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December 3, 2021 01:24
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clusters_lab5.ipynb
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{ | |
"nbformat": 4, | |
"nbformat_minor": 0, | |
"metadata": { | |
"colab": { | |
"name": "clusters_lab5.ipynb", | |
"provenance": [], | |
"collapsed_sections": [], | |
"authorship_tag": "ABX9TyP1myUwgkTfT9rCTb7UOsoQ", | |
"include_colab_link": true | |
}, | |
"kernelspec": { | |
"name": "python3", | |
"display_name": "Python 3" | |
}, | |
"language_info": { | |
"name": "python" | |
} | |
}, | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "view-in-github", | |
"colab_type": "text" | |
}, | |
"source": [ | |
"<a href=\"https://colab.research.google.com/gist/executed/b5d1fc4be0207528df67fdca596947b1/clusters_lab5.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "RWgnQtQqqm4o" | |
}, | |
"source": [ | |
"# Lab 5" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "GLujw0meqq4G" | |
}, | |
"source": [ | |
"Generate 3 clusters and emmisions" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 449 | |
}, | |
"id": "WmYUeG5AWXvj", | |
"outputId": "7d419a9c-5ee8-464c-9867-589a59fe2cd6" | |
}, | |
"source": [ | |
"!pip3 install pyclustering\n", | |
"\n", | |
"import matplotlib.pyplot as plt\n", | |
"import numpy\n", | |
"from numpy import random\n", | |
"import math\n", | |
"\n", | |
"# Normal distribution (10k)\n", | |
"x_normal_dist, y_normal_dist = random.multivariate_normal([-5, -7], [[4, -2], [-2, 2]], 10000).T\n", | |
"\n", | |
"# Elipsis (15k)\n", | |
"x_elip = []\n", | |
"y_elip = []\n", | |
"while len(x_elip) < 15000:\n", | |
" x = random.uniform(0, 10)\n", | |
" y = random.uniform(0, 10)\n", | |
" if (2 * (x - 6) ** 2 + 3 * (y - 4) ** 2) <= 10:\n", | |
" x_elip.append(x)\n", | |
" y_elip.append(y)\n", | |
"\n", | |
"# Rectangle (10k)\n", | |
"x_rectangle = []\n", | |
"y_rectangle = []\n", | |
"while len(x_rectangle) < 10000:\n", | |
" x = random.uniform(-10, -5)\n", | |
" y = random.uniform(5, 10)\n", | |
" if (math.fabs(x + y) <= 2) and (math.fabs(x - y + 15) <= 3):\n", | |
" x_rectangle.append(x)\n", | |
" y_rectangle.append(y)\n", | |
"# Emmisions (500)\n", | |
"x_emis = random.uniform(-20, 20, 500)\n", | |
"y_emis = random.uniform(-20, 20, 500)\n", | |
"\n", | |
"#plt.plot(x_rectangle, y_rectangle, '.')\n", | |
"#plt.plot(x_normal_dist, y_normal_dist, '.')\n", | |
"#plt.plot(x_elip, y_elip, '.')\n", | |
"#plt.plot(x_emis, y_emis, '.')\n", | |
"#plt.show()\n", | |
"\n", | |
"x_combined = numpy.append(x_normal_dist, numpy.append(x_elip, numpy.append(x_rectangle, x_emis)))\n", | |
"y_combined = numpy.append(y_normal_dist, numpy.append(y_elip, numpy.append(y_rectangle, y_emis)))\n", | |
"\n", | |
"combined = numpy.vstack((x_combined, y_combined)).T\n", | |
"\n", | |
"plt.plot(x_combined, y_combined, '.')\n", | |
"plt.show()" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"Requirement already satisfied: pyclustering in /usr/local/lib/python3.7/dist-packages (0.10.1.2)\n", | |
"Requirement already satisfied: matplotlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from pyclustering) (3.2.2)\n", | |
"Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.7/dist-packages (from pyclustering) (1.4.1)\n", | |
"Requirement already satisfied: Pillow>=5.2.0 in /usr/local/lib/python3.7/dist-packages (from pyclustering) (7.1.2)\n", | |
"Requirement already satisfied: numpy>=1.15.2 in /usr/local/lib/python3.7/dist-packages (from pyclustering) (1.19.5)\n", | |
"Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.0->pyclustering) (1.3.2)\n", | |
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.0->pyclustering) (0.11.0)\n", | |
"Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.0->pyclustering) (3.0.6)\n", | |
"Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.0.0->pyclustering) (2.8.2)\n", | |
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.1->matplotlib>=3.0.0->pyclustering) (1.15.0)\n" | |
] | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {} | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "wI812U7w0gZa" | |
}, | |
"source": [ | |
"Getting Hopkins tendency" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "AgqlHrOzsO72", | |
"outputId": "ec26d2fa-8e93-4aef-ff3a-211812eb4a70" | |
}, | |
"source": [ | |
"from sklearn.neighbors import NearestNeighbors \n", | |
"from random import sample\n", | |
"from numpy.random import uniform\n", | |
"from math import isnan\n", | |
"\n", | |
"def hopkins(X):\n", | |
" d = X.shape[1]\n", | |
" n = len(X) # rows\n", | |
" m = int(0.1 * n)\n", | |
" nbrs = NearestNeighbors(n_neighbors=1).fit(X)\n", | |
" \n", | |
" rand_X = sample(range(0, n, 1), m)\n", | |
" \n", | |
" ujd = []\n", | |
" wjd = []\n", | |
" for j in range(0, m):\n", | |
" u_dist, _ = nbrs.kneighbors(uniform(numpy.amin(X,axis=0),numpy.amax(X,axis=0),d).reshape(1, -1), 2, return_distance=True)\n", | |
" ujd.append(u_dist[0][1])\n", | |
" w_dist, _ = nbrs.kneighbors(X[rand_X[j]].reshape(1, -1), 2, return_distance = True)\n", | |
" wjd.append(w_dist[0][1])\n", | |
" \n", | |
" H = sum(ujd) / (sum(ujd) + sum(wjd))\n", | |
" if isnan(H):\n", | |
" print(ujd, wjd)\n", | |
" H = 0\n", | |
" \n", | |
" return H\n", | |
"\n", | |
"rt = hopkins(combined)\n", | |
"\n", | |
"print(rt)" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"0.9764271580655096\n" | |
] | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "2qMYEOO1BLXH" | |
}, | |
"source": [ | |
"Bootstrap sampling" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 265 | |
}, | |
"id": "XRfAKd3Q0jgi", | |
"outputId": "19f0ea5e-d581-477f-9d63-f76027df2f7f" | |
}, | |
"source": [ | |
"import numpy as np\n", | |
"import seaborn as sns\n", | |
"\n", | |
"my_samples = []\n", | |
"for _ in range(10000):\n", | |
" x = np.random.choice(x_combined, size=2835, replace=True)\n", | |
" my_samples.append(x.mean())\n", | |
"\n", | |
"\n", | |
"plt.style.use('ggplot')\n", | |
"plt.hist(my_samples, bins=100)\n", | |
"plt.show()" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": "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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {} | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "fEXOc9AF-edq" | |
}, | |
"source": [ | |
"DBSCAN" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 283 | |
}, | |
"id": "jMLRXW4M-iEV", | |
"outputId": "098d6c8b-b6a3-45aa-dc31-c5ced31eb064" | |
}, | |
"source": [ | |
"from sklearn.cluster import DBSCAN\n", | |
"\n", | |
"epsilon = 0.5\n", | |
"z = 7\n", | |
"dbsc = DBSCAN(eps=epsilon, min_samples=z).fit(combined)\n", | |
"dbsc_labels = dbsc.labels_\n", | |
"\n", | |
"\n", | |
"plt.scatter(combined[dbsc_labels == -1, 0], combined[dbsc_labels == -1, 1], s = 30, label = 'Noise')\n", | |
"plt.scatter(combined[dbsc_labels == 0, 0], combined[dbsc_labels == 0, 1], s = 30, label = 'Cluster 1')\n", | |
"plt.scatter(combined[dbsc_labels == 1, 0], combined[dbsc_labels == 1, 1], s = 30, label = 'Cluster 2')\n", | |
"plt.scatter(combined[dbsc_labels == 2, 0], combined[dbsc_labels == 2, 1], s = 30, label = 'Cluster 3')\n", | |
"\n", | |
"plt.legend()\n", | |
"plt.show()\n", | |
"\n", | |
"print(\"Clusters: \" + str(len(set(dbsc_labels))))" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"Clusters: 4\n" | |
] | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "5itTNyHhFBmp" | |
}, | |
"source": [ | |
"BIRCH" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 283 | |
}, | |
"id": "8BNOG8pQTiKU", | |
"outputId": "85dbceb4-2c42-49f9-90fe-ef1a075e29e0" | |
}, | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"from sklearn.cluster import Birch\n", | |
"\n", | |
"model = Birch(branching_factor = 52, n_clusters = 3, threshold = 0.5)\n", | |
"model.fit(combined)\n", | |
"\n", | |
"pred = model.predict(combined)\n", | |
"\n", | |
"print(set(pred))\n", | |
"\n", | |
"plt.scatter(combined[pred == 0, 0], combined[pred == 0, 1], s = 30, label = 'Cluster 1')\n", | |
"plt.scatter(combined[pred == 1, 0], combined[pred == 1, 1], s = 30, label = 'Cluster 2')\n", | |
"plt.scatter(combined[pred == 2, 0], combined[pred == 2, 1], s = 30, label = 'Cluster 3')\n", | |
"plt.scatter(combined[pred == 3, 0], combined[pred == 3, 1], s = 30, label = 'Cluster 4')\n", | |
"\n", | |
"plt.show()" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"{0, 1, 2}\n" | |
] | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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ZRxy4nlhhQx+PAWXHV/5V9aMKyaYyH5rUtDrn3Mj7wTQkHMikNqJ0KM+rZghbzaY1tHhL5itt+iwMZueZjs2PkLvYvsVUpuRZfXS5gZQ0ICnJmh5gfRdFJUBrI3MRdyJOftwreb2wMyHDTrlYED8A1J8UkivCYcDKUqRbMPHx6FV2lOdBt/8X0NcT+QCPB2TD50KW/JWBAdX5sDvRSQ/sMCT0QK9iFd/Z4bf/CJw/5UyNBOn7wXHApFKQL9zLPmANmy9/3THwi28AWbbW8iJo52Iqm0ebdsd65Ybfr7iIpy9fm1DySrCs5B1SGk5mSVqxwkW5tD4ePbsb8RrsfBsoKBzNGGS5WI7sB3a/y6A5mAbuS/eF+Duu7K1UnQ9Ht9gKEBcfx7OodS680VjoCCHA4huAIweEojCUCjvIc6ciFB9LlmBrE+jQIEjZAtN8QVJZ7FhMpd+kXbtjvXIzXTgj323cZry++uqrOHLkCLKzs/H8888DAN544w188MEHodqu//AP/4CFCxfa0ZwzcChKwknYWRaNlayk5wDQ8CHhiVp2SNk1MyOv15oPBwtmKMGpKAwpdB88q4wRrVhuX0hg7UHBvSAqvkBAfjDJkoXyQOX/gG/Sn60cK4jfAH+iBpSX5GPYrAeczrSVwhYlf+ONN2LTpk145ZVXIv5+6623YvNm+9N0HUEMlIZVRC1jTyXqwHBkglKIY1mFjus8oMkp4H/3Kujs+UL1qDPHovKhAMDQgV1Ri4lnUmV/si+S91xhLOnsclA7FyM9BpBitjIfP3kDehAFPRDtClG2KPmysjK0tbXZ8aiYIdqrq11wlBVRz8dtcAekd5zl13mApNQRSttAKJ4f9z4clYQSAPDVHrJtt2ckDl5pB0G+8dhI0ZXIylACDYSNi5EOxRear3AudxF2hTpGgT4iWnpAGjJKq6tAT9RicNlq0Gvn2NovR+Pk33vvPezevRvTp0/H3XffjYyMDNk1lZWVqKysBABs27YN+fn5ptpyu92m7xVBn3wZwwd3Y7j2MJLLlyB52RrLg22HXE5Aj1yDy1ajr2onImp1epKRtWwNUkbuZV+ThJTsCaB/fA1J5UuRsnxt5CGdxji73W4UTJwYcR1JTsHgO38adfX4/cDp48i+9fNI+U50agn7Fi7H0Id/Ux0PPeADAXQ9eh/4i2cFS3f/B/DMW4Scx55jvm+D+z8coV8OV9rHkXW+DslPvgz/x3sxeORgaCz7fvkTDDEWo+Tzp5BtggCLrv879BzcBd+xIyOLSTKS5lYgZ/1tsnnt/+0rGPzr6xJ/s/ExksnA8+h5+pFRGap2wjN3l+KYqUHr3XdCDyi2JelXX9VOJM1daKpfSiCUSpddc2hra8Ozzz4b8sn39PSE/PGvv/46uru78cADD2g+p6mpyVT7+fn56Ojo0L4wyhjLcsksSPEAUM0nL1rcw15BIXs8o6RYOl9almz8714VuOklIGs3gbtL+72yA3m5uWh74luq46EFyvPgn36ImYlNvvpdeVYutPsuHS/+k32gr70gd4nd9zDz+Xrl1uNe0PPOmIGdfYqnb9Kufk2aNEnxN8cs+ZycnND/33LLLXj22WedaioBh6DHd6iZkm6X3zoOzkzM+lIjCkYkJwMNF+QXBfzKLg2DfXfC5aDXLRg+RsnnT2H4muvscaONwcAIXYhCvxxT8t3d3ZgwYQIA4NChQygtdSZ2OQFnoefjDr+G/92rgs88HDa8tPFyZmL0DERm2RIOocpKkQ+2TWlH+2CP1T5ZtBLZGzfbZzHHwSLvCKLQL1uU/EsvvYQTJ06gv78f999/P774xS/i+PHjuHDhAgghKCgowNe+9jU7mkog3uEgJ30sFZdZMOsasMAohyjCTN/HdJlCBuJlkbcb8n4lA7Pm2NovW5T8d77zHdnfbr75ZjseHXXEawGIsQInP8Z4VFya74sS9bGYVclxArfS99UP2szsIMbTexwvi7zd4yrtV9ayNeifUTZ2omvGGtSSXQCMq4/GKcTLxxgNUJ4H/9MfjZaa2/s+6OxycN/+4Wh/FeL9cdNtIMODjoxPtJK2oo1YL/JOjKt00UhetgYDXV22yp1Q8mFQSuzhj1QBe3eMu4/GKej5GMeDpckf2S8sZOEp8CdrwB+pErjCobyz4f7+n5wLy4tBIRPWfI432D2urEWj5+Au0Pu/l7DkHYPSSfee94Azx6P60YxnmLGIlBaFaCwWYhu95+rAT5892sbu9+WJP5QK74uo5B3c2SjKFeVIFKX5pE++bHtb0YT03aLHa5jjSk+YLNjDWDR8x6pBbNYrCSUfDqVDQ4rxGb4VI5ipIqWU8Ul/9rSjO6zwtof8fsDzToQLTw+ccDOoyhXlSBSl+Rw+uFugnhiDYFZMKywRXG1SXXDuFCjPG3/nmIvxsO16ZWztjx2GUiFrrN4gLzRs4aOxWvB6zEPN0mRAcVH4798aLlRtdOxVi2Gv3iAcoIaDEGD1RtVn2gHVhdJiQXbDUJjP4drDzrQXBTDHt6URyJogv7il0b7i6J5k2xfjhCUfBqWtNQDw+yptiRgZr4dihmDU0lRaFI59rLnDikhEun4+sLfS2NirLEjcP94Pfl8FcLJWKIvncgOz54NbGAV/tIpcZNHK6B5+K8xncvkSMOKKxgZY4xsY+falUEtkUwHrvCZpbgUCNi/GCSUvgdLWWvrRoHxpiFTIiC84Fodi8QbDYZZKi8LcxUBHq+JiIVtQ94740EU/up6xV1mQYhpJpLFQRjMSRWk+zUSKxM2BvNL4zl8MdCq/c0bAen9y1t+GzkR0TWwgKzRs1hofp+nZRj5Oo8pRcVH43N2gTZdkf0f5UsEVs+s94NSngpUNyAuVAJpjr7UgRVOZynYlcZIcZNdiF0+7XMV5v/1uUGmRcQvjLn1/nOinbQRldmEsEJQZIRWKBnmUFHoUrp3jxSQps/BxsmRTIsiS/h3lSyMPY7WgY+zFNmzlYjGI0BiLriHOBcyeD6zegJQLp22Vyy5r2ug7Fo1vw4hcet85O98Hs99lTAjKxjUsWONOp2fHwhqKhgtKyWKW/p3/ZJ+6gidE4Inhg7rH3hEuFoPgP9kfydXOB4X3bfUGZN//qHML9v5K0KJS4JpZIHMWOOo+UQpRjNUuV+87p4VYu6ASSt4MLISoxUM1J9sRTy4oJRoBQJijmXOA1RuiVmjENuxRicnf9FnbFIns/QkEgMbzQON50AM7HTMYKM8DF07Lf3B7xjQJWTy4oBJK3gSsWuMxr+akAcMKI54YAlmycC5g9jyQNZtGlfpIstJ4gK2KRG2RdNBgoNVVQoiiFEUlY5qETFcJzbDvbcxVhhqviGt+FgsKV4gh3w/88TWgt1s4qNShMOKJIVCRRmCsh6iu2SBw5IRb8yMx+bbWnlWq1SrCqR2a0uIy/bqxPW8aRpd0ge6r2mn7+5pQ8iYRa7IkJZhVuLKDPRE6FEY8LXrxJIud4BauBH/9glEytJGDV27hCvj+/Gvb3GWy90cKp3ZoigXejbcVax94BDSMLrml77N9t5RQ8jYhXl4s09WLxJctXMGL0KEwlBa9WIxLvC7AVkA4Dty3f8ic16TypRj68B3bY7fpiWrg/BmgpcHxHZpdu8F48IGHQ7NfY7ky1NUELYriaMOUktM6sDShMGIS6RODRSVabSrNa8rytehjKBIxX8CoXNKckGjsimyLtVdhkiUEtvq99cy7Zr/GSmWoV199FUeOHEF2dnaokPfAwABefPFFtLe3o6CgAA899BAyMjLsaC7uoMpvsnFzbIXTCyVfLOcKWR7Bpibgh/dH/n7ng+DWrGd+MNGO9InVohJry5GlSGT5AiblimrmrB1tKVnGb7wGOtBrm9/byLyr9SsalaFseQtvvPFGfP/734/425tvvol58+bh5Zdfxrx58/Dmm2/a0VR8wiDhVjxCRmrlcgMT8oF/fgR44Pvgf/qMXMEDwO9fAf/1LQgODMh/c2Bc1AjGVBdbhxCLNlkgHAdu0Upwdz0gJA7VHoy5XDEh4mORfnEuIZCA4fc2C7vmXVygyX3fBVm7CdkP/dB2A8GWJ5WVlcms9MOHD2Pt2rUAgLVr1+Lw4bHLSKcJJpvc2CoyLH3ZyD8/Am7bvwNTZgIPfh44oTF/D/0jgm/+IfJDtnlcROuJvvYC6O53QV97Qfi32GYsFtt4XeBjLBflefQ8/YjyXDkEJgNndo78rEnHWKguUjaOb/gCnbLiRtt3gI755Ht7ezFhgkDLmZOTg97eXuZ1lZWVqKysBABs27YN+fn5ptpzu90R91Kex9CBXfDVHkJS+VKkLF/r3JZ9/d+h5+Au+I4dESbak4ykuRXIWX+bTK54gaJcGzcDGzdjqKcHvfd8xthD3/4v8G//F3L+410kZ2WpjovaXCjJNrj/Q/SdPiaxno4j8+wJpKy4EYPLVgtbcb9v9CZPMrKWrUGKDXPAksvpNp2Wy6nvZHD/h+g7dkRxrpyA2JfhSSXgZlwHOjyI5PKloDyPvp8+aWiOxEUq9O5W7YRn7i7kPCbU4nVq3p3QF1E5eCWEgEh5t0ewbt06rFu3LvRvs+nZ4ZwPUn/Z0IfvoM9p3+z93wMJ84kGKpajs6vLFBdFNA7y1OQKXqgHnnnY9LN7/mkTsOIWkLsfBFEYFzOy8Qf3RH5UAOAfRt/B3RiYORf02jnCgWPEAeQc9M8ow4ANaf9MTh2H23RSLie/E625shtK/Em+z31FuCBiLJI154j/ZB/osU8iXDy+Y0fQvuMtcItWOjbvY4q7Jjs7G93d3ZgwYQK6u7uRlZXlVFMyOH3gp6SE7TigiuVBXtDnA579N+DSGesPq/oAtOoD0Kf+L1x2HdzpoNeNdox8vMbl65HL0e+krByQWbrRr05Fqw8IrpCwschatgb9M8rU50gjtDFe550Fx5T84sWLsWvXLmzZsgW7du3CkiVLnGpKDgdjT51WwsyXte4o+Je2gqzdaMmqV0qf5gMB0N/9HNi/w7L8Mjz+NQQB4Ce/hSsnx9Kj9MRSxyJGPl7j8jXlcvA7IRUr4Jm7Cz7RGo5RdSqcrAGtWB5hlOniudcR2hiv8y6Fa+vWrVutPuSll17C66+/js7OTlRWViItLQ233HILtm/fjj//+c8YGBjAPffcg6QkRlUVCfr7+03JkJaWBq/XCwCgAR9QeyiSP9yTBLLhdpBJpaaeL4Ie2Q9Ubh+dfJ4HejqB4lLms8Pl0vX8D94CzkuImigPdLQAtYdA6+tAlq5RdH8pPldcnCq3A+dPY/jwXtD6k6DTy4CH7wQazhl6nmHs+Avo/CXgcnI1L1UaM0IIyNI1QPEUkPQMkA23g9tyZ9SsJz1zSXke9Mh+0A/eEt7DohLDc+WEXCw4+Z0QQpC78bPwZudHZa6U+oL1W0D/+OvQe4/aQ/DXHQO/aJX6vBSVgNbXAT0dwjNFeowtdzo6n2bnMjMzU/E3Wyz573znO8y/P/FEjJKBnORScTpDTY07xMJ2mpk+feoo8IOvWpdZL555WLDqn/9PuEy674xYT9FOjIqHmHlDKF8GFJUAjRcFQ8LjsdXaFqNGYlmdCpTKdsa+Y9UgGt/QWHLHaGFcZrw6OkEOZ6hpcoeYXVCYNSsD5gW1gu/eheCtd4DbfMe4SlIaS6UdKc8LyVLNDYKCJwQoLAH5xmO6xydeqDwA5W+e/v4XoDKjbFhf7Ycx4o7RwrhU8oBzE+Q042IEd8jud4G6o/ItqMKCovrRabELRhtv/wH8238AXvwvuBzIhL7qefU1EBofcaGnFGi9DFpzEPxI+r+a4o7HXQvrm6dMoyx5TOWwWMW4VfJOQcliAGCKJ0SpDbJoJWjFcklYGHtBoTwP/sh+4I1fjVAEB4E974OWTAX5/vPg3O7Rxen4EctjYCse+kcEF68Fue/b4Nw2vo6xULjxxKuvBR3p/2qKe6zsWlhGWdLcCgTGMEe9USSUvAlILQanCMq03E4R/O/dnZE3Ux5oOA/6zHdBH38x9Cz+61ssyeQIPt4F+vEuBP/3r+CyKxEkBgo3nnj1NaFUXEU0EgB1xT1Gdi2sbyhn/W2auRrjCQklbwOcJChTo/Bl8r9Lcfli6CON+0Ojf7sXwQj88PkAACAASURBVPQcBP79vy0/KhYK1+hZUCx92szxyciUGwtKinsM7Vqk31Dcfwc2I6Hk7YCaVeMQC6Uq/3vEhXzkR0o44W/xiis96PyHm4EnfgZX6RTTj4lVdITes6BY+7RZ40N5Hvj1i7oU95jatdgAnlIcaOhHTbMXC4rTsLw0E5zDobF2IaHk7UAsrBo1/vdwSAshb/sV8K9fcUws2/DkNxB85t/hmjhR9TI1azieoyPiwafNdDvuq9SluMdTiKEWeErx1IeN+LT1Cvw8sPNcD+YVpuPxm0rGhKJPKHkbEBOrRk+0jNsDXDcvQg5Xbi6CT/1f4PGvOSebXfjBV4H/9z+KP8faGrYEh3zaVixOo4o7nhdRO3GgoT+k4AHAzwOftnpxoKEfK6dEj67FLBJK3gbEhDNFurC43EBWDvCFewFCQOpqFeVwFRVhwusfoeP+LwLdbY7J6DTiwRo2DQd2f3ZYnOGKm6cUVWPURWEnapq9IQUvws9T1LZ4E0r+akK0rRrNhWXxKtX7XUlJIPMWCrH4YxUGreG4St5xYPdnp8U5ll0UdvvPFxSnYee5nghF7+EIyovSbJDWeSSU/BiG5YUl3hKkpMjOU//dgDUcb64dJ3Z/1c1XbLM4x6qLQro4VZ7tQU6qG/ctLMCKKVmmlP3y0kzMK0wPPdPDEcwrFBaPsYCEkr+KIbMm3R4gEEcK/8lXVH82Yg3rde1E09q3c/fHU4ozHUPM394904N3z/QAADI9wC+2TEeGBlmgky4KJyNVpItTkAKd3gCe29uMBcV9ePymEsPP5AjB4zeV4EBDP2pbvCgvGluuq6teycfTFl4P7JSXGUY3ZyHw/X8G+tmVvKKG5/8TrjT17bAha1iHayferH0tBHgevzh4GTvO1em+p98P3PlHOeNo+UQPHrt5GpJcLgDOuSicdgOxFicA4DG6E9lcUGD4uRwhWDklK7TA8ZRi/6W+MXFecVUr+bH2UTshr9Sa5D/ZBzpknOrUNixajYLvPYOunh5dl+u2hnW4dpjW/oka8H/6DbjPf8VgR5zBgM+Hr/zxHOzeb9W2+fGFPwjFYv6lPAPryiY54qJw2g3EWpxEiDsRq5krY+284upW8ga38PR4DZCSAgwNgcxZEHWrPyrRJHrj753Aj34B16RJ9nLYjECXa4fVd8oDlf8DvukS6JMv2y6XXgwFAvja6/WIxv7q57UD+Hntadw8JQnfWVmMT1sHbXNRqLmBlpdmWnbjiP7z2pYrCNLI3+w6LB1r5xWOK/kHH3wQKSkp4DgOLpcL27Ztc7pJ/TCzhR8BrfoA9Lr50bX6o8EXwrR4PUBSMnBlwJ42pFi0GuSrDzmi3EXocu0oHURTHjh9DMMHdwMO1CfVwtHWVjxe2R31dnde8mHnpWa8/qVrkcKYGzO+dSU30PzCVFusY9F/XtXQh1990o4ubwA87D0sVVqofl8r1GaNN9dNVCz5H/7wh1Gt8aobrI+acKBJKaA8D8JxcutZRCAQ/ZjsKGTWKlm83LeeAN/UBPzoAdvaAgA8+xu4crWrRdkBLddOqO8nqgXq3XD4fRiuPRxVJc9Tit9XncKfzketSSa+9Ho9/uPvpyEnJSX0N7MuC6VIFQrYZh1zhGDVlGysKM1y5LBUySXU2OfDC/ua4s51E3+O5yiCVKwAZs0Dwq0UygMfvQ3+5ScFLg8194VoRUcJIXk9HuEPDmTWihYvue+7IGs3gdz3cGi34iopAX76B3saWrEO5Of/HTUFrwdi37HuswLHTzg8SUguj16dYp5SfO2/Yq/gRfzTny+gb3g49G81l4UaREv74VWTsGlmDh5eVYzHbyrB0ZZBRTeOWYiHpf+ytAgrTYZPsiAuVB6G9tQ7DtEEoVRqstiLBx98EBkjRSHWr1+PdevWRfxeWVmJyspKAMC2bdvg8/lkz9ADt9uNgIlKR5Tn0f/bVzD419clxTmSkf3QD0EpRd9LP0JE1XnJNSkrbrRdLjV5hw/uxnDtYSSXL0HysjWm3EVW5KI8j673/weBX/7Y+M3uJOT+xzvwqETO2D1mRkF5Hj1PPwLfsSPCvHuSkTS3AvlbX0KQZ5zoOYDXdh3Fr2r6otKWEez51ipwhODHH9Rj+7EW2e9b5hXh0ZuvBWBsHj88044n3zsNX5gjPcnF4YcbZ+HGmTbRT4/AjveLpxS76zvx/6ou4kL3oOz38HGIhmxq9bMdV/JdXV3Izc1Fb28vnn76adxzzz0oKytTvL6pqclUO/n5+ejo6DB1L/+7V5mZn2TtJpB/vJ9N6TvCC6Plk7cil5OwQ67gwADw6FeAgM6FeeZccI88rbkoxcOYCYftkf77gokToyJX3/AwvhwvJrwEt88AvrJ8NvZf6sML+5pkvvWHVxWH3CtG5lHq/hHdOE64Pex8v9jjANw6awIGA9TwAbJZ2SZNmqT4m+M++dyR7Xh2djaWLFmC+vp6VSUfE2j5uikFELYW5uQBX/oquIXxHVPvNFwZGcDP/4RgW5t6QfDUDODO+8EtuWHMjFcsybfujlMFDwB/OQvcsThgexaomYSjeKD/lY8DkOpx4a1T3QjQ+AivdFTJDw0NgVKK1NRUDA0N4ejRo/j85z/vZJOmoBZeR6urgDPHIl05fUIM91hRWE7DNXEi+J//N+h//Aw4sDPyxx+8ANc049tWQDnxS09C2FhLchPBUwpHt9Y24F/fOY+fbp5pexaoNOFIDfESqy5dnFJcJKTggfgIr3RUyff29uK5554DAASDQdxwww1YsCB+KsdEKIJV64Ab1svYGynr4JUPCrUwr3JLXqpIuXu+BXLfd2x7Nivxi3zjMdCfPa2aEDbWktxEiIor3nGhX3BbGlHKSjBrjcdTrHr4OLx6sCWk4EXEmrHSUSVfWFiIn/zkJ042YRosRYBZ80AkyoImJ7Mf0NczNihtHYLTilQx8esvv9VMCIsXCmKjCkxUXFcLrFjjZrh1xPmoq+3B7AmcI+6deGSsjF+zxmGo1mVFmBL76B32A4KBqIZPxhu0xs8ylBK/Pv1EOSFM694ozleA5/Hw3y7gJ3ua8F59D17Y14SnPmwErxLnoMS7Ml5hNgwTEJSpNISRA9DS78P+S32ycRYXlBf2NWH7sRa8sK8JD//tAl450My83iyk4ZXxwFh51Sp5LUWgmAQlwuUGbWsRuF6iFFYXV1AYP7r7XXvGo6x8NB9AhCcJmLeI/ffwhDDmvR7Q5BTwv3vV8TnjKcUjf7uI893DEFsRFNgVVQXGUlzxiAUT1Rks9ULNGteCVJkSCKERNS1e5oLKWlDOdw/j/bO9uhZgvVDKA4hlYtQYeKUcgpISEZWFWhIUIYJf/mQN6GsvgH/5SQQ/3hsVBRI3YI0fANQdHU0kswDFxK/b79ZMCJPf6wGSUoGdbwmL0MicOTVPBxr6caFnWPZ3Pw9VBSYqrnjHD26eastzWIuaXtdGuDJdUJQGjozGv7F2BGq7JLsTmLSSsEQGy1cPtti6i1CCa+vWrVsdbcEg+vvNDXRaWhq8XgPZcUUloPV1QE+HEDkjpu9vuROEENCAD6g9FBlVw7mAyVOBgb7RtHeeBzpagCNVwIUzQO0h0Po6kKVrQAgxLleUYFkucfw6WhERXkop0NMJFJeCTCo1Ldvg4CDI0jVA8RSQ9AyQDbeD23InOJeL+ffwcwBCSMQ1uLYMqD8uUFEAI3PWCjo0CHJ9OYhOK0vvmP21rhv1XXJudw7A5+bkojSbfc5DCMGaaVl4v64TQ3FsJ9xVrl5cXYTWeE3OSkJd+xA6vH7wdNS1cWd5ga45IYSgNDsZJ9sHcUYy3jwFMpNdWDJZSMT08zwONfaDV9Cn0uudgug22n6yC6c7h3CosR917UNYMy3Lkr7IzFR2B121Sl6qCGTKgrUIzJ4PTJoCXKyXPzBc6fd0ghaVAM0NCOzYjsDQIFBUoluZRAOs8aI8D3pkP+gHbwmLnIrMhBBg8Q3Ah2/Ls4H5oDCm883RAIiyEUJAJpWCzF8i/HdEFqW/S+UTr8GRKuD8ackVFDh/GvTcqdCCrFcuLfh5Hgcb+iHV09MmJOO+RYWKbYkHg+AIznXLdwLxgPsX5mBmgT5FqDVe4qJWmp2MzGQXbi/LxZ3lBYZdGywF7uEIbi8bXVClC4oUHIDbyyZgSk6K/McwiHVv/1rXDT/PY3JWkqHvuqqhH9tPdoV2FTwFOrwBlGYnoTQ72RElf1VTDaslvCixFtLqKtADO9XpeP0+IcRyoBdDfj/geSfuQ/hMRcvUHgQGGS8k5zJEmiYNxaTr/85kLxSgwS5pd9TN8tJMzC9Kx9GWKwhQwV88LScZz22aqqjApJEmbg4IxKE1v3F2oa3PsyMMU09iVng8+6luHjUNXbjQO2qcUAA7zvaplgi0IzY/FkXBr1pLXg+YFqPUwne5AWn6issNDHmB4AgNwoh1b8WFYTek40WP7Acqt48qQh0y0w/eElxUUuTkgfvyA7osnNDiUrldsLZrD8Ffdwz8olX27XxCriU514qRXYfed0y0UKfkCBbq38/JxX2LC+FSWeBZFp6bQLYbiCX+eMdMuA0YKWrjZdUiDofeHYHo3lk/twSu4BAONgxEfLmdYRY1C1pWuB5o7TqcsOTj06yMY0hZGvHV7wpWa/hBYFZOpC8fiHoIn2GYCTtkHb663MAX7wMgVJnSOoxmhWL6jlXbFooZ2iXkFgDzFkOwq8NgM1WzCKMMiCwLL0CBhcXxsdn+4x0zQ6UBWTBymBgezqg3vFQLRsf7aMugrKiIVmSPlWggEbEIsYyPN2iMQermoQtXRNZJpTzwqxcd5X23HSa46hXpIBYs0+/6YS4uw7YUQpG5oDweID0TGPYKh7AOUDWbhVISzfprJ+LrSzl8fXtsMmG/uiALt5YVa3LIsNwYP/0Cmz0yHrJVzSQt2ZHoFIui4ONSyUebt0Sm9Hke/N5K9VJzcSK7CF3l8aT3qJxb6M44ZS4uyaYXxPDxo8nJQF3tqNvM7xcOyG/+O5DhQfXC31GGml+ZIwR/+cfrsPNsF/7PwfaoyLN2ShK+tWqaLveMktLeXd+JuRPk18dDZSUzBGt2kbLZcQ5hBI5TDRuFVaphpvUWg0NPkao2+fwpDF9znS5lEk3ZWZSmLHpdM+2qUTdzd0VWlpL1mePgmjoD/P96VrMcoHRBRPmySF4bwgmHq1Ks2QjXlx803C+nKZDF6Bo1C4+nFE98cBGftspDNO3AnFwOWzfMUHXNSPHqwRa8Vy8vvL5lXhHumZ8j+zuLnleEh4PjRGPiPOoZbynM3GNGNqOIKdVwtBEvvCWidZ+9cbPuSYu17LbR6xpw/RCOE0jHnvkucPkCwPMINlwAfvY0qMrixuQeKiwBWhtH22UpeABIiR2PiBr0WHgHGoS4ajtRXuDGY7dcY0ixh0PJjbGkVK7gAblFHA4zrhuzJGdmLOpoW+F2YNwp+agUu3YKY1n2MBh2/dQeFJSzuKkMaC9uzAXx8kVlxR6OIXkln7ECpczNTTNz8C9Li6IvEJTdGGuuzUNXZ6fs+nC/9O9rO9DYF5lnYSSkMBqUw1Z562PNez/+lHwUil07BptkjzWXupKvXlEGM4sb6x7KK7toRHg8IGVj4F1QAMtqTnJxMWU5BIB1M7JC0TEbZgpFtNUUmWgRA2BWmNLbH6cPca0uIvHAex/7EyebocR5gvKlukL6Ygk7CnWLbgz62gtR4WlRAuE4cItWgrvrAXCLVqovMlo8QnrvcXuAkmmRnDXpWaOF2j1JAp10HETTmAUrBK+iJEvx8M8KT4qee0Ul9uL+ZtS0eHG8zYvKev21aZVCCpeWZOiS246wRjVYYcq04347MO4seZYVifKlmoUm4gGGLWAGYu3XNwO5eycZmDVHPbJHySX0jccEzqGwuQ//d7xE05gFKwTvtoprmG4RK1ak3nvVlNjmggJT/VlakoFnPrqsS26n+dutZqjGIsNVCseVfE1NDX7961+D53nccsst2LJli9NNyg4Q+U/2jRnFZ+Xwk/I86K73xpxfX7q4ZS1bg/4ZZarKWHVBlI5fjGq1OgXp4Z+SwrbiytB7r5oS22yyP/sv9emW2+5as1JYXUTioYiIo0qe53m89tpreOyxx5CXl4d/+7d/w+LFi1FSUuJks3KMkwNNNYSiTU59Kv9xDJxJhC9uKfn5GNARkRTLYttjAVasSL33OqHE9LQdfph5y4wsrJuRhaOtg7aHNVpdRLTulx7K3paXZ4vc4XBUydfX16OoqAiFhQKp0cqVK3H48OHoK/mxfBirEyE3DR+M/IFzKfr1KaVobvSjvTWAgkI3iks8ccWUmYA1WFHAeu91wpLWajuah5lWM1TV7mf146NLXnxvVaGt/XBUyXd1dSEvbGXKy8vDmTORhFaVlZWorKwEAGzbtg35+exUaC243W7Fe+n6v0PPwV3wHTsiWPCeZCTNrUDO+tsiXAKU5zF0YBd8tYeQVL4UKcvXWvbfqsllJ3rP1QmMlxJ45i/ChMdfkPXD5XKh+oAfzY1e8DzQeN6HlpI0rL+tWODTpxQXzl1Bc4MXxaVpmDY93ZYFQM8Yi2PmxHxYQbTm0ihEuXhKsau+A4cv9WLJlGx8ZsE0fHTJi+rGXviCFEkuDhUlWbit4hpNJXJbXp7ue3/6hXzsru/E4YYeLCnNwZpr88ARYnq8tNr+8Ew7jrV5I9w5x9oGcaKH4MaZ2u2ZkWtzQYFu95Pe+1n9qGnsw4meIl390IuYH7yuW7cO69atC/3bbEahVqYYvf97ICP+Wzq7HD6eR9tj3xB+XLMBZMHyiMPZoQ/fQZ8Nh7NOZ0mK4KfPBjzvyHYrgeU3o7OrS3Z9f29KSMEDAp9ac6MXn9Y0o7jEg4O7r6CzLQCeB86c7MPxiW4sW2NN0UsTmJTGOD8/H+1tbbqujSbsmku746bz8/PR1t4eYRW+c6IF8wrT8YMbJ+NQY1qEFck6pGXhe6sKcaBB371lORR9/Rx2n25BX38flpdmYmJBgenxUmt7z+lW+CTsYr4gjz1nWpg0ClJE7ZvUmGdWP4YN9CMcMct4zc3NRWfYS9HZ2Ync3Fzb26E8j8H9H4I/uEcxLlz039KK5aAvPwmcqB5NvqmrBZ08FWhpHK0eZPBwNuax6QYTkJobvDKiTJ4HLp4dBqU0pODFv3e2BdDc6Mek0tH6nkbdPUYif8ZilJAeOOVqUDooPdQ4YDpDU292p1GCMqttx8Nhphb0zHO0ch4cVfIzZsxAc3Mz2trakJubi/379+Nb3/qWrW2I1mHf6WOCK0YjPJJWVwEna0cVPCD8f+MF+cMlh7NKilyt4IaRflhZJIyGXxaXpuHMyT6Zou9sC2Kgb4i5AHS0BkJKnlIaYe03nvfhkpa1b+QAfJweljuVvBOtUD2WdWqUoMwqnI6osQNKY1LV0AcCgppmL8qLUjG3MB3HwvqhlvNgFo4qeZfLhXvvvRfPPPMMeJ7HTTfdhNJSe4tmGLb4TtTKDyeV4HKDtrUIIZgi+dXJkfv37gC9vnxEsSrLgI3anjxTVZkYMBJtMm16Oo5PdKO9JRApCwWGBikIiVwHOQ7ILxx9XZob/bqs/QgYOQA3cG2sd1FG4JQyjoZ1q2Sd5qe7mX063NCDuRPY/DVWEAu6XqNQmudffdKO3qFAaPzmTkzDQ6uKcbRlUDXnwQoc98kvXLgQCxcudK4BBYuPnqgGDyr/8MvKgb07lBU95xJ+I0T478ka0PrjwMTJQNPFsFquQeBENfgjVSAnVaxOPUo+Bq4JQgiWrUnHgV0D6GiVj0VyCoFvmILnBQWfN1Fwx4hobw1oWvuyNg24lPRea9cCaRZG/etOKeNoWLdK1ulnZuXAw0E3QZkd0HIlxZovhjXPbg7o8gZC1b7EA+MNYbxDTsgY84NXy2BZfG4PcP4MaNVO+YdfsQL0+nLg+BH282bPE/5bd3S0upNIfiUt80cpsOc9YM1GayGaMXJNEEIwdUYyutoj/fMcB5QtSAEhBB2tAeQz/O0FhW40nvfJ7gu39mXtGXAp6b02lr57M/51p5RxNKxbJet0KMAbIihzGvHAF8Oa56wUFzq9kTtnP0/x3pkeRxehsV/jNVRztVOwrj1JQJGEcjasXik3eQrI0jWgw4PAuVORz/Ikgdz+ZZArA+zapSwUFIHb8uXIuq8jVie35U6kp6dr1mykAZ+Qeh+uMT1JIBtud6wmrFhLMiOLQ1dHEENeHpSOWu3Xz09FVrYbhZM8yMx2yfzsSvfNnpeievjKrJurIJuea+kHbwm1YcNhoG6rEUjrb5qp+am3HqkZucQapksmZ6A0O9n2nAe1+qR3lhfI+pSh4913Alrz4kQ9aClY81xRnIZDjQMR4wcA7Vf8ONUxhDXTsnTpCxbUaryOeUtetPgyz55A74HdQEoKcPRjVcuYcBy4z98DvqmB6Q6goHLLnMVuSAiweqOq1Ul5XvDpq/iLzVRlsgui26a50a9otdt5n+2IYaKbWf/6WOQkB7SrV8VLn+KBLwaQzzNPKSrP9qGm+UpEgfYgNcb3YxRjXskDgqJPXrYGePtPkVv3cEg+fFV3AEvpzpwj3FhXK1jcnAuYPR/cwhWh50kPPSnPo+fpR0CPfaLqL7aDmMwKCCGYVJokC49savDh0jkfKICp04Xfw5U4675oI5YL5FgI5bMbRimFY4FYzYvWOYDoUvvRzgbUSFgyjfL9GMG4UPIAMHRgl7KCd7mZH75SNIqS0gVgSBHT6qqRLFttf7GeyBi7aQhCz2vxw+0m8AcoCgrdoJTiZO0whgZH95WdrYO4dM6H5Wsz2G4Tk7Kx7lO9nhFJE6sFMlqhfLE+RBRlCPdzezhBaa0ojb3lLoUd82J0zPWeA3CEYOPMHBxv80ZtERo3St5Xe4it4AHBzWKwlK3iAmCEEOtEreAmCofJA1WjcenhyjN/olDWraMtiPyJLlBKsWfHRfR0ycer4ZzCGALoaA0yQyRNxcyr3Hfr5xToKVQiabgYEJVxhOAHN07Gb6vb8UnTFSyalI67K6z516Vw+hBRrzJzujiHnbB6CG1mzI2MT7Tj/MeNkk8qX4qhD99hK3qeB84cj362ZFk5ULUzUtGb9BfrjUsX3SwnaoYwPERBKXDp7Ohzwv/fDE4dG5RZ/t0dgYh4e54H2lsC2PHXXmRkujB1xqirJ3zxcbuEkMtQVOpIny6eu4KMbHnbZiJpnIyh5ymN4D1vHfChoddnaxSHHcpVSZHrVWY8FSJA4sHPrRdWzgjMjLmRc4Box/mPGyWfsnwt+sJ9s1LEIFuSVKyAZ+4u+ESfvAV/sVpcenGJB82NfrS1+NHbFURfD89+iA0Y6KMY6BsdXzXLf3gQGB4MorNtEJfODWPZmgwc2uONWKyk4HmgqcGLWdkMRWww1NTpGHqzCtiIK8DqIaKaItcjv3j/UUalpfF6/mBmzI2eA0TzoHrcKPlwPzrd/S5QJ6HdjQG1MOE45Dz2HNp3vGW+0tOI5esdYCdvtVz2oa3Zh6FBwx6pqKKjlcc7f+rTlJHjgEmlaQCG5D8ajKRxOoZeSRn8vlYgv2Ipb6OuAKuHiGqKXEn+8Lht8X7pmuzmEHdUAnbBzJjHM9VCfOZ+m0Sorui3twLXh9UAjWLEhaJMemqdSiD6rKsPeJlZqQAwPAQMeuNbwYvQo+DzJroxdXo683fDNXDVLH8bsKA4LVSbNByNfT68sK8JT33YKKtNarTmp1INVL3KQ80qVZL/01ZvSHbW/QAwd2JaVJOLogkzYy66YB5eNQmbZubg4VXFcTM+48aSD0esQxLtgtQPDwih+UkpgitkvCA5FfC4ARCCIM/j/NkBZGZT2aGt4Xl1OIZear2Fw0y5PNbW3ar/Vs0qFeVXi9tWun/jzJy4UGBOwOyYx1OuQDjGpZIHxkdpOJYfnlIgGGBfP1YxPAgMAwAo0Eex671WcJygjyeVelC2IBXciCI3Mq9Ox9CHK4Pf13agsS8yksqucnlmlIfo969uuoKS7GQ09g4zE5i04ra/vqTQVjdEPISD6kG8KmwzGLdKPh5hNJZciR8m/j4J+8Hzgivq/Bk/Lpz1o3SaBwVFHkO5AdHY0YnKAABe2NdkW7k8K8pQ6vd3E6A0Oxmz8lOwoDg94llacdta5euciCUfSxgLi1ZCyUcJZmLJi0s8uDTRHbqH4wTOGCejZ+IRlAcunfOj8YJfV/x9OKK1o9OrvPW4AqwqQ6nfP0CFc4IvzstjWqZasrOsWrtjyUVe+nhWllKMlUUroeSjBDP864QQLF2dhpO1Q2hrCWBikRs+P3/VKXkRYvz9iZpBlC1IlcXds3ZH0SpWbsSPq+UKsBobHw2/v52x5DXNV7CjvjfulaUUYyVBLKHkowQz/OuU0oi4cu+ADxlZnKygBwDm38Yrzp32oanBj+sXpKDhnA9d7UHwPNBwThifCXkuFBR5UDTZHTF+ejNxzcIuP67V2Pho+P3tiiV3c0CKm4wJZSlFvBChacGxcJM33ngDX//61/Hoo4/i0UcfxZEjCvztVwkKCt2QuoK1+NdZ1v9AH4+MLC70LI4DUlLJVaPgRQwNUlRXDaKjNRgaH0qB/l4el875UX3Aiz07BtDRyt49xTNYoY0cgJZ+H/Zf6pOFZUqhNwSQpxT7L/Xh1YMtup6rJaOeWPK5hekRZ0pBHth7sV9RWcYz2GOAuEsQc9SSv/XWW7F5sxO8amMPLP+6tNqSFErWf26+C7PmpIQofimlqDk4qJhFejWC58F0a2ntnuIBUh85gVCupqbFi+NtXk1XRjT8/maSfzhCsH5GFmqbr4TK71AA3YNBuIgQuiliLGTTLi3JQKrHBf/waA5LqseFpSUZMZRKjoS7Jkoww7+uXH3JE0HxSynFpXM+xYSpBEZBiPruySiciK4IV9LvnenBp63ekALU68pwyWRf9gAAIABJREFU2u9vNpa8tmVQlj3LA8hPdYdqn0aDNdIOHGocwJXhyG/uynAQhxoH4spd46iSf++997B7925Mnz4dd999NzIy5CtcZWUlKisrAQDbtm1Dfj6bgVALbrfb9L1OQiqXkZoAeXkULY3NaG70hijsiyenYd6CYtniMHdBCnbvaE1Y8xpwuQnmzC+Ey+UyfK90LnlK8cj246hu7IUvSPHh+V5UlHjx3Gfn2KJgNhcUoK67nhnDfqqHx+aF+Uy59KCulk04Fv5cvTIq7dVZcq2eJYyTL8xsT3Jx+PbaGeAIweGGHiwpzcGaa/MMhYwamQej48VTil31HTh8qRdLpmRj7bX54AjByZpuSM2qIIC67qChMbQimx4QSs17c5966in09PTI/n7HHXdg5syZyMoSVrPXX38d3d3deOCBBzSf2dTUZEqW/Px8dHR0mLrXSViVS4wO0bL+az/24tJZH+MJCUiRmc1h7cZMXdE54ZDO5f5LfbLYeDcnpPxvnJmjaE0asTr3XezFT/Y2R1QXJgAevaEYq6ZmM+XSA5bsHo7g4VXFtlmhLLnkvPSC1W4lksZoX4yMF4tHX3Rr/eZIG7bXdcvu2TJ7Au5ZVGiqL2b1xaRJkxR/s2TJP/7447quu+WWW/Dss89aaeqqhd7qSwWFbjSc8111B7Bm0N/Lo+qjfkydkYyG8z50tgVNRd+woisCvLrvXKo0dtT3YEKqG/cuKsDKKfIqS4rTaXGjoOVT17MQmXGR2EGzK223uolFK2FPlIuaW2swwN42K/09VnDMXdPd3Y0JEyYAAA4dOoTSUmcKUscK0Yq/1oviEg8ysjj098bXCxav6Gzj0dkWSQAkHso2NfoxWcfBLCskUISSj1uqNHgAnYMBvLCvGR+c7ZMtCkdbBmWKno78fdUUBum+Tmhlsmodylo5uLUSaspqtyQ7GW4iJH2JsOvgVi1MsqI4HR+e65XsIIAFxWyCvVjBMSX/n//5n7hw4QIIISgoKMDXvvY1p5qKOsxWQnIShBBMyHMpKnlPknBoO8xg8E1gFJQCJ6oHMUnHoq1GUAawrUklVsdwUrDw6+cXpuC9+shrCYD5halGusWEkrLVcygbq0QgVruNvcMozU5GY5+cn8cq9BC8xSO9cDgcU/Lf/OY3nXp0zGEme1UNencFWtcVFHnQeMEvO3ydWOzCkhvS8dG7/RgeSvhztDA0KFTXIoSo1p6VRsEcbfFGRI6wrEl16z9yUeApxZ+Oy32+FNB011iJNtGT5BOrRCB2u8Cs/BR8cV6e7ZWW1BR5tCs8mcVVFUJp1MWidL2Z7FW1NvTsCniex54dA6HYb9Z1SrH4S1cL1xQWe3CuP3E4qwcnaobgG6aatWdFa3h5aSbzQFFq1SnR+wLyReFAQz8u9gwz5VNz11iNgdeTMWu1mIlZKLW7oDjdEdZILUU+FtgqXVu3bt0aayHC0d/PLp6ghdTUVJw93YtzZ4bBB+lI+n8kh8nB3Vdw7tQwerqCaL3sR1dHEJOnKlvNStfzPNB62R9xyEmIkKTUfNkf0X5aWhq8XuXMveZGP86dGo7I2hzy8sjIciEz2xWSZff7AxGuGNZ1hBBMnupBRpYLSUkEM2YnY/a8lFD/8gtdqK8bVjnNS0BEIDBKE0EpMHiFR05uEpJT2LkIhBCsmZaF0uxkZCa7cHtZLu4slxf1Fq+bkp2EUx1DGA7woBhdFO4sLwjN11/rulHfJfevEQB/PycXpdnJACB7x6oa+rH9ZNeo358CHd4ASrOTQveoYXJWEurah9Dh9YOnbNn0XKP17puBnnal4ClFVUM//lrXDT/PY2ZRDgYH9RdkIISgNDsZSyZnoDQ72VGXrNkxy8xUdhGNC0ueUoodb43Gk7OsXKMuFjFsMbzIdEercL3UYiYEcHuAC/U+Wfta0LMraG70M33trN2DWjQOx3EomepBw/n4TuuPR1AKHN7XgZs+k6H4keu16jhCsGpqNlZMyYqwEJeWZES4WMqLUpmunWk5yap+X6uuFD1uiFi6Km6ZkRWiYNhwrTCOSu2ydjUfXfLie6sK486t4hTGhZJvbvSHFDwwqsBP1AwiEBTCC9tb5L5qNRdLW4tfFo5IKdDeIiwK4dmrLteogg9/blOjXzP5STmrdXRq2luVq4TkGczenFjsweWL8rFIQBtXBoI4sGsAU2ck2xJNFb4osJTR3MJ0zJ2YhmMjXO8EQEYSh8/PmaD6XDtcKXoWLK1rRG4cs5z40jMFALKYdY4QrFCRkXVQW93YhwMNaXHtYrET48Jdc+6M4FIJB6VAd2cQvd2CqyUYBAJ+GqG4OQ6YMTs55O4IR2dbAN2d8q15XoEbE4uFDzwz24XCSR40X/bL2geA7o4A5i6YoLo1zMji0NURxJCXB6WjfvRwNwsfpGhRINXy+3iUTE3SrXBY7aVnEvjYrt8EJPBeoZquPjNguVg6vQHcuSAfK6Zk4lTHEIb8PIaDFIcvD6CufQg3TBU42Lef6MSgz4fJWcJ7MDkrCSfbh9B+xQ8Kseh2uqpLw27wlOKJHefx38facbpzCIca+1HXPoQ107I0ZRAXvO0nuyLu9biA/6kz5ob6a103TndGuryClOKKL4i112jLEm044a4ZW0VPFZA/UT1FXYm9UY0gLBBgO66DQfnfCwrdYL0rQ4MUF89dUZVN5LSpWJ6GqTOSULE8TXboWlziUeRb6WoPGmJVFNtbu6EIU2ckYcGyVMyck4KUlPh62eMZTrBZKrlYjrYMgoCgdygQOqj188DRlit45N2LeGFfE7YfawkVDg/wPPZf6sPF7qEQ3w3PI+o81Aca+lHd2BthQasVLJfeywrP3FHfq+iGUoJSsfKjLV5mofXxiHGh5PWAUiAn16WqTMNRUORRoAaWLwrFJR4kKyjJpgbtVVn0o89fnIZJpXKrXFTM+YXyxUx0DRkBIQTTZmRg3qJUNJz3o/bgIIYSoZWGIBQwsU/Jq1H3MjNrKXCxe1iiCK/gkb9dxAv7mtE1NLqz5AEcaxvUpWDtQk2zN4KfRpBRH32w0oIHwBS98bzCdLgknycP/YuOHlihbXYa40LJd7Rpsy9ynKC41ZRpOIpLPMib6NZl+RNCULYghdnmpFJ7QsoIIZg6I9kwJ70apIfRCRhDe0sAvE2Dp8YBz1oACCALwfTzwIWeYTA2m1HnZ19QnIYkiWbVey6gtOBtuDZbF09+OMQD4nmF8nbtGhPRvfTCvia8V98T2lXFi6IfFwevrMPLcOjhbpfCKDXwpNIkNJz3y2LUp05PR2enPWmmZjjp1cCK7ElAPwa9QmirSHZmBWrRKqyEnJKspFCGZ+gZkCt+EU7EsKslXC0vzURFiRdHGnoMZ4MqJSCtmJIli0jSy5ejVqzcKuK9DKAlFkonYIaFklKK6gOjETaC8nOh9JokdLYFdXG3G2lLKaGKxRhZUFBgKzumXlZKLeTn5+NodROqD3gTit4iFq1Mc7wIiahQw8Mtn/nocqTiz05CQ88wpMdJHAQ+FTtrpqqxM4pt5Obl4a3q86ZCLKX9tRqe6QT7pYhXD7bgvXo5G++mmTn4l6VFhp7lBAvluFDyAJCXl4dPa5pNKz892bDS7FTRklbz7UebAllvVm9+fj7a29sj+pOAOeRN5DB1RjI62oIRFAhOE9iJivBUD4/rcjiZ4ndzQE6KG/cuLFCNJTcDPfS+0Xr3tSgcxN+rm68g1c0B7iTMnuCyLa7fKNWxmrxxRzUcT9BLycuCXmoBuzlr7IZR4jSpSyqv0A1Qis62IPImuiJoeMlVVCjcKMIZLYUxd4FShAqMO0VgJ8apb144qhiilaAUL0WstSgcWDuOhaU5uHveRNsqSRkhKrNKOWEG40bJW4Fe5W0nZ40T0NsPSinOnx3AuTPekJUZ/vvkKcJ/J5UmRSwAl84OhxRXAmwIUTdBxt+E5LyyBamOxmZHi0slVtw1Umj5w9nJUL145G+DoTMNq4qWIwQ/uHEyflfdjo+brmDxpHR8uUJOaaFHXicwLqJrrEJNeYejoNBta3SL3dDTD9Ha3/1+Cy6d9aH6gBcHd18By2sXHto5uTQJy9dmoGJ5GqZMd8NE9byrHudO+xTHeqxBLRoomlDbUSj97gtSXOiRhp+aD6fkKcUzH13G26e70djnw9unu/HMR5eZ0TVa8jqBhJKHfuUtDasEgKRkoYRcPHy4evqhZu1rQVT65UsysOlzWbhmlpAfkJFNULE8BdfMNBflczXB7iSqWEGMBnp41SRsmpmDh1cVO+pyUIJafoHS7xyRc/RZUbRq1rlReZ2AJSVfVVWFhx9+GF/60pdw9uzZiN/+8pe/4Jvf/Ca+/e1vo6amxpKQTkNvTLzow16wLBUpqQSECFmtNQcH48JC09MPvbsWLXAch7kV6djw2WzctCkbJVNTMKciDQVF8bGriVeYGet4hega+pelRczShXaDlXCktaNg/T4jLx1uiahWFK0R6zwWOyBL3DWEEKxatQqXLl1CeXk5cnNzAQCNjY3405/+hB//+MdYsmQJXnrpJWzatEmXL9Is1bAVWlMWRe91c5PRcjkgoy4mhGCgj8fli34ZFW3ATw1TDdsJQggmTXEj4Kfw+ykmT/FgwdJUcGHmPR+kMppkFoePGKWjRN2s1P7kqR74/RQ9DN6fBNT5kswimu+YERiRS0oHLPLwhP/O4rNZe00W1l6jTPHMooD+7vrZqLnUZYiuWA1+nsehxn7wkvKDt5flyjh1pPJsKZuA6ROS8fapHlM0yCIcoxouKSlh/v3w4cNYuXIlPB4PJk6ciKKiItTX12PWrFlWmnMU4dE5WlEqLGuYUsHnChijGrYTlFIc2uMNye0d8KG/jw/J0dzoR3uLH+mZHAb6IgnRwq19K+UNCSGYsyAVA31B2QHk1Q49yWvxVjs4GtATcaJ1YKl22Cw9jHZzHB6/qQRVl/rwfn0vAIG+2CyMlgFUKjTjFA2yI3vrrq4uzJw5M/Tv3NxcdHV1OdGULhj9cLSiVLQybMOv16IathNKcjc1+GTZuBPykpCRRVFQ5JGNh9VQUcGtlYETNYOhhe9qBiFCcp4WRXE81g4Oh5WSgmr36ok4cSJks/JsXygL9nibl1lIXQ/McutHiwZZU8k/9dRT6OmRZ3PdcccdWLJkiWUBKisrUVlZCQDYtm0b8vPlJdb0wO12M+9lFRRpKUnD+tuKFT+c08famH7rgV438ivykZdH0dI4+kwQyE5yxOvdbjfy8vJw4dwVNDd4UVyahmnTnfloleRuboBMafd2+1G+uBDTZmTofo7Yfykopcz+rVlHMTwUNk5XKVLTXZi7IB/TZrALjojjd+pYL9pbRv31PA90tgdwpS+VOU8ilN59O8FTike2H0d1Yy98QYoPz/eiosSL5z47R1GZiXJp3VtXKy+M4ucpTvXw2LxQ6NfqWcJ94aRnSS4Oq2cWGe672+3G8R6EePqF9gQStxM9BDfONDeWmwsKsNnA9ax++4J8RL/tgKaSf/zxxw0/NDc3F52dnaF/d3V1hfz1Uqxbtw7r1q0L/dtshpxSplhTg09WUKS50YtPa5oVrdKM7AA4DrJCHhnZgVAbFcs9KGpMYxYNEa9Pzw7gdF03Du5uw/CQwGV/5mQfjjtknSnJ7ffLdx3BIMW5M13IyJbz6ujpvwip9Snt3+g4CRzsopuIECA9i8A/TDE8BLjcQHB8nEfK4B0IYveOVhyv7ZTNu3T8pOCDUJwnEdHILN1/qS/EQwMIYYhHGnrxVvV5LC/NZFrpolxq966ckoXZEzi8w0EWc39dDhfq15wcYO7EtAiXyNyJqSjLoYb7np+fjz2nW2Usmb4gjz1nWjBXvSYLAGu7GhGsfie5uIh+60XUM14XL16Ml19+Gbfddhu6u7vR3NyMa6+91ommNGEmgUkPEZjUh9/fx0uud+HS2WF0tEYePDmZJaskd+k1HnS1D0YqbZdyfL8RIjQt1450nJR4d/Z/1I/O1vHrw5eOizgWF88Oo0Ol3/GSh6HkLqlpvoId9b1Mf7rWvaKrRY9P2+5yg1aSuezKWmX1u6Iky/ZIG0vRNYcOHcJTTz2FpqYmHDp0CJ9++inWrFmD7OxsDAwM4Je//CX27t2Le++9V3WlCYfd0TV6o0nCoVUQW8/1WTkunD/tY1IBUAokJREUTrI3rlxJ7sxsl6waVHFJGmaWsf3DRvqvVJWL1b/waloZWVxE9E5PVwCDV2Kfa+AkxHGZWOwOFYm/MqDcZ1aVMBaiEV2jFEFSVpCKvZf6mNWariueAK/Xy7yXAJgzMRXlxengGBEwSkXQ7SionZaWhgnugOGC4CKsFkoP74+039+4cRaGbI6uGTcEZUpbVjOkYnag9mMvLp1lHzpyHFCx3HnmwnBIreh5C4ojXGpm0dTgkzFZavWPNScZmRz6GMXKxxPEcQGgyv6p96BWRDTcNUosjvlpbrx/tld2/aaZOXj8M3PR0dERuvdoy5UIhkwWc2U0II6XWaZLO1knlWQzCjUjelzUeAWUrRk9VqmZmHAtsHYQgjzC9lvLOtMLvbKHW9GZ2S6kp6fbYv3pqVErRXOjH+dODYeUHKWA30+RngVZrdnUNIIAI0F0+qwkrLw5HQE/j56uMbI4EKBwshsdrQFFmUX3zPK1GcjKdut6R+yw5LXi1FlW553lBQhSqhgjLlry4r1eP48zHUOhGAWeAu1eP062DSLZTWRtOgVxvMzuDIzExYvQGl+pbEbhWJz8WIEaQ6VTYWtSvzYApKQSlFWkYpKN3PZ6ZZeGkebl2bOBM1pcBVA+J8nL92BWmRvNDcJh8ZQZySie7I6I/RcXEZHoa05FGjrb+sfELoDyQM2BwVCt4fAxMGq92wm9PmYW+ZneGHGOEAwFqKyoSYAHalq8ON7mjYlVbwZG4+JjwTwZjnFvyWuBZVUOeXlkZLlUsxK1LGhxBzGpZAIo9eHa65NRviRNt3Vmp+ziYnDulOA/b73sR1vLMIpKrO9YAPkuQeuZyuckKZg8JRnzFxYhb2IQWSPPUtuJEUIwZboHLZf98A3HledREX4fRWY2B7+PhnY/Rq33cIjvvl5rUQorPmYlC59jZHuzLGARZv3aZmB156PWZxaMjG/CkncAZqJv9FrQYsFstfC3aMjOioBpvuxFUWN0zwVEGC1jqFUrgOM4rN2YGcrobW8JYNAbvwpfLCo/syzFcoUvEVasRauJRnrpjaUWsBSx4KM3CyOUzrHm3r/qWSjN0AdbYXK0E3plZy4GwegSZVFK0dTgQ+3HXjQ3+rF0dRoqlqdh6owkVCxPs+weG2XITMfNt2YiM1v91c7IMsEbzgEej+BaEdoEMrM5pGeyn5Usr+0eeo6RovJ6YIQJUYpoMSOGM1cuKEqTKZ9Y8NFHA7FgngzHVa/k9TJQhsMuJker0Cs7czFQiZO3G+LOp/qAN8Rhf2iPF8UlHtuUXDhEy37RyjRMneFBZjYXUsyCgnVj1pwU2ZioP1MIO92wJQsLVwiL08IVaVi7MROz56UyF9s5C9OwcMUoY6n4dyvF15Vghac8msyIogX8w5tLsaA49nz00UCsufeveneNmYNDFndNLJJW9MrOco8UT06zXdEoIRZlE7WSsABE8PkQAoAIh6NSZGRxuG5uSijsVOo6UnI/iQfs4RW2rLpmWJmWgLXkHrsTjfQgFm3GCtK+zi9MBQXwi0OtlksP6sG4j5O3C+HRKfmS+qdqsffRLuStBL1x8k6wICrlDEydIbgrpIjWmEnHhFKhNoBSzL+aXJRSNDX6cfysF428D9fNSLa9eDarXum8wnT89AsL0NHRwYxjj2W0Sry8+1LEUi6lORTnKVHIO0aQH7QCuQUuLFiehk6bDs6chvTwUokoy2o4KWuRiJedjxTSMaGUytg69bpWKIB/P9M6+vG2CiyHSkrWDPcJy+9e03wFH53pwPzcq8cyjhfYNYdO13hNKHkdYLkbutqDmDoDTEt0rMKqW0VpkVi6Og15BqJpYgUzrjsRRj5es5EwLL87D+D/7DmPX26+JmpFvENt20DSNVZh5xw6HWlz1R+86kG8HLSKCI9UaWrw2VZ20Go//3975x7c1HXn8e+9kg3yS37ISH7IgI2YQnjYWUwMKaENTnYny6RdpumSbqeTthN2lqadgWFoZpiQZJxm6BInTTJlMp0pnZb+EzITht1uZyAOBLIFahYCTCAUv1JkkCzbsiQ/sSWd/UNIyFf36j50r+6Vcj5/2ZZ19NO50u/+zvf8zu8ndJPw3gnjkceKE9k0zY9Y4FxagGuXplW1Xw2Sm5fL2RCWs/GpNBOmuSY1IwUA/FNzos/la52Xyf/Hndybf7mLE70BvPmXu+g4PSg6br7Adw2vDU3i1VPutPOrR6YNjeQlYCS5QcvGEpm+T7G8/VpnIWrqCwzdGEMpcjY+lUZzbc5SVFjMGJ2ef9MNizxXbtSpRqemfIfvGko5vSv3tKwa0EheAkrSLLVCyxz9TN+nlLx9qfZrtVrRCjlpckqjOZZh8KN/qIaJ45cLTWza5wo55PPuEG+0LmWlkUnKZj7Adw3jpFuZJZ8V+CdXOXY/WqP55jiN5CUgRavNVm9OJSd0pZKJJg1IO8kqxX6jtMHjas5bq6oE/1dOSmAm0dzGhjJ83BeSVYNcyCEfvjSM4Ew4JVqXstLIJGUzH8jk9G62906ok5eI0iJnaqO1dCRWQkDsuWI3CSn2f9k/mfW8ei58koVYk2WpX14pNwShTU2+525tWQp/mrLRaxwWnOwNcDtUwj8VThQMS44+pThwPWQHI5F8HU70BHDNOzWv+JqRbnh57eSzFV2nkyDUbuQtt+6LGGrPkdhNQor9HndqrXW1VitS0brJcrobgpgmzn2u2FJf6FFuABqPPv+91Z71Tk25SPw6tDlLU84orFpkQZQQHPqrV/fMo4yc/Pnz5/HBBx/gzp07eP3119HU1AQA8Pl82LVrVyJB3+VyYceOHZlbK4NsLvmFJIhh7xwG+ibQ3zOl2k0mU0klGT1kESn21ziL0PNFSNeNbj7JYjYSzUpRKbU3Na96p1OieCC1/3w8+pTqwLMtOxiZLU1liBICQggWlxfiL7cn0fm/HkSR/dLCXDL61jidTuzZswe/+c1vUh5zOBw4ePBgJsNnhFpH6aVEunwSBMMAAX8EZ056QaKAu38WNrsJjzxWooqjVyqpJKNHuQFA3P4ljcW4LnG1otVqjU+yENvgVAu1c6n55RegvmwBBkP3eKP1r4IDVyPPn7vqYgBcHZrfvk/vzKOMnHx9fb34P+mEGhuUUiNdPgmiuJRBKBBNGgsY9kZwd3AOdTqU9+VDy03cTJC6WtFyJZKtJst8iGnicjaEAWH9fN836tA9OKGZ3BLPtVfrsJSah6/UauTBXXUJ5YDpWUZZs/Wvz+fD3r17YbFYsH37dqxYsYL3/7q6utDV1QUAOHDgAGw2m6LXM5vN857b6JrA4IB3/pLfBDS6KmGzlUgac6BvAqO+4PxIdziMyZAFS5rmj/HP22z4e/8k7rqnUOssws3PAxgPptaR97oJ1rYoe49qYjab0eiqzHiOtLKturpadD9DzvVRwtvP2HC2dxQX3QG0Osvx+NfsiEYi4k/MkK1VVfjk9hQ+GwxiNkJQaGLRUl+GrS1LAQB7jl9PPHZ6IIiz7hn859Mr0jon7nt5bFkVWIbB04sW4WkN3kOUEOz9ry9wyT2WsLOlfgpvfOshRY45SkjK+1Y6ntlsxvUA8Llvap4k9rlvGjcCDL7hkv79vHk1wJtdw6XQxGKTyyHq37h+TA1EnXxHRwcCgdSmtdu3b0drayvvcyoqKnDo0CGUlpaiv78fBw8eRGdnJ4qKUpe67e3taG9vT/yutHAQt7BPSRlJPUpfbUZx2TRGRqQ18ejv4dkAjAD9PX7eRiAlVmC5lQUwg9k5/rz12dlZVYsjKZUrbDYbSsqmBedoeHg6K5vWQrZJmSO510cJqyqAVRXl98eOZK2w1YuP2nHBXTQvyvaPjuLc7RAuux84ltkIwSV3AH/6bCBtlBglBKHxcUxPzyA0HsLICNFUHz53O5Rw8HE7L7uDonamG4/7vqWOl7LyaVmKT28NJWyLMxuJ4tMeL1ZVSLfraxUs/swiraNnAaxaZMHKciL6+dGlQNlLL70k+wULCgpQUBDTTxsbG2G32+HxeBIbs9lAjQ3KTNIVFzcWYpSjzQFAQ6N6MkimcgV3jqoWxVoGXv2/KQT9EUyEooY+lWqkk8hqI6SJK9kQ5pMm6q0L4KpciJbaYk0yP654plKcaCaShdJ9CqFU2M1Oiyp5/lwpLD6LBICZBcoXmvGjh6tVr0gqB02+DaFQCCUlJWBZFkNDQ/B4PLDb7Vq8VFoy2aAk93fKCxcwmJmOfVjlpCvWOgtxu38WI0MPlvc2u0lVrVuNjdP4HHHLDSSjR566FNRKJ02O9NY4LLHNM++07qlvfCjZEObL1hkYu4eBsXs4PRDUJPOjuaYIpweC8xx9JrnjfO/bxMbOAKRDKBV2c4NFlTx/vlrxYIBr3mnDpJVm5OS7u7tx+PBhhEIhHDhwAEuWLMG+fftw48YNHD16FCaTCSzL4vnnn0dJiX4ar1y4ETLDAAsWMljZvFBy0SqGYdC2uQSTIQv6e/yalCNWc+OUe8PgYoQNWS5qrNa4kd7J3pg0SaB/6hsfSjaE+aLgOFplfrQ5S9FSP5WQWDI9LLW+vgQLC0yYu/cgaIpEgZO3AtjgFI6ShVY+17zTquX58626Hm2wyh5HKzJy8uvXr8f69etT/t7W1oa2trZMhtYVrsMjBJi9R8AwjCwHwtfIW82UPzXlCr4bRjJGlUEyTSdNlx2hd+obH0pOvPJFwclokfnBMgze+NZD+NNnA6pk73QPTmDyXuqm97Wh6bTXJ93K56uQJgrQAmULyzKiAAAQFUlEQVS8aFVamK/X6V/PTiouvqVm4TS+4mJxuOPmWvGwdKSLcgFjFt2KO6f/WO/ARglaL7d4GhetjuDLtTMdVzxTKSd0gdip3XTXh69wnNJUWLnlmo2C8UIzA6BGhByP2G997kOJNYya+gLVDx+pefqVq28zTKy3aaXNBJu9IDGuUYqHqYVYlGukGiRc4nsJN68G8LUKNuG4+HLJ49H/Fc8kbo3MwB28hzDJnZozzTVF6OoLgLOXCxZIe32UrHz4UCuvnm9cOWcelJAXTp4Qomr5gEw39LiOkGWB24vMsBQxqh8+Uuv0q9QbhtwbVbbqByklXXaEXg5QyqEfrtP5MwusWlR0f9NvChECdPUFsMZRjP33HVFcmoiPn0s1Z9qcpVjjKMYVz2RCUmOAhP3pkFvrhw81S03E5/+zu5Po8c9gMHhPchE8JeS8k3/gUIOqRZaZRshCjnDJskKwLAyb8iflhiFnszcXov6U7AiHBSAxrVcPB5guYgQeROkLzQyueScRvu/x5qIx2SL50kRIrAfseXdo3kZgLmnRyTe8J5rK0N5Uho96gwCAJ5dZs5aaqFapCe71nT+eukXw4hjDu2SAVvVXMomQhRzh3FwUJjMQnX3wd5MZcNQJXwajRcJypCy9auPIhTc7YrE+2RGCDT5uh/BRXwjXvJMpkkUcPsWJADjZE8x6tkeUEJzuGcant4ZUqwsTv+G9/LhTdCyx1ZDcEglq1c/nXl8uWhTBy3knb8T6K0KOsKCARZhzEDY8B3jv8NuqZSQc3zyVe/OQI2UZ8doYHaGI8URvANcEqkkajbhz/twXOxClVl0YqRKJmH6uRF9Xq36+2Ea/FkXwcj67xnb/lCaXKoG/ZwOhrJdwmIC7IU+IcNaOVq3+CCH46E8eRVk+cSkr3pS7pa1I8KYjpR2gnhgxW0KoNWBgJpLWwRewDJaUp944GcRkjWwSd87xg1BSG5VzUdpiUKx94ZneEdmN1NVq25eubaBWRfCM8W3TAh0ljWRNfyJonpddM/jlnGRNPpNImCvzOOrM8N4JY3goDLMJ91MfH4wpR0aRKmWp3eBETbTKlsgUoYgxQqL4u8BzllRa8K8PVWB9fQleOz2Y0ObjmScbsqy9q6VfK5VIxF7/4u2gIvvU2MvgXl8zAzitC7DcthDNNcWKMn/EyHknP+Ljrwo4OhTWtaRv3BHaWh4UHJLr9JSmcnJlntt9s2DZ2KpBKFjVQkZRM8VTbdRuzKEGcZ3YVmzGU8srMBOOorkmVlvm/O0QrnpTayExAJ5vW5woqrX/cafumTNq6ddKJRKx129tsOLPN7y69KcVa8iixbXKeSefS0Wq5Do9pZEwX4mCdKdZAe3mTK0UT7VJF+21OUtVq1suFe7KooAFVtsfFA/b0FCGZkcQVzhSRbOjCI8tq0pEf0bInIk757gmr1ZdGKk3LbGbw+ZlNqy2D2asryuFNvKWiZElAT7kOL34TeHu4Bxu990DADiXir8vsRIFXIw+Z1ogFO2tcVjSpjBqhdjKgmUYvPy4E+fdIZzsyX4KoRzizvlGgMGnPd6M68LEne8VT+wGJzaWlGj5q9SfNuedfNwRalkITG/c/bPwD0cQjQL+4Wm4B+bSZtjwrW64sCZgcVMhxoMxuUvKzSOfEIr2QCDobJ9Wuyt7EoJZNT2BhANiGQaPNlgNVfxKCJaJNd+QU5udD6V7J2LRcnIT7gvucbzXrTzV0+iYXnnllVf0NiKZ8XF5O/DA/ei4vhyl5XMotZoM5eCLioowNaW89olncA79f7s3r1jazFQUJWUmlFr5M4hKylj4R8KYmuAX4BkGqK23YGoyDP9wBJMTBEN3w/CPRFC3WP8bZKZzxkeUEJx3j+O/b45hLhpFvXUBNi8tg9O6AKULTPiXlZX4t7XV+J+/BXBrdIbzXKB0gQmbXYvm2cUds65MWoVSPuaiUXQPjiPKuWS+iTncGpnBY0vKBMdOni81bZIL97VdjnJMT6fuI8jhvHscx7/wJ26AUQKMTIXhtBbCaV2gaMz4fMVvIMe/8OPW6Ay6B8dxczj9XGuN0s9+aamw1JTzkXy+oyTDhmEYOJcWYphno66gEFi9rgilpaX49KMhwx9UUoN00SA32lvjsOBkb2BeuiKD1LrlamfnxFcWVzmHnaKQviGsZ8aQUHOOTI/oq93UPBkjbr5rQc7nyec7gucARDZJhbKOauoLUOcshHdwWrTSZr5UmxTLm54HISn56AQA4YTYssaUQFwnXm1PzfCQWglTbZvkINScI9PXFjo3oEYmjNI8/FyDOnmVyZpjFBlX6CBStSOmvdc4i9IeVFK7LLKeyPkyn+wL8Y7xEefvWjgIlmHwj65yxU4t204r+TDZiZ7USp7xI/pyxuEeSuMrFaxWJoyWNxAjkZFcc+TIEVy6dAlmsxl2ux07d+5EcXExAODYsWM4deoUWJbFD3/4QzQ3N6tisJHhK0PgHfSgpU2ezp18kGlyQuAcgC+CugbhMcSyjpY0FuN6msdzpe6MFOTkbUu9SmrlgnPJ5Pi8VjbxwZVnWMTmLjkEkHJEX0xi0jITRq1SBUYnIye/Zs0afO9734PJZMIf//hHHDt2DN///vcxODiIc+fO4c0338TY2Bg6Ojrw9ttvgxXqSpEn8DlGz50pOAaLJDtGvtaDXKTktIvl5Is9nk91Z+R8mZ9YZsVV71SKJv+ka35Gi1YOIhOnlk2nxZVnoojNk4mJVb+UekRfii6uVV75VyWVMiMnv3bt2sTPy5cvx4ULFwAAFy9exMaNG1FQUIBFixbB4XCgt7cXy5cvz8xag8PrGCPyHCNf68Fk5OS0i+Xkp3s8lw6ZiSHny7yxoQzNNQ+qPZrvH0ra4CxTPKYSe5U4tWw6LT5piABYbS+Co7RQcnMOLTdWpWCEw2Nao9o39tSpU9i4cSMAwO/3w+VyJR6rrKyE3+/nfV5XVxe6uroAAAcOHIDNZlP0+mazWfFz1aLRNYHBAe88x2gyMWh0VcJmk9bI/NbnPt789lqnBaVlBah1FmFxY+ZVKMXmq6qKwDvogWdwKibnmICauiKsbq7RPL1Mq2v5dHU1npbwf+88Y8PZ3lFcdAfQ6izHY8uqwDIMr11Sx9QSrl3ZsGnTcoLTA8FEETIgJs8883ADvuGy8dolZ5xNLodm32cj+AohtLBN1Ml3dHQgEAik/H379u1obW0FAHz44YcwmUzYtGmTbAPa29vR3t6e+D1e50UuNptN8XPVoqSMoIqjczvqLCgum8bIyIz4AABKrGHexiI1Tga1ThbADEZHpY2VDinz1dJWAMdg0Tw5Z1Tl4klKbdOaVRXAqopyAEhEo0awiw897HqoPNaJKlkaWrXIgpXlJGGLFLukjKM2Rr2OgHLbamtrBR8TdfIvvfRS2sc/+eQTXLp0Cfv3709EeJWVlfOcgd/vR2VlpVR7cxY+nXt1c40sx2ikMg1GrTtD0R+1pKGvii6uJxnJNVeuXMHx48fx6quvYsGCB6fP1q1bh3feeQdbt27F2NgYPB4Pli1blrGxuQDXMcqVNoxcuZFCSUYtPfuroIvrSUZO/re//S3C4TA6OjoAAC6XCzt27IDT6cSGDRuwe/dusCyLH//4x3mfWaMmNIKmUChqkZGTf/fddwUf27ZtG7Zt25bJ8BQKhULJEBpeUygUSh5DnTyFQqHkMdTJUygUSh5DnTyFQqHkMQzJxbKCFAqFQpFE3kTyL774ot4m8ELtko9RbaN2yYPaJR8tbMsbJ0+hUCiUVKiTp1AolDzGcI28M6GxsVFvE3ihdsnHqLZRu+RB7ZKP2rbRjVcKhULJY6hcQ6FQKHkMdfIUCoWSx+ReLzcORm0mfv78eXzwwQe4c+cOXn/9dTQ1NQEAfD4fdu3alSjyH6/cqbddgHGarx89ehQff/wxyspipWefffZZPPzww7rYAsRKav/ud79DNBrFli1b8O1vf1s3W7j85Cc/wcKFC8GyLEwmEw4cOKCLHYcOHcLly5dhtVrR2dkJAJiYmMBbb72F4eFhVFdXY9euXSgpkdYhTUu7jPD5GhkZwa9//WsEAgEwDIP29nY89dRT2swZyXGuXLlCwuEwIYSQI0eOkCNHjhBCCHG73WTPnj1kdnaWDA0NkRdeeIFEIpGs2eV2u8mdO3fIyy+/THp7exN/HxoaIrt3786aHVLt0nu+knn//ffJ8ePHdXltLpFIhLzwwgvE6/WSubk5smfPHuJ2u/U2K8HOnTtJMBjU2wxy/fp10tfXN++zfeTIEXLs2DFCCCHHjh1LfDf1tssIny+/30/6+voIIYRMTU2Rn/3sZ8TtdmsyZzkv16xduxYmkwlArJl4vJesUDPxbFFfX5+2JZdeCNml93wZld7eXjgcDtjtdpjNZmzcuBEXL17U2yzDsXLlypSI8+LFi9i8eTMAYPPmzbrMG59dRqCioiKRRWOxWFBXVwe/36/JnOW8XJOM0mbi2cbn82Hv3r2wWCzYvn07VqxYobdJhpuvEydO4OzZs2hsbMQPfvAD3b6ofr8fVVVVid+rqqrQ09Ojiy1C/OIXvwAAPPHEE/P6JetNMBhERUUFAKC8vBzBYFBnix5glM8XEPMHAwMDWLZsmSZzlhNOXutm4lraxaWiogKHDh1CaWkp+vv7cfDgQXR2dqKoqEhXu7JNOhuffPJJfOc73wEAvP/++/jDH/6AnTt3ZtvEnKCjowOVlZUIBoN47bXXUFtbi5UrV+ptVgoMwximhaWRPl8zMzPo7OzEc889l+ID1JqznHDyRm0mLmYXHwUFBSgoiDXlbmxshN1uh8fjmbcBqodd2W6+LtXGLVu24Je//KVmdojBnZfR0VFDNaWP22K1WtHa2ore3l7DOHmr1YqxsTFUVFRgbGwssdGpN+Xl5Ymf9fx8hcNhdHZ2YtOmTXjkkUcAaDNnOa/Jx5uJ//znP09pJn7u3DnMzc3B5/MZppl4KBRCNBoFAAwNDcHj8cBut+tslbHma2xsLPFzd3c3nE6nLnYAQFNTEzweD3w+H8LhMM6dO4d169bpZk8yMzMzmJ6eTvx87do1NDQ06GzVA9atW4czZ84AAM6cOWOYVaQRPl+EELz33nuoq6vD1q1bE3/XYs5y/sTrT3/6U4TD4YSmlpyS+OGHH+L06dNgWRbPPfccWlpasmZXd3c3Dh8+jFAohOLiYixZsgT79u3DhQsXcPToUZhMJrAsi2eeeSarTkPILkDf+Urm3XffxZdffgmGYVBdXY0dO3YkdEo9uHz5Mn7/+98jGo3im9/8pmF6Fw8NDeGNN94AAEQiEXz961/XzbZf/epXuHHjBsbHx2G1WvHd734Xra2teOuttzAyMqJbCiWfXdevX9f983Xz5k3s378fDQ0NCfXh2WefhcvlUn3Oct7JUygUCkWYnJdrKBQKhSIMdfIUCoWSx1AnT6FQKHkMdfIUCoWSx1AnT6FQKHkMdfIUCoWSx1AnT6FQKHnM/wMNIeYobygDDgAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {} | |
} | |
] | |
} | |
] | |
} |
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