diff --git a/deeptrack/optical/augmentations.py b/deeptrack/optical/augmentations.py
index faa2fd370..4e4927535 100644
--- a/deeptrack/optical/augmentations.py
+++ b/deeptrack/optical/augmentations.py
@@ -95,6 +95,7 @@
 import numpy as np
 
 from deeptrack import utils, TORCH_AVAILABLE
+from deeptrack.backend.core import DeepTrackDataDict
 from deeptrack.features import Feature
 from deeptrack.types import PropertyLike
 from deeptrack.optical.scatterers import ScatteredVolume, ScatteredField
@@ -462,6 +463,37 @@ def __init__(
         self.feature = self.add_feature(feature)
         self.counter = 0
         self.cache = []
+        self._cache_dependency_data = []
+
+    @staticmethod
+    def _copy_data_dict(data: DeepTrackDataDict) -> DeepTrackDataDict:
+        """Create a shallow copy of a node data dictionary."""
+
+        copied = DeepTrackDataDict()
+        for key, data_object in data.dict.items():
+            copied.create_index(key)
+            copied[key].store(data_object.current_value())
+            if not data_object.is_valid():
+                copied[key].invalidate()
+
+        return copied
+
+    def _snapshot_feature_data(self: Reuse) -> dict[Any, DeepTrackDataDict]:
+        """Snapshot cached values of the wrapped feature graph."""
+
+        return {
+            dependency: self._copy_data_dict(dependency.data)
+            for dependency in self.feature.recurse_dependencies()
+        }
+
+    def _restore_feature_data(
+        self: Reuse,
+        snapshot: dict[Any, DeepTrackDataDict],
+    ) -> None:
+        """Restore cached values of the wrapped feature graph."""
+
+        for dependency, data in snapshot.items():
+            dependency.data = self._copy_data_dict(data)
 
     def get(
         self: Reuse,
@@ -503,11 +535,14 @@ def get(
         if recompute:
             output = self.feature(data)
             self.cache.append(output)
+            self._cache_dependency_data.append(self._snapshot_feature_data())
             if len(self.cache) > storage:
                 self.cache.pop(0)
+                self._cache_dependency_data.pop(0)
         else:
             index = self.counter % storage
             output = self.cache[index]
+            self._restore_feature_data(self._cache_dependency_data[index])
 
         self.counter += 1
 
diff --git a/tests/test_augmentations.py b/tests/test_augmentations.py
index a0a785734..c96bda706 100644
--- a/tests/test_augmentations.py
+++ b/tests/test_augmentations.py
@@ -167,6 +167,37 @@ def get(self, data=None, **kwargs):
             self.assertEqual(counter["i"], 3)
             self.assertEqual(out6, 3)
 
+    def test_Reuse_preserves_take_properties_on_cached_output(self):
+
+        config.set_backend("numpy")
+
+        class ImageWithPosition(features.Feature):
+            __distributed__ = False
+
+            def __init__(self):
+                super().__init__(position=lambda: np.array([1, 2]))
+                self.counter = 0
+
+            def get(self, data=None, position=None, **kwargs):
+                self.counter += 1
+                return np.ones((2, 2)) * self.counter
+
+        base_feature = ImageWithPosition()
+        reuse = augmentations.Reuse(base_feature, uses=2, storage=1)
+        label = features.TakeProperties(reuse, "position")
+        combined = reuse & label
+
+        first = combined.update()()
+        second = combined.update()()
+
+        self.assertIsInstance(first, list)
+        self.assertIsInstance(second, list)
+        self.assertEqual(len(first), 2)
+        self.assertEqual(len(second), 2)
+        np.testing.assert_array_equal(first[1], np.array([1, 2]))
+        np.testing.assert_array_equal(second[1], np.array([1, 2]))
+        np.testing.assert_array_equal(label(), np.array([1, 2]))
+        
     def test_FlipLR(self):
 
         backends = ["numpy"]
diff --git a/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb b/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb
index 5db44ca09..97cb89b76 100644
--- a/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb
+++ b/tutorials/2-examples/DTEx212_single_particle_tracking.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -33,7 +33,7 @@
     "id": "1AeNanU2yIog"
    },
    "source": [
-    "This example trains a convolutional neural network with a dense top using simulation data and then applies it to experimental videos of an optically trapped particle."
+    "In this example, you train a convolutional neural network with a dense top using simulation data, and then apply it to experimental videos of an optically trapped particle."
    ]
   },
   {
@@ -71,7 +71,7 @@
     "id": "8L67dUQl1zt3"
    },
    "source": [
-    "Download the `particle_dataset`. This folder contains two videos with an optically trapped particle. One video is acquired with very low noise (`low_noise.avi`), while the other with very high noise (`high_noise.avi`)."
+    "Start by downloading the `particle_dataset`. This folder contains two videos of an optically trapped particle. One video is acquired with very low noise (`low_noise.avi`), while the other has very high noise (`high_noise.avi`)."
    ]
   },
   {
@@ -80,15 +80,7 @@
    "metadata": {
     "id": "lqXGxXj4yJQM"
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Cloning into 'particle_dataset'...\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import os\n",
     "\n",
@@ -100,7 +92,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Define the function to load videos ..."
+    "Next, you define a function that loads a video."
    ]
   },
   {
@@ -133,7 +125,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... use the funtion to load the low noise video and high noise one ..."
+    "You then use this function to load the low-noise and high-noise videos."
    ]
   },
   {
@@ -163,7 +155,7 @@
     "id": "peyfxNAi2IOV"
    },
    "source": [
-    "... and plot some of the frames."
+    "Finally, you plot a few frames from each video."
    ]
   },
   {
@@ -180,7 +172,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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1OrLaraedW23Riida/LKuRYtrVpmtGO95H2Ola33FqucBAwbk/nz22WdLRUWFbNy4URYsWCATJkwQkc1t3uo7Ir44ZcUN7blk3RON1desZ4pW/965oHZO61mqxQirTr3vkz06uo9B8nrLoNWHFS9LzYoF+d566y25//77zedBe1VVVeZxrdiqxS/vFnrasa1nqVUO7RkU1RzAKof1HLT6hJaeX3f55X/uuefk+eefb5PXulee9zTWeMMz97d47qvVr7Q+6H0PpbVH6zmoxQ3rGW3dVy32W9fn+bKL1b60Mlv9xLNGFiTGWPiJYOQcfvjhuQnrxx9/LDfccENBA126dKncdNNNcvHFF0s6nZaxY8fK+PHj5d133+2KIgOA22OPPSb33HOP1NXVtYlxfHMLQE+wYMECueqqqzrcP62hoUHuuusuSSQScvDBB4uIyLRp0+TBBx80J50AEDf33HNPp3mWLl0qv/3tb+X73/++1NTUSEVFhUyZMkUeffTREpQQAKKxxx57yOjRo0VE5L777st9UBgAAJSW7+P26LFSqZTst99+uf9/4IEHzNX/pUuXyssvv5z7/wMOOCDy8gFAWD755BMWEAD0WM8++2yHi6v57rvvvtx4r6ysTMaPHx9l0QCgS2zatEneeuut3P+3/mwwAHRHNTU1csQRR4jI5l8bfPHFF7u4RAAAbL26/Bus/fv3l5/85CcisvlnIL///e+LyOa9QPfff38ZM2aM9O3bV3r16iUzZ86Uv//977l/m0gkZKeddpJx48bJyJEjZejQoVJTUyPJZFI2btwoS5YskX//+98ya9Ys8ydh89100025P5977rkiIjJ8+HDZf//9Zdy4cbmfU1m6dKk8//zz8vTTTxd81Xj77beXAw88UHbccUfp37+/NDU1ybJly+SFF16QV1991VU322+/vey55565OqiqqpKNGzfKihUrctcV1v6nY8aMyX17ta6uTt54440O87/00kvy2c9+VkRExo8fL+Xl5UV9lRro6axYN2rUKNlnn31k1KhR0qdPH6mqqpJZs2bJ3Xffnfu3iURCRo0aJePGjZMdd9xRhgwZIjU1NZJIJGTTpk2yYsUK+eCDD+S5554zf1In380335z785e+9CUR2fyiad9995WxY8fmfgp32bJl8uyzz8pTTz1VEOtGjBghBxxwgOy4447Sr18/aWpqkiVLlshzzz3X5gMYQXQU695++2156KGHAl0XgK41cOBAueqqq0Rk80/HXnLJJSKyeU/QfffdV0aPHi19+vSRXr16yaOPPip33HFH7t+2jukmTpwoo0aNKhjTLVu2TN566y2ZNWuW+ZNp+W655Zbcn88++2wR2TymO+igg2T8+PFtxnTPPfecGue0MV2YcW7Dhg2ybNky+de//iWzZs0yP9gWpbq6Olm6dKlsv/32IiJt9m4FoBswYECbMd1///d/i8h/Yt2YMWPaxLo///nPuX+bSCRk9OjRMnnyZHX+unTpUnn33XfliSeeCBTrbrvtttyfzzzzTBHZPEZrjXX9+vUTEZElS5bIs88+K08++WRBrNthhx1k2rRpMnLkSBkwYIA0NTXlYuMrr7ziqpsdd9xR9t5771yc7dWrVy6Gv/nmm/LSSy912Yfc8uvT+okzAP/Rr18/+e53vysiIqtXr5af/exnImLPX++9997cv00kErLjjjvKhAkTZMSIETJo0CCprq6WZDIpmzZtkiVLlsi7774rTz75ZKBYd8MNN+T+fN5554mIyLbbbiuf+9znZPTo0blx3bJly+TJJ5+UJ554oiDWDR8+XPbbbz/ZfvvtpV+/ftLc3CzLli2TF198UWbPnu2qmx122EH22msvGTdunPTr108qKytl06ZN8vHHH8u7774rzzzzTKSx7qijjpJevXpJc3NzoG/yA7D1799f/ud//kdENo/rLrvsMhHZHOs++9nPyk477ZSLdf/85z8L1iVGjhwpo0ePVsd1y5Ytc8W666+/Pvfn888/X0TsdYkXX3xRnnnmmUDv6hYtWiTPPPOM+8MY1ru65cuXy7///W954oknQluXALqzLl9gbS+VSslJJ50k+++/f6f5rrjiityksb2+fftK3759ZeLEiTJjxgz5wx/+IM8995yrLIcddpgcc8wxBb8PPXLkSBk5cqTsuuuu8pvf/Eaam5slkUjIKaecIgceeGCbvBUVFTJ69GgZPXq0TJw4UW6//fZOfwO/qqpKvvjFL8ruu+9e8Hd9+vSRPn36yJgxY+Swww6TW2+9VV577TXXdWnGjRuX+/PcuXM7/anMBQsWSENDg1RUVEh5ebmMHDlS3nvvvaLLAWwtgsa6ZDIpl19+uRnr8mPCIYccIn/961/dH+Y4/PDD5fjjjy+IdTvuuKPsuOOOsuuuu8qvf/3rXKz7whe+UFDuiooKGTt2rIwdO1YmT54sN998c2ix7tBDD5X//d//dS9oAOhaqVRKvvjFL8pBBx3Uab5f/OIX6l57Iv8Z040fP16OPvpoueWWW9xjus9//vNqnMsf0+XHuS9+8YsyderUNnnDjnP513XUUUfJrbfe6o7fYYty3x6gp0qlUnLyyScHmr9eddVVnca6CRMmyJFHHim33XabvPDCC66yHHHEEXLCCScUxLpRo0bJqFGjZLfddpNrr702F+tOP/10NdaNGTNGxowZI5MmTZJbb72101jXq1cvOeuss2TKlCkFf9c6phs3bpxMnz5d/vznP8vrr7/uuq4wDBkyJPfnVatWlfz8QHeXSqVkxowZss8++3SYL5lMymWXXWbu91pbWyu1tbUyfvx4OeKII+T22293v/Q/5JBDZMaMGQWxbocddpCzzjpLdt99d7n66qtzse7EE0+Ufffdt03eiooK2WmnnWSnnXaSCRMmyJ///OdAse6MM86QPfbYw7yunXbaSaZNmyZ33HFHp19c2BLjx4+XnXfeWUREnn76afnkk09CPwewNUulUmrMaC+ZTMqPf/zjTtclio11Rx99tDmH3WWXXeT666/v9F3d+PHjZfz48bLLLrvITTfdFMq7urFjx8rhhx8e2roE0J3FboH1xBNPzAWDhQsXysKFCyWTyciQIUPaBIBEIpELYvX19bJkyZLczz6m02np16+fjBw5Unr16iWVlZXy9a9/XTKZTOBgtv/++8vxxx8vIiKLFi2SRYsWSUtLi4wcOVKGDRsmIiKTJk2SU045Rf74xz/KaaedJgcccIC0tLTI/PnzZfny5blvY2yzzTYisnmPhCVLlsjjjz9unre2tla+9a1vydChQ3NpS5culUWLFklDQ4P07t1bRo8eLTU1NVJdXS3nnXee/P73vy/6J0Hyz7dgwYJO87e0tMiyZctkhx12EJHNE1YWWIHg8mPdkiVLZPHixZLJZGTQoEFtYl0ymWwT65YuXSorV66U+vp6SaVS0rdvXxk5cqRUVVVJRUWFnHHGGZLJZAK/uDrggAPkpJNOEhGRxYsXy+LFi6WlpUV22GGHXKybPHmynHrqqXL77bfL6aefLvvvv7+0tLTIggUL2sS61m8+TZkyRRYvXiyPPPKIeV4r1i1evDgX63baaadcrPvmN78pN9xwg3tRBUDXOeWUU3KLq61jqUwmI4MHDy4Y07UuOLR+o7KjMd15550nzc3N8tJLLwUqx4EHHpiLc4sWLZKFCxfmxnTbbrutiBTGuQMPPLDDMV2xcW7Dhg1SW1srY8eOld69e+fGdP/7v/9b0p95S6fTMmjQoNz/r1mzpmTnBnqK/DFda6xrbm6WIUOGtPlWQTKZzMW6IPPXr371q5LJZAJ/wOzAAw+Uk08+WUT+M49uaWmRUaNG5WLdzjvvLKeddprceuutcuaZZ8pBBx0kLS0tMm/ePFm6dKkkk0kZPXp0Li5MmTJFlixZ0uF+pbW1tXLppZfmziGyeUy5aNEiqa+vl9raWhkzZoz07t1bevXqJeecc47cdttt7m/HFqP1w86tolj0AHq6o446Kre42tn8tXVxtb6+XlasWCGrVq2ShoaG3N8NHz48F+vOPfdcyWQygWPCvvvuK8cdd1ybcmSzWdl+++1zY66dd95ZTj/9dLnlllvkrLPOkn333VdaWlpk4cKFsmLFity3zlrnr7vvvrssXbpUZs2aZZ63trZWLrrootwcufX8y5Ytk8bGRqmpqZGRI0dKTU2N9OrVS84++2z54x//GOqH5yoqKmTGjBkisvnXYp544onQjg1gs+OPPz63uNr6jkybw7Z/V9fZuG5LYt2xxx4rIva6xMSJE+Xkk0+WP//5z3Lqqad2+q5u7733lkWLFslDDz1knrejdYnWcd1OO+3UZg4bxrpEewMGDJB9991XBg4cKOXl5blvzr7//vuyevXqUM8FFCvwAmvrz8e2l0z+ZxvXsrIyqaqqkoaGBjVvbW1tQVr+NyX79u0rBxxwgKxatUr+8Ic/yIcffti2sOm0pNObi5xKpeT555+XF198UebOnVvwlfjW/AceeGDuk21f/vKXZd68eerLo/Y/b3vyySfL2rVr5frrry9YODz88MPl1FNPFZHNAW/FihVywAEHyPLly+XWW2+VpUuX5vImEgmZPn26HHLIISIicuihh8ojjzyiljeRSMh5552XC2Lz58+Xu+66S5YsWdKmzGVlZXLkkUfKMcccI8lkUs444wx57733cp9c044tsvnTdu3V19eLiMjgwYNzaStXrlS/wdq+jj755JPcAuugQYMK/k0mk1GvUVNeXq6maz/tbP0UsXaM/PaZr7UdtWfdF01ZWZmarv3En/XpIO1aqqqq1Lyt9yrIsSsqKtS8Vn1oP1VhlUOrD+v6ampq1HStD1r3pNSsOspPT6fTUllZaebV7lV+22qNdatXr5abb75ZPvroozZ50+l0m/7z3HPPyQsvvCBz5sxR22hFRUWbWHfyySfLm2++qd6X9mU+9dRTZe3atXLzzTcX7Nl38MEHywknnCAiIvvtt5988skncuCBB8qyZcvk1ltvlSVLluTyJhIJOeaYY2TatGkisvnbYk899ZT600iJREK+9KUvFcS6xYsXt+kT6XRaDjvsMDnyyCMlmUzKOeecI8uWLev0Wwee2JP/ScD8PGVlZQUx03q2tf80oYjdjqyfT9HKZ/1cqHZs63xWH1y3bl1BmhVbrWN7fl5Pa7fWLyVY59Pqw1s2rW14WHVkPXe1uBaXbwhqY7L8tpxKpXLP1aBtI//a+vXrJ9OmTZOVK1fKDTfcIO+//36bvOl0Wpqbm3Ox9Nlnn5UXXnhBPvroIzWGptNpOeSQQ+SEE06QdDotX/rSl+Stt96ShoYGs/5btca53/3udwXx9pBDDsktvraO6Q488EBZunSp/OEPfyiIcyeccEKbOPfII49IY2NjwZggkUjIWWed1SbO3XnnnbJ48WIR+c/4pnVMN2PGDEkmk3LmmWfKwoUL28Q5K/ZofcIaT2l9JZvNyh577JF73re0tMgHH3ygxjQRPdZZn9i2fhZPGzt5nqXWWMFK18Y31vjNqmctblj1rD13O2uf7WljOCt2Wdet/ay+VWaNdT5rfKnF8zjsdW61rfz7lM1mpaWlxWwX2lwkvy779u0rBx54oKxatUp+//vfq/PX1nl06/z1pZdekg8++EBtG8lkUqZOnSrHHnuspNNpOfPMM+Wdd95R22f7+3TaaafJ2rVr5cYbbyyIuYcddph84QtfEJHNY7qlS5fKQQcdJEuWLJEbbrhBFi1alMubSCTktNNOk4MPPlhENs99H3/8cTXmJBIJ+frXv55bXJ0zZ47ceuutucXdVmVlZTJ9+vTc/PWUU06ROXPm5GKdNSbo7FeV8rXvf5WVlTJ06FDZc8895YADDsi1h5deesn8poV2PqttWGMs7RhWXPX8NHxn3zbJZ403rT6hldkzZrLKZr1DWrt2beBjW3Xk2Z5IuxbruNZ1x/lnpQcMGKCm5z8jKisrpU+fPuY4VLu+/HbRp08f+exnPytr1qyRm2++WebMmVNwrtb8LS0tuVi3cuVKNdY1NjbK/vvvL9OnT5dUKiVnnnmmzJs3T22j7Z8nJ510knz66ady8803F8TcadOm5b4occABB8iaNWtk6tSpsnz5cvnTn/6kvqtr/TDgwQcfLE888YQ6/kgkEnL++efnFjXy56/5Y410Oi1HHHGEHH300ZJMJuXkk0+W9957LxfrrPa1cuXKgjTtG8DHHntsbjufP/3pT7l/1/rzy62SyaSUlZWZ99uz/Y4V67T7aj37tf5qjSms82lxw4ox1rsz7bo9fcIzRhbR38F65roi+jPIakfaOzzvHF87dpAt90rB+gWQ/HuYSqWkrKzMLHNn4/q+ffvK/vvvL6tWrZKbbrpJHde1PvNaWlpyc9jZs2erxx44cGBuXJdKpeSMM86Qd955J9Bz98QTTwwU6z73uc/JqlWrZP/995dly5bJzTffXDCHnTFjhhx66KEiIjJ9+nR5/PHH1XabSCTk7LPPzs1h582bJ3fccYcsXry4zbfly8rKZMaMGXLiiSfm1iXy57Ce99f57Tb/Xh599NHqMURE3n33Xbn33ntz7zA971i86xKe8ZfWr6w+6JnHae9uRHzvDD1jMmv+asUNrS1ZzwOr/rXY37t3bzWvVqfW2Ncax2vvRD33ur1QVzR23nln82Eo8p/G+uijj8qnn35a8PepVEoaGhrkV7/6lXz88ccFf9/c3JxrgJlMRv74xz+KiH1zmpub5fHHH5dEIiHHHnus9OrVS/baa68Ov23QKpvNyi9+8Yvci7B8M2fOlF133VUmTJiQ+5nPdevWyXXXXVfwIiebzcrdd98tkyZNkqFDh0plZaXsvPPO8tZbbxUct/V3zUU2B7Hf/va3amdpamqSf/zjHyIictxxx0llZaUceeSRcuutt3Z6XZb8jqY1Mk1+PqujAj3RxIkTpbq62ow9rQOjhx56SH1Y5cc6bTKVP9jKZDK5/bW8se7JJ5/s9Fqy2awZcx9//HGZOHGijB8/PvczKevWrZNrr71WjXX/93//JxMnTpQhQ4ZIZWWlTJo0Sf103l577dUm1v3mN79RY11zc7M8+OCDuclvZWWlHHrooW32bQQQjUmTJuXGdNYkPpFIyIMPPthhnPv5z38uy5cvL/j79nGuszFMc3OzPPzww5JIJOTkk0+W6upq+dznPtfhNw1aZbNZueqqq2Tp0qUFg//HHntMJk2aJBMmTJB0Oi0nn3yyrFu3Tq666qqCQXo2m5W//e1vMmHChNyYbpdddjHjXOv2C/PmzZPrrruu0zHdscceW9I4V15envtUtIjI7NmzY/MCBSiVyZMn5/bK0rS+YHjggQc6jHVXXnmlOaZrnQNnMhn505/+1Oa4Wv5HH31UksmkHH/88VJdXS377LOPPPXUU51eS2usy3+p1uqRRx6RSZMmyaRJkySdTssXv/hF+fTTT+WKK64o6Pf589fWMd3kyZPlX//6V8Fxp0yZIhMmTBARkY8++kh+9rOfmbHunnvukfLy8sjGdEcccUTum12aTCYjjz32WC7mAluT8ePHdzh/bY2BTzzxhPo+qDXW3XjjjW0+kNGq/biuNda1Lga2l8lk5IknnpBkMpnbT3TKlCmBfmaydf6q/TTuP//5T5k4caKMGzdOUqmUHH/88bJu3Tq5/vrr1fnrPffcIxMmTJDBgwdLZWWlTJw4UY11e+yxR+D563333SepVEqOOuooqayslMMOO0z+8pe/dHpdnRk9erTst99+IiLy4osvFnyQBsB/3tVZ46zWBZTO5rBXX311mw9ktGpubs7NJ/Pf1Vnz5dZxXSKRaDOue/bZZzu9ls5i3aRJk2Ts2LGSSqXk2GOPlfXr18vVV1+txrq//vWvMnny5DZzWO1XKPfYYw8ZO3asiGzePvDaa681x3V/+9vfpLq6ukve1Y0fP17Gjh0r999/f5v9v4GuEuoCa+veLp15/vnn1QVWEZFZs2blfrIjLC+88ELuBdK4ceMCLbA++eSTajBt9corr+QmkyIiDz/8sLlhdTablVdffVWOOuooEdm8L4S2wJq//81dd93V6SdaH3jgATnssMNyAfq2227b4tX2/E9nBf00aH4+69NnQE+0ww475L693ZFnnnnG/IT2E088IR9//LH5Qm9LtI91QRZYn3rqKVm6dKn56alXXnlFxo8fn/v/mTNndhjrZs+eLUcccYSIbK4nbeGh9RsRIiJ//etfO411jzzyiEydOlV69eole+65p9x5551FfbIIQOda92DuzNNPP23Guccee0xdXC3GM888k/sJzAkTJgRaYG2Nc5aXX365zZjuoYcekvXr16ufxMxms/LKK6/kPlG74447dhrn7rzzzk7j3IMPPiiHHnqoVFdXy5QpU0oS50455ZTct14aGhpYdMBWqXUPq8489dRTZqz75z//KStWrDC/wbIlnnvuudw3E8aPHx9ogbWzWPfCCy/IpEmTcv9/3333mR+qaJ2/Tp8+XUQ2xzpt0aH1G/0iIrfeemtsx3RLly6Vm2++WV0YArYG22+/vWy//fad5nv55ZfND9w/99xzoe/3+dJLL+Xek40ZMybQAuvTTz8ty5YtM+evr776au5DbiKbv+DR2fz185//vIhsrict1rV+y1Uk2Pz14YcflqlTp0p1dbXstddecscddxT3zZh0Wk4//XRJJpOyYcMG+dvf/rbFxwJ6sqDv6jqawz7xxBOyYsWKUMv1/PPPtxnXBVlg7SzWvfbaa7nFUJHNc++OYl37Oay2wJof6+64446Sj+uy2awsWLBA3nzzTfnggw9k+fLlUldXJ+Xl5TJo0CAZP368TJ06VXr37i3JZFJmzJgh9fX1gcbJQJTi8ZuceYLuMZMvkUjIiBEjZLvttpO+fftKZWWlOcHdbrvtAh2zs99Eb//J4NmzZ3eYP3+y2/rb5/lqa2tl+PDhIiKybNmyDifHrZqamuSjjz6SXXbZRaqrq2W77bbb4klj/lemg/4UU34+6yvXAHRbsu9Ua6wbPny49OvXLxfrtA+kBI11nU1ii4l12s9V1dbWyogRI0QkeKxrbm6WuXPnyqRJk6RXr14ybNgw9dsZAOJlS/ZhSSQSsuOOO8qIESOkf//+UlVVZY7pgrwoFJFO975qH088cdEa0+XHuSDxqqmpSebNm1eyOHfggQfKZz/72dz/33333aG/NAW2FkH3g85njem0l1Ktc8TOdBbr2s8TPfPdzuavS5YsCTQPjXJMN3/+/Nx+hMlkUnr16iXbbbedDB06VIYNGybf/e535fnnn5e//e1vrp+XBbDZ66+/7v43iURCtt12Wxk6dKj06dNHKioqJJVKqe+c8vdx7ohnPirSebmXLVuW+7M1f22dW3vnr5MnTw4l1k2fPl2GDBkiIiJ///vfXT/xC8BnS9clRo4cKTvssIP0799fevXqJalUSv0yUtBxXWexLj92iXS+v3yQcV1rrFu6dGmgmBX2uO4f//hH7lek8p8T9fX1snDhQvnggw/kySeflG9+85u5D4Mff/zx8u9//7vTrcSAKIW6wHrPPffIPffcY/699ZvRrZqbm10dMZlMykEHHSTTpk0z94Bqr6OfMM7XWTnyfzZu06ZNsnbt2g6/xZk/ANJ+Fz//WyJlZWW5T7a0svaFGjRoUO7P/fv33+IF1qamplz5g+6FmZ/Ps38M0N09+OCD8uCDD7r2jcu3JbFu6tSpcvDBB5v7TrQXZazrKEbkxzpt35L8XzkoKyvL7fHayvopl2222Sb35379+rHACkTs/vvvl/vvv19E/Hv3iGyOc54xSTKZlGnTpskhhxwSepzTtnvIlx+3WuNc0PzamK59nDvxxBML8mjjpvyJbpRxbvLkyW3K9Pzzz8szzzwTybmAuLv33nvl3nvvNT8s2tlCXHNzc6cxJl8ymZQDDzxQpk6d2qWxbuPGjbJmzZoO43j+GFAb0+V/87esrExOP/30Nn+vLRaXlZVFNqZ755135J133ilIHz58uJx66qkycuRI2W+//WT77beXK664otPxOtCTzJw5U2bOnGn2+c4+MN/c3FzwMr8jrbHu4IMPVvcS1QTddso7f/3000873Ie8s1iX/204bf6qjemSyWSbWNe/f/8tjnXbbbedHHbYYSIi8v7772/RBxiBrUXruzrvPtuttuRd3bRp02Tq1KnqoqUmqnd11i+FtupsDpsf68rLy+Wkk05q8/fauKmysjLUcZ21j2a+Tz/9VK655hr5yU9+IjU1NZJOp2XatGly1113bfF5gWIVvcCaP0BLpVJSXl5uBiwtPT9t48aNuUmstVjZ+gmGdDot559/vkycONFV3oqKCnVxoP2AMpvNSlVVlTnQzP82RX19vZSXl5sBvP350ul0wQAv/5NyAwcOlP3337/jC1EMGjRI+vXr1+m+Gvla67+hoSFX51VVVWqwbb/Im3+PGhoaCo6v3UPrpwKsnzHQvrWilU1E30DeaovWfdWCubXgYy0yafmtvNonN70bbgd5ALWyHrjWzyAGZX3r2fpggFYfcdn3TWtHIm3vSyKRkFQq5dq0O7/Nbdq0KVcHne3jmk6n5Wtf+1qbn68MoqKiQj12+7T6+npJJBLm/c5Pr6urk2Qy2eF+Fvl9Tvt2bf4Ee0tjXev+QR3tX9ae1Qetb8Ylk8mCv7PasxZbreNqk/aO8gc9hlUX1othrT68P22oPfOs82nPAyumWc9Srf692wlobcN60aTVkVXPFu3YcflAkjZBsq7Peu62v5b8622dwHX2M+gtLS2STqflm9/8ZpufrgyisrJSKioqOv3ljWQymXtpp9V/fjvatGlTLo4FebYlk0lpbGxsU3f5LwgHDhwoBxxwQICraSt/T0jPwk9nz+7Ro0fLV77ylVx/f+ONN+S2225rU37rGFr7sO6vFeu0Y1ixQHtJYT13rdjT2fM4nxUDtVhgjb20Y1t1ZI17tHJY9WnNl7T+bdWzdr+ttm+1jbjEtfaCjGWz2ay0tLS4noH5bWLTpk2STCY7jHX5Y7rzzjvPPX9tjXXtte9P2WxWKisrzVie3z7r6+s7/NWnlpaWgjFd++Pmf3h60KBBbX4aPajWGN7R4kd7nrluNpuVJUuWyDXXXCMXXnhh7hcSvvCFL+T2iMynLfBY4z8r7njinFb/1vzVas+dvWPJ54kl1jfktBfDVvtfvXq1mq5dd2dzoiDlsGix2XoWWPFMu4edvagvlTVr1qjp+W2mNdZZz1GtDeTPi+vq6nJ109lzNJVKyTnnnNPmZ3qDqKioUN8LaePQqqoqs/7z+2Dr89C67nQ6XRDr2r8PyF88KHb+ai0iWzEikUjIWWedJalUSpqamuTvf/+7Wh+JRKLgfUUikVD3BhfR+4/VBz19xfP+zXpWWWMsLW5YMcZ6p9P6LeB8VtvQrs8qs+cDO9Zz13rWaONh6/mjjd+sOrLej2gf/rL2Ui41q43m12l5ebn07t3bfGZq9zu//23atCnXXjuLMcWsS2j9uP1zt/VdXZAxfH19vSSTyQ4/LJNfT2VlZQXHzb/3AwcOlAMPPLDD69C09j3r/YE2DrF+ll5rz/nvE59//nk59NBDRUTM96VaO7DGLJ6xqEXrV1Z/9fyaitUWrS8yajHJmntqsc6qC+uD6PnPyVbWmNNqo9q98ozBrXmxNUbSnoOe9ZX2YvUTwZ7J+VFHHZULYi0tLTJ79mx5/fXXZcmSJfLpp58WvOy64YYbRKTzF31bIox9Y6yG51HMtW3YsCHXMTv7pnGr/IdsMY0Q2Np4Yt0RRxyRGyy0tLTIa6+9VhDr8h/i1113nYhEE+vCYA20POJ6bQD+wzNhOProo3OLqy0tLfLKK6/Ia6+9JosXL5a1a9dKU1OTZDKZXKy76aabRCS+scB6qeMRxbWNGDFCzj///NyE6b333pPf/e537g8OAPgPT6ybPn16m/nra6+9JrNnz24zpst/eXj99deLSHznr2GM6cLct7YjrQsTF198sYiIfO5zn5P/+7//Yw4LBOSJdYcddlhucbWlpUVef/11eeONN2Tp0qW5WJd/vBtvvFFE4hvrOvqluqC29Nr222+/3LYTjz/+uHz88cexHf8CPYHnXV1H47rWOWz+Qtctt9wiIvGdw3b1uoTXhx9+mFtgHTRokKRSqdh88Albn1gtsAaVTqdl6tSpuf+//fb/v707DfZsu+v6/z19zukzDz3dIQMJIQkJkwVCZCqmAksiQqEkIIgIVYyCCg+grNLSskpLHiHi3yotiYkiiAIClpaFSBnAyBDGJIQQCJCE5N7b3Weez+k+/wep2/a9+/Pu7C99+ty+8H49Iot1928N3/Vda+/d3fvf3fPbN2dxIHrQ7j5gvu1tb6s3vOENz/j/p7f2Y/8p3zGefPLJesELXlBV+U8sJXf/s8xPPPHEmbVF0odMTU0940+NvelNb3re57q7c9lv/uZv3nlR8jQf9Et/ukxNTT3jbz294Q1vqLe85S1Y//mW537913/9zkuSu53lGW6MF7zgBfW3/tbfuvNC5Pd///frX/yLf/Fh//avpLMxNTVVn/u5n3vnf7/pTW+K/8zj0y8cn2+57td+7dfq+77v+57x/08P6p7Lv+38nve8586/2jQ1NVUf+ZEfWe94xzues/ZIfxJNTk7WZ37mZ9753z/wAz9wz+8ZPh9y3d156+1vf3u98Y1vfMb/P/2NnrP6wyNPfw+xqurjPu7j6tWvfjX+Lb67/1W8V73qVfWt3/qtd8553/d93/dh//lQSeM9+1z3xje+8Z7/fPdZvLx80J79XuL7v//78f//tLP4Qyx/XM/+m68LCwv4t2GlB+15+YL1Iz/yI+8kpz/6oz+65wuHqvyh+ofN3X9Ve+zfID1Ld78gffpPyN3LhQsX6oUvfOGd/935HoekcV7ykpfcyXUf+MAHPmyuG/uHI55Ldx94notcJ+nhcveZ7v3vf/89X65WPT/OdHc/wHoY/kmtRx99tP723/7bd/4ZnPe///31fd/3ffhP7kg6ey996Uufcf/64b6h93w70z0Mue7DOT09rf39/TsvdMZ+71HSeB/xER9xJ9d98IMfvOfL1arnx7nu7n+2+Lm8f33xi188uu7i4uIz/vnD8/6DfdKfdN1znbnu7D37n7Ht/EsL0ll7OP9e+odx9w3cmI8nv/zlL3+QzTkTf/iHf3jn/37hC194Jv/2d8e73vWuO//3y172sg/7J+5e8pKX3Lk5PTo6qve85z0PtH3Sn0Z3f19gTK77qI/6qAfYmrPxB3/wB3f+7+ci10l6uHTz3Cte8YoH2JqzcfeZ6EUvetFzmueuXr1a3/Ed33Hn7PzEE0/U937v9/rPYkrn7E9irrv7TPfiF7/4oT/T3f097ir+xqikP767n9WN+UP4z4dc9973vvfO//2CF7zgoc91kh687rnula985QNszdm4O9c9H57V3f2Xvg4ODlrfQpbO2vPyjzHd/VfQP9yCn5iYeMY/UfKwWltbqyeeeKIee+yxmpqaqj/35/5c/dzP/dy5/f673vWu2tvbq/n5+Zqbm6tP+IRPqF/7tV/D+p/2aZ925/9+5zvf6Z8UkR6Au/+53DG57tM//dMfdJPu240bN+qDH/xgPf744zU9PV2f9mmfVm9+85uf62ZJeo50z3Sf9Vmf9aCbdN+uX79ef/RHf1QvfOELa3p6uj7zMz+zfuZnfubc27G6ulrf8R3fcedvwt28ebO+93u/9xn/aoqk89E9033GZ3zGg27SfXv2me6zPuuz6qd/+qef62ahj/mYj6np6ek7/9t/gUk6e38Sn9Wtr6/Xk08+WY8++mhNTU3Va17zmvr5n//5c/ntH/zBH6wf/MEffEZZ+sbh5ORkffmXf3l98id/clVVvfWtb60f/uEfrhs3bpxLO6U/bbrnurs//fWwWltbe0au+9RP/dT62Z/92ee6Weg1r3nNnf/73e9+93PYEqnxgnXsPykxMTGB3wRI5XcnpdPT0zv/m/4d79PT07p+/fqd//3KV76yZmdn459UmJ6ers///M8f/FMa6d8+f/Z3/55uK/Xl2d+sOjk5wX9qbXp6+hn9OT09jeP55je/ub78y7+8qqq+8Au/sH77t3/7njd+d//e8vLyh/23xlO/7/6bqv/n//yf+oIv+IKqqnrta19b73znO5/xvYmnb0gff/zxZ7xgffOb3xzH6e4b2KfRd3doQ+p8kyPFAH1gm+Y1fRCb6nY+3k1/Izj9Hn2Um35vfn5+UNZZg1X5n3+gdqTvtaU2VPH3NNPvra+vx7rnbez36E5PT3FeU7+fPZ5P/+975Zgnn3zyzv9+xSteUZOTk7W/vz+oe3BwUK997Wuf8Y2WqnH/RMbT7aD5vrv89PS0Tk5OsN8p/6f+/dRP/VR9zdd8TVVVfdEXfVG9+93vHv2Qa0yuS785Zk1QnbNEY9f5Z5vGxNfT6E/xpZxLOYbydlorFHOp3zQWz+X32f64OvvBw9K/9E8jPntOnl4T9Lcdn93vu+NwYmLiGecAWl93n+k++qM/uubm5vBvFaUz3cnJyYf9dvMfd53TdZ+dF2/dujUYu//23/5bfcM3fENVVX3Jl3xJveMd76j3v//992zH0+tnTJ6rynnj6TFfXFys7/iO76hr165V1Ye+D/Y93/M9z9hrab/rfDeMxpPOxCn+aZzTuqLr0jWe/ubs3Sgv0reRUpsp56azL40R5YI0/tQ/ukbqC53V0j0X9a8zVw/D933HnOGnp6drfn4e5z+ts7vL7s51tHZOTk5qbW3tzv++1/3r5OTk6PtXys10prg7Bp79tzmf7fDw8BnjNDExEa/70z/90/XVX/3VVVX1pV/6pfU7v/M7d/4mR/ou4d1/4+PuXEfrMsXR0+O9sLAw+m+hzs/P11/+y3/5zv9+73vfW/v7+4Mcke49KY7ozJPqd+5Ju98zS/W7/xxoWttLS0uxbpoTmge6l09tpnGm8Uht7lyD5oT63dmTztuY+5wLFy7U1NQU5uYx+/PT/5vGbmZm5hnnl4/6qI+qhYWFuL5v375dX/AFXzDIdWPuGZ7+32Nj4/bt25if5+bmnhGnFy5ciPfbP/3TP11f9VVfVVVVf+Ev/IVn3L+ma9899nfnOvpDbun5SGpHVV5vU1NTz5jD4+Pj2tnZwTyfYubufx702ddO0hrs1KW8Qf1O96/UP9pT0vhTnkq/R+cjOo+lGKXzBsXo3eeHp9EaTP8MLZ3dxt7fURueCxQzd/fx5OSk9vf3z+RcR/NdVc/4wwuvfOUra3FxMcbd6upqfc7nfM7gU3wpZp4dzx/uUwbPvu9I9yH3+r2UB/73//7fd95LvPa1r63f/d3fvZPr0rnu0UcfvfN/Ly0t3VljtAbTPe7T/5z5xYsXn3G2SvdxT8fA53/+59fLXvayO+W/9Eu/dN/fgz2LvziW5oDiiNqbrkF7N7W5c3+X1gr9E9H0eylv03seuidN+ZniKLWDcvnd9x53S98lv5/vpz8v/4ng9773vXcS/Pz8fH3913/94LsvU1NT9drXvra++Iu/+KE5+H44v/qrv3rnn+qdm5urb//2b6/P+IzPwAmenZ2t17zmNfUd3/Ed9RVf8RX3/fs/9VM/dWeTfeSRR+rrvu7rBoH/ghe8oL7xG7/xzoL/nd/5nfqt3/qt+/5tSUPve9/77jwMn5+fr2/+5m8ebA5TU1P1pV/6pfX617/+efNPYvziL/5iO9d9yqd8Sv2dv/N36vWvf/15NlXSA/bsM9298tzrXve6502ee8tb3lLveMc7qupDee7v/t2/W5/zOZ9zzzz3qZ/6qfVd3/Vd9df+2l+7r9+em5urb/u2b6vHHnusqj50s/K93/u9/i0G6Tn07DPdN37jN+L965d8yZc8b+5ff+mXfqne+c53VtWHcs93fud31md91medy5nuq77qq+rrv/7r62M+5mPu+QLzYz/2Y+s7v/M76/HHH79T/pM/+ZP39duSsg9+8IN3HlrOzc3V137t1w4e1E5OTtYXfdEX1Zd+6Zc+b851b33rW+t3fud3qupDeexbv/Vb69M+7dNGPat7+mWFpD85nn2uo/cSf/7P//l67Wtf+7w51/3qr/7qM3Ldt33bt90z183MzNQnfdIn1d/8m3/zGX+Q7Y/jy77sy+rrvu7r6tWvfvU9/xDUX/2rf7Ve97rX3Sl7z3veU29961vv67el+/W8/SeCf+InfqK+9mu/tqo+9M/9/MN/+A/rPe95T62trdXCwkK98pWvvPOnPf7jf/yPd/621MPs9PS03vCGN9S3fuu31otf/OKam5urr/iKr6gv+ZIvqfe85z21ublZt2/frvn5+Xr00Ufrscceu5PkfuVXfuW+f393d7e+//u/v77lW76lJicn66M/+qPr7//9v1/vfve7a2dnpy5fvlwvf/nL7yS69fX1etOb3nTfvyspezrX/Y2/8TeqqurjPu7j6p/8k39Sv/u7v1s3b96sxcXF+uiP/ug7f+LrjW98Y33TN33Tc9jice4n1/3qr/7qff/+8vJyffM3f3NVPfNP7V29evXO//2Zn/mZ9Qmf8AnP+O/W1tbqn/2zf3bfvy/p/zk9Pa0f//Efr6/7uq+rqg/luX/6T//pnTy3sLBQr3rVq+7kuTe96U31jd/4jc9lk0c5PT2t/+//+//qu77ru+olL3lJzc/P19d8zdfU6173uvq93/u92tzcrNPT0zt57vHHH7+T5375l3/5vn77K7/yK5/xN0I++MEP1md/9mcP6qU/xfrkk08+J/+csfQn3enpaf3X//pf66//9b9eVR+6f/1H/+gf1Xve8547Z7q7719/6Id+6M7572F2enpa/+pf/av69m//9ju57qu/+qvrr/yVv1Lvfve7a21trU5PT2thYaEef/zxeuELX3hmZ7qJiYn6xE/8xPqkT/qkOjg4qA984AN18+bNOjg4qMnJyVpeXq6P+IiPGLzc+c//+T/feXgo6Wydnp7W//yf/7O+7Mu+rKqqXvWqV9Xf+3t/r37/93//zrO6l7/85Xdy3Q/+4A/eOQM+zE5PT+vf/bt/V9/0Td9UL3rRi2pubq5e97rX1Rd90RfVe97znlpfX8dz3Vncv0p6uJyentZP/uRP3nnX8OpXv7r+wT/4B/X7v//7d851r3jFK+7kuh/90R+tr/zKr3wumzzK6elpvelNb6pv/uZvvpPrXv/619df+kt/qX7nd37nnue63/iN37iv375w4UJ94id+Yn3iJ35iHR4e1gc/+MFaW1urg4ODmp6erqtXr9aLX/ziZ/yN46eeeqr+5b/8l/f1u9JZeF6+YK360D9n+8gjj9Rf/It/sao+9CcrPuZjPuYZdY6OjurHfuzH6ld+5VeeFy9Yqz70zzR8z/d8T33pl35pffqnf3pNTk7W3NxcfezHfiz+N0dHR8/4GPX9eOc731n/+l//6/rqr/7qWlxcrJmZmfq4j/u4Qb33ve999cY3vnHUP2En6Y/vLW95Sz3yyCP12te+tqo+lOuevSaPjo7qB3/wB+sXfuEXnhcvWKv++Lnufe97333/9tTU1OCfU3625eXlwQM5+mdmJN2fn//5n69HHnmkvuiLvqiqOM/90A/9UP3iL/7i8+IFa9WH/uDaP/7H/7i+4iu+oj7rsz6rpqaman5+vj7+4z8e/5vDw8P6wz/8w/v63Wf/84avfOUr65WvfOWo//a3f/u3fcEqPSD/9//+37p27Vp94Rd+YVV9+PvX58ML1qoP5brv/u7vrte//vX1mZ/5mXdy3Z/5M38G/5uzONPd/c+lzc7O1ste9rJn/HNxz3b9+vX64R/+4XrHO95xz39GT9L9+ZVf+ZW6cuVKfe7nfm5VfehvOL3qVa96Rp2jo6P6kR/5kXrrW9/6vHjBWvWh+9fv+77vqy/+4i+uT/3UTx19/3q/5zpJD6e3vOUtde3atWc8q3v1q1/9jDrHx8f1kz/5k/Xrv/7rz4sXrFUfynX//J//8/qSL/mSZ+S6B32uu9vMzEy99KUvrZe+9KXx/3/79u365V/+5fqhH/qh2t/fb32ySXoQnrcvWKuq/st/+S/1tre9rT7/8z+/PuqjPqoWFxfr8PCw1tfX67d+67fql37pl57xba/ni+Pj4/pP/+k/1U//9E/Xp3zKp9QrX/nKunbtWi0sLNTExEQdHBzUjRs36n3ve1/99m//dr3jHe84039a5W1ve1t993d/d73mNa+pj//4j68rV67U3NxcbW1t1RNPPFG/8iu/Um9961s/7DfPJJ2NH//xH6+3v/3t9dmf/dn1ile8opaWlurg4KDW19fr7W9/e735zW9+xvdany/G5rr3v//99a53vat+67d+63nzz0hJ6vmxH/uxetvb3laf93mfN8hzb3vb2+pnf/Znn7dnun//7/99/ff//t/r0z/90+vVr351Pfroo7W4uFgTExO1v79/J8+9/e1vr7e97W3mOelPsJ/8yZ+sd7zjHfXZn/3Z9fKXv/wZ96/veMc7ntf3r//hP/yH+h//43/Up37qp9arXvWqunbtWi0tLdXExETt7e3VU089VU888cSZnene8IY31M/8zM/UK17xinrpS19ajz76aK2urtbMzEzdunWr9vf3a21trd773vfWb/7mb9Y73/nO+/4+l6Rxfuqnfqre9a531Wte85p62cteduf7hBsbG/Xbv/3b9XM/93PP21z3oz/6o/UzP/Mz9Wf/7J+tV7ziFXX16tU79693n+ve9a53nfmzOkkPl5/4iZ+ot7/97fV5n/d58b3Eb/zGbzwvP9NyfHxcP/IjP1L/63/9r/rkT/7kesUrXlGXL18enOuuX79e7373u+ud73znff8zyD/6oz9av/qrv3rnxerq6motLCzU/Pz8nXPdBz7wgfq93/u9+oVf+IXn5bjqT66J05F3Gd/wDd8Qy+/3w7n0IXX6m0LppR79CVQqT9egl4V0jfRBXUom6RrP/rfZn0YfdE9jeq8PbidpTOlj7J26VJ76TXXpQ8n0keIkfaCb/hRL+rB5VR5/WiJP/3OFz5YO0BRfqd/0IXOa73Rt+mg0rbf08XD6vfRxbRpP6neKr6e/X/Bs//bf/ttY/qB8y7d8SyxPsUTxnPpNY5TitiqPM33YnMb5LP4UV2o3fX8h9YXWD41HJ69Rv1M76PdSX2icn/5G9bOlPEUfdKc2U/vGXoNyKMVXah/FC8V5Gid6gJByDOV32gdTvykWaTzTPt3ZJ7p/sChdm8bo3/ybf9O69v36tm/7tlieYonanPrXyQ9Vec13c1qq/+y/gf40iucUG5SP0hjRmqc2p/q0jkka607uoXMrzWFnDVJf0nhQLkh1KQ9TzKTcQ/FM9x4pZjrnZxoj+ldg0jVoXjt7Jp0v0z69vb0d61JuTfsBxcAP/MAPUBPPHN2/pn7Q/HfOYzTXqT7FLM11Wie0Hrr3P0nKD9Q/yiW7u7uDsmd/Y/tptC7T2FEsd86hdI+fxpna1snZ1GZaa0knvs4iBjrrncaIrpHmhc4JNIdpPDrX6JyRq/KYUuyf9z9X+PVf//Wx/Nn/okUVz1UaI5o/iq/0DILyVOcZUif2qbzT5s4ZpirnOoovks6tdE+U5rBzr1uV+0LPiihvd+6LOudQ6ndam5RbO88u6Ryafo9ijtqc1hWdN+hMl65BsXjlypVBGe0ztDbTfNOLrDe84Q2x/EGhv+2ens12zvWE8mXnnoieG6eY6f7rGp09Pa1vahuNUfpLHY8++misS2OXyqkdaTxSvq06m2ef3bydpDbTnkI5tLPm6dl/yic0Jyl26VnKU089FctTLFJ8Ups7Z+I0pp1cXlV3vhd/N1rHY3Ld6NXYeRjeuZHpDkAKQNrMOouD2tz5J3A7D4sp2XdegBHamNNiosSZxqP7p1FSzFBioYNKGtPOi0ZCySm1r/t7nReQaXPoPnBJ80pxRIksJRFKvmk8Oi+sq3J8PSx/opxisfNCqvPCgPJU54UBravU5u4D9VROfenkS/q9B/XP8FJ8nXfc0Xynchrns/hDQikOOgd0qt+5Aaf9p/MS7bxR2zrnjYehH1V8c5Lmlc43KV9SzNEYpTigM0/nwelZvHjovNTqvuzvnG+o3+nanZzWffHQ6TdJN9DU73SWobZ1HlZRXRrn9JsUG+kadK6gfJn2dLoG5dG0hmi+U046i1x3Fg8p7lfnD8LRnNLYJ3TGSu3o5so0J3TO7ty3d/5QTPcP0KSXOzQn3TNIksaI5o/ulTY2NgZl1LZHHnkklqff7Lzk6O4n6RoUXzT+6b6Pxi7dj3RfIJ/FeT/F3VnkKMqVnT9sc94uXboUy1NO6ox954VPVe9MR3GecvHa2troulU5/mlNpNg/i9yaXnRVVd28eTOWp3js/IH37ku7tA9evnx59O91pfmmvNG57+ieZdM4df7wHrWN+pLaTHFLOn+pKcUzPSuimEnlZ7FHn4XOPUNnHVMcdf4C1NWrV2NdejmdYpT2TDpfpliiZ77pGhSLnb8A1f1DmSnXUV5MY5TOllW9P3Ta3f87OmuQ9u50DepfOrd2dZ4NdvZu2jueeOKJWJ7yKL2X6Jw3Ou9HaD8Yw3+kWpIkSZIkSZIkSZJG8gWrJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI00ugvVacPfFflD9zSR2/Th4TpI7T00eHOx7XpQ8LLy8uDMvpw7urqaixPHxjujFH6IG8Vf2i8U5c+zJz6SB9pT+Pc6R+Vdz6kTuX0cec03xRHnQ+eU8xRefoQdyqryrFIqM2Li4uDMpoT+sh0ihn6kHr6EDd9CDp9pJraQR9jP2+0JhKa1xQbFLd0jZR7tra2Rv8eWVlZieWULzsfWE8fNqfxvHDh/v98D+WN9BFzygWpL7R+aL2ma3dzTxoPGiNaxwnNVVrz9Hu0p6S5pb0t7R9Ul/bjxx9/fFBGeYranH6TziEJ/V7Kw1V5/Ds55kGiMUrxRWsijSfFJ62JFBtra2uxLrUj5UDqH62Jzu+lvlBdaseNGzdGt4P2iYTWVWozxWInx9Dv0Z7SkdpB45nyflU+n9De0Tmb05k4lVNupVyX0D5PcZfGg34vjSmNM/1eWledtfagdO5z6IzVuW46B1XlGKB1tr29HctTfcqrFMtpXuka6fdoXdOaSvUphkjKf531R2gO0+/RelhfX4/lqX4n79DaofutzhjRtVOM0hjRWWhs26p6+2inL1Q3rfnOHl+Vc+jS0lKse94oRiknJSkWu/drKW/Q/kVtS+NM+ZLWVedsn/IUPQOk8djd3R2UURxRv9M9YvfZWULjn9YKtY3yRnrWQ2swjTP9Hu016dqdezAqp2uksaO20d6dnh/Qeu08A+882+g+N0597KypB4lybuf8nXJd9/lPqk/nbMpfKf6pzbSO6Xlr0smtFOdp/Gmfp2un+p39mM5CFM+d9dN55kH9Ttforp/OPTDl0U6/0+/RvQT1O7WD9gNqc+ee9MqVK4MyajPl+LTe6HntGP4NVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSL5glSRJkiRJkiRJkqSRpsZWvHjxYiw/OTkZlB0dHcW6qZyuS46Pjwdl+/v7sS5dO12D2nx6ejq6bWksqqpu3749qg1VVbdu3RrdjgsX8vvx9HtVeZympnIITE5ODsoODw9j3fn5+VieUP+eeOKJWH758uVBGfU79W96ejrWTf2ryuNBbV5eXo7laZx2d3dj3cXFxUEZ9W9vby+WJxT7dO3UR7rGxMTEoIxijmImxT/F4nmjNqc1mMaiKq8JGnu6RspJlGM6uWdrayvWpflO80LrKo0d9e/g4GD071EepphJ40HXSGPUWWtVeexmZmZiXcr9CeWpNKb0e7Q/pvq0jim+Ukx34otijspTX9bX12PdS5cuxfI0drT/05pNKMen+e6cKx4k2tvSGFGb0xh1xq0qxznFXAetNWpfagetwU6OIWn86fcI7VdJmlfKD5S3z+JMnPI25Z70e505qcr5hK5B/UvltP+kvtB1aZxT7NKeubS0NLodndjv3I9U5fHo7HcPSqfPdD+T9giafxq3tNYWFhZiXdrP73e9V/Xyc5prOv/RGk4xQPsz5aM0/t19JumsP+ofnVfud5/vnP+q8rzQuaSTMyiez0LqC+U5yu9zc3OjrluV1xXFEbUjXZueYZy3Tn6g+KT1nXTWILWNfi+t+cceeyzW3d7ejuU7OzuDshQvVTm+umswrR/KaTR2qR1ncR5OY1GVn0N1cnlVzhGda9B4Uu5J80Lj3Ll/JZ37HIqZdG/cvQe+3z2v+9+nNUh58WGRcnwnjrpjn8opnin3JJQXO7mAcnw6587Ozsa6NHa0vpPOPRuNXTpvU5spT6UxpXP8Bz7wgVh+9erVQRnFTFor3fdeqY8UAzTfaQ475ymaP8q5aezoncnKykospzhI0rxS/yh/pXV8P+8l/BuskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSL5glSRJkiRJkiRJkqSRfMEqSZIkSZIkSZIkSSNNja24s7MTyy9cGP+Odn5+fvR1ydLS0ui6h4eHsfzWrVuDssnJyVh3eno6lp+eng7Kbt++PfoaaSyqqg4ODmL57OzsoGxvb2903aqqxcXFQdnExESsm8aDxiiNJ0njVlV15cqVWH50dDT62jRXHal91Oatra1YfnJyMiijcab5TmitzczMjK6b2lZVdXx8PCibmsrpIZVTDKS2VXEsPQwuXrw4ui7Na4qZNMZVHANpjGg8aV4TajOttVROuS5de25uLtal8UixRGuQrpFQPHfmiqQxojmhfSmNHa2rNP60pqjfqX0UX52YodyTyqku9Xt/f39Q1slphGI/jR3lB2pzGruHJf9RX1Kbu3M19rpUTnmjE+eUN+gaKf6pboovOnuRNKaUWzs5nuY19YX2n85cERq71D6KozRGdNajsUu/l87DVb0zWedM3DnLVuX5pjZTjk/3S511THNC9y9pXjpx+6CkfaMq5weK79XV1UEZxQrtPQsLC4Oyzl5X1dtzaezTOqFc2Vl/FOOpPt2/krO4v0vozJPGg/rXyYmkc8/duW9fWVmJdakvnfk+CylGKZ/Rvpbq09pM9+3d37t69eqgrJvfH5TOMzlC++j9orjd3NyM5SnunnrqqVg35daq3pks5eLu/pXGrps3HtR6S3tYVc4b9Hyrcy9OcdQ5a5zFM8rOPQPljRQHtNY69xd0DRq7VN5Z893nEqnN165dG/17DxKNURp/itvO+u7EVzcWO89/qC+pnOY1jV1nvVbl9UO5i66R9tjO80WaPxrntL7p9+gZRCfHd+rSGKW+0D1GZ++g+8nUDhojOj9fvnx5dDso56bxp3aka9B40pkg5dHuM51nXO+P/V9KkiRJkiRJkiRJ0p8yvmCVJEmSJEmSJEmSpJF8wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJGGn6hGNBHtPf29gZl9CH19DFjqksfvU2/Rx8ipo8cp2vMz8+32pE+7tz5IDJJY1SV+7K0tDS6bVVVOzs7o9uRPia9sLAQ69JHpvf39wdlNEb00e40dp269IFv6suVK1cGZTdv3ox1Ox8/pvWzvb09KKMPYNPHpJMU4/e69tWrVwdl9BHtNK+dOanK49FZJw8StSP1mz4SvrKyMihbX1+PdWkdpzXfWcMkre0q/jg6zW2S8hf997R+0pqlXE5jl67d+bA87UspBqpyzFCOWVtbi+UJ5fKEPuhOMZpiifY7Gv/UPqqb1jzlRYrFtNc89thjsS7Nd4pHisXUPxpnmu8UG7RnnjfaH9O62tjYiHXTXNH8Ue5JcUexT/OarnEW5w3aB1Oc0/ohKQ6obTR2aX3TXKU207mC1kQ6sxCKc4q7pLOnUD5J7aC9lNqcxq6zjulcQfky9bGTY6ryWqH8lXTPBGmt0Ho9T7SGU47pnEtoHGjc0lqjdU2xlWKcYoikGKB828lRlG9TH2lOKD5TOfU7jTPdW1MuSn3pnG2q8rqkcU5jSmNE8ZVit3vPkMa5045O/6g+XYPyXHp+Q3knzWEnbquqNjc3R133YZLGlNZEOsdQjFNsnMW5N43p448/Hutev349lqfzCu2jKZ67zzaWl5cHZdRvunZag/R76fyX4vNe7UixQTmGzn+XLl0alNF5ON1fUx7utGN3dzfWpXFO+wSdh9P4015Fv5fGv/MckdpB49x5DkLtSH25cePGvZp4biieU/voGX/K/Z3zdFXvPEXlKf7peVPnuRDluhQznXVC9WlPobGjNZt09jD6vTSmNEada1MspjMEnRXo987inJVitPOcjc6RFBupffS8tvOcgNZmiiMaZ4qN9Nx+a2sr1h3Dv8EqSZIkSZIkSZIkSSP5glWSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNNLU2IqTk5Ox/OLFi6PrHh4eDsq2trZi3dPT01h+5cqVQdnBwUGse3R0FMtv3749KDs+Po51qTy5detWLE/tozG6cCG/897e3h5dd2ZmJpbv7Ozcdzs6dU9OTgZlNK80V8vLy6N/L/UvteFe5X/4h384KJueno51Nzc3Y3mKr7m5uVh3aWlpUEZzsru7G8vTeNA4T03lJZ/GY39/P9ZNfUl9vlc7Ut6g8XxYLC4uDsomJiZi3SeeeOK+rluVxz+th6qqvb29WJ5yTxr7e0l9pPmmdZzQNVKM0nVp/0jjQeuK1ndC8ZyuTXXn5+djeeo37T9pLyWUN1L7KJ5Jugbtg6kujRGVp2vT/k/tSPmLYqAT+9Tm1L7Z2dlY97zRfpD6SOeKNJ60XmnfTTmQxpnmNZXT71G/U26k8wbl3KSzrtKZoIrjPLWDxi7FHeXFdJ6qyuNMv0f9TvsYrZ909qXrUl/SfFObqXzsdaty3HXuR6ryuuruB51zfNIZz6o8L7TfnSc6Y6X20jx14p7KU1xQLHfikNYOxUXnnNbJGZRvU/3OOaEqx37nvp32+M4407h19vPOvkbrjMZufX19ULawsBDrUl9SzNB8d850NFdp/+r2O90H0DU69xfU74dZ5567c2bt7gVpvVGuozyVYqbzHKQqxz+dZTv7NsVzugbFLV0j7Vd0HktzRWuexj+1j2JjZWUllieU6zY2NkbXpd9Lc9jNdUnnXE8ontMapBigNqd1RXXT2qQ9mtZPmhe6xnnr3F/Q/VMa/85YVOX1Q898O9L7jirud+d5zFlIY0q/13lmSHtKmhd6ntk5q1GuI+mehvaUhJ5b0til9Uax0TlnUZ5K5dQ2ek+QxoP2sHSPX5XXED0DT+2jGKC1mfpNeWMM/warJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI0ki9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0khTYytOTk7G8kuXLg3KLl68GOvu7e0Nyqanp2PdCxfyu99U//bt27EuteP4+Hj071F5Gg/qS2rHzMzM6LpVVR/84Afv6/eqqlZWVgZlNHanp6ejyqqqJiYmYvm1a9cGZRsbG7EuofFPZmdnR9c9PDyM5UtLS4OynZ2dWDeNZ1UeD1o/29vbo/77qqrLly/H8jSHNFfdOUympoZpI41bFcdoiv+jo6PRbXiQOmue6i4sLAzKbt682WrH8vLyoIxi8datW7E8zXeav3tJsUG/l1DsU/nYNlRx/lpcXByUUb/39/cHZTRXlLdT7qG1RmsijQf1O13j5OQk1qU2p/HY3d2NdUmKf2pHWt/d2EhtTvt5FY9zQnGU4pzmlca5M6/njc4KaTxSTqvKexjlBxrnFDNUl2IjjSnNFUn16fc6Z5NOv+ls0sm5NK9pjFL+q+KxS2uQ2kZrszPf6fforJdisSrfe6yursa6nbMTnVlSXZoTksaIxpPGv3MmTmgs6PdSefe88SB0zr2dMaa6nd+jvYDySxrPFN9VPP/pbElSfujmxHRu7d5zp/LOvt3Jn1V5nDs5qirncsrvqZzOMFSe+ri+vh7r0nkl3dfS2KXY7ex1VXnsOvcGVTk2OmesznOQe5U/DGj9HBwcDMo6e1JnL6/qncc69zkUG/Pz87G8s+7TNei6hM5TCc1VJ746ebFzLuxeI52FKMekuvR7tLelOKD71xT7XSlPUdzSvtt5ft0d/yS1mfaqzp5CbTtvtH4oJyVprXX3+TTfdG/QeeZBZwWSrnEWz/ipPMUi7RM0dnNzc4OyzvMDGqPO2qTf68wV5Z5Unvp8LynOn3zyyViXck/axx7U89OqHAf0zoT22LW1tUFZ5/kP5TTaD1If6b3LGP4NVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSPmrtcHGxka+QOMj2gl9PJk+Up0+eku/12kHfZi586Fq+vhu+kAxfbidys/io+KdD2B3PnpPc/hHf/RHg7KFhYVYlz5GnD6gTB+k7kgfca7KcUfzSn25cePGoIw+xL28vDwom5mZiXXpI9ppriiOaK4uXbo0KOvMN621nZ2dWL69vT0oo4+Sn7e0XqtyLqC5SmNHMUfxleKIxpk+Ep4+pk4fJafYSOuNYiP9HrW58yF7yg9UnuaK+pfmkOaE1nEnP1Pd9JsUXylP0R7WaTP1u/NheVrHqS+01jq5gMaTYuN+90EaZzqzpN87ODiIdc8bjXPqI+WYtK5mZ2dbv5dilPLGxYsXY3lC8UW5J7WP5rXze7R+UozSmZPGLo11J7dSLNJ8p9+jMaIzUmofzWsaD8pp1OYrV64MyuiehvaJVE7jnOab1gTFTOpjN77S2NFcpf51789SjFIePk+dfY3WWapL40N7RLpGp25VjoHV1dVYt3OGp3akewkaI1rDnecEFOMJjX/S2eMJtbmzpihnpHIaC8olnTMdSftBJ+90n1WkMe2eQ9P9K+X3NFeUo2hNdGL0vFFf0r041U3PJTr7YlXee+h5ALUj5ZPOc72qPN/0LCU9X6S2LS0txfKUT7prMN2j0zXSfRXFPpWna9C9ZycHds7qlNPorJfijs7OdO3Onp7igMaCrpHyBuUYiruUX2mMOnsbtTn1kdp83jr3ORSLqW7n/pDq0xjRukqxQfNK8dx5xpKeL57F85ju8/n0XLTzPobuX2mc05qnNqfn1FVVKysrgzKak5QXu3mqc49P5Zubm7E8SWueYpHGP40R9ZvOjKkdNCcpdmmPpryd+tJ5/jNo0x/7v5QkSZIkSZIkSZKkP2V8wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJG8gWrJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGmlqbMVHHnkklh8dHQ3KJicnY91UfnBwMPq6VVVTU8MmT09Px7qnp6ex/MKF4XvlW7duxbrUl4sXL45uR7p2akNV7l9V1e3btwdlExMTo3+P0PjPzs6OakNV1cnJSSxfXFwclB0fH8e6NHYLCwuj25Hmm36PpGuksaiqWltbi+VpPOgaKb5oXik2Om3uxGiKcbK1tRXLl5aWYnnqN63580YxMzc3N7puWleUSyie01ylNtyrHXt7e4OytC6rqg4PD2N5avfu7m6s28mtlDc66NppTGmM0vqhttH6SePc2TuoffR7aa3MzMzEujRG6fdoX6LxSNegcU7jQf2j30s5kNpM7UjlnVjsruPUPrrGeaPYSOO8s7MT66Z47uzRVTl2OzFQlfvyIPcUiruE5ruTe2hMKRePRfmI2pHigM4bnfGna6T1ms6FVbyH7e/vD8poPGmPTfVp7NJ803imtlXl3NjNPWlN0PkyxTNdl6S1eRb7/P3qnBMoR6UzHfWNrpHaQbFM1ziL+5zUboqLFIed819V716i80yArpvaQbmB+t1BeS7NLc3r/Pz86N9L582qPK+ds1tVb19LY0fjSe1IOY3aQOU3b94c/XupnOKZ1mZq88NypqP1k3IzzVW6n+/eG6R97fLly7EutSP1hfZLOheurq4OymhfS9eg9UrSeNDZmaS8RuOc5qW7HyR0P0m5Lo3TxsZGrJv2QZo/asfm5mYsTzrn086z4M4+X5XnsPssOP1m55kv1e2ckc5izzwLFItp/VDdzhmX7g1SnNNzNvq91D6KDTrLPPnkk4OylP+qcizSHtbJJ7RnUnylfN45g9B1O2ck6nfnWUPnfRNdl6SYoTjqxDPlxdRmelZH10h7d/d5TBrTTv/oLETznWKD+j2Gf4NVkiRJkiRJkiRJkkbyBaskSZIkSZIkSZIkjeQLVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjTS6C/t0keVE/oYe+fD5vQR7XTt9EHrqqrt7e1Ynj7gSx+Cpo87p4/W00eVl5eXB2X0oV76UHIqpw8G00efUzvoA/JpjGheqTx9+Js+gE3tSP1eWVmJdXd3dwdl3Q8zp7FbW1uLddPHuauqHnvssUEZjVFqH8UGfZg5fci5+7Hy9EF2mpO0NmmtUV9Svzs55kHqrAn6GPvc3NygjOaE1nyKRcqL1Ob0mxSLNFcpR1M7kk5O616b3O/Hymlt0zgnNN8k9ZvGIpXTeNIem8pp76A473xwPo0HzQm1mfJXQuOR5nB+fj7WTf2jMaL5TuWdfjxINEZpXtKZpyrvHXQ26extFPsUM6kvnfVKqM2pnMbzLOab2nG/+ZLaTHPY+T3KG6mc1lUqpxigcU75nNYr9Tv9Zjp7VeUxojan9VOVz0P0eySNHf1eGo/u7yV03jhPFFtpTVHMpmtQDNE9aapP94203s/ibJnmpLOvUf/oGmk9UFxQzKUzQSc3n8VZo3tmTfU79wyd/tG16Z57c3Mzlqc9s3OG74wF1acxorlKMZPGk67dWWtVuc03b96Mdc9b50xOdZeWlgZltLbpvj2NEeWpzjnh0qVLse6NGzdieYrnJ554ItZN9wGUN9Lzraq8v169ejXWpVyX5qVzL9i9R0n16R64c5/TOafRMyS6RlqbNEadZ6Wds0LnzErto5xGayLdh1GO79zH0e+leaX+nTe6b0/nE4qBhNYlXaOz79LYpfMQtYOunZ5r077buX/ttJmerVNf0v7ReR9A52eKjbHXreL9MeUvWj8JrXlqcxo7ioGzuG/vrBXaD9IZopPTqvJ4UD/SGFE/6P6l8z5mDP8GqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIU2MrTk5OxvLZ2dlB2a1bt2Ldg4ODsT9XExMTsfzk5GRQdvv27Vj38uXLsfz09HRQdvPmzVh3YWEhli8tLY1uB/WlUze1Y39/P9bd29uL5Wlejo+PY93Dw8NRZXTdqhwz1OZOOy5cyH8uYGNjY1A2MzMT63akua6qWl1djeXr6+uDsosXL8a6ab5pLGj9zM3NDcqo33SNnZ2dUWVVORbp99J6rcp9pBxz3o6OjmJ5il2KxYTyAzmLMZqaGqZ4WsfUl/SbnX5TTuvkxa60Jqjfab7Tf1/Vi2cao87YUd30e2kvruKYSeXd2EjxRfsBlXekmEn7+b2k+U57B/0exQa1I/X7LMbiLNAaTGcIOgulfqe4qOJ+p/iiswK1+UGNKf1eWj8UA7Snd/I5rcHOmbiDzjebm5uDMpqrzlqh+Ut9oXMM7d0Uuwmdn1Mfl5eXY900JxQbFF/T09ODMuo3xcbi4uKgjHJ8al8n9kk3Pz8IdP5Obeu0l8aHrpFiuZsz0pqimD2LM12Kl/n5+Vi3c99OewTdb6X2USwndD7q7Bv0e53zItVN40H3YHQOTX2kNlNOTDF6FnmA6qacTXUpRtP9J+XKlFcpj3dyJV3jvNG8pjinWNze3h6U0Xh2YnF3dzfWTXNSleMgtY1+ryo/j0n7YlVeg9S/zj1RJ08Rakdar3QeozNdWoO0p9DaTHsszUnnGRJJ7aBcTntpqk/7UopRGgu6RhpnqkvSOHWewdKc0BkpxfmDfHbTQWenzhkujQetNRqjlEe3trZiXYrzFF90P0PXSHFO8ZWuQXUp16VzYGc/oHZ03jVQLqc10YmNszg/p3KqS3tsmpfO84CqHF+dPYxig+Y1nV3puQTdT3TWVeoLncloXaU+0pllDP8GqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIU2MrTk5OxvLd3d1B2czMzOgGTE9Px/Kpqdy0ixcvDspOT09H/15V1eHh4aBsZWUl1p2YmBh9Xaqbxmh5eTnWPTg4iOXHx8eDspOTk1iX5ur27duDsgsX8jv2VJfmpCNdtyrPSVXV7OzsoGx/fz/W7cRBGk+6BsXorVu3YnlqM9VN/aY4onWV5oXaTGOX2kdrIo3R0dFRrJvWK5VT7J83GjsqH4tin9ZgiiNa83SNNK+d/FCV55Zi4yzyVELXoHW1vb09KEvjSeWUjyjHpPGn/m1tbcXytCdQ3bR+aG3Pzc3F8hTPFOOdfYLqpjxFewqNHc1LR4pnGqOk0z+ytrY2uu6DROsnzWt3TSS0t3VisdNmQnOYUO5JuY6u24nn7vkmtY/23bH//b2kdtDZZG9vL5annEt1O3sK5fjOeZbiLvWR2pzinGKf4jmhGO/EF10jlVPMddb8/Z6bzgKNcdoLqO78/PygjOaf4nNpaWlQRmuH5indT5LFxcVYnuaE5nRnZ2dQRnmOYjyVb25uxrp0b5bWK41z6t/Nmzdj3dXV1Vie1g7d51Bf0jm5c4bv5qgUMzQndO10diYp39IY0bpK5WmtVfEZJMVo5z6n8zyArtG5n3mQaG2msaNcQnkt6Zyd6VzSWfNdKf7p9xJaa3TWSGOX4rOKc39aEzR2qX+0fuh+snMepphJua5z5uk+H0lzSONJ7VhYWBiUUeynvEjXpTXRuW+nXJfG6dKlS7Fu2pcobinXdfbd80bznfYgWvOdZzc0J6kdnfxQldcEXeP69euxPJ0vKYemnER5g84EaZxpHVNf1tfXB2WdPYXOdWltV/WeWVHeTrmOzj0pZq5cuRLrds4stF7pGtS+JMUMxT7lr7QmOs8R6TfpHHn58uVBGc0fXeOsz3D+DVZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI0ki9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0kijvyC/trYWy9NHkenD36mcPjbbuQZ9OJeu3fmgewd9IDd92LxTt6rq4OBgUNbtH32cPkkfme58pJrQvNJHjjsfd07jQdelsUt93NjYiHUXFxdjeVoT9IH19LF4GiOSrt3td2ozXSOhj5LTB9anp6cHZfSx8vPW6TdJH/hOc13FHw9PHyXv5o1Un9YPfQQ95ROK0fR7e3t7sW6KAfo9iluSrrG1tRXrpr5QrqMPuqd+U+zTHKY+0tilWEoxR9cl9FF4mqu0VqhuZ/+nNXEWH6FP+ZLWT+pL97yRrkF7x3mjNt/vvts9Y6Vr0FxTbKRyWsdnkePTNSiOaP9P6zud9ap640F7TUJ1qTzlGcqLtKd09rZUns4rVb01+NRTT8W6FOcplqhu0jnjVvH+kdA4p3HqxAbt8522dcboQaE9KZ1baXzS/dPCwkKsS+OW1jblqJWVlViecgbl20455dXLly8PyijeLl26FMvTPRSdVyi2tre3B2XU5scee2xQRuNM1+jsERQHy8vLg7LOmYf2k849Iu091I4Ud5ubm6OvQePcyQPde+A0zjR/aX1TXYrR1D4a54dFajON89LS0n3/XlrHnTMFoXMCnZsSylOU1xKKmZRbO/cXVTnXUdvSvUT399LapPG8evXq6GtTbk33mZQ3Hn/88Viezpw0Rqurq7E8xSi1o7MPkhQztN9ReSd/pb7QmaDzzJ3i6Lx1cjzFc9rDaD+nsUvXprp0rkvtoD2T+p3WPcVomlf6Pcon6SxKsdEZf3rulfrdvX9N1+6MZ1XOzySdC+idCT1HT+uYcmvnnq1zv0zxTPf+nWdIHZ33WxQDtB+kdxD386zIv8EqSZIkSZIkSZIkSSP5glWSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNNLU2IpLS0uxfH9/f1A2Pz8f605OTg7KDg8PY92Tk5NYPjMzQ00cOD4+juUXLgzfK09MTIy+LtW/fft2rLu1tTUo297ebv3e0dHRoOzWrVuta0xPT4+ue+PGjUEZ9Y/mu4P6cnp6OrodKWZonFMMVFVNTQ2XxMrKSqxLMbO3tzco293djXVTjHZj8dKlS4MyWj+pf6Szfii2aF5T3lhYWBjdtgeJxq4jxS1dN9Wtqrp48eLoa6SYq8rjfOXKlViXrp3WW8pHVDf1417XSOXUP4qv1A6K0bQv7ezsxLo0RmlNpOtWcS5Ieyztj6kvNBb0e4uLi4MymivKuQcHB4Myyhspr1EepvK5ublY3pH2K+pfJz9Tbk2x1N27HxSa79RvqptigNYJrYk0/p0zAV2b2tHZY6luyq0Ut7QGU2xQmzvnt7PoH62JlJNoTujaKWZo/czOzg7K0thX8f1B6ks6N1Vx/urk3CT1uao3djRGFDNpL6W6qS80f9Tmh1XnfER7TBo3mv/OmursPfeq36mb+t25r6J8tra2FsvP4p477T90hkztoPVHe1JCY0R55/r164My2kfT2qY818kZlOdoPNI9M/U7xX/nTH6v8oRipnO27OQualuaQxrPh8X95uzuPVHatymn0Zo4i3vxtG/TXHXiufNsg9D9XcprFM/p92iuKV+mZ5TXrl2LdWkO03jQ+kntoLPN5uZmLE/jke5pq3i+09jR76UYpbzfORd27yfTtek5Z7rXpXXceYZH6/W8dZ5RpnxUlff/7ppPv9fJMXQNWsd07XTOXV9fj3XT8yaKIzrvJTTOlBdT/bM4b3SeE3TWWlVeQ/R7nXmlHJ9yBOUNWsdpDinXpdigczJdg96bJNSXznOodOanezmK83Ttzv3Bs/k3WCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIvmCVJEmSJEmSJEmSpJF8wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJGmhpbcXZ2NpYvLy8Pyg4ODmLd09PTQdn8/Hysu7+/H8tv3bo1KJuayt24ePFiLJ+YmBiU7e3t3fc1Uv+o7oUL+d325ORkLF9YWBiUbW1txbrU5rm5uUHZ7du3Y93j4+PRdU9OTmJ5ksaiiscjxQHV7Tg6OorlaUwvX74c69I4pzmksUvritYaxVcaDxojasf6+vqgbGZmZvTv0XXTeqVrUL/PG63BhPqd4ovWCf1eJ8fQfKe8QXNCUl8oXyY0rynHVFWtra2NvgaN//T09OhrpP2K8gPtNQnlutS2qpzraH9M16A5odhI40zjmeKIrk1tTmNHMUBrJZVT3c4eS+eNNB5pH62qOjw8jOWpfVevXo11zxvFYgftEwnlr9QOahutzVSf9mhqRyqnfJlit7vmU/uozRTnaW1SOzqo3ylfUv9oDaaY6bSZ5o/20s6ap1yXcgHNVec+pbOHdc4K1L7Nzc37/j1q88N6rqN8m869S0tLsW5afxRDFJ/pfrl7pkv7D8VWZx+l9Z7ihcaIbGxsDMootuj5Qeo3xVa6Nq1r2k9SjHfivir3+yUveUmsm8afzkc0dikOujGaxonGKF2DxoKukXSeYVTlcaL+pZihMaI2U/seBnQOTbHRuT+nmKNxTtfuPrtJ5wRag51nEFQ3xUHnWWRVHmcau84zATpjpfWa7u2qOJ5XVlZieUL5OemcjyiOqC+rq6uDst3d3ViXrp3aR/evaa5oLGic07NE2rvp+W4n56bxoPs1yhupLzSe5617Ph2L1jyds1PMXLp0KdalPT3FEsVzOkdW5bml+Er5hNpG1+g8D6Nrp3bQ+klxTmcCukZ6TkZnQ4qv1A4ai1S3866oqmp7e3t0XcrlaZwXFxdj3RTP9Hud516d92l0Dcq56dq0Z9Kz0rR+Ou8Dns2/wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJG8gWrJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGmn0F4rX19dj+dWrVwdl9MHt9MFaqksfzk0fw+18XLgqf2CYPlhPUjvog/VUntAHdXd2dkbXpY87dz5Mnj4CTP89fUj4LOYqjR19wLzTP5qT9FFx+hA0xUwnvtJcUV36MHOKg9nZ2ViXpDmkj4enujQnW1tbsTx9kJrW/HnrfNSa4jl9NJ3mlcpTO2idkM6aoA+9pw+eU2ykOaQPmJO03lZXV2NdWhMpRmlNLC8vj24bzVXKG6msivuSPmRPH3RP80pxSx+W77SNcnwqp36nnNvdd1O/04fpq7jfqR2dfEnX7cR550zwINFcpViiGEg5ifYDkvIojRHl3NQ+ii+aq1SfrtHJxbQ20zU641yV83bn9+i6m5ubsTyNB+0z6dxaVfXoo48OymhdpRxP87e/vx/LU336PYrd1I7OXNE4U+7pnEOoblor1Oa0p3fOD1Sf9ujzRLGczis0limG6MxEc53O+xRv1I5Un84JnbMl7aPpPHZ8fBzr0npPzw/SubKK83sa/86+TePZ2SNo7dD4v/SlLx2Uvf/974910363srIS677oRS+K5ekMubGxEetevnw5lqe57eyB9PyB8kD3/iBJeaezx1ObaX2nNUHjfN5u3rwZy+83v3fPQamc8gaVpxxBdWkNpnxJOaZzbqV+p/Z1YrEq52Ka19RvyuXUv5R7aJxTjqHfpDFKbab8TDl+bW1tUEbPJWi+U7/pOVQqp7xBY5figPpNew1dO0n7Me27nfGnc/Z5o3hO7yVorlIc0b5Lc5Jig8aIYjGVLy0txbo0h2m90fpJ40H7QefejMaI2pyuTeu48/yHnh90zpF0nr3fZ8T0ezR2qd8UR3TttNd0cgzlRZqr+90PqnJs0Hyna3fb3HlnNYZ/g1WSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRppKmxFS9evBjLT09PB2VHR0ex7oULw/e5MzMzo+tS/ePj41iXTExMDMqof5OTk7H85ORkVFlV1e3bt0dfl6TxmJ2djXXn5uZieRq7zvhTm2/evBnLU79pjChmxraNrr27uxvrLi4uxvKVlZVB2d7eXqw7NTV6+eDvpb5MT0/HummtUTsoBmjsbty4MSjb2tqKdVPcURxRX9J6667jB+Xw8PC+r5FyDMU+9TvNFcVAx+bmZiynOez0Ja2Vg4ODWJdiI+UNyg+pblVuM+XLVJfW9traWizvrGPKlwm149atW4Oy7vpJY0fjSXkjjd1Z1E39q8qxND8/P7puVY4lmquE9gO6Rirf2NgY/XsPUpqTqhwHNJ5j//sqzl/pbEE5phMz1GaKr86ZJZ0tKAboGmk8qH90Rk19obNaah+1rXMOoTVBOSnV39nZiXW3t7cHZTQWlC9XV1cHZRQDJK2V/f390f89xT6tQdqvOlL7aE2kOKAx6pwvz+I8db+oz2nsKXelsaS1Q9JYnMWeS+uPYi6tH1o7H/jAB0b991V8hrx06dKgjOKe5ir1hdZI6gudIakvab7pnoiu8ba3vW1Q9tKXvjTWXV9fH5Rdv3491qU1le5fu23u3GOkGKVxpnvxNFfUP4rRzvOUtCfR+qG1+cQTTwzK6B7/vL3sZS+L5WleKTbSvNJY0DkhrU36PZKuQe3onI86Z8iFhYV7NXEg5S/KU9SONKYvetGLYt205ilv0H6Vzl40V1euXInlqY/p3FWV74FpP6B5TX3p3ONX9fJG5/lpp82U6+jsla5NOTuNB53dziK3Piz+4A/+YFC2vLwc66b9gPYwGue0f9C8ds7OFAO0NlNupHuwdL7pnvdTfVqD9JwmxVdnXdF+0HmnQPeeJPW7c59DZ9yUy6t6z/bo+W7n/VvnuQTl1tRmWj80dp1nhikO6P6c9vQUi93YuJt/g1WSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNFL+qnVAHytPH5Glj2KnDwPTR5WpPH0klz6cSzof8KUPKKdyqpvGI33Evoo/GNz5qPLS0lIsTx/2pQ9SP/roo4My+gDzE088EcvX19dHlVVVbW9vx/LOOKcxpbjtfGyZPvDdiXOS2kEfm6d5Tb9H/dvd3Y3lKQ7oI+Gdj5LTulpcXByUUQycN+pLR4ojilta86kdFFt0jSSt7XtJfaGPh6e1kj5MX8X5JMXu5cuXY10aj0uXLg3KlpeXY91Ojrl27Vosv3HjxqDs+vXrsW5nHR8cHMS6qZzGmXJBihn6+DtJv0ljl/rX2V/pGrSHUYymfYJyfEJzQu04OTkZXfe8UX7u7ClpP6C9sXMNysM0/p3YoLyR5orakWKGznUUz2k/prxIfUntoByTrpH6XFW1ubkZy4+PjwdlGxsbsS7lpBR36bpVuS+0XqkvaV729vZiXYrddGYhqR0Ut3TO6pwjSRpnGrsUG50cWpX3FNozzxOthxSflBNTHujkoqp8P9I9F3b2bYot+s0kjR2tkfn5+dHtoLo0/un8ls55VfkeitY77Ulra2uDsps3b8a6NM4f//EfPyijmEn9ozMr3deme6jHHnss1qU5TGui84yF9i9qcxq77vOYlLuozZ2z19WrV2N5uh+h2Dhvv//7vx/L03qjsUj5nZ430bpKewftz53zIsUAzXfKxXTW2NraiuUJPadJfaG20TXSPTqNXZrDF7/4xbEuzSE9l0voOU0aZ2rzzs7OoIzOiqluVd6X6PkWjXPKM3S26Zx76dx05cqVQRmdTSjO07MGGrvUb7qfoXlN+9XDcv9K6yrtmxQD6VzffS+RziEUt53nxnSuo/hKaL4772NoT09xR+c6WlepPj3vS+NBZy86Z6VcR2dtipmUC+ganecjtI5TfWpb5xkL7QepLrWN8ka6z6R7T7p2KqfzRsqXtH7ofJnKaQ8bw7/BKkmSJEmSJEmSJEkj+YJVkiRJkiRJkiRJkkbyBaskSZIkSZIkSZIkjeQLVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjTS1NiKu7u7sfzixYuDsgsX8nvb27dvjyq71zUODw8HZaenp7Hu1FTuXqqf+lFVtbGxEctnZ2cHZRMTE7Fu6svR0VGsS+OxvLw8KKN+Ly4uxvKVlZVBWepHVdXMzMygbHp6Otadn5+P5ScnJ4Oy4+PjWPfKlSuxfH9/f1RZVR6PW7duxbrUlxQz1OZO3B0cHIy+Rqd/VTnuqC6t46tXrw7KaE3s7OwMyiie6Rrb29uDMlo/562zjmleUwxQTqOxS9dO6/Je1075hOKZ1krKuSTlE/q9FEdVOU/t7e3FupcvX47lCwsLgzLKMSkXUNxSO1LOpRyztbUVy9N4UCx28hTl5xRLNCe0l1LsJmlMKU9RLKZr0BqcnJwcfQ3qN41dQvOa4oBi47xR3khjR7GYyqkunW9SHFDeobXZuQZJ7aZ1lfZpahvFYmfPm5ubi+XXrl0bVUZobVNuvXHjxqCM4iidAavyeqNxTnmK4ojGOcUGnZMp96T2ddYPzR+NP/WlI+WZzlmB5o/mqnP2PU+dvZjqpj7T+qW5SzmD6lIcpnK6xurqaizf3NwclNGcpvGg+0Yaj6WlpVFlVfnsVpXvUWiuOuex69evx/K099M1nnrqqVie1g+th3RPdBa5geKIrk35IUl9oTMd7cWdHEVjl+KR7nXTeFDc0jVS+yi/nzfa+9M403h2zjZUnu4NaG3TPpNihu6BSecZZYqN7j1RyhvUb8qBKX9R3fR71L+UY+j3OueEqjyHdH9IZ6+E4iutWcqLnXxCe1vyyCOPxPK0v1blNdi9V0p7OtVNY0f7XXrGXJXzeWeMngud+6oUG9Q/2sPSGHWe3VD9zvMVukbnHqxzbq3qjR3FV8rn6RlgVV4/L3zhC2PdtbW10deg5zzvf//7Y3k6K9OzwVSX5rUzzp2zUFUeZ6qbzj2UQymXpzinPNUZj867GxojeraRzvEUi2P4N1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSL5glSRJkiRJkiRJkqSRfMEqSZIkSZIkSZIkSSP5glWSJEmSJEmSJEmSRpoaW3FiYiKWX7gw/h3trVu3BmWnp6ej/3tyfHwcy09OTka3g8zOzsby1O/t7e1Yd2ZmZlB2+/btWJfGeXp6elA2OTkZ69K1U7/n5+dj3UceeWRQtri4GOsuLCzE8vX19UEZzcnOzk4sv3jx4qCMxmhrayuW36/9/f1YfunSpVie5pv63UH9TnFA4zk3NxfL9/b2RrcjxWIqq+JYTHNF1zhvKeaqePyTTo6h30sojjq5gOaEYiPl6M3NzVg35ctOTqP2pTVFv1dVNTU13Noo1y0vLw/KKNelnFaVc8TVq1djXVqb6Tc7cbS6uhrLaW2n8aDYoH0+ldM4Hx0dDcoODg5i3TR/VVWHh4eDMoqjztmkcw6httE6Tu04i/3gLNB8d6TzF419Z66685piY2lpaXRdKqfYSHmN8jCVpz5S7qF1la5NeTFdm36PzrPpvEexT7kn1V9bW4t1U46gXEdSfqb9ju4nUi6m9ZNyXfdeh/JMRxp/WlepfdRmWoMpr1GOP0/UhrSGKS7SfND+TOOT4oXWKrU5zQnNaYrDqqrd3d1BGeWodPaiuOicTzv3qVW5L1euXIl1U36gXPTyl788lr/vfe8blF2/fj3WTffLVXkO6X4yzeHKykqsS7khjR2dN2k/SfmPYjHVpT23c/9E64fuA9Lc0h7faQfFaOd5zHmjMUprs7PHdPejVL+75hO6Bp1BUuzSs6JUl67buX+lmKMxTfmV1lXKPXSGobNeyhGdOamqevLJJ0dfI/WP6tL+mHI8zSuNf7r3Jyk2uveCaQ+jvNF5DtUZO6pL5Wm/6sbGw4BiIK1XOt90zvA0f3SNTmxQeZqXTozSvkvnSDr3JJS3U1579NFHY93UZjqvU19Sfcob9Jwz5YLOMx0aT2pz58xC+bLznDnNCa156nfqSzeeO8/70rqis1C6/6nKsUF76Rj+DVZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI0ki9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0ki9r9YH6cPF9KHe9CFb+rht52PSXeljvSsrK7EufYw4fTiaPi5M4zG2bVX5Q8L0e/TR59Rm+ghw+pAwfcyYPp6cPkJPH41OH1KvqtrZ2RmUUcykfqePUd9LiufFxcVYtxMbFAOpnGK/c42rV6/GuhRfaZyobhojGotOLHY+Ev4gdT5ATvGVYpTmjz7a3ckbnY+jd2KgKs8V5cv08fD039+rPMU/rcH5+flYnnIS5cvOXF25cuW+r0E58Pr166OuW1V16dKlQdnW1lasS/Gc5orWa2ef3tvbG30NmhPKBSn3UByluiStE0Jt67SD5uq8LS8vx/JOLk75hPawzpxQnqJ1lWLp+Pg41qX5Tteg800ao84eTe2j36M1mMopFtO16QxIY5fyCe1hlLc3NjYGZZTL05xQbFDcLSwsDMq6+3FnnNPYUezTNc5CunanfzTOFBvp2p1zzINyFrHcudelcUt5h+59KJbTNdbX12Ndyhlpj6Z+p75QjqLx6NwT0XpIuYTOK0tLS6P++6qci6py3nnBC14Q677//e+P5YeHh4Oyzr5GZ8VO3rl27Vqs27mfp9yc7s/P4v6C9iS6dporukbqC50HKG+ksaO2nTdqRzrvU79TeefsVpVzK61Xkn6Tcl26J6rKcZDGoirHPo0R3Vela3T3/pS/KOcm6bxTxbHROSdQX1Kb6RopL3aepVB9GiNqc6rf2Qc7e3RVjsVuv9O16fdSvzttq8prpZsLHmade3+SxiPFeBWv+RR3VLfzjJL614l9OqOmcyStwZQfqvIzCKqb2kf9e+SRR2J5evaSzjFV/JwzzUvnrEBn304+oRxPz9RS+yiO0rUpnjvnOmob6bwzTGuQYvHmzZuxPMXM9vb2vZp4T8/9na8kSZIkSZIkSZIkPU/4glWSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNNLU2Iqzs7Ox/Pj4ePyPTY3+uTo5OYnlt2/fHpR123bx4sVB2RNPPBHrrqysUBNHt2Nzc3NQduvWrVh3f38/lqd+0xil/lH51tZWrDs/Pz8oW1hYGN02QjFAc5XG6ejoKNZN5Rcu5D9DcHp6GsvTmNI4Ly8vx/KdnZ1BGcXGzMzMoCzFS1XVwcFBLH/ssccGZdvb27EuSdemeU2xMTc3N/q6VTkWaa7OG8VXmiua1xQz1D8a5866Sm2ryvlkcnIy1k3zWlX15JNPDsp2d3dHt42u28nPVPf69eux/MUvfvGgLK3Lqhy7NJ6UL1P7KG8sLi7G8tQ+ioG0vimnUZ5KuZjaTGtienp6UEb7xMTExOjfo76kuaLYoHLqS5Lmm/awNBaE5uS80TpOY0f5K+XANNdVHM8pDihPUZvTuqL9h85fqX0UR6kdFM8UGynPbGxsxLp07cuXLw/K6ByZzrPUNhr/VE7rlXJ/OuPQukzjQWuQ9uM03539tSqPP8VXGlMaI9qX0nqj/tEcpj7S+knXoLoUG2mt0NnwPNEYpz7TOuvEPcVWihfKqxTjaU1RO+heMP3mjRs3Yt2Uo6jNlFfTmFKOojan2KLcvLe3NyijPYlyVJorWn+0HlJ9iq80znQfR7Fx9erVQRnFBrU5zS3Na9pzaU5o7FI57QUUd2mPWFpainVT3FH/KBbTHHaehT0X0thR/5LDw8NYTrkuxWg3X6b2dfYe+k1a82tra4Myio3OvkZrnnJSajONUep3N0/RvCSdMxadj1JfOvmIrk331tSOdH9HZ4UXvehFgzLKz51nWZTLaU5SOa3jtA92nm9V5XtViufz1lmblB/SfNN1KW+kPaVzjqnKcUBxS+Wp33SuS+uNrkt5KsXB6upqrEtrJZ3Baewef/zx0b+3vr4ey9NcUW6ldZz2ws77LXqO2HmGR2uQztVpfdMelq5B/aO1knTeNxGa1xS7FLedfaLzXO/ZHo43GpIkSZIkSZIkSZL0POALVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSFNjK25sbMTyo6OjQdmFC/m97cTExKDs4sWLse6tW7fGNq1OT09H/15V1cnJyaBsdna21Y79/f1B2d7e3ujfm5ubi3WnpvKUpHGmtq2trcXyxcXF0ddI800xQHO4vb09KKMxophJ7UtjUZXnhK47PT0dy2/fvj0o68ZGp24q77Y5zQu1OcUi1ae6afwPDw9jXSpPv9cZzweJ1uDm5uagjMZ5ZmZmUEb5iOY7oVxH6DeTFPsk9Y9+b3JycvR1q3L+orbR+KdcsLW1NboNN2/ejOWUt3d3dwdlnTxF9anfaW2mNlTx+Kex6+TyqhwHtH5Smw8ODmJdGruFhYVBGcU4rZXOmSWh3+usn866fJAo56a+UJvTHFIcUWykWKR1Mj8/H8vTvC4tLcW6x8fHsTyNB+2DCcURlXdyI8Xzzs7OoIzyVMqtZ5HrqG1UnvpNe0pa84R+L803xShJ8U/xnM5qlNMovtIYUV0qT3NIeSr9Hq15Grv0e9Tv80Q5I80fzWmKT9oXKb+srKyM/j3aG1OOonsDunaav9XV1Vi3c92O7lk2xS3Fchp/qts5J9A1rl69GsufeuqpQVm6j6jK893dT1Js0BmZrtHZ+9PYdc5SVTl3UT6ja6f1TftXajOdNWgdp2vTOJ+3zrmpk2M656CqHDPda6S5ovscmqtOPKe6dEbr5A26Bj1TS/m1c/7u3GNSOd0bdM7OnTmhtU1tPovnRWkd03kzjTM930pn8qq873bOyFV5DS0vL8e6KWY6e0dV7jc9xz1vNFcpR9AZ6dFHHx2U0fzRNdIY0fzRGSKV0+/RHKa8kZ770+91n22kmKGxo2uk9lHeSOft69evx7q0rtLYUb87ua7zDJyeS9A6Tu2g8wb1pZMvU46hez6K83SvQ2PUaRuNUbo/ozzVeX7dPc8+47/9Y/+XkiRJkiRJkiRJkvSnjC9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0ki+YJUkSZIkSZIkSZKkkYZfRAb0IdtU3vkoLH2Qlz7gm6QPTFfxB7AT+ph05yPH6QPThD4YTB/fTX2kDwNvbm7G8ve85z2DqdsRSgAAPndJREFUssuXL8e6V65cGZR1PrpO5TRX6ePVVL6/vz/697ofgk59pHml2Ehu3rwZy1P75ufnY136MDZ9OLojfRCc5juNHc1rZ03Q7503akeaK4ovWhP3iz5YTx90T+3b3d2NdY+Ojka3g/JXWhPUNspf6RpbW1uxLuXttN6ofxsbG4Myyg/0gfU035TTbt++HcvTOFE7Ur/n5uZiXVqDqby7jlNf6MPyaV1RTqPfS3NIcUTjnNYE1e2cZTpnlj9JUixS/qM12Nm7SYovikXKSSkOaJ9Pv0d7MV0j/V43nlM5tSOd6yiX05kl5QgaZ8qB6RqU61IuoPkjnXV83mj8U787ebgqjxONRRp/GmfaJzptO090pkv9o/bu7OwMyuisTnOa1iWtEZrrdF9L93w0TynH0FkqoTGi3JXu2WiPoLx/48aN0e1Ifenu8SlnpxioqnriiSdieRp/usdP5Wtra7EuxVcafzrvd+5zqM2dtU2/l86tnXuRqhxLnfsO6geNc2ofjfN565zhO/cotE465xJCeSPFTOecUJXXMf1eus+k2Kf5TjFD5zGaq9RmqpvGiJ4T0LOzNFfpvvhe7Uh9pHV8v89PqX73WUNqM8VXGg+6f6WYSfs09buT46l/qS80J3SPkvIz9e+80Rmic95P9y60tulsktYVxUbn2TOtV3q3kfI5/V7n+TVJ40xjR3OV4pxilM5ZSed5Mq0fakfKgZQXU/kjjzwS61KbKRd0rnG/Z6TuvptyHa0J6h+df5O0h3Xu+6g+9XuMh/epgyRJkiRJkiRJkiQ9ZHzBKkmSJEmSJEmSJEkj+YJVkiRJkiRJkiRJkkbyBaskSZIkSZIkSZIkjeQLVkmSJEmSJEmSJEkaaWpsxVu3bsXyk5OT4UWn8mVTXbru5ORkLJ+YmBhdl9px4cLwvTK1I9WtqpqdnR2U3b59O9Y9Pj4e3bajo6NYnvpIbT49PY3lafzX1tZi3d3d3UFZGvuqqtXV1Vg+PT09KKP+pTGqqpqZmRmUXb58OdZN1059ruJ5TeNMdTsee+yxWH7x4sVBGY0FzffS0tKgbH9/f/TvVeX5npubi3VpvSUpBqic1s95o7FLa5biq5MXSVpvaZ6qenmU2tzJo526lDcoztP4U5spng8ODgZlTz75ZKy7uLg4KKP+Xb9+PZan8d/Z2Yl1qS+pzTRGqS6tV8pfab1RjM7Pz4++Nq2fNKa0H9DYpfZR3qA1kXLPWeR4Wpvp2g9LriNpzdI6TvNNdTvxdXh4GOvS+kn7YPdcl9YV7WFpbS4sLMS6ZG9vb9R1q7gvaaxpXd24cWNQRnmjc44ntCZS+zrnZ4qvdC6vyvFF40xSzNA4p75Q22gPS79H+xLNSYovGrvU5u44p2tQ/85TJ2ZJGvvNzc1Yl+7B0r0L5Rda7+k3KQ7T/VNVHg9qx/b2dixPaE2luKBzAo3d1tbW6LalmKPxTOe/qtzmtJ6q8r5B5ZTnUr9p7XTWVOd+pirHOeWBpNO/qjymFM/U5vSb9HspDuj3qN9prVAcnTd6PpLW/PLycqzbeUZG5Z373e5zwI4UGzTfaQ5prdG6Smue4ohiNN3/UN3OPVgnnmlOaOxSfFEu6Ny/0r1nmhc6l9D+n8aDfi+dZSk+6dyb4ovuRTq5n/qd9mOKI7pGJ1+eN4rRdO6hNndikaysrIxuWyenUQxQ+1Jf6PdSeWd/rcrnLxpnivN0rltfX49103p95JFHYl2K87Q2qW103kvrqjPfNCf0e2lP75xvqH6nzTRGFDOpvPM8s6rq6tWro+umPews9gMa5zH8G6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIvmCVJEmSJEmSJEmSpJFGf4U+fcS5Kn/QmD6knj6o26lL0sdt7yV9+HZjYyPWpQ/4po9Ppw/T0++lj3BX8XikD/t2+314eDi6bvqgMX2Y+fr166OvQR9K3t/fj+WdPnY+2k3jnOaFPihO104fcqZ+pzin2KcPM6fYpXGjOVxcXByUUZvTmu9+CDrVpw9gnzeKjbR+aJzTR+Hp49ydHENto3lN0kfeq3IMVOX4p1zXyTEkfdCd8sPW1lYsX15eHn2N1Bdag7QPpmvTmqA4pw+yJykO6LoUGykeqQ003yn+aZxTPNP6SXWrcg6kce6Wj3UW16Xcet6ozZ3zV+e/75z3KG4pZlI8p72qinNuKqe+pLVC40l5McUz7fMkrTca59RmWvOd/bizZ1blcaIck8Z/dXU11qV5TbFE80rlKe6ofynuKBZJ6gv1j6RzSOcs2rluVT4/d/v9INAZPsU43Zul/NI5d1XlsxetP2pHajPlRFrD6Xz0wQ9+MNZNfVxYWIh1O2uH2nzz5s1YnvID5duUj2g8Kd928jDNYVpre3t7o3+vcw9Wlcf0ypUrsW4H3bukPEB7Ac1V6kvnLFyV47yzf3XOm1RO597zRn3prJ/O2aZzhqR4pjya8swf/dEfxbpLS0uxvPMsK60fymkUX6k+xfPa2losTyhvpOc/8/PzsW66t67KY/TUU0/FutTv9PyAcnwnNuiska7RfYbUOYem9lEepr6kPEpztb29HcspvyYpzik/dO4ZHpb71844d/YUqkv7YBo72jvo2inOu3tKype0JtK1KS/SNdL6oX7TOk45sPNcqHNureo9p6Gcm+KOzpepHRS3nXXVff+T0Fyl+0yav849KV2DcmDnnquzBikHpvVDMTDGw5ElJUmSJEmSJEmSJOl5wBeskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSL5glSRJkiRJkiRJkqSRpsZWnJiYGF1+8eLFWPf4+Hjsz9WFC+Pf/d66dSuWLy8vj7727OxsrHtychLLp6aGQ9fp9+npaaxL5aurq6Oue6/yra2tQdnk5GSsm+Z1e3s71qVrJNPT07Gc2pyuffv27Vg3xUGap6re+FMMUDuOjo4GZYeHh7FuisXFxcVYl8rX1tYGZTMzM7EutTnNC9VNY0R1Ozpr/kGam5uL5SlGKZ4PDg4GZd3+pTVIv0fXTuWpbVW9OKd8SWPXsbGxMSijftP63tnZGZTRGrx8+fKgjMZzc3MzlqcxojVIY5fyF41nygX0e3SN3d3dQRn1m/b/1Gbad1PeoL2b2kFx0EFxMBbtd7T/p37TXJ23zljQnKRr0H5O10hrYm9vL9adn5+P5SlGKW4pB165cmVQdvPmzVg39ZFyaMpHVTn+aS+l8UixROebtOYpFim3JvR7lC/TGqJrJN34Sv2mXELjn8o7dbs65w2KuzSmnbGjGOjuE881ytlp/dFYpmssLCzEup1cub+/H+vS2Kf2UT6jvTjlo0ceeSTWTe3r3PNV5TyQ7pPuJY0d5dU0RtRmWqtpT6LzCuWudCagfnfOUpQHOr/XyX8UXyn+6RxE7Uj5iOYq5fGqPN/UjoRi4NKlS6OvcRb3PmeBxijlJDpLpfnu5vbOvHaukc5oVZxzO8/f0hmr2+8U5xRf9EwttZniK/WbYp/yZarfWT9Vuc2UNzp7KZ1X0rW7564UB537O9oP6AyR+tLNl6l9dIZIexjlfVoTaUwflnMe9SWNUef51vr6eqxLazDljbN4nrm0tBTLqS+d546pL91YTHFA65juX1PcpXcVVVUve9nLBmU0VxTP6VxN8dw5m9M4p1ikcaZ5TXFOuZWunXIV5brUF4oBGqNOfHX2R1oTaQ4pBjpnYnpeO8bD8UZDkiRJkiRJkiRJkp4HfMEqSZIkSZIkSZIkSSP5glWSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRppamzFk5OTWH58fDwou337dqw7OTk5bMBUbgJdI9nf34/lGxsbsfzSpUuDspmZmVg39Y9QXyYmJgZl09PTsS71e3t7e3Q7Ll68GMsXFxcHZTSvaUypf6enp6PbRuNJ10j1b926FeteuDD88wI0zvR7VH/s75GVlZVYfnh4OCijeN7a2orlqc0Uz0dHR7H84OBgUEbzncpTjN9LJ2bOG63BTptTrqP/PtWtyvOa5ule10jzMjs7G+vSukrXpthP8dy1uro6KKM8Re1IbaY1kcpprc3Pz8fyzj5Bc5jWVacu5S7aO9LY0ZqnPWV3d3d0O1Luod+jGN3Z2RmUUQzQtSmWxqJcR7k1lXf2mQepc/6i2Kfck9DYpfmmutSONKYpPquqlpeXY3la9xSLaYyobucatP/QeTZdm2I8ldM4d/Y7ugbl3Lm5uUFZ56xG1yXp2p09syrnwM59Slfaj7t5I+UeOoumvtC+Rnkj6c7Vg3D9+vVY3slzaew3NzdjXVo76dq0f3XKaX+mnJHmJO2tVTkGaO3QHpjyDl2Dzivp2hRbKe/TeHbu/Wk86eycUHwtLS2NasO9pHimcaY9KZ3hU76uynOyt7cX63bOabRv0zinNtOaSNeg36N4TuPRvQd+UGiPSGNE9xedsw2Nc1rHNEadcjrbdM4rNEYpNmj9dJ6x0JrvPPeiurTeks65l3JPJ9d1zsM0zhRfZ/EcKqFxTtfu3PtU5Wcb9Hude2OKxRQb9GxjYWEhlqf2dWLgQVpfX4/lKT9Tm1MOfPzxx2NdOkemMzXtKZ34orp039F5FpzaR/td57l9inH6vaoco+ldRVXVe9/73tG/13kWSeu4szY7z5toD6PxT7HbPc+m8aAxSuNBuZX6ndpMdSm+HnnkkUEZjVHnOQGNf4rFzr3us/k3WCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIvmCVJEmSJEmSJEmSpJF8wSpJkiRJkiRJkiRJI43+eit94DZ9vJ0+Qps+LEsfod3Y2Ijl6UPc6YPWVfyB9Z2dnViepI9GV+U+0keHqTyhcU4feqd+dz4CTB+TTh/23d7ejnXp4+HpQ9z0wXr68PoLX/jCQVn6KHlVjg36GDjFRro2fei68wHszkfhKV6WlpZieZpv+hg7XbszV2nN0jqhj0mndlDd80Y5KaFYTONB40lztby8PLod9JFw+s2E+p3inOI5zSt9QJ7Kd3d3R7WhW05jlKR9rYrzSeoLtY3WSsrntB+ka9PH2KnNCa1BKk/to1yexojaTHt0Kqdc3sm5tJemNtOap303te9hyXUUoylmOjFAY0/lnbMhreM0L7TWDg8PY3mab+p3Z8+kdZzaQWuCzmppDim3pjMStY3iubN3p9+ryuPUHbsOivOkE3fUtk6b6UyWxpTmhKQx7axBQusq/V5n/3lQaO2kflB+SWNPdTvnks69SFWOF4qhzt5IcUFz3ambxonOWCSdKzp5p5vnOmeNzjjTGKVy2gsoR9G+NrZtVfk+n/qX1jatd5qr1I7Oubcqz3fnuQTlB1pX+/v7o677XOjkDZLGf21trfV7aUxpXim+Ovs2xRedhZIUM9S/zjNRahv1O41dirmqHPvUZnqumlCeovHsPGtI+wGtQRq79JyArkFt29vbG5TR2HWu2znT0e/R2SLNC63N1A76PepL2oM6z8gepMuXL8fyNHbU5kuXLg3KaB/t7Lt070P7UhpnegZIz1g6z+0799zUlxRfaV1WVa2srMTyhPJ+ah+1mXLr5ubmoIzOWfTMvbOnpDHq3uN3zkid91DUjvR71Gc6x6c1mPLtva6dUGx04pnOaunanbh9Nv8GqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIU2Mr3rx5M5bPzc0Nyi5cyO9tT05OBmV7e3uj61ZV3b59e1A2NZW7cXp6GsupfqcdR0dHo3/v1q1bo9twcHAQy2dnZ0fX3draiuWTk5ODsjSedO3Uj3u1Y2ZmZlC2sbExum1VeZzTWFRVTUxMDMpoTihGp6enB2XUPxq7ZH9/P5YfHx+PvgbVTf2en5+PdXd2dmL54uLioIzmJI0HXXd5eTmWpznsjMWDRO1IsURxlOaE1g/NVYov+r00f/Sbh4eHsS5de2zbSBqL7rWXlpZi3ZQfuu1Ia57GgnJrujatHyrvXCPNK41FZ/w7MUDo99K8Un6mNbiwsDAooz2a1tvKysqgjMYu5Tpq28WLF2N5mkPaD84bjX9ab53zTSfGq3LcdfY70jnrEcp1KWbSebgq55iqPKYUz1Sexpr6nXI/rRPqS7p2J09V5bXSyRtnkae2t7djeTq30m9SjHb2R+pLKu/upWmuKI7StSmOOvP9MOQ66nPqH81H5/6pc99BbaPYolyS0PpL16a6qZzWCM11Gie6r6J+p9/sxCddl2I55Si6z6G+pPMK/V4nNigGUn3qN107odhIfaHY75wJaF47+Y/uc2iuEro3S3sj9fu87e7uxvLV1dVBGT1/SzrrpCrf43efIXXii+4RU/zTOk6/R8+bKEY7+ZLG//r166PaVlV1+fLlQRk9Z6N4Tn3s5Ieq3l6a9oNOHFH9zu/d69oPSspJ1DbK8ZTXkhR3NK8UG51nog+LlCNo7+g8d6TnbGmMaA3Ss4YUi/Tehdrx5JNPDspS3q/K9z8Ui51yqktx29knzuIZUud5X+fMQvGVrkG5rvNegsZ5c3Nz9DWoHenaFLedeaVrdOaqE4t0Xcr7afzX19dj3TH8G6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIvmCVJEmSJEmSJEmSpJF8wSpJkiRJkiRJkiRJI02NrbiyspIvMDW8xO3bt2PdCxeG73OPjo5i3cXFxbFNw9/b2dmJ5ZOTk4OyhYWFWDf1r6rq4sWLg7KJiYlYd39/f1Qb7iWN0/T09Oi2VVUdHh4Oyk5PT2PddG0ao1u3bsXyNHaXLl2KdakdJycng7K5ublYd319ffR1aa5SX6h/JP0mzVVqR2dOqnL8Hx8fx7oUz2ltzszMxLrp2tRmWt8Jxe15o3yS5qoznhRHy8vLsXxra2tQRnkjrZOqXpspvhIao7OQ2tGZk6o8TtTvFLvduUprgmKf2pH60skbnetW5X7TOu6gGE3lNK80/ilH0H6Q1mBVHo9OOzprvqp3ljlv8/PzsTz1uzOehK6R9hrawzrXprbRHCadWKTYp/jqxDPtx51z3ezs7Oi61O/OGYnGI/WFxmh3d3fUf99F9zQkneM79zrkLGKUdO4zOrk/xRz9XmcsHpTOvRKNe8pHlKM6Z/ju/UVaw3R27qzhzj0YXffy5cuxvHOPQmu7c6ZL7Ts4OIh16eycrk33wClHVVWtrq4OyigWU5spv9A10ph2zmNVuc03b96MddPY0XU7Z3W6Ruc8THXT+iFUN7Vve3t79HUfJIrRNEa01jrnPxpnOlsm9KwurUHKG7SOU26k51Dp2hS3VJ7u+6h/dD+5tLQ0KNvb2xv9e5SPKD+na1Ds0/in+pSfO3sKxV26NrU5PUupyn1J+Y9+j9pMeTvtQbR3d56/0bOGdA2qS+Wpj92z83nrPFdNaP4o9tN+QGu7k6eoHdSXa9euxfIk5WeKOWpziufOnlKV9w/6Pbrv6Ojco9A4p2ucxT1p5zkUnZFo/+885+w8e6Ecn2KDxpnydudMnGKG9miKr/TspfNc/Nme+ztfSZIkSZIkSZIkSXqe8AWrJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI0Uv46bUAf+00fXu98GJg+8N352C99hJY+Ory4uDgoo48n08dw08d66WO/qS/pA8BVPB70EeBO3fRR60476CPonY+H00eOU9uq8thRbHQ+Xk19SR85Jvv7+6PbQbGRxpnGkz7YnNpBdakd6aPW9AHsNEZbW1uxLq3N9CFu+r3zRmPU+dB4ugaNEcV+Jza2t7djeRr/1dXV1jVS+6jfqc1Ul2I0XYPyMOWCVE6/l2K/k2Oq8l5DuaSzP3bqdqXx6O7HqX00V2P/+yrOzymf07zS+G9ubg7KOvmZpOtW9cbjvFEcpXmhumlOqM+dHE+/R+XpLENxRGek1D5qc9rDKI5oPFL7aM+kaye7u7ux/OrVq4MyOiOls31Vjg1agzT+qZzO62m/ojlJubwqzze1jdb8lStXBmU7OzuxbjqTUQ6l/T+NP8UAjX8aJxqjdA3KzzT+aW2exV51v+j+LrWNxjLprvdUTr/Xuec7i3szqpv6SDmjc+/SOf9RfYrD1OaUr6s4NlJfLl++HOtSO9Ic0vpL16Cc2NmLaT+hPSK1g2Kxc39OY7S0tDQo6+bmNB70bKPTP4qNVJ9i47zR+G9sbAzK6Iyc1lo3j6c4pzMFrYm0BpeXl2Ndipl0301x1NkvO8/qKF9SfKXyzrO6j/iIj4h16bzSuRekvNG590/5uXOPSdem+KLYoPyapL2bchrNa+pj9/4wzSGNc/o9ikUqT/vHk08+ea8mPuc67wlSXYrFzlxRbNA6Trm4u5ema3TeYVCuo3akvZuuQfc5a2trsTxJubUT+4Su0XlPQPGVckFnTqh93WeDnfFIfaE203yn8zbVpbydYobuuTr3ctSX9Ayc4nYM/warJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI0ki9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0khT93uBxx9/fFC2u7sb6x4dHQ3KZmdnY93bt2/H8pOTk9G/d/HixVi+ubk5KJufn491JyYmYvnMzMygbGoqD+fBwcGgbGFhIda9fPlyLE99TGNxVtK8XLiQ38cvLy/H8jTfaSyqeK6mp6cHZcfHx7FuGtPJyclYl/qS5pCuQVKbt7a2Yt0UdxRHdI0Uo3QNipk0drSuTk9PB2XXrl2LddNYVFXt7OwMymhOHhap3+Tw8HBQRmNP45zq03jS2KU8SnG0v78fy2/dujXqutQ+qkvS7xGakzQenfiiup0YoPmmXHe/KC92pJzd/U1qR9ozO/t8Vc51aa3d6xpLS0uDMprvtF/RGHVisTvODwqNXVqD1D86IyUUGxsbG4Oyubm5WJfakdYV7d2ds9NZ7EvpzFmV9//19fVYN62fqqqVlZVBGfVvb29vUEb7D/U7zSGNM7U5zeHa2lqsm9bg6upqrEttTnteNzbS2NE6TucvOpOl696rHQn1O61vWvPpGrRXdfYwOvOfJ4rDNCeUo9JeRWcVKk9xT/mTznpJJwd3pXZ07nWrcrx09viqPKY0r517NprvlJuvX78e69J9eydXduab9sDOXNEziBTnlF9SOY0n9S/NK+UXyrepzdSO9HuLi4ut39ve3h6UPQx5rqqXs6l/nXtPksa/m+vSWknPDqhuVe43PXdMZxCqS88MUyxSruvcM6RzXlXuN/0e5cs0L3QNOpencupfijvKMdTmdG7qPNeryv2m5yDp2nRdisV01qbfo2ukeKR11bl/pRyY1nG6h36YpLij2Og8b+r8Xvd+OdWnttE1Onv32P/+Xr9H9xIJtaPzzDDlJIrnTn4mnWcQlC/TOqY20Bil8e++l0jXpnnt3AtSjKZnOt299Cz6nXT2ifu5t3q432hIkiRJkiRJkiRJ0kPEF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJI+QvdAX0U9oknnhiU0Udo08dwux/7TR+hpY/v0gd102+mD/JW8Yeq07Xp99J40IeBn3zyyViedD6IXMXtSzofk04fUqffozbQtdM40djRR6YTanMa0/QR7nu1I5WnD8VX5fjqfOC7Ko9pWif3srW1Nbod6cPm9JFq6nca56WlpXs18aFEay2VLy8vx7o0r2k8tre3Y12K0TSHlNNWVlZieVqblHOpHQ8K5cC0BqnfHZ1cR3Vp7DpSX2gsOjrjSfUpx6e6tH4WFhaoiaPrpjxVVbW3tzcom5mZiXVTX2j+KF929t3zRus1nVlojFKc0/5Dc5V+j2KDxnlubm5QRucK2pcSakfK25RjaJzTNR555JFYl66d+kIxl8aI2kb5K41HN2+kdtD+k9YbxVfn3NNtc0Kx2Ilnks5U1L/OPRfFUboGXZfakcbjLPal+9VpA81pWifde4POeYzGfux1u6gdKUfRXkB7Y8rD3fNYJ++cRY5KZ+3V1dVYl/q9s7MzKOucsyln0L6W6u/v78e6NB5pP+nkHYrbzhrsxFFVbl8nNmgdU4ymc8zi4mKse95ojDr7Sdr7zyKPp/VwL+kc0zn/VfX23dRHynUktY/aTPGV2kFzlWKXzrcUGwk9l6B2pDZ3cjzVpbFLeZvmmvJJ+s1OvqTr0p6S6lO+pL6kZ9WXLl2KddOap+tSzHT2Uv0/NEa0T6Q4pzVIayKVd55Rdu9RUj6he3xaV6k+9TvtS51nU1V5zdMa7JzvO8+6qc00/qnNnWcYpHP/2n3fdO3atUEZtbkzdh2d/tHvdd4rDa73x/4vJUmSJEmSJEmSJOlPGV+wSpIkSZIkSZIkSdJIvmCVJEmSJEmSJEmSpJF8wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJGmhpb8fT0NJZfunRpUHZwcBDrpvLp6encsKnctAsXhu+Eb926Nfr3qqrm5+dHlVVVnZycxPLj4+NBGY3RzMzMoGx2djbWpX7v7e2Nrjs5ORnLO27fvj0oOzo6inUfffTR0delOUljVFU1MTExKKM5Sf2+ePHi6OtSOcUotTm1b2lpKdZN8UxWV1dH/x7FAMVo8thjj8Xy9fX1QVln/sj29vboug9Sp81UN60VisW0tqt4TBPKBSk30hqkGO3kHsoRHWm90Tqh8U9jnXJaF62rhYWFQVlnTqp6cZfWPOVFum7KBZ2Yo2tTjkn9pjGinLu5uTkoo72b5oqunRweHo6uS+tqZ2dnUHblypXR132Q0jmmqrdW0jUop9F8pzmkdULzmn6T4pnmKqGzWroGrTWa7xTPaX+t4vyc5oryZYrnzljQtWlOaOxobpOUWyluqS9zc3Oj61J+SHsK1U3XpjVF+auTe+jaqZz2iZS3qW7nzNI54z4o+/v7sTytVzqnpbGgcadxS/UpR1GuTNc4i7MNXSOttc69T1XOA938nuaQ1kiaVxpPuq9K9SmOdnd3Y3kaU+pfuv9ZXl6OdWmcU65Mua+K95nU785zkO5ziXTPcPPmzViX+pLGiWIjzWH3/iLlPxqj80brOMUoxX6ak86eTej3qM1pf6XnBHQm6DyrS3sx7fH0eynO6feoPMUdxXM6a9BZkfJUakfKJVVVN27ciOWdvZTKE4q71D46l9A5NMU51U05gtY8lad+d2KgKscotTnlOtrD0rP8qrzXb21txbr6fyg/0P6Y1jflRdpLU8ycxfNMkvIM5Z4nn3wylqd47jwXojNB51kkrUFax6nNlJ/T85/u8/JUfhZnfjr3pGtTbqX76M7zPirvPo8c04Z7laf46j4fudtzf+crSZIkSZIkSZIkSc8TvmCVJEmSJEmSJEmSpJF8wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJG8gWrJEmSJEmSJEmSJI00NbbiyclJLN/Y2BhedCpf9vj4eFA2MTER61L57u4utHDo4OAglt++fXtQtrm5GevOzMzE8snJyUHZzs5OrHt4eDj6uiSN//T0dKyb+ldVdXp6Ovr35ubmRrWhKvePylMMVFXt7+/H8hRL1I+jo6NB2cLCQqy7t7cXy2dnZwdl1OZObJDUZpq/1DaqT3NFbbt48eKgjOYktYNigHIB9fFhcOvWrVie4q4zztvb27Hu0tJSLE/jT7FPc5VQPFP+SnmU+p3m+8KF/Od4qB1Jis8qjufUvk7MUZspnjvrmOYwrSvaBzt5kaRrp/2cfq9z3ar7n5OqHAc0V2lOqnr5OV2b8gO1I40H5YKHRTpb0JpPc0jxQmPUiQ06A6Y2d3IMoXWV+kixT+fLdG0619F5dux1Cc0VrZM0plSX1gr1cezvUWxQjHbaTNdO40/jnOKAxpnmNbWPfo/GOV2jcyajeKb5S/n5LNbg/aI+p/uAzjydxZ5LY0znsXTWo/mge5TUl7PIO5Tfb9y4MSibn58ffd2qHON0jVSX9lwao5SzO+egqqrFxcVB2dbWVqyb1h/tdTTOqY/Uv87apvu7znMMiqPUDsrNnWc6NFepzTQntL7T+D8Mea6K75XS3kjnkhQDtMd04ojmj+YqxT/9HrUvoX6n50WdmKvKfaHYoHLq41iUNzrPrKhttE90zlgJ7Xe0BjtnSJrv1GbKrakdVJfWYIoZ6l/n3pjmO40/5XL6vfRMoLt3PyidZymUH1IMdHN559kNPZfo7IPkftcg5Qd6Xp5+j+rSXKVr0H1cah/NK63BhHI8PXNPv0nznfYUel77IN9L3O/5pLv/r66u3tfvVfXe9yXdfTTFaPfMfzf/BqskSZIkSZIkSZIkjeQLVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaaTRX2+lj+92PjSePpL7/ve/P9b9iI/4iFi+trY2KFtZWYl16aPK9AHlzjXSx3PpY7jpI9P0UWX6AHkau6WlpdY10lzRR9rT71H/aIxSv+lj83SN9KFk+mh3+kg7jTN98Dn1mz7uTOOf6ndijtDH0dPHvOlD1xQbaZzo95I09lUcM6m8k0sepO3t7Vie1src3Fysmz5iTmuNYjTVp492Ly4uxvKdnZ1BGY0ztY/W24OSYonWK+WNtAap7tg2VPU+eE6/R/Od6tN8p/51P2Kfrk1zTe1IuYfyRsqBlBepHZ01QddIY0fXSHNCsUE5N7WDfu+80d6W4pzanOZkd3d3dN2qquXlZWriAI1zZ31TOzrXPYtr3G/dqjwvnXju5Jiq3n5AfUm5ivJXyhEUA5SfU19o/jpjR2OUrk3jRm0+izNjQvkr9ZvONzRXaW877/NDQnGYzsN0Rk5zSuNA5Z17lM4+02lzVd6jO2cbivvOWZZ0zsm0RjrnI8ol6UxN+xrNVYp9qtvJ+3SGT/PaPWN17vsoDjp103109+ycxpTGOenu8Z15PW80f+k5WScv0jNA6vdjjz02ui5J40zx3Hl+kO5b6BoUt9SXlGcoP6fnW1V5DumMnNq8tbUV65K0z9Nao3FOebST96l/nWd1s7OzsS7NVYoDanO6Bq0fiq+zONOlcxrFV9rT6UxH/U7lly5dulcTz033mUeS5pVyKI1RagfFxvz8fCxPzx0pjjqoHekZZfe+6iz2vNQ+2mtSXWrzWax5ehZ85cqV0e1IfaFcR3tNyrl0FiWdvS09N6YYoFzQORsSylVjdWK/6uzPcP4NVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSL5glSRJkiRJkiRJkqSRpsZWvHr1aiw/Pj4eVVZVNTs7Oyh70YteFOtevHgxlr/kJS8ZlE1MTMS6HQsLC612TE0Nh476TeXJ0dFRLE/tOzk5iXWXl5dj+enp6ejfS3M1OTkZ69L43759e1C2srIS61I7lpaWBmU0nun3aCxo7FL5hQv5zyEcHh7G8rm5uUFZGvuqPKY0nvR76dq7u7uxLvXlypUrgzKak9TmtB7upTPO5y3FflVu861bt0Zfd35+PpZ34ojqUnnKXzRXlOvSuqIYpRyRUDvSmNJ1KWbSmqA1mK5Bdak8oTFKOa0qjz/1O+VAWq8k9Zt+j66d5oriPK0ryuXUjhSLFANU3onRsW2o4jWY6nfz5YPSiXMatxQDdJ7q5HiqS2N3cHAw+hpUntYsreM0RlS3c0alOTmLc24HxXnKU50zWVWew+np6Vg3zRXtVRSjtDY70vjTWaGDzqKp390Y2NnZGZSlcwXZ29uL5TT+aQ7pGueJ5inlLsoNKcYp3iiWO/colOeuX78+KKM9l66R2kFtTmuHYojGeWtra1BGcd+5V+qcqbt5NdXv3qOkMZ2ZmYl1O/eC1I50f722tja6bVX53pHOrOka1ObOfQe1jeb7fs9YdB/XeeZB8XzeaA2mee3kOsr5nb2Y6tLaTPNKdWm+U3nn+Q9dl9Zxah+dhzvnEtpHUyzSeYzGf39/f3TbOuuY1lVnT6GxS32k/EDj0XnWkGKR4ugs7l87z1iofykWKT9QPKcxSmeQ58JZ3Een8ew8K6rKY0rPYM9iHZ+F1Bdar9Tms7j/SeNE45/OBZSnaOw+8IEPDMqo39euXYvlqc10jc4e1om77vPkzj13J5d37l+77veZBz1/6Jyr76cND8cbDUmSJEmSJEmSJEl6HvAFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRppKmxFY+OjmL5zs7O8KJT+bLLy8uDstnZ2Vj34OBg9O9NTk7GultbW6Pbcfv27ViXyqmPSeoL/fcnJyexfHd3d1C2t7cX69KYHh4eDsouX74c6964cWNQtri4GOuSCxfGv7+fm5uL5Wm+KRavXbs2KLt161asS+Oc5vvixYuxbifuKI7SGE1PT8e6x8fHsXxpaWlQRv2ma6fxmJiYiHX39/cHZSm2qniMUjn93nmjcU7to3Wc6qZYruLYT3N4enoa61Kb03xT3uj0m+Y7xTPlI1pXKRZpvVKcp3Gi2B/bhqqqmZmZ0fWpbR00zmkNrq6uxrq0BtN8U4xSLk/xT3t3QnmRckEaj04c0bVpXaXcev369ViXYiONP+1h543Gf319fVCWzk1Vud8UR5QLOm2jsUsx2omBqrwmaB2nfs/Pz8e6nfMG7SmdmOmcN7ptpn0iob6kNUF109pM+a+ql6doXmnsUp7p7IMUc5R7Emoz5dzO/p/WJo0FtTnFKOXF80TzlOKiE9+dva6qamFhYVD2xBNPxLoUL2lPSvm6is88aV5pvSebm5uxnOKiE4ck5Ywnn3yydY2kc7aksxTFQYolmpM0drT+qB1p/dG+QesytW9jYyPWTfFMezw9j0lxQP2ma3fiOf3eyspKrEvXSGO0vb0d6543yl+pvPNsg8ae9ty0R6fnWPdqR7o3pr2f9sZOXyiPdnTuX2mu0pmMrpHGiPJwp5zmpLOfd3LrWdwz0Bqka6R1TDGa2kd546mnnorlae+m8ew8u0zPPquqPvCBDwzKUs6u4vNG6mN6PvxcoHhOOYL6l8aje090Fs88UhxQfqCcm8aj81yVcis9o+xcuzP+JI1H5z1DFT8nSzrXprqpnOKW7oFTOcVi536yc+bv3r+mmKH7BpLyJeX4zrMUepeV6tN6HcO/wSpJkiRJkiRJkiRJI/mCVZIkSZIkSZIkSZJG8gWrJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGil/ATagD72mD6HTB6LTh7Hpw7n0UeX0we3Dw8NY95FHHonl6ePh9DFc+gjw0dFRLE/SeExOTsa66aPrnetWVW1tbcXy9CF0+qD71atXB2X0Ie8UA10UB6m88zFpajN9QD6V04e/qR1XrlwZlNGcpLij8aQ1mD4yvby8HOt2xyNJc5I+0F7FH5NOa7bzofgHiXJB52PXKW/QGHc+Vk7jTLGY8gnF197eXixPKD+nj9AT6ndab1SXxjTFHc0r5Z6EPrCe8jmNc2euqG2p3zRGFLdprmhPoWuneKQP2ae6tN/RvpTa1xnPqjwvlJ/TfM/Ozsa6FItpDju55EGiGE3rh848KW/TWqP8leabrtFBewrNYSqneU17WPccmcqpbTRXaR1T3kh7Cp2fKZen9UZtozWYxpTakdrcydn0e5Q3OucsGqPOuY5iZmdnZ/Q1OvF88+bNWLdzXZLOBZ1zxYNC+1rKaRSHCZ1vKT7T79FZneIztY/OY517s06OovGk31tbWxuU0T0wXSP1sZsHErq/S+j30j1fVZ7DzjgTio2EYoPKk858U/6kNqccQ9egXJnycHqGUZXPerRP0Xynfndz5YOS9qmq3pkz7Ze0Xul8lObk0qVLsS6d09KaWFpainUpb6drUF/SmqDxpJhJ49y5F6nKa6XTDlprNM6dMxbdA6f47zyvoP51zt/0e3ROS79J6+RFL3rRoIz2jhe/+MWxPI1d53lmVe4LnbFSnFPsU27tnGXPG92TpjMV1U1jR7FIc5LijuKWxi7Vp1jsnHs6+y71m2Kjc1YmlE+SzjMyivPOmu+cUWns0nrtnPUI/R7pvEs5CxsbG4Oy7rpKa7bT5u79QXdMPxz/BqskSZIkSZIkSZIkjeQLVkmSJEmSJEmSJEkayReskiRJkiRJkiRJkjSSL1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSFNjK05PT8fyra2tQdnly5djXSpPjo6OYvnh4eGg7Pj4ONa9cCG/P071Dw4OYl3q98zMzOjfOz09HZRNTk7Gurdv347lHVNTo6cV+5dQm9OcdFE7FhcXB2WdMZqfn4/ldI1UTv2jNt+6dWtQRnNy8eLFUWVVVScnJ7E8tZn615lD6l+Kc2rb9vZ2LE/Xnp2djXXPG7Uj9XFiYiLWTf2jPEWxkcopT9H4p1ikeH700UdjeWr32tparDs3NxfLx7aNrpFy6L2ukeKc8nPHyspKLO/sKdTmTl5LfaH+0TpOY0rjvL+/H8tT/C8sLMS6aV3R+qE8lXTyYlXuI7U5nW/S3l/Fe02al07/HiTqy/r6+qCM+pf26N3d3VY70jVo/XSsrq626nfOl2ld0d5NOnsercGUT2jNpzWxs7MT69J5Pc0LtY32mhT/tA+murS2KRekOezsHVVVy8vLo6+Rcgy1mcYo7YOdXF5VtbGxMSijXJdi98aNG7EuXSO172HIdbSGU7zQPKW57t6vpWvQGbkzxt0zRSc+E1qr1I4UW/R7dO20F9Nzgg7K2enanbpVea46Z3Xac+n30rUpv1DOSPmd2pGu0c2rnTbTeTGdH2iMUhx17sEI7YHPRylfdnNd5xqUn9MZZG9vr3WNFI8Uo2m+ab1SLHaeE3Tiq7NeO+eg7u/RmTXlOup3B+WNNHad/lF9uo9Ocbe5uRnrUv6iPT2h8U+5mM4QqW7nuTi14yz23bPQia9OHFF+oN9LY0TjTGOXzhaUHyg2OtJ4nEW/uzrP5TrzTc8i09o8i3uzzjXO4p6Ixq0zntSOs2hf2pfouhRH6TkS7T+ddUzO4v3b3fwbrJIkSZIkSZIkSZI0ki9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0ki+YJUkSZIkSZIkSZKkkUZ/Yb3zsWX6kG368Dp9sL7z8d30Ie/uNbofa04fBO98YJ0+pksfp0+ozTMzM7F8a2trULa6ujq6bneck84H5KvymNKHi1M5ta0z/hT7NB5ra2uDsvQB86o8HhQD1O/Ox8qpHZ2P1qfxoOvSGO3s7AzKOrH/IFHMpDHtfBSbPs5Nv5fGmX6v88Fz+r00J1X5w/I0r6l9FIuUL9Pv0TVobaZYonzZ+T26RmrHyspKrEtzmNqRPhRflcduYWEh1qXYSGs2taGK1+b09PSgjPqXcjyNJ7U5XbsTR9SOS5cuxbppL6WYo5jp5IjzduPGjVieYonyRorR7e3tWPfw8DCWLy8vUxMHKGbS+NP6SXFblftIdVN8UWyQtO/SPrG0tBTLUx87exitbdoPOmdwOoum36R2pDHq7oOpfZ14rqra3NwcfY1UTnmKylMfaf3Q+S2NP/UvrSvaUyhGU3xR3fNE59O0tmm9p/nY2NiIdSku0hqmWKa5TnmH5qlzL97Zi2m97+7uxvJUn9Y7lac4onYkNM6Uo9K6pNigNZyu3Tlj0Vh05pvWeydnU5tTOY1n516c9tHOWtnf349109hdvnw51qV5TfmE+n3eaK4odseisaC5Su2gHEP7V3oORTHQ2Ys78dV9HpP60nn+U5XnqvN8hPIw7cWpHTTONFepfZ3zSmePrsrz2omBqhzT1OYUiy984Qtj3fX19Viexqh7lk33r+lsWlW1uLg4KKPxpPI0Hp1n3Q8SrYk0HtS/dCajtU17aapP8UxnxrQfd+4NqnIfqS/pHp32DupLujbFLa3BdG26RhoPigF6p5ByD12D+t05q6U9j8aZdN5P0dh1rpvmlepSLNIZNaGzWhqnzrNuin1yFtd4xvX+2P+lJEmSJEmSJEmSJP0p4wtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIU2Mrbm5uxvLFxcVB2fr6eqy7t7c3KJucnIx1L1wY/+43Xfde1zg6OhqU3b59O9ZdXl6O5QcHB4Oyixcvjm7f7OxsrHtychLLkzT2VVWHh4exPPX75s2bsW7qC7WN5pDakaTxrKqamhqGKI3z6enpoKwbG+n3qO7+/n4sn5ubG5QdHx/HutTvTt00HjMzM7EuzUnqS2cNpnGr4nW1tbU1uu55o7lK8UVzMjExMSij9bq7uzv6GqkNVJfqU9zSHNL6HovGk+IrxQG1Ia21qqqdnZ1B2a1bt2LdNEbUNupLKqc5oflOe8L09HSsm9Z8yu9VHDOpnMaIxj/lV4qjNKZ0XRrn1D7KG7RPpHJaE6nNFBuUW9M4U2yct845hOY1zcnKykqs28lTFIu0JlJ9ajNJsUTrJ8VuZz+vyrFE8Uzlad3TOKfxoLMCjX9C67UT57SuUnmnf1W5fdRmykmpvDNGFLfU787YddYmtSPFeTcW0+91xuhBofvXtBeks0NVnifac5eWlmJ5ijkaH5r/VJ/uzeganbyTchrlObpGii3aeyjfpj5SLI/97+8ljVH3Po7iI0lj17nXpd+ja9B4dOI81aV4prFL+0/n3oCu0Wnz9vZ2rEt5lZ4rPAxo/0prheYkrc3uvefCwsKgbGNjI9ZdXV2N5fSbCcV5ut/qPK+g69LYpX5TPNNc0W+OrUtnurN4xkLXSPFF+TmNHc0JxVeK0bW1tdY10m/SvkTlY69L5d25SmPauc+hupQvUz6/fPny6N97kGjsUt6Yn5+PdVN+6K7LtP/Tmqd2pOcH3X0wPQ+j502d++XOM8Du85gUd517FDrH0DXSOqZ+d/Y8GqP0e91nqun3qN+dva3zbINyaOeZKMUAreP0m9SONB5Ul2I0tblzBnk2/warJEmSJEmSJEmSJI3kC1ZJkiRJkiRJkiRJGskXrJIkSZIkSZIkSZI0ki9YJUmSJEmSJEmSJGkkX7BKkiRJkiRJkiRJ0khTYyvevn07lp+eno4qq6o6ODgYlC0tLcW6+/v7sTzVn5rK3Ui/V1U1OTk5KJuYmIh1Cf1mQuORpLZVVR0eHg7Kbt26FetSXy5evDgom56ejnVT/2ZmZmLd69evx/K5ublYnszPz8fyFHfHx8exbmcO01hU5fE/OjoafV1Cc0Xjn9D4d8b55OQkls/Ozg7KqG2d9dPpN9U9b7S209h18sDu7m4spzVP+et+UZupHVSepPVK+S/ltKoc59TmjY2NWN5pc4rdTs4mdI201qpymynXpbVCa5DWfCrvtK0q95HqdvLzhQv5z35ReULjn2KUzjedNnf6Tb933mhdpbjrjFH3PJXimX6PYiDFLsV+x1nEIkk5kK5L8ZXOMrSXpjVBa57O4KkdnTjqSuNBZ5POmbhz9upKv0fzSnHeOVuQdL9E55DUDhojipl0ZjmL8/P9orNzuu9YW1uLdVM/VlZWYl3Kf2ntnMW5l85Snfmj/LK+vj4oo3sOivEUF1SX2pzKaZxTOcUA7RHpGjRGdP+arkHrOuVmugfojN1ZrD9qc2cPpDhP1+jsdaRTt/ss5WF2Fvf4KWYoBmj/2t7eHpTRvFIcpbxGuYf2pHQNypepfRRHtDY7z0Rp/NMcdvJz9x4s/R6tCYqDNC80r5177s7zg2vXrsW6nRzfiY2dnZ1Yl2Im9YXq0jktzUsnD9N+0Dlv0hnpvNEaTH2he5HUFzrXdc8QCa351L69vb1Yl3JdyrmdezNaa9TvznmWxii1g67ReW5C6zhdo3ueTWjsOmdAys/p2p13clV5TCkXpH53zq1VvXsMio3UR2pz57kESbn4fs6A/g1WSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRpJF+wSpIkSZIkSZIkSdJIo78Au7i4GMvTB27pQ7ap7pUrV2Ld973vfbE8fQyXPhpNbU4fD6cPitO100eA5+fnY930EWeqS2O3tbU1KKMPXZM0HvQB3/QhYfpIOH0QPH04mj5KTh9sTr9JY5Q+UEzXpbFL16CPOJPOB6kTirnOuiL0MekU/zRGqX3UNipP8U9r8LzRh7HT2NFH0FO/ux+sT7Gf4rOL4oX60vnId7r2zMxMrEsflk9rhcZoe3s7lndyY+dD9pS/Ehq3zvqmup19l8Yixfn+/n6sS+24devWoIxyXWofjT3lqRRL9HudOO/UpXntxBHN1XmjeO7E4uHh4aAsnR+qeF5THFF+oDana1Mup/lOc0vz3T0XJGm90XWpLyn+05xU5b7QvNJ5L80VzWtnjKhuikX6PYq7lAPPYg3SGHVyQRrPqjyvnetWVd28eXNQRueQdLagNUjjn9YmjdF5orWTxqKzP9N9XBr3qjzX3fu4hMaY9sZUTmOUymmtUmzdb9uoHbR2OuNMv5fWGv1euj+n36QzfOdcQu1I56Oz2KfonJ3WxMLCQqxL/U6x271Hud91RWcKygVpnGn9nLfOGYukce7ulykX0PzRvp3OR5RbH3vssdHXprHonHtpTaR8QvsE7a8bGxuDMlo/aYzomVxn/dAapL0mtaNzf0frh34vnWVv3LgR69I4p2dOlMuvXbs2KNvZ2RndtqqqpaWlQRnFM+1L6WxP/UtordH4r66ujr72eaOclMaD+peei1PM0X1Vmiuav859NLWD8klag7QPpj2M2kblKZaoLp0L0hxSjKZrU+yvra3F8hQHtF479/6dutQ/kvIo7Qe0JlL76KyQxojWD/3eWTyrS/NNayLVXV5ejnXpGmk87uf87N9glSRJkiRJkiRJkqSRfMEqSZIkSZIkSZIkSSP5glWSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRpp4vT09PS5boQkSZIkSZIkSZIkPR/4N1glSZIkSZIkSZIkaSRfsEqSJEmSJEmSJEnSSL5glSRJkiRJkiRJkqSRfMEqSZIkSZIkSZIkSSP5glWSJEmSJEmSJEmSRvIFqyRJkiRJkiRJkiSN5AtWSZIkSZIkSZIkSRrJF6ySJEmSJEmSJEmSNJIvWCVJkiRJkiRJkiRppP8f4Qk0s1A/w1sAAAAASUVORK5CYII=",
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zVJfyDO0dqS61S2O0trZWzjE3NzcrVXTdqe009vPmajQazZTt7u7GupRPUl7rxDmNEe0TVL8jXSNdX7oW2n+ob2n8qY33Rme1FP+0flKMUgzQ/pPGn+KZytP40zpO65VQLKZ1PBwOy+cpaoP6THtsR7puin0qp3zSWRPpGun3Up/pPEUxmtqmcx2tzRS7nXVMuZziuRMDFDNpj6W1mcaos04+MoqXFMuUEzt7AY1bZ67pfJTmiea0c79F15LuA2g8z8/P3yzfpnMkjVHqB93PdO6Jurny27dv5fhKubJzziZHR0exnNq+uroqX1+KGeobxVdn76c4SjHTeXZDdakfKWYoFt8b7blp7DrXneJiXu5J52yKOdq3l3FOTnNF92DpuqkPdN2d8xGdCVKu6pxDCZ0T0tweHx+32kjj1HlWR3FLz0pTfXqGRHOScg/9Xtp/6NkGxUY6v9G8Uq5LbdPelsaD4oV+L8XoMu5FlqFzf9fZdzt7Ff0ezUmnDapLbac4pzNZulelHN/JMZ3nBLRPdM4Qy5irzlqjHNFZx3R+7uzHnXcY9AyC5jvFBv1eer8179yZ0HynMxWt4zQn9DyTrjvl88458r/7f+PuWZIkSZIkSZIkSZLegS9YJUmSJEmSJEmSJKnIF6ySJEmSJEmSJEmSVOQLVkmSJEmSJEmSJEkq8gWrJEmSJEmSJEmSJBVtVCvu7u7G8tFoNFN2e3tbbXZlb28vllMbz8/PM2UbG/kytra2Yvnq6upM2c3NTay7trZWboOkutQuXctwOJwpG4/Hreve2dmZKXt8fIx1B4PBTNnT01OsS210xi3N66u7u7vy2HU8PDzE8qurq1KMv9re3i5f48vLS7lv1C5J40FzReUXFxflfqT4ouu7v7+P5evr6+Xfe2+pb13pummMaE1sbm4unI/SOqb1Sm1Mp9PSuqR1nPLOvDWYYpHaoLyRYpRya+f60pyQzrzSnkf7YxqPyWQS61LMnJ+fL7QfUNvU51SXfo9iI+UvqtvZYzvxTGehFEfU56Ojo5WPnOvSddNaS/HcWSc0J9Q32lPSb9KeQrk4lVN8pRxDa76TA2nsOmuTYj/NIZ0XaYxSnqI+03ik3+zEIqEcn8opX6azNo0HjV1a8901kWKXxpPmO/0m3TekMaLxpHNk6sdHONcdHx/H8svLy/J5P61VykW0VlNs0TqjOU37TzdnpGuh30tjtL+/34qL6+vrcixTvk2xSHk15RI6w9DvpXmh8aQYT2esk5OTcj/o92i+UzmdbSjuUozSGKXc3Nl7qD6NJ803nb2qbdBeQO3SGfcjoD6n2KD1mtYm7c+d50Ldc0KKA/q9zpmOYjHFAT2LpLXZ2UepjTTWNP5pvf748SPWpetOex6tY3pWmq6RzkeUT6r7D113NzZSfNH5r7P/0xpMuYfGiK67s37SvkuxSHOS9o/O8++31D33VGOD9ky67rQf0B7RGec0f/POXym+aL7T2FHcUu5JbdMY0Zyk+O/s5zTOtDY7z9lobSad91CdvE/7EuW0w8PDcq6jNtI9Bu0HNM73oZzGs/NOh85qnedQtIel9bPI+wD/glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElSUf4qb3B6ehrLP3/+XP4obPqIM32Elj5ynD6gTB/IpfL0YV/6ODp9FD61TX1OH7WmD0FTP8bjcfmjyvTR4XTd9JFj+pBwQv3o1KW56oxdQtdHc5XGP33weZ4UM9SPNFcUA/Th9bTe6GPS1I9Un66789FuisXO+nlvnXjufGiccgnNd5pXamMZ0ge+KQ5ormi+E1rHg8Fgpuzg4GDhD57T9aU57Obn9NH06+vrWPf4+DiWX11dldd86jPtpRTP6RpT3M7LJ+k3b29vY90Uu5Q3aPzTddO8Up/THNI6Tra3t8t9I2+5jjtSzNG8Unylclony8i5y+gHxRfFY3UP65xNqD5dH52rh8NhqW9UTnUvLy9jeeofXTflwK9fv5bXa8rx9Hu0/6T9isaTpBxPuaBzn9Jpg1DdtK5oraV9nnIatZHyGu0H7yndP9H+SvOUxpj2HmpjGWfcNCd0TuicLSkO9/b2yuuM1vvFxUXpnDdv7FJ+SH3rrj8au1Sfxohi/Pe///1M2X/+53/GumlMj46Oyu3S+Ke8Na/tdM/d2UcpxumsntqgvLOMc1Pa46nPFF8pdlOM/xa+f/8eyylXVdHY097TiQ2Sxrn7fCTVpzNW516w88yK6tKYpjxzfn5ezhuUpyhvpz53c3z6zf39/fJcde7lab117lMpF6SxoHKKuU6c01mK+kz9q557aN+lsUvz2nk+/JYoF6T3EjQn6d0GPW+iuUpzQmNEuSCdydK9XffcQ7kg9bnzfJhyAe0znbij30vo9+hePo0zrTWaw9QGjV3qB80JlS96Tqa9hq475X5aPzSvm6Ht7hk8tUFj1Hmn0Fk/NEYV/gWrJEmSJEmSJEmSJBX5glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElS0Ua14tbWVix/fn6eKbu/v49119Zm3+dub2+vdOzs7MyUTafTlUVtbm6W+/zq6elppuzx8THWfXl5Kbeb6lL9NBav9vb2ynNI87qxsVHu89nZWTk2aIxubm5WqmiMHh4eZsomk0msOxgMYvnh4eFM2d3dXay7vr5e7t9wOIx1V1dXy7GYxpPq7+7uxro0hz9+/Jgpu76+XjiOaIxS/TR/vwXKX9X5o3Gm2KfyNHYUA9SPZDwex3Kaw06f03qj9UNxntYPxUYnX9Jek8Y55b9Xp6enC69jaiOhfqT9h8aI9okUS9QG5Y1UTms+jRHVTddHa5PaoHWcymmuEsqLNM5pjC4vL1c+gs51d9Yg5SkqT3FOOYZyXYoZyj0UX501kc4sNJ6ds2Fnz6S2Kdel/tH1dWKDzm+0BlN9WhNXV1fl66MxOjg4KO8dFKMJnS+p7Q46w3VcXFwstCYobju57vb2duW3towYT3PdiRVaD5SLOmfL7hinfEt559dffy39+3nrMt1XEbqfT2uK1nuaV8pFFANpnVCOojb+7d/+babsj3/8Y6x7fn4+U/b9+/dy3yjPUY6isUvxSLHRWWvUj9R2d646/Us5jfpG6/uXX36ZKRuNRisfwb/8y7+U55X27ZR7Omc32iPSXk6/R21QPzrno859Bz27oT0+xRLtl9SPNKa///3vY939/f3yPSbl1nRPQ3P1+fPncu5P+ai779Kekua1cy7pPudMbR8fHy8ci5TLKc7TeFDd9Cy483yYxohi46P485//XM7Pab/qnEFozdOZrPNsls6GNP6d+9fUPzrvU8yk8eieDVPup3WcYpRivzOH9EyH9qXOOk45nmIj5XKaQ1qv9Hy38w4p6d7rTMP40/qhuUp9pvyc+kfjTO9/UtuL5Dr/glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElSUf4acUAf8765uSl/GDh94JY+4kwf1E0foaXf66APMy9D+hhx5+P29AFl+jDw4eFhLB8Oh+UPbn/69Gmm7OjoKNb95ZdfYvnZ2dlM2fn5eTmOCM335uZmeSwo7tI408e5aQ5T7NLHnVN5uo55H8DufHw6fYyd4oDiK30Ym+KIpGuhj3O/N5rvpPPRbponiufOB91JavvLly+tNu7v78sfD0+xQR9jPzg4KI/pyclJ+ePvtO47uYDmhPpxenpaKpsXM52PtKc5oXGm30t76d7e3kpHmm+K0dSPx8fHWLdzLkh9mLenpD2W8lfqcxq3eeOfrpH6/N4ozmn8q/sg7Y00dmnPozxMayKNM80JSfmE2khzSH2mNXF1dVXOUxQzqZzOCp19/vLyshwbdK6jsUtxQHlqNBqV8xTlkxSPdBaifYnKq3GUcva88u5eXx3nThyl8/C8M2ry008/rfzWBoNB+To69xc0d5Q/UwxRzFKurK6ReWubfrN630j5ncY59YPikK47XSPlytQ/imVaZxcXF+UzHZ1D//Vf/7Xcj3R9NK/0POb6+rp0Lz9vDXeehXTuXynm0nhQDNBcpVii/STtgVSXzvvpWQjFxnv785//XF6bnbMN5RI6j6V57TzXo/qUWzv3VRSLaf1Qu7RPpNxDbdBa+fnnn8vjn85CdD6i3JNyHc0JPadJ40x9Tm107+PSGZfOdJTTUjmtiZTj6dxL/Uj7FZ0raU9JeaZzzqa6tI5TeecZ2VuidZXGdBnP+Cl/pf2gew+c2qb9n+YqoblKeZT6TPeTaUw7dWk/pvNN5/6Vcl3KPbR3U66jtbnoOysa/1Sf5rVz/0Jj13mmk55hdN8TbMO1pHLaD9L6oX2QxiiV0xhV+BeskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKvIFqyRJkiRJkiRJkiQV+YJVkiRJkiRJkiRJkop8wSpJkiRJkiRJkiRJRRvViuPxOJZvbW3NlG1ubsa6Ly8vM2XT6TTWfX5+LvdjbS2/J97Y2Ci3TX2+urqK5Ts7O+V+pN9LY/Hq/v4+lg+Hw3Ibu7u7sfzw8HCmbHt7O9ZN5TRGe3t7sfzx8XGm7OHhoVz31e3tbans1dPTU6ls3nWvr6+X26AYTW1Tnzsxt7q6Wo5zGs+bm5tY/vnz59JYvJpMJqUy6lt3Hb83GufUP1qvqS6tH1oTKWZobVOfl5FzU33KPYPBoHx9FDMHBwfluicnJ7F8NBrNlB0fH5fXK8UtrZ/9/f3yfJ+fn8fyFEs0zmm+aV4pZlKM3t3dxbrd8aieFQhdd+pHN/ekftB1pL2N1tr19XW5Hx8l11E/UnmnLqEck8opt9K6Sm1Q7qH4SqiNtFborNDZU0g6c7768uVLaT+nMaJ1SWvi7OysfFbonENo7NJ8UxzRmq/uM/NiI+XXzr0HjRH1mWKmg2ImSWNKc0Lzmq6ls0e8FRrjlLNpTlMeoDklaa+ifEZ7cZon6nM6l9A9Bs11yg8UVxSz6TyWyugMSec3Gv/UNo3z6elpee+nOPrx40csT2NK57Q0J3SfSmeNNP40r93YXfTMSvt56geNM41d55475S6KW+pzGlOK2/f26dOnWJ7GlMYz5WyKRbq/SPmS8gbt5ykHUhud+KJrSX2m+ws6N6VndalsXnka069fv5bboDVIe3HKl7QmKJ90nr+lZ5Gkcw9MOZ5yXcoRFF+pDTpnX15exvKUI7r7fzq3dp5FpvP7vFhMcU5r/qPoPHNPZyda2zQnnT2F5jutFcppnftXWoPpDEH7LvUjxReNHZ1FUxt0Nkxrk54B0pks/V7nPon2CcqtKTZovdKzhhSj9Hs0/qkNendDe15Cc7URYonWBJ3VUjmtn1RO65WeBf/6668L7VX/3cd4yidJkiRJkiRJkiRJfwd8wSpJkiRJkiRJkiRJRb5glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpaKNacXV1tVz+8vIS6z49PZXrdjw8PJR/j+o/Pz/Hujs7O7F8bW323fT19XWsu7GxUe4bjfP29na5Lo3p4+PjTNnx8XGs++XLl5myg4ODWHc0GsXy09PTUh9e3dzclK87jf2r8/Pz8ljQfKf6k8kk1j05OYnlW1tbM2XT6XSlan19faUjxcH9/X2su7e3F8tvb2/LY5f6l2J8XhtprVAb7436keKuk+vI5ubmwrmO+kxx3sl1nTWRxojWK5WnPlPcUp9TjFIbh4eH5bopx9B6+/TpU6xL+0TqM8VRGv/hcNjKrem6KT937O7ulmM35Z15OTDFBtWl8s6ZpRO3dN2pH5394C118gON0d3dXflsQrkujWmnLsUXrWPKo+laSLrG7t6d8hedp+ha0m+mcxO1PRgMYt3xeFyOc9p/KPekMxLl1pQjUu6aF3dpXjtxRLmY1k9qg9YPldMcdqS9Jo199/6MxjntH5019VboPJzQekg5m+a/c6ajdU1nrNQPOgfR+SGtS1rDKQ4pLmhfS/FCY0d9TnP4888/x7opP9B4/vM//3Ms/8tf/jJTdnZ2Fut+/vw5lqfYp36kmKEzHa3hNKZ0xqI4T+NPazjNN8UR5YxUn3IzXXca004sEtoL0lx12n1LNEbpWmic0/V1ztMUi/R7nftlukeh606xe3FxUc4xFM+Ut1NupFzXeW5CueAf/uEfymue2kjlnTl59euvvy50P9l9Bru/v18+s1Lc0TmyGhu0z1OfUxvLuFeiuUpndZoTGv+0fpbxnGAZqM/d+7BFpfVK+ahzduo+E01x0Nl3KeZoHzw6Olqob3RP+tNPP8W6aUzpHEOxkfI27Qf0rC6dNzprgup2npXSnFDuofLqGFGfO9eyBtdHe2kn5ya0BmleUz9onCv8C1ZJkiRJkiRJkiRJKvIFqyRJkiRJkiRJkiQV+YJVkiRJkiRJkiRJkop8wSpJkiRJkiRJkiRJReUvKNMHgzsfsk8fnqaPUdPvJfR79DHp9NFn+th55+P029vb5X50P86dPiScPg5NHzantqnPqZw+ZkwfEk4fwKaPSd/e3sbym5ublap03dRu52PSw+Ew1qWPH6f4oo+Vp9igj5JTPKd5/fTpU+tD4+lD9p01T+3Sh7XTh8mpjfdG85rGOX2Eu/uBb/pod4oDaoNiJpXTOE+n0/J1HxwclD/+TrFP153inNYg5boUdxSL6fponGldddoYj8ex/Nu3b+V5PT4+LrdL85rmisaIriWhnJv2Cfq4Pa3BVE59pvy1aM6l9UNtJNfX1ysfwf7+fiynvb46r7RXdc51VJdiMZ1ZuntKiiW6lhSLnXVC/aPzVOfMQrk1ldP6obFLsUHnVsrbqQ3K5Z2zKEl5prsvde5f0tjReNLvLeM8lK6R4quzBjtnhe6aeAsUL+n81jmrd+89O/c4nfvX09PTVmylvZ/uBVOe66yReeUdKZfQ+aFT9/LyMpanvPjTTz/Fuv/1X/9Vji9a1ymWKDbS/NFcffnypVyXrrtzPqK1lu4xKcd0cyLNbUL7TELXkvpB4/neKGenc3nnvrEr7RHd+9d0LXSfQ/ekKa/Rukp5ivYDiudUv3N2o3N55/kirYfO80y6blqDqc/URooNGk+SckRnjCjXdfYqitvOPQqdpTrP+0hqg/49nQvTWumcbz66ZeS61AY9G6Q1kcppH6S9pjPfKfYpBuiZTjqHUJ/pWUN6j0HvNlL/6Pro3JOevdCeQv1Iv0nrOJ0hKIfSuuo8E6Xcn/pHfU5t01mI2ngK19h91pDyaCf/0X5A90ufP38u3x9U/PZ3vpIkSZIkSZIkSZL0d8IXrJIkSZIkSZIkSZJU5AtWSZIkSZIkSZIkSSryBaskSZIkSZIkSZIkFfmCVZIkSZIkSZIkSZKKNqoV9/b2YvnDw8NM2cvLS6y7tbVVrvv09FQu393dLfft1ebm5kzZL7/8EuseHx/H8tTv7e3tWPfy8rJ8fZPJJJY/Pz+X20jXR+WpbzTfg8Gg3DcqpzHqzPfj42Osm8o3NnKIU9zd39+X6+7v75fnkK47lY/H41j37u4uln/9+rXcBplOp+V5TeuN1iD1Oc0LzdV7o7yxtjb7/1F2dnbKsZj+/bxx7qB+pFhcX1+PdWkOf/3115my6+vrWDddI7VL153yDM1J6turP/zhD+U+D4fDcixSG6l/lKcoj6acS3nx6upqperg4KC8H9A4p/xA45TGk/IojVEn91CfqY3O2KX+0fqhNZium/aO99aJ507eoD2TytM4r66uts5IKe5ub29jXVpXKWYoRlPb3TNZOhPTmYz68enTp1LfXo1Go3LfaL6pfNE1Qev44uJiofGksaNY7JxnqY3OGNF8d84bNB4pHin/pTZordFZJo0z9fkj5Ll0zbSG0zV371/TeZhihc4g6ZxA/aC4SM7OzsprqnuWTeNBsUV9Tvkh3a/RONOc0Pk0tU2xTHkntU1nqdQ2xS3FBj2vSJZxP9I5j9E9cDoP07zSWkk5lM7ZKTbomikWO/vJe+vMH81Juhaak84eSH2js00af4p96l/neWY6a3TzRlpXdH10Lens29lT0jmP+kbo/N0503XOCVS3swZpTijnpvmm81F6pkDP2TrjTHVpvtM40/5zc3NTHgsaZ8qjH1mKUbruNEa0Xjt5g+pS2ykOKKfR/V36ze/fv5fzcxoLqku5h5430X1OijuK59/97nflNU+/l8auu3en66b1k9pO8TJvzafnRfRsnfJ22utpnFMOpBigGN0IexvVpbWSxo7uUzr3Vp2zIfWtwr9glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKtqoVry4uIjlDw8PM2Vra/m9bSrf3NyMdR8fH6tdW7m9vY3lq6ursfzp6WmmbGdnp9WPm5ubmbLJZFIeo729vViXxiNd48vLS6y7vr4eyweDQWksaL4vLy9j3Y2NHEbj8Xim7O7uLtalmEnjP51OY900/tQu9fn5+bk8JzR2aV6obro+ilvq8/n5+cLxnOpT3RTP9/f3sS7N1fb2dmnsfwsUMyn+d3d3Y92tra3yvHZQGzR26Voob1CMpt+k/JV+j+KWxvnq6mqliuI85ctOu5RD6fdS7qHY76wVmqu0NmkfPDg4iOUpdlPc0n5H40HznfIG7QepLvWZ4ojimepXddfxMtb9W6H4SuV0HSmeaf3QXpriqBNztH6Gw2GsS3tbipnOWZTGiGKOxqkzV2mc0v5KZ7Kzs7NYl/a2lOu6MZ6um/qc9pruOKf9sZsHUhuUL9P1Ud6n+Ep5lOpSeWfs0rVQfqbrTr9H++B7olhOY0z7V4pPOlPQ/pX2Yvo9ipeUozpxSL85Go1i3RQv9HudXEnrr3PGpXMvjV2nbppD+r2jo6PyeNCzlE6fO/sG5dWOzhmrk4MpP9D6obbTNXaum+KW+pzyHN0TvTfK2al/VDddd+f+kFAbnftXyrnURoolWj+pDapLMZPOaTTOlAvSb9L5L+UNuhekdZX6R3U7Z2dqI41z5/5i3jV2pHsJ2gfT79G8Ut9or09oPNL4U5/T+qF2O7FB1/3e6F4w5Qi69/zy5Uvp38/bU9I9EeUjWscJ9bnzTI1iI/VjGc9g6b6dzoxpfVOOSc9gv3//3tpr0th1n6t2noGncpoTKk/jQbHYeZdC0vVRLNLvHYR7nc49DcXo4eFhrJtyEuVhuh9M17LI80L/glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElSUfmL2/Sh1/RxYPpgMJUn9AHfhD6cOxwOyx/w7XxQnD7Kmz5MT23TB587H46eTqex7sXFRfla6IPBJycn5Y8c0weKU//o4+jp49V03fQR7TSv9BH0zoeL6bopNtJ8n56exrqpf/QBZvoAdop/iudOjNJ1p3GmWOx8jL2TH95SZ21SnkpjtAyU0zr9o/XT+dA4jVFa37TWaIxS/1If5sVzWm+Ue87Pz8t93t/fL1/LeDwu16VrpDWR1hXlDVrHqZxig8b5+fl5pmwymcS66VpoPGn8U86lPJz6RrFL8ZXKKafRmvjIuY6k/tEYpTiiOaGzWqrfPSOlGKVYJClmKC+m36McQ2t+b29vob7RvNA4p326k0PpGun3rq6uym3QmkjxRWNBOue9zv0LrYnO/QGdUVOeodxDMZrGqTMW1C7FeWqb2nhPdM1p/ii2rq+vy+uX5inlgdTuvDYGg0H5/qkz9nSWTWNEcd/Zi2mc6byS8hFdX7oW6huty5QraT/59u1bLE/1ab2nPqezafdenHIwtZH2XepzJ39SzKR4pvxCOmfnFAedsw3td7SO3xvdi6d5pXhO49G5B+j2rXPG6jzDoP7R76V7NsqLlE/SWrm9vY11afxT/FMbKUZpX6I20nzTnkJnvVROv5fmhM77tDbT/kh9Iylm6KxwdnZWfiZHeSPl4s59I8VdZ5+ne5FOPHf2g7dEuSflCBrPFKO0/9A4pzYODg5a8Zz6R89j0p45b69f9Lkx9TnVp7xBz6dSLHX2MJrXzjsrin3KXyk+KGbSOH/69CnWpb2t8yyE5jDFLs1r576Rct047KUUt52c29nnO/d9VN591vB//P7/+F9KkiRJkiRJkiRJ0v8yvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElSkS9YJUmSJEmSJEmSJKnIF6ySJEmSJEmSJEmSVLRRrfj09BTLHx8fZxvdyM1Op9NyXSpP1tfXW+Wrq6vl66M2dnd3Z8qen5/L103tPjw8lMeDfo/c39/PlF1eXsa6Nzc3M2Vra/l9/MHBQSzf3t6eKbu7u4t16VpSG8fHx+Wxo3klW1tb5bl6eXkpx9fPP/8c625ubpZjgK5lNBrNlN3e3rbW1WQymSnb29srjxGNRapL5d25eisp9mns0pqi8UhxMW9dpfppnuatn06uozZS/FMc7ezslP79vJhJOYL6TP1I89LJ5dTujx8/YnlaszRXac+kNZv2DhojWq8Ud6kfKd/SGFHs0nWn8af9gMYo5cvO2YTa6KxNWieUc1PbFPvvja47lVPddN1Ul9ZVil0aT5rv1EZ3T0n1KW8kg8Gg9XtprdD+07kWGruUvzp7NPWD4pmuJeU1aiOtY4ovyl9pX+rGRsoFtP+nftB40ppIv0exSNfSOcenNmic03jSHHbXxFugvaCTm9M80f0TtZHuXWj+aZ+5uLgo3zPQekioH7SGEzqvpGuhvb+TS8bj8cL3F8PhMJan+jTOlAfSeFAsJt3cnMaO5iSdg+aVV1Hc0rymvYrGmfJf+k36vTSvnfs4Gv90H/5bODo6iuUp7vb392PdtEfQ+qHyFEedPb67jmlfS7FEv5fGg9ql/JXKO2fIefdQVRSLdC1prmiMaK3Qml30mSidH1JsUF7s5Fz6vbT/dJ6n0bzQnFDbaU+n+/POM1E606Xc2pnrt0TXksaI+pzWK52baG9MY0e/R2fqpPs8Jq3NzjuW7lk0rQnKizR26Qx3fn5eHrsvX77EurTXXF1dLbyOU9x1nlHSWNBZO9030Jx0zl+UFzv3nnQt66E+jVGak1efPn0qx1f6PcppdN2d944V/gWrJEmSJEmSJEmSJBX5glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpKLyF10PDg7KH1Wmjzinj+9SXfpAcUIfCac20oejLy4uYl36sG9q4/r6ulyXPl7d+eA51aUPCaePbnc+6kt1z87OYnmaW+rz7e1t+TdpThL66D3pzBWNx3Q6Lfc5zRV9gJnKOx82p34MBoPyXKXro3VMbXQ+zv1RpHGmD3yna+l8BJ1it5MfqD59SD3FwKvd3d1yGyk2uk5OTsq/Nx6Py/vV5eVlrJvmkNba/v5+OTZovinO03x3ch39Hl1L6kea63l7W+ozfYQ+1aW4pXySrpH2+c4ZotNG9/fSHHby4luiWEwx0xlPijma11SfYp/29JR7KB9R3HVyQToX0HhSP1I8U11qO+VGGuc0dnt7ewvPIcUGXUuqTzk+jRHdj9B+nGKJxrOzT6czNeVAyosk9Zmuj8a/c8+V5rt7f5biaxlngkVRjKe+dfIL5Sgan7SP7uzsxLp037Ho/cWr0Wg0U/bLL7/EuqntzlmR4pZime4nr66uFrpnoPGkPJfmkH6PriXt83Sv25lX6keqn87TXel82z0TkJQXaa5I5z465TQ6D9A4pz7TvL43isW0v9L1pZxEuYRiIO2NFM80/imf/OUvfynnNFqDnX5076tSfdpTzs/PV6ro/JDaoD3l+Pi4fN3fv3+PdWk/Hw6H5X6kmOmcSwi10UH3uqltyovUj5QjaM9M+x3FM/1einOKRVoTKZ98lPvXzlqhcV7GWSGNP+VWajvVpz2l8xyX8lcao87zTCrvPvdK5z26vjSHv/7668LPkKgu5bo0Tp012H22kdqm3No5E3feE3TPvi+NsyGtzRSjy3gmSmsw3Scucq772FlSkiRJkiRJkiRJkj4QX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKtpYWdDq6upM2fb2dqz7+PhYbvfp6alc9/n5OZbv7e3F8rW12ffKOzs7se7Dw0Ms39iYHbrNzc1yGzRG9HuHh4flujTO19fXM2XT6bQ8puPxuDyeFBvr6+utNl5eXkp9o5ih3yPp97rjnMrv7u5i3dS/4XAY61L5+fn5TNnW1lb5+ih2aZw7c9JBfXtvu7u7sTzFAY1zmu9uLKb1Qzkm1aV1RX2mnJvmlvIljV3HxcVFuc8pD1OuozV4fHxcHs/ULo0d9bkz/jTfX79+LY8F7YM3NzflPEx9TrGxv79frks5lMafrjGhsaM9r4rGiH4v5TXa/9/b/f19uc903Wk8ac+kNZjySacuoT7f3t6Wc8HZ2Vl5vdJ1d/IG7YNXV1flnEttpDVPY9FZa7Re09mE9sLOGYLGmfrRya2Uk1IsUd1lnGXS2qQ8TP3o5Nx0fd3zBpX/1ujs1YnDVJf2Vvq9NKeUg2meUixTrjw4OCjngS9fvsS6KT90z7KXl5cLxSztM+k6qI3JZBLrUj/SWus8l6A2KN+mtuksResyldN5h/J7yl0Uoyn+KUdRP9L40/XRfHfO39V/P2/9JB/lTEfxlVB8pTboLEVjl/bo7nOCFKMnJyetvSf1g9Z8ivPOsymKc6pLz9RSnzvnXqpL6yfFbvc5QdqDOmcNer71lvFV7RuNR+dZJMUX5RjKl2nvpf0/9ZnyFMXoMsb0rXSec9J4prlKz6C6Y0dx1DEajcq/R/FFZ7V0LbTvdvYUOhN3zl8Uz3/605/K9+d03WlPob2D8mVqu/N73XdkKc5pPDvnus59HK2fznOaLVivdD+f9kc6s6T11tmrqI3OOXKmvf/xv5QkSZIkSZIkSZKk/2V8wSpJkiRJkiRJkiRJRb5glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpaKNa8enpKZY/Pj7OlL28vMS66+vrsx3YyF1YW6u/+726uorl5+fnsfzo6GimbHt7O9adTqflfmxubpavha57Z2enfI2rq6utfuzu7pbm79VkMpkp29rainWfn59XFo0jaiNdI7XRGU/6vTQvKW6pLsX/8fFxOb4o5m5ubmJ56h9dN7V9d3dXapeum2KRyhet+5Yof3WkNU/tUq5L65jmj9pI5Xt7e7FuZ13RXHXyJUlrhfIUXXeKXcrxKa+Nx+NyDqX+0Xzf39+X1xWNZ5qrwWDQ2h8TyvG0p6S8QW2kup296tX19XU5Big/d+I8od+jPSXNIcXie6Mcn66F8kYa526uo5hJKM5TLNGeORqNyvFFsZjGiK6D5ju1QXFEOSn9JuXL1Dbl8s65jtA5JJXTel30rE1xTrHf2Y+XMUYktU3XTf14eHhY6ExMcURxntY9/d57+v79+8J5Lo09rUmaD2p70X2G4uLi4iKWp/op91EM0VpNezzFEeWd29vbN+kH1aWxS79H49l5XkF7wXA4LPVhWfdVnXtEqpvOsunZwbx8m/pHsUhnt9QP+r2Uo+icQPG86P71liie0xjRWuvkccp1nbN65wxPc9I5c9KZLsVud17T+qG8T2OXyun6Up9pzdO5N90jdu49qX+U6zrrh9ZxmsNOjlnG859O3n91cHBQHk8aj3T/Q2s+5bXLy8tYl2I0jSmdC98bXUs6n9JaS/nk559/jnV//PgRyw8PD8u5laQYpVik8U8xQ3k75Wc6b3TmO71fmTceqR90f/GXv/ylNPbzfi+NaTfHp/VGuSetbxpnKk+xS7mH5ju1Tc8iO+i6H0PM0L5LOfDLly+ldmmMaCzo91IuWCTX+ReskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKvIFqyRJkiRJkiRJkiQV+YJVkiRJkiRJkiRJkorKX/alD+qmD27Th3PTh2XpI7RnZ2exfDgcltug8vThb/qYNH1sOX0wmD72S+WdcU4fVaaPktOHktMHfPf392Pd9NHn8Xi80tGZ74uLi1j+u9/9rhxf9AHlZHt7uzxG9EHkznxTG50YSLFPH/P+9u1buW/0gegUczSHNJ503Wm90Ufo3xvFUYqN6XQa66axow+pn56eLhxHNHYpf62ursa6NN+pbfq9zgfkKc5TfiaUtzt5Mc33aDSKdemD52mcaYw6H6enuqltGucOur7Oh94pl6f+UZ+vr69j+WQyKe/RnRilvTStFYqj1Dea1854fhTU5xSjNEadcpoT6kc6F1BsUBspB1KfUxzReqXy1Gfao9NZu3vOSuuN9gM6Z6VrobVGe2maF5or6t9b6Zz5qW803x0pRmlOSDqX0RmC4rxzfWnsOnv0W6Gzc1oPlBvSWa8zZrRH0Nk5neu795OdvbF7D5x07gNoTii20v0nxXLaO+j6OvfLtCdRvk3jTPPXOR/R76VroTGiOE/nt8710V7Q2Ue7OT/tjZ28043FlIfpXvC90Tl0UfRMLq0TmhOKfcobndig+OrcF6W10t1z03XTGuyc02g/+Pr1a3lOLi8vV6pormg/6Ixz5yxF+STFOZ036dlGGica59S/7rONFAc0V5RP0m/SvKa69Hu0Bjtx+94ODw9jeVqzFBvHx8flXEKxn55Z0f0a7btpvdHz+aurq/J807OUzn0j7Y9pTdDzO5qr1A9a86l/NK8Uz+kcSeuYxj9dN5030rxSPurETOddUfeZYarbfS9xH9Yg5Z7OcxMa585Zm9ZgaoPitsK/YJUkSZIkSZIkSZKkIl+wSpIkSZIkSZIkSVKRL1glSZIkSZIkSZIkqcgXrJIkSZIkSZIkSZJU5AtWSZIkSZIkSZIkSSraqFa8uLiI5Ts7OzNla2v5ve39/f1M2d3dXaz78PAQy6+vr1cWtbm5OVO2uroa606n01j++Pg4U/b09BTrvry8zJStr6/HujQeaZypLo1Rmpfn5+dyPzp1X21vb5fjiKSY2draKv97mhOa742NjXIsUttpnGiMqI2EYiYZjUax/OrqKpYPBoPyOk7XcnNz0+pH+j2Kr/eW1jbFDMVRKk95gMaC6tOc7O3tleMrral5bVfb7Y5R5/f29/djOa2rzu+l3EprfjKZlH8vtdvVGSOKW5LiK+W/t+wzrQm6ljSmlDeojRRLnb2NYj/td6QTR2+JrrsTu2mcOzFAexutQconyTLimcbo9va2PG40Hin+Kb7oLJraprNCyv20TnZ3d2N5apvGiK4lneFoXlPb3fjqnJNpHXdilPJaQtfdOe+RThtpTGn9ULtpvtM6eW8U4+k6KLY6cU/zn9qmNdLpM6E2UjldS+oz5bnOXNMeSHku5Qwai3SPT2s11aVrpPsnuu50tqc1lfJA5x6Txq7bRppviufO/kpz1Xk+0sn7FF8pDmiM6L4q7Y2dnP+W6LoPDw/LdTtnCtovU+xTPqL7uE7OHQ6H5fmmvT/9Hl0fPYdK10j5ksb/27dv5Tx1cnJSfs5GZ7p0jZ1nU93ncmkO6d93npV2+kDrexlnS5LyM8Vz5wxPZ8g0r7QPUpynHN957vLRpfGgXE7PM9P6Pj8/b51v0jifnZ21ct2vv/5ayvv0zLZ7nk31qS7FTMpJ1I/OM+LOvWfn/pzWW+e+gdY2XV/nndXl5WV5fdO+lMaO4paeJ2+Fcabc0zmb07x29ivaB9OYdt9Z/f/5F6ySJEmSJEmSJEmSVOQLVkmSJEmSJEmSJEkq8gWrJEmSJEmSJEmSJBX5glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFG9WKg8Eglm9ubs6UPT8/x7qrq6szZdfX17HucDisdg1/7/b2Npbf3d2Vr29rayuW7+7ulvuX+pHGjcbo1XQ6LfeNyu/v70t9o/7t7e3Fuo+Pj7F8fX19puzo6CjWfXl5KZfT9V1cXMyUPT09xbo0/qk+XR9JbWxslJca6vQ5zfW8fqS52tnZiXXTeNA4Uz86fXtvnfmmOVlbWyu3S7nu6uqqPEaUA9O8bm9vt66lg+Kgs+ZTPx4eHlr9SG3Q76U+03Xs7++X8zPNN+WvNFepjCxj/iiOOlLs07XQnNDYpX2XxpP6kcopT6X+0ZzQ79HZ4iOgPT3FQWc86RxDY5fmkOaE2k65keKL+pGum34vrTdqt3MOoX2X1nfKPbSOU+6n9dM5k3XHOf0m9TnFAe1hHQcHB6366b6BrptipmMZ56HO/tHJ/Z39mPLGe6K1k+KQ6qZrTmtvWfNB45bigtZDd3+t1qV2j4+Py7FFfaD8l9YUzVVqm/YTys1prj5//lzODa8ODw9L7VI/KI9Qzu60QfGVxv/s7Kz8e3R91I9O3qGcmNoejUYL5y46H6WxS/drv4XOeZPyxjLmpPOMjMYuxRL1rXO/Rc+hUj6nddJ5Vndzc9Oaqz/96U8zZZPJJNZNeY3Gk/Jz6jPNX+csS3mq8wyJxj+1TfF8eXlZ7gfFRuoHxSJdS/q97vOYzrOG1Hanb3SNaV/7LXTvMxc9m9B8p9ig53qdZ3Xd+KLzSTU2KBZpz0yxSDmNriXFOb2X6DxP7vxeN8en+nRuXcYztdQG5Qc693Sec3bOSLT/34UzMa1LGrvUP7r36PS5c++xyHPV3/7OV5IkSZIkSZIkSZL+TviCVZIkSZIkSZIkSZKKfMEqSZIkSZIkSZIkSUW+YJUkSZIkSZIkSZKkovx12oA+LJs+vE4fzk0fw6UP5FIbqZw+kEsfKE4fAaYPyNPHcFPb9DHcNHb0EXr6yDR9cL7TRhqn9CFiaiN90HreR5zTddOc7O3tlT8mTbGR6lJ80bVsbW2V26APcaf69BHt9HuExi59+LvzcW6Kc1oT6SPm19fXsS6tifQBeJrX99bJSfTR7tQGrTWakzR2lIcpn6Q2Dg8PY93xeFyeb4qvlDe6sdj5GDvlns6H5dPH0Tt7GOVWuj7SqZ/6QePc0fnYPOnkZ6pL+ZnWW2fPTGuFxi7lZ1qDl5eXsfyj5LXOeKb109nD0pqaNxZpTGnvoH6kfZDiiOI8XTf1OeXFTnxS/+i6qe00/rR3n5yclMeTzjdpjGj90Pin+KBza9qvaE4o7tJ8U9+oH8fHx+V9N+31lDcoFtP401xRbKTyzj0N9blzfu7ug2+Bzl6dPTONBY07xWca+875j/pB80Hz1zkzpf5R3c5eR32j6+60kc5H1C7FRmr76Ogo1j07O1t4b0yxQWeYRc+Kr25ubspzSDkxjVE3NtI+SjmK7pfTOkznARp/ysHURrp/pdj4KNL9HcXXos+3aOxordF8p1ja39+PdSkHpnM5zXeKjW4sdu4Fqc9p7CgW0/r+4x//GOvSeSXNN13f6elpeQ3S/pjGg/bizr5E597OWa/z7Jn6RnPVOW9QP/iwiqEAACOxSURBVFLe7jzX60rr/tu3bysfAeWetI4pf3XOLBRHnXYpNlLe6D73Svm8c96nswn9XnqXQmNE409npyTlJMoxnbMvtUHXkt5X0Dkr7Xnd54upf93nSp2zWudZHe3pg8a5jvJ2Z5w7z16WcQav+O3vfCVJkiRJkiRJkiTp74QvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKvIFqyRJkiRJkiRJkiQVbaws6Oeff54pu7q6inUfHx9nyra3t1u/l9q4vr6OdXd2dmL55eXlTNne3l6s+/T0FMu3trZmyjY28nDe39/PlA0Gg1j3+Pg4lqdrpL4tQxq71dXVWJeuJc1VGgv6vVdra2vl6079WF9fj3XpWtK8Ut2Xl5dYvrm5WYo5ijuKo/F4HMtTfWojzQmN3WQyWan6/Plzef4onqnPHwXNdzKdTstjT/krxXmKrXlxnlB+vru7i+XPz88Lxf5bjjNJ49EZI6pLfUs5gua7u+dV+5FirqvbRrrGh4eHcjzTeNLYpXGmPYX6cXBwsFKV1gS1Szqx8d5o7N7qbEFjd35+PlM2HA7L+YhyD+0p1EZnD+ugvXt3d3em7OLionw2oXim+Ut7Ou3zlAPTHNIYUZ/Tuk8xQGvw8PAw1qWzWhr/zvVR25QvU9zRGNG+m9runpHS+qY+p+uj+aPyzvW9JzqXpPGk+U85o5vHUxsUs525pjaWoZNXaT9J9WnsaJ2ksevc33XXe8rNP378iHVPTk7KbdP10TOIpHP+prmi+/bUdie+aO+hNZjmlfIL5a7O2uzcV1FspHuoj5Dn5l1LKu/c83VyPo0/xS2tzRS7dL9M153WMV3Lzc1N6d93n3t194m03vb392PdlE8oD9N1d842dC5P+YvO2altigGa19vb24XbSNdNayK1TbmVyil2O22k5wedsyXFBu0/qf5oNFr5CCifLOMZUtJ9FrxoG7SX0nyn+lQ39YOug9pIsdE9z6a1SXkj7ce0R3ff6SSU+zvnjZQ36Poof6Xy7pm/M9/p92jvoPEch3tues9Dc9U5x3d0xnmR5z/+BaskSZIkSZIkSZIkFfmCVZIkSZIkSZIkSZKKfMEqSZIkSZIkSZIkSUW+YJUkSZIkSZIkSZKkovzV4YA+qPvXv/61/DHj9DHc7kecU9vpo9/zytNvnp2dtfqRPtZLv5faoA8if/v2LZanjxHTnFB56jPVTf2jj6PTR+HT79FHjtNH77tjl8rp4/bURuoHxQB9qDrFF32IO6EPT1Of05h2P8x8dXVVvr4UB/SRaupz6t/+/v7KR0Dj3/mQfTIajWI5xcZwOCzN07w47+TcTv8ox1P5orq5LsUuxXNHJ9dR3WV8pL3TbiduO+NJ67izD1KeGgwGK1WUe2j8b25uyn3u7PM0RqmNRXPJslDe6Mxr2g+6+SHFbjcWd3d3y7m1sx93+kF1O/n5y5cv5bp0LWksqB80r7e3tytVtI6pz2lNHBwclPvciaNl9TmtWYrFTjxTLkg5sHvdnT0vjQe1S/1I1/JWZ4KOTlzQmKXroGujNlI5zX9njJdxtqF+pPVA+Wxra6t8X0V9pn7Q+lm0Lt2jpLP24eFhrEs5NJ016D4n7aN0HbR/pTVM9+00/p376LSuuufb1Gf6vY5OP+j3KBbTmbNzZn1LdO5N95Op7NVkMll5C3SmoHFO64rq0n6e1hCtqxQztLapH50c37mv6pypaSzoOVsaD+ozravURuc5VPeeKO1L3fN3Gn+K0TTOnXM97Y+duKVn1ScnJws/86VYTNe4jPz8/zoaZ8q5KWbobNJ5Hta97+jUTfmE9sF0FqL6neum/W4ZOuubzmSpz537A2qDcnlH516n+07h8+fP5T5347yqe2+V5ptyeYV/wSpJkiRJkiRJkiRJRb5glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklS0sbKgT58+zZTd3t7Guql8a2srd2wjd21tbfad8MPDQ6x7d3cXy/f29mbKdnd3Y93Hx8dYnn7z6ekp1k3XmPpA1/dqMpnMlG1ubsa66+vrK1Wrq6ux/Pn5uTzOX79+Lf8ezcn29na5f3TdqX87OzutfqTfo/GkuUpjR+NMcZ4cHR2Vf68TAzR2P/30U6x7fn5eXsc0Vy8vLzNlFxcXKx9Z6jNJ8UWxeHNzUx67NNfzYjH1mWJ/OByWcw/FbYojGjcqT9dN19ddm1XUN/q9lM+pLu0THSkOptPpwu1SHqa4o/LqdVMcUT4Zj8flvZTaTvFF+fn+/n6litbV9fX1TNnJycnKR0B7emdeUxspZ8ybkzSH3VyXfpPiiNZKioNO3qa+0XxfXl7OlJ2ensa6+/v75VxF8ZzOs52zEF0j1R0MBrE8zS3l3NQGncsp7lIbdN10Zkm5keKZ2k4of3XaoLFL40xjl+awmx/SeqPYeE90T5r6RjkjjRuNA41xqk977lueHzrtpnJaI9RGukaqSzk0rQca59QGrdWDg4NYnq6R8kva42m+6fpSG6PRaOFx7pyl6Lo7z0EoNui609qk3Ed7cdobaY9Pv0c5ispTGzRG761zPjo8PIx107UsI+/QGYbyaFqzFLcUM528neKL8jDdG3TORyStIbq+tPfTOHfyFD0P+P79e7kflHs65wSaq3Smo2cpdC0pR1COSf2jNUG5Jz1n7jxXovMi5dwUMzRGFDOpzx/9Wd1HQDFA55BUv5s3Uix14qvzHJHWFcXR3/72t3I8d57dLOP+idCennIP3WOknEs5hsY/lXee0ZDOOwzKG519abP5zorGadE1SHk79YPO/BX+BaskSZIkSZIkSZIkFfmCVZIkSZIkSZIkSZKKfMEqSZIkSZIkSZIkSUW+YJUkSZIkSZIkSZKkIl+wSpIkSZIkSZIkSVLRRrXi8/NzLL+8vJwpW19fj3UfHh5mylZXV2PdtbX87ncymSxU99XLy8tM2cXFRay7ublZLk/X9+ru7q5U1h076tvT09PKora3t8vt3t/fx/J0jWns57XRGefHx8dynyk29vb2Su1S32gOt7a2Yt3pdFpeazs7O7E8XSONEa2VdC3X19exbroWmj+K59RnqvveOjmJ5qoznoeHh+XYoPmj8U/rjdYE9S+1Tde9sbFRHs9OPqHrTr9H/aPck1Cfac2nHEF5g9pO67szdp3ro7avrq5iXRr/1Aat4zQetA929iXqW3f8k3QtFLcUG8nNzc3KR0BjkdYVXXcqp3XZiQ1Ce3dqu9Mu6eR4ks7JNP7U7u3tbbkNknIErZ/Ofkx9ppy06D7RPeOmOKAYpT6n8ae66VponCkHpvo0RhSjnTWR2uicF2kPS+eY90bn7zT2FBdp3Lrn7FRO64zyXIpD6jPdM6Q2OmNE6LpPT09nynZ3d1ttpLEeDAblurTnUj/SWaiT8+l+ks5YKZdQDNAYpbY7Z2SKA4oBiq/OPUrKadRnWm/j8bi8rtIZsnseS+O/jOcuy9A5D9O5JI0/jT1Ja6X7nCDFP9Xt3P+keKH1SvsX/V4af9pzqe3OmS759u3bwvs25QfKl1S/WpeeP5CUp6gP9Hw3rVlaP2m+aZ5SjqH+LeO+vXNv0HlWRHv3aDRa+Qho/NM6putLea2b69L6oTVPbS+65uk3O/mS9l2Kr3QtVJekNmjs0rqieKY1mHTfx9BvVmORfo/OIZ1cR9edxrlzZqG6FDN74bq7unvCIrmcxnSR9xL+BaskSZIkSZIkSZIkFfmCVZIkSZIkSZIkSZKKfMEqSZIkSZIkSZIkSUW+YJUkSZIkSZIkSZKkovx12oA+XEwfTa/693//91j+T//0T+UPbh8eHrZ+M33slz4w3SmnuulDu/SRYypPH+UdDoex7nQ6Lc8VfQQ4fbi4+7Hf9GHmNH/zpLlN7dJ108eo6UPj6aPK9MHt/f39ctv0QerOB+7pWtJ40IeuqY0Ud90PRHfyQ4qlRXPJslxcXJT7nD5u3/3QO33YnMa/80Hx1I/OnFA/KAZSOeVFaiOtt27uofWWpP5R3+iD7h0UG6nPNHbpg/OUp+ha0rxSzNH4p1ii/SeVU5+XMc40duk3qW4HjdEy9tK3kuKI9hSKo3Qt3ZyW9lIaI8q5nXntzDdd9zLa6Oyl741yaJqX7vkmlVMuSOXds0Jqo7O/LmOMKKdRnL93PKfxoHMFnZ8nk0n5vP4RpD2Jrq2DztkpXjr3fHS2797nLLqmOmt1Wftruha6vrSv0V5HBoNB+ezWuW7qRyrvnCkonrtnuk7803V3cmUaZ4p9WivpWpaRE2mMUvlH2ctp/g4ODsp9Tvkk5fZ5vnz5stB9Wfc+h555pLVC1532qk6O6e4p9Owy1ae6aX2Px+OVjtFoVM51tCbS2HXu/VMf5o1diiU6ryzjWUP6vU4cLetskdqme+7OMyvaU1Kc07PP97aM8UzXR+NJ8dx55kvP7dOaXcbZmfqR9lL6vU5sLKN/tNek9UZ5n/qW4p/mNb0PePXp06eVqjTOtH5ortL4U98696SUv1LblBePjo7eLDb2IJ9X0fV1ns8vwr9glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKtqoVjw+Po7lT09PM2UPDw+x7vb29kzZH/7wh1h3c3Mzlv/xj3+cKVtb670nfnl5mSnb29uLdXd3d8vtPj4+tso7dQeDwUzZ/f19rLuxsVG+bmoj/d7W1lasu7q6Wo6No6OjWJf6cXBwMFM2nU5XqkajUSzf2dkpjz+NJ/UjjV0aC4pzGk8ao+fn55my29vbWHd9fT2Wf/nypfx7qQ1qN/WNxoOu+71RLkixkdYUGQ6Hsfzu7q6ceyi3UnylNUtzlfJzV2qb5pVyfLpG6nMnZmiuuvtHp+1OTkpzRX1LY0SxQdLY0ThTrktrgvbMlHM7OYbyCY0RlS8a55TTaIw6fX5vdC2pvLPWKIfSvKb1Q2uqkze6sZHK6bpT/6juW+apTu5J/aB/T7GRzkPds2/KdTSvqc+0hjtnNbq+DupzZ31TP5aRI66vr8trM8XBZDJZeH3TWfQ90Xm/c9ZIMUR1qTzNKY0lxfKPHz8WXg+pnOqmPZr2eMolV1dXC59X0ph27uOWkVcpj1MbKT/QXHXOzvR76X75/Py8/Hu05jtn1m6e6+wFFHepbYrnpHN/TvPSjee3QmN0c3Oz0P0FzTWVp7ZpPLvzktB8p9+kc0nnuin3dM5jdO+f4ivNH/0eXR+Nf2qb4pnaSONBaz6dCTr3jd25ovHo7IMpFqldWlep7e49Q2qj80yUzhud++J0BvktdPYf0pkTmtcUu5S76Eyd2u68O+hK10jrlXIPrc2ONB6de396hkRj97e//a08V+m5ON1XdeaKxpmuO53V0nuG/8l7oWouoDGi8tUlPM9ftI3uvXXn+U/Fx3jKJ0mSJEmSJEmSJEl/B3zBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElSkS9YJUmSJEmSJEmSJKloo1rx/v4+lt/c3MyUbW5uxrqj0WimbHd3N9a9vb2N5dfX1zNla2v5PfHV1VW5H09PT7EulW9szA7dy8tLrHt3dzdTtr6+HutOp9NY/vj4OFM2mUxi3Z2dnfIcHh0dxbq//vrrTNlwOFx5K9vb27H84uKiPEbHx8czZQ8PD615fX5+LsfX1tZWLL+8vCzHxurqajk2qM9pXui6aW3SmFbXPP17+r00pmksfguU61Kfaa7SGhyPx7Hu3t5eORYpBjrjT3U7MUDxlcaI8hGtnxQHnfVK5Slnd6+PriXVpz5TLkh9plhMe8rh4WGsSzGa9hTaMykHprapz8uQ+tyJAYovqru/vz9T9v3791auS2PUWWtvia477btpLGjvTnvEvDXYWfOdMxmtY9pr0rzQ76X5pjMS9aOz1ihmOmOXYpHO4GmtzSvvnOtSPyg20jin/Ne97u6aSPNCY9E513XOhlSXcm7aY+neKs0V/R7Fcxo72uff0zLOR0n3/mIwGMyU/fjxo/x71Ea655i3ptI8Uc5OcU9nWYqX1A+K2U4bp6enK4ui9Z7mlvZ4WlOdNtJ1d3IDxS7FKOXmtF4pvtK9C7VLMZPmla6P2k55mNZxmis621BspFxOe9J7oz0pjQfdz6Q5SXmnuyel53fz1kSKL3ruRf1I5XTmSWd7yuWdWOyepdK8UDyna6G4pWtJaA1SzKTf7JzTKD/Q76X+dcaT9jaK0bQ/0j033SOm+wPqG81VusbPnz/Hun/9619LfZgXM2kNnp+fr3wENN8px1M8d+aE1mDKSXQfR+OcciDVpVzXkfYwOsd01g+hup33CuksQ+3SGNGaXfQZUmcsCN0rpbY7uZws4zkUjfMwzCudIztrk55Rdu496byX1uAi4+xfsEqSJEmSJEmSJElSkS9YJUmSJEmSJEmSJKnIF6ySJEmSJEmSJEmSVOQLVkmSJEmSJEmSJEkqmv2SffNjv+kjsvQB+dPT0/IHctOHtenjtPf397HuyclJLE+/2f3QePo4MI1RGo/0gWn6yC6hMaKPtKcPoXfq0gew6UPCHfSR4/RxZxq7zoeg08eyaQ7v7u5afT4+Pp4pG4/H5fmm6yMpnukjzrRWKHar47y9vR3rUj9SLC3jg9vLQGuw82H5x8fH8r9PdWlOKE9RPHfyyWQyKdel+aZr6dRN643q0voeDAblPNX5YD3ly42NjVIZ/R71j+qm2OjEEcVMdx9Mfb64uIh1U9uU625ubsofvac2aL2lPl9dXcW6KW9T7HfGmcbzvdGaSOuns15pTuj3Uu7p5C5CezfFeTqr0VylvZTGqJO/KL6oz519M60J2jvorJDmluaK5jtdd+dsQnmR1nz6PYrRzlmI5jXtHzRGnRxIMdApPzs7K/eZ7uVonNM1ds4Vb4XGJ8VcZz3R+FB8prVG93EUF6l/dH2US9L8dXIUneupz+lMQGcsyhnpGqmNDrqv7bSd7vmWcU9KfaD4Srr7SUIxmtY7XR9dS+oH5eDOnKRnGHTWo7ila0nX3bk/fEudfnTuSel+huYqtXF0dNRag2lNjEajWJfOD6kNWj/p3Esx0BkPymnURiqncU6xSNdH5+EOuldK65hyTKcfdN2pje4ZubNW/vEf/7F8tvn9739fvp+knEblKZ6pHymvdffdzrON90bzmnIE1U3PdDrPo2mc6fc6zw+WsadQn9Oe3tnvlpVP0pqg8e/kus79Xed+pvvOo/OuaBk6MbOM8yW5vLwsx1fnXqezNmksaPw7zxoq/AtWSZIkSZIkSZIkSSryBaskSZIkSZIkSZIkFfmCVZIkSZIkSZIkSZKKfMEqSZIkSZIkSZIkSUW+YJUkSZIkSZIkSZKkoo1qxe3t7Vh+eno6U/bp06dYd319fabs+fk51p1Op7H86elppuzh4SHW3draiuWp/u3tbauNVL62lt9Xp2tMY/Hq5eWl3AaN3erqarltur6E+nx/f7+yqM3NzVi+u7tbigGS/v2rnZ2dWJ7avru7a/U5tbGxkZdaGn9q9/HxMZanOKA46swh9TnFF83JeDwu5xPKMe+NYiPlDVpraexo/micUznFIrXdieevX7+W2055/9VgMIjl1XZpzVI8U9xRLk6o7WQ4HC48zrS3pbHrXAetbconHZPJJJan+B+NRuV1Reun02fa/2l/TOW05q+ursp5iso7+fK9UZ/Pz89nyvb29mLdNN/X19exLs13WlfLOFccHh626qffpPhK641yOeWYTpzTGkzx3DmbpBh/dXR0VM5f3VyX8hqNXYpRWtu0rjqxRHk0xSj1I813t8/pbEhjRG2fnZ2V13GKme/fv8e6lONp7H5rnftJmo/OObtz5qFzEJ2lUgxQnzvnpk4sd+9fO2uY2k55inJzB90Dp5ihupRfUp7r3OPT/esyno/QXpz2GYrFThzRvKY2unt/6h9d98XFRXm/pPI0hzc3NysfAc1rp27KSbTHd3IMzQmVn5yclMe5cw9MddP6ptxKfe6c7WlNdO77Uj8oP3RzQWdN0NmkWpfyxjLaoPlO40Fjn+Kfzs6Uv1Keor7RukrnN+pH55kCxUwa02Xsu8tA15LKO/da3VhcxvPylHuoH3TdaR1T3bR+qC5dSydvkE7e6OTFztmJ4pnmKq3B7j6xKMoPnXsSGvs0zt018Rzqd+9f015P85p078+Wzb9glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklRU/rowfeQ4fdiXPnycPhhMH9bufMw4fch7Xht0LR3pw+R0LWk8qC59KDm1QR9H39nZieXpQ+iHh4ex7ng8Lo9zZzypbvqYMX0gmsYolXfilj62TB9HTx+6fnV2dlb6gDnNK33wmeY7tU3xRbGRxrnzIXW6PoqZNN90fe+tkzdorjpj1PkIPX20u9Nn+tA4rcHU9nA4jHXTeHTWazfX0drs5I10ffR7NHZpnPf392Nd6kdq4/b2ttxGN75SfapLfU7jTzE6mUxWqugMkeKL5oraSGNK+2DKlxQDdN2L1n1L379/L+dtio00numsQWfAeWulM3YpRmn90FpJc0vzneKrk8tpn6Y9mnLd3d1d+dyTymlt036Q2qCzEI1z+k3qRxoj2nfpulM8U106O11eXpbbSHFA10drIo1d2tfm9Xl7e7uch1NdOr915pXOCu8pXRuV016Q9pkUE904pFimOa22O68faZ46exLlKIqt3d3dUh/mxXj6zdRud/1RLKd+UA6muVr0jEVjMRqNYnlqm/ILxUy6RjpLpfjq7D20rmi/7MRM2hcpHx0fH7d+L40RrYn31pkrWvOpvHt/nmKRfo/iPD2HonzZuQemdZyukfpG/Uj1O89/SGc/oLPbMmKUxiOtFco9qZz2aJqrzvMRkuaQ+nxxcTFT9rvf/a5cl9ruPEOieyv6vbRPUB7u3KNQDLw36kd6BkvxlcaIch3tKSn2u8/ZOmckipm0VqiNdHalmKP8lcaJ2qDxSNdNbaT5phigOUxrsPNMjn6Tfi+1TTmNdPIajXOn3c79AcXiAM6XnfuGtKd33g3SvJJ0jYs8q/MvWCVJkiRJkiRJkiSpyBeskiRJkiRJkiRJklTkC1ZJkiRJkiRJkiRJKvIFqyRJkiRJkiRJkiQV+YJVkiRJkiRJkiRJkoo2qhUvLi5i+XA4nCk7Pz+PdW9vb2fK1tbyO14qf3l5mSm7u7uLdVdXV2P5dDottftqMBjE8oeHh5myzc3NWHcymcyUbW1txbpPT08rVWns541Huu7T09NYd3t7u9w3mqv0e+T+/j6Wb2xslPpG/UtjT+3StVAcUds7OzulvtEYPT8/l+tSLKY+zIuNdC3r6+uxblornbqvxuNx+brfG/UjlVPcppjZ29sr50UaUxrPTr6k36M1QXNb9fj4uLIoyq27u7uxPK23zrzSeNK1pHJaaxQzKa/Rdaf1TfmBYiaV0/VRP1IsdXIrxRZdS5pXyq2dsaM1kdYx7Qc0rx8Z7aUpDmg8U92Dg4NYl8YurcFuLKY4oHMWSW1Qn1Psds481EZnvdL+T2si/V4nBmg8Uh/m5VzKr0nKJ505oXnpnLUp7qiN1D+6ZorRzr5LObezjlN80fV1yrvj/BbSeZPG4urqKtZN80frne7N0nx0Yojqd9ZqVzrHdPZnii26R6GckdqmuE9tUI4inTxHe3+q35lXyg00Run3uvm9E+edGKCxS2uwG7dpnKjPqe3r6+ty32hNfIQ8N09abzQn6b6qe++Z7nfPzs5i3aOjo3KM0r5IcZ6ebXTuUahdGrv0zJDGiPqR4pnGP8Uo5Q1qo7PeKG+kcaKxS+uH6nbi+cePH602UizRvpT61z3fpnmh36N8ktqgPJXQ+qHfS9d4fHy88hHQdad1Rc+KUu7vrEva/6lu550CxRHFXbrGm5ubhc9TnXsR6huNR8oF1I/OMyv6vbTeKI46z6RprtLvLfpMtXueomuh6+v0j85Z01BOOZ7KO8/fOs+ZO7lukXso/4JVkiRJkiRJkiRJkop8wSpJkiRJkiRJkiRJRb5glSRJkiRJkiRJkqQiX7BKkiRJkiRJkiRJUpEvWCVJkiRJkiRJkiSpaKNa8eXlJZY/PT1Vm1i5u7ubKRsOh7Hu7e1tLB+NRgv93qv19fXydaytrZXboDF6fn6eKVtdXW393v39/UzZ4+NjuW+vdnZ2Zso2NnIIpPLt7e1Y9/v37+Xfo+ve29uL5WlM01jMazvpXDf9XsfDw0Ms39zcLM9fqvtqd3e33AbFaJrbra2t1thVY5+upZNL3hKNXUJrMJlMJq01n3JgJ8YJzR9dd2c80hxSDHTGLuWSV5eXl7F80XGiPndQHyiPpnGmvJHGmX6PxjmV0zh3YoPqUpx36qZrXMaaoPnuxD7lZ8q5HwHl+BR3nTHqjBu1TeNGsZHW1TL2lO5ZrSOdLTpnTrpuWvNpTGnN0xm8M9+dHL+MuO2uzbeS5rAbL501RDGa7q9ubm7KsUFnBYqZdM9Fe9h7onhJZ+fz8/NyLNP9KM3HMnJlQvcoNH/puik+OzmDpLigMaK5Sv2gNlI5tUs5KrVBY0T3r51clPYqmldqI5VTHu+gOFrG2Su1QdfXyfudut3zX+d89N4o33Zyz3Q6LccAnbHSvdkyzoUpd83LSWkN0bPBFDMUi7Q2Uz7pPAehOaTcc3Z2tvB6TXNIeZHGuXPG6qxNiq8Uo58/f174HNpZP3SWonv8dC00bun6KJ93zpbULsVM6t/p6enKR0Bzla6F7icvLi5myg4ODhaeV9JZ87R30/oZj8cL/R7lqc4zq87zJiqnfnTepXTOPcu4l++03XmGTrHbeb/VPV8u4/51J+wT1AatnzTflL9S291ncp39v8K/YJUkSZIkSZIkSZKkIl+wSpIkSZIkSZIkSVKRL1glSZIkSZIkSZIkqcgXrJIkSZIkSZIkSZJUVP7S7nA4LH8slj6ym+p++vQp1v2P//iP8geR6YPB+/v7sTx9mPz6+rr1Mel0jfTx9/RR3t3d3XK79CHuwWDQ+oAv/Wb148L04Wka5729vfKHmekjx+kjzPTB7TT+NBY0V6ltaoOk+tRG+kA3xTN9zDuhuaKPwk8mk3IbaU3Qx6vpWlLspj78FmgNptxDddN40PXRukz1F/ng9v8tFmkOO3GX0Hql605xR+t1PB7H8tFoVO5f5/oof6UxpXZpDjsfvk9jRPNHY5d+j66P2k7llDfSeNAYUYymsaO9YxlS/2gsqM+d2HhvNN8pr1Hcpj2a2k05tLvm0+9RHFB+pvFP/ejGaEfK8Z3Ypz531jHlHZqrNM60JigXdKQ5pHMM9TnF0jLWIPWDxiPp5K9uzKV7ndvb21g3xQHd99E4p7ijuu+pk7vovJLmie7B0v0atUH3mB2dvErllAdSObWb7nUJtUExnvIAtZHGg/aTZeSos7OzWJ7mlua7c19F853ivJOLaPyvrq7KsUFrgtZVyqGdGKDxoPuL1DbtlxQzaa6o7nvr7BEUG+n6KIfS/pWeqXWfS6T96/T0NNb96aefym13zjYUc7QmOvsExUzaPyhvpNg9ODiIdelaUp8pjuj8nc6y9Hud/Yfiq5OnaJxTn+mZwufPn8u/R+sqPSs9Pz+PdSlGO8+T0xjRHk3jf3Jy8mHvX2mc03hQ3bQ2KcY7z6/T8+956zjlKZormu90tu8866a+Ue5P/aM2aDxS3NF1p3xCz/roTJZ07/EXfRZP+10Hnac6z6Q7968UAzRG26F/nfM6xUbn7Ev7IMVX52xY4V+wSpIkSZIkSZIkSVKRL1glSZIkSZIkSZIkqcgXrJIkSZIkSZIkSZJU5AtWSZIkSZIkSZIkSSryBaskSZIkSZIkSZIkFa2+vLy8VCtLkiRJkiRJkiRJ0v9m/gWrJEmSJEmSJEmSJBX5glWSJEmSJEmSJEmSinzBKkmSJEmSJEmSJElFvmCVJEmSJEmSJEmSpCJfsEqSJEmSJEmSJElSkS9YJUmSJEmSJEmSJKnIF6ySJEmSJEmSJEmSVOQLVkmSJEmSJEmSJEkq8gWrJEmSJEmSJEmSJK3U/H9wq4SckZk8/AAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 2400x800 with 12 Axes>"
       ]
@@ -214,7 +206,7 @@
     "\n",
     "### 2.1. Defining the Training Set\n",
     "\n",
-    "The training set consists of simulated 51 by 51 pixel images (the same size as the experimantal video), containing a single particle each. The particles are simulated as spheres with a radius between 1 micron and 2 microns, and a refractive index between 1.37 and 1.42. Its position in the camera plane is constrained to be within the image, and is sampled with a normal distribution with standard deviation of 5 pixel units in along the axis normal to the camera plane."
+    "The training set consists of simulated images of 51 by 51 pixels, the same size as the experimental frames, each containing a single particle. You simulate the particle as a sphere with a radius between 500 nm and 600 nm and a refractive index between 1.37 and 1.42. Its position in the camera plane is drawn uniformly within 5 pixels of the image center, and its position along the axis normal to the camera plane is drawn uniformly between -1 and 1 pixel."
    ]
   },
   {
@@ -243,7 +235,7 @@
     "id": "o7cK1GQy6sg3"
    },
    "source": [
-    "The particle is imaged using a brightfield microscope with NA of 0.8 and a illuminating laser wavelength of 630 nm. To simulate the broad spectrum we define 10 individual optical devices, each imaging the particle at a single wavelength. The result is then averaged."
+    "You image the particle with a brightfield microscope with a numerical aperture of 0.8, a magnification of 15, and an illuminating laser wavelength of 630 nm."
    ]
   },
   {
@@ -252,20 +244,7 @@
    "metadata": {
     "id": "k3_vvW7R6qHN"
    },
-   "outputs": [
-    {
-     "ename": "AttributeError",
-     "evalue": "'Microscope' object has no attribute 'store_properties'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[8], line 12\u001b[0m\n\u001b[1;32m      1\u001b[0m brightfield_microscope \u001b[38;5;241m=\u001b[39m dt\u001b[38;5;241m.\u001b[39mBrightfield(\n\u001b[1;32m      2\u001b[0m     NA\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.8\u001b[39m,\n\u001b[1;32m      3\u001b[0m     resolution\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e-6\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m      8\u001b[0m     output_region\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m, image_size, image_size),\n\u001b[1;32m      9\u001b[0m )\n\u001b[1;32m     11\u001b[0m dataset \u001b[38;5;241m=\u001b[39m brightfield_microscope(particle)\n\u001b[0;32m---> 12\u001b[0m \u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstore_properties\u001b[49m()\n",
-      "File \u001b[0;32m~/Documents/GitHub/DeepTrack2/deeptrack/features.py:2350\u001b[0m, in \u001b[0;36mFeature.__getattr__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2347\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m key \u001b[38;5;129;01min\u001b[39;00m properties:\n\u001b[1;32m   2348\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m properties[key]\n\u001b[0;32m-> 2350\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\n\u001b[1;32m   2351\u001b[0m     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m object has no attribute \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkey\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   2352\u001b[0m )\n",
-      "\u001b[0;31mAttributeError\u001b[0m: 'Microscope' object has no attribute 'store_properties'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "brightfield_microscope = dt.Brightfield(\n",
     "    NA=0.8,\n",
@@ -277,32 +256,7 @@
     "    output_region=(0, 0, image_size, image_size),\n",
     ")\n",
     "\n",
-    "dataset = brightfield_microscope(particle)\n",
-    "dataset.store_properties()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "T9ajggxw635c"
-   },
-   "source": [
-    "### 2.2. Defining the Training Label\n",
-    "\n",
-    "The training label is extracted directly from the image as the `position` property divided by the image size, such that the posible values are contained within -0.5 and 0.5."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "id": "KHmmMadp6zjg"
-   },
-   "outputs": [],
-   "source": [
-    "def get_label(image):\n",
-    "    px = np.array(image.get_property(\"position\")) / image_size - 0.5\n",
-    "    return px"
+    "dataset = brightfield_microscope(particle)"
    ]
   },
   {
@@ -311,14 +265,14 @@
     "id": "iQMLLnWw67PT"
    },
    "source": [
-    "### 2.3. Visualizing the Dataset\n",
+    "### 2.2. Visualizing the Dataset\n",
     "\n",
-    "We resolve and show 6 images, with a green circle indicating the particle position."
+    "You resolve and show six images, each with a green circle marking the particle position. You read the position directly from the particle with `particle.position()`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -328,21 +282,9 @@
     "outputId": "c7e584bb-3646-4608-af79-0c3b8711d296"
    },
    "outputs": [
-    {
-     "ename": "AttributeError",
-     "evalue": "'numpy.ndarray' object has no attribute 'get_property'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[10], line 8\u001b[0m\n\u001b[1;32m      5\u001b[0m dataset\u001b[38;5;241m.\u001b[39mupdate()\n\u001b[1;32m      6\u001b[0m image_of_particle \u001b[38;5;241m=\u001b[39m dataset()\n\u001b[1;32m      7\u001b[0m position_of_particle \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m----> 8\u001b[0m     \u001b[43mget_label\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage_of_particle\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m*\u001b[39m image_size \u001b[38;5;241m+\u001b[39m image_size \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m\n\u001b[1;32m      9\u001b[0m )\n\u001b[1;32m     10\u001b[0m ax\u001b[38;5;241m.\u001b[39mimshow(image_of_particle[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m0\u001b[39m], cmap\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgray\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     11\u001b[0m ax\u001b[38;5;241m.\u001b[39mscatter(\n\u001b[1;32m     12\u001b[0m     position_of_particle[\u001b[38;5;241m1\u001b[39m],\n\u001b[1;32m     13\u001b[0m     position_of_particle[\u001b[38;5;241m0\u001b[39m],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     17\u001b[0m     linewidth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[1;32m     18\u001b[0m )\n",
-      "Cell \u001b[0;32mIn[9], line 2\u001b[0m, in \u001b[0;36mget_label\u001b[0;34m(image)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_label\u001b[39m(image):\n\u001b[0;32m----> 2\u001b[0m     px \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(\u001b[43mimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_property\u001b[49m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mposition\u001b[39m\u001b[38;5;124m\"\u001b[39m)) \u001b[38;5;241m/\u001b[39m image_size \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m0.5\u001b[39m\n\u001b[1;32m      3\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m px\n",
-      "\u001b[0;31mAttributeError\u001b[0m: 'numpy.ndarray' object has no attribute 'get_property'"
-     ]
-    },
     {
      "data": {
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       "text/plain": [
        "<Figure size 2500x800 with 6 Axes>"
       ]
@@ -356,11 +298,12 @@
     "\n",
     "fig, axs = plt.subplots(1, number_of_images, figsize=(25, 8))\n",
     "for i, ax in enumerate(axs.flatten()):\n",
+    "\n",
     "    dataset.update()\n",
-    "    image_of_particle = dataset()\n",
-    "    position_of_particle = (\n",
-    "        get_label(image_of_particle) * image_size + image_size / 2\n",
-    "    )\n",
+    "    image_of_particle = dataset.resolve()\n",
+    "\n",
+    "    position_of_particle = particle.position()\n",
+    "\n",
     "    ax.imshow(image_of_particle[..., 0], cmap=\"gray\")\n",
     "    ax.scatter(\n",
     "        position_of_particle[1],\n",
@@ -382,21 +325,25 @@
     "id": "Kivd5eQPBHp2"
    },
    "source": [
-    "### 2.4. Augmenting the Dataset\n",
+    "### 2.3. Augmenting the Dataset\n",
     "\n",
-    "Simulating mie particles is slow. To speed up training we implement augmentation techniques. Here we flip and mirror the image. Note that DeepTrack ensures that the position is still correct after the augmentation."
+    "Simulating Mie particles is slow, so you augment each simulated image to get several training examples from it. Here you flip and mirror the image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {
     "id": "FrRpQQHZ7Eco"
    },
    "outputs": [],
    "source": [
+    "flip_lr = dt.FlipLR(p=0.5)\n",
+    "flip_ud = dt.FlipUD(p=0.5)\n",
+    "flip_diagonal = dt.FlipDiagonal(p=0.5)\n",
+    "\n",
     "augmented_dataset = (\n",
-    "    dt.Reuse(dataset, 8) >> dt.FlipLR() >> dt.FlipUD() >> dt.FlipDiagonal()\n",
+    "    dt.Reuse(dataset, uses=8) >> flip_lr >> flip_ud >> flip_diagonal\n",
     ")"
    ]
   },
@@ -406,12 +353,12 @@
     "id": "XrA7vQeMBR36"
    },
    "source": [
-    "We add noises after augmentation. This allows the augmented images to be more distinct."
+    "You add noise after augmentation, so that the augmented images differ more from one another. You apply an illumination gradient, Poisson noise with a signal-to-noise ratio between 5 and 100, and a final normalization."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {
     "id": "6UYaXrVbBKSF"
    },
@@ -434,9 +381,25 @@
     "    lambda: 0.8 + np.random.rand() * 0.2,\n",
     ")\n",
     "\n",
-    "data_pipeline = augmented_dataset >> gradient >> noise >> normalization\n",
+    "data_pipeline = augmented_dataset >> gradient >> noise >> normalization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To get the position of the particle, you use `particle.position` to create a pipeline for the position. Then you create a combined pipeline that holds both the image of the particle and its corresponding position."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pos_pipeline = particle.position\n",
     "\n",
-    "data_pipeline.store_properties()"
+    "combined_pip = data_pipeline & pos_pipeline"
    ]
   },
   {
@@ -445,12 +408,12 @@
     "id": "vcWzwxp1P1lF"
    },
    "source": [
-    "We resolve and show 6 images, with a green circle indicating the particle position."
+    "You resolve and show six images, each with a green circle marking the particle position. Since `particle.position` gives the position before the flips, you reapply the same flips to it here so the circle lands on the particle."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -462,9 +425,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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       "text/plain": [
-       "<Figure size 1800x576 with 6 Axes>"
+       "<Figure size 2500x800 with 6 Axes>"
       ]
      },
      "metadata": {},
@@ -476,11 +439,18 @@
     "\n",
     "fig, axs = plt.subplots(1, number_of_images, figsize=(25, 8))\n",
     "for i, ax in enumerate(axs.flatten()):\n",
-    "    data_pipeline.update()\n",
-    "    image_of_particle = data_pipeline()\n",
-    "    position_of_particle = (\n",
-    "        get_label(image_of_particle) * image_size + image_size / 2\n",
-    "    )\n",
+    "\n",
+    "    combined_pip.update()\n",
+    "    image_of_particle, raw_position = combined_pip.resolve()\n",
+    "\n",
+    "    position_of_particle = raw_position.copy()\n",
+    "    if flip_lr.augment():\n",
+    "        position_of_particle[1] = image_size - 1 - position_of_particle[1]\n",
+    "    if flip_ud.augment():\n",
+    "        position_of_particle[0] = image_size - 1 - position_of_particle[0]\n",
+    "    if flip_diagonal.augment():\n",
+    "        position_of_particle = position_of_particle[::-1]\n",
+    "\n",
     "    ax.imshow(image_of_particle[..., 0], cmap=\"gray\")\n",
     "    ax.scatter(\n",
     "        position_of_particle[1],\n",
@@ -490,6 +460,7 @@
     "        edgecolors=\"g\",\n",
     "        linewidth=2,\n",
     "    )\n",
+    "\n",
     "    ax.set_xticks([])\n",
     "    ax.set_yticks([])\n",
     "\n",
@@ -505,7 +476,7 @@
    "source": [
     "## 3. Defining the Network\n",
     "\n",
-    "Define a convolutional neural network with a dense top ..."
+    "The network is a convolutional neural network with a dense top. You first define its architecture."
    ]
   },
   {
@@ -590,7 +561,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and compile it for a regression task."
+    "Then, you compile it for a regression task, defining the loss function, the optimizer, and the error metric."
    ]
   },
   {
@@ -604,14 +575,6 @@
     "outputId": "0dee008a-c699-41f1-bdf3-046639364ad5"
    },
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO:torch.distributed.nn.jit.instantiator:Created a temporary directory at /tmp/tmpdakdadqu\n",
-      "INFO:torch.distributed.nn.jit.instantiator:Writing /tmp/tmpdakdadqu/_remote_module_non_scriptable.py\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -698,12 +661,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Define a custom dataset ..."
+    "First, you define a custom dataset that generates the simulated images and their position labels.\n",
+    "\n",
+    "In `__getitem__`, you turn each image and position into tensors and rescale the position with `self.positions[idx] / im.shape[-1] - 0.5`. Dividing by the image size and subtracting 0.5 maps the position from pixels to the range -0.5 to 0.5. Networks train more easily when the targets are small and centered on zero, so this rescaling helps the training converge."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {
     "id": "EcRJVoKrRkUQ"
    },
@@ -716,14 +681,20 @@
     "        \"\"\"Initialize simulated dataset.\"\"\"\n",
     "        images, positions = [], []\n",
     "        for _ in range(data_size):\n",
-    "            image = data_pipeline.update().resolve()\n",
-    "            position = image.get_property(\"position\")\n",
-    "            images.append(image), positions.append(position[[1, 0]])\n",
-    "        self.images, self.imges_, self.positions = (\n",
-    "            np.array(images),\n",
-    "            images,\n",
-    "            np.array(positions),\n",
-    "        )\n",
+    "            image, raw_position = pipeline.update().resolve()\n",
+    "\n",
+    "            position = raw_position.copy()\n",
+    "            if flip_lr.augment():\n",
+    "                position[1] = image_size - 1 - position[1]\n",
+    "            if flip_ud.augment():\n",
+    "                position[0] = image_size - 1 - position[0]\n",
+    "            if flip_diagonal.augment():\n",
+    "                position = position[::-1]\n",
+    "\n",
+    "            images.append(image)\n",
+    "            positions.append(position[[1, 0]])\n",
+    "        self.images = np.array(images)\n",
+    "        self.positions = np.array(positions)\n",
     "\n",
     "    def __len__(self):\n",
     "        \"\"\"Return number of images.\"\"\"\n",
@@ -740,8 +711,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and use it to create the train data and test data loaders.\n",
-    "\n"
+    "Then, you use it to create the training and test data loaders."
    ]
   },
   {
@@ -753,11 +723,11 @@
    "outputs": [],
    "source": [
     "train_sim_dataloader = dl.DataLoader(\n",
-    "    SimulatedDataset(pipeline=data_pipeline, data_size=3000),\n",
+    "    SimulatedDataset(pipeline=combined_pip, data_size=3000),\n",
     "    batch_size=32,\n",
     ")\n",
     "test_sim_dataloader = dl.DataLoader(\n",
-    "    SimulatedDataset(pipeline=data_pipeline, data_size=1000),\n",
+    "    SimulatedDataset(pipeline=combined_pip, data_size=1000),\n",
     "    batch_size=32,\n",
     ")"
    ]
@@ -766,7 +736,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Train the neural network regressor with simulation data."
+    "Finally, you train the neural network regressor on the simulated data."
    ]
   },
   {
@@ -798,99 +768,33 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/iluvatar/anaconda3/lib/python3.9/site-packages/lightning/pytorch/trainer/configuration_validator.py:70: You defined a `validation_step` but have no `val_dataloader`. Skipping val loop.\n",
-      "2025-07-01 22:07:04.692890: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+      "C:\\Users\\xgrmir\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\lightning\\pytorch\\trainer\\configuration_validator.py:74: You defined a `validation_step` but have no `val_dataloader`. Skipping val loop.\n",
+      "\n",
+      "  | Name          | Type             | Params\n",
+      "---------------------------------------------------\n",
+      "0 | loss          | MSELoss          | 0     \n",
+      "1 | train_metrics | MetricCollection | 0     \n",
+      "2 | val_metrics   | MetricCollection | 0     \n",
+      "3 | test_metrics  | MetricCollection | 0     \n",
+      "4 | model         | Sequential       | 98.2 K\n",
+      "5 | optimizer     | Adam             | 0     \n",
+      "---------------------------------------------------\n",
+      "98.2 K    Trainable params\n",
+      "0         Non-trainable params\n",
+      "98.2 K    Total params\n",
+      "0.393     Total estimated model params size (MB)\n",
+      "C:\\Users\\xgrmir\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\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=19` in the `DataLoader` to improve performance.\n"
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-       "│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 0 </span>│ loss          │ MSELoss          │      0 │ train │\n",
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-       "┃\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mName         \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mType            \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mParams\u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mMode \u001b[0m\u001b[1;35m \u001b[0m┃\n",
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-       "│\u001b[2m \u001b[0m\u001b[2m0\u001b[0m\u001b[2m \u001b[0m│ loss          │ MSELoss          │      0 │ train │\n",
-       "│\u001b[2m \u001b[0m\u001b[2m1\u001b[0m\u001b[2m \u001b[0m│ train_metrics │ MetricCollection │      0 │ train │\n",
-       "│\u001b[2m \u001b[0m\u001b[2m2\u001b[0m\u001b[2m \u001b[0m│ val_metrics   │ MetricCollection │      0 │ train │\n",
-       "│\u001b[2m \u001b[0m\u001b[2m3\u001b[0m\u001b[2m \u001b[0m│ test_metrics  │ MetricCollection │      0 │ train │\n",
-       "│\u001b[2m \u001b[0m\u001b[2m4\u001b[0m\u001b[2m \u001b[0m│ model         │ Sequential       │ 98.2 K │ train │\n",
-       "│\u001b[2m \u001b[0m\u001b[2m5\u001b[0m\u001b[2m \u001b[0m│ optimizer     │ Adam             │      0 │ train │\n",
-       "└───┴───────────────┴──────────────────┴────────┴───────┘\n"
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-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Trainable params</span>: 98.2 K                                                                                           \n",
-       "<span style=\"font-weight: bold\">Non-trainable params</span>: 0                                                                                            \n",
-       "<span style=\"font-weight: bold\">Total params</span>: 98.2 K                                                                                               \n",
-       "<span style=\"font-weight: bold\">Total estimated model params size (MB)</span>: 0                                                                          \n",
-       "</pre>\n"
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-       "\u001b[1mTrainable params\u001b[0m: 98.2 K                                                                                           \n",
-       "\u001b[1mNon-trainable params\u001b[0m: 0                                                                                            \n",
-       "\u001b[1mTotal params\u001b[0m: 98.2 K                                                                                               \n",
-       "\u001b[1mTotal estimated model params size (MB)\u001b[0m: 0                                                                          \n"
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        "version_major": 2,
        "version_minor": 0
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       "text/plain": [
-       "Output()"
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/iluvatar/anaconda3/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:424: 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=35` in the `DataLoader` to improve performance.\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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-      "text/plain": []
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-     "output_type": "display_data"
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-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
+       "Training: |          | 0/? [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -915,50 +819,50 @@
     "tags": []
    },
    "source": [
-    "### 5.1. Testing the Trained Neural Network\n"
+    "### 5.1. Testing on Simulated Data"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can calculate the mean pixel error (MAE) in train dataset ..."
+    "You calculate the mean absolute error (MAE) on the training set, expressed in pixels."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\xgrmir\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\lightning\\pytorch\\trainer\\connectors\\data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=19` in the `DataLoader` to improve performance.\n"
+     ]
+    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0d647742732d4749a4883b08742b00e0",
+       "model_id": "a53e7a2f951a4c3a84ac04eb2d8a6da2",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output()"
+       "Testing: |          | 0/? [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/iluvatar/anaconda3/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:424: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=35` in the `DataLoader` to improve performance.\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
        "┃<span style=\"font-weight: bold\">         Test metric         </span>┃<span style=\"font-weight: bold\">        DataLoader 0         </span>┃\n",
        "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
-       "│<span style=\"color: #008080; text-decoration-color: #008080\"> testMeanAbsoluteError_epoch </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.0012698841746896505    </span>│\n",
-       "│<span style=\"color: #008080; text-decoration-color: #008080\">       test_loss_epoch       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">   2.5724107217683922e-06    </span>│\n",
+       "│<span style=\"color: #008080; text-decoration-color: #008080\"> testMeanAbsoluteError_epoch </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.0015975942369550467    </span>│\n",
+       "│<span style=\"color: #008080; text-decoration-color: #008080\">       test_loss_epoch       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    4.130964953219518e-06    </span>│\n",
        "└─────────────────────────────┴─────────────────────────────┘\n",
        "</pre>\n"
       ],
@@ -966,42 +870,19 @@
        "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
        "┃\u001b[1m \u001b[0m\u001b[1m        Test metric        \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m       DataLoader 0        \u001b[0m\u001b[1m \u001b[0m┃\n",
        "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
-       "│\u001b[36m \u001b[0m\u001b[36mtestMeanAbsoluteError_epoch\u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.0012698841746896505   \u001b[0m\u001b[35m \u001b[0m│\n",
-       "│\u001b[36m \u001b[0m\u001b[36m      test_loss_epoch      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m  2.5724107217683922e-06   \u001b[0m\u001b[35m \u001b[0m│\n",
+       "│\u001b[36m \u001b[0m\u001b[36mtestMeanAbsoluteError_epoch\u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.0015975942369550467   \u001b[0m\u001b[35m \u001b[0m│\n",
+       "│\u001b[36m \u001b[0m\u001b[36m      test_loss_epoch      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   4.130964953219518e-06   \u001b[0m\u001b[35m \u001b[0m│\n",
        "└─────────────────────────────┴─────────────────────────────┘\n"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean pixel error (MAE) for train dataset: 0.065 pixels\n"
+      "Mean pixel error (MAE) for train dataset: 0.081 pixels\n"
      ]
     }
    ],
@@ -1017,7 +898,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... as well as the test dataset."
+    "Then you do the same on the test set."
    ]
   },
   {
@@ -1048,12 +929,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5bbc78f3f9fe4deb90b89e72f8af3615",
+       "model_id": "3d695a29f83c462ab4cc5f05938b3e79",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output()"
+       "Testing: |          | 0/? [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -1065,8 +946,8 @@
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
        "┃<span style=\"font-weight: bold\">         Test metric         </span>┃<span style=\"font-weight: bold\">        DataLoader 0         </span>┃\n",
        "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
-       "│<span style=\"color: #008080; text-decoration-color: #008080\"> testMeanAbsoluteError_epoch </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.0014535399386659265    </span>│\n",
-       "│<span style=\"color: #008080; text-decoration-color: #008080\">       test_loss_epoch       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    4.048844402859686e-06    </span>│\n",
+       "│<span style=\"color: #008080; text-decoration-color: #008080\"> testMeanAbsoluteError_epoch </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.0017521787667647004    </span>│\n",
+       "│<span style=\"color: #008080; text-decoration-color: #008080\">       test_loss_epoch       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    5.673749456036603e-06    </span>│\n",
        "└─────────────────────────────┴─────────────────────────────┘\n",
        "</pre>\n"
       ],
@@ -1074,42 +955,19 @@
        "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
        "┃\u001b[1m \u001b[0m\u001b[1m        Test metric        \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m       DataLoader 0        \u001b[0m\u001b[1m \u001b[0m┃\n",
        "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
-       "│\u001b[36m \u001b[0m\u001b[36mtestMeanAbsoluteError_epoch\u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.0014535399386659265   \u001b[0m\u001b[35m \u001b[0m│\n",
-       "│\u001b[36m \u001b[0m\u001b[36m      test_loss_epoch      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   4.048844402859686e-06   \u001b[0m\u001b[35m \u001b[0m│\n",
+       "│\u001b[36m \u001b[0m\u001b[36mtestMeanAbsoluteError_epoch\u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.0017521787667647004   \u001b[0m\u001b[35m \u001b[0m│\n",
+       "│\u001b[36m \u001b[0m\u001b[36m      test_loss_epoch      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   5.673749456036603e-06   \u001b[0m\u001b[35m \u001b[0m│\n",
        "└─────────────────────────────┴─────────────────────────────┘\n"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mean pixel error (MAE) for test dataset: 0.074 pixels\n"
+      "Mean pixel error (MAE) for test dataset: 0.089 pixels\n"
      ]
     }
    ],
@@ -1127,7 +985,7 @@
    "source": [
     "### 5.2. Prediction vs Actual\n",
     "\n",
-    "We can also show the prediction of each output versus the ground truth in train dataset ..."
+    "You can also plot each predicted coordinate against its ground-truth value for the training set."
    ]
   },
   {
@@ -1137,14 +995,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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8rIVF02LIKLTw9eYUftx/gp37DpHy+ZMoBa1nzsYrvF01+04hMGN4V669pD0hdVjeQqNpaFLzinl/zUG+3HyCEqBw/XxDVHpfQcSk3yEep55LCQSuuaQNd1/ehXbhgQ1SSdLComkRpOYV8++VB/l+xwmy8zPJmDsLZa8gZuYcvCKM1YE8AAdGF0HbUJg5qicT+7bWoqJxW2x2B3tT8/jHqkRWJhYAULhhAQU//ZeAXmOImPx7F1HpGCIM69Sa20d3JD4quMH80sKiafYUllr5flcai3ecILsgm4y5T6NspcTMnIN3VHyVXSuMKcUdYoLoGRPO6K4Rekqxxm2x2R3sTcnjpUU72JFurO1VuPFLCtZ9in+vy4m4+g9VouILhPrDhH7tGd01mohAvwb1TQuLplljsVawLjGDrzYfJqswh8y5T+MoKyZmxmy8ozu52Ab6wJBOMcRHB3Fp5wjiIoP0WIrGbUlMy+e173efEpVNX1Gw9mP8e15G5NWPuLRU2oa3YkznaMb3bE1cRCC+Xg2br7WwaJothaVW1iWe4J8/7uNASh6Z857Bbikg5uZX8GndxcU21ANGdY3krsu6EOznTXSwrxYVjVtisVZwOLOQVxfvYVNqKQBFm7+mYM1H+PcYTeSUR6uNqfxqaEdGdo0iOsQfDwG/epwBVhNaWDTNEou1gsW7Uvlm63H2phSQOW8W9pM5RE9/EZ+23avZd4j2Y1Lf1rQL88fPu5UWFY1bUblKRNbJMhLTC5m3JZn1x0oAKNryLfmrP8S/+ygir3nMRVQAbhzWhiGdIogI8sPbUy5K/tbComl2WKwVLNudyj9W7Cclu4jMebOoKMwketrz+Mb2rmYf7gHThnXk8p7t6nUuv0ZTH1SuEmGtcLDzWB7/23SIHalG91fR1oXkr/oA/24jaxSV7hEwrndbutbzcyrnQpciTbPBZneQW1zG8r0neHv5ATIKi8ma/yy2vDSib3oe37h+1eIEAneN7cI1A7SoaNyTUmsF1goHm5Kz+OeKfSQXGuFF274jf+X7hqhc+wTi6Zp/O/jDnZf3onfb0Iuet3VJ0jQLLNYK0vMtbD+Wz7+WHiCzpISsBc9izTlG9A3P4hc/oFocH+Cuy+OZObyDnlKscVuKyyo4mFnIgs3JVaJycvv35K/4N37dRtQoKm384L7xvbisa3Sdthi+ULSwaJo8NruDEwUWDp4oZO76Q6SVWMj64gWsmclEXf80fp0GVYsjwE2D2nLLyI5E6inFGjdmb2oen206zC9HLACc3L6YvB/fxa/rcKJqEJW4YLh1RBfG9IgiOrh+1v46X7SwaJo8RaVWNh3O5ZOfE9h/ooysr16iPD2RqKlP4t9lWDV7X+DOEbHcO667FhWNW7M1KYN3Vx1gx4lyAE7uWELej//Cr8tQoqb+EfF0XbOuT0wrfj2uF1f0aNOoXbtaWDRNGou1gvkbjvD+2mRyS8vJ/volylMTiLzmMfy7j6xm7wvcfVk8D1zRVXd/adwWm93B1uRMXl28j90Zpqjs/IG85f/Er/MQoqY+VU1UBsb68NK1A+jeLrzRZzVqYdE0WTIKLSzYeIy/rk7GXmEl+5vZlB3bQ8SURwjoeVmNce68tAO/0mMqGjfFmIBSzu60fN5auov92Q7AFJVl/8Cv02CirnsaaXWaqLTxY871A+jRzj22y9bCommSFJZa+WzDUd5bcwS73Ub2t69SdmQ7EZP+j8DeV9QY594Rccwc0YGYEP+L7K1Gc25sdgdZRaXsOJrHuyv2sT/XFJVdy8lb9g98Ow0i6vrqonJJaz+eu7aP24gKaGHRNEEs1grmbTrKO2uO4LBXkL3odUoPbyH8qocI7Dehmn0bP/jViE5MGxZPRKDe+VHjnhSVWtl1PJ93V+5jb64dgOLdy8n74W18Ow4k+vpZSKtTLW0fYGyPcB6d2JMurUMbx+kzoIVF06QoLLXyw+5U3l9xCIfDTs73b1J6cANh4x8gaMDEavZD2/tz28jOXNZDr1KscW/WJaTz5g/7STUmf1G8ZwW5S9/GN34A0Tc8U01Ubhnenrsv60RsPWwlXN9oYdE0CWx2B5mFpXy0LokFG1MpctjJXfwWlgM/ETb2XoIHXVMtTp/WrXj0qp70jYvUDz9q3Jo1CWnM/mY/OeaO18V7V5K75G/4duhP1GmiAnDdJdHcf0UXWrtpt26j9gmIyEQRSRSRJBF5sobrIiJ/N6/vFpGBTteOisgeEdkpIlsvrueai4nN7uB4zkk+/SmJ/2xMpUg5yF36NiUJawi9/E6Ch1xXLU6UN/x52hCGdWmtRUXj1uw8ksXLi3aeEpV9q8ld/Fd8O/Qj6sZn8PDycbEfEu/DHyb2dltRgUZssYiIJ/AOMAFIBbaIyCKlVIKT2SSgq3kMA/5lvlZyhVIq5yK5rGkk0vKKmbfxCO9vSEMpB3nL3qFk7wpCRt1CyPCbqtl7As/c0NetBjM1mtOx2R3sPJrNK9/v4XCBEWaIylv4duhL1I3P4uHl+pxVz0gPZk3s79aiAo3bYhkKJCmlkpVSVmAeMPU0m6nAp8pgIxAqIm0utqOaxsNirWDZnhMs3JaGUor8Ff+meNcygkfcTMjIGTXGmTW5G5P7xl5kTy8+InK/iGwVka3Z2dmN7Y7mPLDZHSzZncpTC7ayy3z4sSRhLbmL38KnfR+ibnyumqgMbOvHE1f3p3f7iMZw+bxoTGFpB6Q4naeaYbW1UcByEdkmIvc3mJeaRiUhrYAvtySRWa7IX/UBJ7cvJnjoDYSOvhURcbGN9oVZk7oyY3jHFjHzSyn1nlJqsFJqcFRUVGO7ozkPlu1N408L95Bkrv1Vsn8dOd+/iU9sL6JPExVv4LreETx7bV9GdWvdJPJ2Y3Y+Sw1h6jxsLlVKpYtINPCjiBxQSq2rloghOvcDxMXF1cVfzUXEZnew62g2ryzey8E8RcHajzm5dSFBg64ldMxd1USlrT+8eH0/Lu3euEtZaDRnonJPleSsIl77ZjfpZUZ4yf6fyPnuz4ao3PQCHt6nRCUYePzaHkzq165JLT/UmNKXCrR3Oo8F0mtro5SqfM0CvsHoWquGrtU1PWx2B2sPnODFhbvYmV5G4c//o2jTVwReMpmwcfdVE5UA4Jlr+zCml176XuOe2OwO8krKOZp9kndW7Ce1UlQO/EzOd2/g064H0Tc97yIqAcBto+K5cXCHJiUq0LjCsgXoKiIdRcQbmAEsOs1mEXC7OTtsOFColDohIgEiEgQgIgHAlcDei+m8pmGw2R2s2J/Oi1/vZE+WjYJf5lK4fh6B/a4kfMKD1UQlEHjy2p5M6Nu+SXQRaFommYUWtiXn8JdlCfx4qAiAksRfyFn0Oj5te5gtFb8qe1/g+oFtmTasfZOsLDWax0qpChF5CFiGMZHnQ6XUPhF50Lz+LrAEmAwkARbgLjN6DPCN+SfTCvhcKfXDRf4ImnrGZnewPTmLt5buJaUECjd+SeHP/yOgzzjCJz6EiKtwdAiC31zZm2v6x2pR0bgtFmsFa/dnsHRnGj+nFBthietNUelO9LQX8PBxneV1dd9oZo6Io50bPvxYGxpVCpVSSzDEwznsXaf3CvhtDfGSgf4N7qDmomGzO/hhVwp/+XEvR/KNfbwL1n6Mf6/LiZj0u2qickmML/eO684VPfRzKhr3ZvORbP67MYkD2cYyLZaDG8he9Ce8W3chetqLLqIiwE0DYvi/K3sQE+LfZCtMukRqGh2b3cGibceY820CuQ5zd7xVH+Df/VIir36k2j7eI+MDufvyrozsHK1FReO2FJZaWbEnlVe/30+OsUU9lkMbyV74Gt4xXYiZ/lK1lsr1vSP47bhubrlMy/mgS6WmUckpLuPLzSm8tvwgYC4Pbu6OF3nN49VE5bJOgdx3eTcGdYzSoqJxW3KKy/hmyzE++jnplKgkbSL729fwjulMzM0v4eET4BJnbJdgfjOhB/FRwY3gcf1yzpIpIlHAfUC8s71S6u6Gc0vT3LHZHaTml/DZT8n8Z1MqYCy6l7fsH8ZGRtf+sdqWq93C4PFJfejRNqzJdhFomj8WawWLd6bw3/VJpJeYYUmbyf7mVbyjO5otFVdRubZnBE9f18/tn6ivLbWp8i0EfgJWAPaGdUfTErDZHZwss7F4ZzrzK0Vl32pj0b34S4i67qlqe06Ee8Lz1w+kbxN46ljTcrFYK/hiQzJ/W36IPPPfsvTwFrK/nYN3dDzRN7+Mh++pbi4/4Mo+4fzhql7NRlSgdsLir5T6Y4N7omkR2OwOjuYUs/tYLm+vSKIcYy5/1fpINazkGuIBt4zuwNDOMY3jtEZTC2x2Bwu3HOVvyw6RZ+zRRWnyNrK+mY13ZAeib34FTydR8QFuG9me20e559L3daE2wvK9iEw2Z3BpNBeMsUNeGduSs3hvTSLlgOWgOe2yXU+ibniu2kqukQI3X9qBay+J091fGrfmhz2pvPRdIqXmeWnyNrK+fqVGURFg1uSuTB0S3yz3CTqjsIjISYzlUwR4WkTKAZt5rpRSTX+ESXNRKSq1sv1oLu+sSCSlxOx3Xvg6Pm26VXvqGCDcA349sSuD4yNpF9Z8ugk0zQuLtYIlO1N48euEU6JyZDtZX7+CV0R7Q1T8glziPDa2EzMv7dJsK0tnFBalVNCZrmk050thqZUvNh/j3R+TKFBGbS772zl4x3QkevqL1aZdAtw7tjOXd4+hbViAngGmcUss1grmbTzCa0sOYk7+ovToTrK/fgWviFhiZriKSrQ3zLy0I3eN6dpsRQVqsaSLiKysTZhGcyYs1gr++8th/rLcFJWjO8n+ZjZeEXFET3+52gyZVsCjYztz52Vd6BITokVF47as2pvGP04Xla9eolVYW2JufgVPv1MdO8HAr8d157ZLOzX7PH22rjBfjHXQIkUkjFMrDQcDbS+Cb5pmgM3u4OcD6Xy8OhkrUHZ8D9lfvWwWvJdd+p3ByGS3D23HtGFxzb7waZomlasUJ6UX8NLCveSZ4WXHdht5O7QNMTNm4+kfUhUn0g+emtSLSQOa5tpf58vZPuEDwO8xRGS7U3gRxs6PGs1ZsdkdpOdb+Gp7Kjl2KEtNIOvLF2kVEm3U5pwKHkCoJzw4rgs3DW16q7lqWgaVqxTvPp7Lgi3HyDL26KLs+G4jb4fGVBMVL+C1G/szvk/z33yukrONsfwN+JuIPKyUevsi+qRpBtjsDlYnpPPfXw7z09FiytMTyfrieTyDIoieMRvPgFAX+w6B8Mr0gQzvHNOs+541TZuiUisJafm8tXQPB3KNOcVlx/eYFaYYYmbMccnbAcDjU7q3KFGB2k03LhSR208PVEp92gD+aJoBNruDZbuO8/KifWSWQXlGEpkLnsPTP5SYGbNpFei6F32fKC8em9JXi4rG7dmUnM2bi3dz2Nz5sSxlL1lfvkCr4GhiZrpWmIKBu67ozPWDWt4Gg7URliFO732BcRhdY1pYNNWw2R18s/0Yz32VQBlgzUoma/6zePgGEjNzNq2CIl3sBZg5qguXxEVoUdG4LRZrBbuOZfPSN7vJMOcUl6XuI+uLF/AMijJbKmFV9kHAI1d3Z8olsc3yOZVzcU5hUUo97HwuIiHAfxvMI02TxWZ38PPBDP5UKSrZx8ic9wzi5WO0VIKjq8W5Z1g7pvRrmYVP0zSwWCvYmpzN31YkOIlKgikqkcTMnINn4ClR6RgCv53Qm8n9YlvEQH1NXMintgBd69sRTdMnKbOQ1xftIBew5aaQOX8W4tmKmJlz8Apt7WIbAMwY2o4HJ/TQoqJxWyzWClbtS+Pfq/azx9xPpSx1vzFeGBhOzMw5Ll27vSI9ePzqfozq1qZFt8Brs7rxdxhP4IPx3EsvYEFDOqVpeiRlFPDkvC3szwdbXhqZ82YBEDNjNl5hrrPT44LgnjE9uG5gey0qGrfFYq1gz/Fc/r36lKiUpx0g64vn8AwII2aGq6gMifPn5an96dEu/Ey3bDHUpsXyZ6f3FcAxpVRqA/mjaYKk5hXz0qJ97MqyYSvIIHPeLJS9gpiZr+IV0d7FNj4MXr5uIP3jIgjWoqJxY7YdyeLDdYfZk2WKSnqiMQklINRoqQSdWmk7FHh0fA8tKiZnFRYR8QSeVUqNv0j+aJoYOcVlvLVsH+uSC6goyjJExVZOzMzZeEd1cLH1Bu6/rBfd2oTi10L7njXuj83uYNeRLF5ZtIPEXCOsPD2RzPnP4ukfQsyMV10moYQLPDm1B4P06ttVnLV0K6XsImIRkRClVOHFckrTNMgotPDh2iS+2pVDxckcMufOQpUVEz1jNt7RnVxs/YCZw9tzWfcowgN8WnT/s8Z9sVgr2HAok9e/30livhFWfuKQOV0+2GipBJ8SlehW8OsJXbiqf3udp52oTbWxDNgjIj8CJZWBSqnfNZhXGrfnaHYRr3y/mxWJhdiL88mcNwu7pYCYm1/Bp3UXF1tv4DdjOzFtWIdmtZmRpnlhsztYfeAEf/thNwcrRSUjiaz5z+DpG2iKSlSVfXwQ3D+uF1f3b6fHCk+jNsKy2DycUTUZaloGB9LyeG3JPtYcLsJeUmCIyslcoqe/jE/b7i62IcB9Yztx2+jOuvBp3BKb3UFRqZVV+zKYvXAfBeYmXZWiIr6BxMx81WW6fP8oT35zZR9Gd2/dYqcUn43afCOh5vIuVYjI/zWQPxo3J6e4jHdWHjREpbSIzPnPUFGYSfT0F/GN7eliG+cPf5zSmyv6tNz5/Br3pnLtr7UJJ5j97X4q+/utmYcNUfH2o/XMObQKOSUq9w1vz/QRHYiPDNLdX2egNt/KHTWE3VkfiYvIRBFJFJEkEXmyhusiIn83r+8WkYG1jaupfwpLrfzrx0S+S8jFXlZM1vxnqchPJ+rGZ/Ft38fFtk+MF09oUdG4OaXWCn45lM3bPzqLSrL5YK+f0VIJOTUoP7pzIH+Y3IuuMSFaVM7C2ZbNnwn8CugoIoucLgUBuXVN2Jxx9g4wAUgFtojIIqVUgpPZJIyHMbsCw4B/AcNqGVdTj6TmFfPR2mT+sykVR3kJWQuexZpzjOgbnsUvfoCLbbQPPDSuJ0M6RWlR0bg1W5Ozef37PVVP1FuzksmcNwvx8iXmV6+6PNjbt7UXj1zZW+fpWnC2b2g9cAKIBN50Cj8J7K6HtIcCSUqpZAARmQdMBZzFYSrwqVJKARtFJFRE2gDxtYirqScKS6189FMy8zel4Ci3kLXgeayZR4i6/mn8Og1ysfUEbh3VkUviI/VzKhq3xWKtYPnuFOYsSiDL3KXLmnXk1BJEp60W0TtK+N24nvSJ1c+p1IazLZt/DDgGjGigtNsBKU7nqRitknPZtKtlXE09YLM7WJOQztwNKRRby8j68kXKTxwk6ron8e8ytJr9rUPaMalfOz2l+CIgIvcD9wPExbW8FXQvFIu1gnWJmbyxxElUso8aLRVPL0NUwtpU2XcKheemDqKvXii11jTmtyQ1hJ0+2+xMNrWJa9xA5H4R2SoiW7Ozs8/TxZaNze4gITWPv/64j2JbGVlfvUR52n4ir3kc/24jq9lf3iWQmSPi9aDmRUIp9Z5SarBSanBUVNS5I2iw2R1sTs7mL0t3kmYxwozFUp3WtXNagqhva09mTRnAwI66W/d8aMxvKhVwXu8jFkivpY13LeICRuED3gMYPHiwniZ9Huw+lsNrS/aQnGMl++vZlB/fQ8SURwjoObqabb82Ptw9uhtxkYFaVDRuSU5xGSsTMvhwzQEOmvsJW3OOG6Li4WksQRTersr+1oFtmDY0jl7tw3WePk8aU1i2AF1FpCOQBszAmCzgzCLgIXMMZRhQqJQ6ISLZtYiruUAs1gpW7Unl5YX7yLDYyP5mDmVHdxAx+fcE9r6imv2wWH/uH9uNIbpWp3FTCkut/Lgnnc9+OUhinrH2ly0nhcx5TyMixMyYUyUqHsCknhE8dFUPIgJ9tahcAGebFbaHszwIqZTqV5eElVIVIvIQsAxjzPdDpdQ+EXnQvP4usASYDCRhLNd/19ni1sUfjYHFWsHCLUf5yw+JZJVVkL3oT5QmbyX8qocI7Ft9ybipvaN4cFxXuujplxo3ZuexXL7adoR9Oaao5KaQMe8pAKP7K+LU1sGTukfy6yu66FUi6sDZqpdTzNffmq+Vm3vdgvEnX2eUUkswxMM57F2n98op/XPG1dQNm93B99uOMee7RIocdnK+e4PSQxsJn/AgQQMmVrOf3i+GJ67tQ2SgbyN4q9HUjpziMr7YfIytqWUA2HJTyZz7NChofdoK3KM7BvGb8V3p1ja0kbxtHpxrVhgicqlS6lKnS0+KyC/ASw3tnObiYbFWsPFQJq8vPWCIyvd/wZL4C2Fj7yVo4JRq9r+6pDW/m9hLi4rGLalcpmVvaj5/XrqXPZnG9C9jr6CnUcphjKlEnhKVQe19eXXaIGJC/HTru47UpkM8QERGKaV+BhCRkRgbAGqaCTa7g4S0At5cuovscge5S/+OZf9aQsfcSfCQ66rZD2jjw/3juhMR6HPxndVozoHN7iCrqJTtR/L4+497OJRv9Ojb8tLInPsUymEnZsZsvCNPTdHu38aX313Rg9hw/ddWH9RGWO4BPjT3ugcoAO5uMI80F52E1Dwen7uJ5EIHeT/8g5K9KwkZfSshw26qZhvhCbeM6Ey7MH9dq9O4JUWlVo5kF/Hp+qRTopKfTubcp80N6ObgHRVfZd/GF+65rAtDuuj9VOqLcwqLUmob0F9EggHR+7I0LzYePMGDH28n367I+/HfFO9eTsjIGYSOnFHNNsoT7h3fhSv7ttOionFb9qXl8+7qRLakGkPBtvwTpqjYjJaKs6j4w52ju3J5jzZ6RmM9Ups9732AGzGWUWklYjybqJTSYyxNnG+2HmXWl/soUYr8le9TvGMxwcNuImTULdVsvYCHJnXn6gGxevl7jdtyIC2Pt39IYMsJc6C+IMMQlQorMTNewTu6Y5VteCu4f0w3bhjSQefpeqY2Er0QKAS2AeUN647mYmCxVvDB2kP8ZWUySikK1nzEyW2LCBo8ldDL76Cy8lBJIDBrak9uGhqvWyoat8Rmd3DgRAGzv9t1mqg8hbKVGS0Vp11Nwz3h2et7c1Vfvfp2Q1CbbzRWKVV9rqmmSZJRaOG/6w7zzi/HASj86TOKNn9N0MCrCRt7bzVRae8HD03qxQ2DOmhR0bglNruD3cdzeOX73exIM+q+FYWZRkvFWmqISswpUYnyhD/fdgmX92h7pltq6khthGW9iPRVSu1pcG80DUpOcRmfbzjCx6aoFPwyl8IN8wnsfxVh4x+oJiqdguGtW4bTtY1++FHjviRlFvHKoh3sOFEBQEVhFhlzn0aVlxA9YzbeMZ2rbDuFwcvXD2RoZz1Q35DURlhGAXeKyBGMrjDBeHaxTk/eay4uFmsFi7Yd5+M1RykBCjd+QeHP/yOgz3jCr/otIq7C0TYQ5kwfTK/YMC0qGrclp7iMD1YmnhKVoiyj+6usmOgZs/Fp3aXKNgD43bheDO0co/N0A1MbYZnU4F5oGhSb3cHyXSm8ufQQJUDR5m8oWPsJ/r0uJ2LSw9VEJcYb3pg+kEEdo3QB1LgtGYUW/rM2ia/25QBQUZRN5tynsZcVE3Pzyy6i4gc8MK4zV/Zrr/P0RaA2wqJXBG7C2OwO1iWe4C/LEgxR2fYd+av/g3/3UURe/Qji4eliH+MPz13bR9fqNG5NRqGFd5YlsGB7JgAVRTmGqFiKDFFp063KNswTbhvdiTtGddID9ReJ2nzLizm1B4ov0BFIBHo3oF+aeqCw1MrWozm88OVOUixwcudS8lf8G7+uw4m85rFqotI1DB6f0p9RXVtrUdG4LUezi3h3TRILt2dSDlSczCFz3lPYLQXE3PwKPm27V9lGe8Ebt1zCkE7RWlQuIrV5QLKv87mIDAQeaDCPNPVCRqGFpbvTWbj9KCkWKN69nLxl7+DXeQhRU/+IeLr+9P1ivHl8ch8G6aXvNW5Mal4xH65LYsm2E5QCFSdzjZZKSQEx019yERV/4PeTezJSV5QuOuf9D6KU2i4iQxrCGU3dsdkdHMs5yRebj7Ns13GOFkPxvtXkLn0b344DibruKcTTyyVO1wh4ffogerTT+3lr3BeLtYIPViby7fYMioCK4jwy5z2NvSSf6Gkv4dOuZ5WtP3DXZR24ekCsFpVGoDZP3j/idOoBDAT0Hr9uiM3uICElj3dWH2BlYiF2oGT/OnIXv4Vvh75EXT8LaeX6hHGPSE/+PH2wFhWNW5NTXMaC9Uf4eFsGAPbifKOlUpxH9LQX8Y11FZXbRsQybah+or6xqE2LJcjpfQXGmMtXDeOOpi4czijkn6sSWX7QWM7NkrienO/+jE9sL6JueA4PL9fViPu29eKNG7WoaNybjEIL7606xNxNqQDYS/LJmPsU9pM5RE9/Ed/YXlW2oR7wwNiOXDuoA9HBfo3lcounNmMsLwKISJBxqoob3CvNeWOxVvDJL0ksO1hgnCdtInvRn/Bp253oG5/Dw9t135TLOgXy3LX96dI69OI7q9HUkr3Hc3htaQI/HzkJGKKSOXeWISrTXsA39tQcou4Rntw+sjPj+sQSEeiju8Aakdp0hfXB2D0y3DzPAe5QSu1tYN80tcRireD7HSnM3Z4FQGnyNrK/fRXvmM5ET3sBD59TW6x6AKM6BjPnpkuIDQ9sJI81mnOTlFHAGz8kOolKAZlzZ1FRlEn0TS/g275PlW1cIDx1TT8u1QP1bkFtusLeAx5RSq0GEJExZtjIhnNLU1tsdgdrDmTw3tr9AJQe3UnW16/gHdmB6Okv4eHjunHRNX2ieHh8Ny0qGremsNTKX384wNrkAgDslkIy5z1NRWEm0dOexzfu1GRVf+DRib21qLgRtdpBslJUAJRSa0REb7PmBuQUl7Fw23H+veoQWeVQdnwP2V+9jFd4O6JvfhlPX1fxmNgrnD9c1YP4qOBG8lijOTs2u4PtyVm8+WMCm4+XApWiMouKgkyibnoO3zjX1aSmD2zLhH569pc7URthSRaRZzG6wwBuBY40nEua2pCaV8zbyw8wf6fx5HFZagJZX75Iq5AYYmbMxtPPVTxuHhDF01MH6FkyGrfFZnewLiGN577YTZqxRf0pUclPJ+rG5/Dr0N8lzk19orh3fFf97JWbURuJvxuIAr42j0jgroZ0SlMzNruDolIrx3OK+cePp0SlPD2RrC+exzMowhAV/xCXeJN6hPL4lH5aVDRuTVJmEW/84CQqpUVkzn/mlKjED3Cxv6ZXBPeN7UpMiH/1m2kalbPKvIh4Al8opcZfJH80Z8Bmd3CyzIa1wsHSPWnM22GKSkYSmQuew9M/1BCVwDCXeEPjA3h0cl8iA31ruq1G4xZkFFp4fckuDuQa5/bSk2TOewZbbirRNz7rIirewK+GtOHWSzvRISpYd4G5IWf9RZRSdsAiIiFnsztfRCRcRH4UkUPma9gZ7CaKSKKIJInIk07hL4hImojsNI/J9emfO1JqraDIYuWz9cm8vSwJAGtWMlnzn8HDN5CYmbNpFRRZZd8KGNUpmD+M70F0kBYVjftyIC2Px+ZuZnWS8SSDvfQkWfOfwZabQvQNz+DXcWCVbXwIPDmpK09c048urUO1qLgptemYLAP2iMiPQElloFLqd3VI90lgpVLqNVMwngT+6GxgtpbeASYAqcAWEVmklEowTd5SSv25Dj40KfJLrHy3K5X/rj1KMWDNPkrmvGcQLz9iZsymVXC0i/2EbmFcOaAdnaJD8NP9zxo35UBaHr/9ZAOHi4xze1kxWQuexZpzjOjrn8Gv06Aq21hveOrqAQzuFKHHVNyc2q5uvLie050KjDHffwKs4TRhAYYCSUqpZAARmWfGS6CFUVhq5aM1SSzYmoYFsOWmGKLi2YqYmbPxCm3tYn9FZ39uGNaRnm2CCQ/QD4pp3JOtSRn85uNtZBl7dOEoKyZr/rNYs48Sff0s/DoPrrINAO4a35U+7cMI1mOFbk9tnrz/pAHSjVFKnTDvf0JEomuwaQekOJ2nAsOczh8SkduBrcCjSqn8BvCz0ckpLuOLzSl8tjWNCsCWl0bmvFkgEDNjDl5hrvt2D27nwyMT+9M5JljX6po5InI/cD9AXFxcI3tzfuw8ksWDH20jx26cO8pLyFzwLNasI0TdMAu/zqfWufXDWKblqr7tiA721RWlJsAZfyERmSoiv3U63yQiyeZx07luLCIrRGRvDcfUWvomNYRVbjr2L6AzMAA4Abx5Fj/uF5GtIrI1O7tprZ1ZWGplzjc7+dPyg4aoFGSQOW8WymE3RCUi1sX+0g7+vHzjIPq2D9ei0gJQSr2nlBqslBocFRXV2O7UmtS8Yp5csMVVVOY/hzXzCFHXP4W/k6j4AK9O78O9Y7oRGxagRaWJcLZ/nyeAGU7nPsAQjFbpR8CXZ7vx2WaSiUimiLQxWyttgKwazFKB9k7nsUC6ee9Mp3u9D3x/Fj/ew1gpgMGDBzeZ3TBzisuY8+1uvt5nTJOpKMwic+7TKFs5MTPn4B3pWkMdEe/HM9deQpcY/fCjxn05ml3EM19t54DZv+Aot5C54DmsmYeJuu4p/LsMc7F/Zkp3rhvYoRE81dSFs8m/t1LKuSvqZ6VUrlLqOIa41IVFwB3m+zuAhTXYbAG6ikhHEfHGELlFAKYYVXI90GzWLbPZHRzNOck7yw7w9V6jhVVRlEPmvKdR5SVE3/wy3tEdXeL0ivLioSt60iVGT73UuC9JGQU8981Ofj5qzAFylFvIWvAc1owkoqb+Ef+urqIyo38MNw6NbwRPNXXlbC0WlynASqmHnE7r2u5+DVggIvcAx4FpACLSFvhAKTVZKVUhIg8BywBP4EOl1D4z/usiMgCja+wozWRHS5vdwfGcYj7fkMz8LWmA02ZGliJiZryCT+suLnEGxfrzu3HdGNpF71GvcV8yCi38fUUi65KNBSUd5Rayvnie8oxDhqh0G+Fif03vCH4/uZfu0m2inO1X2yQi9yml3ncOFJEHgM11SVQplQuMqyE8HZjsdL4EWFKD3W11Sd9dScsr4X/rDzNvUzoWjNVcs+bNOrVDXptuLvbxwfDs1b3pHRepRUXjtiRlFPD8wp38csSppfLFC5SnJxI59Y/4d3Ndz/bK7qHMurYfrfUT9U2WswnLH4BvReRXwHYzbBDGWMt1DexXi8Jmd5BbXMa7qxKrnqi3WwqN5SyKsqrtkAfQI9KDWdf0Z0DHmibUaTTuwd7jObzy3R42plgAcFhLyfryRcrTDxB57RMEdL/UxX5Cl2B+O66nFpUmzhmFRSmVBYwUkbFA5W46i5VSqy6KZy0Em91BVlEpczceOyUqpSfJnP+ssUbSTc+77DsB0CEAHpvcj0FaVDRuTGGplT/9sM9JVMoMUUnbT+Q1jxPQY5SL/Y19o7j10s7EhmtRaerU5jmWVYAWkwbiWHYRS/dk8o+1xoLRjvISshY8hy33ONE1rObaLRyenTqQQR2jdP+zxm3JKS7jH8sT+CnZWKbFYS0j66sXKU9NIHLKowT0HF1l6wM8fEU8Vw1oT7Cfl34Ashmg/5kakdS8Yt5bdZBVicbsr6qpl5UPiTmtkQQwumMAj17ZmwEdm84zC5qWx97jOfx15SFWJOYB4LCVkfXVS5Sn7CNyyiME9Lq8yjbEEx6f0pPJ/WJp5QF+3q30eGEzQAtLI5FTXMaHa5L4dnc2Viq7CV4wp14+6fKQWCtgcq9IfjWiA73jIhrNZ43mXOw8ksVjc7eQZK795bCVkf3VS5Sn7CXi6j8Q0GtMlW0wcM+YTtwwKE63vpsZ+tdsBHKKy/jT97v4YmcO4FSjSzMGNE+fenlp52CmD4+jXwc9+0vjnhSWWtmTkseLC7c5iUo52V+9QtmxPURMeYTA3le4xLlucFtuGNRei0ozRP+iFxGLtYLE9HzeX5fIkoRCAFSFleyvZ1N+fA+R1zxabUBzVIcAnprch86tQ7SoaNySwlIrq/am85+f9nPI3E/FYSsn++tXKDu2i4irf19NVG4d2JrfTOiuZ381U7SwXCQs1gr2HM9lwabjTqJiI/ubOZQd3UnE5N+7dBMATOkRzjPX99eFT+PW/LA7lY/WJXIg1wGYlaVvZlfl68A+ro+s3TMslt9M6E6E3nyu2aKF5SJgsVawMuEE8zYe4ZejxpPHym4je+FrlCZvJfyqhwjs61r47hzWjocm9NA7P2rcmqSMAt5eup/UMuNcVVjJ+no2ZUd2EDHpdy75WoA7h8Vy/7hueuZXM0cLSwOTU1zGL4eyeXvZbpIKjDDlsJOz6A1KkzYRPuHXBA2Y6BJnTMdAbhnZUYuKxq05kJbHo59vdBIVswV+ZBvhE39HYL8JLvYPjorj5uHxeo+gFoAWlgbEYq1gQ1I2/1mX4Coq37+J5eB6wsbeR9DAq13ijIj158FxPYmPDLr4Dms0teRodhFPzNvMvlxjwXBVYSP72zlVLfCg/le62D88uiM3j+hAbHhd16/VNAW0sDQgu47l8M8Ve9ifYxY+h53cJX/Fsn8doWPuIniI69Y0Q9r68eCEHvSLC9c1Oo1bYrM7SM0v4eXvd7M729hQRVXYyF74KqWHtxiicloL/OHL47nrss4E+Xo1hsuaRkALSwORmlfMX1clnBIV5SBv2TuU7FtN6OjbCBl2o4v9wDa+PDq5N/3i9H7eGvfEZneQlm/h683HWZVoTkCpHCtM2kz4lb9xERUv4LEJnblpWDxBvl66stSC0P9gDUBGoYXPNxxh05FSAJRS5C3/F8W7lxMyciYhI292sb++TyR3X96VHm1DdeHTuC25xeX8sDOFT9YdBSpF5U+nxgovqVqYHAH+ML4Lt43urCtKLRD9i9cjNruDA+n5vLv6ICsTjOUslFLkr3yP4p1LCR5+EyGjfuUS56ru4fzxmr56SrHGrckpLuPdlYl8tjmNCkDZK8he9DqlhzYSNv6BamOFNw+MZvrwDlpUWij6V68nbHYHhzOLeHP5ftYcMrsJlKJgzUec3PYdQUOuI/SyOxCRqjiD43x4fJJeIlzj3uQUl/H3Jfv4dHsGYIhKzqLXKT24gbDxDxA86BoX+yu7hfH7q3rrWY0tGC0s9cSx7JP8c1Wiq6j89F+KNn9N0MAphF1xj4uojO0SyhOTetKldWgjeazRnJuMQgsvfbODJQcKAFNUvnvDmNU47j4XUfEApvSK5IkpvXVlqYWjhaWO2OwO0vKKeevHBBbvy6sKL1w/j6INCwgcMJGw8Q+4iMqNAyK5fWQXerQLbwyXNZpakVFo4a9LEk6JSuVU+cRfCBt7L8GDT81q9ADuHBrL9GHtiQ0PbByHNW6DFpY6YLM7yCsp551lB1xFZcMCCn/+HwF9xxN+5W+qRMUHGNMzlFuGd6Zr65BG8lqjOTcZhRae+2Y7yw+YLfBKUTnwE2FX3EPwkOuqbH2AmYPacc8VXYgO9mschzVuhRaWC8Rmd5CYns/3O9P5Ym92VXjR5q8pWPcpAb2vIGLiw4gYs7y8gF8NacNVA2Lp0TZUD2pq3BKLtYKEtALmLN7B9lQrUCkqfzGfv7qb4KHXu8S5bXh7br00nuhgPz2rUQNoYbkgbHYH25KzeHP5HrakWKvCi7Z9R/7qD/HvMZqIyb9HPDwB8ATuHtme20d3ITrYVxc+jVtSWGplf3ohf/lht4uo5C5+C8v+tYSOuZOQYTe4xLm5fxQPju+mB+o1LmhhuQBWJqQx63+7yXUKO7ljCfkr/o1ftxFETnm0SlQCgCmXtGbmiHgtKhq3xGZ3UFRqZfuxfD5ctY/NaeXAqZUiShLWEHr5HYQMu8kl3s39Y3j+xgG69a2phs4R58mBtDxe/c5VVIp3Lydv+T/x6zyEqGufQDxPfa1T+kXz67FdiY8KvvjOajTnwGZ3cLLMRlZRGZ+tP8QGZ1FZ+jdjpYjLbidk+DSXeDf1i+bxa/poUdHUiM4VtcBmd1BqrSDfYuWfqw5yrOjUteK9q8hd+ja+HQcRdd3TiOep9ZBmXhLD/03spadeatyWolIrWYWlfPzzYdYeNrd0UA5yl75Nyd5VhIy+lZAR013iXN4liCev7au7vzRnpFH6ZUQkXER+FJFD5mvYGew+FJEsEdl7IfHrA4u1gvR8C8dzS/huRxpr951qq5QkrCV3yV/x7dCPqOufRlqdEpW7h7Xn0av7aFHRuC3G2l8l/Hwohx92ZAKVovJ3SvauIGTULYSOnOESp1drL34/vqcWFc1ZaawO/yeBlUqprsBK87wmPgYm1hBe2/h1wmZ3kF5g4Wj2SeZvOsY3W5IoNK+VJP5Czvdv4hPbi6gbn8XDy6cq3ox+rfm/iXqTLo17U2qtYPX+LOZuOEgh5kKpP/yDkj0rCLl0JqGXznSxjwuA+0Z3p0/7iMZxWNNkaCxhmQp8Yr7/BLiuJiOl1Dogr4ZLtYpfF2x2B+n5JSSkFbB8XwZbj2aQZaqK5dAmcha9jk/bHkTf9DweXqcEZErvcO4Z14UQvUOepoERkftFZKuIbM3Ozj53BCcs1gpWH8hk7vpkjhaeEhVjodQZhFzquqZd90hPnrymL2N7tdETUDTnpLHGWGKUUicAlFInRCS6oeKLyP3A/QBxcXG1unnlg49Hc0pYsS+d7cm5pFlAAaWHt5D97at4x3QhetoLeHifeiDs6l7h3DO6q96kS3NRUEq9B7wHMHjwYFXbeIWlVlbvP8E/V+0lo6xyS4d/GqIy4mZCRt3i8lDvbUPaMnVYBzpHB+vBek2taLBcIiIrgNY1XJrVUGnWxIUUvtzicpIyi1i5N52Ve3MpMcNLj+wg65s5eEd1IGb6i3j4GOMnMf5wRddo7h3bjQ6RQbpGp3FbbHYHy/akMm/DUQ7mOG3psOsHgkdMJ2T0rYgI/sCwbqE8MbEXXWJCdJ7WnBcNJixKqfFnuiYimSLSxmxttAGyzvP2dY1/Rmx2Bwnp+Szbm87qvZlVolJ2fDfZX7+MV0Qs0Te/godvIBE+0DbUi5uGduaqPm30QL3Gbal8VmV9Uhb/WrWflAJTVH58t2pLh9DRtyEieAI3DGrDnaM76UVSNRdEY7VrFwF3AK+ZrwsvcvwzkpZXzM+JWWxLyqLQmNJPWeo+sr58iVahrYm5+RU8/YII9YSxPdswMD6Myf3b6TEVjdtSWGrlaHYxe9Ly+XjtAY4UmPsErfg3xTsWEzzsxqotHTyBAe19eejKHrqipLlgGktYXgMWiMg9wHFgGoCItAU+UEpNNs/nAmOASBFJBZ5XSv3nTPEvBJvdQW5xGTklVmy2CjYn57E3NZ8ci6IcKE87QNYXL+AZFEnMjNl4+ofgBwzsEsrVl7ShR+sQLSoat6Ww1Mr2IzmsP5jDsn0pHD95avO5k9u/J3joDYReficiQgDQNzaA347rrkVFUycaRViUUrnAuBrC04HJTuczT7c5W/zzxWZ3kFVUSkZhGSVlFew8nsOSHSmk5tuxAOUnDpH5xfN4BoQaohJgPC7TPsyTa/u0o2t0MBF6SrHGTbHZHexNyWNVQjpL9mSSW14pKu+f2nxuzF1VA/WdY7yZNrwDvWIb7LEwTQuhRU/xKLVWkH2ynEMZRWw+ls3Ww9mkFYEdsGYmk7XgWTx9A4mZMYdWQREIEB8Mt1/amdE9WxPs560HNTVuy97UPN5fc4hNyUWUYorKqg84uW0RQYOnumw+1zkYbh/VjeGdIwnWLXBNHWnZwmJzsD+tgNUHMklKzyP9pCkq2UfJnP8M4u1HzMw5tAqOIsQTerYL4IYh8UzpH6unXWrcmtS8Yt5fm8RmJ1EpWP0hJ7cuJGjQNYSNvbdKVDqGwHUDOzO8c4Re+l5TL7Tof8eiUis7j+dxOLuAzJNQAdhyUsic9wzi6UXMjDkEhMQQ5A3je8VwZd+2DOoUqUVF4/Z8tfkYPyXkYsEUlTUfUbTlG2Ob7HH3V4lKbCDcNrIbNw7toMcKNfVGi/6HzC4qIS2/lLyTDsoAW14amfOeRkRoPWM2YWFtCAiAfu0juHZQewZ0iNCionF7MgotLN6dwklMUVn7CUWbvybwkqurtsn2BwZ3CuDGwR2Z0KedzteaeqVF56bjeWXYlQMvD6jIP0Hm3KdRykHMzFfxjojFsxXEhwcwfXAcfWLDdOHTNAkOZhRRXGbHVymy131C0aYvCbxkMuETHqya/TWhdwTXDIxjsG6BaxqAFp2j8i3lBPt44VGaTcb8p8FuI2bmHLwj4/AH2oR6cXX/OHq2C8VPFz5NE6GorAJ/H0/Sd60jb+OXhA6YRPiEB7Gb3V9TB7bmtlGd6RAZqEVF0yC06Fzl6+VFmB/s/WgWjvJSet81GxUcj2cr6NTal8u6tuGKXjF650dNkyLYtxVx0YFYBwxHVfyBwJ5XUI4H3sCg9gHcN7YbHfV6dpoGpEULS1ykH8VlEVx+0914RMTj36YLdiA62Icx3WMY26uNXvpe0+To1jqYfu3CKbE6CBw9CaujAlsFxIYHctvIeGLDAhrbRU0zp0ULS/eYEEpLHVz/qzsoLbVRVGZFiQd92gYzqnuMFhVNk6R1iD83DY4jwMuLPWl5WG0OOkQEMqJrJEM7R+nWt6bBadHCEhPsR5/2isgCCyfL7XgKRIf40ikqSPc9a5o0seGB3HlZZ0qtHahwQCsP8PNupUVFc1Fo0f+eXp4etAvzJzzAWxc+TbPDy9MDL/1siqYRaNHCArrwaTQaTX2jq+YajUajqVdafItFo2kObNu2LUdEjtXDrSKBnHq4j06/eaXf4XxuIkrVeqvsJo+IZAO68On0G8qHDkqpqMZwpr4Qka1KqcE6fZ1+XWhRLZb6KvTN5cfX6TdtHzQad0WPsWg0Go2mXtHCotFonHlPp6/TrytaWC6MZvHj6/TrhDv4UO8opRr1c+n0m0f6LWrwXqPRaDQNj26xaDQtCBEJF5EfReSQ+Rp2BrsPRSRLRPZeSPx68mGiiCSKSJKIPOkU/oKIpInITvOYXIs0a7yX03URkb+b13eLyMDaxj2Pz10XH46KyB7z825toPR7iMgGESkXkcfOJ241lFL6qOEAwoEfgUPma9gZ7D4EsoC9FxK/HtKfCCQCScCTTuEvAGnATvOYXMt0a7yf03UB/m5e3w0MrG3ci5D+UWCP+Xm3NlD6PYANQDnw2PnEdYcDeL3SN+BJ4E9nsLsMGFhDvq5V/Lr6AHgCh4FOgDewC+jllLcfO4/0zngvJ5vJwFIzfw0HNtU2bkP74JS3I+vwu9cm/WhgCDDb+fu9kO+g0TO6ux6NXQAvduE7j8zXYAWwpRW+RsrXiUAb830bIPEstvE15Otax6+LD8AIYJnT+VPAUxeSt892L6ewfwMzT/exNnEb2od6ytu1/hynf78X8h3orrAzMxX4xHz/CXBdTUZKqXVA3oXGr2P6Q4EkpVSyUsoKzDPjXSi1ud9U4FNlsBEIFZE29eRLXdKvD86ZvlIqSym1BbBdgO/uQIxS6gSA+Rp9kePX9h7tgBSn81QzrJKHzO6iD2vRHXeue53NpjZxa0NdfABQwHIR2SYi9zdQ+vUWVwvLmWnsAnixC19t7nc2m/oogC2q8DUUIrJCRPbWcFw0oasHH6SGsMqZRv8COgMDgBPAm3W417lsahO3NtTFB4BLlVIDgUnAb0XksgZIv97itqgn709HRFYArWu4NKuJpH+uwveyef4yRuG7uw73O5dNfRTA+ih86SISDfwoIgfMFmV9pt8QcesVpdT4M10TkUwRaaOUOmG29LLO8/a1il8PPqQC7Z3OY4F0896ZTvd6H/j+HD6f8V61sPGuRdzaUBcfUEpVvmaJyDcYLeTzydu1Sb/e4rboFotSarxSqk8Nx0LMAgRQlwJ4tvj1kP5ZC59Syq6UcgDvY2TEc1GXzF+XjFsf6bsUPqCy8NV3+g0R92KyCLjDfH8HsPAix6/tPbYAXUWko4h4AzPMeJXloZLrgb01xK/VvU7z6XZzZtZwoNDsKahN3NpwwT6ISICIBAGISABwZS0+84WkX39xL3QwqLkfwBu4Dp6/fhbbeKoPctY6/oWmj9HiTAY6cmrAuLd5rY2T3R+AebVI84z3c7K5GtfB8821jdvA6QcAQU7v1wMT6zt9J9sXcB3grPPnv0j5OgJYiTHbcCUQboa3BZY42c3F6GayYYjmPWeL30A+TAYOYkyKmOUU/l+M2X+7Mf7g2tQizWr3Ah4EHjTfC/COeX0PMPhcflzA574gHzAmhOwyj30X6kMt0m9t/tZFQIH5PvhCvoNGz+juejR2AWyMwleXzH8hma8+02+KhU8f+miuh37yXqPRaDT1SoseY9FoNBpN/aOFRaPRaDT1ihYWjUaj0dQrWlg0Go1GU69oYdFoNG6HiNjNlXz3isgXIuJfh3t9LCI3me8/EJFeZ7EdIyIjnc4fFJHbLzTtlooWliaMLnyaZkypUmqAUqoPYMWY8l2FiHheyE2VUvcqpRLOYjIGqMrbSql3lVKfXkhaLRktLE0bXfg0LYGfgC5mhWa1iHwO7BERTxF5Q0S2mGviPQBV+5r8Q0QSRGQxTuvsicgaERlsvp8oIttFZJeIrBSReIwy9AezwjZajL1fHjPtB4jIRjOtb8Rcf8+8559EZLOIHBSR0Rf363E/tLA0H3Th0zQ7RKQVxsKLe8ygoRgPn/YC7sFY9mQIxlYG94lIR4xlXroDfYH7cKoEOd03CmOpoxuVUv2BaUqpo8C7wFtmhe2n06J9CvxRKdXP9Od5p2utlFJDgd+fFt4iadGLUDYXnArfD2bQUKCPUuqIGKv8FiqlhoiID/CLiCwHLuFU4YsBEjA2LXO+b2Xhu8y8V7hSKk9E3gWKlVJ/Nu3GOUX7FHhYKbVWRF7CKGS/N6+1UkoNFWPHv+eBMy5UqGnx+InITvP9T8B/MARis1LqiBl+JdCvsgsXCAG6YuyRNFcpZQfSRWRVDfcfDqyrvJdSqqatL6oQkRAgVCm11gz6BPjCyeRr83UbxhJPLRotLE0bXfg0zZVSpdQA5wARAShxDsKoxCw7zW4y515ZWmphcz6Um6929P+q7gpr4lSOsQxQSj2sjA2moObCV2nXUSm13LymC5+mKbMM+LWIeAGISDcxVv9dB8wwu4HbAFfUEHcDcLnZdYaIhJvhJ4Gg042VUoVAvlMX7m3A2tPtNAZaWJo/uvBpmisfYHThbheRvRhb+7bC2DLhEMY4yL+oIQ8qpbKB+4GvRWQXMN+89B1wfeX44WnR7gDeEJHdGJuMvVTvn6iZoBehbMKISLFSKvC0sDEYy7lPMc89gFeAazBaINkY2xwXAW8DYzFW5AX4TCn1pYisMe+xVUQmAXMwKiFZSqkJItIN+BJwAA8D4zDHXERkAMYAqD/GMvJ3KaXyT7tnJLBVKRVf71+KRqNpdLSwaDQajaZe0V1hGo1Go6lXtLBoNBqNpl7RwqLRaDSaekULi0aj0WjqFS0sGo1Go6lXtLBoNBqNpl7RwqLRaDSaekULi0aj0Wjqlf8H5iRwJ3wn6l4AAAAASUVORK5CYII=",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1162,8 +1018,8 @@
     "    ax.scatter(gt, pred, alpha=0.05)\n",
     "    ax.plot([np.min(gt), np.max(gt)], [np.min(pred), np.max(pred)], c=\"k\")\n",
     "    ax.set_title(f\"{coordinate}-coordinates\")\n",
-    "    ax.set_xlabel(\"Prediction\")\n",
-    "    ax.set_ylabel(\"Ground truth\")\n",
+    "    ax.set_xlabel(\"Ground truth\")\n",
+    "    ax.set_ylabel(\"Prediction\")\n",
     "    ax.set_aspect(\"equal\")\n",
     "    ax.label_outer()\n",
     "plt.show()"
@@ -1173,7 +1029,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... as well as the test dataset."
+    "Then you do the same for the test set."
    ]
   },
   {
@@ -1190,14 +1046,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1215,8 +1069,8 @@
     "    ax.scatter(gt, pred, alpha=0.05)\n",
     "    ax.plot([np.min(gt), np.max(gt)], [np.min(pred), np.max(pred)], c=\"k\")\n",
     "    ax.set_title(f\"{coordinate}-coordinates\")\n",
-    "    ax.set_xlabel(\"Prediction\")\n",
-    "    ax.set_ylabel(\"Ground truth\")\n",
+    "    ax.set_xlabel(\"Ground truth\")\n",
+    "    ax.set_ylabel(\"Prediction\")\n",
     "    ax.set_aspect(\"equal\")\n",
     "    ax.label_outer()\n",
     "plt.show()"
@@ -1231,34 +1085,53 @@
    "source": [
     "### 5.3. Prediction vs Property Value\n",
     "\n",
-    "We show the the pixel error as a function of some properties."
+    "You can also look at how the pixel error depends on the properties of the simulated particle."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We calculate different properties and pixel error for each datapoint ..."
+    "For a fresh set of simulated particles, you record each particle's properties and measure the network's pixel error on that same image. You read each property directly from the object that defines it, by calling `particle.position()`, `noise.snr()`, and so on, right after resolving the image."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
-    "properties = [\"position\", \"z\", \"snr\", \"gradient\", \"refractive_index\"]\n",
-    "snr = [\n",
-    "    image.get_property(\"snr\") for image in test_sim_dataloader.dataset.imges_\n",
-    "]\n",
+    "properties = [\"position\", \"z\", \"refractive_index\", \"snr\", \"gradient\"]\n",
     "\n",
+    "property_values = []\n",
     "preds, gts = [], []\n",
-    "for image, position in iter(test_sim_dataloader):\n",
-    "    preds.append(cnn_sim_regressor(image))\n",
-    "    gts.append(position)\n",
-    "preds = torch.cat(preds, dim=0).detach().numpy()\n",
-    "gts = torch.cat(gts, dim=0).numpy()\n",
     "\n",
+    "for _ in range(1000):\n",
+    "    image, raw_position = combined_pip.update().resolve()\n",
+    "\n",
+    "    property_values.append(\n",
+    "        {\n",
+    "            \"position\": particle.position(),\n",
+    "            \"z\": particle.z().magnitude,\n",
+    "            \"refractive_index\": particle.refractive_index(),\n",
+    "            \"snr\": noise.snr(),\n",
+    "            \"gradient\": gradient.gradient(),\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "    position = raw_position.copy()\n",
+    "    if flip_lr.augment():\n",
+    "        position[1] = image_size - 1 - position[1]\n",
+    "    if flip_ud.augment():\n",
+    "        position[0] = image_size - 1 - position[0]\n",
+    "    if flip_diagonal.augment():\n",
+    "        position = position[::-1]\n",
+    "\n",
+    "    im = torch.tensor(image).float().permute(2, 0, 1)\n",
+    "    preds.append(cnn_sim_regressor(im.unsqueeze(0))[0].detach().numpy())\n",
+    "    gts.append(position[[1, 0]] / image_size - 0.5)\n",
+    "\n",
+    "preds, gts = np.array(preds), np.array(gts)\n",
     "test_error = np.mean(np.abs(preds - gts), axis=-1) * image_size"
    ]
   },
@@ -1266,37 +1139,26 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and define the function to visualize the relationship."
+    "You then define a function that scatters the pixel error against a chosen property."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
     "def error_vs_property(property_name):\n",
-    "    property_values = np.array(\n",
-    "        [\n",
-    "            image.get_property(property_name)\n",
-    "            for image in test_sim_dataloader.dataset.imges_\n",
-    "        ]\n",
-    "    )\n",
-    "    if property_values.ndim == 1:\n",
-    "        property_values = np.expand_dims(property_values, axis=-1)\n",
-    "\n",
-    "    for col in range(property_values.shape[1]):\n",
-    "        values = property_values[:, col]\n",
+    "    values = np.array([sample[property_name] for sample in property_values])\n",
+    "    if values.ndim == 1:\n",
+    "        values = np.expand_dims(values, axis=-1)\n",
     "\n",
-    "        plt.subplot(1, property_values.shape[1], col + 1)\n",
-    "\n",
-    "        plt.scatter(values, test_error, alpha=0.1)\n",
-    "        plt.xlim([np.min(values), np.max(values)])\n",
-    "        plt.ylim([np.min(test_error), np.max(test_error)])\n",
+    "    for col in range(values.shape[1]):\n",
+    "        plt.subplot(1, values.shape[1], col + 1)\n",
+    "        plt.scatter(values[:, col], test_error, alpha=0.1)\n",
     "        plt.yscale(\"log\")\n",
     "        plt.ylabel(\"Pixel error\")\n",
     "        plt.xlabel(\"{0}[{1}]\".format(property_name, col))\n",
-    "\n",
     "    plt.show()"
    ]
   },
@@ -1304,7 +1166,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We first to see the relationship between the x,y,z position and pixel error ..."
+    "You first look at how the error varies with the position in the camera plane and along the axis normal to it (z)."
    ]
   },
   {
@@ -1312,33 +1174,46 @@
    "execution_count": 25,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\xgrmir\\AppData\\Local\\Temp\\ipykernel_16640\\2082567267.py:2: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
+      "  values = np.array([sample[property_name] for sample in property_values])\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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bf28rZVE05JVEa01eSbKq4b3t7pV/fzfy6McBd8cpO72INPDa+/vNHh7rdZ12uzTt85XK0ChFL/ZeTiHe2K0/8l12ehFK2ucntWZ/EBN6Lp4rWFWS82XZ+jzkqHaGajfyiMATLMrmSzfSfhTgCkEtNUeznEXRvPQM4Nl3IfJdOqHH7VGKwc4vYt/FFYJHF9kLN8dXNYf4soriRRv2s+v9RcKVL3PgvOzv+GP2rVvDxC6hKwojvlWHxzqMscPF/UGyEYB72fgmB6XrRbQomk2L5CmtmbaaeHZBfHq2JI08hCMQQuB7DoHrcrasXtkA/UUH2hqaeXuc8r3tDqM0JPQcIt9hlAbM85pPTldPKbr+/OGEolZfyIhelNkNkmDzwo47IRerio+OFpvPqaTCcxzyWpHXCt91CDyHWV6ThD4/uz3AdWGa17gu/Ozu6Mpoq02/2/28VSf1OuN7MzMP33W4OYg2Lb/dfsx7252X+8dCcGsY24rPwP4w4R/c7LPbj3Gd9bxKMs9rGmXoxz6uI3gy/bx6sEKKEe/vdJ+7ka4rwayWjNKA0HfQGhZl/dKtnHW78JPTJYftuyEESKUJXCuvIoRAOII08l64OX4TZlHP27BNC/p4UQVw1QrhZX/HVfet9XWcLkrOlhXDNMCo5kqokrdyYJ6GHv+197df6u8+O3AFXivs7vL3XoY++q7D2bJE6nCzQR/OiucuiFUp2etFfHL2+SadBC5Vo6+cWb0IBvhVZLDQc4gCD18bKmlIQh+tNcfzskVOGYRwyCpJGvpktWx9A55PNPyqe7TIKy7ymuNFhRCGW8OEUXuwhJ6L62ChuaHHOzvdP3qTWP9+Cx0uaZSDNoatToh4QwNz1xHsD1PubX++Fmup8V/iatZSMnt9az1a9hSPJxnD2KdqFI3UXCxL+kmAAYapXUePJxmny5Lbw4RGmeeCNGC9AdpqTRmY5g17/YjdXkRefzkMeB3rtdiLfQ6nBUezgsB1+LPbAx6cZ3ZOY8zG1XG3F35pUveqyLsvekeex+9YVQ0GXjjg/joD8Jf5HVeBC5eN2hBHG6U5WtQsixpxxaToraw8Kqlfqt/3vCygrCWLsnntkhvPZi3d2OfWKH2KdPWi7N/3HM5WNeNOSBp4lLXmZF6x270a2urLsqCvynjGnZAk9DieF2AMWmvKRhP6Dju9yA5hgVppIt956iW/yvBUGzia5fzi8YyslASeoGw0Dy8ypllFXkvOs5KLrCYMXh3KZf37k8Cln4S4rh0ax4F75QztVYXnOF+7FfNs+8MRgmEatvMmh0leMSsaykYxTHyrJOy73GqHz9Os5vE048ms4GJV0SjF4cxK5fzi4QRtIA08lOapSvAqidf6eWeVZLsb8f29Hnv9mKNZwW4vQhlD0di1uNePcB3nteuofdk78rz3M68UyTPr7/J6f12djau06Q6nOZO8wXMcBknAjX7EolRwTRJkU5p/HTZqNw5opNpsmi8Du/s6JJ6XYaW+KPsfJoHNuF2PtOshlSGrG8Lgao/zZeVHnheR7/LedofzZcWqaKiBnV4IIsR3HGplX4bAdTaHyjpeVlfL4vwrSmlIAg9jYJ7bfvvFqiF0XW6NIrpRsJlr/LEHx+VnCYCx19qL4s+f6zc8MF+HaA/wl4GEvkjQ8vK/Xbe8zDRn3Ik4X5Y0ynCyqDhdlMxLiZKaQWJ1sXzXYatjs/3fHszZHyT0Yp9Pz1acryqS0KeopU0sAndTCb5s9l9JzapsNu0pgDhwWRb2NwReQOC534gsyjq+7B153vsphAV9XI7L6/11EQqvAhc+XVYkgbuBfHdCnztj51pV14Z4Kd2eF23gjRIvvSi/rpbO89jbp8sS+cwB9LwFcTgruDVMmOUNRWNnI77r8HiSfenh9eyGsigahunTs4Crqu0GrmBnELHTjTZD7ceTnNBzMC0vYZpljNLU2px+yUu//sxF0TDNa2Z5Q+x75HWNxlYxDrCsJXu92FYbvkvoO4zSlKySz51tPPu709Ciip497C+X82UtuVjV9OKAd7fTp5KRNxkv08J40Zp8Xhb6LDT20UXGo4ucs2XBILFQ2VUtkZe2laN5icAwKxq2OgHLQhJ1Q4wxm1ZiEbj0Ev9KlWDoOeSNondp85XakIQuCMHNQfzKuRRflviVjeLRRYbjCMK2vbyG/K5bcc++nz/c728kXJ53yI07IR8dzjhaVFSNIvRdbvRCfrg/uNK1PS9etk1nzHPQVV8jHXpLDw8bX7URvigLALtRvMxD+7oknstZi9KaJ9MCsL38Z6umy5+zhkKWjSYNPAaJzzSrEQj6sf/Ciut5G8o0r/Fd5ylC3lXUdgPP5cYg5sk05/Ek59bQDl9HiU8UeOTtkPxnd0dklfzSl/7yZ64H4mVjYbK+J3A1FiaL3VCiwOHHwx73xm32bEzbKnv6ua2f5fp3L0vJx8cLbo9SOpH31GG/LufT0KLHIt8jqyWny5K77fd8F4yunrcmy0bx0eGcW6N08/zvny45W1ZEgW1RDZIABHb2ZiwBNAk9DqaFbRE2iu1uhCMMriM4nhdIpdnuhXhCkDeKnV6EKwRSa368P7jS5j7uhDy8yChqRRy4m9lGJ3SZ5va+h57ztSWHnpdEvEgKB+y68TwHV4gNonFNNly/I8/bsCPffeEhVzaKk2WNbsEXWhtOljXvPCMP86oFHi/Hbj/mcJYjhMBzBVIZ8kbCFX1q3urD46s2wvUGXjaKVdmQN4qmUfTSgO1O9FIP7aqiaJcXsMBKjpwu7JDZdxxOlxWB+/nCfvbgWEMhG2mzmyeTjF4StJlR+MKK63kbypq3EfpXawU8/VkOt0cpp4uS43nJ7VHCu88ZWD9bETz7IleN2nxmrQyOA8rA+bIkDlyyShL7Hu/vdJgWNWnos9eLN5+3KiXTvKYT+U89N4FtYV6sKlaV5Mk0x8V+9vd2P7/Oi1X1VDnfaEPkO7gKzpY1d8ffDrG7l8lGn7cmj+c5Hx0t+OhoQdBuwAaLSuxG/gbufLGsGMQ+ndhnuxsB0A1dnsxyC5c14AiBUvZ+nCwqfnq7j1SGZSkpGmXbv17wtdSVf7Tf56PDOctCk4QundDldFE+dei9KDn6svsyy2s+aqVv7Of6PLrI2OpGL9QvCzyXnW7E8bwk8IR9PxclozT40nfkyyqAT8+WjJJgo4AAkFfyCwoIr5NZvj+IKRpFXkn7rrXzr2u0FTYLfXSRkVWSO6PkhaJva1TRelGlocsK+zB1atFCX/XQropyeDabqKVqWyYS33U3mcDFqkQmIeNGcTjNOV1WnC1LRmnIrZElP1nRN01QK+6O003rZZpVzIunjaOet6F0Iw+pwy/Md+DLK6/nfZbnCPL65Vjcz7sPjyY597ZSwMFgOJxV9GOPqlGM04jIq/Ec+zv2BzGzVcPBJN9sBGfLku1LG8FacPH++YrUd+nGdi5SNgrfsVyF43nJXj+yPhfzksNZQRK4bPciAtdB6bUSifnS5/pNhTG8VDb67JqcFzV//3BKIzW9xGe1kvzheM57O31ujRIarQmETSCmLTQ2vjQ/68Y+n51npL7HuBuglObJNOfWICbxNVrbecwHe5ZLc7ooKZuG+2crqsaKEwoh2OmG7Lfr63Cab+R2trvhUxXzz+6ONgfBNK8skKStjp/3Pj7vYLh8X8pG8eHhHM9xNhXNRVZTtjOW3gukcJLARQiHvX7EyaLgdGETtq8CKHzZQbYqJcNnEqnIt8THy//2k9Ml/dhnmH61HMxVYz2vfPYar2ce2GwKAfe2UlzH+dLKYZLVeK7Tbg8CjCHxrWT1jYHNbNcP7XmL4rJfgtYGxxGkrZzIs3GxqjCGDSM69Bw8R/Dh0YzE8+ilAf3YJ/RcGuUwz2vun2omeWMXsoHzVYkyhrvjlL1+jDGGrFabl+R4XiKAXvR0C+tFh9wa3bWOyxu7I+BwXvCHk2XL2I2fQoGt2yHH8+Ir22bP3odns6o09DhbVdwZeVi+ErjCYbcXIhwwRrDdD/nRDdtTTgOfVdmQtVyPJPDotizy9TX5LTop8T0eT3PGSUg38ikqy1ieFw2PLlasSkUn8ogDh3lR0yjNuBNwsbJooZvDeINeeZMzD6n1c7PRw5lVOr7cjjmc5ps1+YfTJXmrCeU5DmHiMi8b7p8vGXcD3tvpWIl2qemFHmnk00gL30VA1Wje2UpJW0LmrVHCBze6G9kWqa24ojGGJ9McEGx3Aj47t6oIt4fWO+RwXnK6LCkazaJsiDyXyDecLEr2+vGG1HZzmGzu8/0zvuCqeTwveDKxa6wfeZwsK4tEU5pp3mAoeWcreQoea7DDdyHEBu20KDR582IpnMvvizGCnW6E71pJoBet8eclRp+erYg9B4SgaBSisK3Red5QK41ShmHHf6Gu11qB4VUmL68CxvxWQnVDz+XOKCUOvC9lWq4HYpeZ2rO8oVJqgxYqG8Xjac7ji4x/93Cy6eNfhuxVynC2tFIdZ8uSSj3/AF8UDectHDH2XYpG8bujpSVA+VZu4mResqoaq8nVKLJGkYaeXYyxT+h5FLXaqMR2Qh+BxftPswqbJ9vB5eXfflWmqjYWdeM5zsZ8av17L3/W8SznbFVxMCuolX4pmZTnwRW3uyFZKdvrg600QGpNL/bZ60X81Tsj9nrxRj5jDXH2XQfftfOR9bxqLbgoHEE3sGQ3KTVZXdsWWC1ZZJJaSh5c5Eit8D2HXhwAlnz46anNmrUxhL77WkhmVw1t+MJ9U1rz6CJ7Ckp6OM1ZlHKzJo9mJdIYtDbM85rzVYWUtm3RSE3k29nV/iDhZ3eG3B5ZDk3ZSLJKMkp8/tEPdrnRj7jRj9nrRwgEjdJsd0P2ehGuIziaFYS+y+1RQtFopDL0ooCisYee5wo+PFrYZ+g6SK355GzF4aTg45PFcxUSnnXVfHiRcdDKrASew+9PVjw8X3GeVWhjSEP7PZ+dr1i01XclNYnvbsieYCtl33E2786z78TlNf5l79Wz8SwEXxvDNKs4npcsihrHCH7xcMKHhzOk1hhtyKqa2LcH/rO6XgKYZi+Wg3mT8VZWHs9SXb5M/fNpprZgqxNyNC+5NYwparkZZEeBa3V9smqT+U3yml8+nrW485g0bGGzVcPhrLAaVJcibyROu+GBbRUFnoM0LqM0JK8VhVKsSsm9cWoZoPPSoj18FwdbeZSNREpNEng4An603yerJPOiaZVPoy+Uui8L5Vu3pE4W9ne+yHxqjfq6f54zSgP2RgGu43A8L9nthTQvKIDXA/+juR34rxEsruNwZ5zi2OIPZWC7FyL43MMkDtyNCujJoiRwXWLfpZGaaVET+CVKG55McjzHznAcIVDa4LkOi1wxSiO2uxFVo5hkDaEruLvVwRH2PrkuPDrL6EYBH+z16IQei6Jh4X3Ob3lT4YgvEljPlnYNB57TtixrPjldsigbfnijTyf0KBrNLx/NkErTT8IWneduJNofnK++UDFfrCpu9OMvoNEuVhXTvGGWVex0ow3ooJaKQRoyTHyEENRKtwe6IlvaA6GWGq3tsB0Bk1WD7wpKpVjOJLOsZqcX2QXQDqXXsz+wrpqLosF3XbZ6YQvbdVjWCs9tNu2gyHOYtWz5NYtaaY0y0MXHcwVFrQh9i456EZhj/b5cfq8AjmYFlbRV3Ve1dKdZjSsEx4uKe2HKqBsQXHh8fLykqDW3hgl/fndE7HscTG3rdv0cG6nJG4kQVlfuTScvz8ZbeXg827n7MvXP7U64EdLzHAvxTQM7Czmel4SeJb2dLEpi32VVSX5zMKOWhti3rPA7o5Rp3uB71mchMR4n8y8eHkngM88rGqntAi4ljjBsdyOEsP4TWx3bF62U3rTSPMe2h07m1ouhkZrDeYE2hr9+d8wgCTYDaW0+Z7c++9uvwlStpCZuF+rzzKfW7av3dzp4jrPB5QOcrSr2+/EXPvt5A/+jmeUYXM7s09Dj5w8nBK5P5FueyGSV8bO7I0ByOCuoGs2jSd4ewIJxHLLIatLIBwyni4pBErLdD5msanzHECcendBjltfc20o5XpRsdQJc4aCMZcdHnmDUibgxjKml4ULWRJ5LWVvOwsE0f2OS7GuSIHzOK8gqudlwjucFgetSNhrH2FlA4Dm8s5Xym8dT5oXi9jhFK9Bas+2H+G67GRkw4nNBwuetk82fT3M6ofeF9tmsKNo/t1pls9xunGlgK9mDaY7nOlbLrM2qlbI+MTvdECHsvMR1nDZ5+xwqO82tYZgx8N5Oh7A9zOPAxRWGWtlKx3WsEKY2hnkluWksofDJtEBKSe055I397h/t9zfvzvpgXLcAL0Plwb5X2pjNPfZdB+V8ceb0bHu4VrZFl4bW9+ZsWdMJXT7Y7bLTixkktk3tu/aena8qHp5nYCAOXWLfio5+G62a38rDo5KK//L+Oa4QDNKAUew/NYNYL5STeYHnORuvgKKxpkvv73Q2G3/S9klDzyGrJdOsYrKs2RtEKA1ZrdAYQtdhnjfs9Kw/Rd0OMy/PR3qt+mxWtaiUwGlfIMhKyYNshdKCUeozbDHyx/OCWd6QVQ3aaA5mNe9sp9wdJ2gN989WDJLgpSRFXibWn7E2nxIIaqXY68ebg+jyUM8RgqP5iqoxOI6hF1pNo39wc/CFz75c0vstAzkrNYuyfgrWuVa0zSpJ2arlDlsex7gT8vOHUw5mBf3YI/YEea35dLXi3e2UH44tn8RzLNGsajT92ONsVeIrmOQV3cjDcx1uDmJUu8lOsoo4cCgqhefaCvRiVWMwDJOgRRG1B6TjvZH35nkkwTujBNdxWs6N/c3GGKLQtmHvny3pRgF7g5iDWckib4gCh3E3pB/77PUT7m3ZtV5L/VJonhchDBPf2xxudaPIG8k8b7g1SKgC++eBKyzxL2/Y7gZ8erpCa82oaysipa280MmyBCOQ2jBfVez0YppWzHGyqtvkxSUJXRzHxWjD0dwywbuhSxp7FJXi7x9MWFWS0Bf4rq1w39/tPrUZz/LampBhLQE6kU956VDYeIRkNb7jgICsVAS+4GReMivs+gWoGvUUEEAAy0JybztlnttKSyBYVg16UYItwrgxSBikAb99Mif0LcqsUvYA/v5e51vpSfRWHh4AoWsHaGeL6gsDt2c5CqeN3nAUaqk2iJDLWcQgCXj8ZGYrate2uQyGu1spZ8uaW8OYSlqtmGle4wmx6UNfJmmtZwa+Kzhfufzy8ZQbvYRSShLfp5aSW8OEk2XFva2UO+MUyPj0dMGibOiEPjcGEZHvUTaSs3nFzx9OuDNOn2IRT/OGvG5IfG8z83iZzGWdbT3PfGrdc13fv9Bz+MPpioNJSeCC7zksi4Zbo5RDm6G/UAtozSswxjAvmqeusZIabTRnq9L2xx2HbuRRKsMo9Xk8yai0JtUeceBycxTx6DxjWtgKspYaz4XzZUVeN/QTn+1OiNSacRriupb0FbgOF6uSNPQ4mOQMUhfXhTujFICzZWFZw0bQT+yr4ttn/8Zmhc/j/RxMc6sdFno0SpOGdh2dLyuEgEEMSejzoxs+292Yum2NbnVCOpcgo74rmOYNtIKE87ymUprQczdIqWcBE+tolKEX+4w7IZ+dLvn1wZzAc9jrRhSNop5X3BvHSAQ3+nE7T1GEnstP7wzpxwEPz1bEgYvSmj8cr+gnFtzgeQ5J6LHdizicFjRKcb6o6CUejy8KjFY0wqUfOKShbxnwT+bWttmBfhRQVOCEVgbkWSLgR5eRWMowySpGafgFpYWzZYUWBmHs/CNwPSSKJ5OCi1VN6Nq2172tlLNVxYPzjN1+ZNFk2ia1RkNWNzjCIXQFDvDwIiONfGLPcq7mRc0kr0kCl91exKpqWJZfJLV+VXwVfPkLun5XrKjfysPDdRxutRtAozRSf55RfRVH4Vn9pnUmv2Eml5LQE5wvS+tY5zsUlaCUCoxFxLjCMtSfLeuzSm5mBU8mBefLiq004sksp1GaXuSz04uQymzQRzvdiMBz+eH+gKNpThx6nC0rzhc1Z4uSOHCQyecop3EnpGoUJ/OCNLSba14rHj6cMEyCzQv+VUzV/WECQnDS+oXsdMMv3D+pDSfzkiS09yYNPCZZxaKoucjrjZje8xBfX4YMq6Ti14+n9OKQ2Hc5nJV8crZktxfRj3yU0XTa6+9GHnklOZ7nNFPoRZMWfhmw2ws5mhsmy4Yy0LiuaNF1gv1+TBK4yCQkrxu+t9sliTz6kc/JouRwWoCxYoSllETSVlytfPyb86J9JtYb26yoWZWSNPL4yc0evz2cU0nZtogE+/2Ik2XJ+apkq2OhsU+mxSZRAliWkllW4TuCJ9Och5McozW7/Zis9dR4d6f7lRXutGi40Y+plEIq8AXcHsbEgbVHCD2H26MOs6xiuxdt5lYIa+B2OCsw2tAJXCarGl1JHk9tK0c4sJVGHExzW1F4gh/e6LOoFGeLEq2tmrKUmgoLsi6qir2BTdxcx+G3hzOGSbjhFxlzCYnVvqursrGzmUv3+fbIEngnWYXvum0bqyLyXbQ2rKTiIqvZ60fcGaUbi4Eb/ZgPD+fUUpNVDTu9GAGEvkvdGNLQHhyVMjRS0YsCBjHMiobfHc1plOHPbw+eS2R8kXICxlBIu6c8D9b9PFTYVU3O3srDwzK2cwLXoRd7aP25m+CzJfd6UayF/J7X81y3CXqxRy/2eHiec56XnC1LilojjcFzOvxgv8d2J2QRNHiuRZ+syoZCKiLPxXMsJNUYw61RitQ2y7GyGh6VNNZDYQDvbqc8OM84pcR3Bb3Y52Bi+94Xi4qTpUW2aOHx4dGCSd7QSAXCboy92EcgeHyRYYQgapnb2vhfCaW9vLDe2e5sNodn7988t9LbGkPeKAZpQDfyabRpZ57iczhpW4k8ushII4+yksxbtM/NYfIUSssy3z08VzArGuLAZVa03x16jLsRVW0RW48uclallVmpGsXHJwsmWUUS+PRjn6xqqGrNxIE7Y9s6cByD5wh+uN/n5nN+s0XK0CK5LJky9BxOlyWjJAAtr2ZL+Iqikpr7Z6unBsrrdfrj/cHm+n1XMIwDfMe2bX3P4XDaUFQKqQ2DJGCUhMzKioNJTpZI8kZxvqp4f7vDRV5xMC3phB6esMNlsEq5lwETzwNfHExzqkYhhKDREHm29XT/LKMX+zRa00hrzvXOdoe8knxyukIa6/r39w+nhJ7DMA1YVBJtrKLAIm8YpQFpYAfy98YpN0cpDy9WLApJEnjcGaWcrkqkMpQtWrITetRS85snFtjSSwIapfnrd+wB+miSb7gfaySb5woWpWTnmTnp+tDMSkkn8jhd2uNpqxtyuiiRWjNvEZW3hrF1XzRwcxjwF3dHHE5z/uUn5+RVQyfycRCkyeeHUl7X9JOA43nF8bLAwTDLGjtfMbAoG2Z5w+E055ePZoxSn5ujlG7ksSolvz6Y0w1dPNexlZDv0Am95/LVngeXv6rJ2Vt5eNgTXqJ9l1XVMG49J+D5mlIHk5zDecGNfozbMpsfXmSbgdrnZKSA//xXB2SVZp43FsWhNDeGEfOybqGCHo8nOb85mJH4HtIYQs9lUlVsdSI+PJy31YRDKRUCh0JKFucVaewzzyxSK/AcdvsRs6xGOxZK/Nfvjvmv7l9wuiy4WDXs9hw+O10hsbOXyHVQaJQxGx+TXNqXtfE1y0oC4rns9cvx7MLSRjPJa04XJYHvoHVAN7ZcgFlZc9pWEJ4QOMIQ+t5TAAWl7XD7vZ0uNwYRHx0t+MWjKfe2Uj7Y7eI7Dsdzq5zaGGik5tYo4iJrOJgU+J6DVorTubVfTXyP80XOIPX59LTA91yayrDbD5msGhwsgmfHC3l0bmU1hklAXklKR2G02aC4nmL8C0EjLZ/n5iBm1CKrplm9QdfcHCZvThgROJxZHsWtYfxcGZv1ht5NrPNh4FkE3KpSpIFHIRWTrGavHzOIAv7+wYR77VopKsnvj5fMiwaDIWxHO1Ja7tMsq6la7tOz7bNZXvPbwxl/OFkxySq2uxF73aiFy2pWVUPeNNwaJnQSj7LRfHQ454f7fW4NY2Z5w+NpjlQSpQSuECzyhmHiUwqHolZkvsIVgnle4QrBsBNwMC1azw9B6DuczgtmZcNk2dCJXKZ5wzSrWZaN9WdPQvJa8niSc2ecbroJawh9Eth2ptsOqZ/X+pkVNcvKIh47kc/9syX3T1dUyvBn+z3CwPu8sutHm/u1P0y4M0pYVRLXsW1vw+dIwsT3yErFvKhxMRgjaLQmjVzOFiUfHs6JfZetNOSitNbBrpMTbNkDP68swXO/H3Cua7Ky4WRRMkh8Hl5krEqrpJuG3lNJ4BrdJVzvaUXHr4i38vAAqKWyxCjfJfPk51kbVna9Gwcorfn0bMWj84w4cPnkZEkn8rm7ZYfRHx3O+dnd0SZDn6wqNILGKKRWBL5Dklq0RuS6fHqyaIdiFnU1K2u0hnHXwRGOZY9rw6pq6MY+Shp+8eiC81VNrQzbHSuUVjWS3x7OeWdsmbWjNNywYHuxz7ysGaX2oc9LiQHORclWN8Jv0SYXWc3NgUfVWIG/G/2EXuRjDBv2+s0X3LtnF9bx3FY/2hH0ooDHk4ztXsSqbjg4zzDCYatjWd6LouEntwZPyZGcraoN2mSWNyS+z/d2LYBhXkhC375sHx7NGSUh86LhyUXOWVaR1ZIUl2mhCFyBI2y5P0x9TucVi0Ly7o5FDUltNgTRsmqzX6VR0qBaFJq1bq1Q2vDR4ZxpXrPdkr/OVhVZKa34XTvQ32waaUjcakC9qZDakAa+9Rsvmo03x+Xe/No8K/E9zpblpiWzKhuOFwXjNMABjmc5p8uSfhhwbyu1lrHSEPm2ZWOw2l6Baw2OLrKSRdmwN4wom6e1pWZ5zc8fTkhDn+1OwNmy4FePJtwadxinAWngcWoMu51kI8uRhDa5+MXjKe9vdzleLnl8USCVII1c0sgjCSyRrh/bZOfj4wWeK9juhBgj+OWjKbWywo2h67As7KzvbFnSSwIcR/DwbNW2Rl0cBLNSci/wKGorM9+LPUuCHaVUUrEsJFIr/sPv7QBfZPRfrCre2+624oeKPxzPSQIfVwiapuFfP5jy/Z0OaeAyyWqUtjyh9XO5OUws3L9VkyhqxdmybJGEbDogCAfHgUHs00hjKxtjSAOP+xcraqUJ/YRZKelmNeeLmm7oo9qKPw5dqgYenq144gqSwCcN7Wf9/OGEYRpwNFOcrSomK9s+vKrJ2Vt5ePiug0agxeel6LoF0ShD0WaYj6cFy6KhnwZorQHX+kOsam4OYpbF0+iT02XFVifEGFjkkt2e3dCnuWRrLyKr7JDSc+3G8/B8hRBwkVf8YLdHVkmk1hxNC1al5OPTJbOiQWu9QVTdamcDnmMRP7Oi4cnjCaNOxCjxmeUVwzhgMA75l5+c4goX39GsSkUSSG70Y7TS5JViVTU8uigopWpbUCm+59Aoh7x+sQbaujrTRvPx8dL+e9e2Enqt78inZ0vy2grlNcbqGmkE3cgOPH/+aMrFqsJxBC6Cv3lvtCHvaRq20pCjRYlAcDq3BMNGGt7bsjOHnz+ZsJWGuMbwq8cLfE/wg70eZ4uaYeqThBZ2uz+K0RoeXKyY57W1PG0UaWhJbpUCIzSuC7W0nukCcD1nI8B4PC/aIb1FCZ0uKoq64Z2dLrHv8GRSMC9qfnZ3yLh5c9pWxhi8dj0Xja2QJquKRWmf5bPMcg08vsjZ6YWUtQVkJIEHBh5McjwhSAde2/bxcV2Hi6WtOudFze+O5wxacURXWC5SPwq+0Pb89GyJ71oY+yxvOFtUlFLz0cGUfhISOA6eaw/200VJP7HvzbJs+OhwwTyv+dWTGanvYzA8Oss4mVX8YL+LNJo0dDlbwf4gIQld8lJyNMu5MYpZVpJRHFAbw2k7zxq1fuvz3K6FRlnm/O4gYqcfcpGV1FKTN40d6vdjOpFHoGxlkYYeSpsX6kutZ5e/PZxTK6jLetNerRrDybJCGXhvJyXynU2FWCvDMLHkxmlWUzQK3xV0488N2H57MMdzLfnXdRwe15aoOi8aosBl0XY4fCG4WJY8qhVK2Qqm0YZGGp6Qg4G8lhzMC76/28Nr9769QURRKX71eEbRSPJaE7pW5FJ4/tvl5yGEeBf4XwN9Y8z/4GX+je85/PTWAGMMn52uGKbBUwugF/k4wsIG133SP5wWBI6D0pZRqtrW1qJouDm0GfjZoqRWmllRUzQS3/VbQpsl7M2ymouqIg4soc/3XJTRFopbKR6cZww7PqvCCqGdZTWzrLZS48JQNoaHk4wf7fcw2MPq4UXGbjckrxoLk1UaV2mymcIYQ9FIFlLRiwP2+hF5I0kDj62Oz5OLnFle2baONHx2lqHNiqyUbHdD3tvuPlfCfNwJ+fRsxTSzstFrrkVVS+ZFTVbaTQJjGHcjcARaGYQDWVlzNC8xxs47bLZXc/8soxt69JOAoEXC7fVjAtfh4UXBTjfixlZAKTVR4HJ7mHC6qIgDn51uQOQ5SGmolaIXxVRLiRG2vfHbwxlVYyuGvOU47PQDGmXlvPthiOs6tmrLrZaRKwQPLnK6occsb1hVDTeHCWnocpFbt7zJssK0yqPd0OXj46XNDIXzSsqPq65tIazuGcKifZ6VhfnloynSGEZpiNfOGuLAZVk13N3qsCwltbJMfBdIA4ckcK1hl+egG8PRvGC6sm0h34V5qThbVtzb6vDBjS7d2GdZNE8NnY9nVtgz8FxqbaHVx4uS0HXZ7oZM85rzXDJMrYHUo0lG4DlkpeRgmvOgVdI1qeEib1hVksRv6E49BrHPLJf4jkMSWBVa13UYdkMcwMVBA73IIxwnHM8KIs9hUUhKqRglPnlts/9RGqK15vFFyY/3fWLfZVlIOj1vY02whm1frKzmFFjYfehZ46TQczak29h3uTmMOVmUpKGL67h0Y4dG2vZmpQxD//PDZ82DiXxbyZxdVMyLuv3/tr1dt/yqotHEvmC7GyKl5mBWoJTBFZb3dTyvCH2X2HfIqwYjBKfLgne3uoSuoJKGUqq2PWbFLHd6VkD1dF7ycJJxe5hyvsoocImUuXI79rVCDoUQ/5kQ4lQI8Ztn/vy/I4T4vRDiEyHE//LLPsMYc98Y8z+7yvea9j4UtaLRVkLhcqydu4QQVEpt0AmNtqKCZ6saqa1sg/WVsEzVUddCbHe7Uav4WrNqJPv9CKVtVuu7Dtu9iHnZ4ArBqpCcLws+PVtgMBSV5r3tDkfzAiUNAsO0aFr/ck1VKY6nFYfTgt8dLThflTyZFRxMC3qRz41uhOu4NEpj7GXTi+zBUTQSqQz9yGdeShZVw/4gYb8fUynJLx/NOJ7lpIHLvGj45789tk6Az0Tku8SeQ+hbiQ8N7A9jfM/lD8dLGmUYpwHLSnIwLSjKhqKWFJXkcFZR1Ypu7CGEsIcdgt8dLjjPLEEyCV3ySjFIfAax5bSMOwG7vdhWANqaP+31Y35yq88Hez22+zE7vZBbo5jb49QO4137Yr6/k26sT1Pf5fY4JfJcxmnIO+OEQeqz1Q0ZJD6+Z1tfu92IXuTTKMPjyQqt7bPTRuA51o99VUtuDCI8RxAHNmP0HAcRRPGbWNueI8jqhqySm7mNgY2a8jxvaKRuyWgVJ4sS14FH5xlp6LHVDejHVtH1ne0Ou73YPmMsQunDwwVlrfjJzQF3tzpILdjqhvz09oCbg4S8Uht5k7LRGzmUs2XVZtG2cmkUdKIAsFpXF6uKrGw4XRZobXg0yfj//u6MT04tHDdwBFIpfvXEIos6gYvv2urn3Z0OQhi6sce8sEmL0gaMYZo1vLfT4Yf7PasA3MLjd3sJe8OYbuBZq2QP8sq2K89mVVsJuQzSgDtbCUIIfnMw4989nHI8tyoFSms+ObG6Z7HvblSHV6XczPOUMRs3vne3u/RjHwxUjcRxrKtg7LsczwsOZzlZqViUtq326yczi/5qAQm/fjylUYo08vAch3e2OpsuhxDwl/dG7Patxtoib+iGHonv2qpDOHQCl0Fs5zkPJznT3MKN3xmlbHVCdnrRhlj5aJrZ+xx63BgkbHUCAleAc7Wk6HVXHv9H4H8H/J/WfyCEcIH/PfDfAp4A/0YI8f8AXOA/febf/0+NMadX/VJjDJ+eLlEattKQRhku853XZLedbsgvD+Y4wvYWf/VkjjSaW4MYrzW0H6Uhn54t2enG3BomKG0PpR/v97h/tkJq+/JIbZFQoWcJS2tXsXWP92JVc6NniUAaK7JWNZIH55JO4IMQlLVVjjXYHmejFDf6MVIbjhcV/+yXh3xvt0MaWhG1fhogDVRKkdeaSjbs9kP+gw+2+f/94YwbvRjXFZwuKs6XFYPE5XRVY4wgjTwqqfjPf3PEf/9nt75YgQjB7WGykaR2hCCrrJCbwbJ2f33oUNYVh01DP7ZVQ9lIlHYpa01RS4RjvRBc10JBPz5ZkPge210frQyL2vbut1rUUOg5OI6AjdeAtbFdlA21UmSl5BePpjTK0A0tGssYGHYClNRsdSO0MuRSEQcO/TS1nBsMo9Q6MHbDmBtDuyJOFxXKCCv5otaVjcvJvORoUbaijQFZYwESJ4sC4QWxqfJvfG0bbFU4zWseXOSM02CjpgzgupaAahYVviuIPAfTHoq+55Dnin7i8+52Sl4rzuYl98Ypq0ryq8dTXIQdsgcu81Lxzm6nRVoJLvIa33M4X9Vst89qjabbG0QcXFj2+DSvyesGozQGgQJS3yVsZ1Knq4Jp1mCEwfcER3OLWMpqRSEly7wiCjyEUGx17GaYBB5p4DPNVmijkMqCP8paMkqtgGAn8NjvhUyyiuN5YT3O+yGfneeM0wjTqixPspr/yd/c5c/v2Vnm6aLgV49nTLKSO8MUx4Fs3jBIAlxX8PHJgpujhHEaUEvLCXl/rwdTm4R9fLFkltcoNAJbBQzTkEYatrsB09y2xnzHwQkEou2GuMK+g7XUdB1bUT6a5PTjgFle8+giY9wJeXecUGnLoVHaUDaSB6c1cWgZ6KNOxDDxLQ9KaoZJiDIaVzhEviDsBGRtW3PdQZitGm4NYnAE3chnsqpbMVL323N4GGP+hRDi3jN//A+BT4wx9wGEEP9X4L9njPlPgf/u1/0uIcQ/Bv4xwO7+LbZ6Eb4jbH/v0ZTv7/fwXcGnZyvmecPdrZR3tzqgNJ9NLGa9G1qUUDfyaYxtq4Sew+Es5+ZAIITD3XHKNLMEnqyUNAZcYeXc0WAcw/mqJnAFvTggDX1cx2oxCWGRTrXS7PQi/vWnFyhjGKdWf6hRrmVW5yWe77HbtwzoVdUwSgLLoSgbZlnNH85W5I0mcASD2GeU2gV0YxCTV7bM91xB4Nnh8r/5zCKVXMexm6yJ6IQuqqy/AAyAz+ceke+y1484XhTcP83spjG00Nz3tztgLNfDCMFWx+oSuZ7D0SzDb9E6jVR4nkM39NjuWp+UtZrpn98ZbiCetdT0Y5+jWcF01ZBGDmcryzTe7kYIDEIIXMeijfJGM2+1g3Y7EbO8oRO6aGA7iNhKQ7ZagbuolRgvaztId9ryf5ja6mdVN0ht2ehHs5JlZVt7eamYrVac5w23hymhL8Cgv6m1fXld375zx4ojOjbTrJS27SHfDvKHScDPH04wjpWuCVxLxPzBfo/Ic7hzs8+qaphlDcuy4dY4oZTWue/2KKUXu8wKiTaGXmyh5afzkjSwisMO8OB8SSd02e1bVnrZKBwEnutwNMtxHVu5aRd6oWX/P5rbtqRwBFtdj7ujmMeTAik1g8TjfGmTm0pqMlchHKv6cHsUczgr+Q/e3+Kjwzla65Z3oxEYfrjfo240/STgdF5yurKVZ9f3+OwiY7lS3BunzMoGF49Rx0OqZCPDYoUWC4ZJSCkVUguWhWS3H/KHkyWD2EcZw2RVcb6wvjJr/a5VKTlZlIx7IYtKMlk2xKHhg70enuuiteZ8VW8AHonncKfVUKu14f2dDo7j8GRqddhcx3LHIteaTw2TgL2ebUOP4oB+ZNvioySg2TIYbQ/nydL61ASOsDyabrCpMPJK4jrws7sjPj1btn43Hj++3aespTXd8p0WdtzwRWGnL483MfO4CTy+9N9PgL950V8WQoyB/y3wMyHE/6p9Eb8Qxph/AvwTgH/w078wvuMQeA5JYKUofvPYIjPGnYj3dzobtMayttaloe8SBbYNstX5HFlTt5j0Nbx3rUCanTQIx2G/3ZzKxgrBea6wEtbb9pCpW/7DKPH48HDGspa4wljF0cRHYcga2yJ7txvy7lbKZ+dWJqEX+RzOcnqRlfxgZQedVa3pRx6DCKalotGGYRqy1bUL+8PDBdIYDucF/dhnnksqqVBGM44tvn1VNVSNZrsbtAisp6G7l4lgxthB3HbPlr++61r2bDfgNPLZHyTsteTGXxsF2h7Sd4YRGluZGeDeOMVgNsS0WmomK9u7rZVhVhS4wt7jH+53+cPJEqWsdMVWx/IWOnFgSZKrmmlWoWkJnJFvqzoNi6Jma2Dl7ePA5dboae2holZktZWIiX2Xf++9MWeLkjTyOZkXhIHL93a7hL7Dx8dLTlY1vVayvVEGtHrR1PyVr+2n1vWf/4WZZlaOfm8QczSzRFPrrpfgOLCoFGnb9mmk4WxR8KMbPXzPJQ5suzPwFT8Y9eleEjW8s5XgCYfdfluprkr+cLYEYzfaOPCplaGfBHiOuGQBUJC0m1ajfHa7Mauq4b/4ZILShkba3njdKGZ5xem8YG8QU2tNHAZ0A49HF3Z4r13LCI8Da8K0bG2Fe5HPVi9CUyK1YdgJLLDEtdyld7Y7TPOa97c7OI7lahkhOF2UOMKuu07ksyisrMnpsuDxNKQTuEiliQOH93d6eI6VDjle2BZTGnoMW+2rVtOMcRoghCCrJXu9hPvnK36438cRcLaoyRvJu4OYWhnKWlmW+yXdMN8V+I6wbb/QIXCt9e7pvOBwVlpxTiGYFTWH85wk9PjJzT7v7nQJfZePT5ZM8ppFDZFnB+VlrSAQDP2QB+cZaWAH/pZPFjNIgqeMpu6fLnlwkbGqJYtcorTh5iBFl9n8RWv1efEmDo/nwcFeeOIZYy6A//lVvkAZvVGEBegnPp+cWgHCu1vp5u+dLSuqxipb+p7DOA04nBdMVhXvbXc2MshraB58zqh9dJFT1ZLPzi3KYhD7uMJhVlizF6Wh2xK1XEfw2bImDVwaKVnViqNlxc1BzLtbKb87WSGlohN6LIuGm8OYQRzgCIEQxvZLa4UjDGhBLwmIA2+TaTuO4GiaUze2xaOM4UY/wszhwXmOabkmsecjlYXiFktNGihuDCKS0P2CFPZl3sBBKxD5o5t9y3loFMuy4uHpksrYuc0isFXbBzs9VpVkWTUsG0PdKG4OUwT2ZZrlcmPOlVcNvz6YW7Z36NKPAk6XJVtde3hvdSPySrIoGz49XfHBXq8dnLr8/YMpk1XJbj9kmFgF4lEakob2uv/8mUpqHetDcZSGT7Gj/3xjlSufMuHZ7Ub83/7dY9tnB9vXfnG81rUtlSbxPXzPwcdhf5hwtig5mFpP+1oa9roRWdOAA9udkDTweDLL+emtYZsc5HQi/wsIosR3+eR0iee4gGGeV1wsK+4MEwyWVX1rmPDXOyMeXuQ8mmSczkoQlsD6wW6Phxc5s7xGGkMSCM6XNXHoMYgDCqkpGo1y7fpzjcEVMC1qfCG4vZVy0Rp6WXRVxapW/Eff2wIh6IY+4xtWSXcdtbRV5JqHUWibSAWeyzDxmSxLlrViqxsyL2o6ocdeL0Zqzcm0oEgs+7qX+Piuw+miwnMMx7OcUSdsRUAFZ8uKixYd9ZP9Psfzgs/OLQDEc8RmHd0YhASuVdcuasVeL2pl9B2r/JzVjDsht7cSPjle4bqWbXT/bEXRaLY6ljv14emKO+OEu+MUreHDgwX3xh0r1vrxKZHnEnQcjmYFwhHs92IardnthXx2nrGqJLeGFoyy9iG6/C7sD61BXtYodrufexAZVV/JY/lNHB5PgNuX/vsWcPgqv0AbO1xch1R2APYsitnqUFWbwXka+AxbBqpV/+QLkEQ7MHNptEZpK5O9KiXny5p+7OEJuDdO2G4XzmRV8i/+cM7FsuLdnQ692EMq0cIurZTKn90ckDc1h7OKWVbz1++OyWvFoqyYLpvW3c3q4CyqiklWsdULGaQBq6IBbWF6nif4/dGcvFb89sAQBg55rVFKkwYu399NOVzUrfaTwPesMGMn9J+rOrw+QNa8j7X0zW+fzMlKhTRwaxBzOC/I5YqbvYS72wm/P1ryX/9gh8ezAlqDLKUNpdRsdW1Pd5AE/PLJnLJWzMuGZS1ZlDYLOpwWlnvRthB3ehHzzLoAagyHs4KdXkijFPNK0Wvd2YZpwFYaoMyLrYO/TJo+8l2OFwV5pRDCXmM/Cfj+jT6LwrKCA9fBvNjr+bWv7cvHU+i57PSijbvdv/j4lO1+QFhY6ZiDacGyqFjVGh+HRdFwuixbefHPJWpUCxV/d7vLb5/M+N3REiMMNwcJo05M6AuMtn40sh8RtNX1ybLAcy3kebcXcneccLEqqWvN93a7NNL26HEEwzRACA3GIasabg4SOpHHLJeMuwHDTshWGnC+asgbu2YHkWeZ7lHATjfkcG5bv55jkWTT3PqzfHg452hWEIfWSKxsDKB5d7fLqrQs9d2uRy+2wJmdrvUfcRx7Dx+cZ1TtvG5ZSS5yyc1hSjeyEiRK2wTpcFbw//ndCVGrdKu0RmlLDO6EPo20e0xWS9LQtgyP5yUArgPLSuKXDoHj8MP9HoezggfnGUob7o4T5kXDg0lG2KLFPjvLGaY+ke/y6dlyI75oLatd0jCgG7kMOwGNtHD5nW4EAkZJSK3UUxpd64ha6f3vopPgvwG+J4R4BzgA/ofA//hVfLAQ4m+Bv927dZeHk8ya1AiHWim2utFTHb1KKh5NMhaFxHcbi8fWmmVZE/keg9RqRFn5b8U0r+nFPtK35LKjeUlWNq2shkMtYbqquL0VEwUeaejxL/9wxkk7ZL3RjWiUpla2KhjELr85WPDjdzqczEtOF4rIc/jprTFSGpTSzLLaEqA8F9eBomW1KgRZpYhdRRT4+I6VYZgXNafzmu2ujxc6LHLbmooCi5pSxmG3G3A4teQ714HYt1IcL/KpWPtvHM+0lRVpFGno886ORyMVi9K2Fmqp0GiqRvOj/Z710gCWTYPWlmPhOjDPGppQW5jmLGe7E3K2rCgbZV/EwBL01i6OYMlx/cQnKxs+PraD6zRw2e6FGE1bYRqaRtNoO6ty2oz0S6XF+Zxhvmh1nSxz3v6Oo1nBVifk7ijmZOkySoINfPMF8VrW9npd3733Lnk7s1lvoHmtGKdBC1fWKG31nj4+WfBkUhD6DndGMZ+crzhZFdwdpTTKwnzXJMMPDxfklWSS1SShxw9v9jhv1aOlLqyTnedytixZFg3fu9FtWesSB4HW8JvDuc12PZdeYtDG4Z3tDp+cLpkVdi5lW0MOtdYssophGvJX93qcL0uOFwW1NniOVaGVRrNq/XTKRvGDG32k1ExVbZUCausV8me3h2SlJPBdPjlekkYejjBcrBocAf/tn+zx8fHSStToin7k0yjNXj/hZFHy2dmcqjFMiwqjoZaSd7dSHk+spcJO11YgpysrDFpJzTB1mOeSi7zk/Z0u54sKpyfQRjPuROS1pBP67RzK59EkZ5bVdGKPUezTiS11YKsb0U8C7p8tOF/VGwUAqQWVVMShS608BJI/nKyoG03ctqT6sW+9UGrF+bLiBzd6ZJXieG6VvD1XcHdspUue52X0KpwEX+vhIYT4vwD/CNgSQjwB/jfGmP+DEOJ/Afy/sCiU/8wY89tX8X3GmH8K/NOf/PRnf2d5DSvujBJGHSsueDovyCtJ5Ds8Orcl9v4gpp8ErKqGk3mJxvDvv7dlyWGtEZTv2kzuNwdzfNcOBG/0I/7txA4me4mH07oRjuKQeVaT15IocPn+Xo95YfWt0jigqi1cL/Fd0tBlkTdcZPWm/D9urTrvjDpoDIPYY1EpLlY1eSsLXtYKbaz3waATkqQBW72Yg8mKvX5IrWAcBfSjgON5zvmqxhUOjaxsJaIVncAhDjweTnL+47aH/Wys9Z56UcCFLKkazYO2LFbaHoRpYPvCgeuwN4i50bc971luHRED10U7EPuCwBUczOzillJR14qzRUWtNWnogTEsSk3gupZZnPhIbR3eBknA2bJESntYKw2eZ61p50XDqlaMOxF7fct+NsZ8pd/zZT2rspa4jkNWqY0xV1ZL5q1c/DuN2gwdAfNNru31uv7Lv/yrvxslPlmjqKWdm+VlQ95K/N8Zx/z+eMXH05xaa7a7PrUS+K5HJ/IQAhalYsv3EAiOZjlSQ1ZZm+NZ3qAtiYSzuWWUT7OST06XDFOfu+ME1xX84tEUjLZS8FnFJG8YlFZDTmrDIA6QGmoZMOoE4EA3DPAcl05kM/JVGnJzYDXYVqVFJFWVRFs0At3Qp26UVWxwLBpuqxfyu8MF405A4AliP2JVWbFD+/wEq9KqP7iOFdwsKnudUWhnPlYoElaV5GRestuLOVoUhLXLSknubXXwXJeTecGvnsy4OYgoGtty68YB86JGOIJACHa6sZ2TOALXhUB4LEoLpnkysZpy08zyOLZ7IfuDhINW3PQyS+J4ZgEngyTYPIdO4KGURQgeTnPiABxHsNsLeXhhD9TAc+yw3BUMEgs08RyXUT+irg0fHy+5t5V+wTP9VcXrRlv9j17w5/8M+Gev63tdx+Ev7g45XZat454VH3tnK91sAIuy5oPdDqOOHcy5jsC0jnNp5HOyLMlqSV5IDhYZnTBgVUkGcUgceVQtO7RUBlc43BzaF6EX+1xklgU9yxpcR9KNPU5nFZNVgYPDvJVW7yc+QlhOgVSWzX6RNQSe4Dwr+fsHE2ZF09plGuLQRypbQmdlTdkYHM9+9/2TJfNS0ovsy+I4AZNVzcfHK0LfZbvjcji1/BXHdej7Hj/Y6xG4Lr9+PNtsuvB5Nv7JyZKskfQimynVtWSe1WSVJA7tBr/IalZJQOw57A4ilLZWup7rcKOX8IeTBTiCd8YJ88KSln603+Wff3hMEvoUUuIKh6LSeB4Ybfj339/mYJLjCAvxVQoeTzPKxqJt+rFvGenKCtFVjcJxBHfHn7epvsrvuWwUvz2cUTbW0TCrJP0kQGpD0ShuDOLNAbRuaa2HjqYu8jextoVg025YV0peq0i7KCTT3K67s5XL8aTixiDm5ihEa8PpwraYamn43m6HvJZ8elpwZ5xyox9z/zxjltdEfquOMCnISklW1XiuQ1mHhK5FHJbtrGE7jUl8n7yRlpnuuPQSj5NFRdFIlqWyCsWTgii0mfwo7VJLzXYv4r3dLj/c71M2iv/zv/qMvWHMybzie7sxgzRgVjQs6ob305SjeUW3UniuQ1ZboqPSErfRFrpb2znb2apitxOxv5USOg6/PpzZtmde43sRnmMFBg9b5OE0rzhfWLmayFvPCBp6ic/xrORwXlr7gNiqXAsh2O2ESA3HswKjNR/c6G3mooFnFRYmWcPDsxW9xMP3PBysPM5aLfvOyFsvGAyCrLSadn7bno4DS7Cc5RW10gz8gPNlje867A8iVmULLZeWhPybx3PrQyIbEFb+ZVUpfne44L/5473nrv8vtK2uGN96hvnXiVpaoa/tVnp6XZ5d3gAC94x50Vj0TNvOKmpFrSS/fTLndFWy3QlxHZASJrLCKM2DVvTtaFbiuHAzDcGxC/rWKGG7E/LwwtrHPpqs0JpWUkJzulD0Y5+eZwE7vztc4fuCyHE5XlQW7eVaZMp/9dmEeVFRNxrlCJalYttopHFIIoeRH3Ke5cxOSut54LrUSqFNSC8JOG0tYpWBTmCzo3nZcHsQ0418XE/wZFbwZzf7VJdMgNbZeNkoPjld4TqCk1lBPw2ZZQ3jbkDebgxee+DO8gYvDagbvbFFNQZuDCMmec2yrPnd8YLbo5R+HCAVdKOAwLe93TgUFLWmkooP9nrsD6x8d+gKHk0sfyD0rJf6pBW5M4AnIC8l466VlDhdWuvcrJLcP10RhR7Hi+ILTPqyUdw/XfJkWuA7glUlySuJMjabX1YSY6zcx7OmR286Lrv5+Y7g1wfzFjobcjgteHJR8v5WglQG3xEoZThb2sN8t+sR+ZaLMUpD9gcxvcjjl+cZn54ubTbrwi8fz62wKIZKQuBqVpVEKs0P9nocTgu6kcdeLwQjcAVs9WMQlq/xeJrjCMF0ZWGk/dTn7iihVoaPDhdsdUNcJ+HhJOPGwKKBRmnIXj/i3z6YorVhurJ8DW0g37EVajcJwGiOZyWeJxilEUlgk7EH5wX9yGUY+0gNv3w0Ya8XYYTDONUczAsWZdOi0gy/O16w14uoW8b+PG8YdwI+Pl4x7ARsdUOWhSSOPDwEJ6uSTmAtbC9WFatScbYqOV9VxKHHxaLi3Z1uK0RZMUwDiiomChx2+/FmYL7dDfn9yRJaZ8LHFxmeA7vdBGkUrmuhs7W03YY0cOmFHlIplOtwvrTglaJRVEqxKmzb+HhZMjaa/UHSarxZWZdO6Laq3U+v/2c1u76OQ+ZbdXise8P7t+/xZJrz4Fzz/Ru9zf9/SkEVi/o4XRR0woBSSn5/MmeRa/YGIY4QnC1Ldjoxe4OI86zkaFkxjm2bpJtYkt151rDTj9jrRTgIq50kDCctZrvGMoFnmST0wPEER4ua3b6VVUDDRVlRKomqLLP68WRJKBx78DgChIs21nO7E3sI47Is7YbnCEHgW3LiclGzqiR7vZiH5yvOlxW+76CNy+miop/4LCpJGHhsRQHDJOB4UfLBbneDtjqc5hwtSn5/tGCSlZRSM1k1hL7g9igmdENqpdnqRGS1YlbUCC2ZZIr/569WbHcifnZ3wOG84OFZvuERSA1Vo/E7luOxP4ypajv7CDyHTmRhk/e2rAR8L7JL89Yw4cFFZoeg4vN5xjSvKGrNnXGyEVk8XZT8oVWF3elHDGJ/w6R/b6/Ldidk3Ak5nOZM8obY9xAYHMeSp353NGd/kNJtZbynWbYRrHuTsV7X77//PmDX8eNJzvmqomokoe+QBh77w5h5WTPJ7fMSBspG4ruCi2XNKPW5M04R2LU9TAN+dTCzSUEa8PHJko8mGWfLknEnJKsUUksrjy8Ms7KmVArfEfheO+xOA9LWhMryPaAfWbveo2WF0BahJhzBIPSZrOwBP04tEuznDyf87O6I/X7Ew0lOEricLivK2gIy+rHP8TwHHPppwOmiZtJW49Nsge+4HMxzAsdhIQwoQxLa98jaSwsmqwrfAWEshNx3oRtYb/qLVv+qUppKSqpG4zkBvmMh+6JNkC6WDfHAIfJ8Hk7bGUbg0Q1dVqXiwSrDdQRbvYjPzjN6kY/rig2fyXMFRWMrprB1I8RAqSwVAAG+cenH/sa64R++O+bXB3NmRc27O5an5pYOv3w8Y1pU7HYjhh2r45VVitPlAqWsZFDgWnOryHOeQlKuK+7zpRWRdB3b8rrRj6/skPnGHNFeRxhj/qkx5h+n3R6h52CMJTmVrYjcwTTfyC5vdW0pWyvFR8cz/uUfzlhVdtOqpcZzBJOs4mCaAYZBZPHtjmtVa8dpQC8O2OoE3B4lgIXUpqHVuwo9lyjwMFiUSqUU07JhVUoE8OQ842RecpE1uI7LMAnZ7UdIbTVpOpHAcRw6ScCw49MJXUppCWIYw6yoLWbcdVi0JkBb3ZBlXnMwsQeAcAyx55LXNVpZbkhRWzjvXjfEFzDLJfuDeGMv+2hi/Qqk0swLydGiJAlaS9PTnElZM+5YeO+f3Rrw3naHi1JSa0E/8gk8wf/9Fwf84XDBRWYrp8cXOU2tucisbLRUhsjzWNUSrQ2LQpJVkmFi0W5rx8JF641QNZq9vmXtnq8qamn9xAfJ5+q8s9wKxh3OCnb7EaM0pNGGVaUIfKvnsxaoezwtSAKXccf25o3VswFaBI7vEvrWKCyr3oh1x1OxXtf9fn9TNU2ympN5SaMMTyYFWW2H1++MLRHtb94Z88Fel7Ol9Ue5OQzZ68X4rvV2GCYBoetwsigpmoY09OnE3iZDnbfqrv3Q38CUa2XI2+H0rX5AEnj4ntUXGyQ+cehiNKSBTz8J8YRVWbjIKpSGs6WV9A88l71BTBJ65LXm//3hMXX7OxxXEDqQBh47nZCdbsSsVMSRy9G04PfHC2LfwfPgs/OMw1mBbPlVLrDTszpmi7LhYFZsgBnLSjMvKo5nBRfLBs9zuH+W0wtderGH6wieTEpi30UYC+9PI5/tbkgceNwdJ+wPUmpluFhUjJOAd3Y6bLft3qbtFmhjDcpqZW0hrHWuZlk2nK9KfvVoiuc77HQj7m112O8nNBKEsX7nxoDnOow7Ea7jgIbIt/Oq82WFMoaiaZisGiqlCVyryOBguFiWHC8s76eWmqNZju85m/bteg88X1Y8OMs4W1YcTnOeTAp+83iGcNxrSXawc4/bY9tKWXM0Litk+p7N/K2MQEgpDfO8tlae2rrO9SNLoHt4Ye1Yv3+jRz/2OZgULAqLpfZdges6zIuGJPKI3HaAJsDxXEapYKsbsShqZoVCYA+vadaQ1xJpDI6wCqPf2+mw2wtYFRHnq5rEd3GFgy8sFj2vFbXSdOIA2ciW0yHISqusWTcWJXR7K2HWqnCO0gBXCJ5MM5CuhRM7gt8dr3Aw3N3qUCtD1Sh+8WhK3kjK2so/dCMfbQy1NiS+i/YMRSHphj4Pzuyw9f7JwjKvPYdRJ+R8UVLWmt9eLNjtR+RGWWE217Q+IjXvbCWc5w2eI7g1TCgaaZ+FspXP7bHl4uSNraziwEImd/uRlWEvJaNOwDi1fdrjeUngWdG805V9wW4M7SEdeC6RJ5i3FQ5YEmE39Ah9l51eyDxvyGppdcm6IWs8rNdqoH1bopKaXzycbFjgy9LOIwLX4WxZ0Ys8dnoRzlqWf1Xz7m6H/V5iOURVs7EUdoT9vNhzqbG/c1VYRnZZKQ5mObVUrLS2sPLQZxi6TPKad3dTpBEsyxrfCxjGIXv9BEfAbw9mIATzQmKUYF5aH/gn04LIXeuG2ed2uqgwaA7nBUHg4rgWoWcE9FOPYRIS+x6zoxmibfPs9ux6OZmVBL7L7iDmaJJTSsN2z0MbK7lxPC+hZcpLo/BdyGuDMZoktjOuQeoTRz6hgijwGd/0yUtri+AJh3tbKZ+cLqkbxfd2OiAE/STgfFWS+j6e42zekaKx0upni4o0csmrGiEM252QvJI8vMi4N07phvZdOp6X7PWjzbrOaolo703QGseFnlWJsG08awlcNRLP8UiDhsBxOZlX3N6yZlL9OMARxgpLBi7bofVTeX/HJljrmczZsiKTitR3WTX2/fE8gfCCt0tV9+uE51pX+aN52SpsNlYi4FL/epbXBI6wyqCBS14ZqkqiNPSTkE7g4QjbX08Cj+1OSBK6YOAf/WCXT06XOEJYFmzkW9RR6nOytIqkBiux4LYch2UhSUIrb73KbSvBdUBow14vRDgWCfP+doK33+fgoxP2+jF5VbdsaM0odVFGkAYued1QVOAFlrh4uqpQSuF5Pqtacnsct71ZyTjx6UYBi6Lm1ijh3a2EVaPJSyst8S9+f8wgtZXYMAk4W1jJ+CT08B0XZSQ7vRCpNNrYQ7VMFFoZLrIaxwEIEMDBrEBgqLStvlzPwSiD77rcGSV8fLK0MtCew+1xYpnQyqKvbg5TAs9WUwftQLORsj1sa4QQDBKXJIzY6UUIYzhdWq+RqlE8nOQErftgozUODne3Ela1sv//IiNwRau+K1txRYdhYuUfGm2Y5g265aZcrCrujdMXLbNvPKTS/Opgbtt72x3e3+3x2fmKWSEZC8FP3ttqpe2tjtMgCcgbxYPzFbdGth13uigZpcGG69KLA8rGrq9xJ0Aqw3Yv4nhVIYxBYXCEA0Kw3UsQriFyrQrtzYHVXevF9tCKPMeKeE5y6kayqGvrXRP6eBhmlcIIg+sI7p+tqFr3wkZB7Hvc6MUUjaaWtoK4O045nBfsdu0h4jqCfiL47FzSKMNWHCCwookaO3uLXMWtYZ+LZUXkO3RCy4wvGus8aQx4GBalZJz6JJ6Hdg3gsN+PmfrWjyavrAzQLKuQCpLQ6oL1I59B5DEpGgbGKhIsyxbtNuq0unQV250A3wstd6lpuNFWWrVUCKwm2BqgkFcwTkM8x5INF0VjocMGXOFQaQmNJPZdEj8kDgpGXathhYGLRcXpqsR1HO5uddjt2QQocIXtgLQgkjVfK68Vwtiug+9axd3AEQjXuxIs661qWwkh/lYI8U9mM+sX7AlB7HsWXmmsWCHY8u3JpGBeSlZVg1KGTmTF41aNRTt5rmC6qnGEIPQswievrY3n0TxnEHlcZLY6WLv+RZ7ld/Rjf1O6LoqGk2WJEYZh7LU6SrLVHrK9T2WwbSQH+p2Q/+iDXf6TH+yRBB4Cm918sN3h7rhP6Fr1VBdBre0i0FozWRUgBH9xu0s38LgzTtnrWWfESmnujGN+tN+3GkPCZX+Q8Jf3RmSNpJGGVWkzJcvwjljWFs0R+la91iBIfI9e5IPRdGO/9ZKQzFaWnLS29VxV1p42Cjz6cYBw4PEkp1HW4XC7b8X9jKZVqhUb+YxaWSjuGrUy7kREvks3tgdxHPr0Yo/3tju8u9NFtm2Bi5V9xt3YZ55XnMxL5kXFpycrDmcFNwYxse9SS0PVWGfDf/PZOb94NGFWVMSRtQc22g6ljYbzZUml3nzlsV7X2XJBUVmG/iJv6EY+P9jrc3MQYbAVbew5G1tUYwz9yKOX+DyaZHiuTWTWpMg0tL32Wd5wuiism2AtcV3BP9jvMUgCYs/j3e0uP7rRp1GG24OE7b49vAPfVm9paDkH87zGE7CqJfOswcFhrxvRSwIqqdntBAwin8fn1qrWwUqI+K7hD8cLDmcFvz+aE/mCaWaVe6tGc2dsjZqkMUyzmsmqYlaUTIuKWW79eP789pDQc5gXEteFe9sJt4Yxy9JKhtSNxBWgMQjhsNONKaTmcJa3vjsOjbLkxne2Uqt95loNtDS0MORe6BF4Lt+/MbQW0MZsuF4auDGI8F2nnW9Y+HkncOmFPuPUdjFKqVmVNUYbysZWOZ3QZZhaiaSilkyyik7gYTA0yrbc50XNk2lBozT9xKcX+VTKUEjFycLyee6NE7Za3lQtNY1+GnG41qtLAg9XgO9Co9m0MY3RV1rsb1XlscbDv/+jP/u7wHVIYhch2CBxylY2WrX3KPZdOlHAqrLZwLgT4gi4WFYcypI4dPnJzR7dMORwVrLVDfAFPDzP6cYegSO40Y/oRP5GkTX2XQ7nBcLAvO3v3+hF/NU7I46nFY4QfP9GyqcnGbNCgbHDLm0Mo07AZNVwdwz/6Ac7DBKP00VDrSUX85JcGm6PE8pak9cWDdMLPHYGlpx1exRza5jy8cmCrFIsK0t+TCKPcceaVd0eJtweJ0S+x++O5gTuWmhOsNe3eklFo/jzWwOO5gW9KORGL6RQht88meE7cLSwlpmuC++OEh7PCh5drEhDD791ufvBfkIjNZlpmOcNg8S6zAmslH3kuxSNIo18DqYFNwd23rORu9aaVSlZFrJ1szPktaRRmhutxH7ku9wZp2gDR7OCWhp6ccA7W11OlkVLcKz5T36wxzCxWfWiapjnNUnos7sTsSwlF6uK2Pd4Z7trNyxp5W1ujVJma2e3Nxjrdf3jn/7s7wadkPN5zmdnSwzgtu2NWyPrK37/bIVUmpvDmLxR1Moqsg5i61/he4LDmZXhn+cV22nIRasKbYTm3Z0Ov3w8QwhL2LzRj7gxTPAdwayQ/M27Wzye5ixLWxFudUJmecO//uTctoV9K53SSzxwDJ7r0gk90sgj9V36qVVTbpQh8gQ3hhEX84okgmHisag8zleWQKiMBm2NkIQQ7HVD7pcrq6XVsUPhUmki31YU98YdbrwbszOIeDLNkdq6IXqeS1k1BJ7HXs/j+ze6fHKyRErDVtcCR8rGChnuj2L++YfHXGR1Kydi4fSzvOFiOeXOtj3IfnZ7QFZbEzZXWNLe748XrEorx15ryzP7q3eGVozU2FZ5F+vjrozBGBgndnbUi+wBLIDTZUkYWCj8/jDBYDhfVHx2vmJVSd7b6TLNay6WVkLGj2z7tR97nC0qktCKtoJLIfVGnmQtzbPdCTeWtoEL3Y61QjCyLq+yLt+qw2MdFr1jM8laaQ6Ol7iO4Ac3unx6tmKSNaS+h+c5rErFIPUZJX5rVCQwCAax9R8/nlXMfMvaXTNfbwxi9gcxjy9yThZW/78TWZe2jw5ndEOf0LOfUzWK/UHMdjck9OyQvGgkQlixuZ/s90kCl/vnGdOsYacTM81qBonPj28OqNWU3x/lzEpJP/ZYVQ7aaDzPYeD4xFHAKAn40c0B86Lhk9MFw8TnImvwHZeibiilYa8f8eMbPQqpOZqV7A9jslaeY1kpwral57uCJ9OCD3Y6/Hh/wDgNuMhqlllB5FmpdNFmULLWDLshUegxy2uKRnNzmHBjGDPuRMxyKwESBx63Rym7A+tVTdEwiAJOlgWN1HiO/bxaavb6ka0Mp1YUrhd5/OrxjNOlJXQFnsNvDxecLit+eme4eSGmRUPoOmDswPsv7o6RUvPJ2RJtNJ+eLa1fdSEZtSia3X7Mbt+qj350OOfGIKYXf16511Kxag2L/hg8/KuMYRLweLLCGNEKVmq0sJIbYLPLvLI8lbNl1VaNhrKSPLjI+Ot3xiSByyentiK7M074q3dGPLrI+PXhHGOs3L7jOKiORQpJadgeWDDEbw5m1g89dClqj0fnK1aVot8JCJTi/X6PQepzlhXMSolRNWUUWCCC6+Ag+Jv3txgmFt318fGSVa1wPYXSdkieVYp+5LPViRh3LDGwEzpIZdjpxsSBy+nCbsKOA2ezmsBx+Y9/sGO91vOaQRwwWVZ0Aw+NZqdjPU/2ezFFrdgfJryz5XK8LCyKMXRxPcHDs5xF3iC1Ylk0LIqaRdkQBz6hB4M8wHEFP7jTY543lLXEaRMmgeB8VREEHonvkEYuh7OCD3Z7THOraOM6kDeavV60qQDXKNC8tnLzt4aJbQcLO/g3xuC4Dt/f61k4tWNbbIPIp2gUd8cpP77Z52heMllVeO1s6fYofUppYX2APL7I2O2FrKoG4XhkZWOBJ0peKVN6Kw8Pz3HY7VkfiqK2zlyOI2xP1PfohprY97g9jjmeWfmQTuxzexBzbyvlbFniAB+frMhqzaKouT2yuPSbrTmQ7zqM2ww49Bz2+hH/+v4Fi1Kx07OWno0syGvJLx/P+NmdIbdap7pV2bAsFYfzHCEMxzPLVJ9mNdrMkEbRqIRpVjFOI763q/n1kxnTvLHtGQFaWTMrSc0it73sxBesKs1O1+edrdDC8QqHcWyNlQLfwwjJ+arid4cN07yirBQeBmEMF8uaRhmrU7TdwXcEP9jv8/NHU0LXxfc9TuclhZSEroVUOgL2ejHjTsCPbvYZxD6/PVoQexYV5jl2vjNKA357MCev7AC9aqzXh9Sa26OEaW7hoqHn8HiSQ+t5cjwvkNrKix8vSt7b7hL7LqtK8eHhnL+4O+LmMKEXekyyGtcRjDtWVDKr7VB+EIfc6LtIZbh/esHNYUTSAksqqViWNcuq4dFFzt4gIg08ZMtfcTAbhN7XxcO/sjDQSOuUGPnWE36QBMSBS9j2tcedkEcXGVrDdje0ygS1TVbujlN6rbDjvGg20hU73YhBGvLTWwN+9XBK4nucLCtCV5BELkrDp6cZP7zZ52xeU9SSi2UBCLLaHiSDNGBVKvJKsmokoePSDy3fJ6+VVfhdlmDgd4fL1l7W29gPz/Patt+Ew7JseDIt2B8m9GMrXtiNrcJ0rTQf7HTpxgUHE9sNUMow6kY4gAbbUj1bcTQvmebWBfH9vS47LYT1N0+mLIqGQRoySkJr3FQ0NI2mMpoodHlymvNgkjFZ2kRuuyvoBKElkKYxi0ISeC4/2u/zydmKStYtLNpBK8Pt3Q5VI8kri2CMfPu7PCHoJt6Ge3Y5MRmlAQ8vMmqpOJhmNAp6sbVbtkx62O2FbPVCa03gCn52Z4iDQ+R7LYEwxmCZ6GulhWneUJ2tOJkXXKwskfS/8cM9Hl1kYKxSQze8EtAKeEsPD2vhagepTaMRjmGra3kYny0y+pGPxpa097Y7DJKASW7VY4eJjwN8epaxKiV7PZ+DmeZgVtJoTdFYvsUglQSezf4eXWTWwesi472tDmnkkdXKMtKTAIQgaxRKa97bsZvfZ+crRonH41lJXlvhQpHYDWteNIxSxacnS358q48rHELX47SqMUazqhWJ5+I7giDwOFyW7A5jOlHEVmr9Q6rWsU+IAN93wQh8T3C+UsyymmWt2O9FTERDGrrMspqqzf7f2+6wLBvujVPrZri0ZlD9yOd8WbEqJCdNZQ2zXCuueLooSSOXwe0R/+H7W/zy8YxaaXZ7Ee9td3g4yVkUDaVUDBO7+NcoEMcR9A18crbEFVav54O9LlWj+M2TOfOqRkuDFoIH56uN5WcSupus6md3hjy4yGi0aUUY7UHbjz9X6k0Dzzq7LSp+tB/yZJpzPC8RwH4/JgwcPjyYk4aeJVK6gne3Ol9QoL0qHv5VRdkoPjtbcmuUst2LyBtLho39iJN5wf4gbuXs+3x4OMdo2OmGdKIOn52vcB1a0IBDIxVpYGHpwGZGWEjNuztdosC1s4XMkufSXozSsD+IOF5ap0KpDH4r4rfIG/qpx++O5/hCcF5YqX2lNZFxKWvFVjdo7ZYl89aXZqtj3Q19T6CM1ezqRR6ni4rHFysOHIdu7OMIwf4g4XxRsWoUnTDgB/tB69ynCV2HXz+e43l2k9ba0E/91rXScqJMxxq5LSurlgu0iEU4zxtcDEHXpWhFCZdFTa0leS2YFtCJPfK6YZz2rekWUNSSh2crHk9zQtfh1ihqiaoNyhiqWhG4DjvdDoFrLa53fcsFmbWE47Xlw88fTalqS/jtRB7LQnGxrDjPav7q7ohVISkbDQh2e7bSDNyGRxcFnBmy2loxKwODxL5by1JyPC/wXTuzBGtMp7Xhe3td8kpRSet5b1RzXXkEroOUGu1YAl039qzDXysDPcsrpkWz8YAWwpC0sFZjYJI1rc6/S1YbdvshZ4uabuhjtIX7PTjP2OoE9KKAd7c7G9jtg0lG6LvkrVbS2bLm9ihGa2tZeb6s+Ae3BqShx3QlAMGoG7RS51ZO2ncEh7McpeHRRUESeuwMrDHM6VGB49iWWC4lMrNicufLmrtbHXRrXjMpJDcHEWUtWZbWz6NqUTV3xx1c16Ef+7iO4dePF9w/XbKqNePEykLsDew84MH5imESMjM1ujIMEp/zVYUqG8bdEN93MQ6MkoCy0jjCGjdFvsvNgW1fLaqGnW7E0SKnVgYjQCD4/dGCRdHge4Jbg5idXoLnilZGvGCR1USBgzY+T7KCSkqSIG1nV/B4Yvv7AKNOuJGZLmvJxcqSE9/f7aC0xcjLRPPOVsJvD2d8eLggq2wrIXAEO72O1SvqR2BguxcyXVlHvsvhuwIhxBsBmjjCttqS0AIvAFLfVkme52yUhAdJwF/cHXE4KziZFyxKyTJvSHyPfmgrMG1gkpUkUcDpwuqpPb5Y0UjFL5/MCD2HJPRII59a2Z55VUtGg4ShChkklqQZuALX9dHCkFeSR5OiJcza7dlxHO5tBXY9DhM0xroxIsga2ZLUQnqRx7KoSSMPhGB/GHO+qi0hVQYUlUJpK0z4eNq0rPqIstZoYThfNkhg5PoczUsMcKsfMS0rTpeVrZZWFd/b7XFzkFA2svXOsPfWcwVFqZHKcLwoEMIKcrqOS2MUwgnRGnqxjysEW72QXzyZ8ujcAkR2eyGzQnI0b9jqCsSqQirNn90eWM8NqQH7nFa1xBOi1QazDo2R77aoUIdu6DLL7ODcGMNOL6Yb+hbFKO1cZJpVNEpzsqi4M06RSlNpzfGs4Ht7vQ3X42xZ4ruWROq3z3RZNTyelSxK+0xGaWiRqN8BVd3XFpeZuHfGKUWtEAIOpiVJ2NALrYChZYoH+K7V8VFGE/kJ407A2dJaMga+YFkojuclNwcRd8e2VC2lNcSxaAlNNzKkkc+Di4wb3dDKL/Qs2qWUmmlmMzLXsc6C3VZt8+445fdHC0LXZkNHLS59q2PNjsLAtT4gpxl7o4hR4lP2I/5wsgQHepFH6Icsi4ZSWlezQeyTVVZWuqoazldWOjsOHKariodnGUZpBp2Q2+OEXuxzOi/tYZpLdgcRw9inbiT3zzLe3U7tEDrxKJWinGs6oYdSmkppGg1bUdC6L3pkleZ0XtIJLbR2uxcS+g4PJ5boN8+sCOLZouJkWTDNKrbTiF4S0osCXK9itxfheYLzac3BLGOrY3uzi6phEHkUlSQHBomdGR3NC/JG0UjrZzDPJY8nGd3EZ78f47kucWAZ+GvwxJNZQSMNM2nohJYwKjW4QrDXizhZWJikNPBkWmyIiGA1s4wx3ygEa72ub919hx/u9zialzw4z9juRlRS8WSWUzSKo0nBybLkRzf6TDJrZZpGHo2SOI7gNwdzbo1iK4+O4MmspBNItroBgSM4mVeM04CzrGJV2urivZ2UqjaIyOotlY1CKosUbFxbDY5in91+xMdH1vr5dFVza5iQtaZlyrQIt4uMQRJQKk039BmFFsRxc5DwycmCg1nB93c6RJHPrFBc5DWdwLHs+N2A++clNwcpt0Of86zkN09m3BylKKMtpFxrTtsDPy8V/8VnE/JKoZRi1fI3xp2Kj46WzLKKRdGgtGbYibg9jNntRyyrmlne4LvWobNWlqWvlW1/a2WtHO6fLvnl4zllJfGEPSSV0hRa0m080tBgWlHVe1sdIt/laFYwdBykMTTGEAdu2x61sOp5XjMragtgEYZRJ+RkXnAwzcnqhp1e3KKkBPN2xrfViei1rPRRJ6Qf+60Vg51nDpOARdm0EkkQBQ4PzysardBKt4jQmv1BggjT3pevxKfjrTo81qiUv/qrv/q7NPT4+HhBGvrcGkacLmo+W2a42BbFdjfCFWCMoJaSqrHqnDu9kElWsioUndDlL+4OySrJNLOZ9j98d4TW1sAlaBFK08wKlp0UDXHosyxsKem5gpuDmKbRlL6ma0zrZCetamxklTAneU3oCaR2aLTFeYct4ieJXFaFLYF7sfXwaKTCEVDX9oXoJR6hI/j5oym7vRCjDYtK4rhWYgE0k5W0M5/AttpmWc2nZyuWpbXuTCKHRdZQ1IpREiAch4NZwX4/QmnY7UVMVjX3zy2qatwNGKURF8uKWgoEFj0yK2ueTByGqZWiXpQNda3JqsZmS9qgpKFG42LRMqen1mL0xiCm2dOtVLjlWggsyTKrLVt3VTVs9yK6kc/j84JaK0LPRSvNP//olL1eiNeqPxzMCowRjDrBxk8hr+XGM/1sZQ8JDBzNcnqJz9HcqpXGrZz2Z2dW2n/dWqilAi2/Udr5el3/6M9+9neusIrOv15aWf2zZYWD5TOUjeTnD6f84dhaqG73IpQ2fHi45PYo5vY4ZrKqeDIp2B+G3B7GJJGVoG8ayU9uDSgbxUmLvnJdwSRr+Ku7I+ZFbT2vY595UWMMlvOQBNzdTnl0kRF4gh/vdzme1XgOBI71arlYViShx6JsuDFMWFVWpsMRttd/kZfsDxJCz0F4dg7WSMk4DljUEozi8bRkO7UEyD+/PeBf358wjEPSyOXheY50NNvdhL9/eEEpFaui4cnMysn3AlvNfHae2fWoNI/PczKlCB2b9R/O4ft7HnmlcFzRtqR9QmxCJ6WhkoZV1fB4mvGvPrlAGkM3dLnIJMVCMoh9kraNq5Ru4d4Vse+CEJwtSkYdi64yxvoMea5gXtQsioZGGz47yzBYsVVtrFZY7Dk8OF8xSAL2x3YIvtOLqKTeDOuLRmGwCLlnwR1Wl8x6xpe1phP7HE4lkW+r2XkpkRcZGP3lMtTPxFt1eFyOrJLWD7yS1C108YO9Lr96POXOOGFZKUqpCX1BPwkpatvvt9hqq67biSyL2XUd4kDz/d0uO13rgVArvRFUfHCecbbIOZxZZ7t5rhnEPsIVrS+FoKwl01xwdyu1VpGRx0/vDlr3NocbYzsctiqZlswT+x5JanvK1pqy4UY/5vEkI6tsfzN0HaSEvVFAWTd8cmrbX3u9kBuDhN8fL1iWEs9xGHd8tjoxrmPZwfMWS7/IJbEviAKLzFmUksgXjNKQ93Z7lLUkaxSDyOfeKOWdccKTac48r8mqxlZYucMHOx1i3+VXB1PeHXeoGo3QUNQNWa3QwqGorfOiI0G49qCMPOtFst0P+Zcfn/HD/R5x4HJnmBIHXusKKdrDx750Hx8vkEqTRj6LsuHB2YpFoTYWqY5r71tRKbTpWMWA2CPxrSaZbD0RThc2U1XatDLwgdU0EoLIs7IU87LGaSGxN4fJlcv7VxWeI6iVhZXfHMQ0yuC7gu2e5XnMcgm0G1Il8XMrH96NXLJasdMNmbsN97ZjhABXWOKmVIafP5qw3w/59Cxnq2MdGY2xbPztXkg/9TlfVPRjHz1IWBRWnHKQ+kxXlly6148pG00/CTmd51RKM5mX3Bwl7Pf//+39eZRkaVreCf6+uy+2m2/hsWZEZlZlZi1ZC4XQggZJ3QhaBXRJg9D0MEBXw2G0om76SI02pFFLoqWeKW0jNWoY0DJCG2ohGhCMAKmFgEJArVnkFpmxefjutt793m/++K5ZmHu4e7hHeER4RNznnDjhbm5m97Nr3/q+z/s8Dm+ujxmUyr9hnBFJHd9SGm7zbQtJwe1hRBKrqvOWq+yXXUvHLL+/KJdc21LCjLqmEvZNz0RKST+M8UvZ9bfWBwgkvmkwynKSRPmJ7wQpTcegAEyhHP5u9WIWcuUHs9hw6NYsekFKGOeMkpyNUYiQguW2jWnovLU2Uie6tKAXZjiGYBgWpWeHiV/kFNLAsTXe2RwhhNKFkwLeXh9yaa4OUlGQ667JIEhIc2iVRcVRkhNLVeORF6qG6fPXFY06ydypSd3WKKaQlPc95/rmiH6cgYSVfkg/SFhue3i2wc44xpOGIjTEGec6LpfmalzdGLFQs8kLgRD6sVRAn9rFI84K6o4xZZeAGvNWqXk1oTbGWc5bawOlgxSlXNsaM4hT3rtUI5OwOYqpOSY1SyctfYHTXOKbOlFecGM7IEhSHMukVSuIc8nGMMW1NDRdFS1pQhUQhaVMwShKSQsL19RpujaGppXFP0rGZJDmhEnBe8649IKEjm8p10GZUbgWxrzGOFEOgv0ww9U1RckbJ9Qci/Ndh61hwuurA3ShUbcNNENjaxBhGTqt0gd8Z5zSqVkkWYFrmkR5jq1rNFwD2zLZCWPiNMexDBxTp+cmWKaKrduGpkyyxgm+bXChq+xK31ofkpTFV3M1GymhQEPoMY1CMhjHxBnkBURximsZeLZOlBaMI2XgM4ozujWLNCuou8qNcX0YcXM75Kves8j2OGK9HxNlBUstk6KQvLsV0PUMbEtHQ3B9K6Dpm1Nb2XGccmW+rk6RgeTdzbGqkxAwDNUpTwiYr1llQrkgyXMVp5dweb72eDryDISAjm8rwc6mw9trQ+q2IgGsDyNA0nBUSEoXAk2okM9c3eZ2PyJKle6ajrrHy21VIW7oAsvQ6EU5bd8iK1R8fnucUACv3R5wuevz3JxP01e1Or/5yjzb46SsxI/UpmYnJE1zaq7JYsvFNpXXS80xqDsWH7poMooyBmFK07N5frHG+jCmYRssNFzF1opGIMG1deK8YBAlXJ6v4RgGQZqz1PIIkox+GGPrqn7kUsfjl69uMSxps56jYxs6piVYH8f4tlKXGEUJm+OUIDPxDV15uBcqzwFKLeL5hQa5LLANgzdX+whQpk22oYgiozECWGo43OwF5LliigVJgkADTdBKLc60HLZLqZxxkvH5WwM6rkmQFlxdHzFXt4jzgv52QCEL5usOc3WP124PsA2N7XHK5ijhbNvF1HRGSc4vvLHBzijltzw/B9yxVAZY7QVsjJJpseh6X+VEBHBloc6KqTxKAOqWCpvbhqo2dw2BaWlwzFzeU7t42IbGMMqmJw9LV1r6zy/WWS2LpJQ0gHIlu9CtMU4yFpoO7dSi5VsEibKmtQxVP3B9c0xWSDq+yZX5OtvjhDyPFT1PSi60PW73AsZxQqwJWr6FLsCxdW5tK5nzTk2J9iWZ5AtrfRxLYJkWmqbRcAz+07tbiDJWGqeq6HC55XGrp7yn33u2yc4o4fW1geqcRU6mqVoFU9NpOQZnGh7DICfVFbPFtQ3qlk5/rLM1jEEqn/dO3aLt24xDZe5kaIJxnODYBnGa8dJSm7ZvKcmEKMXUNVzTYH0YcbFbo5CqCtc2DCxNR+gaGirWujFKmG+4OKZGt5ZPd4WGruGZapIPUpWTSkv56DhToarrWwFNx8Q2DT5/o89c3aZhm3z0kqNkKMIUz9ZwbYMoUdafpilIJeWkCYsNl0EQY1sGtqmh6ya/dHWTPIeV/pjzrRqmIRhGGbks+KqXFgkSxbcPU8WQmSj4mo+HmHsXJpThD5f+7A3H5DdWlXx6lkkWGg4744RcSrq+WlRzWSixPttgfRQRJRm3i4LL8zXarsWb60PSVN3/d7eC6eny6uZYCRy6arf6+tqQMy2Xq1sBFzse5zoez6FkfrKi4NZOSNu38C2dXpgyHKZ3akaExouLNfpRytsbw1IuJKUXJNQdnTNNtZsukFyeq7E5TpV5lSZY68VsBwnvPdMgyRXh5db2mEGU4ZkFNcekF6YIDUwBnmthCI0rc3UGYcI4K7B0g61RxKB0YZSFmtA1XQOhoQuJJiRhVnCmpcJBNTtTk60GW8OElucgNNDGMRuDhDNNt5TWSZQxmW7gGDqLNZu2bxIkyixNoGHpgrmaTVYUZFlBIgRCCGq2qepRgpj50rDuTMPl2taIXhDjWdq0+NixlIbZG7cHXJ6vEaU5lxfq0xPIrZ5KjBfl3GGYgjCF124PeW6hzuX52vR1v3Ztm6KYbKZV8adnAVp18iDNFcvgrbXRVJo7Su9IbJ9pulNTqDDN+chzXebrDte2xmhCOXv96rUdlhoOXd+iH6gj+rmOSy4LorTgtZU+eumTHmdKQXNrlOOaGjXXYBiWeZKaSZjkvLU5LjuQnMbao7SgF8TYplLGjJIMUI5irq3TD9Ppzm6x4VIgqTsmNcdkcxxzbWuMECpm6zkGSaKMp4ZxyiBKWWpaFFIRAwZhoo7XcUZWFGUCWVEjz3c9euOYjXFK03N4z1KdSx2Pbk0NpJ1xwrubIwSCQkpsXS8rm5VwY5oX9KIUp8znmLrGha5HUUAvzBjHOQs1i2GU0fJswjQjTyVeKU45UbDNZaFOWZrGTpDSD0ecb3ss1B1V/OgrfxYpBc/NqQnu2nZIzTZYqtmsj9LSG15DExKEzpdd6uBaOp+/MUDXdOVWGKT8/PoalxdqvHymwVLDJS+k4sjLkvGmi2mO40HtOh8WllsuYZqzM46Vp3YZbpW5qv+QhZp4NoYRjqHzwnwNBNzYDhmFKr+lvt+YpmfR9S0cw2AQZ7R9i36olGlrttJuS9OCcZKyOhD0QkWDrjuGKkodJQzDrDwtmnimgaZB07FYH0VsjBIKmdMfJegI5euSKdvX0MtZarrY+ohYEzimhi50ciRNP0cDbNOg5Wm8uznG1HVanqqtCso8FhJeOdfG0pWWXadm8u9+Y504ydgehViGqnC3bMEgSkBoFGMVVZAohuXZVqFkQgydt9dHJFLSHySlGRpsBxmeqTNXM1kbRIoqrwt0z8A3Dc62XcI4ZxxnRElGnOQUqPHe8CwGYa4IM7bynt8YxtzcCbndD0iSnLqnIgxRXtCPU0yhYRk5jqlhmwYSgWEItoOE9WHM5ijhykJNKTvoSgXcMXUlayQEpqaha/kuO2bHVLUpX1rpMwwLFmoOt/s9BPLYubxDFw8hhA78USnl/+t+O/ijxNTr+bnLgIoFrg9V1aVpKK387bE6Bk9Moa5ujGYEEyW3+0pQrW4r3/DrOyGuqXGhoxJ9UZajC2W/+fa64tx3PIvtcVwaP+m8sNhgZxwRJTm3ewnzdYuWa2Jo8GvXtpirO3R8i4KCQZxy3vdoORZvro+Yr9vUHAPX0BBCI0gzNoOUl882WelFpXQEXNsc0fYsXNtA08RUSvrN1REfvdzlYtdlJ1KS5x9crPPmusQYqcSloQtyqbT+O57Fxa7Pqm1weU6nVTPQ0TB1Dc/WWe2HWLpiKvXDVNlsmgb9qCDNcixTDehRlHOx67LYcBBCWYkOkwTXMGi6Bk3PUoy0tkNvnLIzTphrKrfDuYaNRDn6GbpeLiCCcDVjO0i4KEATGjd2AjqexTjO6QUpCw2HjmexFSQMQ8lLS3W6Nbtk0Emem/c431VyLZah5PFfXy1DPYbgp3/kB5j75B9ivmYTZ2JqtDSp9p3kOPaz6H2UmPTrS89dnsrKT9p1Zb7GiqlzY1tJbC+1XOZ9i41xwmovZL5u03YsdFNDL021Xj3f4rXbA9a3Rlycr3HhgocuNLaDGB1BlBusbI9Ltz1BnOeK7lq6Z765OuTVix2STNU9vb46LPutqTzHs4Ir834pR57T8lQI8vXVIZ5t8cGLdYRQeUlTU1YAuibIEWyPFHXV1AUNy0RI8GydMw2H9WFEkhWcabrMN22ipMAxlJf5UksVADqmRprrXF0fk+VFKZmiM+db1F21kfviSkaeSzRDbRB826Bbs5hrKkJBzVG6be9ZqPO5mzvEWcG1rZCWryMBx9LJC1mmPAVnGw4fvNBibZjgGKpuIi8KdF3DEBDGObd3QjaGMY4pWDRVznAQqKLBhm2wOorplyoSMofFmk0hoOFYrA1iOlrB5jjm+XmfrZHy8hhEKUGS88bqgJptcmNb1aatDUI6vo1j6Zxve3f5eUzMoYI0Iy0kHzrXIkgLENrJha2klLkQ4uuBJ2LxmLBSPvihj3x7kkscS3VCy9RZLt28rm+N6fgW4zhTu64gJi+UzerGUAnqOZaOaxk0XRvXKshlwTjJWRtGDMYJWdsjLyRCCNb6yjin7dkMo4SdIGWhYdP2GgzCmCBW7KEok4xi5SU+jlO2RhG+bXKx63Ox7WMaGmuDEMcy8C2DogDHUjkb29BVhx73ybJCUXOHMXVL5/J8g7NtRXl8/XYfXVciZ4MwJctyzrc98kLlE+aaDmc7Pq5hMIxSbmyN2BolfNV7F7BNndt9JRcyznNMU2NnrFg1a8OIN9dGuJbyn84yVScQS6nknDXBUsOiU7MJkoIriz5GSZ0UmqBmmDw3V+PSnI+lK7npfqjokBOfg9dvj0hyyfNNdQowdUU9VPV5EsdUsvca4NuCXiAZRxnPL9Q4P+czCJVLXMczy0r8iOfma6z2Q3713W0cQynD2oYyMtJMnc/+x5/lv/mDf5S3N8d88FwLmHHqO0WY7deTgsVZyYnZkMTWSFFQNeCD59vUHYO3N0boQhWWTRZCUxOcabu7PmvbtdgKYm5uBawOYrI8B3SubYxpeSa24aFrStInzwvi0nnRNlQ483zHZ6HhsDmK2R4mnO26XJmv86WVPr6lU7NNzrZdNE1jY6D8VbottfGKkoy6rVN3dFqeja4Lbu1E6ELywkJDncyzfNoPhCaIM2VxcHMrZKHl0HQVLX9zHBEmkueX6ti6zuYopuEahLEKA7//XJMwzpBCyXy0fQtNQNe3KAq4uRNQ98pEtoSsyMmSnM1RxHzD5lzLIYgLEPD8vE8pK42jC1a2lXvic12PpqdYVYamoQuB7+jowFpfTe6mrpEVBU3XZtkxSrOogvefbxHEHq+tDMmlxDYgzdQirIQVM3ShLHG3xzG+bRLnObmEYUk/HsUZFzo+vm3c5edhGUqIsZabDMMhz83XcC2DIglGx+mXRwlb/YIQ4m8B/wQYz3ToXzvOhR41bEPj+lZAkORsB8p5zLN1LF3jtZU+5zs+nqVTFBZvrw8pUANSk5LtYUTdtQiTjKWmw+1+xPXNMXGeq0p1ATdLb+OmqxYiTVPUOMc06NZs+kHCKEo511F0ybmaxVo/oF0uBnkBQZzyFZe7+I7JYkNpOm0OY2xDxzYEcaaE5ZbbDu9ujsuiozbjJFVVvWFGnGW4ltpddWoOjqFCUe850+AD51qsDyJ6YUrLVaY+plAhLCGgW3fIspz/8NYWbcdgseag6YIil2wPY3pBQtM1S29slShNkoK1gSrC2uiHnGk4bIxi4lSyVR6bV3YC3rvUwjRMTENDosyWlpouq/2IFAiSlJZrU3csXlhs0K05bA0j+mFCmCgpBg3lwfD66oBmacyTAbqu03AgziW6rjNft3jPgspBNVxL0bDPNPiNlT4boxi39D25vjGi7ZvkEmxd58X3f4S/8z9+D6/+n76W9ocusWaoifXDH/4wsL/P8+M+hYDi+QfJ3azKOwufyo9NFppJJXkvSEoaNOS5xDL3bDQFRKVulWsZLDY9VvuB8lkZRJiGznzd4fK8yyBKaLg2RVHw3jN11ocJaaZyi/O+zUBPeWW5hWPqLDYctoIEy9DYGqkkuyaUZH9S1k2NS8O2sx2Pm9tKPTZHKr+XJCdxlFFSL0y53VcGZTVLJ04laIqZdH17TD9IcQ0V+7c1Vcyn6xpXN0boYqLirHFxrj6VK19sOtPi1MsLtZKhmDKOcy61PT53q0ecqMmZQrIzVmSDtmtRIGm6Fq+vDUoFiRpZkWNoeskCUz4btiHYCRKSXBm5bQ4jzrQ86q5ZKkOrzy8lvLhUV/pauTrtm5qSeFGboQjfUkzPlm9ybSugbhtKNVnTSivrkk2ma2wOorv8PGYVE3zH4GZpKyx081iS7EdZPH5z+f9fmHlMAr/jOBd6lEiynEGY8ub6EFNTIY9rxYg4VTHNySATQkkfWIbOO1sjDE0p0C62PYpCPdcoxfZMU0PTwLU0okwSJTlRmuEYqpbi8rzLSk9VpvqWTsvzudkLKQrFzmrYJpfmfNJMkhYS19SQhsb1rZCzHZAoHwVNqB1WkiuevUCw2HD5zLUdWq6FZytZjlcvtvnSzR12yslWIml6Oi8vt/FLBk6Sq6Sd75gstxxev90nSFWC2NJ1mr7FcsPhrfUhUSFZsJVUc26AnWW8vTZivuEwijPmaw4Nz1DSJnHZoeOCugO6rqFlKVEiSbKC1X5EnEleWGzw/GKNrZHKzyyUOaSNYTT1NGj7akJeari8uarCS5e6Hq+tjMiKjC+71OG1lSG3+yHvO9uiW7e5ujEm0TS0VEnbbwxj/FKGflYzyHdMHMtAaHB9M8A1TcK0oAhT6mbBtS/9OpoQ3HznTf79jyhWnhCCn/3Znz3Q5/k0nErSfLfU9l5MfBsmaPuWInJEBbIhGUUZaVEwGKtNT8c30TVVWNb0LHphwnzNZhCnvLWWg5CkpfdGxzNpeC66ZvC+s016QUKcFpxtK7e7MM1JskJtInqhoqRGqo7qXNvljdUBO+OMhZaNZ5kEifLPWOuH9Er1ZdPQSPKCIMy4ujnmQ+c601zkyk6Aa+rYuuD2IMbSBJcXasjSCEzR7JXacD/OMEYpNUej7ug0HZOkkCpU5Bo0bCUsuDGK2BmlapNRqOK+YZiWsuwaLy83eGt1TJhlxLnkctPBtXRqpS1BnCqWoudbvLjYoB+mJJmy5Q2SDInkRk/J4Dw351OzDVZ2Atq+Rd01uLoxhkLimjpxWvD2+gi7zF2/90yDceIzCFI0TS0YUkDDN+nULDZvDwkTdWKZWALrmhIwbXmKiLPXz2MWDdvgV1d31AJzzOLXey4eUsqvOs4bngYIobSW1nsBui7o+g5xrqqjR2Fa+iIrJy+nlBKZr9kst70p718WYiolUnNMNCH59NVttsZqh6XkNkL6Qc4o6iNRVbdOaT/bcAy+/tWzvLMxYr3cxb+w0KAXprR9lWDsh8oG17d1rm8GLNYtXjnXpBekvLM5IoxzBkHIZ67DdpDQqd3ZGCw1XbZHETd7IcMoUUyNZo00L0qnM5X4lFLpEYVJjmOZaAgano1haNj6JAylOOpKsluj4ZgYukYqZcn5V2G0nXFS0i5N1bk1HQqJqWlspgW+1Gl6BlkuGUYpO+OIN9dUBzV1VWF7oevzoYudKUd9sgsKk4y5msPaIOLtjZS5uknHq5EV8MJSnVGcYhk6UVKgoyjBHd8iTpTA4pdu9/ldL5+Z3p84KyhKGfe25+CeMdD1IW+sDrAtnRcWa/zgP/1xxnHKhy52pvarE+y3S5s8/vig6mI2hhFtzwKCfU9DE9+GSZuVmqrDIFIy4ztBwnvONNgeKgbS9S3l+d7xlPrB+jAiSDI0lExLlEqSXEmV+K7B9jjl5WXlHulbBtujsTKbcgxGkarwXyxP9jd2lHfHQsMhiHPOd2tsjre5tjkmahY81/UJYqUXZ2gan7vex7A06qZOmOSsDkI+cr5dnrJzFhoucZbT9m0kgrqjBAHXRxFSgqULNgcJiy0H39IpioJhmGNqir77ymIDy9RI0oKVfsC1jTELLXVilwKurg949WKHN24P0DXBjZ2AAnBtjaWWqmNKc8n6UIWNfEvlQc60XIRQJJKmC2v9iKwokLIgTCRtz+JMU1nLJpnkUtfHs3WGQUbNVu5+hq7hWkr+vSgKLs755DlcnnNZbNi8uT4iSpSsymLdIUiUG+LNrYA4VwKIQlP1SR8430BIVYqwX7+I0pxekHBtY6xM7gQnT9UVQjSBPwd8ZfnQvwP+gpSyf5wLPUoESc6/f2ODumPQKZlLhQTH0Nkax7zsqRzH5Bg/e4QXwK2dkH4QYxoaHzjXwjZUAvnLr3T55be3sHQdTcBcqaobRirf8NxcnVdfbE9DAwAtz2KlF/Jr17axDJ0XlxxubCsv9Usdv5QhUTRi3dDLI67OMEx4JwpwLOWnvdxwuL4TYho6DdsgSDJyCV92aY4zTYfNcULTVieqzVHCZ27scLbpcq6rkqGWIfmKK3N8/kZPFVSNY4pCsDlSHu+WqU4dozDh9ZUB/dLlTIXENFb7SupZQxWrpYXkfNvltZUBG6OIOFVVvbqmXiM0RRVc1AWDKOW5eZ+WZ0137t2azdX14VSL6ku3B3R8m694fo61fowQyk2ukKq6/d3NUSkambA+CDnX8Wj7NnGmtMbmGvY0EQhqoGhCEMY5vmNQs01eWW5xruUxTjJu92PC0Yif+od/m+/+1V9GCPjtv/2382f/7J+l2Wzuu0s7KFz0qJAXks1hxMKMmN5s8nyCWf7/hDWmCXhlucVWmRC2DGUytjNOSkE9jctleOP61pjVQrHsXEtHypzldo0LHa+U0UhZbrml3L7Ohy52GMdqUutHCec6d9R7pUTJpI8TEGrSenGxwe1ewLmWR5jmvLMx5o21PttBQtOxyPKclSBjECc813a53Y+U8kKU0vXtUmZEueWtD0NlIR2lWIZi/o3ijKIX4Vuq2rtTs/nwxTpzdZeaY5AXBSu9kEGY8OFLLbZHKeM0Z7nh4lg6W6MEQxd85noPhJKSd2yDt9eHdOsOdVuRLzRANJypbaxV5j5sQ1fePOMEmasQ3XzNxjaUrphlCM40fWxT59evbSsxy6UGgzClAGq2QZxLOr7N5jBCF0pTa6FhE6fGdCFeHYRowELLJUpyNodRSRhQcj1ZUbDc8ugFCW9vDNkep0RxxtmOS5JJNCHIZMFSQ7EMybP0OP3xKGGrHwS+AHxj+fs3A/8f4BPHudCjhC5E6UUNqQSzkFOJ7nMdxSmXhSQqVFV50zNLu84xQZSyNYrJJSw21eSVpBmhEDQck0tdjyDNubkTslBXsVLPVBo1Xd/m6oaSEZgM5klC07N0Pn11i9s9lZR+YUFVTy81lRLqQt3m3c0xSVawPYoJM1XtutxSC1GWSbbDhBvbYxbqDklW8PKZFi8tN+gFCTXHBAlhWvD8Yp04LwjjjLV+hBCCuZpFx7e4vODz+Zt9LEOj4xv0o0yFrFyTUZxxbTPA0JUC79mOx1vrY15ZrvO+sw22RjHb44RzXQ8K5YBoGRphqRzqWzrn5lyV0NMEkgKz9FZxTYOdMJlKUCMlcS5BQj9QVeZZLtkcJoq3LyS5lJwvJ8azLY+ak7CyHVL3LM61PewyRxEmis45yyrp1uypHW2Y5Bi6IEpV5X/Lt2i4Jt/7Rz/JC+99mb/2d36QpabLP/2R/y/f9m3fxo/+6I/etXuHe4eLHjZ0TXCu4+97GpoNpx3GGptdFB1T50xJTw6SfNpnX73Y4TPXdrixHdIwTC7NmYCqS9AQU+n8yf12TH26aF/dYNeiaxsaQZKx2o/wLIO6bbI2CHEtE4lka5TgOzqLTWWPcDsKcCyThqPjmQ5hpiqxX1xqYOqCjaE6+fWDhH4QkWSSui1plt4WwyhTNUNpThhnXJxXDMCmb3OhqybSVELdNimkYBQrh8IXF+vKj7woeO32gEGgTsKerXNtOyAKUnRNEKYZmlQbx4ZrKdMlB3TLoBfEJGmGaarN5qWOR5Irc7HNYcJWqSJ8bqbw1Da06Qn82tYYt5xLNKGiC+fayqAtSHK6nkWYKTuJhmOS5gU3d0IutF1MQ+PmjsmolDnZHidcnFOnv1+/to1vmyzWbXqGxq++q1Q2FhsuZzselq7stdH0Y5VuHOXJV6SUv3fm9z8vhPjMcS7yqJEWSu1znBYYUjF16pbJOFHGKYsNt7TpBE3ABy+0+eV3tuiNY4JM7aZsQ1Fat4KY5aY31ZMydI2ObeDbJklWEGW5KhYslJrvxPt6djBP6HFXFmqs9EJ2RgnvbIz56OXOdMDqpQfJ+jDkzbWRkkZfUFXN6wNVC/Jc11dGVaUrXt01WBtEbAxjFhtqZxOmamfsWzpbw4jnFxoYuiDLZSkpkvGBc22SXNWmrA0T5mtKSdfQBe2aiWPoDCOd8+0aaVFwexDx3FyNTs3mhQW1MP36O9u8uz1Wsut1G1PTaNUMXMOgXyQYmipii9KCtChwQ1WtXJT3/LXVIeMo5eKcksTv+BafvdFjaxRTdw02Rwnrg4gXF2okmSoEfGW5hWcaiA31PsMw4VZPqca2XJPz3d0T6JX5GpqAL97qY+oaiw2bXOXuWag7XHv3HX7wH/6Iik8L+HN/7s/x6quvAvvv3h93zUch2Vfl9/Dk+W7stygOo4xBlHB1gykx4Dc9P4djKQpwo6wByXLJ1Y0BO2FOkOVlHZS96/Sz9/1bnsXVzfG0kFYTkBaSM00lKX9pzicrJDvjmK0gxbUEnibLgreCQZDS9VVh7jBMcY0E1zLYGsbohsHlhqrTaJQng3FS0HYtanWDAsF8XYWTRmUOY7Gh1KLHUcrLSw0KIUnyiDfLIkjH1OkFKoTb8Bw2hwltzyTLcraClDMtj8sLtbKGQtBPc6SUioGVFKwPI1Y2x+RSLXCb45imYzNXt1V4CMEoViG4qxuAVMWJDcdUbo2BMp9quhYQ3pXLmzWO6tZsdsZJKd+j5g9dKMtsQ1MSNr90dZMoKZAo9eOObzNfd1T1uYA0k2wOAzq+dWyfmqMsHqEQ4rdKKf8DgBDitwDhcS7yqDDhw8+fvaBsHMMU3VLi0OMko+5YLNRVUrrj3wmhbI1ieuMEXdOI0xTDUklpx9DZHCRc7PikueBs25tOKrcHEVc3hgyjFFPXVTI8l2RJpqSOZ9q1VRYFjmLF1mr7Fte3At5aG1O3VbJyEKUIqZzSNAS3+iHb4wRT00p7SoGmlWb2Eq5ujpir27imCnFFac7ZsvOD2iUbhj6xLSj/F4zilAtdT8mxxEoOPcskea6KH891vDIs4LAdRMhC6Xh1PEvJY9Rs3tkYkmtqh5nnBq6pEWUFvmORZErOxDY0arZOmuc0XVuZPdVsVvoBKzsRozij7RrsjBOyXJ0ALVOdYkxdp13WBqz2I853NIRQ9qlBmrHccnlzfcg76wENz2CxZpEUSgHgTNOd7oIdU+elM02em6tNWVPrg4illpKm0U2Lf/VT/5aP/aavwDZ03n3tF3Bdd/ra01LzMVvnsXfiH0UZ/T0T/2Ft3LsoDqOMm9vj0nUOVnohb64NudDxeO+ZBnXXJIgzwiRnpRexE6ScbXn4lsHaQN3T5abLyk6AXcqK7wQJ83WHuqNUrH1TKRtf2wrKXbZqf5DktFx1+rzVi2jYOuM4ZSOL1CToWAS6YjwWUoUxhQa9cUIm4TdfbHNhrkYvSCgkjJKcUVJg6Bp5nuNYynhtYxjxvuUW68MQzzQI0ozzHZ8wzfi519fJioJhUCo3uyaOrk4Deeln3/bVJmgQDjnfVp99FGecb3qcb7tsjmLm6q7yMpfKeiGXBe9ujrB0jZ2xYmbGaY5paNzYHvHq+c6UiBGVFF0hBDd3xriGyQBl32xo8OVX5qbf312bAinZChKydEJDbqEJQZqpRWYUpXR8m0JK1gcxCw0b29B4Z3PI2bavFhpdsNqLTrbOo8R3An+/zH0A7ADfcpyLPCpM+PDPvfT+b7d0nfNdn7womK/ZtDyLxboKQ5mlsBgwZdRYukYgMyxDo+EqltXWKKFRxpYn4YpZK8eNQUwmCxqu4N2tMYt1l6WmTZDsDh3GpRrsZIcwqcC+tROWk6OHa2iYZYK2U7NVpx8l7EQJZ5oO/SghLSTzDZvtUUySZWyNlEJw3TW5vqU0cr7sUpckK8jygpeX6kRlIZdtaJxru/TGCVFasDWOGYRqQV0fhqpCPVcc8rwQhElMIaWqGDd0bm6PebWMbWcSXlio4xg6a4MQXdNwDI2aY2KgcW17iKlrioro6GyPEn5jZYBtCBZbnpIAzwU745SWL5ir2/zS25vM+TbNpkXbs0nynKarFF8nPh1FoeoKRlGKQON810VKDSEKXp6vYQiNtzeG0wLQCfYOuJtlwdZ3fs9f5q/96e9iNBwggcW5Ln//7//wga97XJj064985KPfnpQJUFMX0+T0uTI5fVAOZD/K8SRHMYgSzndUndGkILThmmwFSifpbMtlHGfc2A7K5LRanIUQ+LYgTHO2xjFhknNloU7btyik5DdW+ji2QcdXsfrtkapi3xyqYtproxGuqWobskwSJykLLYeisBlFGWFc4Bq5WvwXaqWrpDoBy45kdRhO57qWZ7HajygKmKuZ5AXEuSqc7YVKdUCiLBTiNFE0X8dgq5QFGcQpUgrCOKPpWuSWJCiZfIauKPNxlnOmZVMg8S1VVd92LcZJSsO1MHXBal95nLiWTj9Upk0LdZcoy4nzHKHpbPYVpfb1tSEA83WLjqcm9IajNL6U34oK2w6ijM/d6HFlobbvxkB5nHOXKoIojdqankWSKfl3KOgHKXFa4FjGVNjV1nXm6hacpBlUWWH+f5VSflAI0Sg78uA4F3gcMDWNix2ftWGIoRt84Hx76rIGdwbT9a0xhqGxUHewTZXkbTsWvSCh61vkRQEad4UrxnHG2Y7P+V7I9jhG1zQEkn6YsNiwp45dE9iGktsoSlFFy9DwTKVo2iyTyFc3RtOQhGPqXJirYRkBX7g1UAlNy+BszaJmm7yxNlQ6/p7FzigppQhgEKgdYsNVFfGmodPyVQXv2iDkc9fHBGnGYD1lGClapARc01BJ90HEr17f4WzLo6DAsxRP/ZXlJoahsV26Da73IjRd4JSMrWGUkeXq6D3ftPDcFpe6Hv0w492NEWFa0PIN0gK2xzEIyVzNYSOOGEUpF7tKjjuXBZZhlclyhyTLeWtdsdVcS0cXgkwqmvTN7RELDaUO2605SghPU1z6gxCVyfnNYYypSX7ux3+U//kf/xRGEbPUcFjotu8KN56mOg8xo6a6X3J6vxzIfpTj2QLDSY5itR9h6YptJ6UkS3MsQ1d9vaxSFgJGkVZqOSlRyaSQrA4ilptq5319O+DWToRpCBq2zkLd5TdW+qyOIuZrDssth61RwnYoaZen+1vjgAtdnySX3OorX3VbVxGDS10Pv2SAFbJgfaBsded9izjLWR9GnG971GzFrNoOMvTScjfJlC3uOMlZG8R4lmJmXd8KqNkmKztRKaGiFoKGY7JQt7ndC3hzIyVMlI3BKMlpuSZffrnDMCqI0gzfUgKSbd/GLUN1Sa4Kii1NsQJrtqEsoyUkmcTSJe9sBpypu8zX1X1eG8RESUHDNbixFSAF1Gxzyrqq2Uo1eq+ywOS73RrFJLlkbTgmTZXA52LTnea2LnZ9vnCzN+0fgzAlSDPef7bJ5jhiHGdK2LRz/E3SUSrMP1L+fOoXjQkkarff8eyyMvbOaWx2MGmaUh9d7SuWQsu1iPMcK1Md17V12p591xd2fWus8hxSqZiGaaF2N0IqG013tx+wbythNtswqDkGcVrQG8e8WDp+RWnOThBzfVO5ETqmYsJ0aw5f9ZJKaK71IzxTVyyKrKDbdErWU8H5tk8uLaJYeVFMdPyvrg/pBSk3dgLGUY5jqaTnVqCMgpLMoVu3WWo6CGAQZbywUFO7wbQg0ZQlra4pMcMb28rCFKE0rvphhqYLWq5OL1IKuy8vN+nWYBBmbAwistKVr0ASxpkiLkQZjqEWL1ChlwttD88xVW2NpsKMN7ZD8qI0syrZOot1m1wvuNmPkVJgGhrDWOkqnWkqFtLke9o78at8iqUUTbOCN177HJap03abnOn6u3IHUZrz9saIIM7KWL2SxL/ymNV1Z09De5PTcHcOZD/KcZzmfHGlR9uz2QliisIiKc2OQDno2aVEyOS9bEPl83xHhRpByffnUpJmBQ3HYLUf0Q8V9VQIwUo/Yqmlivyatomlq/qNpabLc/M+AsF7zzT4V78WMkoyCgkvLzYQmmBYkh1eLUUgf/nqJqu9kBxBzdYZZwU6yr1wZ5zQD1N+0/Nz1G/1CRPlwjcMUzbH6qTxxtqQYZTRdEzm6ha3dgI2+hE1V8fUdUZxyjhJ2QlixlHOUtPmV68FREmBbUC3bnJjO+JM3eE9ZxqAIEhUJT9CMAyViZyGIMoKJBMP+ZStcUzd0dkYFPTDlJZrsVlSvgUQJTk7oTKh8UwlhX91fUyrJCYUpbfP5Ps82/Z2zWOuqbFV+q+cabnomsZaP8TQlIbY+861uLY1ZrvU8ro012AUZ8z5DksNlQ+dEBGOg6OErX5dCPFjwD9jd4X5jx77ao8IuhAglOfwxTl/16o9O5iUNa0aUMMIlloO/TClZimDer8smptMQgD90sL2+vaYIM3Js4KzbR9dU0KHozjFt41dxvZxmvPeM02lARWX4mp1h81hjK4J3lwbUkhYH4RKaqCsNN0exXyoHDy9MGEYK9HBjmdxuxcRZykNx0YiibOCpbaiDW6NYro1GykEvUjlQzQNhnGOZ5u4hkbTtxlGGfMNB98yuN0P2RhGND1lVnOx62MZBqB2VAgYBCkvLTfJCvjSap8sU6Y+CPjAuSaXuipBHaVKcC+XkiBOWe0H9McZvmuga5LtkXJLe2GhRrtms9hwlHbXTsA4zUkyxRapuwbjKOWdzTGOUfo6R0qOW+ZKVPJsy0MWkrfWhoRpwte9ev7AAr8kU4WfpqExjnOuvPd9/Pk//K38jq/9Oi4sdBACPlOz+cQnPqGIDeMY3zKnhIOdcczKKagwn+AojLBZdtXkBHpzO0TXBF1fOTi+tTEiSjMMBGZ5wqu7BlfXR9iWRpS6U9WE7bKQrx+o0+t8zebKXI1BrEK+hZQ4hjqdeJZaaHRdbTYWSt9tgCTNGcaK2Xhlqc52WfczClM8W6fpWbx3qX6Heq2rsO6cp5SqgzTnxk5Ip5R8n68rR71Lcxn9IKPpKptY29ARqGrrKMlIspxCFjimwULLZnOYYJtMN5JrfSVB8vbaiPmaQ9022RhH9EYp7112MU2Nn/2NNTaHEU3H5P3nWlzo1pBCULMN1voR66MIz9TYGef0o5g0K9CFCRScb7ul/TWcbbvEacGbG0OuLNRwTYNrWwGOqaSStsfKSGqurqjqk+8QIC5PhpahaPS+rcJQawOVX4mygi+t9Hl5uUnDMXnvUnMaQVnZCRjF+V350OPiKItHB9hid0W5BE7t4pFL5ZplaUr6eHbVnrhvrfZjRnFKL0hL6qGaIHxL59xiHV3TGIYJiRCY5ST09vqQWz1VXJhLiakJdENnO4hxDB1NU2YzX1rp7zK2v74dcGnO5/3nWqoiNyuIU2VMvzmK1fE6KUotfgNZVplf6tamtQuvLLd4e2PEzjhmsemUrmMRhkiJUouWa7HYcKe7xa1RTMMxmas5CNRjWpyx0gtZqNks1m1u7YSsbAcYQrDWi+jWlRHOMMxYHcQsNVTSsOFa0+rjmmOwKG1eW5EUUmDqAsdQBViGLri2FUwnq36YcnsQk+cqbCUEbI4yfMuk65lEaU4QZSSuYqxNfEMm9QCKQOCwszYEcrY2Y3RdsDaIOdf2qDmKXjyKM4SQ9Mcp2+OEnSAulVB3U1p7YYIRqQKxJCsYDXbwGy1+8f/4d3zRNamXxZGf+MQnWOur5KpZvodpCDxpTD0RTgOOwgibLDCFLKYnA9dUp+61QUTbt7A0iKUgkQWjcc7OKKZbt/FMnUtejVs7d4oRiyJhZ5TQ8ExeXGpMqeS/9PYmDUedLqJUmarN122SvKDtWawPI9KsmC7EQZph6xqWocT7ZKGq07O8IEhzFmrm9FTumDqJsv9lsxRH7AVJeQqGOCnYyiIkEgGMk5QwzbAERAIkYpqLSbOcPJdEScar59vc2Bqr6u9CjWfDECRpQS4FoihYH6k6C7tkYb12a0AQ51iGquv4j29ukOTw/EINXRM8t1Cj5avQt6FlrA5yLi/UWKi7JHnBuxsjFuqCcazUH7JCbb7itMCzYLUfUEiBpUs2o4zFpkeaF3zhRh+EohQXkumcAooy7Zo6caZIDZfmfLq+BVKq+54ravo0giIE59ru1IFwkg89Lo6S89iUUv73x37nxwhDE1zs+OVuMeFM686kipTc7EX4tkGzTIzf7kV0fYuzLacMyaikulPGSCeTUD/MqDuqHmGp4bE2CEEW5FlBu+li6Rp5Lu8ytvdtg41RzIWOP3X9+rXrO9iGRi9McQ2dcZLRcU2Gccp7lhrKg8ExpmEDx9RxDY2gPNZemFMnoyRT8uoXuqpjJJPTTrnjnNCHo6RQFqoSUikJM8X8MHSNrSDFdzR0TWcUZdiGwLNMNgYJNVuZNXVcVX2c5qom4Lm5Opqm2H2ijNPe2gnYHKqkZtNVXgWWGKM7BnZ5ijE1JbMw33CVGdAgYpTmtGv2ncmv5SrByhx812JlELI6jKAAISQGKg8V54KLXZ9CFmo3laiNwWQyscr7H6U526OY7XHKrW0lSrdQN2m0uvxf/sj3sFiG7iZFclCyFvduxsSx2YwPFUdhhE0WmO0gUQtMWiA0qTTaEFzbGtP1bGqupOWZZRGsNjVBGsdKpftLK33OdXxeXKpPv6fZPOKFrl+e6lVdx1zdVpN8mFDkECUZb28MpzUhbd9GQy16QigCyeogZBQlNCyTF5fUBm4SMZCoxUMIJaZp6BqGoSE08B1DyRGtDllueZzveHz2Zo8wzWi45pSSahugGQa6Lmh4pirYs3SiJMM2NTzbZNn0eGN1iGsqh0NV+aBcJ19fHaJrijlm6BqOoxQrXl/rs9SwidKccx2/tH5WMA1V5KtsY3NubI1BSHxHo+tbrPRD2q6qUXHTnMvzdfpRyq2tMQ3HwrV0NscRbVeFxzdHMRfmajNzimI2ZoVke5TiWTpmaWbW9m26NXvqPDjBpLZktpg5yQrkScqTlDmPDx/nDU8DNCGmDmmTuofJcV6Fn+QupsF83WK55d3lFjebxAZlnmJqKm7bqSkdmUGYcLsX0nAsGp7B1ijZZWy/1HSZnykANHXB+jAiy3JqjolXqMXGNXXCLMfTLLZGCYsN5+6iNCE43/amE9hSI+d2LyyVNzWSTC0Q3ZrN6mDIaq9ANwQGkBUFgyjFNjRu90J8S8PWNeK84PZGyPvONumHKUGU0S8Kznc8fFvnI5c7zNfsaR7l1k7ATpCQFwU3thXT6lJXSd9fXR9xtuWSFAWWULINpmkwDBOyTH0fLyw2qDkGc3WbIM7RhWB9oKjME7mLrVGsZN8z5WmwULcZlvaaHV9Z6V5dH+E7ypt8Z5hSIDjbVmFHv8wr7YyVoKMKEwjmaxY7AnphTMuzuf7GF/nwxXZZyLa7VmKhbrNSFlgamupPQZKz3HQ4TbgXI2zy9/VBRKEJLFOj7hplyFYyjjNVta1rBHFOx7PxbI04l9RKf/OVXkDNMu86yc0m5me9UM61XW7thLy1PsQ3DXJUmEii5M81cYfFNQm7KUtlnXNtv7SevTM1bY1ibF1D01T/2BzFFFLJjnR8i5Zn8fb6iF4wEV0UtF2L+vkOq/2Qpm+TlXVNQkp1Emg43Nge49smFzoeYVqQ5hLXUhXa41SWWlYFSao8SrbHCS8s1pRAIkJp4dkGO6OYIFV9eW8dzlLT4frWmLSuRCOXWi43dwpsXZ2mGrZyKR3G6vqepWHqyqrAsXSiNGNrpOo+zrZdktJfZ3ZOabpKCr8fxqV+nnLBXGq6d+XA4OAT64n6eZT4zBOX89AESVaQom7OZFI92/ZY6YWca3vKo7h0jJtUfM5iksS+3Vc+E23fYr7hcHN7TM22aDgGt6MIU1e737m6ctybq1lTY/uwVArdGCm5jQnPPMsKLnR9NoYxbU8tFr5tsN6P8O2CcZzi27VdIYhJe1Z7Bb5jTKvY52o2/SiZ7jwnieGGY7GVRQgpMAyNpbrFyk5AnhfKHrbs6OFAVen+yjuq6tS2dFqmTZZLfsuL87x0prnrvnRrNp9+Z4u1nZAUdRLYDmMud3yWmjbzTZuVnYi5ulqsTE1Qd03ee6Y5tay1S2r0KErZGquir0ll7eZI+WQ3XJNCSm73I9YGMYt1G88wsExFP+yHKQWqenyUZPiWwZWFGnFZmX+7FzJOMrVbRYUBJeUiIVQF/Yc+/Crf8c2/n6/5+Dfg+z6fdkyGUcrv/JqPA8pHIisKJeWgCTqeyfIpoO4eF46pc6Hrl7tNJaOf5gWykOVJIed8x2NtEE3tXycLhaErhs7EtnmCvZPS7CkolSA0ON/xyAoQSDRNuXb6ls6ZlqcWrT2T2DjJ0EtBv73XaXoWwzjj3a2AnVECssB1VOFvXI4zZyoxpArlitInfGcclYKJGlfm6yw0XGxd41zHZxwrJmOcJTRdnXc3A67M1/j01U1WejG5LFQOJ8/JZMbV9TGOrQpg40QnzJTZ2Wov4kxbFSDOEma6vk2Y5GTFhAav5pPL83XOtV02hjHXNse8sFhjZSdkEOaM4pQkzdjOCt6zVMM0dPJc0dQngqe6pnGhq2pzUgnLJYEmySWmzlS5YhKJ2Nsf9juxKo2So+OpzHmIUpt/YxhRd+8c2yYVsIVUQmYTJFmxy2p0knBtOhZpFpNkBbd7KgEbpQVZHpPmOTVLQ2gGApVnWSp3pav9kDRX8hw3tgNAcrHrl6JoOYulZ8WE896tqbZ6jqpcb7smnqVP48yT9kwWhDgtuN0LmavZ08rrSfhgWrdiqHDbzjghLTTmmg7f9tsu8wtvbjCKMyXgaOusDSKars52kBCkGXXNxNAVtfCuFRW43QvJpKRVs/Atg5V+yNogxtYFz83VAcFyW7kymiXNOS9gUIZNVnshzy/VaXkmK/1g+vmFEBRSHcs3hzFXFmrc3A5o+zZX5msEiTL9eWGprmTww4Qv3R5ycyckzXLONN3S3VDbtagOohTHVElTS1fy2ys7Adc3A7Y2t2i22vyHf//z2IaKGeuaxse//htIc4mj5ziuGiKngar7IJhM1Jahs9iw2RjFjKNM1U2U8j3KGU+bqttKKVXRpqG8OGZxL6mW7WFCt27RD5XytBBChWBGCRdKZtveScwxNZqOteseT65jGxrhes61zRHrg6isu3BxDI3Xbg/wLJ2lljttZ1qGzDq+spQOSx2uhm1wtuUqQoatTyf6KM15fbVPgcQxDSzToNsQpGlKnCmKfd1Sul4t1yKXBTe2xozTjPedbfK+sw10TZvW3dTLfKcQ8OqFNrf7oRoTusalro8A3t0cs9h0mC8VGpbbLq/d6isGZcdlpR9zayfiykJNCWIOIl5YqitrhHJjOXuvltve9Dveu2nei5OoYTqKqu63PdAVHiFmnQQngm17B/tRkoyzjCyzFFDcHmesD2I+eL5FmhcEsfLffmm5iWPq3NoJ1ADUBR3fZqNMEHq2EjLbNSBKqZOLcz7vbozIEhVTffV8e/qlzj5/tj2TBWGcqMri2YUDdrNr9moXLTVdXj7b5Jff2iTM8tKq1mYUGbRqFoMwQxOSOC1YbrmsDWOeS/Nd7//W2pC5UpV3a6iYZ56tvJY7vsVKL2CpNN7K8gLfNrFNnXGZbzrX8XlurkYhwbdMapZEQzAIY95cG5FmBd26xe1BRD9Oy7CjYuvM1R3GUYZAkEiYb1h0fIdcFlzdHLExiHl5uUFS3veJEOBKaaVqGhomGgtNl+1Rwn/3Fz/F+Y43Pa3NqvxahqDuliZB5d9XeqGaMB9x4mPSr59//vn7fo+9J4Plpkv37J3NydYoxrEMojTnPUtKnXkYpggBX/5cl3GcTcOu+42ZvQy3XEo2BjFWeaI0daGixWWt02zR7Z3TtTtlxe29Ti9I+OW3NxlGGWeaLnGeszlM0QnIi4L//JUz9MKMNC8wNIFEslaqOBvl4tPyLEUVj7N9lYd92+QD55q8sToCCa4ucDQbTUvwHQsDyVzdxbOVT0aU5Vzo+nzgXIdelCJQHjO/8u4m8zWHTs3iynxdsSXHCRc6vgppl77kCw0Pz1Ie7q+t9NkcKjKMNojQNI1XzrrsjGKGccZC3SYo5e6Xmu6+dWtxViBQNtxpzkNXRTiKqu6LwN8BFqWU7xNCfAD4OinlX3woLXoATCpxP/rRj377QavqUZKMeyfgpeYknqsxN3N8T7KC7XEyzTf0wgTPMmk4Bh++2GGlF+JZ+q65Rg0KpTuzNYrRFxsESYpnKtdAVROyuz7hKGJ2ExxG34zSHFlImjUbx9DYGibEufJbVsWSNh3PZpQoCq+xj05XWkgcS+1QTUPjbMsjyzKSAmqOyXJLJT7XeiHdhsPlhVp54iqolV4kk9zSJNewNoj49NUtdKHRqVvEGfzK1S3anhIxvND1y+O3UugtUBLX8zU1oMZRgafrZMCtnqoZcEvlYxC8vT7Etw3lbV5a9l6Z9/nsF3+D//bb/gTbG+v8y3/7i9x+53V++qd+gj/+3//J6Xe1M1ZU51na73FNcx4Us/36Qd7noN3m5PGz7J6I5uvartPvZMzEac76IOIz1xUV9sq8j20Zu+pJlloOt7YDRK7sDbJckmQZ3bpzz93wfmPzVi9ACGXLqukadUs5Dk6kbQZxxjhOeXcrRkPV/6i+qlOUxXhXN8YstxwajsmZlpqwJaq2ouaYCKDrO+jamDhV5k++rVEIkyzNGWUF512TFxYbvLjY4O31IVcW6jRcg5WeCgVqSDxD2RY0HYutkZJulxKlNl2GTAFGkRJbPNu2+PDFDr9+bVv1T0unbpvUHJMozVgbxLRck0VLu2uzuB8tfb9TycPAUbRM/h7wPwApgJTyc8A3PcxGPWxMOunl+dq+N3kyAc8iiHO8Pc/LC2VrW0hluLNQd7F0MR1w+73PZCKftOGlMw0+crHLS8tNfNvgSyt9rm2OGZQmT5NT0kHvsxfdmk2S5RP2xK4k+qRI7pUzDfICpFAy9efn/OnzN0cReS7ZLq07Z5VqQcVWh1FGVqj39i2NUazUaicLbJ7Di2eaGLrG+iBiZxyT5Dn9MNlVfd+t2aRZzsYwpuNbnGnZpJnkxvaYydNUglBJu2iaxvMLddqePV08lThlwVzdxTY02r6lkrFJzuu3B2hComsqKZ9kBQJBmklu9UL+yp/64/yZ7/0LGKZyS7zw/Ev8b//in+26x0GaTSfFCe1bHjM2/CThoLExebzjW1zbDtgaKyq4rgs+vzLgtVs9giTldk+FZ5BQd03yvKDmGBRSYlsGZ5ruoRPbQdcfRRkt18K3NRqeQd0xsAzBOErLIr2UUZTRcBTFN02VG+W7G2O+cGvAThBjGxobo5i1fsjKTsBCXXl+hKWc+eX5GkJAgWSxof5maBq1UicvyQvOtT3ansU4yWm6ygf8l97Z5vr2mNu9gEGU0fCt8rSt+s5aPyzzZ3e6jaELgpImO/ncF7o+yy2PFxcbJUOsQBOChYbNYtO5a+GA3VGJSf+c1Ho9bBwl5+FJKT+956R+rKz8k4b9QltCqJ31LG7uhARpzu1+OD0WT764WRHF2feZ7Ar2VkD7tsFrK32M0g9jnGTc6g3wTQPH1Gi4JvVSQ+cwhdejyHFbnsX7zzV3FYx99Lk272yo/Mxyy6Hl22wMY5Zbu6/x3uVmyQ/PSjFFFav2bIPr28pmt+EYRFlOwzZJ8pwoLRhGig7ZC5JddQNCE6W8dqo0eGxlwWsZhhqgnoWhQX+cYpsa3bM2KzsBt/sRWVYgNNgaq4Wh69slAy6j5qjPe3074FzHZ2MY4RhKhuX6VkCa5+RJzIc/+jHFxKo7bAwjdF2fhlaSLMezTPKi4HYvJsmLKY31WcXbG0OyvMA1TQalI2EhJSv9hKyQXOwqw6Qsl+giY6npstBwHjhnVHMM2r5NL0yQuSRBkmU5mi642FZsqZ1xovxuHB0plK/G9d5Y2StT5uuKgm7NJkgLXjnb5Iyr+neSFeSF5GzbY7HmcHMroFu3kbJgbaDM1paayv0QVA4vKXKSPGcQKkmU1WGMoysVB8oQ6IQ1GY1T3tkaoWvqhF8rHf+6M7Te3Xkph41hzDjOuNDxpkSN2eLjvVGJCR6V78xRFo9NIcQVSnKrEOL3AbcfaqseM/abgF9abiodmTIeO4oyrm+NeW7enzKFVvsRiw2bVB78PnsFGSdHzc9e32FjFOHbJiIQxGmBbWrkUpIDslTKTHNxz1jmveS4C6mKrECw1HBAU34h3ZrNmZaqOM8KyTgu9ctn0PIsvvzKHG9vDBFSsNIf88pyi7m6RZQqphhCKabe7ocYuqBpm4RJBlKF3MIknx7RP3ezNzXsSYuCzWGMY2hESU7bs2h61vSU88KSih/HuTpNpXlBTTfQEKz1Ymq2SdM1lSubUOGpYZyy1HAxdZe1fqxyKFJ91u7cHO9evYoQypHuf/+xn2RhcWnXd7XSC7m5E+Bb5nRSxLDsu27uM4JRqWM2SNJSpUEjzVQYa6LlBIBQYn0LdZvL87UH1gm7Ml/n1k7EOE0xhSApJHmhs9QwaNYskkRyoetRSEFcMqCWGg41SxV6RmnOIE7pejaepVMUktV+OGUlTSZcx9R5+WyTTt3ii7cGhHFOLpXGVl5IclmUhJiCOC3waya2AXGu7kuCxjjJGMQpvbHy30nyAl0I5nybIMm4vhnQ8HS+6r1Lu+7BRHT17Y0hoyij5hi8eqFNy7MOVE1QOY7H4ztzlMXjDwHfD7xXCHELeAf4rx5qq04B9puAHVPfJUp3sevhGIaKY5b87o1RzPJM8c1+7zPLiAIoZMHGUO1sW67GVqDEzhZNmyhRO6WGY95V7HNcTNz7rm8H7AQxQZSjaYKXzjaZr1tc6Hp3VZ3uQ7ii5Vl85GKXW42AF5M622MVTx7FGZomWd0JcSwlqx4lOW+sj/BMjcsXOwgh2BrHZIXk6rpS380LqaijoE4ZYYalC56b9+mUVMe8KKbVzL1xwuX5GoMoY2sY4zsm83VLUU91TXlHpxnzdYcCRXHUNY1zHZelphJTRMJf+Wuf4rv/2B/irTdf59X3XuHCxUv8s3/yj7k4W+8jJao6sPxdwLRI6BlEzVESGpauCuUACgSeo6yXNcFd/ecwP/ijLiAtz+IrX5yndcPkjbUBFoJXz9ZAgGsZjESmVB90QZprSCRpruR4Wp7KPcz5Sl1b1zUMXWDp+rSIeHbC7dZUwd8rZxt88WYfI1Iihpfma6z2I0xdLRA3NgPGccZy2yUcw3zDIY5TfmNlQLdu0fYsRX82lD2zZepKS81XJ498z+CaLLALdZezLTEVsZzMO/vZIqflRgoeve/MUdhWV4HfJYTwAU1KOXzorXpApHnB1Y3Rfe1wDtsh7RWlS+2ct9ZKZoatlxIBBd2zh29M9x41e0Gp45QoocMsk9iGYHMU03CVWOBRj6L3an9SFFzbHGObOg3PxDR0rm+NWWq4PDdfu6vq1DwkRhOXp7A4K9A0wVLTYXMQshMknLE8LFPHLk9lk6rcXqDMa8ZxSpYXnO/4yu1QA0MIpJQYWsHHrnQVC6tksbxcstqA0itaSeefm3qyhLyxNmIQpTRcHT1ROakLHa8UfVOSDElW4Js6Ugga5y/yT//V/05/MCJKU95zfvHuvrKPlANZ+jiNzI+Eo+z07+c0cGW+zhduDQiSFF1AJmEUZ5ytO3iOuW//OcwP/jiTXMuz+Mr3LPCV71mYPvallT79Ug9rZ6RCZ3mhhBot08Al4+31IXFWcL6t1LMdU0OgGFkqJ7ib0jo5AXzxVp+6azJft+lHGa+vDhBSCabmOZimKjreGSs/kbZr0pOSIFUh1Jpb5noMHSG0UiJd6YKtD6Np2Gpyzw+7TweFp9KcA8PUDxtHth2UUo7v/azTASm5rx3OcXdIG8OYTs0mmHgjhCnvOdO457X2MqLi0kksyyUtz2IYpYxjpTL60UudA4t97qf9NzaV/LVn3/nqgzhjpRdg6ooV4tmK1y/ucdKxDY2VfkivTO4HScbGOKHuWuSla9xivVTsDVMc844OTy9MyXKVuI7inCDN6dRMigJeWGwQZwVpJrF0wWLT3XVP96v+1jWd3/r8PA3XnNrcUubpllseSDmVnZnIkEwGXK3mc/GAiXM/KYfTfu44Sj+439NAy7P42HMd3lgdTie7lxZrtGo2wzDdl2Y7YR3OYr/N0P0sZg3XnJ4EMlfppdmGQd1WXiFnmx7nWi6fv9nntdsjXlgQXJxTSe9+lFKUlq97P/c4zpir2dRdU0nwbI9JcokuJIO4oO2bDBPF8Gp6Jos1mzAvWGi4uKYyh8slIJW6Q5rL0kFQSdu7lo6uiWn+bxxnvLU+pOGY+I5BEOckuSKxRIlSy57YR0zauZd886hxLM/aJwVKb0kce4dzrB1SGc5wTJ2aPckRZKUPweHYm0gXQhUZvrBUJ4hzllsem8NIeSTHmapQR+2+H7T9aSERWsHmWKl9moaGkJKdIOUjlxxGUco4yQmSfNdu/6DP8YWVPmu9kJZrITSBFAJDU5a8WQ5RVlCzVDjDNvWp1ebOOKbhWqwPQoQQ6BqEcYau6yw0LAaRYstMJKZnJ7bltkcvUsyeOMuxDZ2llsNz87Vj7biO0if2J0+cIoGrfXCUfvAgp4Hn5mpYpajh7EJxru1NTaZmd8BHUf+938Vs8v10fHuanJ6YIRWFZJxkDKNUFd7aBk3PxNQ01oeRKkA9u3+fibNiypAydQFCMOdbRJkaG75tcqENX7yV8Pb6iLSjFoVay6NuT8QhlQzLta0R6/2IrVHEXM3GsXQWajYLDYc0K3htpc/5jnL1G0QZ72yOWG55GLrg+naAJjReOlNnYxRzYzvgXNudFhw/TrOyh59VecyYhFWOgkkY5kivL8MZkxivJlDKlEeYVyY7Ba1MLHdLoTjXNFhqOlzs+lycq6ELCJMc39JZqDtsjeKpJPN+GIQpW6OIa1tjVvshUZpP2z8ZnGmW84VbQ8axyiukWcGba0PmfaW8udz2eH6hzvlSuuFen6NpG9imQZxLhCa40vWpO5ay3K2ZLNRsmr7J84sNup6Fbahq9otdnywvlPugptqRSslLZxqsD5WMiW+Z9IJ0X/qho2vMN2yWWy7zDRvnCIv2/WDvd6UJkMd0XHvUOEo/PlZf34P97slhk/xh9PEJ7pdyelBbQOVnlpqq6vzSfJ3nF2pkhSSTEttUQqMHtVnZKCu5mls7AZuDiCDN2RwmKkqQ5YyTgvmGw8U5n4ZrcaHjc6FbY5QWDMOElqsIBJkULLXUKSorq/kXyyK/UZyWToAabd9mECpb63GSsTVKMHW1MYoyFeK1DY3VfnTPe/4ocODJQwjxicNeeJq1rWZxHObBUXZIs8/dT5nysBzBLPYeNSdH9p0gJUhSxlF+V3V6khUH7gyV9lUypfpO2F9dX1VJT3Z1y22PtVGkmGOWYi4FSY6hi6n8NdwJK9wrlND0LC6WroGepWiuHV9JTDil5Mdyy5tWxEZpzs1eyO1eyI2dMQ3X5EzDI8oyarZJ27N4e2PEYun9MBG2nA1zTOpVuvU738tB9yZKc1Z6IWt9dcJZqNt8+uf/zXTHvR8+8YlP7PpOJp99WtV7yus8jtKP71VMeq/w0X7997CTw3EKc6M0pxeo4kwpOTB8deD3w25m4a2dYCqYOFe3uNj1p3VCB0GxnkZkeTHNaTqRRsPR8S2dm/0QWUDD0XEsJUWy0HCpOTo1p87a1G5Bcqnrc77jTb3WozTn2taYpqtOzxNZI8dUisNxmjOMstLKWblkhuXYPN/xCJKTPXFM7qM4JovwsLDVxw/526nWtpJS7uLqH+VGR6mqnL2+HeDbBvN1+9Cj4VFkTva+/2EDcpKki9KcWt1lJQ9Kl8O76YT7YWsUM1932B7Hd/ypw5T1fsjzi3VqjlJFtU2dj1zs8vb6iNul5efZlgeSXdcaRtnUqtd3DOZryv/96vpQ+R/DVHPobMvDsWI2h2pDvthyWW7sljif3IO3N0aMo5S5mo1lCMJEeTw0TAtbV4veJAyIVOEv2D35zXqyTO5n0zWnFOm919sZK5VeBKz0I/7Jv/iX1B0TXbt7pRdC8IlPfOLQyfC04yh986DnzNYaHCd8dK8w2L3i8nt9RyxDoyhUOPWX3t4sC+h2S3Lc2gmQEkZxShArh8+Xlpu0PGs6+e+MlQdMlOYMgqykqEPXs0tf7/3hmDqalERlQr3pWry4WOftjRG9kaJ/27pgdRBjahoLdbVJ+8LNPh883+Jcx2O55fH2+pBzbXe6MFzbGqs2ITB8QZIrmfY0V/1+YqjlS4Mky9kaJzRdc+ryeNI03Nl+LmVxMpLsT5Km1V6I8gh7VObB7A28NOezMYp5d3PMha5/4OuPspva7/0PS2D+2vVtNvsxuqGohnM1G/sAOuFexFlB3TGQUvLG2hAJ1GwdXdcUXdDSATXZm7rG2ZZL17O4OF9jVDq6CQTbI2VVeXN7XBZcmQhNGTC1PZPtIMUuVVjTXBJmBUJKlpseFzs+aS4ZRCnAXYy3rVFMEKvCsZ0gpe5axGlML0ip22pHN44zzrddNkYJIDnX9pQo3DCi7VlAQJyqQeXbd9R4b+6Ed8mlT67nW+bU1EkIwfd8399guax0Pgh7J8NCKimajWEMumke+MJTgKP0zYOec9RcyN7N0CBMafu7VVuOU6w26ztSyIKb21E5Rlwsw2RrFCOlnH4O9TtsjRV7r+6ahEnOayt9Plxq2k38b5Ks4Na2cgh0DY2NQUwQZXzoYmdXG2Y/E1JyYydkqeFg6lopyV/w0lKD2/0I3zHYLu9VXijdte1RTN2xGMQZSw0Hy9DwHYONYcyFrjHN/xiaDgLSoqDjOQzClFGU4pk626OIGzsh876D0CSrWyEruuD5+ZrSdSv19E4Ke7/v4+Ao2laLwF8ClqWUXyOEeBn4CinlDxy/qY8Gpq7d5c1xGHbfQI0LHWWypAkOXXiOynK414CM0pyr60NubYc0PRNNCPphyrubYy52PTRxuEIm3Nm5hal6jllKng/jlHGU8drtnFfKXdlqP2JrHIOUvLM5QhNwoaOKoJTUueR8x1cGQmUMOs5yfv3GDr5pIDQxDadZusbWKKYfpgihpLCFlJgzydTJQhlnqhrZt1XhVj9MaXkGgyij7ppcmqtNWVLLTYc4V7TijVHMUtPFtXQKCWv9iKj0Z5j4ixtlUnMWk+sZM7F9QxMkmbLtXVtb43u+53tYWVnhJ3/yJ3nttdf4xV/8RT75yU/eFUZZ7YeYmkYhSjOHU46j9M39nnOUiuX9NkM7QYKpq0l8gv2S4veiwd/cCdRz8oLzZR1VL0houLvVG+JMWT5Pduobw4S4zKus7ATq1Fv636zpEZ5tTHW5NCGmcuwT+fe9n+nGTkCQZIwijUyqsKgQkOfKTgGprI9rtkEB5KXfy3zdIojz6fvO13Z7+WSFpOboOKbO5jDB0AQLTZtekJJJSZRJLE0QpspLhELSjzNW+zHPL9SoOea09uMk8h2TU/ztXnxszbajLDc/BPwbYLn8/Q3gu47VwkcEIcTHhRDf3+/3j/W6B0kensT7b41ixmlOwzXRhToZtDwL39bZCQ6mE04w8Qx/e33Iu1tjsjxnFKXKxMc2Odt2GUcpN7YDpJTUbJ1+oDSBfMtQcg1JQc02p9pRNccoGVOSOMvZHiVKYsTQMDShLE2DhNu9gPV+pDygdWVtelDi0zY0srxgpR+WtRew0HR5z5kGLy83uTxf4/JCncvzNZbbHpau4TkGl+dr+JaSP7ndC1jph9zcGpNOvh+hKLh7vy/b0JQx2IwuWFYobw7b0PjWb/1Wvvqrv5qVlRUAXnzxRT71qU9NXzvRE9sZJ1i6klJR9//R5jzut19PMJkYr26MuLUTHEq6OEyPbYL9ktsTeZdhmHK7F/D22pCb22PlrT3ThqKk0ReSu9rimPrUj7yQykekF6najTDNdo0Z21DmVXlRsD6IKUqjNtvQuL4dlJRd9VniTHloLNQdlhpKkbbu7NZt2/uZJpT1/3RtmxtbAaMoJU5y3t0a0/EtLi/U+fLnupxpu8zVbAxN0PJMBBpn23fylLqmcaFzJ6GvC0FeSKxSuFMX6rQ/X7dVLqYoSErK76WuT823aDoGpi5Ybns0XPPEtatuluE/jukkeJTFY05K+U+BAkBKmQEPXzjlPiCl/NdSyu9oNo93rDvKgHkQ3Ov946ygKCTdmkWS52S5WixEoRQ/P3Sxc8+QmKlrXJrzMTWNdzfHbI9izrS80pdb58LcHaZGlOV8xfNzXOz6tD3lyyG4o5uz1g+5saO8yJM8Z7M0s/JtnUGk2CGbw5hfurrF7X6Mbet4loGhaWwMY7bG0bRtq/2QlV7Aje0AXRMM45xxlKKDyjFtBRil7PksJoNZSnWSLJD0g4SdMMXQVfhJ19UJSOVcTIIk3fUe3ZqNZxuMk5QkzUmynHGc4Zf5pc3NTb7xG78RTSuNjwwDXdenr50whOIsnxaUzRoVPSrcb7+Go03as4tLnCqp/sOYUftthuqOgWsb3Nwec20rYHscU6BUjicnjqOwqSbOkgKJXooDbg4TdCHuqgIXAtb6MYamDKDSoqDpWVNl6sl3KEQpU54ph722b901vvd+JolkZSek7pj4tvLx2R4rZ9AJC3G57dHxVAJeeXq08CyNTincObl3y21vKva4ULexDBW2sg2dbKJgUO5HelGGYxoYupguYrZhMIrvfF/KxfNom4F7Yq+CwjFwlNlxLITockfb6jcB97cFOqU4CpXwYb6/bSip8KyQIGC1H3FjOyBDcqHrHzlR6VqGEntreSR5gW/ppXxBwVLD5XzHY6Hh0PZs5mr2VKojTHMKWRDnRcnwcJXs9lBJQYdxRpjkLNYc0jKR7VpqIeoFCXVnItGiUXcM1npxuXBEqjBP09A1wdWNEefbLmc7HkmuivaWWy5N7242zWQwT/yZ+0GKaxpICbqmY1s6AkFvnJDmKjw1q9gLaid7Zb7GcsubhjSWS69yx9TxfZ9bq+tKKmVjxI/99M9TbzSmr51QQItCTs2+Hic18n5wr0l77+JiGjpCKrmYg2i4B22GolhJ+1/oKKq5ZxrsjJUPylFP97lUirYdT4kXCmCupuorZseMY+q8tNwkTLNy8pSlXwfM15Vg4OQ77HoWgzAlK5TLpAoD7x7fs58pSnO2hgm3eqGqVndNlpoO3bqNb2vTNu+lCXulh5Br6QdTmGco/gAbw4gkV2NtGKa4hoZrqT6vPNshznOlG1a27eaOEjM9aDNwLMy2R4hj7ZaPUiT43wE/BlwRQvwCMA/8n4/fytOLoya/71fc7V7v363ZrA9C3tkKqDsGC3WLYZzimAYd//Cd7t4YtWMqD+neOGEUZfiOMZ30JlXqcZpzozyq2oZS/lwvE9KTvM/5jq/k1IOU812PpmMxTjK8svo1SDJcS2OxofS3SmYtDdfkdhyyPoymBkBpoQxsrq4PWYkzmp7FuY5Ly7Omnh57MRnMkxxNL0hIspw4k2ganGm6aELJl8zV1WK4H3vGMZV/yH45sL/0ff8TX/d1X8e1d97hmz7+n7G5ucnf+Hs/PKUsTyefMpmrlfIpRyrmOSW4Vw5jv3zcxATroJzJQUytOC+o23fICaYh8KTBWl+ZMh2FBu9ZJmkWs9hwmKtbbI9SRnFC03LuGpMtT/lgbI1iVSuha3iWzsYoJpsZo5cX6iyX4y8u6fR732vymeJUnbSTNOdM00EIjZVexFLT4UzTIUmLu+jMAEhZ/pwdOi9MKP5K7LDghcU6vSBhFKZ88XafemmtO05SzJJ2n+aSubo6zawPI0Cy0HDuqxD6oPYsNd1j1y8dRdvqV4UQvx14D+pw8zpPQMLwuJhMFJNOMXGN22sFe7/iboclMB1Tp+nZLLcK5RtQSM52PLqevSuptx/24+vrmsbLy42y+Gi3JWW3ZtMLU+I0xzOVONuN7YAgznhx6Q61dpZTvtxSDm/jUunT1nV8W6flmmyPY8I4R0olQFhIyctnm/TGCYUmVPV3WQszjjOyApaau+tQ9pv0ZymjLdfgi7dSkizn4pyPbyvzHUfX1GfLC8ws51zneDTpiy++j3/+4z/N9XfeQkrJ8y+8qJhcewbi3sWf069QMsVs/5jUT4yjDNvSiFL3viS9D9oMbQzju2cGoUKMR6W2NxwDQ1Nuf0UBCw2b52x/2sa9kuTLrYlRm05eFNzcCZmw9Ca78sOowrtc+IRgYxCSA75r0K5ZBEmOQJmfFQVl+NaY9k1NqJzBRDtt7zX3YpZVZuoCgYZvqrCvY+hICty4YBAm1Fwdx7I534KmZxMkOVmmPEVm3/tBJNhnv5fj4p7HFCHEzwPnpJRflFJ+AXgV+JX7utopx2Hx4f2O/4WEL670Tib2CDy/UOOjlzp89LkOl7o1as7dZkx7cVBIbBJn3Vt5O46VYc75jj8NlSmRQRNd290d9mrn2JbGMFZ0waWmy/muj++YCA2CJCMrCtq+zXNztamxzZmSm78zTmh4FoauEtiGJhCoY/t+4cHZkMBOkPKeM3VeWW6w1HCVOyOSXhDT8JR3gjzgMHDYd/p7f89Xs7m6wntfepmXXn6FL3zus3zd7/rKfe/5pD2X52uQp+k+lzqVmPQPlcgOidMCTVOOfMc1GpvF7P2YTJQLdbv0mi/KOisV+lqo20euSu/W7Kn174XSIlibmbD3fo/A9H1X+xG2oU7NrmXcs0r9rpCdrhFlBWdbLi8uNqa1GYYG2+OYrCh4abmp1BnKuaAXpPiWcgDth/urIczmlCa5mCwrSHPF4LItg7ptlk6DGlcWapzteBiaxnLT5aXl1vT0fKHrHzhO7wez34sQ2omHrf4y8FNCiL8BnAW+Fnhia0AOw3FULdWCElEU4LXuT2Z6L25sB9Pjd9tXfssHUR2BKa1VcLBv8WS3NXntRHytU7M5U0qcy1Lbaj9p5+lxPitouxahqUQcJ89Zarq4hgZlWye7+r07zXGSYekaLy7WCZKcsJROqbsHH/EnHXty7ycKpmv9mKZrcrbt8cKiOi0dVGF+2Hf6R/74d/MHfu/X89985x9k9fYK//an/w1/9W/+nUfihfCoMLmHX1zpkUuJY+q0/TthzLTMJcCDS3ovlyf3cZqTZOokmuUFcVZMBQCPSh8+bv3JpJ9oQrHjJsZdLW938ejsGNoJYpqOtes979Rl+KoeaZxQSEm7ZvHKcgtQSr5aeaoexRnNkp68nxrCvhGLXogUivlnA0ma43r6dCPnmDrn2/tXkh+3OPkomNxzmSXHonAdJWz1b4QQ3wn8DLAJfEhKuXqf7TzVOOwIvzc8tDNO0ISG62gPHHuM0px+EHNrJ8TQVOJ5exyz2HS5UsbqZzvh3qOyruuH+hbPvrbpmiTZbiOcNJc0HGNqVTv5vJPfZ6t4k6xAQ4kcAriGRpxLguSOxexkAZmdBBxTo+lY1F2TZnl7JrU098Lk3jumMpNK8gJDCLSZFx90dD/sO/29X/97QDf51m/8ejrdLj/xc/+RVnf+xIgSpwWOqdMuTZBmNR3V5CM423JPRNLbMXUuL9TZGsUMoozeOOZc26PmGMfaXE02H5NJfmsUMwhTXEvf5ei4d2EA7jLuurkTTN0w907kt/sFaRZjGnc0ruZrNm+sKteJSQ1Ry7Om43ByUumPFYV4Z5xwoevRcK3ppmP2JLBfsenOWPms65oKJ/eCZBpinkiVHHSaOE5x8sPGUcJWfwb4m8BXAt8L/LwQ4r94yO16LDiMUrs3PDROVIHabD7ifmtDVnYCxknBUsvBtZXnRj/K0MqdIuzuhIcdlffj9M++tu3bKHKe4pfP5kL2hiLGcTat4pUI6qUy6U6Q0PEtpJTkEvpBTJ6jPC9K3/VJ0nnyfq8stxCC+2K07b33QkCQZrsqmg/TIDvoO/2rf+Uv8Zf/zJ/gX/z4T/NHvvt7+P1f/zV87hd/7oljVB0Fh92H/UJQ94vJezUcg3Mdfyppfhxv7f1CjWuDiKsbI6QE11QU7pt7Y/X7GnfdocHuDT37loEmxFSyBFRebhCl01qkOFcKCpPXF1ItKpN713RNXl8ZsD2Oy43Z7n69l2W2M1abLMNQrEbb1PAck944oeurBeheY+Mkv68HwZHqPICPSSl/UUr5vwBfzSktEnxQHEap3RuzdUxNySvPfHH3G3tcH8Z4lvLQWGy4PDdX42LHox/dUbWd7YRJrvSgDO3OYmXqqqhqv7iwUupUr3VMtbuxDMVUOqz4cLaK19TVgHMtHYnysrYMJSdiGwaebWCbSg10v4VsEus9qhLrLPbe+4kK8YT9dNhgO+w73dzc5Fd+5dN83Vd/FX/6u/8o//Znfpr/99/6m8f+/p4EPGw6+l7cT+HtpL985voO22W4aLLwqP6dHbgwqMcOV7re26a2b1HIgnGUIaVkGCoXwIWGw+U5NTGb2p1FL84KRlFKzTZZLmXRTUOjU7en6gd7+/XeRTvJi7LGQyvHosvLZxo8v9Q4nOJ7CnGUsNUf2/P7NeA/e2gteoy415FwlrERpYqBtJ/5zXEhpbybvyN3i7fOhs0mld+TTghq4QrSjJrj3hUX7oUJtdyc/q7CAg7zdeeeYnVBnO+SnMhyiWeqYsGzLcV0moi2GZqY5jJW+yHXt8a7zKWi9ODQ2l7sx5DaT1vpXkf3w77Tv/7X//qu5168eJGf+ZmfuWfbnkQ86nDHcRSqYXdISZSV17OhVUPX6NbMfW1uZ695mNL13jZNxsEgSqbW0p26TduzdllLj+J0qkoQpLnSexMaCw1VRyWQNFxrSgeffJbJQhklGXXXKtlVagN0foYZOAkb38/c8aDe8A+CwyTZPyWl/C4hxL9mH2qilPLrHmrLHhOOqld1koNxsemy0guUM17JRgrSbBqrBcU2+dJKXxXJ6WLK+JhYqyZZjmeZ++72PMs8UlJ0b0f0bUMVESa5knnPJUme0/FtCtTRfbKQmcYd5tYoyri2HXCm4U7l4bfKY/lRckJHoUUf5Xs6SLL7u77ru/jUpz7Fxz/+8V05gAl+7Md+7ND3fVJx1L59EjhuYnc2pOSYahdviTuioJoQOJZxqAXCva45W8sxyeFNhAZbnsXVDdAQ0/4MakM0DDPm62pivrY1vjMeCnWCm4Sb4O7c5MYwZmecUItSJftjG4yjiFvbwZEdOw/CSXjDPwgOO3n8g/L/v/bQW/GE4qQG43LLJUxzgjgjyVWSru0rDjvcmQTn6g5bo4jVfqTqLxoOYZLTcO8wUvbb7e2XDN/bwfbriFujmOfma1zdGDGICjxTp+Or0NOVeZUYVVIQEWmuBOrmajYbw4iGM6Ee3r2DuxcexOXusM8zGVjf/M3fDMB3f/d3H+m9Khwfx91czRIbJoWhd+qTCjzbQJThtoMWo6NEDro1m9dW+khUaHdWaNA2NGqOql0CMHRBmKgFZrKjf3m5yZdW+gxD5TTY9a3p30HlL7eDhDjN6QXKemCubpNLiSwKpBCc7XjHcuw8CCcxTh4Ehy0eXxRCfBfwPPB54AdKXasKJ4yJjMZBx89JJ1ExYI0LXR9ZSmZYh9BjZwfYvRa6gzpiXshpFe/etjmmigVnnk2QpNRNtWC0fJsoyQ7cwd0L91O4dtTPszWKeeWVV/jUpz7FW2+9xfvf/34++clPYhgHD4W9J5h9jysV7sJxNlezIaVJXm59GE1FQSdsp3stRrtDy3eHdMZxxvmOv0uCfELz7tZsotLSdhSlDKJsav88uU7Ls/jQAeMhKv2AGq5JnBYYmsZOkDJft5ASxmkOEua6Po0yFJxkxT0LgQ/CSYyTB8Fhi8cPAynwfwBfA7wM/LFDnl/hAXDYQJt0krVBPE1eS02SpfkumeoHCaUd1hEPatvk8bMzj0VpzuogZBBmBLGSavBtY9cO7l44brx8ct1d/hJRRtvbbbsx+Tzf8i3fhmma/Lbf9tumUux78x+z77v3BHNc6eoK98bejY8mBB3Puqv/PujJM8nlgf1idvxkhaRA6aWN42y6WYKDx+rkJK5EGiWOqTSqtsepkvHZp4h4P7n7o+Yw7mecnCQOWzxellK+H0AI8QPApx9JiyrchVlp6UlyOivzDXs73/2G0o7TEQ/q4JMB23Qs0kyia4LNYUSYKCbWZAd3rwFyPy6NeyeK3jjG0MR0hzf7eV577TU+//nPA/DJT36Sj33sYwfel/1OMPKU29AeFY8z2boXR934HLXNB508e2FYOvbt388nJ/iJo+deT5rD7k+cFczXbdYGEQKmpBZ1sqgrXao9PWf22sfNYTyMgsHj4LAlairBUIWrHi+OIy39oNe4F5XzKBIuddfkTMul6Zp0fJuGZ/Lhi51SDO5ovg5HkbKY4DB/if0+jzljBDgbrtqvRmY/yumj9vN4GDjK9/CoMZm4bUObFgfuJx1/lDYfRBX2TOOe/fyo8vF7YRsauqax1HRp+0rcNMpylltKydc3dTzbOPDax73uccfJSeOwk8cHhRCD8mcBuOXvApBSysZDb10F4E4nETD1WJ+Vlj6JncZRd35HlXCZcNhlQ05DAvd6/X7Jz6Ngv5Cbqmq2pgNr9vN89rOfpVFKr0spCcOQRqNBUai6gjdvrk13faL0kZjdqT5JqroH4XEnW/fDvXbex2nzQSfphmvekzxyv7mEWTHPCx2PtmdNySOaQLkbcnDe5kFEKh8HDvMwP90VKs8YJtIP95KWftBr3KsjHkfCBe6I7s0aTSlNLe2u198vDpso9vs8eX73tSY72r0T037aT+IpSJg/7mTrfrjX4nCcNj8IeeRBQ7jjOJv6e0z81Gdx0LUfdw7juDidrapwIB63NMFxJFySrGAQpURJNg01GIbGzT2hhgcdICdRPX1QmAMh7goNHNf34DTiYbtn3g/uVZV+nDY/SEjnQUK4E9bW/YzPR60C8KCoFo8Kd+Ewz+vjSLhoQgkn1l1rGsddqDuAYH0QndgAOYnY73G0n3gKEuaPaqI6Sf/047b5fjdaR+1P95sbedDrnhYcRZL9sUII8Q3AfwEsAH9bSvnTj7dFTzfuFXc+joQLwNWN0a7dpGOqqvhJoeP9VubfS77kuHgczJXH2bcfhVzJSbOHHqXEylFDuMpH5E4/bLp3K/2e9HVPCx7qyUMI8YNCiHUhxBf2PP67hRCvCyHeEkL8ycPeQ0r5v0kpvx34VuD3P8TmVuBou6nj7Oj2203qmsb5zv2H3h4GU+i4u76noW8/7BDow2APPe6w7S5Iyc2dkKJU+i0kysnwyT+YHgkP++TxQ8DfAv7+5AEhhA78bZS44k3gV4QQPwboKOOpWfzXUsr18uc/Xb6uwgniruK6MKXtK0rtxFTH1JSu0Nl7v91deBg7+ofFFDrmru+HqPr2oXjS2EP3wt6xEucFSsG0fIKEOMtZH0R3maM9jXioi4eU8t8LIS7tefhjwFtSyqsAQogfAb5eSvmXgd+z9z1KZstfAX5SSvlrB11LCPEdwHcAXLhw4b7ae5qKph4F9gsr7AQJuZRKeFHXcU2dMMmJxvHUo+M4eBihhtPAFHpUffsk+vXjwpPGHjoM+42VtX7EmZZDmBR3XAQF0xNxmkuurg9xLDXNPm1zyuP4Fs8CN2Z+v1k+dhD+CPC7gN9XOhruCynl90spPyql/Oj8/PyxG3Uai6YeNg4qrru6PkJQKvwWEgnM150HTgSeVKjhNDKFSpx4337Qfv048aSxhw7DfmPFdwwGYcaZlsvFro+laziWie8YCCEopGQ7SNkaxU/lnPI4Eub7ceQPDBJKKf8G8DceXnMUTmPR1MPGfjv4umPgWjqWIaa+CUtNR3kZPMYagFnsDYUNo4yNYUTbs4Dgce7uTmXfflx4lAnuh439xsp8zebdzfFU6XecZGR5AULn2taYQZji28o87UGtqk8jHsficRM4P/P7OWDlMbRjF05DKORR46CwQqdm0a05dymPnoKdPbB7UtoJUnrjmIW6c2yv7IeAU9m3HydOcw7jONhvrOiaxoXOnQS/DsQFmLqOoQnWBhFBnLFY+pLD0zWnPI7Z4FeAF4QQzwkhLOCbgBNx3xFCfFwI8f39fv/Yrz3FoZCHhoPCClfm66c+3DCZlB7EK/sh4KH07Qfp1xVOBgeNleW2Nw3JLjRdtbiU04hlaGRFses8+jTNKQ+bqvuPgV8E3iOEuCmE+GQpsviHgX8DfAn4p1LKL57E9aSU/1pK+R3NZvPYr32a4rNHxUHUyFYphX3cYqXjFISdFO7HK/sk8Cj79oP06wong6NSuc+1PeW+mea0Sx2tPJNTj/Sb22MGUfZU5D4eNtvqDxzw+E8AP/Ewr31cPE3x2ePgXl4dR8XjssR8XIyeJ6lvVzgZHEUTq5CU2m0KgzBlECXsjBN2goT5ukP98YdXTwSnvsL8UeJpic8+DjwuwsHj9jSoUGGC/fqiJuCV5RZbo5iaYz5VhJynI/hW4mmJDT+O8M+D4nGFj540PaD7wdPSr592HNYX7zU+nsQx/1QtHk9DbPhh1Js8io75OAkHp0qy4iHgaejXzwomfXG5DF2t9EJ1GpHywPHxpNaYPVWLx9OAk1bqfFQd81kkHFSosB/2G3NhVjAMk33Hx0mP+UeFKudxynDS9SaPKhdxEoSDZ00epsLx8ST0kf3GXMMxSfNiX2fLJ7XGrFo8ThlOmj30KDvmgxAOHhdbq8KTgyeljxw05tJ8fxfBJ1UD7HS37ph4GhKLJx3+eVKKH5/Uo/ujwNPQr08CT0ofOe6Ye1JDvqdrBnlAPA2JxZNmDz0pHfNxsbWeBDwN/fok8KT0kft1PHzSGINV2OoU4iTrTfbLRUySdKcpbvykHt0r3Bsnlad4UvrI/eT/nsQas9N11ys8FMxSWScLx2mjBT4pJ6QKx8NJsv2epD7ytNPHoVo8njmc1rjxk3p0r3A4TrK/VX3kdOGpClsJIT4OfPz5559/3E05tXjY7KsHCVE8iUf3R4EnuV+fdH972vvIk0BFnuCpOnlUicV742Gyrx52QeKTKOFwEniS+/WTwvY7Ddg7foIk59eubfOllf6p7O/VN/iM4WHGjVd6IdvjhNv9kNV+RCHliYXEnlQJh2cdT1Ke4mHjXpuf2RBfnBVsj2MMTSPO8lPZ36vF4xnDw4obR2nO9a0xuhC4po6UsNoPyYviRKiUpzVXU+FwVHkKhaNsfmapyDvjBEvXcS2dJJensr8/VTmPCkfDw4gbb41ifMdAaAIhBGZJp9wYxlORuAfBkyrhUOHpz1McBUeRCZqlIid5gWvqZMWdEN9p6+/VyaPCiSDOCuZrNklWkOYqRCGRjOPsREIUVey8wpOMoxQ4zob4TE0QJurnlmcBp6+/n56WnAAqGYfHB9vQ0DWNpaaDVtpw5lJyoXN3iOJ+Et/Pcuy86tfHx2kjVxxl8zMb4nMsg7wo6PoWtqGdyv7+VC0e98NKOW2d7EnFZHLXhGCx4XCm6dLxLJb3hCvuN/H9LMfOn2S21VFw0mPwNJIrjrr5mfTzl840+NDFDm7JujqN/f2pWjyOi9PYyZ5UHHVyf5DE97NQtfus4WGMwdNIrrifzc9p7+/PdML8cfluP604SmL0OInvJ6lgqsL94WGMwXv1scfVr5424sAzffJ4UlQ6nyYcNfFdnQqfDTyMMXhYH6v61cnhmV48KgbPo8dRY7+nMfRQ4eTxMMbgYX2s6lcnh2d6lnyWGTyPC0eN/VanwmcDD2MMHtbHqn51cnimcx4n4btd4fg4Suz3SfFuqPBgeFhj8KA+VvWrk8NTtXjcj/ro05bEelrQrdnc2gmAif+zJMnyZ/K7epJVdY+CRzkGq351cniqltunnQ//LOFZruvYi6pfnxyqfnVyeKpOHhVOB06KClmdCis8DDyKfvUs0MyfqpNHhcePigpZ4VnHszIGqsWjwomiokJWeNbxrIyBavGocKKoqJAVnnU8K2OgWjwqnCiqwssKzzqelTFQJcz34FlIdD1MVFTICk8KHtZYf1bGwNO1FD4gnpVE18NERYWs8CTgYY71Z2UMVCePGVQquyeDimJb4bTjYY/1Z2EMPFUnjwd1XHtWEl0VnixUToInj2qsPzieqsXjQStxn5VEV4UnC1WF+cmjGusPjupOzaBS2a1Q4dlANdYfHNXiMYNnJdFVocKzjmqsPziqhPkePAuJrgoVKlRj/UFRnTwqVKhQocKxUS0eFSpUqFDh2KgWjwoVKlSocGxUi0eFChUqVDg2qsWjQoUKFSocG9XiUaFChQoVjo1q8ahQoUKFCsdGVedR4YFQSdg/OsRZwa2doLrHFU4FqpNHhftGJWH/aKEJqntc4dTgqVo8KvXRR4tnxav5cWPSrweDfnWPK5waPFWLR6U++mhRyVo/Gkz6daPRAqp7XOF04KlaPCo8WlSy1o8H1T2ucBpQ9cAK941K1vpRo7rHFU4PqsWjwn2jkrV+tCgk1T2ucGpQUXUrPBAqWetHB9vQqntd4dSgOnlUqFChQoVjo1o8KlSoUKHCsVEtHhUqVKhQ4dioFo8KFSpUqHBsVAnzCg+EStuqQoV742kcJ9XJo8J9o9K2qlDh3nhax0m1eFS4b1TaVhUq3BtP6zipFo8K941K26pChXvjaR0n1eJR4b5RaVtVqHBvPK3j5MlufYXHikrbqkKFe+NpHSfV4lHhvlFpW1WocG88reOkoupWeCBU2lYVKtwbT+M4qRaPCk81nkZ+fQWF6rt9vKjCVhWeWjyt/PoK1Xd7GlAtHhWeWjyt/PoK1Xd7GiCklPd+1hMGIcQGcG2fP80Bm4+4OQehasv+OLG2CMOypSzuItMLoWkyS44yyxzUlotSyvkHbuAxUfXrOzjid/vM3Zcj4kT69VO5eBwEIcR/klJ+9HG3A6q2HISqLcfHaWpn1Zb98TS2pQpbVahQoUKFY6NaPCpUqFChwrHxrC0e3/+4GzCDqi37o2rL8XGa2lm1ZX88dW15pnIeFSpUqFDhZPCsnTwqVKhQocIJoFo8KlSoUKHCsfHELx5CiPNCiJ8TQnxJCPFFIcQfKx/vCCF+RgjxZvl/+4DX/24hxOtCiLeEEH/yIbXlrwohfkMI8TkhxL8UQrQOeP27QojPCyE+I4T4Tw+pLd8rhLhVXuMzQoivPeD1j+K+/JOZdrwrhPjMAa8/yfviCCE+LYT4bNmWP18+/sj7yxHaWvXt47Wl6tuPsm9LKZ/of8AZ4MPlz3XgDeBl4H8C/mT5+J8Evm+f1+rA28BlwAI+C7z8ENrynwNG+fj37deW8m/vAnMP+b58L/Dd93jtI7kve57zPwN/9hHcFwHUyp9N4JeB3/Q4+kvVt6u+/ST37Sf+5CGlvC2l/LXy5yHwJeAs8PXAD5dP+2HgG/Z5+ceAt6SUV6WUCfAj5etOtC1Syp+WUmbl034JOHe/13jQthzx5Y/kvkz+LoQQwDcC//h+r3GMtkgp5aj81Sz/SR5DfzlCW6u+fYy2HPHlVd8+of7yxC8esxBCXAI+hFpxF6WUt0F9wcDCPi85C9yY+f0mR++Ex2nLLP5r4CcPeJkEfloI8atCiO84iXYc0JY/XIYZfvCAI+yjvi+/DViTUr55wMtO9L4IIfQyjLAO/IyU8rH3l3uh6ttHbkvVtx9R335qFg8hRA34F8B3SSkHR33ZPo89MHf5oLYIIf4UkAH/6ICX/hYp5YeBrwH+kBDiKx9CW/4OcAV4FbiNOlLf9bJ9Hnto9wX4Axy+MzvR+yKlzKWUr6J2yR8TQrzviC99KPflnhet+vZR21L17UfYt5+KxUMIYaK+uH8kpfzR8uE1IcSZ8u9nUCvxXtwEzs/8fg5YeQhtQQjxLcDvAf4rWQYZ90JKuVL+vw78S9RR8kTbIqVcKztYAfy9A67xKO+LAXwC+CcHvfak78vM+/aAnwd+N4+pv9wLVd8+eluqvr3rfXs85L79xC8eZUzxB4AvSSn/nzN/+jHgW8qfvwX4V/u8/FeAF4QQzwkhLOCbytedaFuEEL8b+BPA10kpgwNe6wsh6pOfUYnILzyEtpyZedp/ecA1Hsl9KfG7gN+QUt484LUnfV/mRckIEkK4k+vzGPrLEdpa9e3jtaXq24+ybx+WTX8S/gG/FXW8+hzwmfLf1wJd4N8Cb5b/d8rnLwM/MfP6r0UxJN4G/tRDastbqHji5LG/u7ctKJbDZ8t/X3yIbfkHwOfLx38MOPO47kv5tx8CvnPP8x/mffkA8OtlW75AyYJ5HP2l6ttV336S+3YlT1KhQoUKFY6NJz5sVaFChQoVHj2qxaNChQoVKhwb1eJRoUKFChWOjWrxqFChQoUKx0a1eFSoUKFChWOjWjyecgghvlMI8X8rf/5WIcTyzN/+VyHEy/f5vj8khHhHCPGd5e+2UEqibwkhfrmUakAIcUUoxdDRoW9YocIx8Aj79VcKIX5NCJEJIX7fzPOe+X5dUXWfIQghfh6lOvpA0s/le/0Q8ONSyn9e/v4HgQ9IKb9TCPFNwH8ppfz9M88fSSlrD3rdChX24iH360tAA/hu4Mcmj888/5nt19XJ4xRDCHFJKK+EHxZK7O2fCyE8IcTvFEL8ulA+AD8ohLDL5/8VIcRr5XP/WvnY9wohvrvcNX0U+EfljskVQvy8EOKj5fP+QPl+XxBCfN9MG0ZCiP9RKI+AXxJCLB7Q3Fnlzn8O/M6y+rZChV14kvq1lPJdKeXngOKh35gnDNXicfrxHuD7pZQfAAbAf4uqXP39Usr3AwbwfxdCdFCSDK+Uz/2Ls29S7pj+E0p/6FUpZTj5W3nk/z7gd6BE5b5MCPEN5Z994JeklB8E/j3w7Qe0c6rKKZVEdx9V2Vqhwn54Uvp1hQNQLR6nHzeklL9Q/vwPgd8JvCOlfKN87IeBr0QNwAj4X4UQnwD21Rk6AF8G/LyUcqOc+P9R+Z4ACfDj5c+/Clw64D0ei+JshScWT0q/rnAAqsXj9ONIE3A5OD6GUvf8BuCnjnGNw8JLqbyTGMtRO8L9MFXlFEpNtAlsH6MNFZ4tPCn9usIBqBaP048LQoivKH/+A8D/D7gkhHi+fOybgX8nlJ9AU0r5E8B3oY7pezFEWWXuxS8Dv10IMSeE0Mvr/LtjtnNWufP3AT87MzgrVNiLJ6VfVzgA1Wp7+vEl4FuEEP8LShXzj6HsPv9ZucP/FeDvAh3gXwkhHNSO64/v814/BPxdIUQITAYuUsrbQoj/Afi58rU/IaXcT7b5MPwA8A+EEG+hThzfdMzXV3i28ET0ayHEl6F8NtrAx4UQf15K+cqxPulTioqqe4pR0gR/XEp5VDewR4a9lMYjPP+ZpTRW2I2qXz8dqMJWFe4XfeD/MSmmOgiTYipg7ZG0qkKFB0PVr4+I6uRRoUKFChWOjerkUaFChQoVjo1q8ahQoUKFCsdGtXhUqFChQoVjo1o8KlSoUKHCsVEtHhUqVKhQ4dj4/wM7+e7V6nOVTwAAAABJRU5ErkJggg==",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "error_vs_property(\"position\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
-    "error_vs_property(\"position\")\n",
     "error_vs_property(\"z\")"
    ]
   },
@@ -1346,24 +1221,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... then the relationship of signal-to-noise ratio (snr) ..."
+    "Then you look at the signal-to-noise ratio (snr)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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CN72OX0fcdW2+qef2rawo4KofmRQln10seDkKkICpwdOLgL96PiZIcywhyYuSF5OQSZRhGhphXhKlBUITdFyTRwMP29R5NYnwLJ0fH3Q52laVQV6U6lRCYhs6YZrRsQ1mUcrzUcBn5/PmpL9PxFnBr0+mGJpGxzEBwShIKCV39lZXM9FZnN+Zkb0u8/iqvewvkxm/yXvd1n8O04yXk4hJlKIJNZeSEoK0+FarinXZbMsxEYJbs9BvixW9qh0G3Hmv7lor6/rxrqHRdq1r36PtWrjVATOLM/KyvIY4XM3E75Oxv27dfNOzgq9Dg2017vPc3HVtvilo7lt6UKgwdcEkSGnZBi3bQtM0NF1D1wWmIcgLySItkALKUvJXL8YskoyiKBtqfg3he9T32Ou6Cv5mGTzsu7imTt+3kQI6rvq9nzzsVW2PBCS8s+1j6tq9y7/aC8O1dNKi5Gwe85vTOX/62SWfnl1pUi0vqKcXC56ez689yJMgYR7n1167zjpqmOJyq211U/oqZfuXKX/jrGAcJjw9X1wTWXvde932QHimwekkwhACQxMUJUgk+12b8/m3J0Ox7mHWBHx02L114/ou8PdxVvDZxYKTScTFPOZkEvHZxeLavXrdAXbj4BFi7fdACA57LkdbPnlecjqNyaoMf3WTvc8mf581+k1s5t9UvO65qf/9ZBKpTklR3rg231S77a1sPdWRFUoG2NTgoOfQcnU+vwg4GYcIKQnigrSQPOx7dD2di4Xkcp4SZQW+ZTSKs/VrLRPySgn7XZeeZ3E6jRAILEPgmgZCCH72qN+0fOKsYBSmnM9ijrb8O+cESV7i2TpBmnM2i5mFGa6hsUhzRlHG0/M5h1XJW7coXoxCkrzEd0yE0LAMwU7b4Xwe45j6tbK7LseTtKTtGBQlnE4j9ruuklevBn1fpWz/MoPI43FIx7EY5jFJVvJqErFdqffe9V63ld8d12SnbROlBXFeYukaux0HISHJvz100V2tidtcEr8L/P3JJGIcJPiWiaGr5GkcJJyY+jVAyJcZCt/2PZCyaa29u9NiHueczmKSvKTjmjeei9cNhL8vrO2vK+4DuV1uS6ZrDtlv6pq8pQfFVTm227YZBilBkjMNc3zboJSQFJIiSOn4Fr8+meI4Onttm55r0rJ0dqreqZTyxsVevhlSSvJC8moastOy6TimYmInGaMwBSRxVtKyDUpNNFnCbdmNbWi0bJOX4zmLKMM1dXKplHAPug5BVvDZxZzdtntF5kNlIPVcBKDlGGSF1WRk9UZVL0bfMSgkmNVrjIMU3zaYxSlPL2j60EGSf+ke7H03luUHwzI0xkFKkOZM45QfH/bufK+7HogkLzmZhNc2vyDLOOx9uzj21210q6/h20aTpd/1kH+dqJazaYRnGs06MA2BJw3OplFzUHzZA+y2eyOEwNLVvY6zglGgYLJJXlBK88Zz8brv+VXmBN81n2Vd3PXc3Df5+qZmJ2/lQVFKrsFAo7zkd6czbEMnyQuOBh7DIGEWZSyiFN81mEcppW9xPot4b6/Nk51Wc7GTNGca57wch7Qcgyc7bR70PU7GIc9HIb5t8CfvDNA1jVmcMQkzPMvAtXSeDQMu5wkdz6TtGOxXm/5tw6X6IfNtnXEAcV6SFSVbLYtxkFIWEsvSebC06akhurw2fzifK4XbjmtyWDHBh4uET8/ndF0TzzIYhwqBo2vq38ZBwqOB32Qs9Wf8sots3cYyj/Mbh9AszonTnKyUWLpG37fY7zqEafHazeKuB+Kw5xJV0Oa0kGhC4NsmSMnTi8VX3hi+jqHzuteoM8e7Dueve+Cd5iWzOENWc72uq+YoYgmu+mWz1NvuzckkalpS4yDF0nUMXRBlRbMBLkM87/M93wSG+rrX/iYOkfu85l0H8pep6r4JaO5beVDUC7OOJzstLucx8ygjTAre3fbZ7bj88sWQMJHstA2OBh6PBy2iLKcor0gzkzDlF5cLfNuk71nEWckvno34+eMBtqnzZLfdLHKAMFE+FRLJIsm5mMcYmnLMO+y6nE4j9jrrmahwdZMv5glFWZJLZZJiaBqGJkhLiJOceZzTqVpbfd/ixSjANnWitCIwoVpqpYTPLhYIKWm7FrahcTyOSYuS7bYFQlLkkqQoeX+nTds1ibOCSZgSxDmT6PXZ/WqsbizzOOflKLh2CH12seBiGuPZ6kBdJDnHLyd4lk7HM4kzdbi9yabomHpz0DeHZ5pjGldtuK+yuX4dyJLbXiNI8jtfYxn+ezpNSIsSgdrY31sRpXxdxFmBBMKkpOXolKXkeBzRsnXe2fKb33uTLHXdZrW8EaZFqarl8qoyWd74vg4exW1xMg4ZhSlSqs/U86wmeVvX4qnXSv3+X/YAue+hd9eBPFwkX0tb8k0PwbfyoFgNx9R5f7dNKWEUJERZwfg8oOOY+BZstR08S0eiboxnmc3ffnYxx7dNvEpt1rO15ud9z75xysdpzizO6Xomx5MQWYJpCXzLoOWYZHnJxTxhy7fUrOCWG9ZxDB5t+bwYBuiaYDhP8ByD3bbDwDe5WJo/KJ6HjWtoPLsMCLKcjmMxCTP6vkWY5CDAdyRpISlkiWNohElOlmvoQqBrGoskawydLEOj5RjMk/y1LYFatmT5uyxvLLM45dHAxzSU/ElalFwuYlzDQAJBmjOukF1BmrPTcfjLZyOyvMSzFUR5uCiubYqHPfe1mkW1aNuLUYiuCXxHNjMceHPI4NdB5HrT17hSNo6xdEUEzfKS58OAw577pWCu4zBhu22ja4IoLcnLUq0FIThcuS63ZalvrASrCeUgieIbwfWN7z7X502qqzgreD4K6bgmpqGRl5LTacxexyaTtx9QJ+MQCW9UyV3n9qhrJQQIFLdq+RoKIcjygqwQ1w7kr2P2MAlTfn0yVbpzlYL1fb/DH8RBAVeLVNcEx6OQNC+wDR3X0hkGCb7lU0hJ37MI00zJeAC/O1vgmlqziH3HpG3rLOKC/Y577ZSPs4JhkGLqOl3XYhxm2IZBUUosU0dKqaQ+ghSvmpUsElXlPB8GfHTYpedZDBcJbdfCd0zmYcY0zphEGbmUPBy4FaO14K+ej0mqxfLOtk+Y5JxMY/qeiSYU4ezzSyVHst1Wuldtx8S3DSZByihIMHWNnbaDYwlejhXjfLut5JOTrCRMCs6mcVNZgKpQwiSnlJK8lCyijCe77WoucvUA1Yv46YVqBZ5Oo2ZzK3PJOE140Hd5NgyRpcC3dUASJDmGpjFOUkxD41cvJ2y3HPJSEiY5z4YBSdal5Zh3slNrBMlwnlAiOZ/F/GC/Tde1KMqSl5PojdoLX8fQ+U1fwzY0TibqOtZzBaEJfMd47cG3urG+mpZkuWSvo9p9aVFiagLHMr7WTHk5BKpKnCcZ0zBjq2UzWiQ3VAOWr0+cFc38yjE14kwdiG9S2Q0XCb5tIBAK6FK1wi4WCYdd99YD6nisXvPGATKJsA2NWZQRZjmeZdJxjBsM8WXbAtfUyYqS56OQQZXM3BhSrxz666q6OhG6zxqOs4JPKti9a6lKbhikbPnWvRKmP5iDor7QH59M2PJtbEvH0JVQ317HxTY1TE2QFJKOo4bAL8ch0yBjJiQdzyKNC3RdYxKkHHadKwRRVrBIMp4NQ9KypO2YBElOVLWIBILdjk2UFQihqgVb1xgGaUOIi1J1I//48aBZrEJobLdtpknGwLMQQpCkBX92tsDUNH6w1wIJkyjlly8mtG2DgW8RZQWvTuf0fYskK3k+Dnl2GbDT9djv2PR8i4FvUyLZ8mzCLCfNSqQETYMwzvniYkFWSt7Z9vFMnXmS89nFguE84WwW0XVtBi2TSZgRpAXDMME0tLUtq3Wbm2npiFyhrLqe2bQhLudJ07tGqLaVoek8H4fsdxwcSwcNPjme8nffHbCM8F5tXZQSXk0jZklGXiHgfnU85ScPupzPYmzzzfr8X1UaBe5uM9yVpTfKxq6pgBSlAm7sdezXwmhXN1bfMkhzJcNfKxrXMF54fbXwZTbq5UNlv+uQj0t0X4lsRmlBnBV8dNi99j2v2PYxmlCVb9exmnv1JlVZkpfstG3OZko9wdAFspQEcc7WA/vWFo+UkqIsOZ1eXQ/H0Hg1jXnY95hGGZoQTMMEQxPXCLK2oXEyjahtCwAEAt82bgBTVg+g1WtfX9cve0gPFwmSK9j9NMyI0oJZlPKw7/Ggf+slA95yHsVqOKZO37P58LDD33tni//SBzt8eNBG1wRBnONZBk92WnRctQH6lknXN3g5Dnk1iTgeL/j18YSLRYxjXbU3zucxQVpgaIJHfQ8pJK8mEYah2hwtV8fUNAaexcCz6Po2iyRrFo4QAtfSkVyR6l6MQn53OuPjkynn05BxkLJIMn5zvmARp/i2rh5SUycvIC9KJmHGVstikeRI4HgUkWQFRV5imQavxgueDwN+8WzE55cLdKGBgGmYE1VDk6QoGEcZaVniW6o8LUrVKhgHCZ+dz+m5FpoGF3OlyNt2DF5NIk6nMaVUiKs4u5JRqQe0Ekmc5RxPQqZhRpKrllPdhkjzEtdSh0ReSnbaSkgxzDJkpbx7Oo0pS8k8zjgeR9fu72rr4nQa8vnFgjgrmcdKZmU4j/n1yQwQ7LadL01sqzfPrmsSJjmfnS/425Mpvn2/LHx5La7jCQB3YukdU+do4FFISZSpv9vvOuia9tpqZJWn0fctSlkyDFI+v1BcnX/59LICZLxewPB1vI9lrs/HJxNKCZahNc9W37dxTIMHAw/D0Pj1yfTaewjgb0+mnM0TpJAc9NxrPi5vwhmwDQ1d09jvKhmRKCsopORoy2+e55r/EqU5z4eKNJvliri7LC76yas5hqERpLlKOmwD21Bt2OX1tNWyCeIcWaoDJ8tL0qJgp22zWEOMLUrVSlx37etr+svnY0ZBSinlvdZwkpd4pk6Q5JzPEqVOYWkEcc44TF/L8freVxRCiPeA/wXQlVL+t7/q6y2XtI6p8852i8OeR5YXnM1iRkFCkOQs4gyn0kja7bosooyoKNGAv/OwxyTMiDPlrf1o4GMZGq8mEVLCLMrxbZPDvssiyZhHOYWUTOOUBz2P370Y8/R8Qdsx6Xpq4QsBPcdgFufIsqx6yCmzKEdoan7iGDqXi4SOa6BrV4urkCoLVIq2itF9NlVZdJQXPNr26DkWnxxnDIOUva6DocE0ypSsR5rTr1BZB3hczGMsXUPXRLOohVBkNoRAaKLKjEoWSYGpqcx/v6vaalGiNHykvMoujwYep9OYs7kq/d/b8YnTklGQ0PdtirJgp+0wj7Ol3rWLlPDx8QyhSUaLlIGvGL+04dkwYLfj0K5aXqs921+fzGg7Fo6lTKUuq7nOxTzmp496JFnB787mLJIc39LZadvXMrZ12XRNiFwkBdtth/2uS5QWPL1YXPNXuE+s6/vXWeJdWfph32v65euqkZNxyPk8QUpJz7ewdSW6Nw4TitJqQBBOVQ19cTFhmuTYusagZfFqHHJWZcp3fY672merGe/ppGSYx1iG1gyyQa3BOFMHTg0fXwZf7HYdZR62dCCYulBtXV00qMOdto2uaa/t2y8Pq/e7TnPtamRgfU9OJhHPhwGGoVo1L4YhwyDmw4Mevq1zOon425Mp44VDv23xqO9h6lqD4lqubBzzyrYgzwosXR1UmhBNu3b5Gl7ME3zHWFtlyAo1KYRKDv/m5YSeZ6q9xDVvBcnYhkbLMTk+nTXAmDgrMQ3Ven5dkvSNVhRCiP9ACHEuhPjVys//a0KI3wghPhVC/M/veg0p5VMp5b/5dX2mdYzZeZQS5SVGleFLqRbw6UQtbEvXeH+vzR8d9vhwv4PkCvO+nFX1fYu0KEjzgrxUsNYsl3Q8A0MTjIKMv3o+xrcMXFPndBrz29M5UZqTZgWLtGAaqPnEo4HHJMpwLEHLNNjtuLy70+Jh3yWMcnTt6tbpQhEAt1vK9N02NAxdY7+nCIO7LYdJnNLx1GDY1jWSQrLbUZWNZ+kIhOJV6Bo/2GsTZeoaCUHDzUDAbkVmy0uJLkDXBPMkQ9eUSm6alwhN0nYNLhcKggxqcxMCHvRcDroOutAwDcFHh1122jY/fzzAtZSxVFGWbPkKoTXwbTquTtex2O842KYqs3c7Du9s+czidG1G/mIYMA0zskKx001d0PNt9joO+x2XIMn51fGMvJR0qwro07MFkyq7ui2bTvLytdXganxVOZM6w1wW2LutGnl6PudkWm3Iecl/8psz/tOnQwV+MHRejgJmUdas/ctZjKZpPN7yeWfbx7dNgrTkch6/VsDwLimJVTa37xhoQqtgsRp5odpmcQWNFQjs6vfDJCeofm4bekVmVW1NUFDrSZBgGjrvbPsg4IvLgKwo743GuovxXbeLdto20zDlfJ4Q5yVbvs1n53N+82rGMMh4OHDRNME0zPj0bM6LccDzy4BplDKP82uVzWHPZeBbSlOu4milecGTnTZpXjCLMk7GIZ+ez3l+GdCxr+fwpi44m0ZL1xQug1TxULKysU+o5dpX15xvG2gCPNvA0GCRKHTnD/bbtCtfnrvim64o/k/Avw/8h/UPhBA68L8D/qvAS+DPhBD/EaAD/97K3/+PpZTnX+cHWjcUciwDU9do2Qan0xjLUKJlv3o5YdCyCJKCLJdIyqotldD1DD49n9NyjCZLc0yd/a7LMEjIs5KsKJBILN1AlpKzaYRvmWx3DAZtm0WWk+eSi3nE33k0IC8UKsnUBUKoTXLgW8zCnKIqWx1LR9OVPEWaF0quWYcS9fumLsgLpVXVd226rkWUF7yaJOx3bNymnVTyoOcSpgUdx+BkEuHZBjttCw3BbsvhwcCj45jq86AerB/stTmbRoR5SVJp/exv+5wMFYKr6xp0PVvpXiU5YZY3173n20ocbimrqtng9X3ZygpOdMH5POFiHrPXdflHP9jlX/zukjBThMm+byIQHPYdSkkDC13OYh1L5709n88vIwopaDsGA88kTAt+ctjh41czFklOkitYaF6qttefPr3kg73OeuTLJGIcJnx+EajDVRPVUFRVg+seti/bS17N0uOs4OU4REMwi9JrwIdVmOjHJxM+vwjIixJT1zibxaqVJ2ASZYBgt+Mwi1Nl4WtoaJqGZ+k41YZuCNXHnoRpI2B42zD5Ltjs8vzgqmUSVTImHS7mCWmuWojTSFWhh4Oraq6+9n1fKR8UpWS8SFkkOZeLhCc7LUopmUYZUoLvGCDlvSq6+/AMZlHG5xeqovANjTDNifKSspRouuBhzyXJ1XWxdZ3PL+fEeclOy8KuDuSfPx7ceM/bIMY1Gsm3dfb6LheL5BqooFGZqJIICaR5QZDnxHlOXspmrncXR2cSpcRZyXbboO+rCrhOLu+Kb/SgkFL+J0KId1Z+/K8An0opnwIIIf4vwL8upfz3gP/6m76XEOKfAP8E4Ojo6M7fXV0oTy8Wzea8X7nh6Zpgq+Ww37UVDyIraNtqgGjoKgPquiYt21TKsgOftmOgCcHjrZaSCMkKWrYBErKygpI6OtMwwzZ0frjbYRanjALFwO52TF5Nomaj2G5bnE0TWo7BNEp5Pg6JkpyPHnQ56NhM4xwpJe9stxj4VgNRfWfb58lui88vFsyjnOfDBWVZMAoT3nF9JCobvJgnDHyT3bbLftdlHKSkRYlE8v5em8Oe2yzsrZba5F1LwXaPxyGLKKfr6GpmsSWIsxzbMDB01bIqZUnbuhJx6zgGLfuqpAauLdLlBf7Ott+0BXqexc+PegxXsO+rqqPLWaxt6Dzo+YBGVm2coyDFqNowsyjHNTXyomASZXi2QccxWESqL/3OtvrbOuqs/mHfQyPkZBxjmYIt36aUkoUm2Fmz1lYHvqUsGQUpL0chLde4gZJZHXKfz2LSvMTUdSTiBvChJogdj0NmUc48VtXd55cBYVbQMnV2OjY9aWMZ6lr0Pbs5XJ8PA0xdwUSbSkaCa6qs9WIe88XFgrxU/hHv7vg3YMjrNt36wCtl2aDdtloWL8Yhf/lswnbLQpZqQLyIc/otm1mkFBRejUP2OmpNOqZO37f45HiKhsC3dDLbZLRIGAUKxbeKIlqFar8JVybM1Obbqg7QgW/zchQSpDm6LijLEsHV9Wg5uhq2exZtx8TQRAOhXzeMXo4gyXlYta/r5+DFKOR8FvNo4DXPwW7bbvaGLC9V+6iUmJoOAkyhKtK7ODo/Puw1z1i9psdhSssxEIbt3HY9vosZxQPgxdJ/vwT+/m2/LITYAv43wM+FEP9OdaDcCCnlPwX+KcCf/Mmf3NKpuxm1KN2zSwU/dU21mQ185YUtgd2O2yAvzmYRu20HCdUwTufRwGe6lKU9qR7CXzwbUWqqpN7vuko1M1cPj2WoFlfLtui6NvtdV6FXuq6qFIC9tkMQ54wWCaau2MXtgceDnmrj/Gy3fe0hWNUQckydT06mbLdsCk8yjwvGQc4He2rTmEUZPzvqNwtrtWe7urDrvv0iU9LdP33Ua3qsUZrTdk01F6kqhq2W4qfUfzerWgY7baf5u+We8l0omrv68nUsZ7F1JnrYdTidRWTV0P2jww6zOEcg8RyDvJC4lgkCNb/puPiOwcU84Wjr6vGo+8Zt12SnazNPM2QJQZpxtNUir7SMVmM1sz6dRpQVNNG1jLUomeXMsyhlBVwwGsSMa+nM4rKZF9TXLa9Y6Is4RyIwNCik4NU04rDvY2iCeZSz09aae5IWJdMoVbMtV8FGZ3HKdtvh3Z0W//LzIbKQtD0Fq14kClb+OuJb3ZodBSmmppEUBcNFxvu7bSxN43QW03ENPMdkbKTouuByrq5F2zE4m0X82dOSR1suWQHbbafxvRci4ul5QJzn9H0bS1dVkaFrfHIyvUbsfFNipWeZGFpEnJU4poaGYOAZ5HlBVt0/3zKI0xJdaLy73Wa/63LQc4mzgleTiELKe32OVfSWY+o87Cvjs+XqA1RrMcgKPr9Qw+6eZ/Fw4F5V8GmGbWi3osFWZzCmrtBbhtBA0289D76Lg0Ks+dmtG7uUcgj821/1TdcNJ0H1nh1D54sgVH3dTCECxkHCz6uMbbhIyD2bMM2qAaDeHBKgUD6adpMZe7TlN0iPOCtwDZ1fvhrT8SyebHmczVPCNOPxVotPz+cI4EcVRHC4SMgkHHQcxkHKLMpIC0nPU0QhTYhbIXR11IN2zzKQEkokw0XKOMrZrdAz9QB2XUm87po96HswDq9VBssihI8G/rWN3LeNJoPpeyrTOp/HZIVq1y0/PHfBHe/DDl4FKux3Xc5nMaam87DvVIZVOtMo572dFr87X1Qbk06alcyjgr/3jhrgfnEZVJm8+i5BkldVBtiGzo8Pu8yinFl8VQ2Wa1axbWgs4pwgzXk5UmCHYZioDT3J8SyFRKn7+ssEKzU4l5xPEw4HV9DKvJB4VXtn+bq5lpJyyUp1DfJckBUFlqE4PFGq4NnL9+Txll/BklMWcY6mKfLmz476BEnOdqVfVkt6ZIWa0WhLYIpJmPLLZ2OmSYYuhIJfuyaHlcJAKSSLOOew79CqqvK0KPFMg1fTiIOew+eXAZpQ17rrmhV02eB0mpAXkp886DT32jV1TmcRrqlhV3OTSZiy07aRFQKoXpfwZsTKjmPwzk6LLy4D5olCDPVbDq5tkqTqsHBMjSQruFgosc++bzXXQxOiOtTEayGv60ABuqbxaODdOIylUKgV21DPRV6WlR6dMltrm+ZrOTr1ez7ZbTfgDAVbl7cOKr6Lg+Il8Gjpvx8CJ9/kG97WJxaoDHWR5DwYuEzCjPN5zCjIeHenxShIG3niB9Vr1UPO5fbJbZC8VSy4Zej8cL/DJEj565czWraBYWhkpWTgGE1G1PfUJjrwLY6zglLKRlJhHGZIGbLbtng1jXmy2772nbaWSu+zacRBz8WzdX53OkcCToXiGHhWw75dVxLf1Vtft6G/ToSwvl71LGcd7+A+C3z5b2pnwkWc03IMHvQ84uRqeK0JwcC3mpbK2SyuXkvSdk3e22lxMY+ZhgWeo/OThz5dTwECjgZXA88kL5jFGX/+xZCuZ+GaeiPpMvCtphpcNd8BtSn/9nSGb5tkRcE4TDmbpvz4QbtKSFLartloXK1e+4Oey9ks5sUw4tGWiy400qJg4NvNdamvW9sx6VZ957N5DJrgsHJzDJKcrmvyo8MuQZI3/iZpoXg/TgUbfTTwmg1sFKQYAk6m6oCzDI2OY5BmJTvtqzbJL5+NGIVZw+04m8acjCIu5gkt16DrKA5QjXTKC4lvGVBpSulCo+2Y9Fw1S3FMHcuoVIAz5TM/S3J6vkruoqzgoOMQ5gVJIbEMjZ7vcj6JebR1fU29qfWpbxs8GwZKdSDOGFeD9J5r0arQiWfTmJZr8MFeRxkyVSKiQZyjaeDZqpWcFmozn4YpHx32bjxP92VdDxcJHcdku2Vj6ir5vFjE/PrVjIFv03fN5gB63evVz/AyAg25piSu4rs4KP4M+IEQ4l3gGPg3gP/e1/HCQoh/DPzj999//9rPb2tpHI9D3tn2mccZszjjfJbimmoj9Ux9rSzCl6HS15nhnz69ZBRk6AJFLrMN/qjnEWU5XddCohz3xkFKUUpejkOMmcbzy0DBTFEbpm8rCfMoK/jsImCnY1/7TrXp0cOq9DYMjafncwxDfY4wzZmFWTV/ubt3e1cbaLn/PAnTSvAvwzf1RoTwPlXCanyZazsJU37xbHRNg+vXJ1M+OuyqwWeYEaYqw302Chl4Fq6lczZLGFcZ/UHX5e+/t8XLcQgIHvbdBrlTZ/bN+1hqTjS9UOiaw4HHwLd42Peu/c1q1P3noCJfWobGw4FDlJV0XIX+idLiGqz045MJSVriOwY9z+JHD7p8cjzl84uArmtiGBplGfPRYbdBYn16NidOC85nShrl3W2fnmexiHM1f3GNhgD5ahozDRNsQ6Hv8kJSaiVdz7rxHRZpQZoVuKZBWUqeD0Natqpmnl4sGIcJwyCl61mYuoK+honaKOuZ0G9eDTF0DV1AmCqQx+Ntn0mY0nUNkjwnL0vSUmIgKGVJ17PJK0OwUsLT8wCAnYqTMPBNBppN2zabmVhWlrQc89rn/yp6SLtth1eTkONJjBCSJ9stzmYRLcfkQd9FH/ikRcFexyGqEFRhWmBbakZWCx+6phIHzQtZ8R5uysi8rlqOMwVi0KpWtmfrzKMUWULftdTBmamBO3D/6rtCoJnGihLkSnzT8Nj/M/CfAT8UQrwUQvybUsoc+J8A/y/g18D/TUr58dfxflLKfyal/Cfdbvfaz28lBmUFT88X/OZ0UamKioYHkZZlI4uwHPeB19VRLzhH1+m5Bl3X4nKWUFSEsUmY4Vo6lq4WkpQK+jdPcrV5lIq455pqNhIkObqANCuYRhk7K65gizhrMr/a9/t3FwFfXAYYumopHPQ9PqqyyrviLpjmLMr49cmU//zpkN+dzfn0fMY8TKC6JsvkoHGY8NnFgleTqPlZPahbhYp+mWu7rMGlaRqebeDbSl9rq2Vj6YLdtoL19j2L40nIs8uQLC/I85LzacTpNGISphz2PA67zjXV4fo9P7uYY+gaaSHZbrl0fQvD0DmbKv/xdX+zeh3bjsFBz+XdHR/fVm3AZ5cBL0YhUZah6+Jamy7OSlqOkng5ncbYhs57u2pjncUpeVHQdk2OJ5EyrColtqmh6YKWpRPnOUGS4xgaH+x3OBp414QdwzRDExpmNahVrUyNMM2adXs8Dnk5UgPyrmdekdPKEoni0XiWTpKWTIKUpLqPsyjDMTXSXDKqpGoOey7DecSvTqZkRcFux2YW5mrDb9l0PZttz8IxFKKvKEpOJhGfXyyYRRkCwXs7PkgFg0WDg77P4y3/GmnuRw+UKdRX9bGukyTT0JjGOY+3fN7baXM2T8lKkELtEaahYek6F/OkaaO+t9Pix4e95nPX5NGskOx17QbiC+vd+NYZLNX3Yxm+Pw5ShCbQNNH8727bIUxzfvFs1KCcbjNsqqHNvq0O6jDJAXHrefBNo57+u7f8/J8D//ybe1+uCe5ReUostzTUwA/O5zFdx+DFOOBinjLwDB4OFDnmx4fdtZDH+8Dr4GrB5VKiaUrjBSHIyxLbVJLnJ9Vw8/kwoOUYhGnBJFDDRFllU2kh2e24BGlGIRXZ7t0tj7yQnE6v9IomUUbfM6uhqWp17XdsxkHGi1HEg75zDZJ6l0TDbTBN21T6WNNYzU10XcPUNBxbEQfrfntNDuo6Flmu+BW/PZsxWSQgNPY6Nl9cBvzubM7Rlt9UIbe1wVY/5yLO6d8Y3muMw5STScQoSJHAxSxhr2vjWybjMGaeCBxD49HAZ7+r4MEfHtwupreI1UM0TwvKUmJqGo/6LvMkp+OYr18HUvJiHCKlaqvESY7QBDttG00TREnBQfdq/iIlhEnBZJHh2ipzPJ1FvBpHHPRdHg985a+RKFSOVbUuO67FVssh63mkRYGmCfKqmlutHj3TYJpnZIVCzuSlynQtofHLFyP+/PMRSV6SpgXbHZtFnPFg4HI08IjSvCFKJnmpkFWuyeUiwTGVJIiQklmU8t5uG1NXHB/ftvjZwCfNSgxdx9ShZRvXrmE967hYJHRcDUrJLMqaWUoN5cyqVo4mBD3P5GKRKAmOlhLpPJ6ETTvyyU77zsp53fqaRVkFhkgQUuCYav/MSqW4PA5SDKE12m31mr9ahzp9zyLJi4pQWACSy1lCLpcG/pUVweuiVrtNMgU82GrZWJoi+PZ9C00TfH4RcD6LsE2VNBm62g8e9Ny1KLDlmV89f6Usbs0ev/fM7DeJtCgbslRWSKJceVa3XatpaVzMYx70PUrUjeg5JovK3EjKgIOeXyFi3lyfvm67OKbGLFIPtmMIFlGOLrTGP7ksJGFWcD5PcHQN3dAqqKmOLCWjRcLAsygMHd9SMDyhCX75YsR+x6PjKsLYcJ6wW4n/1YQwxzI4MA12Ow6aoHnYlt3G1iEzlttARVnyyaspYVxwtO1xNo/xTJP+ls3ZPOFBz6Eo1YN+lhd8fjHn88uQo4HLUQXdHUcpn58vcGyDR32bz4cBWV6y13F4NVWHyrohOlLdv9oQqv6ctq6uaVqUpIVyspNSEqQ5J0+H9D2T7bbq5Z5MlNSHrmkcdtyG+7CKHloXpqHx/CSk7RpEeUmSFjwvSg46TuMsCKjsRIhr6yPOCvU3WYFnGsRJzhejiK5j8s6OR9+3yQtF+BsuEj45mZLkBR3HrNpuJXGWE1R8hocDp6oAKiG7WcBOxyGRV31mQxdkpZKSCdP1pkdhprgs8zjHtdR8oO0YHI9VFm8YCv45S3KiYc5Ox+OLC9Wvn0Y5WVHQlVYlZaGeJYkkKwqSTJExt1oOB5UqbJSo6rDjmCRGycO+h5SSMM2vJWJBkvNkr827uy0mYcrnlwGebeAYWvO8qedXVXDLfjA1nPrXFerpQc9r+AP13657hpfnQVo1j3l2GXDYdSkB11YaZEqZQMfW1ZDdNrVGu+1ocDNj77gmUaqR5Kpl7Jkaf/VygmkoYEWSlYwW17kWq/dpWBFWPzmecjhwVdtRF1zOU7quTlnCJMyUwGeYNIi0HUmlihtxMY15ste+G311+2iiibfqoKhnFI/ffe9ab109eOW1QWvPtysr0JLtlkPfs/j0fI4mBNsti6QoeDFSxKb7EKbWHSbLQ0ZDV1m80DVKqSCvBSV5CeeTkLZrMskLDNug61nEaU6cl7yz06oebtUy0RwlAb2IM3Y7LpMoBaGysw8POxXrthou5yWeoSGFEj6Ly7Ipx5fdxurrBFc901UYXZZLHm97GLrOF5cBjqk8N4SQTUb6xaXio+hCU+KCqbqGcVuhjQ57HqWUFfpDxzcNgqQgL2N2KxmBZYkFTcAnp3OCOONo22e/c5X5O5bOxydTOo6lTJ7ChOejkB/tdxE2jby4aSjRuTBV1yXOFBnxoOuQFSU9z7xRNS4/pK/GEcfTCG0q2OvaGEIwSRTM9dGW34hHpnmJb+sUBQ0hLqiqjpZtcDaLGQYZW75JUpQcT2IuFykf7rc4mye0XAspQUpBkJb0PYsoK5lGqg35w4P2NTa+oSsmvaap+1jzIPKq77zcm5+EKZ9dzBktUsKsaPzec00yCRLSQhJUma9t6grWaasB9OeXAZoe86DrcjFLOBlHPNltNQislq2GziejiDAtaDtGo1CsCTU7kELSrQQqrSo7z0tZ9duvvtOyGGatBlCUsppVqKi/l2PqN/xgJpOoYpbnlSbUTemL1We4rvqjNOe3ZwrwYeuClxM1t9KBcZxhaBrvDFxGYYrQNN7fbTWSIauS7KBaO794NkKv5DLmaUHPt8nSgl8dT3k48Djoqmy/hrUvr7txmLLTdkjyAtvWlVimociytqGTlyVbPvzt6QzfMUkL9SxeBDECeDkOcAydkivUZU2anEQpT3baHE8ixoGyaLYMDXTDvPFF6vV22z/8PoaU8p8B/+ynP//jf2v553UWsizLG6YZhqY8rmd5yiJVNyzKlNdy37N4OPA5noRr1R2Xs9DbEEL1+/mWoZiuaU6WKx2ky3mCa2gYJnR9m4c9JfQWJgrloRa2hm/rbLdtjgZexcysbEPDlH5F7tFErYsk0TXVa54nOb5lcLStILvns1ipw1b99NptrF5AyxLTNcKrhtE96Htk5YLzaYLrGGpDKpUFbNtWHhtns5gkK3BNG93Q2LcMQFIUEKUF8yjDNDTGQYLkaoOYJzlSSH77asZW2ybJFJyz1u4vSknPtZgEGUjBftephr4lP33UV+qwcUZWSP7oQZdFrKrnJC8Jshwr1xGiZBLlCAllIdnruoRZASg/9Z32Fc9oEqZVZl+yiBW3ZrdtcTbLOJnGHHQd9ruOQjlpgrNZzCTIeFUhqnbbjkKjzM852vLZ7zpqeKlrPOg5jMMM19Z42HOI85JfvZzzwX4Ly9DwbLUBCFTf3bUMwkQ07aUkzhoyV5QWdB0D31TikMeTkHmck+ZquGpWfJ7lob8mBBqCZ5cBR9sewyBVUhpFgVVxbgxDMFqkdFzVOql1tDRNQbIfb/tEaa4IX7qoqvCUR9s+Hx10yArJPEoRQl0b3zb4wW6Ll5OI4TzmkeuT5gVhWjDwzGstm9V2Z8+zeDEKsQ1trSXxKkfleBwihDpsa9i3qQtejqJrhLblZ7iWAP/t2RxD03BMNdydxRFCwCTJm0PrcqEQakd9l1Iqgttts6laiWAWJrwYJbwchZgVjFzXBNu+wyLO0DWNByt7SJIXGJrGKEjIipL9jsOrSczlPOGw5zZqt0KD7Y5NmksugoQ4Lui4BllZkGSSSaD852v+jqXrtG2DRZzzy+djZRNQUBGFNcT3jEfxjcdqJbVq7O5ZOmWpXOGsiuV7MVOeBQddF6Ep/aQgyRgt0mu2o3ATtfM6t7KTcUiSlWgIbF3DdPSKRm/TcxUxbJ5mdF2bji15sOUxCRKyUuKZBm3XuLa5Aw1aoZAlJ5X0sUAdhu9uX7Ev61bbwLeuLWrb0JjHOaMgaZAZUVoQBwlxdmVFOotzpmFCyzYZ5wlpVpJVvemDroNvG0RJUfVvXYSQ7LRshBBczGOyoqAoVfnuWhqaJjClJC9K4kwJH/6w06YsJbom+PR8gWvp/O58zjxSm/5Wy6LrWo3ez8C3kVLSsg12Wg5dt+RiFtN1TU6nCdstG88uibKScZRS5pKdlsVu2+VsHqHrGoYOtqlhmcY1fZxfV5r9sVRs6GihJA92OkpczzHVI3O05ZAWkot5wiLOSLKc56OEaZzyzkBxE55X8MqOa5IWJbquEaUZpRC8moIQqpdvVNl5XXkGcc4wSPHSgq5nsdNRjOq82iijQirCZcXzOZlEan1Vsw/L1BHVd/rsYo6pKwj4y0mEb+nYhs5n5ws+2OtiaIJplDENU0xdYxplFMA0ShvZmAc9xfR3TMXHGEdZM0ReJKqy7bhmwxlouwom/e6Sy+C71RxqEqSkeclh1+FwZZP1beOGsc7AM3EsYy16Zxl993wYMEsykqzEMRRi8WjLRxPXfSdWn+FaAr+eRQghEBoITWPgmRxt+bRsszHNqgfE9wm7OuAPKtWD83nMi2GowAEIPFtvAATLe0hatbzzQjYCowc9h/NZ0sCFj7b8iiMkiMqSbc9iLhQPZhqkyL5EaBqi0ddSw/msUCCd84sFrmkgBTiVZhmy/F7xKL7xUDoo5TWI5Wqrpe2aPBr4XC7UxrjTcfAtnWmcI4C96qQOs4JFrErZOlYhd68jigF4jsE0zBhHOVua0o75q2chg7ZN2zYIs4KdlkVRQMsy8Eyd7ZathPSWdO3rB2MRZ3x8PGUa5ex1LAYtJQcep2pzrQ+o47Eibe3Vwn5VbLVsnj0bKSXJqkKQ0ChJ1llbjZDxKoLdNMyIMpWFvFNVK3Zf42hLZaijMG3K7Z5nMYtUtr/Xtum4JpapMV6knE9j5knGe1teJXde0vVMvriY8/QyI0xzXEMjLhQkc6dTst+1yXJ1QPR8i5fjEN9SEg6GoVXZp2jIZVIWDKpN2rdNoqzgQc9j0FKVSynhYZUdAs0w2bV0RmGKpuapxLmagQw6FpMoZ7tl0XEsorTA0OByoTK/nmtWCLaQJzs+jmU0ToRSSp5fLhgFKS3XJC+VErFfARhAZdDxNKbtmBSypOfa1xzgzmcxRSl5vO3fAB58dNi9IY0yXCSMFilZUWJV8628UO3HcZjwowNRMenVMLblGFwuUnY7dmVWlbHlmRx0HYSoRC+red9WS+mKfXahXPGWVQFWSZK3RZ1FL8+ittsq0w5SVXX8qDLzWhd1m/LVNFZmYJZBlKS4toKmCiE46DrXpC9Wn+Ha38MwhGpPa0pMsWUrjoFChl19rxrdda+QEhAkRcEkShiHKYYm0DVl4uWYGh8eKoTm8h5iG1qj3eRaaqaoDikLgUpAt3yLrmvyYhSSF4rMm5mSeaoEKwskjwcesnKNbNsGWXXv9xtFXuUgeU2+5ZZ4qw6Kekbx3pMnN4hfy9l4HTWj+rDncjKJ+MWzEY5psNe10YVGQcGTipRlm7dLR7xObvnT8wVxXuCaOpYu+OR4SpDltG0TSxeczRM6tsG276hqRoe2aeKuIFa2WjafXSw4nUYEsdKLMs2CMCs5HUf8+GEP1zKaXr8EtltKIfZ0EnE2jRoXvWVkRpSp61S3dZarpWWEjKVr9H0Lz9LpVoS1OiZhyvNRyHAWKwa5bypxwcooqedaJHmJUV2vHx52lJ+4EI2KZZgUOJZBMI7wLaUZpWlApZN1Mol5OHCbQ1AxttT7d12TaWXh2vNMPh8tiDPJoy2bPFcPXVaJLu621XwiLQouFgl5jXaJ86r9o/r8F/OYtqOzW6rfDxO1gfRdi6wo0HWBXtSCiSWHPRtNCKKipJDQq8iFWVEyDdV8oN9SGlUXFUDhsOcxi7NG82rLt7iYx5ViqsCr2pZJXmLpgpZt3Nh870pUCimVn4iu4ZoGz+YBYZKTl0UDenANHd822G47mIZOkKrEaadlsdfzsEyNvY5SPFWifmr+og4Dja5zXV59uYJfVUJoQAqopKbtqvX0ojIAezTwm55/mpdre/irSgG/PpmBUBXZbssmqtqGkyDlT95Rw+Jlg7EwUUPo2ijpaOBxMou5mCV4NnQdnU8v4srDBA77Dr5lVLOu9FrF/ZoNiYd9l0/PFxSFpOdY5LJkGOYYurrmRZXEL+8hPc/i+TBUystS0m0pHTchJf2WzUHXYRimjBcpUabag4s0Uxww26brmMgSXMtgy7eYhimfDwMMTWOnra5lzzO5mKd4ts54kao5kPiO4LHfdtQzij/5kz/5t74M69cxdd7baZHkJXGak5USQ6OBkuqaduPguS8Jb7hIqo1Hb7DZhZSYFbyu41g4pkHHVkiKWjZkXTimjmsoWWFd6FhWwY/7XXRdIy9LwlSpbr6cRCrTqIbMbce8JiZXs3MnYYphqE2gfs9VJUnb0MilZFghh7bbFtst+xqsr/ZAsHQN1zYI5jGvJgXv77Q4qNAjNe6+ZRu040zNZzSBrolGWmMSBpVgoYWtG1wEMY6usdV26HkmHce84gNUD+E0ylQ/39T56cMup5Uncc+xcfSMOCkokZSyMkcqCj491UiKkqJUWjwfHXQoJUyChLZrEiSFagsMcwyh4Zk6RwdtxSlw1Yzgo8NuNSBWh9f0ZMbJNMazDHZalhIiNDTCTF3nfsvmyU6bz86V2U3L1FUWneY83LrijriWzs8fDxguEqK0aFwQ1dBctZhsQ7vWtlkHZa6rD10TTGIlpjhPMlxDZx4lmLrOr15O+XC/haEJno2Cau5lc9DTKXKJZWoc9hzivLjRk7/avJV3+XIFP49SpBCYSzO7p+dzpBANeu3FKGQeZyzSHBBKoNIzGQdp47a33OK9Sylgq1Jstarr0QZ6jkmSF9eSrMaV0FI+HCfjkFGQkhQSHfhgr8UiyXk+DHFNgWUolOR4kYIPQtysuO8K21DQ4E4lZ3IyDnF0g0FLQWMv54lyqVzaQ5KsYBjEPB8FZFnBo20fW9fINcHDQavxnbcMje2WcqdECn50oDxy0lzpgxWSSjsLbMtgy5eVn4wyRfNsg8eWTpAph8NpnKl+2y3xVh0Ud8V9WL+3qZt2nJtZ3HK8Tm657ejM45y80ChLhVCaxWomoevQsxRCpOff7Xk7XCS8GIeUZcl+z8WN1NBXF5CWkkWSs0gybFNJZwdxziLNFJlGCMwKM1+ztw96Li/HIS9GIQ/77g3jlxreiZQMPJNZnPP8MmTqZDza9kguFioTD1NGYYZvG7zvtnlnu0WQ5Bx2lX/EsuRJjULTBPzsqM/xOGykDwRQlLDVcijLEivSOJ0naBK8Q52jQffa5ljKJa+M6l69v6sQN7PoHENZcFMCkyCl3zIRWIzDlCAtOBp47HYdJlGOYxmNXlXXNTmZROpgyVJ+eNil61o83mqR5SXTOGUUqE11aCcs0oKfPurxbBSQpkpryTM0LmYxDwc+oyIhL0qejQJsU60vy1Atv72O8kBfXV/LqJmiLHk1iaCSVh+GiiNyG5R5mWmuLwRFqVRg07zAMQ2OttoMfIuOa3A+TZjEGZ6lcdT3eHoZUE4ltiHwXZNZmPIPP9i5dp3vWvtIySzOlXR7UTbVa5ApSfx6uHo8DrmYJ9imMs4ZLRIuZjFHW15zUCjGf8rTCxiHCV3HWjuQ3uu6nExCJZNeIb/CLOdwaba4bDBWr+2zWYydFjwaeBhaNVOr1Jd3a/hzhTicxzkf7LdvVNx3RX1fREWSbbsWUapmKJqmgBlFNUuq7+MnJ1Mu5olqLXlq1rPbcXhZaWyJVDTQd6lJtn0bBKrjoQl+c74ACQ/6Dn3f5tU0ZqcFjwZ+A1qxDY2eq+RnPjmZstd1eHfbR6ZRcNt3+YM5KG7bzEGVpWpoq0hk/ZbFTut+jlmrr78ajd+FoRMmyp/C0AVHA5+jLbUgs7wkL9WBtC6Ws6muazJPcl5NIrbaNtNQCc4tIqU90/UsfnzYIcoKgiyq2gySvbZDnJVczCJMo35gFPHsfBZzOo3Z7TgIrouXdRwTUxNX0EFD4yJICKu+tmOqwejjba+BTJq66sN+cjKj7SocfJ2sWLpqDWXy5j3ZatnouuD5KODXJ1M8y2DgKURGUElR1PG6Ku5Hh90mGx9XSp+agJ22janrvJyE+JZBy1bQ6UmYstdxWCQ600p2/I8f9wlSNTyMs4LPzxcMFwk/POw0WS1C+X/4uskHux2F8soyFmnBvmsyDlM1B6s2iCwvqveUjfyEZ9687zVqJk5zTiYRGgLdEEzCjFIq2YZ1UOaPjyfVAao4F7tthdlPMpN3t3u8msWkWcF22yZJc15MFpiajiYMApHTcw1O5zGWMNn2bUxD4/MV974bLnqeVRFISyZBbfJjUVTM8v2uQ1leAQZOpxFhphSULxeKwdz3LV5NYr4YBry30yIrJC9HQaME+2pasohDnEBv5o31OjrsuURZQZjkpJWCbt+3G9c6uNmem4QpnnXFkag1yNR7KoRhyzbwLYNdXTCN0mueHKfTm8S+dS0yIQQtU0dh7CSPt9wKrqq8WzzravZZH2aGrsi5ooIXj4MUz1T7R4kkycvKnwL6rslux+HVJOJ8nvCo77LddrAN9V11ETMJU36w16bvW40x1/ksBimvHZ5SlreegH8wBwXc3MyXncymYYImNGxTtXa+uAw4qtQb75LneB0Jb6ulXLJGYUbPM3FN1XIqAdfSSCsClG+bSlKkytKXX28ZEdH3bWZxzuU8YRYqd7rnp4tKrtxUTOwKOruIc4QUlCUUUg35HVMnX+INOKbOo4FXiQ3Ka0ip2pdhHClEjASGYcwsztny7Wrop7LOy5lO21EPSpIXXMyS5v2Ox2o+dNBT1qYvx2GT7a27JyfDUNmjSolvmww8i7KQ/NnnQ/748eCatv9tVVzLMTArlNQszmjbCu1DlXV6pk5UEdkU8kdlW6fjiP2ee6U0G6Z8/GrGKEiqAbSCl1qGRte18J3KNdDQG+Kfa/n85bMJrqk+gyxhFMS4poGuCzShkeSpgjdWbbx166mucIMkZxbnmLpOWUloXFa+3Q/6V2tNSsmWb1dmWmpgut91edhXaKN5kpPnJQc9lzQr+PhkRpHD/sAiiEtOZzEHPYcfH/ZUclFBrudR1hxKcVbw9HzOqFp7SVbwN8cTNQy3dHRNI0hSdKGq1ygtmFe2wrZ+hcCxdcHTsxChCeJMZxJm7LQt8kq2RlStq1GozIqkVOS5lm1x0HPIC9msI8fUebKEsFp9fmopmVfTEt9Shj3zOGMRK3FEpJpdTcJUycADD/teI1U/T0pmofrcuhCkecn/8y9esNWy2WpZhEnBL56NmrbxaotMmjp/ctRnFCrZHqW0YDPw7WuHV32Y1cNsUxeNtWrfs5iGGZMowzaVGkKU5cSmeo+jrStlY8u4ek2ralVfqTWovy2k5PkoVPOOhSKtCu0PhEfxZaPegJXQnXqozaofPPDthsm8Gl/Gtcwxdd7bbeNUGRjAHx+pAds0ykgqLRpZSsylTXr59ZazIcdUcga2oXE8Vj4LP9zt4Dk6F/OUWZLTdZST28O+x4uRkssGSd83KcqikhS+iqyQhGlGq11nO2rQOQuVdWuSlwx8G0MXjfaVpkFWSkxD46Dv8mqisOqGrjaxvCx5MPAQKHazqSnE1KBlA2ItG7Qmhn0+Ctht2zza8rENnfNZgm5CkGSNLelyJr0adc++lhoHFNmr+t6LJCdMcy7mCYYhcAzBOMzZblv0fBNdiGaTjbKC/Y7N6TTGNUw8W7Ftf3c65ycPe+rASQsOtq+y1+fDQEEgNQXNNAyNw57HZaBQVV3P5N0djyyXN2S/1/FwZonKuqWU5CXsdiyKQjKO0mZgXLdmfMdQlrbVdz2bKQJWxzURQM9XDoZfXCovgr2eS15CyzUwDcEXw4AfH/SwaknzUuLZV5Lmw0XCKMoI04JFooySHEP5egyDjEcDj45r8tvTOQ/7Hq6lMQsziqLE6zoEaY6lCxZpjq5r9D1DeWJMYt7b9XEMJSyYZKVSSTUUDPxynlBUctpABWJYv47WPavLUjJfXC44n0XompK4eTGKGAUJOx2b3Y7TaJA92Wkx8G0+eTXFNpSmU5hmfPxqhm9q9HwLhMYiKbB0wZ8+vaTnWs3cLcllU4Xo1bU/2rouw7+OR9LzLE6nMQCylJUyLcrr3tC4mCdolkq84lSJYf5gv4MQghfjgCAtCeKMrFRcn75vczwKcSy9MVHrexYnk4jfns54Z7vNoGXSwLvWxFt1UNymHntbrJPaLcqSk5mCzErJDbRG3ZK5TVn1VjMXU+dnR/21B09d1ZRScjpNGsy2EMrjYnVYWbOcH/Y9ZlHGNMowdZ29jupJns1iWpZOUkhMXaPjKflh19R5d7vFNMqYR9k1BIimwXARs0hyJtWmedB3+MtnEwxNeR4LzaBE0HfV0LEmqm23bSZhxquZ6ulOg4ydjiKlfXq2qHDsYOmKPLjTsjibxdckLyZhyv/312dKWiLKiNOcaZSx31X948t5Siklo0ARGO8aKK62pXzLYLQI6Ps+pSz57ekUUzf4YL/NJMr47EQxqR8NlPBeKcESetPTnYaqFVVnYo6pEcSqJdBylLbWqnfFk22fScUDsXSNREo1jH/QJUwK1cKw1kuxr/JwXo4jhouYojTQdTgdxyR5jmXqPOpftWayPFFyKaHC5udlwbPLgIOex1GlDfZyFKpZVprzqJKwOZsmdLomvqXz7DJgFqccbfkNnLL2Lwcl+nc+jWk7qqV4mRUESUaaq+89nCfouvL4sAwFA/ddg3e2WuiaQMqE42HUQG3zoqTIS4I8Yxgm/OSwyzjISIqSTlliCR3TEJiagqnW0hm2oTXQ5rsSt+VraxpKXPNppQDc9QSfXirhQUoYBxl/51GvIZD+zcsJO20Hz1AOcplU4JAsLxilBbN4VvlOKH94QwiKXFKi2mZtz2LLsxuSW5rlfF5Z/FqGknQ/GYckVaKmCzW832k77HXsRsOq1kI7mUS8v9vi0cBrVJsnUULbMeh7pjrEjudoGsyjlERKHE0lS89GAQ97Lm3Xou+pNZIXBbNYtbHPFzEI7VYo11t1UCyjnu7z+6tSuyUlJxOFe683hc8uFggpGxjfcktmWXx3lYRXM3wl4JkKZRHfUnXU7NCzWdyQ37K8bGTOfdu48Vo1w/p0FilLUF0NuA57Ls8vQ55eBvzoQZeWpeFYJqVUHgB1BvvXLyakhZpBbLUtPj8P2Os6pIVi3I4DJTC427YxdIW0eDjweNh1eD6OyGZqprJIVHa513boty3KUiKIOV+oXrVrKbXLJCtxTeVJcF7BjT1LZxHn/GefXfLXLyZkueSwryCPvztbkBUJ0zBlu+WQlyU/ftCllKxtuyzHaluqRhKNgpS/PZ6jaarFCEoTqWUadKsedZ3NmbpgEWXMk4Lfns/Y9m1FSqzUYFuWrvDpjsFHh11Gi6ThrNTeDrWtrmVoTOOM3bYyAXJNg3ZuNBXDp+dzOo7JYKldssxFeH+3RcvR+eR4pvwjqlmNWJKt9i0lyBdlRfO+J5MY3zEbZziAJ3ttsrxASkmcFHR8iw/3W0R5ySxI+cF+u2lv5rlCbhVlyY8qSfNno4BJpOCUfd/C0DVejWOiPOfd7ZbiiwwjdjsW+12V+LuGziLOcCwldT6PcpVwpSUvxxGzKKPnGpXPvKTjmhRFwW9P5wqObeoUSNJc8rOjK5G/2gPkLkn81dmElIKtllVVZ5IX0xQhVAs1L1R1YujKnzyvNJOOJyFSSp7sdiqpDA1JgabBNMwYlgqs0GvZmIaOEJKzOGc2CpVwpRQYVdU6jZTXTZwV/PZ0Rtu18C0dxzTIZEnXNbmcx/R8m8Ouy9aDK02qcZhwOrmSnwcabpgQgtNpTN8zGYUxtqXTNQ10lNx7x7MQmsZBz+V0GiGRjEMl154WKrnTTPvWYexbdVB8mYgzJWD2fBQ2khTzJAckHccgK8vGIQ0BW+2rRbjOKnOZhLfM8K0ZlqeTEE1XZeOyOQzQsENr9iSAqLL4Wqdmt+00FUCcFQ0G3LNMpmHSSCpoqOz9/b027++2r2m8TGOl8fLJyZT9rqs+Wyk5mYT0fKvCbVfkwCjjd2cqczR1wbvbfvW9Y7KiRBdwPk+Ypzk9x+K93dYVKVGo6iTOcoUkmiXNEP/T8wUd11RD1rxkGCif5FGYsN+2mccFg5bFB/ttXo1Dno0j9rouHx72mhmIYobfLpN+m5uhlJJBS2V4hVQbTc+zKjFBdcirdpXD8SjkbJ4waNnYmkokYkpsU+NyluIMlCFQXdXUKCRTF8zjnBfVIHav4zDwFWpMaILPL1SF5RiCzy4CoqpyatkG8yRvVFKX15NvG81AueUY1QxtwUcHbSZhyn7XrYbBIUFcVu9pMw5S3tn2r/fqg4RplPF4y+f5ZUDLMnBMDV1Tqq+1SN2vT6ZIXWsY0ifjsHKP0xm4BuMoJ6kk20dR0nSChFCyKFFW8GIY8v5eW7H3K9Y/2wrE8benU9wKmnw2i9A1gaFpVfJW8vll0NiQprnyX++6VoOQWwYvnEyiW3kky9V4fWjbhl7Z3jo82pJMwoyuo6TUp2HGJEw4GSc82nbpuSYXc51PzxZ4lpJ+7/smp+MC3RSkRcH5PGURpvzDgU/L1ZWwaKmG6pfzRG3qQrkDGrq6hpMwo+PajIMEXTgMWooQl5eShwP/mrFXXTF1HIthHpNkCgWnYOEafV9V9mfTmEHLZBQmHHYdJGr29vRiwd99Z8DLUcDjLb9pLYMCY/R9qzo8/8CY2a+L5VL1nW1flXiLhCQtmiFmv3IKK6W8YdS607JvWGWuej/XDF8hBCVKa8jU1U1Z7bPX7NDaISwvlXWkZQj+86eXdDyLTiW29mDgoQnREJE6joGhqf+uvao9x6RXbdqOqVdDZEmYFgSJklevP5upC0qpMr+uZxFlOeMwJYxzfNvg4cDj+VD1bM1qCPz+bltlXWHGZJEiS4mht5vrIxBst23mkRoWbrcsJBBnOXkh+dGhsrU8nUZYhoau1UKCCjI6j3P6nknRdei6Jh/stbENZRz0fBgwrQTTVpEmJ5OIF6OAi3nCfs/lYc9trrWoNjnfUoPe+kCehCktW8106vupZB/gp4/6hGnOjx/2eDFSxjMWkh/ut9E1Gk5HvZaWXfweVj7qtfDdYVXhPBz4FGXJn38+4mIe8WirxZZvcTJRcid2Nc9YXk+jIAUE06rdMPBNHg48orzEza/8DLZaDrM4bTbIo4HXCAnWw0wBlVChyW7Xre63Qu78/PGAnmdxPA6vaSMBPB+lIGGrIlw6Vsr5PKm0zHQ6rgVSeYg7lb3rTltJvKyy/g97Ls+HAR3XbGyHF2nBw55NkBQqmy8Ua12WMI4Suq7Fbvumg2J9CL4YhcpTvSKFakttzboNGWcFZpW8GaHq//dck9EiZZ5kHHQdwiTns4uAnq/8Y0ZhRlGCb2m8GEY8HLg4uqFsRENFYrV0jYdbXkX6zOl6BpNIkOXqWd7vOpzNFPS2PtCCJCfJco4nISWw1bawdNVWu0siqEbxBak6qB8uXQNl5SwxNI28KFkkJUWhbHNl5ab49HzOPM6Js5zdlsUsKUEo8UXk98sK9TuP66WqxtHAYL/jcj6PrgkAgrI3XHX51jXtmlXm6qJN8rJh+Jq60tJxLZ2oYnTWr78MbzwaeAzDlLzSrpdIshyCpKDrKaMUQ9eIpzF7HZusOry2WjZxNfisD60ozdc6fYEatE4C5Y+83a6sJZOck3HIe7stHm/5/O50julZ+LaBrmlsV94Jf3sy5VHfp+0ZTMOcg76BLFU/+OU4YreyrryYJ8widZA97HskecFwnipUmaU1JX6Sl43Dmm/pvBxHdBxVhlu6RpqVfPSgy1ZLPWi/ejmh7arDK88l/5+PT3my36ZjG0zjnCDJiNIC31JugbKEoy0Py1Cwx3d3Wg2SRd1H5TfRso2GhLiqLlwjyHzbqJBDGb6t41jG9fu9ktG2HeUbUrPXlw+TZ8OQ40mEQMFHH2/57HRsjscB4yDD0EXjo1A7m7Vtk65rojVWqCbH40gBIaoMWxNcMyiqEyKAcaCyfolk0HIawpYm7HsxvWt4ay0zstd1Oey5/EUpKcuSrbZNlJZst1yyyggnTpV/QttRVq9Sykaa3TG0CsWj/t2z1IFyOQqwLJ2up1RgMxRhVPmt5Hx4eB1dGGcFcSVXrjTcJC9GAX3f5slO61obUkoopGyqNjWDkhx0VEb+ahJj6aqq2WnZqsIGNE21vSZRwh897KJX+lg9adPqGzi6xnk132vZBvM450FPzYTajoFtqPlKXpb4jq2sdaMMiaoWBXA+S+j7So5mtTux7GzX960m8RsHaWPUZOqCB32Xj48nDHyb87ly5cvyksOex/lM3bOuZ7LVtvlPf3dJVuT0fYc4VRB6NvDY63Gb5IFnGqR50fx3ViiLUlG5Za1WD7eR42xDo2WbDAPlZpVUZKMsL4nzgmfDAEtXN77usx/2PZURGTrDRQxScD6P2e3YWLreuMf1PYuLRcJhheZZBxP96LCr/JCXPvMszhBSYhgag5bF5Tzl88sFpkDZVGoajqEzWiSV3EXZMIJrlNXLYQBCuYzpQjBo2QhN0G/ZpFnOJycJR1sevqXxRZRyGSSNNk4uS0QJYQL//PSYw46HbgBSY5FmPOg5tGyDYRAzCWIcQ+OnR30+POg00suPt3wsU2ccxMzjkrIs+duTKUcDn/N5rBBOQuCaCl4YVSX2XkdxCmokVN+zeDYMmUYpLcfgRy0la7JcnZzOFBImTApKVyqBOt+uIJEKEbd8v++ScFmeQyiEU4wQ6qC6nEfM4wxNgGcpJ7zdttv4KAwXCb5j4FiScZBh6so86Wwao6GMjz6/WLDXdW+syeW1MY2yag5yxcKvM9fVVt06oy9NEyCvWnOTMK000Ax6rqpCLF1HSiWd33Yt3ttp0XYM9rtuAzMWUl2Xlmvycjxjv9q8gjTncp5i6MqDxXVM+r5VObopEEOYKdXT5dbtcJGoPr9jNlIndqVgANcNzOq1pAlB1zU4GYcEaYFjaOx0HPZ7Dlsth79+MeF8XkmWV0ZT/ZYiwJ1NY/q+xdGWx/k0VpUUiiT6bLggL1Qn4sl2SxEcK0HDLU+hocKkYBLEtByd81lK37dxDFUBXM5jPtzvNvvLsrOdLpT7Zo3G0yruRz3nCtOC/a5LkBS8moSMw4SOY7DTcpWkv21wtOWxSHJMXeP93Ta/Oh43Mizv7bSQxRsaFwkhdOB/KqX83971e9+XuC/q6bYHe/XC24aSagbu9J9djbrc3fItFklGUKm0erbB+SzBEEpoTtMUxK0mM60+1D1PDVhPxiFhVjKPMzzToJSSLc9qNGfWwUTrh6j+zK6hYRo6viM5ncbsdGw+O1swqzx///57A0oJQeX89+F+95oQ4jzKlLJpklOWYOiSs2mMa+k86rtIYJ4UVXur4I8e9phEKU/PAgxTo+eauFU/fBZlfHYxw3OMyqnO5ocHbXynwDA0unvKZbBGiTmmzl+9mKh+dVGwSNSA2tQ0xlHO2TyhrIxwLF0jSAuiNGeR5FW5b7DbVtaPSVYwClK6rknbUe2aelOuM/hlOKVr6hyPQnY6DpYu2Go5N0iYt5H/lr01uq5Jmkt+ezZXWl6OwRdDRfqrhfqyEj7yzGsVZ5KX7LRszqqMM0wKxlHC6TTmX/3hLr6t5mXPhwFIeUORdXltLDPk6zUP3EAMRbmqBHKpKglNExgCrGpgbhsaA9+mZRvs91yKUiohv6QgLZQqassxOB4HhBclR/2EZ6MQ3xQ82esAqlXadg0mUcK00royDYFjCYpS/btjqvnRLM4YBxk/6roIwbXW7ToPizrbXv1etQbaKEh5NVEeKKczRUibRBk/3FVy7z88aHM8DshLlejpqE35J4cdpBAcdBzGUcosVhDfWkKk5RiMwoSBp7gxDwc3PWtOxiF/Ng4UDNY38C2TWtq8NtOqD8H68++2nYoDodBf57P4mhr08qHy4X6Hh32XvmszTzIe7/hEacleRxGIozTDb5l4HYMPig7nc5UMvZqEIIs3qyiklIUQ4l8Hfi8Oivuinu5i9d6Gzb8PO7uO5U0/KyU7bRspFFT1YhYxi5T43E7L4a+ej/n7T7ZvbPilBC1QssJSKN+IIFbZQNs2bsw5bvsMdTy9UKZC6oFSGaFn63R1k5886AGqX6/ryqMjzQvmEc0AfbhIeG+nRRBnvJxGJLlUXr3AXldJgTze8gAFRzUrcmAplfWoIhwqZmjLNSsSkUPbUeqjvzub86Dv8cNq+Lnc2nFMncfbHkUBizTHqLS3zueJUsy1ciUvresM2hbPhgtlz1qZ5LysDKjCtOCTkyvm8kFF1qqVVtfBKSdhSl7YhGnOzlZrrbXobeS/VaLk6TRWRva66gk7ukbL1rlcKHLik57bzE6Wh7H1552EKZoQxHnBTx/1aTlm4zPQcc0b0h6w3gyn9phI89r7hMba1Da0ioCoZlQASHVI1Laa65QNHvQ9RUYrS07GMVstSw2pc2V+lBclA7926KusRYuSKC15tOUwXigP6LjMkRXa6GQckBUQpjnv7baYJwVZUeKYegORvi3pC7OclnPTRyZIFOLqyW5beZ7MY44GPggI8pLTacRex+Gjgw4vq5lOy1bfXUnMVwNgz2bLVwd4PWC3DA3PNG6FwTumzmHf49EsvgK6lLKBILvW9Wf2+iGo7n9clkh5dY/r+/t8GGAYyg/lwPXwLINPTmbMoxzX1InTEtNQB5GhC4I0p5CSD/bbLCLVAkTTvxI89l8IIf594P8KNFogUsq/vMfffi/jLlbv1/0ejENadhtdV4zeaaSqgLZj0qrQU2o+cDUMrg8y3zJUfxKBLpQekGJQKmLUO1v+lxIoqx+omoiW5mUzf1lmbWqWIC5KpXdfwVh911SmOD0Xy9Q5mcS4ptY4makHymQUpg0nJS+VJHiYKkMdvUJ+LOIMz9bRNYGmaXRdk1eTAkPX1EB9jS/Gk502v3g2YhZmCCQvx4qQ9MFemywv+fR8TphmTGKLtq3Ezkx0djoWvmXw9GLBo4GSTDErB7g6loeH9cNZI0OSvKTnm9iG2jxWY7VtU3t/L79WvR72uw4X84jjsZqRHPQchKYkQLq+zft7LeKsrNSBc2xL40HP49nFooFG9z2LMMl52Hev+QxIKckr06c6c67dCX3HYKdlY+oOF/OYvLQb/bLPLxZMI6UP5ppq4/r8coFvK2mImksSJjmjIF3rxfCgryQvng8D5VPSs5lFOY5h8N6Owv/HWYFjKKn93Y7arOJMtUZnYa4Qe0Jr2iTDRcI4kRwNPCZRystRxHbb4vGWfw0i/e5Oa23S51nmrR4UoIQBT6cJvmWCUOz8PFfinRfzhCd7HVqOib6EXFSzIeVcmWQFF0FKVlTMc1PHNrXGFvU25N3HJxNFkEyU97VvG2QoLa5VW9TbntmaCHzNxlUTFVFUQWTHYcZe12a0SBV/ZBrx4WGHNFfimJfzlO22rRzzdJ3ttoPMs/S2/eM+B8V/sfrff3fpZxL41+7xt9/buK1y+Lqj3izajkku4WHfwdAVaU/TNNquwfk8uXZQLB9k9aaja4KkKBn4Fq6hsUiL1/IJ6piEKS+GAZ8PQ7quyZMdH882m/nL+VzxBmrW5n7X5XyuMPi1NICmKeXSMCl4Z7vV/E5eLdwfVXMRgZrFCE1JHRwNPD4+UcSkvGKZBmnBQeXh3XVtzmYRrqEGkbf5YvQ8i58/HvCnTy95NVXckXe2FTLnYp6w23LZaVsMg5RYCD44aHM0UEPLV5MKEVNBI6WkgUvud10WsYIO1+JzUaortm1FUrxNXvp1DP112a6h6Ri62ij16oF/2PexNIjTkkmUYOnKStY2dH59MlV6YEXZQKP3uo7SIauIoklecDlXSc8kSMlKSd8zK3ViBcs9myXsdx0eDvyG3XwyiXg2CpTmVQV+MHW1YQbkTbWyyutZqz6w0+Kw5/KLZyM0IShKyUFPDYnjNOcySEnyAs/U2WnbRGmBkPDRQYdPz4Pq+8JBz+VsGvNkp02Y5bQdk4t5glMdILVxVA2Rvquau21uVP//aVEyaCm57Rp4IlHEwT962GPgW/zy2YhX0whdoGZxRcmObTOJssYL3bPU/NCvKoZ166JWz01SVT3UreG8KPFtg7Z7c0ifVNe8PuhXteeWK9bldf3p+QJD18iyEqu6Nw/7HrM4xbNM4iDBt3W86r6mRVG17W6nub/2oJBS/lde9zubuD2Wafl5UZJrAiFUPzLNldmNXHN/VttQMKMoZVOu1pn8Kp9gNZPRNcGvT6b4tsn7uz5n84S/eDbm50f9Zv7yi2cjygpVsd9VG0GNcqmj51m8mkQEqdLd0YRg4F13zXNMvcksfcdo+qKPtz0uZ7W5jE7HVkS9nY5DzzeVCJ+lWizK1vWmL0b9Gf7VH+7hGCp7C9OClyOFwf/Joy6mrvHeblv10U2t+VxhUjSZfY16MjWNuCyZRxkvRgEPK/G5orT46+dj9rquEo0rFAKt45p8fDKh79lNhngX0UvJX19vcb4Yh8zilPd3fYI053gcM0tyNMB1DP721Zi+qwT2Hm/5hEmBb5vkpeSgd+XRkOVF0zaax5kyTsolui5Uthootu5wkfBooONUHYVJqGYzz4cBT3bbaAIWUc7n5wuOBj57PQddKIhynOZYute0idJSuRr+4tmIoy3/Rvutvv9HVcZvGzVJLMUy1T13DINFnHGxUDbAP3rQxbNNHg4qa1FdU0lGhTRUaCmXeawc+IpcOe7llXlX27JvPCt1vE4t+ngcKmkMBH3f5HKeIqVUdrC6xscnEx70PHY7Dr5bNLMaIaUisFVe6MuKrI6lttOPTyYk6RUxzjGv1HNriZW2Y+IYOkJwAxxxA74/T9Zqzy1XrPW6LitnxcdbPkKTtF2D02lMzzVIs5K+p7HXdTmfRo1dcv3M36Xh8dqDQgjRBf6XwH+5+tF/DPy7Usrp6/52E1wbaH6w21IqrKlgt22RV5LQjwb+2mx1ubdcyJKiLIlSJfUx8K1rD0v9N6uZzF88HSp2a9VvfmfLJGzljKOUTnWgWJX5zPLwuka51OGYynFvuoTTX4eyqTPL+rOHWYJnmby/1yFJc6ZxjmPoTOOMjmvhGBoP+moIucwgXvXFWH6PGkrcdjS229WgTmiNC1tNPJMd2ahs1hlzXcLXHuLTOOXhwKdTffeOazJoq5mEZWoNLn+0SChL8HpXlUOal/T96+5ry+2NmiPz2cWcRZzzxUXAOzs+g5bDAMVb+d3pjNN5zCPDUyx8y6BtK4mUrFDkz3hJxFFteoIHPRchBP/ys0syKSmq7Nk21OH2/DJA0wWnk5h3dpTnRA1d9h2j8STveBYSybNxwMtJxKO+y2Hf4+nFQoG0pSRIc07GMQeVMdNd87GmbWobvBwFSASWplSKZ3FGv+XTdRVDG2harOqwq4l1Cin0aKA29bZjUkoaky1L19hqOTeQi6vr5K728nK7zHcMjgYOf3M8JckU8/50kvDbVzP+6FFfzTCqSPOygVoLoTWS6FJKxmFW6USp11hWz43TXPmZVHO67baNZ+rMk5x2ft3G4AZ8f8tQ0inzRGl3CcFu24YKybfcmvr4eIpjqlZUrSK7SDJ+/WrGTttpDLSyvKTrWQ2sPlUH9JsfFMB/APwK+O9U//0/AP6PwH/zHn/7Bx/LC3a77SgV17JkHGVYmtKa364eruUBVb3h1xDB4TzBMnU0DVqGGvT6tnHtYVmX4aZF2UB+6xBC8uwiaHSCiso//NHAp1UNOn1TaUU9HwaUVQXh2cY1nP5d33mr8h1oOW6T0UlT52e7V/yAuvLpuKo9sY51uy6WocSWLkhzSUHRZEarxLNVuLAmRIMaWcfq7VUmT4+rtturSYQmNFxHa3yhASZRSqswb21v1N9xt+3yoCcYBykXs4QoVbOheZzRdS10LedB32ccVvOArKDvWsziCtdvajde3zF1DnsubcdknmSczxSkWAiNjmso8UFHWWVute0Gyx/EOe9s+w1LueXoHI9yPFMNbJPKje/9HZ+smnss4pzDvoOtqwx4lQd023q3LcWz8WyjQkg5BHHOLM6aOUr9u13XZBylZLkEJLJUHADb0CqtroR3tlrNIH4WZ+gZa9WWVz/LbWt0Oan5008vibKSw76LV81qZqOCLy4XjaYZUAFCxPoBeiWsuUrqPJ1FDBeKH1MbX13OFQqy6xo3DtxV+L4ik4acz1RLDgEn0xjfUp7vHcds1rVn6fwX3t9iEmZolZDkJEhZpAVblTVrx1Hre1ZVmFmhOh+y+GoziidSyv/W0n//r4QQv7zH3/1ex31lxO8T9YJ90FeG8x+fTLBN41ppehvyBpS/90eHXc7nMY8Gt6tPruOHdByT4SJFCK2RwZ6GGd0lGOZtTOKTcUglPKvkGV6j1Lkcr2vLLD/ENav65ShACEHXMbAto/HFuAtlZBs6YarQPLahNcO+1QNtFS581xxhVegvSPO1vtCeZd7g3dzWQwYlnvg3L8akhZL6PksKkiyjXynzdj2T82lMkORs+xaGEARJxsD31x6gJ+OwmkfYClFXyavkhVL11XWNhz2XcZjgmQZHA6/C82sN2TFOS7ZaDklRkEvlzfBo4KNpNZJHsXpNTVvqZd/UNluugKdV/z5JC3q+xaOBR5Ip7aa8kPi2mvtcOdTZJHlJOiubfnxWqNlZVlh0XJOfPx40iCtQa/E2teUvE806FHA08BofB1MXdH2Dk3EE7179flbIBmq9et8902jUF5ZJnafTmI5rYOha0zZOi5JxmHLQcZStb5XML89Q6jU5DhQjv+vajYtfWpQ8G0UUFd+pU2l6KXVaDcdUbbGomnX0HOW9Uh9ebuWfvoxeW9sDr+I+B0UkhPhHUsr/H4AQ4h8C0X1uwrcdX1Y99rb4MjLiXzYU4cvG66l+fh3rkDfLoTL92yUMYD0/ZKtt8dn5HNcy8G0lrfBstOBf+2j32uuvYxK3XavRuAKuHWarsXqwzioZjuVY3Vzqv6uv9bs7LeZx3hjW1NXNumu/fPjW773uuqxDJcGSd7NUvIE6K6sZzvfxhe44V8J+9XvX/53kJWfTqGpNXJk27XQcwsofwDIFjqnagnkhFfO2pXxEFnFOxzN5stO+AUmtP8f5PGG/q5R7fcvkuIjQgUmY8EcPlEmRbWh4wuBnT/qKVV1db1Eh0KKkwNDhwaCFhqjadKr1s8povupl36ycjschUsL5PGa4SCqxQsFfvRjz7FINVz1Lufu1XUVG3fItpSEFTd9/efD+aEXzqD6oj8chpn7ldlfKklGY8nIU0qrMgOp7c9/n1TI0ikJe2xFdw2Au8juletYN0Os20LjyANEkvLfTQggFoJhGqcrmbRO3UiQAycO+p9Rw05yoso2tE5U0L9nvqsomyQvOJnFFMnV40PMIs5woL3lQVUiWoVe+2Al5IUnKkkKWlLlkGmYEaY6tq+f0wT2uz30Oin8b+A+rWQXAGPgf3uvqf8vxZdVjb4vXZcNfNe5i8t717x3XvPP91w7wspK//2SbYZAwi5Vd6U8f9Ujy68nD8vvD7ez1dTaQ6w7WSZBgaKLp/dfvAdfZsquS7UGiTJyCNKftmve69re1GGqTnSC7Gkaez6KmXK8/a5wpfH5dgteb8W2+0JeLhKfnC1xLZ9CyeLLT5kHfunEdDENrZlCOqUyTHvQ9gqSoyJ0KCqz67zlZoYGEd7Z8hLjpT70aUqrDZbejM62MseZhhmloxLnkB3ttrEoFeZlU+KCvfEKej0KEpuY6GqKpGJbbW8tD+dtag/XzMgqSSsjPYBik2IZCpn12sSCIcn72uMduR/XNs8raM85KHlStRNPQmuSpZtSvW2/La7PWsCqlEph0LYNpqNbebWrN6+L9vTZ/82KMEKIxL0vynL/33uDW5Kwmug0XCSeVp3yc5rRdJcvuV9DwrmcpZF7HYb+rzLssXUcKyafnCzV3MRSR7vF2i7ZrkeVF876OqbHbUUADUMKFQZbjV4KNVgUiCZO8kaZfhkb/5EGHT07nfHo+xzU0bNPEEALPMpQj4cp8dF3ch5n935dS/lQI0akW5+y1V/33PL7MJvkm8TpExn38vWF9e2x1gNfzbfre9QMmSvM7RQ3h9YfZ8nuv8zOu/acd86o9UMuImPrtku1poRRD6wHusuJpfW1uqxZWM8iTcdh4eRuGguc+uwzYaVtsVy07yxC0Xeta5roay62u01nMZ6dzdivBwjgrG3ezIMmvHXq7beW7fD6Llb0myhP8B3tXUtnzKGNawRbDNKNtmtfYuXdF7RXtWyY7beWW9nwUYBs6hz0HsbT5p3l5DbV12Pea9uLzUYihKdVZTYgba+F1g+H6eUnyklJKZlFGnOVMopID4eCaOl3HVPLuVWvH0ASXi5RFnCEEzOKMojRpO2YzeF9NXtatzXrWcjFT99mzDbK8JEjyprq7T3J30HV5MQo5GYcUpWSrbfOD/S4f7nduvQ/rrASkEGR5wSJRydJu28HQBS/HSrDyYd8jSHPyolROh1lJy9IpJBxPosZV8Lw6WJQ6RJvjScQ4SPCkoQ6EOGe3bdGtqnZDF6SFbAymxqGSvJ+EqTKB8i1+/Soi0DXe3bLxbB2BYMu37nWN7sPM/rvV///WHxB1vG6T/KrxugfvPoTAu9pj1276OLzxXXRN42jLbzIW4JpXdq1ndNthtfzeWV7w188ViejhwOODvTbdSg57tVVWy4gsHyirku2WrvyEbVO7oXi6jLYBmnZHzR5/PlQM7DoDP58neJZ+zcvb0JTv9HLcJwmo78npLOLRlt+gyDxbvfZnF3PVUrSut8ce9l1OpzHjMKMoJWGScz6PG1y8WDNPuW8c9lwmUcqrSUSSF9iGzqMtjzQryYqygTuDkn1fRW096Hu8t9tuDozTaYyUygL1tu+/nEHXa6V+XmqJ8NNJhGtpaihc8T8GfZOwklQxdLXBDxcxB12vUhswOZmE0PMApWsVJjlHA+9GxrtOETZIswYlVduH3je5qzd85efiYVRr9d1tBWZYroDrA3ydlcAoSBQhz9SxTcXortf6o4HH+Tzm1STCMTUiwLeUtHghJQKV4Z9OI4KKL6MMxQR+de1dU+esmn3stm32em5z8OaFApzUn3cWqXalrmnMcqUp1XFNbF2jVQkV9jxV+YyDFAgRxhKEciXu03r6hRDiPwL+71xnZv8/7vG3v5dx34z+q8TrCH+v+3fVB1b/Ww+pfVsJndVG93X5W9uXrvsuq+zd5c24PqzGQUqY5XiWqTL4igEcpTkfn8ywTA3b1JmFGb86nvKTB11cy7jRKqtlRJZjVbLdtw3GQcDA99cqntbfHRQ9aBikTd87Sgs+OZnyx5V3sZSSJCsqn2J1jZQ8xHU15S+TBChtquutIMfUGIcp+x137aG821HKqQ/6Hvvd8lZc/HLcF0xhG4rAtoxMc1vXD+TbUFvLmWQt/VGUZaMddTTwrmlHLbfy4jRnnhSUhVQeHYsUUxdczFUrQ2iCHVcjK2G3o6Rc9jsOIJnFOaMw5cODLm3H5HSqjKwOKnx/kBYcbfs87LnomnZjRlU/GyfjkIuZskg1DTUoBrVpWrp2r/u6vOG3W+Y1BvYoSJuB/jrnvGUrAbO6pos4Q69IEatJw6O+R5gWHPZc/vSzS6Qh6bgGryYxEslB1+GLyxCJ8sCuFXVHYYZjKlLue5XpUe1bPo9TpmHGPM7YaSn9rZZjUpQSXdcqdWaNKC1o2SaaJho0X5wVfHq+4Gwac7TlfeVh9gAYcp2JLYG39qD4NiQ+vmrM4pxpqLy+XVMNqeuH+MP9TrV50MAQb9PoWTdEtAy9OXDWaQQ9H4W8s+3zbBjiWQZt1+RipvSKXFPn0/MFP9xv3zjokjTnb09npHlJy1YoHNcyrkm2e5UbXZAorf7bFE9BVRKWoTUVg2vpzOKrgXvPs/ib4wkdx8I2FBltmqTstpw72253RcsxiLOyqSQA4qykVQ1P1yUYAm7g4pelGFbjdWCK+hB5MQobf+Zl/km2BIm+C7VVX8d6xqC4FfGt2lF1K095hhTkpbL8FMBOx1Zw7LzAc3U0CXkJOy3VHlnEOQdVpbJraAw8i75vIYS40rHSBLqm8a+827vG6ak/4+o9ksAPDzoMFzF5AcejiN2Ouq/rxBvXxV0bfpwV13w5bjjnLVkJQOWMF+fsriCXajmYWpblsOdyVMnvSNRBioAsV8KWH+y3FYqtgnQLJC9GZaPe4JiKAX65mPDXL5UB1PvbPgc9j5fjENdSs6h5lFGbjC3Sgk5lejWPMoaBSgYWccF7Ox6GpoFurh+Gcb8ZxaWU8n9259V+C+ObkPj4OiG3YZqhCSVcl+QF41DZdpo6GJrG2UzJbluG3gy4lqPeiNYNEbuuyfNRyJPdNkleYGgaoyDBqgacvm0os6c0p+sYaJpGz1etBYlsBpTL320SpjwbR2rYZ5tkRckvX0z4wa7PR2taL/Wmtk7xtM4Sw6S4tqHkhTJpqfu0dsXnyAup1HqF4KDyUbgLPXZX1JpTaV6S5AXzOCcvC/7RD3ZvTTBOJtGdukOrcReYYpnAKQSVvk/UIJLUAcW1z3Ebaqu+jvWM4XSa3Kod9aDvNa28SaUNFQXKJa2Ugr7vIAR8eGiQ55KdtoVl6I3/+/t77RWdqKuWaI0SSvOSspS0nOvb0rprtc7MJystgjTn8S3ijevirg1fr4y91n2WVSsBQ1MaSgIayPrxWHnIX1bS5poGHUdJstc+ItYSxDfNC4Is52KWMAqzyr3OoijgYnE1dK73EdfS+QfvbjVyOaahNa3ctmNg6ErWPEzU3z3oeWRlyfk85nwW03ZNdF0jSEtargTe0LiomlH88Z1XehP3iq8bcuuZBtNcZQzTMKvkl+U1rPQ4SNnv3o0cqf3CTUNcsXcXCX7VX00L2fRgx0HKQc+l4xj85YsxZ9MYpGS77dCuBNqKQqLrNzPlzy7mDDyLnbbNNMwoinoAKm/9/r5tKEtOSWPJWaOBQJkwRZUn9qpoWx1PdlrXWk89T8067gMMWPe5ep7FR4dd/uXnQ7JcoZcOey2CJG8e5NXXvo9fxfL73gWmWN4gHVNXB6nQm3uzilhS3+06amtdFfViFHI8CWnbJr0lh7jlTVpWbo9pZTyUlSWlpHIoVNL52y2L50PF7zjqOs171bDkOm6rvva6N9t361pIq4KLBz23WevrhAtvi7s2/N22fetnWbUSmEc5otI8qzdzIcStasV18rYKrX4xDHk+D/FsA10IzmdKyv+g697gWa1L8upWbt/zqnaTgWcpJrsQYOuKJW9UbamLuWpdT6PsK7eefvmHNqP4JuKrQm5XNxTbUA5lQaqYru1aIbR6/Xqg9zrkyDI5SKLkLsaLlK5n8mwYMIsySinxLYMoU0O2l5MIA8FR3+M3ZwtOJwmWrjwEiqK8oYIJqrfvWcpPuN60t3zz1qy6/r7bbUd5HaTK66J+EEFxHT45mTKLSzxTZ+ArzZw6o6slug+WNqk0LymL8tqA0rcNjicRYZI3vf5JlDUOaatRlJI/Phpcq3Tu4pjcx69iOXkQcOsGtbxB9jyL02ncSDCo/7vZbrmrlbrsEFe3MF+MQjxb6Qwt4hy3er8aZaXc2tR1UjpmJkVV+emaxn7HabS4bqvYbvtMQCWDUbCIM8JMbdo/Ouw2f6s0pBJOJ9f1lN4EcPK6Df91dgTDRYKmCXba1wfdjZfEHWrFq0mFsqD1OF/ElFKSlep51FDudXWlfFeSV7tv2qbyQAmznLZlNxVWXd3Wf9v1FHv/bBojDPMrDbP/4GYU30R8FcjtumokykuElAx8VcKmuRrgSRSRSlZKrbf1aZc3qb2Ow8U8IUhy9to2gaEhELim6lufjGN22hYt2+B8HjOPMh5t+bQck4Oey7NhwDTK6Xg5/+C97bW4f9vQeTEK6brK0asoVRZ72Ft/SC4frDUXo87E6tfveRZ//HiwthKIM2VS9HykdId22gpltA6i+8vnY0opcS0FPYyyooIvwkcH3Ruf7a57eVtlsm5TvC15WJ0xLG9Qy6qoqmWjYMhlKZtDct3734ZaSrKicYh7MQz4/GKGa+m0LAOk4MUoaA7+w55LlBUIlOaQoSlJinmUEqU5ux21Fg86Du/ttl9bKd/W3t1q2U0lWXMFlpWUj8chHcdimMckWcmrScR2y75Wbd437trwgVsP2Ls+/22qrrVa8W0HWpKrWZeSWFFJi6VrzQFsVnnDcpL3/HJBmJckmZLpb1l6c+3XqUqvJohSQl6UKIrGV9B6klL+j173O9+X+LqY2d9EfBXI7boNpeOoPr8maGQs9rtKV+likRDEOUdb/lpZaFgxV5JqE6g3GaMiTykva+UONw5Udj8JErZ8qzG1absW7+9pnE3iJiOtN6bl6DoGz0slY64JQVZK8lL9fF3c92Bd97Cuqm8ejyP+/IuRqrhMjZ0lBFX9AGtCDbstXadlGwpBdTzl3e2bVcVt9xJuusUttxdvDPdv+Y6rM4blDWq1OllW8X3d+69LOGpggluBEn72uEeYqCpVGS75zeHsmDpPdloMXQUwmIapgjNXHtDns4Q8l/x4qep7kwiS/NoQGa4qNnXPrs8mglTJxL8pzPgu6O/qfauv4V0tynWqrrVa8W1VH1ytq72Oi5TKH0aWkkKu51mVEkqU5HpeSAa+4nHUn3NdwrCaIH5yMkNKyYd7bWQaBTc+VBXijraU+gUhPgD+98CelPInQoi/A/w3pJT/63vcg+8k/uRP/kT++Z//+Vd+na9z+Lz8kN7Xe7uOpxeLyunqamOSUl7rxy5/VqS8nhxU/32f71C/l5KrViJ1piZwLIOPDjocj0NOJhGGdjVIPx6H6ELjQd+5gTapP9P5LMazNM7naWNC/6jvYhr62p5y/SCsbhbriHGr9ynJigYeqrgYEQIFCw2TAk2j6RcD/PnnQy4XCQ/7PkY1vEzzgigp+LvvDu48iFbRTcuw1Ls+85f9jnd932XrzLteb92/P6980I8GPs+GQQWnVC2Pg57brLNaPG/5PYeLhCgtGohy3d/Py7KBKL9J3LXegdc+C28S93k+7/sMr17nOCs4n8UUpeTRwMO3DYIkv9b6DJL8GsLwdQlfnBVr5cxrGfpaNHPd51xeP7XMjGsZ7A/afy3z7Kfrrs99Gnr/B+DfATIAKeVfA//GG92N36OoF0Up1cKs+QVx9mbs7DozqdE29cP7/2/vzGMkue77/v1VVd/TM7MzO7PL5R7kLmmJVASJ9EKQcziJrcCHJNMIbEhIDFiJEyGBnUiBjcDOAdh/KUGMwFFiGCHE2HIcWBYcI6FiWJbtSLBhGJJICQFF0ZLI5bG7s8fsztXTZx2//PGqeqt7qquruqu6qrt/n39m+qp69eq9+r33O6NMJm+l4Wd4N+Id/9y6ql9d0FW50J2DFnYOO9AIka7BO5dnILy0WcPpehmr7sp/c6WEaslAs2eiZ9rYPerAtlViQVX6lLHX6uHLr93D197c67u86hrhqGPj8TN1fM+V03jn+XVUS4WRO6rNFZV4rWc5rmrNOZEEEQi+T2/ttWC7sRL7zZ4blGfhjfsttEwblg03yEixXi24UcWOm6LCQcdycGa91NcL+xl1LzHCSyboGHGucdT5L2+t9B/Y13aPcd133UHnP2qbuH/cwZv3m7h9qKrObdVLaHZULqGirh70Pdvup083bQaYA+fCUdsccFEmIlSKysjqrf4nIWy8R5kLk+DftatYE63v8RXnO8DJ++plK373xVP9++X1Zaunany0e6rPt+tl3Gt0VCbbtQree+U0LgfYysoFlTPu8vbKQA6ugk642whvp3/8XNysQdfG910UG0WVmb8ylKrcGvXlRSGq8TnOrmNSl9s4AYD+dt86eFDq8bBt+qJ0RxvQx53LUz/suFGiSk1Qwdk19blnXG10LWwXy3232u3VMq7vNVUG3FPVsfELUWNZgu6T5757ccPAcddCo22CNEK9bCjD9V4bplPEWdcrZ71WwiObNfQshuUog+B6pYjNWnnkAyiKd1PHtPtVAEdlwfXXq1gpG7iyNV637zGsStI1lSrCi1D2++4ftIrYb/UGajXfPuxgs1bsR+kHZeLtWcp7x9OVA24SvmYPtw+UjvvcRqUfyzLsohz1OvxzaFyQaFjGgFFzcdw8jaLqjKsODRq73v0aldusXimgVNDH7iqB0SpQZg5csATZQ/3zPYwoguIeEV2BW8aGiH4MwK0Iv5trogyKNLPM+okTAOhvt1cqEwDa5gPjaJgB3R/1enO/G5jSoVxQ6qLLbr1ib5t9+7CtJgBDGcOH3GrPn6ri1kE7cvxCFMEadJ+26g+ivVtdC5bDMNyAM5VEz0Gz9yAA8crWCh5erwS64o5b3fvxTzrbcU5kBR0eG8P1Kkyb+w9Iv2pi1OJjWEh6wvjmXguaRgO++6/sHGK1UkCza8GyGYZOA7WaPePncCbeWsnAV6/dh+W6Xp9dL6HVVWkz1msqhf31+21c2KxAJy3QRTmMoDk0Kkg0zMAMjLbPhH3mHTOKDTGOnXHU2B0er/7cZl5gXse0wTw+r9m0Lsb+dt4/7oJo9NYiio3iMoBnoWpn7wN4HcDfZ+Y3Q3+YIUnYKKLojyfVMaeJv0233BUfyCsxWsFR28RRpzdQ0hNA4Iouij3FP9F3DlooaMq/HqQyZHpue5c2a6n0zah7YLq59r956wjdnoXT9TJqbjrvrmVhrVrCEw+tnriWaW1S46Kmx42fRtsMrDsS1PdBuvx2z8JLNw6wsVJCrWjglFuf+bU7DTfbbSnQ9hTEQauHr7+5h6Zpo6QrT7Wb+y08dqaO1UoBGqmI5m/ePAQR4eJGFSvlQiy1alJzKOw4wMnAzeFzJGWjGDeGhtt566CNnuUAxGCmAQO2V1zL+13QeTumHbgjncQeSkQvMvPVoM+ieD1dA/A+IqoB0Ji5Me43i0AUdU/aWWYnwd/u9WoBN/ZbAAjnTykh4dV68FZWr+0eg5hRrzxwF31l5xCn64OeQcCgyso/IcjNmOmvWwAoNZQJ+Pz8x6sIprneUZOi1bPRdN1ew8poJhGN7x3DGxujao4AwePnuGu6hsjx8TZBK1xd07BVL+OR07WBc1dLOpo9G+dc2xMw+CAN4rXdBmqlAlarRdw9UipEnYCb+00Q1fpxHQ+tV9Dp2Vhzk8zFuZ9Rd+7jxsu444w7R5Rd+7jvRNEwDI9XL7dZydBRLqrduOk4OLtWgUZ0wtNL/a9u2s5BG8x8Ykf68Knq2GuJSxTVEwCAmUe6Ti0iUQZO2llmJ+Gk22sVYIbDwFGnhwsbtX7aC+UFZAGEfoGiokHK+NsxB2pJ+CdW0IToWTbe/tCq8kd3jbqbtSJ2Gx3UK6UTK+mwyTSJ3WfUfdpcKaHjpkwYVRkwDtGT9U2mymh17ciLj+GHTqNjYbfRgWUzru+1BnYzKyUV3Bgnx5WXAFHTNGyvlnDYNmHoGg5aJi5suDtG1wBeNLSRrthhjOun4bHW6Fh48809nKoW3Zoeqv/HHafRUbUa/Ak0h/s5ykIh7DtB9rKu653k38H7x6uX2+yVncOBjL/lgn7C08tPQSfc2GuPzEXlCYukiCwoFo0oE37cwJlFltlJGNXua7snB5zjpmXw460+/fgn3ShD/3Bagoo7CYa33mFOApPYfcLuUxz7zjjitG1c+hEgePyoCnODCfGGBczAbg4qQO+464ysf+ClM3/SV7UvSj/4EyCWDB3bdR0FjfDq7jFKhhISlsNgAFv1cuQsA37GzSH/WOuYNvaaXRiacst2uNDv/3Fp8b99+wi1UkHZA0wH+81mYAaBaQiqdX3vWGW3DS0FAODiZi00r1mQEKSQXFRJk93SN0OScn2dxuV1Grz2X9s9jtXuINdCZfAcHGwrpYIb1R3sttl1V6V+PDdMv+tdUF+E/RaI7oIYh3Ft8hPWt1Hb5k8/UikqoXu30RlZ+9s/fp44twaNRvf98NgtuDWtSzrhvLtbrBQNXHDTOKgU42pcrruBeVH6AYBbhlXVhXAc1zHAdvDkQ3UUDWV7UravMlbKRixPp7A+8LfNP172mz0UdR2Voo6ezQP9H3acZtfChY2aqnFiqVonFzZUIGGSDM8vL5CzVjTGjuUwV+lRn3m5qPykpdEYuaMgor8b9sN5zvU0bd4lP0noteMwjadV0KqrWjJA7uDzr2rDVp/TqNzG/TYru0/HtPvV3ryUH8OeSlHbFiX9iEdQ5C/BK8qkPM78fT9q7N7cb7mVAn1t0wgtO/7D22O9WsRTlzbw2m4Dd446ffuT7ThYKRUGMvf23J35JIRFRvvHi+fFZzkPxou//8M8jVbKxkB7/WqdKETRQAx7vb1xrwnbcXD+1IPiS6PG8ridb9BnHdM+UWEvLUeaMNXTB0M+m+tcT7N4GCVpsPUzjZALGoxX3GjWoAE6qlbzOHVB2LWP+22adp+B6HVgIIK907PQNFU2WALh+l4LxYIG22IctFV6iCht65iq0p6mEUqG3vc6ijK+hlOPeH3jZ9TY9WpZe/UPRlUGjDsG16tFvOPc+oAXTaNj4brrFLHi1iiZVuU6agHkBagBSvC1eyrq+OxaGUC0sTHtmIq6OOu7lrvFwAqGhu1qCQVd76eC97LyBhFFhepvk3KtLvcrPHZMG09MmT5lFCMFxTzleIpL2kboNOMrphVyowZjnEketvoZd+1RjM9p2H387dIIA95gu40HwmOtUkDPdnDQUhHHG7UCrt9v4X6jh7KhoW072KgV+6VMhwXkzf0WDEODTsopIMoDwiPKImDU2D2zVukLlaDKgEFG1ahjcbhdq5UCzm/UcNjpuQJxeq+aKHavctFAp9k9ERA4bmzEHVMnUsJYzkivI+9zf5+WDA1XtutwWAU1goCCpuHuUWfA5XUa/P1VH7NrTYKxT0YiOkNEzxHRH7ivnySin0q8JTNk0tQJUUlDz+6RVgqDIML09aP0/v5r71oO9ppd3Dns4OWdg/7vw2wGcew+cWw1/nbdbXTR7NrYb/XwnTvH6JrK+6Rjqqpthy0T5YJ6EN0+7EDXNbRNG42ujYrr6vvGvSbMITdc7xzbdRXx7X9ARBlf4+w3wOix6yV1vNto4y9vN3DQ6uGUm//HM6p2TGcim1xQu+plQ6WQiGjvmOQcw3avJx5axVOXNlBxU19EtQlOMqYGUsLcb55IjWI7Dt663wy0c3rXUi6o7L4aKZdX2+FYfRU2vqOMlSSJ4vX0GwB+HcC/dl9/G8DvAHgulRZNQdTssUl6wgSRpmprVp5Wk+6KvGv31B9FQxVzb3QtvLZ7jIqhjU1QGMXuE7d9/nbd3FcFelaKOlpd9aDVNeoLh3bPRlEnNLom6qUCDJ1QcHXj9YpKZ725UYJpDa48j9qmW95T65f37DgOmKM90KLsdEeNXQD9KG8Nalzst1QlOs+oWi7oI2tmT9uuaYl6jkltglF/F5gSxq0ad3HzweNyt9FFrWwMfM9L1NczHRiGhu162RUWlX7MSlwh4e2Adw7b+M6dRj9B4Kxd86Mc9TQzfxYqoy2Y2QKQXURZCMz8OWb+6NrayRoCw8TxhIlLmqv+WXlaxfHw8a964OrKD1oqo2jBjegt6Br2m13cb/USSbIYd9fm3ZP9Zk8Z8DWCzUClpKKV7xx1UCroOLNaAmkqtUWnZ4PhYO/YRNdSwXqGroyqtuPgrb3Bled+q4fjjvKk8R4Q59aruLAR7f74dwvtnoW39pp47W4DXTe9g0fQ2PX3x8ZKSRWhglJDNTsWHHb6if6AeKvPtHfgszpHFIJW6ltuOhF/25pdC1u+til1VQfdngpA7Jo2ru+10O5ZE12Ldz9VHXPlErxaVnU5bu4rh4tZ9leUJ1eTiDbxINfTewEcptKaBSHtQZ+mkPOIsrUN2qa3LQeNtkpGp5PKld+zbYAZ1YLh2o+nV8fF3Xp796TZs7BRLfQjtVcrBkqGhmrJwGa1CIeBRzeq2KiXsb1aRsUwADjYOeigXFRVwYpu4XuvXKx3PVv1MnYbnYnvu3dfTcvGG/eaAAOPnK6hoGtjhaq/PzwhVdAJh20TJbcUpn+cxFm4zGJxMsk5JnUTDyNokedVjfO37eJGdSDr6n6zB41UzWrlnqwi12+7mZvj9pd3P/0LroKh9dOHe7abpFW0o4iievpZAM8DuEJEfw5gC8CPxz7TEpG2amsWRNnaBm3TvYJKJctGo2uhVjRwdq2CO0fKqFfSH/x+KnUcM67vt8Cs2rpeLUbyKDlo99DtOTizVgJB5QBiMB7bWsHl7ToAN5+RoeN+q4ud/TbWykUUdRv7xya0FWBzpRzojlovG7CcUn/yht33UZ5h5YKOUkHHle36QPCV19+j1CfD96tc0HHaFXaeunI4Ktt7P83Mx2llV07LYSRKShj/+b3vNXsWdDfxpHctFzaqaPUmUwt799MrUQugv0gZVUo1iKT6KUqupxeJ6G8CeBsAAvAt968QwqzjK5JmmlxXpo0TLpUE9fD0UmADk6vjOqbt7lxMmJaqH/H6bhOXNit44tz6yN+VC/qJdnnXdW7oujy/+7OrFew3e2i0ezhom1irqvrDQXn8TZuxWjamnryT2LjGPeCGFy6e22mamY+jpt+YhCRjofxEXeQNf69c0LBWLk68axumL9xtVUDMshhMjO86U4913KT6KYrX05cAnGfml5n5GwDeDeCrkc8gzCVRVAFhtpjh32+ulLBRLUAjilSIKGybfP+4i5KuwdA1gABdJxg64bA9PtI27nWVCyqJ3iNbdTx9aQNPPLSKh0+pAlGTqhfH2VcmsXGNu65hdWWza6XmmRd0nZ4H3IP0G9PZqNL0+omq2vV/7x3n1kEhEfWTtGFzpQTLtHHU7kHXgc2VIu42umi0e5GPm1Q/RVE9fQLA54nokwAeBvDDABY2xkJ4wLhdUZQiR0FBQqNWaipl8rFKGeFWBjtom7gyVOGrazk47pqolwvYqKkJw8w46pixAg+D6Jg2uqY9EKE9HC/hP8Yk6sVxO4ZJPdvi7GKT9swLUjH5z+Gl3zB0lfrDW+FOugMYVrX5y40mGeAalTTUzc2uhStnVvHoNvdTwxsaQBpFVucl5R0VRfX0h0T0TwD8EYB7AJ5i5tuxziJMTVqR3tMQd3KMe5C9vnuM79w+QkHTUSkpdcV+s4udwmBd7ZKhodW1B1IyWDZDJ+D6XjSdexDDkdG7x128ca+Ji5u1fruHdfpJPOSAwck7CxtXku6Vo1RpRBQ5/UZcThaJehBAOU0k+jQkrW5+kKpe66eGb/csvHGviZVSIZLKMCl3+iiqp38L4D8D+F4AvwjgS0T0/lhnEaYi6frdSZKUB1bHtPHNm4coGTpqZeUWuN8yoRPhzmF74LubKyqWod2zVeoKd4fR7Kl4iEn7yK8qqRQNXNyo4cp2vf9gS+oeRPGKS9uzLUnPvFGqNDD3z+Gl3+hZTt/gO40O369qu3XQRsk1HleKRipqtHHMygPLH78RRWWYlMdapDgKAO9h5r9g5v8K4AcAfDzWWYSpSDPSOy/cP+7CMJQLoEqfrLw7jjrWQAEeQA3+J86twXIcHHVMANz3eNpeLU/cR2H63CTvwaxiYWbVhpH9ZnM/weFR20SzZ2GzVhxIvzGNy7h3DWfWKrgw1PY0o5SHSWshFyTMh+M3gPHXmsSiI4rq6WNDr98E8Hdin0mYmDxW0kuaruXg7GoJdxs9UIngPXeO2iYe31458f31ahFPX9roq+M6ZhsPrZ98WMTpI28F57CDg1bPrd4HbFaLid+DPHjFJdWGIDVWo2PhoNnF+Y1aP8Fho61yQyWtTksrSjmquneWHljD8RvAbIqlhaUZ/xVm/jgRfQ4nStsAzPwjqbZM6DPrcP1xBE0gAFPZUEqGho2VMnqWg5bloOfWDd5aKQ24rvrxP+hKhgZnaJTG7aPNlRKu3W1gr2WiWtRhEKFlWmhbDio5uwd5IkgPvtvoYHuonG69UkwlDXYaaW3ixB/MwjHAO+dw/MasiqWF7Sj+u/v3l1NtgTCWPFXSC5pA1+42wKSC7Sb1yfdKlp5dr+K4Y6Ll1mV4MkLaZC8R21v3m6iVjcDMrlEoF3SUiwZKPZUcsKirAjcaEUzb6Wdnzfoe5I2gle+pahEr5cHHS1q74DSM/3F2CbNwDPCuJ6tg3jBB8TIRfRzAYwBeAvCcm+dJmDF5ivQOmkBN0wYYOO3uLCbZevuvUdcI2xF3JSc8lRqup9JGdeI+urBRHbCLqFoPwcVjsvY8ywsn1Vitme7A0vI48hO1dvkkiwhvF3F9r6XG/2oZRFrgXMpCbRkmKD4NwATwZwB+CMCTAD4W8n0hRfKg0waCJ5AzrPNBtNVj0BY77jUOCi4NFzeN2Jk6/YStDvNyD+aBPO2CJyHOLmHahZw/fujWYRuVgo62aePSZg3lQrSiV2kTJiieZOZ3AgARPQfgK7Np0vKSx1iJYYImkKbRCSvWuNVjUjloktYPz/sDLmv8Y5iIYFo2TDuZ4kazJO44mGYRsXPQxn6zi1qxgLVKET3LwWGrhzsFHZc2a7mwhYWd3fT+EZVT+uQ5VsJPkMteraCjWjJi+eQn5W4aJd1FHB/3PLiuzivDY7igq2yn59Yrc9eHsxwHdw7bqBYMFAwNa9UCGIChabh72M4s3fowYTuKdxHRkfs/Aai4rwkAM/Nq6q1bItJysUuaoG22l3U1ztY7qZ1AlPrdcXcuomKajHkZw1GZ1Tggon6a1ZKhY3u1hHuNLtom52ahElYze37E/wIwT7ESoyZQnEmVlKfIOP3woj288sw8jOE8qne36yXsHHZARDA0gkaEWsnA49sruRmj4gSeE2ZZCzsPJJlCIizydNa1hZeZvI/hvKp3z52qYqNagOU4aPUsWI6DjWphZPxQFuTjDgq5KQUZl0lz3MxKB5z3h9cikfcxnNdUOOWCjsvbdZxbq2CrXsa5tQoub9cz3+n4iZJmPFOI6EcBvB/ANoBfZeYvZNuidMhTrERUpvVcmoUOeBm8mPKiTsn7GM6zaizvdrFUl1VE9N+I6C4RfWPo/R8kom8R0atE9PNhx2Dm/8XM/xjARwB8KMXmZk7aGUOTJq8rND+L7sWUN3VKnsew7C4nJ+0dxW8A+C8AftN7g4h0AL8KlVjwBoCvEtHzAHSoIkl+/iEz33X//zfu72ZOXlZseWPWK7RJ70PeV2vTIMb66CzD7jItUhUUzPynRPTI0NvvAfAqM18DACL6DIBnmPkTAD4wfAxSuRT+HYA/YOavjToXEX0UwEcB4OLFi8lcANIr4r4IRPVcSkLQyn0IJs/qlLyRd9VYnsliz/UwgOu+1zfc90bxzwC8D8CPuZX2AmHmZ5n5KjNf3draSqalmA/1SlZEMV4mpRqR+xCMqFPikWfVWJ7JwphNAe+dTBbkfcD8SQCfTK854UyzYlt0lVWUFVpSqhFZOQcj6hRhFmSx7LgB4ILv9XkAOxm0IxKTrtjyZmRMi3ErtKTiGGTlHMyiG+uFfJDFLPsqgMeJ6FEiKgL4MIDnkzgwEX2QiJ49PDxM4nAAJvcNF1WJIqkHfN599LNE1ClC2qTtHvvbAP4CwNuI6AYR/ZSbYPBnAPwhgFcAfJaZX07ifMz8OWb+6NraWhKHAzD5ik0ighVJPeBl5SwsO5MGtyYBMY80D8wtV69e5RdeeCHTNnhqp6Jv5ezVSVg2/fGi22oEIW38Xn/Dtqik5hIRvcjMV4M+y31k9rwiRsYHLHIcgyDMgqzjZRbKEpiGjWJSRFUiCEJUxqmVslZlL5SgSMNGMQ1pGhmz1FcKgpAcUTwks/b6WyhBsSwsi+utICwDUTwks/b6E0Exh4jrrSBkS5I7+ihqpaxV2WLMnkMkSlkQsiPpvGNRc6Zl6RSyUDuKPBmz0yRrfaUgLDNJ7+izVitFYaGeLHkzZqfFPAwsQVhUkvZAylqtFAVRPc0pRIQbe00QEbbrpdwNLEFYVKKqiuKQ91ijhdpRLAOefrSga3jUdbtdvNh6Qcgvy7ijF0ExZ4jHkyBkyzyoipJmoVRPRPRBAB987LHHsm5Kaiyqx5PkgxLmibyripJmoXYUy2DMXkSPp1kHEEpUuyDEY36fLkvKIupHZ6lOk6h2YRyykDiJCIo5YxH1o7NMeCY2HiEMWUgEs1A2imVh0fSjabgbjmJRbTxCMmSdzjuvyI5CyJxZqtMW0cYjJEfW6bzzykLNjmVJ4bFozFKdtog2nkVnljYDWUgEI6VQc4S4iM4G6ef5YRYlQLM8X54IK4W63GIyR4gRbXakWVBKSJZZOx8sorNIEogxOyeIEU2Iw7LsirJwPlg0Z5EkkB1FThAjmhCVZdp9is0gH0hv5wSZEEJUlikWRJwP8oE8hXKCTAghKsu0+xSbQT4QG0VO8CbE/eMuWj0bJUOTCSEEMssAxTwgNoPsWShBMe/ZY2VCCFHYXCnh5n4LAE64cApCGizUEmQZsscKgqhjhFmzUDsKIb8sizvnrJDdpzBLFmpHIeSTZXLnFIRFRASFkDrL5M4pCIuICAohdZbJnVMQFhERFELqSDChIMw3YsxeIrIyKIs7pyDMN7KkWxKyNCiLO6cgzDeyo1gSss5OK+6cgjC/LNSOQircjUYMyoIgTMpCCQqJzB6NGJQFQZgUeUosCZKdVhCESRFBsSSIQVkQhEkRY/YSIQZlQRAmQXYUgiAIQigiKARBEIRQRFAIgiAIoYigEARBEEIRQSEIgiCEIoJCEARBCEUEhSAIghCKxFEIgiDMCVmVCpAdhSAIwhyQZamAhRIUkj1WEIRFJcva8wslKCR7rCAIi0qWpQIWSlAIgiAsKlmWChBBIQiCMAdkWSpABIUgCMIckGWpAHGPFQRBmBOyKhUgOwpBEAQhFBEUgiAIQigiKARBEIRQRFAIgiAIoYgxWxAEIYdkldcpCNlRCIIg5Iws8zoFIYJCEAQhZ2SZ1ykIERSCIAg5I8u8TkGIoBAEQcgZWeZ1CkIEhSAIQs7IMq9TECIoBEEQckaWeZ2CEPdYQRCEHJJVXqcgRFAIgiBkQJ7iJMYhqidBEIQZk7c4iXGIoBAEQZgxeYuTGAcx8/hvzRlEtAvgzazbkTCnAdzLuhE5RPplNNI3wWTeL2QUS8zOiaAIIk1jq5eVtLjEzFtBHyykoFhEiOgFZr6adTvyhvTLaKRvgpF+iY+ongRBEIRQRFAIgiAIoYigmB+ezboBOUX6ZTTSN8FIv8REbBSCIAhCKLKjEARBEEIRQSEIgiCEIoIiZxDRBSL6IhG9QkQvE9HH3Pc3iOiPiOg77t9TWbc1C4hIJ6KvE9H/cV9LvwAgonUi+l0i+kt37HyP9A1ARP/CnUffIKLfJqKy9Et8RFDkDwvAzzLzEwDeC+CniehJAD8P4E+Y+XEAf+K+XkY+BuAV32vpF8V/AvB5Zn47gHdB9dFS9w0RPQzgnwO4ysx/BYAO4MNY8n6ZBBEUOYOZbzHz19z/G1AT/mEAzwD4tPu1TwP40UwamCFEdB7A+wF8yve29AvRKoDvBfAcADBzj5kPIH0DqMSnFSIyAFQB7ED6JTYiKHIMET0C4CkAXwZwhplvAUqYANjOsGlZ8SsA/iUAf+oD6RfgMoBdAL/uquU+RUQ1LHnfMPNNAL8M4C0AtwAcMvMXsOT9MgkiKHIKEa0A+J8APs7MR1m3J2uI6AMA7jLzi1m3JYcYAJ4G8GvM/BSAJkSdAtf28AyARwGcA1Ajop/ItlXziQiKHEJEBSgh8T+Y+ffct+8Q0UPu5w8BuJtV+zLirwH4ESJ6A8BnAHwfEf0WpF8A4AaAG8z8Zff170IJjmXvm/cBeJ2Zd5nZBPB7AP4qpF9iI4IiZxARQemaX2Hm/+j76HkAP+n+/5MA/ves25YlzPwLzHyemR+BMkj+X2b+CSx5vwAAM98GcJ2I3ua+9f0Avgnpm7cAvJeIqu68+n4om9+y90tsJDI7ZxDRXwfwZwBewgNd/L+CslN8FsBFqAnw48y8l0kjM4aI/haAn2PmDxDRJqRfQETvhjLyFwFcA/APoBaCS903RPRLAD4E5U34dQD/CMAKlrxf4iKCQhAEQQhFVE+CIAhCKCIoBEEQhFBEUAiCIAihiKAQBEEQQhFBIQiCIIQigkIQBEEIRQSFIMwYIvoIEe0S0ad87/0CEb1KRN8ioh/wvf9FIjomoqvZtFYQVI4YQRBmhJvFFAB+h5l/xn3vSaho83dA5ST6YyL6Lma2mflvE9GXsmmtIChkRyEIE0BENSL6fSL6f25RnA8R0RtE9EtE9DUieomI3u5+9xeJ6Fki+gKA3ww43DMAPsPMXWZ+HcCrAN4zw8sRhFBEUAjCZPwggB1mfpdbFOfz7vv3mPlpAL8G4Od83/9uAM8w898LONbDAK77Xt9w3xOEXCCCQhAm4yUA7yOif09Ef4OZD933vWy/LwJ4xPf955m5PeJYFPCe5NYRcoPYKARhApj520T03QB+GMAnXLUSAHTdvzYG51cz5HA3AFzwvT4PVYlNEHKB7CgEYQKI6ByAFjP/FlQVtaenONzzAD5MRCUiehTA4wC+kkAzBSERZEchCJPxTgD/gYgcACaAfwpVMCg2zPwyEX0WqoaEBeCnmdlOrKWCMCWSZlwQZgwRfQTAVc89NsL3vwRVf+OFNNslCKMQ1ZMgzJ42gB/yB9yNgoi+COAy1K5FEDJBdhSCIAhCKLKjEARBEEIRQSEIgiCEIoJCEARBCEUEhSAIghDK/wfbUMOeMUnOyAAAAABJRU5ErkJggg==",
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1375,24 +1248,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... as well as the gradient ..."
+    "Then the illumination gradient."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1404,24 +1275,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and the refractiveindex for the last."
+    "And finally the refractive index."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1435,27 +1304,27 @@
    "source": [
     "### 5.4. Experimental Data\n",
     "\n",
-    "We apply the trained model to two experomental videos with high noise and low noise."
+    "Finally, you apply the trained model to real data: two experimental videos, one with low noise and one with high noise. The network was trained only on simulated images, so this lets you see how well it carries over to real frames."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Define a custom dataset for experimental video..."
+    "First, you define a custom dataset for the experimental videos."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
-    "class ExperimantalDataset(torch.utils.data.Dataset):\n",
+    "class ExperimentalDataset(torch.utils.data.Dataset):\n",
     "    \"\"\"Experimental dataset.\"\"\"\n",
     "\n",
     "    def __init__(self, data_images):\n",
-    "        \"\"\"Load experimantal images\"\"\"\n",
+    "        \"\"\"Load experimental images\"\"\"\n",
     "        self.images = data_images\n",
     "\n",
     "    def __len__(self):\n",
@@ -1472,21 +1341,21 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and use it to create the low noise real data and high noise data loaders."
+    "Then, you use it to create the low-noise and high-noise data loaders."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
     "video_low_noise_dataloader = dl.DataLoader(\n",
-    "    ExperimantalDataset(data_images=video_low_noise),\n",
+    "    ExperimentalDataset(data_images=video_low_noise),\n",
     "    batch_size=32,\n",
     ")\n",
     "video_high_noise_dataloader = dl.DataLoader(\n",
-    "    ExperimantalDataset(data_images=video_high_noise),\n",
+    "    ExperimentalDataset(data_images=video_high_noise),\n",
     "    batch_size=32,\n",
     ")"
    ]
@@ -1495,12 +1364,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Use the trained model to predict the particle position in low noise video ..."
+    "You use the trained model to predict the particle position in the low-noise video."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1515,19 +1384,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and display the result."
+    "Then you display the result as an animation."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "tags": []
    },
    "outputs": [
     {
      "data": {
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' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\n        return false;\n    });\n\n    function set_focus() {\n        canvas.focus();\n        canvas_div.focus();\n    }\n\n    window.setTimeout(set_focus, 100);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.findpos = function (e) {\n    //this section is from http://www.quirksmode.org/js/events_properties.html\n    var targ;\n    if (!e) {\n        e = window.event;\n    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n\n    return { x: x, y: y };\n};\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\n\n    /* This prevents the web browser from automatically changing to\n     * the text insertion cursor when the button is pressed.  We want\n     * to control all of the cursor setting manually through the\n     * 'cursor' event from matplotlib */\n    event.preventDefault();\n    return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
+      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n    if (typeof WebSocket !== 'undefined') {\n        return WebSocket;\n    } else if (typeof MozWebSocket !== 'undefined') {\n        return MozWebSocket;\n    } else {\n        alert(\n            'Your browser does not have WebSocket support. ' +\n                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute('tabindex', '0');\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;' +\n            'z-index: 2;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute(\n        'style',\n        'box-sizing: content-box;' +\n            'pointer-events: none;' +\n            'position: relative;' +\n            'z-index: 0;'\n    );\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box;' +\n            'left: 0;' +\n            'pointer-events: none;' +\n            'position: absolute;' +\n            'top: 0;' +\n            'z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        // There's no need to resize if the WebSocket is not connected:\n        // - If it is still connecting, then we will get an initial resize from\n        //   Python once it connects.\n        // - If it has disconnected, then resizing will clear the canvas and\n        //   never get anything back to refill it, so better to not resize and\n        //   keep something visible.\n        if (fig.ws.readyState != 1) {\n            return;\n        }\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            /* This rescales the canvas back to display pixels, so that it\n             * appears correct on HiDPI screens. */\n            canvas.style.width = width + 'px';\n            canvas.style.height = height + 'px';\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        /* User Agent sniffing is bad, but WebKit is busted:\n         * https://bugs.webkit.org/show_bug.cgi?id=144526\n         * https://bugs.webkit.org/show_bug.cgi?id=181818\n         * The worst that happens here is that they get an extra browser\n         * selection when dragging, if this check fails to catch them.\n         */\n        var UA = navigator.userAgent;\n        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n        if(isWebKit) {\n            return function (event) {\n                /* This prevents the web browser from automatically changing to\n                 * the text insertion cursor when the button is pressed. We\n                 * want to control all of the cursor setting manually through\n                 * the 'cursor' event from matplotlib */\n                event.preventDefault()\n                return fig.mouse_event(event, name);\n            };\n        } else {\n            return function (event) {\n                return fig.mouse_event(event, name);\n            };\n        }\n    }\n\n    canvas_div.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    canvas_div.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    canvas_div.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    canvas_div.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    canvas_div.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    canvas_div.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    canvas_div.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\n        return false;\n    });\n\n    function set_focus() {\n        canvas.focus();\n        canvas_div.focus();\n    }\n\n    window.setTimeout(set_focus, 100);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.canvas_div.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '%s' message type: \",\n                msg_type,\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '%s' message: \", msg_type, msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_%s' callback:\",\n                    msg_type,\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\nfunction getModifiers(event) {\n    var mods = [];\n    if (event.ctrlKey) {\n        mods.push('ctrl');\n    }\n    if (event.altKey) {\n        mods.push('alt');\n    }\n    if (event.shiftKey) {\n        mods.push('shift');\n    }\n    if (event.metaKey) {\n        mods.push('meta');\n    }\n    return mods;\n}\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    // from https://stackoverflow.com/q/1114465\n    var boundingRect = this.canvas.getBoundingClientRect();\n    var x = (event.clientX - boundingRect.left) * this.ratio;\n    var y = (event.clientY - boundingRect.top) * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        buttons: event.buttons,\n        modifiers: getModifiers(event),\n        guiEvent: simpleKeys(event),\n    });\n\n    return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
       "text/plain": [
        "<IPython.core.display.Javascript object>"
       ]
@@ -1538,7 +1407,7 @@
     {
      "data": {
       "text/html": [
-       "<div id='ee00436f-db1e-4411-aca4-c99a3f019947'></div>"
+       "<div id='441adf5d-0d57-42c6-9ea5-ae0ce47ffc3a'></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1547,13 +1416,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO:matplotlib.animation:Animation.save using <class 'matplotlib.animation.HTMLWriter'>\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -1742,42 +1604,42 @@
        "</style>\n",
        "\n",
        "<div class=\"animation\">\n",
-       "  <img id=\"_anim_img5b67b5f0d6584d469eba2b90d297088b\">\n",
+       "  <img id=\"_anim_img6c3f2f4dc1a342089efbfa4081da41e5\">\n",
        "  <div class=\"anim-controls\">\n",
-       "    <input id=\"_anim_slider5b67b5f0d6584d469eba2b90d297088b\" type=\"range\" class=\"anim-slider\"\n",
+       "    <input id=\"_anim_slider6c3f2f4dc1a342089efbfa4081da41e5\" type=\"range\" class=\"anim-slider\"\n",
        "           name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\"\n",
-       "           oninput=\"anim5b67b5f0d6584d469eba2b90d297088b.set_frame(parseInt(this.value));\"></input>\n",
+       "           oninput=\"anim6c3f2f4dc1a342089efbfa4081da41e5.set_frame(parseInt(this.value));\">\n",
        "    <div class=\"anim-buttons\">\n",
-       "      <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.slower()\">\n",
+       "      <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.slower()\">\n",
        "          <i class=\"fa fa-minus\"></i></button>\n",
-       "      <button title=\"First frame\" aria-label=\"First frame\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.first_frame()\">\n",
+       "      <button title=\"First frame\" aria-label=\"First frame\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.first_frame()\">\n",
        "        <i class=\"fa fa-fast-backward\"></i></button>\n",
-       "      <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.previous_frame()\">\n",
+       "      <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.previous_frame()\">\n",
        "          <i class=\"fa fa-step-backward\"></i></button>\n",
-       "      <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.reverse_animation()\">\n",
+       "      <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.reverse_animation()\">\n",
        "          <i class=\"fa fa-play fa-flip-horizontal\"></i></button>\n",
-       "      <button title=\"Pause\" aria-label=\"Pause\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.pause_animation()\">\n",
+       "      <button title=\"Pause\" aria-label=\"Pause\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.pause_animation()\">\n",
        "          <i class=\"fa fa-pause\"></i></button>\n",
-       "      <button title=\"Play\" aria-label=\"Play\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.play_animation()\">\n",
+       "      <button title=\"Play\" aria-label=\"Play\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.play_animation()\">\n",
        "          <i class=\"fa fa-play\"></i></button>\n",
-       "      <button title=\"Next frame\" aria-label=\"Next frame\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.next_frame()\">\n",
+       "      <button title=\"Next frame\" aria-label=\"Next frame\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.next_frame()\">\n",
        "          <i class=\"fa fa-step-forward\"></i></button>\n",
-       "      <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.last_frame()\">\n",
+       "      <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.last_frame()\">\n",
        "          <i class=\"fa fa-fast-forward\"></i></button>\n",
-       "      <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"anim5b67b5f0d6584d469eba2b90d297088b.faster()\">\n",
+       "      <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"anim6c3f2f4dc1a342089efbfa4081da41e5.faster()\">\n",
        "          <i class=\"fa fa-plus\"></i></button>\n",
        "    </div>\n",
-       "    <form title=\"Repetition mode\" aria-label=\"Repetition mode\" action=\"#n\" name=\"_anim_loop_select5b67b5f0d6584d469eba2b90d297088b\"\n",
+       "    <form title=\"Repetition mode\" aria-label=\"Repetition mode\" action=\"#n\" name=\"_anim_loop_select6c3f2f4dc1a342089efbfa4081da41e5\"\n",
        "          class=\"anim-state\">\n",
-       "      <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_5b67b5f0d6584d469eba2b90d297088b\"\n",
+       "      <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_6c3f2f4dc1a342089efbfa4081da41e5\"\n",
        "             >\n",
-       "      <label for=\"_anim_radio1_5b67b5f0d6584d469eba2b90d297088b\">Once</label>\n",
-       "      <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_5b67b5f0d6584d469eba2b90d297088b\"\n",
+       "      <label for=\"_anim_radio1_6c3f2f4dc1a342089efbfa4081da41e5\">Once</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_6c3f2f4dc1a342089efbfa4081da41e5\"\n",
        "             checked>\n",
-       "      <label for=\"_anim_radio2_5b67b5f0d6584d469eba2b90d297088b\">Loop</label>\n",
-       "      <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_5b67b5f0d6584d469eba2b90d297088b\"\n",
+       "      <label for=\"_anim_radio2_6c3f2f4dc1a342089efbfa4081da41e5\">Loop</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_6c3f2f4dc1a342089efbfa4081da41e5\"\n",
        "             >\n",
-       "      <label for=\"_anim_radio3_5b67b5f0d6584d469eba2b90d297088b\">Reflect</label>\n",
+       "      <label for=\"_anim_radio3_6c3f2f4dc1a342089efbfa4081da41e5\">Reflect</label>\n",
        "    </form>\n",
        "  </div>\n",
        "</div>\n",
@@ -1787,20720 +1649,19610 @@
        "  /* Instantiate the Animation class. */\n",
        "  /* The IDs given should match those used in the template above. */\n",
        "  (function() {\n",
-       "    var img_id = \"_anim_img5b67b5f0d6584d469eba2b90d297088b\";\n",
-       "    var slider_id = \"_anim_slider5b67b5f0d6584d469eba2b90d297088b\";\n",
-       "    var loop_select_id = \"_anim_loop_select5b67b5f0d6584d469eba2b90d297088b\";\n",
+       "    var img_id = \"_anim_img6c3f2f4dc1a342089efbfa4081da41e5\";\n",
+       "    var slider_id = \"_anim_slider6c3f2f4dc1a342089efbfa4081da41e5\";\n",
+       "    var loop_select_id = \"_anim_loop_select6c3f2f4dc1a342089efbfa4081da41e5\";\n",
        "    var frames = new Array(100);\n",
        "    \n",
-       "  frames[0] = \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90\\\n",
-       "bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAA9h\\\n",
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        "\"\n",
        "\n",
        "\n",
        "    /* set a timeout to make sure all the above elements are created before\n",
        "       the object is initialized. */\n",
        "    setTimeout(function() {\n",
-       "        anim5b67b5f0d6584d469eba2b90d297088b = new Animation(frames, img_id, slider_id, 50.0,\n",
+       "        anim6c3f2f4dc1a342089efbfa4081da41e5 = new Animation(frames, img_id, slider_id, 50.0,\n",
        "                                 loop_select_id);\n",
        "    }, 0);\n",
        "  })()\n",
@@ -22510,7 +21262,7 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -22523,7 +21275,6 @@
     "\n",
     "fig, ax1 = plt.subplots()\n",
     "\n",
-    "x = np.linspace(0, 2 * np.pi, 100)\n",
     "ax1.imshow(video_low_noise[0], cmap=\"gray\")\n",
     "(point,) = ax1.plot(preds[0:1, 0], preds[0:1, 1], c=\"r\", marker=\"o\")\n",
     "\n",
@@ -22556,12 +21307,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Use the trained model to predict the particle position in high noise video ..."
+    "You then do the same for the high-noise video."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -22576,17 +21327,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "... and display the result."
+    "And display the result."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n    if (typeof WebSocket !== 'undefined') {\n        return WebSocket;\n    } else if (typeof MozWebSocket !== 'undefined') {\n        return MozWebSocket;\n    } else {\n        alert(\n            'Your browser does not have WebSocket support. ' +\n                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\n        return false;\n    });\n\n    function set_focus() {\n        canvas.focus();\n        canvas_div.focus();\n    }\n\n    window.setTimeout(set_focus, 100);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.findpos = function (e) {\n    //this section is from http://www.quirksmode.org/js/events_properties.html\n    var targ;\n    if (!e) {\n        e = window.event;\n    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n\n    return { x: x, y: y };\n};\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\n\n    /* This prevents the web browser from automatically changing to\n     * the text insertion cursor when the button is pressed.  We want\n     * to control all of the cursor setting manually through the\n     * 'cursor' event from matplotlib */\n    event.preventDefault();\n    return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
+      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n    if (typeof WebSocket !== 'undefined') {\n        return WebSocket;\n    } else if (typeof MozWebSocket !== 'undefined') {\n        return MozWebSocket;\n    } else {\n        alert(\n            'Your browser does not have WebSocket support. ' +\n                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute('tabindex', '0');\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;' +\n            'z-index: 2;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute(\n        'style',\n        'box-sizing: content-box;' +\n            'pointer-events: none;' +\n            'position: relative;' +\n            'z-index: 0;'\n    );\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box;' +\n            'left: 0;' +\n            'pointer-events: none;' +\n            'position: absolute;' +\n            'top: 0;' +\n            'z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        // There's no need to resize if the WebSocket is not connected:\n        // - If it is still connecting, then we will get an initial resize from\n        //   Python once it connects.\n        // - If it has disconnected, then resizing will clear the canvas and\n        //   never get anything back to refill it, so better to not resize and\n        //   keep something visible.\n        if (fig.ws.readyState != 1) {\n            return;\n        }\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            /* This rescales the canvas back to display pixels, so that it\n             * appears correct on HiDPI screens. */\n            canvas.style.width = width + 'px';\n            canvas.style.height = height + 'px';\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        /* User Agent sniffing is bad, but WebKit is busted:\n         * https://bugs.webkit.org/show_bug.cgi?id=144526\n         * https://bugs.webkit.org/show_bug.cgi?id=181818\n         * The worst that happens here is that they get an extra browser\n         * selection when dragging, if this check fails to catch them.\n         */\n        var UA = navigator.userAgent;\n        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n        if(isWebKit) {\n            return function (event) {\n                /* This prevents the web browser from automatically changing to\n                 * the text insertion cursor when the button is pressed. We\n                 * want to control all of the cursor setting manually through\n                 * the 'cursor' event from matplotlib */\n                event.preventDefault()\n                return fig.mouse_event(event, name);\n            };\n        } else {\n            return function (event) {\n                return fig.mouse_event(event, name);\n            };\n        }\n    }\n\n    canvas_div.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    canvas_div.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    canvas_div.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    canvas_div.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    canvas_div.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    canvas_div.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    canvas_div.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\n        return false;\n    });\n\n    function set_focus() {\n        canvas.focus();\n        canvas_div.focus();\n    }\n\n    window.setTimeout(set_focus, 100);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.canvas_div.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '%s' message type: \",\n                msg_type,\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '%s' message: \", msg_type, msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_%s' callback:\",\n                    msg_type,\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\nfunction getModifiers(event) {\n    var mods = [];\n    if (event.ctrlKey) {\n        mods.push('ctrl');\n    }\n    if (event.altKey) {\n        mods.push('alt');\n    }\n    if (event.shiftKey) {\n        mods.push('shift');\n    }\n    if (event.metaKey) {\n        mods.push('meta');\n    }\n    return mods;\n}\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    // from https://stackoverflow.com/q/1114465\n    var boundingRect = this.canvas.getBoundingClientRect();\n    var x = (event.clientX - boundingRect.left) * this.ratio;\n    var y = (event.clientY - boundingRect.top) * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        buttons: event.buttons,\n        modifiers: getModifiers(event),\n        guiEvent: simpleKeys(event),\n    });\n\n    return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
       "text/plain": [
        "<IPython.core.display.Javascript object>"
       ]
@@ -22597,7 +21348,7 @@
     {
      "data": {
       "text/html": [
-       "<div id='038171ca-4032-4629-896b-f71b1e37399c'></div>"
+       "<div id='30c0bf3b-5115-4836-8fbb-02198f5327f7'></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -22606,13 +21357,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO:matplotlib.animation:Animation.save using <class 'matplotlib.animation.HTMLWriter'>\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -22801,42 +21545,42 @@
        "</style>\n",
        "\n",
        "<div class=\"animation\">\n",
-       "  <img id=\"_anim_img1b1cdc0c782b4e0aa83da8dc557b7713\">\n",
+       "  <img id=\"_anim_img2c6b8bc416754e668be8f14a0d1c948f\">\n",
        "  <div class=\"anim-controls\">\n",
-       "    <input id=\"_anim_slider1b1cdc0c782b4e0aa83da8dc557b7713\" type=\"range\" class=\"anim-slider\"\n",
+       "    <input id=\"_anim_slider2c6b8bc416754e668be8f14a0d1c948f\" type=\"range\" class=\"anim-slider\"\n",
        "           name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\"\n",
-       "           oninput=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.set_frame(parseInt(this.value));\"></input>\n",
+       "           oninput=\"anim2c6b8bc416754e668be8f14a0d1c948f.set_frame(parseInt(this.value));\">\n",
        "    <div class=\"anim-buttons\">\n",
-       "      <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.slower()\">\n",
+       "      <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.slower()\">\n",
        "          <i class=\"fa fa-minus\"></i></button>\n",
-       "      <button title=\"First frame\" aria-label=\"First frame\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.first_frame()\">\n",
+       "      <button title=\"First frame\" aria-label=\"First frame\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.first_frame()\">\n",
        "        <i class=\"fa fa-fast-backward\"></i></button>\n",
-       "      <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.previous_frame()\">\n",
+       "      <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.previous_frame()\">\n",
        "          <i class=\"fa fa-step-backward\"></i></button>\n",
-       "      <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.reverse_animation()\">\n",
+       "      <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.reverse_animation()\">\n",
        "          <i class=\"fa fa-play fa-flip-horizontal\"></i></button>\n",
-       "      <button title=\"Pause\" aria-label=\"Pause\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.pause_animation()\">\n",
+       "      <button title=\"Pause\" aria-label=\"Pause\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.pause_animation()\">\n",
        "          <i class=\"fa fa-pause\"></i></button>\n",
-       "      <button title=\"Play\" aria-label=\"Play\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.play_animation()\">\n",
+       "      <button title=\"Play\" aria-label=\"Play\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.play_animation()\">\n",
        "          <i class=\"fa fa-play\"></i></button>\n",
-       "      <button title=\"Next frame\" aria-label=\"Next frame\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.next_frame()\">\n",
+       "      <button title=\"Next frame\" aria-label=\"Next frame\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.next_frame()\">\n",
        "          <i class=\"fa fa-step-forward\"></i></button>\n",
-       "      <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.last_frame()\">\n",
+       "      <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.last_frame()\">\n",
        "          <i class=\"fa fa-fast-forward\"></i></button>\n",
-       "      <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"anim1b1cdc0c782b4e0aa83da8dc557b7713.faster()\">\n",
+       "      <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"anim2c6b8bc416754e668be8f14a0d1c948f.faster()\">\n",
        "          <i class=\"fa fa-plus\"></i></button>\n",
        "    </div>\n",
-       "    <form title=\"Repetition mode\" aria-label=\"Repetition mode\" action=\"#n\" name=\"_anim_loop_select1b1cdc0c782b4e0aa83da8dc557b7713\"\n",
+       "    <form title=\"Repetition mode\" aria-label=\"Repetition mode\" action=\"#n\" name=\"_anim_loop_select2c6b8bc416754e668be8f14a0d1c948f\"\n",
        "          class=\"anim-state\">\n",
-       "      <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_1b1cdc0c782b4e0aa83da8dc557b7713\"\n",
+       "      <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_2c6b8bc416754e668be8f14a0d1c948f\"\n",
        "             >\n",
-       "      <label for=\"_anim_radio1_1b1cdc0c782b4e0aa83da8dc557b7713\">Once</label>\n",
-       "      <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_1b1cdc0c782b4e0aa83da8dc557b7713\"\n",
+       "      <label for=\"_anim_radio1_2c6b8bc416754e668be8f14a0d1c948f\">Once</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_2c6b8bc416754e668be8f14a0d1c948f\"\n",
        "             checked>\n",
-       "      <label for=\"_anim_radio2_1b1cdc0c782b4e0aa83da8dc557b7713\">Loop</label>\n",
-       "      <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_1b1cdc0c782b4e0aa83da8dc557b7713\"\n",
+       "      <label for=\"_anim_radio2_2c6b8bc416754e668be8f14a0d1c948f\">Loop</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_2c6b8bc416754e668be8f14a0d1c948f\"\n",
        "             >\n",
-       "      <label for=\"_anim_radio3_1b1cdc0c782b4e0aa83da8dc557b7713\">Reflect</label>\n",
+       "      <label for=\"_anim_radio3_2c6b8bc416754e668be8f14a0d1c948f\">Reflect</label>\n",
        "    </form>\n",
        "  </div>\n",
        "</div>\n",
@@ -22846,28545 +21590,26742 @@
        "  /* Instantiate the Animation class. */\n",
        "  /* The IDs given should match those used in the template above. */\n",
        "  (function() {\n",
-       "    var img_id = \"_anim_img1b1cdc0c782b4e0aa83da8dc557b7713\";\n",
-       "    var slider_id = \"_anim_slider1b1cdc0c782b4e0aa83da8dc557b7713\";\n",
-       "    var loop_select_id = \"_anim_loop_select1b1cdc0c782b4e0aa83da8dc557b7713\";\n",
+       "    var img_id = \"_anim_img2c6b8bc416754e668be8f14a0d1c948f\";\n",
+       "    var slider_id = \"_anim_slider2c6b8bc416754e668be8f14a0d1c948f\";\n",
+       "    var loop_select_id = \"_anim_loop_select2c6b8bc416754e668be8f14a0d1c948f\";\n",
        "    var frames = new Array(100);\n",
        "    \n",
-       "  frames[0] = \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90\\\n",
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+       "EBgKQAAAgMBQAAIAAASGAhAAACAwFIAAAACBoQAEAAAIDAUgAABAYCgAAQAAAkMBCAAAEBgKQAAA\\\n",
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        "\"\n",
        "\n",
        "\n",
        "    /* set a timeout to make sure all the above elements are created before\n",
        "       the object is initialized. */\n",
        "    setTimeout(function() {\n",
-       "        anim1b1cdc0c782b4e0aa83da8dc557b7713 = new Animation(frames, img_id, slider_id, 50.0,\n",
+       "        anim2c6b8bc416754e668be8f14a0d1c948f = new Animation(frames, img_id, slider_id, 50.0,\n",
        "                                 loop_select_id);\n",
        "    }, 0);\n",
        "  })()\n",
@@ -51394,7 +48335,7 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -51402,7 +48343,6 @@
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "\n",
-    "x = np.linspace(0, 2 * np.pi, 100)\n",
     "ax1.imshow(video_high_noise[0], cmap=\"gray\")\n",
     "(point,) = ax1.plot(preds[0:1, 0], preds[0:1, 1], c=\"r\", marker=\"o\")\n",
     "\n",
@@ -51439,7 +48379,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "py_env_book (3.10.15)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -51453,7 +48393,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.15"
+   "version": "3.11.9"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {