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23.11.5487_Kmeans.ipynb
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23-11-5487_kmeans.ipynb
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"import numpy as np\n",
"import pandas as pd\n",
"\n",
"# Visualization packages\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from sklearn.cluster import KMeans\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"\n",
"# Determine number of clusters\n",
"from sklearn.metrics import silhouette_score\n",
""
]
},
{
"cell_type": "code",
"source": [
"df = pd.read_csv('/content/Mall_Customers.csv')"
],
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"outputs": []
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" CustomerID Gender Age Annual Income (k$) Spending Score (1-100)\n",
"0 1 Male 19 15 39\n",
"1 2 Male 21 15 81\n",
"2 3 Female 20 16 6\n",
"3 4 Female 23 16 77\n",
"4 5 Female 31 17 40"
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"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df",
"summary": "{\n \"name\": \"df\",\n \"rows\": 200,\n \"fields\": [\n {\n \"column\": \"CustomerID\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 57,\n \"min\": 1,\n \"max\": 200,\n \"num_unique_values\": 200,\n \"samples\": [\n 96,\n 16,\n 31\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Gender\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Female\",\n \"Male\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 13,\n \"min\": 18,\n \"max\": 70,\n \"num_unique_values\": 51,\n \"samples\": [\n 55,\n 26\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Annual Income (k$)\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 26,\n \"min\": 15,\n \"max\": 137,\n \"num_unique_values\": 64,\n \"samples\": [\n 87,\n 101\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Spending Score (1-100)\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 25,\n \"min\": 1,\n \"max\": 99,\n \"num_unique_values\": 84,\n \"samples\": [\n 83,\n 39\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
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"metadata": {},
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{
"cell_type": "code",
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"df.info()"
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{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 200 entries, 0 to 199\n",
"Data columns (total 5 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 CustomerID 200 non-null int64 \n",
" 1 Gender 200 non-null object\n",
" 2 Age 200 non-null int64 \n",
" 3 Annual Income (k$) 200 non-null int64 \n",
" 4 Spending Score (1-100) 200 non-null int64 \n",
"dtypes: int64(4), object(1)\n",
"memory usage: 7.9+ KB\n"
]
}
]
},
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"cell_type": "code",
"source": [
"plt.figure(figsize=(12,9))\n",
"plt.scatter(df['Annual Income (k$)'], df['Spending Score (1-100)'], s = 25) #Point size is 25\n",
"plt.title('Raw Data')\n",
"plt.xlabel('Annual Income (k$)')\n",
"plt.ylabel('Spending Score (1-100)')\n",
"plt.show()"
],
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"execution_count": 5,
"outputs": [
{
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"data": {
"text/plain": [
"<Figure size 1200x900 with 1 Axes>"
],
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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"dari hasil pengamatan gambar visual diatas saya mendapatkan 5 cluster "
],
"metadata": {
"id": "zdveRdslluDg"
}
},
{
"cell_type": "code",
"source": [
"X = np.array(df.iloc[:,[3,4]])\n",
"\n",
"\n",
"X"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "lf6B_K9Xl585",
"outputId": "6003ad5e-202b-4ae6-f634-de9153ab068c"
},
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
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" [ 15, 81],\n",
" [ 16, 6],\n",
" [ 16, 77],\n",
" [ 17, 40],\n",
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" [ 18, 94],\n",
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" [ 19, 72],\n",
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" [ 30, 73],\n",
" [ 33, 4],\n",
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" [ 78, 22],\n",
" [ 78, 90],\n",
" [ 78, 17],\n",
" [ 78, 88],\n",
" [ 78, 20],\n",
" [ 78, 76],\n",
" [ 78, 16],\n",
" [ 78, 89],\n",
" [ 78, 1],\n",
" [ 78, 78],\n",
" [ 78, 1],\n",
" [ 78, 73],\n",
" [ 79, 35],\n",
" [ 79, 83],\n",
" [ 81, 5],\n",
" [ 81, 93],\n",
" [ 85, 26],\n",
" [ 85, 75],\n",
" [ 86, 20],\n",
" [ 86, 95],\n",
" [ 87, 27],\n",
" [ 87, 63],\n",
" [ 87, 13],\n",
" [ 87, 75],\n",
" [ 87, 10],\n",
" [ 87, 92],\n",
" [ 88, 13],\n",
" [ 88, 86],\n",
" [ 88, 15],\n",
" [ 88, 69],\n",
" [ 93, 14],\n",
" [ 93, 90],\n",
" [ 97, 32],\n",
" [ 97, 86],\n",
" [ 98, 15],\n",
" [ 98, 88],\n",
" [ 99, 39],\n",
" [ 99, 97],\n",
" [101, 24],\n",
" [101, 68],\n",
" [103, 17],\n",
" [103, 85],\n",
" [103, 23],\n",
" [103, 69],\n",
" [113, 8],\n",
" [113, 91],\n",
" [120, 16],\n",
" [120, 79],\n",
" [126, 28],\n",
" [126, 74],\n",
" [137, 18],\n",
" [137, 83]])"
]
},
"metadata": {},
"execution_count": 6
}
]
},
{
"cell_type": "markdown",
"source": [
"**Create Cluster**"
],
"metadata": {
"id": "vf0aEfSLmOTE"
}
},
{
"cell_type": "code",
"source": [
"kmeans = KMeans(n_clusters = 5, max_iter = 500, n_init = 10, random_state = 0)\n",
"kmeans_preds = kmeans.fit_predict(X)"
],
"metadata": {
"id": "IBAQMfzal-0Y"
},
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#predict result\n",
"kmeans_preds"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "MLQp-oUSmLQQ",
"outputId": "d4c90d74-7571-4198-975e-214e2eb7b944"
},
"execution_count": 31,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4,\n",
" 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 0,\n",
" 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2, 1, 2, 1,\n",
" 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1], dtype=int32)"
]
},
"metadata": {},
"execution_count": 31
}
]
},
{
"cell_type": "code",
"source": [
"# Menampilkan pusat cluster\n",
"print(kmeans.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "w5cnqCEgmtmt",
"outputId": "1a0c4400-c7f6-4e71-e5eb-83f968d021c0"
},
"execution_count": 32,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[55.2962963 49.51851852]\n",
" [86.53846154 82.12820513]\n",
" [88.2 17.11428571]\n",
" [26.30434783 20.91304348]\n",
" [25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(\"Inertia:\", kmeans.inertia_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "bExCu0S9m6lQ",
"outputId": "dd051616-16d4-4804-b0cd-e564c308ad22"
},
"execution_count": 33,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Inertia: 44448.45544793369\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#create model kmeans20\n",
"kmeans_20 = KMeans(n_clusters = 5, max_iter = 500, n_init = 20, random_state = 0)\n",
"kmeans_preds_20 = kmeans_20.fit_predict(X)"
],
"metadata": {
"id": "wWGz2X8en6Yw"
},
"execution_count": 34,
"outputs": []
},
{
"cell_type": "code",
"source": [
"kmeans_preds_20"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "KaoLul8ToeS7",
"outputId": "fd7593c4-f138-4489-9ae6-1b42350a1418"
},
"execution_count": 35,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4,\n",
" 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 0,\n",
" 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2, 1, 2, 1,\n",
" 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1], dtype=int32)"
]
},
"metadata": {},
"execution_count": 35
}
]
},
{
"cell_type": "code",
"source": [
"print(kmeans_20.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TVBZi_3_ogtz",
"outputId": "ff55be1b-0f77-410a-83ed-f1a3cb7ab421"
},
"execution_count": 36,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[55.2962963 49.51851852]\n",
" [86.53846154 82.12820513]\n",
" [88.2 17.11428571]\n",
" [26.30434783 20.91304348]\n",
" [25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(\"Inertia:\", kmeans_20.inertia_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "nOX54Wnnom-J",
"outputId": "f6206918-97cd-4ef9-db90-a15740a00591"
},
"execution_count": 37,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Inertia: 44448.45544793369\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#create model kmeans50\n",
"kmeans_50 = KMeans(n_clusters = 5, max_iter = 500, n_init = 50, random_state = 0)\n",
"kmeans_preds_50 = kmeans_50.fit_predict(X)"
],
"metadata": {
"id": "T7IHVqM4pLje"
},
"execution_count": 38,
"outputs": []
},
{
"cell_type": "code",
"source": [
"kmeans_preds_50"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "m9mRBALmpWSr",
"outputId": "b7116ee2-d5a6-41bf-96e0-81ed8619efc8"
},
"execution_count": 40,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4,\n",
" 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 0,\n",
" 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2, 1, 2, 1,\n",
" 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1], dtype=int32)"
]
},
"metadata": {},
"execution_count": 40
}
]
},
{
"cell_type": "code",
"source": [
"print(kmeans_50.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "KLzxr1nhpQqf",
"outputId": "0f3e63e4-452a-4ce8-94ff-84e25e8bb403"
},
"execution_count": 41,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[55.2962963 49.51851852]\n",
" [86.53846154 82.12820513]\n",
" [88.2 17.11428571]\n",
" [26.30434783 20.91304348]\n",
" [25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(\"Inertia:\", kmeans_50.inertia_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Mh5yF5elprii",
"outputId": "a809afbd-4b23-40dd-a62e-ece8e8402acd"
},
"execution_count": 42,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Inertia: 44448.45544793369\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#create model 100\n",
"kmeans_100 = KMeans(n_clusters = 5, max_iter = 500, n_init = 100, random_state = 0)\n",
"kmeans_preds_100 = kmeans_100.fit_predict(X)"
],
"metadata": {
"id": "-lE9ZHJep1to"
},
"execution_count": 44,
"outputs": []
},
{
"cell_type": "code",
"source": [
"kmeans_preds_100"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pBKJcidZqB8F",
"outputId": "38235930-7bfd-43ed-9f53-fda3995c856d"
},
"execution_count": 45,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4,\n",
" 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 0,\n",
" 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2, 1, 2, 1,\n",
" 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1], dtype=int32)"
]
},
"metadata": {},
"execution_count": 45
}
]
},
{
"cell_type": "code",
"source": [
"print(kmeans_100.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "fFLc9pNXqIrF",
"outputId": "e9ca2094-ef6c-4ddd-c033-ade99026e260"
},
"execution_count": 46,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[55.2962963 49.51851852]\n",
" [86.53846154 82.12820513]\n",
" [88.2 17.11428571]\n",
" [26.30434783 20.91304348]\n",
" [25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(\"Inertia:\", kmeans_100.inertia_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "V3sQZGRFqMRt",
"outputId": "0af3f6e6-f879-4083-b971-3a3f7e9f3519"
},
"execution_count": 47,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Inertia: 44448.45544793369\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"dari hasil percobaan dengan mengubah inisialisasi (init) dari 4 model diatas saya dapatkan semua hasil centroid nya sama sehingga dengan mengubah inisialisasinya itu tidak mempengaruhi hasil sehingga tidak ada model yang lebih baik dari keempat model percobaan dengan beda init nya tidak ada yang lebih baik"
],
"metadata": {
"id": "k0no1oYrqQET"
}
},
{
"cell_type": "markdown",
"source": [
"**mencoba dengan interasi 10 dan 150**"
],
"metadata": {
"id": "9z90RM6YrAtu"
}
},
{
"cell_type": "code",
"source": [
"kmeans_it10 = KMeans(n_clusters = 5, max_iter = 10, n_init = 10, random_state = 0)\n",
"kmeans_preds_it10 = kmeans_it10.fit_predict(X)"
],
"metadata": {
"id": "44NWxOf-rHc2"
},
"execution_count": 53,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#predict result\n",
"kmeans_preds_it10"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "akWU-dmWrMy1",
"outputId": "61dca7f9-1a43-4e18-b6cc-406551aebbe0"
},
"execution_count": 54,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4,\n",
" 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 0,\n",
" 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2, 1, 2, 1,\n",
" 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1], dtype=int32)"
]
},
"metadata": {},
"execution_count": 54
}
]
},
{
"cell_type": "code",
"source": [
"# Menampilkan pusat cluster\n",
"print(kmeans_it10.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "qa-F8UIyrRY8",
"outputId": "4b75a4f7-0995-4364-e8ad-17553be744df"
},
"execution_count": 55,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[55.2962963 49.51851852]\n",
" [86.53846154 82.12820513]\n",
" [88.2 17.11428571]\n",
" [26.30434783 20.91304348]\n",
" [25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(\"Inertia:\", kmeans_it10.inertia_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "30hsMcUWrXmj",
"outputId": "4a137eef-9bb1-4db8-b454-7a622a93cc97"
},
"execution_count": 56,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Inertia: 44448.45544793369\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"kmeans_it150 = KMeans(n_clusters = 5, max_iter = 150, n_init = 10, random_state = 0)\n",
"kmeans_preds_it150 = kmeans_it150.fit_predict(X)"
],
"metadata": {
"id": "UcBP0RnDrzzZ"
},
"execution_count": 57,
"outputs": []
},
{
"cell_type": "code",
"source": [
"kmeans_preds_it150"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1fX7Nm2jr6Y-",
"outputId": "2a4ecb78-528e-4530-83d8-7d7d657bdfa5"
},
"execution_count": 58,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4,\n",
" 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 0,\n",
" 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
" 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 2, 1, 2, 1,\n",
" 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 0, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,\n",
" 2, 1], dtype=int32)"
]
},
"metadata": {},
"execution_count": 58
}
]
},
{
"cell_type": "code",
"source": [
"print(kmeans_it150.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Ay63TGQcr8J2",
"outputId": "d013c58f-f89a-4c7d-f6ed-1a2382303964"
},
"execution_count": 59,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[55.2962963 49.51851852]\n",
" [86.53846154 82.12820513]\n",
" [88.2 17.11428571]\n",
" [26.30434783 20.91304348]\n",
" [25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(\"Inertia:\", kmeans_it150.inertia_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ti2DGP2Lr_22",
"outputId": "b60378e4-04ab-4c16-ca3a-5d2ab247fe28"
},
"execution_count": 60,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Inertia: 44448.45544793369\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"dari hasil percobaan dengan inisialisasi 10 lalu mengubah iterasi yaitu 500,10 dan 150 dari 3 percobaan diatas diatas tadi menghasilkan centroid dan inertia yang sama tidak ada perubahan yang terjadi sehingga tidak ada model yang lebih baik"
],
"metadata": {
"id": "a5On8LD5sqI8"
}
},
{
"cell_type": "markdown",
"source": [
"**Visualisasi Hasil Cluster**"
],
"metadata": {
"id": "DBAe_ShsnXR7"
}
},
{
"cell_type": "code",
"source": [
"point_size = 25\n",
"colors = ['red', 'blue', 'green', 'cyan', 'magenta']\n",
"\n",
"\n",
"plt.figure(figsize = (12,9))\n",
"for i in range(5):\n",
" plt.scatter(X[kmeans_preds == i,0], X[kmeans_preds == i,1], s = point_size,\n",
" c = colors[i], )\n",
"\n",
"plt.scatter(kmeans.cluster_centers_[:,0], kmeans.cluster_centers_[:,1], s = 200,\n",
" c = 'orange', label = 'Centroids')\n",
"plt.title('Clusters of Clients')\n",
"plt.xlabel('Annual Income (k$)')\n",
"plt.ylabel('Spending Score (1-100)')\n",
"plt.legend(loc = 'best')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 795
},
"id": "f00Z9aRJnZgH",
"outputId": "8f1c9b7c-fff6-4580-9660-9103a66452fa"
},
"execution_count": 61,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x900 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"point_size = 25\n",
"colors = ['red', 'blue', 'green', 'cyan', 'magenta']\n",
"\n",
"\n",
"plt.figure(figsize = (12,9))\n",
"for i in range(5):\n",
" plt.scatter(X[kmeans_preds_20 == i,0], X[kmeans_preds_20 == i,1], s = point_size,\n",
" c = colors[i], )\n",
"\n",
"plt.scatter(kmeans_20.cluster_centers_[:,0], kmeans_20.cluster_centers_[:,1], s = 200,\n",
" c = 'orange', label = 'Centroids')\n",
"plt.title('Clusters of Clients init 20')\n",
"plt.xlabel('Annual Income (k$)')\n",
"plt.ylabel('Spending Score (1-100)')\n",
"plt.legend(loc = 'best')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 795
},
"id": "PqlTdpZhuQhN",
"outputId": "1db5d404-0598-43c0-f9b1-6cf34f6e2a0c"
},
"execution_count": 64,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x900 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"point_size = 25\n",
"colors = ['red', 'blue', 'green', 'cyan', 'magenta']\n",
"\n",
"\n",
"plt.figure(figsize = (12,9))\n",
"for i in range(5):\n",
" plt.scatter(X[kmeans_preds_50 == i,0], X[kmeans_preds_50 == i,1], s = point_size,\n",
" c = colors[i], )\n",
"\n",
"plt.scatter(kmeans_50.cluster_centers_[:,0], kmeans_50.cluster_centers_[:,1], s = 200,\n",
" c = 'orange', label = 'Centroids')\n",
"plt.title('Clusters of Clients init 50')\n",
"plt.xlabel('Annual Income (k$)')\n",
"plt.ylabel('Spending Score (1-100)')\n",
"plt.legend(loc = 'best')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 848
},
"id": "qE-oZ_pDukBH",
"outputId": "9e4c9953-cc18-42f0-ac34-e2a0a618e7e6"
},
"execution_count": 86,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x900 with 1 Axes>"
],
"image/png": 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KUUBkYYUtAACA9qXZ36hOP/10FRUV6eabb1ZVVVWzjqmqqtJNN92kgwcP6vTTTw+4SACRq26FKF8ibYUoh8Oo5ctj5XAQJkm1MzOW5y6Xo8AR7lIQRHUrbPnCClsAAADRp9mPSt1666167733ZLfbtXHjRl188cUaNWqU0tPT1a1bN8XHx6uyslL79+9XXl6ePvvsMy1atEj5+fnq1KmTbr311ra8DwBhEg0rRAXSPLk96wiNazsyVtgCAABoX5od3BxzzDFasGCBrrzySjmdTj3wwANHPMbr9apLly564YUXdMwxx7SqUACRy24vlc2WqPx8Y/0KUWlptcFIJLDZEhs0T3a5DHK5asOcIzVPbo9sS2wNGte6ylxylblkW2JrN41rOzr7dLvfFbYAAAAQXZod3EjSb3/7W33xxRd64okn9O6772r37t1+9+3bt6/OOecc3XDDDerZs2erCwUQuSwWr7KzS+RwGJWXZ1R6emTMtJFa3zy5vaFxbcdgSbAo+6JsVtgCAABoB1oU3EhSSkqK5syZozlz5ujnn3/Wjz/+qAMHDqi8vFydO3eW2WzW0UcfrT59+rRFvQAiWGZm5AQ2dZrTPDnSam5LzWlcyxf89qOjr7AFAADQHrQ4uDlUnz59CGgARLS65sm1PXgairTmyaFQ17jWV/8TGtcCAAAAkYelVQC0a3XNk6XDmxBHTvPkUKprXOsLjWsBAACAyBPwjJsdO3Zo8+bN2r59uwoLC1VWVqaEhIT6R6WGDx+u/v37B7NWAAhIpDdPDjUa1wIAAADRo8XBzZo1a/Tggw8qJyfniPuefPLJuvvuu/Wb3/wmoOIAIBgiuXlyONC4FgAAAIgeLQpuHnnkET388MPyemsfOejfv78GDBigbt26qVOnTqqoqNCBAwf0008/aceOHcrJydH555+vO++8U3feeWeb3AAANFckNk8OJxrXAgAAAJGv2cFNdna2HnroIcXFxemPf/yjLr/8cvXr18/v/rt27dJLL72kp556Sn/729+UlZWl8ePHB6VoAAAAAACAjqDZzYmfeeYZGQwGvfDCC7r33nubDG0kqV+/fvrLX/6i559/Xl6vV88880yriwUAAAAAAOhImh3cfPXVV+rfv7+mTZvWogtMnz5d/fv315dfftni4gAAAAAAADqyZgc3paWlMplMAV3EZDKptLRjrt4CAAAAAAAQqGYHN3379pXD4dAvv/zSogvs3r1bDodDffv2bXFxAAAAAAAAHVmzg5tJkyapsrJSF110kXJzc5t1zI8//qgZM2aourpakydPDrhIAAAAAACAjqjZq0rdeuutevvtt/XNN99oxIgROv300zVq1Cilp6erW7duiouLU1VVlfbv36+8vDx99tlnWrdunWpqatS3b1/dfPPNbXkfAAAAAAAA7U6zgxuTyaQPPvhAl19+ub744gutWbNGn3zyid/9vV6vJOnEE0/U/PnzZTabW10sAAAAAABAR9Ls4EaSUlNTlZ2drQ8//FDvvPOONm3apPz8fHk8nvp9jEaj0tLSNHz4cJ177rk666yzgl40AAAAAABAR9Ci4KbOxIkTNXHiRElSdXW1ioqKVFZWpoSEBCUnJys2NqDTAgAAAAAA4BCtTlhiY2PVvXv3YNQCAAAAAACAQzR7VSkAAAAAAACEVkieadq0aZOqqqo0evToUFwOAKKWw2FUbq5RGRkeZWZ6jnwAALRTjgKHcgtzlWHOUKYlM9zlAAAQNiEJbmbMmKHCwkIVFBSE4nIAEHUKCgyy2RLldBpVVGRQcrJXVqtHdnupLBZvuMsDgJApKCuQbYlNTrdTRRVFSu6ULKvJKvt0uywJlnCXBwBAyIXsUam65cEBAI3ZbInKyYmVy2VUZaVBLpdROTkxstkSw10aAISUbYlNOXty5CpzqdJTKVeZSzl7cmRbYgt3aQAAhAU9bgAgzBwOo5xOXx/HBuXnG+Vw8FENoGNwFDjkdDt9bst358tR4AhtQQAARIBmPyr1+uuvB3yRysrKgI8FgPYuN7f28Shf3G6D8vKM9LsB0CHkFuaqqKLI5zZ3pVt5hXn0uwEAdDjNDm6uvfZaGQy+v1gcidfrDfhYAGjvMjI8Sk72yuVq/DlpMnmVnk5oA6BjyDBnKLlTslxlrkbbTPEmpZvTw1AVAADh1eLmxFarVbGxLTssLy9PHg9fPADAl8xMj6xWz/8FN4eGN16lpbG6FICOI9OSKavJ6jO4STOlMdsGANAhNTuBSUtL044dO/Tss89q+PDhLbpIRkaGDhw40OLiAKCjsNtLZbMlKj/fKLfbIJOpNrSx20vDXRoAhJR9ul22JTblu/PlrnTLFG9SmilN9un2cJcGAEBYNDu4OfHEE7Vjxw59/fXXLQ5uAABNs1i8ys4ukcNhVF6eUenpzLQB0DFZEizKvihbjgKH8grzlG5OZ6YNAKBDa1Fw8+677+rLL79sy3oAoEPLzCSwAQCp9rEpAhsAAFoQ3Jx88snq2rWrfvrppxZf5LzzzlNJSUmLjwMAAAAAAOjImh3cjB49Wjt27AjoIn//+98DOg4AAAAAAKAjM4a7AAAAAAAAAPhGcAMAAAAAABChgh7crFq1Sq+//nqwTwsAAAAAANDhBD24efTRR3XdddcF+7QAAAAAAAAdDo9KAQAAAAAARCiCGwAAAAAAgAhFcAMAAAAAABChCG4AAAAAAAAiVGywT3j88ccrJiYm2KcFAAAAAADocIIe3Pz9738P9ikBAAAAAAA6JB6VAgAAAAAAiFAENwAAAAAAABEqJMFNRkaGLBZLKC4FAAAAAADQboRsxo3X6w3VpQAAAAAAANoFHpUCAAAAAACIUM1eVWrnzp0BX8Tj8QR8LIDWcTiMys01KiPDo8zMyPu9uG1bjDZvNmv48BgNHRruagCgMUeBQ7mFucowZyjTkhnucqIS7yEAAIFrdnBzwgknyGAwBHQRr9cb8LEAAlNQYJDNliin06iiIoOSk72yWj2y20tlsYT/0cX/1mdQYWF3mc1eWa3eiKkPAArKCmRbYpPT7VRRRZGSOyXLarLKPt0uSwK9+5qD9xAAgNZr0aNSXq83oP8AhJ7NlqicnFi5XEZVVhrkchmVkxMjmy0x3KVJOrS+GFVXG+VyxURUfQBgW2JTzp4cucpcqvRUylXmUs6eHNmW2MJdWtTgPQQAoPWaPePGYrFo//79evfdd5WZ2fwprl6vVyNHjlRhYWEg9QEIgMNhlNPpK5c1KD/fKIfDGNbHpiK9PgBwFDjkdDt9bst358tR4OCRnyPgPQQAIDiaHdyceOKJWrVqlXbt2qUxY8a06CI8JgWEVm5u7eNRvrjdBuXlhTcYifT6ACC3MFdFFUU+t7kr3corzCN0OALeQwAAgqPZj0oNGzZMkvTVV1+1VS0AgiQjw6PkZN+PKZpMXqWnNx2KOBxGLV8eK4ejbRaea219gWrr+wqX5z9dodmvzNHzn64IdylBtW3/Nn2y5xNt278t3KWgA8owZyi5U7LPbaZ4k9LN6SGuKPrwHgIAEBwtmnHj9Xr19ddft/giffv2VZcuXVp8HIDAZGZ6ZLV65HIZJB06s8WrtDT/q0uFqqFxoPUFKtIbNQdqc96Pmvj2GfIYSyWDV+8VGHTnpkR9eN4nGp4+MNzlBay+mWmhU4UVhTL/xyyrmWamCK1MS6asJqtcZa5G29JMacwUaQbeQwAAgsNQWFjYrG8t5eXl2r59u+Li4lrU4waQasfPzp07lZqaqs6dO4e7nA6hLqzIzzfK7TbIZKoNRZoKKyZMSFJOzuF5rldZWTXKzi5pk/qcTkN9fW21qlQo7yuUuj/aV57Yw+r3SsaaJO2/bXd4igqCCYsnKGdPTqPXs3pnKfui7DBUhEgUij9X6kLEfHe+3JVumeJNSjOlESK2QDjeQ/7OAX8YG/CHsQF/ImVsNHvGTefOnTVkyJC2rAVAEFksXmVnl8jhMCovz6j09KZnsoS6YXBdfVu2VGnz5gMaPrybhg6NC9r567TXRsjPf7qidqbN4QySx1iq5z9doavGnBX6wlqJZqaIJJYEi7IvypajwKG8wjylm9MZfy3EewgAQOs1O7gBEJ0yM5v36FG4GgYPGlSjxES3UlOTJQU/uGmvjZDX/pQjGfzMTDJ4tc75RVQGNzQzRSTKtGQy7lqJ9xAAgMC1rw6dAAIWrobBba293tfpA7Ikr58V+7wGnWY9ObQFBQnNTAEAAICGmhXc7Nq1K6gX/fnnn4N6PgCtV9cwWDo85GibhsGhEoz7isTVqK4ac5aMnkRftyWjJzEqZ9tI/21m6ktbNjN1FDi0PHe5HAWONjk/AAAAEKhmfQvJysrSn/70J/3666+tutiyZcs0atQoLVy4sFXnAdA27PZSZWXVKCXFo/h4r1JSPMrKqpHd7qOXShQJ9L4KCgyaMCFJU6Yk6fLLEzVlSpImTEhSQYGfmS4h9uF5n8hYkyR5DLUBjscgY02SPjzvk3CX1ir26XZl9c5Sj4QeijPEqUdCD2X1zpJ9uj3o1yooK9CExRM05c0punz55Zry5hRNWDxBBWUFQb8WAAAAEIhm9bg56aST9Oyzz2r+/Pk666yzNGPGDI0fP16xsUc+/KefftIbb7yhxYsXKz8/X126dNHQoUNbXTiA4GtpQ+NoEeh92WyJDVajcrkMcrlqV8OKhNWohqcP1P7bduv5T1donfMLnWY9OWpn2hyqrpnplp+3aHPeZg1PH66hfdrmzw3bEluDFaxcZS65ylyyLbGxghUAAAAiQrOCm/fff19LlizRX/7yFy1ZskTvvfeeOnXqpBNOOEEnnnii+vTpI7PZrM6dO+vAgQPav3+/vv/+e33xxRf65Zdf5PV6ZTQadfHFF+vee+9VSkpKW98XgFZobkPjaNOS+4qm1aiuGnNWuwhsDjeo+yAlliQqtXtqm5yfFawAAAAQDZq9qtT06dM1efJkLV26VC+88II+++wzbdq0SZs3b/a5v9db23ihe/fuuvjii3XFFVcoLS0tOFUDQBtrr6tR4b9YwQoAAADRoEXLgcfGxurcc8/Vueeeq19++UVr167VZ599pvz8fLlcLpWXl8tisSglJUVDhw7VaaedpqysrGY9UgUAkaRuNSqXq3F4E2mrUTkcRuXmGpWR0T5nSrWVuhWsXGWuRttYwSrybdu/TZv3bNbwpLZ7lA4AACASBJyoHHXUUbrwwgt14YUXBrMeAIgIdatR1QY3h4Y3kbPKVkFBbb8dp7N2dlBysldWq0d2e6ksFt9LoOO/6law8hXctOUKVmidgrIC2ZbY5Cx0qrCiUOb/mGU1W2WfbpclwRLu8gAAAIIucta2BYAIE+mrbNU1T3a5jKqsNMjlMionJ0Y2W2K4S4sadStYpSSkKD4mXikJKW22ghWCo66htKvcpWpvtVzlLuXsyZFtiS3cpQEAALQJnmECAD8ieZWtaGqeHMnqVrByFDiUV5indHM6M20iGA2lAQBAR0RwAwBHEImrbNE8ObgyLZl84Y8CNJQGAAAdEY9KAUAUqmue7EukNU8GgqWuobQvNJQGAADtFcENAEShuubJ0uHhTeQ0TwaCra6htC80lAYAAO0VwQ0ARKlIb54MtIW6htI9EnoozhCnHgk9aCgNAADaNXrcAECUiuTmyUBbqWsoveXnLdqct1nD04draJ+h4S4LAACgzRDcAECUi8TmyUBbG9R9kBJLEpXaPTXcpQAAALQpghsAAAAAABA8Xq9i3F8p9tdsxRR+LkN1sbyxXVRjHqHqnhNUYzpRMvheIRWNBSW42bt3r9avX6/du3ertLRUd955ZzBOCwAAAAAAooXXq7hdr6lT7mMyVB6QsWp/g81x+1bJ43xG3vjuqsi4WVX9ZhLgNEOrgpuSkhLdddddev3111VTU1P/+qHBzaWXXqply5bpk08+0fHHH9+aywEAAAAAgEhUVajEnFmKKfpWxuoiv7sZq/ZLVfvVeetditv1ukqzXpXizKGrMwoFvKpUZWWlzjvvPL366qvq1KmTRo8eLYvF0mi/iy++WB6PR++//36rCgUAAAAAABGoqlBdPjtLsfs/azK0OZSxukix+9ery2dnSVWFbVtflAs4uHnxxRe1adMmnXTSSdq0aZOWLl2qgQMHNtpvzJgxiouL08cff9yqQgEAAAAAQITxepWYM0vG4m0yyNuiQw3yyli8TYk5F0velh3bkQQc3Pz73/9WTEyMnnvuOfXp08fvfp06dZLVatX27dsDvRQAAAAAAIhAcbteU0zRty0ObeoY5FVM0TeK2/VakCtrPwIObrZv367+/fsrPT39iPuazWa53e5ALwUAAAAAACKN16tOuY81+/Eof4zVReqU+09m3fgRcHBTU1OjhISEZu1bXFzc7H0BAAAAAEDki3F/JUPlgaCcy1C5XzHur4JyrvYm4OCmT58+cjqdqq6ubnI/t9ut7du3y2q1BnopAAAAAAAQYWJ/zW605HegjFX7FbtvdVDO1d4EHNycccYZKisr00svvdTkfk8++aRqamo0fvz4QC8FAAAAAAAiTEzh58E934ENQT1fexFwcHP99dcrPj5ef/nLX/TMM8+opKSkwfbCwkLNmTNHjz32mJKSknT11Ve3ulgAAAAAABAZDNXFEX2+9iLg4GbAgAH617/+pZqaGt19990aMGCAvv76a0nSCSecoIEDB+qxxx5TTEyMnnrqKR111FHBqhkAAAAAAISZN7ZLRJ+vvQg4uJGkCy+8UEuXLtUpp5yiqqoqlZeXy+v1aufOnaqpqdHQoUP17rvvavr06cGqF2HmKHBoee5yOQoc4S4FHZzDYdTy5bFyOFr1MQYAAAAgQDXmEcE9X7eRQT1fexHb2hOceuqpWrFihX755Rd99913KiwsVFJSkgYPHkxD4nakoKxAtiU2Od1OFVUUKblTsqwmq+zT7bIkWMJdHjqQggKDbLZEOZ1GFRUZlJzsldXqkd1eKouF5QMBAACAUKnuOUEe5zNBaVDsieuu6pRxQaiq/Qk4uJk6dao6deqkRYsWqVOnTjrqqKN4HKodsy2xKWdPTv3PXWUuucpcsi2xKfui7DBWho7GZktUTs5/P7pcLoNcrtowJzu7pIkjAQAAAARTjelEeeO7SUEIbrzx3VVjOjEIVbU/AT9jsGnTJu3bt0+dOnUKZj2IQI4Ch5xup89t+e58HpsKJq9XMYVfqtMPjyhx0/lK+myiEjedr04/PKKYwi8lb8eeUeJwGOV0+vrYMig/38hjUwAAAEAoGQyqyLhFntjkVp3GE5usioybJYMhSIW1LwF/y+ndu7dqamqCWUvQeL1evffee5oyZYoGDRqko446SllZWbrpppvkdDob7V9UVKS7775bxx9/vHr27KkhQ4bo3nvvVXExHa0lKbcwV0UVRT63uSvdyivMC3FF7ZDXq7idi9TlkywlbrpAnbc/qLh9qxR74HPF7VulztsfVOKmC9Tlk+GK27mowwY4ubm1j0f54nYblJdHcAMAAACEUlW/mapJHiKvAgtdvDKoJvkEVfWbGeTK2o+Av+VMmDBB27Zt0759+4JZT1Dcc889mj17tn788UdNnjxZV199tdLS0vTKK6/o9NNP19atW+v3LSkp0eTJkzVv3jwdc8wxuvbaa3X00UfrySef1LRp01ReXh7GO4kMGeYMJXfynaCa4k1KN6eHuKJ2pqpQiRunqPPWuxRTkuv3+VBj1X7FlPyozlvvUuLGqVJVYWjrjAAZGR4lJ/sOrUwmr9LTPSGuCAAAAOjgDAaVZi2Sp8ugFoc3Xhnk6TJIpVmvMtumCQEHN3fccYdMJpP+53/+RwcPHgxmTa2yd+9ePf3000pNTdXnn3+uxx57TPfff7/eeustzZkzRwcPHtTcuXPr93/iiSf07bff6qabbtLbb7+tv/71r3r77bd100036csvv9S8efPCeDeRIdOSKavJ6nNbmilNmZbM0BbUnlQVqstnZyl2/2cyVvue1XQ4Y3WRYvevV5fPzupw4U1mpkdWq0fS4eGNV2lpHmVmEtwAAAAAIRdnVvGoFaruPqrZj015YpNV3X20iketkOLMbVtflAu4OfHq1at12WWX6fHHH9fJJ5+s6dOnKzMzU4mJiX6PmTFjRqCXa7YdO3bI4/Ho1FNPlclkarDtrLPO0p///Ge5XC5JtY9ULVy4UF26dNHtt9/eYN/bb79dL7zwghYsWKBbbrmlzeuOdPbpdtmW2JTvzpe70i1TvElppjTZp9vDXVr08nqVmDNLxuJtMjQKIppmkFfG4m1KzLlYpacu7VDptN1eKpstUfn5RrndBplMtaGN3V4a7tIAAACAjivOrNJTlylu12vqlPtPGSr3+3yawBPXXd747qrIuLn28agO9F0mUAEHN9dee60MBoO8Xq/27dunF1988YjHhCK4ycjIUHx8vDZu3KiioiIlJ/837VuxYoUk6YwzzpAk5ebm6pdfftH48eOVlJTU4DxJSUkaMWKEVq1apV27dqlfv35NXre9P1KVZEjSsnOWadv+bXIWOWVNtmpQ90GSmnfvlZWVDf4PqfPPdsUUfdPi0KaOQV7FFG2Rflqg8j62IFcXOi0dG0lJ0rJlZdq2LUZOZ6ys1moNGlTbb6ud/zbscPjcQFMYH/CHsQF/GBvwh7ERXOUp5+tgj/MUe/BrxResUXzhJhlqSuSNSVKl+RRVWsaquuuw2sCmoiLc5TaprcZG586dW7R/wMHNqFGjZIjAZKx79+667777dM899+iUU07RpEmT1LVrV3333Xf69NNP9fvf/15XX321pNrgRpLS0333aElPT9eqVauUm5t7xODm559/jthmzcGUqEQNjhkslUg7S3a2+Pi9e/e2QVVRyOvV8c5/yFjduscMjdUHFf/jP7S9emTUJ9UtHRuJidLgwbU/3tnyoYgowucGmsL4gD+MDfjD2IA/jI1g6yHFXiD1uKDhy25J7l1hqShQwRwbMTExfjMIfwIObpYvXx7ooW3uuuuuU58+fXTDDTfopZdeqn995MiRuuCCCxQbW3vbRUW1PUUOf6SqTt1snbr9mtKnT5/Wlt2uVVZWau/everVq5fi4+PDXU7YxRZ9pXhvcHpDdfIe1ABzgaqTTwzK+UKNsQF/GBtoCuMD/jA24A9jA/4wNuBPpIyNgIObSPa3v/1Njz76qO6++25deOGFMplM+vbbb3X33XdrypQpWrBggSZNmhTUa7Z0qlNHFR8fz3slqdOOtTJWHwjKuYzVB5TkXq+KniODcr7WcDiMys01KiOj5Y2CGRvwh7GBpjA+AucocCi3MFcZ5ox2udAAYwP+MDbgD2MD/oR7bLS74GbNmjV66KGHdO211+rmm2+uf33kyJFavHixhg0bpnvuuUeTJk2qn1Hjdrt9nqtups2hfXKAYIgp/Dy45zuwIajna6mCAoNstkQ5nUYVFRmUnOyV1VrbMNhiCayHDwCgbRSUFci2xCan26miiiIld0qW1WSVfbpdlgRLuMsDAACHaXVw4/V6tWzZMq1cuVLbt2/XwYMH1bVrVx1zzDE688wzNXny5JD2wvnoo48kSaeffnqjbb169dLRRx+tb775RsXFxcrIyJAk5eXl+TxX3et1+wHBYqgujujztZTNlqicnP9+nLhcBrlctWFOdnZJGCsDABzOtsSmnD059T93lbnkKnPJtsSm7Iuyw1gZAADwpVXBjdPp1OzZs/Xdd99Jqg1x6mzatEmvvvqqhgwZoldeeUVWq7VVhTZXXbfnuiW/D1dQUCCj0ai4uDhlZGToqKOO0ueff66SkpIGK0uVlJTo888/V1pa2hEbEwMt5Y3tEtHnawmHwyin0+hji0H5+UY5HMYWPzYFAGgbjgKHnG6nz2357nw5Chzt8rEpAACima9vW81SVFSk6dOn69tvv5XRaNTkyZN1xx136LHHHtMdd9yhyZMny2g06ptvvtG5557brAa/wXDqqadKkubNm9foEaiXXnpJu3fv1imnnKJOnTrJYDDokksuUXFxsf7+97832Pfvf/+7iouLdemll4akbnQsNeYRwT1ft/D1t8nNrX08yhe326C8vIA/ZgAAQZZbmKuiCt9/J3NXupVX6HsWMgAACJ+AZ9zMnTtXO3bs0JAhQ/Tyyy/7fJwoLy9Pl112mb777jvNmzdPf/rTn1pVbHOcc845evHFF/XZZ58pKytLZ599tkwmk7Zs2aJPP/1UCQkJeuCBB+r3v/HGG/X+++/r8ccf1zfffKOhQ4dqy5YtWr16tU466SRdc801bV4zOp7qnhPkcT4jY9X+Vp/LE9dd1Snj/G5vTcPg5sjI8Cg52SuXq3F4YzJ5lZ7e9DU//DBeH3/cV7/5TbymTw96eWHz/KcrtPanHJ0+IEtXjTkr3OX4FEhj0kDHU1uPw3AJ6D2Mgoaw0VAjApNhzlByp2S5yhrPTDbFm5RubtnypAAAoO0FHNwsW7ZMMTExWrBggd/HoNLT07VgwQKdfPLJWrp0aUiCm5iYGL3zzjuaN2+e3nnnHb355puqrKxUz549deGFF+rWW2/VoEGD6vdPSkrS8uXL9fDDD2vp0qVau3atevXqpeuvv1533nmnEhIS2rxmdDw1phPlje8mBSG48cZ3V42p8VLgoWoYnJnpkdXq+b/g5tDwxqu0NP9f0rdvN2rs2C4qLZW8XumVV6TERGnNmmIdfXT0frHfnPejJr59hjzGUsng1XsFBt25KVEfnveJhqcPDHd5kgJrTBroeGqvjasDeg+joCFsNNSI1sm0ZMpqsvoMbtJMaQR1AABEIENhYWFAf3Pu16+f0tLStH79+iPuO3r0aOXn52vXrl2BXArtQHl5uXbu3KnU1FSW2Ps/cTsXqfPWu2SsDvwxQk9sssoHP6Sq1FmNtk2YkNSgYXAtr7KyaoLeMLjuy3l+vlFut0EmU21o09SX8759k1VScvgsHa+SkqTdu0PzaGVb6P5oX3liD3t/vZKxJkn7b9sdnqIOM2HxhAaNSetk9c7y25g00PHUmnEYyZ8bAb2HARwTatFQY51IHh+Rri6gy3fny13plinepDRTWrsJ6Bgb8IexAX8YG/AnUsZGwM0nvF6vjMbmHW4wGBo0LgYgVfWbqZrkIfIqsFXXvDKoJvkEVfWb2WhbcxoGB5PF4lV2domWLi3R/PmlWrq0RNnZJX5Dmw8+iFVpqa8tBpWW1m6PRs9/uqJ2ps3hDJLHWKrnP10R+qIO05zGpI2OCXA8hXochkpA72EAx4RaNNSI4LAkWJR9UbaWXrBU8yfN19ILlir7oux2EdoAANAeBfy35rS0NDkcDv38889N7rdr1y45HA6lpaUFeimgfTIYVJq1SJ4ug1oc3nhlkKfLIJVmvSoZGh8brobBmZkeTZpUfcQeJps2xchfluv1Sjk5MW1QXdtb+1OOZPBzYwav1jm/CG1BPgTSmDTQ8dReG1cH9B5GQUPYaKgRwZVpydSkjEk8HgUAQIQL+G/NZ511lqqrq3X55Zdrz549Pvf55ZdfdMUVV8jj8WjSpEkBFwm0W3FmFY9aoeruo+SJTW7WIZ7YZFV3H63iUSukOLPPfeoaBvvSnIbBbe2UU2p85U2SanOorKya0BYUJKcPyJK8fm7Ma9Bp1pNDW5APdY1JffHXmDTQ8RTp4zBQAb2HARwTatFQIwAAQEcU8PMIf/zjH7V48WJt3rxZw4YN0znnnKPBgwerZ8+e+vXXX7V161a9++67qqioUJ8+fXT99dcHs24gqh2+YkvpqcsUt+s1dcr9pwyV+32uNuWJ6y5vfHdVZNxc+3iUv+RDgTcMrq+vjVcAOvvsaiUmSiUl3kb1JSbWbm8LbX1fV405S3duSpTHUHL4bcnoSYyI1aUCaUwa6Hhq7TiMVAG9h1HQELa1NbISFQAAQNsIOLjp1q2b3n77bV1yySX68ccf9cYbbzTYXtfT5uijj9aCBQtkNptbVSjQHjS5YkvqLFX1m6kY91eK3bdKMQc2ylBdLG9sF9V0G6nqlHG1q0c1Edgcym4v9dsw2G99IVwBaM2a4v9bVcorr7f2tupWlQq2UN7Xh+d90mBVKXkNMnpqV5WKFPbpdr+NSf0eE8B4as1xkS6g9zCAY0ItkBpZiQoAAKBtBbyqVJ3Kykq98847WrlypbZv367i4mJ16dJFxxxzjM4880yde+65iouLC1a9iFKR0o073MKxYovDYVRenlHp6Uee4RDKlajqLFni0Zo1ZRo7NkHTp7dNz5Nw3Nfzn67QOucXOs16ckTMtPHFUeBQXmGe0s3pzZ4h0ZLx1NrjouFzI6D3MIBjQq0lNYZrJapoGB8ID8YG/GFswB/GBvyJlLHR6qVb4uPjZbPZZLPZglEP0G41Z8WWtvgSl5nZvC/KzVkBqC0ebZk4sVKDB/+s1NRUScH/MAzXfV015qyIDWzqZFoyWzzmmjuegnVcpAvoPQzgmFBrbo3h+lwDAADoSKJzSQ8gCkX6ii3tdgWgdnpfQCSI9M81AACA9iDgbyy//vqrXn/9dX3++edN7rdx40a9/vrr2rdvX6CXAtqFSF+xpd2uANRO7wuIBJH+uQYAANAeBBzcvPLKK7ruuuuUn5/f5H47duzQddddp1dffTXQSwHtQt2KLb5EwqoymZkeWftVSjo8yPDI2rcyah9zycz0qF8/j6TDwxuv+vZtn4/vAKES6Z9rAAAA7UHAwc3KlSsVFxen6dOnN7nf9OnTFRsbqxUrVgR6KaDdsE+3K6t3llISUhQfE6+UhBRl9c6KmFVllnqnaIQ+V0/tVbzK1VN7NUKf6z3vlHCX1iq1i9w1flzKG9wFpYAOKdI/1wAAAKJdwM2J8/Pz1a9fP3Xq1KnJ/Tp16qTU1NQjzswBOgJLgkXZF2VH5KoyRodDPXdv0UaN0lYdqx81UAP1owbre3l+TlGJwyFPZmTU2hIOh1G7d/tuTvzzz23XnBjoKCL5cw0AAKA9CDi4cbvd/7cKzJGZzWbt2rUr0EsB7U4kripjzM2Voai2yehgfa/B+r5+m8HtljEvLyqDm+Y0Jya4AVovEj/XAAAA2oOAH5Xq3r17s2fROJ1Omc3mQC8FIAQ8GRnyJvtuMuo1meRJj84mozQnBgAAABDNAg5uhg0bpv3792vp0qVN7rds2TLt379fw4YNC/RSAELAk5kpj9Xqo4Wv5ElLi8rZNtL/NV22+m5OnJZGc2IAaAlHgUPLc5fLUeAIdykAAHQYAQc3s2bNktfr1Q033KB169b53Gf9+vW64YYbZDAYNHPmzICLBBAapXa7arKy5ElJkTc+Xp6UFNVkZanUHt1NRp9+ukxJSZLB4JXklcHgVVJS7esAgCMrKCvQhMUTNOXNKbp8+eWa8uYUTVg8QQVlBeEuDQCAdi/gHjdTpkzR2WefrQ8++EDTpk3TKaecolNOOUUmk0lut1ubNm3Spk2b5PV6NWnSpCOuPgUg/LwWi0qys2V0OGp72qSnR+1Mm0Ndc02CSkr+2+fG65VKSry65poEZWeXhLEyAIgOtiU25ezJqf+5q8wlV5lLtiU2ZV+UHcbKAABo/wIObiTppZde0s0336zFixfr888/16ZNm+q3eb1eGQwGzZo1S48++mirCwUQOp7MzHYR2Ei1q0o5nb5XlcrPZ1UpADgSR4FDTrfT57Z8d74cBQ4aUwMA0IZaFdx07txZTz/9tK6//notXbpUW7du1cGDB9W1a1cdd9xxmjZtmo499thg1QoALcaqUgDQOrmFuSqqKPK5zV3pVl5hHsENAABtqFXBTZ3jjjtOxx13XDBOhQjnKHAotzBXGeYM/pKGqFC3qpTL1Ti8icRVpRwOo3JzjcrIoHEygMiQYc5QcqdkucpcjbaZ4k1KN0fnqoMAAESLoAQ3aP8KygpkW2KT0+1UUUWRkjsly2qyyj7dLkuCJdzlAX7VrSpVG9wcGt5E1qpSBQUG2WyJcjprZwglJ3tltXpkt5fKYvG9nDkAhEKmJVNWk9VncJNmSuMfcgAAaGNBDW7cbrfmz5+vzZs3q6qqShkZGbrkkkt4XKodoCkhopndXiqbLVH5+Ua53QaZTLWhjd1eGu7S6tlsicrJ+e9HsstlkMtVG+bQQBlAuNmn22VbYlO+O1/uSrdM8SalmdJknx7dqw4CABANmh3cfP3117r//vs1YMAAPfbYY422O51OTZ06Vbt375b03+bEL7zwgp588knZbLbgVY2Qoikhop3F4lV2dokcDqPy8oxKT4+cmTYSDZQBRD5LgkXZF2XLUeBQXmGe0s3p/NkPAECI+Pqm4NOqVav0ySefaMCAAT63/+EPf9CuXbvk9Xp1wgkn6LzzzlNqaqqqqqp00003aceOHUErGqHVnKaEQDTIzPRo0qTqiAtBmtNAGQAiQaYlU5MyJhHaAAAQQs3+NrBx40ZJ0tSpU31u27RpkwwGg/7yl79ozZo1evHFF5WTk6MzzzxTFRUVeuWVV4JXNUKqrimhL81tSrht/zZ9sucTbdu/LdjlIYI4HEYtXx4rhyMyg4ZIra+ugbIvkdhAGa3jKHBoee5yOQoc4S4FAAAAUaDZj0r99NNPSklJkdVqbbTtgw8+kCQNGDBAN910U/3rcXFxuu+++7Ry5Up98sknuvfee1tdMEKvNU0J65saFzpVWFEo83/MspppatzeRHpj3UivL1oaKKN1aPIOAACAQDT7n51dLpf69u3rc1vdbJuJEyfKYGg43X/w4MHq3bu38vJ4nCaa2afbldU7SykJKYqPiVdKQoqyemcdsSlhXVNjV7lL1d5qucpdytmTI9sSeh61J3WNdV0uoyorDXK5jMrJiZHNlhju0iRFfn1SbQPlrKwapaR4FB/vVUqKR1lZNRHVQBmtU/95WOZSpadSrjI+DwEAAHBkzZ5xU1paqsrKykave71efffdd5KkESNG+Dy2d+/e9fsgOgXSlJCmxh1DpDfWjfT66kR6A2W0Dp+HAAAACFSzZ9yYTKb65sOH+v7771VcXCxJGjZsmM9jq6qqFBcXF3iViBgtaUpIU+OOIdIb60Z6fYeL1AbKaB0+DwEAABCoZn9jOf7441VUVFTfz6bOe++9J0nq06eP0tLSfB67Y8cO9erVqxVlIhoFo6kxIl+kN9aN9PrQMfB5CAAAgEA1O7iZPn26vF6vbrnlFr333nv68ccftXDhQj311FMyGAw677zzfB73n//8RwcPHtSgQYOCVjSiQ11TY1+O1NS4vTM6HIpdvlxGR/SvKlPXWFc6PBxp28a6zV0hKlz1AYfi8xAAAACBanaPm4svvlgvvfSSvv32W1122WX1r3u9XpnNZl133XU+j3v77bdlMBh0xhlntLpYRB/7dHv9KirucrdMnU31q6h0RIaCAiXabDI6nTIUFcmbnCyP1apSu11eS/SuKmO3l8pmS1R+vlFut0EmU20o0haNdQNZISqU9QH+1H0e5rvz5a50yxRvUpoprcN+HgIAAKB5mh3cxMbG6u2339b111+vlStX1ve6sVqteuaZZ3w+ClVaWqr58+dLksaNGxecihFV6poab/l5izbnbdbw9OEa2mdouMsKm0SbTbE5OfU/N7hcMrhcSrTZVJKdHcbKWieUjXXrVoiq43IZ5HLVhjnZ2SVhrw/wJ5Am7wAAAECzgxtJ6tGjhxYvXqxff/1V+fn56tq1qzIzm/5L57Jly2QwGHhUqoMb1H2QEksSldo9NdylhI3R4ZDR6Wz0ukGSMT9fRodDniP8fop0mZltG4i0doWotq4PaI5MSyaBDQAAAJqtRcFNnZ49e6pnz55H3C8xMVHHHntsIJcA2h1jbq4MRb5XlTG43TLm5UV9cNPWmrNCFMEMAAAAgPYkstbBBdoxT0aGvMm+V5XxmkzypLOqzJGwQlT4NbcpdDCO27YtRp98Yta2bTEtLTNk2lOj8UM5ChxanrtcjoL2dV+ILoxDAABqBTTjBkDLeTIz5bFaa/vaHPK6V5InLY3ZNs1Qt0KUy2WQDnsXWSGqbQXSFDrQ4/57jEGFhd1lNntltXqPeK1Qaq+NxgvKCuobyhdVFCm5U3J9Q3lLQvTeF6IL4xAAgIaYcQOEUKndrpqsLHlSUuSNj5cnJUU1WVkqtbOqTHPZ7aXKyqpRSopH8fFepaR4lJVVwwpRbayuKbTLZVRlpUEul1E5OTGy2RKDftx/j4lRdbVRLldMs64VSnWNxo0ulwyVlTK6XIrJyVGizRbu0lrFtsSmnD05cpW5VOmplKvMpZw9ObItie77QnRhHAIA0BAzboAQ8losKsnOrm1UnJcnT3o6M21aiBWiQi/QptCBHNfaBtSh0F4bjTsKHHK6nT635bvz5Shw0FQZbY5xCABAY8y4AcLAk5mp6kmTovLLXaTIzPRo0qTqsH+J7wia0xQ6WMcFeq1Qak6j8WiUW5irogrf9+WudCuvMDrvC9GFcQgAQGPh/xswACCiBdoUOpDjoqEBdXttNJ5hzlByJ9/3ZYo3Kd0cnfeF6MI4BACgMYIbQKxcEY0CXd0ILVfXFLq2lfahmm4KHchxgV4rlOoajTeuMLobjWdaMmU1WX1uSzOl8XgKQoJxCABAY/S4QYfGyhXRJ9DVjdA6dnupbLZE5ecb5XYbZDLVBilHagodyHF1xzidhvpj6laVihSldnvtqlL5+TK43bUzbdLSor7RuH26XbYlNuW78+WudMsUb1KaKU326dF9X4gujEMAABoyFBYW8k0Hba68vFw7d+5UamqqOnfuHO5y6k1YPEE5e3IavZ7VO0vZF2WHoaKOp6VjY8KEJOXkHJ45e5WVVaPs7JK2KRL1Am0KHchxW7ZUafPmAxo+vJuGDo0LtOQ21V4bjTsKHMorzFO6OT1iZzhE6p8rCJ5AxyFjA/4wNuAPYwP+RMrYCHjGzdSpU5u9b0xMjLp27aq0tDSNGjVKEydOVExMTKCXBoKClSuiTzSsONTeZWYG9rhSIMcNGlSjxES3UlOTJUVmcOPJzGxXgU2dTEsmn38IO8YhAAC1Ag5u1q1bJ0kyGGpX//B6G0/cOXybwWDQvHnzZLVa9eKLL+rEE08M9PJAqzVn5Qr+whhZmrPiEMENAAAAgPYk4OBm7ty5ys/P1z//+U917txZkyZN0gknnKAuXbqouLhY3377rZYvX66KigrdfPPNslgs+uGHH/Tuu+/qp59+0gUXXKC1a9eqT58+wbwfoNnqVq5wlbkabWPlishUt+KQy9U4vImUFYfgm8NhVG6uURkZzZ95E7Ntm8ybNytm+HBp6NA2rhAAAACITAEHN2PHjtWYMWOUlZWlBQsWqEePHo32KSgo0CWXXKIXXnhBn3zyia666irde++9mjFjhjZs2KC5c+fqgQceaNUNAIGqW7nCV3DDyhWRqW7Fodrg5tDwJnJWHEJDgTSTNhQUKNFmk8HpVPfCQnnNZnmtVpXa7fJaaBoOAACAjiXgdXQfeughHTx4UPPnz/cZ2kiSxWLRyy+/rKKiIj300EOSpOTkZM2dO1eStGrVqkAvDwSFfbpdWb2zlJKQoviYeKUkpCirdxYrV0Qwu71UWVk1SknxKD7eq5QUj7KyaiJqxSH8l82WqJycWLlcRlVWGuRyGZWTEyObLdHvMYk2m2JzchTjcslYXa0Yl0sxOTlKtNlCWDkAAAAQGQKecbNq1Sode+yx6tmzZ5P79erVS8cee6xWr15d/5rValV6erp27twZ6OWBoLAkWJR9UXZUrKCCWhaLV9nZJQGvboTQCaSZtNHhkNHp9HGEZMzPl9HhaJfNgAEAAAB/Ag5u9u/fL5PJ1Kx9KysrtX///gavdevWTbt37w708kBQsXJF9Al0dSOETiDNpI25uTIU+W4abnC7a5feJrgBAABABxLwo1JHHXWUtm3bpq1btza539atW7Vt2zYdddRRDV53uVzq3r17oJcHAES4umbSvvhrJu3JyJA3OdnnMV6TSZ50moYDAACgYwk4uJk2bZq8Xq9mzJihTZs2+dxn8+bNmjlzpiRp+vTp9a///PPPcjqdysjICPTyAIAIV9dMWjo8vPHfTNqTmSmP1erjCMmTlsZsGwAAAHQ4AT8qddttt+nDDz/Utm3bdNZZZ+noo4/WkCFD6pcD/+677/TDDz/I6/UqMzNTt912W/2x8+fPlySNHz++1TcAAIhcdnupbLZE5ecb5XYbZDLVhjZNNZMutdvrV5UyuN3ymkz1q0oBAAAAHU3AwU3Xrl31/vvv65ZbbtF7772nH374QT/88EODfQwGg84991w9+uij6tKlS/3rt9xyi2688UYlJCQEXjkAIOIF0kzaa7GoJDtbVVu26MDmzeo2fLjihg4NUcUAAABAZAk4uJGk7t27a/78+XI6nVq9erW2b9+ukpISJSUl6eijj9a4ceNktVobHde5c+fWXBYAEGUCaSZdM2iQ3ImJSk5NVVwb1QUAAABEulYFN3WsVquuuOKKYJwKAAAAAAAA/yfg5sQAooPR4VDs8uUyOhzhLgXtAOMJkSJm2zaZP/lEMdu2NfsYxi8AAIhGQZlxI0mFhYUqLi6W1+t76VdJSk1NDdblAByBoaBAiTabjE6nDEVF8iYny/N/DV69Fku4y0OUYTwhUtSNRYPTqe6FhfKazfXNq/2NRcYvAACIZq0Kbnbt2qUHH3xQK1asUGFhYZP7GgwGFRQUtOZyAFog0WZTbE5O/c8NLpcMLpcSbTaVZGeHsTJEI8YTIsXhY1Eul7xHGIuMXwAAEM0CflQqLy9PY8eO1eLFi3XgwAF5vd4m//N4WtaUEkDgjA6HjE5no9cNkoz5+TwmgBZhPCFSBDIWGb8AACDaBRzczJkzRwUFBRo4cKAWLFggh8Oh/fv368CBA37/AxAaxtxcGYqKfG4zuN0y5uWFuCJEM8YTIkUgY5HxCwAAol3Aj0p9+umniouL05tvvqn+/fsHsyYAreTJyJA3OVkGl6vRNq/JJE96ehiqQrRiPCFSBDIWGb8AACDaBTzjpri4WAMHDiS0ASKQJzNTHqtVh7cK90rypKXJk5kZjrIQpRhPiBSBjEXGLwAAiHYBBzepqalNriAFILxK7XbVZGXJk5Iib3y8PCkpqsnKUqndHu7SEIUYT4gUdWOxpkcPeeLiVNOjxxHHIuMXAABEs4AflTr33HP1j3/8Q06nU1arNYglAQgGr8Wikuzs2saceXnypKfzL8sIGOMJkaJuLFZt2aIDmzer2/Dhihs6tFnHMH4BAEA0Cji4ueWWW/TBBx/oiiuu0Msvv6y0tLRg1gUgSDyZmXxBQdAwnhApagYNkjsxUcmpqYpr5jGMXwAAEI0CDm6eeOIJjRkzRs8//7xOPfVUjRs3TgMHDlRiYqLfY+68885ALwcAAAAAANDhBBzcPPzwwzIYDPJ6vaqqqtL7778vg8Hgc1+v1yuDwUBwE2GMDoeMubnyZGQ0+18gAzkGAAB/+HMFHQ1jHsD/b+/Ow6Oqz/6Pf86ZSYBJSMISEAUTEoGIIorBfd8QcVeMFZWfSxfUVqVVXGpLrRVxKXipuNXW+ogabfURBO3DUnChILEKuEyQhEQ20QGSmIyQZM75/REnEjIDyWT2eb+ui6t1znbPzH3OzNz5nvsLdFbIhZvLL788aKEG8c3Ytk2ukhKZVVUy6upkZ2XJys+Xt7RUdp8+YdsGAIBg+FxBqiHnAQChCrlw8+STT4YzDkSRq6REzrKy1v82PB4ZHo9cJSVqWLgwbNsAABAMnytINeQ8ACBUIU8HjsRkut0yq6raPW5IMqurZbrdYdkGAIBg+FxBqiHnAQBdQeEmxZgVFTLq6gIuM2prZVZWhmUbAACC4XMFqYacBwB0BYWbFGMVFsrOygq4zM7OllVQEJZtACQn0+2Wc948/jqMLuFzBamGnAcAdEWHetz07t1bkjR06FAtX768zWMdZRiGtm3b1snwEG5WUZGs/PyW+6p3e9yWZOXlBZzdwCoqkjVwYOBtDjiAGRGAFEBTTYRTKJ9FQCIj5wEAXdGhETe2bbf+C/RYR/5ZlhWxJ4HO8ZaWyldcLCs3V3Z6uqzcXPmKi+UtLQ2+kW0r4Bxiu+UEgOTlb6ppejwyGhtlejxylJXJVVIS69CQoEL6LAISGDkPAAhVh0bcrFq1SpKUlpbW7jEkHrtPHzUsXNjSKK+yUlZBwV7/0mO63TI3bWr3uCHJ3LxZptvNX4qAJNaRpppcA9BZnf0sAhIdOQ8ACFWHCjcHHnhghx5DYrGKijr0haEjDfX44gEkL64BiKSOfhYByYKcBwB0Fs2JsU801ANSG9cAAAAAIHYo3GCf/A319uxmQ0M9IDVwDQCih5nbEE6h5pPz7bfV7Q9/kPPttyMU2Y/IeQDYtw7dKjV9+vSwHGzKlClh2Q+i7/snn1TmKafI9npbGhIbhuRy6fsnn4x1aACiwFta2jKrVHW1jNralpE2eXk01QTChJnbEE6h5pP55ZfKPOUUaY/ve/VLlsgaMiQuYgSAVNShws0DDzwgwwg4p1CH2LYtwzAo3CSwHpMmyWho+PEB25bd0KAekyapYeHC2AUGICpoqglEln/mNj/D45Hh8chVUsLnLDot1HzKPOWUgN/3Mk85RXUBJqqIRYwAkIo6VLi5/PLLAxZumpqa9Oabb6qpqUn9+/fXkCFD1K9fP33zzTdat26dvv76a6Wnp+v8889vMyMVEgszygDwo6kmEH58ziKcQs0n59tvt4y0CbCd7fXK+fbbah47NqYxAkCq6lDh5skAt8Ps3LlT5513nrKzszVt2jRdfPHFMs0fW+ZYlqXXX39dd911l6qrqzV37tzwRY2oYkYZAAAih89ZhFOo+eT48MOW26MCsW05ysrCV7gh5wGgU0JuTvzwww/ro48+0ssvv6xLL720TdFGkkzT1KWXXqrZs2dr5cqVevjhh7scLGIjVjPKRLNZXSI0xkuEGAGgs6LZBDVeMXMbwinUfPIddVRLT5tADEO+4uK9Hrcz31PIeQDonA6NuAnkf//3f3XQQQepeB8X8dGjR2vIkCF64403dPfdd4d6OMSQf0YZw+PR7h/nkZpRJprN6hKhMV4ixAgAnRXNJqjxLtqfs0huoeZT89ixksslu6Gh3XZyuYKOtgnlewo5DwCdE/KIm40bN8rlcnVoXZfLpU1hbmiG6PKWlspXXCwrN1d2erqs3Fz5iosjMqOMv1md6fHIaGyU6fHIUVYmV0lJQh8rVIkQIwB0lr8JqmHbMiQZti390AQ1FUXzcxbJL9R8ql+yRMrIkG0YsiXZhiFlZLQ8HkSo31PIeQDouJBH3GRnZ+uLL76Qx+NR3759g67n8Xj0xRdfKDs7O9RDIQ5Ea0aZaDarS4TGeIkQIwB0VjSboCYKZm5DOIWaT9aQIarbtEnOt9+Wo6xMvuLivZ6LXfmeQs4DQMeFPOLmlFNOUWNjo6699lpt27Yt4Drbtm3Ttddeq6amJp166qkhB4n4YRUVqfmccyL2wdqRZnWJeKxQJUKMANBZHWmCmqoi/TmL1BJqPjWPHatd99yzzwJqOL6nkPMAsG8hj7i566679M477+j999/XiBEjdOGFF+rggw9Wbm6uvv32W7ndbr3xxhv6/vvvlZWVpbvuuiuccSNJ+ZvVGR5Pu2XhblYXzWOFKhFiBIDOam2CGqh404EmqADiA99TACA6Qi7c5OXl6c0339S1116r9evX65VXXmm3jm3bys/P11//+lfl5eV1KVAkNkd5uXJWrpRj9Ghp5Mig60WzWV0iNMZLhBgBQPrhlomKClmFhfu8NoXaBBVAfOF7CgBER8iFG0k6/PDDtXz5cr3xxhtasGCB1q5dq/r6emVmZmro0KE644wzdNFFF6lbt27hihcJxj/TgFFVpd41NbJzcmTvY6YBb2lpy+wE1dUyamtb/mKTlxeRZnXRPFaoEiFGAKkr1Jnv6pcsUeYpp8gOMKsUgMTB9xQAiDyjpqYmyE3mQNdlnHGGnHv0KrAl+YqL1bBw4V63jWazukRojJcIMYZi586d2rBhgwYNGqTu3bvHOhzEEXIjMXTlOi+pw01Q90R+IBhyIzYS4XsKuYFgyA0EEy+50aURN/Fu7ty5eu6557Rq1Sp5vV71799fo0eP1h/+8AcNHDiwdb26ujo98MADmjNnjr755hv1799fF154oaZMmaLMzMwYPoPE1tUZkayioqh98EfzWKFKhBgBpJZwzHzXPHYst0YBSYDvKQAQOUlZuLFtW7feequef/55DR48WJdccokyMzO1ZcsWffDBB9qwYUNr4aahoUHjxo3TmjVrdNppp+nSSy/V6tWr9dhjj+mDDz7Q/PnzqbqGqCMzDfABDwCJi+s8AABA5HWpcGNZll555RW98847qqysVH19vewg03sahqFPPvmkK4frsKeeekrPP/+8rr/+ek2fPl0Oh6PN8ubm5tb//+ijj2rNmjW65ZZbNHXq1NbHp06dqpkzZ2rWrFmaPHlyVOJONqkw00BnmnHGSiLEGC28Fomlo03NEX4dPVdS4ToPAAAQayH3uPnuu+906aWXauXKlUGLNW0OZBjavn17KIfqlO+//14HH3ywcnJyVFZWJqczeG3Ktm0NHz5c3333ncrLy5WRkdG6rKGhQcOGDVPfvn2jVnBKRhlnnCFHWVm7mQY62vsgXoXajDOaEiFGKTr3jSbKa4EWuzc1NzrY1BzhEcq5knHKKXJ88kn76/zhh6shgo2G4+Wec8QfcgPBkBsIhtxAMPGSGyGPuJk+fbo+/PBDuVwuXXnllTrqqKOUm5sr0zTDGV+nLV68WDU1NZowYYJ8Pp/mz5+viooKZWdn65RTTlHBbn/9q6io0JYtW3T66ae3KdpIUkZGho4++mgtWrRIGzdubNMTBx3nn2nAqKpqnWnA/wMskblKSto04zQ8Hhkej1wlJXFTkEqEGKOF1yKx7Pl+yeORzfsVFSGdK7bdpmiz++MAAADoupALN3PmzJFpmnr55Zd10kknhTOmLvGPjnE4HDr++OO1bt261mWmaeqGG27QfffdJ6mlcCOpTTFndwUFBVq0aJEqKir2WbjZuXNnGKJPQhkZ+v6tt2R9+qnqP/lEmYcfLvPQQ1uWJehr5igvlxGkGadRVaWmVavkGzYs6nHtLhFi9GtsbGzzv+GWSK8FeL9iKZTX3lFeLmPTpsDbbNoU0fcr0tcOJC5yA8GQGwiG3EAwkcqNzo7eCblws3XrVg0aNCiuijaS5PnhPvsnnnhCI0eO1OLFizV06FCtXr1at9xyix5//HENHjxY1113nep+aKiYnZ0dcF9ZWVmS1Lre3mzevFk+ny9MzyIJZWdLJ5+sWknasCHW0XRJzsqV6l1TE3CZUVurHStXqtblim5Qe0iEGPe0devWiOw3EV+LVMb7FTuhvPbx8H5F6tqBxEduIBhyA8GQGwgmnLnhcDiCDh4JJuTCTZ8+fdSrV69QN48Yy7IkSenp6Zo9e7YGDBggSTruuOP0/PPP64QTTtDjjz+u6667LqzH3X///cO6v2hwlJfLuX69mgcPjvhfsBsbG7V161b1799f6enpET1WpDlGj5adkyMFacbZa/RoZQ0aFP3AdpMIMfpFOjcS6bUA71cshfLax/L9SqbPFYQXuZFY+D6KeEBuIJh4yY2QCzennXaa/vnPf+q7775Tz549wxlTl/hHyRx++OGtRRu/4cOHKz8/X5WVlaqpqWldt7a2NuC+/CNt/OvtTSI1sYplo9b09PSEeq0CGjlSdn6+bI+nXTNOOz9faSNHKi1WsfklQox7iFhuJOBrkdJ4v2InlNc+Dt6vpPhcQUSQG/GN76OIR+QGgol1boTcSfiOO+5Qt27dNGXKlLi6RWjIkCGSgt/+5H98586dKiwslCRVVlYGXNf/uH+9ZOFvPml6PDIaG2V6PHKUlclVUhLr0BKGt7RUvuJiWbm5stPTZeXmyldcHFdNlxMhxmjhtUgs/vfL17evrLQ0+fr25f2KklDOFc4vAKHg+ygAdFzII26qq6t155136p577tHHH3+sq6++WgcddJBce7mX/fjjjw/1cB124oknSpLWrl3bbllTU5MqKyuVkZGhvn37qn///howYIBWrFihhoaGdtOBr1ixQnl5eUk1o5TpdssM0nzSrK6W6XbLKiqKelyJxu7TRw0LF7a8npWVsgoK4u51S4QYo4XXIrH436+mVau0Y+VK9Ro9WmkjR8Y6rJQQyrnC+QWgs/g+CgCdE3Lh5txzz5VhtAyMdrvduvvuu/e6vmEY2rZtW6iH67DBgwfrtNNO0+LFi/XCCy/o6quvbl02Y8YM1dbW6rLLLpPT2fLUr7rqKj344IN66KGHNHXq1NZ1H3roIdXX12vy5MkRjzmazIoKGUGaLRu1tS1fuvmg7DCrqCjuX69EiDFaeC0Si2/YMNW6XMoaNIjbo6IslHOF8wtAR/F9FAA6J+TCzcCBA1sLN/HmkUce0VlnnaVf/epXmjdvnoYMGaLVq1fr3Xff1aBBg/THP/6xdd2bb75Z8+fP18yZM7V69WqNHDlSq1at0uLFizVq1ChNmjQphs8k/KzCQtlZWTKCNJK0OtndGgAAAOgMvo8CQOeEXLhZs2ZNOOMIq8GDB+vf//637r//fi1atEiLFy9W//799dOf/lS33367cnNzW9fNyMjQvHnz9MADD2ju3Ll677331L9/f910002aMmWKevToEcNnEn5WUZGs/HwZARpJWnl5/HUDCBPT7ZZZUSGrsJDzCogAR3m5claulGP0aIlb6YCEwvdRAOickAs38W7gwIGaNWtWh9bNzs7WtGnTNG3atAhHFR+8paUtXfyrq2XU1rb8ZSMvj0aSQBjEcpYMIBX4zzGjqkq9a2pk5+TI5hwDEg7fRwGg45K2cIPgaCQJRI5/lgw/w+OR4fHIVVKihoULYxgZkBz2PMfk8cjmHAMSDt9HAaDjuly4sSxLc+fO1dKlS7Vp0yZ9//33mjNnTuvyTz75RA0NDTr22GNlmiHPPo4IoJEkEF7MkgFEFucYkHz4PgoA+9alwo3b7dbEiRP15ZdfyrZtSWrXsLi0tFRPP/203njjDZ188sldORwAxDVmyQAii3MMAACkopCHwHg8Hl100UVau3atRowYoTvuuEMFATrAjx8/XrZta/78+V0KFOgo0+2Wc948mW53rENBivHPkhEIs2QAXcc5FhifewAAJLeQR9w8+uij+vrrr/WTn/xETzzxhAzD0JIlS7R+/fo2640aNUoZGRlatmxZl4MF9oamsIg1ZskAIotzrC0+9wAASA0hj7h555131K1bN02fPr3d7VF7ysvLU3V1daiHAjrE37DS9HhkNDbK9HjkKCuTq6Qk1qEhhXhLS+UrLpaVmys7PV1Wbq58xcXMkgGEif8c8/XtKystTb6+fVP2HONzDwCA1BDyiJsNGzaosLBQPXv23Oe6LpdL33//faiHAvaJhpWIF8ySAUSW/xxrWrVKO1auVK/Ro5U2cmSsw4o6PvcAAEgdIRdu0tPTtXPnzg6t6/F4lBXknnQgHGhYiXjDLBlAZPmGDVOty6WsQYOUFutgYoDPPQAAUkfIt0oVFBRow4YN2r59+17Xq6qqUlVVlQ4++OBQDwXsEw0rAQCphM89AABSR8iFm7Fjx6qpqUn33Xdf0HVs29bdd98twzB07rnnhnooYJ/8DSvtPR5P1YaVAIDkxuceAACpI+TCzS9+8QsNGDBAzz//vK666iotXrxYu3btktTS/+btt9/Weeedp/nz5ysvL08TJ04MW9BAIDSFBQCkEj73AABIDSH3uMnOzlZpaakuv/xyvfXWW5o3b17rspE/NAm0bVsDBgzQSy+9pB49enQ9WmAvaAoLAEglfO4BAJAaQi7cSNKIESP0wQcf6PHHH9cbb7yhysrK1mUHHHCALrroIt1yyy3q06dPlwMFOoqmsACAVMLnHgAAya1LhRtJysnJ0W9/+1v99re/ldfrVW1trTIyMphFCgAAAAAAoIu6XLjZncvlksvlCucuAQAAAAAAUlbYCjebN2/W2rVr9d1336lnz54aOnSo9t9//3DtHgAAAAAAIOV0uXDz5ptv6qGHHtLnn3/ebtkhhxyi3/zmN7rgggu6ehgAAAAAAICUE/J04JJ0xx136JprrtFnn30m27blcDiUm5srh8Mh27b16aef6pprrtHtt98erngBAAAAAABSRsiFm9dee01PP/20DMPQxIkTtXz5cm3dulXl5eXaunWrli9frokTJ8o0Tf3lL3/Ra6+9Fs64AQAAAAAAkl7IhZtnnnlGhmHokUce0cyZMzVs2DCZZsvuTNPUsGHDNHPmTD3yyCOybVvPPvts2IIGAAAAAABIBSEXbr744gv169dP/+///b+9rjdx4kT1798/YA8cYG9Mt1vOefNkut1JdaxQJUKMSH7RzENHeblyli6Vo7w84sdKBKG89olwHeXallgSIacQG7xfABA5ITcndjqdOuCAAzq07gEHHKCKiopQD4UUY2zbJldJicyqKhl1dbKzsmTl58tbWiq7T5+EPVaoEiFGJL9YnJdGVZV619TIzsmRncI5H8prnwjXUa5tiSURcgqxwfsFAJEX8oibQw45RFVVVbIsa6/r+Xw+rV+/XiNGjAj1UEgxrpISOcvKZHo8MhobZXo8cpSVyVVSktDHClUixIjkF4vz0uHxyGxuliPFcz6U1z4RrqNc2xJLIuQUYoP3CwAiL+TCzU033aTt27frwQcf3Ot6jzzyiHbs2KEbb7wx1EMhhZhut8yqqnaPG5LM6uqwDr+N5rFClQgxIvlxXsZOKK9HIrxfvM+JJRFyCrHB+wUA0RFy4Wbs2LGaPn26ZsyYoUsvvVQLFy7Upk2b1NTUpE2bNmnRokUaP368HnnkET344IM6++yzwxk3kpRZUSGjri7gMqO2VmZlZUIeK1SJECOSH+dl7ITyeiTC+8X7nFgSIacQG7xfABAdIfe46d27d+v/X7x4sRYvXhx03SlTpmjKlCntHjcMQ9u2bQs1BCQhq7BQdlaWDI+n3TI7O1tWQUFCHitUiRAjkh/nZeyE8nokwvvF+5xYEiGnEBu8XwAQHSGPuLFtu8v/9tUfB6nHKiqSlZ8ve4/HbUlWXp6soqKEPFaoEiFGJD/Oy9gJ5fVIhPeL9zmxJEJOITZ4vwAgOkIecbNq1apwxgG08paWtsxOUF0to7a25S82eXnylpYm9LFClQgxIvnF4rw0qqpaj+WfVSoVhfLaJ8J1lGtbYkmEnEJs8H4BQOQZNTU1exbJgbDbuXOnNmzYoEGDBql79+4d2sZ0u2VWVsoqKIj4X2yieaxQJUKMoQglNxA70czDplWrtGPlSvUaPVppI0dG9FiJIJTXPhGuo6Fux7UjNhIhp8iN2EiE7ynkBoIhNxBMvOQGhRtERbwkPOIPuYFgyA3sDfmBYMgNBENuIBhyA8HES26EfKtUMB999JFWrlyppqYmFRYW6vTTT1e3bt3CfRgAAAAAAICk1+HCzcaNG1VaWqqcnBxdd9117ZZ7vV5de+21+r//+782jx944IF68cUXdeihh3Y9WgAAAAAAgBTS4Vml3nnnHf3pT3/S+vXrAy6/7bbb9K9//Uu2bcswDOXm5kqSqqurVVJSooaGhvBEDAAAAAAAkCI6XLhZtmyZJOmSSy5pt6yyslIvv/yyDMPQeeedp/Xr16u8vFwrVqzQkCFDtGXLFr3wwgvhixoAAAAAACAFdLhw43a7lZGRoSOOOKLdsjfffFO2batXr1564oknlJWVJUkaMmSIpk2bJtu29a9//St8UQMAAAAAAKSADhduvv32Ww0ePDjgsv/85z8yDENnnXWWevbs2WbZ6aefrpycHLnd7q5FCgAAAAAAkGI6XLipqamRw+EIuGzVqlWSpBNPPDHg8gMOOEA1NTWdjw4AAAAAACCFdbhw43K59PXXX7d7fNOmTfrmm28kSSNHjgy4bVpammzbDjFEAAAAAACA1NTh6cCHDBmi//73v/rkk090+OGHtz6+YMECSVJmZqaGDx8ecNstW7aod+/eXYsUAAAAgdm2HLUfy/nNQjlqVshorpftzJQv52g19ztDvuwjJMOIdZQAACAEHS7cnH766froo480ZcoUvfjii8rNzdX69es1Y8YMGYahs88+W0aALwSbN2/W1q1bdfzxx4c1cAAAgJRn20rb+JK6VfxZRuMOmU3b2yxO+3aRrKqnZKf31q7CW9U08AoKOAAAJJgOF25+/vOf6y9/+YtWrlyp4cOHq0+fPvrmm29k27YcDoduvPHGgNvNmTNHkijcAAAAhFNTjVxlE+SoWyOzuS7oambTdqlpu7p/fqfSNr4sb/GLUlpO9OIEAABd0uEeN71799Yrr7yifv36qbm5WVu3bm0t2tx///0B+9vYtq2//e1vMgxDp556algDBwAASFlNNcpcdrac25fttWizO7O5Ts7tHyhz2dlSU01k44uh9H/9Swc88YTS//WvWIcCAEBYdHjEjSSNHj1aH330kRYsWKD169erZ8+eOuOMM5Sfnx9w/R07duj666+XYRg66qijwhEvAABAarNtucomyKwvl6HOTf5gyJZZXy5X2ZXyHjM3qW6bMr/8UpmnnCJ5vZJtS3//u+RyqX7JEllDhsQ6PAAAQtapwo0kZWRk6MILL+zQur1799ZPf/rTzh4CAAAAQaRtfEmOujWdLtr4GbLlqFuttI0vqWnQhDBHFzuZp5wio6HhxwdsW3ZDgzJPOUV1mzbFLjAAALqow7dKAQAAIMZsW90q/tzh26OCMZvr1K1iRsvIlCTgfPvtlpE2ezAkyettWQ4AQIKicAMAAJAgHLUfy2jcEZZ9GY3b5aj9OCz7ijXHhx8GL0LZthxlZdENCACAMKJwAwAAkCCc3yxsN+V3qMym7XJ+uzgs+4o131FHBe/XYxjyFRdHNyAAAMKIwg0AAGjDdLvlnDdPptsd61CwB0fNivDub8d/wrq/WGkeO1Zyudp1/bElyeVqWY6U5ygvV87SpXKUl8c6FADolE43JwYAAMnJ2LZNrpISmVVVMurqZGdlycrPl7e0VHafPrEOD5KM5vq43l8s1S9ZosxTTpHtn1XKMFpnlUJq81/bjKoq9a6pkZ2TI5trG4AEQuEGAABIklwlJXLu1gvE8HhkeDxylZSoYeHCGEYGP9uZGdf7iyVryBDVbdok68039f2SJepxyikyL7gg1mEhDux5bZPHI5trG4AEwq1SAABAptsts6qq3eOGJLO6mtum4oQv5+jw7q/XsWHdXzxoHDNGm2+4QY1jxsQ6FMQBrm0AkgGFGwAAILOiQkZd4CmmjdpamZWVUY4IgTT3O0NWWu+w7MtK663m3NPCsi8gXnFtA5AMKNyksFCaT9KwEomM/EW4JVNOWYWFsrOyAi6zs7NlFRREOSIE4ss+QnZ6r7Dsy07vLV/2EWHZFzouma4b4RDp14NrG4BkQI+bFBRK80kaViKRkb8It2TMKauoSFZ+fktfm90etyVZeXmyiopiFRp2ZxjaVThZ3T+/U2Zz4FEEHWE5s7Sr8NbgU2gj7JLxutEV0Xo9uLYBSAaMuElB/gZtpscjo7FRpscjR1mZXCUlYd0GiBfkL8ItWXPKW1oqX3GxrNxc2enpsnJz5Ssulre0NNahYTdNA6+QL2uEbIVWdLFlyJd1mJoGXhHmyLA3yXrdCFU0Xw//tc3Xt6+stDT5+vbl2gYgoTDiJsV0pEHbnn95CGUbIF6Qvwi3ZM4pu08fNSxc2PIcKytlFRQk7HNJaoYhb/FsZS47W2Z9uQzZHd7UliErc5i8xS8y2iaKkvm6EYpovx7+a1vTqlXasXKleo0erbSRI8O2fwCINEbcpJhQGrTR1A2JjPxFuKVCTllFRWo+55yU+iGZcNJyVH/cO2rufZwsZ+D+HXuynFlq7n286o97R0rLiWx8aCMVrhudEavXwzdsmGpPPlm+YcMisn8AiBQKNykmlAZtNHVDIiN/EW7kFOJGWo68x7ylncOnyZdxUNDZpqy03vJlHKSdw6fJe8xcijYxwHWjLV4PAOgcbpVKMaE0aKOpGxIZ+YtwI6cQSabbLbOiQlZhYcdyyTDUNGiCmgZeIUftx3J+u0iOHctlNNfLdmbK1+tYNeee1jJ7FLdGxUwqXDc6k7up8HoAQDhRuElB3tLSli7+1dUyamtb/rKRl7fXBm2hbAPEC/IX4UZOIdy6PMOOYciXM0q+nFGRDxYhSdbrRqi5m6yvBwBEAoWbFBRK80kaViKRkb8IN3IK4eafYcfP8HhkeDxylZSoYeHCGEaGcEnW60aouZusrwcARAKFmxRmFRV1+gMylG2AeEH+ItzIKYQDMw6llmS6boQjd5Pp9QCASKE5MQAAQAwx4xASFbkLANFB4QadYrrdcs6bJ9PtjnUo6CDeMwCIvs5ce5lhB4kq0XLXUV6unKVL5Sgvj3UoANAp3CqFDuly00REHe8ZAERfKNdeZthBokqU3PWfl0ZVlXrX1MjOyZHNdyIACYQRN+gQf+M50+OR0dgo0+ORo6xMrpKSWIeGIHjPACD6Qr32ektL5SsulpWbKzs9XVZurnzFxcywg7iXCLnrPy8dHo/M5mY5+E4EIMEw4gb7RNPExMN7BgDR15VrLzPsIFHFe+7ynQhAMmDEDfaJxnOJh/cMAKIvHNdeq6hIzeecww9JJJx4zV2+EwFIBhRusE+J1ngOvGcAEAtce4H4w3kJIBlQuME++RvP2Xs8Hm+N5/Aj3jMAiD6uvUD84bwEkAwo3KBDEqHxHNriPQOA6OPaC8Qf/3np69tXVlqafH37cl4CSCg0J0aHxHvjObTHewYA0ce1F4g//vOyadUq7Vi5Ur1Gj1bayJGxDgsAOozCDTrFKiriC2iC4T0DgOjj2gvEH9+wYap1uZQ1aJDSYh0MAHQCt0oBAAAAAADEKUbcAACAlGC63TIrKmQVFjIaBkhgnMsAUg2FGwAAkNSMbdvkKimRWVUlo65OdlaWrPx8eUtLZffpE+vwAHQQ5zKAVMWtUgAAIKm5SkrkLCuT6fHIaGyU6fHIUVYmV0lJrEMD0AmcywBSFYUbAACQtEy3W2ZVVbvHDUlmdbVMtzvqMQHoPM5lAKmMwg0AAEhaZkWFjLq6gMuM2lqZlZVRjghAKDiXAaQyCjcAEpLpdss5bx5/YQMiIBHOL0d5uXKWLpWjvHyv61mFhbKzsgIus7OzZRUURCI8hEEi5CGih3MZQCqjOTGAhEJjQiByEuH88sdoVFWpd02N7Jwc2XuJ0SoqkpWfL8PjkbHb47YkKy+PGWniUCLkIaKPcxlAKmPEDYCEQmNCIHIS4fzyx+jweGQ2N8vRgRi9paXyFRfLys2VnZ4uKzdXvuJieUtLoxg5OioR8hCxwbkMIFUx4gZAwuhIY0L+4gaEJhHOr1BjtPv0UcPChS3bV1bKKiiI+XNBYImQh4gdzmUAqYoRNwASBo0JgchJhPOrqzFaRUVqPuccfujFsUTIQ8Qe5zKAVEPhBkDCoDEhEDmJcH4lQozoGt5jAADao3ADIGH4GxPaezwe6caEzGyCVJAI51esYkT08B4DANAePW4AJBRvaWnLbCPV1TJqa1v+ApuXF5HGhMxsglSTCOeXP0ajqqo1Rv+sUkgO0cxDAAASAYUbAAklmo0J/TOb+BkejwyPR66SEjUsXBiRYwKxlAjnlz/GplWrtGPlSvUaPVppI0dGJEbEBg1oAQBoi8INgIRkFRVF9Is8M5sglSXC+eUbNky1LpeyBg1SWmTCRIxFOg8BAEgU9LgBgACY2QSIHM4vAACAjqNwAwABMLMJEDmcXwAAAB1H4QYAAmBmEyByOL8AAAA6jsINAAThLS2Vr7hYVm6u7PR0Wbm58hUXM7MJEAacXwAAAB1Dc2IACIKZTYDI4fwCAADomJQZcTNz5kzl5OQoJydHK1eubLe8rq5Od911lw499FD169dPI0aM0D333KP6+voYRAsgnlhFRWo+5xx+VAIRwPkFAACwdylRuPn88881bdo0ZWRkBFze0NCgcePGadasWRo6dKhuuOEGDRkyRI899pjOP/987dy5M8oRAwAAAAAApEDhpqmpSZMmTdKIESM0bty4gOs8+uijWrNmjW655Ra9/vrrmjp1ql5//XXdcsst+u9//6tZs2ZFOWogfEy3W85582S63RwLQNJwlJcrZ+lSOcrLYx0KAABARCV9j5uHH35YbrdbS5cu1aOPPtpuuW3b+p//+R9lZmbqtttua7Pstttu01/+8he98MILmjx5crRCBsLC2LZNrpISmVVVMurqZGdlycrPl7e0VHafPhwLQELyXwOMqir1rqmRnZMjm2sAAABIYkk94uaTTz7RI488oilTpqgoyL3zFRUV2rJli44++uh2t1JlZGTo6KOPVlVVlTZu3BiNkIGwcZWUyFlWJtPjkdHYKNPjkaOsTK6SEo4FIGH5rwEOj0dmc7McXAMAAECSS9oRN7t27Wq9Rermm28Oul5FRYUkqaCgIODygoICLVq0SBUVFRo4cGDQ/dAHZ+8aGxvb/C8iy1FeLqOqqt3jhiSjqkpNq1bJN2xYXByrM7kRzeeF2OO6gT1xDUBHcO1AMOQGgiE3EEykcqN79+6dWj9pCzf333+/KioqtGTJEjkcjqDr1dXVSZKys7MDLs/KymqzXjCbN2+Wz+cLMdrUsXXr1liHkBJyVq5U75qagMuM2lrtWLlStS5XXB2rI7kRzeeF+MF1A35cA9AZXDsQDLmBYMgNBBPO3HA4HEEHjgSTlIWbDz/8UI899pjuuOMODR8+PCrH3H///aNynETV2NiorVu3qn///kpPT491OGHjKHfIud6p5sHN8g2Ln8KdY/Ro2Tk5ksfTbpmdna1eo0cra9CguDhWZ3Ijms8LsZes141kVe5waL3TqcHNzRrWiT9kdGY7rgHoCK4dCIbcQDDkBoKJl9xIusJNc3OzJk2apEMOOUS33nrrPtf3j6ipra0NuNw/0sa/XjCdHeqUqtLT05PitTK2GXKVuGRWmTLqDNlZtqx8S95Sr+w+dqzDk0aOlJ2fL9vjkbHbw7YkOz9faSNHKi3OjtWh3Bg5UvbAgYGPNXBgeJ8X4kayXDeS1TbDUInLpSrTVJ1hKMu2lW9ZKvV61ccOfj0MabtoXtuQ8Lh2IBhyA8GQGwgm1rmRdIWb+vr61r41ubm5Adc588wzJUkvvvhia9PiysrKgOv6Hy8sLAx3qEhgrhKXnGU/nj6Gx5DhaSnmNCxsiGFkP/KWlrbMvlRdLaO2VnZ2tqy8PHlLSxP6WLLtNj/Ydn8cQPSVuFwqc/54PfQYhjw/FGUWNgS/Hoa6nf96Y1RVtV5v/LNKAQAAJKOkK9x069ZNV111VcBly5YtU0VFhcaOHau+ffvqwAMPVGFhoQYMGKAVK1aooaGhzcxSDQ0NWrFihfLy8vbamBipxXSbMqvaT8hmyJBZbcp0m7KKrBhE1pbdp48aFi6U6XbLrKyUVVAgK8jsaolyLNPtlrlpU7vHDUnm5s0y3e6IPUcA7blNU1VmgAkqDUPVpim3aarIan89DHU76cfrTdOqVdqxcqV6jR6ttJEju/pUAAAA4lbSFW569Oihxx57LOCySZMmqaKiQpMnT9bo0aNbH7/qqqv04IMP6qGHHtLUqVNbH3/ooYdUX1+vyZMnRzpsJBCzouX2qECMWkNmZXwUbvysoqKoFTMifSyzokJGkEbhRm1tS9GIwg0QNRU/3OYUSK1hqDJIASbU7XbnGzZMtS6XsgYN4vYoAACQ1JKucBOKm2++WfPnz9fMmTO1evVqjRw5UqtWrdLixYs1atQoTZo0KdYhIo5YhZbsLFuGp/2PDjvbllUQP0WbZGMVFsrOypIRpDGp1cnu7AC6ptCylGXb8gQowmTbtgqCFF9C3Q4AACAVBRinnHoyMjI0b948TZo0SWvXrtXjjz+utWvX6qabbtKbb76pHj16xDpExBGryJKVb8lW254qtmxZeVZcjbZJNlZRkaz8fO3ZzcaWZOXlMdoGiLIiy1K+ZbXvMWXbyrOsoKNmQt0OQOe4TVPznE65A92aCABIGCk14ubJJ5/Uk08+GXBZdna2pk2bpmnTpkU5KiSi75/8XpmnZMr22i1VA0OSq+VxRFZUGyED2KdSr1clLpeqTVO1hqHsH4ovpV5vRLYDsG+hzvYGAIhPKVW4AcKlx6QeMhp2G+JvS3aDrR6TesTNrFLJKppNlwHsWx/b1sKGBrlNU5WmqYIOjpgJdTsA+xbqrG0AgPhE4QbopESZVSrZRbPpMoB9Kwqx8BLqdgAC68qsbQCA+MQNr0AndWRWKQAAgFjoyKxtAIDEwpUbUeEodyhnaY4c5Y5Yh9Jl/lmlAmFWKcQCzScBAH7+WdsCYdY2AEhM3CqFiDK2GXKVuGRUGepd01t2ji0735a31Cu7T2I2x/PPKmV4DBn68S9azCqFaKP5JABgT/5Z2zyGIe0+8oZZ2wAgYfHnWUSUq8QlZ5lTDo9DZrMph8chR5lDrhJXrEPrEm+pV75in6xcS3a6LSvXkq/YJ28ps6EgevzNJz2mqUbDkMc0VeZwqMSV2OcXAKBrSr1eFft8yrUspdu2ci1LxT4fs7YBQIJixA0iJpmb+Np9bDUsbGh5jpWmrAJG2iC6aD4JAAiGWdsAILlQuEHEdKSJb6IXO6wiCjaIjY40n+RLOgCkNmZtA4DkwK1SiBia+AKRQ/NJAAAAIDVQuEHE+Jv42mr745ImvkDX+ZtPas/iDc0nAQAAgKRC4QYR5W/i6+vrk5VmydfXRxNfIExoPgkAAAAkP3rcIKL8TXybVjVpx8od6jW6l9JGpsU6LCAp0HwSAAAASH4UbhAVvmE+1bpqlTUoS2micAOEE80nAQAAgOTFrVIAAAAAAABxisINAAAAAABAnKJwAwAAAAAAEKco3AAAAAAAAMQpCjcAAAAAAABxisINAAAAAABAnKJwAyCmHOUO5SzNkaPcEetQkMLcpql5TqfcJh+LAAAAiC/OWAcAIDUZ2wy5Slwyqgz1ruktO8eWnW/LW+qV3ceOdXhIEdsMQyUul6pMU3WGoSzbVr5lqdTrVR+bPAQAAEDs8adFADHhKnHJWeaUw+OQ2WzK4XHIUeaQq8QV69CQQkpcLpU5nfKYphoNQx7TVJnDoRIXeQgAAID4QOEGQNSZblNmVfvLjyFDZrUp082lCZHnNk1VBbo1yjBUbZrcNgUAAIC4wLdSAFFnVpgy6oyAy4xaQ2YllyZEXsUPt0cFUmsYqqRwAwAAgDjAt1IAUWcVWrKzAvcPsbNtWQVWlCNCKiq0LGUF6WOTbdsqsMhDAAAAxB6FmxRmuk055znj9raUeI8PobOKLFn5lmy1/dFsy5aVZ8kq4gczIq/IspRvWdKexRvbVp5lqYjCTVQk64xeyfq8AABA9DGrVAryz+ZjVrXcrmJn2bLyrbiZzSfe40N4eEu9rbNKGbWG7OwfZ5UCoqXU61WJy6Vq01StYSj7h6JNqZc8jLRkndErWZ8XAACIHQo3Kcg/m4+f4TFkeFqKJQ0LG2IYWYt4jw/hYfex1bCwQU2rmrRj5Q71Gt1LaSPTYh0WUkwf29bChga5TVOVpqkCRtpEjX9GLz+PYcjzQ9FjYUPiXuuT9XkBAIDYYfxuion32XziPT6En2+YT7Un18o3zBfrUJDCiixL5zQ3U7SJkmSd0StZnxcAAIgtvkGkmHifzSfe4wMAdF2yzuiVrM8LAADEFt8gUky8z+YT7/EBALouWWf0StbnBQAAYovCTYqJ99l84j0+AEDXJeuMXsn6vAAAQGxRuElB3lKvfMU+WbmW7HRbVq4lX7Evbmbziff4AABdV+r1qtjnU65lKd22lWtZKvb5En5Gr2R9XgAAIHaYVSoF+WfzMd2mzEpTVkF8jWSJ9/gAAF2XrDN6JevzAgAAsUPhJoVZRfFdEIn3+AAAXVeUpIWNZH1eAAAg+rhVCgAAAAAAIE5RuAEAAAAAAIhTFG4AAAAAAADiFIUbAAAAAACAOEXhBgAAAAAAIE5RuAEAAAAAAIhTFG4Qt0y3Kec8p0w3aQoAADqm3OHQ0pwclTscsQ4FAICwcMY6AGBPxjZDrhKXzCpTRp0hO8uWlW/JW+qV3ceOdXgAACAObTMMlbhcqjIM1fTurRzbVr5tq9TrVR+b7w8AgMTFUAbEHVeJS84yp0yPKaPRkOkx5ShzyFXiinVoAAAgTpW4XCpzOuVxONRsmvI4HCpzOFTi4vsDACCxUbhBXDHdpsyq9mlpyJBZbXLbFAAAaMdtmqoyA3xHMAxVm6bcgZYBAJAg+BRDXDErWm6PCsSoNWRWkrIAAKCtCtNUnRH4+0OtYaiSwg0AIIHxKYa4YhVasrMC34duZ9uyCqyIHJdGyED8ocEogI4qtCxlBeljk23bKrAi8/0BAIBooDkx4opVZMnKt2R4DBn68S9ntmxZeZasovB+8aIRMhB/aDAKoLOKLEv5liWPYUi7j7yxbeVZlooo3AAAEhjDCxB3vKVe+Yp9snIt2em2rFxLvmKfvKXesB+LRshA/KHBKIBQlHq9Kvb51NfnU5plqa/Pp2KfT6Xe8H9/AAAgmhhxg7hj97HVsLChpVFxpSmrIPwjbaSONUKOxHEBBNeRBqP85RxAIH1sWwsbGrSqqUkrd+zQ6F69NDItLdZhAQDQZRRuELesosgUbPw60giZwg0QXR1pMErhBsDeDPP55Kqt1aCsLInCDQAgCXCrFFJWrBohAwiOBqMAAABAWxRukLL8jZBttf2RGKlGyKmA2bm6LtVfQ3+DUe1ZvKHBqNymqXlOp9xMa5zUeJ8BAMCeuFUKKc1b6m2ZVaralFFrtIy0ybMi0gg5mTE7V9fxGv6o1OttnVWq1jCUvdusUqmodZatH24jy7Jt5VsWs2wlGd5nAAAQDIUbpLRoNUJOdv7ZufwMjyHD01KIaFjYEMPIEgev4Y9oMNqWf5YtP49hyPPDj/yFDamVG8mM9xkAAATDOFxALbdNNZ/TTNEmBB2ZnQt7x2sY2DCfTyfX1mqYzxfrUGKmI7NsIfHxPgMAgL3hmwCALunI7FzYO15DBNORWbaQ+HifAQDA3vBNAECXMDtX1/EaIhhm2UoNvM8AAGBvKNwA6BJm5+o6XkMEwyxbqYH3GQAA7A2FGwBd5i31ylfsk5VryU63ZeVa8hX7mJ2rE3gNEUyp16tin0+5lqV021auZanY50vZWbaSFe8zAAAIhlmlAHQZs3N1Ha8hgvHPsuU2TVWapgoYgZGUeJ8BAEAwFG4AhI1VRLGhq3gNEUwRP+RTAu8zAADYE7dKAQAAAAAAxCkKNwAAAAAAAHGKwg0AAAAAAECconADAAAAAAAQpyjcAAAAAAAAxCkKNwAAAAAAAHGK6cABJCTTbcqsMGUVMn02EIzbNFVhmipkimkAAICEReEGQEIxthlylbhkVpky6gzZWbasfEveUq/sPnaswwPiwjbDUInLpSrTVJ1hKMu2lW9ZKvV61cfmPAEAAEgk3CoFIKG4SlxyljllekwZjYZMjylHmUOuElesQwPiRonLpTKnUx7TVKNhyGOaKnM4VOLiPAEAAEg0FG4AJAzTbcqsan/ZMmTIrDZlurmkAW7TVJUZ4FwwDFWbptyBlgEAACBu8e0NQMIwK1pujwrEqDVkVnJJAyp+uD0qkFrDUCWFGwAAgITCtzcACcMqtGRnBe7PYWfbsgpovgoUWpaygvSxybZtFdCkGAAAIKFQuAFiwHSbcs5zcmtPJ1lFlqx8S7ba/ii1ZcvKS47ZpdymqXlOJ7ezIGRFlqV8y5L2LN7YtvKYXQoAACDhMKsUEEXMiNR13lJvy2tYbcqoNVpG2uS1vIaJjFmAEE6lXq9KXC5Vm6ZqDUPZPxRtSr2JfZ4AAACkIgo3QBT5Z0TyMzyGDE9LMadhYUMMI0scdh9bDQsbWhoVV5qyCpJjpI1/FiA/j2HI80MxZ2EDuYHO6WPbWtjQILdpqtI0VcBIGwAAgIRF4QaIko7MiJQMBYhosYqSo2AjdWwWIH50IxRFFGwAAAASHk0UgChhRiQEwyxAAAAAAILh1wAQJcyIhGB2nwXo4M+l899s+V+JWYCAeEDTcAAAEEvcKgVEiX9GJMNjyNCPoyuSaUYkhKbIsjTyG0t/vNBQwXpDOTVSTY5UOdjWPf9rqagHuQHEAk3DAQBAPKBwA0RRss6IhK576zype9mPBb3+30i537Q8vmthDAMDUhhNwwEAQDygcANEUbLOiISuMd2m0gM0rjZlKL3aVBONq4Goo2k4AACIF9ysDcSAVWSp+ZxmfoxDEo2rgXhE03AAABAvGHEDJBLblqP2Yzm/WShHzQoZzfWynZny5Ryt5n5nyJd9hBTkhwbil79xteFp/97RuBqIDX/TcE+AaypNwwEAQDRRuAESgW0rbeNL6lbxZxmNO2Q2bW+zOO3bRbKqnpKd3lu7Cm9V08ArKOAkEBpXA/GnyLKUb1kthZvdr6e2rTzL4jYpAAAQNYzzBeJdU41cy89V98/vlKOhol3Rxs9s2i5Hwzp1//xOuZafJzXVRDdOdIm31CtfsU9WriU73ZaVa8lX7KNxNRBDpV6vin0+5VqW0m1buZalYp9PpV7OSwAAED2MuAHiWVONMpedLbO+XIY6NvWs2VwnY/sHylx2tuqPe0dKy4lsjAgLGlcD8aePbWthQ4PcpqlK01QBI20AAEAMULgB4pVty1U2oVNFGz9Dtsz6crnKrpT3mLncNpVArCIKNkC8KaJgAwAAYohbpYA4lbbxJTnq1nS6aONnyJajbrXSNr4U5sgAAAAAANFC4QZR4Sh3KGdpjhzljliHkhhsW90q/iyzua5LuzGb69StYoZkh1b8QfS5TVPznE65mWoYAAAAgLhVChFmbDPkKnHJqDLUu6a37Bxbdr4tb6lXdh+KCcE4aj+W0bgjLPsyGrfLUfuxfDmjwrI/RMY2w1CJy6Uq01SdYSjLtpVvWSr1etWHwhsAAACQsviTLiLKVeKSs8wph8chs9mUw+OQo8whV4kr1qHFNec3C4POHtVZZtN2Ob9dHJZ9IXJKXC6VOZ3ymKYaDUMe01SZw6ESF+cKAAAAkMoo3CBiTLcps6p9ihkyZFabMt2kXzCOmhXh3d+O/4R1fwgvt2mqKtCtUYahatPktikAAAAghSXdr4HNmzdr1qxZuuiii3TooYcqNzdXQ4cO1VVXXaWysrKA29TV1emuu+7SoYceqn79+mnEiBG65557VF9fH+Xok4tZYcqoCzybkVFryKxMuvQLG6M5vLkX7v0hvCp+uD0qkFrDUCWFGwAAACBlJd2vgWeeeUZ33XWXqqqqdOqpp+qmm27SMccco/nz5+uss87S66+/3mb9hoYGjRs3TrNmzdLQoUN1ww03aMiQIXrsscd0/vnna+fOnTF6JonPKrRkZwXuzWFn27IKIjO1quk25ZznjMqInkgdy3ZmxvX+EF6FlqWsIH1ssm1bBRGahphGyACihesNAAChS7rmxKNGjdJbb72lE044oc3jy5Yt0wUXXKDJkydr3Lhx6tatmyTp0Ucf1Zo1a3TLLbdo6tSpretPnTpVM2fO1KxZszR58uRoPoWkYRVZsvItGR5Dhn4cTWDLlpVnySoK749RfyNks6plpI+dZcvKtyLSCDnSx/LlHK20bxeFIdIf9tfr2LDtC+FXZFnKtyx5DEPafeSNbSvPslQU5sINjZABRAvXGwAAui7p/uxx/vnntyvaSNJxxx2nE088UTU1Nfr8888lSbZt63/+53+UmZmp2267rc36t912mzIzM/XCCy9EJe5k5S31ylfsk6+vT1aaJV9fn3zFPnlLvWE/lr8RsukxZTQaMj1mxBohR/pYzf3OkJXWOyz7stJ6qzn3tLDsC5FT6vWq2OdTrmUp3baVa1kq9vlU6g3/uUIjZADRwvUGAICuS7oRN3uTlpYmSXI4HJKkiooKbdmyRaeffroyMjLarJuRkaGjjz5aixYt0saNGzVw4MC97ptbqoLIkL5/63tZn1qq/6RemYdnyjz0h3phGF8yR7lDRlX7HiGGDBlVhppWNck3zJc4x+p2sLo7c8Iys5SV1ksN3Q6W4jRHGxsb2/xvqsqQ9Nb336vc4VCV06n85mYN87XkUTjfuXKHQ1WB+ukYhqoMQ6uamlqPG2vkBvaG/Ih/sbrekBsIhtxAMOQGgolUbnTv3r1T66dM4WbDhg1asmSJ9ttvPx1yyCGSWgo3klRQUBBwm4KCAi1atEgVFRX7LNxs3rxZvjj5sROXsiWdLNWqVtoQ/t3nrMxR75rAI1SMWkM7Vu5Qras2oY7lzbpSg3b9WU4r9MbCzWamNvScoG0bN3Y5nkjbunVrrEOICy5Jw3/4/xE4VbQyJ0c1vQPnb61haOWOHXLVhudcCRdyA3tDfsSvWF9vyA0EQ24gGHIDwYQzNxwOR9AaRDApUbhpamrSz3/+c+3atUtTp05tHXFTV1cnScrOzg64XVZWVpv19mb//fcPU7TJqbGxUVu3blX//v2Vnp4e9v07Rjtk59iSp/0yO9tWr9G9lDUoK7GONXCSrP8ukF2zXIY63wfAliEr6zC5DpkkV5AZi+JBpHMDbY12OJRj24HSV9m2rdG9emlQVnjOla4iN7A35Ef8i9X1htxAMOQGgiE3EEy85EbSF24sy9INN9ygZcuWaeLEibr88ssjcpzODnVKVenp6ZF5rUZKdr4t22O3a4Rs59tKG5mmNKUl3LG+P+plOZadLbO+vFPFG1uGrMxh+v6ol9Q9rUdYYokUR7lDOStz1GN0D6WNDNN7lMBMtymzwpRVGP4G3pI0UlK+bctj2+0aIefbtkampUlp8fU+ROy6gaRAfsSvWF9vki033KapCtNUYQSa1odDvMe3u2TLDYQPuYFgYp0bSV24sSxLN954o1577TVddtllmjFjRpvl/hE1tUGG6fpH2mTFyV+fsXfeUm/LTE/Vpoxao2XK8TwrIo2Qo3astBzVH/eOXGUT5KhbI7N536O/LGeWfFmHyVv8opSWE954wsg/M5dRZah3TW/ZOS2Fr0jMApYIojkrWqnXqxKXS9WmqVrDUPYPs1dFohEygNTG9abr4n1mrniPDwCSQdIWbvwjbV555RVdeumlevLJJ2WabSfRKiwslCRVVlYG3If/cf96iG92H1sNCxtaRixUmrIKIjNiIdrHUlqOvMe8pbSNL6lbxQwZjdsDNi220nrLTu+tXYW3qmngFW3/uhmH/DNztfJItseWq8SlhoUNsQssRvZ8PQyPIcNjROT16GPbWtjQILdpqtI0VZAAfx0FkJi43nSdf2YuP49hyPNDsWRhQ+w/L+M9PgBIBklZuNm9aHPxxRfr6aefbu1rs7vCwkINGDBAK1asUENDQ5uZpRoaGrRixQrl5eXtszEx4otVFMEiSqyOZRhqGjRBTQOvkKP2Yzm/XSTHjuUymutlOzPl63WsmnNPky/7iLgv2Eg/3A5UZbZ73JAhs9qU6Taj9h7Gg1i9HkX8gAIQJVxvQuM2TVWZ7T8fZBiqNk25TTOmr2u8xwcAySLpCjf+26NeeeUVXXjhhXrmmWcCFm0kyTAMXXXVVXrwwQf10EMPaerUqa3LHnroIdXX12vy5MlRihzoAMOQL2eUfDmjYh1Jl5gVLbcDBWLUGi2jmFKpcMPrAQAIoOKH248CqTUMVca4MBLv8QFIUrbd8sfsbxbKUbPixz9m5xyt5n5nJMwfszsj6Qo306dP18svv6zMzEwddNBBeuihh9qtM27cOB122GGSpJtvvlnz58/XzJkztXr1ao0cOVKrVq3S4sWLNWrUKE2aNCnaTwExEOmGsGjLKrRkZ9kyPO0vqHa2Lasgtd4DXg8AQCCFlqUs25YnwA+QbNtWQYyLIvEeH4AkY9s/tI/4s4zGHe3aR6R9u0hW1VMJ1T6io5KucPPVV19Jkurr6/Xwww8HXOfAAw9sLdxkZGRo3rx5euCBBzR37ly999576t+/v2666SZNmTJFPXrE94w86JpoNoTFj6wiS1a+1dLHZY+Zuay81CueWUWWGvMtpXsMmbu9HpZsNean3usBAGhRZFnKt6yWwsgeM3PlxcHtZ/EeH4Ak0lTToQlbzKbtUtN2df/8TqVtfDnuJ2zpKKOmpoZfp4i4nTt3asOGDRo0aFBcTbGXcUZG2wa5aike+Ip9KdkgN5p2n1XKPzNXKs8qdcn3GfrjhU4VrJeya6TaHKlysK17/tenf/ZIzVyM1+sG4gP5gWCSLTf8szYFmpkrHmZtivf4dpdsuYHwITfiXFONMpedLbO+XIY6fl2xZcjKHKb6494JuXgTL7mRdCNugI6iQW5s+WfmalrVpB0rd6jX6F5KG5kW67Biwm2aWtXP1HHLpYM/lw5aJ607SPpiuKFcy5S7gR4BAJCq4n1mrniPD0CCs225yiZ0umgjSYZsmfXlcpVdKe8xcxP6tikKN0hZNISND75hPtW6apU1KEtpSs3Cze7NHb8Y3vLPj+aOAAAp/mfmivf4ACSmtI0vyVG3ptNFGz9Dthx1q5W28SU1DZoQ5uiiJ8D8fUBq8DeEDYSGsIgmf3PHQGjuCAAAgJRk2+pW8ee99rTpCLO5Tt0qZkhxdvtmZ1C4QdIx3aac85wy3XtPb3+DXHuP6m2qNshNNG7T1DynU24z8S9j/uaO7T5MaO4IAACAFOWo/VhG446w7Mto3C5H7cdh2VcscKsUkkYoM0R5S70t21SbrQ1yrbyWbRCf/E0Qq364vSjLtpUfp00QO6PU6w3a3BEAAABINc5vFrab8jtUZtN2Ob9dLF/OqLDsL9oo3CBpuEpcbWaIMjyGDE9LMSfYDFH+Brmm22zpaVPASJt4V+Jyqcz54/vsMQx5fijmLGxI3NmXaO4IAAAA/MhRsyK8+9vxn7DuL5oo3CApdHWGKKuIgk0icJumqgLdGmUYqjZNuZOgiS/NHQEAAADJaK6P6/1FU+I3hwDUsRmikPh2n31pT/7ZlwAAAAAkPtuZGdf7iyZ+5SAqyh0OLc3JUbnDEZH9d3WGqI42NEZsMfsSAAAAkBp8OUeHd3+9jg3r/qKJW6UQUa2NZA1DNb17K8e2lW/bYW8k658hyvAYMvTjiIx9zRAVSkNjxI5/9iWPYUi7j7xh9iUAAAAgqTT3O0NW1VNhaVBspfVWc+5pYYgqNhhegIjyN5L1OBxqNk15HA6VORwqcbnCfixvqVe+Yp+sXEt2ui0r15Kv2LfXGaL8DY1Njymj0ZDpMeUoc8hVEv74EB6lXq+KfT7lWpbSbVu5lqVin4/ZlwAAAIAk4ss+QnZ6r7Dsy07vLV/2EWHZVyww4gYRE+1Gsp2dIaqrDY0RG8y+BAAAAKQAw9Cuwsnq/vmdMpvrQt6N5czSrsJb247YTzCMuEHExKqRrFVkqfmc5n0WXWhonNiKLEvnNDdTtAEAAACSVNPAK+TLGiFboRVdbBnyZR2mpoFXhDmy6OKXKTrFbZqa53TK3YGiS1cbyUa6YXBXGxoDAAAAACLIMOQtni0rc1inize2DFmZw+QtfjGhR9tI3CqFDmptMvzDKJos21a+Ze21yXCojWSj1TA41IbGAAAAAIAoSctR/XHvyFU2QY66NR26bcpyZsmXdVhL0SYtJ/IxRhgjbtAhrU2GTVONhiGPaXaoybC/kWxfn09plqW+Pt8+G8lGs2FwKA2NAQAAAABRlJYj7zFvaefwafJlHCQrrXfA1ay03vJlHKSdw6fJe8zcpCjaSIy4QQd0pcmwv5HsqqYmrdyxQ6N79dLItLSgx4p2w+DONjQGAAAAAMSAYahp0AQ1DbxCjtqP5fx2kRw7lstorpftzJSv17Fqzj2tZfaoBL81ak8UbrBPHWkyvK8GscN8PrlqazUoK0vaW+GmAw2DI1FYsYoo2AAAAABA3DMM+XJGyZczKtaRRA23SmGfutpkuDNoGAwAAAAAwI8o3GCf/E2GtWfxZh9NhkPhbxhsq+2xaBgMAAAAAEhFFG7QIf4mw7mWpXTbVq5l7bPJcKhoGAwAAAAAQAt63KBD/E2G3aapStNUQZhH2uyOhsEAAAAAALSgcINOKYpgwWZPNAwGAAAAAKQ6bpUCAAAAAACIUxRuAAAAAAAA4hSFGwAAAAAAgDhF4QYAAAAAACBOUbgBAAAAAACIUxRuAAAAAAAA4hSFGwAAAAAAgDhF4QYAAAAAACBOUbgBAAAAAACIUxRuAAAAAAAA4hSFGwAAAAAAgDhF4QYAAAAAACBOUbgBAAAAAACIUxRuAAAAAAAA4hSFGwAAAAAAgDhF4QYAAAAAACBOUbgBAAAAAACIUxRuAAAAAAAA4hSFGwAAAAAAgDhF4QYAAAAAACBOUbgBAAAAAACIUxRuAAAAAAAA4hSFGwAAAAAAgDhF4QYAAAAAACBOUbgBAAAAAACIUxRuEDUOhyPWISBOkRsIhtzA3pAfCIbcQDDkBoIhNxBMPOSGUVNTY8c6CAAAAAAAALTHiBsAAAAAAIA4ReEGAAAAAAAgTlG4AQAAAAAAiFMUbgAAAAAAAOIUhRsAAAAAAIA4ReEGAAAAAAAgTlG4AQAAAAAAiFMUbtAlmzdv1qxZs3TRRRfp0EMPVW5uroYOHaqrrrpKZWVlAbepq6vTXXfdpUMPPVT9+vXTiBEjdM8996i+vj7K0SOSdu7cqbvuuktjx45VUVGR+vfvr6FDh2rMmDF68cUX1dTU1G4bciO1zZw5Uzk5OcrJydHKlSvbLSc/UseIESNac2HPf+PGjWu3/q5duzR9+nSNGjVK/fv3V1FRkW6++WZ9++23MYge0TB37lxdeOGFGjx4sPr376/DDjtM1113nTZu3NhmPa4bqWH27NlBrxn+f+eff36bbciN1GHbtubMmaNzzz1Xw4YN04ABA1RcXKxbbrlFVVVV7dYnN1KHZVl65plndNJJJ2nAgAEaNGiQxo4dq/nz5wdcP5a5YdTU1NgRPwqS1tSpUzVz5kwNHjxYJ5xwgvr27auKigrNmzdPtm3rL3/5iy6++OLW9RsaGnT22WdrzZo1Ou2003TYYYdp9erVWrx4sUaNGqX58+ere/fuMXxGCJdt27bpkEMO0ahRo3TQQQepb9++qqmp0YIFC7Rhwwaddtpp+sc//iHTbKkfkxup7fPPP9epp54qp9OphoYGLViwQKNHj25dTn6klhEjRqi2tlaTJk1qt+zAAw/UhAkTWv/bsiyNHz9eixYt0ujRo3X88ceroqJCb731lvLy8rRw4UL17ds3muEjgmzb1q233qrnn39egwcP1umnn67MzExt2bJFH3zwgZ599lkde+yxkrhupJLVq1dr3rx5AZfNmTNHX3zxhf7whz/o5ptvlkRupJq7775bTzzxhPbbbz+dc8456tmzpz799FMtXrxYmZmZ+te//qXhw4dLIjdSiW3bmjhxoubMmaPBgwfrjDPOUGNjo+bPn69vv/1WDz74oH72s5+1rh/r3HBGbM9ICaNGjdJbb72lE044oc3jy5Yt0wUXXKDJkydr3Lhx6tatmyTp0Ucf1Zo1a3TLLbdo6tSprev7C0CzZs3S5MmTo/kUECG9evXSV199pfT09DaPNzc368ILL9TixYu1YMECjRkzRhK5kcqampo0adIkjRgxQgUFBXr11VfbrUN+pJ7s7Gzdeeed+1zvpZde0qJFi3TppZfq2WeflWEYkqS//vWvmjx5su677z7NnDkzwtEiWp566ik9//zzuv766zV9+nQ5HI42y5ubm1v/P9eN1HHYYYfpsMMOa/d4Y2Ojnn32WTmdTv3kJz9pfZzcSB1bt27Vk08+qUGDBun9999XdnZ267InnniitajzxBNPSCI3UsmcOXM0Z84cHXPMMXrjjTfUo0cPSdLvfvc7nXLKKbrnnns0ZswY5eXlSYp9bjDiBhFz8cUXa/Hixfr3v/+tI444QrZta/jw4fruu+9UXl6ujIyM1nUbGho0bNgw9e3bV5988knsgkZUPPXUU7rjjjs0bdo0TZo0idxIcdOmTdPMmTO1dOlSPfroo3r55ZfbjLghP1LPiBEjJElr1qzZ57pnnXWWPvzwQ61evVoHHnhg6+O2beuII47Qt99+q3Xr1rV+IUPi+v7773XwwQcrJydHZWVlcjqD//2R6wYk6Y033tA111yjcePGafbs2ZLIjVSzcuVKnXnmmRo/fryeffbZNssqKip05JFHasyYMSotLSU3UszPfvYzvfrqq3r11Vd11llntVn25JNP6s4779Ttt9+uu+66Ky5ygx43iJi0tDRJav1rWEVFhbZs2aKjjz66TbJLUkZGho4++mhVVVW1uz8dycWyLC1atEiSWoelkhup65NPPtEjjzyiKVOmqKioKOA65Edqamxs1OzZs/XII4/omWeeCdg3befOnSorK9OQIUPaFG0kyTAMnXrqqWpoaNDHH38crbARQYsXL1ZNTY3GjRsnn8+nOXPmaMaMGfrrX/+qysrKNuty3YAkvfDCC5Kkq6++uvUxciO1FBYWKj09XcuXL1ddXV2bZe+8844k6eSTT5ZEbqSab775RpJaR9Tszv/Ye++9Jyk+coNbpRARGzZs0JIlS7TffvvpkEMOkdSS8JJUUFAQcJuCggItWrRIFRUVGjhwYNRiRWQ1NjbqkUcekW3b2rFjh5YuXaq1a9dqwoQJbT4oJXIj1ezatav1Fil/34FAyI/UtHXrVt14441tHhs1apSee+45DR48WJK0fv16WZa119yQWnLouOOOi2zAiDj/XzIdDoeOP/54rVu3rnWZaZq64YYbdN9990niugHpq6++0tKlS3XAAQfojDPOaH2c3EgtvXv31u9//3v99re/1VFHHdWmx827776r66+/vrWPCbmRWvr06SNJqq6u1rBhw9osq66ulqTWz5l4yA0KNwi7pqYm/fznP9euXbs0derU1hE3/ir37veW7i4rK6vNekgOjY2Nmj59eut/G4ahX/7yl/r973/f+hi5kZruv/9+VVRUaMmSJe36VOyO/Eg9EyZM0LHHHqvhw4crIyND69at0xNPPKHS0lKdf/75WrZsmXr27ElupBiPxyOppS/FyJEjtXjxYg0dOlSrV6/WLbfcoscff1yDBw/WddddR25As2fPlmVZ+slPftLmM4bcSD033nij9t9/f/3qV7/SX//619bHjz32WF166aWtt12SG6nljDPO0D//+U/NmDFDJ510Umtj4e3bt+vJJ5+UJNXW1kqKj9zgVimElWVZuuGGG7Rs2TJNnDhRl19+eaxDQoxlZmaqpqZG27dv12effaaHH35YL7zwgs4991w++FLYhx9+qMcee0y/+c1vWm+ZA/zuuOMOnXzyycrNzZXL5dJhhx2mp59+WiUlJdqwYYP+/ve/xzpExIBlWZKk9PR0zZ49W6NGjVJmZqaOO+44Pf/88zJNU48//niMo0Q8sCxLs2fPlmEYuvLKK2MdDmJs+vTp+tnPfqbJkyfrs88+08aNG/X2229r586dOvfcc4NO/YzkNn78eJ144on6z3/+o+OOO0633Xabbr31Vh1zzDHq2bOnJLXOfhsP4icSJDzLsnTjjTfqtdde02WXXaYZM2a0We6vRPorl3vy/4j3r4fkYpqmDjjgAF133XV69NFHtXz5cj3yyCOSyI1U09zcrEmTJumQQw7Rrbfeus/1yQ/4XXPNNZKkFStWSCI3Uo3/fTz88MM1YMCANsuGDx+u/Px8rV+/XjU1NeRGiluyZIk2btyok046Sfn5+W2WkRupZcmSJZo2bZp++tOf6tZbb9UBBxygzMxMHXvssXrllVeUlpam3/72t5LIjVTjdDr1j3/8Q3fccYdM09Tf//53zZ07V+ecc05rf6y+fftKio/c4FYphIV/pM0rr7yiSy+9VE8++WS7CmVhYaEktWsg6Od/3L8ektepp54qSXr//fclkRuppr6+vvVe4dzc3IDrnHnmmZKkF198sbVpMfkB//3oXq9XkpSfny/TNMmNFDFkyBBJwYeq+x/fuXMnnyspLlBTYj9yI7UsWLBAknTiiSe2W9a/f38NGTJEq1evVn19PbmRgrp166Y77rhDd9xxR5vH/U2JjzjiCEnxcd2gcIMu271oc/HFF+vpp58O2K+isLBQAwYM0IoVK9TQ0NBuGrUVK1YoLy+PZl8p4Ouvv5b048xj5EZq6datm6666qqAy5YtW6aKigqNHTtWffv21YEHHkh+oJV/Zin/DFI9evTQkUceqZUrV+qrr75qNx34v//9b2VkZLR+8UJi8//wWrt2bbtlTU1NqqysVEZGhvr27av+/ftz3UhR27dv1/z589WrVy+de+657ZbzmZJaGhsbJf3YI2tP27Ztk2maSktLIzfQ6rXXXpMkXXLJJZLi47rBrVLoEv/tUa+88oouvPBCPfPMM0GbjBqGoauuukr19fV66KGH2ix76KGHVF9fr4kTJ0YjbESB2+1u/av47rxer+6++25JP46qIDdSS48ePfTYY48F/HfUUUdJkiZPnqzHHntMhx12GPmRYtauXRvw2rF27VpNnTpVknTppZe2Pu5/7++9917Ztt36+N/+9jdVVVVp/Pjx6tGjR2SDRlQMHjxYp512miorK1tHVPjNmDFDtbW1GjdunJxOJ9eNFPbKK6+osbFRl112mbp169ZuObmRWo455hhJ0qxZs9rd5vLXv/5VmzZt0lFHHaVu3bqRGykoUL/NN998Uy+++KJGjRql8847T1J8XDeMmpoae9+rAYFNmzZN06dPV2Zmpn7xi18ELNqMGzdOhx12mKSWiuSYMWP06aef6rTTTtPIkSO1atUqLV68WKNGjdK8efP4gp0kpk2bplmzZumYY47RgQceqJ49e2rz5s1auHChtm/frmOPPVavv/566/tNbkCSJk2apJdfflkLFizQ6NGjWx8nP1KH/9px3HHHadCgQXK5XFq3bp0WLFigpqYmTZ48Wb/73e9a17csS+PHj9eiRYs0evRoHX/88aqsrNTcuXN14IEHatGiRa33qCPxrV+/XmeddZa+/fZbjRkzpvU2h3fffVeDBg3SwoUL1b9/f0lcN1LVcccdp88//1wffPCBDjnkkIDrkBupw+fz6bzzztOyZcuUm5ursWPHKjs7W6tWrdK7776rHj166K233tKRRx4pidxINUcddZQOOOAADR06VN27d9dHH32k999/X/n5+ZozZ06bkbyxzg0KN+gS/4+svXniiSc0YcKE1v+ura3VAw88oLlz52rr1q3q37+/LrzwQk2ZMqW1gzcS38cff6znn39eH374oTZv3qyGhgZlZWXpkEMO0SWXXKIrr7yydfpFP3IDwQo3EvmRKt5//30999xzWr16tb799lt5vV716dNHRx55pK6//nqddtpp7bbZtWuXZsyYodLSUm3atEm9evXSmDFj9Nvf/lb9+vWLwbNAJG3cuFH333+/Fi1apO3bt6t///4aO3asbr/99nZ9s7hupJaPPvpIp59+uo488kgtWrRor+uSG6lj165dmjVrlt544w2tW7dOjY2N6tevn0444QT9+te/1rBhw9qsT26kjmnTpmnu3LnasGGDmpqalJeXp/POO0+/+tWvAjYajmVuULgBAAAAAACIU/S4AQAAAAAAiFMUbgAAAAAAAOIUhRsAAAAAAIA4ReEGAAAAAAAgTlG4AQAAAAAAiFMUbgAAAAAAAOIUhRsAAAAAAIA4ReEGAAAAAAAgTlG4AQAAAAAAiFMUbgAAQFIYMWKEcnJy9N5778U6FHTCOeeco379+umrr75q8/ikSZOUk5OjadOmdWn/s2fP1rhx4/a53rp169SnTx9dcsklXToeAADhRuEGAIAEcv/99ysnJ0c5OTl66KGHYh1OUvAXfGbPnh3rUFLOm2++qWXLlmnixIk68MADYxrLQQcdpJKSEi1atEj/93//F9NYAADYHYUbAAAShGVZevnll1v/+6WXXpJt2zGMCAhdU1OTfve73yk9PV2//vWvYx2OJGnKlCkyTVP33HOPLMuKdTgAAEiicAMAQMJYunSpNmzYIJfLpfT0dK1fv17vv/9+rMMCQvLWW2+purpaY8aM0X777RfWfS9fvlwTJkzQ0KFD9atf/UoffPCB8vPzdcwxx+gXv/hF0BE1eXl5Ovnkk1VeXq5FixaFNSYAAEJF4QYAgATx4osvSpLOPfdcnX322W0eAxLNX/7yF0nST37yk7Du9x//+IfOOecczZs3T/X19dp///2VlZWl/fffX1VVVXrllVf03HPPBd3eH48/PgAAYo3CDQAACaCmpkbz5s2TJF1xxRWtPy7nzp2rurq6oNvt3rB3w4YNuummm3TwwQerX79+GjFihO6+++6g2/t76VRXV+uzzz7TNddcoyFDhqhfv34qLi7W9OnT1djY2G679957Tzk5ORoxYkTQuII1nrVtWwsWLNBtt92mE088UYWFherXr58OPvhgXX311Vq2bNk+X6tw2fN5zJ8/X+PGjdOBBx6o/fffX6effrr++c9/7nUfX3/9taZOnaoTTjhBgwYN0oABAzRq1Chde+21evvttwNus3DhQl1++eUaMmSIcnNzNXToUF1xxRVaunRph+J87bXXdOaZZ2rQoEEqKCjQFVdcIbfb3br+J598oiuvvFJDhgzRfvvtp5NPPllz5szZ6/OorKzUr3/9ax155JEaMGCABg4cqFNPPVWzZs3Srl279rptIJs3b9YHH3ygbt266Ywzzuj09nV1dbrggguUk5Ojk08+Wd98842kltuvbr/9dlmWpQkTJmjt2rW64447NGLECC1btkxfffWV/v73v+uEE04Iuu+xY8fKNE0tWLBAO3bs6HRsAACEG4UbAAASwGuvvaadO3fqgAMO0EknnaQzzzxTubm58nq9ev311/e5/WeffaYTTjhBr732mvr166f99ttPGzdu1BNPPKFLLrlEzc3NQbf997//rdNPP10LFizQAQccoD59+mjdunWaNm2arr/++nA+TTU0NGj8+PH6y1/+oi1btmi//fbT0KFD9f3332vOnDkaN26c/vrXv4b1mB0xffp0XXHFFfryyy9VUFCgtLQ0ffTRR7ruuuv0zDPPBNxm4cKFOuqoozRz5kx9/vnn2n///TV06FDt2LFDr7/+um6//fZ229xxxx269NJL9c4770hqKbz5fD7Nnz9fF1xwge677769xnnvvffqpz/9qbZs2aL8/Hx5vV7Nnz9fY8eOVUVFhebNm6cxY8bo/fff1wEHHKDu3btr1apVmjhxot54442A+3z11Vd17LHH6rnnntPmzZs1ePBg9e3bV6tWrdJdd92l8847T999912nXk//zF+HHXaY0tPTO7Xt119/rXHjxmnp0qU69dRTNW/ePPXr10+S9Pnnn2v79u3q3r27ZsyYoczMzDbbpqen64ILLtAvf/nLoPvv2bOnioqKZFmWPvjgg07FBgBAJFC4AQAgAfhviSopKZFpmnI6nRo/fnybZXtzzz336Oyzz9batWu1dOlSrV69Wv/7v/8rl8ullStX6pVXXgm67W233aaf//znWrdunZYsWaIvvvhCzz77rAzD0Jw5c/Tuu++G50mq5Ye1v9Cxbt06ffDBB3r//fdVUVGhv/3tb+rRo4emTJmijRs3hu2Y+/L1119r5syZevbZZ7V27VotWbJEFRUVrUWre++9t13hwu126+qrr24dGfLZZ59pxYoVWrp0qdavX6/ly5fruuuua7PNSy+9pKeeekoOh0N//vOfVV5ersWLF2vt2rW67777ZBiGHn74Yb355psB49yyZYueeeYZvfzyy/r000/13nvv6dNPP9XIkSO1Y8cOTZ48WTfccIN+/etft76X69at009+8hPZth2wIe/y5ct1ww03yLZtTZs2TdXV1Vq2bJk++eQTffjhhxo1apQ+/PBD3XnnnZ16Tf0jp4444ohObffll1/qrLPO0po1a3TZZZfp1VdfbVOc8RcgnU6nnE5np/a9u+LiYkmihxQAIC5QuAEAIM59+umnWrVqlaS2/UCuuOIKSVJZWVmbW2ECGTx4sB5//HFlZ2e3PnbyySfryiuvlKTWER6BHHfccfrDH/6g7t27tz42fvx4jRkzZp/bdlZ6err+3//7fxowYECbxx0Ohy666CLdcMMNampq0j/+8Y+wHXNfmpqaNHny5NZCmdRSGLjvvvvUt29f1dfXt44g8fvTn/4kr9er448/Xn/729/aPZ+ioiLdcsstbR7zT+9+zTXX6Nprr5VptnxNczgcuummm1qPP3369IBxNjc36/bbb9fYsWNbH+vbt6/uvvtuSS3NrY8++mjdfvvtrUUNp9OpP/3pT+rWrZs2btyozz77rM0+p06dqubmZv3+97/XpEmT2oyOOeigg/TCCy8oIyNDL7/8srZs2bL3F3I31dXVkqT999+/w9usXLlSY8aM0VdffaVf/vKXevrpp5WWltZmnaKiImVkZKi+vl6///3vA97K1xH+Zsn+OAEAiCUKNwAAxDn/iJri4mINGTKk9fFDDz20ta/J7Nmz97qPiRMntvuRK0lHHXWUpJYeJsEEux2qI9uG6qOPPtIf/vAHXXHFFRo3bpzOPvtsnX322a2386xevTrsx9ybQK9B9+7dddhhh0lq+xrs3LmzddaiX//6160FmL1Zu3at1q9fL0m68cYbA67zq1/9SlLL7UAbNmwIuM7EiRPbPXb44YfvdXnv3r2Vl5fX7nls3rxZy5cvl9Pp1NVXXx3weAMHDtQRRxwhn8/XqduKPB6PJKlXr14dWv+dd97RBRdcoB07duj+++/XH//4RxmG0W69jIyM1mWPPfaYhg0bpscee0xbtmzR22+/rdra2g4dr3fv3m3iBAAglkIfQwoAACKusbFRr732mqTAs+9cccUVuvPOO1VaWqrf//73QW8POeiggwI+npubK0mqr68PGkNXtu2s5uZm3XjjjSotLd3retu3bw/bMfelT58+QQsMgV6DioqK1oa9/uLWvnz55ZeSpB49emjw4MEB1ykqKpLD4ZDP59OXX36pQYMGtYtz9xFVe8YoSQUFBQH33bdvX61du1YNDQ2tj3366aeSWkb87D7aaE/r1q2TJG3atCnoOnvauXOnJKlbt277XPftt9/Www8/LIfDoeeee04XX3zxXte/9tprddBBB2nGjBl67733WhsM/+QnP1FaWpouuOAC3XvvvXsd7eMfXfb999939CkBABAxjLgBACCOvf3229q2bZvS09N1ySWXtFs+fvx4paWl6ZtvvtG//vWvoPtxuVwBH/ePBrFtOyLbdtZjjz2m0tJSde/eXffff79WrFihTZs2aceOHaqpqdFjjz0mqeX2pWgJ9vylwK+Bv9+Nw+Fo1xw3GH/hZ/ciy56cTqf69OnT5hgdiXP3kSn7Wmf351FTUyNJ2rVrl5YvXx70n39UitfrDRr7nvzPoyOzNlVVVcnn8ykzM1NDhw7t0P5POukkvfHGG6qsrNRtt92mgQMHasyYMTJNU//4xz905pln6ttvvw26vT8uf5wAAMQSI24AAIhj/tukGhsblZ+fv891x40bF4Wo9i5QEWBPwX7kv/TSS5KkP/7xj/rpT3/abnkiTM/cs2dPSZLP51N9fX2Hijf+dfZWTGhubta2bdvaHCOSMjIyJLXcDuUffRMu/gJVR0ZO/fznP9fGjRv18ssv6/zzz9cbb7yhkSNHdug4WVlZys/PV15enkpLS1VVVaXzzjtPGzZs0JNPPqnf/e53Abfz55l/tioAAGKJETcAAMSpzZs3a/HixZJa/vLfr1+/gP/8owIWLFigb775JpYhS/rxB//e+oP4b6/Zk78Z7HHHHRdw+cqVK7sYXeQddNBBrbfafPjhhx3axj+S5Pvvv2/tdbMnt9stn8/XZv1IOuSQQyS15GG4C2b+wssXX3yxz3VN09QTTzyhq6++Wtu3b9cFF1yg//73vyEdNz8/v7UguLc+SZ9//rmktv2BAACIFQo3AADEqZdfflk+n099+vSR2+3W2rVrA/4rLy9Xbm6umpub9zqtd7QMHjxYhmFo586drbNh7W758uXtZi/y69GjhyRp69at7ZatXbs2rDNYRUq3bt1aZ9yaMWNGh24lGzJkSGv/mSeeeCLgOo8//rgkafjw4Ro4cGCYog0uPz9fhx9+uCzLaj12uJxwwgmSWppQd4Rpmnr00Ud1/fXXq6amRhdeeGHIRTz/aK/dZ0nbnW3brXGdeOKJIR0DAIBwonADAECc8t825O9jE4zT6dRll10mad+zS0VDTk6Ojj32WEnSHXfc0eZ2mFWrVukXv/hF0Odz/PHHS5Luvfdeff31162Pr1mzRpdffrkcDkcEIw+fu+66Sy6XS++9956uu+66Ns9Fahk9M3PmzDaP/eY3v5Ek/e1vf9Pf/va31oKPZVl68sknWxs2T5kyJfJP4Af33XefnE6n/vznP+u+++5r7Xvjt3PnTi1YsCDorFPBFBcXq3fv3tqyZYsqKio6tI1hGHr44Yc1adIk1dXV6eKLL9by5cvbrPPBBx/ommuuCVoQ+vDDD/XUU09Jkk499dSA63z++efasWOH9t9/fx166KGdeFYAAEQGhRsAAOLQBx980PqD9sorr9zn+v51ysvLO3x7TiT98Y9/VPfu3fWf//xHw4cP1wknnKAjjzxSJ598sgoLC3XRRRcF3O7uu+9WRkaGPvnkE40cOVLHH3+8Ro8erRNPPFGNjY26/fbbo/xMQjNs2DC98MIL6tmzp15//XUNHz5cxxxzjE4++WQVFBTomGOO0XPPPddmmyuuuEK/+MUv5PP5dOutt2rYsGE67bTTNHToUN15552ybVu/+c1vdMEFF0TteZxwwgl69tln5XK59PDDD+uggw7SscceqzPPPFOjR4/WoEGDNH78eM2ZM6dT+01LS2vN2VdffbVT206bNk0333yzvvvuO1166aV6//33W5fZtq033nhDp59+ug499FBNmDBBL774otauXauTTjpJY8aMUU1NjY499lhdddVVAffvj2fixIkdmsodAIBI49MIAIA45B85c/jhh3for/4HH3ywjjzySEk/NjSOpSOPPFLvvPOOxowZo27dumndunVKT0/Xvffeq9LS0qAjZw455BD93//9n8455xx1795d69atU1NTk37+85/r3XffVf/+/aP8TEJ3xhlnaMWKFbrxxhs1dOhQffXVV1q3bp1ycnI0fvx4PfLII+22eeCBB/Taa69pzJgxsixLq1evlmEYOuecc/Tmm2/qt7/9bdSfx0UXXaQPP/xQN998s4qKirRx40b997//1bZt2zRq1ChNmTJF7777bqf3e+2118o0Tb3yyiudnpnsD3/4g37zm9+ovr5el112mZYuXSqpZcTWW2+9pV/84hfKzc3V+++/rxUrVujbb79VRUWFRo4cqXvvvVdvvvmm0tPT2+3Xsiy99tprcjqdnR5FBABApBg1NTXhm8MTAAAA6KBf/vKX+p//+R+98MILOv/88yNyjNmzZ+ull17SvHnz9rnuq6++qp/97Gf62c9+pgcffDAi8QAA0FmMuAEAAEBM3HPPPerZs6emTZsmy7JiGktzc7MeeOAB5eTk6M4774xpLAAA7M4Z6wAAAACQmvr166enn35aq1at0ubNm6MyW1YwGzdu1Pjx43XkkUeqV69eMYsDAIA9casUAAAAktbq1au1Zs0aTZgwIdahAAAQEgo3AAAAAAAAcYoeNwAAAAAAAHGKwg0AAAAAAECconADAAAAAAAQpyjcAAAAAAAAxCkKNwAAAAAAAHGKwg0AAAAAAECconADAAAAAAAQpyjcAAAAAAAAxCkKNwAAAAAAAHHq/wORnu9nT1fUsQAAAABJRU5ErkJggg==\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"karena dari percobaan sebelumnya yang mengubah init dan iterasi terus menghasilkan nilai centroid dan inertia nya sama sehingga dari visual diatas hasil clustering, dapat dilihat bahwa posisi centroid pada setiap cluster sudah berada di tengah-tengah sebaran data sehingga mampu merepresentasikan karakteristik masing-masing cluster dengan baik. Tidak terlihat adanya centroid yang melenceng jauh dari kelompok datanya. Meskipun pada beberapa cluster dengan pendapatan tinggi terdapat data yang menyebar dan beberapa outlier, hal tersebut tidak memberikan pengaruh terhadap posisi centroid. Secara keseluruhan, hasil clustering yang diperoleh sudah cukup baik dan stabil"
],
"metadata": {
"id": "Bbn2Vg4yuPnB"
}
},
{
"cell_type": "code",
"source": [
"#menambahkan hasil clustering ke dalam dataframe\n",
"df['Cluster'] = kmeans_preds\n",
"df.head()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "3iVAI50gwOuA",
"outputId": "704f41f8-5022-45fe-c226-b8e80845ff49"
},
"execution_count": 66,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" CustomerID Gender Age Annual Income (k$) Spending Score (1-100) \\\n",
"0 1 Male 19 15 39 \n",
"1 2 Male 21 15 81 \n",
"2 3 Female 20 16 6 \n",
"3 4 Female 23 16 77 \n",
"4 5 Female 31 17 40 \n",
"\n",
" Cluster \n",
"0 3 \n",
"1 4 \n",
"2 3 \n",
"3 4 \n",
"4 3 "
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"type": "dataframe",
"variable_name": "df",
"summary": "{\n \"name\": \"df\",\n \"rows\": 200,\n \"fields\": [\n {\n \"column\": \"CustomerID\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 57,\n \"min\": 1,\n \"max\": 200,\n \"num_unique_values\": 200,\n \"samples\": [\n 96,\n 16,\n 31\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Gender\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Female\",\n \"Male\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 13,\n \"min\": 18,\n \"max\": 70,\n \"num_unique_values\": 51,\n \"samples\": [\n 55,\n 26\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Annual Income (k$)\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 26,\n \"min\": 15,\n \"max\": 137,\n \"num_unique_values\": 64,\n \"samples\": [\n 87,\n 101\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Spending Score (1-100)\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 25,\n \"min\": 1,\n \"max\": 99,\n \"num_unique_values\": 84,\n \"samples\": [\n 83,\n 39\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Cluster\",\n \"properties\": {\n \"dtype\": \"int32\",\n \"num_unique_values\": 5,\n \"samples\": [\n 4,\n 2\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 66
}
]
},
{
"cell_type": "code",
"source": [
"\n",
"point_size = 25\n",
"colors = ['red', 'blue', 'green', 'cyan', 'magenta']\n",
"cluster_names = {\n",
" 0: 'Cluster 0',\n",
" 1: 'Cluster 1',\n",
" 2: 'Cluster 2',\n",
" 3: 'Cluster 3',\n",
" 4: 'Cluster 4'\n",
"}\n"
],
"metadata": {
"id": "biW0YPMHwRwX"
},
"execution_count": 67,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize = (12,9))\n",
"for i in range(5):\n",
" plt.scatter(X[kmeans_preds == i,0], X[kmeans_preds == i,1], s = point_size,\n",
" c = colors[i], label=cluster_names.get(i, f'Cluster {i}') )\n",
"\n",
"plt.scatter(kmeans.cluster_centers_[:,0], kmeans.cluster_centers_[:,1], s = 200,\n",
" c = 'orange', label = 'Centroids')\n",
"plt.title('Clusters of Clients')\n",
"plt.xlabel('Annual Income (k$)')\n",
"plt.ylabel('Spending Score (1-100)')\n",
"plt.legend(loc = 'best')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 848
},
"id": "Toe2ybqZwW1Q",
"outputId": "85e7abaa-a2c1-4948-afe2-66c9f45be3c8"
},
"execution_count": 85,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1200x900 with 1 Axes>"
],
"image/png": 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xQ0RE1GKefPLJ6t1pVq1ahX379ll8bmpqaoMKy96+tKSu5MH3339v8Zjm3H///dXf35kAqpppUlpaWucYVVs2A5VFkO1BXfdVnwceeKD6+7Vr19baLzs7u3oHqkGDBsHFxaWBUVpGLBbjn//8J4DKIsizZ8+2eCctrVZbvROUNdjbe23pM1qfpjwvRERE9WHihoiIqIW4ubnhyy+/hJOTEwwGA6ZMmYJNmzbVeY5arcbcuXMxbdo0lJWVWXwtiUSCXr16AQDWrVtn9sPk2bNn8fbbb9c6xunTp3Hq1Kk6r7N79+7q7++sQ1K1vOjWrVt1FjAeNmwYIiMjAQBffvkl1q1bV+c1VSpVkxJOKpUKBw8erLNPXfdVnwEDBuCee+4BAGzYsAE7d+406XNnAmXmzJkNukZD/eMf/6jeenzv3r2YMmVKrTs1Vdm+fTuGDRuG/fv3Wy2Oln6v61P1jF68eLHWPnl5edi2bRuMRmOtfZryvBAREdWHNW6IiIhaUHR0NJYvX47nn38ehYWFmD59OpYvX47x48ejT58+6NChAwoKCpCTk4Pdu3dj27Ztjd7GeObMmZgzZw5u3bqF0aNHY968eejevTv0ej327NmDL7/8Er6+vhCLxWZ3+/n9998xe/Zs9OvXD6NHj0bfvn3h5+cHg8GAy5cv4/vvv8fPP/8MoLJWTFWyosp9990HoHL5yEsvvYSZM2dCKpVWt4eEhFR/v3LlSowYMQIajQazZ89GSkoKJk2ahG7dusHZ2Rm5ubk4c+YM0tLScOjQITz00EOYPHlyo16XnJwcPPzww+jWrRvGjRuH/v37o3PnzhAKhbh27Rq2bt2K9evXAwC6dOmCUaNGNfgay5Ytw4gRI1BSUoLY2FjMmDED48aNg6enJ/744w988sknOHv2LABgwoQJGDt2bKPuxVJCoRBff/01YmNjceTIEaSlpaF///6YOHEihg0bhs6dO8PFxQU3b97EiRMn8PPPP+P3339vllha8r2uz3333VddaPjDDz9ETEwM2rVrB6ByNo6/vz/0ej1iY2PRpUsXPPzww4iIiEBgYCBEIhFu3bqFXbt24ZtvvgFQWfT68ccfb5ZYiYio7WLihoiIqIVNmTIFwcHBmD9/Pk6fPo3ffvsNv/32W639pVIpFixYAE9PzwZd56mnnsKuXbuQmpqKCxcumMzqCAwMxMaNG/HYY4/VOc7Jkyfr3AmrZ8+e+Pbbb03qhURHRyMyMhLHjh3D999/bzJz4vbaOzKZDGlpaZg6dSrOnDmD3bt315jFcCcPD486Y7bE+fPncf78+Vrbu3Tpgg0bNlR/kG+IXr164bvvvsO0adOg1WrxxRdf4IsvvjDp98gjjzR7vaMqHTt2RGpqKpKSkrBy5UoUFBRgzZo1WLNmTa3njBo1Cn/729+sGoct3uvaTJ8+HatWrUJeXh7eeOMNvPHGG9VtUVFR2Lp1a/WfL1++jM8++6zWsSQSCf7zn/9U1xMiIiKyFiZuiIiIbGDgwIHYt28f0tLSsGPHDhw5cgQ3btyAVquFu7s77rrrLvTr1w+jRo3CuHHjGlX/RCAQ4Ouvv8a3336LdevWQaFQoKKiAgEBAXj44Yfx3HPPQSKR1Hr+pEmT4Ovriz179uC3337DtWvXcOvWLZSVlaFjx47o3bs3Hn74YUyZMgUikcjkfKFQiE2bNmHZsmXYvn07VCoVCgoKal1yEhISgv3792Pz5s1ITU3F8ePHcevWLZSXl0MikSA0NBSRkZEYM2YMBg8e3ODXo8rgwYOxdetW7N69G8eOHcOVK1dw69YtFBYWQiKRoGfPnhg9ejSmTZvWqKRNlfvvvx+//fYbPv/8c+zcuRNKpRLFxcXo1KkTIiIi8OSTT+LBBx9s9PiN4eLigrfeegvPPvssfvjhB+zduxfnz59Hbm4uysrK0KFDB3Tr1g2DBg3C5MmTERYW1ixxtNR7XR9/f3/s3r0bH3zwAQ4dOoSrV6+iuLi4Rp/AwEDs3r0b6enp+PXXX3Hp0iXcvHkT+fn58PDwQLdu3RATE4Pp06fXmFFGRERkLQKtVlv7gl0iIiIiIiIiIrIZFicmIiIiIiIiIrJTTNwQEREREREREdkpJm6IiIiIiIiIiOwUEzdERERERERERHaKiRsiIiIiIiIiIjvFxA0RERERERERkZ1i4oaIiIiIiIiIyE4xcUNEREREREREZKeYuCEiIiIiIiIislNM3JDdKC4uhlKpRHFxsa1DIbIqPtvkiPhck6Pis02OiM81Oaq28mwzcUN2paKiwtYhEDULPtvkiPhck6Pis02OiM81Oaq28GwzcUNEREREREREZKeYuCEiIiIiIiIislNM3BARERERERER2SkmboiIiIiIiIiI7BQTN0REREREREREdsrZ1gEQERERERERWYPBYEBBQYHDbw9NlQwGA8RiMXQ6Hf766y9bhwMAcHV1Rbt27SAUWm+eDBM3RERERERE1OoZDAZoNBq0b98enTp1gkAgsHVI1MwMBgNKS0shFoutmihpLKPRiOLiYmg0GkilUqvFZPs7s0BycjJeeOEFDBs2DD4+PpBIJFi3bp1F56pUKnTu3BkSiQQvvvhirf2+++47DB8+HP7+/ggKCoJcLsfJkyetdAdERERERETUnAoKCtC+fXu4ubkxaUM2IRAI4Obmhvbt26OgoMBq47aKxE1SUhJWr16NnJwc+Pr6WnyewWDArFmz6u333nvvYebMmbh16xbi4+MxYcIEZGRkYNSoUThy5EhTQiciIiIiIqIWUFxcDFdXV1uHQQRXV1erLtdrFYmbTz75BKdPn0ZWVhamT59u8Xmffvopjh07hldffbXWPllZWViyZAm6du2KgwcPYtGiRVi2bBm2bt0KAHj++edhMBiafA9ERERERETUvDjThuyBtZ/DVpG4GTZsGAIDAxt0zvnz57Fo0SK8+OKL6N27d6391q1bh/Lycrz88svw8vKqPt6nTx9MnDgR586dw+HDhxsdOxERERERERFRYzlkceKKigrMmjULISEhmDdvHo4ePVpr34MHDwIAhg8fbtI2YsQIrF+/HocOHUJUVFSd12TV8qYrLS2t8V8iR8FnmxwRn2tyVHy2yRG1lefaYDBwtUQbYzQaq/9rb++9wWCoNU/Q0CV9Dpm4+eCDD3Dq1Cmkp6dDLBbX2TcrKwvt27c3WzsnNDS0uk99rl69ioqKisYFTDXcuHHD1iEQNQs+2+SI+FyTo+KzTY7I0Z9rsVjs8MkpMq+srMzWIZgoLi6GXq83Oe7k5ISQkJAGjeVwiZvff/8dS5cuxZw5c9CvX796++v1enh7e5tt8/DwqO5TH39//wbFSaZKS0tx48YN+Pr61ptwI2pN+GyTI+JzTY6KzzY5orbyXOt0Ooe+PzJlNBpRVlYGkUhkd/WNXF1dG7S5Ul0cKnFTWlpavURqwYIFLXptVi+3HrFYzNeTHBKfbXJEfK7JUfHZJkfk6M/1X3/9BaGwVZRxtSuLFy/GO++8gy1btmDo0KG2DqdBqpZHCQQCu3vvhUKh1f5/s687a6IPPvgAZ8+exaeffgoXFxeLzvH09Kx1Rs1ff/1V3YeIiIiIiIioNTh58iSee+45DBgwAP7+/vDz80O/fv0wc+ZM7Nmzx6axjRs3DhKJxKYxVCkpKcE777yDAQMGwNfXF+Hh4Xj++edx69YtW4dWg0Mlbk6fPg2DwYCYmBhIJJLqr4cffhgA8M0330AikSA2Nrb6nNDQUOTn55td71lV26aq1g0RERERERGRvTIYDEhISMCwYcOwceNGyGQyxMfH45lnnkG/fv2wc+dOPProo1i6dKmtQ7U5g8GA2NhYLF68GFKpFLNmzUJkZCTWrFmDkSNHQq1W2zrEag61VOqBBx6AVCo1OX7jxg3s3LkT3bp1w3333Yc+ffpUt0VFReHXX3/F7t27MWXKlBrn7dq1q7oPERERERERkT1LSkrCihUr0Lt3b6xZswbBwcE12ouKirBy5Urk5ubaKEL7sX79euzatQuTJk3CypUrq2vkfP3113jppZeQlJSEjz76yLZB/pdDzbj5+9//jk8++cTk65///CeAygTMJ598gr///e/V58TFxcHZ2Rnvv/8+dDpd9fHTp08jJSUF3bt3x6BBg1r8XoiIiIiIiIgspVQqsWzZMnTs2BEpKSkmSRsAcHNzw5w5c7Bw4cI6xzpw4AAkEgkWL15s0padnQ2JRIJZs2bVOJ6VlYVnn30Wffr0gY+PD2QyGaKiovDKK69Ub9stkUhw6NCh6u+rvu4c68yZM5g+fTq6d+8Ob29v9OrVC/PmzTNJOF26dAl+fn6YPXs2zp07h7i4OAQHB0MikSA7O7vOe1yzZg0A4PXXX69R2Dg+Ph4ymQzff/89ioqK6hyjpbSKGTdr1qzB4cOHAQBnz54FAHz77bc4ePAgAGDQoEGYOnVqo8bu2rUrXnnlFSQlJWHIkCF45JFHkJ+fj02bNgEAli1bZndFjoiIiIiIiMh2hAoFhFlZMISGwhAebutwAFTOIKmoqEB8fDx8fHzq7GtpTVhLXbt2DcOHD0dhYSEefPBBPPbYYygoKIBSqcSqVauQlJQEZ2dnLFiwAOvXr0dOTk6NDYV69+5d/f22bdsQHx8PoVCIsWPHonPnzjh37hxWrlyJ3bt3Y9euXSY1cpRKJUaOHImePXsiNjYWubm5de4wVlxcjMzMTISFhSEwMLBGm0AgwAMPPIBvvvkGJ06cwODBg63zIjVBq0jcHD58GBs2bKhx7MiRIzhy5Ej1nxubuAGAuXPnIjAwEJ999hm+/vpriEQiDBo0CAkJCRZtKU5ERERERESOT6DRwF0uh1ClgkCvh9HTEwaZDIXJyTCaKdvRkqo+H0dHR7f4tTdv3gydTofFixebzJ7Jy8uDs3Nl6mHhwoU4ePAgcnJyzM76yc3NxTPPPAOpVIrt27fXSKqkpKRgxowZWLRoEd59990a5x09ehTz589HQkKCRfFevHgRBoMBISEhZturjmdlZTFxY6nPPvsMn332WaPPHzp0KLRabZ19Hn/8cTz++OONvgYRERERERE5Nne5HM6ZmdV/FqjVEKjVcJfLUZCebsPIgJs3bwIA/P39bRaDm5ubybEOHTpYfP6GDRug1+uxdOlSk5kwEydOxMcff4xNmzaZJG58fX0xd+5ci69TtbO0l5eX2faqnaVr24G6pbWKxA0RERERERGRLQkVCghVKpPjAgDC7GwIFQq7WTbV0kaPHo0333wTc+fOxb59+zBixAgMGTIEMpmsQeNk/jcpdvz4cVy8eNGkvaSkBBqNBhqNpsbGRHfffXedS6NaOyZuiIiIiIiIiOohzMqCoJYZGAKdDkKl0qaJGx8fH5w/fx5Xr15FWFhYi147KCgIaWlpWLJkCdLS0vDjjz8CALp164aEhARMmDDBonHy8vIAACtXrqyzX0FBQY3ETX01fe5UNaPm9g2Kblc106aqn62x6i4RERERERFRPQyhoTDW8kHe6OUFQy31UlrKwIEDAQD79+9v8lhVG/RUVFSYtNW2fKhnz55Ys2YNLl68iLS0NMyfPx83btxAfHx8jfq0dfHw8AAAZGRkQKvV1vplrqBwQ8hkMgiFQiiVSrPtVcdDQ0MbNG5zYeKGiKiZncs9h33X9+Fc7jlbhwIAUCiE2LrVGQoFfwQQERERWcoQHg6DTAbjHceNAAxBQTZfJhUbGwsnJyesXr0aarW6zr4lJSV1tlft2nT16lWTttOnT9d5rkgkQmRkJBISEvDOO+/AaDRix44d1e1OTk4AzCeFIiIiAADHjh2r8xpN5ebmhnvuuQcXLlzApUuXarQZjUbs2bMH7dq1Q//+/Zs1Dkvxt3YiomaiKdIgZmMMJm6eiFd+ewUTN09EzMYYaIo0tolHI0BMTDs89FA7xMe746GH2iEmph00mob9CwURERFRW1WYnIyKiAgYvL1hFIth8PZGRUQECpOTbR0aQkJC8Pzzz0Oj0WDSpElQmanHU1xcjOXLl2PJkiV1jhUWFgYPDw/88ssv1cuXgMoCyO+9955J/5MnT5qdiXPr1i0ANbcfrypWfPnyZZP+cXFx8PDwwFtvvYU//vjDpL2wsNBqSZ1p06YBAN58800Yjf9Lx33zzTdQqVSYPHmy2WLLtsAaN0REzUSeKkfm9f/tOqAuVkN9XQ15qhzpT7T8rgNyuTsyM//3175aLYBaLYBc7o709IIWj4eIiIiotTFKpShIT68sVKxUwhASYvOZNrdLTExEcXExVqxYgcjISERHR6NHjx4QiUTIzs7G3r17kZubi8TExDrHEYvFmDlzJt5//31ER0dj7NixyM/Px/bt2xEVFWVSOHjjxo1YvXo1Bg8ejODgYHh4eEChUCAtLQ0dOnRAXFxcdd/o6GikpqZi6tSpGDlyJFxcXNCrVy+MGTMGnTp1wldffYWnn34aQ4YMQUxMDMLCwlBSUoJLly4hIyMD9957L1JSUpr8WsXGxuLHH3/EDz/8gOzsbERFRUGpVGLLli0ICgqq9zVqSUzcEBE1A4VGAZVOZbYtW5cNhUaBcGnL/ZBXKIRQqcxNshQgO1sIhUKI8HBDi8VDRERE1JoZwsPtKmFTRSgU4u2338bkyZOxatUqZGRkICMjAwaDAb6+vhgxYgTi4uIwbNiwesd69dVXIRKJsHbtWnzzzTcIDAzEvHnzMHr0aGzevLlG30mTJqGkpARHjx7F8ePHUVpaCn9/f0yfPh1z5sxBQEBAdd9p06bh0qVLSElJwUcffYTy8nJMmTIFY8aMAQCMGjUK+/fvx8cff4y9e/diz549cHd3h7+/P2JjYyGXy632Wq1fvx4ffvghkpOTsWLFCnTo0AFPPfUUEhMT0alTJ6tcxxoEWq32ziV6RDZRXFyMnJwcBAQEwNXV1dbhEDXJ1qytiN8aj1JDqUmb2EmM1WNXY2zo2JaLZ6sz4uPdUVpquixKLDZi9epCjB1b3mLxUOvHv7PJUfHZJkfUVp7rW7duwdvb29ZhUAsyGAwoLS2FWCyuLqhsL6z5PNrXnREROYhQSSg8XczvOuAl9kKIpGV3HQgNNcDT03ye3svLiJAQzrYhIiIiIrJHTNwQETWDcGk4ZF4ys21BXkEtukwKAMLDDZDJDICZfRCCggxcJkVEREREZKeYuCEiaibJ45MR4ReBTm6dIBKI0MmtEyL8IpA83ja7DiQnFyIiogLe3gaIxUZ4exsQEVGB5ORCm8RDRERERET1Y3FiIqJmInWTIv2JdJy6egrHlMcQGRKJvv59bReP1Ij09AIoFEIolUKEhHCmDRERERGRvWPihoiomXXv2B3uBe4I6BhQf+cWEB7OhA0RERERUWvBpVJERERERERERHaKiRsiIiIiIiIiIjvFxA0RERERERERkZ1i4oaIiIiIiIiIyE4xcUNEREREREREZKeYuCEiIiIiIiIislNM3BARERERERER2SkmboiIiIiIiIiI7BQTN0RERERERERt1OLFiyGRSHDgwAFbh0K1YOKGiIiIiIiIyIGcPHkSzz33HAYMGAB/f3/4+fmhX79+mDlzJvbs2WPT2MaNGweJRGLTGADg4sWLWLx4MZ544gn06NEDEokEvXv3tnVYZjnbOgAiIiIiIiIiajqDwYDExESsWLECzs7OiI6OxpgxYyASiaBSqbBz50589913SEhIwPz5820drk1lZGTgnXfegZOTE7p3744bN27YOqRaMXFDRERERERE5ACSkpKwYsUK9O7dG2vWrEFwcHCN9qKiIqxcuRK5ubk2itB+REVFIS0tDb169YKbmxt8fX1tHVKtuFSKiIiIiIiIqJVTKpVYtmwZOnbsiJSUFJOkDQC4ublhzpw5WLhwYZ1jHThwABKJBIsXLzZpy87OhkQiwaxZs2ocz8rKwrPPPos+ffrAx8cHMpkMUVFReOWVV2A0GgEAEokEhw4dqv6+6uvOsc6cOYPp06eje/fu8Pb2Rq9evTBv3jyThNOlS5fg5+eH2bNn49y5c4iLi0NwcDAkEgmys7PrvEeZTIbIyEi4ubnV2c8ecMYNERERERERUQMoFEJkZQkRGmpAeLjB1uEAANavX4+KigrEx8fDx8enzr4uLi5Wvfa1a9cwfPhwFBYW4sEHH8Rjjz2GgoICKJVKrFq1CklJSXB2dsaCBQuwfv165OTkYMGCBdXn315bZtu2bYiPj4dQKMTYsWPRuXNnnDt3DitXrsTu3buxa9cukxo5SqUSI0eORM+ePREbG4vc3FyIxWKr3qMtMXFDREREREREZAGNRgC53B0qlRB6vQCenkbIZAYkJxdCKjXaNLYjR44AAKKjo1v82ps3b4ZOp8PixYtNZs/k5eXB2bky9bBw4UIcPHgQOTk5Zmf95Obm4plnnoFUKsX27dsRGBhY3ZaSkoIZM2Zg0aJFePfdd2ucd/ToUcyfPx8JCQnNcHe2x6VSRERERERERBaQy92RmekMtVqI0lIB1GohMjOdIJe72zo03Lx5EwDg7+9vsxjMLTvq0KGDxedv2LABer0er7/+eo2kDQBMnDgRffv2xaZNm0zO8/X1xdy5cxsecCvBGTdERERERERE9VAohFCpzM19ECA7WwiFQmg3y6Za2ujRo/Hmm29i7ty52LdvH0aMGIEhQ4ZAJpM1aJzMzEwAwPHjx3Hx4kWT9pKSEmg0Gmg0Gkil0urjd999t0MtjboTEzdERERERERE9cjKqlweZY5OJ4BSadvEjY+PD86fP4+rV68iLCysRa8dFBSEtLQ0LFmyBGlpafjxxx8BAN26dUNCQgImTJhg0Th5eXkAgJUrV9bZr6CgoEbipr6aPq0dl0oRERERERER1SM01ABPT/N1bLy8jAgJse1sm4EDBwIA9u/f3+SxhMLKVEFFRYVJm16vN3tOz549sWbNGly8eBFpaWmYP38+bty4gfj4+Or6O/Xx8PAAAGRkZECr1db6decyKoHAfELNUTBxQ0RERERERFSP8HADZDIDgDuTN0YEBdl+d6nY2Fg4OTlh9erVUKvVdfYtKSmps71q16arV6+atJ0+fbrOc0UiESIjI5GQkIB33nkHRqMRO3bsqG53cnICYD4pFBERAQA4duxYnddoa5i4ISIiIiIiIrJAcnIhIiIq4O1tgFhshLe3ARERFUhOLrR1aAgJCcHzzz8PjUaDSZMmQaVSmfQpLi7G8uXLsWTJkjrHCgsLg4eHB3755Zfq5UtAZQHk9957z6T/yZMnzc7EuXXrFoCa249XFSu+fPmySf+4uDh4eHjgrbfewh9//GHSXlhY2CaTOqxxQ0RERERERGQBqdSI9PQCKBRCKJVChITYfqbN7RITE1FcXIwVK1YgMjIS0dHR6NGjB0QiEbKzs7F3717k5uYiMTGxznHEYjFmzpyJ999/H9HR0Rg7dizy8/Oxfft2REVFmRQO3rhxI1avXo3BgwcjODgYHh4eUCgUSEtLQ4cOHRAXF1fdNzo6GqmpqZg6dSpGjhwJFxcX9OrVC2PGjEGnTp3w1Vdf4emnn8aQIUMQExODsLAwlJSU4NKlS8jIyMC9996LlJSUJr9WGo2mxutQVlaG3NzcGtuZJyUl1ailYytM3BARERERERE1QHi4fSVsqgiFQrz99tuYPHkyVq1ahYyMDGRkZMBgMMDX1xcjRoxAXFwchg0bVu9Yr776KkQiEdauXYtvvvkGgYGBmDdvHkaPHo3NmzfX6Dtp0iSUlJTg6NGjOH78OEpLS+Hv74/p06djzpw5CAgIqO47bdo0XLp0CSkpKfjoo49QXl6OKVOmYMyYMQCAUaNGYf/+/fj444+xd+9e7NmzB+7u7vD390dsbCzkcrlVXqv8/Hxs2LChxrGCgoIax1555RW7SNwItFqt+epKRC2suLgYOTk5CAgIgKurq63DIbIaPtvkiPhck6Pis02OqK0817du3YK3t7etw6AWZDAYUFpaCrFYXF1Q2V5Y83m0rzsjIiIiIiIiIqJqTNwQEREREREREdkpJm6IiIiIiIiIiOwUEzdERERERERERHaKiRsiIiIiIiIiIjvFxA0RERERERERkZ1i4oaIiIiIiIiIyE4xcUNEREREREREZKeYuCEiIiIiIiIislNM3BARERERERER2SkmboiIiIiIiIiI7BQTN0REREREREREdoqJGyIiIiIiIqI2avHixZBIJDhw4ICtQ6FaMHFDRERERERE5EBOnjyJ5557DgMGDIC/vz/8/PzQr18/zJw5E3v27LFpbOPGjYNEIrFpDEajEWlpaXjppZcwePBgBAYG4q677kJUVBTef/99FBcX2zS+OznbOgAiIiIiIiIiajqDwYDExESsWLECzs7OiI6OxpgxYyASiaBSqbBz50589913SEhIwPz5820drs2UlJRg8uTJcHFxwZAhQzBixAgUFxdj9+7deOutt7B161b8/PPPcHd3t3WoAJi4ISIiIiIiInIISUlJWLFiBXr37o01a9YgODi4RntRURFWrlyJ3NxcG0VoH5ycnJCYmIi//e1vNWb/lJWV4amnnsL27dvx1VdfYc6cObYL8jZcKkVERERERETUyimVSixbtgwdO3ZESkqKSdIGANzc3DBnzhwsXLiwzrEOHDgAiUSCxYsXm7RlZ2dDIpFg1qxZNY5nZWXh2WefRZ8+feDj4wOZTIaoqCi88sorMBqNAACJRIJDhw5Vf1/1dedYZ86cwfTp09G9e3d4e3ujV69emDdvnknC6dKlS/Dz88Ps2bNx7tw5xMXFITg4GBKJBNnZ2bXen0gkwty5c02WbIlEIrz00ksAUB2nPeCMGyIiIiIiIqIGUGgUyNJmIVQSinBpuK3DAQCsX78eFRUViI+Ph4+PT519XVxcrHrta9euYfjw4SgsLMSDDz6Ixx57DAUFBVAqlVi1ahWSkpLg7OyMBQsWYP369cjJycGCBQuqz+/du3f199u2bUN8fDyEQiHGjh2Lzp0749y5c1i5ciV2796NXbt2mSRclEolRo4ciZ49eyI2Nha5ubkQi8WNuheRSASgclaOvWDihoiIiIiIiMgCmiIN5KlyqHQq6Ev08HTxhMxLhuTxyZC6SW0a25EjRwAA0dHRLX7tzZs3Q6fTYfHixSazZ/Ly8uDsXJl6WLhwIQ4ePIicnByzs35yc3PxzDPPQCqVYvv27QgMDKxuS0lJwYwZM7Bo0SK8++67Nc47evQo5s+fj4SEhCbfy9q1awEAw4cPb/JY1sKlUkREREREREQWkKfKkXk9E+oiNUoNpVAXqZF5PRPyVLmtQ8PNmzcBAP7+/jaLwc3NzeRYhw4dLD5/w4YN0Ov1eP3112skbQBg4sSJ6Nu3LzZt2mRynq+vL+bOndvwgO+QlpaGb775Bt27d8dTTz3V5PGshTNuiIiIiIiIiOqh0Cig0qnMtmXrsqHQKOxm2VRLGz16NN58803MnTsX+/btw4gRIzBkyBDIZLIGjZOZmQkAOH78OC5evGjSXlJSAo1GA41GA6n0fzOc7r777kYvjary22+/Yfr06fD09MTq1autvpysKZi4ISIiIiIiIqpHljYL+hK92TZdqQ5KrdKmiRsfHx+cP38eV69eRVhYWIteOygoCGlpaViyZAnS0tLw448/AgC6deuGhIQETJgwwaJx8vLyAAArV66ss19BQUGNxE19NX3qc+LECTz66KMQCATYtGkTevTo0aTxrI1LpYiIiIiIiIjqESoJhaeLp9k2L7EXQiQhLRxRTQMHDgQA7N+/v8ljCYWVqYKKigqTNr3efPKqZ8+eWLNmDS5evIi0tDTMnz8fN27cQHx8fHX9nfp4eHgAADIyMqDVamv9unMZlUAgaMjt1XDixAlMmDABRqMRmzZtwoABAxo9VnNh4oaIiIiIiIioHuHScMi8ZGbbgryCbL5MKjY2Fk5OTli9ejXUanWdfUtKSupsr9q16erVqyZtp0+frvNckUiEyMhIJCQk4J133oHRaMSOHTuq26t2azKXFIqIiAAAHDt2rM5rWEtV0sZgMOCHH36ovr69YeKGiIiIiIiIyALJ45MR4RcBbzdviJ3E8HbzRoRfBJLHJ9s6NISEhOD555+HRqPBpEmToFKpTPoUFxdj+fLlWLJkSZ1jhYWFwcPDA7/88kv18iWgsgDye++9Z9L/5MmTZmfi3Lp1C0DN7cerihVfvnzZpH9cXBw8PDzw1ltv4Y8//jBpLywstFpS5+TJk5gwYQIqKirw/fff495777XKuM2BNW6IiNoYhUaBLG0WQiWhNv+XISKyjEIhRFaWEKGhBoSHG2wdDhFRmyV1kyL9iXQoNAootUqESELs6vepxMREFBcXY8WKFYiMjER0dDR69OgBkUiE7Oxs7N27F7m5uUhMTKxzHLFYjJkzZ+L9999HdHQ0xo4di/z8fGzfvh1RUVEmhYM3btyI1atXY/DgwQgODoaHhwcUCgXS0tLQoUMHxMXFVfeNjo5Gamoqpk6dipEjR8LFxQW9evXCmDFj0KlTJ3z11Vd4+umnMWTIEMTExCAsLAwlJSW4dOkSMjIycO+99yIlJaVJr1NeXh4mTJgAnU6HmJgY7NmzB3v27KnRx8vLC88++2yTrmMtTNwQEbURmiIN5KlyqHQq6Ev08HTxhMxLhuTxyZC6SesfgIhanEYjgFzuDpVKCL1eAE9PI2QyA5KTCyGVGm0dHhFRmxUuDberhE0VoVCIt99+G5MnT8aqVauQkZGBjIwMGAwG+Pr6YsSIEYiLi8OwYcPqHevVV1+FSCTC2rVr8c033yAwMBDz5s3D6NGjsXnz5hp9J02ahJKSEhw9ehTHjx9HaWkp/P39MX36dMyZMwcBAQHVfadNm4ZLly4hJSUFH330EcrLyzFlyhSMGTMGADBq1Cjs378fH3/8Mfbu3Ys9e/bA3d0d/v7+iI2NhVze9K3X9Xo9tFotACA9PR3p6ekmfQICAuwmcSPQarX8qU92obi4GDk5OQgICICrq6utwyGyGnt5tmM2xiDzeqbJ8Qi/CKQ/YfrDiqgu9vJcO7qYmHbIzLzz39mMiIioQHp6gU1icnR8tskRtZXn+tatW/D29rZ1GNSCDAYDSktLIRaLqwsq2wtrPo/2dWdERNQsFBoFVDqV2bZsXTYUGkXLBkRE9VIohFCpzP2qJkB2thAKBX+NIyIiagv4E5+IqA3I0mZBX2J+60ZdqQ5KrbKFIyKi+mRlVS6PMkenE0Cp5K9xREREbQF/4hMRtQGhklB4uniabfMSeyFEEtLCERFRfUJDDfD0NL+i3cvLiJAQFikmIiJqC5i4ISJqA8Kl4ZB5ycy2BXkF2WVxPaK2LjzcAJnMAODO5I0RQUHcXYqIiKitYOKGiKiNSB6fjAi/CHi7eUPsJIa3mzci/CKQPD7Z1qERUS2SkwsREVEBb28DxGIjvL0NiIioQHJyoa1DIyIiohbC7cCJiNoIqZsU6U+kQ6FRQKlVIkQSwpk2RHZOKjUiPb0ACoUQSqUQISGcaUNERNTWMHFDRNTGhEvDmbAhamXCw5mwISIiaqu4VIqIiIiIiIiIyE4xcUNEREREREREZKeYuCEiIiIiIiIislNM3BARERERERER2SkmboiIiIiIiIiI7BQTN0REREREREREdoqJGyIiIiIiIqI2avHixZBIJDhw4ICtQ6FaMHFDRERERERE5EBOnjyJ5557DgMGDIC/vz/8/PzQr18/zJw5E3v27LFpbOPGjYNEIrFpDACQlpaG6dOnIzIyEoGBgbjrrrsQGRmJ5557Dn/++aetw6vB2dYBEBEREREREVHTGQwGJCYmYsWKFXB2dkZ0dDTGjBkDkUgElUqFnTt34rvvvkNCQgLmz59v63BtaufOnTh27BgiIiIQExMDkUiEc+fOYcOGDfj+++/x3Xff4f7777d1mACYuCEiIiIiIiJyCElJSVixYgV69+6NNWvWIDg4uEZ7UVERVq5cidzcXBtFaD/eeustvPvuuybH9+3bh/Hjx+Pf//63zWcnVeFSKSIiIiIiIqJWTqlUYtmyZejYsSNSUlJMkjYA4Obmhjlz5mDhwoV1jnXgwAFIJBIsXrzYpC07OxsSiQSzZs2qcTwrKwvPPvss+vTpAx8fH8hkMkRFReGVV16B0WgEAEgkEhw6dKj6+6qvO8c6c+YMpk+fju7du8Pb2xu9evXCvHnzTBJOly5dgp+fH2bPno1z584hLi4OwcHBkEgkyM7OrvMeXV1dzR6///77IZFIoFQq6zy/JXHGDREREREREVEDKIRCZAmFCDUYEG4w2DocAMD69etRUVGB+Ph4+Pj41NnXxcXFqte+du0ahg8fjsLCQjz44IN47LHHUFBQAKVSiVWrViEpKQnOzs5YsGAB1q9fj5ycHCxYsKD6/N69e1d/v23bNsTHx0MoFGLs2LHo3Lkzzp07h5UrV2L37t3YtWuXSY0cpVKJkSNHomfPnoiNjUVubi7EYnGj7uXXX3+FVqvFoEGDGnV+c2DihoiIiIiIiMgCGoEAcnd3qIRC6AUCeBqNkBkMSC4shPS/s0ps5ciRIwCA6OjoFr/25s2bodPpsHjxYpPZM3l5eXB2rkw9LFy4EAcPHkROTo7ZWT+5ubl45plnIJVKsX37dgQGBla3paSkYMaMGVi0aJHJEqejR49i/vz5SEhIaHDsu3fvxtGjR1FaWoqsrCzs2LEDUqkUb7/9doPHai5M3BARERERERFZQO7ujkzn/32MVgsEUP83mZNeUGDDyICbN28CAPz9/W0Wg5ubm8mxDh06WHz+hg0boNfrsXTp0hpJGwCYOHEiPv74Y2zatMkkcePr64u5c+c2Kubdu3dj+fLl1X8OCQnB119/jX79+jVqvObAxA0RERERERFRPRRCIVRCM2ViBQJkC4VQCIV2s2yqpY0ePRpvvvkm5s6di3379mHEiBEYMmQIZDJZg8bJzMwEABw/fhwXL140aS8pKYFGo4FGo4FUKq0+fvfddzd6aVRSUhKSkpKQn5+Pc+fOYenSpRg1ahSWL1+OyZMnN2pMa2PihoiIiIiIiKgeWf9dHmWOTiCA0saJGx8fH5w/fx5Xr15FWFhYi147KCgIaWlpWLJkCdLS0vDjjz8CALp164aEhARMmDDBonHy8vIAACtXrqyzX0FBQY3ETX01fSzRvn173HPPPVi3bh2GDRuGF154AQ888AA6derU5LGbirtKEREREREREdUj1GCAZy11bLyMRoTYeLbNwIEDAQD79+9v8ljC/84sqqioMGnT6/Vmz+nZsyfWrFmDixcvIi0tDfPnz8eNGzcQHx9fXX+nPh4eHgCAjIwMaLXaWr/uXEYlqCWh1hjOzs4YOnQoCgoKcOLECauN2xRM3BARERERERHVI9xggMxgAO5M3hiNCLKD3aViY2Ph5OSE1atXQ61W19m3pKSkzvaqXZuuXr1q0nb69Ok6zxWJRIiMjERCQgLeeecdGI1G7Nixo7rdyckJgPmkUEREBADg2LFjdV6juV2/fh1A5b3YAyZuiIiIiIiIiCyQXFiIiIoKeBsMEBuN8DYYEFFRgeTCQluHhpCQEDz//PPQaDSYNGkSVCqVSZ/i4mIsX74cS5YsqXOssLAweHh44JdffqlevgRUFkB+7733TPqfPHnS7EycW7duAai5/XhVseLLly+b9I+Li4OHhwfeeust/PHHHybthYWFVkvq1DabZteuXfj555/h5eWFyMhIq1yrqVjjhoiIiIiIiMgCUqMR6QUFUAiFUAqFCLGDmTa3S0xMRHFxMVasWIHIyEhER0ejR48eEIlEyM7Oxt69e5Gbm4vExMQ6xxGLxZg5cybef/99REdHY+zYscjPz8f27dsRFRVlUjh448aNWL16NQYPHozg4GB4eHhAoVAgLS0NHTp0QFxcXHXf6OhopKamYurUqRg5ciRcXFzQq1cvjBkzBp06dcJXX32Fp59+GkOGDEFMTAzCwsJQUlKCS5cuISMjA/feey9SUlKa/Fo98MAD6NmzJ+6++274+/ujsLAQZ86cweHDhyESibB8+XK0a9euydexBiZuiIiIiIiIiBog3M4SNlWEQiHefvttTJ48GatWrUJGRgYyMjJgMBjg6+uLESNGIC4uDsOGDat3rFdffRUikQhr167FN998g8DAQMybNw+jR4/G5s2ba/SdNGkSSkpKcPToURw/fhylpaXw9/fH9OnTMWfOHAQEBFT3nTZtGi5duoSUlBR89NFHKC8vx5QpUzBmzBgAwKhRo7B//358/PHH2Lt3L/bs2QN3d3f4+/sjNjYWcrncKq/V66+/jgMHDuDQoUNQq9UQCoXo0qULnn76acyaNQvdu3e3ynWsQaDVas1XV7IjycnJOHz4ME6ePImzZ8+itLQUn376aY2sHQCUlZVh27Zt+OWXX/Dbb7/hypUrEAgE6N69O2JjY/H0009Xr6e703fffYfPP/8cCoUCIpEIAwcOxMKFC+1q73ZHV1xcjJycHAQEBMDV1dXW4RBZDZ9tckR8rslR8dkmR9RWnutbt27B29vb1mFQCzIYDCgtLYVYLK4uqGwvrPk8tooZN0lJScjJyYFUKoWvry9ycnLM9rt48SKmTZuG9u3bIzo6GmPGjIFer8f27dvx8ssvY+fOndi4caNJxen33nsPSUlJCAgIQHx8PPLz87Fp0yaMGjUKqamp1dW5iYiIiIiIiIhaUqtI3HzyyScICQlBYGAgPvzwQ7zxxhtm+7Vv3x7vvfcepkyZUmMtWlJSEh566CHs2LEDqampNfaQz8rKwpIlS9C1a1fs2rULXl5eAIAZM2Zg5MiReP7553H48GG7y94REZEphUaBLG0WQiWhCJeG2zocIoelUAiRlSVEaKgB4eH2t1SAiIjIkbSKbMSwYcNM9mk3x9/fH3/7299MCgi1a9cOs2fPBgAcOnSoRtu6detQXl6Ol19+uTppAwB9+vTBxIkTce7cORw+fNgKd0FERM1FU6RBzMYYPPTDQ4jfGo+HfngIMRtjoCnS2Do0Ioei0QgQE9MODz3UDvHx7njooXaIiWkHjUZQ/8lERETUKK0icWMNVfuv31nj5uDBgwCA4cOHm5wzYsQIAKbJHiIisi/yVDkyr2dCXaRGqaEU6iI1Mq9nQp5qneJ1RFRJLndHZqYz1GohSksFUKuFyMx0glzubuvQiIiIHFarWCplDWvXrgVgmqDJyspC+/bt4evra3JOaGhodZ/6FBcXWyHKtq20tLTGf4kcBZ/t5nUu9xxUWpXZNpVOhVNXT6F7R/vZFcBR8Llue86dc4JKZW5mjQAqlQCnTpWhe/eKFo/L2vhskyNqK8+1wWCAwQ53eqLmYzQaq/9rb++9wWCoNU/Q0CLhbSJxs3r1aqSlpSE6OhoPPvhgjTa9Xl9rpWcPD4/qPvW5evUqKipa/y8r9uDGjRu2DoGoWfDZbh7Hrh+DtkRrtk1XrMMx5TG4F3A2QHPhc912HDsmgVbb0WybTifAsWN5cHfXtXBUzYfPNjkiR3+uxWKxwyenyLyysjJbh2CiuLjYbC7ByckJISEhDRrL4RM327dvx7x58xAQEIAvv/yy2a7j7+/fbGO3FaWlpbhx4wZ8fX0hFottHQ6R1fDZbl6R7SIh+T8J1MVqkzYvVy9EhkQioGOADSJzbHyu257ISCdIJEaoTf9Xg5eXEZGRHRAQ4NnygVkZn21yRG3ludbpdA59f2TKaDSirKwMIpHIZPdoW3N1dTW7sqcxHDpxs3PnTkybNg0+Pj7YsmUL/Pz8TPp4enrWOqPmr7/+qu5Tn4ZOdaLaicVivp7kkPhsN4++/n0hk8igvm76aVLmJUNf/742iKrt4HPddvTtC8hkRqjVRgC3/3JshExmRN++IgAiG0VnfXy2yRE5+nP9119/cTfgNqZqeZRAILC7914oFFrt/zf7ujMr2rFjB5566ilIpVJs2bIFMpnMbL/Q0FDk5+ebnTZYVdumqtYNERHZp+TxyYjwi4C3mzfETmJ4u3kjwi8CyeOTbR0akUNJTi5EREQFvL0NEIuN8PY2ICKiAsnJhbYOjYiIyGE55IybHTt2YOrUqejQoQO2bNlS5/qxqKgo/Prrr9i9ezemTJlSo23Xrl3VfYiIyH5J3aRIfyIdCo0CSq0SIZIQhEvDbR0WkcORSo1ITy+AQiGEUilESIgB4eH2VQySiIjI0TjcjJu0tDRMnToVEokEW7ZsqXe2TFxcHJydnfH+++9Dp/tfQb3Tp08jJSUF3bt3x6BBg5o7bCIisoJwaTjGho5l0oaomYWHGzB2bDmTNkRERC2gVcy4WbNmDQ4fPgwAOHv2LADg22+/xcGDBwEAgwYNwtSpU3H+/Hk8+eSTKCkpwZAhQ/DDDz+YjBUYGIi4uLjqP3ft2hWvvPIKkpKSMGTIEDzyyCPIz8/Hpk2bAADLli2zu7VyRERERERERNQ2tIrEzeHDh7Fhw4Yax44cOYIjR45U/3nq1Km4ceMGSkpKAAApKSlmx4qKiqqRuAGAuXPnIjAwEJ999hm+/vpriEQiDBo0CAkJCejXr591b4aIiIiIiIiIyEKtInHz2Wef4bPPPqu339ChQ6HVaht1jccffxyPP/54o84lIiIiIiIiao0WL16Md955B1u2bMHQoUNtHQ6ZwTVARERERERERA7k5MmTeO655zBgwAD4+/vDz88P/fr1w8yZM7Fnzx6bxjZu3DhIJBKbxmCOVqtFjx49IJFIMHHiRFuHU0OrmHFDRERERERERHUzGAxITEzEihUr4OzsjOjoaIwZMwYikQgqlQo7d+7Ed999h4SEBMyfP9/W4dqVefPmQa/X2zoMs5i4ISIiIiIiInIASUlJWLFiBXr37o01a9YgODi4RntRURFWrlyJ3NxcG0Von1JTU/H999/j3Xffxbx582wdjgkulSIiIiIiIiJq5ZRKJZYtW4aOHTsiJSXFJGkDAG5ubpgzZw4WLlxY51gHDhyARCLB4sWLTdqys7MhkUgwa9asGsezsrLw7LPPok+fPvDx8YFMJkNUVBReeeUVGI1GAIBEIsGhQ4eqv6/6unOsM2fOYPr06ejevTu8vb3Rq1cvzJs3zyThdOnSJfj5+WH27Nk4d+4c4uLiEBwcDIlEguzs7PpfNABqtRovv/wy5HI5HnzwQYvOaWmccUNERERERETUAEKFEMIsIQyhBhjCDbYOBwCwfv16VFRUID4+Hj4+PnX2dXFxseq1r127huHDh6OwsBAPPvggHnvsMRQUFECpVGLVqlVISkqCs7MzFixYgPXr1yMnJwcLFiyoPr93797V32/btg3x8fEQCoUYO3YsOnfujHPnzmHlypXYvXs3du3aZVIjR6lUYuTIkejZsydiY2ORm5sLsVhsUewvvvginJyc8M4770Cn01nl9bA2Jm6IiIiIiIiILCDQCOAud4dQJYRAL4DR0wiDzIDC5EIYpUabxnbkyBEAQHR0dItfe/PmzdDpdFi8eLHJ7Jm8vDw4O1emHhYuXIiDBw8iJyfH7Kyf3NxcPPPMM5BKpdi+fTsCAwOr21JSUjBjxgwsWrQI7777bo3zjh49ivnz5yMhIaFBcScnJ2PLli1Yt24dJBKJ3SZuuFSKiIiIiIiIyALucnc4ZzpDqBZCUCqAUC2EU6YT3OXutg4NN2/eBAD4+/vbLAY3NzeTYx06dLD4/A0bNkCv1+P111+vkbQBgIkTJ6Jv377YtGmTyXm+vr6YO3dug2K9du0aFixYgEmTJmHcuHENOrelccYNERERERERUT2ECiGEKtO5DwIIIMwWQqgQ2s2yqZY2evRovPnmm5g7dy727duHESNGYMiQIZDJZA0aJzMzEwBw/PhxXLx40aS9pKQEGo0GGo0GUqm0+vjdd99t8dKoKnPmzIFIJMI777zToPNsgYkbIiIiIiIionoIsyqXR5kj0AkgVNo2cePj44Pz58/j6tWrCAsLa9FrBwUFIS0tDUuWLEFaWhp+/PFHAEC3bt2QkJCACRMmWDROXl4eAGDlypV19isoKKiRuKmvps+d1q9fj7S0NPznP/+pMY69YuKGiIiIiIiIqB6GUAOMnkYI1KbJG6OXEYYQ2862GThwIA4ePIj9+/fj/vvvb9JYQmHlzKKKigqTNr1eb/acnj17Ys2aNSgrK8PJkyeRlpaGL774AvHx8fDz88PAgQPrva6HhwcAICMjAz179rQ4XoHAfEKtNqdPnwYATJs2zWx7VQHkXr164eDBgw0auzkwcUNERERERERUD0O4AQaZAQK1AAL8L1FghBGGINvvLhUbG4sPP/wQq1evxqxZs9CpU6da+5aUlNS5s1TVrk1Xr141aatKetRGJBIhMjISkZGRCAkJwTPPPIMdO3ZUJ26cnJwAVCaFqr6vEhERgS1btuDYsWMNStw01L333ouCggKT4wUFBdi0aRM6d+6M4cOHo0uXLs0WQ0MwcUNERERERERkgcLkwspdpbKFEOgElTNtgip3lbK1kJAQPP/88/jggw8wadIkrF692qTGTHFxMb766itoNBr861//qnWssLAweHh44JdffkFeXl51geGbN2/ivffeM+l/8uRJhISEwNPTs8bxW7duAai5/XjVWJcvX0ZQUFCN/nFxcXjvvffw1ltv4d5770WPHj1qtBcWFuL//u//EBkZWc+rUbfHHnsMjz32mMnx7OxsbNq0CeHh4fjkk0+adA1rYuKGiIiIiIiIyAJGqREF6QWVhYqVQhhCbD/T5naJiYkoLi7GihUrEBkZiejoaPTo0QMikQjZ2dnYu3cvcnNzkZiYWOc4YrEYM2fOxPvvv4/o6GiMHTsW+fn52L59O6KiokwKB2/cuBGrV6/G4MGDERwcDA8PDygUCqSlpaFDhw6Ii4ur7hsdHY3U1FRMnToVI0eOhIuLC3r16oUxY8agU6dO+Oqrr/D0009jyJAhiImJQVhYGEpKSnDp0iVkZGTg3nvvRUpKSrO8fvaKiRsiIiIiIiKiBjCE21fCpopQKMTbb7+NyZMnY9WqVcjIyEBGRgYMBgN8fX0xYsQIxMXFYdiwYfWO9eqrr0IkEmHt2rX45ptvEBgYiHnz5mH06NHYvHlzjb6TJk1CSUkJjh49iuPHj6O0tBT+/v6YPn065syZg4CAgOq+06ZNw6VLl5CSkoKPPvoI5eXlmDJlCsaMGQMAGDVqFPbv34+PP/4Ye/fuxZ49e+Du7g5/f3/ExsZCLpdb9TVrDQRardZo6yCIgMppezk5OQgICICrq6utwyGyGj7b5Ij4XJOj4rNNjqitPNe3bt2Ct7e3rcOgFmQwGFBaWgqxWFxdUNleWPN5tK87IyIiIiIiIiKiakzcEBERERERERHZKSZuiIiIiIiIiIjsFBM3RERERERERER2iokbIiIiIiIiIiI7xcQNEREREREREZGdYuKGiIiIiIiIiMhOMXFDRERERERERGSnmLghIiIiIiIiIrJTTNwQEREREREREdkpZ1sHQERErZdCIURWlhChoQaEhxtsHY5DU2gUyNJmIVQSinBpuK3DISIiIqIWwsQNERE1mEYjgFzuDpVKCL1eAE9PI2QyA5KTCyGVGm0dnkPRFGkgT5VDpVNBX6KHp4snZF4yJI9PhtRNauvwiIiIiKiZcakUERE1mFzujsxMZ6jVQpSWCqBWC5GZ6QS53N3WoTkceaocmdczoS5So9RQCnWRGpnXMyFPlds6NCIiorbFaIST9je4nF8K918nol3GKLj/OhEu55fCSfsbYOQ/Xtla79690bt3b4v7r1u3DhKJBOvWrWvGqJqOiRsiImoQhUIIlcrcjw8BsrOFUCj4o8VaFBoFVDqV2bZsXTYUGkXLBkRERNQWGY0Q5axD+30RcP91ElwvvA3RrV1wzjsK0a1dcL3wNtx/nYT2+yIhyllnFwmckydP4rnnnsOAAQPg7+8PPz8/9OvXDzNnzsSePXtaLI7Wkhixd1wqRUREDZKVVbk8yhydTgClUsh6N1aSpc2CvkRvtk1XqoNSq2S9GyIiouZUpoV7Zhyc9L9DWG7+ZzIACMtygbJcuJ5dCNHlDSiMWAuIJC0X538ZDAYkJiZixYoVcHZ2RnR0NMaMGQORSASVSoWdO3fiu+++Q0JCAubPn9/i8TW3zZs32zqEZsHEDRERNUhoqAGenkao1abJGy8vI0JCmLSxllBJKDxdPKEuUpu0eYm9ECIJsUFUREREbUSZFu0zRkOYfw4CWDaLRliuhyD3ENpnjEb+4O0tnrxJSkrCihUr0Lt3b6xZswbBwcE12ouKirBy5Urk5ua2aFwt5c77dRScz05ERA0SHm6ATGYATH6BMSIoiLtLWVO4NBwyL5nZtiCvIM62ISIiai5GI9wz4xqUtKkigBHC/HNwz3yyRZdNKZVKLFu2DB07dkRKSorZJIabmxvmzJmDhQsXVh8rLS3F8uXLER0dDX9/f3Tp0gVjxozBtm3bTM6fNWsWJBIJVCoVPv/8c0RGRsLHxwe9evXCkiVLYDAYavSdPXs2AGD27NmQSCTVX1XGjRsHiUSC4uJiJCUloV+/fujUqRMWL15c3efIkSN4/PHHIZPJ4Ovri8jISLz99tsoLCw0ia+2Gjd5eXl48cUXERYWhrvuugsPPPAAtmzZUutruX//fkyaNAnh4eHw8fFBWFgYxowZg9WrV9d6TnPijBsiImqw5ORCyOXuyM4WQqcTwMurMmmTnGz6A5SaJnl8MuSpcmTrsqEr1cFL7IUgryAkj0+2dWhEREQOS3R5PZz0vzc4aVNFACOc9KchurweZQFxVo7OvPXr16OiogLx8fHw8fGps6+LiwsAoKSkBBMnTsTBgwfRu3dvPPnkkygvL8fOnTsRGxuLpUuXYubMmSbnv/766zh06BBGjRqF4cOHY+vWrViyZAnKysrw2muvAahMyuh0Omzbtg1jx46ts2jw1KlTcebMGYwYMQJeXl4ICgoCAPz000+YMWMGXFxc8Oijj8Lb2xu7d+/G0qVLsXv3bmzevBlCYd3zUQoLCzFu3DicPXsW9957L6KionDlyhVMnz4dw4cPN+m/Y8cOPPHEE/Dy8sLYsWPh5+cHtVqNM2fOIDk5GU8//XSd12sOTNwQEVGDSaVGpKcXQKEQQqkUIiSEM22ai9RNivQn0qHQKKDUKhEiCeFMGyIiouZkNMIl64M6a9pYQliuh0vWhyjrEgsIzNcHtKYjR44AAKKjoy0+Z+nSpTh48CDmzZuHhIQECP4b519//YVHHnkEiYmJePjhh3HXXXfVOO/UqVM4dOgQ/Pz8AADz58/HgAED8OWXX2LBggUQi8V46KGHqhM348aNQ1xc7Qmsa9eu4dChQ+jQoUP1Mb1ejzlz5sDZ2Rk7d+5Er169AFQmjf72t79h06ZN+OSTT/D888/XeY/Lli3D2bNnMW3aNCxbtqz6uFwux8SJE036r127FkajEVu2bDFJNtlqiRmXShERUaOFhxswdmw5kzYtIFwajrGhY5m0ISIiamZOuhMQlOZZZSxBaS6cdCesMlZ9bt68CQDw9/e3qL/BYMCqVasQHBxcI2kDAB4eHpg/fz5KS0vNLimaN29eddIGAKRSKcaOHYu//voLFy5caHDsCxcurJG0AYBt27ZBr9fjySefrE7aAIBQKMQbb7wBZ2dnbNiwod6xN27cCLFYjISEhBrHR4wYgfvvv7/W89zc3EyOdezYsd7rNQfOuCEiIiIiIiL6L+eb6ZW7RFmBsCwXzrd2o0IywCrjWdOFCxeg1Wpx1113YcmSJSbtGo2mut+d+vXrZ3Ksc+fOAACdTtfgWO655x6TY6dPnwYADBkyxKQtICAAMpkMf/75J/Lz82tNqOj1emRnZyM8PBy+vr4m7YMGDcK+fftqHJs4cSK2bNmCmJgYTJ48GdHR0Rg8eDCkUmmD78tamLghIiIiIiIi+i8n7VHrjpd32Krj1cbHxwfnz5/H1atXERYWVm//vLzKWUV//PEH/vjjj1r7FRQUmBzz8PAwOebk5AQAqKiosDTkauZq8vz1118AAG9vb7Pn+Pr64s8//8Rff/1Va+KmaoxOnTpZfN0JEyZg3bp1+PTTT/H1119j5cqVEAgEGDp0KJKSktCnTx+L7smauFSKiIiIiIiI6L8E5fl2PV5tBg4cCKByRyRLVCVfHnnkEWi12lq/VqxY0WwxVxGYqQFUFd+tW7fMnlO1NMxcEunOMdRqdZ1j3GncuHHYtm0bVCoVfvjhB0ydOhUHDx7EpEmToNVqa71ec2HihoiIiIiIiOi/jM7t7Xq82sTGxsLJyQmrV6+uNVFRpaSkBN27d4enpydOnDiBsrKyZompKbNwqma2HDx40KTt8uXLuHjxImQyGdq3r/319fT0RFBQEJRKJW7cuGHSfvhw3bOhPDw8EBMTg2XLliE2NhY3b97E8ePHG3gnTcfEDREREREREdF/VUjus+54HQZZdbzahISE4Pnnn4dGo8GkSZOgUqlM+hQXF2P58uVYsmQJnJ2dMX36dOTk5CAxMdFs8ubs2bO1znixRFXB4StXrjT43LFjx8LT0xPr1q2rsZTLaDTi3//+N8rLyzFlypR6x5HL5SgtLcXbb79d4/ju3btN6tsAwKFDh8wmmqpeh6qt1FsSa9wQERERERER/Ve5TwwMqs+tUqDYIOqIcu/hVojKMomJiSguLsaKFSsQGRmJ6Oho9OjRAyKRCNnZ2di7dy9yc3ORmJgIoHI3p1OnTuGLL77Azp07MXjwYHh7e+Pq1as4e/Yszpw5g7S0tFrrzNTn3nvvhZubGz777DNotdrqWjPz5s2r91xPT098/PHHmDFjBmJiYvDoo4+iU6dO2Lt3L06ePIl77rkH//znP+sd5/nnn8fPP/+M//znP1AoFBg8eDCuXLmCH3/8EaNGjcKOHTtq9F+wYAGuX7+OgQMHIjAwEAKBAEeOHMHx48cRGRmJQYNaJhF3OyZuiIiIiIiIiP6rwqs/jOIOgBUSN0ZxR1R49bdCVJYRCoV4++23MXnyZKxatQoZGRnIyMiAwWCAr68vRowYgbi4OAwbNgxA5eyRH374Ad9++y02btyILVu2oKSkBN7e3ggPD8f06dPRs2fPRsfToUMH/Oc//8GSJUuwZs0aFBUVAbAscQNUFgr28fHBhx9+iC1btqCoqAiBgYGYN28eXnjhBbi6uqK0tLTOMdq1a4etW7fijTfewM8//4xTp04hPDwcX3/9NfR6vUni5qWXXsKWLVtw8uRJ7N69G87OzggMDMQbb7yBGTNmVC//akkCrVZrbPGrEplRXFyMnJwcBAQEwNXV1dbhEFkNn21yRHyuyVHx2SZH1Fae61u3bjV6ZsidRDnr4Hp2IYTl+kaPYXD2RHHPxSgLiLNKTGTKYDCgtLQUYrEYQqF9VYKx5vNoX3dGREREREREZGNlXWJR4dkbRpjudmQJIwSo8OyDsi6xVo6M2iImboiIiIiIiIhuJxCgMGIdDO27Nzh5Y4QAhvbdURixFjCzzTVRQzFxQ0RERERERHQnkQT5g7ejvONgGJw9LTrF4OyJ8o5RyB+8HRBJmjc+ajOYuCEiIiIiIiIyRyRB4cCfUdxzMSradYVB1NFsN4OoIyradUVxz8UoHLiFSRuyKu4qRURERERERFQbgQBlAXEo6xILJ90JON/aBae8IxCU58Po3B4VHQah3Ht45e5RXBpFzYCJGyIiIiIiIqL6CASokAxAhWSArSOhNoZLpYiIiIiIiIiI7BQTN0REREREREREdoqJGyIiIiIiImr1hEIhKioqbB0GESoqKiAUWi/dwsQNERERERERtXoeHh7QaDQoLi6G0Wi0dTjUBhmNRhQXF0Oj0cDDw8Nq47I4MREREREREbV6YrEYnTp1gl6vx19//WXrcKgFGAwGFBcXw9XV1aozXJpCJBKhU6dOVo2HiRsiIiIiIiJyCEKhEBKJxNZhUAspLi6GXq+Hr68vXF1dbR1Os7GPlBQREREREREREZlg4oaIiIiIiIiIyE4xcUNEREREREREZKeYuCEiIiIiIiIislNM3BARERERERER2SkmboiIiIiIiIiI7BQTN0REREREREREdoqJGyIiIiIiIiIiO8XEDRERERERERGRnWLihoiIiIiIiIjITjFxQ0RERERERERkp5i4ISIiIiIiIiKyU0zcEBERERERERHZKSZuiIiIiIiIiIjsFBM3RERERERERER2iokbIiIiIiIiIiI7xcQNEREREREREZGdYuKGiIiIiIiIiMhOMXFDRERERERERGSnmLghIiIiIiIiIrJTTNwQEREREREREdkpJm6IiIiIiIiIiOwUEzdERERERERERHaKiRsiIiIiIiIiIjvlbOsAiIioZSk0CmRpsxAqCUW4NNzW4QAAFAohsrKECA01IDzcYOtw7PI1cmT29v4TERER2RMmboiI2ghNkQbyVDlUOhX0JXp4unhC5iVD8vhkSN2ktolJI4Bc7g6VSgi9XgBPTyNkMgOSkwshlRpbPh47fI0cmb29/0RERET2iEuliIjaCHmqHJnXM6EuUqPUUAp1kRqZ1zMhT5XbLia5OzIznaFWC1FaKoBaLURmphPkcnfbxGOHr5Ejs7f3n4iIiMgeMXFDRNQGKDQKqHQqs23ZumwoNIqWDQiVy2NUKnM/hgTIzhZCoWjZH1H2+Bo5Mnt7/4mIiIjsFX8rIiJqA7K0WdCX6M226Up1UGqVLRwRkJVVuTzGHJ1OAKWyZX9E2eNr5Mjs7f0nIiIislf8rYiIqA0IlYTC08XTbJuX2AshkpAWjggIDTXA09N8HRMvLyNCQlq2SK09vkaOzN7efyIiIiJ7xcQNEVEbEC4Nh8xLZrYtyCvIJjsnhYcbIJMZANz54d2IoKCW313IHl8jR2Zv7z8RERGRvWLihoiojUgen4wIvwh4u3lD7CSGt5s3IvwikDw+2XYxJRciIqIC3t4GiMVGeHsbEBFRgeTkQtvEY4evkSOzt/efiIiIyB5xO3AiojZC6iZF+hPpUGgUUGqVCJGE2HwWiVRqRHp6ARQKIZRKIUJCbDvTwh5fI0dmb+8/ERERkT1i4oaIqI0Jl4bbXTIiPNy+PrDb42vkyOzt/SciIiKyJ1wqRURERERERERkpzjjhogcikKjQJY2C6GSUM6YICIiagYKhRBZWUKEhnK2HBFRS2DihogcgqZIA3mqHCqdCvoSPTxdPCHzkiF5fDKkblJbh0dERNTqaTQCyOXuUKmE0OsF8PQ0QiYzIDm5EFLpnTvEERGRtXCpFBE5BHmqHJnXM6EuUqPUUAp1kRqZ1zMhT5XbOjQiIiKHIJe7IzPTGWq1EKWlAqjVQmRmOkEud7d1aEREDo2JGyJq9RQaBVQ6ldm2bF02FBpFywZERETkYBQKIVQqcx8dBMjOFkKh4McKIqLm0ir+hk1OTsYLL7yAYcOGwcfHBxKJBOvWrau1v16vR0JCAnr16gUfHx/07t0br732GvLz8832NxgM+OKLLzB48GD4+fkhNDQUM2bMgEqlaqY7IiJrytJmQV+iN9umK9VBqVW2cERERESOJSurcnmUOTqdAEplq/hYQUTUKrWKv2GTkpKwevVq5OTkwNfXt86+BQUFGDduHFasWIFu3brh2WefRVhYGD755BM88sgjKC4uNjnnhRdewIIFC2A0GvGPf/wDI0aMwJYtW/DAAw8gKyuruW6LiKwkVBIKTxdPs21eYi+ESEJaOCIiIiLHEhpqgKen+To2Xl5GhISwSDERUXNpdHHi//u//8OBAwdw8OBBZGdnQ61Wo6ioCFKpFD4+PujXrx+GDh2KoUOHwsPDo0lBfvLJJwgJCUFgYCA+/PBDvPHGG7X2XbZsGX7//Xe88MIL+Pe//119/N///jc++ugjrFixAi+99FL18f3792PNmjUYPHgwfvrpJ4jFYgDA5MmTMXnyZMybNw+bNm1qUvxE1LzCpeGQecmgLlKbtAV5BXF3KSIioiYKDzdAJjNArRYAuH3mjRFBQdxdioioOTUocVNQUIDvvvsOq1atwtmzZwEARmPNzLtOp4NSqcTRo0fxxRdfwM3NDRMnTsT06dPRr1+/RgU5bNgwi/oZjUZ8++23aN++PebNm1ejbd68efjqq6+wZs2aGombNWvWAABeffXV6qQNAIwcORJDhgzB7t27kZOTg4CAgEbFTkQtI3l8MuSpcmTrsqEr1cFL7IUgryAkj0+2dWhEREQOITm5EHK5O7KzhdDpBPDyqkzaJCcX2jo0IiKHZlHixmg04ptvvsHixYuh0WhgNBrRqVMnREREICIiAn5+fujYsSNcXV2Rl5eHvLw8nD17FseOHcMff/yBb7/9FmvXrsWYMWOQlJSE4ODgZrmZrKwsXLt2DSNGjEC7du1qtLVr1w733Xcfdu3ahcuXL6NLly4AgIMHD6Jdu3YYOHCgyXgjRozAwYMHcejQITzxxBPNEjMRWYfUTYr0J9Kh0Cig1CoRIgnhTBsiIiIrkkqNSE8vgEIhhFIpREgIZ9oQEbUEixI3UVFRUCgU8PDwwNSpUzFlyhTcd999Fl1Aq9UiJSUFGzduxLZt25Ceno4VK1Zg4sSJTQrcnKp6NCEh5utZhISEYNeuXcjKykKXLl1QUFCA69evo2fPnnBycjLb//Zx62Kudg41TGlpaY3/EjWGrJ0MsnYyAPbz/yWfbXJEfK7JUfHZrp9MVvkFAHbyo5bqweeaHFVrfbZdXV0b1N+ixM2VK1ewYMECPPvssw2uVyORSDBjxgzMmDEDR44cwaJFi/Dnn382aAxL6fWVu8p4eXmZbff09KzRr+q/Vcfr61+Xq1evoqKiomEBk1k3btywdQhEzYLPNjkiPtfkqPhskyPic02OqjU9205OTrVONqmNRYmbU6dOQSKRNCamGgYOHIgtW7ZAq9U2eSx74+/vb+sQWr3S0lLcuHEDvr6+NeoNEbV2Z26cwclLJ9EvsB96+faydThEVmHNv7PPnXPCxYvOCA4uR/fu/EcQsi3+PkKOiM81Oaq28mxblLixRtKmOcerUjVDRqfTmW2/c4ZNfTNq6puRc7uGTnWi2onFYr6e5BA0RRrIU+VQaVXQlmgh+T8JZBIZkscnQ+omtXV4RFbRlL+zNRoB5HJ3qFRC6PUCeHoaIZNVFjqVSs1vO0zUUvj7CDkiPtfkqBz92RbaOgBrCg0NBQAolUqz7VXHq/q1a9cOfn5+yM7ONrvM6c7+REQNIU+VI/N6JtTFapQby6EuViPzeibkqXJbh0ZkF+Ryd2RmOkOtFqK0VAC1WojMTCfI5e62Do2IiIjIbjRoO/A73bhxAxcuXIBWq0VRURHc3NwgkUgQFhYGX19fa8VosdDQUNx11104evQoCgoKauwsVVBQgKNHjyIoKKh6RymgsvBySkoKjhw5gqioqBrj7dq1CwAwePDglrkBInIYCo0CKp3KbFu2LhsKjYK7XlGbplAIoVKZ+/cjAbKzhVAohNythoiIiAiNmHGTm5uLN998E3379kWPHj3wyCOPYOrUqfjHP/6BqVOn4pFHHkGPHj3Qp08fvPHGG9BoNM0Rt1kCgQBPPfUU8vPz8e6779Zoe/fdd5Gfn49p06bVOF7150WLFtWoRJ2WloaDBw9i+PDhCAwMbP7gicihZGmzoC8xvwxTV6qDUmt+ZiBRW5GVVbk8yhydTgCl0qEmBRMRERE1WoNm3OzduxdPP/009Ho9jMbKtecikQheXl5wcXFBSUkJdDodysrKkJOTg2XLluGbb77B119/jeHDhzc6yDVr1uDw4cMAgLNnzwIAvv32Wxw8eBAAMGjQIEydOhUA8Pzzz2Pbtm346KOPcPr0afTt2xenTp3C7t27MWDAAMyaNavG2NHR0Zg6dSrWrFmD+++/Hw8++CCuX7+OH3/8ER06dMDSpUsbHTcRtV2hklB4unhCXaQ2afMSeyFE0rBK8kSOJjTUAE9PI9Rq0+SNl5cRISGcbUNEREQENCBxc+HCBUyZMgXFxcW477778PTTTyMqKgpdunSBQPC/X7qMRiMuX76MQ4cO4ZtvvsGvv/6KuLg47N+/H2FhYY0K8vDhw9iwYUONY0eOHMGRI0eq/1yVuGnXrh22bt2KJUuWYMuWLThw4AB8fX3x3HPPYcGCBXBzczMZ/6OPPkLPnj3xn//8B59//jnatWuHhx56CK+99hqCg4MbFTMRtX4KjQJZ2iyESkIbvKwpXBoOmZfMbOImyCuIy6SozQsPN0AmM/w3cXN78saIoCADl0k1E4VCiKwsIUJD+RoTERG1FgKtVmvRtg3PPPMMkpOT8cILL+Bf//qXxRf417/+hY8//hhyuRyff/55owMlx1dcXIycnBwEBAQ4dEVwsn/Vu0HpVNCX6OHp4gmZV8N3g7p9HF2xDl6uXo0ah8geWePv7KpdpbKzhdDpBPDyqkzacFcp6+MOXpbj7yPkiPhck6NqK8+2xYmbu+++G6WlpVAoFHBycrL4AuXl5QgPD4dYLK5e5kRkTlv5n47sX8zGGGRezzQ5HuEXgfQn0hs83qmrp3BMeQyRIZHo69/XGiES2Zw1/85WKIRQKoUICeEskOYSE9MOmZl3TrQ2IiKiAunpBTaJyV7x9xFyRHyuyVG1lWfb4sp/arUaAQEBDUraAICzszMCAgJatEgxEVFjWbIbVEN179gd9/vej+4duzcxOiLHFB5uwNix5UzaNBNLdvAiIiIi+2XxT2qpVAqlUoni4uIGXaCoqAhKpRJSKZcFEJH9425QRORouIMXERFR62bxT+qhQ4dCr9fjxRdfRFlZmUXnlJWV4YUXXsBff/2FoUOHNjpIIqKWUrUblDmOshuUQqPA1qytjZo9RA2nUAixdaszZzWQzVTt4GUOd/AiIiKyfxbvKvXyyy9j8+bNSE5OxpEjR/Dkk09i8ODBCAkJQYcOHSAWi1FaWorc3FwolUpkZGRg3bp1yM7OhouLC15++eXmvA8iIqtw5N2grFV0mSzDYrBkL7iDFxERUetmceKmW7duWLNmDWbMmAGVSoVFixbVe47RaET79u3x1VdfoVu3bk0KlIiopSSPT4Y8VY5sXTZ0pTp4ib0Q5BWE5PHJtg6tSeSp8hpFl9VFaqiL1JCnyhtVdJnqJpe71ygGq1YLoFZXJnNYDJZaWnJyYa07eBEREZF9szhxAwAjR47E8ePHsWzZMvz000+4cuVKrX07d+6MCRMmYM6cOfDx8WlyoERELUXqJkX6E+lQaBRQapUIkYS06pk2gGVFl1v7PdoTS4rBcpYDtSSp1Ij09ALu4EVERNQKNShxAwDe3t5ISkpCUlISrl69ij///BN5eXkoLi6Gq6srJBIJwsLC4O/v3xzxEhG1mHBpuMMkMywpuuwo92oPLCkGyw/NZAvh4UzYEBERtTYNTtzczt/fnwkaIqJWoKrosrnaPY5SdNmeVBWDrawpUhOLwRIRERFRQ3CLCyKiNqCq6LI5rb3osj2qKgYL3FmEmMVgiYiIiKhhGj3j5tKlSzh27BguXLgArVaLoqIiuLm5VS+VioyMRGBgoDVjJSKiJnDUosv2isVgiYiIiMgaGpy42bt3L95++21kZmbW2/eee+5BQkICHnjggUYFR0RE1uOIRZftGYvBEhEREZE1NChxs3TpUixZsgRGY+XU78DAQAQHB6NDhw5wcXFBSUkJ8vLycPHiRVy6dAmZmZmYOHEiFixYgAULFjTLDRARUcM4UtHl1oDFYImIiIioKSxO3KSnp2Px4sUQiUT45z//ifj4eHTp0qXW/pcvX8bXX3+N5cuX45133kFERARGjBhhlaCJiIiIiIiIiNoCi4sTf/755xAIBPjqq6/w2muv1Zm0AYAuXbrg9ddfx8qVK2E0GvH55583OVgiIiIiIiIiorbE4sTNiRMnEBgYiEceeaRBFxg/fjwCAwPx22+/NTg4IiIiIiIiIqK2zOLETWFhIby8vBp1ES8vLxQWchcNIiIiIiIiIqKGsDhx07lzZygUCly7dq1BF7hy5QoUCgU6d+7c4OCIiIiIiIiIiNoyixM3Y8eORWlpKZ544glkZWVZdM6ff/6JKVOmoLy8HOPGjWt0kEREREREREREbZHFu0q9/PLL2LRpE06fPo377rsPQ4cOxeDBgxESEoIOHTpAJBKhrKwMubm5UCqVyMjIwMGDB1FRUYHOnTvjxRdfbM77ICIiIiIiIiJyOBYnbry8vPDLL78gPj4ex48fx969e7Fv375a+xuNRgBA//79sXr1akgkkiYHS0RERERERETUllicuAGAgIAApKenY8eOHfjxxx/x66+/Ijs7GwaDobqPUChEUFAQIiMj8eijj2L06NFWD5qIiIiIiIiIqC1oUOKmyqhRozBq1CgAQHl5OfR6PYqKiuDm5gZPT084OzdqWCIiIiIiIiIiuk2TMyzOzs7o2LGjNWIhIiIiIiIiIqLbWLyrFBERERERERERtawWWdP066+/oqysDFFRUS1xOSIiaqMUGgWytFkIlYQiXBpu63CIiIiaRKEQIitLiNBQA8LDDfWfQEQOqUUSN1OmTIFWq4VGo2mJyxERURujKdJAniqHSqeCvkQPTxdPyLxkSB6fDKmb1NbhERERNYhGI4Bc7g6VSgi9XgBPTyNkMgOSkwshlRptHR4RtbAWWypVtT04ERGRtclT5ci8ngl1kRqlhlKoi9TIvJ4Jearc1qERERE1mFzujsxMZ6jVQpSWCqBWC5GZ6QS53N3WoRGRDbDGDRERtWoKjQIqncpsW7YuGwqNomUDIiIiagKFQgiVytzHNAGys4VQKPgRjqitsXip1IYNGxp9kdLS0kafS0REVJcsbRb0JXqzbbpSHZRaJevdEBFRq5GVVbk8yhydTgClUsh6N0RtjMWJm2effRYCgfm/QOpjNBobfS4REVFdQiWh8HTxhLpIbdLmJfZCiCTEBlERERE1TmioAZ6eRqjVpp+fvLyMCAlh0oaorWlwcWKZTAZn54adplQqYTDwLxgiIrK+cGk4ZF4ys4mbIK8gzrYhIqJWJTzcAJnM8N/Eze3JGyOCgri7FFFbZHEGJigoCJcuXcIXX3yByMjIBl0kNDQUeXl5DQ6OiIjIEsnjkyFPlSNblw1dqQ5eYi8EeQUheXyyrUMjIiJqsOTkQsjl7sjOFkKnE8DLqzJpk5xcaOvQiMgGLE7c9O/fH5cuXcLJkycbnLghIiJqTlI3KdKfSIdCo4BSq0SIJIQzbYiIqNWSSo1ITy+AQiGEUilESAhn2hC1ZQ1K3Pz000/47bffmjMeIiKiRguXhjNhQ0REDiM8nAkbImpA4uaee+6Bh4cHLl682OCLPPbYYygoKGjweUREREREREREbZnFiZuoqChcunSpURd59913G3UeEREREREREVFbJrR1AEREREREREREZB4TN0REREREREREdsrqiZtdu3Zhw4YN1h6WiIiIiIiIiKjNsXri5r333sPs2bOtPSwRERERERERUZvDpVJERERERERERHaKiRsiIiIiIiIiIjvFxA0RERERERERkZ1i4oaIiIiIiIiIyE45W3vAXr16wcnJydrDEhERUVtmNMJJdwLON9PhpD0KQXk+jM7tUSG5D+U+Majw6g8IBLaOkoiIiMjqrJ64effdd609JBEREbVVRiNEl9fDJesDCErzICzLrdEsurULBtXnMIo7oiT0RZR1iWUCh4iIiByK1RM3RERERFZRpoV7Zhyc9L9DWK6vtZuwLBcoy4Xr2YUQXd6Awoi1gEjScnESERERNSPWuCEiIiL7U6ZF+4zRcM7NqDNpczthuR7OuYfQPmM0UKZt3viIiIiIWkiLJG5CQ0MhlUpb4lJERETU2hmNcM+MgzD/HAQwNuhUAYwQ5p+De+aTgLFh5xIRERHZoxabcWPkL09ERERkAdHl9XDS/97gpE0VAYxw0p+G6PJ6K0dGRERE1PK4VIqIiIjsh9EIl6wPLF4eVRthuR4uWR9y1g0RERG1ehYXJ87JyWn0RQwGQ6PPJaK2QaFRIEubhVBJKMKl4bYOx6rO5Z7DsevHENkuEn39+9o6HCK75qQ7AUFpnlXGEpTmwkl3AhWSAVYZj8gWFAohsrKECA01IDycv1O3FnzfiMiaLE7c9OnTB4JGbq9pNBobfS4ROTZNkQbyVDlUOhX0JXp4unhC5iVD8vhkSN1ad22s6nvTqqAt0ULyfxLIJI5xb0TNxflmusmW340lLMuF863dTNxQq6TRCCCXu0OlEkKvF8DT0wiZzIDk5EJIpZxJZq/4vhFRc2jQduCsU0NE1iZPlSPzemb1n9VFaqiL1JCnypH+RLoNI2s6k3srVkN9vRXdm9EIJ90JON9Mh5P2KATl+TA6t0eF5D6U+8Sgwqs/wKQ8WZmT9qh1x8s7bNXxiFqKXO6OzMz//aquVgugVlcmBdLTC2wYGdWF7xsRNQeLEzdSqRS5ubn46aefEB5u+TIGo9GIQYMGQavVNiY+InJgCo0CKp3KbFu2LhsKjaLVLptq1fdmNEJ0eT1csj6AoDTPZPaD6NYuGFSfwyjuiJLQF1HWJZYJHLIaQXm+XY9H1BIUCiFUKnOlKAXIzhZCoRBy+Y0d4vtGRM3F4sRN//79sWvXLly+fBnR0dENugiXSRGROVnaLOhLzBcg1ZXqoNQq7Te5UY9We29lWrhnxsFJ/3udxWGFZblAWS5czy6E6PIGFEasBUSSlouTHJbRub1dj0fUErKyKpfZmKPTCaBUMgFgj/i+EVFzsXhXqX79+gEATpw40VyxEFEbEyoJhaeLp9k2L7EXQiQhDR5ToVFga9ZWKDSKpobXJM1xb9ZS62tUpkX7jNFwzs2weEcfYbkezrmH0D5jNFCmtX6wNrLypwuYumgnVv50wdah2K1z55ywb58E5845WXXcCsl91h2vwyCrjkfUEkJDDfD0NF+iwMvLiJAQfvi3R3zfiKi5NGjGjdFoxMmTJxt8kc6dO6N9e/6LFxHVFC4Nh8xLBnWR2qQtyCuoQTNS7K3IsTXvzVrqfI1cO8I9Mw7C/HMQoGH1zAQwQph/Du6ZT6Jw4JZWvWzq2P/lYdR/noDB8yLgqsXmMxIsyAjGjmkbEXl3B1uHZxf+V3hTAK22IyQSI2Qyo9UKb5b7xMCg+twqBYoNoo4o9x7e5HGIWlp4uAEymQFqtQDA7X+nGhEUxF2K7BXfNyJqLgKtVmvRb1nFxcW4cOECRCJRg2rcEFmquLgYOTk5CAgIgKurq63DoRZSlUzI1mVDV6qDl9gLQV5BDU64xGyMqVEIuEqEX4TNCgHfnijRFevg5epl02RSXa/Rvqh4uJ5daPFMG3MMzp4o7rkYZQFxTQnTpjrOHwWD/x3FcY2A8Np9yF26wzZB2ZmYmHY1Cm9WMiIiosI6hTeNRrTfFwGngqwmD1XRrivy7z/WqpOJ1PLs5feRqiRpdrYQOp0AXl6VH/65O5F9s9f3zV6eayJrayvPtsUzblxdXdG7d+/mjIWI2iCpmxTpT6RDoVFAqVUiRBLS4Nko9loIuOreTl09hWPKY4gMiURf/74tHgdQ32ukguD8kiYlbYDKZVMuWR+22mLFK3+6UDnT5k4CwOB5ESt/uoC/Twhr+cDsSIsU3hQIUBL6klUSiSWhL7bKZ5EIAKRSI9LTC6BQCKFUChESwhkbrQHfNyJqDg3aDpyIqLmES8MbnVyx90LA3Tt2h3uBOwI6Btgshrpeo64CLQSlxVa5jqA0F066E6iQDLDKeC3pwP9VLo8yy1WLg2dVbT5x01KFN8u6xEJ0eT0EuRkNXroHAEYIUOHZpzKJSNTKhYfzg39rxPeNiKzJ4uLERET2yp4LAduLul6jR9qL4WqwzpbJwrJcON/abZWxWtrQu4OBYon5xmIJhvSUtWQ4dqnFCm8KBCiMWAdD++4womEzZowQwNC+e+VOZ5xtQ0RERA7AosTN5cuXrXrRq1evWnU8ImrbqgoBm2OrQsD2pq7XKLqddSdfOuUdtup4LeXvE8Ig1AfDZIKHERDqg9v8bBvgf4U3zb1IVi+8KZIgf/B2lHccDIOz+aTjncqFnriJITjRaSe3pyciIiKHYVHiJiIiAq+88gpu3rzZpIv9/PPPGDx4ML799tsmjUNEdKfk8cmI8IuAt5s3xE5ieLt5I8IvAsnjk20dmt2o7TXqL7VuQkJQbp3ZO7awY9pGCK/dB+T7AOViIN8Hwmv3Yce0jbYOzW4kJxciIqICnTpVQCQyoFOnCkREVCA5udD6FxNJUDjwZxT3XIyKdl1hEHU0263CuSNUud3wwrcfITB+L8aM74yYmHbQaDjjhoiIiFo/i/6ZdcCAAfjiiy+wevVqjB49GlOmTMGIESPg7Fz/6RcvXsR3332HjRs3Ijs7G+3bt0ffvrYpzklEjssaRY4dXW2vkfOvE616HaNze6uO15Ii7+6A3KU7sPKnCzh4VoUhvWScaXOHqsKbp06V4dixPERGdkDfvqLmu6BAgLKAOJR1iYWT7gScb+2CU94RCMrzYXRuj4oOg/CPf4/Fmq0DUbX9rloNqNWVO7tYZacrIiIiIhuyKHGzbds2pKam4vXXX0dqaio2b94MFxcX9OnTB/3794e/vz8kEglcXV2Rl5eH3Nxc/PHHHzh+/DiuXbsGo9EIoVCIJ598Eq+99hq8vb2b+76IqI1qSpHjtuLO16hCch9Et3ZZbfzrLl1h2cIW+/X3CWFM2NSje/cKuLvrEBDgCaAZEzdVBAJUSAaYFL5WKITYdrQdYFILx4o7XRERERHZkMWFDcaPH49x48Zhy5Yt+Oqrr5CRkYFff/0Vx44dM9vfaKxc/96xY0c8+eSTmD59OoKCgqwTNRERWU25TwwMqs8hLMtt8ljqCuCsUxcMtEJcRJZoqZ2uiIiIiGylQRUpnZ2d8eijj+LRRx/FtWvXcODAAWRkZCA7OxtqtRrFxcWQSqXw9vZG3759MWTIEERERFi0pIqIiGyjwqs/jOIOgBUSN1qDEBK/GCtEZVsKjQJZ2iyESkI5g8vOVe10pVabJm+sutMVtRnnzjnh2DEJIiOdwNX9RERkDxqdUbnrrrvw+OOP4/HHH7dmPERE1NIEApSEvgTXswshLNc3ehhtBbC2PBAvduphxeBalqZIA3mqHCqdCvoSPTxdPCHzkiF5fDKkblJbh0dmVO10VZm4uT150ww7XZFD02gq6yKpVAJotR0hkRghkxmRnFwIqfTOndSIiIhajkW7ShERkWMr6xKLCs/eMJrUCbFMhRH40+iBqWPTrRxZy5KnypF5PRPqIjVKDaVQF6mReT0T8lS5rUOjOlTtdOXtbYBYbIS3t6H5droihyWXuyMz0xlqtRPKy4VQq52QmekEudzd1qEREVEbxzVMREQECAQojFiH9hmjIcw/BwEs/9dlA4AS92CEDd0DiCTNFmJzU2gUUOlUZtuyddlQaBRcNmWnqna6UiiEUCqFCAnhTBtqGIVCCJXK3L9nssg1ERHZHmfcEBFRJZEE+YO3o7zjYBicLdsXyuDsiYqOQ1DWypM2AJClzYK+xPxSMV2pDkqtsoUjooYKDzdg7NhyfsCmBrOkyDUREZGt8KcQERH9j0iCwoE/o7jnYlS06wqDqKPZbgZRR1S064rinotROHBLq0/aAECoJBSeLuYTVl5iL4RIQlo4IiJqKVVFrs1hkWsiIrI1LpUiIqKaBAKUBcShrEssnHQn4HxrF5zyjkBQng+jc3tUdBiEcu/hqPDqDwgaVxPHHoVLwyHzkkFdpDZpC/IK4jIpIgfGItdERGTPmLghIiLzBAJUSAagQjLA1pG0mOTxyZCnypGty4auVAcvsReCvIKQPD7Z1qERUTNLTi6s3lVKpxPAy+t/u0oRERHZEhM3RERE/yV1kyL9iXQoNAootUqESEI404aojagqcn3qVBmOHctDZGQH9O0rsnVYRERETNwQERHdKVwazoQNURvVvXsF3N11CAjwBMDEDRER2R6LExMRERERERER2SmrzLi5ceMGDh06hCtXrqCwsBALFiywxrBERERERERERG1akxI3BQUFWLhwITZs2ICKiorq47cnbqZNm4aff/4Z+/btQ69evZpyOSIiIiIiIiKiNqXRS6VKS0vx2GOPYe3atXBxcUFUVBSkUqlJvyeffBIGgwHbtm1rUqBERERERERERG1NoxM3q1atwq+//ooBAwbg119/xZYtW9C1a1eTftHR0RCJRNizZ0+TAiUiIiIiIiIiamsanbj5/vvv4eTkhC+//BL+/v619nNxcYFMJsOFCxcaeykiIiIiIiIiojap0YmbCxcuIDAwECEhIfX2lUgk0Ol0jb0UEREREREREVGb1OjETUVFBdzc3Czqm5+fb3FfIiIiIiIiIiKq1OjEjb+/P1QqFcrLy+vsp9PpcOHCBchkssZeioiIiIiIiIioTWp04ub+++9HUVERvv766zr7ffLJJ6ioqMCIESMaeykiIiIiIiIiojap0Ymb5557DmKxGK+//jo+//xzFBQU1GjXarVISkrCBx98gHbt2mHmzJlNDpaIiIiIiIiIqC1pdOImODgYH3/8MSoqKpCQkIDg4GCcPHkSANCnTx907doVH3zwAZycnLB8+XLcdddd1oqZiIiIiIiIiKhNaHTiBgAef/xxbNmyBffeey/KyspQXFwMo9GInJwcVFRUoG/fvvjpp58wfvx4a8VLdkihEGLrVmcoFE16nIioHgqNAluztkKhUdg6FCIiIiIiaiHOTR1g4MCB2L59O65du4YzZ85Aq9WiXbt26NmzJwsSOziNRgC53B0qlRB6vQCenkbIZAYkJxdCKjXaOjwih6Ep0kD+/+zdfXxT5f3/8fc5aQuk0BZKQRBsaAUiiigW7513TBRU1OnqvfNmvw11U9kUp3NzmxOdOvGh4ub9nHeZ++q8QZ0WJt4wgW4TcCwgLa3cqaTQ1DZA25zz+6OkUppCm6bNSfJ6Ph48Ns85ufI56XVOkk+u63O9WqqqYJXqdtQpp0+OPLke+ab7lN8vP9HhAQAAAOhBMSduzjjjDPXp00fPPfec+vTpo2HDhjEdKs2UlrpVXv5NFwoEDAUCLcmcsrKGPTwSQFeUvlqq8i/KW/87sC2gwLaASl8tVdn5ZQmMDAAAAEBPi3luy5IlS7R582b16dMnnvEgSfj9pqqqonUfQ9XVJtOmgDjx1/hVFayKuq86WM20KQAAACDFxfztep999lE4HI5nLHFj27Zee+01nX766Ro7dqyGDRumkpISXX/99aqqqmp3fF1dnW655RYddNBBGjJkiMaPH6/bbrtN9fX1vR98kqioaJkeFU0waKiyksQNEA8VtRWq21EXdV+wMajK2spejggAAABAb4r52/XkyZO1atUqbd68OZ7xxMXPf/5zXXrppVqzZo2mTZum//f//p8KCwv1pz/9Sccdd5xWrlzZemxDQ4OmTZumuXPnasyYMbr66qs1evRoPfjggzrzzDO1ffv2BJ6JcxUXW8rJiV7HJjfXVlGR1csRAampOK9YOX1you7LzcpVUV5RL0cEAAAAoDfFnLi56aablJubqx/+8If6+uuv4xlTt3z55Zd65JFHNHLkSC1evFi///3v9atf/Ur/93//pzvuuENff/21Hn744dbjH3jgAa1YsULXX3+9Xn75Zd1+++16+eWXdf311+vf//635s6dm8CzcS6v15LHY0naPXljq7DQktdL4gaIB2++V55cT9R9hbmF8uZ7ezcgAAAAAL0q5uLECxYs0Pe+9z3NmTNHhx12mKZPny6v1yu3293hYy644IJYn67TPv/8c1mWpSOPPFK5ublt9p166qm69dZbFQgEJLVMqfrzn/+s/v3768Ybb2xz7I033qjHH39czzzzjGbOnNnjcScjny+k0lK3qqtNBYOGcnNbkjY+XyjRoQEpxTfdp9JXS1UdrFawMajcrFwV5hbKN92X6NAAAAAA9LCYEzdXX321DMOQbdvavHmznnjiib0+pjcSN8XFxcrKytLHH3+suro65eR8M8Xg7bffliQdf/zxkqSKigpt2rRJJ598srKzs9u0k52drSOOOELz58/X+vXrNWLEiD0+bzpOqcrOlt54Y5tWrXKpqipDHk+zxo5tqXsUy8vR2NjY5n+BVNHdvp1tZOuNs97Qqi2rVFVXJU+OR2MHjZWUnvceOAP3bKQq+jZSEf0aqSpZ+3bfvn27dHzMiZujjz5ahhG9OG0iDRo0SL/85S/185//XIcffrimTp2qAQMG6NNPP9X777+vq666Sv/v//0/SS2JG0kqKopeI6KoqEjz589XRUXFXhM3GzdudGyx5p7mdkvjxrX8/3Xrut/el19+2f1GAAfqbt92y61xrnFSg7SuIQ4XGxAH3LORqujbSEX0a6SqZOrbLperwxxER2JO3MybNy/Wh/a4a665RsOHD9ePf/xjPfnkk63bjzrqKJ177rnKyGg57bq6lpVadp9SFREZrRM5bk+GDx/e3bDTXmNjo7788ksNHTpUWVlZiQ4HiBv6NlIR/Rqpir6NVES/RqpKl74dc+LGye6++27de++9uuWWW/Td735Xubm5WrFihW655RadfvrpeuaZZzR16tS4PmdXhzqhY1lZWbyecAR/jV8VtRUqziuOSxFg+jZSEf0aqYq+nTz8flMVFaaKi1kgY2/o10hVqd63Uy5x895772n27Nm6+uqrdcMNN7RuP+qoo/Tiiy/qkEMO0c9//nNNnTq1dURNMBiM2lZkpM2udXIApL6abTUqfbVUVcEq1e2oU06fHHlyPfJN9ym/X36iwwMAAJJqagyVlrpVVWWqrs5QTo4tj6dloYz8/N1XPgWA5NXtxI1t23rjjTf0zjvv6LPPPtPXX3+tAQMGaMyYMTrllFM0bdq0Xq2F8+6770qSjjvuuHb7hg4dqtGjR2v58uWqr69XcXGxJKmysjJqW5HtkeMApIfSV0tV/kV5638HtgUU2BZQ6aulKju/LIGRAQCAiNJSt8rLv/k6EwgYCgRakjllZQ0JjAwA4qtbiZuqqipdeuml+vTTTyW1JHEilixZomeffVbjx4/Xn/70J3k8nm4F2lmRatKRJb93V1NTI9M0lZmZqeLiYg0bNkyLFy9WQ0NDm5WlGhoatHjxYhUWFu61MDGA1OGv8asqWBV1X3WwWv4af1ymTQEAgNj5/aaqqswoewxVV5vy+02mTQFIGdHudp1SV1en6dOna8WKFTJNU9OmTdNNN92k3//+97rppps0bdo0maap5cuX6+yzz+5Ugd94OPLIIyVJc+fObTcF6sknn9SGDRt0+OGHq0+fPjIMQ5dcconq6+t1zz33tDn2nnvuUX19vS677LJeiRuAM1TUVqhuR/T7VbAxqMra6CP0AABA76moaJkeFU0waKiyMuavOQDgODGPuHn44Yf1+eefa/z48XrqqaeiTieqrKzU9773PX366aeaO3eubr755m4F2xlnnXWWnnjiCS1atEglJSU67bTTlJubq2XLlun9999Xv3799Nvf/rb1+Ouuu05vvvmm5syZo+XLl2vChAlatmyZFixYoIkTJ2rGjBk9HjOA+BcCjlVxXrFy+uQosK39qL3crFwV5XVt6T5J+vvav+sfa/6hE5tP1PQDpscjzJTz2N8+0wf/XavjDhyl7581OtHhxFW8imbG6xpxyrXmZHH7m6VwwdRUPjckh+JiSzk5tgKB9smb3FxbRUX0SwCpw6itrY2pctcxxxyjVatWqby8fI/ToKqqqnTYYYfJ6/Xqo48+ijXOLtmxY4fmzp2rV155RWvWrFFjY6OGDBmiY489Vj/5yU80duzYNscHg0Hdddddev3111uXEjvrrLM0a9YsDRgwoFdihrR9+3atW7dOI0eOTOmK4GjLiYWAJ784uU2Nm4iSfUq6VOPmsy2f6YQXTlCoKSRbtgwZcme69d4F72n0oNRKTsRq6X+3asqfzpeVs1bqWyttz5NZN0p/v+xFTTpwYKLD65Z4Fc2M1zUS72stFe/ZcfubpXDB1FQ+t4hU7NupavLkbJWXuyTtmryxVVISpsbNbujXSFXp0rdjTtyMGDFChYWFnUrGHHPMMaqurtb69etjeSqkiXS56NBWvJIk8RT5glsdrFawMajcrFwV5hZ2+Qvuvg/vq4am9h8cszOzteGaDfEMOWkNummKrOGL2260JXPTEdryu78nJqg4aflCsfvA1q5/oYjXNRLvay0V79lx+5vFqR0nSuVzi0jFvp2qIonE6mpTwaCh3FxbhYWplUiMF/o1UlW69O2Yp0rZti3T7NzcUcMw2hQuBgDJuYWA8/vlq+z8Mvlr/KqsrVRRXlGX43ir4i2FmkJR94WaQnqr4i2dVnxaPMJNWo/97bOWkTa7MyQrZ60e+9tnSTttKl5FM+N1jTj1WnOSuP3NUrhgaiqfG5JTfr6tsrIG+f2mKitNFRUxdQ9Aaoq5aldhYaH8fr82bty4x+PWr18vv9+vwsLCWJ8KQIpyeiFgb75XU4unxvSFdskXS2QresLalh115EO6+eC/O6dHRdO3Vh+urOrNcOIqXkUz43WNOP1ac4K4/c1SuGBqKp8bkpvXa2nq1GaSNgBSVszvsKeeeqqam5t1+eWX64svvoh6zKZNm3TFFVfIsixNnTo15iABpKZIIeBoYi0E7BSH73O4DEX/gmPIUMk+Jb0ckfMcd+AoaXte9J3b83TsOE9vhhNXkaKZ0XSlaGa8rpFUvtbiJW5/szi140SpfG4AADhZzFOlfvSjH+nFF1/U0qVLdcghh+iss87SuHHjNGTIEH311VdauXKl/va3v2nHjh0aPny4rr322njGDaCbnLAiiDffK0+uJ+oKToW5hTGNdHHKijmnFZ8md6Y7ao0bd6Y7odOknPIaff+s0Zq1aJSs7K92ryspsy65V5fyei15PNbO1U7anlxhYeevuXhdIz1xraWauP3N4tSOE/XEuTnhvQgAAKeLuTixJPn9fl1yySVas2aNDKPtL8uRmjajR4/WM888I6+XD4XYs3QpLJVoTlsRJF6FgJ24OpXTVpVy4muUDqtKdbdoZryvke62E5GK9+y4/c1SuGBqvF8jp7wX7SoV+zZAv0aqSpe+3a3EjSQ1NjbqlVde0TvvvKPPPvtM9fX16t+/v8aMGaNTTjlFZ599tjIzM+MVL1JYulx0iebUFUG6UwhYcubqVBGv/u9VvVfxnk4oPkHTD5iesDic/Bo99rfP9OHKKh07zpPUI22iiVfRzO5eI/FuJ5Xv2XH7m6VwwdTunptT34uk1O7bSF/0a6SqdOnb3U7cAPGSLhddIvn9pk4/PVuBQPvyVgUFll5/vSEpv1z4a/w6/a+nR50GUtCvQK+f+3pCp4I4oW87/TVC8nFCv0Zycvp7EX0bqYh+jVSVLn2b8v9AGknVFUFYMWfveI0AOEWqvhcBANBTYn5n/Oqrr/TCCy9o8eLFezzu448/1gsvvKDNmzfH+lQA4iRVVwRhxZy94zUC4BSp+l4EAEBPiTlx86c//UnXXHONqqur93jc559/rmuuuUbPPvtsrE8FIE4iK4JIu39gTu7VTrz5XnmyR0Q7LXmy92UKkFpeoxEDRkTdt+8AXiMAvSdV34sAAOgpMSdu3nnnHWVmZmr69D0X2pw+fboyMjL09ttvx/pUAOLI5wuppCSsggJLWVm2CgoslZSE5fOFEh1at7z+nK0j1ktD6qWs5pb/PWK99NpzlPGKsNt9SdrzdgDoKan6XgQAQE/YvZx/p1VXV2vEiBHq06fPHo/r06ePRo4cudeROQB6R36+rbKyhpRa7cT0+zXksw36+J/SygJpzSBp/y3SuM2SVbBRDX6/LG96jyjx1/i14esNUfdt/Hqj/DV+Rt0A6DWp+F4EAEBPiTlxEwwGNXLkyE4dm5eXp/Xr18f6VAB6gNebOh+SzYoKGXUthXfHbW75F2EEgzIrK9M+cdOZ4sQkbgD0tlR6LwIAoKfEPFVq0KBBnR5FU1VVpby8vFifCgD2yCoulp0TvfCunZsrq4jCuxQnBgAAAJJTzImbQw45RFu2bNHrr7++x+PeeOMNbdmyRYccckisTwUAe2R5vbI8nmi1iWUVFqb9aBtpZwHnXE/UfYW5hYy2AQBAkt9vat68DPn9LEsPwDliviNddNFFsm1bP/7xj/Xhhx9GPeajjz7Sj3/8YxmGoQsvvDDmIAFgb0I+n8IlJbIKCmRnZckqKFC4pEQhny/RoTnGI6c8ouzMbBkyJEmGDGVnZuuRUx5JcGQAACRWTY2hyZOzdfrp2br8crdOPz1bkydnq6bGSHRoABB7jZvTTz9dp512mt566y2deeaZOvzww3X44YcrNzdXwWBQS5Ys0ZIlS2TbtqZOnbrX1acAoDvs/Hw1lJXJ9PtbatoUFTHSZjcz3pmhhqaG1v+2ZauhqUEz3pmhsvPLEhgZAACJVVrqVnn5N1+NAgFDgYCh0lK3ysoa9vBIAOh5MSduJOnJJ5/UDTfcoBdffFGLFy/WkiVLWvfZti3DMHTRRRfp3nvv7XagANAZltdLwiYKf41fVcGqqPuqg9WsKgUASFt+v6mqqmgTEQxVV5vy+02KaANIqG4lbvr27atHHnlE1157rV5//XWtXLlSX3/9tQYMGKADDzxQZ555pg444IB4xQoAiBGrSgEAEF1Fham6uuhTooJBQ5WVJG4AJFa3EjcRBx54oA488MB4NIUk5PebqqgwVVzMkp6AU0VWlQpsC7Tbl0qrSvlr/KqorVBxXjGJKABApxQXW8rJsRUItE/e5ObaKiri8y2AxIpL4gbpqaamZd5vVVXLrxQ5ObY8Hks+X0j5+buv7wMgkSKrSkVL3KTCqlI122pU+mqpqoJVqttRp5w+OfLkeuSb7lN+v/xEhwcAcDCv15LHY+1M3OyavLFVWMgPkwASL66Jm2AwqKefflpLly5VU1OTiouLdckllzBdKkVRxA1ILr7pPpW+WqrqYLWCjUHlZuWqMLdQvunJv/JW6aulKv+ivPW/A9sCCmwLqPTVUgovAwD2yucLqbTUrepqU8GgodzclqSNzxdKdGgA0PnEzSeffKJf/epXGjVqlH7/+9+3219VVaUzzjhDGzZskPRNceLHH39cDz74oEpLS+MXNRKOIm5A8snvl6+y88vkr/GrsrZSRXlFST/SRqLwMgCg+/LzbZWVNcjvN1VZaaqoiJE2AJwj2jfvqObPn6+FCxdq1KhRUff/4Ac/0Pr162Xbtg4++GCdc845GjlypJqamnT99dfr888/j1vQSLzOFHED4EzefK+mFk9NmWRGZwovAwDQGV6vpalTm0naAHCUTn+7/vjjjyVJZ5xxRtR9S5YskWEY+sUvfqH33ntPTzzxhMrLy3XKKadox44d+tOf/hS/qJFwkSJu0cRaxG3VKpcWLszTqlWu7oYHxIW/xq95FfPkr/EnOpS4SrXzihRejiaVCi8j+fj9pubNy5Dfz48ZAAAgdp2eKrV27VoVFBTI4/G02/fWW29JkkaNGqXrr7++dXtmZqZ++ctf6p133tHChQt12223dTtgOEM8i7h9U+TYUG3tIOXl2fJ4bIocI2FStdBtqp5XqhdeRvKheD8AAIinTv8EFAgEtO+++0bdFxltM2XKFBlG2+kz48aN0z777KPKSoaqpxqfL6SSkrAKCixlZdkqKLBUUhLuchG3SJHjQMCl5mZTgYBL5eUulZa6eyhyYM8ihW4D2wJqtBoV2BZQ+RflKn01uWt1pep5SS2Fl0v2KVFBvwJlubJU0K9AJfuUpEThZSSfb97XTDU2GgoETN7XAABAzDo94iYUCqmxsbHddtu29emnn0qSjjjiiKiP3WeffVqPQeqIRxE3ihzDaVK10G2qnldEqhZeRvLhfQ0AAMRbp0fc5ObmthYf3tX//vc/1dfXS5IOOeSQqI9tampSZmZm7FHC0bpTxI0ix3CaVC10m6rntbtUK7yM5MP7GgAAiLdOf3o46KCDVFdX11rPJuK1116TJA0fPlyFhYVRH/v5559r6NCh3QgTqaonihwD3ZGqhW5T9bwAp+F9DQAAxFunEzfTp0+XbduaOXOmXnvtNa1Zs0Z//vOf9dBDD8kwDJ1zzjlRH/ff//5XX3/9tcaOHRu3oJE6IkWOpd0/5Ha9yDG6xvT7lTFvnkx/aqwsFC+RQrfRJLrQbXdWg3LyeQGphPc1AAAQb52ucXPxxRfrySef1IoVK/S9732vdbtt28rLy9M111wT9XEvv/yyDMPQ8ccf3+1gkZp8vlDrqlLBoKHc3G9WlUL8GTU1cpeWyqyqklFXJzsnR5bHo5DPJzs/eVcWiiffdJ9KXy1VdbBawcagcrNyVZhbmLBCt/FaDcpp5wWkqsj7WnW12fq+Vlho8b4GAABiYtTW1nZ6XcpAIKBrr71W77zzTmutG4/Hoz/84Q9RCxOHQiGNHz9eW7du1T//+U9G3WCPli1r0tKlWzVp0kBNmEBNpJ6SPXmyMsrL22yzJYVLStRQVpaYoBwqXoVut2/frnXr1mnkyJHq27dvlx8/+cXJKv+ivN32kn1KVHZ+1/9mFPBFPHS3X6eD7hTvR+LQt5GK6NdIVenStzs94kaSBg8erBdffFFfffWVqqurNWDAAHm9e/7Q/8Ybb8gwDJI22KuxY8Nyu4MaOTJHEombnmD6/TKrqtptNySZ1dUy/X5Ze7mm04k335vwxEZPrAblhPMC0oHXS8IGAAB0X5cSNxFDhgzRkCFD9nqc2+3WAQccEMtTAOgBZkWFjLroKwsZwaDMykoSNw7TmdWgSMIAAAAAqYs1KYE0YhUXy86JvrKQnZsrq4iVhZyG1aAQ0Z3i1D3Rzqotq7Twi4VatWVVt9pxIr/f1Lx5GfL7+ZjUEV4joHdwrQGQYhxxAyA5WV6vLI9HRiAgY5fttiSrsJDRNg4UWQ0qsC3Qbh+rQaWHeBWnjns7tVWq3VGrvP/myZPX9XacqKbG2Fks31RdnaGcHFseT0tR4fz8TpcETGm8RkDv4FoDsCtSt0CaCfl8CpeUyCookJ2VJaugQOGSEoV8rCzkVL7pPpXsU6KCfgXKcmWpoF+BSvYpYTWoNFH6aqnKvyhXYFtAjVajAtsCKv+iXKWvlia2ne0BNdvNCmyPrR0nKi11q7w8Q4GAqcZGQ4GAqfJyl0pL3YkOzTF4jYDewbUGYFeMuAHSjJ2fr4ayspZCxZWVsoqKGGnjcPn98lV2fhmrQaWheBWndlo7TuT3m6qqivZ7lqHqalN+v5n2hYZ5jYDewbUGYHeMuAHSlOX1qnnqVJI2ScSb79XU4qlJ+8UYXdeZ4tTJ2I4TVVS0TEeIJhg0VFnJRyZeI6B3cK0B2B1XPQAADhWv4tROa8eJiost5eRErxuRm2urqIhft3mNgN7BtQZgdyRugF5g+v3KmDdPpr97q7ggvcVrNSAkj0hx6mi6Upzaae04kddryeOx1FKufVe2CgstpiWI1wjoLVxrAHZHjRugBxk1NXKXlsqsqpJRVyc7J0eWx6OQzyc7P7lXX0HviddqQEhOvuk+lb5aqupgtYKNQeVm5aowt7DLxanj3U5VsErB7UHl9s1t7Y/JzucLqbTUrepqU8Ggodzcli9JPl8o0aE5Bq8R0Du41gDsyqitrWU9OTjC9u3btW7dOo0cOVJ9+/ZNdDhxkT15sjLKy9tssyWFS0rUUFaWmKDQ67rbtye/OFnlX5S3216yT4nKzqcfpYt4FaeOVzvLNi7T0sqlmlQ0SROGT4i5HSfy+01VVpoqKuKX7Y6k8muUip9HkLzida3Rr5Gq0qVvxzzi5owzzuj0sS6XSwMGDFBhYaGOPvpoTZkyRS6XK9anBpKC6ffLrKpqt92QZFZXy/T7KQyMvUrlVXzQNd58b1z+1vFqZ+ygsXI3uDVy0Mhut+U0Xm/qJSPijdcI6B1cawCkbiRuPvzwQ0mSYbRUPLft9gN3dt9nGIbmzp0rj8ejJ554QoceemisTw84nllRIaMu+uorRjDYshQ3iRvsRWdW8SFxAwAAAKSumBM3Dz/8sKqrq3X//ferb9++mjp1qg4++GD1799f9fX1WrFihebNm6cdO3bohhtuUH5+vlavXq2//e1vWrt2rc4991x98MEHGj58eDzPB3AMq7hYdk6OjECg3T47N1dWUfKuvoLeE1nFJ7CtfT9K9lV8kBj+Gr8qaitUnFfcraSfa9Uq5S1dKtekSdKE1JoqBQAA4CQxJ25OOOEEfetb31JJSYmeeeYZDR48uN0xNTU1uuSSS/T4449r4cKF+v73v6/bbrtNF1xwgf75z3/q4Ycf1m9/+9tunQDgVJbXK8vjkREIyNhluy3JKixktA06JbKKT7TETbKv4oPeFa8i15Gi60ZVlQbV1srOy5NN0XUAAIAeE/Ny4LNnz9bXX3+tp59+OmrSRpLy8/P11FNPqa6uTrNnz5Yk5eTk6OGHH5YkzZ8/P9anB5JCyOdTuKREVkGB7KwsWQUFCpeUKORL/tVX0Ht8030q2adEBf0KlOXKUkG/ApXsU5ISq/ig95S+WqryL8oV2BZQo9WowLaAyr8oV+mrpV1qx11aqozycrkCAZnNzXIFAnKVl8td2rV2AAAA0Dkxj7iZP3++DjjgAA0ZMmSPxw0dOlQHHHCAFixY0LrN4/GoqKhI69ati/XpgaRg5+eroayspVBxZaWsoiJG2qDL8vvlq+z8sritBoT0E68i1xRdBwAA6H0xJ262bNmi3NzcTh3b2NioLVu2tNk2cOBAbdiwIdanB5KK5fXyZQbdFq/VgJB+4lXkmqLrAAAAvS/mqVLDhg3TqlWrtHLlyj0et3LlSq1atUrDhg1rsz0QCGjQoEGxPj0AAOikSJHraLpS5DpSdD0aiq4DAAD0jJgTN2eeeaZs29YFF1ygJUuWRD1m6dKluvDCCyVJ06dPb92+ceNGVVVVqbi4ONanBwAAnRQpch1NV4pcR4qu27ttp+g6AABAz4l5qtRPf/pT/f3vf9eqVat06qmnavTo0Ro/fnzrcuCffvqpVq9eLdu25fV69dOf/rT1sU8//bQk6eSTT+72CQAAgL3zTfep9NVSVQerFWwMKjcrV4W5hV0uch3y+VpXlTKCQdm5ua2rSgEAACD+jNra2t1/OOu0LVu2aObMmXrttddk2+2bMQxDZ511lu69994206K2b9+ucDisfv36yTRjHvSDFLN9+3atW7dOI0eOVN++fRMdDhA39G04SbyKXDctW6atS5dq4KRJypwwIY4RAonFPRupiH6NVJUufTvmETeSNGjQID399NOqqqrSggUL9Nlnn6mhoUHZ2dkaPXq0TjrpJHk8nnaPS+UXFAAAJ4tXkevw2LEKut3KGTlSmXGICwAAANF1K3ET4fF4dMUVV8SjKQAAAAAAAOzEPCUAjmD6/cqYN0+m35/oUABH4hoBescql0sL8/K0yuXqVjt+09S8jAz5KQsAAOimuIy4kaTa2lrV19dHrXUTMXLkyHg9HYAUYdTUyF1aKrOqSkZdneycHFk7C53a+fmJDg9IOK4RoHfUGIZK3W5VGYZqBw1Snm3LY9vyhULK38Pn2w7bMU3VGYZybFsey+pyOwAARHQrcbN+/Xrdeeedevvtt1VbW7vHYw3DUE1NTXeeDkAKcpeWKqO8vPW/jUBARiAgd2mpGsrKEhgZ4AxcI0DvKHW7VZ7xzUfjgKSAbavU7VZZQ0Ps7RiGAjuTOV1pBwCAiJgTN5WVlTrllFO0ZcuWPY6yiejMMQDSi+n3y6yqarfdkGRWV8v0+2V5u19EFUhWXCNA7/CbpqqiTWkyDFWbpvymKa9l9Vo7AADsKuZJt3fccYdqamq0//7765lnnpHf79eWLVu0devWDv8BwK7MigoZdXVR9xnBoMzKyl6OCHAWrhGgd1TsnNYUTdAwVNnJOjXxagcAgF3FPOLm/fffV2Zmpv76179qv/32i2dMANKEVVwsOydHRiDQbp+dmyurqCgBUQHOwTUC9I5iy1KObSsQJemSa9sq6uQomXi1AwDArmJO+9fX12v//fcnaQMgZpbXK8vj0e4TKW1JVmEhU0CQ9rhGgN7htSx5LEvafWq/bavQsjo9vSle7QAAsKuYEzcjR46kbg2Abgv5fAqXlMgqKJCdlSWroEDhkhKFfL5EhwY4AtcI0Dt8oZBKwmENDoeVaVkaHA6rJByWLxSKqZ0Cy1KWbavAsmJqBwCAiJinSp199tm67777VFVVJY/HE8eQAKQTOz9fDWVlLUVYKytlFRUxigDYBdcI0DvybVtlDQ1a1tSkpVu3atLAgZqQmRlzO37TVKVpqoiRNgCAboo5cTNz5ky99dZbuuKKK/TUU0+psLAwnnEBSDOW18uXUWAPuEaA3jE2HJY7GNTInBwphsRNhJeEDQAgTmJO3DzwwAP61re+pccee0xHHnmkTjrpJO2///5yu90dPmbWrFmxPh0AAAAAAEDaiTlxc9ddd8kwDNm2raamJr355psyOlj+0LZtGYZB4sZhTL9fZkWFrOLibv2KG692AAAAYuU3TVWYpooZ6QKkFa59pIOYEzfnn39+h4kaOJtRUyN3aanMqioZdXWyc3JkeTwK+Xyy8/N7vR0AAIBY1RiGSt1uVZmm6gxDObYtj2XJFwopn4U0gJTFtY90EnPi5pFHHolnHOhF7tJSZZSXt/63EQjICATkLi1VQ1lZr7cDAAAQq1K3W+UZ33ykDRiGAju/0JU1NCQwMgA9iWsf6STm5cCRnEy/X2ZVVbvthiSzulqm39+r7QAAAMTKb5qqMqN8nDUMVZum/NH2AUh6XPtIN/ToNGNWVMioq4u6zwgGZVZW9mo7AAAAsarYOUUimqBhqJIvb0BK4tpHuqFHpxmruFh2Tk7UfXZurqyiol5tBwDQOabfr4x58xjRCOyi2LKU00Eti1zbVhGFSoGUxLWPdNOpGjeDBg2SJI0ZM0Yff/xxm22dZRiGampquhge4s3yemV5PC31aHbZbkuyCgs7vSqU5fXKGjEiejv77svqUgAQJxSCBzrmtSx5LEsBw5B2/fXdtlXICjNAyuLaR7rp1Igb27Zb/0Xb1pl/FhePY4R8PoVLSmQVFMjOypJVUKBwSYlCPl/XGrJtRR2gSBV3AIibSCF4MxCQ0dgoMxCQq7xc7tLSRIcGOIIvFFJJOKwCy1KWbavAslQSDssXCiU6NAA9iGsf6aRTI26WLVsmScrMzGy3DcnHzs9XQ1lZS4HhykpZRUVdHiFj+v0yN2xot92QZG7cKNPvZ9QNAHRTZwrBc69Fusu3bZU1NMhvmqo0TRXxazuQFrj2kU46lbjZb7/9OrUNycXyemP+wN+Z4sR8mQCA7uFeC3Sely9tQFri2kc6oDgxYkJxYgDoedxrAQAAQOIGMYkUOd69mk1XixwDADrGvRaAE/lNU/MyMuRnyWUgqnhdI29lZOhXffrorYxOTZTpcVz7idOpHnD33XfH5clmzZoVl3bgDNseeUT9TzhBdijUUpDYMCS3W9seeSTRoQFAygj5fC2rSlVXywgGW0baFBZ2vaA8AHRTjWGo1O1WlWmqzjCUY9vyWJZ8oZDyWZwCiNs18plp6oT+/RVSy481hiS3pPfq6zU6AdPCuPYTr1OJm7vuukuGEXX9oE6xbVuGYZC4STH9ZsyQ0dDwzQbblt3QoH4zZqihrCxxgQFAColHQXkAiIdSt1vlu/zyHzAMBXZ+oSvb9TMhkKbidY2c0L+/Gnb5/m1LarBtndC/vzZ0UPuuJ3HtJ16nEjfnn39+1MRNU1OTXn31VTU1NWno0KEaPXq0hgwZoq+++kpr1qzRF198oaysLJ155pltVqRC8mOlEwDoXd0pKA8A3eU3TVVFmx5hGKo2TflNkwKxSGvxukbeyshQ1AXNDUMh29ZbGRk6rbm52/F2Fte+M3QqcfNIlKkv27dv1xlnnKHc3FzNnj1b55xzjsxd/qCWZenll1/WLbfcourqar3++uvxixoJx0onAAAA6aNi5xSJaIKGoUq+vCHNxesaWeJytattF2FLKne5ejVxw7XvDDFXFbr33nv1r3/9Sy+88ILOPffcNkkbSTJNU+eee66ee+45LV26VPfee2+3g4VzOH2lE9PvV8a8eTL9/oTGEeG0eOIplc8NAJA8nFbEM9UUW5ZyOqhlkWvbKuKLG9JcvK6Rw8NhdVSkxJBUEg53ObbuFBXm2neGmN/Z/va3v2n//fdXSUnJHo+bNGmSRo8erVdeeUW33nprrE8Hh4msdGIEAm1uLIle6cSoqWkp4llVJaOuTnZOjiyPRyGfT3Z+ftrHE0+pfG4AgOThtCKeqcprWfJYlgKG0bIgRYRtq9Cy+MUdaS9e18hpzc1yq6Wmze7tuHfu76x4FBXm2neGmEfcrF+/Xm63u1PHut1ubdiwIdangkOFfD6FS0pkFRTIzsqSVVCgcElJQlc6cZeWKqO8XGYgIKOxUWYgIFd5udylpcQTZ6l8bgCA5BEp4mnv/FJhG4Yadm5HfPlCIZWEwyqwLGXZtgosSyXhsHyhqBU5gLQTr2vkvfp6ZUsybFuybRm2reyd27siUlQ4YJpqNAwFTFPlLpdKO/k9PoJrP/FiHnGTm5ur//3vfwoEAho8eHCHxwUCAf3vf/9Tbm5urE8Fh3LaSidOK5jstHjiKZXPDQCQPJxWxDPV5du2yhoa5DdNVZqmivi1HWgjXtfIaMvShro6vZWRoXKXSyXhcJfvZfEsKsy1n3gxj7g54YQT1NjYqCuuuEI1NTVRj6mpqdEVV1yhpqYmnXjiiTEHCWezvF41T52a8C/qnSmYnM7xxFMqnxsAIHl0pogn4s9rWZra3MwXN6AD8bpGTmtu1m07dsSUgO5MUeGu4tpPnJhH3Nxyyy16++239eGHH2r8+PE666yzdMABB6igoECbN2+W3+/XK6+8om3btiknJ0e33HJLPOMG2okUTDYCgXb7ElEw2WnxxFMqnxsAIHlEinhGS97EWsQTAFJBpKhwIEryhqLCySfmxE1hYaFeffVVXXHFFVq7dq1efPHFdsfYti2Px6Mnn3xShYWF3QoUqc+1apXyli6Va9IkacKELj/eaQWTnRZPPKXyuQEAeo/fNFVhmiqOcdh9PIt4AkAqoahwaunWeomHHHKIPv74Y73yyit69913tXr1atXX16t///4aM2aMJk+erLPPPlt9+vSJV7xIQZHViYyqKg2qrZWdlyc7xtWJQj5fy0pH1dUygsGW0R+FhQkrmOy0eOIplc8NANCz4rHSScR79fUtq0rZdrtVpQAgnflCIZW63ao2TQUNQ7k7kzYUFU4+Rm1tbdfeHYE4y548WRnl5W222ZLCJSVqKCuLqU2nFEx2ajzxlMrnFi/bt2/XunXrNHLkSPXt2zfR4QBxQb9Gd0zOzlZ5xm6/H9q2SsJhlTU0xNRmd4p47oq+jVREv05vqVxUOF36drdG3Djd66+/rieeeELLli1TKBTS0KFDNWnSJP3qV7/SiBEjWo+rq6vTXXfdpddee01fffWVhg4dqrPOOkuzZs1Sf5aS7FE9tTqR5fU6KongtHjiKZXPDQAQf/Fc6WRXpzU3MzUKAKLwpmDCJt2kZOLGtm3dcMMNevrppzVq1Ch95zvfUf/+/bVp0yZ99NFHWrduXWvipqGhQdOmTdOKFSt00kkn6dxzz9Xy5cv14IMP6qOPPtKbb76Z0pm7ROvM6kQkBQAASB2dWemELxgAAHyjW4kby7L04osv6u2331ZlZaXq6+tldzAv2TAMffLJJ915uk77wx/+oKefflpXXXWV7r77brl2WwqyeZdfYx544AGtWLFC119/vW6//fbW7bfffrvmzJmjuXPnaubMmb0SdzpidaKuMf1+mRUVsoqLUy6hlcrn5jS81oiH7haUR3LrTlFhVjoBAKBrYq5x8/XXX+vcc8/V0qVLO0zWtHkiw9CWLVtieaou2bZtmw444ADl5eWpvLxcGbvPn96FbdsaN26cvv76a61atUrZ2dmt+xoaGjR27FgNHjy41xJO6Sp78mS5ysvbrU7UnRo3qSZSwNmsqpJRVyc7J0dWjAWcnSaVzy3CKXNv0+G1Rs/btaC80c2C8kg+8SoqfEJ2tj5xudqtdHJIOKz3YqxxEy9OuWcD8US/RqpKl74d84ibu+++W0uWLJHb7dbFF1+sww8/XAUFBTKjzVnuRQsWLFBtba0uuugihcNhvfnmm6qoqFBubq5OOOEEFe0ygqOiokKbNm3SySef3CZpI0nZ2dk64ogjNH/+fK1fv75NTRzEV2R1IqOqqnV1osiXALRwl5a2KeBsBAIyAgG5S0uTPrmVyufmNLzWiIfd+5ECAdn0o7RR6na3KSocMAwFdiZzulJU2JbaJm123Q4AANqIOXHz2muvyTRNvfDCC/rWt74Vz5i6JTI6xuVy6ZhjjtGaNWta95mmqauvvlp33HGHpJbEjaQ2yZxdFRUVaf78+aqoqNhr4mb79u1xiD5NZWdr2xtvyPr0U9V/8on6H3KIzIMOatnH6yrXqlUyOijgbFRVqWnZMoXHju31uOIhlc9tV42NjW3+NxHS5bVGz6IfpbdVLpeqotWmMQxVGYaWNTVpbDjcqXY2dNDOhi6001OccM8G4o1+jVSVrH27q6ODYk7cfPnllxo5cqSjkjaSFNhZK+Xhhx/WhAkTtGDBAo0ZM0bLly/X9ddfr4ceekijRo3SlVdeqbqdRXFzc3OjtpWTkyNJrcftycaNGxVO4IeMlJCbKx1/vIKStG5doqNxjLylSzWotjbqPiMY1NalSxV0u3s3qDhJ5XOL5ssvv0zYc6fba42eQT9Kb0vz8lQ7aFDUfUHD0NKtW+UOBnutnZ6WyHs20FPo10hVydS3XS5Xh4NHOhJz4iY/P18DBw6M9eE9xtpZ0C4rK0vPPfechg0bJkk6+uij9fTTT+vYY4/VQw89pCuvvDKuzzt8+PC4ttcbXKtWKWPtWjWPGuWIX0gbGxv15ZdfaujQocrKykp0OI7hmjRJdl6e1EEB54GTJiln5MjeDywOUvncduWEvp0urzV6Fv0ovU1yuZRn22r/128pKjxp4ECN3PmjV2+001OccM8G4o1+jXhY5XJpbUaGRjU3J3Rk5K7SpW/HnLg56aST9H//93/6+uuvNWDAgHjG1C2RUTKHHHJIa9ImYty4cfJ4PKqsrFRtbW3rscEOftWJjLTJ6cSHh2QqhOT0AqVZWVlJ9Xr2uAkTZHs8sgOBdgWcbY9HmRMmKDNRsXVXKp9bFAnt22n2WqOH0I/S2gRJHttWwLbbFRX22LYmZGZKmXvvAfFqp6fxeQSpiH6NWMSrMH1PSvW+HXMl4Ztvvll9+vTRrFmzHDVFaPTo0ZI6nv4U2b59+3YVFxdLkiorK6MeG9keOS5VRApLmoGAjMZGmYGAXOXlcpeWJjo0dCDk8ylcUiKroEB2VpasggKFS0pSooBzKp+b0/BaIx4i/Sg8eLCszEyFBw+mH6URXyikknBYBZalLNtWgWWpJByWLxRKSDsAgJ4XKUwfME01GoYCpqlyl0ulTI/uNTGPuKmurtbPfvYz3XbbbfrPf/6jSy+9VPvvv7/ce/jjHXPMMbE+Xacdd9xxkqTVq1e329fU1KTKykplZ2dr8ODBGjp0qIYNG6bFixeroaGh3XLgixcvVmFhYUqtKGX6/TI7KCxpVlfL9Ptleb29Hhf2zM7PV0NZWcvfr7JSVlFRyvydUvncnIbXGvEQ6UdNy5Zp69KlGjhpkjInTEh0WOgl+batsoYG+U1TlaapIsuSd+c09US0AwDoWX7TVFW0laMNQ9WmKb9pcv/uBTEnbk4//XQZO4e3+v1+3XrrrXs83jAM1dTUxPp0nTZq1CiddNJJWrBggZ555hldeumlrfvuv/9+BYNBffe731XGzqUsL7nkEv3ud7/TPffco9tvv7312HvuuUf19fWaOXNmj8fcm8yKChkdFFs2gsGWL3N8kXMsy+tN2b9PKp+b0/BaIx7CY8cq6HYrZ+RIpkelIW+cEi3xagcA0DMqdk6PiiZoGKokcdMrYk7cjBgxojVx4zT33XefTjnlFP34xz/WvHnzNHr0aC1fvlzvv/++Ro4cqd/85jetx1533XV68803NWfOHC1fvlwTJkzQsmXLtGDBAk2cOFEzZsxI4JnEn1VcLDsnR0YHhSWtLla3BgAAAACkpmLLUo5tKxDlu3+ubauIpE2viDlxs2LFinjGEVejRo3SP/7xD915552aP3++FixYoKFDh+r73/++brrpJhUUFLQem52drXnz5umuu+7S66+/rg8++EBDhw7Vtddeq1mzZqlfv34JPJP4s7xeWR6PjCiFJa3CQn6FB5AQpt8vs6JCVnEx9yEACbXK5dLSvDxNcrnEJEAA6c5rWfJYVkviZreC8oWMmuw1Rm1trTPKQKPXtK4qVV0tIxhsGWlTWJjwVaW2b9+udevWaeTIkSldERy7sG25gv9RxldlctUultFcLzujv8J5R6h5yGSFcw9t+waRpOjbHXP6KnfoGP0aqaZ11RTDUK1hKG/nKldOWjUFiBX3bHRH5P5YbZoKGoZydyZtnHB/TJe+HfOIGyQvCpQi4WxbmeufV5+K38to3CqzaUub3Zmb58uq+oPsrEHaUXyDmkZcmBIJHLQXWeUuwggEZAQCcpeWqqGsLIGRAUg3kVVTIgKSAratUrdbZQ0NiQsMABKMgvKJ1+3EjWVZev3117Vw4UJt2LBB27Zt02uvvda6/5NPPlFDQ4OOOuoomdGqUSNhKFCKhGiqlbv8IrnqVshsjl4oW1JLMqdpi/qu/Jky17+gUMmzUmZe78WJHscqdwCcglVTAGDvKCifON1K3Pj9fl122WX67LPPZO8cIrV7wWKfz6c//vGPeuWVV3T88cd35+kAJLumWvVfdKrM+lUy1LlhlWZznYwtH6n/olNVf/TbJG9SCKvcAXAKVk0BADhZzENgAoGAzj77bK1evVrjx4/XzTffrKIoKxKdd955sm1bb775ZrcCBRLB9PuVMW+eTL8/0aEkP9uWu/yiLiVtIgzZMutXyV1+sUSdgZQRWeUuGla5A9CbIqumRMOqKT3Hb5qal5EhP6PyAWCPYh5x88ADD+iLL77QBRdcoIcffliGYei9997T2rVr2xw3ceJEZWdna9GiRd0OFugtFEyNv8z1z8tVt6LLSZsIQ7ZcdcuVuf55NY28KM7RIRFY5Q6AU7BqSu9qLQS9c6RTjm3L45BCpwDgRDGnt99++2316dNHd999d7vpUbsrLCxUdXV1rE8F9LpIwVQzEJDR2CgzEJCrvFzu0tJEh5acbFt9Kn6/x5o2nWE216lPxf2MukkhIZ9P4ZISWQUFsrOyZBUUKFxSopDPl+jQAKQZXyikknBYg8NhZVqWBofDKgmH5QuFEh1ayokUgg6YphoNQwHTVLnLpVK3O9GhAYAjxTziZt26dSouLtaAAQP2eqzb7da2bdtifSqgV1EwNf5cwf/IaNwal7aMxi1yBf+jcN7EuLSHxGKVOwBOEVk1ZVlTk5Zu3apJAwdqQmZmosNKORSCBoCui3nETVZWlrZv396pYwOBgHI6qGMAOE1nCqaiazK+Kmu35HeszKYtyti8IC5twTksr1fNU6eStAGQcGPDYR0fDGpsOJzoUFJSZwpBAwDaivnOWFRUpHXr1mnLlj1/GauqqlJVVZUOOOCAWJ8K6FUUTI0/V+3i+La39Z9xbQ8AAPQOCkEDQNfFnLg57bTT1NTUpDvuuKPDY2zb1q233irDMHT66afH+lRAr4oUTN39IwUFU2NnNNc7uj0AANA7IoWg29WroxA0AHQo5sTND3/4Qw0bNkxPP/20LrnkEi1YsEA7duyQ1FL/5q233tIZZ5yhN998U4WFhbrsssviFjTQ0yiYGl92Rn9HtwcAAHpPpBB0gWUpy7ZVYFkUggaAPYi5OHFubq58Pp/OP/98vfHGG5o3b17rvgkTJkhqGXEzbNgwPf/88+rXr1/3owV6CQVT4yucd4QyN8+PX3sDj4pbWwAAoHdFCkH7TVOVpqkiRtoAwB51q/rX+PHj9dFHH+knP/mJRo0aJdu2W/8NHz5c1157rT744APq2yBpUTA1PpqHTJaVOSgubVmZg9RccFJc2gIAAInjtSxNbW4maQMAexHziJuIvLw8/fznP9fPf/5zhUIhBYNBZWdns4oUgFbh3ENlZw2U4rCylJ01SOHcQ+MQFQAAAAA4X1zX23O73Ro2bBhJGwBtGYZ2FM+UldG9e4OVkaMdxTdIHSwjCgAAAACpptsjbiI2btyo1atX6+uvv9aAAQM0ZswYDR8+PF7NA0hyTSMuVOb652VsWSSj3Zpde2fLUDjnYDWNuLAHogMAAAAAZ+p24ubVV1/VPffco5UrV7bbd+CBB+qnP/2ppk+f3t2nAZDsDEOhkufUf9GpMutXdSl5Y8uQ1X+sQiXPMtoGAAAAQFrpVuLm5ptv1qOPPirbbvkClpGRoUGDBmnLli1qbm7Wp59+qssvv1xXXXWVfve738UlYABJLDNP9Ue/LXf5RXLVrZDZXLfXh1gZOQrnHNyStMnM6/kYAQBAcrFtuYL/UcZXZXLVLpbRXC87o7/CeUeoecjkltp4/PADIInFnLh56aWX9Mc//lGmaerSSy/VjBkzNHr0aJmmKcuy9Nlnn+mRRx7Rs88+q8cff1yTJk3SeeedF8/YASSjzDyFjnxDmeufV5+K+2U0bpEZpWixlTlIdtYg7Si+oWV6FB+4AADArmx75+eJ38to3Nru80Tm5vmyqv7A5wkASS/mxM2jjz4qwzB033336Xvf+16bfaZpauzYsZozZ44OPfRQXX/99XrsscdI3ABoYRhqGnmRmkZc2PIL2eb5cm39+JtfyAYepeaCk/iFDAAARNdU26kRvGbTFqlpi/qu/Jky17/ACF4ASSnmxM3//vc/DRkypF3SZneXXXaZZs+eHbUGDtBTTL9fZkWFrOJiWV5vosNxXDzx1K1zMwyF8yYqnDexZ4IDUojT7iOuVauUt3SpXJMmSRMmJDqclOc3TVWYpootS17LSng78RLPeJx2buhBTbVdrplnNtfJ2PKR+i86VfVHv91h8sZp/chp8SA50Y+SX8yJm4yMDO27776dOnbfffdVRUVFrE8FdJpRUyN3aanMqioZdXWyc3JkeTwK+Xyy8/PTPp54SuVzA5zEaddaJB6jqkqDamtl5+XJ5trvMTWGoVK3W1WmqTrDUI5ty2NZ8oVCyrc7X+Q9Xu3ESzzjcdq5oYfZttzlF3V5oQNJMmTLrF8ld/nFCh35eptRvU7rR06LB8mJfpQ6zFgfeOCBB6qqqkrWXjJ24XBYa9eu1fjx42N9KqDT3KWlyigvlxkIyGhslBkIyFVeLndpKfHEWSqfG+AkTrvWIvG4AgGZzc1yce33qFK3W+UZGQqYphoNQwHTVLnLpVK3OyHtxEs843HauaFnZa5/Xq66FV1O2kQYsuWqW67M9c+32e60fuS0eJCc6EepI+bEzbXXXqstW7bsdbWo++67T1u3btU111wT61MBnWL6/TKrqtptNySZ1dUy/f60jieeUvncACdx2rXmtHhSnd80VWVG+ahmGKo2Tfmj7evBduIlnvE47dzQw2xbfSp+36lVKffEbK5Tn4r7pZ0jDpzWj5wWD5IT/Si1xPzXOu2003T33Xfr/vvv17nnnquysjJt2LBBTU1N2rBhg+bPn6/zzjtP9913n373u9/p1FNPjWfcQDtmRYWMuuhv5EYwKLOyMq3jiadUPjfASZx2rTktnlRXsXNoezRBw1BlJz90x6udeIlnPE47N/QsV/A/Mhq3xqUto3GLXMH/SHJeP3JaPEhO9KPUEnONm0GDBrX+/wULFmjBggUdHjtr1izNmjWr3XbDMFRTUxNrCEAbVnGx7JwcGYFAu312bq6soqK0jieeUvncACdx2rXmtHhSXbFlKce2FYjywTvXtlXUyQKT8WonXuIZj9PODT0r46uydkt+x8ps2qKMzQsUzpvouH7ktHiQnOhHqSXmNJtt293+t7f6OEBXWF6vLI+n3YxnW5JVWNjrq7A4LZ54SuVzA5zEadea0+JJdV7LkseyWqdztLJtFXZhZZB4tRMv8YzHaeeGnuWqXRzf9rb+U5Lz+pHT4kFyoh+llphH3CxbtiyecQBxEfL5WlZfqa6WEQy2/AJcWKiQz0c8cZbK5wY4idOutUg8RlVVazyRVaUQf75QSKVut6pNU0HDUO7OD9y+UCgh7cRLPONx2rmh5xjN9T3WntP6kdPiQXKiH6UOo7a2lnXA4Ajbt2/XunXrNHLkSPXt27dbbZl+v8zKSllFRY74Bdhp8cRTKp9bvMSzbyN9Oe1aa1q2TFuXLtXASZOUOWFCosNJeX7TVKVpqqibv5LGq514iWc88WqLe7ZzuZd8R5mb58etvaaCkxU6/P/abEvVa4R+nd6c1q/jKV36dswjbgAns7xeR3yxiXBaPPGUyucGOInTrrXw2LEKut3KGTlSmYkOJg144/RhO17txEs843HauSH+wnlHxDVxEx54VLttTutHTosHyYl+lPzinrj517/+paVLl6qpqUnFxcU6+eST1adPn3g/DQAAAIA00jxksqyqP8SlQLGVOUjNBSfFISoA6HmdTtysX79ePp9PeXl5uvLKK9vtD4VCuuKKK/TOO++02b7ffvvp2Wef1UEHHdT9aAEAAACkpXDuobKzBkpxSNzYWYMUzj00DlEBQM/r9KpSb7/9tn77299q7dq1UfffeOON+vvf/y7btmUYhgoKCiRJ1dXVKi0tVUNDQ3wiBgAAAJB+DEM7imfKysjpVjNWRo52FN8gRVkmGQCcqNOJm0WLFkmSvvOd77TbV1lZqRdeeEGGYeiMM87Q2rVrtWrVKi1evFijR4/Wpk2b9Mwzz8QvagAAAABpp2nEhQrnjJet2JIutgyFcw5W04gL4xwZAPScTidu/H6/srOzdeih7YcUvvrqq7JtWwMHDtTDDz+snJyWLPjo0aM1e/Zs2batv//97/GLGgAAAED6MQyFSp6T1X9sl5M3tgxZ/ccqVPIso20AJJVOJ242b96sUaNGRd33z3/+U4Zh6JRTTtGAAQPa7Dv55JOVl5cnv9/fvUgBAAAAIDNP9Ue/reZBR3d62pSVkaPmQceo/ui3pcy8no0PAOKs04mb2tpauVyuqPuWLVsmSTruuOOi7t93331VW1vb9egAAAAAYHeZeQod+Ya2j5utcPb+sjIHRT3MyhykcPb+2j5utkJHvk7SBkBS6vSqUm63W1988UW77Rs2bNBXX30lwzA0YcKEqI/NzMyUbduxRwkAAAAAuzIMNY28SE0jLpQr+B9lbJ4v19aPZTTXy87or/DAo9RccFLL6lFMjQKQxDqduBk9erT+/e9/65NPPtEhhxzSuv3dd9+VJPXv31/jxo2L+thNmzZp0KDoWXAAAAAAiJlhKJw3UeG8iYmOBAB6RKenSp188smybVuzZs3S5s2bJUlr167V/fffL8MwdOqpp8qIksneuHGjvvzySxUXF8cvagAAAAAAgDTQ6cTND37wAw0aNEhLly7VuHHj5PV6ddhhh+nzzz+XaZq65pproj7utddekyQdc8wx8YkYAAAAAAAgTXQ6cTNo0CC9+OKLGjJkiJqbm/Xll1/Ktm25XC7deeedUevb2Latp556SoZh6MQTT4xr4AAAAACAvft7VpYe3ndf/T0rK9GhAIhBp2vcSNKkSZP0r3/9S++++67Wrl2rAQMGaPLkyfJ4PFGP37p1q6666ioZhqHDDz88HvECAAAAADrhM9PUCf37KyTJlvQnSW5J79XXa7RlJTY4AJ3WpcSNJGVnZ+uss87q1LGDBg3S97///a4+BQAAAACgm07o318Nu9QhtSU12LZO6N9fG+rqEhcYgC7p9FQpAAAAAEByeCsjQ6FoOwxDoZ37ASQHEjcAAAAAkGKWuFyyO9hnSyp3uXozHADdQOIGAAAAAFLM4eGwjA72GZJKwuHeDAdAN5C4AQAAQJf4TVPzMjLkN/koCTjVac3NckuSvdu4G9uWe+d+INmtcrm0MC9Pq1J8BBkTGwEAANApNYahUrdbVaapOsNQjm3LY1nyhULK3/3LIYCEe6++vmVVKduWrZaRNpFVpYBk1vp+ZBiqHTRIebYtj22n7PsRiRsAAAB0SqnbrfJdCpoGDEOBnR+eyxoaEhgZgGhGW5Y21NXpVcvSe9u26YR+/TSdkXJIAe3ejyQFbDtl34+4agEAALBXftNUVbQvfIahatNk2hTgYFMaG3X1xo2a0tiY6FCAbkvH96PUOyMAAADEXcXO6VHRBA1DlSn4QRkA4Dzp+H7EVKk0Zvr9MisqZBUXy/J6E94OgN7BNQvsmd80VWGaKrYseS0r0eE4RrFlKce2FYjyYTnXtlXEawUgAbhn9x6nvNbp+H5E4iYNGTU1cpeWyqyqklFXJzsnR5bHo5DPJzs/v9fbAdA7uGaBPaPw7p55LUsey2r5oLzrh2XbViFfmAD0Mu7Zvcdpr3U6vh+l3hgi7JW7tFQZ5eUyAwEZjY0yAwG5ysvlLi1NSDsAegfXLLBnkUKHAdNUo2EoYJoqd7lU6nYnOjTH8IVCKgmHVWBZyrJtFViWSsJh+UKhRIcGIM1wz+49TnytI+9Hg8NhZVqWBofDKf1+xIibNGP6/TKrqtptNySZ1dUy/f5OTZ2IVzsAegfXLLBnnSl0mIq/4HVVvm2rrKFBftNUpWmqKEV/2QTgbNyze49TX+vI+9GypiYt3bpVkwYO1ITMzF6Po7cw4ibNmBUVMurqou4zgkGZlZW92g6A3sE1C+xZOhY67A6vZWlqczNfjAAkBPfs3uP013psOKzjg0GNDYcTGkdPo0enGau4WHZOTtR9dm6urKKiXm0HQO/gmgX2LFLoMJpULXQIAMmKe3bv4bV2BhI3acbyemV5PNr90rMlWYWFnZ4qEa92APQOrllgzyKFDrX7h9MULnQIxMpvmpqXkSE/oxqQINyzu6Y71yyvtTNQ4yYNhXy+lpVlqqtlBIMtv7YXFirk8yWkHQC9g2sW2DNfKKRSt1vVpqmgYSh354fSVC10CHSV01aWQXrjnr138bpmea0Tj8RNGrLz89VQVtZSrLSyUlZRUUy/tserHQC9g2sW2DMK7wJ7FllZJiJgGArs/GJY1tCQwMiQjrhn7128rlle68QjcZPGLK83Ll/a4tUOgN7BNQvsmZcPpEA7Tl1ZBuCeHV1PXLO81onDxFQAAAAAe+T0lWUAtMU1m1r4a6HbTL9fGfPmyfT7Ex0Kkhj9CACAntWdAqWsLAMkl3S5Zle5XFqYl6dVLleiQ+lRTJVCzIyampZCp1VVMurqZOfkyPJ4FPL5ZOfnJzo8JAn6EQAAPSseBUojK8sEDEPa9Vd8VpYBHCnVr9nW+5phqHbQIOXZtjy2nbLF0hlxg5i5S0uVUV4uMxCQ0dgoMxCQq7xc7tLSRIeGJEI/AgCgZ0UKlAZMU42GoYBpqtzlUqnb3aV2fKGQSsJhFViWsmxbBZalknCYlWUAh0rla7b1vuZyqdk0FXC5YrqvJQtG3CAmpt8vs6qq3XZDklldLdPvp/gp9op+BABAz4pngVJWlgGSS6pes+lYLJ0RN4iJWVEho64u6j4jGJRZWdnLESEZ0Y8AAOhZPVGg1GtZmtrcnHJfjIBUlWrXbDoWXk69M0KvsIqLZefkRN1n5+bKKirq5YiQjOhHAAD0rHQpUAogfaTjfY3EDWJieb2yPB7tfrnYkqzCQqa3oFPoRwAA9KxIgVLt/iUnRQqUAkg/6XhfI3GDmIV8PoVLSmQVFMjOypJVUKBwSYlCPl+iQ0MSoR8BANCzUrlAKYD0FLmvDQ6HlWlZGhwOp/R9jeLEiJmdn6+GsrKWArOVlbKKihghgS6jHwEA0LNStUApgPQVua8ta2rS0q1bNWngQE3IzEx0WD2GxA26zfJ6+aKNbqMfAQDQs7wkbACkmLHhsNzBoEbm5EgpnLhhqhQAAAAAAIBDMeIGAAAAiDO/aarCNFXMKBcAaId7ZNeQuAEAAADipMYwVOp2q8o0VWcYyrFteSxLvlBI+R0sXwsA6YJ7ZGyYKgUAAADESanbrfKMDAVMU42GoYBpqtzlUqnbnejQACDhuEfGhsQNAAAAEAd+01SVGeXjtWGo2jTlj7YPANIE98jY8coAAAAAcVCxc+h/NEHDUCVfSgCkMe6RseOVAYAkYfr9ypg3T6bfn+hQAKQ5v2lqXkZGSv46usrl0sK8PK1yubr82GLLUk4HNRpybVtFFOBEF6XytYb0wz0ydhQnBgCHM2pq5C4tlVlVJaOuTnZOjiyPRyGfT3Z+fqLDA5BGUrmoZOu5GYZqBw1Snm3LY9tdOjevZcljWQoYhrTrr8q2rUJWTkEXpPK1hvTFPTJ2pG4BwOHcpaXKKC+XGQjIaGyUGQjIVV4ud2lpokMDkGZSuahk67m5XGo2TQVcrpjOzRcKqSQcVoFlKcu2VWBZKgmH5QuFeihypKJUvtaQ3rhHxoYRNwDgYKbfL7Oqqt12Q5JZXS3T75fl9fZ6XADST2eKSibrr6XxPLd821ZZQ4P8pqlK01QRvyKji1L5WgO4R8aGETcA4GBmRYWMurqo+4xgUGZlZS9HBCBdpXJRyZ44N69laWpzM19I0GWpfK0BEdwju4arHgAczCoulp2TE3WfnZsrq6iolyMCkK5SuahkKp8bkg/9EcDuSNwAgINZXq8sj0e7f3yzJVmFhQmfJsVKV0D6iBSV1O5fKB1SVLI7q+84/dyQXuiPAHZHjRsAcLiQz9eyqlR1tYxgsGWkTWGhQj5fwmJipSsgPflCIZW63ao2TQUNQ7k7v0gmsqhkvFbfiZxblWG0nltkVSmgtznxWgOQOCRuAMDh7Px8NZSVtRQqrqyUVVSU8JE2kZWuIoxAQEYgIHdpqRrKyhIYGYCe5MSikpHVdyIChqHAzmROWUNDp9uJnNuypiYt3bpVkwYO1ITMzJ4IGdgrJ15rABKHxA0AJAnL6014wkZipSsALVM5nPAlsidW3xkbDssdDGpkTo5E4gYJ5pRrDUBiUeMGANAlrHQFwClYfQcAkA54NwMAdAkrXQFwClbfAQCkAxI3AIAucfpKVwDSB6vvAADSAYkbAECXhXw+hUtKZBUUyM7KklVQoHBJSUJXugKQnnyhkErCYRVYlrJsWwWWpZJwmNV3AAApg+LEAIAuc+JKVwDSE6vvAABSXdqMuJkzZ47y8vKUl5enpUuXtttfV1enW265RQcddJCGDBmi8ePH67bbblN9fX0CogWA5GB5vWqeOpWkDYCE81qWpjY3k7QBAKSctEjcrFy5UrNnz1Z2dnbU/Q0NDZo2bZrmzp2rMWPG6Oqrr9bo0aP14IMP6swzz9T27dt7OWIAAAAAAIA0SNw0NTVpxowZGj9+vKZNmxb1mAceeEArVqzQ9ddfr5dfflm33367Xn75ZV1//fX697//rblz5/Zy1ED6Mf1+ZcybJ9PvT3QorZwWk9PiAYBUtMrl0sK8PK1yuRIdCgAAktKgxs29994rv9+vhQsX6oEHHmi337Zt/fnPf1b//v114403ttl344036vHHH9czzzyjmTNn9lbIQFoxamrkLi2VWVUlo65Odk6OLI9HIZ9Pdn4+MTkwHgBIRTWGoVK3W1WGodpBg5Rn2/LYtnyhkPI7WHIcAIDekNIjbj755BPdd999mjVrlrwd1F+oqKjQpk2bdMQRR7SbSpWdna0jjjhCVVVVWr9+fW+EDKQdd2mpMsrLZQYCMhobZQYCcpWXy11aSkwOjQcAUlGp263yjAwFXC41m6YCLpfKXS6Vut2JDg0AkOZSdsTNjh07WqdIXXfddR0eV1FRIUkqKiqKur+oqEjz589XRUWFRowY0WE71MHpvsbGxjb/i9TnWrVKRlVVu+2GJKOqSk3Llik8dmzSx9Sdvu3E1wiQuGcjtaxyuVRlGO13GIaqDEPLmpo0Nhzu/cCAOOGejVSVrH27b9++XTo+ZRM3d955pyoqKvTee+/JtYc5ynV1dZKk3NzcqPtzcnLaHNeRjRs3Kswbelx8+eWXiQ4BvSRv6VINqq2Nus8IBrV16VIFe/mXzp6MKZa+7cTXCNgV92ykgqV5eaodNCjqvqBhaOnWrXIHg70cFRB/3LORqpKpb7tcrg4HjnQkJRM3S5Ys0YMPPqibb75Z48aN65XnHD58eK88TyprbGzUl19+qaFDhyorKyvR4aAXuCZNkp2XJwUC7fbZubkaOGmSckaOTPqYutO3nfgaARL3bMTHKpdLazMyNKq5udsjWlyrXMpYm6HmUc0Kj+1aW5NcLuXZttrfaaVc29akgQM1cuePeUAy4p6NVJUufTvlEjfNzc2aMWOGDjzwQN1www17PT4yoibYwa8okZE2OXt5s+7qUCd0LCsri9czXUyYINvjkR0IaNcB6rYk2+NR5oQJykyhmGLq2xMmyB4xIno8I0Yk5jUCdsE9G7FoLQRsmqozDOXYtjyWFVMhYKPGkLvULbPKlFFnyM6xZXkshXwh2fmda2uCJI9tK2Db0q5TpnYWKJ6QmSllcrdF8uOejVSV6n075RI39fX1rXVrCgoKoh7z7W9/W5L07LPPthYtrqysjHpsZHtxcXG8QwUgKeTztayYVF0tIxiUnZsrq7BQIZ+PmCJsW1EqL0iscgIgSUUKAUcEDEOBncmcsoaGLrXlLnUro/ybtoyAISPQksxpKOt8W75QqHVVqaBhKHeXVaUAAEiklEvc9OnTR5dccknUfYsWLVJFRYVOO+00DR48WPvtt5+Ki4s1bNgwLV68WA0NDW1WlmpoaNDixYtVWFi4x8LEAGJn5+eroaxMpt8vs7JSVlGRrA5WgUvHmEy/X+aGDe22G5LMjRtl+v0Jf70AoCv8pqkqM8rCpoahatOU3zTltaxOtWX6TZlV7dsyZMisNmX6TVnezrWVb9sqa2jQsqYmLd26VZMGDmwZaQMAQIKlXOKmX79+evDBB6PumzFjhioqKjRz5kxNmjSpdfsll1yi3/3ud7rnnnt0++23t26/5557VF9fr5kzZ/Z02EDas7xexyUgnBCTWVEho4Pi6EYw2JJYctjrBgB7UrFzelQ0QcNQZVcSNxUt06OiMYKGzMrOJ24ixobDcgeDLTVtSNwAABwg5RI3sbjuuuv05ptvas6cOVq+fLkmTJigZcuWacGCBZo4caJmzJiR6BABpCmruFh2To6MDooTW12sSA8AiVZsWcqxbQWiJG9ybVtFnUzaSJJVbMnOsWUE2rdl59qyirqWtAEAwImijFNNP9nZ2Zo3b55mzJih1atX66GHHtLq1at17bXX6tVXX1W/fv0SHSKANGV5vbI8Hu1ezcaWZBUWMtoGQNLxWpY8ltW+Tpdtq9CyOj3aRpIsryXLY8ne7S5py5ZVaHV5tA0AxIPfNDUvI0P+aNNCgRgYtbW1VLeEI2zfvl3r1q3TyJEjU7oiONJPd/u2UVPTYbFkOz+/ByIG9o57NrojsqpUtWm2FgIu7O6qUtWmjKDRMtKmsGurSu2Kvo1URL/uHfFcMQ+dky59m6lSAOBwTiqWDADxECkE7DdNVZqmiro40mZXdr6thrKGlkLFlaasIkbaAEiMeK6YB+yKxA0AJAknFEsGgHjydiNhszvLS8IGQOLEc8U8YHdMugMAAAAAoBs6s2IeECt6DwAAuzH9pjLmZcj08zYJAAD2LrJiXjRdXTEP2B1TpQAA2Km1yGmVKaPOkJ1jy/LEXuQUAACkh8iKeQHDkHYdeRPDinnA7vgpEQCAndylbmWUZ8gMmDIaDZkBU65yl9yl7kSHBgAAHM4XCqkkHFaBZSnLtlVgWSoJh+ULhRIdGpIcI24AAFDL9Cizqv3vGYYMmdWmTL9J4VMAANCheK6YB+yKxA0AAJLMipbpUdEYQaNlmWESNwAAYC/iuWIeIDFVCgAASZJVbMnOiV7Hxs61ZRXxAQwAAAC9j8QNAACSLK8ly2PJVtvkjS1bVqHFaBsAAAAkBIkbAAB2CvlCCpeEZRVYsrNsWQWWwiVhhXwUFQQAAEBiUOMGAICd7HxbDWUNLYWKK01ZRYy0AQAAQGKRuAEAYDeWl4QNAAAAnIGpUgAAAAAAAA5F4gYAAAAAAMChSNwAAAAAAAA4FIkbAAAAAAAAhyJxAwAAAAAA4FAkbgAAAAAAAByK5cABAEBKMP2mzApTVjHLuQMAgNRB4gYAACQ1o8aQu9Qts8qUUWfIzrFleSyFfCHZ+XaiwwMAAOgWpkoBAICk5i51K6M8Q2bAlNFoyAyYcpW75C51Jzo0AACAbiNxAwAAkpbpN2VWtf84Y8iQWW3K9PNRBwAAJDc+zQAAgKRlVrRMj4rGCBoyK/moAwAAkhufZgAAQNKyii3ZOdHr2Ni5tqwiihQDAIDkRuIGAAAkLctryfJYstU2eWPLllXI6lLpxPSbypiXwfS4PeA1AoDkxKpSAAAgqYV8oZZVpapNGUGjZaRNYcuqUkh9rCq2d7xGAJDcSNwAAICkZufbaihraClUXGnKKmKkTTqJrCoWYQQMGYGWREVDWUMCI3MOXiMASG6MkwQAACnB8lpqntpM0iaNsKrY3vEaAUDy404NAACApMSqYnvHawQAyY87NQAAAJISq4rtHa8RACQ/EjcAAABISqwqtne8RgCQ/EjcAAAAIGmFfCGFS8KyCizZWbasAkvhkjCriu2C1wgAkhurSgEAACBpsarY3vEaAUByI3EDAACApGd5SUbsDa8RACQnpkoBAAAAAAA4FIkbAAAAAAAAhyJxAwAAAAAA4FAkbgAAAAAAAByKxA0AAAAAAIBDkbgBAAAAAABwKBI3AAAAAJDCXKtcyluYJ9cqV6JDARCDjEQHAAAAAACIP6PGkLvULaPK0KDaQbLzbNkeWyFfSHa+nejwAHQSI24AAAAAIAW5S93KKM+QK+CS2WzKFXDJVe6Su9Sd6NAAdAGJGwAAAABIMabflFnV/uueIUNmtSnTz1dBIFlwtQIAAABAijErTBl1RtR9RtCQWclXQSBZcLUCAIAuo9AlADibVWzJzolex8bOtWUVWb0cEYBYUZwYAAB0GoUuASA5WF5LlseSETBk6JuRN7ZsWYWWLC+JGyBZMOIGAAB0GoUuASB5hHwhhUvCCg8Oy8q0FB4cVrgkrJAvlOjQAHQBI24AAECndKbQJb/gAoBz2Pm2Gsoa1LSsSVuXbtXASQOVOSEz0WEB6CJG3AAAgE6h0CUAJKfw2LCCxwcVHhtOdCgAYsAnLAAA0CkUugQAAOh9JG4AAECnRApd2mqbvKHQZc8z/aYy5mXI9PPRDYlHfwSA3kWNGwAA0GkhX6h1VSkjaMjO/WZVKcRfZBUvs6plmpqdY8vyWKzihYSgPwJAYpC4AQAAnUahy94VWcUrwggYMgItX54byhoSGBnSEf0RABKD8Y0AAKDLKHTZ8zqzihfQW+iPAJA43GEBAAAciFW84CT0RwBIHO6wAAAADsQqXnAS+iMAJA41boB0Z9tyBf+jjK/K5KpdLKO5XnZGf4XzjlDzkMkK5x4qGdF/YQMA9JzIKl5GwJChb+7DrOKFRKA/AkDikLgB0pVtK3P98+pT8XsZjVtlNm1psztz83xZVX+QnTVIO4pvUNOIC0ngAEAvi6ziZVabrat4WYUWq3ghIeiPAJAYJG6AdNRUK3f5RXLVrZDZXNfhYWbTFqlpi/qu/Jky17+gUMmzUmZe78UJAGkusoqX6TdlVpqyihjZgMShPwJAYpC4AdJNU636LzpVZv0qGYo+V313ZnOdjC0fqf+iU1V/9NskbwCgM+I4FdXy8gUZzkF/BIDeReIGSCe2LXf5RV1K2kQYsmXWr5K7/GKFjnydaVM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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"df.groupby(['Cluster'])['Cluster'].count()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"id": "_jl-EpBBweHy",
"outputId": "e2f6dab7-dc3a-4191-aaca-0dac8255bdc5"
},
"execution_count": 69,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Cluster\n",
"0 81\n",
"1 39\n",
"2 35\n",
"3 23\n",
"4 22\n",
"Name: Cluster, dtype: int64"
],
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Cluster</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Cluster</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>81</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>22</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div><br><label><b>dtype:</b> int64</label>"
]
},
"metadata": {},
"execution_count": 69
}
]
},
{
"cell_type": "code",
"source": [
"#menampilkan cluster tertentu\n",
"data_cluster1=df.loc[df['Cluster'] == 1]"
],
"metadata": {
"id": "PqoYc4q4wgnz"
},
"execution_count": 70,
"outputs": []
},
{
"cell_type": "code",
"source": [
"data_cluster1"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "MqmFSKmTwimK",
"outputId": "83287d56-279b-4394-dc96-4ff8a4a913c2"
},
"execution_count": 71,
"outputs": [
{
"output_type": "execute_result",
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" CustomerID Gender Age Annual Income (k$) Spending Score (1-100) \\\n",
"123 124 Male 39 69 91 \n",
"125 126 Female 31 70 77 \n",
"127 128 Male 40 71 95 \n",
"129 130 Male 38 71 75 \n",
"131 132 Male 39 71 75 \n",
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"167 168 Female 33 86 95 \n",
"169 170 Male 32 87 63 \n",
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"173 174 Male 36 87 92 \n",
"175 176 Female 30 88 86 \n",
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"187 188 Male 28 101 68 \n",
"189 190 Female 36 103 85 \n",
"191 192 Female 32 103 69 \n",
"193 194 Female 38 113 91 \n",
"195 196 Female 35 120 79 \n",
"197 198 Male 32 126 74 \n",
"199 200 Male 30 137 83 \n",
"\n",
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"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "data_cluster1",
"summary": "{\n \"name\": \"data_cluster1\",\n \"rows\": 39,\n \"fields\": [\n {\n \"column\": \"CustomerID\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 22,\n \"min\": 124,\n \"max\": 200,\n \"num_unique_values\": 39,\n \"samples\": [\n 190,\n 196,\n 132\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Gender\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 2,\n \"samples\": [\n \"Female\",\n \"Male\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Age\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3,\n \"min\": 27,\n \"max\": 40,\n \"num_unique_values\": 13,\n \"samples\": [\n 36,\n 27\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Annual Income (k$)\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 16,\n \"min\": 69,\n \"max\": 137,\n \"num_unique_values\": 26,\n \"samples\": [\n 77,\n 93\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Spending Score (1-100)\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 9,\n \"min\": 63,\n \"max\": 97,\n \"num_unique_values\": 24,\n \"samples\": [\n 93,\n 83\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Cluster\",\n \"properties\": {\n \"dtype\": \"int32\",\n \"num_unique_values\": 1,\n \"samples\": [\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 71
}
]
},
{
"cell_type": "code",
"source": [
"#Method 1 - Elbow Method\n",
"wcss = []\n",
"for i in range(1, 11):\n",
" kmeans = KMeans(n_clusters=i, init='k-means++', max_iter=300, n_init=10, random_state=0)\n",
" kmeans.fit(X)\n",
" wcss.append(kmeans.inertia_)\n",
"plt.plot(range(1, 11), wcss)\n",
"plt.title('Elbow Method')\n",
"plt.xlabel('Number of clusters')\n",
"plt.ylabel('WCSS')\n",
"plt.show()\n",
""
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 472
},
"id": "ab5JDrHFwmGc",
"outputId": "fb378677-ce9b-46f9-d9aa-a58f24d6bde6"
},
"execution_count": 72,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"# A list holds the silhouette coefficients for each k\n",
"silhouette_coefficients = []\n",
"\n",
"# Notice you start at 2 clusters for silhouette coefficient\n",
"for k in range(2, 11):\n",
" kmeans = KMeans(n_clusters=k, init='k-means++', max_iter=300, n_init=10, random_state=0)\n",
" kmeans.fit(X)\n",
" score = silhouette_score(X, kmeans.labels_)\n",
" silhouette_coefficients.append(score)"
],
"metadata": {
"id": "0jz-kjTiwo5U"
},
"execution_count": 73,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.style.use(\"fivethirtyeight\")\n",
"plt.plot(range(2, 11), silhouette_coefficients)\n",
"plt.xticks(range(2, 11))\n",
"plt.xlabel(\"Number of Clusters\")\n",
"plt.ylabel(\"Silhouette Coefficient\")\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 478
},
"id": "LTPA9YJ2wrFM",
"outputId": "57ce9455-b992-4f61-8789-ca732a4bc161"
},
"execution_count": 74,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"import plotly as py\n",
"import plotly.graph_objs as go"
],
"metadata": {
"id": "CH9n5sF9xRdS"
},
"execution_count": 75,
"outputs": []
},
{
"cell_type": "code",
"source": [
"X = np.array(df.iloc[:,[2,3,4]])"
],
"metadata": {
"id": "D-HUV95ixRY_"
},
"execution_count": 76,
"outputs": []
},
{
"cell_type": "code",
"source": [
"X[:5]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "prfnDgnZxWi9",
"outputId": "cab4fc10-3f4c-4cf6-baf6-e68f8835d6e1"
},
"execution_count": 77,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([[19, 15, 39],\n",
" [21, 15, 81],\n",
" [20, 16, 6],\n",
" [23, 16, 77],\n",
" [31, 17, 40]])"
]
},
"metadata": {},
"execution_count": 77
}
]
},
{
"cell_type": "code",
"source": [
"wcss = []\n",
"for i in range(1, 11):\n",
" kmeans = KMeans(n_clusters=i, init='k-means++', max_iter=300, n_init=10, random_state=0)\n",
" kmeans.fit(X)\n",
" wcss.append(kmeans.inertia_)\n",
"plt.figure(1 , figsize = (15 ,6))\n",
"plt.plot(range(1, 11), wcss)\n",
"plt.title('Elbow Method')\n",
"plt.xlabel('Number of clusters')\n",
"plt.ylabel('WCSS')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 605
},
"id": "3CpqWt1Kxa2O",
"outputId": "d8dc73b9-cade-4d1b-9f46-b010503d81cf"
},
"execution_count": 78,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1500x600 with 1 Axes>"
],
"image/png": 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},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"# A list holds the silhouette coefficients for each k\n",
"silhouette_coefficients = []\n",
"\n",
"# Notice you start at 2 clusters for silhouette coefficient\n",
"for k in range(2, 11):\n",
" kmeans = KMeans(n_clusters=k, init='k-means++', max_iter=300, n_init=10, random_state=0)\n",
" kmeans.fit(X)\n",
" score = silhouette_score(X, kmeans.labels_)\n",
" silhouette_coefficients.append(score)"
],
"metadata": {
"id": "OD6Zp-9AxdVe"
},
"execution_count": 79,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.style.use(\"fivethirtyeight\")\n",
"plt.plot(range(2, 11), silhouette_coefficients)\n",
"plt.xticks(range(2, 11))\n",
"plt.xlabel(\"Number of Clusters\")\n",
"plt.ylabel(\"Silhouette Coefficient\")\n",
"plt.show()\n",
""
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 485
},
"id": "HAkjzSbSxewW",
"outputId": "a59f0ca6-5f85-4061-9ebe-5cb5c1325b4e"
},
"execution_count": 80,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"kmeans = KMeans(n_clusters = 6, max_iter = 500, n_init = 10, random_state = 0)\n",
"kmeans_preds = kmeans.fit_predict(X)"
],
"metadata": {
"id": "jy_UzkKxyDhm"
},
"execution_count": 81,
"outputs": []
},
{
"cell_type": "code",
"source": [
"kmeans_preds"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "hyQs5RNNyEN-",
"outputId": "8f9a9354-417e-420c-b920-582f2a388400"
},
"execution_count": 82,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5,\n",
" 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 3, 5, 3, 0,\n",
" 4, 5, 3, 0, 0, 0, 3, 0, 0, 3, 3, 3, 3, 3, 0, 3, 3, 0, 3, 3, 3, 0,\n",
" 3, 3, 0, 0, 3, 3, 3, 3, 3, 0, 3, 0, 0, 3, 3, 0, 3, 3, 0, 3, 3, 0,\n",
" 0, 3, 3, 0, 3, 0, 0, 0, 3, 0, 3, 0, 0, 3, 3, 0, 3, 0, 3, 3, 3, 3,\n",
" 3, 0, 0, 0, 0, 0, 3, 3, 3, 3, 0, 0, 0, 2, 0, 2, 1, 2, 1, 2, 1, 2,\n",
" 0, 2, 1, 2, 1, 2, 1, 2, 1, 2, 0, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,\n",
" 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,\n",
" 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2,\n",
" 1, 2], dtype=int32)"
]
},
"metadata": {},
"execution_count": 82
}
]
},
{
"cell_type": "code",
"source": [
"print(kmeans.cluster_centers_)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "uipKhQxjyGT-",
"outputId": "9b71d21c-2eab-4e5f-eaab-37f70256af4e"
},
"execution_count": 83,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[27. 56.65789474 49.13157895]\n",
" [41.68571429 88.22857143 17.28571429]\n",
" [32.69230769 86.53846154 82.12820513]\n",
" [56.15555556 53.37777778 49.08888889]\n",
" [44.14285714 25.14285714 19.52380952]\n",
" [25.27272727 25.72727273 79.36363636]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import plotly.graph_objs as go\n",
"import plotly.offline as py\n",
"\n",
"# =========================\n",
"# Ambil label & centroid\n",
"# =========================\n",
"labels3 = kmeans.labels_\n",
"centroids3 = kmeans.cluster_centers_\n",
"\n",
"df['ClusterMultiFeatures'] = labels3\n",
"\n",
"# =========================\n",
"# Trace data (titik cluster)\n",
"# =========================\n",
"trace_data = go.Scatter3d(\n",
" x=df['Age'],\n",
" y=df['Spending Score (1-100)'],\n",
" z=df['Annual Income (k$)'],\n",
" mode='markers',\n",
" marker=dict(\n",
" color=df['ClusterMultiFeatures'],\n",
" size=8,\n",
" colorscale='Viridis',\n",
" opacity=0.7\n",
" ),\n",
" name='Data Points'\n",
")\n",
"\n",
"# =========================\n",
"# Trace centroid\n",
"# =========================\n",
"trace_centroid = go.Scatter3d(\n",
" x=centroids3[:, 0], # Age\n",
" y=centroids3[:, 1], # Spending Score\n",
" z=centroids3[:, 2], # Annual Income\n",
" mode='markers+text',\n",
" marker=dict(\n",
" color='red',\n",
" size=14,\n",
" symbol='diamond'\n",
" ),\n",
" text=[f'C{i}' for i in range(len(centroids3))],\n",
" textposition='top center',\n",
" name='Centroids'\n",
")\n",
"\n",
"# =========================\n",
"# Layout\n",
"# =========================\n",
"layout = go.Layout(\n",
" title='3D Visualization of K-Means Clustering with Centroids',\n",
" scene=dict(\n",
" xaxis=dict(title='Age'),\n",
" yaxis=dict(title='Spending Score (1-100)'),\n",
" zaxis=dict(title='Annual Income (k$)')\n",
" ),\n",
" legend=dict(x=0.02, y=0.98)\n",
")\n",
"\n",
"# =========================\n",
"# Render\n",
"# =========================\n",
"fig = go.Figure(data=[trace_data, trace_centroid], layout=layout)\n",
"py.iplot(fig)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 542
},
"id": "6gR-Xa-YyKO6",
"outputId": "a414950b-a07e-4f8d-b151-6f9bf5a47894"
},
"execution_count": 84,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
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"\n",
"df = pd.DataFrame(kmeans_preds, columns=[\"cluster\"])\n",
"df.to_csv(\"23.11.5487_kmeans.csv\", index=False)\n"
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"outputs": []
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{
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" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
"\n",
"\n",
" <div id=\"df-e496587b-3005-4003-a72d-450bc993d6e9\">\n",
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e496587b-3005-4003-a72d-450bc993d6e9')\"\n",
" title=\"Suggest charts\"\n",
" style=\"display:none;\">\n",
"\n",
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <g>\n",
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
" --disabled-bg-color: #3B4455;\n",
" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
" box-shadow: none;\n",
" }\n",
"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
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" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
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" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
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" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
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" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
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" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
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"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-e496587b-3005-4003-a72d-450bc993d6e9 button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
" </div>\n",
"\n",
" </div>\n",
" </div>\n"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df",
"summary": "{\n \"name\": \"df\",\n \"rows\": 200,\n \"fields\": [\n {\n \"column\": \"cluster\",\n \"properties\": {\n \"dtype\": \"int32\",\n \"num_unique_values\": 6,\n \"samples\": [\n 4,\n 5,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 89
}
]
},
{
"cell_type": "code",
"source": [
"df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 423
},
"id": "9JP_qCGB0XeZ",
"outputId": "dadec45f-9747-4175-b361-c592889ed01d"
},
"execution_count": 90,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" cluster\n",
"0 4\n",
"1 5\n",
"2 4\n",
"3 5\n",
"4 4\n",
".. ...\n",
"195 2\n",
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"\n",
"[200 rows x 1 columns]"
],
"text/html": [
"\n",
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"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-85879e84-71b7-4f86-a54a-37f2d2347ba6');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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"\n",
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" title=\"Suggest charts\"\n",
" style=\"display:none;\">\n",
"\n",
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" width=\"24px\">\n",
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" </g>\n",
"</svg>\n",
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"\n",
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" .colab-df-quickchart {\n",
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" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
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" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
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" }\n",
"\n",
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" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
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" .colab-df-quickchart-complete:disabled:hover {\n",
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" fill: var(--disabled-fill-color);\n",
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" }\n",
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" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
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" let quickchartButtonEl =\n",
" document.querySelector('#df-23b94bc5-6bdf-4818-a9c5-b3460e55239e button');\n",
" quickchartButtonEl.style.display =\n",
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"\n",
" <div id=\"id_2be7f4b8-f694-4d4b-bf2f-8858a951ff65\">\n",
" <style>\n",
" .colab-df-generate {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
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" background-color: #E2EBFA;\n",
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" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-generate {\n",
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" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-generate:hover {\n",
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" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
" <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
" title=\"Generate code using this dataframe.\"\n",
" style=\"display:none;\">\n",
"\n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
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" </svg>\n",
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" <script>\n",
" (() => {\n",
" const buttonEl =\n",
" document.querySelector('#id_2be7f4b8-f694-4d4b-bf2f-8858a951ff65 button.colab-df-generate');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" buttonEl.onclick = () => {\n",
" google.colab.notebook.generateWithVariable('df');\n",
" }\n",
" })();\n",
" </script>\n",
" </div>\n",
"\n",
" </div>\n",
" </div>\n"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "dataframe",
"variable_name": "df",
"summary": "{\n \"name\": \"df\",\n \"rows\": 200,\n \"fields\": [\n {\n \"column\": \"cluster\",\n \"properties\": {\n \"dtype\": \"int32\",\n \"num_unique_values\": 6,\n \"samples\": [\n 4,\n 5,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 90
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "N6RDdOT31HJr"
},
"execution_count": null,
"outputs": []
}
]
}
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