Dyna-Q, Dyna-Q+ Learning.ipynb

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   "cell_type": "code",
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   "metadata": {
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     "end_time": "2020-07-18T07:21:39.738126Z",
     "start_time": "2020-07-18T07:21:38.800732Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-18T07:21:39.744932Z",
     "start_time": "2020-07-18T07:21:39.740287Z"
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   },
   "outputs": [],
   "source": [
    "def get_label(x):\n",
    "    if x==0:\n",
    "        return 'Left'\n",
    "    elif x==1:\n",
    "        return 'Right'\n",
    "    elif x==2:\n",
    "        return 'Up'\n",
    "    elif x==3:\n",
    "        return 'Down'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-18T07:21:39.975622Z",
     "start_time": "2020-07-18T07:21:39.748556Z"
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   "source": [
    "class DynaMaze:\n",
    "    \n",
    "    def __init__(self, grid_size, n, terminal_state, blocked_blocks, mode_type = 'DQ', verbose=False):\n",
    "        \n",
    "        self.grid_size = grid_size\n",
    "        self.n = n\n",
    "        self.terminal_state = terminal_state\n",
    "        self.blocked_blocks = blocked_blocks\n",
    "        self.mode_type = mode_type\n",
    "        self.verbose = verbose\n",
    "        self.gamma = 0.1\n",
    "        \n",
    "        self.Q = np.zeros((self.grid_size, self.grid_size, 4)) + 0.25\n",
    "        \n",
    "        self.actions = [(0,-1), (0, 1), (-1,0), (1, 0)]# Left, Right, Up, Down\n",
    "\n",
    "        #Equi-probable action selection at each state for all actions\n",
    "        self.policy = np.random.randint(1,4,size = (self.grid_size, self.grid_size))\n",
    "                \n",
    "        if self.verbose:\n",
    "            print(\"Shape of Q\", self.Q.shape)\n",
    "            print(\"Shape of Policy\", self.policy.shape)\n",
    "            print(\"Initial State-Action/Q Function\", *self.Q, sep='\\n',end='\\n\\n')\n",
    "            print(\"Initial Policy\", *self.policy, sep='\\n',end='\\n\\n')\n",
    "        \n",
    "    def _get_reward(self, x, y, a):\n",
    "        \n",
    "        # Reward of 30, -2, -1 on reaching the terminal state, \n",
    "        # blocked blocks and other blocks respectively.\n",
    "        \n",
    "        if x+a[0]==self.terminal_state[0] and y+a[1]==self.terminal_state[1]:\n",
    "            return 30\n",
    "        if (x+a[0]==-1 or x+a[0]==self.grid_size) or (y+a[1]==-1 or y+a[1]==self.grid_size):\n",
    "            return -3\n",
    "        if (x+a[0],y+a[1]) in self.blocked_blocks:\n",
    "            return -3\n",
    "        return -1\n",
    "\n",
    "    def _get_time_dependent_reward(self, x, y, a, t):\n",
    "        \n",
    "        # Reward of 30, -2, -1 on reaching the terminal state, \n",
    "        # blocked blocks and other maze blocks respectively.\n",
    "        \n",
    "        if x+a[0]==self.terminal_state[0] and y+a[1]==self.terminal_state[1]:\n",
    "            return 30\n",
    "        if (x+a[0]==-1 or x+a[0]==self.grid_size) or (y+a[1]==-1 or y+a[1]==self.grid_size):\n",
    "            return -3\n",
    "        if (x+a[0],y+a[1]) in self.blocked_blocks:\n",
    "            return -3\n",
    "        return (-1 + 0.00000000001*np.sqrt(t))\n",
    "    \n",
    "    def _get_next_state(self, x, y, a):\n",
    "        \n",
    "        if (x+a[0], y+a[1]) in self.blocked_blocks:\n",
    "            return x,y\n",
    "        if x+a[0]!=-1 and x+a[0]!=self.grid_size:\n",
    "            x = x + a[0]\n",
    "        if y+a[1]!=-1 and y+a[1]!=self.grid_size:\n",
    "            y = y + a[1]\n",
    "        return x,y\n",
    "        \n",
    "    def play(self, epochs = 100, threshold = 1e-8, changed=True):\n",
    "        \n",
    "        if self.mode_type == 'DQ':\n",
    "            res = self._play_dq(epochs, threshold, changed)\n",
    "            \n",
    "            fig, ax = plt.subplots(figsize=(self.grid_size*2, self.grid_size*2))\n",
    "            anotations = np.array(list(map(get_label, self.policy.reshape(-1,1)))).reshape(self.policy.shape)\n",
    "            anotations[self.terminal_state[0], self.terminal_state[1]] = 'Terminal'\n",
    "            for i,j in self.blocked_blocks:\n",
    "                anotations[i,j] = 'Blocked'\n",
    "            sns.heatmap(self.policy, annot=anotations, fmt='', cmap='Blues', ax = ax)\n",
    "            plt.show()\n",
    "            \n",
    "            if self.verbose:\n",
    "                print(\"Final Policy:\")\n",
    "                print(*self.policy, sep = '\\n', end = '\\n\\n')\n",
    "                print(\"Final State-Action/Q Function:\")\n",
    "                print(*self.Q, sep = '\\n', end = '\\n\\n')\n",
    "                \n",
    "            return res\n",
    "        \n",
    "        elif self.mode_type == 'DQ+':\n",
    "            res = self._play_dq_plus(epochs, threshold, changed)\n",
    "            \n",
    "            fig, ax = plt.subplots(figsize=(self.grid_size*2, self.grid_size*2))\n",
    "            anotations = np.array(list(map(get_label, self.policy.reshape(-1,1)))).reshape(self.policy.shape)\n",
    "            anotations[self.terminal_state[0], self.terminal_state[1]] = 'Terminal'\n",
    "            for i,j in self.blocked_blocks:\n",
    "                anotations[i,j] = 'Blocked'\n",
    "            sns.heatmap(self.policy, annot=anotations, fmt='', cmap='Blues', ax = ax)\n",
    "            plt.show()\n",
    "            \n",
    "            if self.verbose:\n",
    "                print(\"Final Policy:\")\n",
    "                print(*self.policy, sep = '\\n', end = '\\n\\n')\n",
    "                print(\"Final State-Action/Q Function:\")\n",
    "                print(*self.Q, sep = '\\n', end = '\\n\\n')\n",
    "            return res\n",
    "        \n",
    "        elif self.mode_type == 'PS':\n",
    "            res = self._play_priority_sweep(epochs, threshold)\n",
    "            \n",
    "            fig, ax = plt.subplots(figsize=(self.grid_size*2, self.grid_size*2))\n",
    "            anotations = np.array(list(map(get_label, self.policy.reshape(-1,1)))).reshape(self.policy.shape)\n",
    "            anotations[self.terminal_state[0], self.terminal_state[1]] = 'Terminal'\n",
    "            sns.heatmap(self.policy, annot=anotations, fmt='', cmap='Blues', ax = ax)\n",
    "            plt.show()\n",
    "            \n",
    "            if self.verbose:\n",
    "                print(\"Final Policy:\")\n",
    "                print(*self.policy, sep = '\\n', end = '\\n\\n')\n",
    "                print(\"Final State-Action/Q Function:\")\n",
    "                print(*self.Q, sep = '\\n', end = '\\n\\n')     \n",
    "            return res\n",
    "        \n",
    "    def _get_action(self, x,y):\n",
    "\n",
    "        m = np.round(np.min(self.Q[x][y])-1, 3)\n",
    "        probs = (np.round(self.Q[x][y], 5)-m) / np.sum(np.round(self.Q[x][y], 5) - m)\n",
    "        try:\n",
    "            \n",
    "            return np.random.choice([0,1,2,3],p=probs)\n",
    "        except:\n",
    "            print(m,probs)\n",
    "    \n",
    "    def _play_dq(self, epochs, threshold, changed=True):\n",
    "        \n",
    "        iters = 0\n",
    "        avg_length = []\n",
    "        all_rewards = []\n",
    "        model = {}\n",
    "        states = set()\n",
    "        \n",
    "        while True:\n",
    "            \n",
    "            iters+=1\n",
    "            x=0\n",
    "            y=self.grid_size//2\n",
    "            diff = 0\n",
    "            old_Q = np.array(self.Q)\n",
    "            length = 0\n",
    "            rewards = []\n",
    "            \n",
    "            #After 300 iterations change the block\n",
    "            if (iters == 400 or diff < threshold) and changed:\n",
    "                temp = list(self.blocked_blocks)\n",
    "                temp.pop()\n",
    "                self.blocked_blocks = tuple(temp)\n",
    "                changed = False\n",
    "            \n",
    "            while True:\n",
    "                \n",
    "                    length+=1\n",
    "                    action = self._get_action(x,y)\n",
    "                    new_x, new_y = self._get_next_state(x,y,self.actions[action])\n",
    "                    reward = self._get_reward(x,y,self.actions[action])\n",
    "                    rewards.append(reward)\n",
    "                    \n",
    "                    states = states.union({(x,y,action)})\n",
    "                    model[(x,y,action)] = (new_x, new_y, reward)\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"X, Y, Action, Rewards:\", [x,y,action,rewards])                       \n",
    "                       \n",
    "                    self.Q[x,y,action] = self.Q[x,y,action] + 0.1*(reward + self.gamma*np.max(self.Q[new_x, new_y]) - self.Q[x, y, action])\n",
    "                    self.policy[x,y] = np.argmax(self.Q[x][y])\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"N=\", self.n, \"Length:\", len(states))\n",
    "                    \n",
    "                    for i in range(self.n):\n",
    "                        temp_x, temp_y, temp_action = list(states)[np.random.randint(len(states))]\n",
    "                        temp_new_x, temp_new_y, temp_reward = model[(temp_x, temp_y, temp_action)]\n",
    "                        self.Q[temp_x, temp_y, temp_action] = self.Q[temp_x, temp_y, temp_action] + 0.1*(temp_reward + self.gamma*np.max(self.Q[temp_new_x, temp_new_y]) - self.Q[temp_x, temp_y, temp_action])\n",
    "                        self.policy[temp_x, temp_y] = np.argmax(self.Q[temp_x, temp_y])\n",
    "                    \n",
    "                    x, y = new_x, new_y\n",
    "                    \n",
    "                    if reward>0:\n",
    "                        break\n",
    "\n",
    "            avg_length.append(length)\n",
    "            diff = np.mean(np.square(old_Q-self.Q))\n",
    "            all_rewards.append(np.sum(rewards))\n",
    "            \n",
    "            if self.verbose:\n",
    "                print('IDs & Difference(MSE):', id(old_Q), id(self.Q), diff)\n",
    "                \n",
    "                        \n",
    "            if self.verbose:\n",
    "                print(\"Q function at iter:\", iters)\n",
    "                print(*self.Q, sep = '\\n', end = '\\n\\n')\n",
    "            \n",
    "            if self.verbose:\n",
    "                print(\"Policy at iter:\", iters)\n",
    "                print(*self.policy, sep = '\\n', end = '\\n\\n')\n",
    "            \n",
    "            if epochs==iters or diff < threshold:\n",
    "                return diff, iters, np.mean(avg_length), all_rewards\n",
    "            \n",
    "    def _play_dq_plus(self, epochs, threshold, changed = True):\n",
    "        \n",
    "        iters = 0\n",
    "        avg_length = []\n",
    "        all_rewards = []\n",
    "        model = {}\n",
    "        states = set()\n",
    "        occurence = np.zeros((self.grid_size, self.grid_size, 4))\n",
    "        \n",
    "        while True:\n",
    "            \n",
    "            iters+=1\n",
    "            x=0\n",
    "            y=self.grid_size//2\n",
    "            diff = 0\n",
    "            old_Q = np.array(self.Q)\n",
    "            length = 0\n",
    "            rewards = []\n",
    "            \n",
    "            #After 300 iterations change the block\n",
    "            if (iters == 300 or diff < threshold) and changed:\n",
    "                temp = list(self.blocked_blocks)\n",
    "                temp.pop()\n",
    "                self.blocked_blocks = tuple(temp)\n",
    "                changed = False\n",
    "            \n",
    "            occurence = occurence + 1\n",
    "            \n",
    "            while True:\n",
    "                \n",
    "                    length+=1\n",
    "                    action = self._get_action(x,y)\n",
    "                    new_x, new_y = self._get_next_state(x,y,self.actions[action])\n",
    "                    reward = self._get_time_dependent_reward(x,y,self.actions[action], occurence[x,y,action])\n",
    "                    rewards.append(reward)\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"Occurenece Matrix:\", *occurence, sep='\\n',end='\\n\\n')\n",
    "                    \n",
    "                    states = states.union({(x,y,action)})\n",
    "                    model[(x,y,action)] = (new_x, new_y, reward)\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"X, Y, Action, Rewards:\", [x,y,action,rewards])                       \n",
    "                       \n",
    "                    self.Q[x,y,action] = self.Q[x,y,action] + 0.1*(reward + self.gamma*np.max(self.Q[new_x, new_y]) - self.Q[x,y,action])\n",
    "                    self.policy[x,y] = np.argmax(self.Q[x][y])\n",
    "                    \n",
    "                    occurence[x,y,action] = 0\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"N=\", self.n, \"Length:\", len(states))\n",
    "                    \n",
    "                    for i in range(self.n):\n",
    "                        temp_x, temp_y, temp_action = list(states)[np.random.randint(len(states))]\n",
    "                        temp_new_x, temp_new_y, temp_reward = model[(temp_x, temp_y, temp_action)]\n",
    "                        self.Q[temp_x, temp_y, temp_action] = self.Q[temp_x, temp_y, temp_action] + 0.1*(temp_reward + self.gamma*np.max(self.Q[temp_new_x, temp_new_y]) - self.Q[temp_x, temp_y, temp_action])\n",
    "                        self.policy[temp_x, temp_y] = np.argmax(self.Q[temp_x, temp_y])\n",
    "                        \n",
    "                    x, y = new_x, new_y\n",
    "                    \n",
    "                    if x==self.terminal_state[0] and y==self.terminal_state[1]:\n",
    "                        break\n",
    "\n",
    "            avg_length.append(length)\n",
    "            diff = np.mean(np.square(old_Q-self.Q))\n",
    "            all_rewards.append(np.mean(rewards))\n",
    "            \n",
    "            if self.verbose:\n",
    "                print('IDs & Difference(MSE):', id(old_Q), id(self.Q), diff)\n",
    "                \n",
    "                        \n",
    "            if self.verbose:\n",
    "                print(\"Q function at iter:\", iters)\n",
    "                print(*self.Q, sep = '\\n', end = '\\n\\n')\n",
    "            \n",
    "            if self.verbose:\n",
    "                print(\"Policy at iter:\", iters)\n",
    "                print(*self.policy, sep = '\\n', end = '\\n\\n')\n",
    "            \n",
    "            if epochs==iters or diff < threshold:\n",
    "                return diff, iters, np.mean(avg_length), all_rewards\n",
    "            \n",
    "    def _play_priority_sweep(self, epochs, threshold):\n",
    "        \n",
    "        iters = 0\n",
    "        avg_length = []\n",
    "        rewards = []\n",
    "        model = {}\n",
    "        states = []\n",
    "        occurence = np.zeros((self.grid_size, self.grid_size, 4))\n",
    "        \n",
    "        while True:\n",
    "            \n",
    "            iters+=1\n",
    "            x=0\n",
    "            y=0\n",
    "            diff = 0\n",
    "            old_Q = np.array(self.Q)\n",
    "            length = 0\n",
    "            \n",
    "            if iters == 200:\n",
    "                self.blocked_blocks\n",
    "            \n",
    "            while True:\n",
    "                \n",
    "                    length+=1\n",
    "                    action = self._get_action(x,y)\n",
    "                    new_x, new_y = self._get_next_state(x,y,self.actions[action])\n",
    "                    reward = self._get_time_dependent_reward(x,y,self.actions[action], occurence[x,y,action])\n",
    "                    rewards.append(reward)\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"Occurenece Matrix:\", *occurence, sep='\\n',end='\\n\\n')\n",
    "                    \n",
    "                    states = states.union({(x,y)})\n",
    "                    model[(x,y,action)] = (new_x, new_y, reward)\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"X, Y, Action, Rewards:\", [x,y,action,rewards])                       \n",
    "                       \n",
    "                    self.Q[x,y,action] = self.Q[x,y,action] + 0.1*(reward + self.gamma*np.max(self.Q[new_x, new_y]) - self.Q[temp_x, temp_y, temp_action])\n",
    "                    self.policy[x,y] = np.argmax(self.Q[x][y])\n",
    "                    \n",
    "                    occurence = occurence + 1\n",
    "                    occurence[x,y,action] = 1\n",
    "                    \n",
    "                    if self.verbose:\n",
    "                        print(\"N=\", self.n, \"Length:\", len(states))\n",
    "                    \n",
    "                    for i in range(self.n):\n",
    "                        temp_x, temp_y = list(states)[np.random,randint(len(states))]\n",
    "                        temp_action = self._get_action(temp_x, temp_y)\n",
    "                        temp_new_x, temp_new_y, temp_reward = model[(temp_x, temp_y, temp_action)]\n",
    "                        self.Q[temp_x, temp_y, temp_action] = self.Q[temp_x, temp_y, temp_action] + 0.1*(reward + self.gamma*np.max(self.Q[temp_new_x, temp_new_y]) - self.Q[temp_x, temp_y, temp_action])\n",
    "                        self.policy[temp_x, temp_y] = np.argmax(self.Q[temp_x, temp_y])\n",
    "                        \n",
    "                    x, y = new_x, new_y\n",
    "                    \n",
    "                    if x==self.terminal_state[0] and y==self.terminal_state[1]:\n",
    "                        break\n",
    "\n",
    "            avg_length.append(length)\n",
    "            diff = np.mean(np.square(old_Q-self.Q))\n",
    "            \n",
    "            if self.verbose:\n",
    "                print('IDs & Difference(MSE):', id(old_Q), id(self.Q), diff)\n",
    "                \n",
    "                        \n",
    "            if self.verbose:\n",
    "                print(\"Q function at iter:\", iters)\n",
    "                print(*self.Q, sep = '\\n', end = '\\n\\n')\n",
    "            \n",
    "            if self.verbose:\n",
    "                print(\"Policy at iter:\", iters)\n",
    "                print(*self.policy, sep = '\\n', end = '\\n\\n')\n",
    "            \n",
    "            if epochs==iters or diff < threshold:\n",
    "                return diff, iters, np.mean(avg_length), rewards"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DQ Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-18T07:23:05.659840Z",
     "start_time": "2020-07-18T07:21:39.977912Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Planning size: 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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cA/fbI489uSL7jNs9Cx5+Ms+ueClJ8tC/P5Px++2phBjCvHkP5PGlSzbfXr16ddasWd3DE/UfGbdPxu2TcR1ybp+M2yfjOuTcPhkznLyVSYgvJ9lqCVFKmZxkcpKMPOBDGTnuvW/h23TXQfvvmcHBJitW/j6dCq0FDz+ZIw8bn988+2J+NO+RjBuzaz512vFZtPjpzde8um5g8+cbBjdk5E59v+PzLWs2bMhNt9yaUaNG9foofUvG7ZNx+2Rch5zbJ+P2ybgOObdPxgwn2/zNuZTybx0+fpnkHZ0e1zTN9KZpJjZNM3F7KiDGjd0t106dlBtu3Tj9cP/CpZl08sQkySHj9847990jjz6xIusHBvPMcy/ljJMm5Oe//E3mLlqaz597YuYuXNrL4+/wjj3uA5lzy6zNtx9ZvHir171t112zZs2aWsfqKzJun4zbJ+M65Nw+GbdPxnXIuX0yZjgZahLiHUn+9ySr3nB/SfJAKyfqstG77Jx5cy7NziN3ysDgYGbfOT9fn/XjJMmNt92Xa6dOyvzbpmRgcDAXXnZz1q3fOOEwd9GSfPj9h2btK+szd9HSHLDP2MxdtGRb34otvPLK2px0wgc33/7EuefnkilTc9W0K3LmaR/N4MBgjpw4MV+6/Io/eOwZHz8rF3/mwowbt5eFO9sg4/bJuH0yrkPO7ZNx+2Rch5zbJ2OGu9I0TecvlvLNJN9umub+rXztlqZp/s+hvsHoCZ/r/A3oilXzr+v1EQAAgGFq1Mj09ebG3c++uS9/p3159id68u+2zUmIpmku2MbXhiwgAAAAAF5jmyIAAABQhRICAAAAqOKt/IlOAAAA6G99vfGiPpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0EEplkJ0k0kIAAAAoAolBAAAAFCFEgIAAAB4nVLKO0sp95ZSFpdSHi6l/M1WrvlQKeXlUsqDmz4uG+p57YQAAACADobxToiBJH/bNM3CUsrbk/yilPLPTdP8+g3X/bRpmr/4Y5/UJAQAAADwOk3TLG+aZuGmz3+fZHGS/d/q8yohAAAAgI5KKQclmZDkZ1v58rGllIdKKXeXUt471HMpIQAAAGCYKaVMLqUs2OJjcofrdkvyP5J8vmma373hywuTHNg0zeFJrk3yvaG+r50QAAAAMMw0TTM9yfRtXVNK2TkbC4h/aprm9q08x++2+PyuUsr1pZRxTdO80Ok5lRAAAADQwXBdTFk2/uDfTLK4aZp/7HDNPkmea5qmKaW8PxvfbfHitp5XCQEAAAC80fFJPpHkl6WUBzfdNyXJ+CRpmuaGJGcmuaiUMpBkbZJJTdM023pSJQQAAADwOk3T3J9km2MgTdNcl+S6N/O8FlMCAAAAVZiEAAAAgA6G606ItpiEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgE6shOgqkxAAAABAFUoIAAAAoAolBAAAAFCFnRAAAADQQSmWQnSTSQgAAACgCiUEAAAAUIUSAgAAAKhCCQEAAABUYTElAAAAdGAxZXeZhAAAAACqUEIAAAAAVSghAAAAgCrshAAAAIAO7IToLpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0ImVEF1lEgIAAACoQgkBAAAAVKGEAAAAAKqwEwIAAAA6KMVSiG4yCQEAAABUoYQAAAAAqlBCAAAAAFUoIQAAAIAqLKYEAACADiym7C6TEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANCBnRDdZRICAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOrATortMQgAAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAnVkJ0lUkIAAAAoAolBAAAAFCFEgIAAACoQgkBAAAAVGExJQAAAHRQis2U3WQSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADqwE6K7TEIAAAAAVSghAAAAgCqUEAAAAEAVdkIAAABAB3ZCdJdJCAAAAKAKJQQAAABQhRICAAAAqMJOCAAAAOjESoiuMgkBAAAAVKGEAAAAAKpQQgAAAABVKCEAAACAKiymBAAAgA5KsZmym0xCAAAAAFUoIQAAAIAqlBAAAABAFXZCAAAAQAd2QnSXSQgAAACgCiUEAAAAUIUSAgAAAKjCTggAAADowE6I7jIJAQAAAFShhAAAAACqUEIAAAAAVdgJAQAAAB3YCdFdJiEAAACAKpQQAAAAQBVKCAAAAKCKvi8hVi+4JvPmXJpffGdqfnbrpfnrc07wnp4Kjpk44Y++dt26dZl8wSdz1umn5p6778qsm2Zk7dq17R2uT8i4fTJun4zrkHP7ZNw+Gdch5/bJmOGu7xdTrn11fY6Z9JUkyV5jd8uMqz+ZP91tVKbdcFePT8ZrHln86wwMDOS22+9IknzkpBNyykc/ltGjR/f4ZP1Dxu2TcftkXIec2yfj9sm4Djm3T8bbCa9hd9WQJUQp5T8l2T/Jz5qmWb3F/X/eNM09bR6u255ftToX/8Ps3D/r7zLthruyy5+MzDVTJuXIw8ZnYHAwl3zt9ty34LF899qL8qVr7sivHluWf519Sb5/70O5evo9ueyzp+Sp5Suz9KkX8vefOTkvvrQ6hx28bxYtfjrnT53Z6x9vu7dy5cpM+/Ll+e3yZUmSL146JeMPPChTLvliVq1ambNOPzWnnnZ6VqxYkb86/7yMGTMm35xxc49PvWORcftk3D4Z1yHn9sm4fTKuQ87tkzHDyTZLiFLKXye5OMniJN8spfxN0zR3bPryVUl2qBIiSZ549sWMGFGy9x5vz9mnHJ0kOfqsq/Keg96RO6+/OO/7yysyd+GSHD/hkDy5bGUGBzfk2MMPTpIcd8TBmf3D+dln3O45/NADctSZV2bZ8y/n3hlfyHFHvCsPPPh4L3+07d5Xr74y55x7Xo48amKWL1uWiz59Qb73g7tz+RXTMnPGt3Ld9TcmSWbdNDPf+PbMjB27R49PvOORcftk3D4Z1yHn9sm4fTKuQ87tkzHDyVCTEBcmOappmtWllIOSfKeUclDTNF/PNoZSSimTk0xOkpEHfCgjx723S8ftjtdWQhx3xMG5fs5PkiSPPvFcnlq+Mu8+cO/MXbg0nz37z/LEshdy908fzonHHJrRo3bOgfvtkceeXJF9xu2eBQ8/mWdXvJQkeejfn8n4/fZUQgxh3rwH8vjSJZtvr169OmvWrN7GI3izZNw+GbdPxnXIuX0ybp+M65Bz+2TMcDJUCbHTa2/BaJrmiVLKh7KxiDgw2yghmqaZnmR6koye8LmmS2ftioP23zODg01WrPx9Ou2nXPDwkznysPH5zbMv5kfzHsm4MbvmU6cdn0WLn958zavrBjZ/vmFwQ0bu1Pc7Pt+yZsOG3HTLrRk1alSvj9K3ZNw+GbdPxnXIuX0ybp+M65Bz+2S8ffOHDbprqN+cf1tKOeK1G5sKib9IMi7J+9o8WBvGjd0t106dlBtu3Tj9cP/CpZl08sQkySHj9847990jjz6xIusHBvPMcy/ljJMm5Oe//E3mLlqaz597YuYuXNrL4+/wjj3uA5lzy6zNtx9ZvHir171t112zZs2aWsfqKzJun4zbJ+M65Nw+GbdPxnXIuX0yZjgZahLi3CQDW97RNM1AknNLKTe2dqouGr3Lzpk359LsPHKnDAwOZvad8/P1WT9Oktx42325duqkzL9tSgYGB3PhZTdn3fqNP+7cRUvy4fcfmrWvrM/cRUtzwD5jM3fRkm19K7bwyitrc9IJH9x8+xPnnp9LpkzNVdOuyJmnfTSDA4M5cuLEfOnyK/7gsWd8/Kxc/JkLM27cXhbubIOM2yfj9sm4Djm3T8btk3Edcm6fjBnuStO0+26J7e3tGP1o1fzren0EAABgmBo1sr//iOW7vnBXX/5O+/g/ntyTf7ch/0QnAAAADFd2QnSXbYoAAABAFUoIAAAAoAolBAAAAFCFnRAAAADQgZUQ3WUSAgAAAKhCCQEAAABUoYQAAAAAqlBCAAAAAFVYTAkAAAAdFJspu8okBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRgJUR3mYQAAAAAqlBCAAAAAFUoIQAAAIAq7IQAAACADoqlEF1lEgIAAACoQgkBAAAAVKGEAAAAAKqwEwIAAAA6sBKiu0xCAAAAAFUoIQAAAIAqlBAAAABAFUoIAAAAoAqLKQEAAKCDESNspuwmkxAAAABAFUoIAAAAoAolBAAAAFCFnRAAAADQQbESoqtMQgAAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAHxVKIrjIJAQAAAFShhAAAAACqUEIAAAAAVdgJAQAAAB1YCdFdJiEAAACAKpQQAAAAQBVKCAAAAKAKJQQAAABQhcWUAAAA0EGxmbKrTEIAAAAAVSghAAAAgCqUEAAAAEAVdkIAAABAB3ZCdJdJCAAAAKAKkxB9YOzRn+v1EfreqvnX9foIAAAAOzyTEAAAAEAVJiEAAACgAyshusskBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRQLIXoKpMQAAAAQBVKCAAAAKAKJQQAAABQhRICAAAAqMJiSgAAAOjAXsruMgkBAAAAVKGEAAAAAKpQQgAAAABV2AkBAAAAHRRLIbrKJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0YCVEd5mEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgA6KpRBdZRICAAAAqEIJAQAAAFShhAAAAACqUEIAAAAAVVhMCQAAAB3YS9ldJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACgg2IpRFeZhAAAAACqUEIAAAAAr1NKeWcp5d5SyuJSysOllL/ZyjWllHJNKWVJKeXfSilHDvW83o4BAAAAvNFAkr9tmmZhKeXtSX5RSvnnpml+vcU1H0ny7k0f/znJ/7fpfztSQgAAAEAHw3UlRNM0y5Ms3/T570spi5Psn2TLEuLUJDc1TdMkmVdKGVNK2XfTY7fK2zEAAABgmCmlTC6lLNjiY/I2rj0oyYQkP3vDl/ZP8vQWt5/ZdF9HJiEAAABgmGmaZnqS6UNdV0rZLcn/SPL5pml+98Yvb+2pt/V8JiEAAACAP1BK2TkbC4h/aprm9q1c8kySd25x+4Aky7b1nCYhAAAAoIMyTJdClI0/+DeTLG6a5h87XPb9JJ8rpczJxoWUL29rH0SihAAAAAD+0PFJPpHkl6WUBzfdNyXJ+CRpmuaGJHclOTnJkiT/M8n5Qz2pEgIAAAB4naZp7s/Wdz5seU2T5OI387x2QgAAAABVKCEAAACAKrwdAwAAADoYpnspW2MSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADoolkJ0lUkIAAAAoIq+n4RYveCa/GrJsuw8cqcMDA7mn37w81z7T/emaZpeH61vyLg3jpk4IfMWLPqjrl23bl0+d9HkvLRqVT514afzwvMrcsbH/4+MHj265VPu2GTcPhnXIef2ybh9Mq5Dzu2TMcNd35cQa19dn2MmfSVJstfY3TLj6k/mT3cblWk33NXjk/UPGW//Hln86wwMDOS22+9IknzkpBNyykc/5v+BdZGM2yfjOuTcPhm3T8Z1yLl9MqYfDVlClFLen6RpmmZ+KeWwJH+e5JGmaXa43zCfX7U6F//D7Nw/6+8y7Ya7ssufjMw1UyblyMPGZ2BwMJd87fbct+CxfPfai/Kla+7Irx5bln+dfUm+f+9DuXr6Pbnss6fkqeUrs/SpF/L3nzk5L760OocdvG8WLX4650+d2esfb7sg495auXJlpn358vx2+bIkyRcvnZLxBx6UKZd8MatWrcxZp5+aU087PStWrMhfnX9exowZk2/OuLnHp96xyLh9Mq5Dzu2TcftkXIec2yfj7ZuVEN21zRKilHJ5ko8kGVlK+eck/znJvyS5tJQyoWmaK9s/Ync98eyLGTGiZO893p6zTzk6SXL0WVflPQe9I3def3He95dXZO7CJTl+wiF5ctnKDA5uyLGHH5wkOe6IgzP7h/Ozz7jdc/ihB+SoM6/Msudfzr0zvpDjjnhXHnjw8V7+aNsNGffOV6++Muece16OPGpili9blos+fUG+94O7c/kV0zJzxrdy3fU3JmMDbl4AACAASURBVElm3TQz3/j2zIwdu0ePT7zjkXH7ZFyHnNsn4/bJuA45t0/GDCdDTUKcmeSIJLsk+W2SA5qm+V0p5f9O8rMkWy0hSimTk0xOkpEHfCgjx723eyfugtearOOOODjXz/lJkuTRJ57LU8tX5t0H7p25C5fms2f/WZ5Y9kLu/unDOfGYQzN61M45cL898tiTK7LPuN2z4OEn8+yKl5IkD/37Mxm/355+Qd6CjHtj3rwH8vjSJZtvr169OmvWrO7hifqPjNsn4zrk3D4Zt0/Gdci5fTJmOBmqhBhommYwyf8spSxtmuZ3SdI0zdpSyoZOD2qaZnqS6UkyesLntqvthAftv2cGB5usWPn7jmM1Cx5+MkceNj6/efbF/GjeIxk3Ztd86rTjs2jx05uveXXdwObPNwxuyMid/KGR18i4d5oNG3LTLbdm1KhRvT5K35Jx+2Rch5zbJ+P2ybgOObdPxgwnQ/1Wt66U8rZNnx/12p2llN2TdCwhtlfjxu6Wa6dOyg23bnxl/v6FSzPp5IlJkkPG75137rtHHn1iRdYPDOaZ517KGSdNyM9/+ZvMXbQ0nz/3xMxduLSXx98hyLi3jj3uA5lzy6zNtx9ZvHir171t112zZs2aWsfqKzJun4zrkHP7ZNw+Gdch5/bJePtWSunLj14ZahLig03TvJokTdNsWTrsnOS81k7VRaN32Tnz5ly6+c9Hzr5zfr4+68dJkhtvuy/XTp2U+bdNycDgYC687OasW7/x1fe5i5bkw+8/NGtfWZ+5i5bmgH3GZu6iJdv6VsOWjHvjlVfW5qQTPrj59ifOPT+XTJmaq6ZdkTNP+2gGBwZz5MSJ+dLlV/zBY8/4+Fm5+DMXZty4vSw12gYZt0/Gdci5fTJun4zrkHP7ZMxwV5qm3XdLbG9vx4D/iFXzr+v1EQAAYLs0amT6+u9H/K9fu78vf6f96d9+oCf/bt5kDwAAAFShhAAAAACqGGonBAAAAAxbvVzi2I9MQgAAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAHVkJ0l0kIAAAAoAolBAAAAFCFEgIAAACowk4IAAAA6KBYCtFVJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACgAyshusskBAAAAFCFEgIAAACoQgkBAAAAVKGEAAAAAKqwmBIAAAA6KDZTdpVJCAAAAKAKJQQAAABQhRICAAAAqMJOCAAAAOjASojuMgkBAAAAVKGEAAAAAKpQQgAAAABV2AkBAAAAHYywFKKrTEIAAAAAVSghAAAAgCqUEAAAAEAVdkIAAABAB1ZCdJdJCAAAAKAKJQQAAABQhRICAAAAqEIJAQAAAFRhMSUAAAB0UGym7CqTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANDBCCshusokBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRQiqUQ3WQSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADqwEqK7lBB9YNX863p9BAAAABiSt2MAAAAAVSghAAAAgCqUEAAAAEAVdkIAAABAByU2U3aTSQgAAACgCiUEAAAAUIUSAgAAAKjCTggAAADoYISVEF1lEgIAAACoQgkBAAAAVKGEAAAAAKqwEwIAAAA6KMVSiG4yCQEAAABUoYQAAAAAqlBCAAAAAFXYCQEAAAAdWAnRXSYhAAAAgCqUEAAAAEAVSggAAACgCiUEAAAAUIXFlAAAANDBCJspu8okBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRgJUR3mYQAAAAAqlBCAAAAAFUoIQAAAIAq7IQAAACADoqlEF1lEgIAAACoQgkBAAAAVKGEAAAAAKqwEwIAAAA6sBKiu0xCAAAAAFUoIQAAAIAqlBAAAABAFUoIAAAAoAqLKQEAAKCDETZTdpVJCAAAAKAKJQQAAABQhRICAAAAqMJOCAAAAOjARojuMgkBAAAAVKGEAAAAAKpQQgAAAABV2AkBAAAAHZRiK0Q3mYQAAAAAqlBCAAAAAFUoIQAAAIAq+r6EWL3gmsybc2l+8Z2p+dmtl+avzznBe3oqOGbihD/62nXr1mXyBZ/MWaefmnvuviuzbpqRtWvXtne4PiHj9sm4fTKuQ87tk3H7ZFyHnNsn4x3PiNKfH73S94sp1766PsdM+kqSZK+xu2XG1Z/Mn+42KtNuuKvHJ+M1jyz+dQYGBnLb7XckST5y0gk55aMfy+jRo3t8sv4h4/bJuH0yrkPO7ZNx+2Rch5zbJ2P6Ud+XEFt6ftXqXPwPs3P/rL/LtBvuyi5/MjLXTJmUIw8bn4HBwVzytdtz34LH8t1rL8qXrrkjv3psWf519iX5/r0P5erp9+Syz56Sp5avzNKnXsjff+bkvPjS6hx28L5ZtPjpnD91Zq9/vO3eypUrM+3Ll+e3y5clSb546ZSMP/CgTLnki1m1amXOOv3UnHra6VmxYkX+6vzzMmbMmHxzxs09PvWORcbtk3H7ZFyHnNsn4/bJuA45t0/GDCdvuoQopdzUNM25bRymhieefTEjRpTsvcfbc/YpRydJjj7rqrznoHfkzusvzvv+8orMXbgkx084JE8uW5nBwQ059vCDkyTHHXFwZv9wfvYZt3sOP/SAHHXmlVn2/Mu5d8YXctwR78oDDz7eyx9tu/fVq6/MOeeelyOPmpjly5blok9fkO/94O5cfsW0zJzxrVx3/Y1Jklk3zcw3vj0zY8fu0eMT73hk3D4Zt0/Gdci5fTJun4zrkHP7ZMxwss0SopTy/TfeleTDpZQxSdI0zcfaOlibXlsJcdwRB+f6OT9Jkjz6xHN5avnKvPvAvTN34dJ89uw/yxPLXsjdP304Jx5zaEaP2jkH7rdHHntyRfYZt3sWPPxknl3xUpLkoX9/JuP321MJMYR58x7I40uXbL69evXqrFmzuocn6j8ybp+M2yfjOuTcPhm3T8Z1yLl9Mt6+2SnYXUNNQhyQ5NdJvpGkycYSYmKSr23rQaWUyUkmJ8nIAz6UkePe+9ZP2iUH7b9nBgebrFj5+3T6b2nBw0/myMPG5zfPvpgfzXsk48bsmk+ddnwWLX568zWvrhvY/PmGwQ0ZuVPf7/h8y5oNG3LTLbdm1KhRvT5K35Jx+2TcPhnXIef2ybh9Mq5Dzu2TMcPJUL85T0zyiyRTk7zcNM2/JFnbNM1Pmqb5SacHNU0zvWmaiU3TTNyeCohxY3fLtVMn5YZbNx79/oVLM+nkiUmSQ8bvnXfuu0cefWJF1g8M5pnnXsoZJ03Iz3/5m8xdtDSfP/fEzF24tJfH3+Ede9wHMueWWZtvP7J48Vave9uuu2bNmjW1jtVXZNw+GbdPxnXIuX0ybp+M65Bz+2TMcLLNSYimaTYk+W+llP++6X+fG+ox25vRu+yceXMuzc4jd8rA4GBm3zk/X5/14yTJjbfdl2unTsr826ZkYHAwF152c9at3zjhMHfRknz4/Ydm7SvrM3fR0hywz9jMXbRkW9+KLbzyytqcdMIHN9/+xLnn55IpU3PVtCty5mkfzeDAYI6cODFfuvyKP3jsGR8/Kxd/5sKMG7eXhTvbIOP2ybh9Mq5Dzu2TcftkXIec2ydjhrvSNM0ff3EppyQ5vmmaKX/sY0ZP+Nwf/w34D1k1/7peHwEAABimRo1MXy9NOGfWQ335O+2scw7vyb/bm5pqaJrmh0l+2NJZAAAAYLtiL2V32aYIAAAAVKGEAAAAAKpQQgAAAABV7FB/6QIAAABqKpZCdJVJCAAAAKAKJQQAAABQhRICAAAAqMJOCAAAAOhghJUQXWUSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADooxVKIbjIJAQAAAFShhAAAAACqUEIAAAAAVSghAAAAgCospgQAAIAOrKXsLpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0MGIYitEN5mEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgA6shOgukxAAAABAFUoIAAAAoAolBAAAAFCFnRAAAADQQbEUoqtMQgAAAABVKCEAAACAKpQQAAAAQBVKCAAAAKAKiykBAACgA3spu8skBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHQwwlKIrjIJAQAAAFShhAAAAACqUEIAAAAAVdgJAQAAAB1YCdFdJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACgg2IpRFeZhAAAAABep5TyrVLKilLKrzp8/UOllJdLKQ9u+rjsj3lekxAAAADAG81Icl2Sm7ZxzU+bpvmLN/OkJiEAAACA12ma5r4kK7v9vCYh+sCdDy/v9RH63v9z96O9PsKw8NCt/73XR+h7N8+Y2usj9D3/94J+8V8+8p5eH6HvfeKTV/b6CNAVaxdd1+sj8B9QSpmcZPIWd01vmmb6m3yaY0spDyVZluS/NE3z8FAPUEIAAABAB/369oFNhcObLR22tDDJgU3TrC6lnJzke0nePdSD+jVPAAAAoCVN0/yuaZrVmz6/K8nOpZRxQz1OCQEAAAC8KaWUfcqmv19aSnl/NvYLLw71OG/HAAAAAF6nlDI7yYeSjCulPJPk8iQ7J0nTNDckOTPJRaWUgSRrk0xqmqYZ6nmVEAAAANDBphf7h52mac4e4uvXZeOf8HxTvB0DAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOhgxPFdCtMYkBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRgJ0R3mYQAAAAAqlBCAAAAAFUoIQAAAIAqlBAAAABAFRZTAgAAQAel2EzZTSYhAAAAgCqUEAAAAEAVSggAAACgCjshAAAAoIMRVkJ0lUkIAAAAoAolBAAAAFCFEgIAAACowk4IAAAA6KDYCdFVJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACggxGWQnSVSQgAAACgCiUEAAAAUIUSAgAAAKhCCQEAAABUYTElAAAAdOCV++6SJwAAAFCFEgIAAACoQgkBAP8/e/ceZ1dd3ov/s2ZyN6AB5BIgAcLNVIFAFAhWK1aL6JFaaEF/glyUgyJgVZTboQVF8SD1B6EWkVsJCigK4g1slVYI15AYucglwQAhhADhqiHJzKzzR0KaEHaCuNd3MpP329e8nNl77T3f9ZnF2plnnvVsAACKMBMCAAAAWqiq3l5B/6ITAgAAAChCEQIAAAAoQhECAAAAKMJMCAAAAGihw1CIttIJAQAAABShCAEAAAAUoQgBAAAAFGEmBAAAALRgJER76YQAAAAAilCEAAAAAIro90WIF6acnVsuPy53XHlibr3iuBz90T1T6adpu5P23zMTjz0sE489LOd88RN56L67kiRPz3ssZ33u4Nf0nGccuX/+8NwzbVxl3zb5C+/IJYfskkmH7pJ/P3jnvGXTdZMkm7x+cL5z2PjX9JxXfXLXvH6oq7Je8tL54tYrjstN3/1idttxyyTJqE3Wy5Tvn/CanvPen56S9d/wunYus09zrijD+aJ5Mm6e80UZXvuaJ2NYUb9/pVuwcHF2O+D0JMkbRwzPxV89OOsOH5Ivn/uzXl5Z/zJw0KAcdcYFSZIHfnNbfvHdb+cTp5zVy6vqXxZ29eSgi+5Ikuy65Yh88p1b5lPfnd7Lq+pflj9f/PXub8qpR30w7/2447idnCvKcL5onoyb53xRhte+5skYVtTvixDLe+LpF3Lkly7LjZd+IV8+92cZPGhAzj7hgOw8dlS6urvzxTN/mF9PeSBXTfxk/s/ZP8pdD8zJzZd9MddcPz1fPe/anPyp9+fhx+Zn5sNP5qQj9s5Tz7yQsWM2ybTfPZJDTvz33t69NcaLC/6Yoa8bvtLtixctzDXnfyOPzrwvHZ2d2fugI7PVm8elp6c71136rTww/fakqvLWd38gu7/v71Z43HfOOCl/ses789a//kDJXVljvW5QZ55/sWul2wd1VvnC32yb7Tcenu66zlm/fDBTH34mHVVy5F9tlV23HJEk+dH0x/L9O+Yse9zgAR05/e/+Iv913xP50fS5xfZjTbbu64bkmef+uNLtrc4bHR1VTjvmb/PXu78pdV3noqtuyr9d/t/LHjdk8MBcceYncvUvf5OLrrqp5K6ssZwrynC+aJ6Mm+d8UYbXvubJuG/q0EjfVn9SEaKqqrcneVuSu+q6/kUzS2rWrEefSkdHlQ3XWycffv9bkyRv/YevZNstNspPvnlk3vK3p2by1BnZY9zWeWjO/HR392T3HcckSSbsNCaX/fT2bLzB67Pjdptll/1Oy5wnns31F382E3baKjf95sHe3LVetXjRokw89rB0LV6U55+en8P+6V9W2ubW665Okhx95kV54tGHctGXj80/njUpU//r2jw9b26O/L/fTmfngPzxheeWPWbRiwtyxVmnZtw7/ibj3vk3xfZnTTR4QEcuOWSXDBrQkQ1eNyhHXrbyX9z222XTJMlHL7wjo9cbmrP23yH/cN5t+cAOG2fkG4bkYxfdke46WXfI//ynP2xQZ768z9j87K7H8/O7Hi+2P2uioYMH5pbLj8uQQQOy8Qavz/v+99krbXPE/u9IsvJ546B9dssWm66f3T58erq7ezJi3WHLHvO6oYNzyemH5Ds/uS3f/cltxfZnTeRcUYbzRfNk3DznizK89jVPxrCiVRYhqqq6ra7rty39/BNJjkxyVZJ/qqpq57quTy+wxrZ7aSTEhJ3G5JtLK4n3z3o8Dz82P9uM3jCTp87Mpz78zsya82R+fsPdefdu22XokIEZPXK9PPDQvGy8wesz5e6H8ui8JdcUTr9vdkaNXH+tLkIs3zL58P1358pzvpqjz7xohW1m3Xvnsr9CvHHT0XnDGzfKU4/Nzszf3pG3vfeD6exccjgOG77ussdcesZJ+csPHpCd/vI9hfZkzbV86++bR66bf/rA9vnIBVNW2GaHzV6f79/xaJLkofkLMve5hRm13rC8dYsRuWraY+mul2z33HJ/sfu/+745l97ySK67Z16ZHVmDLd8uuesOW+b8Lx2UXfY7bYVtWp039tx1+3z7+zemu7snSfL0cn/l+P7/f3i+cfF/5vKfr/jzWhs5V5ThfNE8GTfP+aIMr33NkzGsaHWDKQcu9/nhSd5T1/UpSd6b5P9r9aCqqg6vqmpKVVVTup68uw3LbJ8tNl0/3d115s1/vuX7vU65+6HsPHZU9hi3dW6cOiPT752dQz+0R6b97pFl2yxc9D//YOjp7smAzn4/4/NVG7XtX+QPzz+78uCnun7F7eu88u1JMmq7N+f+abembvHYtdVdc57LG4YNzIhhA1e4vVWnWJW0zPC3s5/N7lut194F9gO3/vb3Wf8Nr8sbR6zY/tvqvFGl9bF8828ezHv3GNvmFfZ9zhVlOF80T8bNc74ow2tf82QMqy9CdFRVNaKqqvWTVHVdP5EkdV3/IcnKFz8uVdf1eXVdj6/revyADf6ijcv982wwYngmnnhAzr1iSZXxxqkzc8DeSyZYbz1qw2y+yXq5f9a8LO7qzuzHn8m+7xmX2+78fSZPm5nPHPTuTJ46szeX32c88ehDqXu6M2yddVe4fYuxO2b6Df+ZJHlyziN59sl52WDk5tl6h/G57T+uSXf3kkNq+ZbJv/6HQzJsndfnmvO/UW4H+oDR6w1NR1Xl2QWLV7j9N488m78Zu2GSZPMRQ7PRuoPz0Pw/5tbfP50PjRuZzqUvcMu3/p53w6w8++LifOG92xRbf1+w7RYbpbOjI089+4cVbm913vjPW+7NJ/Z7ezqXFiSXb5f80r/9NPOf/UPOOmH/cjvQBzhXlOF80TwZN8/5ogyvfc2Tcd/UUVX98qO3rG4mxOuT3JGlRbiqqjau63puVVXD07rAv0Z56RqsgQM609Xdnct+cnvOuvRXSZJvfe/XmXjiAbn9eyekq7s7nzh5UhYtXvJiNXnajLzrbdtlwYuLM3nazGy28YhMnjajN3dljfbSdZsv2ffI49PR0bnCNru+d5/86Nv/krM/d0g6Ojuz76eOy4CBgzL+3e/PU4/NzsTPH5bOAQMy/t3vz+57/c/wqPcf/On88N++lmsvPTd7ffSIYvu0pnnp+uNkSbX81J/em56XFcZ/MPXRfHGvbXPpobuku67zpZ/el8Xdda6Z/lhGrTcslx42Pl09dX70m8dy5dT/GYL2jf+cmZP23i6f/qutcs5/rb2XFb10vkiWZPyJkyel52UhtzpvXHTVTdlm9Ia5/XvHZ3FXdy764U0594pfL3vc58/4Qb71zx/NacfskxPP+lHR/VqTOFeU4XzRPBk3z/miDK99zZMxrKh6La1oVVUNS7JRXde/X922Q8d9Wq9bwyZdfGJvL6Hf+/rP7+/tJawVpl/x/d5eQr/nfNE85wv6i8+/b9veXkK/d+DBp61+I+gDFkw7p0/8gfq1OvU/ZvTL32lPfs/WvfJze01v0VnX9R+TrLYAAQAAAPCS11SEAAAAgLVBL45P6Je8pQMAAABQhCIEAAAAUIQiBAAAAFCEmRAAAADQQoeZEG2lEwIAAAAoQhECAAAAKEIRAgAAAChCEQIAAAAowmBKAAAAaKGKyZTtpBMCAAAAKEIRAgAAAChCEQIAAAAowkwIAAAAaKHDSIi20gkBAAAAFKEIAQAAABShCAEAAAAUYSYEAAAAtGAmRHvphAAAAACKUIQAAAAAilCEAAAAAIowEwIAAABaqCpDIdpJJwQAAABQhCIEAAAAUIQiBAAAAFCEIgQAAABQhMGUAAAA0EKHuZRtpRMCAAAAKEIRAgAAAChCEQIAAAAowkwIAAAAaKEyE6KtdEIAAAAARShCAAAAAEUoQgAAAABFmAkBAAAALXQYCtFWOiEAAACAIhQhAAAAgCIUIQAAAIAizIQAAACAFjqMhGgrnRAAAABAEYoQAAAAQBGKEAAAAEARihAAAABAEQZTAgAAQAuVwZRtpRMCAAAAKEIRAgAAAChCEQIAAAAowkwIAAAAaKEjhkK0U+NFiEkXn9j0t4DGff592/b2EtYO73O+oO9zvgAAaM3lGAAAAEARihAAAABAEWZCAAAAQAuVkRBtpRMCAAAAKEIRAgAAAChCEQIAAAAowkwIAAAAaKHDTIi20gkBAAAAFKEIAQAAABShCAEAAAAUoQgBAAAAFGEwJQAAALTQUZlM2U46IQAAAIAiFCEAAACAIhQhAAAAgCLMhAAAAIAWjIRoL50QAAAAQBGKEAAAAEARihAAAABAEWZCAAAAQAsdhkK0lU4IAAAAoAhFCAAAAKAIRQgAAACgCDMhAAAAoAUjIdpLJwQAAABQhCIEAAAAUIQiBAAAAFCEIgQAAABQhMGUAAAA0IK/3LeXPAEAAIAiFCEAAACAIhQhAAAAgCLMhAAAAIAWqqrq7SX0KzohAAAAgCIUIQAAAIAiFCEAAACAIsyEAAAAgBZMhGgvnRAAAABAEYoQAAAAQBGKEAAAAEARZkIAAABACx2VqRDtpBMCAAAAKEIRAgAAAChCEQIAAAAoQhECAAAAKMJgSgAAAGjBWMr20gkBAAAAFKEIAQAAABShCAEAAAAUYSYEAAAAtFAZCtFWa0UnxEn775mJxx6Wsz53cC45/fgs+MPzSZLn5j+Z75558moff8qBe73i7ffcdkPmzZ7VzqX2WTJunoybJ+My5Nw8GTdPxmXIuVkvTDk7t1x+XO648sTcesVxOfqje6by21ZbyRhWtlYUIQYOGpSjzrggx5x5cYYNXze3XHd1kmTd9TbIRz536mt+3ntuv9EL2FIybp6MmyfjMuTcPBk3T8ZlyLlZCxYuzm4HnJ5d9jstHzjinPzN28fmxP/9vt5eVr8iY1jZKi/HqKpq1yS/q+v6uaqqhiY5LsnOSe5J8pW6rp8tsMa22nzbsZn78INJkqfnPZZLvnZ8jjnz4ixa+GJ+8K+n54k5D2fDTUfn6Sfm5n8ddkw2G7N9kuQXl52f+6benIGDBuWjx56Wpx6fk3un3JRZ90zP9T+YlI987tSsv/GmvblrawwZN0/GzZNxGXJunoybJ+My5NysJ55+IUd+6bLceOkX8uVzf5bBgwbk7BMOyM5jR6WruztfPPOH+fWUB3LVxE/m/5z9o9z1wJzcfNkXc8310/PV867NyZ96fx5+bH5mPvxkTjpi7zz1zAsZO2aTTPvdIznkxH/v7d1bI8gYllhdJ8SFSf649POzkrw+ydeW3nZRg+tqRE9Pdx68a2reNH7CSvfdet3VGTp8nRz99Qvzrn0PzJwH71t236KFL2bzbcbmqDMuyBZv2jG3//InGb3dm7P9+AnZ68AjctQZF3jxWkrGzZNx82RchpybJ+PmybgMOZcx69Gn0tFRZcP11skR+78jSfLWf/hKPnb8xTn/1AMzeNCATJ46I3uM2zrrvG5Iurt7svuOY5IkE3Yak8lTZyZJdtxusxx7xg8ybt/TsuVmG2TCTlv12j6taWTcN1VV1S8/esvqihAddV13Lf18fF3Xn6nr+sa6rk9J0vJIr6rq8KqqplRVNeU/rry0bYt9rRYvWpSJxx6W0w79YP74wvPZeofxK23z0L13ZocJeyZJNhq1VTYaPWbZfZ0DBmb7XXZPkozcats8/cTcMgvvQ2TcPBk3T8ZlyLl5Mm6ejMuQc3kv/V4yYacx+e5Pb0uS3D/r8Tz82PxsM3rDTJ46M2/feUwmjNsqP7/h7gwfNihDhwzM6JHr5YGH5iVJptz9UB6d90zqus70+2Zn1Mj1e2t31kgyZm23uiLEXVVVHbL08+lVVY1Pkqqqtk2yuNWD6ro+r67r8XVdj3/Pfh9t01Jfu5euJzz2m1eku2txbrn26pW2qVfx+M7OzmWVoo6OjvR0dze00r5Lxs2TcfNkXIacmyfj5sm4DDmXtcWm66e7u868+c+3fDeAKXc/lJ3Hjsoe47bOjVNnZPq9s3Poh/bItN89smybhYu6LTnLdAAAIABJREFUln3e092TAZ1rxRi6V0XGsPoixMeTvLOqqplJxia5uaqqB5N8e+l9fcqQYcPzgUOOzo0/viLdXV0r3LfF9m/JnTdfnySZN3tWHl96zeGqDB46LAsXLGhkrX2VjJsn4+bJuAw5N0/GzZNxGXJu3gYjhmfiiQfk3Cv+O0ly49SZOWDvJZ0nW4/aMJtvsl7unzUvi7u6M/vxZ7Lve8bltjt/n8nTZuYzB7172WUCtCZjWGKVRYi6rp+t6/rgJDslOTzJbkl2r+v6nXVdTy+wvrYbueU22Xj0mPz2pl+tcPuu790nf3jumZz9+UPz66svy8ajxmTIsOGrfK4dJuyZG665POd84eN5au6jTS67T5Fx82TcPBmXIefmybh5Mi5Dzu03dPDAZW8f+dNzP51f3nxvTvvWz5Mk3/rer9PZ0ZHbv3dCJn3tkHzi5ElZtHhJAWjytBmZN//5LHhxcSZPm5nNNh6RydNm9OaurLFk3D909NOP3lLV9aqa2P58V05/rNlv0CY9Pd3p7urKwEGD89TcR3Phlz6bfzzr0gwYMLC3l9ZvyLh5Mm6ejMuQc/Nk3DwZl9GXcz7w4NN6ewnQFgumndN7Uw4LuGLao33id9o/1f7jNu2Vn9sq36JzbbJ44cKcf8pn0tPdnbqu88GPf7ZPvHj1JTJunoybJ+My5Nw8GTdPxmXIGaBv0QkBAAC9QCcE/YVOiL6ptzohjFEFAAAAinA5BgAAALRQtXo/VV4TnRAAAABAEYoQAAAAQBGKEAAAAEARZkIAAABACyZCtJdOCAAAAKAIRQgAAACgCEUIAAAAYAVVVV1YVdW8qqruanF/VVXV2VVVzaiq6rdVVe38ap7XTAgAAABooarW2qkQFyc5J8klLe5/X5Jtln7smuTflv7/KumEAAAAAFZQ1/Wvk8xfxSb7JLmkXuKWJG+oqmqT1T2vIgQAAACsZaqqOryqqinLfRz+Jz7FpkkeWe7r2UtvWyWXYwAAAMBapq7r85Kc92c8xStdp1Kv7kGKEAAAANCCywdamp1k8+W+3izJnNU9SJ4AAADAn+qaJActfZeM3ZI8W9f1Y6t7kE4IAAAAYAVVVV2W5K+SbFBV1ewk/5RkYJLUdX1ukp8l2TvJjCR/THLIq3leRQgAAABgBXVdf3g199dJjvxTn9flGAAAAEAROiEAAACghap6pTeB4LXSCQEAAAAUoQgBAAAAFKEIAQAAABRhJgQAAAC0YCJEe+mEAAAAAIpQhAAAAACKUIQAAAAAijATAgAAAFqoDIVoK50QAAAAQBGKEAAAAEARihAAAABAEWZCAAAAQAsdMRSinXRCAAAAAEUoQgAAAABFKEIAAAAARShCAAAAAEUYTAkAAAAtVOZStpVOCAAAAKAIRQgAAACgCEUIAAAAoAgzIQAAAKCFKoZCtJNOCAAAAKAIRQgAAACgCEUIAAAAoAgzIQAAAKCFykiIttIJAQAAABShCAEAAAAUoQgBAAAAFGEmBAAAKznw4NN6ewkAa4SOGArRTjohAAAAgCIUIQAAAIAiFCEAAACAIhQhAAAAgCIMpgQAAIAWKnMp20onBAAAAFCEIgQAAABQhCIEAAAAUISZEAAAANCCmRDtpRMCAAAAKEIRAgAAAChCEQIAAAAowkwIAAAAaKGKoRDtpBMCAAAAKEIRAgAAAChCEQIAAAAowkwIAAAAaKHDSIi20gkBAAAAFKEIAQAAABShCAEAAAAUoQgBAAAAFGEwJQAAALRQxWTKdtIJAQAAABShCAEAAAAUoQgBAAAAFGEmBAAAALRQGQnRVjohAAAAgCIUIQAAAIAiFCEAAACAIsyEAAAAgBaqGArRTjohAAAAgCIUIQAAAIAiFCEAAACAIsyEAAAAgBY6jIRoK50QAAAAQBGKEAAAAEARihAAAABAEYoQAAAAQBEGUwIAAEALVUymbCedEAAAAEARihAAAABAEYoQAAAAQBFmQgAAAEALlZEQbaUTAgAAAChCEQIAAAAoQhECAAAAKMJMCAAAAGjBSIj20gkBAAAAFKEIAQAAABShCAEAAAAUsVbMhDhp/z2z0agt09PTnRFv3CR/f9QJGfq6dfLc/Cfzk4vOzkc+d+oqH3/KgXvlnyZdu9Lt99x2QzYYuXk23GyLhlbed8i4eTJunozLkHPzZNw8GTfvhSln564ZczJwQGe6urvznR/flonfuT51Xff20voNGTdPxv1DR2UqRDutFZ0QAwcNylFnXJBjzrw4w4avm1uuuzpJsu56G6z2Hwmrcs/tN2be7FltWmXfJuPmybh5Mi5Dzs2TcfNk3LwFCxdntwNOzy77nZYPHHFO/ubtY3Pi/35fby+rX5Fx82QMK1tlJ0RVVUcnuaqu60cKradxm287NnMffjBJ8vS8x3LJ147PMWdenEULX8wP/vX0PDHn4Wy46eg8/cTc/K/DjslmY7ZPkvzisvNz39SbM3DQoHz02NPy1ONzcu+UmzLrnum5/geT8pHPnZr1N960N3dtjSHj5sm4eTIuQ87Nk3HzZNy8J55+IUd+6bLceOkX8uVzf5bBgwbk7BMOyM5jR6WruztfPPOH+fWUB3LVxE/m/5z9o9z1wJzcfNkXc8310/PV867NyZ96fx5+bH5mPvxkTjpi7zz1zAsZO2aTTPvdIznkxH/v7d1bI8i4eTKGJVbXCfGlJLdWVXVDVVWfqqrqjSUW1ZSenu48eNfUvGn8hJXuu/W6qzN0+Do5+usX5l37Hpg5D9637L5FC1/M5tuMzVFnXJAt3rRjbv/lTzJ6uzdn+/ETsteBR+SoMy7wj4SlZNw8GTdPxmXIuXkybp6My5n16FPp6Kiy4Xrr5Ij935Ekees/fCUfO/7inH/qgRk8aEAmT52RPcZtnXVeNyTd3T3ZfccxSZIJO43J5KkzkyQ7brdZjj3jBxm372nZcrMNMmGnrXptn9Y0Mm6ejGH1RYgHk2yWJcWIXZLcU1XVtVVVfayqqnVaPaiqqsOrqppSVdWU/7jy0jYu97VZvGhRJh57WE479IP54wvPZ+sdxq+0zUP33pkdJuyZJNlo1FbZaPSYZfd1DhiY7XfZPUkycqtt8/QTc8ssvA+RcfNk3DwZlyHn5sm4eTLuHS9dlj1hpzH57k9vS5LcP+vxPPzY/GwzesNMnjozb995TCaM2yo/v+HuDB82KEOHDMzokevlgYfmJUmm3P1QHp33TOq6zvT7ZmfUyPV7a3fWSDJunoz7nqqffvSW1RUh6rque+q6/kVd14clGZnkm0n2ypICRasHnVfX9fi6rse/Z7+PtnG5r81L120e+80r0t21OLdce/VK26xqNExnZ2eqpWeLjo6O9HR3N7TSvkvGzZNx82RchpybJ+Pmybi8LTZdP93ddebNfz6tZsRNufuh7Dx2VPYYt3VunDoj0++dnUM/tEem/e5/rixeuKhr2ec93T0Z0LlWjEh7VWTcPBnD6osQK/ynUdf14rqur6nr+sNJRjW3rGYMGTY8Hzjk6Nz44yvS3dW1wn1bbP+W3Hnz9UmSebNn5fGHW9ZYlhk8dFgWLljQyFr7Khk3T8bNk3EZcm6ejJsn4zI2GDE8E088IOde8d9JkhunzswBey/pPtl61IbZfJP1cv+seVnc1Z3Zjz+Tfd8zLrfd+ftMnjYznzno3cta2GlNxs2TMSyxuiLE/q3uqOu6T75Cjtxym2w8ekx+e9OvVrh91/fukz8890zO/vyh+fXVl2XjUWMyZNjwVT7XDhP2zA3XXJ5zvvDxPDX30SaX3afIuHkybp6My5Bz82TcPBk3Y+jggbnl8uNyx5Un5qfnfjq/vPnenPatnydJvvW9X6ezoyO3f++ETPraIfnEyZOyaPGSItDkaTMyb/7zWfDi4kyeNjObbTwik6fN6M1dWWPJuHkyhpVVTb9H7ZXTH+sTb4Lb09Od7q6uDBw0OE/NfTQXfumz+cezLs2AAQN7e2n9hoybJ+PmybgMOTdPxs3r6xkfePBpvb0EoI9YMO2c3hwx0LhbZjzTJ36n/VPttvUbeuXntsq36FybLF64MOef8pn0dHenrut88OOf7TP/SOgrZNw8GTdPxmXIuXkybp6MAfqJfl1iKU8nBAAAK9EJAbxa/b4TYmY/7YQY0zudEMaoAgAAAEUoQgAAAABFmAkBAAAALVSGQrSVTggAAACgCEUIAAAAoAhFCAAAAKAIMyEAAACghcpIiLbSCQEAAAAUoQgBAAAAFKEIAQAAABRhJgQAAAC0YCREe+mEAAAAAIpQhAAAAACKUIQAAAAAilCEAAAAAIowmBIAAABaMZmyrXRCAAAAAEUoQgAAAABFKEIAAAAARZgJAQAAAC1UhkK0lU4IAAAAoAhFCAAAAKAIRQgAAACgCDMhAAAAoIXKSIi20gkBAAAAFKEIAQAAABShCAEAAAAUYSYEAAAAtGAkRHvphAAAAACKUIQAAAAAilCEAAAAAIpQhAAAAACKMJgSAAAAWjGZsq10QgAAAABFKEIAAAAARShCAAAAAEWYCQEAAAAtVIZCtJVOCAAAAKAIRQgAAACgCEUIAAAAoAgzIQAAAKCFykiIttIJAQAAABShCAEAAAAUoQgBAAAAFGEmBAAAALRgJER76YQAAAAAilCEAAAAAIpo/HKMAw8+relvsdabdPGJvb0EaAvni+Y5XzTPcQy8Ws7JzXNOhjWPTggAAACgCIMpAQAAoBWTKdtKJwQAAABQhCIEAAAAUIQiBAAAAFCEmRAAAADQQmUoRFvphAAAAACKUIQAAAAAilCEAAAAAIowEwIAAABaqIyEaCudEAAAAEARihAAAABAEYoQAAAAQBFmQgAAAEALRkK0l04IAAAAoAhFCAAAAKAIRQgAAACgCEUIAAAAoAiDKQEAAKAVkynbSicEAAAAUIQiBAAAAFCEIgQAAABQhJkQAAAA0EJlKERb6YQAAAAAilCEAAAAAIpQhAAAAACKMBMCAAAAWqiMhGgrnRAAAABAEYoQAAAAQBGKEAAAAEARZkIAAABAC0ZCtJdOCAAAAKAIRQgAAABgJVVV7VVV1X1VVc2oquq4V7j/4Kqqnqiq6jdLPz6+uud0OQYAAACwgqqqOpP8a5L3JJmd5Paqqq6p6/qel216RV3Xn361z6sTAgAAAHi5tyWZUdf1g3VdL0pyeZJ9/twnVYQAAACAVqp++rF6myZ5ZLmvZy+97eX2rarqt1VVXVlV1eare1JFCAAAAFjLVFV1eFVVU5b7OPzlm7zCw+qXff3jJFvUdb1Dkv9M8u+r+75mQgAAAMBapq7r85Kct4pNZidZvrNhsyRzXvYcTy335beTfG1131cnBAAAAPBytyfZpqqqLauqGpTkgCTXLL9BVVWbLPflB5P8bnVPqhMCAAAAWqhe5QCF/qau666qqj6d5LoknUkurOv67qqqTk0ypa7ra5IcXVXVB5N0JZmf5ODVPa8iBAAAALCSuq5/luRnL7vt5OU+Pz7J8X/Kc7ocAwAAAChCEQIAAAAowuUYAAAA0EK1do6EaIxOCAAAAKAIRQgAAACgCEUIAAAAoAgzIQAAAKAFIyHaSycEAAAAUES/74R4YcrZuWvGnAwc0Jmu7u5858e3ZeJ3rk9d1729tH7lpP33zEajtkxPT3dGvHGT/P1RJ2To69bJc/OfzE8uOjsf+dypq3z8KQfulX+adO1Kt99z2w3ZYOTm2XCzLRpaed8h4+Y5X5ThWG6W47h5Mi5DzmU4JzfLcQwr6/dFiAULF2e3A05PkrxxxPBc/NWDs+7wIfnyuT/r5ZX1LwMHDcpRZ1yQJLnynK/mluuuzrv+7sCsu94Gq33xWpV7br8x2++y+1r/ApbIuATnizIcy81yHDdPxmXIuQzn5GY5jmFla9XlGE88/UKO/NJlOWL/dyZJBg8akG/980dz+/dOyM2XfTHvGL9NkuSqiZ/Mm7cZmSS5+bIv5vjD90qSnPyp9+fgD+2ev9xlm1z37WPy3TMOy29+eFIuOu1jvbNDa6jNtx2b5+Y/mSR5et5jOetzBydJFi18MZf9yz/n7M8fmsu/cUr+7YRPZvbMe5c97heXnZ+Jxx6Wc0/8ZF54Zn4euu+u3Dvlplw76dxMPPawPDX30d7YnTWSjJvnfFGGY7lZjuPmybgMOZfhnNwsxzEsscoiRFVVg6qqOqiqqr9e+vVHqqo6p6qqI6uqGlhmie0169Gn0tFRZcP11skR+78jSfLWf/hKPnb8xTn/1AMzeNCATJ46I3uM2zrrvG5Iurt7svuOY5IkE3Yak8lTZyZJdtxusxx7xg8ybt/TsuVmG2TCTlv12j6tSXp6uvPgXVPzpvETVrrv1uuuztDh6+Tor1+Yd+17YOY8eN+y+xYtfDGbbzM2R51xQbZ40465/Zc/yejt3pztx0/IXgcekaPOuCDrb7xpyV1ZY8m4HOeLZjmWy3AcN0/GZci5Wc7JZTiO+6iqn370ktV1QlyU5P1JjqmqalKSv09ya5K3Jjm/4bU1ploa+ISdxuS7P70tSXL/rMfz8GPzs83oDTN56sy8fecxmTBuq/z8hrszfNigDB0yMKNHrpcHHpqXJJly90N5dN4zqes60++bnVEj1++t3VkjLF60KBOPPSynHfrB/PGF57P1DuNX2uahe+/MDhP2TJJsNGqrbDR6zLL7OgcMzPa77J4kGbnVtnn6ibllFt6HyLh3OF+0n2O5PMdx82Rchpzbzzm5PMcxa7vVFSHeUtf1/kk+lOS9Sfar63pSkkOSjGv1oKqqDq+qakpVVVO6nry7fattgy02XT/d3XXmzX9+2Qng5abc/VB2Hjsqe4zbOjdOnZHp987OoR/aI9N+98iybRYu6lr2eU93TwZ0rlVXtqzkpesJj/3mFenuWpxbrr16pW1WNX6ns7Mz1dIfSEdHR3q6uxtaad8l4/KcL5rhWC7Lcdw8GZch52Y4J5flOIbVFyE6qqoalGSdJMOSvH7p7YOTtLwco67r8+q6Hl/X9fgBG/xFe1baBhuMGJ6JJx6Qc6/47yTJjVNn5oC9l1R7tx61YTbfZL3cP2teFnd1Z/bjz2Tf94zLbXf+PpOnzcxnDnr3svYnWhsybHg+cMjRufHHV6S7q2uF+7bY/i258+brkyTzZs/K4w8/uNrnGzx0WBYuWNDIWvsqGZfhfNE8x3LzHMfNk3EZcm6ec3LzHMewxOreHeOCJPcm6UxyYpLvV1X1YJLdklze8NraYujggbnl8uOWvS3OZT+5PWdd+qskybe+9+tMPPGA3P69E9LV3Z1PnDwpixYvOelOnjYj73rbdlnw4uJMnjYzm208IpOnzejNXekzRm65TTYePSa/velX2WL7tyy7fdf37pMr//WrOfvzh2bkFttk41FjMmTY8FU+1w4T9sxV3/p6bv75D/Lhz57imsKlZNwM54vyHMvt5zhunozLkHN5zsnt5zjuH6reHKDQD1Wre4/aqqpGJkld13OqqnpDkr9O8nBd17e9mm8wdNynvQluwyZdfGJvL+FV6enpTndXVwYOGpyn5j6aC7/02fzjWZdmwIA+OeN0jdTXMz7w4NN6ewn9nvNF8xzHwKvlnNw85+QyFkw7p1//lv7A4wv65e+022w0tFd+bqvrhEhd13OW+/yZJFc2uiL6rcULF+b8Uz6Tnu7u1HWdD378s33ixasvkTH9hWMZYM3hnAy002qLENAug4cOy5Gnn9fby+jXZEx/4VgGWHM4JwPtpAgBAAAALbR6JxNeG+/lAgAAABShCAEAAAAUoQgBAAAAFGEmBAAAALRgJER76YQAAAAAilCEAAAAAIpQhAAAAACKUIQAAAAAijCYEgAAAFoxmbKtdEIAAAAARShCAAAAAEUoQgAAAABFmAkBAAAALVSGQrSVTggAAACgCEUIAAAAoAhFCAAAAKAIMyEAAACghcpIiLbSCQEAAAAUoQgBAAAAFKEIAQAAABRhJgQAAAC0YCREe+mEAAAAAIpQhAAAAACKUIQAAAAAilCEAAAAAIowmBIAAABaMZmyrXRCAAAAAEUoQgAAAABFKEIAAAAARZgJAQAAAC1UhkK0lU4IAAAAoAhFCAAAAKAIRQgAAACgCDMhAAAAoIXKSIi20gkBAAAAFKEIAQAAABShCAEAAAAUYSYEAAAAtGAkRHvphAAAAACKUIQAAAAAilCEAAAAAIpQhAAAAACKMJgSAAAAWqhMpmwrnRAAAABAEYoQAAAAQBGKEAAAAEARZkIAAABAS4ZCtFNV13Wj3+DK6Y81+w0AAABewdd/fn9vL2GtcMtx7+zXv6XPfnpRv/yddrMRg3rl5+ZyDAAAAKAIRQgAAACgCDMhAAAAoIWqX19sUp5OCAAAAKAIRQgAAACgCEUIAAAAoAgzIQAAAKAFIyHaSycEAAAAUIQiBAAAAFCEIgQAAABQhCIEAAAAUITBlAAAANBCZTJlW+mEAAAAAIpQhAAAAACKUIQAAAAAijATAgAAAFqoYihEO+mEAAAAAIpQhAAAAACKUIQAAAAAijATAgAAAFoxEqKtdEIAAAAARShCAAAAAEUoQgAAAABFmAkBAAAALRgJ0V46IQAAAIAiFCEAAACAIhQhAAAAgCIUIQAAAIAiDKYEAACAFiqTKdtKJwQAAABQhCIEAAAAUIQiBAAAAFCEmRAAAADQQhVDIdpJJwQAAABQhCIEAAAAUIQiBAAAAFCEmRAAAADQipEQbaUTAgAAAChCEQIAAAAoQhECAAAAKMJMCAAAAGjBSIj20gkBAAAAFKEIAQAAABShCAEAAAAUoQgBAAAAFGEwJQAAALRQmUzZVjohAAAAgCIUIQAAAIAiFCEAAACAItaKIsRJ+++ZiccelrM+d3AuOf34LPjD80mS5+Y/me+eefJqH3/KgXu94u333HZD5s2e1c6l9lkybp6MmyfjMuTcPBk3T8ZlyLl5Mm7OukMG5JJDdsklh+ySn35691xz5G7Lvh7Q0b4hAxuuMzhf3udNbXs+Vlb10//1lrWiCDFw0KAcdcYFOebMizNs+Lq55bqrkyTrrrdBPvK5U1/z895z+41r/cn1JTJunoybJ+My5Nw8GTdPxmXIuXkybs5zL3bloIvuyEEX3ZGrfjMnl98+e9nXXT31ah//ausU855fmJN+9Ls/c7VQzmrfHaOqqjFJPpRk8yRdSR5Iclld1882vLZGbL7t2Mx9+MEkydPzHsslXzs+x5x5cRYtfDE/+NfT88Sch7PhpqPz9BNz878OOyabjdk+SfKLy87PfVNvzsBBg/LRY0/LU4/Pyb1Tbsqse6bn+h9Mykc+d2rW33jT3ty1NYaMmyfj5sm4DDk3T8bNk3EZcm6ejMvZ+80bZd+dR2ZgZ0fufPTZfP0XM9JRJdces0euvOPRvG3LEfnGf87MV/52bH5219yMHz0iHR3J1659IJ/6qy2z6RuGZtItD+dH0+dmszcMyVc+9Bc56KI7enu34FVZZSdEVVVHJzk3yZAkb00yNEuKETdXVfVXja+uzXp6uvPgXVPzpvETVrrv1uuuztDh6+Tor1+Yd+17YOY8eN+y+xYtfDGbbzM2R51xQbZ40465/Zc/yejt3pztx0/IXgcekaPOuMCJdSkZN0/GzZNxGXJunoybJ+My5Nw8GZez1QbD8s5tN8jhk6bloIvuSGdHlfeM3TBJss6QAbnv8Rdy2CXTctec55Ikjz37Yj4+aVrunvN8Tth723zxh3fn8EnTcvhfbtmbuwGv2eo6IT6RZKe6rrurqvqXJD+r6/qvqqr6VpIfJRn3Sg+qqurwJIcnyeEn/d+8Z7+PtnPNf7LFixZl4rGH5Zkn5mbkVttl6x3Gr7TNQ/femQl775ck2WjUVtlo9Jhl93UOGJjtd9k9STJyq20z47dTyiy8D5Fx82TcPBmXIefmybh5Mi5Dzs2TcXlv3WJE3rTJOrno4F2SJIMHdOTx5xYmSRZ19eS/7n9yhe1veOCpJMmMeX9IZ1XlxcU9eXFxT3rqOkMHrhVX1/e6qvfGJ/RLr+aofalQMTjJOklS1/XDSQa2ekBd1+fVdT2+ruvxvV2ASP7nWrdjv3lFursW55Zrr15pm1VdldXZ2Zlq6ZHX0dGRnu7uhlbad8m4eTJunozLkHPzZNw8GZch5+bJuLyqSn7y27nL5kPs/+3bc9FNDydJFnb1rLT9ou4lt9V1vezzJV8nnW0ccAmlrK4IcX6S26uqOi/JzUnOSZKqqt6YZH7Da2u7IcOG5wOHHJ0bf3xFuru6Vrhvi+3fkjtvvj5JMm/2rDy+9Hq4VRk8dFgWLljQyFr7Khk3T8bNk3EZcm6ejJsn4zLk3DwZl3P7rGfy7u3fmNcPXfK33nWHDMhG6w7u5VVBOassQtR1fVaSDyf5RZK/rev6oqW3P1HX9TsKrK/tRm65TTYePSa/velXK9y+63v3yR+eeyZnf/7Q/Prqy7LxqDEZMmz4Kp9rhwl75oZrLs85X/h4npr7aJPL7lNk3DwZN0/GZci5eTJunozLkHPzZFzGzCf+kAsmP5SJB+yYSw/dJWcfsEPWGzaot5cFxVR1vfq3h/lzXDn9sWa/QZv09HSnu6srAwcNzlNzH82FX/ps/vGsSzNgQMurTvgTybh5Mm6ejMuQc/Nk3DwZlyHn5vXljL/+8/t7ewlrhVuOe2e/vi7k6T9294nfaf9UI4Z19srPbbVv0bm2WLxwYc4/5TPp6e5OXdf54Mc/2ydOrH2JjJsn4+bJuAw5N0/GzZNxGXJunoyBdtIJAQAA9Es6IcrQCdE39VYnhPd0AQAAAIpQhAAAAACKMBMCAAAAWqj69cUm5emEAAAAAIpQhAAAAACKUIQAAAAAijATAgAAAFqoYihEO+mEAAAAAIpQhAAAAACKUIQAAAAAijATAgAAAFqojIRoK50QAAAAQBGKEAAAAEARihAAAACrZr/TAAAHlUlEQVRAEWZCAAAAQAtGQrSXTggAAACgCEUIAAAAoAhFCAAAAKAIRQgAAACgCIMpAQAAoBWTKdtKJwQAAABQhCIEAAAAUIQiBAAAAFCEmRAAAADQQmUoRFvphAAAAACKUIQAAAAAilCEAAAAAIowEwIAAABaqIyEaCudEAAAAEARihAAAABAEYoQAAAAQBFmQgAAAEALRkK0l04IAAAAoAhFCAAAAKAIRQgAAACgCEUIAAAAoAiDKQEAAKAVkynbSicEAAAAUIQiBAAAAFCEIgQAAABQhJkQAAAA0EJlKERb6YQAAAAAilCEAAAAAIpQhAAAAACKUIQAAACAFqqqf368un2v9qqq6r6qqmZUVXXcK9w/uKqqK5bef2tVVVus7jkVIQAAAIAVVFXVmeRfk7wvydgkH66qauzLNjssydN1XW+d5BtJvra651WEAAAAAF7ubUlm1HX9YF3Xi5JcnmSfl22zT5J/X/r5lUneXVWr7rNQhAAAAABebtMkjyz39eylt73iNnVddyV5Nsn6q3rSAW1c4Cvab8dN+tybqlZVdXhd1+f19jr6Mxk3T8ZlyLl5Mm6ejMuQc/Nk3Ly+lvF+O27S20v4k/W1jNcGQwakz/1O+2pUVXV4ksOXu+m8lx17r7Tf9cuf5lVsswKdEK/s8NVvwp9Jxs2TcRlybp6MmyfjMuTcPBk3T8bNkzFF1HV9Xl3X45f7eHnxa3aSzZf7erMkc1ptU1XVgCSvTzJ/Vd9XEQIAAAB4uduTbFNV1ZZVVQ1KckCSa162zTVJPrb08/2S/Kqu61V2QjR+OQYAAADQt9R13VVV1aeTXJekM8mFdV3fXVXVqf+vvTsLsbKOwzj+fXICdUqKNswpKogoukgJW4QhMkMr2iBQqItuiqjQuojqougyiOguCMf2FFODiKEF2i+yXIq0aTEzHVumoM0WzHq6eN+YKQKpzjn//Pd84HCWi8PDn5ez/N7/7/cC62w/CQwBD0vaQrMDYuHe3jdFiL+WHqzuyxp3X9a4N7LO3Zc17r6scW9knbsva9x9WePuyxrHf4btYWD4T6/dNuHxT8Blf+c9tZedEhERERERERERHZGZEBERERERERHREylCTCBpvqT3JG2RdHPpPDWStEzSmKRNpbPUStJRkl6QNCJps6TFpTPVRtJkSa9Leqtd4ztKZ6qVpEmSNkp6qnSWWknaJultSW9KWlc6T40kHSRplaR328/mM0pnqomkE9rj9/fbt5KWlM5VI0k3tN97myQtlzS5dKbaSFrcru/mHMdRq7RjtCRNAt4H5tFcZuQNYJHtd4oGq4ykQWAX8JDtk0vnqZGk6cB02xskHQisBy7Osdw5kgT0294laX/gVWCx7dcKR6uOpBuBU4Fpti8onadGkrYBp9r+snSWWkl6EHjF9tJ2uvhU21+XzlWj9vfcTuA02x+XzlMTSTNovu9Osv2jpJXAsO0Hyiarh6STgRXAbGA38DRwje0PigaL6LDshBg3G9hie6vt3TQfABcVzlQd2y+zl+vGxr9j+1PbG9rH3wEjwIyyqerixq726f7tLRXdDpM0AJwPLC2dJeKfkjQNGKSZHo7t3SlAdNVc4MMUILqmD5giqQ+YCnxSOE9tTgRes/2D7T3AS8AlhTNFdFyKEONmADsmPB8lf9xiHyfpGGAmsLZskvq0bQJvAmPAc7azxp13D3AT8GvpIJUz8Kyk9ZKuKh2mQscBXwD3t61FSyX1lw5VsYXA8tIhamR7J3AXsB34FPjG9rNlU1VnEzAo6RBJU4HzgKMKZ4rouBQhxukvXsuZzdhnSToAWA0ssf1t6Ty1sf2L7VOAAWB2u4UyOkTSBcCY7fWls/wPzLE9C1gAXNu2zUXn9AGzgHttzwS+BzJ3qgvaVpcLgcdLZ6mRpINpdgkfCxwJ9Eu6vGyqutgeAe4EnqNpxXgL2FM0VEQXpAgxbpQ/VhoHyBaz2Ee1cwpWA4/aXlM6T83abdUvAvMLR6nNHODCdl7BCuBsSY+UjVQn25+092PAEzTtidE5o8DohN1Sq2iKEtF5C4ANtj8vHaRS5wAf2f7C9s/AGuDMwpmqY3vI9izbgzQtzJkHEdVJEWLcG8Dxko5tK+kLgScLZ4r429qhiUPAiO27S+epkaTDJB3UPp5C88Ps3bKp6mL7FtsDto+h+Tx+3nbOuHWYpP52gC1ti8C5NNuBo0NsfwbskHRC+9JcIIOCu2MRacXopu3A6ZKmtr815tLMnYoOknR4e380cCk5pqNCfaUD/FfY3iPpOuAZYBKwzPbmwrGqI2k5cBZwqKRR4HbbQ2VTVWcOcAXwdjuzAOBW28MFM9VmOvBgO4V9P2Cl7VxCMvZFRwBPNP8n6AMes/102UhVuh54tD3JsRW4snCe6rT98/OAq0tnqZXttZJWARtoWgQ2AveVTVWl1ZIOAX4GrrX9VelAEZ2WS3RGRERERERERE+kHSMiIiIiIiIieiJFiIiIiIiIiIjoiRQhIiIiIiIiIqInUoSIiIiIiIiIiJ5IESIiIiIiIiIieiJFiIiIiIiIiIjoiRQhIiIiIiIiIqInUoSIiIiIiIiIiJ74DRHsxrStmTTQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 1297.7687861271677\n",
      "Planning size: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 996.2692307692307\n",
      "Planning size: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 991.7826086956521\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epochs Count [346, 26, 23]\n",
      "Difference(MSE) Value [3.369031325905964e-17, 9.175506328761679e-17, 7.448550585643646e-18]\n"
     ]
    }
   ],
   "source": [
    "blocks = [(5,i) for i in range(1,10)]\n",
    "\n",
    "epochs_count = []\n",
    "diff_count = []\n",
    "cumm_rewards = []\n",
    "for i in [0,3,5]:\n",
    "    print(\"Planning size:\", i)\n",
    "    game = DynaMaze(10, i, (9,9), blocked_blocks = blocks, mode_type = 'DQ', verbose=False)\n",
    "    diff, epochs, avg_episode_length, total_rewards = game.play(epochs=1000, threshold=1e-16, changed=False)\n",
    "    print(\"Average Length of Episode:\", avg_episode_length)\n",
    "    epochs_count.append(epochs)\n",
    "    diff_count.append(diff)\n",
    "    cumm_rewards.append(np.cumsum(total_rewards))\n",
    "\n",
    "plt.plot(cumm_rewards[0])\n",
    "plt.plot(cumm_rewards[1])\n",
    "plt.plot(cumm_rewards[2])\n",
    "plt.xlabel('Planning Size')\n",
    "plt.ylabel('Cummulative Reward Sum')\n",
    "plt.show()\n",
    "plt.plot(epochs_count)\n",
    "plt.xlabel('Step Size')\n",
    "plt.ylabel('Epochs taken for Converging')\n",
    "plt.show()\n",
    "plt.plot(diff_count)\n",
    "plt.xlabel('Step Size')\n",
    "plt.ylabel('Change in Q function(MSE)')\n",
    "plt.show()\n",
    "\n",
    "print('Epochs Count', epochs_count)\n",
    "print('Difference(MSE) Value', diff_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DQ+ Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-18T07:23:51.124322Z",
     "start_time": "2020-07-18T07:23:05.662871Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Planning size: 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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BlAAAANCJuZRdZScEAAAAUIUSAgAAAKhCCQEAAABUYSYEAAAAdFCKoRDdZCcEAAAAUIUSAgAAAKhCCQEAAABUYSYEAAAAdGAmRHdtECXExw/eP1tN3DEDA/3Z7KXb5O3HnJSxG2+SJ5Y8miu+ekYOPf6Udf78yTMOyCcvuGqty2+74ZqMn7B9ttxuh5ZWPjgsnXNGbrn7gYwcMTx9/f35xvduyJnfuDpN0/R6aRuEbf5sdD7/tlfkf583Z81l73n1pPxhRX++ecPCHq5s8HGuqEPO7ZNx+2Rch5zb5Tlc+2QMa9sg3o4xctSoHHPaeTn29POz0bhNc/0PL0+SbLr5+PX+47Uut914bRYtXNClVQ5ey5avzKsOOTX7vG1W3nT0WfnrV++RmX//hl4vC/5ozhV1yLl9Mm6fjOuQc7s8h2ufjGFtG8ROiGfaftc98tB99yRJHlv0YL7+uY/l2NPPz4rlT+Wyfz01jzxwX7bcdlIee+Sh/M2Rx2a7ybsnSX500bm5c+51GTlqVN55wqwsfviB3DHn51lw2025+rILcujxp2SLrbft5V17UXjksaV5/6cuyrUXfiSfPvsHGT1qRM446ZDsvcfE9PX358TTv52fzflNvnPm+/JPZ/x7bvnNA7nuohPz3atvymfPuSqf+Ic35r4Hl2T+fY/m40cfmMWPL80ek7fJvNt/m8Nnfq3Xd2/Q+dKhU3LXw0uzxzabZOPRIzLrB3fmtgef7PWyBgXnijrk3D4Zt0/Gdci5XZ7DtU/GsMoGsRPiaQMD/bnnlrl52bTpa133ix9enrHjNskHP/+VvPagGXngnjvXXLdi+VPZfpc9csxp52WHl03JjT++IpN2e3l2nzY9B8w4Osecdp5/vJ5hwf2LM2xYyZabb5KjD35NkuSV7/hM3v2x83PuKTMyetSIzJ57d/abunM22XhM+vsHsu+UyUmS6XtNzuy585MkU3bbLiecdlmmHjQrO243PtP32qln92kwGztyeI668Fc57Ue/ycwDd+v1cgYF54o65Nw+GbdPxnXIuQ7P4don48GplDIkv3rlTy4hSimHd3MhbVq5YkXOPOHIzDrizfnD0iez857T1jrm3jtuzp7T90+SbDVxp2w1afKa64aPGJnd99k3STJhp13z2CMP1Vn4IPb0Y3r6XpPzze/fkCS5a8HDue/BJdll0paZPXd+Xr335EyfulOuvObWjNtoVMaOGZlJEzbPb+5dlCSZc+u9uX/R42maJjfduTATJ2zRq7vzora+txT+6PZVef7qt7/LxqOGZ9zo4RVWNTg5V9Qh5/bJuH0yrkPO9XkO1z4Zs6H7r+yEOLnTFaWUo0opc0opc/7jWxf+F/6I7nj6/YQnfOmS9PetzPVXXb7WMet6HTd8+PA1TdGwYcMy0N/f0kqHhh223SL9/U0WLXkynQq2Obfem733mJj9pu6ca+fenZvuWJgj3rpf5t3+2zXHLF/Rt+b7gf6BjBi+QW3cecF+t2xlNhnz7HdWbTpmRB7/w8oka5cUxiB15lxRh5zbJ+P2ybgOOdflOVz7ZAzrKSFKKb/u8HVzkq06/VzTNOc0TTOtaZppr3/bO7u+6D/VmI3G5U2HfzDXfu+S9Pf1Peu6HXZ/RW6+7uokyaKFC/Lw6vccrsvosRtl+bJlrax1sBq/2bicOfOQnH3JT5Mk186dn0MOXPVbi50nbpntt9k8dy1YlJV9/Vn48OM56PVTc8PN/5nZ8+bnQ+963ZotZrxwy1YOZPHSFZk26SVJVhUQr9pp89y08HdJkv/5spcmSaZst2mWLu/L75d7ArY+zhV1yLl9Mm6fjOuQc/s8h2ufjGGV9VVmWyV5V5K/eZ6vxe0urR0TdtwlW0+anF///CfPuvwv/+ot+f0Tj+eMDx+Rn11+UbaeODljNhq3ztvac/r+uea7F+esj7wnix+6v81lv6iNHT0y11/80fzyWzPz/bM/kB9fd0dmffnKJMmXL/1Zhg8blhsvPSkXfO7wvPcTF2TFylVPHmbPuzuLljyZZU+tzOx587Pd1ptl9ry7e3lXBq2Tr7gjh0+flK8fvk/O+rspOe/ae3P/408lSZ58qi/nvHOvfOSvd81nrryrxysdPJwr6pBz+2TcPhnXIefu8xyufTKGtZV1fUZtKeW8JF9tmuba57num03THLq+P+BbNz04KHZ/Dwz0p7+vLyNHjc7ih+7PVz51XP7xixdmxIiRvV7aes04bFavlzDkTTn47b1ewp/kS4dOyRk/mZ87Hlra66W8IB9+w669XsJ6DeZzxWAi5/bJuH0yrmMw5+w5HEPFsnln9W7KYQV/9ncXDIrXtH+s3100oyd/b+v8iM6maY5cx3XrLSAGk5XLl+fckz+Ugf7+NE2TN7/nuEHxjxdQl3NFHXJun4zbJ+M65AwwuKxzJ0Q3DJadEIOZFr19g3UnxGAzGHZCAEC3eA7HUGEnxODUq50QxqgCAAAAVazz7RgAAACwQRvS+zzqsxMCAAAAqEIJAQAAAFShhAAAAACqMBMCAAAAOijFUIhushMCAAAAqEIJAQAAAFShhAAAAACepZSyfSnl6lLK7aWUW0spxz7PMf+jlPK7UsqvVn99Yn23ayYEAAAAdLABz4ToS3J80zRzSymbJPllKeU/mqa57TnHXdM0zZte6I3aCQEAAAA8S9M0DzZNM3f1908muT3Jtv/V21VCAAAAAB2VUnZIMjXJL57n6n1LKTeVUq4spfz5+m5LCQEAAAAbmFLKUaWUOc/4OqrDceOSXJbkQ03TPPGcq+cmmdQ0zZQkZya5fH1/rpkQAAAAsIFpmuacJOes65hSysisKiC+0TTNt5/nNp54xvc/KKV8qZQyvmmaRzvdphICAAAAOthQB1OWVXf8vCS3N03zhQ7HbJ3k4aZpmlLKX2TVuy0Wr+t2lRAAAADAc+2XZEaSm0spv1p92UlJJiZJ0zRnJ3lbkveVUvqSLEtySNM0zbpuVAkBAAAAPEvTNNcmWec2kKZpzkpy1h9zuwZTAgAAAFXYCQEAAAAdbKgzIdpiJwQAAABQhRICAAAAqEIJAQAAAFRhJgQAAAB0YiREV9kJAQAAAFShhAAAAACqUEIAAAAAVZgJAQAAAB2UYihEN9kJAQAAAFShhAAAAACqUEIAAAAAVSghAAAAgCoMpgQAAIAODKbsLjshAAAAgCqUEAAAAEAVSggAAACgCjMhAAAAoAMzIbrLTggAAACgCiUEAAAAUIUSAgAAAKjCTAgAAADoxEiIrrITAgAAAKhCCQEAAABUoYQAAAAAqjATAgAAADooxVCIbrITAgAAAKhCCQEAAABUoYQAAAAAqlBCAAAAAFW0PphyxmGz2v4jNnhTDn57r5cw5H34Dbv2egkAAEAPGEzZXXZCAAAAAFUoIQAAAIAqlBAAAABAFa3PhAAAAIDBykyI7rITAgAAAKhCCQEAAABUoYQAAAAAqjATAgAAADowE6K77IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACAToyE6Co7IQAAAIAqlBAAAABAFUoIAAAAoAolBAAAAFCFwZQAAADQQSkmU3aTnRAAAABAFUoIAAAAoAolBAAAAFCFmRAAAADQgZkQ3WUnBAAAAFCFEgIAAACoQgkBAAAAVGEmBAAAAHRgJkR32QkBAAAAVKGEAAAAAKpQQgAAAABVmAkBAAAAnRgJ0VV2QgAAAABVKCEAAACAKpQQAAAAQBVKCAAAAKAKgykBAACgg1JMpuwmOyEAAACAKpQQAAAAQBVKCAAAAKAKMyEAAACgAzMhustOCAAAAKAKJQQAAABQhRICAAAAqMJMCAAAAOjATIjushMCAAAAqEIJAQAAAFShhAAAAACqMBMCAAAAOjATorvshAAAAACqUEIAAAAAVSghAAAAgCqG/EyIpXPOyC13P5CRI4anr78/3/jeDTnzG1enaZpeL22DsM2fjc7n3/aK/O/z5qy57D2vnpQ/rOjPN29Y2MOVDT4fP3j/bDVxxwwM9Gezl26Ttx9zUsZuvEmeWPJorvjqGTn0+FPW+fMnzzggn7zgqrUuv+2GazJ+wvbZcrsdWlr54CHjOuTcPhm3T8Z1yLldnie3T8awtiG/E2LZ8pV51SGnZp+3zcqbjj4rf/3qPTLz79/Q62XBH23kqFE55rTzcuzp52ejcZvm+h9eniTZdPPx630Sti633XhtFi1c0KVVDm4yrkPO7ZNx+2Rch5zb5Xly+2Q8RJQh+tUj690JUUrZPcm2SX7RNM3SZ1x+QNM0a1fLL2KPPLY07//URbn2wo/k02f/IKNHjcgZJx2SvfeYmL7+/px4+rfzszm/yXfOfF/+6Yx/zy2/eSDXXXRivnv1TfnsOVflE//wxtz34JLMv+/RfPzoA7P48aXZY/I2mXf7b3P4zK/1+u4NOl86dEruenhp9thmk2w8ekRm/eDO3Pbgk71e1qCw/a575KH77kmSPLbowXz9cx/LsaefnxXLn8pl/3pqHnngvmy57aQ89shD+Zsjj812k3dPkvzoonNz59zrMnLUqLzzhFlZ/PADuWPOz7Pgtpty9WUX5NDjT8kWW2/by7v2oiHjOuTcPhm3T8Z1yLldnie3T8awyjp3QpRSPpjk35Mck+SWUspbnnH1Z9pcWFsW3L84w4aVbLn5Jjn64NckSV75js/k3R87P+eeMiOjR43I7Ll3Z7+pO2eTjcekv38g+06ZnCSZvtfkzJ47P0kyZbftcsJpl2XqQbOy43bjM32vnXp2nwazsSOH56gLf5XTfvSbzDxwt14vZ1AYGOjPPbfMzcumTV/rul/88PKMHbdJPvj5r+S1B83IA/fcuea6Fcufyva77JFjTjsvO7xsSm788RWZtNvLs/u06TlgxtE55rTzPAlbTcZ1yLl9Mm6fjOuQcx2eJ7dPxrD+t2O8N8k+TdP8ryT/I8k/lVKOXX1dxw0cpZSjSilzSilz+h69tTsr7aKnP+Z1+l6T883v35AkuWvBw7nvwSXZZdKWmT13fl699+RMn7pTrrzm1ozbaFTGjhmZSRM2z2/uXZQkmXPrvbl/0eNpmiY33bkwEyds0au786K2vre7/ej2VXn+6re/y8ajhmfc6OEVVjU4rVyxImeecGRmHfHm/GHpk9l5z2lrHXPvHTdnz+n7J0m2mrhTtpo0ec11w0eMzO777JskmbDTrnnskYfqLHwQkXEdcm6fjNsn4zrkXJ/nye2TMRu69ZUQw59+C0bTNAuyqoh4QynlC1lHCdE0zTlN00xrmmbaiPF/3q21dsUO226R/v4mi5Y8ueYE8Fxzbr03e+8xMftN3TnXzr07N92xMEe8db/Mu/23a45ZvqJvzfcD/QMZMXzIj9f4k/xu2cpsMubZ7/rZdMyIPP6HlUnWLimM6Ons6ffFnvClS9LftzLXX3X5WsesK7/hw4enrH7QDxs2LAP9/S2tdPCScR1ybp+M2yfjOuRcl+fJ7ZPx4FRKGZJfvbK+R+tDpZS9nv6P1YXEm5KMT/KKNhfWhvGbjcuZMw/J2Zf8NEly7dz5OeTAVY36zhO3zPbbbJ67FizKyr7+LHz48Rz0+qm54eb/zOx58/Ohd71uzfYnXrhlKweyeOmKTJv0kiSrCohX7bR5blr4uyTJ/3zZS5MkU7bbNEuX9+X3yz05WJ8xG43Lmw7/YK793iXp7+t71nU77P6K3Hzd1UmSRQsX5OHV751dl9FjN8ryZctaWetgJeM65Nw+GbdPxnXIuX2eJ7dPxrDK+kqIdyV51r61pmn6mqZ5V5LXtLaqLho7emSuv/ij+eW3Zub7Z38gP77ujsz68pVJki9f+rMMHzYsN156Ui743OF57ycuyIqVq/5hmz3v7ixa8mSWPbUys+fNz3Zbb5bZ8+7u5V0ZtE6+4o4cPn1Svn74Pjnr76bkvGvvzf2PP5UkefKpvpzzzr3ykb/eNZ+58q4er3TwmLDjLtl60uT8+uc/edblf/lXb8nvn3g8Z3z4iPzs8ouy9cTJGbPRuHXe1p7T98813704Z33kPVn80P1tLntQkXEdcm6fjNsn4zrk3H2eJ7dPxrC20vZn1I6d+gE77Fs25eC393oJf5IvHTolZ/xkfu54aEqNcD4AACAASURBVOn6D+6xD79h114v4QUZGOhPf19fRo4ancUP3Z+vfOq4/OMXL8yIESN7vbQhQ8Z1yLl9Mm6fjOsYzDnPOGxWr5cAXbFs3lk9/MDH9u103A+G5Gvae75wYE/+3tb7EZ3A4LFy+fKce/KHMtDfn6Zp8ub3HDconoQNJjKuQ87tk3H7ZFyHnIG29XJ+wlBkJ8QQMFh3Qgwmg2UnBAAweNgJwVAx1HdCTD7+yiH5mnb+6W/oyd+bMaoAAABAFUoIAAAAoAozIQAAAKADIyG6y04IAAAAoAolBAAAAFCFEgIAAACoQgkBAAAAVGEwJQAAAHRQTKbsKjshAAAAgCqUEAAAAEAVSggAAACgCjMhAAAAoAMjIbrLTggAAACgCiUEAAAAUIUSAgAAAKjCTAgAAADooBgK0VV2QgAAAABVKCEAAACAKpQQAAAAQBVmQgAAAEAHRkJ0l50QAAAAQBVKCAAAAKAKJQQAAABQhRICAAAAqMJgSgAAAOhg2DCTKbvJTggAAACgCiUEAAAAUIUSAgAAAKjCTAgAAADooBgJ0VV2QgAAAABVKCEAAACAKpQQAAAAQBVmQgAAAEAHxVCIrrITAgAAAKhCCQEAAABUoYQAAAAAqjATAgAAADowEqK77IQAAAAAqlBCAAAAAFUoIQAAAIAqlBAAAABAFQZTAgAAQAfFZMqushMCAAAAqEIJAQAAAFShhAAAAACqMBMCAAAAOjATorvshAAAAACqsBNiCLjpkv+v10sY8mZc0usVQHdccP7MXi8B/stmHDar10sAAP5EdkIAAAAAVdgJAQAAAB0YCdFddkIAAAAAVSghAAAAgCqUEAAAAEAVZkIAAABAB8VQiK6yEwIAAACoQgkBAAAAVKGEAAAAAKpQQgAAAABVGEwJAAAAHZhL2V12QgAAAABVKCEAAACAKpQQAAAAQBVmQgAAAEAHxVCIrrITAgAAAKhCCQEAAABUoYQAAAAAqjATAgAAADowEqK77IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADoqhEF1lJwQAAABQhRICAAAAqEIJAQAAAFShhAAAAACqMJgSAAAAOjCXsrvshAAAAACqUEIAAAAAVSghAAAAgCrMhAAAAIAOiqEQXWUnBAAAAFCFEgIAAAB4llLK9qWUq0spt5dSbi2lHPs8x5RSyhmllLtLKb8upey9vtv1dgwAAADgufqSHN80zdxSyiZJfllK+Y+maW57xjFvSLLL6q+/TPJvq/+3IyUEAAAAdLChjoRomubBJA+u/v7JUsrtSbZN8swS4i1Jvt40TZPk+lLKS0op26z+2efl7RgAAACwgSmlHFVKmfOMr6PWcewOSaYm+cVzrto2yW+f8d8LV1/WkZ0QAAAAsIFpmuacJOes77hSyrgklyX5UNM0Tzz36ue76XXdnp0QAAAAwFpKKSOzqoD4RtM0336eQxYm2f4Z/71dkgfWdZt2QgAAAEAHZQMdClFW3fHzktzeNM0XOhz23SQfKKVcnFUDKX+3rnkQiRICAAAAWNt+SWYkubmU8qvVl52UZGKSNE1zdpIfJDkwyd1J/pDk8PXdqBICAAAAeJamaa7N8898eOYxTZL3/zG3ayYEAAAAUIUSAgAAAKjC2zEAAACggw10LmVr7IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADoqhEF1lJwQAAABQxZDfCbF0zhm55e4HMnLE8PT19+cb37shZ37j6jRN0+ulDRkybp+M65BzHR8/eP9sNXHHDAz0Z7OXbpO3H3NSxm68SZ5Y8miu+OoZOfT4U9b58yfPOCCfvOCqtS6/7YZrMn7C9tlyux1aWvngIeN2OVfUIef2ybh9Moa1DfkSYtnylXnVIacmSV662bic/9nDsum4Mfn02T/o8cqGDhm3T8Z1yLmOkaNG5ZjTzkuSfOusz+b6H16e1/7tjGy6+fj1vjhel9tuvDa777PvBv8COZFx25wr6pBz+2TcPhnD2tb7doxSyl+UUl65+vs9SinHlVIObH9p3ffIY0vz/k9dlKMP/u9JktGjRuTL//zO3HjpSbnuohPzmmm7JEm+c+b78vJdJiRJrrvoxHzsqAOSJJ/4hzfmsLfum/+2zy754f85Nt887cj86tsfz1dnvbs3d+hFSMbtk3Edcq5j+133yBNLHk2SPLbowXzx+MOSJCuWP5WLvvDPOePDR+Tifzk5/3bS+7Jw/h1rfu5HF52bM084MmfPfF+WPr4k9955S+6Y8/NcdcHZOfOEI7P4oft7cXdelGTcLueKOuTcPhm3T8aDVylD86tX1llClFI+meSMJP9WSvlskrOSjEvy0VLKzArr67oF9y/OsGElW26+SY4++DVJkle+4zN598fOz7mnzMjoUSMye+7d2W/qztlk4zHp7x/IvlMmJ0mm7zU5s+fOT5JM2W27nHDaZZl60KzsuN34TN9rp57dpxcbGbdPxnXIuV0DA/2555a5edm06Wtd94sfXp6x4zbJBz//lbz2oBl54J4711y3YvlT2X6XPXLMaedlh5dNyY0/viKTdnt5dp82PQfMODrHnHZetth625p35UVLxnU4V9Qh5/bJuH0yhvXvhHhbkv2SvCbJ+5P8r6ZpTkny10kO7vRDpZSjSilzSilz+h69tWuL7ZanW5/pe03ON79/Q5LkrgUP574Hl2SXSVtm9tz5efXekzN96k658ppbM26jURk7ZmQmTdg8v7l3UZJkzq335v5Fj6dpmtx058JMnLBFr+7Oi5KM2yfjOuTcfStXrMiZJxyZWUe8OX9Y+mR23nPaWsfce8fN2XP6/kmSrSbulK0mTV5z3fARI7P7PvsmSSbstGsee+ShOgsfRGRcn3NFHXJun4zbJ2M2dOubCdHXNE1/kj+UUuY3TfNEkjRNs6yUMtDph5qmOSfJOUkyduoHXlRTV3bYdov09zdZtOTJjltQ5tx6b/beY2L+8/7F+fH1d2T8SzbOEW/dL/Nu/+2aY5av6Fvz/UD/QEYM90EjT5Nx+2Rch5zb8fS8gqf+sDRfP/Vjuf6qyzP9wIOedcy6/uEYPnz4mo/KGjZsWAb6+1tc7eAk47qcK+qQc/tk3D4Zw/p3QqwopWy0+vt9nr6wlPJnSTqWEC9W4zcblzNnHpKzL/lpkuTaufNzyIGrfju088Qts/02m+euBYuysq8/Cx9+PAe9fmpuuPk/M3ve/HzoXa9bs/2JzmTcPhnXIef2jdloXN50+Adz7fcuSX9f37Ou22H3V+Tm665OkixauCAP33fPem9v9NiNsnzZslbWOljJuH3OFXXIuX0ybp+MB69SypD86pX17YR4TdM0y5OkaZpnlg4jkwyKCShjR4/M9Rd/dM3H4lx0xY354oU/SZJ8+dKf5cyZh+TGS09KX39/3vuJC7Ji5aonabPn3Z3X/sVuWfbUysyeNz/bbb1ZZs+7u5d35UVLxu2TcR1yrm/Cjrtk60mT8+uf/yQ77P6KNZf/5V+9Jd/618/mjA8fkQk77JKtJ07OmI3GrfO29py+f77z5c/nuisvy98dd7KZBavJuPucK+qQc/tk3D4Zw9pK259R+2J7OwbAhuyC8wfHTOGBgf709/Vl5KjRWfzQ/fnKp47LP37xwowYMbLXSxsyBnPGMw6b1eslAPAMy+ad1cPPWmjffzv92iH5mvaa41/dk7+39e2EAIDqVi5fnnNP/lAG+vvTNE3e/J7jBsWL48FExgBALyghAHjRGT12o7z/1HN6vYwhTcYAQC8oIQAAAKCDXg5xHIp8lgsAAABQhRICAAAAqEIJAQAAAFRhJgQAAAB0YCREd9kJAQAAAFShhAAAAACqUEIAAAAAVZgJAQAAAB0UQyG6yk4IAAAAoAolBAAAAFCFEgIAAACowkwIAAAA6MBIiO6yEwIAAACoQgkBAAAAVKGEAAAAAKpQQgAAAABVGEwJAAAAHRSTKbvKTggAAACgCiUEAAAAUIUSAgAAAKjCTAgAAADowEiI7rITAgAAAKhCCQEAAABUoYQAAAAAqjATAgAAADoYZihEV9kJAQAAAFShhAAAAACqUEIAAAAAVZgJAQAAAB0YCdFddkIAAAAAVSghAAAAgCqUEAAAAEAVSggAAACgCoMpAQAAoINiMmVX2QkBAAAAVKGEAAAAAKpQQgAAAABVmAkBAAAAHQwzEqKr7IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADkoxFKKb7IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADoyE6C4lxBBwwfkze70EAKjGv3vACzXjsFm9XgLwHN6OAQAAAFShhAAAAACqUEIAAAAAVZgJAQAAAB2UmEzZTXZCAAAAAFUoIQAAAIAqlBAAAABAFWZCAAAAQAfDjIToKjshAAAAgCqUEAAAAEAVSggAAACgCjMhAAAAoINSDIXoJjshAAAAgCqUEAAAAEAVSggAAACgCjMhAAAAoAMjIbrLTggAAACgCiUEAAAAUIUSAgAAAKhCCQEAAABUYTAlAAAAdDDMZMqushMCAAAAqEIJAQAAAFShhAAAAACqMBMCAAAAOjASorvshAAAAACqUEIAAAAAVSghAAAAgCrMhAAAAIAOiqEQXWUnBAAAAFCFEgIAAACoQgkBAAAAVGEmBAAAAHRgJER32QkBAAAAVKGEAAAAAKpQQgAAAABVKCEAAACAKgymBAAAgA6GmUzZVXZCAAAAAFUoIQAAAIAqlBAAAABAFWZCAAAAQAcmQnSXnRAAAABAFUoIAAAAoAolBAAAAFCFmRAAAADQQSmmQnSTnRAAAABAFUoIAAAAoAolBAAAAFDFkC8hls45I9df/NH88lsz84tLPpoPvnN/7+lpwccP3j9nnnBkvnj8Yfn6qR/Lst8/mSR5Ysmj+ebpn1jvz58844Dnvfy2G67JooULurnUQUvG7ZNxHXJun4zbJ+M65Nw+GbfLa5GhYVgZml89y7N3f3Qdy5avzKsOOTX7vG1W3nT0WfnrV++RmX//hl4va8gZOWpUjjntvBx7+vnZaNymuf6HlydJNt18fA49/pQ/+XZvu/Fa/4CtJuP2ybgOObdPxu2TcR1ybp+M2+W1CKxtg/p0jEceW5r3f+qiXHvhR/Lps3+Q0aNG5IyTDsnee0xMX39/Tjz92/nZnN/kO2e+L/90xr/nlt88kOsuOjHfvfqmfPacq/KJf3hj7ntwSebf92g+fvSBWfz40uwxeZvMu/23OXzm13p99140tt91jzx03z1JkscWPZivf+5jOfb087Ni+VO57F9PzSMP3Jctt52Uxx55KH9z5LHZbvLuSZIfXXRu7px7XUaOGpV3njArix9+IHfM+XkW3HZTrr7sghx6/CnZYutte3nXXjRk3D4Z1yHn9sm4fTKuQ87tk3G7vBaBVf7onRCllK+3sZBaFty/OMOGlWy5+SY5+uDXJEle+Y7P5N0fOz/nnjIjo0eNyOy5d2e/qTtnk43HpL9/IPtOmZwkmb7X5MyeOz9JMmW37XLCaZdl6kGzsuN24zN9r516dp9eTAYG+nPPLXPzsmnT17ruFz+8PGPHbZIPfv4ree1BM/LAPXeuuW7F8qey/S575JjTzssOL5uSG398RSbt9vLsPm16DphxdI457Tz/eK0m4/bJuA45t0/G7ZNxHXJun4zr8FoE1rMTopTy3edelOS1pZSXJEnTNG9ua2FtevptWNP3mpwvXfzTJMldCx7OfQ8uyS6TtszsufPzD3/337PggUdz5TW35nWv2i1jx4zMpAmb5zf3LsrW4/8sc269N/cvejxJctOdCzNxwhb5+a/u6dVd6rmVK1bkzBOOzOOPPJQJO+2WnfecttYx995xc6Yf+LYkyVYTd8pWkyavuW74iJHZfZ99kyQTdto1d/96Tp2FDyIybp+M65Bz+2TcPhnXIef2ybg+r0UGH3M8umt9OyG2S/JEki8kOX3115PP+P55lVKOKqXMKaXM6Xv01m6ttSt22HaL9Pc3WbTkyXR6LM259d7svcfE7Dd151w79+7cdMfCHPHW/TLv9t+uOWb5ir413w/0D2TE8CE/XmOdnn4/4QlfuiT9fStz/VWXr3VMs46fHz58+Jr/cw8bNiwD/f0trXTwknH7ZFyHnNsn4/bJuA45t0/GdXktAusvIaYl+WWSmUl+1zTN/02yrGmanzZN89NOP9Q0zTlN00xrmmbaiPF/3r3V/heN32xczpx5SM6+ZNXSr507P4ccuKrt3Xniltl+m81z14JFWdnXn4UPP56DXj81N9z8n5k9b34+9K7Xrdn+RGdjNhqXNx3+wVz7vUvS39f3rOt22P0Vufm6q5MkixYuyMP3rb+tHT12oyxftqyVtQ5WMm6fjOuQc/tk3D4Z1yHn9sm4fV6LwCrrLCGaphlomuZfkhyeZGYp5awMsmGWY0ePXPOxON8/+wP58XV3ZNaXr0ySfPnSn2X4sGG58dKTcsHnDs97P3FBVqxcddKdPe/uLFryZJY9tTKz583Pdltvltnz7u7lXRk0Juy4S7aeNDm//vlPnnX5X/7VW/L7Jx7PGR8+Ij+7/KJsPXFyxmw0bp23tef0/XPNdy/OWR95TxY/dH+byx5UZNw+Gdch5/bJuH0yrkPO7ZNx93ktAmsrTbOuDVbPObiUNybZr2mak17oz4yd+oEX/gfwJ7ng/Jm9XsILMjDQn/6+vowcNTqLH7o/X/nUcfnHL16YESNG9nppQ4aM2yfjOuTcPhm3T8Z1yLl9gznjGYfN6vUSNgjL5p01pIcmvPPCm4bka9oL3zmlJ39vf9SuhqZpvp/k+y2thSHu/2fvzuPsrOuz8V/fyUZiQFnKTgIEEFMFAnEh+FOLVRGt1kIL9QEKohRFwEpRMBR/orFYpH1YtIgglFARBQUqiraWFghrSIwsghAMGJIQJKwaskzu54+ECMaTCJ77O5nJ++1rXk7OlvtcOdzJXPM5n1myaFHO+8zHsqy3N03T5D0f/Hi/+MurP5Fx+2Rch5zbJ+P2ybgOObdPxqzr7KXsrhc1CfFSmIRoX3+ZhAAAgJpMQtQx0CchDv73gTkJMfn/9M0khDWqAAAAQBVKCAAAAKCKfvWTLgAAAKCmYilEV5mEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgA56rIToKpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0EEplkJ0k0kIAAAAoAolBAAAAFCFEgIAAACoQgkBAAAAVGExJQAAAHRgLWV3mYQAAAAAqlBCAAAAAFUoIQAAAIAq7IQAAACADnqKrRDdZBICAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOrASortMQgAAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAHxVKIrjIJAQAAAFShhAAAAACqUEIAAAAAVSghAAAAgCospgQAAIAO7KXsLpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0EGPpRBdZRICAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOrASortMQgAAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAHxVKIrjIJAQAAALxAKeVrpZT5pZQ7O1z/llLKk6WUH6/4OPn3eVyTEAAAAMBvuzDJ2UkuWs1trm+a5t0v5kFNQgAAAAAv0DTNdUkWdPtxTUIMAAcfOqmvD2HA2/WAv+zrQ4CumHHpt/r6EAa8yRdO7OtDGPC++P2f9fUhrBOcL9rnfAH0pVLKEUmOeN5F5zZNc+6LfJg9SykzksxJ8vdN09y1pjsoIQAAAKCDgfr2gRWFw4stHZ5vWpLRTdM8U0rZN8kVSXZc050Gap4AAABAS5qmeappmmdWfP69JENKKZus6X5KCAAAAOBFKaVsXlb8/NJSyuuyvF94bE3383YMAAAA4AVKKZckeUuSTUops5N8OsmQJGma5pwk+yf5cCllaZKFSQ5smqZZ0+MqIQAAAKCDFd/sX+c0TfPXa7j+7Cz/EZ4virdjAAAAAFUoIQAAAIAqlBAAAABAFXZCAAAAQAc96+ZKiNaYhAAAAACqUEIAAAAAVSghAAAAgCrshAAAAIAO7IToLpMQAAAAQBVKCAAAAKAKJQQAAABQhRICAAAAqMJiSgAAAOigFJspu8kkBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHTQYyVEV5mEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgA6KnRBdZRICAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOuixFKKrTEIAAAAAVSghAAAAgCqUEAAAAEAVSggAAACgCospAQAAoAPfue8ueQIAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAHpfT1EQwsJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACggx5LIbrKJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0YCVEd5mEAAAAAKpQQgAAAABVDPgS4pmpZ+bmb5yQ2y+bmFsuPSHHHLR3inmarnsu51suPSE3fv2TecOu2yVJRm2xUaZ+61Mv6THvufoz2fgVL+vmYfZrUz7xplx02B6Z/IE98m+H7p7XbLVBkmSLlw/Lvx8+/iU95nc+/Pq8fLh3ZT1Hxu1zrqjjpAP2zlnHH56zjj88Z3/yQ3nw3juTJI/Pn5szjjv0JT3maUcdkF899UQXj7J/c75on/NFHc4X7fK1CKxqwP9Nt3DRkrzhwFOTJH+04chc+I+HZoOR6+Vz53yvj49sYHl+zn+656tyytHvyds/eEYfH9XAsmjpshxywe1Jktdvt2E+/Obt8pGvz+jjoxpYZNw+54o6hgwdmqNPOz9Jct+Pb80Pv/7VfOgzcu4m54v2OV/U4XzRLl+LwKoGfAnxfI8+/kyO+uwlueHiT+Rz53wvw4YOzpmfOjC7jx2Vpb29+eTp3851U+/Ld876cP7hzCtz531zctMln8xV187IP557TU7+yLvy0NwFmfnQL3PSkfvmsSeeydgxW2T6T3+Rwyb+W18/vbXGBi9bL0889etVLu+Ud09PyaRj/zx/uuer0jRNLvjOjfnXb/zvyvutN2xILj39Q7niRz/OBd+5seZTWWu9bOigPP3s0lUuHzqo5BPv2Ck7bz4yvU2TM370QKY99ER6SnLUW7bP67fbMEly5Yy5+dbtc1beb9jgnpz6F3+c/7n30Vw5Y16157E2k3H7nCvqeHbhrzP8ZSNXuXzJ4kW56rx/ycMz703PoEHZ95Cjsv2rx2XZst784OKv5L4ZtyWl5LVvfXf2fOdfvOB+/37aSfnj1785r/3Td9d8Kmst54v2OV/U4XzRLl+L9F89hle66kWVEKWUNyZ5XZI7m6b5YTuH1K5ZDz+Wnp6STTdaP3/9rtcmSV77V5/PTttulu9++ai85s9PyZRp92evcTvkwTkL0tu7LHvuOiZJMmG3Mbnk6tuy+SYvz66v3Dp77D8pcx59Mtde+PFM2G373PjjB/ryqfWp4cOG5OZvnJD1hg7O5pu8PO/82zNXuc2RB7wpyap5H/LeN2TbrTbOG/761PT2LsuGG4xYeZ+XDR+Wi049LP/+3Vvz9e/eWu35rI2GDe7JRYftkaGDe7LJy4bmqEtW/Y7b/ntslSQ56Gu3Z/RGw3PGAbvkr869Ne/eZfNs+Yr18jcX3J7eJtlgvd/8pz9i6KB87r1j8707H8n373yk2vNZG8m4fc4VdSxZvDhnHX94li5ZnKcfX5DDP/3Pq9zmlh9ckSQ55vQL8ujDD+aCzx2fvztjcqb9zzV5fP68HPVPX82gQYPz62eeWnmfxc8uzKVnnJJxb3pHxr35HdWez9rI+aJ9zhd1OF/U5WsRWMNOiFLKrc/7/ENJzk6yfpJPl1JOaPnYWvPc27Am7DYmX796+VP82axH8tDcBdlx9KaZMm1m3rj7mEwYt32+f/1dGTliaIavNySjt9wo9z04P0ky9a4H8/D8J9I0TWbcOzujtty4r57OWuG5UbPd/uJzee9Hv5zzPnvIKrfplPfer985X/3WDentXZYkefx53+n41v89IpOvvNk/EvKb0d8Dv3pbPvbNO/Lpd++8ym122frl+f5dy//R+uCChZn31KKM2mhEXrvthvnO9LnpbZbf7qnnfcfun/Z7db77k3nr/D92ExnX4FxRx3Pj1X/3fyfn0In/lMvO/sc0TfOC28y6547s9qa3J0n+aKvRecUfbZbH5s7OzJ/cnte9/T0ZNGj5F8YjRm6w8j4Xn3ZSdn/LO31BEeeLGpwv6nC+qM/XIqzr1rSYcsjzPj8iyduapvlMkrcn+T+d7lRKOaKUMrWUMnXpL+/qwmF2z7ZbbZze3ibzFzzd8ee9Tr3rwew+dlT2GrdDbph2f2bcMzsfeN9emf7TX6y8zaLFv/kHw7LeZRk8aMDv+Py93fKTn2fjV7wsf7ThC8f5OuVdkjRpfud1N/34gbx9r7FdPsL+7845T+UVI4ZkwxFDXnB5p0mxkqzyD4rn/GT2k9lz+426e4ADgIzb51xRx6id/ji/evrJVZfEdXi9dso4SUa98tX52fRbOr7W11XOF+1zvqjD+aJ9vhaBNZcQPaWUDUspGycpTdM8miRN0/wqyapvflyhaZpzm6YZ3zTN+MGb/HEXD/cPs8mGI3PWxANzzqXL3xN4w7SZOXDf5Rusdxi1abbZYqP8bNb8LFnam9mPPJH93jYut97x80yZPjMfO+StmTJtZl8efr+x07abZVBPTx578lcvuLxT3v918z350P5vzKAVJ8/nj0x+9l+vzoInf5UzPnVAvSfQD4zeaHh6SsmTC5e84PIf/+LJvGPspkmSbTYcns02GJYHF/w6t/z88bxv3JYZtOIvu+eP/p57/aw8+eySfOLtO1Y7/v5Axu1zrqjj0YcfTLOsNyPW3+AFl287dtfMuP6/kiS/nPOL2Pj5FwAAIABJREFUPPnL+dlky22ywy7jc+t/XpXe3uV/zT9/vPpP/+qwjFj/5bnqvH+p9wT6AeeL9jlf1OF80S5fi/RfPaUMyI++sqadEC9PcntWFMqllM2bpplXShmZzgX/WuW59xMOGTwoS3t7c8l3b8sZF/93kuQr37wuZ008MLd981NZ2tubD508OYuXLD+JTpl+f/7kda/MwmeXZMr0mdl68w0zZfr9fflU1mrP5Zws/67Eh06enGXLXth8d8r7gu/cmB1Hb5rbvnliliztzQXfvjHnXHrdyvv9/WmX5yv//0GZdOx7M/GMK6s+r7XJc+8/TpZnfMrV9+S3Is7l0x7OJ/fZKRd/YI/0Nk0+e/W9WdLb5KoZczNqoxG5+PDxWbqsyZU/npvLpv1mCdq//NfMnLTvK/PRt2yfs/9n3X0/oYzb51xRx3Pv8X7OfkedmJ6eQS+4zevf/t5c+dV/zpnHHZaeQYOy30dOyOAhQzP+re/KY3Nn56y/PzyDBg/O+Le+K3vu85tFc+869KP59r9+IddcfE72OejIas9pbeN80T7nizqcL9rlaxFYVXkpI1KllBFJNmua5udruu3wcR81g0W/t+sBf9nXhwBdMePSb/X1IQx4ky+c2NeHMOB98fs/6+tDWCc4X7TP+aJ9Bx86qa8PYZ2wcPrZ/eIb1C/VKf95/4D8mvbkt+3QJ39uL+lHdDZN8+skaywgAAAAAJ7zkkoIAAAAWBf04fqEAckaVQAAAKAKJQQAAABQhRICAAAAqMJOCAAAAOigx06IrjIJAQAAAFShhAAAAACqUEIAAAAAVSghAAAAgCospgQAAIAOSmym7CaTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANBBj5UQXWUSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADqwE6K7TEIAAAAAVSghAAAAgCqUEAAAAEAVdkIAAABAB6VYCtFNJiEAAACAKpQQAAAAQBVKCAAAAKAKJQQAAABQhcWUAAAA0EGPvZRdZRICAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOih2QnSVSQgAAACgCiUEAAAAUIUSAgAAAKjCTggAAADooMdSiK4yCQEAAABUoYQAAAAAqlBCAAAAAFXYCQEAAAAd9FgJ0VUmIQAAAIAqlBAAAABAFUoIAAAAoAolBAAAAFCFxZQAAADQQbGYsqtMQgAAAABVKCEAAACAKpQQAAAAQBV2QgAAAEAHPbEUoptK0zSt/gaXzZjb7m8AAKxTDj50Ul8fAgDPs3D62QP6q/QvTZk1IL+mPWqvbfvkz83bMQAAAIAqlBAAAABAFXZCAAAAQAdlQL/ZpD6TEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANBBj50QXWUSAgAAAKhCCQEAAABUoYQAAAAAqlBCAAAAAFVYTAkAAAAd9BSbKbvJJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0YCVEd5mEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgA56LIXoKpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0IGVEN1lEgIAAACoQgkBAAAAVKGEAAAAAKpQQgAAAABVWEwJAAAAHfjOfXfJEwAAAKhCCQEAAABUoYQAAAAAqrATAgAAADoopfT1IQwoJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACgAxshusskBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHTQU2yF6CaTEAAAAEAVSggAAACgCiUEAAAAUIUSAgAAAKjCYkoAAADowFrK7jIJAQAAAFShhAAAAACqUEIAAAAAVdgJAQAAAB0USyG6ap0oIU46YO9sNmq7LFvWmw3/aIv85dGfyvCXrZ+nFvwy373gzLz/uFNWe//PHLxPPj35mlUuv/vW67PJlttk0623benI+w8Zt0/G7ZNxHXJun4zb9czUM3Pn/XMyZPCgLO3tzb//x60569+vTdM0fX1oA4qc2yfj9skYVrVOvB1jyNChOfq083Ps6RdmxMgNcvMPrkiSbLDRJmv8h9jq3H3bDZk/e1aXjrJ/k3H7ZNw+Gdch5/bJuF0LFy3JGw48NXvsPynvPvLsvOONYzPxb9/Z14c14Mi5fTJun4xhVaudhCilvD7JT5umeaqUMjzJCUl2T3J3ks83TfNkhWPsqm12Gpt5Dz2QJHl8/txc9IUTc+zpF2bxomdz+ZdOzaNzHsqmW43O44/Oy58dfmy2HrNzkuSHl5yXe6fdlCFDh+ag4yflsUfm5J6pN2bW3TNy7eWT8/7jTsnGm2/Vl09trSHj9sm4fTKuQ87tk3G7Hn38mRz12Utyw8WfyOfO+V6GDR2cMz91YHYfOypLe3vzydO/neum3pfvnPXh/MOZV+bO++bkpks+mauunZF/PPeanPyRd+WhuQsy86Ff5qQj981jTzyTsWO2yPSf/iKHTfy3vn56aw05t0/G7ZMxLLemSYivJfn1is/PSPLyJF9YcdkFLR5XK5Yt680Dd07Lq8ZPWOW6W35wRYaPXD/HfPFr+ZP9Ds6cB+5ded3iRc9mmx3H5ujTzs+2r9o1t/3ouxn9yldn5/ETss/BR+bo0873D7EVZNw+GbdPxnXIuX0yrmPWw4+lp6dk043Wz5EHvClJ8tq/+nz+5sQLc94pB2fY0MGZMu3+7DVuh6z/svXS27sse+46JkkyYbcxmTJtZpJk11duneNPuzzj9puU7bbeJBN2277PntPaSM7tk3H7ZNw/lVIG5EdfWVMJ0dM0zdIVn49vmuZjTdPc0DTNZ5J0fKWXUo4opUwtpUz9z8su7trBvlRLFi/OWccfnkkfeE9+/czT2WGX8avc5sF77sguE/ZOkmw2avtsNnrMyusGDR6SnffYM0my5fY75fFH59U58H5Exu2TcftkXIec2yfj+p77t9yE3cbk61ffmiT52axH8tDcBdlx9KaZMm1m3rj7mEwYt32+f/1dGTliaIavNySjt9wo9z04P0ky9a4H8/D8J9I0TWbcOzujtty4r57OWkvO7ZNx+2TMum5NJcSdpZTDVnw+o5QyPklKKTslWdLpTk3TnNs0zfimaca/bf+DunSoL91z7409/suXpnfpktx8zRWr3GZ1q2EGDRq0sinq6enJst7elo60/5Jx+2TcPhnXIef2ybiubbfaOL29TeYveLrjBvWpdz2Y3ceOyl7jdsgN0+7PjHtm5wPv2yvTf/qLlbdZtHjpys+X9S7L4EHrxOqu35uc2yfj9skY1lxCfDDJm0spM5OMTXJTKeWBJF9dcV2/st6IkXn3Ycfkhv+4NL1Ll77gum13fk3uuOnaJMn82bPyyIr3z67OsOEjsmjhwlaOtb+Scftk3D4Z1yHn9sm4fZtsODJnTTww51z6v0mSG6bNzIH7Lp882WHUptlmi43ys1nzs2Rpb2Y/8kT2e9u43HrHzzNl+sx87JC3rhytZvXk3D4Zt0/GsNxqS4imaZ5smubQJLslOSLJG5Ls2TTNm5ummVHh+Lpuy+12zOajx+QnN/73Cy5//dvfm1899UTO/PsP5LorLsnmo8ZkvREjV/tYu0zYO9df9Y2c/YkP5rF5D7d52P2KjNsn4/bJuA45t0/G3Td82JDc/I0TcvtlE3P1OR/Nj266J5O+8v0kyVe+eV0G9fTktm9+KpO/cFg+dPLkLF6yvACaMv3+zF/wdBY+uyRTps/M1ptvmCnT7+/Lp7JWk3P7ZNw+GQ8MPQP0o6+Utn9G7WUz5vaLH4K7bFlvepcuzZChw/LYvIfztc9+PH93xsUZPHhIXx/agCHj9sm4fTKuQ87t688ZH3zopL4+BACeZ+H0s/tuy2EFl05/uF98TftiHTBuqz75c1vtj+hclyxZtCjnfeZjWdbbm6Zp8p4Pfrxf/EOsP5Fx+2TcPhnXIef2yRgA6AsmIQCAfsUkBMDaxSRE/9RXkxDWqAIAAABVeDsGAAAAdFA6/TxVXhKTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANCBjRDdZRICAAAAqEIJAQAAAFShhAAAAABeoJTytVLK/FLKnR2uL6WUM0sp95dSflJK2f33eVw7IQAAAKCDUtbZrRAXJjk7yUUdrn9nkh1XfLw+yb+u+P/VMgkBAAAAvEDTNNclWbCam7w3yUXNcjcneUUpZYs1Pa4SAgAAANYxpZQjSilTn/dxxIt8iK2S/OJ5v5694rLV8nYMAAAAWMc0TXNuknP/gIf4Xe9TadZ0JyUEAAAAdODtAx3NTrLN8369dZI5a7qTPAEAAIAX66okh6z4KRlvSPJk0zRz13QnkxAAAADAC5RSLknyliSblFJmJ/l0kiFJ0jTNOUm+l2TfJPcn+XWSw36fx1VCAAAAAC/QNM1fr+H6JslRL/ZxvR0DAAAAqMIkBAAAAHRQyu/6IRC8VCYhAAAAgCqUEAAAAEAVSggAAACgCjshAAAAoAMbIbrLJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0UCyF6CqTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANBBTyyF6CaTEAAAAEAVSggAAACgCiUEAAAAUIUSAgAAAKjCYkoAAADooNhL2VUmIQAAAIAqlBAAAABAFUoIAAAAoAo7IQAAAKCDEkshuskkBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRQrIToKpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAEC/MvnCiX19CEA/cfChk/r6EBgAemIpRDeZhAAAAACqUEIAAAAAVSghAAAAgCqUEAAAAEAVFlMCAABAB8Veyq4yCQEAAABUoYQAAAAAqlBCAAAAAFXYCQEAAAAd2AnRXSYhAAAAgCqUEAAAAEAVSggAAACgCjshAAAAoIMSSyG6ySQEAAAAUIUSAgAAAKhCCQEAAABUYScEAAAAdNBjJURXmYQAAAAAqlBCAAAAAFUoIQAAAIAqlBAAAABAFRZTAgAAQAclNlN2k0kIAAAAoAolBAAAAFCFEgIAAACowk4IAAAA6KBYCdFVJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACggxJLIbrJJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB00GMlRFeZhAAAAACqUEIAAAAAVSghAAAAgCqUEAAAAEAVFlMCAABAByU2U3aTSQgAAACgCiUEAAAAUIUSAgAAAKjCTggAAADooFgJ0VUmIQAAAIAqlBAAAABAFUoIAAAAoAo7IQAAAKADKyG6yyQEAAAAUIUSAgAAAKhCCQEAAABUsU6UECcdsHfOOv7wnHHcobno1BOz8FdPJ0meWvDLfP30k9d4/88cvM/vvPzuW6/P/Nmzunmo/ZaM2yfj9sm4Djm3T8btk3Edcm6fjNv1zNQzc/M3Tsjtl03MLZeekGMO2jul2DDQ3/SUMiA/+izPPvudKxoydGiOPu38HHv6hRkxcoPc/IMrkiQbbLRJ3n/cKS/5ce++7QYn1xVk3D4Zt0/Gdci5fTJun4zrkHP7ZNyuhYuW5A0Hnpo99p+Udx95dt7xxrGZ+Lfv7OvDgj612p+OUUo5Jsl3mqb5RaXjad02O43NvIceSJI8Pn9uLvrCiTn29AuzeNGzufxLp+bROQ9l061G5/FH5+XPDj82W4/ZOUnyw0vOy73TbsqQoUNz0PGT8tgjc3LP1Bsz6+4ZufbyyXn/cadk48236sunttaQcftk3D4Z1yHn9sm4fTKuQ87tk3G7Hn38mRz12Utyw8WfyOfO+V6GDR2cMz91YHYfOypLe3vzydO/neum3pfvnPXh/MOZV+bO++bkpks+mauunZF/PPeanPyRd+WhuQsy86Ff5qQj981jTzyTsWO2yPSf/iKHTfy3vn568Htb0yTEZ5PcUkq5vpTykVLKH9U4qLYsW9abB+6clleNn7DKdbf84IoMH7l+jvni1/In+x2cOQ/cu/K6xYuezTY7js3Rp52fbV+1a2770Xcz+pWvzs7jJ2Sfg4/M0aed78S6gozbJ+P2ybgOObdPxu2TcR1ybp+M65j18GPp6SnZdKP1c+QBb0qSvPavPp+/OfHCnHfKwRk2dHCmTLs/e43bIeu/bL309i7LnruOSZJM2G1MpkybmSTZ9ZVb5/jTLs+4/SZlu603yYTdtu+z5wQv1ppKiAeSbJ3lZcQeSe4upVxTSvmbUsr6ne5USjmilDK1lDL1Py+7uIuH+9IsWbw4Zx1/eCZ94D359TNPZ4ddxq9ymwfvuSO7TNg7SbLZqO2z2egxK68bNHhIdt5jzyTJltvvlMcfnVfnwPsRGbdPxu2TcR1ybp+M2yfjOuTcPhnX99xb8SfsNiZfv/rWJMnPZj2Sh+YuyI6jN82UaTPzxt3HZMK47fP96+/KyBFDM3y9IRm95Ua578H5SZKpdz2Yh+c/kaZpMuPe2Rm15cZ99XTWCWWAfvSVNZUQTdM0y5qm+WHTNIcn2TLJl5Psk+UFRac7nds0zfimaca/bf+Duni4L81z73U7/suXpnfpktx8zRWr3KZZzf0HDRq0coFMT09PlvX2tnSk/ZeM2yfj9sm4Djm3T8btk3Edcm6fjOvadquN09vbZP6Cp9NpL+DUux7M7mNHZa9xO+SGafdnxj2z84H37ZXpP/3NO+QXLV668vNlvcsyeNA6seqPAWJNr9YX/KfRNM2Spmmuaprmr5OMau+w2rHeiJF592HH5Ib/uDS9S5e+4Lptd35N7rjp2iTJ/Nmz8shDHTuWlYYNH5FFCxe2cqz9lYzbJ+P2ybgOObdPxu2TcR1ybp+M27fJhiNz1sQDc86l/5skuWHazBy47/LJkx1GbZptttgoP5s1P0uW9mb2I09kv7eNy613/DxTps/Mxw5568q3YkB/t6YS4oBOVzRN0y/PKltut2M2Hz0mP7nxv19w+evf/t786qkncubffyDXXXFJNh81JuuNGLnax9plwt65/qpv5OxPfDCPzXu4zcPuV2TcPhm3T8Z1yLl9Mm6fjOuQc/tk3H3Dhw1Z+SM6rz7no/nRTfdk0le+nyT5yjevy6Centz2zU9l8hcOy4dOnpzFS5YXQFOm35/5C57OwmeXZMr0mdl68w0zZfr9fflUoGtK06xuwOoPd9mMue3+Bl2ybFlvepcuzZChw/LYvIfztc9+PH93xsUZPHhIXx/agCHj9sm4fTKuQ87tk3H7ZFyHnNvXnzM++NBJfX0I64SF08/uyxUDrbv5/if6xde0L9YbdnhFn/y5rfZHdK5LlixalPM+87Es6+1N0zR5zwc/3i9OrP2JjNsn4/bJuA45t0/G7ZNxHXJun4xZ5w3oiqU+kxAAAMCAZBKijgE/CTFzgE5CjOmbSQhrVAEAAIAqlBAAAABAFXZCAAAAQAfFUoiuMgkBAAAAVKGEAAAAAKpQQgAAAABV2AkBAAAAHRQrIbrKJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0YCVEd5mEAAAAAKpQQgAAAABVKCEAAACAKpQQAAAAQBUWUwIAAEAnNlN2lUkIAAAAoAolBAAAAFCFEgIAAACowk4IAAAA6KBYCtFVJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACgg2IlRFeZhAAAAACqUEIAAAAAVSghAAAAgCrshAAAAIAOrIToLpMQAAAAQBVKCAAAAKAKJQQAAABQhRICAAAAqMJiSgAAAOjEZsquMgkBAAAAVKGEAAAAAKpQQgAAAABV2AkBAAAAHRRLIbrKJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0UKyE6CqTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANCBlRDdZRICAAAAqEIJAQAAAFTh7RgAAKzi4EMn9fUhDHiTL5zY14cAUJ1JCAAAAKAKkxAAAADQic2UXWUSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADoolkJ0lUkIAAAAoAolBAAAAFCFEgIAAACowk4IAAAA6KBYCdFVJiEAAACAKpQQAAAAQBVKCAAAAKAKOyEAAACgAyshusskBAAAAFCFEgIAAACoQgkBAAAAVKGEAAAAAKqwmBIAAAA6sZmyq0xCAAAAAFUoIQAAAIAqlBAAAABAFXZCAAAAQAfFUoiuMgkBAAAAVKGEAAAAAKpQQgAAAABV2AkBAAAAHRQrIbrKJAQAAABQhRICAAAAqEIJAQAAAFRhJwQAAAB0YCVEd5mEAAAAAKpQQgAAAACrKKXsU0q5t5RyfynlhN9x/aGllEdLKT9e8fHBNT2mt2MAAAAAL1BKGZTkS0nelmR2kttKKVc1TXP3b9300qZpPvr7Pq5JCAAAAOC3vS7J/U3TPNA0zeIk30jy3j/0QZUQAAAA0EkZoB9rtlWSXzzv17NXXPbb9iul/KSUclkpZZs1PagSAgAAANYxpZQjSilTn/dxxG/f5HfcrfmtX/9Hkm2bptklyX8l+bc1/b52QgAAAMA6pmmac5Ocu5qbzE7y/MmGrZPM+a3HeOx5v/xqki+s6fc1CQEAAAD8ttuS7FhK2a6UMjTJgUmuev4NSilbPO+X70ny0zU9qEkIAAAA6KD8ngsUBpqmaZaWUj6a5AdJBiX5WtM0d5VSTkkytWmaq5IcU0p5T5KlSRYkOXRNj6uEAAAAAFbRNM33knzvty47+Xmfn5jkxBfzmN6OAQAAAFShhAAAAACq8HYMAAAA6KCsmyshWmMSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADqwEqK7TEIAAAAAVawTJcRJB+yds44/PGccd2guOvXELPzV00mSpxb8Ml8//eQ13v8zB+/zOy+/+9brM3/2rG4ear8l4/bJuH0yrkPO7ZNx+2Tcvmemnpmbv3FCbr9sYm659IQcc9DeKVbUd53Xcru8jmFV60QJMWTo0Bx92vk59vQLM2LkBrn5B1ckSTbYaJO8/7hTXvLj3n3bDU6uK8i4fTJun4zrkHP7ZNw+Gbdv4aIlecOBp2aP/Sfl3UeenXe8cWwm/u07+/qwBhyv5XZ5HcOq1rmdENvsNDbzHnogSfL4/Lm56Asn5tjTL8ziRc/m8i+dmkfnPJRNtxqdxx+dlz87/NhsPWbnJMkPLzkv9067KUOGDs1Bx0/KY4/MyT1Tb8ysu2fk2ssn5/3HnZKNN9+qL5/aWkPG7ZNx+2Rch5zbJ+P2ybh9jz7+TI767CW54eJP5HPnfC/Dhg7OmZ86MLuPHZWlvb355OnfznVT78t3zvpw/uHMK3PnfXNy0yWfzFXXzsg/nntNTv7Iu/LQ3AWZ+dAvc9KR++axJ57J2DFbZPpPf5HDJv5bXz+9tYbXcru8jmG51U5ClFKGllIOKaX86Ypfv7+UcnYp5ahSypA6h9g9y5b15oE7p+VV4yesct0tP7giw0eun2O++LX8yX4HZ84D9668bvGiZ7PNjmNz9GnnZ9tX7ZrbfvTdjH7lq7Pz+AnZ5+Ajc/Rp5zuxriDj9sm4fTKuQ87tk3H7ZFzPrIcfS09PyaYbrZ8jD3hTkuS1f/X5/M2JF+a8Uw7OsKGDM2Xa/dlr3A5Z/2Xrpbd3WfbcdUySZMJuYzJl2swkya6v3DrHn3Z5xu03KdttvUkm7LZ9nz2ntYnXch1ex/1UGaAffWRNb8e4IMm7khxbSpmc5C+T3JLktUnOa/nYumbJ4sU56/jDM+kD78mvn3k6O+wyfpXbPHjPHdllwt5Jks1GbZ/NRo9Zed2gwUOy8x57Jkm23H6nPP7ovDoH3o/IuH0ybp+M65Bz+2TcPhn3jefeSj9htzH5+tW3Jkl+NuuRPDR3QXYcvWmmTJuZN+4+JhPGbZ/vX39XRo4YmuHrDcnoLTfKfQ/OT5JMvevBPDz/iTRNkxn3zs6oLTfuq6ezVvBars/rmHXdmkqI1zRNc0CS9yV5e5L9m6aZnOSwJOM63amUckQpZWopZep/XnZx9472JXruvW7Hf/nS9C5dkpuvuWKV2zSruf+gQYNWLpDp6enJst7elo60/5Jx+2TcPhnXIef2ybh9Mq5v2602Tm9vk/kLnk6nvX5T73owu48dlb3G7ZAbpt2fGffMzgfet1em//QXK2+zaPHSlZ8v612WwYPWiRVpHXkt1+V1DGsuIXpKKUOTrJ9kRJKXr7h8WJKOb8domubcpmnGN00z/m37H9SdI+2C9UaMzLsPOyY3/Mel6V269AXXbbvza3LHTdcmSebPnpVHVrwfbnWGDR+RRQsXtnKs/ZWM2yfj9sm4Djm3T8btk3Edm2w4MmdNPDDnXPq/SZIbps3Mgfsu/479DqM2zTZbbJSfzZqfJUt7M/uRJ7Lf28bl1jt+ninTZ+Zjh7x15Qg7nXktt8/rGJZbUwlxfpJ7kvw4ycQk3yqlfDXJbUm+0fKxtWLL7XbM5qPH5Cc3/vcLLn/929+bXz31RM78+w/kuisuyeajxmS9ESNX+1i7TNg711/1jZz9iQ/msXkPt3nY/YqM2yfj9sm4Djm3T8btk3E7hg8bsvJHG159zkfzo5vuyaSvfD9J8pVvXpdBPT257ZufyuQvHJYPnTw5i5cs/8J5yvT7M3/B01n47JJMmT4zW2++YaZMv78vn0q/4bXcfV7HA0MZoP/rszybZnUDVkkpZcskaZpmTinlFUn+NMlDTdPc+vv8BpfNmLv632AtsWxZb3qXLs2QocPy2LyH87XPfjx/d8bFGTy43+3fXGvJuH0ybp+M65Bz+2Tcvv6e8cGHTurrQxjwJl84sa8P4ffSn1/LXsd1LJx+dh+uOWzffY8s7Bdf075YO242vE/+3Nb4IzqbppnzvM+fSHJZq0fUR5YsWpTzPvOxLOvtTdM0ec8HP94vTqz9iYzbJ+P2ybgOObdPxu2TMQOF1zLQTWuchPhD9ZdJCAAAfsN3kNvXXyYh+jOv4zpMQvSqP7kxAAARQUlEQVRPa+0kBAAAAKyrOv0kE14aP8sFAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOrASortMQgAAAABVKCEAAACAKpQQAAAAQBVKCAAAAKAKiykBAACgE5spu8okBAAAAFCFEgIAAACoQgkBAAAAVGEnBAAAAHRQLIXoKpMQAAAAQBVKCAAAAKAKJQQAAABQhZ0QAAAA0EGxEqKrTEIAAAAAVSghAAAAgCqUEAAAAEAVdkIAAABAB1ZCdJdJCAAAAKAKJQQAAABQhRICAAAAqEIJAQAAAFRhMSUAAAB0YjNlV5mEAAAAAKpQQgAAAABVKCEAAACAKuyEAAAAgA6KpRBdZRICAAAAqEIJAQAAAFShhAAAAACqsBMCAAAAOihWQnSVSQgAAACgCiUEAAAAUIUSAgAAAKjCTggAAADowEqI7jIJAQAAAFShhAAAAACqUEIAAAAAVSghAAAAgCospgQAAIAOis2UXWUSAgAAAKhCCQEAAABUoYQAAAAAqrATAgAAADqyFKKblBAAAKxi8oUT+/oQ4A+26wF/2deHAPwWb8cAAAAAqlBCAAAAAFV4OwYAAAB0UKyE6CqTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANCBlRDdZRICAAAAqEIJAQAAAFShhAAAAACqUEIAAAAAVVhMCQAAAB0Umym7yiQEAAAAUIUSAgAAAKhCCQEAAABUYScEAAAAdFBiKUQ3mYQAAAAAqlBCAAAAAFUoIQAAAIAq7IQAAACATqyE6CqTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANCBlRDdZRICAAAAqEIJAQAAAFShhAAAAACqUEIAAAAAVVhMCQAAAB0Umym7yiQEAAAAUIUSAgAAAKhCCQEAAABUYScEAAAAdFBiKUQ3mYQAAAAAqlBCAAAAAFUoIQAAAIAq7IQAAACATqyE6CqTEAAAAEAVSggAAACgCiUEAAAAUIWdEAAAANCBlRDdZRICAAAAqEIJAQAAAFShhAAAAACqUEIAAAAAVVhMCQAAAB0Umym7yiQEAAAAUIUSAgAAAKhCCQEAAABUsU6UECcdsHfOOv7wnHHcobno1BOz8FdPJ0meWvDLfP30k9d4/88cvM/vvPzuW6/P/Nmzunmo/ZaM2yfj9sm4Djm3T8btk3Edcm6fjNuzwXqDc9Fhe+Siw/bI1R/dM1cd9YaVvx7c070lA5uuPyyfe++ruvZ4rKoM0P/1lXWihBgydGiOPu38HHv6hRkxcoPc/IMrkiQbbLRJ3n/cKS/5ce++7YZ1/uT6HBm3T8btk3Edcm6fjNsn4zrk3D4Zt+epZ5fmkAtuzyEX3J7v/HhOvnHb7JW/XrqsWeP9f9+eYv7Ti3LSlT/9A48W6lnjT8copYxJ8r4k2yRZmuS+JJc0TfNky8fWim12Gpt5Dz2QJHl8/txc9IUTc+zpF2bxomdz+ZdOzaNzHsqmW43O44/Oy58dfmy2HrNzkuSHl5yXe6fdlCFDh+ag4yflsUfm5J6pN2bW3TNy7eWT8/7jTsnGm2/Vl09trSHj9sm4fTKuQ87tk3H7ZFyHnNsn43r2ffVm2W/3LTNkUE/uePjJfPGH96enJNccu1cuu/3hvG67DfMv/zUzn//zsfnenfMyfvSG6elJvnDNffnIW7bLVq8Ynsk3P5QrZ8zL1q9YL59/3x/nkAtu7+unBb+X1U5ClFKOSXJOkvWSvDbJ8CwvI24qpbyl9aPrsmXLevPAndPyqvETVrnulh9ckeEj188xX/xa/mS/gzPngXtXXrd40bPZZsexOfq087Ptq3bNbT/6bka/8tXZefyE7HPwkTn6tPOdWFeQcftk3D4Z1yHn9sm4fTKuQ87tk3E9228yIm/eaZMcMXl6Drng9gzqKXnb2E2TJOuvNzj3PvJMDr9oeu6c81SSZO6Tz+aDk6fnrjlP51P77pRPfvuuHDF5eo74/7bry6cBL9maJiE+lGS3pml6Syn/nOR7TdO8pZTylSRXJhn3u+5USjkiyRFJcsRJ/5S37X9QN4/5RVuyeHHOOv7wPPHovGy5/Suzwy7jV7nNg/fckQn77p8k2WzU9tls9JiV1w0aPCQ777Fnkvy/9u4/yK66vOP4+5PdkGT5oZRSDQQbtFRlrFRMsZWZtGOqAy0DtkOnYaadVuuk09EWZFqH9o92bP9yxmmrte1MmkBpsYAN6qQORZxBK1ahAZRfRTFShPAriCAFIcnuPv3jHk2yZrOk3HOOe/J+zdzZe++e3H32kzt39z77/T6HE175k2y/45ZuCl9EzLh9Ztw+M+6GObfPjNtnxt0w5/aZcfd+ZvWxvHbl0Vz2228EYNnkEh57ehcAu6dn+dy939rv+Bu//gQA23c+y0TC83tmeX7PLLNVrFh6WOyu7136G58wSC/kWfu9RsUy4GiAqnoAWDrfP6iqjVW1pqrW9N2AgL173f7o765mZnoPN133yR845mC7siYmJkjzzFuyZAmzMzMtVbp4mXH7zLh9ZtwNc26fGbfPjLthzu0z4+4l8Kk7Hv3+fIhf/4dtXPbFBwDYNT37A8fvnhndV1Xfvz66DRNjHHApdWWhJsQmYFuSjcCXgI8AJDke+HbLtY3d8qmjOOcdf8AX/u1qZqan9/vc6tf8FHd+6bMA7NxxP481++EOZtmKKXY991wrtS5WZtw+M26fGXfDnNtnxu0z426Yc/vMuDvb7n+Kda85npesGP2t95jlk7zsmGU9VyV156BNiKr6EHABcD3w9qq6rLn/8apa20F9Y3fCyafw8h9/FXd88Yb97n/T287j2aef4sN/+E4+/8krefkrXsXyqaMO+livf/NbuHHrVXzkfe/iiUcfarPsRcWM22fG7TPjbphz+8y4fWbcDXNunxl34xuPP8vm//wmf7P+NK545xv58PrX8yNTR/RdltSZVC18epgXY8vtj7T7BcZkdnaGmelplh6xjCcefYhL/+Ji3vuhK5icnHfXiQ6RGbfPjNtnxt0w5/aZcfvMuBvm3L7FnPEH//3evks4LNx0yc8Pel/Ik9+dWRTvaQ/VsVMTvfy/LXiKzsPFnl272PT+i5idmaGqOPddFy+KF9bFxIzbZ8btM+NumHP7zLh9ZtwNc26fGUsaJ1dCSJIkSRokV0J0w5UQi1NfKyE8p4skSZIkSeqETQhJkiRJktQJZ0JIkiRJkjSPDHqzSfdcCSFJkiRJkjphE0KSJEmSJHXCJoQkSZIkSeqEMyEkSZIkSZpHcCjEOLkSQpIkSZIkdcImhCRJkiRJ6oRNCEmSJEmS1AlnQkiSJEmSNI84EmKsXAkhSZIkSZI6YRNCkiRJkiR1wiaEJEmSJEnqhDMhJEmSJEmahyMhxsuVEJIkSZIkqRM2ISRJkiRJUidsQkiSJEmSpE7YhJAkSZIkSZ1wMKUkSZIkSfNxMuVYuRJCkiRJkiR1wiaEJEmSJEnqhE0ISZIkSZLUCWdCSJIkSZI0jzgUYqxcCSFJkiRJkjphE0KSJEmSJHXCJoQkSZIkSeqEMyEkSZIkSZpHHAkxVq6EkCRJkiRJnbAJIUmSJEmSOmETQpIkSZIkdcKZEJIkSZIkzcOREOPlSghJkiRJktQJmxCSJEmSJKkTNiEkSZIkSVInbEJIkiRJkqROOJhSkiRJkqT5OJlyrFwJIUmSJEmSOmETQpIkSZIkdcImhCRJkiRJ6oQzISRJkiRJmkccCjFWroSQJEmSJEmdsAkhSZIkSZI6YRNCkiRJkiR1wiaEJEmSJEnzSIZ5eWHfe85K8rUk25NccoDPL0tydfP5m5OsXugxbUJIkiRJkqT9JJkA/hY4GzgVuCDJqXMO+x3gyar6CeCvgA8s9Lg2ISRJkiRJ0lxnANur6r6q2g1cBZw355jzgMub61uAdcnB11nYhJAkSZIkSXOdCDy4z+0dzX0HPKaqpoHvAMcd7EEnx1jgAZ1/2spFd1LVJBuqamPfdQyZGbfPjLthzu0z4/aZcTfMuX1m3L7FlvH5p63su4RDttgyPhwsn2TRvad9IZJsADbsc9fGOc+9A33fNfdhXsAx+3ElxIFtWPgQvUhm3D4z7oY5t8+M22fG3TDn9plx+8y4fWasTlTVxqpas89lbvNrB3DSPrdXAQ/Pd0ySSeAlwLcP9nVtQkiSJEmSpLm2AackOTnJEcB6YOucY7YCv9VcPx+4oaoOuhKi9e0YkiRJkiRpcamq6STvAT4NTACXVtXdSf4cuKWqtgKbgX9Osp3RCoj1Cz2uTYgDcw9W+8y4fWbcDXNunxm3z4y7Yc7tM+P2mXH7zFg/NKrqWuDaOff96T7Xnwd+7VAeMwuslJAkSZIkSRoLZ0JIkiRJkqRO2ITYR5KzknwtyfYkl/RdzxAluTTJziR39V3LUCU5Kclnk9yT5O4kF/Zd09AkWZ7kv5Lc3mT8/r5rGqokE0m+nORTfdcyVEnuT3Jnkq8kuaXveoYoyUuTbEny1ea1+ef6rmlIkry6ef5+7/J0kov6rmuIkry3+bl3V5Irkyzvu6ahSXJhk+/dPo81VG7HaCSZAO4F3sroNCPbgAuq6r97LWxgkqwFngH+qape13c9Q5RkJbCyqm5LcjRwK/B2n8vjkyTAkVX1TJKlwBeAC6vqpp5LG5wkFwNrgGOq6py+6xmiJPcDa6rqW33XMlRJLgdurKpNzXTxqap6qu+6hqj5fe4h4E1V9c2+6xmSJCcy+nl3alU9l+RjwLVV9Y/9VjYcSV4HXAWcAewGrgN+r6q+3mth0pi5EmKvM4DtVXVfVe1m9AJwXs81DU5VfZ4FzhurF6eqHqmq25rr/wvcA5zYb1XDUiPPNDeXNhc7umOWZBXwy8CmvmuR/r+SHAOsZTQ9nKrabQOiVeuAb9iAaM0ksCLJJDAFPNxzPUPzWuCmqvpuVU0D/wH8Ss81SWNnE2KvE4EH97m9A9+4aZFLshp4A3Bzv5UMT7NN4CvATuAzVWXG4/fXwPuA2b4LGbgCrk9ya5INfRczQK8EHgcua7YWbUpyZN9FDdh64Mq+ixiiqnoI+CDwAPAI8J2qur7fqgbnLmBtkuOSTAG/BJzUc03S2NmE2CsHuM+/bGrRSnIUcA1wUVU93Xc9Q1NVM1X108Aq4IxmCaXGJMk5wM6qurXvWg4DZ1bV6cDZwLubbXMan0ngdODvq+oNwLOAc6da0Gx1ORf4175rGaIkxzJaJXwycAJwZJLf6LeqYamqe4APAJ9htBXjdmC616KkFtiE2GsH+3caV+ESMy1SzZyCa4CPVtXH+65nyJpl1Z8Dzuq5lKE5Ezi3mVdwFfCWJFf0W9IwVdXDzcedwCcYbU/U+OwAduyzWmoLo6aExu9s4LaqeqzvQgbqF4H/qarHq2oP8HHgzT3XNDhVtbmqTq+qtYy2MDsPQoNjE2KvbcApSU5uOunrga091yQdsmZo4mbgnqr6y77rGaIkxyd5aXN9BaNfzL7ab1XDUlV/XFWrqmo1o9fjG6rKv7iNWZIjmwG2NFsE3sZoObDGpKoeBR5M8urmrnWAg4LbcQFuxWjTA8DPJplqftdYx2julMYoyY81H18B/Co+pzVAk30X8MOiqqaTvAf4NDABXFpVd/dc1uAkuRL4BeBHk+wA/qyqNvdb1eCcCfwmcGczswDgT6rq2h5rGpqVwOXNFPYlwMeqylNIajF6GfCJ0fsJJoF/qarr+i1pkH4f+GjzR477gHf0XM/gNPvn3wr8bt+1DFVV3ZxkC3Aboy0CXwY29lvVIF2T5DhgD/Duqnqy74KkcfMUnZIkSZIkqRNux5AkSZIkSZ2wCSFJkiRJkjphE0KSJEmSJHXCJoQkSZIkSeqETQhJkiRJktQJmxCSJEmSJKkTNiEkSZIkSVInbEJIkiRJkqRO/B85TbQQLRSMVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 515.3217391304348\n",
      "Planning size: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 456.758064516129\n",
      "Planning size: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 540.1860465116279\n"
     ]
    },
    {
     "data": {
      "image/png": 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GCX9nex3PdanLsm2/0W7YHMYv3W69DmM84s/lqUUicmnQkxiTDhHhjmaXMKV/K2qVK8KjXyVw53tLbISVMR7wp2hcCSwUkSQRSRCRVSKSEOxgxpzrkpIFGXdfM57rUpcV2w/Sdugc3p+3hdNnrNdhTHbxZ/TUJWm1q+q2oCQKMLunkTPtPHicx79ZxawNyTS+uBgvda1PbBmbdt2YQMjqGuHb3AJxHOcJ8bObMZ65qFh+3r/7Uobd0pAt+37nujfmMfwHW2bWmGDLtGiISCcR2QRsAWYDW4EpQc5lTKZEhC6NyjNjYBva1S3LqzM20unNeSTsOJj5h40xF8SfexrP4iy8tFFVK+Ms/To/qKmMOQ+lCkUx/FZnAsTfjqXQZcR8Xpi8jhOngjXbjTG5lz9F45Sq7gfyiEgeVZ2FM/+UMSHl2tplmP5wG265tCJvz9lMq5dn8fLU9ZxMteJhTKD4UzQOikghYA4wVkRex5kXypiQUzR/Xl64qT6f3deMRhWL8dZPSXR+cz4b9xzxOpoxOYI/RaMzcAx4GJgKJAE3BDOUMVnVvGpJRveM4/2749h39CQ3DJ/H27OTbH1yY7LIn6JxC1BVVVNV9UNVfcO9XGVMyLuqZhmm9G9N6+oxvDBlPde9MZclWw54HcuYsOVP0agEvC0im0VkvIj0ExG7p2HCRkzhKN7pGcc7PeP4/eRpbn57IY98sZLDJ055Hc2YsJPpw31/HCiSH7gPGASUV9WIYAYLFHu4z/g6lpLKGz8k8s7czZQtEs3QWxrStHIJr2MZE1Ky9HCfiDwhIlOA6UA1nKJRIbARjckeBfJF8liHmoy/vzkReYQeoxcyZNp6u9dhjJ/8uTx1E1ASmAl8DUxU1V1BTWVMkDW5pDiT+7eia+MKjJiVRNeRC9icfNTrWMaEPH+mEWmM80DfEuBaYJWIzAt2MGOCrVBUJEO6N2Dk7Y355cAxrnvDGWFlU5EYkz5/Lk/VBe4A7sIZSbUD+DHIuYzJNh3qlWNq/9ZcXq3kHyOslm37zetYxoQkfy5PvQQUAd4Aaqnqlar6ZHBjGZO9yhaN5t27LuW9u+I4lnKabqMW8OyktRxPsafJjfEVmdkBqnqdO3LqYlW1MYomR7u6VhmaVi7BS1PX8968Lfy4fi/DbmlIg4rFvI5mTEjw5/LUDcAKnKfBEZGGIjIxK18qIt1FZI2InBGROJ/2SiJyXERWuNson31N3AWgEkXkDXf9cmMCrnB0Xp7rUo9P77uME6dO03XkAkbMSrTFnozBv8tTTwNNgYMAqroC54G/rFiNMyprThr7klS1obs94NM+EugFxLpb+yxmMCZDLaqWYmr/1rSrW5Yh0zbQY/RC1uw85HUsYzzlT9FIVdWA/k1R1XWqusHf40WkHFBEVReq8zTiR0CXQGYyJi1FC+TlzVsb8drNDdiw+wjXvTGPPp8uZ9/Rk15HM8YT/hSN1SJyGxAhIrEiMhxYEMRMlUXkZxGZLSKt3LbyOKO2ztrhtqVJRHqJSLyIxCcnJwcxqskNRISbGldg7r+v4qGrqjFj7R7aD5vDrPV7vY5mTLbzp2j0A+oAJ4FPgcPAgMw+JCIzRWR1GlvnDD62C+eGeyNgIPCpiBQB0rp/ke4FZlUdrapxqhoXExOTWVRj/FI0f14Gtq3BxL6XU6pQFPeMWcqTE1bbYk8mV/Fn9NQx4HF3A0BELgG2ZfK5a843jKqexClOqOoyEUkCquP0LHynLqkA7Dzfn29MINQsW4Rv+1zOkGkbeG/eFhYm7WdYj4bUuaio19GMCboMexoi0lxEuolIafd9fRH5FAjKE+EiEiMiEe7rKjg3vDe705YcEZFm7qipnsCEYGQwxh/ReSP4z/W1+egfTTl0/BRdRsxn9JwkUm0OK5PDpVs0RGQI8D7QFfheRJ4CZgCLcf5nfsFE5EYR2QE0d3/2NHdXayBBRFYCXwIPqOrZxQ8eBN4FEnEWgpqSlQzGBELr6jFMHdCaq2qW5n+T19N26BwWJtlyMybnSndqdBFZCzRW1RMiUhznclB9Vd2UnQGzyqZGN9lBVZmxdg/PT17Htv3HuKPZxTzWoRaFojK9AmxMyLnQqdGPq+oJAFX9DdgQbgXDmOwiIrStU5ap/Vvzz5aVGbv4F659bTaTV+3C3zVrjAkHGfU0DvLXh+9a+75X1U7BjRYY1tMwXlj+y2888c1q1u46zNU1S/NC13qULhztdSxj/JJRTyOjotEmox+qqrMDkC3orGgYr6SePsOYBVsZMm0DBfJF8L8b69GhXjmvYxmTqQsqGjmFFQ3jtcS9R3j485Ws+vUQNzS4iP92qkOJgvm8jmVMurK03KsxJmuqlS7M171bMPDa6kxdvYu2Q2czdbUtfmnCkxUNY7JB3og8PHR1LBP7tqRs0Wge+GQ5fT9dzoHfU7yOZsx58btoiEjBYAYxJjeoVa4I3/S+nEFtqzNtzW6ufW02U1ZZr8OED3/W02jhPrOxzn3fQETeCnoyY3KovBF56HtVLN/1a0m5YtE8OHY5fT5dzn6bOdeEAX96GkOBdsB+AFVdiTP81hiTBTXLOr2OR9rVYPqa3bQdOofJ1uswIc6vy1Oquv2cJpvW05gAyBuRhz5XVmNSv1aUL56f3mOX02es9TpM6PKnaGwXkRaAikg+ERmEe6nKGBMYNcoW5usHW/BIuxrMWLuHdrZehwlR/hSNB4A+/LkQUkP3vTEmgCLdXsd3/Vr+sV7HU7Zehwkx/symJqp6e9CTGGMAp9fhu17HnE37qFSyAA9eUY2mlUt4Hc/kcv70NBaIyHQRuVdEigU9kTHmL+t1FI6OZM3Ow9wyeiHPTVpr65MbT/k1jYiINAV6AF2AtcA4Vf0kyNkCwqYRMTnB7ydTee77dYxb+guF8kXy3851uLFReZw1yYwJrCxPI6KqS1R1INAUOAB8GMB8xphMFIyK5IWb6jHj4TbULFeYgeNX0ufT5ew6dNzraCaX8efhviIicpeITAEWALtwiocxJptVK12Icb2a8+/2NZmxdg8tXvyRR75YaZesTLbJ9PKUiGwBvgXGq+rCbEkVQHZ5yuRUv+w/xkcLtzJmwVYK5IvgkfY1ub3pxeTJY5esTNZkaWp0EREN4/nTrWiYnC5x7xGenLCGBUn7aV6lJEO616dC8QJexzJh7EIXYRqmqgNE5DvgbwfZyn3GhA5VZdzS7Tw3aS0iwlM31KZbkwp2o9xckIyKRkbPaXzs/vlKEAINAW4AUoAk4B5VPejuGwzcizNVyUOqOs1tbw+8DkQA76rqi4HOZUy4EhFubXoxLauV4l/jV/LIlwlMW7OHF26qR0zhKK/jmRwk3RvhqrrMfdlQVWf7bjhPhWfFDKCuqtYHNgKDAUSkNs7Q3jpAe+AtEYkQkQhgBNABqA3c6h5rjPFRsUQBPuvVjMc71mLOpmTaDZtjCz6ZgPJnyO1dabTdnZUvVdXpqprqvl0EVHBfd8Z5BuSkqm4BEnFGajUFElV1s6qmAOPcY40x54jII9zXugqT+rXkomLOgk8DP1/BoeOnvI5mcoB0i4aI3Orez6gsIhN9tlm406QHyD+AKe7r8oDvjLo73Lb02tPL3ktE4kUkPjk5OYBRjQkf1csU5pvel/PQ1bFMWLmT9sPmMHeT/X0wWZPRPY2zz2SUAl71aT8CJGT2g0VkJlA2jV2Pq+oE95jHgVRg7NmPpXG8knZxS3dEl6qOBkaDcyM8s6zG5FR5I/Iw8NrqXF2zNAPHr+DO95bQs/klPNahJgXy+TP1nDF/le5vjapuA7YBzS/kB6vqNRntF5G7gOuBq32G9O4AKvocVgHY6b5Or90Yk4kGFYvx/UOteHnqBt6fv4W5m/bx6s0NaHxxca+jmTDjzxPhzURkqYgcFZEUETktIoez8qXuSKh/A51U9ZjProlADxGJEpHKQCywBFgKxIpIZRHJh3OzfGJWMhiT20TnjeDJG2rz6X2XkZJ6hm4jFzBk2npSUs94Hc2EEX9uhL8J3ApsAvID/wSGZ/F73wQKAzNEZIWIjAJQ1TXAeJxJEacCfVT1tHvTvC8wDWcBqPHuscaY89SiaimmDmhF18YVGDEriU5vzuPr5Ts4fcau5JrM+fNEeLyqxolIgjtEFhFZoKotsiVhFtnDfcakb8baPTz3/Vq27T9Gk0uKM6RbfarEFPI6lvFYVme5PeZeElohIi+LyMNAwYAmNMZ44traZfhp0BW8dnMDNu05QofX5/LOnM3W6zDp8qdo3InzFHZf4HecG9JdgxnKGJN9RISbGldg5sA2tIotxfOT19Ft1AIS9x7xOpoJQX4twhTO7PKUMf5TVSas2MlTE9dwLCWV+1pVod9VseTPF+F1NJONLmjuKRFZRcbPQtQPQDZjTAgREbo0Kk/L2FL8b/I63vopiYkrd/JM5zpcVbOM1/FMCMholttLMvqg+xxHyLOehjEXbtHm/Tzx7WoS9x7lpkbleeqGOhQtkNfrWCbIsrSeRrizomFM1qSknuHNWYmMmJVIqUL5eKlrfa6oUdrrWCaIsjR6SkSOiMhhdzsRiIf7jDHhI1+kMxXJN71bUCQ6L3d/sJTHvkrgyAmbADE3yrRoqGphVS3ibtE4I6feDH40Y0woqV+hGN/1a8n9baowPn47HV6fy9KtB7yOZbKZP0Nu/0JVvwWuCkIWY0yIi84bweAOtRh/f3PyiHDz2wt5aep6Tqae9jqaySaZTnMpIjf5vM0DxJHBqCpjTM4XV6kEk/u34tnv1jLypyR+WLeHV7o3oH6FYl5HM0Hmz9zIN/i8TgW2YgsgGZPrFYqK5KVu9WlftyyDv15FlxHz6dKwPJ0bladN9Riv45kgsdFTxpgsO3T8FC9OWc+U1bs4eOwUN8dV4D/X16ZwtA3PDUdZGnLrTlHeD6iET89EVTsFMGPQWNEwJvukpJ7h9R82MvKnJMoVzc+QbvVpUa2U17HMecpq0VgJvAesAv6YeF9VZwcyZLBY0TAm+/38y2/8a/xKNu/7nTubXULvK6tSrmh+r2MZP2W1aCxW1cuCkiwbWNEwxhvHU07z0tT1fLhwK/ki8jC4Q016Nq9EnjxprepsQklWi8ZtOCvoTQdOnm1X1eWBDBksVjSM8dYv+4/x1MTVzNqQTKvYUrzSvQFlikR7HctkIKtF4wWc6dGT+PPylKpqWDyrYUXDGO+pKp8s/oXnv19LdN4Inu1cl+vrl0PEeh2hKKtFYz1QX1VTghEu2KxoGBM6kpKPMvDzFazccYhrapXm2S517V5HCMrqyn0rAXtixxiTZVVjCvHVgy144rpazEvcx7WvzeHjRdvI6UP/cxJ/ikYZYL2ITBORiWe3YAczxuRMkRF5+GerKkwf0IaGFYvxn29X848xS9l39GTmHzae8+fyVJu02m3IrTEmq1SVjxdt4/nv11E4OpIh3RpwZU2bdt1rWbo8paqz3QLxM86zGme3rAQaIiLrRSRBRL4RkWJueyUROS4iK9xtlM9nmojIKhFJFJE3xO6gGRP2RISezSvxXb+WlCoUxT1jlvLolys5dNymXQ9V/qyn0UtE9gAJQDywzP0zK2YAdd0lYzcCg332JalqQ3d7wKd9JNALZ/hvLNA+ixmMMSGiepnCTOh7OX2urMpXy3+l3dA5zNqw1+tYJg3+3NN4BKijqpVUtYqqVlbVKln5UlWdrqqp7ttFQIWMjheRckARVV2ozvW0j4AuWclgjAktUZERPNKuprPYU/5I7vlgKY98Yb2OUONP0UgCjgUxwz+AKT7vK4vIzyIyW0RauW3lgR0+x+xw29Lk9o7iRSQ+OTk58ImNMUFzdrGnPldW5eufrdcRavyZGn0wsEBEFvPXJ8IfyuhDIjITKJvGrsdVdYJ7zOM4062PdfftAi5W1f0i0gT4VkTqAGndv0j3Dr6qjgZGg3MjPKOcxpjQc7bX0a5OWQZ9sZJ7PlhK9yYVeOL62hTNbzPnesmfovE28CPnTFiYGVW9JqP9InIXcD1wtXvJCVU9iVuYVHWZiCQB1XF6Fr6XsCoAO/3NYowJT2d7HW/8sIlRszczd9M+Xripno2w8pA/RSNVVQcG8ktFpD3wb6CNqh7zaY8BDqjqaWOPZggAABFjSURBVBGpgnPDe7OqHhCRIyLSDFgM9ASGBzKTMSY0/a3XMWYp3Zo463VYryP7+XNPY5Z7j6CciJQ4u2Xxe98ECgMzzhla2xpIcKdj/xJ4QFXPrlz/IPAukIhzn2UKxphcw/dexzfuvY45G+2eZXbz5+G+LWk0a1ZHUGUXe7jPmJwnYcdBBo5fSeLeo9zdohKPdahJdN4Ir2PlGBk93Jfp5SlVrRz4SMYYc+HqVyjGpH4teXHKesYs2Mr8xH0MvaUhdcsX9TpajudPT6NnWu2q+lFQEgWY9TSMydnmbkpm0BcrOfB7Cve1qsL9ratStIDd68iKrM5ye6nP1gp4GgiL9cGNMTlfq9gYpg1ozXX1yjFydhLtX5/DmPlbOJaSmvmHzXnLtKfxtw+IFAU+VtWwKBzW0zAm90jYcZDBX69izc7DXFyiAC92rUeLqqW8jhV2strTONcxnKGwxhgTUupXKMb3D7ViXK9miMBt7yzmyQmr+f2k9ToCJdMb4SLyHX8+fZ0HqA2MD2YoY4zJimZVSjK1f2uGTNvABwu2MGvDXoZ0a0CzKiW9jhb2znc9jVRgm6ruSO/4UGOXp4zJ3ZZsOcAjX65k2/5j3N2iEo+2r0GBfP4815x7XdCQWxGpBpQ5d7ElEWklIlGqmhTgnMYYE3BNK5dgSv9WvDx1A2MWbGXWhr280r0Bl1bK6jPKuVNG9zSGAUfSaD/u7jPGmLBQIF8kT3eqw2f3NeOMKje/vZBnJ63leMppr6OFnYyKRiVVTTi3UVXjgUpBS2SMMUHSvKpzr+OOyy7hvXlb6PjGXJZtO5D5B80fMioa0Rnsyx/oIMYYkx0KRkXybJe6fPrPy0hJPUO3UQv53+R1nDhlvQ5/ZFQ0lorIfec2isi9OEu+GmNM2GpRrRTTHm7NrU0vZvSczVz96mwmrPiV8312LbdJd/SUiJQBvgFS+LNIxAH5gBtVdXe2JMwiGz1ljMnMgqR9vDhlPQk7DtG2dhmev7EeMYWjvI7lmYxGT/kz5PZKoK77do2q/hjgfEFlRcMY44/TZ5T35m3mlekbKZgvgmc61+X6+uUQSWvh0JwtS0Uj3FnRMMacj8S9R/jXFwms3H6QjvXK8mznupQslLt6HYGeRsQYY3KsaqUL89UDzXm0fQ1mrt1L26FzmLxql9exQoYVDWOMOUdkRB56X1GNSQ+15KJi+ek9djl9P13Ogd9TvI7mOSsaxhiTjuplCvN17xYMaludaWt203bobKauDosxQEFjRcMYYzKQNyIPfa+KZWLflpQpEs0DnyxjwLifOXgsd/Y6rGgYY4wfapUrwrd9Lufha6ozKWEX1w6dw4y1e7yOle08Kxoi8qyIJIjIChGZLiIXue0iIm+ISKK7v7HPZ+4SkU3udpdX2Y0xuVPeiDz0vyaWCX0vp2TBfNz3UTwDx6/g0LFTXkfLNl72NIaoan1VbQhMAp502zvgLPIUC/QCRgKISAngKeAyoCnwlIgUz/bUxphcr85FRZnYtyUPXVWNCSt20nbYbGat3+t1rGzhWdFQ1cM+bwvy50JPnYGP1LEIKCYi5YB2wAxVPaCqvwEzgPbZGtoYY1z5IvMwsG0Nvu19OcXy5+OeMUt59MuVHDmRs3sdnt7TEJHnRWQ7cDt/9jTKA9t9DtvhtqXXntbP7SUi8SISn5ycHPjgxhjjqlehKBP7XU7vK6ry5bIdtB82l4VJ+72OFTRBLRoiMlNEVqexdQZQ1cdVtSIwFuh79mNp/CjNoP3vjaqjVTVOVeNiYmIC8Z9ijDHpioqM4NH2NfnigRbkjRBufWcRj3+zikPHc16vI6hFQ1WvUdW6aWwTzjn0U6Cr+3oHUNFnXwVgZwbtxhgTEppcUpzJ/Vtxb8vKfLbkF655bTaTV+3KUTPnejl6KtbnbSdgvft6ItDTHUXVDDikqruAaUBbESnu3gBv67YZY0zIKJAvkv9cX5sJfVpSunAUvccu558fxpO496jX0QLCy3saL7qXqhJwCkB/t30ysBlIBN4BegOo6gHgWWCpuz3jthljTMipV6EoE/pczuMda7EgaT/XvDabAeN+DvvhuTbLrTHGBNneIyf4aME2Rs5OIqZQFK90b0DL2FJex0qXzXJrjDEeKl04mkHtavBN7xYUjIrgjvcW8/TENRxPCb8lZq1oGGNMNqlfoRjfP9SKu1tUYsyCrVw/fC5LthwIqxvlVjSMMSYbReeN4OlOdfjk3ss4lnKam99eSM/3l/DrweNeR/OLFQ1jjPFAy9hSzBzYhieuq0X81t+46pWfGDU7ic3JR0O652E3wo0xxmPbDxzjmUlr/5g1t3Kpgjx/Y11aVPXmZrmtEW5FwxgT4lSVpVt/I3HvUd6du5kt+3/nny0rM6hdDaIiI7I1i42eMsaYECciNK1cgtsuu5hJD7Xk9ssu5p25W+j85nzW7z6c+Q/IJlY0jDEmxBTIF8lzXerxwd2Xsu9oCp2Gz+fduZs5c8b7K0NWNIwxJkRdWbM00wa0ok2NGJ77fh09Ri9ic7K305FY0TDGmBBWslAUo+9swpBu9Vm/+zAdXp/L27OTSD19xpM8VjSMMSbEiQjd4yoyc2Ab2lSP4YUp6+ny1nxW/3oo27NY0TDGmDBRukg0b9/ZhJG3N2bP4ZN0GTGfYTM3ciobex1WNIwxJoyICB3qlWPmw23o1OAihs3cxI1vzWfjniPZ8v1WNIwxJgwVLZCX125pyKg7GrPr4AmuHz6P0XOSOB3kEVZWNIwxJoy1r1uOaQ+35soaMfxv8npueXshW/f9HrTvs6JhjDFhrlShKEbd0YShtzRgw54jXPXqT9w8amFQRlhFBvwnGmOMyXYiwo2NKtC8Sik+XbyNvUdOEhkR+H6BFQ1jjMlByhaNZmDbGkH7+XZ5yhhjjN+saBhjjPGbJ0VDRJ4VkQQRWSEi00XkIrf9ChE55LavEJEnfT7TXkQ2iEiiiDzmRW5jjMntvOppDFHV+qraEJgEPOmzb66qNnS3ZwBEJAIYAXQAagO3ikjtbE9tjDG5nCdFQ1V9J4cvCGT2NEpTIFFVN6tqCjAO6BysfMYYY9Lm2T0NEXleRLYDt/PXnkZzEVkpIlNEpI7bVh7Y7nPMDrfNGGNMNgpa0RCRmSKyOo2tM4CqPq6qFYGxQF/3Y8uBS1S1ATAc+Pbsj0vjK9LtnYhILxGJF5H45OTkwP1HGWNMLhe05zRU9Ro/D/0U+B54yveylapOFpG3RKQUTs+ios9nKgA7M/ju0cBocNYIP9/sxhhj0ubJw30iEquqm9y3nYD1bntZYI+qqog0xekJ7QcOArEiUhn4FegB3ObPdy1btmyfiGy7wKilgH0X+FkvWN7gC7fMlje4cmreS9Lb4dUT4S+KSA3gDLANeMBt7wY8KCKpwHGgh6oqkCoifYFpQATwvqqu8eeLVDXmQkOKSLyqxl3o57Ob5Q2+cMtseYMrN+b1pGioatd02t8E3kxn32RgcjBzGWOMyZg9EW6MMcZvVjQyNtrrAOfJ8gZfuGW2vMGV6/KKc8vAGGOMyZz1NIwxxvjNioYxxhi/WdFIQ7jMqCsiW0VklTsjcLzbVkJEZojIJvfP4h7me19E9orIap+2NPOJ4w33nCeISOMQyfu0iPzqM/NyR599g928G0SknQd5K4rILBFZJyJrRKS/2x6S5ziDvKF8jqNFZIk7tdEaEfmv215ZRBa75/hzEcnntke57xPd/ZVCJO8YEdnic44buu3n/zuhqrb5bDjPgSQBVYB8wEqgtte50sm6FSh1TtvLwGPu68eAlzzM1xpoDKzOLB/QEZiCM2VMM2BxiOR9GhiUxrG13d+NKKCy+zsTkc15ywGN3deFgY1urpA8xxnkDeVzLEAh93VeYLF77sbjPEcGMAp40H3dGxjlvu4BfB4ieccA3dI4/rx/J6yn8XfhPqNuZ+BD9/WHQBevgqjqHODAOc3p5esMfKSORUAxESmXPUkd6eRNT2dgnKqeVNUtQCLO7062UdVdqrrcfX0EWIczkWdInuMM8qYnFM6xqupR921ed1PgKuBLt/3cc3z23H8JXC0iac2dFxQZ5E3Pef9OWNH4u3CaUVeB6SKyTER6uW1lVHUXOH9JgdKepUtbevlC+bz3dbvu7/tc7gupvO5lkEY4/7IM+XN8Tl4I4XMsIhEisgLYC8zA6fEcVNXUNHL9kdndfwgo6WVeVT17jp93z/FQEYk6N68r03NsRePvzmtGXY9drqqNcRan6iMirb0OlAWhet5HAlWBhsAu4FW3PWTyikgh4CtggP51rZq/HZpGW7ZnTiNvSJ9jVT2tzoJxFXB6OrXSOsz90/PM5+YVkbrAYKAmcClQAvi3e/h557Wi8XfnNaOul1R1p/vnXuAbnF/oPWe7l+6fe71LmKb08oXkeVfVPe5fwjPAO/x5eSQk8opIXpz/AY9V1a/d5pA9x2nlDfVzfJaqHgR+wrn2X0xEzk7D5Jvrj8zu/qL4f8kzoHzytncvDaqqngQ+IAvn2IrG3y3FnVHXHRHRA5jocaa/EZGCIlL47GugLbAaJ+td7mF3ARO8SZiu9PJNBHq6ozmaAYfOXmLx0jnXd2/EOcfg5O3hjpapDMQCS7I5mwDvAetU9TWfXSF5jtPLG+LnOEZEirmv8wPX4NyLmYUzwSr8/RyfPffdgB/VvePsYd71Pv+IEJz7L77n+Px+J7Lzzn64bDgjCjbiXLt83Os86WSsgjOyZCWw5mxOnOunPwCb3D9LeJjxM5zLDadw/kVzb3r5cLrJI9xzvgqIC5G8H7t5Ety/YOV8jn/czbsB6OBB3pY4lxISgBXu1jFUz3EGeUP5HNcHfnazrQaedNur4BSwROALIMptj3bfJ7r7q4RI3h/dc7wa+IQ/R1id9++ETSNijDHGb3Z5yhhjjN+saBhjjPGbFQ1jjDF+s6JhjDHGb1Y0jDHG+M2Khsm1ROS0O+PnahH5QkQKuO1HM/vsBXxXnIi8EaCfVUNEfnKzrxOR0YH+DmPSY0NuTa4lIkdVtZD7eiywTFVf820PRSIyDXhLVSe47+up6iqPY5lcwnoaxjjmAtV8G0SkkIj8ICLLxVm3pLPbXsn9F/477poF092nb3F7AC+5axpsFJFWbvsVIjLJff20OzHfTyKyWUQe8vnO/4jIenHWwfhMRAalkbUczsOHAJwtGOd8x2T5c+2EQyJylzuR3RARWepOXHd/QM+gyRWsaJhcz50jqAPOE7G+TgA3qjMp5JXAq+40DOBMaTFCVesAB4GuPp+LVNWmwADgqXS+tibQDmcOoKdEJK+IxLk/pxFwExCXzmeHAj+KyBQRefjstBG+VLWjOpPW3QtsA751Xx9S1UtxJq67z52ewxi/RWZ+iDE5Vn53CmlwehrvnbNfgP+5swefwZkyuoy7b4uqnv3sMqCSz+e+Tqfd1/fqTB53UkT2uj+3JTBBVY8DiMh3aX1QVT9wL1G1x1kP4X4RaXDucSJSCmeKjptV9ZCItAXqi8jZOZOK4hS/LelkNOZvrGiY3Oy4+6/x9NwOxABNVPWUiGzFmVsI4KTPcaeB/D7vT/q0p/d37NzPR5L2NNVpUmeG4/eB98VZnrau734RicBZQOwZVT07OZ0A/VR1mr/fY8y57PKUMekrCux1C8aVwCVB/r55wA3irPNcCLgurYPEWcM+r/u6LM4Ehb+ec9iLQIKqjvNpmwY86PPZ6u4Mycb4zXoaxqRvLPCdiMTjzMi6PphfpqpLRWQizszF24B4nJXfztUWeF1ETrjvH1HV3SJS0+eYQcAan8tvTwLv4lwuW+7em0nGw+WATXiyIbfGhBARKaSqR91nRuYAvdRdV9uYUGA9DWNCy2gRqY1z7+RDKxgm1FhPwxhjjN/sRrgxxhi/WdEwxhjjNysaxhhj/GZFwxhjjN+saBhjjPHb/wN0zuksa16IhQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epochs Count [345, 62, 43]\n",
      "Difference(MSE) Value [8.767923411168145e-17, 1.4818105946541725e-17, 4.585236694257994e-25]\n"
     ]
    }
   ],
   "source": [
    "blocks = [(5,i) for i in range(1,10)]\n",
    "\n",
    "epochs_count = []\n",
    "diff_count = []\n",
    "cumm_rewards = []\n",
    "for i in [0,3,5]:\n",
    "    print(\"Planning size:\", i)\n",
    "    game = DynaMaze(10, i, (9,9), blocked_blocks = blocks, mode_type = 'DQ+', verbose=False)\n",
    "    diff, epochs, avg_episode_length, total_rewards = game.play(epochs=1000, threshold=1e-16)\n",
    "    print(\"Average Length of Episode:\", avg_episode_length)\n",
    "    epochs_count.append(epochs)\n",
    "    diff_count.append(diff)\n",
    "    cumm_rewards.append(np.cumsum(total_rewards))\n",
    "\n",
    "plt.plot(cumm_rewards[0])\n",
    "plt.plot(cumm_rewards[1])\n",
    "plt.plot(cumm_rewards[2])\n",
    "plt.xlabel('Planning Size')\n",
    "plt.ylabel('Cummulative Reward Sum')\n",
    "plt.show()\n",
    "plt.plot(epochs_count)\n",
    "plt.xlabel('Step Size')\n",
    "plt.ylabel('Epochs taken for Converging')\n",
    "plt.show()\n",
    "plt.plot(diff_count)\n",
    "plt.xlabel('Step Size')\n",
    "plt.ylabel('Change in Q function(MSE)')\n",
    "plt.show()\n",
    "\n",
    "print('Epochs Count', epochs_count)\n",
    "print('Difference(MSE) Value', diff_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DQ Learning with shortcut maze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-18T07:24:31.623072Z",
     "start_time": "2020-07-18T07:23:51.126982Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Planning size: 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 506.5190615835777\n",
      "Planning size: 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 474.135593220339\n",
      "Planning size: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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QQgAAAABVKCEAAACAKpQQAAAAQBUGUwIAAEAn5lJ2lZ0QAAAAQBVKCAAAAKAKJQQAAABQhZkQAAAA0EEphkJ0k50QAAAAQBVKCAAAAKAKJQQAAABQhZkQAAAA0IGZEN015EuIZ+efk9sXPZSRI4anr78/X/n2zZn9lWvTNE2vlzZkyLh9Mq5DznV8/JADst2EXTIw0J+tXrlD3nXcqRmzxZZ5etnjuepL5+Q9J52x3q8/fcaB+cScq9e5/M6br8u48Ttn250mtbTywUPG7fJYUY9zuV3O5fbJGNY15EuI5StW5Q2HnpUkeeVWY3PxmYflFWM3y6fP+26PVzZ0yLh9Mq5DznWMHDUqx519UZLka+eemZuuuTJv/ssZecXW4zb4hGJ97rzl+uyx736b/JOKRMZt81hRj3O5Xc7l9skY1rVJzYR47Mln86FPzc3Rh/xRkmT0qBE5/5PvzS2Xn5ob556SN02bkiT5xuxj8pop45MkN849JR876sAkyWl/8+c57B375Q/3nZJr/uX4fPXsI/OTr388X5r1/t7coY2QjNsn4zrkXMfOr9ozTy97PEny5NKH8/mTDkuSrFzxXOZ+7pM55yNH5NJ/PD3/fOoxWbL47rVf929zL8zsk4/MeTOPybNPLcv999yeu+ffkKvnnJfZJx+ZJx55sBd3Z6Mk43Z5rKjHudwu53L7ZAyrbVIlRJLc9+ATGTasZNutt8zRh7wpSfL6d/993v+xi3PhGTMyetSIzFuwKPtP3S1bbrFZ+vsHst/ek5Mk0/eZnHkLFidJ9t59p5x89hWZevCs7LLTuEzfZ9ee3aeNjYzbJ+M65NyugYH+3Hv7grx62vR1rvvxNVdmzNgt8+HPfDFvPnhGHrr3nrXXrVzxXHaesmeOO/uiTHr13rnl+1dl4u6vyR7TpufAGUfnuLMvyjbb71jzrmy0ZFyHx4r2OZfrcC63T8aDUyllSH70ym9cQpRSDu/mQmp6Pu/p+0zOV79zc5LkZ/c9mgceXpYpE7fNvAWL88bXTc70qbvme9fdkbGbj8qYzUZm4vit8/P7lyZJ5t9xfx5c+lSapsmt9yzJhPHb9OrubJRk3D4Z1yHn7lu1cmVmn3xkZh3xtvzXs89kt72mrXPM/Xfflr2mH5Ak2W7Crtlu4uS11w0fMTJ77LtfkmT8rq/Kk489Umfhg4iM6/NY0Q7ncn3O5fbJmE3db7MT4vROV5RSjiqlzC+lzO97/I7f4p/ovkk7bpP+/iZLlz2TTuXP/Dvuz+v2nJD9p+6W6xcsyq13L8kR79g/C+/6xdpjVqzsW/v5QP9ARgzf5DaVdCTj9sm4Djm34/nXeJ/8hcvS37cqN1195TrHrG9c1/Dhw9e298OGDctAf39LKx28ZFyXx4r2OJfrci63T8awgRKilPLTDh+3Jdmu09c1TXNB0zTTmqaZNmLc73V90b+pcVuNzeyZh+a8y36YJLl+weIcetDqRn23Cdtm5x22zs/uW5pVff1Z8uhTOfiPp+bm2/4j8xYuzgnve8va7U90JuP2ybgOObdvs83H5q2HfzjXf/uy9Pf1vei6SXu8NrfdeG2SZOmS+/LoA/du8PZGj9k8K5Yvb2Wtg5WM2+exog7ncvucy+2TMay2oXfH2C7JnyZ58iWXlyQ3tLKiLhszemRuuvSja98WZ+5Vt+Tzl/wgSXL+5T/K7JmH5pbLT01ff38+eNqcrFy1+gfbvIWL8ubf3z3Ln1uVeQsXZ6ftt8q8hYt6eVc2WjJun4zrkHN943eZku0nTs5Pb/hBJu3x2rWX/8GfvD1f+6czc85Hjsj4SVOy/YTJ2Wzzseu9rb2mH5BvnP+Z3Pi9K/JXJ57udd5ryLj7PFb0hnO5+5zL7ZMxrKus7z1qSykXJflS0zTXv8x1X22a5j0b+gfGTD3Wm+ACbCTmXDyz10v4lQwM9Ke/ry8jR43OE488mC9+6sT87ecvyYgRI3u9tCFjMGc847BZvV7CJsHjRfucywwVyxee27sphxX8zl/NGZLPaf9z7oyefN/WuxOiaZoj13PdBgsIAPhNrFqxIheefkIG+vvTNE3e9oETB8UTisFExgwVzmWAwWVDL8cAgOpGj9k8Hzrrgl4vY0iTMUOFcxlgcDFGFQAAAKjCTggAAADoZEhPvKjPTggAAACgCiUEAAAAUIUSAgAAAKjCTAgAAADooBRDIbrJTggAAACgCiUEAAAAUIUSAgAAAHiRUsrOpZRrSyl3lVLuKKUc/zLH/LdSyn+WUn6y5uO0Dd2umRAAAADQwSY8E6IvyUlN0ywopWyZ5N9LKf+raZo7X3LcdU3TvPVXvVE7IQAAAIAXaZrm4aZpFqz5/JkkdyXZ8be9XSUEAAAA0FEpZVKSqUl+/DJX71dKubWU8r1Syu9t6LaUEAAAALCJKaUcVUqZ/4KPozocNzbJFUlOaJrm6ZdcvSDJxKZp9k4yO8mVG/p3zYQAAACATUzTNBckuWB9x5RSRmZ1AfGVpmm+/jK38fQLPv9uKeULpZRxTdM83uk2lRAAAADQwaY6mLKsvuMXJbmraZrPdThm+ySPNk3TlFJ+P6tfbfHE+m5XCQEAAAC81P5JZiS5rZTykzWXnZpkQpI0TXNekncmOaaU0pdkeZJDm6Zp1nejSggAAADgRZqmuT7JereBNE1zbpJzf53bNZgSAAAAqMJOCAAAAOhgU50J0RY7IQAAAIAqlBAAAABAFUoIAAAAoAozIQAAAKATIyG6yk4IAAAAoAolBAAAAFCFEgIAAACowkwIAAAA6KAUQyG6yU4IAAAAoAolBAAAAFCFEgIAAACoQgkBAAAAVGEwJQAAAHRgMGV32QkBAAAAVKGEAAAAAKpQQgAAAABVmAkBAAAAHZgJ0V12QgAAAABVKCEAAACAKpQQAAAAQBVmQgAAAEAnRkJ0lZ0QAAAAQBVKCAAAAKAKJQQAAABQhZkQAAAA0EEphkJ0k50QAAAAQBVKCAAAAKAKJQQAAABQhRICAAAAqMJgSgBgUJlz8cxeL2GTMOOwWb1ewpDnXG6f85huMJiyu+yEAAAAAKpQQgAAAABVKCEAAACAKsyEAAAAgA7MhOguOyEAAACAKpQQAAAAQBVKCAAAAKAKMyEAAACgAzMhustOCAAAAKAKJQQAAABQhRICAAAAqMJMCAAAAOjESIiushMCAAAAqEIJAQAAAFShhAAAAACqUEIAAAAAVRhMCQAAAB2UYjJlN9kJAQAAAFShhAAAAACqUEIAAAAAVZgJAQAAAB2YCdFddkIAAAAAVSghAAAAgCqUEAAAAEAVZkIAAABAB2ZCdJedEAAAAEAVSggAAACgCiUEAAAAUIWZEAAAANCJkRBdZScEAAAAUIUSAgAAAKhCCQEAAABUoYQAAAAAqjCYEgAAADooxWTKbrITAgAAAKhCCQEAAABUoYQAAAAAqjATAgAAADowE6K77IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADsyE6C47IQAAAIAqlBAAAABAFUoIAAAAoAozIQAAAKADMyG6y04IAAAAoAolBAAAAFCFEgIAAACoYsjPhHh2/jm5fdFDGTliePr6+/OVb9+c2V+5Nk3T9HppQ4aM2yfjOuRcx8cPOSDbTdglAwP92eqVO+Rdx52aMVtsmaeXPZ6rvnRO3nPSGev9+tNnHJhPzLl6ncvvvPm6jBu/c7bdaVJLKx88ZNw+GbfPY3IdzuV2OY9hXUO+hFi+YlXecOhZSZJXbjU2F595WF4xdrN8+rzv9nhlQ4eM2yfjOuRcx8hRo3Lc2RclSb527pm56Zor8+a/nJFXbD1ug7/srs+dt1yfPfbdb5P/hTeRcQ0ybp/H5Dqcy+1yHg8R5lJ21QZfjlFK2aOU8pZSytiXXH5ge8tqx2NPPpsPfWpujj7kj5Iko0eNyPmffG9uufzU3Dj3lLxp2pQkyTdmH5PXTBmfJLlx7in52FGr7+ppf/PnOewd++UP952Sa/7l+Hz17CPzk69/PF+a9f7e3KGNkIzbJ+M65FzHzq/aM08vezxJ8uTSh/P5kw5Lkqxc8Vzmfu6TOecjR+TSfzw9/3zqMVmy+O61X/dvcy/M7JOPzHkzj8mzTy3L/ffcnrvn35Cr55yX2ScfmSceebAXd2ejJOP2ybh9HpPrcC63y3kMq623hCilfDjJN5Mcl+T2UsrbX3D137e5sLbc9+ATGTasZNutt8zRh7wpSfL6d/993v+xi3PhGTMyetSIzFuwKPtP3S1bbrFZ+vsHst/ek5Mk0/eZnHkLFidJ9t59p5x89hWZevCs7LLTuEzfZ9ee3aeNjYzbJ+M65NyugYH+3Hv7grx62vR1rvvxNVdmzNgt8+HPfDFvPnhGHrr3nrXXrVzxXHaesmeOO/uiTHr13rnl+1dl4u6vyR7TpufAGUfnuLMvyjbb71jzrmy0ZNw+GdfjMbldzuU6nMew4Z0QH0yyb9M0/z3Jf0vyP0spx6+5ruOmlFLKUaWU+aWU+X2P39GdlXbR82/zOn2fyfnqd25OkvzsvkfzwMPLMmXitpm3YHHe+LrJmT5113zvujsydvNRGbPZyEwcv3V+fv/SJMn8O+7Pg0ufStM0ufWeJZkwfpte3Z2NkozbJ+M65Nx9q1auzOyTj8ysI96W/3r2mey217R1jrn/7tuy1/QDkiTbTdg1202cvPa64SNGZo9990uSjN/1VXnysUfqLHwQkXH7ZNwbHpO7z7lcn/OYTd2GSojhTdM8myRN09yX1UXEn5VSPpf1lBBN01zQNM20pmmmjRj3e91aa1dM2nGb9Pc3WbrsmbUPAC81/47787o9J2T/qbvl+gWLcuvdS3LEO/bPwrt+sfaYFSv71n4+0D+QEcO90cjzZNw+Gdch53Y8//rjk79wWfr7VuWmq69c55j1jesaPnx4yppvyLBhwzLQ39/SSgcvGbdPxvV5TG6Hc7ku5/HgVEoZkh+9sqGz9ZFSyj7P/8eaQuKtScYleW2bC2vDuK3GZvbMQ3PeZT9Mkly/YHEOPWh127vbhG2z8w5b52f3Lc2qvv4sefSpHPzHU3Pzbf+ReQsX54T3vWXt9ic6k3H7ZFyHnNu32eZj89bDP5zrv31Z+vv6XnTdpD1em9tuvDZJsnTJfXn0gXs3eHujx2yeFcuXt7LWwUrG7ZNxHR6T2+dcbp/zGFbb0LtjvC/Jix6FmqbpS/K+Usr5ra2qi8aMHpmbLv3o2rfFmXvVLfn8JT9Ikpx/+Y8ye+ahueXyU9PX358PnjYnK1etvrvzFi7Km39/9yx/blXmLVycnbbfKvMWLurlXdloybh9Mq5DzvWN32VKtp84OT+94QeZtMf/6bb/4E/enq/905k55yNHZPykKdl+wuRstvnY9dxSstf0A/KN8z+TG793Rf7qxNO9BnkNGbdPxu3wmFyfc7n7nMewrtL2e9SOmXqsN8EF2EjMuXhmr5fwKxkY6E9/X19GjhqdJx55MF/81In5289fkhEjRvZ6aUOGjNs32DOecdisXi9hyPOY3D7ncR3LF547pN/EctcTvzskn9Pe+7mDevJ929BOCACobtWKFbnw9BMy0N+fpmnytg+cOCh+2R1MZNw+GTNUOJfZ1PVyfsJQpIQAYKMzeszm+dBZF/R6GUOajNsnY4YK5zLQTcaoAgAAAFUoIQAAAIAqvBwDAAAAOjASorvshAAAAACqUEIAAAAAVSghAAAAgCqUEAAAAEAVBlMCAABAB8Vkyq6yEwIAAACoQgkBAAAAVKGEAAAAAKowEwIAAAA6MBKiu+yEAAAAAKpQQgAAAABVKCEAAACAKsyEAAAAgA6KoRBdZScEAAAAUIUSAgAAAKhCCQEAAABUYSYEAAAAdGAkRHfZCQEAAABUoYQAAAAAqlBCAAAAAFUoIQAAAIAqDKYEAACADoYNM5mym+yEAAAAAKpQQgAAAABVKCEAAACAKsyEAAAAgA6KkRBdZScEAAAAUIUSAgAAAKhCCQEAAABUYSYEAAAAdFAMhegqOyEAAACAKpQQAAAAQBVKCAAAAKAKMyEAAACgAyMhustOCAAAAKAKJQQAAABQhRICAAAAqEIJAQAAAFRhMCUAAAB0UEym7Co7IQAAACYTUO8AACAASURBVIAqlBAAAABAFUoIAAAAoAozIQAAAKADMyG6y04IAAAAoAo7IYCNxpyLZ/Z6CQBQzYzDZvV6CQDV2QkBAAAAVGEnBAAAAHRgJER32QkBAAAAVKGEAAAAAKpQQgAAAABVmAkBAAAAHRRDIbrKTggAAACgCiUEAAAAUIUSAgAAAKhCCQEAAABUYTAlAAAAdGAuZXfZCQEAAABUoYQAAAAAqlBCAAAAAFWYCQEAAAAdFEMhuspOCAAAAKAKJQQAAABQhRICAAAAqMJMCAAAAOjASIjushMCAAAAqEIJAQAAAFShhAAAAACqMBMCAAAAOiiGQnSVnRAAAABAFUoIAAAAoAolBAAAAFCFEgIAAACowmBKAAAA6MBcyu6yEwIAAACoQgkBAAAAVKGEAAAAAKowEwIAAAA6KIZCdJWdEAAAAEAVSggAAADgRUopO5dSri2l3FVKuaOUcvzLHFNKKeeUUhaVUn5aSnndhm7XyzEAAACAl+pLclLTNAtKKVsm+fdSyv9qmubOFxzzZ0mmrPn4gyT/vOZ/O1JCAAAAQAeb6kiIpmkeTvLwms+fKaXclWTHJC8sId6e5MtN0zRJbiql/G4pZYc1X/uyvBwDAAAANjGllKNKKfNf8HHUeo6dlGRqkh+/5Kodk/ziBf+9ZM1lHdkJAQAAAJuYpmkuSHLBho4rpYxNckWSE5qmefqlV7/cTa/v9uyEAAAAANZRShmZ1QXEV5qm+frLHLIkyc4v+O+dkjy0vtu0EwIAAAA6KJvoUIiy+o5flOSupmk+1+GwbyU5tpRyaVYPpPzP9c2DSJQQAAAAwLr2TzIjyW2llJ+suezUJBOSpGma85J8N8lBSRYl+a8kh2/oRpUQAAAAwIs0TXN9Xn7mwwuPaZJ86Ne5XTMhAAAAgCqUEAAAAEAVXo4BAAAAHWyicylbYycEAAAAUIUSAgAAAKhCCQEAAABUYSYEAAAAdFAMhegqOyEAAACAKob8Tohn55+T2xc9lJEjhqevvz9f+fbNmf2Va9M0Ta+XNmTIuH0yruPjhxyQ7SbskoGB/mz1yh3yruNOzZgttszTyx7PVV86J+856Yz1fv3pMw7MJ+Zcvc7ld958XcaN3znb7jSppZUPLnJun4zbJ+P2+dnXPhm3T8awriFfQixfsSpvOPSsJMkrtxqbi888LK8Yu1k+fd53e7yyoUPG7ZNxHSNHjcpxZ1+UJPnauWfmpmuuzJv/ckZesfW4DT6hWJ87b7k+e+y7nycVa8i5fTJun4zb52df+2TcPhnDujb4coxSyu+XUl6/5vM9SyknllIOan9p3ffYk8/mQ5+am6MP+aMkyehRI3L+J9+bWy4/NTfOPSVvmjYlSfKN2cfkNVPGJ0lunHtKPnbUgUmS0/7mz3PYO/bLH+47Jdf8y/H56tlH5idf/3i+NOv9vblDGyEZt0/Gdez8qj3z9LLHkyRPLn04nz/psCTJyhXPZe7nPplzPnJELv3H0/PPpx6TJYvvXvt1/zb3wsw++cicN/OYPPvUstx/z+25e/4NuXrOeZl98pF54pEHe3F3Nlpybp+M2yfj9vnZ1z4Zt0/Gg1cpQ/OjV9ZbQpRSPpHknCT/XEo5M8m5ScYm+WgpZWaF9XXdfQ8+kWHDSrbdesscfcibkiSvf/ff5/0fuzgXnjEjo0eNyLwFi7L/1N2y5Rabpb9/IPvtPTlJMn2fyZm3YHGSZO/dd8rJZ1+RqQfPyi47jcv0fXbt2X3a2Mi4fTJu18BAf+69fUFePW36Otf9+JorM2bslvnwZ76YNx88Iw/de8/a61aueC47T9kzx519USa9eu/c8v2rMnH312SPadNz4Iyjc9zZF2Wb7XeseVc2anJun4zbJ+N6/Oxrn4zbJ2PY8E6IdybZP8mbknwoyX9vmuaMJH+a5JBOX1RKOaqUMr+UMr/v8Tu6tthueb71mb7P5Hz1OzcnSX5236N54OFlmTJx28xbsDhvfN3kTJ+6a7533R0Zu/mojNlsZCaO3zo/v39pkmT+HffnwaVPpWma3HrPkkwYv02v7s5GScbtk3H3rVq5MrNPPjKzjnhb/uvZZ7LbXtPWOeb+u2/LXtMPSJJsN2HXbDdx8trrho8YmT323S9JMn7XV+XJxx6ps/BBRs7tk3H7ZNwbfva1T8btkzGbug2VEH1N0/Q3TfNfSRY3TfN0kjRNszzJQKcvaprmgqZppjVNM23EuN/r4nJ/e5N23Cb9/U2WLnum4xaU+Xfcn9ftOSH7T90t1y9YlFvvXpIj3rF/Ft71i7XHrFjZt/bzgf6BjBjujUaeJ+P2ybgdz7/G++QvXJb+vlW56eor1zlmfWOkhg8fvvYtnIYNG5aB/v6WVjq4ybl9Mm6fjOvzs699Mm6fjGHDJcTKUsrmaz7f9/kLSym/k/WUEBurcVuNzeyZh+a8y36YJLl+weIcetDqv1zsNmHb7LzD1vnZfUuzqq8/Sx59Kgf/8dTcfNt/ZN7CxTnhfW9Zu/2JzmTcPhm3b7PNx+ath38413/7svT39b3oukl7vDa33XhtkmTpkvvy6AP3bvD2Ro/ZPCuWL29lrYOZnNsn4/bJuA4/+9on4/bJePAqpQzJj17Z0LtjvKlpmhVJ0jTNC0uHkUkGxQSUMaNH5qZLP7r2bXHmXnVLPn/JD5Ik51/+o8yeeWhuufzU9PX354OnzcnKVat/gZi3cFHe/Pu7Z/lzqzJv4eLstP1WmbdwUS/vykZLxu2TcX3jd5mS7SdOzk9v+EEm7fHatZf/wZ+8PV/7pzNzzkeOyPhJU7L9hMnZbPOx672tvaYfkG+c/5nc+L0r8lcnnu513i8g5/bJuH0yboeffe2TcftkDOsqbb9H7Zipx3oTXOBXMufijX/e7cBAf/r7+jJy1Og88ciD+eKnTszffv6SjBgxstdLG1Lk3D4Zt2+wZzzjsFm9XgIwSCxfeG4P32uhfX/42euH5HPa6056Y0++bxvaCQHAC6xasSIXnn5CBvr70zRN3vaBEwfNE4rBRM7tk3H7ZAwA61JCAPwaRo/ZPB8664JeL2PIk3P7ZNw+GQPAupQQAAAA0EEvhzgORd7LBQAAAKhCCQEAAABUoYQAAAAAqjATAgAAADowEqK77IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADoqhEF1lJwQAAABQhRICAAAAqEIJAQAAAFRhJgQAAAB0YCREd9kJAQAAAFShhAAAAACqUEIAAAAAVSghAAAAgCoMpgQAAIAOismUXWUnBAAAAFCFEgIAAACoQgkBAAAAVGEmBAAAAHRgJER32QkBAAAAVKGEAAAAAKpQQgAAAABVmAkBAAAAHQwzFKKr7IQAAAAAqlBCAAAAAFUoIQAAAIAqzIQAAACADoyE6C47IQAAAIAqlBAAAABAFUoIAAAAoAolBAAAAFCFwZQAAADQQTGZsqvshAAAAACqUEIAAAAAVSghAAAAgCrMhAAAAIAOhhkJ0VV2QgAAAABVKCEAAACAKpQQAAAAQBVmQgAAAEAHpRgK0U12QgAAAABVKCEAAACAKpQQAAAAQBVmQgAAAEAHRkJ0lxJiCJhz8cxeLwEAGGL8fsFQMOOwWb1eAvASXo4BAAAAVKGEAAAAAKpQQgAAAABVmAkBAAAAHZSYTNlNdkIAAAAAVSghAAAAgCqUEAAAAEAVZkIAAABAB8OMhOgqOyEAAACAKpQQAAAAQBVKCAAAAKAKMyEAAACgg1IMhegmOyEAAACAKpQQAAAAQBVKCAAAAKAKMyEAAACgAyMhustOCAAAAKAKJQQAAABQhRICAAAAqEIJAQAAAFRhMCUAAAB0MMxkyq6yEwIAAACoQgkBAAAAVKGEAAAAAKowEwIAAAA6MBKiu+yEAAAAAKpQQgAAAABVKCEAAACAKsyEAAAAgA6KoRBdZScEAAAAUIUSAgAAAKhCCQEAAABUYSYEAAAAdGAkRHfZCQEAAABUoYQAAAAAqlBCAAAAAFUoIQAAAIAqDKYEAACADoaZTNlVdkIAAAAAVSghAAAAgCqUEAAAAEAVZkIAAABAByZCdJedEAAAAEAVSggAAACgCiUEAAAAUIWZEAAAANBBKaZCdJOdEAAAAEAVSggAAACgCiUEAAAAUMWQLyGenX9Obrr0o/n3r83Mjy/7aD783gO8pqcFHz/kgMw++ch8/qTD8uWzPpblv3wmSfL0ssfz1c+etsGvP33GgS97+Z03X5elS+7r5lIHLRm3T8Z1yLl9Mm6fjOuQc/tk3C7PRYaGYWVofvQsz97903UsX7Eqbzj0rOz7zll569Hn5k/fuGdm/vWf9XpZQ87IUaNy3NkX5fjPXpzNx74iN11zZZLkFVuPy3tOOuM3vt07b7neD7A1ZNw+Gdch5/bJuH0yrkPO7ZNxuzwXgXVtUu+O8diTz+ZDn5qb6y/5u3z6vO9m9KgROefUQ/O6PSekr78/p3z26/nR/J/nG7OPyf8855u5/ecP5ca5p+Rb196aMy+4Oqf9zZ/ngYeXZfEDj+fjRx+UJ556NntO3iEL7/pFDp/5r72+exuNnV+1Zx554N4kyZNLH86X/+FjOf6zF2fliudyxT+dlcceeiDb7jgxTz72SP7iyOOz0+Q9kiT/NvfC3LPgxowcNSrvPXlWnnj0odw9/4bcd+etufaKOXnPSWdkm+137OVd22jIuH0yrkPO7ZNx+2Rch5zbJ+N2eS4Cq/3aOyFKKV9uYyG13PfgExk2rGTbrbfM0Ye8KUny+nf/fd7/sYtz4RkzMnrUiMxbsCj7T90tW26xWfr7B7Lf3pOTJNP3mZx5CxYnSfbefaecfPYVmXrwrOyy07hM32fXnt2njcnAQH/uvX1BXj1t+jrX/fiaKzNm7Jb58Ge+mDcfPCMP3XvP2utWrnguO0/ZM8edfVEmvXrv3PL9qzJx99dkj2nTc+CMo3Pc2Rf54bWGjNsn4zrk3D4Zt0/Gdci5fTKuw3MR2MBOiFLKt156UZI3l1J+N0mapnlbWwtr0/Mvw5q+z+R84dIfJkl+dt+jeeDhZZkycdvMW7A4f/NXf5T7Hno837vujrzlDbtnzGYjM3H81vn5/Uuz/bjfyfw77s+DS59Kktx6z5JMGL9NbvjJvb26Sz23auXKzD75yDz12CMZv+vu2W2vaescc//dt2X6Qe9Mkmw3YddsN3Hy2uuGjxiZPfbdL0kyftdXZdFP59dZ+CAi4/bJuA45t0/G7ZNxHXJun4zr81xk8DHHo7s2tBNipyRPJ/lcks+u+XjmBZ+/rFLKUaWU+aWU+X2P39GttXbFpB23SX9/k6XLnkmnc2n+HffndXtOyP5Td8v1Cxbl1ruX5Ih37J+Fd/1i7TErVvat/XygfyAjhg/58Rrr9fzrCU/+wmXp71uVm66+cp1jmvV8/fDhw9f+n3vYsGEZ6O9vaaWDl4zbJ+M65Nw+GbdPxnXIuX0yrstzEdhwCTEtyb8nmZnkP5um+d9JljdN88OmaX7Y6YuaprmgaZppTdNMGzHu97q32t/SuK3GZvbMQ3PeZauXfv2CxTn0oNVt724Tts3OO2ydn923NKv6+rPk0ady8B9Pzc23/UfmLVycE973lrXbn+hss83H5q2HfzjXf/uy9Pf1vei6SXu8NrfdeG2SZOmS+/LoAxtua0eP2Twrli9vZa2DlYzbJ+M65Nw+GbdPxnXIuX0ybp/nIrDaekuIpmkGmqb5xySHJ5lZSjk3g2yY5ZjRI9e+Lc53zjs237/x7sw6/3tJkvMv/1GGDxuWWy4/NXP+4fB88LQ5Wblq9YPuvIWLsnTZM1n+3KrMW7g4O22/VeYtXNTLuzJojN9lSrafODk/veEHL7r8D/7k7fnl00/lnI8ckR9dOTfbT5iczTYfu97b2mv6AbnuW5fm3L/7QJ545ME2lz2oyLh9Mq5Dzu2TcftkXIec2yfj7vNcBNZVmmZ9G6xecnApf55k/6ZpTv1Vv2bM1GN/9X+A38ici2f2egm/koGB/vT39WXkqNF54pEH88VPnZi//fwlGTFiZK+XNmTIuH0yrkPO7ZNx+2Rch5zbN5gznnHYrF4vYZOwfOG5Q3pownsvuXVIPqe95L179+T79mvtamia5jtJvtPSWhjiVq1YkQtPPyED/f1pmiZv+8CJg+KH12Ai4/bJuA45t0/G7ZNxHXJun4zZ1JlL2V2/1k6I34SdEO0bLDshAACgJjsh6hjqOyFmfGVo7oSY8z96sxPCGFUAAACgCiUEAAAAUMWgeqcLAAAAqKkYCtFVdkIAAAAAVSghAAAAgCqUEAAAAEAVZkIAAABAB8OMhOgqOyEAAACAKpQQAAAAQBVKCAAAAKAKMyEAAACgg1IMhegmOyEAAACAKpQQAAAAQBVKCAAAAKAKJQQAAABQhcGUAAAA0IGxlN1lJwQAAABQhRICAAAAqEIJAQAAAFRhJgT/P3t3HmdnWd4N/HdPNhICyiJLgAQIm6kCkbgQfK3iUlQqrwULWrEsiigibqiI1QJSsUj7stQiglCDIoqKiAq2llaIIMTEyCJIgoAhQICwasgy87x/JEQgnozgee7JTL5fPvNx5mxzP1cen3POb67nOgAAAHTQU0yF6CadEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANCBkRDdpRMCAAAAqEIIAQAAAFQhhAAAAACqMBMCAAAAOiiGQnSVTggAAACgCiEEAAAAUIUQAgAAAKhCCAEAAABUYTAlAAAAdGAuZXfphAAAAACqEEIAAAAAVQghAAAAgCrMhAAAAIAOegyF6CqdEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANCBkRDdpRMCAAAAqEIIAQAAAFQhhAAAAACqMBMCAAAAOiiGQnSVTggAAADgKUopXy6lLCil3NDh+leWUh4upfxixden/pTH1QkBAAAAPN15Sc5I8pXV3ObKpmn2fiYPqhMCAAAAeIqmaX6SZGG3H1cnxBDw+R/+eqCXMOTNvvCbA72EtcK0844d6CXAn80xuX0fef0OA72EtcKBB5040EsY8nbZ/y0DvQRgLVZKOSzJYU+66Kymac56hg+zeylldpL5ST7SNM2N/d1BCAEAAAAdDNXTB1YEDs80dHiymUkmNE3zWCnlDUkuTrJ9f3caqvUEAAAAWtI0zSNN0zy24vsfJBlRStm4v/sJIQAAAIBnpJSyWVnx+aWllJdkeb7wQH/3czoGAAAA8BSllAuSvDLJxqWUeUk+nWREkjRNc2aS/ZK8p5SyLMmiJAc0TdP097hCCAAAAOhgxR/71zpN07y1n+vPyPKP8HxGnI4BAAAAVCGEAAAAAKoQQgAAAABVmAkBAAAAHfSsnSMhWqMTAgAAAKhCCAEAAABUIYQAAAAAqjATAgAAADowE6K7dEIAAAAAVQghAAAAgCqEEAAAAEAVQggAAACgCoMpAQAAoINSTKbsJp0QAAAAQBVCCAAAAKAKIQQAAABQhZkQAAAA0EGPkRBdpRMCAAAAqEIIAQAAAFQhhAAAAACqMBMCAAAAOihmQnSVTggAAACgCiEEAAAAUIUQAgAAAKjCTAgAAADooMdQiK7SCQEAAABUIYQAAAAAqhBCAAAAAFUIIQAAAIAqDKYEAACADvzlvrvUEwAAAKhCCAEAAABUIYQAAAAAqjATAgAAADooZaBXMLTohAAAAACqEEIAAAAAVQghAAAAgCrMhAAAAIAOegyF6CqdEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANCBkRDdpRMCAAAAqEIIAQAAAFQx5E/HeGzGablhzvyMGD4sy3p789XvXZvTv3pFmqYZ6KUNKdM/+orMve93KSXp62vy+f+ck+vveiSbP2dUPr/fC/N358x4xo/5nfe8NAed9/M8vGhZCysefJ7Yl0tJenubfOhz38g1s3+T8ZtvmG+fdnimvOWfnvFj3vz947LH3/1zHnjody2sePD55P57ZtPx2yRJSk9P/vqQozJhxxfkwQV35yufOyZHnXLeM37Mk4/YP+/97Bez7vrP7fJqByc1rsMxuX325fZ53qvD8aJd3ovAqoZ8CLFo8dK87ICTkiTP22BszvvsQVl/7Dr5zJk/GOCVDS2Ll/XlHef+PEny0m02yHv+cpu892uzB3hVQ8uT9+XX7P78HH/km/K6d546wKsaWkaMHJkjTz4nSXLrL67Nj772pbzrODXuJjWuwzG5ffbl9nneq8Pxol3ei8CqhnwI8WT3PfhYjjjhglx1/kfzmTN/kFEjh+e0TxyQF00an2W9vfnYKd/OT2bcmu+c/p78w2nfzQ23zs/VF3wsl1wxO58967J86r1vzJ13L8zcO+/PJw9/Qx546LFMmrh5Zv3qtzn42P8Y6M1bY6w7clgefXzV5HvksJKP/tUO2Wmzseltmpz649sy886H0lOSI165bV66zQZJku/Ovjvf/Pn8lfcbNbwnJ/3NX+R/brkv3519T7XtWJOtv+46eeiR369yead9uqen5MSj/m9es/vz0zRNzv3OT/PvX//flfdbZ9SIXHjKu3Lxj3+Rc7/z05qbssZ6fNHvM3rdsatcvnTJ4lxy9r/mrrm3pGfYsLzhHUdk2xdMTl9fby4//4u5dfZ1SSl58av3zu6v/5un3O+rJ38yf/HSv8yLX7N3zU1ZY6lxHY7J7bMvt8/zXh2OF+3yXmTw6jGYsqueUQhRSnl5kpckuaFpmh+1s6R23X7XA+npKdlkw/Xy1je+OEny4r/9p+yw9aa59AtH5IX/9/hMnzkne0zeLnfMX5je3r7svsvEJMnUXSfmgu9fl802fk522XHL7LbfiZl/38O54rwPZequ2+anv7htIDdtQI0a3pOvHLxbRg7vycbrjswRF6yaoO+32xZJkrd/+eeZsOHonLr/zvnbs67N3jtvlnHPXSd/f+7P09sk66/zh91yzMhh+cw+k/KDG+7ND2+4t9r2rIlGjxqRa77+8awzcng22/g5ef27T1vlNofv/4okq+7T79jnZdl6i43ysreelN7evmyw/piV91l39Kh85aSD89VLr83XLr222vasiZYuWZLTjz40y5YuyaMPLsyhn/6XVW7zs8svTpK8/5Rzc99dd+TczxydD546LTP/57I8uOCeHPHPX8qwYcPz+8ceWXmfJY8vyoWnHp/Jr/irTP7Lv6q2PWsiNa7DMbl99uX2ed6rw/GiLu9FoJ/BlKWUa5/0/buSnJFkvSSfLqV8vOW1teaJj1iZuuvEfO37yzfx17ffmzvvXpjtJ2yS6TPn5uUvmpipk7fND6+8MWPHjMzodUZkwrgNc+sdC5IkM268I3cteChN02T2LfMyftxGA7U5a4QnWvkO+NJ1+cA3rs+n995pldvsvOVz8sMblz8J3bFwUe55ZHHGbzgmL956g3xn1t3pXXFq3CNPSuD/ed8X5NJf3uPJK39o59v1bz6Tfd73hZx9wjtWuU2nfXrPl+6UL33zqvT29iVJHnzSX5O++f8Oy7TvXuOFWP7QXv3B/zctBx37z7nojM+ucs7m7Tdfn11f8bokyfO2mJDnPm/TPHD3vMz95c/zkte9KcOGLX8BNmbs+ivvc/7Jn8yLXvn6tf4NRaLGtTgmt8++3D7Pe3U4XtTnvQhru/4+HWPEk74/LMlrm6Y5LsnrkvxdpzuVUg4rpcwopcxYdv+NXVhm92y9xUbp7W2yYOGjHT/vdcaNd+RFk8Znj8nb5aqZczL75nk55M17ZNavfrvyNouX/OEg29fbl+HDfNDIE26Y/0ieO2ZENhgz4imXd+piKknH4Ty/nPdwdt92w+4ucAj42S9/k42eu26et8FT23877dMlSZM/XuOrf3FbXrfHpC6vcPAbv8Nf5HePPpzfPfLQU6/osK92qm+SjN/xBfn1rJ8ZQvU0alyHY3L77Mvt87xXh+NF+7wXgf5DiJ5SygallI2SlKZp7kuSpml+l6TjuNumac5qmmZK0zRThm/8F11c7p9n4w3G5vRjD8iZFy4/J/CqmXNzwBumJEm2G79Jttp8w/z69gVZuqw38+59KPu+dnKuvf43mT5rbj7wjldn+sy5A7n8QWPChqPTU0oeXrT0KZf/4rcP568mbZIk2WqD0dl0/VG5Y+Hv87PfPJg3Tx6XYSsOxE9u5Tvrytvz8ONL89HXbV9t/YPBDltvmmE9PXng4adO9+60T//XNTfnXfu9PMNWPEE9uS31hH//fhY+/Luc+on9623AIHDfXXek6evNmPXWf8rlW0/aJbOv/K8kyf3zf5uH71+Qjcdtle12npJr//OS9PYuPzQ+ub36NX97cMas95xccva/1tuAQUCN63BMbp99uX2e9+pwvGiX9yKDV08pQ/JroPQ3E+I5SX6eFUFnKWWzpmnuKaWMTedQdI3yxPmET3wszgWXXpdTz//vJMkXv/GTnH7sAbnuG5/Ist7evOtT07Jk6fIXBNNnzcmrXrJjFj2+NNNnzc2Wm22Q6bPmDOSmrNGeOJ8wWf5XieO/f3P6nhaMf2vmXfnYXjvk/EN2S2/T5ITv35KlvU0umX13xm84JucfOiXL+pp89xd356KZfxhq9K//NTeffMOOed8rt80Z/7P2nuv2xL6cLK/xuz41LX1PK3Knffrc7/w020/YJNd945gsXdabc7/905x54U9W3u8jJ38rX/zHt+fEo/bJsad+t+p2rUmeOMf7CfsecUx6eoY95TYvfd0++e6X/iWnffjg9Awbln3f+/EMHzEyU179xjxw97yc/pFDM2z48Ex59Ruz+15/GDT3xoPel2//++dy2flnZq+3H15tm9Y0alyHY3L77Mvt87xXh+NFu7wXgVWVZ9PuV0oZk2TTpml+099tR09+n37Clu2y/1sGeglD3uwLvznQS1grTDvv2IFeAvzZPv/DXw/0Eoa8j7x+h4FewlrhwINOHOglDHleUugaBwAAIABJREFUw7XPa7g6Fs06Y1D8gfrZOv4/5wzJ97Sfeu12A/Lv9qw+orNpmt8n6TeAAAAAAHjCswohAAAAYG0wgOMThiRjVAEAAIAqhBAAAABAFUIIAAAAoAozIQAAAKCDHjMhukonBAAAAFCFEAIAAACoQggBAAAAVCGEAAAAAKowmBIAAAA6KDGZspt0QgAAAABVCCEAAACAKoQQAAAAQBVmQgAAAEAHPUZCdJVOCAAAAKAKIQQAAABQhRACAAAAqMJMCAAAAOjATIju0gkBAAAAVCGEAAAAAKoQQgAAAABVmAkBAAAAHZRiKEQ36YQAAAAAqhBCAAAAAFUIIQAAAIAqhBAAAABAFQZTAgAAQAc95lJ2lU4IAAAAoAohBAAAAFCFEAIAAACowkwIAAAA6KCYCdFVOiEAAACAKoQQAAAAQBVCCAAAAKAKMyEAAACggx5DIbpKJwQAAABQhRACAAAAqEIIAQAAAFRhJgQAAAB00GMkRFfphAAAAACqEEIAAAAAVQghAAAAgCqEEAAAAEAVBlMCAABAB8Vgyq7SCQEAAABUIYQAAAAAqhBCAAAAAFWYCQEAAAAd9MRQiG5qPYSYdt6xbf+Ktd6BB5040EsAYIXZF35zoJcw9L3eawuGBscLYG3kdAwAAACgCiEEAAAAUIWZEAAAANBBMRKiq3RCAAAAAFUIIQAAAIAqhBAAAABAFWZCAAAAQAc9ZkJ0lU4IAAAAoAohBAAAAFCFEAIAAACoQggBAAAAVGEwJQAAAHTQU0ym7CadEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANCBkRDdpRMCAAAAqEIIAQAAAFQhhAAAAACqMBMCAAAAOugxFKKrdEIAAAAAVQghAAAAgCqEEAAAAEAVZkIAAABAB0ZCdJdOCAAAAKAKIQQAAABQhRACAAAAqEIIAQAAAFRhMCUAAAB04C/33aWeAAAAQBVCCAAAAKAKIQQAAABQhZkQAAAA0EEpZaCXMKTohAAAAACqEEIAAAAAVQghAAAAgCrMhAAAAIAOTIToLp0QAAAAQBVCCAAAAKAKIQQAAABQhZkQAAAA0EFPMRWim3RCAAAAAFUIIQAAAIAqhBAAAABAFUIIAAAAoAqDKQEAAKADYym7SycEAAAAUIUQAgAAAKhCCAEAAABUYSYEAAAAdFAMheiqtSKE+OT+e2bT8dukr683Gzxv87zlyE9k9Lrr5ZGF9+fSc0/L2z58/Grvf9yBe+XT0y5b5fKbrr0yG4/bKptsuXVLKx8cHptxWm6YMz8jhg/Lst7efPV71+b0r16RpmkGemlDhhrX4VhRhzq3y/GiDvtx++zL7VPj9qkxrGqtCCFGjByZI08+J0ly0RmfzTWXX5xX/c2BWX/Djft9kbA6N113VXbabfe1/oXCosVL87IDTkqSPG+DsTnvswdl/bHr5DNn/mCAVzZ0qHEdjhV1qHO7HC/qsB+3z77cPjVunxrDqlY7E6KU8tJSyvorvh9dSjmulPK9UsrnSinPqbPE7tpqh0l5ZOH9SZIHF9ydUz98UJJkyeLHc8G//GNO+8gh+fq/Hpd//8R7Mm/uzSvv96MLzs7pRx+aM499Tx57aGHuuOWG3Dzjp7ls2pk5/ehD88A9dw3E5qxx7nvwsRxxwgU5fP+/TJKMGjk8X/zHt+e6b3wiV1/wsbxiyvZJku+c/p68YPtxSZKrL/hYjjlsryTJp977xhz05t3zf3bbPpd/6ah87eRD84tvfzLnnvj3A7NBayA1rsOxog51bpfjRR324/bZl9unxu1TY1iuv8GUX07y+xXfn5rkOUk+t+Kyc1tcVyv6+npz2w0z8/wpU1e57meXX5zRY9fL+z//5bxq3wMz/7ZbVl63ZPHj2Wr7STny5HOy9fN3yXU/vjQTdnxBdpoyNXsdeHiOPPmcbLTZFjU3ZY12+10PpKenZJMN18vh+78iSfLiv/2n/P0x5+Xs4w/MqJHDM33mnOwxebust+466e3ty+67TEySTN11YqbPnJsk2WXHLXP0yd/K5H1PzDZbbpypu247YNu0plHjdjlW1KHOdThetMt+XI99uX1q3D41HpxKKUPya6D0F0L0NE2zbMX3U5qm+UDTNFc1TXNcko57einlsFLKjFLKjP+86PyuLfbZWrpkSU4/+tCceMib8vvHHs12O09Z5TZ33Hx9dp66Z5Jk0/HbZtMJE1deN2z4iOy02+5JknHb7pAH77unzsIHsSf26am7TszXvn9tkuTXt9+bO+9emO0nbJLpM+fm5S+amKmTt80Pr7wxY8eMzOh1RmTCuA1z6x0LkiQzbrwjdy14KE3TZPYt8zJ+3EYDtTlrJDXuPseKOtS5PseL7rMfDwz7cvvUuH1qzNquvxDihlLKwSu+n11KmZIkpZQdkiztdKemac5qmmZK0zRTXrvf27u01GfvifM2j/7CheldtjTXXHbxKrdZ3WiYYcOGrUyKenp60tfb29JKh4att9govb1NFix8tOMk2Rk33pEXTRqfPSZvl6tmzsnsm+flkDfvkVm/+u3K2yxesmzl9329fRk+zCfKPkGN2+FYUYc61+V40Q77cX325fapcfvUGPoPId6Z5C9LKXOTTEpydSnltiRfWnHdoLLOmLHZ++D356rvXZjeZcuect3WO70w1199RZJkwbzbc++dt/X7eKNGj8niRYtaWetgtfEGY3P6sQfkzAv/N0ly1cy5OeANy/86tN34TbLV5hvm17cvyNJlvZl370PZ97WTc+31v8n0WXPzgXe8emWLGZ2pcfscK+pQ5/Y5XrTPflyHfbl9atw+NYblVvvpGE3TPJzkoFLKell++sXwJPOaprm3xuLaMG6b7bPZhIn55U//O1vv9MKVl7/0dfvkon/7bE77yCEZt/X22Wz8xKwzZuxqH2vnqXvmO1/8fK7+4bfy1g8dt9aeuzl61Ihc8/WPr/zooQsuvS6nnv/fSZIvfuMnOf3YA3LdNz6RZb29edenpmXJ0uUv0qbPmpNXvWTHLHp8aabPmpstN9sg02fNGchNWWOpcX2OFXWoc/c5XtRnP26Hfbl9atw+NR4a9Jl0V2n7M2ovmn33oPgQ3L6+3vQuW5YRI0flgXvuypdP+FA+eOr5GT58xEAvrV8HHnTiQC8BumLaeccO9BL6NZiPFYPJYK6zY3L7BsOxIhnc+3FiXwb+dItmnTFwUw4ruHDWXYPiPe0ztf/kLQbk3221nRBrk6WLF+fs4z6Qvt7eNE2TN73zQ4PmRQJQj2NFHerMUGA/BoBVCSFWGDV6TI446ayBXgawhnOsqEOdGQrsxwCwKqe3AAAAAFXohAAAAIAOSqfPU+VZ0QkBAAAAVCGEAAAAAKoQQgAAAABVmAkBAAAAHZgI0V06IQAAAIAqhBAAAABAFUIIAAAA4ClKKV8upSwopdzQ4fpSSjmtlDKnlPLLUsqL/pTHNRMCAAAAOihlrZ0KcV6SM5J8pcP1r0+y/Yqvlyb59xX/u1o6IQAAAICnaJrmJ0kWruYm+yT5SrPcNUmeW0rZvL/HFUIAAADAWqaUclgpZcaTvg57hg+xRZLfPunneSsuWy2nYwAAAMBapmmas5Kc9Wc8xB87T6Xp705CCAAAAOjA6QMdzUuy1ZN+3jLJ/P7upJ4AAADAM3VJknes+JSMlyV5uGmau/u7k04IAAAA4ClKKRckeWWSjUsp85J8OsmIJGma5swkP0jyhiRzkvw+ycF/yuMKIQAAAICnaJrmrf1c3yQ54pk+rtMxAAAAgCp0QgAAAEAHpfyxD4Hg2dIJAQAAAFQhhAAAAACqEEIAAAAAVZgJAQAAAB2YCNFdOiEAAACAKoQQAAAAQBVCCAAAAKAKMyEAAACgg2IoRFfphAAAAACqEEIAAAAAVQghAAAAgCrMhAAAAIAOemIoRDfphAAAAACqEEIAAAAAVQghAAAAgCqEEAAAAEAVBlMCAABAB8Vcyq7SCQEAAABUIYQAAAAAqhBCAAAAAFWYCQEAAAAdlBgK0U06IQAAAIAqhBAAAABAFUIIAAAAoAozIQAAAKCDYiREV+mEAAAAAKoQQgAAAABVCCEAAACAKkrTNK3+gotm393uL4AKDjzoxIFewlph2nnHDvQSAKAary8YKhbNOmNIT0247Mb7huR72r3+4nkD8u+mEwIAAACoQggBAAAAVCGEAAAAAKoQQgAAAABVDB/oBQAAAMCaqgzpsZv16YQAAAAAqhBCAAAAAFUIIQAAAIAqzIQAAACADsyE6C6dEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANBBiaEQ3aQTAgAAAKhCCAEAAABUIYQAAAAAqjATAgAAADroMRKiq3RCAAAAAFUIIQAAAIAqhBAAAABAFUIIAAAAoAqDKQEAAKCDEpMpu0knBAAAAFCFEAIAAACoQggBAAAAVGEmBAAAAHRQjIToKp0QAAAAQBVCCAAAAKAKIQQAAABQhZkQAAAA0EGJoRDdpBMCAAAAqEIIAQAAAFQhhAAAAACqMBMCAAAAOugxEqKrdEIAAAAAVQghAAAAgCqEEAAAAEAVQggAAACgCoMpAQAAoIMSkym7SScEAAAAUIUQAgAAAKhCCAEAAABUYSYEAAAAdFCMhOgqnRAAAABAFUIIAAAAoAohBAAAAFCFmRAAAADQgZEQ3aUTAgAAAKhCCAEAAABUIYQAAAAAqlgrZkJ8cv89s+n4bdLX15sNnrd53nLkJzJ63fXyyML7c+m5p+VtHz5+tfc/7sC98ulpl61y+U3XXpmNx22VTbbcuqWVDx5q3K7HZpyWG+bMz4jhw7Kstzdf/d61Of2rV6RpmoFe2pBiP65Dndunxu1T4zrUuV1eX7RPjYeGnmIqRDetFZ0QI0aOzJEnn5OjTjkvY8aun2suvzhJsv6GG/f75LU6N113VRbMu71Lqxzc1LhdixYvzcsOOCm77Xdi9j78jPzVyyfl2He/fqCXNeTYj+tQ5/apcfvUuA51bpfXF+1TY1jVajshSinvT/Kdpml+W2k9rdtqh0m5587bkiQPLrg7X/ncMTnqlPOyZPHj+da/nZT75t+ZTbaYkAfvuyd/fehR2XLiTkmSH11wdm6ZeXVGjByZtx99Yh64d35unvHT3H7T7FzxrWl524ePz0abbTGQm7bGUON23ffgYznihAty1fkfzWfO/EFGjRye0z5xQF40aXyW9fbmY6d8Oz+ZcWu+c/p78g+nfTc33Do/V1/wsVxyxex89qzL8qn3vjF33r0wc++8P588/A154KHHMmni5pn1q9/m4GP/Y6A3b41hP65Dndunxu1T4zrUuV1eX7RPjWG5/johTkjys1LKlaWU95ZSnldjUW3p6+vNbTfMzPOnTF3lup9dfnFGj10v7//8l/OqfQ/M/NtuWXndksWPZ6vtJ+XIk8/J1s/fJdf9+NJM2PEF2WnK1Ox14OE58uRzPHmtoMZ13H7XA+npKdlkw/Vy+P6vSJK8+G//KX9/zHk5+/gDM2rk8EyfOSd7TN4u6627Tnp7+7L7LhOTJFN3nZjpM+cmSXbZccscffK3MnnfE7PNlhtn6q7bDtg2rUnsx3Woc/vUuH1qXIc61+H1RfvUGPoPIW5LsmWWhxG7JbmplHJZKeXvSynrdbpTKeWwUsqMUsqM/7zo/C4u99lZumRJTj/60Jx4yJvy+8cezXY7T1nlNnfcfH12nrpnkmTT8dtm0wkTV143bPiI7LTb7kmScdvukAfvu6fOwgcRNa7viVPTpu46MV/7/rVJkl/ffm/uvHthtp+wSabPnJuXv2hipk7eNj+88saMHTMyo9cZkQnjNsytdyxIksy48Y7cteChNE2T2bfMy/hxGw3U5qwR7Md1qHP71Lh9alyHOtfn9UX71HjwKUP0a6D0F0I0TdP0NU3zo6ZpDk0yLskXkuyV5QFFpzud1TTNlKZpprx2v7d3cbnPzhPnEx79hQvTu2xprrns4lVus7rRMMOGDUtZcbTo6elJX29vSysdvNS4rq232Ci9vU0WLHw0nebkzLjxjrxo0vjsMXm7XDVzTmbfPC+HvHmPzPrVH86uWrxk2crv+3r7MnzYWjEmpiP7cR3q3D41bp8a16HOdXl90T41hv5DiKf8X6NpmqVN01zSNM1bk4xvb1ntWGfM2Ox98Ptz1fcuTO+yZU+5buudXpjrr74iSbJg3u25986OGctKo0aPyeJFi1pZ62Clxu3beIOxOf3YA3Lmhf+bJLlq5twc8Iblfxnabvwm2WrzDfPr2xdk6bLezLv3oez72sm59vrfZPqsufnAO169so2PzuzHdahz+9S4fWpchzq3z+uL9qkxLNdfCLF/pyuaphmUR+5x22yfzSZMzC9/+t9Pufylr9snv3vkoZz2kUPyk4svyGbjJ2adMWNX+1g7T90zV17y9Zzx0XfmgXvuanPZg4oad9/oUSNyzdc/np9fdGy+f+b78uOrb86JX/xhkuSL3/hJhvX05LpvfCLTPndw3vWpaVmydPkLtOmz5mTBwkez6PGlmT5rbrbcbINMnzVnIDdl0LAf16HO7VPj9qlxHercfV5ftE+NYVWl7c+ovWj23YPiQ3D7+nrTu2xZRowclQfuuStfPuFD+eCp52f48BEDvbQhYzDX+MCDThzoJawVpp137EAvoV+DeT8eTNS5fWrcPjWuYzDX2esLhopFs84YyBEDrbtmzkOD4j3tM/Wy7Z47IP9uq/2IzrXJ0sWLc/ZxH0hfb2+apsmb3vmhQfHkNZioMUOB/bgOdW6fGrdPjetQZ6B1QzpiqU8nBPwJ/KWijsHQCQEA3eL1BUPFkO+EmDtEOyEmDkwnhDGqAAAAQBVCCAAAAKAKMyEAAACgg2IoRFfphAAAAACqEEIAAAAAVQghAAAAgCrMhAAAAIAOipEQXaUTAgAAAKhCCAEAAABUIYQAAAAAqjATAgAAADowEqK7dEIAAAAAVQghAAAAgCqEEAAAAEAVQggAAACgCoMpAQAAoBOTKbtKJwQAAABQhRACAAAAqEIIAQAAAFRhJgQAAAB0UAyF6CqdEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANBBMRKiq3RCAAAAAFUIIQAAAIAqhBAAAABAFWZCAAAAQAdGQnSXTggAAACgCiEEAAAAUIUQAgAAAKhCCAEAAABUYTAlAAAAdGIyZVfphAAAAACqEEIAAAAAVQghAAAAgCrMhAAAAIAOiqEQXaUTAgAAAKhCCAEAAABUIYQAAAAAqjATAgAAADooRkJ0lU4IAAAAoAohBAAAAFCFEAIAAACowkwIAAAA6MBIiO7SCQEAAABUIYQAAAAAqhBCAAAAAFUIIQAAAIAqDKYEAACATkym7CqdEAAAAEAVQggAAACgCiEEAAAAUIWZEAAAANBBMRSiq3RCAAAAAFUIIQAAAIAqhBAAAABAFWZCAAAAQAfFSIiu0gkBAAAAVCGEAAAAAKoQQgAAAABVmAkBAAAAHRgJ0V06IQAAAIAqhBAAAABAFUIIAAAAoAohBAAAAFCFwZQAAADQicmUXaUTAgAAAKhCCAEAAABUIYQAAAAAqjATAgAAADoohkJ0lU4IAAAAoAohBAAAAFCFEAIAAACowkwIAAAA6KAYCdFVOiEAAACAKoQQAAAAQBVCCAAAAKAKMyEAAACgAyMhuksnBAAAAFCFEAIAAABYRSllr1LKLaWUOaWUj/+R6w8qpdxXSvnFiq939veYTscAAAAAnqKUMizJvyV5bZJ5Sa4rpVzSNM1NT7vphU3TvO9PfVydEAAAAMDTvSTJnKZpbmuaZkmSryfZ5899UCEEAAAAdFKG6Ff/tkjy2yf9PG/FZU+3bynll6WUi0opW/X3oEIIAAAAWMuUUg4rpcx40tdhT7/JH7lb87Sfv5dk66Zpdk7yX0n+o7/fayYEAAAArGWapjkryVmrucm8JE/ubNgyyfynPcYDT/rxS0k+19/v1QkBAAAAPN11SbYvpWxTShmZ5IAklzz5BqWUzZ/045uS/Kq/B9UJAQAAAB2UP3GAwlDTNM2yUsr7klyeZFiSLzdNc2Mp5fgkM5qmuSTJ+0spb0qyLMnCJAf197hCCAAAAGAVTdP8IMkPnnbZp570/TFJjnkmj+l0DAAAAKAKIQQAAABQhdMxAAAAoIOydo6EaI1OCAAAAKAKIQQAAABQhRACAAAAqMJMCAAAAOjASIju0gkBAAAAVLFWdEJ8cv89s+n4bdLX15sNnrd53nLkJzJ63fXyyML7c+m5p+VtHz5+tfc/7sC98ulpl61y+U3XXpmNx22VTbbcuqWVDx5q3K7HZpyWG+bMz4jhw7Kstzdf/d61Of2rV6RpmoFe2pBiP65Dndunxu1T4zrUuV1eX7RPjWFVa0UnxIiRI3PkyefkqFPOy5ix6+eayy9Okqy/4cb9Pnmtzk3XXZUF827v0ioHNzVu16LFS/OyA07KbvudmL0PPyN/9fJJOfbdrx/oZQ059uM61Ll9atw+Na5Dndvl9UX71BhWtVZ0QjzZVjtMyj133pYkeXDB3fnK547JUaeclyWLH8+3/u2k3Df/zmyyxYQ8eN89+etDj8qWE3dKkvzogrNzy8yrM2LkyLz96BPzwL3zc/OMn+b2m2bnim9Ny9s+fHw22myLgdy0NYYat+u+Bx/LESdckKvO/2g+c+YPMmrk8Jz2iQPyoknjs6y3Nx875dv5yYxb853T35N/OO27ueHW+bn6go/lkitm57NnXZZPvfeNufPuhZl75/355OFvyAMPPZZJEzfPrF/9Ngcf+x8DvXlrDPtxHercPjVunxrXoc7t8vqifWoMy622E6KUMrKU8o5SymtW/Py2UsoZpZQjSikj6iyxe/r6enPbDTPz/ClTV7nuZ5dfnNFj18v7P//lvGrfAzP/tltWXrdk8ePZavtJOfLkc7L183fJdT++NBN2fEF2mjI1ex14eI48+RxPXiuocR233/VAenpKNtlwvRy+/yuSJC/+23/K3x9zXs4+/sCMGjk802fOyR6Tt8t6666T3t6+7L7LxCTJ1F0nZvrMuUmSXXbcMkef/K1M3vfEbLPlxpm667YDtk1rEvtxHercPjVunxrXoc51eH3RPjUepMoQ/Rog/Z2OcW6SNyY5qpQyLclbkvwsyYuTnN3y2rpm6ZIlOf3oQ3PiIW/K7x97NNvtPGWV29xx8/XZeeqeSZJNx2+bTSdMXHndsOEjstNuuydJxm27Qx687546Cx9E1Li+suLAMXXXifna969Nkvz69ntz590Ls/2ETTJ95ty8/EUTM3XytvnhlTdm7JiRGb3OiEwYt2FuvWNBkmTGjXfkrgUPpWmazL5lXsaP22igNmeNYD+uQ53bp8btU+M61Lk+ry/ap8as7foLIV7YNM3+Sd6c5HVJ9muaZlqSg5NM7nSnUsphpZQZpZQZ/3nR+d1b7bP0xPmER3/hwvQuW5prLrt4ldusbjTMsGHDUlYcLXp6etLX29vSSgcvNa5r6y02Sm9vkwULH135RPZ0M268Iy+aND57TN4uV82ck9k3z8shb94js37125W3Wbxk2crv+3r7MnzYWjEmpiP7cR3q3D41bp8a16HOdXl90T41hv5DiJ5Sysgk6yUZk+Q5Ky4flaTj6RhN05zVNM2UpmmmvHa/t3dnpV2wzpix2fvg9+eq712Y3mXLnnLd1ju9MNdffUWSZMG823PvinMOV2fU6DFZvGhRK2sdrNS4fRtvMDanH3tAzrzwf5MkV82cmwPesPwvQ9uN3yRbbb5hfn37gixd1pt59z6UfV87Odde/5tMnzU3H3jHq1e28dGZ/bgOdW6fGrdPjetQ5/Z5fdE+NYbl+gshzklyc5JfJDk2yTdLKV9Kcl2Sr7e8tlaM22b7bDZhYn750/9+yuUvfd0++d0jD+W0jxySn1x8QTYbPzHrjBm72sfaeeqeufKSr+eMj74zD9xzV5vLHlTUuPtGjxqRa77+8fz8omPz/TPflx9ffXNO/OIPkyRf/MZPMqynJ9d94xOZ9rmD865PTcuSpctfoE2fNScLFj6aRY8vzfRZc7PlZhtk+qw5A7kpg4b9uA51bp8at0+N61Dn7vP6on1qPDSUIfrfgNWzv8+oLaWMS5KmaeaXUp6b5DVJ7mya5to/5RdcNPvuQfEhuH19veldtiwjRo7KA/fclS+f8KF88NTzM3z4oJu/ucYazDU+8KATB3oJa4Vp5x070Evo12DejwcTdW6fGrdPjesYzHX2+oKhYtGsMwZwzGH7br130aB4T/tMbb/p6AH5d+v3Izqbppn/pO8fSnJRqysaIEsXL87Zx30gfb29aZomb3rnhwbFk9dgosYMBfbjOtS5fWrcPjWuQ50BBpd+OyH+XIOlEwJWx18q6hgMnRAA0C1eXzBU6IQYnNbYTggAAABYW3X6JBOeHZ/lAgAAAFQhhAAAAACqEEIAAAAAVZgJAQAAAB0YCdFdOiEAAACAKoQQAAAAQBVCCAAAAKAKIQQAAABQhcGUAAAA0InJlF2lEwIAAACoQggBAAAAVCGEAAAAAKowEwIAAAA6KIZCdJVOCAAAAKAKIQQAAABQhRACAAAAqMJMCAAAAOigGAnRVTohAAAAgCqEEAAAAEAVQggAAACgCjMhAAAAoAMjIbpLJwQAAABQhRACAAAAqEIIAQAAAFQhhAAAAACqMJgSAAAAOjGZsqt0QgAAAABVCCEAAACAKoQQAAAAQBVmQgAAAEAHxVCIrtIJAQAAAFQhhAAAAACqEEIAAAAAVZgJAQAAAB0UIyG6SicEAAAAUIUQAgAAAKhCCAEAAABUYSYEAAAAdGAkRHfphAAAAACqEEIAAAAAVQghAAAAgCqEEAAAAEAVBlMCAABAB8Vkyq7SCQEAAABUIYQAAAAAqhBCAAAAAFWYCQEAAAAdGQrRTaVpmlZBGbK6AAAPuElEQVR/wUWz7273FwAAADBg9ttl8yH9Ln3eg0uG5HvaLTcYOSD/bk7HAAAAAKoQQgAAAABVmAkBAAAAHZQhfbJJfTohAAAAgCqEEAAAAEAVQggAAACgCjMhAAAAoAMjIbpLJwQAAABQhRACAAAAqEIIAQAAAFQhhAAAAACqMJgSAAAAOigmU3aVTggAAACgCiEEAAAAUIUQAgAAAKjCTAgAAADooMRQiG7SCQEAAABUIYQAAAAAqhBCAAAAAFWYCQEAAACdGAnRVTohAAAAgCqEEAAAAEAVQggAAACgCjMhAAAAoAMjIbpLJwQAAABQhRACAAAAqEIIAQAAAFQhhAAAAACqMJgSAAAAOigmU3aVTggAAACgCiEEAAAAUIUQAgAAAKjCTAgAAADooMRQiG7SCQEAAABUIYQAAAAAqhBCAAAAAFWYCQEAAACdGAnRVTohAAAAgCqEEAAAAEAVQggAAACgCjMhAAAAoAMjIbpLJwQAAABQhRACAAAAqEIIAQAAAFQhhAAAAACqMJgSAAAAOigmU3aVTggAAACgCiEEAAAAUIUQAgAAAKhirQghPrn/njn96ENz6ocPyldOOiaLfvdokuSRhffna6d8qt/7H3fgXn/08puuvTIL5t3ezaUOWmrcPjVunxrXoc7tU+P2qXEd6tw+NW7P7x99OKcffWhOP/rQfPZdb85J795v5c/Lli3t2u956P4F+fq/Hte1x2NVZYj+N1DWihBixMiROfLkc3LUKedlzNj1c83lFydJ1t9w47ztw8c/68e96bqr1vqD6xPUuH1q3D41rkOd26fG7VPjOtS5fWrcnjHrPSdHnnxOjjz5nLzktW/KHm/cb+XPw4eP6Pf+fX29f9Lvee7Gm+SAD376z10uVNPvp2OUUiYmeXOSrZIsS3Jrkguapnm45bW1YqsdJuWeO29Lkjy44O585XPH5KhTzsuSxY/nW/92Uu6bf2c22WJCHrzvnvz1oUdly4k7JUl+dMHZuWXm1RkxcmTefvSJeeDe+bl5xk9z+02zc8W3puVtHz4+G222xUBu2hpDjdunxu1T4zrUuX1q3D41rkOd26fG9cz8n8tyzeUXp3fZ0ozf8QX560OOStP05Z8O3Scv2+vNuXX2jOx98JG54F8+ncl/uVduu+Hn6evryz7v+nB+9LWzsvDe+XnFPm/Li1+zdx64Z16+dsqnc+TJ5wz0ZsGfZLWdEKWU9yc5M8k6SV6cZHSWhxFXl1Je2frquqyvrze33TAzz58ydZXrfnb5xRk9dr28//Nfzqv2PTDzb7tl5XVLFj+erbaflCNPPidbP3+XXPfjSzNhxxdkpylTs9eBh+fIk89xYF1Bjdunxu1T4zrUuX1q3D41rkOd26fG9dx752256dor8+7PnJEjTz4nfb29uf6n/50kefz3v8u4bXbIez97Zsbv8BdJkg2et1kOP/Hfs9X2k/KdM/85f/eRE/LuE87If10odGBw6q8T4l1Jdm2apreU8i9JftA0zStLKV9M8t0kk//YnUophyU5LEkO++Q/57X7vb2ba37Gli5ZktOPPjQP3XdPxm27Y7bbecoqt7nj5usz9Q37JUk2Hb9tNp0wceV1w4aPyE677Z4kGbftDpnzyxl1Fj6IqHH71Lh9alyHOrdPjdunxnWoc/vUuL451/888+beki98/N1JkmVLluQ5G22SZHk9J73k/zzl9k8EQ5uO3zZ9vb0Zuc7ojFxndEpPTxY//vu6i19LlYEbnzAk/SkzIZ4IKkYlWS9Jmqa5M0nHE5mapjmraZopTdNMGegAIvnDuW5Hf+HC9C5bmmsuu3iV2zSruf+wYcNSVux5PT096ev9087PWpuocfvUuH1qXIc6t0+N26fGdahz+9R4ADTJbq96/cr5EB88dVr23O8dSZb/e5SnveMdNmL5265SSoaP+MNbsFKKejMo9RdCnJ3kulLKWUmuTnJGkpRSnpdkYctr67p1xozN3ge/P1d978L0Llv2lOu23umFuf7qK5IkC+bdnntXnA+3OqNGj8niRYtaWetgpcbtU+P2qXEd6tw+NW6fGtehzu1T43om7rxbbrj6f/K7Rx5KsvxTNB66/94BXhXUs9oQommaU5O89f+3d78xlt1lHcC/j7uFskWE1D9duq0t2BAbItI0RWmyMa2QVkkLpCRtoiEiWWPAtFQk6AsN4hsS4x+iMWnarVWwFbdgNqaBkqCCL6ilhUprQdeKdPvHVmypBaXd7eOLOWS3m53dLb3nnM7h80lu5t47J3e+88zNnbnP/H7PSXJzkjd297XD/Q939/YJ8q3cS08/Iyf98MvzT8O+q297zesvzjceezQffPfb8um/vj4nnfryHL/lhUd8rB977Xn5zO4b8kfveXu+9uB9Y8beUNR4fGo8PjWehjqPT43Hp8bTUOfxqfE0Tjr1ZTnvLW/Nzvf/aj747rfl2t/5tTz+6CNzx4LJVPeRFlg9e7vueGDcL7AiTz21P/v37ctxz3t+vvbgfdn5/ivzrj/80DGdPodjo8bjU+PxqfE01Hl8ajw+NZ6GOo9PjTmaS161ddFTEx755v4N8Z72mXrJlk2z/NyOeorO7xZPfutbufp9V+Sp/fvT3bno7Vd6YV0xNR6fGo9PjaehzuNT4/Gp8TTUeXxqDKySlRAAAAB8x6yE2JjmWglxLGfHAAAAAHjWNCEAAACASZgJAQAAAOuoRW82mZ6VEAAAAMAkNCEAAACASWhCAAAAAJMwEwIAAADWUTEUYpWshAAAAAAmoQkBAAAATEITAgAAAJiEmRAAAACwjjISYqWshAAAAAAmoQkBAAAATEITAgAAAJiEmRAAAACwDiMhVstKCAAAAGASmhAAAADAJDQhAAAAgEloQgAAAACTMJgSAAAA1mMy5UpZCQEAAABMQhMCAAAAmIQmBAAAADAJMyEAAABgHWUoxEpZCQEAAABMQhMCAAAAmIQmBAAAADAJMyEAAABgHWUkxEpZCQEAAABMQhMCAAAAmIQmBAAAADAJMyEAAABgHUZCrJaVEAAAAMAkNCEAAACASWhCAAAAAJPQhAAAAAAmYTAlAAAArMdkypWyEgIAAACYhCYEAAAAMAlNCAAAAGASZkIAAADAOspQiJWyEgIAAACYhCYEAAAAMAlNCAAAAGASmhAAAACwjqplXo7te68LqurLVbWnqt57mM8/v6r+cvj8LVV12tEeUxMCAAAAeJqq2pTkj5NcmOTMJJdV1ZmHHPaLSR7p7h9J8vtJPnC0x9WEAAAAAA51TpI93X1Pdz+R5IYkFx9yzMVJrhuu70pyftWR11loQgAAAACHOjnJvQfd3jvcd9hjuntfkq8nOfFID7p5hQEP65JXbd1wJ1Wtqh3dfdXcOZZMjcenxtNQ5/Gp8fjUeBrqPD41Hp8aj0+Nn3uO35wN9572WFTVjiQ7DrrrqkOee4f7vvvQhzmGY57GSojD23H0Q3iW1Hh8ajwNdR6fGo9PjaehzuNT4/Gp8fjUmEl091XdffZBl0ObX3uTnHLQ7W1J7l/vmKranOT7kvz3kb6uJgQAAABwqFuTnFFVp1fV85JcmmT3IcfsTvLW4folST7V3UdcCTH6dgwAAABgY+nufVX1ziSfSLIpyc7uvquqfjvJ57p7d5Jrkvx5Ve3J2gqIS4/2uJoQh2cP1vjUeHxqPA11Hp8aj0+Np6HO41Pj8anx+NSY54zuvinJTYfc95sHXf+/JG95Jo9ZR1kpAQAAALASZkIAAAAAk9CEOEhVXVBVX66qPVX13rnzLFFV7ayqh6rqzrmzLFVVnVJVf1tVd1fVXVV1+dyZlqaqjq+qf6yqO4Yav2/uTEtVVZuq6vNV9TdzZ1mqqvpKVX2xqr5QVZ+bO88SVdWLq2pXVX1peG3+ybkzLUlVvWJ4/n778lhVXTF3riWqqncNv/furKrrq+r4uTMtTVVdPtT3Ls9jlsp2jEFVbUryL0lel7XTjNya5LLu/udZgy1MVW1P8niSP+vuV86dZ4mqamuSrd19e1V9b5LbkrzRc3l1qqqSnNDdj1fVcUn+Icnl3f3ZmaMtTlVdmeTsJC/q7jfMnWeJquorSc7u7v+aO8tSVdV1ST7T3VcP08W3dPejc+daouHvufuSvKa7/2PuPEtSVSdn7ffdmd39v1X1kSQ3dfefzptsOarqlUluSHJOkieSfDzJL3f3v84aDFbMSogDzkmyp7vv6e4nsvYCcPHMmRanuz+do5w3lmenux/o7tuH6/+T5O4kJ8+ball6zePDzeOGi47uilXVtiQ/m+TqubPAd6qqXpRke9amh6e7n9CAGNX5Sf5NA2I0m5O8oKo2J9mS5P6Z8yzNjyb5bHd/s7v3Jfn7JG+aOROsnCbEAScnufeg23vjjRsbXFWdluTVSW6ZN8nyDNsEvpDkoSSf7G41Xr0/SPKeJE/NHWThOsnNVXVbVe2YO8wCvSzJw0muHbYWXV1VJ8wdasEuTXL93CGWqLvvS/K7Sb6a5IEkX+/um+dNtTh3JtleVSdW1ZYkP5PklJkzwcppQhxQh7nPfzbZsKrqhUluTHJFdz82d56l6e793f3jSbYlOWdYQsmKVNUbkjzU3bfNneW7wLndfVaSC5O8Y9g2x+psTnJWkj/p7lcn+UYSc6dGMGx1uSjJX82dZYmq6iVZWyV8epKXJjmhqn5u3lTL0t13J/lAkk9mbSvGHUn2zRoKRqAJccDePL3TuC2WmLFBDXMKbkzy4e7+6Nx5lmxYVv13SS6YOcrSnJvkomFewQ1JzquqD80baZm6+/7h40NJPpa17Ymszt4kew9aLbUra00JVu/CJLd393/OHWShfjrJv3f3w939ZJKPJnntzJkWp7uv6e6zunt71rYwmwfB4mhCHHBrkjOq6vShk35pkt0zZ4JnbBiaeE2Su7v79+bOs0RV9QNV9eLh+guy9ofZl+ZNtSzd/evdva27T8va6/Gnutt/3Fasqk4YBthm2CLw+qwtB2ZFuvvBJPdW1SuGu85PYlDwOC6LrRhj+mqSn6iqLcPfGudnbe4UK1RVPzh8PDXJm+M5zQJtnjvAc0V376uqdyb5RJJNSXZ2910zx1qcqro+yU8l+f6q2pvkt7r7mnlTLc65SX4+yReHmQVJ8hvdfdOMmZZma5Lrhins35PkI93tFJJsRD+U5GNr7yeyOclfdPfH5420SL+S5MPDPznuSfILM+dZnGH//OuS/NLcWZaqu2+pql1Jbs/aFoHPJ7lq3lSLdGNVnZjkySTv6O5H5g4Eq+YUnQAAAMAkbMcAAAAAJqEJAQAAAExCEwIAAACYhCYEAAAAMAlNCAAAAGASmhAAAADAJDQhAAAAgEloQgAAAACT+H8NkmCPvILkDgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Length of Episode: 441.8958333333333\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epochs Count [341, 59, 48]\n",
      "Difference(MSE) Value [1.3008049174946797e-17, 3.9767320257852284e-19, 3.754744876536313e-19]\n"
     ]
    }
   ],
   "source": [
    "blocks = [(5,i) for i in range(1,10)]\n",
    "\n",
    "epochs_count = []\n",
    "diff_count = []\n",
    "cumm_rewards = []\n",
    "for i in [0,3,5]:\n",
    "    print(\"Planning size:\", i)\n",
    "    game = DynaMaze(10, i, (9,9), blocked_blocks = blocks, mode_type = 'DQ', verbose=False)\n",
    "    diff, epochs, avg_episode_length, total_rewards = game.play(epochs=1000, threshold=1e-16, changed=True)\n",
    "    print(\"Average Length of Episode:\", avg_episode_length)\n",
    "    epochs_count.append(epochs)\n",
    "    diff_count.append(diff)\n",
    "    cumm_rewards.append(np.cumsum(total_rewards))\n",
    "\n",
    "plt.plot(cumm_rewards[0])\n",
    "plt.plot(cumm_rewards[1])\n",
    "plt.plot(cumm_rewards[2])\n",
    "plt.xlabel('Planning Size')\n",
    "plt.ylabel('Cummulative Reward Sum')\n",
    "plt.show()\n",
    "plt.plot(epochs_count)\n",
    "plt.xlabel('Step Size')\n",
    "plt.ylabel('Epochs taken for Converging')\n",
    "plt.show()\n",
    "plt.plot(diff_count)\n",
    "plt.xlabel('Step Size')\n",
    "plt.ylabel('Change in Q function(MSE)')\n",
    "plt.show()\n",
    "\n",
    "print('Epochs Count', epochs_count)\n",
    "print('Difference(MSE) Value', diff_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Deductions/Observations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ul>\n",
    "    <li>DQ Learning: The larger the planning steps lesser the epochs are required for the convergence.</li>\n",
    "    <li>DQ+ Learning: The larger the planning steps lesser the epochs are required for the convergence.</li>\n",
    "    <li>DQ Learning: The number of epochs in shortcut maze is greater than the blocking maze</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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