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Commit ba51ce3f authored by f970dc0df332a50d403a0d887dc1b88b's avatar f970dc0df332a50d403a0d887dc1b88b
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verif

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Showing with 43 additions and 41 deletions
module3/exo3/exercice.ipynb
View file @ ba51ce3f
...@@ -35,7 +35,7 @@ ...@@ -35,7 +35,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 146, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -65,7 +65,7 @@ ...@@ -65,7 +65,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -88,7 +88,7 @@ ...@@ -88,7 +88,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 173, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -556,7 +556,7 @@ ...@@ -556,7 +556,7 @@
"[1314 rows x 3 columns]" "[1314 rows x 3 columns]"
] ]
}, },
"execution_count": 173, "execution_count": 3,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -575,7 +575,7 @@ ...@@ -575,7 +575,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -615,7 +615,7 @@ ...@@ -615,7 +615,7 @@
"Index: []" "Index: []"
] ]
}, },
"execution_count": 9, "execution_count": 4,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -626,7 +626,7 @@ ...@@ -626,7 +626,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10, "execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -654,7 +654,7 @@ ...@@ -654,7 +654,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 33, "execution_count": 6,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -713,7 +713,7 @@ ...@@ -713,7 +713,7 @@
"Yes 443 139 0.239" "Yes 443 139 0.239"
] ]
}, },
"execution_count": 33, "execution_count": 6,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -733,16 +733,16 @@ ...@@ -733,16 +733,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 42, "execution_count": 7,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<matplotlib.legend.Legend at 0x7f64b2d2c6a0>" "<matplotlib.legend.Legend at 0x7f7df9e3ca90>"
] ]
}, },
"execution_count": 42, "execution_count": 7,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
}, },
...@@ -787,22 +787,22 @@ ...@@ -787,22 +787,22 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 258, "execution_count": 8,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f64aeebbfd0>" "<matplotlib.axes._subplots.AxesSubplot at 0x7f7df7d2f748>"
] ]
}, },
"execution_count": 258, "execution_count": 8,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
}, },
{ {
"data": { "data": {
"image/png": 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\n", "image/png": "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\n",
"text/plain": [ "text/plain": [
"<Figure size 432x288 with 1 Axes>" "<Figure size 432x288 with 1 Axes>"
] ]
...@@ -826,16 +826,16 @@ ...@@ -826,16 +826,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 259, "execution_count": 9,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f64aee61da0>" "<matplotlib.axes._subplots.AxesSubplot at 0x7f7df7d95940>"
] ]
}, },
"execution_count": 259, "execution_count": 9,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
}, },
...@@ -860,6 +860,8 @@ ...@@ -860,6 +860,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"On voit bien que l'âge des non fumeuses est en moyenne plus élevé, et donc que les observations ne sont pas bien réparties. Mais alors, comment l'âge rentre-t-il en jeu ?\n",
"\n",
"La prochaine étape est donc d'étudier les données plus précisément, notamment suivant les tranches d'âges.\n", "La prochaine étape est donc d'étudier les données plus précisément, notamment suivant les tranches d'âges.\n",
"\n", "\n",
"## Décès liés au tabagisme suivant l'âge\n", "## Décès liés au tabagisme suivant l'âge\n",
...@@ -869,7 +871,7 @@ ...@@ -869,7 +871,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 260, "execution_count": 10,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -976,7 +978,7 @@ ...@@ -976,7 +978,7 @@
" Yes 7 42 0.857" " Yes 7 42 0.857"
] ]
}, },
"execution_count": 260, "execution_count": 10,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -999,16 +1001,16 @@ ...@@ -999,16 +1001,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 261, "execution_count": 11,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<matplotlib.legend.Legend at 0x7f64aedae898>" "<matplotlib.legend.Legend at 0x7f7df7c44dd8>"
] ]
}, },
"execution_count": 261, "execution_count": 11,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
}, },
...@@ -1056,16 +1058,16 @@ ...@@ -1056,16 +1058,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 262, "execution_count": 12,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<matplotlib.legend.Legend at 0x7f64aed55080>" "<matplotlib.legend.Legend at 0x7f7df7bebd68>"
] ]
}, },
"execution_count": 262, "execution_count": 12,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
}, },
...@@ -1115,7 +1117,7 @@ ...@@ -1115,7 +1117,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 263, "execution_count": 13,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -1237,7 +1239,7 @@ ...@@ -1237,7 +1239,7 @@
"10 Yes 0 30.0" "10 Yes 0 30.0"
] ]
}, },
"execution_count": 263, "execution_count": 13,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -1258,7 +1260,7 @@ ...@@ -1258,7 +1260,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 264, "execution_count": 14,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -1288,7 +1290,7 @@ ...@@ -1288,7 +1290,7 @@
" <th>Date:</th> <td>Fri, 31 Jul 2020</td> <th> Pseudo R-squ.: </th> <td>0.2492</td> \n", " <th>Date:</th> <td>Fri, 31 Jul 2020</td> <th> Pseudo R-squ.: </th> <td>0.2492</td> \n",
"</tr>\n", "</tr>\n",
"<tr>\n", "<tr>\n",
" <th>Time:</th> <td>15:23:47</td> <th> Log-Likelihood: </th> <td> -240.21</td> \n", " <th>Time:</th> <td>15:58:40</td> <th> Log-Likelihood: </th> <td> -240.21</td> \n",
"</tr>\n", "</tr>\n",
"<tr>\n", "<tr>\n",
" <th>converged:</th> <td>True</td> <th> LL-Null: </th> <td> -319.94</td> \n", " <th>converged:</th> <td>True</td> <th> LL-Null: </th> <td> -319.94</td> \n",
...@@ -1318,7 +1320,7 @@ ...@@ -1318,7 +1320,7 @@
"Model: Logit Df Residuals: 580\n", "Model: Logit Df Residuals: 580\n",
"Method: MLE Df Model: 1\n", "Method: MLE Df Model: 1\n",
"Date: Fri, 31 Jul 2020 Pseudo R-squ.: 0.2492\n", "Date: Fri, 31 Jul 2020 Pseudo R-squ.: 0.2492\n",
"Time: 15:23:47 Log-Likelihood: -240.21\n", "Time: 15:58:40 Log-Likelihood: -240.21\n",
"converged: True LL-Null: -319.94\n", "converged: True LL-Null: -319.94\n",
" LLR p-value: 1.477e-36\n", " LLR p-value: 1.477e-36\n",
"==============================================================================\n", "==============================================================================\n",
...@@ -1330,7 +1332,7 @@ ...@@ -1330,7 +1332,7 @@
"\"\"\"" "\"\"\""
] ]
}, },
"execution_count": 264, "execution_count": 14,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -1353,7 +1355,7 @@ ...@@ -1353,7 +1355,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 265, "execution_count": 15,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -1383,7 +1385,7 @@ ...@@ -1383,7 +1385,7 @@
" <th>Date:</th> <td>Fri, 31 Jul 2020</td> <th> Pseudo R-squ.: </th> <td>0.4304</td> \n", " <th>Date:</th> <td>Fri, 31 Jul 2020</td> <th> Pseudo R-squ.: </th> <td>0.4304</td> \n",
"</tr>\n", "</tr>\n",
"<tr>\n", "<tr>\n",
" <th>Time:</th> <td>15:23:49</td> <th> Log-Likelihood: </th> <td> -259.54</td> \n", " <th>Time:</th> <td>15:58:40</td> <th> Log-Likelihood: </th> <td> -259.54</td> \n",
"</tr>\n", "</tr>\n",
"<tr>\n", "<tr>\n",
" <th>converged:</th> <td>True</td> <th> LL-Null: </th> <td> -455.62</td> \n", " <th>converged:</th> <td>True</td> <th> LL-Null: </th> <td> -455.62</td> \n",
...@@ -1413,7 +1415,7 @@ ...@@ -1413,7 +1415,7 @@
"Model: Logit Df Residuals: 730\n", "Model: Logit Df Residuals: 730\n",
"Method: MLE Df Model: 1\n", "Method: MLE Df Model: 1\n",
"Date: Fri, 31 Jul 2020 Pseudo R-squ.: 0.4304\n", "Date: Fri, 31 Jul 2020 Pseudo R-squ.: 0.4304\n",
"Time: 15:23:49 Log-Likelihood: -259.54\n", "Time: 15:58:40 Log-Likelihood: -259.54\n",
"converged: True LL-Null: -455.62\n", "converged: True LL-Null: -455.62\n",
" LLR p-value: 2.808e-87\n", " LLR p-value: 2.808e-87\n",
"==============================================================================\n", "==============================================================================\n",
...@@ -1425,7 +1427,7 @@ ...@@ -1425,7 +1427,7 @@
"\"\"\"" "\"\"\""
] ]
}, },
"execution_count": 265, "execution_count": 15,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -1451,22 +1453,22 @@ ...@@ -1451,22 +1453,22 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 268, "execution_count": 16,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x7f64aebf6fd0>" "<seaborn.axisgrid.FacetGrid at 0x7f7df7b44e80>"
] ]
}, },
"execution_count": 268, "execution_count": 16,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
}, },
{ {
"data": { "data": {
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6OQMOX70rzZ0vxFi3pzeQLBof4KKjohw/OYjqsxawa4Zww3USSPYhAUUIcehJxyDRjNYuXWmbzpRFWRMSc/xtm6hbeWNPni0nVEfHMZ8mOe1d/ReJBza1ZLn1+U6e39XbtHXMxCCXHhNl0YRgv2O1EcQJ16H9Y2s4cLkkoAghDh1aeyO40jEytte8VW6KFAAci+jLvyG6/nco7aBRJGa+n46jLkfvM+Kqqcvm1lWd/GNLb46vheMDXHZslKMnhvoXS/lwQrXoYPSAnt5oJwFFCHFocCzo2o22M3SmbLrS2dLn9OFvf526FdcT6NgCgBU9nLaTriPbMK/fcUnL5Q9ru7hrXVfPZMQZtT6uOq6aE6eE+jVtaRRusAY3VDNgYqMYSAKKEOLgyyYgvoesZdEaH1ynO9qlctPd1Lx4K8q10Mqga84FdC68BMzeJiutNY9tSXHzcx20Jr3rN0QMLj+2mvccEcE0+jeFub4wTrgBzACiPBJQhBAHV6oDEi10pS06BtlXYqTbqVtxA+HdzwFgVU6m7ZSvkW2Y2++4re0WP3qmo2cIcMCECxdU8dGFVT2TEbtpZeKEG8bsXJIDIQFFCHHwJFpwku20JjJkrPISOHYL7F1L/fL/6pmgGJ/xL3Qs/vd+HeYZW/PbNTF+t6YLJxen3n54iGtOqGFC1cCPP9df6dVKxuh6JgdKAooQ4q2nNcT3kEl00hrP4ujBNHFpqjb+keqXbkNpB9cXoe2Ez5Oadka/w17aneH7T7ezvdMbajy5yuTak2o4cerAob5eraQRHag4oKc11klAEUK8tbSGrt3EYp10pgbX8a7sFHXPfJfI9n8CkK15G61Lv4UdndpzTMpyuWVVJ/duSABgKvjowiouPipK0DcwWaPrr8AJNw55rcQ0FDWRsdX/IgFFCPHWcV3czjdpj8VIDmaSImDGm2hY9pWeuSWJGWfRftxn0b7ejve1ezJ8Z1k7O2Petec0+PnC0lqOqBv4wa5RXl/JEA8FVkpRHfZTE/ZjGJJtWAghhp7rYnXsoLUjNri5JUBg7zoaln0FM9OBViYdx15NfNaHeiYpWo7mFy/G+P2aLjTgN+DSY6JcsKCqX6qUbtoIYleMG/IRXJVBH3UVAXzm2BxiLAFFCDH8XId0205aOzoHldARIPzGP6lfcQPKzeIEorQu/SaZCcf27N/eaXH9E2280uIljpxZ7+erb69jRp0/f1ECUa/jXQ1d7SHoN6mvCBDyj+3OfAkoQojh5TokWrbT1tnFYIYEd3e+17z4cwCsqqk0n3YjTtXknkMefi3BD1Z0kLa9paw+urCKTx4TxW/mqZVg4EQaBsyYPxCmoaitCBAN5Q9eY40EFCHE8HFdOvdsIxaPD+487VKz+maqNt0NQKZxIS3vuKEnzXzadvl/Kzp48LUkAI0Rk6++o5ZjJoXyX84IYFeMH9ImrqqQn7qKwIAJkWOZBBQhxPDQmrambSQSgwwmrk3dyu9RsfURAJKHnUbryV/umfW+vcPiq4+1sjW3/O4ph4X40tJaqkP5m5tcX8RLUz9EqVP8pkFjVXDMN2/lIwFFCDHktOvSuvsNUsmuwZ3oZGhY/l+Edz4NQNesD9Kx+DM9wWDZthQ3LGsjaWlMBVcdV8358yv75d/qd7lgLW647kCeSg+lFLURP9Vhf8H7jXUSUIQQQ8p1Nc1NO8gmY4M6T9lpGp78MqGmVQB0zr+Y2MJLQSkcV/PLF2P8+iUvQDVEDK4/vZ7544N5r6VROJFxQ5Y+JeQ3aagMEvCNzdFb5ZKAIoQYMq6r2bvnTaxEx6DOU3aKhie+RGjPCwC0H/NvxOecD0Ay6/LNJ9pYsSMNeIteffP0euoj+ZuctDJxKsYPyeJXhvI63avD0uleDgkoQogh4biapr17cOOtgzrPCybXEdrzIgDti68lfuSHANjdZXPdoy1saff6Sz40t4JrTqjJO7cEujvfJ4B54AEgHPBqJf4xOqdkf0hAEUIcMMfV7G5uRXftGdR5ys70CyZtx/0niVnvB2Ddngxf+kcrnWkXU8FnT67hnNmFm7BcM4RTMeGAU6hIrWT/SUARQhwQ19U0tXXixnYzqK5qx6L+qa/1BpPj/5PETC+Y/HNrkm8/2UbWgeqgwfVn1HP0xPz9JZBbu6RiwgGP5Ar5TRqrpFayvySgCCH2m9aaPZ0JnM5dKAaRTsW1qV9xPeFdKwFoP/YaEjPfj9aaP70c56fPdQIwJerjf97TwORo4Y8q11+JExl3QDPfu0dwjbVkjkNNAooQYr/t7cqQ7diF4Vrln6Q1tc/+D5HtTwDQsehy4rPPxdWam5/t5C/rvXkr88cF+O676gvOL4FcGpVI44E8BZlXMoQkoAgh9ktLPEOqYw+mnRrUedVrbqdyy4MAxOZ9jK75F2G7mu8sa+f/Xvdmvp86LcxX31GXN918NydYgxuu3/8ngJfMsaEyOOayAg8XCShCiEHrSGbp6uzAlxnc8ODKTfcQXf87AOJHvI/ORZeTtl2+9lgbK3d6w4I/OKeCz5xYUzSliROqxQ3t/4RFpRT1lZKDa6hJQBFCDEo8Y9MWS+BLNQ/qvPAb/6Rm1U8ASE05hfbj/oOEpfnC/7Wwdo+30NalR0f5xNFVRWeiO6E63FDtfpffbxqMiwYJ+qSJa6hJQBFClC1tOTTH0pjJvShd/hrwgeaXvRT0aDIN82k95RvELIPPPdzMxlza+f84qYYPzS0+s90JN/QkiNwf0sQ1vCSgCCHKYjkue2JpVKoNw0mXfZ4Z303Dk19GuVmsqim0nPod2iw/n324mc1tFoaC65bWctbM4uu5H0gwUUpRFwlQHZEmruE0rIOtlVJnKqU2KaU2K6Wuy7O/Win1v0qpNUqp9UqpS4azPEKI/eO6mqbONG4miZlpL/s8lY3T+MR1mJkOnECUllO/R6tbyWce9IKJqeAbp9YNazDxGQYTq0MSTN4CwxZQlFIm8FPgLGAucKFSau4+h/0bsEFrvQg4FfiBUkoGggtxiNnTlcaybczk3vJPch3ql38Tf+dWtOGj9e3fptk/iWsfamZrh43PgG+fUc/pMyJFL+OE6vc7mIT8JpNqQjIk+C0ynDWU44HNWustWuss8Efg/fsco4Eq5fXAVQJtgD2MZRJCDFJLPEMq62AmW1C6/Ldn9ZrbCO9+FoC2Ez5PU3QB1z7UzJb23mCy5PDiCRy9Dvia/Sp3ddjPxOrQmF3f/WAYzj6UycCOPo93Aifsc8zNwH3ALqAKOF9rPYjptkKI4RRLW8RSFiqbwLDKX9sksu0fRDfcBUDX7PNomvwePvtgbzC5/vR6TjmsRDAJ1u7XaC6lFA2VAapkSPBbbjhDd75hFPsuKP0e4CVgEnAUcLNSKjrgQkpdoZRapZRa1dw8uKGKQoj9k7YcWuNZcB3MQQwR9re9Su3K73nXmLCYXfOu4HOP9PaZfOv0Mmomger9WhjLNBQTq0MSTA6S4QwoO4GpfR5PwauJ9HUJcK/2bAa2ArP3vZDW+jat9WKt9eLGxgNLsyCEKM3OjejSWmOmmsseImxkYjQs+yqGk8GunMSbJ36dLz7WwcZmbzTX106tY2mJYOL6q3AjDYMus980mFQTlv6Sg2g4A8rzwEyl1PRcR/sFeM1bfW0HzgBQSo0HjgS2DGOZhBAlaK3Z05XBcTUq24VhJco80aVuxQ34Ek24Zoimpd/mK8ttXmryJi1+YUktZ5TogHd9kf3KzRXym0yuCUuW4INs2PpQtNa2Uupq4BHABH6htV6vlLoqt/8W4HrgV0qpdXhNZF/UWrcMV5mEEKW1JrJkLAdcGzNZ/tuxav3vCe96BoC24z/Lt9bWsXKnl5vr2pNqeO+s4kODvfVMxg86a3Bl0EdjVVDWeT8EDOvERq31g8CD+2y7pc/vu4B3D2cZhBDli2dsYilv5rqZbC47JX2waTXVa+8EoOuIc/je3hP5v9e9rMGXHhPlwyVmwGsjsF/rmUTDfhoqC6+TIt5aUj8UQgCQtV1aujIAXlOXnSzrPCPVRv3T16O0S7buSH4e+ERPCvoPzangE0dVFT1fK9NbtneQKy3WVQQkmBxiJKAIIdBas7crjau119SVKnNdeO1S98wNmOk2XH8l9069jp+94KVlOX16mM+cVFO0KUqjvJrJINeAb6gKymJYhyDJ5SWEoC2RJWt7zVtmqqXsUV1VG/5IePfzAKyadS1ffd6rMRwzMchX3lGHUaJfw4mMQ/tCZZdTKUVjVZDKoHx0HYrkryLEGJfM2nTm+k1UNl72qK5Aywaq19wOwK6p7+WStfOwXc30Gh/fPqOegFkimITq0IHifSt9KaUYHw0SCcjH1qFK/jJCjGG249Kc6zdBu5ip8kZ1KStJ/dPfQmmHVNXhnP/m+SQsTUPE4PvvaaAqWLw13fVXDWoWvKEUE6olJ9ehTvpQhBjDWuJZHNdLYGGk28tu6qpZ/RN88V24hp/P2tewI+kj7Ffc+O4GxlcW/57qmqFBzTWRYDJySEARYozqTFkks7lkj04WI9NZ1nnhHU9R+bo3G+CPFRfxUPskDAX/dWodM+uLd5Rrw58bHlzenBHTkGAykkiTlxBjUNZ2aUtkex6bqRbUgFR7AxmpVmqfvRGA1yOL+Erz6QBcfXw1J5dI9qhR2BXjyx4e3B1MZKnekUNqKEKMMd1DhLX2AojKJjDsVDknUrfye5iZTjJmJf/adhkag/fPruAj80p3rjuRcWCWN2/EUIrxUQkmI40EFCHGmPak1TNEGK0x0+XNOanY8iDhXSsB+GLmUpqo55iJQa4tMdcEwAnWlD2iS/pMRi4JKEKMIWnLoSPZ29RlZDpRrlXyPDOxh5rVNwPwqDqJv9knMqnK5Fun1+EzigcT1wzhhspLRS/BZGSTgCLEGOG6uneIMIB2MTIdpU/Umtpnv49hJehQ1XwhdTFhv+I772ygOlT8g18rs+yEj0qCyYgnnfJCjBEtiQyW05vs0Uh3lDVMuOL1Bwjvfg7wmrraiXLD2+uYUVc6XYoTGQ9G6Y8ZpRQTohJMRjqpoQgxBiQyNvF0n/XgXbus2omZ3NvT1PV352QecY/jE0dX8fZpxUd0gbeEr/aXPq47mIQDEkxGOgkoQoxyrqu9pXz7MNPtpYcJa03tcz/EsJO06CjfsC7mxCkhLjl6wCrdA+9phspawrc7nYoEk9FBAooQo1xbMovt9lnXxMmisl0lzwu/8TjhN1cA8A3rE1RU1fD1U0snfOzpNylBKcW4KsnNNZrIX1KIUSxtOT0LZnUz020laydGppPaVT8G4FHnGB4zTuSWd5bO0QW5+SZl9Js0VgWpkKzBo4rUUIQYpbTWtMQz/bYpO1VWNuGa1TdjZjro0mG+Zl3Cf55cy9vK6YQP1qD9xdeNB289E0lBP/pIQBFilOpM9ZnAmGOk2kqeF2xaTcXWRwD4rn0hxx95GGfOLL4ePJQ/36S+Ikg0NLgFtcTIIF8RhBiFLMelPdm/qUtl4xhOuviJToboyh8AsMqdxfPV7+FnJ9aUvJ/G8DIIl+hfqYkEqI5IMBmtpIYixCjUEs/05OoCcilWStdOql7+PaHETixtcgOf5PozGgn6Sk9KdML1YBbPNFwV8lNXIcv2jmYSUIQYZbrSFqls/wmL5aRY8cW2U7n+dwDc6fwLH1qyiEnR0o0Yri+CDhYfSlwR9NFYVV5iSDFySUARYhRxXN0vLT1QXooVrfEv/x982manbmDb2z7GqdNLd65rZXqjuooI+U3GSTAZEySgCDGKtMYzPSswdisrxcrmf9DQ/hIAPw9dxmUnTijrfk64sej6Jn7TYHw0VDIbsRgdJKAIMUrEMzbxjN1/YzkpVrIJKlb9FIBH3eP4l3e9q6x+EzcQRQcKj/7qXiDLLJGNWIweElCEGAVsx6V1nzknAGaq9CTGvU/eQZ3bRkoHaD763zisuvQoLG34vY74AlRugSy/KR8xY4n8tYUYBZrzNHXhZDGs4ilWmt54jYV7/gbAw9GPsGTe9LLu5w0RLvzxMa4qKJmDxyAJKEKMcLE8o7qAksOEM5aLb8UP8SuHHUxgzrs+UVZfhxOsRfsKZxGur5CUKmOVBBQhRjDH1bTvO6oLwMk7uhECAAAgAElEQVSUTLHyzJMPcrS7HoCmo66hIhwqeT9tBHFDtQX3V4Z8MnFxDJOAIsQI1pbIDmzqwus7KeaF7R2c3nQnAJsqT2DCvKUl76VR2BWFZ8OH/CaNlTI8eCyTgCLECJW2HLrSAycrKjuNYScLnteZdtjz1K+ZrFqx8BE59TNl3c8N1YCZP2D4DBkeLCSgCDEi5csk3M0o0neiteYXy17l4/o+APYecS5UTyl9PyOIG8zf1GUoxfjqoAwPFhJQhBiJYil7QCZhAGWlMOxUwfMe2Zzk9KZfEFIWCX89+piLS96rVFNXY1WQoE9GdAkJKEKMOLbj0p7M0xFP8drJnrjNsmdWcrb5LACpxVeVtXaJGyzc1FUbCciILtFDAooQI0xbMourB3bEF0tP72rNd55s5fPqNwAkaueQmv7ukvfSRqDgqK6KoI9ayR4s+pCAIsQIkrYc4ml74I4S6env3RBn2t7HWGhsBSB+3DUl1y4BcCINeY8L+AwZ0SUGkLqqECNE0Y74bKxgevrtHRa/en4Pj/j/BEDi8DPINs4veT83EM07gdE0vLQqhnTCi31IDUWIEaJQRzzaxUi35z3HdjU3LGvnUnU/E1Q7rhGg86grS95LK1/BXF3jqiRHl8hPXhVCjABFO+IznQXT0/9pXRdtzbu5wrwfgPic83EqS6emd8L1eXN11VUECAdkRJfITwKKECNAWyJ/R7y3eFZn3nO2tFnc+UKMz/n/QlhlcUJ1xOb9a8l7ub4wOlA5YHtF0EdNRDrhRWESUIQ4xKWyzsB1TnKMTP7Fs2xX899PtTFTb+ND5lMAdC68tOQwYY3CCTcM2O43pRNelCad8kIcwop1xOM6GOn8tZM/rO1iU0uW3/l/j4HGqp5G4m3/UvJ+XnqV/rUQQ0knvCiP1FCEOIR1piwsJ09HPLm+Ewbu29Jm8csXY5xqrGGJ6WUT7jj6U2AU//6oDX/e9CoNVUECPvmoEKXJq0SIQ5TtuHQk8w8FxnXy9p3YruY7T7Xhui5fD94FQHr8MaQnnVjyfk544JyTaNhPpcyEF2WSgCLEIapgRzyFayd/XNfFKy0W55pPMkPvQKPoOObTJScxuv6KAf0rQb9JvcyEF4MgAUWIQ1DaKtwRX6h2sq3D4hcvxAiR4cuhewBITnsXVt2sovfK1xFvGorxVUFJRy8GZVgDilLqTKXUJqXUZqXUdQWOOVUp9ZJSar1S6snhLI8QI0HRjnjAyA6snTiu5ntPtWO58JnII1Q7bWjDT+eiT5a8nxuqHdC/0lgVxCeTF8UgDVvjqFLKBH4KvAvYCTyvlLpPa72hzzE1wM+AM7XW25VS44arPEKMFLF0gRnxkJsVP7B2cu+GOC/vzVJDF5cpb62T+KwP4lROLHovbQS8bMJ91EQCRALSbyIGbzi/ghwPbNZab9FaZ4E/Au/f55iPAvdqrbcDaK33DmN5hDjkua6mo8CMeMjfd7IrZnPb6hgAP2x8AL+TxPVXEpt/Ucn77dsRH/Kb1Em/idhPwxlQJgM7+jzemdvW1yygVin1hFJqtVLq4/kupJS6Qim1Sim1qrm5eZiKK8TBF0tbedeIB/LOitdac+PT7aRtzYJwC6cmHvKuM+9fcYPVRe/l+ivR/t7kj6ahGFclkxfF/hvOgJKvN2/fd4oPOBZ4L/Ae4GtKqQE9iFrr27TWi7XWixsbG4e+pEIcAhxXFx4mTP6cXQ++lmT1Lq+/5SeNf8dwLexwI/EjP1L0XhpjQPJH6TcRB2o4G0p3AlP7PJ4C7MpzTIvWOgEklFLLgEXAq8NYLiEOSZ0pq+Aw4Xy1k5akw83PdgDw8al7mbb3cQBiCy9B+4rXNNxQTb+OeOk3EUNhOL+OPA/MVEpNV0oFgAuA+/Y55u/AUqWUTykVAU4ANg5jmYQ4JNmOS2eqWO1kYM6uHz3TQTyriQYNPmf+CYXGih5GYsaZRe+1b0e89JuIoTJsX0m01rZS6mrgEcAEfqG1Xq+Uuiq3/xat9Ual1MPAWsAF7tBavzxcZRLiUNWetNCFaid5cnYt25biyW0pAL49dwfRjc8A0Lno8pIpVrzU9F6LtPSbiKE0rHVcrfWDwIP7bLtln8ffB74/nOUQ4lCWtV260iX6TvqM7OrKuPzwGW9BreMmBXh3i7dOfKZ+Dqmpby96L9cX6TcjflxVSPpNxJCRV5IQB1mhhbOAvLPib3m+k9akS9inuOGITYSa1wF4KzEWmdm+74z42ogsliWGlgQUIQ6itOWQKJRihVzfSZ/ayZqmDPdtSgDwyWMqmfbqLwBITTyOzIRjit7LDdaA6QcgHDCplX4TMcQkoAhxELUmitVO7H61k6yj+f5yr6lrdoOfiyueJdDxOgCdi64oeh+tfN7ILsBnGIyrCh1gyYUYSAKKEAdJImOTsfKvBQ/dfSe9HfW/XRPjjU4bU8F1J1dRs+6XACQPOxWr/sii93JCtT1rxI+LBjFlsSwxDCSgCHGQtA2idrK13eJ3a7oAuGBBFQvbH8UffxOtDDoXFk8AqY0gOhgFvH6TkF/6TcTwkIAixEEQSxdeiRHASHf01E5crfn+0+3YLkyuMrl0QYDql38FQGLGmdjVhxe9lxOuA6TfRAw/CShCvMW01nQkCg8TxrUxsrGeh/+7KcG6PV5t5nNLaqnf8jfMVCva8BNbcEnRe7m+MNofwTQUjZUy30QMLwkoQrzFYikb2y1cOzHT7T21k5akwy3Pe01fZx4R4bhGh6r1vwcgPvP9OBXji96rO1+XzDcRb4VBv8KUUrVKqYXDURghRjvX1XSkivSdONl+tZObVnrpVaqDBv92QjVVG/+EmY3h+sIl09O7/iowg9TIfBPxFikroOTSy0eVUnXAGuCXSqkfDm/RhBh9OlJF0tMDZrqt5/cV21M8vtVLr3L1CdXU0UXVxj8B0HXkR7yVFgvwJjHWEfSb1Eb8Q1R6IYort4ZSrbWOAR8Cfqm1PhZ45/AVS4jRx3E1sSIJIJWdwrC8SYtJy+WHK7xMwsdMDPKeIyJUbfg9hp3CDVTSNfeCovdygzUYpp9xsi68eAuVm8vLp5SaCJwHfGUYyyPEqNWRzBZOTw8Yqd7ayS9fiLEn4RAw4XOn1OBLtVD56l8BiM35KDpQVfA6Wpm4oRrGVwXxS7/JIWP16tXjfD7fHcB8Rn7/tQu8bNv2Zccee2zPSrvlBpRv4WUNXq61fl4pNQN4bRgKKcSoZDsusXThFCsqm8Bw0gC82pLlL+vjAFx8VJSp1X6iz/0Gw8nihGqJz/5w0Xu5oVqikSAVQVnf5FDi8/numDBhwpzGxsZ2wzAKf7MYAVzXVc3NzXObmpruAM7p3l7WK05r/RfgL30ebwGKv6qFED06UkXS0+ON7AKvWez7T7fjaJhW4+PCBVWYXbuo2Hw/ALF5F6F94YLX0YYfX6SGeplvciiaPxqCCYBhGLqxsbGzqalpft/tZQUUpdQvGbh8L1rrS4eofEKMWpbj0lW0dhJHud4yvn/dGOeVFq+f5fOn1OI3FdUv/wqlHezIOOIzzyl4HQAdrmdcNCz9JocmYzQEk26559Kv6a7cdrz7gQdyP48BUSA+pKUTYpTqKLZ4Fr21k70Jm9tWe0OG33dkBQsnBPF1biOy9f8AiC34BJiFax6uGaK+vp6Ab6Q3z49dX/ziFyccccQR82bNmjV39uzZcx9//PGKA7ne/fffX3XaaacdMVTlK6XcJq97+j5WSt0F/GNYSiTEKFJq8SyV7UK53ryUHz/TQcrS1IYMPnVcNQDVa3+J0i5W5eSSS/tGasZRKf0mI9Y//vGPikceeaRm3bp1G8LhsN69e7cvk8kctKqmZVn4/YMbcr6/X2VmAoft57lCjBlFF88CzLQ3NPipN1Ise8PrlP/3E2uoChr4214jsv2fAMQWXlJ0aV8zVElDbU3B/eLQ9+abb/rr6urscDisASZOnGhPmzbNmjx58oKrr7568lFHHTV7/vz5c5YvXx5ZsmTJzKlTp86/8cYbGwFc1+XKK6+cMnPmzHmzZs2ae/vttw+YpPTkk09G5syZM3fDhg2BWCxmnHvuudPmz58/Z86cOXN/97vf1QD85Cc/qT/rrLNmnH766UcsXbp01mCfQ7l9KF3070NpAr442JsJMZaUWjyru3aSzLr86BkvsBw3OcgZM7xO9+q1dwJgVU8nefgZha+DonHcJOk3GeE+8IEPxL7zne9MmjZt2vwlS5bELrzwwrb3vve9cYCpU6dmX3rppVc++clPTr300kunPfvss6+kUilj/vz5877whS80/+Y3v6lZt25deOPGjet3797tO/744+e8+93v7umWePTRRyuuvfbaw+67777NM2fOzF599dWTTzvttNhf/vKXbS0tLebixYvnnHPOOTGAF154oXLt2rXrx48fX3hthQLKbfIqPOhdCJFX6dqJ13dy5wsx9ubmnPznybUopQi0rCf85goAOhd9EozCqVNq6+rxBwuP/BIjQ3V1tfvyyy9vePjhh6see+yxqosvvvhtX//613cCnHfeeR0ACxYsSCYSCaO2ttatra11g8Gg29LSYj711FNV5513XpvP52Pq1Kn2CSecEF++fHmkurra3bx5c+jTn/70tEcfffTVadOmWQBPPPFE9JFHHqn5yU9+MgEgk8mozZs3BwCWLl0a259gAuXXUB7TWp9RapsQwpPKOqSyhd+TXu3EYlNLlrs39M45mRz13pLVL90OQLbuSFJTlha8TiTop6KmeIJIMXL4fD7OPvvsrrPPPrtr4cKFqd/+9rf1AKFQSAMYhkEgEOhpLTIMA8uyVLFBH+PGjbMymYyxcuXKyLRp0zrBy3h99913b160aFGm77HLly+viEQihTOXllC0D0UpFcrl72rIJYWsy/1MAybt702FGO1aE5mi+810R8+cE1fD9NycE4Bg02pCe14AoHPRZVCgKctnGNTWjQNTOuJHgzVr1gTXrVvXs8bAiy++GJ4yZUrxam7OO97xjq677767zrZtdu3a5Xvuuecqly5dmgCIRqPOQw899No3vvGNyffff38VwGmnnRb7wQ9+MN7NZb1++umnh6SKW+qVeCVwLV7wWA10v7JjwE+HogBCjDZdaYusXfhLnjfvJMu9G+Jsys05+dwSb84JWlO95g4AMo0LSU88vtBVqKsKY0Tqhrr44iCJxWLmv//7vx8Wi8VM0zT1tGnTMr/+9a/fWLx4cXWpcy+66KKOFStWVM6ZM2eeUkp/85vf3HnYYYfZa9euBWDq1Kn2/fffv/mss86aGYlEtn33u9/ddcUVVxw2e/bsuVprNWXKlMw///nPzQf6HIpWlXoOUuoarfVNB3qzobB48WK9atWqg10MIfLSWrOzPVV0NUZfbCd7YwkuuncPKUtzzpEVfH6JNygn9OYzND7hjXfZ+86fkBl/VN5rVIcDROsnQLhwxmFxyFAAa9as2bZo0aKWg12YobRmzZqGRYsWTet+XG6n/E1KqfnAXCDUZ/tvhryEQoxgsZRdNJgoK4lyM/x4Ze+ck6tyc07Qbk/tJD1hccFgEvSbRCvCEJJhwuLQUm6n/DeAU/ECyoPAWcByQAKKEDklF88CjHQ7y7aleCo35+Sa3JwTgPD2Jwm0ezlXOxddlv98paiLBCBSX7BvRYiDpdyJjR8BzgCatNaXAIsAWaBaiD5KLZ6l7BTpVJIfr+ydc/LO3JwTXKdn3klyyhKyDXPzXqM2EsAXCEFQRvKLQ0+5ASWltXYBWykVBfYCM4avWEKMLFnbpbPI4lkARrqDO/LMOQGIbPs//LHtaBSxhZ/Me35FwE8k4INIw5CXX4ihUO54w1VKqRrgdrzRXnHguWErlRAjTFsiWzQBJE6G15o6uCc35+SSo3vnnOBYVK/9JQDJw8/Aqn3bgNN9hkFthR/8YQhEhrz8QgyFcjvlP5379Ral1MNAVGu9dviKJcTIkczaJLOFU6wA6GQ731vuzTmZUevjggW9TVYVrz+AL9GEVqaXs2sARX1lAIWCCqmdiENXWU1eSqnHun/XWm/TWq/tu02IsUprTWu8xNwzx+Lel5p4rTU35+SUWnyG19Sl7AzVL/8agMSMM7GjUwecXhPxEzBNr9/EJ12XYvBc1+XYY4898s9//nO0e9sdd9xRu3Tp0plDeZ+iNRSlVAiIkJspT+/ExigyU14IOlNW0WHCAM0te7nzBW+dk/fPrmDB+N6gUPnqvZipVrTh99Y72UfI76Mq6PdGdEXqh7TsYuwwDINbbrnljfPPP/9tZ5999gbbttX1118/+cEHHxzSpdwHO1O+WxcyU16Mcbbj0pEs3hGv7Sw/fnInaVtTFza4ss+kZ2UlqFr/ewDiM9+PU9E/J5ehFHXdS/mGayXFyhjzwNpd0duf2jphd2cqOLE6nLl86fSm9y6cFNvf6x133HHpd7/73Z1f+9rXJiQSCfO8885rnTdvXuamm26qv+2228ZZlqUWL14c//Wvf73ddV3OPffc6Rs2bAhrrdXFF1/c/NWvfnVvqXuUeoWuAP4MfCQ3ufFivLXktwF/2N8nJsRo0JbI4pbINLF8w3ZW7PDmnFx7Uu+cE4CqjX/GzMZwzRCxeR8bcG5tJICplBdIZEb8mPLA2l3R6x/YeJjfULoq6LNb4xn/9Q9sPAzYfiBB5cYbb9y1cOHCuYFAwF2zZs3G559/PvT3v/+95oUXXtjo9/u58MILD7/99tvrZs2alWlra/O9+uqrGwBaWloKp7vuo1Qfyq1AJhdM3g58B/g10Anctr9PSoiRLpV1iBdZ6wQgnkjy4+W7AThpaohTp/Xm3zPSHVRt/JN33OxzccP9c3L1DBEGb5iwTGIcU25/ausEv6F0yG+6SilCftP1G0rf/tTWCQdy3Wg06n7gAx9oO++881rD4bB+6KGHomvXrq1YsGDB3NmzZ8995plnql5//fXg3Llz01u2bAldcsklU++5555oXV1dWensS9VQTK11W+7384HbcssB36OUeulAnpgQI5XWmpZ48WzCAHcse422lEvYp/jsSTX9FsCq2vB7DDuJG6gkNueCfuf5DIOaSG7pVX8YgpVDWn5x6NvdmQpWBX39vrEEfYa7uzN1wKMyDMPAMLy6hNaaCy+8sOXHP/7xrn2PW79+/fp77rmn+qabbhp399131951111vlLx2if2mUqo76JwBPN5nnzToijGpVL4ugHXbm7lvgzcj/rJjo0yo6n27mMm9VG36q3etORei95n1XlcRwOgOPtIRPyZNrA5nMrbb7/M5Y7vGxOpw6W8yg3DWWWd1/f3vf6/bvXu3D6Cpqcl87bXXArt27fK5rsull17a/q1vfWvXunXrypr8VCoo3AU8qZRqAVLAUwBKqSPwmr2EGFNsxy25EmPWdvnBo14m8NkNfj48t38NI7ru1yg3ixOqIz77I/32VQb9BH255upgJfhDiLHn8qXTm65/YONhWI4R9BluxnYNy9Xq8qXTm4byPscff3zquuuu23XaaafNcl0Xv9+vf/azn71hmiaXX375NK01SiluuOGGneVcr2hA0VrfkJtvMhH4P907FdgArjmwpyLEyNOWLN0R/8eVW9jekcVU8IUltZhGb1OXL7aDitcfBCA2/yK0r7dfpV9TlwwTHtNyHe/bh3KUV7cf/vCH/Zq3rrrqqrarrrqqbd/jNm7cuGGw1y7ZbKW1Xpln26uDvZEQI13acoini3fEb2tN8Lvn3wTg/PmVzKwP9NtfvfZOlHawKyYQP+KcfvvqKnKz4QGCUTD9Q1d4MeK8d+Gk2FAEkLdSuckhhRjzSnXEu1rzg4c3YrswucrkkmOi/fb7214l8obXDdm58NJ+AaMqFOht6lIKZCVGMQJJQBGiDLESy/oC3PfSLtY3JQBvSd+Qr//bq3rN7QBY1dNJTntXz3a/aVAd7tNYEK4Fo6xh/0IcUiSgCFGC42raE8U74vfG0tz+1BYA/mVmhMWT+nemB/e8RHjXswB0LLqsT8BQ/Zu6ZBKjGMEkoAhRQmsiU3ThLK01P3rsNVKWS23I4N9OqNn3AKpfvAWATMN80lOW9OyqDucSP3aTlRjFCCYBRYgiyumIf/yVZlZu8QbJfOakGqLB/m+r8M6nCLZ6A2Y6jr6yJ2AEfCbRUJ+Od7+sxChGtmENKEqpM5VSm5RSm5VS1xU57jillKOU+kihY4R4q5UzI74zaXHzP705J0sOC3H69HD/A1yb6pe8LEWpSSeRHbcIAEWfxI/dKhqHpuBCFKCUOvbyyy+f0v3461//+vjPfvazQ5Y5ftgCilLKxMtIfBYwF7hQKTVgoezccd8DHhmusgixP2Ipu2RH/E+f2ExnyqIyoPot6dutYsvDPUv7dh51Rc/2mgo/fqPP2y8UlbVOxLALBAL6wQcfrO2eGT/UhrOGcjywWWu9RWudBf4IvD/PcdcA9+CtUy/EIcEqY0b8yi2t/GOj97L99PE1NFT0H5ml7DTR7qV9p72rZ2nfkN9HZaBPU5dSEJZhwmIf6/8a5fYzZvGD2Qu4/YxZrP9rtPRJxZmmqT/+8Y83//d///f4ffe9+uqrgZNOOmnWrFmz5p500kmzXnvttUC+axQznAFlMrCjz+OduW09lFKTgQ8CtxS7kFLqCqXUKqXUqubm5iEvqBD7ao0XnxEfz9j8v0e9tYmOmRjk7FkDUx1VbrobX6oZbfjpXPRJYJ81TrqFamStE9Hf+r9GefjLh5Fo9hOM2iSa/Tz85cOGIqh8/vOf33vvvffWtba29vsGdNVVVx320Y9+tPXVV1/dcP7557d+6lOfGrh8aAnDGVDyDVXZ9x36I+CLWuuiqZG11rdprRdrrRc3Nko7sxhe8UzpNeJvW7aF5niGoKn4wpKBTV1GuoNo9+JZsz6IUzkR8GbDm32PVQrC+4wKE2LFzRMw/Rp/2EUp8IddTL9mxc0HlL4eoK6uzj333HNbv/vd747ru/3FF1+suOKKK9oAPvWpT7WtXr160GmuhzOg7AT6RrgpwL4pkhcDf1RKbQM+AvxMKfWBYSyTEEW5rqatxBrxL7zRzv1rvXVOrlgcZXJ0YO0iuv63GFYC119JbP5FgJf4Mezf51iZxCjyib0ZxBfq34HnC7nE3hySjrYvfelLe/7whz80JBKJIY0BwxlQngdmKqWmK6UCwAXAfX0P0FpP11pP01pPA+4GPq21/tswlkmIotqSWWy3cEd8Kuvwg0e9VHbzxwUGZBIGMOO7qHw1l55+3sdwg9UEfGZv4sduhimTGEV+0ckZ7HT/z2c7bRCdPCTp68ePH++8733va//DH/7Q0L3t6KOPTtxxxx21ALfeemvd4sWL44O97rAFFK21DVyNN3prI/BnrfV6pdRVSqmrhuu+QuyvtOUQSxVfI/6O5VvZ3ZnGbyquW9o/k3C36pfuQLk2dqSR+JEfxlCK+r6z4btF6mQSo8jv5KubcCyFlTLQGqyUgWMpTr56yNLXf+UrX2nq6OjoqTL//Oc/3/7b3/62YdasWXPvuuuu+p/97Gc7ip2fz7D2BGqtHwQe3Gdb3g54rfUnhrMsQhSjtaa5q/iXvzU7Ovjri14m4UuOjnJ4zcBswIGWDVS88Q8AOhddhvYFqa8I4DP2+e7mC0CoemgKL0afeR+MAdtZcfMEYm8GiU7OcPLVTbnt+y2ZTL7Y/fvUqVPtVCrV8/jII4/Mrly58oAyycvQEiGAjqRVdBXGlOVw4yObAJgzLsSFC/L0V2pN9Qs/AyBbO5PktHcTDQUG9puAt068EMXM+2DsQAPIW01Sr4gxL2u7dJRo6rp92Zaepq4vLanGl6epK7xzOaHmtQB0HPNpgsEA1eE8a5oEKiBQ1oqqQowoElDEmNcSz6CLzDl5cXs7f3vJG6B46TG1TK/NEyRcm+oXfw5AatKJ2BOPo74iz4AcpaBCaididJKAIsa0zqRF2io8DSqZtfn+I16z8uzxES6YH857XOVrf8fftROtDDqO/hT1lfvMN+kWqpaVGMcu13XdUTMKI/dc+rUTS0ARY5bluLSVSK/y8ye20BTzmrq+vKQmb1OXynT1pFhJvO29hCcc2bv6Yl+GIcOEx7aXm5ubq0dDUHFdVzU3N1cDL/fdLp3yYsxq7ire1PXs1lYeWOdNYLz8hHFMr8n//av65V9jZmO4vgjJoy+nMVzgbRWqkUmMY5ht25c1NTXd0dTUNJ+R/2XeBV62bfuyvhsloIgxqTNVvKkrlrL4n1xT18LJVZw/O/9bxRfbQeWme7xz5l9ETcPEgfNNQCYxCo499ti9wDkHuxzDaaRHSSEGzXLckkv6/uTxzbQmsoT9Jl9eWodRYAJizYs/Q2kHu2ICvmM+SsAs8JaSlRjFGCABRYw5zV2ZopmEH39lL4+/kktLf8pEJlfkr8kEm1YT3vk0AKnjrqYyUiCXni/grXcixCgnAUWMKR3JbNGmruauDD/6h5eW/sTptZwzo0CtwrWpWX0TANlxC6mc957CN43U73d5hRhJJKCIMSNjO7QnC09gdLXmew+/QjxjUx3284Wl9Rgqf02m8rX7CHRsQaMw3v6fKFXgreQPexMZhRgDJKCIMaE7V1exUV1/e/FNXtjeAcDnTjuMRn8673FGppPo2jsBcGafg2/C/MI3lkmMYgyRgCLGhLZEtuj68FtbEty6bAsAZ80bzzsmFW4Wq15zJ2a2Cx2oxHfy1YVvGqySdeLFmCIBRYx6acuhs0iurqzt8u0HNmI5monVIa45oRql86/Y6G/fTMVmb1kfdfyVXgr6fJSSvhMx5khAEaOa65ZOS3/bsi1sbUlgKPjqe6ZTpZL5D9Samud/hNIuunY6LDi38EXDtbJOvBhzJKCIUa0lkSmalv7Zra3cm1vj5OKTDmdBNFXw2Mi2R3uyCaulnyuck8v0ySRGMSZJQBGjVjxjE0/nbyA39JUAACAASURBVLoCr1/lxoe9NU4WTI5y0YJIwaYulY1Tk1vrhLedAYedWPjGkQaZxCjGJAkoYlSyHJeWIk1drtZ858GNtCctKoM+vvzu6fjtroLHV6+9EzPd5g0DXvqfhW/sD0OwwARHIUY5CShi1NFasyeWLjob/o/P7WB19xDhd81ksq9wMPG3b6by1b96D467HCrH5z9QKaho3O9yCzHSSUARo05riSHC63d18ountwLwvkUTOfUwH8otkNtLu9Q+90OUdqF2Oiz6aOEbh6q9NCtCjFESUMSoksjYxIoMEY6lLL79wEZcDdMbKvi3JVMwM+0Fj694/QGCLbklH97xhcId8YYJ4QJDiIUYIySgiFHDctyiQ4S11nzv4U3siWUI+gy+9t7ZRLKtBY83Um3UvHiL9+DI98KU4wvfPFLvLaAlxBgm7wAxKmit2Vsii/CfV+3kmS1eALn2nTOZUZEt3NQF1L/0U4xsFwSrYcl/FL65PyTZhIVAAooYJVoTWTJFsgi//GYn/7+9O4+Ss67zPf7+Pk8tXVW9pzudPZAQshD2yCoQ1gFEcFCP4nJ1jjOIemfwjrKoiLI4ouPMEVHGcRy5MqPDRVFAFAFZBEGUgGxJCAkhK0l6X2qvep7f/eNXvSTpqq6E7lR1+vs6p053rf2tTnd/8tv/4ym7tcr5R8zg/MWNJbu6ojufp2bjI/bKqVcWX1eiA/FKDdFAUZNefIxxk95klpseGB43+YezFuImO4o+XvJpmp77F3tl1rGwtMQhezUNul+XUgUaKGpSy+S9kuMmnm+4+ddr6YhnqAk6fOWiZcTyPSW7ulpW/1+c/m3gBGHlF4svUnQcHYhXagQNFDVpeb5hV1/pLenvePrNoS3pr/6rxcyv83Gy/UUfH+l5nfDqu+yVd3wCmhcULyDaogPxSo2gvw1qUhpcvJj3i683eXpDJz/981YA3nf8bFYe1lS6q8v3aP7TN+yak+aFcNzHixcQCOtAvFJ70EBRk1JnvPRRvlu7k9zy4GuA3afr8nceiptsRygeQK3r78LpWg/iwNnXF19zAlA7fb9rV+pgpYGiJp2+VI6BdPFB+EQmz5fvW00i69EcC3H9RcsI5XpxvNFPYASoi28m/II9hZGjL4O2Eqcw6kC8UqPSQFGTSjKbpys+xqaPD77Glu4kAUe44eJltITyuJneos8J4NPw9M3g56FhLpz4qeIFOE7xQ7WUmuI0UNSkkc37tPeXPizrv/64mWfesIsXrzx7EUe0RXGT7SWeIbSu+wnSuQ4QOOerdsfgYmKtdpsVpdReNFDUpJD3fHb2ld5B+MnXO/jxHzcDcPHRs3jXkTMIJHaVHDdpTm4k8MKP7JVjPgwzjyleRDBiz4lXSo1KA0VVPd837BxjRtfruwb4+tAgfAOfOXMhTqoL8Yu3aGKuIfbkTeB70DgfTirR1SWiA/FKjUEDRVU1Ywy7BtIlt6Pvime47t5XyeR9ZjbUcOPFRxDykrjZvqLPCQVcml7+D+jaYGd1nXMDBGqKFxJpKj3rSymlgaKqW8dAhlS2+PTgTM7jy/etpjOeJRpyufk9y2kIU3K9iSsOLT0vIi/+t71hxSdgxpHFiwiE9Ix4pcqggaKqVsdAhnim+JnwgzO6Xts5gADXvWsph06LllxvIggtoTTuozfYG9qOsIFSSmy6nhGvVBk0UFRV6k5kS641AfjBkxt5cn0nAJ8+cyEnLZiGm+ossd5EaImFCD31TUi02y6uc28u3ZUVabTb0yulxqSBoqpObzJLb7L45o0A9734Fnev2gbAXx87m/ceNwcn01dyn67mWIiaDQ/A+oftDad9DhrnFf8ibsAenKWUKosGiqoqfakc3YnSYfLMG53c9th6AE5eMI1Pr1yI5FI4qeKnLzZEQsTiW+DJb9obFp4Ny/66dDHa1aXUPtFAUVWjP50ruQoe7EFZNxbONjm8rZbrLlqKa/K4yV0Io69RiYYC1Ac8+O21kM9A3Uw487rSYVFTD6Ho23k7Sk05GiiqKsQzeTpLnGsCsLkrwXX3vko27zOrsYavX3okkYAQSOxEzOgzwUIBl+ZYCJ76V+h+A8SF8/6p9E7BbsBuTa+U2icaKKri4pk87f3FN24EaO9Pc809r9CfztMUDfKN9x5FUzSEm9hZ9LAsVxymxULIugdh9T32xpM+BTOPKl1QbZuec6LUftDfGlVRiUy+5ImLYAfpr/r5y7QPZIgEXb5+6ZHMbozgJDtx8qlRnyMILXUhAj0b4fGv2RvnnQLHfax0QZHG0nt5KaWK0kBRFZPM5mkfKH3iYjyT55p7XmFrT4qgK9z0niM4vK0OJ91bYiW80FIbJuSl4MGrIZ+24ybn3mRXxRcTCOmsLqXehgkNFBE5X0TWicgGEbl2lPs/LCIvFy7PiMjRE1mPqh6JTJ5d/aXDJJ3z+NIvX2V9exxH4PqLlnHcvCYkG8dNF5/R1RwLURNw4NEboXezPRv+/G/a1kcxIlA7Q2d1KfU2TFigiIgLfA+4AFgGXCYiy/Z42JvAGcaYo4CbgB9MVD2qeiQyY7dMsnmfL9/7Kq9st62Qq89fwqmHtSC5VMnt6JtiIWKhADx/B7zxqL3x9Kugbc8fvT1Ep9kWilJqv01kC+UEYIMxZqMxJgvcBVwy8gHGmGeMMT2Fq88CcyawHlUF4mWGyfX3r+b5LfZQrCvPPozzlrWBl7GD8EWmBzfFQtSGgvDmk/Ds7fbGpRfDEZeWLioULd16UUqVZSIDZTawdcT1bYXbivkE8OBod4jI5SKySkRWdXQU3/RPVbeBdI72/nTJMMl5Pjc+sIY/v9kNwKdXLuSSY2aDlyMQ31l0j66hMOl+Ex6+DjDQdiSs/ELpbizHtbO6lFJv20QGymi/xaP+JRGRM7GBcs1o9xtjfmCMWWGMWdHa2jqOJaoDpS+VG3M2Vzbv89X71wyduHj56Qt43/FzwPcIJHYgZvSNIhsjhTBJ9cKv/xFyCXuy4oX/DO4Y3Vi1bXoCo1LjJDCBr70NmDvi+hzgrT0fJCJHAT8ELjDGFB9pVZNWXzJHV2LsMLn+/tVDLZNPvPMQPviOuWB8AvEdiD/6RpG14SB1NUHwsvDgVdC3xYbIhd+yoVJKpFFXwys1jiayhfIcsEhEDhWREPBB4P6RDxCRecAvgI8aY16fwFpUhXQnsmOGSTrn8aV7Xx0Kk8tPX8CHT5wPxuDGdxQ9dTEaCtAUDYEx8NjN8NYL9o5zboC25aUL0ynCSo27CWuhGGPyIvK/gYcAF/iRMWa1iFxRuP/7wPXANOB2sf3ceWPMiomqSR1YnfEM/anSW9DHM3m+9MtXeGW73SX40ysX2m4uY3ATO4tuRR8OFrZUAVj1Q1j3a/v5SZ+BReeVLkynCCs1IaTUAGk1WrFihVm1alWly1AlGGPGPBwLoCeZ5Zp7XmFDexyws7kuOcbO23AT7Ti5gVGfVxMM0FIbQhBYcz88Vjgsa+nFcNb1YwdF3QwI1+7bm1Jq/02Z/7lM5BiKmoI837CzP00mV/zYXoBd/Wmu/vnLbO1J4Qhcc/4Szl1mZ1u5yY6iYRINBWiOFcLkzSfh8ZvtHXNOgJVfHDtMIk0aJkpNEA0UNW4yeY/2/gw5b/SpvYM2dsS59hev0BnPEnSF6y9axqmH2d193WRH0UOyoqEA02Jhe2XHS/DQtWA8aF1SmNFV4uRFsHt0xXTcRKmJooGixsXg9vP+GF2oL27t5cv3vkoi6xELudx4yREcO68JwG72WCRMYqHg8JhJ53p44LP2bJOGOfDu70BojFaHG7BdXUqpCaOBot4WYwxdieyYg+8Aj65t55sPvUbOM0yrDXHLpUeysNUGQamWSW04aGdzAfS8Cfd9GjL9EGmGi7879mwtEaibpetNlJpgGihqv+U9n/aBDOkxxkuMMdz5x838+I+bAZjfHOWW9x5JW32Nnc2VbMfJxUd9bl1NiMZIoSurbxvc+ylIdUO4AS65HRrmjvq8ISJ2p2Hdp0upCaeBovZLMmvPMfH80l1c2bzPtx5ex+/W2g0dj5nbyA0XL7OLEY3BTe7CySVGfe5uYdK/w4ZJogNCMbjke9CyaOxCYy26eFGpA0QDRe0TYwzdiSx9ZXRxdcYzfOX+1azdYWdsXbh8Blees4ig64Dx7TqTIgdk1deEaNitZXIFDOywA+vvvg2mLx272EgT1DSU/d6UUm+PBooqWzbv0z6QJpsvPYsLYM1b/Xzl/tV0JbII8HenHcoH3jEXEQHfK7losSESor6mECa9W+HeT0J8lw2Ti74DM8s4NqemXmd0KXWAaaCosvSlcnQnsiV3Cgbbgvn1Kzu57bH15DxDLOzypQuXctKCwh93P1/Ym2v0c+AbIyHbHQbQvdEOwCc6IBiDi28rL0zCtVA7fV/enlJqHGigqJLynk9HPEMqW3rgHeyeXN/+3XoeXrMLgLlNEW56z3LmNRfGMLyM3YK+2K7B0RB14UKY7HwFfnUlZPrslOCLvwszjhy74FBUt6NXqkI0UFRRA+kcXfHsmGtLALZ0J7nxV2vY2GkH2E9b1MJVf7WY2rD9EZNcqnA41hjnmQBseRYe/DzkUoWpwbfZxYtjCUbsjC7do0upitBAUXvJeT6dZbZKjDE8tHoX33lsPemcjyPwycI5JoUNP5HsAG6yo8hJi0Lz4LG9AOt+A4/eAH7ehsMlt0PjvLGLDtZomChVYRooaogxhr5Ujp5kbsyxErBnw3/7d+t59DU7Jbi1Nsx171rKkXOGZ1Y5qW7cTE+RVxBaakNEggG7Bf2q/4Q//Zu9q3mh7eYqZywkEC4sXJzI0xiUUmPRQFGAHf/oGBh7H65BL23t5ZbfvsaufntWyamHTeOq8xZTPzjV1/i4iV04+eSoz3dEaKkNEw644OXgiX+CtYXjcua8Ay74ZwjXjV1IIAz1szVMlKoCGihTXN7z6U5miadLbzU/KJv3+dHTb/KzVdswQCjgcMXpC7jkmFlDXVx4GQKJ9qIzuQKOQ0tdmKDjQLILHrwadrxo71xyEZx53dgbPYKGiVJVRgNlihrs3upN5soadAe7tuSfH1rH5m7b6ji8rZYvXLCE+dNiQ4+RTD9uqrPIeAmEAi4ttWFcEWhfC7/5nF1jAnDiFbDib8sbBwnWaDeXUlVGA2UKimfy9CSyZXdvpXMedzy9iZ8/b1sljsCHT5zHR0+aT8At/EE3fuEck9H35AKIhYM0RYPDB2P9/hbwMhCMwrk3woIzy3sD4Vo7NVgH4JWqKhooU0gq69GVyJS10n3Qsxu7+M6jG9jZb1e1L2yNcdVfLebwtuHxDcmn7Cwuv9h2LEJTLGinBedS8PtvwGu/snc1zIEL/xWmLSyvoEij3Z9LKVV1NFCmgHTOoyeZLWsa8KCOgQzfe3wDT67vBCDoCh85cT6XnTB3RKvE4KR7SszisuMl02pDhFzXrnz/7bXQ/Ya9c8FKOPur5Q2+gw2SSGPZ70EpdWBpoBzE9idIsnmfnz2/lZ88u4V0oSVz7LxGrjx70fCKdwZbJZ1FB95hxHG9Bnj5/8HTt9ouLseFU66Eoz9UXreViD0cKxQb+7FKqYrRQDkIpbIeval9CxJjDH/Y0MX3f/8GO/ps91ZTNMgnz1jIuUunD8/gMj5uqqvoYVhgpwQ3RguLFRMd8NhNsPlpe2f9bDj3Zph5VHmFuQE7+K7nmShV9TRQDiL70yIBWLujn3974g1efcuGhOsIlx47m4+ePH9o6xQAycbtDC5T/PUjoQCNkSABEXjtAXjqW5Cx29ez+F1wxtVjH9c7KBSF2hk6k0upSUID5SCQznn0JnMks+WtJRm0uSvBHc9s4snXO4duO/HQZj51xkLmTRtxKJWXxU11Fj27BGyrpCFaGHgf2AFP3AKb/2DvrGmAM66FReeVX1ykSbefV2qS0UCZxPY3SHb0pbjzj5t5ZM0uBg9cPKy1livOWMBx85uGH+h7OOkenGx/0XUlALFQkMZoEMfPwwt3wp//HfKFs04Wng1nXDP2ue+DHMdOCdbxEqUmHQ2UScYYQyLr0ZfKkRnjLPc9be9J8ZM/beHhNTuHgmRWYw0fP+UQzloyHWfEOImT6cPJ9JXs3goFXBojQbt9yvbn7XTgwRlc0Wlw+tVw2DnlFxissV1crv5YKjUZ6W/uJJH3fAbSeQbSefJ++etIAN5oj3PXc1t5fF37UJC01ob56MnzOf+Itt2nAWf6cDK9JYNkt+6t/u129tYbj9o7xYEj3w8nfqr86cAitosr0qSLFZWaxDRQqpgxhmTWYyCd3+duLWMML2zp5e5VW3lu0/A6kbb6MB8+cR7nLZtBKDC8yt3J9I8ZJCDU1QSprwngpPvgD3fY6cCDCxpnHAWnXQVty8ov1A3aLq5gzT69P6VU9dFAqULpnEc8kyeRyeP55e2zNfK5v1vbzi9e2MamruGdfudPi/KBFXM5Z+n04RaJ7+Fk+3Ay/WMEiV1T0hAJEsinYdWP4S93QtYepkVtG5z893D4+eW3MESgphGizdoqUeogoYFSJbJ5fyhEyt1ja6Qt3Ul+9dJbPLR6F/HMcGvmqDkNfGDFXE5c0Dw8RuJlbYtkjMF2gJpggIZIgJCXghd+Ai/+N6T77J2hWjjuY3D0Zfa0xHKFohBrLW9HYaXUpKGBUkGeb4hn8sQz+X0eYAfI5DyeXN/Jg6/u5MWtvUO3B13hrCXTufTY2SwauedWLmnHSIqcUTJSKODSUBOkJt8Pq+6Gl++CTGExoxuGoz4Ax3/cTgkuVyBkB+t1BpdSByUNlAPM8w2JrG2J7OsCRADfGFZv7+eRtbt4fF07iczwa8yor+Gio2ZywZEzaIoWVpb7Hk52wLZGim7eOCwcdKkPB6lJbIdnfmp3BfbsIVoEauyA+7EfLX8aMNhZW5FmqKnfl7eqlJpkNFAOgJznk8x4JLJ50vvREjHGsLEzwRPrOnh0bfvQzr8AAUc49bAWLlg+gxWHNA11a0kuZUMklxizWwuEaMilNuQQ3v4svHw3bHlm+O5wHSx/v+3aijaXX7jj2plbNQ06TqLUFKCBMgGMMaRzPslsnmTW268xEWMMb3QkeGp9B79/vZMt3bt3Ux3eVsu5y9o4Z0kbDdHCWISXxcnGcbIDiBl7VpgrDrFwgFiuk8CaB2DNfXaV+6C6mXDMh2Dpe+y4R7kcpxAkjRokSk0hGijjJJP3SGd9UjmPdM4r+xTEkfKezyvb+/jjxi6e3tA1tEnjoFmNNZy5eDrnLJ0+fEqil8NJ9yK5BI6XHuVV9xYOusScPNGtTyDrfgNbnwUzIvTmnmjHSOa/07YyyuW4dnt5DRKlpiQNlP00GCDpvA2QfZ3eO6hjIMOqTd38eVMPqzZ1k9hjXGV2Y4TTFrWwcnEri6bX2l1/vSxOuscOspcZIq44RAOG2vbnCLzxKGx8HHIjWj2RJljyblj2Hmiav29vIhCyIRKu0yBRagrTQCmD7xsyeZ90ziOd98jk/P1qgYA9fvelrb38ZUsvL2zp2W2tyKDFbXWcvLCZdx7WwqEtMUQEyaeQdA9OLlHyDJKRHBEiZKlrX0Vw85Pw5u8hO+KIXicAh7zT7gJ8yGn7No1XxM7WqmnYtynDSqmDlgbKHowxZD2fTN4nk7Mhsj9jIIN6klle3d7Py9t6eXlbH290xNmzMRMLuxw/r4l3HNLMSQuamVYbBj9vWyDJdhsmYyw8HOSKQzT9FrEdfyK47VnY9hx4IwNIYPbxsOhcWHjOvp+A6AYgXG+DZF+6w5RSB70pHSjG2JZH1rPhkfV8snkfs5+tj7zns7Ezwdod/azdMcDqt/rZ3rv3lu+uIyybWcex85o4fl4Ty2bV4+Ij+RROvh/pT5fdCgEhnB8g1vEiNTufw93+HPRt2/0hjguzV9gjdxecte9nsjuOXcQYrtPWiFKqqCkTKDnPJ1cIjGzetkDyvtnv8MjmfTZ1JdjQHuf1XXFe3zXAGx1xct7erxd0hSUz6jhqTiNHzWlg+awGIq6HeBmcfBqJbys/QIwhnO4g2r2GcPtLBHb+BeneuPfjIk0w7xSYfwrMP7X8jRoHDYZIKAbBqI6NKKXGdFAFijGGnGeGw8Pz7fX8/o95+Mawsy/Npq4EmzqTbOxM8GZngi3dyaID8S21IZbOrGfZzHqWz65nUUuUsOQQL43kM0hqa9ldWJJNEO1bT6T7NUJda3DaVyOJjr0f6IZg5jEw5x12ltb0pXbn330RCNvwCMV0s0al1D6blIGSydtZVbm8Iefb8MgXgmR/xdN5tvem2NaTYmtPkq3dSbZ2288z+eKv2xQNsqitjsPbajl8eh2Lp4eZHhHEz9rw8HqRZGfR5w8xPm58JzX9b1LTt5Fg7wYCXa8j/dtHf3wwAm3LYdZx9jJjuV3JXi4RG0LBiL0EInrUrlLqbZl0gZLzfLb3FD+Ktphs3qd9IM3OvjS7+jPs7E+zoy/Njr4Ub/Wm6UuV3pYk6ArzmqMc2hLj0GkxFraEWdQcZlrEIF4O/Bzi9SPGQImtsiSfJjCwneDAVkLxbYT6txDo24TTuwnJF5sCLNB0CLQdYS8zjoJph9lZWuVyAzZwAuHCxxrtxlJKjatJFyh7djIZYzdY7Epk6Ypn6Ypn6Ixn6Yhn6Ixn6Biwl57k2PtYAdTVBJjbFGFuU5S5jWHmN4U4pDHAzDqXoMnZ/bD8PEIOiMOeGeDlcFMdBBLtuImdBAuXQPwt3IHtOMlRuqtGcsPQfChMWwSti6F1CbQssuMZ5RCxQRMI2xbIYIjojCyl1ASbdIGysy/NF3/5Cj3JHD2JLD3J7KgD4cU4Aq11YdrqwsxqCDGrPsTM2gBzGgLMqXOoD4H4ucIYh89QYmTyuOkenHQ3bqoHN92Fk+rCTXURSHUSSHbgJjuRVFcZe2dhxyoa50HjfGheULgcCg3zyvvj7zjgBG1ouMHCJWw/astDKVUBky5Q+lI5nt3YPep9jtgxjWmxIK2xIK2xAC0xlxmxANNrHdqiDq01ecL5ASQbx8kNDO195XQO4Gzvw8kM4GT7cDN9OOk+3Eyv3fI9O7DvxUZboH6W3ROrYQ7Uz7EfG+baqbul/vA7rm1pOAEbEo5bCJCg/ajjHUqpKjOhgSIi5wO3Ai7wQ2PMLXvcL4X7L8SOPHzcGPNCqdecHspw/aHraAxkaQxkaXAz1EuaWidDlAyul7LrOXJJZCCF0520CwRzCbx0PyH27Sjd0ZQ9YSzRaS87Xt7nr+EDGhkHXrup5+r8FZxZu42PZn663/8GBvAo7xfMB6RwGZXY13Ma5sOxH4ZNT5HqeJM3ctO4w7yb1roaPuP9F3UDG8HP26/uBKBlsZ24sf63kIlDuBZO+gysvKZoLU+81s6uB27kgvgviJIiSYQHay9lyXFncPSWH0PvZgZMhIG+HpqNPVp6uzOL+Glf5uiz3r/3C77+CPzuK9C9wb6JlkWw9GLY9BT0brYt9FOuhMPPHX78M7fa+0J2K59UvHe39/rJwAM0xTdAegD8rH2/bhhqZ4AYaJzPxtrjcNbez0xvGwJkGhZQ966v7f112tfaLYi8nJ0V2bIIzv7q6PXsWavai+zvOowxX1jEBV4HzgW2Ac8Blxlj1ox4zIXA32MD5UTgVmPMiaVed8Us16y6vMzxhDJM0NtXk1gWhyB+8T/wlSIgCOmaNjZlotSQoZ4kAZMhStoujh31eYXWrfEAA6dfPWqoPPFaO+t/dj1/492NZ8DDwcXHFZ8EEQJ1MxE/RyixDdf45HDwcXAx9Eotb53+L7uHyuuPwH2fhlS3rcGY4RpiM6C2FXIpGwoXfMs+58HPgxOyf+D7t+Ibw3bTiicu9SQxxieHy3R6cEbrWo61kfaEYHoXBsHDBQwOBr+mifCl3x/+OrksJHYVagIkYFM9Mg0u+d7u9QQju9e6b6FSdT9KE2UiWygnABuMMRsBROQu4BJgzYjHXALcaWyqPSsijSIy0xizY++XGyR2/CEYsQPOI6e9hqIQjNl1FLtd6tjw0PdYIDumzr+s2m8h9n/6+cQz+Jk+RGLkJELU6yRIdoyfa2P7gwmAl4dnvzdqoPz7kxv5gXc/ngEfF8F+DBiPWkmxOe0wM9+BGIMBXAweDh4+MZPCffY2GBkoz9wKmYFCoBXaermcrSfbDzLd/s5mC48F+8c7FIWuDSAued9nGn1sd2YT9ToxgI8UH6dMduITKtxvMNj96Xx8THpg96+T7Ryxy7Z9t0jQnky6Zz2we63aShnVRAbKbGDriOvbsK2QsR4zG9gtUETkcuBygHnz5sGXNu9zMaGHbtUwUZObAQQCJofj2J9mlzwOpvQ0kJHNcHFt99cotvYkiZAiWwiToacAgiGb93FNbuiP+eBHgxDAozm3x/8DezfbLrjRJpmM3F8uGIHeLfYN1jQN3y8OHkKQ3NB7HfM/+8YjUHj8yEcaHBzyu38dr9BdNvQgY7u9/Pze9exVqxrNRHbTj/Yvv+fPfTmPwRjzA2PMCmPMitbW1v0qZptpLWfulVLVq/Dbkpfg0M4PHoFCR1eJP7QjJ38Yz46ljGJuU5QUEdw9WmiDrYJQwMGTIKbwtQY/CoY8Lt3Bmbu/YON8O5YzWr+yGxr+PJcanvGYSw3fbwwuhlyhleERII9LttT/g8UlL8GhuoduxscnsPvXcUPs9n0TsS0WJ7B3PXvWqkY1kYGyDZg74voc4K39eMy4+Kl7CQkTGvuBasrLjt47XyUEJ9yAMYagnyIpURJExhjxEfCN7e7C2IH5UXzy9AXc5V6MK+DgYTD2owhxIrTV+JhoK0YEATwEwcfFkJAI3kl/v/sLnnKl3UPOeOD74Hm2BSAOhOpt0GSTdlzilCvtxc/a26KttrUhPl00DL3XJDUMEB0Ks71EW+z3B8HgIPgIHg4+UlO3+9cJ1Y/YnsgATiFw6/euoQ1tWAAAB6VJREFUZ89a1agmMlCeAxaJyKEiEgI+CNy/x2PuB/6XWCcBfaXHT/bfd796LV9wPke7v4+bJFZINffiH8zaTT2X5z7PneEPva1/AwNlzyf0GaVZPpKAEZCG+bDyC9TMWMT8aJZ4sIWvBT7D7c1fJNWwCHGCDP2P2wnA9CPgyA/YFomfs2MARQbkAVYumc6i99/IPbUfIiM1hMQjIzXcU/sRNp3+HWLTZhENCqmGReyQ6fi4gLDFmbP3gDzYcYZLbrezzQTbApi+FM64FloWQroX6tqGB7kPP9d+Xtdmvysti3GmL6UlFhh6r//RfBXh6YfjRFvACQ+/XzcMDfMhWEPNjEVsXv4PbHPnF759QrrhMDsgP/LrtCyESLMdk3UKU/Nbl9gB+T3r2bNWNaoJm+UFQ7O4vo2dNvwjY8zXROQKAGPM9wvThr8LnI+dNvw3xphVpV5zxYoVZtWqkg9RSqlqMmWGbyc0UCaCBopSapKZMoGia+eUUkqNCw0UpZRS40IDRSml1LjQQFFKKTUuNFCUUkqNCw0UpZRS40IDRSml1LjQQFFKKTUuNFCUUkqNCw0UpZRS40IDRSml1LiYdHt5iUgHsO8nbJWvBeicwNffX1pX+aqxJqjOuqqxJji46uo0xpw/EcVUm0kXKBNNRFYZY1ZUuo49aV3lq8aaoDrrqsaaQOuarLTLSyml1LjQQFFKKTUuNFD29oNKF1CE1lW+aqwJqrOuaqwJtK5JScdQlFJKjQttoSillBoXGihKKaXGxZQOFBGZKyKPi8haEVktIlcWbm8WkUdEZH3hY9MBrKlGRP4sIi8Varqh0jXtUZ8rIn8RkQeqpS4R2SQir4jIiyKyqhrqEpFGEfm5iLxW+Pk6uQpqWlz4Hg1e+kXks1VQ1/8p/Ky/KiL/U/gdqIafqysLNa0Wkc8Wbqt4XdVsSgcKkAc+Z4xZCpwEfEZElgHXAo8aYxYBjxauHygZ4CxjzNHAMcD5InJShWsa6Upg7Yjr1VLXmcaYY0asEah0XbcCvzXGLAGOxn7PKlqTMWZd4Xt0DHA8kAR+Wcm6RGQ28A/ACmPMcsAFPljJmgp1LQf+DjgB++93kYgsqnRdVc8Yo5fCBbgPOBdYB8ws3DYTWFeheqLAC8CJ1VATMAf7S3QW8EDhtmqoaxPQssdtFasLqAfepDDppRpqGqXG84CnK10XMBvYCjQDAeCBQm0V/V4B7wd+OOL6l4GrK11XtV+megtliIgcAhwL/AloM8bsACh8nH6Aa3FF5EWgHXjEGFPxmgq+jf2l8kfcVg11GeBhEXleRC6vgroWAB3AHYXuwR+KSKzCNe3pg8D/FD6vWF3GmO3At4AtwA6gzxjzcCVrKngVOF1EpolIFLgQmFsFdVU1DRRARGqBe4DPGmP6K12PMcYztltiDnBCofldUSJyEdBujHm+0rWM4lRjzHHABdhuy9MrXE8AOA74N2PMsUCCKuoaEZEQcDHwsyqopQm4BDgUmAXEROQjla0KjDFrgW8AjwC/BV7CdpGrEqZ8oIhIEBsmPzHG/KJw8y4RmVm4fya2pXDAGWN6gSeA86ugplOBi0VkE3AXcJaI/HcV1IUx5q3Cx3bsmMAJFa5rG7Ct0LIE+Dk2YCr+vSq4AHjBGLOrcL2SdZ0DvGmM6TDG5IBfAKdUuCYAjDH/aYw5zhhzOtANrK+GuqrZlA4UERHgP4G1xph/HXHX/cDHCp9/DDu2cqBqahWRxsLnEewv3GuVrAnAGPMFY8wcY8wh2O6Sx4wxH6l0XSISE5G6wc+x/e+vVrIuY8xOYKuILC7cdDawppI17eEyhru7oLJ1bQFOEpFo4ffxbOwEhop/r0RkeuHjPOBS7Pes4nVVsym9Ul5E3gk8BbzC8LjAF7HjKHcD87A/8O83xnQfoJqOAn6Mne3iAHcbY24UkWmVqmmUGlcCnzfGXFTpukRkAbZVArar6afGmK9VQV3HAD8EQsBG4G8o/HtWqqZCXVHsIPgCY0xf4bZKf69uAD6A7VL6C/C3QG0layrU9RQwDcgB/2iMebTS36tqN6UDRSml1PiZ0l1eSimlxo8GilJKqXGhgaKUUmpcaKAopZQaFxooSimlxoUGipoyROSvRcSIyJJK16LUwUgDRU0llwF/wC7MVEqNMw0UNSUU9ms7FfgEhUAREUdEbi+cd/GAiPxGRN5XuO94Efl9YcPJhwa321BKFaeBoqaK92DPJ3kd6BaR47DbaRwCHIldnX0yDO3vdhvwPmPM8cCPgK9VomilJpNApQtQ6gC5DLv9PtjNLS8DgsDPjDE+sFNEHi/cvxhYDjxit5fCxW6trpQqQQNFHfQK+y+dBSwXEYMNCMPwHmB7PQVYbYw5+QCVqNRBQbu81FTwPuBOY8x8Y8whxpi52BMVO4H3FsZS2oCVhcevA1pFZKgLTESOqEThSk0mGihqKriMvVsj92APdNqG3e7+37G7TPcZY7LYEPqGiLwEvIg9o0MpVYLuNqymNBGpNcbEC91if8ae/riz0nUpNRnpGIqa6h4oHGgWAm7SMFFq/2kLRSml1LjQMRSllFLjQgNFKaXUuNBAUUopNS40UJRSSo0LDRSllFLj4v8DjM2JUStjdH4AAAAASUVORK5CYII=\n", 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\n",
"text/plain": [ "text/plain": [
"<Figure size 413.359x360 with 1 Axes>" "<Figure size 413.359x360 with 1 Axes>"
] ]
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