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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Scaling Alternating Least Squares Using Apache SystemML"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Recommendation systems based on Alternating Least Squares (ALS) algorithm have gained popularity in recent years because, in general, they perform better as compared to content based approaches.\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"ALS is a matrix factorization algorithm, where a user-item matrix is factorized into two low-rank non-orthogonal matrices:\n",
"\n",
"$$R = U M$$\n",
"\n",
"The elements, $r_{ij}$, of matrix $R$ can represent, for example, ratings assigned to the $j$th movie by the $i$th user.\n",
"\n",
"This matrix factorization assumes that each user can be described by $k$ latent features. Similarly, each item/movie can also be represented by $k$ latent features. The user rating of a particular movie can thus be approximated by the product of two $k$-dimensional vectors:\n",
"\n",
"$$r_{ij} = {\\bf u}_i^T {\\bf m}_j$$\n",
"\n",
"The vectors ${\\bf u}_i$ are rows of $U$ and ${\\bf m}_j$'s are columns of $M$. These can be learned by minimizing the cost function:\n",
"\n",
"$$f(U, M) = \\sum_{i,j} \\left( r_{ij} - {\\bf u}_i^T {\\bf m}_j \\right)^2 = \\| R - UM \\|^2$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Regularized ALS\n",
"\n",
"In this notebook, we'll implement ALS algorithm with _weighted-$\\lambda$-regularization_ formulated by [Zhou _et_. _al_](https://liuxiaofei.com.cn/blog/wp-content/uploads/2014/01/netflix_aaim08submitted.pdf). The cost function with such regularization is:\n",
"\n",
"$$f(U, M) = \\sum_{i,j} I_{ij}\\left( r_{ij} - {\\bf u}_i^T {\\bf m}_j \\right)^2 + \\lambda \\left( \\sum_i n_{u_i} \\| {\\bf u}\\|_i^2 + \\sum_j n_{m_j} \\|{\\bf m}\\|_j^2 \\right)$$\n",
"\n",
"\n",
"Here, $\\lambda$ is the usual regularization parameter. $n_{u_i}$ and $n_{m_j}$ represent the number of ratings of user $i$ and movie $j$ respectively. $I_{ij}$ is an indicator variable such that $I_{ij} = 1$ if $r_{ij}$ exists and $I_{ij} = 0$ otherwise."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we fix ${\\bf m}_j$, we can determine ${\\bf u}_i$ by solving a regularized least squares problem:\n",
"\n",
"$$ \\frac{1}{2} \\frac{\\partial f}{\\partial {\\bf u}_i} = 0$$\n",
"\n",
"This gives the following matrix equation:\n",
"\n",
"$$\\left(M \\text{diag}({\\bf I}_i^T) M^{T} + \\lambda n_{u_i} E\\right) {\\bf u}_i = M {\\bf r}_i^T$$\n",
"\n",
"Here ${\\bf r}_i^T$ is the $i$th row of $R$. Similarly, ${\\bf I}_i$ the $i$th row of the matrix $I = [I_{ij}]$. Please see [Zhou _et_. _al_](https://liuxiaofei.com.cn/blog/wp-content/uploads/2014/01/netflix_aaim08submitted.pdf) for details."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reading Netflix Movie Ratings Data\n",
"\n",
"In this example, we'll use Netflix movie ratings. This data set can be downloaded from [here](http://academictorrents.com/details/9b13183dc4d60676b773c9e2cd6de5e5542cee9a). We'll use spark to read movie ratings data into a dataframe. The csv files have four columns: MovieID, UserID, Rating, Date."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from pyspark.sql import SparkSession\n",
"from pyspark.sql.types import *\n",
"from systemml import MLContext, dml\n",
"\n",
"spark = SparkSession\\\n",
" .builder\\\n",
" .appName(\"als-example\")\\\n",
" .getOrCreate()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"schema = StructType([StructField(\"movieId\", IntegerType(), True),\n",
" StructField(\"userId\", IntegerType(), True),\n",
" StructField(\"rating\", IntegerType(), True),\n",
" StructField(\"date\", StringType(), True)])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"+------+-------+------+\n",
"|userId|movieId|rating|\n",
"+------+-------+------+\n",
"| 53679| 5317| 4|\n",
"| 29545| 5317| 3|\n",
"| 41412| 5317| 3|\n",
"| 28213| 5317| 3|\n",
"| 30878| 5317| 3|\n",
"| 56069| 5317| 3|\n",
"| 49479| 5317| 4|\n",
"| 42362| 5317| 2|\n",
"| 43601| 5317| 4|\n",
"| 45276| 5317| 3|\n",
"+------+-------+------+\n",
"only showing top 10 rows\n",
"\n"
]
}
],
"source": [
"ratings = spark.read.csv(\"./netflix/training_set_normalized/mv_0*.txt\", schema = schema)\n",
"ratings = ratings.select('userId', 'movieId', 'rating')\n",
"ratings.show(10)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"+-------+------------------+------------------+------------------+\n",
"|summary| userId| movieId| rating|\n",
"+-------+------------------+------------------+------------------+\n",
"| count| 2268082| 2268082| 2268082|\n",
"| mean|30028.841485008037| 9068.777048625227|3.6134694424628386|\n",
"| stddev| 17290.49124532639|5131.8304910232055|1.0810520483121464|\n",
"| min| 6| 1| 1|\n",
"| max| 59999| 17770| 5|\n",
"+-------+------------------+------------------+------------------+\n",
"\n"
]
}
],
"source": [
"ratings.describe().show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### ALS implementation using DML\n",
"\n",
"The following script implements the regularized ALS algorithm as described above. One thing to note here is that we remove empty rows/columns from the rating matrix before running the algorithm. We'll add back the zero rows and columns to matrices $U$ and $M$ after the algorithm converges."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#-----------------------------------------------------------------\n",
"# Create kernel in SystemML's DSL using the R-like syntax for ALS\n",
"# Algorithms available at : https://systemml.apache.org/algorithms\n",
"# Below algorithm based on ALS-CG.dml\n",
"#-----------------------------------------------------------------\n",
"als_dml = \\\n",
"\"\"\"\n",
"# Default values of some parameters\n",
"r = rank\n",
"max_iter = 50\n",
"check = TRUE\n",
"thr = 0.01\n",
"\n",
"R = table(X[,1], X[,2], X[,3])\n",
"\n",
"# check the input matrix R, if some rows or columns contain only zeros remove them from R\n",
"R_nonzero_ind = R != 0;\n",
"row_nonzeros = rowSums(R_nonzero_ind);\n",
"col_nonzeros = t(colSums (R_nonzero_ind));\n",
"orig_nonzero_rows_ind = row_nonzeros != 0;\n",
"orig_nonzero_cols_ind = col_nonzeros != 0;\n",
"num_zero_rows = nrow(R) - sum(orig_nonzero_rows_ind);\n",
"num_zero_cols = ncol(R) - sum(orig_nonzero_cols_ind);\n",
"if (num_zero_rows > 0) {\n",
" print(\"Matrix R contains empty rows! These rows will be removed.\");\n",
" R = removeEmpty(target = R, margin = \"rows\");\n",
"}\n",
"if (num_zero_cols > 0) {\n",
" print (\"Matrix R contains empty columns! These columns will be removed.\");\n",
" R = removeEmpty(target = R, margin = \"cols\");\n",
"}\n",
"if (num_zero_rows > 0 | num_zero_cols > 0) {\n",
" print(\"Recomputing nonzero rows and columns!\");\n",
" R_nonzero_ind = R != 0;\n",
" row_nonzeros = rowSums(R_nonzero_ind);\n",
" col_nonzeros = t(colSums (R_nonzero_ind));\n",
"}\n",
"\n",
"###### MAIN PART ######\n",
"\n",
"m = nrow(R);\n",
"n = ncol(R);\n",
"\n",
"# initializing factor matrices\n",
"U = rand(rows = m, cols = r, min = -0.5, max = 0.5);\n",
"M = rand(rows = n, cols = r, min = -0.5, max = 0.5);\n",
"\n",
"# initializing transformed matrices\n",
"Rt = t(R);\n",
"\n",
"\n",
"loss = matrix(0, rows=max_iter+1, cols=1)\n",
"if (check) {\n",
" loss[1,] = sum(R_nonzero_ind * (R - (U %*% t(M)))^2) + lambda * (sum((U^2) * row_nonzeros) +\n",
" sum((M^2) * col_nonzeros));\n",
" print(\"----- Initial train loss: \" + toString(loss[1,1]) + \" -----\");\n",
"}\n",
"\n",
"lambda_I = diag (matrix (lambda, rows = r, cols = 1));\n",
"it = 0;\n",
"converged = FALSE;\n",
"while ((it < max_iter) & (!converged)) {\n",
" it = it + 1;\n",
" # keep M fixed and update U\n",
" parfor (i in 1:m) {\n",
" M_nonzero_ind = t(R[i,] != 0);\n",
" M_nonzero = removeEmpty(target=M * M_nonzero_ind, margin=\"rows\");\n",
" A1 = (t(M_nonzero) %*% M_nonzero) + (as.scalar(row_nonzeros[i,1]) * lambda_I); # coefficient matrix\n",
" U[i,] = t(solve(A1, t(R[i,] %*% M)));\n",
" }\n",
"\n",
" # keep U fixed and update M\n",
" parfor (j in 1:n) {\n",
" U_nonzero_ind = t(Rt[j,] != 0)\n",
" U_nonzero = removeEmpty(target=U * U_nonzero_ind, margin=\"rows\");\n",
" A2 = (t(U_nonzero) %*% U_nonzero) + (as.scalar(col_nonzeros[j,1]) * lambda_I); # coefficient matrix\n",
" M[j,] = t(solve(A2, t(Rt[j,] %*% U)));\n",
" }\n",
"\n",
" # check for convergence\n",
" if (check) {\n",
" loss_init = as.scalar(loss[it,1])\n",
" loss_cur = sum(R_nonzero_ind * (R - (U %*% t(M)))^2) + lambda * (sum((U^2) * row_nonzeros) +\n",
" sum((M^2) * col_nonzeros));\n",
" loss_dec = (loss_init - loss_cur) / loss_init;\n",
" print(\"Train loss at iteration (M) \" + it + \": \" + loss_cur + \" loss-dec \" + loss_dec);\n",
" if (loss_dec >= 0 & loss_dec < thr | loss_init == 0) {\n",
" print(\"----- ALS converged after \" + it + \" iterations!\");\n",
" converged = TRUE;\n",
" }\n",
" loss[it+1,1] = loss_cur\n",
" }\n",
"} # end of while loop\n",
"\n",
"loss = loss[1:it+1,1]\n",
"if (check) {\n",
" print(\"----- Final train loss: \" + toString(loss[it+1,1]) + \" -----\");\n",
"}\n",
"\n",
"if (!converged) {\n",
" print(\"Max iteration achieved but not converged!\");\n",
"}\n",
"\n",
"# inject 0s in U if original R had empty rows\n",
"if (num_zero_rows > 0) {\n",
" U = removeEmpty(target = diag(orig_nonzero_rows_ind), margin = \"cols\") %*% U;\n",
"}\n",
"# inject 0s in R if original V had empty rows\n",
"if (num_zero_cols > 0) {\n",
" M = removeEmpty(target = diag(orig_nonzero_cols_ind), margin = \"cols\") %*% M;\n",
"}\n",
"M = t(M);\n",
"\"\"\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Running the Algorithm\n",
"\n",
"We'll first create an MLContext object which is the entry point for SystemML. Inputs and outputs are defined through a dml function."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"ml = MLContext(sc)\n",
"\n",
"# Define input/output variables for DML script\n",
"alsScript = dml(als_dml).input(\"X\", ratings) \\\n",
" .input(\"lambda\", 0.01) \\\n",
" .input(\"rank\", 100) \\\n",
" .output(\"U\", \"M\", \"loss\")\n",
"\n",
"# Execute script\n",
"res = ml.execute(alsScript)\n",
"U, M, loss = res.get('U','M', \"loss\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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OnEp1HYIVY/o/o/Q5EHgCuAtYnZk3NVizJEmaB41cp+CHTHHWQmaeMu75xcDF9UuTJEkL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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f75adcc9908>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"plt.plot(loss.toNumPy(), 'o');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Predictions\n",
"\n",
"\n",
"Once $U$ and $M$ are learned from the data, we can recommend movies for any users. If $U'$ represent the users for which we seek recommendations, we first obtain the predicted ratings for all the movies by users in $U'$:\n",
"\n",
"$$R' = U' M$$\n",
"\n",
"Finally, we sort the ratings for each user and present the top 5 movies with highest predicted ratings. The following dml script implements this. Since we're using very low rank in this example, these recommendations are not meaningful."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"predict_dml = \\\n",
"\"\"\"\n",
"R = table(R[,1], R[,2], R[,3])\n",
"K = 5\n",
"Rrows = nrow(R);\n",
"Rcols = ncol(R);\n",
"\n",
"zero_cols_ind = (colSums(M != 0)) == 0;\n",
"K = min(Rcols - sum(zero_cols_ind), K);\n",
"\n",
"n = nrow(X);\n",
"\n",
"Urows = nrow(U);\n",
"Mcols = ncol(M);\n",
"\n",
"X_user_max = max(X[,1]);\n",
"\n",
"if (X_user_max > Rrows) {\n",
"\tstop(\"Predictions cannot be provided. Maximum user-id exceeds the number of rows of R.\");\n",
"}\n",
"if (Urows != Rrows | Mcols != Rcols) {\n",
"\tstop(\"Number of rows of U (columns of M) does not match the number of rows (column) of R.\");\n",
"}\n",
"\n",
"# creats projection matrix to select users\n",
"s = seq(1, n);\n",
"ones = matrix(1, rows = n, cols = 1);\n",
"P = table(s, X[,1], ones, n, Urows);\n",
"\n",
"\n",
"# selects users from factor U\n",
"U_prime = P %*% U;\n",
"\n",
"# calculate rating matrix for selected users\n",
"R_prime = U_prime %*% M;\n",
"\n",
"# selects users from original R\n",
"R_users = P %*% R;\n",
"\n",
"# create indictor matrix to remove existing ratings for given users\n",
"I = R_users == 0;\n",
"\n",
"# removes already recommended items and creating user2item matrix\n",
"R_prime = R_prime * I;\n",
"\n",
"# stores sorted movies for selected users \n",
"R_top_indices = matrix(0, rows = nrow (R_prime), cols = K);\n",
"R_top_values = matrix(0, rows = nrow (R_prime), cols = K);\n",
"\n",
"# a large number to mask the max ratings\n",
"range = max(R_prime) - min(R_prime) + 1;\n",
"\n",
"# uses rowIndexMax/rowMaxs to update kth ratings\n",
"for (i in 1:K){\n",
"\trowIndexMax = rowIndexMax(R_prime);\n",
"\trowMaxs = rowMaxs(R_prime);\n",
"\tR_top_indices[,i] = rowIndexMax;\n",
"\tR_top_values[,i] = rowMaxs;\n",
"\tR_prime = R_prime - range * table(seq (1, nrow(R_prime), 1), rowIndexMax, nrow(R_prime), ncol(R_prime));\n",
"}\n",
"\n",
"R_top_indices = R_top_indices * (R_top_values > 0);\n",
"\n",
"# cbind users as a first column\n",
"R_top_indices = cbind(X[,1], R_top_indices);\n",
"R_top_values = cbind(X[,1], R_top_values);\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# user for which we want to recommend movies\n",
"ids = [116,126,130,131,133,142,149,158,164,168,169,177,178,183,188,189,192,195,199,201,215,231,242,247,248,\n",
" 250,261,265,266,267,268,283,291,296,298,299,301,302,304,305,307,308,310,312,314,330,331,333,352,358,363,\n",
" 368,369,379,383,384,385,392,413,416,424,437,439,440,442,453,462,466,470,471,477,478,479,481,485,490,491]\n",
"\n",
"users = spark.createDataFrame([[i] for i in ids])\n",
"\n",
"predScript = dml(predict_dml).input(\"R\", ratings) \\\n",
" .input(\"X\", users) \\\n",
" .input(\"U\", U) \\\n",
" .input(\"M\", M) \\\n",
" .output(\"R_top_indices\")\n",
"\n",
"pred = ml.execute(predScript).get(\"R_top_indices\")\n",
"\n",
"pred = pred.toNumPy()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Just for Fun!\n",
"\n",
"Once we have the movie recommendations, we can show the movie posters for those recommendations. We'll fetch these movie poster from wikipedia. If movie page doesn't exist on wikipedia, we'll just list the movie title."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"titles = pd.read_csv(\"./netflix/movie_titles.csv\", header=None, sep=';', names=['movieID', 'year', 'title'])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import re\n",
"import wikipedia as wiki\n",
"from bs4 import BeautifulSoup as bs\n",
"import requests as rq\n",
"from IPython.core.display import Image, display"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def get_poster(title):\n",
" if title.endswith('Bonus Material'):\n",
" title = title.strip('Bonus Material')\n",
" \n",
" title = re.sub(r'[^\\w\\s]','',title)\n",
" matches = wiki.search(title)\n",
" if matches is None:\n",
" return\n",
" film = [s for s in matches if 'film)' in s]\n",
" film = film[0] if len(film) > 0 else matches[0]\n",
"\n",
" try:\n",
" url = wiki.page(film).url\n",
" except:\n",
" return\n",
"\n",
" html = rq.get(url)\n",
" if html.status_code == 200:\n",
" soup = bs(html.content, 'html.parser')\n",
" infobox = soup.find('table', class_=\"infobox\")\n",
" if (infobox):\n",
" img = infobox.find('img')\n",
" if img:\n",
" display(Image('http:' + img['src']))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"def show_recommendations(userId, preds):\n",
" for row in preds:\n",
" if int(row[0]) == userId:\n",
" print(\"\\nrecommendations for userId\", int(row[0]) )\n",
" for title in titles.title[row[1:]].values:\n",
" print(title)\n",
" get_poster(title)\n",
" break"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"recommendations for userId 192\n",
"Vampire in Brooklyn\n"
]
},
{
"data": {
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TClPFud1NFk01dKSlZPaKEKTZL9r/AM8VCsZZFj1Im5Y6zYdL/wCvcjFo8AZB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\ndQaeSuaJkAZi7EIoKgrdhe1wVsDgdl9ZNQVCz0rhJh0bTcj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"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Jack and Sarah\n"
]
},
{
"data": {
"image/jpeg": 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Ey6gdX4vLfkSPzxyTL6eRZFWRInLsQ/eC1/XzBJ6dMXSJ5MmMszDNazMK+M1k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\npKzwyEHVS05It3gHvSi+gWt4uVvyPh3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"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Damn Yankees\n"
]
},
{
"data": {
"image/jpeg": 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MP89dRERJLNTyJKu4DhrqOlxa/NzbjriJ6yiJzUTxtdZ4I2jYE/KXz/YMWcKj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\nb0cT0gliEjNuNgkhKWtxfqcTWn1DpiWEVKiBKcyExTPTFRI2zexXw34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"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"A Doll's House\n"
]
},
{
"data": {
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rY7V7Cl8/yqL+lpoVna7BplAz+/Q+fX61NNALRjJ650Bg7kZxvg+Y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\nPn5E6uOrPNMTgu4aOD7A0vetbg8ph93Z2lcs8XK6FGOdwVdgfUY9NL6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"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"The Sandlot\n"
]
},
{
"data": {
"image/jpeg": 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CuRuGSxODggHGfxPHpmkXZtmjdjll8xWTAbAYoWkI53BFIwnDbuScYrTH5TgO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SzWsM\nep3d6fKtpAPtMkNjFuV55P3g822jjVMZJavOEtPE3g+7S38S6Bovn2soWEpJHqtmbKOR4jt86A3D\nIQoMyGPcyeWBh8k/0RyTrcJMHRXidwr7gyyEjIypYMx7HAwjccECvn/4r/Ay28aaPJ/Z1rZSXZDu\nbhNPtY5keNlJysds7+cqDak6JuYncSzfMP5i8RvBWpk+VRxvDc81zyjh1KWJw2JVCpjLLmlenOg4\nqUYRScl7GUuibZ/VPh149184zSGA4pllmXqraNCrh4SwuGhK1KMIcspTpw5pOTU51XF67K0T8iLD\nxHo9zqMd3op04a/czR/aLd7W5stPCQq2TbRakVhWR1YLIu2E/KXjVhtFdF/xUTfMNZji3fN5SC5d\nI887FcXgDqn3VYABgAQADW14y+Fj+CL27tLmGwuczeW63ons5ln3q5keT7RbTPJDGZHWUkxshKKh\nJxXIgwxARC3RxH+7DpcW7IwT5dysxLMrYyrMSSCCTmv5VrU1Kcko1aLhOUJQrqLnCUWoyh70YaRk\nrbXfVa2P66wuPpSpRqwnTnCoouE7xlGULQknFqUU73d2m09Nlv8A1eeDvgf4s8apHcW62mj6XJ5f\nn6vqzuI4l2qxEFsALi9f5iABsUngSCvoGx0L4V/B5InaKHxRrwCLNqupW8V35U8a4kOmaaxaC2R5\nQqo0nnSqFAMgwd3z94k/aDuVtksrKWK3SNEgWOOdrZI4tq5EEUZCeZOVfa5YYiVjGAWNfNWv/EfU\nr+5mlM7uk6yKGVjJsZwrRBPnzgJhmjToDuYsxOP0njr6SOd5/R+qZcv7PwziuTD4NqMYxXLaNarG\nnSVSb15kuVW0sk0fzjwJ9GbC5dU+uZ3OE5xvPnqRjOtUqNL4IxbVKF7KK5bWbu5an1B49+Puraxe\nNA99PFbOwWO1t2jjL2sY2orOCGjDMRmJFClBzu4FfPetePpblrlGuDjyY41hLFUiflmYq7Zwy4ST\nLsxOXP3tteKaj4oL3KyFPOMasoJkYqNwbqu0B23BSGY/KoVV6E1yl/rFxcRT4QseQnz7gZiu5y8f\nIjXy84Ock4Hymv50xvEGZ5rVq1cTUrzc5SlKV73clrd8t7aXSlsf1RlHDWTZHRpUcDgcPRdOCgpx\nhDmktNbpbvT77evpV94mEkmZWxu/0i3aQkSQIGIDBV+8hAKqHGPLO4nOK4HUNbnkRpMsqTouxVUB\nlj3lg3mv0XdIFG0gleTurlpLqNWecux+URxxbjgqIxHGB83CuTja57nFZcuoed9mtS48slo3ky2A\nBtcKUwEZFIKMSMgcA+nkU5VWnzR5tuaq433tZKOjf+K+nVNHtckU04pJLonZLVPz/pl2W7lkMlod\nsmzcZl3eWdys2cbAd23K5cHGMhulRPcQ2om+dXWSb5FUCQ7QqlkU/KSpYYVgMkhicis97oGN2g2r\nIsZMjDhd0Tk8SbQQsjNlv4cHac8Y838ReMYNKs3nuJreOOJWZiZFBjdMgyROSuACDuUYOCedpJrS\nlTkqzc+WfNdXjHSOuqvok2m3v03eoTnywd7JSaV17zvo0kla77LS+19r9brHiGK0iJaSIxRFmcow\nXATgEjIV0zwQMsjA54rwu31vxZ8U/FsvgT4bWH23UxEZNX1yZ2XQfCunyzGOa/1a8ijdYywz9lsI\ni17fuoit0wGkWPwH4L8fftF6hcXWkSXfhj4W2cptNY8dyQ7m1CQDN1pvhG2lZU1W+AGya+BXTNO3\n7riaeULat+hvgTwH4b+HegQ+EvB+lx6NpETefNMqhtS1S9YMsmpa1fY87UNQmGCZ5iFijPkwRwwj\nZX9P+Dv0esz42lRz7ilVco4TinVoU3+7zPOlGSlThhYu0MLhZwTnVx8pSlGL/wBjp1a0UfzN4xfS\nEyngeOJ4f4adDOOLZ01Sq8kubLcjUvelVx9WPMsRjIv+HllJOEZxaxtWnBu/J/Cv4W+FvhHp89tp\nUz6x4l1SKI+JfFupIn9p6xcRMrCFRECunaMjfPaaVbFVUbZbtri5zIPXQ+JEYOx3MSHIBVixVcRq\nBnau5wAOg4O7ms82V2CWKEMjsHxt5jCFg7nOWJwgC4+YNjPXNqGC4luLUJGWjPmH5g2CCCWTcONo\nA5Ubdo9BzX+heW5NlmS5dhMpyfCYfLsrwFFUsLgsPGNOlTirOU3FNuVarpKvWblUrTvUqSnOUpP/\nADrzbNs0z7M8XnGdY6vmWaY+o6uKxmJmqlapP3VGCaSjGlSXu0acEoU4WhCMYRilchuzZ3UU/mZM\nZSYhlUkuJAYyQV+ZQyq21yQVyGBUkV+LX7T37IP7I9l4n8SXXiP9qT4+/Cz4aaD4g8Z+M9W+Cnw4\n+GXgXX9ItvGXiFR4q8S6b4c+IniLVt2nJrGpX1rb6XpGp+GdSbQReTWsEt5YWqsn7P3un3MZDiL7\n6Aoi5VO+1s7iGPykHuMEL0BH49/8FDv2O9P1PR/iD+0FB+0lrnwe8Maldadrnjz4fXHg1vGul+If\nHS6XFoGm6p4Wmg8QaNPpB1QwadJ4h02+S8tYkiu9S0r/AEudbM/mvjDlGYZpwnDEYCOAayfGSzHH\n1cXCm6lHL1hq1OrPCympSk3iY4WnUpQ5OaNS3NeST/ZPAPOMLl3GiyzMMTm9D+3qOGy3LcLlblH6\n7mdTMMPyU66acI1I4SOMeHqzSp0/3sqs6atKX5w/AbwB8Nm1TxV4t13Udd1q1sbyOx0jR9bmtbjU\nZbG/e5FidXs9I/s7SLqSC2ggGolIvsE9wd628cZEa9l4x+D/AMOPiR4g+I+s+BFu7WysPh5pt/de\nFovLOh6X4hku5kn1DTdPBn8n7RBZBGt4pks41jaZEG7bXinwn0Pwd4Z8Ga58QPEPxY8Rv4ng0pJ9\nCk0oafbeHrO5C3BuIdS0O5hni1NJmWNZLfUizxA5VEYsR+kX7Mfwc1b4f/C/WfiV4s13+2/EnxZ8\nI6Nr2oRNplvolnDZzWU93b6K+kRNF9mhb7XEzR2ZZJy0ckQVvMx/n3xBj62WYvF5rSxmIljfrFPD\nYWlKOJw8a8ouNWrCKpw5IKNNNuU007cq1ul/plOhGWBo0auDnSp4yEVTjWxirVo04Wi414xnUTbS\navCTimt72Pwh8C/Fq/8Ahl8QNR+GuvXLW80cjL4fvGJeG4tNiSyaexLZjvLeKXFvtDK0agAB1xX6\nG+DfihPLYWqSfaCs8fmErLslAVlIeNlfeHlX5CpBY8ttya+IvjD8JNO8XftK6TcXDx6eINN1DxPZ\naTGyxi/kiv7KOa3tXn/fS/uLqR7eIsDGqRorZ5r648EfCvU9Nvre2Wx13VdNkjdrTU0uI2i2f69r\nORUZH+1QDMZVGEwZBktnn73Oq+U4rA5bi4U+TH4zLcJicTRULU413C1Tkm9Hblu7ebV73Ph+GsPn\ndHEcQ5fmKo1suyvOsXQynGKqpVqmCkqFanTxMVaUalN1bU+a/wC75WrbH1F4P8b3Mt6Lae2kulEa\nQeQ0q7IRLJ5nmXEcwZy8ShD5m3cCrEABdtfbXws8SDSryy1OykbSNRktQt2IHNzaapaxbSsWpWre\nXHdw4K+TOwS5tjuaCSMEofz8s9XufCN7HaxWXlSOVi8prKGOSPoybndndGCnezOSGcMWC5IPso8Q\nXsFhBfWmp+fexor3EayRE5COkTbo1eSJVVi5RsRuMAckAfnX1rMMpzXBZvk+MxOXZhhKqrYPG4Ov\nLD4ihUco2lTqxkvZN8qjJw5HOPuTk46H1Oa5Hl+c5PicszXA4HMsux2Hlh8bg8bh1icJXwtS3tad\nWhJSjUjJxi+eMXXpShGeGnTqXkfrP4e8deH9XuI7K3vBYX8gwlndSrFDcvlWdbS7JWKUys+I4GMU\n+75VSXG49zbai8E7qYCkoXdO0u7AAfa20cMZOo9u/pX4x6N8RtaXeL90lQ+cziST99NHEIyzLtYq\nFDEmA8NG3cV9pfDD433VnBZ2mu/aNe0kRRQRyiRX1mwyRIGiuXcNqMMSNzbXLiZY13xS4ZVr+wfD\nr6TEK06OSeJWHo4etOMKOG4syykqWDnVtCKWb5ZGNGnh5TWk8ZgZShKreriKVpzqw/h7xP8AorYj\nBUq+feGNerXoLnr4rhLMJ1amJpwsnJ5PmM3OriYwSThgsalUUE6eHqXhClP7ygvI7hBvRpF2xkAh\nSVVcgEsACWIxuGd2Mj2rQto1eQK42tu75LKg/ujhTs+VkzkgHBJIrjdAvtN1qy/tPSdRt9QsHG3z\noJHLwSldxiuISRLa3iDPmQTJHKpHQqwY9jp5+dFMm9CGAd2U7vkUMGzk/MMkn+EjjHUf1Xz4fEYe\nhjMFVo4rC4qlGth8Th5xqYfE0pQjJVKM4ylGolFrncHK19bH8jRhicNWr4PG4etg8Xgqro4rC4mn\nUpV8PUpy5HGtTqRjOnzNPlU4xvZ2uS3UCNIyqqSFHADkFi0nIPmDb8vy7jktgHr2rEaCQRbin7mM\n5bHzgOGDc8AgnAAywH8JFdPPtWGNlZgGaNgdwKE7ShBC8hTkEsQT/EPWsiebzEZcLGGkyzoCiBt2\n3dgk7gGHOR82T0yKwg3dKKcrtbJu17dvJdfy23nuvQy5ljdQGXbwX2qrHzjuGwN5a4XDAgbcdMZP\nWs1IFSVAfKdAN+zaTtYE5VicFm/hbIyBgHIrWeCUGKYOXkIclRIcEE/MeoAKkqIlBBUbycnmqDo4\nlPngxSLIyqMj5mK/xEcNkY5449+a1krJ3XT9CVuvVfmVja75ndSXUMZSdwB3/wCrCJwCUPTg/KVH\nUVrQQvFtlUOMbmO0/Mw/jAVsEYPRV5bkjIwBUikYjDmNQgbeS6jHQqowFJBJBztPPfvWmkxITG1J\nDhvvMVbJLHnn5flxwOPSuKad3daO3Vqz01umrPs2erQoy05bcjipy5rOT5lZx10ceuqehzviTwh4\nW8YWiQeJPDun6q4DKs9xZwG4WOSPa8X2loWm2vvA3KQ6E4DKM58Of9ln4TF3I00RgsxCCztyEBJI\nQEtkhegJ5OK+jS2Jo/MljIy4Jy5CbuAGOQw+YZCkLkjg0hXk/Ijcn5tr/N/tff79a/PuJfDjhHiT\nEUsZmWT0J4pKSniMPClhpVryi71o0qcYVJxf23HnafvN3Vvv8g444myChLC4DNMTDDPl5KOIr168\nKSj9mi6lVyhF3fuKTjGyUYxtr4Jf+LLuRjM7yBhDEBCSZtwKNCoYDIUuil3ZiNq9Nm7nEfxRJOBG\nspht9xVGO6MurDZLKSAcsGO7nGYgEVlA58zGpsXbAf8Ae2vlx/K+xwqAqyDliQdrN67TyRWtby27\nmFY3Bjt/LVncEbnZV+ZAQAwb94zbW3JwgG75a/x4ws5ySbhBc2j5Jc/M776XtZ+uz2uf62TjGELr\ndW8r7LVddPu6HTNqd3sgWWZx5gkZWUr+5SPdKXmIIO2QBTGCoJdyOwqtFqs5j864ndRK0izIqkeU\n5jaMF35Ein5SeBuJHJAIrmtQnaOU2cuZFlU5aVlR2YM0ituU/JtztRWbgDpWZcXdxAAVKPLOsZLZ\naRvLCkE4Yt8ylSRg/NnJzXoxejTk4303VtrLfTfTfYyktnZO2776K17d+ivc6eTVjIsR3uWyEEUc\nfBQqT5kgQEeZkFozj72F7c1nuvIjlufNeSNcFo5ZFEjAKomVFAJUEnp0Oew4rlr/AFaO1YTFTD5S\nJOXLA7pVXCnywQzBj8wRQxI+b7ozXgPjr4v6bpCyh7pxNHFJIyg+Ud0iuW3yHooCkkKG2DBIxXoY\nPC1qzhRo01Vbu5NN+4k4+T0e6Wnc5a2Kp0otu0WuVtPs5KF97pczs3fdq73Z694u+JOl+H9Pvbme\n7jt2TdJL5o2pbxiNBtfBX5SimQ7cjoOtdx+zl+yz4k/aXuYfip8X4NQ8KfA+OZLnw54YP2nTvEXx\nUEBXE8bZSXR/ApcBbnUwPtmvqTbaX5dqZ70Uv2Tf2UtT+MdzYfHL4+6dd2fw4SaK++Hnww1COWF/\nHUtvIJLbxL4otXxcxeEVlhSbTtLlEcviFszzKmlbUuv18uNdkPyKgMEcEVvHBEixW9vbwKkcMVtF\nGqpbwQwxpDFDGixRxIqqiquB/Yngz4ExrrC8VcWYeLpStWyrJ6yq2ruS/d4jHQtFLDtcrhTqL96u\nZ83KpJ/xl41ePssJWxnCfB2KmsTJexzXPMPO0cNByXPhMBUhU/3mNpKrVXNyaRcbuLWXJ4V0iwsL\nHStI0qw0fR9Kto9N0vStOsYbHTLGztV/c2dnaW6LDFDEjLhY1OTlndpCzNkJ4bh8xiIQqjkZxtZw\nSR2zyO3OOhx0q9c68zyZAbbKpwrMQsJwGKAFuuRgY2+nHWs7+2DI+SI8ndJ5QfYyAcIyds8biAfv\nHJzX9m0sLi6dKFOM4whSpxp0qSioxp0qceWnSppRXJTpp2hTi+SCdoxifxdVxmHqTnVqU51K1SpK\nrUquTc6tWq1KdWrKUnz1Zyu5za56k9ZybtbobXw3Ys0BuERv4tvlxqSApbEgAwxl4G/Pyj5eCcC8\nPC1khJEOyWRpH/dIqhNucRhMswXZlXxyRnHBNcyNWlQxlWIDMgyW+YAKW6ZyQAA/BHTI5q++v3hZ\n/nO37om84/MXGHCknoVGcY6YIFc86OMho6k2mne0p7dn73W+q7FxxNCctaMYLvyq8W+qV2nZdNNe\n2pV13SrdMrhCjAHaVVfLwpJBVDgDBIAfnJINfNnx8/Zy8IftK/CnxJ8IvFs2tabputNbXumeJfDq\nxvqXhvxHpjmbSdXt45o3sL5LZpJIb7TNRYWt9ZT3ETPDL5VzD9g/Drw23xE8SvZ3ks1v4c0W1XVf\nE2owZDxWEMqrHYW0mMC+1Wb/AES3OC8SNNdKG8glfrs/DvQtXgttV1qyt9J8NaZEJtK0SFfs+lQW\n8X3DPCx3Xc5i/eXEtwJZLhwXkdmYkfnXH3HFHhmC4feV08/xWPoReNwGJxLw+AoYGtG98VVo/wC0\nRU20/dspq3vxklb9G8PuG8Rm2Kw/ECzbE8O4fLMZCpgszy/BxxOZ1Mfh5J0oYGhWUsO5ucm5ylzx\nirx5Hex/I94C/wCCFP7R/iX4mpot/wDEXwLqvwGsNmq6V48sNGvtBtbZIjuvG8baRe3N5BNqdnco\n7Qabo19rlrqkTJ5U6KZvI/ZS0/Y/+Buj6e3hTVvGfi7xnp2mabYeH5dUtZh4T0e4isoTBGtnpFq1\n4VVQXNuJrqaQJsOV27R9g/GX4yR6nCvhXwsFt/D1tstZJrKNrZbpkXaqhIlHk2qlRueQENwMYPPz\nPLc31ykFpIFijuLhvKtiDNbiQ8+eGAxu5JDEHa2duOlfwrxRWyvG5tUqQwdCu1WlKMIzxUcDgotR\nTwuXxqVXWnGMtatbF1sZUm3pVUW4n+g/Dn+tWNwOFxOf5niaX7mMcLh5RwqzDEWlGr/aOYYqhRUI\n4mor8uFwtHBYenFyUsNOT5z8b/2sP+CXv7Ouq+MtH8WfCXxn8TfB/jrw3Z6ivhi4ufFdr4i0nz5Q\nkiWes6bqmnk3unzTxRNJDBeWN7DaiUWlyHCV8f8Aw8+I+p+FbrU/h9420xNG8ZeE9SfS9f05guyO\n8AVv7Us5FaKK6tL+2aLUNOvMqbu3kjlDbxKi/wBGHjT4H2XiXSbybTvEFjpuoQK15Jf35Kw208cY\n2FpUXzkkxlFcL5ZBIccCv53f2qfgz8dfiH8UPDt/8DvhtqHxS+JmmaJrqa5b+EbvSLfT/F/g3wzf\nRJHeLq+salpWl2mr6FNeG3s7DUr6G61CO8jtNOW4DW8YzyzC5jn2OwmQ1ZTrzxdOdDKaNJ89ajUp\nJVKWHoRpRc3TqPmspJ+8nb+U+rpZlkXD2CzDM8bWpYfBUowxGd47F1Y0YJxo0qP1uvVrTVOM40qE\nXUlpdRbaSuzlfGWpef4hn1u2ZdYt41iBt5ybbe0S+X5kVyG/dz+WS2PnRyfnOOTJ4d+Ifh65kngk\nRtL1aQxwoNRMWySHzAGLeUpjcNgwiSLIAO3CluPnHxp4a/aw8D6bJrXxG/Zp/aA8D6BFcSNfanqX\nw51q70uzmhQFmurvQ01eOK1CqzG8fbYyIpZbjByIvBHxK8H+MrNdxsNQdkMayWssYMBIdZnhlTJg\nkR8edGCCj48xVJyPfxvCmZ5ZTo0s0wWJoVLLkdSlVpOUXLSSVSklO/xL3rO1vXbK+KchzqMpZLm2\nV5xQjK0qmWY/B4tUovlf76GHr1JUrKWrmoq+m6Z9bwWlzJMrxB7domkkjwD9ncu2UiiBbaokDA/N\nnevBxjNdFo2u6po8reck0UhDRIRMwgihgIwpG7O9cExAHYxwuWHFeUeDtfvNHMKwXUGradMu1ILt\nhNMUchVZXy5Xy9m3JYLIoUIBivbNCuNP1TzHk2adczJg2UxF5ZTL5nyCMYaSG4DYZTkKW64r47GR\nq0ZyhVpJ01JKN5OM3qrO263+FK297tNL2JzpypuUKfNeLeiumtPeWlmt1dXV09T6L+GXxm1HS9VW\nXS7+G1kkdVmlDbra7jkdhJBqdqw8q6XahLPtEkZYmJ1JzX354M+KekeJBZw3SRaJq8sDMqNJjTb2\nR8BWsbqVsRsw5WC72OclUeXgH8qIvCs1mYrrTJ4fnzvRFgmI2/MxyoJVjklCflBG1juFezeGNV1G\nCXy7x5JokhVSzKqHKEhTsbbGy/xKTkq/MeD0++8PfF7ivw3q08PldaGZ5BUlL63w5mXtZ4Wo04vn\nweISvlVRRWn1WVKFaX8WlN81/wAW8SPBzg3xKpSxOY4OplufQhbDcR5bGnTzCk+SSisZSqWo5rh+\nZ3cMTGriKd2qNWC5FD9PmmlE8UZhcMSu5QuOGVcPtPGQPmHAPA49azMV2EFmALsUZ8FmVgQxVSCM\nLyw3c18z+E/ibq2jiC3lWTWdJjKE2l3MWu7cJne2n6iwZypGCttc+ZASAqNDjJ920DxXo/im2afS\nJ8zwf6/TLlRb6hal85E1tITKY8DAmjMkR4AfPy1/dfAPi3wd4jRpUssrvLs6dJOvw9j5cmPjNJX+\nqT93D5hTu372HftlBLnpQnekv4I8Q/CHjXw2qyq5rhP7UyBTaw/EWVwdfBum5S5fr9CPPissq8qT\naxMfYubkoVqkEqkumZwFiPzTeYsr7iCqISeEjBY9cbTkHGOcYqnJJ5iADcPlBk3PwHXIbClQW54Y\ng456YBFNlnICbdvQ7VBKKFJw5kyoJ2sSFUruDANntVeCRpZjuYsr7lYlsCJmQDAXAbhkLDGeQMkg\nmv0+VPf3btLbW3azTt2s15NPZpflsa0JOydmvsydqi0Tu42ut01e2g1naSNHhwkZkZwHzI6lMBVU\nnjjC7uCO+OKvwvO371wjYBLc4VnTC7YyOhYYYjndgYxmqsETgR5chcybQseQQy43Aqcgg5I6bjkn\ntQu5J5VJZnEe4KAAQqjaJWGNo3A4IHTk85riqJOTjypWsny6Xff/AIY74VJQirN2cbNbu2llG1rd\nrtu2uj6WdpZ1bC7d+9g/3yCP9WELYIUng4yOwzzVoW2QCPIAIBwftAxn2zxVS0LuzK5djJv8thhh\nvUgghQfkKgnLgYPb0qQwzZOJGxn+7Mf13815mMnGk4Xly3vb8O3zZ30Ye1XNTnKK0TTls1bTVLZ9\n9vS58MSPOkaOTISLcGFUkzFBCUCfvHyVEoQkZHRsMAc8Qw3SQW6oZlaNHeYu+4F3U+Y3lqQERYwE\nALEbpiGAya57XfE+j2Nq0oRYpGWN4bRmd5JQkSqpKwnaY1JHAUAklT86muMt/Ezag0U1yEhtpJCn\n2aNlDiSTAO8Acbiu6JRk4KgjKk1/ifhMvxFlKEZKMWuZuDdr7bK3V9dOy92/+z9bE01FSkkul23b\nTl6vXr/n1PRrnV0RWkLRSED5cMZBJK5LNJvZcDYjKWwADgkDJxXO3PjSK3iybuICEGD948IQsgwo\nLucBTySQWyMgeleSeNPGVtp0skUN0paNFEmJV+0tIilmJ3EcRrtTAJyQRjivm/xL8RJLeOdWkWS8\nvWhjhtTE7tcEsPJhhiXeXa5Z0SNUj8yWQqqbicH7DK+Gq+Ju6jahLltFJc2v2V3lKz5YxvKVrJM8\nfE5haDcJRhG0pOpde6kopzldxSjByXNKXLFaKT1R7J8R/i7DpaX08E0c9xDa/upc7bWBScAJt+WR\ntpYhiAUALdSK+gf2Rf2TtQ8d6hpXxz+PWk+V4Uhki1H4f+AdUheOXxZID51n4i8T2LrHLH4bQHfp\n2nTIr61KIZZ1Wwixc9H+yd+xVcmbSvjL+0Zo6m8aS21TwR8KtSw0dg6/v7PX/Hdnl4prsfJc6X4a\nlUR2yqk2rxmYR2w/T66uprgvIw3NwI2WLywvOIY0U4jEa4VUXaNqnYg4Ar+5fBPwBpYKOC4o4swl\nOEda+VZNUoScqr1VLF4/niuSEk+aOHcUvhlK3Lyn8K+OH0iFN43hHgPGyfPCpgs74loVXy+81TxW\nWZVUoOpCrQrUvdxWNvzQlOVCm2lKodXJ4iknZpfM2xhAqRoFVYgiqsabVAQJGiqsaqAiIqoqAKKq\npqKz7yWbkBVJQKhXByc5BOGHODtCk5yK5XNwsYUlgSNrMiiOEFBuIYuv3udmVOWGAORVi3kn3E+W\nxSLbiPy+Ax5ba3bK4yHYjGeQK/rFZelquRaRilFKKSj8MUuVJRgtI2Stonsfxy8enGHvNtpuTk3J\nuTavJyk25Sl1b1bWpsSZYsojeUSYcnIwSo+ZoyDwpP3geNoJAwKykYxyoHIORu2xjZkjBILjK7uT\nyRgjI6dbYuQ7lcEKxKyKFYgDYzKQB8owR8uCOCc1RkLExgEqVWMKVjQbB2LYHQFhgc8EkjFaRpct\n1OCtK1ueVny9baead9FpuN1nPlaltdx5U/e/DV9l3Zfa/YyBpJAPmIZQERQCpjWPgNgFgd7jJO7o\nOtEs0z3EUNvbtPdySQWdrDbubh5ZrmRLe3ihTau+WWWSOFMAnIz2JGewUDPBSNvvqcsDzkuJcFuS\nSBFyo5OB0+lvgB8O/P1aw+KfjWNrDwl4daS+8Nx3I8uXxLrsMTrZTWsDDc+m6USbqe6YCOa+EVtC\nzBJmHi8RZrl/DeUYzOcbUhhqGGo1ZU3VqRUK2K5F9XoRc1yybqayUeZ8l3bqelkeDx2e5nhsrwOH\nq4jEYmtQh7OMW5QpOd682opvSHuxutZeh9N+F/AmgfB/wBp9v4kvorV2mi8Q+KpklQyalq8kQ2ac\ngIy+n6XGRZQxEfNIs1zwZTnxD4n/ABbv/FYk07S5PsGgxiR41jdYnuoFQRoiSIApCL8rIcb+nBPG\nN8W/iHL4n1QXM1zL/Z1qj+TEGUwsq5YSSRhWJZSuCMBRnHPJrw06w13bSyM7bQZVTcm2ORQ4McQQ\nDGOm5lALAkNxmv8ANzi7jfFZxmuZVo1J/wC2V5yxVbm5qmIu040b3tHC05O0Iw0lbm8j/Svw98Ns\nNkmW5XiswpRq4jCUf9lw04WoYFSUXzQilFVcVOylUqyu46RWmpzlxp8kMuoXMmoXckd5eNPGs6RP\nawwxqpFnHDHsf7MAoaJ33kFnjYsBmuc1TV9L8Nq3ltdXVy91IxDs0iR+aivJDEsfCW8XIj254LAH\nrW7fXMjsmmiKSSeb5ok5ggR/MEckbMrFVRt3yRkg7SQuSMVwviLSI7CdpJw0saOD5UchZvLbIyzM\nzDZhzkKAyBW3gHivzuLcqsY2acnKd1du7s769rJLy31P2mkoucHN6xjeN3y6JKPneKS0SseWeOL3\n4i/EiZ/DPhO6uNE0y+jBle2ZvtFwwCCRXMhLeQzHOzAwuc8DNfA+ta/4o/Z/+OPgXwrcwSJ4ot/F\nXh+GSyDuYvEnhvxrdpo+oeSsB2zGdLhy5Jl+y6jYwzOiNDz+hzaxqmi2d/8A2TcvBqJMn2YvChZC\nrbk+5nh/lUkMDt+8c8D460ixvJv2uvBOr/Ezw3HrGt634P8AEsvgPXL97t10i70+ya/vLixR3Wxk\nuokSeEpcI/2NrpLm32TOJK+38NMtrYzj7hfCwxtbAYvE59l/1TNF7yw9WFZShTvHlnFYit7Okoc/\nI5S1Vm7/ABPiljcPgPDzi3G4rL6OaYPDcP5rUr5avq8JYmnLA1sPVm5YiE6UfZUa8q3OoOrTVKUq\nS5lFr7nn1LVrG+nNte3UbJcNEjxSyxrtBeMOMNGXXI3Hg8naAQBXxX+0H+wT+z5+0jLqXiS40eP4\nPfF64QvB8V/hrYWdhc398QVSbxz4Ph+x+H/G1nI4CXE9wmneIFiDm21yNyGH2FNHIbszHJBZlAJ8\nwNtXK5VmYKoxkBeW/A1WdJt+TtEh5GCA0gXg7UYFRhTg5IHopr/VLNcty7PKNXBZthKGZYKrNfu8\nVTi5wjKMYc0ZStKnNLmatOy0a1P8hsiz7OeGsdg80yPMcVlWY4W0o4rB1JxfPduqp07yhXoTXLF0\na8atCcYqXs1J8y/mi+LXwf8Aj7+x3rNnafGDSItS8CXl6mj+F/jL4R8+7+HniCecj7JbXF7LGl54\nQ1+VCzy+GvFMNjcmVXXTp9VhQzHsfCXxPsbmeKTfbXEEoECqkrbvkOSYZlyVLJuysmcnGMA5H9Gl\nzb2Os6Hq3hvxDp2j+I/DWvWMum+IvDXiHTrXWNH13T52KyWeo6ZexS2N3a4P7tZoy0UipLA8U6JI\nPxr/AGjP+CZmteFZdQ+I37HH2nUtMM8t7rX7POt6qpvbVSJXeT4S+IdQnBu0ixth8EeIrv7aU2xa\nJrFwypprfyf4j/R/nQp4jMeE+fMMEnOcsrly/wBo4aLXM3hG3Oni6Kv8EZKrF8zhG9k/7s8KvpVY\nPNpYXJfEONLKcynTjRpcQ0Gv7Kxk1KEKaxtFvny+tVWkqiisPzWk1FNqO74O8U6PPJClrLEjskSM\nryhoIiI1DMNxO5iAC4BEQy2ASTj6C063sb5bZrlR5gjLoIdpEoSTcmVRWBOWUllbGwkdBg/i/wCB\nfipc2+oT6RqNve6PrGhXc2na1oWt29xpPiDSNShcwXel6tp9/FDd2F9busi3Fre28MpBXKbcOft3\n4e/GBmFss0iT+YrxRLnM0WSF+VAQF5Cg7GGe2B0/kPNeHsXl1WpD2cnGnOUK0JxkqtKUXafPGUVK\nE4rXlcU9ex/XtDEUsZSo4mhXoVaNWnGrRqUqkZU6lJxVSMqU4uUKicbS92Ukutne36C2FgluyJG8\ncSScmM5eVsco20Nwrtwyk/KMEdMHoU01HuYntbi6sb9NssN5al4Z7Vi2PME6uWCk8MmMMMbgcAjw\nbwt8QbWYM0jrGsZwQ5jY5+QbkBfzSqowYqUZlfOXxXuWj+JbaZhG0ceQ+GlgZMAjaRndkNuQj5T8\nwUN/ezXzS9rh8RRq05VKFWhUUqFenJ0a1OTcbThWpyhUg1yqSaknGSurM0rOnXpVaNWMK1GtHkq0\nKsFOlVhr7k4t+9F80uaEk4tN3T2PT9M8a6/pdvaReILBdbPzeZqunuq6hEiuBH9rs8RQXSnbzNGY\n52BJkRmAY+k6Bqej68Hm0bUbW+eJVMlvuaG5t5QAD51oxEyKAxBbYUbsxOTXlMWoWV3CmdsgUECK\nKbbvcvswZF4SMqRww3KxOCRVe90GCW5jntI5bO+QqyXFlK8N0jOEDM08ZQBUZQyruwATX9KcDfSL\n4z4bjQwHEEo8Y5VGnCDeNrRw+dUIU1BJwzFxVLEqFO8YLGtznpCddRUeX+ceN/o18D8TSrY/h+/B\n2cSc6sXgsOq2TVqs25TVXARqQqUFVm+abwsoJSvOMOeU3L6AJGApl+WORUeNGQ4BG7aAQGDMeOvA\nI5HUXbW1FwI0lVmyQzsu9GVDu3KTxuAAU+hPGK8L07x94m8PXHl63BH4n06LYhuVVLDWYAWCjbcR\ng2uoKRnK3CRzNkYmAbNfQ3g7XvC/jQpB4f1i1/tGSLL6VeCSy1W34H+psrkxvc4IdM2zTJtUNuOc\n1/UfDfixwbxlRj/Y2ZKlmcoxlUyjNEsJjo6R51SjFyp1+VySTpytNaxWqP5Q4r8H+OOCq03muWTx\nuWRnKOGzfKObH4GpTi21PFxp0/rmClJJ8vt8NRpu2vKl7SfReHtFtru7tlZMOcRsRhiFX5huHy/e\n65OCTwMjk+3x+AdNMaHB5RT91h1A7Z4+nauC0rwxeWl3CDG0J35cgMjHYcFzuXg+mSSOcZr3eMXK\nxxjcgwijHnjjCgY+7XZneMl7Sk1Pl0leHO0000727Ppuuzuj5rA0uSk/3cZxlJuM1FTUtbSScXJe\n7L3Wk9z+UfU/EGohLXVr662jchGJi5KKEkDCQsI0+UAOO5LMcE4rBm+JN1E6GPUHEavL5U/mAGP7\nS37t9m0+ZJ83lrwvlIwccYz4j4o+JFtYW7RXJt1t41h5muGjTLWsahSpxuV5VyuAXckJ8ynj6P8A\n2ff2J/jh+0Y+n+KPFEVx8IPhDNJb3cfivW9Ox4l8Q2bD5o/CHhi4kguruK4jDIusasLLSlHzwG9C\nGM/wFwvwDmvEWLpZflWWV8ViZtcypQiqVCDa5qmJnKLhTjG1nz8u7buj/TvjDjTh3hDK62a8RZrh\n8twlDnvHETk61Vqk37LDYak/b4jEufs1GlTTT5vesmreRLqfjD4ieJtN8B+A9C1bxx411t3Wx0qw\njN5cGXJ3vcqoCWVraBWa5vbuS3sLWLdJPOOA369fsv8A7FOi/Bm4s/iT8WJtK8cfF1FM+l2MUYvf\nB3w9k8vCDSUnQprniODeVfXJ0S1tZAV0iGPAu3+pvhH8DvhZ+z94fk8P/CvwvHpct3bpFrni2+K3\n/i/xM8Yx9o1vWpE+0To8jM8WnWwttMtA4SG0Xy1avS/sczK+5Z8ExBwCFVV6smOQMg5JJy/qOK/t\njw08Eso4OeFzjPVg844gw8o18PQdL2mXZXVu1H2cJxdPF4yCtz12nQgklRh702/89/FX6Q+d8bxx\nWRcNQxPD/C8708ROdWSzbPKMnDmWJqUvdy/Cz1/2GnJ1ZL3q81ywjKJrm4umaWdmkJwxDYZTwTIz\nZOeeDwMnOck9awnRIxuMgaQfKy7SCWXKhVY5BGAQTtI7HOatm3CtjacAKmUU8k/3snnb1PB34wel\nQmzkOFC5VgGY8b9u4EKgYKNwGcD5Svp0Ffviad1J9XLWUvifxOzbSu9Xayvsj+Z5Ka5dZXtZuyj9\npyslFRSSlJ2sttWQRnfAAWdnjDFF3ZzlvnaXd1A5G0njqMkDCm5KPh1ZsxqZMnICbuzBsMpGBu+8\npGQDmrRtH8lfKjZd0jB2JL8EgJuA54/iPGGzjPeNLIAnYjBIQ6nDcl5Mknc5JPQjBBG3spqrQ8vv\nM7zSim2ktrt9bb/d+ZEzLMHEYkXPzcPnlc+WwAIMYzkmTOGX5MGo0mCBR5koPlqUkVWYPITtxuBz\n8vfgelXnsw23fHtH3RuKonKKAS3GNvJIPygYPWu/8JeEgFttc1i2uHs2kt4tNtY4XlllR2Ja+nGd\nsdtCVwrOPnUFsHivkuMuM8l4IyTEZznNWPJBKGCwUZR+tY7FOzhQoU5NTlF6upUjGUYQ132+44E4\nLz/j3PsLkWTQ5qbaqZjmMrrD5Tg00niay2rSl8FPDQlGvObjL+GpFzwV4VMpGs6zpkd1tZW0+y1N\nGexVRGB9su7cFWufL5nht5JBFuwZ1cARnrfFvjS9uHkik1K/ufKt47e1uY5US3gRVVhBZWkSrBBH\nGUEMdvFbxwhTnaAOaus+IpLfzNMgkLR7XYSs6eZjKgxFUVQPL4jULyQQema82urqb7TLNPH5UUcc\nbQSyOZN6OhMiSRFFAEDbQjhnYsWJYDFf5teIfiTxBx1mVXF5pj5xoOtU+qZZSqL6hlmFXuU40acU\nqdSrKDvOtODqSd9lZn+n/hv4T8OcE5fSw+W5dQVRw/f5hUhzZhmNXlg5VsRWk3UhCTlJwwsJKnTi\nuX393VuZb66f7TO7SCSfzjY8MCjZaTneTwhAKOAMjIBAFc3qXiB4WliQCNEEr4LK0O5yEWHZw+Au\nNxBXOCR0IqO4vLi2uWkg851u4xEYsAsjxqY1kgdeEDhxJl2IBwW68crqNremGWS+tpIoo/M3lmG6\ncAlAZM8FGbiQI3LdOpr8wi4uSSi4xikpTb/iaJ81/JNLWy0P2mFKFNUlNxd4xjCNvcSik0lFKyst\nfNJ9iO68RXt2rLZBEvolD28l2m23jl348yaNHAnjUrvEasHZSp461zGu6xeXIZLs4uE+RpokjRW3\nMC4ghDERo+NzMWG1FGcnk8zq2vafp8UcsstvCsMbzTT+YYY14xIGBbKbFVctx5a5YEjdXwv49/bz\n+Eeg6pqGiW+v29xJZq8kmqWtnqF5p7PGp84JqEVrJZXLRKjiX7NLIy4KMdxwfQwdSFWsvZ03J2St\nGUG0tNtd/Xf8uOvStzTalJp6ezhK9t+WN18ku+zPs2f+zZ5tmqaleI0F0b9Gt7lrV5DE4kiFwyuB\nLZv/AMto/u/e3EgCs7w78avDHxJ+KsPw80j+y9Vvfh/4f17xBd38FjFejRWvRYaKltBqWx/sd3eC\n6K3CpLmWCB4irDOPzJ+Bfx1t/wDgoF8cfE3wJ8H+NNd+HXhTQvh34j8bX3jXSdDtZtd1tfD+raDp\nUuiaTp2s3FnJYw3A15ryXVZ7d4447RYUgdnLL+qHwY/Z3+GX7O+gahovw8tdcvrrXr5bjxN4q8Xa\nrDq/iPxA0W97aO4u7W0sbK2s7VpHkisbGzjiSRmlkMsxMg/qfwR8JuIsbxBkPG+Kp4bBZFkubfWX\nSq4unLHV62CcZOgqMLqMo4hYeUk/etGaXZ/yb9ITxn4UyrhjiPw+w7xmL4rznJ1hIQpYaVLAYLBZ\npGF8VWx1eXsqtSphfbxVGlFSU5QjG8nFnpjfNkFyXZ2YkhVdSi7WXZg5Y45YfKVwFAYmoJAWBTLe\nYrnavyDIzkncVDAHrtGAzd8jnQlj+cbSAqvt6LGqg8jgr8wwNrN3/I1C5dJgSihW3MNykDdwflJz\nkZPB4BNf3Yrbp321un57rTr0P85WpNu6d1pZqzXk1ut/mtU2tStGgHzgufMxErKP3Y2uc4bhWBJ5\n9PyzD9oxIZIxsbeGbPUbSNzo3BzJ0YjGMckiriRukUcchUzqTmNiqxjBLDcoAZR1Py55APIqukMr\nF/MWNtu545C2P3TZyibmwATwTnPU44Aq6bind3Wt002pJaXs1Zp3XdMicbxaa3TVpLR6WtJNaxd9\nV1R8s/tM/sbfCD9qzT5tQ8QJP4A+L1jY+R4e+NPhexgfxDAiAi103xrpm+2tfiB4aDLGrWeqzw6z\nYQqTomtac37pvwS+LPww+OP7I3iex8LfGjR/J0LUpmj8E/FPww1xd/DTxzIN2230zW3jjuNI1tIV\n3XvhbxAlnq0H7yRILq2CXcn9TKJMF+7AmPl2eYW2kDghx83I5K4+bkjbWR4o8PeGPHnhnXvAPxC8\nNaD438EeJ7FrPXvCfiHT01LSNSttx2+bE+17a4gcGWzvrWS2v7CcrNZXcMy71/MOOvC/IONaNTEy\nisuzmLbhj8PTp+zxL5ZJLH004OvKSkoOtJuSilrLlSP3Dwv8b+LPDmrQwyrVM74bg4QqZLiq0nUw\n1OcqaqSyvEVOdYeXIpXpO9Nr3UoJuS/m38G/F5Wtoz9tkkVpklgdWfeFIRURHBb9yqq5KcKytnsD\nX1B4M+MDwOk91fC5RREsiNMYz+5yjLhgdwAOVlA3SHK8qoNed/tX/wDBN3x58BYb/wCKP7LkfiP4\nofCCyju9V8Q/C66uH1v4lfDixgVrm4uNAn+W+8f+EbKMsTiGXxho1tHi8h1uyRr5PiDwN8VLHW7K\nCaCaJo5WQiSG4UtDJHLiVJ0IGGVt8LRkKVcMsgR1IH8RcceGmO4ax9XCZhhJUakZSVKrCL+rYlK8\nlPCVLNVUoe9Ll1p31Sg03/orwP4jcM8fZRRzPJcXeXsoSxeEqLlxWBqz5f3eLpXbh70nCFRfu52d\nm3dL9uPCvxbsZGgjN9Fbt+9dIy2d4aQSRFd7gXHmKX5PV8IABXuOifEaC5dLea8EhRSo2uquzPhI\n3khH91shgW/dkgEk1+OWh+OluxZutzGXgjWRHYxqHhLBVj8goMbcDc4Zm449T9AeE/Hk0eGe6t1l\nudhKmQvIVRlcLEViZoo2Kb9oPz4OckgV+U4rJ6uGmp2lFaRUWn3WrSundO3Vfr97Fc13F35d0lfd\nJ32fRp77an6jWmqabfRxgXI82TalypTGY04BhRm52kfMTuLfNkgEZLnTLOeSS6gMqXceXimilaKW\n2A5tpY5EKPDJv43xyYXdgKMbj8c6D8QmnWFrmRrR0kKRlH3BxIiiNhnDqGG4GPYhyGWRVPFe0aF4\n4hIt5vtayf6snEhKIVwB57DAjVTwcFtjtuYkLtrk554eUJS51ySU4zp81OVOSabcatJwqRd1ryyX\nSz6LSC5nyyUZKr7jjJPklHqpxi4qUdfhleLV000z6+8D/tF+PvhyIbDX7X/hY/hmBhGbbWLiS38R\nWcXAI0rXmhk+0BMmNIdTS5iG1Ns0SlmX6vt/2xv2eWt4Gng+IdpMYYjNat4RFw1tKUUyW5uIb8xT\nmF8xmaImOUrvQ7WFfmWPFqXLpFcNbO/ItwkqfMEYCP5pC2XQFgzEbcc55NKxtGJYi3yxJPyKeSc9\nfOGfriv0DKfFvi/KcLHB08esdQpWVF5lSji6tKC09nCtUtUcElop8zTteTPzLP8AwT4Dz/HTx9XK\n62W4mq3LETyPF08ro4qcpKXPWw0YSoqpHX36dOnzX95O2nX/AAB/YJ/Z1+BMtr4hfR774vePrWNZ\nYvGnxOFlqsWm3mAoufDfgyGBfDukTYAMF3PBqd9E6rIl5G3T7jllmvkSWeaQgsGBkYF/3abUAG3p\nGNqKOEEYCqQFAqjaZDIssa4KqF+VtygA5IZxgBeOM9+BnIFx4m2QxkDaJRtcnkAk4C5+8oKkkKNv\nTI71/pRlOV5Tk2Cp4LJsswmV4Vayo4WkqUKstPfq1E5Va1R3d3UqSXvaK1j/ACrzvP8APOJsdPMO\nIs2x2c46dowxeYVnX9hBLSnQg0qWHpbKFKhTp04P4IxWgnlsY1KtGd+dzSA7+7Fo+mAFVS445zg4\nAzHOiPDhJDIzgHb0Z5CmfMGx88beIn46bQeamkLhVxbgyeWyhxxliSC4PTLrtHHQ4HQ4qLZJtFuw\nXeEGOMuG2kgMQBllAIJDH0716SvdKdldrZ+ndI8WEb2TTUmrpbaW6J9vyKZHmspMhGdiOjQtvO4K\n3yhW5wc579+gqcRFtiB9xILHcNw54O3JDJtXAIyp9hUMUUu75erBSzdCQFV1bAO0kqu1VOGQHO8n\nNSHzdpZlVsKcAP8AfZzncqgB8jjc5bCnIG7iujmVt/69N7+W5Lpzmrx2XxaK1nZ6t7aa9PXTSQuI\nSoztLRgbkjJO0HIEgYtj056UyD5QXkePcVcnCBiY3JDI7OcKNmSMNwcYOejFE5Qq5wrF0DthGCAH\nKpg4K4GA7c7vmYV2nhzw81ykepapA8Vgux7e1ZQj3sagFZpAclLMOcs2N1wQAAqk7vleLuMsm4Jy\netnOd14xpw93C4WnKLxGOxHTDUIN2bu17SV70vtJSaT+r4L4Hz7jnOcPkuR4dVKs5wnjMZUhJ4bL\n8JLV4mvNJxSaTdKLcXVs+W8bkfhvw4t6kWramHTSbaSIw2sp2S37JkiRY+SLPPWQZafaNrBc1ra1\n4t8qIW0DxAAZdo2lxGFZ1iEW4KVAjCg8BEcMqnA+avruttdwOlxA9soSSBLOYwxQRNHuRNptmdQ6\noqSRKkhAjlIZUkJC+P6rNfNFPDalWlii+zRx3UrSNI7Al/OlDEMyMQFbLYTA3ZBFf5r+I/iTnHHW\nc1swxld0qT5qeXYBNToZfhk0oUaelnUentJ2UnJXbP8AUnwr8LMk8P8AIcPluBpe1qucK+YY2rCM\na2Y4le9OpWa/5dxcpeyoxk40o+7F222LzWJpp4gN0waT7yLtaVBHuTeCMe+/cSwHOMisaObXNYub\nwNbzWFut0Ybd5sSrqCpErPJGUkYpF5mFeNjGSUBA2jNX7RPKhRrwTKpUqIzjG8ptYKrcyxkxqV4x\nyxwDxXB+PPi9pngfTZ5SElu0TfFCQqs7MnygR5IEmGGQ5XnKnmvyf6x7NSdWpb3veUpK9+VP4dXt\nraK16an7HQptz5KUI8nJpV0dON2o3e/4LpsehaxqnhrwPoj6jrd/DEtnbiWWS6eJJCY03lgzY4Aw\nvHPTrX5NfGb9vDw2Na1Hw94f1eW6d7mSSx03T47rUtRvWlf5kt7CzFxdyBmVVRIowC69Mc1tro/x\nm/a98cXPhqPWrrw18PdJkkbxt4kskZYvD+mynfb6TYCQCLW/GOqwfJYaWMQ2KOb7UALWJVm+p/i/\n8fv2af2UP2evDf7P/wAHPhn4O8J+LvG95Z6L4g8WXdpp0fiFtDkspn1zxx468cm0fxL4j1+3uYls\n7awW8tbdry/QLBbadZ/YX+ypcKYyrkmH4izmNXLckxqxkMkqckorN8XgKcK1TDU6t05wrKbVKVBS\nc3TqKkp+zny/NVeJ8shxMuEcklT4l4mpSwM87wuGxlCjTyDAY+co08bi21VSqU/Zx58Jy0q0I1aM\n8RUpUq1P2n5j+FfFXxU/aX+J/h/4f3fh7XvBnw/+zReL/Fcuq3Nva6n4q0SLUHtbTQI9Ot7qXVtI\ns9RvLeQaqmpwaZeNpkbCGB47tZj+pfibUvh74Jj0jTF8P6BGsbQafBpsWn2UdnDcR25ZYYraOGKO\n2gdI2WIQRKSVG7cxdz+dOr/tc/s4/s/+HFi8DTaX/al2LyS4u7Jv7S1XUNRvyDqOo6rqvkrcXl9c\nyr8rGJ1iQFQF5Nfnp4z/AG0vi78VvE0Pib4e+B9d8U+DdCu49QvbzTpoLYXd1BBdRw/Z7fU5IJNS\n8rbczXJtiRGscaqhBYjx8Fl2Ox2KVbL8HDAYKNqbrYpVMJQfMnL2bq1nGVWc5RqKEt0moxS3f3mL\njhcuowniqzpSldyw8HCriZu6h7RQoqclTTkueSUkr7q1z+j/AMO6D8GNZ1RvFdn4W0Pwn4qazltJ\nfEvhizttE15LHURAb2zk1bTYba9ktrvyIZrq3luJI5XgjMkbELXWX+havptx5mkeNLzULHy3e1s9\nctbS/tZ0jVDse5SOG9iXGU80TNICxBUgZr+eb4H/ALZvjH4leI7vQTpHiLTLzQ9Zs9OvvC8thJHf\nW0c0EckepX9xbbkl09isjWtvb3Hm3EkZF5JHbKxP7meAdf1DXNGt/O82ZXjR187y4WRpV/jcsT5W\nz5pAv3nwECqBX2GXcT8dcH42nhMtzzNsmrUpe1jTwGa4uFCck4Oo6tCNWeGqyqcqc3OlP2i92/K7\nH5zn/BXAfFVCni874fyDP6GIoqjB5hlWCr1nSi3CnCOMq4aONpqneShKNVSpu8otSXMenaddw6pa\nR6lHEsQV5Yp4wpdLW9t3e3ltgCSd0cq5Hy/NFIjgAEU8QqrzbjuZkJPHycKC20Pt+QNglOX4OPmC\n1wvh2/8A7P8AGureH5pHig160/tOzzISBqmnR+Vdxq4/dqbuxInQAEyG25+Zhn0GSFQJF3Hfv3Rq\nc4YMACSzE4Zidx5CnHFf6U+GvGS454LyXiGbh9fqUZZfm8YqEWs2y5rD4ypOFJKFOWIajXjFRguW\nd0ne5/k/4rcBLw749zvhihzLLaU447IZVOeUqmR46P1jBqdScpOVTC/vcHKUpyclQpybUpuCzAhi\nkkck7STEUZFdyq4L4AyV4IK5diY22k5yA1RAUWIYO4BmLR7fLGcKioOm4HJIwee9W1iiBEby7JBv\nywG7btOclQdpkfnA5BBPTimKpMqFpnAXd5Y2rtJB+V8gADPXDZI6EdK+89/fvr0sfm0oX3TVv67F\nQsVadURxtYsrH+HYOSEO4jCjapONw5HYUJskbD7mxGzZ+5IVfkggkMOxA74Bz2OpgcksvI/eHOWb\n6MfujgFkUdCMEDNUNpMnLF1dSu8jcCeu0/7QGFBDDjhhnmtPIdFSatHvdu17LRXfkmRQXc9pcpNb\nzOskJieKRWeJ4yvzJulVuGUFj8nzfxAqea/Mb9r7/gmx4J+Pt1rHxX+BFzoXwj+O16095rujGAWX\nwx+LF8WeeWTXbW0g2+EPGGosEX/hMNKt30/UZWJ8S6VNKzarH+nZgTziuUUBOCWOR34QscZ4+Y5A\nHZqgaJIgTHIyOdoUK2xdqAvjLLkknhyM85AFeLn2S5ZxFgamXZtho4yhNK0pcqr0ZR+CeHryXNRn\nB6+61GdlGopwvE+n4a4hzvhPM6OacP5jUy/G0bRcqPtPq9ei3Fzo4zDxfJiaM9U1OLceZyhKEndf\nx165qPjb4TeNb/4YfF/w1rvw48e6Aqx6t4Z8TWv2S5W13hINU0e83NZ61o95Ihex1fSri702/jIe\n3uS25F9u8IfELzeTqCzRsmN7jkqXG10wQQ6kqqE9FOMiv6XvjJ+zx8Cf2pvCkHgn49eCbLxfptlD\nct4c8QQSSaP458D30zDff+DfGNnt1LRpmJV5LA/a9DvmTGp6Zeq22v5/f2ov+CX37RX7J8Op+Pvh\nFNqv7SXwDsvPvp9a0HTT/wALd+HumriR18f+AtLjlbXNOto8mTxX4HS+05UhafVtJ0JWAP8AJXHf\nhDjMn9risAnmOWupJqrBKOJoQesfb4dxlflaSVSg7SWtovQ/vjwv+kBlvEXsMt4ip0spzV04R9rO\ncpYLFVI8kZSo4hOKTk9XTrRvC+s5R22dA8e7fNCT3MjRK4HnSLscKzTBogzkRqGyshGWMg4KITn2\nDw/4/kjKSCadQ0bo8atmMMSruXiV0GcEHYwIPzEMOK/LLwd8UbPVbeOWC4ju4iFZpN6OwlbKtGCG\nBjKSBlkTZvBbD4ZSK+hPD3jpyUwzLI0LQhlkDsN2Wd5VVuSFUc/eC4yO1fgmYcO8qnZRXK+Vpp8/\nM7K1nqu15LX8T+n8BjKGLjGVDkqxqPnU6XLKmoyjBp80fdejvdS12WqP0e0TxcZ3tXMptwhi81nD\nhJnlYhhKOsbNwY1iRiu0CUsMtXqi+O7RFVGmLFFCk46lRgn/AFo6kZ6D6V+d3h7x4+VmSYNKY4pd\npAIEjFosOJWIU4dtrqofLKAK7r/hOvVpM99rRkZ74JXJHoTyR1r4yrlU41HFJLlsndpav1a8/nY9\nieGTknF8t0tHJt9PNr/J2R/TDHOSxwyP8oyqtngg/KD90NggoSQCBkEmtIMquziZxkogQ5lYnOOO\noVF3Et93IOAaoxooEYEilnRS8SoG3YPIbIUxlcfu2LbduRghlq1JHGXCxyLgyEAk52GQN1IAxtxy\nF68EdK/1qpqKpxtbr8tIv5W/rQ/wxjWUL2XM3b0Vr+vfp/w1maYAxHdkmMMVAViQrFSQTweVzgc9\nOM1TZ9gyG2tJuxIcquWYsB7ZXOTgD3pkwiJThYym9dysWZGRTINqsejY3EYAO75uajAQghJY2Lbc\nhg0ilQMZbaCQznPy8qpx06U1yfa5UnbstH11Cdb2is48tui3e2l1fZ9LatX7i/aVjZWDb0bEgAI4\nwFJXI5cvknCggfezgHMzYAcklWj25VW4aNuWVhnJYFiHIJwSNqjOKrx2sTSWyRR3E8xbdDBDCWZ8\nhgkcaqu3cACMNsGDktzXsPhnwTbWVpbatrKpdXystxHZbikVlsXePPzxcXpDHzQ2UhI2ohKjHwvH\n3iHkHAOA9rjpQxmaVoXwGSU6ihiq8pOPLVrO7lh8La9pyjF1Vd0eaza/QfDrw7z/AI/zGNPA05YX\nJaNTkzLPatNfVcNZRlKlhm4cmJx6TilTc3Tpc16/KYPhjww0rxalq1tcLaWqi5trKQrI08bBiHYZ\nZiVAyIgm5iy56MD0Gt62wZY4oYY4VSVJA04EsSKF+yxoscYJd8SPJH92IIc4xzY1zWoiDHFIIRbc\n+WiSDbHtCtLCzBFzkfLvLFQQOMk149rGuQOHlty++WBlKbFSVyZCD5j8L8nzrgSGNtxZWzX+ePH3\nHOc8Y5pXzLN8T7Wo+ZYXB0+eOEwNFNWoYWDlyyUPhdeSdSrbmqScj/Snw48Osj4MymhlmT4CNKjG\n08TWq2lisfiZWdTF46tGUY1K1drmcKfLTov3KcYw0ebrupvLLZQxRzuskjqJ7cgPaspdnuJlLqjw\n7l2FghLtIGYCufiubV2unWbzGQTHeEXzEYje6l3U4BODGCNyNuGRgCsDVPEGnC7kjmmMT7XCIHD3\nV0IVWSYwkEtIsS4diisV+XcpHI8r8T/EGCxEsVpJLCWDx7zEBIFZFZvNJVf3o6Mpw6N84yOa/I6s\n5TnOesl9iKTclor6K97tdNX1sftFLDpUlFR5YxtduSjGMdL80nZJW329Tf8AGfxFsvDsUaeeslx8\n6xEYQhnjK4A+6pDEqzZyxycBTXxpp2leLv2hfHsngrwzfSWtvYtFe+OPFr27XFj4R0eRzH5gzthu\nNZu2R4tG0wuJbi5U3Mu2yguHrOurjxZ8ZPiBY/DfwO0d1rmpILnVtan859B8I6HbSmG/1zV7o5Mc\nUETCOxs0QXOrai0Vlbbi7vF+m3w4+HPg34PeE7TwR4Mib7LDOb7WdbuwH1XxVr06bL/XNYlXDvc3\nGwrb2it9l0+08u0tlSNWZ/3LwQ8E6/iJmdHP88VajwhluISxM4cinmuJpySll+ElJtSpptQzGtSc\nJ4aN4Rbq80Yfz149eOWC8L8onkWQvD1+OMywzlh4JKpSyTC1IxlTzXMIKTcalr/2dhOTnxNaVPEV\nG8FSrQxGj4T8HeHfh74V0rwX4LsBYaRpQ+RZZBLdanqExDXuratdNzearfTYnvLx+GdgkKxwQxRr\n4p+2L+wP+zV+0jo3hzXtI/aGj+Enxg0vQNSn1fXb/wAOWOvfD/xbbypFPFBfaVJqWkX1m2l3AkWH\nVtLu5L6+Ejtd2lxiDyvoiVIJFlif5UZGiLRZV4kljZWKMMnzUjbdGVI/eDIxwa+C/jN+zd+31pmm\n6Po3h39nHxp8SvBmh2UUun+LvC+veCLhvEeny3JurWe/03UvFWl6xpt8bF447rTLjTpJIZGbY0sa\nh6/pv6Q9TNcn4a4dyvIMjweJyH/aaby6hQfLhq+XU8LWy+nhowpqvhKFCh9drqph2pOupczfOoS/\nl/6M1TKcfxjxBxBnPFuNyjilSwlajmdbGYWhHH0M1q4qGayxNTHR9lj8ViK0cLCpRxClz0X7RJON\nST/MLTP+Cb2h+Hhq934q+MsmrX32jUBp+o+G/DOnQ2htGcwRXdraawtzerDdW5WVEuMTRtKuSwIN\ne+fDv4PeFf2f9D0HwDqC6bdaRrMTR6Lqd7p32W/1C8sdLvWZtSsi8kcN7ewyyX1u1q62sskO6ONW\nTZWtdzfH7X7K9h0n4Yat4akgtr/S9Ri8T67odjfWDIZIpYJLeC5vQJLe4iw7MysFiAMmHU15Bd+C\nP2iZPiD4G1/4wwaNbeArKDUodOv9G8VxanIuvWuj3EemQX9nNYQfZ4J/Mmdbu1kuAjxG3IRipf8A\nzsrZhm+c08THOM4cIUalSpUy/wBon7KdFS+rww1NKKc4yfJVVV31ct07/wCpuIwOCeCjW9vCUoYZ\nzp1KThOvWlUjh5xcoUW1TVSzqcqaSSd9bnxZDLY+Cv2rfEWnR3H2XT/E2k2XiOFLYywmWfTn8q6j\nl3eTuQRXxOU3pIiFsbSc/t38KNds20awMV3dOZEhPBjbCTwKfMUNkEDiMrGXzgkY5FfhV+0Gltov\n7RPws8RtCUguLmTw1ctI0zRyjUfD8jwuJHwPIlntlaNY0McmQfl5I/SH4OfEBGsNOtFvI4RaiNXZ\nYyVihMWVO1SVhDEqE5ZtxGAOK/Q/dllnD2YwlKTnldGE5z0lGdFOnU5+rm5PWd911Vj4HFxqyxWP\nox0hRxk1BQsly1rVYuNtkoy000P0J8Rb7WCx1uzVjdaRdRatbzNIBueCQsUfbgus6BoTGM5R2yMA\nivZ7XULTVrKy1WzYNaalYi9SQNvCRzAEocDa/kSbojHhXVkKscivmDTvFMes6ckW1JAHi2XE7BA6\nIDunEbAgbfmAXAyxOeteleBNYn8P29xpmp2qT+FXmaXTNSRpi+my3ZeV7acBMiylnZpYn2Yt3L5D\nBwV/ffo9+JWX8LZ5jeHs5xtPB5RxF9XlhatVSdGhnVCbjGeImpctGji6NZwr1XG3tYUXJJXa/l/6\nS/hZmnF3DuXcSZBgamLzvhp4mni8Fh4RnisdkOJjCc6WHoqLnicThcRT9ph8PGXNKNSsqUHU5Yv0\nmSSNwSqqu+VirIVY7UXqrMylPMGchwSv3cAAVAVYTM5OAZCi7SzuCyjerHO3bxnIBAYEAcg1fKQv\njGDCULRKibiQ4+9noysMEHAOD06VERCYcAOqtJiPC4MYBCkbQA30ZvlHc9a/vmO0EnFupCNWCvrK\nlKKlCdOLfNOEotSjJJxcdb21P84Zc6uuScXTqulVUoSi6VWElGdGpeMfZ1IN2lTkoyTXK4p6CCXB\nEYWUyLubeSgyGBAjycFS208spx/CcHNPKsPLyWVgkjCNnBIwADtyAHxnJ6HBOeeDDuQukYBBBYKz\nF13bDneW2+WWUbjjBVs/LwaJrhcjaEeJkb98FxkqVY8nJ3MPvLj1zwOZTk7dtL6el/zNIQjdytrq\nvKzS/wAiKRm39N5GGdTwxXgBVcEKozySPp3zWfcNmJ3Qszq/zsdoBDMqnCsQpOOSUPynqMcVLJJi\nTDBipwiDIziUEeYxwCNpBAP3QcHjFVnk2k+SFXG4NyQcj5Tjgq/yqv7wDqT1JpVEktLbP1+f6fM6\nKcEru3l/X9f8BksnlRK6j93lwxzv+4Rt4XALEgfMBtA4JPWuq0LxjqmkyW93aXc9vLHMphaOR45E\nKNuLCWMxurZcl2Ug7RtBJBrj7mSIoTtTcIjIFJJc5LI+Rt2p1DEKCCeTzg1Fb3e1WdoMFUQJySXK\njDEOV4HXgDnoe9cM6UKsXCSTUtGrKzXRSTTTS6LpdnpUpOMYySvZaK7XbazW+z26I+UP2nv+CbH7\nLn7Wlzq3i7SLE/s7fHTUJHuR8UPhfp9vF4f8U3+CyTfEb4bxNa6D4h8+XDXetaOdA8TugaRtRvZD\n5bfgF+0T+x5+13+xbHcax8VvAJ8W/Cq3uWWD45/DGS78U/DiaMsRby+I/KgTXfAV1Ko8z7L4s0yx\ntUL7ItSvR8x/qxstWjgmhwPKUSrE5y20HHzbnGGAQkFtgI6AE819HeB/EUd3bmydrWe2vbeSxvbC\nWCOexv7WeLy5bK+trhXgu7SZAwmtbmOSCdSFliZSa/LOLvDnJsyi8XDDvA4py5Z18PGlKjNNJJ1a\nN4zkk223B3vrvoftnh/4t8U8NyhhaeOnjsGvZxWDxlSq5QjGUUnRqpxS5Ur8knyu7Wulv4X/AAv8\nWLG4W3mtb6JxcJbmORJopl2l+GIEqgqdpIZFK5KsAK9CfxpO7s63V3tZmYYuHAwxJGAOAMHoOPSv\n6Uf2pP8Agih+yV+0ql/4t+GFtd/sofF+9llvB4o+GGkwXXwx8Q3pVmZ/F/wfkuLPRomllb95qvge\n98KakCXmmiv5X21+Pl5/wQY/4KO2t5dWun/FH9k3VdPtrmeCx1OT4gePdMk1GzhlaO2v5NNuPhvc\nz6e95CqXDWM9xcTWjSGCSaV42dv55zXw3zLC170MPHERqN2xGHXtIVYxlaL0UZU2r605RfK2/eb2\n/rbIvpAZLjcJF4+pLAYqnGHtIYqlXm5N2/hzpSalG666q6P6gkJEXLPuAQSOwT91GNobLheSSBgc\nnGMGp5THIJBuY/vRjoMF8uCCvcqAc88e3WssRjj+Xf8AMqsG2YbIXzCrAYKED5cjCnPNQsNsbyKG\nwZ/Nl3ScqhC9QwXCjoqq+cABcCv7bpe9Silvzctre9JtR0in8Ttsv8mf5c2btqkm7OTdkr21dune\nWlrrq7OY5TapdeWYKzAByTgfMAMggdRjPQN3rRsNKuNRuo7GyiklmlGXkKoI4gysxkuHRgqodvyK\nreYzdAu0mrei+HrrW5olb/R4pA08byO6z3EUbDebeJ1G6McA3Ei+WpwUVzg17BZp4e8KWDAR27Ov\n7wgyF1+0IN7O0mQ8020ku3G0H5VPQ/gfiX445TwmsVk/DVXDZrxDCXsa2KjarleTSfK5Rr1KdSTx\n2Ppq6lQoNU8POSliFOPuH9GeFfgLnPFH1fOeKMLictyCcnUpZf71HN85jF2p+zpzhD6jldZPmeJn\nevXgnDDOnP8AeFfw94bsfDsJu7wRy3cqLAXmmCjey7hFGoDpEiqjSIsmWYgl5GzxynjjxpNpsO8C\n8vEFzGEtdOjhmlbziA5JwPJgRcmTbg5yBxWd4n8cq4vPMazt7SRjHaotzIJhCYgySSxlFMMocu6E\nAqUAViPmz8/az4phi064iNzLPNcN5TyyKB9oCxmOSR4ocmA+XgSeWUVnxgr1P8FcR8V4vM8fiMdj\n8bUx2YYyrPEV8ZXcqlV1HyXje/LThdtUoU7QhG6jy2P9DuE+DMHk+DweHoYHC4LBYOlSpYbBYaEY\nUMPGEFHl5XdzqSVvaVajlOc4qU5ykmdtrXi797MonuA8sZLfMwjCqNkjSB3cgKuELKB5qc4PBrxn\nVPFsb3MiwOzPHZtD5rMWVmMrN+7U4MXy/OQBk5UAYNcNq/ioi3t9NtYvsrJC0RlSRjHHAAtsuWkL\nFgsMaoAHZy2SwJJzxEuqBdkh/fFXLGRWIjO5NgcxqCXxtVNhAAZsr0Ir4/63UrVowablJSakm+nS\nzXVbu/R331/QadGnRioQUEtLJLyXla/o3c6HW/FAFzHG0js5NzIblVi3RgRiNnVmzgS8JtUgMAC2\nSK+Y/EniLxR478V6d8M/hvaNrvjfW7mVSJD5VloGmopS98Qa3eqGFnpelwlZLl3275fLtrcyXNxD\nG1Hxv4t8S6/4o0j4f+ALJ9f8deJpH07RdHtkjjjzKqedqV9dniw0XSYvMv767lHkQxQv5pQmNZP0\ni/Z3+Aeg/A3w1dWFtPD4j8c+IEgu/H3juWErc65fRuXTTNOV1M1l4X0p2ZNMsVOJpUOoXnmXMpEX\n7f4QeEmI8RMxePzGU8Fwxlc3/aWOjCVOeLnDl5svwLUfeqzcoc1aL9nhubnqOX8OX4f40eNGB8L8\nq+r4FUcfxjm1CX9g5XNOUKEW+VZtmPJNeywVKonGnGS58XNOnSSjGpWpVvg/8J9A+CfhgeHtFnn1\nfW9TuEuvGfiy7hih1XxTrSw7fOlHWy0i0Dyw6Npsf7izgeSQh7y5nlb1h2LyB9pC7d7DkElQzFXx\nhjuJYp8wGBgnoK6240GWRs28MhZmwsrYAWMDllznf8xY4I6EbQaWDwzq3yuY93ynLeWHzGRhlIOM\nHONvBI3MCR0r/RzLqWU5Rl2DyzL8LhsBl+Ao08PhMNQSp0aNKnGMVCMYWvKSjzVKkk51Ksp1JuUp\nNn+Vma4vOc9zXG5xmuLxOZ5pmNepisbjsVN1K2IrVpc83PmWkYc3JCCfJTpwjTppQikctE8pGIkE\nFzuY28kzKUW6Ef7jztp2+Wkvls5JAjQM2CQRX4+/Ez9u/wCKNtc6z8JvGuq+KPCPi/Qr++ttS0Yx\nalPeXU0V8YPPt1tYmaXT7wtHNb6lCjWNxFcwyxysJFB/az/hDNWZVAhZQ7fwrtV13AHzFA3OVBJx\nkED5lzX51ftfftZ6X8HfFk/wuvTD4a8QpoqWWq6iNPt49V8R+HdTEWo2dnqWrzQNdP4dlnkZ7OAT\niwjmsV+Vbi3BX+ePpMYDLsdwrlmdxq5l/aOX4qtgMJhcvTnh8TSx/sqtT69JVIexp0pUI89X4pU6\njprm53A/qv6JuPzWlxZmnDtTA5PVwOaYTD5jXxONkqeKwlfL5uhS+qWpVJV6dWOKlWr07clJ4WFV\nWk3I+OZ/2jbeTwT4h1L7L428PW+laNLN4g1S58LarLbaVacJJqd7C1tGZLe2P76e5hYttfzHwOa+\ncbD9ojVPjpqHhjwT4M1xvGnhnTruPXdV8Q6Ro+q2umWosInMcS3uqWscV7JqVylqjraF/KiabZJu\nZQ3BeJv2v/EGp6h4y+Gvw51eDx1qXxNebw9DZWyw3tt4cTWHW1u59X1SOV4YNOt4iSIJwLhgPLWI\nYOfvv4S+AdP8CfDy18P20djCdM8OQ6Pe3EdrHHcyXVgbSeRrdj85ZXI8pl2KRJGmWDHP+e+ZQhw7\nQcMXltsZjZqphMPKpyxo0aqjGriKkalN1pONRyjFSbhKyaskkv8ATaWYQjhUsFicFik4VqNepTbx\nCjOFCLpL2tNxjFuPPCyUrON5ba/lJ+2TbTaTe6NrRJux4U8Y+AtRVtzOgt765s9NurOOErG8caQ3\nhMIQEyPMo3gDB9v+DviDTLeSBr263TSG1WGOZSUO+QgpKikNhIyFQMvySRlWBI483/bc0C31XwpK\nn+l2s2qyeHbcztd/6Usdlrvhs2ciQoWiWVWt5MSoPMMm/LhFAP3B4G+CsUWmWfi+w06O8XW7XT7y\nSxcNHLDcy20czyxsqgD98XcKpjVXLMc7sV9fSzHDUeEMndaUpVKn1+jTjDl0VKFOcX5e/NxS6t7a\nnhxwcq2bZheMYUalHL8TGXO+Z4ifPR5EtlH2VODbduh9M+BNHn1aKFtLmVot6nfFERFCZAo8tzK4\nDTD/AFiqu9ieqivsbwfp1zp1u9jeLHe20kaG4MnlykHcUjdSSEdmbhl4KncEwBmvkjwdY6no87G8\njurK1RoZhayTOz3gVU2xKQAYkkC4lKHfImEGCTX2L4P1eC4tgs6QwPFu3fu9qlZgDJvLNgNGrBIi\nGBAXjLnNeHgalPETi3CUEtG5XUuX3ebl66xv27bakY+lUoQ/dyU52UnyOOyfwys0t1+p3L6LEsMY\n05obchIz9lkBZPNbGVj+8YkCgER5KljztJArlrmG4tmkiuUa2YPHmTPysdxUorfws38IPXv1resb\n/wCyfupNkqybriPPDJH91FX5s8fKxB5ORkZrpV/svXLSS2vgN8uBFvwN7bTgqyqTHIrABCcjOD1r\n9+8PvGbirw/q0sG6tbPuH7SUsjzDE1ZKjFpclXL8ZPnng67VuWLk8PolODhc/nTxM8EOD/EahWxX\n1eHD3EalzUs8yzC0lOpUt8GZ4OMoQx1BqS0Vqyb5qdSM2przUy7wygCNyTu3lBuCjb5od/mU+qoM\n8HaSKpySFXVfNwVXY5UEnC4yUDDhjjILcupxnOM2dYtbrw5cubuN77Rw8gju4ctd6aeQouYzHi4t\n2+dWlQFk6kYNVgguUjmhmgmilXeHDBw6ghgCyjEmBhYwNpVxsYdRX958D8dcOcf5VHNOHcb7bljD\n65gK0VRzDL604RcqeLw3M3GPO5xpVqbqUqsYc0ZJ80Kf+evHPh5xN4c5o8q4lwipKpKbwOY0Je1y\n3MqMZKKqYXFKMISq8soSrYeap1qMpJTpxurx3DqZVVZI2ztDYG58rgoGZuRg9QMY5B3Csi4mJkkw\nrriRVEmEBzkKFTjAUOSSOFPGeK1ZghDhXkDSZAZtuVJJyC52EKDheT8mQ2eMVlOWcoMxkHYhYqMK\nV+Ylskl8AZbDcnn3r6+Sckmu2z0/B/r/AMP8Ted1yP3e65XdtrZ3s7JemtnvoxzG2Y+MqBuZwFYj\ncZM5VuV3KBheHztUGqYG4OUdzHncsWGKgcksB1JycEZIx0Aq/NsC+aU3rHGPK4RWlwf3SqCGMi5+\n8Bjg9RVdpsJIGJ3sg+SIr98MNm3G3pkhlwD1HPU5+y68v4/8E35pWinK8klbRLbW1l3d/wCrFZz5\nT4kVUYfIHD4fZ95VXkqQXxk4B7dsV6H4KF3FeCSKWcbjvYKwCgARsHzkDhWYnYAQoAPFeas+WkjZ\nWRwwYSjkGRs7JcEbiqsCoTPDDJODiuk0jWWsjG5JJCOrbSCrso6KedpkPXC4xwcAc4Yyi50ZRi1z\ncrSTipLW19Hr31t/kehga6hWpzlKyg4SqWuno1zebWmm59oaZrrQ2cRmnz5cZbaGUq0rY4DMw3OF\n5KZGMHGBxTT4psySTM+SST8knUnJ/iP8z9a8AsPEE15aW7eYPL3eZCm/JDEbXjlUHczLnJTavylf\nmHNdiqXDqrY+8obiSMDkZ4BOR9D06V+aYvLIU6j9ondttaPbTpDT57u/U+/wuOjUgpWU1aKT7vRt\n62e+v4dGRW9tcXUqQ2kLXF1Jk+XHuQM8hPJdztEKrkMeinHavRdF8GQWCx32tywXNyBvS3iIeCIs\nVKEMy/6TP0UFgYYzhlViQRYW0stCsWMZSe4CtHeyXbLF56EAELIgwm8cBRtVQc/eOa4fW/Fz2gMc\nMrx2lrIsVvDG6yGNRFtFucgAQxKcRY3MCWJdu38k+Jn0hsw4hjisn4ajXyXhudP2MsR7ScM2zeHu\nX+syppfU8HWtzPDUJurB3VWq/hp/1X4S/Rty7h1YXOeI1hc74kj/ALRCnOCqZRk8toww1OpzRxeN\njdqOLrQ5HFP2VNK0p9rrfjWz0mwvruNZCkEOyNrdA9y4yI2SNYSzyyRkYKKNjA44AwfHfE/jeNrR\np5J5N1wkY8lQ0bRM8YJEQUK+WB3SKxO0ggkVw2v+NpD5x3RvAGmkysgVZFSPPyFVGX3kMeSuVYHB\nryPxH4iP7y7lulikEaN5Z+cK7KpCMI12Mu/ILDAYE8kZr+XMwzuriPaQpzcYcqSa5eV2+KbXLvO+\nru5NpXbP7Ay7JMPhIqaguZ3/AHs+dvZWiuZu0e0YpRSuktzpPEni13Ls6HbHJLgyynzXkQCJQyow\nbyjGS7bskkgA4PPkWreLJn2h7pkViwOxShG5sgqw3ll2qBs278feHpzfiXXJrJVZp/tBmYSSyRts\nMYnIRgsasX/dB9zMowcAcDNcXc6giTQlCHfy1ZicnyotuPOIU5JKFg2HIz1GM48qHNNQestLd9Xa\n+r21v1SPUUUleKjqtenrtovwOkbUJ3ScS+YYwzMPMy0uSwLEDcoTA3K2NpB+YkrxXjPxD+IOo6Gd\nL8OeH7S58QeM/EOpW2jeH/DmnQmfVdV1i/maLT9OsoYwYzMyuQC7IsO0zSFI1eRcn4kfFvS/Bmny\nTmSbUby58qxsLGzjW5ur68u5I4baz02ztUkury7ubpo4ba3hR5rmd1ihRnbY36dfsX/sOa78NtN/\n4aA+PGn+X8evGVpNL4e8H3EQkHwT8L6rGGXTyrFlT4ia1bPnxPcw5GhWc3/CPWkpmGpvJ+u+Fvh5\niuNM7w9KrKph8roSdTM8wUFy0qENJ06TlaMq02lyQd+azVtdPyrxT8SMs8PeHK2YYiksVmuIjKlk\n+Vc7jPF4xpezq1kmpwwOHclUxdaUqcHS92lOVRqIv7Lf7KNx8IPD1z4l8byWOsfG7xnbCTxfrVsy\nXlr4VsJN1zF4F8OXLJ/yD7H5JNa1CEbtb1RWbe1naWQH2DoHh17GcNcSI6ksJHKMxKg5yEKgMdow\nw+baMntVi7uNR02VQFlZDI4dmTa7EIdpLYGBxnYQVx83rXV+F549UZGuFlSSRiG24ZlyTmUZ2oBy\nAwAIIGADnn/RTL8FheHMhweTZRRhhcpwVL2NClR5E6nvc08RiPtTxFZvnqzd9Uknyxij/LjNM2zH\nizP8bn2fYqWLz3Ma0quIxNSEoxjvGjh8NSlKfsMHh6PssPQp87jGMHN/vJSlLrrDStMkt4hsRmC7\n3LxrlAeAVwvzcfNsX5sZyc9Nyy0zTvNUeQhjxgzINq/vQSpKcg7gOFJ6EZ6VqppdpaQhQ7OPLCq7\nMA5JYRg7ABsXpyBnGc08WkEIDb2VSojKdEyozuUoSwJ7AgY6ivLni5XUXKpZ6LWV1qkntrr/AHrf\ngduHy9Q5XKFG63s9mrNL3vLtv57k8tjpHlfLAAVZWwDgsF+Vm3YPzAN90f1zXxv+1n+yP+zb+1t4\nattA+NPhG5l1vR7S+s/C/wAQvB9+3hv4g+FobjLyQadrUMVza6jpM0xWW48Pa/Yapo8sqvLHb29y\n7zj6rvG2ltjEqg+6uNzAHLY5DEKDlmODXH3Vn9snjDQnDzSmJy2Sd3K43fK2cghTxk9RyKSweGxc\nXhsfTp4zDVbKdHER9pTqLmVuaE769Y9YtJpo9CljsdltejjsrxdfLcww13h8XgZuhXpOVm+WcErx\n/mjJSjKN001dP+OXxJ+zH4O/ZE/aN+KXwW8H65qPjDQfhlN4P1uDxNreiWWj6tqk/ivStL191u4t\nLuJdOju7BL+XTo3SVTdzwm9WK2Mnkxfo/pUCWtneW95BMqXM8l8bxXkiggS+tdNeOSZ3J8x4oYnB\nUJIVkjRmZm5rlP23f7NH7aXxx0pdMia6sdF8J/atTkSMmJoPDvhuSyaW3x5l2oR5ow/7zymVmfCE\nCu3fUxI2m2MvlSJBpjRJDBfqsdzBE5nkjlVI2eO4nRzPFbHqqqsexG3n/MTxbqUf+IjZ9TwlD2OH\nwWaZrg6MeaUv9kwWMr06CUpNtwhGHKteZ/au9T/VHw9xGOxXh3wfisfVlXxmL4dyjG4qtJRi62Mx\neW4ariq7p04xpQlVqVJOcacIRc22oK0bfld+2lF5fwy1+8jVTLpMNjqqXKsgAg03xWn723ZD50v2\nm2ijdnVQscYCgkHj7S/Z7+LVnqfhHQ4Ptsdxcpb28OXuGMcdukEZbJmwS7bmIypYLzjaBj5a/bF0\nC78Q+Cz4e0iJH1DxBeax4G0uxDQReffa9etbaJvuJjGtjF/ajwxeddFbaNmMjsqAMPF7b4Z/tifs\ntX+k+EvjJ+zd8afBfiHSrUaRdQzeANZ8UaBqdxYZtJrvSfE/hO18QeH9XiujDvgu7HU385JEI25K\nj6PI+HsVxFwPSqYShPEVMvzKq37GjOpKl9Yoc0Y80IOUFL6pUlzJPkUW9D6HE57lGV8Q0cvzXMMJ\ngFmOVUa+GWKxFGgq88JVpwqcvtGpS9n9YpuS0T51u9T9zI9Th1vR4prVibh76IGQjKiONd6KjKx8\nznaqBAAoDHBziug8P+MbzR5M61Ct1YSFY7pWDeWgGPmLRKGgkAwMsG3E8t3H5S+GP2v/AB94Fl0e\nLx/8K/HnhfwpdNDb22qeJfCHiHwzbCd2jt5JIJ9d0mxgkKyAHYs+/hkUl2Nfpf8AC74ieFvHNk2r\n28lveW9wgSS16h0bBNxtODg5MO0gnIJDMVBrz6GVY/LalKlmWGxGHqzu6cq12qrvyqNKUoxv5xa5\nlbmejRxYzHYWqpVMBicPj8O6koRlg60KydnG+tGUruMWm1J7JvVH1Vol5Y62kV/pNzbz23lyk2vJ\nmhUkHDbsjAPQlgegbnmupSM+XI0EmVyp2KNksUinOAQShQ4YPkfJj16eUaD4Zj0+8/tfwfex2+cN\nLpMrl454SwzFEoIKt8xVHHUEnkA59q0q+tdVaIXdpNZaojKsyBCqH5iGKgBQygDdnHTLEmvaxEJW\nhK9pu0HyrrFLa1kreS8+6fhLE8tSUJQcW5c931jaMeZXt0XS+q6X1rQ6yryvZ3UMchUlGDRvsJC5\nYPJIAD8hILdGOR0PHPap4at7KO5vNDlEW6I3Mtiq5tJzI4J8tTkQTxBRl4xtkYjeoBJr06/0Qs7u\n8LFJI1eORBGwCurcnK4wdpPJBwawYrB7XC7BtG8o7uGURvlcqH2jLbhlDwR0zgV05Bnee8KZph85\n4fx1TLMyw9lDEUPdjUg2pVKNenbkrUKkklUpVYTg03JJTUZLz89yTIOLcrxGS5/gMPmuV4iLUsJi\nFdU5XjONfCzuqmFxFOSjOnXoyp1ItX5raPyaWfMiQMPLug0rNBJHiRWxvx5gCpKGDBjsDKuOcEVj\nyrLt80NtHzI6EHChjlSEx948gHpxyQcA+wazpdvqEcaSWZSeFTh1+UxqAN6iQ5C5wCcEk7gAG5A8\n31Cw1HS90c1u80Em4x3MZBlhjQ7T58PlqpQqVfKZIA3/ADE4r+3fDr6ReRcRfVco4xWH4azuUYUa\nWY1ZOORZtVjGnGfLWnLmyrEXbl7DEyxEKnNFqpSi9P4W8SvoycQ8OwxWc8DLEcS5BTlKpWymEJT4\ngyuE5Sko0qdOHLnVGMUl7TBqliKMVedKro5c8wLbCJPuAcMjAEAYVSpUAqBksCcE89sVXk3+WsoC\nqyswLIUYZ67ggG/BBC7SNqfeBJ6XJChDeXumQw4V18zdyrLuKEgKyFlB4yBycDgU3kEbJbrE+0Ro\nzbQSqvnBO0nkFOPlPzMeK/pNSjJQlCdOaqQjUpunONRTpyXNGcHByUouLUk43XLKMtmfyxVpTpzs\n1OFWjWdKrCpzRlSqwdnSqxnrCrGSlF05pS5k9NGyDbMVEjMpXzDg7txx1UPtHyg5OG6Eg/xUsLSI\nyZZAyuCixoWJjJIKl8/LvY9doJ2kgADiCado5GVV8zLldqheExuUou35uTtI6gnGeKS3YgMyxkMN\nkiqSpDgqcbhkbJMkYXA25BxipcU9dvP7t16fmdUE0rLRySUvPa/pr2tY9C0C9isrhJGaNl3ZLSqx\nJd2+YfwkMF3DzJDjHQZGa9M/4SOyPPnQ/h5X/wATXgP2nbCiuG3jCqc/6xzIDjdyrMvKnAxgdql+\n0Snnyz/38A/THH07V4eMy2Faak5pa+cesf7r2se3RzB4emqcY89ne9n15e6dtne3XXsfR+s+Iy0V\n7PHM0iKWKRnzVUvuCs2HJDbWGBGuAozgjNeE+I/EPl2jSy7okW4SSfyZFihBeUo7lQHkYtkhivDK\nqo/G6tXxHrtvDcNGy7Wh2z+ZG7LFKJN7Z8xUIdzkPseIFgVZiSc14BrWsy3cbzajEbWWW+liiiZ4\ndlxbpKCLkY2KvmIxkETnMUoIJJBA/wAV8TiXOK9/VJRWnRcvXXu929duh/tdl2EpqNouMYxtoou7\n2SivTv08yTVta+3BnDQRFSIiFn8vaFRmjV1UbEhkQqWVgQXzk8ivN9Y1mVpJkvHt5FIibb5pkSNB\nkKEjDKZmV2VVUrhicZwKivybzerO1uwlxIYwGM0SKxjdicq37yNTtRsH+HNc1qd9DpdncX92sWxY\nmfEskRuJJIIy0kBaRgVUk5DxruiwcfMM1FLDOrJxio2cbWUoq6dmrLmvvba/zR2Va6g3TduWC02W\n6vK/dfN2XkZmu380MErJL5UczK6yY82SSPG0RWo+8NrMyElgoJ6Epx4X8TPi1o3gbSbiaXV9k4g2\nRKDEZYwQQybUUswjYOm0AuSQFyWweQ+J/wAarTRrRriD7OIApBxMo8mNdz72DnywihTveQhy3zk5\nr9Mf+Caf/BPXUPEmp+HP2yP2q9Db7OgTXf2f/gnr1ix+1l2juNH+LXxC0y9U7rCH/j88AeFL2Ddd\nyGDxTrcYtYtLspf1PgbgHMOJ8woYanB04UoynicRONqNGk7N1JtPWSa5YQTu2ttGfnPHXiBk/A2S\nV83zGpGpUUZQy/A0nGWIx2KfLGFGlB8yVP4nUqzSppac3NKKfrP/AATZ/YL1fTJdF/a//ad0GaLx\n5ew/2n8BPhJrtsEf4f6TdKLiy+Jvi6wlH+j+N9VtyreE9EukEvhbTJhrF/EmuXVtDYfsVqJ+0tJJ\nI7eY7uWEhd2EjM7fMMEE8kBwSWbGATjOtqOszXkktzPcGaSRi8jyAyb3kDeawKgDBdtzAcbueAMV\nizXsc7FsfJ8qsxBJwAPkRVI+UnBDAjHTGa/tvhvI8Hw7gMLlGW0eTD0Jc9Sahy1MTVfK5VKz3lf7\nMZSainpbS3+dPF3FOacZ5vi87zitGticVzU6WH5+ehgcJJKCweGU0lGnGF1dJSk0pPWzPL9asIpC\nRJDEEIZgT5gcZ6ozYKgsQx/2QSDtGcY+kRLYvJ5UPzFMAhX2qrMWPzKeABwGyAe1d5qSwFssERWV\n2KNj5FZSWIQjczZx8x44IzXFyFo5CiqiA5BEYVlYSKdpYHHyjIYrxhuMYr7elXdSnyNuMY2Si23o\n7aX7f8Ol1XwcqEFU9o+SnZrlk9W4ppt3Wun/AA+pvPqNw7wsJiHAXPJO4qcjjJXgYAB4PBOTWgmq\nyrlcqrvukVuc4OdzNkAL3XaMkEghSK4tb4wjeFJydoyGAU7Sc7QwGMqSVHX2zVI6ozTBy7FdhUsB\nlSwj6YBO3rzyfTjpWnsE0nyWWlpO9mtHo+q9OnyBTtKVpScNVF3dpWa1TvqtrPyOuvdSh3Y+Zmch\ncK3z7HALEMcbRuwSd2cAitbRdK1HVrhBaQSXKCSNXYQnyhLI37iHzDhBMzJtiXJeVjtRWOAfKZbu\n5+0xs7kxGWEkIjfLGQpU7hu6kYyBkE5PbP5mfGv9gT9oH9qz4ueNdS+M/wC2xr3hj4HQeJJNX+Ef\nww8BaPrF8fDEX2aKHTo7vw6dR8NeEdP1DSsTRy62s3iDXdalLXpn06S4kjT5Pi/iLNOH6eXUMj4M\n4g4uzTMIYypRpZRShTwGEjgVSdX+182rt4bLZVvrNKpgY1adR432OIowlTmoyX6h4U8E8E8bZtml\nHxD8YOHPBrhrKcDQxtbPc64f4i4qzTNa+IrPDUsq4Z4e4epqvmuZJpV8RTr47L6FDCRlWeIbjKK/\nO39vj4geF/DP7a37SWoa5r2kRgeLrbR1t9KaLVrtoNK03R7KSzkhsLmQlo1jaR0klgWIOyM7upFc\nx4M/al+GvjrxloPg/wAEfDv4kaw2p3mnWzeKF0yztbDSLqWzuIJbq6tbWfUNli11HbLJNc3tiYIB\nJOqS4ETef/FT9nX4Z/ssftY2vwx8L3t98StBn+Gdx4mHiX4j6Lo76xp/izT/ABB4q03UNXsNLsPN\n0RLa5ufC2dPj1GHVZ4INQaKaaa5AmHd/GD9pP4nfCj49WHwn1fwj461Tw5ovgjQotR8H2WlaZ/aH\ninxfeaVf6vb+Pfhzc6NZldZ8HX1nqFjDp++C7VotO1MxJazwYH+XHFfElbP+MMdjHgKGBxeYYriW\nvicHj8zjDEZfXy/M62HzHCfV44OnHFRoZhKrhK2KjjY06T9nNOVKrTqy/wB3eCvCPwzfCnCXBXhx\nkvEnjDmmL8FMP4hZBxhxJxNQ8MsqxmTQwdPLsJi8u4VpYbFZjDFUZwlWhgs9zehh41MPTp4x1aFV\n1anmH7Q8+pal46+J/hu30rX5dc+BPiODxP4/ns7cXun2WkaTrej6gfEKPZ5mi0vTpNRsNOuvtcKG\nO8khUeas6NX776T/AMFUv2PPiX4mi8P+FPjpq2h6zrurWtpp1r4u8GeOPB9jfahqUqW8FuurXVg+\nk25lvpViEl/dWtvDI6/vUUhj+A3w9+MXinxX+37d/EHT/CXxG8KW3xL+Imkw+JvAt/Zrf67B4F8R\nwaToWoaF46028021sdZ8O6vYy20GqRahZJaXFje286b7mOCcx/sceKvGfh3wL4un0D/gnt4a/at0\nNPilZ61qHxLu/CWu61rngy9sLKxFv4S8MapaaVqOm6a9oijxDbLLDJGlxfpPexfZlt5of1DwY8W+\nKuEMRhcg5eFMBQzTK+EsyzKvmMM4xc8Pi8fHMsLjMHCGSwxdaFX2k5f2fXw31qhiIOhCtLD1VKM/\nk/Gn6FPAfFWRcR5xxnknGUOIeDeBfDfOeFsPw94peGfC2Ar5nx3w97DiXDZnjvEG+R1I5VxTw7jZ\n0aFXOaCzChilRyynWjGFU/pf8ZajF4nstV8PeLIrTxHouoRSWWr6Jr9vHrOk30BZoJra80zUori1\nmUgsrB1HLHaySAsPxl+MX7Nniz9nvWrr4j/ACDU9e+FWLq88Q/DezebUfEHgKFtzzXfhqEtJda94\nRt1BL6chuNZ0KJ38pr6yUvB+puo39zeTebILq0kuY7a7uLe6PmTWkt3FHLLaXDRs0bzwSs0M5V2j\nNxFIUYx7WOV5c0csbRTsXSYMkjN5RDRoScuoGOOPlI44JIzX+mfFHAeQ8bZUsBnEKs/cU8HmVJN4\n3L6koRnF0FVg6lpSnaph69WlJRVpQhUkz/A3gfxG4o8Os4+vZJWounOrGGaZJXftcozTDUajVSli\nqWHqNUaiqpPDYujOdSLpe0jelKKl8D/BT9ozTPFVpZ3+n6tDMQgWXDR/JIyr8p3kOqowKNlflddo\nAOa+89C8ZWutC3nlljjm2rI3llVZ+ykBmG9OjMB1HHIJr5I+M/7Ful/EG/u/iP8ABe/tPht8XHaS\n8u7Rc2ngH4gTxMJJB4isLRQug6zdDMUfiTTbcwSSNG2rWU67pU+dPAnxr8TeF/E1z8P/AIm6Xqng\nfx54aCwaloGsR/ZrhVVtkV/ZTEvb6npN8oEthqWnvc2N3AyywTMQ4T+IOOvDPPvD7HSWK/27Ka0n\n9VzTCRlOhUUm+SOI5k3haqhFc0ar1esJyTR/f3AXihwv4m5e6mXVXgM3w9GNTH5Hi5Q+v4L4E6kP\nZSlDGYKVWb9jjKajGorqpToVo1Ka/avTdTSfcsc8U1vHAwWN1ABI5ZWOeMdEUbvkyABmtJ4IJtqB\nGKlCrGM5baSVHlbl2rGpwGLHIGQTmvjPwP8AFhZWRZrnzoZcDe0ygLnaVf51xjoPlByMgZbivqDw\n/wCKbXUFiYPHPEWcEB8OsZ2gupRsiPPXco9SK+EhKnUp8r5Pe7Wlo7WacVZv56eiPuXQlT/eQmp8\nur5ZXta107PrutPK97lrUdLKFsKyxnAZywZiExwu1jnONu4gAngA5556fS3CbJUYiQExMSWY7hub\nzF4+58oILDI4zgV6K5tbnM3meXGg3RvE3z7W3FS4J3svGAz8EkFeOazJLaaXdG8UkglQMXLsHBxt\n+QA84UfP7dQTmuWpgqdRSi1TkpKycoKTS/uvTl6u6Sb01tobUsTVgueNJ88ftqymk7JxUtJJP7SU\nrPzZ4lrPhALKj2sskTyEbgxcReYSW2Rkbk2SDlirNlcjPpw+o6fcWF4YbmKZFaHYrqWkgYsA4Jf/\nAJY4kzgkhWXAAzyfpWXTlEiusZKx7QwY4LEH/Vqeq4U/dA3EY6VpyeGtN1O3kCwJuniSOSMRKAhU\nhiGIXadygYzj3bPNfp3Anixx14f+wwmAxsc5yCnFxnkOdTrYrDUo3i7ZfWUvrOAla6cqNT2btHmh\nyxPzLj7wi4B8RoyxGZ5c8lz+afJxBkkKGGxcppe5/aNJw+q4+kpu6Van7WPvKFRNo+NpAoZGCh1Y\n/IVcloxwGBDHkg4zyCN2CetQxSx5cBWXIfdukYfMmd/AHDFAACDxnPevZfFfwvmiknubCVLJ0kkA\nt3RHtbklcxmMof3TE/LIVVFxydrEk+SzWV7p9yy39ubZ5IyQ77zA7ciVlwCgVxlUBYMCMkV/ZXBP\njTwXxvCnhaWIlkeeThBTyTN6lKnVlVfIqn1PFqUcPj4Xf7uVNwqvWE6MJR1/irjvwI464Dc8bLDP\niDh+nUfLnuSU6tWEKb96nLGZfOnUxeEUYL98m6sV8cKvJNIhYpLFGwMgCsBueYOFLAMpOSNrAYKH\nHzEEbhT2+xgkMyMwJDMC+CwPJHz9Ceaj/dL5Q+VyyeZEwKsGZFBLOyjmMA7VQ4btg4xQQ7EtuXk5\n4U9+e8Oa/Ua0JXjdwjeMZLnqRp80ZP3ZR5pRvF2bvrZa6XTf5NDmvKynWipW5qdKVRQnf36cnCEu\nWUXa6ezvu00cj4l1x7jWZLiG8lNtJGbVbQGFbSRkkH+l+U0XmCZcfZ0dJhFtbaYjnjzjWtlzfRwi\n+jug0bbopfnMdu+cx7QymOYOSSwBHPQVw1/4j3LPgvMVw4kjYAhVcIgXH39jDY6OoVm6/dzVK38U\n6bp8E9/f3cSuirsa7fyFgnBMjoZeVkOEy2flbABGMCv8PsPCpVUIqlLndrWV+1720uui+STs0f7q\n4ilSwkFWpVYwlBSsnFe8pJJpc917vmna/Q7XVL610SwWS5khgKxN+7kX/j3i8ti8qEhw7eWHGGAV\nc7uSK/Oj46/G+31Ca60nS50FjpTlbnUVnjjS2ijUgxwldrFZBzK25DMQV4UZpPj/APtEX+tXK+GP\nDUpvZ7y6i08Np2+4u7uW7KQW1np1vZoZbq+vJZFgtbS3jknlkkWKNGd1U/pr+wl/wTIuPClxpXx5\n/av8P2zeI4nttX+HvwJ1UR3cOhXceLm08WfFSESTWt/r1vKEutF8Fu89npUm268QCa+Cadb/ALr4\nb+GWY8S4+m6FCXKlH2+Jrw5sJg6abcq1WV0va3Xu0Nara0hrc/GfEbxMyTgDK5Zpm+Ipzr1E4Zdl\n0asYYvMcT7n7mil9iLlFVqjUYU+eKc02k8L/AIJ3f8E8LjxbeeFf2n/2q9CuV8LWZsvEPwZ+DOvW\n8qnxUytFf6V8Q/iRp0nMXhy3kWO88K+EruJJ9emji1LXIY9Jht7S+/oFvfF02pXM1zPeESMxULl8\nFSrBdifII1KbVCBQiLgKNgArzvUdamuy9xcTSb5iDtllLEcjJzgARqAFHQBQiKFVcDHa/dE3u25S\nhBwoblOB8oAPzAn5skKRjtX9xcO8J4Hh3LaWX5dSbSjatiZwSq4ubd3UnZvTmvaNkldpXuz/ADZ4\n14/znjXPK2c51iXObvDBYOMr4XLsM+XloYePwqSS9+q7zqS1lJpaeoSeIhJEnmTBdxXD7Cu1SuCD\ntKhjkfewcZ6cYrOuvEb/ALz96NkZjVWU5yRneQcoFD/LlgDgL0G6vPG1Ms0gZSpWNVjO5ihAwcEv\nuVWPUgAgk5xnFZ898H3FpHO2KQsH2/u84CnCj5iDjaMdexr6FZbFNNRs0rba6tatPXXTyZ8p/aTv\n8d/V9NOy9fLY7O515dq5mygDI5kBIBIY8YP8OM7lIOflOR14fxj8R/Bnw+8JeIviH8RfFOn+EPBH\nhWz/ALS8ReJNWaRLK0i3iG0gjihR7i+1DUJiLPTNLsIZ9R1G9litbOGSViFoiR5zDsdcuxBTOxUY\nZ2sVYbn80vzzgZxwOK/E39p3U/Ev7cf7f3hD9hmDW9Q0L4E/CPWJNZ+JA0Zliu9Y1Dwn4YHiP4ge\nIrm6yyyX9hbX0PgHwaHSW20K81C71WO3n1C5cj4PxE4tp8CYXKMBgsPTzXi3i3HyynhXJ5udOjiM\nZGWEp1sbjK0ZJ08Bl08Zg3ieWPv/AFinSdWgqjrw/f8A6N3g5T8dOM88p5/nk+EvDHw04NznxO8X\nOLqEI1sdk3AnDkYPMcPkWHnGdPF8TZxWrUMvyHC1YOlKvUq4irTrwwzo1e51v/gt34OPjSaHwD+y\n7448ZfCrR5ZI9b8VX/i5tG8ctaAOY9TtfD2meHtd8OaEkoT7Qlh4k16SYwZ8+e1fcI/0i/Zp/az+\nBf7XPhjUPE3wf1zU4dV8PR258Y/D3xVb22m+N/CR1FnhsLq8tLK5u9L1bRb6SJ4bPxDod7fabNdI\nbS6axvQLavYPhv4N8H/CfwrYeBfhR4P8OfDrwLp+I4PDnhywitradQvlSXOsSMsl14i1S7XC32ra\n5NqGoX0m6S4lcttX8aNe8N6N+z7/AMFrPhhpXwfiisdN+Peg2f8AwsnwTpVlbaZpejv8SPDniRvE\ncFvY2gjt47Jrrwzo/wAQ4YhEsdlqDStEibkVfyjG8TeLXhtxnwVhOOM24d4s4T47zj+wZV8pwk8F\njeHM7qQo1aGHjQ+o4VzwMqLxVWjjZYjERnHB1sLjMPRxWJwFeX9L5Lwt9FP6S2Q+LHDngf4Ncb+C\nXG/hX4V8SeJfB/FGb+ION4yw/iNkfAlOjis3y/j7K8fRqZfkObZpljrVcDjMnzCOCy7MsRRwtSpi\nMK4UZ/uOJImQbSGyAo4G8ncVLEgnADd+DnHA61atNMkvb23EKSbDdIhkA3K43KFKhDnljwfmGR05\nr83f+ChP7YPxX/Yst/havgb4V+D/AB3L8WtO8X2Ol33iq+1gXVj4z0S90CPSLKx8OaRc2sur2N5b\narcwTs80InvpbSKK6tnt5I7j9YbrWtG+GfgnWvil8R9KvPDun+APATfETx5ommtDqmp6JLovhuHx\nF4g8N2G6W2t9TvrK8iu9FtJDJBbXN3GksksMDs6/reH8S+D8Ri+K8Ng83qR/1Dr4uhxPisXhK+Cy\n7LcTgKuLo45YirjFTpVo4N5fjaixLUKUaFL21ObpVI1X/IGZ+DHiDl3BHhZx7mOVZfV4e8bHnOH8\nOYZXnGX5rnGeSyXGYTLswpyybCOOOwUqeZYvDYGm8Zh4cuKnaVBKVGo/5XP2tUt/HP7RUvjfRde0\nK7v/AIdfEb4+fAz4jaK+o21n4n0q20jxp4m8U+BbmTRWkjuNU0e+0vxULC31jTI7i2ttQ09rW/8A\nKuI41l7X4keFPFviS9/ZW+Kng7UYNa174Calq/gT4k6PYeJ9P0vxf4d8I+MdRbXfCniKwjbVIdQu\n/D+nwav4ptp0tI/PtNiZshp940sfyOPH2g/GX4l/tCfFDwZFqmkaX8Uvip4z8caVp/iGDT4dX0m2\n8YX8t5aadqgsLjULKDVIYJxHJLa39xZJLIskNy5Mbr9JeE7a21b9rP8AbAu4pdmn+E9I+G3w5tjE\nws4JtQ8KaboPhXM7phJ5YLjw9qzMzvgpdXLBn86QN/ldxpgcE+NIRwWN+sYSXFXGPGmDxX1eGLpP\nL86zepRxuVyhGeGr4nCYyhxdiaFCpSqUatssoYirS5qMqGI/2f8AD6nxtkeRxw/EdGjw/wAQ/R98\nEsZw1isozvLKyxmLy7O8wp8H4jhrP6c8TTqU8THD8fZ3DLMXhJUI4V5RltWVHGU3WS5P46+OvCd1\n48074g/ELV9b8D+NPDXgS/0P4f8Ax98AaM2u+KNB8U+DZfD194PuPiBoseqQv430yHw1/bvgyHVI\nIF1zSo77Tr2c6kdKgij+uvgL/wAE0v2yfCHwv0LVPgJ+3Xb+CfCnxF0XQPiXD4Z0jwx40ttMli8U\naBpGq2mp31iW1GJ9VOntp1pqmLVBcQWxtpp5YwUb8xf2tJleP7NFELqKa11qGG3tYcR3UzaVBZzS\n3MTtE0azPYtcrPAgEp5CcnP6gftyfFP4i+Ff+CWv7C/jX4bePfGPgHWbjRPgMNQv/B3iHU/Ddzqg\ns/g1fy2Vve3el3Nrdz6fa6lokV6mmzSPYz3UatPBIkSJX61wPkHCPC3CuccZ4vGccZdHL6/DWX4T\nB8G51lmWSUM5z2WXQi6uLyyvicJgauJxqxGPwWGrSw9KrUqVcBh4TnU5vzPL+M/GTHcX+GfgF4fZ\n5wHQyrxcz+eQ42h4n+G3DfiRw/hp8O8PVsfw/hYYTPcFjMZDAYLlxkcqwGGrfU8LXxmIrYf6jOtW\nrYj9SLv4cavaQadBqt7Ff62un6XZ6zqFvafYrO91eDT7aLVNQtLAmRtPt76/Fzd29m0sj2cMyW24\niIYtW3w8lkR/NwcMsZZvlTI+VdoUZXnknDDjnIrqNV+Jmhp4fsPGPiHXdF0HQm8HeGfE2ueIdd1G\nz0nSrCDUvD+nX97qOoX17JBa2Vu1xdlg00iF5Jlt4UMjwxn5ftv+Ck/7HUHxV8DfDCy+LmgeILjx\ntbSS2vjbQwt38PNG1mDUY9O07wp4n8QTNZ3Wlar4gkD/AGK8/s6XRIw9tHqGrWLXsDn/AEiznjXA\n5Dh8HPN87wmG+t0qay7D43HUIZlmDqe1eGoYOliKsamNqV4UvZUq8pKnXqxc60qHM4x/yV4Y8JPE\nDjvEZ/8A6j8AcUcX0+HHnNXPsZwnw1m2NybJaOUU62JzFV8Tl+CeW4JYWjQr16WBpcuJeH5KOGwd\nV8qqfSOneCHsVdmDnbuZZJRGsgGVUx71BUbxgqpALDkkGvEf2g/2aPhx+0F4at9I8bW02l69pCTH\nwn4+0HyLfxZ4OvJRuP2K6dNl9pU7KGvtA1JZtLvgWOy1udl1H8LeP/Ff/BWj9nXXfGnjnRfHfw+/\nag+Funar4p8Saj4SvNK8P6leeGfBdpcXmps0+hS2HgvxroFhpOiAJcL4V13W4tLS1aab7QoMr+Ye\nCP8Agpf+3V488MXXxY0v9jLwr8Rvg+uq3OlvqXgDRfiBC9nf6bLanUYI9Xtte8T6hdzWUNxbxTzy\neGpbeGSWNpWXDJX4h/xMp4YY6hjMt4wpcQ8MTisN/bGRcX8MYzB4zLo42cZYOrj8vqzhiMFTxFKt\nh6eHliKFKtUdq1BSdWCf9XZD9AzxhzXKMDx/4P8AiR4A+IWRUKmAoYHibhfxjyjJ6mF4nzKnz0uE\ncTh+KcJkVfC55i6dDFKll+Jp/wC10sPV5Zziqso+Q+NLb4vfsp+LLPwn8XrdtV8N6jcSWnhT4maT\nHN/wi/iWOJy9tFI7F5ND19I9rXOi6g3nB2kktZLy123FfTnwz+NMc7QT29/JJC4fbsk4kjddzAqC\n54f5RkqSR0IrX+Gf7Z/w1/bK1bxf8DvGXwQ8R+D528K3viDV/DnjW9tte0nVbKwvbK0v4oZY9K0P\nVtJ1bTHvrW7sLye1tZvkc2dzFeQiOb4++LvwB8e/s23F341+HF/qfjX4NRytc3lhIkl74q8AQFg5\n/tdY48az4ehTbs1u2UT2SkDU7UIWvD8jn3hzlOc5DPjvwux8uJOEq2IxCxFKjCr9ay6pTfLVpyhV\nwtKvUpRknKMpU6coQk7upBQxFT6BcVca+HXGX/EH/H7hypwB4l4XA5ficLDG4zLMdl+f5dj6anlu\nKoZhlOZZjlbxOMpU52WGx9bDV6vLGhJybow/XXw18Tbe7jsRNI1sTEp8wsGaYKN23DnG9WK7w4XC\nEbevPsln4jjuyJkC8lPLy7BMnAZ+GxycnGfUA5r8bPhZ8ctP160trpbxJ5NqtCglR4yf3bYRlJOS\nMvg7F2gYBXFfaPhPx+7NDH56x5aJ44vP8xGTbwMckOc7SvC7ecZ5r8PXtIOUFaM4zcXGUo7rl91O\nW9mrNW0fofqNm+ZpKzSvbZppNO+mjTTT7Pc+4Fu4ptirhgdxXbgpsLMrKd+R1BUuWyOcDIFXrOdr\nWbfFFiOVUEkSMDtYnhllztC427w3UV4PpXi9bxoS8qRHOBG2FQNgOyDnc20gsThcErkc5r0TSdeD\nvukkyAuGUNsjZGclFAwwUqRnIySRjOAK6YxfLHmUeZpXTbTv6JnLVirWS3SVtersep3dtbXip+7g\ncsNr7wXCA9XC42bAfmLbvmyepODyepeFbO8hlWdI5YWjjR41w8TfKx+4FUgYKkBSvX5gBmr1lfNc\nKyRSwoknzPksxAJwwAyAdhxjOMkg49N7ZcOkqCN2imeIJKONqIu1xIhUbgWIGMntzxisK2Fp1XFt\nQ5oSvG7fuNtc7js486SU7O7to0zfD4qvhFaLlGM3aTUt4tRUlbW9o/nY8Hv/AIQaedh0qW5spNkx\nRYlDwB/vnMUiElVUspaM4Rs4OSDXJH4Q+JcnZf6Rsydu62ut23+Hd74xn3r69tLPzQgVjCqLthYt\nuZgo+YM235VGT0xnIJB5BY1vHub9wG+Y8/aITnnrkrk565r77J/FDxI4dwcMvy3ivGfUocrpUMwj\nh8zVFpQi/YzzDD4ypBcsYp8skmox6RSX57n/AIY+GPE+Pljs14Twbxriva4jLZYnKfbOTcv38Mtx\nOCo1JqTk1KVNy96Tb1Z/OFdeKPtAjSBHeRLkzfawJYVlBY7DGw5ZWcMRGRgnOVBAz49481y4sLNN\nMuprvVfEvibUE0zw/wCGdGhuNQ1DX9Yvpmt7HTNP063V5p76d5I4URQC+PMO2MF19s0b9k/9vnxC\nFsZvhJ4Y8F2stxKX1Xxv8TvBcFtZxSLsEwtPDd14j1ieSEOkoto7HznZZCJS2Fr9Df2Z/wBjbwV+\nztNF498Ta2Piv8cZ7aeH/hNr6we10TwTDdALd6X8O9IunuJbFHzJBe+JNRmk8QarGWiQ6bYYsa24\nD+j5xpnOaYeGaZdiOHclhUU8Zj8bh50q0qcV71HB06qVSdSen7xw5YKyclc7/ED6UHhtwtkdWpk+\nc5ZxjxBNOngspyTE08XQdduNquPx9OM8PhMLCN/aOFSrXldexw82ueFn9hb9ibwb+zPb6X8XPi9p\n2keK/wBozVoP7RsrS5hg1Lw98GobqEMlloUZEltqfjiOJhFq/id0dtMn8yw0Boljlvbj9HdR8cpf\nmeXzMGUCRpXUsxGTuJDcFiW6Z75yCK8btg9wUklmk3MXZQzE7GkDByu4ltpTO3JJPQY4auigsrby\nWVmZg6ZQ+Yq5eNRt4LZ8xgDjKkHnjOMf3Xk3CmTcOZfh8ry6nVhhqMY3cXFVK84v3quImnepOXNq\n5N9bo/zN4h444g41znF5/nuNliswxM5tTm+SnhqTqTnSwuCoudRYXB4elKFClThO7VP2k05ylJ7E\nniDKiNwzrkYdiVCMWwuFTIORwuQRg84FUrjxA7JsHGSEKhSNmGChVGMMwGSdp4APfiqEtpGHyZMi\nNcgRnHyydMNyd2ACRn7w4OAMVAisu4ec+2MkEMAUcfxvkHPmHJJyTknHA5+ijQpWtZRSSsrenVLR\n6LVtd+mnydTE4uTTkoJ/3X2a33+/VNb3L8+tSeX+7l8thgn5d2EAzlwcMmTwcfMRz04qlLrrMjtL\nMoEh+ZAp3kAEIyj7wDHkkA8A5BzVeWMYBV9wLFQwU7sqqlCc8FmOQQAMAA85rOlEQJ4ViG8sMW42\n/fkOemASMp6ng9K2hSoKSUox5e6eratvr5PfS6Xz5p1665eeU+borbRVnpprra+l79VsdBbauElg\nfzctE6bQBhmIBZQXJ2kKeoxznBxjFfjl8S/GmhfsJ/8ABUe7+PPxAtNaufg1+0j4F169vdZ0SxOp\nal4dh8Y2Wk6T4ouLXT0xNqcvhLxp4ZsNQ1TSrOQ6lL4d1mKSzjmlkt7eb9a94FwjBMFRxjnoG6qc\n/PyNuOOg4rifjX8C/g3+1B4AtPht8Y9P1JrXTruXVfDPi3w9cW+neL/BWsTQG2mu9GvLy1vLaSC/\niMcWqaRf21xp2oxwwiaITW9tPB/Nv0hPD7i3P48B8feHmDpZjxr4ZZ/jcbhMnqV8JTlneQZ9HK1n\nGDwf17E4PBPMsNmORcP5nSp4zG4enicvweZ4CjWpYrG0ZP8AsD6HnjZwV4WcbcZcPeLmDzfHeDHj\nX4fZ34W+JtLIFzZ3g8kzVU62AznK7Lnli8pzKEcQqcYuU4OqnCtG6p/YXw3n8K/Erwho/wASfhf4\nx8P/ABC8Aa7G02k+K/C2oRarpUsrN81jNIqJc6XqlswaO80jVbWw1exmV47uzgKla89n/ZB+BFh+\n03dft0/EHU9aTxh8PfhteWtxcarqNlB4F8H6V4a8O6nbaj47Swjt0v7nXtP8ITarplsbzUG0yH7Q\n11DYyamYJofxm0X/AIJ5ftv/ALHPiTUvij+wV+0PaeN4lRrrVfA8skPhXXvF2n20Yk/sfxR8PNcf\nUfh18QJPLDQxo11Z6i0mG0l7O5aIj6t8RftK/HL/AIKH/wDBMz4r6Z8G/h1p+m/tJT+MNP8Agj8c\n/h9pupReHIrWxjvLXUfEmoeFz4mvrf8Asyz8WaKIo5dJ1jU2m0RLfxVpcV7ey2Vs1x+JZv4vZTxP\ng68uJ+Bc4y3xX4Apf27wzw5muV53h5RzzPKlLhrLM5oZXUpYbE4zLKOKxf1ur9dp4zK4wwkswweK\nq1MveIw/9KU/o45dwpmmB4i+j19JzhnjH6PviVm2WeEHiJ4gZfmVDhPi/gDg7j7MqTzTJ/FPJcfh\n6VXKcrxuByyvg5Zxl0qGGzTG5fHCzwuD+uQw9T8hv2mdR+LP7d3hT9pL/goXd+IbLQ/h/wDBXx14\nG+F/wW+Gtxqtra3tn4NfVTeTRaVYvdpc2lzoen6h4c8SeJtRtLSe91zxL4iv2DLbaEFtv6TP22fj\nDoPiT/gmH8afjb4dvbe70z4n/s2+FrzTmt760uri3m+KeneHdOFnei1mllguLa71a5splmCytNBd\njh0IX8p1/wCCDXw9ubPRx/w0n4qttfbwxph1TSIfh/oOsaVH42Oj20mtW2masdc0u5k8Pvr/AJsG\nmzTWAvo9PEZle4k+avzW0L4DWfgv/gnl8c/jlpvi34h3PxBvfjrYfsz/ABO+GNjZwQ+BvDmk+FvE\nuieN7TxHr6Wsc+rajdPeadYWGkNdm1stN1DULqCNZZpiJP59zLO+LeDsB4kcKcSZRnOHxniBkeSV\nsd/rPUoYHFU8Dmuc0uGMxzHD11CtDOHj8djcyhLDxqfXcPXzBU5KVClh6kf9DMwyz6Lv0lK3gS/C\n3xowdbhz6O/jr4fZHwdwjlvhXnGUZbk/CXGM+FFgOD8wzTGYvA4erTniPDzN+J8TxtUji8Ni8yzB\n4LFYWjDMcF7Xzb9mLw/4o8J/Gz4W+F/EGm3FjY/E2y+Hfi7RLG4mjWDXPC/iXxNpFppmqW5QSxvb\nX1guohreYCREtrmN08+JVpni3493fhvVP2jbnwhc+IdK8a/ED9p6/wDF9r4ogt7Obwxc+B9F1rx5\ncXnhbU1vYGea5vtQ1fQL2CGFEjGm21wLiSNZIlb2i48SXvhL4Ufst/tDaZo0es+L/wBk/wASw/B7\nxdpFzJNbNeeDvFEev+PPg7fak7xzT2qaT4ifx/4Xz5JEMum6PaFVYg11Pwt0+Uf8EyvjtFqMR1mL\nxRNrHxEnguRGLi31zwp8TPh14b0bxVbbwZHbyl1eG8lUp51ncXMDFo+a/BsdmuMWPnm+aZZGeIyj\nOsFwriqEMwlhp0sRieKvZ16lO9GtL9xlv9h5vh8NVhCGKw2MdFToqCmv6swvFPDPEOZ5h41Zrw5l\n2e5H4pca+GfhFm+S0MdRw+FjxVk/iFxJleb4+vhqzxdTF4Shw7lXCPENTL8Z7GnmuGx9LD/W6MlV\neG+dvi1r/wARfGek6d8QPGXwP8ceCPBty1u0Xi+XQdek8J3UOoWEi6aP7RuNHsrSKO4NwLixZbwx\n3cJjjtzMGVj9w/tja/Pe/wDBIb9gSyjVpra6Xwfp13erKssVnN4X8EeOtOitXKs5ilaTzlaGUiS3\ne0lhZSyMD5l8B/E19pPhbwjqut65qV/8PNY+A/xN0j4uaRNfTS6Hrvg7Tvhb46hFrqNpcXElpqF3\no97b6Muk+bEtxp2t2umSWbwTxBhh+LdK8YS/8EW/hhd3ayTaLB+2B4vutOlmUyNZ6BL4Z13TI3jb\naxhspPGg8QRA5XzLqWXaOWDfpVDifOIcO8bcKZhh8FVwsKnh9mVHHYKNWNKGGnx/lGFhgsVTqe2d\nDFKc3y1frVShXp4vLav7ilifZL+fsq4Q4JzDx68IeM8k4UwXAeP8K/pTUvDKvluX59m+Y8O8SLiH\nhDxQwVOeCo51zYrLOIMlxXDWXY+vgMNiMRhK2ExuDoeywVX2yrfYX7aOn698bPjj+yn+xBpmq3mm\neB9Z8E+E/it8SbzTH2zX+h6XoV79hWGX5oJ/7I8KeFtSvtIha3ntYde1+zv3hmk0+BY+r/as/Z6+\nB+lfsafG/R/BPwu8G+AT4A0Pw54z8O6/o2hWf/CTf2h4c8UaTpbW+reLrtZ/EeqSazpOvahb3cl9\nqE4uLmaGZY43hjWPu/2nPhr8ULHxL+yb+2H+zz4Pm+LOvfCD4a+G/Cvjf4faWtyuveOvhjrnhWO4\nsr2wS1jn1DUVt7HX9b0u/isbS5v9L87StTgsr6C1vIB8wfGT45fFX9vLSdF/Zd+Bf7OXxW+Fun+L\nfEuj3Xxn8Y+PoZYrfw/omiX0F1JaT3UOm6Vp2naDpN2qa/qc2rTprWu3mk6Vo2m6Mkksnnf0PnuZ\n8McScOeNvCnGGBjjfHTMOPaNPhShicFWxGb4TJ8LxLlGL4PxnDNWvRnPCZL/AGLhKmKU6VehDH5X\niIUKjlerCl/JPhll3iVmOYfQx4h8JeOsDwh9GvwajjeJPpB1aHHGS8OYPJ/ETJePeKM38TM78UOG\namcZZj86xef5XhMpwnCc6mUZph1SxeHy/CumqWLpL6V8dfEXVbj/AIJ7+KfiprN1cWWteJ/2UNDt\npbsM6XL+IPHOneHfBDzrIzeYG1CTVLqcsS0jJPNLnLCtr9jXRbzwZ+yV8ArLTopdMur/AMJS+LJn\nt3azuZbvxhrura4980kRSUzTWd1ZKoc58mG3/u1w/wDwUx0y38L/ALNfwd/Zr+G9oZ7z4vfEvwD8\nKvCFqhMEj6B8OrDT7Gw+0RxAoBf69f8AhVrlP4JUmkYkKrN+hz+C9L8IafonhTTlgS08IaBoHhGw\nECosckHhjR7PRYzAhB+RxYmTlm3ht5JZs1/SPh/WqZt45eJ2a410cfS4V4J4J8NPa1YU61HEY6lg\ncDj88lCT05oZqs0Vemr069RVK0E1W56n8XeLlTLMu+htwPl2V4R5bhPHv6VfjT44ZTlc3Oli8FwJ\nwVg6XBHCuHrU1y1U6GN4hx9ChzT9ypl2KVJxcnzee6jdavqMqvqdxLe3Eds8K3lxHDPqIt2KsUlv\ndovZolZVbyZJniVx5gQnmsaBbiMnaoljljaKSCWKOW3a35WUvburD7NMmY3ik4lRmUq6nFdtqKIs\n0sQ3SnYsRlwgAH3tp25wPUkjONuKzLJI/PO5du+Mlm+Qxk7SpBAGGDEcLgY4XkgGv6RyzCZflmBp\n4HLctyzK8DS9p7PAZdgMHgcBH205Vq/Jg8JRo4aKr1alSpWjCkva1JznNynKTf8AClWNWvWdSvic\nRiJuNOn7SvXq15xpwacKUPaSnyUYxfLGlTUacYqEYQSjE/Nz9oT9i/V4bq9+LX7NFrFpetBX1PxP\n8IYC0en64/zyXWo+BFkZbbT9Tk+aaTw23k2l+4ZtNNteyLay/OHwW+P73ksui6/Hc6Vq2n3Jsr+z\n1SCfT76xvYJRDcWs9vepFd2t/bygrcW06JNEcqyLX79abFAyROqbXMa7XdEaRixVhtxnJG3BGAGb\na2VZQa+b/wBov9gLwZ+0pG/irwtqFv8ADf4126Gew8Y21uw0fxS9vl4dK+IGm2+JL2KZ1WGDxDb5\n1rTAzFzqVpm0X+c/Fbwiy/OamIzjhijTwWZVJ+2xOWckYYXFt8z5sDyNLD4jmtzRk6cJK3KuZs/q\nzwi8c8zyeGH4c40r1cyymMVRwuf1ak62Py5R9nGnTx7mpVcdg1TUadOSk62GjFvmqQjGmvCfDXxA\nE7w+XdeeWU7ScAckKMZJeRnA+YgFSnGfT6J0HxxHKYYpLhVLxKSNrbAygAjcoHIPfA2KT1BxX416\n/d/GH9mrx6fhf8fvC2p+D/FEKmbSLqc/aNC8SaWJtket+FPEMJ/s7X9BkyirNaOJrZ98N7a2lxG0\nCfU/gT4qQX0EEi3yzRnDOwmDiPLEbWCnesU2VYuMq6qBwciv5AxmDxmV4ithsbh6lOth6koVYSg1\nKlKLScakN4ySTbjKN1GSeiat/amAxmAzHC4fEYPE4WvRxNONShiKVR1KVanJRlGpCalyPmT0jLVN\nOMkmml+omieIWZhsIzuR3CkyAAjBCsRyMYIyCSWzyBx6ppPimFY9khOI1O3B2nOCdjDG19wyzK3L\nFQQcivz68KePLqQBWvk8tWj27XbMYI2s8ah+UAXYu7r0PTj3HRvGMFxHGC5DybPLTPl7inAcjfgn\nqzEHuR7VyvGWtt7yTWm1+W3pp5dPQ7Z4JShFcyk+bmv0adl0b5Xo7rr8z6/g1iKW3hNrOwichQm5\nC/mFctknHHqozkd6RtTTc27yidxydqjJzzx257dq8K03X7gwCUSrG8YIMbSr5iDcAJAyklOhI3Ed\ne+a1/wC2J2+bCHdzkqSTnnJO8ZJ6k4FJ4pNLm5elr230TVrq332Of6jFSfM7LS1lK3S+tt7ade72\nu995GldvL85yVc71dR8gY7sLwSXzxLwwxx2rJNqy7JNsoG1mywBLIWwGUE5V2YkFjycDHWrMcg/e\nbiqbPMAJ3A7d5+620FnXgADPBG4YNQySjjdJyqADeWAdlkOwgK23O7BkYbRwvAr/AFaw6nGCcW1G\nyjbmdmla+ier9V217f4uVJP2j1vzbt2b95q9m7uOy0ja3S12OhVUVRs2kGQq0uQFUjhjhuSQSAcZ\nXknkVdZtiiJFbJA2KrqCxRGD/vG2sRtJCvn7wz6AZxkYBTy21mUxrIhMobOScsCTkg5X0x6kyyRy\nAnKFE+UcuhYGMnBYBmAU9DySPSt5JaWUF6q33HNCc5JJ82m11a90trWvsW3d8YWTBbbgbkUjGMOy\ntnGc4Mh5IwPWpLXe3mJuaQeUy5wAGf2KrxhiCCevUZFUAxw52wujqMsSP3bsAQoz06bifp3qaNjB\nC5jkyCHXkFX3YHzKwO1VB6feZlz8pzWTS2vFdNJeS2u/P7/kdlKUU05fDbtd99bav5v5nXW2nReU\nQ2SrRo2DIGVJGGDIjcsoyepB+YY5XNPm0KxaIJuw+3PIEZYD7/AxlsbSc8P1UkVyceoXIVCZWAjh\nXIUN8+CSQCQvQE5HHY+tK+qSyB1WT5SBIg4yzD/dPG0L9c9MdK5vY1d3NdPtRt08l/V0tz0XicI0\nm4Ny6qKsn/iv31+Hr16D7jSoUlLgMu35QMKVlfALP169xkcY296rQabcXd3Hb2yebNKLm4SCPy3u\nmhg8vzZktQ3nvbwM6efPHG0Fu0iJK6tMgMUt88TZG0AleMM7kFCSVKs27LHG046kda+Tv2nP2WdH\n/aUm8D+L9C+Kfir4G/GX4b2OpaZ4R8f+Gf7Uu7SfQtZvV1S80XXrHRtW0jWLNYtRia7s9V0e+84L\nJNZajY39v9mWD43xA4n4h4RyOjnORcE5tx9Up5lhcNmWT8P4qjHN8HlFWjiamKzfC4BYTEYnNPq2\nIo4LCvA5fGrjqn1z2tGjOnQrNfd+F/D3AnGXGGX8O8feIdPwn4cx2Fx8J8a4rhvMuLMuyrM40FPK\nKWa5XlWJwuZLLMZi37LGY3DTq1sLSfPTw1f3vZ/fthdad4C0bW/iB4x1qPwn4O8F6bP4p8V+JtXk\nNpp+i6HpCCe9vLhihkBATybWCHdcXd3Jb2ltFLcXEUbfmr/wSu1ubx7pf7bnxvs9PudG8KfGH9py\nfU/C9qEeCJrezsPEWtXfl27KgFza23jLRbe9CZMNxIYpdrxGvnm9/wCCen7WPxHWHwl8fP299T8Y\n/B5tTs9R1jQNN8Q/E/xZf6xBaTb4lttA8WwaT4atdQZPmtbjXrnVbXSrl1u0028eEA/qX8PfDvgr\n4J/Dvwv8I/hVop8PeBvB0F2ukWl5cyXmo3l5qFy97q2u67qbRQnV9f1u9d7zVL9oYYnlEUFtBa2V\nra2sH47w3lfFfib4k8PeJ+a8GZxwVlXB/Dec5HleE4pwmIyviTMsZn7oLNPaYPFUMPiKOXUY0qVT\nDTxGCoU6kounRVV1a1Wn/XXGuJ8DfALwD8RPCfgnxp4e+kF4leN+e8B/27m/AOUZ5gOAeCuAeAc2\nqcU0cNVx+fU6NbMeKOIs9+rYVYXDYbEUsvy2lKGIccRTlLHfTWm6j9ikjnidka3ZCh3jcW4Z/mYH\ngAbgCpckcHgV4t+z38FPDf7P/ij9pbxL4Y8SXuraL8eviQ3xeufC2o6TYxWXgzV4PD2qW+sWunXM\nlxdLqsGsaleNqML3Nlay6fBb2tnKLgw/aTh+Ifiv4b8G2+iXXi7XLTQY/EniPS/C+kS3xb/S9c1Q\nyizjR41cQ2duqvLqOozNHp2mRPHLfXFskilptf8Aif4X0G28U2OreJtB03UrbSNbtLixudTskurK\n5l8N3V3CL6O5uIWs2NvPa3DLMN6QX9jO8Xl3dvJJ99xBwlwhmXEeX8SZ88srZxwfg8zynCfXMxoP\nD0MPxPTwOLxOCzHKpYinSr1sQ8kweIy2WIhKpha1Oc6FJwxVXm/nLhnPeP8AC5HnHDfDNDPIcO+J\nccup5xTwOT1cRh8/pcI51hcZhK2HxnIqnNkubLD01icvq+1oVascvnUUcRKhU/ml+AGoaB4sj+MX\nw18ZaiNL8IfHLwh4h8P6vr80d1q914c8V6BrEvjj4feNBo6n7Zf6X4Z8Y6eqas2myG9fTNXv1s4p\niPKl+zPhdpPhDwd+z/pvwj+KerWuj+F9Z+FPiz4ceOvFGj79QsvDkXjC3vNSm8XWz3f2Fryz8Oa9\ncaZr32a5FnJPFbSQqtvcbAPgD4W21hHfXNsk2oNqSJctavcwJ9mtrqIr5mjmJ1RzJPdSrFdhn3o8\n8MeYzOM/oRp/iyzs1TS7+y8KeKtO8Q+HfE2k+IfDGvaZb6loGq6FLb2dtr9nrFt9ojIto4miS3a1\nnhu7W+snltbyG4tJWX/Hjj3LcPjMfnlWjVqzlxBDA4ivhKGJo4ONfMcPltWjHM8DjKtGosPjsVh4\nZfTw+Ir0q2EjVwmGcsOqUby/2E4bzfjDLeGsDwrRp8RUchw3EmU8dzwGCy2VDMctzfLsF/YbzrL6\nmMouNLGRy14aFOjXoVqEsTlmGg6Uaiqt/mdq/im00P4dD9nDwB4r0nx3d3XizVoPGHxJ8M22p23h\nLVvA9hqaatotv4fn1uz0zWzaavqUr6p4mefTbK38jSdJ0qBr1XvXl/RK78PeO/iX/wAEW/BXgb4a\n+Gte8Yaj4f8AjpqUWtaL4Y0y61vXT4e0jxl4vlu7220iwhuNRuo7TWtY024vTbQyvDDKLiRVtI5Z\nF+fviDpHw+0fQb/T/BmheHfDnm3enyXumeGdPFhZfZ7hrmONZ7zUrm/1K6uGt9t5G+oX0txLau7R\nhkAr9Bv+CeXjbwt4C/ZmstF13XYtF1S5/aF8f+HtMsYLnF9aw65pdt4ls9TvYjcWslloN/ZaZerb\nakzNBdTlY7YS4nEP714S8J5Vxpl/FHC+ZcS4LhjE8Q5dk2JxOeZnRwmYz+s5DxNwpm8KNTB08ZlG\nHrfXqWT0cM6eHxND6jVhhq1GpiPYSjW7/pKfSD4oyriTwk478OfC7iHNsu8M/GOHinLJc/wlahm3\niHx1nGX5pLNs/wCI3kGBll2XRoYClLCYChgKVahlcKP7pSjXhSXnXg/9tj9vvQvDfg/QtH/4J6a1\ndWfhHwj4Z8J6bey+FvjPa3d3B4b0Sx0W11Ccwx28UVxeLYpdXAiSOJJZXWEhAlfen7OPxf8A2qvi\np4J8Q6p+098KYvg/r1j4ls08H6Ra3GrWEmt+HbjTjNeXd54a1nW9b1TTJNMv1is476/ltJNVWdnS\nyhNq8tz71puu6Jr97d2nh/x1o3iS/srayvrqz0XxJbape2mmailvJaXU8FreSyQ21wlzbypJMg3R\n3FuwIWeItqC1WIlpG8xg+Gwp3jHynLruJYsQ285ZenIxX9ycD8EcWZVnWBzniHxfhxxhcuwuIy/K\nsLhuEstyelgo13Tp1XPNqGbZ1iXT5JSlGGBeGnOpGPtq06T9i/8AM7xm8bfDnjfIM44b4f8AoeeH\nHgtn+dZxhM6zPizL+IuP844mpShmDzKpGOX8Q1qWX0o5pVqT+s1a2Fr0amEqVJYblqKnOP5kftYr\nc+Mf25/+CcHw+E7lNF1fxN8TL+CL5ti23iSPVPtEiFTtVrT4fSoc5XDMerc/oTqcs81xczvuI8zz\nfMI8zMkhMgKk4JzwTtBK5K54r5+8Yfs7+IfEv7Znwf8A2oIfFGix+GPhx8I/EvgO78JzRXg8RL4k\nvIPFllpt7pmLZ9Pn027TxdPd3k89xbXVpcacIYre5W7jng+iRplxcSSxqCjb4ixILkoGOMA89wcY\n5znmn4H5NmmW0vEnN8/y3GZVjeJvFrjfN8Lh8xw1TCVpZS8zxEMqrUqVaMXVwfsatWOBxMFKjjMM\nqWJoVa1CVGtLy/pB8YcM57wX9FrhHhXOMPmtLw3+j7hMt4ieGcnPLeOeIuPeK+JuJcpxFSpCF8Vh\nqdfJ1iuSdRRjTpOMmqrcuImCM5DhnBjyHA4QJlgXXrg5IJweSO2aggeBJmZIsRJH/eypdnGXC7cF\nucDoCcHHr3P/AAjzu5lzHld21SzZZy2MSEr8ij73XgCs+fQGtl3PtGSzMijcQd4XLAKPk+XIwSeu\nBjNfvsMRBRUVKEr7N+emn9er0P5c9jP4ox1+KUvPRdX6LVdPUZDqYtmt3LKrEoudpKjdkZPVSBgq\nGyNz9eK9L8M+M/sjwIxVclVU87NpJJ+TB+8ByWLcc7gQc+Q3Nu6eTHs2dl+d9pAJIZArBehzkj69\n6ms2nSfKqVR2RVRtxVUXK/MzN8gIOeM5PQkGuHG4Sni4NPlbtouZNytZ8vK+z10XR+h3YPFVcPKM\nlsmubTXRxTWmux9H/EfwB8Jf2jvAt18OvjN4I0zxx4UvE862S7D2uraDegFU1jwxrts8er+HdWgk\nw8d9plxF5gBjuUubd2ib8Bv2kP8Agn58Z/2TLzUPiJ8J7rVfjX8CI3W6nu7OE3HxG+H9htaT7P4z\n0GwjY6vo9qu5T4s8PwPAIkR9W0zS3Vpm/cvw9r727LJvZEERQJIAu1kO3ZlyFKEfMcbhnHYGuxk8\naTW0ga1kZcLtdEc7NrDDZC8OrhirKcpsJDKVJFflHFfh/k/FFCpSx1J0sWoONDH0lFYij7tl7SnK\nC9vSWnuympW5lGS1P1vgrxHz/hCrz5XXdTA1OV4nKcQ3HCV1Fxk3Skm3hqj256ULOyvGWx/NF8OP\njbYauII/tQBMEckBE0cySSDYRGpQgSMhKhiAAwBYqGzX1t4R+IlpcHeJ2DxK0YcSLsRyu+TfgElA\nQu1wCq8qu7nHtP7TX7AXgH4yXt/8RfgjcaV8Hvi1M01xqOlxWs1v8N/HdyGZ2l1TTtPhLeFNcu2P\n73X9DgNtcu3malpUzg3DfkvrGofFT9nzxUPA/wAavCOt+BNeniYadNqUqXWj67apKVW+8OeIbXzd\nK8QWYZSN1lcy3MSvsubeF1ZB/JHGvhlxBwlVdWtRWJwDl+7zDDRqTwlRXfLGpOWuFqyirexqvde7\nKSkmf2jwN4p8PcYUKVPCYiOEzLkjLEZRi6kFi6Mvc53Qd/8Aa6HvXVWndq7Uoxa1/YPRPHCrEluZ\nI5ZJcZdlDeYj4bJkIVvmDBc8bcbu9ehL40tdoy8gOBkCdsA45A+foOg9q/K7wn8cdHYRN/aKwzNh\nNxkE+6IAjcseNiKx6hcPhs4Pb2SP42ab5af6d/AvRov7o9SD+Yz61+SV1ibpunWg76R5Wla6s07O\n93+jZ+owxuGcd4Np2am5Ratbp66f5H6tOsgMnm4Vc4xzlWXLhnAB+ZlUkyfReaqCc5GI2VFZiisS\nMcZk5Xsx52ngE8AGtWYeZJIuwv5ewhtxLkLkqfmwSDklsHAxjPNVBDIS0biPLyO64wGwOT7Zx/eG\nOpFf7AUKsYUYp2k23LfS0rNd9/w+R/ig6M5VJrk+F8r2tdW1+5rXqQCdcxBFKlTsLM5JwyvIqAZO\n1RwM5zu7jtYS4iUI2JSNhd5JHAbJwQQwYqE9cjcR3Bwa8q+Ifxd8MfDbV9C0fxDpOv3J8Q6de3lj\neaYNKNgRYyXJvrW4e5vYJra5isbZr2CXymgvNyWFvI19IsVZWjftAeC9ZDQQeGfE1tJNbXqafZ3F\n34Y+038unJYPcQLFBq8wstllqVlqC3N88cTWczyytEIHNetDL8dWoU8VDCS+r1FeFZypRhL3pRVv\naTg371OVrJ9F1PPlmOV0sTUwlbHYdYmlJRnR9+U4NwhOzVKE7WjKO9u1nse3uQY0Y4MawhhuBIfA\n67QQw+Ud87vrUyTQyl/KXKFSAGzs3quMuvAVOeMY9Nx5NfP2nftH+AdVutMtbbQvFajWYtUmsLic\n6F9lNrotpPd3V3ORqbNb2qta3dolwy+VHLDHLO8cF5atLt6F8cvh/fSQxaxdt4Me4s724tX8UTWE\nMV1PpupNpt/YWp024vlvZoNjXi3EWbaW1SSSF3aCZEueUZnD4sDVVoxl7sYVLp8rVvZud3ZXte/u\nvRijm+TyUZLMsPKM20pVG6CurXv7WNPRbOW2vTc9akK7d7LlFcIdpZZOPvYIwNnYcAnGOaMxRBiH\nBPLl1G1gj52mUnkjOBt2qN38J5x57F8XfhXcW41OHx34fOlzI7w6pNPOtncfZtZg0KQWwa1E82dV\nu7KzSQQGKSW9thbySkyBI5PjB8LRqlvpP/Cc6GZbtgkZE0xgmMz28FtEXaFZlnnvbg2MNtJAk5ub\ne4d0jhjE5wWAxsk5QwOLnZ8r5MJXnblavdwpSUbaast5jlacf+FLL7SV7PHYVO2mtnWT1vpokb/j\nHxUvhXRW1ibQtc8QrBPHbtYeHbVby/kaW2urtJmVpESKEC1METkN5mpT6fY4Vr2N4+LvfiXf6P4j\n1SG/+Hvja/0FrHwfd6Nq2haR57u2teHY9a1qy8R/abkjTrvR5HGnCZI57NtWH9hzONRmRlhufjb4\nF+2X0OkX8muRaNq0Wi6he6Pc2v2KOZ9HvdUkuILm4mtvtKJHYT2KRWjSXU+pK9gkYkjLHkLr9qbw\nNpuljW10rxgbWW/1q1tIgdJtpLlPD9rZ3Wq6k0tzqMUENjZi7VZRO6TRzRyEhgVLeTj+F+MsdVvl\neaYjKYe2wiw8Y5Nl+LnTnDD4qliKVVY7EUViKWJeKw9Z1oVcLVoywajBVI1Zxj9bknGXhzlOHVDP\nuGsDn9WdHGfWcVV4mzXBLFUqlbBVcsqYWWX4OpDLsRltbB4mNec4Y2ni6GO9nKnCVChUhe0T4reO\n9Q0G88T6/wDCvXdKtIPiV4c8PWukf2ZqNv4gu/BOpaHfaxqXiSSzu7hjb31jMthpTxzxJpUeoyS2\niXDzMvk6WhfFy51C30+31T4bfEXStXvZZUnW48O3Gn6Vpoku5DY3GrXV3M1xo1m2n3NhGLu6hl+3\n+IYtX0O1iQ2MV1Nb1j45eHdG8OWXiu70fxQlvMLpmsoFsW1CG1g1qHRBO7i/ELm5uLu1mjtEm8/y\nZWEi+bE8dc5L+0t4RWy0i7XRPGKvrK+I5tPtXj04SnT/AA0U/tK/llGotDbrPCzXFrBI32ieOAws\nqSuijxsBwR4gQWGqQ4zzKtToQqYOvLE5LkmJVXGU8TUqVJqXt4+xcYShQjh6SnRpxjGPNUSbf02P\n8T/CWs8XSreGGS4OU50cRgf7N4t4pwM8Ph44ajHDSq061LFLHylOjVr4nEVqlJ4x1uW+DjTjONuP\nxlpeu+BPBfjDx38E/F+q6jq2nahoOr+HIvAUPiDW/C8+o2do/iayutD1Oc6lpuha5HZFlvEE7XUV\nlp9tdNFc3dpbSedeMfF/hmKLx3qWq/s8+MNTuPEPhnxhda/qOqeE4vEVxo3ifR/D/h7wn4f1S1XU\nbu603RfDn/CO6THHNq1vM39tX2mQLp6S2XmTV1usftMeENB06z1DVNA8XQ299Zi6jSzm0e9uFWKa\naCTfFb37B7QywhI76PdbTTM0SMGglxoeMPi1omqeBfjhokMv2fxB4f8AhV4v12HQG1ewvbjUtOj8\nL3NxdXVpPpssllBHalo4XFzPCJvMimiRreTzB5HE3hrxJmGTYivisxweIxGHyvnqzr8EcP5i8djc\nsy2tRxNapXqVU5YjG1/apxlQpUsuqZpiKNH6xh6Uah7/AAV41cI5Vnyw2E4Ux9LC4rNp4bBYTB+K\nnG+UU8iy/NcwhjcuwWX0sNQof7Hk1Wlg8TTq1XVlmc8vwmIxT9oqqqfg74FvdfuLjRr+e5W7i1Oe\ncN5ZtG1CeDT7BJ4S0j26PJfT3uFtlnuZLlzDJBO8MEFo9fYcepb/AA1e6ve+Dbpb2a5i0y7t7LTF\ng1KbR20uK/u7ya8Q72N3e3d/pe22WSCTUSHlYSvLct8EfDjxXoWl3GmaleaJeXht4X1O2ht7y1WH\nEdndaaI0haZWS8nRG3pKzZdAWkQrHX3VbeL9M1HQrXVm0rUrO1h1DTtEjeKFby6Z72yh1CG4Swtp\n5nbTXZo7aaW5xIhlwjDaTX+P3Fvh5xTl2IwuIrZDPDZfTxMMCqkMBlOGofWPaRw8aNOnhcxTrcin\nSpOSjOMLKN4pWP8AXnK/FXhTH0cNgaFatjcbTwOHxU/a8Q8SV6+JwWFpVMU6jo1vZUsNVr14e2cf\nbJU/qtKpQ9pKq7eN/Fm0aWWaHTIbiDS4207FxDZWYi8mV8ILq7kU3kebe28iRTCZRNEDGHaVFk+w\n/wBh7xxomk/DDxp/wk/wQv8A4qva/GLVtZutX0/wrpviI2FkfDGm6f4SjtL1Xt9LtLyHV31a+eG5\njmm0vQrzU57R7G4uLyCX4d+LnxI0W4svEOiGwvDfR2c1xPLdG1LWV3p08DqdsM8kjAWkytbRmLKE\nN5x3xE19Kf8ABOv42eGvCnhD4yaJqEOqq2t/FDwDPYpYRw3UUMmuaTLoUJubmGSNS/2sxNNJGrsU\ngaTazLtP9C/R78KuMMw4qy6hVyv+yadXBZi3i8VwtkubRjSo4OOZpSw+NxKpp16ODUIVakasqcav\ntIxUlp+C+PHjfwblnAVevWVbPauGzLA4afsePeL8lr161fHYfAxqVcRgJVKkFl0sRVqYWhh6cKFD\nH1FWjzSjd/qpP8SPAHw01S/Twx8DPFFlNfeGNI1i81LwN4FtA2pNqFlqOpQ+HLk2MqynxFHdaXba\nbew3rbJNVu9NW4vZbSJ763tf8NAXcl1FZN8E/i39onR5/MSz8PLawwrdLZnzr9dREXmPKRJHaIHu\nvsY+2uvl4RvKtW+PHh3RXNrPpviyK/afV447S7sW0l5RoTRrqs0FxfzRW81mltIs63URaCWNGQHz\nSFXX8O/GbRPENjNq9hZ639nU68kSzXFhC06+HtJGszSzyC4KaX9qtsNYG73B4WS9l8q2fdX9/R8P\neKMFTX9nZ5DJsrhWxFXD4HAcJ5HhcLRp1KsZuFL/AGrBqGrfPXjTcpzcq03OfMn/AJ7T8VuBc0qQ\njm3CeK4iz6OHjSxea5p4jcaYzGVPY4SjRp8ypc6XJXm6iwjq8lNcmHoxp4eLi/UPDnxavPGUfiUa\nP8LviJoVzo/hXxR4gsbjxzo9ppFnqGo6JHJHo2iLaW97canc6lrd/wCRmxtlN3ZaeJZpZWleJa0r\nP4621tpE9/qXwS+N1rZ6TpenXfiHU08MWtlpukvcSQWDrIdSvrWeJrXVJnuNVhIkHhrw01v4g1a6\na1MyR+R6H+034astbsdI1Hw34hXUbu9k07yU1zw1dW8F9ALu5dJL5L8W1vBHbWcubohI11GW203B\nubnI+y/Cvxt8N6t8M7X4jQ2mvS6RdQ3DS6GbOLVPEsFnZarPol75uj2c1w10ltc287zJbLKr2is6\nIxJWvFzrhHxAy/D4Rx4jUMT7CvQli6nDWVVMJicVVhXnltb6lhMTVoYZYb2dKNf2ePm8TCndck60\nvZ+pk/iB4U43F4/2Xh9g3glUWIjgMNxjxJhsVgqOHhGljYQxWKw9XEYydenOOIw86kaFHC1OVyw+\nMUasKvOeANd0j4keFNN8a+H7TVrHTNWbWYBY6zbql7HJpOsajok8heIyWV5bXVxp0l3p99ZTT213\np1zZ3AMUsklvB08egT3W5UtmYv5jK5BZYznJ3MQoQJlgvBAz8pziqWt/tM/DvQ49ENx4c8XE6xKN\nNsLbUrCz8Gbb8q0ttYwReI5LWN7eSwgvb8XluhsbaKxmtZP9LYItXTv2k/BWo30ukw+C/FUGsjxC\nfCiWMWpeGdRsn1m4OipZ28+s6dfSWVnHc3Gu6fA7zoTAkv2uWP7OVY+phcu4lp4XDrFYSeKxVPD0\n1isVSjQwdKpWjSg61WlhquJlOlScvhTlJXdudpHg5lnHCNXMMbLAVqeAwVXF15YXBTxGJzKWDw1e\nr7TD4apjlh4+2nRp1FHnko12v4kXO8nb1PwFdbBJHbMXVgWwW+6xI8tkOTgY434x2GM1gQeELlHj\nTyHTG0hnI+XKkHYigcYAB3Zxn1xXQ+F/2jfBPi/xbp/gWHwt4mtNautbsPDt4ZtU8O3tnpmp32lX\n+tAT3lhqMi3lnbafYkape2yumn31za6dMn2uQ7bGv/HX4e+HtDk8S6j4b+IsVnZahp2nTw3ng7UN\nHMdzqFytpaql1qy2lncQecQrXEMjo8UclxEJYhk7qhn8K0KE8BiJVZckoPnotNVJqEGpwqOCvOLX\nvOPkcdPF8PToVK9PMcK6VPndSpJ1YuDpQjKopQqwjU9yDTdot2tsT6d4VdIwTGWkVDt4QMBvbawO\nCBz15zjJPpWqmhwiQn7Pl1jBZX2jIYgA8A8/f7YAA6mvHm/a3+HN1f3ulf8ACJeMLPU7LQvEuqzw\nfafD81it74S0661PxNokmpQah9jgu9I+zC3kuphHZStMlzDMYI5TGa/+1T8OvCGs6tpuveH/ABZG\nuj67ZeGJry0fSJxd6pfeH7LxNDFZWqX3nPDFpV60l3LII3s5rWdJ0UNC0nSsn4glN05ZbiPb8vP7\nL2lB1JRvCPN/GcmnKpFXWnvLvcw/1g4epUlVWa4WNPm9n7R08U4qTi5OLapOOkYTlr9mM27JXPah\npVuoHlQYMbIqqoyWUk7iCwG0DHJHQkEVieNfht4B+KHha88D/EzwVofj7whqQDXfhvxLpaalaJMF\nZEvbKU7L3SdRhDbrbVdKurLU7Z1V4rlCBWJ8PvjP4Z+Ji+Kl07S9W8NTeEtTs9GvoPE0+kxT3epS\nrdi6trA213IXNhcWUkDlyDdRyRXdupt2Oz0pb0jMUhUHduCr1ARFY5I5H3yCQxO4ehzXzuaYXF0q\nlbBZhhfZzShCthK3JKnVpzjGdpcvNCcXCXVvld3oz6PK8Zh8TRw+ZZXj/a07e0wuNws6lOUatOpy\n81KolCpC1SGjg0pWT95NI/Bz9pn/AIJJ+MvBct949/Y/1i88c6B+8vLv4F+LdVU+NdKhUbp4Ph94\ntvZILfxRBHsY2+h+IprLXQpMFrqOrSBVb8jr7XPGGl3t5pmq+B/idpeqaddXFjqWm3fg/wAYRXen\nX9pK9veWN1EdIzHcWlxHJbzRnlJI2U9K/tIN84ZikpBiLGNlUHALAHKqwLgk4y3OQDkkCmnxNqWT\nnULknuSmST3JJQnJPXk896/G+IPCTIM0xf1nBYnFZNzuU6uHo0aeIouUmpXputUlOCWqUI2glZpI\n/duHvG3ibJ8GsJmGDwmfqCpqhicbUqU8XGMYxTjWqUabVVuyabStbfV28cuNsNwhaOSQHcuOQVIJ\nUKwyrFNpJbse3XFc94p1q28J+E/GXi+4gcweE/C3iXxbPCIhcGSz8N6LeatcRRWweJpmMFrJ5USy\nxvLJsQMrODXq/jDT4rW5mkRRGVYjOAruoDHC5AHPftj8TXzJ42v/ABBNdav4ebQPE+seFdZ8Mtpm\noafpumLfaVqMWtRahpmuaTq3m+GNcVrW80ibypPLuYCI5pIJ0RJ0lX+nsjlSxv1R1ZxlSpxp1cQu\nflnVoUalN1qNF8yUa0qTfJK6XRyi9T+Q82o18ujilFSdaqpUqEowUoUsROnNUq87QnKpSjOznTSb\nfTS5+fmgft6/BT46+N/gz4L8QfBj4hT+KPHPi3w98PPCnxA0DW4/DXgrUIPFOotonifxFoVh4o0p\nte/svwxPqtjouv6ZfJJql1c31y9nJa+RbK/smp+Nvhz4H1LxT4Osfhh4xs5NBkmTSJZfjL4OsNSu\nLa7uIoLfVNGt9ZRbzSDeW+hrq9lFr8Tz3lpBLcWiTw74xt2nwp8J6GPhBZ6F8AYbbS/gk3ibW/hp\nZL4Qvba8+HvizU9UtdQXUfC9+ngyVJodeubKz1DVbq+ttQu7TUrG2uE8x0iji+hfDVnp2rRanc+I\nfBYj1FrwgHxP4c02K9uCbYNJLFKfD+kPND58syRzvDIdpYq0fmyQ1+r5jmXD+H9lLKctx2Dy2nRq\nUquBq5/jK0/bf2hVnh8TQVGsnSjLA1IqpQafsa8q0KNSpSVKcvy3Lsnz7FSdPM8bl+KzOeIhVnmU\nuH8LTjKhHA06dbDShUoRdSU8bBVKGJ5lJ4e1OrTg4JHyvpfxH+Hfhy5s9a0r4M+KbrWprO60uXS2\n+MXge6MNlqVpb6vNdqRcRWcja8NVhe7VZFb/AEayuEjgt5LWWfNu/HHw6n09NIPwi8TXNjp902oT\nasnxs8KWslj4g1y0urnU9MvbuS2mlj1OKG6ukmxaxRTCEvZSPGDK/wBqN4Y8MeTGo8K+HNpBK7NI\n06Ly2ARQV/0cHYEjSJVwBGiJHHtUIFZb+HfDUbMw8KeHds/zPGukab8+FaIGQm3y5RC0f7ws2yRw\nAu4k+dHiPLvaRawWNnU5vdlLNcbWcYRsoO9XER5bQbXKu3vJne+Esy5OX+0MvpxkmnTp5Ll9ONpO\n7TccPrq7p7p9NbHzp4Vs/hz4+0LxLpPhbwB4oup/DFpaafoltZ/Fjw5I+vvBrularqmmaTqkP2q2\nsZNLuGjudT/te3S8+yvKrpBHcRS1gWvhnTNMaC/j/Zh+OU11pV9pl5BFP8RrO+Elxp1zLI0kamx/\n06PzWM0zOdmohbd4SuefsC20nw/YTR3un+HND069j89Y72x020t7mBZo1iuUSaK3WVftMaILgRso\nmVVSQMgAGvJdPldgYDaqbSGAMbLnBX+JFPPy/wARyDwBXM+IZKpUjSpV3Qck4qtmmYRlBS+K/scZ\nHncrp2kvRq8k+qPCUKtChHE16CxFGMoSqUMuy1wqwTi6aXtcFJwUVdWtfV77r5sv/hr4C07TNJ8O\nL8OPiBFN40ttN13VtB8M+NbSW90u9+3zzLbXN9qv2QPsuJpby4+zQIrXdvPbGSN4Rv8ABf7Z+B18\ndT0W0+FOu3Vn4bs/GHii3nm+IWpjdJPe6doms6XMI9MuTBYaxHoatHbSPNKssOpyTqtncSXa/cni\nHwp4R8U3Wk3/AIm8N6Zrl5pIYafdXSSi4sI2kE22AxzQgr5y+bsOcMCRtYsTyrfDH4TwfafL+HPh\n9H1K3ms7t4EuoJb2zubn7TNHdOl2krLJcnzHzIZWO5d5R5A2mBzzD0abWLqZp7WU6LgsLjalClC1\naqqslF4qrKUpYeNGnFOSUbppXUjLG8LYidRRwNHJKVFQqwqTxGAw1WtUgqdJ0uX2eCoQhUddVZtq\nm42lypRT1+b77WPhtrPwy1PUtW8GapqWmeDvFmr+FmtLn4geJ7rV73TbXUIvEs0+r3Nj4egke0n8\nRQad9lhghuIU07Tr6UXaJZwR3mVrl94G0zw94Av5PhTq803ia38TXVjpdv8AETXo9X8PwtLqX9u6\nTcRv4dkSe2uPDthFqSmKAWb2F9cyy3wWS1um+srf4e/DuKwutLTwdpEGnXWo22q3VshvhBdX9rYy\n6ZFdTr9tYzy/YneGZHdoLpnE9xFJOqyhP+FZ/C6WaxEvgfTLltPt3tbGO7kv7tbS3kN0zxWq3N/L\nbWsDre3EM0MabJrSRLGVHtobaKLthxDgKfLTlSzX2McTiK3s3mdVXo1KUVCPKqsISq/WH7R1J3bj\nG0t0cdbhbNasVapkDqPC4ejGdTLKdoVqdRqVRqGGk3RjRtBUuZNuXa58z/EG/wDhzH4Y+Hdxrvgr\nUdetLjSbGXT7IePNZh1TSrnTX1CaSW3kttBim1LWLWxh0xbieWKKymuEuJWjFlBDf3XPfErxZ4U0\nn4cfHXxDb+Dbqz1ey+HOueFNS1GXxDrNwLjTNW0PWbewaGzvdGsIZdW1JdO1VZp9kVlcfZbqW1uv\nMEUR+tbz4afDSeHS47zwXol2mh6dcaXoouBqFw2lWFzNcyzw2bXF7I8XmNdTIJ2JnSFhaxSraRQw\np4P+1J4M8CaD+yp8ep7HwfbLJbeCZbuGT7dq9zcNdJfW9la3El1cajPPKbYape/Zo5WlS3F1eeXF\nm6mL+HxFxBltLhXPHiVnMlQybNKlWUcUlUjGWDxVbEKlN4pKnUdOleMlZuolK97H0fC3CWaYjjHh\n6OEnklOVfiHIKdBzwaTWJqY/CYSlKTWD5p0frFRuMbtwpNpqx/PV4AbTvEmobLXQpZLS389IYZdY\nl82NVjkvPJtGZN6NqMzLGjtJJIJTGNoCg19kN4wi8L6ZbadFpFzDNqlnNdNZ3mruLqCeCGPTrj/T\nbSB4/LtEihhjijYTqyhiq43V8q/By20hNae/NvJBfrfRrp0dvbSCK2uH/wBHS8kDs25ApIUPG8kc\nyQGNPMVWH1Te2+mJpunS6zokWr6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"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_recommendations(192, preds=pred)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}