main.ipynb

{
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   "source": [
    "<center><h1>Implementation of SaShiMi</h1><h3>From paper <a href=\"https://arxiv.org/abs/2202.09729\">It's Raw! Audio Generation with State-Space Models</a></h3></center>\n",
    "\n",
    "**Paper authors:** Karan Goel, Albert Gu, Chris Donahue, Christopher Ré\n",
    "\n",
    "**Code authors:** İlker Işık (e238051@metu.edu.tr), Muhammed Can Keleş (e265013@metu.edu.tr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b26ecce",
   "metadata": {},
   "source": [
    "# SaShiMi Architecture\n",
    "\n",
    "SaShiMi is a deep-learning model designed for generating raw audio. It is built around the recently introduced S4 model (from paper <a href=\"https://arxiv.org/abs/2111.00396\">\"Efficiently Modeling Long Sequences with Structured State Spaces\"</a>), which is designed for sequence-to-sequence processing tasks. In SaShiMi, the authors modify S4 for better stability and achieve state-of-the-art results on multiple audio domains (music and speech), with less parameters and shorter inference time.\n",
    "\n",
    "\n",
    "Here, we borrow Figure 1 from the paper:\n",
    "\n",
    "<img src=\"images/sashimi-architecture.png\" alt=\"SaShiMi Figure\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a7944df",
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   "source": [
    "## S4 Block\n",
    "\n",
    "The main component of SaShiMi architecture is the **S4 Block**. The paper explains the details of S4 block in Appendix A.2.\n",
    "\n",
    "### High-level Architecture\n",
    "\n",
    "First pass:\n",
    "1. Input\n",
    "2. LayerNorm\n",
    "3. S4 Layer\n",
    "4. GELU\n",
    "5. Linear\n",
    "6. Residual connection from 1\n",
    "\n",
    "Second pass:\n",
    "1. Output of the first pass\n",
    "2. LayerNorm\n",
    "3. Linear\n",
    "4. GELU\n",
    "5. Linear\n",
    "6. Residual connection from 1\n",
    "\n",
    "All linear layers are position-wise, i.e., they operate on the signal dimensions, not\n",
    "the time dimension."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f38121fd",
   "metadata": {},
   "source": [
    "## S4 Layer\n",
    "\n",
    "At a high-level, S4 layer can be thought of as a mapping from a 1D sequence to another 1D sequence. Some of the important properties of S4:\n",
    "- It's causal. The output at index $i$ depends on inputs from $0$ to $i-1$.\n",
    "- It can be computed using either convolution or recurrence.\n",
    "    - We use convolution during training and recurrence during sampling.\n",
    "- Although it's 1D to 1D, we stack multiple S4 Layers together to process multidimensional signals.\n",
    "    - In this case, different dimensions don't interact with each other.\n",
    "    - Linear layers compute interactions between different signal dimensions but they cannot handle interactions through time. Therefore, linear layers complement S4 layers nicely.\n",
    "- S4 doesn't provide non-linearity by itself. It needs to be combined with activation functions.\n",
    "\n",
    "For more information, you can read the [paper](https://arxiv.org/abs/2202.09729) or the source code of our S4 implementation. Our code contains many docstrings and comments."
   ]
  },
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   "source": [
    "## State Space Models\n",
    "\n",
    "S4 stands for **structured state-space model**. But what is a state space model?\n",
    "\n",
    "A state space model (SSM) is a new class of deep neural network that exhibits the properties of both CNNs and RNNs. \n",
    "In continuous time, SSM can be defined as follows:\n",
    "\n",
    "$$h'(t) = Ah(t) + Bx(t)$$\n",
    "$$y(t) = Ch(t) + Dx(t)$$\n",
    "\n",
    "We can discretize the matrices $A$, $B$, $C$ and $D$ as follows:\n",
    "\n",
    "$$\\overline{A} = (I - \\Delta/2 \\cdot A)^{-1}(I + \\Delta/2 \\cdot A)$$\n",
    "\n",
    "Discretization formulas for $B$, $C$ and $D$ are similar. Once we obtain $\\overline{A}$, $\\overline{B}$, $\\overline{C}$ and $\\overline{D}$, the discretized system is:\n",
    "\n",
    "$$h_{k} = \\overline{A} h_{k-1} + \\overline{B} x_k$$\n",
    "$$y_k = \\overline{C} h_k + \\overline{D} x_k$$\n",
    "\n",
    "This discretized system is evaluated in a recurrent manner. But we can compute the convolutional kernel $\\overline{K}$:\n",
    "\n",
    "$$\\overline{K} =\n",
    "  (\\overline{C}\\overline{B}, \\overline{C}\\overline{A}\\overline{B}, \\overline{C}\\overline{A}^2\\overline{B}, \\ldots)$$\n",
    "\n",
    "And using $\\overline{K}$, computing $y$ from $x$ can be performed in a single convolution operation:\n",
    "\n",
    "$$y = \\overline{K} \\ast x$$"
   ]
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   "id": "0e1f91ae",
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   "source": [
    "## S4 Details\n",
    "\n",
    "Despite their theoretically attractive properties, SSMs deliver disappointing performance in practice. S4 was originally developed to overcome these deficiencies.\n",
    "\n",
    "S4 is a subset of SSM where the matrix $A$ is in _diagonal plus low-rank_ (DPLR) form, i.e., for a diagonal matrix $\\Lambda$,\n",
    "\n",
    "$$A = \\Lambda + p q^*$$\n",
    "\n",
    "Furthermore, in S4, the matrices $A$ (more specifically, $\\Lambda$, $p$ and $q$) and $B$ are initialized according to **HiPPO**. HiPPO stands for **High-order Polynomial Projection Operator**. The state space model defined by HiPPO creates a lossy summary of the signal processed so far.\n",
    "\n",
    "For more information on HiPPO, see the paper [HiPPO: Recurrent Memory with Optimal Polynomial Projections](https://arxiv.org/abs/2008.07669)."
   ]
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   "cell_type": "markdown",
   "id": "562e147c",
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   "source": [
    "## Contributions to S4\n",
    "\n",
    "In SaShiMi paper, the authors make several improvements to S4.\n",
    "\n",
    "When sampling, the recurrent representation of S4 is unstable. The authors observe the source of unstability using state space theory and provide a simple S4 reparameterization that ensures stability theorically. In particular, they change the formulation of $A$ from $A = \\Lambda + p q^*$ to\n",
    "\n",
    "$$A = \\Lambda - p p^*$$\n",
    "\n",
    "There's also a **bidirectional S4** variant presented in the paper, which is simply the concatenation of two S4 layers but one of them is run in reverse order. However, it obviously breaks causality and hence it's not used for autoregressive tasks. Thus, we won't implement it in this notebook."
   ]
  },
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   "cell_type": "markdown",
   "id": "1d05829c",
   "metadata": {},
   "source": [
    "## Up-Pool and Down-Pool\n",
    "\n",
    "The next components **up-pool** and **down-pool** are combinations of reshaping and a linear layer.\n",
    "\n",
    "In particular, for an input of shape $(T, H)$ where $T$ is the sequence length (sample count) and $H$ is the signal dimension, the **down-pool** is\n",
    "\n",
    "$$\n",
    "(T,H) \\xrightarrow{\\text{reshape}} (T/p, H \\cdot p) \\xrightarrow{\\text{linear}} (T/p, H \\cdot q)\n",
    "$$\n",
    "\n",
    "where $p$ is the pooling factor and $q$ is the expansion factor.\n",
    "\n",
    "**Up-pool** is simply the opposite operation:\n",
    "\n",
    "$$\n",
    "(T/p, H \\cdot q) \\xrightarrow{\\text{linear}} (T/p, H \\cdot p) \\xrightarrow{\\text{reshape}} (T,H)\n",
    "$$\n",
    "\n",
    "They use $p=4$ and $q=2$ in the paper."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c721b990",
   "metadata": {},
   "source": [
    "Note that we use our own `Sequential` implementation instead of `torch.nn.Sequential`. Our implementation inherits `torch.nn.Sequential` and accounts for the S4 layer when we want to run it in recurrent mode. `Residual` is the same as `Sequential` but it applies a residual connection from the beginning to the end, i.e., $Residual(x) = x + Sequential(x)$."
   ]
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  {
   "cell_type": "markdown",
   "id": "ec6e85f1",
   "metadata": {},
   "source": [
    "# Prelude\n",
    "\n",
    "Before starting, follow the instructions in README and make sure that:\n",
    "1. The required libraries given in README are installed.\n",
    "2. You have downloaded the datasets and pretrained models.\n",
    "\n",
    "In the following code blocks, we will setup, import modules, select device, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "132b48c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "# Built-in IPython extension to reload modules when updated.\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c1eee2fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using PyKeOps Cauchy kernel.\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "import matplotlib.pyplot as plt\n",
    "from torch.utils.data import DataLoader\n",
    "from torchvision import datasets, transforms\n",
    "from tqdm.auto import tqdm\n",
    "import copy\n",
    "import IPython.display as ipd\n",
    "from torchaudio.functional import mu_law_encoding, mu_law_decoding\n",
    "from scipy.io import wavfile\n",
    "import os\n",
    "\n",
    "# Custom modules\n",
    "from sashimi import *\n",
    "from wav_dataset import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cd3b4d5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cuda')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "#device = torch.device(\"cpu\")\n",
    "device"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f56c5212",
   "metadata": {},
   "source": [
    "# Dataset\n",
    "\n",
    "The dataset is actually just the audio track of [this 4 hour piano video from YouTube](https://www.youtube.com/watch?v=EhO_MrRfftU). It's resampled at 16 kHz and divided into 1 minute WAV files. Thankfully, the authors of the paper have already done this step and uploaded the processed dataset [here on HuggingFace](https://huggingface.co/datasets/krandiash/youtubemix)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2f898191",
   "metadata": {},
   "outputs": [],
   "source": [
    "DURATION = 8\n",
    "train_dataset = YoutubeMixDataset(\"./datasets/youtube-mix/train\", duration=DURATION, device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3082a6e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1589"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cd22d3e1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Check sample rate\n",
    "assert train_dataset.sample_rate == 16000\n",
    "\n",
    "x, y = train_dataset[0]\n",
    "assert list(x.size()) == [DURATION * 16000]\n",
    "assert list(y.size()) == [DURATION * 16000]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6843dfa",
   "metadata": {},
   "source": [
    "`y` contains all samples 0 to N in the sound file, each sample is an integer between 0 and 255. `x`, on the other hand, contains samples 0 to N-1, each sample is an integer between 0 to 255. For each input sample $i$, the network predicts the probabilities for the next sample ($i+1$) in 8-bits using the inputs from $0$ to $i$."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06857041",
   "metadata": {},
   "source": [
    "Let's listen to one of the sound files in the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdb35008",
   "metadata": {},
   "outputs": [],
   "source": [
    "ipd.Audio(mu_law_decoding(x, 256).cpu().numpy(), rate=16000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "471b3cdf",
   "metadata": {},
   "source": [
    "# The Model\n",
    "\n",
    "Here, we define the SaShiMi model with the hyperparameters given in Appendix C.2.1. We use a block count of 2 instead of 8 in the overfitting test for faster training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7c2c24c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.manual_seed(42)\n",
    "\n",
    "model = SaShiMi(\n",
    "    input_dim=1,\n",
    "    hidden_dim=64,\n",
    "    output_dim=256,\n",
    "    state_dim=64,\n",
    "    sequence_length=16000*DURATION,\n",
    "    block_count=2,\n",
    "    encoder=Embedding(256, 64),\n",
    ").to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c61e761",
   "metadata": {},
   "source": [
    "For simplicity, they don't train the low-rank term $pp^*$, the $B$ matrix and the timescale $\\Delta$. In TODO experiments, we do the same, but we still train $\\Delta$ because they don't provide the initial value for that parameter.\n",
    "\n",
    "However, we found that freezing these parameters is highly detrimental in overfitting test. Therefore, we won't do that here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "1567ee43",
   "metadata": {},
   "outputs": [],
   "source": [
    "for module in model.modules():\n",
    "    # isinstance doesn't work due to automatic reloading\n",
    "    if type(module).__name__ == S4Base.__name__:\n",
    "        module.B.requires_grad = False\n",
    "        module.P.requires_grad = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de218767",
   "metadata": {},
   "source": [
    "Let's inspect the number of parameters in our model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f4704a5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total parameters: 1347078\n",
      "Parameters to be learned: 1345542\n"
     ]
    }
   ],
   "source": [
    "print(\"Total parameters:\", sum([i.nelement() for i in model.parameters()]))\n",
    "print(\"Parameters to be learned:\", sum([i.nelement() if i.requires_grad else 0 for i in model.parameters()]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52b170ff",
   "metadata": {},
   "source": [
    "# Training the Model: Overfitting Test\n",
    "\n",
    "In accordance with the well-respected 796 tradition, we first test whether the model works by trying to overfit into a single example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "fa19c2e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = train_dataset[0]\n",
    "overfit_dataset = [(x, y)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5bdd8e76",
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\n",
    "criterion = torch.nn.CrossEntropyLoss()\n",
    "losses = []"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "744f44c9",
   "metadata": {},
   "source": [
    "You can run the following block multiple times to train the same model without restarting:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6e353cfc",
   "metadata": {
    "scrolled": false
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.001631121034733951"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.train()\n",
    "for epoch in tqdm(range(2000), leave=False):\n",
    "    for x, y in overfit_dataset:\n",
    "        y_hat = model(x)\n",
    "        loss = criterion(y_hat.view(-1, 256), y.view(-1))\n",
    "\n",
    "        loss_val = loss.detach().cpu().item()\n",
    "        losses.append(loss_val)\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "plt.plot(losses)\n",
    "plt.show()\n",
    "losses[-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6a49a51",
   "metadata": {},
   "source": [
    "Note that even though the loss seems flat in the last half of the training, it makes a huge difference while sampling."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6aeec02",
   "metadata": {},
   "source": [
    "## Sampling\n",
    "\n",
    "The following method will autoregressively sample from the given model `m`. It can optionally use a priming signal to start with. When `maxp` is `True`, it will always choose the value with highest probability instead of random sampling."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee81581b",
   "metadata": {},
   "source": [
    "Let's generate a sample and listen to it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "bfc9099a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/128000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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AAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAAYABgD6//r/+v/6/wYABgAGAAYABgAGAAYABgAGAPr/+v/6//r/+v/6//r/BgAGAAYABgAGAAYABgAGAAYABgAGAAYABgAGAPr/+v/6//r/+v/6//r/+v/6//r/BgAGAAYA+v8GAPr/FADd/yL/d//d/wYAMgBTAFMAZAB2AHYAdgB2AGQAUwBCADIABgD6/+z/zv/O/77/vv/O/1MAKAGbAm8EcQblB+UHcQaJA0IAOf1++hv43vR68Gnsduhc54PpMPEO+84FRRCKFz4cPhykGNsRKgmbAc77YPYw8Uztaewl7obyMvryBIYPfRbKGaQYtBIbCsgAj/lk9WT1YPYb+Dj5j/l++iP+bwRBDLQSexXbEaAJ3fz07sLjm9yb3BXhg+lk9XYAoAkMEX0W/RqNHesePhyDFBsKCfxM7RXhm9yb3APlevBF/qAJDBGDFHsVexWXE4YPGwojAw77hvJ96zbmA+WD6TDxfvpyAoIHoAmgCSoJKgkbCiILIgu5CFUDd/xk9bvvJe568Nb2of5xBkEMIQ56DSILnApBDIYPtBK0EoYPuQhj/2D2u+9964Xqaez07obyZPU4+YP+8gTaDHsVPhzrHo0dihchDlUDOPnf8Uztfetp7LvvJvOz9wD+8gRBDNsRexV9FpcTQQxyAkf3TO025nPic+ID5XboTO0m84/5yABNCNAOtBK0EtAOyAaR+3rwXOfC48Ljduj07uX1QvybAioJRRB9Fv0ajR3KGbQSggcy+kztA+UV4cLjg+nf8UL8zgV6DZcTihekGH0W2xGvC1UDj/n07jbmc+Jz4nboJvPd/9oMpBhZILkmSSxPLk8uWiplI4oXKgni+UztA+Vz4jbmJe5++G8EIQ57Ff0a6x5ZIFkg/RqXE+UH3fh26EfZX82pyKnIlM/62oPpG/j3A3oNexX9Go0d/Rp9FtoMAP5M7Snet9OUz7HRgdfC4zDxd/9BDH0WjR3XIWUjWSD9GkUQSgIm88LjR9mx0bHRptUp3oPpYPZKAkEMgxT9GlkgZSNlI+sefRYqCeL5aezC4xXhwuNM7Tj5cQbbEf0aZSN/KFoqSSx/KNchgxT3A7/zXOen3yneFeGF6tb2rwRFEMoZWSBlIwYlBiVZIIoXQQy2/fTuwuOb3Prap99c54byjv2CBwwRpBjrHtchZSNZIP0a0A7IACbzXOen36ffc+KD6YbyzvtvBBsKIgu5CDgFQwF3/N70heqn36bVlM8SyxLLlM+B1wPlUfTHAtoMtBJ9FooXexUMEeUHzvu77wPlm9ym1abVR9kD5VH0xwIhDoMUfRaDFAwRnAokAuX1XOeB1ybGzbeTrfmlk63tul/NwuMb+BsKihfXIX8oWipaKrkm1yH9GoMU0A4hDpcTWSChMjNIFV4xcH96/3//f/9/O3VdaxVeM0ihMo0dnAoM/d703/G/88j6rwTQDooX/Ro+HP0apBjbEcgGZPUV4ZTPyMDNt8237bomxrfTwuPf8VH7DgGCBaAJQQwqCSL/u+8p3rHRqcgmxibGEsux0frawuOF6iXuevDf8YbyevB26PraqcjNt9uprp2uneuhk63rvbfTduh++k0I2xGKF/0a/Rp9FtoMzv8m84PpXOd962T1mwKXE7km2jkzSCVWFV4VXhVeB1ptUhVCbDD9GiMH1vZp7Hbofeu/82P/2gz9GgYlWipJLFoqBiX9GnoNRf5M7afft9NfzV/NsdFH2Xbo4vmvC8oZ1yEGJQYlZSPXIY0dfRYhDokDOPm773boA+UD5X3r3vTY/nEGuQhxBsgAfvi77zbmm9ym1V/NEsupyF/Nt9Mp3kztZf7QDv0aWSDXIVkgjR0+HMoZiheXE9AOnAq5CJwKhg+kGGUjbDB6PBVCE0UVQno87jS5JsoZGwri+YXqKd5H2UfZp9+D6eX1uwEbCiEOIQ4qCZsCfvow8TbmR9mpyO26IrGTrSKxzbcmxoHXduh++HEGDBHKGY0dWSDrHooXrwsO+4Pp+tqUzxLLX82x0fraA+VM7WT1Dvut//cDIwdNCCMHmwLI+jDxdujC43PiA+WF6ibzZf25CIMUWSBaKu40ejw4Pzg/ejyhMn8o6x59FgwRhg+0EqQYWSB/KGwwoTLuNO40oTJPLloqZSM+HIMUQQzyBL3+Mvpg9r/zv/Nk9Rv4fvri+WD2MPF96zbmFeFH2ZTPJsbrvc23zbftusjAX8362nbov/Pi+VH7OPne9Lvvhepz4kfZX80mxuu97brtusjAEsuB1zbmhvJ3/L4DKglBDHoNrwsjB4r/YPZp7APlc+Jc54bycgKDFLkm7jQ4PzNIdkt2SzNIE0V6PGwwBiX9GtsRQQwbCq8LRRB9Fj4c1yEGJX8oSSxPLk8uSSxlI6QYKgky+vTuduh26H3revBk9cj6ZAAeBiIL0A5FENAOGwoAAmD2heoV4fra+tqn3zbmaeww8d70YPbW9uX1UfTf8UztNub62pTPhsPtuoq0irTtuobDlM8p3kzt4vmvBCEOexXKGcoZfRbQDh4GRf7i+Y/53fz3AyEOyhm5JqEy2jkVQhNFE0UTRRVCejyhMgYlpBgbCmX9v/Ml7iXuhvJ++jIE0A6kGFkgZSNZIMoZRRAeBpH7evDC44HXlM8Sy1/Nt9Ob3IPp3vS2/fQC8gRvBEoC+v8A/lH71vZ68IPpc+Kb3Pram9wV4Vznaez07vTuaex26MLjKd6B17HRX80mxobDhsMmxl/NR9lc59b2iQNBDNsRexXKGY0dWSBlIwYlBiVlI1kg1yFlI38oTy7uNDg/E0UzSHZLdkszSBVC2jlJLOsehg9CACbzhepc54XqMPGP+VMAbwRxBk0InApBDCILHgZF/r/zdugp3oHXt9Om1UfZc+J961H0Of1xBoYPpBhZIAYluSbXIaQYnAqR+yXuwuOb3EfZR9n62inec+ID5XbohepM7SXuaeyD6QPlKd5H2abVptWB1/raKd4D5Uzt1va7ASEO/Rq5JmwwVzd6PHo8VzehMkksfygGJWUjBiVaKk8uoTLuNFc37jShMkksZSP9GgwRTQhCAH74u+825qff+tqb3Cnec+I25nbog+mD6Xboduhc5zbmA+UV4ZvcptWx0bHRptWb3IPpYPZKAq8L2xGDFLQSRRCvC/IEkfu778LjgddfzSbGhsOGw6nIsdGB16ffwuN26Ezt3/Fg9hv4YPZ68Hbop9/62kfZp9+D6db2zgV7FWUjbDDaORVCdkveTnZLM0gVQto5oTJJLH8ouSa5JloqSSxJLEksWipJLE8ubDBsMFoq6x4MESMDYPZp7APlFeEV4XPiwuNc52nsJvPI+igBggXIBiMDCfwm84XqA+XC41znaeyG8hv43fxDATgFuQivC3oNQQzlBwr/hvID5abVqcjIwOu9673rvYbDEsu306fffevl9Y79fQH2AN38YPb07lznc+Jz4gPlaexg9scCDBHrHkks7jQ4PxNFM0gzSBNFOD/uNH8ojR20EqAJcgJF/qH+MgTaDHsVPhxZINch1yGNHYoX0A6+A7P3heop3qbVsdGx0abVp9996+X1vf6vBE0IGwoiC68LrwsqCfcDDP3l9XrwTO1p7CXuJvPd+EX+SgIyBFUDMgBR+970TO1z4oHXEsvIwOu9673IwBLLgdfC4/Tuj/kAAuUHQQxFELQSlxMMEXoNGwojByMHGwqGD30WWSBaKu40OD8TRTNIdkt2SzNIOD9sMFkghg/0As77j/ni+Qz9fQFxBpwK0A60EnsVfRaDFNAOrwRH94PpKd6m1bHRsdGm1UfZKd7C433rUfTy/qAJlxP9Go0dyhm0EoIHDvu771znc+Kn3ynem9wp3qffc+I25oPpfet961znFeFH2bHREssmxibGJsapyF/NsdFH2XPiTO2P+c4FDBHKGdchuSa5JmUjWSA+HMoZ/Ro+HFkgBiVJLO40OD8TRXZLM0gTRRVC2jmhMn8ojR3bEYIHIv84+WD25fV++Kv8nQAjA/cDVQNfAb3+kftH9zDxduin36bVlM9fzZTPgddz4vTud/xNCNsRihekGIoXgxR6Da8EOPl96ynet9MSyybGJsapyF/Nt9NH2affA+WF6vTu3/Ew8WnsNuYp3oHXsdGx0abV+toD5TDxFACGD40dfyhsMNo5ejx6PNo5oTJaKmUjWSDrHuse6x7rHlkg1yEGJX8oSSxPLmwwTy65Jj4cIQ4OAWT1fesD5affm9z62pvcp98D5Uzt3vQJ/FMAZADO+1H0fesD5affKd6n38Ljg+m772D23P0eBiEOexX9Gj4cpBjQDscC3vRc5/rasdGpyIbDyMCGw6nIlM/62nbo3vSD/vIEggdxBiQCCfze9CXufetM7d/xOPlKAtoMyhl/KFc3FUJ2S21SbVJtUm1SdksVQlc3SSxZIKQYlxPbEZcTpBiNHWUjuSZaKloqfygGJT4ctBLOBUf3duib3KbVsdG300fZFeGD6bvvZPUy+iP+sgDdAd0BZADd/Ef33/FM7YXqg+mF6vTuJvNH9+L5kfsJ/A77G/iG8oPpKd6x0SbG7bqKtIq0irTtuobDlM9H2cLjJe5H97b9mwGJAzIE9wNKAjj/DP2O/ZsBTQgMEcoZZSNPLto5E0XeTiVWB1olVt5OFUJsMNchexV6DU0IggXyBB4GKgnaDNsRiheNHesejR2KF9oMzv/f8TbmKd5H2abVptWB1/rap99c53rwQvxNCLQS/RrrHo0dfRYhDjgFOf3W9jDxaex26DbmA+U25oPpTO168DDxu+996wPlKd6m1ZTPEssmxibGJsYSy5TPgdcp3lznv/MOAdoMfRY+HFkg1yHXIVkgjR39GsoZyhmNHWUjWiruNHo8FUITRRNFE0U4P9o5oTK5Jj4cRRCvBFH7UfR68HrwhvLl9eL5d/y2/QD+3P3d/DL65fW771znp9+B17HRX81fzbfT+to25ibzzv+cCpcTyhmNHY0d/Rq0EoIHyPol7sLj+tqm1bfTsdGx0bfTgdf62qffA+Vc54PpdugD5RXh+tqm1ZTPX81fzbfT+toD5XrwDP2cCqQYBiVsMO40VzfuNGwwSSx/KLkmuSZ/KLkmuSa5JrkmWipPLqEy7jRXN+40Ty4GJf0aRRAjBwr/R/d68IXqNubC48Ljdugl7mT1Ufvy/vL+UftR9GnsNuYV4affFeHC41znfesw8d34mwJBDIMU/RqNHf0agxScCvr/UfSD6Snet9MSyybGhsMmxhLLsdGb3DbmevCz98j64vnl9Xrwheo25sLjc+Jz4lznJe6z91UDRRCNHVoq7jR6PBVCE0UzSBNFOD9XN08uZSM+HH0WlxOXE30W/RrrHmUjuSZ/KFoquSbXIaQYeg3d/4byNuYp3kfZgddH2ZvcwuOD6fTuUfTd+Kv8rf9fAXYADP0b+CbzevD07rvv3/Fk9Tj5Of0oAa8E5QegCRsKcQa9/r/zXOf62pTPJsbIwOu9yMAmxl/NptUp3jbmJe7l9c77Iv+K/7b9fvpH92T1YPY4+Y79SgLlB4YPyhm5Ju40FUJ2S21SbVLeTjNIejxsMAYlPhx7FYYPQQwbCiILIQ6XE/0a1yEGJQYlWSCKF9oMZADe9IXqwuMp3vragdem1abVR9kV4X3rs/dKApwKhg8MEYYPrwseBhQAMvpR9PTug+k25jbmduh96/Tu3/Em8ybzu++F6sLj+tq301/NqcgmxibGhsMmxhLLsdFH2QPlevB++iMDGwpFEJcTgxSXE0UQeg2vC68Lhg97FY0duSZsMNo5FUITRRNFE0UVQno87jRaKusegxSvC4IFmwK7AUoC9wNxBioJrwvaDNoMQQwbCsgGKAHd+CXuwuP62qbVt9Om1frac+Jp7Ef3xwLaDHsVPhzrHusepBiGDzgFyPrf8YPpc+Kb3EfZgddH2fraKd4V4QPlduh9633rduhz4pvcptWUz1/NX82Uz7HRgdcV4SXuOf1BDMoZZSNaKkksSSxaKrkmZSNlI2UjZSNlI9ch1yEGJX8oTy6hMlc3VzdXN2wwWirXIcoZDBFNCBQAG/h68IXqXOdc54Xq3/E4+c7/IwNKArb9R/d68IXqA+UV4affp9+n33Pidugw8Xf8ggcMEaQY/Rr9GooX2xFNCKv8evA25pvcsdESy4bDyMCGw6nIt9Ob3DbmTO0w8SbzhvL07oXqwuOn3/ra+top3sLjaeyz974DRRA+HH8obDDaOTg/FUIVQjg/VzdsMH8oWSD9GooXfRaKF8oZjR3XIbkmWipJLEksfyjXIaQYIgu2/TDxXOen35vcKd4V4QPlg+n07lH0fvjO+0X+Y/9F/g771vYm8zDxevAw8d/xv/NH9wn8SgIqCSEODBEMEdAOKgmK/ybzA+VH2V/NJsaGw4bDhsOpyJTPgdcV4WnsZPXO+4P+AP6R+zj5R/dg9mD2R/d++H76Rf6vBCEOyhl/KFc3FUJ2S95OdksTRXo87jRJLAYlPhyXEyEOnAobCkEM2xGkGOseZSNlI1kgpBghDokD4vkw8YPpc+Kb3IHXsdGx0bfT+toD5fTuG/jy/lUDHgYjB8gGMgQGAMj65fXf8SXufeuF6mnsevDe9N34Dvvi+eX1u+926BXhR9m305TPEssmxibGJsYSy7HR+tpz4n3rUfRC/IkDoAl6DdAO0A7aDJwKTQhNCCILDBGkGGUjSSzuNHo8FUITRTNIE0U4P9o5bDC5Jj4clxN6DaAJTQgqCSILQQxBDNoM2gzaDEEMGwpxBp0A3fi77zbmm9yB17fTsdGm1UfZp9+D6WT1XwEiC9sRexV9FpcTIQ6CByL/1va774PpA+UV4Snem9yb3Kffc+I25oPphep26APlFeGb3EfZptWx0ZTPlM+Uz7fTm9xc51H0cgLQDooXPhzrHuse6x6NHeseWSBZIOse6x5ZINchBiVaKmwwVzfaOdo52jnuNE8ufyjXIT4cexUhDs4FI/6z91H0v/Ng9s77mwEeBuUHHgZfAVH7ZPW774XqA+Wn35vcKd4V4TbmJe6z990BrwuXE6QYpBh9FgwRIguJA8j6MPE25vrasdESy6nIqchfzbfT+tpz4nboaez07vTuaex26MLjKd5H2YHXR9kp3jbmu+/i+TIEIQ6kGNchWipsMO40VzdXN6EySSy5JtchjR39Gv0aPhzrHtchBiV/KEksbDBsME8ufyjrHpcTyAbI+jDxfet26Hbohepp7PTuJvMb+EL8g/69/gz9fvpH91H03/G77yXuJe6774byR/dC/EoCuQghDrQSgxSXEyEO8gQ4+Wnsp9+m1V/NJsbIwMjAhsOpyLHRm9w25iXuJvNk9WT1v/Pf8Xrwu+/07vTuu+968CbzOPkAAiEOPhxaKlc3OD8TRRNFFUJ6PO40Ty65JuseihdFEEEMIgt6DZcT/RplI38ofyi5JlkgfRZ6DTgFOf3e9GnswuMp3pvcm9yn38Ljheow8bP3tv1KAjgFcQbIBs4FiQOt/w771vYm8zDxhvLl9Q777P8jA74DfQEM/Uf3u+9c56ffptWUz6nIhsOGw4bDqchfzabVm9wD5Wnsv/PI+rIAMgSCBW8EfQEA/gn83fwjAIIF2gx9FlkgSSzuNHo8FUITRRNFFULaOaEyfyiNHXsVhg9BDJwKIgvaDCEOhg8MEbQSgxR7FZcT0A5NCCMAR/cl7jbmKd5H2abVptVH2SneNua774/5VQMiCwwRtBLbEXoNyAbO/4/53vQw8Uztg+k25gPlA+Vc54PpheqF6nboA+UV4SneR9mm1bHRlM8SyxLLEstfzbfTKd6F6hv4IwMiC4YPtBKDFHsVexV7FX0WihekGP0ajR1ZILkmSSzuNNo5ejx6PNo5VzehMkksuSbXIY0dfRbQDsgGUwCr/An8Zf4kAh4GoAkiC5wK5Qf0Anf83vRM7TbmFeGb3Pram9wV4Xbo3/EM/YIHhg+DFH0Wihd9FpcTeg3OBQn83/F26KffR9mm1bfTt9OB1/raFeED5YPpaexM7X3rXOcV4fraptW307fTgdcp3sLjaexg9sgAIguDFI0dBiVaKk8uTy5PLloquSZlI9chWSBZIFkgWSBlIwYlfyhJLGwwoTJsMFoqZSOkGHoNvgMO+ybzTO2D6YPphepM7d/xZPUb+Dj53fhH97/zu+9961znA+XC4wPlXOeF6kzthvI4+SgBKgmGD7QStBLQDk0I7P/l9X3rFeGB15TPqcgmxibGqciUz0fZc+KD6SXuu++77/TuJe5M7X3rheqD6YPpg+lp7N/xMvqCBbQSWSBJLO402jk4Pzg/OD96PFc3bDB/KNchyhmDFLQSgxT9GtchuSZaKloqWiq5JlkgyhlFECMH3P1k9SXudugD5XPic+ID5YPp9O5R9H74Ufs5/Qr/ZAB2AKH+UftH9ybzevAw8Sbz1vYO+4r/VQOCBR4GbwRkADL63/F26CneptVfzanIJsYmxqnIEsuUz6bVm9zC44Xq3/FH98j6QvyR+4/51vbe9N70s/fd/FUDIguDFOseWiqhMno8FUITRRNFOD9XN08uBiWNHYoXgxS0EgwRRRAMEbQSexWKF6QYpBh9FrQSeg1xBr3+YPYl7jbmp9+b3EfZR9mb3BXhg+mG8gn8bwSgCUEMrwugCXEGmwKD/jL65fWG8vTuTO1M7fTuevDf8YbyMPH07oXqNuZz4ine+tqm1bHRX82pyKnIEsux0UfZwuMl7hv4ZADOBaAJQQwhDoYPRRBFEAwR2xGXE30W/RrXIVoqoTLaOTg/OD96PNo5VzehMk8ufyhlI/0alxPaDOUHbwRVA/cDzgVNCK8Leg16Da8LggdKApH7v/N968Ljm9xH2UfZKd4D5Uzt5fWh/sgGeg20En0Wihd7FdsRIgtVAw77hvJ96wPlFeEp3pvcm9wp3hXhA+WD6X3raeyD6QPlp9/62qbVsdGx0bfTgdeb3MLjfeve9KH+TQjbEcoZ6x5lIwYlBiVlI9chWSBZINchZSNlIwYluSZaKk8uoTLuNO407jRsMFoq1yGkGNAOOAUM/Uf3v/Pf8Ybyv/Pl9Tj5zvvc/dz9Uftg9jDxfet26APlwuPC48LjNuaD6fTuYPby/sgGeg3bEZcTtBIhDk0IyAAb+CXuwuNH2ZTPEsupyBLLsdGB1ynewuNc54Ppg+mD6XboXOc25sLjc+IV4affc+I25iXus/eJA4YP/RoGJUksbDDuNFc3VzfuNGwwWirXIT4cihd9FooXPhxZIAYlWipJLEksWioGJesefRYhDs4FOf1k9fTuhep26Hbohepp7PTu3/He9LP3Mvp3/Nz9jv1R+xv43vSG8jDxMPG/87P3QvyyAK8ETQgiC0EMnAqCBbb9v/OD6affgdex0V/NEssSy1/NlM+304HXKd4D5X3revC/8970UfSG8nrwTO1p7CXu3/Gz9wr/IwdFEP0auSahMto5OD8VQjg/2jmhMkksBiVZIP0aihd9Fn0WihekGP0aPhyNHY0dPhzKGYMUIQ5xBiL/s/d68IPpwuOn3yneKd5z4nboevAb+Dj/rwTlByoJKgmCBzgFmwI4/5H7fvhg9uX1R/fi+UL8DP0J/OL5YPaG8iXug+nC46ffR9m301/NqcgmxqnIEsux0UfZc+J96ybzG/jO+0X+ZAByAjIErwT3A74DggWgCUUQpBjXIVoqbDDuNFc32jnaOVc3oTJPLn8o1yE+HHsV0A4qCYIFvgMyBM4FggcqCZwKIgsbCk0IMgRl/mD2TO3C4yneR9lH2fraKd4D5WnsUfRC/IkDoAkhDgwR2xGGD68LcQb2AFH7ZPV68H3rXOfC43Pic+ID5Vzng+l964XqXOdz4pvcgde305TPX81fzbHRptX62nPig+km8zn9yAbQDpcTihfKGf0aPhyNHVkg1yHXIWUjBiW5Jn8oSSxsMO40VzfaOdo5VzdsMFoqWSCkGIYP5Qe7AQz94vnd+OL53fxkAPQCVQO7AYP+Mvrl9TDxTO2D6TbmA+XC4wPlduhM7d70Zf2CBUEMDBGDFHsVexW0EiEOcQZ3/N/xNuab3KbVt9O306bVR9mb3Kffc+LC4wPlwuNz4hXhp98p3vraR9mB14HX+tpz4oXqUfS9/k0I2xH9GmUjWipPLqEybDBPLloqBiVZII0d/Rr9GuseZSO5JkksTy5PLkksWioGJesefRZ6DW8Eq/zW9ibzevC77/Tuu+968Iby3vRH9zj5yPoO+376fvhk9YbyMPEw8YbyUfRH95H7DgEjB9oMDBGXE5cTRRCgCcgA1vZp7MLjm9yB17fTsdGx0bHRt9OB1/raFeFc52ns9O677/TuaeyF6oPpg+mF6mnsu+/e9M77OAUMEY0dfyihMlc3ejx6PNo5VzdsMH8oZSPrHv0ayhmkGKQYyhn9Go0d6x7rHo0d/Rp9FgwRrwuCBaH+R/e773bowuMV4affc+I25mnsJvN++N38MgD0Aq8E8gSJA8gAtv3I+n74G/jd+FH7I/4oAfQC9AL2AAD+fvrW9obyTO1c5xXh+tq301/NEssSy1/NsdFH2affXOdM7d/x1vZ++jn9Zf4j/t38kfuR+9z9mwIqCQwRpBjXIVoqbDBXN9o52jnaOVc37jRsMFoqZSM+HH0WDBEhDq8LnAqcCiIL2gzQDkUQDBGGD0EMcQbY/uX1aewD5affm9z62pvcp9825kzt3vSr/IkDuQhBDHoN2gycCsgG9AK9/n765fUw8Uztg+l26HboduiF6n3rTO1p7IXqNuan30fZt9OUz5TPX81fzZTPt9NH2RXhg+nf8eL5MgCvBE0IIgshDkUQ2xGXE30WihfKGT4cWSBlI7kmWipsMKEyVzdXN+40oTJJLLkmWSCkGEUQKglVA93/of53/wAC8gQjB00IggcyBBQAzvtH94byTO126APlc+LC4zbmhep68LP3Y/9xBkEMDBGDFIoXiheDFNAOcQYM/b/zhepz4inem9yb3Kffc+ID5VznXOd26Hboduhc58LjFeGb3EfZgddH2frap9825kzt5fW9/uUHDBHKGVkguSZaKkksWip/KAYlWSCNHT4cjR3rHmUjuSZaKkksTy5sME8uWiplIz4clxOcCvQCq/wb+GT1v/OG8obyhvJR9OX1G/iP+Y/5fvhg9r/zMPEl7mnsfet960ztu+9R9DL6KAHlByEO2xGXE9sReg1xBjn9JvOF6nPim9xH2abVt9Ox0bfTptVH2SnewuNc54Ppg+l26HboNuYD5cLjc+LC4wPlg+m77374mwJ6DaQYZSNJLKEy7jTuNKEyTy5aKgYl1yGNHT4c/Rr9Go0dWSDXIWUjZSNlI1kgPhykGJcTIQ7lB8gAOPnf8Wnsduhc53bofesl7oby1vZ++rb9ZAAkApsCfQEi/3f8fvqP+TL6CfwK/yQC8gQjB00IIwdvBN4AOf04+d709O526BXhR9mx0V/NX81fzbHRptVH2affA+WF6rvvJvNk9eX13vRR9L/zJvPe9H74Zf5xBoYPyhnXIX8oTy6hMlc3VzdXN+40bDBJLLkm1yE+HKQYexW0EgwRhg+GD4YPDBG0EpcTtBLQDioJ3QEy+obyfesD5RXhKd4p3qffwuOD6bvvR/eO/ccCHgblB00I5QfIBvIExwIyALb9yPqz91H03/F68DDxhvK/8970JvO774XqA+Wn3/raptWx0ZTPX81fzbHRgdeb3MLjfevf8bP3d/zd/0oC9wPOBU0IIgshDgwRlxN9FsoZ6x5lI38oSSxsMKEy7jTuNKEyTy5aKmUjjR17FXoNggeJA3ICVQOCBSMHuQgqCbkIyAa+A5z/Dvvl9bvvg+kD5RXhFeFz4jbmfet68Nb2DP1VAyoJeg1FELQStBKGD5wKiQMO+ybzaexc5zbmNuZc51znXOd26Hbog+mD6XboNuZz4qffm9xH2YHXgddH2ZvcFeFc5yXuZPUM/fIE2gyDFD4c1yFlIwYlBiVlI9ch1yFZINchZSO5Jn8oSSxsMKEy7jShMmwwWirXIcoZtBJBDHEGXwG2/VH7j/nd+H74OPl++pH7zvsO+4/5R/fe9IbyevAl7mnsaexp7CXu3/Fg9qv8vgOcCkUQgxR7FbQS2gw4BTn9ZPUl7nboc+Kb3IHXptWm1YHX+top3hXhwuM25lznXOdc5zbmwuNz4hXhp98V4XPiXOdM7WD23gBBDH0W6x65JloqTy5PLkksfygGJdchjR0+HP0aPhzrHtchZSMGJQYlZSPXIVkgjR2kGJcTeg3IBk7/G/iG8iXuaex962nsTO2774by5fXd+A77QvxC/FH7OPnW9mT1UfRk9Uf3Ufut/4kDHgaCByMHzgVvBJsCiv/I+lH0TO0D5Snegde307HRlM+Uz7fTgdf62hXhNuaD6Uztu+968Hrw9O5M7X3raey77970zvv3A9oMexXrHrkmSSxsMO407jTuNKEyTy5aKrkmZSNZII0dyhmKF30WexV9FooXyhnKGaQYfRbbEa8LOAVF/kf3u++D6QPlc+Jz4sLjXOdM7Sbz3fg5/cgAxwJVAyMDcgK7AfYAFACD/kL8OPnW9mT1ZPVg9rP3fviz9+X1JvP07oXqA+Wn30fZptWx0ZTPlM+x0bfTR9mn3zbmfesw8VH0R/c4+Q773fzy/kMB9wOCByIL0A60EooXjR1lI38oSSxsMKEy7jTuNKEyTy5aKmUj/RqDFNAOIgsqCbkIoAkiC0EM2gx6DdoMnArIBt0BCfzl9bvvheo25sLjwuM25oPpJe4m8374jv3HAuUH2gxFENsRRRBBDB4GY/84+VH0evAl7mnsfeuF6n3rTO0l7iXuTO1963boA+UV4Sne+tqB14HXgdf62ineFeE25n3rhvKP+bIAggchDpcTfRakGMoZyhnKGcoZ/Rr9Go0dWSBlI38oSSxsMKEyoTJsMEksuSZZIKQYtBJ6DU0IvgPIACL/Zf6h/mP/MgBTAL7/g/6r/DL61vYm83rwTO1964XqheqF6mnsevDW9qH+yAZ6DdsRlxOXEwwR2gwjB7IA4vmG8mnsXOfC4xXhFeEV4RXhwuM25nbog+mD6XboXOc25gPlwuMV4affKd6n33PiXOcl7tb29gCcCpcT/RpZIAYluSa5JrkmZSPXIesejR2NHese1yEGJbkmfyh/KLkmuSYGJdchjR2kGLQSQQweBlMAkfuz9970JvOG8obyv/Nk9db2G/iP+cj6Dvvi+Uf3UfTf8Xrw3/FR9H74d/xCAFUDzgWCB00ITQhxBlUDof44+Sbzaew25qff+tqB16bVptWm1YHX+top3nPiXOeF6mnsTO1p7IXqXOcD5QPlXOd963rwR/c4/+UHRRCkGFkguSZaKkksSSxJLFoqfygGJWUj1yHrHj4cyhmkGIoXpBjKGcoZ/RrKGYoXgxRFECILbwS2/Uf3MPFp7HboNuY25nbofet68N703fgO+wn8q/xl/UX+Y/8jACMATv/c/Xf8kfuR+5H7kfvO+wn8CfxR+zj55fUw8X3rNuYV4Zvcgde307HRsdG300fZKd5z4lznfev07jDxhvJR9GT1R/c4+ZH7g/5KAsgGrwsMEX0WPhzXIbkmWipPLmwwoTKhMmwwSSy5Jtch/Rp9FrQSRRDQDtAOhg9FEAwR2xEMEYYPQQzlB3ICQvxk9bvvhepc5zbmXOeD6Wns9O6G8tb2zvubASMHrwt6DdoMIgvlBzIEIwDO+xv4ZPUm84by3/Hf8TDxMPEw8Xrw9O5p7HbowuOn35vc+tpH2UfZ+tqb3Kffc+I25oXqevDW9nf83QHIBpwKIQ4MEbQSgxR9FooXpBjKGT4cWSAGJVoqTy6hMqEyoTJsMFoquSZZIMoZgxSGDyIL5QceBvIErwTyBPIEOAXyBIkDDgGO/eL51va/8zDxJe5964PpduiD6UztJvMy+igBggfaDEUQtBLbEYYPnAo4Bb7/Mvre9Lvvfet26FznXOdc53bog+mF6oXqheqF6oPpXOc25gPlc+Kn3yneKd6n33PiXOcl7uX1I/5xBtAOexX9GuseWSDrHo0dPhz9GsoZ/RqNHVkgZSMGJbkmfyh/KH8ouSYGJVkgPhyKF7QSeg3lB1UDY/+r/H76fvhH92D2YPZH9934fvoO++L5R/e/8zDx9O707rvv3/He9Bv4CfxTAPcDIwe5CKAJKgnlB68EBgDI+t70u++F6gPlFeEp3pvc+tr62pvcp99z4lznhepp7GnsfeuD6VznNuYD5QPlNuaD6fTu3vQM/c4FIQ59Fj4c1yFlIwYlBiUGJQYlBiVlI9chWSDrHj4cPhw+HD4cPhw+HI0djR0+HMoZexUMEUEMyAb2AMj63vS772nsfetM7bvvhvJk9Uf3fvg4+eL5fvrI+g77yPoO+5H7CfwJ/EL8DP1F/or/sgB9AbsB9gA4/3f83fhR9PTug+kD5aff+tqB14HXR9mb3KffwuNc54XqTO307rvvu++773rwevCG8lH0G/jd/EoC5Qd6DbQSihc+HFkgBiVaKkksTy5JLFoquSZlI+se/Rp9FpcT2xHbEdsRtBKXE4MUexWDFLQS0A4qCZsCzvvl9TDx9O5M7Wnsfetp7Eztu++/8374DP19AYIFTQigCaAJTQiCBZsCnP/d/H76fvhH92D2YPZg9tb2YPbl9b/zu+9961znc+Kn3ynem9z62pvcm9wp3hXhwuN26GnsMPFk9Y/5DP2yADIE5QciC3oN0A5FENsRlxN9Fv0aWSC5JkksbDChMqEybDBPLn8oZSPrHsoZgxRFENoMGwq5CLkIGwoiCyILGwrlB68EfQFl/pH7G/hR9LvvaeyD6XboduiF6vTuUfQO+5sBggevCyEO0A4hDq8LTQiJA4P+j/ne9DDxJe5p7H3raexp7Gnsaex964Xqhep26FznA+Vz4qffKd6b3Pram9wp3hXhA+V964byfvpyAhsKRRCDFH0WfRZ9FnsVexV9FqQY/RqNHVkgBiV/KFoqSSxJLFoqfygGJdchPhyKF9sR2gwqCXEGvgMOAUX+kft++sj6Cfzd/N38kfuP+db2v/N68CXuaex960ztevC/8xv4d/wOATgFuQgiC68LIgsqCTgFnQCR+2D23/FM7YPpNuZz4qffp9+n3xXhwuM25nbog+mD6XboXOcD5XPiFeGn36ffFeED5YXqhvJR+zIEQQy0En0Wyhk+HOse6x5ZIFkgWSDrHuse6x6NHY0djR3rHlkgWSBZIFkgjR39GooXgxQMEa8LggXy/jj53vSG8jDxMPGG8r/zZPXW9kf31vZg9uX1ZPXe9N70ZPVg9rP33fgy+s77tv3O/90BVQO+A1UD3QGt/6v8fvgm8yXuXOdz4ine+tpH2UfZ+top3hXhA+Vc54Ppfet9633rheqD6YPphepp7HrwZPXI+jIAzgUiCwwRfRY+HFkgBiV/KEksSSxJLFoqfygGJdch6x4+HMoZpBiKF4oXihfKGf0a/RqkGIMUhg+gCb4Dg/7i+eX1hvJ68PTuJe4l7rvv3/He9Bv4kfvy/rsBvgNvBDIEIwPdAZ0AOP+O/c77yPoy+n76UfsJ/An8yPob+FH0u++F6jbmc+Kn3ynem9z62pvcm9yn33PiA+V26IXqaez07t/xZPXd+Hf8rf9KAm8EcQa5CK8Lhg+XE8oZ6x4GJVoqSSxPLk8uSSxaKrkm1yGNHcoZgxQMEYYP0A7QDoYPhg/QDnoNrwsqCR4G9AKc/wn8fvhR9HrwaeyF6oPphepp7Hrw5fXO+ygBggW5CCILrwsiC6AJcQZyAkX+fvpH9970v/OG8t/xMPF68LvvJe5M7WnsfeuD6VznA+Vz4hXhp98p3ineKd6n33PiXOdp7CbzMvreAHEGnAp6DYYPRRBFEAwR2xGXE30WyhnrHtchBiV/KFoqSSxJLFoqfyhlI+seyhl9FrQShg9BDCoJHgb3A0oCXwH2ACgBXwEOAb7/Of3i+WD2hvL07mnsfetp7CXuevBR9Dj53P2bAsgGGwqvC68LGwojB1UDOP9R+0f3JvP07oXqXOfC48LjwuPC4zbmXOd26IPpduh26FznNubC4xXhp98p3inep98D5X3rhvLi+X0BTQh6DdsRgxR9FqQYyhn9Gj4cjR2NHY0djR3rHlkg1yHXIdch1yFZIOsejR0+HMoZexUMEUEMIwfdATn94vkb+Ef3R/cb+H74fvgb+LP31vZg9uX1ZPVk9WT15fXW9hv4Mvp3/PL+XwFVA68EggWCBfIEvgPdAYP+4vlR9PTug+kD5RXhKd4p3inep98V4cLjNuZ26IXqheqD6XboNuY25jbmXOeD6Uzt3/HW9qv8SgLlB9oMtBKKFz4c1yEGJbkmuSYGJQYlZSPXIVkgjR39GqQYpBikGMoZyhn9GsoZpBh7FQwRrwtxBn0BDP3d+GT1hvJ68PTuJe4l7rvvMPG/82D2OPlR+6v8AP7Y/nf/nP84/6H+tv3d/EL8q/xl/WX+Cv8i/yP+zvsb+L/zu+9961znA+UV4Snem9yb3Cnep99z4sLjA+Vc53bohepp7CXuMPFR9Ef34vmr/Nj+DgGJAyMHQQzbEaQY6x5lI7kmWipJLEksSSxaKrkm1yHrHv0aihd7FYMUgxSDFIMUlxO0EgwR0A5BDCoJzgUAAtz9j/ne9HrwTO19633raez07obyYPYO+3f/VQNxBk0IuQjlBx4GVQNkAI79Dvs4+Rv4R/dg9mT1UfQm89/xevD07mnshepc5wPlwuMV4affKd6b3Jvcm9wp3hXhA+WD6fTuUfTi+b3+SgKvBM4FcQaCB6AJQQyGD7QSfRb9GuseBiV/KFoqSSxaKn8oBiXXIese/RqkGHsV2xGGD9oMnAq5CIIHyAZxBh4GOAWJA8gAOf2P+eX1hvK770ztaexp7CXuMPFk9eL58v6JAyMHoAkbCqAJTQgeBvcDKAEA/sj61vYm87vvTO1964XqheqF6n3rfet9633rfeuF6nboNubC4xXhp98p3ineFeE25mnsJvN++sgAzgWgCdoMRRCXE3sVihekGMoZ/Ro+HOseWSBlIwYlBiUGJQYlBiVlI9chWSDrHv0aihe0EiEOKglvBPYAvf6O/Qz93fyr/An8Dvvi+Rv4YPZk9b/zhvLf8d/xhvJR9GD2OPlC/PL+XwFVA/IEggXOBYIF9wNDAWX93fi/8/Tug+k25nPip9+n36ffFeHC4zbmXOd26HboXOcD5cLjFeGn36ffFeED5YPpJe4m8xv4tv2+A6AJhg+DFKQYPhzrHlkg1yHXIdch1yFZIOsejR0+HD4cPhyNHese6x7rHo0d/RqKF5cT0A4bCoIFXwG2/cj6G/jl9VH0UfRR9GT1YPaz99344vkO+3f8tv29/nf/nP93/wr/of6h/or/KAHHAr4DvgP0AigBof4O+9b2hvIl7oPpA+Vz4hXhp98V4XPiwuMD5TbmXOdc53boduiD6X3rJe4w8SbzZPVH9+L5DP1DAR4GrwsMEX0WPhxZIAYluSZaKloqfyi5JmUj6x4+HMoZiheKF30WiheKF30WexWXEwwRIQ6vC00I8gSdAM77R/cm87vvTO19633raez07t/xZPU4+av87P9yAr4DvgNyAp0A2P5l/UL8kfvI+jL64vmP+d34G/jW9t703/H07mnsg+lc5wPlc+IV4affp9+n3ynep9+n33PiNuaF6vTuJvPW9uL5Qvwj/hQAJAJvBMgGGwp6DdsRihc+HNchuSZaKkksSSxaKn8ouSZlI+sePhzKGYoXgxS0EkUQ0A56DdoM2gxBDJwKuQiCBQACI/7i+eX1hvL07kztaexp7PTu3/Fg9g77iv/0AjgFcQbIBsgGzgVvBEoCnP93/Dj5YPa/89/xu+/07kztaexp7H3rfeuF6oXqg+l26DbmwuMV4Sne+tr62ineFeE25n3r3/HW9pH7MgBvBOUHnAraDNAODBG0EnsVihf9Guse1yEGJbkmfyh/KH8ouSa5JgYlZSNZII0dpBiDFEUQQQwqCSMHzgU4BW8EiQNyAvYAIv/d/H76s/dk9SbzMPF68DDxhvJk9Rv4yPq2/XYA9AI4BcgGggeCB3EGbwS7AUX+fvpg9obyJe6F6lznNuY25lznduiD6YXqaexp7IXqdugD5XPip9+n3xXhc+ID5Xboaezf8Uf33fwkAiMHrwuGD7QSfRakGP0ajR3rHlkgWSBZIOse6x7rHuse6x5ZIFkgWSBZII0d/Rp9FrQSIQ4bCnEGmwJO/3f8Mvp++Ef31vZg9mD25fVk9WT1ZPVg9kf3G/jd+Dj5OPmP+eL5Ufvd/PL+sgAAApsCmwIAAmQAtv3i+WT1evBp7HboA+XC43Pic+ID5TbmXOd26HboXOdc51znXOd26IPphepp7CXuevAm82D2fvoi/zIEoAnQDpcTpBiNHdchBiW5JrkmuSYGJdch6x6NHT4c/Rr9Gj4cPhz9Gv0apBiKF4MU2xHQDiILIwebAgD+4vlg9ibzMPF68LvvevDf8b/zYPY4+Qn8AP4i/07/2P5F/o793fx3/An8zvsJ/N38jv22/d38Ufs4+WD2v/O772nsg+lc5wPlA+XC43PiFeEV4affFeFz4sLjNuaD6Wns9O7f8b/z5fUb+OL5CfyD/n0BOAWgCdAOexX9GlkgBiW5Jn8ofyi5JgYl1yFZII0dPhzKGYoXexWXE7QS2xEMEUUQhg8hDkEMKgnOBQACAP7i+eX13/H07mnsaexM7bvvJvNH9w77Rf6yAHICiQMyBL4DmwIOATj/Zf3O++L5G/jW9mT1UfQm89/xu+8l7kztaexp7H3rhep26APlc+Kn3ynem9wp3qffc+I25n3ru++/8xv4kfvY/kMBIwPyBCMHKglBDIYPlxOKFz4c6x7XIQYlBiUGJQYlBiUGJWUjWSCNHf0aiheXE0UQeg2vCxsKKglNCCMHzgVvBMcCnQDc/X76R/e/89/xevC77zDxhvLe9Ef34vnd/N3/SgL3A/IEOAU4BW8E9AKyANz9yPpH91H0MPEl7n3rheqF6n3raewl7iXuJe5p7IPpXOfC43PiFeGn3xXhc+LC41znfet68GT1MvqD/nICHgYqCdoMRRCXE30WpBj9Gj4cjR2NHese6x5ZINch1yFlI2Uj1yFZII0dyhl9FpcThg9BDCoJzgUjAygBvv+9/o79Qvx++t34R/fl9WT1ZPXl9eX15fVg9tb2G/iP+Q773fzy/t4AmwL3AzIEvgNKAnYAAP5++mD23/FM7YPpXOc25lznduiD6YXqheqF6oPpduhc51znNuY25jbmXOd26IXqTO2777/zs/cJ/IkAggWcCoYPgxSkGI0dWSDXIdch1yFZIOsejR2NHY0djR2NHY0djR2NHT4c/RqkGH0WlxNFENoMuQjyBF8BI/4O+374YPZR9L/zv/Pe9GD2G/iP+Q77Qvzd/Dn9Of3d/Hf8d/zd/GX9I/7Y/nf/FAAyAIr/tv0O+7P3v/N68EztfeuD6XboXOc25gPlA+XC48LjwuMD5QPlXOd26IXqaewl7nrwhvK/8+X1G/h++tz9JAIjB9oMlxOkGI0d1yFlIwYlBiUGJWUj1yFZIOsejR39GsoZpBiKF4oXfRZ9FnsVlxPbEdAOQQwqCYIFQwGr/Bv4v/Mw8bvvu+8w8SbzZPV++FH7AP7d//YAfQG7AZsBDgEUAL3+Zf13/JH7Dvt++o/5G/jl9VH0hvIw8Xrwu+/07kztfet26APlc+IV4affp9+n3xXhwuNc54XqJe4w8VH01vY4+Q77q/xl/p0AiQOCB68LDBF7FcoZjR1ZIGUjZSMGJQYlBiVlI9ch6x4+HMoZfRaXE9sRRRDQDnoNQQyvCyILoAnlBzgFmwGO/Y/55fUm8zDxu++777vv3/FR9Nb2j/lC/L3+3gCbAokD9wOJA0oC9gBj/2X9yPqz91H0MPH07kztTO0l7vTuu++777vv9O5p7IPpXOcD5XPiFeGn36ffFeHC41znfet68FH0fvgJ/CL/AALyBOUHIgvQDtsRgxR9FqQYyhk+HI0d6x7XIWUjZSNlI2Uj1yFZII0d/RqKF4MUDBF6DZwKTQjIBs4FrwQjAygBCv8M/VH7OPmz92D2ZPXe9N703vRk9eX11vZ++Mj6Of2t/30B9AIyBPIE8gT3A90Bvf5++mT1MPFM7YXqg+mD6YPphep9633rfet964Xqduhc5zbmA+XC48LjwuMD5VznhepM7TDx3vTd+N38KAHOBZwKhg+XE30Wyhn9Gj4cPhw+HD4cPhw+HI0d6x7rHuse6x7rHo0dPhzKGYoXgxRFEHoNGwojB74DQgBl/VH7j/l++LP3R/ez9374OPni+X76fvp++jL6fvrI+sj6UftC/I79OP8oAfQCMgQyBMcCUwAM/Tj55fWG8rvvTO1964Xqduh26FznXOdc51znXOdc51znduiD6YPphepp7EztJe677zDxJvPl9Y/5Rf6+A6AJhg97FcoZPhzrHlkgWSBZIOse6x6NHT4c/RrKGaQYpBikGKQYpBiKF3sVlxO0EkUQeg2gCYIFDgGr/N34ZPUm89/xhvIm82T1R/c4+cj6QvyO/YP+Cv8i/6H+AP5l/Tn9jv0j/oP+Zf6O/UL8fvp++GD23vS/84by3/F68CXuaeyD6VznA+XC43Pic+Jz4sLjNuZ26H3rJe568IbyUfTl9Uf3fvji+UL8nP/3A7kIeg20EooX/RqNHVkgZSNlIwYlZSNlI1kg6x4+HMoZihd7FZcTtBLbEQwRDBFFEIYPIQ4iC00IbwRTAAn8G/je9IbyMPEw8d/xJvPe9LP3fvpl/Zz/QwFKApsC9AL0AvQCSgIOATj/q/zi+db2UfQm84by3/GG8obyhvKG8jDxu+9M7YXqdugD5XPiFeGn3xXhc+ID5Xboaey77ybz5fV++Mj6Zf1CACMDHgYqCUEM0A7bEYMUihfKGT4c6x7XIdchZSNlI9ch1yFZII0dyhl9FpcTDBHQDtoMrwsiCxsKKgmCB4IFxwIUAGX9Dvs4+Uf35fVR9CbzJvO/89701vbd+A77Of1j/30BVQPyBB4GHgbyBEoCg/4y+uX1hvK770ztaexp7EztJe707vTu9O5M7Wnshep26DbmA+XC43Pic+LC4zbmduh96/Tu3/Hl9eL5I/6bAiMHIgvQDtsRgxR7FX0WihekGMoZ/Ro+HI0djR3rHlkgWSDrHo0dPhzKGX0WgxQMESEOIgtNCM4FIwOdAGX+d/xR+376Mvri+Y/5OPk4+d343fjd+Dj5OPmP+eL5fvoJ/CP+sgBVA/IEzgU4BYkDyACO/TL61va/8zDx9O5M7WnsfeuF6oXqheqF6oXqg+mD6YPpg+mD6YPpheqF6n3rfetp7CXuevAm80f3d/wAAuUHeg3bEXsVpBj9Gj4cjR2NHY0dPhz9Gv0a/Rr9Gv0a/Rr9GsoZyhmkGIoXexWXEwwRIQ6cCnEGJAK2/eL5R/fl9d70ZPXl9db2G/iP+Q77q/yO/SP+3P05/av8Qvx3/Az9I/4i/87/BgCK/6H+DP0O+zj5s/dg9t70hvJ68CXuaeyF6nboNuYD5QPlA+U25lznduiF6mnsJe568DDx3/GG8obyv/Nk9Rv4zvtkADgFGwqGD4MUpBg+HOseWSDXIdch1yFZIOsejR39GqQYfRZ7FYMUlxOXE5cTtBK0EtsRhg/aDCoJ8gTIAN38OPlg9r/zhvLf8Ybyv/Ng9jj5kftl/b3+vv9TAMgAQwGbAZsBDgHd/yP+CfyP+Uf35fXe9FH0UfRR9FH0v/Mm89/xu+9M7YXqXOcD5XPiFeEV4RXhwuM25oPpaez07t/xv/Pl9bP34vl3/Ar/uwFvBIIHnAohDtsRexWkGD4c6x5ZINchZSNlI2Uj1yHrHj4cyhl9FoMU2xFFEIYP0A4hDnoNQQycCk0IzgVVA50AAP5R+374YPbe9FH0UfRk9db2fvgy+s77AP5CAJsCbwTOBR4GzgUyBEMBtv3i+WD2JvN68Lvv9O707vTuu+968Lvvu+8l7mnshepc5wPlwuNz4hXhc+LC4wPlXOeD6Wnsu+8m82D2fvqh/koCggVNCJwKeg1FENsRlxODFH0WpBjKGT4cjR3rHuse6x6NHT4cyhmKF4MUtBJFECEOrwu5CHEGMgQkAnYATv8j/t38zvvI+uL5OPnd+N34fvh++Bv4s/ez9934fvqr/Hf/SgJvBM4FHgaCBYkD9gC2/X76R/dR9N/xu+8l7kztaexp7EztTO1p7GnsfeuF6oPpg+mD6YPpg+mF6oXqhep962ns9O6G8tb2kft2AIIFnArQDrQSfRakGMoZ/Rr9Gv0a/Rr9Gv0a/Ro+HD4cPhw+HD4c/RrKGaQYihd7FZcTRRBBDE0IbwT2AAD+kfvi+X74G/gb+H744vkO+wn8d/yr/EL8zvtR+w77UfsJ/Dn9of7d/50AnQDs//L+tv0J/DL6fvjW9t70hvJ68PTuTO1964PpXOc25gPlA+UD5TbmXOd26IXqaexp7EztTO1M7SXu9O4w8VH0s/dC/F8ByAavC0UQgxSkGP0aPhyNHese6x6NHY0dPhzKGaQYihd9Fn0WfRZ9Fn0WfRZ7FYMU2xHQDiILIwdVA3f/kfsb+OX1UfRR9GT11vbd+Mj6Qvxl/UX+Cv+K//r/dgDeAMgAIwAi/7b9QvzI+o/53fh++Bv4s/dH99b25fVk9b/z3/H07mnsdug25sLjc+Jz4sLjA+Vc54PpfetM7fTuevDf8Sbz3vTW9t34UftF/rsBggUqCXoNDBGDFKQY/RqNHeseWSBZIFkg6x4+HMoZiheDFLQS2xEMEUUQhg/QDnoNQQycCioJyAa+A4kAZf0y+rP35fXe9FH0UfTe9OX1R/fd+H763fxj/7sB9wM4BYIF8gQjA2QAOf0y+rP3ZPW/84by3/Hf8YbyhvKG8oby3/Ew8XrwJe5964PpXOc25lzng+lM7XrwUfSz9376q/xF/jj/zv+dAMcCMgRvBG8E9wObAvYAFACbATgFnAoMEaQYjR1ZIFkgWSCNHaQYtBLQDq8LTQivBCQCUwBj/73+8v72ACMDggVNCK8LIQ7QDiEOIQ4hDiEOIQ4hDiEOrwtNCK8ESgKbAvIEIwe5CE0IrwSc/8j6ZPUw8fTuTO1964PpNuZz4qffKd4p3qffA+Vp7DDx3vR++FH7Cfzi+eX1MPFp7HboA+Vz4qffKd4p3hXhA+WF6obyq/yCB9sR/RrXIbkmWipaKloqfyh/KLkmZSONHYoXtBLQDkEMrwvQDtsRlxN7FXsVgxTbEdAOQQygCR4GxwKc/376UfS77/Tuv/NR+/IEeg2DFMoZpBiXE0EM8gSh/sj6fvjl9d/xTO126MLjp98p3inewuOD6SXuu+/07mnsaewl7oby3fhTAB4GyAb0Aqv8YPa774Xqdug25sLjp99H2bfTlM+Uz6bVc+Iw8c7/IgvbEXsVexWDFH0WPhzXIVoqbDBXN9o5VzehMkksWip/KH8ofyi5JmUj/RpFEFUD1vZp7DbmA+U25oPpfesl7vTuMPHe9M775Qd9FmUjfygGJT4cDBFvBH76JvMl7n3rdujC45vcptWm1fraNuZR9CMDRRCKF4oX2xGgCb3+3vQl7n3rhepM7TDx3vRg9rP3j/k5/SMDKgmvC7kIAALW9lznptUmxu26zbfNt4bDsdEp3n3r5fV2AHoN6x6hMhNF3k5tUt5OE0XuNAYlpBhFEEEMGwqvBA77MPF964Ppfeu/8wYArwu0EpcTRRCvC28EOf2z9+X1G/jd/H0BrwQeBiMHoAnQDqQYZSNJLGwwTy65Jv0aGwrW9sLjt9MSy6nIEstfzbHRptVH2XPiJe7c/SEOyhnrHuseyhmGD8cC3vR26KffR9mx0anIyMDrveu9yMBfzaffhvJvBLQSPhzXIWUjZSNZII0djR1ZIGUjBiUGJVkg6x7rHmUjfyhPLqEy7jShMkksWSBFELb9feub3LHREsupyCbGJsapyJTPKd4m8yoJjR1JLO40VzfuNEksZSOkGIYPzgVR+7vvwuOB11/NqcgSy6bVc+Iw8YP+TQjQDtsR2xHQDiIL5QdvBA4Bq/xH93rwhep26H3rMPE4+ccCIgtFEAwRIQ7IBqv8MPFc5yneR9mB16bVt9Ox0abVFeG/8yILZSPaOXZLJVYHWiVWdksVQu40uSZ9FsgGs/dc50fZlM+Uz6bVc+Im8/QChg+kGD4cPhykGJcTIQ4qCYkD3P2z93rwhepc54Pp9O6P+SMHlxM+HNch6x59FqAJ4vmD6UfZEsuGw8jA7brNt+26yMCUzxXhZPUbCj4cuSZaKn8oZSPKGYYP3QFR9Hbo+tpfzYbD7brrvSbGptWD6Y79RRDrHn8oSSxJLEksWip/KAYlZSPrHsoZgxQMEQwRexWNHbkmbDDaOXo82jlsMGUjgxT3A4bywuNH2bHRqcjIwMjAJsax0cLj3fjQDtchbDDaOdo5VzehMloq6x60EnEG3fiF6inet9OUz7HRgddz4nrwZf4iC7QSgxS0EnoNyAaK/xv4MPGF6nPim9yB16bVR9mn31zn3/FC/K8EggcyBAz9v/N26Cnegde307HRlM9fzZTPptVz4lH0nArXIVc3dkslVgdaJVZtUnZLOD/uNFoqPhwhDs7/v/Np7IXqaezf8eL5VQMiC4YPhg8hDkEMnApNCCMHOAWbAiL/Ufsb+Ef34vm9/jgF2gx7Ff0aPhykGEUQ8gTW9oXqFeFH2bfTX80Sy6nIqchfzabVFeH07kX+rwuDFKQYyhmKF7QSQQzyBI793vSF6inet9NfzRLLEsux0Zvcherd+L4DIgtFEJcTfRbKGT4c6x5ZIFkgjR3KGX0WgxSDFH0WyhmNHdchBiUGJVkgpBjQDjgFjv1g9vTug+nC4yne+tqb3HPiTO0O+yILyhm5Jk8uoTKhMmwwWiq5JlkgpBjQDgAC3vSD6RXh+tqB1/rawuNM7WT1kftO/3YAOP+O/Qn8fvp++FH0u++F6jbmwuNz4nPiNuZ96ybz4vnc/av81vb07nboc+Ip3pvc+tr62kfZ+top3gPlMPFfAZcTuSZXNxNFdkveTt5OM0gVQto5bDAGJYoXKgkM/Ybyhepc53boTO1R9EL89AIjB00IggdxBoIFbwSJAwAC2P5++mD2JvPf8SbzYPa2/SMHDBGKF8oZexXaDPQCfvj07lznp99H2bfTlM9fzZTPt9On30ztCfycCn0W6x5lI9ch6x7KGbQSIgv2AN70duib3LHREsupyBLLt9Mp3n3rfvhKArkIeg0MEYMUfRbKGT4cPhzKGaQYfRZ7FYMUfRb9GmUjWipsMKEyTy5/KOselxNNCCP+v/OD6RXh+tqm1abVR9kV4SXujv3aDP0aBiVJLE8uSSxaKgYl6x59FtoM9ALd+CXuA+Up3vram9xz4oPpMPHW9jL6UfuP+eX13/G770ztg+k25gPlc+IV4SneKd5z4oPp3/Hd+N38Zf3i+SbzfesD5RXhKd6b3Jvcm9wp3nPig+ne9IkDgxQGJe40FUJ2S21SbVLeTnZLE0V6PKEyfyiNHdsRggdl/kf3JvMm8+X1fvjI+gn8zvs4+eX13vRR9FH0JvOG8obyhvIw8bvvu+8m8zL6mwKcCgwRlxPbESILcgIy+obyfes25hXhm9xH2YHXgdf62hXhfetH93ICQQx7Ff0ajR2NHf0afRYMESoJ3f9g9mnsc+JH2bfTsdGm1fraFeGD6d/xG/jd/CgBHgYiC9AOtBJ9FsoZ/RrKGaQYexV7FaQYjR1lI7kmWipaKgYl6x59FoYPyAa9/tb2u+926MLjp98p3nPihere9K3/Igt9FlkguSZaKkksSSxaKgYl6x6KF3oNuwFk9YXqc+Kn3yneFeED5X3ru++G8t70YPbW9mT1v/OG8t/xu+9961znc+IV4XPiNuZ964byfvjO+w77G/je9DDxJe6F6lznA+UV4affKd6n3zbmMPHy/iEOjR1JLNo5FUIzSN5O3k52SxNFejyhMrkm/RraDEMBfviG8rvvu++G8mT1G/gy+qv8Cv/O/zj/g/4j/jn9Cfw4+WT13/F68CbzG/ic/7kI2xGKF6QYexVFELkIdgB++LvvdugV4UfZt9OUz5TPptWb3FznhvLY/qAJ2xGkGI0djR0+HIoX2xEbCpz/v/Nc55vcptW307fTgdcp3jbmTO1R9FH7uwFxBqAJ2gxFEJcTexV7FZcT2xEMEQwRlxOkGOseBiVaKkksWioGJesefRZ6DW8EkfuG8oPpFeH62kfZm9xz4n3r1vZyAnoNpBjXIbkmWipaKn8ouSZZIMoZRRDyBI/5u+926MLjc+ID5Vznher07t/xUfTe9L/z3/Ew8d/xMPH07n3rdugD5cLjA+WD6bvv1vYJ/L3+g/4J/LP3hvJM7YPpNubC46ffm9z62pvcFeGD6eX1VQNFEI0dWiruNHo8OD8VQhVCOD96PFc3Ty4GJcoZhg8jB/YAZf1R+zL64vnI+kL8DP05/Xf8kfvO+2X92P69/qv8j/nW9t70UfTW9kL89AK5CHoNhg/QDiILggU4/4/53vS774PpwuOb3IHXptWm1UfZp9825vTuG/i7ARsKRRCDFIoXpBiKF4MU0A6CBcj6u+9c5xXhm9yb3JvcFeE25mnshvLd+IP+vgOgCUUQfRbKGf0ayhmKF5cTDBFFENsRgxSkGD4c6x5ZIOse/RqKF7QSIQ7lB4kAs/cl7jbmFeEp3ineFeE25iXuG/hKAkEMexWNHdchuSZaKkksfyhlI8oZIQ5yAn74u++D6QPlA+Vc533ru++/8+X1R/c4+Qn8AP7c/Qn8s/ff8X3rNubC48LjNuaF6vTuv/NH9374G/hg9t70v/Pf8SXuduhz4pvcR9n62pvcc+Jp7LP38gS0ElkgTy5XN3o8FUIVQhVCOD9XN0ksWSB7FUEMVQMJ/Nb23vTe9Ef3yPq2/SL/iv+JAAAC9AIjA0oCIv/i+d70evC773rw3vRR+/QCGwrQDgwRRRBBDCMHxwLc/bP39O425inegdex0ZTPsdGm1frawuNp7OX1OP8eBiILhg/bEbQSRRAbCkMBR/cl7jbmFeGb3Pra+top3sLjheow8Uf33fwAAiMH2gy0EooXyhnKGaQYfRZ7FXsVpBg+HFkgBiVaKkksWioGJVkgPhx9FkUQggdF/mT1Je5c58Ljc+ID5YPpu++z92QATQghDrQSfRb9GuseWSDrHv0agxTaDPIEOf1g9nrwaeyF6n3rTO307rvvu++773rw3/He9Ef3R/dg9lH03/G77/Tu9O568L/zR/cO+3f8Dvuz9970JvMw8bvvTO2D6TbmwuMV4XPiA+WD6bvvs/ckAnoNihdZILkmSSyhMlc32jnaOVc3oTJJLLkm6x6KF0UQuQhVA3f/Zf3d/An8fvo4+Y/5d/zO/yMDHgaCB4IHOAVVA5sCmwKJA8gGrwsMEZcTlxMMESEOrwsqCR4GSgKO/Rv4hvJp7FznwuMV4affp9/C43boJe6G8rP3Zf2JA6AJIQ5FENAOQQyCB/YA4vmG8n3rA+UV4SneKd4V4QPlduhp7IbyyPqJA0EMexU+HOseWSBZIOsejR0+HD4cjR1ZINch1yHXIVkgjR0+HMoZgxSGD7kInQB++DDxheo25hXhFeHC43boJe6/8+L5dgBNCEUQpBiNHVkgWSCNHaQYDBEqCVMAR/e774Xqg+mD6YPpg+mF6kzt3/Hl9eL5DP29/iP+Cfw4+eX1hvK777vv3/FR9GD21vbW9tb21vbW9mD23vTf8SXug+kD5XPip98p3inec+J26N/xUfuvBHoNfRZZIH8obDChMu407jRsMEksuSbrHn0Weg2CBU7/Ufvd+Ef35fXe9N705fV++FH7tv3Y/qH+Zf1R+374YPbl9Rv4CfxDAR4GoAkiC68LrwsbCk0IOAUoAVH7UfRM7Vznc+Ip3kfZR9lH2ZvcFeE25oXqevCz94P+9wPlB6AJuQg4BZ0Akftg9nrwg+kD5RXhp9+n3xXhwuMD5XboaeyG8o/5nQDIBq8LRRC0EpcTgxR7FYoXyhmNHVkgZSMGJQYlZSNlI1kgPhyKFwwRoAkkAlH7ZPV68H3rduhc54Ppaez07obyYPaR+w4BggchDrQSexV9FnsVlxNFEJwKvgM5/bP3JvN68CXuhep26DbmNuZc54Ppfesl7rvvMPHf8d/xMPF68N/xJvPe9Nb2R/fW9uX1ZPVk9WT13vS/8zDx9O5p7IXqg+l26HbohepM7YbyG/iO/VUDGwrbEcoZ1yF/KE8uoTLuNO407jShMk8uuSZZIIoXDBEiC/IEg/7d+N70hvKG8lH0R/fI+mX+fQHHAnICmwFDAV8BSgL3Ax4G5QdNCE0ITQhNCLkIoAkqCcgGIwNj/1H7R/eG8iXug+k25sLjc+IV4RXhwuNc50ztZPW2/TIEuQgiC68LnApNCK8EOP8b+Hrwheo25nPiKd6b3Jvcp98D5X3rJvPO+68EQQzbEX0WpBjKGcoZyhn9Gj4cPhw+HI0djR3rHlkg1yHXIese/Rp9FkUQKgkkAg77UfT07n3rduhc51znduh964byyPr3A9oMgxTKGY0djR2NHcoZgxR6DXEGnP84+SbzJe6F6nboduiD6X3r9O4m89b2j/l++n76j/mz9+X13vTe9FH0UfTe9GT15fWz9zL6d/zc/QD+DP1++mD23/El7oXqduhc51zng+lM7TDx1vbc/cgGDBH9GgYlSSxsMKEy7jTuNKEySSy5Jlkgyhm0EkEMzgVCAEL8OPlH92D2s/fi+Qn8Zf0j/iP+DP0O++L54vmR+yP+QwEyBHEGuQgiC3oNhg9FEIYPeg0qCW8ECv/d+IbyTO126APlc+IV4affp98V4QPlheow8Rv4AP4AAm8EzgUeBq8EQwGr/LP3v/O7733rdugD5cLjc+Jz4sLjdugl7t70zvskAoIHrwvQDtsRgxSkGD4c6x7XIdchZSMGJQYluSa5JgYlZSPrHsoZlxNBDK8Eg/7i+WD2JvN68CXuTO1p7CXuMPFg9jn9MgScCkUQgxSKF8oZyhmKF3sVtBIhDrkIIwOO/bP3hvIl7oXqg+mF6mns9O568N/xhvIm87/zZPXW9t344vmP+d34G/hH92D25fXW9hv4fviz92D23vTf8fTuTO1p7GnsaexM7fTuu++G8uX1UftyApwKtBL9GtchfyhJLE8ubDBsME8uWioGJY0dfRbQDsgGof6z94byu+968CbzYPbi+av8Zf7y/r3+Iv92ACQCIwO+A/cDMgRvBPIEHgblBxsKrwtBDK8LoAkeBt0BZf04+WT13/Fp7Fznc+Ip3pvcm9wV4TbmTO1R9FH7fQHOBeUHTQgjB/IEfQGr/Ef3MPGF6gPlp9/62oHXR9mb3HPiheom8877IwO5CNoMRRCXE30WihekGMoZyhnKGf0aPhyNHVkgZSMGJQYl1yGNHX0WRRCgCfcDg/7d+CbzTO126APlwuM25oXqMPGP+XICGwpFEIMUihekGKQYfRbbEdoMyAbIAH76v/NM7XboNuY25lznheol7jDxhvIm8ybzv/NR9N70ZPXl9eX13vRR9L/zv/NR9Nb2j/lC/GX9q/zi+WD2hvK77yXuTO1p7H3rfetp7CXuMPFg9mX9ggXQDooX6x4GJVoqTy5PLk8uTy5JLH8oZSPrHqQYRRAqCQACd/x++Nb2s/eP+ZH7zvsO+zL64vl++s77tv3O/yQC9wOCBcgG5QcqCRsKQQx6DSEOQQwqCa8EBgBC/Dj51vZR9Hrwaex26APlc+IV4XPiNuaF6rvvUfQ4+d38Iv+dALsBAAL2AAr/DP0y+mD23/Fp7FznwuMV4affwuN26PTuZPVR+7IAcQZBDNsRfRb9Guse1yFlI2UjZSPXIdchZSNlIwYlZSNZIP0afRYMEXoNGwojB/cDnP/I+mT1evBM7X3raey771H0MvpTAB4GrwsMEYMUihekGKQYihd7FQwRIguvBDn9ZPW7733rg+mF6n3rTO307nrwhvLe9LP34vnO+2X9AP6O/c77OPlg9lH0v/O/8970ZPXl9d70JvOG8obyhvIm8ybzJvOG8t/x3/Hf8Sbz5fXI+n0BKgnbEaQYWSAGJVoqTy5sMGwwbDBJLH8oZSM+HLQS5QfY/hv4UfRR9OX1s/fd+DL6Cfwj/mQAcgJvBB4G5QcqCSoJ5QdxBjgFOAUeBuUHGwobCioJIweCBb4DuwFj/wn8s/eG8mnsXOcV4Zvc+tqb3KffA+WF6jDxYPYO+wr/AAK+A/cDcgK+/938OPm/82nsA+Up3kfZR9n62qffNuZp7L/zfvreAHEGIgvQDrQSfRakGMoZpBikGIoXpBjKGT4c6x5ZIOsejR3KGXsVDBHaDLkI9wPy/jj5JvNM7YPpNuY25nboJe6/88j6mwHlB3oN2xF7FYoXfRaDFLQShg8iC84Fof5H93rwaeyF6oXqfetp7Ezt9O568N/xhvIm81H05fVH97P31vbl9d70v/O/8+X1G/g4+Tj5G/hg9lH0JvMw8bvv9O707vTuu++773rwhvLl9X763gDlB9AOexX9GtchuSZaKkksSSxJLFoqWiq5JtchyhlFEIIHFABR+3741vbl9eX1YPZH97P3G/h++H76Of1TAFUDggXIBsgGyAYjB7kIGwqcChsKTQjOBb4DfQHy/kL8j/nW9r/zu+9961znwuMV4RXhc+ID5Xbofeu771H0fvjO+wD+8v5j/+z/ZADO/479fvgw8YPpc+Ip3pvcm9yn38Ljhep68GD2QvxKAk0IIQ6DFMoZjR3rHuse6x6NHeseWSDXIdch6x4+HMoZiheXEwwReg2cCiMHxwIj/t34JvMl7oXqduiD6WnsevBk9ZH7cgK5CCEO2xGDFH0WiheKF30W2xEbCt4AG/h68IXqNuYD5cLjA+Vc54Ppaey77ybz5fXd+JH7Zf2O/ZH7fvjl9VH0v/NR9FH0UfTe9GT15fXl9WT1ZPXe9N703vTe9FH0hvIw8Xrw3/He9Dj5Tv8eBtAOihfrHgYlWipPLmwwbDChMmwwSSxlI6QYIQ6vBN38R/dR9L/z3vTW9n74fvpC/Nz9vv8kAjgF5QegCSoJ5QdxBh4GyAaCB00IKgkbCpwKIgucCioJcQZVAxQAq/zd+L/zJe526MLjFeGn3xXhwuNc50ztJvM4+SP+9gByAokDrwSCBTgFxwKO/WD2Je425qffm9yb3Cnec+J26PTu5fXO+w4BHgYiC0UQfRbKGT4cPhw+HD4cjR3rHlkg1yHXIdchWSDrHj4ciheXE4YPIgsjByQCQvzl9XrwaeyF6oPpheol7ibzj/mdAMgGIgt6DUUQ2xGXE4MUlxMMEa8L8gS2/db2evB963boXOdc53bog+mF6n3raez07t/xZPUb+I/5j/k4+d34G/iz90f3R/ez9xv4G/hH92D2UfSG8t/xMPHf8YbyhvKG8obyJvO/82T1fvgM/ccCoAkMEX0W/RrrHtchBiV/KEksSSxJLLkmWSCKF9AOcQby/o/55fW/84byhvKG8t/xJvPe9N34tv1yAnEGKgmcCiILrwsiC5wKGwoqCbkI5QdxBvIEIwNDAXf/3P13/H76R/cm8/TuheoD5RXhp98p3qffwuNc52nsu+8m8+X13fh3/IkAMgSCBb4DTv9++Hrwg+lz4inem9yb3KffA+WF6vTu3vTO+4kDQQyXE8oZjR3rHlkgWSBZIFkg6x7rHo0djR0+HP0apBh9FoMUtBIMEYYPQQyCB3ICq/zW9nrwaeyD6YPpfesw8db23fxyAiMHIguGD4MUpBj9GsoZfRYMEbkIBgBH9/TudugD5cLjA+U25lzng+l967vvv/Mb+A77DP2O/av8yPp++GD2UfQm84byJvO/87/zUfRR9FH0UfTe9GD21vZH99b2ZPW/89/xevB68CbzG/iD/s4F2gyXE6QYjR3XIbkmWipPLk8uWioGJT4ctBKgCWQAOPne9Iby3/Hf8d/x3/GG8t70G/jO+5z/9AI4BcgGIwfIBh4GOAXyBDgFHgbIBoIH5QflB8gGOAX3A0oC7P+r/H74v/P07oPpwuMV4affFeHC43boTO0w8VH0YPaP+Tn9XwHyBHEGggWbAo79YPb07lznc+Kn36ffc+I25oXqJe7f8bP3Rf44BUEM2xF9FsoZPhzrHuseWSBZIFkg1yFZIFkg6x4+HKQYfRaXEwwRIQ4bCh4GQwEJ/GD2evB963boduiF6iXuJvOz9wn8d//0AoIHQQwMEYMUexV7FZcT0A6CB3f/G/iG8iXufeuF6oPpduhc53bog+lM7TDx3vR++A773fxl/Tn9q/wJ/A77MvqP+Tj5G/jW9mT1v/Mm8ybzv/Nk9db2s/cb+LP3YPZk9WT11vYy+tj+bwQbCtAOtBJ9Fj4c1yF/KE8ubDBsMGwwWiplI8oZDBFNCEMBzvuz99703/G77/TuevAm80f3d/x9AR4GoAlBDNoMeg16DUEMIgsbCioJTQiCB3EGHgbOBfIEbwS+A/QCfQHy/sj63vT07oPpA+XC48LjA+U25nbohepM7d/x1var/HICIwecCiILTQjdAY/5MPGD6QPlFeGn36ffFeHC43boJe7e9N38OAV6DYMUyhk+HOseWSBZIFkg6x6NHT4c/RrKGaQYfRZ7FYMUlxPbEUUQIQ4iCx4Gd/9++DDxfetc51znduh96/TuhvLW9pH79gAjB3oNtBKKF8oZpBiDFHoNggXd/N709O6F6lznwuNz4hXhc+LC43boaeww8d70G/ji+X76fvqP+X741vZk9VH0JvOG8t/xevB68HrwMPHf8b/z5fXW9kf3YPbe9CbzMPEw8Sbz1vYO+zj/iQPlB9oM2xGkGOseBiVaKkksSSxaKmUjPhy0EhsK9AIM/Rv4UfR68CXufet96yXu3/Fg9g77iv9VAx4GTQgqCRsKoAkqCbkI5QfIBs4FOAUyBMcCXwGdAJ0AiQCt/2X9j/ne9PTuhepc5wPlA+U25lznduiD6X3rJe7f8db23fz0AoIHKglNCPIEiv84+SbzJe6D6VznNuYD5TbmXOeF6rvvYPYA/oIF2gy0EooXPhzrHtchZSMGJQYlZSPXIesejR39GooXgxTbEQwRRRCGD3oNGwqCBTIADvvW9lH0JvMm87/z3vRg9hv4Mvpl/QAC5QchDoMUpBj9Gv0aihfbEa8LOAUi/4/5UfT07oXqXOcD5QPlNuaD6UzthvLW9n76Of0i/2QA3gB2AE7/jv1R+934YPYm83rwJe5M7SXuevAm82D2fvg4+d34fvh++N34MvrO+7b9nP+bAfcDyAacCoYPfRbrHgYlSSxPLk8uSSx/KFkgyhnbEZwKVQN3/Nb23/El7mnsTO2771H0OPm9/r4D5QevC9AODBHbEUUQ0A7aDCILKgmCB84FMgRVA4kDrwQeBiMHHga+AyMAzvtH9ybzu+9p7IXqg+l26HboduiD6Uzt3/Hd+FMAcQYbCq8LGwrIBigBfvpR9CXudugD5XPiFeEV4cLjXOcl7uX1I/4eBtoMtBKkGI0d1yFlI2UjZSPXIesejR0+HMoZihd7FXsVexV9Fn0WexW0EtAOKglVA9z9OPlk9Sbz3/Hf8d/xJvPe9LP3QvybAhsKRRB7FaQYyhmKF5cTeg2CB4kAj/km80ztdujC4xXhFeFz4jbmheol7t/x3vSz9+L5zvur/N38Cfx++t341vbe9IbyevD07iXu9O4w8b/zZPXW9kf3R/dH99b21vZH9xv44vnO+yP+sgC+A4IHQQy0EsoZWSC5JkksSSxJLH8oZSM+HHsV0A6CB3YA4vm/8/TufeuF6n3rJe7f8WT14vmh/lUDIwcbCq8LQQxBDCILnAoqCYIH8gTHApsBfQFKAiMDiQMjA90BY/9C/N34ZPWG8rvvJe5M7X3rg+l26Fzng+lp7N/xG/iD/r4DIwdNCCMHbwRTAFH75fV68H3rXOfC4xXhFeFz4lznTO1R9Mj63QEqCUUQihc+HFkg1yFlI2Uj1yFZII0dyhl9FpcT2xHbEdsR2xHbEUUQeg2gCR4GAALc/X76G/hg9lH0JvPf8TDx3/He9H76XwEqCUUQexWkGMoZpBh9FtsRQQw4BQD+1va773bowuOn36ffc+ID5YPpTO0w8eX14vll/ez/9gDIAJz/jv0O+7P3v/O772nsfetp7CXuevAm8970YPYb+Dj54vky+jL6fvoO+0L8Of22/WX+IwD3A6AJDBHKGdchuSZJLE8uTy5aKrkmWSDKGdsRoAkoAd343/FM7X3rhepp7PTuJvN++AD+iQNNCK8Leg3QDtAOeg1BDBsKyAa+A30BQgAyAEMBmwK+AzIE9wObAjIADP3i+WD2JvN68Ezthepc5wPlwuMD5Vznaewm8+L53f8yBCMHTQjIBr4DIv/i+VH0Je526MLjFeGn3xXhA+WD6fTuZPWr/DIErwvbEYoXPhxZINchZSPXIdch6x79GooXexWDFIMUgxSDFIMUtBIMESEOGwoeBt0B3P1++hv45fW/8zDxu++779/xYPZ3/CMDoAmGD4MUiheKF30WlxOGD5wKbwQ5/WT1Je526APlwuPC4wPlXOeD6Uzt3/Hl9Tj5Qvxl/q3/IwC+/0X+kfsb+FH03/F68HrwMPHf8SbzUfTl9db2s/cb+H74OPky+lH7Qvx3/Hf8d/w5/b7/MgQbCgwRiheNHWUjuSZ/KH8ouSZlI+seyhnbERsKJAIO+2T1MPEl7mnsTO307obyR/d3/F8BzgWgCUEMIQ6GD4YPIQ4iC00IggUjAwAC3QEkAkoCSgIAAigBiv9l/VH7OPnW9t70hvK7733rXOcD5cLjwuM25oXqevBg9kL8nQCJA/IE8gS+Aw4Bq/xH9zDxheo25nPiFeFz4sLjXOd969/xOPlfAaAJDBF9Fj4cWSBlI2UjZSNZII0dyhl9FpcTtBLbEQwRDBHbEQwRhg96DRsKcQYjA2QA3P0O+0f3v/N68PTu9O4w8d70fvpDAU0I0A6XE30WpBikGIoXlxMhDiMHvf7W9nrwfetc5wPlwuPC4zbmg+lM7Yby1vYy+gz9rf9fAX0B7P+r/H74UfQw8SXuaex962nsTO2779/xv/Nk9WD21vaz9374j/mP+d34R/dg9mD2s/fI+or/ggXaDJcT/RpZIGUjuSa5JgYl1yE+HIMU2gxvBN38YPYw8UztfeuF6n3r9O4m8374jv3dAYIFuQgiC9oM2gyvCyoJcQYyBEoCQwEOAV8BAALHAokDiQNyAnYA3P1R+zj5R/dR9DDxTO2D6TbmwuPC4zbmg+kl7ibzfvhl/UMBvgOvBL4DfQGO/Rv4hvJp7FznwuNz4nPiwuM25oPp9O5k9av8vgOcCgwRfRY+HFkg1yHXIVkg6x4+HMoZihd9FnsVexV7FXsVgxS0EoYPIgvlB/IEmwIGAAz94vnW9r/z3/F68DDxv/Oz9wz9cgKCB0EMhg+0EoMUgxTbESEOuQi7Acj63vS7733rdug25gPlA+Vc54XqJe7f8WT13fjd/AYAfQFfAfr/tv3I+rP3UfTf8Xrwu++77zDxhvJR9N705fXW9n74fvp3/I79I/4A/jn9q/zd/IP+mwEeBq8L2xGKF40d1yEGJX8ofyi5JgYlWSDKGdsRGwojA938R/eG8rvv9O677ybzYPZ++qH+IwPlB0EMhg8MEUUQ0A5BDKAJIwc4Bb4DIwNVAzIEOAWCBTgFvgNyAl8BMgCh/qv84vlg9jDxaeyD6VznNuZ26H3ru+/e9OL5vf5yAvIEHgYeBjIEiQDO+2D2evB961znA+XC48LjNuaD6fTuZPVC/CMDGwoMEYoXPhzrHtchWSDrHj4cpBh7FZcT2xHbEbQSlxOXE7QSRRAhDkEMGwrlBx4G9wOdAHf8s/e/8zDxu+8w8b/zG/hl/VUDKgkhDrQSexWKF30WlxPQDk0I9gDi+SbzTO126APlc+Jz4sLjNuaD6Uzt3/Hl9Y/53fwi/wYAY/9l/X761va/83rw9O4l7rvvMPEm89705fVH9374MvoJ/Nz98v4K/0X+DP2R+8j6kfvc/V8BcQZBDLQSpBjrHmUjuSZ/KH8ouSbXIT4cexUhDnEG2P6z99/xJe5p7GnsJe568L/zR/dR+4r/vgMjByoJoAkqCYIHOAX0AsgAY/8K//r/fQGbAvQCcgJDARQAOP+D/rb9d/wy+tb2JvMl7oXqXOcD5QPlXOeF6vTuv/Pd+Dn93gAjA/cD9AJCAHf8G/gm8yXug+k25sLjc+Jz4gPlduhp7Iby3fi+/8gGeg2XE6QYPhzrHusejR39GooXexWDFJcTgxSDFIMUlxPbEUUQIQ5BDCILGwpNCM4FcgJF/jL6YPZR9CbzUfRg9o/5AP4jA7kIIQ7bEYMUexWDFNsRIQ4qCfQCQvzl9Xrwfetc5wPlA+UD5Vzng+lM7TDxZPWP+Tn9IwAkAnICKAFF/sj61va/84by3/GG8obyv/NR9GT1YPYb+H76Of2K//YAfQEOAd3/AP53/Hf8I/5fAc4FnApFEH0WPhxZIAYluSa5JgYl1yGNHYoXhg8jB/L+s/ff8SXuaex962ns9O7f8eX1yPpj//cD5QciC9oMQQycCoIHbwQkAt4AsgDeACgBXwEoAYkAzv84//L+vf5F/jn9DvtH9ybzJe6D6TbmwuPC4wPlduhp7N/x1vaR+wr/9gCbAUMBrf+r/Bv4JvNM7XboA+Vz4hXhc+ID5XboJe6/88j6mwG5CEUQfRY+HOseWSBZII0d/RqKF30WexV9Fn0Wihd9FnsVlxPbEUUQhg8hDtoMGwrIBnIC3P2P+eX1v/Mm87/zYPYy+iL/8gScCtAOtBKDFHsVgxTbESEOKgn0AkL85fW7733rduhc5zbmXOeD6Wnsu+8m80f3yPpF/sgAAAIoAb3+kft++GD23vRR9GT1YPZH9xv43fiP+X76zvuO/a3/XwEkApsBQgBF/qv8CfwM/WP/mwIjB9oMtBKkGI0dWSBlIwYlBiVlI1kgPhx7FSEOyAac/+L5ZPWG8jDxMPHf8b/zYPbi+Tn99gCvBE0IGwqcChsKTQgeBq8E9wP3A28EOAXOBYIFrwSJAyQCDgGJABQATv/c/VH7s/e/8/Tufet26FznXOeD6WnsMPFk9Y/53fyK/0MBuwEOAWP/3fw4+d70evBp7HboNuY25jbmduhp7HrwZPUO+18B5QfQDoMUyhk+HI0dPhz9GqQYihd9Fn0WiheKF4oXexWXEwwRhg/QDnoN2gyvC6AJyAabAkX+MvrW9r/zhvIm8+X1j/kA/scCggdBDIYP2xG0EtsRRRDaDE0IcgJC/GD2evBp7HboXOc25lznduiF6kztevBk9eL53P1TAPYArf8M/eL51vZR9Iby3/Hf8SbzJvO/87/zUfTl9X74zvvY/rIADgEyAL3+DP1R+zL64vmR+wr/iQNNCHoNtBKKFz4cWSBlI2UjZSPrHsoZtBKvC/cD3fzW9t/x9O4l7iXu9O568L/zs/fd/N0BcQYqCZwKGwq5CHEGMgRKAg4B9gCbAUoCcgJyAgACfQFfAZsB3QHdAZ0AAP5++uX1MPFp7FznA+XC48LjNuaF6vTuv/N++EL8OP/2AJsBDgFO/wn8s/eG8iXug+k25gPlA+U25oPpaeww8db2q/yJA5wKDBF9FsoZ/Rr9GqQYfRaDFJcTlxODFHsVexWDFJcT2xGGDyEOeg3aDCILKgnOBXICRf6P+WT13/F68Hrw3/Fk9TL6Tv9vBCoJ2gxFENsR2xEMESEOGwryBPL+3fgm8yXufeuD6XboXOd26Hboheol7t/xYPYy+qv8tv22/UL8j/nW9lH0v/O/81H03vRk9d70UfTe9OX1G/h++qv8Rf53/87/Iv+2/UL8UftR+6v8nP+JA+UH2gzbEX0W/RrrHtchZSNlI9chjR3KGZcTQQzOBd3/Dvuz92T1v/OG8ibz3vSz9wn8iQCvBOUHnAqvCyILGwpNCCMHHgYeBsgGggeCB8gGggUyBIkDVQOJA1UD9AKbAXf/Qvwb+L/zu+9964Ppduh26IXqJe4w8d70G/hR+2X+iQAoAYkA8v5C/N343vR68EztheqD6Xbog+mF6kztMPFg9jn9bwQiC9sRfRbKGf0ayhnKGaQYiheKF4oXiheKF30WgxS0EgwRRRDQDtAOIQ7aDCILKgkeBnICAP6P+eX1v/Mm81H0R/cO+07/9wO5CHoNDBG0EpcTlxPbESEOKgnHAnf81vbf8SXuhep26FznXOd26H3ru+9R9N34q/x3/4kArf9l/X76s/dg9mT1ZPVk9d70UfRR9N701vY4+UL8OP+7AYkDMgT3A5sCnQCD/jn9DP0A/gYA9ALIBiILRRB7Ff0a6x7XIWUjZSPXIY0dihcMEaAJ9AIM/Rv4v/Mw8bvv9O568Cbz1vbI+iL/9ALOBSMHIwceBvcDAALIAHYAsgAOAV8BXwEOAd4A9gB9ASQCmwKbApsBnP/d/Dj5UfT07oXqXOcD5QPlNuZ26H3r9O4m80f3yPo5/aH+vf5l/Q77R/eG8iXuhepc5wPlA+UD5QPlXOeF6vTu3vQJ/CMDKgkhDtsRlxODFJcTtBK0ErQSlxODFHsVexWDFLQS2xHbEQwRRRCGDyEO2gwiC00IrwR2AAn8fvjl9d703vRg9t34q/wOAYIFoAl6DUUQ2xG0EtsRIQ6gCTIEIv8y+mT1MPFM7YXqduhc51znduh96/TuhvLW9uL5UftR++L5fvhH92D2YPZg9mD25fXe9FH0UfTe9OX1s/fi+Qn8AP6c/4kAZACc/6H+AP7c/WX+d/9fATIE5QdBDAwRexXKGY0dWSDXIdchWSA+HIoXtBJBDHEGyACR+0f3v/Mw8bvvevAm82D2yPoi/yMDHgaCB+UHggcjB3EGcQYjByMHcQaCBW8EiQMjA1UDiQOJA4kDiQOJA5sCdgAM/d343vQw8SXuaex9633rTO168L/z1vZ++o79UwBKAvQCJAL6/938OPlk9TDxJe5963boXOc25lzng+n07t70UftKArkIIQ4MEZcTgxSDFIMUexV7FXsVgxSXE9sRDBFFEIYP0A7QDiEOIQ4hDnoNQQygCc4FmwFl/Y/5YPbe9FH0ZPUb+FH7OP+JA00I2gxFELQStBIMEdAOnAqCBd3/fvpk9Xrwaex26DbmA+U25nboaeww8WT1OPmR+0L8kfsy+jj5G/hH9+X13vS/84by3/Hf8Sbz3vRg9t34kfvc/Yr/nQD2ALIAnP8j/qv8kftR+wn8AP5DAYIFnAqGD3sVyhnrHlkg1yFZII0dyhmDFNAOoAn3A2X+j/lk9Yby3/Hf8b/z1vbI+gr/9AKCBcgGyAYeBoIFggWCBR4GHgYeBs4FHgbIBiMHIwcjB4IHggeCByMHggUjAyMAd/x++FH0evAl7mnsaexM7bvvhvLl9Tj5q/wi/50AQwGdANj+Cfzd+OX1JvN68EztheqD6Xbog+l96/TuJvM4+Qr/rwQqCUEMIQ6GDwwRtBKXE3sVfRZ9Fn0WfRZ9FnsVgxS0EgwRRRCGD9AOeg1BDBsKIweJAwYAq/yP+bP3R/ez9374yPrc/X0BOAVNCK8Leg3QDtAOeg0iC00IbwSyAKv8fvi/87vvaeyD6XboduiF6kztevC/8+X1R/cb+N34j/ky+sj6yPoy+jj5G/hH92D25fXl9WD2s/fd+Mj63fyh/mQAuwFyApsCSgLdAZsBmwEAAiMDggW5CNoMDBF7FaQYPhzrHuse6x6NHcoZfRa0EnoN5QckAt38G/hR9N/xMPGG8mT13fh3/Dj/XwHHAjIEggXIBuUHTQjlB+UHggfIBs4FrwS+A1UD9AIjA4kDvgO+A/QC3QHd/wz9j/nl9Yby9O5M7X3rfetp7PTu3/Fk9d34zvu2/aH+of4A/qv8yPp++GT13/El7n3rduhc51zng+lp7IbyfvjY/m8EKglBDIYP2xGXE3sVfRZ9Fn0WfRZ7FXsVgxSXE9sRDBFFEIYPhg+GD4YPIQ6vC7kIOAV9Adz9MvpH92T13vRg9n74CfwGAG8EuQhBDCEOhg/QDnoNIguCB4kD8v4y+t70u+9961znNuY25lznheol7jDxv/Nk9WD2R/ez9xv4G/iz99b25fXe9N703vTe9GT1YPZH93744vmR+2X92P6t/wYA+v9O/wD+d/xR+1H7d/y9/gACHgacCoYPgxSKF/0aPhw+HP0apBh7FQwRQQyCB5sCjv3d+N703/Ew8d/xUfSz9zL6d/xF/r7/9gDdAZsCVQP3A68EggVxBiMHggeCB4IHIwfIBnEGHgbOBfIE9wMkAgYAZf1++tb2v/Mw8fTuJe5M7SXuu++G8mT1fvh++s77QvxC/M77DvuP+bP35fW/8zDx9O5p7IXqg+mF6kztMPFg9g77OP8jA3EGoAnaDIYP2xGXE3sVihekGMoZyhmkGKQYfRaDFLQS2xEMEYYPIQ7aDK8LGwrlBzgFJAI4/6v8yPqP+Tj5MvpC/Nj+uwGvBCMHKgmcCiILIgucCqAJ5QeCBQACjv1++CbzJe5964Ppg+mF6mnsJe6779/xJvNk9Uf3OPky+n76yPp++uL53fh++Bv4s/fW9tb21vaz9zj5yPoM/Xf/mwEjA74DvgMjA0oCmwFDAd0BVQMeBioJ2gxFEIMUihfKGT4cPhw+HP0apBh7FdsReg2CBw4BUfvW9lH0JvO/82T1s/cy+kL8g/7IAMcCbwQeBoIHTQgqCbkIuQhNCIIHyAYeBoIFOAXyBPIE8gTyBG8EVQPdAb7/3fw4+WT13/El7n3rhep962nsJe4w8b/zYPZ++OL5DvtR+1H7fvrd+Nb2v/O7733rdug25jbmXOeF6vTuv/N++Kv83gDyBLkIrwshDkUQ2xG0EpcTgxSDFIMUlxO0EtsR2xEMEQwRRRBFEIYP0A56Da8LuQg4BQACg/5R+zj5G/gb+I/5Qvx3/yMDcQagCa8L2gx6DdoMQQycCk0IOAWJAA77ZPV68GnsheqF6n3raexM7fTuevCG8r/z3vTl9db21vZg9mD2YPZg9mD21vZH90f3s/ez9xv4fviP+VH7Zf3y/t3/ZACJAAYAOP+9/tj+3f/dAW8EggciC9AOtBJ9FqQYyhn9GsoZpBiKF3sV2xF6DSoJvgOD/n76s/dg9mD21vZH9374j/nI+s77q/yO/b3+IwCbAVUDrwTOBSMH5Qe5CCoJuQhNCIIHyAbOBfIE9wPHAl8Bvv+2/Q77G/je9IbyevB68HrwMPEm81H05fWz9934OPmP+Tj5OPk4+d34s/fl9b/zevBM7YXqg+mF6n3rJe568L/z1vbi+Qz9MgD0As4FuQivC9AO2xGXE3sVfRaKF30WfRaDFLQSDBGGD9AOIQ56DUEMrwsbCk0IzgX0AjIA3P0J/FH7Uft3/CP+QgCbAvIEyAblByoJoAmcCpwKnAq5CIIFdgDI+mT1MPEl7n3rg+mD6YPpg+mF6mnsJe6779/xJvNR9GT15fXl9WD2YPbW9tb25fVk9VH0UfTe9OX1s/fi+UL8of6JAH0BuwF9ASgBDgEoAbsBmwIyBMgGnAohDtsRexWKF8oZ/Rr9Gv0a/RqkGHsVRRAbCvcDg/7i+db23vRR9N705fXW9hv4j/nI+nf8I/7O/0MBmwKJA28EOAXOBR4GcQZxBsgGyAYjB8gGyAZxBnEGzgWvBPQCdgBl/eL5YPa/89/xMPEw8d/xv/Ng9hv4j/nI+pH7zvtC/Hf8q/zO+4/55fXf8SXuhep26FznduiF6kztevBR9Bv4Ufsj/t4AvgNxBioJrwshDoYPDBG0EpcTgxSDFIMUgxSXE7QS2xEMEUUQ0A56DUEMGwqCBzIE9gAA/s77fvp++pH7tv12AFUDzgXlByoJoAkbCpwKrwsiC6AJcQabAgD+OPlk9d/xu+8l7kztTO0l7vTu9O6773rwMPHf8Sbzv/NR9GT1YPZH9374OPmP+eL5Mvoy+jL6MvoO+wn8DP0A/iL/BgCdACgBfQF9AV8BmwHHAvIE5QciC9AOtBJ7FYoXiheKF6QYpBikGIoXgxTbEXoNuQj3AwYADP0O++L5j/mP+Y/5j/k4+d34OPky+s77tv36/yQCMgQeBuUHKgmcCiILrwsiCxsKKgmCB84FrwSJA5sCmwEjAGX+QvyP+Uf3ZPW/8ybzJvNR9GT1YPZH90f31vbW9kf3fviP+eL5j/kb+GD2v/Mw8bvvJe5M7SXuu+/f8VH01vZ++H76DP0jAFUDIwecCiEO2xGDFH0WpBikGKQYpBiKF3sVgxTbEUUQIQ56DdoMQQyvC5wKTQjOBccCFAC2/c77DvuR+wz92P5kAEMBuwGbAjIEcQZNCBsKGwoqCcgGVQMi/376YPaG8rvvJe5p7Gnsfet962nsTO307rvv3/Em8970YPZH9xv43fg4+d34fviz90f3R/dH90f3G/iP+VH7Of1O/w4BAAIkAgACfQGdACMAiQAkAjgFuQivCyEORRDbEYMUfRaKF8oZyhmkGH0WtBIhDk0IIwMK/wn8Mvo4+Tj53fjd+N34j/ky+pH7DP3Y/okA3QEjAzIEOAVxBoIH5Qe5CCoJuQhNCIIHIwfIBh4GzgXyBIkDXwGD/pH7fvhk9YbyevB68DDxJvPe9GT15fVg9kf3G/g4+X76yPp++o/5R/dR9DDxJe5p7H3rfetM7bvv3/FR9Nb2OPmR+yP+yACJAx4GuQivCyEORRC0EpcTgxR7FX0WexWDFJcTtBIMEYYP0A56DUEMGwpNCB4GVQNCAGX9kftR+3f8of52ALsBcgL0Ar4DrwTOBSMHTQi5CE0IyAb3A50A3fw4+WD2UfSG8jDxu++77/Tu9O4l7vTu9O6773rw3/Em8970YPZ++OL5DvvO+0L8QvxC/JH7yPoy+uL54vl++pH73fwj/vL+OP8K/6H+of53/30BMgQjBxsKrwt6DSEO0A5FEAwRtBKDFIMUtBIMESEOGwoeBscCMgBl/t38zvvI+jj5s/fW9mD21vYb+I/5Uftl/c7/SgKvBCMHKgmcCq8LQQxBDCILoAnlB3EGOAUyBFUDxwIkAg4BY/85/X76fvjW9tb21vZH90f31vbW9mD25fVg9tb2G/iP+cj6Dvt++t341vZR9IbyMPF68HrwMPHf8Ybyv/Pe9Nb23fgO+wD+XwHyBLkIQQzQDtsRlxODFHsVexV7FYMUtBIMEYYPIQ56DdoMQQxBDK8LnApNCDgFSgIjAPL+vf4i/5z/+v9CAIkA9gDdAVUDOAWCByoJGwqgCU0IHgabAqH+yPpH91H0hvJ68CXuTO1p7GnsTO1M7SXu9O677zDxJvPe9GD2R/cb+H74OPk4+d34fvgb+Bv4fvg4+X76QvyD/okAJALHApsCuwEoAUMBSgJvBCMHoAlBDCEOhg8MEbQSgxR9FqQYpBikGIoXlxOGDyILcQb0AokAof7d/FH7Mvo4+d343fjd+Dj5j/ky+lH7q/xF/r7/QwFVAzgFIwe5CCoJoAmgCSoJuQjlByMHcQbOBfIEVQP2ACP+Ufvd+Ef3YPZg9kf3s/d++Dj5OPk4+Tj5j/ni+cj6DvsO++L5G/hk9d/xu+8l7kztTO0l7vTuMPEm81H05fXW9n744vnO+yP+3gC+A8gGoAlBDIYP2xGXE5cTgxSDFJcT2xFFENAOeg1BDCILGwrlB4IFxwJTAKH+3P3c/YP+d/92ACgBmwG7Ad0BSgIjA/cD8gSCBR4GggVVA3YAZf3I+hv45fW/89/xMPG77/TuTO1p7IXqg+mD6YPphepp7CXuu+/f8VH0YPYb+I/5Mvp++jL6j/nd+Bv4G/g4+X76Cfy2/dj+Y/93/93/DgH0AjgF5QecCtoMIQ7QDoYPhg9FEAwR2xGXE5cTlxMMEdAOrwu5CM4FVQMoAQr/DP1R+4/5s/fl9b/zhvKG8obyv/Nk9bP3fvpl/XYAIwOCBSMHuQgqCbkI5QceBvIEvgP0AgACQwF2AGP/AP5C/Mj6j/l++Bv4G/h++N34G/hH92D25fXl9WD2R/fd+OL5MvqP+Rv4YPbe9Cbz3/Ew8TDxMPHf8Ybyv/NR9GT1YPaz9+L5d/yt/yMDyAacCnoNDBG0EoMUfRZ9Fn0WgxSXE9sRRRCGD9AOIQ4hDnoNQQwbCuUHHgYyBPQCmwKbAscCxwL0AiMDiQP3A/IEcQa5CJwKrwuvC5wKuQgeBscCOP/O+934YPZR9Cbz3/F68LvvJe5M7UztTO0l7rvvevDf8Sbzv/Pe9GD2s/d++Dj5j/k4+d34fvjd+I/5kfuO/WP/ZADIALIAMgAjAMgAcgLyBIIHoAmvC3oN0A5FENsRlxN7FYoXiheKF3sVlxNFENoMKgkeBokDfQHd/6H+Zf0J/Mj64vnd+Bv4s/ez9xv4OPl++nf8Zf6dACMDggXlByoJGwobChsKKgnlByMHcQaCBTIEmwKJACP+kfs4+Rv4s/cb+N344vl++n764vk4+d34OPni+TL6fvp++uL5fvhg9lH0hvIw8XrwevAw8Ybyv/Pe9GT15fVg9tb2s/fd+DL6q/yK/5sCzgUqCdoMRRC0EoMUexV7FXsVlxPbEQwRhg8hDnoNrwsbCuUHzgX3A5sC3QHdAccCMgSCBc4FzgU4BfIE8gQ4Bc4FyAaCB4IHggdxBvIEmwL6/479kfvi+d34s/dg9lH03/G770ztaex964Xqhep960zt9O4w8Sbz5fUb+DL6UfvO+w77j/kb+Ef31vZH9934MvqR+0L8q/w5/dz9Iv8OAb4DyAagCSILQQzaDNoMIQ7QDkUQ2xGXE5cTlxO0EgwRhg/aDJwKTQhxBq8E9AIoATj/Of0O+934R/dg9uX15fVH9374yPqO/UIAIwPOBU0IGwoiCyILGwq5CCMHggWvBPcDVQObAl8Bvv8A/gn8yPoy+n76DvsO+8j6Mvo4+Rv4R/dH97P3fviP+X76yPp++o/5fvjW9mT1UfS/87/zv/NR9N703vRk9WT15fXW9n74fvqr/Hf/mwIeBioJQQyGD7QSgxR7FXsVgxSXE9sRDBFFEIYP0A4hDtoMrwugCYIHOAW+A1UDVQNVA4kDVQMjA/QC9AIjA/cD8gQeBoIHuQigCaAJTQjOBSMDdgAA/gn8fvrd+Ef3ZPW/89/xevD07iXuTO1M7UztJe707rvvMPEm8+X1s/c4+TL6MvqP+d34G/h++Dj54vkO+877d/xC/M77zvt3/EX+nQBVA4IFggcqCZwKQQx6DYYPDBG0EpcTgxSDFJcT2xFFECEOrwugCeUHcQaCBW8EIwObAfr/g/7d/A77j/l++H743fiP+cj63fw4/90BrwSCB6AJIguvC68LnAqgCbkIggceBq8ExwJkANz9zvsy+o/5j/ky+g77zvtC/An8zvuR+1H7DvvI+sj6yPp++uL5fvjW9mT1v/Mm8ybzv/Pe9OX11vZH97P3G/gb+LP3s/cb+Dj5fvp3/Nj+3QGCBaAJeg0MEZcTexV9FnsVgxSXE9sRRRCGDyEOQQycCk0IHgZvBL4DvgNvBIIFcQYjByMHyAZxBh4GOAWvBK8EggVxBiMHyAbOBW8E9AJ9ATIAOP9l/gz9kfvi+Rv45fUm83rwJe5p7H3rheqF6oXqaewl7jDxUfSz9376kfvO+w774vl++LP3R/ez9374OPk4+Tj5j/ky+pH7I/72AL4DcQa5CBsKIguvC0EM2gx6DSEOhg9FEAwRDBEMEYYPIQ7aDCILGwpNCHEGrwT0AigBOP+r/OL5s/fl9d70v/O/81H05fWz9zL6jv0OATIEcQblB00I5QfIBs4F8gQyBIkDxwJ9Ac7/AP5C/A77yPrI+g77kfuR+w77Mvo4+X74s/fW9tb2R/cb+H74fvgb+Ef35fVR9L/zJvOG8obyhvIm87/zUfTe9N703vRk9WD2R/d++OL5CfzY/iQCzgWgCdoMhg8MEdsR2xEMEUUQRRCGD4YPhg/QDnoNrwugCYIHcQaCBYIFggWCBYIFggWCBTgFrwRvBPIEHgaCB7kIoAmgCbkIggfOBb4DuwHO/wD+q/yR+3763fhH92T1v/OG8nrw9O5M7WnsheqF6n3raez07t/xUfTl9Uf3R/fW9mD2YPZH9374j/ky+jL64vmP+Y/5MvqR+7b9IwByAm8EcQa5CJwKQQx6DdAORRDbEbQSlxO0EtsRRRAhDtoMnApNCHEG8gT3AyMDJAIOAZz/jv1R+9341vbe9Cbz3/Ew8d/xv/Ng9uL5Of1kAPQC8gQeBnEGyAZxBnEGzgWvBMcCiQDc/VH7OPl++H74OPni+cj6UfvO+wn8zvuR+w77fvp++n76MvqP+Rv41vZk9VH0JvOG8obyhvK/81H0ZPXl9WD2YPbl9WT13vTe9N70ZPXW9t34zvtj/74DTQivC9AODBHbEdsR2xEMEUUQhg/QDnoNrwugCYIHzgXyBG8ErwQ4BR4GIwflB+UH5QcjB3EGHgZxBoIHTQi5CLkIuQhNCIIHyAaCBTIE9AJ9ARQAZf53/DL6s/fl9b/z3/G770ztfeuD6YPphepp7PTuhvJk9bP33fg4+d34fvgb+Bv4fvg4+Y/5OPnd+N34j/nI+qv88v5fAb4DHga5CJwKQQzaDHoNIQ6GDwwR2xG0EpcTlxOXE7QSDBFFENAO2gwiCxsKuQgjB/IEcgIUANz9Cfzi+Rv45fVR9L/zUfTl9X74zvsi/yQCbwQeBsgGIwfIBsgGyAbIBnEGOAVVA0MBd/8A/jn9q/yr/Hf8q/zd/Kv8CfwO++L5j/mP+eL5fvp++sj6DvvI+uL53fiz92D2ZPXe9N70ZPVH9zj5kftl/WX+Rf6O/Xf8Ufsy+o/5j/l++gn8Zf4oAb4DHgaCB00ITQhNCE0ITQjlByMHcQYeBs4FrwTHAnYACv+K/wACggUqCa8Leg3QDoYPhg9FENsRgxSKF/0ajR2NHT4cyhl9FtsReg0qCYIFcgIGANz9kft++FH0evBM7YXqdugD5XPip9+n33PiA+WD6Wnsu++G8lH0ZPVg9rP3j/nO+yP+Y/8i/6H+Iv9DAfIETQgiC3oNhg/bEYMUexV9Fn0WfRaKF4oXihd9FpcT0A6cCsgGVQOyANz9zvsO+wn8Zf5fAb4DOAUeBsgGyAYeBlUDCv9++uX1MPEl7kztTO1p7Lvv3vRR+4kD2gyDFI0dBiV/KH8oZSONHX0W2xF6DYIHIv9H93rwfeuD6YXqheqD6XboXOcD5cLjwuMD5Xboaey773rw3/Hf8d/xJvNR9OX15fXe9IbyMPFR9DL6KAFNCIYPfRbKGaQYgxSGD6AJggWvBG8EiQMoAQz93fhk9SbzUfTW9sj6Zf3c/Tn9yPqz92T13vRg9jj5jv2bAb4D8gSCBU0I2gzbEcoZZSNJLKEyoTJsMEksfygGJdch6x6kGEUQgge+/8j6R/dg9n74Uft++lH0duhH2anI7bqTrdupk60isc23yMASy4HXNube9K8EtBKNHdchWSCkGK8LUwBR+0L8FACCB9AOexU+HNchfyhsMNo5OD8VQhVC2jlJLMoZHgbl9YPpc+Kb3IHXsdFfzRLLX82m1cLj3/GO/c4FuQhxBiL/R/cw8fTuevCG8ibzJvNg9jn9KgnKGUksOD92S21SbVJ2S3o8SSz9GtoMJAJ++CXuwuNH2bfTsdGm1ZvcA+WF6mnsaex26HPim9ym1bfTt9Om1UfZ+tqn38LjTO0y+ioJpBi5JqEy2jl6PHo8VzdPLgYlPhyXExsKQwGP+b/zJvNH94kAIguDFMoZPhyKF9oMI/5M7SnesdGpyIbDyMDrvYbDEsuB14Xqjv2GD1kgSSyhMqEySSxlI6QYRRAiC7kITQgqCa8L2xGNHVoqVzcVQjNIM0gTRdo5SSzKGc4FJvNz4rfThsOKtNup66HrofmlirSGw6bVA+Xf8TL6q/zI+kf3v/Pf8TDx9O5p7IXqTO1g9jgFyhlPLhVC3k4lVgdaJVZ2S3o8Ty5ZIJcTIweP+UztNuYD5YXq3vSc/4IHGwqCB1MA5fWD6Snet9MSyybGJsaGw8jAJsaUzxXhZPUbCv0auSZJLE8uTy5aKgYl6x79GooXlxMhDk0IggXlB0UQPhxaKu402jnaOWwwBiWXEwr/g+mm1SbGzbeTrdup26kiseu9sdFc58j6GwqXE6QYihe0EqAJRf5R9EztdugD5cLjXOd68Nj+RRDXIWwwVzfaOVc3bDC5JsoZrwsjANb29O425qffR9mB15vcwuP07g779wOgCSILnAqCB77/5fVM7VznwuMV4affFeED5SXuyPoiCz4cSSxXN3o8OD84P1c3SSzrHrQSIwfd/L/zTO196yXu5fWJAK8LlxODFIYPHgbd+Hbogdcmxu26irQisSKxirTtuibGR9lM7VUDexVZIAYluSZlIz4ctBIbCiQCzvvW9ibzMPHf8bP3QwHQDuseSSzuNFc3VzehMloqWSCDFIIHMvpp7Kffgdex0bfT+tpc5374uQiDFD4cWSDXIVkg/RqXExsKd/9R9H3rA+UD5YPpJvNyAoMUBiVsMO40VzfuNGwwuSaNHdsRzgXd+EztwuOb3EfZR9mb3HPiduhp7PTu9O4l7n3rdugD5XPiKd762kfZR9n62qffXOcw8UX+oAm0EooX/Rr9GsoZiheXEyEOyAbc/VH0aexc5zbmheqG8r3+Igt7Ff0aPhykGNsRuQgK/2T1fevC45vc+tr62ineNubf8fYARRDrHn8oTy5PLloqBiXrHooXDBEiC3EGrwQ4BeUHeg19FtchSSyhMlc3VzehMloq6x6DFJwKd/8m8zbmR9mUz6nIhsOGwxLLsdGb3DbmTO168N/xhvIm8ybzJvMw8SXuaex962nsevCz990Beg2kGGUjfyhaKn8oZSPrHsoZlxOvCzIEvf6R+5H7Rf4jA7kIeg0MEdsRhg+gCbsBMvpR9Lvvheo25hXhp9+n33PihepR9KH+ggfQDrQSlxPbEdAOrwsiC68LQQycCrkIcQZvBG8ETQjQDnsVPhzXIQYlBiVZIKQYeg0jAxv4aeyn37fTqcjIwOu9yMCpyLfTp99M7Y/5VQMqCa8LnAq5CIIFUwDi+SbzJe6F6n3rMPF++nEGtBLrHrkmWipaKgYl6x6KF0UQuQh9AX76JvN96zbmwuPC41znaey/8w779gBVA0oCY/8J/H743vSG8nrwJe5M7UztMPHW9qH+uQiXE+sefyhsMKEyoTJsMEksuSZZIMoZRRCCB/YA3P1F/psByAbaDNsRlxNFEIIHUfsl7qfft9OpyMjA7bqKtIq0zbfIwJTPKd4l7rb9GwrbEYMUgxS0EoYPrwu5CIIFmwFl/cj6Ufut/4IH2xH9GgYlWipPLk8uWioGJesefRZ6DZsCZPV26JvcptWm1UfZFeGF6t70jv2+A+UHIgtBDEEMoAnOBRQAG/i774PpNuaD6d/xtv2vC8oZBiVaKk8uTy5PLn8oZSONHXsV2gyJA376JvP07kztaexM7bvvevD07kzthep26APlc+IV4affKd6b3JvcKd5z4nboMPHI+jIEQQzbEXsVpBjKGcoZihd7FdsRQQzyBDn9YPYm8ybzYPYM/TgF2gzbEYMUlxPQDiMH3P1R9H3rwuOb3IHXt9O304HXKd6D6WD2mwJ6DXsV/RqNHT4cihfbEdoMTQjyBMcCcgIyBE0I0A6kGNchfyhPLk8uTy5aKmUjPhyXE5wKQwHW9n3rFeGB15TPEssSy5TPt9OB15vcp9/C4zbmg+l960ztJe4l7iXuTO0l7rvvZPWh/ioJtBLKGese1yFlIwYlZSNZID4cfRZFEJwKcQavBPIETQghDrQSexWXE4YPoAlVAwD+fvgm80ztNuYV4SneKd4V4VznevCR+3EGIQ60ErQSDBGGD9AOIQ4hDtoMrwugCU0IggcjB00I2gyXE/0aWSAGJbkmZSNZIMoZDBHIBsj6TO0V4abVX80mxobDhsMSy6bVp99962T1DP0jA8gG5QdxBscC3fxg9jDxJe5p7EzthvJ3/LkIexXrHgYluSa5JmUjjR19FoYPgge+/zj5JvNM7XboNuY25oXqMPGz96v8IwC7Ad0BKAG+/wz9OPnl9b/zv/O/8970s/cM/fIE0A6kGFkguSZJLE8ubDBPLkksBiWNHX0Whg+5CIkDmwGbAsgG2gzbEYMUtBJ6DYIFCfzf8TbmR9lfzYbD673Nt823670mxrfTwuMm80IAoAmGD7QSgxR7FZcT0A4qCb4DI/7i+bP3j/m9/sgGhg+kGFkgBiV/KH8oWip/KAYljR3bETIEYPaD6RXhm9z62qffNuYl7uX1DP3HAk0IIQ6XE3sVlxN6DfIEDvvf8WnshepM7VH0g/6gCYMUjR1lI7kmWipJLFoqBiXrHooXIQ44Bdz9G/hR9IbyhvIm87/zv/Pf8Xrw9O5M7X3rdugD5RXhp98p3ineFeED5X3rhvJR+1UDoAnaDIYPtBKDFHsVexWXE0UQnApvBCP+OPnW9kf3yPpfASoJhg+0EpcTtBLQDrkISgIO+4byhepz4pvc+tr62inewuMl7uL5ggXQDnsVyhn9Gv0apBiDFIYPoAmvBCgBBgAAAh4GQQyXEz4c1yG5Jn8ofyi5JmUj6x6kGEUQHgYO+7vvNuYp3kfZptWm1YHXgddH2Zvcp99z4jbmg+l962nsfeuD6XboduiF6rvvYPZF/h4GQQzbEX0W/Ro+HI0dPhzKGXsVhg+5CFUDnQBfAW8EuQjaDIYPhg96DSILggeJA07/fvre9PTuduhz4ineKd7C433rZPWK/+UHeg1FENsR2xEMEYYPIQ5BDBsKggcyBLsBDgFKAs4Frwu0EqQYjR3XIQYlZSNZIP0atBK5CGX9MPED5UfZsdESyxLLX82x0YHXp9+D6d/x4vmc/1UDOAXyBMcC8v6P+b/zu+8l7nrwR/dkAKAJtBLKGVkg1yHXIese/Rp9FtsR2gxxBiL/s/cw8Uztfetp7PTuMPFR9Ef3j/nI+uL5R/fe9CbzMPG77yXuaexp7PTuUfQO+7sBTQjQDoMU/RpZIAYluSa5JgYl1yE+HH0WDBGvCyoJoAlBDIYP2xGXE7QSDBF6DYIHIv9k9YXqKd6306nI673tus23670mxrHRm9xc5zDxMvp9ASMHnApBDK8LKgk4Bd4AQvw4+Y/5Of1VAxsKRRB7Ff0aWSC5JloqSSxJLFoqZSPKGXoNnQDe9Gnsduhc51znXOd26IXq9O5k9Qn8VQOgCdoMeg0iC84FRf5g9jDx9O4w8WT1yPpfAbkIRRCKF40dZSO5JrkmuSYGJVkgyhm0EkEMcQYkAqH+Ufuz9970hvJ68PTuaeyF6nboNubC4xXhp98p3inep98D5YXqevDl9cj6Cv/HAsgGIgvQDgwRlxODFJcTRRAiCx4GcgIOAQACbwTlB68LIQ6GD0UQ0A4iC4IFTv84+SbzaewD5aff+tpH2UfZKd7C44XqhvKP+bIAcQYbCiILnAoqCcgGMgS7ATIAUwDHAiMHQQzbEYoXPhxZIGUjBiW5JgYlZSPrHqQYDBFNCEX+3vRp7Dbmp9/62oHXptW307fTptVH2ZvcFeHC4zbmNuY25lznduiF6iXuJvMb+Az9fQEeBq8LDBF7FcoZ/Rr9GqQYexW0EgwRRRAMEZcTexV9Fn0WlxMMESEOIgtNCG8Erf+P+Ybyfes25nPiwuNc50ztUfTO+90BzgWCB7kIKgkqCbkITQiCB3EG8gT0At0BJAIyBIIHQQzbEaQYjR3XIQYlBiVlI+seiheGD4IFMvr07sLj+tq305TPlM+x0abVm9zC44XqMPHW9gn8OP8UAL3+kftH9ybzevD07nrw3vTO+zIE2gyDFMoZPhyNHY0djR0+HKQYexWGD5wK8gTy/o/55fXe9OX1G/h++s77Qvyr/Az9Of3d/JH7j/lH92D25fXl9db23fjd/LsBIwfaDNsRihf9GuseZSMGJWUjWSA+HIoXtBKGD3oNeg3QDgwRlxN7FXsVlxNFEK8LzgVF/lH0duib3LHRqciGw8jAyMAmxpTPR9nC42ns3vTO+7sBHga5CCoJIwcjA4r/Of1C/Kv8Rf72AK8EGwpFEH0WPhzXIbkmWipaKn8oWSCKF9oM9ALi+SbzTO2D6VznXOeD6WnsevBk9ZH7mwIqCUEMQQy5CIkDOf3W9obyu++779/x1vYj/s4F2gy0EooXPhzrHtch1yHrHj4cihe0EiEOoAnyBCgBg/53/DL6R/e/83rwJe5p7IXqXOfC46ffKd6b3Cnep9/C43boJe6/8934q/wK/0MB8gQbCiEODBHbEUUQQQy5CDgFxwK7AfQCcQavCwwRgxR7FYMUtBJFEHoNuQhyAg77JvN96wPlFeGn36ffwuOD6d/xj/l2AB4GIgvQDoYP0A7aDLkIMgSJAKH+2P7IADIEKgnQDnsV/RpZIGUjuSZ/KH8ouSbXIT4clxOcCrsB4vmG8mnsNuZz4qffm9z62vram9yn3xXhwuMD5QPlwuPC48LjA+Vc54XqJe4m84/5vv+CBZwKhg+0EnsVfRZ7FbQShg96DdoMeg3QDkUQtBKDFHsVexWDFLQSRRDaDE0ImwJR+4byherC46ffp9/C43bou++z99j+MgTlBxsKIgucChsKoAlNCM4F9AIUACP+AP7d/74DoAkMEaQYWSC5JloqWipaKrkm1yHKGUUQrwR++EztwuOb3IHXptWB15vcFeE25mns3/HW9n76Zf1F/t383fgm80ztduhc54Pp9O7l9WX+HgbaDLQSexWKF6QYyhnKGaQYexWGD00IfQGR+7P35fVg9hv44vlR+3f8q/x3/An8DvuP+Rv4YPa/8zDx9O707rvvJvMb+Dn9SgKCB9oMtBKKF/0a6x5ZIFkg6x79Gn0WtBLQDnoN0A7bEYMUfRakGMoZyhmkGIMUhg8jB938evDC44HXX80mxobDhsOpyF/NptWb3APlJe5k9Qn8UwByApsC9gDc/X76R/dk9WT1s/eR+yMAOAUiC9sRpBhZILkmWipaKn8o1yH9GgwRIwdl/kf3hvK770ztaexp7CXu3/HW9gz99AKCB5wKnArlB5sCkftR9LvvJe707t/xYPaR+/YAIwd6DZcTpBiNHVkg1yFZIOseyhmXE9AOIgu5CCMH8gTdAb3+zvs4+Uf33vTf8fTufetc58Ljp9+b3JvcKd5z4nboJe6G8mT13fjd/A4BggWgCdoM0A7QDiEOnAoeBkoC9gCbAh4GGwp6DQwRlxODFHsVgxTbESEOKgmJA2X95fUl7lznc+IV4cLjXOd96zDx1vYM/VUDuQhBDNoMQQycCk0I8gR9AXf/nP8kAnEGrwsMEXsVyhnrHmUjuSZ/KH8ouSZlI40dfRZ6DYIFZf5++CbzJe526MLjp9+b3JvcKd4p3qffp9+n3yneKd6b3JvcKd4V4Tbmheq77970MvpTAMgG2gwMEbQStBIMEYYPeg2vCyILrwt6DYYPDBHbEdsRDBFFEAwRDBHQDhsKiQOR+ybzfesD5RXhp99z4lznTO1R9I/5jv3eADIEyAa5CLkIggeCBccC7P85/cj64vlR+yL/8gSvC7QSpBjrHmUjuSa5JgYlWSCkGIYP8gTi+fTuNuYp3kfZR9lH2fraKd5z4nbo9O7e9OL53fw5/VH7s/cm87vvTO1p7PTuUfTI+rsB5Qd6DbQSihf9Go0d6x7rHv0afRYMERsKMgTY/sj63fh++N34OPni+cj6zvt3/N38zvuP+WD2JvO770ztaexp7EztevDe9Dj5AP6+A5wKDBGKFz4c6x5ZIOsePhykGIMU2xFFEEUQDBG0EoMUexWKF6QYyhnKGYoXtBIbCiL/hvID5UfZlM+pyIbDhsMmxhLLlM+B16ffduh68Nb2kfsj/oP+Of0O+934R/fl9eX1R/eP+Tn9cgIqCQwRyhlZILkmWipaKrkmWSCkGEUQuQjdAZH75fUw8SXuaexp7EztevDe9OL58v4jAzgFbwRDAd38G/hR9DDxu++77zDxZPV++hQAzgWvCwwRexXKGT4cjR0+HMoZfRaXEwwRIQ6cCuUHzgUyBEoC7P8M/eL51va/87vvheoD5affm9z62pvcKd5z4jbmher07r/zG/gJ/L7/vgOCBxsKIgugCSMHMgQAAg4BKAFKAm8EggevC4YPtBKDFIMUlxPbESEOuQgAAjL6hvJp7FznA+Vz4nPiwuN26CXu3vQO+94AzgUqCRsKoAmCB28EmwGc/07/MgAAAq8ETQjaDNsRiheNHdchuSZ/KH8ouSbXIT4cexWGDyILzgVkAH763vS772nsg+lc5wPlA+XC43Pic+Kn3ynem9yb3Cnep99z4jbmg+kl7t70CfybAk0IQQyGD0UQRRDQDtoMnAobCq8Leg3QDoYPhg8MEZcTexWKF4oXfRaXE9AOuQj2ALP39O5c58LjwuMD5YPpJe5R9DL67P9vBCMHuQi5CE0Iggc4BbsBDP3d+GD2ZPVH98j6BgDIBtAOihfrHmUjuSa5JgYl1yE+HJcTKgkj/r/zfesD5RXhKd4p3qffwuN26CXuhvLW9jL6d/xC/I/53vT07oXqduh26IXq9O5R9FH7cgIqCYYPgxSKF8oZPhw+HKQYlxN6DeUHxwKh/pH74vmP+Q77DP2c/7sBxwLHAgACZACO/eL5ZPUw8fTuTO1M7SXuu++/8934vf44Ba8LDBF9FsoZPhw+HP0aihe0EoYPeg3aDEEMeg2GD7QSfRb9GuseWSBZII0dpBgMEcgGyPol7nPiR9mx0V/NEstfzZTPptWb3APlfesw8WT1fvgy+jL6OPnW9t70hvLf8d/xJvNk9Tj5OP8jB4YPpBjrHmUjuSa5JmUj6x6kGNsRIgtvBPL+yPqz92T1UfRR9OX1G/jO+2P/xwI4BR4G8gRfAXf81vbf8SXuTO0l7nrwUfTd+Nz99ALlB0EMRRCXE30WiheKF3sVtBKGD9oMrwuvC68LIgucChsKKgkjB/IE3QEA/jj5v/Ml7nboc+Kn3yneKd4V4QPlg+lM7d/xZPWP+WX9DgH3A4IFzgXyBHICY//d/An83fx3/yMD5QdBDEUQlxN9FooXpBh9FpcT0A65CN0ByPq/8yXuhep26Hbofev07r/zOPnY/vcDTQicCpwKKgnIBvcDKAG9/mX9tv2t/8cCIwdBDNsRpBjrHmUjfyhaKloquSZlI+seyhmDFCEOKglvBEIAd/x++GT1hvJ68PTuJe5963boNubC46ffKd762kfZR9n62qffA+V969/xfvgK//IEoAmvC68LIgugCU0IIwceBs4FcQZNCK8L0A60En0WpBj9Gj4cjR0+HIoXRRDlB2X+ZPVM7VznA+UD5YPpJe5R9OL5I/7dAYIFuQgbChsKTQiCBX0Bq/yz97/z3/GG8mD2q/yvBNoMgxT9GlkgBiV/KH8oBiXrHooXIQ6+A4/5evCD6TbmwuMD5Tbmduh963rwZPWP+Qn8d/wO+7P3JvNM7XboNuYD5XboTO2/8zL6ZABxBtoMtBKKF/0a/Rr9GooXtBJ6DSMHfQE5/Q77yPpC/CP+QgByAm8EzgUeBjgFxwIi/8j65fXf8SXuheqD6YPpaex68GT1DvtDAU0I0A6DFIoXpBiKF3sV2xHQDq8LoAlNCLkInAohDtsRfRb9Guse1yFlI9chjR17Fa8Lvv+/83boKd6m1ZTPX82Uz7HRptX62hXhduj07lH0s/fd+H741vbe9IbyevD07vTuevAm8xv4g/4eBiEOfRaNHWUjuSa5JgYlWSDKGZcTeg3lB/QCY/93/DL6fviz9xv4fvoj/nICcQZNCOUHOAV2AA77ZPUw8fTu9O568Cbz1vbI+qH+9ALlB9oM2xF7FYoXfRaDFNsRhg/aDK8LIguvC9oM2gxBDK8LIgsbCrkIzgV9AZH73vRM7TbmFeGb3Pram9wp3nPiNuaF6vTuv/OP+Tj/9wMjB00Iggc4BSQCIv85/Xf8tv12AG8EuQjaDAwRgxSkGP0a/RrKGX0WDBGcCscCyPq/80ztg+lc5zbmXOeF6vTuv/M4+dz9mwFVAyMDQwGD/s77OPmz90f3G/iP+UL8FACCBUEMtBLKGeseZSMGJQYl1yGNHcoZexUMEdoMoAmCBV8BZf3i+bP3ZPW/89/xu+9p7HbowuOn3/ragde307fTt9Om1UfZKd4D5Wns3vRC/EoCcQa5CCoJTQhxBvcDSgK7AZsCbwTIBqAJQQyGD5cTihc+HOse6x6NHaQY2xHlB479v/N961znA+U25nboaeww8WD2zvuyAPIE5QegCaAJ5QcyBKH+G/iG8rvv9O568CbzG/hF/s4Feg17FY0d1yEGJbkmZSONHXsVrwsAAjj53/Fp7HboNuYD5Vzng+lM7d/x5fU4+cj6fvqz9ybzTO1c58Ljc+LC4zbmheq77+X1DP1vBCILDBF7FaQYyhmkGIMUhg+gCTIEFABl/Qn8zvur/L3+XwEyBMgG5QeCB84FIwMi/+L5v/P07oXqduhc51zng+lp7DDxG/hTAE0I0A6XE30WfRZ7FbQShg9BDKAJTQjlB00IGwpBDEUQfRY+HGUjuSZ/KLkmZSP9GgwRggWP+fTuA+Up3oHXt9O307fTgdeb3MLjg+kl7jDxv/NR9FH0JvN68CXuaeyF6oXqhepM7TDxR/ec/yoJ2xHKGese1yFlI1kgjR2kGJcT0A6cCnEGIwMUALb9q/w5/Tj/SgLOBbkInAqcCioJzgXIAA77YPYm8zDxMPHf8b/z1vZR+yMAOAWgCXoNRRC0ErQS2xFFECEO2gxBDEEM2gx6DdAORRDbEZcTgxSXE9sR0A4bCr4DQvxR9EztXOfC4xXhFeFz4sLjXOd96zDx1vYJ/FMAiQOCBc4F9wNDASP+UfuP+d34j/mR+/L+iQO5CNAOgxSKF8oZyhmkGH0W2xGvC28EDP3W9jDxTO1964Xqaex68OX1Ufvd/5sCvgOJA8cCKAHY/kL8j/mz92D25fVH9+L5g/6vBEEMlxPKGese1yFlI9chWSCNHf0aiheXE4YPQQwqCR4G9wPHAgACQwHO/479Mvrl9Xrwfes25hXh+tqB17fTt9Om1UfZKd425iXuYPaO/ccCHgYjBx4GMgTdAc7/Zf62/dz9Cv9DAW8EKgnQDoMU/RpZIGUjBiVlI40dfRbaDCMDMvqG8mnsg+mD6X3rJe6G8rP3DP1KAiMHGwqvC5wKggebAqv8YPYw8WnsheqF6kzt3/Hd+CgBGwq0Ev0aWSAGJQYlZSONHX0W0A7OBY795fW7733rg+mD6YXqTO168N70fvh++jL6G/hR9PTug+kD5RXhp9+n3xXhA+WF6jDxs/e9/oIFrwtFEJcTgxSXE0UQ2gzlB5sCZf6R+8j6Ufu2/bIAvgPIBioJnAqcCrkIggUoAUL81vYw8X3rXOfC48LjNuaF6jDxfvgyACMHeg3bEYMUgxSXEwwReg2cCiMHrwTHAscCOAWgCYYPfRaNHWUjfyhaKloquSZZIIoX2gwkAkf3aexz4pvcR9mB10fZm9yn3wPlduhp7Lvv3/GG8t/xevD07mnsg+k25gPlNuZ26CXuZPXc/XEG0A59Fv0a6x7rHo0d/RqKF4MURRCvC4IHMgS7AUIAiv++//YA9AKCBeUHTQiCB68EsgBC/Bv4UfQw8bvvu+8w8SbzYPbi+dz9JAJxBqAJQQzaDNoMQQwiC5wKGwobCpwKrwshDkUQtBKDFHsVfRaKF3sV2xHaDM4Fg/5H9zDxfetc5wPlwuPC4zbmg+lM7TDxYPaR+wYAVQOvBDIEAAJO/6v8fvrd+N34fvrc/XIC5QfaDNsRexWkGP0aPhz9GooXtBLaDB4Giv84+VH0evD07rvv3/He9H74Ufu2/Xf/iQCyAL7/3P1R+934YPZR9L/zv/Nk9Tj5of5vBBsKhg+DFKQY/RqNHY0dPhzKGYoXgxTbEYYP2gyvC5wKnAqcCqAJ5Qc4Bd0B3P3d+CbzTO025qffR9mm1bHRsdG300fZp9825vTuZPVR+2P/fQHdAd4AOP9l/c77yPrI+pH7jv2yAPIEnAoMEYoXjR1lI7kmuSYGJeseiheGDx4G3P3W9t/xu+/07nrwJvPW9gn8XwFxBpwK2gx6Da8LTQgjAzn9R/ff8SXufetp7PTuJvMy+koCnAq0Ev0aWSBlIwYl1yGNHYoXRRC5CAACCfxH97/z3/Ew8Yby3vQb+FH7Zf3c/Xf8j/ne9Lvvheo25sLjc+Jz4gPlduhp7N/xG/ih/vIEnArQDgwR2xFFENoMTQj3A2QA3P13/EL8Of1O/0oCggW5CJwKrwsiC6AJyAbHAo79R/cw8X3rdug25gPlNuaD6fTu3vTO+yQCIwecCkEM2gwiC00IbwSyANz9QvzO+938OP9VAyoJRRCKF+seZSO5JrkmZSPrHooX0A4yBOL5MPGD6QPlFeGn36ffFeHC41zng+lp7PTuu+968LvvJe5964PpNuYD5cLjA+Vc533rhvJ++scCGwpFEIMUihekGKQYfRaXEwwRIQ6vC6AJ5QfOBa8EbwSCBYIHKgmcCiILGwpNCK8EUwDO+7P33vSG8t/xMPHf8Sbz5fU4+Qz9BgBKAvcDrwSvBL4DJAKyADIADgH0AjgFggegCUEMhg+0EnsViheKF3sV2xGvC4IFg/6z9zDxaex26DbmA+UD5Tbmg+lM7d/xYPbi+UL8Of3d/FH73fjl9YbyMPEw8YbyZPXd+GX9xwK5CNAOlxOKF6QYpBh9FrQS0A6gCfcDI/44+eX13vTe9OX1G/hR+73+mwFVA1UDSgKyAL3+QvyP+db2UfQm8ybzUfTW9jL68v6vBCILDBF7FaQYyhnKGcoZihd7FZcT2xFFEEUQRRAMEdsR2xHbEbQS2xFFENoMTQibAs77UfRp7MLjKd5H2abVptWB1/raFeF26Lvv1vYJ/Dj/MgA4/zn9fvob+OX13vTe9GD2j/ll/UoCTQiGD4oX6x4GJX8oWiq5Jtch/RrbEaAJmwGR+7P3ZPXe9OX1G/jO+8gAHgYiCyEOhg/QDtoMuQiJA2X91vYw8Uztfet96yXu3/Eb+EIAKgnbEcoZ6x7XIdchWSA+HIoX2xGvC4IFZAB3/OL5fvg4+VH7Zf59Ab4DbwRVA3YAd/xH99/xaex26APlwuPC4wPlduhp7Ibyfvgi//IEoAnaDCEOIQ7aDJwKIweJAyMAZf0J/Kv8of6bATgFTQivC3oNIQ56DSILTQj3A9j+OPkm8yXug+lc5zbmduh96zDxG/ih/m8EuQgiC68LnAq5CHEGiQOdAAD+QvyR+3f8iv+vBCIL2xGkGOseZSO5JrkmZSPrHqQYRRDlBzj/R/d68H3rXOc25jbmNuZ26IPphep962nsaexp7H3rg+l26DbmwuNz4nPiwuNc52nsv/PI+gACuQghDtsRlxOXE5cTtBLbEUUQ0A56Da8LnAqgCSoJoAmcCq8L2gx6DUEMGwpxBkoCtv2P+eX1JvMw8XrwMPEm82T1s/cy+t38Iv92AMgAMgDy/o79d/wJ/EL8Of29/igBbwS5CNoMDBGDFIoXpBiKF4MURRAbCr4DOf3W9jDxaex26APlwuMD5Vznheol7obyZPUb+Dj5OPl++GD2UfTf8Xrw9O707rvvhvLW9jn9MgQiC0UQgxR9FooXihd7FbQS0A4bCq8EnP8O+0f35fVg9n74CfxO/90BIwNVA0oCdgAA/lH7fvhg9r/z3/F68HrwMPFR9N348v44BSILhg+XE3sVfRZ9FnsVlxO0EgwRhg/QDiEO0A5FENsRlxODFHsVgxS0EtAOGwq+A3f8UfR968Ljm9yB17fTsdG300fZKd425kztJvNH9+L5DvvI+n745fW/89/x3/Hf8Yby3vR++EX+ggV6DX0WjR1lI7kmfyi5Jtch/RqXE68L8gQK/zL61vZk9WD23fir/MgArwRNCK8L2gxBDBsKzgWJAMj6ZPV68Gnsg+l26IXqu+9g9rb9ggXaDJcTpBg+HI0dPhzKGX0WDBFBDMgGAAJl/nf8d/wj/lMASgK+A68ErwSJA/YAOf3d+L/z9O6F6lznA+UD5Tbmher07t70yPrs/28E5QciC3oNIQ7aDCIL5QfyBCQCdgAyAH0BbwRNCEEM0A4MEdsR2xEMEdAOQQy5CPcDZf4b+IbyTO2F6oXqaeww8WD2kftCAL4DHgaCB00IuQjlBx4GvgMoAb3+DP2r/CP+mwHIBnoNlxP9GlkgBiW5JrkmBiXXIT4cexUhDh4GY/+P+d703/F68PTuJe4l7kztaex9633rheqF6nboXOcD5XPiFeGn36ffc+I25n3rMPGz92X9cgJxBioJrwvaDCEOIQ7QDtAO0A7QDtAO0A6GD4YPDBHbEdsR2xEMEYYP2gygCYIF9gDd/I/5R/dg9mD2s/fi+UL82P4OAUoCmwJKAn0BMgCh/qv8yPqP+d344vlC/GQAzgUiCwwRexXKGT4cPhz9GooXlxMhDk0I3QEO+970u+9p7H3rfetM7bvvhvLe9Ef3OPmP+Y/53fiz9+X1JvP07n3rg+mF6mnsevBg9nf8cgLlB9oMRRC0EpcTlxO0EkUQQQzIBrIADvvW9t70ZPVH9+L5DP3O/7sBmwJyAkMBiv+O/cj6s/e/87vvaeyF6oXqTO0w8db2q/ybAuUHQQyGDwwR2xHbEQwRhg8hDkEMnAobCiILeg1FELQSexWKF6QYyhmKF4MURRCgCXIC4vl68Fznp99H2abVptWm1frap98D5X3revC/8+X15fVR9Ibyu+9p7IPpXOc25lznheq77+X1Of2CBSEOfRY+HFkg1yFZID4cfRZFEE0IXwEJ/H741vbW9hv4MvqO/X0BggW5CCILrwsiCyoJggV2AH76UfT07n3rg+mD6Wnsu+9R9DL6nQAjB3oNtBJ9FqQYpBh9FrQSeg25CDIEKAGc/wr/Y/9TAH0BxwL3A68EbwQjA4kA3fwb+IbyTO126APlwuMD5Xbofeu777/zs/cJ/FMA9wNxBuUHTQiCBzgFcgLd/4P+vf6JAIkDyAYbCtoMIQ6GD0UQhg/QDnoNIguCB8cCDP1H99/x9O5M7SXuu+8m89b2fvq2/XYAcgK+A28EMgQjAw4Bg/4J/H764vnI+o79fQHIBkEMtBKkGI0d1yFlI2Uj1yHrHv0agxTQDrkIvgMjAGX9UfuP+bP3YPbe9CbzMPH07kztfeuD6XboNubC43Pic+Jz4sLjNuaD6SXuhvJH91H78v59AVUDbwSCBcgGgge5CBsKrwt6DYYPDBHbEbQSlxODFIMUlxO0EkUQQQxNCL4DOP9R+934s/ez9zj5zvtl/rIAcgKJAzIEMgRVA30Bg/4O+7P3ZPW/81H0YPYy+q3/HgbaDLQSihf9Gj4cjR0+HKQYgxTQDk0IuwGR+2D23/G77/TuevCG8t70R/fd+DL6DvtR+w77j/nW9oby9O5963boXOd26H3rMPHW9jn9VQO5CNoMRRCXE4MUgxSXE4YPnAo4BUIAQvzi+eL5kftF/l8BMgRxBoIH5QfIBvIEJAKh/jL6ZPUw8UztfeuF6n3r9O4m8xv4tv30AoIHnAraDHoNeg1BDBsKTQjIBnEGyAZNCJwKeg0MEXsVpBj9Go0d6x6NHf0aexXQDsgGtv1R9H3rA+Up3vraR9n62inewuOD6fTuJvPl9Uf3R/dk9Yby9O5964PpXOdc51znher07mT1Of3OBSEOfRY+HFkg1yFZID4cihcMEZwKOAWJADn9Dvt++pH73P0OATIEIwcqCSILrwucCuUHvgO9/o/5UfS772nsheqD6YXqJe7f8db2q/xKAuUH2gwMEbQSlxPbEYYPQQwqCcgGrwSJA1UDMgSCBcgG5QdNCE0I5QceBlUDCv/i+VH0u+9p7IXqg+mD6X3rTO168L/zR/d++rb9dgByAlUDVQNyAsgAd/8i//r/3QFvBIIHnAp6DYYPRRAMEQwRDBFFECEOrwu5CK8EZAB3/Dj51vZk9eX1R/fi+UL8g/4jAEMB3QHdAX0BiQAi/479CfzI+uL54vnI+t38nQDOBa8LDBF9FsoZjR3rHusejR39GooXgxRFENoMoAnIBq8ExwJfAa3/Zf0y+mD2hvL07mnsg+k25sLjc+IV4affp98V4XPiA+V26GnsevC/8+X1R/d++I/5fvqR+9382P5fATIEIwegCUEMhg/bEYMUexV9FnsVlxMMEXoNoAnyBPr/kft++Nb21vZH9934Ufsj/vYA9AL3A74DSgJ3/5H7R/eG8vTufeuF6oXqJe6G8t34BgAjByEOlxOKF8oZyhmKF3sVDBFBDCMHXwFC/Bv45fXe9N70YPZ++Mj6q/zc/YP+Rf45/VH73fhk9d/xTO2D6VznXOd26GnsMPHW9kL83QHIBiIL0A4MEbQStBIMEdoMTQiJAzj/QvxR+0L8of4AAs4FKgmvC9oMQQwiCyoJHgZyAtz93fhR9LvvTO1p7CXuevDe9I/5vf6JAyMHoAmcCpwKoAm5CIIHzgWvBG8E8gRxBioJ2gwMEXsVyhmNHVkgWSBZII0dpBiXE3oNOAWr/L/zaew25nPic+Jz4jbmg+kl7obyZPXW9tb25fVR9Ibyu+9p7IPpXOc25jbmg+kl7lH0zvv3A68LtBKKF/0aPhz9GqQYexUMEdoMTQivBHICmwHdASMD8gQjB6AJrwvaDHoN2gyvC7kIOAUoAav8G/hR9DDxu++773rw3/G/82D24vkj/nICcQagCa8L2gzaDEEMnAq5COUHggflB00IuQi5CCoJKgm5CE0IyAYyBN4A3fx++L/zevBM7X3rfetp7CXu9O568N/xv/Pl9Rv4j/l++sj6MvqP+X74G/jd+FH7of5yAh4GuQicCkEM2gzaDNoMQQwiC6AJggfyBLsBg/7O++L5OPmP+X76kfvd/Nz92P53/63/Y/+h/o79d/wO+zj5s/fl9eX11vY4+UL8ZADyBKAJ0A60En0WpBjKGcoZpBh9FoMU2xHQDtoMQQyvC0EMrwucCk0IrwQOAQz9fvi/8/Tuhepc5wPlwuMV4RXhc+LC41znheol7jDxv/Pl9Uf3s/dH92D2YPbW9hv44vmr/M7/iQOCB68LRRC0EnsVfRaKF4oXexW0EtAOGwo4BcgADP1++jj5OPl++gz9IwAjA4IFIwflByMHOAUkArb9fviG8kztg+lc53boheq779b2Rf6CBa8LRRCDFH0Wihd9FpcT0A4bCjIEof6P+eX1v/Mm81H05fUb+H76Cfxl/SP+Rf5l/Q77s/cm8/Tuhepc5zbmNuZ26GnsMPFg9g773f+vBCoJeg1FEAwRRRAhDiILcQYkAtj+3fyr/GX+XwHyBE0IIgt6DSEOIQ7aDJwKIwfHAgD+OPne9DDx9O4l7rvvJvPW9g77Tv8jAx4G5Qe5CLkIggeCBb4DSgK7ASQCVQOCBbkI2gzbEX0W/RqNHeseWSBZIOse/Rp9FoYPTQhkAN343/Fp7IPpXOd26IXqaez07jDxJvNR9N70v/Pf8bvvaeyD6VznNuYD5Tbmduhp7N/xfvh3/x4GQQzbEXsVfRZ9FnsVtBJFENoMnAq5COUHggeCB+UHKgmcCkEMeg0hDtAOIQ56DSIL5QdvBN4Atv0O+zj5s/dg9mT1ZPXl9Uf34vkM/cgAbwQjB7kIoAkbCqAJoAkbCpwKIgsiC68LrwuvC68LIgsbCk0IyAb3A0IAQvwb+N70hvIw8XrwevB68DDxhvIm81H0ZPXW9rP3G/gb+Nb25fXe9GT1YPbd+EL8+v++AyMHGwpBDNoMeg3aDEEMIgsbCk0IzgVVA/YAOP8j/o79jv0j/iL/ZABDAX0BKAEyACL/tv0J/H76fvjW9mT1UfRR9N70YPYb+FH7Iv+JA+UHrwvQDgwRtBKXE5cTtBIMEYYP0A7QDtAOhg9FEAwRDBFFENAOrwuCB5sCtv1++L/z9O6F6lznA+XC4wPlNuZc54XqTO168Cbz3vRk9WT13vS/8ybzhvLf8Yby3vSz9877nQCCBRsK0A60En0WpBjKGcoZpBh7FQwR2gxNCPcDdgAj/o79Rf7s/yQCrwSCB6AJIguvC5wK5Qe+A4P+G/jf8X3rXOcD5TbmduhM7b/z4vmJAMgGQQwMEZcTgxSDFLQS0A4bCq8Erf/O+4/53fh++Dj5fvpC/AD+zv9DASQCAAKyACP+4vne9Lvvhep26FznXOd26IXqTO0w8d70j/kA/iQCggVNCKAJKgkjBzIEiQBl/ZH7DvvO+479UwCJAyMHnAraDCEO0A4hDkEMoAmCBfYAd/wb+N70JvOG8ibz3vSz9w77vf67AfcDrwRvBL4DcgL2AGP/3P3d/Az9g/4OAW8E5QdBDEUQgxSkGP0ajR2NHT4cyhl7FUUQoAn0Anf8YPbf8fTuTO1M7Uzt9O568IbyJvO/8ybzhvIw8fTuaeyF6nboNuY25lznduh967vv3vTI+okAzgUbCnoNhg9FEIYP0A7aDK8LGwoqCU0ITQhNCLkIKgkbCiILrwtBDEEMIgugCSMH8gRyAnYAof4M/ZH7j/mz9+X1UfS/81H05fUb+H76q/yh/mQAAAKJAzgFyAa5CJwKQQx6DXoNIQ56DdoMQQycCrkIcQZVAzIADP0y+hv41vZg9mD2YPZg9mD2YPbW9kf3s/cb+LP31vbl9VH0v/Mm81H05fV++EL8nQCvBOUHnApBDNoM2gxBDK8LGwpNCMgG8gSJA0oCQwEOAX0BmwL3AzgFHgZxBh4G8gRVAygB2P6r/Mj6j/l++LP31vbW9rP3j/lC/E7/cgKCBbkIIgt6DYYPRRBFEIYPhg/QDiEOIQ4hDtAORRDbEbQStBLbEdAOrwsjByQCq/zW9t/xTO126DbmwuPC48LjNuZ26H3r9O7f8b/zUfRR9L/z3/G77yXuTO1p7CXuevC/8374Zf1yAoIHQQwMEYMUfRaKF30WexXbESEOGwrOBUoC7P+9/r3+zv+bAfcDyAYqCa8Leg0hDnoNIgsjB30BUfve9LvvfeuD6YPpaex68OX1zvvdAYIHQQxFEJcTgxSXE9sRIQ4bCs4FuwGD/kL8DvsO+877Of29/nYAJAKJA28EvgObAWX+Mvrl9d/x9O5M7WnsaexM7bvvhvJk9X74zvut/4kDyAa5CKAJKgnlB84FVQP2ADj/Zf7Y/nYAxwI4BYIHoAkiC0EMQQyvCxsKIwf3A2QA3fyP+WD2UfS/89701vaP+Qn8Rf4UAF8BJAIAAigB3f+h/rb9Zf22/aH+MgCbAs4FoAl6DQwRgxSKF8oZ/Rr9GsoZpBiDFAwRQQwjB5sCI/4y+kf3ZPW/8ybzJvMm8ybzJvOG8t/xevC77yXuaex964Ppduh26Hbog+l96yXuhvLW9pH7rf/0AoIFgge5CCoJoAkbCpwKIguvC68LQQxBDEEMQQzaDNoMeg3aDK8LGwq5CCMHzgU4BfIErwRvBIkDAALd/2X9Dvs4+bP3R/dH9xv43fiP+Q773fxj/0oCOAVNCJwK2gwhDiEOIQ56DUEMnApNCDgFAAK9/s774vnd+H74fvjd+N343fjd+N34fvh++Bv4R/dg9mT1v/Mw8bvv9O707nrwJvPW9lH7+v8yBOUHGwqvC68LnAoqCYIHzgW+A90BIwDy/mX+of6c/ygB9AKvBHEGggeCB3EGMgSbAQr/d/wy+hv4YPbe9FH0UfTe9GD2fvhR+wD+nQAjA4IFIwdNCKAJGwobChsKoAmgCRsKIgt6DYYP2xGDFH0WfRZ9FoMU2xEhDioJvgO2/bP33/FM7YXqduhc53bog+lp7PTu3/G/82T1YPbl9VH0MPH07mnsfeuF6mnsJe7f8WD2UfuJAB4GIgtFEJcTfRaKF4oXexXbESEOnAojB68E9AIkAiQC9AJvBMgGKglBDNAODBHbEQwRIQ4bCq8EZf4b+IbyJe5p7H3rTO168FH0j/k4/68EoAl6DUUQDBEMEYYP2gwqCc4FxwKJAAr/AP62/QD+2P5CAAACiQNvBPcDcgIUAAz9j/nl9d/xu+8l7kztTO0l7vTuevCG8t70G/gO+wD+dgByAvcD8gSvBL4DJAKyAN3/rf8GAN4AcgIyBM4FggcqCaAJKgm5COUHcQZvBH0BRf5R+934R/dg9tb2s/fd+H76kft3/Kv8CfxR+376j/nd+H74fvjd+DL6QvwK/0oCzgWgCdoMRRC0EnsVfRZ9Fn0WfRaDFNsR0A6vC00IOAUAAjj/q/x++n741vZk9b/zhvLf8TDxu+/07iXuTO1M7WnsfeuF6oXqhepp7CXuevC/89b24vmr/Dj/fQFVA/IEyAa5CBsKrwvaDHoNIQ4hDiEOIQ4hDnoNQQycCioJggceBoIFggUeBsgGggflB4IHHgb3A18Bof7O+zj5R/fl9d703vTl9bP34vkM/bIAbwRNCK8LIQ6GD0UQhg/QDnoNIgvlB68EmwHY/qv8Dvt++jL6yPqR+6v8Of1l/Tn9q/wJ/A77j/mz92T1JvN68PTuJe4l7vTuMPFk9eL5vf4jA8gGKgkbChsKuQgjB/IEmwKyAAr/3P0M/d38jv0i/30B9wNxBuUHTQiCBx4GiQOdALb9Dvt++OX1UfQm89/x3/GG8r/z5fV++Mj6DP3Y/kIAXwEkAscCxwKbAnICcgL0AvcDggXlByILIQ5FELQSlxOXE7QSRRB6DbkIiQPc/Rv4hvIl7n3rg+mD6YPpfesl7nrwhvJR9GT1ZPW/89/x9O5964PpXOdc51zng+lp7Hrw3vSP+YP+VQPlByILIQ6GD4YPIQ6vC6AJIwfyBFUDJAK7Ad0BcgK+A4IF5QcbCtoM0A6GD4YPeg2gCfIEvv9++mT13/G77/Tu9O4w8VH0G/hC/HYAbwTlB5wKQQxBDCILoAnlB4IFiQObAQYACv+9/vL+Y/8GAMgAfQEAAgACQwGt/2X9yPob+OX1UfQm84byhvKG8ibzJvO/8970YPYb+A773P12AEoCIwNVAyMDcgLdAV8BQwHdAccCvgNvBPIEOAUeBsgGggflB4IHyAY4BVUDfQGt/0X+Zf0M/WX9AP6h/vL+Cv/y/r3+g/4A/mX93fx3/Hf8DP1l/iMAJAKvBCMHoAmvCyEOhg8MEbQSlxODFIMUgxSXE7QS2xFFECEOQQwqCXEGiQOdAI79yPob+OX1UfSG8jDxevB68HrwevAw8TDxevB68HrwMPHf8YbyUfTl9bP3OPnI+nf8I/4jAJsCggVNCCIL2gzQDkUQDBEMEQwRRRCGDyEO2gwiCyoJIwfOBc4FyAa5CJwKQQzaDHoNQQwbCiMHvgP6/0L8OPnW9t70v/O/8970s/cO+07/iQOCByILIQ6GDwwRRRCGD3oNnAojB/cDsgAA/gn8UftR+0L8Zf29/vr/yAAOAfYAZABj/7b9kfs4+WD2v/Mw8fTuTO1M7fTu3/Fg9sj6d/++AyMHKgmgCSoJggfOBb4DfQFj/2X9CfyR+wn8jv0GAPQCzgVNCKAJGwqgCeUHzgUjA4kA3P1R+9341vbl9WT1ZPXW9hv44vkJ/GX+QgAAAiMD9wMyBDIEiQP0ApsC9AL3AzgFggcbCnoNRRC0EnsViheKF4oXfRa0EtAOoAkyBL3+4vnl9SbzMPG777vvevCG8lH0YPaz9374s/fl9SbzevBM7YXqg+mD6YPpfesl7nrwUfQb+Kv8QwGCBbkIIgvaDNoMrwucCrkIyAaCBa8EbwQyBG8ErwSCBcgGuQicCtoM0A5FEIYPIQ4iC4IHIwOh/n76R/dk9b/zv/NR9GT1s/fI+tz9DgG+Ax4Ggge5CLkITQiCBx4GOAUyBCMDJAKbASgBDgEOAUMBfQGbAQ4B7P+D/gz9Ufvi+Rv4R/fW9mD2YPbl9WT13vRR9FH03vTl9Uf3OPlR+zn9vf6t/1MA3gBfAQACmwIjA1UDiQNVAyMDVQO+AzIErwTyBDgF8gSvBL4D9AIkArsBXwH2AHYABgBj/6H+tv13/A774vl++LP3R/ez9374MvrO+7b9vv+bAb4DggUjB7kIGwqvC0EM2gx6DSEO0A6GD0UQDBEMEUUQ0A56DSILTQiCBUoC8v6R+xv43vSG8jDxevB68DDx3/Hf8Yby3/Hf8TDxMPF68DDxMPEw8d/x3/GG8r/zZPV++An8zv+JAyMHGwpBDCEO0A6GD4YP0A56DUEMoAmCB4IFbwQyBPIEyAYqCa8LIQ6GD0UQhg/aDBsKyAZVA2P/Ufuz9970v/O/89701vYy+kX+cgLIBhsKeg3QDkUQRRDQDtoMGwrIBokDnQCD/jn9q/wM/dz9Iv+dAAACxwLHAgAC3gCK/9z9kfvd+GD2JvMw8fTuJe707nrwJvNH95H7+v+JA3EG5Qe5CLkI5QfIBoIFvgPdAVMAd/9O//r/mwH3A8gGKgmcCiILIgucCioJIwdvBLsBOP/d/A77j/l++Bv4G/h++Dj5fvqR+wz9Rf44/93/BgC+/3f/Tv93/wYAKAHHAvIEggcbCkEM0A4MEZcTgxR7FXsVlxMMESEOGwoeBiQCg/4O+xv4ZPW/8ybzJvO/89705fXW9tb25fW/89/xu+9M7Wnsfet962nsTO307jDxv/PW9jL6AP6bAa8EyAblB00I5QcjB8gGyAbIBnEGHgbOBYIFOAU4Bc4FcQblByoJnAqvC68LnAq5CMgGMgSbAfL+d/wy+n74R/fW9tb2s/c4+Q77Of2c/90BvgM4BXEGIweCByMHyAbOBa8EVQMkAvYA+v8K/0X+3P2O/Qz9d/xR+zL6j/l++Bv4s/ez90f31vZg9t70v/OG8t/x3/GG8r/zZPUb+H76DP0i/ygB9AJvBIIFHgYeBs4F8gS+A3ICmwFDAV8BmwEAApsCIwOJA4kDiQNVAyMDmwLdAfYArf9F/qv8Dvs4+Uf35fVk9d70ZPXW9hv44vnO+7b9d/8OAZsC9wOCBXEGggdNCLkIKgmgCZwKrwt6DdAORRBFEEUQhg8hDkEMoAlxBnICI/6P+WT13/G77/TuJe707rvvevAw8TDxMPEw8TDxMPF68Hrwu+/07iXuJe707nrwhvLl9Tj5DP3IAPcDcQa5CJwKQQzaDNoMQQycCioJggeCBfcDxwKbAlUDOAWCBxsKQQwhDtAO0A56DSIL5QcyBEIAq/yP+db23vRR9FH05fXd+Hf8dgBvBOUHnAraDCEOeg1BDBsK5Qc4BccCiQCh/o79Of3c/b3+zv/IAH0B3QHdAX0BiQBO/7b9zvuP+Uf33vSG8jDxevB68N/xUfRH9376tv2dAPQCrwSCBc4FzgU4BTIE9AJDAd3/OP93/zIAfQFVA4IFIwe5CCoJKglNCMgG8gT0At4A8v45/c77yPri+Y/5j/ni+cj6kfur/I79g/5O/77/+v8UADIAdgD2AAACiQOCBYIHKgkiC9oM0A5FENsRlxOXE5cTtBIMEdAOQQwqCR4GmwJO/wn8j/lH9+X1ZPVk9eX15fXl9WT1v/OG8jDxu+8l7kztTO1p7EztTO307nrwhvLe9Bv4Dvvc/RQA3QFVA68EzgVxBsgGIweCB+UHTQhNCOUHggcjB8gGyAYjB+UHuQgqCaAJKglNCMgGOAVVA18BTv9l/ZH74vkb+Ef3YPbW9rP33fjI+t38Iv8oAfQCbwTOBcgGggeCB4IHyAbOBW8EVQNyArsB3gAjAE7/Rf45/Xf8CfzO+877CfwJ/An8kft++t341vZk9b/zhvKG8ibzUfTl9bP3j/nO+0X+3gAjA68EggWCBfIEMgTHAn0BiQAjABQAMgB2APYAfQFKAvQCiQP3A/cD9wNVA5sCfQEGAEX+d/x++t34R/dg9uX15fXW9hv44vmR+2X92P5CAJsBIwNvBIIFcQYjB4IHTQi5CBsKIgvaDNAORRDbEbQStBLbEUUQIQ6cCnEG3QE5/d343vSG8nrwu++777vvevAw8TDx3/Ew8TDxevC77/TuTO1p7Gnsfetp7CXuevAm89b2MvoA/rsB8gTlB6AJIguvC68LrwsiC6AJ5QfOBTIE9AKbAlUD8gQjB6AJrwt6DSEOIQ7aDJwK5QfyBH0B3P0y+kf33vS/81H0ZPWz98j6g/5KAoIFTQigCSILrwsiCxsK5QfOBYkD3QGyAFMAnQBDAd0BcgL0AiMDIwPHAiQCKAEUAL3+Of0O+9341vbe9CbzhvKG8r/z5fWz9+L5QvyD/vYA9AJvBIIFzgWCBfIE9wMjA3ICSgLHAokDrwQeBoIHuQigCRsKGwqgCU0IyAbyBFUDuwGJAJz/8v6D/kX+I/4A/tz93P3c/UX+of7Y/r3+Zf4A/iP+vf7d/5sBvgPOBeUHGwqvC3oNhg9FENsR2xG0ErQStBLbEUUQIQ6vC6AJyAa+A7IAAP6R++L5G/hH92D2ZPXe9L/zhvIw8bvv9O4l7kztTO1M7SXu9O677zDxJvPe9Nb23fgO+wz98v52ALsB9AIyBM4FIwe5CKAJnAqcCqAJuQjlB8gGcQZxBsgGIweCB+UH5QeCByMHcQaCBfcDAALs/479Dvvd+Nb2ZPXe9N705fWz94/5zvtF/t4AVQM4BcgGggflByMHzgWvBFUDSgIoAQYAvf5l/UL8Uft++jL6fvrI+g77kfvO+5H7fvrd+Nb23vQm89/xevB68LvvevDf8VH0R/cy+o79nQAjA/IEzgXOBTgFbwSJA5sCmwHeAGQAUwCyAH0BmwK+A/IEzgUeBnEGzgXyBL4DcgL2AE7/Zf0O+374YPbe9N705fXW9n74MvqR+6v83P0i/50AJAJVAzIE8gQ4Bc4FcQYjB00IGwpBDCEORRDbEZcTgxSDFJcTDBEhDpwKcQZKAiP+fvqz92D23vRR9FH0UfRR9FH0UfRR9FH0JvPf8Xrw9O4l7kztTO0l7rvvMPG/89b2Mvpl/YkAVQPOBYIHKgkbCpwKnAobCioJggdxBjgFrwTyBM4FIwe5CJwKQQx6DSEOIQ7aDCILuQiCBUoCvf5R+374YPZk9WT1YPYb+DL6q/w4/wACbwTIBk0IuQhNCMgGOAW+A/QCmwKbAvQCVQOJA4kDVQP0AiQCmwFDAZ0Azv/Y/o79Cfwy+n74R/fW9tb2R/c4+X76Mvri+eL5OPk4+TL6CfyR+9345fWG8nrw3/FH90L8xwIbCoYPtBKXE7QSRRAhDtoMrwu5CPIEuwEj/pH7kfsi/74DIwegCSoJcQabArb9j/l++I/5UfvO+5H7kft++uL5MvoJ/E7/uwGbAmQAzvsb+Nb2G/h3/HICGwrbEYoXyhnKGYoXlxMhDqAJzgWbApz/Qvx++OX1UfTe9N34Zf4yBCMHyAavBBQA4vm/87vvaex962nsaexp7GnsheqD6WnsMPGz9zj/cQavCyEOIQ6vC00IHgY4BYIFcQYeBjIEQwG2/Qn83fx3/84Fhg/KGVkg1yFZIP0alxMbCn0B4vlR9Lvvaex26DbmXOd964byCfzlB7QS/RpZINchPhyXE00IRf5H94byMPHf8Ybyv/Pe9GD2fvoAAkEMexX9Gj4c/RqDFJwKRf4m833rA+Vz4hXhp98p3pvcm9yn31znhvIK/xsK2xF9FnsVDBG5CCgBDvtH9+X13vSG8rvvTO1M7bvv1vZKAtAOyhnXIbkmBiXrHoMUTQgM/WT1evBp7HboA+UV4RXhwuNp7Dj55Qd7FeseZSMGJVkgihfaDPQCkftg9obyu+9M7Wnsfev07kf3vgO0ElkgSSyhMu40oTJaKuseDBGvBDj59O425qffR9mB14HXm9w25ibzdgDaDHsVpBh9FoYPOAXd+EztwuOb3IHXt9Ox0bHRt9Ob3IXqfvqcCsoZBiVaKkksfyjrHpcTyAZR+3rwduhz4pvc+tqb3HPiu+8yANsR1yFJLKEyoTJPLgYlpBgiC479MPFc56ffR9m307HRgden30ztZf6GD+sefyhPLk8ufyhZIIMUKgll/t70aew25qffKd6n33boUfRVA5cTWSBaKk8uTy5/KOsetBKCBX74aexz4kfZlM8SyxLLsdGb3EztIwAMEY0dBiW5Jtch/RqGD/QC1vZp7MLj+tqm1bHRsdFH2TbmR/cbCv0afyhPLmwwSSxlI6QY2gxTAGT1aezC45vcgdeB15vcXOfl9XEGfRbXIX8oWip/KFkgfRacCqH+ZPUl7nbowuOn3xXhNuZ68Dj/hg/rHkksoTJXN+40Ty4GJcoZ2gwAAhv49O425qffm9yn3zbmMPFF/iILexU+HI0dyhmXE5wKY/+/84Ppp99H2bHRX81fzZTPR9lc59b2Iwd7FeseBiW5JgYl6x57FSIL9gCz9/TuXOcV4Snep99c54byyAAMEVkgWipsMKEybDB/KI0dRRDHAmD2heqn34HXsdGUz7fTKd5p7GX90A6NHbkmWipaKrkmjR20EoIHq/zf8XboFeH62kfZKd425oby3gCGDz4cZSN/KH8oZSP9GkUQrwTd+Eztc+JH2bHRlM+x0UfZA+W/874DDBH9GtchBiVlI+seihfQDvIEkfuG8oXqwuMV4cLjhepk9VUD2xGNHbkmWipJLFoqBiWNHXsVQQwkAhv4u+926APlA+WD6d/x3fxNCNsRpBg+HI0dyhmDFHoNggWO/eX1Je5c53PiFeFz4lznevCr/BsKfRZZILkmWip/KGUjPhy0Ek0IRf5R9IXqwuMp3pvcp98D5bvvkfseBiEOtBKXEwwRrwu+A1H7hvKD6RXhR9m307HRsdGB16fffevi+cgG2xHKGY0d6x6NHaQYlxMhDiMHrf+z9zDxTO1p7LvvR/ckAtAOyhllI38oSSxaKrkm6x59FnoNbwRR+4byherC4xXhFeE25nrwd/y5CJcTPhxZINch6x7KGdsRIguJA0L8ZPX07oXqduh26Gnsv/Nl/SMHRRB9FsoZpBh7FYYPTQhfAX76JvN96wPlp9/62kfZm9xz4mns1vZTACoJ0A4MEUUQ2gxNCIkDZf7d+CbzTO126DbmA+V26PTu3fiJA3oNexX9Gj4c/RqkGJcTIQ5NCF8Bj/mG8mnsXOfC4wPlg+l68Dj53QEqCSEORRCGD9oMKgk4BV8B3fyz9ybz9O5964Ppfesw8Tj5IwN6DYoX6x5lIwYl1yGNHaQYtBIiC/QCfvqG8oXqA+Vz4gPlg+kw8eL5AALlByILrwugCYIF9gBR+970TO025hXhm9xH2UfZKd4D5bvvyPrOBYYPexXKGcoZpBh7FQwRnApVAwn83vQl7oPpg+lp7IbyDvs4BYYPpBjrHtchWSCNHcoZlxOvC5sCMvow8Xboc+Ip3qffwuNp7Ef3SgLaDHsVyhn9GsoZfRbbESILMgRl/WD29O6D6TbmXOeF6jDxfvpvBCEOexWkGMoZiheXE3oNHgZF/uX1TO0D5Sne+tr62inewuNM7bP39ALaDJcTfRZ9FnsVtBJ6DU0IAAJR+1H0Je6F6oPpaeyG8n76MgR6DXsVyhn9GsoZfRbbEUEMOAXc/WD2Je5c58Ljc+ID5YXqhvLO+4IFIQ60EoMUlxMMEXoNuQj3AyL/4vne9HrwJe4l7jDx1vY4/6AJgxTrHgYluSa5JmUj6x6kGNsRGwpyAn76JvNM7YPpg+lp7N/xOPmbAbkI2gx6DUEMuQi+A479R/cw8X3rA+UV4Snem9yn3wPlTO1g9l8BIgu0EooXyhmkGH0WtBJ6DeUH3QHO+2D2hvK773rwJvOz92P/uQjbEaQYPhyNHY0dyhmXEyEOggdTAN34MPF96zbmA+U25oPpMPEO+4IFIQ6XE4oXpBh9FrQS0A6gCTIEZf7d+L/zu+8l7iXuMPHW9qH+IwchDrQSgxSDFNsR0A4bCm8EI/5H97vvg+nC4xXhp99z4lznu+/d+H0BTQh6DUUQDBFFENAOrwvlB8cC3fzW9obyevC77zDx5fVl/YIF2gy0En0WpBikGH0WgxRFEJwKbwQ5/eX1u+9p7IXqfev07uX1jv1vBKAJeg3QDtAOIQ7aDBsKcQZKAjn9G/i/8zDxu+8w8eX1jv1xBoYPfRY+HFkgWSBZIOse/Rp9FoYPIweD/tb2MPFM7YXqaex68OX1kfv2APIEIweCB3EGiQOK/376UfRM7TbmFeEp3pvcKd4V4XboevCP+ZsCnApFEIMUfRZ7FZcThg8bCiMDQvzW9oby9O4l7jDxYPYj/sgGhg99Fv0ajR2NHT4cihe0EiILAAJ++Lvvduhz4qffc+Jc57vvj/mJA0EMtBJ9FqQYpBh9FrQSIQ7IBr7/OPm/8/Tuaewl7oby3fjeALkIhg+XE30WfRaDFAwRQQzOBY793vRM7Tbmp9+b3Jvcp98D5SXu1vYi/4IFGwraDHoNeg2vC+UH3QGR++X1MPFp7IXqfeu772D2Rf7IBiEOlxOKF8oZyhmkGHsVRRC5CN4Aj/mG8mnsg+l26IPpJe5R9H76ZAA4BbkInAoiC5wKoAlxBt0BDP0b+Cbz9O5p7Eztu+9k9Y79cQbQDnsV/RqNHese6x6NHcoZtBKvC/cDQvze9PTuaex96yXu3/FH9938mwFvBIIF8gS+AygBd/xg9nrwheoD5affm9yb3Cnec+J26LvvfviyAIIHQQyGD9sRtBIMESEOoAnyBM7/yPrW9lH0v/PW9s77cgIbCgwRfRbKGT4cPhw+HKQYlxMhDnEGI/7l9SXug+k25lznfeuG8sj6mwIqCXoNDBGXE4MUlxNFENoM5QckAkL81vaG8jDx3/Fk9Q77uwG5CCEO2xGDFHsVexW0EtAOKglyAsj6JvN96wPlFeEV4XPiduj07mD2Zf0jA+UHQQwhDiEO2gygCTgFzv8y+lH0u+9M7UztevBk9Xf8vgMbCtAOlxN9FooXiheDFEUQnAoyBDn9YPZ68Gnsfetp7PTuUfQy+jj/IwNxBrkIGwobCioJcQbHAkX+3fi/8/Tuaex960zt3/Hd+A4BTQjQDoMUpBj9Gj4c/RqKF9sRrwsyBAz95fV68Eztaewl7obys/er/LIAMgRxBoIHyAZvBGQAUftk9bvvg+kD5RXhp98V4QPlfeu/8w77JAJNCHoNDBGXE5cT2xHQDiILzgXs/zL65fUm8ybz5fVR+7sB5Qd6DbQSfRbKGf0ayhl9FtsRQQyvBEL8v/NM7XboXOd26Eztv/My+okAcQYiC9AODBEMEUUQeg2gCa8E2P44+VH0evD07nrwUfSP+U7/bwQqCUEM0A6GD9AO2gygCfIECv8b+HrwheoD5RXhFeED5YPp9O5k9Q77BgBvBOUHGwqcChsKTQivBDIAUfvW9obyevB68CbzR/cJ/CgBHgYbCiEORRAMEQwRhg96DSoJbwQ4/zL6ZPXf8TDxhvLe9H74Qvyc/5sC8gQjB7kIoAkbCqAJ5QevBPYAq/x++OX1ZPWz91H7UwCCBZwKhg+XE4oXyhn9Gv0ayhmKF7QS2gxxBor/j/lk9b/zUfRk9Uf3j/nO+yP+zv+JAGQA3f9l/s77fvhR9Lvvhepc5wPlNuZ26GnsMPFg9s77KAHOBSoJQQwhDtAOIQ5BDLkIMgQi/8j6G/iz9zj5Qvzd//cDTQjaDAwRlxN7FX0WexWXE9AOKgkkAsj6UfS77yXuJe568FH0fvhl/ZsCIwecCnoNhg9FEIYPeg0bCoIFFADI+tb23vRR9OX13fgJ/EIAbwTlBxsKQQx6DXoNrwtNCL4D3P3W9rvvheo25gPlNuaD6UzthvIb+GX9uwHOBbkIGwqcCqAJggeJA73+j/ne9N/xMPGG8mT1j/ll/lUD5QevC9AORRAMEUUQIQ6cCs4FFADi+VH0evD07vTuevCG8uX1j/nd/Pr/IwMeBuUHuQhNCMgGVQPY/uL55fUm8ybz3vR++N38SgLlB9oMDBF7FYoXpBikGH0WlxPQDrkIAAKR+2D2JvPf8d/xJvNk9X74Ufvc/b7/nQAyAPL+DP0y+mD23/FM7YPpNuY25jbmg+lM7SbzOPkK/28EKgnaDNAORRCGD9AOQQxNCL4DCv+R++L5j/nI+mX9XwHOBRsK0A7bEYMUexWDFLQShg8iC84FTv/d+L/zevD07vTu3/Hl9X76Iv++A4IHGwqvC0EMQQwiC6AJcQZyAtz94vlH9+X15fUb+FH72P4kAoIFTQgbCpwKnAqgCU0IggV9AQn85fV68Gnsg+mD6YXqJe7f8eX1yPo4//QCzgVNCKAJGwobCk0IOAXeAKv8OPnW9uX11vaP+av8QgAyBOUHnApBDHoNeg3aDCILuQhvBGP/fvpg9ibzMPEw8d/xJvNk9X74kftl/vYAVQM4BcgGIwceBokDrf/O+934YPZk9WD23fgJ/GQAggWcCtAOtBKDFH0WfRZ9FoMURRAiC84F+v9++mD2v/Mm87/zZPWz9376q/wA/mX+Rf4A/jn9kfvd+GT1MPFM7YPpXOdc54PpTO3f8Uf33fzdAR4GKgmvC3oN0A7QDtoMoAmCBd4Ad/yP+X74OPmR+yL/vgO5CNoMRRC0EpcTlxO0EgwR2gzlB5sBDvve9DDx9O707jDx3vTi+SL/9wPlB5wKQQwhDoYPhg96DRsKggUyAA77R/dk9WT11vYy+iP+SgIeBrkInAqvC9oM2gyvC00IiQM5/WD2u++F6lznNuZ26H3ru+/l9VH7MgD3AyMHGwraDHoNQQygCYIFFADI+mD2v/OG8r/z1vYO+xQAOAWgCdoMhg8MEdsR2xHQDiILcQadAA775fWG8nrwevDf8VH0G/gJ/Pr/IwMeBioJnAoiCxsK5QevBEIAzvsb+GT13vRg9o/5AP73AxsKhg+XE30WpBjKGcoZpBh7FQwRnAoyBNz9fvhR9IbyhvK/82D2j/nO+wz9tv3c/bb9Of13/Mj6s/cm8/Tuhepc5zbmXOeD6SXuJvM4+YP+cgKCBU0InAqvC9oM2gwiC4IHiQOK/3f8fvoy+pH7g/70AuUHQQzQDgwRtBK0ErQS2xGGD68LyAb2AA775fWG8jDx3/G/87P3zvt3/wAC9wPOBYIHuQigCaAJTQg4BUMB3fw4+WD2ZPXl9bP3yPpF/kMBiQOCBSMHTQgqCaAJuQgeBrsBd/zW9jDxTO2F6oPphepp7HrwUfQb+JH7of5fATIEcQaCB4IHggWbAoP+fvpH9970v/NR9Ef3Uft3/1UDcQYqCSIL2gwhDiEO2gycCiMHxwIj/uL55fUm84byJvNk9Rv4Dvvc/XYA9ALOBU0IGwoiCxsK5QdvBLIA3fyP+bP3s/cy+iP+xwKCB68L0A7bEYMUihekGMoZpBiDFNAOuQgkApH7YPYm8ybzUfRg9n744vkO+0L8jv0i/3YA9gC+/938fvi/8/Tuhepc51zng+lM7d/x1vZR+yL/9AIjByIL0A4MEQwR0A6vC8gGAAIM/Tj5s/d++FH7Cv/0AsgGGwp6DUUQtBKDFIMUtBIhDk0I3QEO+970u+9M7Uztu++G8tb2yPpl/t0BggUqCUEMIQ4hDkEMuQj3A/L+Mvpg9lH0UfRg9uL5tv1DAW8EIwcbCkEMIQ7QDnoNnAqCBb7/OPmG8kztg+l26IXqJe6G8tb2UftO/1UDIwecCnoNIQ7aDJwKcQZ9AQn8R/dR9L/zZPXd+Az9XwE4BbkIIgt6DYYPDBEMEYYPQQzlB/QCOf0b+FH03/GG8lH01vbi+Xf8OP8AAq8EggcbCiILIgugCcgGmwIA/o/51vZg9rP3Ufvs/zIETQivC9AO2xF7FaQYyhmkGH0WtBLaDM4FCv+P+eX13vTe9GD2s/d++I/5MvqR+zn9Iv8UAHf/jv1++tb23/El7oXqg+mF6kztMPFR9Bv4zvsi//QCyAacCnoN0A7QDnoNnAoeBl8BZf3I+jL6kfvc/bIAvgNxBioJrwvQDgwRtBK0EgwReg0qCVUDZf0b+FH0JvMm8970R/fi+av8Iv8AAoIFKgmvC3oNeg1BDKAJggUOAav8OPmz90f3fvji+c77tv2K/7sBbwQjByoJnAobCk0IbwQi/934hvJM7YXqg+mF6mnsu++G8uX1j/lF/lUD5QevC3oNIQ5BDLkIiQO2/d34ZPXe9GT1s/d++t38OP8AAoIFKgnaDIYPRRCGD3oNKgmJA2X9s/cm8zDxu++77zDxhvLe9LP3zvuJAPIEuQgiC68LGwrIBt0BQvyz91H0JvO/8+X13fhC/Jz/9wMqCSEOlxOKF6QYpBh9FtsRnAojA8775fXf8bvv9O707rvvevDf8d70G/iR+wD+Tv8K/wz9OPlR9CXug+k25sLjwuM25nboaey77970Mvrs/4IFnAohDkUQRRAhDpwKggUGAJH7fviz9374fvoM/ez/iQPlB0EMRRC0EoMUgxTbESEOTQhDATL6UfR68PTu9O568Iby3vR++Kv8fQEeBhsK2gwhDnoNIgsjBwACq/wb+N70JvO/82T1R/eP+av8QgAyBOUHIgt6DSEO2gygCa8ERf6z99/xTO1964Xqaewl7nrwUfR++I79mwIjByILeg0hDtoMoAmvBE7/MvrW9mT15fVH94/5Qvyt/4kD5QevC4YP2xGXE7QSDBF6DU0I9AKO/d34ZPW/8ybzJvNR9OX13fh3/IkAbwTlB5wKQQyvCyoJggVDAd38OPlH99b2s/c4+c77vf6bAiMHQQwMEYMUihfKGaQYfRbbEa8LggWt/w77G/jl9VH0v/O/89701vY4+Qn8vf7IALsBQwFO/0L8G/i/87vvaex9633raexM7bvvhvLW9lH7FADyBKAJeg2GD4YPIQ4iC8gGJAJF/s77fvoy+sj6QvyD/psBOAWgCXoNDBGXE4MUtBJFECILggV3/3761vZR9CbzJvMm8970s/eR+zIA8gQqCdoM0A6GDyEOIgsjB0oCAP7I+n74R/dg9mD2R/eP+av8dgBvBE0IIgvaDEEMGwoeBokAfvre9LvvaeyF6oPpg+mF6kzt3/HW9gz9IwNNCEEMIQ4hDq8LggdyAo79OPlg9t70v/NR9GT1fvir/F8BcQavC4YP2xGXE5cTDBHaDIIHXwEJ/Ef3v/Mw8bvvu+/f8WT14vk4/68EKgnaDIYPhg8hDiILHgYOAXf83fjW9mT15fVH98j6Y//yBCILDBF9Fv0ajR0+HMoZexXQDoIHsgDI+mD2hvK77/Tuu+/f8WT1OPll/fYAvgM4BfIE9AIK/4/5v/P07n3rduhc51znduh96/Tu3vTI+vYAyAavC4YP2xEMEdAOGwryBDIACfw4+Uf31vaz9zL6tv0kAiMHQQxFEIMUfRZ9FpcThg8bCvcDRf44+WT1hvJ68Hrw3/FR9H743fxfAYIFKgmvC9oMQQygCc4FfQE5/Y/51vbe9L/zv/Pe9Ef3yPq9/scCyAagCa8LQQwiC+UHiQMj/t34v/O772nsheqF6n3rJe7f8WD2kfudADgFKgmvC9oMIgu5CG8EMgBC/N34YPZk9WT1YPbd+An8iv8jA8gGGwraDNAOhg/QDtoMuQj3Azj/DvtH91H0hvKG8ibz3vSz9w778v6bAh4GKgmcCiILoAkeBpsCCv/O+zj5s/ez9xv44vmr/FMArwSgCSEOtBJ9FqQYihd7FdsReg3lB/QCI/4y+tb2UfQm8ybzUfTl9X74Dvvc/XYASgKbAkMBof5R+7P3UfTf8bvvJe5M7SXu9O7f8eX1yPqt//IEGwohDgwR2xFFECEOnApxBpsCY//d/FH7yPrO+wD+QwE4BSoJ2gxFELQSlxOXEwwReg0qCfcDCv8y+mD2v/Pf8YbyUfRH98j6g/5yAnEGGwpBDHoN2gycCiMHIwO9/jL61va/84byJvNR9Ef3fvoj/t0BzgWgCa8LQQwiC+UHVQPc/Rv4hvIl7n3rg+mD6X3rJe6G8kf3DP0jA7kI2gyGD4YPeg2gCTgFMgBR+7P33vS/81H05fV++An87P8yBCoJIQ7bEZcTtBJFEEEMyAbeAA775fXf8fTuJe707jDx3vQ4+SP+9wOgCXoNRRBFECEOIgtxBrsBZf2P+db2ZPVk9Uf3fvo4/68EnAoMEX0W/Ro+HD4cpBiDFNAOuQhyAkL8R/cm83rwu+8w8Sbz5fXi+SP+3QFvBIIFrwRKAqH+fvrl9TDxTO2D6VznXOd26H3revBk9VH7QwEjB0EMhg8MEUUQIQ4iC3EGmwE5/eL5s/fW9hv4yPq9/iMDggevC4YPtBKXE4MUtBKGDyILzgUjAMj6YPYm89/xhvLe9LP3UfsK//QCyAYbCtoM0A7QDtoMGwpxBiQC3P1++rP31vZH9934DvuO/TIAIwNxBqAJrwvaDEEMGwpxBn0BQvyz97/zevD07vTuevCG8t703fg5/SQCIwevCyEOhg8hDq8LTQgyBIkAOf3I+jj53fg4+TL6kfuO/YkAMgRNCK8LIQ7QDiEOrwtNCPcDTv/I+tb2v/Pf8XrwevDf8b/zR/eR+0IArwTlB6AJGwoqCcgGMgQoAdz9fvob+GD2YPZH94/5DP19AXEGrwsMEYMUfRZ9FnsVtBLQDqAJ9wMj/jj53vSG8jDxMPHf8b/z5fWP+av8Y/8OAZsB9gAi/0L83fje9DDxTO1964Xqhepp7PTuhvLW9qv8mwJNCNoMhg8MEUUQIQ6cCnEG3QHc/VH74vmP+TL6zvsA/n0BzgWcCtAOtBKDFIMUtBLQDhsK9wMA/t343vTf8XrwevAw8YbyYPbI+jIAggUbCtoMIQ4hDq8L5QcjAyP+4vlg9lH0JvOG8ibz3vR++Az9cgLlB0EM0A7QDnoNGwrOBSMAMvpR9LvvaeyF6oPphepM7TDxs/dl/jgFIgvQDkUQhg/aDCoJrwSK/8j61vZR9Iby3/GG8t703fhF/m8EnAqGD5cTgxSXEwwReg3lB7sBzvtg9obyu+/07vTuevBR9Dj5Iv84BRsKeg3QDtAO2gwbCoIFnQCR+0f3UfSG8ibzUfQb+Az9VQMbCkUQexXKGf0a/RqkGIMU0A5NCF8BUftg9ibzMPEw8d/xUfSz95H7d//HAjgFHgbOBb4DZAAJ/Nb23/FM7YXqg+mD6YXqTO168GT1DvtDASMHrwvQDkUQRRAhDhsKHgZ9Adz9kfsy+jL6Dvvd/Jz/IwMjB68LRRCXE3sVfRaDFAwR2gyCB90BOf3i+bP35fXl9WD2s/cy+mX9fQHOBaAJQQzaDEEMnArlB28EyAC2/Q77j/kb+LP3R/cb+DL6DP0OAfIETQicCq8LIgsqCXEGxwJl/uL5YPYm83rw9O4l7vTuMPHe9I/5OP8yBOUHGwoiCyILoAkjB/cD3gAA/pH7j/kb+LP3G/iP+UL8BgBvBLkIQQzQDoYPhg8hDiILIwf0Atj+Dvuz9970JvOG8ibzZPU4+bb9JAIeBioJIgtBDNoMIgu5CDgFmwEA/g77OPkb+H74Mvpl/QACggfaDNsRfRakGMoZpBh9FrQS2gwjB18BCfxH97/z3/F68HrwhvLl9Y/5DP0yAEoCVQNVA7sBvf7I+tb2hvL07n3rg+l26Hbofet68GD23fxVAyoJeg0MEbQS2xGGD0EM5QeJA3f/CfyP+bP3s/c4+d38mwEjB9oMDBGDFH0WfRaDFEUQIgvyBPL+j/ne9DDxJe5M7SXuMPFg9gn8AAIjB68LIQ6GD9AOQQy5CG8EnP8O+9b2JvN68PTuevAm87P33fwAAnEGGwpBDNoMrwtNCL4D3P2z99/xaexc5wPlwuM25oPpu+9g9mX9iQO5CNoM0A4hDkEMuQj3A/L+fvpg9ibzevC77zDxv/N++EX+bwQbCtAO2xGXE7QShg8iC4IF3f8y+t70evBM7X3raez07ibzG/i2/VUD5QevC3oNeg2vC7kIbwS+/1H7R/e/89/x3/Em89b2QvybAioJhg+DFKQYyhnKGX0WtBLaDMgGdgDI+uX1hvK77/Tuu+/f8d70fvjO+73+sgBfAcgAvf6R+7P3JvP07oXqdug25gPlNuZ26Gns3/Gz92X99AKCB5wKQQxBDJwK5QevBCgB3P1R+zj5G/iz9934zvtj/4kD5QevC9AODBHbEQwRIQ6cCs4FQwEM/Tj5YPa/84byhvK/82D24vkA/iQCHgYqCSILrwsiCyoJyAaJA3YAZf3I+n741vZg9kf3OPnO+/L+cgLOBbkIGwqcCqAJIwf3A/r/zvuz97/zevAl7iXu9O4w8d70j/ll/lUDggecCkEM2gxBDBsKggevBLsBg/5R+3741vbW9hv4fvoj/psCIwciCyEORRBFEIYPeg0bCoIF3gAJ/Ef3v/Mw8bvvevCG8uX1MvoK/74DTQivC3oNeg1BDBsKcQZKAiP+MvpH9+X15fUb+JH7QgCCBSILDBF7FcoZ/RrKGYoXlxMhDrkIcgJ3/Ef3JvMw8bvvevAm8+X14vlF/koCOAUjByMHzgXHAqH+4vne9HrwaeyF6oPphepM7d/xR/eO/TIEnAqGD7QSgxSXE9sRIQ4qCW8Ed/9R+374R/ez94/5Of0AAuUHIQ6XE4oXyhnKGYoXlxPQDrkI9AI5/Rv4UfTf8d/xJvPl9TL6vv/OBSILhg+0EpcTtBJFEEEMggdKAgz9fvhk9SbzhvK/89b2yPrd/zgFnAohDkUQDBGGD68LIwcOAX76UfT07oXqduh26IXqJe4m84/5UwBxBiIL0A6GD4YPeg0bCs4FfQEM/d34ZPW/8ybz3vQb+Hf8uwEjB0EMRRC0EpcTtBKGD68LcQbeAFH7YPaG8rvv9O568IbyYPYO+93/rwS5CK8Leg16DUEMKgk4BcgAQvwb+GT1v/NR9GD24vkA/vQCTQghDrQSfRaKF4oXexXbEdoMIwebAUL8s/fe9CbzhvKG8r/z5fV++FH7of5DAccCmwL2AEX+yPrW9oby9O5964Ppg+mF6mns9O4m87P3q/zdAXEGoAkiC5wKoAkjBzIEDgHc/VH7j/l++N34j/mR+0X+AAIeBpwKIQ5FEEUQhg96DRsKyAbHAr3+Dvuz92T1v/Mm87/z3vSz91H7Tv9VA3EGTQgqCbkIIwc4BZsCnP93/I/51vbe9L/zJvNR9GD2j/mO/V8BbwRxBoIHIweCBZsCCv/I+mD23/H07mnsfet960ztevDe9OL58v5VA8gGuQgbChsKKgkjBzIEQgBC/N345fVR9L/z3vRH9w77iv9vBCoJ2gyGD0UQRRAhDiILcQZfAXf8s/dR9N/xevB68N/x3vQ4+UX+iQNNCK8Leg0hDtoMoAmCBcgAd/zd+OX1UfS/8970s/dC/EoCuQjQDoMUihekGKQYfRbbEdoMyAadAA775fXf8fTuTO0l7rvvv/N++I79AAKCBSMHIwc4BQACjv1++L/z9O6F6nboXOd26IXq9O7e9An89AIqCSEODBHbEQwRIQ6cCnEGmwEM/Tj5YPbe9GT1R/eR+ygBggchDpcTfRakGIoXexXbEXoNgge7AQn8R/e/89/xMPGG8uX1fvojAB4GIguGDwwR2xEMESEOGwqCBZ0AkftH91H0hvKG8lH01vYO+93/8gSgCdoMIQ4hDkEMTQhVA479s/ff8Uztg+l26IPpfev07lH04vn6/zgFoAlBDHoNeg2vC7kI8gR2AAn8G/hk9VH0UfTl9X74QvyyAIIFGwp6DUUQRRCGD3oNoAnyBK3/yPpg9r/zhvLf8Yby3vSz91H73f9vBE0IIgvaDEEMnArlB28EdgDd/OL5G/hH97P3OPkJ/M7/rwQbCtAOlxN7FX0WfRaXE0UQQQzlByMD2P4O+xv45fVR9L/zUfTl9X74kftF/jIAKAH2AM7/3P1R+xv43vTf8fTuJe5M7Uzt9O4w8WT14vny/okDggecCkEM2gxBDCILuQgeBlUDiQAA/kL8UftR+938nP9VA4IHIgshDkUQDBEMEYYPeg0bCnEGcgKh/g77G/jl9VH0UfTl9d34q/yyAG8EggegCSILrwsiCyoJcQZVA93/d/w4+db23vRR9GT1G/hR+07/IwMeBrkIoAmgCU0IggWbAd38G/gm8/TuaeyF6oXqaex68N70MvqK/28EuQivC3oNIQ5BDKAJHga7AWX9OPnl9Sbz3/Em82T1j/mh/r4DTQhBDNAOhg/QDtoMuQj3A/L+j/ne9HrwTO1962ns9O4m8934Cv+vBCoJ2gwhDiEO2gygCYIF9gAJ/LP3v/Pf8d/xv/Mb+Nz9rwSvC9sRfRakGMoZyhl9FrQS2gzIBmQAMvpR9HrwTO1M7SXu3/Fg9lH7+v/3A8gG5QcjB/IE9gAJ/GD2MPFp7HboNuY25nbofesw8Rv4OP8eBq8Lhg/bEbQS2xHQDpwKzgWyAM77s/fe9FH0ZPV++GX9VQOgCdAOtBJ7FX0WexW0EiEOKgmJA7b9G/i/83rw9O707jDxZPXI+p0AHgacCiEORRBFENAOQQxNCPcDd/8O+0f3UfQm8ybz3vQb+Az9SgIjByILeg3QDiEOrwtNCIkDI/7d+L/zu+9p7H3raez07ibzfviD/jIEuQhBDNAOhg/QDtoMGwpxBkoCRf7I+hv4YPZg9hv4DvsK/4kD5QevCyEOhg+GDyEOrwvlB74Dd/9R+7P3UfSG8jDxMPGG8uX1j/m2/V8BMgQeBiMHIwceBvcDmwG9/gn8OPlH9+X15fVH93762P6+A7kI2gxFENsRtBK0EgwRIQ4iC4IHiQNj/w77R/dR9CbzhvK/82T1s/d++t388v5kAN4AUwDy/t38fvqz9970hvJ68PTu9O6779/xZPU4+Y79fQHyBOUHGwoiCyILnAq5CHEGVQNCADn9yPo4+Tj5fvoM/Z0AbwRNCCILeg2GD4YP0A56DSIL5QcyBPr/kfuz9970JvO/82T1fvgJ/Oz/vgOCBxsKQQx6DdoMrwugCXEGcgIA/o/55fVR9FH05fU4+av8nQBvBOUHnAqvC0EMnArlBzIEd/8y+t70u+9p7H3rfesl7obys/cM/ccC5QdBDIYPDBEMEYYP2gy5CL4DZf44+WT1v/O/82T1fvg5/UoCggdBDIYP2xHbEQwR0A4iC3EG9gDI+t70evBM7WnsJe7f8WD2kfsOAXEGnAp6DdAO0A56DRsKzgVTAMj65fWG8jDxhvJk9X76nQAjB3oNtBJ9FsoZyhmkGH0W2xFBDM4FCv/d+L/zevD07vTu3/Fk9TL6Iv+JAyMHKgkqCeUHOAUoAXf8R/eG8kztg+l26Hbofet68OX1zvskAuUHQQyGDwwRDBHQDkEM5QfHAo793fje9IbyJvNk9eL5Tv84BSILhg+0EoMUexWXEwwReg0qCb4DI/44+d70hvLf8SbzYPZ++iL/9wNNCK8Leg3QDiEOQQwbCnEGmwIj/uL5YPa/87/z3vRH98j62P7HAh4GuQgbCpwKKgkjB4kDd//I+uX1MPFM7X3rhepp7PTuJvOz90L8dgAyBCMHuQigCSoJ5QeCBUoC2P5R+xv45fVk9eX1s/fI+gD+mwE4BU0IGwoiC5wKoAlNCM4FxwJO/1H7s/dR9IbyhvIm8970R/d++rb9yABVAzgFcQZxBh4GrwRyApz/d/w4+db25fVg9hv4DvuD/nICHgagCdoM0A6GD0UQhg8hDq8LTQgyBM7/kfsb+GT1v/Mm8ybz3vTW9jj5kftl/aH+Tv9O/6H+Of0O+7P3UfQw8fTuTO1M7SXuu+8m82D2fvqh/nICggVNCBsKnAobCk0IOAVDATn94vlH92D2R/fd+M77OP/0AnEGoAnaDNAORRBFENAOQQxNCFUDI/6P+eX1v/Mm8ybzZPUb+M777P8yBOUHIgt6DdAO0A7aDCoJbwQK/+L55fUm89/x3/Em82D2MvqD/scCcQagCSILIgugCR4GXwGR+2T1u+9964Ppg+mF6kzt3/FH92X9VQO5CHoNRRAMEQwRIQ4bCvIETv/i+WT1JvPf8Yby3vQ4+SP+iQO5CHoNDBG0EpcT2xGGD5wK8gSD/n74JvO77/Tu9O4w8WT1fvoGAM4FIguGD9sRtBLbEdAOnAo4BXf/4vnl9b/zv/Pl9eL52P6vBJwKRRB7FaQY/Rr9GqQYexVFEJwKvgNl/Rv4UfTf8TDxJvPl9eL5of70AsgGKgkbChsKTQiCBX0Bd/xH94by9O5p7GnsJe4w8WT1yPojAIIFGwp6DUUQDBEMEdAOIgtxBkMBQvwb+OX1ZPVg9jj5Of3dAXEGIgvQDgwRtBK0EgwR0A6cCs4FdgBR+0f3UfSG8obyUfRH98j62P7HAnEGoAmvC9oMQQwiC7kIggVDAQz9j/nW9mT1ZPVg9n74Ufuh/iQC8gQjB00IuQiCB4IFmwKD/uL5ZPXf8fTuTO1M7SXuevC/87P3zvsGAIkDHgblB7kIuQjlB84FxwJ3/0L8j/mz99b2R/d++Mj6jv2JAIkDHgblByoJGwqgCbkIcQaJA77/Cfx++GT1v/Mm8ybzUfRg9o/5q/yt/3IC8gTIBoIHggceBokDdgAM/TL6G/hH90f3G/gy+t38UwD3A4IHnAp6DdAORRBFENAOQQy5CK8EQgCR+7P3UfSG8t/x3/G/8+X1fvhR+wD+FACbAXIC3QFCALb9fvpH97/zevD07iXu9O568Cbz1vYO+77/MgRNCK8Leg0hDtoMoAnOBV8BDP04+db2ZPXl9Uf3Mvq2/d0BcQacCiEODBHbEdsRRRDaDLkIIwPc/Tj5ZPUm89/xhvJR9LP3zvt2ADgFKgnaDNAOhg8hDiILyAabAUL8R/cm83rwu+968Iby5fUy+iL/vgOCBxsKIgucCk0IMgTy/jj5v/P07n3rduh26IXqJe4m84/5IwBxBq8Lhg/bEbQS2xHQDhsKbwS9/uL5YPa/87/z3vSz9877yADOBZwK0A7bEbQStBIMEdoM5QcAAs77YPaG8rvv9O6779/xYPZR+w4BcQYiCyEOhg+GD3oNGwo4BSMAUftH91H0JvO/8+X14vkK//IEnAqGD5cTfRaKF30WgxRFEK8LHgZCAMj65fWG8nrwevCG8t703fir/Pr/mwIyBK8EvgPdASL/kfuz97/zu+9M7X3rfetM7bvvv/N++Az9XwE4BeUHoAkbCqAJggevBA4BOf3i+bP3YPZg9rP3fvoj/iQCHgagCUEMIQ6GD4YPIQ5BDCoJggXdAWX+Ufs4+X74fvji+Qn8vf67AW8EyAa5CBsKnAqcCqAJ5Qc4BSQC8v7O+4/5G/hH97P3OPlR+479iv9DAZsCVQNVA5sCKAHy/kL8OPlg9ibzMPG77/Tuu+/f8VH0s/dR+73+uwFvBHEG5QdNCOUHcQavBHIC7P+2/c77yPrI+pH7Of1j/5sB9wMeBk0IoAmcCiILnAqgCSMHbwRDASP+Ufvd+Ef31vaz94/5zvuD/n0BbwTIBrkIoAmgCSoJggc4BZsC3f9l/ZH7yPpR+938d/+bAh4GoAlBDNAODBG0EpcTtBIMEXoNKgkyBDj/yPpH9970UfTe9GD2G/jI+jn9iv+7AYkDrwSvBFUD3gBl/Y/55fWG8nrw9O677zDxUfQb+Hf89gCCBaAJ2gwhDtAO2gwbCnEGAAKO/eL5R/fl9WD2fvhR+yL/VQOCB68L0A7bEbQStBIMEXoNuQhVAyP+OPnl9b/zJvNR9Ef3yPry/lUDggciCyEORRBFENAOrwsjBwACq/wb+FH0hvLf8SbzYPYy+mX+mwJxBioJIgsiCxsKggdVA0X+3fgm8yXufeuD6YXqTO0w8db2QvzdASMHIgshDoYPhg8hDpwKHgZ9Aav8fvhk9VH03vTW9n76vf4jAyMHIgshDoYPRRCGD9oMKgnyBN3/yPpg9ibzMPEw8Yby5fUy+tj+VQMjBxsKrwtBDCILKgkeBkoCI/4y+tb23vRR9OX1fvjd/JsBHgacCiEORRDbEbQS2xGGD9oMuQgyBHf/yPpH9970UfRk9Uf34vl3/Nj+nQDdAZsCmwK7Afr/jv3I+rP33vTf8bvv9O707jDxJvNg9uL5Of1kACMDOAVxBsgGHgavBJsCFABl/cj63fgb+H744vlC/Ar/3QFvBMgGTQigCRsKGwqgCU0IcQb3Aw4BI/6R++L5OPk4+X76Cfy2/WP/DgGbAjIEzgXIBiMHIwdxBq8EmwIjALb9zvt++uL5MvoO+0L8tv3y/kIAfQFKAscCmwIAArIAof4J/Dj5YPa/84by3/GG8r/zZPUb+Mj6tv2yAIkDzgWCB00ITQiCB84FiQMOAYP+q/xR+w77DvvO+wz9vf7IAPQCOAUjB00IKgkqCeUHzgX0AmP/kfsb+GT1v/Mm87/zZPWz9376tv3IAL4DzgWCB+UHIweCBfQC3f/d/DL6fvgb+N34yPo5/RQAVQMjB5wKIQ5FENsRtBLbEdAOnArOBVMAkfuz9970v/O/81H05fUb+A77AP7eAFUD8gSCBa8ExwJ3/1H7R/e/83rw9O4l7rvvMPHe9N34Zf1KAsgGnAraDHoN2gycCiMH9AKD/n76s/dg9mD2s/cy+mX9QwGCBaAJeg1FENsR2xEMEXoNoAlvBAr/Mvpg9lH0v/NR9GD2j/k5/X0BzgWgCdoMhg9FENAO2gy5CPcD8v4y+mD2UfS/89701vbi+WX9DgGvBOUHoAmcChsKTQjyBGQADvvl9TDxTO1962nsJe7f8eX1yPr6/68EuQivC3oNeg1BDBsKcQYAAmX9OPlg9t703vRg9jj5q/xkADIEggecCkEM2gzaDCILuQiCBQ4Bd/wb+FH0hvLf8SbzZPXd+Hf8BgBVAx4G5Qe5CE0Iggc4BUoCof7I+rP3ZPXe9OX1fviR+wr/mwIeBioJrwt6DdAO0A7QDtoMoAmCBUMBOf3i+Rv4R/ez93744vmR+zn9of6+/3YAyACdAAYA2P4M/Q773fhg9t70v/O/81H05fWz9+L5QvzY/l8BiQPyBB4GyAYeBjgFiQN9AXf/tv2r/Kv8Of1l/s7/fQEjA/IEcQaCB7kIoAmcChsKoAnlB84FVQMOASL/3P0M/d38DP2O/UX+Y//IAHICMgTOBYIHTQi5COUHHgb3A5sBY/+O/UL8UfvI+n76yPqR+3f8tv0K/4kAuwFyAnICmwHO/2X9fvob+OX1UfS/87/z3vRg9n74DvsA/igBbwSCB6AJnAoiCxsK5QeCBZsCIwAj/t38CfzO+wn8DP2D/nYAxwI4BYIHoAmcCpwKKglxBpsCg/5++rP3ZPW/87/zUfTl9Rv4yPoj/psB8gSCByoJKgnlBzgF3QGD/pH7j/l++H74OPl++nf8Iv9yAnEGnArQDtsRtBK0EkUQ2gxNCFUDof7I+rP35fVR9FH03vRg9n74kfuD/kMBiQOvBK8EVQN2AKv83fje9N/xu+8l7vTuu++G8uX1Mvry/okDggecCkEMQQycCoIHiQM4/1H7fvjW9mD21vZ++A77I/4AAh4GnAohDkUQDBFFECEOnApxBn0BOf3i+Uf35fXl9db23fjO+3f/VQPIBhsKQQx6DXoNIgtNCPcDnP+R+xv45fVR9FH0ZPWz9376tv32APcDHgaCB4IHcQb3A3YACfxH9ybzu+8l7kztJe4w8VH0G/h3/LIAbwSCB6AJnAqcCioJIwe+A0IADP1++t34fvg4+Q77tv2JAFUDHgblB6AJnAoiC5wKKglxBiMDTv+R+9341vbl9WD2s/eP+UL8vf4oASMDrwTOBR4GzgVvBHICnP+r/DL63fh++Dj5yPoM/WP/3QFvBCMHKgkiC9oMeg16DUEMnAqCB28EQwGh/qv8UfsO+w77UfvO+3f83fw5/bb9AP4j/iP+3P0M/c77Mvrd+LP3YPbl9eX15fXW9hv44vmR+2X9Y/8oAZsC9wNvBG8EvgPHApsBnQDO/2P/Y//O/0IA9gDdAfQCMgSCBcgG5QcqCaAJoAkqCU0IIweCBYkDmwEjAAr/Rf4j/mX+Cv8UAH0BVQPyBMgGTQgqCaAJKgnlBx4GvgNfASL/Zf0J/FH7DvtR+877q/zc/Tj/sgAAApsCcgJfAXf/3fzi+Uf33vS/8ybzJvO/8970R/eP+UL8Tv9yAjgFIwdNCE0IIwc4BccCUwAj/nf8kfsO+1H7zvsM/dj+DgG+A3EGKgmcCq8LnAq5CM4FAAJF/sj6G/hg9mT1ZPXl9bP3j/lC/CL/JAKvBHEGyAYeBjIEuwHy/kL8Mvrd+H74fvg4+VH7AP5DAfIEuQhBDIYPDBHbEUUQIQ4bCh4GuwHc/cj6fvhH99b2R/d++H76q/wK/30BiQPyBIIFrwT0AlMADP2P+WD2v/OG8t/xJvNk9Rv4kfsK/5sCzgW5CBsKnAqgCYIHrwQoAdz9UfuP+d34OPl++t38zv/0Ah4GKgmvCyEOhg+GDyEOrwtNCK8E3gCO/VH74vmP+X76QvyD/g4BvgMeBrkInAqvC68LnAq5CM4FmwIi/wn84vnd+H74OPkO+wz9Iv8OAfQCbwSCBc4FOAWJA94Ajv3i+WD2v/Pf8TDx3/Em8+X1OPlC/CL/uwEyBB4GggflB4IHcQavBEoC3f/c/av8d/wM/SP+7P+7AVUDrwTOBSMH5Qe5CLkI5QdxBm8E3QE4/938Dvsy+jL6yPoJ/Dn9g/6+//YAJAIjA/cD9wNVAyQCiQDy/mX9QvzO+877d/y2/Xf/KAHHAm8EHgaCByoJGwoiCyILGwq5CCMH8gTHAvYAnP+h/kX+I/7c/Y79Of3d/Hf8d/xC/Hf8d/yr/Hf8CfwO+4/5fvhH99b21vbW9kf3s/d++I/5yPpC/AD+d/+yAJsB3QG7ASgBUwCK//L+g/5l/mX+g/69/gr/nP+JAN0BiQM4BcgG5Qe5CE0IggdxBvIEVQO7AVMATv+D/gD+AP5l/k7/nQBKAjIEHgblB7kIKgm5CIIHggWJA30Biv8A/qv8zvtR+1H7zvvd/GX++v9fAXICxwIAAkIAAP4O+xv45fW/84by3/Hf8Ybyv/Pl9d34zvsi/3ICOAXIBiMHcQY4BSMD3gC9/t38Uft++jL6fvpR+wz9Cv99ATIEyAYqCRsKGwq5CB4GIwPd/6v8Mvob+Nb2YPbW9rP34vl3/Hf/SgLyBMgGggcjB84F9wObASL/3fxR+zL64vl++s77AP7IAPcDggciCyEORRAMEUUQIQ4iC4IH9wNTADn9DvuP+d343fiP+cj6CfyO/U7/DgFKAscCSgKyAEX+Ufsb+GT1hvIw8XrwMPHf8VH01vYy+mX9nQCJA4IFHgbOBW8EcgIUAI79UfuP+d343fji+ZH73P12AFUDHga5CCIL2gzaDEEMnApNCM4FxwLs/7b9QvwJ/Hf8jv1O/0MBVQPyBMgGTQgqCSoJuQiCB4IFIwOJACP+QvxR+w77kft3/AD+nP8oAZsC9wPyBDgFrwSJA5sBCv9C/Dj51vbe9FH03vTl9bP3j/nO+yP+MgAkAr4D8gQ4BfIEMgTHAigBY//c/d38q/wM/QD+OP+dAN0B9AK+A68EOAXOBR4GzgXyBIkDAAIGAEX+3fzO+5H7zvtC/Az9AP7Y/s7/nQBDAZsB3QG7AV8BsgDs/wr/Zf7c/dz9Rf7y/s7/yADdASMDbwSCBcgG5Qe5CCoJKgm5COUHcQbyBIkDcgJ9AZ0A7P9O/73+AP45/Xf8Qvyr/Az9tv1F/oP+g/4A/jn9QvxR+zL6j/nd+H74fvjd+Dj5MvqR+938Rf6K/7IAfQHdAd0BXwGdAM7/Cv9F/o79Of05/WX93P29/gYAmwFVA/IEyAblB7kIuQjlB3EGrwTHAvYAiv9l/rb9Zf1l/dz92P4yAAACvgOCBSMH5QeCB8gGOAUjA94Avf6r/A77MvqP+eL5MvpR+938vf5kALsBSgIkAg4BIv+r/OL5s/dk9VH0JvMm87/zZPVH94/5Qvw4/wACMgTOBXEGHgbyBPQCnQAj/gn8fvqP+Tj5OPni+Q773fwK/30BvgOCBXEGcQY4BSMDQgAM/eL5R/dk9b/zv/NR9OX1s/d++jn9+v9KAvcD8gTyBPcDJAL6/479UfuP+Rv4s/d++I/5zvuD/rsBOAVNCJwK2gx6DXoNrwugCcgGiQN2ALb9zvvI+n76fvoO+wn8Zf0i/8gAJAIjA74DiQNyArIAg/7O+zj5R/dk9d703vTl9bP3MvoM/d3/SgIyBDgFzgWCBW8EmwKdAGX+Qvx++jj53fiP+cj6d/zY/l8BvgPOBYIHTQgqCSoJuQiCB84FiQNfAYr/Rf7c/WX+d//eAHICMgSCBcgGggflB+UH5QcjB4IF9wMAAuz/I/4M/Xf8q/w5/SP+OP8yACgB3QFKAnICSgJ9ASMAI/7O+4/5s/fl9WT1ZPVg9rP3OPkO+wz9Cv/eAEoCiQMyBK8ErwRvBIkDcgKbAfYAyAAOAZsBSgL0AokDbwTyBIIFHgZxBnEGcQbOBfIEvgNyAigB3f+9/gD+jv2O/bb9I/7Y/nf/FACdAA4BfQGbAZsBfQEoAbIAQgC+/zj/8v7y/jj/nP9TACgBSgKJA68EzgXIBuUHuQi5CLkITQgjB84FrwSJA3ICQwEGANj+tv0M/Xf8CfxC/Kv8Zf1F/gr/nP/O/2P/Rf7d/FH7Mvrd+Bv4G/gb+N344vkO+0L8tv1j//YASgJVA74DVQNyAkMB3f+h/o793fx3/Hf8DP22/dj+MgAAAjIEHgblByoJKglNCCMHOAWJAwACiQBj/6H+Rf5F/qH+nP/2AJsCbwQeBoIHTQhNCIIHzgW+A30BTv85/VH7Mvo4+Tj54vkO+3f8Rf7d/w4BuwGbAbIA8v6r/OL5s/dk9b/zJvOG8ibzUfRg9t34kfuD/kMBvgOCBXEGcQaCBfcDSgJ2AL3+Zf13/An8Qvxl/dj+yAD0AvIEyAZNCLkIKglNCHEGvgOyALb9yPp++Nb25fVg9kf33fgO+2X9nP9fAZsCVQOJAyMD3QH6/7b9kfvi+X74G/h++OL5zvuh/n0BbwTIBioJIgtBDEEMIgugCSMHbwSbATj/Of0J/FH7UfvO+6v8tv2D/mP/FADIAH0BmwEOAa3/jv0O+374YPbe9FH0UfTe9GD2fvjI+t38Cv+yAAACxwL0ApsCXwGc/7b9Cfx++uL5j/ky+lH7DP3Y/p0ASgL3A4IFcQYjB4IHIwceBm8ExwJDASMAiv9j/77/ZABfAXICiQNvBPIEOAWCBTgF8gRvBL4DmwJfAUIAY//Y/oP+g/69/jj/zv92ACgBmwG7AZsBDgFTACL/jv0J/Mj6j/nd+Bv4G/jd+I/5fvqR+9383P0i/1MAKAG7ASQCcgJyApsCmwLHAscCxwIjA4kDvgMyBK8EOAXOBR4GcQZxBh4GHgYeBs4FOAVvBIkDcgJ9AYkA3f9O/wr/Cv9j/93/UwCyAN4ADgFDAV8BfQF9AUMB3gCJAAYAnP9O/zj/d//6/7IAmwHHAvcD8gTOBcgGggflB+UHggfIBh4G8gT3A/QCuwFCAGP/g/6O/Xf8zvuR+877d/yO/Tj/iQAAAr4DMgRKAr7/d/zd+GD25fVR9DDxTO2F6oPpaewm8zL6xwIiC0UQtBIMEdoMuQiCBYkDDgE5/TL6s/dg9hv43P2vBJwKhg8MEYYPQQyCB28EvgPyBIIFrwRvBPQCyACc/+z/uwHHAiQCof6P+eX1ZPVH91H7iQAjB68L2gwiC8gGKAFR+7P3YPZg9tb2R/dH97P34vll/q8EIguGD4YPQQwjB+z/OPne9IbyhvLe9Nb2G/h++H74yPrY/okDoAmGD7QStBKGD6AJSgJ3/Dj53fiP+TL6Mvo4+d34fvpl/fQCrwt7Ff0a/Rp9FnoN3QFg9mnsNuYD5QPlNuZc52nshvKR+8gGlxPrHgYluSbXIYoXTQg4+UztXOcD5Vznfeu771H0j/myACILpBhlI1oqWioGJaQYGwoy+iXuXOcD5QPlNuZ26IPpfeu77xv49wNFEMoZjR2NHX0Wrwvy/t70TO2F6oPpduh26Hboher07kf39wMMET4c1yFlI40dlxPIBjj59O526APlwuNz4sLjA+WF6mD2ggV7FWUjSSxPLkksZSOKFxsKIv+z99/xJe5964Ppg+lp7N70fQGGDz4cBiV/KLkm6x6XE3EGyPow8YPpc+Ip3vraR9mb3APlhvJ9AYYP/RpZIFkg/RrbER4GMvq771znp9/62oHXptVH2cLj3/FyArQS6x65Jn8oBiU+HNsRcQYM/VH0aewD5aff+tqb3MLju+9l/kEMiheNHesePhx7FUEMVQMO+7/zJe6D6TbmwuMD5X3rYPZVAwwRjR0GJbkmZSONHZcTggcy+kztFeGB11/NJsaGwybGlM8p3vTuI/5NCNoMrwseBgz93/E25ineptWx0V/NEsuUz0fZg+mc/4oXTy44PzNIdksTRdo5Ty5ZIIMUrwvyBIP+4vmP+WX+KgmkGFoq2jkVQjNIE0U4P+40fyjKGdoM3QEb+PTuXOcD5XbohvIAApcTBiVsMFc3VzfuNEks6x4MEccC1vZ96xXhgdex0ZTPt9Ob3FznhvKR+1MAmwEyAEL8YPb07nbowuMV4ZvcR9lH2ZvcNua/8ygBeg19Fv0a/Rp9FtAOvgNg9nbom9yx0anIyMDtuuu9JsaUz5vcg+nf8VH0MPF26CnelM/IwIq0k635pfml+aWTre26X80D5d3/yhlsMBVCdkt2SzNIFUJXN2wwfyjXIY0d/Rr9GuseuSahMhVCbVIVXr5mvmZSYgda3k44P2wwWSCXEyMHDP3l9b/zR/eK/68L/Rp/KKEyVzdXN6EyWirrHpcTIwfI+vTuwuP62oHXgdeb3APlMPGr/IIFIgshDtAOIguCBWP/fvjf8X3rA+UV4affc+J26DDxq/wjByEO2xHbEdAOggcj/ibzXOf62pTPhsPtus237bqGw1/N+tpc5/Tu3/F68H3rc+KB11/NhsPtuoq0IrEisYq0671fzXPiMvoMEQYloTJ6PDg/OD/aOe40Ty5/KFkgyhmXE0UQ2xF9FlkgSSxXNzg/E0UTRRVCejyhMn8ojR3bEc4FMvow8Wnsfeu777P3IwPQDqQY1yG5Jn8ouSZlIz4cgxSvC8gAZPV968Ljp98p3hXhdui779b23fzIAEoCfQEi/5H7fvje9Hrwaex26DbmNuZ26LvvG/h9AaAJRRC0EgwR2gyCBQz9UfSF6hXhgdeUzxLLqchfzabVp99967/zfvh++L/zfetz4kfZlM+pyMjA7brtuu26672pyEfZaeyJALQS1yFPLu40VzdXN1c37jRsMEksuSbXIY0dPhzrHgYlSSzuNHo8FUIVQhVCejzuNEks1yGKFyIL+v/W9rvvfetp7Hrws/d2ALkIRRB7FYoXpBh9FpcThg8bCokDOf3W9nrwaeyF6mnsevDW9rb99wNNCBsKKglxBvQCzv/O+7P3v/O772nsg+mD6WnsMPGz94P+bwTlB+UHbwTY/t343/GD6RXhR9m301/NX82Uz4HXFeFM7d34QwGCBfIEY/+z9/TuNuab3LfTX82pyCbGJsZfzUfZg+nO+yEOjR1/KGwwoTKhMmwwSSy5Jlkg/Rp9FtsRhg9FEJcTyhnXIVoqoTJXN9o5VzehMkksZSOkGNAOOAUJ/FH09O5M7fTuUfRC/M4Fhg+kGI0d6x4+HKQYlxPaDPIEOf3e9GnsA+Wn3yneKd5z4oPp3/GP+QD+Iv9l/t384vlg9ibzu+9p7HboNuYD5Tbmg+l68Dj5cgIbCiEOeg0iCx4GTv9H9/TuXOen30fZptW304HXKd6D6d70nQC5CK8LGwo4Bb3+1vYl7jbmKd6m1ZTPX81fzabVc+Lf8YkDexUGJU8u7jTaOdo5VzfuNKEyTy5/KGUjjR39Gj4c6x4GJUks7jR6PDg/OD96PFc3bDC5JusegxSgCWP/1vZ68CXu9O6G8o/5xwIiCwwRlxODFLQShg8iCx4Gvv+z9/TuA+Wb3IHXt9O300fZFeF26CXuMPEm84by3/F68PTuTO2F6jbmc+Ip3pvcKd4V4Xbo3/Ey+gYA9AIjA4kACfxg9rvvduin30fZt9Ox0bHRptUp3nbov/Nl/fQC8gRVA/L+3fiG8oXqc+JH2bHRX81fzbHRgdfC4ybzMgSDFNchSSyhMlc32jnaOVc37jRsMEksfyi5JgYlBiV/KE8u7jR6PBVCE0UTRRVCejxXN08uBiXKGUUQcQah/jj5ZPXe9N34nP/IBnoN2xGXE7QSRRDaDOUH3QF++t/xg+kV4UfZt9Ox0bfTgdcp3nPiNuZ26HboduiD6YPpheqF6nboNuYD5cLjwuMD5YXq3/GP+ez/MgTOBa8EJAIA/jj5JvNp7MLjKd5H2abVptVH2affdui772T1G/iz92T1MPFp7Dbmp9+B15TPEsupyKnIX82m1cLj3vTOBXsVZSNPLu402jl6PHo8ejxXN6EyTy5/KAYlZSMGJVoqbDBXNzg/E0UzSDNIFUJ6PFc3Ty5lI6QYeg2+A376v/N68N/x1vZl/a8EIguGD9sR2xEMEYYPrwseBoP+YPZM7cLjm9xH2YHX+tqn3wPlhepM7fTu9O707vTuJe5p7IPpXOfC4xXhKd6n33Pidui777P33P0AAokDxwJ2AHf8YPYl7gPlm9ym1ZTPX82Uz6bVKd5c57vv5fU4+eL5G/hR9PTuXOen34HXlM+pyCbGJsYSy6bVA+Xe9M4FexXXIUksoTJXN9o5ejzaOe40bDBaKgYlWSBZINchfyhsMFc3OD8VQhNFFUI4P9o57jRJLGUjpBghDscCOPmG8nrw3/HW9gz9iQO5CEEM0A7bEZcTtBKGDyIL9wN++rvvNuan35vcm9wV4Tbmfeu774by3vTW9jj5Mvoy+jj51vaG8kztdugD5QPlduhM7VH0CfwkAh4GTQgqCU0IMgQj/tb29O425qff+tqB10fZKd7C433r3/FH9zj53fjW9obyfevC4/rat9MSyybGhsOGw6nIt9MV4d/x3QFFED4cBiVPLqEy7jRXN+40oTJPLloquSZlI2UjBiV/KE8u7jRXN9o52jnaOVc3oTJJLAYlPhy0ErkIIv9H94byMPEm89b2zvut/8cCcQagCUEMIQ4hDkEM5QcOAd34u+926HPiFeFz4gPlg+lM7bvv3/FR9OX1s/eP+eL5OPnW9ibz9O6F6nboduiF6rvv5fV++gD+nQC7AUMBCv8O+2T19O526HPim9z62kfZ+toV4VznJe4m82D2s/fW9r/z9O526BXh+tqx0RLLJsaGwybGX81H2Vzn1vY4BbQSjR25Jk8u7jRXN9o52jnaOe40oTJPLkksSSxsMO402jl6PDg/FUIVQjg/ejxXN6EyWipZIHsVnAreAN34v/OG8r/zYPY4+Qn82P67AW8EyAblB4IH8gTs/xv4u+9c56ffm9yb3Kffc+Jc54XqTO168L/z1vZ++o79rf+t/479Mvpg9obyevAw8VH0fvgM/UMB8gSCB7kI5QfyBPYACfzl9bvvg+nC46ffKd4V4QPlg+n07ibzZPXl9VH0evBp7FznFeFH2bHREssmxobDJsZfzUfZNuZR9JsBeg2KF1kguSZJLKEyVzdXN1c3oTJPLloqfyh/KEksbDDuNFc32jl6PHo82jlXN+40Ty65Jo0dtBIjBwn8JvMl7n3raez07oby1vYJ/A4BOAW5CJwKoAlxBigBj/kw8Xboc+Kn36ffp99z4gPlduh96/Tu3/Fk9X74yPqR+1H73fhR9LvvaeyF6n3rJe6G8rP3Zf0AAjIErwT3AyQC2P5++mT1u++D6cLjp9+n3xXhwuN26GnsMPG/81H0JvN68GnsNuan30fZsdESyybGJsapyJTPR9kD5Xrwkfs4BSEOexWNHWUjfyhJLEksSSx/KAYlZSNlIwYluSZaKk8ubDDuNO40VzdXN1c37jRsMFoq1yF9FkEMSgJ++mT1hvIw8Yby5fUy+mP/8gQbCnoNIQ7aDLkImwJ++obyfes25sLjc+Jz4nPiA+U25nboaex68GT1OPlC/Lb9Zf3I+tb2JvO77/Tuu++G8mD2yPqh/rsBvgMyBPQCnQDc/TL6ZPV68IXqNubC48LjNuaD6UztMPFR9GT13vQm8/TuheoD5aff+tqm1ZTPX82Uz7fTm9wD5SXuR/cUAE0IDBGkGOseBiVaKk8uTy5PLkksfyh/KLkmfyhaKkksTy5sMKEy7jTuNO407jShMk8uuSbrHnsV2gxvBNz9OPlH90f3j/kM/QACggdBDIYP2xHbEUUQ2gzIBvr/OPkm8yXug+lc5zbmNuY25nbofev07t/x3vSz94/5fvrd+GT13/El7oXqg+mF6kztMPHl9X763P1j/4r/of4M/Q77fvhR9PTuheo25gPlA+Vc533r9O4m8+X11vZk9d/xTO126MLjKd5H2bfTlM9fzZTPsdGB16ffdugw8VH7OAXQDooX6x4GJVoqSSxJLEksWiq5JgYlBiW5Jn8oWipPLqEy7jRXN9o52jnaOe40bDB/KOseexWvC/QCQvwb+OX1YPaP+SP+iQNNCK8LIQ7QDiEOrwsjBygBfvom833rA+UV4Snem9wp3hXhwuM25nbofeu77ybz5fXW9uX1hvIl7oXqXOdc54PpTO2G8hv4DP12ACQCcgIkAkMBIv+R+9b2MPFp7FznNuY25nboaeww8d701vbW9t703/El7oXqNuYV4fraptWx0ZTPlM+304HXp9926N/xQvxxBkUQpBhZILkmSSxPLk8uTy5aKn8oBiVlI2UjBiW5JkksbDDuNFc3VzfaOVc37jRPLrkmjR2XE5wKxwJC/LP35fVg9o/5g/6JA00I2gwMEZcTgxS0EoYPGwqJA3f8ZPX07oXqXOcD5TbmXOeF6kztevDe9Dj5d/yh/oP+Cfyz94byJe6F6oPphepM7d/x1vYy+qv83P2D/mX+Of1R+xv4JvMl7oPpNuYD5Tbmg+lp7Hrwv/NR9CbzevBM7YXqNuZz4ineR9m305TPlM+Uz7HRptWb3DbmevDi+fQCrwuDFD4cZSN/KEksSSxJLFoquSYGJWUjZSMGJX8oSSxsMO40VzdXN1c37jRsMFoqZSP9GrQSnAqbAgn8R/dk9db2Mvqh/okD5QciC3oN0A6GDyEOIgvIBmQAOPmG8mnsXOcD5QPlNuZc54PpTO0w8WT14vmO/Qr/Zf6R+7P3JvP07kztaez07ibzG/hC/GP/DgF9AV8BiQCh/lH71vbf8Wnsdug25jbmNuaD6Uztu++G8ibzhvIw8bvvTO2D6TbmFeGb3IHXt9Ox0bHRt9NH2affg+km82X9IwcMEcoZZSNaKmwwoTKhMmwwSSy5JmUjWSDXIQYlfyhPLqEy7jRXN1c37jShMmwwWirXIcoZhg+CBQn8UfR68HrwhvJg9sj6Iv9VAyMHnAp6DSEOeg0bCjgFvf7W9vTudugD5cLjwuMD5Vzng+kl7obyG/hl/Q4BcgJfAUX+4vlR9LvvTO1M7XrwZPUy+tz9QgB9ASQCcgJKApsBiv9C/H74UfR68GnsheqF6n3rJe568N/x3/Hf8Xrw9O5M7YXqXOfC46ff+tqm1bfTsdG304HXKd425rvvOPn3A9AOyhllI1oqTy5sMGwwTy5/KAYl1yFZINchBiV/KEksTy5sMKEyoTKhMmwwSSx/KFkgpBjQDjIEyPq/83rwu+8w8b/z1vbI+r3+mwLOBU0IuQiCB/IEIwCP+Ybyfes25nPip98p3inep99z4lznTO0m8374kfur/FH7G/i/87vvTO1p7CXu3/Hl9d34Dvt3/GX9Zf6c/yMAzv+9/t384vnl9Ybyu+/07rvv3/G/8970ZPXe9Cbz3/F68CXufeuD6TbmFeGb3IHXptW306bV+toV4XboMPEO+zgFhg/KGdchfyhJLE8uTy5JLH8oBiXXIWUjBiV/KFoqTy5PLmwwbDBsMGwwTy5JLLkmWSCKF9oMxwIy+t703/Hf8b/zYPaP+Qz9DgHyBE0InAoiC5wKggfHAnf8ZPX07oPpNubC43PiwuMD5YPpJe5R9Dj5q/xl/gD+zvt++N703/Ew8d/xUfSz93763fyD/t3/XwGbAlUDVQPHAl8Bg/7I+mD2hvJ68LvvevCG8r/zUfS/84by3/F68PTuTO2F6lznc+Ip3oHXt9OUz5TPsdGB16ffXOd68A77HgYMEf0aZSN/KEksSSxaKrkmZSPXIdchZSO5JloqSSxPLmwwoTLuNO407jTuNGwwWirXIYoX2gz0AlH7YPZR9FH0ZPWz98j68v5VA4IHnAraDHoN2gy5CPQCkfu/82nsXOfC43Pic+LC43boTO0m8934Of3s/94AFAC2/TL61vZR9IbyJvPe9GD2fvgy+nf8Zf4yAJsBSgJKAn0Biv8J/Ef3hvIl7n3rhep962nsaexp7GnsTO1M7UztTO1p7IXqXOfC4ynegde305TPlM+x0YHXKd425nrwkfvIBtsR/RrXIX8oWipaKloquSZlI9ch1yHXIWUjBiW5Jn8oSSxPLmwwoTKhMqEyTy65JuseexUiC5sCCfyz9970v/O/8+X1OPmO/QACcQacCnoN0A7aDLkIxwIO+ybzaexc53PiFeEV4XPiNuaF6vTuv/NH94/5fvoy+t341vZR9Iby3/Hf8Ybyv/Nk9db23fjI+nf8AP5j/1MAZAAi/938j/nl9YbyMPG77/Tu9O707iXuJe4l7iXuTO1M7X3rdugD5RXh+tqm1bHRlM+Uz7HRgdeb3APl9O44+fQCQQyDFP0aWSBlI2UjZSPXIese6x7rHlkg1yFlIwYluSZ/KEksTy5PLk8uSSx/KNchyhkMEU0IiQB++uX1JvPf8SbzZPU4+Y793QHOBSoJIgtBDJwKHgYGAN343/Fp7HboA+XC4wPlduhp7Hrw3vTd+M77tv0K//L+jv0O+934R/fW9tb2s/fd+H76d/yD/mQAcgIyBIIFHgbOBW8EmwG2/eL51vZk9VH0v/Mm87/zUfRk9WD2R/dH99b2ZPWG8iXudugV4Zvcgdem1YHXR9mn3zbmJe4b+AACrwuDFD4cZSN/KFoqfyi5JgYl1yHXIVkgWSDXIWUjuSZ/KEksbDChMqEyoTKhMk8uuSbrHoMUrwtVA938G/hk9eX1s/dR+93/rwSgCXoNDBG0ErQShg+gCXICyPom82nsXOfC48LjA+Vc533ru++/87P3Ufu2/b3+AP7O+934YPZR9CbzhvIm87/zZPWz9+L5d/y9/igBVQOvBG8EcgI4/1H7s/dR9DDxu+8l7iXuu+8w8Sbz3vTl9WD25fW/83rwfesD5affR9mm1bfTt9Om1fraFeGD6Sbztv3lBwwRyhlZIGUjuSa5JgYl1yFZIOsejR2NHY0d6x7XIQYlfyhaKk8ubDBsME8uWiplI/0a2xFNCDj/G/gm83rwevDf8d703fg5/X0BggUqCa8LrwugCTgFY/8b+DDxheoD5XPiFeFz4gPlduhp7Hrw3vQ4+Xf8AP7c/d38Dvvd+GD2UfQm84byhvIm89701vbd+FH73P12AEoCcgIOAUX+yPrW9ibzevD07iXu9O6779/xJvNR9FH0v/OG8nrwTO2D6QPlFeGb3EfZgdeB10fZKd4D5SXuR/feABsK2xHKGeseZSMGJQYlBiVlI9chWSDrHo0djR3rHtchZSO5Jn8oSSxPLkksWiq5JusefRbaDL4Dzvvl9d/xMPHf8d70G/jO+2P/VQOCByIL2gzaDJwKHgbs/374MPGF6jbmwuPC4wPlXOeF6iXu3/Hl9Y/5Cfw5/Tn9Qvx++hv45fW/84byhvIm82T1s/fi+av8zv/0AjgFzgWvBLsBAP6P+eX1hvJ68LvvevDf8b/z5fVH97P3fvgb+Nb23vQw8WnsXOdz4pvcR9mB14HX+toV4YPphvJC/B4Ghg+KF+seBiV/KFoqWipaKn8oBiXXIVkg6x5ZINchZSO5JloqTy5sMKEyoTJsMH8oWSB9FkEMcgIy+lH0MPF68DDxJvNk9X743fwAAsgGnAraDNoMoAn3A0L8UfRp7Dbmc+IV4RXhc+I25oXq9O5R9Dj5DP2t/ygBfQEyALb9MvrW9r/zMPF68DDxJvPl9Y/53P0kAoIFggeCBx4G9ALy/sj6YPYm83rwu++77zDxhvK/82T1YPaz9xv4s/fl9Sbz9O6D6QPlp9/62kfZR9n62hXhdugw8TL69wN6DXsVjR1lI7kmWipaKn8ouSZlI1kgjR39Gv0aPhzrHtchuSZaKk8ubDBPLloqBiWNHYMUIgubAlH75fWG8nrwu+968N/x5fUO+ygBIwevC9AO0A6vC3EGOP9H97vvheo25sLjc+LC4zbmg+n07lH0OPnc/ZsB9wOvBIkD3gA5/Tj55fVR9L/z3vTW9jj5q/x2APcDcQaCB8gGOAVKAgr/kfuz9970hvIw8TDxMPHf8YbyhvIm8ybzJvPf8XrwTO2D6cLjKd5H2abVt9O304HXKd4D5UztZPUA/nEG0A57FT4cWSBlIwYlZSPXIY0d/RrKGaQYyhn9Guse1yG5JloqWipaKn8oBiXrHooX0A5xBmX+s/eG8vTuTO1962ns9O4m8zj5Iv9vBE0IoAkqCc4FZACP+Ybyaexc58Ljc+Jz4sLjNuaF6rvv5fUO+zj/SgK+A4kDXwGO/Tj5ZPUm84byJvPe9Bv4kftj//QCzgWCB00IIwc4BZsC2P7I+tb2v/Pf8TDx3/GG8ibz3vTl9db2s/ez90f33vTf8WnsXOcV4fragdeB10fZm9xz4oPpMPHi+fQCQQyDFD4c1yG5Jn8ouSZlI1kgPhzKGaQYpBjKGT4cWSAGJVoqSSxPLk8uSSx/KNch/Rq0EqAJAAKR+2D23/G77yXuu+8m8xv4Rf6vBKAJ2gwhDkEMTQjdATL6hvJ96zbmc+IV4RXhc+I25n3rMPGz92X9AALyBM4FbwRDAQz93fjl9VH0v/Pe9Ef3fvrc/V8BbwTIBk0IuQjlBx4GVQO+/877G/hk9b/zhvKG8obyv/Pe9GD2s/d++N34s/dk9d/xTO1c53PiKd762kfZ+top3nPiduh68I/5iQN6DX0WjR1lI7kmfyi5JgYl1yHrHj4c/RrKGT4cjR3XIbkmWipPLk8uTy5JLH8o1yH9GpcTIguJA3f8YPbf8fTuJe568FH0fvreAMgGrwvQDkUQIQ4bCvcD3fzl9fTug+kD5XPic+ID5YPpu+/l9ZH7dgBvBMgGyAavBCgBDP04+WD23vTe9OX1s/d++o793gC+Ax4GggdNCOUHcQZVA87/Cfzd+GD23vS/8ybzv/NR9OX1R/d++Dj5OPl++Nb2JvMl7lznFeGb3EfZgddH2ZvcFeF26Hrwj/n0Aq8LlxPKGeseWSDXIesePhzKGX0WlxO0ErQSgxSkGD4c1yEGJX8ofyh/KLkm1yE+HH0WIQ5xBoP+1vZ68Gnshep96/Tuv/My+sgAIwdBDIYPRRAhDioJAALi+d/xheoD5RXhp98V4Tbmfesw8Uf33fx9Aa8EzgXyBAAC3P2P+eX1JvOG8obyUfTW9jL6tv0oATIEIwcqCaAJTQjOBSQC3P3i+db2UfSG8t/xMPEw8d/xJvPe9GD2G/jd+Bv4ZPV68IXqwuOb3IHXt9O307fTgdcp3gPlTO1H97IAGwrbEaQYjR3rHusePhzKGX0WlxMMEUUQDBG0En0W/RrrHmUjuSa5JrkmBiXXIT4cgxTaDPcDkfu/8yXug+l26IPpTO2G8o/5DgHlB3oNRRBFENoMIwci/2D2Je5c53Pip9+n3xXhNuZ96zDxs/eO/XICzgXIBs4FxwK9/n761vZR9L/zv/Pe9LP3yPoj/rsBOAXlBxsKnAqgCSMHvgNkAAz9Mvob+GD23vRR9L/z3vRg9n74Dvtl/b3+I/4O++X1u+926HPiKd762vram9yn3wPlaeze9Nz9IwdFEIoXjR3XIWUjZSPXIese/RqkGHsVgxSDFH0WyhnrHtchBiV/KFoqWip/KGUj6x6KF4YPyAYj/uX19O6F6nbog+kl7r/zkfuJA5wKhg8MEUUQQQyCBY79ZPUl7lznwuNz4nPiA+WD6SXuv/OP+SL/iQMeBsgGggX0Apz/d/yP+Rv4R/cb+I/5kfsj/t4AvgPIBioJnAqcCioJIwevBEoC+v+O/cj6G/hg9t703vRk9Uf3j/kJ/Nz9Rf7d/I/5UfQl7lznc+Ip3pvc+top3hXhNuZM7d70jv1xBtAOfRY+HFkg1yHXIVkgjR3KGYoXexWDFH0WpBj9Guse1yFlIwYluSa5JgYl1yGNHX0WIQ6vBFH7JvNM7YPpduh967vvYPbc/TgFIgvQDoYPeg25CEoCyPom82nsXOfC48LjA+Vc533revDl9ZH7UwD3A84FHgavBCQCIv9C/OL5fvh++I/5Dvs5/WP/uwEyBHEGTQgqCSoJ5QceBjIEuwG9/lH7G/hk9SbzhvK/82T1G/gO+2X9vf5F/pH7R/cw8X3rA+Wn35vcR9lH2frap98D5X3rJvPO+68Eeg2DFP0ajR3rHusePhykGIMU2xFFEAwRtBJ7FYoX/RqNHVkgZSO5JrkmuSZlI40dexWvCw4BR/f07oPpXOdc54Xqu+/W9oP+HgavC9AOIQ6vC3EGrf8b+Hrwheo25sLjc+LC4zbmheq77+X1Cfx9ATgFyAbIBjgFmwLO/2X9kfsO+w77UfvO+6v8I/5kACMDHgZNCKAJoAm5CCMHbwRDAWX93fje9N/xu+/07vTuMPG/80f3j/l++t345fUw8WnsNuYV4ZvcR9mB10fZ+top3nPig+nf8ZH7ggUhDnsV/RqNHY0djR39GooXexWXE7QS2xG0EoMUihfKGY0d1yEGJX8ofyi5JmUjPhyXE6AJTv/l9fTug+lc53boaezf8Tj59gCCB0EMeg1BDCoJ9wOO/db2evB961znA+XC4wPlXOdp7N/xG/jc/SQCrwSCBfIEiQNDAWP/3P3d/EL8zvvO+wn8DP0K/90BOAVNCBsKIgsiCxsK5Qc4BbsB3P3i+WD2v/OG8obyUfRH9zL63fwj/rb9Ufuz9ybzJe526MLjp9+b3Pra+tqb3BXhNuYl7tb2UwCgCQwRihc+HI0d6x6NHf0apBh9FoMUlxOXE4MUfRbKGY0d1yEGJX8oWipaKn8oZSP9GtsRIwcM/VH0Je6F6oPpaeww8bP3of44BRsK2gzaDCILggdyAgn8ZPX07oPpNubC4wPlNuaF6vTuUfTi+YP+3QH3A/IE8gQyBMcCDgFO/wD+Of3d/Az9AP6t/yQCOAVNCCIL2gwhDiEO2gycCiMHmwLc/Y/5YPbe9FH05fUb+Mj6jv2K/zIAY/85/Y/53vS774XqA+Wn35vc+tr62ineFeFc5yXuR/fIAKAJDBGKF/0ajR2NHf0apBh7FbQSDBGGD4YPRRC0En0W/RpZIGUjfyhaKn8ouSZZIH0WQQybAbP3u++F6lznXOeF6rvv5fUM/SMD5QecCq8LGwpxBigByPq/8yXug+k25gPlA+Vc54Xq9O6/83743fydACMDrwQ4BW8E9ALeANj+DP0J/JH7kft3/GX+QwGvBOUHnAraDHoNeg1BDKAJzgW7AY79Mvqz9+X15fXW9t34Dvtl/fL+Y/+D/kL83fhR9PTug+nC46ffm9z62vram9yn3wPlaexk9WX+IwfQDoMUihfKGaQYfRaXE0UQeg0iC6AJKgmcCnoNDBF9Fj4cWSBlIwYlZSPrHqQYRRDIBo79ZPX07oXqduiD6UztJvPi+bIAyAYiC9oM2gwbCs4FnQDI+t70u+9963boXOdc54Ppaex68GT1Mvpl/rsBMgTOBR4G8gSJA5sBrf8A/qv8Cfx3/Nz9QgBVA3EGoAmvC9oMeg3aDCILuQjyBCgBZf0y+rP31vZH9zj5zvuD/rIAuwFfAa3/3fzd+FH09O6D6QPlFeEp3pvc+top3hXhXOf07rP3nQC5CIYPlxN9FooXihd7FdsR0A5BDBsKKgkbCtoMDBF7Ff0aWSAGJbkmuSYGJVkgpBhFECMHZf3e9CXuheqD6X3ru+/l9Xf8cgIjBxsKrwsiCyoJggWyAA77ZPV68H3rg+l26IPpfeu777/zfvjd/N4AMgTIBuUH5QfIBvIEmwJ2AKH+tv22/b3+nQAjA84FTQicCkEMeg0hDnoNrwu5CK8EdgB3/Dj5R/fW9rP3j/nO+wD+d/+t/73+3fwy+tb2JvP07oPpA+Wn35vc+tpH2frap99c5/TuG/j2ALkIhg+XE30Wihd7FbQShg9BDCoJggcjB7kIrwuGD4MUpBiNHVkgZSNlI1kgPhyDFCILmwF++Hrwfet26Hboher07lH0j/ll/nICOAXIBsgG8gQAArb9fvgm8yXuhep26FznduiF6iXuJvOz90L89gDyBIIHTQhNCCMHOAWJAyQCKAHIAA4BAAKJA4IF5QcbCq8Leg2GD4YP0A56DZwKyAYjA77/Of0J/EL83P36/yQCvgMyBPcDIwN9AU7/d/zd+N70evB96zbmc+Kn36ffc+Jc5yXuYPZO/4IH0A6DFIoXpBikGH0WlxMMEXoNIgsqCSoJGwraDAwRexXKGY0dWSDXIVkgPhx9FtAOggVC/FH0Je6D6Xboduh967vvUfQ4+WX9DgGJA68EMgRKAiL/yPrl9TDxaex26DbmNuZ26H3ru+9R9Dj5jv0oAYkD8gTyBDIExwJfARQAIv+h/r3+iv/2ACMDggW5CK8L0A5FEAwRDBHQDkEMuQjyBJsBof6r/EL8DP3y/igB9AIyBK8ErwS+AwACzv+r/N34v/Ml7nboc+Ip3pvcm9wV4Vznu++P+ZsCnApFEIMUfRaKF30WgxQMESEOnApNCIIHuQgiC4YPgxTKGese1yEGJQYlZSONHYoX0A44BUL8UfQl7oPpduiD6WnsevBk9Y/5jv2yAPQCMgT3AyQCvf7i+VH09O6F6lznNuY25nboaex68GT1fvqh/t0BvgOvBK8EMgQjA5sBBgCD/o79jv2D/nYA9ALOBbkIrwshDoYPhg8hDtoMoAkeBiQCI/7I+t34fviP+Q77Qvxl/SP+of7y/vL+Rf7d/DL65fW774Ppc+Kb3EfZR9n62hXhdugw8TL6mwKgCdAOtBJ7FX0WexWXEwwReg0bCuUHggcqCUEMRRCDFMoZjR1ZINch1yHrHv0alxOvC/QCyPq/8/TufeuF6n3rTO168FH0fvh3/EIA9AJvBDIEJAKD/jj5JvNM7YPpNuY25jbmg+lp7Hrw3vSP+QD+uwGvBHEGIwfIBh4GbwT0ApsBDgFDAUoC9wMeBrkIrwshDkUQ2xHbEQwRhg9BDLkIrwQOAWX+3fxC/Hf8q/zd/Dn9tv2D/k7/rf84/zn9j/lR9CXuXOcV4ZvcR9lH2Zvcc+KD6d/x4vm7AbkIIQ7bEYMUgxSXE9sRIQ4iC7kIggflBxsK2gwMEXsVyhmNHVkg1yHXIY0dpBjbERsKAAIy+r/zu+9p7H3raewl7jDxZPWP+dz9fQGJA/cDcgJ3/w775fV68H3rdug25jbmduiF6iXuhvLW9lH7iv/HAjgFcQbIBnEGggWvBIkD9AJVAzIEzgXlB5wKeg1FELQSlxODFIMUlxMMESEOGwoeBpsCFACh/iP+Rf7y/t3/3gAkAlUD9wOJA7sBZf6P+SbzaewD5aff+tr62vrap98D5Wns3vSr/PcDGwrQDtsRtBK0EtsRhg9BDCoJIwdxBiMHKgnaDAwRexX9Guse1yHXIVkgjR2KFwwRoAmbATL6v/P07n3rheqF6kztMPFg9lH7iv9yAr4DvgPdAYP+4vne9PTuhepc5wPlA+U25oPpTO2G8tb2Ufu9/kMBIwMyBK8EMgQjA90B9gBTADIA3gAkAvcDHga5CCILeg3QDkUQRRBFECEOrwvlBzIEyAAj/nf8zvvO+3f8jv0K/7IAAAKbAnICnQAM/Rv4MPGF6sLjKd5H2UfZ+tqn3wPlaey/81H7AALlB0EM0A5FEEUQ0A5BDKAJIwfOBc4FIwcbCnoN2xF9FsoZjR1ZIFkg6x4+HKQY2xGcCscCDvve9LvvTO1p7CXuevDe9OL5Zf5KAjgFyAYjB4IFSgJl/bP33/Fp7HboNuZc53bofev07obyYPYy+gz9vv+7AfQCVQMjA5sCuwEOAcgAQwEkAlUD8gQjB6AJQQzQDgwRtBKXE7QSRRB6DSoJggVKAhQACv/y/k7/+v/2ACQCiQOvBPIE9wMoAav8YPa773boc+Kb3Pra+tqb3BXhXOf07mD2jv2+A7kIQQzQDkUQhg8hDkEMoAnlByMHIwdNCJwKeg0MEXsVyhmNHeseWSDrHv0aexXQDoIH3f84+b/zu+8l7iXuu++G8mD2yPrY/iQCrwSCBfIExwIK/zL63vS7733rduhc51zng+lp7Lvvv/PW9uL5q/zy/sgAAALHAvQCxwJyAgACmwFfAX0BSgL3A3EGoAnaDIYP2xG0ErQSDBHQDiILIwf3A5sBFABj/07/zv/2AHICMgTOBcgGyAavBMgAUftR9EztNuan35vc+tr62inewuOF6t/x3fg4/28EuQhBDCEO0A6GD9AO2gyvC6AJTQjlB7kInAohDrQSihc+HOseWSDrHj4cpBi0Eq8LbwTd/GD2evBM7YXqfetM7Xrw3vQ4+Qz9MgByAlUD9ALIAAz9G/iG8kztg+lc51znXOeF6kztu+8m8+X13fiR+wD+MgAkAokDMgT3A/QCmwEjADj/Y/8OAfcDggciC9AO2xGXE5cTtBIMESEOIguCB68EcgIOAXYAsgDdAYkDzgXlB6AJnAqgCSMH9AJl/db2u++D6cLjFeGn36ffwuOD6bvvYPZ3/JsBzgUqCUEM0A4MEdsR2xFFECEOQQwbCqAJnAp6DQwRexXKGY0d6x5ZIOsePhykGJcTeg0eBtj+G/gm87vvJe6779/xZPU4+av8BgDHAq8EggWvBCQCAP7d+L/z9O5964Ppg+mF6mnsJe6779/xv/Pl9d34CfwK/18BxwL0AkoC3gAK/9z9jv29/vYA9wMjBxsK2gzQDoYPhg8hDkEMoAlxBr4DmwHd//L+2P53/8gAxwLyBMgG5QeCB84FmwIA/n743/F96zbmc+Kn36ffc+I25oXqevBk9eL5I/4kAh4GGwp6DYYPhg/QDnoNIgu5CIIHTQgbCnoN2xF7FaQYPhyNHY0djR39Gn0WRRAbCiMDQvxg9t/xu+/07nrwJvNg9o/53fzO/0oCMgRvBJsCd/9R+9b2JvO77yXuTO1M7SXuu+8w8Yby3vRH9zL6Zf1kAPQCrwQ4BfIEiQMAAp0AFADIAMcCzgUqCdoMRRDbEZcTlxO0EgwRIQ4iC+UH8gSbAvYABgAGACgB9ALyBCMHuQgqCU0IggXIAMj6UfQl7nbowuOn3ynep98V4QPlg+kl7ibzG/jd/EMBOAW5CCILQQxBDJwK5QeCBYkD9AIyBMgGnArQDrQSfRbKGT4cPhz9GqQYlxN6DSMH+v84+b/zu+9M7Uzt9O7f8WT1OPnd/M7/mwEkAigBCv/O+7P3v/N68EztfeuF6oXqhep960ztu+/f8WT1OPmr/Ir/uwH0AvQC3QFCAIP+Of0M/SP+nQD3A+UHrwvQDgwR2xHbEQwR0A7aDJwK5QfyBMcCXwHeAH0BIwOCBU0InAqvC68LoAnOBUMBCfxg9jDxaex26DbmA+U25nbofeu771H0OPmO/UoCyAYiC9AODBHbEQwRhg/aDJwKKgm5CBsK2gxFEIMUpBj9Go0d6x7rHo0dyhl7FdAOggcjAI/5UfQw8bvvevCG8mT1s/d++t388v5kAPYAZAC9/gn8fvje9N/x9O5M7Wnsaexp7Ezt9O568Cbz5fXd+JH73P1j/+z/Tv/c/UL8yPp++lH73P0oAfIETQgiC3oN0A7QDtAOIQ7aDJwKggevBCQCdgDO/4kAcgKvBCMHuQgbChsKuQhxBscCRf6P+VH0u+9961znA+XC4wPlXOeF6iXuhvJg9sj6OP++A+UHIgvaDHoNQQygCSMHggXyBM4FTQgiC9AO2xF7FaQYPhyNHY0d/Rp9FgwRnAqJA938R/cm8zDxevAw8YbyUfRg9n74DvsM/WX+2P5F/nf8j/nl9Yby9O5p7H3rheqF6n3rfetM7bvvJvPW9n76tv0UACgB9gAGAIP+DP1C/Hf83P1CAFUDyAagCUEMIQ6GD4YP0A56DSILuQjOBSMDDgEUADIAKAGbAjIEzgUjB+UHggfOBfQCY/8O+2D2MPFp7HboA+Vz4nPiwuMD5Xbofeu779704vlO/28EuQivC9oM2gwiC7kIcQbyBK8EzgXlB5wKIQ7bEX0Wyhk+HI0dPhzKGYMU0A65CCQCd/wb+N70JvPf8YbyJvNk9bP3yPq2/WQAcgL0AkoCMgA5/eL51va/89/xu+/07iXuJe707jDxUfSz91H7of4OAZsCIwPHAn0B+v+h/iP+2P7IAIkDyAYbCnoNhg8MEdsR2xFFENAO2gycCuUHHgavBDIEbwQ4BR4Ggge5CKAJGwobCrkIHgabAmX+4vne9Hrwaex26DbmNuY25nbohepM7TDx5fXI+gYA8gQqCa8Leg3aDCILKgmCB3EGyAblB5wKeg3bEXsVpBg+HI0djR0+HKQYgxTQDqAJMgQ4/w77s/dk9VH0UfRk9db2OPkJ/Nj+3gAAAkoCXwF3/6v8j/lg9r/z3/F68PTuJe4l7vTuevAm8+X1OPkJ/GX+vv/O/9j+Zf0J/FH7kfsM/Xf/cgLOBbkIIgtBDNoMQQyvC5wKKgnlBx4GrwQjA0oCJAJKAscCvgPyBM4FHgYeBjgFVQN2AAz93fhR9Lvvfetc5wPlwuPC4wPlXOeD6UztMPFk9X76iv/3AyMHKgkqCeUHggVVA90BfQFyAm8EIwecCiEODBGDFH0Wihd9FnsVtBKGD5wKggUyAFH7R/dR9N/xMPEw8Yby3vRH9376Of13/50AQgCD/pH7fvhk9SbzMPG77yXuTO1M7SXu9O4w8VH0R/d++t38Zf69/gD+d/wO+zL6fvpC/Ar/cgIeBrkIIgtBDHoNeg16DXoN2gyvC5wKKgnlByMHcQZxBsgGgge5CBsKIgtBDK8LIgu5CDgF3gAJ/Ef3hvIl7oXqdug25jbmXOd26IXqJe6G8hv4Of1KAnEGKgkbCioJIwfyBFUDcgKbAvcDHgYqCUEMhg+0EnsVihekGKQYiheDFAwRQQwjB7sBq/x++N70JvPf8YbyUfRH9zL6Zf3s/30B3QEOAWP/DP0y+rP3ZPUm89/xevC777vvevDf8d70fvjO+6H+iQAoAd4A7P/y/kX+Rf5j/18B9wPIBioJIgvaDHoNIQ4hDiEOIQ4hDnoN2gxBDCILGwqgCSoJoAmcCq8L2gx6DXoN2gycCoIHvgOt/5H7R/cm8/TufeuD6VznNuY25lznheol7ibzG/gM/UMBbwRxBiMHcQY4Bb4DxwJyAiMDbwTIBqAJQQyGD9sRlxN7FXsVgxSXEwwReg0qCW8EY//I+kf3UfQm8ybzUfTl9X74yPp3/AD+2P69/tz9Qvwy+hv45fVR9IbyevD07iXu9O568N/xUfTW9jj5yPoJ/EL8QvxC/Hf8Of29/vYAvgPIBqAJQQwhDtAO0A7QDiEOIQ4hDiEOIQ56DUEMrwsiCyILIguvC3oN0A5FEAwRRRDQDkEMoAkeBpsCvf7I+mD2hvIl7n3rg+mD6YXqaex68FH0G/h3/IkA9wNxBoIHggceBm8E9AIkAkoCiQPOBU0IrwshDgwRtBKDFHsVexWDFLQShg+cCoIF+v/I+mD2JvMw8XrwMPEm8970YPZ++H76zvur/EL8Dvs4+WD2v/Mw8fTuTO1p7H3rfetp7CXuevAm8+X1G/iP+X76fvoy+uL5fvpR+479MgBVA3EGKgkiC0EM2gx6DSEO0A7QDtAOIQ56Da8LGwq5CE0ITQgqCZwKQQwhDtAO0A4hDkEMGwojB/cDQgBC/LP3JvP07n3rg+lc53bog+l96/TuhvJH95H7iv/HAvIEzgXOBfIEvgPHAnIC9AIyBB4GuQgiC3oNRRC0EoMUfRaKF30WlxNFECILOAV3/zL65fUm8zDxevAw8d/xv/Pl9X74fvrO+wn8Ufvi+bP3ZPUm8zDx9O4l7mnsaexp7EztJe568Ibyv/Nk9WD2R/ez9374OPl++qv8Iv8AAq8EIwe5CBsKIgtBDNoMeg0hDtAOhg+GD9AOeg1BDCILnAobChsKnAqvC0EM2gzaDK8LnApNCM4F9AKK/5H7R/e/87vvaeyF6oPpg+l960ztevC/80f3Dvuh/rsB9wM4BYIFOAWvBG8EbwTyBM4FIwcqCSILeg1FELQSgxR7FXsVgxTbESEOKgkyBPL+4vnl9YbyMPF68DDxhvLe9Nb23fgy+n76Mvrd+Ef3ZPW/84byMPG77/TuJe4l7vTuu+8w8YbyUfRk9WD2R/cb+N344vnO+wD+iQAjA84FTQicCtoMeg3QDtAOhg+GD4YPhg+GD4YP0A7QDnoN2gzaDHoNIQ6GDwwR2xHbEdsRRRAhDq8LTQhvBIkAd/x++N70MPH07kztTO0l7rvvhvJk9X74zvsK/90B9wOCBR4GzgU4BTIEiQOJAzIEzgXlB5wKeg2GD9sRlxN7FXsVexWXE0UQ2gxNCCMD3P04+eX1v/Mm81H05fWz9+L5kfur/Az9d/xR++L5fvjW9mT1v/OG8t/xMPEw8TDx3/GG8r/z3vTl9WD2YPbW9rP3fviP+X76CfwA/p0AiQMeBrkInAqvC0EMQQzaDNoMeg0hDiEOeg1BDCILoAm5CE0IKgmcCkEMeg3QDtAOIQ5BDKAJcQb0AvL+yPpg9t/xTO2D6VznNuY25lznduiF6kztMPFR9Bv4kftF/vr/iQAyACL/I/62/SP+OP8oAYkDcQagCUEM0A7bEZcTlxOXE9sR0A4iCx4GnQBR+9b2v/OG8obyv/Pl9bP3j/l++g77Dvt++uL53fiz99b25fXe9L/zhvLf8TDxMPEw8TDx3/GG8r/zUfTe9OX11vaz94/5Uftl/d3/JAJvBHEGggdNCLkIuQgqCRsKIgtBDNoMeg3aDCILGwq5COUHTQgqCZwKQQx6DSEOIQ7aDCILuQjOBZsCIv+R+7P3UfR68CXufeuF6oXqfetp7CXuMPHe9H74kfsj/gYADgFfAQ4BsgCJAN4AuwFVAzgFIwegCUEM0A4MEZcTgxR7FXsVlxMMEdoMTQhVAwr/zvsy+uL5fvrO+2X9g/44/07/8v4j/mX9d/zO+w77fvri+d34s/dg9mT13vTe9GT15fVg9tb21vbW9kf3G/g4+cj6DP1O/90BbwTIBrkIGwoiC68LQQzaDCEO0A6GD0UQRRBFENAOeg3aDEEMQQx6DdAORRDbEbQStBK0EgwRIQ4iC00I8gRfAQD+yPpH91H0MPH07iXuTO0l7nrwhvLl9d34zvtF/lMAmwEkAgACuwGbAbsBJAIjA28EHgZNCJwKeg1FELQSgxR7FXsVgxQMEXoNuQiJA73+yPp++Ef3s/fd+OL5DvtR+1H7yPoy+jj53fh++Bv4s/fW9uX13vS/8ybzhvKG8obyhvIm8ybzJvMm8ybzv/Pe9GD2G/ji+UL8g/6dAJsC9wM4BR4GyAaCB7kIoAkiC0EM2gxBDCILoAlNCCMHyAaCB7kInApBDHoNIQ56DdoMIgsqCcgGbwSbAYP+Ufuz91H0MPEl7kztaexp7Eztu+/f8d70G/gO+479Tv9CAHYAMgC+/2P/Y/++/4kAmwEjAzgF5QecCnoNRRDbEbQS2xGGD9oM5Qf0AgD+4vlH9+X15fXl9WD21vZH99b2YPbl9eX1YPZg9tb2R/fW9mD2ZPVR9L/zhvLf8TDxevB68Lvvu++773rwevDf8Sbz3vTW9jj5Ufu2/ez/mwH0AvcD8gTOBcgGTQgbCq8LQQyvC5wKuQgjBx4GHgYjB7kInApBDHoNeg16DUEMIgsbCuUHHgb3A18Bg/5R+xv43vSG8nrw9O4l7iXu9O568IbyZPV++FH73P13/zIAUwAGAJz/iv/6/8gAAAKJA84FuQivC4YPtBKDFH0WfRaDFNsRIQ4bCoIFuwEi/7b9Of05/Y79jv1l/av8zvvI+jL64vni+Y/5j/k4+X74G/iz90f31vZg9uX13vRR9CbzhvKG8obyhvIm81H05fVH94/5zvtF/p0AxwJvBB4Ggge5CBsKrwvaDCEOIQ4hDkEMnAq5CIIHggdNCKAJrwt6DdAORRBFEEUQhg8hDtoMIgu5CIIFJAKD/g77s/dk9SbzMPF68HrwevDf8b/zYPY4+c77AP6K/2QAiQAyAM7/iv+K/93/yAByAvIE5QciC9AO2xGDFH0WfRZ7FbQShg8iC8gGxwKK/zn9zvuR+5H7zvsJ/JH7Dvsy+o/53fjd+N343fjd+N34fviz90f31vbl9WT1UfS/8ybzJvOG8obyhvKG8r/z3vRg9hv44vnO+479d/9fAVUDOAUjByoJIgvaDCEO0A7QDiEO2gyvC5wKGwobCiILQQx6DdAOhg9FEEUQhg/QDnoNrwsqCcgGvgOdAGX94vlg9ibzevAl7mnsaexp7Eztu++G8mT1G/jI+qv8jv3c/bb9Of3d/N38Zf2D/kIAmwKCBSoJQQyGD9sRlxOXE7QSRRB6DaAJHgbHAjIAZf5l/Qz93fyr/M77yPqP+X74G/gb+Bv43fjd+Dj53fjd+H74G/hH92D2ZPVR9L/zhvKG8obyhvIm87/z3vTl9Uf33fjI+qv8vf7IAMcC8gTIBk0IGwqvC9oMIQ4hDnoN2gwiCxsKKgm5CCoJGwqvC9oMeg0hDiEOIQ56DUEMIgsqCSMHrwS7Ab3+kft++GT1hvK77yXuaexp7Ezt9O4w8VH0s/cy+kL8Of1l/Qz9d/xC/EL83fwA/t3/SgLyBE0IrwshDgwRtBKXE5cT2xHQDq8L5QevBN0B+v8K/73+Zf4A/jn9zvsy+t34fvgb+H743fiP+TL6yPrI+sj6fvri+Tj5G/jW9uX13vRR9FH0UfTe9N70ZPXl9db2s/fd+H76q/zy/kMBVQPyBMgGTQigCSIL2gx6DXoN2gwiC6AJ5QcjByMH5Qe5CBsKnAqvC68LQQxBDK8LnAqgCeUHzgUjA3YAjv1++tb2JvO770ztheqF6oXqaez07t/xZPV++H76zvtC/EL8zvtR+1H7zvvd/GX+MgCbAoIFuQivC9AO2xG0EpcT2xFFENoMoAkeBlUDXwEGADj/vf4j/mX9d/wO+4/53fgb+H74OPni+X76DvsO+w77fvri+d34s/fW9uX13vTe9N703vTe9N703vTe9GT15fWz94/5zvu2/Yr/KAHHAm8EHgblBxsKrwvaDHoNeg3aDCILGwoqCSoJoAmcCq8LQQzaDNoM2gzaDEEMrwucCqAJ5QceBr4DKAFF/g77s/dR9HrwJe5p7H3raewl7jDxv/PW9jj5fvpR+5H7kfuR+877d/wM/QD+OP8OAVUDHgYqCUEMhg8MEbQStBIMEYYP2gwbCuUHzgVvBIkDmwK7AZ0A8v4M/VH74vmP+Y/5MvoO+wn8q/wM/Qz9d/yR+zL63fgb+Ef3YPbl9WT13vTe9FH0v/O/87/zUfTl9bP34vkJ/CP++v+7AYkDggUjByoJIgtBDNoMQQwiC6AJTQiCByMHIwflByoJoAmcCiILIgsiCyILnAobCioJ5QceBvcDfQGh/lH7R/e/87vvTO1964XqfetM7fTu3/G/8+X1R/cb+N343fg4+Y/5MvoO+0L83P0GAJsCggW5CEEM0A7bEbQStBLbEUUQIQ6vC6AJTQgjB3EGzgU4BTIExwLeAPL+Of0J/M77Cfzd/I79I/5F/gD+Zf2r/An8kfsO+zL6j/nd+Bv4R/dg9mT13vS/87/zv/NR9GT1R/c4+Q77Of04/ygBVQOCBeUHGwqvC0EMQQyvCxsKTQjIBs4FzgUeBiMHTQgqCaAJGwoiCyILrwtBDEEMrwucCioJcQZVA5z/kfuz97/zMPH07kztTO307nrwJvNk9Uf33fji+X76fvp++n76fvrI+pH7d/wA/gYAmwKCBbkIQQzQDgwR2xEMEUUQIQ5BDBsKuQgjBx4G8gS+AyQCUwBF/kL8yPqP+Y/54vnI+pH7CfxC/EL8CfyR+8j6MvqP+d34fviz90f3YPbl9d70v/Mm84byhvIm81H05fWz94/5Dvur/IP+iQDHAvIEIwcqCZwKIgsiC5wKoAm5COUH5QdNCLkIoAkbChsKnAqcCiILQQzaDCEOIQ56Da8LoAkjBzIEsgDd/H743vTf8bvv9O707rvv3/G/8+X1R/d++I/54vl++g77kfsJ/N38tv3Y/lMASgKvBIIHnAp6DYYPRRAMEUUQ0A4hDtoMrwucCioJ5QdxBq8EmwJ2AEX+d/zI+uL54vky+g77kfsJ/EL8zvuR+w77fvri+Y/53fgb+Ef3YPZk9b/zhvIw8Xrwu+968DDxhvK/8970YPYb+OL5Qvyh/igBvgPOBSMH5QflByMHcQbOBYIFOAU4BYIFzgUeBsgG5Qe5CBsKrwvaDCEOIQ56DdoMIgu5CHEGVQPd/0L83fhk9b/zhvKG8ibz3vTW9n744vkO+5H7Qvzd/I79I/7Y/pz/ZABfAZsCbwTIBqAJQQzQDgwRtBKXE5cTlxO0EtsRDBFFENAOeg2vCxsKTQhxBvIEIwObAYkABgDO/87/3f/s/5z/Cv8j/gz9CfxR+8j6yPp++jL6j/l++Nb2ZPW/8ybzhvKG8obyhvKG8ibzv/Pe9GD23fiR+0X+yAD0AvIEcQaCB+UHTQjlB4IHIwceBs4FOAU4BTgFHgYjB00IGwoiC0EMeg16DdoMrwsbCuUHOAWbAY79j/nl9Sbz3/Ew8Ybyv/Nk9Uf33fji+VH7QvwM/QD+vf53/xQAyAC7AfQCrwTIBioJrwshDkUQ2xGXE4MUexV7FYMUlxPbEUUQIQ5BDBsK5QeCBVUDKAFO/7b9q/xC/Hf83fy2/UX+g/5l/tz9Zf3d/Hf8CfyR+8j6j/kb+GD2UfQm89/xevB68LvvevB68DDx3/Em81H0YPaz94/5kfuO/Yr/QwHHAvcDbwSvBK8EbwT3AyMDxwJyAnIC9AKJA28EHga5CK8LIQ4MEbQStBK0EkUQ2gyCB0MBj/kw8YPpc+Ip3kfZgdem1YHX+tpz4oXq3/GP+d4AggchDpcTfRaKF4oXpBiKF4MUhg+vCxsKuQjyBE7/j/lg9t70hvK77yXu9O568LvvTO1960zt3/GP+UIAbwTOBVUD8v7I+kf3v/Mw8d/xv/Pl9WD23vTf8bvv9O5p7HbowuMV4XPiNuZM7VH03fgy+n74R/ez93768v6vBKAJ2gzaDKAJ8gRyAvQC9wOJAygBof4A/hQAOAV6DcoZuSbuNHo8FUIzSHZLM0gVQlc3SSxlI6QYeg0jA877YPYl7nPit9OpyMjAhsOpyJTPptVH2UfZR9mB10fZ+toV4XboevBH94/5fvjW9kf34vkO+5H73fzs/zgFrwsMEYMUihfKGYoXlxPQDtoMIQ5FEAwRIQ6gCW8EDgFkACQCbwQ4Ba8EAALY/gD+ZAA4Ba8LDBF7FaQYpBikGHsVDBEbCpsCUftk9YbyJvMb+Nj+9wNvBKH+v/Nc55vcptW307fTptWB14HXgdem1abVgden34Pp3vRF/okDIwciC4YPtBKDFHsVpBiNHWUjfyhJLE8ubDBJLAYlyhmGD7kIzgXyBFUDIwCR+7P3YPbd+Nj+cQZ6DdsRexWkGD4cWSAGJX8oSSxPLk8uWiq5JgYl1yE+HHsVIQ5xBl8BsgDyBEEM2xG0EiEO8gQy+jDxg+kD5cLjA+U25jbmwuOn35vcKd5z4oXqv/Pi+dz9UwDdAUoCTv84+YbyTO1964Xqhepp7LvvhvLf8WnsNuZz4nPiXOcl7lH0G/iP+eL5yPqD/q8EnArQDtAO2gycCioJoAnaDJcTPhwGJVoqSSxJLEksfyi5Jtch/RrbERsKbwQkAt0BDgEM/d70heop3rfTX82pyBLLlM+m1UfZR9mB16bVgden34XqUfTO+4kA9wPOBYIFcgJl/Tj5R/dH9374UfveACoJDBGXE7QSIQ6gCeUHTQgbCiILoAnyBDj/UfuR+0IAyAZBDEUQlxN9FqQY/RrrHrkmTy7uNFc3VzehMkksuSZZIH0WIgsA/t/xhep26IXqfeuF6gPlKd6m1RLLyMDrveu9hsNfzbfTptWm1bfTt9NH2RXhdui779b2Rf44BZwKIQ6GDwwRtBKXE5cTfRb9GlkgZSPXIT4c2xFNCN4Ajv0M/Y79QvxH9zDxTO1M7TDxR/cj/q8EIgtFELQSexWKFz4c1yG5Jn8oWipaKloqWipJLFoquSaNHYMUhg9FEJcTihekGIoXlxMbCt38aeyn34HXptWm1abVsdESyybGJsapyJTPgdcV4X3rZPU5/UoCbwSvBFUDFAAO++X13/GG8mT1fviP+Uf3JvMl7n3raex68GT1R/dH92T13vTW9n763f9xBtoM2xGXE7QSDBFFEAwRgxSkGD4c6x5ZINchZSO5JrkmZSP9GrQSeg2vC0EMQQxBDCIL5QeD/rvvp9+301/NX82Uz7HRlM9fzRLLEsuUz6bVm9zC433rhvJg9hv4fvji+Qn8Zf22/SP+dgDOBSEOfRaNHVkg6x6NHf0aPhyNHVkg6x79GnsVhg9BDBsKnAp6DbQSfRaKF30WlxPbEbQSfRY+HFkgWSBZINch1yFlI+seihfaDHICfvre9DDxu++G8kf3OPne9IXqKd6m1bHRptVH2ZvcKd6b3PragdeB1/raKd7C44PpJe4w8d/xJvPe9GD2R/fl9b/zhvJR9I/5Tv8jA4kD9gBl/VH7d/ydADgFTQhNCB4GmwJl/lH7yPqO/VUDGwqGD7QSlxODFIoXPhzXIQYlfyhaKk8uoTJXN+40bDBaKmUj/RqXE9oMKgkiC4YP2xF6DSMD3vRc5yneR9mm1abVsdGUzxLLqcgmxqnIlM+B16ffXOcl7t/x3vQb+H76DvuP+WD23vTl9TL6Iv/HAokDDgGr/Dj5G/ji+Qn8Rf4UACgBKAH6/73+Cv9KAk0Ihg+DFIoXiheKF8oZjR1ZIAYlfyhJLKEyVzfaOdo5VzehMkks1yF9FkEMzgWvBHEGIwebAn74fesp3rfTEsupyKnIJsYmxobDyMCGwybGEsu30/rac+J26H3rTO2779/xJvOG8obyv/Pd+LIAKgkMEXsVfRZ7FXsVfRakGP0aPhyNHT4cpBi0Eq8LyAaCBU0I2gxFENsRlxN7FYoX/RrrHmUjuSZJLGww7jTuNKEyTy5aKtchfRYqCWX9YPbe9GD2s/dk9SXuA+VH2ZTPEssSy1/NlM+x0ZTPX80Sy6nIEsuUz6bVm9yn38LjXOd96/TuevB68Lvvu+/f8WD2CfwkAh4GyAY4BTIEvgMyBPIEcQa5CBsKuQj3A9z9j/k4+d38AAKCB0EMRRCDFIoXpBjKGf0ajR3XIbkmWipPLmwwoTLuNKEySSxlI8oZgxSDFIoX/Ro+HMoZ2xFxBuL5evCF6lznA+UV4ZvcptWUz1/NX82Uz6bV+tqn38LjXOeF6n3rhep26DbmwuPC4wPlg+kl7jDx3/Hf8d/x3/Hf8Sbz5fV++mP/JALdAQYAiv99ATgFoAnQDpcTpBj9Go0d6x5ZIGUjfyhsMO402jl6PDg/FUIVQjg/7jR/KD4clxPQDnoN0A4hDiILmwLW9n3rc+Ip3pvc+tpH2abVsdFfzRLLX82300fZKd5z4gPlXOd26IPpg+mD6YPphep967vvZPXI+r3+uwEyBHEGuQicCtoMDBF7FaQYiheXEyEOKgk4BfQCxwKvBE0Irwt6DSEOhg/bEXsVPhxlI38oTy5sMO40VzfaOVc3Ty5lI4oX2gzOBSMDvgNvBAACyPp68Dbmp98p3qffc+LC43PiKd5H2abVt9O306bVR9mb3BXhA+Vc53bog+mD6XboduiD6X3rJe6G8uX13fjI+lH7Mvrd+N34zvuK/wACuwG9/uL53vS772nsTO3f8eL5JAJNCK8LIQ5FEIMUyhnrHmUjfyhPLu402jk4PxVCOD9XN08uBiXrHj4c6x7XIdchjR2DFBsKQgDd+L/zevBM7YPpwuOb3IHXt9O307fTptX62inec+LC48Ljc+Kn3ynem9z62vra+top3hXhwuMD5TbmA+XC4wPlXOdp7LvvJvPl9Uf3YPa/8zDxhvLW9rb9bwRNCBsKrwvQDrQSpBjrHgYlWipsMFc3OD8TRRNFE0U4P+40WirXIY0djR2NHY0dpBiGD68E4vkw8X3rXOfC46ff+tqB17fTsdGUz7HRptVH2SneFeHC4wPlA+XC48LjwuPC48LjNuaD6SXuJvPW9jj5fvrd/F8BIwfaDAwRgxR9FnsVDBEqCd0Bg/7s/zIETQicCq8L2gyGD7QSfRY+HNchfyhPLu40ejw4PxVCOD/aOWwwZSOKF9AOrwucCrkI9wPO+4byheoD5cLjwuMD5TbmNubC4xXhm9xH2UfZ+top3sLjXOeD6YPpg+l26FznA+XC43Pic+ID5YPpJe7f8b/z3vTl9Rv4yPpl/Z0ArwTlB4IHmwF++Hrwaewl7ibzfvi2/ZsCcQagCdoMDBF7Ff0a1yFaKu40ejwTRXZL3k7eTjNIejyhMkksWipaKkksfyhlIz4ctBIbCiMD2P5C/DL6s/dR9PTug+nC46ffp99z4jbmg+lp7Gnsaex964XqXOcD5XPip9+n3xXhwuPC43PiFeEV4affp9+n38LjfeuG8tb25fXf8fTuJe677ybz1vbI+mX+QwG+Ax4GKgl6DdsRpBjXIVoqoTJ6PBVCE0UTRRVCVzdPLn8oBiVlI9ch6x7KGdsRuQgj/t70TO1c53Pip98p3kfZptWUz1/NlM+304HX+tqb3Cnep98V4RXhp98p3ineKd6n38LjXOeF6iXu3/Fg9jj5zvs4//IEQQy0EpcTDBGcCm8EZAAj/o792P59ATIEcQblB6AJQQzQDpcTyhlZIH8obDDaOTg/E0UzSBVC2jlPLgYljR2KF5cThg8iC/IEDP1k9fTuheqD6YXqfetp7H3rNuYV4Zvc+top3qffc+LC4zbmXOd26DbmwuMV4Snem9wp3qffFeHC41znhepM7SXuJe677970UfvIAJsCiv+P+SbzTO2D6Xbofeu771H0fvhC/Ar/XwGvBBsK2xHKGWUjTy5XNxVCM0jeTnZLM0gVQto57jRsMGwwbDBPLkksBiWNHYMU2gwjB28EiQObAjj/fvi773boA+XC48LjA+U25lznduhc5wPlFeEp3pvcm9yb3Jvc+tr62pvcm9wp3pvc+tr62ineNuZM7d/xUfRR9N/xJe6F6oXqfev07ibz1vbi+Qn8AP72AIIFQQyXEz4cBiVPLto5FUIzSHZLM0gTRXo8VzdsME8uSSxaKgYl6x57FSILsgB++FH0JvOG8nrwfesD5affKd4p3qffFeED5YPpfet964PpNubC48LjwuPC48LjwuMD5XboTO168N/xv/PW9kL8VQMbCtAO2xEMESEOuQj0Atj+DP1l/Qr/3gC7AX0BQwEAAjIETQghDnsV6x5/KO40OD8TRTNIE0U4P1c3Ty65JtchPhx9FrQS2gw4BQn8JvNM7Uztu++G8obyJe6D6cLjp9+b3Jvcp98D5YPpaeyF6lznwuNz4hXhFeGn3ynem9wp3nPiNuZ26IPphepp7LvvZPVR+1MAVQO+AzIA4vmG8mnsg+mF6kztevC/82D2fvh++gz9sgCCBUEMfRbXIU8u2jkVQjNIdkt2SzNIE0U4P3o82jnaOVc37jRPLmUjpBhFEEEMIgucCuUHIwOr/GT1TO025sLjwuNc54XqfeuD6TbmwuNz4nPiFeEp3vraR9mB14HXR9mB16bVt9O306bVR9kp3gPlfesw8Sbz3/H07n3rg+mF6mnsu++/89b2j/nO+yP+ZACJA7kIDBH9GrkmoTLaORVCE0UzSDNIFUJ6PFc3oTJsME8uWioGJcoZ0A6vBCP+MvpH9970MPFp7APlKd5H2YHX+tqn3wPlNuYD5cLjc+Jz4nPic+IV4affKd6n33PiNuaD6Wns9O4w8VH03fgK/x4GQQwMEbQSRRCvC8gGJALy/gz9q/w5/SP+I/45/c77Ufur/H0BGwqDFFkgSSzuNNo5OD84Pzg/2jmhMloqZSONHcoZgxTaDL4Dfvq/87vv9O568IbyJvN68IXqc+Kb3PraKd7C43boheqD6XboNuYD5cLjc+IV4SneKd4p3hXhc+ID5TbmNuZc53bofeu77+X1d/zeAN0Bvv8O+2T19O6F6nbog+lM7TDxUfTe9FH0v/NR9N34nQCvC4oXZSNJLO40ejwVQhNFE0UVQjg/ejx6PHo82jnuNEksZSPKGbQShg/QDkUQDBHaDDIE3fj07oPpduiD6YXqfet9633rg+lc5zbmA+XC4xXhKd6b3PraR9mB14HXptW307fTt9Om1frac+J26CXuMPHf8bvvfetc5zbmduhM7d/x5fVH92D2UfS/82D23fzOBUUQ/RplI08uVzc4PxNFE0UTRRVCOD96PNo52jnuNEksZSOkGCEOggdvBIkDAAJl/WT1fevC4xXhc+ID5Xboaewl7vTuJe5p7H3rg+l26DbmA+XC48LjwuM25nbofetM7fTuevBR9Dj5d//OBUEMDBHbEYYPGwr3A63/tv0j/or/zv8j/sj61vZR9OX1CfzyBCEOihfXIVoq7jR6PDg/OD96PNo57jRsMEksWioGJY0dlxO5CIr/Mvri+UL8I/5C/GD2Je5c58Ljc+ID5Vznfesl7vTuJe5964PpXOc25sLjc+IV4affp9+n3xXhwuPC48LjA+Vc54Xqu+9g9t38yADeAHf8ZPVM7VznNuZ26GnsevDf8Xrwaex96yXuv/OR+68E0A7KGQYlbDDaORVCE0UzSDNIM0gzSDNIE0UTRTg/7jRaKlkgyhmkGMoZ/RqkGNsRggfd/L/zTO2F6oPpg+l9633rhep26APlc+Jz4hXhp9/62oHXptW307fTt9Ox0ZTPX80SyxLLlM+B16ffXOdM7SXufes25nPiFeED5X3revAm89/x9O5M7SXu3/HW9jn9zgVFED4cuSZsMFc3ejw4PxVCFUI4Pzg/OD96PNo5oTK5Jv0aDBFBDJwKKgnOBYr/s/e773bowuMV4XPiNuaD6WnsaeyD6VznNuY25gPlwuNz4hXhp99z4gPlduiF6n3rfeuF6mnsu+/W9hQAoAlFELQSRRAbCokDBgBCAJsCMgRyAgz91vaG8nrwMPG/8zj5uwFBDIoXWSB/KE8uoTJXN9o5VzfuNKEybDBPLn8oWSCDFCoJ9gCO/bb9Rf6O/cj6YPYw8X3rNubC4zbmhep68CbzhvJ68CXuaexp7H3rg+lc58LjFeEV4XPiwuMD5QPlA+XC4wPlXOdp7FH0Of0jA4kDg/7W9rvvaewl7obyYPYb+GD2JvMw8bvv9O4w8eX1g/4qCZcTPhwGJU8uVzc4PxNFM0gzSHZLdkt2SzNIE0XaOWwwWiq5JgYlBiUGJdchPhyXE00IOf3e9DDxhvJR9GT13vS/84by3/Ew8TDx9O5961znwuMV4affp98p3pvcR9mm1bHRlM+x0UfZc+J967vv9O6F6jbmA+Vc52ns3/Fk9WD2ZPUm87vvTO1M7TDx3fgAApwKtBL9GmUjSSyhMlc32jl6PHo8OD8VQjg/ejzuNFoq1yHKGYMUhg9BDLkIvgNC/Ibyg+nC4xXhc+I25nbog+mD6YPpg+mD6YPpg+lc5zbmA+UD5TbmduiD6X3rheqD6TbmA+Vc5yXuOPn3AyILQQwqCfIEAAK7AccC9wP3A5sC8v44+SbzJe5M7Xrw1vbY/nEGeg17FY0dBiVJLGwwoTLuNFc3VzdXN+40Ty4GJf0a2xGgCa8EmwIAAl8BCv8y+obyfesD5XPiwuM25oPpheqF6oPpg+mD6YPpduhc5wPlwuNz4nPiwuPC4wPlNuYD5cLjFeFz4nbohvJR+3YAnP8y+r/zu+/07rvvJvNg9n74R/cm8yXug+lc54Xqu+9H92X+HgbQDqQYZSNJLO40ejw4PxNFM0h2S3ZLM0gTRXo87jRPLloqfyh/KH8oBiXrHnsVnArd/7P3v/Mm87/zv/Mm89/xMPEw8TDxu+9M7YPpNubC4xXhp9+n36ffp9+b3KbVlM8Sy5TPgdcV4XbofeuD6TbmA+UD5VznTO0m80f3G/jl9XrwaeyD6X3r9O5R9OL5vv/IBoYPpBjXIX8oTy6hMlc3ejwVQhNFE0UVQno87jRaKmUjPhykGHsV2xHaDPIEzvuG8n3rduhc53boheqF6n3rfet962nsfeuF6oXqg+l26FznXOeD6Wns9O4l7oPpwuNz4jbmJe5++LsBgge5CCMHMgRyAnIC9wPOBXEG8gTs/934hvL07rvvhvLl9Y/5g/6vBEEMlxP9GlkguSZaKmww7jRXN1c37jRsMFoq1yGkGEUQnAojBx4GOAXHArb9YPYl7lznwuNz4sLjNuZc53bog+mD6YPpg+mD6XboXOcD5RXhp98V4QPlXOc25nPiKd4p3qffNuYl7mT1fviz91H0u+9p7Gnsu++/87P3G/hk9bvvhepc5zbmXOeF6iXuv/OR+zIE2gx7FeseuSZPLlc3OD8TRTNIM0gzSBNFFULaOe40bDBPLk8uTy5JLLkmjR3bESMH3P2z92T13vRk9WT13vQm84by3/GG8t/x9O5961znNuZc54Xqhepc5xXhR9m307HRt9NH2affA+U25gPlc+IV4XPiNuZp7IbyZPXl9SbzevBM7YXqhep96yXuJvM4+Tj/OAWvC7QS/RplI1oqoTLaORVCE0UzSDNIFUJ6PO40SSy5JmUjWSDrHsoZlxMbCnf/YPZ68CXuTO0l7iXuTO1p7H3rTO307rvvJe5964PphepM7bvv3/F68GnsXOdz4hXhwuOF6lH0d/woAQACsgBj/4r/fQFvBMgGggceBpsCZf0b+Cbzu+/07jDxUfSz9w77vf73AyILtBL9GmUjWipsMO40VzdXN+40bDBaKtchyhmDFAwRhg+GD3oNKgl9Ad34MPF964Pphep9633rfet962nsJe6777vvJe6F6lznXOd26IPpheqF6oPpNuZz4hXhc+Jc5yXuhvK/89/x9O5p7H3raey77ybzZPVg9t70MPF96zbmc+Jz4gPlduhp7HrwZPUJ/L4DQQx7FesefyhsMFc3ejw4PxVCFUI4P9o57jShMmwwoTKhMqEySSwGJaQYIQ44BTj/zvvi+Rv41vbl9eX1YPZg9t70hvL07kztaexM7fTuu+/07oXqwuOb3KbVt9Om1UfZKd4V4RXhp98p3ineFeED5YXqu+9R9GD23vR68H3rduh26IXqTO2774by5fXi+dj+OAV6DX0W6x5/KGwwVzc4PxVCE0UVQno87jRPLn8oBiUGJWUj6x6KF3oN9ALi+Sbz9O5p7IXqg+l26IPpfetp7Gnsaexp7GnsTO307nrw3/GG8jDxTO126MLjc+ID5YXqMPHW9n76Cfyr/GX9Rf7s/5sCHgYqCaAJyAb2AH76ZPUm8ybzv/Pe9GT1YPbd+Dn9vgOvC4MUjR0GJUksbDDuNFc3VzfuNE8ufyhZIP0apBikGKQYihe0EiILmwJR+2D2JvN68CXuJe677zDxhvKG8t/xevD07vTuJe4l7iXu9O6773rwJe6F6lznA+U25nbofetM7SXuTO1p7H3rfetp7LvvUfQ4+Qn8yPrl9Xrwfet26Hbog+l962nsJe4w8WT1Dvu7AaAJtBI+HAYlSSzuNNo5ejw4Pzg/ejxXN+40oTLuNO407jRPLgYlPhy0EhsKJAJR+9b2UfS/8ybzhvJ68PTuTO1M7UztTO1M7SXu9O568Hrwaew25ineR9mB14HXgddH2UfZ+tr62kfZR9n62qffNuZM7Sbz3vS/83rwTO1p7EztJe4l7vTuu+8w8b/zYPZ++lMA5QcMET4cBiVPLu40ejw4Pzg/ejzuNE8uSSxJLEksfyhlIz4clxMiCyQCOPkw8WnsheqD6YPpg+mD6Xbog+l962nsTO1M7SXuevAm87/zMPFp7HboA+UD5Tbmg+lM7TDx3vTW9kf3R/ez93768v4yBOUH5QcyBDj/yPqz92T1v/Pf8TDxMPHf8b/zYPZ++rIAuQi0Ev0aZSN/KE8uoTLuNO40bDB/KGUjWSBZIOsePhykGIMUhg+gCfQCQvzW9r/zJvO/81H0v/Mm84byhvK/87/zJvOG8ibzZPUb+N34R/dR9N/xu+/07iXu9O568DDxhvKG8jDxu+/07jDx3vTi+Tn9I/53/Dj53vQw8SXuaex962nsJe6779/xUfRH93f89wPaDH0W6x4GJU8u7jR6PHo8ejzaOVc3VzdXN1c3VzfuNKEyTy65Jj4ctBKgCccCof5C/I/5YPYm8zDx9O5M7Wnsfet96yXu3/FR9N70JvO7733rNuZz4qffKd6b3CneKd6b3PraR9lH2frap98D5X3revAm87/zJvMw8bvv9O707vTuu+968DDxMPGG8mT1Ufv0AiILlxM+HLkmbDBXN3o8ejzaOe40oTKhMmwwbDBsMEksfyjXIaQYIQ6vBAz9G/je9Ibyu+8l7kztTO1M7WnsaexM7bvvJvPl9Uf3R/dk9SbzevAl7mnsfetp7CXuevDf8YbyhvLf8d/xv/Mb+Dn93gByAt0Biv93/N34ZPWG8jDxevC77/TuJe6774bys/cA/m8EIgu0Ev0a1yF/KEksWip/KAYl1yFZIOsejR0+HP0apBiDFCEOyAYjAMj6R/dR9IbyevC77/TuJe5M7WnsaexM7bvvJvNk9db21vZg9mT1UfQm8zDxu+8l7kztJe4l7iXuaeyD6Xbog+lM7TDxUfRg9tb2YPa/83rwJe4l7iXu9O707vTuJe707jDx3vSP+a3/cQbQDooX1yFaKk8ubDBsMKEyoTKhMu407jRXN1c37jRsMFoq1yHKGQwRoAm+Awr/DvtH91H0evAl7n3rhep967vvv/PW9hv4fvgb+Nb23vTf8SXug+k25gPlwuPC4xXhKd762kfZ+top3sLjheow8eX1fvgb+Nb2ZPVk9eX1YPbl9d703vTe9OX1s/d++r3+rwR6DYoX1yFaKmwwoTLuNO407jShMqEyoTKhMqEybDBJLLkmjR2DFJwKmwJC/LP3UfSG8nrwTO2F6lznXOd26H3r9O4w8SbzUfRk9WD2YPbe9Ibyu+8l7iXuevCG8r/zv/Mm84byv/Ng9jL62P6JA3EGyAYyBIkAZf1R+4/5s/fl9VH0v/O/87/z3vRg9uL5zv/lBwwRpBhZIAYluSZ/KLkmBiXXIesejR0+HP0ayhmkGHsV2xGvC4IFMgDO+zj5s/dg9r/zevBp7IPpg+mF6mnsJe707nrwhvJR9GD2s/cb+GD2v/Mw8XrwMPHf8d/xMPH07kztfet960ztevC/8+X1ZPW/89/xu+8l7kztaexp7Gnsaexp7H3rheqF6kztJvMJ/M4F0A6KF40dZSO5JloqSSxJLE8ubDBsMKEyoTKhMmwwSSy5Jo0dgxQhDqAJHgbdAUL85fV68Gnshep962nsJe677zDxJvNR9GT15fXe9Iby9O5963boXOc25sLjc+Ip3vraR9lH2fraFeFc50ztMPG/89703vRR9CbzJvO/8+X1R/ez92D2UfQm81H03fhTALkIDBGkGFkguSZJLE8ubDBsMKEyoTKhMqEyoTKhMqEySSxlI8oZRRC5CL4Dzv+R+2D2evB961znNuYD5TbmXOd26IXqTO2779/xv/Pe9L/z3/G77yXuTO0l7rvvevB68PTuJe4l7jDx3vTi+UX+mwG+A/cDSgIi/5H7OPnd+I/5j/l++OX1hvJ68DDxZPVR+3ICoAkMEYoXjR3XIWUjZSNlI9chWSCNHT4cPhyNHesejR3KGZcTIQ6gCcgGMgSyAEL8R/cm87vvTO1p7GnsTO0l7rvv3/FR9GD2fvgy+n76OPnW9t70UfRR9GT13vS/83rwTO1964XqfetM7bvvhvLe9GT1v/N68Eztaexp7CXu9O4l7n3rXOcD5QPlduj07mD2Rf5xBiEOexX9GuseZSO5Jn8ofyhaKloqTy6hMu407jRsMFoqBiXrHsoZgxSGD6AJmwLO++X1MPEl7n3rhep960ztu+/f8VH0YPYb+N34R/dR9HrwJe5p7IXqdujC46ff+tqB14HX+top3sLjhep68L/zUfSG8nrwevCG8mT1s/cb+OX1hvL07iXuu++/8zj5+v/lB0UQihfrHgYlWipPLmwwbDBsMGwwoTLuNO40oTJPLn8oWSCkGJcTIQ4qCb4D3P1++L/z9O5961znNuY25lzng+l96yXu3/He9Nb2YPZR9N/xevB68N/xJvMm89/xu+/07vTuevAm80f3Qvz2AIkD9AJ3/877MvrI+nf8jv1C/N34UfQw8fTuu++G8rP3AP44BdoMlxPKGeseZSMGJQYlZSNZIOse6x5ZIGUjZSNlI1kgPhyKF4MUDBHaDE0IvgO+/wn8fvje9IbyMPEw8YbyJvO/81H01vbi+Qn83fzO+zL63fjd+OL5fvqP+WD2JvN68CXufeuF6mnsu++/8+X1UfQw8SXuTO307jDx3/Hf8fTufet26DbmNuZ26GnshvIy+n0B5Qd6DZcTyhnrHtchZSMGJbkmfyhJLGww7jTuNKEyTy5aKrkm1yE+HH0WDBGvC84FOP9++CbzevC777vvu+968N/xZPV++FH7d/yR+zj51vbl9VH03/El7nbowuOn35vc+tr62ineA+V967vvu+8l7mnsaez07t/x3vTl9eX1UfTf8fTuaex960zt3/Gz9wD+vgMbCgwRpBjrHmUjBiW5JrkmuSZaKkksTy5PLloquSZZIP0aexWGD5wKHgZfAQn8ZPUl7oPpNubC48Ljc+LC4zbmg+kl7t/xv/Mm89/xMPHf8YbyJvMm84by3/F68PTuTO1M7TDxR/e2/X0BJAKdAGX+3fzd/I79AP6O/Qn8OPne9HrwTO1p7PTuJvM4+dj+bwScCgwRpBiNHVkgWSDrHj4cyhn9Go0dWSBlI2Uj1yFZII0dpBiDFAwReg0bCs4FXwFl/TL6s/dk9Sbz3/Ew8TDxhvJk9bP3OPmP+Y/54vnI+gn8q/xC/FH74vlg9t/xTO19633rJe7f8b/zUfSG8nrw9O707rvvMPHf8d/xu+9961znwuPC4wPlg+kl7ibzs/fd/IkDIgu0EqQYjR3rHlkg1yEGJX8oTy5sMKEyoTKhMk8uWiq5JtchjR3KGZcT2gweBiMAyPrW9r/z3/Ew8d/xv/Ng9n744vl++sj6yPoy+t34YPYm87vvheo25hXhm9z62pvcFeE25oXqTO0l7kztTO1M7XrwUfSz9zL6fvp++GT13/H07vTuevCG8mT1fviO/a8Eeg17FY0d1yFlIwYlBiW5Jn8oSSxJLEksSSx/KAYlWSDKGXsVRRAiCzgFof4b+DDxfes25nPiFeEV4XPiA+V26IXqaexM7UztJe707rvvevB68Lvv9O5M7YXqXOdc53boaezf8bP3Cfwj/gD+DP2r/I79Cv8jAM7/AP4O+0f3v/Mw8XrwhvLe9Ef3DvsGACMHRRCkGOseWSBZIOsePhw+HD4c6x7XIQYluSa5JgYl1yGNHf0aiheXE0UQrwsjB5sC3P2P+WT1JvPf8d/x3/GG8r/zUfRk9Uf3OPnI+gn83fxl/WX9zvt++L/z9O6F6nboduiF6kztevAw8bvvJe5M7SXuu+968DDxevAl7oXqXOcD5QPlNuZ26IPpfeu772D2g/7IBiEOlxN9FqQY/RqNHVkgBiV/KE8ubDChMqEyoTJPLkksfygGJVkg/RqDFHoNggXc/bP3UfSG8obyhvIm81H0YPbd+JH7tv3Y/tj+I/53/DL6YPYw8X3rNuZz4qffp99z4lznhepp7H3rfetp7CXu3/Fk9d34yPrI+jj51vZR9CbzMPG77/Tuu+8m8374zv9NCEUQihc+HOseWSDXIWUjBiV/KFoqSSxPLkksWioGJdchjR2kGJcT0A6gCXICMvrf8Wnsduhc5zbmNuZc51zng+l960ztJe6773rwhvJR9GT1ZPVR9N/x9O5964Ppheol7ibzG/iR+938Of0j/mP/3gAkApsCmwFj/938fvp++GD2UfSG8t/xJvPl9cj6KAG5CEUQexWKF6QYihd9Fn0WfRbKGT4cWSBlI2UjZSPXIY0d/RqKF3sVlxNFECILrwTy/sj6G/jl9VH0JvPf8TDx3/GG8lH05fVH94/5kfuO/aH+I/4J/H74v/Ml7nboNuY25lzng+mD6YPpduh26Hbog+l9633rheqD6VznXOc25sLjc+IV4RXhFeHC4zbmfesm81H7SgKCByILeg2GDwwRgxSkGI0dZSN/KEksTy5PLk8uSSxaKloqfyjXIf0a2xEqCZsCtv0y+rP35fVk9WD2G/ji+Qn8AP4GAN0BIwOJA8cCsgBl/d34JvNM7XboA+U25lzng+mF6oXqhep960ztevAm82T1R/fd+H76Uft++hv43vTf8bvvJe5M7fTuJvN++scCGwpFEJcTexV9FooXyhk+HOse1yEGJX8ofygGJdch6x4+HP0apBiXE68LVQMO+1H0Je6D6TbmwuPC4wPlNuZc53bohepM7bvvJvPl9Rv4j/ni+d345fWG8rvvJe707jDxUfSz9+L5zvuD/l8BVQP3A4kDxwIAApsBKAHd/7b9Dvvd+Nb2ZPXe9GD2fvoOAbkIRRCDFH0WfRZ9FnsVexV9FsoZjR3XIQYluSYGJdchWSBZIFkgWSCNHaQYlxMhDioJiQNF/o/55fW/89/xMPF68HrwMPGG8t70G/gO+479OP+K/0X+UfvW9t/xJe5964XqheqF6oPpg+mF6n3raex9633rheqD6YPpheqD6XboXOcD5cLjc+IV4affc+J26HrwG/hl/vQCcQYqCSILeg0MEXsV/RrXIbkmWipJLE8uTy5sMKEyoTJPLn8o1yH9GoMU2gzOBRQACfyP+bP3YPZk9WT15fWz9376Zf2c/4kAdgB3/zn9OPlR9PTufeuD6XboXOc25jbmXOd26IPpaewl7rvv3/FR9Nb2j/nI+uL5G/hk9d/xJe5964Ppfet68Ef3Rf4yBCoJ2gzQDgwRlxN7FaQYPhxZIAYluSa5JgYlZSNlI2Uj1yHrHsoZlxPaDM4Ftv1g9nrwaeyD6VznNuYD5QPlA+U25oPpTO168CbzZPWz9xv41va/83rwJe5M7SXu9O4w8b/zYPaP+Qz9rf+dACMAiv+c/1MAKAFfAd4Arf/c/Q77s/dR9Cbz3vQ4+b7/cQavC4YP2xG0EpcTlxOXE3sVpBg+HFkg1yHXIVkgWSBZIFkgWSBZII0dPhykGJcTeg0jB7IAUftH97/zMPEl7n3rhepp7CXuMPG/82D2MvoM/UX+3fzi+WD2JvN68CXuaeyF6oPpduiD6X3raexp7H3rfet9633raexM7SXuJe5p7IXqNuZz4hXhFeED5YXqMPHW9s77ZABvBCMHKgmcCnoN2xGkGI0dZSO5JloqSSxsMKEyoTKhMmwwTy5/KNch/Rq0Eq8LzgW7AWX+Uft++Nb21vZ++Mj6q/zY/n0BbwRxBsgGrwRDATn9j/nl9Yby9O5963boXOd26IPpheqF6n3raez07jDxv/Ng9n74j/l++GT1evB963boXOeD6Uzt3/HW9gn8sgDyBOUHoAmvCyEO2xF7FcoZPhzrHuseWSDXIdch1yFZIOsePhyKF9sRGwpyAg77ZPV68Eztg+lc5wPlA+UD5TbmduiF6vTuv/Oz9+L54vnd+Ef3ZPVR9CbzhvLf8YbyZPV++M77I/4K//L+AP5l/WX9Rf4UAEoC9wNVA0IAkftH91H0JvNR9LP3zvuyADgFKglBDNoMeg3aDHoNhg/bEYMUfRakGMoZyhn9Gj4cPhyNHY0djR0+HKQYgxTQDrkIVQNl/uL55fWG8rvvTO1M7WnsTO307obyR/fO+6H+3f8UAIr/Zf6r/DL6R/dR9N/xMPHf8YbyJvMm89/xu+8l7kztTO307jDxJvOG8rvvfetc5wPlwuPC4zbmheq779704vnc/bIAcgKJA/IEggevC0UQexX9GlkgBiVaKk8ubDChMu40oTKhMk8ufyjXIf0agxQhDrkI9wPd/6v8fvo4+X74OPlR+6H+cgLOBU0IuQjlB3EG9wMoAQz9G/gm8/Tuaex9633raexp7H3rfeuF6n3rTO0w8eX1fvjd+Ef3v/O772nsg+lc53boheol7oby1vZ++mX9d//2APQCggW5CNoMRRCXE30WpBj9Gj4cjR3rHusejR0+HKQYlxN6Dc4FAP7W9nrwfetc58LjFeGn3yneKd4V4QPlg+n07obyZPVH9xv4fvh++LP35fVR9L/z3vSz98j6tv0K/6H+DP0O+zL6DvuO/fYAiQMyBPQCUwDd/Dj55fW/87/z5fWP+QD+SgLOBU0IKgkbCpwKrwvaDNAORRDbEZcTexV9FqQYyhk+HI0d6x7rHuse6x79GnsVhg8qCb4Dvf4y+mD2hvL07n3rheqF6mns9O6G8mD2OPnO+wD+Tv+t/4P+Cfx++GT1v/Mm81H03vTe9L/zMPEl7mnsfetp7CXuu++77/TuTO2F6lznA+XC48LjA+WD6SXuhvLW9uL5QvxF/lMAcgKvBOUHrwsMEX0W/RpZIAYlWipPLmwwbDBsMGwwbDBJLLkm6x6KF9sRrwsjB3ICtv04+WD23vTe9GD23fhR+9z9ZABKAiMD9ALdAU7/Uftg9jDxJe5p7GnsTO1M7UztfeuD6Xbog+lp7LvvhvLe9GD2YPZR9DDxTO2F6oPpg+l967vvv/NH98j6I/59ATIEHgblB6AJQQyGD9sRgxR9FqQY/Ro+HI0d6x5ZIFkg6x79GoMUQQwyBGX9s/cm8/Tuheo25sLjc+Jz4sLjA+V26GnsevAm8+X1s/fd+N34G/hg9mT1ZPVH91H7Tv8AAkoCyAAK/0X+vf4yAHIC8gTlB6AJKgnIBiMD8v6R++L5Mvqr/J0AbwTlB68L0A4MEdsR2xHbEdsRtBKDFHsVfRaKF6QYyhnKGf0aPhzrHlkg1yHXIY0dpBjbEdoMTQi+A2X+fvgm8/TufeuD6VznXOd26H3ru++/89b24vnO+3f8Uft++N703/F68DDxJvMm89/xu+9M7X3rg+l26Hbog+l960ztTO1p7IPpNubC43Pic+LC41znheol7obyYPY4+cj6Cfw5/U7/SgIeBiILRRB7Ff0a6x7XIQYluSZaKk8ubDBsME8uWioGJeseyhmDFNAOuQhVAwr/zvuP+Rv4s/c4+Qn8Tv9yAvIEyAblB4IHOAXeAJH71vbe9FH0UfS/89/xu+8l7mnsfet962ns9O4m89b2fvgb+OX1hvL07mnsfet9633raez07obyYPaP+Qn83P2c/30BiQOCBeUHIgshDgwRlxN7FX0WpBg+HOse1yFZID4cihcMEa8LHgbeAM771vbf8SXuhepc5wPlA+U25oPpTO168Cbz5fV++DL6Mvrd+Ef3R/c4+Xf8nP+7AZsCJALeAJz/g/4A/tj+XwE4BbkIGwoqCXEGcgIK/3f8fvri+cj6DP2JAG8E5QcbCiILrwsiCyILIguvC0EMIQ5FEAwR2xHbEdsRlxN9Fv0ajR3rHusePhykGHsV2xF6DbkIvgMK/376ZPW774Xqduhc54Ppfev07ibzR/cO+wz93fzI+n745fVk9eX1s/fd+Dj5fvjW9lH03/H07mnsaewl7rvvMPF68PTuaeyF6lznNuYD5QPlXOeF6vTuhvJk9Uf33fji+VH73fxj//QC5QfaDNsRexWKF/0ajR3XIbkmSSxPLk8uTy5aKrkmZSPrHsoZgxRFECIL8gQ4/8j6fvgb+Dj5UftF/rsB8gSCB7kI5QfyBPYADP1++uL54vmP+X741vbe9Ibyu+8l7kzt9O7f8eX1fvgy+jL63fjl9Yby9O5p7IPpg+mF6kztevAm82T1R/c4+X76kfur/IP+mwGvBIIHoAmcCkEMIQ4MEXsVpBj9GsoZiheXE4YPnArOBd0Bg/4O+9b2MPFp7HboNuYD5QPlXOeD6UztevBR9Nb2s/ez92D2YPaz98j6I/7eACMDbwTyBPcDJAKJACMAXwEyBOUHnAqvCyILKgkeBscCIv/O+zL6yPo5/cgAMgTIBioJnAqvC68LnAqcCiILQQx6DdAO0A4hDnoNIQ6GD7QSfRakGMoZyhnKGYoXgxQMESEOrwuCB0oCzvtk9fTug+k25gPlA+U25oPpTO0w8d705fVk9Sbz3/Hf8Ybyv/Pe9GD2R/dH9+X1JvO772nsheqF6mnsJe6773rwevC77yXufet26FznXOeD6Wnsu+8m8+X1G/ji+cj6DvtC/L3+9ALlB0EMhg+0EoMUihc+HNchuSZJLGwwoTKhMmwwTy5aKn8oBiXrHsoZtBJBDCMHmwI4/wz9d/w5/a3/IwNxBrkIoAlNCM4FIwOyACL/I/62/WX9DP3O+zj55fXf8bvvJe707jDx3vSz9+L5Dvt++n74ZPXf8fTuTO1p7CXuu+/f8d70G/gy+sj6yPrI+gn8g/4oAVUD8gTOBcgGuQivC4YPtBJ9FqQYpBh9FrQShg9BDBsKggcyBL7/fvre9Lvvheo25nPiFeFz4gPlduhp7PTuMPHf8YbyhvIm89701vaP+d38zv+bAQACQwEUAPL+of6K/90BOAXlBxsKGwoqCXEGxwIi/0L8DvsO+3f82P4AAoIFTQigCaAJKgkqCaAJIgtBDHoN2gxBDJwKoAkbCkEMhg+XE30WiheKF4oXfRZ7FXsVgxTbESEOGwqvBKH+G/gw8Wnsg+l26IPpaex68L/z5fXW9tb25fXe9FH0ZPVH94/5CfyO/bb9d/zi+eX13/G77/Tu9O4w8Ybyv/O/84byu+9M7YPpXOdc51zng+lM7TDxv/Nk9WD21vZ++FH7Iv8jAyMHGwpBDHoN0A7bEX0WPhzXIbkmWipJLEksSSxJLFoqfyi5JmUjjR2kGLQS2gwjB3ICY/9F/r3+UwBKAjIEggWCBW8EcgIGANz9QvzO+877zvtR+zL6G/je9DDxJe5p7Ezt9O6G8mT1s/fd+H741va/87vvaeyD6Xbog+l96/TuMPHf8YbyJvNR9OX1G/h++t38g/4i/2P/QgCbAsgGrwuGD9sRtBK0EgwRhg8hDnoNQQycCrkIHgYkAt381vYw8X3rduhc51znduh96yXuMPG/89705fXl9eX11vY4+Qn8nP9VAx4GggcjB4IFvgP0Ar4DHgYqCa8L2gx6DUEMGwrIBvQCY/+r/M77DP2c/0oC9wOvBK8ErwTyBIIFcQblByoJKgnlB4IF9wP3A4IF5QciC3oNhg8MEQwR2xG0EpcTlxOXE7QSDBEhDioJIwNC/OX1MPFM7X3rfetM7bvvhvJR9GT13vS/84by3/GG8t70s/fI+mX9Zf4M/Y/53vR68CXuTO0l7rvvMPGG8ibz3/G772nsdugD5cLjA+Vc54Xqfetp7CXu9O677zDxUfQb+An8g/76//YAcgI4BSoJIQ6DFMoZ6x7XIQYluSZ/KFoqfyh/KLkmBiXXIY0dihfbEa8LHgYkAr7/Cv/O/7sBbwTIBuUHIwfyBEoCIwC9/gD+3P2D/vL+I/6R+7P3JvO770ztTO0l7jDxv/Pl9Uf3G/jW9r/z9O5964Pphep962nsTO0l7vTuu++77zDxJvPl9X74MvoO+1H7Cfzc/Q4BOAWgCdoM0A6GD0UQDBEMEQwRDBEMEQwRDBHQDiILHgYyADL6UfR68EztaexM7fTu3/He9Ef3s/cb+Bv4fvji+Qn8Iv8jA4IHnApBDK8LnAoqCbkIKgkiC9oMIQ6GDwwRDBHQDpwKHgbHAl8BfQFKAiMD9wNvBK8EbwRvBK8EHgZNCBsKGwq5CHEG9wNyAscCbwTIBk0IoAkiC9oM0A6GD0UQDBG0EpcTgxSXEwwR2gyCB18BUftk9TDxJe5M7SXuu+/f8SbzJvOG8t/xMPEw8d/xUfR++Hf8Y/8UAIP+Ufuz91H03/F68HrwMPG/8+X11vZk9d/xJe5964Ppg+mF6n3raewl7vTuu+968N/xUfQb+M77Rf4i/9j+8v6dADIEuQh6DdsRfRb9Guse1yFlIwYluSZ/KH8ofyi5JgYlWSA+HH0WRRAbCq8EyADy/gr/IwCbAccCIwNyAvYA2P53/A77yPoJ/I79Zf6O/VH7G/hR9DDx9O5M7SXuevC/89b23fjd+Nb2UfQw8fTuJe4l7vTu9O6777vv9O707rvv3/He9LP3j/k4+X74fviP+Xf8QgAyBCMHGwpBDCEO0A6GD4YPRRC0EoMUgxSDFNsRhg8iC3EGsgB++t70MPH07vTuu+8w8Sbz3vTl9eX1ZPXe9GT1G/hC/A4BOAXlB6AJoAm5CIIHcQZxBoIHGwraDNAORRCGD3oNnArlBzgFiQPHAscCVQP3A/cDiQNVA/cDHgZNCJwKIgugCSMHMgTdAQ4BXwFKAiMD9wM4BXEGIwflB00IGwpBDNAODBHbEdsRDBEhDpwKOAWh/hv4hvIl7mnsaexp7CXu9O6777vv9O5M7Uzt9O4m8xv4Cfwi/2QArf85/Y/55fW/84byJvNR9GD2s/ez92D2v/N68CXuaex962nsTO0l7iXuJe707nrwJvNg9jj5UfvO+1H7yPpR+479DgGvBLkI2gwMEXsVpBj9Go0d6x7XIWUjBiW5JrkmBiVlI1kg/RqDFHoNggf0AokAzv/d/8gASgJVA8cCMgDd/H764vnI+gn8jv2h/mX+q/zi+WD2hvK77yXuTO307jDxJvPe9N70v/Pf8bvvJe5M7UztTO1M7Wnsfet962nsJe568CbzZPXl9WT1ZPXl9bP3Mvo5/SMAIwPOBeUHKgkbCiIL2gwhDkUQtBKDFHsVexWDFNsRIQ5NCEoC3fzd+GD23vTe9GD2fvji+Y/5fvjW9uX1R/cy+kX+xwLIBhsKrwtBDK8LnAoqCU0IKgmcCtoM0A6GD4YPeg0iC+UHOAVVA8cCmwLdAYkACv8j/kX+zv8kAm8EzgXOBTIEJAIjAIP+tv22/YP+rf/eALsBJAJyAscCvgM4BSMHoAmvCyEORRBFEIYP2gxNCJsCq/zW9oby9O4l7vTuevDf8d/xevD07iXu9O4w8d70OPll/VMA3QGbAez/DP3i+bP3YPZH9934MvpR+1H7Mvqz9970JvPf8d/xhvKG8t/xevB68HrwhvLe9Ef3j/kO+5H7Cfx3/Dn9vf5DAfIEKgnaDEUQlxN9FsoZPhyNHVkgZSMGJX8oWipaKn8ouSbXIT4cfRZFEJwKyAaCBR4GggdNCOUHzgX0AmQAg/62/SP+iv9DAXICcgJfAdj+DvvW9ibzMPF68DDxhvK/82T1ZPXe9L/zJvOG8oby3/F68CXuaeyF6oXqfetM7fTuMPGG8ibzv/O/87/zZPVH9zL6DP2t/90BvgOCBSMHTQigCSILeg2GD9sRtBKXE7QSDBEhDhsKMgQj/t34ZPW/81H0ZPXl9eX13vS/8ybzJvO/89b2Mvpl/koCOAUjB+UHggdxBjgFrwQ4BXEGTQigCZwKnAoqCYIHzgU4BW8EVQN9AWP/jv1C/An8q/wj/uz/XwHdAUMB7P8A/gn8yPp++lH7Qvw5/SP+Cv/O/yMAMgCJALsB9wPIBhsK2gyGD9sRtBIMEXoNggd2AOL5ZPWG8t/x3/Hf8TDxevD07kztaexp7PTuhvLW9n76Zf0i/4r/g/6r/DL6fvgb+Bv4OPky+n764vkb+GD2ZPXe9FH0UfS/84byMPF68HrwMPGG8t701vZ++OL5DvuR+wn83fyh/g4BMgSCB68Lhg+XE30Wyhk+HOse1yEGJbkmWipJLE8uTy5JLH8oZSM+HHsVDBF6DUEMrwsiC5wKKglxBlUDZACh/kX+Iv+yAAACIwOJA5sCdgAM/d343vSG8jDxMPHf8YbyJvMm8ybzJvO/8ybz3/F68CXuaeyF6oPpg+mD6X3raewl7rvvMPHf8d/xhvK/8+X1G/gy+t38iv8AAr4DOAVxBrkInApBDCEOhg/bEZcTexV7FbQS0A4qCb4DOP9C/Mj64vk4+d34fvjW9t70v/O/89701vbi+Tn9nQD3A3EGggcjBx4G8gQyBK8EHgaCB7kIKgm5CE0I5QcjBx4GrwSJA90Bzv8A/t38q/xl/YP+3f9DAUoCmwLdAZ0Azv+c/77/FACyALsBmwLHAkoCfQFfAbsBmwL3A3EGoAkhDtsRexWKF4oXlxPQDrkIVQMK/877j/l++LP31vbe9IbyevC777vv3/FR9Ef3fvpl/Xf/QgCK/9z9kfuP+d343fjd+H74R/fl9d70v/Mm84by3/Ew8Xrwu+8l7mnsaex962nsJe4w8Ybyv/NR9N70ZPVg9rP3j/lC/M7/iQPIBqAJQQyGD9sRexWKF/0ajR3XIQYlfyhaKn8ouSZZIP0afRa0EtAO2gyvCyILGwrlB68EfQHY/mX9DP22/SL/yABKAlUDIwNDAbb9OPlk9Sbz3/Ew8XrwevB68N/xJvO/87/zv/OG8jDxu+9M7X3rg+l26IPphepp7CXu9O707rvvevAw8d/xv/Pl9Tj5Cfyh/vYAIwM4BSMHuQgbCq8Leg2GD7QSfRakGKQYiheXE4YPIgsjB74DmwF2AOz/Cv9l/Q77OPlH99b2s/fd+A773P1fAa8EIwflB4IHcQYeBnEGIweCB4IHggeCB4IHggcjB3EGOAVvBCMDmwGc/2X9zvtR+wn8DP22/bb9tv22/Y793fwJ/FH7UfvO+938tv0j/gD+tv2O/Y79Zf2O/b3+XwGCBSILRRCDFIoXiheDFAwRrwvIBvQCFABl/jn9zvuP+db2UfSG8jDxMPEw8YbyZPV++M77I/4i/wr/Rf5l/av8zvsO++L5fviz90f3YPZk9d70UfS/87/zhvJ68PTuTO1p7EztTO0l7rvvMPGG8r/zUfRR9FH03vTW9jj5zvuD/n0BrwTlB5wK2gzQDtsRgxSkGI0d1yEGJX8ofyi5JmUj6x79Gn0WlxPbEUUQIQ6vC00IggWbAjIAg/62/SP+Y/8OAZsCVQPHAsgAtv1++kf3UfTf8bvv9O6773rw3/GG8ibzv/NR9L/z3/G77yXuaex964XqheqF6n3rTO307rvvevC777vvu+8w8Sbz5fV++FH7I/6dAEoCVQP3A/IEcQa5CEEMhg+XE3sVfRZ9FoMUDBF6DaAJyAavBHICIwAA/gn8Mvp++Nb2ZPXe9GT11vY4+Qn88v5DAZsC9AJVA/cDMgT3A74DvgP3A28EbwSvBDgFggU4Ba8EvgObAl8BMgBO/6H+Rf4j/mX+OP9kAA4B3gD6/wr/vf7y/or/UwBDAUoC9ALHAt0BnQCc/4r/yAC+A00IIQ60EooXyhn9GqQYfRbbEdAOrwu5CM4FIwP2AKH+zvt++GT1JvPf8TDx3/G/89b2j/mR+3f83fzd/Hf8zvvI+o/5G/jW9mT1UfS/8ybzJvMm8ybzhvLf8TDxu+8l7kztaexp7Ezt9O4w8YbyJvMm84byhvK/8970YPY4+av8ZAC+A8gGKgmcCkEM0A7bEX0W/RrrHmUjuSa5JrkmBiXXIesePhzKGX0WlxMMEdAOQQwqCR4GIwPIADj/Cv9CACQCiQP3A4kDJAJTAAD+Dvsb+GT1v/OG8obyhvK/89705fXl9eX13vRR9Iby3/F68PTuJe4l7iXu9O568DDxMPF68HrwevB68DDxhvLe9LP3fvrd/Nj+BgCyACgBAAK+Ax4GKgnaDEUQlxN9Fn0WexWXEwwRIQ4iC+UH8gSbArIA8v7d/H76s/fe9CbzJvPe9GD2fvh++qv8vf5kAH0BSgL0AiMD9AJKAt0BAAJyAiMDiQO+A/cDvgNVA3ICXwFTACL/3P0M/Tn9I/5O/xQAnQAOAUMBKAGyAJ0A9gC7AZsCVQOJA/QCXwGc/2X+Zf7O/5sCcQYiC0UQgxSKF6QYpBiKF3sVlxMMEXoNnArlB4IFIwMGAEL8G/hR9N/xMPHf8Sbz3vTW9jj5kfsM/QD+g/6D/gD+3fxR+4/5fviz90f31vZg9uX1ZPXe9FH0JvMw8bvvJe4l7iXu9O568N/xJvNR9N70UfS/87/z3vTW9o/53fxkAIkDHgblB7kIGwpBDNAOtBJ9Fv0a6x7XIWUjBiUGJQYl1yFZID4cyhl9FoMUtBKGD0EMuQjyBHICDgGyAA4BAAIjA74DvgPHAvYA8v7d/Mj6fvjW9uX15fVg9mD2YPZg9mD2YPZg9uX1ZPVR9Cbz3/Ew8XrwevAw8YbyJvO/8ybzhvLf8TDx3/G/82D23fjO+0X+BgD2ACgBmwGbAq8EggecCiEODBGXE3sVfRaKF4oXexW0EoYPQQwbCk0IcQYyBA4Bjv3i+WD2UfQm8ybzv/Pl9Rv44vnO+7b9d//IAF8BQwH2AJ0AnQDIAMgAnQCdAMgAKAFDAQ4BIwDy/o79QvwO+zL64vl++pH7q/zc/UX+AP5l/Qz9Zf0A/oP+Iv+c/63/of7d/Mj6j/mP+Q77jv0OAa8ETQivC9AO2xGXE4MUlxPbEYYP2gwiCyoJIwevBH0BZf3d+N70MPG77/Tuu+/f8b/z5fVH9934MvpR+877kfsO+zL6j/nd+LP31vZg9mD2YPbl9WT1UfQm8zDxu+/07vTu9O677zDxJvNR9FH0UfS/87/zUfTe9Nb2OPl3/M7/JAKJAzIE8gRxBk0IIgvQDrQSfRbKGY0dWSBlIwYlBiVlI1kg6x4+HMoZihd7FbQShg+vC+UHrwRyAkMBQwHdAUoCAAJfAXYAY/8j/kL8fvrd+LP3R/dg9mD25fXl9WD21vbW9tb2YPbl9d70v/Mm84by3/Ew8d/xhvIm8ybzhvKG8t/xhvIm81H0YPbd+FH7DP1F/r3+8v44/wYAmwG+Ax4GTQgiCyEODBGXE4MUgxS0EkUQIQ5BDBsKuQiCBzgF3QHc/Y/5ZPWG8nrwevAw8d/xJvPe9Ef3j/lR+3f8jv1l/gr/Tv9O/4r/BgCJACgBAAL0AlUD9AIkAg4B7P/y/tz93fyr/GX9g/6c/4kAKAF9AX0BQwFDAd0B9AL3A68EbwS+AyQCIwC9/oP+zv/dAfcDHga5CEEMhg+0EoMUexV9FoMUtBIMEYYPIQ5BDKAJzgVfAUL8s/e/89/xMPEw8TDx3/Em8970YPaz9934j/ky+jL64vk4+X74s/fW9tb2YPZg9mT1UfSG8jDxevC77/TuJe4l7vTuevAw8d/xhvKG8oby3/Hf8Sbz3vRH9zL6DP3y/q3/3f92AAACMgTIBioJrwuGD5cTihc+HOse1yHXIdchWSCNHT4c/RrKGYoXexXbEXoNKgk4BXICDgEyAM7/rf+t/3f/vf6O/UL8Ufsy+jj5fvhH92D2ZPXe9N703vTe9N703vRR9L/zJvOG8t/x3/Ew8TDx3/GG8ibzv/O/87/zv/O/81H0ZPWz9zL6q/wj/r3+8v5j/1MAuwHHAr4DOAUjB6AJ2gxFELQSgxSDFJcTtBJFENAOIQ56DdoMGwpxBn0Bd/yz91H03/F68LvvevDf8SbzUfTl9db2fvji+Q77kfuR+5H7Cfzd/CP+nP/eAJsBmwEOARQA2P62/av8CfwJ/Hf8jv2h/vr/QwFKAvQC9AL0AlUDMgSCBcgGggcjB84F9wNyAn0BKAEOAUMB3QFVA84FuQhBDEUQtBJ7FXsVexWXE7QStBK0EgwR0A6vC8gGuwE5/Tj5YPbe9L/zv/NR9N70ZPVg9rP34vkJ/GX9tv05/UL8kfsO+8j6DvsO+8j64vnd+Ef35fVR9CbzhvLf8d/x3/GG8ibzv/NR9FH0v/Mm8ybzUfRg9t34zvu2/Qr/vv+dAH0BcgJVA28EHga5CEEMRRB7FcoZjR1ZIFkg6x6NHY0dPhw+HD4c/RqkGHsVDBF6DaAJIwfyBL4D9AJyAn0BFAC9/iP+I/4j/mX9Cfx++t34R/dg9mD21vZH97P3s/dH99b2YPZk9d70UfS/8ybz3/Hf8d/xJvNR9N70UfS/8ybzv/Pe9LP3Mvo5/d4AxwKbApsBBgCO/Qn8d/x3/H763fgb+N34Of0yBBsKDBGKFz4cjR39GooXlxPQDhsK9wNC/GT19O6D6YPpTO0m87P3kfur/EL8Dvvd+LP3j/lC/CP+vf4GAHYAsgB9AfQC8gTyBJsC3fxk9Xrw9O4w8d70fvpKAioJ2gwhDkEM5QfHAmP/3P3c/aH+8v5F/tz9of5yAuUHIQ7bEdsRRRBBDOUHMgQjA/cDyAYbCkEM2gyvC6AJoAlBDEUQexXKGf0apBjbEeUHZf3e9PTuTO1p7IXqg+lc51zng+kl7t70OP+gCYYPRRBBDPIEkfvf8YXqA+Vz4qffKd4p3qffwuOF6r/zAP7lB9AODBHQDs4FfviF6hXhm9z62qffwuN26EzthvLd+CQCeg2kGOseWSCNHXsVrwv0AgD+CfwM/UIAmwL3AzgFggdBDHsV1yFJLO407jRsMLkmpBicCk7/s/e/89/xu+9M7Wnsaey77xv49AIhDnsVpBiKF7QSKgk5/TDxdujC46ffKd6b3Pram9wV4YXqG/hxBrQS/RrrHj4cgxRNCJH7MPF961znA+XC48LjA+WF6r/zKAGGD/0a1yEGJdch/RrbEU0Irf/d+L/z9O6F6nboduhp7N70AAJFED4cBiW5JtchpBhBDIP+3/Fc56ffR9mm1bfTt9NH2QPlUfQyBLQS6x4GJbkmBiU+HNsRzgV++rvvXOcV4Zvc+tqb3Dbm3vTOBYoXBiVJLGwwSSwGJcoZeg1yAt343/Fp7HboNuZc5yXuOPmCB30WZSNJLE8uSSx/KFkgihchDs4F3P3W9rvvheqF6nrwQvzaDI0dSSzuNO40bDAGJaQYuQiP+Wnsp9+m1RLLhsOGwxLLgdeD6WX90A79GlkgWSDKGdAO9gCG8gPl+tqx0anIyMDIwIbDlM+n37/zHgaDFP0aPhyKF9AOcgLl9X3rwuOb3IHXt9Om1ZvcXOfd+EEM6x5JLO40VzfuNE8uBiXKGYYP5QeJAI/5UfS/8934bwSDFAYloTJ6PDg/ejyhMn8o/RraDK3/3vSF6nPim9z62qffg+kb+CMHgxSNHWUjZSPrHqQY0A70ArP3TO0D5ZvcptW306bVKd5961H7IguKF+se1yHrHooXQQwK/4byXOcp3oHXt9O300fZA+Xe9MgGihdlI0ksTy5JLLkm6x6XE00IOf3f8VznKd6B10fZFeFp7M77rwukGOse6x79GpcTTQgO+0ztFeG306nIhsOGw6nIsdEV4XrwXwEMEY0duSZJLE8uWiplI/0atBKcCiQCfvrl9VH0s/ec/68Lyhm5Jk8ubDBJLGUjpBgiC9j+v/OD6affR9mm1abV+tpz4iXufvojBwwRexV9FoMU2xGGD9oMoAkjA8j6hvJ964Pp9O6P+eUHihd/KKEy2jl6PNo5bDBlI4MUOAXl9XboKd6m1bfTt9Om1ZvcA+W77934dgDOBSMH9wO2/d70heop3rfTEssmxobDJsapyLHRp9/07tz9GwrbEZcTRRC5CMgAOPkm8yXufetp7DDx3fj3AwwR6x5/KE8ubDBPLn8o1yHKGdsR5Qd3/HrwNuan35vcp9+D6Uf3ggd9FlkgBiUGJdchPhx7FYYPggdF/lH0aex26IPpJe5g9iMAKgkMEX0W/Ro+HMoZfRbbEXoNGwojB4kD2P6P+b/z9O5p7LvvR/dDARsK0A7QDiILrwRC/FH0Je6D6TbmwuMD5Vzng+kl7lH0tv1NCNsRihekGH0W2xEhDq8LoAlxBjIAs/e773boNuZ26LvvyPpxBtsRPhxlI7kmBiXrHn0WnArd/PTuwuP62qbVt9O300fZFeF96+X1IwAqCYYPlxN9Fn0WlxN6DR4GsgAM/cj6OPni+d38uwGgCZcTPhzXIdchPhyDFJwKsgBH9yXuXOdz4qffFeF26L/zdgDaDH0WPhyNHY0dPhzKGYoXlxMhDiMH+v/d+CbzMPG/8wn8TQh9FmUjWipJLH8oZSP9GrQSKgmr/PTuc+JH2bfTsdGm1UfZp99c5/Tu1vbd/GP/g/53/FH7yPrI+lH7CfzI+rP3v/Pf8YbyR/fy/oIH0A6XE4MU2xHaDB4GRf5g9nrwTO1964PpNuY25lznaeze9GP/oAlFENsRDBHQDnoNrwu5CL4Dq/xR9Gnsduh26IXqMPF++s4F2xHrHn8oTy6hMmwwWirXIaQYIQ44BQz91vbf8Xrw3/Fg9t38MgSvCwwRgxR9Fn0WDBGgCXYAG/gw8X3rdugD5cLjNuZp7Nb2xwJ6DZcTgxQMERsKQwFH9yXuNuan3/ra+tqn33bov/MjAEEMfRaNHdch1yHrHj4cfRZFEKAJSgJ++obyaeyD6WnsUfTY/pwKexX9Go0d/RqkGJcTIgtDAeX1heoV4UfZptW307fTt9OB16ffXOe77970R/ez92D2v/Mm87/z5fUb+N34G/iz9934q/wjA0EMihfXIX8oSSxaKrkm6x6kGLQSIQ6vCyoJOAWdAI79q/w4/68EnArQDtAOQQy5CDgFuwGO/Rv4MPF26KffR9m307HRptWb3DbmJvPd/68LfRaNHVkg6x79Gn0WRRAbCokDjv0y+o/5UfvY/q8EQQy0EooXjR3XIWUjWSA+HHsVeg04BZH73/F26KffR9mB10fZFeFc5yXuMPEw8SXug+nC45vcptWUzxLLJsapyF/NgdcD5WT18gSXE1kgfyhsMKEy7jTuNO40bDBaKtchpBjbESEOhg+DFD4cZSN/KEksSSxaKgYl6x59FiILof7f8Tbmm9ym1bHRlM+Uz7fTR9kV4Vznaewl7vTuevCG8uX1fvpl/aH+Iv8jAN0BbwS5CEUQpBjXIVoqbDChMmwwWirXIaQYDBGcCm8Eof44+VH0evB68L/zR/d++pH7yPo4+bP35fVR9N/xTO025pvct9NfzanIJsapyF/NgdcD5b/zfQHaDIMUyhmNHY0dPhyKF0UQoAm+A9j+3fxl/t0BHgavC7QSpBiNHVkgWSDrHv0agxTaDG8ECfyG8lznKd5H2UfZm9wD5WnsJvNg9hv4R/dk9YbyJe5c5xXhm9xH2frap9926N70cgIMEY0dfyhsMO402jnaOdo5VzehMn8ojR20EhsKggVxBiILtBLKGVkgZSMGJQYlWSDKGUUQMgTl9Xbom9yx0anIyMDrvcjAJsaUz4HXp98D5Vzng+lp7Hrwv/Pl9bP3j/ni+Tj54vmr/AACGwqDFFkgWipsMKEyTy5/KNchyhm0Eq8LMgSR+ybzaeyD6YXqJe7f8d70YPZg9mT1UfS/84byu+996zbmp99H2abVsdGx0bfT+to25ibzmwHQDsoZZSNJLGww7jTuNKEyTy65JtchjR3KGcoZyhk+HOseZSMGJbkmuSYGJdchjR19FoYPIwd3/HrwwuP62qbVptWB1yneA+WD6X3raexp7H3rXOcV4UfZsdESy6nIqchfzabVFeEl7gz9rwuKF1kgfyhsMO40VzdXN2wwfyg+HAwR5Qf0AkoCbwS5CNAOgxSkGP0a/RqkGAwRggdC/Lvvc+Km1RLLyMDtus237brIwBLLptWb3HPiXOdp7HrwZPXi+WX9MgCbAjIEOAVxBqAJ0A6KF2UjbDDaOTg/FUIVQno8VzehMkksZSP9GtsRKglVA4kA+v8OAZsCxwJfAez/8v7c/UL83fiG8n3rA+Wn30fZptWx0bHRt9P62gPlevBR+4IF0A6kGOseBiW5JgYl1yGNHYoXtBLQDkEMnAqcCtoMDBGDFKQY/Ro+HD4c/RqkGIMU0A4jBwn8u+/C40fZt9Ox0bfTgdf62pvcp99z4nPiFeEp3oHXsdFfzanIJsYmxqnIsdEp3n3rj/nIBrQSjR25Jk8u7jTaOdo5VzdsMH8o6x6kGJcTtBJ7FaQYPhzXIQYlfyh/KLkmZSM+HJcTGwq9/t/xA+VH2bHRX81fzbHRgdeb3Kffc+ID5Xbofev07ibzs/fO+9j+9gDdAZsCOAUiC4MUWSBaKqEyVzfaOVc3oTJJLH8o1yHKGQwR5QfO/4/55fXe9FH0v/Mm81H05fVH90f33vQw8Wnsduhz4pvcptWUz6nIJsapyF/Nt9Ob3DbmMPF3/CMHRRCKFz4cjR0+HMoZfRaXE4YPQQycChsKrwuGD5cTihf9Go0djR2NHY0dPhykGAwR5Qer/N/xg+nC4xXhFeEV4cLjduhp7LvvMPF68CXufetc53PiKd6b3Pram9xz4n3r5fVDAa8LfRZZIH8obDBXN9o52jnuNEksBiU+HIMURRB6DXoNhg+0EooX/RqNHY0d/Rp7FYYP5Qcj/obyA+WB1xLLyMDrveu9yMAmxhLLlM+m1UfZKd5z4jbmg+kl7obyZPVk9VH0v/Nk9Q779wMhDqQYWSAGJbkmuSYGJdchjR2KF0UQKgkkAnf8s/dR9N/xevC773rwJvNk9db2YPbe9N/x9O5961znc+Ip3kfZptW307fTR9kp3jbm9O4y+h4GtBI+HGUjfyhaKloqSSxaKn8oBiXXIVkg6x6NHeseWSDXIdchZSNlI2Uj1yFZID4cgxScChQAYPYl7lznc+Kn3ynep98V4XPiwuPC4xXhm9xH2bfTlM8SyybGhsMmxhLLt9Mp3nboUfQjAEEMpBhlI1oqbDBsME8ufyjXIT4cfRbbEYYP0A5FELQSfRbKGT4cPhz9GooXtBJBDJsCYPZ26PralM+pyIbDyMDIwIbDqchfzbHRgdf62qffA+V964by3fg5/SL/7P/dAR4Geg19FtchWiruNNo5OD8VQhVCOD96PFc3oTJPLn8oZSONHaQY2xF6DSILGwq5CIIHOAVDAav8s/cm8yXug+lz4vraptWx0ZTPX82Uz7HRgden34XqR/ckApwKDBF7FcoZPhyNHT4c/RqKF4MU2xG0EpcTfRbKGT4c6x5ZINchZSNlI1kg/RqXExsK3f9k9X3rc+L62qbVt9O304HXgdeB14HXptWx0ZTPEsupyIbDyMDrvcjAhsMSy6bVp99p7H76Kgl9FmUjSSyhMu40VzfuNKEyTy5aKgYlZSNlIwYlfyhJLGww7jTuNO40oTJPLrkmjR20EnEGfvq77zbmKd5H2YHXgdeB10fZ+tqb3CneFeED5YXqu++/8+X1YPZg9rP3CfxVA9oMfRZZIH8obDDuNFc3VzfuNGwwSSy5Jtch/RqDFEEMOAX6/wz9d/w5/WX+g/7d/OL5YPYm8/Tug+nC45vcptVfzanIhsPIwMjAyMCpyLHRm9x26N/xfvpfAYIH2gzbEYMUexW0EkUQIQ56DdAODBGDFIoXPhxZIGUjuSZaKloqWiq5JlkgpBiGD68EMvow8YXqNuYD5TbmduiD6YPpXOc25gPlwuOn35vcR9mm1bfTt9Om1fraFeGF6mT19AJFED4cuSZPLu40VzdXN1c3oTJPLn8oZSNZIOseWSDXIbkmWipJLE8uSSxaKmUj/RoMEa8E1vaD6ZvcsdESy4bDyMDIwIbDqcgSy1/NlM+x0YHXm9xz4jbmduh26IPpfet68Nb2vf5NCLQSPhwGJVoqSSxJLEksWip/KAYl1yE+HHsVeg1xBn0Bvf5l/pz/iQAyAIP+zvvd+GT13/FM7Vznc+Ip3oHXsdFfzanIqchfzbfTp9+F6t70Rf7IBoYPpBjXIX8oSSxPLk8uSSxJLFoqWipaKkksSSxPLmwwoTLuNO407jShMk8ufyhZIHsVoAm2/Sbzfetc51znNuYD5cLjFeGn35vc+tqB17fTX82pyIbDyMDIwMjAJsZfzYHXA+W/85sChg/9GmUjWipsMKEyoTJsMFoqBiXrHv0apBikGP0ajR1ZIGUjBiUGJWUj6x6kGIYP8gTd+Gnsp9+306nIhsPIwIbDhsMmxqnIEstfzbfT+toV4Xboaez07rvv3/Fk9X76mwGcCnsV1yFJLO402jk4Pzg/OD8VQhVCFUI4P9o5oTJ/KFkgyhl7FbQSDBGGD3oNGwoeBrsBq/yz94byaew25qffgdeUzybGyMDIwIbDEsu305vcNuZM7WT1jv0eBnoNtBJ7FX0WexWDFLQS2xG0EoMUfRbKGY0dWSBlI7kmfyhaKn8oBiVZIIoXQQzy/obydugV4ZvcR9mB16bVptW307HRsdGUz1/NEssmxsjA673tus23zbfrvYbDlM8p3mnsfvojB7QSjR25Jk8uoTLuNKEybDBJLH8ouSa5Jn8oWipPLmww7jRXN1c3VzfuNGwwWirXIX0WGwqr/LvvA+Up3vraR9mm1bfTt9O306bVR9mb3HPiA+U25jbmNuZc54PpTO1R9I79TQiXE40dBiVaKkksTy5sMGwwbDBPLloqZSP9GpcT2gy5CMgGcQZxBnEGggW+AygBRf5++uX1MPFM7Vznp9+B11/NJsbrveu9yMAmxl/Nt9P62sLjTO3W9or/yAavC9AORRBFEEUQhg+GD0UQtBKDFKQYPhxZIAYlfyhJLE8uTy5PLloq1yGkGCEO8gQ5/bP3v/N68EztfeuD6YPpg+mF6oPpXOcD5RXhm9yB17fTlM9fzZTPptUp3oPpZPWJAK8LihfXIVoqbDChMqEybDBJLLkmZSNZIOseWSDXIQYlfyhJLE8uTy5PLloqBiWNHZcTyAZ++IXqKd6m1ZTPEsupyCbGJsaGwybGqciUz7fTgdf62vra+tr62vram9yn3wPlTO0b+McCQQy0EqQYPhxZIAYluSa5JgYlWSCkGNsRrwtxBlUDmwEOAV8BuwG7AQ4Biv85/cj6G/jl9YbyJe5c56ffgdeUzxLLEstfzbHRgdcp3jbmu+9++vIE0A59Fo0d1yEGJbkmuSYGJdch1yHXIWUjBiW5Jn8oSSxPLqEyoTKhMk8ufyjrHnsVrwubAsj6UfS7733rXOcD5cLjwuNz4hXhKd762oHXsdFfzSbGyMDrve26672GwxLLptUV4UztfvrlB4MU6x65JloqWip/KAYlWSA+HKQYiheKF8oZPhxZIAYlfyhaKloqWioGJesegxS5CFH7Je7C4/raptWx0V/NEsupyKnIEsux0abV+top3hXhc+LC48LjA+U25oXq3/FR+4IFhg+KF+seuSZJLKEyVzd6PHo8ejxXN6EySSy5Jlkg/RqkGH0WexWDFJcT2xEhDhsKzgW7ATn9R/d68FznKd6301/NqcipyKnIX82Uz6bVm9wD5SXuYPbd/EoCyAYiCyEOhg+GDyEOeg16DdAORRC0En0WyhnrHmUjfyhJLEksWioGJY0dgxQiC0oCMvqG8mnsNuZz4hXhFeEV4RXhp9+b3EfZptWx0V/NqciGw+u9673rvYbDX82m1afffes4+YIHgxRZIH8oSSxPLmwwTy5aKrkmZSPXIWUjBiW5JloqTy7uNFc32jnaOdo57jRJLNchexW5CNz9UfRp7APlKd5H2YHXgddH2fraKd6n3xXhc+Jz4hXhp9+n3xXhA+V96ybzQvzyBNoMgxQ+HGUjfyhJLE8uTy5JLFoqBiWNHX0WDBHaDBsKoAmgCRsKnAqcChsKuQgjBzgFcgIA/kf3TO1z4oHXlM8SyybGJsYmxqnIlM+B16ffduj07mT1Dvv2AHEGnApBDEEMrwsiCyILIgtBDNAOtBKKF40dZSN/KEksSSxJLH8oBiXrHooXRRDlByMAOPlR9N/xMPGG8ibzv/O/84by3/F68EztXOcV4UfZt9Ox0bHRt9OB1yneNuYw8bb9GwqDFI0dBiV/KFoqWiq5JtchjR39GqQYpBjKGT4cWSAGJX8oSSxPLk8uSSy5JusegxS5CI79JvOD6affgdex0V/NEstfzZTPt9OB10fZ+tqb3Jvc+tpH2YHXgddH2SneA+Vp7N70jv1xBtAOexX9Guse1yFlIwYl1yGNHaQYtBIhDhsK5QcjByMHTQi5CLkITQjlB4IHIwfOBfQCDP3e9GnsA+Wb3IHXt9OUz7HRptX62sLjfesm83763QGgCQwRihf9Go0d6x6NHY0dPhz9Gv0aPhzrHmUjfyhJLE8uTy5PLkksfygGJVkgyhkMEeUHOP8b+CbzMPF68LvvJe5p7IXqg+l26APlp99H2bHREssmxobDyMDIwCbGEsum1RXh9O7O++UHtBI+HNchBiUGJWUj6x79GooXexWXE4MUfRbKGY0d1yG5JloqWip/KAYljR17Fa8LcgJ++CXuwuP62rfTlM9fzZTPsdG306bVR9mb3Cnep9+n3yneKd4p3hXhwuOD6Xrw3fibAkEMexU+HGUjWipsMKEy7jShMmwwSSy5JlkgPhz9GsoZpBikGIoXexWXE9sRDBGGD9oMggeJAN34evBc56ffgdex0V/NlM+x0abV+toV4TbmaeyG8jj5iv+vBE0InAqvCyILoAnlB8gG5QecCoYPgxTKGeseZSMGJbkmuSYGJdchjR19FtoMVQN++r/zu+9M7X3rg+lc5zbmNuYD5cLjFeH62qbVlM+pyIbDyMDrveu9yMAmxpTP+tpc51H0mwEhDsoZ1yG5Jn8ofyi5JmUjWSDrHuse6x7XIbkmWipsMFc32jl6PHo82jnuNE8uuSbrHoMUKglF/t70TO126DbmwuNz4hXhFeEV4XPiFeGn3ynem9z62kfZ+tqb3BXhXOe77zj5uwGgCQwRpBiNHdchBiW5JgYlWSD9GoMUhg+vCxsKGwqcCq8LrwuvC0EM2gx6DXoNIgvIBvYAj/kw8VznKd6m1ZTPEssSy1/NlM+x0abV+tqn31znTO2/8+L58v5KAvcDMgT0ApsBDgGbAh4GIgsMEX0W/RrrHmUjuSZ/KH8ofygGJY0dexXaDIIFIwCr/OL5G/jW9tb2R/cb+H74R/dR9HrwheoD5affR9m305TPlM+Uz6bV+tpz4n3rYPZ9AdoMfRaNHdch1yHXIVkg6x79GqQYiheKF8oZPhxZIAYlWipPLmwwTy5JLLkm1yGkGNAOvgMb+EztA+Wn3/ragdem1abVptWB10fZ+tr62vraR9mm1bfTsdGx0bfTgdcp3jbmJe5g9tz9zgV6DYMU/RrrHtchWSA+HIoXtBIhDpwKKgm5CE0ITQhNCCoJnAraDCEO0A4hDq8Lgge7AX76MPF26KffR9mB16bVgdeB1/rap98D5YXq3/E4+QYAHgavC4YP2xHbEQwRRRBFENsRgxSKF/0ajR1ZIGUjuSZ/KFoqSSx/KGUjPhyXE68LMgSD/jL61vZR9IbyhvKG8ibzhvJ68GnsXOcV4UfZt9MSyybGyMDIwIbDJsZfzabVp9996934ggUMEaQY6x5ZIFkg6x4+HKQYexWXE7QStBJ7FcoZjR3XIbkmfyhaKn8ouSbXIcoZhg9vBDj59O5c5xXhm9xH2abVptWm1YHX+tqb3CneKd6b3PraR9mB14HXR9kp3gPlaexk9SP+yAaGD6QY1yFaKmwwoTJsME8uWiq5JmUjWSDrHo0dPhz9GqQYpBiKF4oXihd9FoMUDBGvCzIEUfsw8VznKd5H2bfTsdGx0bHRt9Om1frap9825n3revDl9eL5DP2D/mX+tv22/Qr/AALOBRsKeg3bEXsVyhnrHmUjuSZ/KAYl1yH9GoMUeg3IBvYAzvuz9970JvMm87/z3vTe9Cbzu+996zbmp9+B15TPqciGw4bDhsMmxqnIsdH62lzn3vQAAnoNexU+HFkg1yFlI9ch6x4+HP0ayhn9GuseZSN/KE8uoTJXN9o52jnaOVc3bDB/KOsegxScCiQCfvq/80ztdug25gPlA+UD5QPlA+XC4xXhKd762oHXptWm1UfZKd4D5X3rJvOR+/IE0A6KF40d1yFlI9ch6x79Gn0WtBJFECEOQQwiC5wKnApBDCEODBGXE4MUgxSXE4YPoAn2AEf3TO0D5Snegde305TPlM+x0bfTgdeb3HPiXOdp7Iby1vaP+TL6j/k4+Y/5DvuO/bIAMgTlB0EMDBF9Fj4c1yEGJbkmuSZlI1kg/Rp7FYYPoAkyBDIAAP6O/aH+FAAoAZsBKAGt/3f8s/ff8X3rwuMp3kfZt9Ox0bHRt9OB1xXhfevW9rsBIgu0EqQYPhyNHY0d/RqkGIMUtBLbEbQSexXKGeseZSN/KEksbDBsMGwwSSwGJT4clxMbCn0B3fgw8YXqA+UV4RXhFeFz4sLjA+UD5QPlc+Kn3/ragde307fTptWB1/raFeFc53rwMvpvBHoNgxTKGf0a/RqkGH0WtBKGD9oMnAq5COUHgge5CJwKeg1FEJcTfRaKF4oXexUMERsK3QHi+d/xheoD5affm9yb3CneFeHC43boJe5R9A77fQFxBioJoAmgCaAJoAmcCq8L2gzQDgwRgxSKFz4cWSBlI7kmuSa5JmUjWSD9GoMUIQ7lB/QCY/9l/Qz9Zf22/QD+tv2r/H76YPYw8YXqc+L62qbVlM8SyybGJsapyF/Ngddz4iXu3fj0Aq8LlxOkGP0a/RqkGIMUDBEhDkEMrwshDtsRihc+HNchuSZaKkksSSx/KGUjPhyDFEEMvgNR+ybzaex26APlwuPC48LjwuMD5TbmNuYD5XPip9+b3PraR9n62pvcp98D5Uzt1vZfAUEMexWNHWUjuSZ/KH8ofygGJWUjWSCNHf0ayhmkGKQYyhn9Gj4cjR1ZIFkg6x79Gn0Whg+CBwr/YPZM7TbmFeGb3Jvcm9yb3CneFeED5YXqu+9R9Ef3OPni+TL6fvoO+877DP04/3ICcQYiC0UQexX9GlkgBiW5JrkmuSbXIY0diheGDyoJvgOdAAr/of6D/qH+Cv8K/yP+kfuz99/xfevC45vcptWUz6nIhsOGw4bDqcix0UfZA+W77zL6bwR6DYMUpBjKGcoZfRaXE0UQhg+GD9sRexX9GlkgfyhPLqEyVzdXN+40oTJPLrkm6x59FnoNOAUj/t343vTf8bvvJe5M7WnsfeuD6TbmFeGb3EfZptW307fTptWB1yneNub07jj59AKvC9sRihfKGf0a/RqkGH0WlxNFEHoNrwsiC0EMeg2GD7QSfRb9Go0d6x7rHo0dpBgMESoJOP/e9H3rwuMp3kfZgdeB14HXgddH2Snec+I25oPpaewl7vTuu+968N/xJvPe9Ef3MvoA/gACcQavCwwRihc+HFkg1yFlI9chjR2KFwwRQQy5CHEGggU4Bc4FyAZNCCoJoAnlB/IEsgDO++X19O5c56ffR9m307HRsdGm1UfZp99c53rwOPlyAhsKRRCXE5cTtBIMESEOrwsbChsKrwshDrQSpBiNHWUjuSZ/KFoqfygGJesepBhFECMHI/5g9nrwaex26DbmA+UD5TbmXOdc5wPlFeEp3kfZt9Ox0V/NEstfzZTPptWb3APl9O5++F8BuQghDtsRlxOXE9sRhg/aDBsKTQgjBx4GzgVxBuUHnAohDrQSfRbKGf0ayhl9FtsRIgtKAjj5evCD6cLjp98p3pvcm9yn33PiXOdM7d/xZPUb+H76d/wA/mP/nQAkAjIEcQa5CCILIQ7bEXsVpBg+HFkgZSMGJWUj1yE+HIoX2xHaDCoJcQbyBDIEvgNvBPIE8gS+A18Bjv3d+CbzfevC4/rasdESyybGJsYmxqnIlM+m1Sneg+m/87b9HgZBDEUQDBFFENAOrwsqCSMHyAZNCK8LRRB7Ff0aWSBlIwYluSYGJWUj6x6kGAwRKgl9AX76UfT07oXqdug25jbmXOdc51znNubC4xXhKd5H2abVsdGUz5TPt9NH2RXhfevl9d3/oAm0EsoZ6x7XIdch1yFZIOsejR39Gv0ayhnKGcoZ/Ro+HOse1yEGJbkmuSYGJVkg/RqXE5wKKAF++DDxfetc58LjFeGn3xXhwuM25oPpaez07nrw3/GG8r/zUfTe9Nb2j/ll/X0BzgUbCtAOlxPKGeseZSO5Jn8ofygGJVkg/Rp9FtsRIQ4iC6AJTQjlB+UH5QcjB4IFxwIi/3763vQl7gPlm9y301/NqciGw4bDhsMmxhLLt9Mp3oPpUfQj/s4FrwvQDoYP0A7aDJwKKgkqCSIL0A6DFP0aWSC5JkksbDChMqEyoTJsMFoqBiXrHooXDBGcCvIE7P8J/Dj5s/dg9t70hvJ68GnsdujC4yneR9mm1bHRsdG300fZKd425rvvj/kjAyIL2xF9FooXihd7FbQSRRB6DUEMIgsiC68L2gyGD5cTpBg+HFkgZSMGJQYl1yH9GpcTnAqbAY/53/F96wPlFeGb3Pra+tqb3CneFeFz4sLjNuZc51znduh26IPpfetM7bvvhvJk9Tj53P2+A5wK2xGKF40dWSBZIOse/RqKF7QShg9BDKAJ5QflByoJIgvaDCEO0A7QDnoNIgvIBmQAfvh68Hboc+Kb3IHXt9O307fTR9mn31znu+84+bsBTQjaDIYPhg8hDq8LuQjIBoIFcQYqCSEOlxOkGOseBiV/KFoqSSxaKgYlWSD9GpcTeg0jB18Bd/zd+Nb2YPbl9eX1ZPW/84byu+996zbmp9/62qbVt9Ox0bHRt9OB16ffXOcw8cj6VQMbCtAODBEMEUUQ0A56Da8LGwrlB84FrwSCBYIHIguGD3sV/RrrHtch1yFZID4cfRbQDoIHzv8b+DDxheo25sLjc+LC4wPlXOeF6iXuevCG8t705fVH9374MvoJ/AD+BgAAAjIEyAacCtAOgxTKGese1yFlI2Uj1yHrHv0afRbbEXoNIgugCaAJIgtBDCEO0A6GD9AO2gxNCCQCMvrf8YXqc+L62rfTX80Sy6nIEsux0YHXp9+D6YbyfvrdASMHnAqvC5wK5QevBCQCnQDeAJsCzgUbCoYPgxTKGese1yFlI9chWSA+HIoX2xGvCzIEZf2z97/z3/F68HrwMPHf8Yby3/F68EztdujC4yneR9mm1bfTt9Om1UfZFeGD6VH0Y/8qCQwRfRbKGT4cPhw+HD4c/RqkGH0WgxS0EtsRtBKDFKQYPhxZIAYluSa5JgYl1yE+HH0W0A4jB73+1vZ68H3rduhc51znduiD6YXqaexM7UztTO1M7SXu9O568N/xv/Ng9jj5q/yyAIIFIgsMEYoXPhxZINch1yFZIOse/Rp9FtsRIQ4iC6AJKgkqCRsKIgtBDNoMQQwbCh4GyAB++ibzfetz4kfZsdGpyIbDhsOGw6nIX82m1SneXOd68N34iv9vBMgGggceBvcDAAJfASQCbwRNCHoNgxT9GtchuSZaKkksTy5PLkksWioGJesepBjbEUEM5QevBMcCuwEoAbIAnP9l/eL5ZPV68IPpwuMp3kfZptW307fTgdcp3nbohvIM/YIFrwuGD9sRtBK0ErQS2xGGD3oNIgsqCU0IuQicCiEOtBKKF40dWSBlI2Uj1yHrHv0aexXQDnEGtv3l9fTug+kD5cLjc+IV4RXhc+Jz4nPic+Jz4sLjwuMD5QPlNuZ26IPpaey777/z3fi9/vIEnApFEIMUpBj9Gv0ayhmKF5cTRRDaDJwKoAmgCSIL2gyGDwwRtBK0EgwR0A6vC+UHxwJ3/N70aexz4vraptWx0bHRt9OB1yneA+V967/zyPpfAR4GTQhNCCMHOAW+A/QC9wNxBpwKRRB9Fj4c1yEGJX8ofyhaKloquSZlI+sepBi0EnoNuQiCBYkDcgIkArsBDgH6/yP+UftH99/xfesD5Snegdex0V/NX82x0YHXp9+D6d/x3fiD/nICggWCB7kIKglNCB4GiQPIAIP+Zf2O/Yr/IwNNCHoNtBJ9FsoZPhw+HD4cpBiDFCEOyAYi/xv43/FM7YXqg+l26Hboduh26IPphepp7CXu9O568Ibyv/Pl9Uf3j/kJ/Jz/9wNNCNoMDBF7FcoZjR3rHlkgWSCNHf0afRa0EoYPIQ56DSEORRDbEYMUexWDFJcTDBEhDqAJrwTy/rP39O425pvcptWx0V/NX82Uz7fTR9mn31znu++z99z9AAIyBDIEmwIjAI79Cfx3/PL+9ALlB9oM2xF9FsoZjR1ZINch1yHrHj4cihcMEa8LHgbdAQr/Of1C/An8d/wM/d38zvuP+WD23/Fp7Dbmp99H2bfTlM+Uz7fTR9lz4n3rUfRC/FUDKgkhDgwRlxN7FXsVgxS0EkUQIQ7aDHoN0A60En0W/RrrHtchBiUGJQYlZSNZIP0agxRBDPIEg/6P+eX1JvMw8bvvJe5M7WnsfeuD6XboXOdc51znXOd26IPpfesl7t/xZPXi+b3+vgMqCdAOgxSkGD4cjR2NHf0apBiDFIYPQQwbCqAJGwoiC9oM0A6GD4YP0A7aDJwK5QeJA4795fVp7HPiR9mx0RLLqcipyKnIEsuUz6bVKd425iXuZPXI+tz9g/5l/ZH74vk4+TL6Of2bASMH2gy0EqQYjR3XIbkmWipaKloqfyhlI+se/Rp9FtsR0A7aDK8LIgsbCqAJTQjOBZsCg/44+SbzfevC4/raptWx0bHRt9NH2RXhduh68Nb2d/zeADIEyAblB7kITQgjBzgFxwL2AHYAXwH3A4IHQQwMEX0W/RrrHtchZSPXIese/RqXE9oMzgV3/zL65fXf8fTuaeyF6oPpduhc5zbmA+XC48Ljc+IV4RXhFeFz4sLjNuaD6Uzt3/HW9qv8IwOgCYYPgxSKF4oXfRaDFAwReg0bCk0ITQigCUEM0A7bEYMUfRaKF4oXihd9FoMUhg9NCL7/1vYl7lznFeGb3PraR9n62pvcc+J26PTuZPUO+2P/fQGbAUIAZf7d/N38Zf4OAa8EKgl6DdsRfRbKGY0d1yFlI2Uj1yHrHv0aihe0EtAOrwu5CIIHIweCB+UH5QflB8gGbwQoAQn8ZPVM7cLj+tq305TPX82Uz7fTR9mn3zbmTO0m8xv4Cfx3/90BxwJyAsgAg/4J/DL6OPk4+VH7I/4AAsgGrwsMEXsV/RqNHesePhzKGYMU0A4qCYkDof5++rP3ZPVR9CbzJvOG8t/x3/Ew8Xrwu++777vvu+968IbyUfTW9o/5d/wUAG8EKgkhDrQSihfKGf0a/RrKGX0WlxNFECEO2gzaDCEORRC0EoMUexV7FXsVgxSXEwwReg3lB50Afvh68HboFeH62qbVt9O306bVR9kp3sLjhep68GD2yPoM/bb9DP2R+zL6j/l++t38rf8jA4IHrwtFEHsVyhk+HOse6x6NHT4cpBiDFEUQrwvlB/IE9AIAAgACcgL0AiMDIwNyAlMAQvzl9SXuNuYp3oHXsdGUz7HRptX62nPig+kw8bP33P0jA4IHnAraDCEOIQ7aDCILoAm5CCoJIgt6DUUQgxSKFz4cWSBlIwYlBiXXIeseyhmDFIYPGwqCBX0BZf4J/H763fhH92T1JvMw8fTuaeyF6nboXOdc53bog+l960ztevBR9N34I/73A6AJ0A6XE30WihekGIoXgxTbESEOnAoqCbkIoAmcCkEM2gx6DSEO0A4hDnoNIgsjB0oCzvtR9H3rwuP62qbVlM9fzRLLEstfzbfTR9mn31znJe4m89b2G/gb+Ef3R/cb+OL5q/x2APIEGwpFEH0WPhxZIAYluSZ/KFoqWip/KAYl1yHrHv0apBh9FnsVgxSXE7QS2xFFECEOnAo4BYP+YPYl7jbmKd5H2YHXgdf62qffA+V96zDxYPYO+/L+JAKvBHEGyAbOBTIEJALIAIkAXwEjAx4GoAkhDrQSihc+HOseWSDXIVkgPhykGJcTIQ5NCMcCI/5++kf33vSG8nrwJe5964PpNubC43PiFeGn36ffp9+n3xXhc+ID5Vznaezf8Rv4of7yBBsKIQ7bEbQStBIMEdAO2gycChsKIgvaDNAO2xGDFH0WpBjKGf0a/Rr9GqQYgxRFEBsKxwJR+7/zTO1c58LjFeGn36ffc+I25oXqu+9R9LP3MvoO+w77yPoO+877Of13/5sCcQYiC0UQgxSkGD4c6x5ZIFkgWSDrHo0d/RqKF3sVtBIMEUUQhg+GD4YPRRBFEIYPeg2gCTIEOf3e9GnswuOb3KbVsdGx0bHRptX62qffwuOD6SXuhvJg9o/5DvuR+3763fhg9t70v/NR9OX1fvh3/JsBggd6DbQSihf9Gj4c/RrKGX0W2xHaDE0IbwRDAdj+Of1C/FH7fvrd+Ef33vSG8nrw9O4l7kztTO0l7vTuu+8w8SbzZPV++Kv8QwEeBpwKIQ4MEZcTlxOXE9sR0A7aDK8LIguvC3oNhg/bEYMUfRaKF4oXiheKF3sVtBLQDioJmwIO+7/zTO1c53Pip9+b3Jvcm9wp3nPiNuZ967vvv/Pl9db21vbW9mD2YPZH9374DvtF/koCcQacCiEO2xF7FYoXyhnKGaQYiheDFNsRIQ6vC7kIggcjB+UHuQgbCiILIgugCYIHIwMM/eX1TO0D5Snegde307fTptVH2SnewuOD6SXuJvMb+Az9DgH3A4IFzgU4BW8E9wO+A68EcQYqCUEMRRCDFIoXPhzrHtchZSNlI9chjR3KGXsVDBF6DSILKgnlB3EG8gSbAq3/Qvzd+N70MPEl7n3rg+l26Hboduh26IPpaex68GT1Mvp3/28EKgl6DQwRtBKXE5cT2xFFEHoNrwsbChsKnApBDHoNhg8MEdsRtBK0ErQS2xGGD0EMyAYGAH74evCD6XPim9xH2abVt9O306bVR9mb3HPiNuaF6kztJe707vTu9O677zDxUfQb+EL8yACCBRsK0A6XE4oXPhzrHtch1yFlI9chWSDrHo0d/RrKGcoZpBjKGcoZyhmkGH0WlxPQDrkIDgEb+PTuXOcV4Snem9wp3qffwuNc54XqJe6G8uX1j/lC/Lb93P05/Qn8Dvt++lH7q/wK/0oCHgYbCtAOlxOKFz4cWSDXIdchWSCNHcoZgxRFENoMoAkjB68EmwLIANj+d/yP+eX13/El7oXqXOcD5XPiFeGn36ffp98V4cLjXOdp7N/x1vbO+3YArwSCByoJKglNCMgGggWvBPIEzgXlBxsKeg2GD9sRlxN7FYoXpBjKGcoZpBh7FUUQIgvyBPL+OPm/8/Tuhepc5zbmA+Vc54Ppaey779/xhvIm8ybzJvMm87/zZPUb+FH7vf6bAnEGoAnaDEUQlxN7FYoXihekGIoXfRZ7FZcT2xEMEQwRDBHbEbQSlxOXE5cTlxMMEXoNTQj2AH74u+825qff+tqB14HXgddH2ZvcKd5z4jbmheol7nrwhvKG8t/xMPG77yXuJe707jDxUfSz9877iQAeBq8LDBF7FaQYyhmkGIoXgxQMESEOQQwbCrkIggfIBoIF9wNKAhQAjv0O+9341vZk9b/z3/Ew8Xrwu+968N/xv/Ng9uL5jv3dAR4GGwraDNAO0A4hDtoMIgugCbkIKgkbCkEMIQ5FENsRtBKXE3sVfRaKF4oXexW0EtAOGwpvBCL/Mvpk9Xrwfetc58Ljc+Jz4sLjNuaD6Uztu+8w8d/xMPF68HrwevAw8Yby3vQb+FH7of4kAs4FKglBDNAODBG0ErQStBIMEYYPeg0iCxsKoAmgCZwKrwvaDCEO0A7QDiEOIgsjB7IA3fgw8YPpwuOn35vcm9yb3CneFeHC43boTO3f8Uf3zvsK/8gAXwEoAd4AsgAOAQACiQM4BeUHnAohDrQSihf9GuseWSDXIVkg6x4+HMoZihd7FZcTtBLbEUUQ0A5BDCoJggVfAav8G/i/83rwJe5964Ppduh26Hbohepp7PTuJvOz93f8XwGCBSoJIgvaDEEMIgugCYIHHgaCBR4GggcqCZwKrwvaDNAORRDbEbQStBLbEdAOnAoeBvYAUftk9bvvg+kD5affm9z62vram9wp3nPiA+Vc54Ppfetp7EztJe707jDxv/Ng9o/5q/yJAPIEKgl6DQwRgxSkGP0ajR3rHusejR2NHT4c/Rr9GsoZ/Rr9Gj4cPhw+HD4cyhl9FgwRGwokAuL5hvJM7XboNuYD5cLjA+U25nboheol7t/x3vRH9934j/mP+Tj5fvh++Dj5MvrO+7b9+v9VA+UH2gy0EooX/RqNHesejR0+HKQYexW0EgwR0A56Da8LGwq5CMgGvgPd/5H71vYm8/Tufetc58LjFeEp3inem9wp3qffc+I25oXq9O6/8xv4CfyK/7sBcgIkAigBdgCJAEMBmwJvBHEGuQicCtoMhg+0EnsVihfKGcoZyhmKF5cTRRBBDE0IVQPc/X74JvO772nsheqF6n3raewl7vTuu+968HrwMPGG8r/z5fUb+DL6DP0yAFUDHgZNCJwK2gzQDgwRlxODFHsVexWDFJcTtBK0ErQStBKDFHsVfRaKF6QYpBiKF3sVhg+5CHYAG/h68IPpwuOn35vc+tr62vram9yn33PiNuaD6X3rTO1M7Uztaexp7GnsTO0l7vTuMPG/80f3Cfy7AeUHeg20En0WpBikGIoXfRZ7FZcTtBIMEUUQRRBFEEUQ0A7aDBsKggdvBH0Bg/6R+934YPa/84byMPF68DDxhvLe9Ef3fvrc/V8BrwQjB00IKgm5CE0IIwfIBiMHTQigCSIL2gzQDkUQ2xGXE3sVfRaKF4oXihd7FdsR0A4iC+UHvgMK/+L5UfS772nsg+l26HboduiF6n3rfetp7Gnsaexp7GnsTO0l7rvv3/FR9Ef3MvoM/b7/JAKvBCMHKgkiC0EMQQxBDCILnAqgCbkITQi5CCoJnApBDCEORRAMEQwR0A4iC4IFvf6z9zDxfes25nPip98p3inep98V4cLjduhp7DDxUfRg9rP3fvg4+TL6UfsJ/Kv8Zf2h/t4A9wOCB68LRRCXE30WpBjKGcoZyhnKGaQYpBiKF4oXiheKF4oXfRZ7FdsR0A4bCoIF9gBC/LP3v/O772nsg+l26FznXOd26H3rJe7f8WT13fhC/CL/DgGbAQ4BMgBj/9j+of7y/s7/KAHHAm8EHgblB6AJrwt6DdAO0A4hDkEMnAq5CHEGVQMi/zL6ZPW7733rXOcD5cLjwuPC4wPlNuY25lznXOd26HboduiD6YXqaez07oby5fU4+av83f8jA3EGGwp6DUUQlxN7FX0WiheKF4oXihekGMoZ/Ro+HI0djR3rHusejR39GooXtBJBDB4Giv+P+VH0u+9p7IXqduh26Hbohepp7PTuu+968HrwMPEw8d/x3/Hf8YbyJvNR9OX1fvgJ/EIAOAUbCiEO2xGXE3sVfRZ7FYMUlxPbEQwRRRBFEEUQRRBFENAOQQxNCDIErf8O+9b2hvIl7oXqXOfC4xXhp9+n3xXhc+ID5Xboaex68FH0R/fi+VH7Qvyr/N38Of3c/Qr/3gD0AjgFggcbCnoNDBGDFH0WpBjKGf0a/Rr9GsoZpBh9FpcTRRCvCyMHcgKD/lH73fjW9uX13vRR9FH0UfRR9FH0v/O/81H0ZPXW9jj5QvxO/7sBvgOCBSMHuQgbCq8Leg0hDtAO0A4hDnoNeg0hDtAOhg8MEbQSgxR9FooXpBikGIoXlxPQDrkISgLO++X1evBp7HboA+XC43PiwuMD5TbmXOd26IPpheqF6oXqheqD6YPpg+mD6YPpfesl7t/x5fV++iL/iQPlByILIQ6GD4YPhg+GD9AO0A7QDkUQ2xGXE5cTlxPbEYYPQQwqCc4FxwK+/6v8OPlg9r/z3/Ew8TDx3/G/82T1R/fd+A773fyD/r7/sgBfAX0BfQGbAUoCVQOvBB4GTQicCnoNhg8MEbQSlxODFIMUlxO0EtsRDBGGD3oNGwpxBkoCI/7i+eX1JvN68PTuTO1p7Gnsfet9633rfet9633rfetp7CXuevCG8t701vZ++DL6CfyD/igBvgPOBSMHggflB4IHggeCB+UHTQigCZwKQQwhDkUQ2xGXE5cTtBJFENoMggebAVH73vT07oXqNubC43PiFeFz4sLjNuZ26IXqaez07jDxhvJR9GT11vaz9934fvp3/PL+uwHyBLkIQQyGD7QSexWKF8oZyhnKGaQYpBikGKQY/Ro+HI0djR0+HKQYexUMEUEMggfHAtz93fi/87vvfeuD6XboXOd26IPpfesl7nrwhvJk9Uf3OPky+sj6UfuR+5H7zvt3/I79Iv/eAMcCrwTIBrkInApBDHoNeg16DXoN2gyvC5wKTQiCBSQCZf4y+uX13/H07mnshep26FznXOdc53boduh26Hboduh26IXqaez07t/xUfTW9n74yPo5/UIAvgOCB5wKIQ5FENsRlxODFHsVihekGMoZ/Rr9Gj4cjR3rHlkgWSDrHo0dyhl7FYYPoAn3Awr/yPrW9r/zMPG77/Tu9O6777vvu++777vvu+968HrwevB68DDx3/Em81H0YPbd+An8Tv/HAnEGGwp6DUUQtBKXE5cTtBK0EpcTgxR7FX0Wihd9FnsVlxNFEHoNoAmCBbIAzvtg9jDxaex26APlwuNz4sLjwuMD5Tbmg+l96yXuMPEm81H0ZPXl9eX1YPZH9374fvp3/KH+yABVA3EGoAlBDNAODBG0EpcTexV9FooXiheKF30WgxTbEdAOIgvIBscCCv8J/OL5fvhH92D2ZPVR9Cbz3/Hf8Sbz3vRH94/5Ufvd/CP+Iv9kALsBVQPyBHEG5QcqCaAJoAkbCq8L2gzQDkUQDBHbEbQSgxR9FooXyhnKGcoZpBh7FQwRrwtxBkMBCfzW9obyJe5964Ppg+mD6YPpg+mD6YPpg+mD6YPpg+mD6YPpg+mD6YPphepp7PTu3/Fk9Tj5Of1DAfIE5QcbCiILrwtBDNoM0A5FELQSgxR9Fn0WfRZ7FZcT2xGGD9oMGwrIBscCg/7I+hv45fXe9FH0UfRR9FH03vTl9Uf33fgy+pH7QvxC/An8zvtC/Dn98v7IAJsCbwTIBqAJQQwhDoYPRRBFEEUQhg+GD4YPhg+GD4YP0A56DSILggf3A+z/Qvzd+GD2v/OG8jDxevD07iXuaexp7H3raexM7fTuu+8w8YbyUfRk9WD2s/eP+ZH7jv3y/or/7P+JAH0BxwIyBIIFyAblByoJnApBDCEORRC0EpcTlxO0EgwRIQ6cCsgGSgKO/d343vTf8bvvJe5M7WnsaexM7SXu9O6773rw3/GG8lH0ZPXW9rP3fvg4+cj6q/wi/90B8gRNCK8LIQ5FENsRlxOXE4MUfRakGP0ajR3rHtch1yHXIVkgjR39GooXtBIhDrkIvgPy/g77s/dk9b/zhvIw8TDxMPHf8YbyUfTl9bP3fvjd+Dj5OPmP+Y/5MvrI+pH7d/yO/fL+yAD0AvIEyAa5CKAJoAmgCaAJoAmgCRsKGwqgCU0IHgb0Anf/zvt++OX1JvPf8bvv9O5M7WnsheqF6oXqhep962nsJe6779/xJvNR9OX1G/h++mX9UwDHAvIEyAZNCBsKQQzQDgwRtBKDFHsVihekGMoZPhyNHeseWSBZIOsejR39Gn0WtBLQDiILIwe+A2QAjv0O+934R/fl9VH0JvPf8Xrwu++777vvevB68DDxMPEw8d/xJvNR9GD2OPlC/Jz/9ALOBeUHoAmcCq8L2gwhDoYPDBGXE3sVfRaKF4oXfRZ7FZcTDBFBDIIHJAKr/LP3JvO772nsg+l26FznNuY25jbmXOd26IPphepp7EztJe707rvvevAw8YbyJvNR9OX1G/jI+tz9sgBVA4IFgge5CBsKrwt6DYYP2xGXE4MUgxS0EkUQeg2cCiMH9wNDAdj+d/zi+Uf33vQm89/xMPEw8Ybyv/Nk9db2fviP+cj6zvsM/UX+OP8GAJ0AKAG7AccC9wOCBSMHuQigCZwKrwtBDHoN0A4MEbQSgxR7FX0WexWXEwwRIQ6cCs4F3gDO+9b2JvO770ztfeuF6oPpduhc5wPlwuPC48LjA+UD5QPlNuY25jbmXOdc54Ppfesl7t/x3vQb+JH7Rf6JAJsCMgTOBYIHKgkiC9oMhg8MEbQSlxODFIMUlxPbEYYP2gygCXEGIwMyANz9zvsy+jj5fviz90f3R/ez9374OPni+TL6fvrI+lH7Cfzd/Lb9vf7d/18BVQOCBYIHoAmcCq8LQQxBDK8LrwuvC9oMIQ6GD0UQRRCGDyEOrwu5CM4F9AIyAGX9yPob+OX1v/OG8jDxevC777vvu++773rwMPGG8r/zZPVH99344vkO+877d/wM/QD+Tv+yACQCVQOvBM4FyAaCB00IKgmcCkEMIQ5FENsRtBKXE7QS2xGGD0EMTQiJA/L+fvrW9r/zMPG77yXuTO1964Xqhep962nsJe677zDxJvNR9GT15fXW9rP33fh++nf8vf4oAVUDggWCB6AJQQzQDgwRtBJ7FYoXpBj9Go0d6x7rHusejR0+HKQYexXbEXoNKgk4BV8BI/5R+9341vbe9L/zJvMm8ybzv/NR9GT1YPbW9hv4OPky+jL64vmP+Y/5MvpR+zn9OP8oAZsCiQP3A/cDvgNVA4kDMgSCBcgG5QflB8gGOAUjA94ARf7O+934YPa/8zDx9O5M7WnsfeuF6oXqg+mD6YPphepp7CXu9O568IbyUfRg9n74MvrO+4793f9KAvIE5QecCnoNRRDbEZcTgxR7FX0WihekGMoZ/Rr9Gv0aPhz9GsoZiheDFAwReg2gCR4G9ALs/wz9MvpH99703/G77/TuJe4l7vTu9O6777vvevB68DDxMPHf8Sbz3vTW9t34Ufu2/Z0AvgMeBuUHKgkbCiIL2gzQDgwRtBKDFHsVexWDFJcTDBEhDpwKyAabAkX+Mvpg9obyu+9M7X3rg+l26FznXOdc51znduiD6X3rTO0l7vTuu++773rwMPGG8lH0YPbd+M77of72AMcCvgOvBB4GTQicCnoNRRC0EoMUexV7FYMUlxMMEdAOrwtNCG8EyAC2/ZH7Mvo4+X74s/dH97P3G/g4+eL5yPrO+wz9AP6h/r3+of7Y/jj/+v/eAN0BIwOvBHEGuQicCkEMeg3QDoYPRRAMEbQSgxR9FqQYyhnKGaQYiheDFAwReg0qCTgFKAGO/TL6R/e/83rwTO2F6nboXOc25jbmNuY25gPlA+UD5QPlNuY25lznduiD6X3rJe7f8WT1OPmr/E7/XwEjA68EcQZNCJwKeg1FELQSgxR7FX0WfRZ7FYMU2xGGD0EMKgkeBr4D3QFCANj+Zf2R++L5G/hg9mT13vRk9WD2R/ez93743fg4+TL6Ufur/IP+ZAByAvIEIwe5CBsKnAqcCpwKIgtBDHoN0A5FENsRtBKXE4MUlxO0EgwR0A6vC00IOAVyAgYAAP4J/DL6fvhH92D25fXl9eX15fXW9kf3G/jd+N34OPmP+eL5fvoO+1H7kftC/GX9Cv9DAVUDrwQ4BYIFOAWCBXEG5QcbCkEMIQ5FEAwRDBFFECEOrwsqCYIFJAIK/wn8j/nW9lH03/G77yXuJe5M7SXuJe707nrwhvJR9GT15fVg9tb2R/ez9xv4OPkO+2X9FAD0As4FTQicCtoM0A4MEZcTfRakGP0aPhyNHese6x7rHo0dPhzKGX0W2xF6DaAJyAZvBEoCBgC2/VH7OPnW9mT1UfRR9N70ZPXl9eX15fXl9eX1YPZg9tb2R/cb+I/5Dvt3/GX93P1F/oP+vf4K/2P/7P/eAEoCvgM4BR4GcQYeBjgFVQMoAYP+zvs4+db23vQm8zDxu+8l7kztaexp7H3raexp7EztJe707rvvevAw8d/xJvNR9OX11vZ++A77Zf4kAoIFTQgbCiILrwtBDEEM2gwhDkUQ2xGXE4MUexV9Fn0WexWDFLQSRRB6DZwKggcyBLIAZf1++rP3ZPWG8nrw9O5M7UztTO1M7UztTO1M7UztTO1M7SXuJe677zDxv/PW9o/5Cfwj/pz/3gAkAokDggWCByoJIgvaDCEOhg9FEAwRDBHQDkEMuQjyBF8BRf5R+3745fW/8zDx9O5p7IPpduh26Hbog+mD6YXqhep9633raexp7Ezt9O568IbyUfRg9n74fvp3/AD+Iv8yAJsBiQPOBbkIIgshDgwRlxODFHsVexWDFLQShg/aDKAJHgZVA/YA8v45/c77fvri+Y/54vky+g77kfsJ/Hf8q/zd/Dn9jv22/WX93fyr/Dn92P4oAfcDyAYqCRsKnAqcCpwKnAqvC9oMIQ5FENsRlxODFHsVexWDFLQSDBHQDq8LTQhvBN4Ajv1++kf3v/Mw8SXufeuF6oPpduh26Hboduh26Hboduh26Hbog+mD6X3rTO168L/zYPbd+A77DP0i/18BvgMeBrkIIgt6DYYP2xGXE3sVfRZ9Fn0WexWXE9sRhg8hDnoNQQwiCxsKTQjOBYkDKAFO/yP+jv1l/Qz9DP3d/Az9tv2h/q3/sgDdAfQCMgQeBk0InAqvC9oM2gzaDEEMrwsiC68L2gwhDkUQ2xGXE4MUgxSDFLQSRRB6DZwK5QeCBSMD9gDy/gz9Ufvi+Rv41vZg9uX15fXl9eX15fVg9mD21vbW9tb25fVk9WT15fXW9jj5kfvc/Xf/dgDeAMgA3gBfAXICvgOCBYIHKgmcCq8LQQzaDNoMQQwiCyoJyAb3A0MBof5C/OL5R/fe9IbyMPG777vvu+968N/xhvK/89705fVg9tb21vZg9mD2R/fd+H76q/wK/30B9wPOBeUHoAmvC3oNRRC0EoMUihfKGf0aPhw+HD4cyhmKF4MU2xHQDkEMnAq5CMgGMgQOAdz9yPp++Nb2YPbl9WT13vTe9N703vTe9GT1ZPVk9WT15fXW9n74MvoJ/I79g/7Y/qH+Rf7c/Y79tv1l/s7/XwH0AjIEOAWCBTgFrwRVA5sBTv+r/DL6s/fl9VH0hvIw8bvv9O4l7kztTO1M7UztTO0l7iXuu+968DDxMPGG8ibz3vRH98j6Iv8jA8gGKgmcCq8LQQxBDEEM2gx6DdAORRAMEbQSgxR7FYoXiheKF30WgxS0EgwR0A7aDBsKIwe+AwYAd/w4+db2ZPVR9L/zJvOG8obyhvLf8TDxevC77/Tu9O6773rwhvJk9bP3Mvrd/PL+sgAkAlUDrwTIBrkIIgt6DdAODBHbEbQStBLbEYYP2gwbCuUHHgYyBEoCMgDc/Q77G/hk9SbzhvIw8Xrwu+/07iXuJe707rvvu++777vvu+8w8Yby3vRH9zL6q/y9/kIAQwGbAQACxwK+A68EzgUjB+UHuQigCaAJKgnlB4IFmwJCAHf/Tv8GACgB3QG7AQ4BUwCJAHICggUqCa8Leg16DdoMIgtNCIIFxwIi/376ZPV68H3rduhc54PpTO0m8zj5Zf6bAjgFyAagCdAOlxPKGese1yEGJbkmBiUGJdch6x7KGXsVIQ5vBDj5Je7C4/rat9Ox0bHRt9Om1UfZKd4D5Wns3vSO/fIEGwraDNoMnAqCB74Dd/9R+0f3hvJM7TbmKd5H2abVgdf62hXhg+kw8bP3g/7IBoYPpBhZILkmSSxsMKEyoTJsME8uSSy5JlkgpBh6DTIAhvI25pvcgde306bVR9kp3sLjheqG8gn8ggXQDooXjR1lI7kmuSYGJdchjR2KF9sRrwsyBJH7JvN961znNuZc533ru+9R9N34Of2bArkIhg99Fo0d1yEGJQYlZSONHYoXhg/IBo79v/N26JvcsdESy4bDyMCGwybGX82m1ZvcA+W77zL68gSGD6QYWSAGJbkmfyi5JmUjWSD9Gn0Whg/lB6H+ZPVM7Tbmc+IV4XPiXOcl7mT1jv3OBXoNgxT9GlkgZSO5JrkmBiXrHqQY2xGcCvQC4vn07sLjgddfzYbD673rvYbDqcix0fraA+W771H7ggeXE+sefyhsMFc32jnaOVc3oTJPLrkmPhwMEa8E3fj07jbmFeGn3xXhwuN26EztJvOP+WQA5QeGD4oXjR1lI7kmfyi5JmUjjR19FtAOzgXO+zDxNuab3LfTX80SyxLLlM+305vcNuYw8WX9Gwp9FtchWiqhMu407jShMkksZSP9GtsRggeR+/Tuc+Km1RLLJsaGw4bDJsYSy7HR+trC40zts/dfARsK2xGKFz4c6x5ZIOsejR39Gn0WDBEqCa3/ZPWF6nPiKd6b3JvcFeF26N/xQvwjB7QSjR25JmwwVzd6PBVCFUI4P9o5oTJ/KI0d2xGCBbP3g+n62pTPJsaGw8jAhsMmxhLLsdFH2XPiaezW9l8BrwuDFD4cWSDXIVkg6x79GnsVhg8qCcgAR/cl7jbmFeEp3pvcKd5z4lznTO3e9GX+TQjbEcoZ1yG5JloqSSxaKrkm1yH9GrQSIgskAhv4TO1z4kfZsdFfzRLLX82x0YHXp9+F6t70nP+gCbQSPhxlI1oqTy5PLk8uSSxaKrkm1yE+HLQS5Qd3/DDxXOen35vc+tqb3KffA+V964byyPrHApwKtBLKGese1yFlI9ch6x7KGZcT2gy+Azj5TO1z4kfZt9OUz5TPsdGm1UfZp9926N/xCfxxBgwR/RoGJU8u7jRXN9o5VzehMkksuSaNHbQScQaP+UztFeFH2bHRlM9fzZTPsdGB1yneNua77zj5IwOvC9sRfRaKF3sV2xF6DU0ImwIJ/FH0fetz4kfZsdFfzRLLX82x0YHXp9+D6WT1fQEhDsoZBiVPLu402jl6PHo82jlXN6EySSwGJf0aIQ4oAb/zXOcp3oHXptW304HX+tpz4oXqhvJR+28Eeg17FY0dZSN/KFoqfyi5JmUjjR17FdoMVQM4+bvvduhz4hXhFeHC43bo9O7l9d38vgMiC5cT/RrXIX8oWipaKn8oBiXrHsoZ2xGgCez/3vR26Cnet9NfzanIJsYmxibGEsux0UfZc+JM7Y/5rwTQDooXjR3XIWUj1yFZII0dyhmDFNAO5QcyAH743/Fp7IPpXOdc54PpTO3f8bP3tv1vBCIL2xGKF/0a6x5ZIOsejR39GooXlxPQDuUHZf4m8zbm+tqx0RLLqcipyF/Nt9NH2XPifetk9bIAQQyKF1kgfyhPLmwwoTLuNKEybDBJLAYlPhwMER4GQvxR9CXug+lc51znduh96/TuJvPd+CL/HgbaDJcTpBg+HI0dPhz9GqQYgxTQDoIHCv9k9X3rwuOb3IHXt9Ox0bHRptX62qffXOd68Mj6HgbbET4cBiV/KFoqWiq5JmUj6x7KGbQSoAkj/obyXOcp3oHXsdGUz5TPlM+300fZp99c57vvs/fO/3EGIgshDoYPRRBFEEUQhg/QDq8LOAU5/VH0aew25hXhKd4p3hXhNuZM7eX1rf+gCYMU6x5/KKEy2jk4Pzg/OD96PNo57jRJLAYlpBivCwD+MPE25pvcgdem1abVptVH2Snec+Jc50zt3vQ5/YIF2gzbEXsVfRaKF4oXfRaDFEUQoAkAAuL53/F961znA+UD5QPlduhp7N/xG/j6/7kI2xHKGdchuSZaKloqfyhlI+seyhmXE0EM9ALd+PTuNuYp3oHXsdGUz1/NlM+300fZp99c5/Tus/edALkIhg97FaQYyhnKGf0a/Ro+HMoZfRZFECoJ3gB++N/xaeyD6XboduiF6kztMPHl9c77cgKgCUUQfRb9Gj4cPhz9GsoZiheDFNAOyAYM/Ybyduin30fZptWm1YHXR9kp3sLjg+kw8Y/5mwKvC4MUPhxlI38oSSxPLk8uTy5JLH8o1yH9GtsR5Qeh/mD2u++F6jbmwuPC48LjNuaD6fTu5fUA/s4F2gzbEYMUlxPbEdAOIgsjBwACCfxR9GnswuOb3IHXt9Ox0bHRt9OB15vcc+KF6lH0I/5NCNsRyhlZIAYluSZ/KH8ofyi5JgYlWSCKFyEOiQM4+bvvduhz4inem9wp3qffA+WF6jDxG/hO/3EG2gy0En0WpBikGKQYpBh9FrQSIQ5xBmX9v/N96wPlFeGn36ffc+Jc533rMPHW9mX9bwRBDJcT/RpZIGUjZSPXIVkgjR3KGYMUeg04BVH7MPFc56ffR9mm1bfTsdGx0bfTptX62nPiheq/8zn9zgXaDNsRexWKF6QYihd9FpcThg8bCr4Djv0b+Cbzu+9M7WnsJe568L/zG/gM/ZsCTQjQDoMUpBj9Gj4c/RrKGYoXexWXE0UQQQzIBmP/YPZp7HPi+tq305TPlM+Uz7HRptVH2affXOcw8Q77rwTaDJcTpBiNHVkgZSMGJbkmZSPrHqQYRRC5CLsBzvtH9970JvOG8ibz3vTW9o/5Of1KAoIH2gwMEYMUfRakGMoZyhmKF4MUhg+5CN4Afvh68Hboc+Kb3EfZR9lH2fram9wV4TbmTO3l9Zz/oAm0EsoZ6x7XIWUjBiVlI9chjR2KF0UQTQgK/+X1TO025hXhm9z62kfZR9n62inewuN96ybzfvoUAPcDcQZNCBsKrwt6DXoN2gwbCnEGyAAy+r/zTO126APlc+Jz4gPldugl7lH0QvweBkUQ/RoGJUksbDDuNNo5ejx6PNo57jRPLgYlyhkhDkoCs/f07nbowuNz4nPic+LC4wPlduhM7Sbzj/mt/68EuQivC9AO2xGDFHsVgxTbEdoMHgbY/rP33/FM7YXqduh26IXqaex68N70kfu+A9oMexWNHWUjuSZ/KFoqWip/KAYlWSD9GrQSnAq7ATj5MPGD6XPim9xH2YHXptWB10fZKd4D5Wns3vRC/McC5QevC9AO2xF7FYoXpBikGH0W2xFBDM4FCv/d+L/zu+8l7mnsaexM7fTu3/HW9t38iQOgCSEO2xGXE30WpBj9Gj4c/Rp9FgwRuQiK/2D2Je425hXhm9z62kfZ+top3hXhNuZM7d70q/xvBK8L2xGKF40d1yG5JloqSSxJLH8oBiXrHooXDBEbCokDtv3d+N703/H07iXuJe568N70yPooAcgGnAp6DdAO0A4hDkEMGwpxBg4BMvqG8n3rwuMp3kfZptW307HRsdG304HXm9zC42nsZPVF/h4G2gy0EooXPhxZIAYluSa5JgYlWSDKGQwRTQic/0f3u++D6QPlc+Jz4nPiNuZ96zDxG/gA/lUDTQjaDEUQlxN9FqQYyhmkGHsVDBEbCscCyPq/80ztg+lc5zbmXOd26GnsevBg9rb9ggXaDJcTpBjrHtchBiW5Jn8ofyi5Jtch/RrbEbkIOP9g9iXudujC46ffm9xH2UfZ+top3sLjherf8d34zv8eBq8LRRCXE30Wihd9FpcTRRCvCx4GZAAO+2D2JvN68PTuJe707nrwv/Pd+IP+MgQqCSEO2xGDFH0WihekGKQYpBiKF3sV2xGvC/cDUfuG8oPpc+L62qbVsdGUz5TPsdGm1ZvcwuNp7L/zDvt9AYIH2gzbEX0W/Ro+HI0dPhykGJcTeg1NCL4DMgA5/cj6OPl++N34yPrc/V8B8gS5CEEMhg+0EnsVyhk+HOse6x7rHj4cihfbEZwKmwLI+r/zTO126APlc+IV4affFeED5YPpevBH96H+ggWvC9sRfRb9GuseWSBZIOsejR2kGLQSIgtVA8773vT07oXqNuZz4qffp98V4QPlg+n07r/zR/cy+t383f/0As4FggdNCE0IIwfyBCgBd/zW9jDxaex26APlc+IV4RXhA+WD6XrwfvgOASoJDBGkGOseuSZJLGwwoTLuNO40oTJJLAYl/RrbEeUHiv/d+L/z9O5964Ppduh26IXqTO168CbzZPWz98j6Rf4kAoIFTQicCq8LIgu5CPIEIwDI+uX13/H07mnsheqD6YPpheol7r/zMvr2AIIHeg20EooXPhxZINchZSPXIVkg/Rp9FkUQKglfAeL5JvNp7Fznc+Kn35vcm9yb3KffwuN26Ezt3/Fk9Y/5jv1fATgFuQivC3oNIQ4hDtoMoAk4BYkAd/w4+WD2v/Mw8bvvu+8w8VH03fgA/vQCIwciCyEODBF7FaQYPhyNHY0d/Rp9FgwRGwq7ATj5MPGF6gPlFeEp3ineKd4V4QPlg+n07r/z3fgA/r4DoAlFEH0WPhxZIGUjBiUGJWUjWSA+HIoXtBJ6DU0IvgMK/1H7G/hg9mT1YPbd+An8rf+JAyMHnAp6DYYPDBFFENAOrwsjBw4B4vmG8n3rA+Wn3/ragde307HRsdG306bVm9xz4nboJe7e9A77QwGCByEOlxOkGD4c6x7rHo0d/Rp9FgwRnAr3A6v85fW7733rduhc54Ppfev07ibzR/eR++z/MgS5CNoMDBGXE3sVexWXE0UQIgs4Bb3+G/jf8Uztg+k25jbmNuZc54Xq9O7e9A77fQHlByEOlxOkGI0d1yG5Jn8ofyi5Jtch/RqDFNoMggUj/kf3MPFp7HboA+XC43PiwuNc54Xqu+/e9Mj6yADIBq8LRRCXE30WfRaDFNsR2gzlB5sCjv1++L/zevAl7kztTO307t/xZPXi+b3+vgMqCSEOtBJ7FYoXyhn9Gj4cPhz9GqQYlxPaDB4GI/5g9vTuXOcV4fragde307fTptVH2SneA+WF6t/xfvgK/4IFIgsMEXsVpBj9GsoZiheXE4YPnApxBnICIv9C/DL6OPky+kL8g/4oATIEIwecCiEO2xF9FsoZjR1ZINchZSPXIese/RqDFEEMbwSr/GT19O6D6QPlc+IV4affFeHC41znaeyG8t34iv8eBkEM2xF9FsoZjR2NHT4cyhmDFNAOuQj0Ajn9R/cw8X3rXOcD5cLjwuM25nboaey771H0G/jO+yL/3QGvBCMHKgkbCqAJTQg4BUMBDP1++L/z9O6D6QPlc+Jz4nPiA+WD6SXuUfRR+yMDrwuXEz4c1yF/KEksbDChMqEybDBaKmUj/RrbERsKSgLI+lH09O5963boduh26IPpfetM7Xrwv/PW9n76AP6bAYIFuQgiCyILGwojB3ICjv3d+L/zu+9p7HboNuYD5QPlXOeF6rvv5fVC/IkDIgu0EsoZWSBlI7kmfyh/KLkmZSONHYoXRRC5CJsByPpR9CXudugD5XPiFeEV4RXhwuM25oXqu++/8xv4Cfzd/4kDyAYqCZwKIgugCcgGIwPY/sj6R/e/87vvaeyD6Xboduh96yXuhvJH9938cgKCB0EMRRCDFKQY/Ro+HI0d/RqKF9sRrwuvBGX9YPa774XqA+Vz4hXhFeFz4gPlduhp7DDx1vZC/AACTQghDpcTpBiNHVkg1yHXIVkgPhyKF5cThg8iCyMHmwKh/lH7OPkb+LP33fgO+4P+SgJxBpwKIQ4MEZcTexV7FYMUDBFBDM4FZf7W9rvvduhz4ineR9mm1bfTt9O306bV+tqn3wPlheow8Rv4of44Ba8L2xF9Fv0ajR3rHo0d/RqKF7QSeg2CB30Bkftg9t/x9O5M7Uzt9O6G8tb2UfsUAK8EKgl6DdsRexWkGP0a/RqkGHsVRRAbClUDq/zW9t/xTO2D6VznNuY25nboaeww8db23fz0AioJhg97Ff0aWSAGJX8ofyi5JmUjjR2KF0UQuQi7Acj6UfQl7oPpA+UV4RXhFeFz4jbmher07lH04vk4/28EoAkhDgwR2xEMESEOGwqvBPL+j/lR9HrwTO2F6oPpduiD6Wnsu+9R9OL57P/OBSILhg+XE4oX/RqNHese6x6NHf0aexVFEKAJSgJ++ibzfesD5SneR9m307fTt9OB1/raFeFc50ztv/My+l8BTQghDpcTfRaKF30WexXbESEOoAnyBCgBRf5C/Mj64vmP+X76Qvwi/yMDggevC4YPlxOKFz4cWSAGJbkmfyi5JmUj6x6kGNsRGwqbAg77UfQl7nbowuMV4SneKd4V4QPlg+n07r/zj/mc/x4Geg2XE6QY/Ro+HP0apBiDFEUQIgseBt4AkfvW9obyJe5964Ppg+mF6kztMPHe9H74kfsK//QCyAYbCtoMIQ56Da8LTQgyBOz/Dvtk9Xrwheo25hXhKd6b3Pram9yn3zbmaey/83763QGgCdsRyhnXIX8oSSxPLk8uWiq5Jtch/RqDFHoNyAZCAH76ZPXf8fTuJe707nrwJvNk9Uf3j/kJ/E7/VQOCByILeg0hDtoMnAqCB4kDIv9++mT1evBp7HboA+Vz4nPiwuNc533r3/F++Dj/HgZ6DYMU/RrXIbkmWipaKn8oBiVZIMoZtBKvC68Etv1H9zDxfetc58Ljc+Jz4sLjA+V26H3r9O7f8eX1MvpO//cDIwcqCaAJuQgjB68E3QGh/lH7s/e/87vvaeyD6YPpg+lp7LvvUfQ4+aH+vgO5CHoNlxOkGI0dWSDXIVkg6x7KGYMU0A5NCN0BUfve9CXudugD5XPiFeFz4gPlduhp7HrwZPV++gYAHgZBDLQSihf9Go0djR2NHf0apBh7FbQShg+vCyMHxwIK/wn8Mvri+X76Cfzc/TIA9AIeBhsK0A60En0WpBikGH0WtBLaDM4Fvf6z9zDxherC4yneR9mm1bHRsdG306bVR9mb3BXhNuZ969/x3fjd/8gG2gzbEXsVihekGIoXfRaDFAwReg25CIkDI/7d+FH0hvIw8d/xJvPl9Tj53fz2AIIFnAqGD5cTfRakGKQYiheXE9AOoAkyBGX+fviG8kztXOfC4xXhp98V4cLjXOdp7Hrw5fVC/CMDnAq0EsoZWSC5Jn8oWip/KAYl1yE+HH0WRRAbCiMDCfxk9bvvaeyF6oPphep960ztu++/8xv4DP1KAuUH2gyGDwwRRRAhDpwKcQYOAc771vbf8UztdugD5XPic+LC41znaex68GT14vny/m8EnApFEHsVyhmNHesejR0+HKQYgxSGDxsKMgSO/eX1Je425qffR9mB14HXgddH2Zvcp9/C44PpevB++HYAIwfaDEUQtBK0EtsRRRB6DRsKcQabAtj+yPpH9970UfRk9bP3Dvuh/iQCzgWgCSEOlxPKGeseZSO5Jn8ofyh/KAYlWSA+HH0WDBEbCnICyPom82nsXOfC48LjwuMD5Vznheol7ibzj/mdAOUHIQ6XE30WpBikGIoXgxQMEXoNKgmvBIr/Mvpk9TDxJe5p7GnsJe677zDxJvNk9d34Of1KAiMHIgshDoYPRRCGD3oNGwrIBvQCRf7d+CbzTO1c5xXhm9z62vram9yn33PiNuZ969/xj/mbAq8LgxT9GlkgZSMGJQYlBiXXIeseyhmXE3oNyAZ2AH765fUm89/xhvK/8970ZPVg9t34QvzIAIIFGwp6DYYPRRCGDyEOQQwbCiMHIwO9/uL5UfT07oXqNubC48LjA+V26H3ru+/e9Mj6AAIbCrQS/RrXIbkmfyh/KH8oBiVZID4cexWGDyoJSgKR+2T1evBM7X3rheqD6YPpg+mF6n3rTO0w8WT14vll/QYAmwFKAkoC3QH2AHf/Zf1++tb2hvJM7YPpNubC48LjA+Vc54XqJe6G8rP3tv3yBEEMlxOkGI0d6x5ZIFkgjR39GooXtBLaDHEGd/9++IbyTO2D6VznNuYD5TbmXOeD6WnsevDl9Qn8JAKCB0EMhg8MEbQSlxOXE7QS2xGGD0EMTQgyBAYAq/x++t34fvh++I/5yPp3/L3+mwLlB3oNlxOkGD4cjR2NHf0apBiXE9AOuQjdATL6hvKF6sLjp9+b3EfZR9lH2fram9wp3hXhNuaF6nrwR/c5/ZsCIwecCtoM0A5FEAwRDBFFEHoNKglvBGP/fvpg9r/z3/Ew8TDx3/G/89b2DvsUAM4FrwsMEXsVihekGIoXfRaXE0UQQQwjB0MByPpR9CXug+k25sLjwuMD5TbmXOeF6vTuUfR++n0BuQhFEH0WPhzrHtchZSNlI2Uj1yHrHsoZgxR6DcgGyADO+7P33vQm89/xMPEw8Sbz5fXi+YP+vgMqCSEO2xGXE4MUlxMMESEOGwo4BZz/j/km80ztdug25gPlA+UD5Vzng+lp7Hrw5fWR+5sB5QchDrQSfRakGMoZyhnKGYoXexW0EiEOTQj2ADj53/F96zbmc+Ip3pvc+tr62pvcp9/C44PpevCz90X+vgNNCCILQQzaDEEMrwugCcgG9AKD/uL5YPa/8ybzv/Pe9GD2fviR+zj/vgMqCdAOgxTKGY0d1yEGJbkmuSa5JgYlZSNZID4cexUhDs4F3P3W9jDxTO2D6TbmA+XC48LjNuaF6rvv5fVC/HIC5QfaDEUQ2xHbEdsRDBHQDq8LggfHAtz9OPlk9YbyMPF68Lvvu++773rwhvJk9Y/53P0AAoIFuQivC9oMeg3aDEEMIgsqCc4FfQHO++X1u++F6gPlc+Kn3yneKd4p3qffc+Jc5yXu5fVl/fIEQQy0EooXPhzrHlkg1yFZIOse/Rp7FYYPKgmJAwr/zvvi+Rv4R/dg9mD2R/eP+av8FACJA8gGoAlBDHoNIQ7QDtAOIQ7aDJwKIwdyAt381vYw8Uzthep26DbmNuY25nbofeu772D23P0eBtAOfRY+HNchBiW5JrkmuSZlI+se/RqDFHoNHgac/zL6YPYm83rwJe5p7H3rfetp7PTu3/Hl9Tj5Qvy9/vYA9AJvBDgFOAVvBCMD9gCO/d34UfS7733rduhc5zbmA+U25nbofeu772T1Qvy+A5wKDBF9FsoZjR1ZINchWSDrHj4cihe0EkEMOAWD/n74v/O772nsheqD6YPphepM7Xrw3vTi+fL+VQMjB5wKIQ4MEbQSgxR7FXsVgxS0EoYPrwvlB68EmwEK/wz9kfvI+n76yPp3/Ir/9wOgCdAOlxOkGP0ajR3rHusePhzKGXsVhg+5CN4A3fjf8X3rNuYV4Snem9z62vra+tqb3KffwuN26EzthvKz9wn8BgCJA8gGGwpBDCEOIQ7aDJwKgge+A5z/UftH91H0MPG77yXuJe6774by1vZC/AACggfaDAwRlxN9FooXihd9FpcThg+cCvIEg/4b+IbyTO2D6TbmA+XC48LjA+Vc533ru+9k9c77cgIqCdAOlxOkGD4cWSBlI2UjZSNZID4cihfbEUEMyAZ9AXf8G/je9IbyevB68DDxJvPW9lH7dgA4BSoJQQzQDkUQ2xHbEYYP2gzlByQCzvtk9bvvfetc58LjFeEV4RXhc+ID5Xboaezf8bP3Rf5vBKAJIQ7bEXsVihfKGf0ayhmKF4MU0A6gCb4Dtv2z99/xfetc58LjFeEV4RXhwuNc52ns3/Eb+CP+VQOCB5wK2gzQDoYP0A5BDLkIMgSc/5H7G/hk9Sbz3/Hf8Sbz3vSz91H7d/8yBCoJIQ6XE6QYPhzrHtchZSMGJbkmBiXXIesepBi0Eq8LrwRl/WD2evB961znA+Vz4nPiA+Vc52ns3/Gz9yP+vgNNCEEM0A5FEAwRRRB6DaAJ8gSdAHf83fhk9Ybyu+8l7kztTO0l7vTuMPFR9Ef3UfvO/74DIwegCSIL2gwhDtAOIQ6vC+UHVQPc/Rv4hvJp7Fznc+Ip3vraR9lH2fram9wV4VznTO1k9WX9OAVBDNsRfRb9Go0d6x7rHo0dyhmDFEUQIgseBt0BAP7I+n74R/ez9374Mvp3/CL/SgIeBqAJ2gzQDgwRtBKXE4MUgxS0EkUQQQzIBvYAyPre9Lvvheo25nPip9+n36ffc+I25n3rhvJ++scCnArbEaQYjR1ZINch1yFZID4cihfbEa8LzgUjAA771vaG8rvvJe5M7WnsTO0l7rvv3/He9LP3yPpl/b7/3QFVA28E8gSvBIkDKAGO/Tj5UfS774XqXOfC4xXhFeEV4XPiA+WD6bvvYPYA/s4F2gyXE6QYjR1ZINch1yHXIese/Rp7FYYPoAkjA2X9G/i/87vvTO1p7H3raewl7jDxUfQb+EL8QgBvBE0IrwvQDgwRtBKDFIMUtBIMEXoNoAk4BX0BRf5R+zj5s/dg9mD21vbd+M777P/yBJwKRRB9Fv0ajR1ZIFkg6x4+HKQYlxN6DR4GZf7W9rvvg+kD5XPip98p3pvcm9wp3hXhwuNc533ru+9R9Dj5Zf19ATgFTQicCtoMeg16Da8LKgmCBX0Bjv0y+tb2UfTf8XrwevDf8VH0G/hl/VUDKgnQDpcTihf9Gj4cjR0+HMoZihe0EnoNIwdTAOL5UfS772nshep26Hbog+mF6kztMPFk9X76vv/yBJwKRRB7FcoZ6x7XIWUjZSPXIese/Rp7FYYPGwryBAYAkfuz99703/Ew8d/xv/Oz90L8QwEeBpwK0A7bEYMUgxSDFLQShg+vC3EGQgDi+b/zJe6F6lznA+UD5cLjA+U25oPpJe4m8zj5OP/yBJwKhg+XE30WpBjKGf0ayhmkGHsVRRCcCm8Ejv1H9zDxaex26MLjFeEp3ineFeED5YXqevDW9qv8SgIjByILIQ5FEEUQhg/aDCoJ8gSc/zL63vQw8fTuTO0l7vTuu+/f8d703fgA/lUDTQh6DbQSfRb9Guse1yEGJQYlBiVlI1kgPhyKF0UQoAlyAnf81vbf8Uztg+k25gPlNuaD6UzthvJ++EX+iQNNCEEM0A4MEQwRhg96DRsKHga7ATn93fhk9SbzMPF68PTu9O707vTuMPG/80f3Uftj/yMDHga5CK8Leg2GD4YP0A56DZwKyAa7AQn85fV68H3rNuZz4inem9z62vram9wV4Tbmaey/8w77AAJNCCEOlxOkGD4c6x7rHusePhykGJcT0A4bCnEGVQMOAU7/AP4M/d38jv2K/0oCggW5CK8LIQ5FELQSgxR9Fn0WfRZ7FbQShg8iCx4GUwB++t70evB961znwuMV4affFeHC43bo9O7l9WX98gSvC9sRihc+HOseWSDrHj4cpBi0EnoNTQj0AiP+MvpH91H03/G77yXuTO0l7rvv3/He9Ef3j/nO+9z97P/dAVUDbwRvBL4DmwGD/sj6YPbf8WnsdugD5RXhKd6b3Jvcp9/C43bou++z92P/yAZ6DZcTpBg+HFkg1yHXIVkgPhyKF9sRrwseBt4AQvx++N703/G77yXuJe707jDxv/Oz91H72P5KAoIFuQhBDIYPtBKDFIMUlxMMEXoNoAkeBvQCMgCO/cj6G/jl9d70UfRk9Rv4CfwoAcgGQQwMEXsVpBg+HI0djR0+HKQYlxN6DXEGTv9++IbyTO2D6QPlFeEp3pvcm9yb3Cnec+ID5YPpaex68L/zR/fI+kX+uwHyBCMHTQjlB3EGbwSbAnYAAP7I+kf3v/Mw8fTuJe707t/xYPZC/CQCTQh6DbQSfRb9Go0d6x7rHo0dyhl7FYYPoAm+A6H+4vlk9d/xJe5964Xqg+mF6mns9O7f8eX14vmh/okDuQghDrQSpBg+HOseWSDrHj4cpBh7FdsReg1NCCMDjv1++FH0MPF68DDxJvNg9n76vf4jAyMHnAp6DUUQ2xHbEQwRIQ6gCb4DAP7d+FH0evBM7YPpNubC43PiFeFz4jbmher07lH0Mvqc/68EKgl6DQwRgxSkGMoZ/RrKGX0WtBLQDpwKHgbIAMj63vQl7oPpA+XC48LjNuaD6UzthvKz9938mwEeBhsKeg2GD0UQhg/aDLkIvgPy/sj6R/e/8zDx9O5M7WnsTO168L/zG/ir/JsByAavC0UQgxSkGI0d1yEGJX8ofyi5JgYlWSA+HH0W2xFBDM4FCv8b+N/xTO2D6Xbog+l96yXuhvJH9wn8sgA4BbkIIgvaDNoMIgtNCG8EBgDO+xv4ZPWG8rvvTO2F6nboXOd26IXqaey77ybzYPbi+Y79KAGvBE0IrwshDoYPRRDQDtoMKgk4BfYAq/wb+CbzTO1c5xXhm9z62vram9wV4QPlhep68GD23fwjAyoJ0A6XE4oXyhn9GsoZiheDFNsRIQ4iC+UHrwQoASP+CfwO+w77d/xF/lMAJAIyBB4GuQivCyEODBG0EoMUgxSXE9sR0A4iC8gGSgKO/X74hvJp7DbmFeGb3Pram9wp3nPiNuZp7CbzMvpfAU0I0A6DFKQYyhnKGYoXgxQMEXoNoAnOBUoCof4O+7P3UfSG8t/xhvK/82T11vZ++H76q/wK/5sBMgTIBrkIoAkqCU0IcQa+A2QAd/yz94byaew25hXh+tpH2UfZ+top3nPiduj07mT1q/y+AxsKRRB7FcoZPhw+HP0apBiDFAwRQQzlB1UDg/6P+d70MPH07kztJe707jDxJvNk9bP3yPpl/psCggevC4YP2xGXE5cTtBLbEYYP2gycCoIH9wMGAAn8G/hk9VH0UfTl9d34d/zIAIIFnAqGD4MUyhmNHese6x6NHf0afRbbEUEMIwdfAVH7ZPV68H3rXOcD5cLjc+LC4wPlXOeD6X3rJe4w8VH0fvh3/M7/cgJvBM4FyAYjB4IHIwdxBjIE3gCr/Bv4v/N68PTuJe6774by1vaR+94AHgavCwwRfRY+HFkg1yHXIVkgjR3KGX0WDBFBDCMHfQEJ/Ef3v/Mw8fTuJe4l7iXuu+8w8SbzZPXd+GX9cgKCB9oMDBGDFH0WihekGKQYihd7FbQSIQ65CJsC3fyz97/zMPG777vvevAm8+X13fjd/F8BHgacCtAODBEMEYYP2gwbCsgGIwOK/5H7R/cm8/Tufet26DbmNuY25nboheol7t/x5fUy+iL/MgSgCdAOtBJ7FYoXpBjKGcoZpBh9FrQSeg0jB4kAMvpR9LvvaeyD6Xbog+l96yXu3/Hl9TL6Tv+vBCoJ2gzQDtAOeg2vC7kIggW7AY79OPne9HrwTO19633raewl7nrwJvPW9n76of70AoIH2gzbEYoXPhzrHtchZSNlI9chWSDrHv0afRaGD7kIfQFR++X1MPFM7X3rheqF6mnsu++/8934tv1yAnEGKgmcCpwKuQgeBiMD3f+r/I/5YPYm87vvaex964XqheqF6mnsJe6774byZPV++M77iv9VAyMHnAp6DdAOhg+GDyEO2gwiC00I9wMj/rP3MPGF6jbmc+IV4affFeHC41znfet68OX1zvtKAk0IIQ60EnsViheKF4oXfRZ7FbQShg+vC+UHrwTdAd3/vf5F/gD+AP6D/pz/KAFVA84FuQivC9AODBGXE4MUexWDFJcT2xGGD0EM5QdyAkL8ZPX07oPpA+UV4affKd6n3xXhwuOD6bvvR/e9/h4G2gzbEXsViheKF30WexW0EkUQeg0bCsgG9AKc/zn9zvtR+w77DvsO+1H7Qvwj/iMAcgKvBMgGuQicCkEM2gx6DXoN2gwiC+UHiQMj/rP3MPGF6gPlp9+b3Pra+tqb3KffA+WF6jDx3fhkAIIHeg20En0WpBjKGcoZihd7FbQS0A6cCsgGSgLc/TL6s/fl9WT1ZPVk9WT15fVH9zj5zvs4//QCyAacCnoNhg8MEdsR2xEMEdAOQQwqCYIFXwFl/Y/5YPZR9IbyhvKG8lH0R/cO+0IAHgavCwwRexWkGMoZ/RrKGYoXgxRFECILHgZ2AMj6ZPV68Gnsdug25sLjwuNz4sLjwuMD5Vzng+lp7LvvhvJk9bP3j/mR+7b9Tv9kAMgAiQBj/2X9fvpH97/zevAl7kztJe707jDx3vTd+GX+rwQiC9sRihf9GuseWSDXIdchWSCNHaQYgxTQDqAJrwQyAEL83fhg9lH0hvIw8XrwevB68DDxJvNg9jL6AP7dAYIFKglBDIYP2xG0ErQS2xGGD9oMKgk4BYkACfyz9970JvPf8d/xhvK/82D24vm9/vcDuQjaDIYPDBEMEYYPIQ6vC00IbwRkAAn8G/hR9DDxJe5964Xqg+mD6YXqfesl7nrwv/N++Dn9AAJxBhsKeg0MEZcTfRaKF4oXfRaXE0UQrwtxBvYAUfvl9TDxTO2F6oPpg+mF6kztu+9R9N343P1KAh4GuQgbCiILnAoqCSMHvgOK/w771vaG8rvvTO19633raexM7bvv3/He9LP3Dvuc//IEGwqGD4MUpBg+HOse1yFlI2UjZSPXIY0dyhl7FUUQIguCBRQADvtH91H0JvO/8970R/cO+5z/MgRNCCIL2gx6DXoNrwsqCc4F3QGO/Y/5YPYm8zDx9O4l7kztTO1M7fTuevDf8b/z5fXd+Hf8dgBvBOUHIgt6DdAORRDbEdsRDBGGD9oMuQj3A6H+OPlR9LvvfeuD6Xbog+mF6kztevBR9I/58v5vBKAJIQ7bEYMUfRaKF30WexWXE9sR0A5BDBsK5QceBjIEmwJDAXYAQgCdAF8BSgKJAzgFIwcqCa8Leg2GDwwR2xHbEQwRhg96DZwKcQbdAd38s/eG8kztdujC4xXhp9+n36ffc+I25n3r3/F++CL/8gSgCdoM0A5FEIYP0A7aDJwKggevBCQC+v8A/nf8Dvsy+uL54vky+g77d/wj/gYA3QG+A84FggegCSILQQzaDNoMQQycCoIHVQNl/t34hvJp7DbmFeGb3Pra+tr62ineFeE25mnsJvPi+cgAIwdBDEUQtBKXE4MUlxPbEYYPQQy5CPIEKAFl/TL6G/hg9mT1UfS/8ybzv/Pe9Nb2OPl3/BQA9wOCB5wK2gwhDtAOhg/QDtoMGwojB74DMgB3/H743vTf8bvvJe4l7rvvhvJg9g77FACCBSILRRCDFIoXyhnKGYoXgxQMEdoMTQj3A07/fvpg9t/x9O5p7IPpXOc25jbmXOd26IPpfetM7bvv3/He9Ef3j/mR+2X9Y/8OAQACSgJfAU7/Qvw4+eX1v/Pf8XrwevB68IbyZPU4+WX+MgQbCkUQexX9Guse1yFlI9chWSCNHcoZexUMEdoM5QdVAyL/kfvd+GD2v/OG8jDxevC777vvevDf8VH0R/fI+tj+xwJxBqAJQQwhDtAO0A56DSIL5Qf3A5z/kfuz91H03/F68PTu9O4w8b/zG/g5/XICggevC4YPDBEMEUUQ0A5BDKAJcQZVA93/Cfwb+FH0MPH07kztfeuF6oXqfetM7bvvJvNg9jL6Zf4jA+UHQQxFEJcTexWKF4oXihd7FbQS0A6gCb4Dtv0b+L/zu+9p7IXqg+mF6mns9O4m80f3kfsUADIEggegCZwKGwpNCB4GvgN2AHf8s/cm8/TufeuD6YPpg+mD6YXqfesl7nrwUfR++GX9mwLlB9oM2xF9Fv0ajR3rHlkgWSDrHo0dyhl7FUUQnAryBIr/yPpg9ibzMPF68N/xv/Oz9wn8sgDyBE0InAqvC68LoAlxBiMDzv+r/I/5YPYm87vvTO1p7H3rheqF6n3raewl7rvv3/Fk9d34DP2dAL4DyAYbCtoM0A5FEAwR2xEMEdAOIgseBnYAyPpk9XrwTO2D6XboXOdc54Ppaey77970Mvo4/zIEuQjaDEUQ2xG0ErQS2xEMEYYPeg0iC00IggX0AigBzv84/zj/OP8K/yL/nP/IAJsC8gQjBxsK2gyGD9sRtBKXE7QStBIMEdAOIgvIBn0Bzvtg9nrwaex26APlFeGn36ffFeED5YXqMPFH9479IwOCByILeg2GD0UQRRBFENAOeg0iCyoJcQZvBJsCXwHIAHYAFADs//r/iQC7ASMD8gTIBrkIIgvaDCEORRAMEdsR2xEMEdAOIgvIBg4Bfvq/80ztXOfC4xXhKd4p3qffFeED5YXqMPEb+Ar/OAUbCiEODBGXE3sVexV7FZcTDBF6DRsKcQYjA8gA8v6O/Qn8fvo4+Rv4s/ez9zj5Uftl/gACOAVNCCILeg2GDwwRtBK0EtsRRRB6DRsKHgYkAtz9MvrW9lH0hvKG8ibz3vSz90L8mwGCB3oNtBJ9FsoZ/Rr9GsoZpBh7FbQShg8iC8gGJAK2/eL5YPYm8zDx9O5M7Wnsfet962nsJe4w8Sbz3vTW9n74MvoJ/GX+nQBKAvQCSgKyACP+Ufsb+N703/G77yXuTO1M7SXuevAm8xv4tv33A5wKRRB7FcoZjR1ZIFkg1yFZIOse/Rp9FtsReg0qCTgFfQGD/gn84vkb+GD23vS/8ybzJvPe9Ef34vmr/Hf/AALyBE0IIgshDoYP0A56DSIL5QcyBGQAq/zd+GT13/G77yXuJe707t/xYPYO+0IAOAUqCa8L2gzaDHoN2gxBDBsKggf3AwYACfx++N703/G770ztheqD6YPpg+mF6mnsJe4w8WT14vm9/iMDIwciC9AOtBJ7FX0Wihd9FpcThg8iCx4G9gAJ/Ef3JvO770ztaexp7Eztu+8m80f3zvvs/1UDHga5CJwKrwuvCyILuQjyBHYAkftH97/zMPH07kztfet964XqfetM7bvvJvPW9s77nQA4BaAJIQ60En0W/RqNHVkgWSBZIOsePhyKF5cT0A6gCTIE2P4y+tb2UfQm87/z5fU4+Y79AAIeBioJIgtBDEEMIgugCYIHrwTeAHf8G/hR9N/xu+9M7X3rheqD6YPpg+l960ztu+8m89b24vk5/VMAvgMjBxsKeg1FENsRtBLbEdAOnArOBcgAzvvW9t/xTO2D6VznNuY25lzng+lM7d/xYPaR+2QA8gS5CCILeg3QDoYPRRDQDtoMGwqCB68EcgJkAL3+jv2r/EL8CfwJ/EL8Of2h/nYAmwI4BeUHIgshDgwRtBKDFHsVexWDFNsReg0qCW8Eiv/I+mT1evB961znwuNz4nPiwuNc533revBk9TL62P4jA8gGoAlBDHoNeg3aDCILuQhxBjIE3QHs/0X+DP0J/FH7DvuR+3f83P2K/30BiQOCBYIHoAlBDNAODBG0EoMUgxSDFLQS0A4bCm8EI/4b+N/xaew25nPiKd4p3inep99z4lznTO2G8hv4tv2bAiMHIgshDkUQDBFFECEOIgvlB28EDgFl/gn84vmz9+X1UfSG8t/xhvK/82T1s/d++o79DgHyBLkIQQzQDgwRtBK0EtsRRRB6DaAJOAX2AHf8fvhR9DDx9O4l7iXuevC/8374tv0jA7kIeg3bEXsVihekGMoZpBh9FpcTRRBBDOUHVQO9/n76YPYm83rwTO1964Xqhepp7CXuu+8w8YbyUfTW9o/5q/yK/yQC9wOvBK8EvgNKAhQAZf1++tb2v/Mw8fTuTO1p7GnsJe7f8eX1DvvIAHEGQQwMEX0WyhmNHVkgWSBZII0d/Rp9FrQS0A4bCs4FcgLs/479Ufvd+Ef35fVk9d70ZPXl9Uf3OPlR+wD+QwGvBE0IIgvaDHoNeg1BDJwKTQjyBJsB3P0y+tb2JvN68Lvvu+/f8d70fvir/N4ArwRNCCILIQ5FEAwRDBFFECEOIgtNCPIEKAEM/Tj55fUm83rwJe5964XqheqF6n3rTO277ybz1vbI+jj/9wO5CHoNDBGXE4MUexV7FZcTDBHaDLkIvgM4/8j61vYm8zDxu+/07rvv3/He9Bv4yPrc/X0BOAUqCUEMeg16DUEMGwrIBlUDrf/O+xv4UfQw8fTuaex964Xqhep962ns9O7f8WT1OPll/QACIwdBDNsRfRbKGT4cjR2NHT4c/RqkGHsVDBGvC3EGmwGO/TL6s/dg9tb2fvgO+0X+uwHyBOUHGwqvC9oMeg1BDJwKggdvBLIADP2P+eX1hvK770ztfeuF6oPpg+mF6mnsJe4w8b/zYPaP+d38UwAyBOUHrwvQDkUQDBFFENAOQQy5CDIECv/i+d70evBp7IPpXOdc51zng+lp7Lvvv/Oz95H7zv++AyMHGwpBDHoNIQ4hDtoMrwugCSMHOAVVA7sBnQCt//L+Rf62/bb9AP7Y/iMA3QH3A3EGKglBDIYPtBKDFIMUgxSXE9sR0A5BDE0IvgOD/jj5UfT07n3rdug25jbmNuZ26IXqJe7f8eX14vlF/nICzgVNCBsKnAqcCqAJTQjIBvIEIwMOAQr/Zf1C/An8Cfyr/Dn9I/5O/94AxwJvBHEGuQgiC3oNRRDbEYMUexV7FYMU2xEhDqAJ8gRj/zj5JvMl7oPpNubC48LjwuMD5Xbofeu779704vlO/zIEuQivCyEOhg+GD9AO2gycCk0IcQZvBCQCzv+O/ZH74vl++Ef3YPZg9mD2R/fd+A77I/67ATgFuQivCyEORRDbEdsRRRAhDq8L5QcyBAYACfx++GT1v/OG8ibzUfTW9uL53P1yAiMHQQxFEIMUfRakGMoZyhnKGYoXexW0EtAOIgvIBpsCg/7I+kf33vQm89/xMPEw8TDx3/GG8lH05fUb+H763fwi/0MBxwKJA1UDcgLIAL3+Cfzd+GT13/H07mnsheqD6YXqfesl7nrwUfTd+AD+iQMqCSEOtBJ9FsoZ/Ro+HP0apBh9FrQS0A6vC00IggWbAt3/jv2R+zL63fhH9+X13vTe9GT1R/fi+Xf8Tv9KAoIFTQicCkEM2gxBDJwKuQhxBokDBgBC/H74ZPUm89/x3/Em82T1s/fI+kX+JALOBSoJrwshDtAOhg+GD9AOeg2vC7kIggVKAjj/QvyP+Uf33vQm89/xMPF68HrwMPHf8VH01vZ++mX+mwJxBpwKIQ4MEZcTexV7FZcT2xHQDpwKcQZyAoP+yPqz9970v/OG8obyhvK/82T1G/hR+/L+mwLOBU0IGwqcCpwKoAmCB/IEAAK9/pH7fvhk9Ybyu+8l7mnsaex962nsaewl7rvvhvLW9g77zv+vBKAJeg3bEYMUihekGKQYihd7FZcTRRDaDLkIbwRkADn9Dvsy+uL5yPpC/IP+fQGvBOUHnApBDHoNeg16DUEMnArlB68EyACr/Dj55fW/8zDx9O5M7UztTO1M7SXu9O568N/xv/Ng9uL5tv27Ac4FKglBDNAORRAMEUUQeg0bCh4GmwEM/X74UfR68EztfeuF6oPphepp7CXuMPFR9Bv4Cfzd/1UDHgZNCKAJnAqcChsKuQjIBjgFvgNyApsByABTAN3/Tv/Y/qH+2P53/50ASgKvBIIHnAohDgwRgxR9FooXiheKF30WgxTbEdAOIgtxBrsBDP3d+N703/H07iXuJe4l7rvvMPG/80f3fvoA/igBvgPOBYIHTQhNCOUHyAY4Bb4DAAIjAIP+Of1C/M77UftR+1H7Cfzd/AD+OP/eAPQCggXlB5wKeg2GD9sRlxOXE5cT2xGGD0EMggebAo79fvi/87vvfet26FznNuY25lzng+lM7XrwZPUy+oP+mwIeBrkIGwoiC5wKoAlNCMgG8gT0Ag4Bd//c/UL8fvrd+Ef35fXe9N70ZPVg9n74UfuD/iQCzgW5CK8Leg3QDoYP0A4hDq8LTQhvBJ0A3fyP+WD2v/OG8jDx3/GG8mT1fvgJ/BQAMgRNCEEMhg+0EoMUexV7FYMUlxMMEdAOrwvlB/cDdgA5/X76G/jl9b/z3/Ew8XrwevAw8Ybyv/Pl9X74Ufu2/b7/KAEAAgACfQFTAGX+zvt++N703/El7n3rheqD6XboduiD6X3rJe7f8eX1yPrO/zgFnAqGD7QSexWKF30WfRaDFLQSRRB6DZwK5QeCBYkDuwGt/2X9UfuP+X74s/ez93744vkJ/IP+QwEyBMgGKgkiC0EMQQxBDK8LGwrlB/IEfQEj/lH7fvjW9mT1UfTe9GT1R/fi+av83f/0As4FuQgiC3oNIQ4hDtoMIgugCSMHMgQoAdz9yPob+OX1v/Pf8bvvJe5M7UztTO307nrwJvPl9Tj53fz2ADgFoAnaDIYPDBG0EtsRDBEhDiILggeJAwYA3fwy+rP3ZPW/8ybzJvO/82T1s/cy+jn9dgD3AyMHoAmcCiILGwoqCYIHggX0AgYAq/yP+WD2v/Mw8bvvTO1p7H3rfetp7CXuMPFR9Bv4q/ybAXEGIguGD7QSexV9FooXihd9FoMU2xEhDpwKyAa+A8gAZf5C/Mj6fvpR+wz9Y//dAW8EggcbCkEMeg0hDiEO2gycCuUH8gS7AWX+Ufsb+N70hvJ68PTuJe5M7UztTO0l7rvvMPG/89b2fvqD/nICcQagCdoM0A6GD9AOeg2cCoIHVQPy/n76YPaG8rvvTO1964Ppg+mD6X3rTO168L/zR/cO+6H+uwEyBM4FyAYjB8gGHgY4BTIE9ALdAfYAQgCK/73+3P05/av8d/wM/UX+FACbAoIFuQivC9AOtBKDFH0WiheKF30WgxS0EoYPrwvlB4kDd//O+3745fW/89/xevC773rwMPG/82D2j/lC/CL/3QH3A4IFHgbOBTgF9wNyAp0Aof6r/Mj63fiz99b2YPZg9mD21vZH9xv44vkJ/IP+DgG+A8gGoAnaDIYPDBG0ErQSDBHQDq8LTQj3A3f/yPpg9t/xJe6F6nboNuY25jbmXOeD6WnsevDe9Dj5Zf32APcDHgblB7kIuQjlB8gGggUyBMcCKAFj/479zvvi+Rv41vbl9WT1ZPVg9n74Ufuh/koCzgW5CK8LIQ5FENsR2xFFECEOIgvlBzIEyACO/cj6G/jl9VH0v/NR9OX1G/gO+9j+9AKCB68L0A7bEYMUfRZ9Fn0WexWXE9sR0A4iC4IHMgTIAI79fvqz9970JvPf8XrwevAw8d/xUfTW9jj5Cfxl/rIAcgKJA74D9AJ9AWP/q/w4+eX1hvL07mnsg+lc5zbmNuY25lzng+lp7Hrw5fVR+7IAggUbCiEODBGXE3sVexWDFJcTDBGGD9oMIgu5CHEGMgTdAfr/Zf45/Xf8zvvO+938of72AIkDHgZNCJwK2gwhDoYPhg+GDyEOQQwbCoIH8gRKAnf/q/wy+n74R/dH97P33fh++qv8rf/0AnEGKgmvC9oMeg16DXoNQQwiC7kIzgXHAhQAtv1R+zj51vZR9IbyevD07iXuJe4l7rvvMPG/80f3yPqh/nICzgW5CK8Leg0hDiEOQQycCuUHggXHAjIAjv0O+934R/fl9d703vRk9WD2G/h++o79yAC+Ax4G5QcqCRsKnAobCioJIwfyBMcCQgC2/Q77fvjl9b/zMPG77yXuTO0l7vTu3/He9N34Zf27Ac4FoAl6DQwRlxN7FX0WfRZ7FYMUtBJFECEOrwsqCR4GvgMAAvYAyAAOAQAC9wNxBioJQQzQDgwR2xG0ErQS2xFFEHoNGwpxBvQCiv93/I/51va/8zDxu+8l7kztTO0l7vTuevAm82D2Mvoj/gACggVNCCIL2gx6DXoNQQwbCnEGxwLy/g77s/dR9HrwTO1964PpduiD6YXqaey774byYPYy+mX9UwCbAm8EzgXIBiMHyAYeBvIE9wMjA5sCJAJfAWQATv9F/o79Of3c/WP/fQH3A8gGGwp6DQwRlxN9FqQYyhnKGcoZpBh9FrQShg+vC00IrwRfAUX+kfvd+GD23vS/87/z3vRg9n74fvrd/PL+yAAkAiMDvgP3A1UDSgLeADj/tv1C/Mj6j/l++LP31vZg9uX1ZPVg9rP3j/kJ/IP+XwFvBIIHGwraDIYPDBHbEdsRDBGGD9oMoAnOBSQCI/4y+mD2hvL07n3rg+l26FznduiD6Wnsu+8m89b2MvoM/c7/3QFVAzIErwRvBDIEiQObAn0BnQDd//L+jv3O++L5fviz97P3fviP+ZH7tv0yAPQCHgYqCUEM0A5FENsR2xEMEdAOQQygCXEGiQPeAGX+zvs4+Uf35fXl9WD2G/jI+gD+XwGvBIIHnAp6DYYPDBHbEdsRDBFFENAO2gycCuUH8gRKAor/d/yP+WD2v/Mw8bvvu++77zDxhvLe9Nb2OPmR+7b9OP8GAAYAIv+O/VH7fvhk9d/x9O5p7IPpXOcD5cLjc+Jz4nPiwuNc533revDe9Dj53P1yAsgGnAraDNAOhg+GD4YP0A56DUEMGwq5CMgGrwTHAvYATv/c/Qz9DP22/Qr/nQBKAjIEcQa5CCIL2gwhDtAO0A4hDnoNrwugCYIH8gRyAgYA3P0J/DL63fgb+Bv4OPlR+9z93gC+A3EGuQgiC0EMeg16DdoMIgugCYIHOAX0AnYAI/4J/OL5s/dk9SbzevD07kztTO1M7fTuevCG8t70s/cO+4P+3QHyBCMHTQi5CE0IggceBq8E9AIoAWP/tv0J/DL6fvjW9mT1ZPXl9Uf3j/mR+7b9zv/dAb4DzgUjB+UHTQjlB4IHcQY4BYkDmwGK/2X9Ufvd+Nb2UfSG8jDxevB68N/xUfTW9uL53fwUAPcD5QevC9AODBG0ErQStBLbEdsRRRCGD3oNrwugCSMH8gQjA7sB9gAoAUoC9wMeBk0IGwqvC3oN0A7QDtAOIQ7aDJwK5QfyBN0B8v7O+934ZPWG8rvvTO1964Ppduh26HbohepM7bvvJvNg9jL63P0OAb4DzgXIBsgGHgZvBJsCiQAj/lH7fvhk9Yby9O5p7IXqg+mF6n3rJe568IbyZPV++FH7I/6yAMcCMgTyBPIErwT3A4kDVQP0AkoCmwGdAJz/g/6O/d383fyO/Qr/KAGJA3EGoAnaDEUQlxN9FqQYyhnKGaQYfRaDFLQShg9BDCoJzgXHAr7/3fwy+hv4YPbl9eX1YPaz9zj5Dvvd/CP+OP8yAA4BmwF9AbIAY//c/Xf8Uft++o/5G/jW9uX13vS/8ybzJvNR9GT1R/c4+c77g/59ATIEyAYqCSIL2gx6DdoMrwsbCuUHHgb3A7sBCv/O+3743vTf8fTuTO1p7H3rfetp7CXuevC/82D2fvgO+zn9Iv+yAN0BcgLHAscCxwL0AvQCxwJKAl8BMgDy/tz9DP2r/N38Of3c/SL/nQCbAvIE5QecCtoM0A5FEAwRDBFFENAO2gwiCyoJIwevBLsBvf4J/DL63fjd+I/5yPqr/KH+DgGJAx4GuQgiC9oMIQ7QDoYP0A7QDnoNQQycCioJIwevBAACCv8J/N34YPa/84byMPEw8d/xJvNk9Uf3j/mR+wz9AP7Y/gr/of6O/ZH7j/lH9970JvN68CXufet26FznNuYD5TbmXOeD6X3r9O4m80f3UfuK/4kDyAYbCkEMeg3QDtAO0A4hDnoN2gyvCxsKggc4BVUDAAJDAfYA3gD2AH0BxwKvBMgGKgkiC9oMIQ7QDoYPhg/QDiEOQQycCk0IcQZvBEoC7P+2/ZH7fvoy+n76zvtl/Xf/AAKvBCMHoAmvC3oNIQ4hDnoN2gwiC6AJIwfyBJsCnQDY/t38MvpH91H03/F68Lvvu++773rwMPEm8970R/cy+gz9iv+bASMD9wNvBDIEvgPHApsBQgAi/7b9Qvx++t34R/dg9uX15fXW9hv4j/kO+9382P7IAHICvgOvBIIFHgZxBnEGHgY4BTIE9AKbASMAI/7O+4/5R/fl9VH0v/O/81H0ZPXW9jj5CfwK/0oCggW5CCILeg3QDkUQRRBFEEUQRRBFEIYPIQ6vCxsKTQjIBh4GzgUeBsgGggdNCKAJIgvaDCEO0A6GD4YP0A4hDtoMIgu5CHEG9wNfAaH+kfsb+N703/H07kztaexp7GnsTO307jDxv/PW9n763P3IAFUDOAXIBoIHggfIBh4GrwT0At4ARf5R+7P3UfTf8Xrwu++777vvMPGG8lH0YPbd+M77Zf7IAJsCvgNvBPIE8gQ4BTgF8gRvBFUDSgL2AIr/I/7d/EL8Cfx3/I79Tv99ATIEIwecCiEO2xGDFIoXpBjKGcoZpBiKF3sVtBJFENoMoAlxBlUDdgDc/ZH7MvqP+eL5fvpR+6v83P3y/vr/9gDdAZsCxwKbAt0B3gDO/73+tv13/A77j/mz9+X1UfQm84byhvIm81H05fUb+H763fy+/5sCggVNCBsKrwuvC68LIgsbCioJ5QfOBYkDDgFF/lH7G/hk9SbzMPG77/Tu9O6773rw3/Em82T1R/c4+Q773fyD/vr/DgEkAlUD9wNvBG8EMgS+AyMDcgLdAUMByACdAN4AfQEkAvQC9wOCBYIHGwraDNAODBHbEdsRDBFFEIYP0A56Da8LKglxBlUDiQAA/gn8fvoy+n76DvtC/I79Cv+dAEoCvgOCBYIHuQgbCpwKnAqcCpwKGwqgCU0IcQb3A5sBIv+r/OL5R/fe9CbzhvKG8ibzUfTl9bP3j/lR+zn9of53/4r/Iv8j/gz9zvsy+n745fUm83rwTO1964Ppduh26Hbog+mF6kztu++G8mT1fvhC/Oz/iQNxBrkInAqvC9oMeg0hDnoN2gwiCyoJggeCBfcDmwKbAfYAsgD2AJsBxwJvBB4G5QegCa8L2gx6DSEOeg3aDK8LGwpNCHEGbwQkAor/Of1R++L5OPk4+Y/5fvpC/IP+3gAjAzgFggegCa8Leg0hDiEOeg1BDJwKKgmCB4IFiQP2AAD+yPob+GT1v/Pf8TDxevAw8TDxhvIm89701vY4+ZH7jv04/zIAZAAjAJz/Iv+9/iP+DP1R+zj5R/dk9VH0v/Mm8ybzJvNR9GT11vZ++OL5DvtC/I798v5TAH0BJAJyAnICcgIkArsBDgH6/4P+DP1R++L5fvhH92D25fVk9WT1YPYb+DL6d/wi/90BrwSCB6AJIgtBDNoM2gx6DSEOIQ56DUEMnAoqCeUHIwfIBsgGyAbIBiMHggflB7kIoAmcCq8LQQzaDHoN2gxBDCILGwpNCHEGbwQAAiL/zvt++GT1hvK77yXuaex9633raexM7bvv3/FR9Nb2j/kJ/EX+BgBfAXICIwNVAyMDmwJDATj/d/yP+WD2UfSG8jDxevC773rwevAw8Ybyv/Ng9t34UfuO/Tj/ZABDAd0BcgKbAvQC9AJyAn0BIwCh/jn9QvyR+1H7UfuR+0L8jv13/wAC8gTlByIL0A7bEYMUfRaKF4oXihd9FoMUtBJFENoMoAnIBm8ESgKdAHf/of5F/iP+Zf7y/r7/sgCbAXICVQP3A28EMgT3A1UDcgJfAVMATv8A/kL8Mvqz92T1v/OG8obyhvIm81H0ZPXW9jj5Cfwi/yQCrwTIBk0IKgmgCaAJoAm5CIIHHgb3A5sBCv93/OL5R/dk9b/zhvLf8TDxMPEw8TDx3/G/8970YPYb+I/5yPpC/GX9g/5j/93/BgAGAOz/3f+t/zj/vf5l/mX+of44/93/UwDeALsB9ALyBCMHoAmvCyEO0A6GD4YPhg+GD4YPIQ7aDJwKTQjOBVUD3gC9/jn9QvwJ/An8CfxC/Kv8jv0K/8gAmwIyBIIFyAaCB+UHTQhNCE0I5QcjBx4GrwQjAygB8v53/DL6G/jl9d70v/O/87/z3vTl9Uf3OPnI+nf83P0K/63/3f++/wr/3P1C/DL6G/hk9YbyevAl7mnsfeuF6oXqhep9633rTO2774by5fU4+UL8OP8AAm8EyAYqCZwKQQzaDNoMQQwiC6AJ5QdxBvIEvgObAgACmwF9AZsBcgL3Ax4GuQgiC9oMIQ7QDoYPhg+GDyEOQQwbCuUHOAX0AsgAvf7d/FH7Mvri+TL6yPqR+6v8AP7s/yQC8gSCB6AJIgtBDEEMQQyvCyILoAlNCB4GiQPIAAD+Ufvd+Nb23vS/84byhvKG8obyhvK/82T1s/fi+UL8AP4i/87/MgB2AHYAMgBj/0X+3fxR++L5fvhH92D25fXl9WD21vYb+Dj5fvrO+938I/53/8gAJAJVAzIE8gQ4BYIFggWCBfIEMgRVA0oCDgG+/2X+DP0J/A774vk4+d343fji+VH7Zf3s/0oCbwTOBSMH5Qe5CCoJoAmgCaAJKglNCIIHyAYeBh4GHgYeBnEGcQZxBnEGyAaCB00IKgmcCq8LQQzaDNoM2gxBDEEMrwucCrkIcQb3A5sBCv9C/I/5YPa/8zDxu+8l7iXuJe707nrw3/FR9Nb2OPlR+wz9Zf6+/w4BJAIjA4kDIwMkAt4AOP+O/c77fvrd+LP3YPZk9d70UfRR9N705fWz94/5zvtl/dj+3f+yAH0BSgLHAiMD9AJKAl8BIwAK/wD+DP1C/FH7fvoy+n76kfsM/SL/uwGvBOUHIgshDgwRlxN7FXsVexWDFJcT2xFFECEOrwugCYIHggX3A3ICXwHIAHYAZACyAH0BcgKJA68EzgVxBiMHIwcjB3EGzgWvBFUDAAIyAAD+kfs4+db23vS/84by3/Hf8d/xhvJR9Nb24vk5/Z0AiQPOBYIHuQgqCaAJoAm5COUHcQavBHICQgAA/gn8Mvrd+Ef3YPbe9FH0v/O/87/zv/NR9GT1YPYb+I/5yPqR+3f8Of22/SP+Zf6D/kX+AP62/WX9Of1l/WX9tv3c/UX+8v4jALsBiQOCBeUHGwpBDCEO0A6GD4YPhg/QDtAOIQ7aDCILoAmCB84FMgQjA0oCmwH2ACMArf+K/87/dgBDAUoCVQOvBM4FyAaCB+UH5QflB+UH5QeCB4IHyAbOBW8ExwLeAAr/Of2R+zL6j/k4+Y/5MvpR+0L8jv3Y/iMAXwFyAvQCIwPHAkoCXwEjAIP+d/wy+hv45fVR9CbzhvIw8Xrwu+/07vTuu+968IbyUfRg9n74fvoM/U7/fQG+A84Fgge5CCoJKgm5COUHyAaCBTIE9AKbAYkAvv93/+z/KAH0AvIEIwe5CJwKQQx6DSEOIQ56DUEMIgugCeUHzgW+A90B+v9l/mX9d/yR+w77yPrI+g77QvwA/iMAmwLyBCMHKgkbCiILIgucCpwKGwoqCeUHHgaJA50Atv0O+9341vZk9b/zhvLf8d/xhvK/8+X1s/eP+VH73fwA/tj+Y/+t/63/Y/+h/rb9d/zI+jj5s/dg9mT1ZPVk9WT1ZPVg9kf3G/iP+cj6Cfxl/aH+zv/2AAACmwL0AiMDVQNVA4kDVQMjA0oCDgHO/6H+jv13/JH7yPoy+jL6fvrO+479iv99AVUD8gQeBoIHTQgqCSoJKgm5CE0I5QcjB3EGHgYeBh4GcQbIBsgGcQYeBh4GHgbIBoIHTQgqCaAJGwqgCaAJoAmgCSoJuQjlB8gGzgUyBEoCIwCO/cj6G/hk9b/z3/Ew8Xrwu+968DDxhvJR9OX1s/c4+X76zvs5/WX+d/9kAPYAKAHIAPr/Cv8j/jn9d/yR+376OPmz92D2ZPXe9N705fXW9hv4OPni+cj6zvvd/CP+Y/9kAA4BQwEOAYkArf+h/mX9QvwO+zL6OPnd+H743fji+VH7jv0UACMDHgYqCUEM0A4MEdsRtBK0EtsRDBFFECEO2gycCrkIyAY4BYkDSgJDAVMAvv93/77/nQC7AfQCvgMyBG8EbwRvBG8EbwT3A1UDSgLeAPL+q/wy+rP35fW/89/xevC777vvevDf8b/z1vYy+o79UwDHAq8EHgaCB00IuQi5COUHyAbyBCMDXwGc/9z9QvzI+o/5fviz90f31vZg9uX15fVg9kf3G/jd+I/5fvpR+0L8Of0A/r3+OP9j/zj/vf4j/o79Of0M/Tn9Zf22/UX+Tv+JACQCMgRxBioJrwt6DdAOhg+GD4YPRRCGD4YPIQ7aDCILoAlNCMgGzgXyBL4DmwKbAbIAFADO/93/UwAOAQAC9AK+AzIEbwSvBK8E8gQ4BYIFzgUeBs4FOAVvBPQCXwGt/9z9Cfx++jj5G/iz90f3s/cb+Dj5MvqR+6v8jv1F/r3+Tv++/87/Y/9F/qv8Dvs4+bP3YPbe9L/zhvIw8Xrw9O707vTu9O6773rwMPGG8r/z3vTW9jj5Qvw4/90B9wOCBR4GyAbIBsgGcQaCBTIExwJ9AXYAzv+t/wYAyAAkAr4DHgZNCBsKrwvaDHoNeg16DdoMQQycCioJIweCBb4DJAKdAAr/jv1C/A77fvoy+n76Ufur/GX+ZAByAm8EzgUjB00IKgmcCq8LrwuvCxsKTQjOBYkDQwHy/qv8Mvqz9+X1UfS/81H03vRg9rP3OPnI+gn8Of0j/vL+d//O/87/iv+9/o79zvsy+n741vZk9d70v/O/87/zv/Pe9OX11vaz9934MvpR+3f8tv3Y/s7/iQAoAbsBSgKbAnICAAJDAUIAOP8j/gz9zvt++o/53fjd+Dj5MvqR+2X9Tv/2AHICvgOvBIIFHgbIBiMHyAbOBa8EiQPHAkoCcgL0AokD9wNvBK8E8gSCBXEGIwdNCCoJGwqcCiILrwuvC68LrwuvC68LrwuvCyILGwq5CMgG8gSbAhQAZf3I+n741vZk9d703vRk9eX11vaz9374OPky+g77zvvd/Nz9vf6K/77/iv8i/4P+AP7c/dz9jv3d/An8yPqP+X74G/gb+Bv4G/iz9xv4fvg4+TL6Ufvd/GX+vv/eALsBJALdAV8BiQCK/4P+Zf1C/FH7fvri+Y/54vnI+kL8I/4yAJsCOAXlB5wKeg3QDkUQDBEMEQwRDBFFENAOeg2vCxsKuQgjB84FbwQjA3ICJAJKAvQC9wOvBDgFggXOBR4GyAYjB4IHggcjB3EGOAWJA90Bzv+O/Q77G/hk9YbyevC77/Tuu+8w8Sbz5fV++A77Zf2+/yQCbwRxBuUHuQi5CE0IIwfOBfcDJAKJAAr/tv1C/FH7fvri+Y/5OPnd+N343fg4+Y/54vky+sj6UftC/Az9AP6h/jj/d/8i/2X+Of0J/A77fvri+Y/54vni+cj6CfwA/kIAxwLyBCMHuQgbCq8L2gx6DSEOeg16DUEMIgugCU0IIwfOBa8E9wMjA3ICmwHIAEIA7P/s/0IA9gDdAZsCIwOJA74DMgSvBPIE8gTyBPIEOAWCBc4FggWvBFUDuwFCAAr/AP45/Xf8CfzO+wn8d/wM/bb9Zf4K/3f/+v+dAEMBfQFDAbIAzv/Y/rb9q/xR+zL63fiz92D2ZPVR9CbzhvLf8d/x3/Ew8TDxevB68Hrw3/G/8+X1fvjI+jn9Tv8oAZsCvgMyBG8E9wNVA3ICXwGdABQAzv/d/1MADgEkAr4DggWCByoJIgtBDHoNIQ4hDnoN2gyvC5wKoAlNCCMHzgVvBCMDuwFkAAr/3P05/Tn9jv1F/gr/7P/eAAACVQPyBHEGTQigCZwKnAqcChsKuQgjBzgFxwL6/zn9fvob+GD2ZPXe9GT15fVH9934MvqR+938I/5O/0IA3gAoAQ4BnQDs/wr/I/45/c77Mvrd+LP31vbW9kf3s/cb+H74j/l++lH7Cfyr/I79Zf44/yMAKAEkAvQCVQOJA1UD9AJyApsBdgAi/9z93fwJ/JH7UfuR+wn83fzc/SL/iQAkAokDOAVxBiMH5QflB4IHcQbyBL4DxwJKAiQCJAIkAkoCmwIjA74DrwTOBSMHTQgqCRsKnAoiCyILrwuvC68LrwuvC68LrwuvC68LIgsbCrkIIwfyBJsCUwAj/gn8fvqP+d34fvh++H74OPni+X76DvtR+1H7kfvO+wn8QvxC/Hf8d/yr/N383fwM/d38q/xC/JH7DvvI+jL64vk4+Rv4R/dg9mT1ZPVk9WT1YPaz9934MvpR+wn8d/yr/Hf8CfxR+376j/nd+Bv4G/gb+Bv4G/h++I/5Dvs5/b7/SgKvBCMHKgmcCkEM2gwhDtAO0A7QDiEOeg3aDK8LGwq5COUHyAYeBoIFOAWvBK8EbwRvBK8E8gQ4BYIFzgXOBR4GcQYeBs4F8gQyBPQCfQFj/9384vnW9lH03/F68Lvvu+8w8YbyUfRg9t34DvuO/Zz/QwGbAokDMgRvBDIEvgPHArsBdgA4/wD+3fzO+w77fvp++jL6Mvri+Tj5fvgb+LP3R/dH97P3s/d++Dj5MvoO+1H7UfvI+uL53fiz99b25fVk9d703vRk9db2G/gy+kL8g/7IAPQCOAWCByoJnAoiC68LIgsiC5wKoAm5COUHIwdxBs4FggXyBG8E9wO+A74DiQOJA1UDiQO+A/cDMgRvBK8ErwRvBG8EMgRvBK8EOAWCBYIFOAVvBIkDmwK7Ad4AFACc/2P/OP84/07/nP8UALIAKAF9AbsB3QHdAX0BDgGyAGQAQgDs/2P/of62/d38zvvI+uL53fh++Bv4s/fW9uX13vS/84byMPF68HrwevDf8Sbz3vTW9t34Dvs5/dj+FAD2AH0BuwG7AV8BDgH2AN4A9gBfAd0BxwK+AzgFyAa5CJwKQQx6DSEOIQ4hDiEOIQ56DUEMrwsbCioJ5QcjB84FrwRVAyQC9gAGADj/vf5l/iP+Zf4K/wYAQwFyAr4D8gQeBiMHTQgqCSoJuQjlB84FvgN9ATj/3fzI+t34s/fW9tb2R/ez9374j/l++pH7d/zd/Az9Of05/Tn9Of0M/Xf8zvvI+jj5s/fW9uX15fXl9eX15fVg9tb2R/cb+H74j/l++pH7q/yO/aH+rf+yALsBcgIjA1UDIwObApsBZAA4/0X+Zf3d/Kv8d/yr/Dn9tv1F/iL/UwC7ASMDbwQ4Bc4FHgbOBTgFMgQjAyQCQwF2AN3/nP+c/+z/dgAoAQAC9AL3A/IEHgbIBuUHuQgqCaAJoAkbChsKnAqcCiILrwtBDEEMQQwiCxsKTQjIBvIE9AIOAU7/3P3d/An8kfuR+877CfxC/Hf8d/xC/An8Uft++uL5j/mP+Y/54vni+TL6Mvp++sj6DvuR+877kftR+w77fvri+d34G/jW9uX1ZPXe9GT15fXW9hv4j/nI+gn8q/yr/Hf8kfvI+jL6j/mP+Tj53fjd+H74fvjd+I/5yPpC/Nz9rf9fASMDrwQeBoIHuQgbCiILrwtBDNoM2gxBDK8LIgsiC5wKGwoqCbkI5QcjB8gGcQZxBnEGcQZxBnEGcQbIBiMHggflB+UHggcjBx4GbwQkApz/3fwy+rP35fVR9CbzhvKG8ibz3vRg9n74yPqr/GX++v9fAXICIwOJA74DiQNVA/QCJAIOASMAOP+D/tz9Of3d/Hf8QvzO+1H7fvri+Tj53fh++H743fiP+X76UfsJ/Hf8d/wJ/A774vkb+Nb2ZPXe9N703vRk9eX11vZ++H763fxj/90B9wMeBoIHuQgbCpwKnAobCqAJKglNCIIHyAYeBoIFOAXyBK8ErwSvBK8EbwQyBDIEbwSvBK8ErwSvBK8ErwSvBPIEOAWCBc4FzgWCBTgFrwT3AyMDJAIoAYkAQgAyAAYAvv+c/77/ZABDASQCxwIjAyMD9AKbAgACmwFDAQ4B3gBkAN3/Y/+9/gD+DP0J/FH7DvvI+sj6yPri+d34s/dg9t70v/OG8t/x3/Hf8SbzUfTl9bP3OPnI+gn8Of0j/r3+Cv9O/2P/d/++//r/QgCdACgB3QHHAvcDOAVxBuUHKgkbCiILrwtBDNoM2gzaDEEMrwsiC5wKoAkqCU0IggfIBh4G8gS+A5sCfQGyACMA7P/6/2QAKAFyAvcDzgWCByoJGwoiCyILIgsbCrkIyAavBHICQgAj/kL8Dvsy+o/54vl++lH7d/w5/dz9Rf6D/tj+OP93/63/zv/d/77/OP+D/mX9QvwO++L5OPk4+Tj5j/mP+Y/5j/mP+eL5fvpR+877q/yO/b3+BgBfAZsCiQMyBDIEvgPHAt0BsgB3/0X+Zf2r/EL8QvxC/Hf8q/w5/SP+OP9TAH0BmwJVA/cDMgQyBDIEiQObApsBdgCc//L+of5l/oP+2P6c/7IAJAKJA68EggVxBiMHggflB7kIoAkbCiILrwuvC0EM2gx6DdoM2gxBDCILGwpNCMgG8gSJAyQC9gAUAJz/d/+c/87/FABCACMArf/Y/tz9DP1C/JH7UfsO+8j6fvoy+jL6Mvoy+n76yPpR+wn8d/x3/Hf8CfyR+376OPkb+Nb2YPbl9eX15fXW9rP33fiP+eL5Mvp++jL6j/k4+X74G/gb+LP3s/cb+Bv4fvjd+Dj54vkO+3f8AP5j/94AcgL3A84Fgge5CBsKrwtBDNoM2gzaDNoMeg16DXoNeg16DUEMrwucCioJTQjlB4IHggeCB4IHggeCB+UHTQhNCE0I5QcjBx4GMgRKAvr/Zf1++rP3ZPW/84by3/Ew8TDx3/GG8r/zZPVH9934fvrO+938AP4i/zIA9gBDAQ4BdgC+/yL/vf6D/mX+Zf6D/mX+I/62/Tn9q/wJ/JH7UfsO+1H7zvtC/Az9AP6h/iL/Cv9l/gz9kfvi+Rv41vZk9d70UfRR9N705fVH9zj5yPqr/GX+UwBKAvcDggXIBiMHggcjB8gGcQaCBa8EvgPHAiQC3QG7Ad0BJAJKAkoCJAIkAt0BuwG7Ad0BSgL0AokD9wMyBG8ErwQ4BYIFggWCBfIEbwRVA3IC3QFfAV8BfQF9AZsB3QFyAiMD9wOvBIIFzgXOBYIFOAVvBPcDVQP0AnICJAJ9Ad4ABgAi/0X+jv05/av8QvzO+1H7fvqP+X741vbe9CbzMPG77/TuJe4l7iXu9O677zDxhvJR9GT1YPZH97P3fvjd+OL5yPpR+wn8q/xl/QD+vf6K/3YAuwEjA68EzgUjB+UHuQigCRsKnAqcCpwKGwqgCaAJoAmgCRsKGwqgCbkIggdxBvIEiQNyAn0ByABkAHYAKAFKAr4DOAVxBuUHKgkbCpwKnAqgCbkIIweCBfcDJAJ2APL+jv13/JH7UftR+5H7zvsJ/EL8d/yr/Hf8d/yr/Az9Zf22/bb9Zf3d/M77Dvsy+o/5OPk4+d34fviz90f3R/dH9xv4fvg4+eL5Dvt3/AD+zv+7AVUD8gTOBR4GzgXyBPcDmwJ9AXYAzv84/73+Rf7c/bb9AP5F/qH+OP/s/8gA3QGbAiMDVQNVA/QCSgJDATIAIv8A/t38CfyR+1H7zvur/Nz98v7s/7IAXwEkAscCvgPyBB4GggdNCCoJGwoiC68LQQzaDHoN2gxBDCILGwq5COUHIwceBvIEvgPHAnICSgKbAvQCIwNVA/QCcgJ9AYkArf/Y/tz9DP1C/JH7UfsO+8j6yPoO+5H7Qvzd/I793P0A/tz9jv2r/M77fvo4+Rv41vZg9uX15fVg9tb2R/ez9374fvh++Bv4R/fW9mD2YPbW9kf3R/ez97P3s/cb+H74j/nI+pH7d/wM/dz9Cv92ACQC9wOCBSMHTQgqCRsKIgtBDHoNIQ6GD4YPhg+GDyEO2gyvC5wKoAm5COUHggcjByMHggflB00ITQi5CE0I5QcjBx4G8gSJA7sBvv+O/VH7OPlH92T1v/OG8t/xhvIm87/z3vTl9db2s/fd+DL6kfsM/WX+OP++/+z/zv+c/5z/rf/O/87/iv8i/4P+tv3d/EL8kfvI+n76Mvoy+jL6yPrO+wz9Zf5j/wYAFACt/9j+tv2r/FH7Mvrd+LP3R/dg9mD21vaz9zj5yPp3/CP+3f9fAccC9wM4BXEGyAYjB8gGcQbOBfIEMgRVA5sCcgJyAnICmwJyAgACXwGJAPr/rf/6/50AXwHdAUoCxwJVAzIE8gSCBYIFOAWvBPcDVQPHAkoCJAIAAt0BuwGbAd0BSgL0AvcDOAVxBoIH5QflB4IHyAYeBs4FOAWvBDIEVQNyAn0BnQDd/2P/2P5l/tz9Zf3d/Hf8zvvI+o/5G/jW9mT1UfQm89/xevC777vvu++773rw3/GG8ibzv/Pe9GT1YPZH9xv4OPni+X76UfsJ/N38AP4K/xQA9gC7AXICIwMyBDgFcQblB7kIoAmgCaAJoAmgCZwKrwtBDNoM2gzaDK8LnAqgCeUHcQY4BfcD9AJKAgACSgL0AvcD8gRxBoIHTQi5CCoJoAmgCaAJuQiCBx4GrwT0AigBd/8j/gz9d/xC/An8zvuR+1H7DvvI+n76yPqR+0L83fwM/d38q/yr/Kv83fzd/Kv8d/zO+8j64vnd+LP3R/dH97P3G/jd+I/5fvqR+zn9Iv8oASMDrwSCBc4FzgU4Ba8E9wP0ArsBiQBj/4P+tv1l/Qz9DP3d/N38DP2O/UX+Cv/O/2QA3gBfAZsBfQEOAUIATv9l/o79DP3d/Az9Of1l/bb93P0A/kX+2P6t/8gAJAKJAzgFyAblB6AJnApBDNoMeg0hDiEOIQ56DdoMQQyvC5wKoAlNCMgGzgU4BfIEOAXOBR4GHgYeBs4FOAVvBPcDIwMkAvYArf9l/mX9d/wJ/M77CfxC/Hf8q/zd/Dn9Of05/Tn9DP2r/An8Uft++o/5fviz90f31vbW9kf3s/cb+Bv4s/dH99b21vZg9mD2YPZg9tb21vZH97P3G/jd+OL5fvrI+lH7kfsJ/Kv8jv3y/mQA3QH0AjIEOAVxBuUHoAmvC3oN0A5FEEUQRRCGD9AOIQ7aDK8LnAobCioJKgkqCSoJKgkqCSoJKgkqCSoJKgm5CE0IggdxBjgFvgMAAgYAAP7O++L5fvhH92D25fVk9WT1ZPXl9WD2R/d++I/5yPpC/GX9Zf5O/yMAyAB9AQACSgJKAt0B9gDs/wr/Zf7c/WX93fwJ/FH7yPp++sj6UftC/GX9Zf44/63/+v/6/5z/2P62/Xf8Dvs4+bP31vbl9WT1ZPXl9db2s/fd+DL6kfs5/fL+yAByAr4DbwTyBIIFggWCBYIFOAXyBPIE8gTyBK8E9wMjA0oCXwGyAGQAZACyAA4BXwG7AXICVQMyBDgFzgUeBs4FggXyBDIEVQObAiQCuwEOAYkAFADs/zIAyACbAccC9wPyBM4FcQZxBsgGyAZxBh4GggVvBPcDiQMjA8cCSgK7AQ4BUwCK/6H+3P0M/Xf8zvvI+uL53fiz92D23vS/84byMPF68Hrwu++777vvu+968HrwMPHf8YbyJvNR9GT11vaz9934MvqR+wz9Zf6K/2QADgGbAUoCIwMyBIIFcQYjB4IH5QdNCCoJGwoiC0EM2gx6DSEOIQ56DdoMQQwiC6AJTQhxBvIEvgP0AnICcgL0AokD9wOvBDgFzgVxBoIHTQhNCE0IggfIBs4FrwRVA90BUwAK/yP+jv0M/Xf8CfxR+376j/k4+Tj5j/ni+TL6yPoO+5H7Qvzd/GX93P3c/Y793fzO+376OPkb+Ef3YPbl9WT1ZPVk9eX11vYb+DL6CfwA/r7/KAFyAokDMgRvBDIEiQObApsBiQCt//L+g/4j/rb9Zf0M/av8q/zd/Az9jv0j/r3+OP/d/2QAsgDIALIAUwAGAK3/OP/Y/mX+3P1l/Qz9q/x3/EL8q/w5/SP+Tv+dAAACiQM4BSMHTQigCZwKIguvC0EMQQxBDEEMrwucCqAJuQiCB3EGggU4BfIEOAWCBYIFggXOBYIFggWCBfIEMgRVA0oCKAEUADj/of5F/gD+jv05/d38q/yr/N383fyr/Hf8QvzO+w77fvqP+d34s/dH99b2YPZg9mD2YPZg9mD25fXl9WT1ZPXe9FH0UfRR9FH03vRk9eX11vaz93743fg4+Y/5j/ni+X76DvtC/I792P4GAEMBxwKvBMgGuQgiC9oMIQ6GD0UQRRBFEIYP0A4hDtoMQQyvCyILIgucCpwKGwqgCaAJKgkqCSoJKgkqCbkITQgjBx4G8gRVA5sB7P9F/t38Ufvi+Rv41vZk9d70v/O/8ybzJvO/89705fVH9934MvqR+938Rf53/0IAiQB2APr/Tv+h/gD+Zf2r/An8Uft++uL5j/mP+Y/5MvoO+wn8DP0j/jj/FACdAMgAiQDd/9j+Zf0J/A77MvqP+Y/5OPk4+Tj5OPni+X76kfur/AD+Y//IACQCVQNvBDgFggXOBXEGyAYjByMHIwfIBs4F8gT3A8cCuwH2AGQAFAAGACMAdgAOAbsBcgJVA28EOAUeBnEGcQbOBTgFrwQyBIkDmwKbAbIAMgAUAGQADgG7AZsCVQMyBDgFHgbIBiMHIwcjB8gGcQYeBh4GzgWCBTgFrwT3A1UDmwKbAZ0AnP+h/rb93fwJ/A774vnd+LP31vZk9VH0JvOG8t/xMPEw8TDxMPEw8XrwevB68DDx3/GG8ibzUfRk9db2fvji+VH7Qvw5/bb9I/6h/mP/QgBfAUoCIwO+AzIE8gTOBcgG5QcqCRsKrwtBDNoMeg16DXoNeg3aDK8LnAoqCU0IIwceBjgFbwQyBPcD9wMyBK8EOAXOBXEGIweCB4IHggcjB3EGggWvBPcDIwNyApsBsgDO/9j+tv13/A774vk4+X74s/ez90f3s/cb+N34j/l++s77d/zd/Kv8CfwO+zL6OPl++LP3R/dg9uX1ZPXe9N70ZPVg9kf3OPkO+wz9Cv+yAAACxwJVA1UDIwPHAnICSgIAArsBfQEoAcgAQgCt//L+g/5F/mX+of4K/4r/BgCdAF8BJALHAlUDvgO+A74DiQMjA0oCXwFCAAr/AP45/d38q/yr/N38Of3c/b3+FACbAVUD8gRxBoIHTQgqCaAJGwobChsKoAkqCeUHIwdxBoIFrwT3A74DiQOJA4kDiQOJA74DvgO+A1UDxwIkAkMBnQAyAOz/zv+t/4r/Iv+D/gD+jv05/Qz9DP0M/d383fyr/Hf8CfyR+8j6fvoy+uL5Mvoy+n76yPrI+n76MvqP+d34G/iz90f31vbW9tb2R/cb+Dj54vnI+g77DvvI+sj6fvrI+g77UfsJ/Kv8Of0j/k7/3gDHAvIEyAa5CJwKQQx6DSEO0A7QDtAO0A4hDiEOeg3aDEEMQQxBDK8LrwuvCyILIgucCpwKnAobCqAJKglNCIIHyAbOBfIE9wObAkMB+v+h/jn9zvsy+t34R/dg9mT13vTe9N705fVg9hv44vnO+7b9d//eALsBSgJyAnICSgIAApsBQwHIAAYA8v7c/av8zvtR+w77kftC/Dn9I/4K/xQADgHdAXICcgIkAl8BnQDd/zj/vf5F/rb9DP2r/An8kftR+w77UfvO+3f8jv29/iMAfQHHAvcDOAVxBuUHuQigCRsKoAkqCbkIggdxBjgF9wPHAn0BZAB3/73+Zf6h/jj/MgBDAUoCIwOJA74DvgP3A/cDvgNVA8cC3QEOAVMAzv+c/5z/3f9CAMgAfQEkAvQCiQP3AzIEbwSvBK8ErwTyBIIFHgbIBiMHIwfIBh4GggVvBL4DxwK7AZ0AY/8j/gz9QvwO+zL6OPkb+Ef31vZg9uX1ZPXe9N70UfRR9L/zv/Mm8ybzJvMm87/zUfTl9Uf33fgy+pH7d/wM/WX9jv3c/YP+Y/9CAPYAmwEkApsCiQOvBM4FIwdNCKAJGwqcCiILrwtBDEEMQQyvCyILoAm5COUHIwdxBs4FOAXyBG8EMgT3AzIEbwTyBIIFHgZxBsgGyAbIBnEGcQYeBs4FOAWvBPcD9AIAAsgATv+2/Qn8yPqP+Rv4R/fW9mD2YPbW9rP33fgy+lH7Qvx3/Hf8CfyR+w77fvri+d34s/fW9mT13vS/87/zv/NR9GT11vZ++DL6Qvzc/Xf/sgB9AQACSgJyAnICxwIjA1UDIwPHAiQCXwFkAHf/g/7c/Y79Of0M/Tn9jv1F/jj/UwCbAccCvgOvBDgFggWCBTgFbwSJA5sCmwFkADj/I/45/av8d/zd/I79of4UAH0B9AIyBDgFcQaCB00IKgmgCRsKoAkqCU0IggfIBh4GggU4BW8EvgMjA5sCSgIkAiQCAALdAZsBKAHIAIkAiQCyAPYAKAFDAUMBDgGdADIAvv9O//L+g/4j/tz9Zf3d/EL8zvtR+8j6Mvoy+uL5Mvp++sj6DvsO+8j6fvoy+o/53fgb+LP31vbW9tb2s/d++Dj5j/mP+Y/5OPnd+H743fjd+N34OPk4+Y/5MvpR+3f8AP7O/7sBiQOCBSMHuQgbCiILQQzaDNoM2gxBDK8LrwsiC5wKnAobCqAJuQhNCOUH5QflB4IHggcjB8gGHgbOBYIFggU4Ba8E9wMjAyQC9gCc/wD+Qvx++t34R/fl9VH0JvPf8TDxMPHf8Sbz3vRH94/5Ufvd/AD+vf4i/2P/iv+t/5z/Tv+h/o79QvwO++L5OPnd+H74fvjd+Dj5MvoO+0L8jv2D/jj/nP/d/wYAMgBkAIkAnQB2AAYAOP8j/gz9CfwO+376Mvoy+jL6yPpR+0L8tv0i/8gAmwJvBB4GggdNCCoJoAmgCSoJuQiCB3EGOAW+AyQCiQAK/wD+jv2O/QD+g/44/+z/iQAoAd0BSgLHAvQC9AL0ApsCJAKbAQ4BiQAyAAYA7P/d/77/3f8jAJ0AKAGbAbsBuwG7AbsBAAL0AvcDOAUeBsgGIwcjByMHyAZxBs4FrwSJA3ICKAH6/9j+tv2r/JH7yPoy+uL5OPnd+N34fvh++Bv4G/iz90f3YPbl9WT1ZPVk9eX11vYb+I/5fvqR+wn8d/yr/N38DP2O/QD+Zf6h/tj+Iv+c/4kA3QFVA/IEHgYjB00IKgmgCZwKrwtBDEEMQQxBDK8LnAobCioJuQhNCIIHyAYeBs4FOAU4BfIEOAU4BTgFggXOBXEGyAYjB4IH5QflB+UHggfIBh4GggWvBIkDJALIADj/jv3O+zL63fiz90f3R/cb+Dj5MvpR+0L8DP2O/Y79jv2O/Tn93fxC/A774vl++Nb25fXe9N703vTe9GT1YPaz9zj5Dvur/EX+d/9kAEMBJAIjAzIEOAXOBR4GHgbOBfIEMgSJA3ICXwEUANj+tv2r/EL8CfxC/Az9Zf6+/w4BJAL0Ar4DMgRvBG8EMgS+A/QCuwEyAIP+3fxR+zL6j/mP+TL6DvsJ/GX9g/53/3YAXwFyAokDrwQ4Bc4FzgXOBYIFOAU4Ba8EbwS+A/QCSgK7AV8BKAH2AJ0AFACK/wr/vf7y/mP/BgCyAH0BJAJyAscCmwJyAiQCmwEoAZ0A7P8i/2X+tv05/d38q/xC/An8zvvO+wn8Qvyr/Kv83fyr/Hf8QvzO+w77MvqP+d34G/iz97P3G/gb+H74fvgb+Bv4s/dH99b2YPZg9uX15fXl9WD21vYb+Dj5fvoJ/I79OP/2APQCrwRxBk0IKgmgCRsKGwqcCpwKIgsiCyILIgsiCyILIgsiCyILIgsiC5wKGwqgCSoJuQhNCOUH5QeCByMHyAbOBfIEMgQjA90BnQDy/gz9Dvvd+Nb2ZPW/8ybzJvMm81H0YPYb+DL6zvs5/UX+OP8jAN4AfQG7AX0ByAD6/wr/Rf6O/d38QvzO+1H7DvtR+5H7QvwM/dz9of53/yMAsgAoAd0BcgL0AlUDiQOJAyMDmwK7AfYA+v/y/gD+3fwJ/FH7UfvO+wz9Rf6+/0MBxwJvBB4G5QcqCZwKIguvC68LIgsbCioJggeCBb4D3QFCAAr/Rf7c/bb93P0j/mX+of7y/mP/zv9CAGQAdgBCAOz/d//y/mX+3P2O/Tn9DP0M/Qz9Zf3c/SP+Zf6D/oP+of4i/+z/9gAkAlUDrwTOBcgG5Qe5CCoJKgkqCbkIggdxBvIEiQMkAg4B+v8K/yP+Of13/JH7DvvI+sj6fvp++uL5j/nd+Bv4R/dg9mT13vTe9N705fXW9rP3fvjd+Dj5j/ni+TL6fvp++n76fvp++sj6UfsJ/N383P0K/zIAQwFyAokDrwTOBcgGggflB00ITQjlB+UHggcjB8gGcQbOBTgFrwQyBPcDvgOJAyMDxwJyAkoCcgL0AokDMgSvBDgFzgUeBnEGyAbIBsgGcQbOBa8EiQMAAlMAg/6r/Mj6OPkb+LP3s/cb+N344vnI+s77d/wM/Y793P0A/rb9Of13/FH7Mvrd+LP3YPZk9d70UfRR9FH0ZPXW9hv4j/nI+gn8Of1l/s7/KAGbAr4D8gTOBXEGyAbIBsgGyAYeBjgFvgMkAnYA8v7c/Qz9q/zd/GX9Rf5j/50A3QEjAzIEOAXOBR4GHgaCBW8EIwObAd3/AP53/A77fvoy+n76DvvO+6v8tv29/uz/KAFKAlUDMgSvBDgFggXOBc4FzgWCBTgF8gQyBIkD9AIkAl8BsgD6/zj/g/7c/Y79jv3c/aH+nP/IALsBxwKJAzIErwTyBK8EMgSJA/QCSgKbASgBsgAjAK3/OP/y/tj+8v44/63/BgBTAJ0AsgCyAGQA7P9O/4P+tv3d/An8kfsO+w77yPrI+sj6fvoy+uL5j/nd+H74s/dH99b2YPbl9eX1YPZH9xv4OPl++s77jv13/18BIwOvBB4GIwflB7kIKgmgCRsKGwobChsKGwqcCiILIgsiCyILIgucChsKKgm5CE0I5QeCB4IHIwcjB8gGcQbOBYIF8gRvBIkDSgKyANj+3fx++n74YPZR9CbzJvO/81H05fVH9934MvqR+wz9Rf6K/3YA9gAoAd4AUwCK/6H+tv3d/An8kfsO+376fvoy+n76fvoO+1H7Cfx3/Dn93P29/r7/sgCbASQCmwLHAvQCxwJyApsBiQA4/9z9d/xR+376Mvoy+sj6zvs5/fL+3gDHAq8EcQZNCKAJIguvC0EMQQyvCxsKuQjIBvIE9AJfASMATv+9/mX+Zf5l/oP+2P5O/+z/nQAOAV8BfQF9AZsBfQFDAcgAMgCt/07/Cv/y/tj+vf6h/kX+3P2O/WX9jv0A/r3+vv/2AHICMgSCBcgGTQgqCRsKnAqcChsKKgnlB3EG8gQjA7sBZAA4/wD+Of2r/EL8QvwJ/An8zvuR+w77yPoy+jj5s/fW9uX1ZPXe9N70ZPXl9WD21vZH97P3G/h++H74fvgb+LP3s/ez9xv4fvg4+TL6kfur/Nz9Cv9TAJsB9AIyBDgFHgZxBsgGIwcjByMHIwcjByMHIwcjByMHIwcjB8gGcQYeBoIFOAWvBG8ErwTyBDgFzgVxBsgGggflB7kIKgmgCaAJKgm5CIIHcQbyBCMDKAFO/479CfwO+376Mvp++sj6UfvO+3f8Of0j/tj+Iv8i/9j+I/45/Qn8yPo4+Rv41vbl9d70UfRR9FH0UfTe9GT1YPZH9374j/kO+3f8AP6K/w4BSgJVA28EOAXOBXEGcQYeBjgFvgMkAlMA2P62/Qz9q/zd/Dn93P3Y/vr/XwHHAm8EzgUjB+UHTQjlByMHggWJA0MBOP9l/Qn8Dvt++jL6Mvp++g77CfwM/SP+OP8yAA4B3QFyAvQCiQO+AzIEbwSvBPIErwRvBL4DIwNKAl8BZABO/0X+Zf2r/Hf8d/wM/bb9of6c/7IA3QEjAzIEOAXOBc4FggXyBDIEIwNKAl8BZACt/wr/of6h/r3+Cv9j/63/FAB2AN4AKAEoAQ4ByABkAN3/Cv9F/o79DP2r/EL8zvtR+w77fvoy+o/53fgb+Ef3YPZk9d70UfRR9FH0UfTe9GT15fVH9934fvp3/GX+IwCbAccCvgNvBDgFHgbIBiMH5QdNCCoJoAkbCiILrwtBDNoM2gxBDK8LIgucChsKoAkqCSoJKgm5CLkIuQhNCOUHggcjBx4G8gSJA5sBd/85/Q773fhH92D25fXl9eX11vYb+OL5Ufs5/fL+UwB9AUoCxwLHAnIC3QH2ADIAiv/y/kX+jv3d/EL8zvvO+5H7kfuR+5H7zvtC/N383P29/s7/9gAAAvQCvgNvBK8ErwRvBIkDSgLeAE7/tv1C/FH7fvoy+n76DvsJ/GX98v7IAPQCOAWCB6AJIgtBDNoM2gxBDCILKgmCB4IFvgMAAnYAIv8j/jn93fx3/Hf8q/zd/Az9Of1l/bb9AP5F/oP+vf69/oP+Rf4A/tz9Zf0M/av8QvzO+1H7yPp++n76yPoO+wn8DP1l/s7/XwFVAzgFggegCSILQQzaDEEMrwucCioJ5QceBq8EIwO7AYkAiv/Y/mX+I/4A/iP+Rf5F/tz9Of13/FH7fvri+Tj53fh++Bv4G/gb+Bv4fvjd+Dj5OPmP+Tj5OPnd+Bv4s/ez97P3G/h++Dj54vkO+3f83P13/w4BcgKJAzIErwTyBDgFOAXyBPIE8gTyBPIEOAXOBR4GyAYjByMHIwdxBh4GggXyBPIErwTyBIIFHgZxBiMHggdNCLkIKgmgCaAJoAm5COUHyAY4BVUDmwH6/0X+3fyR+376Mvri+TL6fvpR+0L8DP0A/oP+vf6h/kX+tv3d/M77yPo4+Rv41vZk9d70UfS/87/zv/O/87/zUfRk9WD2s/eP+ZH7Zf1O//YAcgL3AzgFcQaCB00ITQhNCCMHzgUyBEoCiQAK/9z93fxC/M77Cfyr/Lb9OP8OASMD8gRxBoIHTQjlByMHzgX3A0oCZAC9/jn9CfwO+376Mvoy+n76DvvO+3f8Zf0j/gr/IwAoASQCIwP3A68EggXOBR4GHgYeBoIF8gT3A/QCmwFkAE7/Zf6O/Qz93fwM/bb9g/7O/0MB9AKvBHEGgge5CCoJKgm5COUHyAaCBTIEIwPdAcgA7P+K/2P/iv++/xQAZACJAMgAyADIAMgAyADIAIkAQgDO/07/vf4j/o79DP2r/Hf8CfxR+376OPl++Ef3YPZk9d70UfS/87/zv/O/89705fVH9zj5Dvur/GX+zv/2AN0BmwJVA/cDbwTyBIIFHgZxBoIHTQigCZwKIguvC68LrwuvC68LIgsiCyILIgucCpwKGwobCqAJoAmgCaAJKgm5COUHcQbyBMcCiQBF/gn84vkb+GD2ZPXe9N703vTl9Uf3OPkO+6v8Rf6K/1MAsgCdAEIArf8K/2X+tv05/av8CfyR+w77yPoy+uL5j/k4+Y/54vnI+pH7d/yO/aH+zv8oAXICvgOvBIIFzgXOBTgF9wNKAnYAvf4M/ZH7fvo4+X74fvjd+OL5kfuO/SMAxwI4BSMHKgkbCiILIgucChsKuQiCB84FMgRyAsgAY/8j/jn9QvyR+8j6fvp++n76DvuR+0L8q/wM/Tn9Zf2O/Y79tv2O/WX9Of2r/An8Dvsy+jj5fviz97P3s/ez93743fji+VH7Zf2t/0oC8gSCB6AJIgtBDNoMQQyvC5wKKgnlBx4GrwQjA5sBUwBO/6H+Rf4j/tz9tv1l/Tn93fyr/Hf8CfyR+w77fvri+Y/5j/mP+Y/5j/mP+Tj5OPnd+H74s/dH92D25fVk9d703vRk9eX1R/fd+Mj6q/xl/gYAXwFyAiMDvgP3AzIE9wP3A74DvgO+A/cDbwTyBDgFggXOBc4FzgWCBYIFOAU4BTgFOAU4BTgFggXOBXEGggdNCKAJnAoiCyILIgucCqAJuQiCBx4GbwTHAvYATv/c/av8CfwJ/EL83fyO/YP+Y/8UAJ0A9gAOAfYAiQDd/wr/I/4M/c77yPqP+d34s/dH92D25fVk9WT15fVg9kf3fvji+ZH7DP29/nYAcgJvBB4G5QcqCaAJGwobCioJTQjIBvIEIwObAez/Zf4M/UL8Qvyr/Nz9iv99AYkDOAXIBoIH5QflB4IHcQY4BYkD3QEUAGX+3fyR+zL6OPl++Bv4G/jd+I/5MvpR+0L8Of1l/or/nQDdAfQCMgQ4BR4GyAbIBnEGzgXyBPcDmwIoAZz/I/7d/JH7DvvI+g77zvsM/b3+nQCbAm8EHgaCB00IuQhNCOUHIwceBvIEvgNKAvYA3f8K/6H+g/6D/oP+vf7y/iL/Y/++/yMAdgDIAN4A3gDeALIAiQBkADIA+v+K//L+I/4M/Qn8yPqP+X74R/fl9d70v/OG8t/x3/GG8r/z3vRg9hv4j/kO+0L8Of1F/jj/FADeAJsBSgL0AlUD9wOvBDgFHgYjB+UHuQigCRsKnAqcCpwKnAqcChsKGwqgCSoJuQi5CLkIuQgqCSoJKgm5CIIHcQbyBCMDKAEK/6v8Mvob+Nb2ZPVR9FH0UfTe9GD2s/eP+Q77q/zc/SL/BgCdAN4A3gCyAFMA3f93/yL/of4j/mX9q/wJ/FH7yPp++jL64vni+TL6fvpR+0L8jv3y/lMA3QEjA28EOAU4Ba8EvgNyAvYAIv85/Q773fhH9+X1ZPVk9WD2s/fi+UL8of7eACMD8gRxBoIHuQgqCSoJuQjlB8gGggUyBMcCXwHs/6H+Zf13/JH7Dvt++sj6DvtR+877Qvzd/GX9AP6h/jj/vv8UAEIAMgDO//L+tv13/FH7Mvrd+Bv4s/ez97P3fviP+Q77Of2t/3ICOAXlB5wKQQx6DdAO0A7QDtAOeg1BDJwKuQjIBvIEiQNKAkMBnQD6/3f/8v6h/iP+3P2O/Tn9q/xC/M77UfsO+8j6fvp++sj6yPrI+n76Mvri+Tj53fiz99b25fVk9d703vTl9db2fvgy+gn83P2t/30B9AIyBPIEzgXOBc4FzgXOBYIFOAXyBPIE8gQ4BYIFzgUeBh4GHgbOBc4FzgWCBYIF8gSvBG8EbwSvBPIEzgXIBoIHuQgqCSoJKglNCIIHcQaCBfcDmwIOAYr/I/4M/UL8zvvO+wn8q/w5/QD+of5j/yMAyAAoAUMBDgGJAOz/OP9F/jn9CfwO+zL6OPkb+Ef35fVk9d703vTe9GT15fXW9rP3OPnI+qv8of72ACMDOAUjB00IKgkqCSoJTQgjB84F9wMkAkIAg/7d/An8kfvO+6v8AP6t/30BIwOvBB4GIwflB+UH5QcjB3EGOAW+AyQCiQDy/mX9CfwO+zL6j/mP+eL5fvoO+5H7QvwM/SP+Y/+yACQCvgOCBcgG5QdNCE0ITQiCBx4GrwTHAvYAIv+O/Qn8yPoy+uL5fvqR+wz98v72ACMD8gRxBuUHuQgqCSoJuQjlB8gGOAW+A0oC9gDs/zj/vf5l/gD+tv2O/Y79tv3c/UX+of7y/iL/OP9j/77/QgDIAEMBXwEOAXYArf+D/mX9Cfx++t34R/dk9b/zhvLf8TDxMPEw8Ybyv/Pe9GD2s/fd+DL6Uft3/GX9Zf4i/77/UwDeAEMBmwEkAscCiQMyBDgFcQaCB00IuQigCRsKGwqcChsKGwqgCaAJoAmgCRsKnAqcCpwKnAqgCSoJ5QfIBvIEIwMoAQr/3fzI+jj5s/fW9mD2YPbW9rP33fji+ZH73fwj/jj/7P9TAFMAMgDd/4r/Iv+9/kX+tv05/av8CfyR+8j6MvqP+Tj5fvh++Bv4G/jd+I/5Dvvd/L3+nQBKAokDbwSvBK8EMgQjA90BQgBl/gn84vmz9+X13vTe9GT1YPYb+DL6QvxF/mQAmwKvBHEG5QcqCaAJoAmgCbkI5QcjB84FbwT0ApsBZABj/4P+AP6O/WX9Zf2O/bb9AP5l/iL/+v8OASQCIwO+AzIE9wNVA3ICXwHs/2X+q/xR+4/5fvhH99b2YPbW9hv44vkJ/L3+fQEyBMgGKgkiC9oMIQ7QDtAOIQ7aDCILoAmCB84FMgTHAn0BZACK//L+Rf62/Qz9QvzO+w77fvoy+uL54vni+TL6Mvoy+jL64vni+Tj53fh++LP31vZk9b/zJvPf8TDxMPHf8SbzUfTl9Rv4MvpC/EX+FACbAccCvgMyBG8ErwRvBPcDiQNVAyMDIwNVA4kD9wNvBPIEOAWCBc4FHgYeBs4FggU4BTgFggXOBcgGggdNCCoJoAmgCaAJoAkqCbkITQgjB84FMgSbAkMBFAA4/73+g/6D/qH+8v5j//r/nQBfASQCmwLHAscCcgLdAQ4BQgBj/2X+Zf1C/FH7fvqP+X74R/dg9mT1UfRR9L/zv/Pe9GT11vZ++H76d/yh/sgAxwJvBM4FyAYjB4IHIwceBvIEIwMoAQr/DP2R+3764vni+TL6Dvt3/Nz9Y//2AHICvgPyBIIFzgWCBfIEMgQjA7sBZADy/o79QvwO+3764vni+TL6Mvp++g77kft3/Lb9Iv/eAMcCrwRxBuUHKgkbCpwKnAobCioJ5QceBvcDuwF3/2X9kft++uL54vnI+gn8jv13/30BiQOCBSMHuQigCRsKGwoqCeUHcQavBCMDmwF2AIr/vf4A/jn9q/xC/An8CfwJ/EL8d/yr/Az93P29/q3/nQBfAd0B3QHdAX0ByAD6//L+Zf3O++L5s/fl9VH0hvLf8TDxMPHf8Ybyv/Nk9WD2s/c4+X76kfur/GX9I/6h/gr/Tv9j/3f/vv9CAA4B3QH0AvcD8gQeBiMHTQgqCRsKnAoiCyILrwuvC68LQQxBDEEM2gzaDEEMQQyvC5wKoAm5CMgG8gT0At4Avf7d/FH7Mvo4+X74fvh++N344vkO+3f83P0K/87/UwCdALIAnQBkADIABgDd/87/nP9j//L+Rf6O/d38CfwO+zL6j/nd+H74fvjd+I/5yPpC/Nz9d//2AEoCiQMyBK8EbwT3A/QCfQGc/2X9Dvvd+Ef3YPbl9eX11vYb+Dj5DvsM/SL/XwGJAzgFcQaCB00IuQi5CLkIuQjlByMHHgbyBL4DmwKbAZ0Avv8K/2X+I/4A/gD+I/69/or/nQDdAfQCMgTyBIIFggU4BW8EVQPdAUIAg/6r/A77OPmz99b2YPZg9kf33fh++qv8Tv8AAq8EIwegCa8L2gwhDiEOIQ7aDK8LnAq5CIIHHgZvBPQCuwGJAIr/of7c/Tn9q/wJ/JH7UftR+5H7zvtC/EL8d/xC/EL8QvwJ/M77Uft++o/5G/jW9t70v/OG8jDxMPEw8d/xJvPe9GD2G/gy+kL8Rf7O//YA3QFyAscCmwJyAkoCJALdAbsBuwG7AQACSgLHAiMDiQP3A28ErwTyBPIErwRvBK8E8gSCBXEGIwflB7kIKgmgCRsKGwobCqAJuQiCB3EG8gSJA3ICXwF2APr/zv++/93/QgDeAH0BJAL0AlUDvgP3A74DVQPHAiQCfQH2AHYAzv8K/0X+Zf1C/A774vl++Ef3YPZk9d70UfRR9N705fXW9n74fvp3/GX+UwAkAokDrwTOBXEGyAYeBjgFvgPdARQAZf4M/c77UfsO+w77kft3/Lb9Iv92AN0B9AL3A68E8gQ4BTgFrwQyBCMDAAKdADj/AP4M/UL8kftR+w77yPrI+sj6DvuR+3f8tv04/w4B9AKvBB4Ggge5CKAJoAmgCSoJ5QceBjIE3QF3/wz9DvuP+d34fvjd+I/5Dvt3/EX+FAAAAvcDggXIBoIH5QeCB3EGggWvBL4DmwK7AcgA3f/y/kX+jv0M/av8QvwJ/M77zvtC/N38jv2h/r7/yACbAUoCxwL0AscCcgIAAigB7P9F/kL84vmz9+X1UfQm84by3/GG8ibzv/Pe9GD2R/d++Dj5MvoO+877d/zd/Dn9jv3c/QD+Zf7Y/nf/MgAOAQAC9AIyBDgFcQaCB00IKgmgCRsKnAoiC68LrwtBDEEM2gzaDNoM2gzaDEEMrwsbCrkIyAbyBMcC9gBO/9z9q/yR+8j6Mvoy+n76DvsJ/Az9I/4K/77/IwBTAHYAdgCJAIkAnQCdAIkAdgBCAPr/rf84/4P+tv2r/JH7yPri+Tj5OPk4+Y/5fvqR+938I/6K/94AJAJVAzIErwSvBL4DcgKJAGX+Qvx++t34s/fW9tb2R/cb+N34fvrO+7b9iv9fAfQCbwTOBcgGggdNCLkIuQi5COUHggdxBs4F8gQyBFUDmwK7AcgAFACt/4r/rf8UAN4A3QEjAzIEggXIBoIH5QdNCOUHIwceBm8EcgJTACP+Cfx++jj5fvh++N34j/nI+kL8I/5kAPQCggXlBxsKrwvaDHoNIQ56DdoMQQwiCxsKuQgjB84FbwQjA7sBZAA4/wD+DP1C/M77zvsJ/Hf83fwM/Tn9Of1l/Y79tv3c/dz9Zf2r/FH7j/mz9+X1UfQm89/xMPEw8d/xhvK/8970YPYb+OL5zvs5/YP+d/8GAFMAZABCABQA3f+c/3f/d/93/63/+v9kAPYAfQEkAscCIwOJA4kDiQO+A/cDbwTyBIIFcQYjB+UHuQigCRsKGwobCqAJuQiCBx4GrwS+A8cC3QEOAXYABgCc/2P/d//O/2QADgGbAQACJAIkAt0BmwEoAcgAUwAGAK3/OP+h/gD+Of1C/A77j/kb+GD2ZPW/8ybzhvKG8obyJvO/8970YPZ++DL6QvxF/gYAmwHHAr4D9wO+A/QCAALIAIr/I/4M/Qn8UfvI+n76yPpR+0L8Zf2h/r7/3gDdAZsCVQP3AzIEbwQyBIkDmwJfATIAOP9F/o793fxC/JH7Dvt++jL6Mvoy+sj6zvs5/aH+UwAAAr4DggUjB7kIKgmgCSoJTQjIBq8EmwKJAIP+q/xR+zL6j/k4+Y/54vkO+6v8g/7IAPQC8gRxBiMH5QflB4IHyAZxBoIFbwS+A8cC3QH2AAYAIv9F/o793fxC/An8CfxC/Az93P0K/0IAXwFKAiMD9wOvBPIE8gSvBL4DJAJCACP+zvuP+bP35fVR9CbzJvOG8ibzv/NR9GT1YPaz9934j/l++g77kfvO+wn8CfxC/Hf8q/wM/Y79AP69/nf/ZAB9AZsC9wPyBM4FyAaCB00IuQigCZwKIguvC9oMeg0hDtAO0A7QDiEO2gyvCxsKTQjIBjgFvgMkAp0ACv+O/UL8UfvI+sj6UfsJ/N38jv0A/iP+Zf5l/qH+2P7y/vL+2P7Y/r3+vf69/oP+I/62/Qz9CfwO++L53fiz99b2YPZg9tb2s/d++OL5Dvt3/CP+rf8OASQC9AIjA/QCJAIOAYr/3P1C/H76OPl++Bv4G/gb+N344vlR+6v8Zf4GAJsBIwNvBIIFyAaCB00ITQhNCOUHggfIBh4GOAWvBL4DmwJDARQA8v4A/o79Of1l/QD+8v4jAJsBIwNvBM4FyAYjB8gGHgbyBIkDmwGc/479kfvi+X74R/dg9mD2YPZH9374Mvp3/PL+uwFvBMgGuQicCq8LQQzaDNoMQQwiCxsKKgnlB8gGggX3A3IC9gBj/wD+q/wJ/JH7kfvO+wn8d/wM/Tn9Zf22/SP+g/69/qH+I/4M/ZH74vkb+GD23vQm89/xMPEw8XrwMPHf8Sbz3vTW9t34fvpC/Lb98v6+/zIAZAB2AGQAUwAyAOz/vv+c/5z/7P9kAA4BmwEkApsC9AJVA4kDiQP3AzIE8gTOBcgG5Qe5CBsKnAqvC68LQQyvCyILGwq5COUHyAbOBa8E9wP0AiQCXwHeALIA3gBfAd0BcgLHAvQCIwMjA/QCmwIAApsBKAHIAHYAIwDO/3f/8v4j/gz9kfvi+Rv41vZk9b/zJvOG8obyJvO/81H05fVH9zj5yPqr/IP+FABfAXICIwNVAyMDmwKbAZ0Aiv+D/rb93fxC/An8zvtC/N38tv2D/nf/iQCbAZsCvgOvBIIFzgXOBYIFrwS+A/QCSgKbAcgA7P/Y/o79d/xR+8j6Mvp++sj6kfur/CP+vv+bAYkDggUjB7kIoAkbChsKKgmCB84F9wMkAjIAZf7d/FH7Mvo4+d34OPky+s773P0UAHICrwTIBk0IoAkbChsKGwobCqAJKgm5COUHIwceBvIEvgNyAigBzv+h/tz9jv2O/QD+of5j/zIAKAEkAlUDMgQ4Bc4FzgU4BW8E9AIoAQr/q/x++hv45fVR9Cbz3/Ew8TDx3/GG8ibzUfRk9WD2R/cb+N34OPmP+eL5Mvp++n76yPoO+1H7zvtC/Hf8DP3c/aH+nP92AH0BcgJVA28EggXIBuUHKgkbCq8L2gx6DSEO0A4hDnoN2gyvCxsKKgnlB8gGggX3A0oCnQDY/o79q/xC/EL8d/zd/Dn9tv0A/kX+of7Y/gr/Iv84/zj/Tv+K/87/IwBTADIA3f9O/4P+Zf1C/A774vnd+Bv4s/ez97P3G/h++I/5fvrO+zn9of4GAEMBJAKbApsCJAJDARQA8v62/Xf8Ufsy+o/5OPmP+eL5yPrO+wz9Zf6+/w4BcgK+AzgFyAblB7kIKgmgCaAJoAmgCSoJTQiCB3EG8gSJAwACnQCc/73+Rf4j/oP+Iv8yAJsBVQPyBHEGggflB+UHggdxBjgFiQPdARQARf53/Mj6OPkb+Ef3R/dH9xv4OPkO+2X97P9yAq8EyAa5CBsKrwtBDNoM2gzaDNoMQQyvCxsKKgkjB4IFiQN9Ab7/g/6O/Qz93fzd/N38DP1l/bb9I/7Y/nf/7P8GAL7/Cv/c/Xf8Dvs4+bP35fVR9IbyMPF68Lvvu+968DDxhvJR9GD2s/c4+cj6zvur/Dn9jv0A/kX+Zf6D/mX+I/4A/tz9AP5F/tj+d/8jALIAQwGbASQCxwJVAzIEOAVxBoIHKgkbCq8LQQx6DXoNeg16DdoMrwsiC5wKoAm5COUHyAbOBa8E9wO+A74DMgSvBPIEOAWCBYIFggU4BfIEbwT3A1UDxwJKAgACuwGbAUMBnQCt/2X+3fxR+4/5s/fl9d70JvOG8t/x3/GG8obyv/Pe9OX1s/c4+cj6QvyO/b3+nP8yAIkAdgAGAGP/g/62/d38QvwJ/An8Qvyr/Az9jv3c/WX+Cv8GAA4BAAL0Ar4DbwSvBG8E9wOJAyMDmwIAAigBBgDY/o79d/yR+8j6Mvri+eL5MvrI+s77Zf1O/0MBIwPyBHEGggflB00I5QcjBx4GrwQjA30Bvv/c/UL8yPqP+d34fvjd+DL6kfs5/Tj/DgHHAjIEOAXOBcgGIweCB4IHggcjB3EGHgY4BTIExwJDAb7/Zf45/Xf8CfzO+wn8d/wM/dz98v4yAH0BxwK+A28ErwRvBPcDxwJfAZz/jv1R+9341vZR9Cbz3/Ew8TDxMPHf8Ybyv/NR9GT1YPbW9rP3G/h++Dj5j/ky+n76fvp++sj6yPoO+1H7zvt3/Dn9I/4i/xQAKAFyAr4DOAXIBk0IGwqvC3oN0A5FEEUQDBEMEUUQhg/QDnoN2gyvC5wKKgmCB84FMgT0At0BQwH2ALIAiQCJAJ0AyAD2AA4BKAFDASgBKAEOAfYA9gAoAV8BmwG7AbsBfQHeABQACv8A/qv8kft++o/53fh++Bv4G/gb+H743fiP+X76zvsM/SP+Cv+c/77/iv/y/iP+DP3O+376j/nd+Bv4G/gb+H743fg4+eL5fvqR+6v8AP5j/7IAAAJVAzIEOAUeBsgGggflB+UHggfIBh4G8gT3A/QC3QHIAM7/Cv+h/oP+Cv/6/0MBmwL3AzgFcQbIBiMHIwdxBoIFbwT0Al8BnP8A/kL8yPo4+X74s/dH97P3fvji+ZH7jv2t/90B9wMeBuUHoAkiC0EM2gx6DSEOIQ4hDnoNrwsbCk0IzgX3AyQCsgCc/73+AP5l/Qz93fwM/Y79I/7y/nf/3f8GAM7/Tv+D/jn9zvsy+hv4YPZR9N/xevC77/Tu9O707rvvMPGG8r/z3vRg9rP33fji+cj6kftC/N38Of1l/Tn9DP2r/EL8Qvx3/Kv8Of22/WX+2P5j//r/nQBfAUoCVQOvBB4GggcqCRsKIgtBDEEMQQxBDEEMrwsiC5wKoAm5CIIHyAbOBTgFrwSvBK8ErwTyBDgFggWCBYIFggU4BfIEMgSJA5sCAAK7AbsBmwFfAfYAIwA4/yP+3fxR++L5G/hg9t70v/OG8t/xMPEw8TDx3/GG8r/z3vTl9Uf3fvji+cj6zvt3/Az9Of0M/av8QvwJ/An8CfwJ/EL8Qvx3/Kv83fw5/Y79Rf5O/2QAmwGbAokDbwQ4Bc4FHgZxBnEGHgY4BW8EIwMkAg4B7P/Y/tz93fwJ/JH7UfvO+6v8AP6c/30BVQPyBMgG5Qe5CCoJKgm5CE0IIwceBq8EIwN9Ab7/AP6r/JH7DvsO+877q/zc/Tj/sgAkAokDrwTOBcgG5Qe5CCoJoAmgCaAJKglNCMgGggX3A5sCKAHO/6H+tv0M/av8q/wM/bb98v5TALsBIwNvBDgFzgXOBYIF8gT3A3ICUwDc/VH73fjW9mT1v/Mm84byhvKG8ibzv/NR9FH03vRk9WD21vaz9374OPni+TL6fvrI+sj6yPrI+g77kfsJ/N38tv2h/nf/dgB9AccCMgTOBeUHoAmvC3oNhg8MEdsR2xHbEdsRDBFFEIYP0A56DUEMnAoqCYIHHgbyBDIEiQP0AnICJALdAZsBmwF9AX0BXwEoAQ4B3gDeAMgA3gAOASgBQwFDASgB3gB2AN3/8v7c/av8kft++jj5fvgb+LP3R/dH90f3s/cb+N344vnI+s77d/zd/Dn9DP13/M77yPri+Tj5fvgb+LP3R/dH90f3R/dH97P3G/jd+OL5DvtC/Lb9OP+dAAACiQOvBM4FyAYjB4IHggeCByMHcQbOBa8EiQMkAt4A3f84/wr/Tv8GAPYAJAKJA68EzgVxBsgGyAbIBh4GggUyBMcCKAF3/7b9Cfx++jj5fviz97P3G/jd+OL5Ufs5/SL/KAEjAzgFIwcqCZwKQQx6DSEO0A6GD9AOIQ7aDCILKgmCB4IF9wNyAg4B3f8K/4P+Zf6h/iL/zv9kAN4AKAFDASgByAAyADj/3P1C/DL6fvhg9lH0hvIw8Xrwu++773rwMPHf8Sbzv/Pe9OX1R/d++OL5Uft3/GX93P3c/bb9Zf0M/d383fzd/Az9Of1l/WX9tv3c/QD+g/44/yMAQwGbAvcDggUjB7kIoAmcCiILrwuvC68LrwsiCxsKKglNCIIHyAZxBh4GHgYeBh4GHgZxBsgGggflB+UHTQjlB+UHIwfIBh4GzgWCBTgFrwRvBPcDVQObApsBMgCh/gz9UfuP+bP3YPbe9L/zJvMm8ybzJvO/81H0ZPVg9kf3fvji+cj6zvt3/N38DP0M/Qz9DP0M/WX9tv0j/kX+Rf5F/iP+3P0A/iP+vf53/1MAKAEAAvQCvgNvBPIEggXOBc4FzgU4Ba8E9wP0At0BsgCK/2X+Zf13/M77zvsJ/Kv8tv04/94AmwJvBM4FIwdNCCoJKgmgCSoJuQjlB8gGggX3A0oCnQAi/wD+Of2r/Hf83fxl/WX+d/+dAN0BIwNvBIIFyAaCB00IKgmgCaAJKgm5COUHyAY4Bb4DSgLIAGP/Rf5l/av8d/zd/Lb9vf4UAH0B9AIyBIIFcQYjB4IHIwceBq8ExwKdAEX+zvuP+bP3YPbe9FH0v/Mm8ybzhvKG8ibzJvO/81H0ZPXl9db2R/ez9xv4G/gb+Bv4G/gb+Bv4G/h++N34OPky+sj6zvvd/AD+iv9fAYkDHgZNCJwK2gzQDoYPRRAMEQwRDBFFEEUQ0A4hDkEMIgugCbkIggdxBoIFrwT3A4kD9ALHAnICcgJyAkoCJALdAZsBXwFDAQ4B9gD2AA4BKAEOAfYAnQD6/yL/I/4M/Qn8Dvsy+o/53fgb+LP3R/fW9tb21vZH97P3fvjd+I/54vky+uL54vk4+d34G/iz90f31vZg9mD25fXl9WT1ZPVk9eX1YPbW9rP33fji+VH7q/wj/r7/QwGbAvcD8gTOBR4GyAYjByMHyAZxBoIFbwQjAwAC9gAyAN3/7P9kAEMBSgJVA28EggUeBsgGyAbIBnEGzgXyBL4DcgLIACL/jv3O+376OPl++LP3R/dH9xv43fgy+pH7Of3Y/rIAmwJvBHEGTQgbCiILQQzaDEEMrwucCqAJ5QceBm8ExwIoAYr/Rf5l/d383fwM/Y79I/7Y/or/BgB2AJ0AiQAyAGP/Rf7d/A77OPlH9970JvPf8TDxevC777vvu+968DDx3/GG8r/zZPXW9n74MvpR+3f8Of2O/bb9jv1l/Tn93fx3/Hf8QvxC/EL8QvxC/EL8q/w5/UX+d//2AJsCbwQeBoIHuQgbCpwKrwtBDEEMQQxBDK8LIgucChsKoAkqCbkIuQi5CLkIuQgqCaAJGwqcCpwKnAqcCpwKGwobCqAJKgm5CE0I5QeCByMHHgY4BfcDcgLeACL/Of1R+4/5s/dg9t70UfQm8ybzhvKG8ibzv/NR9N705fXW9rP3fvg4+Y/5j/ni+eL5MvrI+lH7Cfx3/Kv8q/yr/Kv8q/zd/Dn9jv0j/tj+rf+JAJsBmwK+A28EOAWCBc4FzgXOBYIFrwT3AyMDJALeAK3/g/6O/d38d/yr/Az9AP5O/8gAcgL3A4IFyAZNCCoJGwqcCpwKnAobCioJ5QdxBq8EIwNfAd3/of6O/d38d/xC/EL8q/xl/UX+Y/+JALsBIwNvBIIFcQYjB4IHggcjB3EGggUyBMcCQwGK/wD+d/yR+w77yPoO+877q/y2/SL/sgBKAvcDOAVxBsgGIwfIBs4FbwRKAiMAAP4J/DL63fhH92D2ZPVR9L/zJvOG8obyhvIm87/zUfRk9eX1YPZH90f3s/ez97P3s/dH90f3R/fW9kf3R/dH97P3G/h++I/5DvsM/Tj/mwH3A3EGuQicCkEMIQ6GD0UQRRBFEIYP0A4hDtoMrwsbCioJ5QfIBh4GOAWvBPcDVQP0ApsCcgJyAnICcgJyAnICcgJyAnICmwL0AiMDVQNVAyMDxwIkAkMBUwB3/6H+3P0M/Xf8zvsO+3764vmP+Tj5OPk4+Tj5j/ni+X76yPrI+n76MvqP+d34fviz97P3R/fW9mD25fVk9WT13vTe9N703vRk9WD2R/d++DL6zvuO/U7/9gCbAjIEggXIBuUHuQigCaAJGwqgCbkI5QfIBoIFrwS+A1UD9AIjA1UD9wPyBM4FyAaCB00IuQgqCbkITQiCB3EGOAW+A0oCyAA4/7b9QvzI+o/5fvgb+LP3G/h++I/5fvrO+2X9Tv99Ab4DzgVNCBsKrwtBDNoM2gxBDCILGwpNCMgG8gQjA5sBQgA4/2X+AP4A/iP+vf5j/wYAsgBfAd0BJAIkArsByAB3/9z9Qvx++t34R/fl9VH0v/Mm84by3/Ew8TDx3/GG8r/z3vTW9n74MvqR+wz9AP7Y/k7/iv93/zj/2P5l/gD+jv0M/av8CfzO+877Cfx3/Dn9Rf5j/8gASgL3A4IFIwe5CBsKIguvC0EMrwuvCyILnAobCioJuQhNCOUH5QeCB4IHggflB00IuQgqCaAJoAkbChsKGwqgCaAJoAmgCaAJoAkqCbkI5QfIBoIF9wNKArIACv85/ZH74vl++Ef35fXe9L/zJvMm8ybzJvO/81H03vRk9eX1YPZg9mD21vZH97P3G/h++Dj5j/ni+TL6Mvp++n76fvp++sj6UfsJ/Kv8jv2D/s7/KAFyAokDrwSCBR4GcQbIBnEGHgbOBTgFbwSJA3ICQwFCAGP/vf5l/mX+8v7d//YASgKJA/IEHgaCB00IKgkbChsKnAobCqAJKglNCMgGggW+AyQCnQA4/yP+Of13/An8zvsJ/Hf8Of1F/pz/9gByAr4D8gQeBsgGIwcjB8gGHgY4BfcDmwIoAc7/of6O/av8QvwJ/EL8q/yO/aH+BgCbAVUD8gRxBoIH5QflByMHHgavBCMDfQHO/yP+d/zI+t34s/dg9t70v/Mm8ybzJvMm8ybzv/Pe9GT1YPZH97P3fvh++H74G/gb+LP3s/dH90f31vbW9tb21vZH97P33fjI+qv82P5DAb4DHga5CJwK2gwhDoYPRRBFEEUQhg/QDiEOeg1BDK8LnAobCioJTQiCB8gGzgU4BfIErwRvBDIE9wP3A/cD9wMyBG8ErwTyBPIE8gSvBDIEiQP0AiQCKAFkAHf/of7c/Tn9d/zO+w77fvri+Y/5OPk4+Tj5j/mP+Y/5j/mP+Tj5fvgb+LP3R/dH99b2YPbl9WT13vTe9FH0UfS/87/zv/O/81H0ZPVg9rP3OPkO+6v8Rf7s/30B9AJvBIIFyAblB7kIKgkqCSoJTQiCB8gGzgU4Ba8EbwSvBPIEOAUeBsgG5Qe5CCoJoAkbChsKoAkqCU0IggdxBoIF9wNyAt4AIv+O/Qn8yPri+d34fvh++H743fji+VH7DP0i/18BiQPOBeUHoAkiC0EM2gzaDEEMrwucCioJggfOBTIExwJ9AYkA3f93/2P/d//d/3YAKAHdAXICxwL0AscCJAJDAfr/of5l/Qn8fvo4+bP31vZk9VH0JvOG8oby3/GG8ibzv/Nk9db2fvgy+pH7q/yO/QD+Rf5l/kX+AP6O/Qz9QvyR+8j64vk4+d343fjd+I/5MvpR+3f8AP7O/7sBiQM4BcgG5Qe5CCoJoAmgCaAJKgkqCbkIuQhNCE0I5QeCB4IHggeCB+UHTQi5CCoJoAmgCRsKGwqcCpwKnAqcCpwKGwobCqAJuQjlB8gGzgUyBJsC3gAK/zn9kfsy+t34R/dg9t70UfS/87/zv/O/81H0UfRR9FH0UfRR9FH0UfTe9GT15fVg9tb2R/ez9xv4G/gb+Bv4G/gb+H743fg4+eL5fvqR+3f8jv2D/q3/sgC7AZsCVQO+AzIEMgQyBL4DIwNKAl8BUwBj/4P+3P2O/Y79AP6h/nf/iQC7AfQC9wPyBM4FyAaCB+UHuQi5CCoJKgm5COUHyAaCBfcDcgIOAa3/Zf45/UL8kftR+5H7Cfyr/Lb9vf7d/w4BSgJVA28E8gSCBYIFOAVvBIkDcgIOAb7/g/5l/Xf8zvtR+w77UfsJ/Az9g/5CACQC9wOCBcgGggdNCE0I5QeCB8gGzgWvBFUDAAJTAKH+3fxR++L53fiz99b2YPZg9mD21vZH97P3fvjd+Dj5j/mP+Y/5OPk4+d34G/iz99b25fVk9d70UfTe9N705fXW9n74fvrd/GP/JAKvBCMHoAkiC9oMeg0hDiEOIQ4hDiEOeg3aDEEMrwsiCxsKKglNCOUHIwdxBh4GzgXOBc4FzgXOBc4FzgXOBR4GcQZxBsgGyAbIBh4GggXyBPcD9AIkAkMBiQDs/07/of7c/Tn9d/wJ/M77zvsJ/An8CfzO+1H7yPp++uL5j/k4+d34fvgb+LP3R/fW9uX1ZPXe9FH0v/O/87/zv/O/81H03vRk9WD2s/c4+X76zvs5/b3+MgCbAfQCbwSCBXEGIweCB+UH5QeCB8gGcQbOBYIFOAU4BYIFHgbIBiMH5QdNCE0IuQi5CE0ITQhNCOUHggcjBx4GrwRVA7sBIwCD/gz9kfsy+t34G/hH90f3R/ez9xv4OPnI+kL8I/4yACQC9wOCBSMH5Qe5CLkITQjlByMHHgavBFUDAALeAOz/Tv8K/wr/d/8GAIkADgG7ASQCmwL0AiMD9AKbAgACKAEyAAr/tv13/A77j/kb+Nb2ZPVR9CbzhvKG8ibzv/Pe9OX1R/d++OL5yPrO+3f8DP1l/Y79Zf3d/An8Dvsy+jj5fviz99b2YPZg9mD21vaz9934fvpC/AD+rf8oAXICiQNvBDgFzgUeBnEGyAbIBnEGcQYeBs4FggU4BfIE8gQ4BYIFzgVxBiMH5Qe5CCoJoAmcCiILIguvC0EMQQxBDEEMrwsiCxsKuQgjB84FMgSbAvYATv+2/Qn8yPqP+X74G/hH99b2YPZg9uX1ZPVk9d703vTe9N703vTe9GT15fVg9tb2R/ez9xv4G/h++N34OPmP+eL5fvoO+5H7d/w5/SP+Iv9CAF8BcgKJAzIE8gSCBR4GHgZxBh4GzgU4BW8EiQObAt0BQwH2AA4BfQEkAscCiQMyBK8EOAXOBcgGggdNCKAJGwqcCiILIgsiC5wKoAm5CIIHHgZvBMcCQwHO/6H+tv0M/av8q/zd/GX9I/4K/yMAQwFyAokDbwTyBDgFOAWvBDIEiQNKAkMBBgC9/rb93fxC/An8Qvyr/GX9I/5O/50AJAK+AzgFcQaCB00IuQi5CE0I5QfIBs4FbwT0Al8Brf8A/kL8yPqP+X74s/dH90f3R/dH97P3G/h++Dj5j/ni+eL54vmP+Tj5fvgb+Ef3YPZk9VH0v/O/8ybzv/NR9OX1s/eP+Qn8Rf52AJsCrwRxBk0IoAmcCiILrwuvC68LrwsiCyILnAobCioJTQiCB3EGzgWCBTgFOAU4BfIE8gTyBPIEOAWCBc4FcQbIBiMHIwcjB8gGHgaCBW8EiQObArsB9gAjAE7/of4j/rb9Zf0M/d38d/xC/An8zvtR+8j6fvri+Y/5OPnd+H74G/iz90f3YPbl9WT13vRR9L/zJvMm84byhvKG8obyJvO/81H0ZPVg9rP33fgy+pH73fwj/or/yAAAAiMD9wOvBDgFOAU4BTgFOAU4BTgFggWCBc4FHgZxBsgGIweCB4IH5QflB00ITQhNCE0ITQjlByMHHgY4BfcDcgL2AHf/AP6r/JH7fvqP+d34fvgb+H743fgy+pH7Of04/ygBIwPyBHEG5Qe5CKAJoAmgCbkITQgjB84FrwS+A/QCJAK7AX0BXwFDAX0B3QFyAiMD9wNvBPIEOAXyBK8EbwS+A/QC3QHeAK3/Rf7d/FH74vl++Ef3YPZk9WT1ZPXl9db2s/fd+OL5Dvt3/I79Zf4K/07/Iv+h/tz9DP3O+8j6j/l++LP3R/fW9tb2R/ez93744vlR+938Zf7d/18BmwK+A68EzgVxBiMHggflB+UH5QflB4IHyAZxBh4GzgXOBXEGyAaCB+UHTQgqCaAJGwoiC68LQQzaDHoNIQ4hDiEOeg3aDEEMnAqgCeUHcQavBPQCfQHd/2X+DP3O+376j/nd+LP3R/fW9mD25fVk9d70UfRR9FH0v/O/87/zv/NR9FH03vTe9GT15fXl9WD21vZH97P3G/h++N34j/ky+lH7d/y2/dj+3f/IAH0BJALHAlUDvgMyBDIE9wOJA/QCSgKbAfYAiQBTAFMAdgCdAN4AKAF9Ad0BSgLHAokDMgTyBB4GyAaCB00IuQi5CLkITQiCB8gGggVvBCMDuwEyAL3+Zf1C/JH7DvsO+1H7zvt3/Dn9Rf5j/3YAfQEkAscC9AL0ApsCAAIoATIATv9l/o79q/wJ/JH7UfsO+1H7Cfzd/EX+rf8OAZsC9wOCBXEGggdNCE0ITQiCB8gGzgVvBPQCXwG+/wD+d/zI+jj5G/jW9mD25fXl9WD2YPbW9kf3s/cb+H74fvgb+LP3R/dg9mT1UfS/84by3/Hf8TDxMPHf8YbyUfTl9bP34vlC/IP+sgD0AvIEyAZNCKAJnAoiC68LQQxBDK8LrwucChsKoAm5CE0IggcjB8gGcQYeBs4FzgXOBc4FHgZxBiMHggflB00IuQi5CLkI5QeCB8gGzgXyBDIEiQPHAgACXwHIAFMA7P+K/2P/Iv/Y/oP+AP5l/d38d/xC/M77kftR+8j6MvqP+d34G/iz90f3YPbl9WT13vRR9L/zJvMm84byJvMm81H03vTl9Uf3fviP+cj6zvsM/WX+rf/2ACQCIwP3A68EOAXOBR4GHgZxBnEGyAbIBiMHggeCB+UHTQhNCLkIKgkqCaAJGwobChsKGwqgCSoJTQgjBx4G8gSJAwACdgC9/gz9kfsy+t34G/iz97P3s/d++I/5yPpC/AD+zv+bAVUD8gRxBoIH5QdNCE0I5QcjB3EGzgXyBDIEiQP0ApsCSgIAAiQCSgKbAiMDvgNvBDgFggWCBYIFOAXyBDIEVQNyAl8BIwC9/gz9UfuP+Rv41vZk9d703vTe9GT1YPZH93744vkO+3f8jv1l/tj+8v6h/gD+Of13/JH7yPri+d34G/iz90f3R/dH97P3fvji+Q77Qvy2/SL/iQDdASMDMgQ4BR4GyAYjB4IHggeCByMHyAZxBh4GzgWCBYIFggXOBR4GcQYjB+UHuQigCZwKrwtBDNoMeg0hDiEOIQ56DdoMrwucCioJ5QdxBvIEiQMAAp0AOP8A/gz9QvxR+3764vk4+X74G/gb+LP3s/dH99b2YPZg9uX1ZPVk9WT1ZPVk9WT1ZPVk9eX15fXl9eX1YPZg9kf3s/d++I/5yPrO+wz9AP7Y/pz/QgDeAH0BAAJyApsCmwJyAiQCuwFDAd4AiQBTAEIAQgBkAIkAsgDeACgBfQEAApsCVQMyBPIEzgVxBsgGIweCB+UHTQjlB4IHyAaCBTIEmwIOAZz/g/6O/d38QvwJ/An8Qvyr/GX9g/6K/7IAuwGbAlUDiQO+A4kDIwObAt0BDgEyAE7/Zf6O/d38QvwJ/M77Cfyr/GX9of7s/18B9AJvBM4FyAblB7kIuQi5CE0I5QcjB84FMgRyArIA2P4M/ZH7Mvo4+X74G/gb+Bv4fvjd+I/5fvoO+1H7UftR+w77fvri+Tj5fvhH92D2ZPVR9L/zJvMm8ybzv/Pe9GD2G/ji+Qn8Rf52AJsCbwQeBoIHuQgbCpwKrwuvC0EMQQyvCyILnAobCioJuQjlB4IHIwfIBnEGcQbIBsgGIweCB00IuQigCRsKGwobCqAJKgm5COUHIwceBjgFMgQjAyQCQwGyAFMAQgAyABQA3f+c/zj/vf5l/gD+3P22/WX9DP13/An8Uft++uL5OPl++LP3R/dg9mT13vS/8ybzhvLf8d/x3/GG8obyv/NR9OX11vaz9374j/l++pH7q/y2/b3+vv+yAH0BSgLHAlUDiQP3AzIErwTyBIIFzgUeBnEGyAYjB4IH5QdNCLkIKgmgCaAJoAmgCaAJKgm5CE0IggceBq8E9AJDAZz/I/7d/M77yPri+Y/5OPmP+eL5yPrO+zn9of4yAN0BVQOvBM4FyAaCB4IHggcjB3EGzgU4Ba8EMgSJA/QCmwIkAgACAAJKAscCVQP3A28E8gQ4BYIFggWCBTgF8gQyBFUDSgKyAPL+DP0O+zj5s/dg9mT13vRR9FH03vRk9WD2G/g4+cj6Cfzd/GX9jv2O/WX9DP13/M77Dvvi+d34s/dg9uX1ZPXe9GT1ZPVg9kf3fviP+cj6Cfxl/aH+3f/2AAAC9AK+A28ErwTyBPIErwQyBL4DVQP0AscCxwL0AlUD9wPyBM4FIwdNCKAJIgtBDNoMIQ7QDtAO0A7QDtAOIQ7aDEEMnAoqCYIHzgUyBMcCfQF2AHf/g/5l/Xf8kfvI+jL64vmP+Y/5OPnd+H74s/dH90f31vZg9mD25fXl9WT1ZPVk9WT1ZPVk9WT15fXl9WD2R/cb+Dj5MvpR+wn8q/w5/dz9g/4K/5z/IwCJALIAsgB2ABQArf9O/wr/2P69/tj+8v4i/07/Y/+K/87/QgDeAJsBSgL0Ar4DMgTyBIIFcQaCB00IuQgqCbkI5QcjB84FrwSJA0oCQwFCAGP/vf5l/iP+I/6D/vL+iv9kAEMBSgIjA/cDbwSvBK8EMgS+AyMDcgK7Ad4AFAA4/2X+tv0M/Xf8QvxC/N38jv1l/or/yABKAr4DOAVxBoIHTQgqCSoJKgm5COUHcQbyBCMDfQHd/2X+Of0J/A77fvoy+jL6fvoO+5H7CfxC/Hf8d/xC/EL8zvtR+8j64vnd+Ef3YPbe9L/zJvOG8obyhvKG8r/z3vRg9n74fvp3/KH+nQBKAvcDggXIBk0IoAmcCiILIgsiC5wKGwqgCSoJTQjlByMHyAZxBh4GHgZxBnEGyAaCB+UHuQgqCaAJoAmgCaAJoAkqCbkI5QfIBoIFMgQjAyQCmwFDASgBDgH2AMgAdgBCAAYA3f++/77/vv+c/2P/Cv+h/iP+jv0M/Xf8zvsO+zL6OPkb+Ef35fXe9L/zJvOG8t/x3/Hf8YbyJvO/81H0ZPXl9WD2R/cb+N34j/l++lH7zvur/GX9I/69/mP/BgCdACgBuwFKAscCIwO+AzIErwSCBR4GyAYjB4IH5QflB00IuQgqCaAJGwqgCSoJTQiCBx4GrwSJAwACnQBO/wD+3fwJ/A77yPp++n76yPqR+0L8Zf29/kIAuwEjAzIE8gSCBYIFzgXOBYIFggXyBG8E9wMjA3IC3QF9AUMBQwFfAZsBAAJyAscCIwOJA/cDMgRvBK8ErwQyBIkDSgLeAE7/jv0J/H763fhH92D2ZPVR9FH0UfTe9OX11vYb+Dj5fvpR+wn8d/zd/Az93fx3/M77Dvsy+jj5G/hH92D2ZPXe9N703vRk9eX11vYb+Dj5MvpR+3f8jv3Y/jIAfQFyAlUDvgP3A74DiQNVA/QCcgLdAV8BKAEOAV8B3QGbAokDrwQeBoIHuQgbCiILQQzaDHoNIQ7QDtAO0A4hDtoMrwucCioJ5QfIBs4FrwS+A5sCfQF2AIr/of4A/o79DP2r/An8kftR+8j6Mvri+Tj53fgb+Ef3YPbl9WT13vTe9N70UfRR9FH0UfTe9GT1YPZH9374OPky+g77Cfyr/I79Rf69/k7/rf/d/wYABgDd/63/iv9j/07/Iv8K//L+8v4K/zj/d//d/0IAnQAOAV8BmwEAAnIC9AK+A68EzgXIBoIHTQhNCE0ITQjlByMHcQaCBa8EiQObAt0BKAGdAEIABgDs/xQAdgAoAd0BxwKJA/cDMgQyBDIE9wO+A1UD9AJyAt0BDgEyAGP/of7c/WX93fyr/N38DP22/YP+nP/IACQCvgM4BXEGggdNCLkIuQhNCIIHyAaCBW8E9AJ9Aez/Zf4M/c77Dvt++n76fvrI+g77UftR+5H7zvvO+877kfsO+376j/l++LP3YPZk9VH0JvOG8t/xMPEw8d/xhvK/82T11vbd+H76d/xl/lMASgL3A4IFIwflB7kIKgkqCSoJuQjlB4IHyAYeBoIF8gRvBDIEMgRvBK8EOAXOBcgGggdNCLkIoAkbCpwKnAqcChsKKglNCIIHHgY4BW8EvgNVAyMDxwKbAkoCJAIAAt0B3QHdAd0B3QHdAd0BuwF9AQ4BZACc/73+tv3d/M77yPri+d34R/dg9t70v/Mm84byhvKG8ibzJvO/81H03vTl9WD2R/ez93743fiP+TL6yPpR+wn83fy2/YP+Y/8GAJ0AQwHdAUoC9AKJA28E8gTOBR4GcQbIBiMHggflB00IuQgqCSoJKgkqCbkI5QcjB3EGOAX3A5sCXwEGANj+tv3d/An8UfvI+jL6Mvp++g77Qvxl/aH+3f/2AAACxwKJAzIE8gQ4BYIFggU4BfIErwT3A4kDxwJKAt0BfQF9AZsB3QFKAscCIwO+AzIErwTyBPIE8gSvBDIEVQNyAkMB7P+D/gz9kfvi+X74R/dg9uX15fVg9tb2s/d++I/5yPrO+938jv1F/oP+of6D/kX+tv0M/UL8Dvvi+d34s/fW9mD2YPZg9tb2R/ez9374OPni+Q77d/y2/SL/QgBDASQC9AKJA/cD9wO+A1UDxwIkArsBXwFDAV8BuwFKAiMDMgSCBcgGTQigCSILQQx6DdAOhg9FEAwRRRBFEIYPIQ56DUEMIgsbCioJTQgjBx4G8gS+A8cCAAJDAbIAQgDd/4r/Iv+9/mX+tv0M/UL8Ufsy+jj5fviz90f3YPbl9WT13vRR9FH03vTe9GT15fXW9kf3G/jd+OL5fvpR+877Qvyr/Az9Of1l/WX9jv2O/WX9Zf05/Tn9DP0M/Qz9Of05/Y793P1F/r3+Cv9j/63/7P8yAJ0AKAEAAvQC9wPyBM4FyAYjB4IHggcjByMHyAZxBs4FOAWvBPcDVQObAgACmwF9AX0B3QFyAiMDvgP3AzIEMgQyBDIEMgQyBPcDiQMjA5sC3QFDAYkAzv/y/kX+jv0M/av83fwM/bb9of6+/w4BmwIyBIIFyAblB7kIuQgqCbkITQjlB8gGzgVvBMcCXwEGAPL+AP5l/Qz93fzd/Az9DP05/WX9jv2O/Y79Of3d/EL8kfvI+uL53fhH9+X1UfQm89/xMPF68HrwMPEw8YbyJvPe9GD2G/ji+Qn83P3O/5sBVQOvBM4FyAYjByMHIwfIBh4GzgWCBfIEbwQyBPcD9wP3AzIErwSCBR4GIwflB7kIoAmcCiILIgsiCyILnAqgCbkIggfIBh4GggXyBG8E9wOJA1UD9AL0AscCxwLHAvQCIwMjA1UDVQMjA8cCSgKbAfYAIwBO/0X+Of0J/H76OPmz99b2ZPXe9L/zv/Mm8ybzJvO/87/zUfTe9GT1ZPXl9eX1YPbW9tb2R/ez93743fiP+X76UftC/Az9tv2h/mP/ZABfASQC9AK+AzIEbwTyBDgFggUeBsgGggdNCLkIKgm5CLkI5QeCB8gGzgXyBL4DxwKbAYkAiv+D/mX9d/yR+w77yPrI+lH7zvt3/Dn9AP7y/t3/yAC7AXIC9AKJA/cDMgRvBG8EMgT3A1UDxwJKAt0BXwEoAQ4BKAFfAbsBJALHAlUDvgNvBK8E8gSvBG8E9wMjA3ICfQFkAAr/Zf3O+zL63fiz99b2YPZg9mD21vaz9374OPky+g77kftC/Kv8DP05/Tn9DP13/M77Dvsy+jj5fviz90f3R/fW9tb21vZH90f3s/d++Dj5MvpR+3f8tv0K/zIADgGbAd0BAALdAZsBKAGdADIAzv93/2P/d//s/50AmwHHAjIEggUjB7kIGwqvC9oMIQ6GD4YPRRCGD4YP0A4hDnoN2gyvCyILoAm5CIIHHgY4BfcDIwNKAl8ByABkABQA3f+K/yL/of4A/mX9d/yR+376j/l++Ef3YPbl9WT13vRR9FH0UfRR9FH03vTl9db2s/d++Dj5MvrI+lH7zvt3/N38DP05/Tn9Of0M/d383fzd/N383fzd/Az9DP1l/dz9Rf7Y/jj/iv++/+z/IwB2AA4B3QHHAr4DrwSCBR4GyAYjB4IHggeCB4IHggcjB8gGcQbOBTgFrwT3A4kD9ALHAscCxwL0AiMDVQOJA74DvgO+A74DiQNVAyMDxwKbAkoCAAKbAQ4BZACc/9j+AP5l/d38q/x3/Kv8Of0A/jj/nQAAAlUDrwSCBXEGyAYjB4IHggcjB8gGzgWvBFUDAAKyAJz/vf4j/o79Of0M/Qz9DP0M/Qz9DP3d/N38q/x3/An8kfsO+zL6OPkb+Ef35fXe9L/zJvOG8t/x3/Hf8YbyJvNR9GT11vZ++DL6Qvxl/nYAcgIyBIIFcQYjB4IH5QflB+UHggeCB8gGcQbOBYIFggWCBYIFzgUeBnEGIwflB7kIGwqcCq8LQQxBDK8LIgucCqAJKglNCIIHyAYeBoIF8gRvBPcDVQP0AscCmwLHAvQCIwNVA74DvgP3A74DiQP0AkoCfQGJAGP/I/6r/FH7j/kb+Nb2ZPVR9CbzhvKG8t/xhvKG8ibzv/NR9N70ZPXl9eX1YPZg9mD2YPbW9kf3s/cb+N34j/ky+g77zvur/Lb98v4GAA4BAALHAokD9wOvBIIFcQYjB00IKgmgCRsKGwobCqAJKgm5CE0IggfIBs4F8gQyBIkDmwK7AfYAIwBj/9j+Zf5F/kX+g/7y/or/IwCyAF8BAAKbAlUD9wOvBDgFzgVxBsgGyAZxBh4GzgU4BfIErwRvBPcD9wP3A/cDbwTyBIIFHgZxBnEGcQYeBh4GggU4Ba8E9wPHAn0BIwCh/gz9kft++jj5fvh++Bv4fvjd+Dj54vl++lH7zvt3/N38Of2O/bb9tv1l/Qz9QvyR+8j6MvqP+d34fviz90f31vbW9mD21vbW9rP3fviP+cj6Qvxl/YP+d/8jAJ0A9gAOAfYAyABkAN3/Y/8K//L+Iv9j//r/nQBfAXICiQPyBMgGTQgbCq8Leg0hDtAOhg+GD9AO0A7QDiEOeg3aDK8LnAqgCU0IyAbOBW8EIwMkAkMBnQAjAN3/vv++/5z/Y//y/kX+jv2r/FH7Mvo4+Rv41vbl9d70v/Mm84by3/Hf8d/xhvIm87/z3vRk9WD2R/cb+N34j/ky+n76fvp++n76fvrI+sj6yPp++n76fvp++n76yPpR+877Qvyr/Az9Zf3c/UX+vf5O//r/sgB9ASQCxwJVA74D9wMyBG8EbwRvBG8ErwRvBG8EMgT3A4kD9AKbAkoCAAIAAiQCSgKbAscCxwL0AvQCxwKbAnICcgJKAiQCJAIAAt0BmwFfAfYAdgDd/yL/Zf6O/d38QvwJ/An8d/w5/SP+OP9kAF8BSgIjA74DrwQ4Bc4FHgYeBs4FOAVvBFUDcgJfAYkAvv8i/6H+I/4A/tz9tv2O/WX9Of3d/Kv8d/xC/M77kfsO+3764vk4+X74R/dg9mT13vS/8ybzhvKG8t/x3/GG8ibzUfTl9bP3j/mR+479Tv/2AEoCiQNvBDgFggXOBR4GzgWCBTgF8gRvBDIE9wP3A/cD9wNvBPIEzgXIBuUHKgkbCpwKIgsiCyILIgucChsKKgm5COUHIwdxBs4F8gQyBIkDmwIAAn0BKAEoAV8BuwEkAscCIwOJA74DvgOJA1UDxwIAAigBBgC9/jn9kfsy+n741vbl9VH0v/Mm8ybzJvO/87/zUfRk9eX1YPbW9tb21vbW9mD2YPZg9tb21vZH97P3G/h++Dj5MvoO+wn8Of0j/iL/+v/2AN0BxwL3AzgFcQaCB00IKgmgCRsKnAqcChsKGwqgCSoJTQiCB8gGHgY4Ba8EvgMjA0oCmwEOAYkAIwDs/93/zv/O/77/zv8GADIAZACdAPYAfQEAApsCIwO+A/cDMgQyBPcDvgNVA/QCmwJKAgACAAIkAnIC9AJVA74D9wMyBG8EbwRvBG8EbwQyBL4DIwNKAl8BFAC9/o79QvwO+zL64vmP+Y/5j/ni+TL6fvrI+lH7zvsJ/Kv8DP05/WX9Zf05/d38d/xC/M77UfsO+3764vk4+X74G/iz90f3s/ez9374OPky+pH7d/y2/b3+vv+dAF8BuwEAAgAC3QF9AQ4BdgAUAM7/rf+t/87/IwDIAJsBxwIyBM4FggcqCSILQQx6DSEO0A7QDtAO0A7QDtAOIQ4hDnoNQQwiCxsKuQgjB84FbwRVA3IC3QFfAUMBQwFfAUMBKAHeAIkABgBO/4P+jv1C/A774vl++Ef35fXe9L/zJvMm8ybzJvO/8970ZPVg9kf3fvg4+TL6yPpR+5H7kfvO+877zvvO+5H7kfuR+5H7UfuR+5H7kfvO+wn8d/zd/GX9AP6D/gr/vv+JAF8BSgIjA74DbwQ4BYIFHgYeBnEGcQZxBsgGyAbIBsgGcQZxBh4GzgWCBYIFggWCBc4FzgUeBh4GHgbOBYIFOAWvBDIE9wOJA1UDVQMjA/QC9AKbAkoC3QFDAYkAvv/Y/iP+jv05/Tn9Zf3c/YP+Iv/s/7IAfQFKAiMDvgNvBPIEOAU4BfIEbwS+A/QCJAJfAbIAMgC+/4r/Y/9O/zj/Cv/Y/qH+Rf7c/Y79DP2r/An8zvtR+8j6Mvri+Tj5fviz99b25fXe9FH0v/Mm84byhvKG8ibzv/Pe9GD2G/ji+c77Zf3y/mQAuwHHAr4DbwSvBPIE8gSvBG8EMgT3A74DiQNVA4kDvgMyBPIEggVxBoIHTQgqCRsKnAoiCyILIgsiC5wKnAobCqAJKglNCOUHIwceBvIEMgRVA5sCSgIkAkoCmwL0AlUD9wMyBK8E8gTyBPIEbwT3AyMDAAKdAAr/Zf2R++L5G/jW9mT13vS/87/zv/O/81H03vRk9eX15fVg9mD25fXl9WT1ZPVk9WT15fXl9eX1YPbW9rP3fvg4+TL6UftC/Az9AP7y/vr/DgEkAlUDrwQeBiMHTQgqCRsKGwqcCpwKGwqgCSoJuQjlByMHHgaCBa8E9wNVA5sCJAK7AX0BQwH2AMgAiQBCAAYArf9O//L+2P7Y/gr/Tv+t/xQAiQDeACgBXwF9AX0BQwEOAZ0AUwAGAM7/zv8GAFMAsgAoAZsBAAJyApsCxwL0AvQC9ALHAnIC3QEoAUIAIv8j/gz9CfxR+8j6fvp++n76fvp++n76yPrI+g77UfvO+wn8Qvx3/Kv83fwM/Qz9DP0M/d38q/xC/M77Dvt++uL5OPl++Bv4G/gb+H743fiP+X76UftC/Dn9Rf4i/93/ZADIAPYAyAB2ABQAnP8i/73+g/6D/oP+2P53/0IAXwHHAjIEzgWCB7kIGwoiC0EM2gx6DXoNIQ4hDiEOIQ4hDnoN2gxBDCILGwq5CIIHcQaCBW8EiQP0AscCmwJyAnICcgJKAiQCmwEOAUIAY/9F/t38UfuP+Rv4YPbe9L/zJvOG8obyhvIm87/zUfRk9eX11vaz93743fiP+Y/54vky+jL6Mvp++n76yPrI+sj6DvsO+1H7kfvO+wn8d/zd/GX93P2D/jj/7P+yAJsBmwJVAzIE8gSCBc4FHgZxBnEGcQZxBnEGHgbOBYIFggU4BTgFOAU4BTgFggWCBc4FHgYeBh4GzgWCBfIEbwT3A1UD9AJyAgACmwFfAQ4B3gCyAHYAFACc//L+I/5l/av8CfzO+5H7zvsJ/EL83fxl/QD+2P6+/50AXwEkApsC9AL0ApsCSgLdAV8B3gCJAFMAQgBCAFMAZAB2AHYAUwAjAOz/nP84/9j+Zf4A/o79DP3d/Hf8CfzO+1H7yPoy+o/53fgb+Ef3YPZk9d70UfRR9FH03vRk9WD2s/c4+X76Cfy2/Tj/iQC7AccCiQP3A28EbwRvBG8EMgQyBDIEMgQyBG8EbwTyBIIFHgbIBoIHTQgqCaAJGwqcCpwKnAqcCpwKnAqcChsKGwqgCbkI5QfIBs4FrwT3A1UD9AKbApsCmwL0AlUDvgMyBK8E8gQ4BYIFggXyBDIEIwO7ATIAZf6r/Mj6OPmz92D2ZPXe9FH0UfRR9FH03vTe9GT1ZPVk9WT1ZPVk9d703vTe9FH0UfRR9N703vTe9GT1YPbW9rP33fiP+X76kft3/Lb98v5CALsBIwOvBB4Ggge5CKAJnAoiCyILIgucChsKoAm5COUHIwdxBs4FOAWvBG8EMgT3A74DiQNVAyMDxwJyAt0BQwGdACMAvv93/07/Tv93/77/FABkALIA9gAOAQ4B3gCyAIkAdgBTAEIAUwCJAPYAXwHdAXIC9AKJA/cDbwSvBPIE8gSvBDIEiQPHAgACKAFTAIr/2P5l/iP+tv2O/WX9DP3d/N38q/x3/Kv8q/yr/N383fwM/Qz9Of1l/WX9Zf2O/Y79Zf05/d38QvyR+w77Mvri+Tj5OPk4+Tj5j/ni+X76UftC/Dn9Rf44/xQAsgAOASgB9gCyAFMA+v+K/yL/2P6h/oP+vf4K/5z/iQCbAccCMgSCBcgG5Qe5CKAJnAoiC0EM2gx6DXoNIQ4hDiEOIQ56DUEMIgsbCioJ5QfIBoIFrwT3A1UDIwP0AvQC9AIjAyMDIwPHAgACKAHs/2X+q/zI+jj5R/fl9VH0v/Mm84byhvIm8ybzv/Pe9GT1YPZH9xv4fvjd+Dj5j/ni+TL6fvrI+sj6yPrI+sj6yPoO+w77DvsO+1H7kfvO+0L8q/wM/bb9g/5j/2QAfQGbAokDbwQ4BYIFzgUeBh4GcQYeBs4FggU4BfIErwRvBG8ErwTyBDgFzgUeBnEGyAbIBsgGcQYeBs4FOAWvBDIEiQP0ApsCJAKbAV8BDgGdADIAvv8i/2X+tv3d/EL8kfsO+8j6yPrI+g77kftC/Az93P29/q3/dgAoAZsB3QEAAt0BuwF9AUMBKAEoAUMBXwGbAbsB3QEAAgAC3QG7AX0BDgGdAAYAd//Y/kX+3P1l/Qz9q/xC/M77UfsO+zL6j/nd+LP31vbl9d70UfS/8ybzv/O/81H0ZPXW9hv4j/kO+6v8AP44/0IADgGbAd0BAAIkAiQCAAIAAiQCJAJKApsC9AJVA74DbwTyBIIFHgbIBoIH5QdNCLkIKgkqCaAJGwobChsKGwoqCbkI5QcjBx4GOAVvBIkD9AJKAgAC3QHdASQCmwJVA/cDrwSCBc4FzgWCBfIE9wPHAl8Bvv8A/kL8fvrd+LP3YPZk9d703vTe9N703vRk9WT15fXl9eX15fXl9eX15fXl9WT1ZPVk9WT15fXl9WD21vaz9xv43fiP+X76UftC/GX9g/7s/30BIwPyBHEGTQigCZwKrwtBDNoM2gzaDEEMrwucCqAJuQjlByMHyAYeBh4GzgXOBc4FzgWCBYIF8gRvBL4DIwNKAn0B3gBkAAYA3f/d/+z/BgAUACMAMgAyABQA7P++/3f/OP8K//L+Cv84/5z/FACdAEMB3QFKAscCVQOJA74DvgNVA/QCcgK7AQ4BdgDs/4r/Tv8K/9j+vf6D/mX+Rf4j/tz9tv2O/WX9Of0M/d38q/x3/Hf8d/x3/Kv83fwM/Qz9DP3d/Hf8CfxR+8j6MvqP+Tj53fh++H743fg4+Y/5MvoO+wn83fzc/aH+OP+t/93/3f+t/2P/Cv+h/kX+3P22/Y79jv3c/WX+Cv/s/94AAAL0AvcD8gTOBcgGgge5CKAJnAqvC0EM2gzaDHoNeg3aDEEMrwsiCxsKuQjlB8gGzgXyBG8E9wP3A/cD9wMyBG8ErwRvBPcDIwMAAp0A2P4M/VH7j/mz92D2ZPVR9L/zJvMm8ybzv/NR9N70ZPVg9tb2s/cb+N34OPmP+eL5Mvp++sj6DvsO+1H7UftR+w77DvsO+w77DvtR+1H7zvtC/Az9AP4K/zIAXwFyAokDbwTyBIIFHgZxBnEGcQYeBs4FOAWvBDIE9wO+A74DvgMyBG8E8gSCBR4GcQZxBnEGcQYeBs4FggXyBG8E9wOJAyMDmwJKAt0BmwEoAbIAFAB3/73+I/5l/d38QvzO+5H7kfuR+5H7Cfx3/Az9tv2D/jj/3f9TAJ0AsgCdAHYAUwAyAEIAZACdAPYAQwGbAQACSgLHAvQCVQOJA4kDVQP0AnIC3QEoAYkA+v93/yL/2P6h/kX+AP62/Qz9d/yR+376j/l++Ef3YPZk9d703vTe9N70ZPVg9kf3fviP+Q77Qvw5/SP+Cv+c/yMAdgCyAPYADgEoAV8BmwHdASQCcgL0AokDMgSvBDgFzgVxBsgGIweCB00IuQigCRsKnAoiCyILIgsiC5wKoAm5COUHIwceBjgFbwS+AyMDxwLHAvQCVQP3A68EggVxBsgGyAbIBh4GggUyBPQCmwEjAIP+3fwO+4/5G/jW9uX1ZPXe9N703vTe9GT1ZPVk9WT15fXl9eX15fXl9WT1ZPVk9WT15fXl9eX1YPbW9kf3R/cb+H743fji+cj6CfyO/Tj/DgHHAq8EHgblByoJnAqvC0EMQQxBDEEMrwucCqAJuQjlB8gGHgaCBTgF8gTyBPIE8gTyBK8EbwT3AyMDcgK7AQ4BZADd/3f/Cv/Y/r3+of6h/oP+Zf5F/gD+3P2O/WX9Zf05/Tn9Of1l/dz9Zf4K/77/dgAoAbsBJAKbApsCmwJKAt0BXwHIAFMA3f+K/zj/Cv/y/tj+8v7y/gr/Cv8i/yL/OP84/wr/2P6h/kX+AP62/Y79jv2O/dz9AP5F/oP+g/5l/iP+tv0M/av8CfyR+w77yPp++jL6Mvoy+n76DvuR+0L83fyO/QD+Zf6h/qH+of6D/mX+AP6O/Qz9q/xC/EL8Qvx3/Az9jv1l/k7/IwD2ALsBmwKJA28EggVxBuUHKgkbCiILrwtBDNoM2gzaDNoMQQyvC5wKoAm5CIIHcQaCBa8EMgQyBDIEbwSvBPIEOAXyBK8E9wP0ArsBQgCh/gz9UfuP+bP3YPbe9FH0v/Mm8ybzJvMm87/zUfTe9GT15fXW9kf3s/cb+H743fiP+eL5MvrI+g77UftR+5H7UftR+w77DvsO+w77UfsJ/N383P0K/1MAmwH0AjIEOAUeBsgGggflB+UH5QflByMHyAYeBjgFrwRvBDIEbwTyBDgFzgVxBsgGIweCB4IHggeCB4IHIwfIBnEGHgaCBfIErwQyBL4DVQObAt0BKAFkAJz/2P4j/mX93fxC/An8kfuR+5H7Cfx3/N38jv0j/qH+Iv9j/4r/nP+K/2P/Tv9O/3f/rf/6/1MAyABDAbsBSgL0AokD9wNvBK8ErwRvBPcDVQObAt0BQwHIAFMA7P+c/2P/Iv/Y/kX+jv2r/JH7fvqP+X74R/dg9uX1ZPVk9WT1ZPVg9tb2s/fd+OL5yPrO+938tv2D/gr/d/+t/+z/BgBCAIkA3gBfAd0BcgL0AokD9wNvBK8E8gQ4BYIFzgVxBsgGggdNCCoJoAkbCpwKnAqcChsKGwqgCbkI5QfIBh4G8gQyBFUD9AKbAscCIwO+A28EggUeBsgGyAbIBsgGcQbOBa8EvgNyAvYAd/8A/qv8Ufsy+jj5fviz90f3R/fW9tb21vbW9tb21vZg9mD2YPbl9eX15fXl9eX15fXl9WD2YPZg9mD2YPZg9mD21vZH9374j/kO+3f8Rf4GALsBiQM4BcgGTQigCZwKIguvC68LIgsbCioJTQiCB3EGzgU4BTgF8gTyBPIE8gSvBG8EMgS+AyMDmwLdAUMBsgAjAL7/iv9O/yL/8v6h/mX+I/7c/bb9jv1l/Tn9Of0M/Qz9DP1l/dz9g/5O/yMADgHdAZsCVQOJA74DiQMjA5sCAAJfAbIAIwDd/5z/iv93/3f/d/+K/5z/vv/6/yMAMgAjAPr/rf9O//L+g/4A/tz9tv22/QD+I/5l/oP+g/5l/gD+jv05/d38QvzO+1H7yPp++n76fvp++sj6DvtR+877Qvx3/N38Of1l/Y79jv2O/Tn93fx3/An8kftR+1H7kfvO+0L83fyO/SP+vf5j/+z/iQBDASQCVQOvBM4FIwdNCKAJnAoiC68LQQzaDNoM2gxBDK8LIgsbCioJ5QcjB3EGzgWCBYIFzgUeBnEGcQZxBh4GzgXyBPcDmwIOAWP/tv0J/H763fiz99b25fVk9d703vTe9N70ZPXl9WD21vZH97P3G/h++Dj5j/ky+sj6UfuR+wn8QvxC/An8zvuR+w77yPp++jL6MvrI+lH7Qvxl/YP+vv/2ACQCIwMyBDgFzgUeBnEGcQYeBs4FOAVvBPcDVQMjAyMDVQO+AzIErwQ4BYIFHgYeBh4GcQZxBh4GHgYeBs4FzgWCBTgFrwQyBIkDxwIAAkMBdgCt//L+Rf6O/av8CfxR+w77fvp++n76yPpR+877Cfyr/Az9Of1l/WX9Of3d/N383fzd/Az9Zf3c/UX+2P53/zIADgEAAvQCvgMyBK8E8gTyBK8E9wOJA/QCSgLdAV8B9gCyAGQAFACc/wr/Zf62/d38zvvI+o/5fvhH99b25fXl9eX15fVg9mD21vaz9xv4OPni+X76UfvO+0L8d/x3/Kv83fw5/bb9Rf7y/pz/ZAAOAZsBJAJyAscC9AL0AlUDiQMyBPIEzgXIBoIHTQi5CKAJoAkbChsKGwqgCSoJuQjlB8gGzgXyBDIEiQNVA1UDvgMyBPIEzgVxBiMHggeCB4IHIwfIBh4GOAX3A/QCuwF2AGP/Zf5l/Xf8kfvI+jL6j/k4+d343fh++Bv4G/iz90f3R/dH99b21vbW9mD2YPZg9mD2YPZg9uX15fVk9WT1ZPXl9db2s/c4+X76Qvy2/Xf/QwH0Aq8EcQblByoJoAkbChsKGwqgCbkI5QcjB3EGHgbOBc4FzgXOBR4GHgYeBs4FggU4Ba8EMgSJAyMDmwJKAt0BfQEOAZ0AIwCt/07/8v69/oP+Rf4A/rb9Zf05/Qz9DP05/dz9g/5j/1MAXwFKAiMDvgMyBDIE9wOJA/QCJAKbAQ4BnQBTAAYA+v/6/yMAZACyAA4BQwGbAd0BAAIAAgACuwFDAbIAMgCt/2P/Tv9O/07/Y/9j/3f/Y/84//L+g/4A/o79DP13/An8zvuR+5H7kfvO+wn8CfxC/Hf8q/wM/Tn9Zf2O/Y79Zf0M/av8d/wJ/JH7UftR+5H7zvsJ/Hf8DP2O/dz9I/5l/r3+Tv/6//YAAAIjAzIEggVxBoIHTQgqCRsKIguvC0EMQQzaDEEMrwsiC5wKoAm5CE0I5QeCB4IH5QflB00IuQhNCE0I5QcjBx4G8gRVA7sBIwCh/jn9zvvI+o/53fgb+Ef31vZg9mD21vbW9tb2R/dH97P3s/cb+Bv43fg4+Y/54vl++sj6DvsO+w77fvri+Tj53fgb+Bv4G/h++N34j/l++pH7q/zc/SL/QgBDASQC9AKJA74DvgOJAyMDcgLdAUMB9gDIAN4AKAGbASQCmwIjA74DMgSvBPIEggXOBc4FHgZxBnEGcQZxBh4GzgU4BW8EvgP0AiQCQwFTAHf/of62/d38QvyR+1H7DvsO+w77UfsJ/Kv8Zf3c/UX+Zf5F/gD+jv05/Qz93fzd/N38DP1l/dz9Zf4K/93/yADdAfQC9wPyBM4FcQZxBnEGHgbOBTgFrwQyBL4DIwPHAnICAAJ9Ad4AIwBj/2X+Of3O+8j6j/nd+Bv4s/ez90f3R/dH97P3G/h++N34j/ky+n76yPoO+1H7UftR+5H7zvsJ/Kv8Zf0j/gr/7P/IAJsBJAJyApsCxwIjA1UD9wNvBPIEggUeBsgGggflB00IuQgqCSoJKgkqCbkITQiCB8gGzgXyBPcDiQMjAyMDiQP3A68EOAXOBXEGyAbIBsgGcQYeBoIFrwT3A/QCJAJfAYkAnP+h/rb93fwJ/FH7yPp++jL64vk4+d34fvh++Bv4s/dH90f31vbW9tb21vZg9mD25fVk9d70UfS/87/zv/NR9N70ZPVg9rP3OPl++kL8AP7O/5sBiQM4BXEGggdNCLkIuQi5CE0IggcjB8gGcQZxBnEGcQbIBsgGyAYjByMHyAbIBnEGHgbOBYIFOAXyBK8EMgS+AyMDcgLdAV8ByABTAM7/Tv+9/iP+jv0M/av8q/zd/GX9I/7y/gYAKAFKAlUD9wNvBDIE9wOJA/QCSgK7ASgBnQAyAM7/rf+K/4r/nP++/+z/QgCdAPYAKAFDAUMBDgGyAEIA3f+K/zj/Cv8K//L+8v7Y/r3+g/4j/rb9Of2r/EL8zvtR+1H7UftR+5H7CfxC/Hf8d/yr/N38DP05/Tn9Of05/Qz9q/xC/M77UfvI+n764vni+eL5MvrI+g77UfuR+877CfxC/Kv8Of3c/b3+rf+dAJsBmwKJA68EggXIBoIHuQigCRsKnAoiCyILIgucChsKKgm5CLkITQi5CLkIuQgqCaAJoAmgCSoJuQhNCCMHzgVvBPQCmwFCAPL+tv13/A774vnd+Bv4s/dH90f31vbW9tb21vbW9tb21vZH90f3s/cb+N34j/ni+X76yPrI+n764vk4+d34G/iz90f3R/dH97P3fvg4+TL6UftC/GX9g/6K/50AfQEkAnICmwJKAt0BXwHIAEIA7P/d//r/MgCdAPYAXwHdAUoCxwJVA74DMgSvBPIEggUeBnEGyAYjByMHIwfIBh4GggXyBG8EiQObApsBiQCc/73+AP5l/d38q/yr/Az9Zf0j/r3+OP+t/93/zv+K/yL/of4j/rb9Of0M/av8d/x3/Kv83fw5/QD+vf6+/7IAmwGbAokDMgSvBPIE8gSvBG8EMgT3A74DiQMjA8cCcgIAAl8BsgDO/73+tv13/JH7yPoy+uL5j/mP+Tj5OPk4+Tj5j/ni+TL6yPoO+1H7kfuR+1H7UfsO+w77UfuR+wn83fy2/b3+rf92AA4BfQHdASQCcgL0AiMDVQP3A28E8gSCBXEGIweCB00ITQi5CCoJKgkqCSoJuQhNCIIHcQbOBfIErwRvBK8E8gSCBc4FcQbIBiMHggflB4IHggfIBh4GggWvBDIEiQPHAiQCQwF2AK3/8v5l/rb9Of13/An8zvtR+w77fvoy+uL5j/k4+Tj5OPk4+Tj5OPnd+H74G/hH92D2ZPXe9N70UfTe9N70ZPXl9db2G/g4+X76Cfy2/Xf/QwH0Am8EzgXIBiMHIwcjByMHyAZxBnEGHgYeBh4GHgZxBnEGyAbIBsgGcQZxBh4GzgXOBc4FggWCBTgF8gSvBPcDiQMjA5sCJAJ9AcgA+v8i/2X+tv05/d38q/yr/Az9tv2h/r7/9gAkAiMDvgMyBG8EMgT3A1UDmwIAAkMBnQAUAJz/OP+9/oP+Zf5l/oP+vf4K/2P/rf/O/63/d/8i/73+Zf4j/tz93P3c/bb9jv1l/Qz93fxC/M77UfvI+jL6j/mP+Y/54vky+n76yPpR+5H7Cfx3/N38Of1l/bb9tv22/Y79Of3d/EL8zvtR+w77yPrI+g77UfuR+877CfxC/EL8Qvx3/Kv83fxl/QD+of53/zIADgEAAvQC9wOvBIIFcQYjB+UHuQgqCSoJKgkqCbkIuQi5CE0IuQi5CLkIKgmgCRsKGwqcChsKGwoqCU0IIwfOBa8EiQNKAg4Bvv9l/jn9CfwO+zL6j/k4+X74G/iz97P3R/dH99b21vbW9kf3R/cb+H74OPmP+TL6Mvoy+uL5j/nd+H74s/dH90f3R/dH90f3s/d++Dj54vkO+wn8Of1l/pz/sgB9AQACJAIAAt0BmwFfASgBDgEoAUMBfQG7ASQCmwIjA4kD9wMyBG8ErwQ4Bc4FcQYjB+UHTQi5CLkIKgm5CLkITQiCB8gGzgXyBPcD9AIAAg4BIwBj/9j+g/6D/r3+Iv++/1MAyAAOASgBDgGyAFMAzv9O/73+I/62/Tn93fyr/Kv8q/zd/Dn93P2D/nf/UwAoAd0BcgL0AiMDiQO+A/cD9wP3A74DiQMjA8cCJAKbAd4A+v/Y/o79d/xR+3764vk4+d34fvgb+LP3s/ez9xv4G/h++N34OPmP+Y/5j/mP+Y/5OPk4+d34OPk4+eL5fvpR+wn83fy2/WX+8v5j/87/IwCJAPYAfQEkAvQCvgNvBDgFzgVxBsgGIweCB+UH5QflB+UHggcjB3EGzgXyBK8EbwRvBG8E8gQ4Bc4FcQYjB4IH5QflB4IHggcjB3EGHgbOBTgFbwT3A1UDmwIAAkMBnQDs/zj/g/7c/WX9q/xC/M77UfvI+n76Mvoy+uL54vni+Y/5j/nd+H74s/fW9uX13vRR9L/zJvMm8ybzJvO/81H03vTl9Uf3fvgy+gn83P13//YASgIjA74DbwSvBPIEOAU4BTgFggWCBYIFzgUeBnEGcQZxBnEGHgbOBc4FzgUeBh4GcQZxBh4GHgbOBYIF8gSvBPcDVQObApsByADO/9j+AP45/av8d/xC/Kv8Of3c/fL++v8OAQACxwJVA4kDiQNVA8cCSgK7ASgBnQAjAL7/Tv/y/r3+of6D/qH+2P4i/3f/rf++/63/nP+K/5z/rf++/77/vv+t/5z/iv9O//L+g/7c/Tn9QvyR+w77yPp++n76yPrI+g77UfvO+0L8q/w5/bb9Rf6D/tj+8v7Y/qH+Rf7c/WX93fx3/An8zvvO+wn8Qvx3/Kv8q/yr/Kv8q/yr/N38Of3c/YP+OP/6/8gAmwFyAiMD9wPyBM4FyAaCB+UHTQi5CLkIuQgqCSoJKgkqCSoJoAmgCRsKnAoiC68LQQxBDK8LrwucChsKKgnlByMHHgbyBL4DmwJfAUIAOP8j/jn9d/zO+w77fvri+Y/5OPnd+H74fvh++H743fg4+Y/54vky+n76fvoy+uL5OPl++Bv4R/dH99b21vbW9tb2R/ez9xv43fji+cj6Cfxl/YP+iv9CAJ0A3gD2AA4BDgH2AN4AyADeAPYAQwG7ASQCmwL0AiMDVQOJA74DbwTyBM4FcQYjB+UHuQgqCaAJGwobChsKGwqgCSoJTQgjB3EGOAVvBFUDcgK7AQ4BnQB2AJ0ADgF9AQACSgJyAkoCJAK7ASgBiQD6/2P/2P5F/rb9Of2r/EL8CfwJ/EL8d/wM/bb9Rf7Y/or/MgDeAJsBSgLHAiMDiQO+A74D9wP3A74DiQP0AiQCKAEjAAr/AP45/Xf8zvtR+8j6fvri+eL5j/ni+eL5Mvp++sj6DvsO+w77DvvI+n76Mvri+eL54vni+TL6yPpR+wn8q/xl/dz9Rf6h/vL+Y//O/1MA9gB9ASQCxwKJAzIErwQ4Bc4FHgbIBsgGIwcjB8gGyAZxBs4FggU4BfIErwSvBPIEOAXOBXEGyAaCB4IH5QeCB4IHIwfIBnEGzgWCBfIEbwS+AyMDmwIAAl8BsgAUAHf/vf4j/o79DP2r/EL8zvtR+8j6fvoy+jL6Mvri+Y/5OPl++LP3YPZk9VH0v/OG8t/x3/Ew8TDxMPEw8TDx3/GG8r/zZPVg9hv4j/nI+gn8Of1F/jj/BgCJACgBmwHdAUoCmwIjA4kD9wNvBK8E8gTyBPIE8gTyBDgFggUeBnEGyAbIBiMHIwcjB8gGyAZxBs4FOAVvBIkDxwLdAfYAIwBO/6H+I/4A/iP+of5O/yMADgHdAZsCIwNVA4kDiQNVAyMDxwJKArsBKAGdAAYAd/8K/73+g/5l/mX+g/69/tj+Cv8i/zj/Y/+K/63/vv/d/wYAMgBkAHYAZAAyAN3/Tv+h/tz9DP13/M77kfsO+w77yPoO+w77kfsJ/Hf8DP2O/QD+Rf6D/oP+of6D/kX+3P1l/d38QvzO+1H7UftR+1H7UftR+1H7DvsO+8j6yPrI+g77UfsJ/Kv8Zf0j/tj+nP9kAEMBJAL0Ar4DbwTyBIIFzgUeBnEGyAYjByMHggflB00IuQgqCaAJnAoiC68LrwuvC68LIgucChsKoAm5CE0IIwceBvIE9wPHApsBiQCK/4P+tv3d/EL8kfsO+8j6Mvri+eL5j/mP+Y/54vky+n76yPrI+sj6fvoy+o/5OPl++Bv4s/dH99b21vZg9mD21vbW9kf3G/jd+I/5yPqR+3f8Of22/UX+g/69/r3+vf69/r3+2P4i/2P/zv8jAHYAyAAOAV8BfQHdAUoCmwJVAzIE8gTOBXEGggdNCLkIoAmgCRsKoAkqCbkITQgjB3EGggVvBFUDcgKbASgB3gD2AEMBfQHdASQCJAIkAgACmwEoAbIAQgDO/07/vf4j/o793fx3/An8zvuR+877zvtC/Kv8Of3c/aH+Y/8yAA4B3QGbAlUD9wOvBPIEOAWCBYIFOAWvBL4D9ALdAd4A3f8K/yP+jv3d/Hf8QvwJ/M77zvvO+877zvsJ/An8QvwJ/An8zvtR+w77fvoy+uL54vni+eL5MvrI+g77kfvO+0L8q/wM/Y79I/6h/k7/BgDeALsBmwJVA/cDrwQ4Bc4FcQbIBsgGyAbIBnEGcQbOBYIFOAXyBK8ErwSvBDgFggUeBsgGIweCB+UH5QflB4IHIwcjB8gGcQYeBoIF8gSvBDIEvgMjA8cCJAJ9AfYAdgD6/5z/OP+9/kX+3P1l/Tn9DP0M/Tn9Of05/Qz9q/wJ/A774vnd+LP31vbl9WT13vRR9L/zv/O/87/zUfTe9OX11vYb+Dj5MvpR+3f8jv1l/k7/IwDeAH0BAAJyAvQCiQP3A28E8gQ4BYIFggXOBc4FzgUeBnEGyAYjB4IH5QdNCLkIuQgqCbkIuQhNCOUHIwceBjgFMgQjAwAC9gAUAGP/2P6h/tj+Iv+c/0IA9gCbASQCmwL0AiMDIwMjA/QCxwJyAiQCuwEOAYkA3f9j/9j+Zf4j/gD+3P3c/QD+I/4j/kX+g/6h/tj+OP+K/+z/QgCJAJ0AiQBTAN3/OP9l/o79d/zO+w77Mvri+Y/5j/mP+eL5MvrI+lH7zvt3/N38Zf3c/QD+Rf4j/tz9jv0M/av8QvwJ/M77kfuR+5H7kftR+1H7DvvI+n76fvp++sj6DvuR+0L83fyO/WX+OP/6/7IAXwEAAnICxwIjA4kDvgP3AzIEbwTyBDgFggUeBnEGIwflB7kIoAkbCpwKIgsiCyILnAqcChsKoAkqCU0IggfIBs4F8gT3A8cCuwHIAM7/8v4j/o793fxC/JH7yPp++uL54vmP+eL54vky+jL6Mvoy+uL5j/k4+X74G/hH99b2YPbl9eX1ZPVk9WT1ZPXl9WD21vaz9374j/ky+g77zvt3/N38Zf22/QD+Rf5l/qH+2P4K/2P/rf8GAEIAiQCyAMgA3gAOAUMBuwFyAiMD9wPyBB4GIwdNCCoJoAkbChsKGwobCqAJKglNCIIHyAbOBa8E9wMjA8cCcgKbApsC9AIjAyMDIwP0AscCSgIAApsBQwHIAFMAvv8i/4P+3P1l/av8QvzO+5H7kfuR+5H7zvsJ/Hf8DP3c/b3+rf+dAH0BSgIjA74DMgRvBG8EMgS+A/QCJAIoATIATv+D/rb9Of2r/EL8CfzO+877zvvO+877CfwJ/An8zvvO+5H7DvvI+jL6j/k4+d34fvh++H74fvjd+N34OPmP+eL54vl++sj6kftC/Dn9I/4K/yMAKAEkAvQCvgNvBPIEOAWCBc4FHgYeBs4FzgWCBTgFOAU4BTgFOAWCBc4FcQYjB4IHTQhNCLkIuQi5CLkITQhNCOUH5QeCByMHyAZxBh4GggXyBK8EMgSJAyMDmwIkAn0B9gB2AAYAvv+K/2P/Y/9j/3f/Y/84/9j+Rf5l/Xf8Ufsy+jj5G/jW9mD2ZPXe9FH0UfRR9FH0UfTe9GT1YPZH9xv43fji+cj6kfur/I79Zf4i/87/dgAOAZsBSgLHAlUDvgP3A/cD9wP3A/cD9wMyBK8EOAXOBXEGIweCB+UHTQhNCE0ITQjlB4IHyAYeBjgFbwRVAyQCKAEjAGP/8v6h/qH+8v5O/63/MgCyACgBmwEAAkoCmwLHAscCxwKbAkoCAAJ9Ad4AUwC+/yL/of5F/tz9jv1l/Tn9Of1l/bb9I/6h/iL/rf8yALIAKAF9AbsB3QGbASgBiQC+/9j+AP4M/UL8kfsO+8j6yPrI+g77kfsJ/Kv8Of3c/WX+2P4i/2P/iv9j/zj/2P5l/tz9Zf05/d38q/yr/Hf8CfzO+1H7yPp++jL64vky+n76yPpR+wn83fyO/WX+Iv/O/4kAKAGbAQACSgJyApsC9AIjA1UDvgP3A28E8gSCBR4GyAblB7kIoAmcCiILrwuvC68LrwsiCyILnAobCqAJKglNCIIHcQaCBW8EVQNKAigBFAAi/0X+Zf2r/An8UfsO+8j6fvp++n76fvp++sj6fvp++jL6j/k4+X74G/hH99b2YPbl9eX1ZPVk9WT15fXl9WD21vaz9xv43fiP+TL6DvuR+0L8q/wM/Y793P0j/oP+2P44/4r/3f8GABQABgD6/+z/3f/s/yMAdgAOAbsBmwKJA68EggVxBiMH5QdNCLkIKgkqCbkIuQjlByMHcQaCBa8EvgMjA8cCmwKbAscC9AIjAyMD9AL0AscCmwJyAiQCuwFfAd4AZADO/yL/g/7c/WX93fxC/M77UfvI+n76fvrI+g77zvt3/GX9Rf5O/1MAfQFyAlUD9wNvBK8ErwRvBL4D9AIkAigBQgB3/73+I/6O/Tn9DP3d/N383fzd/Az9DP0M/Qz9DP3d/Hf8CfyR+w77yPoy+jL64vni+Y/5j/mP+Y/5j/mP+Y/54vky+sj6UftC/Az9AP7y/vr/3gDdAccCiQMyBK8E8gQ4BTgFOAU4BTgF8gTyBK8EbwQyBDIEbwTyBIIFHgbIBiMH5QflB00ITQhNCE0I5QflB4IHIwfIBnEGcQbOBYIF8gRvBPcDVQP0AkoCuwFDAd4AiQAjAM7/nP93/3f/d/+c/77/rf+K/yL/g/62/av8kft++o/5fvhH92D2ZPXe9FH0v/O/87/zv/NR9FH03vRk9eX1YPbW9rP3fvg4+TL6DvvO+6v8Zf1F/iL/7P+dAEMBuwEAAiQCJAJKAnICmwL0AlUD9wOvBIIFcQYjB4IH5QdNCLkIuQi5CE0I5QeCB8gGzgWvBL4DmwK7AfYAUwAUABQAMgB2ALIADgFfAbsBJAJyAscCIwOJA74DvgO+A74DiQNVA/QCcgIAAn0B3gBTAK3/OP/y/r3+vf7Y/iL/Y//O/0IA3gB9ASQCmwL0AlUDVQMjA5sCJAJfAXYAd/+D/o79q/zO+1H7DvsO+w77UfvO+0L8q/w5/bb9I/6D/tj+Cv8K//L+of5l/iP+AP7c/bb9jv1l/Qz9q/xC/M77UfvI+n76fvp++sj6DvuR+wn8q/yO/UX+Cv++/2QA3gAoAV8BmwG7Ad0BAAIkAiQCJAJKApsC9AKJA28EggVxBoIHTQgqCRsKnAqcCiILIgsiCyILnAqcChsKoAkqCbkI5QcjBx4GOAUyBCMDSgJfAXYArf/y/kX+3P1l/Tn9Of05/Tn9Of1l/Tn9DP3d/Hf8zvtR+8j6MvqP+Tj5fvgb+LP3R/dH90f3s/ez9xv4fvjd+Dj5j/ni+TL6yPpR+5H7CfxC/Hf83fw5/Y793P1F/oP+of69/r3+vf69/qH+of69/vL+Tv/d/4kAXwFKAlUDMgQ4BR4GyAaCB+UHTQi5CLkITQjlByMHcQaCBa8EMgS+A4kDVQNVA4kDiQOJA4kDiQOJA1UDVQMjA/QCxwJKAt0BXwH2AGQA7P9j/9j+AP45/Xf8kfsO+8j6fvp++n76DvuR+3f8Zf1F/k7/UwBfAUoC9AKJA74DvgOJA/QCSgJ9AYkArf+9/gD+Zf0M/d38q/yr/Hf8d/x3/Hf8d/yr/Kv8q/x3/An8zvtR+w77yPp++jL64vmP+Tj53fh++H74G/gb+Bv4G/h++N34j/ky+lH7Qvxl/YP+iv+dAJsBSgL0AokD9wMyBG8EbwRvBDIE9wOJA1UDIwMjA1UDvgMyBK8EOAWCBR4GyAYjB4IHggflB+UH5QeCB4IHIwcjB8gGcQYeBs4FOAWvBPcDVQP0AnICAAKbASgByABkAEIAMgAyAGQAiQCdALIAnQB2AAYAd/+9/tz93fzO+8j6j/l++Ef3YPZk9d703vTe9N703vTe9N70ZPVk9eX15fVg9tb2s/cb+N34OPky+g77zvur/GX9AP6h/iL/Y/+K/63/vv/O//r/MgCJAA4BuwFyAiMD9wOvBDgFzgUeBnEGyAbIBsgGcQYeBjgFMgRVA5sCuwEOAZ0AUwAyACMAMgBCAGQAsgD2AF8B3QFKAscCIwOJA74D9wMyBG8EbwRvBPcDiQP0AiQCXwGdAN3/OP+9/mX+I/4A/iP+Rf6h/iL/rf9TAN4AXwG7ASQCSgIkAt0BXwGyAM7/2P7c/d38CfyR+w77yPp++n76yPoO+1H7zvt3/Az9jv0A/mX+g/6h/qH+of6h/oP+Zf5F/iP+3P1l/d38QvyR+w77fvoy+uL5j/mP+Y/54vky+sj6kftC/Dn9AP69/nf/+v92AMgADgEoASgBDgH2APYADgFDAZsBJAL0Ar4DrwTOBcgG5Qe5CKAJGwqcCiILrwuvC68LrwuvC68LrwsiC5wKGwoqCU0IggdxBoIFbwRVA0oCXwGJAOz/Y/8K//L+8v7y/vL+Cv/y/r3+g/4j/rb9Of2r/M77Dvt++o/53fh++Bv4s/ez97P3G/gb+H74fvh++N34OPmP+eL5Mvp++sj6DvtR+5H7Cfx3/Kv83fzd/N383fzd/N38q/x3/Hf8d/x3/Kv8DP2O/UX+Cv8GAPYAAAL0AvcD8gTOBcgGIweCB+UH5QeCByMHcQYeBoIFOAXyBPIErwSvBPIE8gTyBPIE8gTyBPIE8gTyBK8EbwT3A74DVQMjA5sCAAJDAYkArf/Y/tz9DP1C/JH7DvvI+sj6yPpR+wn8q/y2/b3+7P8OASQC9AK+A28ErwSvBDIEvgP0AkoCfQHIAEIAzv9j//L+g/5l/kX+Rf5F/kX+Rf4j/gD+3P2O/Tn9DP2r/Hf8QvwJ/JH7Dvt++uL5j/nd+Bv4s/ez90f3R/dH90f3s/d++Dj5MvpR+3f8jv29/q3/iQBDAd0BcgLHAvQC9AL0ApsCSgIAAt0B3QHdAQACSgKbAvQCVQP3A68EOAXOBXEGyAbIBiMHggeCB4IH5QeCB4IHIwfIBnEGzgWCBfIEbwT3A1UDxwIkArsBXwEoAQ4BKAFDAX0BmwHdAQACAALdAX0BDgF2AK3/vf62/Xf8Ufsy+t34G/hH99b2YPZg9uX15fXl9eX15fXl9eX1YPZg9tb2R/ez9xv43fiP+eL5fvoO+877Qvzd/Dn9jv3c/dz93P3c/QD+Zf7Y/or/UwAoAd0BxwKJA28EOAUeBsgGIweCB4IHIwfIBh4GOAVvBPcDIwObAkoC3QF9ASgBDgH2APYA9gAoAV8BmwHdAUoCmwLHAiMDiQO+A/cDMgT3A74DVQPHAkoCmwHIABQAY/+9/kX+AP7c/QD+I/6h/iL/nP8jALIAQwHdAUoCmwLHApsCSgKbAfYAQgCK/9j+I/6O/Qz9q/x3/EL8Qvx3/N38Zf3c/UX+of7y/jj/d/+t/77/vv/O/77/rf93/zj/2P5l/tz9Of2r/An8UfvI+n76Mvri+eL54vky+sj6UfsJ/Kv8Zf1F/vL+iv/s/yMAMgAjAOz/vv+c/3f/d/+c/77/IwCdAEMBAAL0AvcD8gTOBcgGggdNCLkIKgkbCpwKnAoiCyILIgsiC5wKGwqgCSoJTQiCB3EGggVvBIkDmwLdAUMB3gCyAJ0AnQCJAIkAdgBkAEIA+v+c/wr/g/62/d38CfxR+376j/k4+d34fvh++H74fvh++N343fg4+Y/54vky+n76yPoO+5H7CfxC/Kv83fwM/WX9Zf2O/Y79tv2O/WX9Of3d/Kv8q/zd/Az9Zf3c/WX+Iv/d/7IAuwHHAvcDOAUeBsgGIweCB+UH5QflB4IHIwcjB8gGcQYeBh4GzgXOBc4FzgXOBc4FzgUeBh4GzgXOBc4FggWCBTgF8gSvBDIE9wNVA5sC3QHeAM7/vf62/d38CfyR+1H7UftR+877d/w5/QD+Cv8UACgBJAL0AokDvgO+A4kDIwPHAnICJAKbAQ4BnQAyAM7/nP+K/3f/iv93/2P/Tv8i//L+vf6D/kX+I/4A/rb9jv05/Qz9q/wJ/JH7yPoy+jj53fgb+LP3R/dH90f3R/ez9374OPky+lH7q/y2/dj+7P/IAH0BAAJKAnICcgJKAiQC3QG7AZsBfQFfAV8BXwGbAQACmwIjA74DMgSvBDgFzgUeBnEGIweCB4IH5QflB+UHggeCByMHyAZxBs4FOAVvBPcDVQP0AnICSgIkAiQCSgKbAvQCVQOJA74D9wP3A74DVQPHAt0B3gC+/4P+Of0J/Mj6j/l++LP3R/fW9mD25fXl9eX1ZPVk9WT1ZPXl9eX1YPbW9kf3s/cb+H743fiP+TL6yPoO+5H7zvvO+877zvsJ/Hf83fyO/SP+2P6K/2QAXwFyAokDrwSCBR4GyAYjByMHyAZxBs4FggXyBG8EvgNVA8cCSgIAArsBfQF9AX0BfQGbAbsBAAJKAnICxwIjA4kD9wMyBG8ErwSvBG8E9wOJA8cCAAJDAWQAnP/y/kX+3P22/bb93P0A/mX+2P5j/wYAnQAoAZsB3QHdAbsBXwH2AHYA7P84/4P+3P0M/Xf8CfzO+5H7kfvO+877Cfx3/Kv8DP1l/bb9AP4j/mX+g/69/tj+2P69/oP+I/6O/Qz9QvyR+w77MvqP+d34fvgb+LP3s/ez9xv43fiP+X76UfsJ/Kv8Of22/QD+I/4j/gD+3P3c/dz9tv22/bb9AP5l/vL+rf+dAJsBcgJVAzIE8gTOBcgGgge5CCoJoAmcCpwKIgsiCyILIgucChsKoAm5COUHyAaCBW8EiQPHAkoC3QG7AZsBmwGbAZsBmwF9AV8BDgGyAEIArf/y/gD+DP0J/FH7fvqP+Tj53fh++Bv4G/gb+Bv4G/gb+H74fvjd+N34OPmP+TL6fvrI+g77DvtR+5H7kfuR+5H7kftR+w77yPp++jL6Mvoy+n76fvrI+lH7Cfzd/Nz98v4GAA4BAAL0AokDMgSvBPIE8gQ4BfIE8gSvBK8EbwRvBG8EbwRvBG8EbwSvBK8E8gTyBDgFOAWCBYIFOAU4BTgFOAXyBK8EMgSJA/QCAAIOAfr/2P62/av8CfxR+w77yPoO+w77kftC/Az9AP7y/gYADgG7AUoCmwL0AvQC9AL0ApsCSgLdAX0BDgHIAHYAUwAyADIAIwAjAAYA7P/O/5z/d/9j/07/OP8i//L+2P6h/mX+AP5l/d38CfxR+8j64vk4+X74s/dH90f3R/dH97P3fviP+X76Uft3/I79of6c/1MA9gBfAbsBAAIkAiQCJAIAAgAC3QHdAd0B3QEkAnICxwIjA4kD9wOvBDgFzgVxBiMH5QdNCLkIuQgqCSoJoAkqCSoJuQhNCOUHIwdxBs4FOAWvBDIE9wO+A/cDMgRvBPIEOAWCBc4FHgYeBh4GzgWCBa8E9wP0ArsBdgA4/yP+DP0J/FH7fvri+Tj5fvgb+Bv4s/dH99b21vbW9kf3R/dH97P3G/gb+H743fiP+eL5Mvp++n76fvp++n76yPrI+g77kfsJ/Kv8Of0j/gr/IwBfAZsCvgPyBM4FcQbIBsgGyAbIBnEGHgbOBTgF8gRvBPcDiQMjA8cCcgJKAiQCJAJKAnICmwKbAscCIwOJA/cDbwSvBPIEOAU4BfIErwQyBL4D9AIAAigBZACt/zj/2P6h/qH+of7y/mP/3f+JAEMBAAKbAvQCVQOJA4kDiQNVA/QCSgK7AQ4BZAC+/yL/of5F/gD+3P22/bb9tv3c/dz9AP5F/mX+g/69/gr/Tv93/5z/rf+c/07/Cv+h/gD+Zf3d/An8Uft++uL5OPnd+H74fvh++N34OPni+X76UfsJ/N38Of2O/bb93P3c/dz93P3c/Y79jv1l/WX9Zf2O/QD+of44/93/iQBfASQCIwP3A/IEHgYjB+UHuQigCRsKnAoiCyILIgsiC5wKGwoqCU0IggdxBoIFbwS+A1UD9AKbApsCmwKbAscCxwLHAscCxwKbAkoCmwHeAPr/Cv8j/mX9d/yR+8j6Mvri+Tj53fh++H74fvgb+Bv4G/gb+Bv4fvjd+Dj5j/mP+eL5Mvp++n76fvp++jL6Mvri+Y/5OPnd+N34fvh++H74fvjd+I/5MvpR+0L8Zf2D/pz/nQCbAXICIwOJA/cDMgRvBG8ErwSvBK8ErwSvBG8EbwRvBG8EbwSvBPIE8gQ4BTgFggWCBc4FzgUeBh4GHgbOBYIFOAXyBDIEiQObAn0BUwA4/0X+Zf3d/EL8CfzO+877Cfx3/Dn9AP7Y/r7/iQAoAbsBJAJKApsCmwKbAnICSgIAApsBQwEOAd4AyADIAMgAsgCdAIkAZAAyAOz/vv+K/4r/iv+K/4r/iv9O//L+g/4A/mX93fxC/JH7yPri+d34G/hH99b2YPZg9tb21vaz9374OPl++pH7d/w5/dz9g/7y/mP/vv/6/zIAZAB2AHYAdgB2AIkAnQDIAN4AKAFfAbsBSgLHAokDMgTyBM4FcQYjB+UHuQgqCaAJGwobChsKGwqgCSoJuQjlB4IHyAYeBs4FOAU4BTgFggWCBc4FHgZxBsgGIwcjByMHIwfIBh4GOAVvBFUDSgJDARQA2P62/d38zvsO+3764vk4+X74G/iz90f31vbW9tb2R/dH90f3s/ez9xv4G/h++N343fg4+Tj5OPk4+Tj5OPk4+Y/5j/ni+X76DvvO+9383P0i/2QAmwGbAr4DbwTyBDgFggWCBYIFggWCBTgFOAWvBG8E9wOJA1UDIwMjA/QC9AL0AvQC9AJVA4kD9wNvBK8EOAWCBc4FHgZxBnEGcQYeBoIF8gT3A1UDcgK7ASgByAB2AFMAQgBkAMgAKAGbASQCmwIjA1UDiQO+A74DiQNVA/QCcgLdAUMBsgAUAIr/Cv+9/mX+AP7c/bb9jv1l/WX9Zf2O/bb93P1F/oP+2P4K/yL/OP8i//L+vf5l/gD+Zf2r/An8Dvsy+jj5fvgb+Ef31vbW9tb2R/ez9xv43fg4+eL5Mvp++sj6DvtR+5H7kfuR+877zvvO+877zvsJ/EL83fw5/dz9g/44/xQADgEkAlUDbwSCBXEGggdNCCoJGwqcCiILrwuvC68LrwsiCxsKoAlNCIIHyAYeBoIF8gSvBK8EbwRvBG8EbwSvBK8EbwQyBL4DIwObArsB9gAUACL/Rf5l/av8CfxR+8j6Mvri+Y/5OPnd+H74G/gb+Bv4fvh++N34OPk4+Y/54vni+TL6Mvoy+uL54vmP+Tj53fh++LP3s/dH90f3R/dH97P3G/g4+TL6DvtC/GX9Zf5j/zIA9gCbASQCmwIjA4kD9wMyBDIEbwQyBDIEMgQyBDIEbwRvBG8ErwTyBDgFOAWCBc4FzgXOBc4FzgUeBh4GzgWCBfIEMgRVA0oCQwEyADj/Rf6O/d38d/wJ/M77zvtC/Kv8Of0A/r3+Y//s/3YA3gBDAZsBuwHdAbsBmwFfAQ4B9gDIAJ0AdgBTAEIAMgAjAAYA3f+c/2P/Tv9O/2P/d/+K/3f/Y/84/wr/2P6D/iP+tv0M/UL8Uft++o/5fviz99b2YPbl9eX15fVg9tb2s/d++Dj54vl++lH7zvtC/Kv8Of22/SP+Zf6D/qH+vf7Y/tj+8v7y/gr/OP93/87/UwDeAH0BSgL0Ar4DbwQ4Bc4FcQYjB+UHTQi5CCoJKgm5CE0I5QcjB8gGHgaCBfIErwRvBG8EbwRvBPIEOAWCBR4GcQZxBnEGcQZxBs4FggXyBPcDIwMkAvYA3f/Y/tz9DP0J/FH7fvqP+d34G/iz90f31vbW9tb21vbW9tb21vbW9kf3s/ez9xv4G/gb+Bv4G/gb+Bv4G/iz97P3s/ez9xv43fiP+X76kfur/Nz9OP9TAF8BSgL0AokD9wOvBPIEOAWCBYIFggU4BfIErwRvBDIE9wOJA4kDVQNVA1UDVQNVA4kDvgP3AzIErwTyBIIFzgUeBnEGcQYeBoIF8gT3A1UDcgK7AQ4BdgD6/63/iv+c/93/MgCdAA4BfQHdASQCcgLHAvQCIwP0AvQCmwJKAt0BXwHeAFMA7P+K/zj/8v6h/mX+I/4A/tz9tv3c/SP+Zf69/gr/Y/+c/+z/FABCAHYAdgBkABQArf8i/2X+jv3d/An8Dvsy+o/5OPnd+N34OPmP+eL5Mvp++sj6DvtR+5H7CfxC/Kv83fzd/N383fzd/Kv8q/zd/Az9Of2O/dz9Zf4i/+z/3gDdAfQC9wPyBM4FyAblByoJGwoiC68LQQzaDNoM2gxBDK8LIgsbCqAJuQjlB4IHyAZxBnEGHgYeBh4GHgYeBh4GHgbOBYIFOAWvBDIEVQObApsBsgDO//L+Rf62/Tn9q/wJ/JH7yPp++jL64vni+eL54vni+TL6Mvp++sj6DvtR+1H7UftR+w77yPp++uL5j/nd+H74G/iz90f3R/dH97P3G/jd+OL5fvqR+3f8Zf1F/gr/3f+yAH0BJALHAlUDvgP3A/cDMgQyBDIEMgRvBG8EbwSvBK8E8gSCBc4FHgYeBnEGcQbIBiMHggflB+UH5QeCByMHcQaCBa8EiQObApsBsgDd/yL/g/4A/rb9tv3c/SP+g/7y/mP/3f9kAPYAfQEAAnICmwLHApsCcgIkAt0BuwGbAX0BXwFDASgBDgHIAHYAMgD6/93/3f/O/87/vv++/63/rf+t/63/nP93/zj/2P5F/rb93fwJ/A774vk4+Rv4s/dH99b21vZH97P3G/jd+I/54vl++lH7Cfyr/GX9AP6D/tj+Iv9O/4r/vv/O/87/zv++/63/rf/d/xQAdgD2AH0BJALHAlUD9wOvBIIFcQYjB+UHuQgqCaAJoAmgCSoJuQhNCOUHIwfIBnEGHgbOBc4FzgUeBh4GcQbIBsgGIweCB4IH5QflB4IHIwfIBh4G8gT3A/QCAAL2ABQAIv8j/jn9QvwO+zL6j/nd+H74G/iz97P3R/dH90f3R/dH97P3s/cb+Bv4G/gb+LP3s/ez97P3R/dH90f3R/dH97P3G/h++Dj5MvpR+3f8jv2D/nf/ZABDAQACxwJVA74DMgQyBG8EbwQyBPcDvgOJAyMD9ALHAscCxwKbApsCmwLHAscC9AIjA4kD9wOvBDgFzgVxBsgGyAZxBh4GggXyBG8EvgP0AkoCuwFDAfYA3gDIAN4A3gD2ACgBQwF9AbsBJAJKApsCmwKbAkoCAAJ9AQ4BiQAUAK3/OP/Y/mX+AP6O/Tn9DP3d/Kv8q/yr/N38DP1l/bb9I/6D/tj+OP+K/5z/rf+K/07/Cv+h/gD+Zf2r/M77Dvsy+o/5OPk4+d34OPk4+Y/5j/ni+TL6fvoO+1H7zvtC/Hf8d/x3/Hf8d/x3/EL8CfwJ/M77zvvO+wn8d/wM/dz9g/5O/yMADgEkAiMDMgSCBXEG5QcqCRsKnAoiCyILIgsiC5wKGwqgCSoJTQjlB4IHIwfIBsgGcQZxBh4GcQZxBnEGcQZxBnEGHgaCBfIE9wMjAyQCKAFCAHf/of4A/jn9d/yR+w77fvri+Y/5j/k4+Tj53fjd+Dj5OPmP+eL5Mvoy+n76Mvoy+uL54vmP+Tj53fgb+LP3R/fW9mD2YPZg9tb2R/ez9xv43fji+cj6kft3/Dn9I/7y/q3/ZAAOAZsBJAJyApsCxwL0AvQCIwNVA1UDvgP3A28ErwTyBDgFggXOBR4GcQbIBoIH5QdNCLkIuQhNCOUHggfIBh4GOAVvBFUDcgJ9AbIABgCK/zj/8v7Y/qH+g/69/vL+OP+t/xQAdgDIAA4BKAEOAfYAyACJAGQAMgAGAN3/vv+K/2P/Tv8i//L+2P6h/oP+Zf6D/qH+2P4K/yL/OP84/zj/OP8i//L+of4j/mX9q/zO+8j64vnd+Bv4R/dg9mD25fXl9WD2YPbW9kf3s/cb+N34j/ky+sj6UfvO+3f83fwM/WX9Zf2O/WX9Zf1l/WX9jv22/QD+Zf7Y/k7/zv9kACgBAAL0AvcD8gTOBcgGggflB00IuQi5CE0I5QeCByMHcQYeBoIFggU4BfIE8gTyBPIEOAU4BYIFHgZxBsgGIwcjByMHIwdxBs4FOAVvBL4D9AIkAkMBUwBj/2X+jv2r/M77Uft++uL5j/k4+d343fjd+N343fjd+N34fvh++H74fvgb+Bv4s/ez90f3R/fW9mD2YPZg9mD21vZH97P3fvg4+TL6UftC/GX9Zf5j/0IAKAEAAscCVQO+AzIEMgQyBDIEMgQyBDIEMgQyBDIEMgQyBDIEMgQyBG8EbwTyBDgFzgVxBsgGIweCB4IHggeCByMHcQbOBTgFbwSJA/QCcgLdAX0BQwEOAcgAsgCdAJ0AyAAOAV8BuwEkAkoCcgJyAiQCAAK7AV8BDgGyAFMA7P+K/yL/2P5l/gD+jv05/Qz93fzd/Az9Of2O/dz9Rf6D/tj+Cv9O/3f/nP+t/5z/Tv/y/kX+jv3d/An8UfvI+jL6j/k4+Tj53fjd+N34OPmP+eL5MvrI+g77kfsJ/EL8q/zd/N38DP0M/d38q/x3/EL8QvxC/EL8d/zd/GX9AP6h/mP/QgBDAUoCiQOvBM4FIwdNCCoJGwqcCiILIgsiC5wKGwqgCaAJKgm5CE0I5QflB4IHIwcjByMHggeCB+UH5QflB+UH5QeCB8gGHgaCBa8E9wMjA0oCfQGdAL7/8v4j/mX9q/wJ/JH7DvvI+sj6fvrI+sj6DvtR+5H7kfvO+877kfuR+1H7DvvI+n764vk4+d34G/iz90f3R/fW9tb2R/dH9xv4fvg4+TL6yPqR+3f8Of0A/tj+rf9kAA4BmwEkAnICxwIjA1UDiQO+A/cDbwSvBPIEOAWCBYIFHgZxBsgGggflB00IKgkqCaAJoAmgCSoJuQjlByMHcQaCBW8EiQPHAgACQwGyABQAnP84/wr/8v4K/zj/d/++/yMAdgDIAPYAKAFDAUMBKAEOAfYAyACdAIkAdgBTADIA+v++/3f/OP84/zj/Y/+c/93/FABCAGQAiQCyAN4A9gD2AN4AnQBCAL7/Cv9F/mX9d/yR+3764vk4+X74G/iz97P3s/cb+Bv4fvg4+Y/5MvrI+lH7zvtC/N38Of2O/dz9AP4j/gD+3P3c/bb9tv3c/QD+I/5l/r3+OP/O/3YAQwEkAvQC9wPyBM4FyAYjB+UH5QflB+UHggcjB8gGcQZxBh4GzgWCBTgFOAU4BTgFggXOBR4GyAYjB4IH5QflB+UH5QeCByMHyAYeBoIF8gQyBFUDSgJDAVMATv9l/o79q/wJ/FH7yPp++jL64vmP+Y/5j/mP+Y/5OPk4+d34fvh++Bv4s/dH90f31vZg9mD25fXl9WT15fXl9WD2R/ez9934j/l++lH7CfwM/QD+8v7s/8gAfQEAAkoCmwLHAvQC9AIjAyMDVQNVA1UDVQNVA1UDiQO+A/cDMgSvBDgFzgVxBsgGIweCB+UH5QeCB4IHyAZxBs4F8gRvBL4DIwObAiQCuwFfASgB9gDeAN4A9gAoAV8BfQGbAZsBuwG7AZsBXwEoAd4AdgAjAM7/Y/8K/4P+I/6O/Qz9q/xC/An8CfwJ/EL8d/zd/GX9tv1F/r3+Iv+K/93/FABCAFMAMgDs/4r/Cv+D/rb9DP13/An8kfsO+8j6yPp++n76fvp++sj6yPoO+1H7kfvO+0L8Qvx3/Kv8q/yr/Hf8QvwJ/M77UfsO+w77DvsO+1H7zvtC/Az9tv2h/pz/nQDdASMDbwSCBcgGggdNCE0IuQi5CLkIuQhNCE0I5QeCByMHyAbIBnEGcQZxBnEGyAbIBiMHIweCB4IHIwcjB8gGHgbOBTgFbwS+A/QCJAJfAXYAnP+9/tz9DP13/M77UfvI+n76fvp++n76yPoO+1H7UftR+5H7kfuR+1H7DvvI+jL64vk4+d34G/iz90f31vZg9mD21vZH90f3G/h++N34OPni+cj6kftC/Az93P2h/mP/BgCJAPYAXwG7AQACSgJyApsCxwL0AlUDiQP3AzIErwQ4Bc4FcQYjB+UHuQgqCaAJoAmgCaAJKgm5CE0IggfIBs4FOAVvBIkDxwIkApsBKAHIAGQAMgD6/+z/+v8UAEIAdgCdAMgAyADIALIAiQBkAEIAIwAGAOz/rf9j//L+of5l/iP+I/4j/kX+Zf6h/tj+Iv9j/63/+v9CAHYAsgDeAPYA3gCyAEIArf/y/kX+Zf2r/M77Dvt++uL5j/k4+Tj53fjd+Dj5OPmP+eL5fvrI+g77kftC/Kv8Of2O/dz9AP4j/iP+I/4A/tz93P22/bb93P0j/mX+vf44/77/dgBDASQCIwMyBDgFzgVxBiMHIweCB4IHIwcjB8gGcQYeBh4GzgWCBYIFOAWCBYIFzgUeBnEGyAaCB+UHTQhNCE0ITQhNCE0ITQjlB4IHIwdxBs4F8gT3A/QCAAIOARQAOP9l/o79DP13/An8zvuR+5H7UftR+1H7DvsO+8j6fvri+Y/5OPnd+H74s/dH99b2YPbl9eX15fXl9eX1YPbW9kf3G/jd+I/5fvpR+0L8Zf1F/jj/BgCyAEMBuwEAAiQCSgJyAnICmwJyAnICSgJKAkoCcgKbAscCIwO+A28E8gSCBR4GyAYjByMHggeCByMHyAZxBs4FOAWvBPcDiQP0ApsCJAK7AX0BQwEoAQ4BKAFfAX0BuwHdAQACAALdAd0BmwF9AV8BKAHeAIkAFACK//L+Zf7c/Tn9q/xC/An8zvvO+877CfxC/Kv8DP2O/QD+g/7y/mP/rf/s/wYA+v++/07/2P5F/rb9Of2r/EL8zvtR+w77yPp++jL6Mvoy+jL6Mvp++n76yPoO+1H7kfvO+wn8QvxC/EL8CfyR+1H7Dvt++jL6Mvoy+jL6fvrI+g77kft3/GX9Zf6c/8gAAAIjAzIE8gSCBc4FHgZxBnEGcQZxBnEGHgYeBs4FggU4BfIE8gTyBDgFggWCBc4FHgYeBh4GHgYeBs4FzgWCBTgFrwQyBIkD9AIkAkMBiQDO/wr/Rf5l/av8CfyR+w77DvsO+w77UfuR+877CfwJ/EL8QvwJ/An8zvtR+w77fvri+Tj5fvgb+LP3R/fW9tb21vbW9tb2R/dH97P3fvjd+I/5MvoO+wn83fy2/YP+Tv/6/4kADgF9Ad0BJAJyApsCxwL0AvQCIwNVA4kDMgSvBIIFHgYjB+UHuQgqCaAJGwobChsKoAkqCbkI5QcjB3EGggWvBPcDVQObAt0BQwGyAEIA7P+t/4r/iv+K/4r/rf+t/77/vv/O/93/3f/d/77/rf93/zj/8v6h/kX+3P2O/Tn9DP3d/Az9Of1l/dz9I/6D/vL+Tv++/zIAnQD2ACgBKAH2AJ0AMgCc/wr/Zf7c/Tn9q/wJ/FH7yPp++jL64vni+eL5Mvoy+n76yPoO+1H7zvt3/Az9jv0A/kX+g/6h/qH+g/5l/kX+I/4A/tz9jv2O/Y79tv0A/qH+Tv8jAA4BAAL0Ar4DrwQ4Bc4FHgZxBnEGcQZxBnEGHgYeBs4FggWCBTgFOAU4BYIFzgUeBnEGyAYjB4IH5QflB00ITQi5CLkIuQi5CE0I5QeCB8gGHgY4BW8EVQNKAigBBgDy/iP+Zf3d/Hf8QvwJ/M77zvvO+5H7kftR+w77yPp++jL6j/k4+X74G/iz90f31vZg9uX15fXl9eX15fVg9tb2R/ez9374OPky+g77Qvw5/UX+OP/6/50AQwG7ASQCmwLHAvQC9ALHApsCcgIkAiQCAAJKApsCIwO+A28EOAXOBXEGIweCB+UHTQhNCE0I5QeCByMHcQYeBoIF8gQyBL4DIwPHAnICJAIAAgACAAIkAkoCcgJyAnICmwKbApsCxwLHApsCmwJyAiQC3QF9AfYAZAC+/wr/Zf7c/Y79Zf05/Tn9jv3c/SP+of44/93/dgAOAZsBJAJyAnICSgIkArsBfQEOAZ0AIwCt/zj/of4j/rb9Zf0M/d38d/x3/EL8QvxC/EL8d/yr/Az9Of2O/bb93P3c/dz9jv05/d38d/wJ/JH7DvvI+n76Mvp++sj6UfsJ/N383P3y/vr/DgEkAiMD9wOvBPIEggXOBc4FHgYeBh4GHgbOBYIFggU4BTgFOAWCBc4FHgZxBnEGyAbIBsgGIwcjByMHggcjByMHyAZxBs4FggWvBDIEVQNyAl8BZABj/4P+tv0M/av8d/xC/EL8d/x3/Kv83fwM/Tn9Of05/Qz93fx3/M77UfvI+jL6j/nd+Bv4s/dH99b21vZg9mD2YPbW9tb2R/ez9xv43fiP+X76UfsJ/N38tv1l/iL/rf8yALIADgEoASgBDgHeAN4A3gAOAV8B3QFyAiMD9wOvBIIFcQYjB4IHTQhNCE0I5QflByMHyAYeBoIFrwT3AyMDcgKbAfYAUwDO/3f/Iv/y/tj+2P7Y/tj+2P7y/iL/OP9O/3f/iv+c/5z/nP93/07/8v6D/gD+Zf0M/av8q/x3/Kv83fwM/WX9tv0j/r3+Y/8GALIAQwGbAd0B3QG7AV8BDgHIAGQA+v93/9j+I/5l/d38QvzO+5H7UfsO+8j6yPp++sj6yPoO+1H7zvtC/Kv8Of2O/dz9AP4j/iP+AP7c/bb9Zf3d/Hf8CfzO+877zvtC/Kv8Of0A/tj+rf+JAF8BJAKbAiMDiQO+A/cD9wP3A/cD9wO+A4kDVQMjA/QC9AIjA4kDvgMyBG8E8gQ4BYIFzgUeBnEGIwcjB4IH5QflB+UH5QflB4IHyAYeBjgFMgQjAwAC9gD6/yL/g/7c/WX9DP3d/N383fzd/Kv8q/x3/EL8zvtR+8j6fvri+Tj53fgb+LP3R/fW9mD25fXl9WT1ZPVk9eX15fVg9tb2R/cb+Dj5MvpR+3f8Of0j/gr/zv+JAEMBuwEkAkoCJAIAApsBXwFDAUMBXwGbAQACcgL0Ar4DbwQ4BR4GyAaCB+UH5QflB+UHggeCByMHcQYeBoIFrwQyBIkD9AJyAiQC3QG7AZsBfQF9AV8BXwF9AX0BmwG7AbsB3QHdAQACAAIAArsBfQH2AFMArf/y/kX+jv0M/Xf8QvwJ/An8CfxC/Kv8Of3c/b3+Y/8GAIkA3gAOASgBKAEOAfYAyAB2ACMArf84/73+Zf4A/o79Of3d/Hf8QvzO+5H7kfuR+5H7kfvO+wn8d/yr/N38Of1l/WX9Zf0M/d38QvzO+1H7yPoy+uL5j/mP+eL5MvrI+pH7q/yO/aH+rf+JAF8BAALHAlUDvgMyBG8ErwTyBPIErwRvBG8EMgQyBG8ErwTyBDgFggWCBc4FzgUeBnEGcQbIBiMHIwcjByMHIwcjB8gGcQYeBjgFbwSJA3ICXwFCADj/Rf6O/Qz9q/xC/EL8QvxC/Hf8q/zd/N383fzd/Kv8d/xC/M77UfvI+jL64vk4+d34fvgb+LP3R/fW9mD2YPZg9mD2YPbW9kf3s/d++Dj54vl++lH7QvwM/dz9of5O/77/BgAGAOz/zv++/77/vv/d/yMAnQAoAQAC9AL3A/IEzgXIBoIH5QdNCE0IuQhNCE0I5QcjB8gGzgU4BW8EvgMjA5sCJAKbASgByAB2AEIAIwAUAAYABgAjAEIAZACdAN4AKAFfAZsBmwF9AUMB3gBkAN3/Tv/Y/oP+I/4A/tz93P3c/SP+g/4K/77/ZAAoAd0BSgKbApsCmwKbAnICJALdAV8B3gBTAL7/Iv+D/gD+jv3d/Hf8CfyR+w77yPrI+sj6yPrI+g77UfuR+wn8d/zd/Dn9Zf2O/bb9jv1l/Qz9q/xC/M77UfsO+8j6yPoO+5H7d/w5/QD+8v7d/7IAfQEkAscCIwO+A/cDMgRvBG8EMgT3A/cDvgO+A74D9wMyBG8ErwSvBPIEOAXOBR4GcQbIBiMHggflB00IuQgqCSoJoAmgCSoJuQjlByMHHgY4BTIEIwMkAigBZAC+/zj/8v69/qH+of6h/qH+of6D/kX+AP62/WX93fx3/An8UfsO+376Mvri+Y/5OPnd+H74G/iz97P3R/ez9xv4fvjd+I/5fvoO+wn83fyO/YP+d/9CAPYAXwGbAbsBmwFfAQ4B3gCyAJ0AnQCyAPYAfQEkAscCvgNvBDgFHgbIBiMHggeCB+UH5QeCByMHyAZxBs4FOAWvBDIEvgNVA/QCmwJKAgACAALdAd0B3QG7AbsB3QEAAiQCcgLHAvQCIwMjA/QCmwJKArsBKAF2AM7/OP+D/gD+jv1l/Tn9DP05/bb9Zf4K/87/iQAOAZsB3QFKAnICcgJyAkoCJAK7AX0BDgGyAFMA+v+K/wr/g/4A/mX93fyr/EL8CfwJ/M77zvsJ/An8Qvyr/Az9Of1l/Y79jv1l/Qz9q/xC/M77Dvt++jL64vni+eL5MvoO+8773fzc/dj+vv+dAH0BJAL0AokD9wNvBK8E8gQ4BTgFOAXyBPIEOAU4BYIFggXOBc4FzgXOBR4GHgZxBsgGyAYjB4IH5QflB00ITQhNCE0I5QeCByMHHgY4BW8EVQNKAkMBUwB3/9j+Rf7c/bb9tv3c/dz9AP4j/iP+Rf5F/iP+3P2O/Qz9q/xC/M77UfsO+8j6Mvri+Tj53fgb+LP3R/dH99b21vZH90f3s/d++N34j/l++lH7QvwM/dz9of44/63/7P8GAPr/3f+t/3f/Y/9O/2P/nP8jAN4AuwGbAokDbwQ4BR4GcQYjB4IHggeCB4IHIwfIBnEGzgWCBfIEbwT3A4kDIwObAiQCuwFfAQ4ByAB2AEIAIwAyAEIAdgDIAA4BXwGbAbsBuwF9ASgByABCAK3/Cv+D/gD+jv05/d38q/yr/N38Of22/YP+OP/s/4kADgFfAZsBuwHdAd0BuwF9AUMB9gCdAEIA3f93/wr/Zf7c/Tn9q/wJ/JH7DvvI+n76fvoy+n76fvrI+g77kfvO+wn8Qvx3/Kv8q/x3/EL8zvtR+8j6Mvri+Y/54vky+n76UfsJ/N38tv2D/mP/MgD2AJsBJALHAiMDiQO+A74DvgOJA4kDiQO+A/cD9wMyBG8EbwSvBK8E8gQ4BTgFggXOBR4GcQbIBoIH5QdNCLkIuQi5CE0I5QeCB8gGHgY4BTIE9ALdAd4ABgBO/73+Zf4j/gD+3P3c/dz93P22/Y79Of3d/EL8zvtR+8j6fvoy+uL5j/k4+d34fvgb+Ef31vZg9mD25fXl9eX1YPbW9kf3G/h++I/5MvoO+wn8DP0A/r3+Tv+c/87/zv+t/3f/OP/y/r3+of7Y/iL/nP8yAMgAmwFKAvQCvgMyBK8E8gQ4BYIFggU4BfIE8gSvBG8EMgS+A1UD9AKbAkoCAAK7AZsBXwEoAfYAyADIAMgADgFfAbsBJAJyApsC9AL0AvQCxwKbAiQCmwH2AGQAvv8i/4P+AP6O/Tn9Of1l/bb9I/69/k7/7P9kAMgADgFDAV8BfQFfAUMBDgHeAJ0AdgBTABQAzv93//L+Zf62/Tn93fxC/M77kftR+w77yPrI+sj6DvtR+1H7kfvO+wn8CfwJ/An8kfsO+376j/k4+X74G/gb+Bv4fvjd+I/5fvpR+0L8DP3c/aH+Tv/6/4kAKAGbASQCcgLHAvQCIwNVA74D9wMyBG8ErwTyBPIE8gQ4BTgFggWCBc4FHgZxBnEGyAaCB4IH5QdNCE0ITQjlB4IHyAYeBjgFMgRVA0oCXwGJAN3/Y//y/r3+g/6D/oP+of7Y/vL+8v7Y/qH+Rf7c/Y79Of0M/d38d/xC/M77kfsO+3764vk4+d34G/iz97P3s/ez97P3s/cb+H74OPni+X76kft3/GX9Rf7y/nf/vv/s/+z/zv+t/3f/OP8i/yL/d//d/4kAQwEkAvQCvgNvBDgFzgUeBnEGcQZxBnEGcQYeBs4FggU4Ba8EbwT3A4kDIwObAkoC3QF9AQ4BnQBTABQABgAUADIAdgDeAEMBmwEAAiQCSgJKAiQC3QFfAfYAdgD6/4r/Cv+h/kX+AP4A/gD+Zf7Y/mP/BgCdAA4BfQG7Ad0BAAIkAiQCAAIAAt0BmwF9AV8BKAHeAHYA7P9j/9j+Rf62/Tn93fx3/An8zvvO+877zvsJ/EL8d/zd/Dn9jv3c/SP+Rf4j/rb9Of2r/EL8kftR+w77DvsO+1H7zvtC/N38jv1F/tj+Y//6/3YA9gBfAd0BJAJyApsCmwLHAscC9AIjA1UDVQOJA74D9wP3AzIEMgQyBG8EbwSvBPIEOAXOBR4GyAaCB+UH5QdNCE0I5QeCByMHcQaCBW8EiQNyAn0BsgDs/2P/2P6D/kX+I/4j/iP+AP62/Y79Of2r/EL8CfyR+1H7DvvI+sj6fvoy+uL5j/k4+X74G/iz90f31vbW9tb21vZH90f3s/cb+N344vnI+s77q/yO/WX+8v53/63/zv++/5z/Y/84/wr/Cv84/4r/FACdAEMBAALHAlUD9wOvBPIEggXOBc4FHgYeBh4GHgbOBc4FggXyBK8EbwQyBPcDvgOJAyMDxwKbAkoCAALdAQACJAJKApsC9AJVA4kDvgP3A/cDiQNVA/QCSgK7AQ4BZACt//L+Rf7c/WX9Of1l/Y79AP5l/vL+Y//O/yMAdgDIAN4A9gD2APYA9gD2APYADgH2AN4AsgBTAAYAnP84/73+Rf7c/WX9DP2r/Hf8QvxC/EL8Qvx3/N38DP1l/bb93P3c/bb9Zf3d/EL8kfvI+jL64vni+eL54vl++g77kftC/Az9tv1F/tj+d/8UAMgAXwHdAUoCxwL0AlUDiQO+AzIEbwSvBPIEOAU4BYIFggWCBc4FzgXOBc4FHgZxBsgGIwflB00IuQi5CCoJKgm5CLkITQiCB8gGzgWvBL4D9AIAAkMBnQAGAJz/Y/84/zj/Tv9O/07/OP8K/9j+of5l/iP+AP7c/bb9jv1l/Tn93fx3/An8kfvI+jL64vk4+d343fh++H74fvh++H743fiP+TL6DvsJ/Az9tv1F/r3+Iv84/zj/Cv+9/mX+Rf4j/kX+g/4K/77/iQBDASQC9AK+A28EOAXOBXEGyAbIBiMHIwfIBsgGcQYeBs4FggU4Ba8EbwT3A1UD9AJKArsBQwHeAIkAUwBCAFMAnQDeAEMBuwEAAkoCSgJKAgACuwFfAfYAdgDs/07/2P5F/tz9jv2O/Y793P0j/qH+Cv+K/+z/UwCyAN4ADgEoASgBDgEOAQ4BDgH2APYAsgB2ABQArf84/6H+I/6O/Qz9d/wJ/JH7UfvI+sj6fvp++sj6yPpR+5H7CfxC/Hf8d/xC/M77kfsO+376Mvri+Y/5j/ni+TL6yPpR+877d/zd/I79I/7Y/nf/FACdAA4BfQG7Ad0BAAIkAnICxwL0AiMDiQOJA74D9wMyBG8ErwSvBK8ErwTyBDgFzgUeBsgGIwflB00IuQi5CLkIuQhNCOUHIwdxBs4F8gT3A/QCJAJfAZ0AIwC+/3f/Tv8i/wr/2P69/mX+AP62/Tn93fyr/EL8CfzO+877kftR+w77yPoy+o/5OPl++Bv4s/ez90f3R/dH90f3R/ez9374OPky+g77Cfzd/I79AP5l/qH+vf6h/oP+Rf4A/tz93P0j/mX+vf44/63/MgDeAH0BJALHAlUDvgMyBK8E8gTyBPIE8gTyBK8EbwQyBPcD9wO+A4kDIwPHAnICJAK7AV8BKAEOAQ4BQwGbAQACcgL0AlUDiQO+A74DvgOJAyMDxwJKArsBDgF2AL7/Iv+h/mX+I/4j/kX+of7y/k7/zv9CAJ0A9gAoAUMBQwFfAV8BfQF9AZsBmwGbAX0BQwEOAbIAUwDs/4r/Cv+h/iP+tv05/d38q/x3/Hf8d/yr/N38DP05/WX9jv1l/Qz9q/wJ/JH7yPoy+uL5j/k4+Y/5j/ni+X76yPpR+877d/wM/Y79I/7Y/mP/3f9CAJ0A9gBDAX0B3QEkAnICxwIjA1UDvgP3AzIEbwRvBG8EbwRvBK8ErwQ4BYIFHgZxBsgGIweCB4IHggeCByMHyAYeBoIFrwT3AyMDSgJ9AbIA7P9j//L+of5l/kX+I/4j/gD+tv1l/Qz93fx3/EL8CfwJ/M77kftR+1H7Dvt++jL6j/k4+X74G/iz90f31vbW9mD2YPZg9tb2R/ez9xv43fji+X76UfvO+3f83fzd/N383fyr/Hf8d/x3/Kv8DP1l/dz9g/4i/93/nQB9ASQC9AKJAzIErwTyBDgFOAU4BTgF8gSvBG8EMgT3A74DiQMjA8cCSgK7AUMByAB2ADIAFAAjAGQAsgAOAZsBJAJyApsCxwKbApsCcgIkAt0BXwH2AGQA3f9j//L+of5l/mX+g/7Y/iL/iv/6/2QAyAAOAUMBXwF9AX0BmwGbAbsBuwGbAX0BXwEoAd4AiQAjAK3/OP+9/iP+tv05/av8d/xC/An8zvvO+877CfxC/Hf83fzd/N383fx3/An8kfsO+376Mvri+eL54vni+TL6fvoO+1H7zvtC/N38Zf0j/qH+OP+c/wYAUwCdAMgA9gAoAX0BuwEAAiQCcgL0AiMDiQO+A/cD9wMyBG8ErwTyBIIFHgZxBiMH5QdNCLkIKgkqCSoJKgkqCbkITQiCByMHHgaCBa8EvgMjA3IC3QFfAQ4ByACJAFMAFADO/3f/Cv+h/kX+3P2O/Tn9DP0M/d383fyr/EL8CfyR+w77yPoy+uL5j/k4+d343fjd+N34OPmP+eL5fvpR+wn83fy2/WX+2P44/07/Y/84/wr/2P69/qH+vf7Y/gr/Y/++/yMAnQBDAd0BcgL0AokD9wNvBK8EOAU4BTgFOAU4BfIE8gSvBG8EbwQyBPcDvgNVA8cCSgLdAZsBXwEoAUMBXwG7ASQCmwL0AlUDiQO+A74DvgOJA1UD9AJyAt0BQwGyABQAiv8K/73+g/5l/mX+g/7Y/jj/iv/6/0IAdgCdAMgA3gD2APYAKAFDAV8BXwFDASgB3gCdAGQABgCt/zj/vf5F/tz9Zf0M/av8q/x3/Hf8d/x3/Kv83fwM/Qz9DP3d/Hf8CfxR+8j64vmP+d34fvh++H74fvjd+Dj5j/ky+sj6UfvO+3f8DP3c/WX+8v53/87/IwB2AMgADgFfAZsBAAJKApsC9AJVA4kDvgO+A/cDMgRvBK8EOAXOBR4GyAYjB+UHTQhNCLkIuQi5CE0I5QeCByMHcQaCBfIEMgSJA8cCAAJ9AfYAsgB2AFMAMgD6/77/d/8i/73+g/4j/gD+3P3c/dz9tv2O/WX9DP2r/EL8zvtR+w77fvri+Y/5OPnd+N34fvh++N34OPmP+eL5fvoO+877d/zd/Dn9jv2O/Y79Zf1l/Tn9Of1l/Y793P0j/oP+Cv+c/0IA3gCbAXICIwO+A28E8gQ4BYIFzgXOBR4GzgXOBYIFggU4BTgF8gSvBDIEvgNVA8cCSgLdAZsBfQGbAbsBJAJyAvQCVQOJA74DvgO+A4kDVQMjA5sCSgK7ASgBsgAjAK3/Tv8K//L+Cv84/4r/3f9CALIA9gBDAX0BmwHdAQACJAJyAnICmwKbAnICSgIAArsBXwH2AGQA3f84/6H+AP6O/Tn93fyr/Hf8QvxC/EL8d/yr/N38Of05/Tn9DP2r/An8kfvI+n764vni+Y/5j/mP+Y/54vky+n76DvuR+wn8q/w5/dz9Zf7Y/k7/rf8GAEIAdgCdALIA3gAOAUMBfQG7AQACJAJKAkoCcgKbAscC9AJVA/cDbwQ4Bc4FcQbIBoIH5QflB00ITQhNCOUH5QeCB8gGcQbOBfIEbwS+AyMDmwJKAgACuwGbAV8B9gCdADIAzv9O//L+of5l/iP+AP7c/bb9jv05/d38d/wJ/JH7Dvt++jL6j/k4+d343fh++H74fvjd+N34j/ky+sj6UfsJ/Hf83fw5/Tn9Zf05/Tn9Of05/Tn9Of1l/Y793P0j/oP+8v53//r/iQAOAX0BAAKbAiMDiQP3AzIEMgQyBDIEMgQyBDIE9wP3A74DiQMjA8cCSgLdAZsBXwFfAX0BuwEkApsC9AJVA74D9wMyBDIEMgQyBPcDiQMjA8cCJAKbAfYAZADd/2P/Iv/y/tj+2P7Y/vL+Iv9O/3f/nP++/93/IwBkAIkAyAD2AA4BDgEOAfYAyACJAEIA7P93/wr/of5F/tz9jv05/Qz93fyr/Kv8q/zd/Az9Zf2O/bb9jv1l/Qz9d/wJ/FH7yPoy+uL5j/k4+Tj5OPmP+Y/54vky+sj6UfvO+3f8DP3c/WX+Cv+K//r/QgCJAMgADgFfAbsBAAIkAnICxwLHAvQCIwMjA1UDiQP3A28E8gSCBR4GyAYjB+UHTQi5CCoJKgkqCSoJuQhNCOUHggfIBnEGggXyBDIEiQMjA5sCcgIkAgACuwF9ASgB3gB2ADIA+v/O/77/rf+c/3f/Y/84/9j+g/4A/o79DP13/M77UfvI+jL64vmP+Tj53fjd+N34OPk4+Y/5Mvp++g77kfvO+wn8QvxC/EL8QvwJ/EL8Qvx3/Hf83fwM/WX93P1F/tj+Y/8GAJ0AXwEkAscCiQP3A28ErwTyBPIE8gTyBK8ErwRvBDIE9wO+A1UDxwJKArsBQwH2AMgAnQCyAPYAQwGbAQACcgLHAvQCIwMjAyMDIwP0AscCcgIAApsBDgGdAEIA3f+t/4r/d/93/5z/zv/s/xQAQgBkAJ0A3gAOAUMBfQG7Ad0BAAIAAgAC3QG7AV8B9gB2AN3/Tv+9/iP+tv1l/Qz9q/x3/EL8QvxC/Hf8q/wM/Tn9Zf1l/Tn9DP2r/An8kfsO+8j6fvoy+uL54vni+eL54vni+TL6fvrI+lH7zvtC/N38jv0j/oP+8v5j/77/BgAyAFMAiQCyAN4A9gAOASgBKAFDAUMBXwGbAd0BJAKbAiMDvgNvBPIEzgVxBsgGIweCB+UH5QflB+UHggcjB8gGcQbOBTgFrwT3A1UD9AKbAiQC3QF9ASgBsgBTAOz/d/8i/73+g/5F/gD+3P22/Y79Of3d/Hf8CfyR+w77fvri+Y/53fh++Bv4G/iz97P3s/cb+Bv4fvg4+Y/5Mvp++g77UftR+5H7kfuR+5H7kfuR+877zvsJ/EL8d/yr/Az9Zf22/UX+vf44/87/ZAAOAZsBJAKbAscCIwMjA1UDVQNVA1UDVQMjA/QCmwJKAt0BfQEoAd4AsgDIAPYAQwGbAQACcgL0AlUDiQO+A/cD9wP3A/cDvgOJAyMDxwJKAt0BXwH2AIkAMgDs/77/nP+K/3f/iv+c/77/+v8yAHYAyAAOAV8BmwEAAiQCSgJKAkoCAAKbAUMB3gB2ABQAnP84/9j+g/4j/rb9jv1l/Y79jv3c/QD+I/5l/mX+Rf4A/o79DP2r/An8kfsO+376Mvri+Y/5j/mP+Tj5j/mP+eL5MvrI+lH7zvt3/Dn9tv1F/r3+Iv+K/+z/QgCdAN4AKAFfAZsBuwG7Ad0B3QEAAiQCcgLHAlUDvgNvBDgFzgVxBiMHggflB00IuQi5CLkITQhNCOUHggcjB8gGHgaCBfIEMgS+A1UD9AKbAkoC3QF9AQ4BnQBCAOz/nP9j/zj/OP8i/wr/2P6h/kX+3P1l/Qz9d/wJ/JH7Dvt++jL64vmP+Tj5OPk4+Tj5j/mP+eL5Mvp++sj6DvtR+5H7kfuR+877zvvO+877zvsJ/An8Qvx3/N38DP1l/dz9Zf7y/pz/UwAoAd0BmwJVA74DMgSvBPIEOAU4BYIFggWCBTgFOAXyBG8E9wOJA/QCcgIkAt0B3QEAAiQCcgLHAiMDVQOJA74D9wP3A/cD9wO+A4kDVQP0AnICAAKbASgByABkACMA7P/O/77/rf+c/63/vv/d/xQAUwCJAN4AQwGbAd0BJAJKAkoCSgIkArsBXwHeAFMAzv84/6H+I/62/Tn9DP2r/Kv8d/yr/Kv83fwM/Tn9Zf1l/Tn93fx3/An8kfsO+8j6Mvri+eL5j/k4+Tj53fjd+Dj5OPmP+TL6yPpR+wn8q/w5/dz9g/4K/4r/3f8jAGQAnQDIAN4A9gAOAfYA9gDeAN4A9gAOAUMBuwFKAvQCiQNvBDgFzgVxBiMHggflB00IuQi5CLkIuQi5CE0I5QeCByMHyAYeBoIFOAWvBG8E9wOJA1UDxwJyAgACmwEoAd4AnQB2AFMAIwDd/5z/OP/Y/kX+3P05/av8CfyR+w77fvri+Y/5OPnd+N343fjd+Dj5j/ni+TL6yPoO+1H7kfuR+877zvsJ/An8CfxC/Hf8d/yr/N38DP0M/WX9tv0A/oP+8v6K/yMAyABfAQACmwIjA4kDvgP3AzIEbwSvBK8ErwSvBG8E9wOJAyMDmwIkAgAC3QEAAiQCcgLHAiMDVQO+A/cDMgRvBK8ErwSvBK8EbwRvBPcDvgNVA/QCmwIkApsBKAHIAGQAIwDd/77/rf+t/63/vv/d/xQAUwCyAA4BfQG7AQACJAIkAgACuwF9AQ4BsgAyAL7/Tv/y/oP+I/7c/bb9jv1l/WX9jv22/dz9AP4j/iP+AP62/WX93fx3/M77UfsO+376MvqP+Tj53fh++H74fvh++H743fg4+eL5MvoO+5H7QvwM/Y79I/69/jj/rf8jAIkAyAAOASgBQwFDAUMBQwFfAX0BuwEkAscCVQP3A68EggUeBsgGggflB00IuQi5CLkIuQi5CE0ITQjlB4IHIwdxBh4GggXyBK8EMgS+A4kDIwObAkoCuwFfAQ4B3gDIALIAsgCJAGQAMgDO/3f/Cv+D/gD+Zf2r/An8UfvI+jL64vmP+Tj53fjd+N34OPk4+Y/54vni+TL6fvp++sj6yPrI+g77DvsO+w77UftR+1H7kfuR+877CfxC/Hf8DP2O/SP+2P6c/2QAKAHdAXIC9AJVA/cDMgSvBPIEOAU4BTgFOAXyBG8E9wOJAyMDxwKbAnICcgKbAscCIwNVA4kDvgMyBG8EbwSvBK8ErwSvBG8EbwQyBL4DiQMjA8cCcgIAApsBXwEOAcgAiQB2AFMAQgBCAFMAdgCyAPYAQwGbAd0BAAIkAiQCAALdAZsBKAGdAAYAiv8K/4P+I/62/WX9DP3d/N383fzd/Az9Of2O/bb9tv22/WX9Of3d/Hf8CfzO+5H7DvvI+n76Mvri+Y/5OPk4+d34OPk4+Y/54vl++g77kftC/N38Zf0A/oP+8v5O/4r/vv/d/93/3f/O/63/nP93/2P/Y/+K/+z/ZAD2ALsBcgIjA/cDrwQ4Bc4FcQbIBiMHggflB+UHTQhNCOUH5QeCByMHyAYeBs4FggXyBK8EMgS+A1UD9AJyAgACuwF9AUMBKAH2AMgAnQBCAPr/nP84/73+I/5l/d38CfyR+8j6fvri+Tj5OPnd+N343fjd+N34OPmP+Y/54vky+jL6fvp++sj6yPrI+g77DvsO+w77UftR+1H7kfuR+877zvsJ/Hf83fyO/SP+2P6K/zIA3gB9AQACmwL0AlUDvgP3AzIEMgT3A74DVQPHAnICAAK7AX0BfQGbAbsB3QEkAnICxwL0AlUDiQOJA74DvgO+A74DvgO+A1UDIwP0ApsCJAK7AUMByABTAOz/iv8i/9j+g/5l/kX+Rf5l/oP+2P4i/3f/zv8jAFMAdgCJAGQAIwDO/3f/Iv+9/mX+AP62/Tn9DP3d/Kv8d/yr/Kv83fw5/WX9tv22/bb9tv2O/WX9Of0M/av8d/wJ/JH7DvvI+n76Mvri+Y/5OPk4+Tj5j/ni+TL6DvuR+wn83fxl/SP+vf44/87/QgCdAN4ADgEoASgBKAEOAfYA3gDeAA4BQwG7ASQCxwJVAzIE8gSCBR4GcQYjB4IH5QflB00ITQi5CLkITQhNCOUHggcjB8gGHgbOBYIF8gRvBPcDiQP0AnICAAK7AX0BXwFDASgBDgH2AMgAiQBCAM7/Y//Y/iP+jv3d/EL8kfsO+3764vmP+Tj5OPk4+Tj5OPk4+Tj5OPmP+Y/5j/mP+eL54vni+eL54vni+TL6Mvoy+n76fvp++n76yPrI+lH7kftC/N38jv1l/iL/7P+yAH0BJALHAlUD9wNvBK8EOAU4BTgFOAXyBG8EMgS+A4kDVQNVA1UDiQOJA/cDMgRvBK8E8gQ4BYIFggXOBc4FHgYeBh4GHgbOBYIFggXyBK8EbwT3A4kDIwObAkoC3QGbAUMBDgH2APYADgEoAV8BmwHdASQCcgJyAnICSgIAApsBQwHeAHYABgCK/zj/2P6D/kX+AP7c/dz93P0j/kX+g/69/tj+2P69/qH+Zf4j/gD+tv1l/Qz93fx3/EL8zvuR+w77yPp++n76fvp++n76yPpR+877Qvzd/I79I/7Y/nf/+v9kAMgA9gAoASgBDgH2AN4AnQB2AHYAiQCyAA4BfQEkAscCiQMyBK8EggXOBXEGIweCB+UHTQi5CLkIKgkqCSoJuQi5CE0ITQjlB4IHIwdxBh4GggXyBG8E9wOJAyMD9AKbAnICcgJKAiQCAAK7AV8BDgF2AN3/OP+h/tz9Of2r/An8UfvI+n764vni+Y/5j/mP+Y/54vni+eL5Mvoy+n76fvp++n76fvp++n76fvrI+sj6yPrI+sj6yPrI+sj6yPoO+1H7zvt3/Az9tv1l/gr/zv+JAEMBAAKbAiMDvgMyBG8EbwRvBG8E9wO+A4kDIwP0AvQC9AL0AiMDVQOJA74DMgQyBG8ErwTyBPIEOAU4BTgFOAU4BTgF8gSvBK8EbwT3A4kDIwObAiQCmwEoAbIAQgDs/63/d/93/3f/rf/6/2QAsgD2AA4BDgH2AMgAdgAyAN3/iv84/9j+Zf4A/rb9jv1l/Tn9Of05/Tn9Zf2O/bb93P22/Y79Zf05/Qz9q/xC/An8zvtR+w77yPp++uL5j/k4+d34fvh++Bv4fvh++N34OPni+X76DvvO+6v8Of3c/YP+8v5O/4r/rf+t/63/rf+K/3f/Y/9O/2P/iv/s/2QA9gCbASQCxwJVA74DMgTyBIIFzgUeBsgGyAYjByMHggeCB4IHIwcjByMHyAZxBh4GzgWCBfIEbwQyBL4DVQP0AscCxwKbApsCmwJyAkoCAAK7AUMBsgAUAHf/vf4A/jn9d/zO+1H7yPp++jL64vni+Y/5j/mP+Y/5j/mP+eL54vni+eL5j/mP+eL54vni+TL6fvrI+sj6yPrI+sj6yPoO+w77kfsJ/Hf8DP22/YP+Tv8UAN4AuwFyAiMDvgMyBK8E8gTyBPIErwRvBDIEvgOJA1UDIwP0AvQC9AIjAyMDVQOJA74DvgP3AzIEMgRvBG8ErwSvBK8ErwRvBG8EMgT3A/cDiQMjA8cCSgLdAV8B9gCJADIA3f+c/3f/iv+t/93/MgB2ALIAyADIAJ0AdgAyAN3/iv8i/6H+Rf7c/Y79Of3d/Kv8d/x3/Hf8q/zd/Az9Zf22/dz9AP4A/gD+3P22/Y79Zf05/Qz93fyr/EL8CfyR+1H7yPp++jL64vni+eL5Mvoy+sj6UfvO+3f8Of3c/WX+8v5j/63/3f/6/wYABgDd/77/iv9O/zj/OP9j/77/MgDIAF8BAAKbAiMDvgNvBPIEggUeBnEGIweCB+UH5QdNCE0ITQhNCE0ITQjlB4IHIwfIBnEGzgU4BfIEbwT3A4kDVQMjA/QC9ALHApsCcgIAArsBKAGdAAYAY/+9/gD+Of2r/An8UfvI+n76Mvri+eL5j/mP+Y/5j/mP+Y/5j/mP+Y/5j/mP+Tj5OPk4+Y/5j/ni+eL5Mvoy+uL54vni+eL5Mvoy+n76DvuR+wn83fyO/WX+OP/6/8gAmwFKAvQCiQP3A28EbwRvBG8EMgQyBPcDvgO+A74DvgO+A/cDMgQyBG8ErwTyBDgFggWCBc4FzgXOBc4FzgWCBYIFggWCBTgF8gSvBDIEvgMjA8cCJAK7ASgBsgBCAN3/rf+t/87/FABkALIA9gAOASgBDgH2AMgAiQBCAOz/iv8i/9j+Zf4j/tz9jv1l/Tn9DP05/Tn9Zf2O/bb93P3c/dz9tv2O/WX9Of0M/d38q/x3/EL8CfyR+1H7yPp++uL5j/k4+Tj5OPk4+Tj5j/ky+sj6kftC/Az9tv1l/vL+Y/++/wYAIwBCAEIAMgAUAOz/zv/d/wYAQgCyAA4BmwEkApsCIwO+A28E8gSCBc4FcQbIBiMHggflB+UH5QdNCE0ITQjlB+UH5QeCB4IHyAZxBh4GggU4Ba8EbwQyBPcD9wP3A74DvgOJA4kDIwP0AnIC3QFDAZ0A3f8i/0X+jv3d/EL8zvtR+w77yPp++jL6Mvri+eL54vni+eL54vmP+Y/5OPk4+Tj5OPmP+Y/54vni+eL54vni+eL54vni+TL6fvrI+g77zvt3/Dn9AP69/pz/dgBDAQACmwIjA4kD9wP3AzIEMgT3A74DvgOJA1UDIwMjAyMDIwMjA1UDVQOJA74DvgP3A/cDMgQyBDIEMgQyBG8EbwRvBG8EMgQyBPcDvgNVA/QCmwIkArsBQwHIAFMA+v++/63/vv/s/xQAQgB2AJ0AsgCyAJ0AdgAyAOz/nP84//L+g/4j/rb9Zf0M/d38q/x3/Hf8q/zd/Dn9Zf2O/Y79tv22/Y79jv1l/WX9Zf05/Tn9DP3d/Kv8QvwJ/JH7UfsO+376Mvoy+uL5Mvoy+n76DvuR+0L8DP2O/SP+g/7y/jj/d/+t/63/rf+K/zj/8v69/r3+vf7y/k7/rf8jAJ0AKAG7AXIC9AKJAzIErwQ4BYIFHgZxBsgGIweCB4IHggflB+UH5QflB+UHggcjB8gGcQbOBTgF8gSvBDIEMgT3A74DiQNVAyMD9AKbAiQCmwEOAWQAvv8K/0X+jv3d/EL8zvtR+w77yPp++jL6Mvri+eL54vni+eL54vni+eL5j/mP+Tj5OPmP+Y/5j/ni+eL54vni+Y/5j/mP+Y/5j/mP+eL5Mvp++g77kftC/Az9tv2D/jj/BgDIAH0BAAKbAscC9AIjAyMDIwMjA/QC9AL0AvQCIwMjA1UDiQP3AzIEbwSvBPIEOAU4BYIFggWCBYIFggWCBYIFggWCBYIFggU4BfIEbwQyBL4DIwObAt0BQwHIAHYAMgAjADIAUwB2ALIA3gAOASgBKAEOAfYAyACdAFMABgC+/3f/Iv/Y/qH+Zf5F/kX+Rf5l/qH+vf7y/vL+Cv8K//L+8v69/qH+g/5l/iP+AP7c/Y79Of3d/Hf8CfyR+w77fvoy+uL54vni+eL5MvrI+lH7Cfyr/GX9AP6D/gr/iv/6/zIAZABkAEIAFADd/77/rf+t/77/3f8GAFMAnQAOAZsBAAKbAvQCiQP3AzIErwTyBIIFzgXOBR4GHgYeBh4GcQZxBnEGcQYeBh4GzgU4BfIErwRvBDIE9wO+A4kDiQNVA1UDVQMjA/QCxwJyAgACXwHIAAYATv+D/rb9DP13/M77kfsO+8j6fvoy+jL6Mvoy+jL6Mvoy+uL5j/mP+Tj5OPnd+N34OPk4+Tj5j/mP+Y/5j/mP+Y/5j/mP+Y/54vky+n76DvvO+3f8Of0A/tj+nP92ACgB3QFyAvQCIwNVA1UDVQNVAyMDIwP0AvQCxwLHAvQC9AIjA1UDiQO+A/cDMgQyBG8EbwRvBG8ErwSvBK8ErwTyBPIE8gSvBK8EbwRvBDIEvgNVA8cCSgK7AV8BDgHIALIAnQCdALIAyADeAPYADgH2AN4AsgBkABQAvv9O//L+g/4j/rb9Zf0M/d38q/yr/Kv83fwM/Tn9Zf2O/Y79tv22/dz93P3c/dz93P22/Y79Zf05/Qz9q/xC/An8kfsO+8j6fvoy+uL54vky+n76DvuR+wn8q/w5/bb9Zf7Y/k7/iv+t/63/nP9j/zj/Cv/y/tj+2P4K/07/iv/6/3YADgGbASQCxwJVA/cDbwTyBIIFzgVxBsgGIwcjB4IHggflB+UHTQhNCE0I5QeCByMHyAZxBh4GzgWCBTgFOAXyBK8ErwRvBG8EMgT3A4kD9AJyAt0BKAFkAK3/Cv9F/rb9Of2r/EL8CfzO+5H7kfuR+5H7kfuR+5H7UftR+w77DvvI+sj6yPrI+n76fvp++n76fvp++jL6Mvri+eL54vni+eL5MvrI+g77kftC/N38jv1F/gr/zv+JACgBuwEkAnICmwLHAvQCIwMjAyMDIwMjAyMDVQOJA74D9wMyBG8E8gQ4BTgFggWCBYIFzgWCBc4FzgXOBc4FzgXOBc4FggWCBTgF8gSvBDIEvgNVA5sCJAKbAUMB3gCyALIAyADeAPYADgEoASgBKAEOAd4AnQBTABQAzv93/yL/2P6D/iP+AP4A/tz9AP4j/kX+Rf5l/mX+g/6D/oP+g/6D/oP+Zf5F/iP+AP7c/Y79Zf0M/Xf8CfyR+w77fvri+Y/5j/k4+Y/5j/ni+X76DvvO+3f8DP22/UX+vf4i/3f/iv+c/4r/d/9O/zj/Cv8K/wr/Cv84/4r/zv8yAJ0AKAGbASQCmwIjA4kD9wNvBPIEOAU4BYIFggXOBc4FHgYeBh4GHgYeBs4FggU4BfIErwRvBDIE9wP3A74DvgP3A/cD9wP3A/cDvgOJAyMDmwLdAUMBdgCt//L+I/5l/d38QvzO+1H7DvsO+8j6yPp++n76fvoy+jL64vni+Y/5j/k4+Tj5OPk4+Tj5OPnd+N343fjd+H74fvh++H74fvjd+Dj5j/ky+sj6kft3/I79Zf5j/zIA3gB9Ad0BAAJKAnICmwKbApsCcgJKAkoCJAJKAnICmwLHAscCxwL0AvQCIwNVA4kDvgO+A/cD9wP3A/cD9wP3A/cD9wP3A/cD9wO+A74DVQP0AnICAAJfAQ4BsgB2AEIAUwB2AMgADgFDAV8BXwFDASgBQwGbAXICiQM4BcgGTQgqCaAJKgnlB84FVQOJAGX94vnW9r/zMPG77yXuTO1964Ppduhc51znXOeD6X3r9O4w8d/xJvNR9Ef3zvt9AYIHIQ6DFD4c1yF/KFoqSSxaKn8oZSM+HH0W0A5NCAACd/xH94byTO126MLjp98p3qffFeED5YPpJe568N/xhvIm8+X1fvoyAIIHhg+KF1kguSZaKloqfyjXIcoZ2xG5CBQAfvjf8UztheqD6Xboduh26IPpfesl7t/xR/dC/F8BOAXlB7kITQjlB+UHKgkiC3oNRRCDFKQYjR1ZIFkg6x79GnsVhg8qCVUD3P04+WT1hvL07n3rXOfC46ffm9wp3hXhXOcl7mD2Of1KAjgFHgZxBh4GHgZxBiMHKgmvC4YPtBKDFIMU2xF6DcgG3f/d+Ibyaex26APlwuNz4nPiFeEV4XPiwuN26PTus/dfASILlxP9GuseWSDrHo0dPhz9GqQYiheKF4oXihd9FoMUhg+gCd0Bj/kw8YPpc+Kb3EfZgdeB10fZR9n62inec+J26HrwMvqCBQwRPhwGJVoqTy5PLmwwTy5PLk8uSSxJLFoqWip/KAYljR17Fa8LQgBR9HboKd6m1ZTPEsupyCbGJsapyBLLlM+m1ZvcNubf8dz9Kgm0EsoZjR1ZINchZSNlIwYlBiVlI2UjZSNZID4cihdFEOUH2P5k9WnswuOb3IHXptW307fTt9O306bVgdf62hXhXOd68H76vgMiC0UQlxODFHsVfRaKF6QYyhn9Gj4cjR2NHY0d/RqKF7QSQQw4Bdz9YPa7733rXOcD5XPiFeGn35vcm9yb3KffA+Vp7GD2rf+CB9oMRRDbEbQSlxODFH0Wihf9Go0d1yEGJbkmuSYGJdchPhx7FXoNOAVl/Uf3JvO77yXufeuD6VznNuYD5Tbmg+kl7mT1QvzdAfIEzgWCBTIEIwNyAkoCIwM4BU0IQQyGD9sRtBK0EkUQ2gzlB90BUftk9XrwTO2F6nboNubC4xXhKd4p3inep98D5X3rUfTO+0MBrwQeBsgGIweCB+UHoAlBDIYPlxOKF/0ajR2NHT4cpBiXE0EMOAWD/t343vTf8fTuTO2F6nboNuYD5QPlXOd964byDvv0AioJeg2GD0UQRRBFEEUQDBGXE4oXPhxZIGUjuSa5JgYl1yE+HJcTIgskAjL6v/Ml7oPpA+UV4Snem9xH2UfZ+tqn3zbm9O7W9jn9mwEyBPIE8gQyBIkDvgM4BeUHIgvQDtsRgxSDFIMU2xF6DSMHFAA4+b/zu+9p7IXqduh26FznNuYD5TbmXOd969/x4vlDASMHIgt6DSEO2gwiCyoJggdxBsgG5QcqCZwKIgucCioJzgWdADL6JvNp7FznwuMV4affp98V4XPiwuMD5VznfeuG8lH7OAXQDooXjR1lIwYluSYGJWUjWSDrHo0djR2NHY0dPhz9GqQYgxQhDs4FDP1R9GnsNuZz4qffm9yb3Jvcm9yb3Jvcp98D5UztR/dfAZwK2xGKF/0aPhw+HMoZpBh9Fn0WfRaKF6QYpBikGIoXexUMERsKAALi+Ybyaexc5wPlc+IV4RXhp98p3inep9/C44Pp3/Hi+d0BTQh6DUUQ2xHbEYYPIQ5BDK8LQQx6DdAORRDbEbQStBJFEK8LHgb6/zL6ZPXf8fTuTO1p7H3rheqD6Xboduh963rwR/e9/h4GQQwMEYMUexV7FZcTDBHQDnoNeg16DdAOhg9FEAwRRRDaDE0IAAIO+1H0Je526APlc+Jz4hXhFeGn36ffFeED5X3rhvIO+4kDIgsMEXsViheKF30WlxPbEUUQ0A7QDtAOhg9FEAwRRRB6DbkIxwJC/OX1u++F6jbmwuNz4nPiFeGn36ffp99z4lzn9O5g9r3+cQbaDNsRgxR9Fn0WexWDFIMUgxR7FX0WpBj9Gj4cPhzKGX0WDBGcCr4D3fxg9jDxTO1964PpXOcD5XPiFeFz4jbmaewm81H79AKgCdAOtBKDFIMUgxSXE5cTlxODFHsVihekGP0a/RqkGHsVhg8qCZsB4vkm80ztdugD5XPiFeEp3pvc+tqb3CnewuOF6t/xj/l2AM4FoAkiCyILnAobChsKGwqcCq8Leg1FENsRtBLbEYYPrwseBuz/OPkm8yXug+lc5wPlwuMV4affKd6n33PiNuZM7d703fyvBCILhg/bEZcTlxOXE5cTlxODFHsVihfKGT4cjR0+HMoZexVFECoJmwEy+r/z9O5963boA+Vz4qffKd6b3KffwuOD6TDxj/lKAqAJhg+XE30WihekGKQYpBikGMoZ/Ro+HOse6x6NHf0afRZFECoJ9gDd+DDxfetc58Ljp9+b3EfZgdem1YHX+toV4XboMPHi+QACuQh6DUUQtBKXE5cTgxSDFHsVihfKGf0ajR2NHf0apBiXE9oM8gQ5/WD2evBp7HboA+Vz4ine+tr62vraKd5z4oPpMPGP+ZsBTQjaDEUQtBKDFHsVexV9FooXyhk+HOseWSDXIVkgjR3KGZcTrwuJAwn85fUw8Uztg+k25nPip9+n36ffc+I25kztZPXc/R4Geg20En0WpBj9Gv0a/Rr9Gv0a/Ro+HI0djR0+HMoZexVFELkIMgBH9/TudujC46ff+tqB17fTsdGUz5TPsdGB15vcA+X07rP3iv/OBRsKeg1FEAwR2xG0ErQSgxR9FooXyhnKGcoZiheDFCEOIwec/374hvJM7YPpNuZz4ine+tpH2YHXR9mb3BXhdugw8Y/5uwG5CCEOtBJ7FYoXyhnKGf0aPhzrHlkgZSMGJQYlZSNZIP0agxR6Dc4FIv/i+WT1MPFM7XboA+UV4affp98V4Tbmaey/80L8vgMbCtAOtBJ7FX0WiheKF4oXihekGP0aPhw+HD4c/RqKF9sRIgsjA1H7UfT07oXqNuZz4qff+tpH2YHXgddH2SnewuNp7FH0zvtKAoIHIgshDoYPhg+GD4YPRRAMEbQSgxR7FXsVgxS0EiEO5QfIAI/5JvMl7oXqXOfC46ffm9xH2YHXptWB10fZp9825vTu1vYj/m8EoAkhDkUQ2xGXE4MUexWKF8oZPhyNHese6x7rHv0aexUhDsgGMgDI+mD23/El7oPpNuZz4qffp9+n33PiXOdM7WT1Of2vBCILDBF7FYoXyhnKGf0a/Ro+HI0d6x5ZIFkgWSDrHsoZgxTaDK8EOf1H99/xTO2D6QPlFeEp3vraR9mB10fZKd7C44Xq3/F++L3+MgRNCCILQQx6DSEO0A5FENsRtBKDFH0WfRZ9FpcT0A65CJsBUfvl9d/xJe6F6lznwuMV4Snem9yb3CneFeFc5yXuZPUM/TIEnAqGD5cTexWKF6QYyhn9Go0d6x5ZINchZSNlI1kgPhx7FSEOggcoAQn8R/eG8iXug+kD5RXhKd6b3Jvcp9/C44XqMPHd+M7/HgavC4YP2xGXE4MUexV7FX0WihfKGf0a/Rr9GsoZgxTQDoIHyAB++mT1evBp7HbowuOn35vcR9mB14HX+top3gPlfeuG8o/57P84BSoJrwt6DdAOhg9FEAwRtBKDFH0WihekGIoXgxRFEBsKbwRO/8j61vYm87vvaeyD6QPlc+Kn3ynep9/C43boJe5R9FH7fQHIBpwKeg2GDwwR2xGXE4MUfRakGP0ajR3rHusePhyKF7QS2gyCB/QCvf7I+kf3v/O7733rXOfC43PiwuMD5YPp9O5k9UL8xwK5CHoNDBG0EoMUexV9Fn0WihekGMoZ/Ro+HP0apBiXE9oMcQbd/zL63vR68GnsdujC46ff+tqB16bVptWB1/raFeFc5/Tu5fVC/CgB8gSCByoJnAqvC0EM2gzQDgwRlxN7FXsVgxQMEdoMggebAtz94vnl9Ybyu+9961znc+Kn35vcm9wp3hXhNuZ964byj/lCAB4GnAohDgwRtBKDFH0WpBjKGY0dWSDXIWUj1yFZIP0aexVFECILHga7Adz94vlk9Xrwfes25sLjc+Jz4gPlduhM7b/zfvreAB4GnAp6DUUQ2xGXE4MUexV9FooXyhk+HD4c/RqKF5cTeg3lB0oCOf3d+N70MPFM7XboA+UV4Snem9yb3Kffc+J26PTu5fWr/EoCyAacCnoNhg8MEdsRtBK0EoMUfRaKF6QYiheDFEUQIgvOBYkAzvuz91H0evBp7HbowuOn35vcR9lH2UfZm9wV4Vzn9O5k9ZH7yAA4BaAJ2gyGD9sRlxN7FYoX/RqNHeseWSDrHj4cihe0EiEOKgk4BZsBAP7i+eX1MPFM7YPpNuYD5Tbmduhp7N/x3fiK/84FIguGD5cTihfKGf0aPhw+HI0dWSDXIdch1yFZID4cfRYMESILOAVkAEL8fvhR9Lvvfes25nPip98p3pvcp99z4lznTO0m8xv43fwOAW8EggcqCRsKGwqcCq8Leg2GDwwRDBFFECEOnAoeBkMBq/w4+WD2v/Mw8SXuheo25nPip98p3inep9/C43boJe5R9Mj6ZACCBRsKIQ4MEbQSlxOXE3sVihfKGf0aPhz9GqQYexUMESILzgVfAbb9fvrW9obyJe6D6QPlc+Kn3ynep99z4jbmaewm8zj5OP+vBBsKIQ4MEbQSlxODFHsVihekGMoZ/Rr9GqQYexVFEBsKrwT6/wn8fvje9Hrwaexc58Ljp98p3pvcm9yn38Ljg+l68GD2q/xyAuUHQQyGD9sRtBKXE4MUfRakGMoZ/Ro+HP0aiheXE9AOnApxBvQCBgDd/N343vS7733rXOfC4xXhFeEV4cLjduhM7SbzG/hl/UoCcQYbCkEMeg0hDoYP2xGDFH0WpBjKGcoZpBiDFAwR2gy5CDgFSgLy/lH71vaG8iXug+k25sLjc+Jz4jbmheq772T1DvsOAcgGrwuGD9sRlxOXE4MUfRaKF6QYyhn9GsoZiheXEyEOKglvBGQAq/w4+d70evB961znc+Kn35vc+tr62ineFeE25n3rMPFH9wz9JAIeBrkIGwqcCq8L2gzQDgwRtBKDFIMUlxMMEXoNoAkeBiMDUwBl/TL6YPaG8iXuheo25sLjc+Jz4sLjXOd96zDx1vbd/CMDuQh6DUUQtBKDFHsVihfKGT4c6x5ZINchWSCNHf0afRa0EtAOIguCB4kD8v4y+t70u++F6jbmwuNz4nPiA+V26Gns3/FH92X9xwIjBxsKQQx6DSEOhg8MEbQSexV9FooXfRaDFAwR2gy5CPIEfQEj/sj61vYm8/Tuheo25nPip98p3qffFeED5YPpJe5R9Mj6iQA4BU0InAqvC0EM2gwhDkUQ2xGXE4MUgxS0EoYPrwtNCPIEAAIi/wn83fje9Hrwaexc58LjFeGn36ffFeFz4jbmfesw8Uf3Of0kAs4FTQgbCiIL2gzQDgwRgxR9FqQYyhmkGH0WlxOGD0EMKgnOBUoCg/4y+uX1MPFp7FznwuMV4RXhc+LC41znaeyG8o/5zv84BaAJ2gzQDkUQ2xGXE3sVihfKGf0a/RrKGYoXlxOGD68L5QcyBHYAd/x++L/z9O6D6QPlp98p3pvcm9wp3hXhA+WF6rvv5fV++oP+KAH0AjIE8gQeBuUHGwpBDNAOhg+GDyEOrwsqCXEGvgMoAYP+Cfw4+eX13/FM7YPpA+Vz4hXhFeFz4gPldugl7lH0Mvq+/zIE5QecCkEMeg2GDwwRgxSKF8oZ/Rr9GsoZihd7FdsR0A6vC7kIggUAAiP+j/lR9PTuhepc5wPlA+UD5Vznfet68GD2QvzdAcgGnAraDCEOhg9FENsRlxN9FqQYyhmkGIoXgxTbESEOGwrIBiMD3f+r/Dj5ZPV68H3rXOfC43PiFeEV4cLjXOdp7N/xG/jc/ccCcQa5CJwKIguvC9oM0A4MEbQSgxSDFJcTDBHQDq8LuQjOBfQCZAAA/g77R/eG8iXug+kD5XPiFeEV4RXhwuNc52ns3/Gz90L8MgD0AvIEHgaCByoJrwvQDtsRlxODFIMUlxPbEYYPQQygCcgGMgQAAjj/kftH94byTO2F6lznNuYD5TbmduhM7Sbzj/nd/4IFGwp6DUUQDBG0EpcTexWKF8oZ/Rr9GsoZiheDFAwR2gy5CPIE3QHy/pH7R/eG8kztdugD5XPip9+n36ffc+I25n3r3/Eb+Nz9cgLOBeUHKgkbCiIL2gzQDgwRtBKXE5cTtBIMESEOIgvlB/IEmwIyAI79Mvrl9TDxTO2D6TbmwuNz4nPiwuNc52nshvJ++IP+vgPlByIL2gzQDgwRlxN9FsoZPhyNHY0dPhz9GooXgxQMEXoNnAqCB28EdgCR+2D23/FM7YPpNubC43PiwuM25oXqevBg9kL8mwHOBSoJIgvaDCEORRC0EoMUihekGKQYihd7FZcThg+vC00IOAVyAor/zvuz9ybz9O6F6lznwuNz4hXhc+ID5YPpu+9k9VH7yAA4BU0IGwqvC0EMeg2GD9sRlxODFIMUlxPbEYYPQQwqCR4G9wPdAZz/q/zd+N70evBp7IPpNubC43Pic+ID5XboTO0m8zj5Iv/3A+UHGwqvC3oNhg/bEYMUihekGMoZ/RrKGYoXexXbEdAO2gwbCoIH9wPs/5H71vaG8iXuhepc5zbmNuZ26H3ru+/l9UL8mwLlB0EM0A4MEbQSgxSKF8oZPhyNHese6x6NHf0aiheXE4YPQQygCR4GcgIj/jj5UfS774XqXOfC4xXhFeFz4gPlduhM7Sbz3fjc/ZsB9wM4BXEG5QcbCkEMIQ5FENsRtBLbEUUQIQ4iCyoJyAbyBCMDnQBl/Y/5ZPUw8Uztg+k25sLjc+LC4wPlg+kl7r/z4vlj//cDIwcqCa8LIQ4MEZcTfRbKGf0aPhw+HP0apBh9FpcTDBHQDkEMKgk4BbIAzvvW9t/xTO2D6VznA+UD5Vznher07t70DvvIAIIFuQgiC9oM0A7bEYMUfRakGMoZ/Rr9GsoZiheXE0UQeg0iC+UHbwRTAM77R/eG8kztg+kD5XPiFeEV4RXhA+V26CXuUfTi+WX+fQGJAzgFIwegCa8LIQ5FENsRlxOXE7QSDBEhDq8LoAmCBzgFxwKc/877s/cm8/Tuheo25nPiFeGn36ffFeED5YPp9O5R9N34Cfy9/igBiQMeBioJQQyGD9sRgxR9Fn0WexWXE9sRhg8hDkEMoAlxBvQC8v5++uX1MPFp7IPpNuYD5QPlXOeF6rvv5fXO+ygBOAVNCCILIQ5FELQSexWkGP0aPhw+HD4cyhmKF4MU2xHQDq8LTQhvBBQAUftg9jDxaex26MLjFeGn36ffFeHC43boTO0m8xv4zvuh/igBiQOCBeUHGwpBDNAODBHbEdsRDBHQDtoMIgsqCSMHrwS7AYP+yPrW9obyTO126APlc+Kn3ynep98V4QPlhep68GT1j/kM/VMAVQNxBqAJ2gwMEYMUihekGMoZyhmkGIoXexWXE9sR0A6vC7kIrwQUAMj6ZPV68Gnsdug25gPlA+U25oPpJe6/8934Of3eADIEIwegCUEM0A7bEYMUihekGMoZpBiKF30WgxTbEYYPQQwqCc4FAAKO/d34v/P07oXqXOcD5cLjwuMD5XboTO3f8db2DvtF/igBiQOCBYIHoAmvCyEORRDbEdsR2xFFENAO2gwiC7kIyAYyBF8BI/4y+uX1MPFM7XboA+Vz4hXhp98V4cLjduhM7d/xYPZ++iP+DgG+A3EGoAnaDEUQlxN7FYoXpBiKF4oXfRaDFLQSRRAhDiILggeJA73+4vne9Hrwfet26DbmwuMD5Vznfeu779704vkj/gACggW5CK8L0A7bEXsVihfKGf0a/Rr9GqQYihd7FbQSRRDaDKAJggUOAUL8R/ff8Uztg+k25nPiFeEV4XPiNuaF6vTuJvPW9jL6q/zy/vYA9AI4BeUHnAraDCEO0A7QDiEO2gyvC5wKuQgjB/IEmwKc/wn8s/e/87vvaex26DbmwuPC4zbmduhp7DDxZPXi+dz9XwFvBCMHGwp6DQwRgxSKF6QYyhnKGcoZpBiKF3sVlxMMESEOIgsjB5sCtv3d+FH0u+9963boA+UD5QPlXOd967vv3vSP+bb9fQGvBIIHGwraDEUQlxN9FqQYyhnKGaQYihd7FZcTDBEhDq8L5Qf3A2P/fvpk9TDxaex26APlc+IV4XPiA+Vc533revDe9Dj5q/x3/90BbwQjBxsK2gyGD9sRtBK0ErQS2xFFENAOeg2vC6AJIwf3AzIACfwb+L/zu+9961znA+Vz4nPiwuM25oXqJe6G8tb2fvpl/QYAxwLOBSoJ2gxFELQSgxR7FX0WfRZ7FYMUlxPbEUUQeg2cCsgGmwJF/uL5ZPUw8Uztg+l26Fzng+lp7LvvUfQ4+bb9uwE4BeUHnAp6DQwRlxN9FqQYyhnKGcoZpBiKF3sVtBJFEHoNGwoeBrsBDP1++L/zu+9961znwuMV4affFeHC4zbmher07ibzYPY4+ZH7jv3s/5sCggVNCJwKQQzaDHoNeg3aDK8LnAoqCeUHHgaJA0IA3fw4+eX13/El7oPpNubC43Pic+ID5Vznfeu777/zs/cO+wD+9gAyBOUHrwuGD7QSexWKF6QYpBikGIoXihd9FnsVtBJFEEEMuQivBJ0AQvyz9ybz9O5964Ppg+mF6mnsu++/87P3Ufuh/kMBvgNxBioJQQyGD7QSgxR9Fn0WfRZ9FnsVlxPbEUUQIQ4iC4IHvgPs/wn8G/i/8/Tufet26DbmNuY25nbofeu777/zR/cy+t38Cv9fAfcDyAagCUEMIQ6GD4YPhg+GDyEO2gxBDJwKuQgeBvQCvv93/Dj5ZPUw8WnsdugD5XPiFeEV4cLjNuaD6UztMPHe9LP3fvoM/SMAvgOCB5wKeg1FELQSlxOXE5cTlxO0EtsRRRB6DZwKIwf3A0IAQvyz94byJe6F6lznNuY25lzng+kl7t/xYPYy+rb93gAyBOUHrwuGD5cTfRbKGT4cPhw+HD4cPhz9GqQYfRaXE0UQQQxNCG8EFAAO+2D2MPFM7YPpXOdc51zng+lp7Hrwv/PW9jj5kfu2/TIA9AKCBU0IIgt6DdAOhg9FEEUQhg/QDiEO2gycCk0IggX0AgYAd/x++FH0u+9p7HboNuYD5TbmXOeF6iXu3/Fk9X74Dvu2/cgAMgSCByILIQ4MEZcTexV7FX0WexV7FYMUtBJFEHoNGwrIBvQCCv9++uX1MPFp7IPpNuYD5QPlXOeF6iXu3/Hl9d34zvu9/rsB8gTlByIL0A7bEZcTexV7FXsVexWDFJcT2xHQDq8LuQg4BbsBAP7i+WT1evBp7HboNuYD5QPlNuaD6WnsevBR9Ef34vmr/E7/AALyBOUHnAp6DUUQ2xHbEbQStBK0EtsRDBHQDtoMnApNCIIFmwI4/1H7R/cm8/TufeuD6Xbog+l96/Tu3/Fk9Rv4yPo5/Zz/JAKvBIIHnAohDgwRtBKXE4MUgxR7FYMUlxPbEYYPeg2cCuUHrwQOAd38fvhR9HrwaeyF6oPpg+l96/TuhvJg9uL5Of1kACMDzgW5CEEMhg+0EoMUfRZ9FooXfRZ9FnsVlxNFEHoNnAqCBzIEnQCr/H74UfS7733rdugD5QPlA+U25oPpTO0w8VH0R/fi+Qn8I/52ACMDHga5CCILQQx6DXoNIQ56DXoNQQycCrkIcQZvBAACd/93/N34ZPUw8Uztg+lc5wPlA+U25oPpaey777/z1vbi+Xf8Tv9yAh4GoAl6DQwRtBKDFH0WiheKF4oXfRZ7FZcTDBHQDq8LuQg4BV8BOf3d+N70evBM7YXqhep960ztevC/89b2MvoM/Yr/AAKvBIIHIgshDgwRtBKDFIMUexV7FYMUlxMMEdAOQQygCcgGiQPs/wn8G/hR9Lvvaex26DbmNuZc53bofev07oby5fV++A77Of2K/0oCggW5CCILeg3QDoYPRRBFEEUQhg8hDq8LGwqCBzgFmwKt/3f83fhk9TDxTO2D6VznA+U25lzng+lp7LvvJvPl9Rv4Mvqr/K3/IwPIBhsK2gzQDgwRtBKXE4MUgxSXE9sRRRAhDkEMKgkeBvQCTv+R+0f3hvL07n3rheqD6X3rTO168Cbz1vbi+UL8of5fAW8ETQivC4YP2xGDFH0WihekGKQYihd9FoMU2xHQDkEMKgnOBUoCvf7I+tb2hvIl7oXqg+l26IPpfesl7nrwv/Pl9bP3OPnI+qv8Iv+7ATIEcQblByoJnAoiC68LIgucCioJ5QdxBq8ExwLeAKH+Qvw4+eX13/El7oXqduh26Hbohepp7LvvhvJk9Uf3OPlR+wD+KAGvBOUHIgt6DYYPDBG0EoMUgxSDFJcT2xFFECEOrwu5CB4GIwOK/1H7YPbf8SXufeuF6oXqfetM7Xrwv/PW9jj5Ufu2/WQAiQPIBhsK2gyGDwwRtBKDFHsVexWDFJcT2xGGD3oNIgtNCIIFSgKh/n76YPbf8SXufeuD6Xbog+l960ztevAm82T1R/fd+FH73P2JAIkDcQagCXoN2xF7FaQYyhmkGIoXexW0EiEOnApxBpsBDP3d+L/zTO025qffR9mm1abVgdf62qffA+V26IPpg+kl7mD22P5xBtAOiheNHVkg1yFlI9ch1yHXIVkg/RqXExsKfQF++DDxaeyF6oPpg+l26FznA+Vz4sLjhepR9I79HgbQDooXPhyNHVkg1yEGJX8oWip/KNch/RoMEfcDs/f07nbowuMV4RXhc+LC4wPlXOf07jj5QwFxBiILDBGDFHsVgxS0EgwRRRAhDhsKMgRF/kf3Je4D5Sne+tpH2UfZ+tqn38LjXOeD6bvvUfvIBkUQyhllI0ksbDChMk8ufyhlI/0aRRBvBH76u+8D5UfZsdESy6nIJsapyJTPptWb3HPiheqz9x4GtBLrHloq7jR6PBVCFUI4P3o8VzdsMH8o1yGkGEEMAP707hXhgdeUzxLLEsuUz7fTgdeb3DbmMPFC/CMHtBI+HAYlWipPLkksWip/KAYlWSA+HKQYlxOvC5sBs/f07lznFeEp3qffp9+b3EfZR9kp3sLjaexg9p0AnAqXE8oZ/Rr9GqQYgxQMESEO2gyvC6AJggUoATn93fje9Cbz3vSz99b2UfQm81H0s/cJ/GQAvgOCB68L2gyvCyoJzgXdAWX94vlH92T13/Fp7Fznc+Ip3vraR9kp3gPlfev07oby1var/PcDIgsMEaQYWSC5JloqSSxaKrkm6x59FnoNcQbY/mD2TO025hXh+tqB14HXm9xz4lznfeu77+X1of6CB0UQyhkGJU8u7jTaOXo82jnuNE8ufyjXIY0diheGD8gG3fx68HPiR9m307HRlM+Uz5TPsdGB1yneA+VM7X74vgMhDn0WPhzXIWUj1yHrHo0d/RqkGLQSeg3IBtz9hvKD6QPlc+LC43Pip9+b3JvcKd6n33Pidugw8cj6iQOcCoYPtBK0EgwRhg/QDiEOQQwiC5wKgge7Ac77G/hH9zL63fzd/M77Qvwj/t4AiQNxBpwKhg+XE3sVexWXE0UQIgtxBm8EvgNKAkMB9gCh/o/5hvJp7Hboheol7nrwJvPW9pH7KAFxBq8LDBGKF40d1yEGJbkmuSbXIT4cihfbEZwKvgOO/Uf3u+825pvcptW306bVgddH2frap98D5X3rhvIO+84FDBH9GgYlSSyhMqEybDBPLloqZSPrHsoZgxTQDoIFfviF6hXhR9m305TPEssSy1/NlM+m1frawuNM7db2zv8qCQwRexV9FooXpBiKF3sVlxO0ErQShg/lB7b9ZPV68CXuTO1p7H3raexp7EztTO0l7t/x1vZ3/DIE2gy0En0WihekGKQYfRaDFLQStBK0EoYPTQiJAA773fg4+eL5Mvp++s77Of0A/jIA8gScCoYPexU+HOse6x4+HIoX2xF6DU0IbwTHAkoCzv84+bvvXOdz4qffp9+n33PiNuaF6iXuJvPI+scCGwq0Ev0aZSO5Jn8ofygGJdch/RqDFCEOuQibAjj5aeyn36bVlM9fzRLLEstfzZTPsdGm1frac+KF6mT1KAF6DcoZ1yF/KEksSSxJLH8oZSPXIVkgPhyDFCoJI/5k9SXuXOcV4Zvc+tqB14HX+top3nPiduh68OL59wNBDLQSihf9Gj4c/RqkGIoXyhnKGYoXDBHlByMADvtg9obyevB68Lvvu++77zDxMPHf8SbzR/e2/a8EnAqGD5cTexWDFAwR0A7QDkUQDBF6DcgGUwAJ/H745fVk9db2s/d++OL5kfu2/d3/SgJxBtoMlxOkGP0a/RqkGJcTQQwyBHf/3P22/VH73vRM7Vznc+Ip3pvcm9wp3hXhwuNc52ns3/FH97b9zgWGD4oX6x4GJX8oWiq5JtchPhykGIoXtBK5CN38MPE25pvcptWx0bHRlM+x0bfTptVH2SnewuN962D2SgJ6DYoX1yFaKk8uTy5JLEksSSxJLH8o1yHKGQwRIweh/kf3MPF96wPlp9+b3PraR9lH2Zvcc+KF6ibzkfv3A68L2xGDFIMUgxSKFz4cjR0+HMoZgxQhDsgGUwDO+xv4UfQw8SXuTO1964PpXOdc53bofeu77970kfvdAc4FzgWvBB4GKgmvC0EMIgu5CPIEvv9R+9343fg4+Y/5yPp3/Nz9tv05/WX+DgGvBCoJIQ60EqQY/RqKFwwRrwu5CCMHOAVKAoP+j/km82nsXOfC43PiFeEV4XPiNuZ26H3r9O7e9EL8bwRBDIMUjR0GJX8ouSZlI9chWSDrHo0dpBgMEXEGyPq77zbmp99H2abVt9O306bVptWB1/raFeF26DDxfvrOBdsRPhxZIGUjBiW5Jn8oWip/KLkmWSCkGIYP5QcoAX76v/NM7XbowuOn35vcR9n62inec+J26HrwDvuvBJwKIQ5FELQSgxSKF8oZPhw+HKQYlxMhDrkI9wMK/w77G/hg9t70hvJ68LvvevAw8XrwhvJH9yP+VQPOBcgGggdNCKAJrwt6DSEOQQzlB5sCAP7i+eX1v/Mm87/z5fVg9tb2G/gO+9z9iv+7ASMH0A59Fv0aPhzKGX0W2xHQDq8LKgmCBa3/OPkm80ztXOdz4qffKd6n36ffp98V4QPlher07lH0kfseBgwRyhnrHtch1yFZIFkg6x7rHo0dpBgMESMHq/yG8nbop9/62oHXptW307fTptWB1/rap98D5SXu4vkeBgwRpBiNHdchBiV/KEksTy5PLloqBiWNHXsVeg04BYP+j/ne9PTudujC4xXhp98p3ineFeGD6YbyQvy+AyoJQQwhDgwRgxSkGP0aPhz9GooXgxSGD6AJbwRDATj/d/zd+GD25fXl9WT1v/OG8lH0fvi2/d0BrwQ4BW8EiQMyBB4GuQigCU0IggVyAmX+OPlR9DDxevAw8XrwevCG8mT1G/g4+eL5Cfz2AIIH0A57FaQYyhmKF4MUtBJFECEOoAm+A7b9s/d68Hboc+Ip3pvc+tpH2UfZm9wV4cLjNuaF6t/xUftxBtsRPhzXIQYlBiW5Jrkmfyh/KLkm1yH9GrQS5Qd3/IbyfevC4yne+tpH2UfZ+tr62vrap9825rvvyPrOBdAOexXKGT4cWSC5JloqSSxJLFoquSZZIIoXRRAbCvcDtv2z94by9O6F6jbmFeEp3inec+J26DDxOPk4/3ICbwQjB5wKIQ5FEAwR2xHbEdAOoAlvBLIAI/5R+xv4ZPVR9L/zJvMw8bvv9O4w8WT1yPpkADIEOAW+A3ICmwL3A68EbwQyBL4DuwE5/Rv4v/N68CXuaeyF6mns9O6G8mT1R/eP+av8XwHlB0UQiheNHese6x6NHY0dPhzKGX0W2xHaDB4GZf3e9CXudujC46ffKd4p3hXhc+ID5Tbmg+n07uX1QgCvC30WjR3XIQYlfyhaKloqfyh/KH8oZSONHZcTnAqbARv4Je425hXhKd6b3PraR9lH2UfZm9zC40ztG/iyAB4GnAqGD5cTfRbKGY0dWSBlI9chjR2KF7QS2gxxBnYAzvt++GD2JvO774XqNuZz4nPiNuZp7Iby1vaP+Xf8OP+bAYkDzgUqCUEM2gwiC+UHOAX0AnYAI/6r/EL8q/zd/Hf8kfvi+X74s/fi+b3+9wPIBiMHHgbyBIkDuwF2AJ0A3QHdAez/q/yP+db2v/N68CXuTO307jDxv/Ng9o/5CfxF/t0BTQiGD30W/RqNHeseWSDrHj4c/RrKGX0W2xEbCiQCyPq/80ztNuYV4Snem9yb3Cnep98V4XPiA+WF6obyd/yCBXoNgxTKGY0d6x7XIWUjBiUGJWUj6x6kGLQSrwtVAzL63/F96wPlFeEp3pvcR9mm1abV+tpz4oXqMPEb+KH+9wOCByILhg97Ff0a6x7rHusejR3KGXsVRRAiC8gGxwKt/479UftH9zDxfet26IPpaez07oby5fU4+Q77d/yD/psCggecCtoM2gxBDK8LKgkeBvcDmwJfAbIAQwFKAiQCzv9C/OL5DvuD/koCggXlB6AJuQgeBlUDmwIjA/cDiQMAAuz/AP5R+0f3JvO770ztfet960zt9O568HrwMPFR9OL5nQAjB3oNtBJ9FooXiheKF6QYyhnKGX0W2xHaDHEGCv9H97vvduhz4inem9yb3Cnem9z62pvcp9825kztZPVF/iMHIQ6XE4oXPhzXIbkmfyh/KH8ouSbXIY0dihdFEIIHIv8b+Cbzu++F6sLjp9+b3CneFeE25mnsJvM4+bb9KAHyBBsKRRB7FcoZjR1ZINch1yHrHj4cihe0EiEOrwucCrkIMgSh/uL5YPZR9CbzUfRg9n74OPnd+N34fvrc/cgAIwM4BcgGggdxBq8EcgLO/3f8j/k4+Q77DP1l/ZH7j/nd+N34fvoA/nICIwcbChsK5QdxBh4GggWvBFUDAAIyAAD+Dvsb+FH0u+9963boduiF6n3raexp7CXuMPHl9UL89wNBDIMUpBj9Go0d6x7XIWUjBiUGJWUj6x6kGNsRnArdARv49O6D6VznNuYD5XPiFeEV4XPiA+WD6XrwfvhO/68EoAnQDoMUyhnrHmUjuSa5JrkmZSPXIT4cfRZ6Dc4F+v9R+2D2evCF6gPlp98p3pvcp98D5YPpJe4w8b/zs/fO+93/9wNNCEEM0A4MEbQSlxPbEXoNKgnOBTIEIwPdAWP/d/yP+WD2JvPf8Ybyv/NR9L/zhvKG8ibzUfTl9bP3j/nI+s77d/zd/FH7s/e/8zDxMPG/89b23fgy+lH7UftR+wn8Tv8yBCoJQQx6DSEOeg3aDEEMIgugCYIHrwQkAlMAAP6P+SbzTO2F6oPphep9633raexp7Eztu+9R9An8bwRBDLQSfRb9Go0d6x7XIQYlBiUGJdch6x79GnsVQQzdARv4MPFp7IPpNubC4xXhKd6b3Jvcp98D5YXqu+9k9X767P/yBJwKRRB9FsoZ/RqNHY0djR39GnsVhg8bCh4GcgJl/uL53vT07lznc+Ip3ineFeFz4gPlduh96yXuMPFk9eL5jv1TAFUDIwevCyEOIQ5BDJwKGwqgCSoJuQi5CIIHOAXdAfL+jv1l/dz9jv3d/EL8Dvsy+n76CfyO/SP+g/6+/yQC9wP0Apz/zvuP+X743fji+UL8g/6+/77/OP+K/30BrwTlB68L0A4MEdsR2xHbEQwRhg+vC00IHgZvBLsBq/zl9bvvfeuD6VznXOdc51znNuYD5QPlXOdp7Ibyj/koAYIHQQxFEJcTihf9Go0djR2NHesejR3KGZcTnAoAAo/53/Fp7HboA+UV4ZvcR9mB10fZ+tqn3wPlher07lH0j/kGACMH2gzbEX0W/RpZINchWSCNHcoZexUMEXoNGwrIBscCq/xk9fTuhepc5zbmXOeD6WnsJe4w8WT1Mvpl/kMBiQPIBiILhg/bEbQS2xHbEUUQhg/QDtAOhg8hDkEMKgnIBvIEMgRvBPIE8gSJA30BUwB2AA4BnQA4/6H+3f+bAXIC3QGc/0L83fhk9YbyhvK/82T15fXl9eX15fXW9jj5Of19AYIFTQgiCyEODBG0EgwRhg96Da8LoAnIBiQCd/xg9nrwhepc5zbmNuYD5cLjc+IV4RXhwuOD6bvvR/eD/vIErwu0EsoZjR1ZIGUjBiV/KH8ofygGJesefRbaDG8Etv1++L/zJe6D6cLjp98p3ineFeED5YPpTO3f8Rv4vf6vBKAJ0A6DFP0aWSBlIwYlBiVlI+se/RqKF3sVtBLQDioJxwJR+1H09O5964XqheqD6YXqaey777/zYPYb+DL6Zf0oATIEyAa5CLkI5QceBoIFHgbIBiMHyAaCBVUD3gDY/oP+IwBKAvQCcgK7AbsBAAK7AUIAvf5F/qH+OP/6/2QAnP8M/Tj5ZPUm84byhvIm8ybzv/NR9N705fU4+QD+SgLOBSoJeg3bEX0WpBjKGcoZyhmkGH0WgxQMEa8LrwQM/WD2MPEl7mnshep26DbmwuMV4XPiNuaF6vTuv/N++iQCGwpFEIMUpBg+HFkgZSO5Jn8ouSZlI40dfRbQDiMHnQB++t709O526HPiKd6b3JvcKd6n33PiNuZ963rw3vR++N383QEjB9oM2xF9FooXfRaDFAwRIQ5BDJwKKgkjByMDDP1g9jDxJe5963boNuY25lznduiF6n3rTO307nrwJvPW9n763fy2/d38zvuR+0L8jv2t/90BxwLdARQA8v6c/30BIwP3A68EHgaCB+UHIwceBq8EIwPdAZsBcgJVA/QCUwB3/N345fW/8ybzv/NR9L/zhvKG8r/zYPbi+av8nP+JA00I2gwMEYMUfRakGKQYpBiKF4oXexUMESIL9wMM/db2hvK77yXuaex26APlwuNz4sLjA+Vc54Xqu+9g9mX9vgOgCSEOtBJ9FsoZ6x7XIQYlZSPXIY0dihfbEUEM5QdVAzn95fX07oPpNuZz4hXhp98V4cLjXOd967vvJvPW9uL5AP73A5wKRRCXE3sVexWXEwwRhg+GD0UQRRAhDhsKzgVyAiL/kfsb+GT1v/O/81H0ZPVg9rP3G/h++Mj6vf5yAq8EOAVvBPQCKAEUAN4AVQPOBSMHcQaCBYIFHgZxBiMHuQicCtoM0A5FENsR2xFFECEOQQxBDEEMQQwiC7kI8gRCAFH7R/dk9d70v/Mw8fTuTO0l7vTuevDf8d70OPnc/ccCTQh6DdsRgxR9FqQY/RqNHY0d/RqKF9sRoAmbAQ771va/8/Tug+kD5XPip98p3ineKd6n38Ljduj07tb2I/73AyoJ0A6DFP0aWSAGJbkmfygGJdchPhykGHsVDBEiC74Dd/zl9Xrwheo25gPlwuPC4zbmheol7t/xUfTW9g77UwBxBtoM2xF9FooXfRZ7FYMUgxR7FYMUlxMMEdAOrwsjByMDnP93/I/5s/dH97P3s/dH99b2YPaz9+L5q/xj/0MBQwGh/g77fvh++OL5yPoO+8j6yPrI+n76MvrI+kL8I/6yADIETQivC3oNIQ7aDEEMrwsiCyILIgsbCnEGdgB++mD2UfQm83rwTO1964Ppduhc51znduh96/TuUfQy+rIAcQavC4YPlxN9FsoZjR1ZINchWSD9GpcTrwuCBWQAUftk9Xrwfes25nPiKd6b3Pra+tqb3BXhNuZp7Ibys/cM/fQCKgnQDnsVPhzXIWUj1yHrHo0d/RqkGIMURRAiC68Etv3W9nrwfes25nPiFeFz4sLjXOeD6X3rTO277ybzs/cj/jIEuQgbCqAJKgmgCRsKGwobChsKoAnlBx4G9wObAfL+Cfzi+X74fvh++Bv4R/dg9mT13vTe9Ef3fvq2/SP+Cfw4+Uf3YPbl9eX1YPaz9374fvjd+Dj54vl++pH7Rf7HAoIHrwvQDgwR2xHbEQwRRRAMEbQS2xHQDioJ9wOc/877fvhg9lH0hvK770ztaex9633rfetM7TDxR/fd/EoCIwevC4YPtBJ9Fv0aWSBlIwYl1yGNHYoX2xFBDCMHJAIM/Uf3MPFp7HboNuZz4qffp98V4QPlduhp7DDx5fUy+oP+vgMiC9sRihfKGf0a/RrKGaQYihd9FoMU2xHaDCMHfQEJ/OX1u++F6lznNuY25jbmduiD6X3rfetM7TDx1vZ3/DIAmwIyBDgFHgYjB7kIGwoiCyILIgsiC5wKoAkjBzgFMgS+A1UDIwNVA4kDIwP2AEX+Of3y/rsBiQMyBIkDmwFj/479d/wJ/An8kfsO+5H7q/yO/WX9Of0j/mQAvgOCB68LRRCDFH0WfRZ9FooXyhn9Gv0ayhl7FUUQnAqCBbsBof4O+9b2v/Mw8fTuaeyD6VznXOd26H3r9O5R9I/5I/6dAMcCcQavC9sRfRbKGf0ayhl9FrQSIQ6cCh4GdgB++t70u++F6gPlFeEp3vra+tqb3Cnec+Jc54Ppfev07t70Qvz3A5wKhg+0EoMUexV7FX0WfRZ9FoMU2xGGD68LyAYoAc77R/cm87vvTO1M7fTuu+/07iXuu++G8rP3QvxkAIkD8gSCBc4FIwe5CKAJGwobCpwKIgucCrkIIwceBjgFMgRVA/cDggVxBoIFIwPIAOz/dgCbAfQCMgT3AwACY/9l/c774vmz92T1UfS/8ybzhvLf8TDxMPHf8Yby5fXI+hQAbwQjB6AJQQzQDtsRgxR9FooXexUMEUEMTQj3A4r/DvtH97/zMPEl7oXqXOfC43PiFeEV4QPlg+n07r/z1vYO+87/ggWvC9sRihf9Gj4cPhz9GsoZfRa0EiEOoAmvBGP/OPkm8yXug+kD5XPiFeHC41zng+l960ztevBR9DL6XwG5CNAOlxN9FqQY/Ro+HI0dPhw+HD4c/RqKF5cTRRCvCx4GdgCR+934G/hH9+X1UfSG8t/xJvPl9TL63P2+/yMABgCJALsBmwJyAkoCxwKJA4kDIwObAiQCQwHd/9j+Tv99AfcDggWCBa8EiQMAAl8BJAKJA/cDxwKdAGX+DP1R+374ZPUm8zDxu+8l7kztTO1M7Wnsfetp7Lvv3vTi+YP+cgIeBioJ2gwMEXsVyhn9Gv0ayhmKF4MUhg+gCa8EdgB3/H74UfQw8fTufet26APlA+Vc54Xqu++/87P3Ufsi/zIEnAoMEYoX/RqNHVkg1yFZIOse/RqkGIMURRCcCvIEiv/i+SbzTO126DbmNuZc54PpheqF6n3rTO3f8bP3I/4jAyMHIgshDgwR2xHbEdsRtBK0EtsRDBFFECEOIgtxBpsB3P1R+4/5G/jW9lH03/G777vvMPFR9Nb2fvji+cj6kfuR+w77DvsJ/N38Zf22/aH+7P9CAE7/3P2O/aH+3gC+Ax4G5Qe5CE0IggeCB7kIoAmgCbkI5QfIBvIEJAJj/2X9kfvd+OX1v/Mm8ybz3/F68PTuu+/f8eX1Mvqh/psCzgVNCEEMDBF9Fv0ajR3rHlkgWSCNHcoZexUMEUEMcQbeAN384vlg9t/xTO2D6VznNuZc54XqJe568IbyZPWP+WP/8gSgCSEOtBJ9FqQYyhnKGcoZpBh7FdsR0A4iC8gGsgCP+d/xfetc58LjwuMD5QPlA+UD5TbmduhM7TDx5fV++nf/vgPIBioJrwt6DSEOIQ7QDoYPRRBFECEOnAojB/cDDgEi/2X+Zf0O+7P3UfS/87/zZPXW9t34UfsM/Y79jv0j/r3+of5F/iP+2P5kALsBmwFCAL3+jv0M/dz9dgD3A3EGIweCB+UHoAkiC68LrwtBDEEMnAq5CHEGrwSbAt3/q/yP+Uf35fVR9DDx9O5p7IPpg+mF6iXu3/FR9GD2fvh3/EMBzgWcCtAOlxOKF6QYpBikGH0WtBIhDrkI9wPO/877R/eG8iXug+nC4xXhFeFz4gPlA+U25oPpJe4m87P3Of0jA7kI2gwMEYMUfRakGKQYihd9FoMUtBJFEK8LcQat/xv4MPFM7X3rfeuF6nboduiD6X3rTO168N70j/kA/gACzgUbCnoNhg9FEEUQDBG0EpcTlxO0EgwReg2gCSMHcQZxBvIESgKK/2X9kfvi+Tj54vnO+7b92P44/93/yAD2APr/Zf45/Tn9tv2D/jj/vf6r/I/5s/cb+Mj6Zf04/94A9AI4BcgGTQgbCkEMeg0hDnoNrwucCioJcQYjA3f/Qvw4+db23vSG8vTuheo25gPlNuZ26IXqaez07oby5fXi+WX+9wMbCkUQgxSkGP0ajR3rHo0dyhl9FrQSIQ6gCR4GuwEJ/GT1u+9p7IXqheqD6YPphepp7CXuMPHl9ZH7fQFxBpwKhg+DFKQY/Rr9Gv0a/Rr9GsoZpBh9FtsRrwv3A479fvje9DDx9O5M7WnsfeuF6n3rTO0w8b/zYPY4+Y79AAKCBeUHoAmcCpwKIgtBDCEO0A56DZwK5QdxBs4FOAVvBL4DmwKyANz9Ufvi+eL5Mvoy+jL6DvtC/N38q/zO+3763fhH99b2G/ji+eL5s/dk9b/zv/Pe9Nb2OPlC/Dj/uwEyBCMHnAohDkUQDBHbEbQStBIMEdAOQQy5CK8EsgBF/t38yPpg9jDxaeyD6XboduiF6mnsu+/f8VH0s/dC/JsByAavCwwRfRY+HOse1yFlI9chWSD9GooXgxRFECILrwTc/bP3hvIl7n3rg+mD6Xboduh26IXqJe6G8mD2fvoi/74D5QevC9AO2xG0EtsR2xG0EoMUgxQMEdoMggckAt38s/cm87vvaeyD6VznNuY25lzng+mF6mnsu+8m82D2Mvoj/p0ADgEOAUoCOAXlByoJTQgjBx4GzgXOBc4FcQaCB4IHIwfOBfIEMgQjAwACXwGbAQACJALHAr4D9wMAAtj+QvzO+3f83fwJ/OL5G/jW9mD25fVH9zj5zvsA/jIAIwPIBpwKeg1FELQSgxR9Fn0WfRZ9FpcT0A4bCh4GVQMOAdz9OPlR9Lvvfetc5zbmNuY25nbog+mF6kztMPHe9N34jv30Ak0Ieg20EooX/Rr9GsoZpBiKF3sVtBJ6DYIHQwHI+lH0Je6F6lznA+XC4xXhFeFz4sLjNuaD6SXuhvLW9kL8JAKCB5wKQQzaDNAO2xGDFIMUgxTbEYYPIgtxBpsBtv0y+mD2hvK77yXuTO1p7GnsJe707nrwJvPW9g77of6yALsBxwLyBIIHKgmcCpwKnAqgCeUHyAbIBuUHuQhNCE0IuQi5CE0IggfIBh4GggXyBDgFyAblB+UHzgVVA30BUwBj/0X+Zf1C/DL6s/dR9IbyhvIm8ybzUfTl9d34zvvY/koCHgagCUEMhg+0EnsVfRZ7FdsR0A6vCyoJHgb0Aq3/zvvW9jDxfet26DbmwuPC48LjA+U25nbofeu777/zG/ir/PQCGwoMEX0WpBjKGT4cPhw+HP0apBh7FQwRGwr0Agz9G/i/87vvTO1964Ppduh26IPpfesl7jDx3vTI+l8ByAacCtoM0A4MEZcTexWKF8oZpBiKF5cTDBF6DaAJggWbASP+yPpH97/z3/Ew8TDxevB68N/xZPU4+c77Zf1l/or/yAAkAr4DzgXIBnEG8gSJA/QC9AKbAscCiQOvBIIFzgUeBsgGyAYeBm8EvgNvBIIFcQbOBTIEJAIUANz9CfwO+zL63fjl9SbzevAl7mnsaexp7EztJe6779/xZPWP+WX9QgCJA00IIQ60En0WfRZ9FoMU2xGGD9oMIgtNCK8E3f8O++X1MPFM7X3rheqD6YPpg+mF6iXuMPG/82D2MvpkAOUH0A6XE4oX/RqNHeseWSDXIdchWSA+HH0WDBGcCjIE2P5++kf3v/O770ztaexp7GnsaexM7bvv3vTi+YP+SgKCBeUHKgmcCnoNRRC0ErQS2xFFECEOrwsqCcgGMgQOAQz9OPlg9t70JvMw8SXuJe707t/xv/Nk9Uf33fg4+Tj5yPoM/Tj/iQCyABQACv/c/Tn9Zf1l/jj/rf9CALsBMgRxBiMHyAYeBsgGTQigCRsKGwobCk0IzgW+A5sCAAL2APL+d/w4+eX1hvJ68Lvv9O707iXu9O4w8VH0R/eP+ZH7Iv8yBKAJhg+DFKQYyhnKGaQYfRZ7FYMUDBF6DSoJ9wNF/n74v/N68Eztg+lc5zbmXOd26IPpg+mF6kztMPFg9gz9vgOgCXoNhg/bEYMUihfKGf0a/RqkGIMUhg8bCvIEzv9++mT1MPH07kztfeuD6VznXOd26IXqJe4m87P3Dvs5/dj+KAFvBIIHGwqvC0EMQQyvCxsKuQiCB84F9AKt/9z93P05/c77yPrd+GD2UfS/8ybzv/Pl9d70MPFM7YXqg+lM7VH0kfsjAxsKIQ6GDyEOrwtNCIIFrwTyBG8EiQObATIAfQFxBtoMtBKkGP0aihe0EtoMKglNCKAJnAobCioJOAWK/+L5YPZk9Sbz9O5c56ff+tr62inewuNp7Ef3fQEqCYYPlxODFAwR0A4hDnoNQQycCk0IHgYyBDIEggVNCCILKgn3A5H7hvKF6gPlFeGn3xXhc+Jz4nPiwuOD6Yby3fy5CHsV6x65JloqWip/KLkmBiXXIese/RqXE+UHUfuG8iXuaex68GD2DvtR+xv4hvJp7HboNuY25gPlA+UD5QPlheq/8yL/2gz9GrkmSSxPLkksBiWKF7kICfyG8oPpNuYD5QPlNuY25lznaezl9dj+9ALHAmP/1vZ96ynesdEmxsjA673rvcjAJsaUz/rag+kJ/NAO6x5aKqEyVzehMk8ufygGJVoqbDBXN3o8OD8VQjNI3k4HWlJiXWsxcF1rFV52S+40/RrOBd70XOeb3LHREssSy5TP+tqF6gD+2xHXIUksSSwGJYoXKglC/L/z9O5963bowuOn35vcFeGD6WD2JAIbCq8LggUO+/TuFeGm1RLLhsPrvc23zbfNt+26hsO30zbmR/fOBdAODBHaDJsC1vZM7TbmFeGb3EfZptW304HXp98l7mX+QQx9Fj4cPhzKGYMUhg/aDEEMGwpNCCMHggciC9sRjR1JLHo8dkslVgdaJVZ2S3o8WiqKF+UHj/lp7BXhgdex0bfT+tpc52T1vgMhDpcTtBLQDioJ9gDW9oXqm9yx0anIhsPIwCbGX8362mnsiQB7FX8ooTLaOVc3bDAGJXsVMgQm8wPlR9mUz6nIEsum1RXhevBj/68LlxODFIYPHgY4+YXqm9yx0RLLJsbIwIbDqciB12nsggcGJTg/JVa+Zl1rvmZSYgda3k4VQlc3fyiNHXsVtBKDFP0aBiVPLu407jRsMAYlfRYeBmD2hepz4pvcgdex0ZTPlM+m1affevAjA9sRyhmkGJcTnAooAbP3u+9c55vcsdGpyCbGqcix0affu++yAHoN2xGGD00IAP4w8XPigddfzanIyMDtus23zbfIwJTPwuM4+ZwKfRb9Gv0apBi0EioJjv3f8QPlgddfzRLLlM8p3r/zIgvXIVc3E0XeTt5OdksTRVc3WirrHpcTTQhl/mD2v/PW9rIA0A7rHk8uejwTRTNIdkszSDg/7jR/KIoXOAXl9YXqA+XC41znTO3W9kMBuQhBDJwKvgOz93bo+tpfzYbD7bqKtIq0zbfrvSbGptVc5xv4bwTaDNsRgxQMERsKIwBk9YXqFeFH2bfTt9OB15vcXOdR9F8BrwsMEdsRIQ6CBY/5Je425nPiwuMD5YPpMPEM/doM6x6hMhNF3k4lVgdaB1ptUjNIejxJLP0aQQwj/jDxdug25nbou++R+yoJfRZZIGUjWSB9FpwKnQAb+LvvXOen34HXt9OB16ffTO0M/ZwKgxT9Gj4c/Rp7FdAOKglKAuL5Je5z4oHXlM8SyxLLsdGb3Fzn9O4m81H0MPFp7DbmFeEp3kfZt9NfzRLLEsuUz/raherO+xsKlxOkGD4cWSAGJX8oSSxPLk8uTy5aKn8ouSa5JloqbDDaORVCM0gzSBVCVzd/KKQYTQjd+H3rp9+m1V/NX82x0frag+lg9igBKgmGD5cTexW0EnoNHga2/WD2u++F6gPlp9+b3Jvcp98D5X3r3/Hd+N38Qvyz93rwXOcp3qbVEsuGw+u97brtuuu9qci30yneg+lR9I79iQPOBW8EfQG9/pH71vYm83rwTO2F6nbofeu/887/IQ4+HLkmbDDuNFc3VzfaOVc3oTJPLloquSYGJQYluSZaKmwwoTLuNKEyTy5/KFkgihdFECILIwfHAkL8JvOD6QPlA+WF6ibzfvpO/1MAI/4O+7P33vQw8Uztduhz4vrat9OUz7fTm9yD6Uf3ggXbEcoZPhz9GooXtBJ6DcgGI/7e9IPpKd6305TPsdFH2RXhg+kw8eX1R/dk9SbzhvJ68H3rc+JH2bHRX81fzbfTFeEm800IjR2hMhNFbVIHWhVeFV4VXgdabVJ2Szg/oTK5Jv0alxNFEEUQ2xG0EtsRDBGGDyEOnApVA374TO1z4kfZsdFfzRLLEsuUz0fZwuMw8dz9TQjQDtsRDBFBDB4GBgB++t709O5964Ppheol7obyfvgK/74DbwSbATn91vYl7nPiR9mUz6nIhsPrveu9yMCGw1/NR9l26LP39ALlB00IrwS+/8j6s/dg9uX1YPYb+Kv8rwSGDz4cWiraORNFdkveTt5OdksVQto5bDAGJcoZhg9xBtz9fvh++EX+uQh9FtchuSZ/KAYlWSD9Gn0WRRAqCc7/5fVp7DbmwuN26LvvfvryBK8Leg2vCyoJzgWbASP+Dvtg9nrwg+lz4inem9wp3sLjTO04+UoCyAaCB3EGIwOK/6v84vne9EztwuP62qbVptVH2SneNuYl7r/z1vYb+H74s/fW9tb2R/cb+Dj5MvoO+6v8sgAjB0UQPhxJLNo5E0UzSDNIE0U4P1c3Ty7XIYMUKgneAAn84vni+ZH7Iv8yBCoJeg2GD9AOIgv3A3f83vRM7Vznc+Kn3ynem9yb3CneA+Ul7jj5MgQhDnsVyhnKGaQYgxR6DTIEfvqG8mnsXOfC4xXhc+I25n3revAm8ybzu++F6sLjKd762kfZptW305TPX81fzZTPptUV4bvv3P2cCn0WWSBaKmww7jRXN1c37jShMmwwTy5PLk8uoTJXN3o8OD96PO40SSxlIz4cfRZFEKAJsgDW9iXuNubC4wPlheqG8uL5vv8jA28EzgXlBxsKIgsqCVUD4vm771znFeEp3nPig+mG8qv8ggUiC3oN2gwbCnEGSgKr/CbzXOf62pTPqciGw4bDEsu305vcwuOF6nrw5fXI+gr/AAJ9Ac77hvKD6XPiKd762qffduje9PcDtBLrHn8obDDuNFc32jnaOVc3bDBaKgYl6x79GqQYihfKGY0d1yEGJX8oWipaKn8oBiXrHnsVQQzHAjL63/GF6gPlFeFz4jbmaey/8+L5Zf3d/Dj5JvNp7MLjKd5H2abVt9Ox0abVR9mn31znMPHI+r4DoAmvC5wKcQZO/+X1aewD5SneptVfzanIqchfzabVp99967/zs/dH99703/El7oPpA+Vz4qffp99z4lznevB3/CIL/RpJLNo5E0V2S21SbVJtUt5OM0h6PGwwZSOKF3oNuQigCXoNDBGDFHsVlxNFECEOrwuCB8gAG/hM7afft9MSy6nIX82m1affg+kw8Uf3CfzeAHEGIgvaDHoNQQxNCA4BOPmG8iXu9O7f8Uf3Of3eALIAtv0O+4/5R/eG8mnswuP62pTPJsbIwMjAJsZfzabVp9+D6d/xfvgj/r4DKgkhDrQSexV9FoMUtBIMEdsRfRaNHbkmbDDaORVCM0h2S3ZLM0g4P+40WiqNHdsR5Qec/4/55fXl9Tj5Tv9xBtoMtBKKF8oZpBiXEyEO5QckAtz94vlk9bvvfeuD6X3revBH92X9IwMqCXoN0A7aDCoJIwPO+1H0TO025qff+tqB16bVR9mn38Ljduhp7CXuJe5p7IPpXOc25sLjp99H2abVsdG306bVm9zC433rUfS2/R4GQQwMEZcTfRaKF4oXfRaXE5cTexXKGVkgfyhsMO40VzdXN1c37jShMmwwSSwGJT4c2xGCB4P+3fgb+A77Cv9fAUMBY/8M/c773fxO/4kACv/I+lH0aezC4yne+tqb3MLjTO0b+MgAggd6DdsRfRbKGf0ayhmDFK8LIwC/83bop9/62kfZR9n62vram9wp3hXhwuM25gPlwuMV4Zvcgdex0RLLqchfzabVp99p7Dj5ggXbEY0dWiqhMto5OD8VQhVCFUI4P9o57jRPLloqfyi5JrkmuSYGJWUj1yGNHYoXDBGvC84FOP9++HrwdugV4Zvc+tqn3zbmJe7l9av8XwG+A68ErwQjA1MADP3i+WD2JvPf8Yby3vQb+N383QFxBioJoAmCB1UDDP1k9WnswuP62rHRJsbIwOu9672GwxLLt9P62nPiher07t/xJvNR9L/zv/OG8nrw9O707ibzMvqJA3oNfRZZIFoqoTLaOXo8FUIVQjg/VzdsMAYl/Rq0EiEOQQzaDNAODBGDFIoX/RqNHVkg1yHrHqQYhg+JA0f3TO126FznXOeF6kztu+8w8Sbzv/NR9GD2fvg4+X74YPbf8WnsXOcD5Tbmduhp7Hrwv/PW9t34MvoO+wn8kfsb+N/xfesD5Snegde305TPsdG304HXm9yn38LjNuaF6vTuJvPl9bP33fiP+Tj53fgy+iP+8gR6DX0WWSBJLFc3OD8TRXZLdkszSBNFOD9XN0ks1yGkGAwRrwugCaAJrwvQDtsR2xFFEK8LzgW+/376ZPV68IXqA+UV4Zvc+tpH2ZvcFeF26Hrwj/lDAYIHQQzQDgwRDBGGD9oMTQjHAjn9s/cm87vv9O6777vvJe5M7Wnshep26APlc+Ip3vraptWx0V/NEstfzbHRR9kV4YPphvKR+zIEQQyDFP0aWSBlI2UjZSPXIWUjBiV/KE8uoTLuNO407jTuNKEyTy5aKgYl6x6KF9AOHga9/uL5s/dH90f31vZg9mD2R/eP+UL8Iv9yAvIE8gTdAZH7UfRM7XboXOd26H3ru+/e9I/5g/5VAyMHGwp6DYYPIQ4qCUMBs/cl7jbmp9/62oHXgddH2fraKd5z4jbmfeu77ybzv/OG8vTuheo25sLjc+IV4cLjXOdM7WT1Rf7IBiEOexX9Guse1yEGJbkmBiVlI9chWSA+HMoZpBikGMoZPhzrHlkg1yHXIdchWSBZIOseyhmXEyILuwHd+Ibyu++774byR/dR+zn93fzI+hv45fVR9N/x9O5961znA+XC48LjNuZp7FH0AP4eBq8LIQ7QDiEOQQxNCAACfvqG8oPpp9+B17HRlM+x0abVR9kp3hXhc+ID5TbmduiD6VznwuOn35vcm9wp3sLjhepR9KH+oAl7FVkgWiqhMno8E0UzSDNIE0V6PO40SSxlI+se/RrKGcoZ/Rr9Gj4cjR3rHusePhx9FtAO9wMb+EztNuYV4RXhFeHC4zbmg+lM7Ybys/fd/AACyAYqCSoJyAZVA87/DP3O+877Qvzd/CP+3f8oASgBrf+O/ZH73fi/82nsc+JH2bHRX82pyCbGJsapyF/Nt9Ob3APlaezf8db2kftj/5sCOAVxBh4GOAWvBB4GoAnQDn0WWSBJLO40ejwVQhVCFUI4P9o5oTJaKlkgfRZ6DXEGmwLHAh4GIgsMEXsVfRZ7FZcTRRB6DSILTQgyBEX+YPYl7lznwuNz4sLjdugl7ibzYPbd+FH73P2yAL4DOAVVA/L+OPkm80ztXOcD5QPlXOd96/Tuu++777vvu++773rwu+9p7FznFeGb3EfZR9n62inewuNc52nsMPGz9/L+zgWvC4YPDBFFECEOQQwiC0EMDBF9Fo0dBiVaKk8ubDChMu407jTuNKEyTy65JlkgpBi0EiEOGwrIBvcDQwGh/gn8yPqR+6v8jv2O/UL8fviG8n3rA+Wn35vc+tpH2frap99c5/TuG/hDAbkI0A6DFIoXihe0Eq8LiQMO+ybzaexc58LjFeGn36ffFeHC4wPlA+U25jbmNuYD5cLjFeH62qbVsdGx0bfTm9xc59/x3fxxBtAOfRaNHWUjWipPLqEyoTKhMk8uWiq5JgYluSa5Jn8ofyh/KLkmBiUGJWUjZSNZID4cfRbaDF8B5fVM7Xboduh967vvUfQb+H76Of3d/3IC9wP0Aor/Mvq/8yXufeuF6kzt3/Gz94P+bwS5CJwKIgsiCxsK5QcyBCP+5fVp7BXhgdeUz1/NlM+x0abVR9mn3zbmTO3e9DL6d/wJ/N343vTf8fTuJe707obys/dl/VUDoAmGD4oXWSB/KGww7jRXN+40bDBaKmUj/RqDFEUQIQ4hDtAODBGXE6QYjR1lIwYlBiVZIMoZDBHlByP+5fW7733rheqF6mns9O4w8b/zYPZH9374j/ni+d341vZR9DDxJe5M7fTuMPG/82D2fvjI+gD+3gAjA68EiQNO/9343/F963Pi+tq307HRsdGm1UfZp9/C4zbmduh96/TuhvJk9bP33fh++Nb2UfSG8ibzR/e9/k0ItBKNHX8obDBXN3o8OD84P3o82jmhMloqWSCKF9sRhg9FELQSexV9FooXfRaXE9sR0A6cCh4GDgHI+obyg+nC46ffKd6n3xXhwuN26GnshvI4+UIAyAavC4YP2xFFEK8L8gS2/bP3UfS/89705fXl9VH03/F68PTuTO1961znc+Ip3kfZptWx0ZTPlM+x0abVR9kp3gPlTO2z9wACIgvbEXsVfRZ7FYMUtBK0EoMUpBjrHgYlWipPLmwwoTLuNFc3VzdXN6EySSwGJY0dfRZFEEEMKgkjB4IFVQMoASMAfQGvBE0IGwqcChsKTQhvBNj+s/e774PpNuY25lznfev07lH0DvvHAqAJ0A7bEQwReg3lB30ByPpR9EztXOdz4inem9yb3JvcKd4V4QPlduh96/TuevC772nsXOcV4ZvcR9lH2SneA+V964by3fjy/m8EoAnQDpcTihf9Gj4cPhz9GsoZihd9FooXyhmNHVkg1yFlIwYlBiW5Jn8ofyi5JmUjPhzbEYIHRf5++GT1UfQm8ybzv/Ng9jj5zvsM/UL84vlg9t/xfes25hXhp98V4Tbmaey/88j6UwCvBE0IIgvQDgwRDBEhDiMHjv0m84PpFeH62oHXptWm1YHX+tqn3wPlg+lM7SXuJe5961znwuMV4affp99z4gPlduhM7SbzUfvyBIYPPhy5JmwwVzfaOVc37jRPLloquSZlI+sePhykGIoXihfKGY0d1yFlI9chjR19FiEO8gTO+ybzfes25sLjwuM25oPpaeww8eX1Mvq2/VMA3QFKAt0BKAF2AM7/Y/8K/yP+DP2r/KH+cgIjB5wKrwsiC7kIMgRl/kf3Je4D5frat9OUz1/NlM+x0YHXm9xz4lznaeww8eX1yPoi/5sBXwHY/pH7fvjW9tb2MvoUAOUHDBH9GtchfyhJLGwwoTLuNKEySSwGJT4ctBIbCjgFbwTIBpwKIQ4MEbQStBK0ErQSRRDaDOUHmwKr/Nb2MPFp7IPpXOcD5QPlNuZ26H3ru+9k9ZH7AALIBioJggebAkL81va/84byhvIm84byJvO/8970YPZH9xv41vZR9Hrwfetc53PiKd762kfZR9mB14HXR9mn3zbm9O5g9t38fQH3A68E9wObAkMBQwFVAyMHrwtFEHsVPhxlI0ksoTJXN3o8ejx6PFc3bDBaKgYlWSA+HKQYlxMhDpwKTQgjB3EGcQZxBsgGIwcjBx4G9AK2/WD2Je5c5xXhm9z62vrap9926N/xkfv3A5wKIQ5FENsRtBJFEEEMcQZ3/3743/Fp7HboNuY25gPlA+UD5TbmXOd26IXqfet26MLjm9ym1bfTsdG304HXKd4D5Uzt3vRC/PQCoAkMEaQYjR3XIdchWSBZIOse6x5ZINchBiV/KFoqWip/KH8oWipJLE8uSSx/KFkgfRZ6DfIEOf3W9t/xu+8w8VH0OPkA/rsB9wOvBPcDuwE5/Uf3MPFM7YXqg+l96/TuhvLW9sj68v4jA4IHrwvQDkUQIQ65CMgAs/cl7gPlm9ym1bHRlM+Uz7fTR9kV4Vznfesl7rvvevC77/TuTO1964Ppduhc53bofev07mT1Zf0eBtAOihdZILkmWipJLEksWip/KAYl1yE+HIoXgxSDFIoXjR1lI38oSSxJLEksWioGJY0dgxQiC0oCUfvW9lH0JvOG8ibzv/NR9GT1YPZH9xv4OPni+eL53fjW9r/zevBM7WnsJe7f8Rv4Zf5VAyMHoAkiCyILoAmCBdj+5fV963Pi+tqm1abVptWB1/ram9wV4QPlg+lM7d/x5fV++N341vYm87vvaeyF6n3r9O5k9QD+5QfbET4cBiVPLu40ejw4P3o8VzdsMLkm6x7KGX0WexV9FooXyhn9Gv0ayhmKF4MUDBF6DSoJ9wOO/WD29O5c53PiKd6b3Cnep9/C44PpevAb+GP/ggW5CLkIyAaJA0IA3fzi+bP31vbW9kf3s/fd+I/5j/nd+Ef33vQw8UztdujC4yneR9m305TPX82Uz7HRgdcp3gPlaexR9FH7iQC+A/IEbwQjA5sBiQBTAH0BMgS5CNAOihdZIH8oTy6hMqEyoTJsMEksfygGJVkgyhmDFIYPnAojB28ExwJyAlUDzgUqCdoMhg+GD3oNoAmJA1H73/GD6XPip9+n33PiXOcl7lH0DvsOAXEGIgshDkUQDBHQDhsKvgNC/N709O5964Ppg+l26Hboduh96/Tu3/FR9N70v/N68IXqA+Wn3/raR9lH2Snec+J26CXuv/M4+b3+bwQbCiEODBHbEdsRhg/QDtAODBGXE4oXPhzrHlkgZSMGJVoqTy6hMu407jRsMFoqWSB7FSIL9AKO/VH7kftC/GX9Cv9DAVUDbwT3AwACI/7d+Ibyaexc58Ljc+LC41znfet68OX1Qvy+A0EMlxOKF8oZihe0EtoMzgVl/b/zhepz4ine+tr62pvcp9/C43bofesl7vTu9O5M7YXqNuZz4qffm9yb3CneFeE25mns3vQ4/yoJ2xHKGVkguSZJLE8uTy5JLLkmWSD9GooXfRaKF8oZ6x5lI38oSSxPLkksuSZZIKQYRRCCB2X+YPZ68Eztaexp7CXuu++G8t70s/d++gz9vf6c/2P/jv3i+WT13/G773rwJvN++AD+SgKCBbkIrwt6DSEOrwtxBoP+UfR26CneptWx0ZTPlM+x0bfTgdeb3BXhXOdM7Yby1vaP+eL5s/e/8yXufeuF6mnsevDe9DL6dgC5CLQS6x5/KGww7jTuNKEySSwGJY0dpBiDFJcTlxN7FX0WihekGMoZ/RqNHY0djR39Gn0Whg+5CCgB4vm/8yXug+lc5zbmXOeD6fTuZPXO+18B8gQeBjgFvgNfAYP+zvvd+Nb2ZPXl9Uf3OPl3/GP/fQEkAp0AOf3d+FH0u++D6cLjm9yB17fTsdGx0bHRptX62nPiherf8db24vnO+3f8QvzI+rP33vSG8obyYPbd/DgF0A6kGNchuSZJLE8ubDBsMGwwTy5aKrkmWSD9GoMU0A4bCoIHHgbIBuUHKgmcCkEMeg3aDBsKrwQM/b/zg+lz4pvc+tr62inec+Jc5yXuZPWr/DIEIgtFEJcTlxMMEdoM5QcjA4r/DP0O+374ZPXf8bvvu+8w8b/zZPXl9d703/Fp7Dbmp99H2YHXgddH2frap98D5YXqevCz99j+rwS5CCILQQzaDNoMeg2GD9sRlxODFHsVihekGP0a6x5lI1oqTy5sMGwwTy5/KFkgfRbQDk0ImwIA/g774vkO+wD+SgIeBrkIoAm5CB4GAAIM/bP3hvL07n3rg+mD6YXqJe4m8zL6mwEqCYYPgxSKF4oXfRaXE9AOTQgjAGD2aezC46ffm9wp3hXhA+WF6vTuhvK/87/zJvMw8SXufet26DbmwuPC4wPlXOd963rwYPYM/fcDIgu0EsoZWSBlI2UjWSA+HIoXlxNFEIYPDBGDFMoZWSC5JloqTy5PLk8uWioGJeseexXaDDgFCv/I+rP3ZPVR9FH0ZPVH9934yPpC/GX9jv1C/Dj5ZPXf8fTuTO0l7vTu3/Fk9TL6QgAjByEOgxSkGMoZfRaGD84FDvsw8VznFeGb3EfZgdeB10fZ+tqn38LjduhM7TDxv/O/89/x9O6F6jbmc+IV4affFeED5Wns1vZVA4YP/RplI38oSSxJLH8oZSPrHsoZfRaXE7QS2xHbEZcTexWkGP0ajR2NHY0dPhykGLQSQQxvBKv85fW774XqNubC4wPlduhM7Sbz3fgA/scCyAYqCaAJTQiCBbsBI/4O+zj5OPmR+63/MgTlBxsKGwq5CB4GcgK2/X74hvJ96wPlKd6B17fTlM+Uz7HRgden31zn9O7l9Q77vf6JABQAZf04+WT1JvOG8lH0G/gA/vIE2gyDFD4c1yG5JloqSSxJLEksWioGJVkgyhmXEyEOGwqCB3EGIwe5CCILIQ5FENsRtBLbESEOTQidABv4u+926MLjp98p3qffwuOD6TDxfvi+/x4GIgshDiEOQQwqCc4FmwJj/0L8j/nW9t70JvOG8obyv/Ng9t34DvvI+hv4hvJ96wPlKd5H2YHXgdeB10fZKd7C44Ppu+9k9TL6vf5KAvIEcQZxBs4FrwRvBDgFcQZNCJwKIQ60EqQY6x65JkksbDChMmwwSSx/KFkgyhnbEZwKrwTd/wz9d/y2/VMAVQMeBuUH5QfIBvcDCv/d+N/xheoD5XPip9+n33Piduj07tb2Zf7OBUEMtBKKF8oZ/RqkGIMUeg2vBFH73/GF6jbmNuZc54Ppaez07jDx3/Hf8d/xevBM7YPpNuZz4qffm9yb3Jvcp9/C44PpMPHi+ZsCIgu0EqQYjR1ZIFkgjR3KGXsV2xEMEdsRgxSkGD4cWSBlI38oWipJLEksfyhlI/0atBKgCQ4Bfvrl9b/zJvO/89701vY4+Q77q/wA/tj+2P5l/X761va/8zDxu+/07rvv3/Fk9cj6XwG5CEUQfRb9Gj4cpBjbEU0II/7e9GnsNuYV4Sne+tr62vram9wV4Tbmaeww8WT1R/dg9r/zu++F6jbmc+IV4XPiA+WD6XrwfvgAAkEMfRaNHWUjBiUGJdchWSA+HKQYlxMMEYYPhg9FELQSfRb9Guse1yHXIVkgjR2kGJcTIQ6CB4kAj/km8yXuhep26Hbofesl7obyR/fO+zIAiQOCBYIF9wOyAN38j/kb+H74Dvut/4IFnArQDgwR2xEMEdAOQQwqCfIEIv9H9yXuA+Wb3IHXptWB10fZKd7C44Xqu+9R9Bv44vky+t341va/83rwJe5p7Ezt3/Eb+Jz/ggeGD30WjR0GJVoqTy5PLk8uWioGJVkgyhl7FbQSDBGGD9AOeg3aDCEORRC0EoMUgxS0EtAO5Qec/9b2Je5c53Pip9+n3xXhwuOD6TDx3fhTAHEGnAraDNoMrwugCYIHzgX3A0oCUwCO/TL6R/fl9Uf34vnd/AD+d/wb+Ibyaew25qff+tqm1bfTt9O304HXR9kp3sLjg+l68Nb2Cfwi/1MAdgAyABQAFABCAMgAAAIyBIIHQQzbEaQY6x4GJX8oWipJLFoqfygGJVkgpBhFELkI9AJj/wD+g/6dAL4DggecCkEMQQycCiMHJAIJ/N70Je526APlwuMD5Vznheq772T1CfybAioJ0A6XE4oXpBiKF9sRoAmyAH74hvK77yXuJe4l7iXuu+8w8Sbz3vRk9d70JvO772nsXOfC46ffm9z62pvcp98D5YXqevCz9yL/cQbaDNsRgxR7FZcTDBEhDtoM2gx6DdAORRC0En0W/RrXIX8oSSxPLkksfyjXIcoZDBGgCVUDZf4O+934s/fW9tb2fvh++kL8Zf1l/Xf8yPqz97/zevBM7YXqduh26IPpaeww8Rv4DgGcCpcTyhk+HP0afRYMEZwK9wPd/GT1Je526MLjFeGn3xXhwuN26EztMPFR9OX1ZPWG8iXug+k25nPiFeGn3xXhwuN26LvvG/i7ASILlxPKGese1yFlI9chWSA+HIoXlxMMEQwRtBJ7FaQYPhzrHtch1yHXIVkgjR2kGJcTeg3IBgr/fvgm8/TuaeyF6n3rTO168N70j/nc/fYAmwJyAt4AAP4y+tb23vTe9Nb2yPoK/4kDggciCyEORRDbEdsRRRCvC/IEd/y/84XqwuMp3vra+tr62inewuOD6fTuJvNH9zL6CfxC/A77fvje9N/xu+/07nrwJvOz97b9OAUhDn0W6x4GJVoqSSxaKn8oBiXXIY0d/RqkGHsVlxPbEUUQDBG0En0Wyhk+HD4c/RqkGJcTQQy+A1H7JvNp7FznA+XC4zbmg+kl7r/zOPm9/iMDzgXIBsgGzgWvBL4DcgKdAAD+UfuP+eL5Cfw4/0oCbwSvBFUDiQCr/LP33/F96zbmFeEp3pvc+tpH2fram9xz4nbou+/l9X76jv2h/iP+d/x++jj53fg4+X76q/wyAPIEIgvbEaQYjR1lI7kmWipJLEksWioGJesepBjbESILyAb3A/QC9wMeBioJ2gzQDoYP0A4iC3EGUwDi+b/zTO126MLjFeEV4cLjXOdM7b/zfvoOAYIHeg3bEYMUlxNFECILOAUGAFH71vaG8rvvTO1M7SXuevDf8b/zUfRR9CbzevBp7FznFeGb3EfZgdeB10fZKd7C44Pp9O5k9c773QHIBhsKQQxBDEEMIgucChsKoAkqCRsK2gwMEX0WPhxlI38oSSxJLH8oBiXrHooXhg8qCfQCRf4O+zj5fvg4+cj6DP13/5sB9ALHAsgAZf3d+N70MPEl7mnsheqD6YXqTO2G8jL69AIiC9sRexWKF4oXfRa0EkEMrwRC/L/zaexc58LjFeFz4gPlg+n07r/zYPbW9uX1v/Mw8SXuaeyF6nboA+XC48LjA+WD6bvvG/jeACoJRRB9Fj4c6x7rHo0dyhl9FrQSRRDQDoYP2xF7FcoZjR3XIWUjZSNlI9ch6x79GnsVhg+5CLsByPre9HrwJe5M7fTuevAm89701vbd+A77CfyR+zj5ZPUw8SXuaexM7bvvv/N++CP+MgQbCtAOtBKXE7QShg8bCokDCfy/833rNuYV4affp9+n33PiA+Vc533r9O6/80f3j/mP+db2JvP07n3rg+mD6YXqJe4m81H7bwQhDn0WjR1lI7kmfyh/KLkmZSPXIesePhykGHsVtBIMEQwRtBJ7FYoX/Rr9Gv0apBiDFNAOKglKApH73vT07oPpNuYD5Tbmheq77+X1zvtCAPQC9wMyBPcDiQObAvYAIv85/Qn8Cfxl/d3/mwLyBMgGggfIBm8EDgFl/Y/5ZPV68IXqA+Wn3/ragdeB1/rap99c5yXuv/NH94/5fvp++jL6OPkb+Ef3YPbl9bP3Dvu+/4IFrwvbEYoXPhzXIbkmfyhaKloqfyhlI40dfRZFEK8LTQgjB+UHoAmvCyEORRDbEdsRDBGGD68LzgVl/mD29O526APlA+U25oPpTO3f8WD2CfwAAoIHQQzQDkUQhg8hDiILIwdyArb9j/nW9t70v/NR9OX13fhR+zn9tv13/I/5ZPW774PpwuOn3yneKd4p3hXhwuNc52nsMPHW9s77+v8jA4IFyAblB00ITQgjBx4GggVxBioJIQ6DFP0a1yG5JloqSSxJLH8oBiVZIP0agxR6DYIHxwJO/479Zf3y/l8B9wM4BfIEmwIi/w77R/e/8zDxTO2D6QPlc+IV4cLjduj07mT13fy+AxsK0A7bEbQS2xHQDrkIKAHd+DDxheo25gPlA+Vc54Ppfesl7vTu9O4l7kztaex964XqXOfC46ffm9z62pvcFeE25mnsJvMO+/QCnAoMEXsViheKF30WlxMMEdAO0A6GD9sRgxSKF/0a6x7XIQYlBiUGJWUjWSD9GnsVIQ5xBuz/Dvsb+GD2ZPVR9L/zv/Pe9Ef3Mvrd/AD+Zf1R+xv43vTf8fTuTO1M7XrwUfQy+p0AIwfaDAwRtBK0EkUQrwuCBfL+G/gw8YXqNubC4xXhFeEV4XPiA+V26EztMPHe9Nb2R/fl9Sbzu+9963boNuYD5Tbmhep68LP3ZAC5CEUQexXKGT4c6x5ZIOsejR39GqQYexWXE5cTlxODFH0WpBj9Gj4cjR0+HP0apBh7FdsR2gzIBmP/s/cw8Wnsg+mF6kztMPFk9Tj53fwUACQCmwIAAsgATv+2/UL8zvsJ/Dn9Y/8kAvIEIwdNCCoJGwqgCbkIyAb3A1MAkftk9SXuXOdz4qffKd4V4cLjduhM7d/x5fV++H76yPoy+t341vZR9N/xMPHf8d70j/m9/m8EnApFEH0WjR3XIbkmfyh/KH8ouSbXIY0dpBiXE0UQ0A56DXoNIQ7QDkUQtBKXE4MUtBLQDioJfQE4+d/xaex26DbmNuZc54XqJe4w8WT1OPkM/SgBOAVNCJwKIgugCYIH9wMGAHf8j/mz99b21vYb+DL6q/wj/oP+Zf3I+tb23/F96zbmFeEp3ineKd6n3xXhwuN26GnsMPFk9Y/5d/zy/sgAJAL0AvQCmwIAAiQCvgPIBiILhg+DFMoZWSAGJX8oWipaKn8oBiXrHqQY2xGcCjgFmwGt/5z/DgFVAzgFHgY4BYkDQwHY/gn83fhk9TDxTO2D6TbmwuPC4wPldugl7lH0CfyJAxsK0A7bEdsRRRCvC84F8v5++Cbz9O5M7Uzt9O568N/xv/NR9N70UfRR9L/zhvJ68Eztg+kD5XPiFeEV4XPiA+V26EzthvLd+CL/OAUbCnoN0A7QDiEOQQycChsKGwqvC9AOtBKKFz4cWSBlIwYluSYGJWUjWSDKGbQSQQyCB74D9gBl/pH7OPlH99b2s/c4+ZH73P13/87/Rf7I+uX1evBp7IPpg+l963rwYPZ3/PQCKgkhDrQSgxSDFLQS0A6gCb4DRf7d+FH0u+9p7IPpduhc53bohepM7XrwJvNk9WT1UfSG8vTufet26APlwuNz4sLjXOcl7mT1Of04BUEM2xF9FsoZ/Rr9GqQYihd7FZcTlxOXE5cTgxR7FYoXyhn9Gv0a/RrKGaQYihd7FdsRrwtvBKv8ZPV68EztaexM7XrwUfR++FH7Of0A/gD+Of13/M77UftR+877d/zc/b7/JALyBIIHoAkiC68LrwuvCyILoAnIBt0BUftR9EztXOfC43Pic+ID5Xboaex68L/z1vaP+VH7kfsy+rP3UfTf8bvv9O4w8VH0G/gM/ZsCTQh6DbQSihc+HOse1yHXIdch6x79GooXgxQMEdAO2gyvCyILQQzQDrQSexV9FnsVtBLaDHEGTv9++L/zu+8l7mnsaexp7Ezt9O4w8b/zs/dC/N4ArwSCB7kIuQiCB84FIwMjAAz9yPqP+eL5zvtl/vYAmwL0ApsB8v4O+9b23/Fp7HboA+Vz4qffp98V4XPiNuaF6vTu3/G/89705fXW9hv4OPni+X76yPrI+g77q/xj/4kDuQiGD3sVPhxZIGUjBiW5JgYl1yE+HH0WRRCcCiMHggXOBYIHKgkbCpwKoAnlB84FiQPdAez/Zf3i+WT1evB963boNuY25oPpJe5R9FH7JAK5CCEO2xGXE5cTDBFBDHEGyADO+xv4YPZk9WT1ZPXl9WD21vbW9mD2YPZk9SbzevBM7YPpNubC48LjwuPC4wPlNuZ26EzthvJ++Nj+bwS5CK8L2gxBDCILoAm5CLkIGwraDAwRexXKGeseZSO5Jn8ouSYGJVkgPhyKF5cT0A4iC4IH9wNTADn9UftR+6v8Cv99AVUDbwT3A0oCIv/I+uX13/H07kztJe568N70fvr2AIIH2gwMEZcTlxO0EgwRIQ4bCs4F3gCR+2D23/El7n3rhep96yXuevAm81H0ZPVg9tb2YPZk9Yby9O6F6lznA+UD5Tbmfesw8X74Y//OBSILhg+0EoMUexV7FYMUlxO0EtsRDBHbEZcTfRakGMoZ/Rr9Gj4cPhw+HD4c/Rp9FgwRGwrHAgn81vYm89/xhvJR9Nb23fjI+pH7kfsO+zL6OPl++LP3R/fW9tb2s/eP+Qn82P67AW8EyAa5CBsKIguvC5wK5QeJA0X+fviG8mnsXOfC43PiFeFz4gPlg+lM7TDx3vRg9tb2ZPWG8vTufeuD6XboduiF6iXuJvN++CP+iQO5CCEOlxOkGP0ajR2NHY0dPhz9GooXlxNFEHoN2gx6DdAO2xGDFH0Wihd9FoMURRCvCx4GiQAO+2D2hvK77yXuTO1M7Uzt9O4w8b/zR/dR+6H+XwEjAzIEMgQjA/YAg/53/FH7DvsJ/Lb9iv8OAUoC9AKbAg4Bof4O+2D2MPF96zbmFeGn36ffp99z4jbmhepM7bvv3/G/8970ZPVg9kf3fvg4+Y/5j/ni+Q77Zf1fAXEGrwsMEX0WPhzXIQYluSa5JmUjWSD9GnsVDBEhDtoMQQxBDNoMeg0hDnoN2gyvC5wKKgnlB4IFJAJl/bP33/FM7YPpduiD6WnsevBk9cj6iQDOBaAJ2gwhDnoNIgvlB74DOP9R+934R/dH97P3fviP+TL6fvoy+jj5s/dk9Ybyu+9M7YXqdug25gPlwuPC4wPlNuZ26GnsMPFg9pH7ZAC+AzgFggWvBL4D9AL0Ar4DHgYbCoYPgxTKGY0dWSBlI2UjZSPXIVkgPhykGIMURRCvC4IH9wP2APL+3P0j/or/XwEjA/cDiQN9Adz9OPlR9LvvfeuD6Xbog+lp7Hrw5fXO+5sBIwevC9AORRBFECEOrwtNCPcDd//I+kf3UfSG8jDxevB68HrwMPHf8SbzUfTe9N70UfTf8SXuheo25hXhp9+n33PiXOcl7t70yPoUAG8ETQivCyEOhg9FEEUQRRCGD0UQDBHbEYMUfRakGMoZPhyNHese6x7rHo0d/Rp9FoYPTQh9Ac77G/jl9eX11vaz9934OPmP+Tj53fh++Bv41vZk9b/zhvLf8d/xJvPl9Tj53fzd/0oCbwRxBk0IoAkbCioJIwdVA4P+3fgm8yXug+k25sLjwuM25nboaey774by3vRg9uX1v/O7733rduhc51zng+lp7LvvJvOz93f8uwEjB9oM2xF9Fv0aPhyNHY0dPhzKGYoXgxSXE5cTlxN7FYoXyhn9Gj4cPhz9GooXlxOGD5wKzgVfAWX94vnW9lH0hvLf8Ybyv/Nk9bP34vl3/KH+UwCbAZsC9AJyAg4BY/8j/rb9Rf6t/5sBiQOCBcgG5QflB3EGVQMK/4/5v/NM7XboNubC48LjNuZ26H3rTO307rvvu+968N/xv/Nk9WD25fVk9VH0UfRk9Rv4CfyyAM4FrwsMEX0WPhxZIGUjBiUGJWUjWSCNHcoZfRaDFJcTtBK0ErQS2xEMEUUQRRBFEIYP0A7aDCoJ9wNF/n74v/N68CXuTO1M7fTuMPFR9N34Rf6JA+UHIguvCyILuQiCBSQCY/+O/Xf8CfwJ/Hf8DP2O/bb9DP2R+4/5R/fe9Iby9O5p7IPpduhc5zbmwuNz4nPiwuNc533ru+9R9LP3fvpC/Lb9Rf5F/kX+g/53/0MBMgTlB0EMDBF7FaQYPhzrHlkg1yFZIOsePhykGIMURRBBDE0IrwRKAl8BmwGbAvcDbwRvBIkDJAIGAAz9OPne9HrwaeyF6nbog+lp7Hrw5fVR+2QAbwSCByoJnAqcCqAJ5QevBA4BZf0y+kf33vSG8rvvJe5M7UztTO0l7vTuevDf8d/xevBM7XboA+UV4affp98V4cLjXOd967vvUfQ4+SP+mwJxBioJrwvaDHoN0A6GD0UQ2xGXE3sVpBj9GuseWSBlI2UjBiVlI9chjR2kGLQSeg0qCYIFxwKdACL/Zf4A/gD+3P22/Tn9QvzI+t34YPZR9Iby3/Hf8b/zZPWz9zL63fyt/3IC8gQjB7kIoAkbCioJggevBJ0Akfvl9XrwaeyD6XboXOeD6X3rJe4w8SbzJvOG8nrwJe5p7IXqg+l26FznduiD6WnsevBk9X76MgCCBZwKhg+0En0WihekGKQYpBiKF4oXfRaKF4oXpBjKGf0aPhw+HD4c/RqkGH0WgxQMEdoMuQhvBGQA3fwy+hv41vbl9WT1ZPXl9eX11vYb+I/5DvtC/Az93fx3/M77UfuR+0L8Of1F/t3/uwH3A84FcQbOBYkD3f+R+9b23/El7oXqduhc53bog+mF6n3rfetp7EztJe6773rwMPEw8Xrwu++777vv3/FR9LP3Ufuc/28EoAkhDrQSfRbKGY0d6x5ZIFkg6x4+HP0apBh9FnsVgxSDFJcTlxOXE7QStBLbEUUQIQ4iC4IHIwNl/uL55fWG8rvvJe5M7Uztu+/f8WT1j/mO/Z0AmwJVA/QCuwEGAAD+d/wJ/Hf8tv3Y/q3/vv/y/gD+DP3O+zL6G/hk9SbzMPH07kztfeuD6XboXOdc53bohepp7PTuMPG/82T1s/eP+Q77Qvw5/UX+vv+7ATIEIwecCiEO2xF9Fv0a6x7XIWUjBiVlI9chWSA+HMoZexW0EkUQ0A56DdoM2gxBDEEMrwsiCxsKTQjOBd0BOf0b+Cbz9O5p7IXqfetM7TDx3vR++An8Y/8kAr4DbwRvBDIEIwMkAsgA8v6r/H76fvhH9+X13vRR9L/zUfRk9WD2R/dH9+X1v/N68Gnsg+lc5zbmXOdc54Ppfesl7t/x5fV++tj+9AIeBrkIGwqcCiILIguvC3oNRRCXE4oX/RqNHeseWSDXIWUjZSPXIesePhykGJcThg9BDCoJIweCBa8E9wO+A1UDxwK7ASMAAP5R+xv43vSG8jDxevB68N/xv/Pl9bP34vkJ/EX+nQBVA84FggdNCIIHggVKAqH+fvrW9ibzu+9M7WnsaexM7fTuMPGG8ibzJvOG8jDxu+9M7X3rg+lc5zbmNuZ26H3r9O6/8zj5Rf70AiMHnAraDCEOhg8MEdsRtBKXE5cTlxODFHsVfRaKF6QYyhnKGcoZpBiKF3sVtBLQDiILIweJA3YA3P3O+zL6OPkb+Nb2ZPVR9L/zUfRk9db2G/h++H74G/jW9mD25fXW9n74Ufsj/p0AmwIyBPIEOAWvBPQCzv/O+0f3hvL07n3rg+mD6YPphep962nsTO307rvvMPHf8TDxevD07iXuTO1M7SXuMPFR9H743fzIAG8E5QevC4YPlxOKF/0ajR2NHY0dPhz9GsoZpBiKF4oXihd9Fn0WexV7FXsVgxSXE9sRhg/aDKAJHgYkAgD+4vnl9SbzevB68DDxJvNk9X74kfsj/or/FADd/3f/Cv+D/iP+AP5l/r3+OP++/1MAsgCJAOz/vf7d/H76G/jl9b/z3/H07kztfeuF6oPpg+mF6n3raewl7vTu9O568N/xv/Pl9X74fvoJ/Az9I/6c/5sBbwTlB0EMDBF9Fv0a6x5ZINch1yHXIdchWSCNHcoZfRaXE9sRDBFFEIYPhg/QDtAOIQ56DUEMGwojB/QCtv1++L/zevD07vTuu+8w8b/z1vY4+ZH7tv2K/18B9AIyBG8EvgMAAvr/Rf7d/JH7fvqP+Rv41vZk9VH0UfS/87/zJvPf8XrwJe5p7IPpdug25gPlA+UD5QPlNuZ26GnsMPFk9eL5jv1CAN0BmwLHAiMDbwRxBioJ2gxFEIMUihfKGT4cjR3rHlkgWSDrHj4cyhl9FrQSRRB6DSILKglNCOUH5QflByMHggUjA0IAjv0O+3745fW/84by3/Hf8YbyJvPe9GD2fvgO+9z9dgByAokDMgT3AyMD3QHs/zn94vlg9ibzevD07iXuJe4l7iXu9O6773rwevAw8Xrw9O5p7IPpNuYD5cLjA+V26GnsevBk9Y/5DP1CACMDzgVNCJwK2gzQDgwR2xGXE4MUfRaKF8oZyhn9Gv0a/Rr9Gv0ayhmkGIoXgxTbESEOrwsqCeUHyAbyBPQCyACh/nf8yPo4+X74G/h++N343fgb+Nb2ZPXe9GT11vbd+Mj6Qvxl/YP+rf+yAH0BuwEOAU7/d/w4+WT13/El7mnsheqD6YXqhepp7EztJe707vTu9O4l7mnsfeuF6oPphepp7PTuhvJk9d34zvu9/rsBOAW5CNoMDBF7FaQY/Ro+HD4c/Rr9GsoZyhnKGaQYpBikGIoXihd9FnsVgxSXE9sRRRAhDiILggeJA63/QvyP+Uf3ZPVR9FH03vRk9db2s/d++Dj54vky+sj6fvp++jL6MvrI+gn8jv2h/k7/Y//y/tz9q/wO+934YPa/83rwTO1964XqheqF6n3rfet9633rheqD6YPphepp7PTuMPG/82T11vYb+Dj5DvuO/YkAMgTlB0EMDBF7FcoZPhzrHlkg1yHXIdch6x6NHf0apBiKF30WexWDFJcTtBLbEQwRRRCGD3oNnArIBscCI/7i+eX1v/Pf8d/x3/Em81H0ZPXW9n74yPo5/U7/nQAOAZ0Arf+h/gD+3P0j/iP+3P3d/JH74vkb+GD23vS/8ybzJvMm84byMPH07kztfeuF6oPpduhc53bog+l96/TuhvJg9o/5Cfy2/b3+Tv8GAJsBbwTlB68Lhg+XE30WpBg+HI0dWSDXIdch1yFZII0d/RqkGHsVlxPbEUUQhg/QDnoNQQycCrkIyAZvBN0B8v6R+xv43vSG8jDxu++77/Tuu+8w8b/zYPbd+Mj6d/y2/aH+Tv/d/zIArf+D/gz9Ufs4+db2UfSG8jDxevB68N/xJvO/81H0UfQm8zDx9O5964PpXOc25lznduh967vvJvPW9uL5q/zy/n0B9wNxBrkIIgt6DYYPDBGXE3sVpBj9Go0d6x7rHuse6x6NHY0dPhz9GqQYexW0EkUQIQ6vC6AJ5QdxBq8E9AKyAEX+Cfx++o/53fgb+Nb23vS/84byJvNR9GD2fvgy+lH7QvwM/WX+IwAkAvcD8gSvBPQCBgBC/Bv4v/Mw8bvv9O6773rwMPHf8d/x3/Hf8d/xevD07kztfeuF6oXqaewl7jDxv/Ng9n74yPpl/TIAvgPlB0EMhg+0EnsVihekGP0aPhw+HI0djR0+HD4c/Rr9GsoZpBiKF4oXfRaDFNsRhg/aDBsKggevBN0BCv9C/OL5G/hH92D25fVk9d70ZPVk9WD2s/d++Dj5OPnd+N34OPky+gn8AP6t//YA3QHdAcgAof6R+3745fUm89/xevC777vvu+/07vTu9O4l7mnsfeuD6YPphep96yXuu+968N/xJvNR9OX1G/h++mX93gCvBLkIQQxFEIMUihf9Go0d6x7rHusejR0+HP0ayhmkGIoXfRZ7FYMUlxO0EgwRRRDQDtoMoAlxBkoCg/4O+xv45fVR9IbyMPF68HrwMPEm8+X1G/ji+cj6fvri+Y/5j/ky+pH73fxF/gr/vf6O/ZH7j/mz9+X1ZPXe9FH0v/OG8t/xevD07kztfeuD6VznNuY25jbmXOeD6Wns9O4w8b/zZPXW9hv4j/lR+yP+XwHyBE0IQQxFEIMUpBj9Go0dWSBZIFkgWSDrHj4c/RqkGIoXexWDFLQS2xFFEIYPIQ5BDCILKgnIBm8EfQGh/pH7fvjl9b/zhvLf8Ybyv/Pl9Rv4OPni+TL6DvvO+wz9g/7s/ygBmwEoAfr/I/4J/I/5R/dk9VH0JvMm81H03vRk9WT13vS/8zDx9O5p7IXqg+l26IPphepp7PTu3/FR9Nb2OPnO+wD+QgBKAjIEHga5CK8Lhg+0En0WpBj9Gj4cjR2NHese6x6NHY0dPhz9GsoZiheDFLQS2xFFECEO2gwiCyoJIwfyBPQC3gC9/nf84vlH92T1v/Mm87/z3vTl9WD2YPZg9mD2R/fd+Mj6Of1O/7IAKAGJAKH+zvt++GT1hvIw8bvvu++777vvu++777vvu+8l7mnshep26DbmA+UD5TbmXOeD6X3rTO307jDxv/Ng9jj5zvvY/t0BOAW5CEEM0A7bEYMUfRaKF6QYpBikGKQYpBikGKQYiheKF30WgxS0EgwR0A7aDCILuQjIBm8ESgLs/7b9kfs4+db23vS/8ybzv/NR9N70ZPVk9d70UfRR9GT1YPYb+DL6d/wj/mP/vv8K/wz9fvqz92T1v/OG8t/xMPEw8TDxMPEw8Xrwu+8l7kztfeuF6oXqhep962nsJe568N/xv/Pl9bP3j/lR+2X9zv/0AsgGIguGD5cTfRbKGf0ajR2NHY0djR2NHT4cPhw+HP0ayhmkGH0WexWDFJcT2xFFENAO2gycCuUHOAVKAjj/Qvw4+db2ZPXe9GT1YPZH9xv4G/gb+LP3s/cb+Dj5yPp3/KH+dgCbAbsBsgDY/t38DvuP+X74G/hH99b2YPZg9uX13vS/84byMPH07kztfeuD6YPphepp7PTuevCG8lH05fXW9hv4OPnI+mX9ZAC+A4IHIgvQDrQSfRakGP0aPhw+HD4cPhw+HD4cPhz9GsoZpBh9FoMUtBLbEUUQhg/QDtoMnApNCIIFJALY/pH7fvjl9VH0JvMm8ybzv/NR9FH0UfRR9FH03vTl9bP34vkJ/AD+Cv8i/2X+3fzI+t341vbl9d70UfRR9N703vRR9L/zJvPf8bvvJe5964Ppduh26Hbog+mF6kzt9O4w8Sbz3vRg9hv4j/kJ/Ar/cgJxBpwK0A60EnsVpBjKGf0aPhw+HI0djR2NHY0djR39GsoZihd7FYMUtBLbEQwRhg/QDtoMIgugCYIHcQY4BZsC8v6R+xv4ZPW/81H0v/N68H3rXOfC4wPlg+kw8d34mwKcCoYP2xGGDyILcQZyApz/d/wb+GT1hvJ68LvvhvJH98j6Of1l/TL6ZPW774XqXOd26H3r9O4w8b/zZPXl9WD2R/eP+c773fx3/OL5R/dH98j6ZABNCEUQyhnXIQYluSa5JmUjWSA+HKQYexXbEYYPQQygCU0IuQhBDAwRfRb9Gj4cyhmXE68LxwIO+970evD07vTu9O4l7mnsg+l26IXqJe5R9An8IwPlByoJIwf0Atz9j/nW9mT1v/Pf8fTufet26Hbog+kl7mD2KAGgCUEMoAn0An74TO1z4vraptW307fTt9Om1UfZp99c59/xg/6vC30WjR1ZIOsepBhFELkIIwNkAHf/fQEyBMgGGwohDoMUPhwGJWww7jRXN+40Ty5lI30WKgmh/tb2hvK77yXufeuD6Xbog+lM7eX1dgAbCgwRlxPbESIL9gDW9iXug+l26IPphep962nsJe4w8db2iv8bCpcTyhk+HP0agxQbCtz93/F26MLjp9+b3EfZptW306bV+to25r/z3QF6DXsVyhnKGZcTnAoGAEf33/El7mnsfetM7Xrw3vTc/RsKpBi5JqEyejw4Pzg/ejyhMn8oPhxFEHEGg/4b+L/zevB68FH0zvsjB5cT6x65JloqfyjXIYoXnApF/ibzherC46ff+tpH2UfZ+trC4zDxdgCGD40dBiV/KLkmWSB7FU0IUfv07sLjm9ym1ZTPlM+x0frag+k4+U0IlxPKGT4cpBhFEIIFj/kl7sLjm9yB16bVt9Om1UfZwuN68Ir/RRDrHloqoTJXN+40bDC5Jj4chg+JA9343/FM7WnsMPF++nEGgxRlI6Eyejw4P3o8VzdPLmUjgxTOBX74feun36bVlM9fzbfTKd677/cDfRYGJU8ubDBPLrkm/RrQDsgA3/ED5frasdFfzV/NsdFH2QPlv/NyAtAOihf9Gv0aexWvCyP+9O6n37fTqcjIwOu9yMAmxrfTA+Xi+XoNPhy5Jn8oBiU+HEUQBgD07qffptWUzxLLX82x0ZvcJe5yAqQYSSw4P3ZLbVIlVm1SM0h6PEks/RraDAACMvpR9N/xJvPd+N0B2gx9FuseBiV/KH8oBiU+HIYP3gDf8QPlR9mx0V/NlM+30yneTO0j/iEO/RoGJX8ouSZZIHsVzgUm8xXhsdGGw823IrEisc23hsOB133rdgC0EuseuSZ/KLkm1yF9FnEG3vQD5YHXlM8SyybGJsYSy7HRm9x26GD28gTbET4cZSMGJdchyhmGD84F8v7O+0L8Iv84BdAO/Rp/KO40FUJ2S95O3k52SxVC7jRlI4YPOf1965vclM8mxobDqci30xXh3/HHAkUQyhlZIGUjZSPrHnsVKgmR+/TuA+Up3vraR9n62qffNuZM7d703P0eBkEMRRDbEQwR2gw4BUL8UfQl7oPpNuYD5Xbo9O6z98cCIQ59Fv0aPhzKGbQSggd++mnsp9+306nIyMDtuu26yMBfzZvc9O6bAoMUBiVsMHo8FUIVQjg/7jRaKo0d2xHlB4r/4vlH99b2R/fd+N38cgKCB0EMhg9FEHoNIwfc/VH0aewD5RXhm9yb3BXhduiG8r3+QQyKF9chfyhJLFoqBiU+HEUQ9AK/8wPlptWpyOu9673IwBLL+tqF6jj5OAXQDnsVyhnKGX0W0A6CBVH7MPFc5yneR9mm1abVgdeb3APlJe44+W8Ehg+kGD4cjR3KGZcT0A6cCuUHcQblB0EM2xHKGdchWiruNHo8E0UzSBNFOD+hMmUjlxOJA7/zA+WB11/NJsaGw6nIlM+b3H3rMvrlB5cTPhxZIFkg/RqXE68L9AI4+TDxaeyD6TbmA+Vc54Xqu+9k9c773QEeBuUHcQYAAkL8YPa773boc+Ip3ineFeFc5zDxCfyCB7QSjR1lI7kmZSM+HAwRrwR++Gnsp9+m1V/NqcipyF/Ngdc25tb25QekGFoqVzcVQhNFFUI4P9o5bDAGJcoZ2xEiC84FxwJKAr4DcQacCoYPgxSkGKQYgxQhDsgGZf5k9WnsA+Wn3yneFeE25mnsZPVO/5wKexXrHmUjZSPrHn0WnAqr/Eztm9xfzcjAzbeKtIq0672pyKbVwuMw8aH+nArbEYMUgxTbEUEM9wMy+t/xheoD5RXhKd4p3qffc+J26DDxUfs4BdoMRRBFENAOQQwqCTgFIwP0Aq8ETQjaDJcT/RplI08uVzcVQjNIdksTRTg/oTK5JooXyAZg9lzn+tqx0V/NX82x0YHXp9996zj5cQZFEH0WyhnKGYoX2xGvCzgFCv/i+eX1JvPf8TDxMPGG8uX1kfsAAnEG5QcjB/IE9gB++obyg+lz4pvc+tqb3KffwuOF6ibzq/zIBkUQexV7FdsRQQwyBOL59O7C40fZsdESyxLLX8230/raXOdg9k0I/RpaKu40ejwVQjg/ejxXN2wwuSbrHooXDBGcCnEGiQObAvcDuQjQDrQSlxPbEdAOKgndATj5evCD6cLjFeGn3xXhwuOF6t/xCfxNCIMUjR3XIWUj1yE+HNsRggVH91znR9mUz6nIJsapyBLLt9Ob3HboZPVKAtoMexXKGf0aihfbERsKQwF++HrwheoD5RXhKd4p3hXhdujf8ZH7VQOgCSEOhg8hDiILyAbHAr7/Zf69/t4ArwQqCYYPihfXIUks7jTaOXo82jnuNEksWSDbEQAChvI25pvcptWx0bHRptWb3FznZPWJAwwRPhxlI7kmuSZlI+sefRbQDuUHSgK2/Tj53vQw8bvv3/Hl9Q773f8yBCMH5QeCBXYA3fh68HboFeGb3Jvcm9wp3nPidujf8c77ggV6DdsRtBLbESEOyAbO+/TuwuNH2bfTlM+Uz7HRgddz4rvvMgDbEWUjoTJ6PBNFE0UTRRVCejzuNEksZSM+HIMUIQ65CHEGyAagCdoMRRC0EpcT2xEhDuUHFABH9/Tuduhz4qffp98V4QPlheom89z9KgmXE8oZjR1ZIOsepBghDl8Bv/Nc55vct9OUz1/NX82x0UfZwuO77wz9oAmXE8oZjR2NHcoZgxR6DfIEq/xk9fTuXOdz4qffFeHC44PpMPF++KH+iQPIBk0IIwdvBJsB8v45/av8Zf04/90BcQZ6DYoX1yFaKmww7jRXN1c3oTJ/KI0dDBG+A0f3TO0D5SneR9mB10fZp9926N703gCvC4MUyhn9Gv0apBiDFIYPnAqCBb7/3fiG8iXufet96yXuJvN++Lb9JAJvBL4DUwCR+2T19O526MLjp9+b3Pra+top3sLjfeuG8n763QFNCK8LrwtNCN0B3fj07gPlKd6B17fTsdG304HXFeEl7qH+RRBZIE8u2jkVQhNFE0UTRTg/VzdsMLkmPhzbEaAJvgPIAA4BiQMjByIL0A6GD3oNoAmvBCP+5fUl7lznc+Kb3EfZR9mb3MLjfeve9L3+uQjbEaQY/RrKGYMUrwsjAL/zduin34HXsdFfzV/NlM+m1RXhTO3I+k0IlxP9GuseWSCNHaQYtBKvC8cCj/l68Hboc+Kn3xXhwuOD6TDx4vkOAR4GoAkiC6AJcQYjA3YAtv3I+jj5MvoA/jIErwuDFI0duSZsMO40VzdXN6EyWiqNHQwRMgSz92nsc+L62oHXgdf62nPiaezd+IIFDBGkGOse1yHXIesePhx9FkUQKgn2ADj5JvP07kztJe4w8Uf3jv3HAnEG5QdxBrsBUftk9fTuduhz4ine+tpH2frap98D5Wns5fWK/yMH2gyGDyEOuQi+/2T1hepz4vrat9OUz5TPsdGm1SnefevI+q8L/Rq5JmwwVzfaOdo5VzfuNE8uuSbrHn0W0A65CG8ExwJvBE0IrwvQDkUQRRB6DSoJvgMj/hv4MPF96zbmc+Jz4gPldugl7mD2+v+gCdsRpBiNHese/Rp7Fa8L3QGz9/TuNuYp3oHXptW306bV+toD5TDxq/wjB9AOlxN9Fn0WfRaDFEUQGwojAwn8ZPUl7nboA+UD5Vznfevf8Rv43fx3/50AfQHdAZsByAAi/479Zf0i/wAC8gQqCdAOfRbrHrkmTy6hMu40oTJPLrkm6x6DFBsKzv/l9SXuXOcV4SneKd7C42ns1vZDAZwK2xGKF/0ajR3rHusePhyKF9sRrwu+A877ZPXf8TDxv/NH98778v4GAK3/Zf6r/DL6R/e/8/Tuhepc58LjFeGn33PiNuZp7FH0DP2vBJwK2gyvC4IH3QHO+970TO1c5xXhm9xH2YHX+tpz4kztyPoqCX0WZSNPLu40ejw4Pzg/ejxXN6EyWipZIIoXhg+gCc4FOAXIBioJIgtBDNoMrwsbCsgGAAIJ/OX1evBp7HboNuYD5Tbmg+n07tb2MgCgCdsRfRaKF3sVDBGcCgACj/kw8Xbop99H2bfTlM+x0YHXFeFp7Nb2BgCCB9oMDBG0EpcT2xHQDqAJiQPO+ybzfesD5XPic+Jc50ztJvMb+Kv8UwBVAzgFOAX3A3ICXwHIAFMABgBTAAACggWcCgwRyhnXIX8oSSxPLkksfyjXIcoZDBGCBwD+v/OF6nPim9z62pvcwuN961H0Of04Ba8LDBF7FYoXpBikGH0W2xHaDB4GCv/d+GT13vRH9376jv0yALsB3QFDAQYAtv0y+uX13/FM7XbowuMV4SneKd6n38Ljherf8d34I/5DAQAC+v9R+2T19O526HPiKd5H2abVt9O300fZFeF967P38gQMET4cBiVJLGwwoTJsME8uSSx/KGUjPhyDFCEOnAqgCSoJGwqvC9oMeg16Da8LTQi+A6H+Mvpg9ibzMPH07iXuTO307t/xs/fY/sgGIQ6DFIoXiheDFIYPuQgkAs773vRp7MLj+tqm1abVgdf62nPig+l68Ef33fx9Aa8EcQaCB4IHcQa+A2X+YPZM7TbmFeGn36ffwuNc52nsevBk9Tj5Ufvd/GX+FAAAAjIEHgbIBnEGHgYjByoJeg2DFD4cZSNaKk8ubDBPLloqBiXrHsoZlxMiC0IAZPVM7VznwuMD5XboJe5k9bb9HgbaDLQSfRbKGf0aPhz9Gn0WRRBNCEIA4vnl9VH03vTl9Uf34vl3/GX+nP8UAGP/jv1R+zj5YPbf8WnsXOfC43PiwuNc50ztUfSR+30BOAUeBvcD3f+R+7P3v/NM7TbmKd6B17fTt9Om1ZvcXOcm850AIQ7KGWUjWipPLqEy7jTuNGwwWirXIcoZ2xEiC4IHcQZxBrkIrwvQDgwR2xFFEK8LIwdVA50A3P1++tb2JvO770ztJe6G8t34XwGcCoMU/RqNHT4cpBiDFNAOuQjIANb2aezC4/raptW306bV+tpz4oXqv/NR+/YAMgQeBuUHKgkqCcgGDgE4+Xrwduhz4ineKd4V4QPlfesw8db2Dvs5/QD+2P6JAHIC9wM4BYIF8gRVA1UDzgWcCkUQpBjXIUksoTLuNO40bDBJLH8o1yH9GtsRIwd3/N/xg+kD5XPiwuN26Lvv3fjdASoJIQ4MEZcTexWKF30WgxRFEJwKMgRF/o/5YPZk9WT1R/cy+o793f/6/2X+d/wO+4/5s/dk9d/xTO126APlwuPC41znfesm88j6QwE4Bc4FbwQAAor/d/x++CbzTO025ineR9mB14HX+tpz4mnsfviCBQwRyhnXIbkmSSxsMKEyoTJsMFoqZSM+HHsVDBF6Da8Lrwt6DUUQDBFFEHoNGwrIBjIE9AIkAp0Ajv2P+eX1hvK777vvJvPi+XICIgvbEXsVfRZ9FpcTRRBBDCMHvv9g9kztwuOb3EfZgdeB1/raFeF26LvvZPUy+gr/vgMjByoJKgnIBt0ByPom82nsNuZz4hXhFeHC43boTO3f8VH0YPZ++FH7Iv/0As4FggflB4IHyAbOBXEGoAmGD4oXWSC5JkksTy5PLkksWiq5JmUjPhyXE7kIZf3f8Xboc+Ip3qffA+Vp7N70CfybAXEGIguGD5cTfRaKF4MUhg8qCSQCDvtR9LvvTO0l7jDx3vQb+OL5Mvri+Y/5j/k4+db2v/O7733rNuYV4SneKd6n3zbmJe5k9ZH7Y/99ASQCJAJ9AXf/kfvl9SXuNuYp3kfZt9O304HXp9+F6kf39AJ6DYoX6x65Jk8uoTKhMqEySSy5JuseihdFEJwKggeCBxsKeg1FEAwRhg96DUEMnAobCioJggdvBBQAMvpR9LvvTO307lH0Cfw4BXoNgxSKF6QYpBiKF4MUhg+5CDIA1vZM7QPlm9yB16bVgdeb3HPig+l68GD2Dvu+//cDIwflB8gG9AIM/eX1Je425qffm9z62inec+Jc533r9O4w8VH0s/dR+/L+xwIeBoIHggdxBjgFOAWCB9oMgxSNHQYlWipPLmwwbDBsMGwwTy5/KFkgihfaDEMBYPYl7oPpduhp7Iby3fgj/koCHgacCoYPlxOKF6QYpBh7FQwRrwvyBAz9YPYm84byUfTW9hv43fg4+Tj53fjd+N34OPl++GD2JvP07oPpA+XC48Lj\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "torch.manual_seed(42)\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    gen = generate_audio_sample(model, 8*16000, maxp=True).flatten()\n",
    "    gen = mu_law_decoding(gen, 256).cpu()\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(gen)\n",
    "ipd.Audio(gen.numpy(), rate=16000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed1b9ff3",
   "metadata": {},
   "source": [
    "We can also save it as WAV:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "e321ab94",
   "metadata": {},
   "outputs": [],
   "source": [
    "wavfile.write(\"overfitting.wav\", 16000, gen.flatten().numpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6ecc54e",
   "metadata": {},
   "source": [
    "We can save this model together with the optimizer state as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3b5515a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save({\n",
    "    \"model_state\": model.state_dict(),\n",
    "    \"optimizer_state\": optimizer.state_dict(),\n",
    "}, \"./models/ym-overfitting.pt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b73b055a",
   "metadata": {},
   "source": [
    "Then, we can load the model and the optimizer from their `state_dict`s similarly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3a7c0bcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "checkpoint = torch.load(\"./models/ym-overfitting.pt\", map_location=device)\n",
    "model.load_state_dict(checkpoint[\"model_state\"])\n",
    "optimizer.load_state_dict(checkpoint[\"optimizer_state\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cec145e8",
   "metadata": {},
   "source": [
    "# Full Dataset Training\n",
    "\n",
    "Since training on the full dataset takes a lot of time, we won't demonstrate it in this notebook. The training script `train.py` is available in the repository, see `README.md` for details."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f8ada8d",
   "metadata": {},
   "source": [
    "## Loading a Pre-Trained Model\n",
    "\n",
    "The following function will load a pre-trained model. You should have downloaded the pre-trained models using `download_data.sh` script. All pre-trained models should be available in `models` folder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9a49b61c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_model(model, name, _epoch=None):\n",
    "    global epoch, device, model_name, model_folder\n",
    "    model_name = name\n",
    "    model_folder = \"./models/\" + name\n",
    "\n",
    "    with open(os.path.join(model_folder, \"train_loss.txt\"), 'r') as f:\n",
    "        train = [float(i.strip()) for i in f.readlines()]\n",
    "\n",
    "    with open(os.path.join(model_folder, \"validation_loss.txt\"), 'r') as f:\n",
    "        valid = [float(i.strip()) for i in f.readlines()]\n",
    "\n",
    "    plt.title(label=\"Training Loss\")\n",
    "    plt.xlabel(\"Epoch\")\n",
    "    plt.ylabel(\"Loss\")\n",
    "    plt.plot(train)\n",
    "    plt.plot(valid)\n",
    "\n",
    "    epoch = len(train) if _epoch is None else _epoch\n",
    "    checkpoint_filename = os.path.join(model_folder, f\"epoch{epoch:04d}.pt\")\n",
    "    print(\"Loading model:\", checkpoint_filename)\n",
    "    checkpoint = torch.load(checkpoint_filename, map_location=device)\n",
    "\n",
    "    return model.load_state_dict(checkpoint[\"model_state\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6183b4bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total parameters: 4302744\n",
      "Parameters to be learned: 4302744\n"
     ]
    }
   ],
   "source": [
    "model = SaShiMi(\n",
    "    input_dim=1,\n",
    "    hidden_dim=64,\n",
    "    output_dim=256,\n",
    "    state_dim=64,\n",
    "    sequence_length=16000*8,\n",
    "    block_count=8,\n",
    "    encoder=Embedding(256, 64),\n",
    ").to(device)\n",
    "\n",
    "print(\"Total parameters:\", sum([i.nelement() for i in model.parameters()]))\n",
    "print(\"Parameters to be learned:\", sum([i.nelement() if i.requires_grad else 0 for i in model.parameters()]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebd69d4b",
   "metadata": {},
   "source": [
    "The following code block will load the pre-trained model and plot the losses.\n",
    "\n",
    "Here's how we scheduled the learning rate manually throughout the training process:\n",
    "- AdamW optimizer was used with a learning rate of 0.001.\n",
    "- Starting at epoch 60, the learning rate was reduced to 0.00025.\n",
    "- Starting at epoch 99, the learning rate was reduced to 0.000125.\n",
    "- Starting at epoch 140, the learning rate was reduced to 0.00004."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "74b31c7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model: ../models/ym-8l/epoch0160.pt\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "load_model(model, \"ym-8l\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2de3e83",
   "metadata": {},
   "source": [
    "Now, let's sample from this model that has been trained on the full YouTube Mix dataset.\n",
    "\n",
    "The following code block will generate 32 samples at once and save them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e217a3bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/128000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seed = 42\n",
    "torch.manual_seed(seed)\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    gen = generate_audio_sample(model, 8*16000, batch_size=32)\n",
    "    gen = mu_law_decoding(gen, 256).cpu()\n",
    "\n",
    "dirname = \"outputs/\" + model_name\n",
    "if not os.path.exists(dirname):\n",
    "    os.makedirs(dirname)\n",
    "\n",
    "for i, g in enumerate(gen):\n",
    "    wavfile.write(f\"{dirname}/epoch{epoch:04d}-seed{seed}-{i}.wav\", 16000, g.numpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ccd7f88",
   "metadata": {},
   "source": [
    "Let's listen to the generated samples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "16ec62dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_index = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "521161f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected = gen[selected_index]\n",
    "print(\"Sample\", selected_index)\n",
    "selected_index = (selected_index + 1) % gen.size(dim=0)\n",
    "plt.figure()\n",
    "plt.plot(selected)\n",
    "ipd.Audio(selected.numpy(), rate=16000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b219cf7",
   "metadata": {},
   "source": [
    "You can run the previous block repeatedly to switch to the next sample.\n",
    "\n",
    "Since the audio files cannot be saved inside a Jupyter Notebook unlike images, we provide the samples separately. **You can listen to our samples [in this link](https://necrashter.github.io/sashimi-796).**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5484b480",
   "metadata": {},
   "source": [
    "# Reproducing the Results\n",
    "\n",
    "By sampling from the model in the previous section, we have seen some qualitative results. You can compare our samples with the official samples provided on [this webpage](https://hazyresearch.stanford.edu/sashimi-examples/).\n",
    "\n",
    "To get quantitative results, we need to compute negative log likelihood (NLL) values on the test dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c34ea37",
   "metadata": {},
   "source": [
    "## NLL Test\n",
    "\n",
    "Note that [CrossEntropyLoss](https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html) simply calculates the NLL by applying softmax internally:\n",
    "\n",
    "$$\n",
    "l_n = - \\log \\frac{\\exp(x_{n,y_n})}{\\sum_{c=1}^C \\exp(x_{n,c})}\n",
    "$$\n",
    "\n",
    "PyTorch uses natural log by default. We convert this to NLL in bits by dividing the result by $\\log(2)$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "09598dba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "111"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_dataset = YoutubeMixDataset(\"./datasets/youtube-mix/test\", duration=8, device=device)\n",
    "test_dataloader = DataLoader(test_dataset, batch_size=1, shuffle=False)\n",
    "\n",
    "def test_nll(model):\n",
    "    model.eval()\n",
    "    criterion = torch.nn.CrossEntropyLoss()\n",
    "    with torch.no_grad():\n",
    "        nll = 0.0\n",
    "        for x, y in tqdm(test_dataloader, leave=False):\n",
    "            y_hat = model(x)\n",
    "            nll += criterion(y_hat.view(-1, 256), y.view(-1))\n",
    "        nll /= len(test_dataloader)\n",
    "\n",
    "        print(\"Average NLL:\", nll.item())\n",
    "        print(\"Average NLL in base 2:\", (nll / torch.tensor(2.0).log()).item())\n",
    "        print(\"Average NLL converted to probability:\", (-nll).exp().item())\n",
    "\n",
    "len(test_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8a7f0eb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/111 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average NLL: 0.9182284474372864\n",
      "Average NLL in base 2: 1.3247236013412476\n",
      "Average NLL converted to probability: 0.3992256820201874\n"
     ]
    }
   ],
   "source": [
    "test_nll(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11da2d3c",
   "metadata": {},
   "source": [
    "For comparison, the test NLL provided in the paper is **1.294** in base 2. Our results are close, albeit slightly worse. However, please note that they train this model longer in the paper (**600K steps** on page 19, which would be about 400 epochs in our setup). We could only train it for 160 epochs. We believe it's reasonable to expect that our model can achieve the same or better NLL value with longer training and better hyperparameter choices. For example, they might have used a different optimizer and a better learning rate schedule."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbefe729",
   "metadata": {},
   "source": [
    "# Generating Longer Samples\n",
    "\n",
    "Although the model was trained on 8-second chunks, it can generate samples of unbounded length thanks to being an auto-regressive model. In this section, we will generate 64-second long samples and save them. Again, we are unable to save them inside the notebook but we provided them separately. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c6764064",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1024000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seed = 0\n",
    "torch.manual_seed(seed)\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    gen = generate_audio_sample(model, 64*16000, batch_size=16)\n",
    "    gen = mu_law_decoding(gen, 256).cpu()\n",
    "\n",
    "dirname = \"outputs/\" + model_name\n",
    "if not os.path.exists(dirname):\n",
    "    os.makedirs(dirname)\n",
    "\n",
    "for i, g in enumerate(gen):\n",
    "    wavfile.write(f\"{dirname}/long-epoch{epoch:04d}-seed{seed}-{i}.wav\", 16000, g.numpy())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c85e69f2",
   "metadata": {},
   "source": [
    "# Challenges\n",
    "\n",
    "In this section, we list the challenges we faced while implementing the paper.\n",
    "\n",
    "The challenges we overcame after version 1 submission:\n",
    "1. The authors don't give detailed information about the encoder and decoder layers, i.e., what happens before/after the SaShiMi model. In version 1, we used linear layers to transform 1D input to 64 dimensions (encoder) and then 64 dimensional output to 256 dimensional probability output. When we switched from a linear layer to [embedding layer](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) in the encoder, we observed significant improvements both in NLL and sample quality.\n",
    "2. We didn't use [mu-law](https://en.wikipedia.org/wiki/%CE%9C-law_algorithm) encoding in our version 1 submission. The authors clearly communicated this in Table 1, but we forgot to implement it due to our unfamiliarity with the audio domain.\n",
    "3. Parameter tying was incorrect in our version 1 submission.\n",
    "    - In particular, this was the version 1 submission:\n",
    "        - $\\Lambda$, $p$: Shared\n",
    "        - $B$: Separate\n",
    "        - $C$: Shared\n",
    "    - This is the updated version:\n",
    "        - $\\Lambda$, $p$: Shared\n",
    "        - $B$: Shared\n",
    "        - $C$: Separate\n",
    "    - The updated version reflects the details given in Appendix C.2.1. In our version, $dt$ is also shared but learned unlike what the paper describes. As mentioned previously, our model learns $dt$ because they didn't provide the initial value for $dt$. We tried learning a separate $dt$ for each dimension [in this PR](https://github.com/necrashter/SaShiMi-796/pull/17), but this results in a separate $A$ matrix for each dimension, which causes a significant slowdown. Also we didn't observe any noteworthy benefit from learning a separate $dt$ for each dimension.\n",
    "\n",
    "General difficulties we dealt with:\n",
    "1. The details of S4 are not given in the SaShiMi paper. We had to go back to the S4's paper and implement it from scratch, which took the first few weeks of our time. It was like implementing two papers at once.\n",
    "2. While describing the model structure in Appendix C.2.1, the authors provide the \"model dimension\", but it's unclear whether this term refers to the hidden dimension of the signal or the state dimensions (size of $x$ computed by $A$ and $B$ matrices). See the Ablation notebook for more information about this.\n",
    "3. The authors give the learning rate for SaShiMi model, but they don't tell the name of the optimizer. We used `AdamW` in all of our experiments on Youtube Mix.\n",
    "4. We had to implement the Cauchy kernel computation in PyKeOps. The naive implementation would lead to out-of-memory errors on large context sizes (as it's the case in Youtube Mix dataset)."
   ]
  }
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