ztangent/inv_plan_from_scratch.ipynb

## inv_plan_from_scratch.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Inverse Planning from Scratch\n",
    "\n",
    "This tutorial explains how to use probabilistic programming to implement\n",
    "inverse planning for a simple gridworld agent. By modeling the agent as\n",
    "an *approximately rational planner* who takes efficient actions towards\n",
    "a goal, then inverting this generative process, inverse planning allows us\n",
    "to infer the agent's goal from their observed actions.\n",
    "\n",
    "We will see how to do this \"from scratch\", in the sense that we won't be using\n",
    "existing library code for planning or inverse planning. Instead we will\n",
    "implement everything using [Gen.jl](https://github.com/probcomp/Gen.jl), a\n",
    "general-purpose probabilistic programming framework that allows us to write\n",
    "generative models and inference algorithms with minimal math.\n",
    "\n",
    "Specifically, we will cover the following material:\n",
    " - Modeling agents with probabilistic programs\n",
    " - Simulating and visualizing our agent model\n",
    " - Inferring goals via inverse planning\n",
    " - Online inverse planning via incremental computation\n",
    " - TODO: Extending the model with compositional goals\n",
    " - TODO: Scaling inference to compositional goal spaces\n",
    "\n",
    "## Modeling agents with probabilistic programs\n",
    "\n",
    "Inverse planning treats goal inference — and the inference of mental states\n",
    "more generally — as an inverse problem: Given a generative model of an agent's\n",
    "goal-directed actions (that is, a model where agent's actions are generated\n",
    "conditional on a latent goal), we want to invert the model, inferring the goal\n",
    "from the actions we observe.\n",
    "\n",
    "What does this model look like? At a high level, the model should specify:\n",
    "- $P(g)$, a prior distribution over possible goals $g$ (*Goal Prior*)\n",
    "- $P(a_t | s_t, g)$, a model of how the agent takes an action $a_t$ given\n",
    "  their goal $g$ and the current environment state $s_t$ (*Action Policy*)\n",
    "- $P(s_{t+1} | s_t, a_t)$, a model of how the environment changes in\n",
    "  response to the agent's action $a_t$ (*Environment Dynamics*)\n",
    "\n",
    "Together, these components define a joint distribution over the agent's goal,\n",
    "actions, and environment states up to any timestep $T$:\n",
    "\n",
    "$$\n",
    "P(g, a_{1:T}, s_{1:T}) = P(g_1) \\prod_{t=1}^T P(a_t | s_t, g) P(s_{t+1} | s_t, a_t)\n",
    "$$\n",
    "\n",
    "In this tutorial, we'll start with a simple goal prior $P(g)$ that is\n",
    "uniform over a set of possible goals $\\mathcal{G}$. For the environment\n",
    "dynamics $P(s_{t+1} | s_t, a_t)$, we'll model a deterministic gridworld\n",
    "where the agent's location changes based on their action (i.e. if the **up**\n",
    "action is taken, the agent moves up unless there is an obstacle in the way).\n",
    "\n",
    "But what about the action policy $P(a_t | s_t, g)$? A key assumption in\n",
    "inverse planning is that agents are *approximately rational*. In particular,\n",
    "agents are more likely to take actions that lead them efficiently towards\n",
    "their goals. To capture this assumption, we'll model the agent as following\n",
    "a *Boltzmann-rational policy*:\n",
    "\n",
    "$$\n",
    "P(a_t | s_t, g) = \\frac{\\exp(\\beta \\cdot Q_g(s_t, a_t))}{\\sum_{a' \\in A(s_t)} \\exp(\\beta \\cdot Q_g(s_t, a'))}\n",
    "$$\n",
    "\n",
    "Here, $Q_g(s_t, a_t)$ is the expected utility of taking action $a_t$ at\n",
    "state $s_t$ when the agent's goal is $g$, also known as the *Q-value*.\n",
    "The parameter $\\beta$ is called the *inverse temperature* or\n",
    "*rationality coefficient*, and controls how optimal (vs. random) the agent is.\n",
    "When $\\beta$ is higher, the policy assigns higher probabilities to actions\n",
    "with higher expected utilities. $A(s_t)$ is the set of possible actions\n",
    "at state $s_t$.\n",
    "\n",
    "### Writing an agent model probabilistic program\n",
    "\n",
    "We can now specify our generative model of an agent as a probabilistic program,\n",
    "which includes each of the components described above (setting aside for now\n",
    "how Q-values are computed):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Gen\n",
    "using Gen.Distributions: softmax\n",
    "\n",
    "\"Uniform distribution over a list of labels.\"\n",
    "@dist labeled_uniform(labels) = labels[uniform_discrete(1, length(labels))]\n",
    "\n",
    "\"Categorical distribution over a list of labels.\"\n",
    "@dist labeled_categorical(labels, probs) = labels[categorical(probs)]\n",
    "\n",
    "\"Return the next gridworld environment state given the current state and action.\"\n",
    "function gridworld_env_step(grid, loc, act)\n",
    "    # Return next location if in-bounds and not a wall\n",
    "    next_loc = loc .+ act\n",
    "    if checkbounds(Bool, grid, next_loc...) && !grid[next_loc...]\n",
    "        return next_loc\n",
    "    else\n",
    "        return loc\n",
    "    end\n",
    "end\n",
    "\n",
    "\"Boltzmann-rational agent model in a gridworld environment.\"\n",
    "@gen function gridworld_agent_model(T, grid, init_loc, goal_locs, beta)\n",
    "    # Sample goal from uniform goal prior P(g)\n",
    "    goal = {:goal} ~ labeled_uniform(goal_locs)\n",
    "    loc = init_loc\n",
    "    loc_history = [loc]\n",
    "    act_history = Tuple{Int, Int}[]\n",
    "    # Iterate over timesteps\n",
    "    for t in 1:T\n",
    "        # Compute Q-values and Boltzmann action probabilities\n",
    "        actions, q_values = compute_q_values(grid, loc, goal)\n",
    "        act_probs = softmax(beta .* q_values)\n",
    "        # Sample action according to Boltzmann policy P(a_t | s_t, g)\n",
    "        act = {(:act, t)} ~ labeled_categorical(actions, act_probs)\n",
    "        # Update location following environment dynamics P(s_{t+1} | s_t, a_t)\n",
    "        loc = gridworld_env_step(grid, loc, act)\n",
    "        push!(loc_history, loc)\n",
    "        push!(act_history, act)\n",
    "    end\n",
    "    return goal, loc_history, act_history\n",
    "end;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Probabilistic programs are programs that make random choices during their\n",
    "execution, allowing us to specify generative models as code. When using\n",
    "Gen.jl, probabilistic programs look almost exactly like regular Julia functions,\n",
    "except they are annotated with the `@gen` macro at the start, and make random\n",
    "choices using the `~` operator. The `gridworld_agent_model` above makes random\n",
    "choices at two places: first, when sampling a goal $g$ frm a uniform prior\n",
    "$P(g)$ over goals:\n",
    "\n",
    "```julia\n",
    "goal = {:goal} ~ labeled_uniform(goal_locs)\n",
    "```\n",
    "\n",
    "and second, when sampling an action $a_t$ from a Boltzmann-rational policy\n",
    "$P(a_t | s_t, g)$:\n",
    "\n",
    "```julia\n",
    "act = {(:act, t)} ~ labeled_categorical(actions, act_probs)\n",
    "```\n",
    "\n",
    "Each of these random choices is associated with an *address*, which gives a\n",
    "unique name to the random variable being sampled. The result of the random\n",
    "choice can optionally be assigned to regular Julia variable. For example, when\n",
    "sampling the agent's action at step `t` of the for-loop, the sampled action\n",
    "is given the address `(:act, t)`, and is assigned to the local variable `act`.\n",
    "\n",
    "### Computing Q-values via planning\n",
    "\n",
    "To complete our probabilistic program, we need to specify how to compute the\n",
    "Q-values of each action via the `compute_q_values` function. To do this, let's\n",
    "first think about what $Q_g(s_t, a_t)$ represents: What is the expected utility\n",
    "of taking action $a_t$ at state $s_t$ when the agent's goal is $g$?\n",
    "\n",
    "In our simple gridworld, we assume that the agent wants to reach their goal $g$\n",
    "while minimizing the cost of the actions it takes to get there. So the expected\n",
    "utility of taking action $a_t$ is just the (negative) cost of action $a_t$\n",
    "itself, plus the expected utility of reaching $g$ from the next state $s_{t+1}$\n",
    "(denoted $V_g(s_{t+1})$). Recursively, we define $V_g(s_t)$ — also known as the\n",
    "*value function* or *cost-to-go function* — as the maximum expected utility\n",
    "(i.e. minimum expected cumulative cost) of taking any action from state $s_t$:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "Q_g(s_t, a_t) &= -C(a_t) + V_g(s_{t+1}) \\\\\n",
    "V_g(s_t) &= \\max_a Q_g(s_t, a)\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "Let's assume that cost of any action $C(a_t)$ is 1. Together with the fact that\n",
    "our environment is deterministic, these definitions imply that $V_g(s_t)$ is\n",
    "just the *length of the shortest path* from $s_t$ to $g$ (but negated).\n",
    "Correspondingly, $Q_g(s_t, a_t)$ is the length of the shortest path from $s_t$\n",
    "to $g$ that involves first taking action $a_t$. This means we can compute\n",
    "$Q_g(s_t, a_t)$ for each action $a_t$ via a path planning algorithm. In our\n",
    "simple gridworld, it is enough to use [Dijkstra's algorithm](https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Compute Q-values for each action given the current location and goal location.\"\n",
    "function compute_q_values(grid, loc, goal)\n",
    "    # Define list of possible actions (stay, up, down, left, right)\n",
    "    actions = ((0, 0), (-1, 0), (1, 0), (0, -1), (0, 1))\n",
    "    # Compute shortest path from each successor location to goal\n",
    "    q_values = zeros(length(actions))\n",
    "    for i in 1:length(actions)\n",
    "        next_loc = loc .+ actions[i]\n",
    "        if checkbounds(Bool, grid, next_loc...) && !grid[next_loc...]\n",
    "            # Run Dijkstra's algorithm from next_loc to goal\n",
    "            q_values[i] = -shortest_path_length(grid, next_loc, goal) - 1\n",
    "        else\n",
    "            # Negative infinite Q-value if next_loc is unreachable\n",
    "            q_values[i] = -Inf\n",
    "        end\n",
    "    end\n",
    "    return actions, q_values\n",
    "end\n",
    "\n",
    "\"Compute the shortest path length from start to goal via Dijkstra's algorithm.\"\n",
    "function shortest_path_length(grid, start, goal)\n",
    "    # Initialize distances to infinity\n",
    "    distances = fill(Inf, size(grid))\n",
    "    distances[start...] = 0\n",
    "    # Initialize priority queue\n",
    "    queue = [(0, start)]\n",
    "    while !isempty(queue)\n",
    "        dist, loc = popfirst!(queue)\n",
    "        if loc == goal\n",
    "            return dist\n",
    "        end\n",
    "        for d in ((-1, 0), (1, 0), (0, -1), (0, 1))\n",
    "            next_loc = loc .+ d\n",
    "            if checkbounds(Bool, grid, next_loc...) && !grid[next_loc...]\n",
    "                alt = dist + 1\n",
    "                if alt < distances[next_loc...]\n",
    "                    distances[next_loc...] = alt\n",
    "                    push!(queue, (alt, next_loc))\n",
    "                end\n",
    "            end\n",
    "        end\n",
    "    end\n",
    "    return Inf\n",
    "end;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question**: The approach above is not the most efficient way of computing\n",
    "Q-values, since it requires invoking Dijkstra's algorithm for each action.\n",
    "Can you think of an approach that requires invoking Dijkstra's algorithm only\n",
    "once for all actions?\n",
    "\n",
    "## Simulating and visualizing our agent model\n",
    "\n",
    "With our model fully defined, we can now run `gridworld_agent_model` with\n",
    "specific arguments to generate a possible trajectory for our agent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "goal = (1, 5)\n",
      "loc_history = [(5, 3), (4, 3), (3, 3), (3, 4), (2, 4), (1, 4), (1, 5), (1, 5), (1, 5), (1, 5), (1, 5)]\n"
     ]
    }
   ],
   "source": [
    "grid = BitMatrix([ # 2D grid where 1s are walls\n",
    "    0 0 0 0 0\n",
    "    0 1 1 0 1\n",
    "    0 0 0 0 0\n",
    "    0 1 0 1 0\n",
    "    0 1 0 1 0\n",
    "])\n",
    "init_loc = (5, 3) # Initial location at row 5, column 3\n",
    "goal_locs = ((1, 2), (1, 5), (5, 1)) # 3 possible goal locations\n",
    "beta = 10.0 # Assume the agent is highly optimal\n",
    "T = 10 # Run the model for 10 timesteps\n",
    "goal, loc_history, act_history =\n",
    "    gridworld_agent_model(T, grid, init_loc, goal_locs, beta)\n",
    "@show goal;\n",
    "@show loc_history;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the agent starts from its initial location, then navigates the\n",
    "gridworld towards one of the three possible goals. The path the agent takes is\n",
    "highly optimal, due to `beta` being set to a high value. Once the agent reaches\n",
    "the goal, it stays in place.\n",
    "\n",
    "### Generating traces of probabilistic programs\n",
    "\n",
    "A key benefit of writing our model in a probabilistic programming language is\n",
    "that we can do more than just simulate executions of our model and collect\n",
    "their return values (as shown above). We can also *evaluate* the probability of\n",
    "a specific simulation, and run *constrained* simulations, where certain random\n",
    "variables are fixed to specific values. This can be done with the following\n",
    "functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "│\n",
      "├── (:act, 1) : (-1, 0)\n",
      "│\n",
      "├── (:act, 4) : (0, -1)\n",
      "│\n",
      "├── (:act, 3) : (0, -1)\n",
      "│\n",
      "├── (:act, 2) : (-1, 0)\n",
      "│\n",
      "├── :goal : (1, 2)\n",
      "│\n",
      "└── (:act, 5) : (-1, 0)\n",
      "logprob = -2.437251221207088\n",
      "\n",
      "Traced choices given constrained goal:\n",
      "│\n",
      "├── (:act, 1) : (-1, 0)\n",
      "│\n",
      "├── (:act, 4) : (0, -1)\n",
      "│\n",
      "├── (:act, 3) : (0, -1)\n",
      "│\n",
      "├── (:act, 2) : (-1, 0)\n",
      "│\n",
      "├── :goal : (1, 2)\n",
      "│\n",
      "└── (:act, 5) : (-1, 0)\n",
      "weight = -1.0986122886681098\n",
      "\n",
      "Traced choices given constrained actions:\n",
      "│\n",
      "├── (:act, 1) : (-1, 0)\n",
      "│\n",
      "├── (:act, 4) : (-1, 0)\n",
      "│\n",
      "├── (:act, 3) : (0, 1)\n",
      "│\n",
      "├── (:act, 2) : (-1, 0)\n",
      "│\n",
      "├── :goal : (1, 5)\n",
      "│\n",
      "└── (:act, 5) : (-1, 0)\n",
      "weight = -0.7301575864224461\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "-0.7301575864224461"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simulate an execution trace from our agent model\n",
    "model_args = (5, grid, init_loc, goal_locs, 2.0)\n",
    "trace = Gen.simulate(gridworld_agent_model, model_args)\n",
    "show(stdout, \"text/plain\", get_choices(trace)) # Show the choices in this trace\n",
    "\n",
    "# Evaluate the log-probability (a.k.a. score) of the sampled trace\n",
    "logprob = Gen.get_score(trace)\n",
    "@show logprob\n",
    "\n",
    "# Generate a trace with the goal constrained to a specific value\n",
    "goal_constraint = choicemap((:goal, (1, 2)))\n",
    "trace, weight = Gen.generate(gridworld_agent_model, model_args, goal_constraint)\n",
    "println(\"\\n\", \"Traced choices given constrained goal:\")\n",
    "show(stdout, \"text/plain\", get_choices(trace)) # Goal is fixed, other choices are sampled\n",
    "@show weight # Log-prob. of constrained choices given ancestors (= log P(g))\n",
    "\n",
    "# Generate trace with actions constrained to observed values\n",
    "act_constraints = choicemap(\n",
    "    ((:act, 1), (-1, 0)), ((:act, 2), (-1, 0)), ((:act, 3), (0, 1)),\n",
    "    ((:act, 4), (-1, 0)), ((:act, 5), (-1, 0))\n",
    ")\n",
    "trace, weight = Gen.generate(gridworld_agent_model, model_args, act_constraints)\n",
    "println(\"\\n\", \"Traced choices given constrained actions:\")\n",
    "show(stdout, \"text/plain\", get_choices(trace))  # Actions are fixed, other choices are sampled\n",
    "@show weight # Log-prob. of constrained choices given ancestors (= log P(a_{1:T} | g))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `simulate`, `get_score`, and `generate` functions are basic primitives that\n",
    "can be used to implement a wide variety of inference algorithms (MCMC,\n",
    "particle filtering, etc.). All of them operate over **traces**: a representation\n",
    "of an execution trace of a probabilistic program, which records all the random\n",
    "choices sampled along the way (exposed by `get_choices`), and also the joint\n",
    "probability of those choices (exposed by `get_score`).\n",
    "\n",
    "Most users of Gen can make use of higher-level interfaces that call these\n",
    "functions under-the-hood, but being familiar with concept of a trace is crucial\n",
    "to using Gen. We'll also see later how the `Gen.generate` function can be used\n",
    "to implement an inference algorithm via constrained generation and weighting\n",
    "of traces.\n",
    "\n",
    "### Visually inspecting our model\n",
    "\n",
    "While it is possible work with and inspect traces entirely in code, it is good\n",
    "practice to visualize our model and the traces it generates. Visualization\n",
    "can surface modeling errors that are otherwise hard to notice, whether at the\n",
    "level of individual traces, or in terms of the overall distribution of traces\n",
    "sampled from the model. Below we provide code to visualize our agent model\n",
    "using the [Makie](https://docs.makie.org/stable/) plotting libary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "anim_traces"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "using GLMakie\n",
    "using Printf\n",
    "using FileIO\n",
    "\n",
    "GLMakie.activate!(scalefactor=1.0)\n",
    "Makie.inline!(true)\n",
    "\n",
    "include(\"videodisplay.jl\")\n",
    "\n",
    "AGENT_IMG = rotr90(FileIO.load(joinpath(@__DIR__, \"images\", \"human.png\")))\n",
    "GOAL_COLORS = [\n",
    "    colorant\"#D41159\", colorant\"#FFC20A\", colorant\"#1A85FF\", colorant\"#007D68\",\n",
    "    colorant\"#785EF0\", colorant\"#D55E00\", colorant\"#56B4E9\", colorant\"#CC79A7\"\n",
    "]\n",
    "\n",
    "\"Render a trace of the gridworld agent model to an existing axis.\"\n",
    "function render_trace!(ax, trace::Union{Trace, Observable}, t = nothing)\n",
    "    # Wrap trace in Observable to enable interactive plotting\n",
    "    trace = trace isa Observable ? trace : Observable(trace)\n",
    "    t_obs = isnothing(t) ?\n",
    "        @lift(Gen.get_args($trace)[1]) :\n",
    "        t isa Observable ? t : Observable(t)\n",
    "    # Plot heatmap showing grid\n",
    "    grid_obs = @lift reverse(transpose(Gen.get_args($trace)[2]), dims=2)\n",
    "    cmap = cgrad([:transparent, :black])\n",
    "    heatmap!(ax, grid_obs, colormap=cmap, colorrange=(0, 1))\n",
    "    hidedecorations!(ax, grid=false)\n",
    "    map!(h -> (1:h-1) .+ 0.5, ax.yticks, @lift(size($grid_obs)[1]))\n",
    "    map!(w -> (1:w-1) .+ 0.5, ax.xticks, @lift(size($grid_obs)[2]))\n",
    "    # Render goal locations\n",
    "    goal_locs_obs = Observable([(1, 1)])\n",
    "    goal_colors = Observable(GOAL_COLORS[1:1])\n",
    "    scatter!(ax, goal_locs_obs, color=goal_colors, marker='♦',\n",
    "             markerspace=:data, markersize=1.0)\n",
    "    # Render agent trajectory\n",
    "    loc_history_obs = Observable([(1, 1)])\n",
    "    scatter!(ax, loc_history_obs, color=:black, marker='⦿',\n",
    "             markerspace=:data, markersize=0.4)\n",
    "    # Render current agent location\n",
    "    agent_x_bounds_obs = Observable((0.5, 1.5))\n",
    "    agent_y_bounds_obs = Observable((0.5, 1.5))\n",
    "    image!(ax, agent_x_bounds_obs, agent_y_bounds_obs, AGENT_IMG)\n",
    "    # Update observables with values from trace\n",
    "    onany(trace, t_obs) do trace, t\n",
    "        # Extract argument and return values\n",
    "        T, grid, init_loc, goal_locs, beta = Gen.get_args(trace)\n",
    "        retvals = Gen.get_retval(trace)\n",
    "        if length(retvals) == 2 # Handle Unfold-model variants\n",
    "            goal, model_states = retvals\n",
    "            loc_history = [s.loc for s in model_states]\n",
    "            pushfirst!(loc_history, init_loc)\n",
    "        else\n",
    "            goal, loc_history, act_history = retvals\n",
    "        end\n",
    "        h, w = size(grid)\n",
    "        # Clamp rendered timestep to [0, T]\n",
    "        t = max(0, min(T, t))\n",
    "        # Update goal locations\n",
    "        empty!(goal_locs_obs[])\n",
    "        append!(goal_locs_obs[], [(x, h-y+1) for (y, x) in goal_locs])\n",
    "        empty!(goal_colors[])\n",
    "        append!(goal_colors[], GOAL_COLORS[1:length(goal_locs)])\n",
    "        notify(goal_locs_obs)\n",
    "        notify(goal_colors)\n",
    "        # Update location history (flipping y and x coordinates)\n",
    "        empty!(loc_history_obs[])\n",
    "        append!(loc_history_obs[], [(x, h-y+1) for (y, x) in loc_history[1:t+1]])\n",
    "        notify(loc_history_obs)\n",
    "        # Update agent location bounds\n",
    "        cur_loc = loc_history[t+1]\n",
    "        agent_x_bounds_obs[] = (cur_loc[2] - 0.5, cur_loc[2] + 0.5)\n",
    "        agent_y_bounds_obs[] = (h - cur_loc[1] + 0.5, h - cur_loc[1] + 1.5)\n",
    "    end\n",
    "    notify(trace)\n",
    "    return ax\n",
    "end\n",
    "\n",
    "\"Render a trace of the gridworld agent model to a new figure.\"\n",
    "function render_trace(trace::Union{Trace, Observable}, t = nothing;\n",
    "                      size = (512, 512))\n",
    "    figure = Figure(size=size)\n",
    "    ax = Axis(figure[1, 1], aspect=DataAspect())\n",
    "    render_trace!(ax, trace, t)\n",
    "    return figure\n",
    "end\n",
    "\n",
    "\"Animate a trace of the gridworld agent model over time.\"\n",
    "function anim_trace(trace; size = (512, 512), kwargs...)\n",
    "    T = trace isa Observable ? Gen.get_args(trace[])[1] : Gen.get_args(trace)[1]\n",
    "    t_obs = Observable(0)\n",
    "    figure = render_trace(trace, t_obs; size=size)\n",
    "    anim = Record(figure, 0:T; kwargs...) do t\n",
    "        t_obs[] = t\n",
    "    end\n",
    "    return VideoDisplay(anim)\n",
    "end\n",
    "\n",
    "\"Render a collection of traces as a grid of subplots in a new figure.\"\n",
    "function render_traces(\n",
    "    traces::AbstractVector, ts = nothing;\n",
    "    n_rows = ceil(Int, sqrt(length(traces))),\n",
    "    n_cols = ceil(Int, length(traces) / n_rows),\n",
    "    size = (192 * n_cols, 192 * n_rows)\n",
    ")\n",
    "    figure = Figure(size=size)\n",
    "    for n in 1:length(traces)\n",
    "        i = div(n - 1, n_cols) + 1\n",
    "        j = mod(n - 1, n_cols) + 1\n",
    "        ax = Axis(figure[i, j], aspect=DataAspect())\n",
    "        t = ts isa AbstractArray ? ts[n] : ts\n",
    "        render_trace!(ax, traces[n], t)\n",
    "    end\n",
    "    return figure\n",
    "end\n",
    "\n",
    "\"Animate a collection of traces over time.\"\n",
    "function anim_traces(\n",
    "    traces::AbstractVector;\n",
    "    n_rows = ceil(Int, sqrt(length(traces))),\n",
    "    n_cols = ceil(Int, length(traces) / n_rows),\n",
    "    size = (192 * n_cols, 192 * n_rows),\n",
    "    kwargs...\n",
    ")\n",
    "    T = maximum(traces) do trace\n",
    "        trace isa Observable ? Gen.get_args(trace[])[1] : Gen.get_args(trace)[1]\n",
    "    end\n",
    "    t_obs = Observable(0)\n",
    "    figure = render_traces(traces, t_obs; n_rows, n_cols, size)\n",
    "    anim = Record(figure, 0:T; kwargs...) do t\n",
    "        t_obs[] = t\n",
    "    end\n",
    "    return VideoDisplay(anim)\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using this code, we can now visualize a single trace from our model:\n",
    "Specify arguments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\"/>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid = BitMatrix([ # 2D grid where 1s are walls\n",
    "    0 0 0 0 0 0 0 0\n",
    "    0 1 1 0 1 1 1 0\n",
    "    0 0 0 0 0 1 0 0\n",
    "    1 0 1 1 0 0 0 0\n",
    "    0 0 0 1 0 1 1 0\n",
    "    0 1 0 1 0 0 0 0\n",
    "    0 1 0 1 0 1 0 0\n",
    "    0 0 0 1 0 1 0 1\n",
    "])\n",
    "init_loc = (8, 7) # Initial location at row 5, column 3\n",
    "goal_locs = ((1, 1), (1, 5), (8, 2)) # 3 possible goal locations\n",
    "beta = 1.0 # Assume the agent is noisily rational\n",
    "T = 20 # Run the model for 20 timesteps\n",
    "model_args = (T, grid, init_loc, goal_locs, beta)\n",
    "\n",
    "# Simulate trace\n",
    "trace = Gen.simulate(gridworld_agent_model, model_args)\n",
    "\n",
    "# Visualize trace\n",
    "render_trace(trace)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also animate the trace over time (this allows us to more easily see\n",
    "actions when the agent randomly backtracks):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video controls autoplay muted>\n",
       "    <source 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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anim = anim_trace(trace, framerate=3, format=\"mp4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get a sense of the distribution over possible traces, we can also visualize\n",
    "multiple traces at once:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simulate 9 traces at random\n",
    "traces = [Gen.simulate(gridworld_agent_model, model_args) for _ in 1:9]\n",
    "# Animate all traces\n",
    "anim = anim_traces(traces, framerate=3, format=\"mp4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As can be seen, the agent tends to take actions that eventually lead it to\n",
    "towards one of the goals, though there is a fair amount of stopping and\n",
    "backtracking due to the randomness associated with Boltzmann rationality.\n",
    "We can see this randomness more clearly if we visualize the distribution of\n",
    "trajectories towards a specific goal (e.g. the red goal at (1, 1))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Constrain goal to specific value\n",
    "goal_constraint = choicemap((:goal, (1, 1)))\n",
    "# Generate 9 traces with constrained goal\n",
    "traces = [Gen.generate(gridworld_agent_model, model_args, goal_constraint)[1] for _ in 1:9]\n",
    "# Animate all traces\n",
    "anim = anim_traces(traces, framerate=3, format=\"mp4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the animation demonstrates, the agent may take many different, approximately\n",
    "optimal paths towards the same goal.\n",
    "\n",
    "## Inferring goals via inverse planning\n",
    "\n",
    "Now that we have visualized our model and checked that it produces reasonable\n",
    "forward predictions of agent actions, let's turn to the inverse problem:\n",
    "inferring the agent's goal from their actions. Suppose we observe the following\n",
    "sequence of actions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Specify observed actions as a choicemap\n",
    "actions = [\n",
    "    (-1, 0), (-1, 0), # Up twice\n",
    "    (0, -1), (0, -1), # Left twice\n",
    "    (-1, 0), (-1, 0), (-1, 0), # Up thrice\n",
    "    (0, -1), (-1, 0)  # Left, then up\n",
    "]\n",
    "observations = choicemap([((:act, t), a) for (t, a) in enumerate(actions)]...)\n",
    "\n",
    "# Visualize trace with observed actions\n",
    "T = length(actions)\n",
    "model_args = (T, grid, init_loc, goal_locs, beta)\n",
    "obs_trace, _ = Gen.generate(gridworld_agent_model, model_args, observations)\n",
    "anim = anim_trace(obs_trace, framerate=3, format=\"mp4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Which of the three goals do you think this agent is heading for? You've probably\n",
    "made some intuitive inferences at this point. With inverse planning, we can\n",
    "replicate such inferences. Given our agent model $P(g, a_{1:T}, s_{1:T})$, we\n",
    "wish to compute the posterior distribution $P(g | a_{1:T}, s_{1:T})$ over goals\n",
    "given actions $a_{1:T}$ and environment states $s_{1:T}$. This can be done via\n",
    "Bayes' rule:\n",
    "\n",
    "$$\n",
    "\\begin{align*}\n",
    "P(g | a_{1:T}, s_{1:T})\n",
    "&= \\frac{P(g) P(a_{1:T}, s_{1:T} | g)}{P(a_{1:T}, s_{1:T})} \\\\\n",
    "&= \\frac{P(g, a_{1:T}, s_{1:T})}{\\sum_{g' \\in \\mathcal{G}} P(g', a_{1:T}, s_{1:T})}\n",
    "\\end{align*}\n",
    "$$\n",
    "\n",
    "### Inference via enumeration with Gen.jl\n",
    "\n",
    "If we had not written our model as a probabilistic program, we would have to\n",
    "manually implement the math above. With Gen.jl, we can instead use the\n",
    "`enumerative_inference` algorithm, which computes both the numerator and\n",
    "denominator of Bayes' rule by enumerating over each possible goal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "goal = (1, 1)\tP(goal = (1, 1)) = 0.537\n",
      "goal = (1, 5)\tP(goal = (1, 5)) = 0.352\n",
      "goal = (8, 2)\tP(goal = (8, 2)) = 0.111\n",
      "log P(obs) = -4.906\n"
     ]
    }
   ],
   "source": [
    "# Specify latent choices (in this case, goals) to enumerate over\n",
    "choice_iter = choice_vol_grid((:goal, goal_locs))\n",
    "\n",
    "# Run enumerative inference given observations and the space of enumerated goals\n",
    "T = length(actions)\n",
    "beta = 1.0\n",
    "model_args = (T, grid, init_loc, goal_locs, beta)\n",
    "traces, log_posterior_probs, lml =\n",
    "    enumerative_inference(gridworld_agent_model, model_args,\n",
    "                          observations, choice_iter)\n",
    "\n",
    "# Display probability of each latent choice\n",
    "for (trace, log_p) in zip(traces, log_posterior_probs)\n",
    "    println(\"goal = \", trace[:goal], \"\\t\",\n",
    "            \"P(goal = $(trace[:goal])) = \", @sprintf(\"%.3f\", exp(log_p)))\n",
    "end\n",
    "\n",
    "# Display log marginal likelihood of observations (= log P(a_{1:T}, s_{1:T}))\n",
    "println(\"log P(obs) = \", @sprintf(\"%.3f\", lml))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also plot a bar chart next to our trace rendering to visualize the\n",
    "posterior distribution over goals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
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\"/>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "GLMakie.Screen(...)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"Plots bar chart of goal probabilities to an existing axis.\"\n",
    "function plot_goal_probs!(ax, goal_labels, goal_probs,\n",
    "                          goal_colors = GOAL_COLORS[1:length(goal_locs)])\n",
    "    n_goals = length(goal_labels)\n",
    "    barplot!(ax, 1:n_goals, goal_probs, color=goal_colors,\n",
    "             bar_labels = :y, label_formatter = s -> @sprintf(\"%.3f\", s))\n",
    "    ylims!(ax, 0.0, 1.0)\n",
    "    ax.xticks = (1:n_goals, [string(g) for g in goal_labels])\n",
    "    ax.xticklabelsize = 20\n",
    "    return ax\n",
    "end\n",
    "\n",
    "# Render trace and add new axis with goal probabilities\n",
    "figure = render_trace(obs_trace, size=(1024, 512))\n",
    "ax = Axis(figure[1, 2], title = \"P(goal | actions)\", titlesize = 24)\n",
    "goal_probs = exp.(log_posterior_probs)\n",
    "plot_goal_probs!(ax, goal_locs, goal_probs)\n",
    "display(figure)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The inferred goal probabilities here make intuitive sense. The agent appears to\n",
    "be heading towards either the red goal at (1, 1) or the yellow goal at (5, 1).\n",
    "However, the yellow goal is slightly less likely, since there is another path\n",
    "the agent could have taken to the right to reach the yellow goal. In contrast,\n",
    "most of the observed actions are part of *all* optimal paths from the start to\n",
    "the red goal. Finally, the fact that the agent moved up at the final step\n",
    "indicates that the blue goal at (8, 2) is unlikely.\n",
    "\n",
    "Recall that an important parameter in our Boltzmann-rational agent model is the\n",
    "rationality coefficient $\\beta$ (`beta`), which controls how optimal or noisy\n",
    "we assume the agent to be. Let's see what happens to our goal inferences when\n",
    "we compute them with different values of $\\beta$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
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\"/>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "GLMakie.Screen(...)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Render observed actions\n",
    "figure = render_trace(obs_trace, size=(512*4, 512))\n",
    "\n",
    "# Iterate over different values of beta and add plots\n",
    "betas = [0.5, 1.0, 2.0]\n",
    "for (i, beta) in enumerate(betas)\n",
    "    # Run enumerative inference with current beta\n",
    "    model_args = (T, grid, init_loc, goal_locs, beta)\n",
    "    traces, log_posterior_probs, lml =\n",
    "        enumerative_inference(gridworld_agent_model, model_args,\n",
    "                              observations, choice_iter)\n",
    "    # Add axis and bar chart of goal probabilities\n",
    "    ax = Axis(figure[1, i+1], titlesize = 24,\n",
    "              title = @sprintf(\"P(goal | actions; β = %.1f)\", beta))\n",
    "    goal_probs = exp.(log_posterior_probs)\n",
    "    plot_goal_probs!(ax, goal_locs, goal_probs)\n",
    "end\n",
    "display(figure)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the figure above shows, lower values of $\\beta$ result in more graded\n",
    "inferences, whereas higher values of $\\beta$ result in sharper inferences.\n",
    "This is because suboptimal trajectories to a particular goal have a much lower\n",
    "likelihood when $\\beta$ is high.\n",
    "\n",
    "**Question**: Which value of $\\beta$ leads to goal inferences that best\n",
    "correspond with your own intuitive inferences? Now go back and use that value\n",
    "of $\\beta$ to simulate forward predictions of thhe agent's actions. Does the\n",
    "$\\beta$ that best capture your goal inferences also capture your intuitions\n",
    "about how an agent acts over time?\n",
    "\n",
    "### Understanding enumerative inference\n",
    "\n",
    "Let's take a moment to understand how enumerative inference actually works in\n",
    "Gen.jl, since this is useful for appreciating how it differs from the more\n",
    "efficient algorithms we'll use later. Under-the-hood, enumerative inference\n",
    "works as follows:\n",
    "- Use `Gen.generate` method to generate traces consistent with both the\n",
    "  observations and each possible latent choice.\n",
    "- Call `Gen.get_score` to compute the log joint probability of each trace.\n",
    "  This gives us the (log.) numerator of Bayes' rule for each latent choice.\n",
    "- Summing the probabilities of each trace to get the denominator of Bayes' rule,\n",
    "  and then dividing to get the posterior probability of each latent choice.\n",
    "\n",
    "Here's how that looks in code for our agent model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "goal = (1, 1)\tP(goal = (1, 1)) = 0.537\n",
      "goal = (1, 5)\tP(goal = (1, 5)) = 0.352\n",
      "goal = (8, 2)\tP(goal = (8, 2)) = 0.111\n",
      "log P(obs) = -4.906\n"
     ]
    }
   ],
   "source": [
    "# Specify model arguments and latent choices to enumerate over\n",
    "model_args = (T, grid, init_loc, goal_locs, beta)\n",
    "latent_choices = [choicemap((:goal, g)) for g in goal_locs]\n",
    "\n",
    "# Iterate over traces and record joint probabilities\n",
    "traces = []\n",
    "log_joint_probs = Float64[]\n",
    "for choices in latent_choices\n",
    "    # Combine observation constraints (a_{1:T}) with latent choice (g)\n",
    "    constraints = merge(observations, choices)\n",
    "    # Generate trace constrained to current latent choice and observations\n",
    "    trace, log_weight =\n",
    "        Gen.generate(gridworld_agent_model, model_args, constraints)\n",
    "    # Compute log joint probability (= log P(g, a_{1:T}, s_{1:T})) of the trace\n",
    "    log_joint_prob = Gen.get_score(trace)\n",
    "    # (Note: We could also use `log_weight` directly, w/o calling `get_score`)\n",
    "    push!(traces, trace)\n",
    "    push!(log_joint_probs, log_joint_prob)\n",
    "end\n",
    "\n",
    "# Compute log. denominator of Bayes' rule (= log P(a_{1:T}, s_{1:T}))\n",
    "log_total_prob = logsumexp(log_joint_probs)\n",
    "# Compute log. posterior probabilities (= log P(g | a_{1:T}, s_{1:T}))\n",
    "log_posterior_probs = log_joint_probs .- log_total_prob\n",
    "\n",
    "# Display probability of each latent choice\n",
    "for (trace, log_p) in zip(traces, log_posterior_probs)\n",
    "    println(\"goal = \", trace[:goal], \"\\t\",\n",
    "            \"P(goal = $(trace[:goal])) = \", @sprintf(\"%.3f\", exp(log_p)))\n",
    "end\n",
    "\n",
    "# Display log marginal likelihood of observations (= log P(a_{1:T}, s_{1:T}))\n",
    "println(\"log P(obs) = \", @sprintf(\"%.3f\", log_total_prob))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that our manual implementation of enumerative inference gives the same\n",
    "results as the `enumerative_inference` function provided by Gen.jl.\n",
    "\n",
    "As the implementation above makes clear, enumerative inference requires a\n",
    "for-loop over *every* possible value of a latent variable. In other words, for\n",
    "inference over discrete latent variables, enumerative inference is an *exact*\n",
    "algorithm, since it computes Bayes' rule exactly. This is fine for small\n",
    "hypothesis spaces, but scales poorly as the number of possible values or\n",
    "latent variables increases. We'll see later on how to scale more efficiently\n",
    "by turning to approximate, *sampling-based* inference algorithms.\n",
    "\n",
    "Another limitation of enumerative inference — at least as we implemented it\n",
    "above — is that we need to rerun the whole algorithm every time we receive\n",
    "a new observation. This makes it inefficient for online goal inference.\n",
    "In the next section, we'll see how to avoid this problem via *incremental\n",
    "computation*.\n",
    "\n",
    "## Online inverse planning via incremental computation\n",
    "\n",
    "In many scenarios, we want to infer an agent's goal (and other mental states)\n",
    "from a stream of incoming observations, updating a posterior distribution over\n",
    "the agent's goal as we receive them. For example, this is important for\n",
    "collaborative robots or AI assistants that have to interact with a user in\n",
    "real-time. Such systems should continually update their inferences in order to\n",
    "guide their actions.\n",
    "\n",
    "A naive way to achieve online goal inference would be to run an inference\n",
    "algorithm on the entire set of observations each time a new observation arrives.\n",
    "Let's try this with enumerative inference and measure the runtime:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Construct a series of 20 actions to the blue goal\n",
    "actions = [\n",
    "    (-1, 0), (-1, 0), (0, 1), # Up twice then right\n",
    "    (-1, 0), (-1, 0), # Up twice\n",
    "    (0, -1), (0, -1), (0, -1), (-1, 0), # Left thrice then up\n",
    "    (0, -1), (0, -1), (0, -1), # Left thrice\n",
    "    (1, 0), (1, 0), (0, 1), # Down twice then right\n",
    "    (1, 0), (1, 0), (1, 0), (0, -1), # Down thrice then left\n",
    "    (0, 0) # Stay in place\n",
    "]\n",
    "\n",
    "# Allocate buffers to store runtime and goal probabilities\n",
    "T = length(actions)\n",
    "runtimes_enum = Vector{Float64}(undef, T)\n",
    "goal_probs = Matrix{Float64}(undef, length(goal_locs), T)\n",
    "\n",
    "# Iterate over timesteps and run inference\n",
    "choice_iter = choice_vol_grid((:goal, goal_locs))\n",
    "observations = choicemap()\n",
    "for (t, act) in enumerate(actions)\n",
    "    # Add current action to observation choicemap\n",
    "    observations[(:act, t)] = act\n",
    "    # Run enumerative inference given all actions observed so far\n",
    "    model_args = (t, grid, init_loc, goal_locs, beta)\n",
    "    stats = @timed begin\n",
    "        traces, log_posterior_probs, lml =\n",
    "            enumerative_inference(gridworld_agent_model, model_args,\n",
    "                                  observations, choice_iter)\n",
    "    end\n",
    "    # Record runtime and goal probabilities\n",
    "    runtimes_enum[t] = stats.time\n",
    "    goal_probs[:, t] = exp.(log_posterior_probs)\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's plot both the goal probabilities over time, and the runtime of the\n",
    "algorithm for each step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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+ADQaDUSVlZVZWVmOjo4Ajhw5cujQIdSnkpISiHiez8rK8vDwAHD27Nldu3bhcX369Dl8+DCACxcurFu3bvTo0SzL3r59e9WqVWlpaQDGjx+Px1VUVBQXF8vlcvyJ/v37Hzx4EMCtW7dmz54dEhJiZmZWWlr6zTffJCQkQPT++++jhg4dOrRt2zYAzZs39/b2bty4sZWVVb9+/SorK8PDwwEwDAMDycnJEHl5eYG8LDgQQgghhBgwMTE5deqUj4+PQqHQaDSCIED09ddfKxQKAK6urk2aNLl//35ycnJOTo6DgwNELi4uI0aMWLNmDYDbt2937txZoVCUlJTwPI8nBAUFbdq06c6dOwCmTZu2bdu2pk2b3rp168GDBxANHDiwa9euADw9PSEqKyvr1auXt7d3UVFRdHS0IAioT82aNWMYRhAEvV7/3nvvvf7662VlZZcuXdLr9XjckCFDVq5ceffuXQCff/75hg0bLC0tr169qlarAVhbW48bNw4ihmEg0mg048aNs7Gx+emnn/A0gwcPXrdu3YULFwAsWrTo0KFDLi4u8fHxSUlJEAUEBLz33nuooQEDBmzbtg3AnTt3unTp4u3tbWFh8eDBg0uXLkHUtm3bJk2aoMqlS5cgeuutt0BeFhwIIYQQQgyMGjXqxIkTKSkpxcXFEDEMM3Xq1NGjR0MklUq7deu2efPm0tLSS5cu9e/fH1UWL16cnp5+6NAhAHq9vri4GECrVq18fHw2bdoEA5aWllu2bBk6dGhCQgKA2yJUCQwMXLt2LUT+ojNnzgDIy8s7fvw4AAcHh8GDB3///fcAMjMz8/LybG1tUad8fHz69et38OBBAGq1+uTJkwAsLS3HjBmzcOFCALm5uQ8ePHBxcVGpVD///POQIUPu378vCMLVq1dRRaVSrVixwsPDA6KOHTva29vn5OQA2L9/v6enJ/6EVCrdvHnzhx9+eO3aNQB3RKjSuXPnTZs2cRyHGnrvvffGjRu3evVqQRDui2DAzs5u4cKFEokEIkEQoqKiAEil0m7duoG8LDgQQgghhBhQKBSnT59esmTJlStXysvLW7VqNXLkyJ49e8LAsGHDNm/eDGD37t39+/dHFXNz8wMHDmzatOmXX365f/++hYVFQEDA1KlTp0+fjif4+PicP39+7dq1Bw8evHfvXnl5uYWFRfPmzT/66KORI0dyHAeRiYnJzp07Z8+efeTIkfz8fGtr6549e86YMSMlJSUqKorneYZhZs6c+dNPP5mamrZu3ZrneblcLpFIUDsMw2zatMnFxWX//v15eXmWlpZ+fn4zZsyoqKg4deqUTqdjGGbWrFnbtm0D0LFjx4iIiFWrVh09ejQtLU2v19vZ2fn5+U2ZMqVVq1ao4uLismfPnlWrVqWkpAiC0KRJE4hcXV1NTEwASKVSVGnWrNnZs2fXrVu3b9++pKSk0tJSc3Nzd3f3Dz/8MCgoSCaToYq9vf2HH34IwNzcHAbMzMyGDBkiCAIAmUwG0Q8//BAYGLh58+br168/fPiwoqJCJpM1bNiwW7du48ePd3d3R5Vr167dunULQI8ePVxdXUFeFhwIIYQQQh7n4uLy448/AhAEgWEYPMHPz+/NN9+Mjo4+evRoWlpa48aNUUUikQSJBEFgGAai/Px8iBiGgQFbW9tvRRqNpqyszNzcXC6X4wn29vY//fRTeXl5cXGxUqmUyWQA3Nzcrl27BgP+/v43b95E3bG0tFy+fPmCBQuKiorMzc3lcjlEMTExeIKzs/PSpUsXL16sVqt1Op2lpaWpqSme0FWExx09ehRPo1Qqp4hKSkoePXqkEOEJwcHBeBpPT8+dO3fiCb1Fer1eo9FUVlbKZDJzc3OGYfC4LVu2CIIA4PPPPwd5iXAghBBCCPkTDMPgaViWnTRp0uDBgzUazbZt22bMmAHg4MGDCxYs4HmeZdn58+cHBARAFBcXd+7cOYh8fHzwNEoR/pKZCM+cVCq1s7ND9bAsa21tjbpmLkKdkkgklpaW+BN5eXm7d+8G0KVLl169eoG8RDgQQgghhNTcwIEDN2zYcPLkyfXr148fP16pVHp7e6empubm5gIYOXLklClTPDw8EhISVq9enZubC8DNzW3AgAEgL4JNmzbl5eUxDDN79myWZUFeIhwIIYSQv1RRUcEwjKmpKf4Ez/OCIEgkEpBXCcMwoaGhkZGRqamp69evnzx5cuPGjVevXv3ll19mZmamp6dPmjQJBry8vNatW9egQQMYDYZhQJ4mPz//+++/BzBy5MiAgACQlwsHQggh5C+FhIQ0bdp0zJgxeIJOpwsNDd27d69Wq+3Vq9eCBQsUCgXIi8nGxqZZs2YAOI5D9XTo0GHmzJkZGRnp6ellZWUymeyDDz5466239uzZc/r06bS0NI1Go1KpXF1de/bsOXDgQAsLCxgHjuM+//xzhmEkEgnIEw4cONCvXz+GYYKDg0FeOhwIIYSQpxEEQa1WX7p0ad26daGhoXiaZcuWrV69etOmTXK5fNy4cTqd7scffwR5Me3fvx8ihmFQbcHBwXicg4PDBBEAnudZloXx6SIC+RNBQUEgLy8OhBBCyNPk5OQEBAQUFhYWFBTgabRa7caNG+fOndu3b18AixcvHjZs2Jw5c2xtbUFeQCzLoq6xLAtCiJHhQAghhDyNvb399evXi4uLe/Togad58OBBUlJS586dIXrjjTe0Wm1cXJytrS0IIYQYKw71z8/PD4Cfnx+MjyAIEDEMA+MjCAIAhmFgfARBgIhhGBgfQRAAMAwD4yMIAkQMw8D4CIIAgGEYGB9BECBiGAbGJyIiAkBERAReFgzDSKVSW1tb/In8/HyJRGJtbQ2RhSg3NxcGQkJCYGDz5s2NGjXq0qULaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaofneQAsy6J2eJ4HwLIsaicqKkoikZw7dw7VxuGVp9FolEoljFJlZSUAqVQKo6TRaJRKJYxSZWUlAKlUCqOk0WiUSiWMUmVlJQCpVAqjpNFolEoliDFhGAYGeJ7Hn+N5Xq/Xo9a0Wi0AqVSK2tFqtQCkUilqR6vVApBKpagdrVYLQCqVona0Wi0AqVSK2tFqtQCkUilqR6vVApBKpagdrVYLQCqVona0Wi0AqVSK2tFqtQCkUilqR6vVApBKpagdrVYLQCqVouaWLFkiU9qYtv+XFlJUYfjKsmsbdaUPm/YO1vPQCdDzDC+AF8AL4AUIAv6H5swczsZd1uYjPK7s5k5dfqLSfzbDwBADgMF/MPj/MBAxKDw5l7N2kbX9GGDw/xPKbmzXFaTYvj0LT8Mw+B+5J+Zy1s6yNsPAMPgvQSi7uU1XkGrXcxaqJ/fEXM7aWdZmGBgG/yUIZTe36QpS7XvOQvXknJjLWTvL2gwDw+C/BKHs5jZdQap9z1monpwTczlrZ1mbYWCYikzudScdaoJD/fPz8wMQEhIC46PX67OyshwdHSUSCYxPUVERAJVKBeOj1+uzsrIcHR0lEgmMT1FREQCVSgXjo9frs7KyHB0dJRIJjE9RUREAlUoF46PX67OyshwdHSUSCYxPSEgIXjHm5uZ6vb6srAwirVZbUVGhVCphICQkBAYqKioALFiwALVTVFQEQKVSoXaKiooAqFQq1E5RUREAlUqF2ikqKgKgUqlQO0VFRQBUKhVqp6ioCIBKpULtFBUVAVCpVKidoqIiACqVCrVTVFQEQKVSoXaKiooAqFQq1E5RUREAlUqF2ikqKgKgUqlQQ7yARYsWqVzfEAIWmOExldm/a+MP4605ZhJwLKQSmHIwlcCMg5kJzDjITCAzgdwEMhPITRB2+Tvoip06j9SYOaOKZWVq6vWfpOYWx34OYRmwLFgGLAOWAcOAZcAyYBmwAMOAZcAy6NRiXX5Bessu7903bYcqzpWxl6MW2jk43NgXAgMMHsMw+K92nhtyczPadH33nqk3qrhUXo2OWujo5HRjfwiqp63HhpyctNZd30kx9UEVl4qYS5HzHZ2cbu4PQfW08diQk5PWuus7KaY+qOJSEXMpcr6jk9PN/SGonjYeG3Jy0lp3fSfF1AenQ7p0qEBNcCCEEEL+kYYNG1pbW8fHxzdr1gxASkpKYWGhq6srCCEvAgG4X4jIFJxMBGMiz753s4EmS6J0RBWlLktTcJORyY98AjMOphKYcpBKwLEwkYBlwDJgGRi63afXnj177JPXosU0DawAKFHYIHHtHXXOoEGDOjujmkYM/3jJkiVFJ2e79Zx3T9IagKv+Vv7J2Xpt5YhhHzsqUU0jRwxfsGBB7rEZ7n3m3+PaAnDV3cg6FqzXVY4cMdxOgWr6ZOSI+fPn5x6Z4f7O/HuSdgBc9bGZR4N5ve6TkSNsFaimT0aOmD9/fu6RGe7vzL8naQfAVR+beTSY1+s+GTnCVoFq+mTkiPnz5+cemeH+zvxYCKghDoQQQkhN7N+/X6vV9uzZ08rKqlevXhs3bvTz8zM1Nd24caOvr6+7uzsIIcYtS4PzqTiZiOgHyH+E/zB39yv+44jT/S2FLSdWwgyAKcobP9gSn/ugb9++ze1QTfPmzYuOjo7cudCt3WUv794AUq8djYw926RJk3nz5qHaZs6cee3atTNnDplcP+3W1h9A9I0z2vJH/v7+M2fORLUFBwfHxsYeP348+XqEc+suAM7fitLrKnv16hUcHIxqCw4Ojo2NPXbsWHLsWZdWXQBE3Y7i9brAwMDg4GBUW3BwcGxs7LFjx5Jjz7q06gIg6nYUr9cFBgYGBwej2oKDg2NjY48dO5Yce1Zl2wgdPkRNcCCEEEL+kpmZGcMwqJKUlPTjjz/26tULQGho6ODBg998800TE5Py8vIdO3YwDANCiFF6WIrLaQhPwPn7yNbgP6xk6OWBHu5QvTV3+PuXY3dNb//2HdsW3QHk/XHqVPi2Bg0azJkzB9Xm4eFx8ODBcePGXbx4Njn2LESdOnVatWqVh4cHqk2pVB44cCAkJGT79u1x0YcB2Nrafvz5ZyEhIUqlEtWmUCj27dsXGhq6devWlBtnATg4OAwfPvzbb79VKBSoNrlcvm/fvrCwsC1btqTcOgfA0dFxxIgRwcHBcrkc1SaXy/ft2xcWFrZly5aUW+cAODo6jhgxIjg4WC6Xo9rkcvm+ffvCwsK2bNmSmXkfNcSBEEII+UsHDhwQBAFVBorkcjmApk2bnj17NjY2Vq/Xt2nTxsLCAoSQZysuLm7ixIknT57keR4Ay7I9evRYsWLFa6+9BlFxOa5mIDwRkfdwX43/MDeFrwu6u8PPFS7WYPAf7f/973+PHz/+evg2hG+DyMvL64cffmjfvj1qol27dhcuXACQkpICwMXFBf+IhYXFclFRUREAlUqFf0ShUCwQFRUVAVCpVPhH5HJ5mKioqAiASqXCPyKXy8NERUVFAFQqFf4RuVweJpo+fTpqiAMhhBDylxwdHWHA1dUVBmQyWadOnUAIeR5SU1P79euXkJDQyLO9q08fAPeuHjlx4kS/fv0OHjlRaOJ8MgkRyUjKBy9AyqFDY3RvBn83eNhCwsBQQEDAnTt31Gr1Rx99BGDnzp2WlpaoBWtraxCjxIEQQgghhLyYZs2alZCQ0GnAhOL2M5IYewBWXmMbXJ5/49DK7sNnce9u1fHgWLS0h38zdG+GlvYwkeAvWFpa7tq1C4BKpQJ5SXEghBBCCCEvpsOHD8stbLTtxhcw9hAVMva8x3hWviP7xuGuI+Hnhh7N0NYJchMQ8n9xeAHp8zUSGyUIeZa0+TCxASGEEGJM1Gq1xxuBmYwbDLBWbtZub+T/fuzX4bAwAyH/g8OLpmDTqYJ1J5psn2Lq5gBCno2sDchcg+a7IWsGQgghxGhIJJLy4gITpqISZqhiylSY6AvUEomFGQh5EocXyqNLcTnB2/nyyszJG5ru+ZqRmoCQ+lZ0Afe+AV+GpPFocQCsGQghhBDj4O7ufvdOdJeiiGRVL1SXZQOvAAAgAElEQVTxLIs4cSfay8sLhDwNhxeHLq8oc/LPfHklgNKoOzlzdzuEfQxC6lVlLpImgC/Df6gjkRoC14UghBBCjMPEiRM/++yzy2s/Me/9g8rldZVUcHp0NWrDeACTJk0CIU/D4UXBC1lTN1bEZ6BK/pqjZq2bWg7uAkLqC4/kiXgUh//K+AHmbWA3BIQQQogR+PTTT8/ExO/++buCXQM1UnkGgxvljxiGmTx58ujRo0HI03B4QeR992vxoRg8Lnv6VrPXGpm1cQEh9SFtKR7+iv+RPBVyL5i3BSGEEPK8afUwe3uZjdDHImZOdmIMgK5du86ePdvf3x+k7vzxxx+JiYkSicTV1bVRo0b4p+Li4gAIguDl5YXnh8OLQHP8et6i/XiCXl2aMXGD88FgiUoOQupWwVHcD8OTdGokjkWro+BUIIQQQp6r4wk4kwRPb//dy/yVKAKgUqlA6s6dO3emTJly8uRJvV4PQCKRdOvWbdGiRe3bt0fN7dq1KywsbNGiRV5eXnh+OBi9yuTsrCkbBZ0eT1N+MyVn1g6n70eDkDpUloTELyHo8FQlN5AyA+6rQQghhDw/mgqsvwK9gJHeaKRCURFI3crKyhowYEB8fLy3t3ffvn0Zhjl69OipU6eCgoIiIyPNzc1Rc3q9XhAEPFccjJtQqcuc8rM2qwB/rnDbWWnzxjaf9QIhdUKoRNIEVGbiL2RvhqIFnL4AIYQQ8pzs/x3XMtDGEQNbgdSHJUuWxMfH9+rVa8+ePUqlEsCECRO6d+8eFxcXHh4+YMAAABcvXty3b196erqzs/MHH3zQoUMHiG7durVr166UlBSlUunn5zd48GCO42AcOBi3nDn/Lo38A38nJ2SX2WuNFL4tQUjtpcyC+hz+VspMyJvD0g+EEELIM5etwaarYBmMeh2WMpA6p9frjx49CmDChAlKpRIiKyurnTt3arXaxo0bA9i4cePnn39eWVnZoEGDhw8frlq1au3atcOGDbt169bbb7+dk5NjY2NTWlq6YcOGO3fuhIWFwThwMGLq3VH5a46iGoQKbebUjS6HZ3H2liCkNnJ3IeMHVAdfjqQv0foETB1ACCGEPFvbY5GUDz9X9H0NpD4UFxdnZWWxLOvu7g7RmjVrGIYpKysD0KBBg379+oWEhGi12j179gQGBh44cGD48OFz58794IMP9uzZU1lZuWDBgrFjx16/ft3f3z88PDwsLAzGgYOxKruRkj19K6qtMjk7c/LPjbdOYiQsCPlnSmKRPBXVV5aEpAnw2gVGAkIIIeRZSXiIHTdgKkFQB0g5kPrAMAxEer0eoqNHjx4+fBiiRYsW3blzJy0trXPnzgMHDgQwdOjQ5cuX37hxIzEx8euvv546deqNGze2b98eExPD87wgCDAaHIySXl2aNXmDXl2KmtAcu/Zw2UHbaQNAyD+gUyNxPHRq1Ej+EaQtRpPpIIQQQp6VTVeRW4IBLeHrAlJPLCwsnJ2db926FR0d7enpCWCkKCkp6ZtvvgGg0WgAWFpaQsSyrIWFBYDS0tLo6OhPP/00NTX1NZFEIoEx4WCUsqdvLbuRgprLW/KLWYsmyj4+IKSmkqeiJBb/wIMFULSEzTsghBBC6t+VNPzyO1RmGPU6WAaknrAsO3DgwFu3bi1cuPDNN9/09PR8//33MzIyFixYAJGTkxPLsomJiRqNRqlU5ufn37t3z9TU1M7OLiwsLDU1de/evQMGDLhy5crBgwdhTDgYn/zVR9S7o/CPCHo+c8pGl9cambo5gJDqS1+J3F34ZwQ9kr6E3AuyZiCEEELqk17AhhiUVGJ0B7R1BKlX48ePP3bs2MWLF319fXv16iWRSMLDw3NzcyHy8vLy9fU9e/bsF1988e677+7Zsyc9Pb1Pnz5ubm48zwO4fPmyTqf74YcfYGQ4GJnSc7/nzNuNWtDlqjMnb2iyexprZgpCqkN9FqmzURuVOUgajxa/gJWBEEIIqTenEnEiAQ0tMNIbpL6pVKp9+/Z99dVXBw4c2LJlC4CWLVuuX79+4sSJAFiWXbt2bVBQ0M6dO7dv386y7Ntvv71mzRoAQUFB0dHRS5culclkEydOTEpKyhcBkEgkDMPgueJgTCpTczO+XC9U6lA7pVF3cuf822HBcBDyt8pTkDgWQiVqSR2JlFlwWwJCCCGkfjzSYn0MdDyGtYezFcgz4OjouH379oyMjNTUVJlM5uXlVVlZ+euvvyqVSgDu7u5nzpy5e/duXl6evb39a6+9xrIsgAEDBnh7e9+7d69x48bNmjUbOXIkgJKSkiEiQRDwXHEwGkKFNnPSBu2DPNSF/LXHpS2aWH3sB0L+Al+BxHEov486kfkjFC3hMAKEEEJIPTj4B6Lvw8sOQ9qAPEsNRRBVVlY6ODioVCqIJBJJy5Yt8YSmIog8PDxgTDgYjdwF+0rP/Y66kx28TdaqqVkbFxDyZ+7PgzoCdeje1zBvA/O2IIQQQurUw1JsvAoB+JcPGihAyD/GwTiU3UjJX3MUdYrXlGXP3ul8YAYYBoQ8qSQWGatQt/QapMxAqyMAA0IIIaTu7LqJu7no2BTvtQAhtcHBOEjdHMxaNCm7kYI6pejaEgwDQp5K1gyKliiJRd2y7AYwIIQQQupOaiG2XQfHYvTrkJuAkNrgYBxYpczpu6DUfmH64keoIxb93rCd+C4I+TMSJdxX4XYgdMWoKw0GoPEUEEIIIXVq8zVkFKPPa+juDkJqiYPRMGvj4hA2LGP8WtQF6WuNHBd/ApYBIX/BvC1cFyNhDOqE3AvNlgMsCCGEkLpzIwt7bsHcFEGvQ8KAkFriYEwsh/qW33mQv+YYaoeVS52+H83ZWoCQv2U/DKW/I2MVakmigPtqmNiCEEIIqTu8gJ9jUFSO4e3RoTEIqT0ORsZu5uDyW6mlF+6iFhxCP5a/7g5Cqsk5BCU3URSF2nBZAIs3QAghhNSpcyk4Egc7c3ziA0LqBAcjw5qZOq0YndJ3ri5HjX/Eari/1cgAEFJ9rAzuq3CrJyqz8c84fALHUSCEEELqVIUOG66gQoehbeHRAITUCQ7Gx9TNwXHxyPR/rRT0PGpI/qanw/xhIKSmZM3gtgxxwyHoUVMWneC6CIQQQkhdOxyHyBQ0s8HH7UBIXeFglCze6WA7tX/uov2oCa6BhdN3QaxcCkL+gQbvock3uB+GGjFpAPcfIFGAEEIIqVPqMmyMAS/gEx84KEFIXeFgrBpM7V92457mRCyqiWUcl34i9WwIQv6xxl9Dcx0Fx1BdLJqtgPw1EEIIIXVt723cyIJPI7zfEoTUIQ7GipGwjstGVSSFViZnoxoajOtr8e4bIKQ2GAmafY/biShLQnU0+hIN+oMQQgipa+lF2HwNEgZBr0MpBSF1iIMRM3Gydlo26v7gxUKFFn/JvEdbu+BBIKT2pA3RbCX+6A++An/NuiecZ4MQQgipB9uuI7UQPdzRywOE1C0Oxk3RtYX9rA+zg7fhz5m62DstH8WYSEBInbD0hfNc3Psaf8HMFc1WgjEBIYQQUtfu5OLftyAzwejXYSIBMX5qtVomk0mlUtRacXExz/OWlpaoNxyMns3ngeU3U9R7zuNpGFPO6bsgk4Y2IKQONRyHkljk/htPxZjCfRWkjUAIIYTUNQHYGIOHpRjcGp2cQZ6NEydOLFy48Nq1a1qt1tnZedSoURMnTuQ4DtWQmZk5ePDgs2fPokpMTMzKlSu3bduG6hk9evTQoUP9/PwAFBcXDx069MSJE2ZmZqgfHF4EDgtHlMdnlN9MwRPsvh2k6NoChNQ5t2V4FIeSG3iScwgsfUEIIYTUg0v38esd2Mgx6nUwIM/CXJFer7dWWCiliri4uK+++ur06dO7d++2sLDA35k/f/748eM5joMoJydnxYoVarUa1aDX66Oionbu3Pnhhx9C1KhRo65du65Zs2bSpEmoHxxeBBJLhdN3QfcHzNerS2HAcnCXBuP6gpD6wFnCfRVu94VODUN2Q9DoSxBCCCH1QMdj/RU80uITH7SwB3kGwsPD586dK+ekiwKGtE7Vm5TrH7SVf59+/vjx49OnT1+9ejX+Ulpa2sGDBxctWgRRv379zp07V1xcHBgYiL9z8+bNMWPGJCQk6PV6GBg+fHjv3r3HjBkjk8lQDzi8IGRtXRwXjUwf8yMEASKzNi4OC4aDkPpj3g5uyxE/ChDwf5m3hdtSEEIIIfXjeDxOJ6GpFYa1B6kPglYPQYCBBWHz9Xr9wm4fdo15BJHXreIZzToNy07bunXrqu++x186cuSIn5+fQqGA6PvvvwewcuXK+Ph4/J3GjRsfPXpUrVYHBATAgLu7u42NTURERGBgIOoBhxeHamDn8tv3H646DIBVypyWj5JYKkBIvbIbjNKbSP8e/yFRwv0HcJYghBBC6oGmAhtioBcwoj0aq0DqSUqv2YKA/4q5cEklkba4UQSYokqTpJK3TRvvKvzjXs/ZMOC0fBRcbWAgPDy8d+/eqOLs7AyAYRhUg7W1tUqlKikpwRPeeOON8PDwwMBA1AMOLxS7bweV/36/JOK248IRsnauIOQZcA5B6W0UnoHbMpi3ByGEPG7r1q2fffYZgLVr1w4fPhz/1NatWz/77DMAa9euHT58OMir55ffEZOO1g4Y1BqkXlXcTUMVHa9XMKamOgYMDEnLeQAVd9Pw5wRBSEhIGDt2LOqal5fXL7/8gvrB4YXCmHJO348uOXPLckhXEPJsMKZwX43CU7AfCkIIMbBjx44pU6bk5ORANGLEiGnTpi1btmzo0KGoiR07dkyZMiUnJweiESNGTJs2bdmyZUOHDgV5ZeSUYNM1MMCo12ElA6k/Tt8FwYBL/0txKUkPPMxbJlagSrEFd5UrlVRIXE/MwZ/TarVFRUVKpRJ1zcLCorCwEPWDw4vGpHEDqxH+IORZkjaBw79ACCEGTp8+PXr06LKyshlfdOrSmgUQdYuf/+PF0aNHOzg4BAQEoHpOnz49evTosrKyGV906tKaBRB1i5//48XRo0c7ODgEBASAvLzu3r07derUM2fOAHBp65//5tKADl7veIHUH8ZEYtbGBQY+mzB20qRJ3+dd+dajc9OEEgAaa9MDjUp+P/fA39/frI0LHldRVIQqHMcpFIpHjx6hrpWUlCgUCtQPDoQQQgipudDQ0LKysnVh3YPeusQwAoCeXoxzw+6fBp8KDQ0NCAhA9YSGhpaVla0L6x701iWGEQD09GKcG3b/NPhUaGhoQEAAyEtq9uzZ8+fP1+l0DMsCuBt9lLkSzo2dIR0yB+QZGj9+/KlTp44cOfJxzoO+zd9UmErPp/7x+7nUhg0bLl26FH+JZVkXF5e0tDT8peTk5LS0NHNzcx8fH1RPSkqKh4cH6gcHQgghhNRcdHS0p5vt+z53GEaAiGGE99tdW+asiL50HvfnonqiL533dFa83/4awwgQMYzwvvedZW620dHRIC+prVu3zps3TypXvj1hZZ5Fh4IyNj85uuTIhO2r5vV4vdmwYcNAnhWJRLJr164ZM2Zs2bJl29VTACQSSUBAwNKlS9u2bYu/061btwsXLgwbNgx/rqSk5J133tm9ezf+hJmZGR535cqVMWPGoH5wIIQQQkjNVVRUeLg4W8sewIC1eYVHw4qE+3o8WITqqajUeTQUrBUCDFjL1R4uTRLuPQQxSlqtdurUqevWrQPw6aefLl261MTEBDWxbNkyQRD8Jmy7Yf4u/sME8naerZpaRS3rt3Tp0mHDhoE8Q0ql8gcRau6dd97p37+/Vqs1MTFBlQ8++EAikaBKo0aN1q9fz3EcnkYikezfv1+pVKJKVlbW7du3AwICUD84EEIIIaTmpFJpfGJmfjFrY8GjSn6JWXw6IzWtQNNZqB6p6bfx6dL8EqmNeTmq5D+yik9+KJVKQYzPqlWrZsyYodFoIFq5cuWmTZvmz58/btw4/B0BqNChuBx37t61a+ZzR94dBjKsuzf29Ll79ybIi8PLy6t169Znzpzp2bMnqnTs2BEG1Gp1RETEhAkT8DQymezNN9+Egf3793/yySfW1taoHxwIIYQQUlOVWZ3a2Z65lLbnjOln/UxYRgDAC+yemHYJ90/7+/ujydeonk6dw8+cObMn5s3P/C6zDA+AF5g9l19LSDnt7+8PYmR+/fXXSZMm6Xm+x6dLKuw7AZDmXDy14etJkyY1adLk3XffRRWtHpoKFJQhtwSZxcgoRnoRMouRXYKCUuh0umKJPcfKYKACMgtre12CDuSFMnPmzGnTpvXs2RN/gmGYSZMmeXp6ohqKi4t//PHHyMhI1BsO9U8QhIqKCrVaDeOj1+sLCgr0er1EIoHx0Wg0ADQaDYwPx3HFxcUymUwikcD4FBcX63Q6jUYD46PX63Nzc/V6vUQigfHRaDQANBoNjA/HccXFxTKZTCKRwPiUl5dLpVKQV0HBCdyfN2tI3uUbzBfLK5OL2/q2kwI4d0O7bP1phUIxa9YsVNusWbMuX778xezTyaPf9GutZ8v/OHOdX7brtEKhmDVrFoiRWbhwoU6n6/3VjhuWH+H/atrp7UlOJ5YN/XbOAsb93YxipBchsxjZGuSVoqgcZVrwAv7LVAILM3BSpT7rqvTRgwp5U1Sx4x8kxV9VKpUgL5RWrVqFhoZmZ2c7ODjgaVxdXVFtqamp27dvb9CgAeoNh2eCYRiWZWF8Kisrv/vuO51OxzCMWq0GkJ6ejiqJiYl4rgRBAMAwDJ4fd3d3VGnUqBEAS0tLABYWFmPGjGFFMD48zy9atKisrAyAWq0GkJ6ejiqJiYl4rgRBYBgGRkkQBAAMw+D5cXd3R5VGjRoBsLS0BGBhYTFmzBhWBOPDMAzIS0+nRvoKZK6BvsTXr9vGNZ0mzVizbMOVZfh/nJycvvvuO19fX1Sbr6/vxo0bJ02atGx99DL8P04OVt99/5Ovry+Ikbl+/bqTW+skVV8Y+F3R19Sx9e83r485gP/iWJhLYWcOe3M4KtHQAo1UcLKAgxINFBh7vtf+fXsap/yU3fzrEsYSgLmgVt79SVOQM2jQIJAXjbe3N+pI69atUc841D+GYaRSqYWFBYwPz/Msy27fvh3kT8TGxqJKbGwsqgwZMoTjOAsLC4lEAuOj0WjKy8u3bdsG8gKKjY1FldjYWFQZMmQIx3EWFhYSiQTGRyqVgrzcii/i/jyoIyExR5Ov0fDLQa1Ug0Z8e+TIkYEDBwLYu3dvnz59UHODREeOHBk4cCAD3Z4Qtk+/9+A5CMT4aLVaS/umasYCBgSphalV08rs27090VCFhhZoqIKjErYKWMogM4GEwf8IC50bcyU6cufCZu1jvLx7Abh/7Xjk9dNNmjSZO3cuCKlPHAghhBDy1/gyZK5F+nJo82HeHs4zYfU2qvTp0ycrKwuASqVCLfTp0ycrK0tSftc8uR+KLqAyG6YOIEZGLpdn37ttq8vWcA6oYqnPLiu4rZDL17+PavL09Dxw4MC4ceMuXTqddP00RB07dly1apWnpycIqU8cXnmFhYUgNadWq2HcCgsLQV4uarUahDx7pbdxPxT5h8GYwmkMGn8FUwfUG720GczboSgKxZfQoD+IkfH19T169Kj06lb4fMlwUgAmQkXDtK13slN79+6Nmmjfvv3FixcBJCYmAnB3dwchzwQHQgghhDyVoEPONjxYhIo0yD3QZAZsPwAY1CvGBFbdURSFgnA06A9iZGbMnHM6Mjrr0Ne2uXdavdmdY4X8O6dPnthibW09Z84c/CN2dnYg5Bni8MpLS0sDqbnMzEwYt4yMDJCXS2ZmJgh5Zsrv4f4C5P4b/2H3IZrMgMwNz4ZlN7ALUXQe2nyY2IAYk4uVPuYf7GKPTci7vOXM5S0QeXp6rly50sfHB4S8CDgQQggh5DEC8n7BgzA8ioe0IRp/DYfhYEzwzChaQtEKmhhoLsO6N4jR+OV3rImGTYu3t30T52Od9+677wL47bffbG1tQciLgwMhhBBC/qsyB2lLkf0z+ApY94bzTCha4xljpbAKgOYKCk7CujeIcYjNxIIIVOowpRsCPQHYHj9+HIBKpQIhLxQOhBBCyKvn559/Xr16dVxcHIDXXntt7Nixo0aNQuEp3J8HzVWYWKPpt3AaA1aO58LKH2nLUHQOuiJwKpDnLacEc04hsxiDW+PTDiDkf6jVaplMJpVKUWvFxcU8z1taWqLecHjlxcfHg9RccnIyjFtCQgLIyyU5ORmE1Jperx89evSmTZsANHZUAYiNjQ0KCrpw4sf1E9IlQglUXdD0W6jewnOkaANFc5TehuYqrAJAniutHgsjEJOODo3xjR9MJCAvnxMnTixcuPDatWtardbZ2XnUqFETJ07kOA7VkJmZOXjw4LNnz6JKTEzMypUrt23bhr+UkJDw22+/wcCECRMqKiqGDh164sQJMzMz1A8OhBBCyKtkxYoVmzZtau5ht3xq89ebxAGISWk2ecnvm/Zeb+lgPnnyFDSaBM4Kz5dEActuKLmBwlOwCgB5rtZewd5bcLLA7ADYmYO8fOaK9Hp9A2u5ylwaFxf31VdfnT59evfu3RYWFvg78+fPHz9+PMdxEOXk5KxYsUKtVuPvZGZmhoaG9ujRAyKO4xiGadSoUdeuXdesWTNp0iTUDw6EEELIq2TNmjUAVk/38HO7AlHPFsWrJzIBX+LHw8rJK+fCSFh1R8YPUJ+FvgQSc5Dn5Fg8Vl6AKYcZ3dDWCeTlEx4ePnfuXIWcWzvHz++1ZJmk7FZWq9lrM44fPz59+vTVq1fjL6WlpR08eHDRokUQ9evX79y5c8XFxYGBgfg7ycnJvr6+hw8fNjU1hYHhw4f37t17zJgxMpkM9YADIYQQ8ipJTU3t0qFpJ+fbMNCpFdfZp9HF61kwHkpvyNzxKA4lN6B6C+R5uJOL0DMorcSkt9C/BcjLQNACAgwsWBCm1+vXzun6oc8liLq4Xv9+kmdAvHzr1q2rV32Hv3TkyBE/Pz+FQgHR999/D2DlypXx8fH4O4mJiU2bNr1x48bDhw+dnZ2bN28Okbu7u42NTURERGBgIOoBB0IIIeRVwvO8XGbKsXoY4FjI5TKe52E8JEpYdsOjuyg8BdVbIM9cwSPMPY3UQrzbHGM7grw8bvgDAqpci7lsbcH6uV6DgVYO8R/4cWt+KcaNbjDk/gPgBgPh4eG9e/dGFWdnZwAMw6Aa7t27l5ycfPXqVZlMduPGjfHjxy9fvpxhGABvvPFGeHh4YGAg6gEHQggh5FViY2Nz4er9uDyv5naJqBKX53bh6l0bGxsYFavuyPwJ6jPgvwYrA3mG9AKWRCIqBW0cMaMbZCYgL5XSO6ii1fJKGSP9P+zBC0DN9+M//uf7vN/nnM79nO5C6B4iCrlFotxyv7Yx5h5SZkamzOYy5mPSaJ+5xEzbXFu5hAgzKZeS6S6WS+TUOadOt3P779vn337ts9knVi16PR5sDUChDj6nEr9S38WLGQyG7OzshQsX4uUZDAYjI6NZs2YtW7aMYZgTJ074+fkNGjTIz88PgLOz89GjR9E4GBAEQRBESzJhwoTIyMjN0boPJ9G2rXQA8oqtN39Llamr3542Ac2KuCd4NlD/DHU6RD1BNKGo6zhwC2YCrPZGWwmIN4p9BOro0GFcRlZ++lNnT1EmasnVkoTbGpouhusFvJhGo1EqlSKRCC+Poqj9+/dLJBLUGDlypKenZ2Jiop+fHwCxWFxSUoLGwYAgCIIgWpKPPvooJSUl6siNs5eoUf3Fem6HuAv5jwqVbm5uH330EZoVRgaJJwr3oOQ8RD1BNJUL97DlMlgUlg9Ab2sQbxSKDaEr6pg7PzA4ODj0y+Lwpc5dWmUAeK42/uJ0h9S7lwcNGgShK/6LUolaDMMIBILy8nK8vKysrIKCgr59+1paWqIGl8ulaRo1ysrKBAIBGgcDgiAIgmhJzM3Nf/ghZvm8/kfP5u88qgRSeTzeW2+9tWnTJnNzczQ3xkNQuBclCWi7FBQHROPLk+PjBCgrMb8XprqCeOMtXrz43LlzJ06cGDTv6fhhHYUC9vmfHqTevdy6devPPvsMf4nFYnXo0KGgoAB/KS8vr6CgQCgUuru7o5aVldW4ceNWrVq1YMECAKmpqVeuXAkODkaN/Px8BwcHNA4GBEEQBNHCWMnKD6zSYlWbUpsYPddWIpGg2RJ5wMga6jSoMyDsCqKRlVbh4/PIKoKPPYL6gQLx5qNpOjo6OiQkZN++ff+OvgGApmlvb+/PPvvM1dUV/4uXl9eVK1emTZuGFysrK/Pz8/vuu+9Qh0gkWrZsWWBg4MmTJ3k83pkzZ2bOnDl06FDUSE5Onj9/PhoHA4IgCIJoaYpPQyOH6Vg91wbNHMcc4r54dhCKCxB2BdGYDMDWH3E2B05m+HAQRFwQLYRIJNpeAy/Pz89v7NixGo2GzWaj1oQJE2iaRq02bdp89dVXDMPg92bOnDlgwICrV69WVFQsWrTI09MTNZ48eZKenu7t7Y3GwYAgCIIgWhRDNeSx+JXpKIBC82c8BM8OouQsWi8GRYNoNAdTsTsFUh4+9IatCQiiPpydnbt06XL+/HlfX1/U6t27N+pQKBSJiYmBgYH4g2418HtHjhyZOXOmsbExGgcDgiAIgmhRSm+g9DqMbCD1QjleA+K+4LRC2U1UZIPvDKJxXH2AzRehN+C9/vCyAUHU3+rVq5cvX+7r64sXoCgqODjY0dER9aBSqXbs2HHp0iU0GgYEQRAE0aLIY6GvgrEv2GaAEs0ftzUkfVB0BIpE8J1BNIICJdYmoEiNd9zwjhsI4qW4uLh88sknhYWFlpaW+DM2Njaot/v37x84cMDU1BSNhgFBEARBtBzaEhSfAsWGySi8RmQ+KDqCkrOwmgewQDSoCg3WncftQnh2wPueoCkQxMtyc3NDA+nSpQsaGQOCIAiCaDkUF1GeA1EPiHvgNVgXSJEAACAASURBVCLpB7YZSlNQcQ88OxANKuIqYjPQXoZQb8h4IIg3HgOCIAiCaDnkMYABpn5g8fAaMWoHcS/I46C8DJ4diIZz9A52JkHIwYeD4GwOgmgJGBAEQRBEC1F5DyUXwEhgPAyvGQqyIZDHoeQsLGcAFIiGcOsxNiSiWov3vDDMEQTRQjAgCIIgiL+k0WjYbDbeAMVnoCmCyUjwnfDakQ4AI4XqKqoKwLVGY8rLywsODj558qROpwNA0/Tw4cO3bt1qa2uLl5GXlxccHHzy5EmdTgeApunhw4dv3brV1tYWLyMvLy84OPjkyZM6nQ4ATdPDhw/funWrra0tXkZeXl5wcPDJkyd1Oh0AmqbNugzXD9r61kDbuT1BEC0HA4IgCIJ4gZiYmE2bNj18+LBz584ff/xx9+7d8XtHjhyJjo5GLS6Xe+DAAYqi0AwZNJD/gF+ZjgYovHZ4thD1QMlZKK/A3BqNpqCgwM/PLyMjw6J9J/teIwDkXDsRGxubm5sbHx/ftm1b1E9BQYGfn19GRoZF+072vUYAyLl2IjY2Njc3Nz4+vm3btqifgoICPz+/jIwMi/ad7HuNAJBz7URsbGxubm58fHzbtm1RPwUFBX5+fhkZGRbtO9n3GmEwIPXHE4W3YkVPc6fPjmfTbUEQLQYDgiAIgvgzaWlpb7/99kcffTRgwIBdu3ZNmzbtypUrUqkUdeTk5OTl5fXr1w81KIoyGAwURaEZKkuFKhlG7SAdhNcSC7LBKDmL4jMwn4pGExoampGR4TF6QUWPD+9RVgAsXZZ0SPkkKWZnaGjo3r17UT+hoaEZGRkeoxdU9PjwHmUFwNJlSYeUT5JidoaGhu7duxf1ExoampGR4TF6QUWPD+9RVgAsXZZ0SPkkKWZnaGjo3r17UT+hoaEZGRkeoxdU9PjwHmUFQGizhH3pE8VPO7d9Grp3714QRIvBgCAIgiD+zN69e/v06bN06VIANjY2zs7Op0+fnjJlCurIzs4eOHDg1q1b0fzJY6GvgMwHHEu8pqReoIVQXUH1E3BaoXHExMTwRDKDW3ARZYUaRZSVWddgbsK3R47FLFiLejpyLIYrlFV0DS6irFCjiLIy6xrMTfj2yLGYBWtRT0eOxXCFsoquwUWUFWoUUVZmXYO5Cd8eORazYC3q6cixGK5QVtE1uIiyQg1aZNV6UHBV+rcxMTEgiJaEAUEQBEH8maSkJD8/P9SQyWTdu3e/evXqlClTUEdubu4777yza9eu0tJSNzc3T09PNE9aJYpPgWJgMgqvL74jhN2gvAzlTzAbj8ahUCgceg59yLJDHUUcO8rKozTn9IQDqKdSlcLIfmgRxw51FHHsKCuP0pzTEw6gnkpVCiP7oUUcO9RRxLGjrDxKc05POIB6KlUpjOyHFnHsUIfCyM66o0d28mkQxN+jUCh4PB6Xy8XfplKp9Hq9VCpFo2FAEARBEH+g0+meP39uZWWFWmZmZo8ePUIdWq22oKBg+fLlgwYN0mg0S5cuXbZs2ebNm1HHmjVrUMfly5d79uypVCrx96hUKrwMtiqer87U8VzUcDYolailUqnQEFQqFRqCSqXCX+Ly+hspL1c/PVHBGYwXU6lUeFUsmi6Slxjpq0Fz8Rt9NV2toCi6q6UW9fOQoulqBfTVoLn4jb6arlZQFN3VUov6eUjRdLUC+mrQXPxGX01XKyiK7mqpRf08pGi6WgF9NWguajGoLleV0DStVCrx8lQqFRqCSqVCQ1CpVGgIKpUKDUGlUqEhqFQqNASVSoUXS0hI2Lp1a2pqqlartba2njZt2oIFCxiGwR+oVCr8XmFh4YwZM+Li4iorK/Py8iIjI9PT0y0tLd96660hQ4bgBVQqFYDDhw8fO3asuLi4U6dOc+bMcXR0fPz48ezZs48ePWpkZIR6qKqqYrPZeBkMCIIgCOLPGAwG/J5er0cdRUVFI0aM8Pf379OnD4CjR49OnDhxypQpbm5uaGYY5SlAr5H4Glh8vM60ov6GZzxGnURp5QbGBA2qQkOdzGFzTWyLc5NM8y9y7HxQy7kiIeH+VTt7+31j1aifXhs65OZc9ag4nyEchlrOFQkJ96/a2dvvG6tG/fTa0CE356pHxfkM4TDUcq5ISLh/1c7eft9YNeqn14YOuTlXPSrOZwiHoZa9OuFcRpK9vT2Ilu3TTz/dtGmTTqfji024Ikl2dvbq1asvXry4d+9ekUiE/2XLli3z5s1jGKa4uPitt97q2LHj/PnzMzIypkyZEh0d7ePjgxeIjo5esWLFmjVr2rVrFxMTM2HChJiYGBsbm759++7ZsycgIACNgwFBEARB/AFN0yKRqKysDLXKy8ulUinqaNWqVUREBGqNHDnS2tr69u3bbm5uqLVmzRrUUVVVBUAikaAhSCQS1EfVL1BfAi0yshpnJJDgDyQSCRqCRCJBQ5BIJHgRUS887UqpromRAckI/CWJRIL60eoRn40915H0C9i9AvHDwsrYOe5ztj3iuQNoU3E9ac8SAEuDg42lEtRPcFDQwoULb+6Z7/Hutoc8dwBtKq4n7VkCYGlwsLFUgvoJDgpauHDhzT3zPd7d9pDnDqBNxfWkPUsALA0ONpZKUD/BQUELFy68uWe+x7vbHvLcAbSpuJ60ZwmA4OBgiUSCVyWRSNAQJBIJGoJEIkFDkEgkaAgSiQQNQSKRoCFIJBL83pkzZzZt2sQ2EvgGfFkgGVgFXg/N7fwfws6dO7dhw4YvvvgCf0YikaBGQUHByZMnt27dKhAIzp8///z58y+//NLU1BRAXl5ebGzsxIkT8QKHDx/+4IMPQkNDAUycOLF3794nTpz48MMP58yZM3z48KCgIB6Ph/+Fy+XiJTEgCIIgiD/j6Oh48+ZN1DAYDHl5edOmTUMdhw8ffvjwYUBAAIfDAaDX63U6nUgkQnNTfAbVhTAeCkEnvO5YXEgHQZWEkrMwGYG/zQBcuY/dKTifB60eHc0xY82CH9tkRu7YfnrDWCO+GEB6uQrA4sWL58+fj3pbsGBBZmbm9u3bT20Ya8QXA0gvVwFYvHjx/PnzUW8LFizIzMzcvn37qQ1jjfhiAOnlKgCLFy+eP38+6m3BggWZmZnbt28/tWGsEV8MIL1cBWDx4sXz588H0WJo9TAYUNf69Rt0Ot2QBV+mSqegxl1Of5ux2wrzvffv3/95+Bf4SydOnBg4cKBAIABgZGRUWVlZWlpqamqq1WrVarWZmRleoLKy0szMrE+fPqjB5/NNTExUKhUAe3t7ExOTxMTEYcOGoREwIAiCIIg/M3HixLlz5/7888+dOnWKi4vLzs4ePnw4gCNHjmg0Gl9fX3d393fffdfY2Pjtt982GAzffPNNdXV1nz590KwYtJD/gF+ZjgZYeAPIvPFwC5QXoVWAkeJvSHuCPdcRl4FKLdpJMa07JnWBCZ9664vwEcN81q9fn5qaCqB3794hISEjR47Ey6AoKjw83MfHZ/369ampqQB69+4dEhIycuRIvAyKosLDw318fNavX5+amgqgd+/eISEhI0eOxMugKCo8PNzHx2f9+vWpqakAevfuHRISMnLkSBAtzKh9MOD/uXLtBs03vsMdiDru0S68zhOe/7jTbx/q+nQY2vNR15kzZ4YPH44aQ4cOnTJlip+fn6+v77179548eRIZGYkXMDIyOnjwoEQiQY3Y2NgLFy58+OGHqNGrV68zZ84MGzYMjYABQRAEQfyZcePGnTt3rl+/fs7OzqmpqZ999pmjoyOA3NzcHTt2DB06tH379p988snChQu3bt2q1WpLSkq2bdtmZWWFZkWdDlUSuG0g9cabQdgF/I5Q30bpdcgG45XkybH/Jg6lQ1kJMwHm9MRb3dBWgt+MrKFUKgFIJBK8qpE1lEolAIlEglc1soZSqQQgkUjwqkbWUCqVACQSCYiWKrMIv9FpNSy+SMvisvA7VRQfQGYR/oLBYMjOzl64cCFqyOXyR48eSSQSPp9vZGRUWlpaUFBgbW2Nv/Tw4cONGzdGRkZu3rx50KBBqOHs7Hz06FE0DgYEQRAE8WdYLFZkZOSiRYuePHlib2/fvn171JhYg8/nAwgMDBw9enRGRgZN0926dTM1NUVzI4+DTg2zieC2xpuBxYfUC2W3UHIOssF4SYWlOJiKg6l4UgoRF9O6Y4YbnMxAEC3HpuGoa8zuDvdyMmx16fnwRC2RXq59lKCm6dh38Bc0Go1SqRSJRKixYcOGsrKyM2fOCAQCABs2bFi8eHFycjLDMHiBPXv2hISE9O3bNzk5uXv37qglFotLSkrQOBgQBEEQxIt1roE6bGxsUEe7GmiedGWQnwRFw3Q03iSyIXgUDsUF6MpAC1E/ykocTsf+m8iVg01jVEfMcod7GxBEi8Kw4GKJuhYHzA0ODi48GWo7LjyP7gJAanhukfNF1r3UQYMGuVjivyiV+A3DMAKBoLy8HDUyMzM7deokEAhQw93dfePGjWVlZVKpFH9m3759oaGhUVFRY8aMwe+VlZUJBAI0DgYEQRAE8aZSXoH6DgSdIe6DN4moO/gOKM9C2S1I+qNWdnZ2UFBQfHy8Xq8HwGKxfH19P//8c2sbh7hM7E1B6hOwKAy0waweGGgDFgWCIBYvXnzu3LkTJ048uTfIxXM8my/Mv3X+bk5q69atP/vsM/wlFovVoUOHgoIC1OjWrdvRo0cfP35sZWWl0WhOnDjRsWNHsVicl5dXUFAgFArd3d1Rq7q6OrzGwIEDFQoFauj1emNjYwD5+fkODg5oHAwIgiAI4k0ljwH0MBkBWog3CS2E1Avquyg5B0l/1Pjll19GjRqVlZVlZdfVrudIALnJcadOnbqTec81+MzNUmsD0L013nXHcEdwGRAE8R80TUdHR4eEhOzbt+9a3L8B0DTt7e392Wefubq64n/x8vK6cuXKtGnTACxZsiQ5OblXr149e/b85ZdfioqK9u3bx2KxysrK/Pz8vvvuO9Tx6NGjZ8+eLa6BWkuXLg0LCwOQnJw8f/58NA4GBEEQBPFGqnqEknOghTAZgTePbAge7UTJeVivAIsHYPXq1VlZWb3HLipzW5VLWQIQOy7ChXUFiRHyvat7zt/3jhvGd4aIC4Ig/otIJNpeAy/Pz89v7NixGo2GzWabmZnFxcVdvHgxKyvL0tLS09PT3NwcQJs2bb766iuGYVAHwzBHjhwRCoWoQ6/XA3jy5El6erq3tzcaB4MWz9HR8fr16yBekq2tLZo3BweHmzdvgniD2NragiDqr+Qcqh5BNhiCLnjziNzBs0X5zyi7DXEvALGxsXyxsa77EjlliRoqxlLXfQmdfBC5sd/5w1wIgiAanLOzc5cuXc6fP+/r6wuAw+EMqYE6FApFYmJiYGAg6mhbQyKR4A+OHDkyc+ZMY2NjNA4GBEEQBPEG0kMeg1+ZjAJF483DyCD1xJPdUJyHuBcAhULh0GvoI8oWddDGtu079bp3/bS5EARBNJLVq1cvX77c19cXL0BRVHBwsKOjI+pBpVLt2LHj0qVLaDQMCIIgCOLNo/4ZyivgtILxELypZEPwZA9KEtD2PVAcmqYrS0vYVFU1jFCLQ1Vpy0tomgZBEI3GxcXlk08+KSwstLS0xJ+xsbFBvd2/f//AgQOmpqZoNAwIgiAI4s0jPwFdGUxHg2uNN5XYA0btUJYG9V0IXe3s7DJ/ThqsvnhX4ItaThUXT/+c5OTkBIIgGpObmxsaSJcuXdDIGLR4bdu2vX79OoiXZGVlheatdevWN2/eBPEGsbKyAkHUh04NeRzAgslovMHYZpD0xdNvoLgAoeuSJUsWLFhwZee7vGHhgvY9ZUaGNuUpP+4KBBAUFASCIIhaDAiCIAjiDaNKgjodAidI+uPNJvPB029QchatF8+bNy/9btaOiG0VByeUGgmfUbhdUUZRVFBQ0Ny5c0EQBFGLQYsnk8lAvDypVIrmTSaTgXizSKVSEESNpKQkAL6+vvhT8h9g0MJ4OBgx3mySPuBYofQmyrMpQccBs7d+VzpMf+Xjyoc3APTr12/16tU+Pj4gCIKogwFBEARBvCYOHDgQEBBQWlqKWiKRaMeOHW+//TZ+U12IkrNg8WAyEm88jhUkfVF0CMrECk7H6DRw7X0+DfTxs1ECkEgkIAiC+AMGjc9gMADQ6XRofthsdnV19ZQpUyiKUigUAB4/foxaeXl5+EcZDAYAFEXhn2Nra4taVlZWAKRSKQCRSMRms3U6HZolhmFomp46dSoAhUIB4PHjx6iVl5eHf05lZaVWq0UzxjCMkZER/jm2traoZWVlBUAqlQIQiURsNlun06FZMhgMIBrT6dOnZ8yYodPphBbOre0GAHiUe7H0acaMGTNMTU2HDh2K/1CcR+UDSAdA6IqWQDYERYdQfDZBueD6Q8rJHCOcgGoQBEG8CIMmUVZWVlhYiOZHp9MtXLhQIpGwWCw0P2VlZQCEQiGaHzabXVxczGazaZpG81NaWrp06VI2m41/Tl5eHmo9fvwYgEKhAKBQKD799FOtVotmiWGYpUuXmpmZAZBKpQCsrKxQy9bWFv8cNptdXFzMZrNpmkbzU1ZWJhQKQTSaOXPm6HS6dq7jGZ/wUokVAAvlY5MzgQ9Sj8yZM6egoAD/x4DnMfiVyShQbLQEkn5gm2mUqQfvV+gN/MkukPGgrAZBEMSLMGgSQqHQ0tISzY9OpzMYDK1ataJpGs2PUqkEIJFI0PzodDqapi0tLWmaRvPD4/EASCQS/HPs7OzwZ3bt2sXj8UpLS9EsGRkZWVlZLVq0CM2PTqejadrS0pKmaTQ/QqEQRGN69OgRiysS9F2lkFihRoXEStp3FSvjzKNHj/Af6gwoL4NjDmNftBBG1hB7XMzRXikw6mCM0Z1AEATx1xg0PoqiANA0jWaJroXmh6ZpADRNo1mia6H5oWkaAE3TaH4oikLzxmKxaJpGs0TXQvNDURSIxmQwGARmTgorV9ShtOoqNO6genIb/1F8ClolzCfDqANaCkon9TlYaK7Vsya6GCyEFAiCIP4SA4IgmpaxsTGaN5lMBoJoNp7+Unr1yrMLmRqwmCqDwVBdTnEEqMUuV1VXKPAf+grIYwEKJqPRkiSV+SaWmFoZPRlrpwdagyAI4i8xIAiCIIjm55fskh+vFCXmGW4aTAsFNgYuxTbvqHl0nXv7u2r3d1HLkHGsUvELj8fDr1QpKEsF3wFST7QYBuBghlWVnhpndtCaagX4gyAI4i8xIAiiabVt2xbNW+vWrUEQjWbjxo3btm07fvy4j48Pfk+vM+T9LL/0k/ziL6xU2lzOcwAfXG11Z1VBX2nZrT59jx29/eCHABdVtqH9sGoWu+j53cITSwG88847+JX8Bxg0MB4KRoYW4+YjnM2hzHjlE80PoNgV5v5oIAqFYurUqQCio6OlUilelUKhmDp1KoDo6GipVIpXpVAopk6dCiA6OloqleJVKRSKqVOnAoiOjpZKpSCIlocBQRAEQTStiooKX19fe3v77OxsAJpqXeatootJJZeecNO5FiquI4QQVFf0UOX3M6sc1F/S2d2Kw2OAHQMH3r148eLthE+BTfg/BrAYWb9l704JhqYIxfFgGcHEDy3Jt2lQV2Ny10o70ROo1Kh+Ak4r/D0JCQmLFy/OyMhADZlM5uzsvH37dm9vb7yMhISExYsXZ2RkoIZMJnN2dt6+fbu3tzdeRkJCwuLFizMyMlBDJpM5Oztv377d29sbLyMhIWHx4sUZGRmoIZPJnJ2dt2/f7u3tDYJoSRgQBEEQRBNq1WuSWMTPOn8gJyen36CJo4atvSznZRpZlHMsIYa0srR/aZ6nlWZAb5mjazuGYaGOxMTEM2fOTJ8+/enTpwDMLSx7+n15s8Oodafy91heNq68B0k/iNzQYvz8FCcyITHCFDcJirpBcQnKn2A2Hn/DjRs3Jk+eLJfLJ7r272NiA+An+b1DqZcnT54cHx/v5uaG+rlx48bkyZPlcvlE1/59TGwA/CS/dyj18uTJk+Pj493c3FA/N27cmDx5slwun+jav4+JDYCf5PcOpV6ePHlyfHy8m5sb6ufGjRuTJ0+Wy+UTXfv3MbEB8JP83qHUy5MnT46Pj3dzcwNBtBgMCIIgCKIJlQmcKa817WXd7h9akpyZmz/YGWKYliv6Vj8c2F7fr4+pbScbiqLwAj4+PoWFhUqlEoBEInmQVTxz76MUcYdt56+t6UxRJiNBcdBifHcbykpM7YpOljS0Q6C4hJIzMBuPvyEsLEwul6/ymjThLpv9oBrAQI61g9ekdRe+DwsLi4uLQ/2EhYXJ5fJVXpMm3GWzH1QDGMixdvCatO7C92FhYXFxcaifsLAwuVy+ymvShLts9oNqAAM51g5ek9Zd+D4sLCwuLg71ExYWJpfLV3lNmnCXzX5QDWAgx9rBa9K6C9+HhYXFxcWBIFoMBgRBNC1HR0c0bw4ODiCIRlbVcRbbap+m8LZfeZaXA6tPX7O2tvZ4ee0cjT/wyF+Spt6nGNfl6ZXx7kPRYuTK8cNdCDiY6or/I/UCiw/lj9AUARy8qsTExDZSs6GP+OzqKtRgV+t9c5kovuzCuYSS/edRPxfOJbTmy3xzaXa1HjXY1XrfXCaKL7twLqFk/3nUz4VzCa35Mt9cml2tRw12td43l4niyy6cSyjZfx71c+FcQmu+zDeXZlfrUYNdrR/6mL9PapaYmAiCaEkYEARBEESTozh8NgONXhv5iSP+Ht8xHQKeHtkkH/dpzsoON6nufdFCHE5HkRpjOqF7a/wfQScIu0B1DaprYPrjVZWXl/extpEVVaEO4zKDvYZ/UVPyOGgX6qeiqrIn28S4DHUZlxnsNfyLmpLHQbtQPxVVlT3ZJsZlqMu4zGCv4V/UlDwO2oX6qaiq7Mk2MS5DXbJnVU58s4QnGQatjmJoEETLwIAgCIIgmpyJOrnwWQ4ahL5qfo+vcm5qjz6bvC723m7HCqkpD2+6AiWO3gGHhn9XUKhBcSDzhioJJWdh1h8vyaDRVd65X3omlaFYDx4VqIWOAoqNWmrGUMjVMHpG9s4g1A+z/VAhV6NmDAIthVpqxlDI1TB6RvbOINQPs/1QIVejZgwCLYVaasZQyNUwekb2ziDUD7P9UCFXo2YMAi2FWmqD5penjxlQ98esE/bvJOjfycilHUvEQ1MxGAwffvjhv/71LwBLly795JNPKIoCQTQyBgRBEATRtHjawvILofrKUgtjFp7uh/lUUGy8stLrnIrkZbaG2/n9ksQ2myPvrvuwI950R+/gkQq+DvBoh/9H6o2Cz6C4SBkrDbQE9aE3VOU8LktIKz19s+JGnr6iypklva2V/2RWNeQ5G7WudxNknnnWq1cvq62zUT/dr+66du3a9T6CASnlqHW9myDzzLNevXpZbZ2N+ul+dde1a9eu9xEMSClHrevdBJlnnvXq1ctq62zUT/eru65du3a9j2BASjlqXbXWZ99WdOVZlF/NKv8pk/rXcY6NJb+3k3BgZ567PbuVDBSFRhMZGblixQqlUoka69ev/+KLLzZu3Dh//nwQRGNiQBAEQRBNiJN//Gnmd2WPM1kUvlzGRvZCFJ9B2/ch7IpXI4+Dvqpdu64fdK8KSq84SNt3jsqZOsMeb65nZTiUDoYFf1fQFP4fYRfwO6EslS6/qRV54S9pfikqu3in9OT18qQsnbIcANvaTDLQZYXEffr6D5blnVztNdmlnAcgnV/x8bkohmFWrlyJeluxYsXEiRMDz0Wt9prsUs4DkM6v+PhcFMMwK1euRL2tWLFi4sSJgeeiVntNdinnAUjnV3x8LophmJUrV6LeVqxYMXHixMBzUau9JruU8wCk8ys+vhDDMEzoji3WZo5lF++U/5RRlfukKutRSVQCYyHludsJPTvz+zhx7a0oDoNad+/eXbJkSUJCgsFgAEBRlLe397Zt2zp27Ih6O3HiRGBgoE6rDfGa1LVKBCCNW7ox8VBgYGDbtm1HjBgBgmg0DAiCIAiiCcnz0wCwWKzly5eOnuGEh1vx/BhUV9E6EK1mgRbipWiKUXwKFAcmfsPH29y5l7FN4/yvHFnHpMKuHpZ4Q8XcRX4xPDtgQAfUpdWzP9yhOHWhPPPB2GotjIyMRo0a9c033zAMg1raIqX6x7ulJ2+oL9/VPlMAYMwkknG9RcPcBP07MubSqUCRCbNq1ao1CQdRSygUrlu3bvTo0ai3MWPGbNmyZdWqVWsSDqKWUChct27d6NGjUW9jxozZsmXLqlWr1iQcRC2hULhu3brRo0ej3saMGbNly5ZVq1atSTiIWkKhcN26deNmvAVANMJdr66s/PkX9eW76ss/V6bll564XnriOktgZNTJWtDPWdC/k1HXDr+UPBs9enRubm63tvaD27sAOHc//dy5c6NHjz5z5kyHDh1QP+vXr9doNOG+7w5KrgDKAXQCbekzMzB+z/r160eMGAGCaDQMCIIgCKIJ2dvbZ2Rk0DSN/5B6omALnn2L/BCUnIH1Ckj6o/6UiajIhbgXRD0ABAbY3V2Xc1Zov+74vV0OlWJjI7xxSirw7W2wKPi7gk3jN5WVlR07dszPzwdg04pVVoFnisrvv/8+JSXl7t277Gp9xbVs1akb6sT06vvPANBivnCIq3i4u2CgC6edGeoIDAycN2/ee++9t3v3bgCzZs3asmULl8vFSwoMDJw3b9577723e/duALNmzdqyZQuXy8VLCgwMnDdv3nvvvbd7924As2bN2rJlC5fLxUsKDAycN2/ee++9t3v3bgCzZs3asmULl8tFLZbAiN/Tgd/TwTRoVHX+0/KkLPXFO+XJ2eUpOeXJ2c+3xbLbW6wovZKbmzvHbchMhZX4TjWAscZ9onrb//vqydWrVx84cAC/0RsMOr1BqzVU6wzVGkNFtb6yWq+u0pdX6dWVN1JSHKWWvdIqUYdHhsbJsu2NGzdAxAzm+wAAIABJREFUEI2JAUEQBEE0ofHjx9M0jd/w7OGwA7IhKPgMikSU3USrObBaBI456uP5D4ABJn5gGQEwErBXTZHlRhdeEdtsicz4KMQZb5wTmch8hp5tMdgOdY0fPz4/P9/ajPnqfW5vF72+mj59Ufr+/sL8/PyRXXpHmvlUZT2E3sAy4vD7OImGdhcNduU6tAaLwp/hcrkRERHr1q0DIJFI8Kq4XG5ERMS6desASCQSvCoulxsREbFu3ToAEokEr4rL5UZERKxbtw6ARCLBC1A0i2vXimvXSvb2QG2RquJWnvriz+qfMqoyH559ekvG4o6/xxejGjXExdUT9dLDXEHc0eOFq7/Rl1Xoyyr1ZRX68ip9WZW+ospQUaWv0BiqNYYqrUGrNej00BuqNZpWalpAGVAHv1RrbWmR9fQhCKIxMSAIgiCIfxgLZuMh6YNH4XiyBwVbUHIe1sth4gdQ+AsVeVBcACOF8TDUsu9i+kHmvaUZlV9Ttp0P5Ex82x5vkLJqRKfhV1O7gsdGXWfOnKEohM+y8PEoASgI9JPHFHN0svHhRYk5t6sVnY1c2ouGuIp8uxm5tKc4DIj6YczEIp9uIp9u+oqqqoyHZe5fewrbtQYfdVgqDJ304h+rnsi/OIHfsCiKZlE0TXEYistmiXgscy6Lz6H4XJbAyOjokTxaXWKkl1WyUEtpwsl6WsDj8UAQjYkBQRAEQTQHnFbosAEyH/zyKZSXkTkD5m+hbTCMbPAiJfHQPIfJKPAdUIffJJv0T+9+oeu45a604/Wnndwt8KaIz0baY3SxxDBH/BetVuvYhjPMW4k6RoyssP+eyX6ibXfoA14PexafC+JVsXhcXndbmqZLJWxNFYuj0aOWhmUo5bPoUtpirT8t5LGERiwhjyUwYgm4LD6X4nFZRmyKy6Y4DMXQFEODRQ0YduH06dMJHVlj0ylaYwCghf6U4PmD3KdDhw4FQTQmBkRDqK6uvlLj4cOHYrHYzc3Ny8vL3NwczcODBw/Onz+flpZWWVlpa2vr6enZo0cPFouFZqC6uvpKjYcPH4rFYjc3Ny8vL3NzczQPDx48OH/+fFpaWmVlpa2traenZ48ePVgsFgiCaCRSLwjd8OTfeBSBwj1QXkKbpbCYCoqD/2LQ4PkP+JXpaIDC7y0JsL27PveCyO6TI7lf2UuFEi5ef5VaRKfCAEzuChEXf8Rhsxi2AXUwbAOXywBawYDOIBqCo6PjzZ9/Th/s5XajFLXSu4lTzz3q1KmT6aKRqJ81a9YkJSWtSYjOdfPuLbXWFSou5dw+nJYnlUjWrFkDgmhMDIi/LTY2dvXq1WlpaTweTyaTlZeXb9682dTUdNGiRStXruRwOPjnKBSKkJCQ/fv3q9VqExMTLpf7/Pnz6urqAQMGbNiwoXfv3vhHxcbGrl69Oi0tjcfjyWSy8vLyzZs3m5qaLlq0aOXKlRwOB/8chUIREhKyf/9+tVptYmLC5XKfP39eXV09YMCADRs29O7dGwRBNBJGjLbLIPVCwWbI45CzCCVn0fZ9CLuihlwuHzt2LKUvPRrywMSsA6SD8AcCEXfVJMm9759dEtn9a0dG6EpnvP7O5+FaARxM4eeMP2KxWJkFlclXTD36l6PWnVxkPapksVggGkhQUNCcOXPeS/pubZ+Jjg+1ALLaMKE/fQcgODgY9darV69vvvlmyZIlB24kHMD/z5ol2vTW0l69eoEgGhMD4u8JDw8PDg7u2LHj119/7e3tbWJiUl5enp6eHhERsWbNmuvXrx88eFAkEuGf8Pjx43HjxiUnJ8+dO3fOnDmOjo5sNruwsDAuLm7jxo2DBw+OioqaOHEi/iHh4eHBwcEdO3b8+uuvvb29TUxMysvL09PTIyIi1qxZc/369YMHD4pEIvwTHj9+PG7cuOTk5Llz586ZM8fR0ZHNZhcWFsbFxW3cuHHw4MFRUVETJ04EQRCNR+QGp314egAPt+L5MaiuovXisz/bBAZ9kJmZiRqmI+BkS4XvTBsyZAj+wLmb2fsZuctyJPtg43Iwd6y/HV5nWj0O3oLegEldYMLHH3Vyck6/+/OyqNIIrsC1ZyWAjDzWp99VVGswwKMdiAYye/bs7OzsLVu2BJzZxWXYAKrualgs1vvvvz9r1iy8jOE18vPzvby8APywYguz+hj7Womm4Dm7rSkIotEwIP6G48ePBwcHT548OTIyUiwWowaHw+lfY+DAgQEBAUFBQbt370aT02q1M2bMuHPnzvHjx0eNGoVa7dq1W7hwoZ+f39SpU2fPnm1jY+Pm5oYmd/z48eDg4MmTJ0dGRorFYtTgcDj9awwcODAgICAoKGj37t1oclqtdsaMGXfu3Dl+/PioUaNQq127dgsXLvTz85s6ders2bNtbGzc3NxAEETjYXHRahaknijYgmff3ji9cur7ermievp418E9BXTFz/FJZftPF0+dOjU+Pt7NzQ1/MNbfLn1DxpcG583p4o6pRY6uZnhtXcrH5ftoJ8OYTvgjbZEqwmHUsIysKzlV/VZXezgIAVzLKSsrN/TqyDocWoVnB2HuD6IhbNq0adSoUatXr05KSgIwsF/fjz/+uF+/fnglHTp0SEtLAyDmCQou5Zeevlm856xF2FQQRKNhQLyqqqqq1atXu7i4REZGisViAGfPnr19+7apqemYMWMkEsmCBQsKCgo2bNgwffr0AQMGoGnt27fv7NmzX3311ahRowAUFhbGxMSo1eo+ffp4eHhYW1vv37/fw8MjLCwsLi4OTauqqmr16tUuLi6RkZFisRjA2bNnb9++bWpqOmbMGIlEsmDBgoKCgg0bNkyfPn3AgAFoWvv27Tt79uxXX301atQoAIWFhTExMWq1uk+fPh4eHtbW1vv37/fw8AgLC4uLiwNBEI2NZw+HHTD2CV0xS65QfLqAt2RCHpetAzC+P7dTlz4fbLoUFhYWFxeHPxO8oEPGp7mXRHYff5f7pa1YIOLiNaQ3IDoVWj3Gd0YrEf6L9rnqybLdJhfvH+kybXHJhbyCBwlppQAoinJysP1u50BT6lvkBkFTjNYLAQrE39avX78LFy4olUoAEokEDYHiMCYLhqsv/VxyIFEyxsOoawcQRONgQLyqxMTEO3fufPvtt2KxGEBAQEBkZKTBYADQo0ePw4cPW1tbBwcHf/XVV1FRUQMGDEDT2rdvX7du3WbOnAkgJSVl0qRJ9+/fB8Bms9evX79s2TJbW9vAwMCPP/44KyvL0dERTSgxMfHOnTvffvutWCwGEBAQEBkZaTAYAPTo0ePw4cPW1tbBwcFfffVVVFTUgAED0LT27dvXrVu3mTNnAkhJSZk0adL9+/cBsNns9evXL1u2zNbWNjAw8OOPP87KynJ0dARBEI2OBdNxF1OntbfiTfeluGwdanDZhukDf9l5UJaYmIgXEEmNVo0T5R8ruiCy27bjbsgHHfEaulaA83mwFGFCZ/wX7XPVk/f2qGJTuA6tB0TMy3HfA0CpVAKQSCT4lUGLAnv8shH5q6AthvUKUBwQzZKgn7NkfJ+Sry/Ivzzd+ov5oCgQRCNgQLyqS5cuCYVCLy8vAKdOndq5cydqpaSkrF27dteuXWZmZv37909KStLr9SwWC01FLpenpqYGBATQNA1g+fLl9+/fRw2NRhMaGjpixAhnZ+eRI0eGhoampKQ4OjqiCV26dEkoFHp5eQE4derUzp07USslJWXt2rW7du0yMzPr379/UlKSXq9nsVhoKnK5PDU1NSAggKZpAMuXL79//z5qaDSa0NDQESNGODs7jxw5MjQ0NCUlxdHREQRBNIny8gqX3o6Wxr+gDkvhMxcn67iELLxY5x4W72XlfHBPsldj4/L9Pb9JNnitGIDoVFRqMbYT2slQl05e+mTZXlVsMtehtdX2uTx3O/wRxcD6A7CNkb8av3wKTQk6rAUtAtEMUZTxvKGl8beUx5IkE/oKB3UBQTQCBsSrun//vomJibGxMYDk5GT83tWrVw0GA0VRVlZWSUlJGo2Gy+WiqTx//ry0tNTGxgaASqVKTU1FHRUVFWlpac7Ozubm5hwOp6SkBE3r/v37JiYmxsbGAJKTk/F7V69eNRgMFEVZWVklJSVpNBoul4um8vz589LSUhsbGwAqlSo1NRV1VFRUpKWlOTs7m5ubczickpISEATRVNhs9oOHClWVSMwtRS1VlejBQwWbzcZfmvi2/Z31Gbvg/OktvpPzc3sXU7w+0h4jPhsmfEx0QV06eenjZXtUP1zj2ltZbZ/L72GPv9BqDhgZ7i3Hk39DWwybTeBYgGh+jDq2lb3jVbT5mHzHSUFfZ4rLBkE0NAbEqzI2Ni4vL6+qqmIYxsLCAr9nZmZGURSAyspKmqYpikITEgqFHA5HqVQCMDIyMjY2VigUqMPMzAxAVVWVTqejaRpNy9jYuLy8vKqqimEYCwsL/J6ZmRlFUQAqKytpmqYoCk1IKBRyOBylUgnAyMjI2NhYoVCgDjMzMwBVVVU6nY6maRAE0VS6d++elJQUd9vbv8dV1Iq73fl2ZoKHhwf+l/fmd8jYdO+K2GZddE6kjcRIwMZrIjoNZdUY7wJHM/xGV1z25P29qphrXLtWVtvn8nvY438ymwBGhrylKDoMbQls/wWeHYjmRzbDW3X8WtmFdOWxJOmU/iCIhsaAeFWurq4REREZGRnu7u7jx4/ftm1bZmYmatA0HRAQAECv19+4ccPJyYnD4aAJWVhYWFtbJyUlAeBwOLNnzw4JCUEtLy8vT09PANevX9fpdC4uLmharq6uERERGRkZ7u7u48eP37ZtW2ZmJmrQNB0QEABAr9ffuHHDycmJw+GgCVlYWFhbWyclJQHgcDizZ88OCQlBLS8vL09PTwDXr1/X6XQuLi4gCKKprFixYsKECdPeP/94+YA+zmoAP2UIPth0nmGYlStX4n8RGxutGsOfHfv8rNA+fGfG8mXOeB1kPsOJTIi4mNIVv9GVlD15f6/yeBLHtpXV9nn8ng6oJ5k3HHcjNwglCciaBbvPIewGoplhtzI2nuv75P298i9Pi4a40iYiEESDYkC8Kh8fH7FYvGPHjj179piZmR07diw0NPTWrVsWFhYBAQGTJk0CEBsbm5qaunPnTjQthmH8/PwiIiJSU1NdXV1XrlzJ5/O//vprtVrt6em5du1aNput0+kiIiLs7e3d3d3RtHx8fMRi8Y4dO/bs2WNmZnbs2LHQ0NBbt25ZWFgEBARMmjQJQGxsbGpq6s6dO9G0GIbx8/OLiIhITU11dXVduXIln8//+uuv1Wq1p6fn2rVr2Wy2TqeLiIiwt7d3d3cHQRBNZfTo0Vu3bl25cuX7GxNRSygUbtiwYdSoUaiHrh6WSzNzQgoku8rauxy5N2y8DZq9b2+jpAKTuqCLJf5DV1L25P29ymNXObaWrbfP5fdywEsRucNpL3KDoEhE5kzYfQ7pQBDNjHRyf+XRq+VXM0u+STQN9ANBNCgGxKtq27btvHnzNm/ePHjwYH9/fycnp++//16n09E0jRq5ublLly51cXGZNm0amlxgYOCBAweCgoKOHz8ulUqX1DAYDBRFocbGjRsvX74cGRnJ4/HQtNq2bTtv3rzNmzcPHjzY39/fycnp+++/1+l0NE2jRm5u7tKlS11cXKZNm4YmFxgYeODAgaCgoOPHj0ul0iU1DAYDRVGosXHjxsuXL0dGRvJ4PBAE0YQWLVo0d+7c999//9///jeAuXPnbt68mcPhoN6mzrC/88ndPTpL/49XKyd9Z9DrAFAU1alTp+PHj9va2qI5yS9GzF3w2JjaFf+hU6ifLI9SHr3KsbVsHT6X7+GIV8Czh+Mu5L2P58eQNRu2m2E6FkRzwhIamcwfVpGSU7z7rHhkT46NBQii4TAg/oawsLDU1NRp06Y9ePBg4cKFYrGYpmkABoPh1KlTS5YskcvlUVFRAoEATa59+/aff/75tGnTRowYsWnTpr59+wKgKApAYWHhxo0bt23bNn369Llz5+KfEBYWlpqaOm3atAcPHixcuFAsFtM0DcBgMJw6dWrJkiVyuTwqKkogEKDJtW/f/vPPP582bdqIESM2bdrUt29fABRFASgsLNy4ceO2bdumT58+d+5cEATR5DgczrZt29auXQtAIpHg5U0ezvxrhFdl4W0WRyBt1QkGg+Lx7Tt37ri5uaWlpbVr1w7NxqF0PCuDnzPc2+BXOoX6yfIo5ZGfODYWrbfN5fd2wivjtIL9DrCN8WQ3cgKgLYHluyCaE9Gw7qJhbqrY5OLdZyzXTQNBNBwGxN8gEAgOHTo0f/78kJCQL774YuDAgdbW1gqFIjk5+caNG507d46Jienfvz/+If7+/gzDBAcH9+vXz9PTs1u3bnw+Pysr68KFCwqFYsmSJZs3b6YoCv8EgUBw6NCh+fPnh4SEfPHFFwMHDrS2tlYoFMnJyTdu3OjcuXNMTEz//v3xD/H392cYJjg4uF+/fp6ent26dePz+VlZWRcuXFAoFEuWLNm8eTNFUSAI4jU0c87UysLbPKdRIp91jEVnANa55x6cW6EouDFu3LgbN26geXikwtE7YNPwdwWLgk5Z/uSDKOXhK5wOFlbb5vL7OOFvYsSw2QxGhodbkbcMmmK0CQZFg2geKIY2WTCsLDFdEX1JMq43z80OBNFAGBB/j0QiiY6Onj59elRU1JUrV06cOMHlcp2cnMLDw2fOnCkUCvGPmjRpkqen565du2JjY7/55hutVmthYTFu3LiZM2f27dsX/yiJRBIdHT19+vSoqKgrV66cOHGCy+U6OTmFh4fPnDlTKBTiHzVp0iRPT89du3bFxsZ+8803Wq3WwsJi3LhxM2fO7Nu3LwiCeG2lpqaCxbTtE1Rm0Rk1iuwGt9evTf16dGpqKpqNo3dQoMRgO/RpB52yvPCDKOWhK5z25lbb5gj6OqNBsLhoHwbGBA/W4v5H0MrRLhQsHojmge/hKJ3cv3jXGfnOU62/XEjRLBBEQ2BANIRhNTQaTUVFBZvN5vF4aDYsLS0/rKFWq3U6nVAoZLFYaDaG1dBoNBUVFWw2m8fjodmwtLT8sIZardbpdEKhkMVigSCI15xerxdaOKk7eKKOIjtfobljWeHPaB6K1DicDpqCvyuosvLCFfsU3//IaW9uFT5X0K8jGhILbQLBluHeSjwMh6YENhvAyEA0D8ZzfEpPXlfFpUjOpoqGdgdBNAQGRMNh10BzJRAI0Fyxa6C5EggEIAjiDWLQa1l6rY5Fo5YBBg1XBopK+OF+T09LkdQI/6gf7iJXjr7t4WlWXrhin+K7y5x2Zlbb5gr6dURjsJgGRoa8ZXj6NbQlsP0M3LaFhYW+vr4A4uPjLS0t8aoKCwt9fX0BxMfHW1pa4lUVFhb6+voCiI+Pt7S0xKsqLCz09fUFEB8fb2lpieaNa28lm+H9bP0h+c6TAs9OLD4XBPG3MSAIgiCIloRhGPXzHMeMo4UuU/Gb/EtVBT/RkrYzb7e1ufrUU6jw6Sly72NpJGCjySkr8d1tUMBUx+riD/crvr3Mtjaz2jZX0L8jGo/JSDBS5AZBHhd/KS/wX/LsnPuo0apVKwcHh/DwcF9fX7yM+Pj4wMDA7Oxs1GjVqpWDg0N4eLivry9eRnx8fGBgYHZ2Nmq0atXKwcEhPDzc19cXLyM+Pj4wMDA7Oxs1WrVq5eDgEB4e7uvri2ZM9s4g1fEk9Y8ZyiM/yaZ5gSD+NgYEQRAE0ZIMGDAgISHh7plVHQ0auf0YACY5x++e/Qh6fQd7Twt1UZ7QMoey2p+kdUh4MlBWOsRD6uphwebSaConMvHzU7hZ6jtHfa2IvsS2Nmu9bY7AsxMam6QfnPamxMzy/+B6scrw7niHQR6tAJxPVu05dMvf3//06dM9evRA/aSkpPj7+xcXF787sdugnmIA55NVew7d8vf3P336dI8ePVA/KSkp/v7+xcXF707sNqinGMD5ZNWeQ7f8/f1Pnz7do0cP1E9KSoq/v39xcfG7E7sN6ikGcD5ZtefQLX9//9OnT/fo0QPNFWMmMZ4/7PGSr4q/PC0a2p0xk4Ag/h4GBEEQBNGSHD9+3NnZ+eHD/JvfvcOVWAF4oHwMoE2bNrfO79RX0VcS75+5Xf2TxuSuuM3POmp3YpXzqYeDzMt9+hl3dDNn0RTq2LVr1/Lly0tKSgDIZLJNmzbNnj0bL2/Xrl3Lly8vKSkBKF67noL/jz34gGvqXvzH/T7JSULCCENEcAAiLnALCjYFQZRiFUVRqyhaZ1HrqANaa4+riFYFUVFvVfTS9rpAFBeOglAQpCpF3IpRcLGHgSQk59/m+8/90Vdrm4AXaft5nvci36uUK765wGvfqm3UTEMPZzQPwx7Mv43KqtiNH/Hmjy0S8AoBjO3P7+bguXR9CsMwJ0+ehG4YhikrK9sY6jl/2HUBVwFgbH9+NwfPpetTGIY5efIkdMMwTFlZ2cZQz/nDrgu4CgBj+/O7OXguXZ/CMMzJkyehG4ZhysrKNoZ6zh92XcBVABjbn9/NwXPp+hSGYU6ePIkWTDzGrfLID68u5Zfvv2i5ZDQIomloEARBEMQ/iZGR0Z07d8aNG3fu3Dl55VMAfD7fx8fn0KFDIpEIRnhvTMf3xqDk6au0lAfJN1VZrOU1E9trddh5qrZnfIFXW8UQiYVjr1YURbm5uV2+fBk/43ABlJeXz5w5c8+ePZmZmdCHm5vb5cuX8TMOFxRVK82q3TVoB7+Nd+cxNlEzDT2c0YxS07Lt2pkGvUcJeHJoCLiKoEG3trc1TE25gGe7oZvUlAt2bQ2DBt0UcBXQEHAVQYNubW9rmJpyAc92QzepKRfs2hoGDbop4CqgIeAqggbd2t7WMDXlAp7thm5SUy7YtTUMGnRTwFVAQ8BVBL37aHucWWpqKlo2jlBg8ZGf7PKd8n0XTPwHCBxtQBBNQIMgCIIg/mFEIlFSUhKAyspKAGKxGL/RysZw9MROo4GnBVUpKXfP3cOPXKtMk46Z1dgWX9Pn4IMnP351+fJlDk/Uw2tZvf17AOiC03kXN1y+fPnDDz/cu3cvdDN16tTLly9zeKIeXsvq7f0qDcSvnv5YmTjnhvzpmraP/+3ZA81LJpP1cOvSxvQxGmgjru5hJ096qsL9RdCNrFbeo099GzGLBtqIq3vYyZOeqnB/EXQjq5X36FPfRsyigTbi6h528qSnKtxfBN3IauU9+tS3EbNooI3Ryx5dOyRduIMWz9int8kI18qjGWW7z1pvnAaCaAIaBEEQBEG8no29yUR7k4nAo9tlF1PvnHvEvc63TjHu9DI3HUDb0f8q7jUR/6e9a2+B6dXjC7/99ts9e/ZAN//5z38A9H7vy+cDFkBDaNm5XfnTvHNLDn9/5t9objwe79GT8iq5sYmgGlpVtbxHLygeXQfrWdANj45+9MKgqpY2ESqhVVXLe/SC4tF1sJ4F3fDo6EcvDKpqaROhElpVtbxHLygeXQfrWdANj45+9MKgqpY2ESqhVVUnePSknMfjoeXjUBYfvVdzIbfiYJp4jLtoYBcQRGPRIAiCIAhCB3ZdzT/saj6NZe/llpxLezyv5Da/nUt999EU/p8XfWbyr8TKX+SNCXsE3ciV9Xzr3i/6zEQDVQNmGORsqyt/hGbXr1+/zMzME7lDJrlmQOtEnkve/fNubm7otAW66dc/KzMz80TekEmuGdA6keeSd/+8m5sbOm2Bbvr1z8rMzDyRN2SSawa0TuS55N0/7+bmhk5boJt+/bMyMzNP5A2Z5JoBrRPptXl3yt3c3PBXIOzrYPqBR2nMqdKYU8L+nSiaC4JoFBoEQRAEQeiMoqjOvS0797ac97GKz9ZTtAEaYHlCytgGz3OzTeygI1ZNGduwPCEaqDcw5hkY1+EtCAsLGzNmzJRlF54u83DvJgOQcUsUuuECj8cLCwuDzsLCwsaMGTNl2YWnyzzcu8kAZNwShW64wOPxwsLCoLOwsLAxY8ZMWXbh6TIP924yABm3RKEbLvB4vLCwMOgsLCxszJgxU5ZdeLrMw72bDGAzrleERt3j0Qib6QSwAIUWz3yGT9XJK9Wnr1afvmoywgUE0Sg0CIJodl26dMnJyUGL1LlzZxAEoQOKomTFd+0Kc8rau0DL6Fnuc2k6xaG/7voIuvHj0EpputGz3Bqb3tAyK/zxWelDiqLQ7EaMGLFly5awsLBl61OgZWxsHB4ePmLECOhsxIgRW7ZsCQsLW7Y+BVrGxsbh4eEjRoyAzkaMGLFly5awsLBl61OgZWxsHB4ePmLECOhsxIgRW7ZsCQsLW7Y+BVrGRoLwWdwRjofwxBHtlwActGx8eyvz6T4vvvi2NOaU0eAeHCMDEIT+aBAEQRAEoT9bW9tHjx5VpK8xGhZVY24PwKisQJa6Ui2vsrOz8w2wh25s27d99OiRLHWl0bCoGnN7AEZlBRXpa9SKV3Z2dngb5s6dO3v27OXLl+/YsQNASEhIREQETdPQ09y5c2fPnr18+fIdO3YACAkJiYiIoGkaepo7d+7s2bOXL1++Y8cOACEhIRERETRNQ09z586dPXv28uXLd+zYASAkJCQiIoIu3ouHn0G6FmolOoSC4qJlM5vkWZWQKbt8p+Jgmvl0HxCE/mgQBEEQBKG/2NhYHx+fwhsnDJ7eaOvwDoDHD9Lrygp4PF5sbCx0Fhsb6+PjU3jjhMHTG20d3gHw+EF6XVkBj8eLjY3FW0LT9KZNm1auXAlALBajsWia3rRp08qVKwGIxWI0Fk3TmzZtWrlyJQCxWIzGoml606ZNK1euBCAWi/Ez61mgeHgYisfrwSph+xkoHlowrrmR+Wzfork7y3afNfbrx7M2B0HoiQZBEARBEPrz8PA4dOjQtGnTKsoKHpQVQMPU1HTfvn0eHh7QmYeHx6FDh6ZNm1ZRVvCgrAAapqam+/bt8/DwANEM2kwDxcPdZzE5AAAgAElEQVTDpXjyFVgl7L4AxUcLJh41sPJIRs2F3PJ9F1p/GgiC0BMNgiCaXfv27XNyctAitW3bFgRB6GaUBoDKykoAYrEYjTJKA0BlZSUAsVgMoplZBYHi4cEnKIwEq4TdanAM0FJRAp5FyHuv0m+W779oMmqgQff2IAh90CAIgiAIgiBajwdF48FiFG2HWomO68ARoaUy8uwhDnCr+O5S2a4zNpEzQFEgCJ3RIAii2ZmZmaGlMjMzA0EQxD+T5RhweLi/EM92g1Wi43pwjdAyUZTFbN/q5GuVRzLEY9wN33UCQeiMBkEQBEEQBPF/LEaC4uH+AjzfB1aBjl+BNkGLZNDTzizIsyTqRGnMKdHALhSfBkHohsb/Hsuycrm8uLhYLpejhaFpuqqqSigUcrlctDxVVVX19fXV1dVoeVQq1cuXL1UqFZfLRcujUChommZZFi1PXV0dy7KTJ0+mKKq8vBxAUVERtO7evYtm0blzZ2i1bdsWgJmZGQADAwO5XF5RUYGWR6VSVVVVCYVCLpeLlqeurk4gEIAgiL868/fgyMO9+XjxDVglHDaDNkOLZP6hT9WJ7Opz16uSrogD3EAQuqHRLCIiIl69elVZWQmgoqICQGFhIbTu3buH/zFHR0dotWvXDoCpqSkAExOT2bNnUxpoeVQqVURERG1tLYCKigoAhYWF0Lp37x7eKpZlKYrCW+Xo6Aitdu3aATA1NQUgFApDQ0MpikLLw+fzFy1aJBaLuVwuWh6FQkHTNEVRaHmoBtDyUBQFgiD+HsyGoPNO3JuHl4egrkenLeC1QsvDa9/KfMaw558eKI05beTVExQIQhc0/vcoigKwbds2vD3Xrl2D1rVr16D1wQcf8Hg8sVjM5XLR8tTU1NTV1f373/8G8RrXrl2D1rVr16A1ZcoUPp8vFovR8qhUKplMZm1tzeVy0fJUVlYCEIvFaHlUKpVMJhOLxVwuFy2PQCAAQRB/G6Ye6LwT9+aiJB6sEp0iwW+Dlsf0g3cr4zNeXrn5qa9/Yu4PAMaNGxcVFWVqagqCeA0aBEEQBEEQxG+JB6HzLtybi9ITYJXotBWCtmhhuGLRtzbl6yqP1WWpoHHgwIHDhw+vXr16yZIlIIjfQ+OfraKiAi1beXk5CP2Vl5eDIAiCIJrIZAC67MbdEJSdwb2P0CkaBrZoSY4cOcLExXCAT4X9+lvZc1uLb5jIme//ExoaamdnN3bsWBDEb9AgCIIgCIIgXseoL7rsxt0QlF/AvTlw3A6DjmgxIiIiVCrV1gETPe6yqAQqZQ6Ahfe0Ocn/ioiIGDt2LAjiN2j8sz19+hQtW1FREQj9FRUVgSAIgiDeCMOe6Lwb9+ai4hLuzoHjdggd0TLk5uY629gNKOQC9dDql1/nbGOXm5sLgvg9NAiCIAiCIIg/ZtgdnXfh3lxU/lB4KXjJ16bHTlyUy+UABALBqFGjvvrqq3bt2qHZ1dfX24hbGTyvRwNCWb0V3yC/vp5VqigeFwTxazQIgiAIgiCIPyXqjM47n1+eOWJ+6vV7aru2JsO9nAGc/P7hwYMH79y5c/r06TZt2qB5GRoa3nhaUNamh/nLOmi9VNfmFz8Wgn40ep3x0D5G3r0EXdtRXA4IQoMGQRAEQRAEoQuhwxffWF+/p/5wOHfFVMre6haAT8a2X/uN3d5D17744otdu3aheXl5eR0/fvxkn+pxVQaCOhUAuQHnlKX8+U8yL5OOsozbsozbxV8liPo7Gg3rY+TVU+BgDQ4F4p+Nxj/bgwcP0LLdvXsXhP7u3r0LgiAIgnjTjh47a2LEXzLJ2N6qFhr2Zk+WjO905JTg6NGju3btQvNavXr15cuXI1KO3HQe+G5rRwCXXt478dPl1q1bbzx4oF0Ft+bM1VdpN2tS8mpS8rimhqIBnY2H9TX0cObbtQZF4Tdqa2tDQ0MBbN68WSgUgvg7okEQBEEQf0ipVPJ4PLyeWq1mWZbL5YIg/u7KysqGvtupS9tnaKBLqwduPY2SM8tQcw2CDqBNQXGhgxs3bixdujQlJQWAp6fnxo0bnZ2doY9evXodOXIkJCTkxI3LJ3AZGs7Ozjt27OgrGQRAPGqg8mnZq7T86jNXZRm3qs9eqz57jW5lInLrauzb1/BdJ15bC2ikpqbOmzfvxo0b0Ni5c6ezs/O2bds8PDzQKFVVVQDEYjGIFoYGQRAEQbxGYmLihg0bCgsLnZ2d16xZ07dvX/xafX392rVrDx8+rFQqfX19w8PDDQ0NQRB/XxwO55VMUa+m+VwFtOrr2Vc15RyKRa43eJYwsIeoC0TdIeoKAzvwrcAxwG98/vnn69evr6+vp7kcAGfOnDl//nxoaOiaNWugj06dOvXu3fvBgwe1tbUAhEJh7969O3XqBC2ejbnpeInpeIlCWvwqNa/67DXZ5TtVJ7KrTmTTbcwM3+lu7Nv3vrh+7ISxJSUlBjRPXq8EIKB5N27cGDt27Llz53r37g2dZWZmjhs3rrCwEFrt2rU7dOiQm5sb9PHixYuRI0fm5OSo1WoAHA6nf//+x48ft7Kygj6Ki4v9/f2zs7NVKhUALpfr6uqamJhoaWkJfZSUlPj7+2dlZalUKgBcLnfAgAGJiYmtWrWCPkpKSvz9/bOyslQqFQAulztgwIDExMRWrVpBHyUlJf7+/llZWSqVKjQ0FPqgQRAEQRC/Jzc3NygoaNWqVR4eHl9//fXkyZN/+OEHU1NTNLBp06bt27fv27dPJBLNmzevvr5+x44dIIi/L3t7+/Qr99MfSrwcf4RW+n379J/yO3UwhrAT5IWoTEdlGn7BAc8UgvYQOkLUDaJuEHaCoB1ok/37D6xdu9bUxCBqhadrxyIA2Q/bLlibvnbtWkdHxylTpkA3xcXFI0eOzMnJsbEyCfLvCuDk9w/i4uJu37596tQpS0tLNMC3teRP8TKbPFj+4Pmr7/Oqz16VXblXeeSHyiM/fFKfUVJdAoBl671sTQCkF1YDKCkp+fTTT0+dOgXd5Obment719bW0hyql70RgNyCmsLCQm9v78zMzF69ekE3L1++dHJyKi0t5XDgZGsA4NaTuuzsbCcnp5s3b7Zu3Rq6KS4udnJyKi4u5nDQ3VYA4PYTeWZmppOTU35+vqWlJXRTUlLSvXv34uJiDgfdbQUAbj+RZ2RkdO/e/ebNm61atYJuSkpKunfvXlxczOGgu60AwO0n8oyMjO7du9+8ebNVq1bQTUlJSffu3YuLizkcWIq50BMNgiAIgvg9+/btc3d3X7x4MYCOHTt269btzJkzEyZMgJZSqdy7d+/q1avff/99ABs2bJg8efKqVassLS1BEH9TISEhixcv/mjdrcjlA1w63AFw5XGXhRF5AOYuWo3es6B4jtqHkN2G7CZkd1H3CK9uoiYX/4cjAr8NhB03r88EsH+t88jeGdDo2lpqGu7uP/fipk2bpkyZAt188cUXOTk5wWN6rwiSd7K4A+D+eNu1cR33H81ZuXJlTEwMfouiBJ2sBZ2szT4corhbVH0htyb5esaJgwA8OxivmyIa6F0D4PKF1p99U5dSUHnh/Hn5rSeUgE8JaIrPo/g0xeNSNBdcDsWhQFFo4IMPPqitre3rYLTlA8NBXjUAfrjYetF3r64+qJk4cWJ+fj504+/vX1pa6mwnjJxq6vluFYCUS9YLYytuPCr19/fPzMyEbkaNGlVcXOxkZxA1zcxTUgUgJc18wb7y/EfFo0aN+uGHH6Abf3//4uJiJzuDyGlmnpIqAClp5gv3lec/Kvb39//hhx+gG39//+LiYic7g8hpZp6SKgApaeYL95XnPyr29/f/4YcfoBt/f//i4mInO4PIaWaXHpYooR8aBEEQBPF7Ll++PGLECGiYmZn17ds3MzNzwoQJ0Hr8+PH9+/cHDRoEjQEDBiiVytu3b1taWoIg/qYWLFhw8+bNr7/+2m/299atjQE8e/k9gBkzZnz88cfgcGDQEQYdYTYEP2ProSyDXArZXchuQnYbtQ+geIa6h7fuy1y6coZ0vYkGhnS+4tLd8PrNG3jwCSg+ODxQfFA8cPigeODwQfFA8cHhgeKB4oPDO3zoWyND3rJxsk4WhdDoZCFdNr7D0TO8I4cPxmxaCFCgKPz/KIACRQEUAAqUwJ4SzOxpMdVZLf6cBtZNM3D3roaG+9DqdRxDj7VQqZSPxy4BzaF4NMXjcvg8is+DAY8j4FMGPI4Bj2Mg4Aj5EPI4QsG9u7e5HGwOEr3rXQ2Nd4dWb+Yaeq+puXvnliwtDRyK4lCgOOCA4lDgUKA4FIcCRYHDoTgUOACH82NONoeDrR+aDPashIa3V2UUx8SHqf0xJ1v55C7+i0JDFIWGrmRncTjY+qHYy7MSGt6DK7dSYh+m7kp2Vv3Te9DNlewsDgdbPxR7eVZCY8jgyq0csc8XdVeys+qf3YdurmRncTjYOl3s5VEJjSGDK7dyxD5f1F3Jzqp/dh+6uZKdxeFg63Sxl0dl+iPoiwZBEARB/IZKpSopKbGxsYGWpaVlUVERGigtLeVyuebm5tAw0Xj58iUaYBgGDXzzzTdt27YNCwtD08jlcgACgQBNI5fLAQgEAjSNXC4HIBAI0DRyuRyAQCBA08jlcgACgQBNI5fLAQgEAjSNXC4HIBAI0DRyuRyAQCBA08jlcgACgQCN0qpVq/fffz8nJ6e4pARAmzZt+vfv36pVq88++wx/whFqW0pdQ6kqlPWHK2S8Dd8qQeH/YZUVVfXKepZZFw3dlJQqHdpSB08XUBT+i2UfWJmqHhSVM/P7ABT+Hwr/D4UG1GrYWlNnpRXJ+/BfLFvRrjUlfc7G9TmBn7Fg8X9YsPiFGpABMvyXSsXatqEuSsu/34f/YtmK9q0p6XN2fcxQ/BEKWvX1ats2VMrDstQC/BfLlnVoTUmfq9cs7w3d1NerbNtQqQ/LLhXgv1i2rENrSvpctXpJL+imvl5l24ZKfVh2qQD/xbJlHVpT0ueq1Z/0hG7q61W2bajUB2WXHuK/WLasQ2tK+ly1+pOe0E19vcq2DZX6oOzSQ6RcU9UbpkEfNAiCIAji97Asi19Tq9X4DYqi0IBarcbrVVVV4U3Izs4GIJFI0DTZ2dkAJBIJmiY7OxuARCJB02RnZwOQSCRomuzsbAASiQRNk52dDUAikaBpsrOzAUgkEjRNdnY2AIlEgqbJzs4GIJFI0FjOGmlpaQAkEgl0RYEjYDkClrYIDQ0FIMcv0tLSAEgkEgBjgvAzOXQVGoqfKfCLtLQ0ABKJBEDgZPxMDl0tD8XPFPhFWloaAIlEAmDCVPxMAV0tD8XPFPhFWloaAIlEAmDCVPxMCV0tD8XPFPhFWloaAIlEAmDCVPxMCV0tD8XPFPhFWloaAIlEAmDCVPxMCV0tD8XPFPhFWloaAIlEAmDCVPxMCV0tD8XPFPhFWloaAIlEAmDCVPxMCV0tD8XPFPjFw9JvOOWF0AcNgiAIgvgNLpdrbGxcU1MDLZlMZmpqigaMjIxUKlVtbS00lEqlXC43NjZGAwzD4DcYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTMAwDgGEYNA3DMAAYhkHTCAQC6IkG8eZUV1dXVlYaGBhYWFhQFAXib0GlUpWUlCiVSnNzc5FIhBamurq6srLSwMDAwsKCoii0JCqVqqSkRKlUmpubi0QitDDV1dWVlZUGBgYWFhYURYH4jS5duly9ehUaLMs+ePBg8uTJaKBt27bm5uZ37tzp1KkTgIKCgvLy8o4dO4IgCIJowWgQTaZSqb777rsDBw5cvXq1qqqKz+c7ODiMGjUqJCTEysoKxF/WnTt3YmJiTp8+/fjxY5VKZW5uPnDgwBkzZrz//vt421Qq1XfffXfgwIGrV69WVVXx+XwHB4dRo0aFhIRYWVnhbbtz505MTMzp06cfP36sUqnMzc0HDhw4Y8aM999/H2+bSqX67rvvDhw4cPXq1aqqKj6f7+DgMGrUqJCQECsrKxANBAYGzpo1Kz8/38nJKSkp6e7du35+fgCOHj2qVCqHDRtmZmbm6+u7d+9eT09PPp+/d+9eDw8PR0dHEARBEC0YDaJpnj17Nn369NOnTzs5OQUFBXXs2LGkpCQrK2vNmjX79u2Ljo729/cH8Re0a9eu5cuX19XV+fr6TpkyxcjI6NatW2fOnBkxYsTkyZNjYmIMDQ3xljx79mz69OmnT592cnIKCgrq2LFjSUlJVlbWmjVr9u3bFx0d7e/vj7dn165dy5cvr6ur8/X1nTJlipGR0a1bt86cOTNixIjJkyfHxMQYGhriLXn27Nn06dNPnz7t5OQUFBTUsWPHkpKSrKysNWvW7Nu3Lzo62t/fH4RWQEDA+fPn33nnnW7dul2/fv2rr77q0qULgPv37+/YscPX1xfA2rVrx48fP3DgQB6PV1dX980331AUBYIgCKIFo0E0QXl5eUBAwE8//bRr165p06bxeDxoZWRkzJ8/f/z48fHx8X5+fiD+UmJiYkJCQvz8/DZs2ODk5ASt6urqyMjIlStXVldXHz58mKZpNLvy8vKAgICffvpp165d06ZN4/F40MrIyJg/f/748ePj4+P9/PzwNsTExISEhPj5+W3YsMHJyQla1dXVkZGRK1eurK6uPnz4ME3TaHbl5eUBAQE//fTTrl27pk2bxuPxoJWRkTF//vzx48fHx8f7+fmB0OBwODt37pw3b96zZ88cHR3t7OygEaghEokA2Nrafv/999euXVOpVL169TIxMQFBEATRstEgmuCzzz7Lzs5OSEgYOXIkNOrq6ng8HpfLdXd3T0pK8vX1/fjjj93c3MzMzED8Rdy6dWv58uXDhw8/fPiwUCgEoFQqVSqVgYGBsbHx559/bmZmNn/+/MjIyCVLlqDZffbZZ9nZ2QkJCSNHjoRGXV0dj8fjcrnu7u5JSUm+vr4ff/yxm5ubmZkZmtetW7eWL18+fPjww4cPC4VCAEqlUqVSGRgYGBsbf/7552ZmZvPnz4+MjFyyZAma3WeffZadnZ2QkDBy5Eho1NXV8Xg8Lpfr7u6elJTk6+v78ccfu7m5mZmZgdBy1kADHTt2RANCodDd3R26YRgGbwLDMHgTGIbBm8AwDN4EhmHwJjAMgzeBYRi8CQzD4E1gGAZvAsMweBMYhsGbwDAM3gSGYfAmMAyDN4FhGLwJDMPgTWAYBm8CwzB4ExiGwZvAMAz0RINorIcPH+7fvz8kJGTkyJEArl27Fhoampuba2FhMX/+/Dlz5lhbW3/11VdDhw6NjY1dtGgRiL+Ibdu2qVSqTZs2CYVClUq1bt26AwcOyGSyQYMGbd68uX379nPnzj1x4kR0dPScOXOMjIzQjB4+fLh///6QkJCRI0cCuHbtWmhoaG5uroWFxfz58+fMmWNtbf3VV18NHTo0NjZ20aJFaF7btm1TqVSbNm0SCoUqlWrdunUHDhyQyWSDBg3avHlz+/bt586de+LEiejo6Dlz5hgZGaEZPXz4cP/+/SEhISNHjgRw7dq10NDQ3NxcCwuL+fPnz5kzx9ra+quvvho6dGhsbOyiRYtAEARBEH9TNIjGOnfuXG1t7YwZMwAUFRWNHj1aKpUCePHiRUhIiFAoDA4OHjJkiIuLy/HjxxctWgTir0ChUJw6dWrEiBFdunQBsGrVqjVr1kDjyJEjT58+vXjxokAgCAkJGTVq1JUrVwYPHoxmdO7cudra2hkzZgAoKioaPXq0VCoF8OLFi5CQEKFQGBwcPGTIEBcXl+PHjy9atAjNSKFQnDp1asSIEV26dAGwatWqNWvWQOPIkSNPnz69ePGiQCAICQkZNWrUlStXBg8ejGZ07ty52traGTNmACgqKho9erRUKgXw4sWLkJAQoVAYHBw8ZMgQFxeX48ePL1q0CARBEATxN0WDaKzc3FxLS0tHR0cA8fHxUqkUWizL7tmzJzg4mKKoPn36nDx5UqFQ8Pl8EC3ey5cvi4qKXFxcANTV1e3fvx8NZGRkpKamDh06tHfv3jRN5+fnDx48GM0oNzfX0tLS0dERQHx8vFQqhRbLsnv27AkODqYoqk+fPidPnlQoFHw+H83l5cuXRUVFLi4uAOrq6vbv348GMjIyUlNThw4d2rt3b5qm8/PzBw8ejGaUm5traWnp6OgIID4+XiqVQotl2T179gQHB1MU1adPn5MnTyoUCj6fD4IgCIL4O6JBNFZVVRWfz6dpGkB5eTl+rbS0lGVZiqJ4PJ5arWZZFsRfgUwmUyqVIpEIgFwur66uxq+VlZUBoGmaw+GwLIvmVVVVxefzaZoGUF5ejl8rLS1lWZaiKB6Pp1arWZZFM5LJZEqlUiQSAZDL5dXV1fi1srIyADRNczgclmXRvKqqqvh8Pk3TAMrLy/FrpaWlLMtSFMXj8dRqNcuyIAiCIIi/KRpEY3Xq1Ck+Pr60tNTa2nrQoEEcDketVkNLIpFQFAVAKpWam5vz+XwQfwWtW7c2NTW9f/8+ALFY7OrqevbsWWgZGRn169cPwNOnTxUKhaWlJZpXp06d4uPjS0tLra2tBw0axOFw1Go1tCQSCUVRAKRSqbm5OZ/PRzNq3bq1qanp/fv3AYjFYldX17Nnz0LLyMioX79+AJ4+fapQKCwtLdG8OnXqFB8fX1paam1tPWjQIA6Ho1aroSWRSCiKAiCVSs3Nzfl8Poj/jdra2oCAgEOHDhkbG6NRampqtm7dmpqaqlKpPD09FyxYYGxsDP09efJky5YtV69eNTQ0HDFixKxZszgcDpogLS3tyy+/TExM5PP50N/XX38tlUqhRVHU6tWr0SjHjh2LjY2tqqoaNmzYokWL+Hw+9HT69OnMzEz8Ws+ePceOHQs9yWSyqKioixcv0jTt5+f30Ucf0TQN/RUXF2/dujUtLU0sFk+YMOGDDz6AnliWDQgIiIqK6tChAzTkcvmWLVvOnz8vEomCg4PHjBkDHbAsGxAQEBUV1aFDBzTw8uXLDz/88Pjx4xwOBzpgWTYgICAqKqpDhw7QKC4ujoyMzMrKomna19c3JCSEz+fjz7AsGxAQEBUV1aFDB2jcunVr69at+fn55ubm48aNmzhxInTAsmxAQEBUVFSHDh3wawkJCbGxsYmJidABy7IBAQFRUVEdOnSAxubNm8vLy6HF5XIZhsGfYVk2ICAgKiqqQ4cO0Dpw4MDBgweVSuXo0aPnzJlDURT+DMuyAQEBUVFRHTp0ALB///4HDx7g14YOHfrOO+/gD7EsGxAQEBUV1aFDB2iUlpZu3rw5MzNTJBIFBgZOmTKFoij8GZZlAwICoqKiOnToAI1Hjx5t3bo1JyendevW06ZNGz58OP6QUqmMiYk5c+ZMbW2tm5vbggULrKysAMjl8i1btpw/f14kEgUHB48ZMwavR4NorHfffXfVqlXJycnBwcHe3t5LlizZvHlzfX09AIlEsnr1agCFhYWXLl2aMGECRVEg/gpMTU379u175syZL7/8UiAQbNy48cmTJzdv3gRgaGi4bt06R0dHAEePHhUIBC4uLmhe77777qpVq5KTk4ODg729vZcsWbJ58+b6+noAEolk9erVAAoLCy9dujRhwgSKotCMTE1N+/bte+bMmS+//FIgEGzcuPHJkyc3b94EYGhouG7dOkdHRwBHjx4VCAQuLi5oXu++++6qVauSk5ODg4O9vb2XLFmyefPm+vp6ABKJZPXq1QAKCwsvXbo0YcIEiqJA/A/IZLLY2NisrCw0wUcffZSenr5y5UqKoiIiIrKyshITEzkcDvShUCiCgoKEQuHcuXOfP3++ePHi8vLysLAwNFZ5efncuXPLysooikKj/PTTTwcPHuzVqxc0LC0t0SjffPPN9OnTw8PDTU1NP/vss5KSko0bN0JPHA7n8uXL0Hr16lVGRsahQ4egv1mzZmVnZ3/66ad1dXWff/55YWFhREQE9FRXVzdhwoT6+vq5c+c+fvw4ODhYoVAEBwdDZ3K5PCEhISkpKTIyElpLly5NTExcs2bNs2fPAgMD4+PjR40ahT8kl8sTEhKSkpIiIyPRQFVV1c6dO+/cuQPdyOXyhISEpKSkyMhIaKjV6ilTprx8+fKTTz6prq5etWpVbm7uvn378IfkcnlCQkJSUlJkZCQ0ysrKAgMDe/XqtWDBgvv37wcFBSkUiqlTp+IPyeXyhISEpKSkyMhI/JpUKp0/f76lpSV0IJfLExISkpKSIiMjoZWRkVFQUGBhYQENOzs7/Bm5XJ6QkJCUlBQZGQmtTZs2hYeHr127lmXZZcuW1dbWLl68GH9ILpcnJCQkJSVFRkZCQ6FQXL58GVplZWU//vjjsGHD8IfkcnlCQkJSUlJkZCQ01Gr1pEmTysvLP/744+Li4jlz5pSXly9cuBB/SC6XJyQkJCUlRUZGQqOkpGT06NH29vYff/zxjRs3Ro4cefLkSV9fX7xeWFjY3r17v/zySxMTk23btqWmpiYnJxsaGi5dujQxMXHNmjXPnj0LDAyMj48fNWoUXoMG0VgSicTFxWXdunV+fn6WlpYRERGBgYF5eXmtW7f28fHh8/kANmzYUFNTM336dBB/HTNmzJg4cWJMTMzChQt79OiRnp6ekpLy6tWr/v37d+3aFUBeXt6OHTtGjhzp4OCA5iWRSFxcXNatW+fn52dpaRkREREYGJiXl9e6dWsfHx8+nw9gw4YNNTU106dPR7ObMWPGxIkTY2JiFi5c2KNHj/T09JSUlFevXvXv379r164A8vLyduzYMXLkSAcHBzQviUTi4uKybt06Pz8/S0vLiIiIwMDAvLy81q1b+/j48Pl8ABs2bKipqeGkEewAACAASURBVJk+fTqI/4G1a9fu3Lnz+fPnJiYmaCypVHrkyJHjx4/7+PgA6NWrV79+/a5cuTJgwADo4+rVq9nZ2Tdv3rS3twdQXV19+PDhsLAwNNaSJUskEkliYiIa68GDB5988smyZcvQBEqlcv369dHR0TNnzgQgFou3bt1aW1srFAqhj2Ea0GBZlmGYHj16BAYGQk8vXrxITEyMj4/38fEBIBAIVq9evXbtWh6PB32cOXPm2rVrP/30U7t27QAYGhpGR0dPmTKFoijoIC4ubsWKFYWFhRRFQauwsHDfvn1HjhwZNmwYgGfPnm3dunXUqFF4vbi4uBUrVhQWFlIUhQbmzp179OjRkpISe3t76CAuLm7FihWFhYUURUHr6tWrZ8+evXbtWq9evQDY29uPGDFi5cqV9vb2eI24uLgVK1YUFhZSFAWtS5culZaWbtu2zczMDEBBQcGhQ4emTp2K14uLi1uxYkVhYSFFUfg1lUo1b968wMDAlJQU/Jm4uLgVK1YUFhZSFIUGCgoKli5dOmHCBOgmLi5uxYoVhYWFFEVBq7y8fNOmTXv37h05ciQAlUqVlJS0aNEiiqLwGnFxcStWrCgsLKQoClozNaDBsuysWbNGjhw5aNAgvF5cXNyKFSsKCwspioLWrVu3zp49e+3atd69ewOorq7+7rvvFi5ciNeLi4tbsWJFYWEhRVHQOnToUE1NTWxsrImJydixY1UqVXR0tK+vL16juro6Li4uOjp60qRJANzd3Xv27Hn+/Pl+/frt27fvyJEjw4YNA/Ds2bOtW7eOGjUKr0GDaCwejxceHj58+PDg4OA9e/ZYW1v314CGWq2OiIiIjo5esGCBq6sriL+OCRMmHD58eOnSpa1atQoKCjIzMxs9ejS08vPzJ02aJBQKV61ahWbH4/HCw8OHDx8eHBy8Z88ea2vr/hrQUKvVERER0dHRCxYscHV1RbObMGHC4cOHly5d2qpVq6CgIDMzs9GjR0MrPz9/0qRJQqFw1apVaHY8Hi88PHz48OHBwcF79uyxtrburwENtVodERERHR29YMECV1dXEP8DkydPDgoKysvLCw4ORmM9ffrU29u7d+/e0LCxsRGJRLW1tdBTeXl5eHi4nZ0dNHg8Hp/PR2PFxsbm5+evWLEiMTERjcKyrFQq7dy587lz59Rqdc+ePa2traG/O3fu3Lt3b/jw4QqNAA00TUZGxsGDBy9fvgz98Xg8oVBYVVUFjerqakNDQ4qioKf79+/b29u3a9cOGi4uLosXL37x4kWbNm2gA4lEkpKSIpVKvby8oHX9+nUDAwN3d3do+Pn5HThwoLKyUiwW4zUkEklKSopUKvXy8kIDy5YtW7p06aVLl9asWQMdSCSSlJQUqVTq5eUFLalU6u/v361bN2i0bdtWoVDU1dXh9SQSSUpKilQq9fLyglZNTc2yZcvMzMygwdfAH5JIJCkpKVKp1MvLC7+2ceNGlmW7dOmSkpKCPyORSFJSUqRSqZeXF7Tq6uqePn1qbW199uxZDofTr18/c3Nz/CGJRJKSkiKVSr28vKB19epVlmW9vb1ra2tZlp2ngT8kkUhSUlKkUqmXlxd+z7Fjx27durV9+3b8IYlEkpKSIpVKvby8oMXn83k8XlVVFTSqq6tFIhH+kEQiSUlJkUqlXl5e0MrPz+/cubOJiQk0BgwYsGfPnrq6OgMDA/ye4uLivn37uri4QMPKysrU1PTVq1fXr183MDBwd3eHhp+f34EDByorK8ViMX4PDaIJvL29d+/ePWvWrAEDBixevNjX19fKyurVq1c5OTnbt28/f/78pEmTNmzYAOIvhaKovXv3jh8/fvLkyceOHZszZ46zszOfz3/y5ElCQkJUVBRN03Fxcd26dcPb4O3tvXv37lmzZg0YMGDx4sW+vr5WVlavXr3KycnZvn37+fPnJ02atGHDBrwNFEXt3bt3/PjxkydPPnbs2Jw5c5ydnfl8/pMnTxISEqKiomiajouL69atG94Gb2/v3bt3z5o1a8CAAYsXL/b19bWysnr16lVOTs727dvPnz8/adKkDRs2gPjfsLW1BVBQUIAmcHNzS0pKgoZarY6JiWnTpk3v3r2hp/c0AGzYsOHhw4fffPPNt99+i0a5cePGwoULz5079/LlSzRWVVVVUVHR3LlzbWxsampqysrKoqOjx40bBz09evSodevW+/fv3717d01NjZub24YNG7p27YrGUqvVn332GcMwpqam0J+5ufnatWuDgoJSU1Pr6ur2799/+PBhmqahJzs7uwcPHkilUltbWwCXL1+uq6srKSlp06YNdGBrawtAJpOhgcePH1taWhoZGUHDxsamsrKyrKxMLBbjNWxtbQHIZDL8mq2tLYCMjAzoxtbWFoBMJkMDYzSgoVAotm7d6urq2qlTJ7yera0tAJlMhgaCgoIAKBSKjRs33r9//9y5c4cPH8YfsrW1BSCTyfBrqampkZGRGRkZycnJ0IGtrS0AmUyGBp4/f15cXBwYGGhra1tWVqZSqfbs2ePt7Y3Xs7W1BSCTydDAvXv3zMzMvvjii//85z/19fWDBw/euHFju3bt8Hq2trYAZDIZfs+rV69WrFixbds2Pp+PP2RrawtAJpOhAUdHR4ZhAgMDP/jgg/Ly8lOnTiUmJuIP2draApDJZGigc+fOZ8+eLS8vNzMzA5CRkVFRUVFZWWlgYIDf07Fjx1OnTkFr7969MpnM3d391KlTlpaWRkZG0LCxsamsrCwrKxOLxfg9NIimmTJlir29/cqVKxcvXvzJJ58YGhrK5XKFQmFnZ7dt27aPPvqIw+GA+KsxNTU9duxYeHj4rl27jh49KhQKaZqurq7m8Xh+fn7h4eHdunXD2zNlyhR7e/uVK1cuXrz4k08+MTQ0lMvlCoXCzs5u27ZtH330EYfDwVtiamp67Nix8PDwXbt2HT16VCgU0jRdXV3N4/H8/PzCw8O7deuGt2fKlCn29vYrV65cvHjxJ598YmhoKJfLFQqFnZ3dtm3bPvroIw6HA+KvIDMzc9WqVXfu3Nm9e7epqSkahWXZFy9eVFdXKxSKgoIC6E8ul8+bN2/t2rUuLi4nT54EwLIs9Pfy5UtXV9fFixcPGzZMLpdHREQsWLBg8ODBlpaW0IdMJnvy5ElOTs7Ro0e5XO7KlSs//PDD1NRUHo+HRomPj5fJZIGBgWisBw8eWFhY0DTN0ygoKID+3nvvvV69egUEBAQFBUml0vj4eAAURaEJ1Go1GqAoSq1WK5VKvG3nzp1btWpVVVXV3r17eTweGqW+vr60tLSmpkYulz969MjNzQ16Kisrmzdv3tatWzt27IgmKCwsHDJkCMMwAwcOrKmpWb58+ccff/zjjz8aGBhAH9XV1bdu3ZJIJGfOnKmtrV24cOHcuXMTExPRWHv37u3YsePgwYPRKPX19QUFBWZmZnw+XyAQvHr1SiqVuru7Q0/jx4/fs2dPYGDg8OHDb9++nZ6eDoCiKPyZvLy81atXp6SkbN++3c7OTq1WowGKotRqtVKpxGvQIJpMIpFcvHgxNzc3Kyvr+fPnhoaGvXr1cnd3NzQ0BPGXJRQKV69evXDhwvT09Pz8fIVCYW9vP3DgwM6dO6MFkEgkFy9ezM3NzcrKev78uaGhYa9evdzd3Q0NDfG2CYXC1atXL1y4MD09PT8/X6FQ2NvbDxw4sHPnzmgBJBLJxYsXc3Nzs7Kynj9/bmho2KtXL3d3d0NDQxB/BTKZ7NNPP/3Xv/41b968/fv3W1lZobEoitq0aROAMWPGTJs2bezYsTY2NtDHmjVrDA0NHRwcTp8+XVpaSlHUuXPnhEKhl5cX9OHo6Hj27FloCASCmTNnrl+//qeffvL29oY+aJoWCoWbNm2ys7MDEB4e7uzsnJ+f37t3b+iPZdmtW7eGhIRwuVw0ypkzZ6Kjo69cueLk5ARg7NixQ4cO9fLy6tGjB/RhaGiYkJCwa9euzMzMTp06HTp0yMPDw8zMDE1gZGQkl8vVajWXywUgl8tpmhYKhXh7ysvLFy1alJSUtHjx4nnz5pmYmKCxRCLR5s2bAezcuTMsLMzf318kEkEfoaGh7u7uxsbGp0+frqurq6+vP3XqlJmZmZubG/TxzjvvnDlzBhpGRkZz5szZsWPHgwcPnJycoA8ej2djYxMREWFqagrgyy+/9PX1LSoqatu2LfQnl8t37NixZcsWNFZcXNzJkyezs7PbtWsHwMfHJyQkxNPT09raGvpo06bNqVOndu/enZmZ2bNnz02bNk2dOtXIyAivp1Kp1q5dGx4ePm3atCtXrtjZ2QEwMjKSy+VqtZrL5QKQy+U0TQuFQrwGDeJNoCiqtwaIvxdzc/ORGmh5KIrqrYEWydzcfKQGWh6KonprgPgL+uijj+7fv5+dne3k5ITGWr169Y0bNw4dOgQNZ2fn6urqyspKGxsb6KOuru7Ro0dLliwBoFarCwsLly9fvnTpUujp7NmzAIYNGwYNgUDA4/G4XC701K5dO4FAYGpqCg1TU1M+n69QKNAoOTk5eXl577//Phrr0aNHtra23bt3h0a/fv2MjY2Liop69OgBfUil0pqamrCwMGh88803Dg4OVlZWaAIHB4fnz5+XlJRYWVkBKCgosLKyatWqFd4SpVI5adIkmqZ//PFHW1tbNFZISIhSqfzXv/4FDWdn5+Li4levXolEIuhDLpfn5OSkp6cDkMlkjx49Wr58eVRUFPR06tQpDofj6+sLDQMDA44G9GRvby8SiYyMjKBhZmam1ECjJCcnK5VKLy8vNNbt27cdHR3btWsHjf79+5eXl7948cLa2hr6uHXrllqtXr16NTQiIiK6du0qEonweqGhoSdPnkxJSRk4cCC0HBwcnj9/XlJSYmVlBaCgoMDKyqpVq1Z4DRoEQRAE8Rfx448/Hjx48PLly23btq2oqIAGTdNGRkbQh6ur68aNG/Py8nr06MGy7KlTp2xtbdu3bw89bdSAxsmTJ+fMmXPx4kVLS0voicfjvf/++ykpKa6urgCOHz9uZGTUo0cP6KlHjx6tWrU6fPjwzJkzWZZNSEiwsrLq3LkzGiU+Pn7QoEGtWrVCY3Xr1u3OnTupqamenp4Azpw5U1tb6+DgAD2p1WpPT8/9+/f7+fmVl5fv2LFj7NixXC4XTdCnT582bdocO3Zs9uzZSqXy22+/HTJkiFAoxFuSnJyck5OTnp4uFosrKiqgIRKJ+Hw+9NG/f3+GYR4/ftyhQweVSnXixAknJycLCwvoKTY2Flq7NFJSUkxMTKCnioqKRYsWpaenOzo6siybkJDQvXt3BwcH6MnV1bWsrOzEiROjR49Wq9WHDx/u2bNn27Zt0SiHDh3y8vLi8/lorL59++7YseP69eu9e/cGcOrUKUtLy/bt20NPVVVVvr6+Z8+edXV1LSws3LNnz5IlS/B6jx8/3r59e3JycteuXSsqKqBBUVSfPn3atGlz7Nix2bNnK5XKb7/9dsiQIUKhEK9BgyAIgiCakYGBARrr+vXrcrncw8MDWkKhMDExccCAAdDHkCFD/Pz8PD0933nnnYqKitzc3JiYGCMjI+iJoihoURTF4/HMzMwoioKeBg8ePG7cOB8fHz8/v8rKyrS0tJiYGAsLC+hJKBQyDDNz5sxDhw6xLJudnb1r1y5TU1Poj2XZs2fPfvDBB2gCDw+PRYsW+fj4DB06VKFQpKSkrF+/3tHREXqyt7efNWvW6NGjhw8ffvPmTVtb28WLF0N/IpEIWkZGRmvWrJk6dWp6evrLly+Liori4+OhG5FIhN9D0zT0IRKJoJWVlVVcXOzi4gItMzOz77//3t7eHn9GJBJBa9y4cQcPHnR3d3d1dX327Nnjx49jY2M5HA50IBKJoEVRFBqgKEosFkM3IpEIWmPGjDl48KCHh4eXl9fz589v3Lhx4MABPp8PHYhEImhZW1uvWLFizJgxvr6+NTU19+/f//e//83j8aADkUiEBmpra1NTUzdu3Ag9iUQiaI0ePfrUqVPvvvuup6dndXV1Tk7Ojh07LCwsoAORSAStAQMGBAYGDhs2zMvLKycnZ+DAgVOnTsXr3bx5U6FQDB8+HFo0Te/du9ff33/NmjVTp05NT09/+fJlUVFRfHw8Xo8GQRAEQTQXKyur+Ph4LpeLRnF2ds7IyMCvmZubQ080TX/77bcpKSm3b982NTV1c3Pr2LEjmsbGxua7775Do1AUtXfv3kmTJl2/ft3ExCQqKsrR0RGNMmnSpL59+2ZlZVEUFRMT4+joiEapqqravHmzsbExmmbTpk0ffPBBbm4uTdORkZFOTk5olHXr1g0dOjQvL2/q1KlDhw41MDCAnoyNjZOTk4VCIbQmTpzo7Ox85coVoVDo4+NjaWkJHRgbGycnJwuFQvyao6NjbGwsdGZsbJycnCwUCqHh6+v73nvv4ddEIhH+jLGxcXJyslAohIaRkVFiYuL333//4MEDS0tLiURiY2MDHRgbGycnJwuFQvxGv379YmJioBtjY+Pk5GShUAgNgUBw6NChc+fO5efnDx48eNiwYe3atYMOjI2Nk5OThUIhtBYtWuTh4XH16lWhUOjh4dGuXTvowNjYODk5WSgUQqu4uHj//v02NjbQh7GxcXJyslAohAaPx9u3b9/MmTNv3LghEom+/vprBwcH6MDY2Dg5OVkoFEJr586dY8eOvXv37syZM318fLhcLl7PwsIiLS0NvyYUCgFMnDjR2dn5ypUrQqHQx8fH0tISr0eDIAiCIJpL9+7d0QQDBgzAG8Llcr018Ib06dMHTcDhcHw00GTdNNA0YrHY09MTb0J/DTSZhwYaq70Gfq2nBvTRXgO/4eLiAn2014CWu7s7GqW9BhowMDB47733oKf2Gvg9Li4u0Fl7DTQgEAje14A+2mvg1/pqQB/tNdBABw3oqb0GGqAoapAG9NFeAw1wOJyhGtCBi4sLXq+nBnRAgyAIgiAIgiCIfwwaBEEQBEEQBEH8Y9AgCIIgCIIgCOIfgwZBEARBEARBEP8YNAiCIAiCIAiC+Meg8c/m4OCAlq1z585Xr14FQRAEQRAEQbwJNAiCIAiCIAiC+MegQRAEQRAEQRDEPwYNgiAIgiAIgiD+MWj8s9nY2KBla9u27dWrV0EQBEEQBEEQbwINgiAIgiAIgiD+MWj8s5mamqJlMzMzA0EQBEEQBEG8ITT+91iWRUul1lCpVGiRVCoVy7IgGkWlgZZHpYUWSaVSAVCpVGh5VFpokViWBUEQBEG0eDSay+LFiysqKgCUl5cDePLkCbTu3LmD/7EuXbpAq3379gDMzMwAiMXiysrKZ8+ecblctDyVlZUmJiYffvjh/8cefABFcfB9AP7t7V7jDpYmClgRRbCCEjGKYjdG3zdqVGyJvUYsGKNRFHvsBTEG9UNjiy+WKGpijMaCLYjGDvYKogjccSDs3t1+MzdzMzjGRN0EUf/PAyAnJwfAvXv3YJeWloY3p7CwUBRFlFaSJD169EihUKD0sVgs6enp+fn5CoUCpY/JZAKg1+tR+iiVyuzsbAAsy6L0ycvLc3R0BCGEEFK6cSgRU6ZMmThxYmFhIUoZpVKZlZXl6enJsixKHwcHh6ioKLVajTcnLS0Ndvfu3QOQnZ0NICcnJyoqShRFlEoMw3h4eHh6eqL0KSwsnDx5siiKCoUiNzcXQHp6Ouxu3LiBN0qSJAAMw+DNqVq1Kuy8vLwAODs7A9Dr9V999ZWnpyfLsih9HB0dQQghhJR6HP59DMMA0NiglLFYLKwdSh/Whud5vDkNGzaEXcOGDWEXFxen0WhEUURpxdqg9BFFUaVSbdiwAeQFzp07B7tz587BrkePHqIosjYofRiGASGEEFLqcSCEEEIIIYS8NzgQ8lpcXV1BXldOTg7Iq8vNzQUhhBBC5OFACCGEEEIIeW9wIOS1VKhQAeR13bt3D+TVpaengxBCCCHycCCEEEIIIYS8NzgQQgghhBBC3hscCCGEEELeG1euXCkqKgKg0Whq1KgBQt4/HAh5LX5+fiCvKy0tDeTV3bhxA4QQIk+vXr3Onj3LMExkZOT8+fNRagwePPj06dMVK1bcsmWLWq3GS/j++++XLVvGcVxcXFydOnVAyMvhQAghhBDyztm4ceOJEycAsCy7aNEilmVhIwgCAEmSUJrs2bNn9erVkiSNHz9erVbj5XTr1u2bb765cuXK+PHj9+7dq1AoQMhL4EAIIYQQ8s7Jy8uLjY0FUKFChQULFrAsCxu1Wg2AYRiUGkVFRVOmTJEkqXbt2p07d8ZL02g0kZGRAwcO3Ldv3+bNm3v16gVCXgIHQgghhJD3xubNm81mMwB3d3eUDmvXrj1z5gyAoUOHqlQqvIpu3brNmDHjzp07s2fP7tKli0ajASF/hwMhhBBCyL9p69atgiAAYBimR48eWVlZW7ZsuX79+uLFi48ePXrv3j0AHMd16dKFZVnYXLx48cKFC5IkMQwTGhpavnx5ANu2bSsqKgLAMEyPHj3u3Lmzd+/e69eva7XaDz74oF27diqVCoDZbDYYDBaLBTaSJN25c8fVBkBWVpYgCABYlvXw8ACQlJR09+5dAAzDdO3aNSMjY+vWrbdu3SpXrlzr1q2Dg4MB5OfnJyYmXrx4URTFmjVrdujQwdXVFc9KT08/evTozZs3LRaLj49PaGhohQoV8HcEQVi2bBkADw+P8PBwPOvatWvHjx+/e/euKIre3t4NGjQICgpiGAZ2jo6OvXv3njVr1uXLl7du3dq7d28Q8nc4EEIIIYT8mxITE7///nsA9evXr127drdu3a5cuRIQECBJ0rVr1wYMGADAx8enS5cusDMYDL169ZIkSalUnj9/HjZ79uyJj48HULduXZZlR4wYkZWVBbtmzZpt3rzZ09MzLS2tVatWubm5sLl//369evUCAwOPHj1qNps/++yzGzduAJg7d+748eMB3L17t1evXgB0Op0kSWPHjs3MzITN1KlTJ0yYEB4e/vnnn6ekpMDOz89v06ZNQUFBsJEkac6cOQsWLMjJyYEdz/NjxoyJiopSKBR4sf3791++fBnAxx9/7OrqCjuTyTRhwoQ1a9YUFhbCjmGY5s2bL126tFatWrDr2bPn3LlzzWbzqlWrevfuDUL+DgdCCCGEkBJRUFDQr1+/K1euwE6SJNhYrVY8S5IkAGazGc8RRfHzzz8vLCxEMYcPHx43btzGjRsBFBQUFBYWwi4/P18QBNgIgoAXKCoq6t+/f1FREezMZvOsWbMSEhLS0tJQTFpa2qhRow4fPqxQKABERUXNmjULNgqFAoDVajUYDNHR0QaDYdGiRXixjRs3wqZLly4oZsyYMatXr8azJEk6ePBg586dDx065OXlBZuAgIDAwMDk5ORjx45duXLF398fhPwlDoQQQgghJeLOnTsFBQVlypSpXLmyh4cHXtfly5ddXV2jo6P9/Pxu3LgxZ86cJ0+eANi9e/ejR48qVKhw7NixX375JTIyEoCnp+eOHTt4nsffMZvNOp1u5syZ1apV+/nnn1euXAlAkqS0tLS2bdv27dtXFMU5c+ZcuXIFwIkTJ27evOnr63vmzJn58+fDZvTo0YMHD5Ykae3atfPnzwewdOnS//znP2FhYfgzhYWFR48eBeDk5NSwYUPY3bx5c8OGDbAZM2ZM165dVSrVqVOnJkyYkJeXd+3atVWrVk2dOhV2oaGhycnJFovl0KFD/v7+IOQvcSCEEEIIKREFBQUjR46cMmWKu7s7ZOA4bvv27c2aNYONUqkcNWoUAKPRmJGRUbdu3Vq1aiUlJcGG47igoCClUomXEBsb26tXLwDt2rVLSkq6ePEigCpVqmzcuNHNzQ2Am5vbxx9/DMBisWRmZvr6+q5bt04QBAAhISHz5s1TKpUAvvnmm3Pnzv3yyy9WqzUuLi4sLAx/5tatW+np6QAqVark5uYGuxs3bhQWFgJQqVQDBw4MCAgAUL9+/StXrmzbtg3ApUuXUEyDBg1gc+LEiWHDhoGQv8SB/BPMZvPJkyePHz9+//59JyenoKCgZs2aubm5oXR48ODBb7/9dv78+cLCQh8fn9DQ0KCgIIZhQMh7yWw2nzx58vjx4/fv33dycgoKCmrWrJmbmxsIIf+yMmXKTJkyxd3dHfL4+/s3bdoUdsHBwbArLCzE69JoNC1atICNWq12dHSETcOGDd3c3GBTrlw5PCspKQk2H330UWZmJsMwACRJat++/S+//ALgxIkToigqlUo85/bt21arFUCFChUYhoEdy7KwEQTh008/bd++/UcffRQSEhITE7NgwQIALMuimCpVqsDm+vXrIOTvcCCy/fTTT1FRUSkpKWq12tnZuaCgIC8vr2zZshEREV9++aVSqcSbYzQao6Ki1q5dazQanZ2dVSpVdna2xWJp2bLl7Nmzg4ODQch75qeffoqKikpJSVGr1c7OzgUFBXl5eWXLlo2IiPjyyy+VSiUIIf+aChUquLu7QzaWZRmGgR3DMPiHKBQK/CWGYVBMYWFheno6bKZPnz5z5kw8JyMjIysry9PTE8/JzMyETZkyZVBMvXr1fH19r1+/DuCKzcKFC8uVK9e4ceP27dt/8sknrq6uKMbZ2ZlhGEmSsrKyrFarQqEAIS/GgcizYsWKiIiIatWqxcfHt2zZ0t3dvaCg4Ny5c8uXL580aVJycvKGDRt0Oh3ehMzMzC5duhw7dqx///6DBg3y9/dXqVTp6emJiYnz5s1r0aLFunXrOnfuDELeGytWrIiIiKhWrVp8fHzLli3d3d0LCgrOnTu3fPnySZMmJScnb9iwQafTgRDy72AYBu8WURSLiopgY7VaJUlCMQqFAoCjo6PJZMJf4jgOxbi6um7bti06Ovrnn39++vQpbB4+fLjNZubMmatWrWrZsiXslEolwzCSJIGQl8CByJCYhRAf8gAAIABJREFUmBgREdG5c+fvvvvOxcUFNlqttoVNTExMRETEmDFj4uLiUOIsFkvfvn3PnDmzffv2Tp06wa5q1aqjR4/+73//26NHj/79+/v4+NSrVw+EvAcSExMjIiI6d+783Xffubi4wEar1bawiYmJiYiIGDNmTFxcHAghJU6ywdtGrVbrdLqcnBwAy5Yta9euHf5M+fLl8Wc4joON0WjEs+rUqbN9+/a7d+8eOHBg586dR44cycnJgc2tW7fGjRuXnJzMcRxs8vPzrVYrAJZlGYYBIX+JA3ldRUVFkydP9vf3j4uLc3Z2BnDo0KELFy64ubl17NjR0dFx5MiR9+/fnzdvXp8+fUJDQ1Gyvv/++59//nnlypWdOnUC8Pjx4927d+fn54eEhDRo0KBKlSrr168PCQmZOnXqzp07Qci7rqioaPLkyf7+/nFxcc7OzgAOHTp04cIFNze3jh07Ojo6jhw58v79+/PmzevTp09oaCgIISUrOzs7KyurXLlysDl79izeBiqVqkqVKvfv3wdw/fp1X19fFGM2m2HDcRz+jJeXF2yePHmCYhISEsxmMwAnJ6d+Nk+ePDl8+HBMTMyhQ4cAXLly5dGjR15eXrDJycmBTdmyZRmGASF/iQN5XUeOHDl//vymTZucnZ0BjBw5MjY2VpIkACEhIQkJCeXLl4+MjFy9enV8fHxoaChK1rp16+rVqzdgwAAAZ86c6dat240bNwCo1eq5c+eOGjWqWrVqERERs2bNunr1avXq1UHIO+3IkSPnz5/ftGmTs7MzgJEjR8bGxkqSBCAkJCQhIaF8+fKRkZGrV6+Oj48PDQ0FIaREODs7wyYvL2/evHkjR47U6XT79++fOHEi/iFPnz7Ny8tzdXXFv+Pjjz8+evQogG3btg0bNszPzw+A1WqdMmXKhg0bJEmqXLnywYMHWZbFc6pWrapUKkVRvHv3rsViYVkWNv/73/+2bt0KIDAwMCgoyNPT083NrXPnzgUFBYcOHQLAMAyKuXbtGmxq1qwJQv4OB/K6Dh8+rNPpWrRoAWDfvn2xsbGSJMHm5MmT06dPj4uL8/DwaNq06YkTJ6xWq0KhQEnJzs4+e/bskCFDOI4D8OWXX964cQM2RUVFX3/9dbt27fz8/Dp27BgdHZ2cnFy9enUQ8k47fPiwTqdr0aIFgH379sXGxkqSBJuTJ09Onz49Li7Ow8OjadOmJ06csFqtCoUChJB/X0hIiLOzc25uLoDFixfHxsYqlcr8/HzIxjAMbLKysoYOHeru7r5ixQr8C/r167dy5crbt2/fv3+/ZcuWbdq04TjuypUrSUlJsJkxYwbLsvgz5cuXr1q1ampq6p07d+7evVulShXYdO7ceevWrQDOnj0bGhpar149nU537969EydOwKZ+/fqenp6wO3HiBGwaN24MQv4OB/K6bt265ebm5urqCuDkyZOSJKGYY8eOSZLEMIy3t/epU6dEUVSr1Sgpjx8/NhqNvr6+AIxG45kzZ1BMQUHB2bNn/fz8ypYtq1KpsrOzQci77tatW25ubq6urgBOnjwpSRKKOXbsmCRJDMN4e3ufOnVKFEW1Wg1CyL/P29t7oo3VagUg2Oj1+sWLFw8aNAgyNG3a1MXFJScnB0BCQkJQUBD+HR4eHmvWrOnZs2dmZuaDBw/i4+Nhx3Hc119//dlnn+EFWJZt1apVamqqKIpJSUlVqlSBTXh4+G+//bZq1SoAN2xQjJeX15w5cxiGgY3ZbD5+/DgAnU7XtGlTEPJ3OJDX5erqWlhYKIqiUqn08PDAs9zd3RmGAVBUVMSyLMMwKEF6vV6lUhmNRgBqtdrFxSU3NxfFuLu7AxAEwWq1KhQKEPKuc3V1LSwsFEVRqVR6eHjgWe7u7gzDACgqKmJZlmEYEEL+OeXLlw8PDwfA8zyeM378+ICAgLVr16ampnIcV79+/REjRqhUql69egFgGEalUsHG29s7PDwcgJOTE4rRaDTh4eGw0Wq1sPH399+yZct33313+/ZtAL6+vgAYhvHz8+N5HoBSqYSNVqsNDw8HwLKsSqWCXb169SpVqgSgYsWKsNNoND169JAkCYBGo4FNixYtjhw5smjRogMHDjx48EChUJQtWzYkJGTYsGFNmjTBX+rdu3dsbKwkSVu2bOnTpw9sGIaJi4vr0KHD999/f/bs2aysLFEUtVqtt7d3y5YtR44c6ePjA7tTp06lpqYCaN++ffny5UHI3+FAXlfdunWXL1+empoaFBTUuXPnxYsXX7t2DTYKhWLo0KEArFZrSkqKn5+fSqVCCfLw8KhQocKpU6cAqNXq/v37R0VFwa6pDYDTp0+bzebatWuDkHdd3bp1ly9fnpqaGhQU1Llz58WLF1+7dg02CoVi6NChAKxWa0pKip+fn0qlAiHknzNr1iz8pQ42kiQxDAO7DRs24FkzZszAn6lXr97mzZvxnNY2KIZl2f379+NZnWzwnBUrVuA5/v7+mzZtwnOqV6++cuVKs9mcnZ3NsizP8xzH4SU0bNiwRYsWBw4c+PXXX69evVq9enXY/cfGYrEYjUZRFB0cHHQ6HcMweFZ8fDxshg4dCkJeAgfyulq3bq3X67/99ttVq1aVLVt2x44dUVFRZ8+eLVu27PDhw3v06AFgz549Z8+ejY2NRclSKpUdOnT49ttvz58/X6dOncmTJ2s0mg0bNuTn54eGhs6aNUulUlksltjY2KpVqwYHB4OQd13r1q31ev233367atWqsmXL7tixIyoq6uzZs2XLlh0+fHiPHj0A7Nmz5+zZs7GxsSCEvAkMw+Atx3Gch4cHXtGYMWMOHDhQVFT0f//3f9988w2exbKsi4sLXuDBgwfbtm0D0KpVq+bNm4OQl8CBvK5KlSoNHjx40aJFrVq16t69e82aNbdv3242mzmOg82tW7ciIyMDAgL69OmDEhcREbFhw4YxY8bs2LHDyclp3LhxkZGRkiQpFArYLFiw4PDhw7GxsVqtFoS86ypVqjR48OBFixa1atWqe/fuNWvW3L59u9ls5jgONrdu3YqMjAwICOjTpw8IIaQEffzxx5988smPP/64bt26cePGubu746WtXr06NzeXZdno6GiGYUDIS+BAZJg2bdoff/zRu3fvu3fvDhs2TK/XcxwHQJKk/fv3R0REPHz4cNeuXY6OjihxPj4+ixYt6tu3b8eOHefNm9ewYUPGBsDjx4/nzZu3YMGCnj17Dhs2DIS8H6ZNm/bHH3/07t377t27w4YN0+v1HMcBkCRp//79ERERDx8+3LVrl6OjIwghpGTNmDHj119/ffjwYWxs7NSpU/FyHj58GBsbC2Dw4MGNGzcGIS+HA5FBr9dv3bp18ODB48ePj42Nbd68eaVKlXJzc0+dOnXy5MkaNWrs2LEjLCwMb8hnn33GcdzYsWMbNWrUvHnz+vXrOzg4pKamHjhwICsra/jw4YsXL2YYBoS8H/R6/datWwcPHjx+/PjY2NjmzZtXqlQpNzf31KlTJ0+erFGjxo4dO8LCwkAIISWuVq1a06ZNu379ek5OjsFg4HkeL2H79u2ffvopwzDR0dEg5KVxIPK4uLgkJCQkJiauXbv2wIEDubm5arXaz89v4cKFAwYM4Hkeb1TPnj2bNWsWFxe3e/fu1atXm81mDw+P9u3b9+vXLywsDIS8Z1xcXBISEhITE9euXXvgwIHc3Fy1Wu3n57dw4cIBAwbwPA9CCHlDxo4di1c0fPhwEPLqOJB/QkcbQRDy8/OVSqVer0ep4e3tPc3GaDRaLBYnJyeWZUHIe6yjjSAI+fn5SqVSr9eDEEIIeW9wIP8clQ1KKycnJxBC7FQ2IIQQQt4zHAghhJCSEhYWBiAsLAzySJIEgGEYyCNJEgCGYSCPJEkAGIaBPJIkAWAYBvJIkgSAYRjII0kSAIZhII8kSQAYhoE8kiQBYBgG8kiSBIBhGMgjSRIAhmEgjyRJABiGgTySJAFgGAbySJIEgGEYyCNJEgCGYSCPJEkAGIaBPJIkAWAYBvJIkgSAYRjII0kSAIZhIM+hQ4cAHDp0CC+NAyGEEFJSLBYL/gmCIABQq9WQRxAEAGq1GvIIggBArVZDHkEQAKjVasgjCAIAtVoNeQRBAKBWqyGPIAgA1Go15BEEAYBarYY8giAAUKvVkEcQBABqtRryCIIAQK1WQx5BEACo1WrIIwgCALVaDXkEQQCgVqshjyAIANRqNeQRBAGAWq2GPIIgAFCr1ZBHEAQAarUa8lgsFrwiDoQQQkhJadKkCYDo6GjIYzAYAPA8D3kMBgMAnuchj8FgAMDzPOQxGAwAeJ6HPAaDAQDP85DHYDAA4Hke8hgMBgA8z0Meg8EAgOd5yGMwGADwPA95DAYDAJ7nIY/BYADA8zzkMRgMAHiehzwGgwEAz/OQx2AwAOB5HvIYDAYAPM9DHoPBAIDnechjMBgA8DwPeQwGAwCe5yFPUVERXhEHQgghhBBCyHuDAyGEEEIIIaQEHTt2LDExEUDHjh0bN26MksWBEEIIIYQQUlKmTp06e/Zss9kMYOHChV9//fW0adNQgjgQQgh5+xUWFqanp7MsW6FCBYVCgT9jMBgyMjLKlSvn7OwMmz179uTl5eFZDMN0794dfyYzM9NoNHp7ezs4OOA5qampFStWdHBwACGEkBc4ceLE7NmzzWYzbMxm8+zZs9u1a9eoUSOUFA6EEELectu3b580adKjR4+ePn0aHBy8dOnSevXq4VkrVqyYOXOm2WxmWXby5MkjRowAYDKZevTo8cEHH6CYihUrdu/eHc+yWq2RkZGrVq3SaDQeHh7Lli1r1aoVilm/fv1XX3117tw5BwcHEEIIeYFff/3VbDajGLPZ/OuvvzZq1AglhQMhpMT5+fmdPn0a5BVVrVoV5DmPHz8eOXLkiBEjhg8fnpeXFxkZOXTo0KSkJI7jYPfHH3+MHj36+++/79ix465duz7//PPGjRvXq1cPgLu7++7du8uUKYO/tHHjxvj4+J9//rlWrVpLliwZMWJESkqKXq+HzZUrV0aPHv306VMQQgj5SwzD4Dk3btyQJIlhGJQIDoQQQt5mp0+fFgRh6NChzjZff/11UFDQ7du3fX19Ybd169aQkJDw8HAA4eHhsbGx27Ztq1evHmx0Oh3+zvr16/v379+kSRMAI0eOXLZs2ZEjR9q3bw9AFMUvvvhiypQpEydOBCGEkBfLz8+/desWnrN582ar1Tpq1Kj69evj38eBEELI20ySpFWrVvE8D5uHDx86ODhotVoUc+bMmcDAQNgwDBMUFHT27FnYPXnyRKVSoRiO41CMIAhXrlwZMGAAbNzc3KpXr37+/Pn27dsDmD59upubW+PGjUEIIeTFbt269dVXXyUkJKjVarPZbLFYACiVyiZNmly5cmX9+vV79+7t16/fsGHDfHx88G/iQAgh5G3Wvn172B05cmT48OF9+/b19vZGMTk5Oc7OzrBzdnbOzs6GTVZWVtOmTVFMx44dly1bhmKePn2al5fn7OwMO0dHx/T0dAA//fTThg0bjh07lpGRgT8THR195swZ2GVnZ9evX//x48eQx2g0AhAEAfIYjUYAgiBAHqPRCEAQBMhjNBoBCIIAeYxGIwBBECCP0WgEIAgC5DEajQAEQYA8RqMRgCAIkMdoNAIQBAHyGI1GAIIgQB6j0QhAEATIYzQaAQiCAHmMRiMAQRAgj9FoBCAIAuQxGo0ABEGAPEajEYAgCJDHaDQCEAQBr+LYsWPR0dHnzp3z8fGZOnVquXLl9u/fD6B169aBgYGpqamrV6/etm3bggUL/ve///Xr169nz54uLi54CQUFBRqNBq+CAyGkxFWoUOH06dMgr8jLywvkBW7fvj1t2rQtW7aMGjVq+vTpeGllypRZtWqVSqWCnSRJAKZMmVJYWAhAoVBMnDgRf+bhw4dffPFFTEyMl5dXRkYGAIvFgmfVt4Hd2rVrVSqVXq+HPFarFYBer4c8VqsVgF6vhzxWqxWAXq+HPFarFYBer4c8VqsVgF6vhzxWqxWAXq+HPFarFYBer4c8VqsVgF6vhzxWqxWAXq+HPFarFYBer4c8VqsVgF6vhzxWqxWAXq+HPFarFYBer4c8VqsVgF6vhzxWqxWAXq+HPFarFYBer4c8VqsVgF6vx8uRJGndunXR0dGPHj1q2bLlnDlzatWqBaBu3boAnJycADSw6d279/Lly/fu3Ttt2rSdO3eOGDGic+fOWq0Wf0mlUuEVcSCEEPKW271796BBg9q2bXvmzJkaNWrgOe7u7tnZ2bDLzs52c3ODjSRJH374oYODA56lVqs5joONg4MDz/PZ2dmwMxqNnp6eCQkJ9+/fX716dXx8vCAIT58+HTZsWP369SdPngy7jh07opjjx48D0Gq1kEcQBABarRbyCIIAQKvVQh5BEABotVrIIwgCAK1WC3kEQQCg1WohjyAIALRaLeQRBAGAVquFPIIgANBqtZBHEAQAWq0W8giCAECr1UIeQRAAaLVayCMIAgCtVgt5BEEAoNVqIY8gCAC0Wi3kEQQBgFarhTyCIADQarWQRxAEAFqtFi/BaDTOmDFj6dKlFotl+PDh06dPd3Nzg40gCAC0Wi3sWrdu3bx58507dy5ZsiQpKWnw4MEJCQmjR49u27atQqHAC3Ach1fEgRBS4lxcXEBenbOzM8hz7ty5M2DAgNmzZw8YMAAvEBwc/Msvv0iSxDCMJEl//PFHmzZt8JcmTZqEYmrVqnXq1KkePXoAePLkybVr14KCgtLT06Ojo2EjSdL+/fs/+OADvV4PQgghwNWrV7/88stdu3a5uLhER0ePGDGCZVn8JY7junTp0qZNmw0bNixfvvyXX345fPjwp59+OmrUqODgYPxDOBBCCHmb7d2718nJSalUfv/997Br0aKFWq2eOnWqv7//yJEju3btOm/evE2bNnXo0CExMfHcuXOrV6+GDcMwycnJarUaxdSqVUuv16OYvn379u/fv0uXLgEBAYsWLapYsWKzZs00Gg3sUlJSZs6cOWDAAA8PDxBCyHtv375948aNu3jxYs2aNefPn//RRx/hpTk6Og4bNuy///1vXFzcqlWrNm7cuHfv3r59+w4fPtzX1xeycfj3SZIkCILBYEDpY7FYcnJyrFYry7IofQRB4DgOpZLRaJQkCaWVJEl5eXkGgwGlT1FRkdVq7d27N8Mwubm5AO7fvw+7a9eu4Y2SJAkAwzB4c6pVqwa78uXLA3B2dgbg5OQkiqLBYGBZFqVPUVGRSqVCibty5YpSqfzmm29gp9VqW7ZsCeD48eN+fn4A/P394+Lipk2bNnLkSA8PjzVr1tSoUQMAy7JqtbpXr14oxtXV9fDhw3hW165dL1++3K1bt6dPnwYEBKxdu1aj0aAYhmFq1qzJMAwIIeT9ZrFYvv3226lTp2ZnZ3fo0GH+/Pk1atTAq/Py8oqOju7Wrdvy5cs3bNiwePHi7du3Dxs2rH///mXKlIEMHEqEZIPSRxCExYsXm81mhmFycnIAPHjwAHZXr15FiahevTrsvL29Abi4uADQaDRfffWVJEkofSRJQukm2aD04ThuzJgxPM+zLIvSJy8vD4CjoyNKH47jsrOzJRuUPpIk4U1YunQpnsMwDICUlBSr1Qqbnj17dunSJTs729XVVa1Ww6ZDhw7/+c9/8ByVSoXnTJ06NTIysqCgwN3dXaFQ4FlBQUG///47wzAghJD3WHZ29tSpU7/99luGYcaOHTtlyhSe5yFDQEDAihUrevbsuWTJkp07d06YMOGHH36IiIjo3r27g4NDQUFBRkaGp6cnXgWHfx/DMBqNxtnZGaVPbm4uwzDr16/HG3XmzBnYnTlzBnafffaZWq12dnZGqcQwDEorhmGcnJycnZ1R+lgslqdPn3p6erIsi9LHYDAA4HkepY/FYjGbzc7OzizLovTRaDR4ExiGwQuwNrBTq9Wenp4oRqPR4FXobfACDMOAEELeYxcvXhw3bty+ffvKlCkzc+bMgQMHKhQK/BOaNGkSEhKSmJi4ZMmSI0eODBgwYOPGjWFhYZs3b758+fKECRPwKjgQQgghhBBC5Nm1a9f48ePT0tICAwMXLFjQokUL/KM4juvUqVPr1q03bdoUExNz4MCBgwcPSpKEV8fhvZeTk4PSKicnB4QQQgghpBQTRXHp0qUzZswwGo1dunSZN2+ej48P/h16vX7w4MH/+c9/BgwYsHfvXrwWDoQQQgghhJDXkpmZGRUVtXr1apVK9bWNTqfDv6xcuXL16tXbu3cvXguH9969e/dQWj148ACEEEIIIaRUOnPmTGRk5KFDh7y8vGbPnv3555+jpAQHB+N1cSCEEEIIIYS8hGPHjiUmJgLo2LFjenr6V199devWrYYNGy5cuLBx48YoQR06dOjcufP27dvx6jgQQgghhBBC/s7UqVNnz55tNpsBzJ8/n2VZURR79eo1Z86cChUqoGRxHLd+/fr69et/++23eEUcCCGEEEIIIX/pxIkTs2fPNpvNsLHaDBw4MCYmRqPR4E1wcHD4+uuv8/Ly8Io4vPfS0tJQWl29ehWEEEIIIeQNsVqtOTk5t2/fXrhwodlsxrMqVqyo0WjwtuFACCGEEEIIsbFarU+ePLl58+bly5cvXLhw8eLFa9euZWRkFBUV4TkMw+AtxIEQQgghhJB3l8lkWrhwYWJiIoCOHTtGRkbq9XrYmc3mrKysmzdvXrp06fz585cuXbp+/XpmZqYgCLBxcnKqVq2ah4fH4cOHLRYL7JRKZevWrfEW4kAIIYQQQsg7ShTF3r1779y5EzYpNjExMXfu3Ll06dL58+cvXbp048aNR48emc1mAAzD8Dzvb1Pbxs/Pz9vbW6fTzZo1a/r06YIgAFCpVFOmTGnYsCHeQhwIIYQQQgh5RyUmJu7cuRPFJCYmHj16NC8vz2KxAFAoFC4uLnXr1vX3969Tp06tWrWqV6/u5eWl1WrxrEmTJrVp02bPnj0APv744+DgYLydOBBCCCGEEPKOOnnyJJ4jCEL9+vUDAgLq1KlTq1atatWqeXp6qtVq/J3g4ODq1asD4Hkeby0OhBBCCCGEvHOysrJ+/PHHbdu24TlfffXVhAkTVCoV3kscCCGEEEIIeYfcvHnzhx9+2Lhx4+XLlwEolUpRFGHn7e39+eefq1QqvK84EEIIIYQQ8vaTJOns2bPr169PSEh48OABy7KhoaGff/65u7v7lClTzp8/D6BOnTpLliypVKkS3mMcyPvBarVmZ2ebzWZnZ2eNRgNC/n1WqzU7O9tsNjs7O2s0GpQyBQUFRqNRrVY7OzszDANCCCFvLVEUDx8+vHbt2t27dxsMBgcHh08++aRv375t2rTRarUA2rZtm5ycDCA4OFij0eD9xoG8627cuLFy5cq9e/feuXPHbDa7u7s3atRo4MCBbdu2BSH/jhs3bqxcuXLv3r137twxm83u7u6NGjUaOHBg27Zt8aZZrdaEhIR169alpKQYDAa1Wu3r69upU6ehQ4e6u7uDEELIWyUvL2/Pnj1r16797bffBEFwd3cfNGjQZ5999uGHHyoUCthpNJo6deoA0Gg0eO9xIO+0NWvWfPnllyaTqXXr1p9++qmjo+Ply5f379+/devWfv36xcbGarVaEPKPWrNmzZdffmkymVq3bv3pp586Ojpevnx5//79W7du7devX2xsrFarxRvy6NGjAQMG7N6928/P79NPP/Xx8Xn8+PHvv/8eFRW1Zs2a5cuXf/zxxyCEEPI2yMjI2Lp16/r160+fPi1Jko+PT3h4eK9evQICAkD+Egfy7oqLixsyZEibNm3mz59fp04d2BkMhoULF86YMcNoNG7ZsoVlWRDyD4mLixsyZEibNm3mz59fp04d2BkMhoULF86YMcNoNG7ZsoVlWZQ4g8HQuXPnlJSU5cuXDxw4UK1Ww+7IkSMRERFdu3bdsWNH27ZtQQghpNTIz88HwPM87FJTUzdt2rR58+br168zDBMYGNinT5+uXbt6e3uDvAQO5B2VlpY2fvz4du3abd26VafTAbDYqFQqnuenT5/u6uo6ZsyYmJiY0aNHg5B/Qlpa2vjx49u1a7d161adTgfAYqNSqXienz59uqur65gxY2JiYkaPHo0SN3ny5OPHj2/btq1Tp06wEQSB4ziFQtG0adPdu3e3a9cuIiLi999/53kehBBC3rRbt25NnDjxwIEDAFq2bDlr1qxHjx59//3327dvf/TokVKpbN269eeff96hQwee50FeGgfyjlq+fLkgCIsWLdLpdFarde7cuevWrSsoKGjSpMmCBQu8vLxGjRq1Z8+epUuXDho0SKfTgRDZli9fLgjCokWLdDqd1WqdO3fuunXrCgoKmjRpsmDBAi8vr1GjRu3Zs2fp0qWDBg3S6XQoQbdv346Pjx86dGinTp0AnD9/fuLEiefOnXN3d//iiy8GDhxYvnz5BQsWfPTRR2vXrh01ahQIIYS8UUajsVu3bqdPn4bNli1bfvnll6KiooKCAicnp/Dw8L59+zZv3lylUoG8Ig7kXSSK4p49ezp06ODv7w9gxowZ0dHRsNm8efO9e/cOHDigUqmGDx/euXPn5OTksLAwECKPKIp79uzp0KGDv78/gBkzZkRHR8Nm8+bN9+7dO3DggEqlGj58eOfOnZOTk8PCwlCC9u/fX1BQMHjwYADp6emdOnW6efMmgAcPHgwZMkSj0fTu3btt27YNGjTYuXPnqFGjQAgh5M2RJGnTpk2nT59GMTk5Oc7OzgMGDPjss8/q16/PMAzIa+FA3kWZmZn3798fMWIEgMLCwvj4eBSTlJR0+PDh1q1bBwYGchx36dKlsLAwECJPZmbm/fv3R4wYAaCwsDA+Ph7FJCUlHT58uHXr1oGBgRzHXbp0KSwsDCXojz/+KFOmTPXq1QFs37795s1uptU0AAAgAElEQVSbsLNaratWrerduzfDMIGBgXv37hUEQaVSgRBCiAy5ubkAeJ7H37FarXl5eRkZGbdv375qd/r0aTyne/fuy5YtA5GHA3kX5efni6Ko0+kAFBUVGY1GPOvJkycAlEqlQqGwWq0gRLb8/HxRFHU6HYCioiKj0YhnPXnyBIBSqVQoFFarFSXLYDCo1WqlUgkgOzsbz8rKypIkiWEYlUpltVolSQIhhJDXde3atS+//PLQoUMAwsLC5s+fX61aNdhZrVaj0ZiRkXHr1q2rNteuXbt9+3ZmZqbJZJIkCTZqtRrPadiwIYhsHMi7yMPDg+f569evA+B5vkGDBvv374edTqcLDAwEkJGRIQiCu7s7CJHNw8OD5/nr168D4Hm+QYMG+/fvh51OpwsMDASQkZEhCIK7uztKVtWqVXfs2PHkyZNy5cp9+OGHDMNIkgS7xo0bMwwD4O7duy4uLiqVCoQQQl5Lbm5u165dz507B5udO3feuHFj1apVWVlZV22uXbt2+/btR48e5efnS5IEgGEYnU5XtmzZ4ODgatWq+fn5Va9e3d3dfdCgQRcuXIBdvXr1OnXqBCIbB/IucnFxCQoK2rdv3+zZs1Uq1fz587t3756WlgZAq9VOnz7dz88PwI4dO9RqdXBwMAiRzcXFJSgoaN++fbNnz1apVPPnz+/evXtaWhoArVY7ffp0Pz8/ADt27FCr1cHBwShZTZs2nT59+v79+/v06dOqVasxY8YsXbrUYrEA+PDDD6dPnw4gPT39yJEj3bp1YxgGhBBCXp0kSZs2bTp37hyKuXjxYlhYWFFREWwYhtHr9eXKlatcuXK1atX8/PyqV69euXJlT09PJycnhUIBu23bto0fP/63334D0Lx583nz5jk7O4PIxoG8o/r379+nT5/vvvtu5MiRdevWTUpKOnjwYH5+fnBwcK1atQBcunRp+fLlHTp08PX1BSH/hP79+/fp0+e7774bOXJk3bp1k5KSDh48mJ+fHxwcXKtWLQCXLl1avnx5hw4dfH19UbKaNm1av379WbNmtW/f3s3NbeHChV27dj137lzZsmXbtWun0WgAzJ8/32g09u/fH4QQ8h6zWCx4aSaT6eHDh7du3UpLS0tNTU1LSzt9+jSeo9PpmjVrVq1aNT8/v+rVq1euXLlcuXJOTk4Mw+DFqlWrtmPHjrt37wKoWLEiyD+EA3lH9ezZMyEhITIy0t3dvUePHu7u7t26dYNdampq7969VSrVtGnTQMg/pGfPngkJCZGRke7u7j169HB3d+/WrRvsUlNTe/furVKppk2bhhKnVCpnz57doUOHfv36rV692sPDI8QGNpIkLViwYMmSJV988UVISAjeGxkZGfgznp6eIIS8fx4/fjx9+vSff/4ZQLt27aZMmVKmTBkU8/Tp00ePHt25c+fq1aupNjdv3kxPTzcajZIkAWAYRq1W4zmzZs0aMmQIwzB4dTzPg/yjOJB3lEKhiI+P79q1a8+ePXft2jVkyJBatWqpVKp79+79+OOPixcvliRp/fr1NWvWBCH/EIVCER8f37Vr1549e+7atWvIkCG1atVSqVT37t378ccfFy9eLEnS+vXra9asiTehTZs2K1euHDZsWEhISGRkZNu2bT08PPLz88+cORMbG/vTTz+Fh4fPnz8fb607d+4MGjRo3759DMPgWWazefTo0VarFXYf2xw9erR///6iKKKY0NDQX3/9Fc9JTEyMiYnJysoKDg6Ojo729PREMSkpKSNGjNi1a5eHhwcIIW+hp0+fhoeHHzx4EDbLly+/ePFifHz8w4cPr127lpqampaWdv369fv37+fm5losFthotVoPD4969epVr169Ro0afn5+ZcuWHTJkyJkzZ2AXHBzcq1cvhmFASgcO5N3l6uqamJg4Y8aMVatW/fDDDzqdTqlUGgwGlmXbtm07Z86c2rVrg5B/lKura2Ji4owZM1atWvXDDz/odDqlUmkwGFiWbdu27Zw5c2rXro03p3///lWqVJkyZcoXX3zBsqyjo2NRUdHTp0/Lly+/ZMmSkSNHKhQKvIWsVmtmZuaSJUsePHiAP5Obm7t27dp27dopFArYKBQKAJIkabXa48ePOzs7w45hGDzn2LFjXbp0mTlzZu3atefOnTtgwIDdu3crFArYFBQUfPHFF+fPn2cYBoSQt9OPP/548OBBFHPo0KHAwMD8/HxRFGGjUqnc3d2Dg4OrVavm7+/v5+fn6+vr7e3t7OzMsizstm3bNnHixAMHDgBo2bLlnDlzHB0dQUoNDuSd5uDgMGfOnLFjxx45cuTixYuCIPj4+DRq1CggIACE/DscHBzmzJkzduzYI0eOXLx4URAEHx+fRo0aBQQEoBRo3rz54cOHz5w5c/LkyYyMDJ1OFxgY2LhxYycnJ7y1Bg0atGXLFqvVWqVKFfyZ9PR0juO+++47Nzc3PMfX19fBwQF/KTY2tkuXLuPHjwdQuXLl2rVrnzp1qlGjRrCZOHFilSpVzp07B0LIW+v8+fN4jiAItWvX9vX1rWHj6+tbsWJFV1dXpVKJF6tcufLmzZszMjIAeHp6gpQyHMh7oEyZMl1sQEhJKVOmTBcblD4KhaKBDd4V8+bNmzt37s6dOxctWoQ/c/v2bW9v7xs3buzbt69MmTKhoaEajQZ2VqsVf8lisSQnJ0+YMAE2NWrUqFmzZnJycqNGjQBs3br14MGDcXFxP/74Iwghbyez2ZyZmYnnREVFjRkzRq1W49U5ODiAlEocCCGEvOXc3NwAMAyDF7h69erly5c/++wzb2/v8+fPBwQEbN682cvLC0B2dvaYMWMYhoFd2bJlZ8yYgWJMJtPjx4/Lly8PG4ZhPDw87ty5A+DWrVsRERGbNm1SqVT4M7GxsSgmJSWldu3aeXl5kMdkMgFQKBSQx2QyAVAoFJDHZDIBUCgUkMdkMgFQKBSQx2QyAVAoFJDHZDIBUCgUkMdkMgFQKBSQx2QyAVAoFJDHZDIBUCgUkMdkMgFQKBSQx2QyAVAoFJDHZDIBUCgUeEWpqakLFizYtm0bnuXj49O1a1fBBq/OZDIBUCgUkMdkMgFQKBSQx2QyAVAoFJDHZDIBUCgUkMdkMgFQKBSQRxAEjuPwKjgQQgh512VkZAwePHjRokU6ne727dvt2rWbO3fu0qVLASiVSr1ezzAM7JRKJYDjx49LkgSAZVl/f388RxRFi8UycuTIESNGhIWFpaSk4M88fvw4KysLdgUFBRaLRRRFyCOKIgBRFCGPKIoARFGEPKIoAhBFEfKIoghAFEXII4oiAFEUIY8oigBEUYQ8oigCEEUR8oiiCEAURcgjiiIAURQhjyiKAERRhDyiKAIQRRHyiKIIQBRFvLSioqINGzbExMTcu3fP29u7c+fOycnJp0+fBvDBBx/MmjXLxcVFFEW8FlEUAYiiCHlEUQQgiiLkEUURgCiKkEcURQCiKEIeURQBiKIIeSwWC8dxeBUcCCGEvOsWLlwIu8qVK/fu3XvHjh2wcXR0nDlzpk6nw7PWrFlz4cIFAFWqVFm3bp1Wq3369CnsCgsLeZ5fuXJlenp6lSpVNm3aVFhYCODnn39WKpXh4eGwi46ORjETJ04E4OrqCnlYlgXA8zzkYVkWAM/zkIdlWQA8z0MelmUB8DwPeViWBcDzPORhWRYAz/OQh2VZADzPQx6WZQHwPA95WJYFwPM85GFZFgDP85CHZVkAPM9DHpZlAfA8j5eTnJw8c+bMxMREhmHCw8MnTZpUq1Ytq9V66dIlADVr1lQoFJCBZVkAPM9DHpZlAfA8D3lYlgXA8zzkYVkWAM/zkIdlWQA8z0MerVaLV8SBEELIO62goGDPnj06na59+/aw4ThOrVbDjmEYPGfNmjUopnLlypcuXfrkk08AFBUV3b17NyAg4PHjx2q1OiYmBoDVan369OmKFSvatWsHQkjpZjQaV6xYsXjx4kePHvn5+U2YMKF3794cxwFQKBQVK1YEoFAoQN5RHAghhLyLcnJyUlJSWJZt3rx5QkKC1Wpt1qyZTqfLyMj44YcfOnXqBLusrCxPT08Uo1Qq8az//ve/mzZtGjp0qJubW2JioslkatasmZeXV0REBGxOnz7dtGnThISE8uXLgxBSiv32228zZ848ePCgSqUaPHjwV1995ePjA/I+4UAIIeRdwXEc7Mxmc8+ePSdPnty8efOoqKiuXbt++OGHFStWPHPmTIMGDSIjI2GTlZXVpEkTFOPq6vrbb7+5uLigmGHDhv32229hYWGVK1f+5ZdfYmJivLy8UAzDMDzPq9VqEEJKq0ePHi1ZsiQ2NtZoNAYGBk6ePLlTp04Mw4C8ZzgQQgh5JzRq1CgkJIRhGNhoNJq9e/cqFAoAtWvXPn78+JEjRx49ehQZGRkaGsqyLIAqVaokJSXhOUqlEs/ieX7Xrl1HjhzJzs6eO3duQEAAnuXp6fnrr7/qdDoQQkofSZJ27949c+bM33//Xa/Xjxs3buzYsZ6eniDvJQ6EEELeCf7+/ijG0dGxQYMGsHN1df3kk0/wrA8++AAvTa1Wt27dGi/gZQNCSOlz9+7defPmrVmzprCwMDQ0dPLkyW3atAF5j3EghBBCCCHvIovF8sMPP8yZM+fSpUtubm5ff/31F1984eLiAvJ+40AIIYQQQt45qampc+bM2bRpk9ls/uijj6Kioho1agRCAA6EEEIIIeQtd+HChX379gFo27Zt9erV4+Pj586de/v2bW9v73Hjxg0ePNjBwQGE2HAghBBCCHlv3Llz58CBAwBatmxZqVIlvBMWLVoUFRVVUFAAICoqytfX99KlSwzDdOvWbdKkSXXq1AEhxXAghBBCCHk/rFmzZvz48dnZ2QBcXV3nzZs3YMAAvOVSUlImTZpUWFgIm8LCwosXL1asWHHq1Kl9+vRRKpUg5FkcCCGEEELeAxcuXBg9erTJZIJNdnb26NGjP/jgg9q1a+OtZbFYNm/eXFhYiGd9+umn/fv3ByF/hgMhhBBCyHtg7969JpMJxZhMpo0bN86cOZPjOLw9JEnKzMz8448/kpKSjh8/furUKTyH53kQ8gIcCCGEEELeA/n5+XhOTEzM8ePHP/jgg5CQkHr16lWqVEmpVKJUysnJuXTp0vHjx5OSks6ePfvgwQNJkgC4uLg8ffpUkiTYsSzbvHlzEPICHP59kiQBsFgsKH0sFgtKN4sNSh+LxYLSzWKD0sdih1LJYrEAsFgsKH0sdiiVJEkCIaS0un37dnJyMp6jVquTkpKOHj0KwMXFpUaNGsHBwSEhIYGBgVWqVFGr1fiXSZKUkZEBwMnJiWEYPKugoODq1asnT548evRocnLy7du3RVEEwPN8o0aNPvzwwyZNmgQFBS1fvnzBggVWqxWAQqEYN25caGgoCHkBDiXCZDI9fPgQpY/RaLRarSitJEl6/Pgxy7IofYxGo9VqRWklSdLjx49ZlkXpY7FYMjIyCgoKFAoFSh9RFDmOe/r0KUofi8Xy+PFjhmFYlkXpYzKZ9Ho9CCGlz/bt26dOnXrx4kWdTpefnw+7YcOGff311xcuXDh58uSpU6cuXrx46tSpEydOLFu2zMnJyc/Pr0GDBiEhIUFBQVWrVtVqtSjmxIkTu3fvBtChQ4dGjRrhtZw/f37s2LHHjh0D0Lhx40WLFtWpU0cUxVu3biUnJyclJZ08efLq1asFBQUAtFptQEBAw4YNQ0NDg4ODfXx8lEolbObOndu6desff/wRwCeffNKqVSsQ8mIcSoRery9XrhxKH41Go1AoUFoxDFOmTJly5cqh9NFoNAqFAqUVwzBlypQpV64cSp/CwsJJkyaZzWaGYXJzcwGkp6fD7saNGygRVatWhZ2XlxcAZ2dnABqNZs6cOe7u7ih9LBaLJEnlypVjWRalj16vB/l/9uAGrsb7/x/463POdc5Vp5vTLdHNiJSQVG6TL7qZ5W4I21czfGMzw0bG3J7chLCN2Zi7bcLcLbTJRGNmRhLGkJi+kmXpRqe7c6461//3OL/H+T3yt5tyFWf2fj4JMTMFBQXLli37+OOPq6qqIiMj4+LicnJykpKSAAwdOnTYsGGMMTc3txdeeEEUxfz8/MuXL58x+umnnzIzM8+ePbtu3Tpra+vWrVsHBQV169YtMDDQy8tr5cqVS5YsEQQBwIoVK+bMmbNgwQLUU0FBwYgRI7KysmCUlpYWGRn54osvXrhw4eeffy4pKQHAcVyLFi06d+7cs2fPbt26eXt7W1lZ4feEhYV17twZgFqtBiF/ikPjY4wBkMvlMD9yuRzmTW4E8yOXy2He5EYwP4IgKJXKbdu24am6ePEiTC5evAiT0aNHV1dXy+VymCW5CcwPYwyEEHPy7bffzps379SpU3Z2dnPnzp06daq1tXVQUFB4eDgAtVqNWhhjzYzCw8NFUSwoKLhy5coZowsXLly+fPnChQubNm1SqVQuLi45OTkGgwFGgiAsXry4bdu27du3r66uFh6h1+sFQdDr9YIg6I0EQdDr9T/++GNWVhZqycvL++ijjxhjzZs372nUo0eP9u3b29vbg5CGw4EQQggh5Nmi1WpXr169atWqkpKS4ODghQsX9u3bF3XGGGti1Lt3bwCFhYVXr149e/bs6dOnz58//8svvxgMBtRSXV39yiuvcBxnqEUURQCiKKI+unfvPnfu3E6dOrm4uDDGQEgj4EAIeeKKi4throqLi0EIIX9nGRkZ8+fPP3TokKWl5fTp02fOnOns7AwJHB0dexoBKCkpmTVr1ieffIKH2djYNG3alOM4xSOUSqVCoVAqlQqFQmmkUCiUSmVWVlZSUhIe9uabb0ZGRoKQxsSBEEIIIeSZoNfrN27cGB8ff/fu3Q4dOsTFxQ0ZMgQNys7ObuzYsVu2bBEEASYKhWLPnj1du3aVmTDGZDIZAMYY/kB5efn9+/dPnDgBk169eg0ZMgSENDIOhJAnLjc3F+YqLy8PhBDyN5SVlRUXF7dz506ZTDZu3Lh58+a1aNECjaBr167z5s1btGiRIAgAFArFvHnz+vTpg3qysrLatWvX/PnzU1NTAURERCxcuNDS0hKENDIOhBBCCCF/ZwaD4YsvvoiLi8vOzm7RosX8+fNHjx4tl8vRaObNmxcREfH1118DGDBgQNeuXfFYXFxcNmzYcP/+fQBOTk4g5IngQAghhBDyt5WXl7dkyZJNmzYJgjB06NC4uLj27duj8XXt2tXHxweAWq2GNAqFAoQ8QRwIIYQQQv6eDh48OH/+/MzMzCZNmsycOfONN96wsLAAIeRPcSCEPHFZWVkwV9evXwchhJi94uLilStXrlmzpqysLDQ0dOHChT169AAhpA44EEIIIYSYt5qamm3btiUlJQEYOnRoy5YtNRrNsWPHbGxs5s6dO336dDs7OxBC6oYDIYQQ8gTdu3evqqrKwsIChNSNKIoTJkzYsmULjJKTky0sLKqqqoKCghYuXPjCCy+AEFIfHAghhJAn6NNPP83IyFi9enWfPn1ASB2kpqZ++umnqKWqqmrgwIHr169v3rw5CCH1xIEQQgh5si5duvTKK6/88MMPzz33HAj5Kz/88IMoiniYv79/8+bNQQipPw6EEELIE5eXl5ecnDx58mQQ8leKiorwCBsbGxBCHgsHQggh5Gn49ddfQcifKiws/PDDD7dt24aH2dnZDRgwAISQx8KBEEIIeRqCgoJAyB9LSUlZsmTJqVOnLC0tIyIiLly48NtvvwFo1qzZqlWr2rZtC0LIY+FACCGEPHGRkZEDBw4EIb/n9u3bK1eu3Lx5c0VFRffu3efMmdO/f/979+4dP34cQO/evZs2bQpCyOPiQP4B8vPzjx8/funSpaqqKk9Pz549e3bs2BGENKb8/Pzjx49funSpqqrK09OzZ8+eHTt2BCGAQqGorq7+97//rVAoQMjDampqdu7cuXTp0p9//tnBwSE2NnbKlCmOjo4AmjZt2q9fPwBqtRqEEAk4kGdaWVnZggULtmzZUlJSYmNjo1Qqi4uLAURERMTHx3fq1AmENLSysrIFCxZs2bKlpKTExsZGqVQWFxcDiIiIiI+P79SpE0jjKCoqWrFiRXx8PGMMj6isrNyzZ8+VK1d8fHxGjBihUqkA7NmzZ+3atXiYi4vLrl278Ihff/1179699+7d69Kly8CBAxljqKW4uDghIWHatGnOzs74U8HBwcePH//qq69GjRoFQmq5cuXK0qVLd+7cWV1d3a9fv7lz5wYHB4MQ0tA4kGdXQUFBVFTUiRMnRo8ePX78eF9fX6VSmZeXl5ycvHLlyj59+nz++eeDBw8GIQ2noKAgKirqxIkTo0ePHj9+vK+vr1KpzMvLS05OXrlyZZ8+fT7//PPBgweDNIIDBw4kJyfHx8fjEYIgvPTSS1evXg0PD1+yZElSUtLevXuVSqXBYLh06dKKFSsYYzARRRGPuHPnTmRkpLOzc+vWraOjo19//fWEhATU8s477+zYsWPatGn4K15eXpcuXTp69GhWVpa3tzcIASorKzdt2rRy5crbt2+7ubnFxsaOHz9epVKBENIIOJBnlMFgGDNmzJkzZ3bv3j18+HCYeHt7z5gxY8iQIS+//PLYsWOPHz/u5+cHQhqCwWAYM2bMmTNndu/ePXz4cJh4e3vPmDFjyJAhL7/88tixY48fP+7n5wfScObMmZORkXHkyJG2bdvi9xw4cOD777/PyMjw9PS8efNmUFDQV199NWzYMAByufzll19WqVT4Ux988IG1tXVycrKVldWLL744ePDgmJiYNm3awGjr1q179+4VRRF14ODgEBoaunv37uTk5BkzZoD84/34449Lliw5ePCgXC5/+eWXZ8+e3b59exBCGg0H8oxKTExMSUn5+OOPhw8fDqCwsPDQoUPl5eVdu3b19/dv3bp1YmJi9+7dFyxYsG/fPhDSEBITE1NSUj7++OPhw4cDKCwsPHToUHl5edeuXf39/Vu3bp2YmNi9e/cFCxbs27cPpOEEBAQEBQVFRkZu2LABvyclJaVPnz6enp4AWrVq1bdv30OHDg0bNgx1I4rit99+++9//9vKygpAWFiYu7v7jz/+2KZNGwBXrlyZOnXq7t27Bw8ejDpgjEVFRe3ZsycpKenNN9+0tLQE+acqKir60KiwsLBt27bvvvvuyy+/zHEcCCGNiQN5Rn322Wd+fn7jx48HcPHixREjRly/fh2AhYXFypUrJ02a5OPjM3ny5OXLl2dnZ3t5eYEQyT777DM/P7/x48cDuHjx4ogRI65fvw7AwsJi5cqVkyZN8vHxmTx58vLly7Ozs728vEAayLBhwwBs2bIFf+DWrVvdunWDiZeXV0ZGBowYY8eOHZPL5TAxGAyRkZGopaqqKi8vz9vbG0YKhcLd3f369esA9Hr9m2++uWjRIgcHB/yeq1evopaCggIHB4devXp5e3tnZGR89913oaGhqD9BEAAIggBpBEEAIAgCpBEEAYAgCJBGEAQAgiBAGkEQAAiCAGkEQQAgCAKkEQQBgCAIqOWbb75ZtmzZqVOnLC0tJ06cOH36dA8PD1EUBUHAHxAEAYAgCJBGEAQAgiBAGkEQAAiCAGkEQQAgCAKkEQQBgCAIkEYQBACCIEAaQRAACIIAaQRBACAIAqQRBAGAIAiQRhAEAIIgQBpBEAAIggBpampqGGOoDw7kWVRUVJSZmTlhwgSO4wDExsZev34dRlVVVTNnzgwPD2/Tps3gwYMXLVp09uxZLy8vECJNUVFRZmbmhAkTOI4DEBsbe/36dRhVVVXNnDkzPDy8TZs2gwcPXrRo0dmzZ728vECelKqqKqVSCROlUllRUQGjgoKC2NhY1BIREREZGanX6xljAERR1Ov1Op1OqVTCRKFQaLVaAHFxcY6OjpMmTcrMzMTv2bVr1+7du2Hi4ODQqVOnmpqasLCwa9eu7dixw8/PD/Wn1WoB6PV6SKPVagHo9XpIo9VqAej1ekij1WoB6PV6SKPVagHo9XpIo9VqAej1ekij1WoB6PV6GN29e3f9+vU7duyorKwMCAiYOnVqaGgoY6ygoAB/SqvVAtDr9ZBGq9UC0Ov1kEar1QLQ6/WQRqvVAtDr9ZBGq9UC0Ov1kEar1QLQ6/WQRqvVAtDr9ZBGq9UC0Ov1kEar1QLQ6/WQRqvVAtDr9ZBGq9UC0Ov1kKayslKlUqE+OJBnUUFBQWlpaevWrQE8ePDg3LlzqKW8vPz8+fNt2rRxcXFRKpWFhYUgRLKCgoLS0tLWrVsDePDgwblz51BLeXn5+fPn27Rp4+LiolQqCwsLQZ4ghUKBhykUChg5OTmlpaU1a9YMJqIoAhg/fvyxY8cABAYGJiYmchwniiJqsbCwOHTo0ObNm48cOXLv3r3S0lIAd+7cEQShefPmMHnHCCbz58/nOK5Zs2bR0dFbtmz57rvvampq3NzcUE8qlQqAWq2GNCqVCoBarYY0KpUKgFqthjQqlQqAWq2GNCqVCoBarYY0KpUKgFqthgTZ2dlpaWkAwsLCPD09d+3atWzZssuXL9vb28fGxk6ePNnJyQl1o1KpAKjVakijUqkAqNVqSKNSqQCo1WpIo1KpAKjVakijUqkAqNVqSKNSqQCo1WpIo1KpAKjVakijUqkAqNVqSKNSqQCo1WpIo1KpAKjVakijUqkAqNVqSGNlZYV64kCeRdbW1kqlsqysDICFhYVarS4uLkYtDg4OAARBMBgMMpkMhEhmbW2tVCrLysoAWFhYqNXq4uJi1OLg4ABAEASDwSCTyUCeIHd391u3bsHk1q1b7u7uMLGzs2OMwYQxBmDRokUGgwEAY8zKysrFxeXWrVswMhgMd+/ejYqKunnzZmFhYVBQEIz0en23bt1mz569YMECmKhUKtSiUCgAMMYCAwN79uyZmpp6+PDhmJgY1BNjDABjDNIwxgAwxsBRoE4AACAASURBVCANYwwAYwzSMMYAMMYgDWMMAGMM0jDGADDG8LjWrVs3a9as0tJSANbW1u3atTt37lx1dXW/fv3mzJnTs2dP1AdjDABjDNIwxgAwxiANYwwAYwzSMMYAMMYgDWMMAGMM0jDGADDGIA1jDABjDNIwxgAwxiANYwwAYwzSMMYAMMYgDWMMAGMM0jDGUE8cyLOoSZMmbm5uZ86cAcDz/JgxYzQaDUyCg4N79eoF4Ny5c9XV1e3btwchkjVp0sTNze3MmTMAeJ4fM2aMRqOBSXBwcK9evQCcO3euurq6ffv2II1MFMWKigpRFK2trcPDwzUaTUlJiZ2dXUlJyffffx8XFweTmpoaPMLDwwO1BAcHHzp06PXXX2eMXbx48erVq127dnV0dBw8eDCMrl+/PnDgwO+//97Z2Rl1wHFcVFRUamrq3r17x4wZw3EcyDPn4sWLsbGxFRUVMCorKztz5kzTpk1nzZo1fvx4KysrEEKeBg7kWaRQKCIjIzdu3Hj58uX27dvPnz+f5/lt27ZVVFT07NkzPj6e53mDwfDRRx95enp27twZhEimUCgiIyM3btx4+fLl9u3bz58/n+f5bdu2VVRU9OzZMz4+nud5g8Hw0UcfeXp6du7cGaSR3b9/PyQk5I033pgyZUpUVNTGjRvHjx/fv3//5ORkDw+PqKgoGN2/f3/KlCmMMZgwxlatWmVnZ4dapkyZEh4eHhsb6+vru3r16nHjxvn7+6OW3377jTHm4eHh7OyMunnhhRfc3d1Pnjx5/vz5zp07gzxbdDrd1q1bKyoq8LCXXnrprbfeAiHk6eFAnlFTp07dvn37tGnTkpKSrK2tZ82a9c477xgMBo7jYPTee+8dO3ZszZo1KpUKhDSEqVOnbt++fdq0aUlJSdbW1rNmzXrnnXcMBgPHcTB67733jh07tmbNGpVKBdLQeJ4fO3asKIqMMRiNGDHC0tISgLW19d69e9etW/fVV1+1b99+4sSJVlZWMIqNjcUjDAYDHtauXbuUlJRNmzalpqa+9tprMTExeJjBYIiLizMYDKgzNze3yMjITz75JCkpqXPnziB/f+Xl5Tdv3szMzDxz5kxGRsalS5fwCDs7OxBCnioO5BnVunXrVatWjRs3btCgQStWrAgMDJQZASgsLFy5cuWyZctGjhw5adIkENJAWrduvWrVqnHjxg0aNGjFihWBgYEyIwCFhYUrV65ctmzZyJEjJ02aBNIIRo0ahVqcnZ0XLlwIk2bNmi1cuBAPG2mEuvH391+7di3+QGcj1FNUVNTmzZuTk5Pfeecde3t7kL+hBw8eZGdnZ2RknDlzJjMz8+bNm+Xl5QDkcrmjo2NBQYEoijCRyWS9e/cGIeSp4kCeXWPHjpXL5dOnT+/SpUtYWFhQUJCVldXVq1ePHDly7969CRMmrF69WiaTgZCGM3bsWLlcPn369C5duoSFhQUFBVlZWV29evXIkSP37t2bMGHC6tWrZTIZCDEKDg4ODAxMT09PS0uLiooCMRuiKB44cCApKQnA0KFDBw8ezBiDSWFh4dWrVzMyMk6fPn3hwoWcnBydTgdAqVR6eHh07Nixa9eunTt39vX1jY+PX7NmjSiKABhjkydP7t27NwghTxUH8kwbPXp07969169ff/DgwbVr19bU1Dg7O4eGho4dOzYsLAyENILRo0f37t17/fr1Bw8eXLt2bU1NjbOzc2ho6NixY8PCwkBILZaWlkOHDj1z5szevXujoqJAzMbUqVM//PBDGCUmJk6ePHn27Nk///xzenr6mTNnfvrpp9zc3OrqagCWlpatWrXq1KlTt27dgoKCvL297e3tYfLBBx+Ehobu27cPwJAhQwYOHAhCyNPGgTzrPDw84uPjlyxZUlJSUlNTo1arFQoFCGlMHh4e8fHxS5YsKSkpqampUavVCoUChPyeQYMGJSQkHD169Nq1az4+PiBm4Ntvv/3oo49Qy9q1a7/44ouioiKDwQDA2tq6Q4cOAQEB3bp1CwwMbN26tY2NDf7AwIEDe/XqBUCtVoMQYgY4kH8Gxpi9vT0IeYIYY/b29iDkT/n4+ISGhu7evTs5OdnHxwfEDJw4ccJgMKAWURTLyso6G3Xt2rVTp06enp6WlpYghPwNcSCEEEKequHDh+/ZsycpKWny5MmWlpYgT5soinjE5MmTFy9erFQqQQj5m+NACCGEPFV9+/Zt27btuXPnfvjhh7CwMJCn6tSpUykpKXiYlZVVdHS0UqkEIeTvjwMhhBDyVDk4OAwaNGjZsmV79+4NCwsDeUr0ev369euXLFny22+/tWjR4v79+2VlZQDs7OyWL1/u5+cHQsgzgQMhhBDytA0dOnTNmjUpKSl37txxc3MDeeJu3rw5f/78L774Qi6Xv/766/Pmzauqqjp69CiAsLAwT09PEEKeFRwIIYSQp61Tp04hISGHDx8+dOjQ+PHjQZ6spKSkefPmXblypUWLFgsWLBg9erRMJgMwcuRIAGq1GoSQZwgHQggh5GnjOC4qKurw4cN79+4dO3Ysx3EgT0RxcfHy5cvXrFlTWVk5cODAxYsX+/n5gRDyTONACCGEmIF+/fp5eHicPHkyMzOzS5cuII3v9OnTc+bM+fbbb21tbWfPnv32229bWVmBEPKs40AIIYSYATc3txdeeOGTTz7Zt29fly5dQBqTIAgbNmxYvHhxfn5+UFDQ4sWLn3/+eRBC/hk4/ON5e3tnZGTALLVp0waEEPKPERUVtXnz5gMHDsyYMcPBwQGkcfzyyy8ajWbbtm1yuXzChAnz5893dXUFIeQfgwMhhBBiHoKDg4OCgs6cOZOWljZ8+HCQRrB///558+ZdvnzZw8NjwYIFr776qlwuByHkn4QDIYQQYh4sLS2HDh16+vTpvXv3RkVFMcZAGk5JSUlCQsLq1asrKir69++/ePFif39/EEL+eTgQQgghZmPQoEHLly9PS0vLysry8fEBaSDp6elz5sw5evSojY1NXFzctGnTrK2tQQj5R+Lwj+fu7p6RkQGz5OrqCkII+Sfx9vYOCwvbtWtXcnKyj48PiGTV1dUbN25ctGjRr7/+GhAQsHjx4hdeeAGEkH8wDoQQQog5iYqK2r17d1JS0ptvvqlSqUDq6eeffz58+DCA559/3srKSqPRJCYmMsZiYmLmz5/v7u4OQsg/G4d/PHt7e5gre3t7EELIP0xoaGjbtm3PnTv3ww8/hIeHg9THBx98MGfOnIqKCgCzZ892dHS8e/euu7v7/Pnzx44dK5fLQQj5x+NACCGEmBN7e/vBgwcvXbp079694eHhIHWWmZn57rvvVlVVwUin0929ezc4OHjNmjUBAQEghBAjDo1PFEW9Xl9aWgrzo9frDQZDdHQ0Y6ykpATAnTt3YJKdnY0nwsvLCyZubm4A7OzsAFhYWAiCUFpaCvOj1WpFUYQZ02q1paWlMD9arVYURZgxrVZbWloK81NTU1NSUiKKolwuh5nheV6n0ymVSpCGMGTIkDVr1hw6dOjOnTtubm4gdfPNN99UVVXhYaGhoQEBASCEEBMOT4QoigaDAeZHLpe//fbbarVaLpfD/Oj1eplMZjAYYH4MBgPMmGhkMBhgfgwGA8yYaGQwGGB+dDrde++9V11dzRgrLi4GkJeXB5Pr16+j8bVp0wYmrq6uAOzt7QGo1eoPP/xw/vz5IA0hICCgZ8+ehw8fTklJmTBhAkgdZGdnp6Wl4RFyuRyEEFILh8bHGLOwsLCzs4P5qampqaysbNasmVwuh/l58OABALVaDbPEGIO5YozZ2tra2dnBLDHGYK4YY7a2tnZ2djA/JSUljLHExEQ8PZmZmTDJzMzEwxhjIA1BLpdHRUUdPnz4yy+/HDduHMdxIH/AYDCcOXMmMTFx3759+fn5eJhcLu/Tpw8IIaQWDoQQQoj5eeGFFzw8PE6ePJmZmdmlSxeQR5SXl6empm7dujU1NbWiosLa2joqKspgMOzfv99gMACQyWTTpk0LCQkBIYTUwoEQQv4+iouLQf4ZXF1dIyMj169fn5SU1KVLF5Ba8vPzk5KStm3bdubMGYPB4OrqGhMTEx0dHRQUxBg7cuTIvn37AAwZMiQ8PByEEPIwDqQhMMbwiAMHDgwaNAiEEEIeS1RU1ObNm5OTk9955x0HBwcQ4MqVKzt27Ni1a9eNGzcAdOjQYdSoUSNGjGjZsiVMwsPDu3TpAkCtVoMQQh7BgUjDGMMfGDx4MICLFy/6+fmBENIQcnNzQf4xevToERgYeObMmbS0tOHDh+MfrLq6+uTJk4mJiQcOHCgsLFQoFKGhoaNHjx44cKC9vT0IIaQ+OJDHZTAY5HI5/krHjh1jYmI2btwIQggh9WFpaTl06NDTp0/v2bMnKiqKMYYGdfny5cOHDwN4/vnn27dvDzMgiiIeVlpampKSsnXr1m+//Van09nZ2UVHR48ePfpf//qXUqkEIYTUHwfyuORyOepm06ZNpaWlu3btAiGEkPoYNGhQQkJCWlratWvX2rZti4bz/vvvz507t6KiAsD8+fMXL1789ttv4+kpLi5esmRJSkoKgMjIyDlz5pSVle3du3fbtm3nz58XRbFFixbDhw8fNWpUx44dQQghEnAgj4UxhvrYvXv3rl27QAghjaC8vBwPs7KywiNyc3Pv3Lnj6urq4eEBo3379uXk5OBhoihOmzYNv+f69evFxcWenp7Ozs4wqqioEEURtVhZWaHheHt7h4WF7dy5Mzk5uW3btmggmZmZs2fPrqqqglFFRcXs2bN79eoVGBiIp0Gn07300kupqakwunr16pdffmkwGG7fvs0YCwwMHDVqVFRUlJubGwghRDIO5ElhjImiCEKIBFlZWSCPmDJlyoEDB2AyaNCgLVu24GGLFi1KSEho3rz5nTt3Zs2aNW/ePAB6vX7atGmRkZGoxc7ODo8QBCEmJmbnzp3u7u6VlZWrV6+OiooCkJSUNG3aNIPBACMvL69Tp04xxtBwoqKidu3alZSUNHnyZJVKhYbwzTffVFVVoZaqqqpVq1bNnDnT3d3dzs5OJpPhCUpKSkpNTUUtOTk5CoUiMjJy9OjRkZGRNjY2IISQBsKB1B9jDIQQYjays7M1Gk27du3wB06fPj1//vyvvvoqMjIyJSVl4MCB4eHh3bp1A+Dk5LR9+3Y7Ozv8qS1btqSmpp49e9bHx2ft2rXTp08PDQ21t7fPysrq3r37W2+9BSPGGBpa3759fX19MzMzT548GRERgYag1WrxiC+++GL//v1Nmzb19PRs27Ztu3btfHx8PD09mzZtamFhgT917949AGq1GnVQWVlZWFiYm5v7yy+/ZBsdP34cjxg+fPjnn3/OcRwIIaRBcSCPSxRFANbW1uXl5fhjoigCmDp16po1a9atWzdx4kQQQkjDEQTh9u3bvr6+ffr0wR9ISkrq06fPgAEDAAwYMKBPnz779u3r1q0bjJRKJf7Kzp07X331VT8/PwD/+c9/li1bduLEicGDB2dlZfn5+fXp0weNxt7eftCgQUuXLv3yyy8jIiIgWWpqakpKCh7GGOvRo0dRUVFeXt5///vfb7/9FoBMJrO3t/fw8GjTpo2vUZs2bdzd3dVqtUwmg9HPP/88ffr0EydOAOjVq9eqVavatWsHE1EUtVrtvXv3bt++ffPmzevXr9+4cSMnJ+fu3bvFxcXV1dUwkslkeETPnj05jgMhhDQ0DuSxiKIIo7KyMsYY/srq1avXrFkzY8aMiRMnghBCGk5RUdG9e/cuXLiwaNEihUIxaNCgiRMnyuVy1HLx4sWOHTvCxM/P76effoLJ3bt3mzRpglpsbW1Ri06nu379+htvvAEjtVrdunXrn376afDgwbdu3erTp0///v3Lysp69Ojx9ttvN2nSBLXU1NSgFoPBIJPJUE9Dhw5ds2ZNSkpKbm6uu7s7Hld+fv577723bt26srKyZs2a5efni6IIQCaTxcbGLl++vKys7O7duzdv3rxidO3atZycnMuXL58/fx5GlpaWLi4urVq1atu2ra+vr6ur6/Tp07Ozs2F0+PDhnJycDRs2lJSU3LhxIzs7+8aNG7dv387Pzy8rKzMYDDBSKpWOjo7+/v4tW7b0MlKr1VOmTLlz5w5MWrZsOXjwYBBCSCPgQB5LREREamoq6qm8vByEENKg7ty5I4rixYsX33zzzZycnFmzZt28efP9999HLaWlpba2tjCxtbV98OABjO7fv9+5c2fUEh0d/eGHH6KWqqqq8vJyW1tbmFhZWRUUFFRVVeXn5+/YseONN97Q6/UJCQlnz549ePAgz/MwWbRo0dGjR1FLp06d8vPzUR/NmjXr0qXLsWPHdu3aFR0dDaC0tBRAZWUl6kYUxcOHD7///vs//fSTjY3NlClTJkyY8PPPPx86dAjACy+80KtXr/z8fAC2tradjABUV1cXFRXduXPn5s2bWVlZ169fv3XrVn5+fk5OztGjRwHIZDKDwYBasrKywsLCBEGAEWPM0tLS0dHR19e3RYsWLY2ee+45FxcXe3t7hUIBk/Xr1y9YsODChQsA/P394+LiZDJZfn4+HktpaSmAyspKSFNaWgqgsrIS0pSWlgKorKyENKWlpQAqKyshTWlpKYDKykpIU1paCqCyshLSlJaWAqisrIQ0paWlACorKyFNaWkpgMrKSkhTWloKoLKyEtKUlpYCqKyshDSlpaUAKisrIU1paSmAyspKSFNaWgqgsrIS0pSVlalUKtQHB/JYjhw5whhDHTDGHjx4oFarATDGQAghDUoul6ekpPTt2xdGTZo0mTx58rvvvtukSRPUgZOT08GDB62srGAiiiKAqVOnFhUVAVCpVAkJCfg9lZWVW7du9fPzc3R0BBBg9N1330VERMAk3Agm69ats7CwsLe3Rz2NHDny2LFj33zzzcSJEzmOk8lkANRqNeogNzd31apVn332WVVVVa9evWbPnt27d28ArVu37t27NwC1Wo0/4Ozs7O3tHRoaCiOtVvvrr7/evHnz2rVrV65cSUtLu3v3Lh5ma2sbFBTk6enp5eXVqlUrDw8PFxcXW1tbuVyOPxYWFta7d++ffvoJgJ+fH8dxkEAmkwFQq9WQRiaTAVCr1ZBGJpMBUKvVkEYmkwFQq9WQRiaTAVCr1ZBGJpMBUKvVkEYmkwFQq9WQRiaTAVCr1ZBGJpMBUKvVkEYmkwFQq9WQRiaTAVCr1ZBGJpMBUKvVkEYmkwFQq9WQRiaTAVCr1ZDGwsIC9cSBND61Wg0jlUoFQghpUP7+/qilc+fODx48KCwsbNKkCUyaNm1aUFAAk4KCAmdnZ5i0b99epVLhYe3atZPJZABqamqsrKzs7e0LCgpgUlJS4ubmZm9v36dPH5j4+vp6eHjcuXMHtQQHB6OWr7/+GgDP86inAQMGeHh4/Pjjj5cvX+7atSvP8wB4nsefMhgMu3fvXrJkyeXLlx0dHefMmTN58mS1Wg0TnucB8DyPuuF53snJqUOHDjD6/PPPx4wZg4ctX7583LhxjDHUE8/zvr6+AKysrCANz/MAeJ6HNDzPA+B5HtLwPA+A53lIw/M8AJ7nIQ3P8wB4noc0PM8D4Hke0vA8D4DneUjD8zwAnuchDc/zAHiehzQ8zwPgeR7S8DwPgOd5SMPzPACe5yENz/MAeJ6HNDzPA+B5HtJwHId64kCeoLKyMhBCSIOaOXPmnTt3tm/fDqO7d+/a2to6OTmhlm7duiUlJRkMBplMZjAYzp07N2zYMPypCRMmoJaOHTv+8MMP0dHRAH799desrKygoKCUlJQ1a9Z88cUX9vb2AAoLC4uKitzc3NAIXF1d+/fvv27duqSkpK5du6IOsrOzly1blpiYKAhCv3795s2b16NHDzSoYcOGbdiw4dSpUzDp0aPHSy+9xBgDIYSYKw6k/iZOnLhu3ToQQogZGD58eI8ePbp37z5gwIDc3NwZM2a8/PLLzs7O9+/fnzhxYkhIyJQpU0aOHLlq1ar169cPHDgwOTn5v//978iRI2EkiuKRI0fkcjlq6dmzp52dHWoZP378iy++2L9//3bt2iUkJHTo0CEkJESn082YMePdd9996623qqurV61a5e3t3atXLzSOYcOGbdq0KTk5+Z133uE4Dn9MEITExMSlS5feuHGjWbNmsbGxr732mpWVFRqatbX17t27586de+TIEQDh4eGLFy+2srICIYSYMQ6k/jQrPl63bh3qyfm5dnh6RFEsKSmprq5Wq9VKpRKEND5RFEtKSqqrq9VqtVKpBGkcQUFBW7ZsWbly5ezZs+3t7aOiouLi4gCIovjrr7+KogigZcuWiYmJGo1mwYIFrVu3TkxMbNGiBQC5XN68efO5c+eiFmtr65SUFDysf//+H3zwwcyZMwsLC4OCgrZu3aow+vTTT999993g4GC5XN67d+8dO3ZYWFigcfTo0SMoKOj06dNpaWnPP/88/sDly5eXLFmye/duURSHDBkyd+7cgIAANBpXV9dPP/30t99+A9CkSRMQQojZ40DqqUbEu4dg4fti1ZX9qA/FhMtfXsaw9njCcnJyNmzYcPDgwZycnOrqaicnpx49esTExISGhoKQxpGTk7Nhw4aDBw/m5ORUV1c7OTn16NEjJiYmNDQUpBFER0f/+9//fvDggaWlpYWFBYycnZ1PnjwJk379+j3//PMVFRUqlYoxBqOhQ4dGRUWhbiZNmvT666/r9XpLS0uYdOnSJS0tTavVymQyKysrNCZLS8uhQ4f++OOPe/fujYiIYIzhYVVVVZs3b05ISLh9+/Zzzz03c+bMcePG8TyPxsfzPAgh5G+CA6mn1SfxzXU4jNp3dw5DnTVfIgKYmwovJ/i54In5/PPPY2Nji4uLQ0ND+/fvb21tffXq1bS0tJ07d44fP37NmjUWFhYgpEF9/vnnsbGxxcXFoaGh/fv3t7a2vnr1alpa2s6dO8ePH79mzRoLCwuQhiaTyezt7fGnGGNWVlaoRSaToT7kcrmlpSUeYWNjgydi4MCBy5cvT0tLu379ure3N2rJyMhYvHhxcnKyTCYbNWrU7NmzfX19QQgh5BEcSH2kZOGDk/hfzZeIv33QtrrgGv5K8yUijEqrMOsQdv0bNjyegM2bN8fExPTt23fFihUBAQEwKSoqWrly5dKlSx88eLBjxw65XA5CGsjmzZtjYmL69u27YsWKgIAAmBQVFa1cuXLp0qUPHjzYsWOHXC4HIfXn7e0dFha2c+fOlJQUb29vGJWVla1bt27VqlX37t1r06bN7NmzR40axXEcCCGE/B4OpM6y72PON6gR8X8YZ4G/wuRKQ2mezNYVRhd/xfwjeH8AGlt2dvaMGTPCw8OTkpKsra0BGIw4jnNwcIiPj3d0dIyNjQ0ODp4yZQoIaQjZ2dkzZswIDw9PSkqytrYGYDDiOM7BwSE+Pt7R0TE2NjY4OHjKlCkg5LEMGDBg586dK1asSEpKGjRoUEhIyHvvvZeamqpQKGJiYmbNmtWqVSsQQgj5YxxI3ZTpMe0gfivH/9HfPiX8epFr4ttk6s8A7s5hqMVlbqHM0kH7bZw2TfPg4Fv2L++Bye6f0NYZE7qiUa1du7aiouL999+3trY2GAzvvffeZ599Vl5eHhISkpCQ4OLi8vbbb6ekpHzwwQcxMTEqlQqESLZ27dqKior333/f2traYDC89957n332WXl5eUhISEJCgouLy9tvv52SkvLBBx/ExMSoVCoQUk96vX7r1q0AKioqLhkpFApBEPz8/ObMmRMVFSWTyUAIIeRPcSB1sygNmXmorSL9E0C06T337hyGR+QvdsT/kimqsg7iYUuPo70LejyHRiIIwtdffz1w4MB27doBiI+PnzdvHoxycnJu37595MgRhUIxadKkYcOGZWRk9OrVC4RIIwjC119/PXDgwHbt2gGIj4+fN28ejHJycm7fvn3kyBGFQjFp0qRhw4ZlZGT06tULhNTTV199lZqailoEQYiMjPzkk0/c3NxACCGkDjiQOthzCdvO4/9TcX4rgOLd/8af4hw8q+9nFSUOcnglGSb6Grz7Dfa9AgcVGsO9e/dyc3MnTpwIQKfTbd68GbV8ZxQWFtapUyeO4y5dutSrVy8QIs29e/dyc3MnTpwIQKfTbd68GbV8ZxQWFtapUyeO4y5dutSrVy8QUk/nzp3DIzp27Ojm5gZCCCF1w4HUQdoN/H/uzmH4HzIOhmr8KbHqAYCqa1/lL3FymXMfJjcKkZGHCC80hvLyckEQbGxsAOh0upKSEjzs/v37AJRKpUwmMxgMIESy8vJyQRBsbGwA6HS6kpISPOz+/fsAlEqlTCYzGAwgpP5cXV3xCFdXVxBCCKkzDqQOZvTCmdv4rRz/Q3/7x/uf9MD/MlTjr9SU5YPJIBoMFYV357DmS0QYjfRDhBcaibOzs62t7Y0bNwDY2toGBgampaXBRKVS+fv7A8jPz9fr9U5OTiBEMmdnZ1tb2xs3bgCwtbUNDAxMS0uDiUql8vf3B5Cfn6/X652cnEBI/Q0aNGj58uW5ubkwcXd3HzRoEAghhNQZB1IHrRyx+Hm8vg+/beytv/Ud6olzbF19/zqM7s5hzZeI/s0QF47G4+DgEBAQcPjw4fj4eIVCkZCQMHLkyBs3bgDgeV6j0fj4+ADYv3+/UqkMCgoCIZI5ODgEBAQcPnw4Pj5eoVAkJCSMHDnyxo0bAHie12g0Pj4+APbv369UKoOCgkBI/bm7u2/fvn3q1KkXLlwA4O/vv3r1and3dxBCCKkzDqRu+vvgzmyGWnjvSF1WCupAZtMM96/D5O4cti+7xIZXozGNHTv21Vdf3bhx4xtvvBEQEHDy5MmjR4+Wl5d36dLF398fwLVr19auXdu/f38vLy8Q0hDGjh376quvbty48Y033ggICDh58uTRo0fLy8u7dOni7+8P4Nq1fhBZkwAAIABJREFUa2vXru3fv7+XlxcIeSwhISGnT58+d+4cgMDAQKVSCUIIIfXBgdQNYwwPc3zlq7tz5agD/a3v8LCuXnaiKKIxRUdH79mzZ9q0ac7OzsOHD2/atOmoUaNgkp2dHR0dLZPJ4uLiQEgDiY6O3rNnz7Rp05ydnYcPH960adNRo0bBJDs7Ozo6WiaTxcXFgRAJlEqlr68vAKVSCUIIIfXEgdRZt27dTp8+DZNfF9mjzhxGHyza2h8moiiuXLkyNjYWjUYmk3366adRUVEjRoyIjo5+7bXX2rVrp1Ao8vLyDhw4sGrVKp1Ot3Xr1g4dOoCQBiKTyT799NOoqKgRI0ZER0e/9tpr7dq1UygUeXl5Bw4cWLVqlU6n27p1a4cOHUAIIYSQp4QDqYOamhoAp0+fTklJiYyMBMC3DtfdOII6s/COhFHq0bQXBw1kjAGIjY1FY3Jycvr666/j4uI2bdq0bds2W1tbhUJRXFwMIDw8fNmyZf7+/iCkQTk5OX399ddxcXGbNm3atm2bra2tQqEoLi4GEB4evmzZMn9/fxBCCCHk6eFA6oDjOBhFRkYCmLg86UD1kLtzGOosf6kLgH4Dh0SEheIJsra2XrFixbRp006cOHHp0iW9Xu/p6dmjRw8/Pz8Q0jisra1XrFgxbdq0EydOXLp0Sa/Xe3p69ujRw8/PD4QQQgh52jiQ+ls3c+iLcan7UQ+Gsnv7Mu4PCXJCLUlJSUOHDkXja9as2UgjEPKkNGvWbKQRCCGEEGJOOJB66t69+6lTpxhjqKcXAx1FUWSMwWTYsGGiKIIQQgghhJAnhQP5K4wxmAQGBp46dQqPpX379pcvXxZFkTEGQgghhBBCngYOpM4yMzM7deoEoKioCPX3888/w0gURcYYjG7dutWyZUsQQgghhBDyRHAgdZOXl9e8eXMYOTo6QhpRFBljADw9PUVRBCGEEEIIIU8EB1IHoiiioYmiyBgrKioCIYQQQgghTwoH8ldEUUQDYYyJoggTURRBCCGEEELIE8SBNISUa+JrSagR8X+6uGPHS1ApGWoRRRGEEEIIIYQ8PRxI/W3YsGHChAkwOXXqVHdvTAnG+yfxv5ytsCISlgoQQgghhBBiVjiQ+hs/fvyECRNg0r17dwBvh+BaAQ5lgQGLI9DaEYQQQgghhJgbDqSByBni++G3MoS0xIC2+F8jR47ctWsXjN588008W7y9vTMyMmCW2rRpAzPm7e2dkZEBs9SmTRuYMW9v74yMDBBCCCHkcXEgDaeJFbaNhDWP/7Nz585du3bB6MMPPwQhhBBCCCFPFQfyWFJTUyMiIgDk5eWhFlsLEEIIIYQQYrY4kMcSHh4Oo+bNm4MQQgghhJC/CQ6kkeXl5bm6ut64cQPPHHd394yMDJglV1dXmDF3d/eMjAyYJVdXV5gxd3f3jIwMEEIIIeRxcSCPSxRF1EHz5s1FUQQhhDSO6upqjuPwxwwGAwCZTAaTa9eu4REqlcrDwwN/ShTFmpoajuPwMIPBIIqiXC4HIYQQs8eBkMdlb28Pc2Vvbw8zZm9vD3Nlb28PM2Zvbw9ism3btjVr1hQUFHTq1Gnp0qXe3t54WGVl5fz587/66isAL7744sKFC5VKpSiKI0aM+OWXX+RyOUx4nt+3b5+Hhwf+2GeffbZ27drCwsKgoKBly5a1atUKQHV19eLFi/fs2SMIQr9+/ZYuXWplZQVCCCFmjAMhhJC/oePHj7/66qvr1q3z9/d///33x4wZc/z4cZ7nUcuCBQu+/PLL9evXGwyG8ePHKxSKRYsWAdDr9XFxcTExMahFJpPhjx05cmTs2LGbN29u165dQkLC2LFjv/32W47jVq1a9dFHH3366acqlerNN9+srq7++OOPQQghxIxxIOSxWFhYKBSKcePGyWSyoqIiALm5uTC5du0anggfHx+YuLu7A3BwcABgaWnJ8zzMkoWFhUKhGDdunEwmKyoqApCbmwuTa9eu4Ynw8fGBibu7OwAHBwcAlpaWPM/DLFlYWCgUinHjxslksqKiIgC5ubkwuXbtGhqfj48PTNzd3QE4ODgAsLOzW7lyJZ6gjRs3jhw5csKECQASEhLatm37/fffh4WFwaS0tDQxMXH16tUREREAFi9ePG/evHfffdfS0hIAY0ytVqPOPvnkkzFjxowbNw7AihUrfH19T5061b179y1btixcuHDAgAEAEhISXnnllbi4OGdnZxBCCDFXHAh5LAqFYtasWXZ2dnK5HOZHp9MpFAqYJYVCMWvWLDs7O7lcDvOj0+kUCgXMkkKhmDVrlp2dnVwuh5mxsLCwsrLCk1JTU5ORkTF9+nQYubu7t2/fPj09PSwsDCbXr18vLCzs1q0bjIKDg/Py8n755Zd27drhr9y8eXPZsmUbN26EUXV1dWZm5oIFC2Dk6enp6+t79uxZV1fXGzduBAcHw6hr166CIFy7ds3Z2RmEEELMFYfGd/z4cQAajQbmRxRFrVZrY2PDGIP50el0AHieh/kRRVGr1drY2DDGYH50Oh0AnudhfkRR1Gq1NjY2jDGYH51OB4DneZgfURS1Wq2NjQ1jDObn+PHjeFKqqqoKCwubNWsGEycnp9zcXNRy//59KysrOzs7GNnb26tUqvv378No//793333HUxkMtn69eubNm0KI1EUz58/D5Py8vKioiIXFxeYODo65ubmFhYWyuVyBwcHGNka/fbbb6hFo9Gglu3bt7u6ur777ruQRqfTAeB5HtLodDoAPM9DGp1OB4DneUij0+kA8DwPaXQ6HQCe5yGNTqcDwPM8pNHpdAB4noc0Op0OAM/zkEan0wHgeR7S6HQ6ADzPQxqdTgeA53lIo9PpAPA8D2l0Oh0AnuchjU6nA8DzPKTR6XQAeJ6HNDqdDgDP85BGp9MB4Hke0uh0OgA8z0Oa48ePy+Vy1AeHfzwbGxuYK6VSCTNmY2MDc6VUKmHGbGxsYK6USiXMmI2NDcjvEUXRYDCgFlEUATDGYMQYA2AwGGAUEhJiZ2eHWgwGA4Dq6moAlZWVAIqKimxtbUVRxO8xGAwwYoyhFoPBgD9WWlqKhpCeng4gJCQE0qSnpwMICQmBNOnp6QBCQkIgTXp6OoCQkBBIk56eDiAkJATSpKenAwgJCYE06enpAEJCQiBNeno6gJCQEEiTnp4OICQkBNKkp6cDCAkJgTTp6ekAQkJCIE16ejqAkJAQSJOeng4gJCQE0qSnpwMICQmBNOnp6QBCQkIgTXp6OoCQkBBIk56eDiAkJATSpKenAwgJCYE0eXl5MpkM9cGh8R0/fhyEEEIajlKptLKyKi8vh0llZaW9vT1qsbW11ev1Op3OxsYGQFVVlSAINjY2MHJ0dJw2bRoe8fzzz//yyy8AcnJyAgMDAYwaNWrevHlWVlbl5eUwqaystLe3t7a2rqmpqayshJEgCDqdzsbGBrVoNBo8QqPRQBqNRgNAo9FAGo1GA0Cj0UAajUYDQKPRQBqNRgNAo9FAGo1GA0Cj0UAajUYDQKPRQBqNRgNAo9FAGo1GA0Cj0UAajUYDQKPRQBqNRgNAo9FAGo1GA0Cj0UAajUYDQKPRQBqNRgNAo9FAGo1GA0Cj0UAajUYDQKPRQBqNRgNAo9FAGo1GA0Cj0UAajUYDQKPRQBqe51FPHAghhPzdKBQKLy+v8+fPv/TSSwB0Ot2tW7f+85//oJbnnnuupqYmOzvbyckJwI0bNziOc3d3x59KTEwE8N///nfy5Ml79uzheR4Az/OtWrW6ePHi0KFDAVRUVOTk5HTo0MHV1dXBwSErK6t169YAbt26VVxc7OnpCUIIIWaMAyGEkL+h4cOHx8fHT5w4sUWLFnv37q2oqOjbty+AHTt2cBw3aNAgNze30NDQLVu2BAQEiKK4efPmiIgIFxcXURQBiKL44MED1GIwGOzt7Zs3bw6goqICQMuWLWEyfPjw1atXx8TEuLm57dmzRxTFf/3rX2q1ul+/flu2bOndu7dSqdyyZcu//vUvLy8vEEIIMWMcCCGE/A2NHTv2xIkT3bp1a9myZVZW1ocfftisWTMAZ8+ePXTo0IsvvghgxYoVL730Uvfu3aurq3me3759O4yUSuWCBQsWLlwIE8bYW2+9pdFoYMQYc3NzQy3jx48/efJkt27dPDw8bty48dFHHzk7OwNYvHjxyJEju3XrplAoqqqqtm/fzhgDIYQQM8aBEELI35BSqdy2bduFCxeKiop8fHxcXV1hNNmI4zgAvr6+P/zww08//QSgU6dOKpUKAGNs9+7deITBYIBJq1at9u/fj1osLCx27tx5/vz5kpKStm3bNmvWDEbPPffcsWPHzp8/X1NT07FjR1tbWxBCCDFvHAghhPw9McY6deqEh3l6eqIWGxub4OBgPMzHxwf1xxgLCAjAIywtLXv06IG60Wg0aAgajQYNQaPRoCFoNBo0BI1Gg4ag0WjQEDQaDRqCRqNBQ/h/7cEJUFMH3gDw/4MX4IWEQ6QgIgEprlXwLCjULBhFEFuPCK4Hq9gdrIqrQj1qm+1GYT3KoAmoWFsR3GgXtMTYiBCcNlQGL7zvrSzExoqAhMtAQPK+mTeTGZyvKC+47ezw//2kUim8CVKpFN4EqVQKb4JUKoU3QSqVwpsglUrhTZBKpfAmSKVSeBOkUim8CVKpFN4EqVQKb4JUKgWWSEAIIYQQQggNGCQghBBCCCGEBgwSEEIIIYQQQgMGCQghhBBCCKEBgwSEEELot9Le3i4WiwsKCvh8Plilra0tMzOzrKysu7s7IiJi3bp1fD4f2Pv555/37Nlz9epVR0fHDz74YMWKFTY2NtAP586d2759u0qlsrOzA/a+/vprnU4HFgRBbNu2Daxy8uTJ3NzclpaWqKio5ORkOzs7YOnMmTPnz5+Hl40ZMyY2NhZYMhqNcrn8+++/J0kyJiZm1apVJEkCe/X19ZmZmefOnXN2dl64cOGiRYuAJZqmxWKxXC738fEBhslk2rNnz9mzZ7lc7rJly+bPnw99QNO0WCyWy+U+Pj7QQ11d3Ycffnjq1CkbGxvoA5qmxWKxXC738fEBRn19vUwmu3jxIkmS0dHRq1evtrOzg9ehaVosFsvlch8fH2Dcu3cvMzPzzp07gwYNWrBgweLFi6EPaJoWi8VyudzHxwdeplQqc3NzVSoV9AFN02KxWC6X+/j4AGP37t0GgwEsbG1tpVIpvA5N02KxWC6X+/j4gMWRI0fy8/O7urrmzZu3cuVKgiDgdWiaFovFcrncx8cHAPLy8qqqquBlM2bMmDJlCrwSTdNisVgul/v4+ADj2bNnu3fvPn/+PJfLjYuLW7p0KUEQ8Do0TYvFYrlc7uPjA4yamprMzMzKysq33npr+fLls2bNglfq6urKzs4uLi5ub28PDQ1dt26dh4cHAJhMpj179pw9e5bL5S5btmz+/PnQOxIQQgih34TRaMzNzb148SL0w6pVq8rLyz///HOCIHbt2nXx4kWVSmVjYwNsdHZ2xsfHUxSVlJRUW1ubkpJiMBi2bNkC1jIYDElJSY2NjQRBgFVu3ryZn58/duxYYLi7u4NVjh49+pe//GXHjh0uLi6fffZZQ0NDeno6sGRjY3PhwgWweP78eUVFRUFBAbC3YsWKS5cuffrppx0dHX/729/0ev2uXbuApY6OjoULF7548SIpKenRo0fLli3r7OxctmwZ9JnJZFIqlWq1WiaTgcXGjRtVKlVqauqTJ0/i4uIKCwvnzp0Lr2QymZRKpVqtlslk0ENLS8uBAwcePHgAfWMymZRKpVqtlslkwDCbzUuXLq2rq/v4449bW1u3bt1648aNw4cPwyuZTCalUqlWq2UyGTAaGxvj4uLGjh27bt26hw8fxsfHd3Z2JiQkwCuZTCalUqlWq2UyGbxMp9P99a9/dXd3hz4wmUxKpVKtVstkMrCoqKiorq52c3MDhq+vL7yOyWRSKpVqtVomk4FFRkbGjh070tLSaJretGlTe3t7SkoKvJLJZFIqlWq1WiaTAaOzs/PChQtg0djYeOXKlaioKHglk8mkVCrVarVMJgOG2WxesmSJwWBYu3ZtfX39ypUrDQbD+vXr4ZVMJpNSqVSr1TKZDBgNDQ3z5s3z8/Nbu3bt7du3Z8+effr06ejoaOjdli1bcnJytm/f7uTktHfv3rKyMo1G4+jouHHjRpVKlZqa+uTJk7i4uMLCwrlz50IvSEAIIYT++9LS0g4cOFBbW+vk5ATW0ul0J06cOHXqVGRkJACMHTt24sSJly9fnjRpErBx9erVS5cu3b1718/PDwBaW1uPHz++ZcsWsNaGDRuEQqFKpQJrVVVVffzxx5s2bYJ+6Orq2rlzZ1ZWVmJiIgA4OztnZma2t7dTFAVsRDGAQdO0VCoNCgqKi4sDlp4+fapSqQoLCyMjIwHA3t5+27ZtaWlpHA4H2CguLr527drNmze9vb0BwNHRMSsra+nSpQRBQB8oFAqJRKLX6wmCAAu9Xn/48OETJ05ERUUBwJMnTzIzM+fOnQu9UygUEolEr9cTBAE9JCUlffvttw0NDX5+ftAHCoVCIpHo9XqCIMDi6tWrJSUl165dGzt2LAD4+fl98MEHn3/+uZ+fH/RCoVBIJBK9Xk8QBFj8+OOPz54927t3r6urKwBUV1cXFBQkJCRA7xQKhUQi0ev1BEHAy7q7u9esWRMXF6fVauF1FAqFRCLR6/UEQUAP1dXVGzduXLhwIfSNQqGQSCR6vZ4gCLAwGAwZGRk5OTmzZ88GgO7ubrVanZycTBAE9EKhUEgkEr1eTxAEWCQygEHT9IoVK2bPnv3ee+9B7xQKhUQi0ev1BEGAxb1790pKSq5duzZu3DgAaG1t/eabb9avXw+9UygUEolEr9cTBAEWBQUFbW1tubm5Tk5OsbGx3d3dWVlZ0dHR0IvW1laFQpGVlbVkyRIACAsLGzNmzNmzZydOnHj48OETJ05ERUUBwJMnTzIzM+fOnQu9IAEhhBD67/vzn/8cHx9/69atZcuWgbV++eWXadOmjRs3DhheXl5cLre9vR1YMhgMO3bs8PX1BQaHw7GzswNr5ebm3rlzRyKRqFQqsApN0zqdbsSIEaWlpWazecyYMUOGDAH2Hjx48NNPP82aNauTIWZA/1RUVOTn51+4cAHY43A4FEW1tLQAo7W11dHRkSAIYOnhw4d+fn7e3t7ACA4OTklJefr0qaenJ/SBUCjUarU6nU4kEoHF9evXHRwcwsLCgBETE3PkyJHm5mZnZ2fohVAo1Gq1Op1OJBJBD5s2bdq4ceOPP/6YmpoKfSAUCrVarU6nE4lEYKHT6ebMmfPOO+8AY+jQoZ2dnR0dHdA7oVCo1Wp1Op1IJAKLtra2TZs2ubq6AsOOAa8kFAq1Wq1OpxOJRPCy9PR0mqb/8Ic/aLVaeB2hUKjVanU6nUgkAouOjo5ffvllyJAhJSUlNjY2EydOHDRoELySUCjUarU6nU4kEoHF1atXaZqeNm1ae3s7TdNrGPBKQqFQq9XqdDqRSAS/5uTJk/fu3du3bx+8klAo1Gq1Op1OJBKBhZ2dHYfDaWlpAUZrayuXy4VXEgqFWq1Wp9OJRCKwuHPnzogRI5ycnIAxadKkQ4cOdXR0ODg4wK+pr6+fMGFCcHAwMDw8PFxcXJ4/f379+nUHB4ewsDBgxMTEHDlypLm52dnZGX4NCQghhNB/n0AgAIDq6mroh9DQULVaDQyz2Zydne3p6Tlu3DhgaSYDAL744ov//Oc/R48ePXbsGFjl9u3b69evLy0traurA2u1tLQ8fvw4KSnJy8urra2tsbExKytrwYIFwFJNTc1bb72Vl5d38ODBtra20NDQL774YuTIkWAts9n82WefSaVSFxcXYG/QoEFpaWnx8fFlZWUdHR15eXnHjx8nSRJY8vX1raqq0ul0AoEAAC5cuNDR0dHQ0ODp6Ql9IBAIAMBoNEIPjx49cnd35/F4wPDy8mpubm5sbHR2doZeCAQCADAajfAygUAAABUVFdA3AoEAAIxGI/QwnwGMzs7OzMzMkJCQt99+G3onEAgAwGg0Qg/x8fEA0NnZmZ6e/vDhw9LS0uPHj8MrCQQCADAajfCysrIymUxWUVGh0WigDwQCAQAYjUbooba2tr6+Pi4uTiAQNDY2dnd3Hzp0aNq0adA7gUAAAEajEXr46aefXF1d//73v//rX/968eLF1KlT09PTvb29oXcCgQAAjEYj/Jrnz59LJJK9e/fa2dnBKwkEAgAwGo3QQ0BAgFQqjYuLW7RokcFgKCoqUqlU8EoCgQAAjEYj9DBixIiSkhKDweDq6goAFRUVTU1Nzc3NDg4O8GuGDx9eVFQEFjk5OUajMSwsrKioyN3dncfjAcPLy6u5ubmxsdHZ2Rl+DQkIIYTQ/5rz589v3br1wYMHBw8edHFxAavQNP306dPW1tbOzs7q6mpgz2QyrVmzJi0tLTg4+PTp0wBA0zSwV1dXFxISkpKSEhUVZTKZdu3atW7duqlTp7q7uwMbRqPx559/rqys/Pbbb21tbT///PMPP/ywrKyMw+GAVQoLC41GY1xcHFirqqrKzc2NJEkOo7q6GtibOXPm2LFjxWJxfHy8TqcrLCwEAIIgoB/MZjP0QBCE2Wzu6uqC31tpaenWrVtbWlpycnI4HA5Y5cWLF8+ePWtrazOZTDU1NaGhocBSY2PjmjVrMjMzhw8fDv2g1+unT58ulUonT57c1ta2efPmtWvXXrlyxcHBAdhobW29d++eUCgsLi5ub29fv359UlKSSqUCa+Xk5AwfPnzq1KlglRcvXlRXV7u6utrZ2dnb2z9//lyn04WFhQFLf/rTnw4dOhQXFzdr1qz79++Xl5cDAEEQ8Dq3bt3atm2bVqvdt2+fr6+v2WyGHgiCMJvNXV1d0AsSEEIIof8dRqPx008//eqrr9asWZOXl+fh4QHWIggiIyMDAObPn798+fLY2FgvLy9gIzU11dHR0d/f/8yZM8+ePSMIorS0lKIokUgEbAQEBJSUlADD3t4+MTFx586dN2/enDZtGrBBkiRFURkZGb6+vgCwY8eOwMDAO3fujBs3DtijaTozM3P16tW2trZgleLi4qysrMuXL48ePRoAYmNjZ8yYIRKJgoKCgA1HR0elUvnll1+eP3/+7bffLigoCA8Pd3V1hX7g8Xgmk8lsNtva2gKAyWQiSZKiKPj9GAyG5ORktVqdkpKyZs0aJycnsBaXy929ezcAHDhwYMuWLXPmzOFyucDGJ598EhYWxufzz5w509HR8eLFi6KiIldX19DQUGBjypQpxcXFwODxeCtXrty/f39VVdXo0aOBDQ6H4+XltWvXLhcXFwDYvn17dHT048ePhw4dCuyZTKb9+/fv2bMHrKVQKE6fPn3p0iVvb28AiIyMXL16dURExJAhQ4ANT0/PoqKigwcPnj9/fsyYMRkZGQkJCTweD3rX3d2dlpa2Y8eO5cuXX7582dfXFwB4PJ7JZDKbzba2tgBgMplIkqQoCnpBAkIIIfS/Y9WqVQ8fPrx06dLo0aPBWtu2bbt9+3ZBQQEwAgMDW1tbm5ubvby8gI2Ojo6ampoNGzYAgNls1uv1mzdv3rhxI7BUUlICAFFRUcCwt7fncDi2trbAkre3t729vYuLCzBcXFzs7Ow6OzvBKpWVlbdu3Xr//ffBWjU1NQKBYNSoUcCYOHEin89//PhxUFAQsKHT6dra2rZs2QKMo0eP+vv7e3h4QD/4+/vX1tY2NDR4eHgAQHV1tYeHx+DBg+F30tXVtWTJEpIkr1y5IhAIwFqrV6/u6ur66quvgBEYGFhfX//8+XMulwtsmEymysrK8vJyADAajTU1NZs3b5bL5cBSUVGRjY1NdHQ0MBwcHGwYwJKfnx+Xy+XxeMBwdXXtYoBVNBpNV1eXSCQCa92/fz8gIMDb2xsY7777rsFgePr06ZAhQ4CNe/fumc3mbdu2AWPXrl0jR47kcrnQu08++eT06dNarXby5Mlg4e/vX1tb29DQ4OHhAQDV1dUeHh6DBw+GXpCAEEII/Y+4cuVKfn7+hQsXhg4d2tTUBAySJHk8HrAREhKSnp5+69atoKAgmqaLiooEAsGwYcOApXQGME6fPr1y5crvv//e3d0dWOJwOO+//75Wqw0JCQGAU6dO8Xi8oKAgYCkoKGjw4MHHjx9PTEykaVqpVHp4eIwYMQKsUlhY+N577w0ePBis9c477zx48KCsrCwiIgIAiouL29vb/f39gSWz2RwREZGXlxcTE2MwGPbv3x8bG2trawv9MH78eE9Pz5MnT3700UddXV3Hjh2bPn06RVHwO9FoNJWVleXl5c7Ozk1NTcDgcrl2dnbAxrvvviuVSh89euTj49Pd3f3dd9+NHj3azc0NWMrNzQWLLxlardbJyQlYampqSk5OLi8vDwgIoGlaqVSOGjXK398fWAoJCWlsbPzuu+/mzZtnNpuPHz8+ZsyYoUOHglUKCgpEIpGdnR1Ya8KECfv3779+/fq4ceMAoKioyN3dfdiwYcBSS0tLdHR0SUlJSEiIXq8/dOjQhg0boHePHj3at2+fRqMZOXJkU1MTMAiCGD9+vKen58mTJz/66KOurq5jx45Nnz6doijoBQkIIYTQb8jBwQGsdf36dZPJFB4eDhYURalUqkmTJgEb06dPj4mJiYiImDJlSlNT040bN7Kzs3k8HrBEEARYEATB4XBcXV0JggCWpk6dumDBgsjIyJiYmObm5nPnzmVnZ7u5uQFLFEVJpdLExMSCggKapi9duvTll1+6uLgAezRNl5SULFq0CPohPDw8OTk5MjJyxowZnZ2dWq12586dAQEBwJKfn9+KFSvmzZs3a9asu3fvCgSClJQUYI/L5YIFj8dLTU1NSEgoLy+vq6t7/PhxYWEh9A2Xy4VfQ5IksMHlcsHi4sWL9fVOM4rpAAAD90lEQVT1wcHBYOHq6vrDDz/4+fnB63C5XLBYsGBBfn5+WFhYSEjIkydPHj16lJuba2NjA33A5XLBgiAI6IEgCGdnZ+gbLpcLFvPnz8/Pzw8PDxeJRLW1tbdv3z5y5IidnR30AZfLBYshQ4ZIJJL58+dHR0e3tbU9fPjwn//8J4fDgT7gcrnQQ3t7e1lZWXp6OrDE5XLBYt68eUVFRX/84x8jIiJaW1srKyv379/v5uYGfcDlcsFi0qRJcXFxUVFRIpGosrJy8uTJCQkJ0Lu7d+92dnbOmjULLEiSzMnJmTNnTmpqakJCQnl5eV1d3ePHjwsLC6F3JCCEEEK/FQ8Pj8LCQltbW7BKYGBgRUUFvGzQoEHAEkmSx44d02q19+/fd3FxCQ0NHT58OPSPl5fXN998A1YhCCInJ2fJkiXXr193cnKSy+UBAQFglSVLlkyYMOHixYsEQWRnZwcEBIBVWlpadu/ezefzoX8yMjIWLVp048YNkiRlMtno0aPBKv/4xz9mzJhx69athISEGTNmODg4AEt8Pl+j0VAUBRaLFy8ODAy8fPkyRVGRkZHu7u7QB3w+X6PRUBQFLwsICMjNzYU+4/P5Go2GoihgREdHz5w5E17G5XLhdfh8vkajoSgKGDweT6VS/fDDD1VVVe7u7kKh0MvLC/qAz+drNBqKouD/mThxYnZ2NvQNn8/XaDQURQHD3t6+oKCgtLT0zp07U6dOjYqK8vb2hj7g8/kajYaiKLBITk4ODw+/evUqRVHh4eHe3t7QB3w+X6PRUBQFFvX19Xl5eV5eXsAGn8/XaDQURQGDw+EcPnw4MTHx9u3bXC7366+/9vf3hz7g8/kajYaiKLA4cOBAbGzsv//978TExMjISFtbW+idm5vbuXPn4GUURQHA4sWLAwMDL1++TFFUZGSku7s79I4EhBBC6LcyatQo6IdJkybBG2JrazuNAW/I+PHjoR9sbGwiGdBv7zCgf5ydnSMiIuBNeJcB/RbOAGsNY8DLxjCAjWEM+H+Cg4OBjWEMsAgLCwOrDGNADw4ODjNnzgSWhjHg1wQHB0OfDWNAD/b29u8zgI1hDHjZBAawMYwBPfgwgKVhDOiBIIj3GMDGMAb0YGNjM4MBfRAcHAy9G8OAPiABIYQQQgghNGCQgBBCCCGEEBowSEAIIYQQQggNGCQghBBCCCGEBgwSEEIIIYQQQgMGCQghhBBCCKEBgwSEEEIIIYTQgEECQgghhBBCaMAgASGEEEIIITRgkIAQQgghhBAaMEhACCGEEEIIDRgkIIQQQgghhAYMEhBCCCGEEEIDBgkIIYQQQgihAYMEhBBCCCGE0IBBAkIIIYQQQmjA+D+vHN1vtLSxNAAAAABJRU5ErkJggg==",
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\"/>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "GLMakie.Screen(...)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Render observed actions\n",
    "obs_trace = Gen.generate(gridworld_agent_model, model_args, observations)[1]\n",
    "figure = render_trace(obs_trace; size = (1024, 512))\n",
    "\n",
    "# Plot goal probabilities over time\n",
    "layout = GridLayout(figure[1, 2])\n",
    "ax = Axis(layout[1, 1], titlesize = 24, title = \"p(goal | actions)\",\n",
    "          limits = (1, T, 0, 1), xticks = 1:T)\n",
    "series!(ax, 1:T, goal_probs, color = GOAL_COLORS[1:length(goal_locs)],\n",
    "        strokewidth = 2.0, markercolor = GOAL_COLORS[1:length(goal_locs)],\n",
    "        labels = string.(goal_locs))\n",
    "axislegend(ax, \"Goal\", position = :rt, framevisible = false)\n",
    "\n",
    "# Plot runtimes for each timestep\n",
    "ax = Axis(layout[2, 1], titlesize = 24, title = \"runtime (s)\",\n",
    "          limits = (1, T, 0, nothing), xticks = 1:T,\n",
    "          ytickformat = ys -> [@sprintf(\"%.1E\", y) for y in ys])\n",
    "series!(ax, 1:T, runtimes_enum', markersize = 10.0, solid_color=:black)\n",
    "display(figure)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the top-right plot, we see that the posterior distribution over goals evolves\n",
    "in a reasonable manner as more actions are observed. When the agent turns right\n",
    "at `t = 3`, the probability of the yellow goal increases significantly. But once\n",
    "the agent turns left again at `t = 6`, the yellow goal drops in probability.\n",
    "\n",
    "As for the bottom-right plot, we can see that while the runtime of inference\n",
    "is low (due to the simplicity of our gridworld environment), it increases more\n",
    "or less linearly over time. The cumulative runtime of all steps is thus\n",
    "*quadratic* in the number of observations. This is because each time we observe\n",
    "a new action, we are re-evaluating the likelihood of *all* actions observed so\n",
    "far, which requires recomputing the Q-values via planning for all steps.\n",
    "\n",
    "While a quadratic runtime for online goal inference is acceptable for small\n",
    "environments like the above, in more complex environments where planning is\n",
    "harder, this can lead to significant runtime costs. Ideally then, we would like\n",
    "to reuse our previous computations, and only compute the likelihood of the most\n",
    "recent action when it is observed. We'll address this by using *incremental\n",
    "computation* in the following ways:\n",
    "\n",
    "1. Rewriting our agent model probabilistic program using Gen's `Unfold`\n",
    "   combinator, enabling *incremental simulation* of our model using the\n",
    "   `Gen.update` function.\n",
    "2. Performing inference via a *Bayesian filtering* algorithm instead of\n",
    "   `enumerative_inference`, which allows us to update our inferences\n",
    "   step-by-step instead of re-running inference from scratch.\n",
    "3. Further accelerating inference with an *incremental planning* algorithm,\n",
    "   instead of rerunning Dijkstra's algorithm to compute Q-values at every step.\n",
    "\n",
    "### Incremental model simulation with the `Unfold` combinator\n",
    "\n",
    "Gen.jl provides the `Unfold` combinator, which allows us to replace a for-loop\n",
    "in a probabilistic program with a subroutine that can be incrementally simulated\n",
    "when the number of timesteps is increased (or decreased). To use the `Unfold`\n",
    "combinator we'll write a *kernel function* called `agent_step` that simulates\n",
    "just one timestep of the agent and environment (replacing the body of the\n",
    "original for-loop). We'll then apply the `Unfold` combinator to our kernel to\n",
    "construct a new probabilistic program (`agent_unfold = Unfold(agent_step)`), and\n",
    "call `agent_unfold` as a subroutine in our full agent model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Kernel function for one step of the gridworld agent model.\"\n",
    "@gen function agent_step(t, model_state, grid, goal, beta)\n",
    "    loc = model_state.loc\n",
    "    # Compute Q-values and Boltzmann action probabilities\n",
    "    actions, q_values = compute_q_values(grid, loc, goal)\n",
    "    act_probs = softmax(beta .* q_values)\n",
    "    # Sample action according to Boltzmann policy\n",
    "    act = {:act} ~ labeled_categorical(actions, act_probs)\n",
    "    # Update location following environment dynamics\n",
    "    next_loc = gridworld_env_step(grid, loc, act)\n",
    "    # Return new state containing both location and action\n",
    "    next_model_state = (loc=next_loc, act=act)\n",
    "    return next_model_state\n",
    "end\n",
    "\n",
    "# Apply Unfold combinator, returning a new generative function\n",
    "agent_unfold = Gen.Unfold(agent_step)\n",
    "\n",
    "\"Agent model using the Unfold combinator for incremental simulation.\"\n",
    "@gen (static) function unfold_agent_model(T, grid, init_loc, goal_locs, beta)\n",
    "    # Sample goal from uniform goal prior\n",
    "    goal = {:goal} ~ labeled_uniform(goal_locs)\n",
    "    # Initial state contains location and a dummy action\n",
    "    init_state = NamedTuple{(:loc, :act)}((init_loc, (0, 0)))\n",
    "    # Simulate agent and environment for T steps\n",
    "    model_states = {:steps} ~ agent_unfold(T, init_state, grid, goal, beta)\n",
    "    # Return goal and history of locations and actions\n",
    "    return goal, model_states\n",
    "end;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note the `(static)` annotation in front of `unfold_agent_model`, which declares\n",
    "it as a [static generative function](https://www.gen.dev/docs/dev/ref/modeling/sml/).\n",
    "This is currently required by Gen.jl to support incremental computation.\n",
    "\n",
    "By rewriting our model with the `Unfold` combinator, we can incrementally\n",
    "simulate our model using another of Gen's interface functions, `Gen.update`.\n",
    "Starting with a trace initialized with `T=0`, we'll repeatedly apply\n",
    "`Gen.update` to update the arguments passed to model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial trace at T=0:\n",
      "│\n",
      "├── :goal : (1, 1)\n",
      "│\n",
      "└── :steps\n",
      "\n",
      "After extending to T=20:\n",
      "│\n",
      "├── :goal : (1, 1)\n",
      "│\n",
      "└── :steps\n",
      "    │\n",
      "    ├── 1\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 2\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 3\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 4\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 5\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 6\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 7\n",
      "    │   │\n",
      "    │   └── :act : (0, 1)\n",
      "    │\n",
      "    ├── 8\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 9\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 10\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 11\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 12\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 13\n",
      "    │   │\n",
      "    │   └── :act : (0, 0)\n",
      "    │\n",
      "    ├── 14\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 15\n",
      "    │   │\n",
      "    │   └── :act : (-1, 0)\n",
      "    │\n",
      "    ├── 16\n",
      "    │   │\n",
      "    │   └── :act : (0, -1)\n",
      "    │\n",
      "    ├── 17\n",
      "    │   │\n",
      "    │   └── :act : (0, -1)\n",
      "    │\n",
      "    ├── 18\n",
      "    │   │\n",
      "    │   └── :act : (0, -1)\n",
      "    │\n",
      "    ├── 19\n",
      "    │   │\n",
      "    │   └── :act : (0, -1)\n",
      "    │\n",
      "    └── 20\n",
      "        │\n",
      "        └── :act : (0, 0)\n"
     ]
    }
   ],
   "source": [
    "# Start with T=0 (no actions taken yet)\n",
    "fixed_args = (grid, init_loc, goal_locs, beta)\n",
    "init_args = (0, fixed_args...)\n",
    "goal_constraint = choicemap((:goal, (1, 1)))\n",
    "trace, _ = Gen.generate(unfold_agent_model, init_args, goal_constraint)\n",
    "println(\"Initial trace at T=0:\")\n",
    "show(stdout, \"text/plain\", get_choices(trace))\n",
    "\n",
    "# Incrementally extend the trace for T=1, 2, 3, ...\n",
    "runtimes_unfold = Float64[]\n",
    "for T in 1:20\n",
    "    new_args = # Update the timestep argument\n",
    "        (T, fixed_args...)\n",
    "    argdiffs = # Inform Gen.update that no other arguments have changed\n",
    "        (UnknownChange(), NoChange(), NoChange(), NoChange(), NoChange())\n",
    "    stats = @timed begin\n",
    "        trace, _, _, _ = # Update the previous trace to get a new trace\n",
    "            Gen.update(trace, new_args, argdiffs, EmptyChoiceMap())\n",
    "    end\n",
    "    push!(runtimes_unfold, stats.time) # Record runtime\n",
    "end\n",
    "println(\"\\n\", \"After extending to T=20:\")\n",
    "show(stdout, \"text/plain\", get_choices(trace))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compared to our original model, the Unfold-based model has a slightly different\n",
    "address structure for its random choices: All addresses for the action variables\n",
    "are now nested under the address `:steps`, such that action $a_t$ has the\n",
    "address `:steps => t => :act`.\n",
    "\n",
    "If we plot the runtime of each update, we'll see that it is more or less\n",
    "constant across steps. This is because `Gen.update` only simulates the model for\n",
    "the most recent step when `T` is incremented."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
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\"/>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "GLMakie.Screen(...)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure = Figure(size=(800, 400))\n",
    "ax = Axis(figure[1, 1], title=\"Runt

## inv_plan_from_scratch.jl

      
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              inv_plan_from_scratch.jl
            
          
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              (Sorry about that, but we can’t show files that are this big right now.)
        
    
## videodisplay.jl

      
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              videodisplay.jl
            
          
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              (Sorry about that, but we can’t show files that are this big right now.)
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