{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Getting started with InferLO\n", "\n", "In this Notebook we will review basic concepts of InferLO library, show how to define graphical models and how to solve different tasks (inference, maximum likelihood and sampling) for models. Also we will review different kinds of models (generic, pairwise and Normal Factor Graph), and show how you can use different algorithms to solve the same problem.\n", "\n", "Purpose of this Notebook is to give understanding of how graphical models are represented in the InferLO library, rather than to be tutorial on graphical models." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Don't run this cell unless you are InferLO developer and this notebook is in inferlo/docs/tutorials.\n", "%load_ext autoreload\n", "%autoreload 2\n", "import sys \n", "sys.path.append('../..')" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import inferlo\n", "import numpy as np\n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction\n", "\n", "Essentially graphical model is a way to represent a probabilistic distribution over variables. This distribution is usually defined by non-normalized probability density function, represented as a product of factors, each factor being a function of small number of variables. Then we can define a graph describing structure of those factors (there are multiple ways to do so).\n", "\n", "In InferLO you define a model in terms of two basic building blocks: `Variable`s and `Factor`s. First we review how you can do it by defining them explicilty." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Defining a model\n", "\n", "Let's start by defining a generic graphical model, which is explicitly defined by (non-normalized) probability density function. Let's say we have 4 variables $x_0, x_1, x_2, x_3$ which can take any value, and we want to represent probability distribution\n", "\n", "\n", "$$p(x) \\sim e^{x_1 \\cdot x_2} \\cdot |x_2+x_3| \\cdot \\cos(x3-x4)^2.$$\n", "\n", "For this we will use `GenericGraphModel`. First, we should initialize the model with number of variables. Then, we will add factors add by one. \n", "\n", "In this case we will use `FunctionFactor`, which defines factor explicilty by indices of variables on which it depends and a function. To define such a factor we need three things: a model, indices of variables and a function. Function should take a list of values (its length must match number of variables this factor depends on) and evaluate value of this factor for given values of variables." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": true }, "outputs": [], "source": [ "model = inferlo.GenericGraphModel(4)\n", "model.add_factor(inferlo.FunctionFactor(model, [0, 1], lambda x: np.exp(x[0] * x[1])))\n", "model.add_factor(inferlo.FunctionFactor(model, [1, 2], lambda x: np.abs(x[0] + x[1])))\n", "model.add_factor(inferlo.FunctionFactor(model, [2, 3], lambda x: np.cos(x[0] - x[1])**2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we can evaluate value of the whole product at any point:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "10.785309445728231" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model.evaluate([1,2,3,4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can define the same model in more succint way, using symbolic expressions. Note that `*=` is just shortcut for `add_factor` and expression on the right creates a `FunctionFactor`." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "10.785309445728231" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = inferlo.GenericGraphModel(4)\n", "x0, x1, x2, x3 = model.get_symbolic_variables()\n", "model *= np.exp(x0*x1)\n", "model *= abs(x1+x2)\n", "model *= np.cos(x2-x3)**2\n", "model.evaluate([1,2,3,4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Variables and domains\n", "\n", "In example above variables could take any real value. In practice it's useful to have variables with limited domain. You can specify domain for every individual variable in the model. Note that `model[i]` accesses `i`-th variable:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[RealDomain, DiscreteDomain([10,100,1000]), DiscreteDomain([0,1]), DiscreteDomain([0,1,2,3,4])]\n" ] } ], "source": [ "model = inferlo.GenericGraphModel(4)\n", "model[0].domain = inferlo.RealDomain()\n", "model[1].domain = inferlo.DiscreteDomain([10, 100, 1000])\n", "model[2].domain = inferlo.DiscreteDomain.binary()\n", "model[3].domain = inferlo.DiscreteDomain.range(5)\n", "\n", "print([var.domain for var in model.get_variables()])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example $x_0 \\in \\mathbb{R}, x_1 \\in \\{10, 100, 1000\\}, x_2 \\in \\{0, 1\\} , x_3 \\in \\{0, 1,2,3,4,5\\}$. \n", "\n", "By default domains of all variables are real. If you want to change domains of some variables, please do so first thing after you created the model. \n", "\n", "If you want all variables to have the same (default) domain, you can specify this domain when creating a model.\n", "In example below all variables are binary, except last one, which can take values 0,1 or 2." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[DiscreteDomain([0,1]), DiscreteDomain([0,1]), DiscreteDomain([0,1]), DiscreteDomain([0,1]), DiscreteDomain([0,1,2])]\n" ] } ], "source": [ "model = inferlo.GenericGraphModel(5, domain=inferlo.DiscreteDomain.binary())\n", "model[4].domain = inferlo.DiscreteDomain.range(3)\n", "print([var.domain for var in model.get_variables()])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Factors\n", "\n", "In example above we used `FunctionFactor`, which is defined explicilty by a function, and it can be any function. There are other ways to represent factors.\n", "\n", "If all variables, on which the fcator depends, are discrete, number of possible combinations of variable values is finite, so you can tabulate the function and represnt it by this table (which will be a multidimensional array). You can do this in InferLO by using a `DiscreteFactor`." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = inferlo.GenericGraphModel(2, domain=inferlo.DiscreteDomain.binary())\n", "factor = inferlo.DiscreteFactor(model, [0, 1], [[0, 1], [2, 3]])\n", "factor.value([1, 0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Above we described a function $f(x_0, x_1)$ such that $f(0,0)=0, f(0,1)=1, f(1,0)=2, f(1,1)=3$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can define a function explicilty (using `FunctionFactor`) and then convert it do `DiscreteFactor`, obtaining explict table of function values:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[[ 2., 3., 4.],\n", " [ 12., 13., 14.]],\n", "\n", " [[102., 103., 104.],\n", " [112., 113., 114.]]])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = inferlo.GenericGraphModel(3, domain=inferlo.DiscreteDomain.binary())\n", "model[2].domain = inferlo.DiscreteDomain([2, 3, 4])\n", "x0, x1, x2 = model.get_symbolic_variables()\n", "function_factor = 100 * x0 + 10 * x1 + x2\n", "discrete_factor = inferlo.DiscreteFactor.from_factor(function_factor)\n", "discrete_factor.values" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Pairwise models" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generic model can express any distribution, but it's too abstract. InferLO defines classes for more concrete models, which may be subjects to some additional constraints, but allow for efficient algorithms to solve certain problems.\n", "\n", "First such example is Pairwise Finite model - a model where every factor depends on at most 2 variables, and where variables come from the same discrete domain. Famous partial cases of this kind of model are \n", "[Ising model](https://en.wikipedia.org/wiki/Ising_model) and \n", "[Potts model](https://en.wikipedia.org/wiki/Potts_model).\n", "\n", "In InferLO such model is represented by class `PairWiseFiniteModel`. It's defined by `gr_size` - graph size and `al_isze` - alphabet size. Domain of all variables is set of integers `0, 1, ..., al_size-1`.\n", "\n", "Denote $N$ - `gr_size`, $T$ - `al_size`. \n", "Probability of given state $X \\in \\{0, \\dots T-1 \\}^{N}$ is given by formula:\n", "\n", "$$p(X) = \\frac{1}{Z} \\exp \\Big(\n", "\\sum_{i=0}^{N-1} F[i, X_i] + \n", "\\sum_{u, v \\in E} J_{i,j} [X_i, X_j] \\Big),$$ \n", "\n", "where $F \\in \\mathbb{R}^{N, T}$ - \"field\", $E \\in V \\times V$ --- set of edges ($V = \\{0, \\dots, N-1\\}^2$ - vertices), \n", "$J_{u, v} \\in \\mathbb{R}^{T, T}$ - interaction matrix corresponding to edge $(u, v)$.\n", "$Z$ is normalization function, which is constant defined to ensure that $\\sum_{X} p(X)=1$, also known as *partition function*.\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In InferLO you can create such a model by field, all edges and interaction at once, or by setting field and individual interactions one by one. Below we show two ways to create the same model. It has 4 vertices, 3 edges, and all edges has the same interactions matrix." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "model1 = inferlo.PairWiseFiniteModel(4, 2)\n", "field = np.array([[1,2],[3,4],[5,6],[7,8]])\n", "J = np.array([[-5, 5], [5, -5]])\n", "model1.set_field(field)\n", "model1.add_interaction(0, 1, J)\n", "model1.add_interaction(0, 2, J)\n", "model1.add_interaction(0, 3, J)\n", "\n", "edges = [[0, 1], [0, 2], [0, 3]]\n", "model2 = inferlo.PairWiseFiniteModel.create(field, edges, [J, J, J])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let's can show pairwise grap for this model - this is the graph $G=(V, E)$ from definition above, where vertices represent variables and edges represent interactions." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model1.draw_pairwise_graph(plt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also draw factor graph for this model. Factor graph is a bipartite graph with variables in one part and factors in other. There is an edge between variable and factor if factor depends on that variable." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model1.draw_factor_graph(plt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that there are 3 factors corresponding to edges and 4 factors corresponding to fields in vertices." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inference, Optimization and Sampling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let's do something with this toy model. First task is inference - finding partition function $Z$ and marginal probabilities." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "InferenceResult(log_pf=34.12701627818652, marg_prob=array([[0.88076347, 0.11923653],\n", " [0.11923653, 0.88076347],\n", " [0.11923653, 0.88076347],\n", " [0.11923653, 0.88076347]]))" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model1.infer()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "InferenceResult(log_pf=34.12701627818652, marg_prob=array([[0.88076347, 0.11923653],\n", " [0.11923653, 0.88076347],\n", " [0.11923653, 0.88076347],\n", " [0.11923653, 0.88076347]]))" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model2.infer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that we return not parttion function, but its logarithm, because it itself may be so high that it doesn't fit in float data type." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another task is optimization, i.e. finding state having the highest probability." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0, 1, 1, 1], dtype=int32)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model1.max_likelihood()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Yet another task is sampling - sampling realizations of distribution represented by the model. You can specify number of samples and get that many independent samples." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[0, 1, 1, 1],\n", " [0, 1, 1, 1],\n", " [0, 1, 1, 1]], dtype=int32)" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model1.sample(num_samples=3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithms" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The same problem for the same model can be solved by different algorithm of different accuract and efficiency. Let's build a model whose graph is 5x5 grid and perform inference using three algorithms - dynamic programming on path decomposition (exact), mean field (approximate) and message passing (approximate)." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "156.4906749764044\n", "[0.41116171 0.00963484 0.57920346]\n" ] } ], "source": [ "from inferlo.testing import grid_potts_model\n", "model = grid_potts_model(5, 5, al_size=3, seed=123)\n", "\n", "result = model.infer(algorithm='path_dp')\n", "print(result.log_pf)\n", "print(result.marg_prob[0])" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "6639.478242081531\n", "[0.4127652 0.00997726 0.57725754]\n" ] } ], "source": [ "result = model.infer(algorithm='message_passing')\n", "print(result.log_pf)\n", "print(result.marg_prob[0])" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "146.0209085386057\n", "[0.27666686 0.00299012 0.72034302]\n" ] } ], "source": [ "result = model.infer(algorithm='mean_field')\n", "print(result.log_pf)\n", "print(result.marg_prob[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First answer is guaranteed to be exact. \n", "\n", "Message passing gives good approximation for marginal probabilities, but partion function is completely wrong (in fact, we can restore correct patition function for this algorithm only if graph is a tree).\n", "\n", "Mean field is guaranteed to give lower bound on partition function, and we can see that estimate is close to correct answer, but estimate of marginal probablities is worse than for message passing." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Normal Factor Graph models\n", "\n", "If every variable appears in exactly two factors, we can build a Normal Factor Graph - a graph where edges correspond to variables, and vertices correspond to factors. We we will call such models Normal Factor Graph (NFG) models. Also they are known ad Edge-Variable or Forney-style models.\n", "\n", "Not any model can be represented in such a way, but every model can be converted to NFG model. Conversion may add new variables and factors. This conversion is implemented by function ```inferlo.NormalFactorGraphModel.from_model```, which takes arbitrary graphical model and returns equivalent NFG model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Conversion to Normal Factor Graph model\n", "\n", "Below we demonstrate how the conversion algorithm works. We build generic model with 5 variables and 4 factors. Then we convert it to equivalent Normal Factor Graph model.\n", "\n", "We plot factor graph for initial model, Normal Factor graph and factor graph for the new model." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model1 = inferlo.GenericGraphModel(num_variables = 5)\n", "x1, x2, x3, x4, x5 = model1.get_symbolic_variables()\n", "model1 *= np.exp(x1*x2)\n", "model1 *= np.exp(x1*x3*x4)\n", "model1 *= np.exp(x2*x3*x4)\n", "model1 *= np.exp(x2*x3*x5)\n", "\n", "for i in range(len(model1.factors)):\n", " model1.factors[i].name = 'f%d' % i\n", " \n", "fig = plt.figure(figsize=(30, 10))\n", "model1.draw_factor_graph(fig.add_subplot(1, 3, 1)) \n", "\n", "\n", "model2 = inferlo.NormalFactorGraphModel.from_model(model1) \n", "model2.draw_edge_variable_graph(fig.add_subplot(1, 3, 2))\n", "model2.draw_factor_graph(fig.add_subplot(1, 3, 3))\n", "\n", "ax = fig.get_axes()\n", "ax[0].set_title('Initial factor graph')\n", "ax[1].set_title('Normal Factor graph of an equivalent model')\n", "ax[2].set_title('Factor graph of converted model')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note how each of variables $x_1$ and $x_2$ is replaced with three variables and a factor requiring new variables to be equal (denoted \"=\"). \n", "\n", "Also there is a trivial factor $f(x_4)=1$ (denoted \"1\") which is added so that $x_4$ appears in exactly 2 factors, so we can draw an edge.\n", "\n", "We add new variables only if necessary. If variable appears in only 1 or 2 factors, it won't be cloned." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Three graphs of a model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below we build a simple model which is both pairwise and NFG model, and show 3 graphs for it: pairwise graph, factor graph and Normal Factor (edge-variable) graph.\n" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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uqVMn6eefpXz5rE4EAIBlbFYHAADACsnnkxUaE6qwamF6qdlLVscBAAC5QHp6un7++WdFRESoXLlymjp1qvr37699+/Zp9OjRatKkCeUSkBu8+67zuUyRkZLDYXUaAAAsQ8EEAMhzUtJS1GVSFwWWDNSwNsOsjgMAAHK4TZs26ZVXXpG/v79efvll3XXXXdq6datiY2PVtWtXeXt7Wx0RQGay2aTvvpMOHJBeftnqNAAAWIYl8gAAeUq6I13hP4SrgGcBjQ4bzV3EAADglvz111+aMGGC7Ha79u/frz59+mjOnDkKDAy0OhqArODtLc2YITVtKlWqJA0YYHUiAACyHAUTACDPME1TA2cP1NGzRxXXK07uNn4MAgCAG5eSkqK4uDjZ7Xb98ssvCgsL0zvvvKPWrVvLzc3N6ngAslqxYtKcOVKzZlL58lLHjlYnAgAgS3FlDQCQZwxZNERrDqzRwoiF8nZnqRoAAPDvTNPUb7/9pqioKE2ePFl16tRRRESEoqOjVbBgQavjAbBa5crOmUxhYc6yqUEDqxMBAJBlKJgAAHnCiJUjNHXjVC3tu1QFvbgYBAAArm/37t0aN26c7Ha7TNNUZGSk1qxZo4oVK1odDUB207ixNHas1KmTtHy55O9vdSIAALIEBRMAINeLio/SyFUjtbTvUpXwKWF1HAAAkE39/fffmjZtmux2uxITE9W9e3fZ7XY1atSI5zYCuL5OnaTdu6UOHZwlU9GiVicCAOCOo2ACAORqsVtiNWjBIC2KXKQKhStYHQcAAGQz6enpWrBggex2u2bNmqUWLVro//7v/xQaGiovLy+r4wHISZ5+Wtq1S+rSRZo7V+LfEABALmezOgAAAHfK4qTF6hfbT7E9YhVQPMDqOAAAIBvZsGGDXn75ZVWoUEGvvvqqGjdurG3btmnGjBnq0qUL5RKAW/Phh87ZS/36SaZpdRoAAO4oCiYAQK609sBadZvSTRMemqCGfg2tjgMAALKBw4cP65NPPtFdd92lkJAQGYah+fPn6/fff9dTTz2lEiVYShfAbXJzk8aNk7Ztk15/3eo0AADcUSyRBwDIdbYe3arQmFCNDhut1pVbWx0HAABY6Ny5c5o1a5bsdruWLFmiBx54QMOHD1fLli3l5uZmdTwAuVH+/FJsrNS0qVSpkvToo1YnAgDgjqBgAgDkKntP7VXIuBC93fJtdanZxeo4AADAAqZp6tdff5XdbteUKVMUHBysyMhIxcTEqECBAlbHA5AXlCwpzZ4t3XuvVK6c1Lat1YkAAMh0FEwAgFzj6JmjChkXov4N+uux+o9ZHQcAAGSxpKQkRUdHy263y83NTZGRkfrjjz9UoUIFq6MByIuqV5emTpW6dJHmz5eCg61OBABApqJgAgDkCsnnkxUaE6qwamF6qdlLVscBAABZ5NSpU5o6darsdrs2bNighx9+WOPHj1fDhg1lGIbV8QDkdffcI332mdSxo7RihXM2EwAAuQQFEwAgx0tJS1GXSV0UWDJQw9oMszoOAAC4w9LS0vTzzz/Lbrdr9uzZatmypZ599ll16NBBnp6eVscDgEs9/LC0e7cUGiotXSoVKmR1IgAAMgUFEwAgR0t3pCv8h3AV8Cyg0WGjuVMZAIBcbN26dbLb7Ro/frzKly+viIgIffrppypevLjV0QDg+l58Udq1S+rWTZo1S/LwsDoRAAC3zWZ1AAAAbpVpmho4e6COnj2qmIdi5G7jvgkAAHKbQ4cOaeTIkapXr55CQ0Pl6emphQsXatWqVRo4cCDlEoCcwTCcS+V5eEj9+0umaXUiAABuGwUTACDHGrJoiNYcWKMZD8+Qt7u31XEAAEAmOXfunCZPnqywsDAFBAQoPj5eH330kZKSkvTOO+8oICDA6ogAcPPc3aWJE6W1a6V337U6DQAAt41bvQEAOdKIlSM0deNULe27VAW9ClodBwAA3CbTNLVixQrZ7XZNnTpV9evXV0REhCZNmiQfHx+r4wFA5ihQwLlEXpMmkr+/1Lu31YkAALhlFEwAgBwnKj5KI1eN1NK+S1XCp4TVcQAAwG3YuXOnoqOjFR0dLU9PT0VGRiohIUHlypWzOhoA3BllykhxcVKrVpKfn9SihdWJAAC4JRRMAIAcJXZLrAYtGKRFkYtUoXAFq+MAAIBbcPLkSU2ZMkV2u12bN29Wjx49NHHiRN11110yDMPqeABw59WuLU2YID38sPTLL1LNmlYnAgDgplEwAQByjMVJi9Uvtp/iesUpoDjPXgAAICdJS0vT/PnzFRUVpblz56pNmzZ64YUX1K5dO3l6elodDwCyXqtW0gcfSB06SCtXSqVLW50IAICbQsEEAMgR1h5Yq25TumnCQxPU0K+h1XEAAMANSkhIkN1uV0xMjPz9/RUREaFRo0bJ19fX6mgAYL2ICCkpSQoLkxYvlnjmHAAgB6FgAgBke1uPblVoTKhGh41W68qtrY4DAAD+xcGDBxUTEyO73a7jx48rPDxcixcvVvXq1a2OBgDZz5Ah0q5dUo8e0g8/SO5crgMA5Aw2qwMAAHA9e0/tVci4EL3d8m11qdnF6jgAAOAazp49q4kTJ6pDhw6qWbOm1q9fr5EjR2rXrl0aOnQo5RIAXIthSF99JZ07Jz3zjGSaVicCAOCGcEsEACDbOnrmqELGhah/g/56rP5jVscBAACXMU1Ty5Ytk91u17Rp09SwYUNFRERoypQp8mGZJwC4cR4e0tSpUsuW0ubNUs2aVicCAOBfUTABALKl5PPJCo0JVVi1ML3U7CWr4wAAgIvs2LFDdrtd0dHRyp8/vyIjI7Vu3Tr5+flZHQ0Acq7ChaWVK6X0dKuTAABwQyiYAADZTkpairpM6qLAkoEa1maY1XEAAICkEydOaPLkybLb7dq2bZt69uypqVOnql69ejIMw+p4AJA7eHlddfO5c+d04sQJlS5dWqZp8u8uACBb4BlMAIBsJd2RrvAfwlXAs4BGh43mFycAACyUmpqquLg4Pfzww/L399f8+fM1aNAg7d27VyNHjlT9+vX5WQ0AWeCHH37Qww8/rNTUVKUzwwkAkE0wgwkAkG2YpqmBswfq6NmjiusVJ3cbP6YAAMhqpmkqPj5edrtdEyZMUJUqVRQREaHRo0eraNGiVscDgDwlPT1dbm5uOnv2rHr27CkPDw/Xaw6HQzYb944DAKzDlTsAQLYxZNEQrTmwRgsjFsrb3dvqOAAA5Cn79+9XTEyMoqKilJycrPDwcC1dulTVqlWzOhoA5Dnp6ek6f/68du7cKTc3N02YMEEFCxaUm5ub1qxZo9GjR1MuAQAsR8EEAMgWRqwcoWmbpmnJI0tU0Kug1XEAAMgTzpw5oxkzZshut+u3335Tly5d9MUXX+iee+7hwiUAWGjHjh169tln5ePjo3PnzmnBggV65plndP78eVWrVk1nz55Vvnz5rI4JAMjjKJgAAJaLio/SyFUjtazvMpXwKWF1HAAAcjWHw6GlS5fKbrdr+vTpuvvuuxUZGanp06crf/78VscDAEiqXr263n//fQUGBuq7775TjRo19OGHH1odCwCAS1AwAQAsFbslVoMWDNKiyEUqX7i81XEAAMi1tm3bpujoaEVHR6tgwYKKjIzU0KFDVaZMGaujAQAuYpqmDMNQrVq1JEkbNmxQsWLFJEnnz5+Xp6fnVd+XlpYmd3cu9QEAsg5rHgAALLM4abH6xfZTbI9YBRQPsDoOAAC5zrFjxzR69Gg1bdpUzZs3V3Jysn744QclJCTo+eefp1wCgGzIMAxJci1VarPZ1LRpU0m6arlkmqaSkpL0yCOPKCUlJeuCAgDyPG5rAABYYu2Bteo2pZsmPDRBDf0aWh0HAIBcIzU1VXPnzlVUVJTmz5+vdu3a6dVXX1Xbtm3l4eFhdTwAwA06ffq0fHx89P777+vs2bPX3M8wDPn7+8vX11cPP/ywZsyYkXUhAQB5GjOYAABZbuvRrQqNCdXosNFqXbm11XEAAMjxTNPUmjVr9Mwzz8jPz0/vv/++QkJCtHv3bk2aNEmhoaGUSwCQw0yaNEljxoyRJOXLl++a+x08eFCS9Omnn8rb21vjxo3LknwAADCDCQCQpfae2quQcSF6u+Xb6lKzi9VxAADI0fbt26fx48fLbrfrzJkzioiI0MqVK1WlShWrowEAblOfPn3UunVrVapUSW3btpXD4ZDNZpPD4VBKSoqrdHr//fd14sQJffvttzpw4IC8vb0tTg4AyCsomAAAWebomaMKGRei/g3667H6j1kdBwCAHOn06dOaMWOGoqKitHr1anXt2lWjR49Ws2bNXM/tAADkfJ6enpo1a5batWunMmXKqE6dOkpPT9fq1avl4eGh+vXrS5KGDRum2rVrq1u3bipVqpQ6d+5sbXAAQJ5BwQQAyBLJ55MVGhOqsGpheqnZS1bHAQAgR3E4HFq8eLHsdrtmzJihpk2b6rHHHtPMmTOvu2wSACBnK1y4sCZOnKh27dpp1apVKlSokI4dO6aXXnpJv/zyi4oVK6adO3eqQoUK+vjjj1W+fHmrIwMA8hAKJgDAHWeapg4lH1Jjv8Ya1maY1XEAAMgxtmzZIrvdrnHjxqlo0aKKiIjQe++9p9KlS1sdDQCQRSpWrKh58+apUKFCkqT27dsrISFB3bt3V48ePTR//nyFhYVRLgEAshwFEwAgU5imKcMwXOuCX8wwDFUoXEEj241k6R4AAP7F0aNHNWnSJNntdu3evVu9e/dWbGysgoODrY4GALBIhQoVJEmpqany8PDQoEGDVKRIEW3fvl1hYWFq1qyZxQkBAHkRBRMAIFMkJSWpUqVKrofOXl4yebh5WJQMAIDs7/z585ozZ47sdrsWLFig9u3b64033tD9998vd3d+bQMAOHl4eLh+33ryySetjgMAyONs/74LAADXN3HiRFWpUkVDhgyRJNlsNqWnp1ucCgCA7M00Ta1evVpPPfWU/Pz89PHHH6tDhw7avXu3JkyYoPbt21MuAQCucPnNfJc4c0baty/rwgAA8jR+WwEA3Jb9+/crOjpaY8aM0ccff6yjR49q1KhRcnNzU1paGhfGAAC4zJ49ezR+/HjZ7XadP39eERERWrVqlSpXrmx1NABAThcfLz38sLRihcQzmQAAdxgzmAAAt6VMmTJ69tln9fjjj+vXX3/VkiVL1LNnT0miXAIAIENycrKio6PVpk0b1a1bV7t27dLYsWO1bds2vf7665RLAIDM0bSp9MwzUmiodPKk1WkAALkcBRMA4JaZpinDMHT//ffL4XCocOHCWrdunXbt2qX27dtLksaPH68VK1ZYnBQAgKyXnp6uBQsWKDIyUuXLl9fkyZP1xBNPaN++fRozZoyaNm0qwzCsjgkAyG2ef15q3lzq1k1KTbU6DQAgF6NgAgDcsosvitlsNqWlpckwDP3666/Knz+/8ufPr/fff1/16tWzMCUAAFlr8+bNGjx4sPz9/fXiiy+qXr162rJli3788Ud169ZN3t7eVkcEAORmhiF98onk5SU98YRkmlYnAgDkUhRMAIBM4+7urrS0NElS586dVaxYMc2bN0/58uWTw+GwOB0AAHfOX3/9pc8//1yNGjVSq1atlJaWptmzZ+uPP/7Qs88+q5IlS1odEQCQl7i7SxMnSomJ0tChVqcBAORSPBwDAJCp3N3ddeDAAS1evFjz589X6dKllZaWxvOYAAC5TkpKimbPni273a5FixYpNDRUb7/9ttq0aSM3Nzer4wEA8jofH2nWLKlJE8nfXwoPtzoRACCX4WofAOCGrVq1Sm5ubmrQoIFr24XnMF2sTJky+uSTT+Tj4yOHw0G5BADINUzT1O+//66oqChNmjRJgYGBioyMVFRUlAoVKmR1PAAALlW6tBQXJ7VsKfn5Sa1aWZ0IAJCLcMUPAHBDOnToIE9PT23atEldunRRkyZNFBoaKjc3tytKpvT0dPn4+Mg0TdlsrMYKAMj5/vzzT40bN052u10Oh0MRERFavXq1/P39rY4GAMD11arlXC6vRw9p4UKpdm2rEwEAcgmu+gEA/tXvv/+u9PR0zZgxQ0uXLlXx4sX1yy+/aOLEiTp//vwV5ZKbm5sOHz6sb7/9lmcvAQByrL///ltRUVFq1aqV6tWrpz179uj777/Xli1b9Nprr1EuAQByjpYtpY8+kkJDpQMHrE4DAMglKJgAAP/Ky8tLu3bt0o4dO1SyZEk9+eSTqlmzptasWaMdO3ZIci4ZdKFcOnv2rLp06aLAwEBmMAEAcpT09HTNnz9f4eHhKl++vKZPn66BAwdq//79+vLLL3X33XdfsTQsAAA5Qp8+Ur9+UliYlJxsdRoAQC7AVT8AwL8KCgpSeHi47Ha7kpKS5OPjo/DwcJ05c0Yffviha78LDzR/+OGH9eabb6px48ZWRQYA4KZs3LhRgwYNUsWKFfXKK6+oYcOG2rZtm2bOnKmHHnpIXl5eVkcEAOD2vfqqVK+e9PDDUlqa1WkAADkcBRMA4Ia0bt1aKSkpGj9+vBITE+Xt7a13331XZ86cUXJysutu7tDQUPXq1Utt2rSxODEAANd35MgRffrpp2rQoIHatm0rSZo3b55Wr16tp59+WiVKlLA4IQAAmcwwpC+/dJZLTz0lmabViQAAOZi71QEAANmTw+G4ZHm7pk2bKjU1VYsWLdIbb7yhe++9V3PmzFGlSpVUoEAB135PP/20QkJCrIgMAMC/SklJ0axZs2S327V48WJ17NhR7733nlq1auWaiQsAQK7m4SFNmSI1by598IH00ktWJwIA5FAUTACASyxbtkxpaWlq0aKFzIvuZjMMQ/fdd5+qVaum7du3Ky4uTu3atdNzzz0nSUpLS5O7uzvlEgAg2zFNU6tWrVJUVJSmTJmioKAgRUZGaty4cSpYsKDV8QAAyHqFCklxcVKTJlLFis4l8wAAuEkUTACAS+zevVvh4eGaMWOGHnjgAUm6pGgqW7asypYtq3vvvde1LT09Xe7u/EgBAGQvSUlJGjdunOx2uwzDUGRkpNasWaOKFStaHQ0AAOuVKyfNmiXdf7/k5yfdc4/ViQAAOQzPYAIAXKJ3796Ki4tTnz599M0330hyzl5yOByufS7++4XXAQDIDk6dOqXvvvtOLVu2VIMGDXTgwAFFR0dr8+bNGjx4MOUSAAAXCw6WoqOlrl2lLVusTgMAyGEomAAAl3A4HGrfvr3mzp2rF198UR988IEkyWazuYqlC89mWrx48SWfAwBghfT0dM2bN0+9e/dWhQoVFBsbq6efflr79u3TF198ocaNG3MzBAAA1xISIr3zjtShg3T4sNVpAAA5COsZAQAucaFIatq0qZYvX65WrVrp6NGjGjZsmGw2m1JTU+Xh4aHY2Fj973//06+//sryeAAAS6xfv152u13jx4+Xn5+fIiIi9Mknn6h48eJWRwMAIGd57DFp1y7pgQekhQul/PmtTgQAyAG4IggAuMKFkqlmzZpas2aN7r33XiUnJ+vzzz+Xh4eHFi9erA8++ECLFy+mXAIAZKnDhw8rJiZGdrtdR44cUXh4uH7++WfVrFnT6mgAAORsb78tJSVJffpIU6ZIbm5WJwIAZHOsaQQAuITDdMhhOlwlU9myZbVmzRolJCRo4cKF+uOPP/TMM88oNjZWPj4+VscFAOQB586d05QpU9SxY0dVr15da9eu1QcffKCkpCS9++67lEsAAGQGw5C++UY6flx64QWr0wAAcgAKJgCAy9EzR/XQ5Id0Pv28pH9mMhUuXFgNGzbUli1b9McffyguLk5Fixa1OC0AIDczTVMrVqzQk08+KT8/P40ZM0bdunXT3r17FRUVpdatW8uNO6sBAMhcXl7S9OnSvHnSp59anQYAkM2xrhEAQJKUfD5ZoTGhuq/iffJ293Ztt9lsOn36tAzD0AMPPCA/Pz8LUwIAcrtdu3YpOjpadrtdHh4eioyMVHx8vMqXL291NAAA8oaiRaXZs6VmzaQKFaTOna1OBADIpiiYAABKSUtRl0ldFFgyUMPaDLvidR8fHw0fPpznLQEA7oiTJ09q6tSpstvt2rhxo3r06KEJEyaoQYMGMgzD6ngAAOQ9/v7SzJlShw5S2bJSo0ZWJwIAZENcKQSAPC7dka7wH8JV0KugRoeNvuaFPMolAEBmSktL088//6yoqCjNmTNHrVq10nPPPaf27dvL09PT6ngAAKBBA+nbb50zmJYtkypXtjoRACCb4WohAORhpmlq4OyBOnr2qOJ6xcndxo8FAMCdlZiYKLvdrvHjx6tixYqKiIjQ559/rmLFilkdDQAAXC4sTHrtNedMphUrJF9fqxMBALIRriQCQB42ZNEQrTmwRgsjFl7y3CUAADLTwYMHNWHCBEVFRenYsWMKDw/XL7/8oho1algdDQAA/JsBA6Rdu5wzmX76SfLmd0cAgJPN6gAAAGuMWDlC0zZN0+xes1XQq6DVcQAAuczZs2c1adIkhYaGqmbNmkpMTNSIESOUlJSkd955h3IJAICcZPhwqXRpqW9fyeGwOg0AIJugYAKAPCgqPkojV43UT31+UgmfElbHAQDkEqZpatmyZfrPf/4jPz8/ffPNN+rZs6f27t2r7777Ti1btpTNxq8gAADkODabZLdLf/4pvfqq1WkAANkES+QBQB4TuyVWgxYM0qLIRSpfuLzVcQAAucDOnTtlt9sVHR0tb29vRUZGat26dfLz87M6GgAAyCze3tLMmVLTplKlStJ//mN1IgCAxSiYACAPWZy0WP1i+2l279kKKB5gdRwAQA524sQJTZkyRXa7XVu2bFHPnj01efJk1a9fX4ZhWB0PAADcCcWLS7NnS82bS+XLS+3bW50IAGAhCiYAyCPWHlirblO6aWLXiWpQtoHVcQAAOVBaWprmzZsnu92uuXPn6v7779dLL72kdu3aycPDw+p4AAAgK1StKk2fLnXqJM2bJ9WrZ3UiAIBFKJgAIA/YenSrQmNCNTpstFpVamV1HABADhMfHy+73a6YmBhVrlxZERER+vLLL+Xr62t1NAAAYIUmTaQvv5Q6dpRWrJAqVLA6EQDAAhRMAJDL7T21VyHjQvR2y7fVpWYXq+MAAHKIAwcOKCYmRna7XSdPnlR4eLiWLl2qatWqWR0NAABkBw89JO3eLYWGSsuWSYULW50IAJDFKJgAIBc7euaoQsaFaECDAXqs/mNWxwEAZHNnz57VjBkzZLfb9euvv6pLly769NNP1bx5c9lsNqvjAQCA7Oa//5V27XKWTbNnS56eVicCAGQhfksEgFwq+XyyQmNCFVYtTC82e9HqOACAbMrhcGjJkiXq16+f/Pz8FBUVpfDwcO3bt0/ffPON7rvvPsolAABwdYYhjRwp+fhI//mPZJpWJwIAZCFmMAFALpSSlqIuk7oosGSghrUZZnUcAEA2tG3bNkVHRys6OloFChRQZGSk1q9fr7Jly1odDQAA5CRublJMjNSihfS//0lvvGF1IgBAFqFgAoBcJt2RrvAfwlXQq6BGh42WYRhWRwIAZBPHjx/X5MmTZbfbtX37dvXq1UvTp09X3bp1+XkBAABunY+PNGuW1KSJ5O8vRUZanQgAkAUomAAgFzFNUwNnD9TRs0cV1ytO7jb+mQeAvC41NVXz5s1TVFSUfvrpJ4WEhGjw4MFq27atPDw8rI4HAAByi1KlpLg450ymcuWk1q2tTgQAuMO48ggAuciQRUO05sAaLYxYKG93b6vjAAAsYpqm1q5dK7vdrgkTJqhatWqKiIjQV199paJFi1odDwAA5FY1a0qTJ0vdukkLF0qBgVYnAgDcQRRMAJBLjFg5QtM2TdPSvktV0Kug1XEAABbYv3+/xo8fL7vdruTkZEVERGj58uWqWrWq1dEAAEBecd990siRUmiotHKlxPMdASDXomACgFwgKj5KI1eN1LK+y1Q8f3Gr4wAAstDp06c1Y8YM2e12/f7773rooYc0atQoNWvWTDabzep4AAAgL+rVS0pKcpZMS5ZIBbkJEgByIwomAMjhYrfEatCCQVoUuUjlC5e3Og4AIAs4HA4tWbJEdrtdP/zwg5o0aaK+fftqxowZypcvn9XxAAAApFdekXbtkrp3l378UXLnMiQA5Dbc0ggAOdjipMXqF9tPP/b8UQHFA6yOAwC4w7Zu3arXXntNlSpV0jPPPKPAwEBt3LhRs2fPVo8ePSiXAABA9mEY0qhRkmlKAwc6/wQA5CoUTACQQ609sFbdpnTTxK4T1aBsA6vjAADukGPHjunLL79UkyZNdO+99+rs2bOKjY1VQkKCnnvuOZUpU8bqiAAAAFfn4SFNmSKtWiUNH251GgBAJmNuKgDkQFuPblVoTKhGh41Wq0qtrI4DAMhk58+f19y5c2W32/Xzzz+rXbt2GjJkiNq2bSt3lpcBAAA5ScGCUlyc1KSJVLGi1LOn1YkAAJmE304BIIfZe2qvQsaF6O2Wb6tLzS5WxwEAZBLTNLVmzRrZ7XZNnDhRNWrUUGRkpMaOHasiRYpYHQ8AAODW+flJs2ZJbdo4/37vvVYnAgBkAgomAMhBjp45qpBxIRrQYIAeq/+Y1XEAAJlg7969Gj9+vOx2u86dO6eIiAitXLlSVapUsToaAABA5gkK0qiNQ5TqtlY6vva2DuUhDw0oOiCTggEAbhUFEwDkEMnnkxUaE6qwamF6sdmLVscBANyG06dPa/r06bLb7frjjz/UtWtXffXVV2ratKkMw7A6HgAAwB2R6ubInOMoNVOOAwC4PRRMAJADpKSlqMukLgosGahhbYZZHQcAcAscDod++eUX2e12zZw5U82aNdPjjz+ujh07Kl++fFbHAwAAAADgplAwAUA2l+5IV/gP4SroVVCjw0ZzZzsA5DCbN29WdHS0oqOjVaxYMUVERGj48OEqVaqU1dEAAACy3GcdP1ODbg1UpmYZzX53tvYm7JXhZqhqs6rqMqyLCpcuLEn6ZdQvWvr1UiUfTZZXAS/V61xPD/zvAbm5u1l8BgCACyiYACAbM01TA2cP1NGzRxXXK07uNv7ZBoCc4OjRo5o4caLsdrv27Nmj3r17a9asWQoKCrI6GgAAQLZw5sQZNY1sqoBWAbK52zT1pama8H8T9OTUJyVJge0D1ah3I+UvnF+nj5/W9498ryVjlqjlwJYWJwcAXMCVSgDIxoYsGqI1B9ZoYcRCebt7Wx0HAHAd58+f1+zZsxUVFaVFixapQ4cOeuutt9SmTRu5uzPsBgAAuFit+2td8nnzx5vr846fuz4vXqn4Py+akmEz9Neuv7IqHgDgBvCbLgBkUyNWjtC0TdO0tO9SFfQqaHUcAMBVmKap33//XXa7XZMmTVLt2rUVERGhqKgoFSpUyOp4AAAAOcaOFTtUukbpS7atmbpGk5+brJTkFPkU81GntztZlA4AcDUUTACQDUXFR2nkqpFa1neZiucv/u9vAABkqT179mjcuHGy2+1KS0tTRESEfvvtN1WqVMnqaAAAADnO/g379dMHP+mx8Y9dsv2urnfprq536ciOI/p94u8qWIKbLwEgO7FZHQAAcKnYLbEatGCQ5vWZp/KFy1sdBwCQITk5WXa7Xa1bt1bdunX1559/6ttvv9XWrVs1ZMgQyiUAAIBbcGTnEY3pPkYPvvegqjSpctV9SlQpodIBpTX1xalZnA4AcD3MYAKAbGRx0mL1i+2n2b1nK6B4gNVxACDPS09P16JFi2S32xUbG6t7771X/fv3V1hYmLy9eTYeAADA7Ti255hGPThKbV9oq4YPN7zuvo50B89gAoBshoIJALKJtQfWqtuUbprYdaIalG1gdRwAyNM2bdoku92ucePGqWTJkoqIiNCHH36okiVLWh0NAAAgVzix/4S+6PSFmvdrrmZ9m13x+kr7SgW2D1TBEgV1cPNB/TziZ9VoVcOCpACAa6FgAoBsYOvRrQqNCdXosNFqVamV1XEAIE86cuSIJk6cKLvdrv3796tPnz6aM2eOAgMDrY4GAACQqxiGoV+jf9XRpKOa+/5czX1/ruu19/e8L0natWqX4t6J0/nT5+VTzEd1O9VVh8EdrIoMALgKCiYAsNjeU3sVMi5Eb7d8W11qdrE6DgDkKSkpKYqLi5Pdbtcvv/yisLAwvfPOO2rdurXc3NysjgcAAJDrpPydovy++XV3+N1q93K7a+7X64teWZgKAHArKJgAwEJHzxxVyLgQDWgwQI/Vf8zqOACQJ5imqd9++01RUVGaPHmygoKCFBERoejoaBUsWNDqeAAAALnWgU0HdGjrIZULKmd1FABAJqBgAgCLJJ9PVmhMqMKqhenFZi9aHQcAcr3du3dr3LhxstvtMk1TkZGRWrNmjSpWrGh1NAAAgFzv5Zdf1pjoMQp7I0y+5X2tjgMAyAQUTABggZS0FHWZ1EWBJQM1rM0wq+MAQK71999/a9q0aYqKitK6devUvXt32e12NWrUSIZhWB0PAAAgzxg+fLjKDiprdQwAQCaiYAKALJbuSFf4D+Eq6FVQo8NGc4ETADJZenq6FixYILvdrlmzZqlFixZ66qmnFBoaKi8vL6vjAQAAAACQK1AwAUAWMk1TA2cP1NGzRxXXK07uNv4ZBoDMsmHDBtntdo0bN05ly5ZVRESERowYoRIlSlgdDQAAAACAXIcrmwCQhYYsGqI1B9ZoYcRCebt7Wx0HAHK8w4cPa8KECbLb7Tp06JDCw8M1f/581apVy+poAAAAuIyHPJSq1Ns/jsMtE9IAAG4XBRMAZJERK0do2qZpWtp3qQp6FbQ6DgDkWOfOndOsWbNkt9u1ZMkSPfDAAxo+fLhatmwpNzcuNgAAAGRXA4oOuP2DTJwovfCCtCxM8ve//eMBAG4ZBRMAZIGo+CiNXDVSy/ouU/H8xa2OAwA5jmma+vXXXxUVFaUpU6aobt26ioyMVExMjAoUKGB1PAAAAGSVHj2kw4elkBBp+XKpOL9jA4BVKJgA4A6L3RKrQQsGaVHkIpUvXN7qOACQoyQlJSk6Olp2u11ubm6KjIzU2rVrVaFCBaujAQAAwCpPPy0dPCiFhkoLFkjccAQAlqBgAoA7aHHSYvWL7afZvWcroHiA1XEAIEc4deqUpk6dqqioKG3cuFEPP/ywYmJi1KBBAxmGYXU8AAAAZAfvvCMdOiR17Sr9+KPk4WF1IgDIc2xWBwCA3GrtgbXqNqWbJnadqAZlG1gdBwCytbS0NM2dO1e9evVShQoVNGvWLP33v//Vvn379Pnnn6thw4aUSwAAAPiHYUhjxjiLpUcflRwOqxMBQJ5DwQQAd8DWo1sVGhOqMWFj1KpSK6vjAEC2tW7dOr344ouqUKGC3njjDTVr1kw7duzQ9OnT1blzZ3l6elodEQAAANmVu7s0aZK0c6f08stWpwGAPIcl8gAgk+09tVch40I0tNVQPVjzQavjAEC2c+jQIcXExMhut+vo0aMKDw/XwoULFRDAUqIAAAC4SfnzO5fIa95cKlVKeuEFqxMBQJ5BwQQAmejomaMKGReiAQ0G6NF6j1odBwCyjXPnzik2NlZ2u13Lly9Xp06d9NFHH6lFixay2ZhUDwAAgNvg6yvNnSvdc4+zZAoPtzoRAOQJFEwAkEmSzycrNCZUYdXC9GKzF62OAwCWM01TK1asUFRUlKZOnaq77rpLkZGRmjRpknx8fKyOBwAAgNykfHlpzhypZUupeHGpfXurEwFArkfBBACZICUtRV0mdVFgyUANazPM6jgAYKmdO3cqOjpa0dHR8vT0VGRkpBITE1WuXDmrowEAACA3q1VLmjFDeuABadYsqXFjqxMBQK5GwQQAtyndka7wH8JV0KugRoeNlmEYVkcCgCx38uRJTZkyRXa7XZs3b1aPHj00adIk1a9fn38XAQAAkHWaNJG++07q1En65ReJ53wCwB1DwQQAt8E0TQ2cPVBHzx5VXK84udv4ZxVA3pGWlqaffvpJdrtdc+fOVZs2bfTCCy+oXbt28vT0tDoeAAAA8qqwMGnYMKldO2n5csnPz+pEAJArcSUUAG7DkEVDtObAGi2MWChvd2+r4wBAlkhISJDdbldMTIz8/f0VERGhUaNGydfX1+poAAAAgNMjj0iHDjlLpiVLpKJFrU4EALkOBRMA3KIRK0do2qZpWtp3qQp6FbQ6DgDcUQcPHlRMTIyioqJ04sQJhYeHa/HixapevbrV0QAAAICre+kl6eBB5zOZfvpJypfP6kQAkKvYrA4AADlRVHyURq4aqZ/6/KTi+YtbHQcA7oizZ89q4sSJ6tChg2rWrKn169frk08+0a5duzR06FDKJQAAAGRvhiF99JFUvrzUo4eUlmZ1IgDIVSiYAOAmxW6J1aAFgzSvzzyVL1ze6jgAkKkcDoeWLl2qxx9/XH5+fvruu+/Up08f7du3T99++61atGghm40hJAAAAHIIm036/nvp7Fmpf3/JNK1OBAC5BkvkAcAF585JSUnSyZNSaqrk4SEVLixVqiR5eUmSFictVr/Yfprde7YCigdYmxcAMtH27dsVHR2t6Oho5c+fX5GRkVq3bp38eCAyAAAAcjpPT2naNKlVK+n116W337Y6EQDkChRMAHDsmLRpk3NdZklyOP55zc1N2rBBKl1aW0rY1G1mN03sOlENyjawJisAZKITJ05o8uTJstvt2rZtm3r27KmpU6eqXr16MgzD6ngAAABA5ilYUIqLk+65RypVSvq//7M6EQDkeBRMAPK27dulxEQpPf3qr2dsN/fvV/m95zWvySjVq9QqCwMCyLNuYFblrUhNTdVPP/2kqKgozZs3T23bttWgQYMUEhIiDw+PzMsPAAAAZDclS0rz5knNmzv/3r271YkAIEejYAKQd/1buXQRQ1J+m6fqHbY531e16p3PByBvusFZlapZU/L1vaFDmqap+Ph42e12TZgwQVWqVFFERITGjBmjokWL3oGTAAAAALKpSpWcM5nuv18qVkxq3drqRACQY1EwAcibjh274XLpEunpzvf5+t7whV0AuGE3OKtS+/dLhw5JQUHXLbz379+vmJgYRUVFKTk5WREREVq6dKmqVat2B8IDAAAAOURwsDRlitStmzR3rlS/vtWJACBHslkdAAAssWnTDZdLk1esUNPXXlP+Pn3U4s03ne/bvPnO5gOQ99zErEpJ/xTe27dfsvnMmTOKiYlRu3btFBgYqM2bN+uLL77Qjh079NZbb1EuAQAAAJJ0333S6NFSWJi0Y4fVaQAgR2IGE4C859y5f5aeugG+BQro2Q4dtHn/fi1cv9658cABKSXltp6DAgAuNzGrssGgQUrcvVup6enydHdXZIsWGj1xopauXy+73a7p06fr7rvvVmRkpKZPn678+fNnwQkAAAAAOVCXLtLhw1JIiLR8uVSqlNWJACBHYQYTgDxlx44d8i1dWn/s3ClJ2n/smEo89ph+2bDhmu9pExSk7k2bquzFzykxDCkp6Q6nBZBn3MSsSh8vL8148UWlxsRoVL9+Gvvzz3omIkJPPfWUatWqpY0bN2rOnDnq2bMn5RIAAADwb558UgoPl9q3l06dsjoNAOQoFEwA8pQqVapoeP/+6vPJJzqTkqK+X36pyPvuU4vatW/uQOnp0okTdyQjgLxj4cKFstlsGj95siTpj507ZXv4YY2Mi7vmexa/9ZY61K8vd3d3PdaqlUoWLqykQ4eU8Ntvev7551WmTJmsig8AAADkDq+/LjVuLD34oHO1EgDADaFgApDnPB4aqqqlS6vx4ME6cPy43unZ89YOlJqaucEA5DmtWrVSn7AwPTpqlP46dUpthw5V/UqV9Gxo6A29/1hyso6cOqXG1avL2L37DqcFAAAAcinDkD7/XCpSxDmb6UafiwoAeRwFE4C8x8NDj7durfV79uipdu3k5eFxy8cBgNtlf/VVFfXxUbn+/XU6JUULX3/9ht/bcNAgFS1QQIM7dWJWJQAAAHA73Nyk8eOdz2R65hnJNK1OBADZHgUTgDwn2d1dz0ZF6bFWrfTmlCk6lpx88wdxc3Pe2QQAtys1VY+3bq2U1FR1u/tuFbrB5yY1fOUVHThxQvHvvy+bzaYTR47o7NmzdzgsAAAAkIt5e0szZ0rLlknvvmt1GgDI9iiYAOQ5z3z2mRpUqaKxTz6p0Pr19eRXX113/3SHQ+fOn1daerocpqlz588rNTVV8vfPmsAAcrWDp05p2MyZql6mjMYvW6YdBw/+63vue+MNrdu9WwkffKByxYpJkpasWiVfX1/Vrl1bvXr10vDhwzV37lwdOHBAJndfAgAAADemcGFpzhzpm2+ksWOtTgMA2RoFE4A8ZebMmZo7f76+fO01SdLHkZH6Y9cujV+69JrviV6yRPn69FH/sWO1dNMm5evTR49HRUleXlkVG0Audu+AASpTpIi2fPKJqpcpoxZvvnnd/UOGDtXKrVv123vvqVqZMs6Nbm56oE8fnThxQuPHj1dISIgOHTqkDz74QHXq1FGpUqV0//3364UXXtC4ceO0bt06Z1EOAAAA4Eplykjz5klDhkixsVanAYBsy7jeHa0NGjQwV69enYVxACCLHDsmx6JFsjkcN/9eNzepRQvJ1zfTYwG3yjCMNaZpNrA6R153s2OnwYMHa/jw4dr6ySeqUqqUDp44ofL9++vx1q01ql+/q77H6N79im33BwXpp99+u2rxbZqm9u3bp4SEhEs+/vzzT9WoUUPBwcGXfBTLmBEFAEBuxbgp++C6E7K91aulDh2k6dOle+6xOg0AWOJ6YycKJgB50uHTh/X5hP9qSJFO8jCNG3+jm5sUFCRVrXrnwgG3gAsl2cMtj52WL5f277/1L+znJzVtelNvOXPmjNavX+8qnOLj45WYmKhChQqpbt26l5ROVatWlZub263nAwAgG2HclH1w3Qk5wvz5Up8+0oIFUmCg1WkAIMtdb+zkntVhAMBqf6f8rQ7jOyi0Wqg8yteXEhNVoFevq+47Z/BgNa9Z0/kJ5RKAO6VmTenQISk9/ebf6+YmBQTc9Nvy58+vRo0aqVGjRq5tDodDSUlJrtJpwoQJGjRokA4fPqzatWtfUjoFBQWpUKFCN58XAAAAyEnuv18aOVJq315atkyqWNHqRACQbVAwAchTzqefV5fJXXRXmbv0Zos3JcOQfH2VvHChdOCA8/OLL/C6uUmm6Vx/OSCAZfEA3Bm+vs4COzFRSk+/6jJ4kvTZo4/q/9q1+2fDheI7k/5tstlsqly5sipXrqwHH3zQtf3kyZNat26d4uPjFR8fr6ioKG3YsEGlS5e+Yok9f39/GcZNzAwFAAAAsruePZ03hLVrJy1dKhUvbnUiAMgWKJgA5BkO06HIGZEq6FlQo0JH/XMB1NfXubRUSoqUlCSdOCGlpkoeHlKRIpK//1WfawIAmerC7MjERJmTJ//7/lk4q7Jw4cK65557dM9F686np6dr27ZtrtlOX3/9tRISEvT3338rKCjIVTjVrVtXgYGBypcv3x3PCQAAANwxzz4rHTwohYU5l8vz8bE6EQBYjoIJQJ5gmqb+O/e/2v/3fs3rM09utqs8S8TLS6pRI+vDAcAFVas6S+/Nm7P9rEo3NzcFBAQoICBADz/8sGv7X3/95Sqdli1bpi+++EJbtmyRv7//FbOdypYty2wnAAAA5BzvvSf17St16ybNnOm8MRUA8jAKJgB5wvDlw7UoaZGW9F0ib3dvq+MAwLXl8FmVxYsXV+vWrdW6dWvXtvPnz2vz5s2u4mnEiBGKj4+XaZquWU4XSqeaNWvK09PTwjMAAAAArsEwpK+/lh58UHrsMen77yWbzepUAGAZCiYAud53a7/TmDVjtPzR5SriXcTqOABwY3LRrEpPT08FBQUpKChI4eHhkpwzSw8cOOAqnebMmaNhw4Zp165dql69+hWznUqUKGHxWQAAAABy3vg1ebLUurU0aJD0/vtWJwIAy1AwAcjVZm2dpcELB2vxI4tVtmBZq+MAADIYhqGyZcuqbNmyat++vWv72bNntWHDBiUkJCg+Pl4zZ85UYmKi8ufPf8lMp+DgYFWvXl1ubldZ8hQAAAC4k/Lnl2bNkpo3l0qVkp5/3upEAGAJCiYAudaKPSv06MxHNavXLFUvVt3qOACAG5AvXz41aNBADRo0cG0zTVO7d+92zXaaMmWKXnvtNR04cEC1atVyFU5169ZVUFCQChcubOEZAAAAIE8oVkyaN09q1sxZMvXpY3UiAMhyFEwAcqWNRzbqwUkPyv6gXY38GlkdBwBwGwzDkL+/v/z9/dWpUyfX9r///lvr1q1TfHy8EhISNH78eK1fv14lSpS4Yom9SpUqycb6+AAAAMhM5ctLc+ZIrVpJxYtL7dpZnQgAshQFE4BcZ8/JPWo3rp0+avuR2lVlcAcAuVXBggXVtGlTNW3a1LUtPT1dO3bscM12+u6775SQkKATJ06oTp06rplOwcHBCgwMlI+Pj4VnAAAAgByvdm3phx+kTp2cy+Y1bmx1IgDIMhRMAHKVY2ePKWRciJ69+1n1CWJ6OgDkNW5ubqpevbqqV6+ubt26ubYfO3bMVTqtXLlSo0eP1ubNm1W+fPkrZjuVK1dOhmFYeBYAAADIUZo2lb79Vho/XmrYUGLmPIA8goIJQK5xJvWMwmLCFFY9TM81ec7qOACAbMTX11ctW7ZUy5YtXdtSU1O1ZcsWV/H06aefKiEhQWlpaQoKCnLNdAoODlatWrXk5eVl4RkAAAAgW+vYUWrfnnIJQJ5CwQQgV0hNT1X3Kd1VrVg1DWszzOo4AIAcwMPDQ4GBgQoMDFTv3r1d2w8ePOgqnebPn68PP/xQO3bsUNWqVa+Y7VSqVCkLzwAAAADZivuVl1qPHDmiU6dOqUqVKhYEAoA7i4IJQI5nmqb+M+s/cpgOje04VjaDu4UAALeudOnSKl26tEJCQlzbzp07p40bNyohIUHx8fGKi4tTQkKCvL29ryidatSoIferXFwAAABA3vPtt99q+fLlio2NVWpqqjw8PKyOBACZht98AeR4gxcM1qYjm7QgYoE83BioAQAyn7e3t+rXr6/69eu7tpmmqT179rhmO/3www968803tXfvXtWsWdNVONWtW1dBQUEqWrSohWcAAACArORwOGSz2ZQ/f37XbHlbxvJ5pmnyzE8AuQIFE4Ac7ZNfP9EPm3/QskeXycfTx+o4AIA8xDAMVahQQRUqVFDHjh1d25OTk7Vu3TpX8TRp0iStW7dOvr6+V8x2qlKliutCAwAAAHK+1NRUnTx5Ulu2bNHp06f19ddfq3z58kpISFBiYqJiY2MZ/wHINSiYAORYE9dP1IcrP9SyvstUPH9xq+MAACBJKlCggJo0aaImTZq4tjkcDu3cudNVOkVHR+v555/XsWPHFBgYqLp167pKpzp16qhAgQIWngEAAABu1Y4dO/TMM8+obNmyOnLkiNavX69HHnlEVapUUYsWLWSaptURASDTUDAByJHm75ivZ+Y+owURC1SxSEWr4wAAcF02m01Vq1ZV1apV9dBDD7m2Hz9+XImJiUpISNDvv/+usWPHauPGjfLz87titlOFChVYSgUAACCbCwgI0JdffqnKlSsrOjpajRo10nPPPWd1LAC4IyiYAOQ4q/evVu/pvTWt+zQFlgy0Og4AALesaNGiuu+++3Tfffe5tqWlpWnr1q1KSEhQfHy8Ro0apYSEBJ07d+6K0ql27dry9va28AwAAABwwYVnK1Ws6LwRdtmyZfL395fkXDrPw+PK50afPHlSJ06ccL0HAHISCiYAOcq2o9vUcUJHfd3xazWv2NzqOAAAZDp3d3fVqlVLtWrVUs+ePV3bDx8+7Fpib9GiRRo5cqS2bdumypUrX1I61a1bV6VLl7bwDAAAAPKmC7PN3dzcJEk1atRQ06ZNJemq5VJycrLWrl2rQYMGadiwYWrRokWWZQWAzEDBBCDHOPD3AYWMC9HbLd9Wp4BOVscBACBLlSxZUvfff7/uv/9+17aUlBRt3LjRVTzNmzdPCQkJcnd3v2K2U0BAwFUvbAAAACBz/f333ypYsKCee+45nTt37pr7FShQQC1atNDgwYP1xBNPaObMmQoICMjCpABweyiYAOQIJ8+dVPvx7fVYvcfUr34/q+MAAJAteHl5qV69eqpXr55rm2ma2rdvn6t0+vHHHzV06FD9+eefqlGjhmuW04XiydfX18IzAAAAyH3mz5+v33//Xe+99568vb3lcDhks9lcf5qmqbS0NHl4eCgtLU0PPPCAVq9erT/++IOCCUCOQsEEINs7l3ZOnSd1VvMKzTW4+WCr4wAAkK0ZhqFy5cqpXLlyCg0NdW0/ffq01q9f7yqepk6dqsTERBUuXPiK2U5Vq1Z1Le0CAACAm/Pggw9q6tSp+uKLLzRw4EDZbDZJcv1pGIZrZrm7u7t+//13jR07Vl999ZVlmQHgVlAwAcjW0h3p6jO9j0r6lNTIdiNd6xkDAICb4+Pjo8aNG6tx48aubQ6HQ0lJSa7SKSYmRi+//LKOHDmiwMDAS0qnoKAgFSxY0MIzAAAAyBkMw1B0dLQ6d+4sX19f9ezZUw6HQ7Gxsfr4449Vu3ZtJSQkqFChQipUqJB+++03vfLKKwoLC7M6OgDcFAomANmWaZp6es7TOn7uuGb3mi03G3dSAwCQmWw2mypXrqzKlSvrwQcfdG0/efKkEhMTlZCQoLVr1+r777/Xhg0bVLp06StmO/n7+3MDCAAAwGXc3Nw0ZcoU3X333QoMDFSdOnVUr149bdy4UU2aNNH48eN18OBBlSlTRunp6apSpYrVkQHgplEwAci2hi4ZqhV7V2jxI4vl5e5ldRwAAPKMwoULq3nz5mrevLlrW3p6urZt26b4+HglJCToq6++UkJCgk6fPq2goKBLSqfAwEDly5fPwjMAAACwnre3t3799Vd5e3tLkipWrKgFCxboiSeeUKdOndS0aVPXvqZpctMOgByHgglAtvTVmq/0fcL3Wv7ochXyKmR1HAAA8jw3NzcFBAQoICBAPXr0cG3/66+/XEvsLV26VJ9//rm2bNkif39/V+FUt25dBQcHq0yZMlw4AQAAecqFcik9PV2GYSg4OFiDBw/W0KFDNXHiRBUq5LzmwRgJQE5EwQQg2/lh0w9685c3taTvEpUuUNrqOAAA4DqKFy+u1q1bq3Xr1q5t58+f16ZNm1zF00cffaSEhARJumKJvZo1a8rT09Oq+AAAAFnCzc257L9pmnrggQfUqFEj+fj4XLpTWprkzuVaADkH/2IByFaW7F6iJ2Y9obl95qqqb1Wr4wAAgFvg6enpKpAuME1TBw4ccJVOc+bM0XvvvaekpCRVr179kplOwcHBKl68uIVnAAAAcGdcmKlUuvRlN9SapvTnn9Kvv0q9elmQDABuHgUTgGwj8VCiuk3ppgkPTVD9MvWtjgMAADKRYRgqW7asypYtq/bt27u2nzlzRhs2bHAVTzNmzFBiYqJ8fHyumO1UvXp1192/AAAAuYphSA6H9PzzUoEC0gMPWJ0IAP4VBROAbCHpRJI6jO+gz9p/ptaVW//7GwAAQK6QP39+NWzYUA0bNnRtM01Tu3fvVkJCguLj4zV58mS9+uqrOnjwoGrXrn1J6RQUFKTChQtbeAYAAACZpGpVaeZMKTRUmjFDatbM6kQAcF0UTAAsd+T0EYWMC9HLzV5W99rdrY4DAAAsZhiG/P395e/vr06dOrm2nzp1SuvWrXPNdho3bpzWr1+vEiVKXFI61a1bV/7+/rLZbBaeBQAAwC1o1EgaN07q0kVauFCqXdvqRABwTRRMACyVfD5ZYRPC1LVmVz3V+Cmr4wAAgGysUKFCatasmZpddDdvenq6duzYofj4eCUkJOjbb79VQkKCTp48qaCgoEuKpzp16ih//vwWngEAAMANCAmRPv5YatdOWr5cqlDB6kQAcFUUTAAsk5qeqq6TuyqwRKCGthpqdRwAAJADubm5qXr16qpevbq6d/9nJvTRo0eVmJiohIQErVy5UqNHj9bmzZtVvnz5S2Y6BQcHy8/Pz/XAbQAAgGyhd2/p8GFn2bRsmVSsmNWJAOAKFEwALOEwHXo09lF5unlqTMcxXNQBAACZqlixYmrZsqVatmzp2paamqrNmze7ltj75JNPlJCQoLS0tEtmOgUHB6tWrVry8vKy8AwAAECe99//SgcPOp/JtGCB5ONjdSIAuAQFEwBLvDT/Je06vks/hf8kdxv/FAEAgDvPw8NDderUUZ06ddSnTx/X9oMHD7pKp59++kkffPCBdu7cqapVq7pmOV34KFmypIVnAAAA8pxhw6S+faXu3aUZMyQPD6sTAYALV3UBZLkPV3youdvnaknfJcrvwXMQAACAtUqXLq3SpUsrJCTEte3cuXPasGGDq3iaNWuWEhIS5O3tfcVspxo1asjdnV+tAADAHWAY0tdfS507S/36Sd9/79wGANkAvwUByFL2BLs+++0zLX90uXzz+VodBwAA4Kq8vb1111136a677nJtM01Te/bsUUJCguLj4zV9+nS98cYb2rdvn2rVqnVF8VSkSBHrTgAAAOQeHh7S5MlSmzbSoEHS8OFWJwIASRRMALLQ7G2z9dL8l7QocpHKFSpndRwAAICbYhiGKlSooAoVKqhjx46u7cnJyVq3bp1rttPEiRO1bt06+fr6XlI41a1bV5UrV5bNZrPwLAAAQI7k4yPNmiXdc49UqpT03HNWJwIACiYAWWPV3lV6ZMYjiu0Zq5olalodBwAAINMUKFBATZo0UZMmTVzbHA6HduzY4Sqd7Ha7nn/+eR07dkx16tS5pHiqU6eOChQoYOEZAACAHKFYMWnevH9Kpt69rU4EII+jYAJwx23+a7M6T+qs7zt/r7vL3W11HAAAgDvOZrOpWrVqqlatmrp27erafvz4cSUmJiohIUG///67vv76a23atEl+fn6uWU4Xiqfy5cvL4BkLAADgYhUqSHPmSK1aScWLSxc9QxIAshoFE4A7at+pfWo3rp2GtR6mDtU6WB0HAADAUkWLFtV9992n++67z7UtLS1NW7Zscc12+uKLL5SQkKCUlBQFBQVdMtupdu3a8vb2tvAMAACA5WrXlqZPlzp3luLipEaNrE4EII+iYAJwxxw/e1ztxrfTgIYDFFk30uo4AAAA2ZK7u7tq166t2rVrq1evXq7thw8fdpVOCxcu1IgRI7R9+3ZVqVLlktIpODhYpUuXtvAMAABAlmvWTPr2W6lTJ+mXX6QaNaxOBCAPomACcEecTT2rByY+oPsr368Xm75odRwAAIAcp2TJkrr//vt1//33u7alpKRo48aNruJp7ty5SkhIkLu7+xWlU0BAgDw8PCw8AwAAcEd17Ci9847Urp20fLlUtqzViQDkMRRMADJdmiNNPab1UIXCFfRh2w95dgAAAEAm8fLyUr169VSvXj3XNtM0tW/fPsXHxyshIUGxsbF6++23tWfPHgUEBFxRPPn6+lp4BgAAIFM9+qh06JCzZFqyRCpSxOpEAPIQCiYAmco0TfWf1V/n0s5pSrcpshk2qyMBAADkaoZhqFy5cipXrpzCwsJc20+fPq3169e7ZjtNnTpViYmJKly4sKtsqlu3roKDg1WlShW5ublZeBYAAOCWDRokHTwoPfCANG+elC+f1YkA5BEUTAAy1euLXlfCoQQtjFwoTzdPq+MAAADkWT4+PmrcuLEaN27s2uZwOLRr1y5X6TR+/Hi99NJLOnLkiAIDAy+Z6RQUFKSCBQtaeAYAAOCGGIY0YoTUq5fzY+pUiRtHAGQBCiYAmebz3z7XpA2TtPzR5SrgWcDqOAAAALiMzWZTlSpVVKVKFXXp0sW1/eTJk0pMTFRCQoLWrl2r7777Ths3blTp0qVds5wufFSsWJElkAEAyG5sNikqSgoLkwYMkEaPdhZPAHAHUTAByBSTN0zWsGXDtOzRZSrhU8LqOAAAALgJhQsXVvPmzdW8eXPXtrS0NG3bts0122nMmDFKSEjQ6dOnFRQUdEnpFBgYqHwsxwMAgLW8vKTp06WWLaW33pLefNPqRAByOQomALdt4a6FemrOU5ofPl/+RfytjgMAAIBM4O7urpo1a6pmzZrq0aOHa/uRI0eUmJio+Ph4LVmyRJ999pm2bt2qSpUqXVI6BQcHq0yZMsx2AgAgKxUsKM2eLTVrJpUqJfXvb3UiALkYBROA27L2wFr1mNpDU7pNUVCpIKvjAAAA4A4rUaKEWrdurdatW7u2nT9/Xps2bXLNdvroo4+UkJAgSZcUTnXr1lVAQIA8PXlWJwAAd0zJktK8eVLz5lKJElLXrlYnApBLUTABuGU7ju1QaEyoRoeN1n3+91kdBwAAABbx9PR0lUgXmKapAwcOKD4+XgkJCZo9e7bee+897d69W9WrV79itlPx4sUtPAMAAHKZypWlWbOkkBCpeHGpRQurEwHIhSiYANySQ8mHFDIuRK/f97q61Ozy728AAABAnmIYhsqWLauyZcuqQ4cOru1nzpzRhg0bXLOdZsyYoYSEBBUoUEB169a9pHSqVq2a3NzcLDwLAABysHr1pIkTpe7dpZ9+kurWtToRgFyGggnATTuVckrtx7dXeFC4nmzwpNVxAAAAkIPkz59fDRs2VMOGDV3bTNNUUlKSq3SaNGmSBg8erIMHD6p27dqXlE5BQUEqXLiwhWcAAEAO0qqV9MUXUmiotHSpc2YTAGQSCiYANyUlLUVdJnVRY7/Gev2+162OAwAAgFzAMAxVqlRJlSpVUufOnV3bT506pXXr1rmW2YuOjtb69etVsmTJK2Y7+fv7y2azWXcSAABkV926SUeOOJfLW77c+YwmAMgEFEwAbpjDdChiRoQKexfW5x0+l2EYVkcCAABALlaoUCE1a9ZMzZo1c21LT0/X9u3bXbOdvvnmGyUkJOjUqVOqU6eOq3CqW7euAgMDlT9/fgvPAACAbGLAAOngQalDB2nRIqlgQasTAcgFKJgA3BDTNPXs3Gd1KPmQ5vaZKzcba+EDAAAg67m5ualGjRqqUaOGunfv7tp+9OhRJSYmKj4+XitWrNCXX36pLVu2qEKFCpfMdAoODpafnx83SwEA8p633nKWTF26SHFxkqen1YkA5HAUTABuyLBlw7R492IteWSJvN29rY4DAAAAXKJYsWJq2bKlWrZs6dqWmpqqzZs3u2Y7ffLJJ4qPj1d6erprltOF0qlmzZry8vKy8AwAALjDDEMaNcq5ZF5kpDR+vMTysgBuAwUTgH/1zR/f6Ks/vtLyR5ersDcPVAYAAEDO4OHhoTp16qhOnTrq06ePJOfM/IMHD7pKp3nz5un999/Xzp07Va1atStmO5XkORUAgNzE3V2KiXE+j+m//5VGjnQWTwBwCyiYAFxX7JZYvbboNS1+ZLHKFixrdRwAAADgthiGoTJlyqhMmTJq166da/u5c+e0YcMGJSQkKD4+Xj/++KMSEhKUL1++K2Y7Va9eXe7u/DoNAMih8uWTYmOle++Vhg+XBg2yOhGAHIoRMYBrWv7ncvWL7ae4XnGqXqy61XEAAACAO8bb21t33XWX7rrrLtc20zT1559/umY7TZs2Ta+//rr279+vmjVrXjHbqUiRItadAAAAN6NIEWnuXKlZM6lUKalvX6sTAciBKJgAXNWGwxvUZXIXjesyTg39GlodBwAAAMhyhmGoYsWKqlixoh544AHX9uTkZK1bt84122nChAlav369ihUrdkXpVLlyZdl4vgUAIDsqW9ZZMt13n1S8uNSxo9WJAOQwFEwArrDv1D61G99OI0JGqG2VtlbHAQAAALKVAgUKqEmTJmrSpIlrm8Ph0I4dO1yznaKiopSQkKBjx46pTp06lyyzV6dOHfn4+Fh4BgAAZKhRw7lcXmioNHOm1LSp1YkA5CAUTEAeZpqmjMse5Giapgp4FtCw1sPUq04vi5IBAAAAOYvNZlO1atVUrVo1de3a1bX92LFjSkxMVEJCglatWqWvvvpKmzZtUrly5a6Y7VS+fPkrxucAANxxjRpJ0dHSgw9KCxdKtWtbnQhADkHBBORhV/vl1TAMFfQqqN5BvS1IBAAAAOQuvr6+atGihVq0aOHalpaWpi1btrhmO33++edKSEjQ+fPnFRQU5JrpFBwcrFq1asnb29u6EwAA5A3t2kkffSS1by8tXy6VL291IgA5AAUTkAe9++67OnXqlMqXL6/27durcuXKl7xuM1gjHgAAALhT3N3dVbt2bdWuXVu9ev2zasChQ4dcpdOCBQv08ccfa/v27apSpcoVs51Kly5t4RkAAHKlPn2kw4elkBBp6VKpWDGrEwHI5iiYgDzmmWeeUVJSktq0aaOkpCTNmzdP/fv3v+pyeQAAAACyTqlSpdS2bVu1bfvPc1BTUlK0ceNGV/E0Z84cJSQkyNPT84rSqUaNGvLw8LDwDAAAOd5zz0kHD0phYdLPP0s8MxDAdVAwAXnInDlztHr1ai1fvlySNH36dI0YMULh4eEqUKCAxekAAAAAXM7Ly0v16tVTvXr1XNtM09TevXtdpdPMmTP1v//9T3v27FFAQICrcLqw1F7RokUtPAMAQI4zbJjUt6/08MPSDz9I3LwA4BoomIA8pGnTpnrppZdcs5W6dOmiqKgoHT58WAUKFJDD4ZDNxvJ4AAAAQHZmGIbKly+v8uXLKywszLX99OnTWrdunat4mjJlitatW6ciRYpcMdupatWqlo79Rx0fpVSl3vZxPOShAUUHZEIiAICLzSaNHSt16iQ9/rj03XcSq94AuAoKJiCPcDgcKly4sDp16iRJrpIpJSVFf/31lypVqqRXX31Vffv2VfXq1S1OCwAAAOBm+fj46O6779bdd9/t2uZwOLRr1y5X6TR+/Hi9+OKL+uuvvxQYGHjJTKc6deqoYMGCWZI1M8qlzDwOAOAyHh7SlClS69bSK684ZzUBwGUomIA84vK7E9PS0uTh4aHq1avr5MmT6tevnwoWLEi5BAAAAOQiNptNVapUUZUqVdSlSxfX9hMnTigxMVEJCQlas2aNvv32W23cuFFlypS5YrZTxYoVeV4rAORFPj5SXJx0zz1SqVLSf/9rdSIA2QwFE5BHXXj4r5+fnx588EGFh4dr5MiRksRSeQAAAEAuV6RIEd1777269957XdvS0tK0bds212yn0aNHKyEhQWfOnLmidKpdu7by5ctn4RkAALJEsWLSvHlSs2ZSyZJS795WJwKQjVAwAbnYjRRF+fPnV8WKFfXll19KktLT0+Xm5pYV8QAAAABkI+7u7qpZs6Zq1qypHj16uLYfOXLEVTotXrxYn376qbZu3apKlSpdUjrVrVtXpUuXvuHZToP8BymwfaC6ftBV7zV+T38f/luOdIc6v9NZLfq3cO331cNfaevirUo7nyabm00BrQL0n0n/yezTBwBcS4UK0pw5GlV4tlKPf3Lbh+P5eUDuQcEE5EIXiiWbzfavJdNTTz2lAQOcP9QplwAAAABcrkSJEmrTpo3atGnj2nb+/Hlt2rRJ8fHxSkhI0IcffqiEhATZbLYrZjsFBATI09Pzul+jfL3yCmgZoGkvT7viNdM01eOzHgrqGKTty7ZrbM+xmvbyND00/KFMP1cAwDUEBir1+IJMORTPzwNyDwomIBfq0aOHKlWqpOHDh1+3ZEpPT5fNZpObm5v+/vvvLHugLwAAAICczdPT01UgXWCapvbv3++a7RQXF6d3331XSUlJqlGjxiUznVTvn2N5F/BWv3H9JOmqBdMTk59w/b1Wm1oqHVBa25dvv2PnBgAAgBtDwQTkMn379lVSUpJKlCih//u//9MHH3ygfPnyXbVkMgxDhmFowYIF+uOPP/TCCy/w8F4AAAAAt8QwDPn5+cnPz08dOnRwbT9z5ozWr1/vKp5++OEHdY3tektfw+Fw6MiOI6oTWiezYgMAAOAWUTABucwDDzygJ554QkWLFtWnn36qAQMG6P3331eJEiUu2e/CcniJiYl64YUXtGDBAsolAAAAAJkuf/78atSokRo1auTa9sktPsPji45fyDRNdf+oe2bFAwDchM86fqYG3RqoYY+Gin48Wn/G/6nje45rYOxAVbunmmu/hZ8u1G8Tf9Pxvcfl4+ujex69R62ebmVhcgB3wrUfzAIgR3rwwQd19913q0aNGnr22WdVqlQpDRw4UKdPn9bff/+t1atXu8qlP//8U//5z3/0448/ytfX1+roAAAAAHBN3/X9Trt+26WnZj0l70LeVscBgDyv0t2VFD4mXIVKFbriNVOmen/ZW+/ufFdPTHlCS8cu1R/T/rAgJYA7iYIJyMWqVaumxx9/XE2bNlWnTp1Urlw57d27V25ubjp37pwiIiI0duxYlStXzuqoAAAAAHKpM2fOaNWqVfrqq680cOBA3XPPPTd9jJiBMUr8MVH9f+ivindVvAMpAQA3w93TXS36t1DluyvLsF25Ik7rp1urfHB5ubm7qVS1UgrsEKhdv+2yICmAO4kl8oBcIC0tTe7uV//PuUqVKnrggQc0dOhQDR48WJ07d5YkeXt765tvvlGVKlWyMCkAAACA3Mo0Te3bt8/1rKULH7t371ZAQICCg4MVHBysrl27KlGJl7z33KlzcjgckqTUs6k6c+KMvAt5y2azacoLU/T7pN/12PjHLll+CQCQM5imqZ0rd6rpI02tjgIgk1EwATnYkiVL5OfnpypVqriWvbuYaZoyDEMffvihevTooZdfflmSlJqaKg8PD8olAAAAALckJSVFmzZtUnx8/CVlkru7u6tI6tixo1577TUFBATIw8PjkvcnHncWTBeeAzu4ymA50p0FU9zQOMUNjdNTcU+pSpMqWhm1UqbD1NieY13vL1W9lF759ZUsOlsAwO2YO2yuTIepxr0aWx0FQCajYAJysCVLluh///ufVqxYoQYNGsjhcMgwDNcvaRf+fO+991S4cGFJksPhuOKXOwAAAAC4lsOHD18xK2nbtm2qXLmyq0wKCQlR3bp1Vbp06Rs+bvr5dNdzOz4+8vE197veawCA7G3p10v1+6Tf9XTc03L34lI0kNvwXzWQg7322msqVaqUWrdurZiYGIWGhkr6Z+aS5JytdKFcAgAAAIBrSUtL09atW10l0oXZSefOnXMVSS1bttSzzz6r2rVry9vb+5a/VmJcolLPpap2u9qZeAYAgOzk13G/6ueRP+upuKdUxK+I1XEA3AEUTEAO9/jjj6tEiRLq2bOnRo4cqUcffVSGYbhmM12YrRQXF6fQ0FDZbDaLEwMAAACw2okTJ66YlbRp0yaVLVvWVSYNGDBAwcHBqlChgusGtszQuHFj/b76dwWFBaly48qZdlwAQNZKS0mTaZqSnLNSU8+lyt3LXYZhaPWU1YobGqeBMwequH9xi5MCuFMomIAczjRNde7cWXPnzlXHjh116NAhvfLKK7LZbEpLS5O7u7u+++47jR8/Xu3bt6dgAgAAAPIQh8OhnTt3XlIkxcfH6+jRo6pTp46Cg4PVsGFD9evXT3Xq1FGBAgXueKZVq1bpk+Of3PGvAwC4My7cdPBOo3d0fM9xSdLorqMlSUPih6hYhWKa/c5snT52Wh+3+WeZ0wbdGqj7x92zPjCAO4aCCcjhLsxWatq0qVauXKnWrVvr2LFj+uCDD+Tu7q4ff/xRMTExmj17NuUSAAAAkIslJydr3bp1l5RJ69atk6+vr2tWUnh4uD788ENVqVKF3w8AADct5e8U5ffNL0l6I+GNa+73evzrWRUJgIUomIAczDRNmaYpm80mh8Oh6tWra82aNerUqZNWrFghh8OhN954Q0uWLJGnp6fVcQEAAABkAtM0tWfPniuWuNu7d69q1qzpKpN69OihoKAgFS1a1OrIV/CQh1KVminHAQBkjQObDujQ1kMqF1TO6igAsgkKJiCHcpgOvTj/Rb3W/DUV8S7iKplKliyphg0bauPGjTJNU/PmzcuSZS4AAAAAZL5z585p48aNlyxvl5iYKC8vL1eR9OCDD+rNN99UjRo15O6eM37NH1B0gNURAAA34eWXX9aY6DEKeyNMvuV9rY4DIJvIGSNPAJcwTVPPz3teqw+slre7t2vtW5vNpuTkZLm5uSksLEylS5e2OCkAAACAG3Xw4MErZiXt2LFDVatWdZVJHTp0UHBwsEqVKmV1XABAHjJ8+HCVHVTW6hgAshkKJiAH+mDFB/p5189a8sgS5fPId8lrBQoUcD1/CQAAAED2k5qaqi1btlwyKykhIUGpqakKDg5W3bp1df/99+uFF15QrVq15OXlZXVkAAAA4ApcgQZymKj4KI36fZSWP7pcRfNdfS11yiUAAAAgezh27NgVs5I2b96s8uXLu2YlPf300woODla5cuVcqxMAAJDd8Pw8AJfjKjSQg8RtjdPLP7+sXx75RX6F/KyOAwAAACCDw+HQ9u3bryiTTpw4oTp16ig4OFhNmjTRk08+qcDAQPn4+FgdGQCAm3Lbz887dky65x7pscek5zMnEwBrUTABOcSve39V35l99WPPHxVQPMDqOAAAAECe9ffff2vdunWXLG+3fv16lShRwjUrqW/fvgoODlalSpVks9msjgwAgPV8faV586RmzaRSpaQ+faxOBOA2UTABOcCmI5vUeWJnRXWOUuNyja2OAwAAAOQJpmlq9+7dV8xKOnDggGrVquUqk3r37q2goCAVKVLE6sgAAGRv5ctLc+ZIrVpJJUpIISFWJwJwGyiYgGxu76m9aje+nd6//321r9be6jgAAABArnT27Flt2LDhkllJiYmJyp8/v4KDg1W3bl1169ZNQ4cOVbVq1XjuKQAAt6p2bWn6dKlzZ2n2bKlhQ6sTAbhFjIiBbOzY2WMKGReipxo9pYjgCKvjAAAAADmeaZo6cODAFbOSdu3aperVq7tmJXXq1EnBwcEqUaKE1ZEBAMh9mjWT/r+9+46v+V78OP4+GRJ7VY3EHhEjJzWK2lQFkdhbUtRsjVIrV9Ga1YkWVaV2jVIzVrVWF9qIWYIgMUrtlXl+f+Q2v7pGjSSfk+T1fDw8rpycxEvv7fV13t/v93z5peTnJ23bJpUqZboIwFNgYALs1O2Y2/Jb7KdGJRrprZfeMp0DAAAApDrR0dE6cuTIfWNSfHx84lVJjRo10rBhw+Tp6akMGTKYTgYAIP3w85P+/FPy8ZF27ZLy5zddBOAJMTABdig2PlbtlrdT0ZxFNanBJNM5AAAAgN3766+/7rm93b59+3T06FEVLlw48aqkN998U1arVQUKFJDFYjGdDAAAXntNunBBatQo4Uqm7NlNFwF4AgxMgJ2x2WzquaanYuJjNNtvthwsDqaTAAAAALsRFxenY8eO3XdV0o0bN+Tl5SWr1aoaNWrojTfeUNmyZZUpUybTyQAA4FGCgqRz5xLekyk4WHJ1NV0E4DExMAF25u3v39b+P/dra+BWOTs6m84BAAAAjLl+/bpCQ0PvuSrp4MGDyps3r7y9vWW1WtW9e3dZrVYVKVKEq5IAAEiNLBZp8mSpfXupUydpyRLJ0dF0FYDHwMAE2JGpv0zVskPLtLPLTmXJkMV0DgAAAJAibDabTp48ed9VSRcuXFC5cuUS3y8pMDBQXl5eypYtm+lkAACQlBwdpfnzE26V16+f9OmnCcMTALvGwATYiSUHlui9Xe9pZ9edypM5j+kcAAAAIFncvn1bBw4cuGdICg0NVdasWROvSmrfvr0mTpyoEiVKyJEzmAEASB9cXKSVK6U6daSxY6W33zZdBOBfMDABdmDLiS3qG9xXWwK2qEiOIqZzAAAAgGdms9l09uzZe25vt2/fPp0+fVoeHh6yWq2yWq1q0aKFrFarcufObToZAACYlj17wvswvfSSlC+f1L276SIAj8DABBj227nf1OGbDlreZrm88nqZzgEAAACeWHR0tA4dOnTfLe4cHBwShyRfX1+NGDFCpUuXlrMz7zUKAAAeIl8+aeNGqVYtKU8eqVkz00UAHoKBCTAo7HKYfBf5ambTmapVuJbpHAAAAOBfXbx4Ufv27bvnyqRjx46pWLFiiWPS4MGDZbValS9fPll4/wQAAPCkSpaU1qxJeE+m3LmlmjVNFwF4AAYmwJDzN8+r4YKGGl1ntJqVbmY6BwAAALhHbGysjh49et9VSbdv304ckurUqaP+/furbNmyypgxo+lkAACQllSqJC1aJLVqJX33nVSunOkiAP+DgQkw4HrUdTVa2EivWl9Vj4o9TOcAAAAgnbt69apCQ0MTR6SQkBAdOnRIBQoUkLe3t6xWq3r37i2r1apChQpxVRIAAEgZDRpIn3yScCXTzp1S4cKmiwD8AwMTkMKiYqPUfElzveT+kkbUGmE6BwAAAOlIfHy8Tpw4cd9VSZcuXVL58uVltVpVsWJFde3aVeXLl1fWrFlNJwMAgPSufXvpwgXJxydhZMqd23QRgP9iYAJSUFx8nDqv7KxcGXNpSqMpnPkJAACAZHPr1i3t37//niEpNDRUOXPmTLzFXefOnfXBBx+oePHicnBwMJ0MAADwYAMGSOfOSU2aJNwuL3Nm00UAxMAEpBibzab+G/rr4u2LCu4YLEcHR9NJAAAASANsNpsiIiIUEhJyz5gUEREhT0/PxDGpTZs28vLyUq5cuUwnAwAAPLmJE6UuXaQ2baRvv5WcnU0XAekeAxOQQsbvGK+dp3dq26vb5OrkajoHAAAAqdDdu3d16NCh+25xlyFDhsQhqVmzZho1apQ8PDzkzAsvAAAgrbBYpC++kJo1k7p3l+bMSXgMgDEMTEAKmPXbLM0Oma2dXXYqu2t20zkAAABIBS5cuJA4IP19ddLx48dVokSJxDGpcePGslqtyps3r+lcAACA5OfsLC1dKtWvLw0fnnBVEwBjGJiAZLbqyCqN/H6ktr26Tfmz5jedAwAAADsTExOjP/74476rkqKjoxOHpJdfflmDBg1SmTJl5OrK1fAAACAdy5xZWrtWqlFDypcv4f2ZABjBwAQkox2ndqj7mu4K7hiskrlLms4BAACAYVeuXLlnRAoJCdGRI0fk7u4uq9Uqb29v9e3bV1arVe7u7rJw2xcAAID7PfectHFjwsiUN6/Uvr3pIiBdYmACksn+C/vValkrLWyxUBULVDSdAwAAgBQUHx+vsLCw+65KunLliry8vGS1WlWlShX16NFD5cuXV+bMmU0nAwAApC6FC0vr10svv5wwODVoYLoISHcYmIBkcOrqKTVe1FiTfSarQXH+cAMAAEjLbty4of37998zJB04cEC5c+dOvMXdq6++Km9vbxUtWlQODg6mkwEAANKG8uWl5culFi2kDRukipzkDaQkBiYgiV26fUk+C330VrW31K5cO9M5AAAASCI2m02nT59OvLXd32PSuXPnVKZMmcQxqUOHDvLy8lKOHDlMJwMAAKR9NWtKX3whNW0qbdsmleRtKoCUwsAEJKFb0bfku8hXzTyaqX/V/qZzAAAA8JTu3LmjgwcP3nNVUmhoqDJmzJg4JLVq1UpjxoxRqVKl5OTEX60AAACMadZM+vNPycdH2rVLypfPdBGQLvC3ICCJxMTFqPWy1iqTp4zG1x9vOgcAAACPwWaz6fz584kj0t9XJp08eVIlS5aUt7e3rFar/Pz8ZLValSdPHtPJAAAAeJAePaTz56VGjRKuZMqWzXQRkOYxMAFJIN4Wr26ru8nRwVEzm86UxWIxnQQAAID/ERMTo8OHD99zVdK+ffsUHx+feFWSj4+Phg4dKk9PT7m4uJhOBgAAwJN4++2Ekal5c2n9eonjOSBZMTABSWDYlmEKuxymLQFb5OTAv1YAAACm/fXXX/cNSUeOHFHhwoUTx6Q333xTVqtVBQoU4AQhAACAtMBikaZOldq2lTp3lhYvlhwdTVcBaRavhAPP6MMfP9Tao2u1s+tOZXLOZDoHAAAgXYmLi1NYWFjire3+/nHjxg15eXnJarWqevXq6tOnj8qVK6dMmTheAwAASNMcHaUFCxLej2nAAGnKlIThCUCSY2ACnsGC0AWa8usU7eyyU7ky5jKdAwAAkKZdv35doaGh9wxJBw8e1PPPP594VdJrr70mb29vFSlShKuSAAAA0itXV2nVKqlWLWnCBCkoyHQRkCYxMAFPaUPYBr216S1tDdyqgtkLms4BAABIM2w2m8LDw7Vv3757rky6cOGCypUrlzgmBQQEyMvLS9l4A2cAAAD8r+zZpeBgqXp1KW9eqVs300VAmsPABDyFXyN/VcDKAK1qt0pl8pQxnQMAAJBq3b59WwcOHLjnqqTQ0FBlzZo1cUhq166dJkyYoJIlS8qRe+gDAADgcRUoIG3cKNWuLeXJI/n5mS4C0hQGJuAJ/XHpD/l/7a/Z/rNVrWA10zkAAACpgs1m09mzZ+8ZkkJCQnTq1Cl5eHjIarXK29tbLVq0kJeXl5577jnTyQAAAEgLSpVKuF1ekybSt98mXNEEIEkwMAFP4OyNs/JZ6KPx9cbLt5Sv6RwAAAC7FB0drUOHDt0zJu3bt08ODg6JVyU1adJEQUFBKl26tDJkyGA6GQAAAGnZiy9KCxZILVpIW7dKZcuaLgLSBAYm4DFdvXtVPgt81LNiT3V5oYvpHAAAALtw8eLF+4ako0ePqmjRoolj0uDBg2W1WpUvXz5ZLBbTyQAAAEiPGjaUPvxQatRI2rVLKsh7qgPPioEJeAx3Yu7Ib7Gf6hWtp6HVh5rOAQAASHGxsbE6duyYQkJC7hmTbt++nTgk1a5dW/369VPZsmWVMWNG08kAAADAvTp1ki5cSBibdu6UcuUyXQSkagxMwL+Ii49ThxUd5J7NXR81/IizbgEAQJp39epVhYaG3jMkHTp0SPnz508ck3r16iWr1arChQtzfAQAAIDUY9Ag6fx5yddX2rJFypTJdBGQajEwAY9gs9nUZ10f3Yy+qSWtlsjB4mA6CQAAIMnEx8fr5MmTiSPS31cnXbp0SeXKlZO3t7cqVqyorl27qnz58sqaNavpZAAAAODZvfeeFBgotW0rrVwpOfEyOfA0+DcHeITRP4zW3nN79X3g98rgyJtPAwCA1OvWrVvav3//PVcl7d+/Xzly5Ei8KqlTp056//33Vbx4cTk6OppOBgAAAJKHg4M0e7bk5yf17CnNmiVxVT7wxBiYgIeYvnu6Fh1YpF1ddymrC2frAgCA1MFmsykiIuKeIWnfvn06c+aMSpcuLavVKm9vb7Vp00ZeXl7KxX3nAQAAkB45O0vLlkn16kkjRkjjxpkuAlIdBibgAZYfWq6xO8ZqR5cdej7z86ZzAAAAHigqKkoHDx68b0zKkCFD4lVJ/v7+GjlypDw8POTs7Gw6GQAAALAfWbJI69ZJNWpIBQtKvXqZLgJSFQYm4H/8EP6D+qzro02dN6lYzmKmcwAAACRJFy5cuG9ICgsLU/HixRPHpEaNGslqtSpfvnymcwEAAIDUIU8eafNmKSpKio3l/ZiAJ8C/LcA/hJwPUZtlbbSk1RJ55/M2nQMAANKh2NhY/fHHH9q3b59CQkISx6To6OjEIal+/foaOHCgypQpI1dXV9PJAAAAQOpWqJAUH5/w3kz/cOnSJV27dk3Fixc3FAbYNwYm4L9OXDmhJouaaFqTaapbtK7pHAAAkA5cuXLlvquSDh8+LHd398Qx6Y033pDValXBggVl4Y2HAQAAgOTxP+OSJM2ePVvbt2/X2rVrFRMTwy2ngf/BwARI+vPWn2q4oKFG1ByhVmVamc4BAABpTHx8vI4fP37PkBQSEqIrV66ofPny8vb2VpUqVdSjRw+VK1dOWbJkMZ0MAAAApFvx8fFycHBQxowZ1blzZ0mSw38HKJvNxolfwH8xMCHduxF1Q40XNlaHch3Uu3Jv0zkAACCVu3nzpkJDQ+8Zkw4cOKDcuXMnXpUUGBiojz76SMWKFUv8iyoAAAAAs2JiYnTt2jUdPXpUt27d0qxZs1SwYEGFhoZq//79WrVqFeMS8A8MTEjXouOi1WJpC1XMX1Gj64w2nQMAAFIRm82m06dP33eLu8jISJUpUyZxTOrQoYO8vLyUI0cO08kAAAAAHuHEiRPq16+f8ufPr0uXLmn//v0KCAhQ8eLFVbNmTcXHx8vR0dF0JmA3GJiQbsXb4vXqt68qa4asmtZkGmcfAACAh7p7964OHjyYeGu7ffv2KTQ0VBkzZkwcklq2bKl3331XpUqVkpMTh9kAAABAauPh4aFp06apePHimj9/vipXrqxBgwY98mu4ZR7SM/7mi3TJZrNp4MaBirwRqY2dNsrRgTMPAABAwjHC+fPn77sq6cSJEypZsmTimNS0aVNZrVY9//zzppMBAAAAJIG/h6IiRYpIknbt2qXChQtLSrh1nrOz8wO/7tatW7yHKtItBiakS5N2TdLWk1u1vct2uTq5ms4BAAAGxMTE6MiRI4kj0t9XJsXFxclqtcrb21sNGzbUkCFD5OnpKRcXF9PJAAAAAJLJ31ch/X0LvBIlSqh69eqS9NBxKTw8XD179tSwYcNUt27dlAkF7AgDE9KdOb/P0Yy9M7Sr6y7lcM1hOgcAAKSAv/76676rkv744w8VKlQo8aqkAQMGyGq1ys3NjVtcAAAAAOnUjRs3lDVrVr311lu6e/fuI5+bKVMmVaxYUa+++qp+/vln5c+fP4UqAfvAwIR0Ze3RtQraGqQfAn9QgawFTOcAAIAkFhcXp7CwsPvGpGvXrsnLy0tWq1XVq1dXnz59VK5cOWXKlMl0MgAAAAA7snnzZu3du1fjxo2Tq6ur4uPj5eDg8MDnXrp0SU5OTqpSpYpcXblLEtIfBiakGz+e+VFdV3XV2g5r5fGch+kcAADwjG7cuKHQ0NDEW9vt27dPBw8e1PPPP594VVK3bt1ktVpVpEiRh/6lEAAAAAD+1rx5cy1dulTTp09X79695eDgoNjYWDk5OSW+T1N0dLQOHDig6dOny8nJSbNnz1aWLFkSPw+kFwxMSBcOXTyk5kuaa17zeXrR7UXTOQAA4AnYbDaFh4ffd1XS+fPnVbZs2cQxKSAgQOXLl1f27NlNJwMAAABIpSwWixYsWKBmzZopV65catu2rZycEl5G37NnjypXrqzdu3dr+vTpyp8/vyZNmiSLxfLIK52AtIqBCWnemWtn5LPARx++8qF8SviYzgEAAI9w584dHThwQPv27Uu8Mik0NFRZsmSRt7e3rFar2rZtq/Hjx6tkyZKJb8ALAAAAAEnFyclJy5cvV5UqVVSuXDmVLVtW58+fV5s2bdSuXTtduHBBJUuW1KhRoySJcQnpFgMT0rTLdy6r4YKGGlB1gDp5dTKdAwAA/stms+ns2bP3XZUUHh4uDw+PxKuSmjdvLqvVqueee850MgAAAIB0xNXVVT///LMyZswoScqXL58WLFigRo0aqW3btoxLgBiYkFrdvSuFh0vXrkkxMZKzs5Q9u1S0qOTiIkm6HXNbTRc3lW8pXw2sNtBsLwAA6Vh0dLQOHz58z5AUEhIii8Uiq9Uqb29vNWnSREFBQSpdurQyZMhgOhkAAAAAEseluLg4WSwWVa9eXbNnz9YHH3ygmzdvKkuWLIxLSNcYmJC6XL4sHT4snT+f8HF8/P9/ztFROnhQypdPsR6l1HZzVxXPWVwTX55ophUAgGfxGCdT2KOLFy/ed1XS0aNHVbRo0cSrkgYNGiSr1ar8+fPzBrgAAAAA7N7ft+a22Wxq1aqVvL29zQYBdoKBCalHWJgUGirFxT348/993Hb2rOLOntYrKqFefpPkYOEsAgBAKvKYJ1PI01PKlctMoxLO4Dt69Oh9Y9KtW7fk5eUlq9WqWrVqqV+/fipbtmzimX8AAAAAkFr9fYJciRIl7v/k3bsJJwbyPrFIRxiYkDr827j0DxZJLnLSGy41ZDl5SnrQ/+EDAGCPHvNkCp09K124IHl5pcifc9euXVNoaKhCQkISh6RDhw4pf/78iVcl9ezZU1arVYULF+aqJAAAAADpi80mzZiRcELgzJkSfydCOsHABPt3+fJjj0tvzZunVXv26PzVq3LLlUtBLVsqYPRoo2d4AwDwWJ7gZApJCc8LDU34eRKNTPHx8Tp58uR9VyVdvHhR5cqVk9VqVYUKFdSlSxeVL19e2bJlS5JfFwAAAABSNYtF6tZNqltXGjVKevdd00VAimBggv07fPixX2zL7OqqNUOHqlT+/Np9/Lh8xo9XibJl9VLPnskcCQDAM3iCkynu8ffIlCvXE59McevWLR04cCBxRAoJCdH+/fuVPXt2eXt7y2q1qmPHjpo0aZKKFy+eeM9xAAAAAMADZM0qrV8vVa+ecFvzPn1MFwHJjoEJduv48eOqXLmytgwfrgpFiujs5cuyDh6sZQMHqk7Zsg/8mnfatEn8eZWSJVWzdGn99OOPeunVV+36DdEBAOncE5xM8eZXX2nW1q26efeusmfKpKtffSUdOSK99NIDn2+z2RQREXHfVUlnzpxR6dKlE29x16pVK1mtVuXiql8AAAAAeDrPPy9t3CjVrJnw81atTBcByYqBCXarePHiem/AAHWaMkV7JkxQl+nTFVi79kPHpf91Jzpau48fV59GjaTwcMnDI3mDAQB4GnfvSufPP/bT8+fIodfq1dO+U6f028mTCQ+eOydFRSlK0qFDh+4bk5ycnBKHJH9/f40cOVIeHh5ydnZOnt8TAAAAAKRXxYpJ69ZJr7wi5c6dcNs8II1yMB0APEr3hg1VIm9eVQkK0rkrVzSuffvH/tpeM2fKWriwGpYvL129mnyRAAA8pa1bt8ohUyYt3L5dkvTbiRNyaNtWn6xb99CvGdKsmT5+9VUVzJ078bGo6Gh92LevcuTIoc6dO2vz5s3Knz+/hg4dqoMHD+rChQvatGmT3n//fXXs2FHlypVjXAIAAACA5OLtLS1ZIrVtK4WEmK4Bkg1XMMG+xcSoe/368ps0STN79JDLY74YNnj+fB04c0bfjxoli8UixcQkcygAAE+uXr166tSwobpOm6aGXl56ZexYVShaVAOaNHmi7+Pi5KRXmzfX61OmyNXVNZlqAQAAAACPrW5d6bPPpCZNpJ07paJFTRcBSY4rmGDXbsbEaMDcuepWr55GL1umyzdv/uvXjFq6VMEhIdo0YoSyZcqU8CBnaQMA7NS8//xHOTNnlnvv3roVFaWtI0c+1ffJnTUr4xIAAAAA2JPWraWgIKlhQ+nPP03XAEmOgQl2rf+nn6pS8eKa1auXmlSooF4zZz7y+RNWrtSinTu15e23lTtr1oQHHR2lHDmSPxYAgKfh7Kzu9esrKiZGratW/f+TI57i+wAAAAAA7MzrryfcKq9JE+kxTp4HUhMGJtitVatWacNPP2l69+6SpI8CA/XbyZNauGPHQ78maPFinb50SSX69lWWzp2VpXNnjV++XCpSJIWqAQB4MuejozVx1SqVyp9fC3fu1PHz55/4e8RbLLJlz54MdQAAAACAZ/buuwnvy9SypRQdbboGSDK8BxPslr+/v/z9/aVdu6SzZ5XF1VVhU6c+8mtsS5fe/6Cbm+TikkyVAAA8m1pduyp/jhz6Y/JkeQ4YoDqjR+vMjBkPfX50bKxu372rmLg42Ww2Xb15U/E2m5oFBsqvdWt16NBBBQoUSMHfAQAAAADgkSwWafr0hIGpSxdp/nzJgWs/kPrxv2LYP0/PhNvcPQ1HR6l06aTtAQAgiQQFBen4iRP6fto0SdL3o0fr/LVr6jNr1kO/ps+sWcrZtasW79ql63fuKGfXrnpx5EiNff99HTlyROXKlZOPj48WLVqk27dvp9RvBQAAAADwKE5O0tdfS6dOSW+9JdlspouAZ2axPeJ/yJUqVbLt2bMnBXOAB9v/47cqfuamMjm4KEvnzg98TnBQkGp6ev7/A46OkpeXVKJEClUCgDkWi2WvzWarZLojvXvqY6fLl6UffpDi4p78ax0dpTp1pFy5JEm3b9/WqlWrNG/ePP38889q0aKFAgICVLNmTTlwhhwAABw32RFedwKQLl2+LNWqJQUGSoMHm64B/tWjjp24RR7s3u7I3Wq8q7t+qbtIxU7f0M358//9ixiXAACpSa5cCX9uhYY+2cj09593/x2XJClTpkxq37692rdvr3PnzmnRokXq27evbty4oc6dO6tz584qWbJkMvwmAAAAAAD/KlcuacMGqXp1KW9eKSDAdBHw1BiYYNfCLofJ72s/zfabrWIeDaRil6UjR6Rz5xLuXfrPF+EcHRMuLc2fP+G2eP94sQ0AALv390kRoaGytGz5wKdM7dpVb/j4JHzwGCdT5M+fX4MGDdLAgQO1b98+zZs3TzVr1lSxYsUUEBCgNm3aKBd/XgIAAABAynJ3TxiZ6taV8uSRGjUyXQQ8FQYm2K0/b/0pnwU+Gl17tJp6NE14MFcu6aWXpKgoKTxcunpViomRnJ2lHDmkIkUkFxdz0QAAPIsSJaRcuWTbtStJT6awWCzy9vaWt7e3Jk2apE2bNmnu3LkaOnSoGjRooMDAQPn4+MjZ2TmZfmMAAAAAgHt4ekorV0p+ftLatVKVKqaLgCfGwAS7dCv6lnwX+ap9ufbqWann/U9wcZE8PFI+DACA5JbMJ1M4OTmpcePGaty4sa5evaply5Zp0qRJ6tatm9q3b6+AgABVqFBBFosliX5DAAAAAIAHqlZNmjNH8veXtm3j9U6kOrzTM+xObHys2ixvo7LPl9W7dd81nQMAgBl/n0xRpYpUo0bCf3p4JOmVujly5FD37t21Y8cO/fTTT8qZM6dat26t8uXLa9KkSYqMjEyyXwsAAAAA8AC+vtKECVLDhhJ/B0Mqw8AEu2Kz2dR7bW/F2+I103cmZ08DAJBCihcvrtGjR+v48eOaMWOGwsLCVL58eb3yyitauHChbt26ZToRAAAAANKmLl2kXr0kH5+Eu1gAqQQDE+zKu9ve1e/nf9ey1svk7Mj7QAAAkNIsFotq1KihmTNnKjIyUt26ddOiRYvk7u6uLl266Pvvv1d8fLzpTAAAAABIW4YOlerVS3hPpjt3TNcAj4WBCXbjy9++1Nx9c7WuwzplyZDFdA4AAOlexowZ1bZtW61bt06HDx+Wl5eX3nzzTRUtWlT/+c9/9Mcff5hOBAAAAIC0wWKRPv5YKlBA6thRioszXQT8KwYm2IX1x9ZrxPcjtKHTBuXNktd0DgAA+B/58uXTm2++qZCQEK1evVpRUVGqU6eOqlatqmnTpumvv/4ynQgAAAAAqZuDgzR3rnT9utSnj2SzmS4CHomBCcbtjtytwG8DtbLtSpXKXcp0DgAA+BdWq1UffPCBzpw5o1GjRmnHjh0qXry4WrZsqVWrVik6Otp0IgAAAACkTi4u0ooV0u7d0jvvmK4BHomBCUYdv3xc/l/760u/L1XVvarpHAAA8AScnJzUqFEjLV68WKdOnVLjxo310Ucfyc3NTX379tWePXtk44w7AAAAAHgy2bJJwcHSggXSjBmma4CHYmCCMRdvXZTPQh+Nqj1Kfh5+pnMAAMAzyJ49u7p166Zt27bpl19+UZ48edSuXTuVLVtWEydO1JkzZ0wnAgAAAEDqkTevtHGj9O67CVc0AXaIgQlG3Iq+Jd/FvmpXtp16VuppOgcAACShYsWKaeTIkTp27JhmzZqlkydPytvbWy+//LLmz5+vmzdvmk4EAAAAAPtXvLi0dq3Uq5e0bZvpGuA+DExIcbHxsWq7vK3K5Cmjd+u+azoHAAAkE4vFopdeekmff/65IiMj1bNnTy1dulQFCxZUYGCgvvvuO8XFxZnOBAAAAAD7VaGCtGiR1Lq1FBpquga4BwMTUpTNZlOfdX0UGx+rmb4zZbFYTCcBAIAU4OrqqtatW2vNmjX6448/9MILL2jw4MEqUqSIgoKCdOTIEdOJAAAAAGCfXn5ZmjpVatxYCg83XQMkYmBCihqzfYz2ntur5W2Wy9nR2XQOAAAw4Pnnn9eAAQP022+/af369YqNjVW9evX04osv6tNPP9WlS5dMJwIAAACAfWnbVhoyRGrYUOLvTLATDExIMbN/n625++ZqXYd1ypIhi+kcAABgB8qXL69JkybpzJkzGjNmjH766SeVKFFCzZs318qVKxUVFWU6EQAAAADsQ79+UsuWUpMm0q1bpmsABiakjPXH1ivouyAFdwxWviz5TOcAAAA74+joqIYNG2rhwoU6ffq0/Pz8NHnyZLm5uen111/Xr7/+KpvNZjoTAAAAAMwaN04qW1Zq1UqKiTFdg3SOgQnJbnfkbr367av6tt23KpW7lOkcAABg57Jly6YuXbrohx9+0J49e5Q/f3516tRJnp6eGj9+vE6fPm06EQAAAADMsFikmTMlJyepWzcpPt50EdIxBiYkq+OXj8v/a3/N8pulqu5VTecAAIBUpkiRIhoxYoT++OMPffXVVzpz5oxeeOEF1atXT3PnztWNGzdMJwIAAABAynJykpYskcLCpGHDTNcgHWNgQrK5eOuifBb6aFTtUfLz8DOdAwAAUjGLxaKqVatq+vTpOnv2rF5//XWtWLFCBQsWVOfOnbV582bFxcWZzgQAAACAlJEpk7RmjbR2rfTRR6ZrkE4xMCFZ3Iq+Jd/Fvmpbtq16VuppOgcAAKQhLi4uatmypVatWqVjx46pcuXKGj58uAoXLqxhw4bp0KFDphMBAAAAIPnlzi1t3Ch98om0cKHpGqRDDExIcrHxsWr3TTt5PuepMXXHmM4BAABpWJ48edSvXz/t2bNHGzdulCS98sorqlSpkqZMmaKLFy8aLgQAAACAZFSwoBQcLA0cmDA2ASmIgQlJymazqc+6PoqJi9EXTb+QxWIxnQQAANKJsmXLauLEiTp16pQmTJig3bt3q2TJkvL399c333yjqKgo04kAAAAAkPTKlpVWrJA6dZJ27zZdg3SEgQlJauz2sdp7bq+WtV4mZ0dn0zkAACAdcnR0VIMGDTR//nydOXNGLVq00GeffSY3Nzf17t1bP//8s2w2m+lMAAAAAEg61atLX34p+flJR4+arkE6wcCEJDP799maEzJH6zqsU1aXrKZzAAAAlDVrVgUGBmrr1q3au3evChYsqMDAQHl4eGjs2LEKDw83nQgAAAAAScPPTxozRvLxkc6dM12DdICBCUki+Fiwgr4LUnDHYOXLks90DgAAwH0KFy6soKAgHTlyRAsWLNC5c+dUqVIl1a1bV3PmzNH169dNJwIAAADAs3ntNalbN6lRI+naNdM1SOMYmPDM9pzdo4BvA7Sy7Up5POdhOgcAAOCRLBaLXnzxRX322WeKjIxUv379tHr1ahUqVEgdO3bUxo0bFRcXZzoTAAAAAJ5OUJBUo4bUrJl0967pGqRhDEx4JscvH5ffYj/NajpL1QpWM50DAADwRFxcXNS8eXOtXLlSYWFhqlatmt5++20VKlRIQ4YM0YEDB0wnAgAAAMCTsVikyZOlPHmkTp0kTqBDMmFgwlO7eOuifBb6aGTtkfIv7W86BwAA4Jk899xzeuONN/Trr79qy5YtcnJyUqNGjVShQgV98skn+vPPP00nAgAAAMDjcXSU5s+XLl+W+vWTbDbTRUiDGJjwVG5F35LvYl+1LdtWvSr1Mp0DAACQpDw9PTV+/HiFh4fr/fff1++//65SpUqpadOmWrZsme5ymwkAAAAA9s7FRVq5UvrxR2nsWNM1SIOcTAcg9YmNj1W7b9rJ8zlPjak7xnQOAABAsnF0dFT9+vVVv3593bx5UytXrtTnn3+uXr16qXXr1goICFC1atVksVhMpwIAAADA/bJn17TvXlOMJVa6MvmZvpWznNUnZ58kCkNawBVMeCI2m0191vVRTFyMvmj6BS+mAACAdCNLlizq3LmztmzZopCQEBUpUkTdunVTyZIl9e677+rkyZOmEwEAAADgPjGW2KT5PopJku+DtIOBCU9k7Pax2ntur5a1XiZnR2fTOQAAAEYULFhQw4YN06FDh7R48WJdvHhRL774omrXrq0vv/xS165dM50IAAAAAECyYmDCY5vz+xzNCZmjdR3WKatLVtM5AAAAxlksFlWuXFlTp05VZGSkBg4cqHXr1qlw4cJq3769goODFRubNGcLAgAAAABgTxiY8FiCjwVr+HfDFdwxWPmy5DOdAwAAYHcyZMggf39/rVixQsePH1fNmjX1zjvvqGDBgnrrrbcUGhpqOhEAAABAOja16VT9NO8nSdLRbUc1vsp4DXYbrE/9PtXlM5cTn/f7yt/1ScNPNNhtsKY2nWoqF6kAAxP+1Z6zexT4baBWtl0pj+c8TOcAAADYvdy5c6tPnz76+eef9cMPP8jV1VVNmzaVt7e3Pv74Y50/f950IgAAAIB06uZfNzU7YLYaD2+s8cfHq6B3Qc3tOjfx85lyZlLtXrVVv399g5VIDRiY8EgnrpyQ32I/fdH0C1UrWM10DgAAQKrj4eGhsWPH6uTJk/r4448VGhoqT09PNWnSREuWLNGdO3dMJwIAAABIR0LXhCpf6XzybuYtZ1dn+Qz10dmDZ3Xh6AVJkkcdD73Q/AVlz5fdcCnsHQMTHurirYvyWeCjkbVHyr+0v+kcAACAVM3BwUF169bVnDlzFBERofbt2+vLL7+Um5ubevTooZ07d8pms5nOBAAAAJDGnT9yXgXKFUj82CWzi3IXya3zR7jTAp4MAxMe6HbMbTVd3FSty7RWr0q9TOcAAACkKZkzZ1anTp20adMm7d+/XyVKlFDPnj1VokQJjR49WsePHzedCAAAACCNiroVpYzZMt7zWMZsGXX35l1DRUitGJhwn9j4WLVb3k4ez3lobL2xpnMAAADSNDc3Nw0ZMkQHDhzQ0qVLdeXKFVWrVk01atTQF198oatXr5pOBAAAAJCGuGR20d0b945Jd2/clWsWV0NFSK0YmHAPm82m19e9rqi4KM1qOksWi8V0EgAAQLpgsVhUsWJFTZ48WZGRkRo6dKg2bdqkIkWKqG3btlq3bp1iY2NNZwIAAABI5fKVzqezB84mfhx1K0qXwi8pX+l8BquQGjEw4R7jdozT7rO7tbz1cjk7OpvOAQAASJecnZ3VtGlTLVu2TCdOnFDdunU1btw4ubu7a+DAgQoJCTGdCAAAACCV8vL10rnD57Rv9T7F3I3Rxvc3qkCZAspbKq8kKT4uXjF3YxQfFy9bvE0xd2MUFxNnuBr2iIEJieb8Pkezf5+t9R3XK6tLVtM5AAAAkJQrVy716tVLP/74o3bs2KHMmTOrWbNmslqt+vDDD3Xu3DnTiQAAAABSCYvFoizPZVGXuV20btw6BRUL0qm9pxTwZUDic3Yv2a3BBQZr2aBlOvHTCQ0uMFhfD/jaYDXslZPpANiH4GPBGv7dcG17dZvyZeFSSAAAAHtUsmRJjRkzRu+884527NihefPmqUyZMqpataoCAgLk7++vTJkymc4EAAAAYIeibkQpU66Evy941PFQ0C9BD3xelQ5VVKVDlZRMQyrFFUzQnrN7FPBtgFa2XSmP5zxM5wAAAOBfODg4qHbt2vryyy8VGRmpzp07a+7cuXJ3d9drr72m7du3Kz4+3nQmAAAAADtx7vA5XTh6Qe5e7qZTkIYwMKVzJ66ckN9iP33R9AtVK1jNdA4AAACeUKZMmdShQwdt2LBBBw4cUOnSpfX666+rePHiGjlypI4dO2Y6EQAAAIBBq0ev1oxWM+Q7yle5CuYynYM0hIEpHbt466J8Fvjo7Vpvq1npZqZzAAAA8IwKFCigt956S6GhoVqxYoVu3LihGjVqqHr16vr888915coV04kAAAAAUpjfaD+9c/Ad1e5Z23QK0hgGpnTqdsxtNV3cVK3LtFbvyr1N5wAAACAJWSwWvfDCC/r4448VERGhoKAgfffddypSpIhat26ttWvXKiYmxnQmAAAAACAVY2BKh2LjY9VueTt5POehsfXGms4BAABAMnJ2dlaTJk20dOlShYeHq0GDBpo4caLc3d01YMAA/fbbb7LZbKYzAQAAACQTZzknzfe5GSUdPZok3wtpg5PpAKQsm82m19e9rqi4KM1qOksWi8V0EgAAAFJIzpw51aNHD/Xo0UNhYWGaP3++WrZsqcyZMyswMFAdO3ZUgQIFTGcCAAAASEJ9cvZJmm+0crb0TgNpxw6pUKGk+Z5I1biCKZ0Zt2Ocdp/dreWtl8vZMWmWawAAAKQ+JUqU0DvvvKPjx49r+vTpOnr0qMqVK6eGDRtq4cKFunXrlulEAAAAAPaka1fpzTell1+Wzp83XQM7wMCUjnwV8pVm/z5b6zuuV1aXrKZzAAAAYAccHBxUs2ZNffHFF4qMjFSXLl20cOFCubu7q2vXrvrhhx8UHx9vOhMAAACAPRgwQOrUSXrlFenyZdM1MIyBKZ3YELZBw7YMU3DHYOXLks90DgAAAOxQxowZ1a5dO61fv16HDh1SuXLl1L9/fxUtWlQjRozQUe63DgAAAODttxMGpkaNpBs3TNfAIAamdGDv2b0KWBmgFW1XyOM5D9M5AAAASAXy58+vgQMHat++fVq9erXu3LmjWrVqqVq1apo+fbouc7YiAAAAkD5ZLNL770tWq+TvL925Y7oIhjAwpXEnrpxQ08VNNbPpTL1U8CXTOQAAAEiFrFarPvzwQ0VEROjtt9/Wtm3bVLRoUbVs2VKrV69WdHS06UQAAAAAKclikaZPl/LmlVq3lmJiTBfBAAamNOzS7UvyWeCjEbVGqFnpZqZzAAAAkMo5OTmpcePG+vrrr3Xq1Ck1atRIH3zwgdzd3dWvXz/t2bNHNpvNdCYAAACAlODoKM2bJzk4SJ07S3FxpouQwhiY0qjbMbflu8hXrcq0Up/KfUznAAAAII3JkSOHXnvtNW3fvl0///yzcufOrbZt26pcuXJ67733FBERYToRAAAAQHJzdpaWLpUuXpR69ZI44SxdYWBKg2LjY9X+m/YqlbuUxtUbZzoHAAAAaVyxYsU0atQohYWFaebMmTpx4oSsVqsaNGig+fPn69atW6YTAQAAACQXV1dp1Spp/35p0CBGpnSEgSmNsdlsemP9G7oTc0ez/GbJYrGYTgIAAEA6YbFYVL16dX3++eeKiIhQ9+7dtWTJErm7u+vVV1/V1q1bFR8fbzoTAAAAQFLLkkVav1767jvp3XdN1yCFMDClMeN3jNcvkb/omzbfKINjBtM5AAAASKcyZsyoNm3aaO3atTpy5IisVqsGDRqkIkWKKCgoSEeOHDGdCAAAACAp5colbdokLVwoffyx6RqkAAamNOSrkK806/dZWt9hvbK6ZDWdAwAAAEiS8ubNqzfffFO///671q5dq5iYGNWrV09VqlTRZ599pr/++st0IgAAAICkkDevtGWLNHmyNGuW6RokMwamNGJj2EYN2zJMwR2DlT9rftM5AAAAwAN5eXnp/fff1+nTp/Xuu+9q165dKl68uJo3b65vv/1W0dHRphMBAAAAPItChaTNm6VRo6QlS0zXIBkxMKUStke8MVpUbJSGbB6ib9p8o9LPlU7BKgAAAODpODk5qWHDhlq0aJFOnz6tpk2b6pNPPpGbm5veeOMN/frrr488BgYAAABgx0qWlIKDpX79pHXrTNcgmTAwpRJ/n8kZGxt73+ccLA76tfuvql6oekpnAQAAAM8sW7Zs6tq1q3744Qf9+uuvyps3rzp27KgyZcpowoQJOnPmjOlEAAAAAE/Ky0tavVp69VXp++9N1yAZMDClAteuXVPnzp01ZMgQTZo0SdeuXbvn886OznJxcjFUBwAAACSdokWL6u2339bRo0c1e/ZsnT59Wt7e3qpfv77mzp2rmzdvmk4EAAAA8LiqVJGWLpXatJF++cV0DZIYA1Mq0KpVK3l4eKhixYo6dOiQYmJiTCcBAAAAycpisahatWqaPn26IiMj1bt3b33zzTdyd3dXQECAtmzZori4ONOZAAAAAP5N3brSnDmSn5+0f7/pGiQhBiY7N3HiRJUuXVpjxoxR27ZtFRYWpjFjxmjSpEnavHmz6TwAAAAg2bm6uqpVq1ZavXq1jh49qooVK2ro0KEqUqSIhg8frsOHD5tOBAAAAPAovr7SlCmSj4907JjpGiQRBiY717VrV3300UeSpJEjRypnzpxq0KCBcufOrcmTJ+v48eOGCwEAAICU8/zzz6t///7au3evgoODFR8fr5dfflmVK1fW1KlTdfHiRdOJAAAAAB6kbVvpnXekBg2k06dN1yAJMDDZMZvNpueff17Ozs6SJB8fHwUHB8vX11ctW7ZU9uzZuV0eAAAA0q1y5crpvffe0+nTpzVu3Dj98ssvKlmypJo1a6YVK1YoKirKdCIAAACAf3rtNal//4SR6cIF0zV4RgxMdsxisdzz8UsvvZT4cwcHBx05coQ3OQYAAEC65+joqFdeeUULFizQmTNn1KxZM3366adyc3NTnz599PPPP8tms5nOBAAAACBJb74ptW8vvfKKdOWK6Ro8AwamVOjQoUNq0qSJAgICVKlSJdM5AAAAgN3ImjWrXn31VW3dulV79+6Vm5ubAgMDVbp0aY0bN06nTp0ynQgAAABg1Cipfn2pcWOJiyhSLQYmO/RvZ1fu3LlTtWvXVv/+/R/r+QAAAEB6VLhwYf3nP//RkSNHNG/ePEVGRqpixYqqW7euvvrqK924ccN0IgAAAJA+WSzShx9K5cpJ/v7S3bumi/AUGJjsxF9//aVff/1Vx48fv+/WeP+rR48eGjt2bOLH//Z8AAAAID2zWCyqUqWKpk2bpsjISPXt21fffvutChYsqE6dOmnTpk2Ki4sznQkAAACkLxaLNGOGlCeP1KaNFBNjughPiIHJDly7dk0NGjTQ1KlTVb16dS1duvShz42NjU38+aVLl1IiDwAAAEgzXFxc1KJFC3377bc6duyYqlSpov/85z8qVKiQhg4dqoMHD5pOBAAAANIPR0dp3jwpPl4KDJQ48StVYWCyA61bt5a/v7/mz5+vWbNmaciQITp27NgDn+vk5CRJ+uijj7Rhw4aUzAQAAADSlDx58qhv377avXu3Nm/eLAcHBzVs2FAVK1bU5MmT9eeff5pOBAAAANK+DBmkZcukc+ekPn0k3hIm1WBgMuzs2bOqU6eOhg8fLkny9fVVnTp1dO3atfue+/d7LS1evFhbtmxR+/btU7QVAAAASKvKlCmjCRMm6NSpU3rvvfe0d+9elSpVSn5+flq+fLnuck94AAAAIPlkzCitXi2FhEhDhjAypRIMTIbly5dPnTt3lrOzc+KAlDVrVh06dEiSFBISooiICNlsNlksFm3ZskUzZszQypUr5ejoaDIdAAAASHMcHR318ssva968eYqIiFCrVq00ffp0ubm5qVevXvrpp58Sj9sBAAAAJKGsWaXgYGnDBmncONM1eAwMTIY5ODioYMGCslgsiX9RzZgxo27cuKHDhw+rZcuWunbtmiwWiyIiIvT2229r1apVcnFxMVwOAAAApG1ZsmRRQECAvvvuO/3+++8qXLiwunTpolKlSmnMmDEKDw83nQgAAACkLblySZs3S3PnSpMnm67Bv2BgMiQ2Nva+xxwcEv7rqFu3rrZt26ZevXppwoQJKlu2rCTJ3d1d69evV44cOVIyFQAAAEj3ChUqpOHDh+vw4cNatGiRLly4oMqVK6t27dqaPXu2rl+/bjoRAAAASBvy5ZO2bJE++kiaPdt0DR6BgSmFbd++XXfu3JGTk5Pi4uIe+Jzs2bNr+fLlatu2rdq0aSPp/wepnDlzplgrAAAAgHtZLBZVrlxZn376qSIjI/Xmm29q7dq1KlSokDp06KANGzY88GQyAAAAAE+gcOGEK5lGjJCWLTNdg4dgYEph8+bNU+HChXXmzBk5OjreNzLZbDaVKlVK69evV58+fRIfc3JyMpELAAAA4CEyZMigZs2aacWKFTp+/LiqV6+uUaNGqVChQho8eLD2799vOhEAAABIvUqVSnhPpjfekNavN12DB2BgSmGzZs1Snz59VKFCBe3evVuOjo6y2WyJ779ksVj03HPPycfHx3ApAAAAgMeVO3duvf766/rll1+0detWZciQQU2aNNELL7ygjz/+WBcuXDCdCAAAAKQ+Vqu0apUUGCht22a6Bv+DgSkF/T0ijR49WmPGjFH9+vW1atUqWSwWWSwWxcfHKz4+PvH5S5YskZQwOgEAAABIHUqXLq1x48YpPDxcH374ofbt26fSpUvL19dXS5cu1d27d00nAgAAAKlH1arS119LrVtLu3ebrsE/MDClIIvFkjgy9erVS4sWLVJAQIA+++wzSZKDg0Pi5z/++GOtXLnSWCsAAACAZ+Pg4KB69erpq6++UkREhNq1a6cvvvhCBQoUUI8ePbRr167E438AAAAAj1C/vvTll1LTptKBA6Zr8F8MTCns76uRbDabfH19tXXrVo0ZM0ajRo2SJDk6OmrRokXavn27Fi1aZDIVAAAAQBLJnDmzOnXqpM2bNys0NFTFixdX9+7dVaJECb3zzjs6ceKE6UQAAADAvjVtKn38sdSwoRQWZroGYmBKcf98r6X4+HhVrFhRv/76q4KDg7V3715t3rxZU6ZM0ddffy0HB/7rAQAAANIad3d3DR06VAcPHtTSpUv1119/qWrVqqpVq5ZmzZqla9eumU4EAAAA7FP79tKoUVKDBlJEhOmadI8FI4XdjL6pmLgYSQm3zIiPj1ehQoVUqVIl7d+/XydPnlRwcLBcXFwMlwIAAABIThaLRRUrVtSUKVMUERGht956Sxs2bFDhwoXVrl07rV+/XrGxsaYzAQAAAPvSo4f0xhvSyy9Lf/5puiZdY2BKQfP2zVPtr2rf85iDg4Nu3LihDBkyqEmTJurRo4dy5sxpqBAAAACACRkyZJCfn5+WL1+uEydOqHbt2hozZowKFiyoQYMGad++faYTAQAAAPsxaJDUpk3C7fKuXjVdk24xMKWQTcc3acjmIVrYYqGcHZ3v+VzWrFn1/vvvK0+ePIbqAAAAANiLXLlyqXfv3vrpp5+0bds2ZcyYUX5+frJarfrwww91/vx504kAAACAee+8I9WuLTVuLN28abomXWJgSgG/nftNnVZ00jdtvpFnHs8HPsfZ2fmBjwMAAABIv0qVKqWxY8fq5MmTmjx5sg4ePChPT081btxYX3/9te7cuWM6EQAAADDDYpE++kjy9JTef1+y2UwXpTsMTMns5JWTarq4qWb4zlD1QtVN5wAAAABIhRwcHFSnTh3Nnj1bkZGR6tSpk+bMmSM3Nzd1795dO3bsUHx8vOlMAAAAIGU5OEhffCEFBSUMTg9gY3hKNgxMyeiv23+p0cJGGl5juFp4tjCdAwAAACANyJQpkzp06KCNGzdq//79KlWqlHr37q0SJUpo1KhRCgsLM50IAAAApBwHB8nF5b6HDx48qH379snykOEJz46BKZncibmjpoubqlnpZnrjxTdM5wAAAABIg9zc3DR48GDt379fy5cv17Vr11S9enXVqFFDM2fO1FXe8BgAAADpzN9XLM2cOVMzZ86UJMXGxnIlUzJgYEoGcfFx6rCig4rlLKbx9cebzgEAAACQxlksFlWoUEGffPKJIiIiNGzYMG3evFmFCxdWmzZttHbtWsXExJjOBAAAAJLd31cs5cuXTw0aNJAkXb9+nSuZkoGT6YC0xmazqV9wP92IuqElrZbIwcKGBwAAACDlODs7y9fXV76+vrpy5YqWLl2qCRMmqFu3burQoYMCAgLk7e3NX7ABAACQpty5c0cRERH6448/dPbsWU2ZMkVWq1WrVq3S6dOntW7dOrm6uprOTFMYmJLYxJ0TtevMLm3vsl0ZHDOYzgEAAACQjuXMmVM9e/ZUz549dezYMS1YsEAtWrRQlixZFBgYqA4dOqhAgQKmMwEAAIBnFh4ergEDBsjT01Ph4eGKiopSz549VaRIEeXOnZtxKRkwMCWhefvm6fO9n+vHbj8qm0s20zkAAAAAkKhkyZJ65513NGrUKO3cuVPz5s1TuXLl9OKLLyogIEDNmjVTpkyZTGcCAAAAT8XT01NfffWV8ufPr0WLFql69epq3rz5A59rs9m4oj8JcP+2JLLp+CYN3jxYwR2DVSArZwACAAAAsE8ODg6qVauWZs2apYiICAUGBmr+/Plyc3NTt27dtG3bNsXHx5vOBAAAAJ5Ynjx5JEnr169PfA/SuLi4xM/bbDZJ//8+TXfv3k3hwrSFK5iSwO/nflenFZ20ou0KeebxNJ0DAAAAAI8lU6ZMat++vdq3b69z585p0aJF6tu3r65fv67OnTurc+fOKlWqlOlMAAAA4LE4OSVMHk2aNEk8jnV0dEz8vMVi0c2bN/XHH39o5syZioqKUsGCBTVmzBgjvakdVzA9o/Cr4fJd7KsZvjNUo1AN0zkAAAAA8FTy58+vQYMGad++ffr2229169Yt1apVSy+99JJmzJihy5cvm04EAAAAHunatWuSpPbt26t8+fL3ff7y5cuaN2+eFixYIGdnZ40aNUpr1qzRnDlzUjo1TWBgegZ/3f5LPgt8NLzGcLXwbGE6BwAAAACemcVikbe3tz766CNFRERoxIgR+uGHH1SsWDG1atVKa9asSbzdCAAAAGBPQkJC1LFjR0lShgwZEm+PZ7PZFB0drRUrVuj48eOqVq2aPv30UxUtWlQdOnTQlStXTGanWgxMT+lOzB01XdxU/h7+euPFN0znAAAAAECSc3JyUuPGjfX1118rPDxcDRs21KRJk+Tm5qb+/ftr7969ifexBwAAAEyrXbu2Spcurf79+0tKuD1eXFycLBaLbt++re+++06VK1dWmzZtJEk//vij1q9frxo1uDvZ02Bgegpx8XHqsKKDiuUspgkvTzCdAwAAAADJLkeOHOrevbt27Nihn376STlz5lTr1q1Vvnx5TZo0SZGRkaYTAQAAAL399tvKnDmzhg4dKun/34Np7ty5cnR0VLt27SRJv/zyi9auXavGjRvLy8uLE6eeAgPTE7LZbOoX3E83om5otv9sOVj4RwgAAAAgfSlevLhGjx6t48ePa8aMGQoLC1P58uX1yiuvaMGCBbp165bpRAAAAKRj48eP14ULF7RmzZrEx5ycnBJHpMWLF2v58uXKkCGDGjVqJFdXV1ksFlO5qZblUatcpUqVbHv27EnBHPs3cedEfX3ga23vsl3ZXLKZzgEAQJJksVj22my2SqY70juOnQCkZ3fu3NHq1as1b948/fjjj2rWrJkCAgJUu3ZtOThwYh7sB8dN9oNjJwBASqtTp46yZcumiIgIvfnmm6pSpYpKlSplOsuuPerYySmlY1Kz+fvma8aeGfqx24+MSwAAAADwDxkzZlTbtm3Vtm1bnT9/XosXL9bAgQN1+fJlderUSQEBAfLw8DCdCQAAgHQmPj5eNptNjo6O+v7773Xy5Em5u7srQ4YMptNSPU4je0ybj2/WW5vf0vqO61UgawHTOQAAAABgt/Lly6c333xTv//+u9asWaOoqCjVqVNHVatW1bRp0/TXX3+ZTgQAAEA64eDgIEdHR8XHx8tisahYsWLKkCGD4uPj//9JUVHSPz/GY2Fgegy/n/tdHVd01PLWy1UmTxnTOQAAAACQanh5eemDDz7QmTNnNHr0aO3YsUPFixdXy5YttWrVKkVHR5tOBAAAQDrwv7dtTvzYZpMiI6XmzROGJjw2BqZ/EX41XL6LfTW9yXTVLFzTdA4AAAAApEpOTk7y8fHR4sWLderUKTVu3FgfffSR3Nzc1LdvX+3evVuPeo9gAAAAIFlYLFKhQpKzs9S+vRQba7oo1WBgeoS/bv8lnwU+GlZ9mFqWaWk6BwAAAADShOzZs6tbt27atm2bfvnlF+XJk0ft27dX2bJlNXHiRJ05c8Z0IgAAANITJydp4ULpzh2pa1dul/eYGJge4k7MHfl97Sc/Dz/1rdLXdA4AAAAApEnFihXTyJEjdezYMc2aNUvh4eHy9vbWyy+/rHnz5unmzZumEwEAAJAeuLhI33wjhYdLffsm3DoPj8TA9ABx8XHqsKKDiuQoookvTzSdAwAAAABpnsVi0UsvvaQZM2YoMjJSPXv21LJly+Tu7q7AwEB99913iouLM50JAACAtCxTJmntWumXX6SgINM1do+B6X/YbDb1C+6n61HXNcd/jhws/CMCAAAAgJTk6uqq1q1ba82aNTp69KgqVKigwYMHq0iRIgoKCtLhw4dNJwIAACCtypZN2rBBWr1amjDBdI1dYz35H+/tek87z+zUijYrlMExg+kcAAAAAEjXnn/+efXv31+//fab1q9fr9jYWNWvX18vvviiPv30U126dMl0IgAAANKa556TNm+WvvxS+uwz0zV2i4HpH+bvm68Ze2YouGOwsrtmN50DAAAAAPiH8uXLa9KkSTpz5ozGjBmjn376SSVKlFCzZs20cuVKRUVFmU4EAABAWlGgQMLINHGiNG+e6Rq7xMD0X5uPb9Zbm9/S+o7rVSBrAdM5AAAAAICHcHR0VMOGDbVw4UKdPn1a/v7+mjJlitzc3PT666/rl19+kY03ZQYAAMCzKlpU2rRJGjpUWrHCdI3dYWCSFHI+RB1XdNTy1stVJk8Z0zkAAAAAgMeULVs2denSRd9//7327Nmj/Pnzq3PnzvL09NT48eN1+vRp04kAAABIzTw9pfXrpd69pY0bTdfYlXQ/MIVfDZfvIl9NazJNNQvXNJ0DAAAAAHhKRYoU0YgRI/THH3/oq6++UkREhCpUqKB69epp7ty5unHjhulEAAAApEYvvJBwBVOnTtLOnaZr7Ea6Hpgu37msRgsbaUj1IWpVppXpHAAAAABAErBYLKpataqmTZumyMhIvf7661qxYoUKFiyozp07a/PmzYqLizOdCQAAgNSkenVp0SKpRQvpt99M19iFdDsw3Ym5I7/Ffmpaqqn6VelnOgcAAAAAkAxcXFzUsmVLrVq1SseOHVPlypU1fPhwFSpUSEOHDtWhQ4dMJwIAACC1aNBA+vxzqUkTiePI9DkwxcXHqeOKjiqUvZAmvjzRdA4AAAAAIAXkyZNH/fr10549e7Rp0yZZLBa98sorqlSpkqZMmaKLFy+aTgQAAIC9a95cmjRJathQOnnSdI1R6W5gstls6r+hv65FXdMc/zlysKS7fwQAAAAAkO6VLVtWEydO1KlTpzRhwgTt3r1bJUuWlL+/v7755htFRUWZTgQAAIC96txZGj5cevllKTLSdI0x6W5dmbRrknac3qEVbVbIxcnFdA4AAAAAwCBHR0c1aNBA8+fP15kzZ9SiRQtNmzZNbm5u6t27t37++WfZbDbTmQAAALA3ffpIPXok3Dbv0iXTNUakq4FpQegCTdszTes7rFd21+ymcwAAAAAAdiRr1qwKDAzUd999p99++00FCxZUYGCgPDw8NHbsWIWHh5tOBAAAgD0ZOlRq1izhdnnXrpmuSXHpZmDacmKLBm0apOCOwXLL5mY6BwAAAABgxwoVKqSgoCAdOXJECxYs0Llz51SpUiXVqVNHs2fP1vXr100nAgAAwB6MGydVqyb5+kq3b5uuSVHpYmAKOR+iDt900PLWy1UmTxnTOQAAAACAVMJisejFF1/UZ599psjISPXv319r1qxRoUKF1LFjR23cuFFxcXGmMwEAAGCKxSJNmSIVKyY1by6lo/fyTPMD06mrp+S7yFfTmkxTzcI1TecAAAAAAFIpFxcXNW/eXCtXrlRYWJiqVaumt99+W4UKFdKQIUN04MAB04kAAAAwwcFB+vJLKUsWqUMHKTbWdFGKSNMD0+U7l+Wz0EdDqg9RqzKtTOcAAAAAANKI5557Tm+88YZ+/fVXbdmyRU5OTmrUqJEqVKigTz75RH/++afpRAAAAKQkJydp0SLp5k3ptdek+HjTRckuzQ5Md2LuyG+xn3xL+qpflX6mcwAAAAAAaZSnp6fGjx+v8PBwvf/++/r9999VqlQpNW3aVMuWLdPdu3dNJwIAACAluLhIK1ZIYWFS//6SzWa6KFmlyYEpLj5OnVZ2UqHshfReg/dM5wAAAAAA0gFHR0fVr19fc+fOVUREhNq0aaPPP/9cbm5u6tmzp3788UfZ0viLDAAAAOle5szSunXSjz9KI0aYrklWaW5gstlsGrBhgK7cuaI5/nPkYElzv0UAAAAAgJ3LkiWLOnfurC1btigkJERFixZVt27dVLJkSb377rs6efKk6UQAAAAkl+zZpQ0bpJUrpffS7kUwaW59ef/H97Xt1DatbLtSLk4upnMAAAAAAOlcwYIFNWzYMB06dEhff/21Ll68qBdffFG1atXSl19+qWvXrplOBAAAQFLLk0favFn6/HNp2jTTNckiTQ1MC0MX6rPdnym4Y7Cyu2Y3nQMAAAAAQCKLxaJKlSpp6tSpioyM1KBBg7R+/XoVLlxY7du3V3BwsGJjY01nAgAAIKm4uUlbtkjjx0sLFpiuSXJpZmDacmKLBm4aqPUd1sstm5vpHAAAAAAAHipDhgzy9/fXN998o+PHj6tmzZp65513VLBgQb311lsKDQ01nQgAAICkUKyYtGmTNHiw9O23pmuSVJoYmELOh6jDNx20rPUylX2+rOkcAAAAAAAeW+7cudWnTx/9/PPP+uGHH+Tq6qqmTZvK29tbH330kc6fP286EQAAAM+iTBlp7VqpR4+E2+alEal+YDp19ZR8F/nqs8afqVbhWqZzAAAAAAB4ah4eHho7dqxOnjypjz/+WPv375enp6eaNGmiJUuW6M6dO6YTAQAA8DQqVpS++Ubq0EHatct0TZJI1QPT5TuX5bPQR4NfGqzWZVubzgEAAAAAIEk4ODiobt26mjNnjiIiItShQwd9+eWXcnNzU/fu3bVz507ZbDbTmQAAAHgSNWsmvBdTixbS77+brnlmqXZguhNzR36L/eRb0lf9q/Y3nQMAAAAAQLLInDmzOnbsqE2bNmn//v0qWbKkevbsqRIlSmj06NE6fvy46UQAAAA8roYNpWnTpMaNpcOHTdc8k1Q5MMXFx6nTyk4qmL2g3mvwnukcAAAAAABShJubm4YMGaIDBw5o2bJlunLliqpVq6YaNWroiy++0NWrV00nAgAA4N+0bClNnCi98ooUHm665qmluoHJZrNpwIYBunLnir7y/0oOllT3WwAAAAAA4JlYLBZVqFBBkydPVmRkpIYOHapNmzapSJEiatu2rdatW6fY2FjTmQAAAHiYwEBp6FDp5Zels2dN1zyVVLfOvP/j+9p2aptWtl0pFycX0zkAAAAAABjl7Oyspk2batmyZTpx4oTq1q2rcePGyd3dXQMHDlRISAjv1wQAAGCP3nhD6tpVatBAunTJdM0TS1UD08LQhfps92cK7his7K7ZTecAAAAAAGBXcuXKpV69eunHH3/Ujh07lCVLFjVr1kxWq1UffPCBzp07ZzoRAAAA/zR8uNS0qeTjI12/brrmiaSagem7E99p4KaBWt9hvdyyuZnOAQAAAADArpUsWVLvvvuuTpw4oalTp+rw4cMqU6aMGjVqpMWLF+v27dumEwEAAGCxSBMmSC++mDA0paJjtFQxMO07v0/tv2mvZa2XqezzZU3nAAAAAACQajg4OKh27dr68ssvFRkZqYCAAM2bN0/u7u7q1q2btm/frvj4eNOZAAAA6ZfFIn36qVSokNSypRQdbbrosdj9wHTq6ik1WdREnzX+TLUK1zKdAwAAAABAqpUpUya1b99ewcHBOnDggDw9PfX666+rePHiGjlypI4dO2Y6EQAAIH1ycJDmzJFcXaWOHaXYWNNF/8quB6bLdy6r0cJGGvzSYLUu29p0DgAAAAAAaUaBAgX01ltvKTQ0VCtWrNCNGzdUo0YNVa9eXZ9//rmuXLliOhEAACB9cXKSvv5aunZN6t5dsvOrzO12YLobe1f+X/urccnG6l+1v+kcAAAAAADSJIvFohdeeEEff/yxIiIiFBQUpK1bt6po0aJq3bq11qxZo5iYGNOZAAAA6YOLi7RypXT0qPTmm5LNZrrooexyYIqLj1OnFZ3kns1dkxpMMp0DAAAAAEC64OzsrCZNmmjJkiU6efKkGjRooPfee0/u7u4aMGCAfvvtN9ns+EUOAACANCFzZmndOmn7dmnkSNM1D2V3A5PNZtObG9/U5TuX9ZX/V3Kw2F0iAAAAAABpXs6cOdWjRw/t3LlTu3btUo4cOdSqVSuVL19ekyZN0tmzZ00nAgAApF05ckibNknLl0vvv2+65oGcUvRXu3tXCg9PuH9gTIzk7Cxlzy4VLZpw2ZekD378QD+E/6DtXbbLxcklRfMAAADsxmMcNwEAkFJKlCih0aNHa9SoUdq5c6fmzZuncuXKqXLlygoICFCzZs2UOXPmx/5+065MU4ye/bZ7znJWn5x9nvn7AAAA2KU8eaTNmzVNixVzZfIzf7ukPnZKmYHp8mXp8GHp/PmEj//5xlSOjtLBg1K+fNrgfFqf7v5Uu7ruUg7XHCmSBgAAYFce87hJnp5SrlxmGgEA6ZbFYlHNmjVVs2ZNTZkyRatXr9bcuXP1xhtvqHnz5goICFCtWrXk4PDou5EkxbiUlN8HAADAbrm7K+ZKhiT5Vkl97JT8958LC5N++EE6ezbhBZJ/vkgiSXFxUny84s+eVa2TcfqpzgK5Z3NP9iwAAAC785jHTTp7NuF5YWEmKgEAkCRlzJhRbdu21fr163X48GGVK1dO/fv3V9GiRTVixAgdPXrUdCIAAACSUfIOTGFhUmhowoshjxGSycFFBU5c5MUSAACQ/jzBcZOkhOeFhnLcBACwC/ny5dPAgQO1b98+rV69Wnfu3FGtWrVUrVo1TZ8+XZcvXzadCAAAgCSWfAPT5ctP9iLJ3/5+sYSDTwAAkF5w3AQASEOsVqs+/PBDRUREaOTIkdq+fbuKFSumli1batWqVYqOjpYkDSsyTAt6L5AkbZ26VYPyDtKAXAM0vOhwnfjlROL3Wxm0UkMLDtWAXAM0rMgwI78nAAAAe7Tjix36sN6HGpRvkBa+vjDFf/3kG5gOH37sF0mGLFiggr17K1tgoAr36aPxy5ZJR44kWxoAAIBdeYLjpuu3b6tUv36ytGkjx7Zt5T9hAsdNAAC75OTkpEaNGmnx4sU6deqUGjVqpA8//FDu7vfeFv/CsQtaPWq1ar5WU+NPjNdzxZ7TjFYzEj+fLW82Ve1cVSVqlEjp3wIAAIBdy5YvmxoMaqAqHasY+fWTZ2C6e/f/35j6MXSrV09HPv5Y1+fO1Y9jx2rhzp1asXKlFBWVLHkAAAB24wmPmxqOG6cL167pxNSpWjVkiNbu3auxU6dy3AQAsGvZs2fXa6+9pu3bt+vnn3++53ObPtgkl8wuajaumTLlyKQeX/dQ9K1oHdp0SJJUv399NR/fXDncchgoBwAAsF/WplZ5NfFS5lyZjfz6ST4wHT9+XLny5dNvJxIuZz97+bLydOumHw4efOjXeBQooMyurv8fZbEo7MIFKTw8qfMAAADsxtatW+WQKZMWbt8uSfrtxAk5tG2rT9ate+jX/BoWpmHNmqlo3rzyrVhRL5UqpZlbtnDcBABINYoVK3bPx+cOn1MO9xyJH2fNk1VOGZx0bMexFC4DAADAk0jygal48eJ6r3dvdZo8WbejotRl+nQF1q6tOmXLPvLrJn77rbJ07iz3Xr10KypKHV56Sbp6NanzAAAA7Ea9evXUqWFDdZ02TZeuX9crY8eqQtGiGtCkyQOff/LCBcXbbGpasWLiYy+WLKk/r13juAkAkGrF3ImRaxbXex5zzOCo29duGyoCAADA43BKjm/avUkTrdm8WVWCgmSxWLR6yJB//ZphzZppqL+/QsLD9e3u3cqeKZMUE5MceQAAAHZj3n/+o00//ST33r1lkbR15MiHPvfPa9ckSe65ciU+lidbNsXGxWn1ihXyr1o1uXMBAEgSn1z+JPHnzhmdFXXr3lu9xsXEKVP2TClcBQAAgCeRPO/B5Oys7vXr68CZM+rr4yMXZ+fH+jKLxaIXihZVxgwZNGrpUukxvw4AACDV+u9xU1R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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "field = np.zeros((4, 2))\n", "edges = [[0, 1], [1, 2], [2, 3]]\n", "j1 = np.array([[0, 0], [0, 1]])\n", "interactions = [j1, j1, j1]\n", "model1 = inferlo.PairWiseFiniteModel.create(field, edges, interactions)\n", "\n", "fig = plt.figure(figsize=(30, 10))\n", "model1.draw_pairwise_graph(fig.add_subplot(1, 3, 1))\n", "\n", "model1.draw_factor_graph(fig.add_subplot(1, 3, 2))\n", "\n", "model2 = inferlo.NormalFactorGraphModel.from_model(model1) \n", "model2.draw_edge_variable_graph(fig.add_subplot(1, 3, 3))\n", "\n", "ax = fig.get_axes()\n", "ax[0].set_title('Pairwise graph')\n", "ax[1].set_title('Factor graph')\n", "ax[2].set_title('Edge-varable graph')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can define pairwise graph only for pairwise model and Normal Factor Graph only for NFG model. Factor graph is defined for any model. \n", "\n", "For this example we selected model which is both pairwise and NFG. In general, we wouldn't be able to convert pairwise model to NFG model without adding.\n", "\n", "This example demonstrates how factors and variables correspond to different elements of graph in different representations. In pairwise graph vertices are variables and edges are factors. In Normal Factor Graph vertices are factors and edges are variables. In factor graph vertices in one part are variables, and vertices in other part are factor.\n", "\n", "Note how things representing variables are always red, and things representing factors are always green." ] } ], "metadata": { "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 2 }