e5bXXnuNgwcPkpmZaRiJS0lJISIigmPHjnHbbbfVOvLVrl07Q1EHFVeRpaen37A9QLdu3Qw/KxQK/Pz8DK85fvw4586dM+oTKs4TvP4wcU1OnjzJqFGjmDdvXq1F4Ntvv83rr5tmRE2bmkpZdjaq4CDcVTb4+voydPEvUFGX4qu0Zkp4P/R6PW+++WaTCq3y8nKysyv+EF+9epU2bdpwxx13sH37dpKSkli2bBkODg7odDpKSkp46aWXOHnypClWs8lef6AL93T2Ycynv3Atr6S500Fbric5q6IoOnk5j26BbkT1bcfLW5pve1UWdQGOAUzcNdEwWgegLdeSmpRKXnIWeTsvogp0wqlvADlbKi5E0GvKKdOUY+3riMJaiUdbHwoLC9ErFFgrlfR2cySqjRdBe4+zV51P7wMJeNhYUaaHtB3bOPN/UXx78SqGN24j5JWVc75IQ3t7W/Zm52OrVOJibWU0auetsiG9hnO9WqJr166xceNGZj7jSMmV31l53o9XXnmludNqsqr7qZKjlZJ/39qRgjIdT528QFnL+T4oRKvS6OMVUVFRhgsHPvrooxrbjBw5kuDgYFasWEFAQAA6nY6IiAjDIc/Kiy9qc/0VrwqFwuhQbUNfU1BQQI8ePfjyyy+rvc7bu/bzf06dOsW9997LM888U+cf3zlz5jB9+nTD47y8PNq2bVvra27E2tcXKzc3ytIzSI/7mYiICBbdZ8uIWyrWM+v+j/jul1OcP3/e5KNnCoXCMFljpaKiimKlffv2ODo6Gg5zN6fXH+jC4C5+PPrZL6Sqi+t+QTNQKkFl3Xx38ass6oKcg5i4cyK5mjrO5VIqUNSQr+ZcDtc+OILn5K7Mf30+sbf25aMhAzhbVMJHKelU/e3M/uOq5Ls7BOPj48OO2EPgG9jodXCwUhJsryLtmpbf8oso1em4y92J/2ZUrEtHe1sC7VQcymveKXgaq7y8ea7iNrWq+wkqRuo23NqRUp2eJ0+cR6OTqk4Ic2l0YVd5TppCoWDw4MHVns/KyuLMmTOsWLGCu+66C4D9+42v2OvWrRsrV64kOzvbIle3QsXFHxs3bsTHxwcXl/ofFvr999+55557ePLJJ2s9DFzJ1tYWW1vbGp9TODigqnLBgSowENvOnSnPzaU8Nxfv558jb9f3lGdmYNM2CJ/olyhNSaFw/37KCgv5PfkiuaF24FYxs3VZSSFZWVlcuXIFf3//eq/T9e69917OnTtHbm4uKpWKrl270q5dO9atWwdAZGQkmZmZFBYW0rZtW4YMGcIvv/xCVlZWo2OawhujIhgVGcDTnx+iUFOOt1PFds8r0aKx4ESYVc0cHEpsYgZXcopxVFkzKjKA3u09eWL1r2aLaW9tT5Dzn++rNs5tCHUPJbc0l8yiTP454J+EeYbx/O7nUSqUeNp5ApBbmsvzkc+zI2MHVsFWOAW643JvO2zbu5K5+iRWHnY4dPOi5GwOugItVq4qnAe0paxEy4oVKyh/I4Kich1qbTmnCytGSh/18yCxqISs0jJ6ujryxh0PsnTpUs45BWDjW/91mtcxgF1ZuaSWaPFVWRPd3h+dHramq8kv1/Hvq9m8HtKGHG05+WXlvHVLIPG5hTfFFbFQcXuhYcOGofK8gH3bW5n+yHRycnJqvOVQS1bbfnKyUrLx1o7YWyl5/tQFnKytqDwrN6u0jJv/gLoQLUujCzsrKyvDhLiVV0xW5e7ujqenJ5999hn+/v6kpKQwe/ZsozZjx45l4cKFjB49mrfffht/f3+OHj1KQEAAffr0aWxqtXr88cdZvHgxo0aNYsGCBQQGBpKcnMzmzZuZOXMmgYHVRxNOnjzJPffcw+DBg5k+fTrXrl0zrHddo3w1sY/oQvDnnxse+86p2C45W7Zwbf7r2IaG0nb0aKycndFmZFAYF0fGB8vQa807qaOjoyMPPvggTk5OaDQa0tLSWLdunWEqEy8vL+677z7s7e3Jyclh3759/PJL85/LNr5PMAAbnzV+z7z01XG+PpzaHCnh6WTLP8fcirezLfklZZy+ms8Tq39l/znznTDexbMLa4b8eVHTzNtnAvDNuW/4+NjHDAyqmEZj0wObjF731I6n8LDzYOmEpfj8nw9odOjTSshcfRLNuRyUzipU7Vxx6tsGpb015QVaSi/ksmnmCjIyMqjpK1lHB1te7uCPm40Vl0pKeS92P2+/9BIen6xv0Dr529qwPLwd7jZWZJWW8WtuIcMOJ5L1x0jga+cuo9PrWRnRDlvlnxMU3yxycnL4+OOPaevvgzb3Kos//ZThw4ffdIVdbfvpTjcnerhWXKV8sI/xzdNv/+UUl0paxtXrwjLyMtMpbsA5501l7+KCi5ePWfqOjY1l4MCBqNVqw8T+LUGTLh2rbcRLqVSyYcMGpkyZQkREBKGhoSxbtowBAwYY2qhUKnbt2sWMGTMYNmwYZWVlhIeH3/DQrik4ODjw008/MWvWLB566CHy8/Np06YN99577w3X5+uvvyYjI4MvvviCL774wrA8ODi41mlSbqTo13gSOofd8PlL/3i6Qf39MG8wL24u4ZlnargzRQN8++23tcf54Qd++OGHJsUwh3azb3wRS3OZtck0k0Y3xKG0Q3SN6XrD52t77lDaIXJ+ziH1s1S+e3IFXf1CDc/p8kvJWvt7tdfkXP6zSH3omPGEwG+dv8pb568aHhfHNW6kctKp5Fqf1+j0zDl7mTlnLzeq/+aWmppKjx49OPxMReHz6meFDBs2rJmzarja9tPPOQX4/XjMcsmIFisvM53V056l3MyDFFVZ2dgQ9f6n9S7uJkyYQE5ODlu3bjVbTgMGDGDv3r1Gy2q68UNjNaiwq+uOEtdviPvuu49Tp04ZLbv+HLDg4GC+/vrrGvubP38+8+fPN1o2bdo0o3nrrr8St6ZC6/pbkvn5+RnunlAfNeUhhBBCiPorzsuzaFEHUK7VUpyXZ7ZRu8Z6+umnWbBggeGxg4ODyfpuvjO5hRBCCCFaKI1Gw5QpU/Dx8cHOzo5+/foRHx9frV1cXBzdunXDzs6O3r1712umCAcHB/z8/Az/GnLOf12ksBNCCCGEuM7MmTPZtGkTMTExHDlyhJCQEAYPHmyYEqxSdHQ0S5YsIT4+Hm9vb0aOHIm2jpHJL7/8Ei8vLyIiIpgzZ45htglTkMJOCCGEEKKKwsJCli9fzuLFixk6dCjh4eGsWLECe3t7Vq1aZdR23rx5DBo0iK5duxITE0NaWlqt95597LHH+OKLL/jxxx+ZM2cO69atY9y4cSbL/ea4744QQgghhIUkJSWh1Wrp27evYZmNjQ29evUyzAhSqeosHh4eHoSGhlZrU1XVCx27du2Kv78/9957L0lJSXTs2LHJucuInRBCCCFEM7njjjsAOHfuXB0t60cKOyGEEEKIKjp27IhKpSIuLs6wTKvVEh8fT3i48XyMBw4cMPysVqtJTEwkLOzGU5pdr3LmjqbcYKAqORQrhBBCCFGFo6MjkydPJjo6Gg8PD4KCgnj33XcpKipi4sSJRm0XLFiAp6cnvr6+zJ07Fy8vL0aPHl1jv0lJSaxfv55hw4bh6enJb7/9xosvvsjdd99tdJ/7ppDCTgghhBAC0Ol0hvujL1q0CJ1Ox/jx48nPz6dnz57s3LkTd3d3o9csWrSIqVOncvbsWSIjI9m2bRsqlarG/lUqFT/88APvv/++4facDz/8cJ33n28IKeyEEEIIYXb2Li5Y2dhY/M4T9g2YIy49PZ2QkBAA7OzsWLZsGcuWLaux7YABAww3XRgxYkS9+m/btm21u06YmhR2QgghhDA7Fy8fot7/tEXeK1atVhMXF0dsbCyTJk2yQGbmI4WdEEIIISzCxcunxd3eCyAqKor4+HhmzJjBqFGjmjudJpHCTgghhBB/abVNKHyzkelOhBBCCCFaCSnshBBCCCFaCSnshBBCCCFaCTnHzsIulGpwUDa+nk4q1VT0o9Zz5Gq54WeAjIyMpifYjCrzL8tNQ3PNNLdWaYiy3DQAtFmXLB67MSrz1VzRmKS/0sxSAM5lJder/aXcqxV5pFyos235tcv1bttcmjO3hAxds8WGlr1f6uNmz18IU1LoKydhEWaVl5eHq6urSfpSAtd/DCgUClrDrmz29VAoQd+8H7INogBMuLmUCiW6hqy/Ugm6erZvSNtmYufgwJmEBIKCgiwSLyUlhbDOoRQVlwDgYG9HwukzFo0fGhZGSVGRReKZk6X33V9d5Wdabm4uLtfNE1dSUsKFCxdo3749dnZ2zZRh69KQbSojdha2d+9enJycmtSHRqPB1ta2zmU3o+Zej+aO31Cmzreh/TWk/c2wbb28vCxaGAQFBZFw+gyZmZnNFv9MQoIh/s3M0ttOiJZKCjsLi4yMrPbtRgjx1xUUFNSsBUlzxxd/LWU5JegKyywWT+lojbWbeUYNY2NjGThwIGq1Gjc3N7PEaAwp7IQQQghhdmU5JVx77xCUWfB0G2sFfi/1rHdxN2HCBHJycti6datZ0/rll1+YO3cuBw8exMrKisjISHbu3Im9vX2T+5arYoUQQghhdrrCMssWdQBleouOENbHL7/8wpAhQ7j//vv59ddfiY+P54UXXkDZhAsrq5LCTgghhBDiOhqNhilTpuDj44OdnR39+vUjPj6+Wru4uDi6deuGnZ0dvXv35uTJk7X2++KLLzJlyhRmz55Nly5dCA0NZcyYMSY7B1kKOyGEEEKI68ycOZNNmzYRExPDkSNHCAkJYfDgwWRnZxu1i46OZsmSJcTHx+Pt7c3IkSPRarU19pmens7Bgwfx8fHhzjvvxNfXl/79+7N//36T5S2FnRBCCCFEFYWFhSxfvpzFixczdOhQwsPDWbFiBfb29qxatcqo7bx58xg0aBBdu3YlJiaGtLS0G9579vz58wDMnz+fp59+mh07dtC9e3fuvfdezp49a5LcpbATQgghhKgiKSkJrVZL3759DctsbGzo1asXCQkJRm379Olj+NnDw4PQ0NBqbSrp/pjL89lnn+Wpp57itttuY+nSpYSGhrJ69WqT5C6FnRBCCCGEBfj7+wMQHh5utDwsLIyUlBSTxJDCTgghhBCiio4dO6JSqYiLizMs02q1xMfHVyvKDhw4YPhZrVaTmJhIWFhYjf22a9eOgIAAzpw5Y7Q8MTGR4OBgk+Qu89gJIYQQQlTh6OjI5MmTiY6OxsPDg6CgIN59912KioqYOHGiUdsFCxbg6emJr68vc+fOxcvLi9GjR9fYr0KhIDo6mnnz5nHrrbcSGRlJTEwMp0+f5uuvvzZJ7lLYCSGEEEJQcQ6ctXVFabRo0SJ0Oh3jx48nPz+fnj17snPnTtzd3Y1es2jRIqZOncrZs2eJjIxk27ZtqFSqG8aYNm0aJSUlvPjii2RnZ3Prrbfy/fff07FjR5Osg0LfGu4cfxOo7YbJQgghxM2kts+0G92w/ma488SQIUMICQnhX//6l5kTa5gbbdOayIidEEIIIczO2s0Ov5d6tsh7xarVauLi4oiNjWXSpEkWyMx8pLATQgghhEVYu9mBW3NnUV1UVBTx8fHMmDGDUaNGNXc6TSKFnRBCCCH+0m40ofDNSKY7EUIIIYRoJaSwE0IIIYRoJaSwE0IIIYRoJaSwE0IIIYRoJaSwE0IIIYRoJaSwE0IIIYRoJWS6EyGEEEJYRE5ODkVFRRaL5+DggJubm1n6jo2NZeDAgajVarPFaAwp7IQQQghhdjk5OfzrX/+irMxyd56wtrbmhRdeqHfhNWHCBHJycti6datZ8rl48SLt27ev8bn//Oc//O1vf2tyDDkUK4QQQgizKyoqsmhRB1BWVmbREcK6tG3blqtXrxr9e/3113FycmLo0KEmiSGFnRBCCCHEdTQaDVOmTMHHxwc7Ozv69etHfHx8tXZxcXF069YNOzs7evfuzcmTJ2/Yp5WVFX5+fkb/tmzZwpgxY3BycjJJ3lLYCSGEEEJcZ+bMmWzatImYmBiOHDlCSEgIgwcPJjs726hddHQ0S5YsIT4+Hm9vb0aOHIlWq61XjMOHD3Ps2DEmTpxosrylsBNCCCGEqKKwsJDly5ezePFihg4dSnh4OCtWrMDe3p5Vq1YZtZ03bx6DBg2ia9euxMTEkJaWVu97z65atYqwsDDuvPNOk+UuhZ0QQgghRBVJSUlotVr69u1rWGZjY0OvXr1ISEgwatunTx/Dzx4eHoSGhlZrU5Pi4mLWr19v0tE6kKtiLe7YsWPVjqNrNBpsbW2bKaMbM0VeLXXdbsSc+bakbdHcuTQlfnPnbgqmWoeWui2aI6+Wui2q8vLyIigoqLnTEC3E119/TVFREU888YRJ+5XCzsL69+9fbZlCoUSv1zVDNrVTAk3NyhR9WJI5821J20KhUKDX62/O+Aqg+VI3CVO9F5p7P95Ic+TVUrdFVQ72DiScTpDi7ibQsWNHVCoVcXFxBAcHA6DVaomPj2fatGlGbQ8cOGDYp2q1msTERMLCwuqMsWrVKh544AG8vb1NmrsUdhY29u7pBHl1Mjy+lpNCzJ638XnIB+duzs2YmbH83/JJ35zOO/7+dFQ17lvwT4UFLMvMbFIflpRUqmHW1atm2Rem2J6mUrlfHrsjEh8X01yF1RDpeQWsP3isUdu5cjsGPhOIbUDLf0/VxFTvhcr9+OCDD5r8g6Epzp49y48//mjRvDIyMtiyZQvRd01kYIfeFonZUOeykpmy/U0yMzOlsLsJODo6MnnyZKKjo/Hw8CAoKIh3332XoqKiaodOFyxYgKenJ76+vsydOxcvLy9Gjx5da//nzp3jp59+4rvvvjN57lLYWZivayBtvW+ptlzlpcK+nX0zZFQzzRUNAB1VtoTb2TWqj/OapvfRHMyxL0yxPU2lcr/4uDgR6O7abHk0ZjtXbkfbANsW9fvSEKZ6L1TuR29vb/z9/U2SmylkZmYCzZNXW1d/uvqFWjSmaF10Oh3W1hWl0aJFi9DpdIwfP578/Hx69uzJzp07cXd3N3rNokWLmDp1KmfPniUyMpJt27ahUqlqjbN69WoCAwO5//77Tb4OUtgJIYQQwuwcHBywtra2+J0nHBwc6t0+PT2dkJAQAOzs7Fi2bBnLli2rse2AAQMMh/9HjBjRoLwWLlzIwoULG/Sa+pLCTgghhBBm5+bmxgsvvNAi7xWrVquJi4sjNjaWSZMmmT8xM5LCTgghhBAW4ebmVu/7tlpSVFQU8fHxzJgxg1GjRjV3Ok0ihZ0QQggh/tLqO6HwzUAmKBZCCCGEaCWksBNCCCGEaCWksBNCCCGEaCWksBNCCCGEaCWksBNCCCGEaCWksBNCCCGEaCVkuhMhhBBCWERJyRVKtdkWi6ey8cDOLsAsfcfGxjJw4EDUanWLmptPCjshhBBCmF1JyRV+OXAfOp3GYjGVSlv69P6h3sXdhAkTyMnJYevWrWbL6dq1a0RHR/P999+Tn59PaGgoc+fO5eGHHzZJ/3IoVgghhBBmV6rNtmhRB6DTaSw6QlgfTzzxBGfOnOHbb7/lxIkTPPTQQ4wZM4ajR4+apH8ZsbMQe3t7brnlFqNl4f0CGBrZmZfXPIaLiwt3rr+TfG1+nX318O3BhC4TCPcMx8fBh6l7prLn0h6jNs9HPs/DnR7GWeXMsfRjvHHgDVLyUxqct1evXgROnoRdly7Y+Phw6fkXKNi926iNqkMHfF6agcPtt6OwskKTlETqlKmQm9vgeFXZ9+yJ58SoG8YOO51Q4+vS3l1M9urVTYpdqa5tfW/QvYwJHUO4Rzhudm488u0jnFGfaVLMutZb4eCAz4zpON97L1ZubmhTU8le9wU5Gzc2Ke71bh00lFsHDcPF2xeArNQUftn0by4eOwyAlY0NA8ZPJPTOu7GyseHi8SPsXrWcotycOvu+6667ePX5V7k15NYat+vkWycztP1QfB18KdOVcSrrFMuOLmMf+0yybvX5Har0au9XGRM6hnd+fYcvEr4wSXyA0Ocm027oUFQdOqAvKaH46FHSlyyh9MJFQxuFSoXPrFm4DB+G0saGgrg4rr2+gPKsrCbH79evH/fddx8HDhxgx44dQMWNzDt06ICzszOlpaVcunSJH374gczMzCbHq28OVT3++ON06tSJDRs2cPr0aZPGdrzDH8fe/li72wKgTSsif3cKJYlqrNxt8Z/Vq8bXZX2ZQPEJ82wP0bJoNBqio6PZsGEDeXl59OzZk6VLl3L77bcbtYuLi2POnDkkJiYSGRnJypUriYiIuGG/P//8M8uXL6dXr4r32CuvvMLSpUs5fPgwt912W5PzbtEjdvPnzycyMrLWNgMGDGDatGkWyaepdu3ahcr2z1raWqXkzLEUFi5c2KB+7K3tSVQn8tbBt2p8PioiisfCHuONA2/w+HePU1xWzKeDPkWlVDU4ZysHezSnz5C24I0an7dp25bg9V9Sev4CyU88yflRo8n8eDl6TdO/lSnta4+d2O8uo39XXn4ZvU5H/q5dTY5dqa5tbW9tz9G0oyw9stRkMetab9/Zs3Dq148rM2dyfvhwsj//HL9XX8Fp4ECT5QCQn5XFvvUxfDFnGl++PI2Uk8cZHf0KnoFBAAx44mk69OjFtqWL2Dh/Nk7unjww4+V69e3o6EhCasINt2tyXjILDy7k4W8f5okdT3C54DKfDvoUDycPk6xbXfu10j1B99DNuxtpRWkmiVuV1x13oF6/not/f5SUqIkorG0IWrkKhb29oY3vnDk4DxzA5anTSH7iCax9fAj8cFmTYwcEBNCjRw+uXbtmtPzq1at88803fPTRR3zxxRcoFArGjx+PQqFocsz65lCpd+/eJo9ZVXmehrwdF0j/8Cjp/zqGJikHzyfCsfZxoDxHw5U3Dxj9y/0+GZ2mjJIzLWv0R5jPzJkz2bRpEzExMRw5coSQkBAGDx5MdrbxeyA6OpolS5YQHx+Pt7c3I0eORKvV3rDfO++8k40bN5KdnY1Op2PDhg2UlJQwYMAAk+TdoMJuwoQJKBQKJk2aVO25559/HoVCwYQJE0ySWH1t3ryZN96o+QPQlKZMmUKPHj2wtbWts9isSUlJCcHBwQSG+BqW/bYnlb1bjnHgwIEG9bX/8n4+PPohe1JqHmEYFzaOz377jB8v/UiiOpGX97+Mt4M39wTd0+C802L3kvHBB+T/8EONz3tPm0bh3p9If+89NAkJaC9douDHHynPbvofv8J9+2qNXZ6ZafTP+Z57KDp4EG1qapNjV6prW28/v51PfvuEA1catg9rU9d620feRu7Wbyj6NR7t5Svk/OcrSs6cwb5bN5PlAHD+yK9cOHaInGtXUF+9QtzGdZSWlODfKRSVvQNd7xlE7OeruPT7b6RfSGLn8vdpExqOf6fQOvvesWMHi79ZfMPt+t2F7zhw9QCpBakk5SSx+NBinFXOhAWGmWTd6tqvAD4OPrzc62Vm75tNma7MJHGrintyArlbtlJ67hyaM2e4MmcONm0CsOvSBQClkxNuDz9E2jvvUHTwICW/n+LqnJdx6N4du1tvbXRclUrFww8/zLZt2ygpKTF67vDhwyQnJ5OTk8PVq1fZs2cPrq6uJj8xvLYcAPz8/Ljzzjv55ptvTBq3qpKEbErOqCnLKqEss5i8XcnoS8tRBTmDHnQFWqN/9l08Kf4tE32pzmw5iZajsLCQ5cuXs3jxYoYOHUp4eDgrVqzA3t6eVatWGbWdN28egwYNomvXrsTExJCWllbrvWf/85//oNVq8fT0xNbWlmeffZYtW7YQEhJiktwbPGLXtm1bNmzYQHFxsWFZSUkJ69evJygoyCRJNYSHhwfOzs4WiRUVFcXf//73JvVRlF/9j5gpBToF4u3gbVRoFGgLOJFxglu9G/9hUCOFAqcB/Sm9eJG2K1fQKW4/7TZuwOnee00bpx6sPD1x6t+fnE2bLB7b0oqPHcXpnoFY+/gA4HBHL1Tt2lEQF2e2mAqFktA778bG1o4riafx7RCClbUNKSeOGdpkX0klLyMd/06dTRrbWmnNI7c8Ql5pHqcunTJp3zeiQMHCfgtZ8/saknKSLBJT+cffMd0fpzDYdemCQqWi8OdfDG1KL1xAe/kKDo34cllp2LBhJCYmcv78+Vrb2djYEBkZiVqtJi8vr9HxGpqDjY0NDz/8MP/9738pKCgwadwbUoB9N28UKitKU6qfDmPTxglVgBOF8TWPLorWJykpCa1WS9++fQ3LbGxs6NWrFwkJxqcB9enTx/Czh4cHoaGh1dpU9eqrr5KTk8MPP/zAoUOHmD59OmPGjOHEiRMmyb3BhV337t1p27YtmzdvNizbvHkzQUFB1Y4N79ixg379+uHm5oanpycjRowgKcn4j2Rqaipjx47Fw8MDR0dHevbsycGDB43arFu3jnbt2uHq6sqjjz5Kfv6fv3jXH4pt164dCxcuJCoqCmdnZ4KCgvjss8+M+rt06RJjxozBzc0NDw8PRo0axcWLF2td72XLlvH888/ToUOH+mymauzs7Ni/fz/XUpp+bkxtPO09AcgqMY6TVZKFl72XSWNZeXpi5eiI59P/oHDfflIm/oP8H34g8MNlOFx3DoK5uY4eja6wkPxd31s0bnNIe+NNNElJdPppL51P/EbbFStIW/AGxYcOmTyWV9tg/i/mK6Z9uYX7/vEc3773FtmXL+Ho5k6ZVoumqNCofWFuDo5u7iaJfXfg3Rx87CCHxx1mfPh4ntn1DOpCtUn6rktURBTl+nK+TPjSIvFQKPB9eQ5Fhw+jOXsWAGtvL3SlpejyjQuNsqxMrLwa97scERGBv78/u687T7aq22+/nZdffpm5c+fSqVMnPv/8c8rLyxsVrzE5DB48mEuXLnHmTNPOVa0Pa18HAl6/kzZv9sP9wRCy1p2iLL2oWjvHnr5o04pqLPqEaIikpCT+9a9/sXr1au69915uvfVW5s2bR8+ePfnoo49MEqNR59hFRUWxZs0aw+PVq1fz1FNPVWtXWFjI9OnTOXToELt370apVPLggw+i01UMZRcUFNC/f38uX77Mt99+y/Hjx5k5c6bheajYCFu3bmX79u1s376dvXv3smjRolrzW7JkCT179uTo0aM899xzTJ482fBHQqvVMnjwYJydndm3bx9xcXE4OTkxZMgQSktLG7M5aqTRaMjLyyMvL4/S0lIUCgWPPvqoyfpvCRTKivNu8vfsITsmBs3p02StWElBbCxujzZtZLOh3B5+iNzt29GbcB+2VO7jx2F/661cmjyZCw8/Qvo77+D72qs4VPnWaCrZVy6zbuYUvpw7nePf/48hz7+IR5u2Jo9Tk/hr8Tyy7RHGfzeeuMtxvNf/PTydPc0eN9wjnHHh43hl/ytmj1XJ77XXsO3UicvTZ5gthouLC0OGDGHz5s2Uld340PJvv/3GJ598wpo1a8jKyuJvf/sb1tamuc6urhxCQ0Np3759jRdSmENZZjFpy46Q/vExCg5cxf1voVj7OBg3slbiEOlD4SEZrfsr6dixIyqVirgqR0K0Wi3x8fGEh4cbta16OpVarSYxMZGwsJpPGykqqvjioFQal19WVlZGtU9TNOq3ddy4ccyZM4fk5GSg4oqQDRs2EBsba9Tu+jlZVq9ejbe3N6dOnSIiIoL169eTkZFBfHw8Hh4VJ0Vff4xZp9Oxdu1aw+HW8ePHs3v3bt5668YnPQ8bNoznnnsOgFmzZrF06VJ+/PFHQkND2bhxIzqdjpUrVxpOCF6zZg1ubm7ExsZy//33N2aTVPP222/z+uuv8+GHHzJq1CjuvvtuLl++DN1N0v0NZRVXjNR52nmSWfznlVuedp6czjbtVWVl6hz0Wi2ac8ajsJqk8zj0MPOKVmHfowe2HTpw+cXpFovZXBS2tvhMm0bq/02hYO9eADSJidh1DsMz6imKfvmljh4aRldeRk7aVQDSLyTh17ET3Yc9wJmf92FtY4Otg6PRqJ2jqxuFOaYZVSsuK+ZS/iUu5V/it8zf2P7gdh7t+yjHlxw3Sf830t23Ox52Hux65M+LcKyV1rzU8yXGhY9jyKYhJo3n++orOA3oT/K48ZSl/XmRRllGJkqVCqWzs9GonbWnF+WNuEo1ICAAJycnnn32WcMypVJJcHAwvXr14o033kCv16PRaNBoNGRnZ5OamsqsWbPo3LkzJ0+ebNqK1iOHys+C2bNnG71uzJgxpKSksHbt2ibnYKRcT3lWCeWA9nIBqkAnnPoGkLPlnKGJQ1cvFDZKio6kmza2aNEcHR2ZPHky0dHReHh4EBQUxLvvvktRURETJ040artgwQI8PT3x9fVl7ty5eHl5MXr06Br77dy5MyEhITz77LO89957eHp6snXrVr7//nu2b99uktwbVdh5e3szfPhw1q5di16vZ/jw4XjVcGjg7NmzvPbaaxw8eJDMzExDNZqSkkJERATHjh3jtttuMxR1NWnXrp3ROXT+/v6kp9f+C9atyknkCoUCPz8/w2uOHz/OuXPnqp2XV1JSUu0wcVPMmTOHl19+GWtra4qKiti3bx9t25p/pCO1IJWMogzu8L/DMO2Go40jXb27svGMaafDQKul+ORJbNu3N1ps264d2itXTBurFm6PPEzxyZNoLHDoprkprK1RqFTor/tmp9eVg9L8F7krFAqsrG1IO3+O8jItQRG3cvbXnwFw92+Di7cPV8+a9gtEJaVCicq64Vd2N9S289s4cNX4YphPBn3C9qTtbD231aSxfF99Bef77iP5iSfRXr5s9FzJ77+jLy3FsU9vwykGqvbtsGkTQNGxYw2Odf78eT7++GOjZaNGjSIzM5O4uDj0en2Nr1MoFCYbsasrh6KiIg4fPmz0/HPPPcfOnTstcmgWpQKFtfHvkePtvhQnZKMrvPFVjqL10Ol0hvf7okWL0Ol0jB8/nvz8fHr27MnOnTtxdzc+3WTRokVMnTqVs2fPEhkZybZt21Cpav5bZWNjw3fffcfs2bMZOXIkBQUFhISEEBMTw7Bhw0yyDo3+bY2KiuKFF14AuOFx4ZEjRxIcHMyKFSsICAhAp9MRERFhOORpX+Wy/huxsbExeqxQKOocrqztNQUFBfTo0YMvv6x+7oy3t3ed+dSXra2t4WcnJyf0ej2+vr7YqKwMyx1cVPg7ehLiXjFK2cm9E4XaQq4WXiWv9MYnK9tb2xPk/OeFKm2c2xDqHkpuaS7XCq/xRcIXPNvtWVLyU7icf5kXbnuBjKKMWq8AvBErBwdsq8y/pwoMxLZzZ8pzcym7epXsVatp888lFB06ROHBgzjd1Q+ngQNIfuLJBse6nsLBAVWVC3Kujw2gdHTEZfBg0t55t8nxalLXtnZRueDv6I+PQ8WFDO1c2wGQWZxZ7TzH+qprvQt//RWf6GjSNCUVJ9L3uh3XUaNIW/RO41e0Bv3GPsmFY4fIz8xAZWdP534DaBvelU0LX6O0uIgTe75nwBP/oKQwH01REfc+NYkrZxK4erbuD2BHR0fCA8Nxdq/4glV1u+Zqcnm669PEXoolozgDd1t3Hu38KD4OPvz38H9Nsm517ddcjfEcjGW6MjKLM7mYd9Ek8QEi31iA68iRpD7/ArrCQsN5c7r8fPQaDbqCAnI2bcZ31mzKc3PRFRTg+8orFB09Ssnxho9alpaWVvtSrNVqKS4uJj09HXd3d7p06UJSUhJFRUW4uLjQr18/tFotZ/8476+p6soBqPGCidzcXHJyckySQyWXwe0oScymPEeDQmWFQ6QPtu1dyVz958iklacdqnauZK793aSx/6pUNh4olbYWv/OEyqb+0ySlp6cbjhza2dmxbNkyli2reYqhAQMGGL4QjRgxot4xOnXqxCYzXujX6MKu8pw0hULB4MGDqz2flZXFmTNnWLFiBXfddRcA+/fvN2rTrVs3Vq5cSXZ2dq2jdqbUvXt3Nm7ciI+PDy4uLhaJCeDs7My1a9dY//5O1H8MaHS5uw29RvQD/gZAzNAYAF7Z/wrfJN34Mv8unl1YM+TPcxxn3j4TgG/OfcMrca+w+uRq7K3tmddnHs4qZ46mHWXSD5Mo1TX8/DP3bl3psGGD4bHvnIpDJDlbtnB1zsvk//ADV+e/jtczz+A792VKL1wgdcpUio8caXCs69lHdCH4889vGBvAZfgwUCjI+69pPvCvV9e2Hth2IG/2e9Pw/Hv93wPg42Mfs/z48kbFrGu9L0+fgc/0FwlYvBgrV1e0V66Q8f775FTZT6bg4OLK0Oem4+juQWlRIRkpF9m08DWS/7gSNvbzFaDXMXL6y1hb23DxtyP8sPLj2jv9Q8+ePdn56k7D46rbdcEvC2jv2p4HQh7A3dadHE0Ov2f+zpP/e5LEq4kmWbe69qsldBw/HoDgdZ8bLb8yZw65W7YCkPb22+h1OgI/+ACFSkXB/jiuLVhglnzKysoIDg6md+/e2NvbU1BQQHJyMqtWraKwsLDuDm4yVk42eIwJxcpZha6kDO3VQjJXn0RzLsfQxrGnL+V5GjRnLXPRTmtnZxdAn94/tMh7xarVauLi4oiNja1xSrebSaMLOysrK8PlvFZWVtWed3d3x9PTk88++wx/f39SUlKqnTcxduxYFi5cyOjRo3n77bfx9/fn6NGjBAQEGF0+bEqPP/44ixcvZtSoUSxYsIDAwECSk5PZvHkzM2fOJDAwsMbXnTt3joKCAq5du0ZxcTHH/jgUEh4efsMh16ry8vJwdXVl2sh/EhJQMe1I/PYLbF6zk3c2TybwmUDc7nSr1zocSjtE15iutbb56NhHfHSs6VfYZB44SELn2ucOy928mdwqV0mbStGv8XXGzvnPV+T85yuTx65U17b+JumbWovwxqhrvcszM7n68lyTxqzJrk9rnwi3XKtl9+pP2L36kwb3vXfvXto+2/aG7/kXY19scJ8NUZ/foapMfV4dwKZ27Qm3s6u1jb60lLQ33iDNTHN1Vj1nLT8/v8YjGeZW13lz8+fPN0tc9aa6RyHzdiaTtzPZLPH/quzsAup931ZLioqKIj4+nhkzZjBq1KjmTqdJmnTiRG0jXkqlkg0bNjBlyhQiIiIIDQ1l2bJlRjMrq1Qqdu3axYwZMxg2bBhlZWWEh4eb7JLfmjg4OPDTTz8xa9YsHnroIfLz82nTpg333ntvrevzj3/8g71/nKwOGKZ2uXDhAu3atTNbvkIIIYQwr9omFL7ZNKiwq+ub1datW40e33fffZw6ZTyh6PUn6AYHB/P111/X2N/8+fOrfVubNm2a0bx111+JW9N8dMeuO9HYz8+PmJiYGmPeyPVxhBBCCCFamhZ9r1ghhBBCCFF/UtgJIYQQQrQSUtgJIYQQQrQSUtgJIYQQQrQSUtgJIYQQQrQSprlPjBBCCCFEHVJLSsnWllksnoeNNYF25rkVYWxsLAMHDkStVuPm5maWGI0hhZ0QQgghzC61pJS+BxPQ6Gq+L7E52CoVxN0RVu/ibsKECeTk5FSbvs2UkpKSeOmll9i/fz8ajYYhQ4bw4Ycf4uvra5L+5VCsEEIIIcwuW1tm0aIOQKPTW3SEsC6FhYXcf//9KBQK9uzZQ1xcHKWlpYwcOdJwT/umksJOCCGEEOI6Go2GKVOm4OPjg52dHf369SM+Pr5au7i4OLp164adnR29e/fm5MmTN+wzLi6OixcvsnbtWrp27UrXrl2JiYnh0KFD7NmzxyR5S2EnhBBCCHGdmTNnsmnTJmJiYjhy5AghISEMHjyY7Oxso3bR0dEsWbKE+Ph4vL29GTlyJFqttsY+NRoNCoUCW1tbwzI7OzuUSiX79+83Sd5S2AkhhBBCVFFYWMjy5ctZvHgxQ4cOJTw8nBUrVmBvb8+qVauM2s6bN49BgwYZRt/S0tJueO/Z3r174+joyKxZsygqKqKwsJCXXnqJ8vJyrl69apLcpbATQgghhKgiKSkJrVZL3759DctsbGzo1asXCQkJRm379Olj+NnDw4PQ0NBqbSp5e3vz1VdfsW3bNpycnHB1dSUnJ4fu3bujVJqmJJOrYoUQQgghLOT+++8nKSmJzMxMrK2tcXNzw8/Pjw4dOpikfxmxE0IIIYSoomPHjqhUKuLi4gzLtFot8fHxhIeHG7U9cOCA4We1Wk1iYiJhYWF1xvDy8sLNzY09e/aQnp7OAw88YJLcZcROCCGEEKIKR0dHJk+eTHR0NB4eHgQFBfHuu+9SVFTExIkTjdouWLAAT09PfH19mTt3Ll5eXowePfqGfa9Zs4awsDC8vb355ZdfmDp1Ki+++CKhoaEmyV0KOwtLy03F1sbe8PhaTgoApZmlFF8sbq60qinNLAUgqVTT6D5Sy7RN7sOSKvM0x74wxfY0lcr9kp5X0CzxK+M2ZjtXbkfNlebfjo1lqvdC5X7MyMhock6mpFarAcvmVRnrUu5VTlw7Y7G4DXEuK7m5UxD1oNPpsLauKI0WLVqETqdj/Pjx5Ofn07NnT3bu3Im7u7vRaxYtWsTUqVM5e/YskZGRbNu2DZXqxhMinzlzhjlz5pCdnU27du2YO3cuL774osnWQaHX6y07W+BfVF5eHq6urjU+p1Ao0etNMzGhKSmBpmZlij4syZz5tqRtoVAoaM5f/SbFVwA3+V8tU70Xmns/3khz5NVSt0VVDvYOJJxOICgoqLlTabLKz7Tc3FxcXFyMnispKeHChQu0b98eOzs7w/Kb4c4TQ4YMISQkhH/9619mzqxhbrRNayIjdha2d+9enJycjJZpNBqjOW1aClPk1VLX7UbMmW9L2hbNnUtT4jd37qZgqnVoqduiOfJqqduiKi8vr1ZR1DVWoJ2KuDvCWuS9YtVqNXFxccTGxjJp0iQLZGY+UthZWGRkZLVvN0IIIcRfQaCdqt6jZ5YUFRVFfHw8M2bMYNSoUc2dTpNIYSeEEEKIv7QbTSh8M5LpToQQQgghWgkp7IQQQgghWgkp7IQQQghhcjpdS5kH4ObXkG0p59gJIYQQwmRUKhVKpZIrV67g7e2NSqVCoVA0d1o3Jb1eT2lpKRkZGSiVylrnx6skhZ0QQgghTEapVNK+fXuuXr3KlStXmjudVsHBwYGgoCCUyroPtEphJ4QQQgiTUqlUBAUFUVZWRnl5eXOnc1OzsrLC2tq63qOeUtgJIYQQwuQUCgU2NjbY2Ng0dyp/KXLxhBBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEKyGFnRBCCCFEK2Hd3An81Rw7dgwnJ6dmia3RaLC1ta338tbAkuvW3NuxueObgqXWoSVtq+bOxcvLi6CgoGaLL4QwLSnsLKx///7NFluhUKDX6+u9vDWw5Lo193ZUKJTo9bpmi28KltqGzb2vjCiVoGu+/Wbn4MCZhAQp7oRoJaSws7C/9ehKGw9Xi8c9fTWdHScTeeyO/2/vvqOiOtM/gH+HGRg6Qy+hqhgLqKDRJZrVRCKWWKI/C4vEkjWrYiJx1xg3sSSuLW56jFnNsazR1TXBRmxEDQajgCA2DCiiqIA0Yeht7u8P14kjo9SZkev3c86cw33vO/d9njvDzMN7C73gZP37jGGesgzb41PwynPT0N2jr97j0qVLNxMQnbgJr776KhwdHXU6Vn5+Pnbv3m2w/Xg/1ykvLYSLon1+Qd/P4eH3aFu7/55f9qIcw30N+xF44EodFh2vhvXfl0Pm6aP38euyMqFc8R4KCgpY2BGJBAs7PXOwtoC7rf4LuzxlGQDAydpS6/j2li7wcOys77B0KvduFgDA0dERrq6uehnTUPvxfq4uCs92+zrez+FR79G25mMrQaCrVOfjPM7lgnoAgMzTB8aduxo0FiISB148QURERCQSLOyIiIiIRIKFHREREZFIsLAjIiIiEgkWdkREREQiwcKOiIiISCRY2BERERGJBAs7IiIiIpFgYUdEREQkEizsiIiIiESChR0RERGRSLCwIyIiIhIJFnZEREREIiEzdAD0u75jxsO3bxDs3NxRV1OD7PTLOLFtM+7m3AYAWDs6YcZXG7U+d/+nK5F++uQjt5WachZn3pip8RxzGwXCZryJBf/uCVsbOyjzq3Hm4HVcO5vfqjwCQ7zQIcARti7mqKtRIfdaCU7tzkDxnQoAgNxchr4jfeDR1Q5WdqaoLKtFZko+4vddQ01VfavGbokBAwYgODgYp0+fxqFDhwAAMpkMQ4YMgZ+fH2QyGa5evYoff/wR5eXlLR6nsf0CAIP+9Czcu9rBwsYEtdX1yL1Wgl+jNPvoUlNifNArc3rCy88eB9adR+a5Ap3E1PPlYej58nBYOzoDAApvZeHUD//B9ZQkAID/4BB07T8ITj4dITc3x1fTJqK6ouWvU6MizwMKr4btCRuAA3/TyZB/83bB33xcNNqulFfhhYTfAACTXe0x1tkW/lZmsJJJ0fmXC1DW6f93iYgM74ku7JYuXYo9e/YgJSXlkX0GDRqEXr164bPPPtNbXLri3tUPKYd/RG7GFRhJpRgw6TX833vLsOmvs1BXXY3SggKse2OyxnN6BA/FcyPHIvNs0mO35T96Ao4cOYKv3/yzus+wiHmQyE0xatQoDPQdj3ETxiFkhh92rUxEwc2yFufh1lmBi7G3kHe9FBIjCf4wpgNGvdUL2z84jboaFSwUcljYyPHrD1dRlFMBK3tTDPrTszBXyHF4/cUWj9uiWN3c0Lt3b+Tm5mq0h4SEoHPnzti1axeqqqowfPhwTJw4ERs3ai+smzRWI/sFAPKySpGWcAdld6vuFcCv+GDU3F7Y+t6vEIRWpdpmMd7Xc7AHAN0HVVpYiF+2b8Hd3GxIJEC3Pw7GmPnvY+uCuSi8lQVjuRzXzyXh+rkkvPCnqTqPB+tfBIykvy87dQNe2wuk7tHpsL+VVWL8uQz1cv0DbwgzqRGOFSlxrEiJ9zu66TQOInqyNetQ7NSpUyGRSDBz5swG6yIiIiCRSDB16tS2iq1JoqKisGzZMp2Pk5WVhREjRsDc3BxOTk6YP38+6urq2nSMqJVLcCn2KApvZSH/RiYOff0prB2d4NyhEwBAEFSoKCnWePg+F4S0U3Gora567Lb+tWwJvLy84O77rLqP27NdEbc3ComJicjPuYukg9dRU1EHR0+rVuUR/eU5/HYqF0U55Si8XYajWy7Dyt4Ujp7WAICi7HIcWn8R1y8UQllQidtpd3F6bwZ8/B0gMZK0auzmMDExwbhx47B//35UVf2+/+RyOQIDA3H48GFkZmYiJycHe/fuhaenJ9zd3Vs8XmP7BQBS47KRc7UYpYVVKLhZhvh912BlZwore7NW5dqWMQKAg7slegV74Ni/f9N5TNeSE5CZcgbFudm4m5ONkzu3oqaqCq7/ey8nH9iHhL3fI/tKms5jAQBUFAJleb8/OocARdeA63E6HbZOAPJr6tSPotrfZ+Q23MrHV1l5SFbqZ2aXiJ5czT7HzsPDAzt27EBlZaW6raqqCtu3b4enp2ebBtcUdnZ2sLJqXSHSmPr6eowYMQI1NTX49ddfsWXLFmzevBmLFy/W6bhycwsAQFWZ9tkzJ5+OcPLpiIvHjzS6LXNLSwBARalS3Zaddhm9Br4EW1tbSCQSdOrjBKmxEbLTi1sf/APkZvcmhqsrah/Zx8RMhpqqOggqPUxL/c/w4cORnp6Oa9euabS7ublBKpVqtBcUFKC4uLhVhd3DGtsvMhMjdHneFSX5lSi7W6W1j65pi1FmbISXX++OEzvSUaGs0Ws8EokRnn3+jzCWmyI7XfdFZaOkxkCPicDZ73Q+VAdzE6Q83x3xf+iKtV098YzcWOdjElH70+zCLjAwEB4eHoiKilK3RUVFwdPTEwEBARp9Dx06hAEDBkChUMDe3h6vvPIKMjIyNPrcunULoaGhsLOzg4WFBfr06YP4+HiNPlu3boW3tzdsbGwwadIklJaWqtcNGjQIkZGR6mVvb2+sWLEC06dPh5WVFTw9PbF+/XqN7d28eRMTJkyAQqGAnZ0dRo8ejevXrz8y5yNHjiA1NRXfffcdevXqhWHDhmHZsmVYu3Ytamp09MUmkWDQlBm4/dslFN68obWL/0tDUHgrq/EvOIkE4ZF/Q1xcHHKvZ6qboz9bDalMhqKiImw4/CEGhXXBwW8uoCS/8jEba24ewIDxvsi+WoyibO3nPZlaGOO54T64FJfdduM2ws/PD66urjh69GiDdZaWlqirq9OYxQOA8vJyWP6vQG61x+wXv4HP4I3P/oi/fDEIXt3tse/zFKjq9VfwNhbjgPG+yM0o0dk5ddo4eHjhzS27ELltN4L/PBv7/rkcRbdv6m38R+ryCmBqA6Rs0+kwycpyzL2chdBzGViQfgueZnLsDfSFhZTXvxGRphZ9KkyfPh2bNm1SL2/cuBHTpk1r0K+8vBzz5s3DmTNncPToURgZGeHVV1+FSnXvXJ2ysjIMHDgQt2/fxr59+3Du3Dm888476vUAkJGRgT179iA6OhrR0dGIjY3FqlWrHhvfxx9/jD59+uDs2bOYPXs2Zs2ahbS0e4dpamtrERISAisrK/zyyy84efIkLC0tMXTo0EcWaadOnYK/vz+cnZ3VbSEhIVAqlbh06ZLW51RXV0OpVGo8mmPw9Flw8PBC9OcfaV0vMzZBl/4DceF4TJO25d6xEyZNmqTR3n/iZJhZWmLw4MH4YOZanPspCyEzusPOzaJZsT7OwEmdYfeMBY58q30/GZtK8cqcHijKKUfi/kytfdqatbU1hg4diqioqDY/nN5Uj9sv6fG52LkiEVH/TEbxnQqEzOgOqUz/X+DaYvTu4YBnutgibtcVvcZSlH0bW995C9vem4dzMQcxNOJt2D3jodcYtAoIB67EAKW5jfdthWNFpdifX4LL5VX4uagUYeevwVomxSgnhU7HJaL2p0UXT0yePBkLFy7EjRv3ZpJOnjyJHTt24Oeff9boN27cOI3ljRs3wtHREampqfDz88P27duRn5+PxMRE2NnZAQA6deqk8RyVSoXNmzerD7eGh4fj6NGjWL58+SPjGz58OGbPng0AWLBgAT799FMcP34czz77LHbu3AmVSoVvv/0WEsm987k2bdoEhUKBn3/+GUOGDGmwvdzcXI2iDoB6+eGT7u9buXIlPvjgg0fG+DgvTZuJjoHPYcfSd1FWVKi1j+8f+sNYLkdqbMMZJ23bWjRjKm7fvg108wEA2Di7IGDoSKyeEY5jx47B48V+SPzxOlw7KeA/yB2x21t/vtILkzrDy98Buz9ORnlxdYP1xnIpRr7ZCzVV9Tj4zQWo9HQY1s3NDZaWlvjLX/6ibjMyMoKXlxf69u2LrVu3QiaTwdTUVGPWzsLCAmWPOCzeHI3tl5qqetRUVaIkrxJ3Mkvw50/+iA69HHHlzJ1Wj93aGN2ftYWNgxn+/MkLGv2H/sUfOVeLseeTszqJR1Vfh+I7OQCAvMwMuHT0ReDwUfhpw1qdjNckNh5Ah0HAzsmNdm1ryrp6XKuoho+ZXO9jE9GTrUWFnaOjI0aMGIHNmzdDEASMGDECDg4ODfpduXIFixcvRnx8PAoKCtQzcVlZWfDz80NKSgoCAgLURZ023t7eGufQubq6Ii8v77Hx9ejRQ/2zRCKBi4uL+jnnzp3D1atXG5yXV1VV1eAwcWssXLgQ8+bNUy8rlUp4eDQ+w/DStJno1DcI//1gIZT5j/4i939xCDLOJKCy9NEzgQ9uKz9H8zCnscm9L4SHiylBJUDSBtcvvDCpMzr0csSeT5JRWtjw/DBjUylGvdUL9XUqHPj6POrrVFq2ohvXrl3D119/rdE2evRoFBQU4OTJkygpKUF9fT18fHxw+fJlAIC9vT0UCgVu3brVqrEb2y8NSO49pMb6u6jkcTEmH76B1JOa76XQxf1wctcVZJ7X36FZiUQCqczA55gFhAHl+cCVw3of2lxqBC8zE9zJffR5q0T0dGrx7U6mT5+OOXPmAADWrtX+V/PIkSPh5eWFDRs2wM3NDSqVCn5+fupDnmZmjV/pZ2ys+eEtkUg0DtU29zllZWXo3bs3tm1reE6Mo6Oj1u25uLggISFBo+3OnTvqddrI5XLI5c37a3rw67PQpf9A7F3zD9RUVsDcRgEAqKmoQF3t74eJFc6ucO/aHVGrljZ5WzZ29nB2doaxiQkAoCj7Fu7mZGNC5N+w+0I6HN3s0CvYAx5d7fDj1+ebFffD/hjaGZ2fc8aBdRdQW1UPc+t7Y1ZX1qG+VqUu6mQmUsRsTIWJmQwm/3srVJbW6Py2HjU1NQ3+OKitrUVlZaW6PTk5GSEhIaisrER1dTWGDx+Omzdvtqqwa2y/WDuYolNvZ9y8XITK0hpY2soRGOKF+hoVblzUPnPb1hqLsUJZo/WCidKiqqYVqi0wIHQKMlPOoLQgHyamZugyYBA8uvnjhxX3Ll4yt1HAQmELWxdXAICDpzdqKitQWpCPqvLWz7BqJZEAvcKAc/8BVLq/X9ySjm44UliCW1W1cDaRYb6PK1QCsCfvLgDA0UQGJxNjeJvde726WpiirF6F21U1KOb97IieKi0u7O6fkyaRSBASEtJgfWFhIdLS0rBhwwa88MK9wzZxcZq3A+jRowe+/fZbFBUVPXbWri0FBgZi586dcHJygrW1deNPABAUFITly5cjLy8PTk5OAICYmBhYW1ujW7dubRZbryEjAAATl2qeQ3jo609x6YFDrn4vvozSogJcP//ow17atvU1gO1rViDnzK9Q1dcjatVS9Pm/P2H//v1QWNuitLAaP2253Ooiwn/gvStHX/1roEb70S2p+O1ULhw9reDSwQYAEP6PII0+/37vV50VCM1x+PBhCIKAiRMnQiqVIiMjAz/++GOrttnYfqmrVcHN1wY9B3tAbi5DhbIGOVeL8cOaJFSW6mdmprEYDcHc2gbDZs+Dha0dairKkZ91HT+sWIwbF1IAAD1fHo7nx/9J3X/SB6sBNPy9aVMdXgQUnsDZrbrZ/kNc5cZY180btsZSFNbUIaGkHMOT0lH4v1ueTHFz0LiB8d5AXwDA3MtZ2JlbpJcYiejJ0OLCTiqVqg9TSaXSButtbW1hb2+P9evXw9XVFVlZWXj33Xc1+oSGhmLFihUYM2YMVq5cCVdXV5w9exZubm4ICgpqsM22EBYWhjVr1mD06NH48MMP4e7ujhs3biAqKgrvvPOO1ttZDBkyBN26dUN4eDg++ugj5Obm4v3330dERESzZ+Ue5+OJrzSpX9yOfyNux7+bta3kG7exPT4FkS8PgLvtvaKqODcbm5ctwmcxcZjy4kI81zm4ZYE/ZO3MY49dn51e3Ggffdu8ebPGcl1dHQ4cOIADBw602RiN5VxRUoPor1o3W9paLXlddP1aHvnXF49df+r77Tj1/XadxtBAxjFgqY3ehpuZqv3K+Pv+eT0X/7xumMKbiJ4srbrUztra+pGzXkZGRtixYweSkpLg5+eHt99+G2vWrNHoY2JigiNHjsDJyQnDhw+Hv78/Vq1apbVQbCvm5uY4ceIEPD09MXbsWHTt2hWvv/46qqqqHpmLVCpFdHQ0pFIpgoKCMHnyZLz22mv48MMPdRYnERERUXM1a8bu4VmNh+3Zs0djOTg4GKmpqRptwkMnUHl5eeH777/Xur2lS5di6dKlGm2RkZEa9617+Epcbfeje/hfkrm4uGDLli1ax3wULy+vNp29ISIiImprvLslERERkUiwsCMiIiISCRZ2RERERCLBwo6IiIhIJFjYEREREYkECzsiIiIikWBhR0RERCQSLOyIiIiIRIKFHREREZFIsLAjIiIiEgkWdkREREQiwcKOiIiISCRY2BERERGJBAs7IiIiIpFgYUdEREQkEjJDB/C0KVCWQy7T/24vKq8AAOQpyzTa7y8XluXiZn663uPSpcKyXABAfn6+zse6P4ah9uP9XHOLs/Q+dlu5n8PD79G2dn/7mXcFJOfU63SsxmTeFQAAdVmZBhnfUOMSke5IBEEQDB3E00CpVMLGxsagMUgkEmh7uR/VLgb6zM3Q+1EiMYIgqAw2flvQ1z409GulwcgIUBnudTM1N0fa5cvw9PQ0WAzU/tz/TispKYG1tbWhw6EHcMZOz2JjY2FpaWmQsaurqyGXy5vcLgb6zM3Q+9HQ47cFfeXwJO0rQ8fi4ODAoo5IRFjY6VmvXr341w0RERHpBC+eICIiIhIJFnZEREREIsHCjoiIiEgkWNgRERERiQQLOyIiIiKRYGFHREREJBIs7IiIiIhEgoUdERERkUiwsCMiIiISCRZ2RERERCLBwo6IiIhIJFjYEREREYkECzsiIiIikWBhR0RERCQSMkMH8LQQBAEAoFQqDRwJERFR69z/Lrv/3UZPDhZ2elJYWAgA8PDwMHAkREREbaO0tBQ2NjaGDoMewMJOT+zs7AAAWVlZov4lUCqV8PDwwM2bN2FtbW3ocHTqacmVeYrL05In8PTkaog8BUFAaWkp3Nzc9DIeNR0LOz0xMrp3OqONjY2oP2Dus7a2firyBJ6eXJmnuDwteQJPT676zlPMkxTtGS+eICIiIhIJFnZEREREIsHCTk/kcjmWLFkCuVxu6FB06mnJE3h6cmWe4vK05Ak8Pbk+LXlS00gEXqtMREREJAqcsSMiIiISCRZ2RERERCLBwo6IiIhIJFjY6cnatWvh7e0NU1NT9OvXDwkJCYYOqVVWrlyJ5557DlZWVnBycsKYMWOQlpam0aeqqgoRERGwt7eHpaUlxo0bhzt37hgo4raxatUqSCQSREZGqtvEkuft27cxefJk2Nvbw8zMDP7+/jhz5ox6vSAIWLx4MVxdXWFmZobg4GBcuXLFgBE3X319PRYtWgQfHx+YmZmhY8eOWLZsmca/RWqveZ44cQIjR46Em5sbJBIJ9uzZo7G+KXkVFRUhLCwM1tbWUCgUeP3111FWVqbHLBr3uDxra2uxYMEC+Pv7w8LCAm5ubnjttdeQnZ2tsY32nufDZs6cCYlEgs8++0yjvT3kSW2PhZ0e7Ny5E/PmzcOSJUuQnJyMnj17IiQkBHl5eYYOrcViY2MRERGB06dPIyYmBrW1tRgyZAjKy8vVfd5++23s378fu3btQmxsLLKzszF27FgDRt06iYmJ+Ne//oUePXpotIshz7t376J///4wNjbGwYMHkZqaio8//hi2trbqPh999BG++OILfPPNN4iPj4eFhQVCQkJQVVVlwMibZ/Xq1Vi3bh2++uorXL58GatXr8ZHH32EL7/8Ut2nveZZXl6Onj17Yu3atVrXNyWvsLAwXLp0CTExMYiOjsaJEyfwxhtv6CuFJnlcnhUVFUhOTsaiRYuQnJyMqKgopKWlYdSoURr92nueD9q9ezdOnz6t9T9AtIc8SQcE0rm+ffsKERER6uX6+nrBzc1NWLlypQGjalt5eXkCACE2NlYQBEEoLi4WjI2NhV27dqn7XL58WQAgnDp1ylBhtlhpaang6+srxMTECAMHDhTmzp0rCIJ48lywYIEwYMCAR65XqVSCi4uLsGbNGnVbcXGxIJfLhf/85z/6CLFNjBgxQpg+fbpG29ixY4WwsDBBEMSTJwBh9+7d6uWm5JWamioAEBITE9V9Dh48KEgkEuH27dt6i705Hs5Tm4SEBAGAcOPGDUEQxJXnrVu3hGeeeUa4ePGi4OXlJXz66afqde0xT2obnLHTsZqaGiQlJSE4OFjdZmRkhODgYJw6dcqAkbWtkpISAL//T9ykpCTU1tZq5N2lSxd4enq2y7wjIiIwYsQIjXwA8eS5b98+9OnTB+PHj4eTkxMCAgKwYcMG9frMzEzk5uZq5GljY4N+/fq1qzyff/55HD16FOnp6QCAc+fOIS4uDsOGDQMgnjwf1pS8Tp06BYVCgT59+qj7BAcHw8jICPHx8XqPua2UlJRAIpFAoVAAEE+eKpUK4eHhmD9/Prp3795gvVjypObj/4rVsYKCAtTX18PZ2Vmj3dnZGb/99puBompbKpUKkZGR6N+/P/z8/AAAubm5MDExUX+Y3ufs7Izc3FwDRNlyO3bsQHJyMhITExusE0ue165dw7p16zBv3jz8/e9/R2JiIt566y2YmJhgypQp6ly0vY/bU57vvvsulEolunTpAqlUivr6eixfvhxhYWEAIJo8H9aUvHJzc+Hk5KSxXiaTwc7Ort3mXlVVhQULFiA0NFT9P1TFkufq1ashk8nw1ltvaV0vljyp+VjYUatFRETg4sWLiIuLM3Qobe7mzZuYO3cuYmJiYGpqauhwdEalUqFPnz5YsWIFACAgIAAXL17EN998gylTphg4urbz3//+F9u2bcP27dvRvXt3pKSkIDIyEm5ubqLKk+5dSDFhwgQIgoB169YZOpw2lZSUhM8//xzJycmQSCSGDoeeMDwUq2MODg6QSqUNrpK8c+cOXFxcDBRV25kzZw6io6Nx/PhxuLu7q9tdXFxQU1OD4uJijf7tLe+kpCTk5eUhMDAQMpkMMpkMsbGx+OKLLyCTyeDs7CyKPF1dXdGtWzeNtq5duyIrKwsA1Lm09/fx/Pnz8e6772LSpEnw9/dHeHg43n77baxcuRKAePJ8WFPycnFxaXBBV11dHYqKitpd7veLuhs3biAmJkY9WweII89ffvkFeXl58PT0VH8u3bhxA3/961/h7e0NQBx5UsuwsNMxExMT9O7dG0ePHlW3qVQqHD16FEFBQQaMrHUEQcCcOXOwe/duHDt2DD4+Phrre/fuDWNjY42809LSkJWV1a7yHjx4MC5cuICUlBT1o0+fPggLC1P/LIY8+/fv3+B2Nenp6fDy8gIA+Pj4wMXFRSNPpVKJ+Pj4dpVnRUUFjIw0P/akUilUKhUA8eT5sKbkFRQUhOLiYiQlJan7HDt2DCqVCv369dN7zC11v6i7cuUKfvrpJ9jb22usF0Oe4eHhOH/+vMbnkpubG+bPn4/Dhw8DEEee1EKGvnrjabBjxw5BLpcLmzdvFlJTU4U33nhDUCgUQm5urqFDa7FZs2YJNjY2ws8//yzk5OSoHxUVFeo+M2fOFDw9PYVjx44JZ86cEYKCgoSgoCADRt02HrwqVhDEkWdCQoIgk8mE5cuXC1euXBG2bdsmmJubC9999526z6pVqwSFQiHs3btXOH/+vDB69GjBx8dHqKysNGDkzTNlyhThmWeeEaKjo4XMzEwhKipKcHBwEN555x11n/aaZ2lpqXD27Fnh7NmzAgDhk08+Ec6ePau+GrQpeQ0dOlQICAgQ4uPjhbi4OMHX11cIDQ01VEpaPS7PmpoaYdSoUYK7u7uQkpKi8dlUXV2t3kZ7z1Obh6+KFYT2kSe1PRZ2evLll18Knp6egomJidC3b1/h9OnThg6pVQBofWzatEndp7KyUpg9e7Zga2srmJubC6+++qqQk5NjuKDbyMOFnVjy3L9/v+Dn5yfI5XKhS5cuwvr16zXWq1QqYdGiRYKzs7Mgl8uFwYMHC2lpaQaKtmWUSqUwd+5cwdPTUzA1NRU6dOggvPfeexpf+u01z+PHj2v9nZwyZYogCE3Lq7CwUAgNDRUsLS0Fa2trYdq0aUJpaakBsnm0x+WZmZn5yM+m48ePq7fR3vPURlth1x7ypLYnEYQHbrlORERERO0Wz7EjIiIiEgkWdkREREQiwcKOiIiISCRY2BERERGJBAs7IiIiIpFgYUdEREQkEizsiIiIiESChR0RERGRSLCwI6J2Z+rUqRgzZoyhwyAieuLIDB0AEdGDJBLJY9cvWbIEn3/+OfhPc4iIGmJhR0RPlJycHPXPO3fuxOLFi5GWlqZus7S0hKWlpSFCIyJ64vFQLBE9UVxcXNQPGxsbSCQSjTZLS8sGh2IHDRqEN998E5GRkbC1tYWzszM2bNiA8vJyTJs2DVZWVujUqRMOHjyoMdbFixcxbNgwWFpawtnZGeHh4SgoKNBzxkREbYeFHRGJwpYtW+Dg4ICEhAS8+eabmDVrFsaPH4/nn38eycnJGDJkCMLDw1FRUQEAKC4uxksvvYSAgACcOXMGhw4dwp07dzBhwgQDZ0JE1HIs7IhIFHr27In3338fvr6+WLhwIUxNTeHg4IAZM2bA19cXixcvRmFhIc6fPw8A+OqrrxAQEIAVK1agS5cuCAgIwMaNG3H8+HGkp6cbOBsiopbhOXZEJAo9evRQ/yyVSmFvbw9/f391m7OzMwAgLy8PAHDu3DkcP35c6/l6GRkZ6Ny5s44jJiJqeyzsiEgUjI2NNZYlEolG2/2rbVUqFQCgrKwMI0eOxOrVqxtsy9XVVYeREhHpDgs7InoqBQYG4ocffoC3tzdkMn4UEpE48Bw7InoqRUREoKioCKGhoUhMTERGRgYOHz6MadOmob6+3tDhERG1CAs7Inoqubm54eTJk6ivr8eQIUPg7++PyMhIKBQKGBnxo5GI2ieJwNu3ExEREYkC/ywlIiIiEgkWdkREREQiwcKOiIiISCRY2BERERGJBAs7IiIiIpFgYUdEREQkEizsiIiIiESChR0RERGRSLCwIyIiIhIJFnZEREREIsHCjoiIiEgkWNgRERERicT/A4XoeabMgI64AAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<Figure size 640x480 with 0 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<Figure size 640x480 with 0 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "env.render(td, 0)\n",
     "# Update plot within a for loop\n",
@@ -393,7 +294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -413,82 +314,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/utilities/parsing.py:198: Attribute 'env' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['env'])`.\n",
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/utilities/parsing.py:198: Attribute 'policy' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['policy'])`.\n",
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/accelerator_connector.py:551: You passed `Trainer(accelerator='cpu', precision='16-mixed')` but AMP with fp16 is not supported on CPU. Using `precision='bf16-mixed'` instead.\n",
-      "Using bfloat16 Automatic Mixed Precision (AMP)\n",
-      "GPU available: False, used: False\n",
-      "TPU available: False, using: 0 TPU cores\n",
-      "IPU available: False, using: 0 IPUs\n",
-      "HPU available: False, using: 0 HPUs\n",
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/logger_connector/logger_connector.py:67: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `lightning.pytorch` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default\n",
-      "val_file not set. Generating dataset instead\n",
-      "test_file not set. Generating dataset instead\n",
-      "\n",
-      "  | Name     | Type           | Params\n",
-      "--------------------------------------------\n",
-      "0 | env      | FJSPEnv        | 0     \n",
-      "1 | policy   | L2DPolicy      | 81.2 K\n",
-      "2 | baseline | WarmupBaseline | 81.2 K\n",
-      "--------------------------------------------\n",
-      "162 K     Trainable params\n",
-      "0         Non-trainable params\n",
-      "162 K     Total params\n",
-      "0.649     Total estimated model params size (MB)\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "812cd22f33dd469cb501b27936cc1105",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Sanity Checking: |          | 0/? [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=7` in the `DataLoader` to improve performance.\n",
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=7` in the `DataLoader` to improve performance.\n",
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/loops/fit_loop.py:293: The number of training batches (32) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fcda6b7e273945b3880e38863d6c53ae",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Training: |          | 0/? [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/trainer/call.py:54: Detected KeyboardInterrupt, attempting graceful shutdown...\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Policy: neural network, in this case with encoder-decoder architecture\n",
     "policy = L2DPolicy(embed_dim=embed_dim, num_encoder_layers=num_encoder_layers, env_name=\"fjsp\")\n",
@@ -521,7 +349,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -529,12 +357,14 @@
     "from rl4co.envs import JSSPEnv\n",
     "from rl4co.models.zoo.l2d.model import L2DPPOModel\n",
     "from rl4co.models.zoo.l2d.policy import L2DPolicy4PPO\n",
-    "from torch.utils.data import DataLoader"
+    "from torch.utils.data import DataLoader\n",
+    "import json\n",
+    "import os"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -563,7 +393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -587,64 +417,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using bfloat16 Automatic Mixed Precision (AMP)\n",
-      "GPU available: False, used: False\n",
-      "TPU available: False, using: 0 TPU cores\n",
-      "IPU available: False, using: 0 IPUs\n",
-      "HPU available: False, using: 0 HPUs\n",
-      "Overriding gradient_clip_val to None for 'automatic_optimization=False' models\n",
-      "/Users/luttmann/opt/miniconda3/envs/rl4co/lib/python3.9/site-packages/lightning/pytorch/utilities/parsing.py:43: attribute 'policy' removed from hparams because it cannot be pickled\n",
-      "val_file not set. Generating dataset instead\n",
-      "test_file not set. Generating dataset instead\n",
-      "\n",
-      "  | Name       | Type          | Params\n",
-      "---------------------------------------------\n",
-      "0 | env        | JSSPEnv       | 0     \n",
-      "1 | policy     | L2DPolicy4PPO | 25.5 K\n",
-      "2 | policy_old | L2DPolicy4PPO | 25.5 K\n",
-      "---------------------------------------------\n",
-      "51.1 K    Trainable params\n",
-      "0         Non-trainable params\n",
-      "51.1 K    Total params\n",
-      "0.204     Total estimated model params size (MB)\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5b3c9b45d4fc4eb2a60a3bf80ac42a6f",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Sanity Checking: |          | 0/? [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c0bdcd678f8140b7b5b6b123fa5084c8",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Training: |          | 0/? [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "CHECKPOINT_PATH = \"last.ckpt\"\n",
     "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
@@ -666,124 +441,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Folder does not exist. Creating folder and downloading taillard instances...\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "bash: line 11: wget: command not found\n",
-      "bash: line 12: wget: command not found\n",
-      "bash: line 13: wget: command not found\n",
-      "bash: line 14: wget: command not found\n",
-      "bash: line 15: wget: command not found\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%bash\n",
     "\n",
-    "# Define the folder path\n",
-    "DATA_PATH=\"./taillard\"\n",
-    "\n",
     "# Check if the folder exists\n",
-    "if [ -d \"$DATA_PATH\" ]; then\n",
-    "    echo \"Folder already exists.\"\n",
+    "if [ -d \"JSPLIB\" ]; then\n",
+    "    echo \"Found JSPLIB\"\n",
     "else\n",
-    "    echo \"Folder does not exist. Creating folder and downloading taillard instances...\"\n",
-    "    mkdir -p \"$DATA_PATH\"\n",
-    "    ! wget http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/jobshop.dir/tai20_15.txt -O taillard/tai20_15.txt\n",
-    "    ! wget http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/jobshop.dir/tai15_15.txt -O taillard/tai15_15.txt\n",
-    "    ! wget http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/jobshop.dir/tai20_20.txt -O taillard/tai20_20.txt\n",
-    "    ! wget http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/jobshop.dir/tai30_15.txt -O taillard/tai30_15.txt\n",
-    "    ! wget http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/jobshop.dir/tai30_20.txt -O taillard/tai30_20.txt\n",
+    "    echo \"Cloning JSPLIB\"\n",
+    "    git clone https://github.com/tamy0612/JSPLIB.git\n",
     "fi\n",
     "\n",
-    "exit 0"
+    "exit 0\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Provided file name ../../ai4co/rl4co/data/jssp/taillard/15j_15m not found. Make sure to provide a file in the right path first or unset test_file to generate data automatically instead\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done evaluating instance type 15j_15m with reward -1408.0999755859375\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Provided file name ../../ai4co/rl4co/data/jssp/taillard/20j_15m not found. Make sure to provide a file in the right path first or unset test_file to generate data automatically instead\n",
-      "Provided file name ../../ai4co/rl4co/data/jssp/taillard/20j_20m not found. Make sure to provide a file in the right path first or unset test_file to generate data automatically instead\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done evaluating instance type 20j_15m with reward -1380.699951171875\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Provided file name ../../ai4co/rl4co/data/jssp/taillard/30j_15m not found. Make sure to provide a file in the right path first or unset test_file to generate data automatically instead\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done evaluating instance type 20j_20m with reward -1349.9000244140625\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Provided file name ../../ai4co/rl4co/data/jssp/taillard/30j_20m not found. Make sure to provide a file in the right path first or unset test_file to generate data automatically instead\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done evaluating instance type 30j_15m with reward -1374.0999755859375\n",
-      "Done evaluating instance type 30j_20m with reward -1371.699951171875\n"
-     ]
-    }
-   ],
+   "outputs": [],
+   "source": [
+    "def prepare_taillard_data(nj, nm):\n",
+    "    fp = f\"taillard/{nj}x{nm}\"\n",
+    "    if os.path.exists(fp):\n",
+    "        pass\n",
+    "    else:\n",
+    "        os.makedirs(fp)\n",
+    "        with open('JSPLib/instances.json', 'r') as file:\n",
+    "            data = json.load(file)\n",
+    "\n",
+    "        instances = [x for x in data if \"ta\" in x[\"name\"] and x[\"jobs\"] == nj and x[\"machines\"] == nm]\n",
+    "\n",
+    "        for instance in instances:\n",
+    "            os.popen(f\"cp JSPLIB/{instance['path']} {fp}/{instance['name']}.txt\") \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# path to taillard instances\n",
-    "FILE_PATH = \"./taillard/tai{instance_type}.txt\"\n",
+    "FILE_PATH = \"taillard/{nj}x{nm}\"\n",
     "\n",
     "results = {}\n",
-    "instance_types = [\"15_15\", \"20_15\", \"20_20\", \"30_15\", \"30_20\"]\n",
+    "instance_types = [(15, 15), (20, 15), (20, 20), (30, 15), (30, 20)]\n",
     "\n",
     "for instance_type in instance_types:\n",
-    "    \n",
-    "    dataset = env.dataset(batch_size=[10], phase=\"test\", filename=FILE_PATH.format(instance_type=instance_type))\n",
+    "    nj, nm = instance_type\n",
+    "    prepare_taillard_data(nj, nm)\n",
+    "    dataset = env.dataset(batch_size=[10], phase=\"test\", filename=FILE_PATH.format(nj=nj, nm=nm))\n",
     "    dl = DataLoader(dataset, batch_size=5, collate_fn=dataset.collate_fn)\n",
     "    rewards = []\n",
     "    \n",
@@ -807,7 +518,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "rl4co_pypi",
    "language": "python",
    "name": "python3"
   },
@@ -821,7 +532,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.12.5"
   }
  },
  "nbformat": 4,

From 010ca6f287ffdc77e7884d87fbbb9046fe61c7f1 Mon Sep 17 00:00:00 2001
From: Laurin Luttmann <laurin.luttmann@gmail.com>
Date: Mon, 25 Nov 2024 15:51:43 +0100
Subject: [PATCH 2/2] [BugFix] fixed taillard instances in scheduling nb

---
 examples/other/2-scheduling.ipynb | 139 ++++++++++++++++++++++++------
 1 file changed, 112 insertions(+), 27 deletions(-)

diff --git a/examples/other/2-scheduling.ipynb b/examples/other/2-scheduling.ipynb
index 4b2423de..a9d3986c 100644
--- a/examples/other/2-scheduling.ipynb
+++ b/examples/other/2-scheduling.ipynb
@@ -22,18 +22,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!conda info"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 37,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
    "source": [
     "%load_ext autoreload\n",
     "%autoreload 2\n",
@@ -56,7 +56,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,13 +99,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {
     "jupyter": {
      "source_hidden": true
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Create a bipartite graph from the adjacency matrix\n",
     "G = nx.Graph()\n",
@@ -180,7 +191,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -203,9 +214,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([1, 60, 32])\n",
+      "torch.Size([1, 5, 32])\n"
+     ]
+    }
+   ],
    "source": [
     "encoder = HetGNNEncoder(embed_dim=32, num_layers=2)\n",
     "(ma_emb, op_emb), init = encoder(td)\n",
@@ -222,9 +242,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[ 0,  4,  8, 13, 19, 25, 31, 37, 42, 46]])"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# next operation per job\n",
     "td[\"next_op\"]"
@@ -232,9 +263,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 44,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([1, 51])\n"
+     ]
+    }
+   ],
    "source": [
     "decoder = L2DDecoder(env_name=env.name, embed_dim=32)\n",
     "logits, mask = decoder(td, (ma_emb, op_emb), num_starts=0)\n",
@@ -244,7 +283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -273,9 +312,55 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/luttmann/opt/miniconda3/envs/rl4co_pypi/lib/python3.12/site-packages/matplotlib/axes/_axes.py:2316: DeprecationWarning: __array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0)\n",
+      "  dx = [convert(x0 + ddx) - x for ddx in dx]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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vZ+XKlbi4uPDYY4/Vqo2SbC3Z28+R/M9DJH92GG1iJl5Ph6PydcTGVY3SVU3WtnNcW3CQjPXx2N/hgccjd9SqrZqKdHHg6UAv/sgtMNn+z9YaQh3teObYOXr9epptKVksadOUCGeHKuvs5u7MysupPPD7GR7eugdbW1ve+HQxKjs7Y5mBL7+GT1AwDz74IKt630f2Dz/QZMEC7Fq3rlU/qnqd2wYHE7LmK4rOnuPC089wdugwUj9fjEGrrVV7Da2q/sb3uMfk35U338Sg15Pz/fcWizG4WzcWLVrEommb+O7TwyhtFDw4IRKV+q+3mB6PhhIY6kbC78nEbij98NZreHvjfnuVPW382/Dee+9x6tSpGsfQs2dP9m//gw0f/V5hDE7udji52fHzhgT+M+tXdkWfRNPGi0de6lnH3gvRuNT4UmxwcDBr166loOCvN4fCwkLWrFmDRqMxa3DV4enpiYuLi8XaGzt2LO3atbNYezWRt28fKZ9+Ss7OnRXuz976X/J/+QXdpUsUJSRwfc4cbFxcsAsLs3CkpeLj4zlz5gzp6emkpaWxe/duioqKCAoKQqPR4O7uzubNm0lOTiY5OZlNmzYRGBhIs2bNatyWWq3m4YcfZsuWLRQWFhq329nZ0aFDB3bs2MG5c+e4evUq3377LRqNhqCgoBq3U3gyncLTGRSnFVKcWlA6GldUglrjQvH1fNK/PEnhyXRK0gvRJmaR/f0FHFp71vukCEcbJYvCQ5h8+iJZOtPRwbtcnVh+KZVDOfkkFRbxyYXrZBWX0M6l6sTuiaNnWXctndP5hfyRnsno0aPxDgjAr3mosUxgWGt++nYjcXFxZCUlkfbFF5Tk5ODQpk2t+lLV69xn0iTy9v5I8scfoz15Et3Fi+Tu2UNJenqt2mtoVfW3JDXV5J/LffeRf+AAukuXLBbjN088SXR0NMkXM0i7nMuu6JO4eNnjo3EFQG1vQ+vugez9z2l2rjzBkZ0XAfAN8qBLly4A5OpyGf3laNavX4+2Fkn4wIED+X3PadKv5lUYQ/qVPLYvOc75Y2lkpxZw+XQG+79NpHWnptjY2JjpTAjR8Gr8dtKhQweCg4PZuHGjcdvGjRvRaDS0b9/epOz27dvp0aMH7u7ueHl5MXjwYBITE03KXLp0iZEjR+Lp6YmTkxOdOnXiwIEDJmVWr15N06ZNcXNz4/HHHycnJ8e4r1evXkyaNMn4fdOmTfnwww8ZM2YMLi4uaDQalixZYlLfxYsXGTFiBO7u7nh6ejJ06FDOnz9fZd8XL15MZmYmr7/+epVlGz1bW9wfG0FJdjbaWnw6NjeFQkFERAS2trZcunTJ+Ie2uPivS3rFxcUYDIZafYAYNGgQ8fHxnD171mR7YGAgNjY2JttTU1PJzMysVWJnQgEO7XxQqG0oSsqpuIi9DfrCEtDXramqzGkZxM60bPZl5JbbF5edx1Bfd9xVNiiAob7u2CsV/JxZvmxV3NzcACjM/evYK6dPEtnzPjw8PEChwHXQIJRqNXm//lrr/tySQoFzr54UnT9P8LKltIz9iabr1uLcp4/522qEbLy8cO7Zk8wNGxo0DjuH0lk+2nwdAD4hrtiolFw8mWFSLjergG7dulkkhoqoHVQU5hdRUmKZqRBCWEKtxgnGjBnDypUrjd+vWLGCZ599tly5vLw8XnvtNX777Td27dqFUqlk+PDh6PWl72K5ubn07NmTy5cv891333HkyBGmTJli3A+QmJjI5s2b2bp1K1u3bmXv3r3MmTOn0vjmz59Pp06dOHToEC+99BLjx4/n9OnTAOh0Ovr374+Liwv79u0jNjYWZ2dnBgwYQFFR0S3rPHHiBLNmzeLf//43SuXte8+Jc69ehP3+G62OHMbzmWdIGjOWkga8pOzr68ubb77J22+/zeDBg1m3bh0pKSlcunSJoqIi+vbti62tLba2tvTr1w+lUomzs3ON2oiIiCAgIIBdN83DAnB2dqa4uNhkFA9KX7s1baeMys+RwHfvpsn7PfAYHkra6hMUJ+eXK6d0VOF6n4a8X+t33tdQX3faujjw4dmK23nhjwuolApO3dOWpJ53Mi8smGePned8wa1/HyqiAD755BNOHzlE2sULxu1bP/kIG5WK9PR0XrtwHv93Z3Lp//4PXVJSXbpVIRsvL2ycnPB6/jny9v1E0tjnyNm5k6B/LsTxrrvM3l5j4zZsGPq8vFrPXzQLBfR4tCVXEjJJv1I6T9XRVU2JTk9RQbFJ0cI8Lf7+/haJ4Wb2TrbcNagZv+6seI6iELerWt088dRTTzFt2jQuXCj94x0bG8vatWuJiYkxKffwww+bfL9ixQp8fHw4ceIEERERrFmzhpSUFOLi4vD09AQgNDTU5Bi9Xs+qVauMl1tHjRrFrl27+OCDD24Z36BBg3jppZcAmDp1KgsWLGDPnj2EhYWxbt069Ho9y5YtM87VWrlyJe7u7sTExNCvX79y9Wm1WkaOHMm8efPQaDTlRn0qotVqTS4nZGdnV3mMJeQdOMDZ4Q9h4+GBx6OP0uSTBZwf8ViDXaZKS0vjiy++wM7OjvDwcIYNG8aqVatISUlh/fr1PPDAA3Tp0gWDwcCxY8e4cuUKBoOh2vW7uroyYMAAVq9ebTL6V5+KUwu4vvAgSnsVDhHeeDwaRsqSoybJncLOBu/RbShOzid7p/kTnDKBdra837IJIw4notVXfN6mNvPHTWXDI4cTSC8qZqCPG0vaNGXooTOcyius8JiKzOvRiQgnW+b/34s0dbQ1bu/+2FM4ODvTp08fRqHggWFDabJgAReeegpt/Jk69/FGCmXp73TO7t2kR0cDoD11Cof27XF//DHy4+LM2l5j4/7wQ2Rt3Yqhkg+p9a3n43fg2cSJjfMONtoYbO1tGPxKO9Kv5rFz3W8Wjk6I+lWrxM7Hx4cHHniAVatWYTAYeOCBB/D29i5X7syZM7zzzjscOHCA1NRU40hcUlISERERHD58mPbt2xuTuoo0bdrUZA5dQEAAycnJlcZ34xw4hUKBv7+/8ZgjR46QkJBQbl5eYWFhucvEZaZNm0br1q156qmnKm33RrNnz+bdd9+tdnlLMRQUoEtKQpeUxNUjR2ixfTvujzxM2pKlDRJPSUkJ6X8mlVevXqVJkyZ06dKFrVu3kpiYyMKFC3F0dESv11NYWMjrr7/O8ePHq11/YGAgzs7OvPjii8ZtSqWSkJAQOnfuzOrVq1GpVNjb25uM2jk5OZGbW/NLkaWdMlCSVkgJoLucizrIGefugWRuKp0wrlDb4D0mAr22hNTVJ+AWCZc5tHNxxEdtyw+d/ppHqVIq6OruxJgm3nQ/cJKxQT70PHCK0/ml/T+RV0gXN2eebeLN1PjqzdP6sGUT+rk70qNtBHf7udM0pAkAbn7+tB8whI+eH8Xu3bsZ4B9A6uXLOHbshMcTT3Btpnl/R4ozMjHodGgTTH+XtYlncezYwaxtNTYOHTti17w5l199rcFiePC5HoS09WbT/IPkZf71wTY/uwgbWyVqB5XJqJ29k125m5lUKhXNmzevdQz3PH5HhTGUsbWzYcj/RVJUWML/vjiGvqSe50EIYWG1Xu5kzJgxvPLKKwAsWrSowjJDhgwhJCSEpUuXEhgYiF6vJyIiwnjJ08Gh6snZtra2Jt8rFAqTS7U1PSY3N5eOHTvy1VdflTvOx8enwvp2797NsWPH+OabbwCMI0be3t5Mnz69wgRu2rRpvPbaX39gs7OzCQ4OrjTuBqFUoFCrGzoKI4VCgUpl+rLMzy8d6WrWrBlOTk7Gy+rVcfbsWT7//HOTbUOHDiU1NZXY2FiysrIoKSmhWbNmnDxZeknGy8sLd3d3Lplr8rlSgUJVevleYVea1FGiJ+3fJ6C4/pI6gH0ZOfT61XQO5SetNJzJL2RRUjIONqVx6TGNowQDymrefPxhyyYM9HHjwY07OH/+PHf7RRr32apL747V35S8GvQlUB9TGnQ6Co4fx+6mG2zsmjZFd+WK+dtrRNwfeZiC48fR1uD3w5z++c9/0qZzM7795BA5aaYjvSkXsikp1hPUyoOzh1KM253dHPjll1/gztLvVUoVX3/9NXY33FVdEw8+14PmkT5s/sfBcjFA6UjdgxMiKSnWs+3zo5QUS1InrE+tE7uyOWkKhYL+/fuX25+Wlsbp06dZunQp99xzDwA//fSTSZl27dqxbNky0tPTKx21M6cOHTqwbt06fH19cXV1rdYxGzZsMLkLOC4ujjFjxrBv3z5atGhR4TF2dna1/uNUWwpHR9Q33FigDgrCrlUrSrKyKMnMxHvci+Ts3kNxSgoqD3c8nngClZ8f2dt3WDTOMn369CEhIYGsrCzUajVt27aladOmrF69GoDIyEhSU1PJy8sjODiYAQMG8Msvv5CWllbtNoqKisqN8Op0OgoKCozbDx48SP/+/SkoKECr1TJo0CAuXrxYq8TOtX9TCuPTKcnUolDb4Bjpi10zN1JXHC9N6sZGoLC1IW31aRR2NijsSm8S0efpoB5yvLwSfbnLqfklejJ0JZzKK0SlgLP5WuaGBTMr4QrputJLsT09XBh1tOopB3PuCGK4rwejj58lV1eMn58fbp5eqGzVFOuKSL9yiYyrVxgx6XU2HYvHXWmD5/BhON19NxfHja9Vnyp7nRdfvUr68hU0+cd88n/7jbwDB3C+pwfOvXtx4elnatVeQ6uqvwBKJydc+/fn+kdzGyTG+2d/SLNhw1g7fydqrReOrqUfFrUFxaVz6wpLOBl7hR6PtsTeUYXuz3Ub05OzKSwsJNAjkCJFEQseXUCYUxjnz5+ndQ2Xw1m0aBHt723J9i/+QFdYUi6GsqROpbbhhxUnUDuoUDuAs87htp43LcTNap3Y2djYGEc4KrpV3MPDAy8vL5YsWUJAQABJSUm88cYbJmVGjhzJhx9+yLBhw5g9ezYBAQEcOnSIwMDAertT6sknn2TevHkMHTqUWbNmERQUxIULF9i4cSNTpkyp8E7Im5O31NRUAFq3bm1cXLcxcIhoQ8i//2383m9a6fnO3LSJazNmom7WnKCFw7Dx8KAkM5PCY8e48ORTFP25ILClOTk5MXz4cJydndFqtVy/fp3Vq1cb5zB6e3tz//334+DgQGZmJvv27Sv9dG9mO3bswGAw8Nhjj2FjY0NiYiL//e9/a1WXjbMtniPCsHFRoy8sRnc1j9QVx9EmZGLX3A27P5deCJhiOpH/6ke/UpJh+XXWig3w5NFEpjcP5N/tmuFko+RcQRETTiaxK73iO3lvNLpJ6RSMTe1bQvuW8PRwALZ/voA/9u5CX1LCxjkz6fTIE2zZsgUPFxf0SUlceWMaeT/+WKuYK3udX532Jjk7d3J15rt4v/ACftPfpOjcOS5NmEjBwYab81UXVfUXwPWBQaBQkF3L121dtf9z/dIX3xtqsn1X9AlO/VJ6qfWn9Qk4utnRe9RfCZunryuHDx9m/c/rWXZlGfe3ur/WMZTNqx4+2fSSe1kMPhoX/JuX3rU96v0b3196sGzXjFq3K0RjU6cnT1Q24qVUKlm7di0TJkwgIiKCsLAwFi5cSK9evYxl1Go133//PZMnT2bQoEEUFxcTHh5+y0u75uDo6MiPP/7I1KlTeeihh8jJyaFJkyb06dOn2iN4jVX+r3GcbHXrT7mXJ0ywYDRV++677yrdv3PnTnbeYu2uuli1apXJ98XFxWzbto1t27bVue6MDbe+GUB7NotLb+yrcxt19dBh00T+XEERz/1xvlZ1+e85bPxaF3+S9HFP8ESXSDr8OccOIPPaFVa99zaf/PATc/0DGPznkii1VdXrHCBr40aybliS6XZWnf5mfr2ezK/XWyii8uYFBDLl2lWmPrSYYJ+KF9wuKdbzvy+OmWy7mBLPRxvHE/RCEO53uxP6biiJMxP5/fff6dChZnMiFQpFpe1fic9k0bjd5bZfTIk33ggohDWoUWJ38xvizTZv3mzy/f3338+JEydMtt18R2NISIhx7trNZs6cycyZM022TZo0yWTdupvvxK1oPbqbH0nm7+9P9J93zNVGr169anRnphBCCCGEJcjEAiGEEEIIKyGJnRBCCCGElZDETgghhBDCSkhiJ4QQQghhJSSxE0IIIYSwEpLYCSGEEEJYCUnshBBCCCGshCR2QgghhBBWQhI7IYQQQggrIYmdEEIIIYSVkMROCCGEEMJKSGInhBBCCGElJLETQgghhLASktgJIYQQQlgJSeyEEEIIIayEqqED+Ls5V6TFUfn3yacvFesASElJsVibGRkZZm+zrK6LWVc5du202eqtiYtZVwEoTjrXIO1XpSyu9Lx8LmVkmexLzs4FSl8PJwoLLR6bOZW9phOLtA0cSeNRdk6uZSbV6Liy8kWpRRScL0B7pW7ntKbt1/YYIRozhcFgMDR0EH8H2dnZuLm5NXQYDUKhUGDpl1l9tNkQ/ShHqQS9vmFjqEwl8TWK82cmSqAR/xQahEKhxGCo+Vm5+Th7B3tOnzqNRqOpdh1JSUm0atWagoL8GrcP4ODgyKlTJ2vU5t9d2XtaVlYWrq6uDR2OuIGM2FnY3r17cXZ2bugwLEqr1WJnZ3fbt9kQ/WiMMVSmsvgae+w1YU19MZfanpObj/P29q5xgqXRaDh16iSpqak1br+2bQrRWMmInYXIpxshhBDWQt7TGq+/z2QvIYQQQggrJ4mdEEIIIYSVkMROCCGEEMJKSGInhBBCCGElJLETQgghhLASktgJIYQQQlgJSeyEEEIIIayEJHZCCCGEEFZCEjshhBBCCCshiZ0QQgghhJWQxE4IIYQQwkpIYieEEEIIYSUksRNCCCGEsBKS2AkhhBBCWAlJ7IQQQgghrIQkdkIIIYQQVkISOyGEEEIIKyGJnRBCCCGElZDETgghhBDCSqgaOgAhhBBCWKeSkhJ0Ol1Dh3Fbs7W1xcbGptrlJbETQgghhFkZDAauXbtGZmZmQ4diFdzd3fH390ehUFRZVhI7IYQQQphVWVLn6+uLo6NjtRISUZ7BYCA/P5/k5GQAAgICqjxGEjshhBBCmE1JSYkxqfPy8mrocG57Dg4OACQnJ+Pr61vlZVm5eUIIIYQQZlM2p87R0bGBI7EeZeeyOvMVJbETQgghhNnJ5Vfzqcm5lMROCCGEEKKGYmJiUCgUje4GEZljJ4QQQgiLuJxZQEZekcXa83BS08TdodrlR48eTWZmJps3b663mAoLC5k8eTJr165Fq9XSv39/Pv/8c/z8/MxSvyR2Fnb48GGcnZ3NWqdWq8XOzq7R1NMQbufYa+J27mdlsVuqX7fz+atMbfvVGM9HfcTUGPvZELy9vdFoNA3W/uXMAu77OAZtsd5ibdqplOx+vVeNkrv69uqrr/Lf//6X9evX4+bmxiuvvMJDDz1EbGysWeqXxM7Cevbsaf5KFYChEdXTAGwUUHKbxl4TSiXoLfc30awqjV2hBEP9d+x2Pn+VqW2/GuPvjUKhwGAwb1D1UeftyMHBnlOnTjdYcpeRV2TRpA5AW6wnI6+oVomdVqslKiqKtWvXkp2dTadOnViwYAF33XWXSbnY2FimTZtGfHw8kZGRLFu2jIiIiArrzMrKYvny5axZs4b77rsPgJUrV9K6dWv2799P165da97Jm0hiZ2GBowNxaGq+Tw45R3NI3phM0AtB2AXW/hOp9oqWS0su8V5vOwa1vL1eFtvOFPP2Hi1fDnegtY/1Thst6+e0aT5oNOqGDqdGkpKKmD07Bbd7nsKheSeTfQVnfyNr35d4DZ6MrVdwvcVQ1s7teP4qU3Zua/q72xh/b8pieqJLJL6u5rmycepqMtuPx5u1zttRcnYuaw4cJjU1tUFH7W4nU6ZMYcOGDURHRxMSEsLcuXPp378/CQkJeHp6GstFRUXx6aef4u/vz5tvvsmQIUOIj4/H1ta2XJ2///47Op2O+++/37itVatWaDQafvnlF0nsbkd2/nZmTey0V7Sl9Qaap95mHgo6BFT/0SWNwcnUEgBa+yhvu9hroqyfGo2alnfcnpeVVG5+2PmHmmzTpV0EwNYruNw+cypr53Y+f5Wp6e9uY/y9KYvJ19WZIA83s9SZnJ1r9jqF9cvLy2Px4sWsWrWKgQMHArB06VJ++OEHli9fTlRUlLHsjBkz6Nu3LwDR0dEEBQWxadMmRowYUa7ea9euoVarcXd3N9nu5+fHtWvXzBJ74/iYJoQQQgjRSCQmJqLT6ejevbtxm62tLZ07d+bkyZMmZbt162b82tPTk7CwsHJlLEkSOyGEEEIIC/D396eoqKjcEinXr1/H39/fLG1IYieEEEIIcYMWLVqgVqtN7lTV6XTExcURHh5uUnb//v3GrzMyMoiPj6d169YV1tuxY0dsbW3ZtWuXcdvp06dJSkoyGfmrC5ljJ4QQQghxAycnJ8aPH09UVBSenp5oNBrmzp1Lfn4+Y8eONSk7a9YsvLy88PPzY/r06Xh7ezNs2LAK63Vzc2Ps2LG89tpreHp64urqyv/93//RrVs3s9w4AZLYCSGEEEIAoNfrUalKU6M5c+ag1+sZNWoUOTk5dOrUiR07duDh4WFyzJw5c5g4cSJnzpwhMjKSLVu2oFbf+s77BQsWoFQqefjhh00WKDYXSeyEEEIIUe88nNTYqZQWX6DYw6n6yxslJycTGlp6d769vT0LFy5k4cKFFZbt1auXcX3EwYMHV7sNe3t7Fi1axKJFi6p9TE1IYieEEEKIetfE3YHdr/dqlI8Uy8jIIDY2lpiYGMaNG2eByOqPJHZCCCGEsIgm7g6N6vFeZcaMGUNcXByTJ09m6NChDR1OnUhiJ4QQQoi/tU2bNjV0CGYjy50IIYQQQlgJSeyEEEIIIayEJHZCCCGEEFZCEjshhBBCCCshiZ0QQgghhJVo1HfFzpw5k82bN3P48OFblunVqxeRkZF88sknFourvigVSl668yUeaP4A3g7epBSk8G3Ct/zr6L9qVZ+jypFX2r9CH00fPO09OZV+ijm/zuGPtD/MHHk19XgV7p8J+z+H7dMaJoa66vUG9Lop9tR4+OyuhomnDkJCXiS0xRSSLq7kzJn3UancaN5sEp6ePbC3D0SnSycl5QcSz/6DkpJcs7TZrU1zJj7TibZN3PBzteeFf//Gxhq8HF/q1YL+bfxp4etMoa6EgxcymPO/U5xNzTNLfHVx8/kE6ND+Kzw8TB8TdOnyGk6ffrv+A3IJgL7vQmhfsHWA9LPw7ctw5ZB56p90FNxDym//dSlse90sTXQe9igtO3fDMzCI4qIirsSf5MevVpFx9bKxjJufPz2fGkuTVuHYqGw5f+R3dq/8F/lZmWaJobru7DuQO/sOwtXHD4C0S0n8suE/nD/8OwA2trb0GjWWsLvvxcbWlvNHDrJr+WKLxymsX41G7EaPHo1Coahw8b6XX34ZhULB6NGjzRVbtWzcuJH33nuvXttIS0tjwIABBAYGYmdnR3BwMK+88grZ2dlmbWdMxBhGhI3gwwMfMnTzUBb8voBnI57liVZP1Kq+d+9+l26B3Xjzpzd56LuH+PnKzyzttxRfR1+zxl0tgR2g47Nw7Zjl2za35BPwccu//q3o39AR1ZiLS1uaBI4kJ+ekcZudnR92dr4kJMzmwK8DOXFyCl5e9xLeeo7Z2nW0V3PyajbvfHu8Vsd3aebJ6v0XGL4ollHLD6CyUfLvsZ1xsLUxW4y1UdH5LHP58lr2/dTF+C8h4aP6D8jeHcbugBIdfPUwLOoC378FBZnma2NJb9Pfg3//ufbXic1mayKodQSHd/yXNW+9zjcfvI3SRsUj099DZWcHgMrOjkfefA8wsH7Wm6x9JwoblYphU94BhcJscVRHTloa+9ZE8+W0SXz15iSSjh9hWNRbeAVpAOj19PM079iZLQvmsG7mGzh7ePHg5DctGqMwr5iYGBQKBZmZmQ0diokaj9gFBwezdu1aFixYgIND6SKDhYWFrFmzBo1GY/YAq+Lp6VnvbSiVSoYOHcr777+Pj48PCQkJvPzyy6Snp7NmzRqztRPpE8mei3vYd3kfAFfyrjCw2UDaeretcV12NnbcH3I/E3ZP4PfrpZ8YFx9ZTK/gXjwW9hj/PPRPs8VdJbUTPLwUtkyAe83zSb5B6YshN7mho6g1GxtHItos4OSpN2nW9GXj9ry8eI4d/+v7goIkEhPn06bNfBQKGwyGkjq3vev3UxwoDKj18c+sjDP5/vX1Rzj4dl/aBrnx67n0uoZXK7c6n2VK9AUUFaVaNqgekyDrcukIXZnMC+ZtIz/tpjZfLR0VPP+T2ZrYOHuGyffbP1/AS8vW4Nc8lMsn/6BJWDiuvr6sfmMCRQUFAPxv0QJeWbEWTUQ7ko4dMVssVTl78FeT72PXrebOfoMIaBlGTloqbe/ry38XfszFP44CsGPxJzy74AsCWoZx9cxpi8XZ4DIvln/t1CdHL3APrnbx0aNHk5mZyebNm+stpCVLlrBmzRoOHjxITk4OGRkZuLu7m63+Gid2HTp0IDExkY0bN/Lkk08CpaNmGo2GZs2amZTdvn0777//PsePH8fGxoZu3brx6aef0qJFC2OZS5cuERUVxY4dO9BqtbRu3ZpFixbRpUsXY5nVq1fz9ttvk5GRwcCBA1m6dCkuLi5A+UuxTZs25YUXXiAhIYH169fj4eHBW2+9xQsvvGCs7+LFi0yePJnvv/8epVLJPffcw6effkrTpk0r7LOHhwfjx483fh8SEsJLL73EvHnzanr6KnU45TCP3PEIIa4hXMi+wB0ed9DBtwPz4mrejo3CBpVSRVGJ6aNbCosLae/b3lwhV8+gjyF+B5yNsY7EzrMFTD4FxVq4+CvseheyLjV0VNUWdse7pKbuISPj5woTkRupVC4UF+eaJamrDy72pX/CMvMt94iim1V1Pv39HsTfbyhFRamkpu7i3PnP0OsL6zmogZCwCx6NhqbdIfsqxC2Dg9H1056NLbR7DH6pn2dflrFzdAKgMLd0aoCNyhYMUKLTGcuU6IowGAw0CWtj0cTuRgqFkju69cDWzp4r8afwax6KjcqWpGOHjWXSr1wiOyWZgJat/j6JXeZF+Kxj6d9OS1HZwSu/1yi5q2/5+fkMGDCAAQMGMG2a+acl1ermiTFjxrBy5Urj9ytWrODZZ58tVy4vL4/XXnuN3377jV27dqFUKhk+fDh6fekDgHNzc+nZsyeXL1/mu+++48iRI0yZMsW4HyAxMZHNmzezdetWtm7dyt69e5kzp/JLQ/Pnz6dTp04cOnSIl156ifHjx3P6dOkvjk6no3///ri4uLBv3z5iY2NxdnZmwIABFBVV783hypUrbNy4kZ49e1arfHUtP7ac7ee2892w7zg46iDrh6xn9YnV/Pfcf2tcV35xPoeTD/PinS/i4+CDUqFkcPPB3OlzJ94O3maNu1IRD0PAnaXJjzW49Btsfgm+fBi2vgYeIfDs/0Dt3NCRVYuf72BcXNqQeLbqDwu2th40bfYKl6+ss0BkNadQwDuDw4k7n078dfPMAaypqs7ntetb+OPEZA4eepLzFxbj7z+MNuH/qP/APJrCXWMhPRFWPwS/LYeBH8GdI+unvVaDwd4NDn9VP/UDKBT0euZ5Lp/6g7SLpaOPV8+cQqct5J4nn0WltkNlZ0fPUWNR2tjg5OFRf7HcgndwCP8XvZ5JX23i/ude4ruPPyD98kWc3D0o1unQ5pvOBc3LysTJ3fJxNpj8NMsmdVDaXi1HCLVaLRMmTMDX1xd7e3t69OhBXFxcuXKxsbG0a9cOe3t7unbtyvHjlU81mTRpEm+88QZdu3attFxt1ermiaeeeopp06Zx4ULpL1dsbCxr164lJibGpNzDDz9s8v2KFSvw8fHhxIkTREREsGbNGlJSUoiLizNeUg0NDTU5Rq/Xs2rVKuMI3ahRo9i1axcffPDBLeMbNGgQL730EgBTp05lwYIF7Nmzh7CwMNatW4der2fZsmUo/pyDsXLlStzd3YmJiaFfv363rHfkyJF8++23FBQUMGTIEJYtW3bLslqtFq32rxdwdebj9W/anweaP8DUH6eSmJlImGcYU++aSkpBCt8lflfl8Teb9tM03rv7PXaP2E2xvpiT6Sf537n/Ee4VXuO6asW1CQyYA6uHWf6Xub4k7Pzr6+t/wOXfYNIxaDMcDq1uuLiqwc4ugDvueJtDh55Gr6/8Q4yNjTN3tltGXl4C5859aqEIa+a9oRGE+bvwyOJfGqT96pzPK1fWGr/Oy4unqCiFDu2/xMFBQ0FBUv0Fp1CW3iSxa1bp99eOgm9r6DQGjvzH/O21HwVnfoCca+av+099xozHOziEtTOmGLcV5GSzZcEc7h/7Eh0GDMFgMHAqdi/XzyZg0BvqLZZbSb9ymdVTJqB2dOSOrj0Y8PKrrJv5hsXjEOYxZcoUNmzYQHR0NCEhIcydO5f+/fuTkJBgMg0sKiqKTz/9FH9/f958802GDBlCfHw8tra2DRJ3rRI7Hx8fHnjgAVatWoXBYOCBBx7A27v8KNCZM2d45513OHDgAKmpqcaRuKSkJCIiIjh8+DDt27evdJ5c06ZNjUkdQEBAAMnJlc9vateunfFrhUKBv7+/8ZgjR46QkJBgUieUzhNMTEystN4FCxYwY8YM4uPjmTZtGq+99hqff/55hWVnz57Nu+/WbJRqcqfJpaN257cDcCbzDIHOgTzX9rlaJXaXci7x7I5ncVA54GTrRGpBKvPuncelXAtdNgyMBGdfePHHv7YpVRDSHTq/AO/5gEF/y8NvC4VZkJYIns0bOpIqubhEoFZ7c9ddf72WlEoV7u6dCWoyij0xrQE9NjZOREaupKQkj2PHxmEwFDdc0Lfw7oNtuK+VLyP+9QvXsuv5suYtVPd83igr6zAADg4h9ZvY5VyDlJsu76XEQ+sHzd+WWzA07wXrnjJ/3X+679lxtOhwF2tnvkFuuunoy4Wjh1g+8XkcXFzRl5Sgzc9j3L9Wk5Vcf0nmrehLism8fhWA5HOJ+LdoSYdBD3L6532obG2xc3QyGbVzcnMnLzPD4nGKquXl5bF48WJWrVrFwIEDAVi6dCk//PADy5cvJyoqylh2xowZ9O3bF4Do6GiCgoLYtGkTI0aMaJDYa73cyZgxY3jllVcAWLSo4nkVQ4YMISQkhKVLlxIYGIheryciIsJ4ybPs5ovK3JzxKhQKk0u1NT0mNzeXjh078tVX5S8Z+Pj4VFqvv78//v7+tGrVCk9PT+655x7efvttAgLKTwYvS/zKZGdnExxc+TV+ext79De9EZToS1BQt7u7CooLKCguwFXtyt1N7mbBbwvqVF+1nd0Ln9801Dz089LlQWI/uf2TOii9McSzGRxdW3XZBpaR8TP7Dww02Rbe+iPy8hO5cGEJpUmdM+0jV6LXF3Hk6AtVjuw1hHcfbEP/Nv48vuQXLmUUNFgc1TmfN3NxKR0tL9LW8803Fw+Al+nVD7xaQNZF87fV/knIS4EzO8xfN6VJXWjnbnz97jSyU67fslxBTulVkeA27XB0dSPxtwP1Ek9NKBQKbFS2XD+bQEmxDk3EnZz59WcAPAKa4Orjy9Uzpxo4SlGRxMREdDod3bt3N26ztbWlc+fOnDxpevd7t27djF97enoSFhZWrowl1TqxK5uTplAo6N+//HIPaWlpnD59mqVLl3LPPfcA8NNPpndLtWvXjmXLlpGenm6Ru1uh9OaPdevW4evri6ura63rKUsUb7zceiM7Ozvs/rwlv7r2XtrLC21f4GruVRIzE2nl1Yqn2zzN5jObaxXj3YF3o0DB+ezzaFw0vNbpNc5lnWNzQu3qq7GiXEi+6cWty4OC9PLbbxf93ofT/yt9g3Txh15vgr4Ejn3T0JFVqaQkj7y8+Ju25aPTZZKXF/9nUrcKpY0Df5yYjErlDJTOHSwqSqeiRKWmnOzVhAf89XsX7OlIRLNAzgYHo6vkuDLvDY1gaGQgz//7N/K0Jfg4l/6OZRfq0BZb9oNCVefTwUGDn9+DpKXFoNNl4OzcipYtp5ORcYDcvHqeLP/L5zD2e7hnMvyxCZp0gI6jYctE87ajUEDkk6WXd/Xmv8Gmz9jxtOrek2/nvU9RQT6Obu4AFOXnU6wr/dDRptf9pF++SH52FoEtW9F79Av8vu1bk7XuLKHHyGc4d/g3clJTUNs70KpHL4LD27Lhw3coKsjn2O4f6PX0cxTm5aDNz6fPs+O4cvrk3+fGCWExtU7sbGxsjBmpjU35NaQ8PDzw8vJiyZIlBAQEkJSUxBtvmM41GDlyJB9++CHDhg1j9uzZBAQEcOjQIQIDA00yYHN68sknmTdvHkOHDmXWrFkEBQVx4cIFNm7cyJQpUwgKCip3zLZt27h+/Tp33XUXzs7O/PHHH0RFRdG9e/db3klbGx8e+JBX2r/CW13fwtPek5SCFL6J/4bFRxbXqj4XWxcmdpyIn6MfWdosdibtZOHBhRQ3wktrtw3XQHhkOTh4Qn4qJO2HZfdb9vb9euLi0gY3t9I7pu/utsdkX+zP91JYWPc3ysjQYL6deI/x+7cHh/P24HBWdfBkWkxWlceP6la6IO66F03/Pry+/gjf/N647kzW63V4etyNJng0SqUjWu1VUpJ3cO58/d45CsCVg7DuSegzA3pOgYwLpYuCH1tv3naa9wZ3Tb3NL43s9wAAj800vWFu++cL+GPvLgA8A5pwz8hnsHd2Jis5mQObvub3/26ul3gq4+jqxsCXXsPJw5Oi/DxSks6z4cN3uPDnnbAx/14KBj1DXnsTlcqW80cPsnNZxVN5RMNr0aIFarWa2NhYQkJK/+7odDri4uKYNGmSSdn9+/cbl3vLyMggPj6e1q1bWzpkozo9eaKyES+lUsnatWuZMGECERERhIWFsXDhQnr16mUso1ar+f7775k8eTKDBg2iuLiY8PDwW17aNQdHR0d+/PFHpk6dykMPPUROTg5NmjShT58+t+yPg4MDS5cu5dVXX0Wr1RIcHMxDDz1ULlGtq/zifObGzWVu3Fyz1Lfjwg52XKifyyO1tmpwQ0dQN9+MaegIzOrgoSeNX2dmHmDX7haVlK672OOJNH3D9C7v3D/2kLZ1Pv7PfFLl8Tcf29jceD612qscPFS7xcXNIn5H6b/6lLgbZrrVW/XzH6v678W+/0Sz7z/1tIxLDXz/r4WV7i/R6di14gt2rfjCQhGJunBycmL8+PFERUXh6emJRqNh7ty55OfnM3bsWJOys2bNwsvLCz8/P6ZPn463tzfDhg27Zd3Xrl3j2rVrJCQkAHDs2DFcXFzQaDRmuXpZo8Ru1apVle6/eUG/+++/nxMnTphsMxhM71QKCQnhm28qvow1c+ZMZs6cabJt0qRJJtnyzXfinj9/vlw9Nz+SzN/fn+jo6v8h6N27Nz///HO1ywshhBDi9qPX61GpSlOjOXPmoNfrGTVqFDk5OXTq1IkdO3bgcdNSOnPmzGHixImcOXOGyMhItmzZglqtvmUbX3zxhcnNlffeey9QukKHOZ7e1aifFSuEEEIIK+HoVbpgsKUXKHb0qnbx5ORk47Jr9vb2LFy4kIULKx6N7dWrl3GwavDg6l+NqmjQypwksRNCCCFE/XMPLn0KRCN8pFhGRgaxsbHExMQwbtw4CwRWfySxE0IIIYRluAc3qsd7lRkzZgxxcXFMnjyZoUOHNnQ4dSKJnRBCCCH+1jZt2tTQIZhNrZ4VK4QQQgghGh9J7IQQQgghrIQkdkIIIYQQVkISOyGEEEIIKyGJnRBCCCGElZDETgghhBDCSshyJ0IIIYSwiKu5V8nQZlisPQ87DwKcA+ql7piYGHr37k1GRgbu7u710kZtSGInhBBCiHp3NfcqgzcPpqikyGJtqm3UbB22tdrJ3ejRo8nMzGTz5s31Ek96ejozZszg+++/JykpCR8fH4YNG8Z7772Hm5ubWdqQxE4IIYQQ9S5Dm2HRpA6gqKSIDG1GvY3a1dSVK1e4cuUKH3/8MeHh4Vy4cIFx48Zx5coVvvnmG7O0IXPshBBCCCFuotVqmTBhAr6+vtjb29OjRw/i4uLKlYuNjaVdu3bY29vTtWtXjh8/fss6IyIi2LBhA0OGDKFFixbcd999fPDBB2zZsoXi4mKzxC2JnRBCCCHETaZMmcKGDRuIjo7m4MGDhIaG0r9/f9LT003KRUVFMX/+fOLi4vDx8WHIkCHodLpqt5OVlYWrqysqlXkuosqlWAvTXtOitDdfPl2UWjqsrb2irVM9ZcefyzBw8GpJneOypHMZBgBOpugbOJL6VdbPpCTLXsowh7KYi7Ouo72WYLKvOOs6ALq0i/UaQ1k7t+P5q0xZf2r6u9sYf2/KYkrOzjVbnel5+Wav83b0d+9/TeXl5bF48WJWrVrFwIEDAVi6dCk//PADy5cvJyoqylh2xowZ9O3bF4Do6GiCgoLYtGkTI0aMqLKd1NRU3nvvPV544QWzxS6JnYVdWXXF/JUq4NKSS2ap5+09Wt7eU7cksSHYKOCpTQUNHUa9Uyph9uyUhg6jVpRKyNr3JVn7viy/U6Ekbet8i8Rwu56/yiiVtfvdbYy/NwqFgjUHDjf6Om9HDg72eHt7N3QYt4XExER0Oh3du3c3brO1taVz586cPHnSpGy3bt2MX3t6ehIWFlauTEWys7N54IEHCA8PZ+bMmWaLXRI7C9u7dy/Ozs5mrVOr1WJnZ9do6mkIt3PsNXE797Oy2C3Vr9v5/FWmtv1qjOejPmJqjP1sCN7e3mg0moYOQwA5OTkMGDAAFxcXNm3ahK2trdnqlsTOwiIjI3F1dW3oMIQQQghxCy1atECtVhMbG0tISAgAOp2OuLg4Jk2aZFJ2//79xoQ5IyOD+Ph4Wrdufcu6s7Oz6d+/P3Z2dnz33XfY29ubNXZJ7IQQQgghbuDk5MT48eOJiorC09MTjUbD3Llzyc/PZ+zYsSZlZ82ahZeXF35+fkyfPh1vb2+GDRtWYb3Z2dn069eP/Px8vvzyS7Kzs8nOzgbAx8cHGxubOscuiZ0QQgghBKDX6413p86ZMwe9Xs+oUaPIycmhU6dO7NixAw8PD5Nj5syZw8SJEzlz5gyRkZFs2bIFtVpdYf0HDx7kwIEDAISGhprsO3fuHE2bNq1zHySxE0IIIUS987DzQG2jtviTJzzsPKou+Kfk5GRjwmVvb8/ChQtZuHBhhWV79eqFwVB6J/fgwYOrVf+Nx9QXSeyEEEIIUe8CnAPYOmxro3xWbEZGBrGxscTExDBu3DgLRFZ/JLETQgghhEUEOAc0msd73WjMmDHExcUxefJkhg4d2tDh1IkkdkIIIYT4W9u0aVNDh2A28kgxIYQQQggrIYmdEEIIIYSVkMROCCGEEMJKSGInhBBCCGElJLETQgghhLASktgJIYQQQlgJWe5ECCGEEBahu3KF4gzLLVCs8vDANjCwXuqOiYmhd+/eZGRk4O7uXi9t1IYkdkIIIYSod7orV0gcMBBDkeUeKaZQq2mx/X/VTu5Gjx5NZmYmmzdvrreYXnzxRXbu3MmVK1dwdnbm7rvv5qOPPqJVq1ZmqV8uxQohhBCi3hVnZFg0qQMwFBVZdISwOjp27MjKlSs5efIkO3bswGAw0K9fP0pKSsxSvyR2QgghhBA30Wq1TJgwAV9fX+zt7enRowdxcXHlysXGxtKuXTvs7e3p2rUrx48fr7TeF154gXvvvZemTZvSoUMH3n//fS5evMj58+fNErckdkIIIYQQN5kyZQobNmwgOjqagwcPEhoaSv/+/UlPTzcpFxUVxfz584mLi8PHx4chQ4ag0+mq1UZeXh4rV66kWbNmBAcHmyVuSeyEEEIIIW6Ql5fH4sWLmTdvHgMHDiQ8PJylS5fi4ODA8uXLTcrOmDGDvn370rZtW6Kjo7l+/XqVz579/PPPcXZ2xtnZmf/973/88MMPqNVqs8QuiZ0QQgghxA0SExPR6XR0797duM3W1pbOnTtz8uRJk7LdunUzfu3p6UlYWFi5Mjd78sknOXToEHv37uWOO+5gxIgRFBYWmiV2uStWCCGEEMKC3NzccHNzo2XLlnTt2hUPDw82bdrEyJEj61y3jNgJIYQQQtygRYsWqNVqYmNjjdt0Oh1xcXGEh4eblN2/f7/x64yMDOLj42ndunW12zIYDBgMBrRabd0DR0bshBBCCCFMODk5MX78eKKiovD09ESj0TB37lzy8/MZO3asSdlZs2bh5eWFn58f06dPx9vbm2HDhlVY79mzZ1m3bh39+vXDx8eHS5cuMWfOHBwcHBg0aJBZYpfETgghhBAC0Ov1qFSlqdGcOXPQ6/WMGjWKnJwcOnXqxI4dO/Dw8DA5Zs6cOUycOJEzZ84QGRnJli1bbnkjhL29Pfv27eOTTz4hIyMDPz8/7r33Xn7++Wd8fX3N0gdJ7IQQQghR71QeHijUaos/eUJ1UyJWmeTkZEJDQ4HSJGzhwoUsXLiwwrK9evXCYDAAMHjw4GrVHxgYyLZt26odT21IYieEEEKIemcbGEiL7f9rlM+KzcjIIDY2lpiYGMaNG2eByOqPJHZCCCGEsAjbwMBqP7fVksaMGUNcXByTJ09m6NChDR1OnUhiJ4QQQoi/taoWFL6dSGJnYYcPH8bZ2bmhw6gxrVaLnZ1dQ4fRqFR2Tupyvqz1XJurX3J+GofbLd7q8vb2RqPRVKtsUlISqamp9RxR9dUkdmG9JLGzsJ49ezZ0CLWjVIJe39BRNC6VnBMlUNuzVZdjGzVzvYas9bV4u/Xrdou3muwdHDl96mSVCVJSUhKtWrWmoCDfQpFVzcHBkVPViF1YN0nsLMxl8tvYtqz+woWNgfbXn8hb8Tmub36AStOsocNpFIqTzpH94XQmeHtzr5PpCOyPebksTE3lo4AAWqhrNqKRWKRl6tWruN3zFA7NO5kz5AZVcPY3svZ9WefXkLW+Fm+3fpW9/q3tdapLu0ja1vmkpqZWmRylpqZSUJDPM/dNw9+94ROpa5lJRO+eXa3YhXWTxM7CVEEh2N5xeyV2xUnnAFBpmt12sde3IJUt4fb2JtvO/rl6eAu1Xbl91aVy88POP7TO8TUWurSLQN1fQ9b6Wrxd+2Vtr9Pa8HfXEOxzR0OHIYSRPFJMCCGEEMJKSGInhBBCCGEl5FKsEEIIISwiJ72Qwlydxdqzd7bFxbN2U2KqEhMTQ+/evcnIyMDd3b1e2qgNSeyEEEIIUe9y0gv56p39lBRb7m5qG5WSJ2d1rXZyN3r0aDIzM9m8eXP9BgYYDAYGDRrE9u3b2bRpE8OGDTNLvXIpVgghhBD1rjBXZ9GkDqCkWG/REcKa+OSTT1AoFGavVxI7IYQQQoibaLVaJkyYgK+vL/b29vTo0YO4uLhy5WJjY2nXrh329vZ07dqV48ePV1n34cOHmT9/PitWrDB73JLYCSGEEELcZMqUKWzYsIHo6GgOHjxIaGgo/fv3Jz093aRcVFQU8+fPJy4uDh8fH4YMGYJOd+tRwvz8fJ544gkWLVqEv7+/2eOWxE4IIYQQ4gZ5eXksXryYefPmMXDgQMLDw1m6dCkODg4sX77cpOyMGTPo27cvbdu2JTo6muvXr1f67NlXX32Vu+++m6FDh9ZL7HLzhBBCCCHEDRITE9HpdHTv3t24zdbWls6dO3Py5EmTst26dTN+7enpSVhYWLkyZb777jt2797NoUOH6idwZMROCCGEEMIidu/eTWJiIu7u7qhUKlSq0vG1hx9+mF69epmlDUnshBBCCCFu0KJFC9RqNbGxscZtOp2OuLg4wsPDTcru37/f+HVGRgbx8fG0bl3xowHfeOMNjh49yuHDh43/ABYsWMDKlSvNErtcihVCCCGEuIGTkxPjx48nKioKT09PNBoNc+fOJT8/n7Fjx5qUnTVrFl5eXvj5+TF9+nS8vb1vuSadv79/hTdMaDQamjVrZpbYJbETQgghhAD0er3x8uicOXPQ6/WMGjWKnJwcOnXqxI4dO/Dw8DA5Zs6cOUycOJEzZ84QGRnJli1bUKvVDRE+IImdEEIIISzA3tkWG5XS4k+esHe2rXb55ORkQkNDAbC3t2fhwoUsXLiwwrK9evXCYDAAMHjw4FrHWFaHuTTqxG7mzJls3rzZeA26Ir169SIyMpJPPvnEYnE1Fq9ofHmrRSBLLqbwTsJl4/aOro5Max5AB1dHSgxwPLeAkUcSKdSb98VjKTf3M9heTVy38ArLPn/8HFtSsuoljq5uTryk8aWdiyP+vSMZ9r91cODXCstu3ryZoUOHUpKTg42LCxdffoXcXbuM+wNmf4j78OEmx+Tu28eJUU/XS+w3G9U1hBd7NsfH2Y6TV7OZ8d0fHLlUP+etMhW9hkPs1cwIDaSLmzNqpYI96dm8GX+ZVF1xvcTwelN/Xm9memnkTF4h9/x6CgA7pYKZLQIZ6ueBnULBnvQc3oi/VG/x1FRV8T8V4MVDfh60dXHARWXDHfuOkV1c0hCh1shTXTQ82TWEIA8HAM5cz2XhrjPExKc0cGS106F/CM3b++Dh70hxkZ5rZ7P4ZVMimdfzKyw/+JU7CYnwYtvio5w7kmrhaOuHi6c9T87q2iifFZuRkUFsbCwxMTGMGzfOApHVnxoldqNHjyY6OpoXX3yRL774wmTfyy+/zOeff84zzzzDqlWrzBljpTZu3IitbfWz8do4cuQIc+bM4aeffiI1NZWmTZsybtw4Jk6cWK/tVibSxYGnA734I7fAZHtHV0f+c2cLFl64zvT4yxQbDLRxduA2zekq7OflwiLaxpqu7D0q0IuXgn3ZlZ5Tb7E42ij5I7eA/1xNZ2XbW8+FaDlwABEREehyc8nd8T0ejzxcYbncH3/kypvTjd8biorMHnNFBrcL4K3BrXlr03EOXcxkTPdm/HtsF+77OIa0PMvEABX/bB2VStZFtuCP3AIePpwAwNRmAaxu14xBv5+pt1hO5Rbw6JFE4/clN3yCnhXahD5erjx//Dw5xSV8eEcQK9o25cGDCfUWT01VFr+DjZLd6dnsTs/mrRaBDRFerVzNLuSj7ac4n5qHQqHg4Q5BLHm6Ew8s3MeZ5NyGDq/GAu9w5/jeSySfz0GhVNB1WHMenBDJmnf3U1xkOoJ1Z59g4Db9o10FF0/7aj+31ZLGjBlDXFwckydPrrf15SylxiN2wcHBrF27lgULFuDgUPpJqrCwkDVr1qDRaMweYFU8PT3rvY3ff/8dX19fvvzyS4KDg/n555954YUXsLGx4ZVXXqn39m/maKNkUXgIk09f5NUQ00/qs0KbsOxSCp8lJRu3JRZoLR2iWdyqn3ogpch0tGSgtxvfJWeSX1J/Q/y703PYXUXiqPL1pc/779O1b19+3bEDbXz8LcsaioooSbX8J/HnejRj7a8XWf/7JQCmbz7Gfa18GdEpmMV7E6s42jxu9bO9y82JYHs198edJvfPn+WEkxc4fU9beng48309xVNsKP+aAnCxUTIywJOXTlwgNrM0mZh0KomfurSmg6sjB7MrHm2xtFvFD7D0UukI193uzpYMqc52nUw2+f7j70/zVFcN7TUet2Vit/WfR0y+3xV9krEf34OPxpWrCZnG7d5BzkTeH8z62b/x7NweFo7y76uyBYVvNzVe7qRDhw4EBwezceNG47aNGzei0Who3769Sdnt27fTo0cP3N3d8fLyYvDgwSQmmr5xXLp0iZEjR+Lp6YmTkxOdOnXiwIEDJmVWr15N06ZNcXNz4/HHHycn56831169ejFp0iTj902bNuXDDz9kzJgxuLi4oNFoWLJkiUl9Fy9eZMSIEbi7u+Pp6cnQoUM5f/78Lfs8ZswYPv30U3r27Enz5s156qmnePbZZ03OgSXNaRnEzrRs9mWY/nHztlXR0c2JtKJitnRoybHubdjUPpTObk4NEmdd3aqfN2vn7EBbF0fWXE2zUGS3oFAQOPcjfl28mBMnTlRZ3LFzZ1rG/kTz/23Df8YMbNzd6z1EWxsFEU3ciE34K6E0GCA2IZUOIfXffplb/WzVSgUGAxTdMMSs1RvQG6CLW/0lJs0d1Ry+uw0HurZmUWsNTexKrwK0c3FErVTy4w1xJuRruVRYRCfXxvN7dav4rYVSAUPaBeCgtuFgUkZDh2MWdg6l4yra/L8uS6pslfQd24Yf18aTn2250XNhXWq1jt2YMWNM1ltZsWIFzz77bLlyeXl5vPbaa/z222/s2rULpVLJ8OHD0etLP4nn5ubSs2dPLl++zHfffceRI0eYMmWKcT+Urv68efNmtm7dytatW9m7dy9z5sypNL758+fTqVMnDh06xEsvvcT48eM5ffo0ULoOTf/+/XFxcWHfvn3Exsbi7OzMgAEDKKrBpbCsrCyLjBbebKivO21dHPjw7NVy+zQOpXfhTG7mz1dX0hh55CxHc/JZH9mCZg4Nd4dObVTWz5s9EehFfF4hvzXw6InX889hKCnh4LLlVZbN2/cTV6a+QdKzz5L88Xwc7+pE8JJ/gbJ+l5b0cFSjslGSmms6ipuSq8XH2a5e2y5T2c/2YHYe+Xo9b7UIxEGpwFGpZEZoICqlAl91/UwJPpidx8STSYw8ksjU+EtoHOz4tkNLnGyU+KpVaPX6cnPSUop09RZPTVUW/+0uzM+FP97tT/z7A/lgeFteXP07CbfhaF05CujxaEuuJGSSfiXPuLnHoy25lphlNXPqRMOo1V+mp556imnTpnHhwgUAYmNjWbt2LTExMSblHn7YdG7RihUr8PHx4cSJE0RERLBmzRpSUlKIi4szJklld6OU0ev1rFq1ChcXFwBGjRrFrl27+OCDD24Z36BBg3jppZcAmDp1KgsWLGDPnj2EhYWxbt069Ho9y5YtQ6FQALBy5Urc3d2JiYmhX79+Vfb/559/Zt26dfz3v/+9ZRmtVotW+9ebZ3Z2dpX1ViXQzpb3WzZhxOFEtBVMmiv7M776Shprr5U+pPh4QgH3eLgwMsCrWklSY1BVP29kr1Qw3NeDBReuWSi6W8TRJhzPUaM493DF8+lulr1tm/FrbfwZtKdPE7rzB3y6doVzZ+srzAYX6ORY6c82TVfC88fP81FYEM8FeaM3wKbkDI7k5NfbjKMbL6+fzCvkYHY+v3UL50Ffdwrr8dK+uVQW/3+upldyZON3NjWXQQv34WKvYlBEAPMfvZPHluy/7ZO7no/fgWcTJzbOO2jc1rSdN01aefD1B3ENGJmwBrVK7Hx8fHjggQdYtWoVBoOBBx54AG9v73Llzpw5wzvvvMOBAwdITU01jsQlJSURERHB4cOHad++faUjX02bNjUmdQABAQEkJyffsjxAu3btjF8rFAr8/f2Nxxw5coSEhASTOqF0nuDNl4krcvz4cYYOHcqMGTMqTQJnz57Nu+++W2V9NdHOxREftS0/dAozblMpFXR1d2JME2+6Hyh9Nl18XqHJcWfyCm+rSzNV9VOz9whlb7eDfdxxsFGw/lrDvoE5dOyEjZcXobt3Mxl4FVCpVDhOnVKt43WXLlGcno5z05B6jTMjv4jiEj3eN43O+TjbkZJb/3MxI308qvzZ7s3Ioev+k3ja2lBsgOziEo7e3YZvLTRXNLu4hLP5Wpo52LE3PQc7pRJXlY3JqJ2P2pbkW8xpa2g3xn+705UYuJBWOhJ//HI27YLcGdO9KW9uOl7FkY3XPY/fQUhbbzbNP0he5l+v6aAwD9y8HXjuH/eYlB/wYluuJmSy+R/192xRYV1qfS1hzJgxxhsHFi1aVGGZIUOGEBISwtKlSwkMDESv1xMREWG85Fl280Vlbr7jVaFQmFyqrekxubm5dOzYka+++qrccT4+PpXWe+LECfr06cMLL7zAW2+9VWnZadOm8dprrxm/z87OJjg4uNJjqrIvI4defy5hUOaTVhrO5BeyKCmZC4VFXNUW0cLR9A96c0e7Kif9NyZV9fPGn/4TAV58n5pNmq5hl2/I/u478n/5BYC9OTnMT00hbudO8r7bgvcLz1d5vMrPDxt3dwqT63cpB12JgeOXs7g71JvvT1wHQKGAu0O9+PfPF+q1bYAfL1+v9s82/c+faXd3Z7zVKnak1n3UuzocbZSEOKi5fk3H0Zx8ivR67vFw5r9/LqPTwsGOIHs1v2XnVVFTw7gxfmujVIJadfteYr7n8TtoHunD5n8cJCfN9AP4wR0XOBF7xWTbyHe6ELv+DOeOyqVZUX21TuzK5qQpFAr69+9fbn9aWhqnT59m6dKl3HNP6SeQn376yaRMu3btWLZsGenp6Rabr9ahQwfWrVuHr68vrq6u1T7ujz/+4L777uOZZ56p9DJwGTs7O+zszPuJOa9Ez6mbRuPyS/Rk6EqM2z9PSiGqmT8ncgs4nlvACH9PQh3tee74ebPGUp+q00+Apg5quro78eRRy1y6dLRRmoyCNGvWDN/cPFQlJRRfvUpJZiYAqVlZnM/JLs2Y/pwzpw4Kwq5VK0qysijJysLn5ZfI/v4HSlJTsA3W4Bv1OkVJSVz/8cd678eyn84x/9E7OXYpk8MXsxjboymOahXrf79Y723n6oqr/Nk+7u9JfH4haUXFdHJz4r2WTVhyMaXe7u6e0SKQ79OyuFSow0+tIqpZAHoDbE7OIKdEz3+upvNuaBMydSXkFJfwwR1BxGXlNZo7YiuLH8BHrcJXbUvTP+fZtnayJ7dEz+XCIjIb8Xp2U/qHEROfwpXMApzUKoZGBtK1mRdPr6h47cjG7t6Rd3DHXX5sW3wMXWEJjq6lPw9tQTElOj352UUV3jCRk15YLgkUojK1TuxsbGw4efKk8eubeXh44OXlxZIlSwgICCApKYk33njDpMzIkSP58MMPGTZsGLNnzyYgIIBDhw4RGBhIt27dahtapZ588knmzZvH0KFDmTVrFkFBQVy4cIGNGzcyZcoUgoKCyh1z/Phx7rvvPvr3789rr73GtWvXjP2uapTP0pZeSsFOqeDd0CZ42NrwR24hjx1J5EKh9d1hNTLAiytaHTEWGo2MdHFkY/u/5oAuWLAAgMxNm7g67U2Tsp06dcLBzw+H50qfKeg37Q1j2Wsz38UuLIzgYcOwcXFBl5JCXmwsKZ8uRG+Btey2Hr2Kp5OaV/vegY+LHSevZPPMil9JzW0cr5EWjna82TwAd1sbLhYW8emF6/zrYv2NZAbY2bI4vCketjakFRXza1Yeg36PN44Cv5NwGb3BwLKIptgp/1qguLGoKv5nAr1NFjD+tkNLACaeTGJdA09hqIyXsx3/GHEnPi525BQWc+pqDk+v+JWfEm7P0au2PUvfW4ZP7mCyfVf0CU790rBzhC0pOzWZAjPMOa8uB1dXXL1966XumJgYevfuTUZGBu4WWNWguup0W1dlI15KpZK1a9cyYcIEIiIiCAsLY+HChfTq1ctYRq1W8/333zN58mQGDRpEcXEx4eHht7y0aw6Ojo78+OOPTJ06lYceeoicnByaNGlCnz59btmfb775hpSUFL788ku+/PJL4/aQkJBKl0mxhIcOl18k9bOkZJN17KxBRf2cffYqsy14Q8jPmbn47zkMgC7+JOnjnmCufwCD3dzKld27dy8bmjYj3L7ihTgvPlf15dn69O9fLvDvX+r/0mt13Pyz/eDsVT6w4M913InKz4NWb2DamctMO3O50nINpar4Pz5/jY/P336Jw9QNRxs6BLNaNG63RY5pzLJTk1kx6UVKdJabJmBja8uYT/5V7eRu9OjRZGZmsnnz5nqLqVevXuzdu9dkW0UPfqitGiV2VT1R4uYTcf/995dbz+vmZ6KFhITwzTffVFjfzJkzmTlzpsm2SZMmmaxbd/OduBUlWjc/kszf35/o6OgK26xuHEIIIYSovoLsbIsmdQAlOh0F2dn1NmpXW88//zyzZs0yfu/o6Gi2um/fWahCCCGEEPVEq9UyYcIEfH19sbe3p0ePHsTFlV+OJjY2lnbt2mFvb0/Xrl05frzqu7YdHR3x9/c3/qvJnP+qSGInhBBCCHGTKVOmsGHDBqKjozl48CChoaH079+f9HTTualRUVHMnz+fuLg4fHx8GDJkCLoqRia/+uorvL29iYiIYNq0aeTnm+9mLEnshBBCCCFukJeXx+LFi5k3bx4DBw4kPDycpUuX4uDgwPLlpk8XmjFjBn379qVt27ZER0dz/fr1Sp89+8QTT/Dll1+yZ88epk2bxurVq3nqqafMFnvjeCaOEEIIIUQjkZiYiE6no3v37sZttra2dO7c2bgiSJkbV/Hw9PQkLCysXJkbvfDCC8av27ZtS0BAAH369CExMZEWLVrUOXYZsRNCCCGEaCBdunQBICGh/OoPtSGJnRBCCCHEDVq0aIFarSY2Nta4TafTERcXR3h4uEnZ/fv3G7/OyMggPj6e1q1bV7utspU7AgIC6hb0n+RSrBBCCCHEDZycnBg/fjxRUVF4enqi0WiYO3cu+fn5jB071qTsrFmz8PLyws/Pj+nTp+Pt7c2wYcMqrDcxMZE1a9YwaNAgvLy8OHr0KK+++ir33nuvyXPu60ISOyGEEEIIQK/Xo1KVpkZz5sxBr9czatQocnJy6NSpEzt27MDDw8PkmDlz5jBx4kTOnDlDZGQkW7ZsQa1WV1i/Wq1m586dfPLJJ+Tl5REcHMzDDz9c5fPna0ISOyGEEELUOwdXV2xsbS3+5AmHGqwRl5ycTGho6aMj7e3tWbhwIQsXLqywbK9evYwPXRg8eHC16g8ODi731Alzk8ROCCGEEPXO1duXMZ/8q1E+KzYjI4PY2FhiYmIYN26cBSKrP5LYCSGEEMIiXL19G93jvQDGjBlDXFwckydPZujQoQ0dTp1IYieEEEKIv7XKFhS+3chyJ0IIIYQQVkISOyGEEEIIKyGJnRBCCCGElZA5dhZWfOkCCgfHhg6jRkquXQagOOlcA0fSeJSdi0vFOk4UFprsu1Rceit/YpG2xvWWHVOcdR3tNfM8XqYxKM66Xvp/HV9D1vpavN36VRantb1OdWkXa3zMtcykeoik5hpLHKLhKQxli7CIepWdnY2bm1tDh1F7SiXo9Q0dReNSyTlRArU9W3U5tlEz12vIWl+Lt1u/brd4q8newZHTp06i0WgqLZeUlESrVq0pKMi3UGRVc3Bw5FQ1YjeHsve0rKwsXG9aJ66wsJBz587RrFkz7O3t6z2Wv4OanFMZsbOwvXv34uzs3NBh1JhWq8XOzq6hw2hUKjsndTlf1nquzdUvOT+Nw+0Wb3V5e3tXKzHSaDScOnWS1NRUC0RVPdWNXVg3SewsLDIystynGyGEELcfjUYjiVQNFWcWos8rtlh7SicVKvf6GTWMiYmhd+/eZGRk4O7uXi9t1IYkdkIIIYSod8WZhVz7+DcotuAMMJUC/9c7VTu5Gz16NJmZmWzevLlew/rll1+YPn06Bw4cwMbGhsjISHbs2IGDg0Od65a7YoUQQghR7/R5xZZN6gCKDRYdIayOX375hQEDBtCvXz9+/fVX4uLieOWVV1AqzZOSSWInhBBCCHETrVbLhAkT8PX1xd7enh49ehAXF1euXGxsLO3atcPe3p6uXbty/PjxSut99dVXmTBhAm+88QZt2rQhLCyMESNGmG3OqiR2QgghhBA3mTJlChs2bCA6OpqDBw8SGhpK//79SU9PNykXFRXF/PnziYuLw8fHhyFDhqDT6SqsMzk5mQMHDuDr68vdd9+Nn58fPXv25KeffjJb3JLYCSGEEELcIC8vj8WLFzNv3jwGDhxIeHg4S5cuxcHBgeXLl5uUnTFjBn379qVt27ZER0dz/fr1Wz579uzZswDMnDmT559/nu3bt9OhQwf69OnDmTNnzBK7JHZCCCGEEDdITExEp9PRvXt34zZbW1s6d+7MyZMnTcp269bN+LWnpydhYWHlypTR/7n244svvsizzz5L+/btWbBgAWFhYaxYscIssUtiJ4QQQghhAQEBAQCEh4ebbG/dujVJSeZ5eogkdkIIIYQQN2jRogVqtZrY2FjjNp1OR1xcXLmkbP/+/cavMzIyiI+Pp3Xr1hXW27RpUwIDAzl9+rTJ9vj4eEJCQswSu6xjJ4QQQghxAycnJ8aPH09UVBSenp5oNBrmzp1Lfn4+Y8eONSk7a9YsvLy88PPzY/r06Xh7ezNs2LAK61UoFERFRTFjxgzuvPNOIiMjiY6O5tSpU3zzzTdmiV0SOyGEEEIISufAqVSlqdGcOXPQ6/WMGjWKnJwcOnXqxI4dO/Dw8DA5Zs6cOUycOJEzZ84QGRnJli1bUKvVt2xj0qRJFBYW8uqrr5Kens6dd97JDz/8QIsWLczSB4XBYLDwaoF/T5U9MFkIIYS4nVT2nnarB9bfDk+eGDBgAKGhoXz22Wf1HFjN3OqcVkRG7IQQQghR71Tu9vi/3qlRPis2IyOD2NhYYmJiGDdunAUiqz+S2AkhhBDCIlTu9uDe0FGUN2bMGOLi4pg8eTJDhw5t6HDqRBI7IYQQQvyt3WpB4duRLHcihBBCCGElJLETQgghhLASktgJIYQQQlgJSeyEEEIIIayEJHZCCCGEEFZCEjshhBBCCCshy50IIYQQwiIyMzPJz8+3WHuOjo64u7vXS90xMTH07t2bjIyMemujNiSxE0IIIUS9y8zM5LPPPqO42HJPnlCpVLzyyivVTrxGjx5NZmYmmzdvrpd4zp8/T7NmzSrc9/XXX/Poo4/WuQ25FCuEEEKIepefn2/RpA6guLjYoiOEVQkODubq1asm/959912cnZ0ZOHCgWdqQxE4IIYQQ4iZarZYJEybg6+uLvb09PXr0IC4urly52NhY2rVrh729PV27duX48eO3rNPGxgZ/f3+Tf5s2bWLEiBE4OzubJW5J7IQQQgghbjJlyhQ2bNhAdHQ0Bw8eJDQ0lP79+5Oenm5SLioqivnz5xMXF4ePjw9DhgxBp9NVq43ff/+dw4cPM3bsWLPFLYmdEEIIIcQN8vLyWLx4MfPmzWPgwIGEh4ezdOlSHBwcWL58uUnZGTNm0LdvX9q2bUt0dDTXr1+v9rNnly9fTuvWrbn77rvNFrskdkIIIYQQN0hMTESn09G9e3fjNltbWzp37szJkydNynbr1s34taenJ2FhYeXKVKSgoIA1a9aYdbQO5K5Yizt8+HCF19G1Wi12dnbVqqMmZc15bEO7nWOvjDX1qyH6Yi3nz1r6UVPm6re3tzcajaZWxyYlJZGammrRNoX45ptvyM/P5+mnnzZrvZLYWVjPnj0r3K5QKDAYDNWqoyZlzXlsQ7udY6+MNfVLqVCiN+itvs16oQCs42VQIwqFEoMZfn4ODo6cOnWyxolWUlISrVq1pqCg5ndO1rZN0fi1aNECtVpNbGwsISEhAOh0OuLi4pg0aZJJ2f379xtfAxkZGcTHx9O6desq21i+fDkPPvggPj4+Zo1dEjsLGzx4MIGBgSbbzpw5w549exg+fHiVP+CUlBQ2bdrE4LuepU1w5xq1/cfFX9kat5InukTi62qeu28s5dTVZLYfj78tY6+MNfWrrC8LB79FqFeIRdpMSLvAhK3v4/uQLy7tXCzSZn3IOZpD8sZkgl4Iwi7w7zNqV9bvZ+6bhr977ZOja5lJRO+eTWpqao2TrNTUVAoK8mscQ13aFI2fk5MT48ePJyoqCk9PTzQaDXPnziU/P7/cpdNZs2bh5eWFn58f06dPx9vbm2HDhlVaf0JCAj/++CPbtm0ze+yS2FmYt7c3AQEBJtvKLgH4+PiU23crXs7+BPvcUaO2r2UkAeDr6kyQh1uNjm1oydm5wO0Ze2WsqV9lfQn1CqGtf5hF21Z7q3Fo6mDRNs1Je0ULgF2g3W3dj5oq67e/u6bGf8/MrTHEIBqeXq9HpSpNjebMmYNer2fUqFHk5OTQqVMnduzYgYeHh8kxc+bMYeLEiZw5c4bIyEi2bNmCWq2utJ0VK1YQFBREv379zN4HSeyEEEIIUe8cHR1RqVQWf/KEo6NjtcsnJycTGhoKgL29PQsXLmThwoUVlu3Vq5dxGs3gwYNrFNeHH37Ihx9+WKNjqksSOyGEEELUO3d3d1555ZVG+azYjIwMYmNjiYmJYdy4cfUfWD2SxE4IIYQQFuHu7l7t57Za0pgxY4iLi2Py5MkMHTq0ocOpE0nshBBCCPG3Vt0FhW8HskCxEEIIIYSVkMROCCGEEMJKSGInhBBCCGElJLETQgghhLASktgJIYQQQlgJSeyEEEIIIayELHcihBBCCIsoLLxCkS7dYu2pbT2xtw+sumAtxMTE0Lt3bzIyMhrV2nyS2AkhhBCi3hUWXuGX/fej12st1qZSaUe3rjurndyNHj2azMxMNm/eXG8xXbt2jaioKH744QdycnIICwtj+vTpPPzww2apXy7FCiGEEKLeFenSLZrUAej1WouOEFbH008/zenTp/nuu+84duwYDz30ECNGjODQoUNmqV9G7CzExcWFn3/+mV9++YXs7Gzc3d2ZNGlShWV//PFHdu/eDYCzszN9+/alRYsWqNVqrl27hq+vLw8PeoKWrZvj5G7HtsVHOXck1Xi8g4st3R4KRdPaE7WjiitnMtm3Lh7i69aHzsMepWXnbngGBlFcVMSV+JP8+NUqMq5eNpYZ8c5sgtu0NTnuyA//Y+eyRXVr3Myq0xeAgJat6PH4KAJCw9Dr9aRcOMuGD96hWFfUQJHfWlV9cvXx5fnPVlR47JYFs4nfH1uv8Tl1CcCpawAqDzsAdNfzydmVRGF8BgDuw0OxD3XHxlWNXqunKCmbrP+doziloF7jKtPRryOj24wm3CscX0dfJu6eyO6Lu03KvBz5Mg+3fBgXtQuHkw/z3v73SMpJskh8dVVV//po+jAibAThnuG427vzyHePcDrjtEVi6zW8Pe17tMbD35HiIj3Xzmbxy6ZEMq//9UzR8B6B3NHZD59gF9QOKpa++iNFBXV/mLyfnx+//vor7SLupERHhW33eiKMoNaeOLmp0WlLuHY2i43Lk+vctmjctFotUVFRrF27luzsbDp16sSCBQu46667TMrFxsYybdo04uPjiYyMZNmyZURERNyy3p9//pnFixfTuXNnAN566y0WLFjA77//Tvv27escd6MesZs5cyaRkZGVlunVq9ctE6TGJC8vj927dzNhwgR8fHzIysri448/ZuPGjXzyySd069aNXbt2UVxcTPfu3fHx8QFg+PDheHt785///IfFixdz6NAhZs6cSWZ6LnvXVvxHd9D4drh5O7Bt8VG+/iCO3LRChk5sj9retk59CGodweEd/2XNW6/zzQdvo7RR8cj091DZ2ZmUO7pzO4tfeMr478evKk4mGlJ1+hLQshUPv/kuF44e4qvpr/HVm69yaPtWDAZ9A0Z+a1X1KSc11eTnsviFp4j9+kuKCvI5d+j3eo+vJFtL9vZzJP/zEMmfHUabmInX0+GofB0B0F3OJf2beK7943dSVxwDwHtsBCjqPTQAHFQOxGfE88GBDyrcPyZiDE+0foL39r/Hk9uepKC4gH/1/RdqpdoyAdZRVf1zUDlw6PohFhxcYOHIoFmbAI7vvcSGj37nu08Po7RR8OCESFTqv96iVGolSX+k8/v2C2Zt29nZmUWLFrFo2qZbtp2clMOu6JOsefcA3y08DMDYtx9AqWzUb6GijqZMmcKGDRuIjo7m4MGDhIaG0r9/f9LTTUcAo6KimD9/PnFxcfj4+DBkyBB0Ot0t67377rtZt24d6enp6PV61q5dS2FhIb169TJL3DV6VY4ePRqFQsG4cePK7Xv55ZdRKBSMHj3aLIFV18aNG3nvvffqvZ0JEybQsWNH7Ozsqkw2K6LX63nrrbcoLCwkKCgIg8FAbm4uR48eZd++fezfv5+WLVty9OhRioqKCAoKAiA4OJgDBw5w+fJlMjIy2LZtG5mZmZw9eZFzh1PLtePm64B/czf2rjlN8oUcMq/nE/Of09jYKul63511OgcbZ8/gj727SLuURMqFc2z/fAGuPr74NQ81Kacr0pKflWn8V1RgmRGXmqhOX3o98xwH/7eFX7/9hrRLSWRcvUz8/p8oKa77KEF9qKpPBoPe5OeSn5VJy7u6cfqXn9BpC+s9vsKT6RSezqA4rZDi1AKyv7+AoagEtcYFgLxfr1F0LpuSDC26K3lkf38elbs9Nh729R4bwE+Xf+Kfh/7J7qTdFe5/qvVTLDm6hD0X9xCfEc+bP72Jj6MP92nus0h8dVVV/7ae3coXR79g/5X9Fo4MVr6/jVO/XCP9ah5pl3PZFX0SFy97fDSuxjJHd1/i4I4LXDuXZda2ExMTiY6OJvlixi3bPvHTFa4mZJKTVkjqxVwOfHcWdx8XmjZtatZYROORl5fH4sWLmTdvHgMHDiQ8PJylS5fi4ODA8uXLTcrOmDGDvn370rZtW6Kjo7l+/Xqlz579+uuv0el0eHl5YWdnx4svvsimTZsIDQ295TE1UeOPG8HBwaxdu5aCG96sCwsLWbNmDRqNxixB1YSnpycuLi4WaWvMmDE89thjtT7+sccew87OjkuXLpXb16FDBzQaDVlZWdja2hrLXLx4kYiICBwcHFAoFHTq1Al7e3tOHT5bYRs2qtIfabHuhlElA5QU67kjIqTWsVfEztEJgMLcXJPtrXv04qWlX/HMx4voMfIZVGq7ig5vVG7ui4OrG4EtW1GQncnIWfMY96/VjJgxmyZh4Q0ZZo3c6udTxrdZC3ybteD4nu8tGVYpBTi080GhtqEoKaf8blsljp38KU4roCTLsnNyKhLkHISPo49J0pOry+VYyjHu9KnbByZRnp1D6Swhbf6tRz0aqm2VWkmruwNIu57NxYsXLRmasKDExER0Oh3du3c3brO1taVz586cPHnSpGy3bt2MX3t6ehIWFlauzI3efvttMjMz2blzJ7/99huvvfYaI0aM4NixY2aJvcaJXYcOHQgODmbjxo3GbRs3bkSj0ZS7Nrx9+3Z69OiBu7s7Xl5eDB48mMTERJMyly5dYuTIkXh6euLk5ESnTp04cOCASZnVq1fTtGlT3NzcePzxx8nJ+euN4OZLsU2bNuXDDz9kzJgxuLi4oNFoWLJkiUl9Fy9eZMSIEbi7u+Pp6cnQoUM5f/58pf1euHAhL7/8Ms2bN6/OaSrHxcWFL774gs8++4yUlBSTfRqNhv3792MwGOjWrRvr1q0zllm/fj1KpZKpU6fy1ltv8dRTTzF8+HCSr1Q8GTTzWj45aYV0G94cO0cVShsF7ftpcPG0x83LjAmwQkGvZ57n8qk/SLv416WRk7ExbPtsPl/PepMDm9cTfk9vBv3fZPO1Wx8q6Iu7nz8A3R55gqO7d7Bx9gySzyXyyNsf4O5fP7fOm9Utfj43antfP9IuJXEl/pTFwlL5ORL47t00eb8HHsNDSVt9guLkv+YyOXUNKN3/Xnfs7/AgZflxKDFYLL5b8XLwAiCtMM1ke1phGt4O3g0RkvVSQI9HW3IlIZP0K3mNpu2Ink144ZN7eXFhL0LaeLH83a2VXm4ToiKJiYl89tlnrFixgj59+nDnnXcyY8YMOnXqxKJF5pmLXqsJAmPGjGHlypXG71esWMGzzz5brlxeXh6vvfYav/32G7t27UKpVDJ8+HD0+tLRpNzcXHr27Mnly5f57rvvOHLkCFOmTDHuh9KTsHnzZrZu3crWrVvZu3cvc+bMqTS++fPn06lTJw4dOsRLL73E+PHjOX26dD6aTqejf//+uLi4sG/fPmJjY3F2dmbAgAEUFZlvQrxWqyU7O5vs7GxycnJITk5m8eLFPPfcc8b5c2VSUlIoKChg586dxMXFMWzYMGOZ3r17Y29vT3R0NEuWLGHnzp18/fXXBDXzq7Bdvd7A//51DHdfR577x728uLAnTcI8uHA8FYPefG+QfcaMxzs4hK2fzjXZfmzXDi4cOUjqxQuc+imG/y36By07343bn4lSY1RRXxSK0oldR3du54+YnSSfP0vMv5eRceUSEb37NlSo1Xarn08Zla2aVt17cmzPDxaNqzi1gOsLD5L8+WFy91/F49Ew4xw7gPxDySQvPEjyv45QnFqA1xOtQGWhSXaiUej5+B14NnHi+2V/NKq24w9cY92HcWz8+CCZ1/N5YnJf7Owa/9UIUTtlNyzGxv51U5lOpyMuLo7wcNMrN/v3/zWSn5GRQXx8PK1bt66w3vz80g+yN8/PtLGxMcl96qJWd8U+9dRTTJs2jQsXSkcCYmNjWbt2LTExMSblbl6TZcWKFfj4+HDixAkiIiJYs2YNKSkpxMXF4enpCVDuGrNer2fVqlXGy62jRo1i165dfPBBxROAAQYNGsRLL70EwNSpU1mwYAF79uwhLCyMdevWodfrWbZsmfHNe+XKlbi7uxMTE0O/fv1qc0rKmT17Nu+++2657Q8++CBdunRh69atxm2dO3fG3t6e7du34+LiQpMmTejSpQuxsbF06dKFRYsWGUfwDh8+jIODA32GduXEtoo/zaYk5bDugzjU9jYoVUoKc3U8MrUjCQkZZunbfc+Oo0WHu1g78w1y09MqLXs1oTShdvcPJOv6NbO0b0636ktuRum5Srtkesdj+uWLuHqbJuaNTXV+Pi27dsfWzo4Te3dZNrgSAyVphZRQerOEOsgZ5+6BZG5KAMCgLaFYWwJphaQlnSRwRjcc2nhTcCSl8nrrWVpB6Xn0svciteCvua1e9l6cSrfciKe1u+fxOwhp682m+QfJy7TsJfgHn+tRadtFhSUUFRaQlVzA9XNZjJ3fg+HDh1s0RmE5Tk5OjB8/nqioKDw9PdFoNMydO5f8/HzGjh1rUnbWrFl4eXnh5+fH9OnT8fb2ZtiwYRXW26pVK0JDQ3nxxRf5+OOP8fLyYvPmzfzwww8meUFd1GrEzsfHhwceeIBVq1axcuVKHnjgAby9y1+OOHPmDCNHjqR58+a4uroaJ5omJZW+WR4+fJj27dsbk7qKNG3a1GQOXUBAAMnJld9m3q5dO+PXCoUCf39/4zFHjhwhISEBFxcXnJ2dcXZ2xtPTk8LCwnKXieti2rRpZGVlGf+VzcVQKpWoVKb59H333cd3331H7p9zoRQKBSqVClvb0rtYDQbTkbaSkhIUyqpHMYoKSyjM1eHm64BPiCsHfz5R537d9+w4Qjt34+v3ppOdcr3K8r5NSy9d52U0rnWEoPK+ZKdcJyc9DY/AIJPtHgFNyE5pvMscVPfn07Z3PxJ/+5WCnGwLRlcBpQKFqvI/Q4pGMGJ3KfcSKfkpdAnoYtzmZOtEW5+2HEk50oCRWY97Hr+D5pE+fPvJIXLS6v9mnhv985//pE3nZtVvW1H6T0bsrI9erze+R8+ZM4eHH36YUaNG0aFDBxISEtixYwceHh4mx8yZM4eJEyfSsWNHrl27xpYtW1CrK75b3tbWlm3bthnvnm3Xrh3//ve/iY6OZtCgQWbpQ63XsRszZgyvvPIKwC2vCw8ZMoSQkBCWLl1KYGAger2eiIgI4yVPBweHKtspS27KKBSKKocrKzsmNzeXjh078tVXX5U77uZLpHVhZ2dn8kuvVCr58MMPCQsL48svvzRuHzx4MOHh4cybN4/mzZtz33330bRpU1avXk1qaippaWkMGTKE77//nvz8fNq0aUPfvn356p9b8Q4qvbzp6u2Ad5AzhXk6cjO0tOjgQ0Gujtz0QryaONNjREvOHU7hj98S6tSnPmPH06p7T76d9z5FBfk4urkDUJSfT7GuCDc/f1p378XZQ3EU5ubgo2lKr6ef5+KJY6Qmna9T2+ZWVV8AftuygbsffZKUC+dIOX+W8J598GgSxHcLZjdg5LdWnT4BuPsFENS6DRvnzLRofK79m1IYn05JphaF2gbHSF/smrmRuuI4Np72OLbzpvBMJvpcHTZualx6BWPQ6Sk8ZZ6R5qo4qBzQuPx1A1gTlyaEeYSRVZTFtbxrfHnyS15s9yJJOUlczrnMK+1fISU/5ZZ3mTY2VfXPVe1KgFMAvo6+ADR1awpAakFqubmF5jb0+XsI6+zHtsXH0BWW4Oha+qaoLSim5M8bwRxd1Ti6qnHzKX3f8GrihK6whJz0uiWBwcHBPPXUU6ydvxO11qtc267e9oR29OPiyXQKcopw9rCjQ/8QdEUlbNu2jQkTJtSp/b8Tta0nSqWdxZ88oba99eDRzZKTk41XDu3t7Vm4cCELFy6ssGyvXr2MAy+DBw+udhstW7Zkw4YN1S5fU7VO7MrmpCkUCvr3719uf1paGqdPn2bp0qXcc889APz0008mZdq1a8eyZctIT0+vdNTOnDp06MC6devw9fXF1dW16gPMxNHRkbvuuov58+eTl/fXJdSypU+WLFmCVqslNTWV1atXc/Zs6V2vX331Fffffz8jR45ErVZz/fp1Zs+ezfTp04119Hi0JQAnf7nK7uiTOLnZ0f2Rlji6qsnPKuLU/qv8tu18nfsQ2e8BAB6baTrHcfvnC/hj7y70xcVo2t5Jh0EPYmtnT05aKmd+/Zn9G9fWuW1zq6ovAAe3fYfKVk3vp5/D3tmFlAvn2PD+243ykjJUr08AEb37kpOeyvmj5lnlvLpsnG3xHBGGjYsafWExuqt5pK44jjYhE6WLGnVTN5y7N0HpoKIkV0fRuSxSFh9Bn2eZCeptvNqwcsBfc4en3DUFgG8TvuWt2LdYcXwFDioHZnSbgYvahUPXDzFu5ziK9I1vseqKVNW/3sG9eb/H+8b9H/f8GIDPD3/O4iOL6zW2bgPaADB8cgeT7buiT3Dql9Lftzb3NqHz4GbGfQ+93tFYJqEOS9uVfaB/8b2hFbZdrNMT2NKNO/sEY+eoIj+7iKsJmSx+c1O5G+FE5eztA+nWdWejfFZsRkYGsbGxxMTEVLik2+2k1omdjY2N8XZeGxubcvs9PDzw8vJiyZIlBAQEkJSUxBtvvGFSZuTIkXz44YcMGzaM2bNnExAQwKFDhwgMDDS5fdicnnzySebNm8fQoUOZNWsWQUFBXLhwgY0bNzJlyhTj+nE3S0hIIDc3l2vXrlFQUMDhw4cBCA8Pv+WQ641yc3Pp27cvo0ePJiTkr2VHvvjiC44dO8bGjRt54YUXCAgIMDkuPT2dr7/+2vj91atXWbJkCWd25XHXHfdX2NbRPZc4uqf8kip1Nf+xyj+R5KSl8vW708zebn2oqi9lfv32G3799pt6jsY8qtunn9b+m5/W/rueoykvY8OZW+7T5xSRtsryk+Vv9Nv132gb3bbSMosOL2LR4cb1FJXqqqp/3yZ+y7eJ31owor+88fAXBPvcUWmZuK3niNt6zuxtHzx4kI4dOzL1ocUVxpCfVcTWz46W256aYt719P4u7O0Dq/3cVksaM2YMcXFxTJ48maFDh1Z9QCNWp0eKVTbipVQqWbt2LRMmTCAiIoKwsDAWLlxosrKyWq3m+++/Z/LkyQwaNIji4mLCw8PNdstvRRwdHfnxxx+ZOnUqDz30EDk5OTRp0oQ+ffpU2p/nnnuOvXv3Gr8vW9rl3LlzskilEEIIcRurbEHh202NErtVq1ZVun/z5s0m399///2cOGE6Yf/mGwFCQkL45puKR0RmzpzJzJkzTbZNmjTJZN26m+/ErWg9urLRtTL+/v5ER0dX2Oat3NyOEEIIIURjIw+6E0IIIYSwEpLYCSGEEEJYCUnshBBCCCGshCR2QgghhBBWQhI7IYQQQggrUaflToQQQgghqutSYRHpumKLtedpqyLIvuq1ZmsjJiaG3r17k5GRgbu7e720URuS2AkhhBCi3l0qLKL7gZNo9YaqC5uJnVJBbJfW1U7uRo8eTWZmZrnl28wpMTGR119/nZ9++gmtVsuAAQP45z//iZ+fn1nql0uxQgghhKh36bpiiyZ1AFq9waIjhFXJy8ujX79+KBQKdu/eTWxsLEVFRQwZMsT4TPu6ksROCCGEEOImWq2WCRMm4Ovri729PT169CAuLq5cudjYWNq1a4e9vT1du3bl+PHjt6wzNjaW8+fPs2rVKtq2bUvbtm2Jjo7mt99+Y/fu3WaJWxI7IYQQQoibTJkyhQ0bNhAdHc3BgwcJDQ2lf//+pKenm5SLiopi/vz5xMXF4ePjw5AhQ9DpdBXWqdVqUSgU2NnZGbfZ29ujVCr56aefzBK3JHZCCCGEEDfIy8tj8eLFzJs3j4EDBxIeHs7SpUtxcHBg+fLlJmVnzJhB3759jaNv169fv+WzZ7t27YqTkxNTp04lPz+fvLw8Xn/9dUpKSrh69apZYpfETgghhBDiBomJieh0Orp3727cZmtrS+fOnTl58qRJ2W7duhm/9vT0JCwsrFyZMj4+Pqxfv54tW7bg7OyMm5sbmZmZdOjQAaXSPCmZ3BUrhBBCCGEh/fr1IzExkdTUVFQqFe7u7vj7+9O8eXOz1C8jdkIIIYQQN2jRogVqtZrY2FjjNp1OR1xcHOHh4SZl9+/fb/w6IyOD+Ph4WrduXWUb3t7euLu7s3v3bpKTk3nwwQfNEruM2AkhhBBC3MDJyYnx48cTFRWFp6cnGo2GuXPnkp+fz9ixY03Kzpo1Cy8vL/z8/Jg+fTre3t4MGzbslnWvXLmS1q1b4+Pjwy+//MLEiRN59dVXCQsLM0vskthZWGpqKmq16UKJGRkZAKSkpFR5fFmZtNxrXEyJr1HbabnXAEjOzq3RcY1Bel4+cHvGXhlr6ldZXxLSLliszbK2ilKLKDhfYLF2za0otQgA7RVtA0diWWX9vpaZVKd66np8beowR5ui8dHr9ahUpanRnDlz0Ov1jBo1ipycHDp16sSOHTvw8PAwOWbOnDlMnDiRM2fOEBkZyZYtW8q9z9/o9OnTTJs2jfT0dJo2bcr06dN59dVXzdYHhcFgsOxqgX9T2dnZuLm53XK/QqGguj+KmpQ157EN7XaOvTLW1C+lQoneYJ5FNhtzm/VCAVjHy6BGFAolBjP8/BwcHDl16iQajaZGxyUlJdGqVWsKCvIt1qY1KHtPy8rKwtXV1WRfYWEh586do1mzZtjb2xu33w5PnhgwYAChoaF89tln9RxZzdzqnFZERuwsbO/evTg7O5fbrtVqTda1qUxNyprz2IZ2O8deGWvqV0P0xVrOn7X0o6bM1W9vb+9aJVgajYZTp06SmppqsTb/roLs1cR2ad0onxWbkZFBbGwsMTExjBs3zgKR1R9J7CwsMjKy3KcbIYQQDUej0UiCZiFB9upqj55Z0pgxY4iLi2Py5MkMHTq0ocOpE0nshBBCCPG3dqsFhW9HstyJEEIIIYSVkMROCCGEEMJKSGInhBBCCLPT663gbvVGoibnUubYCSGEEMJs1Go1SqWSK1eu4OPjg1qtRqFQNHRYtyWDwUBRUREpKSkolcpK18crI4mdEEIIIcxGqVTSrFkzrl69ypUrVxo6HKvg6OiIRqNBqaz6QqskdkIIIYQwK7VajUajobi4mJKSkoYO57ZmY2ODSqWq9qinJHZCCCGEMDuFQoGtrS22trYNHcrfitw8IYQQQghhJSSxE0IIIYSwEpLYCSGEEEJYCUnshBBCCCGshCR2QgghhBBWQhI7IYQQQggrIYmdEEIIIYSVkMROCCGEEMJKSGInhBBCCGElJLETQgghhLASktgJIYQQQlgJSeyEEEIIIayEJHZCCCGEEFZCEjshhBBCCCshiZ0QQgghhJWQxE4IIYQQwkpIYieEEEIIYSUksRNCCCGEsBKS2AkhhBBCWAlVQwfwd3P48GGcnZ0bOgwAvL290Wg0DR3GbSMpKYnU1NSGDqNeWOK1UNn502q12NnZ1Wv7lmynuhpbPDdr7PHd6HaKtb7I33QBkthZXM+ePRs6BCNHB0dOnjopfwiqISkpiVatWlFQUNDQodQLBwcHTp06VW+vhaSkJFq3DiM/v7DC/Uol6PX10nSDtFNdSoUSvaERBXSTxh7fjW6nWOuLo709J0+flr/pf3OS2FnYR/2jaOt/R0OHQULaBSZsfZ/U1FT5I1ANqampFBQUMHz4cHx8fBo6HLNKSUlh06ZN9fpaSE1NJT+/kGnTfNBo1Cb7fv01j5UrMyvcZ05JSUXMnp1C1D1j6d28a721U117zu5n3r7lLBz8FqFeIQ0dTjmNPb4blf09m+Dtzb1OjeOKiKUlFmmZevWq/E0XkthZWgvPYNr6hzV0GKKWfHx8CAgIaOgwblsajZqWd5heLktKKrrlvvoQ7BbQKH4HE9IuABDqFdIo4rlZY4+vIkEqW8Lt7Rs6DCEalNw8IYQQQghhJSSxE0IIIYSwEpLYCSGEEEJYCUnshBBCCCGshCR2QgghhBBWQhI7IYQQQggrIYmdEEIIIYSVkMROCCGEEMJKSGInhBBCCGElJLETQgghhLASktgJIYQQQlgJSeyEEEIIIayEJHZCCCGEEFZC1dABiPKcugTg1DUAlYcdALrr+eTsSqIwPqN0f2d/HCN9sA10Rmmv4vLMnzEUljRkyKKOevTowf3338/+/fvZvn07AB07dqRt27YEBARgZ2fHnDlzKCwsbOBIa2/q1KmMGzeHpIsrOXPmfQBahb1P5J3dePttPyCf3NyDJCTOJT//bLnjQ0JeJLTFFJPjb3TnnSvw9urJkaPjSE39oU6xVvU7eCPvZ9tgH+ZJ6r9PUHgirU7t1jUunxfaYtfc3eSY3P1XydycUK9x1TROALXGBdf+TVEHu4DegO5qHinLj0Ox3qKx1oRDp054jR2DfZs22Pr6cvHlV8jdtcu4X+HoiO/k13Dp0wcbd3d0ly6RvvpLMteta8Coxd9No07sZs6cyebNmzl8+P/bu/ewqOp9f+DvGYbh4nCR28AEA1YWGqgo6Sbr6NlxvFFZefLEg+alk2XUDj2/vFRq5fGWp93VbVt7vJxdpl3IlLNtR4qYpoACmoKgaKByc0QYbsMMM9/fH+Vsh7sKs3B4v56H52HW+s5a7/noWvOZdRly2x0zduxYDBs2DO+//77dcvU0s74J+u/Po1nXCMhkcB8eAN9nBqPiwxw0VzZA5iyHoeAqDAVX4TVxgNRx6RZpNBqMGDEC5eXlNtOdnZ1x9uxZnD17FrGxsRKl6x7u7u54/vnnodPl2UzX157E//3fF1i58gT+53/CMWbM/0PUsK049PMYAP98g/fwiMQdmnjU1ua3ufyQkFmAEN2Wt7Nt8BrVg5ruXG235KrLKIM+tdj6HGGyf6PUWU6l1gN+syNQm3YB1d8VARYB56B+3fpv2BPkbm5oOl2Amm+SEfzxR63mqxctRL9Ro1C6YAFMly6h3+jRCFy6FM2VlahLS5MgMfVFN3QqdubMmZDJZHjhhRdazUtMTIRMJsPMmTO7K1uXJCcnY/ny5T2+npKSEsTFxcHd3R0BAQF49dVX0dzc3CPrMuRXwVBwFc1XDGjWNUL/QzGE0Qyl1gMAUHeoFLXpF2G8UNsj6yf7USqVmDJlCnbv3t3qaNyRI0dw8OBBXLx4UaJ03ScsLAzPPfccjMYam+mlpdvx669HUFxcDJ3uJM6d+zNcXTVwcwu2jnFyckfEfe8h//RraG6uabloqFSDoA15FvmnF3Zb3s62QQBwDuoH1UPBuPp1YbettztyCZMFljqT9Uc02f9ofmc5vR6507ofa65sQLOuEY2/6ABz727s6n/6CZc/+AC1P/7Y5ny3YVGo2fkdGjKzYLpUiuovv4KhoABuQ4bYOSn1ZTd8jV1ISAi2b9+OxsZG6zSDwYBt27ZBq9V2a7iu8PHxgYeHR+cDb4HZbEZcXByMRiN+/vlnbN26FVu2bMHSpUt7dL0AABngNsQfMqUTjCVs5BzNpEmTUFhYiHPnWp96dCQ1NTXYe90pq7YoFG4ICvp3NDaWwGAos06/9563oNOl4erVn1s9Ry53RcR976Gg8E0Yjbpuzw2gzW1Q5iyHz9PhqP7uLCx1pp5Z703kAgD3YQEIWvIHqJOGw3N8GGTOEl9K3SKnvJ8zXLSeMNeb4D93KIJeHwX/OUOgDPWUNmc3aMzNgeqP/wpFQAAAwH3USCjDwlB36JDEyagvueEtfvjw4QgJCUFycrJ1WnJyMrRaLaKiomzGfv/993jwwQfh7e0NX19fPPLIIygqKrIZc/HiRcTHx8PHxwf9+vVDdHQ0MjIybMb87W9/Q1hYGLy8vPD000+jtvafO7GxY8ciKSnJ+jgsLAwrV67E7Nmz4eHhAa1Wiw0bNtgs78KFC5g6dSq8vb3h4+ODyZMn49dff233Nf/www/Iy8vDZ599hmHDhmHixIlYvnw51q1bB6PR2NXS3RCF2h2atx7AHf/9IPo/cTeu/C3P5hQQ3f4iIiIQFBTUacPjCEpLS9udN2rULNTW1uI///MMfH3HICd3BoT4rVlSBzwCD4/7UHRubZvPvWfgG6iuyYZO1/YRlFvR0Tbo9cidMJboYcir6vb13kquhtzLqNpxGpc3nIB+/wW4Dw+Az3/ca/eMHeVU+LgCADwf1qI+sxy6zSdhLK2D/3ORUPi6SpK1u1Qs/280FRVh4IF0hP9yAiEbN6Li7eVoPHpU6mjUh9zUR7nZs2dj8+bN1sebNm3CrFmzWo2rr6/H/PnzcfToUezduxdyuRxPPPEELJbfrvmoq6vDmDFjcOnSJezatQvHjx/HggULrPMBoKioCDt37kRKSgpSUlKQnp6O1atXd5jv3XffRXR0NHJycvDiiy9i7ty5KCgoAACYTCaMHz8eHh4e+Omnn3Do0CGoVCpMmDCh3Sbt8OHDiIyMhFqttk4bP3489Ho9Tp061eZzmpqaoNfrbX5uRLOuERUfZqPyL7moO1KG/k/dC0WA+w0tg3ovT09PTJgwAcnJyT12Sr83ER1cO5Wb+zWioqLw3XdT0NBwHhH3fQS5XAkXlyDcc88SnDo1DxZL623Tz+9h9O8f0+aNFN2hvW3QdZAPXO7yRvXuos4XYsdcAFCfWY6mM9VormhAY+5lXP2yAG4RfnDysX/D1G5OGX7PWoaGYxUwldajJuUcTJcb4R4daPec3an/9GlwGzoUF+bOxfkp/47KNWugXroE7jExUkejPuSmbp6YNm0aFi9ejOLi3y7QPXToELZv3479+/fbjJsyZYrN402bNsHf3x95eXmIiIjAtm3bcPnyZWRlZcHHxwcAcPfdd9s8x2KxYMuWLdbTrdOnT8fevXuxYsWKdvNNmjQJL774IoDf7sR77733kJaWhnvvvRc7duyAxWLBp59+Cpnstz3M5s2b4e3tjf3792PcuHGtlldeXm7T1AGwPm55wfs1q1atwltvvdVuxk6ZBcxXDDADMF2qgzJYBdVoDaq/te/dbdQzNBoNVCoVnn/+ees0uVyO0NBQjBw5EsuXL++wGbrdREVFwWQyQaFQQIhRCL5jOtL2DwJgQVNTLc6evYyyskb8cvIUxvxLNvz9x8NsNkCp9MP99++yLkcuV8DbeySC75iOS5e2wc1Ni395KMdmXUMi16G6OgvZOQm3FrqdbVCYLFD4uEKz7AGb4b7TBsH4aw0ub/jl1tZ7k7na2jdcO0Wr8HWFucrOd1S3k7N2/wUAQHOF7RmI5soGKLxd7JuxG8lcXBCQlISLL/8JdenpAICmwkK4hg+C7+xZaDh8WOKE1FfcVGPn7++PuLg4bNmyBUIIxMXFwc/Pr9W4M2fOYOnSpcjIyIBOp7MeiSspKUFERARyc3MRFRVlberaEhYWZnMNXVBQECorKzvMN+S6C1VlMhkCAwOtzzl+/DjOnj3b6ro8g8HQ6jTxrVi8eDHmz59vfazX6xESEnLzC5TLIFPwawcdxblz5/CXv/zFZtrkyZOh0+lw6NAhh2rqACA/Px9Tp07Fvn2fwWw5j+LiDbj+rtd/kgGQQS5TQnd1H45kTLSZO3jQGtQ3FKG4eANMpipcKv3CZv4fRu1B4ZkV0Ol64PT279ugPrUY9Vm2H+gC541ATco5NOb37NeddJSrLc4aFQDAUtszl4zckN9zmq82wVzTBIW/7RkIhb8bDAX2P7XdXWQKBWRKJYTF9v+1sJgBOffdZD83/XUns2fPxksvvQQAWLduXZtjHn30UYSGhmLjxo3QaDSwWCyIiIiwnvJ0c3PrdD3Ozs42j2Uymc2p2ht9Tl1dHUaMGIHPP/+81fP8/f3bXF5gYCAyMzNtplVUVFjntcXFxQUuLjf36dNzfBgMhVUwVzdBpnSC+7AAuAzwgm7TSQCAXOUMJw8lnH6/HsU5sB9EkxnN1U0QjY5/Ws8RGI3GVh9QTCYTGhsbrdNVKhVUKpX1g09AQACMRiNqampsbl66HRgMBpw6dQrNzY1oNlejvr4Qrq4hUKvjoNH8AyEhhVCroxAZ8TIsFgN0V/bDbK5Hfb3tHadmcwNMpmrr9LZumDAYSmEw3NqdxB1tg9fuNm2puboJ5qtNt7TeW8nl5OMK92H+MBRchaXBBOfAfvB+5E40nauBqdy+1+d2tg+rPXARnv8WClNZPYxldeg3XA1nfzdc+azCrjlvlMzdHcrrbhJUBgfDJTwc5poaNJeVoT4zEwGvvoqKJgNMl0rhPvJ+eE2ejIrVayRMTX3NTTd2165Jk8lkGD9+fKv5V65cQUFBATZu3IiHHnoIAHDw4EGbMUOGDMGnn36KqqqqDo/adafhw4djx44dCAgIgKdn1+7CiomJwYoVK1BZWYmA3+92Sk1NhaenJwYPHtztGZ1UzvCZei+cPJSwGJphKquHbtNJNJ2tBgCo/hAEz9hQ6/iAF4YCAKq+KkDDsY6PZtLtIzo6GmPHjrU+nj17NgB0+t2OtwuLpQneXvdj5syZmDPHC0ajDnV1WTh67CmYTBIc+bpOZ9tgb8zl5KWE6939oRp9B+RKJzTXNKHxpA76fRd6VU7gt69skink8HrkTsjdFb99OfGnJ+1/uvgGuUXch9D//V/rY/XiRQCA6m+/Rdni13Bp/n8hYP48aNauhZOXF0ylpbj8/vuo3r5dqsjUB910Y+fk5IT8/Hzr7y31798fvr6+2LBhA4KCglBSUoJFixbZjImPj8fKlSvx+OOPY9WqVQgKCkJOTg40Gg1ieuhi04SEBKxduxaTJ0/G22+/jeDgYBQXFyM5ORkLFixAcHBwq+eMGzcOgwcPxvTp0/HOO++gvLwcb7zxBhITE2/6qFxHrn5zpsP5+h9LoP+xpNvXS9LasmWLzeP9+/e3um71drdr11MYeM9v24zRWInjJ57F3h9rsWrVZaxff4d1Xns6u25u7767uiVnZ9tgSxcX/dQt6+1MR7nMNUZc3nDCLjk605X61aZfRG367fUdjQ2ZWcgPH9TufLNOh7LXXrdjIqLWbunEv6enZ7tHveRyObZv345jx44hIiIC8+bNw9q1tl9ZoFQq8cMPPyAgIACTJk1CZGQkVq9e3Waj2F3c3d1x4MABaLVaPPnkkxg0aBCeffZZGAyGdl+Lk5MTUlJS4OTkhJiYGEybNg3PPPMM3n777R7LSURERHSjbuiIXcsjCi3t3LnT5nFsbCzy8mz/hFDLi8JDQ0Px9ddft7m8N998E2+++abNtKSkJJvvrWt5RKOt76NredoqMDAQW7dubXOd7QkNDcXf//73G3oOERERkT3xVh0iIiIiB8HGjoiIiMhBsLEjIiIichBs7IiIiIgcBBs7IiIiIgfBxo6IiIjIQbCxIyIiInIQbOyIiIiIHAQbOyIiIiIHwcaOiIiIyEGwsSMiIiJyEGzsiIiIiBwEGzsiIiIiB8HGjoiIiMhBsLEjIiIichAKqQP0NUVVF+CudJM6Bs5eKZY6wm3p8uXLUkfodvZ8TSUlxlbTystN7c7riXVfqCnDL+UFPbqurrhQUwag926LvT3f9a5lvNhsQp7BIHEaaRQZm6SOQL2ETAghpA7RF+j1enh5eUkdw4a7mzvyT+dDq9VKHaXXKykpQXh4OBobG6WO0iPc3Nxw+vTpHvu/UFJSgkGD7kVDQ9tvunI5YLH0yKolWU9XyWVyWEQvCtRCb893vdspa09xd3VFfkGBXfbp197Tampq4Onp2ePro67jETs7S09Ph0qlkjoGAMDPz49NXRdptVqcPn0aOp1O6ig9oqf/L2i1WuTnF7Rbv6amJri4uPTY+u29nq7qbXla6u35rnc7Ze0p3KcTwCN2dsNPN0RE5Cj4ntZ78eYJIiIiIgfBxo6IiIjIQbCxIyIiInIQbOyIiIiIHAQbOyIiIiIHwcaOiIiIyEGwsSMiIiJyEGzsiIiIiBwEGzsiIiIiB8HGjoiIiMhBsLEjIiIichBs7IiIiIgcBBs7IiIiIgfBxo6IiIjIQSikDtBXCCEAAHq9XuIkREREt+bae9m19zbqPdjY2cmVK1cAACEhIRInISIi6h61tbXw8vKSOgZdh42dnfj4+AAASkpKuBG0Q6/XIyQkBBcuXICnp6fUcXod1qdjrE/nWKOOsT6du1ajkpISyGQyaDQaqSNRC2zs7EQu/+1yRi8vL+4wOuHp6ckadYD16Rjr0znWqGOsT+f4XtZ78eYJIiIiIgfBxo6IiIjIQbCxsxMXFxcsW7YMLi4uUkfptVijjrE+HWN9OscadYz16Rxr1PvJBO9VJiIiInIIPGJHRERE5CDY2BERERE5CDZ2RERERA6CjZ2drFu3DmFhYXB1dcWoUaOQmZkpdSRJrFq1Cvfffz88PDwQEBCAxx9/HAUFBTZjDAYDEhMT4evrC5VKhSlTpqCiokKixNJavXo1ZDIZkpKSrNNYH+DSpUuYNm0afH194ebmhsjISBw9etQ6XwiBpUuXIigoCG5uboiNjcWZM2ckTGw/ZrMZS5YswYABA+Dm5oa77roLy5cvt/nTT32tPgcOHMCjjz4KjUYDmUyGnTt32szvSj2qqqqQkJAAT09PeHt749lnn0VdXZ0dX0XP6ag+JpMJCxcuRGRkJPr16weNRoNnnnkGpaWlNstw5PrcbtjY2cGOHTswf/58LFu2DNnZ2Rg6dCjGjx+PyspKqaPZXXp6OhITE3HkyBGkpqbCZDJh3LhxqK+vt46ZN28edu/eja+++grp6ekoLS3Fk08+KWFqaWRlZeGvf/0rhgwZYjO9r9fn6tWrGD16NJydnbFnzx7k5eXh3XffRf/+/a1j3nnnHXz44Yf45JNPkJGRgX79+mH8+PEwGAwSJrePNWvWYP369fj444+Rn5+PNWvW4J133sFHH31kHdPX6lNfX4+hQ4di3bp1bc7vSj0SEhJw6tQppKamIiUlBQcOHMCcOXPs9RJ6VEf1aWhoQHZ2NpYsWYLs7GwkJyejoKAAjz32mM04R67PbUdQjxs5cqRITEy0PjabzUKj0YhVq1ZJmKp3qKysFABEenq6EEKI6upq4ezsLL766ivrmPz8fAFAHD58WKqYdldbWysGDhwoUlNTxZgxY8Qrr7wihGB9hBBi4cKF4sEHH2x3vsViEYGBgWLt2rXWadXV1cLFxUV88cUX9ogoqbi4ODF79mybaU8++aRISEgQQrA+AMS3335rfdyVeuTl5QkAIisryzpmz549QiaTiUuXLtktuz20rE9bMjMzBQBRXFwshOhb9bkd8IhdDzMajTh27BhiY2Ot0+RyOWJjY3H48GEJk/UONTU1AP75t3SPHTsGk8lkU6/w8HBotdo+Va/ExETExcXZ1AFgfQBg165diI6OxlNPPYWAgABERUVh48aN1vnnz59HeXm5TY28vLwwatSoPlGjBx54AHv37kVhYSEA4Pjx4zh48CAmTpwIgPVpqSv1OHz4MLy9vREdHW0dExsbC7lcjoyMDLtnllpNTQ1kMhm8vb0BsD69Df9WbA/T6XQwm81Qq9U209VqNU6fPi1Rqt7BYrEgKSkJo0ePRkREBACgvLwcSqXSusO4Rq1Wo7y8XIKU9rd9+3ZkZ2cjKyur1TzWBzh37hzWr1+P+fPn47XXXkNWVhb+9Kc/QalUYsaMGdY6tLXN9YUaLVq0CHq9HuHh4XBycoLZbMaKFSuQkJAAAH2+Pi11pR7l5eUICAiwma9QKODj49PnamYwGLBw4ULEx8db/1Ys69O7sLEjySQmJuLkyZM4ePCg1FF6jQsXLuCVV15BamoqXF1dpY7TK1ksFkRHR2PlypUAgKioKJw8eRKffPIJZsyYIXE66X355Zf4/PPPsW3bNtx3333Izc1FUlISNBoN60O3xGQyYerUqRBCYP369VLHoXbwVGwP8/Pzg5OTU6u7FisqKhAYGChRKum99NJLSElJQVpaGoKDg63TAwMDYTQaUV1dbTO+r9Tr2LFjqKysxPDhw6FQKKBQKJCeno4PP/wQCoUCarW6T9cHAIKCgjB48GCbaYMGDUJJSQkAWOvQV7e5V199FYsWLcLTTz+NyMhITJ8+HfPmzcOqVasAsD4tdaUegYGBrW52a25uRlVVVZ+p2bWmrri4GKmpqdajdQDr09uwsethSqUSI0aMwN69e63TLBYL9u7di5iYGAmTSUMIgZdeegnffvst9u3bhwEDBtjMHzFiBJydnW3qVVBQgJKSkj5Rr4cffhi//PILcnNzrT/R0dFISEiw/t6X6wMAo0ePbvUVOYWFhQgNDQUADBgwAIGBgTY10uv1yMjI6BM1amhogFxuu2t3cnKCxWIBwPq01JV6xMTEoLq6GseOHbOO2bdvHywWC0aNGmX3zPZ2rak7c+YMfvzxR/j6+trM7+v16XWkvnujL9i+fbtwcXERW7ZsEXl5eWLOnDnC29tblJeXSx3N7ubOnSu8vLzE/v37RVlZmfWnoaHBOuaFF14QWq1W7Nu3Txw9elTExMSImJgYCVNL6/q7YoVgfTIzM4VCoRArVqwQZ86cEZ9//rlwd3cXn332mXXM6tWrhbe3t/juu+/EiRMnxOTJk8WAAQNEY2OjhMntY8aMGeKOO+4QKSkp4vz58yI5OVn4+fmJBQsWWMf0tfrU1taKnJwckZOTIwCIP//5zyInJ8d6V2dX6jFhwgQRFRUlMjIyxMGDB8XAgQNFfHy8VC+pW3VUH6PRKB577DERHBwscnNzbfbbTU1N1mU4cn1uN2zs7OSjjz4SWq1WKJVKMXLkSHHkyBGpI0kCQJs/mzdvto5pbGwUL774oujfv79wd3cXTzzxhCgrK5MutMRaNnasjxC7d+8WERERwsXFRYSHh4sNGzbYzLdYLGLJkiVCrVYLFxcX8fDDD4uCggKJ0tqXXq8Xr7zyitBqtcLV1VXceeed4vXXX7d5E+5r9UlLS2tzvzNjxgwhRNfqceXKFREfHy9UKpXw9PQUs2bNErW1tRK8mu7XUX3Onz/f7n47LS3NugxHrs/tRibEdV9HTkRERES3LV5jR0REROQg2NgREREROQg2dkREREQOgo0dERERkYNgY0dERETkINjYERERETkINnZEREREDoKNHREREZGDYGNHRLedmTNn4vHHH5c6BhFRr6OQOgAR0fVkMlmH85ctW4YPPvgA/KM5REStsbEjol6lrKzM+vuOHTuwdOlSFBQUWKepVCqoVCopohER9Xo8FUtEvUpgYKD1x8vLCzKZzGaaSqVqdSp27NixePnll5GUlIT+/ftDrVZj48aNqK+vx6xZs+Dh4YG7774be/bssVnXyZMnMXHiRKhUKqjVakyfPh06nc7Or5iIqPuwsSMih7B161b4+fkhMzMTL7/8MubOnYunnnoKDzzwALKzszFu3DhMnz4dDQ0NAIDq6mr88Y9/RFRUFI4ePYrvv/8eFRUVmDp1qsSvhIjo5rGxIyKHMHToULzxxhsYOHAgFi9eDFdXV/j5+eG5557DwIEDsXTpUly5cgUnTpwAAHz88ceIiorCypUrER4ejqioKGzatAlpaWkoLCyU+NUQEd0cXmNHRA5hyJAh1t+dnJzg6+uLyMhI6zS1Wg0AqKysBAAcP34caWlpbV6vV1RUhHvuuaeHExMRdT82dkTkEJydnW0ey2Qym2nX7ra1WCwAgLq6Ojz66KNYs2ZNq2UFBQX1YFIiop7Dxo6I+qThw4fjm2++QVhYGBQK7gqJyDHwGjsi6pMSExNRVVWF+Ph4ZGVloaioCP/4xz8wa9YsmM1mqeMREd0UNnZE1CdpNBocOnQIZrMZ48aNQ2RkJJKSkuDt7Q25nLtGIro9yQS/vp2IiIjIIfBjKREREZGDYGNHRERE5CDY2BERERE5CDZ2RERERA6CjR0RERGRg2BjR0REROQg2NgREREROQg2dkREREQOgo0dERERkYNgY0dERETkINjYERERETkINnZEREREDuL/A6oYB45bbP+3AAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "env.render(td, 0)\n",
     "# Update plot within a for loop\n",
@@ -294,7 +379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -349,7 +434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [