project.ipynb

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      "source": [
        "# Lunar Lander Reinforcement Learning Project #\n",
        "\n",
        "Tyler Kinkade    \n"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "aDi3EokJtVWB"
      },
      "source": [
        "## Overview ##\n",
        "\n",
        "This write-up reports on a small project to compare the effectiveness of artificial agent algorithms ranging in sophistication from naive to deep reinforcement learning (Russell & Norvig, 2022; Sutton & Barto, 2018) to successfully land a virtual \"lunar lander\" in a Gymnasium (2022) model environment. After comparing the various models, I explore the effects of various hyperparameters on a deep Q-network model (Mnih et al., 2015).\n",
        "\n",
        "The report is divided into three main sections: approach, results, and discussion."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "oxfx3dpPtVWB"
      },
      "source": [
        "## Approach ##\n",
        "\n",
        "My approach to the problem is described in the following environment, models, and methods subsections."
      ]
    },
    {
      "attachments": {},
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      "source": [
        "### Environment ###\n",
        "\n",
        "The lunar lander environment (pictured below) simulates rocket trajectory physics with the primary aim of landing a lunar lander on a central landing pad (marked by two flags) by means of turning its three rocket thrusters (left, right, and main) on or off. The agent operating the lander is rewarded for landing slowly, in an upright position, on both legs, on or near the landing pad and penalized otherwise. Fuel is unlimited, but a penalty is given for each time an engine fires. Episodes are truncated after 1000 time-steps. Scores of 200 points or more are considered a solution. \n",
        "\n",
        "The state space is described by an 8-vector comprised of the lander coordinates $(x,y)$, its linear velocities $(v_x,v_y)$ in the $x$ and $y$ directions, its angle $(\\theta)$, its angular velocity $(\\omega)$, and two Boolean variables $(l,r)$ that encode whether the left and right legs are in contact with the ground. The environment has both discrete and continuous versions, but only the discrete version is used here, in order to include simple models in the comparison. The environment gravity, wind power, and turbulence can also be specified. The starting state is the top center of the space with a random force applied to the lander. The termination state occurs when the lander stops moving or moves outside the frame. The action space is comprised of 4 discrete actions: do nothing, fire left thruster, fire main down thruster, or fire right thruster."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "DfDyQ_Q6tVWC",
        "outputId": "364740f7-3360-4ad3-a556-ff95baae1f48"
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      "outputs": [
        {
          "data": {
            "text/html": [
              "<img src=\"https://gymnasium.farama.org/_images/lunar_lander.gif\"/>"
            ],
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Display Lunar Lander GIF\n",
        "from IPython.display import Image\n",
        "Image(url= \"https://gymnasium.farama.org/_images/lunar_lander.gif\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "ACpbtMfztVWE"
      },
      "outputs": [],
      "source": [
        "# Install dependencies\n",
        "# Packages preinstalled on Google Colab:\n",
        "# !pip install numpy\n",
        "# !pip install pandas\n",
        "# !pip install matplotlib\n",
        "# !pip install torch\n",
        "\n",
        "# Packages not pre-installed on Google Colab:\n",
        "# !pip install moviepy\n",
        "# !pip install torchinfo\n",
        "# !pip install ufal.pybox2d\n",
        "# !pip install gymnasium\n",
        "# !pip install gymnasium[box2d]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hGBVDYBDtVWF",
        "outputId": "da48a956-65d0-451a-b780-6c8e2d5afd0f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Environment metadata:\n",
            " {'render_modes': ['human', 'rgb_array'], 'render_fps': 50}\n",
            "\n",
            "State space:\n",
            " Box([-90.        -90.         -5.         -5.         -3.1415927  -5.\n",
            "  -0.         -0.       ], [90.        90.         5.         5.         3.1415927  5.\n",
            "  1.         1.       ], (8,), float32)\n",
            "\n",
            "Action space:\n",
            " Discrete(4)\n",
            "\n",
            "Starting state:\n",
            " [ 0.00786695  1.4032904   0.796822   -0.33911794 -0.00910905 -0.18049194\n",
            "  0.          0.        ]\n"
          ]
        }
      ],
      "source": [
        "# Display environment parameters\n",
        "# References: \n",
        "# https://gymnasium.farama.org/api/env/\n",
        "# https://gymnasium.farama.org/environments/box2d/lunar_lander/\n",
        "\n",
        "import gymnasium as gym\n",
        "\n",
        "# Initialize environment\n",
        "env = gym.make(\"LunarLander-v2\", \n",
        "               continuous = False,      # Discrete version\n",
        "               gravity = -10.0, \n",
        "               enable_wind = False, \n",
        "               wind_power = 0.0, \n",
        "               turbulence_power = 0.0, \n",
        "               render_mode=\"rgb_array\") # Render for machine\n",
        "\n",
        "# Reset environment with random number generator seed for reproducibility\n",
        "state, info = env.reset(seed = 21)\n",
        "\n",
        "print(\"Environment metadata:\\n\", env.metadata)\n",
        "print(\"\\nState space:\\n\", env.observation_space)\n",
        "print(\"\\nAction space:\\n\", env.action_space)\n",
        "print(\"\\nStarting state:\\n\", state)"
      ]
    },
    {
      "attachments": {},
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        "id": "j9WYmiQbtVWF"
      },
      "source": [
        "The table below summarizes the descriptive statistics for 100 randomly sampled initial states for this environment. We can see that the initial linear and angular velocities vary more than the position and angular orientation."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "xkBzvsWztVWF",
        "outputId": "f3057c8d-ab76-4a53-935e-f0cfe981a880"
      },
      "outputs": [
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              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "      <th>vx</th>\n",
              "      <th>vy</th>\n",
              "      <th>angle</th>\n",
              "      <th>ang_vel</th>\n",
              "      <th>left_leg</th>\n",
              "      <th>right_leg</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>-0.000202</td>\n",
              "      <td>1.410030</td>\n",
              "      <td>-0.020460</td>\n",
              "      <td>-0.039560</td>\n",
              "      <td>0.000241</td>\n",
              "      <td>0.004635</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.004445</td>\n",
              "      <td>0.007046</td>\n",
              "      <td>0.450270</td>\n",
              "      <td>0.313165</td>\n",
              "      <td>0.005151</td>\n",
              "      <td>0.101993</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-0.007806</td>\n",
              "      <td>1.398572</td>\n",
              "      <td>-0.790636</td>\n",
              "      <td>-0.548822</td>\n",
              "      <td>-0.009096</td>\n",
              "      <td>-0.180236</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.003390</td>\n",
              "      <td>1.404051</td>\n",
              "      <td>-0.343335</td>\n",
              "      <td>-0.305285</td>\n",
              "      <td>-0.003875</td>\n",
              "      <td>-0.076865</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-0.000128</td>\n",
              "      <td>1.409595</td>\n",
              "      <td>-0.012973</td>\n",
              "      <td>-0.058933</td>\n",
              "      <td>0.000155</td>\n",
              "      <td>0.002939</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.003350</td>\n",
              "      <td>1.416666</td>\n",
              "      <td>0.339339</td>\n",
              "      <td>0.255355</td>\n",
              "      <td>0.003934</td>\n",
              "      <td>0.077771</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>0.007856</td>\n",
              "      <td>1.421770</td>\n",
              "      <td>0.795693</td>\n",
              "      <td>0.482209</td>\n",
              "      <td>0.009052</td>\n",
              "      <td>0.179091</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                x           y          vx          vy       angle     ang_vel   \n",
              "count  100.000000  100.000000  100.000000  100.000000  100.000000  100.000000  \\\n",
              "mean    -0.000202    1.410030   -0.020460   -0.039560    0.000241    0.004635   \n",
              "std      0.004445    0.007046    0.450270    0.313165    0.005151    0.101993   \n",
              "min     -0.007806    1.398572   -0.790636   -0.548822   -0.009096   -0.180236   \n",
              "25%     -0.003390    1.404051   -0.343335   -0.305285   -0.003875   -0.076865   \n",
              "50%     -0.000128    1.409595   -0.012973   -0.058933    0.000155    0.002939   \n",
              "75%      0.003350    1.416666    0.339339    0.255355    0.003934    0.077771   \n",
              "max      0.007856    1.421770    0.795693    0.482209    0.009052    0.179091   \n",
              "\n",
              "       left_leg  right_leg  \n",
              "count     100.0      100.0  \n",
              "mean        0.0        0.0  \n",
              "std         0.0        0.0  \n",
              "min         0.0        0.0  \n",
              "25%         0.0        0.0  \n",
              "50%         0.0        0.0  \n",
              "75%         0.0        0.0  \n",
              "max         0.0        0.0  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "# Determine average starting state from 100 random samples\n",
        "starting_states = []\n",
        "for _ in range(100):\n",
        "    starting_state, info = env.reset()\n",
        "    starting_states.append(starting_state)\n",
        "\n",
        "features = ['x','y','vx','vy','angle','ang_vel','left_leg','right_leg']\n",
        "starting_states_df = pd.DataFrame(starting_states, columns = features)\n",
        "starting_states_df.describe()"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "86xigl67tVWG"
      },
      "source": [
        "### Models ###\n",
        "Four models are compared in this project: an agentless lunar lander, a random agent, a simple reflex agent, and a deep Q-network agent. "
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "s3etHtRptVWG"
      },
      "source": [
        "#### Agentless Lunar Lander ####\n",
        "An agentless lunar lander takes no action and is at the complete mercy of its environment. Because the starting state is directly above the landing pad, this might not be as terrible a strategy as it initially seems. The lander will simply fall to the ground in a trajectory determined by the physics of the environmental forces and the initial force placed upon it.\n",
        "\n",
        "#### Random Agent ####\n",
        "\n",
        "A random agent selects any of the possible actions uniformly randomly at each step without regard to the environment. The animation above is an example of such an agent and appears to be a poor strategy. Is this a worse strategy than an agentless lander though?\n",
        "\n",
        "#### Simple Reflex Agent ####\n",
        "\n",
        "A simple reflex agent can only react in a fixed way to sensory input but does not retain any memory of the past and, as a result, cannot learn (Russell & Norvig, 2022). As explained in the environment section, the initial lunar lander position is generally centered above the landing pad, but there is wide variation in initial linear and angular velocity. Thus, the primary task is counteracting any horizontal velocity while at the same time, avoiding turning the ship on its side. Therefore, there is a balance to be achieved, and the programmer must select appropriate threshold constants for the algorithm. Depending on the algorithm and constants, this could potentially be a better strategy than doing nothing or acting randomly."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
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      "source": [
        "#### Deep Q-Network Agent ####\n",
        "\n",
        "A deep Q-network (DQN; Mnih et al., 2015, 2016) agent is a deep-learning neural network approximation of a Q-learning agent (Russell & Norvig, 2022; Sutton & Barto, 2018). A Q-learning agent alternates between learning through exploration and exploiting what it has learned by choosing the action with maximal value for each state. Although this is obviously better than the relatively ignorant reflex agent, Q-learning agents can quickly become computationally expensive and slow to learn in large and complex environments (Russell & Norvig, 2022; Sutton & Barto, 2018). \n",
        "\n",
        "Approximate Q-learning agents address this problem by approximating the Q-value of actions in particular states with a weighted feature function based on states and actions (Russell & Norvig, 2022; Sutton & Barto, 2018). However, in the environment in this project, we only have access to the current features and do not know with certainty how any particular action will influence those features. \n",
        "\n",
        "Fortunately, the universal approximation theorem tells us that we can approximate any function with a neural network of at least two layers  (Russell & Norvig, 2022). Thus, we can approximate a Q-value function with a DQN by recording a log of previous attempts (i.e., replay buffer) to train the model (Paszke & Towers, 2017). In other words, the agent remembers and learns from its experiences. In addition, this allows us to sample randomly from the buffer to reduce variance (Morales, 2020). Value gradient clipping will be used to avoid exploding gradients (Goodfellow et al., 2016).\n",
        "\n",
        "For this project, the DQN consists of three fully-connected neural network layers. A non-linear activation function is placed between the layers to prevent the model from collapsing into a one-layer linear model. Here, a rectified linear unit (ReLU) function is selected for this because of its computational simplicity and its consistent, demonstrated effectiveness in previous studies (Goodfellow et al., 2016; Karpathy, 2016). The inputs to the network are the eight state features and the output is a vector of approximate Q-values for each of the four possible actions given the input state. \n",
        "\n",
        "It is worth noting that image-based convolutional neural networks are frequently used for DQNs (e.g., Mnih et al., 2015). However, I am interested here in solving the lunar landing problem from the perspective of the sensory information available to an agent within the lunar lander, rather than an outside observer.\n",
        "\n",
        "Another design choice is how often the agent should explore versus how often it should exploit what it has learned thus far. For this project, I will use an epsilon-greedy policy which prioritizes learning at the beginning but gradually shifts to prioritizing the highest rewards by selecting the policy it has learned thus far.\n",
        "\n",
        "To train the model, I will use the Huber loss function (Huber, 1964), which is more robust to noisy data than mean-squared error for training the model (Paszke & Towers, 2017).For optimization, I will use the AdamW optimization algorithm (Loshchilov & Hutter, 2019). Unlike the stochastic gradient descent algorithm, Adam optimization maintains and adapts separate learning rates for each parameter (Brownlee, 2017). AdamW improves upon this by decoupling weight decay from the gradient update (Loshchilov & Hutter, 2019). Gradient clipping will be used to avoid exploding gradients (Goodfellow et al., 2016).\n",
        "\n",
        "A potential problem with training DQNs is that parameter updates cause the targets to shift leading to divergence away from an optimal policy (Morales, 2020). To counteract this two networks of parameters are used: an online network which is updated every iteration and a target netowrk which is updated less frequently, or at a specified rate $\\tau$, and whose Q-values are used to calculate the loss and train the online set. This allows the parameters to stabilize.\n",
        "\n",
        "It is expected that the DQN model will perform better than the first three; however, it is still possible that some difficulties might arise in creating a neural network which converges to an optimal policy."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "ah58GhAitVWH"
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      "source": [
        "### Methods ###\n",
        "\n",
        "The first three models do not require training, so they will only be run for 100 episodes because their average score will not differ significantly after even more episodes. The DQN model will likely require more training as well as hyperparameter tuning. For all models, the single-episode truncation will be reduced to 600 time-steps in order to decrease the training time.\n",
        "\n",
        "The scores over each of the episodes will be plotted and compared. Visualizing each model's performance over successive episodes permits comparison of how each agent progressed in learning how to solve the model. As Machado and his colleagues (2018) point out, this is preferable to single metrics, such as maximum or average scores which can conceal important distinctions. For example, we can discover whether an agent achieved a maximum only once, but performed poorly most of the time. Similarly, an average score can conceal unstable, fluctuating performance. Ideally, we would like to see an agent learning quickly and then stably maintaining high scores above the solution threshold of 200 points.\n",
        "\n",
        "Applying this methodology, we will be able to explore the advantages and disadvantages of the various models and also demonstrate how a solution to the problem can be explored through the modfication of features and comparison of models.\n",
        "\n",
        "In the following code blocks, I construct the Python classes required to implement each of the agents."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "NWD40CbatVWH"
      },
      "source": [
        "#### Agentless Lunar Lander ####\n",
        "The following code implements an agentless lunar lander which never fires any of its thrusters. This will also be used as the base class for the other agents."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "JsUcVw-RtVWH"
      },
      "outputs": [],
      "source": [
        "# Define general lunar lander class\n",
        "#\n",
        "# Adapted from: \n",
        "# CSPB 3202 Gym tutorial (https://applied.cs.colorado.edu/mod/folder/view.php?id=43136)\n",
        "# https://gymnasium.farama.org/\n",
        "# https://gymnasium.farama.org/api/utils/#save-rendering-videos\n",
        "# https://gymnasium.farama.org/environments/box2d/lunar_lander/\n",
        "# https://github.com/openai/gym/blob/master/gym/envs/box2d/lunar_lander.py\n",
        "# https://gymnasium.farama.org/tutorials/training_agents/FrozenLake_tuto/\n",
        "# https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html\n",
        "#\n",
        "# Additional references:\n",
        "# https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.isinteractive.html\n",
        "# https://www.statology.org/matplotlib-inline/\n",
        "# https://www.tutorialspoint.com/how-to-check-that-pylab-backend-of-matplotlib-runs-inline\n",
        "# https://learnpython.com/blog/average-in-matplotlib/\n",
        "\n",
        "from gymnasium.utils.save_video import save_video\n",
        "import numpy as np\n",
        "from IPython.utils.capture import capture_output\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Display graphs inline\n",
        "%matplotlib inline\n",
        "\n",
        "# Check if inline display is possible\n",
        "is_ipython = 'inline' in matplotlib.get_backend()\n",
        "\n",
        "# If Jupyter notebook\n",
        "if is_ipython:\n",
        "    from IPython import display\n",
        "\n",
        "class LunarLander:\n",
        "    '''\n",
        "    General lunar lander class \n",
        "    subject entirely to its environment\n",
        "    '''   \n",
        "    def __init__(self, name = \"Agentless Lander\", step_limit = 600):\n",
        "        '''\n",
        "        Initialize agent\n",
        "        '''\n",
        "        self.name = name\n",
        "        self.prefix = \"-\".join(name.split()).lower() # filename prefix\n",
        "        self.step_limit = step_limit  # max. allowed steps/episode\n",
        "\n",
        "        # Initialize environment\n",
        "        self.env = gym.make(\"LunarLander-v2\", \n",
        "               continuous = False,           # Discrete version\n",
        "               gravity = -10.0, \n",
        "               enable_wind = False, \n",
        "               wind_power = 0.0, \n",
        "               turbulence_power = 0.0, \n",
        "               render_mode=\"rgb_array_list\") # Render for machine\n",
        "\n",
        "        # Define actions\n",
        "        self.NOOP = 0   # No operation (i.e., do nothing)\n",
        "        self.LEFT = 1   # Fire left orientation engine\n",
        "        self.MAIN = 2   # Fire main downward engine\n",
        "        self.RIGHT = 3  # Fire right orientation engine\n",
        "\n",
        "        # Reset environment with random number generator seed for reproducibility\n",
        "        self.state, self.info = self.env.reset(seed = 21)\n",
        "        \n",
        "        # Set environment dimensions\n",
        "        self.features_size = len(self.state)\n",
        "        self.actions_size = env.action_space.n\n",
        "  \n",
        "        # Initialize data logs\n",
        "        self.scores = []\n",
        "        self.steps = []\n",
        "        self.policy = []\n",
        "\n",
        "        # Initialize total iteration step count\n",
        "        self.total_steps = 0\n",
        "\n",
        "        # Initialize parameters needed for reinforcement learning agents\n",
        "        # to prevent errors. These will not be used for non-RL agents\n",
        "        self.memory = [] \n",
        "        self.batch_size = 1\n",
        "        self.scheduler = None\n",
        "\n",
        "    def select_action(self, state):\n",
        "        '''\n",
        "        Select action given state\n",
        "        '''\n",
        "        # Do nothing\n",
        "        return self.NOOP\n",
        "\n",
        "    def episode(self):\n",
        "        '''\n",
        "        Complete episode in given environment\n",
        "        Return score, steps count, and actions log\n",
        "        '''\n",
        "        # Initialize rewards total\n",
        "        score = 0.0\n",
        "\n",
        "        # Initialize steps count\n",
        "        episode_steps = 0\n",
        "\n",
        "        # Initialize actions list\n",
        "        actions = []\n",
        "\n",
        "        # Start new episode  \n",
        "        state, info = self.env.reset()\n",
        "\n",
        "        # Until end of episode\n",
        "        while True:\n",
        "            # Get action based on current state\n",
        "            action = self.select_action(state)\n",
        "\n",
        "            # Obtain next state, reward, terminated status, truncated status, \n",
        "            # and environment info for given action\n",
        "            next_state, reward, terminated, truncated, info = self.env.step(action)\n",
        "            \n",
        "            # Accumulate reward total\n",
        "            score += reward\n",
        "\n",
        "            # Increment episode steps\n",
        "            episode_steps += 1\n",
        "\n",
        "            # Increment overall step count\n",
        "            self.total_steps += 1\n",
        "\n",
        "            # Record action\n",
        "            actions.append(action)\n",
        "\n",
        "            # If number of steps has been surpassed or end of episode\n",
        "            if (episode_steps > self.step_limit) or terminated or truncated:\n",
        "                break  # out of loop\n",
        "            \n",
        "            # Advance to next state \n",
        "            state = next_state\n",
        "\n",
        "        return score, episode_steps, actions\n",
        "    \n",
        "    def iterate(self, n = 100,      # Number of iterations\n",
        "                verbose = False,    # Print results for each episode\n",
        "                video = False,      # Output videos of (k^3)th episodes\n",
        "                plot = True):       # Display plot updated every episode\n",
        "        '''\n",
        "        Attempt task for n episodes\n",
        "        '''\n",
        "        # Enable interactive plotting\n",
        "        plt.ion()\n",
        "\n",
        "        # Counter for indexing start of videos\n",
        "        video_step_start = 0\n",
        "\n",
        "        # Repeat n times\n",
        "        for episode in range(n):\n",
        "            # Complete one episode\n",
        "            score, episode_steps, actions = self.episode()\n",
        "            \n",
        "            # Log scores, steps, policy\n",
        "            self.scores.append(score)\n",
        "            self.steps.append(episode_steps)\n",
        "            self.policy.append(actions)\n",
        "\n",
        "            # If there are at least buffer_size transitions \n",
        "            # in the buffer memory\n",
        "            if (len(self.memory) >= self.batch_size):                        \n",
        "                # Increment learning rate scheduler count\n",
        "                # Scheduler will perform learning rate decrement\n",
        "                # after kth episode specified in lr_period parameter \n",
        "                self.scheduler.step()\n",
        "            \n",
        "            if plot:\n",
        "                # Update training plot\n",
        "                self.plot_scores()\n",
        "\n",
        "            if verbose:\n",
        "                # Report result\n",
        "                print(f\"Episode {episode} score: {score}\")\n",
        "\n",
        "            if video:\n",
        "                # Suppress MoviePy stdout\n",
        "                # https://stackoverflow.com/a/35624406/14371011\n",
        "                with capture_output() as captured:\n",
        "                    # Save mp4 of every (k^3)th episode (0, 1, 8, 27, ...)\n",
        "                    save_video(self.env.render(),\n",
        "                               video_folder = \"videos\",\n",
        "                               name_prefix = self.prefix,\n",
        "                               fps = env.metadata[\"render_fps\"],\n",
        "                               step_starting_index = video_step_start,\n",
        "                               episode_index = episode)\n",
        "\n",
        "            # Advance starting step index for videos\n",
        "            video_step_start = episode_steps + 1           \n",
        "        \n",
        "        if plot:\n",
        "            # Plot final result\n",
        "            self.plot_scores(show_result = True)\n",
        "            plt.show() # Display plot\n",
        "\n",
        "        # Disable interactive plotting\n",
        "        plt.ioff() \n",
        "    \n",
        "    def score_stats(self, verbose = False):\n",
        "        '''\n",
        "        Return mean, max, and min of scores if they exist \n",
        "        '''\n",
        "        # If scores exist\n",
        "        if (len(self.scores) > 0):\n",
        "            # Calculate average, max, and min score\n",
        "            average = np.average(self.scores)\n",
        "            max = np.max(self.scores)\n",
        "            min = np.min(self.scores)\n",
        "            \n",
        "            # Calculate average episode length\n",
        "            avg_length = np.average(self.steps)\n",
        "\n",
        "            if verbose:\n",
        "                # Report average, max, and min\n",
        "                print(f\"\\nAverage score: {average:.1f}\") \n",
        "                print(f\"Maximum score: {max:.1f}\")\n",
        "                print(f\"Minimum score: {min:.1f}\")\n",
        "                print(f\"Average episode length: {avg_length:.1f}\")\n",
        "\n",
        "            return average, max, min, avg_length\n",
        "        else: \n",
        "            print(\"No scores have been calculated\")\n",
        "            return None, None, None\n",
        "        \n",
        "    def plot_scores(self, show_result = False):\n",
        "        '''\n",
        "        Dynamically plot episode scores\n",
        "        Plot running average at conclusion \n",
        "        '''\n",
        "        # Initialize plot\n",
        "        plt.figure(1)\n",
        "\n",
        "        # If not final plot\n",
        "        if not show_result:\n",
        "            # Clear current figure\n",
        "            plt.clf()\n",
        "\n",
        "        # Plot solution threshold\n",
        "        plt.axhline(y = 200, color = \"r\", linestyle = \"dashed\", label = \"Solution Threshold\")  \n",
        "\n",
        "        # Plot episode-by-episode scores\n",
        "        plt.plot(self.scores, label = self.name)\n",
        "        plt.title(self.name)\n",
        "        plt.xlabel(\"Episode\")\n",
        "        plt.ylabel(\"Score\")\n",
        "\n",
        "        # If final plot\n",
        "        if show_result:\n",
        "            # Plot running average\n",
        "\n",
        "            # Span for running average\n",
        "            window = 25\n",
        "            \n",
        "            # Initialize list with one fewer NaNs than window\n",
        "            averages = [np.nan] * (window - 1)\n",
        "\n",
        "            # Calculate running average\n",
        "            for idx in range(len(self.scores) - window + 1):\n",
        "                averages.append(np.mean(self.scores[idx : idx + window]))\n",
        "\n",
        "            # Plot running average\n",
        "            plt.plot(averages, color = \"k\", label = \"Running Average\")\n",
        "\n",
        "        plt.legend()\n",
        "\n",
        "        # Pause to allow plot to update\n",
        "        plt.pause(0.001)\n",
        "\n",
        "        # If Jupyter notebook\n",
        "        if is_ipython:\n",
        "            if not show_result:\n",
        "                # Display plot\n",
        "                display.display(plt.gcf())\n",
        "                # Clear plot when done\n",
        "                display.clear_output(wait = True)\n",
        "            else:\n",
        "                # Display plot\n",
        "                display.display(plt.gcf())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "41"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Video clips are saved in cubic intervals of episodes, so for reference, the first 41 cubes (from https://oeis.org/A000578) are:\n",
        "cubes = [0, 1, 8, 27, 64, 125, 216, 343, 512, 729, 1000, 1331, 1728, 2197, 2744, 3375, 4096, 4913, 5832, 6859, 8000, 9261, 10648, 12167, 13824, 15625, 17576, 19683, 21952, 24389, 27000, 29791, 32768, 35937, 39304, 42875, 46656, 50653, 54872, 59319, 64000]\n",
        "len(cubes)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "i3fbD0QRtVWJ"
      },
      "source": [
        "#### Random Agent ####\n",
        "The following coe implements an agent which selects any of the four possible actions randomly at each time step:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "t86p3I3GtVWJ"
      },
      "outputs": [],
      "source": [
        "# Define random agent class\n",
        "\n",
        "class RandomAgent(LunarLander):\n",
        "    '''\n",
        "    Inherits from lunar lander class\n",
        "    and acts randomly\n",
        "    '''\n",
        "    def __init__(self, name = \"Random Agent\"):\n",
        "        LunarLander.__init__(self, name)\n",
        "\n",
        "    def select_action(self, state):\n",
        "        '''\n",
        "        Randomly select action\n",
        "        '''\n",
        "        # Randomly select action from action space\n",
        "        action = self.env.action_space.sample()\n",
        "\n",
        "        return action"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "24fs2PoStVWJ"
      },
      "source": [
        "#### Simple Reflex Agent ####\n",
        "\n",
        "This is an agent which can fire its side thrusters in reaction to its current horizontal and angular velocity in relation to threshold constants chosen by the programmer."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "VJiSwQLktVWJ"
      },
      "outputs": [],
      "source": [
        "class ReflexAgent(LunarLander):\n",
        "    '''\n",
        "    Inherits from lunar lander class, but \n",
        "    selects actions according to horizontal \n",
        "    and angular position and angular velocity\n",
        "    '''\n",
        "    def __init__(self, name = \"Reflex Agent\"):\n",
        "        LunarLander.__init__(self, name)\n",
        "\n",
        "    def select_action(self, state):\n",
        "        '''\n",
        "        Select action according to horizontal and\n",
        "        angular position and angular velocity\n",
        "        '''\n",
        "        # Set tolerances\n",
        "        horiz_vel_tolerance = 0.4\n",
        "        ang_vel_tolerance = 0.001\n",
        "\n",
        "        # Horizontal velocity\n",
        "        vx = state[3]\n",
        "\n",
        "        # Angular velocity\n",
        "        ang_vel = state[5]\n",
        "\n",
        "        # If leftward horizontal velocity\n",
        "        if ((vx < -horiz_vel_tolerance) and\n",
        "            # and clockwise velocity\n",
        "            (ang_vel > ang_vel_tolerance)):\n",
        "\n",
        "            # Then, fire thruster to move right\n",
        "            action = self.RIGHT\n",
        "        \n",
        "        # If rightward horizontal velocity\n",
        "        elif ((vx > horiz_vel_tolerance) and\n",
        "              # If counter-clockwise velocity\n",
        "              (ang_vel < -ang_vel_tolerance)):\n",
        "            \n",
        "            # Then, fire thruster to move left\n",
        "            action = self.LEFT\n",
        "\n",
        "        else:\n",
        "            # Do nothing\n",
        "            action = self.NOOP\n",
        "        \n",
        "        return action "
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "F9Sjqo-2tVWJ"
      },
      "source": [
        "#### Deep Q-Network Agent ####\n",
        "\n",
        "A deep Q-network agent has the capacity to remember and learn from its previous experiences using a neural network.\n",
        "\n",
        "##### Replay Memory and Deep Q-Network #####\n",
        "First, we must define a buffer to remember previous experiences and a neural network for the agent to use for learning."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "bkRp09t2tVWJ"
      },
      "outputs": [],
      "source": [
        "# Define Replay Memory Buffer and Deep Q-Network\n",
        "# Adapted from: https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html\n",
        "# Additional references:\n",
        "# https://pytorch.org/tutorials/beginner/introyt/modelsyt_tutorial.html#building-models-with-pytorch\n",
        "# https://pytorch.org/docs/stable/notes/randomness.html\n",
        "\n",
        "import random\n",
        "from collections import namedtuple, deque\n",
        "\n",
        "# Named tuple data structure to encode a single state transition\n",
        "Transition = namedtuple('Transition',\n",
        "                        ('state', 'action', 'next_state', 'reward'))\n",
        "\n",
        "# Buffer class to hold and randomly sample recent transitions\n",
        "class ReplayMemory(object):\n",
        "\n",
        "    def __init__(self, capacity):\n",
        "        '''\n",
        "        Initialize buffer with empty double-ended queue\n",
        "        of size \"capacity\"\n",
        "        '''\n",
        "        self.memory = deque([], maxlen = capacity)\n",
        "\n",
        "        # Set random seed for reproducibility\n",
        "        random.seed(21)\n",
        "\n",
        "    def push(self, *args):\n",
        "        '''\n",
        "        Add a transition to buffer\n",
        "        '''\n",
        "        self.memory.append(Transition(*args))\n",
        "\n",
        "    def sample(self, batch_size):\n",
        "        '''\n",
        "        Randomly sample batch of transitions from buffer\n",
        "        '''\n",
        "        return random.sample(self.memory, batch_size)\n",
        "\n",
        "    def __len__(self):\n",
        "        '''\n",
        "        Returns number of transitions in buffer\n",
        "        '''\n",
        "        return len(self.memory)\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "\n",
        "# Deep Q-Network\n",
        "class DQN(nn.Module):\n",
        "\n",
        "    def __init__(self, features_size, actions_size):\n",
        "        '''\n",
        "        Initialize neural network\n",
        "        '''\n",
        "        super(DQN, self).__init__()\n",
        "\n",
        "        # First fully-connected layer: \n",
        "        # Input dimensions: 1 x no. of state feature\n",
        "        # Output dimensions: 1 x 128\n",
        "        self.fc1 = nn.Linear(features_size, 128)\n",
        "\n",
        "        # Second fully-connected layer: \n",
        "        # Input: 1 x 128; Output: 1 x 128\n",
        "        self.fc2 = nn.Linear(128, 128)\n",
        "\n",
        "        # Final fully-connected layer: \n",
        "        # Input: 1 x 128; \n",
        "        # Output: 1 x no. of possible actions\n",
        "        self.fc3 = nn.Linear(128, actions_size)\n",
        "\n",
        "    def forward(self, state):\n",
        "        '''\n",
        "        Forward propagation function\n",
        "        Input: State features (e.g., position, velocity, ...)\n",
        "        Output: tensor of action values\n",
        "        '''\n",
        "        # First layer followed by ReLU activation function\n",
        "        z = F.relu(self.fc1(state))\n",
        "        \n",
        "        # Second layer followed by ReLU activation function\n",
        "        z = F.relu(self.fc2(z))\n",
        "        \n",
        "        # Final output layer\n",
        "        return self.fc3(z)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "q0SUVYjMtVWK"
      },
      "source": [
        "##### DQN Agent ####\n",
        "Now we can define the agent."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "q0DyA0d-tVWK"
      },
      "outputs": [],
      "source": [
        "# Define DQN agent\n",
        "# References:\n",
        "# Adapted from: https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html\n",
        "# Additional references:\n",
        "# https://pytorch.org/tutorials/beginner/introyt/modelsyt_tutorial.html#building-models-with-pytorch\n",
        "# https://pytorch.org/docs/stable/notes/randomness.html\n",
        "# https://pytorch.org/docs/stable/generated/torch.optim.AdamW.html\n",
        "# https://pytorch.org/docs/stable/generated/torch.max.html\n",
        "# https://stackoverflow.com/questions/19339/transpose-unzip-function-inverse-of-zip/19343\n",
        "# https://pytorch.org/tutorials/beginner/basics/optimization_tutorial.html\n",
        "# https://pytorch.org/docs/stable/optim.html\n",
        "# https://pytorch.org/docs/stable/generated/torch.optim.lr_scheduler.StepLR.html\n",
        "# https://machinelearningmastery.com/using-learning-rate-schedule-in-pytorch-training/\n",
        "\n",
        "\n",
        "import torch.optim as optim\n",
        "import math\n",
        "\n",
        "class DQNAgent(LunarLander):\n",
        "    '''\n",
        "    Inherits from lunar lander class, but \n",
        "    iteratively learns from experience to approximate \n",
        "    Q-values from state features with a neural network\n",
        "    '''\n",
        "    def __init__(self, \n",
        "                 name = \"DQN Agent\", \n",
        "                 alpha = 0.1,          # initial optimizer learning rate\n",
        "                 epsilon = (1.0,       # epsilon-greedy max\n",
        "                            0.01,      # epsilon-greedy min\n",
        "                            0.001),    # exponential decay rate (smaller = slower)\n",
        "                 gamma = 0.99,         # discount rate\n",
        "                 tau = 0.005,          # target network update rate\n",
        "                 lr_period = 100,      # episodes between learning rate decreases\n",
        "                 lr_decay = 0.1,       # learning rate decay      \n",
        "                 batch_size = 128,     # replay buffer batch size\n",
        "                 buffer_size = 1000000 # replay buffer size (no. of transitions)\n",
        "                 ):\n",
        "        '''\n",
        "        Initialize agent hyperparameters and data structures\n",
        "        '''\n",
        "        LunarLander.__init__(self, name)\n",
        "        self.alpha = alpha\n",
        "        self.eps_max, self.eps_min, self.eps_decay = epsilon\n",
        "        self.gamma = gamma\n",
        "        self.tau = tau\n",
        "        self.batch_size = batch_size\n",
        "        self.total_steps = 0\n",
        "\n",
        "        # Set random seeds for reproducibility\n",
        "        torch.manual_seed(21)\n",
        "        random.seed(21)\n",
        "\n",
        "        # Set device to GPU if available\n",
        "        self.device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "        print(\"Device:\",self.device)\n",
        "\n",
        "        # Initialize online and target deep Q-networks \n",
        "        # and move to selected device\n",
        "        self.online_net = DQN(self.features_size, self.actions_size).to(self.device)\n",
        "        self.target_net = DQN(self.features_size, self.actions_size).to(self.device)\n",
        "        self.target_net.load_state_dict(self.online_net.state_dict())\n",
        "\n",
        "        # Initialize optimizer\n",
        "        self.optimizer = optim.AdamW(self.online_net.parameters(), \n",
        "                                lr = self.alpha, # learning rate\n",
        "                                amsgrad = True)  # Reddi et al., 2019 variant\n",
        "        \n",
        "        # Initialize learning rate scheduler\n",
        "        self.scheduler = optim.lr_scheduler.StepLR(self.optimizer, \n",
        "                                                   step_size = lr_period, \n",
        "                                                   gamma = lr_decay,\n",
        "                                                   verbose = False)\n",
        "\n",
        "        # Initialize Huber loss function\n",
        "        self.criterion = nn.SmoothL1Loss()\n",
        "\n",
        "        # Initialize replay memory buffer \n",
        "        # with maximum capacity of buffer_size transitions\n",
        "        self.memory = ReplayMemory(buffer_size)\n",
        "\n",
        "    def select_action(self, state):\n",
        "        '''\n",
        "        Epsilon-greedy action selection with online DQN\n",
        "        '''       \n",
        "        # Calculate exponentially decaying epsilon-greedy threshold\n",
        "        # (as number of steps becomes large, threshold becomes minimum)\n",
        "        eps_threshold = (self.eps_min + (self.eps_max - self.eps_min) \n",
        "                        * math.exp(-self.total_steps * self.eps_decay))\n",
        "        \n",
        "        # Increment total steps\n",
        "        self.total_steps += 1\n",
        "\n",
        "        # Epsilon-greedy algorithm\n",
        "        # If random number [0,1) is greater than epsilon threshold\n",
        "        if (random.random() > eps_threshold):\n",
        "            # Without backward propagation \n",
        "            with torch.no_grad():\n",
        "                # Select action with maximum expected reward \n",
        "                # from online network\n",
        "\n",
        "                # Get index of maximum expected reward\n",
        "                max_value_index = self.online_net(state).max(1)[1]\n",
        "\n",
        "                # Get corresponding action\n",
        "                best_action = max_value_index.view(1,1)\n",
        "\n",
        "                return best_action\n",
        "            \n",
        "        else:\n",
        "            # Randomly select action from action space\n",
        "            # and return as tensor\n",
        "            return torch.tensor([[env.action_space.sample()]], \n",
        "                                device = self.device, dtype = torch.long)\n",
        "    \n",
        "    def optimize_model(self):\n",
        "        '''\n",
        "        Perform single step of optimization on batch of transitions\n",
        "        '''\n",
        "        # If fewer transitions in replay buffer than batch size\n",
        "        if len(self.memory) < self.batch_size:\n",
        "            # Can't run batch yet\n",
        "            # so, just keep collecting transitions\n",
        "            return\n",
        "        \n",
        "        else:\n",
        "            # Randomly select batch of transitions from\n",
        "            # replay buffer\n",
        "            transitions = self.memory.sample(self.batch_size)\n",
        "\n",
        "            # Transpose from batch array of transitions \n",
        "            # to transition of batch-arrays\n",
        "            batch = Transition(*zip(*transitions))\n",
        "\n",
        "            # Mask to select only non-final states \n",
        "            # (i.e., states whose next state is not null)\n",
        "            non_final_mask = torch.tensor(tuple(map(lambda s: \n",
        "                                                    s is not None, \n",
        "                                                    batch.next_state)), \n",
        "                                                    device = self.device, \n",
        "                                                    dtype = torch.bool)\n",
        "\n",
        "            # Concatenate the non-null next states\n",
        "            non_final_next_states = torch.cat([s for s in batch.next_state\n",
        "                                                if s is not None])\n",
        "            \n",
        "            # Concatenate states, actions, and rewards\n",
        "            state_batch = torch.cat(batch.state)\n",
        "            action_batch = torch.cat(batch.action)\n",
        "            reward_batch = torch.cat(batch.reward)\n",
        "\n",
        "            # Calculate online network Q-values for each state and action, Q(s,a) \n",
        "            online_Q_values = self.online_net(state_batch).gather(1, action_batch)\n",
        "\n",
        "            # Initialize tensor of next state expected rewards, V(s') = 0\n",
        "            target_next_state_values = torch.zeros(self.batch_size, device = self.device)\n",
        "                    \n",
        "            # Without back propagation\n",
        "            with torch.no_grad():\n",
        "                # Calculate target network expected reward (i.e., value) \n",
        "                # for each next state, V(s') (post-terminal states will have have value 0)\n",
        "                target_next_state_values[non_final_mask] = self.target_net(non_final_next_states).max(1)[0]\n",
        "                           \n",
        "            # Calculate target network expected Q values \n",
        "            target_expected_Q_values = ((target_next_state_values * self.gamma) \n",
        "                                            + reward_batch)\n",
        "\n",
        "            # Calculate loss by comparing online and target network Q values\n",
        "            loss = self.criterion(online_Q_values, \n",
        "                            target_expected_Q_values.unsqueeze(1))\n",
        "\n",
        "            # Reset optimizer gradients\n",
        "            self.optimizer.zero_grad()\n",
        "\n",
        "            # Back propagation\n",
        "            loss.backward()\n",
        "\n",
        "            # Perform gradient clipping by value to prevent exploding gradients\n",
        "            torch.nn.utils.clip_grad_value_(self.online_net.parameters(), 100)\n",
        "            \n",
        "            # Adjust learning weights\n",
        "            self.optimizer.step()\n",
        "\n",
        "    def episode(self):\n",
        "        '''\n",
        "        Complete episode in given environment\n",
        "        Call DQN optimizer\n",
        "        Update online and target networks\n",
        "        Return score, steps count, and actions log\n",
        "        '''\n",
        "        # Initialize rewards total\n",
        "        score = 0.0\n",
        "\n",
        "        # Initialize steps count\n",
        "        episode_steps = 0\n",
        "\n",
        "        # Initialize actions list\n",
        "        actions = []\n",
        "\n",
        "        # Start new episode  \n",
        "        state, info = self.env.reset()\n",
        "\n",
        "        #Convert to tensor\n",
        "        state = torch.tensor(state, \n",
        "                            dtype = torch.float32, \n",
        "                            device = self.device).unsqueeze(0)\n",
        "\n",
        "        # Until end of episode\n",
        "        while True:\n",
        "            # Get action based on current state\n",
        "            action = self.select_action(state)\n",
        "\n",
        "            # Obtain next state, reward, terminated status, truncated status, \n",
        "            # and environment info for given action\n",
        "            next_state, reward, terminated, truncated, info = self.env.step(action.item())\n",
        "\n",
        "            # Accumulate reward total\n",
        "            score += reward\n",
        "\n",
        "            # Convert reward to tensor\n",
        "            reward = torch.tensor([reward], device = self.device)\n",
        "\n",
        "            # Increment episode steps\n",
        "            episode_steps += 1\n",
        "\n",
        "            # Increment overall step count\n",
        "            self.total_steps += 1\n",
        "\n",
        "            # Record action\n",
        "            actions.append(action)\n",
        "\n",
        "            # If action taken leads to terminated state\n",
        "            if terminated or truncated:\n",
        "                # Next state is null\n",
        "                next_state = None\n",
        "            else:\n",
        "                # Convert next state to tensor\n",
        "                next_state = torch.tensor(next_state, \n",
        "                                        dtype = torch.float32, \n",
        "                                        device = self.device).unsqueeze(0)\n",
        "\n",
        "            # Store transition in replay buffer\n",
        "            self.memory.push(state, action, next_state, reward)\n",
        "         \n",
        "            # Advance to next state \n",
        "            state = next_state\n",
        "\n",
        "            # Perform one step of optimization on online network\n",
        "            self.optimize_model()            \n",
        "\n",
        "            # Get target and online network state dicts\n",
        "            target_net_state_dict = self.target_net.state_dict()\n",
        "            online_net_state_dict = self.online_net.state_dict()\n",
        "\n",
        "            # For each parameter in the online network state dict\n",
        "            for param in online_net_state_dict:\n",
        "                # Update target network weights at rate tau\n",
        "                # target parameter <-- tau(online parameter) + (1-tau)(target parameter)\n",
        "                target_net_state_dict[param] = (online_net_state_dict[param]*self.tau \n",
        "                                                + target_net_state_dict[param]*(1-self.tau))\n",
        "            \n",
        "            # Load updated target network state dict\n",
        "            self.target_net.load_state_dict(target_net_state_dict)\n",
        "\n",
        "            # If max. number of steps has been surpassed or end of episode\n",
        "            if (episode_steps > self.step_limit) or terminated or truncated:\n",
        "                break\n",
        "\n",
        "        return score, episode_steps, actions\n"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "b3xNdtajtVWL"
      },
      "source": [
        "## Results ## \n",
        "\n",
        "In this section, I compare the five different models: an agentless lunar lander, a random agent, a simple reflex agent, and a DQN agent."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "m66zGN-UtVWL"
      },
      "source": [
        "### Agentless Lunar Lander ###\n",
        "First, we consider the agentless lunar lander which never fires any of its thrusters and is therefore subject entirely to its environment:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "KDniF4JqtVWL",
        "outputId": "9435a2d4-8f84-4234-a126-37abc6d44f5c"
      },
      "outputs": [
        {
          "data": {
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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -135.8\n",
            "Maximum score: -2.8\n",
            "Minimum score: -270.4\n",
            "Average episode length: 71.0\n"
          ]
        }
      ],
      "source": [
        "# Instantiate agentless lunar lander\n",
        "agentless_lander = LunarLander()\n",
        "\n",
        "# Maintain list of agent objects\n",
        "agents = [agentless_lander]\n",
        "\n",
        "episodes = 100\n",
        "\n",
        "# Iterate over selected number of episodes\n",
        "agentless_lander.iterate(episodes, verbose = False, video = True, plot = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = agentless_lander.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "ojuXxHMxtVWL"
      },
      "source": [
        "[Link to the video of the agentless lander in the 64<sup>th</sup> episode](videos/agentless-lander-episode-64.mp4)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "nUoU5YJatVWL"
      },
      "source": [
        "In the above graph, we can see that an agentless lunar lander is not sufficient to solve this problem. In the video linked above, we can see the lunar lander simply falling in a slightly curved trajectory toward the ground."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "dM7A_JJNtVWL"
      },
      "source": [
        "### Random Agent ###\n",
        "\n",
        "Next, we consider the random agent which selects an action randomly."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "pR2-uokwtVWL",
        "outputId": "bb9668be-e851-4946-a00e-7ee5afb8c282"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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heTNWqbQdK96MNRgs452hUABSqfdjjUbLd+EMuRwgWR7ejDWZLL+dM2Qyy3hvx5rNlmPNH2OlUst3AVjOiaIi/4z15rwvj9cIci6bTMLnHvdaZzY7324ZjB3w/PPQ6/VYvWIFatasiczMTOzZuxfZ2dmebZdbMNCTsVxNC/nOrATI5QiIjLQ8xx3rzXZdjE2Ij0d6Who7du7XX2PHzp34Z+dOdkxYWBjWrV9vecAwHs9BbzRCzj3eXV3bRSLb98YdS/7lHkPOxjrbLoFhnN8H7LfB3a7JZPl/UZHt/dxrhKcwFZQbN24wAJgLFy4wDMMwe/bsYQAwubm5vHHVqlVj5s+fzzAMw3z88cdMkyZNeK/funWLAcCcPn1a8HO0Wi2Tn5/P/qWkpDAAmHzLz+H416sXfwOBgcLjAIbp2JE/tnJl52NbtOCPrV7d+dgGDfhjGzRwPrZ6df7YFi2cj61cmT+2Y0fnYwMD+WN79XI+1v4wHDjQ9djCQtvYYcNcj83Kso19803XY5OTbWMnTnQ99uJF29gZM1yPPX7cNnbOHNdj9+61jV20yPXYv/+2jV250vXY9ettY9evdz125Urb2L//dj120SLb2L17XY+dM8c29vhx12NnzLCNvXjR9diJE21jk5Ndj33zTdvYrCzXY4cNs40tLHQ9duBAhoerseXwGqF55hnm8vbtjObECYax/zt3jr/dS5ccx5C/M2f4Y69edT721Cn+2OvXnY89cYI/NimJYU6cYHL//ZcBwOxbupQ/1mi0jb11i7nz11/Mcx06MEEBAUxIUBAzqEsXJmPHDstYvZ6ZMWOG5d5w+zbDnDjBdHziCebdF1/kbbNvx47MsFdeYRiGYTp27MgA4P0xJ04wK6dPZ8KCgy3vKSpiGIZhvv/+e6Zm9eqMTCplHqtWjflp5kzedgEwPy5axPTr148JCAhgaicmMn/Onev8e1Cp2F2bMXEi06ROHYcxZB47fv+dqVevHhMUFMR079yZSdu+nR0zrHdvpm/HjsxnY8cycZUrMzWqVWMYhmHu3r3LDOrblwkLDmYiQkOZ5zp0YJL//JN9396lS5mWzZoxgYGBTFhYGNO2VSvm9pYtDHPiBDNj1CimSZ06zE8zZzLV4+KY0KAgZnDfvoyKzFmlYrSHDjFvDx7MREVEMAq5nGnXpAlzfNUqy/bT05m9e/cyAJjce/d4+5MQE8MEKBRMv06dmLnvvsuEhYbafuOiInas5sQJy7HMPf6t14j8/HwGAJOfn8+4o8KE1biYzWaMHz8e7dq1Q6NGjQBYCpjJ5XKHOGRMTAwyMjLYMTExMQ6vk9eEmD17NsLCwti/hIQEP+8NhUKhlGOKiiweK/JXVGTxNGk0jl5Fjcb5WHtPodBYLwkOCEBwYCA2//cfdE48p2azGX0nTECOSoX/fvgBuxctwq3UVAyeOtXrzyNs3LgRVePiMGv0aKRv34707dsFx23atAnvvvsuJrzxBi7+9htGP/88Xps1C3tPnuSNmzl7Nl544QWcP38evZ5+GkOmT0dOfr7P8wOAIq0Wcxctws8//4z9+/fjbmoqJtqFAfecOIFrd+5g96JF+PvXX2EwGNC9e3eEBAfjwI8/4tCyZQgOCECPd96B3mCA0WhEv4kT0bFtW5w/fx5HjhzBG8OH8zLEbqamYvO+ffh7/nz8vWAB/jtyBF9++SX7+gfffos//v0Xq2fMwOmff0btqlXR/Z13nO7vsYsXMfKzzzDuhRdwds0adG7eHJ+tWFGs78Yj3JpP5ZAxY8Yw1atXZ1JSUtjn1qxZw8jlcoexLVu2ZD744AOGYRhm1KhRTLdu3Xivq9VqBgCzbds2wc9y6jlKS7OsJu3/NBr+BoTGkD/rysKnsWq187Fqte9ji4pcz8PXsRqN/8aazdwfyH9jTSbbWJ3Of2O5q1hvxur1rscaDL6NNRhcj9XrfRtrNLoeq9P5NtZk8t9YrdY21mz231hvzvtyeI3Q5OQwly9eZDTkGOT+ufKC9ezJH+vKC9ahA3+skBfM/rO5f1xMJvb539evZyIiIhilUsm0bdOGmTJ5MnPu7Fl26K4dOxiJRMLcTU5m33Pp/HkGAHP8yBGGMZttniPrdjt26MC8+847vM/v+9xzzDCON7F69erMgnnzeGNWLl/OhIWFWR6bzUzbtm2ZUaNG8eY7aOBAphfnewPATPvoI9tPrFIxAJjtf/8t/D1wrmkzpk+3zNtuzMrlyxkATNKNG+zYxYsWMTExMeyYYUOHMjExMYyuqIjd7s8//8zUrVuXMXPmqysqYgICApid27Yx2VlZFk/dv//yzw3r2Bkff8wEBgYyqtxc9rlJEycyrVu3tuxbQQEjk8mYNT//zL6u12iY+Ph4Zs6XXzKMyWTzHOXkMIzRyLz04ou874sxGpnBL7xg+Z4F5qApLLQcy9nZDtcIbzxHFUZzRBg3bhz+/vtv7N+/H1WrVmWfj42NhV6vR15eHs97lJmZidjYWHbM8ePHedsj2WxkjD0KhQIKEoflEhTE18k4w5Mxvoz1plibN2O5mgV/juVqLPw5VqGw6UL8OVYu9zxGXVJjZTKbnsefY6VSm/7In2MlEs+PYW/GisUlM1YkKpmxQPkY6+15LxZbfhchLaUzRCLPx3sy1tNtcXRCAwYNQu9nn8WBAwdw9OhRbN++HXPmzsWyZcswfPhwXLl2DQkJCUioUYN9T4PGjREeHo4r16+j5ZNPOm5XJHKcr1D9HPKd2b/f+tyVK1fwxhtv8Obb7qmnsHDhQt77Hm/ShP1/UEgIQkNDkZWd7f77IHOyHycWIzAwELVq12afiouPR1ZWlm2sSITGjRtDzrmOnzt3DklJSQgJDeVtTqvV4ubt2+jWsyeGDx+O7j17omvXrujSpQteeOEFxMXFsZ9bo0YNhHDuweznArh56xYMBgPatW/PzkMmkaBVq1a4cu0aX/9l/f6vXL2K/v378/axTdu22MHRWfF+K4nEsp3AQO/uJXZUmLAawzAYN24cNm3ahH///ReJiYm815s3bw6ZTIY9e/awz127dg13795FmzZtAABt2rTBhQsX2B8KAHbv3o3Q0FA0aNCgdHaEQqFQKhKFhc7//viDPzYry/lY+9DT7duOY3xEqVSia9eu+Pjjj3H48GEMHz4cM2bM8Hl7YrEYDMPwnjO4SqQoJvZtLkQiEcyuhMs+btN+n4LsjO3CwkI0b94cZ8+e5f1dv34dL7/8MgBLotORI0fQtm1brFu3Do899hiOHj1aovtSFlQY4+itt97CL7/8grVr1yIkJAQZGRnIyMiAxpqZEhYWhpEjR+L999/H3r17cerUKbz22mto06YNnrSuDLp164YGDRrg1Vdfxblz57Bz505MmzYNb731lrB3iEKhUB51iJdc6M9+Ze5qrL2nWWiMn2jQoAFb5qV+/fpISUlBSkoK+/rly5eRl5fndFEcFRWF9PR09rHJZMLFixd5Y+RyudsWFfXr13coKXDo0KFyuxh/4okncOPGDURHR6N27dq8v7CwMHZcs2bNMGXKFBw+fBiNGjXC2rVrPdp+rVq1IJfLed+JwWDAiRMnnH4n9evXx7Fjx3jPcY2xkqLCGEdLlixBfn4+OnXqhLi4OPZv3bp17JgFCxagT58+GDBgADp06IDY2Fhs3LiRfV0ikeDvv/+GRCJBmzZt8Morr2Do0KGYNWtWWewShUKhUIpBdnY2nn76afzyyy84f/48kpOTsWHDBsyZMwd9+/YFAHTp0gWNGzfGkCFDcPr0aRw/fhxDhw5Fx44d0aJFC8HtPv3009i6dSu2bt2Kq1evYuzYsQ5FCWvUqIH9+/cjNTUVDx48ENzOpEmTsGrVKixZsgQ3btzA/PnzsXHjRkycONGv34O/GDJkCCpXroy+ffviwIEDSE5Oxr59+/DOO+/g3r17SE5OxpQpU3DkyBHcuXMHu3btwo0bN1C/fn2Pth8UFISxY8di0qRJ2LFjBy5fvoxRo0ahqKgII0eOFHzPO++8gx07dmDu3Lm4ceMGFi1a5FDapySoMJoje3egEEqlEosXL8bixYudjqlevTq2bdvmz6lRKBQKpQwIDg5G69atsWDBAty8eRMGgwEJCQkYNWoUplqz0UQiEf7880+8/fbb6NChA8RiMXr06IHvvvvO6XZHjBiBc+fOYejQoZBKpXjvvffQuXNn3phZs2Zh9OjRqFWrFnQ6neA9ql+/fli4cCHmzp2Ld999F4mJiVi5ciU6derk1+/BXwQGBmL//v2YPHkynn/+eRQUFKBKlSp45plnEBoaCo1Gg6tXr2L16tXIzs5GXFwc3nrrLYwePdrjz/jyyy9hNpvx6quvoqCgAC1atMDOnTsREREhOP7JJ5/Ejz/+iBkzZmD69Ono0qULpk2bhk8//dRfuy2IiPHE6qCwqFQqhIWFIT8/H6F2ojUKhUKpiGi1WiQnJyMxMRHKYohYKZSyxtWx7M39u8KE1SgUCoVCoVBKA2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoXiIyKRCJs3by7raVD8DDWOKBQKhVJhGT58OEQiEUQiEWQyGRITE/HBBx9Aq9WW9dRKhSNHjkAikaB3795lNofbt29DJBLh7NmzZTYHf0ONIwqFQqFUaHr06IH09HTcunULCxYswA8//IAZM2aU9bRKheXLl+Ptt9/G/v37kZaWVtbTeWigxhGFQqFQKjQKhQKxsbFISEhAv3790KVLF+zevZt9PTs7Gy+99BKqVKmCwMBANG7cGL/++itvG506dcI777yDDz74AJUqVUJsbCw++eQT3pgbN26gQ4cOUCqVaNCgAe8zCBcuXMDTTz+NgIAAREZG4o033kBhYSH7+vDhw9GvXz988cUXiImJQXh4OGbNmgWj0YhJkyahUqVKqFq1KlauXOl2vwsLC7Fu3TqMHTsWvXv3xqpVqxzGbNmyBXXq1IFSqUTnzp2xevVqiEQi5OXlsWMOHjyI9u3bIyAgAAkJCXjnnXegVqvZ12vUqIEvvvgCI0aMQEhICKpVq4b//e9/7OuJiYkAgGbNmkEkEqFTp05u517eocYRhUKhUBxgGAZFemOp/zEMU6x5X7x4EYcPH4ZcLmef02q1aN68ObZu3YqLFy/ijTfewKuvvorjx4/z3rt69WoEBQXh2LFjmDNnDmbNmsUaQGazGc8//zzkcjmOHTuGpUuXYvLkybz3q9VqdO/eHREREThx4gQ2bNiAf/75B+PGjeON+/fff5GWlob9+/dj/vz5mDFjBvr06YOIiAgcO3YMY8aMwejRo3Hv3j2X+7p+/XrUq1cPdevWxSuvvIIVK1bwvr/k5GQMHDgQ/fr1w7lz5zB69Gh89NFHvG3cvHkTPXr0wIABA3D+/HmsW7cOBw8edJjzvHnz0KJFC5w5cwZvvvkmxo4di2vXrgEA+z3+888/SE9Px8aNG13OuyIgYop7JD5iqFQqhIWFIT8/H6GhoWU9HQqFQik2Wq0WycnJSExMhFKpBAAU6Y1oMH1nqc/l8qzuCJRLPR4/fPhw/PLLL1AqlTAajdDpdBCLxVi/fj0GDBjg9H19+vRBvXr1MHfuXAAWz5HJZMKBAwfYMa1atcLTTz+NL7/8Ert27ULv3r1x584dxMfHAwB27NiBnj17YtOmTejXrx9+/PFHTJ48GSkpKQgKCgIAbNu2Dc8++yzS0tIQExOD4cOHY9++fbh16xbEYot/ol69eoiOjsb+/fsBACaTCWFhYVi2bBlefPFFp/vQrl07vPDCC3j33XdhNBoRFxeHDRs2sJ6bDz/8EFu3bsWFCxfY90ybNg2ff/45cnNzER4ejtdffx0SiQQ//PADO+bgwYPo2LEj1Go1lEolatSogfbt2+Pnn38GYDGcY2NjMXPmTIwZMwa3b99GYmIizpw5g6ZNm3r605UIQscywZv7t+dHIIVCoVAo5ZDOnTtjyZIlUKvVWLBgAaRSKc8wMplM+OKLL7B+/XqkpqZCr9dDp9MhMDCQt53HH3+c9zguLg5ZWVkAgCtXriAhIYE1jACgTZs2vPFXrlxBkyZNWMMIsBgwZrMZ165dQ0xMDACgYcOGrGEEADExMWjUqBH7WCKRIDIykv1sIa5du4bjx49j06ZNAACpVIrBgwdj+fLlrHF07do1tGzZkve+Vq1a8R6fO3cO58+fx5o1a9jnGIaB2WxGcnIy6tev7/DdiEQixMbGupxfRYcaRxQKhUJxIEAmweVZ3cvkc70lKCgItWvXBgCsWLECTZo0wfLlyzFy5EgAwNdff42FCxfim2++QePGjREUFITx48dDr9fztiOTyXiPRSIRzGazj3viHKHP8fazly9fDqPRyDPWGIaBQqHAokWLEBYW5tFcCgsLMXr0aLzzzjsOr1WrVs3lnEviuykvUOOIQqFQKA6IRCKvwlvlBbFYjKlTp+L999/Hyy+/jICAABw6dAh9+/bFK6+8AsCiH7p+/ToaNGjg8Xbr16+PlJQUpKenIy4uDgBw9OhRhzGrVq2CWq1mvUeHDh2CWCxG3bp1/bSHgNFoxE8//YR58+ahW7duvNf69euHX3/9FWPGjEHdunWxbds23usnTpzgPX7iiSdw+fJl1rj0BaLvMplMPm+jvEEF2RQKhUJ5qBg0aBAkEgkWL14MAKhTpw52796Nw4cP48qVKxg9ejQyMzO92maXLl3w2GOPYdiwYTh37hwOHDjgIG4eMmQIlEolhg0bhosXL2Lv3r14++238eqrr7IhNX/w999/Izc3FyNHjkSjRo14fwMGDMDy5csBAKNHj8bVq1cxefJkXL9+HevXr2cz2kQiEQBg8uTJOHz4MMaNG4ezZ8/ixo0b+PPPPx0E2a6Ijo5GQEAAduzYgczMTOTn5/ttX8sKahxRKBQK5aFCKpVi3LhxmDNnDtRqNaZNm4YnnngC3bt3R6dOnRAbG4t+/fp5tU2xWIxNmzZBo9GgVatWeP311/H555/zxgQGBmLnzp3IyclBy5YtMXDgQDzzzDNYtGiRH/fOElLr0qWLYOhswIABOHnyJM6fP4/ExET8/vvv2LhxIx5//HEsWbKENegUCgUAi5bov//+w/Xr19G+fXs0a9YM06dP54Xr3CGVSvHtt9/ihx9+QHx8PPr27eufHS1DaLaal9BsNQqF8rDhKsOH8nDx+eefY+nSpUhJSSnrqZQINFuNQqFQKBSKS77//nu0bNkSkZGROHToEL7++muvQmaPKtQ4olAoFArlIeXGjRv47LPPkJOTg2rVqmHChAmYMmVKWU+r3EONIwqFQqFQHlIWLFiABQsWlPU0KhxUkE2hUCgUCoXCgRpHFAqFQqFQKByocUShUCgUCoXCgRpHFAqFQqFQKByocUShUCgUCoXCgRpHFAqFQqFQKByocUShUCgUih/45JNP0LRp07KeBsUPUOOIQqFQKBWW4cOHQyQSQSQSQSaTITExER988AG0Wm2pz2XixInYs2dPqX3evXv3IJfL0ahRo1L7zEcFahxRKBQKpULTo0cPpKen49atW1iwYAF++OEHzJgxo9TnERwcjMjIyFL7vFWrVuGFF16ASqXCsWPHSvzzDAZDiX9GeYEaRxQKhUKp0CgUCsTGxiIhIQH9+vVDly5dsHv3bvb1GjVq4JtvvuG9p2nTpvjkk0/YxyKRCMuWLUP//v0RGBiIOnXqYMuWLezr+/btg0gkwp49e9CiRQsEBgaibdu2uHbtGjvGPqw2fPhw9OvXD3PnzkVcXBwiIyPx1ltv8YyM9PR09O7dGwEBAUhMTMTatWsF52sPwzBYuXIlXn31Vbz88stYvnw5+9rUqVPRunVrh/c0adIEs2bNYh8vW7YM9evXh1KpRL169fD999+zr92+fRsikQjr1q1Dx44doVQqsWbNGmRnZ+Oll15ClSpVEBgYiMaNG+PXX3/lfU5BQQGGDBmCoKAgxMXFYcGCBejUqRPGjx/PjtHpdJg4cSKqVKmCoKAgtG7dGvv27XO5z6UJbR9CoVAoFAcYhkFRUVGpf25gYCBEIpHP77948SIOHz6M6tWre/3emTNnYs6cOfj666/x3XffYciQIbhz5w4qVarEjvnoo48wb948REVFYcyYMRgxYgQOHTrkdJt79+5FXFwc9u7di6SkJAwePBhNmzbFqFGjAABDhw7FgwcPsG/fPshkMrz//vvIyspyO9e9e/eiqKgIXbp0QZUqVdC2bVssWLAAQUFBGDJkCGbPno2bN2+iVq1aAIBLly7h/Pnz+OOPPwAAa9aswfTp07Fo0SI0a9YMZ86cwahRoxAUFIRhw4axn/Phhx9i3rx5aNasGZRKJbRaLZo3b47JkycjNDQUW7duxauvvopatWqhVatWAID3338fhw4dwpYtWxATE4Pp06fj9OnTPMNx3LhxuHz5Mn777TfEx8dj06ZN6NGjBy5cuIA6dep4/qOVFAzFK/Lz8xkATH5+fllPhUKhUPyCRqNhLl++zGg0Gva5wsJCBkCp/xUWFno192HDhjESiYQJCgpiFAoFA4ARi8XM77//zo6pXr06s2DBAt77mjRpwsyYMYN9DICZNm2aw/5v376dYRiG2bt3LwOA+eeff9gxW7duZQCw39uMGTOYJk2a8OZWvXp1xmg0ss8NGjSIGTx4MMMwDHPlyhUGAHPixAn29Rs3bjAAHOZrz8svv8yMHz+etz8rV67kPZ41axb7eMqUKUzr1q3Zx7Vq1WLWrl3L2+ann37KtGnThmEYhklOTmYAMN98843LeTAMw/Tu3ZuZMGECwzAMo1KpGJlMxmzYsIF9PS8vjwkMDGTeffddhmEY5s6dO4xEImFSU1N523nmmWeYKVOmuP08VwgdywRv7t/Uc0ShUCiUCk3nzp2xZMkSqNVqLFiwAFKpFAMGDPB6O48//jj7/6CgIISGhjp4cbhj4uLiAABZWVmoVq2a4DYbNmwIiUTCe8+FCxcAANeuXYNUKsUTTzzBvl67dm1ERES4nGdeXh42btyIgwcPss+98sorWL58OYYPHw4AGDJkCFasWIGPP/4YDMPg119/xfvvvw8AUKvVuHnzJkaOHMl6sADAaDQiLCyM91ktWrTgPTaZTPjiiy+wfv16pKamQq/XQ6fTITAwEABw69YtGAwG1osEAGFhYahbty77+MKFCzCZTHjsscd429bpdKWq2XIFNY4oFAqF4kBgYCAKCwvL5HO9JSgoCLVr1wYArFixAk2aNMHy5csxcuRIAIBYLAbDMLz3CImLZTIZ77FIJILZbHY6hoT/7Md4u01vWbt2LbRaLU9XxDAMzGYzrl+/jsceewwvvfQSJk+ejNOnT0Oj0SAlJQWDBw8GAPZ3/fHHHx20SVxDDrB8t1y+/vprLFy4EN988w0aN26MoKAgjB8/Hnq93uP5FxYWQiKR4NSpUw6fFxwc7PF2SpIKJcjev38/nn32WcTHx0MkEmHz5s281xmGwfTp0xEXF4eAgAB06dIFN27c4I3JycnBkCFDEBoaivDwcIwcObJMLgAUCoVSnhGJRAgKCir1v+LojQCLITR16lRMmzYNGo0GABAVFYX09HR2jEqlQnJycrE+xx/UrVsXRqMRZ86cYZ9LSkpCbm6uy/ctX74cEyZMwNmzZ9m/c+fOoX379lixYgUAoGrVqujYsSPWrFmDNWvWoGvXroiOjgYAxMTEID4+Hrdu3ULt2rV5f4mJiS4/+9ChQ+jbty9eeeUVNGnSBDVr1sT169fZ12vWrAmZTIYTJ06wz+Xn5/PGNGvWDCaTCVlZWQ6fHxsb6/kXWIJUKONIrVajSZMmWLx4seDrc+bMwbfffoulS5fi2LFjCAoKQvfu3Xn1LoYMGYJLly5h9+7d+Pvvv7F//3688cYbpbULFAqFQilhBg0aBIlEwt4rnn76afz88884cOAALly4gGHDhjl4LMqCevXqoUuXLnjjjTdw/PhxnDlzBm+88QYCAgKcGolnz57F6dOn8frrr6NRo0a8v5deegmrV6+G0WgEYLnf/fbbb9iwYQOGDBnC287MmTMxe/ZsfPvtt7h+/TouXLiAlStXYv78+S7nXKdOHezevRuHDx/GlStXMHr0aGRmZrKvh4SEYNiwYZg0aRL27t2LS5cuYeTIkRCLxew+PfbYYxgyZAiGDh2KjRs3Ijk5GcePH8fs2bOxdevW4nylfqNCGUc9e/bEZ599hv79+zu8xjAMvvnmG0ybNg19+/bF448/jp9++glpaWmsh+nKlSvYsWMHli1bhtatW+Opp57Cd999h99++w1paWmlvDcUCoVCKQmkUinGjRuHOXPmQK1WY8qUKejYsSP69OmD3r17o1+/fmwWV1nz008/ISYmBh06dED//v0xatQohISEQKlUCo5fvnw5GjRogHr16jm81r9/f2RlZWHbtm0AgIEDByI7OxtFRUXo168fb+zrr7+OZcuWYeXKlWjcuDE6duyIVatWufUcTZs2DU888QS6d++OTp06ITY21mHb8+fPR5s2bdCnTx906dIF7dq1Y0sGEFauXImhQ4diwoQJqFu3Lvr164cTJ0441W6VNiLGPhBbQRCJRNi0aRP7o9y6dQu1atXCmTNneOmCHTt2RNOmTbFw4UKsWLECEyZM4LksjUYjlEolNmzYIGh06XQ66HQ69rFKpUJCQgLy8/MRGhpaYvtHoVAopYVWq0VycjISExOd3pQppcO9e/eQkJCAf/75B88880xZT8cvqNVqVKlSBfPmzWN1YCWFq2NZpVIhLCzMo/v3QyPIzsjIAGCJpXKJiYlhX8vIyGBjrgSpVIpKlSqxY+yZPXs2Zs6cWQIzplAoFMqjzr///ovCwkI0btwY6enp+OCDD1CjRg106NChrKfmM2fOnMHVq1fRqlUr5Ofns4Un+/btW8Yz85wKFVYrC6ZMmYL8/Hz2LyUlpaynRKFQKJSHBIPBgKlTp6Jhw4bo378/oqKi2IKQFZm5c+eiSZMm6NKlC9RqNQ4cOIDKlSuX9bQ85qHxHBGFe2ZmJlt7gjwmYbbY2FiHmhVGoxE5OTlOFfIKhQIKhaJkJk2hUCiUR5ru3buje/fuZT0Nv9KsWTOcOnWqrKdRLB4az1FiYiJiY2N5HZFJM742bdoAANq0aYO8vDzej/bvv//CbDYL9qGhUCgUCoXy6FGhPEeFhYVISkpiHycnJ+Ps2bOoVKkSqlWrhvHjx+Ozzz5DnTp1kJiYiI8//hjx8fGsaLt+/fro0aMHRo0ahaVLl8JgMGDcuHF48cUXER8fX0Z7RaFQKOWDCpqfQ6Gw+OsYrlDG0cmTJ9G5c2f2MSmFPmzYMKxatQoffPAB1Go13njjDeTl5eGpp57Cjh07eIr1NWvWYNy4cXjmmWcgFosxYMAAfPvtt6W+LxQKhVJeIPqWoqIiBAQElPFsKBTfIZW6i1vHqsKm8pcV3qQCUigUSkUhPT0deXl5iI6ORmBgYLErVVMopY3ZbEZaWhpkMhmqVavmcAw/kqn8FAqFQvEdkpRin7RCoVQkxGKxoGHkLdQ4olAoFApEIhHi4uIQHR0t2JSVQqkIyOVyiMXFzzWjxhGFQqFQWCQSSbnoO0ahlCUPTSo/hUKhUCgUij+gxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCoXCgxhGFQqFQKBQKB2ocUSgUCoVCYdl7LQtJWQVlPY0yhRpHFAqFQqFQAAB3stV4beUJvLXmTFlPpUyhxhGFQqFQKBQAQGquBgCQrdaV8UzKFmocUSgUCoVCAQDkawwAAL3RXMYzKVuocUShUCgUCgWAzTgympkynknZQo0jCoVCoVAoAGzGkcFEPUcUCoVCoVAoHOOIAcM8ut4jahxRKBQKhUIBYDOOgEc7tEaNIwqFQqFQKAD4xtGjHFqjxhGFQqFQKBQAdsaRkXqOKBQKhUKhPOKouMaRmXqOKBQKhUKhPOLQsJoFahxRKBQKhUIBQMNqBGocUSgUCoVCAcMwUGmN7GMaVqNQKBQKhfJIU6gzwsRJ36dhNQqFQqFQKI803JAaQMNqFAqFQqFQHnEcjCMaVnv0WLx4MWrUqAGlUonWrVvj+PHjZT0lCoVCoVDKDJXGyHtsMFLj6JFi3bp1eP/99zFjxgycPn0aTZo0Qffu3ZGVlVXWU6NQKBQKpUxw8ByZaFjtkWL+/PkYNWoUXnvtNTRo0ABLly5FYGAgVqxYUdZTo1AoFAqlTFDRsBrLI2cc6fV6nDp1Cl26dGGfE4vF6NKlC44cOVKGM6NQKBQKpexwFGQ/usaRtKwnUNo8ePAAJpMJMTExvOdjYmJw9epVh/E6nQ46nY59rFKpSnyOFAqFQqGUNjSsZuOR8xx5y+zZsxEWFsb+JSQklPWUKBQKhULxO/bGkZGG1R4dKleuDIlEgszMTN7zmZmZiI2NdRg/ZcoU5Ofns38pKSmlNVUKhUKhUEoNe+NI/wiH1R4540gul6N58+bYs2cP+5zZbMaePXvQpk0bh/EKhQKhoaG8PwqFQqFQHjZoWM3GI6c5AoD3338fw4YNQ4sWLdCqVSt88803UKvVeO2118p6ahQKhUKhlAnEOJJLxNCbzI90WO2RNI4GDx6M+/fvY/r06cjIyEDTpk2xY8cOB5E2hUKhUCiPCiSVPzJYjvR87SMdVnskjSMAGDduHMaNG1fW06BQKBQKpVxAPEeVgxVIz9c+0mG1R05zRKFQKiZqnRG37heW9TQolIcShmFY4ygyWA4AMJoeXc8RNY4oFEqF4O1fz+Dpef8hKaugrKdCoTx0FOlNMJotnqLKwQoAgIEaRxQKhVK+uWE1iq5nUu8RheJviNdIKhYhLEAGANDTsBqFQqGUb0jH8By1voxnQqE8fBDjKCxABpnEYhrQsBqFQqGUY8xmBiqt5eJNjSMKxf9wjSO5RASAhtUoFAqlXFOoN4KxevipcUSh+B+Sxh8SIIPU6jmiYTUKhUIpx+QX2Sr35hZR44hC8Tc0rMaHGkcUCqXcQ0JqAPUcUSglAd84omE1ahxRKA85eqPZoWdSRYM7f2ocUSj+R8UaR1LWc0SLQFIolIeWYSuOo9PXe5Gp0pb1VHyGZKoBQC41jigUvyMUVqOeIwqF8tByITUfuUUGbDmbVtZT8RleWI1qjigUv0PDanyocUShPMQwDIMivcXr8tf5CmwcccJqWoOZ3ScKheIfhD1HNKxGoVAeQvQmM6wdAXD+Xj5uP1CX7YR8RGWnmaK6IwrFv9CwGh9qHFEoDzEavYn3+K9zFdN7ZC8oz1ULC8zVOiPO3M0Fw5SPFa/ZzGDJvps4dSe3rKdCobiEnGOhNKwGgBpHFMpDjcZgZxxV0NCaSssPo2WrdYLjZv51Cf2/P4z/rt8vjWm55WhyNr7acRWf/n25rKdCobgk35r0QMNqFqhxRKE8xBRZPUcKqRhyiRjXMwtxLaPidbV38Bw5EWVfte5beQkfpuZqAPAF5RRKeYNhGE4qPw2rAdQ4olAeakhYLTxQho51owBUzNAauXDLpZZLVo6TsBopV1CgLR+C7fuFFg+X3vjo3mQo5R+twQy91RAKC5BBSsNq1DiiUB5mSFgtQCbBc03iAVhCa+VFk+MpxPNSvVIgAOFaRyYzg/sFOt74sobMhxpHlPIM8cxKxCIEK2gRSIAaRxTKQw3xHAXIpXimfjQCZBLcyS7C+Xv5ZTwz7yAX7+qRQQCAbAHjKLtQx2bmlRfPUZbVOHqUV+CU8g8rxlZKIRKJIKe91ahxRKE8zBDNUYBMjEC5FF0axACoeKE1UiE7sbJzz1GmyibSLi/GEfUcUSoC3DR+AGxYTU89RxRK+eNebhFNgS4mWmtYLVAuBQA8+3gcAODv8+kwm8vPhW/LuTQs2H1dMNynN5rZ8GCNyhbPkVCV7AxOe5RyF1Z7hFfglPKPvXFEBdnUOKKUY15ffRIDlx5Ger6mrKdSYSGeI6VMAgDoWDcKIUopMlRanCxHhucnWy5h4Z4bSMoqdHiNa+hUc6E5yuQZR+XLc2QwMeXKGKVQuHBrHAGgYTVQ44hSjknL04BhbDcYiveQNhuBcotxpJBK0L1hLADgz7OpZTYvLmYzw6bmc0NjBHLhDlFKUTlYAUC4QnYWxzgq0JS956hIb0ShzmakGcyP7o2mtNAbzRUu2aA8oHISVnMlyE7JKarQzazdQY0jSrlFa7DcTMoiY4JhGHy06QImbThXoS+2Wk62GqFf0yoAgM1nUh3qB5UFar0R5Ct+UOhoHKlYsagMkUFyAJY6R/aeGK5hVR48R/ZGPdUdlSz5GgPafrkHI1efLOupVDichdX0JmFjU2swodfCA+i76FCFvj66ghpHlDLBbGZcxrNNZobVaZRF3Pt2dhHWHLuLDafu4W5OUal/vr9gBdlym3HUrnYkHosJhlpvwroTd8tqaixc8bSQccS9cIcHWowjM+OoK8osKF+aI2oclS7n7+XhQaEeB288eGhv2CWFvXFEwmqA5VpsT26RHgU6IzJUWocq/A8L1DiilDoMw6Dv4kPo/s1+pzFtLeeEM5aB5+hg0gP2/zcyHXUwFQW2zhHHOBKJRHj9qZoAgFWHbpe56JJvHDmGy4gXKDRACrlUjBCFRVxun87P9RzpjWbeMVQWZNkbR4+wfqM0uJ1tWcToTWbamNhLVHaaIxJWA4Q991xDv7xkhvobahyVEy7cy8dL/zuKt9acLuuplDh3c4pwITUft+6rBbOOAL5xVBY378Nc40hAJFxRIHWOAjlhNQB4rmk8KgfLkZavxfaLGT5v/8K9fNzJLl6rjgKOl8dVWI2saiNIaM3BOOLrH8r6om3vOTIYqTejJOG2jMl4iLUwJYGzsBogbNTrqHFEKS0YMDhyKxsnbueU9VRKnAuptgKEWr2w4cN11Zb2ittkZnD4Zjb7+EZWxetFRhDyHAGW7LVXn6wBAFh24JZPYYgslRYDlhzGgCWHWSPMFwo4ouVsF2G1UKXlwl3JahxxvQM6o4l9LLYuegvKOLTmEFYzPZzhh/IC10jPyKfGkTc4Gkc2z5GQd5/vOSr7EHZJQI2jckKV8AAAFle8zvhwX0QvpqrY/zuLV5dlWO1ymoonVL5ZgT1HQpojwitPVoNcKsb5e/k4cdv7tP5rmQXQm8x4UKgvVlFJ92E1/oW7EkeUTSCGiEwiQmyo0mG7ZUFWAf8GrXvINEdrjt1B+zn/4mxKXllPBQCQzPEcpVPjyCvsjSORSASp2HnGGvcexc3IfJigxlE5oVKQHEqZ5edIz3u4T+xLaTbPkXPjyHYjKe2w2qGblpBaTWvBwRtZhRVW4GkrAuloHEUGKzDgCUvm2rIDt7zeNleovvrIbZ+/I0/DakQPEWEVZXM1R0RvFB2iZMeVtSj7YRZk772ahWmbLyIlR4M9VzLLejowmRmk5NjqoT3MKeYlgb1xBLguBMk19AtpWI1SkohEItZ7lJr38BY9ZBgGFzlhNWfhGE0Zao4OWfVGL7WqBqlYhCK9CWkVdCVqax/iaBwBwIh2iQCA3VcyeZoNT7ibbTOOLqWpcPpunk9z5Hp4sgv1DkYWaR0SqrQIsSODHTVHpMZRbJiSDb+VvefITnP0kLRiuJFZgLd/PeOy/EJpk5an4YXfqefIO4SNI+I5opojShlTJcJS/Tc19+E1jlLzNMgtsq3onWUU8QXZpXdT0RpMrO6rU90oJBLvUWbF1B1xG88KUScmBJ3qRoFhgJWHkr3aNvEcEcPr5yO3fZoj13OkN5kdahSxF+5AvucoR217H/EUxIQqEBpg2VdVGddwIp4jkVW+8TB4jnLVeoxcfRKFOiP7u5dWkda0PA1b1NSeO9n8chtUc+Q5WoOJNXZCBT1HbrLVaFiNUtIQz9G9h9hzxNUbAc7DalyPUnE9R3qjGdcyCjwK+5y+mwutwYzoEAVqRwejdnQwAAi2tagIaASKQNpD0vrXn7yH/CLPDQpyQxrd0fL+bRcyfPIi2K887bdBwmM2QbblX67mKIMTVgspB54jk5lhw37RIZaq3hVdkG0wmTF2zSnczSlCQqUAzHyuIQDgvoBOzN9cTlOhw5y9mLThvODryVYxdrC1zAPNVvMcsogQicCWyQBch9X0NKxGKU2qRljDag+x54irNwKch9W0Rv9pjr7YdgXdv9mPfdfuux17OMmSpda2ViREIhHqVHTjSO9cc0RoVzsS1SMDoTGYcCbFM2E2wzBIsXqO+jwehyYJ4dCbzFh3IsXrOToYR3aeCIdUfgHNURbrOVIixBp+K0vNUY5aD5OZgUgExIVZzuuK7jn6ZMslHL2VgyC5BMuHtUSdGMu5Yf97lQT/XMmE0cxg37UswR51JCTcskYEAOo58gZuNqhYbMtSk0k9DavRbDVKCWPTHFXciszu4KbxAy4E2Xr/hdVI+OfmffcGDin+2K52ZQBA7ZgQABW31hEJQyhdeI5EIhFirBleap1n3o3cIgPrTq8aEYihT1YHAKw5esfrZpX2F1f7jDX7pphCmiNSHTsmVFEuNEck1BQZpGC9dvoKrDm6l2upGC8SAd++1AyPxYSwfe7uF+pKPGGBhLrVehPrJeJC0vifrBkJwJJB9bDetP2NkN4IAGRiz8JqNFuNUuJUiXi4BdlcMXb1SIu+ypnmSMNL5S9+WA1w329LpTXg/L08ADbjiHiObmR6FpYrb5CsP1eeIwAIsr6udqLpsIcYnLGhSihlEvR+PA6VgixFJfdczfJqjuR3IYvWbLXNE8EwDPu6vecoVyBbLbaceI7uW0ODUSEKyKTWPlUV2HNEDNb4sAA8Uz8GgGXfAMt+laTuxGgy49Qdm0fzot0CC7Cl8TeID2V/f5qx5hlOjSOX2Wq26zPVHFFKHOI5Ss/TCvazqehkFejwoFAPsQholhAOwEVYzY/ZauSm5C42fuxWDsyMJYU/3vpbJFYOglhkuYHfLwdZOd5gNJnZDB5XmiMACLRqDYo8vNCRlXq1ShYjVymT4IUWCQCAn4/c8WqexMNT1ZqQwA3TqPUm9lywLwJZoDOyF2lyI4wO5aTya8ruok3CfFEhCrZPVUU2jogHMkhhO46UMgmrUSnJ0NqlNBWbdQk4GkfcNP4akUGIC7N4QWnGmmc4NY5chNVo+xBKqRITqoRULILRzDgUkHsYIBe12tHBbAsIp4JsXoXs4hmKOuvJXahz7UkgKfxta0eyzyllEtYASKpgPdaKON+hUBFILjbPkWdhNaI3qmb1AALAkNbVIBZZQpPeaLRI+INkBnIFvkRvJJeI2TpgoUoZJFY3U16RAUV6I3uBjglVsJ6DsgyrEEM6OkQBBes5qriC7CKdcNZjZav3qCQz1khIjRQltA/NkzR+uUSM+PAAxFo1XlR3JExWgZZn8DgzjqQuwmr8OkcPZ/iSGkflCIlYhFjrqqc8irILtAZ0nf8fZm+/4tP7yUWtUZUw1pPhSRFIf4XV3K1wiHHUrlZl3vO1oyum7ojotkQisDdoZwRab3rOUqXtIZlqxHAEgIRKgehUNxoAsPOS5/3ayO9CjCNutppNbySFyJoTLxaLEGFN689R69mQWqBcgmCFlPUwuQujliRZKltYTS51fpOpKBBDO8jOyK5s1X8JVTYHLMfT5jOpvIrz3nI82WIc9Xk8DgBwKVXFE2WTYzGhUoDlGhpqMdioceTIvmtZaDv7X3RfsB/XreVJ2DpidsaR3MNsNeo5KmM+//xztG3bFoGBgQgPDxccc/fuXfTu3RuBgYGIjo7GpEmTYDTyf7h9+/bhiSeegEKhQO3atbFq1aqSn7wXlOdCkJfSVLiRVYi/z6X79H6Sxt8o3mYccY0gLv4Nq1m25Uo4mKnS4kZWIUQioE2tSN5rJCunovVYK+I0nSWGhTOIJslTQTbRHFXneI64j9UehucYhmF/F2Iccfur2VfHJnB1R5mcTDWRSFTuPEekmF5xegQyDIO31p7GO7+eKRPtGwm32mvXiCjbWQmHn4/cwfh1Z/Hjfu8rsAOA2cywnqOXW1eHXCpGgc7Iq85OBNo1Ii3HD/EcpVPNEY9CnRFTN16A0czg1gM1+i0+hL/OpfkUVqPtQ8oRer0egwYNwtixYwVfN5lM6N27N/R6PQ4fPozVq1dj1apVmD59OjsmOTkZvXv3RufOnXH27FmMHz8er7/+Onbu3Flau+EWIsq+50fP0aW0fDwzbx92XPTNqCEQL4+nol2heQBWz5GcGEceaI6Kqb8iNyVXnoTD1pYhjeLDEG698RJqR1XMdH5nTWeFCFJ45zkiN6eESnzjSCG1fJanfcSKOJoim+fI5oWwbzpLIGHZbJ5xZLlRkzpHZVkEkoSZuJ6j4vRWU2mM2Ho+HVvOpZWJR4w1tO3CalFuwmrknPFVJnDzfiFyiwxQysRomhCO+nGhAICLnJIgd6xi7BrW44f01sukniMeX++4irR8LRIqBaBd7UgU6U14+9cz2Hw2FYB3YTVa56gcMXPmTLz33nto3Lix4Ou7du3C5cuX8csvv6Bp06bo2bMnPv30UyxevBh6veViu3TpUiQmJmLevHmoX78+xo0bh4EDB2LBggWluSsuqVoCnqPfjqfg5n01tl3wPNQhhM56sy3y0LvA5UGhDun5WohElowSklruUfuQYgpZbYJs5zfLcymWi23rxEoOrxHPUUUzjlw1nbUn0AvNkdZgYovsVbczjmyGgGfHCHHJS8Qi1tDieiGIIWDvOaoUaGs+S0JYpBwBqZBdqDOWWYYhaxwFKyCXWFP5i3EccxckeUUlX3TRHmI0e+s5SsvXWN/vm97quNVr1CwhAnKpGI3iLcYRV3d0m/UcWY4fKsh25NSdHPx01JIoMbv/41j9WiuM7VQLgCU0DXibrcYxjvRGwdpTgEWqsO2C94vyvVeznC6cS4sKYxy548iRI2jcuDFiYmLY57p37w6VSoVLly6xY7p06cJ7X/fu3XHkyJFSnasrqpRAIcgjtyyFDYubLUNCYHqT2ettETF2YuUgBCukbjVH/q6QDbiOjZMbDtF8call9Rw9KNSzF5KKANt0VibcOoRLkNzzbLV7uRowjEV/QjLHCAov09aJSD5EKWX1K0V6E3szti8ASagUTFqI8MNqgM3LZGY8F5j7G2IcRYcqOZoj349jrkcv14sq5v7CmefInXFEmmj7eqM7YdUbtbQuWhpXCQPAz1hLtvccWc9hWiXbgs5owuQ/LoBhgEHNq+KpOpUhlYgxuUc9LH2lOVtVnNx7CHJrWE1I88k9vxlGOJrAMAzG/HIKb6097ZXncO/VLIxYfQKD/3fU6eK5NHB/1awgZGRk8AwjAOzjjIwMl2NUKhU0Gg0CAvgHBwDodDrodJyVrErlMMafVAm39lfzk+coq0DLejw8Xc07g2vIaPQm9qLvCZfSbHojwObNcCrI5lbILm5YjXiOXNz4WQ+FXfgGsIScqoQHIDVPg6SsQrQS8C6VR8gNTemJ50jhuefIlqkW5KBlUngZQiLfe4hSimCFFAqpGDqjGdmFegRWknLCavxLVaVAm3FEjAXSpkMhFUMuEVv6tGkM7MW/tCjSG9ljzZLKb9UcFcdzxPHWlo3nSLjSuquwGsMw7HXM2XnuDiLGblXDcs41Yo0jFRiGgZkBL40fsIXVctR6aA0mlwVQHwUW772JpKxCVA5W4KPe9Xmv9WgUi4bxobiUlo/2tfmJKCSsJpQtbH9+F+qMbDiboNab2AXp3ewiRIc4LjztSX6gxju/WZoaN4oP9cjrXVKUqefoww8/hEgkcvl39erVspwiZs+ejbCwMPYvISGhRD+P6znyR0jgyM1s9v/FEYQC/NWft7ojstIjKz+bINuDCtnFDatZ95urb7GHeChClMI30rLosZaSU8QTJ3uLhvUceaA5snoEPFmp2WocOS4mFNbP0jkR2ttDLp4hChlEIhGv6jJgK+Ro7zkimqMctZ7VlhDPEV+UXfp6CGIoBMgkCJJL2EWE/8JqZeE5sobVFJ5nq+UWGdibqC9htXu5RUjL10IiFqFZtXAAwGMxIZBJRMjXGHAvV8Om8cskIrY2WXigjDXSScj1UeVaRgGW7EsCAMx8rqGDnhKw6AZ7NIrjtQ4BPA+rAcLnGdeI92SxX6gz4o2fTqJAa0Tz6hGY8WxDt+8pSYplHOn1ely7ds0hI8xTJkyYgCtXrrj8q1mzpkfbio2NRWZmJu858jg2NtblmNDQUEGvEQBMmTIF+fn57F9Kive9o7yBxMs1BpNf3OdHb9mMI09vWM7gZpZ5KtwlEAFlwyoWzYA7zZGW4+UyFsNzxDAMT1DoTDzINjcNcPQcAZxK2X7IWGMYBr8ev4uzKXlOxxy7lY2n5+3D4P8d9flzNNbfyDvNkfvf9a51pV7dulLnoiAFDz00xElGWbDVmGFvtlYDw751CIHbfJa0DuGGRMuySrYtpKaASCSyGUfFWJxwz5PcMvAcqfXChrarFiJpnBuiL+ERkqXWqEoYmzAgl4pRN9ZSWuNiaj4njT+QrX0lEonY62h5Cq0xDIM9VzLxwtIj+HjzxWKXKPGEz7ddgcHEoEv9GPRqHOvVe12F1eyjEMLGke3cc2ccMQyDievP4UZWIWJCFVgy5AmvIhMlgU/+5qKiIrz99ttYvXo1AOD69euoWbMm3n77bVSpUgUffvihR9uJiopCVFSUL1NwoE2bNvj888+RlZWF6GhLrZXdu3cjNDQUDRo0YMds27aN977du3ejTZs2TrerUCigUCj8MkdPUMokiApR4H6BDqm5GgdNh7dwPUfFyZYB7DxHXoiy84r0rOu7oYdhNX9pjuxvSAU6A8ICHQ0gttaHQFgN8E6UnV2oQ0Sg3GElRjhxOxdTNl6AQirGTyNaoXVNfumA9HwN3lp7GgYTg6SsQuiNZp8uFBovBNlstpoHv+vdHIvnyD5TDQAUMt8E2aGscUQ0LBYDgPwuDpqjIMu47EKO5ojjtifGVFmk82dxxNiArV5McYwjbrizLDxHbANjhXC2mt5ohkpr5P1OXOPIF83R8WRLy5BW1mayhMZVwnAxVYULqfmII5Xs7Qz1mFAlbmcXIT2/fJREOXUnB19uv4oTty37dPx2DtQ6I74e1IQ16kqCq+kWOcO4p2u7Ledhj6uwmr0XVOg84xrxaW6Mo8V7k7DjUgbkEjGWvNIc0aHuQ3AljU+m2ZQpU3Du3Dns27cPSqVtJ7p06YJ169b5bXJc7t69i7Nnz+Lu3bswmUw4e/Yszp49i8JCy82qW7duaNCgAV599VWcO3cOO3fuxLRp0/DWW2+xxs2YMWNw69YtfPDBB7h69Sq+//57rF+/Hu+9916JzNlX/NWANi1Pg9vZtm0UX5DtW1iN6I2qRwayF0+3YTXOzbU483Y8id15jpyF1ayFIN1UyT6XkoeWn/+DGVsuOR1DMm10RjNe/+kkLqfZdGxagwljfjnNC1Nwe415Aync5651COCt58ha40jIOCKaI4/DaiScaTkuiHFEwokqJ6n8RHOUklPEejSjQ22LGNZzVAYtRLieIwB+6a3GFcqXheZI7aTOEa+FiF0ImHtD9CWsdjzZsrBrWYOv8WN1R2kqNo3f3ovJeo7KOGMtJacIo346iQFLjuDE7VwopGI8/0QVSMQibDyTio82XXCa6eUPiOc10odFtjdhNSE9JzfykZbn/HfYezUL83ZfBwDM6tsQT1SLcDq2NPHJc7R582asW7cOTz75JM8abdiwIW7evOm3yXGZPn0666kCgGbNmgEA9u7di06dOkEikeDvv//G2LFj0aZNGwQFBWHYsGGYNWsW+57ExERs3boV7733HhYuXIiqVati2bJl6N69e4nM2VeqRATgbEpesWsdEa8REacWV5DNNWSceRgYhsGX26/i1J1caI0maA1mtkEoEWMDYFtBOE3l13MqZBfj4mF/QxI6iQ0mM3vxduY5IpqjDJUWBVqDg/iQcCVdBTMD7LvuvPkqWc3JJWIUaI0YtvI4/hjTFgmVAjD9z4s4l5KH8EAZTGYGBVojHhToERcmHPZ1hdaJiFYIW50jExiGcbrKZBiGNY6qCRhH3tb0KeAIsgEgktWwuNMcWR4Tj0pYgIwnvCW/o9CK9vYDNdYev4vXn0oskRUqycxx8BwVS3PEDauVgeeIrZDteMuoHKJAgc6IBwU6NrMTANI4hom3guzsQh1u3rcYPg7GUbwtY42I3RMr849FtoVIGYfVZv51Cf9cyYJYBLzQIgHvdqmDuLAAdK4bjXd/O4PfTqRAJhFjVt+GXnt23KE1mNjzUMhb7g6ZB9lq5N4iJFfI99Bz9Pm2K2AYS/uhF1tV83qeJYVPxtH9+/fZ0BUXtVrt9x+YsGrVKrfVrKtXr+4QNrOnU6dOOHPmjB9n5n/8VeuIpPC3TIzAoaRsv6XyA849DKl5GvzgpBpux8dsIVRuKr/QzdhfFbIdwmoCN0uuN8mZIDssQIboEAWyCnRIyipEMyerG2J8peRokK8xONzUAeBqhkW39Fm/RlhxKBlXMwrw6opjGPhEVaw/eQ9iEfDdS83w5faruJSmcpom7Q62zpEXniOTmYHOaHaa4XO/QAetwQyxyDH1F7AVgfT0WLM3jhzDasIevcggfqg7JpT/2KY5cjxOf9h/E78eT8GltHz8MrK1369Z3AKQAPwiyNZwBdllUNySeI6EQrRRwQokP1A7NGYuTliNhJ8ei7H1YSTUjQ2BVCxCjlrPjrP3HJWXFiKkT+C8F5qgf7Oq7PPPNomHwWTGhA3n8PPRO5BLxZjWu75fj0Vy7ohFQLCAUesOmcveapbfMzJYjvR8raBHPtcDzZHeaMat+xZv/NtP1/F6jiWJT2G1Fi1aYOvWrexj8oMuW7bMpX6H4hn+qnVEPEedHrMYssXVHGk80BxxS9GvHN4Sv456EpvebIt9EzvhhZa2TD+SXm5mhLUYfOPIf54joZOYXESC5BJIJc5PCVsbEeehNa5niniIuJjMDNvTqGViJfw0ohWqVQrEnewi1rX8QY96aF8nyiFzy1u8qZDNrV/jKgRCvEbx4QGs252LwssikCr7sFoIv26Os9YGAXIJ630EbJlqBFt/NUdDgujfDiVlY8u5NI/m6Q1sWM2qgVL4oc4RX3NU+mE14uEV9hzxRfQErnFkMDFe7T8RY9t7jQBLKK9OjCXMTY4PUl2dwLYQKWPjiBiV9scnADz/RFXM7m8parz8YDJ2X850GFMcuMkMzvSPrpC50MqR54int0AwrGY7Tgu0RsFzMTVPAzNjiSTYL3DKGp+Moy+++AJTp07F2LFjYTQasXDhQnTr1g0rV67E559/7u85PnL4o79aSk4RUvM0kIpFbJd5f2qOnGWrEaOpUpAcnetFo02tSDSrFsEWaCNwvRlaPX9eBpOZF0orlufIg7Cau0w1Qh2r7siVKJvbU+yygHF0O1sNndGMAJkE1SoFIjpUiZ9HtmINod6N4zC6gyVD012BPXdovPAcScQi9ibuqi+aUMNZLsUNq1XmhNWMJjNrFAiFOytx0pLtbz4hbFjNcV+4It1P/75SrKaoQmTZeY5c3WQ8has5KstsNSFD25kRb2+YeBNaO2k1jpzVFGtszXoFwEvjJxDNUWYZh9XI7yZkVALAi62q4dkm8QD839ja2cLCU1yF1YimkHhwhcJq9okDQqG125y+eCUVdfIVn4yjp556CufOnYPRaETjxo2xa9cuREdH48iRI2jevLm/5/jIwXqOimEckV5hTRLC2Sadxc5W47zfmeeIVDx2V3hPJhFDal3N2F807V3wxTGOPKnH4S5TjVDV+ru4ctUXcr4XrtCacDXd4jV6LDaEzVKpHhmETW+2xRf9G2PeC03Yi4RtRe7bzdBZ4T5ncHVHznDWcJbgfVhNWJD9oFDPC4kJhTu54RanYTU7w4dhGPamXSlIjgeFOszdec2juXpKSYTVyku2WpBCOKwG8I9To8nsYJhoPRRlMwyDW1a9EemlZg8RZQP8NH4CKeuQVaBzWtusNFCz35vz62G41XjR+Vgo0xnFNo5c9Vaz9xwJeIXsPZxCxpFNUC98PSlLvDaODAYDRowYAZFIhB9//BHHjx9ne5o563tG8Q7iOcorMnjc3dweElJrUzOSV2elOIUluRc3Z54jYhwIXUTtcdZCxP6xsThhNTvDSmiF4y5TjUBuuK5+E65n6pKAcXQtw/JcPWtYgJBQKRAvt67G0/pEFddzZP0ePa0Q7EnGmrOGswRvK2Q70xzlawxsxlqwQioY7qwU5NxzZEvl5++LSmtkjb95g5oAAH45dgfnXNSc8gaTmUG2NQGBVOz2hyCbm7hQoDWWSo0cgsFkZs8joVY09qFQAMgs0MHMWLw6QdbjytOMNZXGyIZpqgro2gC+cWSfxg9YjiOJWASTmfH5/CkuDMOw1wpX10OlzLtzxlOKbRyRyu4uPUeWc9BVthrZTqpAxhrJpq4h8BuWNV4bRzKZDH/88UdJzIViJUQpY+u++OI9YhiGFWO3rRXJ3rAA5yegRm/C7O1XcPpurtPtctPrnd1AifERrHB/QhLdkb2nyD4NvDjhCE/qcThLF7eH7JNQfJ3ANZxuZBU4fP4Vqxi7XhzfOBLCX2E1+35YzrD1V/PAc1RJ+GLma+NZcryHB8hYL8At66rSvnUIgWsc2bcmcFYEkoTUIgJl6FwvGv2bVQHDAB9tvuAXD0OOWg+TmYFIZJufP4pA2p9vpSnK5ho1nobViJcgNkzJ1kbyNKyWkltk3a7c6bFbPzYUxFkkVIxUIhYhxmq0lZXuSM+RB7g6B4m31d/GkcpJAVVPISUoBLPVWM+RNawmcE0knqPHrAtBIQ2tzRP9EBhHANCvXz9s3rzZz1OhcKkSYe2x5oMoO/mBGpkqHeQSMZ6oHsErIOjsAv3f9fv44b9bWGAVBQvhSSo/MQ6cZX1x8dxz5EfjqBiaI1LF2VmVbYB/kSBFHLlcJZ6jWOFwARf2piPQt8oTbIJsz05zW3813zVHNvEx41H9FvuwmlgsYlejJLTi7HeJ4GiO7BsGhzrRHJEbJRHsTu1VH6FKKS6mqvDzkdtu5+sO8ltFBilYb5fMD54j+/OtNENrxEssk4gEi5GS8CFXkE2Mo/iwALdNpu0hvfuqRjgPtQTIJawG0D6NnxDD1joqmUKQyw7cwqvLjznNxOP+ZkEuQtvknPF3F/p8JwVUPcVZWM1oMrMLCXKuCmWFEgO+YbzlWudKc1Qew2o+pfLXqVMHs2bNwqFDh9C8eXMEBfGtvnfeeccvk3uUqRIegCvpKtzzwXN02BpSa1YtHEqZhBdK0xnMgEBpF3KTciVO1XhQBLLAAzcygS0Eaedut699VNLZavbeC2cQHZWrBrbEOCQu/cvpKjSwXhwKdUY2U6perAeeoxB+zR9vITe1AIFQiBDu+qsV6Y3sXKo50xxxQnh6kxlKsfPjgGEYh7AaYFmNZhXo2BRfZ8ZRJQ80R/aeQtIlPt5644wKUWByz3r4aNNFzN99Ha88Wd1lxqI72BpHIbb5KPzgOSoy2HmOSlGUXeTGA8ntr0bKcpCif/HhAawh52kLEeI5chZSI7zWrgZ+OXYHT9ePEXw9LkyJMyi5dP7lB5ORnq/Fmbt5aFMr0uF1cp1QSMUujykS9i6psJo7j7gziCDbXvPJPY7JAq7Q7jwzmRn28y1dEe45GEcmM8Mawg+NcbR8+XKEh4fj1KlTOHXqFO81kUhEjSM/ULUY6fy2kJqlyzLp76Q3mp1eoD1pEMnvrebac+RNWM2ZIFspE0NrcD5nT/BIc+Sh+5nccF0ZR+S1RvGhOHcv3yLKtuYoXLOG1GJCFQ61W4QgF57cIgMMJrNg6rwryO/laWdrd5oj4gIPC5A5XY3yQrgG5/WSAMsxR8IO3KKa5GZ702ocOfssYhyJRLbvikDeY18hm3gRuJ6mF1tWw7TNF6HSGpGnMThsyxvsxdiAfwTZ9p6j0iwEST7bmbCffF96kxkqjRFhgTKb5yhciWRreNRT44gUv3WmayO82Mp10cDYUGs6fwlkrJnMDJuV6Ox6UOSBGBvwvuWOpxRfcyRcgoIre7AJsu20fRoDyJq8gRPPUVqeBgYTA7lE7FOR25LGJ+MoOTnZ3/Og2OFrOj/DMDhmNY64qxmF1ThylhFBDBJXFzCu29fZBcGmOfLEc2Stku0krBailEFr0BUrrGZ/Ygun8nuWrcZ6jlyE1Yhx2LJGJZy7l49L1oa7gM04qutBSA2whI3EIkstqBy1XrBWiivYTureZqs5CZnezXa/ypOKRRCJAIYBdCYTAOffKQlnikX8sAMRoiezmiPXxlFkkMLBcCSGrMZg4hmWpGozN/VbIhYhWC5Fgc4IVXGNo0JS48jROCpenSPLb1k5WIEHhbpS9hy5Po6UMglClFIUaI24X6hDWKCM1XbFFSOsluAirOYJsWElVwjyQaEtC45k6Nqj9vD8s4XVypcgW+okrEYWnBKxCOEBwoJsUm4iWCFl2wxlqLQwmsysF83WNDigRPvL+Uqx294yDFOsDCiKMLZCkN71V1NpjWx14cacjA53rn3iOXJ1AfNEc1TIeo680Bzp7T1HlrmQG5yZgc9iWbJfpP+TS0G2m2w1ojly1YqF7H9La32Wy+kq9vwgeqP6HoTUAMvFhzRY9UV3xGqO/JSt5i5TDbB4KT3tr1agtR0r3BonJPuJeEecXdxJSxehECX3+OOuasmNMtZJdpuQdsIbslSOniPbCty5DuvPs6lsbR8hyPlGrgulqzlyL+y3z6wkmUlVwgNsTaY9DqsRz1HxvAlsCxE3xlF2oQ6fb72Me15ca7nbLHRyLSS/mbtroS2s5l/PkaqYxpHcWViN0zqEXBOL9CbeNZrojcIDZagcrIBcIoaZ4bdz4dY4Ko/4bBz99NNPaNy4MQICAhAQEIDHH38cP//8sz/n9kjjq+fovlXzEKKU8sIpbEaEkxuWLawmfHMwmRneCsJpthqrOfLAOHKSrUYecz0Gvq66yYlM3L8ui0C68RxxC7kJeY+MJjNr2DVLCIdMIkKB1siGCUiNI08y1QiVg33THZnNjNdhNXd1jlw1nOXiafaNTW/E/97tm2Q6M1ofiwnB328/he9eaubwmlQiZr1RXIM4jXg0woWz24SMZ29w5TkChBcnqXkavPvbWbz721nBbTIMwzYRrmKdd2kWgvSkXpZ98kA653v2xnPEMAxrpLgSZHsCMYDd9Vf7ds8N/HggGcsOeB4R4WbAOfMkk2uNp54jT5s1e4r/wmp8g54YcQqZmGf4cb8H4tmMCJRDLBax5xu3Ae0dVoz9EBlH8+fPx9ixY9GrVy+sX78e69evR48ePTBmzBgsWLDA33N8JCErxKwCnVdahUzrytU+BOPec2Q54LUGs+Dq1t6AcXYDLfQiW00pdZ2txt1GcY2jSi6yKoguxVkzWYJEbKvZImRkcQtjhgfK2Wwa4j0inqO6MZ6F1QBOJlChdzdDbtkFT8NqrOfISciU6N/c3bQ81djYMtX4x4oz/ZAQjaqE8fRbGRkZuHTpEhiGYX9P8vsyDMOu+Lkahzt37uDCqmnI2vgZbt2+63LO7rgv4DmSS1wbR6Qxc6ZKK+iF1xlt2UHx1nmXZiq/J+GhKE6toyK9kfVsxXM9Rx4YRw8K9dAazBCJLHql4hDHZqsJf6+EQ9YEFm8WotwCl87OF7LQdKs5sl4HteVMc2QLq9lpjjieI7lUzN5bCjjhxVy1zXME2I5bru7ojgdh+rLEJ83Rd999hyVLlmDo0KHsc8899xwaNmyITz75BO+9957fJvioEhkkZwXJ6fkaj61rki3DXbkCnPozzjxHnOc1BpPDCW1/YXN2QVB74TliBdl27UO0gsaRb2E1+3oceqMlJEYuSIDnRSABy36p9SbBrLdC68WQXDQaxoficroKl9NUaFwlDCqtEVKxCLWiPV8p+VrriGu8KqUeeo7krj1H5IZcKcj1xdbT/mpCmWqALaxGcOXRu3XrFvbu3YuDBw/iwIEDuHnzJgBLg2lRi1cBSQxrhKk0tgKQcWFKMAyDn376CW+//TYKCixevXEDuyD8p1Xo27evy7k7I5M9/2w3dq5xZBAwGMm5ZbR6++w9fdzfI54tEFt6niO2XpaLc5rr4STegRCFFKFKmdPwuRAkUy02VMk7R30h2prBqDOakVdkEEyCyCrQsuU2srwQbnO9Uc70l2x1bDd1xlhBdjnzHDkLqxHjiMw7RCmFrlDP+x6IZzPcWm4jXiASUt6NI588R+np6Wjbtq3D823btkV6enqxJ0WxaDfYA8qLjLUst54j4QsU90YmtMJzKNRoNAsKpbk6Ene4q3MUKJeyQj1fRdms54hTE8feDe5pEUiAU+tI0HNk5I0hWRqX0lSs16hmVJBXF332puOl5ojciJQyscdNJwPceI7yPczq87RKtn2NIwLZZ4LQ5508eRL9+vVDrVq18Prrr2PVqlW4efMmRCIRZDIZ9u3bh6PzRiF71/e4l2Fp6JmushWALMjLwYABAzB8+HAUFBQg7rEmkMfWRqEqD/369cO4ceOg0XifDJHOeqZs559YLGJb5bhrsiwU1iO/h1ImZsPDZGVeGrCeIxfaNW5YjXgHSCjFG88Rm6lWzJAaYPHIkBCts0KQR2/ZdF7E6+4JmfkeGEckrOYmOaUkikDqjWb2+y5uWM2+QwFXcwQI9zEk14oIq+eIRELIsWE2M7iT8xBqjmrXro3169c7PL9u3TrUqVOn2JOiWCC6I29qHZETvFieI4EVHqtf4VwgiwQuduRC6o1x5Kg5sn2Wq5uKJ5ATOUAuYcMC3IsZr7mpBxeREBcZa+TiQGo8NbD2hbqSrsJVUhnbw0w1gq+eI2/F2IBt3s48R54akXIP+6s59Ry5CKsdOnQIPXv2RMuWLfHnn39CJBKhffv2+Oijj7B9+3bk5ubixo0bGDRoEMCYUXhmG0b0bodXXnkFb44chvubvkDq+plo1KgRNm3aBJlMhi+++AKvf/kTYl/5Gh0GvAYAWLx4MVq3bo0ff/wRZ8+ehdHoXqidrdZDb7SEhOyLUroKNXKzlITCvtzFAlmJl2ZYTeNBSjo3/Ev0RmRx55XniC0A6Z/U7lg3DWhJmyXAohfzNPGDa2w5Dau5aTpLKIkikMQ4EYk8kzgIQcJq9tde1nNkPc+FsnjtPUdEK0c8R1kFOmgNZkjEItZwKm/49K3NnDkTgwcPxv79+9GuXTsAlovWnj17BI0mim+Qm4Q3LnQ2rObgOXK9OuHGu4VujqxIOkAKg7UsfpHOxLtRMgxjS+X3pEK2kywWbp0juURs9VIVL6wml1rEg0V2ITHu/z25iHjiOSIXw/pWz1FqnoZdoXojxgb4jVi9wdvWIdyxzsT2nrrpPfUcqZwYR9zijozJgCunD+OPpQewfft2XLhwAQAgkUgwZMgQTJkyBfXq1eO9PywsDOvXr8eA6cvw1w9fQJ2VjDVr1rCvk5ykBg0a4JdffkGzZs0wf9c1iCQydHjlfUwdNRjDhg3DhQsX8MYbbwAAAgIC0KxZM3Tu3Bnjxo1DbGysw/6QApNRwY6lBeRSMYr0JifGkesSGWqOsJesxEszrEa0dK6E/VwjnmSqEV2Xd54jq3HkRvTvKXFhSlxKU7FCfHuO3rIZR5a+eDqHVjRCZHoTVvM4W81/niNyroYopB57ju1xm61mPc+JccRt1UMyTUlTXWIoE88RyVSrGhHgdf220sIn42jAgAE4duwYFixYwLYRqV+/Po4fP45mzRwzRyi+YfN0eL6iyHLjOXK2mrfXHNmj5XgiAuUSqLRGh5sot6ifJ54jpZOwGvezpBLhE9RTuC7gEKUUWQU6nkFETuhAucSjk5Tsl1AbErVdGYNQpQwJlQKQkqPBwRv3AXhWGZuLUFNPTyjihNU8xVVvNa3BxF68wwL9pTkSDqvJJGIEm1RI/msxNLdOYfhc241IJpNh+PDhmDx5MmrVquVy+/WatcbJYd+go+wWHo8w4uCtXBy4mYc2dWIw4ulG6NWrF5RKy43Q1qjWgO79uuPcuXNYtGgRjhw5gpMnTyI/Px+HDx/G4cOHMW/ePLzxxhv44IMPUKVKFfbzbJlwtpUwwzC4desWpGaD9TvxPqxWxNGukLoypZmtpjEQo9+FcRTiGFYj3gLvPEckrOYfb0Kt6GD8cyULh5IeYEjr6rzX0vM1SH6gttTZUljqNGWp3BtHDMN4pjnSuf/eAM/PF29gFzJuzlVXOAursdlqUpvmCOB/D/lW4ygiiG8cpeZqwDBMuc9UA3w0jgCgefPm+OWXX/w5F4od5Cbrqgu8PcRz5Exz5OwE5F60hdL5ietfKZMgSCG1GEd28+KeHO5cyYALzRG5sXMMFl/DajrOKifYehPmzpNkMnlaYp9U/hYMq+kcvWYN4kKRkqMB8dZ7H1bzLZWf3NC88hyRsJrBcd9ISE0sAoLdbNNdCJfgLKxWUFCAO2unoygtCQAQHRODHt27o0ePHujatSsqV67swd5YDB6RWILaT3bDxGcbIH39OZwNvYee3evi+c61+WNJZpt1TjExMfj0008BAGazGTdu3MDRo0exdOlSHD16FN9++y2WLl2KkSNHonv37oiNjcXFewYwRgMqibX47bffsGvXLuzatQupqalQRlZBRL+PBI18vnHkwnOkkCDcerPRGszQGkwuK5D7C5vnyH1YLbtQb9McFcdz5AfNEQD0a1oFP/x3C/9czkKuWs8TZZOQWuMqYTAxDC6mqqzXzzAnW7NQoDPyvOtOk1M8ELIDNmGz1mBm268Ul+LWOALAFmu0v/Y6eI4Eek46CLKtx4Jab4JKa7SJsf3kISwJfDKOtm3bBolEgu7du/Oe37lzJ8xmM3r27OmXyT3qBHlpHDEM415z5MxzxBVkuwirKWQSBFpPFrWdh4G7UvLElUsaotrH2slFVCmVOF29eAo5kWUSMds7jbs69yZTDeCukpwLZ7lu9IbxYdh5ySIIDlVKeUJdTyDF9Ui3d08ryZIMQK80Ry48RyqOl8fdb0tCuO4MWiHPkcFgwKBBg1CYlgRxYDjiBn6MOyvehUTivRFAfisy9wwVuWk7/gbk91cJaHnEYjHq1q2LunXrYujQodizZw9mzpyJgwcPYsmSJViyZAlv/CrrHxdtdioyfp6AHU8EoNmbw/mvcYxIIc+RTXMkQYhCyvbtyysyIDas5I0jm+fK+WcR4bPeZGb1dd5qjkxmhtWkFLcAJKF+XCgaxofiUpoKW86lYVjbGuxrxDh6slYkkjILcREqj0TZ9kUlndU5KmI9ya5/I6VdP8LiZukBtmO+OMaRzInX3l5zZCuwy61zRATZluMiQG4Rx2er9UjN1ZT7TDXAR0H2hx9+CJNA1hPDMPjwww+LPSmKBXKTddXLi0uhzsheSKPtGnG604G465tmE/iKOcUC+fOyCZI9MzTcCrLlEqcnqKfYa44Ae8+Rd80ZXbUQYcNqcr7niFAvNtTrVWGlIDlEnBYinsI2nfWwxhHgukK2N2nBttRkz1L5idHKMAzGjBmDnTt3QqpQInrgDETXbuyTYWTZri1UBtg0QfZiae5YlZsikCKRCF26dMH+/fuxd+9evPDCC2jVqhWqVasGsdT23TRu3BgTJ07Erl27kJKSgkp1ngCj12DqW69h6tSpMJlMMBqNOHjwIH7/YS7Sf5qA9J8nYNHMSZg/fz527NiBe/fuAbAtQgLllkriRMdRWqE1T44l0kIEsB2n8XZhNaEEDi6ZKi0MJgZSscivvbYGNq8KAPj91D3e86QHZZuakaxG05lwmwsxjsiC02krJZ1n3lteP0I/6Y6Km8YPADKrIJux61CgZ40jfraaYCo/5/O5uqPyXh0b8NFzdOPGDTRo0MDh+Xr16iEpKanYk6JYICsOTz1HZNUTopA6nJBuNUcepvJzVzlqvbDnyBMxNndbrhrPOqvS6il6637JpWJOFWRHzZEnmWqAbd+ENEdEG8YLq8VzjCMvxdiAxbUdEShHjlqPB4U6XnFBV2h9ylaTWt9rdvBSeWUceZzKzw+rffrpp1ixYgXEYjEGTZqLw4Yaxbq4s54jjZGXZh8vcOO1LxjpDpFIhE6dOqFTp07scwO+P4Tj11Lw1fON8HLHRrzxbd6ahwNrvoXqxCbMnj0bf/31F1JSUpCfn88bdzDtGg5utSW11KxZE1UbtoJaXAPiml0BWArrZav1pdZCpMjDej1RIQreuUWMUGJ0a914jkgaf3y4f3tt9W1aBV9su4ILqfm4mqFCvdhQpOQU4V6uBlKxCC1rVMLZlDwAnqXzE71RzcpBuJpRgEKdUTAcZms86/oclEvEbD9CrcHk8ULNFfluWu94goxjtBlMZkjE/DYnCruwGvntdUYTu+8RnBIq8eFKXEjNR2qezXNUo/JD5jkKCwvDrVu3HJ5PSkpCUFD5tQQrGrawmmdCPaI3igp1vIG6y1bjPi8YVrO+rpRKOOEXYc2RJ2JswFVvNa4gu3hNO4lRpZCIWb0QzzjS8L0X7nDlOSKhNq7nLC5MyVaJreulGJtg37fKEzxp+WAPd6y9VzDfw/5zAKemlhd1jlatWoUZM2YAsKTRt3vaErL39HcRghVZ6wzI1xhYI1zQc0TCasVoH5Kh0kESEIJ6iVUcXlPI5Yh4eiQmz/keAQEBuHjxIvLz81GpUiU07tATkb3Go/Jzk9HxxbEYOHAgGjRoAIlEglu3bmH/X7/hwZ9f4n9juqBbt26QFz0AUHoZa542MOaWYIgKUbDXHKWHmiN/p/ETKgXJ8Uy9GADA7yct3iMSUmuSEI4ghZTVaHpSCJLUOCK9/cyMcNNY4oF1Z1R604/QU/K99IgLQbz2AD9Ebq85sm+9QwwzsV0ZAeI5upCaj0KdESKR/7RlJYFPxlHfvn0xfvx4thotYDGMJkyYgOeee85vk3vUYY0jJ6nV9rAFIAWyLdx5jnhNZYWMI70tndc2L/44r40jtrcaf04ajpdK7q9sNamYk4ZvuwEWeOk5Iie70G+iZhtN2m4iIpEIzzWJR4hSio6PRfmwB0DlEO9F2ex36IVxpJCK2RW7/TFAjEjPPEeepSaT4+XUwT14/fXXAVhC9mPGjGE1c0JVjT0llLOiJV6jSkFyQREzuYkU6U0+FRw1mW0ZTEKeKVIwr03X53Dy5El8/fXXOHr0KLKystBn/FcIbtwFQfXbo+Xzo7FhwwZcunQJubm5+Pvvv9Gu31DIomoADIPdu3djzxfDUHh+t1dh1uJQxDn3XRHFMY7iOQYoG1Zz4zki1bH9UQDSHhJa23w2FQaTmRdSA2waTVLh3BXpHM8RwWVpDw+uh/4uBOlpwVZXkLAawNd86uzCavZyBW7DaK4+kdTtI4ZpfFhAqSQU+IpPy7I5c+agR48eqFevHqpWtRx0KSkp6NChA+bOnevXCT7KeJutZqtxJOQ58jxbzXVYzXbCOPMceas5ch5Wk/ghrGYzjkIFw2reZqu58hwJ7/+svo0wq28jh/GewtaQKfD8ZsjWOfLi4iMSiRAol6BAIBPRt7Ca65uhSmuELvUq3vv2Y5hMJrzyyiv4/PPPAQDdG8XiTEoe+jdz9MJ4ii1UZmALE8aGCgviuSvcAq3Ra6PsfoGlgKBULBIMfXIXJw2aNuDJEpxlq4WEhKB37944aqiOe3VfwMv15DiwfBYOHjyI7O0L8XXhZXTfuNbj7D1fKfKwXg93v+M55QzYsJpbz5F/xdhcOtaNQuVgOR4U6rHv2n32Bt2mlsU4snmO3C9AiOcoNiwAwQopCnVGFOqMDr97kc5z762/C0EWR3N0+/ZtvPHGG2jSpAnE0k4wM/zFKbmmplw8jtV5p6CSV4ZJW4hCnSXLj3g0w5VSPHjwAIGBgQgMDHRopl6exdiAj8ZRWFgYDh8+jN27d+PcuXMICAhAkyZN0L59e3/P75GGuGM9rXPkrOks4GWdI6FUfjbOLGG9Cw6eI6Ih8dA4UjoNq3EqZBfTc6QjgmyJWNCwUXkRLgJc1zliC2B6uP+e4kuVbFZA74XnCLAccwVao8Mq35uVKHHHuwqr6YwmqDPuIOv3mTBrNejZsyerNwIsxuoX/Rt7NXd7QjltDUi/L2fNTKUSMYLkEmuqsXAfLleQGkcxoUpBvQx7/gkcx9xzr0AoC9J6PlZPrIlP9+1Dz5ETsfvnRTh3YDcaN26MjRs3ok2bNl7N1xtYQbYbQ5vb9oUrqOYuglylqpM0/oQSSO+WScTo17QKlh1MxoLd15Gh0kIuEaN59QgAtgXlg0IdjCYzG84XgngI48KUCFJIUKhzXEwwDONVtwB/F4L01Ti6fPkyunbtirS0NOzevRuVOz9AUKuBvHNZZzRDfXkfVv41Fys5780MCkfrnx9DRnYe7qVn4o6mAFGTzQgICMCQIUPQbdAw3mc9VMbRkSNHkJ2djT59+kAkEqFbt25IT0/HjBkzUFRUhH79+uG7776DQuGZaJTiGu89R8Jp/IBrty3DMLxVvmC2mt5W54iEuux1Kd64kcm2AMeLpkbAc2Q0Fz+sJtQDiBVke+o5EqjpQfDmYugNbN8qHzRHnhpHmzZtwsGDByENbgdA4dRz5Op7YhgGM2fOxPyFi6DsPBq6lglOx15NSkbm+o9h1hagdevW2LBhA2Sy4gtRuRBvkNHMIPmBJTvGVRZUaIDMYhx5KMrmkp5nu2EKQYwjocazvArZAscV64FQSCGRSNB32Fu4KEqEfvdCZKTeQp8+fXDs2DHUrl3b4b3FxWRthgu4P6+5miOuEUpCuyYz4zJVnQiy/a05IgxsURXLDibjcrqlz2GzauHsNSgySMGWSMhW6wUXmASS0RYTqkSwQopM6BzqU2kNZra2mbs6R4D/C0H6YhwdP34cPXv2RE5ODmJjY5GRkYEHe1dDVKkajOZO7LjrZ47iwdZvAABNmjRBZtYDZKSnwqDOw/Hjxx22q9FosGzZMixbtgyKhEYIadYLkqAI5IWkYPXqM8jNzYVYLEa9evXQsGFDxMfH+6XWU3Hx6io+a9YsdOrUCX369AEAXLhwAaNGjcKwYcNQv359fP3114iPj8cnn3xSEnN95CBZDhqDyaMaN+SktW8dArj2HBlMDLgthYQF2TaRNEnVto+zCxVBdAX3xq0zmtkLFVeQzYbVjMXPVhPKNGMF2Z5qjkgRSMFsNe+MQ0+xFYL0Iqxm8CysxjAMvvrqK0yZMgUAoAhZhbAe76JI35I3zl1ROZPJhDfffBP/+9//AADqbQuR3bUjgMcdxubk5GBQv2dhKngAeeUEbN26tUQSOQLlEvaGdz3TUntHSIxNCFFKkZ7vmyg7XaA6Nhe5i2KmGidhNUKR3W8ZHiiDPKYWus9YjUs/vo8TJ06gd+/eOHLkCCpVquT13F3BnZu78JCzsBrX46TVCxtHBpOZ/Q5LQnMEWEppNK4ShguplgxBElIDAIlYhKhgBTJUWmSqtE6NI53RxJ6HsWFKpwtYribRk9C2rfyF80WgwWDweAFBzteinAysXbsbCoWCDW8FBgYiJiYG8fHxkEot8//nn3/Qr18/qNVqtG7dGtu2bcNHH32EpUuX4sFfX+Pqu88isX0LXLhwAX98NR4wG9G8cy8c/+cvpOZp0e6zbRDlp+ObPlWx71YhNlzKR5/WdbHotY44duwYvvvuO2zcuBG6lIvQpVwEACy1/tkTFhaGBg0aoF27dvj666892t+SwKur+NmzZ9mqsQDw22+/oVWrVvjxxx8BAAkJCZgxYwY1jvwE9yar1hvdejfuu/QcOV+Z2D/nTnNELpL2xQLt22e4Q8lJFdXoLdV+GYbheI7EthCNH+ocEQNRsAikl56jIr2jwert/nsK20KkwIuwmgeeI5PJhPfeew/fffcdACAuLg7p6enI2jAD3yhS0HbZItYL7GolqtPp8Morr+D333+HWCxGRHQcsjNSseuHWWDGdOWtArVaLfr27Ysb165CEhyJhiO+RGRkpMM2/YFIJEKIUoq8IgOusYUJnRtHoRyNkrewYTtnniOJ88UJ13Mk1HiWbWBqXSyR9OhCkxhbtmxB69atcf36dQwYMAA7d+6EXO67iN3ZZ4tF/Ho8QvA9RzbjSCaxnMcGk+XcDoPjMZSep4WZsXyGp+UqfGFg86o246gm/7iLCSXGkfPzjGiS5FIxIgJlTpNmuHojTwriKlnPPv+ayjAM9u7di3nz5mHHjh145ZVXMH/+fLfnTL7GAPXVgxjwzHcoKlILjhGLxYiPj0dCQgJOnToFvV6PLl26YNOmTQgODsbChQuxZschFNy+gLHDXsTfWzajZ8+e0GsKoajaEG9MmwexWIxQpQxieQAQVRO9n+2Jq7uvQX7/FhKqVIFcLkf79u3Rvn173Lt3D08Nn4rU03sAkRgNasQiProywsPDodPpcPnyZSQlJSE/Px9HjhxhDbeywqtPz83NRUxMDPv4v//+41XDbtmyJVJSUvw3u0cchVQMqVgEo5mBWufeOMriuHuFtgU40TzYXbBdNZ5VyiROG5R6m60mlVgay+pNZmgMJkRY58dYnUTc9iG+ZBAB/N5q5DsQKgLpaedqbs2SQp2RZyyUlObIl1R+m3EkPBetVouhQ4diw4YNAIAFCxZg9OjRaP7scFzZsx5bflmG1hdOYNq0aahWrRoyM9LBmKUOxlFBQQH69++PPXv2QC6XY+3atbhtDMfEIT1x99whrFixAiNHjgRgacMxfPhwHDx4EMEhoQgZNBOVY30XXHtCqFKGvCIDG3KODXUdVgOEvTfuYD1HbsJqwsaR6wrZbBsK629JCuvlFRkQGxtryWhr1w779u3D2LFjsWzZMr+FJYo4n+1um5VDhMNqgOW6YTAZBVsTAbZMtSoRASUaUnmuSTzm774OhVSMptXCea9FhSgB5LssBGkLqSkgEolsGkSt8LXQXQHI06dPY+7cudi6bReY0DgsTWuH/N6d0aJFCxw7dgxz587FmTNn2PE//fQTduzYgcWLF2PgwIGC29To9Li3axlUx/4AADRs2BAREREoKiqCRqNBYWEhMjIyYDAYcO/ePbbY6MCBA/HLL7+wCyK5XI66Q2bgzHdjcSf5Jpo2bQqTyYTw+EQEPz8NQUGWc4l7TVTrjMhTk+rY/GtF1apV0e7FN3GoxWAAwJFZ3R2+H51Oh+vXr+Py5csICCiZ8KqneHUVj4mJQXJyMhISEqDX63H69GnMnDmTfb2goMDvuoFHGZFIhCCF1LIKcKM7KtQZ2YuoS8+RgNvW3jgSbh9iE0mTk8HeiGKLIHphHChlNuMIsLjdCQF+zFZTcFP5tbaibWy2modhNYVUArlUDL3RzDOOzGbG4y7c3kJW5NlqPcxmxqOVaBEnNAlYXPK3b99GUlISkpKSsG7dOhw6dAhyuRw//fQTBg+2XLA6j5iMB+H1oNmzCOfOncOgQYNsGxWJMWBVFAIDFJBKpZBKpcjPz0dmZiaCg4OxefNmPPPMM9h05h7C27+KvH0r8N5776FLly6oXr06pk6dinXr1kEmk+GjBcuw9EagQ9NZf2Nv9Lr2HPle6yjNmsHkNKzGLk4cj2Mtx1ugM5qhN5rZ8YAtQYKcd6RfFUmZbty4MdatW4c+ffpgxYoVqFSpEnr06IHIyEhUrlwZlStXZhvseovaSY2jnJwcfPjhh/jjjz/w0ksvYcqUKYiJjcNjMcGQScSoHMS/BgXILFmQzmodkRpHJRVSI0QEybFjfHtIRCKH8F6MVZTtqtYRK8a2GtnOwmq22lBipKenQ6lUIiQkBFKpFAzDYMeOHZg7dy7+/fdf25vys/Hnzxfx588/8LYVEBCAESNGoGvXrpg6dSouX76MQYMGoX///pg3bx6qVavGVpF/8OABBr4wGKpjlu2+P2ECvvrySwcvjNlsRmZmJu7evYuUlBQoFAr06tXLoRp9cHgkop//GDm/TYZOq0FcXBzavLsAp3Kk7PcnlYgRIJNAYzChQGtkq2OHBTp6MEmZi+gQhaDhqFAo0LhxYzRuXLxkDH/g1VW8V69e+PDDD/HVV19h8+bNCAwM5GWonT9/3m2nbIp3BFuNI3cZa+SEDlZIBW/OrrJlnPU2ExqjkIltniP7VH6tYxFEdwTIJVBpjaxBRm4UErGIdccDgMGPgmyjVWQqk4jYFZ43xQZDFFJkG/U88Sy3NYKnXihPibRqjkxmBnkaAyp5kElFbqhKqQgjR47E6tWrHVr+hISEYPPmzXj66afZ54LkEgTWboXxL/6F5J0rcfHiRcvqMjUNYMx4cD/TcX6Rkdi+fTtatrTolOQSCUJb9oXk7glk37qAkSNHYsCAAfjqq68AAMuWLYOywZPAjfN+/67ssd++K6EtMZB9CaulW9OThWocAbYO50KeI/sFS6HOiEpS229MjO4AmWVfSKfzvCI9a+T37NkTCxcuxNtvv425c+c6lFSpXbs22rRpw/41atTIo7CFxq6YKMMw+PnnnzFhwgQ8eGApRrl48WIsW7YMY8aMwfKJkxAXF4fLly9h27Zt2LZtG06fPo3Yrq8DdZ5xmqpOxNglkcZvD1eUX1hYiI0bN+LAgQNQh9WE2VSb9TIKQVqHxIQpsWDBAmzfsB2GRgNRqOOL4dV6E0yFubj0+zTETz7LPh8QEACFQoG8vDwAgEQiweDBg1FQrR0On7+BJooHUKVcxblz51CpUiWMGzcOY8eOZcNoPXr0wOeff47Zs2dj06ZN2LRpk6WlTHg4IiMjkZ+fj/v370MkU6Lqc+9j3tzPBfdDLBYjLi4OcXFxaN26tdP9lUlEkMfUxOzvV+PAX7/ik08+wRdH1UBODs+AD1FKLcaRzsDpq+a48CHh1vKeqQZ4aRx9+umneP7559GxY0cEBwdj9erVvPj2ihUr0K1bN79P8lEmyMMWIs4azhLYbDUhz5HBPqzm+FncDDJbbzV7zZHlsTc3PPv+amw4SGZblQDFEGSbbI1nA2UStkx/gc7A6kAsc/bcgxGslCJbrecVkySGkkQscqvN8BaZRIzwQEt46EGhzjPjyPp9rl/xPVasWAHAcmGuXbs2+zdixAjUq1eP9z5i+MpCKrFaQqPJjFpT/oZJnYc1r9RHkEwEo9HI/jVr1gxhYbZO5gqpGCKxBE1emYojX4/Anj17sGfPHgCWpI6hQ4di+cFkAN59777ADUVHOikAaT9WSPfjCr3RzGYSxjnxTNkWJ877FhIKtHwD2F5zFB5gec1o9VYS78W4ceMAAOvXr0d2djays7Px4MEDmEwm1mP4888/AwCioqLw3XffsR5DZ3BDelevXsXYsWOxb98+AECDBg3w/vvvY+XKlTh06BAWLlyIH374AVFRUQ7yisLN3yLm5Soo0rcS/JySLABpj9lsxr59+7B69Wr88ccfUKttmhyRTInfTzyDXlEfoH379g4hPmIc3TmwEYuWfGZ5z8kDOBA4De93ncqOP3XiONJXvwtTYQ7v/RqNBhqNBsHBwRg1ahTGjx+PatWq4b11Z3GeqY4Xe9XHqA41YTAYIJU6hjIVCgVmzZqFgQMHYuzYsTh8+DAYhkFubi5yc3MBAAk1asL49PtIqFO/2N+V1Fpa44l2nfDeaxYvsv7gIctcONe5YKUUWQU6FGqNyNNYPEcRAp6j1omVIBIB7WqXbG0uf+CVcVS5cmXs378f+fn5CA4OdnDBbdiwAcHBwX6d4KOOp81nXRWABNzUWbEXZHscViteEUgAnAw1y/a5YmzAJmT1pc6R2cyw4Ti5VAyx2KIRKNAaUaA1shVgA2QS3irIHUI6A3bf5ZIS0UxUDlZYjKMCHR6Lcd+GRKM3QZd6BUt+tVzAlyxZgtGjR7udm80Y54uERWIJpCGRaNequcsaMIAt80YWEY8vv/wS7777LgBgxIgRmDZtGgBu65CS9hzZjCNXmWrcuXjrOcpUacEwlmMs0onh6qqlir03hXtcMQxjy1azGq4BcgkUUjF0RjNy1XpeGHvcuHGskUTe/+DBA5w6dQpHjhzBkSNHcOzYMdy/fx8vvvgi/vzzTyxevBgRERGC8yYeSH3WLTRv3gNFRUUICAjAjBkz8N5770Eul2PEiBH4559/MH36dBw9ehQpKSlQKpXo3LkzevXqhX///RebNm3C/S1fIXNsL6COY6V4W+sQ/xpHRUVF2LVrF65cuYJr167h6tWruHr1Kq+nXe3atdGjRw9s/msb7t25hZuHtqJjx61o2LAhfvnlFzRt2pQdm6HSoijpOP7e9AUAoHJ8NTxIu4s/F07DkKxLWLp0KTZs2IDJY9+EyaBHWFwNHNu7A4mJiSgoKGD/atSogZAQ23lsXwTSnTzl8ccfx6FDh2AwGJCTk8MawxqNBuboxzDmt0vF6qtGIP3VDHZ1jgDYeY5sej0S7g0X8By1rV0ZZ6d3K1ZboNLC5yKQQvg7jZTiea2jLNZzJHwDsGmOnBs+xKsi1D1bx/UcsWG14rUPAWzZVKzmyK7BbXHCalxDkO0DZDWOCrVGNtPM0wKQBPty+UDJZaoRKgfLkZTlWOvo/Pnz0Ol0bEiLUJifh/tb5sBkMuHFF1/0yDACbDdgruFLjIUgucStYQTYvJR6oxnj3h+He/fuwWg04quvvmLnYN90tqTg/rbuOr2zYTUvNUdpeTYxtrPvWO5EO8cwDHvMhwXIkK8x8D5fa7AlKHCFrxGBcmSotMgrMiDBxWVXJBIhKioKPXr0QI8ePSxzMBjw6aef4osvvsCvv/6K/fv3Y+XKlejatavD+9U6E8x6LU78aqll1759e/z000+oUaMG7zO6du2KLl264NChQygsLESHDh0QGGgxdIYOHYrdh06gMOsevpryDp7fu5Mt9klI8XNYzWw2Y82aNZgyZQpSU1MdXg8LC8OLL76IoUOHok2bNhCJRBjz4Wd4ZvL/YLz6L3TXDuLSpUt48sknsWDBAowZMwYikQhXL5zFgy1fgTGbMXLkSLQbNgXvT5uF/INr8Ouvv2Lnzp3IybF4iwLqPIlBk75C3bp1AVjCz86yzHwtAimTyRATE8NLlNpyLs2yj34wjoTaN3F1nARS+NcSVrNWyBbwHPlrXqWBf/3/FL8T5ETfYw/xHMW48RwJnXzEc0QOWiHPkUYglZ/UXwIsF3mfjCO7FiIag//CatwTmtycuCsclY/NGUMECkGy+15CN3tblWxbraOffvoJTzzxBFq1aoX+/fsjKSkJgOXGkLJlAUyq+6iRWBM//PCDx96sIOtvy61+7m1BOe6xJhaLMWfOHMyfP5+3Gi7wsoSCr3A9R84yyQi+htVI3zZX23dWNZxbY4zUs+IeV9yMUCVHQExW5SSE4Q0ymQyzZs3CoUOHUKdOHaSmpqJbt26YNGmSgy6tyGBCzj8/QJVxB/Hx8di4cSPPMOIiEonw1FNPoUePHqxhBAChoaHo8taXgESGk/v/cdBDaQ0mtgyJP8JqBw8eROvWrTF06FCkpqaiatWqGDJkCD799FNs2LAB58+fR1ZWFpYuXYq2bduy50ZMmBLKqg0Q3GUcbty0FNfU6XR488038cILL+D8+fPYv3gSGIMOT7bvjCVLliAkUIGwNi+g++QfUKNGDeTk5EAkEuHZke8hqv9UhIcLOxLs8WcRyOK0DrGHhNUMZue91QDbNT9TpWMXAEKao4pE+fdtPeLYwmquT5pMt54j22reHnKwRwTKkVdkgM5odqjhwy3MyA2bFemNCFHK2PcA3hkIrObIejMm+ieb58j3CtncfSXGkVDzWW+bMwp5jvxVADI/Px93797F3bt3ce/ePdSpUwedO3d2aCHy9ddf44MPPmDft3nzZmzduhXjx49HWEQlFF0/AoilWPnzGoSGhnr8+aSaL7dvnrdNLBUuDHFCqXmOONt3pgdixwb4FlYjrUOcibEBQO6kQj1XbxQVosDN+2peWM1ZvRxiHJEQhjeodUZkFejQunVrnDlzBh988AG+//57zJ07F9evX8fatWvZopz/bdsE9YXdgEiENWvW+NzHrUrt+qjUZTRydi7C1KlT0bZtWzz11FMAbGLsYIVUMBTjCVlZWdixYwd+//13/PXXXwAsCQdTp07F+PHjPcrWqxQoZ0unmOXB2LJlC7755htMnjwZv//+O37//XcAgCyqBlb8vBYymYy9FgRUrYezZ8/iu+++Q9u2bXHKEI/ze296fD2whdWK3z7E25ZIrhAKq9k8RzZjnZzHJDwql4rdtpsp71DjqJwT7KEg253myNUNizzHvTBpDCaeB0jLMVoUUjHEIsDMWETZIUoZ74LuTbNTpRvPkUzse281mxhbxN5YuHohEq7wNv7NVtrW+iesdvHiRcyZMwdbtmzhaSEILVq0wBN9R4JhquB+vgYTJ07EvHnzAAATJ07E8OHDMWHCBOzcuZNXUTai02to96SwANYZrKeyGJ4jT1bBpWccee858rbOEds6xIXx5UzzR8LVIpGlhYXl820Gjy2Vnv89EbErCWF4w9g1p3Hwxn3sGN8Bj8WEYPHixejQoQOGDRuGLVu2oEOHDvjrr7+g0WjwyzyLRuypQW+gU6dOXn8WIVAuQXCT7qhpvIOTe/5C79690aNHD3Ts2BEB1RuDYRhUdVHj6PLly/j+++9RWFiIsLAwhIaGIiwsDCqVCjt27MDJkyfBWE9osViMUaNGYebMmbxwkzvEYhGiQxRIy7dUyY4PD8B7772Hdu3a4cUXX0RycjIkwZGIHvgJalWJBsCVPZgQFhbGaur2b7kEgB8KdYWCDauVL8+RYFjN5Kg5ItdEEh4ND5CVixYgxYEaR+UcjwXZbjxH3IuzffNHruaB6I40nCwYbtVqhUxsqb8kl6KA03CRaxx4UoeHYG8ccUsGAJyViw91jrgFIAkhHMPGbL2Yeu85cmwh4otxdPjwYXz55ZfsSpcQGRmJatWqISYmBv/99x9OnjyJkydPQhZVA+t3JSDl7AEAFu/RxIkTAQDbt2/H9u3b8f777+PatWsIqN0KlVr3ZT1vnhIoILZnq4h7GVZz1XiWtHAh7VhKCq7x5bHmyEvPka0ApCvPkXBvNW6iQ4iA0V3E1s7i32TZsJoPnqOr6SqYGeC/a/dZcf/gwYORkJCAvn374vTp02jdujUiIyOhK1JDUbUhur/yltefwyVAZklUeP7tT2DKuYczZ85g/fr1WL9+PQBAHBgGedN2+KtWPrp27cp6eq5cuYJZs2Zh3bp1rPHjjCeeeAK9evXCSy+9hAYNGvg0z+hQJdLytbx0/latWuH06dP4evGPWJVSCbHxVdjfk/wu9tfnIidGrTPceVuzC3VYf/IeBjxRRbA9FJf8ohIOq5FrtIDm6J7VcySUqVbRoMZROSfIU0G29WR2pjniHsjcPmbkMWDRNATIJCjSm3i6I+4JSzw6gQoJCnS27u2+6I0AIEBumRf5PAfPUTGy1fSCWRU2Y9NoPeH9oTkq8CKslp6ejiFDhmDv3r0ALFqN559/Hu+99x6aNm3K6zN2//59LFiwAAu//Q5F928j5f5tSKVSrFixAq+++io7TiQSoVevXujatSv+2LEXk/drPL4wcyFeP25rGO89R7YQkrMu7KWVrcY16Nx5jljjRGf0qJchgW0d4spz5KQNDqnrpeQaRzqucWT5v32IwlYI0jvPkdnMIEdtec/JOzkYhZrsa23btsXRo0fRu3dvXLt2Dffu3YMyOBSRz05EcEDxWnqwzWclShw9ehTHjh3Dvn37sG/fPhw4eAiGonwkHd6G557bhpCQELZ/52+//cYaRc8//zxatWoFlUqF/Px85OfnQyQSoXPnzujRowfi4uKKNUfAeSHI8PBwPP38UKxZfRKxYbbvgns94UKSVYI8bPyssCtpYs+aY3cxf/d15Gn0mNLTdYq+Pz1HgmE1Ac8R0faREKmv4dHyRIUQZN++fRsjR45EYmIiAgICUKtWLcyYMQN6Pf/CcP78ebRv3x5KpRIJCQmYM2eOw7Y2bNiAevXqQalUonHjxti2bVtp7YZPsG5bJ2X3AYvhRE5OZ6sK7oHszLWv4PZNMxg5r9vGE6PKXihOVrueupEJzuocOWSr+WAcuU45NfgcmycXPF88R3fu3EGHDh2wd+9eyGQyvP7667hy5Qp+//13tGvXzqEBa1RUFL744gvsOHIBYe1eRnC1Bvjrr794hhEXmUyGRk+0hkgiddlXzem+CdSw8to4kjk/1gi2sFrpeY5cFYC0H1voRWjNG8+RvTeNzc6UilmPJD9cK1x1ndtCxBtUWgO7KDh5O9fBG1OrVi0cOXIEXbt2hUKhQNcxMyENjWLPd18JtBaw1BhMbL+tjz/+GHv27MG09ccQ89IXePLZIahSpQoKCgrw66+/4tdffwXDMOjXrx/OnDmDP/74A5MnT8bnn3+ORYsW4eeff8ZPP/2E1157zS+GEWA7RoT6q5Hq2LGc44i7eOV+l2q954slwNZn0pnniBi09z3or+itRtAV9tdfbnkUruaIhNXI+U49R6XE1atXYTab8cMPP6B27dq4ePEiRo0aBbVazWY+qFQqdOvWDV26dMHSpUtx4cIFjBgxAuHh4XjjjTcAWMIYL730EmbPno0+ffpg7dq16NevH06fPo1GjRqV5S46xRNBNvEaBcolTm/O3NCSzmAGOPcJrueIGCXcm6N91WruvMg41jjw8mZnn61G5uLoOfIhrCYUG+eEKclnees5IvtYoBO6iTk3SG7cuIFnnnkGKSkpSExMxK5du1C7dm2n47nUTIhB+FMvQy55Bd27d3c5tsiuF5c3BLLZao6p/J5+T9xjTW8U7sJeWp6jKuEBkElEqFYp0GUBSMBysVfKxNAazFBpDQjzYPWr0ZtYUbRLQbZEOCGCuxiwhdVsBk+Rk/YdvmqOuNmO2Wo9bmcXIbEy3yCPiIjArl27oFar8f7GKzh/KdMnQ5sL6yEW8IwUGgBltcfxSvdBGNuxJo4fP44//vgDKpUKo0ePxhNPPFGsz/YGUkRXqL9aJqmOzTGOyPXEaGZ4HvkiJ0atM1jNkRNBNjkOVBr3RrtfPUdikhBjuf4KlUcBHBeFD4PnqEIYR9waHQBQs2ZNXLt2DUuWLGGNozVr1kCv12PFihWQy+Vo2LAhzp49i/nz57PG0cKFC9GjRw9MmjQJgKXi9+7du7Fo0SIsXbq09HfMA9jUahdhtUwXDWcJIpGI7QnmiedIyzGO7KtWA443UVtYzbuLKHG3s2E1u27y0uIIsl1ojlRaI3sh8jlbTWvA1KlTIRaLcVYdCkNhGAKldQTfc+HCBXTt2hWZmZmoW7cu/vnnH1StWtXjzyTFBfUmM1QaI3vjvpdbBIYBEirZUqDtQ5PewDV62f5z1gtymIceNvsQrn3JSoPJzGptSjqVPzJYga3vtPf4RhGqlEFr0Hlc64h4jQLlEpceSFZz5BBWs2b+uNMcyYVvPt5mq2Xb1ck6cTvHwTgiBAUFOdU8eQu7CBIoE5LH0ciIxWI8+eSTePLJJ4v1eb5CPO+ZAh4aQc8R53cp1BlZ48jWeNbDsBrJVnMiyCYJEp4cl/4Nq/FLUHCNN4WAXIHgrMZRRaJCGEdC5Ofn84pOHjlyBB06dOC1M+nevTu++uor5ObmIiIiAkeOHMH777/P20737t2xefNmp5+j0+mg09lOFJVK5b+d8ABPNEfEcxTlpHUIQWE1juwLQXLrVgTI+R4hgKuLsJ0M7E1UV0zNkRtBNrmpGIsjyOa6f1nDxtYE01fNUYHWgKVLl7Jl+wHgvZ8UWNm4EeLj4xEREYHw8HCEhIRgyZIlyMnJQZMmTbBr1y5ER0d79ZnEs1CgNeJ+oQ5hgTKsO3EXH2++BKVMjGNTu9gKahKdig+rfXIxN3FWwuzF1sPVINcQFwoTcG/+xb3peoInFcUJoQEyZBXoPFqhA/waR66yc0h4wv77sJXIEPNCvgRnnqNwHz1H2Wr++FO3c/FCiwSn44vYhVHxbhX2iRdc8jTOKyqXNmSBKdR8lvzW3ErrYrEIgXKLTrNQa2RLbpDfzdProdKN54gYlZ4kC6j8aRzZaT51Jlt2pZSjybM3jip6jSOgghpHSUlJ+O6773jFxDIyMpCYmMgbR9I4MzIyEBERgYyMDIfUzpiYGGRkZDj9rNmzZ2PmzJl+nL13eJKtluWB5wiwGD8FENAccepWBFiNEm6VbLLK54ZHnHmOvK3z46A5ciLIdqZdcYU7QTYxOH2ukF2kx6effopz585h057DyE5JgkGvw6lTp3Dq1CmH97Vu3Rrbt2932qrBHVEhChRojUjP12DloWSsOXYXgOW7uXm/EI2qWArOke/Q01UrF24orkhv4htHXlxsFRKrl1LQODKw8/Ok4nZpEsp6Fj3zyJDq2KShpjOcpfJzK8KHCpaIsP6WCvuwGikC6ZvnKEgugVpvwok7OS7Hq9nzunhGLDmuhDxHJLuK9IwrS1hBtoDniHjo7dvQBCukFuOIG2b3MrTtrvwF+R3cGUcmM8OG+/1pHJGwms5gW0hzFwP22sHyYOgWlzI1jj788EO2U7czrly5wmuOmZqaih49emDQoEEYNWpUSU8RU6ZM4XmbVCoVEhKcr7T8TbCAQNYeciI7azpLcNZ81naBFnMuYrYT3T7UBTgKssm/IV5nq9l7jvhFIIsVViOaI4njSVygNbA3Hu81R1bjyMjgrbcsKc73vz+E07ez8UmnygjXZeLBgwfIy8tDXl4ecnNzUblyZUyaNInXT8lbKgcrcOu+Gu/+dhY5aj1EIsvc8zUG3MgqYI2jIjtRuzdIxCJWd6PWGVEpSG4TeHrxPSlkYhTohC/2pVXjyBfI8SF0E9IaTCjSm3hNYT2pjg04763GNY6CBTKfiAfCMaxmmUO+xuBVZh3RHHWqG42tF9Jx674a2YU6RAYLXzuKY2hzcaU5yi9PniNrKZQctR46o4m3ICRNZ2NDHY2jrAIdz7vvrVHprggk+d7cVW/nHrf+FGST49Z2TeUvahw1R2Vv6BaXMr06TZgwAcOHD3c5pmZNW6ppWloaOnfujLZt2+J///sfb1xsbCwyMzN5z5HHsbGxLseQ14VQKBRQKIqXxlocnNXR4GLzHLmep9NCdFzPkdxRGyAUViMrWbJCsmWreXdIKe20CFp7z5FfwmoCgmxr81nA+5t0CMebR3Q5hdbmrHUfewxta7f1eq6eEGW9geWo9QhRSLHwpabYcyULa47dxY3MQnacRl+8G1qQXAqtQc8aWcSL4pXnyIkhzt1eSWeq+YKtv5rj+Tb4hyNIyirEH2+2Rb1YS9VxTzLVAJsg20FzxC4GuGE1R82RvQeC/BYMY7khRjhpeGtPttqykKoVFYQ60cG4kVWIU3dy0a2h8DWQ9VwVM1vN/jznQlqglIeeW+GBMsglYuhNZtwv0LGNcIv0RvaYiLH3HNkZtWYzw9FqeRlWc5Ktxi2ZYjSZnXpciaEZJJd4XeNMCIewGvEc2S287LsiPAzZamXq046KikK9evVc/hENUWpqKjp16oTmzZtj5cqVDo0L27Rpg/3798NgsFnOu3fvRt26ddkwRps2bbBnzx7e+3bv3o02bdqU8J76DrmZ641mp94Td61DCLbms/bGEUeQTbItOCs8tums1NFzVGTnOfK2t5hNc2S2/mtfIdsPdY4EBNn5GgPrfvZakK0kxTEds/WK2z7EFTUqWy7UtaOD8ee4dni6XgzqRAcDAG5kORpHvpbvtxm+RpjNjE8aBoUTQxwo354jNqxm5znSGkw4dy8far0J7607xx5bntQ4AhyFrdztAvxstUJrnSWAaxzxf0u5VMxeG7wJrWVbPUeRwQq0qGG5Lp66k+t0vMaJ5slbWI+0nedIazCxBqKnmraSRCQSsdpNbjo/8RoFySUO3nFyLSTGEXcfPS2B4C6sxm3n42qh7E8xNsAJq5n42WoOniOHCu5l/1sWl/IV8HcCMYyqVauGuXPn4v79+8jIyOBphV5++WXI5XKMHDkSly5dwrp167Bw4UJeSOzdd9/Fjh07MG/ePFy9ehWffPIJTp48iXHjxpXFbnkE92brTJTtrnUIweY5shNkk9WrE8+RxuAYprH3HPleBJJ4GJxUyC5GnSNXZe657TG8vUkHyCQgUQyy3/7qreaKMR1rYfHLT2DzW+1QM8piFNWxio2TOMYRMWx9Tb+2Gb4mFOqNbGNUb4xIuRNDHCi9Gke+QPbRvoXIvdwi9v9X0lVYuOc6AG88RzbthplTbZgbRubVWbJbdNhrjgBuxprnomybcSRHi+qWhJYTt4V1RwzDsMdScT1HzrLVyM1cIhZ5HZIvKYQKQZJMtRgB4b29LpT8ZmIR39vuCrep/ByDy1WygLfV7N1hf/3V2V2fCWKxiHftLw+GbnGpEMbR7t27kZSUhD179qBq1aqIi4tj/whhYWHYtWsXkpOT0bx5c0yYMAHTp09n0/gBSwXYtWvX4n//+x+aNGmC33//HZs3by63NY4Ai+VObjTOVgzuWocQnHmOtBzPkWBYzU4HBHBuoA6p/MXLVnPwHPmjfQjH42Wvm1HKxIJ1eFwhEonserQx7P6XpDckRClD78fjeN8x8RzdyVY7FNL02XPEEdsTD4pcKvZKw+RqJVxaNY58gRwf9oLsu9a2COS7WbLvJk7dyWX7qrnzHDkrwsqGrKUSKKQS1ogix5OzVH6A20LEc+PogTWsFhmkQMsaFuPoQmq+YGVmrcHM9h8stubISbYaN42/vPTishWCtBlHt+6rATjqjQDbcczqLzm/maf7pOR4WrnGM4GrOXWVLFBSniNyzDrzHAH8a395ENcXl/J3dRJg+PDhbrVJAPD444/jwIEDLscMGjQIgwYN8tPMSodghRQ5Rj0b/+dSpDey4SGfNUecDARSyZafrSagOWLrLxXPc0S26UyQXaywmsCJrJCK2c7bgO91dkKUMqi0lsrkWoOZ9a6UpOdIiKgQBUKVUqi0RtzOVqNebGjxNUcKm+Hr68VW4aQLPWCrPu1tw9/SgGQu2ofV7mZbjKMOdaIQKJdg45lUvPPrGfbcc+s5sjOO7DU45DwIUUqRrdZbDcgAp6n8ALcQpPdhtcrBciRUCkBUiAL3C3Q4fy8frRIr8cZyC4EWt8M6N/GC21KGGHbh5UBvRIixq3V0v0CHBbstnsLWiZEO4226UH6IXcjb5wyuhkdvMkMptj02mvhZn64y1vxZHRsAq20iYTVnmiPAcuxmqCz3AO7xXlGp+HvwCOBKlE28RgEy59WxCc5EsnxBNr/XGSAcVgtW8D1HvnaldyrIlhPPEXHr+keQLRKJeLooXy8itm7cRt7vEljMm4i3iEQiNrRGRNlCv5c3kBuhWmfy2Thy1Xy20EkGVnkgxInniHQbrxYZiBnPNURcmBKp1jT+UKXUrVEs42gkud+Jzsj/rewLQbqqdm7rr+aZcaQ3mtnfMzJYAZFIhJZW3ZFQaI3rgfSmmbQQ5HxmGL7BnOdlDa3SIJoNq+nAMAw+/OM8stV61IsNwZhONR3Gs42otfxroTfHN7egor0Xr8jucWl6juR2YTWy4FQIeY6sx255yDr0B9Q4qgDYp81z4TacdefCJR4UnZNaK5awGt/osbzOb+kBAIGscWD1HGmLJ8jWGS3uZHYlLSWp/MUXZCvsVjHccI6v3otgzk2MaxgW9ybiC/ai7OK0DwFsniON3uRzQTlXYbXSEK/7ik2QzT/XSFgtISIAYQEyfD2wCfuauxpHgEWTYZ8WDTieW/aFIIn3RlBzFOBdWI1ok8Qi23ubW3VHQqJsW3+w4hv83GsHd+Flq3FUfm6oJJ0/q0CLX4+nYM/VLMglYnzzYlPBEDzpCqC2D4V6cXzLJGK2HIO9t7XILmKQ74HnqKTCatzkHXvIgpEaR5RSg+ulsIfExd3pjQDbAe28QraE9XxoON4lnUBYjbQ1sdcceV0EkhMu0BpNrAaDeLBYIaufBNmAbaUHFN9zVMjxHJVGtWchaluNo6Ss/7d37lFSlGf+/1bfZ4a5MQwzg1wEJIDcgpDwG7zkIgsYT9ZJXPaEEAMJv+WnogFhVYjrbVkXg0rWS46EPWuyu2IwmGg2RrPOQpZEQUQEFQU0BpREBsQZ5sp093S/vz+637feqq7u6a6u7q7qfj7n9FG6a3qqaury1Pf5Ps/TDUBW38yd3lrPkbkUmDjWDJQjHlBnqjLmA7WUX6cc8eAoPqblsgnDsGzuhQCA8XFz/GDwY1kbHCWm1QBJORLT3RP3VW2Ghuyz8QaQQyv8IojnytHrJ9oTvC6iO3aWfiMgZrjm56HsO+Jl/Hbqi8OVoyOnurHh+XcBALctnCjaN+hJMGSbrPBL5gnt0w0dT2nItjg40qfVjCqAOdyiUAxl/IBDPEelTqou2aIB5CB+I0C6OCf0OYo/DXjU2WqaJpBG1WqifDWiNSRnmlbzaJ8o5UGcgEVpNXcq5chkcMTLrvvDealUSwUPjnhajV9MzY58kOermU6rGQQCnB4Tnox8UWXQa4gxJpSj0dIMu+9/ZTKmXVCN5vGJPhQjfB4XekMRjQp6Xqi2sX0hG/2B5KX8AFAtGkGmN+pE9htxJjdVoczrRlf/AP74SY9m1EqqwMwMZV43QgNRjblYNmTbBe454sHk3PF1+O6lY5MuPyRJtVqm1wO/x4W+UCRhvpq+AXAh02riQTqlclQcwREpRw4glXJ0xpRyZOw5CnjdYhCsZraaQXDEVZK+UGxGmVlDssuliCemvlBEsy6AmlYLRaJgLLMAKWjgOQK0AVymo0P03yGPISlUKTL3HB0/24twJCpUP7NP/KrZPjeGbLP+tHzAj4fu/rBQUtp7Yw0xFQW4oFZNofk8Llw7a2RaaTVATVEEDZUjfVot1usoVYfqTNNq7b1qGb+8TjNH1wBI9B31ZTGjzwj9qCDAXnPVOA3StbQq4MGDi2akTJfrr89cGTXbEDdROdIFRwVIqwnPUQrliD902ilFmg0UHDmACl1PIZlPetIbOguoXXqTDb+MVaslltwalfKXSwNq+VOuopirkOIXX7nqhl9I5ZMwYlDimgojQzZgkXLEn/A1abXC3OxHVAdQ4XNjIMrw4ad9WTfuq/BlrxwlS+EC5gyr+YIfD1Gmpke4atRYFci47YOMUbWoOLc8+rRaWNtM0ODYqq2IrWsqD4oMV0LqKrTXitlj4s0gT2h9R6naCJih3Jd4bRGjQ2x0Q60q84hgbUPL1EGDX32HbHXki8m0WoJypEurpRghYnVw5BHBUbxaTbJg6Ll6ehNmjKrBNZ8dYcnvLjT2uzoRCaRKq30ST6vJUnky+A1LTnUwxjRSqdGAyPNGniMpJcLXYUgGfT1kyrxunENY450QypE0Fy0cYcjk3sRvQvo2+pZUq4m0WuGDI0VRcNHwIXjzz53445nuhF5RmVIuGUyjcbUu0/2UzPwPSH1gbKgcBbxuMT6iq38AlQGvasaWUmpmMKrg01dnysNn+U3RpSQWFQBAdVlmpfyfGihHAHBJPDh688/nNO/3Wqwc8XO6z8CQbadqNUVR8ONvzcLZnhCunt406PKJniNzBRE84NDPVzOjHOWsCWSSB04AmDm6Fr9aeaklv9cOkHLkAFKl1fggyfSUo8Qnk3CEiUZvcim/UVpNvtkGPG7wOIh36M60Uo3Dv5cHRz6pckMObMLRzEzZofh2pjRkZ6kcyWm1QqaJLhqulvNna6Q1Uo4yvdgmS+EC9k6rAYm9jv7My/izDY50KQoACWnkIZJyJHt+jB46Mm0C+WkPf5DSXit4Wvaj9j6tH0ooRxal1QwazApDts2aBs4ZV5dWYAQk9xwNydBTF/AmU44y8BxZ7OHSH7OyP7XYKf4tLAJSKUdnk1zwjDBSjmTzX0Aq5ZcvYEGDtJrLpYgUHJ9BZFYJ4N/LPRGy2c8rK0dJhjImQ5TypzJkm/UcycpRf+Fv9hMa1HL+/hQ+lXSQq9Vy0gSywNV9gyG6ZMe3nTeAHFVrvXKkb13BPUc9wYFBlZsaUVk3kFY1pxgdohtS21QVQMDrQjjCRFUeoHpnyiw0ZAM6z5ENlaNMSeY5Ks/YkG18zvA0eWWSNhOcaJSJpqS5SqslsyoUI8W/hUVARRLlKBJl4mkwM+VILtOPaj7nAU8oEhUXXKO0mrxevBGl2eCAX/x5MztZoVIUBR6XuYq1ZKX81niO4sbZ4IDojFvINNFF8XLyI6e6xH4ym1YT1WpSE8hM95M/SRNIxpit+xwBQKVuvpqoVKtLz3idDMNS/gHtuSVugP0Dg/bLkW+AqXwonLPxh4+huuDI5VIwbljs+OFjMgCgL2zOO5OMMoNiDzv2OcoU/vcJRxiCAxHznqP4MaBvAsnTdHx0STLlKDbKKPb/1hmyk1SrZeG9cwoUHDkAtcmY9qTp6AuJKjH9Bc8IXi5s1KHX73FBURTNU6o60sO44zK/KJyOp9XMzsriN3GeHtA/KesrJtIlPBDbOSmDIws8R2ZldCvhytEfP+kR72VdrSb1OTLbIVufIijkqJV0EY0g4zehkx2JZfxmMDZkJ69WS1XGD8Se6nmFZDqpNf4gVWegMo+rrwAA/OmsevzwtF62c9U4+vlq4UhUKB1OLv+WHwqz8SAmU474cdBYHQuOkhnw+ftlXrdlyo4+rUbKEWErKnzGaTW1qZsvwXRshN/Ac6T3PMSCpNhnYqTHgHFwxC+aXDkyW9US8GqVo4DuqcSje3pJF24G1pedaj1HJjtky00gQ4VPq42sLYff4xJPji7FuNw2HeQ+R10mxzsku9AXctRKuohGkOfDCEei+Dg+JsTqtBpjLKEStFLjORq8qo//Xc6lUbFm1OeIM67eQDkKmUsPJUOfVpONxXacs5cubpeiGbljtkN9sgpPfhw0xYOjPl2vLA4P5q3sGZWsCSR5jghbkMyQfbY7+cXOCOE5Mnhy5Qe7oigJ5fxqubFOOYqf/NkasnlKoSMu+wd0T6qiS3YOSvkrTQ+elYKj/sKnidwuRdOpudxk5SCgVfL4sWJ2fIg+raaW8Wc/rytXVEmprY/PnUeUxbYnndR1KhJHMaj7RqTVZKN/GsZ6bsruHKRijfcjA4yVo/Fx5egDSXlMNfTWDHpDNg/oKgMecRN2Kvzc7w6GpbSxuVL+fr1yFNam1QBtk1KO1WX8gJpW048PIeWIsAXJPEef9MSCknTM2IBxe3qjjqdlUrUSAPQnuUjzkm8+wsS050hXrRbQnXjeFN2WU5G8Wk0OjrJUjvrtUa0GqKk1wPzQWUA93ngs6nYpGfsnkqXV1Hld9lUKZEO23BnbbLDJ0StHsrfEOK02+E2WV3nxqq9kcNXI73EZ/i3Hp1KOrDJk6zxH3IxtpwaQZuHXkd5gxPQxnqwJJA8mKwNe8bczKudXK0utO7eSpdVIOSJsQbJqNa4cpftEa+R54CeibLDTl/PrTaNiveIXTdHnKFtDdq+x58hsWi2ZIZv3eakMeEwHEVwlC0WiaI8HdYW+4fMBtEB2T/v6n60KZK5CqQ3t9MqRfeeqceT5aifbrSnjB9S0thocxf7rdiniAYDfZCNRJtp0pApORFptEOVIrmo1+luOHRZTjj7tDQkVynLlSKdId9q0jN8MPIDtCYZNj11J1gSSP3yV+dxJZ/8BuVGOuKIXZbFjMlWfo2LDvlcoQiDSaqHYHDN+ccukjB+QfCAa5Sgx8Cn3quX8A5GoqH7Sp9X4RTNbgy2/aPIgQ19llXVaTSfZN1WXYUPLVAzPIk0iX/jaOrNLK1oF73UEmK9UA2IXabdLER3JzVxsjcz/gPm5U/lEbsRoVQNIQL2h8CDfqH9Yuc8NlxI7p07Hj6tUqp06QiR1cCTK+JOk4Cv8HjRWBdDW1Y8PzvbgktG1gxrCM4V/D9/uYlKOVA9iJIvBs0lK+cO8atGNqoAXpzr7Dcv51YbA2aV/ZTStVCJRSTmyp1/QSoo//CsCePpKjtyBzE+GVOMLtMqR+oQn57/1io7+Bmfec6TtDKtXc4RyZLbPkcFTznX/ZwwWTGnMeF05bpciLn78JlJoNUROq2XT1VhRFM2F3UxwZNQ2ApCGzlp0w80FWuXIuuBInx42UmQVRRHHUVs8XZ2qz5DwHA1iyP60l48OSa7S8Iq1D87EfEdWp9XUDtmxY8COQ2fNwv9mnefD4jqW6fUgkKSUXzR19XrUBqUGyhH3fmbz0KdH04Q3EpVK+Ys/dCj+LSwCZJVC9h1lMlcNkD1HcrVaYsdT9aY/oDlR9SeE/gZntpRdfyPXB0eilN8iQ7ZV6C9+hVZDxgwtF0962ShHgPaYM9PuwJ+k269d/FmpUD1HA5aV8QOSD4v3Dwvxc0/7t+K+I+7lS60c8REiqT1HZ4VylPxaIXxHZ2O+o9yl1WLbn4s0UKHg5/4n8b8ZoD7Upksy5Ug2eOsblMrwquH6qsGHkKeLHBwNRBh5jgh7oS8V5ZxNUZprhKHnaCBRrREXsVBEU82m9yokKEd+cxc5/Y1c720SwVGmylESz5FV6JWyQt/wPW6X8I5ke0OTL+ymgiMD8z+Ags+hS4dKqc+RmlbLrgEkYGTI5ueecTXlmbgynKqUPt1S/sHSaoDU6yhesWZ1nyORVgtxz1HxpdX438zjUjJupZHMp3de6nifynN0Ov67GyxUjtwuBbyoNKYcUbUaYTOMTNmWeI7CicqRJq2WpAEkkPhEa3YchD440v9b36U1HaJRJrxS6fSAMkOlXjmyQapoQtx3pG+HkCmycmTKc2QQiAMYtOuzHeA3oLbOfpH6ybbHEZBY+ZOsfxhXB/g4HUs8R/G02rCK5NcKudcRY0yUkFv1t+LHJO+8zdWuYjBk8+BIqH3+zIsYAro+UBwxxsXrEX44ozQqV62GW6gcAaopO0SeI8KOiC7Zcak709EhQKKsD8Awhyx7afjTrVGaRv9EW2lSOdLfyK1Iq8k35XwoRwGvyxa9WiY2xoKjbMcxZOs5MgrEAfNDOfMJD074uTFsiM+SAEGvHAUNDNlAYnuJ1H2OYoHFoJ6jdJSjuOp44tNenA9HhCE/G/+ajKxIA6ra5eS5ahw1OOINcTPfZ0mVI6mlQ3WZmvKViUaZsFlY6TkCpIKYCFWrETZErxzx0SGKkt7oEEDbmI9XvRnNyjFKq+mlfyCxVNWsIXsw5chjIq2mCY5yFLTIabRCp9Q43/o/Y3A+HMHfzh6V1ffIwYCZ+XPJypKdkFbT94mxwowNJM5WO59EldWfR6lKwmtFKf9gnqPko0M4F9SUwe9xITgQxbG2bvG+VZ3M1Wq12PafK4K5apwKf/qp0GQYdciWFbxUpfwdfSGhlGfbrFSPrNzT+BDCdugbQfKLXW15eqNDAO0BLTqeGgQ/chPIZBdwINFwaFVaLbFDduzkHIhmEBwN5CM48kr/b4+b/dAKH25fOEl4j8xilXIUZdBMjO9NYyRGoSnzusWwY8CalBqQ6PkbzHPESWXsrZaq1aIplNVP4ym6VNVqLpcijpvDH3eJdbZKES3TVaupnqPiSavx9KWZ4J+3SpErhPvDUTESqNznSWrI5kFZXZqjpDJBTqtRtRphO/QjRNQy/vQvLPIBHRTlxLxDtrbXCsA9R8bl9UDiDc5sWo03neQk7ZAdST+txn0dXreSszEV8k3MzkqIGbL1HPkMjjUg1gcGsPf+UhRFY0K3olINkNNqseNYFDskpNW0+zvlbLX4ekaZ8UgJIJZy4f6lwfyJvGLt8J87AVjbciHgVa8rgOQ5Koa0WvxawAMZU2k1A+WIB5JALLhUS/m1f2seHFmtGgGyV47lvMjFThT/FhYJalotduKczdBvBGgVFO4FMTJki+BIKuU3SqvJF06XYrxMOugDr8QO2SbSakkaQFqJrBbZ+WZvBlmtsDI4Mjt3Kt/Iga9VwZF+tlqymYUJylGKG63f4xafJxsh0nk+LPxDg6XgecXa23+JBUdWKnxyWi0SZapyVERpNY6Z3lBcbZVVb17AEPDGGrMmU464EbzBYjM2oKbV5DYypBwRtkEYsnlarTu9J0EZRVESpH2jUn61WVvqtFqFznNjdvaU/rv1NwtvFmm1XD7hyN4QfeWa05FvyGZmNcVGYsSHVsrBUcj+fY4Arc9qpAVl/ICsHPGBztxLokur6W+0g+yrwSrWeKqnKuAZ9HzgytF7p7vj62ZdECt/1yfdQdFZ30yrCLuhP57NFBwYNYEU1Z3xYCuZ54hnEqw2YwPqw6lcKU3KEWEb+Mkh0moZlvFz+Hwnrhj1p1KOwpGkFTWxdVLfy+Zml2DI1l2QvS5V1k2XfFRVFLVylGVaDZC7ZKsXeyeMDwG0AaFlabWE2WrxB48kTSA5g6Voqsv58NkkwVFP+g9SXDnio3qsbE8hb+epztjMujKvO6shyXZBf/0zZcg2aALJ02r8mig3KJU5I8r4rQ+OuOIpK0e5VOTtQvFvYZGgr1Y7a3KODs9r65Uj47Raas+RfAHIZq5YYhNIXXDkybzPUT5y48XtOcourQaoXhptWs0eo1YGg9+EPC4FTdXWKEf8HONBfrIeYolptXSVI+O0mjBjp+FP1Bv5rVSOXC5F7AM+j7AYumMDiWliq0r59fPteNB+PhzRKLK8hcDwSuvTaj5dWs1n0BC4GKHgyCEkGLJNeI4A6Wk+rA+OBkurGXiOpIt6NsFB4vgQ7e/yCOXIvp4jO/ftMYMc+OqVjHTx6/r6AOrxa+fZaoAaHI2sLYPbIkN/wmy1pNVq6v72uJRBA/zB5qvxfmh1KRpAyr9bTs1YXVXI/+6n4sFRMZixgcRiFFPVagZNIPXz7eRjQ06t8blqDTlQjtS0WmKWoZgpja0sAhIN2ZmNDuGIaelCOeIVM7JypD6dpOqQ7ZKGr2ajBOhPNr2S5PNknlZTPUe5uwlrg6PiuMhz+E2x0u8xHRyIpqPxY4wx5hzPUfwJ3aoeR4BBKX+SDtmycpROEFlTntpzdDaNBpAy3HcEWKscAeq5zYfqFq9yZCatFm+2GGWi/YV+vp3bpQhPmmzKVqvVcm/IpuCIsBUVOkP2JybTanrliD+9yspRumm12LKxEzWbm52iKJqAKLFDtom0Wp4N2XavvsoUXq2WjVlWP1/tfDgiTLh2T0M2xlNpfByLFeg7ZJ8PGQdHmXrZqsXw2dSG7FQ9jmS47wiwXjkKFKly5HG7NApgpkNnAe0DakgER1rlCJBN2bF7AWNMDJ3NhSHbqzNkl8LoEIA6ZDsGkVYLDSASZWjvNXcyqJ6j2ElnpBzxp8W+0ICaVktyQlT43Tjbk70SUOZzi9+V0CHbTFotvqw/h2m1Shs2gbSKi+qHwONSMGVElenvEAbT+N+CX1wVxf5ptW98bhQqAx7Mm9xg2Xf69KX8BpWigLZSLiPlKEkpvzo6JL1rxbgcKkcirXYuZsguhrlqnCF+D/rDIfH/mSIHHf3hKMp9iZ4jQBqMHFeOOs+HxTGVS0N2j+Q5KgWK64pexMiGbDOjQzgJniODXitlUrO2YJJyYw5/oslWCUilHPGTccBEWo2buXOBrBxlY0i3I6OGluPV71+ZVdrDp1OOuBm7wme+7UO+qPB7sh7Bosfn0bY2SNZDbIgmrTb4ccUN2Z3JlKMM02oa5chiRZSf58WmHAGxY4anMM30OeLtL8IRJh5a+ww8evpyfp5Sqyn35kTVobQaYWtkQzZPqdWW+zJu7Z+0Wk3jOYqdYOEIQ3f8hEiWVuNVGfoKm0yRbxD6k4+PctBPeE9FPgzZ8o3D7mkiMwwb4s9qFIF+vppTGkDmCp9b2+QvmESVdbsUcV5lphwl8Rz1pm/IBmKqIcfMTT4V/DrCmxYWw9BZjiYdalJx0w9s5nPVNGk1XTk/35e5SKkBpasclcZWFgHqbLWI6I6dqRkbMPIcJVYgyFI6Lw9OllbjVU1WpNWAWJCkH/fhldrXp0swD6X8fo9bfH+xpdWsQF+a7JQeR7ki2Ww1o9QVV48y8xylTqule70YUVMm1tXq9Cf/Pt5HqZjSahUZesWMEI0g4w8U5w3SauoIkbhyFPcb5aI7NpDY54iUI8JWCEN2SFWOzMzR0ftAjEr5fW4XeHzCZzLph8FyRlTHTsimmux6wXC53Uih8oq0mhlDdm5VCm5yzTS9WQroxyHwSjU7D53NJTzgiEQZIlGWsk0GL9nORDkyKuUPDUTF++l6jtwuBWPrKtL+/Zmg9xMWU1qtUhMcWaMcidYX0vfpR4jkcq4aIKfVYsdrqShHpXmVciBcmWAM+Ki9D0DmlWqA7APRGrLlC7SiKCj3eeL+ptgJqB8Gy7lt4SR8ceJwXDl5eMbrIsODIqNO3F5X5tVqfNlcd3Ld+PVp+OCTXk35MxHDp1OO1KGzpZlW4zcZIHZ8qqpt4v7gaepMS/kZYxo/V0dcTXIpmc0wmz+lAR+292L6yJq0fyYd9CpZMcxV48hqkdl0pF5tFWk1r6wcaYNhNa2WW+WIqtUIW1LmdcOlxKZvf/ip+eDIL0n7jDHDUn4gdhHj5m8guedoaIUPC6c2ZrweelIqRybSavko5QeAL04cji9OzOmvcCzJPEelmoLUD+NN1UNMVY4G31e18fEhA1GG3lBEs395Cn5ohT8hXZ2KtfMn4uYvT7D8/CnzarenmDxHVqTV/LpGkKohW/Yc8bSatq1LLhpAAlJaLa78lsLoEIDSao5BURSRjjjxaS8Ak2k1r+o5kg3Ofp20z59YWTwesbqkV08gRXDkyaLPUankx+2IMP+T5wiA9qYSGohKpfxGaTXuORr8vAt43eI47+jV+o4y9Rtp1jcH546+6rVYmkACmTfvNCJBOeKeI+k44PtMTavlWjnSVasZHK/FiGO28q//+q8xevRoBAIBNDU14brrrsPHH3+sWeatt97C5ZdfjkAggFGjRmHTpk0J37Njxw5MmjQJgUAA06ZNwwsvvJCvTcgaflPJRjkSFTORqGaGj95wnTDvLMdSaplIqyUekj6hHNlrthqRGn6sqWm10g6OFEURx3K/NBvLKJXcFDfXpnvDS+Y74spRumX8uSbRc2SP9bIC/vDq87hMV3nq1dbzYSNDtraUX8xVy7FyxJV7Uo5sxpe+9CX8/Oc/x7Fjx/CLX/wCH3zwAf7mb/5GfN7V1YX58+djzJgxOHDgAB544AHcc8892Lp1q1hmz549WLx4MZYvX46DBw+ipaUFLS0tOHz4cCE2KWP4UyQ3SZt5GpSVI276UxStHwIYfN6Z1ajVahan1UrkRLYj8rEGqE/BpZpWA9RgvUeacG50zK/80kV4aNEMLJo9Mq3vrUnSJfvE2ZjKfEGWBRNWUSalhzxSy4JigFcYZnN8q/PVtGqrnI6UDdmMMXWuWo6UI327mFJRjhxzlbrlllvE/48ZMwbr1q1DS0sLwuEwvF4vtm3bhlAohCeeeAI+nw9TpkzBoUOHsHnzZqxYsQIA8PDDD2PhwoW49dZbAQAbNmxAa2srHnvsMWzZsqUg25UJ+pPOnHKkdsiWy/j1Tfn0snAyz5FVpDJkm0mrBfPkOSKSo/rbYsdZj0OGzuYS/hAiz8UyOrdqK3y4dlZ6gRGgenf0XbLfP9MDAPhMg3VjULJBPr9ryr22bwaaCXz4dDbHd4JyFEosYlBL+QfQHRwQgVSulCOf7sGZK8LFjiPvHO3t7di2bRvmzp0Lrzd2Udi7dy+uuOIK+HyqmrJgwQIcO3YMHR0dYpl58+ZpvmvBggXYu3dv0t8VDAbR1dWleRUKvTnTTNMvjXJkUMbPSUir5Tg4SmXI5gGdmQ7ZFBwVjsQO2aVtyAbUfcLNtF63Ynqwrwyv+tIrR++d7gYATLBLcCR5jorJbwSo6eJsWlVwQ7Y4Z4z6HEnK0Zl4pVplwJOza7Q+RVgqypGjtvL2229HRUUF6urq8NFHH+FXv/qV+KytrQ0NDdo5SPzfbW1tKZfhnxuxceNGVFdXi9eoUdaOFMgE2athZnQIIDWBHIgalvFzynQneK7TarzSwshk7snGc0RptYIheraQIVsggqO4cmTVDc3IcxQciOBE3J/4mQZ7tJrQKkfF4zcCgIkNlVAU4DON5gNR3jIlsQlk4uDZ4EAUJztiM+py1QASSEyrlco1taBbuW7dOiiKkvJ19OhRsfytt96KgwcP4qWXXoLb7ca3v/1tMJa+mmCG9evXo7OzU7xOnjyZ09+XiiGStGpmdAigPpmEBqJJy/gBbV8NIPfKUcvMC/Do4plYdeWEhM94KiKz8SGl1bDMjoi0GhmyBfzGws201gVHiV2yT5ztQyTKUOn3oDGHN89MkB+6iqnHERBT5/as+zI2/+0M098hK/vhiFpRrBk86/eAZyM/iKdNczU6BEhMq5WKclTQq9TatWuxbNmylMuMGzdO/P+wYcMwbNgwfOYzn8HkyZMxatQovPrqq2hubkZjYyNOnz6t+Vn+78bGRvFfo2X450b4/X74/bk78DJBvqnUm/AbAeqU+uBARChHRuXusiHb41KymrGVDgGvG1+dMcLwM2+KtFp/OIK2zn5cOKxC8z4ZsguPL6HPETdkl4ZnwQh+LPO5WFYpstUGaTU1pTbENt4eWTkqph5HnKbq7IzvstrKCxgA7fXY5VIwxO9Bd/8A3j+d++BIf+0vlWtqQYOj+vp61NfXm/rZaDQ+/iIYK2Nsbm7GHXfcIQzaANDa2oqJEyeitrZWLLNz506sXr1afE9rayuam5uz2Ir8IXs1hlWak6TlwbNB0WfFwHMknYy5Vo0Gw5sirXbL04fw4uE2/Hb15ZjUWCXep1L+wpN0tlqJjg8B1H0ilCOLWmQYDZ99nwdHw+3hNwJ0abUimqtmFWK2WjgiUmoel5IQkFSXeWPB0ZnY3zifaTV/ge8H+cIRd459+/bhsccew6FDh/Dhhx9i165dWLx4McaPHy8Cm29+85vw+XxYvnw53nnnHTz99NN4+OGHsWbNGvE9q1atwm9/+1s89NBDOHr0KO655x68/vrruOmmmwq1aRkhK0dmKtUA7eDZoEirJR4Gclot136jwfCmqFb7Y1xWPnqqW/M+GbILT9LZaqWcVsuV5ygeaHRqlKPYuTHBJn4jQPvQVUxz1axCqxzFy/h97gTlj5uy+fUvV3PVgMQ2L/4SUY4csZXl5eX45S9/iSuvvBITJ07E8uXLMX36dOzevVukvKqrq/HSSy/h+PHjmDVrFtauXYu77rpLlPEDwNy5c/HUU09h69atmDFjBp555hk899xzmDp1aqE2LSOsCI60ylFE856MPZWjxLQa97F8qusMTGm1wiP8E0I54mXJFBxx5ciodYUZagxK+bmqYJcyfkB7XSm2ajUrkEv5eVrNSGmVy/kBYHgOlSP9NZQ8RzZi2rRp2LVr16DLTZ8+HX/4wx9SLrNo0SIsWrTIqlXLK7JXw+yTguharFGOnJtW64lfHNp7g5r3qc9R4ZH9bYwxSTkqDVneCL3nyKobjd5zpK1Us1Fw5CXlKBUBqZS/z6CMn8OVI05DDpUjqlYjbE+ulCOjtFm5z35ptYEo01QnRqMMPSEeHGmVozB5jgqOPFutLxQRc/pKus9RzqrVVM8RYwzHz/aKSrVcDSQ1QzkpRymRlaNeKa2mp0q373KpHCWk1UpEOSqNrSwStMGROTOj6jmKDNIE0iP9f2Gf9OUnFzm11hdWb7h8wCaHDNmFR/ZPcDO2Syn88VRI9Gk1q0v5eYsO2W9kl0o1QOtvLLY+R1Ygp6LPp0qr6ZSj3Jby65Wj0jh/6c7hIOQnbrNpNVk5kseH6Cm3UVpNPjkHompqjafUgETliDxHhccnVav1SJVqdrpZ5xvVkB0v5bcoeK/wueGJd9o+dz6EP562n98IiA3f5SpXLk3EToVXL/aHVc+RsXKk3guG+D059fHRbDXC9shPEGb7HGmq1dIs5TdSlvKJR5J1wwMMiD9w9gTVypxkwZFR4EfkB5EiCEfIjB2Hn3/d3JBt0Zy5WNDhw9meIDp6w5JyZK/gCAAe/JsZaOvqt80wXDshK0e8Wm0wz1EuVSMgMa1WKg+cpX2lchiV8anPZkeHANLsnog8W82gWk0KmKy6gJvFI82ekrtkd0vKUdJqNQqOCoYo5Y9EhX+ivITN2IB6PEbj6WArVdmaci/O9gRx7nwI753hPY7sU8bPmXdxw+ALlSgiFa0xZBtVq6nBUa4VuFKdrUbBkYMYWVuGq6c1oak6YGp0CKBG/SEppz1oWq3AAYaixJqghSJRTVpNDo46z4cRjkTFiUyeo8LD9304wsTfqpTN2EDiU7eV5xYfx/FJdxAf2rBSjRgc0QRyIIK+YHLlSDaz57IBJEAdsgkHoCgKfrTkkqy+Q476uQ/EqOOpnUr5gVhqLRSJp9Xi8PXndPSFMLwygGiUCeN2qZzIdkQOujviyl4pd8cGEoN1K7sNcy/PwY/OxSrVAvaqVCMGx1A5MlBbqwLqeZTvtBp1yCaKEjlY4F16jTtkS9VqBU6rAVKvoySGbED1HcmpN1KOCod8XPG0Z6l7jvRP4VZW7lXHu2S/drwdQEw1KmXzuxPRNIGMF8zI12KOnFYbnuMAuFSVo9LYSkIg37B4qmNQ5cgGAYbRCJFunXLU3pMYHOV6YC6RHI/bBW4X4006S3noLJAYrFvtOQKAo21dAIDP2GhsCJEe/HjoD0dTptWqCphWKxXPUWlsJSHg/h1A7bVipBz5PC5hhLaDjCqUIzmtplOOznLlaEBSjig4Kig8TdDeGzvWSl050p9rVjZY5Z4jbva+yEYDZ4n0MBofMlhaLfeG7NKsViuNrSQ0iMnggwy/5JK/HZr2GabVpFJ+AGjviakTPDjyuhW4XJRWKCT8KZMrR6UeHOVDOeKQcuQ8+MNElKkPr0bKUYXPA3f82ja8MsfKkd4nZ4NMQj4o7StVieLzuICgOrQw2cFe5nOjOzhgG0M2AIQH5OAoieeIGkDaBn5stcdnfpW6IVuforBSOarWdZymSjXnIaesOnp5cJR4zrhcCv7vZWNxsqMP44ZV5HSdvC51nXxuV8n42Er7SlWi8BuWqFZLEhzxJ5ZCz1YD1EBnIKqm1bhnqjLgQXf/gDD9Uhm/feB/A1GtVuqeo4TgyELlSPKhVAU8Oa9iIqxHvha398XOGSPlCADWf2VyXtZJTquVimoEUFqtJEkoJ07SAZtfuO2kHMlmax7cjakrB2CgHJXQiWxXVM9R7G9T8n2O8pRWm0CVao5EUZSEB4pkwVG+cLsU8EOplK6ppbOlhEAfDCVThiY2xmT58fWF9y6ohuzEUv4xQ2OyMilH9kOvUpLnSN8E0krlSE2rkd/IufDqYK6SG6XV8omiKCK1VkrKUWlfqUoUfSlmMuXowUUzsP6qyWiszq3hLx28Bmk1fsMdnUw5Is9RwdEHAyWvHOXUcyQpR1Sp5lj8XjcgVeIWWjkCYqm1UKS0HjhLZ0sJgf4CnaxvhdftskVgBCTpcySUo2RptcJfVEod/ZOmHS70hSSXabVKv0f0lSIztnPRnzO2aMLr4cpR4dclX1BwVILogyE7eIoGQ6TVIsmVo46+ECJRRp4jG6G/mFJaLXcdsl0uBVMvqEal34NpF1Rb9r1EftFfj+1Q4emJp9VK6Zpa+L1O5J0E5cgBBzw/OblyxBgTwdGo2vL4e8C5vpDwHPkprVZwKK2mJZfVagDw8//XjP5wRJNiI5xFgnJkg4dXX1y5d8K9wipKZ0sJgf5p3gkHvM+jTav1h6OIxP1HtRU+MaW6vTdEypGN0B9bpa4cJYxisPgYDXjdqNH1OyKchXxMlHndtmhky9NqpXRNLZ0tJQTplvLbCX1arTveHVtRgHKvG3UVsRvCpxQc2Qr9sVXyypF0TPo8Llvc+Ah7IauJdvHo8VFSpXRNLZ0tJQTyk4lLSZydY0f0aTVexj/E54HLpWBoPDhq7w0hGFHHhxCFxac71uzQULSQyOeeHQY6E/ZDoxzZJDjiD6dOyDJYRelsKSGQb1h+j9sRzeJ4Wm2AB0dxv9GQ+ADGoYbKkT0uLKWMfDGt8HkccazlEp8Nb3yEvZDVVjuYsQE1OCqlayoFRyWIfPIlK+O3G1w5CsXTakI5iqdp6obERiW094Soz5GNkI+vUvcbAVrPkROqRIn8I6urdgmgvWTIJkoBn0bat8fJNxiq5ygW+HTrlKM6kVYLkufIRmiegkt8rhrgzHOPyC92PGdU5ah0rqmls6WEQI7+naIcefVpNZ1ypEmrRSIASuspx67If4NSN2MDWjWz1P1XhDHyNbnMa49zhjxHREmg9Rw54xDwCkN2PK0WV44quXI0JB4c9YTEMqX0lGNXNJ4jCo40RQKUViOMsGO1Gj9uS+maWjpbSgj8OkO2E9Cn1YQhW6ccafockeeo4FBwpEVRFHFcUnBEGKE9Z+xxjKjKkT3WJx/Q3aME0ZQTO0Ta9+hmq/G5apWBWPNHOa0WJM+RbfBRWi0Bvk+ccu4R+UXbBNIe5wyl1YiSQFOt5pAnAZ9bn1aLNYEU1WoVsWq1jr4QggMxzxEFR4VHPr7skiIoNGpwRPuDSMSOabWq+AQCPomgFLBHWErkFUd6jnTKUU+/1nNUWxE7aSNRhrM9IQCUVrMDZMhORKTVHPJgQuQX+Zwpt0labeWXxmPssHJc89kRhV6VvEFXqxJEm1azx8k3GJ5BPEd+jxuVfg+6gwNo6zwPgJQjO+Ajz1ECvPLSLj1sCHuhUVttcn0eWVuOFVeML/Rq5BW6e5QgTlSO+NP2AJ+t1q/tcwQAQ+MVa6c6+2M/45BtK2a0PVsoOALUY9kpbTSI/CIfF+V0zhQMOjtLEEd2yI6n1UJJlCNANWXzwMkpgV8xIx9fQ2ySIig0fAQDpdUII8inZw/o7lGC6GerOYFkpfyVknLEu2Trf4YoHLLvi5SjGGTIJlKhUY4oOCoYdPcoQRzZIVuXVlM7ZKvVE0N1wREZsguPZraaTYZoFhpfXAWlUn7CiIBGOaJzplDQ2VmCOFM50vU5Chp4juLl/BzyHBUe8hwlwo/LMlKOCANIObIHdPcoQfwONGR7pT5HwYGI6IIte470aTUKjgqPHbv9FprPX1iHgNeFaSOrC70qhA3RlPKTclQwaM+XID5HlvKrylFvMCLeNzJkcyg4KjzUITuRVfMm4IYvjqfjkzDEjk0gSxHHnZ3BYBCf/exnoSgKDh06pPnsrbfewuWXX45AIIBRo0Zh06ZNCT+/Y8cOTJo0CYFAANOmTcMLL7yQpzW3D9oO2c44BHySIZv7jcp9brhd6iBPXsqv/xmicNBsNWMoMCKSoVWOKDgqFI47Q2+77TaMGJHYpbOrqwvz58/HmDFjcODAATzwwAO45557sHXrVrHMnj17sHjxYixfvhwHDx5ES0sLWlpacPjw4XxuQsFxYp8jOa3WrRsdwtGn1ZyybcVMuc+DC2rK0FDlR00JjR4gCLPIyhE1Ci0cjnqUe/HFF/HSSy/hF7/4BV588UXNZ9u2bUMoFMITTzwBn8+HKVOm4NChQ9i8eTNWrFgBAHj44YexcOFC3HrrrQCADRs2oLW1FY899hi2bNmS9+0pFNpqNWecfHJarcegASRAaTU74nYp+O3qy8GgdjknCCI5dRU+XPPZEagMeBxTMFOMOOZqdfr0afzd3/0d/vM//xPl5eUJn+/duxdXXHEFfD71BrlgwQIcO3YMHR0dYpl58+Zpfm7BggXYu3dv0t8bDAbR1dWleTkdzfgQhwQQokN2lKk9jhKUI6pWsyOVAS+qAqQaEUQ6KIqCh78xE//UMq3Qq1LSOOLuwRjDsmXLcP3112P27NmGy7S1taGhoUHzHv93W1tbymX450Zs3LgR1dXV4jVq1KhsNsUWKIoijTBwxpOJmK02EFW7Y+uUozKfW5OjJ88RQRAEYYaC3j3WrVsHRVFSvo4ePYpHH30U3d3dWL9+fd7Xcf369ejs7BSvkydP5n0dcgFXj5ziy/FK40PEXDUDg6+cWiPliCAIgjBDQT1Ha9euxbJly1IuM27cOOzatQt79+6F369Nm8yePRtLlizBv//7v6OxsRGnT5/WfM7/3djYKP5rtAz/3Ai/35/we4sBn8cFBJ1Tym+UVpO7Y3PqKnz4c8f52M9QcEQQBEGYoKDBUX19Perr6wdd7pFHHsE//dM/iX9//PHHWLBgAZ5++mnMmTMHANDc3Iw77rgD4XAYXm/sptna2oqJEyeitrZWLLNz506sXr1afFdrayuam5st3CpnMLGxEm981IFRtWWFXpW04Gm1SJSh63ysWq0yMIhyRGk1giAIwgSOqFYbPXq05t9DhgwBAIwfPx4jR44EAHzzm9/Evffei+XLl+P222/H4cOH8fDDD+OHP/yh+LlVq1bhC1/4Ah566CFcffXV2L59O15//XVNuX+p8JPvfA59wQhqdRVedoWn1QCgo8+4lB9QR4h43bG0LEEQBEFkStE8WldXV+Oll17C8ePHMWvWLKxduxZ33XWXKOMHgLlz5+Kpp57C1q1bMWPGDDzzzDN47rnnMHXq1AKueWHwe9yOCYwAtc8RAHT0hgAkGrIBoC7eCJJUI4IgCMIsjlCO9Fx44YVgjCW8P336dPzhD39I+bOLFi3CokWLcrVqRI6Qg6P2vnhwlMKQTX4jgiAIwix0ByEcgdulgGfJzsWDo1SeIwqOCIIgCLPQHYRwDFw9au9N7jmqo+CIIAiCyBK6gxCOgfuIzqVIq01qqoLHpeCi+iF5XTeCIAiieHCk54goTfh8tYFozG9mZMi+oKYMe9Z/GTVlzjGbEwRBEPaCgiPCMXh1FWiVBk0gAWB4ZSAfq0MQBEEUKZRWIxyD16XtW2SkHBEEQRBEtlBwRDgGr85kXeF3xugTgiAIwllQcEQ4Bjmt5vO44PdQcEQQBEFYDwVHhGPwSGm1SoNKNYIgCIKwAgqOCMcg9y4ivxFBEASRKyg4IhyDrBwZ9TgiCIIgCCug4IhwDLLniIIjgiAIIldQcEQ4BjmtZjRXjSAIgiCsgIIjwjFQWo0gCILIBxQcEY5Bk1Yj5YggCILIERQcEY5B6zkyHh1CEARBENlCwRHhGLxuqc8RKUcEQRBEjqDgiHAMVK1GEARB5AMKjgjH4KHgiCAIgsgDFBwRjsFHaTWCIAgiD1BwRDgGD1WrEQRBEHmAgiPCMcieo0qqViMIgiByBAVHhGOQ02qkHBEEQRC5goIjwjGQIZsgCILIBxQcEY5Bk1Yj5YggCILIERQcEY6BN4H0uBT4PXToEgRBELmB7jCEY+DK0ZCAB4qiDLI0QRAEQZiDgiPCMYjgiPxGBEEQRA6h4IhwDJ54Wo2CI4IgCCKXUHBEOAYfKUcEQRBEHqDgiHAMsy+sxbhhFfjqjBGFXhWCIAiiiKFHcMIxjKwtx66//2KhV4MgCIIockg5IgiCIAiCkKDgiCAIgiAIQoKCI4IgCIIgCAkKjgiCIAiCICQoOCIIgiAIgpCg4IggCIIgCEKCgiOCIAiCIAgJxwRHF154IRRF0bzuv/9+zTJvvfUWLr/8cgQCAYwaNQqbNm1K+J4dO3Zg0qRJCAQCmDZtGl544YV8bQJBEARBEA7AMcERAPzjP/4jTp06JV4333yz+Kyrqwvz58/HmDFjcODAATzwwAO45557sHXrVrHMnj17sHjxYixfvhwHDx5ES0sLWlpacPjw4UJsDkEQBEEQNsRRHbIrKyvR2Nho+Nm2bdsQCoXwxBNPwOfzYcqUKTh06BA2b96MFStWAAAefvhhLFy4ELfeeisAYMOGDWhtbcVjjz2GLVu25G07CIIgCIKwL45Sju6//37U1dVh5syZeOCBBzAwMCA+27t3L6644gr4fD7x3oIFC3Ds2DF0dHSIZebNm6f5zgULFmDv3r1Jf2cwGERXV5fmRRAEQRBE8eIY5eh73/seLrnkEgwdOhR79uzB+vXrcerUKWzevBkA0NbWhrFjx2p+pqGhQXxWW1uLtrY28Z68TFtbW9Lfu3HjRtx7770Wbw1BEARBEHaloMrRunXrEkzW+tfRo0cBAGvWrMEXv/hFTJ8+Hddffz0eeughPProowgGgzldx/Xr16Ozs1O8Tp48mdPfRxAEQRBEYSmocrR27VosW7Ys5TLjxo0zfH/OnDkYGBjAiRMnMHHiRDQ2NuL06dOaZfi/uU8p2TLJfEwA4Pf74ff7B9sUgiAIgiCKhIIGR/X19aivrzf1s4cOHYLL5cLw4cMBAM3NzbjjjjsQDofh9XoBAK2trZg4cSJqa2vFMjt37sTq1avF97S2tqK5uTnt38sYAwDyHhEEQRCEg+D3bX4fTwlzAHv27GE//OEP2aFDh9gHH3zAnnzySVZfX8++/e1vi2XOnTvHGhoa2HXXXccOHz7Mtm/fzsrLy9mPf/xjscwrr7zCPB4Pe/DBB9mRI0fY3XffzbxeL3v77bfTXpeTJ08yAPSiF73oRS960cuBr5MnTw56r1cYSyeEKixvvPEGbrzxRhw9ehTBYBBjx47FddddhzVr1mhSXm+99RZWrlyJ/fv3Y9iwYbj55ptx++23a75rx44d+Id/+AecOHECEyZMwKZNm/CVr3wl7XWJRqP4+OOPUVlZCUVRLNtGIBbVjho1CidPnkRVVZWl301ooX2dP2hf5w/a1/mD9nX+sGpfM8bQ3d2NESNGwOVKbbl2RHBUKnR1daG6uhqdnZ10suUY2tf5g/Z1/qB9nT9oX+ePQuxrR/U5IgiCIAiCyDUUHBEEQRAEQUhQcGQj/H4/7r77bmodkAdoX+cP2tf5g/Z1/qB9nT8Ksa/Jc0QQBEEQBCFByhFBEARBEIQEBUcEQRAEQRASFBwRBEEQBEFIUHBEEARBEAQhQcGRTfjRj36ECy+8EIFAAHPmzMFrr71W6FVyPBs3bsTnPvc5VFZWYvjw4WhpacGxY8c0y/T392PlypWoq6vDkCFDcO211yYMJyYy5/7774eiKJo5hrSvreMvf/kLvvWtb6Gurg5lZWWYNm0aXn/9dfE5Ywx33XUXmpqaUFZWhnnz5uH9998v4Bo7k0gkgjvvvBNjx45FWVkZxo8fjw0bNmhmc9G+Ns/vf/97fPWrX8WIESOgKAqee+45zefp7Nv29nYsWbIEVVVVqKmpwfLly9HT05P1ulFwZAOefvpprFmzBnfffTfeeOMNzJgxAwsWLMCZM2cKvWqOZvfu3Vi5ciVeffVVtLa2IhwOY/78+ejt7RXL3HLLLfj1r3+NHTt2YPfu3fj444/x9a9/vYBr7Xz279+PH//4x5g+fbrmfdrX1tDR0YFLL70UXq8XL774It5991089NBDYsA2AGzatAmPPPIItmzZgn379qGiogILFixAf39/AdfcefzgBz/A448/jsceewxHjhzBD37wA2zatAmPPvqoWIb2tXl6e3sxY8YM/OhHPzL8PJ19u2TJErzzzjtobW3F888/j9///vdYsWJF9iuX9sRVImd8/vOfZytXrhT/jkQibMSIEWzjxo0FXKvi48yZMwwA2717N2MsNqzY6/WyHTt2iGWOHDnCALC9e/cWajUdTXd3N5swYQJrbW1lX/jCF9iqVasYY7SvreT2229nl112WdLPo9Eoa2xsZA888IB479y5c8zv97Of/exn+VjFouHqq69m3/3udzXvff3rX2dLlixhjNG+thIA7NlnnxX/TmffvvvuuwwA279/v1jmxRdfZIqisL/85S9ZrQ8pRwUmFArhwIEDmDdvnnjP5XJh3rx52Lt3bwHXrPjo7OwEAAwdOhQAcODAAYTDYc2+nzRpEkaPHk373iQrV67E1VdfrdmnAO1rK/mv//ovzJ49G4sWLcLw4cMxc+ZM/Ou//qv4/Pjx42hra9Ps6+rqasyZM4f2dYbMnTsXO3fuxHvvvQcAePPNN/Hyyy/jqquuAkD7Opeks2/37t2LmpoazJ49Wywzb948uFwu7Nu3L6vf78nqp4msOXv2LCKRCBoaGjTvNzQ04OjRowVaq+IjGo1i9erVuPTSSzF16lQAQFtbG3w+H2pqajTLNjQ0oK2trQBr6Wy2b9+ON954A/v370/4jPa1dfzpT3/C448/jjVr1uD73/8+9u/fj+9973vw+XxYunSp2J9G1xTa15mxbt06dHV1YdKkSXC73YhEIrjvvvuwZMkSAKB9nUPS2bdtbW0YPny45nOPx4OhQ4dmvf8pOCJKgpUrV+Lw4cN4+eWXC70qRcnJkyexatUqtLa2IhAIFHp1ippoNIrZs2fjn//5nwEAM2fOxOHDh7FlyxYsXbq0wGtXXPz85z/Htm3b8NRTT2HKlCk4dOgQVq9ejREjRtC+LnIorVZghg0bBrfbnVC1c/r0aTQ2NhZorYqLm266Cc8//zx+97vfYeTIkeL9xsZGhEIhnDt3TrM87fvMOXDgAM6cOYNLLrkEHo8HHo8Hu3fvxiOPPAKPx4OGhgba1xbR1NSEiy++WPPe5MmT8dFHHwGA2J90TcmeW2+9FevWrcM3vvENTJs2Dddddx1uueUWbNy4EQDt61ySzr5tbGxMKFwaGBhAe3t71vufgqMC4/P5MGvWLOzcuVO8F41GsXPnTjQ3NxdwzZwPYww33XQTnn32WezatQtjx47VfD5r1ix4vV7Nvj927Bg++ugj2vcZcuWVV+Ltt9/GoUOHxGv27NlYsmSJ+H/a19Zw6aWXJrSkeO+99zBmzBgAwNixY9HY2KjZ111dXdi3bx/t6wzp6+uDy6W9TbrdbkSjUQC0r3NJOvu2ubkZ586dw4EDB8Qyu3btQjQaxZw5c7Jbgazs3IQlbN++nfn9fvbTn/6Uvfvuu2zFihWspqaGtbW1FXrVHM0NN9zAqqur2f/+7/+yU6dOiVdfX59Y5vrrr2ejR49mu3btYq+//jprbm5mzc3NBVzr4kGuVmOM9rVVvPbaa8zj8bD77ruPvf/++2zbtm2svLycPfnkk2KZ+++/n9XU1LBf/epX7K233mLXXHMNGzt2LDt//nwB19x5LF26lF1wwQXs+eefZ8ePH2e//OUv2bBhw9htt90mlqF9bZ7u7m528OBBdvDgQQaAbd68mR08eJB9+OGHjLH09u3ChQvZzJkz2b59+9jLL7/MJkyYwBYvXpz1ulFwZBMeffRRNnr0aObz+djnP/959uqrrxZ6lRwPAMPXT37yE7HM+fPn2Y033shqa2tZeXk5+9rXvsZOnTpVuJUuIvTBEe1r6/j1r3/Npk6dyvx+P5s0aRLbunWr5vNoNMruvPNO1tDQwPx+P7vyyivZsWPHCrS2zqWrq4utWrWKjR49mgUCATZu3Dh2xx13sGAwKJahfW2e3/3ud4bX6KVLlzLG0tu3n376KVu8eDEbMmQIq6qqYt/5zndYd3d31uumMCa1+iQIgiAIgihxyHNEEARBEAQhQcERQRAEQRCEBAVHBEEQBEEQEhQcEQRBEARBSFBwRBAEQRAEIUHBEUEQBEEQhAQFRwRBEARBEBIUHBEEURKcOHECiqLg0KFDOfsdy5YtQ0tLS86+nyCI/EDBEUEQjmDZsmVQFCXhtXDhwrR+ftSoUTh16hSmTp2a4zUlCMLpeAq9AgRBEOmycOFC/OQnP9G85/f70/pZt9tNk9IJgkgLUo4IgnAMfr8fjY2NmldtbS0AQFEUPP7447jqqqtQVlaGcePG4ZlnnhE/q0+rdXR0YMmSJaivr0dZWRkmTJigCbzefvttfPnLX0ZZWRnq6uqwYsUK9PT0iM8jkQjWrFmDmpoa1NXV4bbbboN+GlM0GsXGjRsxduxYlJWVYcaMGZp1IgjCnlBwRBBE0XDnnXfi2muvxZtvvoklS5bgG9/4Bo4cOZJ02XfffRcvvvgijhw5gscffxzDhg0DAPT29mLBggWora3F/v37sWPHDvzP//wPbrrpJvHzDz30EH7605/iiSeewMsvv4z29nY8++yzmt+xceNG/Md//Ae2bNmCd955B7fccgu+9a1vYffu3bnbCQRBZE/Wo2sJgiDywNKlS5nb7WYVFRWa13333ccYYwwAu/766zU/M2fOHHbDDTcwxhg7fvw4A8AOHjzIGGPsq1/9KvvOd75j+Lu2bt3KamtrWU9Pj3jvN7/5DXO5XKytrY0xxlhTUxPbtGmT+DwcDrORI0eya665hjHGWH9/PysvL2d79uzRfPfy5cvZ4sWLze8IgiByDnmOCIJwDF/60pfw+OOPa94bOnSo+P/m5mbNZ83NzUmr02644QZce+21eOONNzB//ny0tLRg7ty5AIAjR45gxowZqKioEMtfeumliEajOHbsGAKBAE6dOoU5c+aIzz0eD2bPni1Sa3/84x/R19eHv/qrv9L83lAohJkzZ2a+8QRB5A0KjgiCcAwVFRW46KKLLPmuq666Ch9++CFeeOEFtLa24sorr8TKlSvx4IMPWvL93J/0m9/8BhdccIHms3RN5ARBFAbyHBEEUTS8+uqrCf+ePHly0uXr6+uxdOlSPPnkk/iXf/kXbN26FQAwefJkvPnmm+jt7RXLvvLKK3C5XJg4cSKqq6vR1NSEffv2ic8HBgZw4MAB8e+LL74Yfr8fH330ES666CLNa9SoUVZtMkEQOYCUI4IgHEMwGERbW5vmPY/HI4zUO3bswOzZs3HZZZdh27ZteO211/Bv//Zvht911113YdasWZgyZQqCwSCef/55EUgtWbIEd999N5YuXYp77rkHn3zyCW6++WZcd911aGhoAACsWrUK999/PyZMmIBJkyZh8+bNOHfunPj+yspK/P3f/z1uueUWRKNRXHbZZejs7MQrr7yCqqoqLF26NAd7iCAIK6DgiCAIx/Db3/4WTU1NmvcmTpyIo0ePAgDuvfdebN++HTfeeCOamprws5/9DBdffLHhd/l8Pqxfvx4nTpxAWVkZLr/8cmzfvh0AUF5ejv/+7//GqlWr8LnPfQ7l5eW49tprsXnzZvHza9euxalTp7B06VK4XC5897vfxde+9jV0dnaKZTZs2ID6+nps3LgRf/rTn1BTU4NLLrkE3//+963eNQRBWIjCmK4xB0EQhANRFAXPPvssje8gCCJryHNEEARBEAQhQcERQRAEQRCEBHmOCIIoCsghQBCEVZByRBAEQRAEIUHBEUEQBEEQhAQFRwRBEARBEBIUHBEEQRAEQUhQcEQQBEEQBCFBwRFBEARBEIQEBUcEQRAEQRASFBwRBEEQBEFIUHBEEARBEAQh8f8BjvLEKoa+a1wAAAAASUVORK5CYII=",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -172.2\n",
            "Maximum score: 40.3\n",
            "Minimum score: -473.6\n",
            "Average episode length: 89.2\n"
          ]
        }
      ],
      "source": [
        "# Instantiate lunar lander random agent\n",
        "rand_agent = RandomAgent()\n",
        "\n",
        "# Add to list of agents\n",
        "agents.append(rand_agent)\n",
        "\n",
        "# Iterate over episodes\n",
        "rand_agent.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = rand_agent.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "b1S8c-nTtVWM"
      },
      "source": [
        "[Link to the video of the random agent in the 64<sup>th</sup> episode](videos/random-agent-episode-64.mp4)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "6nWzOXuJtVWM"
      },
      "outputs": [],
      "source": [
        "def plot_comparison(agents):\n",
        "    '''\n",
        "    Plot scores of multiple agent objects\n",
        "    '''\n",
        "    # Initialize plot\n",
        "    plt.figure(1)\n",
        "    plt.ylim([-600,300])\n",
        "\n",
        "    # Plot solution threshold\n",
        "    plt.axhline(y = 200, color = \"r\", linestyle = \"dashed\", label = \"Solution Threshold\")  \n",
        "\n",
        "    # Initialize list of agent names\n",
        "    names = []\n",
        "\n",
        "    # Iterate over agents list\n",
        "    for agent in agents:\n",
        "        # Plot agent's scores\n",
        "        plt.plot(agent.scores, label = agent.name)\n",
        "        names.append(agent.name)\n",
        "\n",
        "    plt.title(\", \".join(names))\n",
        "    plt.xlabel(\"Episode\")\n",
        "    plt.ylabel(\"Score\")\n",
        "    plt.legend()\n",
        "    plt.show();"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "svouIuUPtVWM",
        "outputId": "eaa692b7-876b-42ec-abbb-230d5de7f4c5"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Plot agentless lander and random agent scores over all episodes\n",
        "plot_comparison(agents)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "07Vkx0vTtVWM"
      },
      "source": [
        "As the above graph shows, doing nothing is better than acting randomly in this environment. The agentless lunar lander is relatively more consistent and successful compared to the random agent and also has a slightly higher average score. Obviously, neither learn anything nor come remotely close to consistently reaching the solution threshold, as expected."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "682LCasFtVWM"
      },
      "source": [
        "### Simple Reflex Agent ###\n",
        "\n",
        "Next, we examine the agent which can reflexively fire its side engines in reaction to its current horizontal and angular velocity mediated by pre-selected threshold constants. Choosing ideal threshold constants requires tedious trial and error on the part of the programmer, rather than the agent. Thus, only the programmer is learning in this scenario."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "1tqQ5PhctVWM",
        "outputId": "184de646-28a0-46b9-fb8d-1a1946b2df18"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -118.5\n",
            "Maximum score: -21.0\n",
            "Minimum score: -200.9\n",
            "Average episode length: 69.1\n"
          ]
        }
      ],
      "source": [
        "# Instantiate lunar lander reflex agent\n",
        "rflx_agent = ReflexAgent()\n",
        "\n",
        "# Add to list of agents\n",
        "agents.append(rflx_agent)\n",
        "\n",
        "# Iterate over episodes\n",
        "rflx_agent.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average max, min\n",
        "average, max, min, avg_length = rflx_agent.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "FYHBv_J9tVWN"
      },
      "source": [
        "[Link to the video of the reflex agent in the 64<sup>th</sup> episode](videos/reflex-agent-episode-64.mp4)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "-VljD0TqtVWN",
        "outputId": "1918e035-625d-48af-e704-741d9cc4e17f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Plot comparison of agents\n",
        "plot_comparison(agents)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "qB4J_Jb5tVWN"
      },
      "source": [
        "In the above graph, we can see that the reflex agent is only slightly more consistent and successful than the agentless lunar lander but still not even close to solving the problem. Additionally, it is clearly not learning, as expected. Landing a lunar rover appears to be more difficult than firing the left and right thrusters based on horizontal and angular velocity. It might be possible to achieve a higher score by comparing various algorithms and parameters through trial and error, but this would be a tedious process, so we would like to find a more expedient way to find the best policy to follow."
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "idym3iPetVWN"
      },
      "source": [
        "### Deep Q-Network Agent ###\n",
        "\n",
        "Next, we examine the performance of a remembering, learning deep Q-network agent. We'll start with the following hyperparameters."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "hW65uXBztVWN"
      },
      "outputs": [],
      "source": [
        "# Hyperparameters\n",
        "name = \"DQN Agent 1\"\n",
        "alpha = 0.1             # initial optimizer learning rate\n",
        "epsilon = (0.99,        # epsilon-greedy max (starting value)\n",
        "        0.01,           # epsilon-greedy min (ending value)\n",
        "        0.001)          # exponential decay rate (smaller = slower)\n",
        "gamma = 0.99            # discount rate\n",
        "tau = 0.005             # target network update rate\n",
        "lr_period = 100         # episodes between learning rate decreases\n",
        "lr_decay = 0.1          # learning rate decay\n",
        "batch_size = 128        # replay buffer batch size\n",
        "buffer_size = 1000000   # replay buffer size (no. of transitions)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Let's confirm the neural network architecture and estimated computational requirements."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-OtAzYvltVWN",
        "outputId": "bc157c8c-224f-459a-b62e-697f5fa21540"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Device: cpu\n",
            "Model parameters on CUDA? False\n",
            "DQN(\n",
            "  (fc1): Linear(in_features=8, out_features=128, bias=True)\n",
            "  (fc2): Linear(in_features=128, out_features=128, bias=True)\n",
            "  (fc3): Linear(in_features=128, out_features=4, bias=True)\n",
            ")\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "==========================================================================================\n",
              "Layer (type:depth-idx)                   Output Shape              Param #\n",
              "==========================================================================================\n",
              "DQN                                      [128, 4]                  --\n",
              "├─Linear: 1-1                            [128, 128]                1,152\n",
              "├─Linear: 1-2                            [128, 128]                16,512\n",
              "├─Linear: 1-3                            [128, 4]                  516\n",
              "==========================================================================================\n",
              "Total params: 18,180\n",
              "Trainable params: 18,180\n",
              "Non-trainable params: 0\n",
              "Total mult-adds (M): 2.33\n",
              "==========================================================================================\n",
              "Input size (MB): 0.00\n",
              "Forward/backward pass size (MB): 0.27\n",
              "Params size (MB): 0.07\n",
              "Estimated Total Size (MB): 0.34\n",
              "=========================================================================================="
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Instantiate lunar lander DQN agent\n",
        "dqn_agent1 = DQNAgent(name, alpha, epsilon, gamma, tau, lr_period, lr_decay, batch_size, buffer_size)\n",
        "\n",
        "# View model summary\n",
        "# https://github.com/TylerYep/torchinfo\n",
        "# https://discuss.pytorch.org/t/how-to-check-if-model-is-on-cuda/180/7\n",
        "\n",
        "print(\"Model parameters on CUDA?\",next(dqn_agent1.online_net.parameters()).is_cuda)\n",
        "print(dqn_agent1.online_net)\n",
        "\n",
        "from torchinfo import summary\n",
        "import warnings\n",
        "\n",
        "# Temporarily disable warnings to suppress this\n",
        "# PyTorch warning: UserWarning: TypedStorage is deprecated. \n",
        "# It will be removed in the future and UntypedStorage will \n",
        "# be the only storage class. This should only matter to you \n",
        "# if you are using storages directly.  To access UntypedStorage \n",
        "# directly, use tensor.untyped_storage() instead of tensor.storage()\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# Print TensorFlow-like model summary\n",
        "summary(dqn_agent1.online_net, \n",
        "        input_size = (dqn_agent1.batch_size, dqn_agent1.features_size))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Re-enable warnings\n",
        "warnings.filterwarnings(\"default\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 811
        },
        "id": "4R7Bm5MmtVWO",
        "outputId": "f58e16be-e4ee-4998-91d1-7c2b5d52574d"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: 10.1\n",
            "Maximum score: 273.8\n",
            "Minimum score: -750.3\n",
            "Average episode length: 450.1\n"
          ]
        }
      ],
      "source": [
        "# Train DQN agent\n",
        "\n",
        "# If GPU device is available\n",
        "if torch.cuda.is_available():\n",
        "    episodes = 513\n",
        "    print(\"Device: cuda\")\n",
        "else:\n",
        "    episodes = 344\n",
        "    print(\"Device: cpu\")\n",
        "\n",
        "# Train for specified number of episodes\n",
        "dqn_agent1.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = dqn_agent1.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "5orcJHXytVWO"
      },
      "source": [
        "[Link to the video of the first DQN agent in the 343<sup>rd</sup> episode](videos/dqn-agent-1-episode-343.mp4)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "This agent seemed to be headed in the right direction and even experienced some high scores above the solution threshold, but then it seemed to settle on a policy that resulted scores around 50 points. In the video linked above, we see the agent hovering just above the landing pad accumulating points for being close to the landing.\n",
        "\n",
        "Let's give the agent some more incentive to finish the job and land by decreasing the discount rate $\\gamma$. This should make hovering a less profitable activity."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "IjRuEovVtVWO"
      },
      "outputs": [],
      "source": [
        "# Hyperparameters\n",
        "name = \"DQN Agent 2\"\n",
        "alpha = 0.1             # initial optimizer learning rate\n",
        "epsilon = (0.99,        # epsilon-greedy max (starting value)\n",
        "        0.01,           # epsilon-greedy min (ending value)\n",
        "        0.001)          # exponential decay rate (smaller = slower)\n",
        "gamma = 0.8             # discount rate\n",
        "tau = 0.005             # target network update rate\n",
        "lr_period = 100         # episodes between learning rate decreases\n",
        "lr_decay = 0.1          # learning rate decay\n",
        "batch_size = 128        # replay buffer batch size\n",
        "buffer_size = 1000000   # replay buffer size (no. of transitions)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "tlOHE4HdtVWO"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -28.2\n",
            "Maximum score: 287.7\n",
            "Minimum score: -464.7\n",
            "Average episode length: 486.2\n"
          ]
        }
      ],
      "source": [
        "# Instantiate second lunar lander DQN agent\n",
        "dqn_agent2 = DQNAgent(name, alpha, epsilon, gamma, tau, lr_period, lr_decay, batch_size, buffer_size)\n",
        "\n",
        "# Train for specified number of episodes\n",
        "dqn_agent2.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = dqn_agent2.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "[Link to the video of the second DQN agent in the 343<sup>rd</sup> episode](videos/dqn-agent-2-episode-343.mp4)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "AEMO6SRdtVWP"
      },
      "source": [
        "Even though the average score is lower, there were more experiences above the threshold. In the video linked above, the agent is moving towards the ground, albeit slowly.  \n",
        "\n",
        "Let's try decreasing the discount rate a little more and increasing the $\\alpha$ learning rate decay period. This should give the agent a little more encouragement to land and more time to learn."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "zfVIMEPDtVWP"
      },
      "outputs": [],
      "source": [
        "# Hyperparameters\n",
        "name = \"DQN Agent 3\"\n",
        "alpha = 0.1             # initial optimizer learning rate\n",
        "epsilon = (0.99,        # epsilon-greedy max (starting value)\n",
        "        0.01,           # epsilon-greedy min (ending value)\n",
        "        0.001)          # exponential decay rate (smaller = slower)\n",
        "gamma = 0.75            # discount rate\n",
        "tau = 0.005             # target network update rate\n",
        "lr_period = 200         # episodes between learning rate decreases\n",
        "lr_decay = 0.1          # learning rate decay\n",
        "batch_size = 128        # replay buffer batch size\n",
        "buffer_size = 1000000   # replay buffer size (no. of transitions)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "ITi_JD00tVWP"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -52.9\n",
            "Maximum score: 286.8\n",
            "Minimum score: -460.5\n",
            "Average episode length: 404.4\n"
          ]
        }
      ],
      "source": [
        "# Instantiate lunar lander DQN agent\n",
        "dqn_agent3 = DQNAgent(name, alpha, epsilon, gamma, tau, lr_period, lr_decay, batch_size, buffer_size)\n",
        "\n",
        "# Train for specified number of episodes\n",
        "dqn_agent3.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = dqn_agent3.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "[Link to the video of the third DQN agent in the 216<sup>th</sup> episode](videos/dqn-agent-3-episode-216.mp4)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "[Link to the video of the third DQN agent in the 343<sup>rd</sup> episode](videos/dqn-agent-3-episode-343.mp4)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "UnuBEqPZtVWP"
      },
      "source": [
        "The average score was lower this time. The agent is experiencing more high scores, but perhaps because the state space is so large, it is having difficulty transfering the optimal actions for those transitions to other transitions in the environment. Looking at the videos, in the Episode 216 video, the agent lands, but in the 343rd episode, it is just hovering near the top center.\n",
        "\n",
        "Let's try decreasing the discount rate more, decreasing the greedy-epsilon decay rate to encourage more exploration, increasing the target network update rate, and increasing the buffer and batch sizes to try to remember more optimal actions."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "7IT-fpSStVWP"
      },
      "outputs": [],
      "source": [
        "# Hyperparameters\n",
        "name = \"DQN Agent 4\"\n",
        "alpha = 0.1             # initial optimizer learning rate\n",
        "epsilon = (0.99,        # epsilon-greedy max (starting value)\n",
        "        0.01,           # epsilon-greedy min (ending value)\n",
        "        0.0001)         # exponential decay rate (smaller = slower)\n",
        "gamma = 0.7             # discount rate\n",
        "tau = 0.01              # target network update rate\n",
        "lr_period = 200         # episodes between learning rate decreases\n",
        "lr_decay = 0.1          # learning rate decay\n",
        "batch_size = 256        # replay buffer batch size\n",
        "buffer_size = 10000000  # replay buffer size (no. of transitions)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "VOvuDvlltVWP"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -28.9\n",
            "Maximum score: 282.6\n",
            "Minimum score: -354.2\n",
            "Average episode length: 348.9\n"
          ]
        }
      ],
      "source": [
        "# Instantiate lunar lander DQN agent\n",
        "dqn_agent4 = DQNAgent(name, alpha, epsilon, gamma, tau, lr_period, lr_decay, batch_size, buffer_size)\n",
        "\n",
        "# Train for specified number of episodes\n",
        "dqn_agent4.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = dqn_agent4.score_stats(verbose = True)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "[Link to the video of the fourth DQN agent in the 343<sup>rd</sup> episode](videos/dqn-agent-4-episode-343.mp4)"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Things are looking up. The average score is higher than Agent 3's. There also seems to be an overall trend upward. The average episode length has decreased as well, which suggests there may be less hovering and more landing. Supporting this hypothesis, the lander in the video clip lands in the landing pad, a little roughly, but both of the legs are intact and on the ground.\n",
        "\n",
        "Let's give the agent more memory by increasing the batch and replay buffer size again. We'll also train for longer to give the agent more time to master the task."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Hyperparameters\n",
        "name = \"DQN Agent 5\"\n",
        "alpha = 0.1             # initial optimizer learning rate\n",
        "epsilon = (0.99,        # epsilon-greedy max (starting value)\n",
        "        0.01,           # epsilon-greedy min (ending value)\n",
        "        0.0001)         # exponential decay rate (smaller = slower)\n",
        "gamma = 0.7             # discount rate\n",
        "tau = 0.01              # target network update rate\n",
        "lr_period = 200         # episodes between learning rate decreases\n",
        "lr_decay = 0.1          # learning rate decay\n",
        "batch_size = 512        # replay buffer batch size\n",
        "buffer_size = 100000000 # replay buffer size (no. of transitions)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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UjBgxAs3NzZgyZQpmzJiBjz76CMXFxbjiiitw0003obS0FEVFRbjuuuswceJEHH744QCAk046CePGjcMll1yCe++9F5WVlfjDH/6Aa665BtnZ2b18dQECBAgQIECAvoJdRjmqrq7GpZdeiu3bt6O4uBgTJkzARx99hBNPPBEA8MADDyAUCuG8885DLBbDySefjH/961/2+eFwGO+99x6uvvpqTJw4Efn5+fjxj3+MO++8s7cuKUCAAAECBAjQB7FL5znqDQR5jgIECBAgQIBdD9/5PEcBAgQIEECO9s4kgjlvgABdQ6AcBQgQIMB3BCu2N2HsrVNxyxtLe1uUAAF2aQTKUYAA3zEQQmCaAXPwv4h/froWAPDy/CDlSIAAXUGgHAUI8B2CaRKc86/ZOOOfXwQK0v8gzMCcFiBAtyBQjgIEyBBJk6A1luhtMThsrmvD4i0N+LaiCc0dPS8bIfw96IgncfcHKzB/Y12Ptx3AjUA36luYvW4H/vbRKiSSZm+LEiBNBMpRgAAZ4qxHvsA+t32EutbO3hbFxoYdrc6G0fPt/f6tZdjnto+wYFM9AODxmevx+Kz1+P5jc3q+8QAuEATaUV/Cj56ci39+tjYwc+6CCJSjAAEyxLJt1iLEn6+p6WVJHHDK0U4YJ6fM3QwAeGj6GgDA+h0t0nIvfLUJL8zZ2PMC/Y8jYI76JjbXtfW2CAHSxC6TBDJAgL6KvGjf+Yw21jrKUW+wCDKyqjWWwB/fWgYAOGO/ISjJi+5cof6HEOhGAQJ0DwLmKECADNCZcHwI8qPhXpTEwdb6Nvx7ziZ7u6+wCG2dSft3Sx/z0fquQeeZB/4vAQL4I1COAgTIAG2dziCf20eUo76Q28Yw3NxRRzxQjnYW/JI/LtnSgLG3TsVjM9d1W5tJk+Dh6Wswb0PghB/gu4NAOQoQQAOmSfDagq1YX2P51LQybEg4tBM8n1MyeKGxPc5t9xHiiGOOdkYE3f8y/J75799ainiS4K8fruy2Nl9bsAV//3g1Lng8cML3AyEEq6uaEU+xd0/OWo+fPv+1vR2g7yBQjgIE0MDrC7fiV68uwfF/nwkAaGMYkJ1hvnp78Tbsd8c0fLl2h7KMKEdfWUKCZdmaO+IeJQN0Fb3xzNezQQASfLFmBzbXBg7JAPDqgq046YFZuPLfXwMA/vLBCnyyogofLN3ey5IFEBEoRwECaGDh5gZumzUP7Yzh6IaXF6M5lsCPn5mnLCM6YPcN1cha64siYI56Fn3lmVMs2FSPi5+ei2Pu+2ynt714SwPq+1CaDQB45osNAIDPVvERriy7GqBvIFCOAvR5/GfeZpz9yJfY0RLrbVFssJ3Zzpyte7XkZo56VBRtsPeqKVCOehR95ZlTLNpc36Xz2zoT+NtHq7BsW2Na581euwNnP/Iljr535ytlMuwcw3uA7kSgHAXo87jljaVYvKUBD3y8urdFsdG6k5kjCq/lIfrCwCgbBNriLHO0c81qHfFk2v4cO1piWLG9qYck6ln0gVeAg8xBXxdJk+BvH63GPz9bi9Mf/iKtc6evrAbQ9wIA+sI3GkAPfSdBS4AAPmiP9x3qmWeOdl67Xm2Jh/pKtuSOXjKrdcSTGH/bR+hfEMXc303WPu/gP38CAPj4l8dgzKDCnhKvR+DHYhq7CIcRSyRx0gOzsOk75qvUV77JAP4ImKMAuwz6Usfe2skO8n2jw3MNjDtRLC+CoLccstfVtCBhElQ1ZWaO/XpT10xCvYF0FfX1NS2YubprGd69vstMv9ilWxu/U4pR3+ghAqSDQDkKsMugCwx9t6N1J0erZYKdKZZ9DyTPiDer7TzmKMS8MH5pENLF7e98i79PW9WtdXYH0mUmjv/7TPz4mXld9g1SIdNvtiDnu2nU6O6+ghArLcN/vw7WbutuBMpRgF0GfUg3Qmus75j4KPqqQ3ZvRauxylGyG2/G5to2PDd7Ix7+dC2S3ax0dRWZXuayir7lYxUN962haXNtG+Zv7HtJLhdsqsdjM9fhN6990631bm9sx5b/8fXg+tYbGCCAB0LdQB11V7I11lTUV4ZHXdbg7cXb8Nmq6h6RQWZi4ZNA7jyzGpubMxMlRvW2xRJ9TzGm8FOOlJ9QX9GkU+hb0gDH3PcZvv/YHDsJbKbo7utqaOv+7ylpEky8+1Mcfe9nHEP+v4ZAOQqwy6CrulFFQzv2ufUj3JzBLEtsu7WXHLK94HY5cgu2raEdN7y8GJc/O38nScU70u9M5oh9Zl5RfumCramvJNqk8FOQd7a4mX6yXb2v3XmdrGK9qYtsSl97X2RgJ5B9KX3KzkagHAXYZeBSUGIJfLayWnsm/+yXG9CZNPFKN9jn+QzZfaPDc0WrScSqa9m5SfF2tMQwY6XDUu1c5YjxOerGR8Te177x5B1k+ip25Tp6whfQ6zpqmmM9nnF7S10bLn5qLmatrkEtoyD0z4/2aLvpoq+9f98lBMpRgF0IfC989UsLcflz83H3B3rrRHWnDsMxR91XbZcgKmkyuXraqV2s/5x/fYmKxg57e2fmneF8jnrIN6iP6MU2ZPK0dybtAX5nBzVkmufI63Ed8pdPcMx9n3FKS3fjV68uwRdrd+DSZ+ahssl5f7vDtN/X0dfe6d5CoBwF2GUg9kuzUiHI/5m3uefbFrZ7Klot0QWfKDdz5Gdi6flecEtdO7fdsRNzVbE+R6potdqWGI7/+ww88tla7XpZ01Vfy1sjk+fQuz7BQX/+BDXNamWip16FTHUJ8TryomFXmXU13mu6dQXVzL1iU0H0JcVhyZaGHlmTra+9072FQDkKsMsgpOhoe2Myxw7y3dWZPD97I8bf/hHmbdCPikkkTcxaXWM5OqcpRk909H6PIpYwM1bKttS1peUMzTqHq6LVHpu5DutrWnHfR+6wfJ33qjcGy3U1LUoGTiYPNWUu8MjbpPtM6lo78e85G9HQ1rPmWVOYI+Rn79zQfvZ+VDHMUVe/9e58Xc565Eu8uWhbN9ZoobcCMH/5ymKc/vDnaOoji1MHylGAXQaqZHO6ySG785vnOpBuqvi2d75FR9zEza/rO4w/OmMdLn1mHi55ep6Wz1FPOSmng1gifXZs7vpaHH3vZzj7kdnKMo3tcTw/e6PNkLADmYo5iifTvwey21bR0I4pczf3ODP2zdYGnPD3mThWsWaY19WoJhfp4NopC3Hr29/imikLtcpn2qT4bhakqRx1pxLDKUcZVmvfh12AlOlORnnBpjqc/MAszF67w7fsm4u2Ydm2Jtw/rW8sExUoRwF2GfQlc38P6EY28rPdJgQVXl2wFYC1ArlOp8Yqkt05Q0zn2WSiHL2+0LpOrzXPfvPaEtz2zre49Jl5APiBTMUcZfJOcQ7Zqd+nPfQ5fvfm0h5f/2/at1UAgFrFavNe70DIUE8jdF+F2etqAQBfrq3VO6GbPlqZWa0nzcJs1Txz1DPoQ11bt/YLFz7+FVZVNeNHT83VPue52Rv7RJBLoBwF2GWg6kB0+99u/d6Yyrr7O05nlsz7vwjHfJij7vQtUN2DoSW5rn2xHmJXPkopDlSBYkVSOWR3dUkaeg/rU/lmuroUR1fhyRyF0hvcq5o68NV6TSWomyEyR+EU7bWzBk3226jkfI56x6y2pa5t55mbutOHMkNNqy8kVw2UowC7DFSRL90162psi+PaKQvx2Ur/BIk8c9S9H3JBdlZG5+nkOeKUo9ThqcsqccHjc1DR0O4q31XIFL1MmKNMlBh2IBN9WCgyMTVxCmnv9+EcvMYUr3sou47D7pqOHzzxVa8oSKps7zvrfrPvS2O7o5T0xuOuaGjH0fd+hiPv/nSntNcVc/uSLQ2YuqyyyzL0hc8qUI4C7DLoKkPvp8T8bdoqvPfNdlz+nH+CRJlpxQtVTR341atLsHRro2/ZwjTWleJz7qTXpdBzr3pxAeZtqMOtby9L63wZxGdEZfrLOePRL89S+jLxy8nI/MX8zsSspqOQ9YVOnIPXy2hkNpHwU4686uwunyP6HukuA9OdShSRsMQLNtVj0t9m4NOVVRnXpYslWxoAAM2xhOcagd3FqnVFOTrrkS9x1YsLsLJSbv5+c9FW/HvOxh6VobsQKEcBdhmocoxkmktFBJvPxA/pKiL/998leG3BVpzxzy+kx9lOLx3liJNJMdtmwfsc8QXqe2ApAtrE6AH5yI5YfiMd8e5ZwkW3bcDDrJbBu8Mrxr3fibNgpXnuyw1cVJlXjh6vq2DfmWgkvSEj81B+HpTJYd/Z7vrufWXhhLE2bnh5ETbsaMVPnvu6x9sfUJht/97R2vPpGDhWPMM6N+5wJ+kkhOCXryzBrW9/68tS94XP6ru59HGA7yS62hV272yS+a1RflVVs+fxVmattoyZI5dZzY2dHa1GWzBgICfLGlgzWZsss3GQMat1o0O2vIUMzyekWwd59jJvf3c5Plvl+EBl2gorXnY4hM4MzKKWbPrXqkpourMGTY4tkphRd2YmcvaOVTR0oKwwp9vqlsHkrr37wE5Q2LUp/WToLQTMUYBdBj2e3Zn5PXXZdk/zT3ezB03MshpZ3bQiuW8SSGE7ndu7ZEsDTnpgpmu/aIqiMhgG+iZzlMZVP/vlBky8ezo27HCSD3bl0S/cXI9D75qOtxd3X64akdFkHcS7I7tz2swRc3+97pVpEiyvaLKfk5sFtXbsrEGTbYX1P6L7WTYnrXozEJ99d7d7MC7ddW/YajKv030eaxL1exf7gD92oBwF2HWgNKv1QFtXvbgQt739rdOGy5dG/pvFtxWNtr+GXx/TxDh9ZtoxiMrQ8X+fib9+yC+twl4G6YKOcvFTc7G6yn+Fcoc5QpeYo0yesk60WjoO2Xe8uxzbGztwx7vL5Y2kiZ+/sAA1zTHc8PLizCsR4OlyZEA5wyCEKJVp9h7JFHdPvy1NpvK+aavwvYc+x5/fX54qK8oH6f6egooZpvsHFjhrrF33n0U9mhSTVSq2eShH3WZWS9OfUheskin25S6mMGCOAgRIA8pY/m6qXqjHa4Faouo9GZz20Bf4wRNfobLR35eJVY4y7RhkZ4mRd91lVmtWZGh2DZSE7je6xBx1NR+RrlmNu/eKNhNML9+VSEXdpWLSeR88o9U87mFTexxH3/sZrv/PIvzpveVYV9PCnOecmJ2V+ZDhJdujM9YBAJ79cmOqLF/YlDBHPZrnCPJ26O8BBQ5z9O6SCjw3e2Pa9fL71WCViooGdV/SXcxR99xj98vGfjdhYVYivht9gTkKfI4C7DJQZ8jWg9+HnmnOG78B0prteZdhzWoZ+zNIzvOSzauZbQ3t+N0bS/GTo0bj2D0H+ratGngJczy7S8xR+mCvXc0ceXfS0nq7aWat43/z6tdbcN9Hq/DMZYdg/NBiDdnUAnm9328s2oat9e3YWm8xE6ypL540cekz83DIyH6IpmnyZVtMZ/BW+c91he1MB6pnTH8W5fLpNnpyMGeZIy9H5u7SFdnnlPl1uU9klTzPSYlkuzcQMEcBdhns7BXlvZDuAJmeWS1T5kjSIXn5eXi089vXv8HM1TX4cSrbdKawfY4A5GR1gTnKoG22M1YyR8J2up2yy28rjZdIp+SMVTWobo5h/sa6VHuZDxpeotFnQ7GjxTETTV1WiVmra/D3j1d3mz+cn2zic5AxRz0J3mzOMiny8sMkyU6l9SrOv+WNpbh/mnt9P4CPZK1p8YhW6yb36a6kB/ECyxyJ30lfZI4C5SjALgN1huzuWVstLeUozUSAfkXY7LeZ+xy597nyxWg6W27XMAXK6lX5ZlkO2b3HHKnuqVcnrfM6qJSp2pYYTn5gFh75bK1GLWqoHJTV8qiPeTnBekVIsoEJ6Tpks/B630RGylXS9jki6jLdCDVzlFLShBdKV4nwej5Pfr5Bup9lPb0yTmfSb8STJh75bC0Wp3IpAUIf0Y1MnVeOKvH+BdFqAQKkAXWeo50rRyJpph3K78dINGboc0T8BguvqjyOdRet7VRjdIk5yiTSSi/PkXCOxtP0vecA/vrhSqyqasZ9H8nZAFnbMtABRfdpeMnv1Z7ukjVdyXPkNXiL9bqTQLrr8HpFu/7+soq1+2MXr0XTfcwTqneUVSq6OwnkS19twn0frcLZj3zptKFIY9BVcFF/HpM22XZvIFCOAuwy6HJOGp8PTtfnaI/ff4g11Y7DKvuh17d24q1F23zzeIhgFQaZmDrXrsUcccc86vJvTgEhCiVVU1eZo64+e9Wg4o6a8a9Lx6S6cHO9hlT+F2XazFHXmQmvyLyIx0HOIZtRYnTWv/JKOsoiW1COxKL0XJlzdE9AGa0myEOhm7nbC6r7Y2oyR1vr2/H7N5dyzvR+WCWJOOWutxtvMRfI4KMM9QWfo8AhO8Aug64Eq5km8e/AuiGb72XPzceSLQ248ODhTrWGv7LBRi7JBvKQYUjlV6s+qbo8OiFPZ+1umpXb5jZ0zecoE3DMkabPkQ6drzOzXlfTKt3PtZ0Gc+SHl+dtRlVTzFN+w1Cr/16tsOewPkexRBJ50Yj2pMLLmVo0q6nMwez73JN+KUSxQeUQv4FkN1BHqmenyxxd8dx8VDR24MNllVj4xxO7RY7uNG95mejc0Ynd1mzGCJSjAH0afGh1ZsuHEEJwxj+/wLcV8vV+uhN0HaQ3FznRPoT4z8DYGaGsYwgZgB/fohOtpuOHYx1TH0xHuXF8kYyuMUdpn6EZrRbKgDlSblhgFV0xZJmFzjXp+hz99o2lvnV51SHenpyskPQ5s0pMR9xEXpQ/7sqCrZk6gjWrrdje5F4+ROKQ3R1sjQpEoSDYPkeiWc1HlGe+3IDy4hzPiQWt87NV1fjrByvxt+/vh32HFQs+R+pvryLlJ1jX2rWcS5lGY7LXdtWLC/HTo0Zzx9nnpYpGpAh8jtLA3XffjUMOOQSFhYUoKyvD2WefjVWreHt+R0cHrrnmGvTv3x8FBQU477zzUFXFLwy4efNmnHbaacjLy0NZWRl+/etfI5FIzwQSYOeB7YRU44zfINPUntBSjDK13Mi+Y7ET82Nbkqa8M6ZQzc79fJ/EvpR3tsyMOWKdx3XR28yRbmers3aXn1Mwm6hvZGmesi0d5sg2J3WL74fX8+aP5UWZebNCTlkG+UwVblY5OvXBzzGLyextyWf99ftOugsyUxorh8uB2IfqiCcJ7nh3OVpibMoOCRNMCC5/dj5WVTXbC2B3T2i9PlSKoR9E2Z76YgO3nfTID6bKa9Wb2GWUo5kzZ+Kaa67BV199hY8//hjxeBwnnXQSWlsd+vqXv/wl3n33Xbz66quYOXMmKioqcO6559rHk8kkTjvtNHR2dmL27Nl4/vnn8dxzz+HWW2/tjUsKoAG2M8w0D5EuvBgo77a9zVlaZjXOHi9RjrR8juSdLb/tXw/gPRizzuO6MnXd56irGbJV9arPUdbrMbM2YA2EOtB5n9ONVvOCN3PEH8wVQvtl5WTKkesd1DSD0QShFB8s3Q7AeT60Xv7e9yRz5PyWmZnczJGeLJ1Jtd8NwPd3zalJCPvu6vh5dRWZmi79J4BsWfFc7+3ewC5jVps6dSq3/dxzz6GsrAwLFizAMcccg8bGRjz99NOYMmUKjj/+eADAs88+i7Fjx+Krr77C4YcfjmnTpmH58uX45JNPMGjQIOy///7405/+hJtvvhm33347otGorGk5WluBsKQDCYeBnBy+nAqhEJCbm1nZtjb1G2QYQF5eZmXb272Nw/n5mZXt6ACSHoOioqzJDKRGvNO6R3l53KhmgKjvXV6efOYrKW/I7hEtl1ArBCSe8H52SZMfdSVlEzEmWo3+iMeBTosi51gzen42v76TUjlqbbXKRiK8Wa21Dchme8KkVTYa5R+rIG9jnZuFMwwAySQM9j61tjrKUUcHckLW71jctJ5vh0e6gKwsgH6Ppsnff/H+sWXZttsdBifZ3m6dF4k4940QhOKCvKzix7apcAQmba1AhH+vuZm3abrlTfURhuyZCqDvv11jp8d98AFpb4eh+F6JoLDmReRhZuwbFmtuBfIMIO6YcczWVqCo0Cnf6RyLN7cAIYGlT333YrRaTthqP2wYSBBnaRNOUWnvUN4D7lOIxQAv6wDbn6TKcs/YdP92+Rx1xNyy5LpzH7EME5HI7lJGWlthMt9JMpm0vh3Z2COcB8D+7gFw/YkN9h1PJFx9BNrbgVbJuBiNWt8dPS8Wg+njd8VNANvaAObyiTDhIgTp9xHt6gSZ0j7CB7sMcySisbERAFBaWgoAWLBgAeLxOCZPnmyX2XvvvTFixAjMmTMHADBnzhzsu+++GDRokF3m5JNPRlNTE7799lvIEIvF0NTUxP0DAAwZAhQUuP+ddx5fQVmZvFxBAXDqqXzZUaPUZY85hi87bpy67CGH8GUPOURddtw4vuwxx6jLjhrFlz31VHXZsjK+7HnnqcsWFPBlL7nE3k8GOPUYf/qTtb+tjS9fXa2ud8cOSCErK9bLlnviCXk9AMgbb2DxmANRO3CIvIBg/pW1nXhpin3YHgCeeMI+HmppcZ//0Ue8HHX1rqbNbRVW2TfftMqwutB++/H3fs4ca/ull/jOX5C16Yxz5Nf5+efA089w55Ftlu+VcdRRyJ7xGYAUc7Rwoff7cNddTj0rVgD/elR9/37/e7csBQUgkyY513rRxVbZm25yyuzYAeMPf7A3SUEBzOEjnOPPPuf8Zt4Nk1FQyF57u95fbua9br2yj+B0dsV9MJdZ/ZJtznnkEdc5RPx+FCAnnQwyX57Uk3z9NbdtrFjh/F6/3inHMkdHpfqKe+91jo/Zk6/3H/+wfx/x0Ff499EXSvsI0SE7e7X1zYQ6raSH9D3ilKMLLlS/P+yg//Ofu45XDxqGC3/2MN455Ht8H3HTTdY9bWhwrmHTJud4tbUcj6hjmnfc6ZaBuYd2OfbdKS52HyeCYlJQgOQ119q7klu3Wd+ZH2R9xEsvuWV8hvleU30Elzx18ony+/vSS0iaBO8sqcC2tz+y3tXS/p4icaH8++/P1UfY747eh3T7CK+ysj7CB7sMc8TCNE3ceOONOPLIIzF+/HgAQGVlJaLRKEpKSriygwYNQmVlpV2GVYzocXpMhrvvvht33HFHN19BAF2YIkPUg/AychgeTc8zC/HcpfcjbKqZMV+zWsiZCUodspVrMjEzUYnpyfQwR3nJ5HWsKTvf46hYj20XQY5h9Y6Wz1G6y1Ck/+wJ80SThry9EDvYGiHpPRTB3lMieWu4AbyLOQio3N7LwHQ9Caop1BEPO0MDe+/Zd7Mj4l6ZXrx/4vXfetLVuHTR+67zXMxRwlKKQqkQNyofp3gqnqkO7jn2MswdsS/mjtgXZ8oKsM+Ye96ptgXmiP1+vWAq6rX3yUxtzHUmDL12ugLd9/eV+VvwuzetQICNgK/tn3PI9nlP+oLP0S6pHF1zzTVYtmwZvvjiix5v65ZbbsFNzGyzqakJw4cPByoqgKIi9wki3Vld7S5DERI+7o0b9csuX+5tKmMxf75+2Vmz9NOifvihftnXX/c2q7F44QXguecAAGYsAdxrPWfjttuAo57hzYCANQNtUeT2yMsD2hPu/ZLyxrurATTKy324Gvi6QtrErJLRQG0bkqoOcq+9QGbP92w78eoyYKU1g7Vn51deCVx2mSXbfV8AdP01en52NrBkhl0HKS4GYoKJZ9Agq3zKlMQxR4sWAQPygT9ZdRgTjwAeb7HMavfNVMqbWLIdeIdnwwgBcPTRMGqKgQUV9nnkgdlASyeM2V8iuykOvPKNxRwdeLD6mQEOZQ8AY8cCv/gFMG+bVB6uLCvzlkbguUXWtT77HLDvIMfEAAADBsC4+y7gY2vRU7OhAWZHArh/tnX88sucssw7ZzLPmaxYAZTk2PfQvhf098iRbnlTfQTnR6W4F+bTC4CKZqfOa64BvtzMnWOaJvCXWdLzWZCPPoIxfT2wzW0WJQceCGx23v3O0bsBjZaCYuyxO1BjMWfsoBV79z1gj/7AZ+uBLyyZyMqVfL3XXQ+8LzCnkmsVlaPsQw8BtjQikp8PdCZBBg+26mMH2ClTgLGKdf8+dpyByWOPwWAZNwCNLy8F1tRaGwMGOAfuvx+4916Qez4HOlMmzWHDgaYUgzVwYOo+8M2Zv70FmCSwy7m5SKkNTjn23amvB+7inxurQBi5uUBLC8z524Cpa6zzy8qAo4/297di+wiKiy4Cvv99vtz7q4CFln8XznEzwuSjj4CRJe76o1F8+V8mQrKlBWZnErhHzWpxDtkLF1p9D91u7XS+O6Tu74EHptdH6JbVxC6nHF177bV47733MGvWLAwbNszeX15ejs7OTjQ0NHDsUVVVFcrLy+0y8+bxtDKNZqNlRGRnZyM72z1DQn4+7yejgk6ZTMqKCkJ3lZXYybulLOuHlUZZ03Bo6FB2tvQeGaGQ572Tzrpl9chmPrSc18flxw6I61FJ2mZnnna/l5Vlt8uFnCuvVTIThcGV5+5Fbi5fV9i5j1zfK7RHopLvAbAGfVb5yM+3Z4hGbh5y4pb/QEfctMrqvu+hEIwsxl9A87sjOc46VMlo1H2eYcBgvu1kbh6I4SjShGFPVM+Y5OYC+fz3xUezGV3qJ5Jiu+x7SJ+VZo4dkp3jfhfpMWHylWCev8Ec45ijsHVPDcaXw8zl7wWRfTeSa3UxRzn8e+8wNk4ZMyrvDyyhGRmi2TDEUNeI4tlmZwPZ2UK0mpspFPuUZCSSXv8NgEj6ZY4xMQDk5yPJ3MOESYBwmPODkkImC9Of2Igw26l7wjFHij5X1p4ZkUxCGXCvqdD3mCY/sSSEpN1HpHv/favs1tp6EIQQXHvttXjzzTfx6aefYvRoPofCQQcdhKysLEyfPt3et2rVKmzevBkTJ04EAEycOBFLly5FNcPmfPzxxygqKsI40fcmQJ8AH1otL+NnVOjpAA+/6g2NMv6h/Iq2WZZCctx7bTW1PJ73zOMY+4wIIUyeIyfnj1eWX1dTTLRbumBbUS4fwrUlMBMZvje691grCaRJ61RXpGuCSCfpZ2dC4bjNMkeSqEOxBd2IsmxBaaPJJuk7Q6vJJM+RrJTfvWfPkaVuEJvOJOeS7BRZoky+b3DL54dFm+tR3aS/ViL3zno1JNxDv/fQK0O22E7vG9V2IebommuuwZQpU/D222+jsLDQ9hEqLi5Gbm4uiouLccUVV+Cmm25CaWkpioqKcN1112HixIk4/PDDAQAnnXQSxo0bh0suuQT33nsvKisr8Yc//AHXXHONnB0K0OvglKMM69DtoHuqfgL/gTbOZsiW+RwxvXkiaSKeJMiNSmZbAlwZsrljXoOll4+L5qBEnBYNw7kGWnd7Z9J1DSzu/mAF3l1SgfeuP1qrPXn7FlTXyhIKSUL4tbu01lmT7FOty5UBnOVD0pNBXlA8zz3oR0IGEibhlCP23ePMapJ8VV7L1XhBtWYbVY5kSSA931Hh2YeFrzudb53TFQQ5ssIG4knim+dIF7L3hd1HFQzdPu2brQ0451+WuWrjX0/TOofPc+RVUDzPu17OIVs8Jpop+4DP0S7DHD366KNobGzEcccdh8GDB9v/XnnlFbvMAw88gNNPPx3nnXcejjnmGJSXl+ONN96wj4fDYbz33nsIh8OYOHEiLr74Ylx66aW48847e+OSAmhAp8/xmwX2NnNEiP9A68scMRd5wv0zMfbWqWiJJZTJ6py29dkC7piHrLr9lskyRzBsRYQQ4J+frsHYW6di+ooq5fmPz1qPisYOPPvlhswyZLMsgzLPET/wcw7uGtcpe666eWLSWT7EizHQZ47cTJlYR798y0QWUzBH7ABHmSNVnbJtFcRM5fR7sBVqD5n9ICvmyxwRxW+7betvJGVyzGT1EJlcsmti66b3X7dLm7u+Lm25zAzuMeCvsHlnyOZ36Lqy9iR2GeZIR1POycnBI488gkcE5zsWI0eOxAcffNCdogXoQfhlIwb8k+lpZxfusRyT/u0nkuqOA+AZjk21lnPs4s0NfCsyFsODLfDq+DxZJeUR/lkQpqxhOIqISQj+Nm01AOB3by7F3LGD4IVMZ5HsWSqzB3tfTZNoKzZ2G74DnLoSnSSQNnOUhklMtxyRHKMh9SrTp1+2ZrGfzlSBocqRl1lNdwBNJ+O8LQ+nJLu/TVpnJGwAcd7ZWBeyZypTIGSmxJ4kVmSMog68vpeQwd8jv7XUAuYoQAAfmJLOIl3ontdTGbhN4i+DX4ZscfV4wOpc+VmtNyVvlWF+ezFHHsfkzJa8nO0zBEcRSbfjIyRDnyNu9q9ok2OOwCfp0zGr+bTbXcxRus9DB7IV7lXmLaecd7uZMkfinRSZI1lmam8F3rvhtJgjiZz0flHfqG7zOZLsY1nlpGl9U92znIxCLuZ3dzFHhmH4ZMgW7nLv60aBchSgb0PHBySdjs4Lmaak8be1+3dlOgvP+rVrm7BYp2iPczIdcL3O4x2y5cxRuh0fQabLh/CDiryQuowecyRTEPTYOZ0rspcP8SijazZ2L0Ls/p0V1s9VI7unmfocuZgjwjNHtKJMJksZmdW4891t0r+RlHwZmdUk++RmNfd72ZN9GjdBSEMB9ZwIwHttNT8zW28gUI4C9GnwH6q8jH+0mt6Hlilv5Fc/sf9TgzWr+fkccfVKtlUOtOJZnnJndshd1i7M+Bwpym6pa8Mx936G52dv5PZnTLEzp6mUI3EQ5NrSaFc+wDG/PUYMHYXPFsFDCdN1ztVRhmXMEStnwud7dCvjmclmCmY1U3KtmSwmTOHLEnMMlXu345Ad4uRNBzoBFGxbFOKi1t0NM71PgCmrLhzyZY7UMvQWAuUoQJ+GzsfpN8h0x3fWFYOb6OgrQ9Jn0JFdomqRT86PxqMTytTnSLfHNBllQ/Q5kuHP7y/H5ro23PaOeymfjByyBVmkZYRBUG1OUbThM5h11TzgxRyJLIYf3IqL+7e4jAfA33uZ34iXqUtfNr4gZY5EhZpzTs7wugH4vlD+PkfW30iKaZOZ1XSiWEXIlCwXc2R2jTXzPYebQKVzngcMb9Oj2wep97WjQDkK0KfBOyhm9sFoh/L3kFmNaNDgcQ/KGVD4HAmUFD2PVRZdtnzFb1fdaR5T+k+k9uv4HLVLQsN9hfEA58iqqpotIzBHemwAX8Yw9BUsLbOazZi4j8nC273gfhfcg34kFPL8DrgV4qlsUF9wemkfHKiYo0zyHKWTN0wmD/88eQaLmtVk74pOv6Ajq3idCdPsRrOTt9zpKCl+JuSkR54jt+IeKEcBAnhiZzpk9xR02udC+SUDuZQ5UtjtWebIi77ONLGg7v20GDMLhmE4zJFCUVEpIyYhGVFHOp08xy6ZYp6j9Npw9rEzb49aNK7JK1qN7kmHQeEVZ6YdumEAWUK2bPbdkw1wXhF+mX571HwXEvzUdPMc+cmQDtvM/RauOcsjus9XOqlyJCnmUhx7tk+TKYY1zTFMmbsZrbGEtBzgF60mmNVc/kridloi9wh2mVD+AP+byDSslK9Dr5yXH0JXvlVWSVDBz+dIycyw26m/7HW4zRx6yqb3Me8ZIiuPLFqNL+/sVPoFkcwiCdnavOqmMFmqC5oO2ZJ9uhFV3cUcac+yNZ63Acspu1OxDCKvxLtlS8dJ10s0VSg/97w8KvebBPgzR3IlzFFIU8yRh1nNDzrRpYD73U0Sd1JLFfzZcHcBmQJ60VNfYXVVCxZsqsffL9hPWpN3tJoPc9RNSnV3ImCOAvRpZOocyNehd6JXR+JVhV/9bEi7CgnOl0PSvmJkkw0Cnj5HUB9T1euWRQ+EMAqb4Q7LturyZ1kyV4qdM3Ucsk0ivm/+LUuVVk0FS8chW8fnKONoNYkSZxhAluCUzZaTL2Whvt6MzWpEUI5S9fjlWdKpG0h3+RC2Ll4hpEkg5WY1bwH9WEcK8d1NmGaPmp1kueVWV1mLuk77tlJ5nh9JyjNH4rneTFJvIFCOAvRpqAZSFul0dF7wqqcrH6vOmXwSyK4xR6J/kootEq/Ji3FioT8o8RmyqViqur2cpsU127Ta16qbV6DSfcx+GbJ1WTYVRHZGZvLIVAHhfI5smQx7wBePAUIov4TVEpUEfVJLVACooi+a1Zi2NCvvss+RB8NDUx/IlG8/6WTHZb5xLpOT2TUm2w9e341Xu17PI2QYnv6j4pmBchQggA/8orgAneVDtNUj5RGvGvyqJzpmNS75oF4bRFFWvB+qjj5TdkhqpjDoX96nxXESd5QvlXKlZncyG3DZ05R5jrh6BYfsDJmjbo1WowqI1OeIsil6dVnmSX7b+e08p2hYrVxz62NpmPUyNfnpOGTrvr/yb0TfTCtVSEXmSHNCwx9XK10s5MyRd91dgfbaagI8yxpAMskGnYjnZviN9yAC5ShAnwY/sMvhuxRAN3xoXVmIVceB0m9tNZ2OlG6K61TpsCbpHNMFu7aaJRetW14+qdgvDur6a4m5WQ5Z3WyZdBUbaRlNdkNnfLaVEZlyTNkUzRFMVKa538SRKRJWm9USklB+LzYyQ93ISQLpWltNT3n1K5eOB5tscuHyOZIyR94XLzsqk1XGHPUkdSRTgHXgm+dIomSqtgPmKEAAH6SblE+G7hjoPWeprAIgjSrzRzzp7XOkimLRcTblziWK/Rrtse3qgB2MWZ8j1fPwTpjI16vVPnutGqyUqMTqOWTzhQxD3y9Gx8ncYY7ckCknXnAv0cAogoxMYpZsPiWC+9q8/AL1n5VEAYBboTYlqQTk9fkIkYZ2JGNbxSSQ0mg1X+ZIb5+UOepB7UimNOvAb6kcU9URoW9GqwXKUYA+DZ3Q6r7kcxSWaEc65/LmQ91ZqLxel8+RxLdEXac/vBdBFQYSymYZhm+eI5XpK9MEcRwrpMxzxNerMkHqtOHUI5aR16PFHFFzkodPi7bPEdzRhGI7huEM+OIxQBGt5uFUnykDIEarAW6zp1fVfgpqOtGPsvmZnQRSMPulA+nCs9IkkPy2+J52F+h76mVa9op29fOv88qunk5dOwuBchSgT0PL58inju5YPkT3W5Uu8+FzMiHEd1kGJXOkIYOKfMt0dubJonHlnMzglkhunyMdJ3DLrCbPz+MpJ/NbK88RI2867Yjorlkw69AuVY3N9Or3GpDY36JyxJ7GrwFI3PX4tKmUTdh2MmSz74fgkO1x4fykyl0unYSvsugt+sNeeDYD5kj2UHXMagmzZ3gjO/owTdOyXdbjmGEY8vuoaKcP6EaBchSgb6OnTWIsvJkjj/qZ32GpcuTdrnthSb2OVlWtSF6lGzrvB6+zxIGSbhvs2mppMkeZOmRrhfILymK3hPJrM0feI7TfxEAW3p4OZH45huE2q6nMk/LBVHhW2rLw2yrmSNdZWKX4UaTlc8TVy99z6nMkS2yamc+Re58rz5HpnxpEH97KbndmyOZyuYlRjT5mtt5AoBwF6NPwmwEC/oOMPnPkFa2mroOtXm5W825X9FeQy6s/M3WH8ivO6UbmyGE4+M6WbvE+R/J6vZym2UvSd8jWqJt12jYzcMiWPhfxefrXIwMX+ixpR6aceMM9yNpHbCXW7ZDNlpMyR2wLmoqht2SMcsRGP0Jgjjzq9nXITsfnSFD42TpptJp8bTX9ep197p1i3T0Vyk/veaY+ZF7r4RqG+D4L5xLv7d5AkCE7QJ+GzmCVTs4SL3h2mJ51OAd1lvkQ4VaO3GXk++T1ejNH/uf7QVdRJMTp7K0M2T5JID0SNap8ZTzl1GCB3GX4wTidNijcHb1Cqfepm48akrXtnul7wa1kSmQy3IvPssqRzOfIy78nE5aPrZuNvDSJqLyqK/frNzLJuG5VRuu3/nYtz5Fa4eX29Wgov9tcrZNbTnbMq6xhGNx1+CnRAXMUIIAPvOzU3Q2v7tJ7lur8li0Q6zcLSoox7JozSrFtCpFJU5mKMu1/vM4jwm9723AGZmWeI81r1O845YO6CqK5QivPkXSfMGiolHqf8VnKRnDMHP/XD+7ZuvtaLeaIF4xTjiSKEM+s6A+YXrIlZMwR0Y8E5N5DhRKYCVwLz3opRz7vj+yw3CHbrTj0hNeRjAlMh8HxulyXQ7bLjKZf185CoBwF6NPwmz0D8J2Cd8csRLcGaSi/T/txgY+WO2Xqy+Tq+In0Z7f4qohtiv4pjrnGyZCt6tjVtDxPeRAP+p6X0/mtjlbjB1u/QdXrfLYeflvBHPlk/ZZFMMoUkUyi98Tz7OdkGJ7RajJ/FO6dckVWaYnmepntPEchL+XIizliq1a/r+nCYVesv7ZZLSPmSFa/7H0SmKMk0e+Q0oDjc5TZBMovQzaflkUsIU4oel87CsxqAfo0tJYP8alDZZKgDEt7Z9KloLjl8KiflaXHHLL1Z6Yie6XqlHoiWk3Va/NrqzH7NRaeNU3RrJY+G+EVCceWSTcBns4Ap9bp+YFffHU4M4Rsnz1Q694PcQBi2mKYI9Gs5rfcC/H4RrXNaiKTIDGrERDtPEf+DBPv6K2bMZvYf61f1KyWSYZsmRlZyyGb9HS0GrtP/3n65TnilkjyOTfwOQoQwAfes40M6qBVMYPRfndOQ2fCxIUHD1fWoZtNWtbF+g1e8aTIHMna0JdLN1ot0xvqdZaqY2V9jpTRaioFxoeC15FFb+FZApN03edI1wzIjsdJQhAS3h5+LSq3TPa+DO4HIE/oaGXI5uWQJTgEHJaI+0SFoukO4yHDksXJkM20JzBHntfNyeTNHJmEb8cLtkKauvaIRyi/36XL5JcuHyJ5brrPPL1lUohLhu7KkG246hXP5bcDn6MAAXzQDbqRwi/EQWfC6uk27GjVksOrLllf5OtzJIa1Sn1N9GVyM0fyc3qCOVIlDDQMw9fnSOmQTfxNUNLzWJ8jDeYoaWaS50g2+xeep4YZUGpKlfhoyMxK+uyMsC1VINxmNb/knJ7KUZqKmxjRGHKF8jPte+Y58maO2C9Exx/NlkF4Dlkp+fz8w/xktGXxeQ8A93vqKW8aSobMhy2dLsKbOTJ4M7FrwuO93RsIlKMAfRo6sxi/2ZG2Scqjmq4Q2X4dlDgzlytC8kFYWrNwHUofH7FO3dmzZrQabz5jHbI15bHby0yp0xlIRWXIy6Tg14ZKPjVzxERiSVdjd7cjmyzo+xwJg6xE0bIyZAvKtVI5crfvlVHZWzbrr7guIOuQLTJHXu8BL4e7YCapIVg56V/KHEkzmPtNijT7JalDdrfpDjJlm9nnk4+IO5ZGP5epEr0zEShHAfo0uiNDttT0kaYcXi5Jfh+23/FE0t35udqXXYOiXt08R5l2SLosGmdu1Mlz5MEcqer1lFOzbrZMutGRsjK6s2DDp4wsL4xs4EpncFdlJKf3x4A7V5eKdZPmORLK6LNaVkExiSonC+G/A90IUjlz5J+ZXS4nfw41QUrXVvOrS8oSucuJ9z+R7D6fI7Y9eRJI9bki8+glEyFE6kPHHufk6gPaUuBzFKBPI1OKV1WHXZc9A9RrQHfGlE4+IoqEGK2mmW2X2P/x6Pk8Rx7HWGWDVY6YDNkqqDpiAp7S0ZVaJyxfvB8q5iidVAqigDry+plT6GHdHFgyiE3I6jcMJwLLKSevj94fL+YoXdnEd8TlkK3xTMR2pSSxT74nP0Eds5oXc+RdsSyC0s+8Sst0VzSXzK8tk/QphPiZOUXmiC8rnukTH7NTEDBHAfo0dMJKfRee9fAH0O1jdKPVMgnpzZw5ktfszRz5309fSM0Bqb8sTc92cIY/w6fLHGWi1Cn9SgTFNt3IPvEZGDAkCoL8ZM6PSsYYcI1SlkamiOjdDy/HdjpIGjDSYI7czbvMJWlGFvqZ1fSXD/FXjCnS8TmyI7pS23aeI2kf41eX3nfuYo660SFbxh5yb51mQ1Ywg/q4S7H1kEO23RsIlKMAfRp++UoA/2y3ur4Jur40XpB1tP7MkUblMuVIUdSdBFLeKWVKznuKq2BeWLOaCl6h2ZmYA7mOX6XcCOXd6oi7LtX5TlmhjEqpZ37Lrp3zCZIsMuvFJskgNsFHq6WUI0NiVvNzyObaEBiBNGUT2xbXVtM2q/nIwC1om45DtmB6cqLVZGW965IrR5J9Eofs7oKMKfX2IZPXY+UIU8tlEkFun2+kD+hGgVktQN+GjPYV4cscyUxSwgwQ0J+JShqwIZrI/OoFgIQrlF9TwdIYdAG1YpEpde29pABTP2dWg+9UTB2txkfnZJL00CsSjq1X5YyqalL+WNKfBetGq0kHswwHS5lzs0w5Up4v8Xnq6pgmKtCi+Us/CaTepMevHhG0pBitlgnTIXfC5ycUgFtxTieU31cGqVkNrn0yuCYWPv1nEK0WIEA3ojts694frV5bmmSJIt+J9zW4o1H02lcF9AouI0Lz6Q9kLbEElm1rdM2aWTgZst0DrnXcyJg5IhCfk5bYLmdred2EK8MlgWTKqZkjt/+HbkI7jgWRFJLmOZIoIpkyRzLl0YCBiK5yJHkfZP4xmtIBkPgcGXxmdf6eecnG1Cz9JJnnno5yZCsQ1g+qSMrN6ekrZVKzWuo62bYyYX39srmbzkvmKY+8bh8mj3gH14hn9r5qFChHAfo4VA6Y6SUnU+8jmsqC94fPD7Duc73lcy88K+lopfvk9XllyJYxD3449cFZOP3hLzBjVY1Vh0dZlaJoJYH0bsebsvcv5ymL4iRxEFUpRMo2iUzpIJ7bMvnkg6JMEXJ/A+n49fCmRnYQTP3WMH+KMntdR7qKrIs5gsOEEiIq33rfpB/pms78y34OKYUlGsk8CaRuKD9VONlFbjOZM/oFizipGRh5NN8tP+bIJITr59zvSaZKdc8hUI4C9GmoZvLst+Ob50ga6eWe9eoyTO66HHRHtJqseDpRSto+R5od0Ja6dgDA+0u3K+Vz6pTXbxiZr4TuSv6nbVZjOuNMQvk1BglR4RDPk23L5JNHq7nrkL2v+goIUSp/tlkN0GaOpBmVhfuUtkO28O6GQgaXAkKW1VsuG5hysgmLekLjZaZ02FPrb5fWVpPIJV14NlWOLuuS6fIhfvneZD5HfgwPe66fD5hXpKF4aje6VWWMQDkK0KehHqzSqcO9z2826SWHCD8HSb/BS4xW02UeVCG97lB+uSyZTs50fY545sjw9Q3zqlOX4VPK4mEWo/Ca/XoFu4mHdP0nOOXEz6wGOnAxbfvU75IV/gqjYRgIa66lkZRQR5kOclQu0d+JTR4qmtW8Q/m93xcuUi8DUyAt4Rmt5lON7oSHPifKUlkLOqf/8Urvg2QtQU6x1HyAViShx3FT9Dlyn8/JGjBHAQJ4Q2dg8U8CqZ7Vmd2gLfh3gt4FKN0csZ079epXZgx3l2R+6c28PeE5Y5fXrxOt5tmeDxOgPE8ii7oMkc6kAS/TGD9jNgx9n6N02A0qp8wxXfs5EtHHxF3EgDsRowqmRCZd1kwiGgC3v5y17IzzXeg6ZPvdW6/PXoeRsh2y6cKzGfgc6Ua2isxRwsyUOXLvk5vVMpiI+DFHxMfnSJxQ9AHqKFCOAvRpqOzfsqiOjnjSXieNhZQlks2SvGY+XsyRzwjgyxyJM0OROVK1q+gk3WY1uSzp2vVtM45XGa48X1JmrdEZh0X300zWVlMvH+LAJF73StGGZMas6z/hp6jIMgrLBnV95oi/j7LBOa1oNaqcSbIss61qyZYq5jKrGazPkai8+svG1s235+wUv19v8xCvkNpmtYyYI9k5EuWI+hwx/k2ZzONkvYXUIdtLRkW7fswRgTxvl6ra3leNAuUoQB+H0qwmfD2xRBITbp+Gw+76xG2Wkvoc8X9V5VTtqWSUnuvzqdNQfsocuWey/oMrC3FoSydHjw500xpwGbINuW+YTidvKSDeg53qPFsWjzQBbBnefEek5bjzJfLosid+jvz8TJsOypIJQjr3w4cNS8/niDavZhp000XQ80TWSlx2xlS8XyrZrN/eiks6ZjX7mlM/2G/WvQ6ZN/zW03PKpZSjMOvfpPfQ2bvpyxyZkn1en7rw/vqlVvBKy+IX8dkbCJSjAH0aMh8LwP1xbalrR2fSRH1bHK2dSby2YCuqmzusOjwStOkOuroUvvxc7+Mic6SbSE/mI2MpIWr5+HuYXg/kLBzrPiYbKDmzmsbyIXx9vBKgy/BxdTC/lQqiMIiq2BwvBcfPx0hn6REpYyAxb3SNORInA24YhjtDtgpUqfBiH9I1AInvLhfKT/RMnWK7slJe9Xj5ENIjtAhlcwC3sub3fUlNaLoO2RkoD77KEXE/T6+GRP8vPybPy+fIT1nqDQTKUYCMQAjB/R+vxtRl23u8Hee3s180q7H9+V8/XIFfvboEFzw2xzpPWjFcxzwJkS58q36DV1KYGbp8jlSRUpLdVuizVyi/njLo1Z7ufWJn0irmSKceQvQZPlUd6jxHDizTgP/7Jp4vHtH1OVKF1dvHJdFqfkn7vCAqF1KzGoCw6PijgCzPkXgz9Fk+q6BXKL8pKq+aeY5kJlUvBiodnyOWZRPvp/+kyV1Ablaz/tpmtQwXntU1q+lORNwMk4dSSbx9jtzfTO8rR0GG7AAZ4fM1O/DQ9DUAgI1/Pa3H2lHZqXmHbIMbeN//xlLYNta2uco6NaU6AkWqAFf5LnyrfucmXMqRXicruy7DcC9ipns+69vhBVkn67BKqmdkISRxWJa3wf/mlS7/80U5ldFqggKlYnO8HLr92BK9aDX3cSlzJGknLZ8jP4XPSN+spvourW2tqmy4otWY5KHWe6Bui29XzVJY+9T3XoeRokXoN+snj5+Mzj51ueweYI5k77iX07uKGRYVV1nbXhmyvdb96y0EzFGAjFDTHNsp7SjD0IVybJ8ad4XGu+uVmYF0afp04Uuv02g1GvmiOftWRRu525f/VnVAXUlNoKqfKq+67JHI4Kh8gXTlVDtk8wNB+nmO3AOVe1asOte7DL98CeH+WufI21OBEH82zIDhWvxVBaq8eZkf5Uv3yPZZf6XLhzCKt74/DJhy6vZkxz3NaoICEQl3gTnyWT5ErDcr0sUM2TIZJIqQLAu7DOz76ZfnyGVWc30jgqyBchRgV0WmUdnpQmXmYBkfMUw8nhSTKko6R0md3nLolZPBbxZkd34huc+RF/MgdpIS4kiYRfsrg+kspyCCPVPMkA34Z8mW1QOIjE4GsmgwR6Jvk1eIOrvfLwzZ61y2bRHSDNnSvDSayqLQjmxwNtJgjmSDqU50k3SykiooWvRChqF0yPaczHjNpAQ5dZbvcddv/Y0wArsYKB8FRrrYsMwESH0Sw12LVpMr4M5veQSvt8LjnOszaRLLi8c1+7ydiUA5CpARdpZypBrYRZONwTFHgnIkqddZekHelpcc6cJ3BpkqQE0Kro5DdZ7UZ8SdbFE34s+pl6lP8py9ByV5OVqPyByp3iOvUGz9PEdOOVmKB3ebMj8K7zZlg4K741e1px6gAWHwJPSPWz5tE4TIkEiZo3RC+TnRXL+tMpIB2YPJEaPVQlyAgcgceX2vapnY9mT1eAdfEK4M53MknOf3muouCUTrzepxh2z+r3WSug7xWfj1nwkJE6qSLXDIDrDLItOlINKFVo4eg/c50qFoiX3Mnx1gy2cCfYdsalbT66ylg6JkmY508xzJfIVYeF8NM+BzypFVkzZzJAxuGYXyM7874nLlyB3Kr5BB0aY4I4bGtqxOvzxH0kiiNH2OxDalofxp5DkiEpncaTTc8Ip2dCvPDnMk5tLxNKt5+EGJ+9JTjvgy4ZAzGXEtA6QWL1WHbJ9ESRaiWS2H7Ey0I8ku9n6a7vdJVwH1zXNE1KZtSzTxGajr2lnYpZSjWbNm4YwzzsCQIUNgGAbeeust7jghBLfeeisGDx6M3NxcTJ48GWvWrOHK1NXV4aKLLkJRURFKSkpwxRVXoKWlZSdexXcDO4s5UoV/8mOEdzp9r5mq16yXr8NLSm/4zYKoEhEJO8sD8OerZJKE8kP2bDTuoUQeQJ7V2q8TdORzHxcVN51xPZ3BS1V3LJGUl+HKE0EJ8x8kxPXKrLLitr8SKh0UJQqh7P7qvpoE/CCUlJnVkH4ov5fi6sdWiHA7ZPMLz8oURhlkkX6cXJw8/LF0QvlDIcNmu9Jx7Fa146UwdTmUXxqtxt5PWs5bHvtYGj5HABBnbpCLDRbuXWBWSxOtra3Yb7/98Mgjj0iP33vvvXjooYfw2GOPYe7cucjPz8fJJ5+Mjo4Ou8xFF12Eb7/9Fh9//DHee+89zJo1C1deeeXOuoQAaUIntJrAZ8CW7pPMkiQ9AZGNSmnCdwZJHbIVSSBVFahm/q76FTN75aDNnCBVjjyuSFQ2RJkyYo6IvhLL1+GU7IibvmaMpKk2x+gyR6ZEUVfJK5u1s+BlUSsi2j5HxN9UmJ7PES+HKLOqDa/oUbFpNhLVFcqvOSHyC5lPx5HaPkaVIwO2A7vLrKauRimXp0M2lwQyffgxVTIfNq97IZ7r9xqya0i6o9V49AHdaNcK5T/11FNx6qmnSo8RQvCPf/wDf/jDH3DWWWcBAP79739j0KBBeOutt/CDH/wAK1aswNSpUzF//nwcfPDBAICHH34Y3/ve9/C3v/0NQ4YM2WnXsqsjnZw1XYFsgAD0TB7OcY+po09nS4h8vax04G9Ws/7SyBextJdZTTwi9TlSsW8KsbjO10fZEiEbdNgqdNZXCxnCs4b4vDWVAWE7ljCRkxUWyoiKjbwdpXJE+IYIkbEn8pO9lrAAhOdGHBlZecV9XnAvvyFXjnSj1Ry/Pf1Bz2pXVhdtX+1zZCl37GRGS0y5DOySJy6HbC/ln7/nIYNljvSVLFU77jochTCawfIh7O2UJxpl5XHL5Q7ld5env/3ewx0tToSzH1MU+Bx1IzZs2IDKykpMnjzZ3ldcXIzDDjsMc+ZYyQDnzJmDkpISWzECgMmTJyMUCmHu3LnSemOxGJqamrh/AfwXe+0ucB+NQiESF/8UocsqyTrtpGQASBe+0WqpNmjki1eHJDuPhSHxOSKKDVUH5OWQaZ2nEAjy+8kOeEoHbIGtEpWUTBbMFeWM+ay75xUqrn6/3Fm13WZA+ZleIfCA3KQsU27TURL45yMTzMggWo3dJ2lUcZ6smGz5ED4JpLdyJzsmj1ZVv0/phPKzDuzu87xfVJ3lQ9htljnKJJ2F7AyZgq47EXEzpt6yxDnmSBRErNu7rp2B74xyVFlZCQAYNGgQt3/QoEH2scrKSpSVlXHHI5EISktL7TIi7r77bhQXF9v/hg8f3gPS73rIeIX1NKFiPdIJI/XqjHmzimQmR2fnmgOQDL4zyIwdsomrU5H5HKXl0C2Ul3fCeooovS5WHBXjyEayhEKGZCYp/62Wwy15LO72OxLfKVWOF6VqRERG050MT+WImk60mjMos20TVz1eEFkuVSh/+suHqBUR6bcn+5ZSxcS22VB+d1tq2fwUT/Z4WhmyhTKWw7i8noyYI4/7x+U58qlbFo0rvw9uZdMv0k96rpneBNLvPQl8jnYB3HLLLWhsbLT/bdmypbdF6hPYeaH8zm+VSUCiI3CQfWd0n1/eH6dc5tB2yA4plg9RnC7b77e4q07uHlWyNjE7sFQm5rc9u/bwOZJl1g4bhqtTVynGSjmI+77LItZ45VjdjtIhG5LnpRl543dNvFJF771bedN9N4nQjjKUXztRJ/9X/C3bBhQKE9zvii0TZ1bzrsdpl312suPqejzfL0GBDhlOIIXLd0ldi7Idr3XeOIdsn7qdZ8O+L7J3zN22dhZy1jQpmRR4yuezHTBH3Yjy8nIAQFVVFbe/qqrKPlZeXo7q6mrueCKRQF1dnV1GRHZ2NoqKirh/AXYeRMdr+7fQuelS7E5d7lmSl8NiV2zgvp1kquEw9TlyzUDlNcjzHEnaVwxeMudhQB0hKKvDfcw9+LJmPhXjyDJH4ZDhUsrSZo4k5TqkEWu8cmwqps1ei8d6LZJrVaM613sQ8o9WS+/dFNk0lUM/m/XZC3b7bJ0unyPJgOwxCfFijsT3VdeULp/0MPWk5XPE9xOsfOk6SnuZ8WWyUOUokfSOzmXP8/tuZD5cvNLOl1fdf51oNb4itRxiO72F74xyNHr0aJSXl2P69On2vqamJsydOxcTJ04EAEycOBENDQ1YsGCBXebTTz+FaZo47LDDdrrMuzLYPswrf0VXoaLHdWao9jHZPsnMSuoUKxmU0oXf/aEdgypaTXW2tFrDzR6pFUw5Pe8b6aPJVdjyMeKozGpJxh8hZPCCWp02r8T4t+32y4j5MEemqDxosGwyxU0/FYPzWxZWLzMpy8xKac3Yfdq0Qvl1F56ldboHWLGM3z66S5YEki3DsxVesjkH526oc6Vy8DJp+vkc8cyRAbq82trqFmxraOfKekEnlJ8tU5BjxU+1dSY0WKmUDD7vsEzZlgUCyNtg+4n0+kiXEq3Z5+1M7FLRai0tLVi7dq29vWHDBixevBilpaUYMWIEbrzxRvz5z3/GmDFjMHr0aPzxj3/EkCFDcPbZZwMAxo4di1NOOQU/+9nP8NhjjyEej+Paa6/FD37wgyBSLW3wfgChHnLRVvmAuAcJrw5NNsCz56rLpRsRJIOvQzaNVlM5ZCsHV8nyIfBZPoS9Xsjvmp+/ho/VgflNbJls+RSvCZtALxwyPDtPHWWASDprGXMkKgsck6gxEBMim0HzZZQmOT/miBukJEyAT/06soowDH2zmpPnyC0T26ZbDrW80iSQIUdeXYds9sjTX2xAfWsn7r9wf+lxXTO2dZ7wfJn7dd1/FgFwFuL2m0R49Tf2NvMOluZHAQBN7QltfyaRgfVqT5bnyNshm69HLPuTI0fjm60N+HpTvetc9+RWvO7eV492Kebo66+/xgEHHIADDjgAAHDTTTfhgAMOwK233goA+M1vfoPrrrsOV155JQ455BC0tLRg6tSpyMnJset46aWXsPfee+OEE07A9773PRx11FF44okneuV6dmWwfVhPvseqWZzoNKw7YDv7/GdtAGzn0a5col8nSa8lS7HwrKdDtgDDcIfyqzpIsUOj5/kuPOt5zD0j9/I5os2LpjxRZtk1fLB0O+6ftgpiiDrgZoEAoEPqkK2+HzqL3bpldZfViVaTDQZJoV4qI4Tfunq7m+WSvD9IP0O2atIC11FaRl2X2HSIib60lDuvttTH3li0TSlDOj5HooLJ5jmSlfWC7DsTz2HZ7JK8lHLUEYduj8QrOu7jMmd6L6d31bOWBSIM65eLKT873Fcu2XYf0I12LebouOOO85113HnnnbjzzjuVZUpLSzFlypSeEO9/Fj0ZWaByyBY/em+K3b2PVsUzB+qZVVeuUbeTZH09CCH2LFp1umrmL3bVKmrdJCrmyG/Gqz7GznSdPEfp+Ry5GQ5RibH+/uKlhQCAg0eV4qg9BvjKqWVWI4pjimhFIrAZMsZKR7mVmp8k5g2umP0Oaw6ULrncZQzDSMPniP51D7CqNgG5+ZrucSlmTDSYK0+TRwSpX3SpF2vnlyGbLR4yDDvE3t2Gtwx+zxwAEilaOWQA/fKyAACN7fEMmSNvGWUuBLp+XbIUFvy6eDwa2+O48eVFOO+gYTh6zMC0/L52FnYp5ShA34EqvLa74eUvw+73ztqsd8wztLYLl+h3f8RoNcDqeOxILiV75u6AZX0RF5HC7JcN5IAGc+RpznDfT545UvgcCSYkUQnwYjxqmmPS2b/43KVmNeEclcKieoYrK5txw8uLOdlcZVW3i1XMfUws9JdsUNedZRPF+SJ003TI8+LwZfyj8PjzxLZDjA8dEerrrgmL+L57hvILSkDIMJAXFRKLpiY2vmY1yT7xPehMKUeRcAhFOZZy1NQez8jnSJ6F3X0//SL9bFlNvm7xcYRChut5hkMGkibBvVNXwiTAW4srsPGvp0nMsb2vHO1SZrUAfQfsK9+TFCj3kUhmObSM17ckO0b36eZD6ZrPkfe54vIhuu3Jo40MT4ds9iLF5IoUXTKrSZ6R11DrLNopKLuCYiIqdSJkfiNiuXRD+XU04kdnrHOdkQlzJM9e7D4ue1/T8zli6pdFO6axfIg89Fsoo5DDtS/1VzRRGQzvKMrvyWD6fXMeSpa3LxOv/BoGkB/lOQbdIA4vJZGCLrkRDYdQlGspR62dScRl3vQMPltZ7dsvAvw7JlO2vRQ8cSIh3jc2BxQFfbfcrgP8du+rRgFzFCBDsONvpmv96ED1oYqzam/6V9IJQdaxyzorYreRKfzuj2NWc+YqOqyF6RrM5Q7ZRPFbFnYO+HfquvmgHOaIMasJ07HtjR14ed5mHDyqHyek17IeOhF0skvw8zkSWR9d/xYWspBmHZ8jqUlXZlaTzvS1RLPKKkysFOksPCt14PVwpHfOU790okWPNc2k45CdjmnYFWHnSR3x1xsyDORlu5kjnTUEPJnqFOI2c2SgKMcZrpvaE551X/efRa6M8NJnIVmg19PnSKGcyhQxlvWjyAqHFJnq9RXUnYWAOQqQEfzW7OkuyHK9iL9Fs4sIr9kre8wrtLYrHyu74KIM9BqzwnLmSNW0cvkQl9Ozxj30qdc6gfsjO8Sze7bPkQOZyea3byzF9BVO/jEi1iMoSzoKnSx6RtYpc6YtU/Q5kitKXhDZDSqLtKzEj4pF0nSXNYX74lW/rD2OKVO8P/rKkVs507l2uXJrwW1Wc5hQkQ3U9YeRgQvlFwor3/+UnGyG764wR36mVMBZciMrHEIkHEJ+yoTX1B73rhzA24u3Ce4HskkNcx9o9KGHPJz8rFmNuOunz5J9pKp3y/39KpvdaQiUowAZweBC+XuuHdXArvJFkkFKX0vq9JrldkX/8+psAdasxvsc2b9V50kUABl3pHJqV+Um8fc5ku2jHatkwNfwOVq8pYGri9N9CT9d1xlwxYEUkDNHLsdvxXuVntOzKIv8XP9oNfe7z5a66sUF+HDpdu13U1TcpA790DeryZYP0RHGK0DCFfllgHPI9nNi1zkmiqnjRM6W9fM5MiXfgp8MFKK1jDJHNAEkNa01tHd61g1YTs8yZZqXlf1N+zrviYhYnv4W66fPjf3msxTO/m7Gsfe1o0A5CtBl9KhDtmT2DPhTuixkh5yPj//AXe13g3Lkl7ODEktctJqPXCqZZLqHmgiS+xwpnycdpORHXW050Wre8gFAfZvT2RNBBnG5BAL3PXXT/5mtraYaTPSZI+Iy0yjvP/F593zMagBw9UsL0/z+mDYVPkf6ofz8X0Du++U+Ty2vO5Tf8ToiENkKdT1+gyufcoI/lm4of3623DvFl72S+hzx+1izGgDbKbtRgzkSo9q2N7bjXzPWoq7V+dZkDLW4LIhSfkGxkvkcAfz3H1EkGHUxjl1Yy7K7EPgcBcgIflEQ3QWVeUlkVnQ/YvYc8Zg0xFgxKKWDhM/9kTtku2VwnaeY+XstPMuzIWkyRx73QsZs2EkgGYFUw25Dm9PZu8wnpjibJYgLvacOcyT3deDrUDEKus9f5piqvJ0+7x7HHNlmNcm915LMPYlQhfKnbVYT2pCV4fdJZEvVIjKL7PvsVl49lBi12C4ZXGY1n1B+9rDhyRx5I12zGgAU5+orR1ZUm1PfRU/NBSHAV+vr8O+fHJpqTya3vM8VITJMYln6LK2/qT5OxRylzu3csRlmawMS+w2SltuZCJijABlBN41/V8EPEGybwofpUYfnYO6jhKQbLi1Dc4e386TcIdt/YJYPbvoZsmWzvdZYAi0+8sqkkTu4OzJRqMxqnHIk8FlitJpJ/MOvpaH88SQqGzvw+oKt6EwpSmK9SmVcKrUbrgzKKVlmr9uB37+5FC2xBLdfJT+gYo4k5TQVN/E7kUarIROfI/V16MpLd4lmtVAIgs8R05ZXniM/5og53tDaic/X1Nj32+tU1pRNRRWZI90JlZ+ZC2CYo1RjRblWW40+DtlWmbi0f5u1uobZ5352utFqbN9s+evxZe1HyTxSVU4okxCYsTZUvvB/qHr5d3j9nuuV7e4sBMxRgIygUlS6vR2m6paOBBraOlGSFxXYEO+FGOWH3LMkGWT5QtLFTKYzkkHmkE0UuYl42dxSGfDLkM3vZ7fjSYJ9bvvIU1aVQDLmyFl41oFKOWJnwq5B0MXoODNqlUwE7ufeETdxyoOz0NAWx9b6dtwweYww2KozZOuyo9Y9FRU3gh89OReAtT7WLaeOTe1nysh8joT0BuI5bJtaskFD6TbUpg+7iJEyL9Hs8R5KpG6qCFqHuHSJASccXFTmPZe28GNrmcN//3g1AOBPZ4/HJYeP9F9bLfWbvsuZMkd+eYcMGPayOtFIyucoZVZraPP3OTJ9Jo1ieyYheO7LDXhtwVZGRo9zBROn2+eIMkfOPi/Fu7NmA0intTbdlmXzkUgkEIn0nooSMEcBMoIsyqEnwNY9Z30t9r/zY7R3JnnlzJQPGhTyKA3+rwrdwRz5gXYybMeh43Ok8hkxBO5IDFdn62Wrrm7u0JNXk4mThfKrfI7aGX8gUbERO3mTEJfiIMtVI0rZkUjaDNXM1dX2uRRJU51PSffxy5zc2e0tdW2pfW55RSQlAkiXvUlHcRPuqwgDhivdgogsYQ1A1fulakP2OjsKhyAPE31JhPp8Iu49IbuP739TAUAjgMJ+r61tkTnSjVbz8zMDgM4EnTjxDtlNPuyujTTYK0IIbn93OX+6x510faNCUXp/2AmRytnfNAniNZuc7WQCmzZtkpbdWQiUowAZQTWIdDdqW2Oufdsa2iSdm8cs0qMz9pNdtuBnd8NmjkLyPEeqtlU+R65yitmfScDdNl0nSK97wSutxCWTmPfEtxLwpgx6OMF40ZqmIis14ZVOdvkQWxFlToslkq6ZtOy3n/Au/yemEXadMBZ+62w5Zkt3i9rO4gLDqgrlp8xRZ9V6tHwzzfWthe1Efu6Jg85n6ZVPzGVWYxyyQfSfie93LdlH2/FSNtk1xOi7LIbyO5XrKyaqfaJZjTJIsuACqbw+x31Nux4ViCye+DxCEods5VIrADprNnL71qxZo258JyBQjgJkBBlD0BPYWt8u3S/OeGQi0E7cezDX7cC67xrFwUa2tppOniP5bM1tVlPXxfvlJDS1IykT51AbnHyWTE45HXcWV7I/F6NDOCf3uGm6JGLZptwsy+zBLh9CO2625vZ4UjnQ677ismfC3VbGRMRCVj+/pIr8PEDf5OtmjuTKNX1G25+7HrUfPoT29V9zZRI1G1E/41nE25pS9aoVlrSiISExqzGh/CLT6ckcabI/MngFUBA4yhOVS0wCqRvhqpOSQjSrUdO7X4ZsCj9/R9E0JsLrPiaFb93tc2RwfwG1Q7ZJeOYICJSjALso/Gag3QHTJKhoUChHLrOKuwztaHXNQNJ2esCs5ho8GYbDkAye6lB++X6XzxH3m1U6/M0s8nbV+9hDjtyOQDrrdjGkjyOXMKiziTUTSTlbQ3flZFndHJvnKGS4Fef2zqRSIdJ9xWUzaN6PhMrHwz9aTX6eVb+mbML5smuyzFgGSNLxAeusXMuV2f7Ro2ia+zqqX/mjvaZWsq0RxExKldR05JUxR2CelS5z5HdPZPMAStz6MVL0cEjBHHXF50hsOp4yq1HmiLJ6Lp87BWpa3Mw7J4PP9+/13rtD+fnj9FGyn3yWKpTfJIjvsJSjnNEHAgBWr16tbnwnIFCOAmQEcSbfE6hujik7AbGTl8ng5TvhZaZgYWeNzfAaCSFo+vpttK2bj5ZvpiHZUu8eGO2ZKL+OlB/U0WqCz5GCOXJFgen6rnjs4+qnZrU0mSMxR5EYeUYIz3IlTDdzaDFH1k5K5bNMTDhk4F8z1uLDZZX2vvZ4Uu2Qrfn8/XyOVPWx289+uQGzVtfwEwBbSU9vdi8KIjqgi6DvTryuwjktyTrLE7Ru/AYA0Fm1DnO++gptO7Zh6z8vQc1bd0sYMT156S5Rd2aZLBej6Kkced8T2VF67V4Z7dm11VQO2bJvQQapQiw8E5qygr7DlDnqlGV7l6C+Ve64fee7y9HWmXAxtCJ0c0nJokPtPEcazFFzQy3MjhYABnJ3PwRA7zNHQbRagIyQCeOQLrbWtymPsbSyPJWhwxx55+Xx6URThzO9xvZ181A//Ul7O3v4eJAHfwSWTaHjfDi1irXbfCBvXGoWMeByPOJDc/nfmTCA0mKS+2mb1VwC+tQvyOU2B/Gmj0TSlCgkzj2k5lV24Iklkrh36irunPZ40qV0O23q3hv328gxRxLGCnAGpgWb6nBHyin2+wcNc+p1/chANuF0lc8RAMRrt9j74jWbUPXyH5A9dG8U7HcSV3716tWomDsVICba13zlfg4SOeQ+gNZOt1nN4Ng2vwg/r3a5417mIp9otW+2NaZks/a5HbL1JlQ6SnM8pQRlpcxqNN2HrllNumQOgGe+3ICt9W2+77i3z5Hz22L1+ONOhmxnX0Tic3TWP79AosJ65yPFZYiWjQYANDc3qxvfCQiUowAZgc8w2zPakcrfaHVVC37x0kJHFslsHXAoei+6WNeslilz1LmdN0nEtixTmlRChpMwTcfnSJ6nxq18qMxDInOU1KTqZUOPnaSQ6YvtUP60mSNhEBeYISKa1SQO2WxnLWOOZH4l7Z2m0gcjnTvjypDN/FYxg7TZmmZnpi9bPsTLRKwDv/eKyscqR+1rrTQEHZsWI1xUxpWvrKoCDIc5aWmoE9rzlkGUxZUE0mBNoIJjvsd1Z6KY0Ka9JgkLNtXjpbmbrfKpffkCc+RMFLyho4zYSSBTHw59lzu1lSO14/a05VWebQPe1yBmK1c5ZLPIknQAS7Y2onnJMgBAtP8wZA/ZGz958nM8/dOjPFrveQRmtQAZQbQ39wQocyR+T3d9sILbFpkGCplfiXMOsc/1gm5YrgrUjs617RoYqXKUrs+Re59vEkj2igWlsivMEZEMCHaG7DR9jsQ2fM1qMp8j4lwr9ddgFSLZNXSIDtmSa9GR29PnSOGQTWXLZ5x72Vm/Y1Zzt5mOrxj3vFV2WQDx2q3uYwDqpj7EbVdXV6Ozpd7ertq60d2oKK/M1yb1VxqtRoPViH6/4+tz5HGul0P2ykqHzaCy5ilC+f0gj1AUmCOFWU2bOYprhqAiPZOtNGWDyByFmGMpqMxqibptAIBo/6EwwhGEojl6QvcgAuUoQEbQncF1BS0xa9ZTkhfl9ouJxESmQSzn7ZDtLbyuc6UKse1uu7lJ+A6LzXPEDgS2rD6ysTDgDpdXZ9gWotV8mCMi/JUe43wYUjKlyRy56hEGdZPw0WoJU2JWg/NSRCTMkewaRB8Mrk3tNAeyDNnuci4FKlWI9V9hV1537r3+AOYqJ5ztlQqCZY5kyNv7aABAVVUVOuodv62qLRuENt2g9+PzNTWYvXaHVS4lizsJJGOKFGTuqWg1Xd87qujTaEixbtckKNYGkogj0bwDscq1SCTckWRus1pKwU+9w3aaBU2fI5VZTQZpDi1l3+EuJ5alz43dr0owGq+zlPGcAcNTsujJ3JMIzGoBuoyeYo5U6y25s6zKQ/lDTKeqgl8/6OUI64dESx2Sze7s2A0NjSgf2N/ets1qKZ8jq11WBnn9cp8jt2FNFZ4uzvZ0qXrdGaYsQ7bM7Cdvg2+PY3EAl1lNZqaiu+hsO6m6Ecw5MraGtqkvN1+arUcVrSauFQe415sD5Eqavj8U37CKODJN057Jy7D3+b9ETauJtpWfo6amBrF6xzxTLTBHqnD1po44Lnl6HgBg5Z9OcZgj4fUIhZx7RiOiCDHRMPPfaM0vAnCKVEbf71qyjw7mfmsh2rKlBAuHDBy+Wym+Wl/H1c1NPJp2YPtz18Nsb7L3Pf3Jbsg+/XfIKim394nzEzuUP0zNampXARm8zGoiZMEvuiZ92aSA9mWssiljjpLtTYht+RYAkFM2QmkJ2NkIlKMAGcGXnu/GNsQOU8yyKjNlAAD1/fNyyPYb9rpiVuvcLg9F3bp1K68cUYdsw1GOxARrUtkkA6U10+b3KalxpMeI6UTSiQwPoJchW4RoVnQzR6xZzZRGSdlsBHXI1mAd2jud2bwfyyKDdG01ZofNggjPjvp7sedyS6p4PCndd9PFvCh81jZt2gSSiAHhCIb+7Al0Vm9A0/w3Edti+YUUD9kddRWW0v/JNH65mcpNvI+dTDaTEI4V60ya9s0WzWqGaFYzCTo2LELT3NcAAM3N/0BhYaHQpv8NkZqkU3+TmjQh+15P+enhGHzWTTAjuTDNSalGnLLNiz9gFCPLr7B223qUrPwCxYefr5SdTlgcs1p6xp50mCNZWd1gEFmUphNl6OxjmaNYxSrUvPVXAARmrBVZA0eheNS+aOhwf8+9gcCsFiAj6NLbXYE4uFGITJJqkA9LWBjnHDn1LYIOIJl8rLGUcpS/74kY9MO7EcovAQBs28bPymVmNR1nYKmPkET54AkTXulI57qI8Fd+zHvw1fU5cg/irLLIM0fxpFt1YDtrmluFN6vJr7u105lp6zjFu+V2vyvsFsuCsKBsBSujuN6c7Dzapg5E87Mq2nHFCsunL6vfUESKy5A35jBEB460y5QM2Q2hvBJpG+u+mceZi6TfnjCQsr9dDtnMPvq+tnzzsX1clgtH51nJFCjbIVtTn2Al3b69AtXv/QM73robXy5ZhTP/+QU+XZlaosZMomXJNABA4UFnYsjPn0ThIWdbbbXUcnX6mtUUPjssmhdPxfbnf4mWZdNR881MvYuBnGVSvVvi7UtKgiJkiVbZ9SPrP3sayeYaJJst02q/Yy+z11LrqTElHQTKUYCMwHduPfMm0w9E7DDFDkKMYqEI6fgcacqQyRV2Vlgdd/aQPZEzYl9Ey3YHAFQIyhFVcr6a+QnWPX0j4ju28GYlRU+hWlXd0yFbeG6ZPDrP1Agcw5OSifU50uxx2HqaOhL4ZEU11z577bKOme2SqXLNKlSq627rlA/s+rmEJL4mEu1IrI0yYWZGypE+q+W7fAgY5aj/cGk92QVFCKcUfYrCg85AKKcA7S1NmDdvnqdsIhOYSDoZzl1mNSHje9IkaF/n1L9qFZ+OQdWmu4z6mC5zxPZLbE6ea+74B77Z2oinvthg1ddSC7OtAaFwBJff9AdklZQjUjwodcwyxSWaqpFsbXCxwaJZzW9RYACo++if6Kxcg9r3H0DF63chyTjMe6FD5rytuE9eTC2FPdEz2X3OPSMJPgdTzugDPP1EdzYC5ShARmBf3R43qwlvaVjYQSAf7Lx8jmymw0d0Z2219K4x2dGC2Har484evCcAIFJomdK2buUjgeiA+Kuf/hDtW1dix3t/0/J3kSpHhuG5fhl7hsgkdAUyVkkWyq/rc+SZawZ8tI7MIZtljiJhd4erqr41xiyAK1H0/MAmCXTqcbbt9btE5khiVuPrdcskq99HOKX/mS2fASxbZpnPWOWo8KAzYWTloPCgMxEygCxGOeq//2SUTv45ckYdAACYOnWqpxivL9zKLTRspWqwhBFZYjaU3yQEnS0N3KC6cuVKV/06z8rLGV3X54itY/369fbv5m9ncOUSTRY7lN+vDA/+6BAcNLIfwgWlACzlKNnejIqnrsa2x36C9XM+4M6111ZLMUfRiPf3Q0w3+5OQ+D0mGqvRWb2e2ydnjhQTM4lZTelzxL7/jPiJFGMEAPnjJ8MIhV0O+b2JwOcoQEYQo4l6AmImWgoXM2Kq0kDy9bDQdbTO1Oeoac5/QTrbkdV/BLIGjgIAREqHAgBWLP+WKyt2NJ3VG1xKjAyqTlyXOTIVjJsfpKdIlEgieX6Z+By5jpk8c5RIuq/DUvysfdRPgw/ll9fPMkfKFAiecjv3JxwyFKyWh1lNIVe3hPIL2yrlesGCBQCAaPnu9v6s0qEYfsN/YISzEDIMhLOcCNKCUfsBAHJG7Iu2lZ9zzJHscj5YWsn5zsRNwjBHahM6IUB74w7u+IqVbuZI51nJFUO3A7EX2PeJVY7itVthxmMIZWWDmEnEq9cBAPJLrRxRIQOIpJSjREsdOqvWgcStZT4Wv/oQyq95AYbBLxOSJUSrKWWq3+7aJzJHnVXrUTnlZpBEHEN//iQiRQMByMP+VXdC9JmTZcimz46+082LPsCbn69FbLcTESkdCrO1AQBQPPFCFB12nnVOH2KOAuUoQEbYGWY1CnE2IVLvKubI/sBks23610d00x6U9K+REIKWZZ8CAEqO+zGMkBXqGy3bDQDwzTdLuPKuQYqYgkIjb1vuUAuXdsTn7uEVpYzMarJwcuGvJR8jUwr6Pkfex+JCQkdZaDGrpACW+cYPbZ3y6B59vx5nkAgbBpKCg7Z9+UJ9VDb/gVl27/WEc+emcZ/X2dGOb7+1lPdo+R7cMSOcBSCVrDRkoPSkX+B7Q2JYPuoE1LabiA6ylKmFCxeCEAIjle1dBuqPA1jO6DZLLLwevM8R0N7AK0fLhYmGdZ3SJoUyXWeOWPaSVY5ATMRrtyC7fA/sePdvaFv5OQCgoP+gVDsGwgUWi5xsqUV8x2b71M7WRsRrNtlZouO2Q3bKrObjcxSv3ezaJ/o17fjgHyCdVoLdjo2LUTDhROt3XJ85kjlku5kj6y8hQLK9GXXTn0BdMgF89SkGnvkbAEC4qAwlx1xin2Ob1fT9yHsMgVktQEbgMmT3mM+RVa84nroGWMUg7+Wn4ehNfswRoU1oI9FYBbOtAQhFkJsyNQBAdJClHK1bu5ZLjW+abuajo91ZMFLVdkLSg8h0DzVz5HERHvC616ywjlnNESqTPEeuY+D9QuJJ0/Uc2dPpwML6VKg6/TalQ7Y+c8QuByPKYjDlWNAB2S/hZ1eYI1E3lDW1bd0KmKaJcH4/ewAXYRgGQgZQeMD3cPf9DwEha46dNXAUQqEwampqsGnTJqsNhSzsNxw3nefnNqux0WoEHY2WiSirbDcgFMHyb7/FZ599xp1D72G8oRIVz1xrT1T4MgrBoN+fsT5snHIEIF69AQBsxQgACvunQvYNIFzQL9VYArGtvILXsfkbVxtstFrL0unY9vjP0LFlGTp3bEayowVmZ4fV7g53fqqOLcvQMPtlVDx9DRrnvoY4Y07r2LLU/i2PVpNfu57PkYGamho0fvUq6j99CkimWFkzgYbZLwOArQRS9CWfo4A5CpARumOQ1W3DRbWLofzw/pjkh9SskuzcdL7VzgqL6o+WjYYRccwP4bxihAv6I9lSi3vuuQf9+/fH3LlzUdk5DOawA7k61q9bg/1HW3S3biI2wJqV2gtoNu1AKKeAZ/m4a8vMIVuqbNLoP6F+SyZGvm5gjgghXE6WpElcM03WZEh91FifCtV1t8ZUDtlaYlvyCP4zWhmyU9ej8rWyl2fxMBH7QTxX1tamldZgGS3fQ/msnGVurPtim7+zsjFg2GhUb16L0aNH45tvvlHKJjpZ02Jim1xbAGKNFguSXb4HcoaNRfPC9/G3v/0NkyZNss+hdTV+8RLiNRtR+/79yN9nElevbFJkR6tpLqNDWR1CCNats0xn2cPHI7ZlGWo/fBDZI/blyhcwZjUjnIXsgmLEWhrRtupLAJZyGa/ZaOX8OfgsAPJQ/toPHgAAVE35rV13pHQYBl/2D7RvXAQAyB9/AhJ12xCrWIm2FbPscg0znrN+hLOAZBwdm5baLJ80J5K2z5G7LwkZwMMPP4yGmc+7zqcKWu7uB3P7vSKMdzYC5ihARuDMJz3MHLn9EARZiJz/8WJ9PCxurjrSNRvSEP7sIXu6jkUHjwEA/OUvf8FNN92EV155BZvef8RFfW9a7+SLUfscybhngg8e+i0qnr4G2x6/AjVv383Lz/nR6JtkuBY8mCMuGsoOV3PK6TJHfsouO7DHJcuHAM6zzbKVFPcxEVwSSE153PLxypE0uk/Y1mWOpObjNLJ3c+dJKlvxtcV0ZA/fR1lPiMnHlTT5N2j4XvvZvz/99FPlfWZfA9Y8JWWOGPk7Uj5H4YL+yBt7HADHgZzCNoV3tDhtCMv4eCnfumY1Wm7+/PnYsWMHjKxs5O/trAdW/d8/cuUpc0SvKL8fv05dXurcRJNjcnQcsq1zGnZUQ4ZE3VZUv3q7lYsqFEHJ0Re5FglmUTr554ARskLpW+sByKPVdEP5ZSksQobBRRPm7X00zvvVfVyZ3N0P5bb7EnMUKEcBMoJfMrnuAK1Vtt6SWC5ts5pQRgWZLd0PlCaPDtnbdazf8T/FL667AWeccQbOOOMMhMNhmJ0d6Kxcx5Wr3eFEmCgjRiQz3FhTLVZ+OdUaDMwkOtYvQCtjwhMH/Mx8jiT7JMqmRDfSZ448brpJCOc/JAu9Zv2p3BnVdcO9mXc8HeaIyVslnmtHqwkV2qH8qsFIIpNzTE84WYQRtx3vwOpFXwEAcnc7RFmPFUHmyMNWO+ni61BSUgLAykFEj7161UQctccAuxz7DbPMkTuUH4xZDYg1pZSjwlJk9bOUjS1btiAWc8zQ9LoSDc6yJm1rvuLqlT/+zAbmF198EQDQb+yRyB8/GbljDrfaF5yjcwqKrGtKjbpjjjnTWsg3nIVISTlyRkwAwDtQU0YxmmKOvp7zOVSgSTrz9zkOkaIyzizab9JPEMopsLcLJpyIrFSASLzKYnHSiVZz+xzJM2Rv3LgRADDgjF9j4Fk3Y8+Dj7Uj9XJGHWBH8LLnAOm5MfQUArNagIywc8xqlDnyl8VrXaB0FSexjnSYo2RrPTorLdYnd+T+ruNZJeX40x8vQWm+ZW7bY489sG7dOs7PAADq6pzVzVWty2a4bdVuh8y1S+YBZx3o2m+SDDshj5P498La0PE5IoSgad4bMCJRFOx7oq9DNr+2mps5YqNnIpKswuI6ctFIyL1eFUe4pfEOCEoZ53PEDPTcOZIkkJwoHlSn7vfn8vsXhIhtXoZ4ZwwjRowABoxQ1hMyDCaqiP+GCvoNwAMPPIDLL7/cUo5Gpd4BCCkdmA32WYrKs2E4+5ImQUetpXCEC/ojlFeC3Lx8tLe1YuPGjdhrr71SFwaQRBxxZgmU2LYVtvlIdu20LVEePzQ3N9vK0YD9T0AsmoOyc/+A+k+fRtP8N+1yOSMnYPCeE1L3wmpo7xMuQOWwSVb4PTGRbG20rrOtAYSYAMIus9qi+bySJ0P20HEAwOWiyhm5PyL9hqBu+pPof8p1MEJhZJXthnjtFnRWr0fu7gdLfY5Ur717+RB3WcOArRxl9R9myZaXhyFXPolkUzUixeUQIUu70VsImKMAGSFTk0NabShm/q4PUzF3dtghyWzbw+QmlktH+WtfvxCA5bNhO10q2gYs5QgAWr/9jCtTV8tE5Sjal9331qpNrn0rF85m2ublyCiU3yNaTVz2A9BbWy22ZRkaZjyL+k8eR920R5TvVKxyLf55808wf4azbEU8aboHfjjXmiWJ8BFXNWcXfBWvCVAPEjLYGc898ryI95DK4++QrZ4E+MGlkKWef+ULv8K2J69CbJuV/PGYY47xZPgMg10DkNewCQH23NMyJ69evRqJznbUf/o0Pp36LscWsZ80m4rBtfAsY1ab8e4raK/eCIQjiA7aDYZhYNhIy6F37VrHDG0SgnjdFrDx5p2V67h+wyvPka7PEQA88cQTqK+vx5577omSMY7/DBvplz1iXwz6wV2IRLJS10RlSLUbCsMIZznKjJmE2W6xvQnBrLZm5XJfmaIpxTZSOhThglJESociq2wU8sYcjmFXPY3cUftb5QZZ9659gxVd2BFPIrZ9NRpnv4KOrcvRsWWZ7/tIIQsqiXW0o7raMgOGi51IvVBWNrL6D4eRuh8s2MjE3kagHAXIDKzvSg/7HIkdtTizk81a6H7AWwHyX707Pb8calLLGe1matg6KahyRFE0ajwAoJ5RjlQdlGyG21rtVo4qNznZe12h/Eop3XASYuods0P5WZ8jRY/TWbPR/h3fsZmPFEsmYKbywDQveAfL583Co3+4Gh2bLLYtKemYTcYPTWZWE1mi/KibRM8kzxGVh21Xzmpaf1uXz8SWB3+I7Su+drXJggjnccc0RXPfI8v0FKtYiUTdVjR/Yymc48ePx4Rhxcp6QoxZLUl41o4QYitHmzdvxuJHrkfT/Dfxp5uvh8kkKAxxzJGpfFY0lL9t9Ww8fbflgFxy5I+QVWSZ6AYPHwkAtkO0dV3ENqllDRwFGCGYbQ3YvMVJviq7ZQZzTbp4++23AQA33HADwmFHwc5illsJp5Zaof2YKp+SEY4gK9+679QPKM6Y1QghWL3CrRzl7HaQnUsNALJSK9uHsnIw5KePYfCP/2HnTWJBU4tYDuQPIZYwUfnvm9Dw+Quoeuk3qJryW3S2NLnOA1Sh/Py+ym1W5JwRzUMoOz917dLqbEQ8vpmdjUA5CpAR2FdXdy2itNugzJHwQYn5aggUbAZ1zPTyOfKRIV2/HJr1NatksLIMK+uQIUPs3/99dyqGHH4GAKChznHQ1qW2AaBFwhy1NjImOlZ56UafIxnsUH6GLVIxEvFaJwQ52VrvKLbJOCqe/Dm2P3sdzFgbYltX2OXaN1gsneWQLcjIKMyyxTpF5SgacZfJ1HRMn0tEuoK6wyaRZBw73r0PZkczvn3vmdS58jodplP9nuvKRWGaBJ2VjuJMk/KNHz8er1w5ETecMEZaD+uQbZr8+2ASoH///ujXz2JNW7dbSktLUxOqN6xk6nDOSTB5jmRpOwwDaJr/NgghKN1/MooOOw+5WZYiMmiopYTccMMNdn4mAiCZupZISTmyUkzK118v4K5dhXQy/m/ZYr23+++/P/duU38eqzFLKaRHnXQO7naiRTT/kfXNsg7Z27ZtQ2NjA1c+f/wJGPT9OwBG+aGKiPU7D6ForlT27GHjrJQIAFqXfoyGLe516lokky1LdnHb/Q1WbLVM/JHiMkcxlNbmoC8lgQyUowAZwfShqLuljVS1ogN2XKS9iWJGTf96zbZ9RGedRXVAOzXqdCgFU9/+++9v/z7yqKMRLSgBANQzypHSIVvGHFU5SkYo13IAbWmQ+y9Z1epfnJe/hq3MSBhFjjmSKEck0WmnPwCAZFsjEklrQInXbUOisQqJ+grUTnsEiQbHyZVGIFnLh4hsIrGvTcocCVpIxMdpO513PEkISCJud65SsxoB2lbPcepPLdaaCXOUqc+RSYjtH8di/PjxyI2Gse9QOXvEhteLCjaB5ddz5JFHus7bsvgL+zerSCSZDPey5UM6W5tsk1/5pEthhMK2crT3AU600yOPPGLLRJmXcH6JnUvnWyZhpJQ5oikwNG8oIaa9iPSwYcN4n6qwYzJKtjfRBgDwzuwionRZEZs5cnyOli610ixE+jkTKiNsMZ7UVIaw21SlQigrB0Mufwh5ex8NAKj86HFXmZYqtw8jIFG0Ca+2J5p2YOq7b6bkdSaKfsxREMofYJcHP1vsmTeZfm5itJoYwi4uqCnKJVec1KwSV46oTSodW79Fc2q1bQq7U1b4G1ltOzj11FMx4NTrMfgnjyASCiFaYA1I9XU7pOVZiJ24GY/ZSfKGXfsiBl/2EACgtbEepklzsjDl0/Sn8vLTkuU5ktXtSsNgJlHx7PXorGKi9cwkGhtSgwPjVNu2fCZ3LmWbEkn3EyJgmCMd5UjCLvH+We5rUaGzrRXbHvsJ5t5zseUIzBxjw9JZU2JrbQUANaPhpczr+xy5B7QYwxwBQCQatRyyoTaB0iSQtA5ZVN/FF19s76PsxIoPnkHb2rkAeJ+veNJZG8+dDd/AlqVzAGJi6Og97QVbc1LK0X5HnIA77rgDALBo0aLUdTLfYX4/+5ytW5yJg9ct042+NdsaEY/HYRgGBg8e7FL888dPBgAUT7wAgKN82WY1STPRQqvfoBFr9kQwmcBdd91llRnMMHqpuoqP+AGKJl6AwZferyU7i4L9TwHgRLuxkJnpAfm7RN+DREsdtj3xM7zx8ktW/fueyIjrrR3JIjx7C4FyFCAjiINsT7Yhjm0ynyOv86UjChHLyOGlQFS9dDPqpj6EjpSphyQTMNusiJNwvpo5om1OXbYdH31bifwJJyE6cCQMw0B2SqlqqKtl/HjkArjCwVN+Ftl5hQjlFSOc8l8wzSTq663OloDAjHeg+rU7sOKjFzKaoXn5vbD10dkl2yHSXx1bv0X1G39G28ovkKhjFuJNZVumqQwSjHJEceCk061jDVUw4x1WtJrEZERl8VN8ALnTNl9e/0Y1V65HsrUe7bUVqHnrbnR2xlxlTMKHbHc216G+vl69tppnEkg9uVyh/KajYGYPGwcjKwdHnHwOYwKR35OQwQ/wbjYSOPPMMzFw4ECEojkYePZvsdsYK5Ksac6rAPh8UiwLIYtW25RinCZMPM6+/tyUA30sYeKCCyzl45tvvkEymUwpRw0ALOUonFo7bMsWhwWR3UeqDMrzh7mRaLbY3cGDByMrK8vFivQ/9ToM+flTyE35H9LjtllN8iFFCq1+o2Hmc2jfttJ2IZgz42N88cUXKC4uRvHECx2Zc61vPJSdh37HXOrKOK2DnKFjlYxTq4I5crOQzjcS27wUSMYBAEcffTRyd3fSQviZ1bz89HY2AuUoQEbgGALXsgQE90xdiVfmyz8s7TaInGoXw7DF2at4vqyv85iIC3UrHGrjzoCXaLBm/bRDNkJhhPKKlHUSELTGErjqxYW46sWF9v5wyEB2ijlKxOP48MMPU9chr0dUEhONlnJUMmioFeUTzrL9D2pqamjjaFsxC+3r5mPpm4+ita0FunB0Tcm9Zq7NKZZSjlLbsVgMX0x5EO3rF6DqpZvRvuYr7HjXSQpXeMjZiJRY4b31KeWIMkfFR1+MIVc+iUEX3YsLb7oL+cWlAAjitVtTi7u65VGZamTwN6v5VmGjrd7JUZVsqcPiGe/b22y0mtlaz5339ddfq/McEbdMMjm9INadTCZhtlkmnwFn/RYjbnoNl998t1NAcdtChsEn6+MYtpTykpuLefPmYfwv/oWsfkPw+EuvA4Dl/N1Sx+XU4ReeFWROmti8xIq23PeI4+37QKMLOxNJjBkzBnl5eWhra8Ott96KznicZ44KLeftrVsZh2zJLaPKoK4PZTLlXzhs2DD7vnD1hcLIKnHC1W2fI0kUI0XxHgfZv5tXzUFnqq9bt8pyxD7nnHMQHTACpSdejeyh41B0yNl6wnrAiESRPXSs9Fjtijm46KKLpEyRuE130SS4Rx93PD788ENe4fUzqwU+RwF2dRBu4OBf5NVVLXh0xjrc/PrStJwbRah8jqQO2V5shtSJlf71lk/FHCWbnAGQJDqtfa2Wb0+0sJ80OoRtW7bIY9gwkJXtOE+edtppuOeee7S9ghL1lnLUr3y4vS+UZylbNKSWAOiscajyObN4U5UXTPt+uiGLVnPWVrO277nnHix493lUv3qb6/z+37sRpcf/1A5nrrOVI2tAy+o3FFn9BiNn2DiEo1GUjbQiomLbVkjXVmOfW4gxA6ngb1bTf49jDXwW48/+8xia5r2J7c/fiNYGi20wTcf0Q3HmmWdi9TcLIAPxvPd6clkDmIn2dV/DjLWhvbURNNw9nPJPk7F8ItgkkISI0WpOuVGjRiE7FTk1eOgw5A4aBQDY9silaNrqOP8mTcasJjyopYvmo6OlEaGcAuw27gC7P6FmtVjCRDgcxn777QcAuOuuu3DR+WcimWJ1wvklNnO0jTGreQ2+sqSi0nKCcuTnT2MzR0IoP4uC3Q5AUYoZSrbU2+bHDWssn7x99tnHWtfuwNNQfvG9COcWasnqh/yxxwCw8kcVHng68vY8AkbKkXvKlCncEiSAPM8Rvaed2y1T7Tnf/wHy8/O5cio2kiII5Q+wy8PLrMaOMxUN7Zm3kfrrcsjWDeVnjruPEa6MUgZhZkzBpvinHTE1k2QXyRfsZOVyOZXDovUNw0DWgJH2vttuu812TvYDdVZmlSMaRmwrR4Qgts0JB371pedBUhS4H7xC+e0yzG8xlP/NN99Unpc93EphEM63zIr1tTUghCBRm1KOmOgfkxCM2s/KQty+/msu2okVhO4zDCCicqBJQWZWy5Q5iqX8vkYdeRbCBaWor9yC+s+eRmflWqycPc2umypH/U+9ATn9h6KjowN//7/LYMZalXXL7r3fLDu2bSVaV30JQgjaVs1G9Wu3o3LKzVi82mJ2QzmFtmOvn/O8VYZdPsTb/5BuGTDQb99J9n6ahgGgTDCRtrl0kaUsZg8fj1A44pjVGOUIsKLVRo+2TEpfzJxhKy4hhjlqamrEjh3WfuktSzWtvXxIk6Ac+ZSnioGXQ3bShM02JVrr7YngujVWpN+4ceOk0ZddRcF+J2Po1c9g6NXPoPTEqzDwnN9h6FXPoOwgawmSlmXTufKi6GaKvTVjrbb/4IEHu7Os+zpkh2j9va8dBcpRgIzAztTdfYnzBayr0TfbuNogtMPk94vMkSWDh1nNi1Xy+QZl+TsAINHIKEepCDXKHOUWD3CVF+WSpeoPh6zuc+DZv8WfHnnOWgwyFkMDmxDSA9TniGOO8nnmKNbezi1VMvOTqWia+4ZW/Z5MnFAGYPJUwUBzc7Mdai3CyMpGpNhaZ4oyR/W1NUjUboUZa4URidq5W6x6gdH7W+tQxTYvRWesQzooUzkNqJ2LKWTKE1H89kKypR5NG5YAAIoGj0K/SVdwxztj1mQhkUjaZtic0Qdi7DWPory8HO0tzYjvcJujvRJ2erGzhBBUvvgr7HjrbmxeNg/tqWU04tUbENtqKcmUXQTEpV7kdUZCBhdyzeeDEtu3/oZCQMnh5yNntGU2SrQ4EZQJdvkQ4WPfmFpjMGvAiFTghbXfUY6s7+jCCy/E+vXrcckll3Dnh/NLEMrOs31qBg4ciK+++sozb5WuSSfRWAUAjgO7z8hPXzF7CRmFiZROEBItdYgnCYiZxPq1FhvTU8qRYRiIFJXBCDm5msK5heg/4XgATh9HIfplmanJSMMXU0ASMURKh2H3PdypIPwUSPod9gHdKFCOAmQGb4dsZ3vDDvUsWLcNP58jvkVWLnrMazD3N6vJSrDMEXXMpLPhvNIyyRlM28SdZwegyzIAWf2H48gTTkV5uTWDrKms8KzPkcliLErKnFDfcMphk/oc1VVtBYiJUE4hdjvu+wCA2PZV0IHNtkltO64fTBJPYOXKlYjH5QxVpN9Q2wwZSZlAPn5jClqWfgwAiA7ekwuNJgQoHro7wvn9QBKdaK5Y457JMoyfHnPUdbNay7JPse3xK9BWYQ3o+aVlyB93LM648a92mbZUWoX6+tqUSctAOL8EJJyNMWOswaR+xrNoXvge59dGoGavvJgOk4aRA1g75yNO42ma+xoAfpkJcGY1+VCWHQkp11ZzKamMghw3DTvknFs/jPE5EqPVNqSUgqzSoZYTu+CQLX5Hxx9/vCN/dj5CWTkpQZxyZ599NpKSd5G2LOtfrCr4CQ11Zh871vLX8V82MMUcpV41mW9T0iR2GpBESz3ipolE/XbE43Hk5eVhxIgRdv6snYFoKkCEKvIU1c18kIFJCJLxOFqWTAUAlB7/U0TC7qzzfvcoyHPUB/DII49g1KhRyMnJwWGHHYZ58+b1tki7FNj+2BUpxGx2STmiM3+XWU22BpBMAVIP5rrLh6iYoyTHHNUitm0l2lZ+Dhgh7HbUmT61QrqOUTjEL8tA6fra6kpXWRmSbQ0AgIJ+jlmPDnw0H0tDtaVoRYrL0H/PA1PyOwOVF7zYNjlzZP01AFRUqBW8UHae/Tt/3xORNWAkmhrq0DTPYrSyh/ErxFM/l0h/i01q37FNMijzJh0/p2yZWU3lV9e68gvUTvsX2tbNt/clWupQN+0R2/8MAApKrRDyPY84BSXH/cQ6t9FSpGuqLdYhlFcMIxRGwiQ2AxHbuhx1Hz+GuqkPI9FYBWImOZ8OEewsnhCCttWz7WSkiXrnvm9a9DnizDZlGqm/EaDHHEUjIS4JJAci3zQMK31C2M7jwzBHSSdPlfiYNqyjytEw7h7kCGY1ikmTHNNd0YGn27+Lj/gB8gss/5yqqirEU6wPC3YNNxE1b9+DbY/+BPGUmZeYSdsfbty4cSnZvd8xJ1pNHZGVNB3mKNnaADOZtCc9o0ePRigU8lX0uxO0/zDbmzjlcGu9xYB2Vm/AtievwvQXHsSHf7sWJB5DKLcIObsdKPXz8/M5igSh/L2LV155BTfddBNuu+02LFy4EPvttx9OPvlk2/QQwB9eZjXSTcoR7XjF2aRsZiebhdnMkVRxosf8ZCD44RPuxR5Fs1rbaiuiJm/s0SgbtbdnnYQolCPDYJYWAIYOtfxsdlRvd5V11Wk6kUcFxY5yRBd8XLHCSjdAlaNw0UBEU2HDImWugumhUMqUTVtpNgxP5cjIyrZ/h3MLbedQiuyh/P0ksPzOslLJ5TpqK6TMEZuE0k85kjpks79TG2asFTveuRctiz5AzRt/AUlYDETTV6+BxPnZdGF/i0FMJE17kKEO2VQ5ovsTSYKRI0dy57cun4Ftj12BiqeuQked+xopWP+11m8/Q82bd6HyhV9Zx5iV4Tua6rhkmxQhhjniF4eVt5cdCTuKhCRqiYWo9ND8X8mWOrQsnY7W5TM5ZYQyBySZwPZ//xLVVallQPoP41gq26wW57+jkSNH4td/uAPFR/wQxUdfZO8vOfKH+Hr1Vuy+++4AgLjAhADM2mriNZhJtK38HMmWWlS+8H9INNciUb8dSCZsNgfwz+FjCD/kPkfEinQ1QgAIkm2N9vdJ+4PoTmSOwnnF1nURk2Mht6WUo/pPn0aibiu+eO1JVK2yIm+zh42DYYSk98OXOfKI5NvZ+J9Uju6//3787Gc/w+WXX45x48bhscceQ15eHp555pneFm2XgReVzm5v65JDdqpjFd5SmRlB+jHRAc3DDOS3ZlZFQzvWVLv9plizmtneZLMcubsdLB1oRVmlZrUQn1yPdoa1VdYAF6/dirY1X8lTC7Q3WRdlGMgv7mfvp87dS5cuBSHEYY6KBiKrMLVUgb0KuDcc5kjPTMkuPLt9u3UNg/fYByJKjvwRtx3K78dts+HQgKV0JZPEzhQcq93meo4EvHLjyxxphvK3r1/omGjMhM2+tK+3WKSB5/wOBWMOQ+6Yw1HQzzIRJkyCcMqvpyWlHC352mKqo6lrSzLMkYhE/XZUfP5fNXPEzAzaVn5u1SdhjlQIcz5H/ma1aCRkO86KkV2y/De0NsCKhgKs/FW1HzyAHe/eh6amJlfwRWfNRjvqyQiFEcrO55SovCjvc8Tiyut+iZKjL3JFjCYJQVmZpbCarY3Sa7OuiVfo6L0ELOW45vU7Ea+1/MLGjh2LUKqD8nXINvhrlDFUSUJghML2MzFb65Fssd4ZutQQ27+cNG4QHvzB/j4tdwGhMPr3t57Z1n9eYmcq31rfBgAgzW5CIXuwFUkqZ4684ThkZyZud+J/Tjnq7OzEggULMHnyZHtfKBTC5MmTMWfOHI8zA6jgxRw1tSe06miNJbBWUEJUofwyeJrVZOW9/GcYyKLKSDJuz+YiwhpqOSP2lQ60fNvuTp0O3vRMk4Axq1WhedEHqHjqKtSkEieKoD4B2QXFCIWdRVSzSofBCIXR2NiIbdu2oaHKMq9Fisps5ggM6+QFh4mTXJOtbLrLG4ZjVtvzkONQfJQ1o+83+ecY+ovnkT1kL64uzgcGwMBB/D02iWVKosxRZ32FizkkDMtgGIaLfRTB+nF07tiMtnXzpUvktK/jze/x+m3orFpvMQlGCDkj98PgC25D2bl/sH0uWCfb1oZaVFRUYMrT/wIAlIw/1qrHNJXKEQDULZ2Jzs5O6TF2smAK7BVljooOPx8RmiYiHEE0NYABTkQjoMschbhoNRbiqyEuIRMWFF8AqNi01nHIphFjDY4p+agLr0615dRu+xxJKGOVD5ZpwlaOqAmahb3wLF0bL6X02OxbOALAQGfVOntdP2pSA/yd/u0M2altaeQhVcyoaa2lTqIcMQpsD5NIJgEGDRpkb+9438rAva2hHWZHC2L1PKttRKLI2/uolGwy5shb4L6UBNK9FPV3HDt27EAymeQeOGC9ACtXrnSVj8ViiMWcDqepyX8Q+V8AN3BI1tmhaOrQCxM/6YFZ2NbQjrevORL7DS8BwES6aPQAslkY3eWVVVh27M1fHIHnZ2/EW4sr0NbpVu4SzZYzrRGJYshPH0Xdx4+iZclHyOo/ApHCAb4dAJEwR3Twdq7VYY5mvv8aV7Zj4yLkjz2a22dHPhWW8gNcJAsl5SNQX7EBhxx2OCorLOUoXDQQRiiMktL+aKirRfvGRcgZPt52iFZInvrfQxFlDtkZsuEoR0X9y1Ay4lQUHvA9hHKLpPeKHUAj2XmI5OQDLaxzMkHCdJijRF2FK90B73Okb1YjhKDm9TuRaKiEUf0j3Nz+KY444gigaB8QQtCxcbEtY7K1Hk1fv4PYZssRPzpoN4Sy8+3vgbYZTxLbdNXaWIcJEyagtaUFodwilI4/Ck2dlrxDhw6z5Sk+8kdo/HIKCvY/Fe1rvkKytR4zZsyQys4q8CTe4fxOdCJevQGANZsfnB/Cqun/RaRoIPLHHYvOVLK+cJETXcn5HCnuVTQSYvxzRObIzeABznvN+pdRVGxcD5K3n3U8dc8o43XuBT/Enudfic3zNnPfeI7CrGbJJB9Y//LBciystson29zM0duLK7CupsXOQZYVNtCZdFJk5I46AImGKsRrN6NlseV4fOyxx9rn+/nTOMxRSk6ZWS21L1Jchnj1enTu2OIyq2UxWpgBQ6t/zBwEAwc6fYLZYblJbK1vR6xiFUAIQnklOOnHN6Bw3NH4akOD4wQvgX8ov9xc2xv4n2OO0sXdd99tpWxP/Rs+fLj/SX0AjW1xrKlq7rH6eYZA/SJ3JkxpwkMR1Pw2faVD06qcNGWQh+tL6Az7mLqu7EjY7nBaYrxy9OvJo9H6jRVFFS4qgxGOoPTkazDgjF9hwFk3a8lrMUd8p077OzYJmuiDQpOydWxdDhF0Jpxd6J6ZxwqtTpUqRoDV+RICDCizJgm17/0d2x67AvEdW1znU+gwR7LFWg3DsM1qRSk/HNuXQQJWOcouHuBej41YAyDNpm3GWrGjlvebYjObG4Yz2040VqN58Ye2rxAFZfsSDZU2a1E9awruvfdenH322Yh1dCDRWGXlJgpFkL+P5fhLFSMAyBl1gFUHZR7CjvmEdXqura1FSWl/DDz3D8jJdgaSoQxzVHz4+Rjys8dROvnnyB4xAQCwYIE8QSRrVjM7nG++fcNCy/wTjiB7+L7Y+6SLEB08BgX7nYrCg85E2ffvQL/jf2ovb0HvFYUYVk9hfR9IXZtwUMEiG5BnIQeAyk1rXdFq9BmMGr2bLRPLCIl5jliolKOv1tehCZZyZkqYIwBYtq0J62osBYAqzIkUOxIpKUd08B5c+e9973v2b7/vnh72ypBNd+UM3xeANREyU87rlDnKivDMkUo50uk3/WAS2EsPUQFbYgk0tsdtpTF72FiMn3QOImx0INzKdcjQcci27nlXkgd3F7qkHHV2dmLVqlVIJPRMJ30BAwYMQDgcRlUVH61QVVVlh06zuOWWW9DY2Gj/27JFPXj0JVz14gKc+MAsbKrN3CHaC7KoJNkxAGju0H8/CrMdMlOcdXpBnjNEfczxkXHXZRhOB9YqKEdNC95H45xXADhh54YRQv644xAdOFJLXlkoPx0UnOy5BEceeSR+//vf4/Jf34nyH/8DQ698EgCQqNuKhtkvo22N4yhuUuaoqNTVAUUH7cZfXySKrH5DYBKCEOuXQUy0b1rsIbfaTOkUcn7KmKPCfl7MlAW6JhwARKLZrvtJCEE8aSKUlYNwKsHflo3rXWU45ihVR+VLv0HdR4+g6eu3uPJ0IIxtWSqVaemcz2x/i2j57sgaOIo7XnDAaSg+/PvcPip3wiQwwhFbuQWA3939IHKG8TlrcvPycd3Dr2Hw5Q9bz6h0KIxwxH5+3yxeJJWNKg3ETCLR6GRur3njzwCAvDETEc4tRE7JQAy+9AEUH3YuDMNA7m4HoeiQs7k0CbzPkRxstJquQ7ZhAK9ffQQAoP+p1yN3z4m2ebVqy3r7vaH10qi6kaN3YxQx55vJjaael8TnyCu1AWXwxNB0GWgEY7yBKkeDES13cveUjNgbgwezK877MUeC6dzDzS9ntKVox7Z+i3gq871tVmOZI0POxugEIejAJIQbK82OZqzZmIrYa7F8sSKFA5VRvSxChuHLHEUjKVOmIp3CzkRGylFbWxuuuOIK5OXlYZ999sHmzZZz2nXXXYe//vWvPmf3LqLRKA466CBMn+5k/DRNE9OnT8fEiRNd5bOzs1FUVMT92xWwotIy/9GQy+4GH63m3UH6mdbYmW9hjqMc0XpUM1ivNjlZPVglmYmIXR6htZPvfB/8h7PqtegbQyHzPZjys8NQnEsHISJhjkTlCAiHw/jzn/+Mk87/MbLL90A4vwTRQVa0TePnL6Lmjb/YTA9ljnKLSl0dULTcme2Gcosw+LKHEMopgEkIYrEOrmzTvDfQIVmd25I69ddjxivzOSLJuB0JWlzqrxxxg3Uo7JoB17fFHb+QlN+RqByZxBHGYNYCo8617Wvnc+WzwiG0rZ6N2g8fAmDdJxaLZ32I2DbL7J49dCyy+jNZyPP7ofTEn7tMRnabqVEwf+wxiObm41e/+hWOmGRlHqaDAWANCIN3H+daPJQ+8yVLlkAGusREsqUWMMWJiIGig89y7okftH2OrN+iWU18NRwF1cB+w0tw7aQ9UDDhJJSd83t7Pa+qzeuciRBd/DXFHO22++7SNc8ocyQLbJAt6EpBHZ1lZjURNouRikyNlJQjZ+R+AAwU9euP159/nCuva93yYo4osvoPR7hwIEii05bVZo5YnyPIl8ZhI1+7AkKABx98kNu3aMk36NiyDG2rrAjdSNEA5TJLLEIhN280oCCb246Gd3Hm6JZbbsGSJUswY8YM5OQ4NNrkyZPxyiuvdJtwPYWbbroJTz75JJ5//nmsWLECV199NVpbW3H55Zf3tmjdglgiiYa2uP27J+CV50h8rZvavZWjJoZZKmCUI9FJ0wuqxSLFtZ/Mzna0fDMN1anEirL+KcQsjyAyR3vt7YSVG4qVrGWdUiQUchYdJdaCmSzoQMrmObJlZmTsf9ovGSdwgoYvp4AQ086qnFNc6uqAWOUoe9g4O7yfALjp1rsQ6TcYRYecA8BaM65qym9R8/Y9qJzyW1Q8dTUaPn/RShWgtlLakEWrNVVYfi8lJSUoLPXOHi7CCIdd9/OdJRWYv9Gi+rNSfkfbNq0XziRMnizr/pqxNqfeLL5TzgobaPjyP/b2gDN+xflf1W7fgviOTQCA7PI9EC3fAyVHX4LsoWNRcsyl0rX06DOlqSf6n3Idbv7PV7jvvvvskZQd6JImkQ7slDnasH6ddGkROpB0bHKzXqUnX2OnQtBxcjU8tiiyIyHlIq2qiZK4rhiAlBJooHbbRnSmluIIhwy0rZptKbFGCLvvsYdUEWPzHFU0tOP+aatQ3WQp+l7MEXU+12GObFNsyiE6UjgA0QEjMOTnT+Ljr5bg+OP4lBPaeY4Ydlhd1kDpiT+3t/Pz823LBpfnyLD/c8miSxx5iW0SggsuuADDrnsJeXtazN+0D99H1ZTfIlZH04KUWeOMcDnUaZ4VlW2rODcLc245nitDmdS47uq/PYiMHLLfeustvPLKKzj88MO5jmufffbBunXrPM7sG7jwwgtRU1ODW2+9FZWVldh///0xdepUl5P2roodLU5Ui8xhsVugGLytbZE58jarNbTJo3BoPSp6+MlLD8bP/v21tE1WNnrE7GxHxTPXItlYhX+2r8TFJ3wkN6vBmcGKylF1pUMxFwlmFApZJxlmZk0E7igb0SGblYtlt6IDR2HIzx5D5/Y1qHzx12hb+Tm2blwEs8OK9Bu4276uzo5L8heJOvUSYOKxJ2DolU8i0VyLpvlv2sdoSDgANM5+GaG8YpC9LncuQIA0z1FqX90myxx18MEHa7GALAoGDPXsvClztH3LRsSztqFh5vMomngBTHIg5+8SDhl2RmMAMDvbuHrqt2+xnZfLL/k7sofshd2ueRrPnTEARxxxBJrra5FMvQrhlNN98REXoviIC5Wy0WfKzoLpPbFZ0dQgZhKLQZWNCeHcImQVDUS8qQad1RuQk1qHjoKaIGhGcRZ5ex1p/9aZjbP9uepRZUccRd9vYuREDLrrD+cVIzp4DDq3r0bLuq8RHTcZBoC6Ty3zceHBZ6J/aX8YRgMAtc/RJU/PxbqaVnyxdgfe+MWRntdJzWoqnyMWWeEQSDJhh/3TBJZZJeUoLHQv+Or3Zotrq/mN/3ljDkf5pfcjWrkMz99yCSIRa7jOYthGUeGw9xvu/HAq5ETCaFf4hdLnF84rRvawcWhbPRuvPPcEVyZSNBDNHQn7nb7u+D1w8j7ltgJLERLYrEjIHUVKmVTd9e16EhkxRzU1NXZIJIvW1tZuofJ2Bq699lps2rQJsVgMc+fOxWGHHdbbInUbapjU7jKHxe4A++q6kqYJ77Ufc9TAHJd1bKp3inXwVM2K2ZDujk1LkExlxp0/6xN0dLjX5LLaY3yOBLNaRcqpechPH7VDyV3nK2RlFR9RaXWb1Sy5EkkTby3axpU1QmFkD93bTnJndrTAiOai9JTrUL73gZCheOKFMKK5XE4hNqlepLC/bb7h5MopAAC0rfpSbjqLtaFj67dOgkgJo1ifUo4OOeQQX4dMil/c9RhyRh+E8ede4zkjp8xR1daNqP3gH2hbPRuVL/zKilazbTqWWY0yPwCf4Zwk4nj3yXsBADkj97dTC5BQxI4Qaq7fgWSz5RhLc/X4wWYemHfacVy3/oYMw2YCEiZRKvk5g61n01klMmRWWoNY5VrEtiwDjBAiqUSLALhV23XGG/ZOq747L58j8Tt0HgGvGFDk7nYwAKBlrTXJqd6+DcmmGsAIoeSoi2EwfiqyUP6OeNJ2oF64ucFVTkQkldvL7GiB2entchAJGanFgQkQClvJGVOQZVTvjgzZIrIH74ndTrwExx13nNM2cxMNw5AmxWXZbz/kZPFqwGVHjMIvjrPet9bOBD5fY/mxZQ8b5zoXsCYLLTFHOdpnSDHGDy12lxMefji1Rh+7O4sJYujtcP6MlKODDz4Y77//vr1NX/ynnnpK6rcTYOeC0stAz5nVOGbDp4P08zlqbHOOy6KdVDOgCGeSkNfNRi2xmaBN08QXX3yhMBE5HyzLHHVs/sZO5eA1QEp9AEJOJ09AfJkj2r//Z95m24QkonjihSg7/zYMuuheDL9+Cgr3O9mSXnK/So65BCN++aptUrPa4DugQT+8G6Un/cLeHnrNv1H+438AsJa0iKVm0Ow5Ne/cg6qXbsaOxZ/a1+bUb/2t32z56hxyyCHaVP++R0zGoAvuQJ4kWo0FDeffsW2TwwyZiZRRLWXSgXX/O2sY5ai13s4J1PT12/jmy4+BUBhFh57jVE6YvDiJOEjCKh9mlA8vOA7ZTDQZVTBtfzpGiUp6KEeDPJSjJEHDrH8DAPLHHYtRZ/8SAFA08QKunJZZjfU5UpTJjoSZ9cFEM5pQWDCNiwN2zohUVNZ2az26bxZZEXnRstEIRXOsiQp4JTNkAPmpwA2R2ZXJxCKUnY+8Iuv50WirWOVa1M941pUjKhIOOfnMCko506lsCQ8/XYQe1jGrcXIIHwCX5wiQphth+xs/iAzPsXsOxG9O2RvnH2Qt2fL3aVbKh2jZbi5zNGB9Dy0dCSaARt6O6DxOr4tNapkt+OD1JjIyq91111049dRTsXz5ciQSCTz44INYvnw5Zs+ejZkzZ3a3jAHSRE3LzmCO3EqMc4yHXyLIhnbHrMbqDH4+R+xMRNXREEZScQ2xTz75BAeet5frHDY8ti3FHMW2rUTVf35nHY/mSvO1UMhmbFaHxjBHYrSagjmau6GOK0M7/sLsCJpjCeTufogguy43Y0XLsHctlJ2Hgn1PRMfmpcgaMAIRakboPxzx2i2oWr0EwEncANix3hrMts14EcBdrszpJJmwfY4OOOAArFvFD0BK2RhfFS82OlJkKS/tLU222QMA4okkZ9KJhKzkfSySjdXobKtHw8znAAClJ16N3N0Oso8TEOTk5KC4uBiNjZZiaAjhyl4QfY5orQAb4u44iydMUzmw55anlKNqt9tCZ0cbOjYsAgAUH/lDDBy1GzqueYFbFgTQyx3DKUeK284xRx45ztht0aREQZX1eEMVSCKOxQssR/monWXZzRyFDAMFKeVITLUB+JtkSsqHo62pHvH67YiW7YbK528EYEX7lR7/U+c6w4adgJFmk6eQLf7qp4w47LD83qkgLooc5pgjSE1ihqEXyAK4lSNa/0WHjcBrC7balggjHEHBhJPQvOBdu2xRcQkMI4SWWAJ5qWeiTi1gcMxxOHUPIyEDdARgrzVhmoj2YrahjFo+6qijsGTJEiQSCey7776YNm0aysrKMGfOHBx00EH+FQToUVQ3McoRY76pbu7oNqqS/a5dTpnCR+/HHDW0sWY1dpZNZ9cqs5rz+qrNak49dLFLOmgsX75cHq0G9wfetsbJns4uLiqD3CGbYY6IPMoGbLspsfrlOT5CLIM2tF8uZDDs//xhUdfC+ZEsDDzrZpQc+UNH9lLLtNTWUJ0SzX3PYvWVME2TN7eaBIn67TCTCRQUFGDkyJHazJGj2HjPgEPZeXaIPOtku33LRi5SyiDEYV1CVide8fTVtsJb2K8/CsbzzqH0NWZTfEQYBcwPdJDh2FC68ojtc+QMCJZZTV5Xdko5iu/YbOdoIoQg0VKHturNAKxEk1n9hiAcNhAu6Ge/h0NLcrm2vaCzfEg2lwSSF1jcZiybqb98naG8EkRz8wEQxBu2Y8lCy7xGTZshg8mabTr9AWWOZPdLjKATUTzIijRM1G/nls2JbeYd2lnmKKuQf+4y5sjXrEb/Mv2ADlgfI7EdA0B7p1s5Yhex9kO2UD9V/Og9Zpmpfif8DN+/8U70O/5nuOSuf+O9T78EAIs5EpzvRYQE5oj2Z6yyJ0Zv9ibSVo7i8Th+8pOfwDAMPPnkk5g3bx6WL1+OF198Efvuu29PyBggTfDMkfXhvLVoGw79y3Tc+va33dKGp1lNKOvrc8QpR+42VB85Z1bzUI7oIdrR5QyzHFrXrFnjG63WsXkpWlfMQpJdi8n0NlXKzWohxiGbuMyd1c0d3Ll08HTC//mOJU+IBGHL6HJHSUKkio5L9lRSxvZG6/7ZvkfMzSOJOPbcc0+YcUdxJAToZNagMkRe3QNUwZYpqiIiqVxHYAa6X198OjrbLadrwwA66reDdLYB4QgGnnMLQE0k4QhydzsYv7j175yzOnt9bKCGrkkNcMwGLHMkZhJn0wwkkvJoNcByei0p6QeYSXSmfKfqpj2CbY9cirrPXwIARAdYSSRZJfqJSw7C5UeOAqBnxtFljughvzQe4oApPkvDMFBcPhKApfgtXWIxYFQ5yotGnNB3xqyWlxVWyufn6FxUZrFVifoKO8EjAJcPUiRkWNnwAWQV8VGWMubIVxmx70FKTk3tSFyOiFOODMNmt8Uy2sqRwBxRxY86vbfGnPoNI4QJJ5yHokPOwtj9DsbeYyylvaUzwTF7MoQEVpu+9yxbxDFHvRyxlrZylJWVhddff70nZAnQTeCYoxRDcc9Uy+/jha82eZ67tb4Nby/e5kv5eprVhFP9otUaWYdsdsBN/VRFq7G2eJW4BIRhjiyzWvZwa/HT9evXIyHxyTJSs1WSTKDqP7dgxzv3onXZJ/bx4iN+6DpHPF8mKztjFM1qdJbk5ECx9pfkOcoRe05+ttwirmtSA1KDjUb/TM1V7Y1WuLWtHAmDybp169DJLHRqEmKnGNhnH+ue6zJH7LpsfufQRJAs2lqasGG+9cwMAA1brEVMowNHIW+Pw1B2/m3od/zPMPTKJ1H2/dtx8NEnKGVgmSNdZ2zAUogBYe0zQv86SoOtRJmmesA0DOwzYT8Alt9R26rZ9hIW7essU9SEfffFy1fyEcRHjxlo158uaawaW/kM2YJy5ArtT9VF1xWT1FlUbjE5batno6O9HUZ2vs1WRpnIOOq7FTYsR978qPwbSPgwRwUp5ajlm2moeNIJl0/Ub+fSPWSFQ5ZzOIDsIv65Z2Xkc2Rwf3V9jjzNanCYQQA4cg9Lzh8dOkL7W8vxYY5E/8jWFJOUnx2x89IRwpg4Fe2KLDC9DvZ6woyDdm9HrGVkVjv77LPx1ltvdbMoAboLMp8j3Y7xqHs+ww0vL8bL8zd7F/Qwq4lMUoufQzarHDGVsXlqZGCpbaXPEStnijnKHrwnIllRdHZ2oqZqm+scA1bn21m51nXs40+mo/jIH6gvBtYM6YUrDsW5Bwy191mh/M4gpfIFE2fkoj8AhZo50nfEtJgjf1DmqKOxlj+/3b3OYLK1AWZnO5qXfISO+kpbOaILdOrOZqmS4Ld2lGEA4UK5wtKwfRMIIZj32QfYMPs9AE5CRSs79Fl2LiNZ9BEFzxxZimKBQjllQcc0dgYsjVZjotq83uPxKeUoXr0OzUs+cpU59rADcfhu/bnvj/XZ0mOO/M1qXtFqKuXOYY7cxwrLLMarbbVlus4evCfn/OzkVOKZifxsMVQcXDkViobsoThC0FltmV7jDZWY+ufL0Lp8htXWUN43Ue5z5GNWM/i/umO/2BbXjAGce+BQXH/8HvjPzw7HE5ccjBevOAw3TB6j/a2J+YioMq3qY+iKBwXZEWRHQnb5bamEw0U58vxv4RD/TlH52EluyHActHs711FGDtljxozBnXfeiS+//BIHHXQQ8vPzuePXX399twgXIDPUsNFqGuuayfDl2h246LCRyuOyqDIK8ZsXbcdJk+D2d77FwaP64az9h3J5jtiitPPQiVZTmSOszK0EhJi2T0q4sD/Kh4/E1vVrULl5AwDen8AwgLkfvIzKF+/kKwtFcPRRR8H42J1Phj/fwNFjBmJkaT7eSIXhc8wR3AvP2k2kCtGrUflSZUcUyhH02SOZz5EM1JTU0UTNagQdW5ahaspvreNFZcgtLUfLxm8Qb6zGjs+eQ+f21TCiuSCpCKCxY61syPo+R96KMUVuVtgxqwEIFw9C0cFnoX76E2iq2oy6in/hgcUf2sdpVmYRMh8SKsfuuzspDnbfbyLOPGIUcqNhPDrDO6cbNUu0Md+g8zwdE5Edyu9hVjMJwdh9LLeF5oXvS8vsvpc81Dqd6Chu3FUyR47PkWvR6dT28oomrGbWdrQXnpVUWr7PYTDef9725ctOOWNThVVkEmgVBdkRVMGZCOo6OhcO2Q15445F2/KZVjv9R8CMtSDZUod4zSbkDB+PtpWfo2GTxbZH+g1GyZgDUd3s9FMyNtvv1abHQ4p7p0JUZI4EBTYSDuGmkxzl7agxA1LtaFWPnIjcrEYzoYti0gjBgmzL5FmQE0FDW9x+PmWFfETbiNI8bK5rw0njyrl3ylaOOOXPQFbKQVuWomBnIiPl6Omnn0ZJSQkWLFjgWgzRMIxAOepFEEK6JVrNrx/18jkSO2GRlp26rBIvfLUJL3y1CWftP5SLOGE7DGfhWflXHpaY1Q7frRT//NGBOPjPlkmFpOrc/uz1tk9KOK8E5cNHW8rRlo1AxO1kO/Xpv3HboUgEP/jRpYhG5bMiFtTBUaSQ6aYXc0THaHrtqv5TNXCl4dYD00zP54gyRwRA3SePM8eL7dw6zd98Yq/2zprdhg0blpJPTzjW7OQ1A87NCnNmtUh+Pzv3UeXKhYi18uyWUjlSMEcmAa688krM3NSBee0D8aOzj8SvTt4L909b5XsN/fItHybWp47ebdbcxJvV5HURABP253NYhXIK7OSfMELYax+3z6flg5aqQ2OskQ1eIqLM8iGi6YM+t+899Dm3n9YkTTMxch+MuPppNCz8EEcPaMfiYacDcFhTMVqNfvcie6fLHMWTJvqfdA0ixeXI2+NQZA/ZC/UznkPT3Ndsf64Ekwer5NjLbBMphWjqYttXQbz0TM1qvM+R+jz9aDW5Wc0wDORFI66IQLpNVzMoyI5w77i4JMhrV03Epyurcdb+Q/HS3E32fvoc2YmJwxwlfc2jPY2MlKMNGzZ0txwBugkNbXGOqekx5Yj57bfwrEiPsqH7AL8wrcw/Qx2txipHVuFR/fM5J2ZiAu1NdYjXbAQAZA0cBSMcweARowFYyQMxih906mpr0Nnh+B4M+dnjeP7GszB5nF4G9fJiK9SbvQ/W8iEOK0SXD5k8dhA+WVFlR2mIM3JVR+9haErPIVuHOaLKUXOdFZEmnBPKLUIkFQEYk5giAcdvR1txY8xOClIHgDWAsst8ZI/YF5FSSzkSFSPAyYskQmVWI4QgNzcX+x57GhbO2eTIr3EhbKQhhZgh2zD4kH/lgEmA3cbsiX6Tf45EYxWQjCN/n+NR+cL/AbDW+WOXcqIw4GjL63f4L0LNRat5MEcq9kOl3HmZ1ZImQbigFCVH/QhP/e4EHHaXte4lNeuIaQPoNrvUkNWGY570QjxpIpSdh37HXGLvy0otGh1P5cKivkalJ1+L/L2OdCkkMubIP1qNZ88yNaux/aFXi/pJIOWh/ID1DETliDWrsX/pb9FMV1aUgx8cOsIlE70OPjWB4Sz4uysyRywc+luXzA/Qk2BZI2DnJIH0W5lbVI5EZ0ZWOTIJwXvfVGBoSa5vUjH2Q2Nz2rDFCQha65xZ4KAfWQsjDx5uKUfbt2wARqXKJjrROOdV7H+PtcZWpHQYyi++D+HcQqX9XYbBKeWIvS/hMCurY1b7/sHDcPYBQ7BvKqOs2HGqBkvV95bOZ2iaerNXusAuSSZQX18PAoJwfinisCZJJNaGSGpBTxK3TLrhglLbx8swQhg40FJgdDtsVi6vc7KzQsgZMQGDDvkeOgvKUXjQmYBhIByOIJla7yO/sBgdHR3Im3Cy8r6pzGrienLiyupeYJ3pKZxIP+tvyDBsZkC1tprVvhXmX3TQGdLj4fx+0vskfg8AMKgoG5dOHIX7PnKzX1y0mrQly8xjszmK6DR3vWqzWtw0nXGE2Z+Xcrim+xyzmrVHdMgWIz1VkA26NNIvvmOzlSKhKbXYbLGVR4t9PWTO2JZcns26fI50IZrV2P7QkznSNasJyhF7fbJ+j/bX1GGbXSx8QIF7QsCCY9NTv10+R4yZuTeRcYalf//739h3332Rm5uL3NxcTJgwAS+88EJ3yhYgA7CRaoCT50jP9daBX3m2A/IL5Y8n+D1ZEedjSJoEzYzD9jdbG3DtlEU451+z7Xq9fI5Eyh0wkEwm0bp8JpIdLSAEaK+3ZoHRwWMQTi2HMXjEKADA8pWr7fpaV3yOxtnO4qM5I/a1l1/ISUM5GkLzyjD3hfc5chi97EgIp08YgpH981PSgztXGbykaNuAfuer65BthLPsVeq3b98OkwBmrMU+nmjaYTNHFNxit4UlCIcpC6AnG5/nyDnpe/uWc+Vys8IwIlkYduYvUXTouTDCERihMMqGOf5yhx53Eq5+Zhb6nfAzZXsqsxq9Q2xeIksu/2uQMUcbdrRieUWTnfsrKxKyZ87xpOnpkC07VnjwWUAojNKTr5HKJHsf2MSTsvL2b6Xp1mDYHP6Ykun0YY7ss5jj1GcLdlvUrGbtdpvVHAYOACbtNRBXHbs7xpQVcOWouYYdlCOlwwAjBLOjGcmWOiRSzBFNMsoqdcp758scuS5RCy7mSMNpXiznhWzBrMZO5PIkEYG0v6ZKUSHjgD2w0J1BmwUrkcznyDCc7Xgvm9UyUo7uv/9+XH311fje976H//73v/jvf/+LU045BVdddRUeeOCB7pYxQBqoaengtnvKrMZCfIdFZUlkjthZemtngqNt11Y7g649u1Z0RmG2k2bMFI/+6xHsePc+VP3nFpiE2MkL2TDs8hRzlGioRLK1Hh2bv0HrilkAgOzsbEw4+mQUHXaeXT4T5oi9D9zyIcRJAhl1JXjj61JH/6iZI93ON6kZyg84UVpbt261Buo2x2TVb9LlNrtEER3kKEe5xY5Pl3a0GpPnSNahUtBZb7uwhMKovfaxfw8cPAzRaLbn4CXzIQHc0WViOLYXZMzR0m2N+N5Dn2PqskoAwH7Dirn1pFQBOgRyVqbfpJ9g2HUvIXvwnlLFQ3bNCZN4LvHgda5YTlTYfM3AMnmSjnmXva+OWc2R29qWm9VE81tJXhS/PXVvm5WloN8eOyiHsrKRlUof0LH5G9tfLlxEnZsZRUpDsZQXSLFnujOEFPwyZPs05wsxuCMr5H4GLGh/TY+xSqqvciQ1q4W44yyT2pvIyKz28MMP49FHH8Wll15q7zvzzDOxzz774Pbbb8cvf/nLbhMwQHqgzFFOVggdcTNjs5rfa8l21H4Lz4oO2WxHU9vSKWTbZn2OiKs8Vw/n5OzM7F999VUAQLx6AzpiMbSlmCM2qqnfwHIYkShIohNb/3kJV+/TL76M2n774P6PHVZJFR0mw6CilFmNuWxWkQMIwxy5V64G3L4pAHDr6eNw53vLATh+D2IHwvqY6EB7faeigYjXbMSWLVsAjEKyrREAUHbhn5E7an+Ea1Zz5aPlToRXOOJNtXvJZTlkO/vFWTt1JhWXUBi99wTMmfaOJePgYfCDasATzWDpmEai4RDyo2HX4sUA8PkaK2fUEbsPwPyNlvkx7hnKL8+ebYTCNhsqNavBrch1xJMeSqoh+eWGyNI4cnqXl91m1vGWFYv6rjih/CZXl5jrSzT1yfLoAI5ZzbUifPkeiNduQXsqpUBecam9VAz3DipYRu0M2Z6l3BCVI16BVZ+nYrhEiA7ZnM+RJGUFfQ/pxK6AM6v5KUdMO5Q5EnyoIgyT2pvIiDnavn07jjjiCNf+I444Atu3b5ecEWBnga6DM6yftfbXznHIlneQUUW+CrYzZBfJBeRJIFXfOGuqcpgGA/37OwzRF7NmOswRkw/HCIUQKRksrffQQw93taky7clAO7PRA/LRPz+K3QbmC4qcM3sVU/eLSSDpPfjBIcOxV7mzwroBd/I26/z0Ol/dRGs0IuzKK6/EpncftrJNwzGfiWa1SDHrvK7nP8TCYRIEk4ZwPjW9iJcxeuwE+3fZkGG+kS+qgcQ2qwmRUjpXETIMlEhMaxQ5WSEcOLKEmSl7mNXgr8gqfY6E3W2dCS2fNS/mSOXf45/nSM5k2eWY/ZSZoGaftlSm5pCPWY32BRGlcsQrWRQ0B1bb6tkAgJKBTv/g9Q7aZXxGU0exTpc54svz7Xs9I03lSAzlZ5SxPEWeNcDxTZrAMHO5HuUBXlonWo1hkwzDbn+X9DnaY4898N///te1/5VXXsGYMWO6LFSAzEETKg4qsjR42+co7fcsHZ8j+TE68IsOkOx2VTPvI8WOYXrMEa9MGAawceNGu8ydt/4eLVVWIkLWrEYIQf74SfZ24UFnAOEIckZOQHG/ElcH5tfxyRCNhDDnlhPw8S+PTclm1UngsGmiWU00VyQZJ1RDKCdGhbDn60KXumYjwnbMSy08GQojlJ2fOj4AkYgzWNEINwAgzEPVz5DtPHtZhAuFKknmyD0ds1r/QYOVeaUoVGYyx6zGv4s69zlkGCjKVad+GFKSi+xI2FaOmjsSyudBiP/aaHLlyH1lJlE/B71h162I2HUrzWoezJFiEKT+LqUpBXNHKtjENqspQvlpffRdEd8Z+10QZGH95ABgzMHHMHWr30EKP1Or1z3wgiuUX9uspteQ6HMU4ZgjtbJDzZLnHzTMVorGCyZMiVCun6LPUZadFHUXDOW/4447cOGFF2LWrFk48sgjAQBffvklpk+fLlWaAuw80FlRYbbVKVOzWrq6UTp5jlSLTUYjISAGxF1LZaiZI9kHofrGIyGHJnFW/+ZTTSxf5iwmyZrVCIDiw85HtGx3JNsakD/uOBQddh5C2QXSrMw6FHUkZOAXk/gOllV+WOaIZk0W66Wb4qAcDoHrzA0YUsXAgH6GbCB95ojbl1vkRCGFo5g48Qh8/rnltxXKdViugv7MDFxzZGDNaux1i+YvlXIUzcnDQT/6NdZu3Ipho3bHgkXuTOgsVPfMMW9a245DtsZ1GECJh3JETaoHDC/BpyurMe3bKs9ACD/3ebUDtXufasLB+YR4jrzWH79IVVEG2X1j+wP2OFX+ab4ougwRZU5Es5qjsPEO1+I705EywcqYIyMrx4643P/4s7BxndUm+96qmCO/V4JWEVH4t6kglhcXnvVrzw9i9J0Yyq88LyVXJBzCl789Hl+s3YFTx5crywMq5ojNc2QwZrVdkDk677zzMHfuXAwYMABvvfUW3nrrLQwYMADz5s3DOeec090yBkgD9IWiduCMzWppHFctNkkVA9HniF1OoVpgjpIS5kilmLALGVIR2psb0dJiOXUPOPNmrnxW/+GuC8gdfQAK9pkEwzAQKRyAUDQHIcPdseiY1ZbefjJuOnFPdQFb8XH8R8R67QzZdFBmnFD/v73zjo+i6P/4Z+8uvYckJEAgoYZeBQPSBAmKCoqoiAqKYIHfg4Io8CigPj74+GBBfR4rxcf+YH+wgQiogIAUQekdlSYlIUD6/v647N7M7MyWu0tykXm/XpC73dmZ2b3dme9+27C5VriCgWLPWVjDagVzDU+8UThyRfveElUAd959N9E/F1Kvm4HIRu3R/eZJZPds9st3BPlbGDVHohB8FU17X4PEniOgwHgP2kW7s820mKz2jzyY55TNHje4g9cReNWeP3Akv0hY3h/NEcC/H2xpjkx+LHGeI+dmNXISJPdq2ogk5hpqVcQyWg09QzYzbrBtFpVpZjW6H67wKKRd/xjC05siuevVSMnwjRdmfm++Mhaao8rd4SZL1fBgy9sN5bfrc8RGw5GaKl60mn4cUX9yTDiubl/PUvDj+Rx1aeTTMitAyJjV/M5z1LlzZ7z55pvB7IskCGiTgKZy9t/nyPzGpDNk8/f5zGp0H0qIm57VHPHMdWYZslmfo9PHfvXui0lCdM4lyD2xCqtXfofkvPF4elRvfLjhN6zee4Jbn4aiGDVHdjQFwklSq6Pyb4UqFvxYnyMyGSI7cfEEAwXOTGt2ByB3XKpxW3S8/llVVQy9bhjufWcDPEleTVF0k4sQ3eQixKX4/I9sZ8gmloow8/dg/SV8/aGdqK2eA1G3KpOq+4QjzeeIKD/9ylbo3CgJl8+hs0JHhruohKQs2vPRsE40OmQmYtOh09hzXJyo0WoVd+FkyNnsNE+W5vzfpr73N9eaYleEFwlwZiYlWnPk2x7NaI40tPtBFOmpaUN5Dr+Az6zGuwaRDVoiY+SzSIwOowRxe6H83M3Efn6/rTBfeFbcqN1nzaiZ8n020xzZFb6oPhH91a7vDV0z8VRl8EtJeUXtNqt9/vnncLvdyMvLo7Z/9dVXqKiowOWXXx6Uzkmco5vVNM2Rn2urqfBOeKIHjIpWMywh4P2rDQIVamUWXE4UwlEmLxOpVSpnJiQWt0L6HHnL7vvpBwBAWHI9KIqCBe9+gDtfWYp9JXFIjYvQH3YzEwVPwLAzEFiV8PkcqYQvEV2GdXQlNRb0b6FwBQOej4kZtn2OOGY1Mtu0VktMq97GPoE/yZhBmknNJiae35V2vNYnBYpl5IvQ50jPc+T9rpvViPJhbgUtM3yCYnS4G19O6IUIj9uWcAQAea3TsenQadM+Wv1WukmW2c47M7FZjf+5e5M6eHxIW9RNiKCOP3WOznYvMquZ5YeqoByyfQW03zaZcWrX7oFwNz/Ss1yLRqucZMWaHu5m7zGKQjkXU2Y1PzVHGqK0ESJY4YVaHNhUu2ev/jDBCxogFo7C3Ox4ZA/yEK3ZtLhIPHxlK3y/6zgublwH81buB1BLzWpTpkxBeblx0lVVFVOmTAm4UxL/KQ2S5qisXMVVL3yPu95Yz91PjoHGhWc1h2zfg0VOTqQAdPQMqznyffYtF2BsX1EqHbI1YaJCxYmvXsDX/3kWAJDYcSAAICo6BlF16lceQ+caEsFqKwB7ZjXLN0ftg6nmyPtXuw66gKgYJy6uQ7ZlL2ns+hwpnjDUuXIS4PK9T4WnZumfSU2N4VjOgGgFpTGjjmc0R2bRMYTmyNIhW6Q50jR4TI4d+regD26SGouGdbzRoiLhDaAzHw9obb00jVW0mlgbZNwuVjKJtSUN60Trz7RWp7amlqbFFCeB1DRHxoape5DUWlT+tvFRYdzrzdMc7T5WiO93e9MkiKLVuI0xuF0KYgiznR2zmvXLkfevU+GINavRC8+KsSusmZnCRGY1UUZ5K8gekddx9CXZmH9bV0SGuXVhraw2hvLv2rULrVoZV4DOycnB7t38tZUk1YOWjVrzOSqrUDHurQ2Oo9U2HTqNn38rwJe/HEF5hYp1+0/qjowArXlhx0NWcwTQPh+kWe14Aetz5NtXJshHQm7T9pw6fBCFm74EALRp0wYJRCSaVqP3mVOobTwUxs8FABQbYbqWGXKJN3srnyPtB9N+N7eL7pMCfu4lRRFP9DycJFqLbd0XCT1u1L+HkcIRxIvYUsKNTenItywRfV3ZcVwkHHk1Rz7tk7/CkUGDxwnlZychUiNkNhGSUUJNUmMRH2muyLerOWJxojminP6Jz+xkqLWlaY60bOAVKn8JFK0q3jNCnhe5u22DRADee590bNcuqTHSU0H/p1dg+5EzleVc+vE8zG5Fj0uhBAM7ofzWGbI1jVegDtn22rT7IiLKDg+Iny+zY8wwe9Fh6y6t4SSQfglHCQkJ2Lt3r2H77t27ERMTE3CnJP7D+hwBwGdbDlv6EInqAYD5K/dh2Eur8X/vbNS30T5HAods4qEmI9bIN4IzldlWtQGMHCjZhSZJ9HwzioJzu9bg89l/8X53ufD999/ry1VUqCqxbpM9zREU4yRupTmyM1Rog6Oq0iH6JOzaanQ5+q1epDlyou52mmjNFRalfw5LaaR/NtUcEf0WJVtkESeBpIcskUM263Nk5ZAt6uOmQ6fxR2Gx6fIh7CmRkzabx4oqx0x6ZlomwHcvNE6JwZL7eqF/S1rbZMdUZrYNYByyTX437fj8Ss1Roi4c8TVcWnluKD+ZBBLAFxN64uVbOqMz4ahL+h3pPkeGEHe6Xu2Z9ccM5mI0R+TzLxLwrW5trYpAfY7svmDY1hyZ1Cfa5VT7pUHeU6LfxeeQXQs1R4MHD8a9996LPXv26Nt2796NSZMm4eqrrw5a5yTO0QYaNgeI00mQLP/2Gm+eoCVbj+rbKPOXyM/ABe4Ky7y+aPZ9si59uQDOQ6QLU+fP4PiHj6Gg0hG7S95QJCQk+Px7iEmSiPw39zniaIGsfI7sDEQ+k5mvbbFZjfU5MprVbuiSCRanfgBOU/S7InzCkZsI1wdMtHE2TBIs5HIdtHmHLidKOkevjKIY0kkYusi80WoTxujXf8T4tzfo0XO6Wc3Ej8qu5oidJK2ysJN+as3qxplmNibh3RJ2QvkpzZFgfS/t5SY5JkzvI288MDOrsbdgy4x45LWmQ8LJdepEZjXWb0zrsz+h96zmSKHuYf4xds3qTgULNgkkG7Uqwr5wJO6PqA62T7axoTnymdVqoeboySefRExMDHJycpCdnY3s7Gzk5OSgTp06mD17drD7KHGAZlZjJw27viUa5PjWIDnauN/UrObT+GgDASkQcVfF9hh9Fsr05QKM/dMGvJNrP6G2Z2TnACCFIEIYIQQMM82RS1HE5i4B/pqy2HbYpJa0WY0YFAFc0iwFX0/sjdb14qntTvri9L6IadUH0Tk9UeeKe6ntmgM/D7I7VtdR+63Lid+M0hzZ9DmiNIYKMKBysrWlMWE0h4fziwyLILOCKkm4XbMaIwyJtGAa5cRzBYgFazuI5kNF8JnVLrC/o645qlANEWtOfM5Ewj0pHGnzMquVM6Tf0EL5/dAcuV0KYgjhiLzWrPbSTn0A6XPkTLAwaI7Ie89EZ23mFkSej1l/RKcUDJ8jsVmtcs6ojdFqCQkJWLVqFZYsWYKffvoJUVFRaN++PXr27Bns/kkI9h4vxPi3N+Kevk1wZbt63DKaEBLmceHixsn4Ya933aZApPAGST5tQUlZhXfwNzWr+T57H+xyyqzB0xzxVLt61AlPc+RWsHfvXhxfuZDaXi+7BQBaA0NGLel9NNToQwEnB4qfgzqvDOVjwYwxvogjlSprzJDt/dY0LZYWhB2+0DnVHCmecKQOftC4QxVfU9pnyLyDbpeCinLSFOr7HzBOdMI8RxXk7w48ODAHbeonoFGdaAx7aTWnj77P7KBdVq5SCxuz58T+9qTQYzbxONUckekNALMcWfRx/DxH1toU8ryMEVP0cVouogrVqDlixX8zRHvJfFHiUH76aFEov96WSVfcLoXKDk37HPGPsdYc8ftthb8Lz1oJf/oyKyYCfLA1R2ZaYLbuWqU5Wr16NRYtWgTA++AMGDAAaWlpmD17NoYOHYqxY8eiuLjYohaJv8z49BdsPVyA8W9vFJbRhBCPS8Fbd1ysb7eSwrcdLsDNr63h7iOdIX895V1Ti7xtRaH85ArLpRbCEe8NW+szT/BwKwrmzJkDtawYEQ3bIqvbAERktkHDFm2pY7xmNcI05cvEyD1X77GcgdbSrGa621tv5d8yE82RNvkbMmQr4szX1IQGxfRtksWp5kiEClXPCcTiRHOkXecKwozlj+aoXCVWeq/0z7qucwOkChfGJAQwhf69S8orqOg54znRNZEaDbOJ0CgcWWiOGB88VlB05nMkKEucGWVWs2hL0+yUq6phPCCvpV2/HBby2mjnzfocsceKFp61ast7jIvSHNkJ5bcbkOHcIZvVEBK/kclxZs8a+Xua+RxZ+QU5hTZPCup21UKfo0cffRS//PKL/n3Lli0YM2YMLrvsMkyZMgX/+9//MGvWrKB3UuLFjt+Qrjlyu+B2+XwnrPyxb35tjR4Cy0K+CR44USkcEdtEGbJdii8MVTP3Afw3At4kog2y3Gg1l6L7vMW07I0edzyK9JueQFi4d/Lzmc/oSVLfzj3TynJQmDdoGwOfDYFE00RTZjWRz1GF5nNUeawinrjY7c5MfMEZgFRV7MdlZ0DU0AZG2iHbTHMkMKsxmiP9eBsChEtRqH6WlVf4zGp6IIC4zkZ1fGZos4mQFYZM0xKAvCaVk75Bc2R6uK2y9H1FlDcIR/RxSYRDNqtJZpeH4LXla1OkqSDr8P610hx5LPMcmQsPZI4ft8nvzfbLijCHmiP2HiL7Yq45Eu8j7x0z06+oDruBFSxmz41ed22MVtu0aRP69eunf3/33XfRtWtXvPrqq5g4cSKee+45ubZaFWKWUE5D8+fRBg67IZcnzpYI95UTwsz+E94MvuR9y97DhLuIPhDQofw8zZGxn7pDNucU3C4Fv/3mXS/LE1fHkFRRNzGADuW343NkmJBtmcwsi+gDPylsssex0Wp6fh2XIhSI2I9Ohq1Ve8yzhdvF63PE30f2x+qFU/utK4h7iHRvYAdlkbalnPDEN/MP4vVRYTRHZeXGpJ08zdFrt3bBDV0ycUfPxvo+Zw7Z5heHTUTJCizO8hyJNEf844zRavT35BifzxGrOaJWXSdOkV3Ty1svt1uGldsB4/Vjbz+Rb5beFr+pyn4q1NptZN2iMdVy4Vmt3w61Lob1FymzmrhNq2g8DbM5QlR/MKLVxCY785xZ1YUjn6NTp06hbl1f+OiKFSuobNgXXXQRDh06FLzeSShsCUdlPs0R4B2AihCYdoA0vRyuXPuJvG3ZvCbaO7vYIdueWU2PMuMMbi5Fwa+/Vi4VElfH8FatHaGqtBbCF05v/uCR47adBJC2MmhXFiG1NUaHbC/8DNnGushjtO1ONEcbD54W7nMpRsFXhKqK4/9onyPzQVVT16vE72nmsySaaMorYDCFAfacc1nn99KKCsPaajyfo/6t6qJ/Kzq83kxLwPadXR2dxWBWY06Fp9UC+EKA8HZV+GWMy+nQh2k+QeUcnyO323itAO8LUYnNBP6kGce3YCndCXYcskoC6URzROZ481dzpO12nCHbxKRp1qSZ4EQ5ZPsRrRaMPEdis1ql5qg2mdXq1q2rr3heUlKCDRs24OKLfX4tZ86cQViY9QQu8Y/4SN+15SVaA3xaGU0T4+9NTELmIdHWQjMzq/l8jsAVjnhmNXPVbuXDcvI3lBzf792mluKPP7xmQHdcCqWt8rataWBos5ruciRsTfNz4b/tinCyvAh5/oa3QmYwojJkgz8oCjVKAeIkIsVutJqVoKmnaCAcsmktDX286L4pr6jwmfkEEz7VR0rwVCgNV1k5sVCwDbMa3T/xvgjGjCZaJ06DzbVkvHf4x7HdW/R/l9jzOTLJSSPyOVJV4/pqPK0P4MxvJZwjYLHnwK4GoPsciYQZM18bRaE0eedLiRcaP32OfOZAZ8+oKBead6f4OLPLS/8OZton/nYzgcouVtFqtcoh+4orrsCUKVPw3XffYerUqYiOjqYi1DZv3owmTZoEvZMXOuv2n8T6A6cQT2iOzhSVYe73+zD+7Q1U9l9NCNHeSv11nCMh1ZvHC70O95RDtsispig+nyMLs5qZ46rbBagV5fj91TtxeN54lJ8/g7Iz3ig8xRMGV2QcJ5rI15cKzkRrZVYjByQ7ZjU72iWtU3RGYP4Ep/WZCuUnLpGpz1GQBCQn459qEq1GCScWdWrXUb9EilGrQ8IO7OG6Sh4GgRkwMyeRvzctGJYRpiKtebpO8fmY+hz5qTkS5QwigxCo7URvezStgzb1E+w5b5u85bPnTEaTsW/8IodsnmArNKtxfI5YRO2KhBmzZ9a7qLVvfxGh4vInb5J3v7cAuyacFWz/yctmGspvoRnjfbZbh/+aI/JZ5pfR8xzVplD+xx57DNdeey169+6N2NhYvP766wgP9+WfmDdvHgYMGBD0Tl7IFBaX6aHHE/o107efOleCxxZtBQD0apaK6y/KRHmF7w1XG3j8dZwjISX4Y5XLfVCaI4FZTSH6UWLhkG2ea0NBeeFJ/Xvp8f0oLfdmYg+PS4GiKEazR2XZpduOUuti+RZ/FaOAHoCDZlar/KuvGs45htR4kX+9ofx8gY01tzkxq5lhN4mchp0M2XY1Ryrxe7oUX8Xs2z4rfHgqTTUGjaHWF5uaI1aIM6zkblN4dhatZi8JpO5zJBCsWXhaLmFZwXFWmiPyXFghhRQ02QV7je1bT8aie8ipcGR2K7KT/3nCrObvwrPa7jCHmiOD6d3G/WzVH3KX2Qu0HWHVCXZeVPQ8RzWsOXIkHKWkpODbb79Ffn4+YmNj9SUaNBYuXIjY2NigdvBC50xRqf75XEmZ/vnYGV/KhK2HCwDQg0OYQ4dsM0hNh9YuORGKQvkD9TnScCsKygqO+44/cQglHu8q8eEJKVSb2tlqD95TS3bqxxFWNVOfI8VgVguScFRZxGpBXcC4fAjpTO4taDzGsCNAbGnDCIISreamhUOvoCqeGNlBWsurVe4wWg1UGWM7mnDErukHmE9Q5kkgnTpk0y8AbNVOnKztZMg2u+6sxpPVtFH73GSd/O2+erndosw4IvMVO5lqfRJqjhxoTIpsCEdWd5a236nPkWhZFKs2ze5LcvgzN6vx94X5+dJNCeqCOnx5jmqRz5FGQkKCQTACgOTkZEqTJAkc8k2KfPh3HTujfz5QGUFGmqu0GywYtmFysMs/X4risnLq4TKspUSYuDQhLRDhyKUoKC84pn8vOX4A5//wRqqFxVcKR2w0Eee5Y52aRRg0RzYGAlsRbZV/zdaMYxP5kWY1WjZS+J8Va98Hu9hdw0nHRrSaVZ26Wa3yFmHPh9WEsgO7HunCZMjW27dhEmFD+QHfs6U9TnbqJPvDw6A5InyQejbz3tekuYpdwsRuLi5KODV5PtjtZr8bezipBTIzq1FmFYWzwDO/W7TmSHBJWXO9pVnN5F5k7zNScyR06rf0yK4ckwOOVjNUye+PyU5yzLZKFsnDb7OaDS2y7pBdm0L5JdUPeROTD//OIz7h6Kdf86GqKrV+lCYUBdshGwCOnymmtATsmyKpOeL5HJktH8LDpQBl+YRwdGQXDq36BAAQn92+sk1+tBqLT3MkbI7jcyQuq2HnOrMZsnkDj7ZJ5ZnVTExp+mfrrtrGqUlWNJZRKnwr4cjFao4U4dumohjr0+43Mv0E60/E7yOtMWF/m+LKydF3f/E1LCxmPkdmofwPDszBY4NbY9H/XaJvY/3qjKH8opaMfbWnZfJ9tlpOh9TgGTU4/OvPu84iwZ72ORJpjhw6ZDsQCijNkQ0Bm7u/8q+VhtDQF5Nrb+ZzZCb8JRML+Uaa9EeoyQtCEkiRMFmrF56VVB+kyaqYiJjYcdQnHJ08W4LjhcX6oORxKfqNZxZxpBJv12awPkLHzhTTeY5YnyPCE1b3ObJYeNZMTaswZrWSwztRnP8HMjMzkdbZ6+NGRshpxxjrIZxWTReeZcxqNjQxdkxQWokyE80R63MkMqspnGO8n4MnIDnVHPFWYwfg6FoahCOF1eIRnzmTq6appDNk+/aLo7SAmy9uCACYnNfC0E/txcTO2mp0f8Q7WR8jctKMifDgltwsNEjyJZQs17RXuoBD1+dkSRBbZYk7ybjwLH2cueaIEGxIQYlJmeBtk0+42/oeYm8/61B+QWOcY0iBT7gciWWeI+9f52Y1E+HIpEmzfZFhbqyY3AffP9jXz+VDguFzxC9TK5cPkVQ/5EBTXOZ7e9l5tJAqd6ygmMqOrSFydFZVFTe9ugY3vPKDpYDE+hT9/bNtWLL1qP69rELFzqNnDFmdFaIvpFaLt2SF2cN25vRJFG5ZYtg+bdo0uD1aCLFP0wCYmNWErYA6zrFZzYHPERuSzfbRWwbUXzfTd6GgBHumQzs49TkSCUeKxbXk7SeFXZFw5VKMCwRrE5c3Q7bPb8l3DL/vigI8NrgNfpjaD0M61udojmjBRPRbsDjRHJEZsnnXvpwR9oRrq5kI/i7O/U3Dn3gNzt+sedNFao5o4ShM4HPkUsQZ4lk8AgHLjEDMatq+yyrzVo3MbWTZvqVVDb7+OHnvMDOfmlVj9SLSqE4MJXw7qSMYGbLFZrXKOUOa1SRmkIJJEaE5OslktPZqjugcR4A4qiD/fClW7z2BtftO4vgZ8/XwWGHmxwOnqO8HT57DgGe+xZNf7QBAZqQ2OmQfO1OEfX+cNbRhZlZ78uH7gXKvM3psB2/S0ejkdNx+++0GU5VPuDE+eGXlqj6aWGVzdqo5sjNYaINjmcmCuqwARSeBJAdF/iQWVM2Rw4rEMravIus16ljNkTgJpMKZXGmfI0PzpqH8iqIgPSESgPH31HLoaJvNBAeqP06SQBJleZqpCkbjKEoDwUJu9uVpElwHTrve48Tl2MmeNauJfI7YfGJmiJy6zQ63Eo7smNX+PaITltzXC8O6ZPr2+WtWI/Y7WXzWdJkYk0bNHjW77z2iOvxPEUP8jhb+TNKsJjGFHGhIzRHL8TM+sxr54IkmbVLoYjPampU146UV3rXOSEdYLeGZJhx1fXwp91gzzdGu7b71/JL6jELa9Y+i933PU87/rDaGffhTYsORnRqjCxWiM/IlmPNts+PTbmuQryyiZcjmO2RXftA1R5XnxUxAYs2ReOJzituhv5odzRHXlMgpS2ofRW+bmsBIXhft3qej1awFXXYzO3D7HLIV23UCFnmOmLxGpEM2TzvA+hzZ9dfhRaDZEaToJJB0X+mXB02I9X5nJzUP51y0OgwO2TbMOOw9ICIYwlGY24VmdePo4/yoD6DP3YlZih1/7C48a0fjbYX49/Cvbistsrfu0EgC6SiUX1L9kM7QJWViSdorHPHMavyHkMwme94ih7/TNO76sh+E5qjE4kY3e9hOnvD6G9W740W4ImIQld0JcanJ3jYqT883mWqTl4+Xb+mMvi3SEO5x6Q+nSODTjjMLY+ZhL6Ktsm1C4DGWoTUnwoVnyT5TPgjBEYwAf8xq/O08zQVJQlQYTp0rpcqSAjY1oXKcez0uF5EZ3lXZF360muiU2M2WTryUwMevk+wPD1ZwIh1jDdoWVTVEOZJlzO4/nvApmuBFTv/s48k6VnvLKChTVVPNEZvQ0+4E7mGvB9EP0ehl5XPkJFqNvBZCnyMr4YgU4h0IR4YkkILfyGl/7CDUHPkZBU0Lx6K6vTtKa1MSSEn1Q5q0ijjCUbO0WOw6VojjZ4r1CcJDmdX4dyAlHJWaC0dOFwDkJYG0ErBEk4haVoLCAm8eJ1dMkr5dNw9UPm5mZjWPS9E1CtpW0fIrvOODludIM6tp0Wo8LYouHNH9NKQhMHl7DJZ85NQhWyhwUpOssc5maXG4pFkKUuMi8O4679qMomg1ntbATcyQpDOnozxH7ORv4VciEk5ZzO4LQ54jQnPE0wyqJtpRuyYUJ5ojs8zkvKVFvOVV0ySQ7HPFmklFkOZJo2AmCATQhCORoGvD50jvmw3TsNXTQtYRkFnNdoZs202Y1MGvxH/NEV9QJmldPwFPDm2H1LgIv9oIFlI4CnFI1WIxR4hpmBytC0fsorOAWMInTXRWmiMrsxuLz5lWoRyyRQIJIB4sys+d9n5we+CKiNG3+/wutDbpUH5yzOANwKJz0gYb3puxGY6SQJaLHbJ14Y31OXIpwsmQ1YwESTZyngTS4poCAlOdAvylMvv7e5XCkTa/Kop4ktYnP2IbqTkCcR/yjhf1ERBrB3SzGqO98Ac2Wi1cYDryaTu19oyTvpmAxjNl2PI5IrabpQ3QBS5v/k1D6g+RAORifluzy0jmaxNpoli031D0gmj2u5k5iovatBwniN3OzGqMcGRTc+Q0w72TOvxNEePi3Iss9ROjcP1Fmdx91Umt8Tl6/PHH0b17d0RHRyMxMZFb5uDBgxg0aBCio6ORlpaGyZMno6ysjCqzfPlydOrUCREREWjatCkWLFhQ9Z0PACuzWoOkKABeR2fd58hGtBqZFiDomiMiqkYLwS0przAVsoQLiJ49DQBwRyfSE5KuOWLa1PZbTIhWWg42WZ0VtkL5K4voofxcs5r3r9Y7OpSfnEgo3QW9PUiqI6c+C2I/LqJOm6YHVeVrzHhmNZ5wRPkcCYRKUR/ZOkl40Wr+TkLsCwG5ICntc+T9XM68ALB+PyJ4zvtmjulsWcB8ZXj9d6jcVlpG3wlhgjB8NhWDmYBHTsZ2hF1yn+hcze5F9qWSFjD5x1g9LuRu7tIpguONy8TYEyhNlw8xOY6qQ3CufpvVbAhHoUKtEY5KSkowbNgw3H333dz95eXlGDRoEEpKSrBq1Sq8/vrrWLBgAaZPn66X2bdvHwYNGoS+ffti06ZNuPfee3HHHXfgq6++qq7TcAylOeIIR5nJ3lBMkc+RKKrAic+RU8c40jk6nMiQbSZkiWzw5We9kXFuwqQGkJl+KycONkM2WZYz0Tz/zW5ue77Jw7fNjnnJzljBmgC5SSArt2nCAem/RYlDivhzsIYcp5O+0CGbrJNznXhiHlmXKKsuz/dGm3TKVTK9A1G/UCigEWsHtHqsy1rBCkfkc0v1s/JjBSEoA6ygaCodGcrZERLNTCA8DYBWhvUVobV9dF9sa46qIlrN5Lk25l8iBTL+w251G5B18l4GRcIau92uKdLJfdm7eSoAX2Z2qzr8NqtRwndoC0e1xqz2yCOPAIBQ07N48WJs3boVX3/9NerWrYsOHTrgsccew4MPPoiZM2ciPDwcL730ErKzs/HUU08BAFq2bInvv/8ezzzzDPLy8qrrVBxBao540Wqa5uiPwhLCKZV4CAUDAGVWs9Ac+bs6sgJFNx0Ul1YIJ09A/LDpmqOYRGq7z+fISwUzEYq0Fdaab+OAaucFx86blEFzxOmM7nNU4RVai4nEfyKTh+hzoDh9sxPdJk60cKzPldes5ttPL53AE44qzWoCzRHgrY+V09mB2lJzZHOCNoNtwyMwHWmfylX6vnEJ7nEWSjjVhX9nnTYkgeQIZto29mVK7HNk/x4TXRs7TtVCh2xFQYu6cVRCXf1Y5nztaI6cOGTzsmS7XQo3B5wxWs1em04e3+du7IjPfz6MK9pkMHXwK/E7lN/mPRsK1BrNkRWrV69G27ZtUbduXX1bXl4eCgoK8Msvv+hl+vfvTx2Xl5eH1atXC+stLi5GQUEB9a86oX2OjLNPYrQ3nL2otFygOeLfgCVONEcOzWrkOmdauHJxmbnmSJQPpqJSOHJFJ1LbWd8iPaqLo0qnVfLmfeea1Wxpjuw/6KwGgGq/8u/ZkjK0mfkVfjp0Wi8r8jVgtwdrzAlWhmwSq2tpFHYVqh+05si4TdNAllVUEHmXWK0HRyi12U+fWc3+PcVj1rVtDdsosxrnt9bvG5exj6aKI869LCpv17TDM3Fr3TFdW42p0+45eASmOfNwfJehfRKXC3hjdFeM79uUcyxzvuQ+kfbR5tgCCDRHIiGO2W5XqHDy/CZEh2F414ZIINbyA8QClt9JIInPfqdKqiZCvHv2OXLkCCUYAdC/HzlyxLRMQUEBzp8/z6131qxZSEhI0P9lZlavoxgpmPDManGRHr2cliSSynNkx6wW9Gg1L4qi6G9IxWXlQs0CYOZzpJnVEqnt7OroPBOKXpZ69bI3OTt2yLYxVmgTSpmZWa2yzKZDp6nrblh4ViAoKYpiGsHiBKeac2FiTUrzY+/tmvRbo3xfOJMkX3NERE0aNEcc4YjZJI5wMpZ3qoXp3CgJw7s2NGynzWpE3wwRmQr119sve5ojy+VDBPeOHWFBK8MuACsKw2eTR5rdt6TZ3a5wpDtkmwi6afGRGH1JtmEf+/vbuYet8xwZ71OzNkX1susLCtsLwjAg0kw5ibYT1RcMh/GqpEaFoylTpkDLgCv6t3379prsIqZOnYr8/Hz936FDh6q1ffItjB10ACA+0ifpny32Op9TeY5smNXOVZHPkaL4InKKy8wdskU+R2WFJwAA7thkajsbdVNOzqZgBmEnZjXO5GFHcyTyQ6DqrvxrJwkkK5C6FEUo17HmNjtjjr1zcjZ4ab+7aRi0hWBiEAQgngx5Dtket+9+YJ30ee3x+sg7B7P+Ox3kRZdVy84NsMKA9y9rVrObDJEW5MzLi6oxW/yUrdNgVhP6CzF5jkwuo4dzPdjPLDwtMomZw7bx9yfuMaFwJO4LQF9bnnAhErrYvtB+WuJGTU2tdrVPgmLByXMU2sJRjfocTZo0CaNGjTIt07hxY1t1paenY+3atdS2o0eP6vu0v9o2skx8fDyioqK49UZERCAioubyLVhpbUjhqFAXjsjJQqA5Ikx0RUH2OfI5Efts68WltFntwYE5+MeXPsFXpDkqO3XYuz8xndrORqsZnFWJ587uWkTkfruRQL42rMtoVZbr10c80bITjKKIzWrUACmWoZj+Kpb3lr8O2W5FQTkRu6YIfgsuCl2Xi9GY8UL5ycmKilbjhPIDgvNiNglD/nlaG4djvOi6Rnjc2DJzABRFYbQD3s8VFbR2lLzn7EarOXHIJjFO0MRn1iHbbOFZ6qWFnejFeDi/OwCM6dkYj3++zfQY0USum0g5u01D+UX3hgONrROzmpkzvNkjGoqh/I7GghqmRoWj1NRUpKamBqWu3NxcPP744zh27BjS0tIAAEuWLEF8fDxatWqll/n888+p45YsWYLc3Nyg9KEqsNLaREe49YnuTJFRc2QrCaRVniN/zWpQCJ+jckqzMKxLA0o4+vHbxTjx1btQXB6441KQcPF1UFVVF448SfWoNtioIZ+WQKG2A/76HJFtWT/E9pJAetE0R2Zrq/EifsjSrEBEbrczJnpcCkosyjjXHBHHEbeUSLjx7TdOkCKtD0+LRE5W2hs5mSGbbZLr62VTONLvO+pYZ9fJ7H6KiwwzbNNKlzEvACIThZnrl4sj3NFtOddesFFhbIZsSrBh+mw7CaTArDb6kmy0rhePm15bI+yzSMnhExSNDVeNzxF5n1q36eunuJxZk8GQPaoyWs2pT2N1U2ui1Q4ePIiTJ0/i4MGDKC8vx6ZNmwAATZs2RWxsLAYMGIBWrVrhlltuwZNPPokjR47goYcewrhx43TNz1133YUXXngBDzzwAG6//XZ88803+O9//4vPPvusBs/MHLMU6i7FO/BEeFw4V1Kum9WoPEc2kkCes9QcOc1zRITyu31mNTLEnx1g/v33v6Lw8G/69+icS6C4w6CWFcPtdsOTQPuK+XyOvH/ZdadEphirt7sqNasxWiH+JO3dyE5wLkUxmdDI4y27AaBqzGqqyKxGvi1amdUqP1cQ0pHobVP7SGuOfNeYFNJJ7DhkW5lieKYquzi2SDDXJDCzmnZ/W5clsZ0EEsa11YRJIF1sKL/4HEQvOC6Xgg4NE7nHaNdHpDnShknetTAuH2I9HlhGqxGfeW4EYqFLfP+aNRmU5UOqMs+RNKsFh+nTp+P111/Xv3fs2BEAsGzZMvTp0wdutxuLFi3C3XffjdzcXMTExGDkyJF49NFH9WOys7Px2Wef4b777sOcOXPQoEEDvPbaayEbxg+Ya20iw9y60/O5knLCrMbXHJWePoIz6z7C/3pUoCQmR99eZKU5qpzMPS5+qCkLac7gRau5GLOBWlGOY4RgBABF+zYgrI7X+T2zYSOobvpWdTGTlGHhWaKsRzA489CFKyYfixW2HLIr/5ImIxbRpMXmOaLqZUwTdtT7dqJN/E0CabYgqqVDdmXfqeVDqBwzRoGAlz+mgvQ5YprUvoe5FV3LYQzl5/ePF63m3OfIWXmtNOuQ7bJtVjOWEztk83Hic2RcPoT/+7sU2HYuJsc0NipSdC6+54xfpxOfI8Vkn68f/Hb0Ooj9TsxqZvWYLx8SBOEo6Jojsm6/qqg2ao1wtGDBAsts1o0aNTKYzVj69OmDjRs3BrFnVQuroibRTAja3z8KiwEAMRG+n5V8CE8ufhFF+9bj6qs/ww33z4KqtELJsX04ftT8LiWjq+wIR7RDtuZz5ItWYxecLCs4rn+ObtED53asxPm96wGX9zwaN2mCPUwb7GCt1a0PFoI3PavnUdvvcjCh2y2jVWm2tppZ8kE7E5qiwPokYU/T5XjhWUEUnuU1V4yfyTxHQj+Fyo/kCwCdIZt/r/p8lVwoLS/n9lF0fVihHKgG4aiyvG/5EGM9ploCzvVz6pDdMiNeWE43q1VuZBeZJv0eWSHD7hxLTsbsMkSic4kO944fIi2HkzXxhPegjX7w4KUusauMsWuKDEaovNDnyE/NEXkDSLOaJCDKTcxq2huZFhF26OQ5AEBafIShTMkfB1G0b72+/b3ZU/XPH3ySipTb/g1XON8pXXPI9rgUFNvoM+VzxIlWcysK3IqC0pO/wR1bx+d0XScTCbnX49yOlSjavwmuqDgAQJMmTQ3CkUtXidOaBugTh6+s3SUKyP3U8TaeYTuaGDabt52Qcg2XSxFKGeybpJ0hx54DuUPhiHDEpyuyX4cuHBHOx9SEymjJvO2RwlHlNTbRHGnlw9wKzpfyy1gtEWEQSB3gVCOn1a8yZjU2oaLweNKnS9N8CbtA79jw8GU4W1xmWASUZ7bWhX8zzREj0Nl9cSEnY/b9jL2eSdFhWHBbV0SFe8ceq8zTvOfQYFazoSl0ch/wzGp2BQ67QlhQzGqCKvx2yLaIXA0l/jR5jv5snDpbgm+2H+UmfvThvbk0zdGhU95cTWnEQKYNHOe2fw8AiMzqqEfvaZw/fRxn1v9P2IpZXh4epInLl+eIMKu5FKxdsxq/v3onTnz+LMpO/Q4A8CRlICytMTzJ9aGWFePslq8BAL369DW0wQ7Ius9R5X6yp04SlunH2/Tn0HDikK37HPGW0hBqjsSO1uxEbWdQtDMQO33z9C08y056Tq4/Ley6GNUR7zqTv2+4nufIzOfI+5fKK8SG8pv8DoDR78UJTl+YteLljJnI7gKstJar8q/Qb4b+nhwTri9RJK5TofpjlgSSfulQDMKSCFJzZExzQZftkJmI9pmJvv2WZjXjPjMfK9F44kQY4Yby2zzc7jULhllNVL+ThXPp+nyfQz1aTQpHIco1/16J2xf8iFe/22tZVhNAtEEjLc6XL0W7iYt/3wEAiGraFYsWLULfWyci47bnkXTpGADAmU1fCldV1zbbThlPvLGLotVeeG4OAODcju9R8sdBb/1J9aAoCmJbX0pVdymT1VyrQ2uD7CMvGseuGpo8zrFZzcZApAtypkkgRfWL36xZnyM72BmYnKrOywmhmLJ+ORgDuWY1Yj8vxJ3Oc+TS+yL2OVIqy4rvC+tEf/wJn8dN3eiEj07f6I3rBxrvUVKYYx9j6vpxNKOismbwAhZ0nyNGeBElgXQp9k3e5HGsz5HCvDiwJlGxWU3rh7nAzSIO5TeHTgJpLG1XWOBYli3L+YtQc+Rn5aJnORSRwlGIsv+E10RWUBmez0N7ptl1eiizmluBqqooObzTW7ZeDjp07IT2V9yC8LRsxHbIg8sThvKCYyg9YZ7g0qnmyOss7kZF8Tmc3rIM584XAfAORmRG8sKN3mjBsOT6AIDYDgP1pI9RTS5CQlycoQ2eY6y3TboPbL+to9W0+n3b7Kh/bZnVKtsuM00CKZ6UqXBtQR4hKPb0NHb663z5EF9/7Oav8e43liDXylMsfgvy99U0R94gAlGGbO9fM+HPKtEfa8o04/EhbbDgtot8/XUqHFX+ZYMO7Aqg/KU+AtN+mCeBZDRHgiSQbCi/XcmMF6RCXlP2HU6oOTIxMbLXx+oe5B1jBk/zYvd4+z5HgQsfoj5Fhrn9qi+Q/GDVjfQ5qsVo9xaroiXNamEuF8pO/Y6KojOAOwzhaVmoUFU9lN8VFon47A44vWsdDs+9B4m9R8IdWwcxrftAUdg3MHt3s08uUbFx3Q848sb9KD1xEP/pkASgPdwuGJzi0zPqISznEgCAOzoB9Ub/G4W/LEN0066mQoRRK+D9S46fjjRHTP3s8SKcOGSbJ4HkH+t2mZnVxAO5VV/McOpWQK2Hpti/5nS/vIV9Fjrai4o30VlnyKY7QPocifpopTmitTHcokTdCmWacurLymocWTMWuc3seLKvdky0ZlBCjovuDxtEQqYTofrpUIjW4K3h562Hr5EVh/JrY4ixZePCs9bjgYu5zmaxKzyzml0/HrvXLDg+R/w6NH8u5/X5PkufI0mV4dMc+W7UcI8LCVG+RHIet4Kig1u85dKbQnGHoUJVqYVnY1tcrH8+veJ1nPjsaRT+tNjQnt03EW1M2P7DMvTv2xulJ7xms4/fexMAUF54Cr///ruvj4kZeHnBWwiP9kXEuCJjEd/5KngS6gomRO9ftkcufXL1jUzk4GipxeBpBkQTicMH3TfJmSWBFL3RizUUzHzj2EFYhFOfBX19O8U/bZ23rJcKxodMg/wteXmVfNFq5Bp/dB3aeXn88TniTKh2JiFamHL6A1UKfHq0mlH7YyoccdoO1KmYFrgq67Thc8Rq3JwES2jwYlTIMYI1qwlN1SbjGVuHQu2zvnY8FwRyv5M8Ryw80zK3nEl1du9AXvZwAIjyW3Pk+xzqZjWpOarFaAM6+RaSFhdBPTAetwvndq4C4DVRAd63cjJDdlKny3GupBwnF/9b35b//VsoObwT7vhUJPYY7q3LoVlt14bvqe0Fp08hFsC5w7u9/U5piPTbngcUF7p2uxiub5dxX7e4GhaLV2BS9U6Oc9aaI+PkIRwMQeT2sfHWp5vVzJJACo5lNUfkyzN5jJkQRWInrafjDNl6OgV7wiUPVkuiKNZCKOWQzcmQzR6hVSFa6BWw1g4onG1m2BVkePBMxQA7SVof723bvA92ned5axdqdRvyHFEaOrrP/jgN89ZopP2vxH2ljxG3YbbwrJ0kkGEu8wz0geQ5smtODYZDtkhg89esRj450iFbUuVEMMIRSdGZ0yg68BMAbw4hoFI4IqLgVMWFuI5XIHngX6BUhvOXnz2Fws2LvULSUW8gvW3NUeXYdWDbJgBAXIvuAIATx46grOAPnPt9FwAgMr0pFJc3kaVLcWbL92XIptHXoSLGTyeOxVpTImdXXltmZegDUNk3cSi/mc+RHQ2W7cgwG9KR08GrjIhGdJJbikQrSzrYU4II56fkhvKT0WoKv3wY5QtDF7LKZaNytpnBE1DsohVnzWqUicJUUCLO0yRCi38sH14aAe0ZYJc8EkWrefc5b5vNc0S27a3T3vNu9syaLZdi9oxq8PIYkfDManafN146C35/bFVnSrDNaoE8B9WNFI5qMTyzWp1YWjj6YuEbQEU5wtIa6w7PpM8R4Bts4toPQMP7FiJ16MNQwnz15K/5EIB9IUNVVVQUn8OR/V4n8IZXjUdYmncB4VMr5uPQsncAANH1munHuFwKVzPl1YQYEfkcaVWQZjX6Tcv8idT22jmG3OoolN8kz5F4HSgTsxqVx8beJGNHc8Q6+ltB5sOifUssrjnHRCV0yOZcZ2ESSP0k+YKPx0SAE+bGqTyGvr+sL7jT6EcSVnOkHS5aPsQQrUZNSNpzE9jMxDpWA4RZzSRajfWX8UeI5mmO6HvEXj1mv4MxzxFZv/V4YDVWBpYh296zFQyzlaj6SIdjg14f8TkYmq2qRApHtRjt1iLfQkh/o7Nnz+LD/7zi3d7tWn27VziqIL7T9UY37Yb6Y19DyhBvosjzu35ARcl5Rz5HJUd2Q62oQFZWFmKT0hDbxhuef27rClSUeqPWojKa6se4FYXrkMhOjhq674ehvE9zoG+z+aZFlqUdMEVlif7Y0h7QfXPic8RqjoSfLXvhRZS2gcSp6lzTGLhd7JpZ9tHKklnWSXg5XmjNESkc8evQvntMzGpWeYDIqyfyyxDhb0ZtMk+Yty9ijYy4LvPy/miO2HxBpWVsEkiBQzb4v6cV3Gg1F9mfwJMpGp5N4qswkpFo1mp5jUBC+e2b3wIXPoQZsv3Oc2S8b0IVKRz9CYgQCEfbt2+HJ8wDT2I6onN66tsrGJ8jXvSHOzYJ0c27wx2XArWsGIeeGYYNc6eh/HyBZX8qVBWlp71Zr1u2bImIMBfiOl2JRjntqHKR6U30zy5FoTRg5HbeoOkLw2Xe8Ji3bAMWz6PCmTzs+GfYC+X3wk5ydrpnCOUnfY4YQcnOJGNLc+RQONJ8TcLcLr/MJWRZX1oA+vfn1UUvPEvkOdKOYcrzo9XoUuJQfk1zZNxmBvlb+xvKX1ZBC3t2nZl5b+uBhvLzXgxESSBF+aQUxT/NEXe8ooQje/WYTc7GJXAIQVSoOSLGAwvhiKeVtSvMUM2bvOQEx6wWeB0kUnMkqRa0gUxLtAjQwlHnzp3x4YoNSB06HYrLN9FNXvgTDuf78gwJ5QhFQWRWB/370S3f48Sipy21DqoKlOUfAwBkZWUhwuOC4vZgzBOvo/64/6Bx/5vx/PPPwx1BhzeT5+HrA78NcbSaxTnZjJyyFf5PThBOQvkraPMIianPkbhmog17Xkc2FEeI5PweZpCZ1GnNkT+6I9FeUkA0CplkhmwQAhaJbpYy0TCIJk6fYMM324r7TbTvOJTfe3SFIZSfqNOkD7xs72KB31mfyLb1PEeMZkeUcsDflA+8aDUqCCUImiODWY34KvZB9H0Oqyazmlm6AFOB2ea1DrYA41TbXpNI4ehPQATxoCVGh1H7YqOjEJ5CZ+hdvPUoikrNNUf68W292aldkXFQ3B6c3/sjzu/90bQ/FSpQln8EAJCdna1rhEqVMHhik5Fz1ViMHz+eOsbtUrhvU+LQdk1zZNgDgO+XwC/PHs3XSPHL+vDH58jRwrMucd/9GWNEi7KSOA3X1ZL/sT5H1tec+MyUNTMnapDXMczj+/2tNEfhJm/3VqHujjVHfpiPWFifI7smCvptXTtWUNb2pOn7zGbILjGY1cSaI/ra2Wuc92yL/K/MMNMwGZYPofYJjiEFNEuzmv+h/ORvbfaialbfsM6ZttoKtvxCra0mzWqSqkK7cUnzB6k5Auy9RZkJR5GZbVD/7nlo8H9volHXAQC8/kQaRb9uRfnZ0ygvPIXiwzvxj3/8AyVFZ1F++igAn+YIAM6XeJ3A9YeCeYvgmdVEj48ogZuVWc3qceT7ZFi/KTpZeLbCxKwmqkZkXmR75zWrWXbFpubIqVmN0ByRZjUHdbBlFYUeUHl1UZNSZcOqau23ZLY+FN8fzPcb2jFLssfqdTs1q1UWZ5OHUlFLNrUEvAzZlMBi89fiRW9p16ysgs1zJPY58sf8yhMIaGHNXj3ONEfWwhc9HlRdtBpZzOw+5HWhVUY8Ph7XA8O6NLDVVjASSdL1+T776bZUbcg8R7WYmHDvz0cmFItnhSMb+XfMVLMA4IlPAwAkpDcCAH2h2PN7fsSx92dSZacAqNu4JUory2RnZyMi37sEyrnSyqzcAo0Jz4wjGoiEofyVf3mqd8B6ANYcDe1oPuys1M1rW/PJ4I2FosHIVDPATG628hzZmN0da470aDUXM3GbH2emGVLAOD9zKiM3kc+C7qPDXI+bujXE51sOo3OjJHzx8xFun3jXW7R+WZWH8msCv8naaqZmNcbsypYnr7HduZBnHtHqZEP5PYLlQxTFvyzJPIdsyqcrCGY1M82RVZoHgO9wTW4JLM+Rr5zZ2M07v5gINzoQi/LWJNKsJgk613VugIbJ0Xjmhg4AxD5HgP+rJ/NIqOtVxZad8jpbF2z4H7fc0b3bUFHpuO3VHHkn2fMlXiGJO/G4BJojkSZF1xwx2zXtjFBzZP5Aejhv1nawZ1bzljGPVhMca1I9K8gFa8wJms+Rgw7xlkKhhT9yn/Ee0MxqAJ1IkuTmixvh7TEXIzZC/G7IXxRYNCkKq/H11YZDr9WxrK8aKQOYZsjmaK1EeXvs9owfreb9W8I6ZJs4jjtpu2ezFADArblZFv2xqEgv50RzRLZlXbdVNBcvQ7bd+4IOzBBLR/wXiZoVSHhCdagiNUe1kGs61sfsYe3176JoNcD/1ZN5JGV4fZc0rVBZpelMRGRMLOrUqYMIzwEAwDnNrMbVHDmL4PBZ5viDmFA4stQcGSdc0SG0iti+9sC3er2TCdhk8mM+2/nF7YTyO41W0zQGHrfiSACgBR52nwJFtMgupwbyZYCnYbAL7x4lN6mUQ7b1udKaGofCEXNP85yqnUY6CbV1NrvGy9skilYTPxvs8iHmbc4fdREO5xdR69Tx2rCvORLvM4tWEwkY5JhjNe6SQrzepmBcNOub2WPM1Uyb9qrqkT5HkiqFfYbIwaAqNUeJdb126orzBSj54yDKTv5K7Y9qchEmTJigf2/RMReK4nO01oQj3tilKAo/Wk3QF+3Byj9fytTj/SuaF60eR81XwJ5ZzdgfM7QSbKZjElE17MBJCjdWoe487IgNkRxNnhmaQ7ZXc+Tb7uQF0SAcsZojzlszpTmyWNPKznaA/xYvmpTsnJ8/UVl6+cq/rObIrmDBe1unc3/xP5v2iaNJ0aPV2AzZZuYrQT94eNwurmDE9sefNcpYzPIciQRR8p6wGnd5miOeQGU1RpgFVjgJ+HBCIC/c1H0jhSNJsGFv8KJSX7Zrg+bI6dLqJkTFxMIdkwQAOP7h3+h2khsg7boZGDp0qL6tXXdv4kfN+VDrp0iQcGRWq9yx+3ghU967XagZsRgcNF8Bp2/6ThaeLfMzCaQdFIiXGXEKT1g1Q8uMbIhWs0yfIC7rTU1g/4R4vh528lSxWE1UVn5Qhrao+8kZevJQXRg0ao7Mo9UshCg/BFnKAVrrj+6QLV4DjmpWsS/gWUE+f3bHPLNn1p9QfvKs/YlW4wdomI8R5qH8xm1O00jw8H9dNf+E2JpCmtVqIexASApH7EPnZF0xO+3GtLkUBWs+0J2yo5t3R0TDtohulgtFATp16qSXb3dxX6pPRSYO2QDfx8XKQZkNG9ZKB1NzJMJptldtkiLXDTPWKTjWxZbjTyrez9Z9seOQzXu7NYPWHPk56Ylf2IWQl96J5siscm6CTvKN3c4FpI4NXHNUwfhQkV207XPEOy/BZ9M+ccxq4khLQR1MfwKZKkW5lMww1xzR9xF1jQSHqZRZzfw+5EWrcbtjcSrmtyHvtw5cIHHqiyhqP8QVR1I4qo2wN1VxmSA0C9Zp7J3gcSlI7D0KRQd+0sP5w+o2Rnznq/QyMTExuPFvb2L59iNITEmt7IMmHPkmTx78DNn8vggHXO0tWyAd+eVzZDK4azjxOdLgHWIVncfvh/gtV4SdPEdOB0EtlN/jcgW88Kz+XbE+HzZTuaLQk4boBcGsWt71DsRHQmQatHew9w/rq2a2oKuobSuB3G7feJFy4ntUrDkKRv4n9li7Zh/T5UMU9pmyFr5os5p5H7gO2Q7M7BpmaVj40bDm9dmBN07bRZrVJFUKO4hc1a4eAOCirCRDWX/XwOHhdrmgKAqimlykbwuv40swqfUqtXErRNTP0fupm9XKaIds9tFwkgRSG0gaJEUx271//Y1W0wQ5W+uxOXzQ2VPhR0Txj2UHTtrniGwjeBmyw93+hfI79Tkid7Pnaedc2PNnJzbeW7pWVgTvsREt32KHQHw9fJojrS5jnTxfLN/x9rVWdntJ5xWq1ByZmM9EBGt4orKF25x0zdp2u8X3oUgZTzlkW5xYmM2xLqD7pop8jpya20nIWzPUzWpSOKqFsDdVwzrR2PjwZXhnzMWGssGMVtPqiqjfUt8WxmTfBmDITKy9RelmNaHmyKaqGb4BmT1n1nTFYqk58jPKyt5xdBm7Pgbe+Afj3AAAUeFJREFUsuJaSQ2P3d7f1buJZRmng6Aereaio9WcqPLZ02fXVmP3eeunYa8r776yghfxZNcRloci+GzrWEYbqker2dQckXA1Rw6EJ149bJ4jY/2i7UZB1l/oRKBVoTkS79OooLSVVi9hPM2ksz4CPlOrXYJxuZ0GapCQAqTUHEmCDu+BSYoJ576tBDNaTXubiqiXAyU8Gu74VHiSMvT92nPKRhEZzGqCJ5QfOs4vqwlHmcnRuKp9PV9pC82R1Rs/32fFfHIG7Poo0d+dqL3N6m9bP4E63o55okPDRPw0Y4BpGac+R1SGbAc+NpTmx2Qfi8jvh72/RMKRWbeqVHPkcE7Qihsdsn1l7CYJtcqt5Y9PCs/MR9cvrpMSogOYK3mpBXikxUVwj2HxJ5RfpM3lYdesZlWP2W3IOzQYmqNAfI7o5KkBd6VKkT5HtRAn93cwb0A9QWJENOqPfRlQXNSCtoD3TYZ1OGYFDrHPkX3NETlAUaurV/4V+RyVi1JnV+Ikuo/25bBRnvnOzaUjmJyMZjXf504Nk/TPZ4vLbE9vbGQjAMpfx6nmSLu2Hrf/GgHjcjB0niM7x5D3V7jbZSLciuu0ykHlVDgKRADR2jWE8gvMaoZrSNXF6Zvwi3WfAGMSSNP6ye0Kew722ub3x/eZd+8tv78P1uw7geNnijF78U5vOZOH1p8kkFR6BwcRmr567W0jMfM54h0ajPkgEJ8jsr8yz5Ek6Di5qRRFCZpTNpVoLSYJ7ugEQxnvgp+05oh9S/Jlt2be8DmaI9HYQA6ApFDlC+XnHydakFbDKsqE2k72xx+HbJ5ZTbiopbjetPhI/fOmQ/m2JhlREXIwdqw5IlIUsH5Adntj0BzB+aRJ/hZmJjWzenn3QSBjOX09/DuWTQJpV3Pp5LewbVbjZOcWBhOINEqA3+ZXszZ4Jq2slBjccFFD6kXNyfIhorZI6MSgpt3l4o8wY54Ekndw4HNBt8bJfh/rdNmdmkQKR7UQpzdVsML57djyyytU3XFUG4hZ4UxUjZMM2eS8TU7iVma1cnPFkd+CpC2HbNbnyMGbotWkpi2tcE3H+vaEIxtv+U6d+bVQ/kCi1Qyh/Ir18eypUJojM+HIpGbeI0P+xo4XnjURAO1ilgTSqnUNq7w5dmvkRqtx+tOzWQpaZcTze6UEkPKBU5feH5uCjRPNEYmdaDV/BBOr34bbptnOKtAcTbsiB3f3sfZXFFGbNEfSrFYLcXpPedwKUGpdjiQlNgIXN07Gos2H9W120vJXkJqjym1sZIbQ54gXwSFoh17k0eiQLNIQmamhAb5ZTTSJOvU5Yn83J9FqVrx6axfsPlaI1vXisWzHMcvyomYCmaDKguJzRBf2JrW00HaYCJ3+ao6szWrOxCMn0Xss2vmzC88KkxGy0WpEMZ68S9ZiP5SfrJOvOXrk6tYY2T3LtB6yP4FMlVQSSJuCjdmzxj6b5Hd2cW8N0pLvz/uoP+OB6dpqnG2BaGvcLgVje/kvGAGMcCQ1R5Jg49TL38wpm6cpaZYWizXT+iEpOpzabltzZOFzJI5W45nV+GUp8w8xAWp1C81qFtEd/prVbPkcMRUFU+0dGeZGm/oJsJtRWmu6cUoM07r5sWamNipDtr95jjiaI6fHUFpFPyLVRNDRas4wywJueWzlXzbPEZsY1Op4th9WZU3LcXyc2GfAzjgVrDxHVM4nU+EI3HLzR12Em7o1hKJ4HY7ZMSvM7cJ/78zFW3d04/rqAbRZzZ9z8UdzZO5zZDzWyq3ADKcvBNw6iM8hLhtJzVFtxLlZzVzNXMqshaTCmKtGK2tFRYVPMBH5HOl5jpjq+Bmyxf3W4GmORFgJR36b1Wz8JqwWg3c5g6JptiNQVBZ6a0w3fLD+V91J1erYtPgI/HrqPHcfmSGbvIxOJgq2pAIT4VS7j5jttD+a/86jLK4ApKPANEfev2yeI7tv3pYaTj/6RhbTHj+DtsWGf1OwTCtkU1bjnf6ZOKhvThr65qShd/NUhLtd3H51zTb3taE0R36cFn/pG/NjTJcP4WwrOO/QhEAQuGgkXhMyFJGao1qI0wdPpDlyKRaZl5l9vEGHPbxcVfUHQCvOmqqcaI7EeX/4miOr583arGbftEe2ZUc4ig6n30X4avTABww7NWjNZCREYfylzfTtLerGCY+5vUc2BrRKF+7fdrgAAGdtNYsO0ZoNep9LEetZeAvPAnQCP7OIO7PB2cok4TjPkR9+Pb5jvX/LmfO1a+az0nBS199m76hoNY6DuKgtlupePsRlUS6vdTr65qT51wkyh48fz3FUuP3xj9OkAd6h7ELdTgiC4shUmAs1pHBUSyC1Ko41RwJtiItxiNTQBlrDm6ANrcobqw9g6Xavz4s20BpD+fnH8iYyoeZI4Fdi9TZiqTlyJHmSA6116ZgIevDzJ3TXVq8CqKNVRjzmjuyCLyb0pLb3aZGK6Ve1Mk11cOqcd+B1u1z+m9UMHtlwrGoh7w0zM2DHzEThPt5dQimOqnGQ165JOeNzZNevhfI5snLItnmpeeYw9lJbmdUUMONPALe+3SSQ5PkHcdlJAPQ9Q+Yes0tMuNGQYy0cmQnFxmNPnStx3K9g0ig5ukbbd4I0q9USosLcehJFpz5HosHCxYRcG/Yz+7iaI9CDwrNLd/r2VRYXmdVY7CZGY/vmxKzmj+ZIBKU5svGbxEbQjxv3Ld7mTxvo3Cw2VQH9WtY1bC+tNJnZ6Z/HzZhkbZhXREUVWP+mBo0FGcpvojnKTI7G1xN7Iyma70Oi4XEpKKtQ6Qk4kOSqDoU9njaN/AtYJQM0CjKBQjt5VwpHTN1OzWqB9KyUCEM1e4njabyCRXyk7z66rnMDFBSVYem2o1i154St43maIytMf3fO6Z0+57/mKBikxUfif+MvQVxk6IseUnNUCwj3uKjB2OlDbWZW403qqr6fGey4zsp0GSoRmoVDNtsyz3lWdKZis1pgmiNutJpIkCD7Y8esFmFtVqsuM7ydCDySksrFje2cp9ul0LmG/BQ4AXsO1WyP7GqOAKBpWizqxEaYltE0k+S5X9kuA+0zE/0Ka3b6E7PlrXyO2DucNv9y6jcRTkWQz5/2W9u5v6l2IU5k6ZS0OF+ur3YmWhtev4PFle0ycG2n+vjH0LZQFAWjL8nG28TyRuzpkZn9ASCaIxxZugmYjGe8Q80WKa8u2jZIQBYTCBKKhL74JkGE20WZe/wK5efgFpjVNGz5HJm0q+1jHQ1Fg7odnya9Dr8dss33h9kQABunxGDvH2dxRdsMLFi1H4C93ySWNatVkc+RHcw0RzxKymk/MjM8Ljr8Pikm3KQ0K6jRDUR43ChUyswbZPpEJ4EM3CE7zOMCSsopM0xkmBufjOvhV32Of2KDL4/iXz2wZ+qyVQ9HoDJoRu1EqwVJczQ5rwUuykrCoHYZiIsUawKp1AFBftY8bheevr6D7fLP3dgBj1zdGp0eWwKALxxZmtVM9oW6w3OoI4WjWkC4x0Wpip3e9KIkkF6fI86OyieOfel2qunQmjXkORIMmk7WNROG8ltcG//yHNG8f3d3rNrzB3o2TSWEI+vfhPUpCMTnqKp8XkTzWalTzRFRLjnG3GxFwlYf4XFZL8XA7KeEowDWgdLQnp9gmWH8DeXXvyvaX2KPzfvB6vfzx+dIuy6sqSQuwnx68ZrVnLfNIz0hEjd2NS6CzcJb9qSmUBSFEiijwng+R+Z1OF0+RGIfaVarBUR4XJSA4/ShFoWnu1zmmiN2H19zZKJ5qtwnWj6EhR+tIeqb7zMvQ7YIa7Oa9SORHBOOK9vVo4QyO79JDGt24ApHltVYYicfidhUyN+h+xzZaN/DpIFIjjE3W5n55EZ4XI6SSALGtdX8gZzoteenpt7E2efOqXbR0qwm+GxaJ/FZu96scBQfZf3uXd1LSFSlz5E/kF3wS3NkM5T/jkuyAQB9W6Q66d4FjRSOagHhzATh2Kwm1BzxHz7teTNb0FPHpC/a4YZoNYU/2aTERuDO3o3RrgGxyrygAXqJCPsXxCoJGjdazUb1tjRHdswO1TRei32O+OUjK9e9MzNZaLhdLpQRQmgyk0x0XF+xn04wfI6oDNl+ao5a10vA+L5N8fg1bXRtYlXk5LEDew78Z9ZeMkDL5UNsdo53TGwEfW+IkiWSx9EO2VV/81Pt1bxsRJ1xpIO1JTVMo9WIgx8YmIN5o7rg+Zs6Oe3iBYsUjmoB4R5XQJlkhT5HnESPJIZoNRsmJ2qf7pDNvPmaNDr18paYfmUrog5R30jtgJu7nYeZAyMgynNkLUjYCQs2hvIby9h9kw50YLdzXQHg3yM6oXndWDx1fXsAwM0XN0LPZil45OrWwro9LoXKp8JqFCZd1sKQKkDvF8fnyOpUr++SCcC3vhytOfLf5+j+vBYY0a2RLtwHywrjtJpIj/V9Y7c9S7OazTrJPmiPt0FzZEeQpsY1m40HANXvajar8Vojx3Lu0i4B+Rz5Pod7XLg0p67BL0wiRl6pWkC4x6VHCwH+mNX4M7ei8NetUpllCnztOpOltW6KNEeitx7yDUo0ONAO2fYH2KrKkG1HRc8OTIEkgQzU58juWV7RNgNXtM3Qv0eFu/HG6G4AgBmf/sI9xu1SqEy8rDDsciloKVyMlP7Oak15ZKXEYMvMAbpPF5UDKwg+R5qTflWEwduBPQen/bAS4imzms2qeS9r7P0tWoOMbLe6TZWh5HME0NeeZ34WdXFMz2y8t+4Q7uptooUNsG8XOlI4qgWEu136op6AP2Y1gYChKKYaD3bwcBJNBhA+RzaWzSChkjoKyogcsi1DXy2ECidO55SvjI1BPirMDUUhl1fhCUeW1QQFp9FqTvC4FZx2kInX0ufIxjBPmvvoaLUgOGRrZrWgCUfO6mEj7pxrjqzMas77xquH1BwpCt9MBACjL8nGJ5t+w+ie2fjpUL7jtgPBbibt6sLlUvDhPd1RVFqOZE5Up6iPfx3UClMub2kq4IXA6dVqpFmtFuB9e/b/oTbNc2Tqc0Rv5woOJhOXSHOk5zkSnAc5qGrC2w2VphNfX3yfedFq13aqDwAY3pU+zjJajRfKb3qE1q51GUVRqIg1q2zFVQu/nWBMGG7GrOYE9vzDPS7Hr8CxxCQdjIVnNVNrsDMq24Vdc5Cv7RUfT/srco07jvtELnqrVUn61JndRw9f2Qprp/VHWlwkZaqvjjvfRY2j1dAgQXPB0jydGiahe5MU7j6z8cBa8yWlo0CoFcLR/v37MXr0aGRnZyMqKgpNmjTBjBkzUFJCp0LfvHkzevbsicjISGRmZuLJJ5801LVw4ULk5OQgMjISbdu2xeeff15dp+E3HpeLepCDtnxIMKLVzDRHunDEmufM+09rjrxl/3FdO7x/Vy63b+GcPEezrm2Lt+/ohpmMb0yZH2a1tDh+tBXZBzuOygDtd8T3MfB9blyZKE3zpQkm4mi1wPG4FEeZeM0EbH80P3Xjfb9XMPIchVfeE8HSNDg2q9nQHNmNWqoKvyntM/kSZNWO9oJE5hWrFp+jKkwCKWL5/X3wwd25fiU+DKSLKbHm+cUk5tQKs9r27dtRUVGBl19+GU2bNsXPP/+MMWPG4OzZs5g9ezYAoKCgAAMGDED//v3x0ksvYcuWLbj99tuRmJiIsWPHAgBWrVqF4cOHY9asWbjyyivx9ttvY8iQIdiwYQPatGlTk6doiovJOBy8aDW+Q7Y20LL7nA8mlQOgzeVDNCIIzREpzIgGNp5ZLcLjRvemRqHCiUP2Szd3woqdx3FTt0bcsmFuF+bc2AHFpRVIFQhQLF7NUXFlX3lmNd+2+klR+N//XYIojnnC6cKndgnGBOXUN81sVfhwj8sy6omlLpEtOSiaI5cxQ3YgOI3KYgVEx/0gX6yClJWdXhPN/D42w4m/YDCg1larJi1tVkqM3xmhA+ljozoxmHVtWyRFSyHJH2qFcDRw4EAMHDhQ/964cWPs2LEDL774oi4cvfXWWygpKcG8efMQHh6O1q1bY9OmTXj66ad14WjOnDkYOHAgJk+eDAB47LHHsGTJErzwwgt46aWXqv/EbOJSrMNxzRA5Gbsda46cmZyszGoiyMmgpKyc2x/yM5Uh2+LaOFl4dmCbDAxsk2FSGhjcob7pfhbS9GCV58jtUgzh/8FCpGlwcm91b1KHu26Ux6VgQKu6WLz1KPJaG9dp08hJj8P2I2cwtJPvGvKi1fq3rItrO9VHB5OFYknqxvuEo2D6HAVN6+JUc8QIx85lIwufI2fVGerhHW/3PgpojTo/IIcwp2tU1gSBdnG4jcSYEj61QjjikZ+fj+TkZP376tWr0atXL4SH+6TkvLw8/OMf/8CpU6eQlJSE1atXY+LEiVQ9eXl5+Pjjj4XtFBcXo7i4WP9eUFAQvJMQwEZxsUn1HC88KxCOFKHPkShazdkbom+1bq/mSxNMtO6IjqSEI2K9D8o8INAcWWGV56iqB2varGZ+Pas2SR19HbSIyN4OksS9cmsXrNl7AqNf/5Ha7nYpmH19e3y99SgGtE4XHv/xuB44dPIcmhG+GOwph7m9EZVOlmVIo8xqQYhWcwdbc+SMQDVHZg7v/mKhOLI9qdMm8aoXVkItCaQltaGPf1Jqhc8Ry+7du/H888/jzjvv1LcdOXIEdevSb6na9yNHjpiW0fbzmDVrFhISEvR/mZmZwrLBglVueM1f/j8kIrOaW1HMl/9g9vGErGQTuzZ5PKm9slyQkugUmcJANLCRwpGVZsjarFa1g1FilO96WYU6866TliCTXbSSxI7BjZURV0+5FB/c3V3oGMojNsKDfi2NmiGPS0F8ZBiu7dTANK9KZJibEowAevKOYAIR7BJ0zVHl71BTmgY7whFpZmV/W9rniPMMW6x9x8NqPLKvOapmsxrpnlALZr9aoNz601Kjt8eUKVP0XDuif9u3b6eO+e233zBw4EAMGzYMY8aMqfI+Tp06Ffn5+fq/Q4cOVXmbbESVVbJGK0Sh/FZCFzsZ8Cbrp4a1R8eGidzjFUo4Ipw1HZwMKRxRUTdktJrbxS3PwzpDdtU+EuP6NsXwrpne68YxE1nlYfnw7u7Y8PBlaJIaG1A/WBmxTmwEOjdKCqhOjUAcXcnf2F9/IVI4Ckb0n7Y2YE2Z1diQeMeh/ApfAHl+eEf0bZGK+y5r7qxCpg88jY/dc3SyaHQwCCSwpSaoDX38s1KjZrVJkyZh1KhRpmUaN26sf/7999/Rt29fdO/eHa+88gpVLj09HUePHqW2ad/T09NNy2j7eURERCAiwp6zbbBghSOXi5+s0S4iU5HLZZ7nyLB8CKcP2Skx+OieHrjq+e+x5bd84fGkAONEnS0SdkQ+R1bRaFe0ycDGg6eF+6tac9S2QQJmNWgn3G9lPvW4XX696bME06H7s79cgrveXI9DJ88DCOwakveMv5FmSdE+jZy/KQVIND+0UHHIdhrKTx/r+3xV+3q4qn09HC0octQftg9kne0zE/HTodO4tlMDW/VQ/pDVIgjULrOa1BzVHDUqHKWmpiI11Z6Pw2+//Ya+ffuic+fOmD9/PlzMrJ6bm4u//vWvKC0tRViYd3BcsmQJWrRogaSkJL3M0qVLce+99+rHLVmyBLm5uQgl2IHOLYgqs4tw4VmRzxEnWk1UVhskuVEwxGdywvTlObLqOe1zROIWaFjKBOU1buuRhcapMQY/GQ1/M2QHi+ryiQg0wzZJ63oJuKlrI/zjS6+W13G0GgFrVuORkRCJw/lFXJMeQE/c8ZGBD3G+PEdBEo4cVsM6ZAeyfAhPsKobH4mP7uluOx0F2weyxvmjLsLyHcdwuUUgg0Z1a45IQtEhu2PDROrlraYWO5bUEp+j3377DX369EHDhg0xe/ZsHD9+HEeOHKF8hW666SaEh4dj9OjR+OWXX/Dee+9hzpw5lAP2hAkT8OWXX+Kpp57C9u3bMXPmTPz4448YP358TZyWEFZz5LGIKrNC6HNkUS+97hHfP0nRyxr3ibQ7Wr0psdYaudJyvi+FaGBrkBRtWp/H7RJOqoD4WlUX5DWuyjwswRSOANoEJjLj2oI4VCQcfTKuB/55XTtMNDEHvXprF9zZqzEuayXWCtslLMh5jpwSyfocOby+lDlacGjHhklommbfVCvSHCXHhOPaTg0QxVlhnkd1+xyRhMLyISwvjuiMmy/2RZiFYBcvGGpFtNqSJUuwe/du7N69Gw0a0OpaLbIrISEBixcvxrhx49C5c2ekpKRg+vTpehg/AHTv3h1vv/02HnroIUybNg3NmjXDxx9/HHI5jlhTklWyRivE0WpWeY4IbY9Qc+T9a7XsBmVWqyz7wk2dMOWDzfi/fs2sTgEALTSy7X09sTfyz5ciPSGSPcwRVW1Ws0IRaMSCTbDzJJHCUUA+R4R0JPI5SouPxLAu5oERl7Wqi8taiYVgJwR94VmHz7IdzZHpAqTENa2KiLBA6iTHBaulfYJNKAoe6QmR+NuQtnjzh4MAqieCT8KnVghHo0aNsvRNAoB27drhu+++My0zbNgwDBs2LEg9Cz7f7jyOW+etpbZZRZVZIcxzJBB4NOhwXb5/km5Ws0gEx3PIbpoWi/fv7m7adxJy7GQHNidvvWaIllqpCWqLWQ2gtTyBaI7IUw5GpFkw0LSJwfo9Wmbwl5EQYcfniIQVfMnvoWalIf0hrUziwaY2ODvXhoi6Pyu1Qji6kLj3vU2GbQFrjkwzZIvrDVhzRHwO8wTuS0Pmf6qqgS0gk1CQCUWfCBERQdMc+QhGdutgoL1cBOr/8eW9PbH7WKGjdAmAMVqN1wszYZfcVyV3VJBe3MjFtauDUDSrsaTacD2QVA1SOKoFuF2BPchCh2yXudKWyiYrMMHpPkdmO8H4HPk555FDZ1UNbNWdsdeMquxK0H2O3KTmKACHbEpzFPi6aMEgWBmyc9LjkZMe7/i4QJNAkj91VTj4BlIjmTqjrEJqjjReuaUz3ll7EH8d1Kqmu3LBEjozgUQIu/Cs4+NFofwCbZCmoWGX6+ANrP6Y1fwdoEnNUaAmDm0x16va18MDA1vo22s6Wo2kKp3Dg+1bRfkcBRLKb8PnqLrRzWohnATSDNJXryrkgUAELlI7apWGI9iEsuJoQOt0zL+tq+01GyXBR2qOQoRjZ4qw+JejOHm2xLBPJJjYRWQqshrsqfWTRGY1k7rILbEWa4rZgTIPBDiwvXxLZ/x0KB8XZSVh17FCPPnlDgA1H61G4vebrckck5EQiW7ZychJd+b3YgUpyIT9yXyOmlT6szWq49/ioYFiMKtZXF5WH0xqZ6rCpy5YMkZ1m9VkmLzEDCkchQiHTp7HQx//zN3ndgX2liMaEEWTr8rZLzKrucw0R8QBmUlR+mc7b+Dhbpchx1EwzQPR4R7kNqkDgF5yJKQ0R0Huy8K7ctGlUVKVTAq8aER/CEWfo6vb10PHzEQ0IO7h6sSe5kgsWCREh2FCv2ZQFCDBYsmamqS6zWoSiRlSOAoRzCaUfi3r4vVV+/2uWzTJWq+PRH82d8jW/voWmCVLZyb78g/ZcTSO8HCEoyp6saQ1UqEjHAXbJ+KirGTrQn5C3mMBad+oDNmhIRwB9P1b3RhC+TmXhbyHeWka/FkixC7Buk2rQ3PUpn48UmLDkZFQM4KupPYghaMQQWT6+mRcD7TPTMQbqw/4XXdOery+6jqJSEbRBlqF0RyZDYKa6j81NgJHKpcjII8nJxc7ZrVwjwsoprexyTGDRat68ejSKAn1EkNrwAwh33BLqMzeAfkc+QgVzVFNY0gCGUICPBA84ai0GkL5IzxurJ7ar1YsHSKpWeToEyLwBrxwtwvtKxcnDeRZbpoWi03TLzNst8yQTUhPikXY/+09sjG8ayYGd6hHHOPb35DSHFn3mTcxdm7kzeLb3yTDtT+4XQrev7s7nhveMaj1Bkogy3BUN+S9Eqw8R+Hu0IhWq2k8bhe9mjzn8pLPy625WQB8QQdVTbASFZZXk0N2mNtVq9JkSGoGqTkKEawyTAf6thgdbvypRSYkTS1vx6ym0T4zEe0zE/Had3uJY/iao/Ml5Zb95QlHYW4XFt/bK+QS2VUVtentltIcBSlDdkRY7REOq5oIjwvnKp8b8rl9bHBrzFu5H9OuaKlvu6t3E3TNTkbb+gnV0regaY6qO0W2RGKCFI5CBJ4JhU3CGPQ2FQUVJo6cVg7ZN3TJNETSkFoDUbRaYXGZZd/CRU7kF9AbX20yq1Gh/AHMluShUWFSc6QRGebWhSPyubwlNwu3VGqKNNwupUr9y1iSY8KDUk91aY4kEjvUouH3zw3PhEJpbqpAKHAJkktOv7I1AOOCleQb6/i+TfGP69oZjnVT+YzofZPzWqBbdjIG2FgMdNa1bQEADw7MsSz7Z6U2CYJNU2PRLTsZl7dJD6jf5JGt6zlPmPhnJSbCJyiGym0x58YOuLN3Y1zSNDjmOykcSUIJqTkKEXhv26zmJti4FIXSG025PAfDL2qIhGhvuK/R5wjEd36dHpe4z+P6NsW4vk1t9a1LVjJ2/u3yC9opN5SWMrHC5VLw3p25Addzgsjz1aVR9Wk/Qp2U2AgcOnkeQOg4ZA/uUB+DO9Sv6W5IJFXChTvzhBj8RV2J/VUwHrIRaG5F0QUjbT/ZPzuDcjCzCF/IghEQOpNgdbL+wCn9M3kvXujINbYkkurlwp59Qgi+Q3bVao7YaDW2D6xDuJ0+mGmOJM6oDQtjBps7emYD8PqzSXykEMtI1CZzq0RSW5FmtRCBNxHSZqzgD4jeJUF839lkkYa11WyI0rQpLuAuXtD465DMSwJYW7i6fT20qZ+ARjWYdDEUSSE0R1I2kkiqHqk5ChGsfI4GtPbm9glWZIjWpplfk5211VjI7MhSc+QfE/o1Q9esZAzpeOH5cyiKgiapscLFki9UUmN9z718riSSqkdqjkIEK7Nan+ap+ODu7miSGrzFL12KggpSc8T0gdRciNZWY5Gao8C577LmuM+Ys1NyAUOuzl7Vz1V5eTlKS0urthGC+nG+caaoqKja2pXYo7b9PuHh4XAFIYGuFI5CBJ4fAWtW69woKehtugkTDNuH+Cjf7WGVBFKD9jkKQiclEgljVquaB0tVVRw5cgSnT5+ukvpFzOybpn/et29ftbYtsaa2/T4ulwvZ2dkIDw/MyiKFoxCBF7Zd1epzlwKoRBtsH+IjfdFCFaq9N1Z6XS0pHUkkwYA0p1fVuKAJRmlpaYiOjq62RZhLogr0z9npMrdVqFGbfp+Kigr8/vvvOHz4MBo2bBjQPSyFoxDBbMX7qsLtUkDmXWNNe3GRvtvjbHGZrUE5jPI5CryPEomEjlYrqwj+Aq3l5eW6YFSnTp2g12+G4vGZaiIjI6u1bYk1te33SU1Nxe+//46ysjKEhfmfDkQKRyECP1qtqjVHClyKTzpi+0A6xRYW2ROO2MSRkuqnXYPEmu6CJMjER4ZhVPcsFBaXIS0u+BOU5mMUHV39UYIKlFodYflnJyEqDPnnSw1LRYUqmjmtvLxcCkd/BnjRatUhW7hMzGokZ4rLbGmCyHQAUjSqGVJiI7B2Wj9ER3jQZsZXNd0dSZCYeXXrKm+jJl5oFAVQpWwUsjRIikJshAfxUbUjKWuw7mEpHIUILpdiGCSqI2SXWr/Noj07N51bJoEMCdLiQ1/9LZEA8iUq1HG7XKhzAWZol8lEQghWexRsn50XR3QybCMFHjYJpD94ZCi/RCJxQgiMEzNnzkSHDh0CrmfBggVITEwMuJ7a2o9gXMfly5dDURTTqMnqOD8pHIUQbCh9sDUvl7fNwM+P5FHbSE2POwi5IWSeI4lE4gQlQOno+PHjuPvuu9GwYUNEREQgPT0deXl5WLlyZZB6yCcrKwvPPvsste2GG27Azp07q6zN/fv3Q1EU038LFiyosvYvJKRZLYQw+B1VgXDB+hWRX3l+T9HhbpwrKXdQv0/Akg7ZEonEikCHiaFDh6KkpASvv/46GjdujKNHj2Lp0qU4ceJEcDrogKioKERFRVVZ/ZmZmTh8+LD+ffbs2fjyyy/x9ddf69sSEhLw3nvvOa67pKQk4NxAfyak5iiEMAouwRcuzJYI4UXMxUY4k5/dMgmkRPLn4uxZ8T82Y7JZ2fPnuWVd585CqfznlNOnT+O7777DP/7xD/Tt2xeNGjVC165dMXXqVFx99dV6uYMHD2Lw4MGIjY1FfHw8rr/+ehw9elRYb58+fXDvvfdS24YMGYJRo0bp+w8cOID77rtP19gAfHPPiy++iCZNmiA8PBwtWrTAG2+8Qe1XFAWvvfYarrnmGkRHR6NZs2b49NNPuf1yu91IT0/X/8XGxsLj8VDbSOHsq6++QsuWLREbG4uBAwdSgtWoUaMwZMgQPP7446hXrx5atGgBADh06BCuv/56JCYmIjk5GYMHD8b+/fv145YvX46uXbsiJiYGiYmJ6NGjBw4cOED184033kBWVhYSEhJw44034syZM/q+4uJi/OUvf0FaWhoiIyNxySWXYN26dcLfQruuDRs2RHR0NK655ppqEXylcBRCGM1qVdAGq5yy8DmKjXQmHFE+R6HgTCCRSAIjNlb8b+hQumxamrjs5ZfTZbOygNhYtGhaD21bNEDbFg386FosYmNj8fHHH6O4uJhbpqKiAoMHD8bJkyexYsUKLFmyBHv37sUNN9zguD2NDz/8EA0aNMCjjz6Kw4cPU0IHyUcffYQJEyZg0qRJ+Pnnn3HnnXfitttuw7Jly6hyjzzyCK6//nps3rwZV1xxBUaMGIGTJ0/63T8AOHfuHGbPno033ngD3377LQ4ePIj777+fKrN06VLs2LEDS5YswaJFi1BaWoq8vDzExcXhu+++w8qVK3XBqqSkBGVlZRgyZAh69+6NzZs3Y/Xq1Rg7diw1j+zZswcff/wxFi1ahEWLFmHFihV44okn9P0PPPAAPvjgA7z++uvYsGEDmjZtiry8POH5rlmzBqNHj8b48eOxadMm9O3bF3/7298CujZ2kGa1EILV3FSF5sjYhnl7cVJzJJFIQhSPx4MFCxZgzJgxeOmll9CpUyf07t0bN954I9q1awfAKwBs2bIF+/btQ2ZmJgDgP//5D1q3bo1169bhoosuctxucnIy3G434uLikJ6eLiw3e/ZsjBo1Cvfccw8AYOLEifjhhx8we/Zs9O3bVy83atQoDB8+HADw97//Hc899xzWrl2LgQMHOu6bRmlpKV566SU0adIEADB+/Hg8+uijVJmYmBi89tprujntzTffREVFBV577TVd4Jk/fz4SExOxfPlydOnSBfn5+bjyyiv1elu2bEnVWVFRgQULFiAuLg4AcMstt2Dp0qV4/PHHcfbsWbz44otYsGABLq8Ull999VUsWbIEc+fOxeTJkw3nMWfOHAwcOBAPPPAAAKB58+ZYtWoVvvzyS7+vjR2k5iiEYIWTqvDZYeu0ynPkNLcFpX2SwpFEUvspLBT/++ADuuyxY+KyX3xBl92/HygsxJk/TmHLjl9x5LfjfnVv6NCh+P333/Hpp59i4MCBWL58OTp16qQ7Jm/btg2ZmZm6YAQArVq1QmJiIrZt2+ZXm3bZtm0bevToQW3r0aOHoV1NkAO8Akt8fDyOHTsWUNvR0dG6AAMAGRkZhjrbtm1L+Rn99NNP2L17N+Li4nStXHJyMoqKirBnzx4kJydj1KhRyMvLw1VXXYU5c+YYtGZZWVm6YMS2u2fPHpSWllLXJCwsDF27dhX+Ftu2bUO3bt2obbm5uQ6vhnOkcBRCmDlLVxWUQzanwUeubo2k6DA8MLCFrfrc0qwmkfy5iIkR/2OXkzAryzoqV26Pq5OIVk0zkF4vxe8uRkZG4rLLLsPDDz+MVatWYdSoUZgxY4bf9blcLqhMZkoti3hVwGZyVhQFFQEuE8Orkz2nmJgY6nthYSE6d+6MTZs2Uf927tyJm266CYBXk7R69Wp0794d7733Hpo3b44ffvihSs+lJpDCUQjBE06qGhcVym9sv3FqLDY8fBnu6dPUVn28iDeJRCIxIxhpREhatWqFs2e9Dt4tW7bEoUOHcOjQIX3/1q1bcfr0abRq1Yp7fGpqKqURKS8vx88//0yVCQ8PR3m5eSRvy5YtDSkFVq5cKWy3punUqRN27dqFtLQ0NG3alPqXkJCgl+vYsSOmTp2KVatWoU2bNnj77bdt1a85ppPXpLS0FOvWrRNek5YtW2LNmjXUNlIYqyqkcBRCsONDRTWk1LezfIgT8x4pYLFvKRKJRBJMTpw4gUsvvRRvvvkmNm/ejH379mHhwoV48sknMXjwYABA//790bZtW4wYMQIbNmzA2rVrceutt6J3797o0qULt95LL70Un332GT777DNs374dd999tyEpYVZWFr799lv89ttv+OOPP7j1TJ48GQsWLMCLL76IXbt24emnn8aHH35ocIwOFUaMGIGUlBQMHjwY3333Hfbt24fly5fjL3/5C3799Vfs27cPU6dOxerVq3HgwAEsXrwYu3btMvgdiYiJicHdd9+NyZMn48svv8TWrVsxZswYnDt3DqNHj+Ye85e//AVffvklZs+ejV27duGFF16ocn8jQApHIQWrdakO4YJyyA6C5oqsozqEO4lEcuESGxuLbt264ZlnnkGvXr3Qpk0bPPzwwxgzZgxeeOEFAN6Xu08++QRJSUno1asX+vfvj8aNG5vmArr99tsxcuRIXYhq3Lgx5UANAI8++ij279+PJk2aIDU1lVvPkCFDMGfOHMyePRutW7fGyy+/jPnz56NPnz5BuwbBJDo6Gt9++y0aNmyIa6+9Fi1btsTo0aNRVFSE+Ph4REdHY/v27Rg6dCiaN2+OsWPHYty4cbjzzjttt/HEE09g6NChuOWWW9CpUyfs3r0bX331FZKSkrjlL774Yrz66quYM2cO2rdvj8WLF+Ohhx4K1ikLUVT5eu+IgoICJCQkID8/H/Hx8UGtu99Ty7HnuC/XR4u6cfjqvl5BbQMAsqZ8BgAY1T0LqXER+OdXOwAAKyb3QaM6MWaH6sf+36VNMWmA0Q+psLhMX+x05ZRLUT+x6hKiSazRfi8A2P/EoBrsiSSUKSoqwr59+5CdnY1I1o9IIqlFmN3LTuZvqTkKIVifHxXVoTkK7kKx0WFuPeNt6gW4WGGo8eR13iiYKZfn1HBPJBKJpPYg8xyFEKxwUh06PVIeC8bCsy6Xgq2PDES5qiLcI2Xvmub6LpnIa52OBIcpGSQSieRCRgpHIYRRc1S9bQYrWi4q3B2UeiTBQQpGEolE4gz5ah9CsNFiFdXsDibD8CUSiUQikcJRSGGIFqtmV3lPkHONSCQSiURSG5GzYQhhCOWvhjZJ7ZSUjSQSiUQiqUXC0dVXX42GDRsiMjISGRkZuOWWW/D7779TZTZv3oyePXsiMjISmZmZePLJJw31LFy4EDk5OYiMjETbtm3x+eefV9cpWGLwOaoGsxqZi0hqjiQSiUQiqUXCUd++ffHf//4XO3bswAcffIA9e/bguuuu0/cXFBRgwIABaNSoEdavX49//vOfmDlzJl555RW9zKpVqzB8+HCMHj0aGzduxJAhQzBkyBBDWviaghWOqiOJIil/1cTyJRKJRCKRhBq1Jlrtvvvu0z83atQIU6ZMwZAhQ1BaWoqwsDC89dZbKCkpwbx58xAeHo7WrVtj06ZNePrppzF27FgAwJw5czBw4EBMnjwZAPDYY49hyZIleOGFF/DSSy/VyHmR1ESeI7INJ8KRjICSSCQSyZ+VWqM5Ijl58iTeeustdO/eXV8BePXq1ejVqxfCw8P1cnl5edixYwdOnTqll+nfvz9VV15eHlavXl19nTeBzXNUHQsZk5ojO7LR7GHtcUXbdNx8caOq65REIpHYZNSoUVAUBYqiICwsDHXr1sVll12GefPmcVeDX7VqFa644gokJSXp7hVPP/20YRFZRVEQGRmJAwcOUNuHDBmCUaNG2epbTk4OIiIicOTIEb/PL1D69OmDe++917IceR21fwMHDqz6DoYotUo4evDBBxETE4M6derg4MGD+OSTT/R9R44cQd26dany2nftxhSVMbtxi4uLUVBQQP2rKmrCrEX6NdlZYPa6zg3w7xGdERkmcxlJJJLQYODAgTh8+DD279+PL774An379sWECRNw5ZVXoqysTC/30UcfoXfv3mjQoAGWLVuG7du3Y8KECfjb3/6GG2+80eDnqSgKpk+f7lefvv/+e5w/fx7XXXcdXn/99YDOr7rQrqP275133qnpLtUYNSocTZkyxSCpsv+2b9+ul588eTI2btyIxYsXw+1249Zbb61yp+VZs2YhISFB/5eZmVllbbGiSXU7ZEskEkltJCIiAunp6ahfvz46deqEadOm4ZNPPsEXX3yBBQsWAADOnj2LMWPG4Oqrr8Yrr7yCDh06ICsrC3fccQdef/11vP/++/jvf/9L1Tt+/Hi8+eabfvmlzp07FzfddBNuueUWzJs3z7D/8OHDGDRoEKKiopCdnY23334bWVlZePbZZ/Uyp0+fxh133IHU1FTEx8fj0ksvxU8//aTvnzlzJjp06IA33ngDWVlZSEhIwI033ogzZ84A8GqDVqxYgTlz5uhz6v79+y2vo/ZPtBjshUCN+hxNmjTJUj3ZuHFj/XNKSgpSUlLQvHlztGzZEpmZmfjhhx+Qm5uL9PR0HD16lDpW+56enq7/5ZXR9vOYOnUqJk6cqH8vKCioUgGJpDrkFrnssEQi4aGqKs6XllsXDDJRYW5bWmwrLr30UrRv3x4ffvgh7rjjDixevBgnTpzA/fffbyh71VVXoXnz5njnnXdwww036Nt79OiBnTt3YsqUKVi0aJHtts+cOYOFCxdizZo1yMnJQX5+Pr777jv07NlTL3Prrbfijz/+wPLlyxEWFoaJEyfi2LFjVD3Dhg1DVFQUvvjiCyQkJODll19Gv379sHPnTiQnJwMA9uzZg48//hiLFi3CqVOncP311+OJJ57A448/jjlz5mDnzp1o06YNHn30UQBAamqqsN/Lly9HWloakpKScOmll+Jvf/sb6tSpY/u8/0zUqHCUmppq+kOZodmSi4uLAQC5ubn461//qjtoA8CSJUvQokULXfrNzc3F0qVLKfvrkiVLkJubK2wnIiICERE1s4BqdQgu1Z2FWyKR1A7Ol5aj1fSvqr3drY/mITo8OFNTTk4ONm/eDADYuXMnAKBly5bCsloZklmzZqFdu3YG4caMd999F82aNUPr1q0BADfeeCPmzp2rH799+3Z8/fXXWLduHbp06QIAeO2119CsWTO9ju+//x5r167FsWPH9Dlo9uzZ+Pjjj/H+++/rgUYVFRVYsGAB4uLiAAC33HILli5discffxwJCQkIDw9HdHS0qRIA8JrUrr32WmRnZ2PPnj2YNm0aLr/8cqxevRpu94XnRlErfI7WrFmDF154AZs2bcKBAwfwzTffYPjw4WjSpIku2Nx0000IDw/H6NGj8csvv+C9997DnDlzKK3PhAkT8OWXX+Kpp57C9u3bMXPmTPz4448YP358TZ2aKVUtuOSkx1V3Em6JRCKpNlRVNWihzNwVyIAejVatWuHWW2/FlClTbLc7b9483Hzzzfr3m2++GQsXLtTNXTt27IDH40GnTp30Mk2bNqXMWD/99BMKCwtRp04dxMbG6v/27duHPXv26OWysrJ0wQgAMjIyDBooO9x44424+uqr0bZtWwwZMgSLFi3CunXrsHz5csd1/RmoFaH80dHR+PDDDzFjxgycPXsWGRkZGDhwIB566CFdok5ISMDixYsxbtw4dO7cGSkpKZg+fbouXQNA9+7d8fbbb+Ohhx7CtGnT0KxZM3z88cdo06ZNTZ0aBatJrip/oP+NvwRr9p3AsC6ZePZr45uSRCKRRIW5sfXRvBppN1hs27YN2dnZAKBrZbZt24bu3btzy3bo0IFbzyOPPILmzZvj448/tmxz69at+OGHH7B27Vo8+OCD+vby8nK8++67GDNmjK2+FxYWIiMjgyucJCYm6p81S4mGoijcKD2nNG7cGCkpKdi9ezf69esXcH21jVohHLVt2xbffPONZTlN9WnGsGHDMGzYsGB1rYqpGumobYMEtG2Q4G1Bqo4kEgkHRVGCZt6qCb755hts2bJFz5GXl5eH5ORkPPXUUwbh6NNPP8WuXbsoZ2iSzMxMjB8/HtOmTUOTJk1M2507dy569eqFf/3rX9T2+fPnY+7cuRgzZgxatGiBsrIybNy4EZ07dwYA7N69W087AwCdOnXCkSNH4PF4kJWV5fDsfYSHhxvSFNjh119/xYkTJ5CRkeF327WZWmFWu1CpDsGlOhJNSiQSSVVSXFyMI0eO4LfffsOGDRvw97//HYMHD8aVV16JW2+9FQAQExODl19+GZ988gnGjh2LzZs3Y//+/Zg7dy5GjRqFMWPG4IorrhC2MXXqVPz+++/4+uuvhWVKS0vxxhtvYPjw4WjTpg3174477sCaNWvwyy+/ICcnB/3798fYsWOxdu1abNy4EWPHjkVUVJRuBuzfvz9yc3MxZMgQLF68GPv378eqVavw17/+FT/++KPta5OVlYU1a9Zg//79+OOPP7hapcLCQkyePBk//PAD9u/fj6VLl2Lw4MFo2rQp8vKqX3sYCkjhKISpnoVnq6ERiUQiqUK+/PJLZGRkICsrCwMHDsSyZcvw3HPP4ZNPPqGcia+77josW7YMBw8eRM+ePZGdnY077rgDU6ZMoZaa4pGcnIwHH3wQRUVFwjKffvopTpw4gWuuucawr2XLlmjZsiXmzp0LAPjPf/6DunXrolevXrjmmmswZswYxMXFITIyEoBXc/f555+jV69euO2229C8eXPceOONOHDggCFfnxn3338/3G43WrVqhdTUVBw8eNBQxu12Y/Pmzbj66qvRvHlzjB49Gp07d8Z3331XYwFJNY2iVkcynT8RBQUFSEhIQH5+PuLj44Na9x2v/4ivt/lSDSRFh2Hj9AFBbYPliS+246UVXue+/U8MqtK2JBJJaFJUVIR9+/YhOztbn5wvBIqKijB48GAcOnQIK1as8Dt6Ohj8+uuvyMzMxNdff31B+vgEC7N72cn8LTVHIUz1LDwrZWOJRHJhEhkZiU8++QS33norvv3222pt+5tvvsGnn36Kffv2YdWqVbjxxhuRlZWFXr16VWs/JHxqr7fdBUB1CC5SNJJIJBcykZGRjsL0g0VpaSmmTZuGvXv3Ii4uDt27d8dbb71liD6T1AxSOAphqkNwCXNX/3puEolEcqGTl5d3wTo71wakcBRCGDLmV4N0dMcljbFk61EM7lC/6huTSCQSiaQWIIWjEKY6lvZIignH4vt6V3k7EolEIpHUFqRDdggj/YEkEolEIql+pHAUwshFYSUSiUQiqX6kcBRCGFyOpGwkkUgkEkm1I4WjEEbKRhKJRCKRVD9SOAplpHQkkUgktYaZM2eiQ4cONd0NSRCQwlEIIxeFlUgkEnNGjRoFRVGgKArCwsKQnZ2NBx54wHQNtKri/vvvx9KlS6utvV9//RXh4eFo06ZNtbV5oSCFoxCCzXMkF4WVSCQSawYOHIjDhw9j7969eOaZZ/Dyyy9jxowZ1d6P2NhY1KlTp9raW7BgAa6//noUFBRgzZo1Vd5eaWlplbcRKkjhKIRgHbBltJpEIpFYExERgfT0dGRmZmLIkCHo378/lixZou/PysrCs88+Sx3ToUMHzJw5U/+uKApee+01XHPNNYiOjkazZs3w6aef6vuXL18ORVGwdOlSdOnSBdHR0ejevTt27Nihl2HNaqNGjcKQIUMwe/ZsZGRkoE6dOhg3bhwlZBw+fBiDBg1CVFQUsrOz8fbbb3P7y6KqKubPn49bbrkFN910E+bOnavvmzZtGrp162Y4pn379nj00Uf176+99hpatmyJyMhI5OTk4N///re+b//+/VAUBe+99x569+6NyMhIvPXWWzhx4gSGDx+O+vXrIzo6Gm3btsU777xDtXPmzBmMGDECMTExyMjIwDPPPIM+ffrg3nvv1csUFxfj/vvvR/369RETE4Nu3bph+fLlpudcncgkkCGMlI0kEklNoaoqzp07V+3tRkdHQzEsF2Cfn3/+GatWrUKjRo0cH/vII4/gySefxD//+U88//zzGDFiBA4cOIDk5GS9zF//+lc89dRTSE1NxV133YXbb78dK1euFNa5bNkyZGRkYNmyZdi9ezduuOEGdOjQAWPGjAEA3Hrrrfjjjz+wfPlyhIWFYeLEiTh27JhlX5ctW4Zz586hf//+qF+/Prp3745nnnkGMTExGDFiBGbNmoU9e/agSZMmAIBffvkFmzdvxgcffAAAeOuttzB9+nS88MIL6NixIzZu3IgxY8YgJiYGI0eO1NuZMmUKnnrqKXTs2BGRkZEoKipC586d8eCDDyI+Ph6fffYZbrnlFjRp0gRdu3YFAEycOBErV67Ep59+irp162L69OnYsGEDJTiOHz8eW7duxbvvvot69erho48+wsCBA7FlyxY0a9bM/o9WVagSR+Tn56sA1Pz8/KDXPeb1dWqjBxdR/yQSiaSqOX/+vLp161b1/Pnz+rbCwkIV3rCQav1XWFjoqO8jR45U3W63GhMTo0ZERKgAVJfLpb7//vt6mUaNGqnPPPMMdVz79u3VGTNm6N8BqA899JDh/L/44gtVVVV12bJlKgD166+/1st89tlnKgD9us2YMUNt37491bdGjRqpZWVl+rZhw4apN9xwg6qqqrpt2zYVgLpu3Tp9/65du1QAhv6y3HTTTeq9995Lnc/8+fOp748++qj+ferUqWq3bt30702aNFHffvttqs7HHntMzc3NVVVVVfft26cCUJ999lnTfqiqqg4aNEidNGmSqqqqWlBQoIaFhakLFy7U958+fVqNjo5WJ0yYoKqqqh44cEB1u93qb7/9RtXTr18/derUqZbtmcG7lzWczN9ScxRCBPCyJJFIJBcsffv2xYsvvoizZ8/imWeegcfjwdChQx3X065dO/1zTEwM4uPjDVocskxGRgYA4NixY2jYsCG3ztatW8PtdlPHbNmyBQCwY8cOeDwedOrUSd/ftGlTJCUlmfbz9OnT+PDDD/H999/r226++WbMnTsXo0aNAgCMGDEC8+bNw8MPPwxVVfHOO+9g4sSJAICzZ89iz549GD16tK7BAoCysjIkJCRQbXXp0oX6Xl5ejr///e/473//i99++w0lJSUoLi5GdHQ0AGDv3r0oLS3VtUgAkJCQgBYtWujft2zZgvLycjRv3pyqu7i4uFp9tsyQwpFEIpFIDERHR6OwsLBG2nVKTEwMmjZtCgCYN28e2rdvj7lz52L06NEAAJfLBZXxU+A5F4eFhVHfFUVBRUWFsIxm/mPLOK3TKW+//TaKiooovyJVVVFRUYGdO3eiefPmGD58OB588EFs2LAB58+fx6FDh3DDDTcAgP67vvrqqwbfJFKQA7zXluSf//wn5syZg2effRZt27ZFTEwM7r33XpSUlNjuf2FhIdxuN9avX29oLzY21nY9VYkUjkKYvNZ1a7oLEonkAkVRFMPEWBtwuVyYNm0aJk6ciJtuuglRUVFITU3F4cOH9TIFBQXYt29fDfbSS4sWLVBWVoaNGzeic+fOAIDdu3fj1KlTpsfNnTsXkyZN0rVEGvfccw/mzZuHJ554Ag0aNEDv3r3x1ltv4fz587jsssuQlpYGAKhbty7q1auHvXv3YsSIEY76vHLlSgwePBg333wzAOgCWatWrQAAjRs3RlhYGNatW6dr0/Lz87Fz50706tULANCxY0eUl5fj2LFj6Nmzp6P2qwsZrRZCRIb5JOi/DWmDfw5rX4O9kUgkktrJsGHD4Ha78a9//QsAcOmll+KNN97Ad999hy1btmDkyJEGjUVNkJOTg/79+2Ps2LFYu3YtNm7ciLFjxyIqKkrolL5p0yZs2LABd9xxB9q0aUP9Gz58OF5//XWUlZUB8JrW3n33XSxcuNAgBD3yyCOYNWsWnnvuOezcuRNbtmzB/Pnz8fTTT5v2uVmzZliyZAlWrVqFbdu24c4778TRo0f1/XFxcRg5ciQmT56MZcuW4ZdffsHo0aPhcrn0c2revDlGjBiBW2+9FR9++CH27duHtWvXYtasWfjss88CuaRBQwpHIcSDA3PQODUGj1zdGjdf3AjxkWHWB0kkEomEwuPxYPz48XjyySdx9uxZTJ06Fb1798aVV16JQYMGYciQIXoUV03zn//8B3Xr1kWvXr1wzTXXYMyYMYiLi0NkZCS3/Ny5c9GqVSvk5OQY9l1zzTU4duwYPv/8cwDAddddhxMnTuDcuXMYMmQIVfaOO+7Aa6+9hvnz56Nt27bo3bs3FixYgOzsbNP+PvTQQ+jUqRPy8vLQp08fpKenG+p++umnkZubiyuvvBL9+/dHjx499JQBGvPnz8ett96KSZMmoUWLFhgyZAilbappFJU1xEpMKSgoQEJCAvLz8xEfH1/T3ZFIJJKAKSoqwr59+5CdnS2clCXVw6+//orMzEx8/fXX6NevX013JyicPXsW9evXx1NPPaX7gVUVZveyk/lb+hxJJBKJRFJDfPPNNygsLETbtm1x+PBhPPDAA8jKytL9c2ojGzduxPbt29G1a1fk5+friScHDx5cwz2zjxSOJBKJRCKpIUpLSzFt2jTs3bsXcXFx6N69O9566y1DlFttY/bs2dixYwfCw8PRuXNnfPfdd0hJSanpbtlGCkcSiUQikdQQeXl5yMvLq+luBJWOHTti/fr1Nd2NgJAO2RKJRCKRSCQEUjiSSCQSiUQiIZDCkUQikUgAwJBFWiKpbQTrHpbCkUQikVzgaM6/586dq+GeSCSBoS1jEmiST+mQLZFIJBc4brcbiYmJ+iKr0dHRwgzNEkmoUlFRgePHjyM6OhoeT2DijRSOJBKJRIL09HQAMKxCL5HUJlwuFxo2bBiwcC+FI4lEIpFAURRkZGQgLS2Nu2K9RFIbCA8Ph8sVuMeQFI4kEolEouN2u0NiUVaJpCaRDtkSiUQikUgkBFI4kkgkEolEIiGQwpFEIpFIJBIJgfQ5coiWYKqgoKCGeyKRSCQSicQu2rxtJ1GkFI4ccubMGQBAZmZmDfdEIpFIJBKJU86cOYOEhATTMooq88U7oqKiAr///jvi4uKCniStoKAAmZmZOHToEOLj44Nat0Re36pGXt+qRV7fqkVe36olFK6vqqo4c+YM6tWrZxnuLzVHDnG5XGjQoEGVthEfHy8fzipEXt+qRV7fqkVe36pFXt+qpaavr5XGSEM6ZEskEolEIpEQSOFIIpFIJBKJhEAKRyFEREQEZsyYgYiIiJruyp8SeX2rFnl9qxZ5fasWeX2rltp2faVDtkQikUgkEgmB1BxJJBKJRCKREEjhSCKRSCQSiYRACkcSiUQikUgkBFI4kkgkEolEIiGQwlGI8K9//QtZWVmIjIxEt27dsHbt2pruUq3g22+/xVVXXYV69epBURR8/PHH1H5VVTF9+nRkZGQgKioK/fv3x65du6gyJ0+exIgRIxAfH4/ExESMHj0ahYWF1XgWocusWbNw0UUXIS4uDmlpaRgyZAh27NhBlSkqKsK4ceNQp04dxMbGYujQoTh69ChV5uDBgxg0aBCio6ORlpaGyZMno6ysrDpPJSR58cUX0a5dOz0xXm5uLr744gt9v7y2weWJJ56Aoii499579W3yGvvPzJkzoSgK9S8nJ0ffX5uvrRSOQoD33nsPEydOxIwZM7Bhwwa0b98eeXl5OHbsWE13LeQ5e/Ys2rdvj3/961/c/U8++SSee+45vPTSS1izZg1iYmKQl5eHoqIivcyIESPwyy+/YMmSJVi0aBG+/fZbjB07trpOIaRZsWIFxo0bhx9++AFLlixBaWkpBgwYgLNnz+pl7rvvPvzvf//DwoULsWLFCvz++++49tpr9f3l5eUYNGgQSkpKsGrVKrz++utYsGABpk+fXhOnFFI0aNAATzzxBNavX48ff/wRl156KQYPHoxffvkFgLy2wWTdunV4+eWX0a5dO2q7vMaB0bp1axw+fFj/9/333+v7avW1VSU1TteuXdVx48bp38vLy9V69eqps2bNqsFe1T4AqB999JH+vaKiQk1PT1f/+c9/6ttOnz6tRkREqO+8846qqqq6detWFYC6bt06vcwXX3yhKoqi/vbbb9XW99rCsWPHVADqihUrVFX1Xs+wsDB14cKFeplt27apANTVq1erqqqqn3/+uepyudQjR47oZV588UU1Pj5eLS4urt4TqAUkJSWpr732mry2QeTMmTNqs2bN1CVLlqi9e/dWJ0yYoKqqvH8DZcaMGWr79u25+2r7tZWaoxqmpKQE69evR//+/fVtLpcL/fv3x+rVq2uwZ7Wfffv24ciRI9S1TUhIQLdu3fRru3r1aiQmJqJLly56mf79+8PlcmHNmjXV3udQJz8/HwCQnJwMAFi/fj1KS0upa5yTk4OGDRtS17ht27aoW7euXiYvLw8FBQW6hkTifYt+9913cfbsWeTm5sprG0TGjRuHQYMGUdcSkPdvMNi1axfq1auHxo0bY8SIETh48CCA2n9t5cKzNcwff/yB8vJy6uYAgLp162L79u011Ks/B0eOHAEA7rXV9h05cgRpaWnUfo/Hg+TkZL2MxEtFRQXuvfde9OjRA23atAHgvX7h4eFITEykyrLXmPcbaPsudLZs2YLc3FwUFRUhNjYWH330EVq1aoVNmzbJaxsE3n33XWzYsAHr1q0z7JP3b2B069YNCxYsQIsWLXD48GE88sgj6NmzJ37++edaf22lcCSRSGwxbtw4/Pzzz5RPgSRwWrRogU2bNiE/Px/vv/8+Ro4ciRUrVtR0t/4UHDp0CBMmTMCSJUsQGRlZ093503H55Zfrn9u1a4du3bqhUaNG+O9//4uoqKga7FngSLNaDZOSkgK3223w4D969CjS09NrqFd/DrTrZ3Zt09PTDY7vZWVlOHnypLz+BOPHj8eiRYuwbNkyNGjQQN+enp6OkpISnD59mirPXmPeb6Dtu9AJDw9H06ZN0blzZ8yaNQvt27fHnDlz5LUNAuvXr8exY8fQqVMneDweeDwerFixAs899xw8Hg/q1q0rr3EQSUxMRPPmzbF79+5af/9K4aiGCQ8PR+fOnbF06VJ9W0VFBZYuXYrc3Nwa7FntJzs7G+np6dS1LSgowJo1a/Rrm5ubi9OnT2P9+vV6mW+++QYVFRXo1q1btfc51FBVFePHj8dHH32Eb775BtnZ2dT+zp07IywsjLrGO3bswMGDB6lrvGXLFkoIXbJkCeLj49GqVavqOZFaREVFBYqLi+W1DQL9+vXDli1bsGnTJv1fly5dMGLECP2zvMbBo7CwEHv27EFGRkbtv39r1B1coqqqqr777rtqRESEumDBAnXr1q3q2LFj1cTERMqDX8LnzJkz6saNG9WNGzeqANSnn35a3bhxo3rgwAFVVVX1iSeeUBMTE9VPPvlE3bx5szp48GA1OztbPX/+vF7HwIED1Y4dO6pr1qxRv//+e7VZs2bq8OHDa+qUQoq7775bTUhIUJcvX64ePnxY/3fu3Dm9zF133aU2bNhQ/eabb9Qff/xRzc3NVXNzc/X9ZWVlaps2bdQBAwaomzZtUr/88ks1NTVVnTp1ak2cUkgxZcoUdcWKFeq+ffvUzZs3q1OmTFEVRVEXL16sqqq8tlUBGa2mqvIaB8KkSZPU5cuXq/v27VNXrlyp9u/fX01JSVGPHTumqmrtvrZSOAoRnn/+ebVhw4ZqeHi42rVrV/WHH36o6S7VCpYtW6YCMPwbOXKkqqrecP6HH35YrVu3rhoREaH269dP3bFjB1XHiRMn1OHDh6uxsbFqfHy8etttt6lnzpypgbMJPXjXFoA6f/58vcz58+fVe+65R01KSlKjo6PVa665Rj18+DBVz/79+9XLL79cjYqKUlNSUtRJkyappaWl1Xw2ocftt9+uNmrUSA0PD1dTU1PVfv366YKRqsprWxWwwpG8xv5zww03qBkZGWp4eLhav3599YYbblB3796t76/N11ZRVVWtGZ2VRCKRSCQSSeghfY4kEolEIpFICKRwJJFIJBKJREIghSOJRCKRSCQSAikcSSQSiUQikRBI4UgikUgkEomEQApHEolEIpFIJARSOJJIJBKJRCIhkMKRRCK5INi/fz8URcGmTZuqrI1Ro0ZhyJAhVVa/RCKpHqRwJJFIagWjRo2CoiiGfwMHDrR1fGZmJg4fPow2bdpUcU8lEkltx1PTHZBIJBK7DBw4EPPnz6e2RURE2DrW7XbX+ErfEomkdiA1RxKJpNYQERGB9PR06l9SUhIAQFEUvPjii7j88ssRFRWFxo0b4/3339ePZc1qp06dwogRI5CamoqoqCg0a9aMEry2bNmCSy+9FFFRUahTpw7Gjh2LwsJCfX95eTkmTpyIxMRE1KlTBw888ADY1ZgqKiowa9YsZGdnIyoqCu3bt6f6JJFIQhMpHEkkkj8NDz/8MIYOHYqffvoJI0aMwI033oht27YJy27duhVffPEFtm3bhhdffBEpKSkAgLNnzyIvLw9JSUlYt24dFi5ciK+//hrjx4/Xj3/qqaewYMECzJs3D99//z1OnjyJjz76iGpj1qxZ+M9//oOXXnoJv/zyC+677z7cfPPNWLFiRdVdBIlEEjg1vPCtRCKR2GLkyJGq2+1WY2JiqH+PP/64qqqqCkC96667qGO6deum3n333aqqquq+fftUAOrGjRtVVVXVq666Sr3tttu4bb3yyitqUlKSWlhYqG/77LPPVJfLpR45ckRVVVXNyMhQn3zySX1/aWmp2qBBA3Xw4MGqqqpqUVGRGh0dra5atYqqe/To0erw4cP9vxASiaTKkT5HEomk1tC3b1+8+OKL1Lbk5GT9c25uLrUvNzdXGJ129913Y+jQodiwYQMGDBiAIUOGoHv37gCAbdu2oX379oiJidHL9+jRAxUVFdixYwciIyNx+PBhdOvWTd/v8XjQpUsX3bS2e/dunDt3DpdddhnVbklJCTp27Oj85CUSSbUhhSOJRFJriImJQdOmTYNS1+WXX44DBw7g888/x5IlS9CvXz+MGzcOs2fPDkr9mn/SZ599hvr161P77DqRSySSmkH6HEkkkj8NP/zwg+F7y5YtheVTU1MxcuRIvPnmm3j22WfxyiuvAABatmyJn376CWfPntXLrly5Ei6XCy1atEBCQgIyMjKwZs0afX9ZWRnWr1+vf2/VqhUiIiJw8OBBNG3alPqXmZkZrFOWSCRVgNQcSSSSWkNxcTGOHDlCbfN4PLoj9cKFC9GlSxdccskleOutt7B27VrMnTuXW9f06dPRuXNntG7dGsXFxVi0aJEuSI0YMQIzZszAyJEjMXPmTBw/fhz/93//h1tuuQV169YFAEyYMAFPPPEEmjVrhpycHDz99NM4ffq0Xn9cXBzuv/9+3HfffaioqMAll1yC/Px8rFy5EvHx8Rg5cmQVXCGJRBIMpHAkkUhqDV9++SUyMjKobS1atMD27dsBAI888gjeffdd3HPPPcjIyMA777yDVq1acesKDw/H1KlTsX//fkRFRaFnz5549913AQDR0dH46quvMGHCBFx00UWIjo7G0KFD8fTTT+vHT5o0CYcPH8bIkSPhcrlw++2345prrkF+fr5e5rHHHkNqaipmzZqFvXv3IjExEZ06dcK0adOCfWkkEkkQUVSVScwhkUgktRBFUfDRRx/J5TskEknASJ8jiUQikUgkEgIpHEkkEolEIpEQSJ8jiUTyp0B6CEgkkmAhNUcSiUQikUgkBFI4kkgkEolEIiGQwpFEIpFIJBIJgRSOJBKJRCKRSAikcCSRSCQSiURCIIUjiUQikUgkEgIpHEkkEolEIpEQSOFIIpFIJBKJhEAKRxKJRCKRSCQE/w+JUbBNPry0zQAAAABJRU5ErkJggg==",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Average score: -11.4\n",
            "Maximum score: 284.3\n",
            "Minimum score: -353.5\n",
            "Average episode length: 374.3\n"
          ]
        }
      ],
      "source": [
        "# Reset the second lunar lander DQN agent\n",
        "dqn_agent5 = DQNAgent(name, alpha, epsilon, gamma, tau, lr_period, lr_decay, batch_size, buffer_size)\n",
        "  \n",
        "# If GPU device is available\n",
        "if torch.cuda.is_available():\n",
        "    episodes = 730\n",
        "    print(\"Device: cuda\")\n",
        "else:\n",
        "    episodes = 513\n",
        "    print(\"Device: cpu\")\n",
        "\n",
        "# Train for specified number of episodes\n",
        "dqn_agent5.iterate(episodes, verbose = False, video = True)\n",
        "\n",
        "# Print average, max, min\n",
        "average, max, min, avg_length = dqn_agent5.score_stats(verbose = True)\n"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "[Link to the video of the fifth DQN agent in the 343<sup>rd</sup> episode](videos/dqn-agent-5-episode-353.mp4)"
      ]
    },
    {
      "attachments": {},
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      "source": [
        "[Link to the video of the fifth DQN agent in the 512<sup>th</sup> episode](videos/dqn-agent-5-episode-512.mp4)"
      ]
    },
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      "source": [
        "The average has increased slightly compared to Agent 4 and the average episode length has decreased. However, we are still a long ways from consistently solving the problem. In the video of Episode 343, the agent lands more or less successfully, but in the final episode, its just hovering at the top of the screen. More tuning is obviously necessary and a longer training time, but we will leave that for another day and another report."
      ]
    },
    {
      "attachments": {},
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      "source": [
        "## Discussion ## \n",
        "\n",
        "As predicted, the DQN agent performed better than the non-learning agents. Of the four types, the random agent performed the worst.Surprisingly, the reflex agent was not much better than an agentless lunar lander falling to the ground.\n",
        "\n",
        "In tuning the DQN agent hyperparameters, it tentatively appears that incentivizing landing through a lower discount rate, giving more time for learning by slowing the learning rate decay, encouraging exploration through a slower epsilon-greedy decay rate, and increasing memory capacity through larger batch samples and replay buffer size all contributed toward achieving higher scores. More tuning is necessary, however. In particular, it will be important to determine to what extent each of these hyperparameters contribute as well as any interactions.\n",
        "\n",
        "Although the non-learning agent results are somewhat trivial, they provide a useful baseline for comparison with reinforcement learning agents. In addition, coding and running the non-learning agents allowed me to set up and confirm the environment, agent class objects, and visualization tools were working before taking on the more daunting task of designing a DQN model. \n",
        "\n",
        "Coding and then tuning the DQN agent hyperparameters was particularly challenging. This is in part due to the fact that it takes hundreds of episodes of training before trends or problems might appear. An agent that appears to be doing well in the first 100 episodes, might prove to be worthless after 500 episodes. I would have liked to explore hyperparameter tuning more, but time and computer resources were limiting factors."
      ]
    },
    {
      "attachments": {},
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        "id": "b5V6pQeQtVWQ"
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      "source": [
        "### Suggestions for Future Work ###\n",
        "\n",
        "There are a number of directions for future research:\n",
        "\n",
        "I have only explored a few optimizations in this paper. There are still many ways to improve upon the DQN model presented here, ranging from more hyperparameter tuning to the exploration of different optimization algorithms and neural network architectures. More rigorous model testing is also needed. In addition, the Gymnasium lunar lander environment is deterministic. In such environments, Machado and his colleagues (2018) recommend introducing stochasticity with frame skipping and sticky actions that repeat with a given probability in order to test the robustness of models in more realistic environments. Another direction for exploration is applying convolutional neural networks and comparing the results with the state features-based model.\n",
        "\n",
        "More complex Gymnasium environments, such as the \"Arcade Learning Environment\" (Bellemare, 2023; Bellemare et al., 2013; Machado et al., 2018), which simulates classic Atari 2600 games (AtariAge, 2023), can also provide opportunities to explore more challenging problems. \n",
        "\n",
        "### Conclusion ###\n",
        "This project compared four different artificial agents in a lunar lander simulation. As expected, the deep reinforcement learning agent performed better than the three non-learning agents. Of the three non-learning agents, the simple reflex agent was only slightly better than an agentless lunar lander, and acting randomly was the worst strategy. A deep Q-network with three fully-connected neural network layers was used for the learning agent.\n",
        "\n",
        "Finally, it is only natural to ask: What is the value of crashing a virtual lunar lander model hundreds of times in order to eventually land successfully? There are two main reasons. First, it is better to train a far less-expensive virtual model and then transfer that learning to a real-world environment. Thus, the long-term aim is to develop the ability to transfer this virtual knowledge to a real-world environment. Second, through this project, I have gained skills and experience with deep reinforcement learning that I can build on to explore more sophisticated artificial intelligence algorithms in the future."
      ]
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      "source": [
        "## References ##\n",
        "\n",
        "_AtariAge._ (2023). [Website]. [https://atariage.com](https://atariage.com)\n",
        "\n",
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        "\n",
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        "\n",
        "_Gymnasium._ (2022). Farama Foundation. [https://gymnasium.farama.org/](https://gymnasium.farama.org/)\n",
        "\n",
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        "\n",
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        "\n",
        "Machado, M. C., Bellemare, M. G., Talvitie, E., Veness, J., Hausknecht, M., & Bowling, M. (2018). Revisiting the Arcade Learning Environment: Evaluation protocols and open problems for general agents. _Journal of Artificial Intelligence Research, 61,_ 523–562. [https://doi.org/10.1613/jair.5699](https://doi.org/10.1613/jair.5699)\n",
        "\n",
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        "\n",
        "Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., Petersen, S., Beattie, C., Sadik, A., Antonoglou, I., King, H., Kumaran, D., Wierstra, D., Legg, S., & Hassabis, D. (2015). Human-level control through deep reinforcement learning. _Nature, 518_, 529–533. [https://doi.org/10.1038/nature14236](https://doi.org/10.1038/nature14236)\n",
        "\n",
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        "\n",
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        "\n",
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        "\n",
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        "\n",
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        "\n",
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        "\n",
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