{"cells": [{"cell_type": "markdown", "id": "829d77e5", "metadata": {"papermill": {"duration": 0.139908, "end_time": "2021-12-04T15:58:00.173929", "exception": false, "start_time": "2021-12-04T15:58:00.034021", "status": "completed"}, "tags": []}, "source": ["\n", "# Tutorial 5: Transformers and Multi-Head Attention\n", "\n", "* **Author:** Phillip Lippe\n", "* **License:** CC BY-SA\n", "* **Generated:** 2021-12-04T16:52:50.580472\n", "\n", "In this tutorial, we will discuss one of the most impactful architectures of the last 2 years: the Transformer model.\n", "Since the paper Attention Is All You Need by Vaswani et al. had been published in 2017,\n", "the Transformer architecture has continued to beat benchmarks in many domains, most importantly in Natural Language Processing.\n", "Transformers with an incredible amount of parameters can generate long, convincing essays, and opened up new application fields of AI.\n", "As the hype of the Transformer architecture seems not to come to an end in the next years,\n", "it is important to understand how it works, and have implemented it yourself, which we will do in this notebook.\n", "This notebook is part of a lecture series on Deep Learning at the University of Amsterdam.\n", "The full list of tutorials can be found at https://uvadlc-notebooks.rtfd.io.\n", "\n", "\n", "---\n", "Open in [![Open In Colab](data:image/png;base64,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){height=\"20px\" width=\"117px\"}](https://colab.research.google.com/github/PytorchLightning/lightning-tutorials/blob/publication/.notebooks/course_UvA-DL/05-transformers-and-MH-attention.ipynb)\n", "\n", "Give us a \u2b50 [on Github](https://www.github.com/PytorchLightning/pytorch-lightning/)\n", "| Check out [the documentation](https://pytorch-lightning.readthedocs.io/en/latest/)\n", "| Join us [on Slack](https://join.slack.com/t/pytorch-lightning/shared_invite/zt-pw5v393p-qRaDgEk24~EjiZNBpSQFgQ)"]}, {"cell_type": "markdown", "id": "4bd97ecd", "metadata": {"papermill": {"duration": 0.139186, "end_time": "2021-12-04T15:58:00.454648", "exception": false, "start_time": "2021-12-04T15:58:00.315462", "status": "completed"}, "tags": []}, "source": ["## Setup\n", "This notebook requires some packages besides pytorch-lightning."]}, {"cell_type": "code", "execution_count": 1, "id": "6df421c0", "metadata": {"colab": {}, "colab_type": "code", "execution": {"iopub.execute_input": "2021-12-04T15:58:00.739046Z", "iopub.status.busy": "2021-12-04T15:58:00.738548Z", "iopub.status.idle": "2021-12-04T15:58:03.208213Z", "shell.execute_reply": "2021-12-04T15:58:03.207638Z"}, "id": "LfrJLKPFyhsK", "lines_to_next_cell": 0, "papermill": {"duration": 2.615354, "end_time": "2021-12-04T15:58:03.208358", "exception": false, "start_time": "2021-12-04T15:58:00.593004", "status": "completed"}, "tags": []}, "outputs": [], "source": ["! pip install --quiet \"torchmetrics>=0.3\" \"pytorch-lightning>=1.3\" \"torchvision\" \"torch>=1.6, <1.9\" \"matplotlib\" \"seaborn\""]}, {"cell_type": "markdown", "id": "a5126640", "metadata": {"papermill": {"duration": 0.138671, "end_time": "2021-12-04T15:58:03.486977", "exception": false, "start_time": "2021-12-04T15:58:03.348306", "status": "completed"}, "tags": []}, "source": ["<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/hGZ6wa07Vak\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "Despite the huge success of Transformers in NLP, we will _not_ include the NLP domain in our notebook here.\n", "There are many courses at the University of Amsterdam that focus on Natural Language Processing\n", "and take a closer look at the application of the Transformer architecture in NLP\n", "([NLP2](https://studiegids.uva.nl/xmlpages/page/2020-2021/zoek-vak/vak/79628),\n", "[Advanced Topics in Computational Semantics](https://studiegids.uva.nl/xmlpages/page/2020-2021/zoek-vak/vak/80162)).\n", "Furthermore, and most importantly, there is so much more to the Transformer architecture.\n", "NLP is the domain the Transformer architecture has been originally proposed for and had the greatest impact on,\n", "but it also accelerated research in other domains, recently even [Computer Vision](https://arxiv.org/abs/2010.11929).\n", "Thus, we focus here on what makes the Transformer and self-attention so powerful in general.\n", "In a second notebook, we will look at Vision Transformers, i.e. Transformers for image classification\n", "([link to notebook](https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/tutorial15/Vision_Transformer.html)).\n", "\n", "Below, we import our standard libraries."]}, {"cell_type": "code", "execution_count": 2, "id": "31508898", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:03.772463Z", "iopub.status.busy": "2021-12-04T15:58:03.771979Z", "iopub.status.idle": "2021-12-04T15:58:05.871634Z", "shell.execute_reply": "2021-12-04T15:58:05.871226Z"}, "papermill": {"duration": 2.246581, "end_time": "2021-12-04T15:58:05.871763", "exception": false, "start_time": "2021-12-04T15:58:03.625182", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["/tmp/ipykernel_1492/2689201066.py:34: DeprecationWarning: `set_matplotlib_formats` is deprecated since IPython 7.23, directly use `matplotlib_inline.backend_inline.set_matplotlib_formats()`\n", "  set_matplotlib_formats(\"svg\", \"pdf\")  # For export\n", "Global seed set to 42\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Device: cuda:0\n"]}], "source": ["# Standard libraries\n", "import math\n", "import os\n", "import urllib.request\n", "from functools import partial\n", "from urllib.error import HTTPError\n", "\n", "# Plotting\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "# PyTorch Lightning\n", "import pytorch_lightning as pl\n", "import seaborn as sns\n", "\n", "# PyTorch\n", "import torch\n", "import torch.nn as nn\n", "import torch.nn.functional as F\n", "import torch.optim as optim\n", "import torch.utils.data as data\n", "\n", "# Torchvision\n", "import torchvision\n", "from IPython.display import set_matplotlib_formats\n", "from pytorch_lightning.callbacks import ModelCheckpoint\n", "from torchvision import transforms\n", "from torchvision.datasets import CIFAR100\n", "from tqdm.notebook import tqdm\n", "\n", "plt.set_cmap(\"cividis\")\n", "%matplotlib inline\n", "set_matplotlib_formats(\"svg\", \"pdf\")  # For export\n", "matplotlib.rcParams[\"lines.linewidth\"] = 2.0\n", "sns.reset_orig()\n", "\n", "# Path to the folder where the datasets are/should be downloaded (e.g. CIFAR10)\n", "DATASET_PATH = os.environ.get(\"PATH_DATASETS\", \"data/\")\n", "# Path to the folder where the pretrained models are saved\n", "CHECKPOINT_PATH = os.environ.get(\"PATH_CHECKPOINT\", \"saved_models/Transformers/\")\n", "\n", "# Setting the seed\n", "pl.seed_everything(42)\n", "\n", "# Ensure that all operations are deterministic on GPU (if used) for reproducibility\n", "torch.backends.cudnn.determinstic = True\n", "torch.backends.cudnn.benchmark = False\n", "\n", "device = torch.device(\"cuda:0\") if torch.cuda.is_available() else torch.device(\"cpu\")\n", "print(\"Device:\", device)"]}, {"cell_type": "markdown", "id": "940525e1", "metadata": {"papermill": {"duration": 0.144686, "end_time": "2021-12-04T15:58:06.158145", "exception": false, "start_time": "2021-12-04T15:58:06.013459", "status": "completed"}, "tags": []}, "source": ["Two pre-trained models are downloaded below.\n", "Make sure to have adjusted your `CHECKPOINT_PATH` before running this code if not already done."]}, {"cell_type": "code", "execution_count": 3, "id": "a7a72c1a", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:06.442497Z", "iopub.status.busy": "2021-12-04T15:58:06.442012Z", "iopub.status.idle": "2021-12-04T15:58:06.793103Z", "shell.execute_reply": "2021-12-04T15:58:06.792670Z"}, "papermill": {"duration": 0.496404, "end_time": "2021-12-04T15:58:06.793239", "exception": false, "start_time": "2021-12-04T15:58:06.296835", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial6/ReverseTask.ckpt...\n", "Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial6/SetAnomalyTask.ckpt...\n"]}], "source": ["# Github URL where saved models are stored for this tutorial\n", "base_url = \"https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial6/\"\n", "# Files to download\n", "pretrained_files = [\"ReverseTask.ckpt\", \"SetAnomalyTask.ckpt\"]\n", "\n", "# Create checkpoint path if it doesn't exist yet\n", "os.makedirs(CHECKPOINT_PATH, exist_ok=True)\n", "\n", "# For each file, check whether it already exists. If not, try downloading it.\n", "for file_name in pretrained_files:\n", "    file_path = os.path.join(CHECKPOINT_PATH, file_name)\n", "    if \"/\" in file_name:\n", "        os.makedirs(file_path.rsplit(\"/\", 1)[0], exist_ok=True)\n", "    if not os.path.isfile(file_path):\n", "        file_url = base_url + file_name\n", "        print(\"Downloading %s...\" % file_url)\n", "        try:\n", "            urllib.request.urlretrieve(file_url, file_path)\n", "        except HTTPError as e:\n", "            print(\n", "                \"Something went wrong. Please try to download the file manually,\"\n", "                \" or contact the author with the full output including the following error:\\n\",\n", "                e,\n", "            )"]}, {"cell_type": "markdown", "id": "1e17404e", "metadata": {"papermill": {"duration": 0.140163, "end_time": "2021-12-04T15:58:07.075728", "exception": false, "start_time": "2021-12-04T15:58:06.935565", "status": "completed"}, "tags": []}, "source": ["## The Transformer architecture\n", "\n", "In the first part of this notebook, we will implement the Transformer architecture by hand.\n", "As the architecture is so popular, there already exists a Pytorch module `nn.Transformer`\n", "([documentation](https://pytorch.org/docs/stable/generated/torch.nn.Transformer.html))\n", "and a [tutorial](https://pytorch.org/tutorials/beginner/transformer_tutorial.html)\n", "on how to use it for next token prediction.\n", "However, we will implement it here ourselves, to get through to the smallest details.\n", "\n", "There are of course many more tutorials out there about attention and Transformers.\n", "Below, we list a few that are worth exploring if you are interested in the topic\n", "and might want yet another perspective on the topic after this one:\n", "\n", "* [Transformer: A Novel Neural Network Architecture for Language Understanding\n", "(Jakob Uszkoreit, 2017)](https://ai.googleblog.com/2017/08/transformer-novel-neural-network.html) - The original Google blog post about the Transformer paper, focusing on the application in machine translation.\n", "* [The Illustrated Transformer (Jay Alammar, 2018)](http://jalammar.github.io/illustrated-transformer/) - A very popular and great blog post intuitively explaining the Transformer architecture with many nice visualizations.\n", "The focus is on NLP.\n", "* [Attention?\n", "Attention!\n", "(Lilian Weng, 2018)](https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html) - A nice blog post summarizing attention mechanisms in many domains including vision.\n", "* [Illustrated: Self-Attention (Raimi Karim, 2019)](https://towardsdatascience.com/illustrated-self-attention-2d627e33b20a) - A nice visualization of the steps of self-attention.\n", "Recommended going through if the explanation below is too abstract for you.\n", "* [The Transformer family (Lilian Weng, 2020)](https://lilianweng.github.io/lil-log/2020/04/07/the-transformer-family.html) - A very detailed blog post reviewing more variants of Transformers besides the original one."]}, {"cell_type": "markdown", "id": "c7a1d465", "metadata": {"papermill": {"duration": 0.14018, "end_time": "2021-12-04T15:58:07.355646", "exception": false, "start_time": "2021-12-04T15:58:07.215466", "status": "completed"}, "tags": []}, "source": ["### What is Attention?\n", "\n", "The attention mechanism describes a recent new group of layers in neural networks that has attracted\n", "a lot of interest in the past few years, especially in sequence tasks.\n", "There are a lot of different possible definitions of \"attention\" in the literature,\n", "but the one we will use here is the following: _the attention mechanism describes a weighted average\n", "of (sequence) elements with the weights dynamically computed based on an input query and elements' keys_.\n", "So what does this exactly mean?\n", "The goal is to take an average over the features of multiple elements.\n", "However, instead of weighting each element equally, we want to weight them depending on their actual values.\n", "In other words, we want to dynamically decide on which inputs we want to \"attend\" more than others.\n", "In particular, an attention mechanism has usually four parts we need to specify:\n", "\n", "* **Query**: The query is a feature vector that describes what we are looking for in the sequence, i.e. what would we maybe want to pay attention to.\n", "* **Keys**: For each input element, we have a key which is again a feature vector.\n", "This feature vector roughly describes what the element is \"offering\", or when it might be important.\n", "The keys should be designed such that we can identify the elements we want to pay attention to based on the query.\n", "* **Values**: For each input element, we also have a value vector.\n", "This feature vector is the one we want to average over.\n", "* **Score function**: To rate which elements we want to pay attention to, we need to specify a score function $f_{attn}$.\n", "The score function takes the query and a key as input, and output the score/attention weight of the query-key pair.\n", "It is usually implemented by simple similarity metrics like a dot product, or a small MLP.\n", "\n", "\n", "The weights of the average are calculated by a softmax over all score function outputs.\n", "Hence, we assign those value vectors a higher weight whose corresponding key is most similar to the query.\n", "If we try to describe it with pseudo-math, we can write:\n", "\n", "$$\n", "\\alpha_i = \\frac{\\exp\\left(f_{attn}\\left(\\text{key}_i, \\text{query}\\right)\\right)}{\\sum_j \\exp\\left(f_{attn}\\left(\\text{key}_j, \\text{query}\\right)\\right)}, \\hspace{5mm} \\text{out} = \\sum_i \\alpha_i \\cdot \\text{value}_i\n", "$$\n", "\n", "Visually, we can show the attention over a sequence of words as follows:\n", "\n", "<center width=\"100%\" style=\"padding:25px\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/attention_example.svg\" width=\"750px\"></center>\n", "\n", "For every word, we have one key and one value vector.\n", "The query is compared to all keys with a score function (in this case the dot product) to determine the weights.\n", "The softmax is not visualized for simplicity.\n", "Finally, the value vectors of all words are averaged using the attention weights.\n", "\n", "Most attention mechanisms differ in terms of what queries they use, how the key and value vectors are defined,\n", "and what score function is used.\n", "The attention applied inside the Transformer architecture is called **self-attention**.\n", "In self-attention, each sequence element provides a key, value, and query.\n", "For each element, we perform an attention layer where based on its query,\n", "we check the similarity of the all sequence elements' keys, and returned a different,\n", "averaged value vector for each element.\n", "We will now go into a bit more detail by first looking at the specific implementation of the attention mechanism\n", "which is in the Transformer case the scaled dot product attention."]}, {"cell_type": "markdown", "id": "d9697f03", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.139603, "end_time": "2021-12-04T15:58:07.635701", "exception": false, "start_time": "2021-12-04T15:58:07.496098", "status": "completed"}, "tags": []}, "source": ["### Scaled Dot Product Attention\n", "\n", "The core concept behind self-attention is the scaled dot product attention.\n", "Our goal is to have an attention mechanism with which any element in a sequence can attend to any other while\n", "still being efficient to compute.\n", "The dot product attention takes as input a set of queries\n", "$Q\\in\\mathbb{R}^{T\\times d_k}$, keys $K\\in\\mathbb{R}^{T\\times d_k}$\n", "and values $V\\in\\mathbb{R}^{T\\times d_v}$ where $T$ is the sequence length,\n", "and $d_k$ and $d_v$ are the hidden dimensionality for queries/keys and values respectively.\n", "For simplicity, we neglect the batch dimension for now.\n", "The attention value from element $i$ to $j$ is based on its similarity of the query $Q_i$ and key $K_j$,\n", "using the dot product as the similarity metric.\n", "In math, we calculate the dot product attention as follows:\n", "\n", "$$\\text{Attention}(Q,K,V)=\\text{softmax}\\left(\\frac{QK^T}{\\sqrt{d_k}}\\right)V$$\n", "\n", "The matrix multiplication $QK^T$ performs the dot product for every possible pair of queries and keys,\n", "resulting in a matrix of the shape $T\\times T$.\n", "Each row represents the attention logits for a specific element $i$ to all other elements in the sequence.\n", "On these, we apply a softmax and multiply with the value vector to obtain a weighted mean\n", "(the weights being determined by the attention).\n", "Another perspective on this attention mechanism offers the computation graph which is visualized below\n", "(figure credit - [Vaswani et al., 2017](https://arxiv.org/abs/1706.03762)).\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/scaled_dot_product_attn.svg\" width=\"210px\"></center>\n", "\n", "One aspect we haven't discussed yet is the scaling factor of $1/\\sqrt{d_k}$.\n", "This scaling factor is crucial to maintain an appropriate variance of attention values after initialization.\n", "Remember that we intialize our layers with the intention of having equal variance throughout the model, and hence,\n", "$Q$ and $K$ might also have a variance close to $1$.\n", "However, performing a dot product over two vectors with a variance $\\sigma$ results\n", "in a scalar having $d_k$-times higher variance:\n", "\n", "$$q_i \\sim \\mathcal{N}(0,\\sigma), k_i \\sim \\mathcal{N}(0,\\sigma) \\to \\text{Var}\\left(\\sum_{i=1}^{d_k} q_i\\cdot k_i\\right) = \\sigma\\cdot d_k$$\n", "\n", "\n", "If we do not scale down the variance back to $\\sigma$, the softmax over the logits will already saturate\n", "to $1$ for one random element and $0$ for all others.\n", "The gradients through the softmax will be close to zero so that we can't learn the parameters appropriately.\n", "\n", "The block `Mask (opt.\n", ")` in the diagram above represents the optional masking of specific entries in the attention matrix.\n", "This is for instance used if we stack multiple sequences with different lengths into a batch.\n", "To still benefit from parallelization in PyTorch, we pad the sentences to the same length and mask out the padding\n", "tokens during the calculation of the attention values.\n", "This is usually done by setting the respective attention logits to a very low value.\n", "\n", "After we have discussed the details of the scaled dot product attention block, we can write a function below\n", "which computes the output features given the triple of queries, keys, and values:"]}, {"cell_type": "code", "execution_count": 4, "id": "f65c1f5d", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:07.923041Z", "iopub.status.busy": "2021-12-04T15:58:07.922459Z", "iopub.status.idle": "2021-12-04T15:58:07.924745Z", "shell.execute_reply": "2021-12-04T15:58:07.925122Z"}, "papermill": {"duration": 0.148521, "end_time": "2021-12-04T15:58:07.925250", "exception": false, "start_time": "2021-12-04T15:58:07.776729", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def scaled_dot_product(q, k, v, mask=None):\n", "    d_k = q.size()[-1]\n", "    attn_logits = torch.matmul(q, k.transpose(-2, -1))\n", "    attn_logits = attn_logits / math.sqrt(d_k)\n", "    if mask is not None:\n", "        attn_logits = attn_logits.masked_fill(mask == 0, -9e15)\n", "    attention = F.softmax(attn_logits, dim=-1)\n", "    values = torch.matmul(attention, v)\n", "    return values, attention"]}, {"cell_type": "markdown", "id": "10dc2e7e", "metadata": {"papermill": {"duration": 0.139995, "end_time": "2021-12-04T15:58:08.204876", "exception": false, "start_time": "2021-12-04T15:58:08.064881", "status": "completed"}, "tags": []}, "source": ["Note that our code above supports any additional dimensionality in front of the sequence length\n", "so that we can also use it for batches.\n", "However, for a better understanding, let's generate a few random queries, keys, and value vectors,\n", "and calculate the attention outputs:"]}, {"cell_type": "code", "execution_count": 5, "id": "c417bca9", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:08.490138Z", "iopub.status.busy": "2021-12-04T15:58:08.489665Z", "iopub.status.idle": "2021-12-04T15:58:08.498288Z", "shell.execute_reply": "2021-12-04T15:58:08.497857Z"}, "papermill": {"duration": 0.15228, "end_time": "2021-12-04T15:58:08.498402", "exception": false, "start_time": "2021-12-04T15:58:08.346122", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Global seed set to 42\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Q\n", " tensor([[ 0.3367,  0.1288],\n", "        [ 0.2345,  0.2303],\n", "        [-1.1229, -0.1863]])\n", "K\n", " tensor([[ 2.2082, -0.6380],\n", "        [ 0.4617,  0.2674],\n", "        [ 0.5349,  0.8094]])\n", "V\n", " tensor([[ 1.1103, -1.6898],\n", "        [-0.9890,  0.9580],\n", "        [ 1.3221,  0.8172]])\n", "Values\n", " tensor([[ 0.5698, -0.1520],\n", "        [ 0.5379, -0.0265],\n", "        [ 0.2246,  0.5556]])\n", "Attention\n", " tensor([[0.4028, 0.2886, 0.3086],\n", "        [0.3538, 0.3069, 0.3393],\n", "        [0.1303, 0.4630, 0.4067]])\n"]}], "source": ["seq_len, d_k = 3, 2\n", "pl.seed_everything(42)\n", "q = torch.randn(seq_len, d_k)\n", "k = torch.randn(seq_len, d_k)\n", "v = torch.randn(seq_len, d_k)\n", "values, attention = scaled_dot_product(q, k, v)\n", "print(\"Q\\n\", q)\n", "print(\"K\\n\", k)\n", "print(\"V\\n\", v)\n", "print(\"Values\\n\", values)\n", "print(\"Attention\\n\", attention)"]}, {"cell_type": "markdown", "id": "a9d22885", "metadata": {"papermill": {"duration": 0.141388, "end_time": "2021-12-04T15:58:08.781187", "exception": false, "start_time": "2021-12-04T15:58:08.639799", "status": "completed"}, "tags": []}, "source": ["Before continuing, make sure you can follow the calculation of the specific values here, and also check it by hand.\n", "It is important to fully understand how the scaled dot product attention is calculated."]}, {"cell_type": "markdown", "id": "09bc5c7a", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.141201, "end_time": "2021-12-04T15:58:09.064542", "exception": false, "start_time": "2021-12-04T15:58:08.923341", "status": "completed"}, "tags": []}, "source": ["### Multi-Head Attention\n", "\n", "The scaled dot product attention allows a network to attend over a sequence.\n", "However, often there are multiple different aspects a sequence element wants to attend to,\n", "and a single weighted average is not a good option for it.\n", "This is why we extend the attention mechanisms to multiple heads,\n", "i.e. multiple different query-key-value triplets on the same features.\n", "Specifically, given a query, key, and value matrix, we transform those into $h$ sub-queries, sub-keys,\n", "and sub-values, which we pass through the scaled dot product attention independently.\n", "Afterward, we concatenate the heads and combine them with a final weight matrix.\n", "Mathematically, we can express this operation as:\n", "\n", "$$\n", "\\begin{split}\n", "    \\text{Multihead}(Q,K,V) & = \\text{Concat}(\\text{head}_1,...,\\text{head}_h)W^{O}\\\\\n", "    \\text{where } \\text{head}_i & = \\text{Attention}(QW_i^Q,KW_i^K, VW_i^V)\n", "\\end{split}\n", "$$\n", "\n", "We refer to this as Multi-Head Attention layer with the learnable parameters\n", "$W_{1...h}^{Q}\\in\\mathbb{R}^{D\\times d_k}$,\n", "$W_{1...h}^{K}\\in\\mathbb{R}^{D\\times d_k}$,\n", "$W_{1...h}^{V}\\in\\mathbb{R}^{D\\times d_v}$,\n", "and $W^{O}\\in\\mathbb{R}^{h\\cdot d_k\\times d_{out}}$ ($D$ being the input dimensionality).\n", "Expressed in a computational graph, we can visualize it as below\n", "(figure credit - [Vaswani et al., 2017](https://arxiv.org/abs/1706.03762)).\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/multihead_attention.svg\" width=\"230px\"></center>\n", "\n", "How are we applying a Multi-Head Attention layer in a neural network,\n", "where we don't have an arbitrary query, key, and value vector as input?\n", "Looking at the computation graph above, a simple but effective implementation is to set the current\n", "feature map in a NN, $X\\in\\mathbb{R}^{B\\times T\\times d_{\\text{model}}}$, as $Q$, $K$ and $V$\n", "($B$ being the batch size, $T$ the sequence length, $d_{\\text{model}}$ the hidden dimensionality of $X$).\n", "The consecutive weight matrices $W^{Q}$, $W^{K}$, and $W^{V}$ can transform $X$ to the corresponding\n", "feature vectors that represent the queries, keys, and values of the input.\n", "Using this approach, we can implement the Multi-Head Attention module below."]}, {"cell_type": "code", "execution_count": 6, "id": "9a857f4f", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:09.357800Z", "iopub.status.busy": "2021-12-04T15:58:09.357266Z", "iopub.status.idle": "2021-12-04T15:58:09.359052Z", "shell.execute_reply": "2021-12-04T15:58:09.358641Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.152505, "end_time": "2021-12-04T15:58:09.359159", "exception": false, "start_time": "2021-12-04T15:58:09.206654", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class MultiheadAttention(nn.Module):\n", "    def __init__(self, input_dim, embed_dim, num_heads):\n", "        super().__init__()\n", "        assert embed_dim % num_heads == 0, \"Embedding dimension must be 0 modulo number of heads.\"\n", "\n", "        self.embed_dim = embed_dim\n", "        self.num_heads = num_heads\n", "        self.head_dim = embed_dim // num_heads\n", "\n", "        # Stack all weight matrices 1...h together for efficiency\n", "        # Note that in many implementations you see \"bias=False\" which is optional\n", "        self.qkv_proj = nn.Linear(input_dim, 3 * embed_dim)\n", "        self.o_proj = nn.Linear(embed_dim, embed_dim)\n", "\n", "        self._reset_parameters()\n", "\n", "    def _reset_parameters(self):\n", "        # Original Transformer initialization, see PyTorch documentation\n", "        nn.init.xavier_uniform_(self.qkv_proj.weight)\n", "        self.qkv_proj.bias.data.fill_(0)\n", "        nn.init.xavier_uniform_(self.o_proj.weight)\n", "        self.o_proj.bias.data.fill_(0)\n", "\n", "    def forward(self, x, mask=None, return_attention=False):\n", "        batch_size, seq_length, embed_dim = x.size()\n", "        qkv = self.qkv_proj(x)\n", "\n", "        # Separate Q, K, V from linear output\n", "        qkv = qkv.reshape(batch_size, seq_length, self.num_heads, 3 * self.head_dim)\n", "        qkv = qkv.permute(0, 2, 1, 3)  # [Batch, Head, SeqLen, Dims]\n", "        q, k, v = qkv.chunk(3, dim=-1)\n", "\n", "        # Determine value outputs\n", "        values, attention = scaled_dot_product(q, k, v, mask=mask)\n", "        values = values.permute(0, 2, 1, 3)  # [Batch, SeqLen, Head, Dims]\n", "        values = values.reshape(batch_size, seq_length, embed_dim)\n", "        o = self.o_proj(values)\n", "\n", "        if return_attention:\n", "            return o, attention\n", "        else:\n", "            return o"]}, {"cell_type": "markdown", "id": "b56973f7", "metadata": {"papermill": {"duration": 0.142069, "end_time": "2021-12-04T15:58:09.642785", "exception": false, "start_time": "2021-12-04T15:58:09.500716", "status": "completed"}, "tags": []}, "source": ["One crucial characteristic of the multi-head attention is that it is permutation-equivariant with respect to its inputs.\n", "This means that if we switch two input elements in the sequence, e.g. $X_1\\leftrightarrow X_2$\n", "(neglecting the batch dimension for now), the output is exactly the same besides the elements 1 and 2 switched.\n", "Hence, the multi-head attention is actually looking at the input not as a sequence, but as a set of elements.\n", "This property makes the multi-head attention block and the Transformer architecture so powerful and widely applicable!\n", "But what if the order of the input is actually important for solving the task, like language modeling?\n", "The answer is to encode the position in the input features, which we will take a closer look at later\n", "(topic _Positional encodings_ below).\n", "\n", "Before moving on to creating the Transformer architecture, we can compare the self-attention operation\n", "with our other common layer competitors for sequence data: convolutions and recurrent neural networks.\n", "Below you can find a table by [Vaswani et al.\n", "(2017)](https://arxiv.org/abs/1706.03762) on the complexity per layer, the number of sequential operations,\n", "and maximum path length.\n", "The complexity is measured by the upper bound of the number of operations to perform, while the maximum path\n", "length represents the maximum number of steps a forward or backward signal has to traverse to reach any other position.\n", "The lower this length, the better gradient signals can backpropagate for long-range dependencies.\n", "Let's take a look at the table below:\n", "\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/comparison_conv_rnn.svg\" width=\"600px\"></center>\n", "\n", "$n$ is the sequence length, $d$ is the representation dimension and $k$ is the kernel size of convolutions.\n", "In contrast to recurrent networks, the self-attention layer can parallelize all its operations making it much faster\n", "to execute for smaller sequence lengths.\n", "However, when the sequence length exceeds the hidden dimensionality, self-attention becomes more expensive than RNNs.\n", "One way of reducing the computational cost for long sequences is by restricting the self-attention to a neighborhood\n", "of inputs to attend over, denoted by $r$.\n", "Nevertheless, there has been recently a lot of work on more efficient Transformer architectures that still allow long\n", "dependencies, of which you can find an overview in the paper by [Tay et al.\n", "(2020)](https://arxiv.org/abs/2009.06732) if interested."]}, {"cell_type": "markdown", "id": "c9ea3bc6", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.142611, "end_time": "2021-12-04T15:58:09.927152", "exception": false, "start_time": "2021-12-04T15:58:09.784541", "status": "completed"}, "tags": []}, "source": ["### Transformer Encoder\n", "\n", "<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/QdTgJ85E6YA\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "\n", "Next, we will look at how to apply the multi-head attention blog inside the Transformer architecture.\n", "Originally, the Transformer model was designed for machine translation.\n", "Hence, it got an encoder-decoder structure where the encoder takes as input the sentence in the original language\n", "and generates an attention-based representation.\n", "On the other hand, the decoder attends over the encoded information and generates the translated sentence\n", "in an autoregressive manner, as in a standard RNN.\n", "While this structure is extremely useful for Sequence-to-Sequence tasks with the necessity of autoregressive decoding,\n", "we will focus here on the encoder part.\n", "Many advances in NLP have been made using pure encoder-based Transformer models (if interested, models include the\n", "[BERT](https://arxiv.org/abs/1810.04805)-family,\n", "the [Vision Transformer](https://arxiv.org/abs/2010.11929), and more),\n", "and in our tutorial, we will also mainly focus on the encoder part.\n", "If you have understood the encoder architecture, the decoder is a very small step to implement as well.\n", "The full Transformer architecture looks as follows\n", "(figure credit - [Vaswani et al., 2017](https://arxiv.org/abs/1706.03762)).\n", ":\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/transformer_architecture.svg\" width=\"400px\"></center>\n", "\n", "The encoder consists of $N$ identical blocks that are applied in sequence.\n", "Taking as input $x$, it is first passed through a Multi-Head Attention block as we have implemented above.\n", "The output is added to the original input using a residual connection,\n", "and we apply a consecutive Layer Normalization on the sum.\n", "Overall, it calculates $\\text{LayerNorm}(x+\\text{Multihead}(x,x,x))$\n", "($x$ being $Q$, $K$ and $V$ input to the attention layer).\n", "The residual connection is crucial in the Transformer architecture for two reasons:\n", "\n", "1.\n", "Similar to ResNets, Transformers are designed to be very deep.\n", "Some models contain more than 24 blocks in the encoder.\n", "Hence, the residual connections are crucial for enabling a smooth gradient flow through the model.\n", "2.\n", "Without the residual connection, the information about the original sequence is lost.\n", "Remember that the Multi-Head Attention layer ignores the position of elements in a sequence,\n", "and can only learn it based on the input features.\n", "Removing the residual connections would mean that this information is lost after the first attention layer\n", "(after initialization), and with a randomly initialized query and key vector,\n", "the output vectors for position $i$ has no relation to its original input.\n", "All outputs of the attention are likely to represent similar/same information,\n", "and there is no chance for the model to distinguish which information came from which input element.\n", "An alternative option to residual connection would be to fix at least one head to focus on its original input,\n", "but this is very inefficient and does not have the benefit of the improved gradient flow.\n", "\n", "The Layer Normalization also plays an important role in the Transformer architecture as it enables faster\n", "training and provides small regularization.\n", "Additionally, it ensures that the features are in a similar magnitude among the elements in the sequence.\n", "We are not using Batch Normalization because it depends on the batch size which is often small with Transformers\n", "(they require a lot of GPU memory), and BatchNorm has shown to perform particularly bad in language\n", "as the features of words tend to have a much higher variance (there are many, very rare words\n", "which need to be considered for a good distribution estimate).\n", "\n", "Additionally to the Multi-Head Attention, a small fully connected feed-forward network is added to the model,\n", "which is applied to each position separately and identically.\n", "Specifically, the model uses a Linear$\\to$ReLU$\\to$Linear MLP.\n", "The full transformation including the residual connection can be expressed as:\n", "\n", "$$\n", "\\begin{split}\n", "    \\text{FFN}(x) & = \\max(0, xW_1+b_1)W_2 + b_2\\\\\n", "    x & = \\text{LayerNorm}(x + \\text{FFN}(x))\n", "\\end{split}\n", "$$\n", "\n", "This MLP adds extra complexity to the model and allows transformations on each sequence element separately.\n", "You can imagine as this allows the model to \"post-process\" the new information added\n", "by the previous Multi-Head Attention, and prepare it for the next attention block.\n", "Usually, the inner dimensionality of the MLP is 2-8$\\times$ larger than $d_{\\text{model}}$,\n", "i.e. the dimensionality of the original input $x$.\n", "The general advantage of a wider layer instead of a narrow, multi-layer MLP is the faster, parallelizable execution.\n", "\n", "Finally, after looking at all parts of the encoder architecture, we can start implementing it below.\n", "We first start by implementing a single encoder block.\n", "Additionally to the layers described above, we will add dropout layers in the MLP and on the output\n", "of the MLP and Multi-Head Attention for regularization."]}, {"cell_type": "code", "execution_count": 7, "id": "23103d12", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:10.224411Z", "iopub.status.busy": "2021-12-04T15:58:10.223932Z", "iopub.status.idle": "2021-12-04T15:58:10.225971Z", "shell.execute_reply": "2021-12-04T15:58:10.225565Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.157144, "end_time": "2021-12-04T15:58:10.226077", "exception": false, "start_time": "2021-12-04T15:58:10.068933", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class EncoderBlock(nn.Module):\n", "    def __init__(self, input_dim, num_heads, dim_feedforward, dropout=0.0):\n", "        \"\"\"\n", "        Args:\n", "            input_dim: Dimensionality of the input\n", "            num_heads: Number of heads to use in the attention block\n", "            dim_feedforward: Dimensionality of the hidden layer in the MLP\n", "            dropout: Dropout probability to use in the dropout layers\n", "        \"\"\"\n", "        super().__init__()\n", "\n", "        # Attention layer\n", "        self.self_attn = MultiheadAttention(input_dim, input_dim, num_heads)\n", "\n", "        # Two-layer MLP\n", "        self.linear_net = nn.Sequential(\n", "            nn.Linear(input_dim, dim_feedforward),\n", "            nn.Dropout(dropout),\n", "            nn.ReLU(inplace=True),\n", "            nn.Linear(dim_feedforward, input_dim),\n", "        )\n", "\n", "        # Layers to apply in between the main layers\n", "        self.norm1 = nn.LayerNorm(input_dim)\n", "        self.norm2 = nn.LayerNorm(input_dim)\n", "        self.dropout = nn.Dropout(dropout)\n", "\n", "    def forward(self, x, mask=None):\n", "        # Attention part\n", "        attn_out = self.self_attn(x, mask=mask)\n", "        x = x + self.dropout(attn_out)\n", "        x = self.norm1(x)\n", "\n", "        # MLP part\n", "        linear_out = self.linear_net(x)\n", "        x = x + self.dropout(linear_out)\n", "        x = self.norm2(x)\n", "\n", "        return x"]}, {"cell_type": "markdown", "id": "7820dae1", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.143711, "end_time": "2021-12-04T15:58:10.516987", "exception": false, "start_time": "2021-12-04T15:58:10.373276", "status": "completed"}, "tags": []}, "source": ["Based on this block, we can implement a module for the full Transformer encoder.\n", "Additionally to a forward function that iterates through the sequence of encoder blocks,\n", "we also provide a function called `get_attention_maps`.\n", "The idea of this function is to return the attention probabilities for all Multi-Head Attention blocks in the encoder.\n", "This helps us in understanding, and in a sense, explaining the model.\n", "However, the attention probabilities should be interpreted with a grain of salt as it does not necessarily\n", "reflect the true interpretation of the model (there is a series of papers about this,\n", "including [Attention is not Explanation](https://arxiv.org/abs/1902.10186)\n", "and [Attention is not not Explanation](https://arxiv.org/abs/1908.04626))."]}, {"cell_type": "code", "execution_count": 8, "id": "5619cdd3", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:10.816718Z", "iopub.status.busy": "2021-12-04T15:58:10.816231Z", "iopub.status.idle": "2021-12-04T15:58:10.818205Z", "shell.execute_reply": "2021-12-04T15:58:10.817797Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.158399, "end_time": "2021-12-04T15:58:10.818313", "exception": false, "start_time": "2021-12-04T15:58:10.659914", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class TransformerEncoder(nn.Module):\n", "    def __init__(self, num_layers, **block_args):\n", "        super().__init__()\n", "        self.layers = nn.ModuleList([EncoderBlock(**block_args) for _ in range(num_layers)])\n", "\n", "    def forward(self, x, mask=None):\n", "        for layer in self.layers:\n", "            x = layer(x, mask=mask)\n", "        return x\n", "\n", "    def get_attention_maps(self, x, mask=None):\n", "        attention_maps = []\n", "        for layer in self.layers:\n", "            _, attn_map = layer.self_attn(x, mask=mask, return_attention=True)\n", "            attention_maps.append(attn_map)\n", "            x = layer(x)\n", "        return attention_maps"]}, {"cell_type": "markdown", "id": "8a328d53", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.142344, "end_time": "2021-12-04T15:58:11.102765", "exception": false, "start_time": "2021-12-04T15:58:10.960421", "status": "completed"}, "tags": []}, "source": ["### Positional encoding\n", "\n", "We have discussed before that the Multi-Head Attention block is permutation-equivariant,\n", "and cannot distinguish whether an input comes before another one in the sequence or not.\n", "In tasks like language understanding, however, the position is important for interpreting the input words.\n", "The position information can therefore be added via the input features.\n", "We could learn a embedding for every possible position, but this would not generalize to a dynamical\n", "input sequence length.\n", "Hence, the better option is to use feature patterns that the network can identify from the features\n", "and potentially generalize to larger sequences.\n", "The specific pattern chosen by Vaswani et al.\n", "are sine and cosine functions of different frequencies, as follows:\n", "\n", "$$\n", "PE_{(pos,i)} = \\begin{cases}\n", "    \\sin\\left(\\frac{pos}{10000^{i/d_{\\text{model}}}}\\right) & \\text{if}\\hspace{3mm} i \\text{ mod } 2=0\\\\\n", "    \\cos\\left(\\frac{pos}{10000^{(i-1)/d_{\\text{model}}}}\\right) & \\text{otherwise}\\\\\n", "\\end{cases}\n", "$$\n", "\n", "$PE_{(pos,i)}$ represents the position encoding at position $pos$ in the sequence, and hidden dimensionality $i$.\n", "These values, concatenated for all hidden dimensions, are added to the original input features\n", "(in the Transformer visualization above, see \"Positional encoding\"), and constitute the position information.\n", "We distinguish between even ($i \\text{ mod } 2=0$) and uneven ($i \\text{ mod } 2=1$)\n", "hidden dimensionalities where we apply a sine/cosine respectively.\n", "The intuition behind this encoding is that you can represent $PE_{(pos+k,:)}$ as a linear function\n", "of $PE_{(pos,:)}$, which might allow the model to easily attend to relative positions.\n", "The wavelengths in different dimensions range from $2\\pi$ to $10000\\cdot 2\\pi$.\n", "\n", "The positional encoding is implemented below.\n", "The code is taken from the [PyTorch tutorial](https://pytorch.org/tutorials/beginner/transformer_tutorial.html#define-the-model)\n", "about Transformers on NLP and adjusted for our purposes."]}, {"cell_type": "code", "execution_count": 9, "id": "9a4179be", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:11.394604Z", "iopub.status.busy": "2021-12-04T15:58:11.394124Z", "iopub.status.idle": "2021-12-04T15:58:11.395735Z", "shell.execute_reply": "2021-12-04T15:58:11.396116Z"}, "papermill": {"duration": 0.151358, "end_time": "2021-12-04T15:58:11.396243", "exception": false, "start_time": "2021-12-04T15:58:11.244885", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class PositionalEncoding(nn.Module):\n", "    def __init__(self, d_model, max_len=5000):\n", "        \"\"\"\n", "        Args\n", "            d_model: Hidden dimensionality of the input.\n", "            max_len: Maximum length of a sequence to expect.\n", "        \"\"\"\n", "        super().__init__()\n", "\n", "        # Create matrix of [SeqLen, HiddenDim] representing the positional encoding for max_len inputs\n", "        pe = torch.zeros(max_len, d_model)\n", "        position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1)\n", "        div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model))\n", "        pe[:, 0::2] = torch.sin(position * div_term)\n", "        pe[:, 1::2] = torch.cos(position * div_term)\n", "        pe = pe.unsqueeze(0)\n", "\n", "        # register_buffer => Tensor which is not a parameter, but should be part of the modules state.\n", "        # Used for tensors that need to be on the same device as the module.\n", "        # persistent=False tells PyTorch to not add the buffer to the state dict (e.g. when we save the model)\n", "        self.register_buffer(\"pe\", pe, persistent=False)\n", "\n", "    def forward(self, x):\n", "        x = x + self.pe[:, : x.size(1)]\n", "        return x"]}, {"cell_type": "markdown", "id": "ab85f000", "metadata": {"papermill": {"duration": 0.143264, "end_time": "2021-12-04T15:58:11.687431", "exception": false, "start_time": "2021-12-04T15:58:11.544167", "status": "completed"}, "tags": []}, "source": ["To understand the positional encoding, we can visualize it below.\n", "We will generate an image of the positional encoding over hidden dimensionality and position in a sequence.\n", "Each pixel, therefore, represents the change of the input feature we perform to encode the specific position.\n", "Let's do it below."]}, {"cell_type": "code", "execution_count": 10, "id": "f3c3e710", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:11.979041Z", "iopub.status.busy": "2021-12-04T15:58:11.978542Z", "iopub.status.idle": "2021-12-04T15:58:12.357315Z", "shell.execute_reply": "2021-12-04T15:58:12.357708Z"}, "papermill": {"duration": 0.527144, "end_time": "2021-12-04T15:58:12.357871", "exception": false, "start_time": "2021-12-04T15:58:11.830727", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"222.954375pt\" version=\"1.1\" viewBox=\"0 0 442.082438 222.954375\" width=\"442.082438pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:58:12.126505</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 222.954375 \n", "L 442.082438 222.954375 \n", "L 442.082438 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g id=\"patch_2\">\n", "    <path d=\"M 40.603125 185.398125 \n", "L 366.763125 185.398125 \n", "L 366.763125 22.318125 \n", "L 40.603125 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p1331aa580f)\">\n", "    <image height=\"164\" id=\"image12608288ac\" transform=\"scale(1 -1)translate(0 -164)\" width=\"327\" x=\"40.603125\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.398125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_1\">\n", "    <g id=\"xtick_1\">\n", "     <g id=\"line2d_1\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L 0 3.5 \n", "\" id=\"mf5f2eca3c2\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_1\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(37.421875 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_2\">\n", "     <g id=\"line2d_2\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"71.180625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_2\">\n", "      <!-- 10 -->\n", "      <g transform=\"translate(64.818125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_3\">\n", "     <g id=\"line2d_3\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"105.155625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_3\">\n", "      <!-- 20 -->\n", "      <g transform=\"translate(98.793125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" id=\"DejaVuSans-32\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_4\">\n", "     <g id=\"line2d_4\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.130625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_4\">\n", "      <!-- 30 -->\n", "      <g transform=\"translate(132.768125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" id=\"DejaVuSans-33\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_5\">\n", "     <g id=\"line2d_5\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"173.105625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_5\">\n", "      <!-- 40 -->\n", "      <g transform=\"translate(166.743125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" id=\"DejaVuSans-34\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_6\">\n", "     <g id=\"line2d_6\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.080625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_6\">\n", "      <!-- 50 -->\n", "      <g transform=\"translate(200.718125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" id=\"DejaVuSans-35\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_7\">\n", "     <g id=\"line2d_7\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"241.055625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_7\">\n", "      <!-- 60 -->\n", "      <g transform=\"translate(234.693125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" id=\"DejaVuSans-36\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_8\">\n", "     <g id=\"line2d_8\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"275.030625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_8\">\n", "      <!-- 70 -->\n", "      <g transform=\"translate(268.668125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" id=\"DejaVuSans-37\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_9\">\n", "     <g id=\"line2d_9\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"309.005625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_9\">\n", "      <!-- 80 -->\n", "      <g transform=\"translate(302.643125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" id=\"DejaVuSans-38\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_10\">\n", "     <g id=\"line2d_10\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"342.980625\" xlink:href=\"#mf5f2eca3c2\" y=\"185.398125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_10\">\n", "      <!-- 90 -->\n", "      <g transform=\"translate(336.618125 199.996562)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" id=\"DejaVuSans-39\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_11\">\n", "     <!-- Position in sequence -->\n", "     <g transform=\"translate(152.387813 213.674688)scale(0.1 -0.1)\">\n", "      <defs>\n", "       <path d=\"M 1259 4147 \n", "L 1259 2394 \n", "L 2053 2394 \n", "Q 2494 2394 2734 2622 \n", "Q 2975 2850 2975 3272 \n", "Q 2975 3691 2734 3919 \n", "Q 2494 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 2053 4666 \n", "Q 2838 4666 3239 4311 \n", "Q 3641 3956 3641 3272 \n", "Q 3641 2581 3239 2228 \n", "Q 2838 1875 2053 1875 \n", "L 1259 1875 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-50\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" id=\"DejaVuSans-6f\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" id=\"DejaVuSans-73\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-69\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" id=\"DejaVuSans-74\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-6e\" transform=\"scale(0.015625)\"/>\n", "       <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "M 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 -1331 \n", "L 2906 -1331 \n", "L 2906 525 \n", "z\n", "\" id=\"DejaVuSans-71\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" id=\"DejaVuSans-75\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" id=\"DejaVuSans-63\" transform=\"scale(0.015625)\"/>\n", "      </defs>\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"421.082031\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"448.865234\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"512.244141\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"544.03125\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"596.130859\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"657.654297\" xlink:href=\"#DejaVuSans-71\"/>\n", "      <use x=\"721.130859\" xlink:href=\"#DejaVuSans-75\"/>\n", "      <use x=\"784.509766\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"846.033203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"909.412109\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"964.392578\" xlink:href=\"#DejaVuSans-65\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_2\">\n", "    <g id=\"ytick_1\">\n", "     <g id=\"line2d_11\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L -3.5 0 \n", "\" id=\"mdf4e267ff5\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mdf4e267ff5\" y=\"22.318125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_12\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(27.240625 26.117344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_2\">\n", "     <g id=\"line2d_12\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mdf4e267ff5\" y=\"52.895625\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_13\">\n", "      <!-- 10 -->\n", "      <g transform=\"translate(20.878125 56.694844)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_3\">\n", "     <g id=\"line2d_13\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mdf4e267ff5\" y=\"86.870625\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_14\">\n", "      <!-- 20 -->\n", "      <g transform=\"translate(20.878125 90.669844)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_4\">\n", "     <g id=\"line2d_14\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mdf4e267ff5\" y=\"120.845625\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_15\">\n", "      <!-- 30 -->\n", "      <g transform=\"translate(20.878125 124.644844)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_5\">\n", "     <g id=\"line2d_15\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mdf4e267ff5\" y=\"154.820625\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_16\">\n", "      <!-- 40 -->\n", "      <g transform=\"translate(20.878125 158.619844)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_17\">\n", "     <!-- Hidden dimension -->\n", "     <g transform=\"translate(14.798438 149.090937)rotate(-90)scale(0.1 -0.1)\">\n", "      <defs>\n", "       <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 2753 \n", "L 3553 2753 \n", "L 3553 4666 \n", "L 4184 4666 \n", "L 4184 0 \n", "L 3553 0 \n", "L 3553 2222 \n", "L 1259 2222 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-48\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" id=\"DejaVuSans-64\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" id=\"DejaVuSans-6d\" transform=\"scale(0.015625)\"/>\n", "      </defs>\n", "      <use xlink:href=\"#DejaVuSans-48\"/>\n", "      <use x=\"75.195312\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"102.978516\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"166.455078\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"229.931641\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"291.455078\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"354.833984\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"386.621094\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"450.097656\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"477.880859\" xlink:href=\"#DejaVuSans-6d\"/>\n", "      <use x=\"575.292969\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"636.816406\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"700.195312\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"752.294922\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"780.078125\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"841.259766\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_3\">\n", "    <path d=\"M 40.603125 185.398125 \n", "L 40.603125 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_4\">\n", "    <path d=\"M 366.763125 185.398125 \n", "L 366.763125 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_5\">\n", "    <path d=\"M 40.603125 185.398125 \n", "L 366.763125 185.398125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_6\">\n", "    <path d=\"M 40.603125 22.318125 \n", "L 366.763125 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_18\">\n", "    <!-- Positional encoding over hidden dimensions -->\n", "    <g transform=\"translate(71.633438 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-6c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2906 1791 \n", "Q 2906 2416 2648 2759 \n", "Q 2391 3103 1925 3103 \n", "Q 1463 3103 1205 2759 \n", "Q 947 2416 947 1791 \n", "Q 947 1169 1205 825 \n", "Q 1463 481 1925 481 \n", "Q 2391 481 2648 825 \n", "Q 2906 1169 2906 1791 \n", "z\n", "M 3481 434 \n", "Q 3481 -459 3084 -895 \n", "Q 2688 -1331 1869 -1331 \n", "Q 1566 -1331 1297 -1286 \n", "Q 1028 -1241 775 -1147 \n", "L 775 -588 \n", "Q 1028 -725 1275 -790 \n", "Q 1522 -856 1778 -856 \n", "Q 2344 -856 2625 -561 \n", "Q 2906 -266 2906 331 \n", "L 2906 616 \n", "Q 2728 306 2450 153 \n", "Q 2172 0 1784 0 \n", "Q 1141 0 747 490 \n", "Q 353 981 353 1791 \n", "Q 353 2603 747 3093 \n", "Q 1141 3584 1784 3584 \n", "Q 2172 3584 2450 3431 \n", "Q 2728 3278 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 434 \n", "z\n", "\" id=\"DejaVuSans-67\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 191 3500 \n", "L 800 3500 \n", "L 1894 563 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2284 0 \n", "L 1503 0 \n", "L 191 3500 \n", "z\n", "\" id=\"DejaVuSans-76\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" id=\"DejaVuSans-72\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-68\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-50\"/>\n", "     <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "     <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"389.294922\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"450.574219\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"478.357422\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"510.144531\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"571.667969\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"635.046875\" xlink:href=\"#DejaVuSans-63\"/>\n", "     <use x=\"690.027344\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"751.208984\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"814.685547\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"842.46875\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"905.847656\" xlink:href=\"#DejaVuSans-67\"/>\n", "     <use x=\"969.324219\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1001.111328\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1062.292969\" xlink:href=\"#DejaVuSans-76\"/>\n", "     <use x=\"1121.472656\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1182.996094\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"1224.109375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1255.896484\" xlink:href=\"#DejaVuSans-68\"/>\n", "     <use x=\"1319.275391\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1347.058594\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1410.535156\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1474.011719\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1535.535156\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1598.914062\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1630.701172\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1694.177734\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1721.960938\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"1819.373047\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1880.896484\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1944.275391\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"1996.375\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"2024.158203\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"2085.339844\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"2148.71875\" xlink:href=\"#DejaVuSans-73\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_2\">\n", "   <g id=\"patch_7\">\n", "    <path d=\"M 389.083125 185.398125 \n", "L 397.237125 185.398125 \n", "L 397.237125 22.318125 \n", "L 389.083125 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g id=\"patch_8\">\n", "    <path clip-path=\"url(#paae788ae78)\" d=\"M 389.083125 185.398125 \n", "L 389.083125 184.761094 \n", "L 389.083125 22.955156 \n", "L 389.083125 22.318125 \n", "L 397.237125 22.318125 \n", "L 397.237125 22.955156 \n", "L 397.237125 184.761094 \n", "L 397.237125 185.398125 \n", "L 397.237125 185.398125 \n", "z\n", "\" style=\"fill:#ffffff;stroke:#ffffff;stroke-linejoin:miter;stroke-width:0.01;\"/>\n", "   </g>\n", "   <image height=\"163\" id=\"imageca2a10cd47\" transform=\"scale(1 -1)translate(0 -163)\" width=\"8\" x=\"389\" xlink:href=\"data:image/png;base64,\n", "iVBORw0KGgoAAAANSUhEUgAAAAgAAACjCAYAAAC31F+mAAAA/klEQVR4nO2WSw6DMAwF409yjd6v998BSRfdeypZWNCWbZ7GY8cg5CmP1YLHh0p03twEAh8QwvPmnUrkHfKSJYTT21Qc9dA4IAYBJmiWYMOoBLZJBLhOJmjaQTGAkj3bpnYnB7gsHUDAfdDR44CRJC4ttslrf76D0RwK2lQHh6a0cp0IPoBAC1NBMGiz0aAEAzRJLsGS6UEZ3SYGsIRmPyDsIEgAh4oSgh9zIvCo4y5kzRn/T4anrTWfc8aBtWKGH8eRJKBDQYl8ID+oK9xFASE/hwLJvMMtJNFh3/dkACV/hHALyTxh27ZkiTwBJfG9+Lf5DhRIXoFwC8mvaPMFhZj7x7gJVREAAAAASUVORK5CYII=\" y=\"-21\"/>\n", "   <g id=\"matplotlib.axis_3\"/>\n", "   <g id=\"matplotlib.axis_4\">\n", "    <g id=\"ytick_6\">\n", "     <g id=\"line2d_16\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L 3.5 0 \n", "\" id=\"m1aadf11d86\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"165.013822\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_19\">\n", "      <!-- \u22120.75 -->\n", "      <g transform=\"translate(404.237125 168.813041)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 678 2272 \n", "L 4684 2272 \n", "L 4684 1741 \n", "L 678 1741 \n", "L 678 2272 \n", "z\n", "\" id=\"DejaVuSans-2212\" transform=\"scale(0.015625)\"/>\n", "        <path d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" id=\"DejaVuSans-2e\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"147.412109\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"179.199219\" xlink:href=\"#DejaVuSans-37\"/>\n", "       <use x=\"242.822266\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_7\">\n", "     <g id=\"line2d_17\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"144.628723\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_20\">\n", "      <!-- \u22120.50 -->\n", "      <g transform=\"translate(404.237125 148.427942)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"147.412109\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"179.199219\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"242.822266\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_8\">\n", "     <g id=\"line2d_18\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"124.243623\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_21\">\n", "      <!-- \u22120.25 -->\n", "      <g transform=\"translate(404.237125 128.042842)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"147.412109\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"179.199219\" xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"242.822266\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_9\">\n", "     <g id=\"line2d_19\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"103.858524\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_22\">\n", "      <!-- 0.00 -->\n", "      <g transform=\"translate(404.237125 107.657742)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"159.033203\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_10\">\n", "     <g id=\"line2d_20\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"83.473424\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_23\">\n", "      <!-- 0.25 -->\n", "      <g transform=\"translate(404.237125 87.272643)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"159.033203\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_11\">\n", "     <g id=\"line2d_21\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"63.088324\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_24\">\n", "      <!-- 0.50 -->\n", "      <g transform=\"translate(404.237125 66.887543)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"159.033203\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_12\">\n", "     <g id=\"line2d_22\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"42.703225\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_25\">\n", "      <!-- 0.75 -->\n", "      <g transform=\"translate(404.237125 46.502443)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-37\"/>\n", "       <use x=\"159.033203\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_13\">\n", "     <g id=\"line2d_23\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"397.237125\" xlink:href=\"#m1aadf11d86\" y=\"22.318125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_26\">\n", "      <!-- 1.00 -->\n", "      <g transform=\"translate(404.237125 26.117344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"159.033203\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"LineCollection_1\"/>\n", "   <g id=\"patch_9\">\n", "    <path d=\"M 389.083125 185.398125 \n", "L 389.083125 184.761094 \n", "L 389.083125 22.955156 \n", "L 389.083125 22.318125 \n", "L 397.237125 22.318125 \n", "L 397.237125 22.955156 \n", "L 397.237125 184.761094 \n", "L 397.237125 185.398125 \n", "z\n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"p1331aa580f\">\n", "   <rect height=\"163.08\" width=\"326.16\" x=\"40.603125\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"paae788ae78\">\n", "   <rect height=\"163.08\" width=\"8.154\" x=\"389.083125\" y=\"22.318125\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 576x216 with 2 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["encod_block = PositionalEncoding(d_model=48, max_len=96)\n", "pe = encod_block.pe.squeeze().T.cpu().numpy()\n", "\n", "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(8, 3))\n", "pos = ax.imshow(pe, cmap=\"RdGy\", extent=(1, pe.shape[1] + 1, pe.shape[0] + 1, 1))\n", "fig.colorbar(pos, ax=ax)\n", "ax.set_xlabel(\"Position in sequence\")\n", "ax.set_ylabel(\"Hidden dimension\")\n", "ax.set_title(\"Positional encoding over hidden dimensions\")\n", "ax.set_xticks([1] + [i * 10 for i in range(1, 1 + pe.shape[1] // 10)])\n", "ax.set_yticks([1] + [i * 10 for i in range(1, 1 + pe.shape[0] // 10)])\n", "plt.show()"]}, {"cell_type": "markdown", "id": "d5cc9a34", "metadata": {"papermill": {"duration": 0.154874, "end_time": "2021-12-04T15:58:12.659676", "exception": false, "start_time": "2021-12-04T15:58:12.504802", "status": "completed"}, "tags": []}, "source": ["You can clearly see the sine and cosine waves with different wavelengths that encode the position\n", "in the hidden dimensions.\n", "Specifically, we can look at the sine/cosine wave for each hidden dimension separately,\n", "to get a better intuition of the pattern.\n", "Below we visualize the positional encoding for the hidden dimensions $1$, $2$, $3$ and $4$."]}, {"cell_type": "code", "execution_count": 11, "id": "a476a12e", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:12.994247Z", "iopub.status.busy": "2021-12-04T15:58:12.979090Z", "iopub.status.idle": "2021-12-04T15:58:14.181132Z", "shell.execute_reply": "2021-12-04T15:58:14.181526Z"}, "papermill": {"duration": 1.37322, "end_time": "2021-12-04T15:58:14.181688", "exception": false, "start_time": "2021-12-04T15:58:12.808468", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"279.814375pt\" version=\"1.1\" viewBox=\"0 0 721.920312 279.814375\" width=\"721.920312pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:58:13.463512</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 279.814375 \n", "L 721.920312 279.814375 \n", "L 721.920312 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g id=\"patch_2\">\n", "    <path d=\"M 45.120313 99.975268 \n", "L 349.483949 99.975268 \n", "L 349.483949 22.318125 \n", "L 45.120313 22.318125 \n", "z\n", "\" style=\"fill:#eaeaf2;\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_1\">\n", "    <g id=\"xtick_1\">\n", "     <g id=\"line2d_1\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 58.955023 99.975268 \n", "L 58.955023 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_1\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(55.773773 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_2\">\n", "     <g id=\"line2d_2\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 77.401304 99.975268 \n", "L 77.401304 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_2\">\n", "      <!-- 2 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(74.220054 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" id=\"DejaVuSans-32\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_3\">\n", "     <g id=\"line2d_3\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 95.847585 99.975268 \n", "L 95.847585 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_3\">\n", "      <!-- 3 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(92.666335 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" id=\"DejaVuSans-33\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_4\">\n", "     <g id=\"line2d_4\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 114.293866 99.975268 \n", "L 114.293866 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_4\">\n", "      <!-- 4 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(111.112616 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" id=\"DejaVuSans-34\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_5\">\n", "     <g id=\"line2d_5\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 132.740147 99.975268 \n", "L 132.740147 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_5\">\n", "      <!-- 5 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(129.558897 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" id=\"DejaVuSans-35\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_6\">\n", "     <g id=\"line2d_6\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 151.186428 99.975268 \n", "L 151.186428 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_6\">\n", "      <!-- 6 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(148.005178 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" id=\"DejaVuSans-36\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_7\">\n", "     <g id=\"line2d_7\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 169.632709 99.975268 \n", "L 169.632709 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_7\">\n", "      <!-- 7 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(166.451459 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" id=\"DejaVuSans-37\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_8\">\n", "     <g id=\"line2d_8\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 188.07899 99.975268 \n", "L 188.07899 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_8\">\n", "      <!-- 8 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(184.89774 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" id=\"DejaVuSans-38\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_9\">\n", "     <g id=\"line2d_9\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 206.525271 99.975268 \n", "L 206.525271 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_9\">\n", "      <!-- 9 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(203.344021 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" id=\"DejaVuSans-39\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_10\">\n", "     <g id=\"line2d_10\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 224.971552 99.975268 \n", "L 224.971552 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_10\">\n", "      <!-- 10 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(218.609052 117.073705)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_11\">\n", "     <g id=\"line2d_11\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 243.417833 99.975268 \n", "L 243.417833 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_11\">\n", "      <!-- 11 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(237.055333 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_12\">\n", "     <g id=\"line2d_12\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 261.864114 99.975268 \n", "L 261.864114 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_12\">\n", "      <!-- 12 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(255.501614 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_13\">\n", "     <g id=\"line2d_13\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 280.310395 99.975268 \n", "L 280.310395 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_13\">\n", "      <!-- 13 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(273.947895 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_14\">\n", "     <g id=\"line2d_14\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 298.756676 99.975268 \n", "L 298.756676 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_14\">\n", "      <!-- 14 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(292.394176 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_15\">\n", "     <g id=\"line2d_15\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 317.202957 99.975268 \n", "L 317.202957 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_15\">\n", "      <!-- 15 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(310.840457 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_16\">\n", "     <g id=\"line2d_16\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 335.649238 99.975268 \n", "L 335.649238 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_16\">\n", "      <!-- 16 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(329.286738 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_17\">\n", "     <!-- Position in sequence -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(146.006818 130.75183)scale(0.1 -0.1)\">\n", "      <defs>\n", "       <path d=\"M 1259 4147 \n", "L 1259 2394 \n", "L 2053 2394 \n", "Q 2494 2394 2734 2622 \n", "Q 2975 2850 2975 3272 \n", "Q 2975 3691 2734 3919 \n", "Q 2494 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "M 628 4666 \n", "L 2053 4666 \n", "Q 2838 4666 3239 4311 \n", "Q 3641 3956 3641 3272 \n", "Q 3641 2581 3239 2228 \n", "Q 2838 1875 2053 1875 \n", "L 1259 1875 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-50\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" id=\"DejaVuSans-6f\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" id=\"DejaVuSans-73\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-69\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" id=\"DejaVuSans-74\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-6e\" transform=\"scale(0.015625)\"/>\n", "       <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "M 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 -1331 \n", "L 2906 -1331 \n", "L 2906 525 \n", "z\n", "\" id=\"DejaVuSans-71\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" id=\"DejaVuSans-75\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" id=\"DejaVuSans-63\" transform=\"scale(0.015625)\"/>\n", "      </defs>\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"421.082031\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"448.865234\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"512.244141\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"544.03125\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"596.130859\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"657.654297\" xlink:href=\"#DejaVuSans-71\"/>\n", "      <use x=\"721.130859\" xlink:href=\"#DejaVuSans-75\"/>\n", "      <use x=\"784.509766\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"846.033203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"909.412109\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"964.392578\" xlink:href=\"#DejaVuSans-65\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_2\">\n", "    <g id=\"ytick_1\">\n", "     <g id=\"line2d_17\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 45.120313 93.503839 \n", "L 349.483949 93.503839 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_18\">\n", "      <!-- \u22121 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(20.878125 97.303058)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 678 2272 \n", "L 4684 2272 \n", "L 4684 1741 \n", "L 678 1741 \n", "L 678 2272 \n", "z\n", "\" id=\"DejaVuSans-2212\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_2\">\n", "     <g id=\"line2d_18\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 45.120313 61.146696 \n", "L 349.483949 61.146696 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_19\">\n", "      <!-- 0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(29.257813 64.945915)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_3\">\n", "     <g id=\"line2d_19\">\n", "      <path clip-path=\"url(#p0d45a3076c)\" d=\"M 45.120313 28.789554 \n", "L 349.483949 28.789554 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_20\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(29.257813 32.588772)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_21\">\n", "     <!-- Positional encoding -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(14.798438 109.613103)rotate(-90)scale(0.1 -0.1)\">\n", "      <defs>\n", "       <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-6c\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" id=\"DejaVuSans-64\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2906 1791 \n", "Q 2906 2416 2648 2759 \n", "Q 2391 3103 1925 3103 \n", "Q 1463 3103 1205 2759 \n", "Q 947 2416 947 1791 \n", "Q 947 1169 1205 825 \n", "Q 1463 481 1925 481 \n", "Q 2391 481 2648 825 \n", "Q 2906 1169 2906 1791 \n", "z\n", "M 3481 434 \n", "Q 3481 -459 3084 -895 \n", "Q 2688 -1331 1869 -1331 \n", "Q 1566 -1331 1297 -1286 \n", "Q 1028 -1241 775 -1147 \n", "L 775 -588 \n", "Q 1028 -725 1275 -790 \n", "Q 1522 -856 1778 -856 \n", "Q 2344 -856 2625 -561 \n", "Q 2906 -266 2906 331 \n", "L 2906 616 \n", "Q 2728 306 2450 153 \n", "Q 2172 0 1784 0 \n", "Q 1141 0 747 490 \n", "Q 353 981 353 1791 \n", "Q 353 2603 747 3093 \n", "Q 1141 3584 1784 3584 \n", "Q 2172 3584 2450 3431 \n", "Q 2728 3278 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 434 \n", "z\n", "\" id=\"DejaVuSans-67\" transform=\"scale(0.015625)\"/>\n", "      </defs>\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"450.574219\" xlink:href=\"#DejaVuSans-6c\"/>\n", "      <use x=\"478.357422\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"510.144531\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"571.667969\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"635.046875\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"690.027344\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"751.208984\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"814.685547\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"842.46875\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"905.847656\" xlink:href=\"#DejaVuSans-67\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"line2d_20\">\n", "    <path clip-path=\"url(#p0d45a3076c)\" d=\"M 58.955023 61.146696 \n", "L 77.401304 33.9191 \n", "L 95.847585 31.72443 \n", "L 114.293866 56.580456 \n", "L 132.740147 85.634663 \n", "L 151.186428 92.174747 \n", "L 169.632709 70.187783 \n", "L 188.07899 39.888487 \n", "L 206.525271 29.13389 \n", "L 224.971552 47.811719 \n", "L 243.417833 78.749666 \n", "L 261.864114 93.503523 \n", "L 280.310395 78.508663 \n", "L 298.756676 47.551292 \n", "L 317.202957 29.093472 \n", "L 335.649238 40.105239 \n", "\" style=\"fill:none;stroke:#1f77b4;stroke-linecap:round;stroke-width:1.5;\"/>\n", "    <defs>\n", "     <path d=\"M 0 3 \n", "C 0.795609 3 1.55874 2.683901 2.12132 2.12132 \n", "C 2.683901 1.55874 3 0.795609 3 0 \n", "C 3 -0.795609 2.683901 -1.55874 2.12132 -2.12132 \n", "C 1.55874 -2.683901 0.795609 -3 0 -3 \n", "C -0.795609 -3 -1.55874 -2.683901 -2.12132 -2.12132 \n", "C -2.683901 -1.55874 -3 -0.795609 -3 0 \n", "C -3 0.795609 -2.683901 1.55874 -2.12132 2.12132 \n", "C -1.55874 2.683901 -0.795609 3 0 3 \n", "z\n", "\" id=\"m06b48c932f\" style=\"stroke:#000000;\"/>\n", "    </defs>\n", "    <g clip-path=\"url(#p0d45a3076c)\">\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"58.955023\" xlink:href=\"#m06b48c932f\" y=\"61.146696\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"77.401304\" xlink:href=\"#m06b48c932f\" y=\"33.9191\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"95.847585\" xlink:href=\"#m06b48c932f\" y=\"31.72443\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"114.293866\" xlink:href=\"#m06b48c932f\" y=\"56.580456\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"132.740147\" xlink:href=\"#m06b48c932f\" y=\"85.634663\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"151.186428\" xlink:href=\"#m06b48c932f\" y=\"92.174747\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"169.632709\" xlink:href=\"#m06b48c932f\" y=\"70.187783\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"188.07899\" xlink:href=\"#m06b48c932f\" y=\"39.888487\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"206.525271\" xlink:href=\"#m06b48c932f\" y=\"29.13389\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"224.971552\" xlink:href=\"#m06b48c932f\" y=\"47.811719\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"243.417833\" xlink:href=\"#m06b48c932f\" y=\"78.749666\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"261.864114\" xlink:href=\"#m06b48c932f\" y=\"93.503523\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"280.310395\" xlink:href=\"#m06b48c932f\" y=\"78.508663\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"298.756676\" xlink:href=\"#m06b48c932f\" y=\"47.551292\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"317.202957\" xlink:href=\"#m06b48c932f\" y=\"29.093472\"/>\n", "     <use style=\"fill:#1f77b4;stroke:#000000;\" x=\"335.649238\" xlink:href=\"#m06b48c932f\" y=\"40.105239\"/>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_3\">\n", "    <path d=\"M 45.120313 99.975268 \n", "L 45.120313 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_4\">\n", "    <path d=\"M 349.483949 99.975268 \n", "L 349.483949 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_5\">\n", "    <path d=\"M 45.120313 99.975268 \n", "L 349.483949 99.975268 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_6\">\n", "    <path d=\"M 45.120313 22.318125 \n", "L 349.483949 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"text_22\">\n", "    <!-- Encoding in hidden dimension 1 -->\n", "    <g style=\"fill:#262626;\" transform=\"translate(101.073381 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 628 4666 \n", "L 3578 4666 \n", "L 3578 4134 \n", "L 1259 4134 \n", "L 1259 2753 \n", "L 3481 2753 \n", "L 3481 2222 \n", "L 1259 2222 \n", "L 1259 531 \n", "L 3634 531 \n", "L 3634 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-45\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-68\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" id=\"DejaVuSans-6d\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-45\"/>\n", "     <use x=\"63.183594\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"126.5625\" xlink:href=\"#DejaVuSans-63\"/>\n", "     <use x=\"181.542969\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"242.724609\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"306.201172\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"333.984375\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"397.363281\" xlink:href=\"#DejaVuSans-67\"/>\n", "     <use x=\"460.839844\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"492.626953\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"520.410156\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"583.789062\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"615.576172\" xlink:href=\"#DejaVuSans-68\"/>\n", "     <use x=\"678.955078\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"706.738281\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"770.214844\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"833.691406\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"895.214844\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"958.59375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"990.380859\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1053.857422\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1081.640625\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"1179.052734\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1240.576172\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1303.955078\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"1356.054688\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1383.837891\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1445.019531\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1508.398438\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1540.185547\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_2\">\n", "   <g id=\"patch_7\">\n", "    <path d=\"M 410.356676 99.975268 \n", "L 714.720312 99.975268 \n", "L 714.720312 22.318125 \n", "L 410.356676 22.318125 \n", "z\n", "\" style=\"fill:#eaeaf2;\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_3\">\n", "    <g id=\"xtick_17\">\n", "     <g id=\"line2d_21\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 424.191387 99.975268 \n", "L 424.191387 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_23\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(421.010137 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_18\">\n", "     <g id=\"line2d_22\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 442.637668 99.975268 \n", "L 442.637668 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_24\">\n", "      <!-- 2 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(439.456418 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_19\">\n", "     <g id=\"line2d_23\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 461.083949 99.975268 \n", "L 461.083949 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_25\">\n", "      <!-- 3 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(457.902699 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_20\">\n", "     <g id=\"line2d_24\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 479.53023 99.975268 \n", "L 479.53023 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_26\">\n", "      <!-- 4 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(476.34898 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_21\">\n", "     <g id=\"line2d_25\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 497.976511 99.975268 \n", "L 497.976511 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_27\">\n", "      <!-- 5 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(494.795261 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_22\">\n", "     <g id=\"line2d_26\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 516.422792 99.975268 \n", "L 516.422792 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_28\">\n", "      <!-- 6 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(513.241542 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_23\">\n", "     <g id=\"line2d_27\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 534.869073 99.975268 \n", "L 534.869073 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_29\">\n", "      <!-- 7 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(531.687823 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_24\">\n", "     <g id=\"line2d_28\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 553.315354 99.975268 \n", "L 553.315354 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_30\">\n", "      <!-- 8 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(550.134104 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_25\">\n", "     <g id=\"line2d_29\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 571.761635 99.975268 \n", "L 571.761635 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_31\">\n", "      <!-- 9 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(568.580385 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_26\">\n", "     <g id=\"line2d_30\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 590.207916 99.975268 \n", "L 590.207916 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_32\">\n", "      <!-- 10 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(583.845416 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_27\">\n", "     <g id=\"line2d_31\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 608.654197 99.975268 \n", "L 608.654197 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_33\">\n", "      <!-- 11 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(602.291697 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_28\">\n", "     <g id=\"line2d_32\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 627.100478 99.975268 \n", "L 627.100478 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_34\">\n", "      <!-- 12 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(620.737978 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_29\">\n", "     <g id=\"line2d_33\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 645.546759 99.975268 \n", "L 645.546759 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_35\">\n", "      <!-- 13 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(639.184259 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_30\">\n", "     <g id=\"line2d_34\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 663.99304 99.975268 \n", "L 663.99304 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_36\">\n", "      <!-- 14 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(657.63054 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_31\">\n", "     <g id=\"line2d_35\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 682.439321 99.975268 \n", "L 682.439321 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_37\">\n", "      <!-- 15 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(676.076821 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_32\">\n", "     <g id=\"line2d_36\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 700.885602 99.975268 \n", "L 700.885602 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_38\">\n", "      <!-- 16 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(694.523102 117.073705)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_39\">\n", "     <!-- Position in sequence -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(511.243182 130.75183)scale(0.1 -0.1)\">\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"421.082031\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"448.865234\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"512.244141\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"544.03125\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"596.130859\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"657.654297\" xlink:href=\"#DejaVuSans-71\"/>\n", "      <use x=\"721.130859\" xlink:href=\"#DejaVuSans-75\"/>\n", "      <use x=\"784.509766\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"846.033203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"909.412109\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"964.392578\" xlink:href=\"#DejaVuSans-65\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_4\">\n", "    <g id=\"ytick_4\">\n", "     <g id=\"line2d_37\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 410.356676 93.503839 \n", "L 714.720312 93.503839 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_40\">\n", "      <!-- \u22121 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(386.114489 97.303058)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_5\">\n", "     <g id=\"line2d_38\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 410.356676 61.146696 \n", "L 714.720312 61.146696 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_41\">\n", "      <!-- 0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(394.494176 64.945915)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_6\">\n", "     <g id=\"line2d_39\">\n", "      <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 410.356676 28.789554 \n", "L 714.720312 28.789554 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_42\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(394.494176 32.588772)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_43\">\n", "     <!-- Positional encoding -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(380.034801 109.613103)rotate(-90)scale(0.1 -0.1)\">\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"450.574219\" xlink:href=\"#DejaVuSans-6c\"/>\n", "      <use x=\"478.357422\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"510.144531\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"571.667969\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"635.046875\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"690.027344\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"751.208984\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"814.685547\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"842.46875\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"905.847656\" xlink:href=\"#DejaVuSans-67\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"line2d_40\">\n", "    <path clip-path=\"url(#p72e0f3d56f)\" d=\"M 424.191387 28.789554 \n", "L 442.637668 43.664057 \n", "L 461.083949 74.612019 \n", "L 479.53023 93.180025 \n", "L 497.976511 82.296736 \n", "L 516.422792 51.968198 \n", "L 534.869073 30.07833 \n", "L 553.315354 36.752573 \n", "L 571.761635 65.854662 \n", "L 590.207916 90.628268 \n", "L 608.654197 88.296653 \n", "L 627.100478 61.003493 \n", "L 645.546759 33.841994 \n", "L 663.99304 31.784311 \n", "L 682.439321 56.722271 \n", "L 700.885602 85.728026 \n", "\" style=\"fill:none;stroke:#ff7f0e;stroke-linecap:round;stroke-width:1.5;\"/>\n", "    <defs>\n", "     <path d=\"M 0 3 \n", "C 0.795609 3 1.55874 2.683901 2.12132 2.12132 \n", "C 2.683901 1.55874 3 0.795609 3 0 \n", "C 3 -0.795609 2.683901 -1.55874 2.12132 -2.12132 \n", "C 1.55874 -2.683901 0.795609 -3 0 -3 \n", "C -0.795609 -3 -1.55874 -2.683901 -2.12132 -2.12132 \n", "C -2.683901 -1.55874 -3 -0.795609 -3 0 \n", "C -3 0.795609 -2.683901 1.55874 -2.12132 2.12132 \n", "C -1.55874 2.683901 -0.795609 3 0 3 \n", "z\n", "\" id=\"m962bdbc73d\" style=\"stroke:#000000;\"/>\n", "    </defs>\n", "    <g clip-path=\"url(#p72e0f3d56f)\">\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"424.191387\" xlink:href=\"#m962bdbc73d\" y=\"28.789554\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"442.637668\" xlink:href=\"#m962bdbc73d\" y=\"43.664057\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"461.083949\" xlink:href=\"#m962bdbc73d\" y=\"74.612019\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"479.53023\" xlink:href=\"#m962bdbc73d\" y=\"93.180025\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"497.976511\" xlink:href=\"#m962bdbc73d\" y=\"82.296736\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"516.422792\" xlink:href=\"#m962bdbc73d\" y=\"51.968198\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"534.869073\" xlink:href=\"#m962bdbc73d\" y=\"30.07833\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"553.315354\" xlink:href=\"#m962bdbc73d\" y=\"36.752573\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"571.761635\" xlink:href=\"#m962bdbc73d\" y=\"65.854662\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"590.207916\" xlink:href=\"#m962bdbc73d\" y=\"90.628268\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"608.654197\" xlink:href=\"#m962bdbc73d\" y=\"88.296653\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"627.100478\" xlink:href=\"#m962bdbc73d\" y=\"61.003493\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"645.546759\" xlink:href=\"#m962bdbc73d\" y=\"33.841994\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"663.99304\" xlink:href=\"#m962bdbc73d\" y=\"31.784311\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"682.439321\" xlink:href=\"#m962bdbc73d\" y=\"56.722271\"/>\n", "     <use style=\"fill:#ff7f0e;stroke:#000000;\" x=\"700.885602\" xlink:href=\"#m962bdbc73d\" y=\"85.728026\"/>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_8\">\n", "    <path d=\"M 410.356676 99.975268 \n", "L 410.356676 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_9\">\n", "    <path d=\"M 714.720312 99.975268 \n", "L 714.720312 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_10\">\n", "    <path d=\"M 410.356676 99.975268 \n", "L 714.720312 99.975268 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_11\">\n", "    <path d=\"M 410.356676 22.318125 \n", "L 714.720312 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"text_44\">\n", "    <!-- Encoding in hidden dimension 2 -->\n", "    <g style=\"fill:#262626;\" transform=\"translate(466.309744 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-45\"/>\n", "     <use x=\"63.183594\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"126.5625\" xlink:href=\"#DejaVuSans-63\"/>\n", "     <use x=\"181.542969\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"242.724609\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"306.201172\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"333.984375\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"397.363281\" xlink:href=\"#DejaVuSans-67\"/>\n", "     <use x=\"460.839844\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"492.626953\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"520.410156\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"583.789062\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"615.576172\" xlink:href=\"#DejaVuSans-68\"/>\n", "     <use x=\"678.955078\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"706.738281\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"770.214844\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"833.691406\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"895.214844\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"958.59375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"990.380859\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1053.857422\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1081.640625\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"1179.052734\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1240.576172\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1303.955078\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"1356.054688\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1383.837891\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1445.019531\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1508.398438\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1540.185547\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_3\">\n", "   <g id=\"patch_12\">\n", "    <path d=\"M 45.120313 239.758125 \n", "L 349.483949 239.758125 \n", "L 349.483949 162.100982 \n", "L 45.120313 162.100982 \n", "z\n", "\" style=\"fill:#eaeaf2;\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_5\">\n", "    <g id=\"xtick_33\">\n", "     <g id=\"line2d_41\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 58.955023 239.758125 \n", "L 58.955023 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_45\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(55.773773 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_34\">\n", "     <g id=\"line2d_42\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 77.401304 239.758125 \n", "L 77.401304 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_46\">\n", "      <!-- 2 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(74.220054 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_35\">\n", "     <g id=\"line2d_43\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 95.847585 239.758125 \n", "L 95.847585 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_47\">\n", "      <!-- 3 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(92.666335 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_36\">\n", "     <g id=\"line2d_44\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 114.293866 239.758125 \n", "L 114.293866 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_48\">\n", "      <!-- 4 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(111.112616 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_37\">\n", "     <g id=\"line2d_45\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 132.740147 239.758125 \n", "L 132.740147 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_49\">\n", "      <!-- 5 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(129.558897 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_38\">\n", "     <g id=\"line2d_46\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 151.186428 239.758125 \n", "L 151.186428 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_50\">\n", "      <!-- 6 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(148.005178 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_39\">\n", "     <g id=\"line2d_47\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 169.632709 239.758125 \n", "L 169.632709 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_51\">\n", "      <!-- 7 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(166.451459 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_40\">\n", "     <g id=\"line2d_48\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 188.07899 239.758125 \n", "L 188.07899 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_52\">\n", "      <!-- 8 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(184.89774 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_41\">\n", "     <g id=\"line2d_49\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 206.525271 239.758125 \n", "L 206.525271 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_53\">\n", "      <!-- 9 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(203.344021 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_42\">\n", "     <g id=\"line2d_50\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 224.971552 239.758125 \n", "L 224.971552 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_54\">\n", "      <!-- 10 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(218.609052 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_43\">\n", "     <g id=\"line2d_51\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 243.417833 239.758125 \n", "L 243.417833 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_55\">\n", "      <!-- 11 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(237.055333 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_44\">\n", "     <g id=\"line2d_52\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 261.864114 239.758125 \n", "L 261.864114 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_56\">\n", "      <!-- 12 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(255.501614 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_45\">\n", "     <g id=\"line2d_53\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 280.310395 239.758125 \n", "L 280.310395 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_57\">\n", "      <!-- 13 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(273.947895 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_46\">\n", "     <g id=\"line2d_54\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 298.756676 239.758125 \n", "L 298.756676 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_58\">\n", "      <!-- 14 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(292.394176 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_47\">\n", "     <g id=\"line2d_55\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 317.202957 239.758125 \n", "L 317.202957 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_59\">\n", "      <!-- 15 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(310.840457 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_48\">\n", "     <g id=\"line2d_56\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 335.649238 239.758125 \n", "L 335.649238 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_60\">\n", "      <!-- 16 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(329.286738 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_61\">\n", "     <!-- Position in sequence -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(146.006818 270.534688)scale(0.1 -0.1)\">\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"421.082031\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"448.865234\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"512.244141\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"544.03125\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"596.130859\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"657.654297\" xlink:href=\"#DejaVuSans-71\"/>\n", "      <use x=\"721.130859\" xlink:href=\"#DejaVuSans-75\"/>\n", "      <use x=\"784.509766\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"846.033203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"909.412109\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"964.392578\" xlink:href=\"#DejaVuSans-65\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_6\">\n", "    <g id=\"ytick_7\">\n", "     <g id=\"line2d_57\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 45.120313 233.286696 \n", "L 349.483949 233.286696 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_62\">\n", "      <!-- \u22121 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(20.878125 237.085915)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_8\">\n", "     <g id=\"line2d_58\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 45.120313 200.929554 \n", "L 349.483949 200.929554 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_63\">\n", "      <!-- 0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(29.257813 204.728772)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_9\">\n", "     <g id=\"line2d_59\">\n", "      <path clip-path=\"url(#p101870f51c)\" d=\"M 45.120313 168.572411 \n", "L 349.483949 168.572411 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_64\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(29.257813 172.371629)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_65\">\n", "     <!-- Positional encoding -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(14.798438 249.39596)rotate(-90)scale(0.1 -0.1)\">\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"450.574219\" xlink:href=\"#DejaVuSans-6c\"/>\n", "      <use x=\"478.357422\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"510.144531\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"571.667969\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"635.046875\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"690.027344\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"751.208984\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"814.685547\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"842.46875\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"905.847656\" xlink:href=\"#DejaVuSans-67\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"line2d_60\">\n", "    <path clip-path=\"url(#p101870f51c)\" d=\"M 58.955023 200.929554 \n", "L 77.401304 180.551117 \n", "L 95.847585 169.27126 \n", "L 114.293866 172.12622 \n", "L 132.740147 187.841315 \n", "L 151.186428 209.400055 \n", "L 169.632709 227.17688 \n", "L 188.07899 233.234779 \n", "L 206.525271 224.869018 \n", "L 224.971552 205.814747 \n", "L 243.417833 184.57933 \n", "L 261.864114 170.643974 \n", "L 280.310395 170.230546 \n", "L 298.756676 183.523619 \n", "L 317.202957 204.588128 \n", "L 335.649238 224.019151 \n", "\" style=\"fill:none;stroke:#2ca02c;stroke-linecap:round;stroke-width:1.5;\"/>\n", "    <defs>\n", "     <path d=\"M 0 3 \n", "C 0.795609 3 1.55874 2.683901 2.12132 2.12132 \n", "C 2.683901 1.55874 3 0.795609 3 0 \n", "C 3 -0.795609 2.683901 -1.55874 2.12132 -2.12132 \n", "C 1.55874 -2.683901 0.795609 -3 0 -3 \n", "C -0.795609 -3 -1.55874 -2.683901 -2.12132 -2.12132 \n", "C -2.683901 -1.55874 -3 -0.795609 -3 0 \n", "C -3 0.795609 -2.683901 1.55874 -2.12132 2.12132 \n", "C -1.55874 2.683901 -0.795609 3 0 3 \n", "z\n", "\" id=\"mdc54303fd7\" style=\"stroke:#000000;\"/>\n", "    </defs>\n", "    <g clip-path=\"url(#p101870f51c)\">\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"58.955023\" xlink:href=\"#mdc54303fd7\" y=\"200.929554\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"77.401304\" xlink:href=\"#mdc54303fd7\" y=\"180.551117\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"95.847585\" xlink:href=\"#mdc54303fd7\" y=\"169.27126\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"114.293866\" xlink:href=\"#mdc54303fd7\" y=\"172.12622\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"132.740147\" xlink:href=\"#mdc54303fd7\" y=\"187.841315\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"151.186428\" xlink:href=\"#mdc54303fd7\" y=\"209.400055\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"169.632709\" xlink:href=\"#mdc54303fd7\" y=\"227.17688\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"188.07899\" xlink:href=\"#mdc54303fd7\" y=\"233.234779\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"206.525271\" xlink:href=\"#mdc54303fd7\" y=\"224.869018\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"224.971552\" xlink:href=\"#mdc54303fd7\" y=\"205.814747\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"243.417833\" xlink:href=\"#mdc54303fd7\" y=\"184.57933\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"261.864114\" xlink:href=\"#mdc54303fd7\" y=\"170.643974\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"280.310395\" xlink:href=\"#mdc54303fd7\" y=\"170.230546\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"298.756676\" xlink:href=\"#mdc54303fd7\" y=\"183.523619\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"317.202957\" xlink:href=\"#mdc54303fd7\" y=\"204.588128\"/>\n", "     <use style=\"fill:#2ca02c;stroke:#000000;\" x=\"335.649238\" xlink:href=\"#mdc54303fd7\" y=\"224.019151\"/>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_13\">\n", "    <path d=\"M 45.120313 239.758125 \n", "L 45.120313 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_14\">\n", "    <path d=\"M 349.483949 239.758125 \n", "L 349.483949 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_15\">\n", "    <path d=\"M 45.120313 239.758125 \n", "L 349.483949 239.758125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_16\">\n", "    <path d=\"M 45.120313 162.100982 \n", "L 349.483949 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"text_66\">\n", "    <!-- Encoding in hidden dimension 3 -->\n", "    <g style=\"fill:#262626;\" transform=\"translate(101.073381 156.100982)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-45\"/>\n", "     <use x=\"63.183594\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"126.5625\" xlink:href=\"#DejaVuSans-63\"/>\n", "     <use x=\"181.542969\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"242.724609\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"306.201172\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"333.984375\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"397.363281\" xlink:href=\"#DejaVuSans-67\"/>\n", "     <use x=\"460.839844\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"492.626953\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"520.410156\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"583.789062\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"615.576172\" xlink:href=\"#DejaVuSans-68\"/>\n", "     <use x=\"678.955078\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"706.738281\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"770.214844\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"833.691406\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"895.214844\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"958.59375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"990.380859\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1053.857422\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1081.640625\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"1179.052734\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1240.576172\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1303.955078\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"1356.054688\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1383.837891\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1445.019531\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1508.398438\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1540.185547\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_4\">\n", "   <g id=\"patch_17\">\n", "    <path d=\"M 410.356676 239.758125 \n", "L 714.720312 239.758125 \n", "L 714.720312 162.100982 \n", "L 410.356676 162.100982 \n", "z\n", "\" style=\"fill:#eaeaf2;\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_7\">\n", "    <g id=\"xtick_49\">\n", "     <g id=\"line2d_61\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 424.191387 239.758125 \n", "L 424.191387 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_67\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(421.010137 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_50\">\n", "     <g id=\"line2d_62\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 442.637668 239.758125 \n", "L 442.637668 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_68\">\n", "      <!-- 2 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(439.456418 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_51\">\n", "     <g id=\"line2d_63\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 461.083949 239.758125 \n", "L 461.083949 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_69\">\n", "      <!-- 3 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(457.902699 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_52\">\n", "     <g id=\"line2d_64\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 479.53023 239.758125 \n", "L 479.53023 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_70\">\n", "      <!-- 4 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(476.34898 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_53\">\n", "     <g id=\"line2d_65\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 497.976511 239.758125 \n", "L 497.976511 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_71\">\n", "      <!-- 5 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(494.795261 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_54\">\n", "     <g id=\"line2d_66\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 516.422792 239.758125 \n", "L 516.422792 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_72\">\n", "      <!-- 6 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(513.241542 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_55\">\n", "     <g id=\"line2d_67\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 534.869073 239.758125 \n", "L 534.869073 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_73\">\n", "      <!-- 7 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(531.687823 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_56\">\n", "     <g id=\"line2d_68\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 553.315354 239.758125 \n", "L 553.315354 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_74\">\n", "      <!-- 8 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(550.134104 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_57\">\n", "     <g id=\"line2d_69\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 571.761635 239.758125 \n", "L 571.761635 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_75\">\n", "      <!-- 9 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(568.580385 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_58\">\n", "     <g id=\"line2d_70\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 590.207916 239.758125 \n", "L 590.207916 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_76\">\n", "      <!-- 10 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(583.845416 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_59\">\n", "     <g id=\"line2d_71\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 608.654197 239.758125 \n", "L 608.654197 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_77\">\n", "      <!-- 11 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(602.291697 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_60\">\n", "     <g id=\"line2d_72\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 627.100478 239.758125 \n", "L 627.100478 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_78\">\n", "      <!-- 12 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(620.737978 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_61\">\n", "     <g id=\"line2d_73\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 645.546759 239.758125 \n", "L 645.546759 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_79\">\n", "      <!-- 13 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(639.184259 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_62\">\n", "     <g id=\"line2d_74\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 663.99304 239.758125 \n", "L 663.99304 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_80\">\n", "      <!-- 14 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(657.63054 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_63\">\n", "     <g id=\"line2d_75\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 682.439321 239.758125 \n", "L 682.439321 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_81\">\n", "      <!-- 15 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(676.076821 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_64\">\n", "     <g id=\"line2d_76\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 700.885602 239.758125 \n", "L 700.885602 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_82\">\n", "      <!-- 16 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(694.523102 256.856563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_83\">\n", "     <!-- Position in sequence -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(511.243182 270.534688)scale(0.1 -0.1)\">\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"421.082031\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"448.865234\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"512.244141\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"544.03125\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"596.130859\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"657.654297\" xlink:href=\"#DejaVuSans-71\"/>\n", "      <use x=\"721.130859\" xlink:href=\"#DejaVuSans-75\"/>\n", "      <use x=\"784.509766\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"846.033203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"909.412109\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"964.392578\" xlink:href=\"#DejaVuSans-65\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_8\">\n", "    <g id=\"ytick_10\">\n", "     <g id=\"line2d_77\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 410.356676 233.286696 \n", "L 714.720312 233.286696 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_84\">\n", "      <!-- \u22121 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(386.114489 237.085915)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-2212\"/>\n", "       <use x=\"83.789062\" xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_11\">\n", "     <g id=\"line2d_78\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 410.356676 200.929554 \n", "L 714.720312 200.929554 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_85\">\n", "      <!-- 0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(394.494176 204.728772)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_12\">\n", "     <g id=\"line2d_79\">\n", "      <path clip-path=\"url(#p382fded3e0)\" d=\"M 410.356676 168.572411 \n", "L 714.720312 168.572411 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_86\">\n", "      <!-- 1 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(394.494176 172.371629)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_87\">\n", "     <!-- Positional encoding -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(380.034801 249.39596)rotate(-90)scale(0.1 -0.1)\">\n", "      <use xlink:href=\"#DejaVuSans-50\"/>\n", "      <use x=\"56.677734\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"117.859375\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"169.958984\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"197.742188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"236.951172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"264.734375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"325.916016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"389.294922\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"450.574219\" xlink:href=\"#DejaVuSans-6c\"/>\n", "      <use x=\"478.357422\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"510.144531\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"571.667969\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"635.046875\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"690.027344\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"751.208984\" xlink:href=\"#DejaVuSans-64\"/>\n", "      <use x=\"814.685547\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"842.46875\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"905.847656\" xlink:href=\"#DejaVuSans-67\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"line2d_80\">\n", "    <path clip-path=\"url(#p382fded3e0)\" d=\"M 424.191387 168.572411 \n", "L 442.637668 175.795831 \n", "L 461.083949 194.240974 \n", "L 479.53023 215.67244 \n", "L 497.976511 230.521489 \n", "L 516.422792 232.158311 \n", "L 534.869073 219.852094 \n", "L 553.315354 199.097327 \n", "L 571.761635 179.160615 \n", "L 590.207916 168.943312 \n", "L 608.654197 173.007253 \n", "L 627.100478 189.537961 \n", "L 645.546759 211.154797 \n", "L 663.99304 228.206249 \n", "L 682.439321 233.079196 \n", "L 700.885602 223.597927 \n", "\" style=\"fill:none;stroke:#d62728;stroke-linecap:round;stroke-width:1.5;\"/>\n", "    <defs>\n", "     <path d=\"M 0 3 \n", "C 0.795609 3 1.55874 2.683901 2.12132 2.12132 \n", "C 2.683901 1.55874 3 0.795609 3 0 \n", "C 3 -0.795609 2.683901 -1.55874 2.12132 -2.12132 \n", "C 1.55874 -2.683901 0.795609 -3 0 -3 \n", "C -0.795609 -3 -1.55874 -2.683901 -2.12132 -2.12132 \n", "C -2.683901 -1.55874 -3 -0.795609 -3 0 \n", "C -3 0.795609 -2.683901 1.55874 -2.12132 2.12132 \n", "C -1.55874 2.683901 -0.795609 3 0 3 \n", "z\n", "\" id=\"mc0971a33c3\" style=\"stroke:#000000;\"/>\n", "    </defs>\n", "    <g clip-path=\"url(#p382fded3e0)\">\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"424.191387\" xlink:href=\"#mc0971a33c3\" y=\"168.572411\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"442.637668\" xlink:href=\"#mc0971a33c3\" y=\"175.795831\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"461.083949\" xlink:href=\"#mc0971a33c3\" y=\"194.240974\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"479.53023\" xlink:href=\"#mc0971a33c3\" y=\"215.67244\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"497.976511\" xlink:href=\"#mc0971a33c3\" y=\"230.521489\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"516.422792\" xlink:href=\"#mc0971a33c3\" y=\"232.158311\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"534.869073\" xlink:href=\"#mc0971a33c3\" y=\"219.852094\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"553.315354\" xlink:href=\"#mc0971a33c3\" y=\"199.097327\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"571.761635\" xlink:href=\"#mc0971a33c3\" y=\"179.160615\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"590.207916\" xlink:href=\"#mc0971a33c3\" y=\"168.943312\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"608.654197\" xlink:href=\"#mc0971a33c3\" y=\"173.007253\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"627.100478\" xlink:href=\"#mc0971a33c3\" y=\"189.537961\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"645.546759\" xlink:href=\"#mc0971a33c3\" y=\"211.154797\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"663.99304\" xlink:href=\"#mc0971a33c3\" y=\"228.206249\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"682.439321\" xlink:href=\"#mc0971a33c3\" y=\"233.079196\"/>\n", "     <use style=\"fill:#d62728;stroke:#000000;\" x=\"700.885602\" xlink:href=\"#mc0971a33c3\" y=\"223.597927\"/>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_18\">\n", "    <path d=\"M 410.356676 239.758125 \n", "L 410.356676 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_19\">\n", "    <path d=\"M 714.720312 239.758125 \n", "L 714.720312 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_20\">\n", "    <path d=\"M 410.356676 239.758125 \n", "L 714.720312 239.758125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_21\">\n", "    <path d=\"M 410.356676 162.100982 \n", "L 714.720312 162.100982 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"text_88\">\n", "    <!-- Encoding in hidden dimension 4 -->\n", "    <g style=\"fill:#262626;\" transform=\"translate(466.309744 156.100982)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-45\"/>\n", "     <use x=\"63.183594\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"126.5625\" xlink:href=\"#DejaVuSans-63\"/>\n", "     <use x=\"181.542969\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"242.724609\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"306.201172\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"333.984375\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"397.363281\" xlink:href=\"#DejaVuSans-67\"/>\n", "     <use x=\"460.839844\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"492.626953\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"520.410156\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"583.789062\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"615.576172\" xlink:href=\"#DejaVuSans-68\"/>\n", "     <use x=\"678.955078\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"706.738281\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"770.214844\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"833.691406\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"895.214844\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"958.59375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"990.380859\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1053.857422\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1081.640625\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"1179.052734\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1240.576172\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1303.955078\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"1356.054688\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1383.837891\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1445.019531\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1508.398438\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1540.185547\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"p0d45a3076c\">\n", "   <rect height=\"77.657143\" width=\"304.363636\" x=\"45.120313\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p72e0f3d56f\">\n", "   <rect height=\"77.657143\" width=\"304.363636\" x=\"410.356676\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p101870f51c\">\n", "   <rect height=\"77.657143\" width=\"304.363636\" x=\"45.120313\" y=\"162.100982\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p382fded3e0\">\n", "   <rect height=\"77.657143\" width=\"304.363636\" x=\"410.356676\" y=\"162.100982\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 864x288 with 4 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["sns.set_theme()\n", "fig, ax = plt.subplots(2, 2, figsize=(12, 4))\n", "ax = [a for a_list in ax for a in a_list]\n", "for i in range(len(ax)):\n", "    ax[i].plot(np.arange(1, 17), pe[i, :16], color=\"C%i\" % i, marker=\"o\", markersize=6, markeredgecolor=\"black\")\n", "    ax[i].set_title(\"Encoding in hidden dimension %i\" % (i + 1))\n", "    ax[i].set_xlabel(\"Position in sequence\", fontsize=10)\n", "    ax[i].set_ylabel(\"Positional encoding\", fontsize=10)\n", "    ax[i].set_xticks(np.arange(1, 17))\n", "    ax[i].tick_params(axis=\"both\", which=\"major\", labelsize=10)\n", "    ax[i].tick_params(axis=\"both\", which=\"minor\", labelsize=8)\n", "    ax[i].set_ylim(-1.2, 1.2)\n", "fig.subplots_adjust(hspace=0.8)\n", "sns.reset_orig()\n", "plt.show()"]}, {"cell_type": "markdown", "id": "323263e4", "metadata": {"papermill": {"duration": 0.162339, "end_time": "2021-12-04T15:58:14.500062", "exception": false, "start_time": "2021-12-04T15:58:14.337723", "status": "completed"}, "tags": []}, "source": ["As we can see, the patterns between the hidden dimension $1$ and $2$ only differ in the starting angle.\n", "The wavelength is $2\\pi$, hence the repetition after position $6$.\n", "The hidden dimensions $2$ and $3$ have about twice the wavelength."]}, {"cell_type": "markdown", "id": "2a423f6a", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.150745, "end_time": "2021-12-04T15:58:14.801934", "exception": false, "start_time": "2021-12-04T15:58:14.651189", "status": "completed"}, "tags": []}, "source": ["### Learning rate warm-up\n", "\n", "One commonly used technique for training a Transformer is learning rate warm-up.\n", "This means that we gradually increase the learning rate from 0 on to our originally specified\n", "learning rate in the first few iterations.\n", "Thus, we slowly start learning instead of taking very large steps from the beginning.\n", "In fact, training a deep Transformer without learning rate warm-up can make the model diverge\n", "and achieve a much worse performance on training and testing.\n", "Take for instance the following plot by [Liu et al.\n", "(2019)](https://arxiv.org/pdf/1908.03265.pdf) comparing Adam-vanilla (i.e. Adam without warm-up)\n", "vs Adam with a warm-up:\n", "\n", "<center width=\"100%\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/warmup_loss_plot.svg\" width=\"350px\"></center>\n", "\n", "Clearly, the warm-up is a crucial hyperparameter in the Transformer architecture.\n", "Why is it so important?\n", "There are currently two common explanations.\n", "Firstly, Adam uses the bias correction factors which however can lead to a higher variance in the adaptive\n", "learning rate during the first iterations.\n", "Improved optimizers like [RAdam](https://arxiv.org/abs/1908.03265) have been shown to overcome this issue,\n", "not requiring warm-up for training Transformers.\n", "Secondly, the iteratively applied Layer Normalization across layers can lead to very high gradients during\n", "the first iterations, which can be solved by using Pre-Layer Normalization\n", "(similar to Pre-Activation ResNet), or replacing Layer Normalization by other techniques\n", "(Adaptive Normalization,\n", "[Power Normalization](https://arxiv.org/abs/2003.07845)).\n", "\n", "Nevertheless, many applications and papers still use the original Transformer architecture with Adam,\n", "because warm-up is a simple, yet effective way of solving the gradient problem in the first iterations.\n", "There are many different schedulers we could use.\n", "For instance, the original Transformer paper used an exponential decay scheduler with a warm-up.\n", "However, the currently most popular scheduler is the cosine warm-up scheduler,\n", "which combines warm-up with a cosine-shaped learning rate decay.\n", "We can implement it below, and visualize the learning rate factor over epochs."]}, {"cell_type": "code", "execution_count": 12, "id": "da5c81cf", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:15.111318Z", "iopub.status.busy": "2021-12-04T15:58:15.110838Z", "iopub.status.idle": "2021-12-04T15:58:15.112740Z", "shell.execute_reply": "2021-12-04T15:58:15.112354Z"}, "papermill": {"duration": 0.159462, "end_time": "2021-12-04T15:58:15.112851", "exception": false, "start_time": "2021-12-04T15:58:14.953389", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class CosineWarmupScheduler(optim.lr_scheduler._LRScheduler):\n", "    def __init__(self, optimizer, warmup, max_iters):\n", "        self.warmup = warmup\n", "        self.max_num_iters = max_iters\n", "        super().__init__(optimizer)\n", "\n", "    def get_lr(self):\n", "        lr_factor = self.get_lr_factor(epoch=self.last_epoch)\n", "        return [base_lr * lr_factor for base_lr in self.base_lrs]\n", "\n", "    def get_lr_factor(self, epoch):\n", "        lr_factor = 0.5 * (1 + np.cos(np.pi * epoch / self.max_num_iters))\n", "        if epoch <= self.warmup:\n", "            lr_factor *= epoch * 1.0 / self.warmup\n", "        return lr_factor"]}, {"cell_type": "code", "execution_count": 13, "id": "a0668690", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:15.442783Z", "iopub.status.busy": "2021-12-04T15:58:15.438778Z", "iopub.status.idle": "2021-12-04T15:58:15.738564Z", "shell.execute_reply": "2021-12-04T15:58:15.738973Z"}, "papermill": {"duration": 0.475589, "end_time": "2021-12-04T15:58:15.739126", "exception": false, "start_time": "2021-12-04T15:58:15.263537", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"228.357813pt\" version=\"1.1\" viewBox=\"0 0 503.407187 228.357813\" width=\"503.407187pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:58:15.545554</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 228.357813 \n", "L 503.407187 228.357813 \n", "L 503.407187 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g id=\"patch_2\">\n", "    <path d=\"M 49.807188 185.398125 \n", "L 496.207187 185.398125 \n", "L 496.207187 22.318125 \n", "L 49.807188 22.318125 \n", "z\n", "\" style=\"fill:#eaeaf2;\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_1\">\n", "    <g id=\"xtick_1\">\n", "     <g id=\"line2d_1\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 70.098097 185.398125 \n", "L 70.098097 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_1\">\n", "      <!-- 0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(66.598722 203.256406)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_2\">\n", "     <g id=\"line2d_2\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 120.850746 185.398125 \n", "L 120.850746 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_2\">\n", "      <!-- 250 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(110.352621 203.256406)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" id=\"DejaVuSans-32\" transform=\"scale(0.015625)\"/>\n", "        <path d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" id=\"DejaVuSans-35\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_3\">\n", "     <g id=\"line2d_3\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 171.603395 185.398125 \n", "L 171.603395 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_3\">\n", "      <!-- 500 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(161.10527 203.256406)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_4\">\n", "     <g id=\"line2d_4\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 222.356044 185.398125 \n", "L 222.356044 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_4\">\n", "      <!-- 750 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(211.857919 203.256406)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" id=\"DejaVuSans-37\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_5\">\n", "     <g id=\"line2d_5\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 273.108693 185.398125 \n", "L 273.108693 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_5\">\n", "      <!-- 1000 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(259.111193 203.256406)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_6\">\n", "     <g id=\"line2d_6\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 323.861342 185.398125 \n", "L 323.861342 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_6\">\n", "      <!-- 1250 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(309.863842 203.256406)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_7\">\n", "     <g id=\"line2d_7\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 374.613991 185.398125 \n", "L 374.613991 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_7\">\n", "      <!-- 1500 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(360.616491 203.256406)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_8\">\n", "     <g id=\"line2d_8\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 425.36664 185.398125 \n", "L 425.36664 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_8\">\n", "      <!-- 1750 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(411.36914 203.256406)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-37\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-35\"/>\n", "       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_9\">\n", "     <g id=\"line2d_9\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 476.119289 185.398125 \n", "L 476.119289 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_9\">\n", "      <!-- 2000 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(462.121789 203.256406)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_10\">\n", "     <!-- Iterations (in batches) -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(206.709062 218.662188)scale(0.12 -0.12)\">\n", "      <defs>\n", "       <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-49\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1172 4494 \n", "L 1172 3500 \n", "L 2356 3500 \n", "L 2356 3053 \n", "L 1172 3053 \n", "L 1172 1153 \n", "Q 1172 725 1289 603 \n", "Q 1406 481 1766 481 \n", "L 2356 481 \n", "L 2356 0 \n", "L 1766 0 \n", "Q 1100 0 847 248 \n", "Q 594 497 594 1153 \n", "L 594 3053 \n", "L 172 3053 \n", "L 172 3500 \n", "L 594 3500 \n", "L 594 4494 \n", "L 1172 4494 \n", "z\n", "\" id=\"DejaVuSans-74\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" id=\"DejaVuSans-72\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 603 3500 \n", "L 1178 3500 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 3500 \n", "z\n", "M 603 4863 \n", "L 1178 4863 \n", "L 1178 4134 \n", "L 603 4134 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-69\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" id=\"DejaVuSans-6f\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-6e\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" id=\"DejaVuSans-73\" transform=\"scale(0.015625)\"/>\n", "       <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 1984 4856 \n", "Q 1566 4138 1362 3434 \n", "Q 1159 2731 1159 2009 \n", "Q 1159 1288 1364 580 \n", "Q 1569 -128 1984 -844 \n", "L 1484 -844 \n", "Q 1016 -109 783 600 \n", "Q 550 1309 550 2009 \n", "Q 550 2706 781 3412 \n", "Q 1013 4119 1484 4856 \n", "L 1984 4856 \n", "z\n", "\" id=\"DejaVuSans-28\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "M 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2969 \n", "z\n", "\" id=\"DejaVuSans-62\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3122 3366 \n", "L 3122 2828 \n", "Q 2878 2963 2633 3030 \n", "Q 2388 3097 2138 3097 \n", "Q 1578 3097 1268 2742 \n", "Q 959 2388 959 1747 \n", "Q 959 1106 1268 751 \n", "Q 1578 397 2138 397 \n", "Q 2388 397 2633 464 \n", "Q 2878 531 3122 666 \n", "L 3122 134 \n", "Q 2881 22 2623 -34 \n", "Q 2366 -91 2075 -91 \n", "Q 1284 -91 818 406 \n", "Q 353 903 353 1747 \n", "Q 353 2603 823 3093 \n", "Q 1294 3584 2113 3584 \n", "Q 2378 3584 2631 3529 \n", "Q 2884 3475 3122 3366 \n", "z\n", "\" id=\"DejaVuSans-63\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 4863 \n", "L 1159 4863 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-68\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 513 4856 \n", "L 1013 4856 \n", "Q 1481 4119 1714 3412 \n", "Q 1947 2706 1947 2009 \n", "Q 1947 1309 1714 600 \n", "Q 1481 -109 1013 -844 \n", "L 513 -844 \n", "Q 928 -128 1133 580 \n", "Q 1338 1288 1338 2009 \n", "Q 1338 2731 1133 3434 \n", "Q 928 4138 513 4856 \n", "z\n", "\" id=\"DejaVuSans-29\" transform=\"scale(0.015625)\"/>\n", "      </defs>\n", "      <use xlink:href=\"#DejaVuSans-49\"/>\n", "      <use x=\"29.492188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"68.701172\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"130.224609\" xlink:href=\"#DejaVuSans-72\"/>\n", "      <use x=\"171.337891\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"232.617188\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"271.826172\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"299.609375\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"360.791016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"424.169922\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"476.269531\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"508.056641\" xlink:href=\"#DejaVuSans-28\"/>\n", "      <use x=\"547.070312\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"574.853516\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"638.232422\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"670.019531\" xlink:href=\"#DejaVuSans-62\"/>\n", "      <use x=\"733.496094\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"794.775391\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"833.984375\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"888.964844\" xlink:href=\"#DejaVuSans-68\"/>\n", "      <use x=\"952.34375\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"1013.867188\" xlink:href=\"#DejaVuSans-73\"/>\n", "      <use x=\"1065.966797\" xlink:href=\"#DejaVuSans-29\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_2\">\n", "    <g id=\"ytick_1\">\n", "     <g id=\"line2d_10\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 49.807188 177.985398 \n", "L 496.207187 177.985398 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_11\">\n", "      <!-- 0.0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(22.81375 182.164538)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 684 794 \n", "L 1344 794 \n", "L 1344 0 \n", "L 684 0 \n", "L 684 794 \n", "z\n", "\" id=\"DejaVuSans-2e\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_2\">\n", "     <g id=\"line2d_11\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 49.807188 148.150832 \n", "L 496.207187 148.150832 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_12\">\n", "      <!-- 0.2 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(22.81375 152.329973)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_3\">\n", "     <g id=\"line2d_12\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 49.807188 118.316267 \n", "L 496.207187 118.316267 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_13\">\n", "      <!-- 0.4 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(22.81375 122.495407)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" id=\"DejaVuSans-34\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_4\">\n", "     <g id=\"line2d_13\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 49.807188 88.481701 \n", "L 496.207187 88.481701 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_14\">\n", "      <!-- 0.6 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(22.81375 92.660842)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" id=\"DejaVuSans-36\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_5\">\n", "     <g id=\"line2d_14\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 49.807188 58.647135 \n", "L 496.207187 58.647135 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_15\">\n", "      <!-- 0.8 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(22.81375 62.826276)scale(0.11 -0.11)\">\n", "       <defs>\n", "        <path d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" id=\"DejaVuSans-38\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_6\">\n", "     <g id=\"line2d_15\">\n", "      <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 49.807188 28.81257 \n", "L 496.207187 28.81257 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;\"/>\n", "     </g>\n", "     <g id=\"text_16\">\n", "      <!-- 1.0 -->\n", "      <g style=\"fill:#262626;\" transform=\"translate(22.81375 32.99171)scale(0.11 -0.11)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n", "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"text_17\">\n", "     <!-- Learning rate factor -->\n", "     <g style=\"fill:#262626;\" transform=\"translate(16.318125 163.486875)rotate(-90)scale(0.12 -0.12)\">\n", "      <defs>\n", "       <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 531 \n", "L 3531 531 \n", "L 3531 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-4c\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2906 1791 \n", "Q 2906 2416 2648 2759 \n", "Q 2391 3103 1925 3103 \n", "Q 1463 3103 1205 2759 \n", "Q 947 2416 947 1791 \n", "Q 947 1169 1205 825 \n", "Q 1463 481 1925 481 \n", "Q 2391 481 2648 825 \n", "Q 2906 1169 2906 1791 \n", "z\n", "M 3481 434 \n", "Q 3481 -459 3084 -895 \n", "Q 2688 -1331 1869 -1331 \n", "Q 1566 -1331 1297 -1286 \n", "Q 1028 -1241 775 -1147 \n", "L 775 -588 \n", "Q 1028 -725 1275 -790 \n", "Q 1522 -856 1778 -856 \n", "Q 2344 -856 2625 -561 \n", "Q 2906 -266 2906 331 \n", "L 2906 616 \n", "Q 2728 306 2450 153 \n", "Q 2172 0 1784 0 \n", "Q 1141 0 747 490 \n", "Q 353 981 353 1791 \n", "Q 353 2603 747 3093 \n", "Q 1141 3584 1784 3584 \n", "Q 2172 3584 2450 3431 \n", "Q 2728 3278 2906 2969 \n", "L 2906 3500 \n", "L 3481 3500 \n", "L 3481 434 \n", "z\n", "\" id=\"DejaVuSans-67\" transform=\"scale(0.015625)\"/>\n", "       <path d=\"M 2375 4863 \n", "L 2375 4384 \n", "L 1825 4384 \n", "Q 1516 4384 1395 4259 \n", "Q 1275 4134 1275 3809 \n", "L 1275 3500 \n", "L 2222 3500 \n", "L 2222 3053 \n", "L 1275 3053 \n", "L 1275 0 \n", "L 697 0 \n", "L 697 3053 \n", "L 147 3053 \n", "L 147 3500 \n", "L 697 3500 \n", "L 697 3744 \n", "Q 697 4328 969 4595 \n", "Q 1241 4863 1831 4863 \n", "L 2375 4863 \n", "z\n", "\" id=\"DejaVuSans-66\" transform=\"scale(0.015625)\"/>\n", "      </defs>\n", "      <use xlink:href=\"#DejaVuSans-4c\"/>\n", "      <use x=\"53.962891\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"115.486328\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"176.765625\" xlink:href=\"#DejaVuSans-72\"/>\n", "      <use x=\"216.128906\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"279.507812\" xlink:href=\"#DejaVuSans-69\"/>\n", "      <use x=\"307.291016\" xlink:href=\"#DejaVuSans-6e\"/>\n", "      <use x=\"370.669922\" xlink:href=\"#DejaVuSans-67\"/>\n", "      <use x=\"434.146484\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"465.933594\" xlink:href=\"#DejaVuSans-72\"/>\n", "      <use x=\"507.046875\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"568.326172\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"607.535156\" xlink:href=\"#DejaVuSans-65\"/>\n", "      <use x=\"669.058594\" xlink:href=\"#DejaVuSans-20\"/>\n", "      <use x=\"700.845703\" xlink:href=\"#DejaVuSans-66\"/>\n", "      <use x=\"736.050781\" xlink:href=\"#DejaVuSans-61\"/>\n", "      <use x=\"797.330078\" xlink:href=\"#DejaVuSans-63\"/>\n", "      <use x=\"852.310547\" xlink:href=\"#DejaVuSans-74\"/>\n", "      <use x=\"891.519531\" xlink:href=\"#DejaVuSans-6f\"/>\n", "      <use x=\"952.701172\" xlink:href=\"#DejaVuSans-72\"/>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"line2d_16\">\n", "    <path clip-path=\"url(#p10c8c45f2a)\" d=\"M 70.098097 177.985398 \n", "L 89.587114 35.592052 \n", "L 90.399156 29.730852 \n", "L 97.504527 30.48331 \n", "L 104.609898 31.456105 \n", "L 111.918279 32.683463 \n", "L 119.226661 34.136891 \n", "L 126.738053 35.861378 \n", "L 134.249445 37.813933 \n", "L 141.963848 40.049729 \n", "L 149.881261 42.57891 \n", "L 158.001685 45.409884 \n", "L 166.325119 48.54904 \n", "L 174.851564 52.000456 \n", "L 183.78403 55.855814 \n", "L 193.122518 60.128835 \n", "L 203.070037 64.928363 \n", "L 213.626588 70.270225 \n", "L 225.198192 76.378163 \n", "L 238.19087 83.491721 \n", "L 254.025697 92.425912 \n", "L 281.432127 108.199226 \n", "L 303.154261 120.582905 \n", "L 317.771024 128.66423 \n", "L 330.15467 135.262305 \n", "L 341.320253 140.962432 \n", "L 351.673794 145.998525 \n", "L 361.418302 150.489325 \n", "L 370.553779 154.456898 \n", "L 379.283235 158.01014 \n", "L 387.80968 161.24043 \n", "L 395.930104 164.08312 \n", "L 403.847517 166.624241 \n", "L 411.561919 168.872118 \n", "L 419.276322 170.886789 \n", "L 426.787714 172.61752 \n", "L 434.096096 174.077165 \n", "L 441.404477 175.310859 \n", "L 448.712859 176.314657 \n", "L 455.818229 177.067115 \n", "L 462.9236 177.596962 \n", "L 470.028971 177.902597 \n", "L 475.916278 177.985306 \n", "L 475.916278 177.985306 \n", "\" style=\"fill:none;stroke:#4c72b0;stroke-linecap:round;stroke-width:1.5;\"/>\n", "   </g>\n", "   <g id=\"patch_3\">\n", "    <path d=\"M 49.807188 185.398125 \n", "L 49.807188 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_4\">\n", "    <path d=\"M 496.207187 185.398125 \n", "L 496.207187 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_5\">\n", "    <path d=\"M 49.807187 185.398125 \n", "L 496.207188 185.398125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"patch_6\">\n", "    <path d=\"M 49.807187 22.318125 \n", "L 496.207188 22.318125 \n", "\" style=\"fill:none;stroke:#ffffff;stroke-linecap:square;stroke-linejoin:miter;stroke-width:1.25;\"/>\n", "   </g>\n", "   <g id=\"text_18\">\n", "    <!-- Cosine Warm-up Learning Rate Scheduler -->\n", "    <g style=\"fill:#262626;\" transform=\"translate(148.179062 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 4122 4306 \n", "L 4122 3641 \n", "Q 3803 3938 3442 4084 \n", "Q 3081 4231 2675 4231 \n", "Q 1875 4231 1450 3742 \n", "Q 1025 3253 1025 2328 \n", "Q 1025 1406 1450 917 \n", "Q 1875 428 2675 428 \n", "Q 3081 428 3442 575 \n", "Q 3803 722 4122 1019 \n", "L 4122 359 \n", "Q 3791 134 3420 21 \n", "Q 3050 -91 2638 -91 \n", "Q 1578 -91 968 557 \n", "Q 359 1206 359 2328 \n", "Q 359 3453 968 4101 \n", "Q 1578 4750 2638 4750 \n", "Q 3056 4750 3426 4639 \n", "Q 3797 4528 4122 4306 \n", "z\n", "\" id=\"DejaVuSans-43\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 213 4666 \n", "L 850 4666 \n", "L 1831 722 \n", "L 2809 4666 \n", "L 3519 4666 \n", "L 4500 722 \n", "L 5478 4666 \n", "L 6119 4666 \n", "L 4947 0 \n", "L 4153 0 \n", "L 3169 4050 \n", "L 2175 0 \n", "L 1381 0 \n", "L 213 4666 \n", "z\n", "\" id=\"DejaVuSans-57\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" id=\"DejaVuSans-6d\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 313 2009 \n", "L 1997 2009 \n", "L 1997 1497 \n", "L 313 1497 \n", "L 313 2009 \n", "z\n", "\" id=\"DejaVuSans-2d\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 544 1381 \n", "L 544 3500 \n", "L 1119 3500 \n", "L 1119 1403 \n", "Q 1119 906 1312 657 \n", "Q 1506 409 1894 409 \n", "Q 2359 409 2629 706 \n", "Q 2900 1003 2900 1516 \n", "L 2900 3500 \n", "L 3475 3500 \n", "L 3475 0 \n", "L 2900 0 \n", "L 2900 538 \n", "Q 2691 219 2414 64 \n", "Q 2138 -91 1772 -91 \n", "Q 1169 -91 856 284 \n", "Q 544 659 544 1381 \n", "z\n", "M 1991 3584 \n", "L 1991 3584 \n", "z\n", "\" id=\"DejaVuSans-75\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1159 525 \n", "L 1159 -1331 \n", "L 581 -1331 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "z\n", "M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "\" id=\"DejaVuSans-70\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2841 2188 \n", "Q 3044 2119 3236 1894 \n", "Q 3428 1669 3622 1275 \n", "L 4263 0 \n", "L 3584 0 \n", "L 2988 1197 \n", "Q 2756 1666 2539 1819 \n", "Q 2322 1972 1947 1972 \n", "L 1259 1972 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "L 2053 4666 \n", "Q 2853 4666 3247 4331 \n", "Q 3641 3997 3641 3322 \n", "Q 3641 2881 3436 2590 \n", "Q 3231 2300 2841 2188 \n", "z\n", "M 1259 4147 \n", "L 1259 2491 \n", "L 2053 2491 \n", "Q 2509 2491 2742 2702 \n", "Q 2975 2913 2975 3322 \n", "Q 2975 3731 2742 3939 \n", "Q 2509 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "\" id=\"DejaVuSans-52\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3425 4513 \n", "L 3425 3897 \n", "Q 3066 4069 2747 4153 \n", "Q 2428 4238 2131 4238 \n", "Q 1616 4238 1336 4038 \n", "Q 1056 3838 1056 3469 \n", "Q 1056 3159 1242 3001 \n", "Q 1428 2844 1947 2747 \n", "L 2328 2669 \n", "Q 3034 2534 3370 2195 \n", "Q 3706 1856 3706 1288 \n", "Q 3706 609 3251 259 \n", "Q 2797 -91 1919 -91 \n", "Q 1588 -91 1214 -16 \n", "Q 841 59 441 206 \n", "L 441 856 \n", "Q 825 641 1194 531 \n", "Q 1563 422 1919 422 \n", "Q 2459 422 2753 634 \n", "Q 3047 847 3047 1241 \n", "Q 3047 1584 2836 1778 \n", "Q 2625 1972 2144 2069 \n", "L 1759 2144 \n", "Q 1053 2284 737 2584 \n", "Q 422 2884 422 3419 \n", "Q 422 4038 858 4394 \n", "Q 1294 4750 2059 4750 \n", "Q 2388 4750 2728 4690 \n", "Q 3069 4631 3425 4513 \n", "z\n", "\" id=\"DejaVuSans-53\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" id=\"DejaVuSans-64\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-6c\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-43\"/>\n", "     <use x=\"69.824219\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"131.005859\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"183.105469\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"210.888672\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"274.267578\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"335.791016\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"367.578125\" xlink:href=\"#DejaVuSans-57\"/>\n", "     <use x=\"460.080078\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"521.359375\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"560.722656\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"658.134766\" xlink:href=\"#DejaVuSans-2d\"/>\n", "     <use x=\"694.21875\" xlink:href=\"#DejaVuSans-75\"/>\n", "     <use x=\"757.597656\" xlink:href=\"#DejaVuSans-70\"/>\n", "     <use x=\"821.074219\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"852.861328\" xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"906.824219\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"968.347656\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"1029.626953\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"1068.990234\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1132.369141\" xlink:href=\"#DejaVuSans-69\"/>\n", "     <use x=\"1160.152344\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1223.53125\" xlink:href=\"#DejaVuSans-67\"/>\n", "     <use x=\"1287.007812\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1318.794922\" xlink:href=\"#DejaVuSans-52\"/>\n", "     <use x=\"1386.027344\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"1447.306641\" xlink:href=\"#DejaVuSans-74\"/>\n", "     <use x=\"1486.515625\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1548.039062\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1579.826172\" xlink:href=\"#DejaVuSans-53\"/>\n", "     <use x=\"1643.302734\" xlink:href=\"#DejaVuSans-63\"/>\n", "     <use x=\"1698.283203\" xlink:href=\"#DejaVuSans-68\"/>\n", "     <use x=\"1761.662109\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"1823.185547\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"1886.662109\" xlink:href=\"#DejaVuSans-75\"/>\n", "     <use x=\"1950.041016\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"1977.824219\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"2039.347656\" xlink:href=\"#DejaVuSans-72\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"p10c8c45f2a\">\n", "   <rect height=\"163.08\" width=\"446.4\" x=\"49.807188\" y=\"22.318125\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 576x216 with 1 Axes>"]}, "metadata": {}, "output_type": "display_data"}], "source": ["# Needed for initializing the lr scheduler\n", "p = nn.Parameter(torch.empty(4, 4))\n", "optimizer = optim.Adam([p], lr=1e-3)\n", "lr_scheduler = CosineWarmupScheduler(optimizer=optimizer, warmup=100, max_iters=2000)\n", "\n", "# Plotting\n", "epochs = list(range(2000))\n", "sns.set()\n", "plt.figure(figsize=(8, 3))\n", "plt.plot(epochs, [lr_scheduler.get_lr_factor(e) for e in epochs])\n", "plt.ylabel(\"Learning rate factor\")\n", "plt.xlabel(\"Iterations (in batches)\")\n", "plt.title(\"Cosine Warm-up Learning Rate Scheduler\")\n", "plt.show()\n", "sns.reset_orig()"]}, {"cell_type": "markdown", "id": "54af6807", "metadata": {"papermill": {"duration": 0.154142, "end_time": "2021-12-04T15:58:16.048540", "exception": false, "start_time": "2021-12-04T15:58:15.894398", "status": "completed"}, "tags": []}, "source": ["In the first 100 iterations, we increase the learning rate factor from 0 to 1,\n", "whereas for all later iterations, we decay it using the cosine wave.\n", "Pre-implementations of this scheduler can be found in the popular NLP Transformer library\n", "[huggingface](https://huggingface.co/transformers/main_classes/optimizer_schedules.html?highlight=cosine#transformers.get_cosine_schedule_with_warmup)."]}, {"cell_type": "markdown", "id": "a8c7d2a2", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.154296, "end_time": "2021-12-04T15:58:16.357362", "exception": false, "start_time": "2021-12-04T15:58:16.203066", "status": "completed"}, "tags": []}, "source": ["### PyTorch Lightning Module\n", "\n", "Finally, we can embed the Transformer architecture into a PyTorch lightning module.\n", "From Tutorial 5, you know that PyTorch Lightning simplifies our training and test code,\n", "as well as structures the code nicely in separate functions.\n", "We will implement a template for a classifier based on the Transformer encoder.\n", "Thereby, we have a prediction output per sequence element.\n", "If we would need a classifier over the whole sequence, the common approach is to add an additional\n", "`[CLS]` token to the sequence, representing the classifier token.\n", "However, here we focus on tasks where we have an output per element.\n", "\n", "Additionally to the Transformer architecture, we add a small input network (maps input dimensions to model dimensions),\n", "the positional encoding, and an output network (transforms output encodings to predictions).\n", "We also add the learning rate scheduler, which takes a step each iteration instead of once per epoch.\n", "This is needed for the warmup and the smooth cosine decay.\n", "The training, validation, and test step is left empty for now and will be filled for our task-specific models."]}, {"cell_type": "code", "execution_count": 14, "id": "a392e677", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:16.678659Z", "iopub.status.busy": "2021-12-04T15:58:16.678143Z", "iopub.status.idle": "2021-12-04T15:58:16.680126Z", "shell.execute_reply": "2021-12-04T15:58:16.679738Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.168727, "end_time": "2021-12-04T15:58:16.680237", "exception": false, "start_time": "2021-12-04T15:58:16.511510", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class TransformerPredictor(pl.LightningModule):\n", "    def __init__(\n", "        self,\n", "        input_dim,\n", "        model_dim,\n", "        num_classes,\n", "        num_heads,\n", "        num_layers,\n", "        lr,\n", "        warmup,\n", "        max_iters,\n", "        dropout=0.0,\n", "        input_dropout=0.0,\n", "    ):\n", "        \"\"\"\n", "        Args:\n", "            input_dim: Hidden dimensionality of the input\n", "            model_dim: Hidden dimensionality to use inside the Transformer\n", "            num_classes: Number of classes to predict per sequence element\n", "            num_heads: Number of heads to use in the Multi-Head Attention blocks\n", "            num_layers: Number of encoder blocks to use.\n", "            lr: Learning rate in the optimizer\n", "            warmup: Number of warmup steps. Usually between 50 and 500\n", "            max_iters: Number of maximum iterations the model is trained for. This is needed for the CosineWarmup scheduler\n", "            dropout: Dropout to apply inside the model\n", "            input_dropout: Dropout to apply on the input features\n", "        \"\"\"\n", "        super().__init__()\n", "        self.save_hyperparameters()\n", "        self._create_model()\n", "\n", "    def _create_model(self):\n", "        # Input dim -> Model dim\n", "        self.input_net = nn.Sequential(\n", "            nn.Dropout(self.hparams.input_dropout), nn.Linear(self.hparams.input_dim, self.hparams.model_dim)\n", "        )\n", "        # Positional encoding for sequences\n", "        self.positional_encoding = PositionalEncoding(d_model=self.hparams.model_dim)\n", "        # Transformer\n", "        self.transformer = TransformerEncoder(\n", "            num_layers=self.hparams.num_layers,\n", "            input_dim=self.hparams.model_dim,\n", "            dim_feedforward=2 * self.hparams.model_dim,\n", "            num_heads=self.hparams.num_heads,\n", "            dropout=self.hparams.dropout,\n", "        )\n", "        # Output classifier per sequence lement\n", "        self.output_net = nn.Sequential(\n", "            nn.Linear(self.hparams.model_dim, self.hparams.model_dim),\n", "            nn.LayerNorm(self.hparams.model_dim),\n", "            nn.ReLU(inplace=True),\n", "            nn.Dropout(self.hparams.dropout),\n", "            nn.Linear(self.hparams.model_dim, self.hparams.num_classes),\n", "        )\n", "\n", "    def forward(self, x, mask=None, add_positional_encoding=True):\n", "        \"\"\"\n", "        Args:\n", "            x: Input features of shape [Batch, SeqLen, input_dim]\n", "            mask: Mask to apply on the attention outputs (optional)\n", "            add_positional_encoding: If True, we add the positional encoding to the input.\n", "                                      Might not be desired for some tasks.\n", "        \"\"\"\n", "        x = self.input_net(x)\n", "        if add_positional_encoding:\n", "            x = self.positional_encoding(x)\n", "        x = self.transformer(x, mask=mask)\n", "        x = self.output_net(x)\n", "        return x\n", "\n", "    @torch.no_grad()\n", "    def get_attention_maps(self, x, mask=None, add_positional_encoding=True):\n", "        \"\"\"Function for extracting the attention matrices of the whole Transformer for a single batch.\n", "\n", "        Input arguments same as the forward pass.\n", "        \"\"\"\n", "        x = self.input_net(x)\n", "        if add_positional_encoding:\n", "            x = self.positional_encoding(x)\n", "        attention_maps = self.transformer.get_attention_maps(x, mask=mask)\n", "        return attention_maps\n", "\n", "    def configure_optimizers(self):\n", "        optimizer = optim.Adam(self.parameters(), lr=self.hparams.lr)\n", "\n", "        # We don't return the lr scheduler because we need to apply it per iteration, not per epoch\n", "        self.lr_scheduler = CosineWarmupScheduler(\n", "            optimizer, warmup=self.hparams.warmup, max_iters=self.hparams.max_iters\n", "        )\n", "        return optimizer\n", "\n", "    def optimizer_step(self, *args, **kwargs):\n", "        super().optimizer_step(*args, **kwargs)\n", "        self.lr_scheduler.step()  # Step per iteration\n", "\n", "    def training_step(self, batch, batch_idx):\n", "        raise NotImplementedError\n", "\n", "    def validation_step(self, batch, batch_idx):\n", "        raise NotImplementedError\n", "\n", "    def test_step(self, batch, batch_idx):\n", "        raise NotImplementedError"]}, {"cell_type": "markdown", "id": "2818f62b", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.154523, "end_time": "2021-12-04T15:58:16.990037", "exception": false, "start_time": "2021-12-04T15:58:16.835514", "status": "completed"}, "tags": []}, "source": ["## Experiments\n", "\n", "<div class=\"center-wrapper\"><div class=\"video-wrapper\"><iframe src=\"https://www.youtube.com/embed/e7xvF2yS4Dg\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe></div></div>\n", "\n", "After having finished the implementation of the Transformer architecture, we can start experimenting\n", "and apply it to various tasks.\n", "In this notebook, we will focus on two tasks: parallel Sequence-to-Sequence, and set anomaly detection.\n", "The two tasks focus on different properties of the Transformer architecture, and we go through them below.\n", "\n", "### Sequence to Sequence\n", "\n", "A Sequence-to-Sequence task represents a task where the input _and_ the output is a sequence,\n", "not necessarily of the same length.\n", "Popular tasks in this domain include machine translation and summarization.\n", "For this, we usually have a Transformer encoder for interpreting the input sequence,\n", "and a decoder for generating the output in an autoregressive manner.\n", "Here, however, we will go back to a much simpler example task and use only the encoder.\n", "Given a sequence of $N$ numbers between $0$ and $M$, the task is to reverse the input sequence.\n", "In Numpy notation, if our input is $x$, the output should be $x$[::-1].\n", "Although this task sounds very simple, RNNs can have issues with such because the task requires long-term dependencies.\n", "Transformers are built to support such, and hence, we expect it to perform very well.\n", "\n", "First, let's create a dataset class below."]}, {"cell_type": "code", "execution_count": 15, "id": "d73f1841", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:17.308123Z", "iopub.status.busy": "2021-12-04T15:58:17.307642Z", "iopub.status.idle": "2021-12-04T15:58:17.309563Z", "shell.execute_reply": "2021-12-04T15:58:17.309179Z"}, "papermill": {"duration": 0.163367, "end_time": "2021-12-04T15:58:17.309674", "exception": false, "start_time": "2021-12-04T15:58:17.146307", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class ReverseDataset(data.Dataset):\n", "    def __init__(self, num_categories, seq_len, size):\n", "        super().__init__()\n", "        self.num_categories = num_categories\n", "        self.seq_len = seq_len\n", "        self.size = size\n", "\n", "        self.data = torch.randint(self.num_categories, size=(self.size, self.seq_len))\n", "\n", "    def __len__(self):\n", "        return self.size\n", "\n", "    def __getitem__(self, idx):\n", "        inp_data = self.data[idx]\n", "        labels = torch.flip(inp_data, dims=(0,))\n", "        return inp_data, labels"]}, {"cell_type": "markdown", "id": "5640c756", "metadata": {"papermill": {"duration": 0.157285, "end_time": "2021-12-04T15:58:17.623302", "exception": false, "start_time": "2021-12-04T15:58:17.466017", "status": "completed"}, "tags": []}, "source": ["We create an arbitrary number of random sequences of numbers between 0 and `num_categories-1`.\n", "The label is simply the tensor flipped over the sequence dimension.\n", "We can create the corresponding data loaders below."]}, {"cell_type": "code", "execution_count": 16, "id": "8e1d16b7", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:17.940041Z", "iopub.status.busy": "2021-12-04T15:58:17.939564Z", "iopub.status.idle": "2021-12-04T15:58:17.956756Z", "shell.execute_reply": "2021-12-04T15:58:17.957137Z"}, "papermill": {"duration": 0.177314, "end_time": "2021-12-04T15:58:17.957279", "exception": false, "start_time": "2021-12-04T15:58:17.779965", "status": "completed"}, "tags": []}, "outputs": [], "source": ["dataset = partial(ReverseDataset, 10, 16)\n", "train_loader = data.DataLoader(dataset(50000), batch_size=128, shuffle=True, drop_last=True, pin_memory=True)\n", "val_loader = data.DataLoader(dataset(1000), batch_size=128)\n", "test_loader = data.DataLoader(dataset(10000), batch_size=128)"]}, {"cell_type": "markdown", "id": "7a21b9dc", "metadata": {"papermill": {"duration": 0.156233, "end_time": "2021-12-04T15:58:18.269306", "exception": false, "start_time": "2021-12-04T15:58:18.113073", "status": "completed"}, "tags": []}, "source": ["Let's look at an arbitrary sample of the dataset:"]}, {"cell_type": "code", "execution_count": 17, "id": "aeda9084", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:18.587916Z", "iopub.status.busy": "2021-12-04T15:58:18.587443Z", "iopub.status.idle": "2021-12-04T15:58:18.590343Z", "shell.execute_reply": "2021-12-04T15:58:18.590793Z"}, "papermill": {"duration": 0.16296, "end_time": "2021-12-04T15:58:18.590927", "exception": false, "start_time": "2021-12-04T15:58:18.427967", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Input data: tensor([9, 6, 2, 0, 6, 2, 7, 9, 7, 3, 3, 4, 3, 7, 0, 9])\n", "Labels:     tensor([9, 0, 7, 3, 4, 3, 3, 7, 9, 7, 2, 6, 0, 2, 6, 9])\n"]}], "source": ["inp_data, labels = train_loader.dataset[0]\n", "print(\"Input data:\", inp_data)\n", "print(\"Labels:    \", labels)"]}, {"cell_type": "markdown", "id": "e5c8430c", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.156663, "end_time": "2021-12-04T15:58:18.903232", "exception": false, "start_time": "2021-12-04T15:58:18.746569", "status": "completed"}, "tags": []}, "source": ["During training, we pass the input sequence through the Transformer encoder and predict the output for each input token.\n", "We use the standard Cross-Entropy loss to perform this.\n", "Every number is represented as a one-hot vector.\n", "Remember that representing the categories as single scalars decreases the expressiveness of the model extremely\n", "as $0$ and $1$ are not closer related than $0$ and $9$ in our example.\n", "An alternative to a one-hot vector is using a learned embedding vector as it is provided by the PyTorch module `nn.Embedding`.\n", "However, using a one-hot vector with an additional linear layer as in our case has the same effect\n", "as an embedding layer (`self.input_net` maps one-hot vector to a dense vector,\n", "where each row of the weight matrix represents the embedding for a specific category).\n", "\n", "To implement the training dynamic, we create a new class inheriting from `TransformerPredictor`\n", "and overwriting the training, validation and test step functions."]}, {"cell_type": "code", "execution_count": 18, "id": "9e00bf72", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:19.222837Z", "iopub.status.busy": "2021-12-04T15:58:19.222299Z", "iopub.status.idle": "2021-12-04T15:58:19.224262Z", "shell.execute_reply": "2021-12-04T15:58:19.223880Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.164853, "end_time": "2021-12-04T15:58:19.224372", "exception": false, "start_time": "2021-12-04T15:58:19.059519", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class ReversePredictor(TransformerPredictor):\n", "    def _calculate_loss(self, batch, mode=\"train\"):\n", "        # Fetch data and transform categories to one-hot vectors\n", "        inp_data, labels = batch\n", "        inp_data = F.one_hot(inp_data, num_classes=self.hparams.num_classes).float()\n", "\n", "        # Perform prediction and calculate loss and accuracy\n", "        preds = self.forward(inp_data, add_positional_encoding=True)\n", "        loss = F.cross_entropy(preds.view(-1, preds.size(-1)), labels.view(-1))\n", "        acc = (preds.argmax(dim=-1) == labels).float().mean()\n", "\n", "        # Logging\n", "        self.log(\"%s_loss\" % mode, loss)\n", "        self.log(\"%s_acc\" % mode, acc)\n", "        return loss, acc\n", "\n", "    def training_step(self, batch, batch_idx):\n", "        loss, _ = self._calculate_loss(batch, mode=\"train\")\n", "        return loss\n", "\n", "    def validation_step(self, batch, batch_idx):\n", "        _ = self._calculate_loss(batch, mode=\"val\")\n", "\n", "    def test_step(self, batch, batch_idx):\n", "        _ = self._calculate_loss(batch, mode=\"test\")"]}, {"cell_type": "markdown", "id": "5bbaf3a6", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.155556, "end_time": "2021-12-04T15:58:19.534838", "exception": false, "start_time": "2021-12-04T15:58:19.379282", "status": "completed"}, "tags": []}, "source": ["Finally, we can create a training function similar to the one we have seen in Tutorial 5 for PyTorch Lightning.\n", "We create a `pl.Trainer` object, running for $N$ epochs, logging in TensorBoard, and saving our best model based on the validation.\n", "Afterward, we test our models on the test set.\n", "An additional parameter we pass to the trainer here is `gradient_clip_val`.\n", "This clips the norm of the gradients for all parameters before taking an optimizer step and prevents the model\n", "from diverging if we obtain very high gradients at, for instance, sharp loss surfaces (see many good blog posts\n", "on gradient clipping, like [DeepAI glossary](https://deepai.org/machine-learning-glossary-and-terms/gradient-clipping)).\n", "For Transformers, gradient clipping can help to further stabilize the training during the first few iterations, and also afterward.\n", "In plain PyTorch, you can apply gradient clipping via `torch.nn.utils.clip_grad_norm_(...)`\n", "(see [documentation](https://pytorch.org/docs/stable/generated/torch.nn.utils.clip_grad_norm_.html#torch.nn.utils.clip_grad_norm_)).\n", "The clip value is usually between 0.5 and 10, depending on how harsh you want to clip large gradients.\n", "After having explained this, let's implement the training function:"]}, {"cell_type": "code", "execution_count": 19, "id": "13fba27b", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:19.861262Z", "iopub.status.busy": "2021-12-04T15:58:19.860777Z", "iopub.status.idle": "2021-12-04T15:58:19.862292Z", "shell.execute_reply": "2021-12-04T15:58:19.862689Z"}, "papermill": {"duration": 0.170942, "end_time": "2021-12-04T15:58:19.862822", "exception": false, "start_time": "2021-12-04T15:58:19.691880", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def train_reverse(**kwargs):\n", "    # Create a PyTorch Lightning trainer with the generation callback\n", "    root_dir = os.path.join(CHECKPOINT_PATH, \"ReverseTask\")\n", "    os.makedirs(root_dir, exist_ok=True)\n", "    trainer = pl.Trainer(\n", "        default_root_dir=root_dir,\n", "        callbacks=[ModelCheckpoint(save_weights_only=True, mode=\"max\", monitor=\"val_acc\")],\n", "        gpus=1 if str(device).startswith(\"cuda\") else 0,\n", "        max_epochs=10,\n", "        gradient_clip_val=5,\n", "        progress_bar_refresh_rate=1,\n", "    )\n", "    trainer.logger._default_hp_metric = None  # Optional logging argument that we don't need\n", "\n", "    # Check whether pretrained model exists. If yes, load it and skip training\n", "    pretrained_filename = os.path.join(CHECKPOINT_PATH, \"ReverseTask.ckpt\")\n", "    if os.path.isfile(pretrained_filename):\n", "        print(\"Found pretrained model, loading...\")\n", "        model = ReversePredictor.load_from_checkpoint(pretrained_filename)\n", "    else:\n", "        model = ReversePredictor(max_iters=trainer.max_epochs * len(train_loader), **kwargs)\n", "        trainer.fit(model, train_loader, val_loader)\n", "\n", "    # Test best model on validation and test set\n", "    val_result = trainer.test(model, test_dataloaders=val_loader, verbose=False)\n", "    test_result = trainer.test(model, test_dataloaders=test_loader, verbose=False)\n", "    result = {\"test_acc\": test_result[0][\"test_acc\"], \"val_acc\": val_result[0][\"test_acc\"]}\n", "\n", "    model = model.to(device)\n", "    return model, result"]}, {"cell_type": "markdown", "id": "11c5e6ce", "metadata": {"papermill": {"duration": 0.157063, "end_time": "2021-12-04T15:58:20.175228", "exception": false, "start_time": "2021-12-04T15:58:20.018165", "status": "completed"}, "tags": []}, "source": ["Finally, we can train the model.\n", "In this setup, we will use a single encoder block and a single head in the Multi-Head Attention.\n", "This is chosen because of the simplicity of the task, and in this case, the attention can actually be interpreted\n", "as an \"explanation\" of the predictions (compared to the other papers above dealing with deep Transformers)."]}, {"cell_type": "code", "execution_count": 20, "id": "a41d7448", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:20.491778Z", "iopub.status.busy": "2021-12-04T15:58:20.491301Z", "iopub.status.idle": "2021-12-04T15:58:24.308685Z", "shell.execute_reply": "2021-12-04T15:58:24.308229Z"}, "papermill": {"duration": 3.977688, "end_time": "2021-12-04T15:58:24.308813", "exception": false, "start_time": "2021-12-04T15:58:20.331125", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["/home/AzDevOps_azpcontainer/.local/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning: Setting `Trainer(progress_bar_refresh_rate=1)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.\n", "  rank_zero_deprecation(\n", "GPU available: True, used: True\n"]}, {"name": "stderr", "output_type": "stream", "text": ["TPU available: False, using: 0 TPU cores\n"]}, {"name": "stderr", "output_type": "stream", "text": ["IPU available: False, using: 0 IPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["/home/AzDevOps_azpcontainer/.local/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:901: LightningDeprecationWarning: `trainer.test(test_dataloaders)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.test(dataloaders)` instead.\n", "  rank_zero_deprecation(\n", "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Found pretrained model, loading...\n"]}, {"name": "stderr", "output_type": "stream", "text": ["Missing logger folder: saved_models/Transformers/ReverseTask/lightning_logs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["/home/AzDevOps_azpcontainer/.local/lib/python3.9/site-packages/pytorch_lightning/trainer/data_loading.py:111: UserWarning: The dataloader, test_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n", "  rank_zero_warn(\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "b9ed1cfedbeb4586bab29909930e47b1", "version_major": 2, "version_minor": 0}, "text/plain": ["Testing: 0it [00:00, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stderr", "output_type": "stream", "text": ["LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "89c0145b83d34648bacf9da6ad15d74d", "version_major": 2, "version_minor": 0}, "text/plain": ["Testing: 0it [00:00, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}], "source": ["reverse_model, reverse_result = train_reverse(\n", "    input_dim=train_loader.dataset.num_categories,\n", "    model_dim=32,\n", "    num_heads=1,\n", "    num_classes=train_loader.dataset.num_categories,\n", "    num_layers=1,\n", "    dropout=0.0,\n", "    lr=5e-4,\n", "    warmup=50,\n", ")"]}, {"cell_type": "markdown", "id": "ccc85090", "metadata": {"papermill": {"duration": 0.163772, "end_time": "2021-12-04T15:58:24.638088", "exception": false, "start_time": "2021-12-04T15:58:24.474316", "status": "completed"}, "tags": []}, "source": ["The warning of PyTorch Lightning regarding the number of workers can be ignored for now.\n", "As the data set is so simple and the `__getitem__` finishes a neglectable time, we don't need subprocesses\n", "to provide us the data (in fact, more workers can slow down the training as we have communication overhead among processes/threads).\n", "First, let's print the results:"]}, {"cell_type": "code", "execution_count": 21, "id": "02e867c0", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:24.972467Z", "iopub.status.busy": "2021-12-04T15:58:24.971991Z", "iopub.status.idle": "2021-12-04T15:58:24.974029Z", "shell.execute_reply": "2021-12-04T15:58:24.974648Z"}, "papermill": {"duration": 0.171511, "end_time": "2021-12-04T15:58:24.974782", "exception": false, "start_time": "2021-12-04T15:58:24.803271", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Val accuracy:  100.00%\n", "Test accuracy: 100.00%\n"]}], "source": ["print(\"Val accuracy:  %4.2f%%\" % (100.0 * reverse_result[\"val_acc\"]))\n", "print(\"Test accuracy: %4.2f%%\" % (100.0 * reverse_result[\"test_acc\"]))"]}, {"cell_type": "markdown", "id": "389ff9fb", "metadata": {"papermill": {"duration": 0.164894, "end_time": "2021-12-04T15:58:25.304480", "exception": false, "start_time": "2021-12-04T15:58:25.139586", "status": "completed"}, "tags": []}, "source": ["As we would have expected, the Transformer can correctly solve the task.\n", "However, how does the attention in the Multi-Head Attention block looks like for an arbitrary input?\n", "Let's try to visualize it below."]}, {"cell_type": "code", "execution_count": 22, "id": "f740e35c", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:25.645172Z", "iopub.status.busy": "2021-12-04T15:58:25.644677Z", "iopub.status.idle": "2021-12-04T15:58:25.650646Z", "shell.execute_reply": "2021-12-04T15:58:25.650153Z"}, "papermill": {"duration": 0.178894, "end_time": "2021-12-04T15:58:25.650756", "exception": false, "start_time": "2021-12-04T15:58:25.471862", "status": "completed"}, "tags": []}, "outputs": [], "source": ["data_input, labels = next(iter(val_loader))\n", "inp_data = F.one_hot(data_input, num_classes=reverse_model.hparams.num_classes).float()\n", "inp_data = inp_data.to(device)\n", "attention_maps = reverse_model.get_attention_maps(inp_data)"]}, {"cell_type": "markdown", "id": "82e9b36d", "metadata": {"papermill": {"duration": 0.164929, "end_time": "2021-12-04T15:58:25.982199", "exception": false, "start_time": "2021-12-04T15:58:25.817270", "status": "completed"}, "tags": []}, "source": ["The object `attention_maps` is a list of length $N$ where $N$ is the number of layers.\n", "Each element is a tensor of shape [Batch, Heads, SeqLen, SeqLen], which we can verify below."]}, {"cell_type": "code", "execution_count": 23, "id": "ba03c69a", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:26.324791Z", "iopub.status.busy": "2021-12-04T15:58:26.324320Z", "iopub.status.idle": "2021-12-04T15:58:26.326971Z", "shell.execute_reply": "2021-12-04T15:58:26.326543Z"}, "papermill": {"duration": 0.178216, "end_time": "2021-12-04T15:58:26.327081", "exception": false, "start_time": "2021-12-04T15:58:26.148865", "status": "completed"}, "tags": []}, "outputs": [{"data": {"text/plain": ["torch.Size([128, 1, 16, 16])"]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["attention_maps[0].shape"]}, {"cell_type": "markdown", "id": "1ff46b13", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.16452, "end_time": "2021-12-04T15:58:26.658828", "exception": false, "start_time": "2021-12-04T15:58:26.494308", "status": "completed"}, "tags": []}, "source": ["Next, we will write a plotting function that takes as input the sequences, attention maps, and an index\n", "indicating for which batch element we want to visualize the attention map.\n", "We will create a plot where over rows, we have different layers, while over columns, we show the different heads.\n", "Remember that the softmax has been applied for each row separately."]}, {"cell_type": "code", "execution_count": 24, "id": "f23fa88e", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:26.999173Z", "iopub.status.busy": "2021-12-04T15:58:26.998690Z", "iopub.status.idle": "2021-12-04T15:58:27.000240Z", "shell.execute_reply": "2021-12-04T15:58:27.000618Z"}, "papermill": {"duration": 0.176536, "end_time": "2021-12-04T15:58:27.000749", "exception": false, "start_time": "2021-12-04T15:58:26.824213", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def plot_attention_maps(input_data, attn_maps, idx=0):\n", "    if input_data is not None:\n", "        input_data = input_data[idx].detach().cpu().numpy()\n", "    else:\n", "        input_data = np.arange(attn_maps[0][idx].shape[-1])\n", "    attn_maps = [m[idx].detach().cpu().numpy() for m in attn_maps]\n", "\n", "    num_heads = attn_maps[0].shape[0]\n", "    num_layers = len(attn_maps)\n", "    seq_len = input_data.shape[0]\n", "    fig_size = 4 if num_heads == 1 else 3\n", "    fig, ax = plt.subplots(num_layers, num_heads, figsize=(num_heads * fig_size, num_layers * fig_size))\n", "    if num_layers == 1:\n", "        ax = [ax]\n", "    if num_heads == 1:\n", "        ax = [[a] for a in ax]\n", "    for row in range(num_layers):\n", "        for column in range(num_heads):\n", "            ax[row][column].imshow(attn_maps[row][column], origin=\"lower\", vmin=0)\n", "            ax[row][column].set_xticks(list(range(seq_len)))\n", "            ax[row][column].set_xticklabels(input_data.tolist())\n", "            ax[row][column].set_yticks(list(range(seq_len)))\n", "            ax[row][column].set_yticklabels(input_data.tolist())\n", "            ax[row][column].set_title(\"Layer %i, Head %i\" % (row + 1, column + 1))\n", "    fig.subplots_adjust(hspace=0.5)\n", "    plt.show()"]}, {"cell_type": "markdown", "id": "5575de2c", "metadata": {"papermill": {"duration": 0.165585, "end_time": "2021-12-04T15:58:27.339327", "exception": false, "start_time": "2021-12-04T15:58:27.173742", "status": "completed"}, "tags": []}, "source": ["Finally, we can plot the attention map of our trained Transformer on the reverse task:"]}, {"cell_type": "code", "execution_count": 25, "id": "70711ff5", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:27.678174Z", "iopub.status.busy": "2021-12-04T15:58:27.677704Z", "iopub.status.idle": "2021-12-04T15:58:28.093751Z", "shell.execute_reply": "2021-12-04T15:58:28.094142Z"}, "papermill": {"duration": 0.587062, "end_time": "2021-12-04T15:58:28.094303", "exception": false, "start_time": "2021-12-04T15:58:27.507241", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"263.63625pt\" version=\"1.1\" viewBox=\"0 0 245.2025 263.63625\" width=\"245.2025pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:58:27.918905</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 263.63625 \n", "L 245.2025 263.63625 \n", "L 245.2025 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g id=\"patch_2\">\n", "    <path d=\"M 20.5625 239.758125 \n", "L 238.0025 239.758125 \n", "L 238.0025 22.318125 \n", "L 20.5625 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pc938b705e4)\">\n", "    <image height=\"218\" id=\"image2361410ca4\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.758125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_1\">\n", "    <g id=\"xtick_1\">\n", "     <g id=\"line2d_1\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L 0 3.5 \n", "\" id=\"ma790357cec\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"27.3575\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_1\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(24.17625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" id=\"DejaVuSans-39\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_2\">\n", "     <g id=\"line2d_2\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.9475\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_2\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(37.76625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" id=\"DejaVuSans-34\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_3\">\n", "     <g id=\"line2d_3\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"54.5375\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_3\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(51.35625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" id=\"DejaVuSans-37\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_4\">\n", "     <g id=\"line2d_4\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"68.1275\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_4\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(64.94625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_5\">\n", "     <g id=\"line2d_5\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"81.7175\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_5\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(78.53625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" id=\"DejaVuSans-33\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_6\">\n", "     <g id=\"line2d_6\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"95.3075\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_6\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(92.12625 254.356563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_7\">\n", "     <g id=\"line2d_7\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"108.8975\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_7\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(105.71625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_8\">\n", "     <g id=\"line2d_8\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"122.4875\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_8\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(119.30625 254.356563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_9\">\n", "     <g id=\"line2d_9\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"136.0775\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_9\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(132.89625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" id=\"DejaVuSans-36\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_10\">\n", "     <g id=\"line2d_10\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"149.6675\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_10\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(146.48625 254.356563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_11\">\n", "     <g id=\"line2d_11\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"163.2575\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_11\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(160.07625 254.356563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_12\">\n", "     <g id=\"line2d_12\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"176.8475\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_12\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(173.66625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" id=\"DejaVuSans-32\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_13\">\n", "     <g id=\"line2d_13\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"190.4375\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_13\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(187.25625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" id=\"DejaVuSans-35\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_14\">\n", "     <g id=\"line2d_14\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"204.0275\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_14\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(200.84625 254.356563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_15\">\n", "     <g id=\"line2d_15\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"217.6175\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_15\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(214.43625 254.356563)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" id=\"DejaVuSans-38\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_16\">\n", "     <g id=\"line2d_16\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"231.2075\" xlink:href=\"#ma790357cec\" y=\"239.758125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_16\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(228.02625 254.356563)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_2\">\n", "    <g id=\"ytick_1\">\n", "     <g id=\"line2d_17\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L -3.5 0 \n", "\" id=\"mc325d06913\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"232.963125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_17\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 236.762344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_2\">\n", "     <g id=\"line2d_18\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"219.373125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_18\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 223.172344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_3\">\n", "     <g id=\"line2d_19\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"205.783125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_19\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 209.582344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_4\">\n", "     <g id=\"line2d_20\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"192.193125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_20\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 195.992344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_5\">\n", "     <g id=\"line2d_21\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"178.603125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_21\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 182.402344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_6\">\n", "     <g id=\"line2d_22\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"165.013125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_22\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 168.812344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_7\">\n", "     <g id=\"line2d_23\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"151.423125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_23\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 155.222344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_8\">\n", "     <g id=\"line2d_24\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"137.833125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_24\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 141.632344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_9\">\n", "     <g id=\"line2d_25\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"124.243125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_25\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 128.042344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_10\">\n", "     <g id=\"line2d_26\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"110.653125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_26\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 114.452344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_11\">\n", "     <g id=\"line2d_27\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"97.063125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_27\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 100.862344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_12\">\n", "     <g id=\"line2d_28\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"83.473125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_28\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 87.272344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_13\">\n", "     <g id=\"line2d_29\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"69.883125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_29\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 73.682344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_14\">\n", "     <g id=\"line2d_30\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"56.293125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_30\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 60.092344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_15\">\n", "     <g id=\"line2d_31\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"42.703125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_31\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 46.502344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_16\">\n", "     <g id=\"line2d_32\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mc325d06913\" y=\"29.113125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_32\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 32.912344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_3\">\n", "    <path d=\"M 20.5625 239.758125 \n", "L 20.5625 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_4\">\n", "    <path d=\"M 238.0025 239.758125 \n", "L 238.0025 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_5\">\n", "    <path d=\"M 20.5625 239.758125 \n", "L 238.0025 239.758125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_6\">\n", "    <path d=\"M 20.5625 22.318125 \n", "L 238.0025 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_33\">\n", "    <!-- Layer 1, Head 1 -->\n", "    <g transform=\"translate(81.600313 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 531 \n", "L 3531 531 \n", "L 3531 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-4c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" id=\"DejaVuSans-79\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" id=\"DejaVuSans-72\" transform=\"scale(0.015625)\"/>\n", "      <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 750 794 \n", "L 1409 794 \n", "L 1409 256 \n", "L 897 -744 \n", "L 494 -744 \n", "L 750 256 \n", "L 750 794 \n", "z\n", "\" id=\"DejaVuSans-2c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 2753 \n", "L 3553 2753 \n", "L 3553 4666 \n", "L 4184 4666 \n", "L 4184 0 \n", "L 3553 0 \n", "L 3553 2222 \n", "L 1259 2222 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-48\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" id=\"DejaVuSans-64\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"pc938b705e4\">\n", "   <rect height=\"217.44\" width=\"217.44\" x=\"20.5625\" y=\"22.318125\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 288x288 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plot_attention_maps(data_input, attention_maps, idx=0)"]}, {"cell_type": "markdown", "id": "163001ca", "metadata": {"papermill": {"duration": 0.169201, "end_time": "2021-12-04T15:58:28.432387", "exception": false, "start_time": "2021-12-04T15:58:28.263186", "status": "completed"}, "tags": []}, "source": ["The model has learned to attend to the token that is on the flipped index of itself.\n", "Hence, it actually does what we intended it to do.\n", "We see that it however also pays some attention to values close to the flipped index.\n", "This is because the model doesn't need the perfect, hard attention to solve this problem,\n", "but is fine with this approximate, noisy attention map.\n", "The close-by indices are caused by the similarity of the positional encoding,\n", "which we also intended with the positional encoding."]}, {"cell_type": "markdown", "id": "d8ac4d91", "metadata": {"papermill": {"duration": 0.169547, "end_time": "2021-12-04T15:58:28.770515", "exception": false, "start_time": "2021-12-04T15:58:28.600968", "status": "completed"}, "tags": []}, "source": ["### Set Anomaly Detection\n", "\n", "Besides sequences, sets are another data structure that is relevant for many applications.\n", "In contrast to sequences, elements are unordered in a set.\n", "RNNs can only be applied on sets by assuming an order in the data, which however biases the model towards\n", "a non-existing order in the data.\n", "[Vinyals et al.\n", "(2015)](https://arxiv.org/abs/1511.06391) and other papers have shown that the assumed order can have a significant\n", "impact on the model's performance, and hence, we should try to not use RNNs on sets.\n", "Ideally, our model should be permutation-equivariant/invariant such that the output is the same no matter how we sort the elements in a set.\n", "\n", "Transformers offer the perfect architecture for this as the Multi-Head Attention is permutation-equivariant, and thus,\n", "outputs the same values no matter in what order we enter the inputs (inputs and outputs are permuted equally).\n", "The task we are looking at for sets is _Set Anomaly Detection_ which means that we try to find the element(s)\n", "in a set that does not fit the others.\n", "In the research community, the common application of anomaly detection is performed on a set of images,\n", "where $N-1$ images belong to the same category/have the same high-level features while one belongs to another category.\n", "Note that category does not necessarily have to relate to a class in a standard classification problem,\n", "but could be the combination of multiple features.\n", "For instance, on a face dataset, this could be people with glasses, male, beard, etc.\n", "An example of distinguishing different animals can be seen below.\n", "The first four images show foxes, while the last represents a different animal.\n", "We want to recognize that the last image shows a different animal, but it is not relevant which class of animal it is.\n", "\n", "<center width=\"100%\" style=\"padding:20px\"><img src=\"https://github.com/PyTorchLightning/lightning-tutorials/raw/main/course_UvA-DL/05-transformers-and-MH-attention/cifar100_example_anomaly.png\" width=\"600px\"></center>\n", "\n", "In this tutorial, we will use the CIFAR100 dataset.\n", "CIFAR100 has 600 images for 100 classes each with a resolution of 32x32, similar to CIFAR10.\n", "The larger amount of classes requires the model to attend to specific features in the images instead\n", "of coarse features as in CIFAR10, therefore making the task harder.\n", "We will show the model a set of 9 images of one class, and 1 image from another class.\n", "The task is to find the image that is from a different class than the other images.\n", "Using the raw images directly as input to the Transformer is not a good idea, because it is not translation\n", "invariant as a CNN, and would need to learn to detect image features from high-dimensional input first of all.\n", "Instead, we will use a pre-trained ResNet34 model from the torchvision package to obtain high-level,\n", "low-dimensional features of the images.\n", "The ResNet model has been pre-trained on the [ImageNet](http://image-net.org/) dataset which contains\n", "1 million images of 1k classes and varying resolutions.\n", "However, during training and testing, the images are usually scaled to a resolution of 224x224,\n", "and hence we rescale our CIFAR images to this resolution as well.\n", "Below, we will load the dataset, and prepare the data for being processed by the ResNet model."]}, {"cell_type": "code", "execution_count": 26, "id": "5ff1954f", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:29.115622Z", "iopub.status.busy": "2021-12-04T15:58:29.115139Z", "iopub.status.idle": "2021-12-04T15:58:34.276229Z", "shell.execute_reply": "2021-12-04T15:58:34.275775Z"}, "papermill": {"duration": 5.338193, "end_time": "2021-12-04T15:58:34.276369", "exception": false, "start_time": "2021-12-04T15:58:28.938176", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Downloading https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz to /__w/1/s/.datasets/cifar-100-python.tar.gz\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "efc763b5cd4e4ed9b3e3881bad434e2b", "version_major": 2, "version_minor": 0}, "text/plain": ["  0%|          | 0/169001437 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Extracting /__w/1/s/.datasets/cifar-100-python.tar.gz to /__w/1/s/.datasets\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Files already downloaded and verified\n"]}], "source": ["# ImageNet statistics\n", "DATA_MEANS = np.array([0.485, 0.456, 0.406])\n", "DATA_STD = np.array([0.229, 0.224, 0.225])\n", "# As torch tensors for later preprocessing\n", "TORCH_DATA_MEANS = torch.from_numpy(DATA_MEANS).view(1, 3, 1, 1)\n", "TORCH_DATA_STD = torch.from_numpy(DATA_STD).view(1, 3, 1, 1)\n", "\n", "# Resize to 224x224, and normalize to ImageNet statistic\n", "transform = transforms.Compose(\n", "    [transforms.Resize((224, 224)), transforms.ToTensor(), transforms.Normalize(DATA_MEANS, DATA_STD)]\n", ")\n", "# Loading the training dataset.\n", "train_set = CIFAR100(root=DATASET_PATH, train=True, transform=transform, download=True)\n", "\n", "# Loading the test set\n", "test_set = CIFAR100(root=DATASET_PATH, train=False, transform=transform, download=True)"]}, {"cell_type": "markdown", "id": "1c5dfc81", "metadata": {"papermill": {"duration": 0.173119, "end_time": "2021-12-04T15:58:34.624021", "exception": false, "start_time": "2021-12-04T15:58:34.450902", "status": "completed"}, "tags": []}, "source": ["Next, we want to run the pre-trained ResNet model on the images, and extract the features before the classification layer.\n", "These are the most high-level features, and should sufficiently describe the images.\n", "CIFAR100 has some similarity to ImageNet, and thus we are not retraining the ResNet model in any form.\n", "However, if you would want to get the best performance and have a very large dataset,\n", "it would be better to add the ResNet to the computation graph during training and finetune its parameters as well.\n", "As we don't have a large enough dataset and want to train our model efficiently, we will extract the features beforehand.\n", "Let's load and prepare the model below."]}, {"cell_type": "code", "execution_count": 27, "id": "388c7fb4", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:34.978079Z", "iopub.status.busy": "2021-12-04T15:58:34.977597Z", "iopub.status.idle": "2021-12-04T15:58:36.776906Z", "shell.execute_reply": "2021-12-04T15:58:36.776462Z"}, "papermill": {"duration": 1.977758, "end_time": "2021-12-04T15:58:36.777046", "exception": false, "start_time": "2021-12-04T15:58:34.799288", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Downloading: \"https://download.pytorch.org/models/resnet34-333f7ec4.pth\" to saved_models/Transformers/hub/checkpoints/resnet34-333f7ec4.pth\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "236a5851e62d43d7b60a7d52dce28c1a", "version_major": 2, "version_minor": 0}, "text/plain": ["  0%|          | 0.00/83.3M [00:00<?, ?B/s]"]}, "metadata": {}, "output_type": "display_data"}], "source": ["os.environ[\"TORCH_HOME\"] = CHECKPOINT_PATH\n", "pretrained_model = torchvision.models.resnet34(pretrained=True)\n", "# Remove classification layer\n", "# In some models, it is called \"fc\", others have \"classifier\"\n", "# Setting both to an empty sequential represents an identity map of the final features.\n", "pretrained_model.fc = nn.Sequential()\n", "pretrained_model.classifier = nn.Sequential()\n", "# To GPU\n", "pretrained_model = pretrained_model.to(device)\n", "\n", "# Only eval, no gradient required\n", "pretrained_model.eval()\n", "for p in pretrained_model.parameters():\n", "    p.requires_grad = False"]}, {"cell_type": "markdown", "id": "8070a826", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.178455, "end_time": "2021-12-04T15:58:37.130131", "exception": false, "start_time": "2021-12-04T15:58:36.951676", "status": "completed"}, "tags": []}, "source": ["We will now write a extraction function for the features below.\n", "This cell requires access to a GPU, as the model is rather deep and the images relatively large.\n", "The GPUs on GoogleColab are sufficient, but running this cell can take 2-3 minutes.\n", "Once it is run, the features are exported on disk so they don't have to be recalculated every time you run the notebook.\n", "However, this requires >150MB free disk space.\n", "So it is recommended to run this only on a local computer if you have enough free disk and a GPU (GoogleColab is fine for this).\n", "If you do not have a GPU, you can download the features from the\n", "[GoogleDrive folder](https://drive.google.com/drive/folders/1DF7POc6j03pRiWQPWSl5QJX5iY-xK0sV?usp=sharing)."]}, {"cell_type": "code", "execution_count": 28, "id": "68fcd0ab", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:58:37.486821Z", "iopub.status.busy": "2021-12-04T15:58:37.484217Z", "iopub.status.idle": "2021-12-04T15:59:11.196064Z", "shell.execute_reply": "2021-12-04T15:59:11.196470Z"}, "papermill": {"duration": 33.893166, "end_time": "2021-12-04T15:59:11.196649", "exception": false, "start_time": "2021-12-04T15:58:37.303483", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "336b58f1c17b4c2998f77978c46f92b2", "version_major": 2, "version_minor": 0}, "text/plain": ["  0%|          | 0/391 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "3aa4aeee7b5f4eb5aee77dce65dcade9", "version_major": 2, "version_minor": 0}, "text/plain": ["  0%|          | 0/79 [00:00<?, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}], "source": ["@torch.no_grad()\n", "def extract_features(dataset, save_file):\n", "    if not os.path.isfile(save_file):\n", "        data_loader = data.DataLoader(dataset, batch_size=128, shuffle=False, drop_last=False, num_workers=4)\n", "        extracted_features = []\n", "        for imgs, _ in tqdm(data_loader):\n", "            imgs = imgs.to(device)\n", "            feats = pretrained_model(imgs)\n", "            extracted_features.append(feats)\n", "        extracted_features = torch.cat(extracted_features, dim=0)\n", "        extracted_features = extracted_features.detach().cpu()\n", "        torch.save(extracted_features, save_file)\n", "    else:\n", "        extracted_features = torch.load(save_file)\n", "    return extracted_features\n", "\n", "\n", "train_feat_file = os.path.join(CHECKPOINT_PATH, \"train_set_features.tar\")\n", "train_set_feats = extract_features(train_set, train_feat_file)\n", "\n", "test_feat_file = os.path.join(CHECKPOINT_PATH, \"test_set_features.tar\")\n", "test_feats = extract_features(test_set, test_feat_file)"]}, {"cell_type": "markdown", "id": "3d19971a", "metadata": {"papermill": {"duration": 0.183123, "end_time": "2021-12-04T15:59:11.562707", "exception": false, "start_time": "2021-12-04T15:59:11.379584", "status": "completed"}, "tags": []}, "source": ["Let's verify the feature shapes below.\n", "The training should have 50k elements, and the test 10k images.\n", "The feature dimension is 512 for the ResNet34.\n", "If you experiment with other models, you likely see a different feature dimension."]}, {"cell_type": "code", "execution_count": 29, "id": "42549377", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:11.928672Z", "iopub.status.busy": "2021-12-04T15:59:11.927770Z", "iopub.status.idle": "2021-12-04T15:59:11.930439Z", "shell.execute_reply": "2021-12-04T15:59:11.929967Z"}, "papermill": {"duration": 0.188248, "end_time": "2021-12-04T15:59:11.930551", "exception": false, "start_time": "2021-12-04T15:59:11.742303", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Train: torch.Size([50000, 512])\n", "Test:  torch.Size([10000, 512])\n"]}], "source": ["print(\"Train:\", train_set_feats.shape)\n", "print(\"Test: \", test_feats.shape)"]}, {"cell_type": "markdown", "id": "2cdcf692", "metadata": {"papermill": {"duration": 0.182311, "end_time": "2021-12-04T15:59:12.294547", "exception": false, "start_time": "2021-12-04T15:59:12.112236", "status": "completed"}, "tags": []}, "source": ["As usual, we want to create a validation set to detect when we should stop training.\n", "In this case, we will split the training set into 90% training, 10% validation.\n", "However, the difficulty is here that we need to ensure that the validation set has the same number of images for all 100 labels.\n", "Otherwise, we have a class imbalance which is not good for creating the image sets.\n", "Hence, we take 10% of the images for each class, and move them into the validation set.\n", "The code below does exactly this."]}, {"cell_type": "code", "execution_count": 30, "id": "7801b139", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:12.667132Z", "iopub.status.busy": "2021-12-04T15:59:12.666641Z", "iopub.status.idle": "2021-12-04T15:59:12.687713Z", "shell.execute_reply": "2021-12-04T15:59:12.688120Z"}, "papermill": {"duration": 0.211518, "end_time": "2021-12-04T15:59:12.688296", "exception": false, "start_time": "2021-12-04T15:59:12.476778", "status": "completed"}, "tags": []}, "outputs": [], "source": ["# Split train into train+val\n", "# Get labels from train set\n", "labels = train_set.targets\n", "\n", "# Get indices of images per class\n", "labels = torch.LongTensor(labels)\n", "num_labels = labels.max() + 1\n", "sorted_indices = torch.argsort(labels).reshape(num_labels, -1)  # [classes, num_imgs per class]\n", "\n", "# Determine number of validation images per class\n", "num_val_exmps = sorted_indices.shape[1] // 10\n", "\n", "# Get image indices for validation and training\n", "val_indices = sorted_indices[:, :num_val_exmps].reshape(-1)\n", "train_indices = sorted_indices[:, num_val_exmps:].reshape(-1)\n", "\n", "# Group corresponding image features and labels\n", "train_feats, train_labels = train_set_feats[train_indices], labels[train_indices]\n", "val_feats, val_labels = train_set_feats[val_indices], labels[val_indices]"]}, {"cell_type": "markdown", "id": "423696b4", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.176838, "end_time": "2021-12-04T15:59:13.053281", "exception": false, "start_time": "2021-12-04T15:59:12.876443", "status": "completed"}, "tags": []}, "source": ["Now we can prepare a dataset class for the set anomaly task.\n", "We define an epoch to be the sequence in which each image has been exactly once as an \"anomaly\".\n", "Hence, the length of the dataset is the number of images in it.\n", "For the training set, each time we access an item with `__getitem__`, we sample a random,\n", "different class than the image at the corresponding index `idx` has.\n", "In a second step, we sample $N-1$ images of this sampled class.\n", "The set of 10 images is finally returned.\n", "The randomness in the `__getitem__` allows us to see a slightly different set during each iteration.\n", "However, we can't use the same strategy for the test set as we want the test dataset to be the same every time we iterate over it.\n", "Hence, we sample the sets in the `__init__` method, and return those in `__getitem__`.\n", "The code below implements exactly this dynamic."]}, {"cell_type": "code", "execution_count": 31, "id": "492e816e", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:13.424718Z", "iopub.status.busy": "2021-12-04T15:59:13.422548Z", "iopub.status.idle": "2021-12-04T15:59:13.426739Z", "shell.execute_reply": "2021-12-04T15:59:13.426332Z"}, "papermill": {"duration": 0.189738, "end_time": "2021-12-04T15:59:13.426849", "exception": false, "start_time": "2021-12-04T15:59:13.237111", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class SetAnomalyDataset(data.Dataset):\n", "    def __init__(self, img_feats, labels, set_size=10, train=True):\n", "        \"\"\"\n", "        Args:\n", "            img_feats: Tensor of shape [num_imgs, img_dim]. Represents the high-level features.\n", "            labels: Tensor of shape [num_imgs], containing the class labels for the images\n", "            set_size: Number of elements in a set. N-1 are sampled from one class, and one from another one.\n", "            train: If True, a new set will be sampled every time __getitem__ is called.\n", "        \"\"\"\n", "        super().__init__()\n", "        self.img_feats = img_feats\n", "        self.labels = labels\n", "        self.set_size = set_size - 1  # The set size is here the size of correct images\n", "        self.train = train\n", "\n", "        # Tensors with indices of the images per class\n", "        self.num_labels = labels.max() + 1\n", "        self.img_idx_by_label = torch.argsort(self.labels).reshape(self.num_labels, -1)\n", "\n", "        if not train:\n", "            self.test_sets = self._create_test_sets()\n", "\n", "    def _create_test_sets(self):\n", "        # Pre-generates the sets for each image for the test set\n", "        test_sets = []\n", "        num_imgs = self.img_feats.shape[0]\n", "        np.random.seed(42)\n", "        test_sets = [self.sample_img_set(self.labels[idx]) for idx in range(num_imgs)]\n", "        test_sets = torch.stack(test_sets, dim=0)\n", "        return test_sets\n", "\n", "    def sample_img_set(self, anomaly_label):\n", "        \"\"\"Samples a new set of images, given the label of the anomaly.\n", "\n", "        The sampled images come from a different class than anomaly_label\n", "        \"\"\"\n", "        # Sample class from 0,...,num_classes-1 while skipping anomaly_label as class\n", "        set_label = np.random.randint(self.num_labels - 1)\n", "        if set_label >= anomaly_label:\n", "            set_label += 1\n", "\n", "        # Sample images from the class determined above\n", "        img_indices = np.random.choice(self.img_idx_by_label.shape[1], size=self.set_size, replace=False)\n", "        img_indices = self.img_idx_by_label[set_label, img_indices]\n", "        return img_indices\n", "\n", "    def __len__(self):\n", "        return self.img_feats.shape[0]\n", "\n", "    def __getitem__(self, idx):\n", "        anomaly = self.img_feats[idx]\n", "        if self.train:  # If train => sample\n", "            img_indices = self.sample_img_set(self.labels[idx])\n", "        else:  # If test => use pre-generated ones\n", "            img_indices = self.test_sets[idx]\n", "\n", "        # Concatenate images. The anomaly is always the last image for simplicity\n", "        img_set = torch.cat([self.img_feats[img_indices], anomaly[None]], dim=0)\n", "        indices = torch.cat([img_indices, torch.LongTensor([idx])], dim=0)\n", "        label = img_set.shape[0] - 1\n", "\n", "        # We return the indices of the images for visualization purpose. \"Label\" is the index of the anomaly\n", "        return img_set, indices, label"]}, {"cell_type": "markdown", "id": "2fc781ed", "metadata": {"papermill": {"duration": 0.177543, "end_time": "2021-12-04T15:59:13.783170", "exception": false, "start_time": "2021-12-04T15:59:13.605627", "status": "completed"}, "tags": []}, "source": ["Next, we can setup our datasets and data loaders below.\n", "Here, we will use a set size of 10, i.e. 9 images from one category + 1 anomaly.\n", "Feel free to change it if you want to experiment with the sizes."]}, {"cell_type": "code", "execution_count": 32, "id": "d089f9e7", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:14.150564Z", "iopub.status.busy": "2021-12-04T15:59:14.150080Z", "iopub.status.idle": "2021-12-04T15:59:15.603980Z", "shell.execute_reply": "2021-12-04T15:59:15.603533Z"}, "papermill": {"duration": 1.641455, "end_time": "2021-12-04T15:59:15.604117", "exception": false, "start_time": "2021-12-04T15:59:13.962662", "status": "completed"}, "tags": []}, "outputs": [], "source": ["SET_SIZE = 10\n", "test_labels = torch.LongTensor(test_set.targets)\n", "\n", "train_anom_dataset = SetAnomalyDataset(train_feats, train_labels, set_size=SET_SIZE, train=True)\n", "val_anom_dataset = SetAnomalyDataset(val_feats, val_labels, set_size=SET_SIZE, train=False)\n", "test_anom_dataset = SetAnomalyDataset(test_feats, test_labels, set_size=SET_SIZE, train=False)\n", "\n", "train_anom_loader = data.DataLoader(\n", "    train_anom_dataset, batch_size=64, shuffle=True, drop_last=True, num_workers=4, pin_memory=True\n", ")\n", "val_anom_loader = data.DataLoader(val_anom_dataset, batch_size=64, shuffle=False, drop_last=False, num_workers=4)\n", "test_anom_loader = data.DataLoader(test_anom_dataset, batch_size=64, shuffle=False, drop_last=False, num_workers=4)"]}, {"cell_type": "markdown", "id": "70f843f4", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.178644, "end_time": "2021-12-04T15:59:15.961336", "exception": false, "start_time": "2021-12-04T15:59:15.782692", "status": "completed"}, "tags": []}, "source": ["To understand the dataset a little better, we can plot below a few sets from the test dataset.\n", "Each row shows a different input set, where the first 9 are from the same class."]}, {"cell_type": "code", "execution_count": 33, "id": "cf7e1059", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:16.325926Z", "iopub.status.busy": "2021-12-04T15:59:16.325451Z", "iopub.status.idle": "2021-12-04T15:59:17.628117Z", "shell.execute_reply": "2021-12-04T15:59:17.628507Z"}, "papermill": {"duration": 1.488315, "end_time": "2021-12-04T15:59:17.628671", "exception": false, "start_time": "2021-12-04T15:59:16.140356", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "JVBERi0xLjQKJazcIKu6CjEgMCBvYmoKPDwgL1BhZ2VzIDIgMCBSIC9UeXBlIC9DYXRhbG9nID4+CmVuZG9iago4IDAgb2JqCjw8IC9FeHRHU3RhdGUgNCAwIFIgL0ZvbnQgMyAwIFIgL1BhdHRlcm4gNSAwIFIKL1Byb2NTZXQgWyAvUERGIC9UZXh0IC9JbWFnZUIgL0ltYWdlQyAvSW1hZ2VJIF0gL1NoYWRpbmcgNiAwIFIKL1hPYmplY3QgNyAwIFIgPj4KZW5kb2JqCjExIDAgb2JqCjw8IC9Bbm5vdHMgMTAgMCBSIC9Db250ZW50cyA5IDAgUgovR3JvdXAgPDwgL0NTIC9EZXZpY2VSR0IgL1MgL1RyYW5zcGFyZW5jeSAvVHlwZSAvR3JvdXAgPj4KL01lZGlhQm94IFsgMCAwIDY4NCAzMDAuMDI1NjYyMjUxNyBdIC9QYXJlbnQgMiAwIFIgL1Jlc291cmNlcyA4IDAgUgovVHlwZSAvUGFnZSA+PgplbmRvYmoKOSAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDEyIDAgUiA+PgpzdHJlYW0KeJxVj0tvgzAQhO/7K+YYDjW7Bhs4kqZB6S0RUg9VDxGlaSMMpUh9/PsuVH1ZWo121uNvLThTXApOExhnrTcIKsSb9vWpaQ/VGs1ErH4gn6eq3aIJs2HrvLdq8P/2kainEZmxS3lfGA+bsXHMesM6yfDS4gY94tLOZFGyKJlRadBnM481Ij+PNAHxTrAZsKc9xu8g4/Q3PPc0kqhesJo2TU3hErEONk9M9stvAq1rxFuBWNQPyw/re7rFquyHcOw+0EYQbwrdO0/mg9X7MTx37YShx+VuG6EQI6n7muq4PAhzhDvU13RVk+5Jn4+UTC0KZW5kc3RyZWFtCmVuZG9iagoxMiAwIG9iagoyMzkKZW5kb2JqCjEwIDAgb2JqClsgXQplbmRvYmoKMTggMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA5MSA+PgpzdHJlYW0KeJw1jLsNwDAIRHumuBH4OID3iaIU9v5tiC0X3D3pifNsYGSdhyO04xaypnBTTFJOqHcMaqU3HTvoJc39NMl6Lhr0D3H1FbabA5JRJJGHRJfLlWflX3w+DG8cYgplbmRzdHJlYW0KZW5kb2JqCjE5IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMjM1ID4+CnN0cmVhbQp4nDVRSW4AMQi75xX+QKWwJ++Zquqh/f+1hlEvAwPY2CTvwUYkPsSQ7ihXfMrqNMvwO1nkxc9K4eS9iAqkKsIKaQfPclYzDJ4bmQKXM/FZZj6ZFjsWUE3EcXbkNINBiGlcR8vpMNM86Am5PhhxY6dZrmJI691Svb7X8p8qykfW3Sy3TtnUSt2iZ+xJXHZeT21pXxh1FDcFkQ4fO7wH+SLmLC46kW72mymHlaQhOC2AH4mhVM8OrxEmfmYkeMqeTu+jNLz2QdP1vXtBR24mZCq3UEYqnqw0xoyh+o1oJqnv/4Ge9b2+/gBDTVS5CmVuZHN0cmVhbQplbmRvYmoKMjAgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA3NiA+PgpzdHJlYW0KeJwzNTdVMFCwtAASpobmCuZGlgophlxAPoiVywUTywGzzEzMgCxDS2SWibEhkGViYYbEMjaxgMoiWAZAGmxNDsz0HK4MrjQANRcZBQplbmRzdHJlYW0KZW5kb2JqCjIxIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggNTEgPj4Kc3RyZWFtCnicM7I0VTBQsLQAEoaW5grmRpYKKYZcQD6IlcsFE8sBswyANFhpDkxFDlcGVxoAv4wNVgplbmRzdHJlYW0KZW5kb2JqCjIyIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMjMyID4+CnN0cmVhbQp4nD2QS3IEIQxD95xCRwB/4TydSs2i5/7byO6ZbJCqwPITcRwTZ/OICKQc/KxhZlATvIeFQ9VgO6DrwGdATuAaLnQpcKPahHN8ncObCpq4h8dstUisneVMIeowJkls6EnINs5ocuOc3KpU3kxrvcbim3J3u8pr2pbCvYfK+jjjVDmrKmuRNhGZRWsbwUYe7LDPo6toy1kq3DeMTV0TlcObxe5Z3cniiu+vXOPVLMHM98O3vxwfV93oKsfYyoTZUpPm0jn1r5bR+nC0i4V64Ud7JkhwdasgVaXWztpTev1T3CT6/QP0wVcdCmVuZHN0cmVhbQplbmRvYmoKMjMgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAzMDcgPj4Kc3RyZWFtCnicPZJLbgMxDEP3PoUuEMD62Z7zpCi6mN5/2ycl6Yoc2RZFapa6TFlTHpA0k4R/6fBwsZ3yO2zPZmbgWqKXieWU59AVYu6ifNnMRl1ZJ8XqhGY6t+hRORcHNk2qn6sspd0ueA7XJp5b9hE/vNCgHtQ1Lgk3dFejZSk0Y6r7f9J7/Iwy4GpMXWxSq3sfPF5EVejoB0eJImOXF+fjQQnpSsJoWoiVd0UDQe7ytMp7Ce7b3mrIsgepmM47KWaw63RSLm4XhyEeyPKo8OWj2GtCz/iwKyX0SNiGM3In7mjG5tTI4pD+3o0ES4+uaCHz4K9u1i5gvFM6RWJkTnKsaYtVTvdQFNO5w70MEPVsRUMpc5HV6l/DzgtrlmwWeEr6BR6j3SZLDlbZ26hO76082dD3H1rXdB8KZW5kc3RyZWFtCmVuZG9iagoyNCAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDI0OSA+PgpzdHJlYW0KeJw9UDuORCEM6zmFL/Ak8iNwHkarLWbv364DmilQTH62MyTQEYFHDDGUr+MlraCugb+LQvFu4uuDwiCrQ1IgznoPiHTspjaREzodnDM/YTdjjsBFMQac6XSmPQcmOfvCCoRzG2XsVkgniaoijuozjimeKnufeBYs7cg2WyeSPeQg4VJSicmln5TKP23KlAo6ZtEELBK54GQTTTjLu0lSjBmUMuoepnYifaw8yKM66GRNzqwjmdnTT9uZ+Bxwt1/aZE6Vx3QezPictM6DORW69+OJNgdNjdro7PcTaSovUrsdWp1+dRKV3RjnGBKXZ38Z32T/+Qf+h1oiCmVuZHN0cmVhbQplbmRvYmoKMjUgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA0NyA+PgpzdHJlYW0KeJwzMrdQMFCwNAEShhYmCuZmBgophlyWEFYuF0wsB8wC0ZZwCiKewZUGALlnDScKZW5kc3RyZWFtCmVuZG9iagoyNiAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDI1OCA+PgpzdHJlYW0KeJxFkUtyBCAIRPeegiOA/OQ8k0plMbn/Ng3OZDZ2l6j9hEojphIs5xR5MH3J8s1ktul3OVY7GwUURSiYyVXosQKrO1PEmWuJautjZeS40zsGxRvOXTmpZHGjjHVUdSpwTM+V9VHd+XZZlH1HDmUK2KxzHGzgym3DGCdGm63uDveJIE8nU0fF7SDZ8AcnjX2VqytwnWz20UswDgT9QhOY5ItA6wyBxs1T9OQS7OPjdueBYG95EUjZEMiRIRgdgnadXP/i1vm9/3GGO8+1Ga4c7+J3mNZ2x19ikhVzAYvcKajnay5a1xk63pMzx+Sm+4bOuWCXu4NM7/k/1s/6/gMeKWb6CmVuZHN0cmVhbQplbmRvYmoKMjcgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxNjMgPj4Kc3RyZWFtCnicRZA7EgMhDEN7TqEj+CMDPs9mMik2929j2GxSwNNYIIO7E4LU2oKJ6IKHtiXdBe+tBGdj/Ok2bjUS5AR1gFak42iUUn25xWmVdPFoNnMrC60THWYOepSjGaAQOhXe7aLkcqbuzvlDcPVf9b9i3TmbiYHJyh0IzepT3Pk2O6K6usn+pMfcrNd+K+xVYWlZS8sJt527ZkAJ3FM52qs9Px8KOvYKZW5kc3RyZWFtCmVuZG9iagoyOCAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDIxOCA+PgpzdHJlYW0KeJw9ULmNBDEMy12FGljAeu2pZxaLS6b/9Ej59iLRFkVSKjWZkikvdZQlWVPeOnyWxA55huVuZDYlKkUvk7Al99AK8X2J5hT33dWWs0M0l2g5fgszKqobHdNLNppwKhO6oNzDM/oNbXQDVocesVsg0KRg17YgcscPGAzBmROLIgxKTQb/rnKPn16LGz7D8UMUkZIO5jX/WP3ycw2vU48nkW5vvuJenKkOAxEckpq8I11YsS4SEWk1QU3PwFotgLu3Xv4btCO6DED2icRxmlKOob9rcKXPL+UnU9gKZW5kc3RyZWFtCmVuZG9iagoyOSAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDgzID4+CnN0cmVhbQp4nEWMuw3AMAhEe6ZgBH4m9j5RlMLevw0QJW64J909XB0JmSluM8NDBp4MLIZdcYH0ljALXEdQjp3so2HVvuoEjfWmUvPvD5Se7KzihusBAkIaZgplbmRzdHJlYW0KZW5kb2JqCjMwIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMjM5ID4+CnN0cmVhbQp4nE1QyW0EMQz7uwo1MMDoHLseB4s8sv1/Q8oJkpdoS+Kh8pRblspl9yM5b8m65UOHTpVp8m7Qza+x/qMMAnb/UFQQrSWxSsxc0m6xNEkv2cM4jZdrtY7nqXuEWaN48OPY0ymB6T0ywWazvTkwqz3ODpBOuMav6tM7lSQDibqQ80KlCuse1CWijyvbmFKdTi3lGJef6Ht8jgA9xd6N3NHHyxeMRrUtqNFqlTgPMBNT0ZVxq5GBlBMGQ2dHVzQLpcjKekI1wo05oZm9w3BgA8uzhKSlrVK8D2UB6AJd2jrjNEqCjgDC3yiM9foGqvxeNwplbmRzdHJlYW0KZW5kb2JqCjMxIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzM0ID4+CnN0cmVhbQp4nC1SS3LFIAzbcwpdoDP4B+Q86XS6eL3/tpKTRUYOYPQx5YaJSnxZILej1sS3jcxAheGvq8yFz0jbyDqIy5CLuJIthXtELOQxxDzEgu+r8R4e+azMybMHxi/Zdw8r9tSEZSHjxRnaYRXHYRXkWLB1Iap7eFOkw6kk2OOL/z7Fcy0ELXxG0IBf5J+vjuD5khZp95ht0656sEw7qqSwHGxPc14mX1pnuToezwfJ9q7YEVK7AhSFuTPOc+Eo01ZGtBZ2NkhqXGxvjv1YStCFblxGiiOQn6kiPKCkycwmCuKPnB5yKgNh6pqudHIbVXGnnsw1m4u3M0lm675IsZnCeV04s/4MU2a1eSfPcqLUqQjvsWdL0NA5rp69lllodJsTvKSEz8ZOT06+VzPrITkVCaliWlfBaRSZYgnbEl9TUVOaehn++/Lu8Tt+/gEsc3xzCmVuZHN0cmVhbQplbmRvYmoKMzIgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxOCA+PgpzdHJlYW0KeJwzNrRQMIDDFEOuNAAd5gNSCmVuZHN0cmVhbQplbmRvYmoKMzMgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA4OSA+PgpzdHJlYW0KeJw1TbkRgDAM6z2FR8CPSLwPx1GE/VvshDSWTp8Rygdr5AGC4Y0vIfiiLxmEtQsPKvtIdNhEDWcVJBPDryzwqpwVbXMlE9lZTKOzQcv0re1vgx66P92OHAoKZW5kc3RyZWFtCmVuZG9iagozNCAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDE0MSA+PgpzdHJlYW0KeJw9j8EOwzAIQ+/5Cv9ApNgpoXxPp2qH7v+vI0u7C3oCY4yF0NAbqprDhmCb48XSJVRr+BTFQCU3yJlgDqWk0h1HkXpiOBhcHrQbjuKx6PoRu5JmfdDGQrolaIB7rFNp3KZxE8QdNQXqKeqco7wQuZ+pZ9g0kt00s5JzuA2/e89T1/+nq7zL+QW9dy7+CmVuZHN0cmVhbQplbmRvYmoKMzUgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAyMTUgPj4Kc3RyZWFtCnicNVE5DgMhDOz3Ff5AJIwveE+iKM3+v82M0VYewVyGtJQhmfJSk6gh5VM+epkunLrc18xqNOeWtC1zgLi2vC+tksCJZoiDwWmYuAGaPAFD19GoUUMXHtDUpVMosNwEPoq3bg/dY7WBl7Yh54kgYigZLEHNqUUTFm3PJ6Q1v16LG96X7d3IU6XGlhiBBgFWOBzX6NfwlT1PJtF0FTLUqzXLGAkTRSI8+Y6m1RPrWjTSMhLUxhGsagO8O/0wTgAAE3HLAmSfSpSz5MRvsfSzBlf6/gGfR1SWCmVuZHN0cmVhbQplbmRvYmoKMTYgMCBvYmoKPDwgL0Jhc2VGb250IC9EZWphVnVTYW5zIC9DaGFyUHJvY3MgMTcgMCBSCi9FbmNvZGluZyA8PAovRGlmZmVyZW5jZXMgWyAzMiAvc3BhY2UgNDggL3plcm8gL29uZSA2NSAvQSA2NyAvQyA3MCAvRiA3MyAvSSA4MiAvUiA5NyAvYSAxMDEgL2UgMTA4Ci9sIC9tIC9uIC9vIC9wIDExNSAvcyAxMjAgL3ggL3kgXQovVHlwZSAvRW5jb2RpbmcgPj4KL0ZpcnN0Q2hhciAwIC9Gb250QkJveCBbIC0xMDIxIC00NjMgMTc5NCAxMjMzIF0gL0ZvbnREZXNjcmlwdG9yIDE1IDAgUgovRm9udE1hdHJpeCBbIDAuMDAxIDAgMCAwLjAwMSAwIDAgXSAvTGFzdENoYXIgMjU1IC9OYW1lIC9EZWphVnVTYW5zCi9TdWJ0eXBlIC9UeXBlMyAvVHlwZSAvRm9udCAvV2lkdGhzIDE0IDAgUiA+PgplbmRvYmoKMTUgMCBvYmoKPDwgL0FzY2VudCA5MjkgL0NhcEhlaWdodCAwIC9EZXNjZW50IC0yMzYgL0ZsYWdzIDMyCi9Gb250QkJveCBbIC0xMDIxIC00NjMgMTc5NCAxMjMzIF0gL0ZvbnROYW1lIC9EZWphVnVTYW5zIC9JdGFsaWNBbmdsZSAwCi9NYXhXaWR0aCAxMzQyIC9TdGVtViAwIC9UeXBlIC9Gb250RGVzY3JpcHRvciAvWEhlaWdodCAwID4+CmVuZG9iagoxNCAwIG9iagpbIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwCjYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgMzE4IDQwMSA0NjAgODM4IDYzNgo5NTAgNzgwIDI3NSAzOTAgMzkwIDUwMCA4MzggMzE4IDM2MSAzMTggMzM3IDYzNiA2MzYgNjM2IDYzNiA2MzYgNjM2IDYzNiA2MzYKNjM2IDYzNiAzMzcgMzM3IDgzOCA4MzggODM4IDUzMSAxMDAwIDY4NCA2ODYgNjk4IDc3MCA2MzIgNTc1IDc3NSA3NTIgMjk1CjI5NSA2NTYgNTU3IDg2MyA3NDggNzg3IDYwMyA3ODcgNjk1IDYzNSA2MTEgNzMyIDY4NCA5ODkgNjg1IDYxMSA2ODUgMzkwIDMzNwozOTAgODM4IDUwMCA1MDAgNjEzIDYzNSA1NTAgNjM1IDYxNSAzNTIgNjM1IDYzNCAyNzggMjc4IDU3OSAyNzggOTc0IDYzNCA2MTIKNjM1IDYzNSA0MTEgNTIxIDM5MiA2MzQgNTkyIDgxOCA1OTIgNTkyIDUyNSA2MzYgMzM3IDYzNiA4MzggNjAwIDYzNiA2MDAgMzE4CjM1MiA1MTggMTAwMCA1MDAgNTAwIDUwMCAxMzQyIDYzNSA0MDAgMTA3MCA2MDAgNjg1IDYwMCA2MDAgMzE4IDMxOCA1MTggNTE4CjU5MCA1MDAgMTAwMCA1MDAgMTAwMCA1MjEgNDAwIDEwMjMgNjAwIDUyNSA2MTEgMzE4IDQwMSA2MzYgNjM2IDYzNiA2MzYgMzM3CjUwMCA1MDAgMTAwMCA0NzEgNjEyIDgzOCAzNjEgMTAwMCA1MDAgNTAwIDgzOCA0MDEgNDAxIDUwMCA2MzYgNjM2IDMxOCA1MDAKNDAxIDQ3MSA2MTIgOTY5IDk2OSA5NjkgNTMxIDY4NCA2ODQgNjg0IDY4NCA2ODQgNjg0IDk3NCA2OTggNjMyIDYzMiA2MzIgNjMyCjI5NSAyOTUgMjk1IDI5NSA3NzUgNzQ4IDc4NyA3ODcgNzg3IDc4NyA3ODcgODM4IDc4NyA3MzIgNzMyIDczMiA3MzIgNjExIDYwNQo2MzAgNjEzIDYxMyA2MTMgNjEzIDYxMyA2MTMgOTgyIDU1MCA2MTUgNjE1IDYxNSA2MTUgMjc4IDI3OCAyNzggMjc4IDYxMiA2MzQKNjEyIDYxMiA2MTIgNjEyIDYxMiA4MzggNjEyIDYzNCA2MzQgNjM0IDYzNCA1OTIgNjM1IDU5MiBdCmVuZG9iagoxNyAwIG9iago8PCAvQSAxOCAwIFIgL0MgMTkgMCBSIC9GIDIwIDAgUiAvSSAyMSAwIFIgL1IgMjIgMCBSIC9hIDIzIDAgUiAvZSAyNCAwIFIKL2wgMjUgMCBSIC9tIDI2IDAgUiAvbiAyNyAwIFIgL28gMjggMCBSIC9vbmUgMjkgMCBSIC9wIDMwIDAgUiAvcyAzMSAwIFIKL3NwYWNlIDMyIDAgUiAveCAzMyAwIFIgL3kgMzQgMCBSIC96ZXJvIDM1IDAgUiA+PgplbmRvYmoKMyAwIG9iago8PCAvRjEgMTYgMCBSID4+CmVuZG9iago0IDAgb2JqCjw8IC9BMSA8PCAvQ0EgMCAvVHlwZSAvRXh0R1N0YXRlIC9jYSAxID4+Ci9BMiA8PCAvQ0EgMSAvVHlwZSAvRXh0R1N0YXRlIC9jYSAxID4+ID4+CmVuZG9iago1IDAgb2JqCjw8ID4+CmVuZG9iago2IDAgb2JqCjw8ID4+CmVuZG9iago3IDAgb2JqCjw8IC9JMSAxMyAwIFIgPj4KZW5kb2JqCjEzIDAgb2JqCjw8IC9CaXRzUGVyQ29tcG9uZW50IDggL0NvbG9yU3BhY2UgL0RldmljZVJHQgovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAzIC9Db2x1bW5zIDY3MCAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMjcxIC9MZW5ndGggMzYgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggNjcwID4+CnN0cmVhbQp4nOz9Wa8kSZYeCJ5FRFTVzO69vkVkRlZVJslpVg+7MSgOMA0Q/ef45+ZlyHlgz4BVLFZlZWRkLO5+V1t0EZGzzIOo3cXDI7IKM8AAREh6hpvbNdOrKnLkrN/5BP/jf/yP8Mv4Zfwyfhm/jF/GL+N/lEH//76BX8Yv45fxy/hl/DJ+Gf+/HL+Y9l/GL+OX8cv4Zfwy/ocav5j2X8Yv45fxy/hl/DL+hxrh+T/efvFvLl/9BhEA8McfxWf//fHPHAAA/PFj/umHEREAoV3c3dePP7s44rNP/uTw85fW23R3gPu7b68//r69byB3/k8Oiu0XqZmpmjoCEsUYU+qYI1MIIYUQYwxMWHIueXEDBAIHcHB3Fc1LLqWKGiCGjtMQhm3s+9h1MVAkD6DkAm6ISO6u7uCOTjF0XeqJAiK1R0+hDxTHcZymSawA+WYzpL4T1XmZbh9uTuN4yb/i86L863/9r//6r//6Z6bi//thZiJaSimliIi5BQ4xxhhjCKFNblsrRGQiDvzzq9PGhw8f/st/+S/tNTP/X/+3/73vN+7tSu6AbfXOMuMAdv4t4IDgq6ggAoCbm5u1jyMiAgEgAPoz8cGz1LTf8Il0rd9dxe+fOxz8v/0f/8/j4aH989e//vXf/M3f/Au+DfC57dIetrouS96P052BhMAcYuDOzE0hpYu+u3KvVU5LuVnKPWEKvBv6d316g5gA+F/wGAAPDw//6T/9p3VWEP/i//I/D1c7bBsSgQAYkRGp/Xed3Ke7f9y3bZs7eHsGW5ezXem8mu7Q/nceiOgIBmDrD+Hl0jwfT9P12U98+1//4XB9115vt9t/83/61+M0H/Ynd2AOuH7LHcDbaGKFgE2roDeBfn55t/Um21/rF9Gf3Yz7T93vo+LyR9WG51mCJtWmqlIRYei63Xb7+tWlO/y///bvzKxd4d//+3//q1/96nPX9k+m4dltmLtVWUqZVYubHI8P9/e3d3d39/f3+4fjvCyvX1/96tdf/NVf/vZXv/qKOQCgqtRaS8lqEmPo0tB3r1PcICEiOSA4nZ8Af3o1nt79+7//+6+//rq9jv32L/7d/45E8KjI12kHQiAAQnAHt8cLmIObqZu1zUnICKBSax7H480y700mBEkcEFykmKm5O6BjQIoc+pg2qd+lbhtjj8gOYI4OSCESRyTCdWnAAZrsOYCfF8gB0MGk/vBf/+9aS7utL//yr9988dsmPT9+bvzcX7DqpbPhfHoFjzoJnv/4R+PZBvqJgc+u/PTO+i9CIMT33/3xmz/8/ePPX5j2q9e/+eqv/uazph2f9jk+vvP8x8/FsN1nUxDrxdqT41kLnLX8swd7uld8/PenY/38WUed33UH90fT7qAP/o1DZSRwNxMRqVKBkBL3NGzSNoYucOdpoG6gPsXIdRz1dAKDJopoYGpS6jQfxzLnqk44xLSLXbro6XJIm74LffQeSrAMrgwAalZNwIAchy5tNymEjigAOKIP3S5Sf38PjrkoYPDLN2m7G7JUOM51Oh5PNzt/y7guyldfffUf/sN/aA/4UwZ1tWT+qH4+Ix/tu3hWW9Y+7eAOolJLHcdxHE+lVlXr+24Yhr7vU0rr1c0RkZlDCDFFZjovwePy4Se397d/+7ePpp2I/s//699cvXpj6rYuPDqgrzLijuamZuJggGAGZgCIhESM7bbNzF3BnZoBAm4JJ3d8vIFVs/uz/z1OCDo+zsQ/wzU5y5V9849//2ja371715bjpweef+NzR/f5m+4uZlnqqeT7w5FuH47q2vWUUpfi1gxE4GLz68uLv3Aoud7vj+U47plCl3avLv/ycvevmC8I+8/l237yuf70p2/+83/+z6vzBPDF//S7q998QYSESOCMGIkiYiQKiAGerDtCU8rPjBaCuRu4uKuZO8Jq2vHsD68DnvlihqAACqup/aypfHTuHfCFa/C4HAD33398NO193//uX/3u7u7B/RqB+mFLSGe5dnc3czN381XvEiI08bcXjpeut9n8Q2tb5FP775+9JXjcXI4ASI7Nj3FEBzM3cJOS52kE06Hr3ry6+t1f/SU4/Nf/9vePpv3f/tt/++/+3f/yuce1Zw4wgj9OG7qLWh6nh+PppuRTLfPHD3Ot5f7+fpy+vbn9eDicQvzqL0L88tf/5q//+ouUOnAsJS95HsdRtPRdt91evbr47XbzJsTIHBwjADcrTEhnaTpvqaeoDR5fHA6HR9Me0vCb//l/oxBh1fer7DMCIQQCBjBz07bv20YQ0apazR2QIkcClLJMp1v+iPhQJC/kMCQk91JVpJq7ARkihcQp9puLzcW77fb1sLkiDOaojoYcuiF0G6KAxOhNM6ADOKIBGqID2PmR6jJ9+G//j0fT/uaL3/7ur/9vq/ScRfVRhZ7/BnhprFYRe/rnOgNNotePv7Scz+0s4qPL8SRYj5Pd/INn13xxBQRghBZy/aRpX32b5uXg03uPr/DlZ58W+qXU+wsvZL2x5tv6o+P+40t9uuF/HPd83of1H6kKZgIkxoDuRsjMMUUKHPsUU4iRiQBBRBdfFLxzS4CWhogAhJRSYmapNc+MUWnAMGdH2F0NF682u8uuH4KjitVAkUNACwqsCmJQxdwMHZAL1RwdiES0qtTTOBHwPC5zmcQymo/TUaEULdN8MCuBXpjIF1rypXX3czxt5qJaq4qoqToYrSqsmXFj5pQSEQGAiOScS6211qbnRbWUMp7GcRrdnUPY1k0VneaFicABEVOMKaWu6xDJS20bxczUtE01M8cY8Zngf7Ig7t7U7Plx3Hx1nwEdwcVyzlOtS5FcZamaAYkp9v22S1umDiGoiomCAyGF0DMnXH1ydzBY3QZHaLa/RSHn8HNV8G0Wf9Y7fpS4n5BV+CnLhC+2wWpGHcAN3AyKQ3WQUo7TeH04fH94+NPD/tuH0/eGOQ2cYh9CjxgI0+X2N+P02y5tiXw67o/7eyLq08QQkXhIX6X4hig8Zi/O7vNPPteny2Hqqg4EhM3QGoAAgHmzJwxAgARAzSddddqjQ+0Aju7kq9ZvIe45ml/nw8+OoXkL2VvU/mTaX7qDqwo9O3yfewp4oSKq1Lu7u4eHw/F42u2udhdXIaRmgv2scx79T0RvUXu7ErbQutnzZ7rbz0GWmlYRb24LERM3Z/HRYznfyKqjsE0TIDhaU9LuAEbgyzze6Pv9/c3D7c3psA+IXZd+Lg/wMkR6+bpNKqpqLtPD/sP3H/7x8HAzHve3t9c31x/v7x9KGUPU7QWlXtVPD/vvv/2emdnNay2l5lKqmTLzMFyMV9PlxZfb7cWw2XXdZQgdQEAIL4JLfAxxn98YrpP17C1CYDxP79kzQAAChOYxiYhUcHWXWqdS5iqLSFETcEhpiBxcpcz7mvcqo1s2L0uu5GZa3RUBEBRcXFRBCgjo4nkv0xaJzd2cDGMaLtJwSZyQAhMjEjavlSNwJA6OtKoGf2lQ190h54QPPCYPn8wqnmP0RwuLjz85x9argMGjpW/Tcv7CWeLOX3lMocFT3P8sdXJ2EdYXzwKV9vWWdQsvc3kvTXtzHFYt+ELKXq7qyzef/LnHN5rrjGeNh4Dun+7NZ+HTc4/wmSb658RXn4tWkQgBiRAJKBBBRCSKXUp9ogBI1gJBlSylIiqzcaAuBSIkpmHTxRhzJpoBkmEPNIG776663WU3bBMzVMngLhgRAyCbWxEvteZa3QXBgQg4RFcmLrWUsoC6K0hRKaIuyA6TZmXxMi+zaaUfWZ1H0/7s4VZXxszUrBQtuc5LyUuptZgrM+Bqec3NUkqbzSaE4O7LspxOp2mal7y4AxKJWq11HKd5mQOHru9KKUvJTTIJIISw2Ww2w+DuIqvEu0OrcRBhs/pExPyTWeKzSV8NurmZNfMiAApouUzTdBzn/Tjup/wwlyMghtBdbN9dXnzRxcvAQy0ipZoZAW+Gy77fBg5IACjmRS2riisgxRQ3gXrAFoLAM8XUzNKfE6tmqBwe46o/syJnb+YxI9U+B4Bg5iaqS9VD1ZP5PM03d7d/vLn+p48ffv/w8N1xvgGu3YZCTMwpcIqh322/eth9f7n79aa73O8/PNzfIErX9YCMIeFuYN4hAFBYt7YT4Mst9Gce0MAMCNwIEAxA25O6GwADMkDLzDMgITogPeYbm2JAb4mX1abDObp7nFx88o1amGznrMV5cp7f76MJ9p8x7fCiBAMqst8/HA7jPM8Xl28uLl+lbmP+aKmbrWla158iJ3qMz4HWYP6ckGjuMjoAFKnzsjhA4FagSgDwlO+CR33jT3dsq8Gz1QlwRGD06bSfTqfbjx8+frg+Ptxf7ra73fZnTfvTnIDDy/TM6hiVkg+nh483f/rjN393c/39/v7heDiOp7HkUmvloD0jh1Jkf3v/J/MRm0bQqqZ+3gpd2kyn8erq/urq9atX766uZKArpu4cTfL5Nh6THM+NAH0qb9hiR38erbZJQDBQVZWSl1pm9+qWl/m4LIdSZ5EsUsC9S0OMiQFqmWW5dxnBi1ut5uiOboSABLS6CQpSxbLXk+W+xg4RDdwwAHY1X9V8SZSQInNgDsSJQkdpy2lD2BMnaN4/widal8AIdE3b4JOVbTuA1vTPy6LFWibER9O+Wt9zSeL8A3j+5uogrJK6GksCf5EZePQMcHVFHt2mp/QAQEBggPizph3w2X/h5erh0/28kL9nC96cYAGvBoLghMEhArS4ql0vIAREADR3ddc2n4QRMeALGcKfj0Uen//Hn3FDdReTQNStMWcX+5T6gKyOxUxVvWSrRSkoR0sdhcghBo6MjIpiqp6Mt9SF6ElUBWMtOmEuSKhayckISKtnLgvMs4iqghIBM7XUfLI+xuRgENRctOpS8rJUc0WC4nOsRMGrFbPqZp/ZMs/MxvN31DTncjot47hMU57nZZ6nWjOimotKdVNwGPrh8vKSiGqtp9Npvz8sy1KlPoqJg4uIqTLznOOyjOnYERETdTH1XQdgKuVw3JtqlWpmCEhExDwM/W63I6Ku635umejxVzkQooNbzeV0nO5zHUWyyFzq9LC/ub17vz9ej/O9mRGlq8svXl/9ard506WLUmvJxdSZ05vXv3796othGEKgUo9LOc7LoeRFKnbp4vWrr3abtynumBIAnXNQ/ijPf1atnkO9f7ax/GS9mn/t6ljMj3P+cPfw++Pp+1z343h3f3d9f3fzcHu7PzycplNIvr0IMSlRQSTCcINToOvL3RcX29c1n/L84KapS0i7bvPFdsi42iV/5mn/C271XP58ej53t9VqY7MfBk4AAsiAjEQOBNCs5GOgb08G6sm/fiw2P87FY4hHDvb02ed3/GxZ/JkK/NydP452G8zcdf1me7G7eJW6jTo60PMo6KnYt2ZkV31KBKs6Rm9a2lxFVEzV1ESqGjOnYbMZ+r7rAND0uVe3TlQz4+dnRnc8lwQAwZmcCS52u2HoicBcRaWq/DkZfFSAL+YBgRxMteyPt998+49ff/Pf//jH3x/292XJphBDLwKWRdXUyjSdHh4AwJZ5BAIEJwYiJEIiCjFAlZs73R/uN7fbN29+9ZvfzG/f/Ga3eUORYC14Pd8un1j3H3m3AMzAjNjC08e8rSuYSJ3qfBpPD9PpAFDRay2nkkfVxbSYV3fTmQk5cHQTyXvXhdmAGHQt9xIBswN6gNVqIDqiuJyWcmyLSqFHrmWUMh/NwB1C4BAZKXHcpM3rbvu6276O3QVTAgxtKz1/kBRp15G6q7m3qlTLtbfNRmdz/KLODgBI7UpPefrzV89h/7MfAT67DJ7zb4S+fhyfrgtPCQAE9Oc/OhcGoFUo+WWN7oVpPzu559/9o8V72lxnl+J5sHDGQy1iR/fZXQgiQQ9gDgpIhJFpizg4uLuoTWoZHAgDw5YpnTMgdAb3/BmFtd6Ff3q3pqgGrkaBsAsp9ZvNNg0xdIxcHdFMRBRQHTRE4GgcPXTAEYlRXEWleFUUTBCZIUQRBzOBjKKAICKgWFxRZi+cZ5vnYg4UMcSQQgA3FTGqTgMzYQA0B1Kxksusqo5OAqFCSASgVYqqAH0ao39a7DBwcDUT0Vzq8TTu96fxlMdxGsdjzrN5Vi1SC7gR0Ga7necFCfOSj8fDw8M+56wqjgCExMzMSEhIRIhIIxMzM3GMcdP3m2GoNTNTzqWUXEpxN6KQUur74eLigohSSqLC3Mqyn9fISIAOhi0tl3M9Hsfrm7vvDqfbeT6oF4fysL/5+PG7+4ePh+NtLQJOV5dvX7/+8vLyzWa4FJFSqirE0M/LX+by1cXFRYg4Lw/jdDfO98syS+Ht8Na8OvjFhrpEhMGfVCT6eesBPtfRZ+H9RNg/p39/9ID+8v1WqRX3arqoHEu+3u+//uH9/3F790/zcjeOh+NxOh3y6SDjqUyjhgSuHpMSqbureq17lQ+7zfXF9hW5gRZXi6nrd++u3h7lqgAYeLUWUzyDwf0zDTyd1dAL4XoEGbXkua9JRXUgV/RH3Ay2ONcfU+6wFobMzcGJiIjO0cjZgQQkB0Mnx8c87qNyOkPrHhXZp+Hgy5l+epuJQghd3/fD0A/b1G/VaPUlHisILQx6adqpVY+oeQHrHYmKU5Fiteqc82maUtf17sTcdR0hmX56T35e8vX+8RPTDgHNtQzD0HWRAwG6tRr858eP5Q2fvY3uXksZp4ePH779wx/+/utv/vH7H74vy4yOXdykuCEE02xK5pBzOZ1O4JBzBnQk77rQdYEIY2Sk3kzm8ahCzOlwegD0lnnYbigERiRwerYU+DN2vQ0mYPI1IQ8t/+EqonXJ834+3hzvr4+HOwRhUtPFZHEr7uIgDipi7hi4Q4CSJzdBIEJ2J3dseg8QifwcKqyoqFJqyQUQmUNwYEAREfEqVUVigBAIKFLc9PmoMqMLWkXeICfmiFqeP1EXcNuzqIm5OZijP9XQW2nq0ebCoxQ/3g+cg+zVFjfBewq1H5MAa8Dd3qfzTn5850nPPHMOztn48/Y6m2N+dCyejU+jdlivjj/pOT9eEAHOz3KWvCw6Vf2Q5VvVe7MRjN0iICFxCEOKF134MvJrNa8yL/VjlQckDxwjvwq4dQDEEHnDvCHcIMSfCZ3O28v9R59wdULiGFOKMUZOTBEpEkemgMioJqgCrJyMCI1MQF1cSxYzAzcHM3OHwIGYKHDASARMxMyqlrOWqUouqMwQpXrWSsSJU+yx6wnR3QsEdELHRBhjSCHGwrp4qSrViol6VmJ3sJKrCnj48aT7OTuCpi5qqiqqYlaqzUs5HafD8TQex2keS56rLGbFVAGciRuoNMQI7qJm7mJWqxgYELZEPREbttK8mam7MVGIoYuxi5FDIETVFaZOzCkltR4ZYw6nKcQYUpeIKMZIz2X/PMyrgwChiU7TaZzuT9PHu4fvPt788fbu/f39jYPEhKXMp/EwHQ/zfhrHJWc5PcyHh/3F5W6z26wAAiOmbp4+3t1e9X3HAaqMVSe1WVXN0jTfOVit1d7Cbgdd2jLFVV780W19iuB/TrT+BeNcg4JiNoseSrmb54/T+OF0en9/9+37H/7pYf8+lzFLEbVSXdTdnJBAMJ9Qk1NQMxNpWUxY5pPV4ipaFQz7fvt6Py+nqjm7jlXMrKopOBJtmDchbJjj2WX5uVC+gW5ahOHPLOG5eorn3LgDgJi5Wim1loIAHDil1Jb7nKQHUStS57yUWgKHFGPqUgyRnoXZSEiA5q049yxwx5bd98c44Sfj2Zc2H5FijFGcq+EKGngsCPuj2V23zrMEB8J5+R0MgfBcGnVU8Lnk+4f7h/3D/nBIKYpm0zeE3qeeMZxzo89z8k/rD09TeE5XECGhr0AEAzBcUVz/ooEtua2i9/c3X3/z9//0h//6+z/83cfr7w+HRasSoHVgifJMJTPREFMMbG5QK+Cs5gqgKipViCxEMjPCOE1aspthzsXdlrzkpbx7q1eXnBITRmiP9BTPPU7sjwM/D+gEZq7gZqt1c8nzfHqY9h+n/fvT4WY6PRBZZCcyRAUXcEFXAOOGb5ciass0VylEhEhupApqBgjMEAKGQCFQYI4xpNjySgEc3dkNXA0BecViGqiZu0M1KbOJlknmfeovkQcKm9hvG9jy8UESwya6EIiBGKiv7RKPIfKa5nny7rAhOQgB0R/D9DUsP2fjzy5Ak44n091yb/i4DVfH6IUGfUrc42PB/plhd6D1t79YlJemHc9eCXyqnR/H8yDFwRsMqnnuYqdcb3L9ZpHfq966nUzBhJEicYppZ3CFuCAuIlBkXsq3S71GUqYY8RXjDoCYh75729EbxAgYPnHhX+Sln93Tiw85gBkShBBjTBQZGZzMUW1VJmSIhgCBCMHNq6lWhwrLknMpgAhruZ5SgsBk6s1jpBBCCACGIKqSlwqmMSIgADsG5wSho7RhADcRIgQiAHJn9ICI6ATeus5EvAqIgpirm6PTp0W4hpYDa7hxEa/VSq1V1MGXXOc5j9N0Op5Op2Ne5lIWkWwmAE5EHjDXCtMUYwrMYu5EgGgO6r527BE3tS5qUqWULFqZMQRaiJmxQaQREAlb6VFVHJyYEbGVaTkEAN9sth4C4Yqwe3yCw+mWIsQ41KrjfLrfX9/cfX1z84ePN19fX/9we3cNYMM2IbiKlGkpkyynOk25ZhHJRY5zidzuwgghTKfru5hCIGIAqIAVWZEQsJ/nk4pXMQMqIhe7NylumAJiQAzYYkp0fIxLH6um5xcEq6X5qfFMCP38zVZV1iLHUu7m5ftp+u50+uZw+Pbh/v393fXd9e3xeKxaFRwCq6AKugEaq8JckKOF5Aam6kwUGKoXKYtWkaquXAoe7k/724f97kOkZFZFF9HsgDFe9f3b7eZXXXexJpqfCoH48oYBAAJgPCuWx1AZHQifqQ4Ad3T0IjLPy/F0Op5ORJS6tNtutr6NkRtAyQFyztM87w+HaZlDDH3X73bbTT8EDoxtpoGIoeEr12IHECIQEqCjN2uPT6WTH03/j2w+IjAFIkEEBzc3dTd7oZTW3MI5DGq+iLe8pUHDC1QzAEf0KnXK8+F0vL2/vbm9edg/MNPx9JCXGd2vLl/thm0TuDanZ5/hGT7Az52bZ/uHSO2T5u6u7cboZ2TrfOH1mf1Jwkw153x7e/2Pv//bf/rD371//93pdMzZTQBctVaJtRRwjV2XNlsCKkiVMIKzqZupBABQtUzkZhhY51nyoiKQc231CBN0izHsmBIyIdHqdz35ND/llzjo4o6q1VxbDRER83QcD3fT4WY+3CzjfV2OROYBYgBicFMzPad+GlLBVFRVpIq7m4Gqi3hpPi9hSqHvU5dijNZ6d9wRKbQWMHdUVVrBtO7k3jAGbgYAeV7Gw3y85zggDdzt+u1rJPZnqBpG79gZvEEHxFdHcA2yz7sFH0Pfs01eM2GPtvwR1fEUxz9F8y8Ee80otjzT83j8bMYfv/vC4J/3xPorPrXYn0nIP6slfCZ+bHsGV/EV92KQ3Yt6nfP1afqmyHfm7xFnRiMEIAKsiMVsKXIAOKq+d4jmAHSPtBfJWdzkHr1jDl13CSjEIdAOcXiWFXgU/U+tO346Ww6uDuau5mpA6lotW6moCGgOVlWqVFuniwjQzUVkmZdcSiskN2RsDkJEAAYAIVBKDgMzhWHYogfCxRViighoatBSSBFDZERTNnJHUNOqFaWaZ8h5qTWrVnNrWAtTr6qmAuck5/MJd3M1q6K1aqlWq9WqVURMl2WZ5mXJeSlzLkupRUTAgYiQKMbQdR0HBsQiNZeiqgBAgTkGVzBTdzSDEEIMyb1UV3cCbyU5dgAzIDqLs0OV1QdW81p1HOcY4zROeclLfvv2rXcpAcCy5MdHMLd/+P3/6+r1mzevv0ppk+syTsf3H759//7r27tvDoe7eRyZicgQXKqWRUyAPESGoeu3m2EzhL5j1apVtSqoaJXKjAhETgGR3KECOXGpyVQwl3IaD29efffu7W9229d9t0tpG+MuxD5yB0AtfMTPtJCBP4tT/tw4f8zBXUWm4/H7h4c/3N//w+Hwh1w/TNP1/v7+8DBOh7rMksUV3YO4o1WshcpENaMIcMTUE0cgcmMQdWYgQnBGQDWY53r94QPj382H09XVP5iLWlFbkHHYXr1+89vffPU3zL8LYYscP28dzyMgprVG0jBfcFY+65/HopA6LNPy8fbmw/XN9d0tx7C72L16dfkqX3QpxsDoZOqncTocj7f7h+N0osD90L+6urq6vNz0QyTWWsEhpUTELQRiohRD33UBw+pJrUDlz9r1c3DyclXcQdVEraqKmbiTeYvtEBzdcfUZnus/QIIVHAXg4KWWaTkVyYhQSj6Np/v7++ub65ub65ubm1oyM//FV7+ppf72L63vusiMAGsj+Op0N7DgenOrJX5Uums433wNdzd0Q/8p6/i5sXooUCWfTvfX19//6Zs/3N5cg1PkQUmyzSXnZT4R1K7rhmFzddVfXEXzWS2nFEPkWrNa7Tpy1Gk/lZJNQ0pQskoFd1a1aTrd3X0EC4T9dvM6hLQZiDCtua7n1v1zmE03LdONgeUyq1RzQyRCWuZxPu7rcnDLTB4TgZuDFlEv2rANzES8RjVEjAH7TQqJa5VSatVapC5LEVEHGIY+hijckoxVFUIIzKE1c5qpiSgRIrobgKrV1vxcRVTdHTl0SJ1jx93F5nKKsX8OmEU3VCEHcuCzMAE6raWcRzu6RsBwfvE8an80w4+h9qOlfkx5n4XgbPGfXj8T+mfvvMgUwMuLIOCnC/KpaX+86Wcpg6eLPd946CBmi9hB9L7qKDKP84fj9I3ZDfMhBufAiExEgAZeRbSqidxXHkLYEiWkzDzXkmupJR/cQup6DKb22r04KICdnaJH5+Yzz/zpTkGIkQzdXcSQFFDMMpE4AJibmJYqRaSZ9UBMQCJSc1lyLqWEEEIIREzESAURiZCZQmQzZLYucQihH9ZMGTETIsDa4BUShRSJLFhr6UV1c1RzMHdHxQAEQA4OaGsb7KOH98mOWY3oNC/TnJdFSpEqJqpVZMnL4Xia5nlZllJyrcVMGYGIOYSYYuw6JBSRWmstxax5x0CBGQGV3EHEQ0AABm/IaCZyIiamtaOs+ZRrr50KoJpX0SXXVpVfVlYfdce+7wDwdDo9PoGZ/f7rv93e7r54e3d5+a5L/bScDsf7+4eb/cPdPB1VDZzrUs28FqlFTZEpdF3ou77vui5yYHBVUTVxE3dXNwM3QGdCIFCviB6SqbqK5TydTrfj+H5Z3l9evN0Or4bNm83m3WbzBvAVc2oYcHrmSD2K2M9ZxU/k7Nm+cCu1Hg6Hbz9+/G8fP/zdfv+1wX0ux+P9NB6lzlwqiaESWOurEVQBqZhnyItzABPqeoiduYGRoyEEdCM3MHVTPTw8oNl0fBj6zdr26JkTXr5+lfN+u7ns+80wYODdz7FMIkRsUTs6oCH4Z6y7g4GYZpH94fj+4/W373/44fo6pHBxdXFcxnEZ+y5FZhCoRQ+H0/3hcH/cn5aJEvdD/2oaX42ni802cqjLAu59P7QWLAKMgTf9cHmx2/R9CoGJzoptjRr82SI8LsiPF8Xa7lDLVZbSsl9M6ETekmXkeIbGuyMS0VqyJYQGWJCyPzwcxn2teVnm03g6HPb39/e3d7e3N7fjNJqoiOx2F1eXV+/efRFiBCRRc5ezi0CPc+bYAvdzLA9uBqvpt7Xdfq3D/wtGa8nQXMaH/ce7uw+H/UOeMzMTpgZldHDVoubDkDbbfrPt+yGYuRrEGEIIzGgemL1Klgp5sRTM1UpVFXADFQMQN68F+u7iyy/+Yru9SF0fGQFCo7J50sGfS2mZyXT4wVyXPIpWM2twhrLkPE+SJ9OMIMzQqn5VitQqIuaeUgwA5tpwPMzMISCxOWAVM1cVNVFVB7AWXBhqC3EFABEZEcDc1MRUwdYY1t1Ea6kll5JzKaVUcaJE3GEY0uAQhpjsxYqs7lfr/KQWoQMC02PeGxAACQgRCZHOkPnnMLqzvJ6D72cNgU9G69yL+VK2n33q03nGF38BwHMv69MPf5KQx2emHQDwGdqoyS89MoGollL3U/5hnL+Zl9tpGXM5VDkEnrouIwBTYHTioNpMURGpIVCMqR8uurQlgsimwS22HhnuutSlbQw7pqGJC4IjNhBa257rba3piCfk+NODEdLVq12WeVpyKaJeSyViCIE4oJqVKqVKqeqIiNwC0lpLKaWWaqaNjo2YEcncAZADpy5uoNdgOVc3DwxE0G3IreGLYeWcA05dil0KTIRuYlqdmSEwdOQVKHW8sTnjUnCp2cQjY/DInBiZXsIcHVDNc5HDcbq7359O0zhnbeV201LKNE3zNM7zXEtREQSnQEhMgZFIzVqxqdQ6z0vrXiPmEEKIiRItS8m5uhczUlVzRArMxIGJQKSaKbU0o7fmdAMAVqUqgQNzCBzc0R1VbZ5zlxJzuL29e3oEtx8+/sE/+h/+8PWb17/+3W//DWAlxhijOyBySskdc7Zaa8ni6uDIgRNTjAgmWhUBXRyVwACAGDlw48DQWquomDsHJCZXrzCaZZWT6UOdf7jrdl262O1+9er1X755+7s3/tuuf8U8MAV/Qqf8RAnxz42zLTLR05LfH/Z/vL39p4eH70/HO8dJaikLSKZSQBUwYowEAVVBqgMCsjlCFTDHUCgwBHYnACRzAiMVqdXMgMjRq9Vxf7fsndzIHQxq7Fm19kO/3//DZpc4IgVC2gCGn3oWQmSg1Z981r3V/k+NT8T9NC93h/33Hz98//Hjx9vbh8MeGMdlmpdpHI8pRkIoc53HfDiOx3HKWhUt9V2fay5yOJz6lBhJSgH3mBIRmhoTdSle7i7evn796uLyYrvddF2XEiPC6pK8UIGr3+GfWR1ENIciPi7ycFpiZHfmgDFADNjYK6iZ8Vb4bc50a0MhAPSq9Tgefvjw3fXNh+NxX0qe53mcptNpPB1PJVd3mOb5OI7jMmUp0ROBj9M0HidCjiH1/dClDtb2AvcznZ0bgpsD1eoiqmqtd67hDX8aUPAjAXNwV/U8zQ83t9+M8912uynlap5zXvI0nZDqxUVCJIS4u+h2FwyUp3lEqkgKKgZEjAxeZcl5IeQUt4idKWvVZSnTNBHC7jKqmlTaH+6Ox7v59dvtbhdCACQEc280c/hTW8S0Ptz+0cHUylobaQ2vYiqiNWvNZsVczES1lpJLLu6tIBiQ2BVEzWoFkBgckKqCGIkBIHep65IjYoxdC5M5xJi6mDpEqKLVqnsFV3BvaRVogZxW0VprzbVMcy7VKEDquovtdnPxerO9irE7vKiCPCbU2wOj00qV16w7rnliIIImYXgGlbSPf256Wj0enko36+o+BfPtRz+e3Bfv/Et8wh9H7eei1JPXcQaaru6omhW1Jdf9NH08jn/an/5wnK6neVQtiNp3iuiMROjOTmiiVquUXKsUCWBeiZHIEdAMAJTZMDmAx4TMAFBVT8Uc6YAYmVKAgSjhOax8CuM/O4uEl1ebubh6XYpIw8IDhEgxkpnVqiKm6tpozsxctdZSazE1AARnOjcRipqvGbbIzMwBWlc3OgbuuggAa6IHoG1uIFB3JiZmAHEXJMQADAhOPKSwQMwUZvRRdamkhAhdl1JINCGck0Mt3VeKTnPZH8a7+8PxNM5Lbka21ppLWZY55yy1iIirIgI5mruZV1FRb36mKuQqOWcVjTF0PSRkZDLDUhVAiVp1gpkJyIBA3cRcVdtUP+/ndnBqbZ/oTihi07So2pJL33UpdeNper4ipczjcjo8fHd985GD73Z9lQXQEYk5BE4iVmopi+dsiBAYQ8AYCdG0WnXygmoggrW6NdgIIRK6QWO0AmBiBmdXFy3ic4ZxOd2fkAN3KWwuLm+mcTSFEDaXEIeha+Cmn4Zp/qR8Pb46Q7fEbC7lZpq+G8fvx9OHeTos8+xeRKzMWBdaZnf01BEnxEBQXdCBnDsPFUJFAkRyM695jTga00YtUKsTYYygVUsuWkHE3dgdzDX2HBLuLm72h68vXm37zesQLwJ2iJ8BZJ4f4NOHXrNhfm4DAyhqh2l6f3P7w8fr65ubh8NhyrO5LXmuUnJeQgjosIzLeJynOS+lGAIG6lRVTUSXOTcgS+P5iikhoaoiYhfD5e5iysucc1Wx3QUR4UpivCYyHc/Wst3h89rj+R0kMsciNi714TTHFAhjjNQlMCdwZyLGJ0WGZrZKTYvEXM2qyjie3n/4/vrmY85zKbnUWnLNWUwdgae8jPN4nE6H8ahuCPhwf9jfH/rU7zYXzcDDWnFvBEpubq4tkwtSTdVtZeVtP/4XyZubq8gyzw/3+x+WZT8MwzzV8VhqqaJ56GB32aWUmGLXhdSpSC515uBM6FrVsKNIgUANCft+06XAHAFQFYlcanHT1CFhURkPh/v7h/dXV5ebzYCEMTQzdw4PfyKppSrHh/cOqlbd9VFhIDIju1WzolrVauPeNVU1o5UIMSA0WJWLiJmZKmIjBSTEEAIEAqKGxSQ3K7Wao0FQVzcVKeCFsDBhYAZbhcXB2+ybmVSr1XIxVHPy3sicP0992DbgORZ3BCQgQiY8J+ShVbT4DNeHJ5/n7JJ+eslnPzwHzfiUcm5dXj9jun/k2z6WmZ4qWS/G56N2OAPyzlD7VW7dRPVU5H7OH8f59nC4Oxw/Ho4fp/mQawHSGIEQAiNDBOsqOaCamZmLBFNGUlUoRU2nNufMyIwpMWF1GEVv5qJZPoIRYuDQxXDRxTeRXwW6YNoyDghhrZLimRXheY4CYbPt4+AU4DTmcW5d3GgVxQCACCgFihFKlVxKFZMqUs0VEZiYIndd7FPXcaCixd1SHzeb4eJi2w/dmflUADCmnjk0WRSVUmopUuqSi/edDn2HbuZKaBiMAkbmYDFWToXjTBZEqdZSALAfYp96WujRtKtZrjIt+XCaD8f5dJqrGHPgwI4uo8liVaTW2oICc0WHqmDuuVZAQqSYUt/3gMGMqkDJUqpXgRgthFCLiHoMCNiKVQ3qZCJZpIpUNX1sLkRszDTNHnMgTjH1XU+IZiZVC9bAse+bT/MkU19+8euH49397R/v7n/45tt0cTGonHI+MSOEhBRRdeXgUSWGluQCdBXTYkosGEqFUixXNfe6jf1AFBRJDYQZOYQQAyKZqohLriUrmAfkFHKKVZaopWe8SvEd00XfvcbwPEEFP6m0fmqbnV+rTKXcnsZvjsc/1HJHoOgAxlKpLlgmXEafRvHgvMVIRASAIG4eIHXIPcUtuSIZSvFpMld0I0JDhFpdBGKCvgdytwox9IGigZuqmWiFPNp4nMbT9Tj+sN39LqVfIV3is/j307tf6yyw9qb7E2jWwQFIzJcq+3H6cHP78fZ2fzzmsrR6TM7Sej9iCARUllpEibnr+yJVVbWIUO27hAC11FpLrZVWDDGLVDWbF8i1FmmsiA4OgRm7gTisCvUsOY+gHj/b++faiogNYBH1pXRj7q1PKTg5KhDZ6p23LvdVhSMiKgCatWDLHLtu0w87wLDkcnt3O8+juamYSiu1paUsU5nvjw/ff/whhaRVT4dxHpc3r952sRdRqXa+SW9+dcN/oSOBt3gdWr6W/Mdwpz8jaehmtdZpXvbjdFvqmFIKgWst5tL3uN3x7iIOm5Rip6a1juoFSIiRCUXUzEOAENMw9EO/cYuuwYHcfLOpXZfBUs6Z0ExBQE6n/Q8/fBMThwjmenHBKT4eL/Booz41JO62TGOVZV5GM0Fsmzj0fT/0A5Ehqdacy9JWlohS7JhS4EQQQJkhAEanUrVKUQBj5sBh6DrwwOhEiIhVdFpyqUuLrgCDg7lJF33ocLPpmIObq8pZiogoIAg6EUQCE8V5Lnb3UCqUKn3q8bm31TxBQgAkQkds1IxEQK3iDo/VdGvMwo/Qt0/T8S/W8en9My6jAUFaDHk2tyu24mdF4ulK54z+5xpfP1NrhxXF97iE5q4O6lZFx1xu5vzhOH17PN0cDqdxPMzLQTQjGhEwIThKpdm4ZAIQ87ImLoAQmAgRTdVUas5Vzfqehz4gIZHmMmopGU+IAcCQKMQYw6XYuy68S+Fd4FfRr5i2TD2u+PlPaU0BAAkC0TB0aijSErf4CJtCMCJCRjMQEgGAdR8yM4cYu9g3GCZHwgrqtdUD3a01lZlpLVUjpOR9x0wRXF1AqiyLqFTA3HelbPpASOSMwIRACkEdCQIwYDSOHYcFa3FTNVUzfV71KbUejqeH/enubv+wPxxPk7khYUdrACSNY8ONiAijIrqZmlepqg5AxAEpEXddH4ZqolCyNqLy5hUZEHPi2HFMiAhg52t4FVMDd2qcL+d0bbPvRMyExBxiTExkvp79oapV5HFfNTl+/eodEKT0/fF0fNhfV+kYi0pBYOZAFI0E0ZAUSZkxJiJ0U9MqVq2Yg4MIFYEi3tpZRLEfPPUeAnBY78kVRLAsnmebR/FqDJKidR1IOansU7obNrf98G67nREphgBE5xzVo9f886p33U5rnthNdFnywzR9HKf3OR9VqorVAjVTnmg++XT0aQbsvCvA1clcqps5MFBC7jAOZAU0e60+Ly4LurYsoLuTQyBEIZodtcJmG/uuB1BAQQQEc0cVy3nJeam1qoqv7uHnVYS6i6k1EGwVc2cOzMztfA6VcVpu9ocPH2/ef7y+vbs/nU5iFVdiDXQzKeLqCNSOFOIQIhKA52quqrVqrUZkKmba8tJu7qa11OYBLLlU0WbzwCAg4QXGzZbpyXgYgJuLq5itxPXP5ArAbWV3EC86F8PojUuPFIgc0VsQTQ1h5dBIk9xdVczU3HJdVAExgFOtOp7GcTwaNHFGhMDs4zTeP9wPHwcHDxRBAZ0iR2aOZ2zgejIDObSqeqO1e1bMPCdDCT8JRP78cNEyjvvD8fZwvF2WfaBLZksdDh6QumEAjp46GAZcFlnyJNqoZCNgOOfaiCmmFJjZJEjFnNXdUopMDJamcSnlZFIJfVnG65vvQnRmFVUDvtxi36eVn/BJqF5Kl7vUknOex1FUEIGIA0eEpvTNXBwUcYVP4dnPaZ060HqPGAiZkWrNDhYjM6M7gyu4IgARYsacRWs5zaUKqGErhG8GIowxhsDmbqIGqyg1A8GBu5SiuUmRnEuph1LFTTfDcPmixwqfLC2dhZ4AVyTdI2kM4KeuJvyzYoPW72+Ql5xzkVrdLaXUdSnGQKG1YDzlpZ/P8kuS+XO8/wRBfTE+bX57Hrk7uHs1L+7VbK5yyOVmWr47TT8cxuvT6TBNRbV2vWwCckiI2FrCRSEvqnURrWal72gYQt9D7D0lDIlUoIrVYiLK1FoVg5vNU16yORAzpY5DgGpWJYl9rPF1p+8iv438NoUvUvgy8Jaow0ZB+Bzy5z6OI5A6UODQpx5da3Hi0MhVSs22OtUeI7sFMCcgN0ip6/qudcMH5tYlZSplUa21LjmEgNgQehpD0oLbrW+GjTvWBfJkyyi5lKoSw9j1aehi18VWmOdMxAxOqIxAJmaq7lByLUvRYnMoX5o9Lsk4TR8+frx/ON7dHQ6H0zhOVaq5DZs+RJ6XpdYsKoCYUhdDcLOSyziNOZtKaxRhor7rdzGGYXMR070ZimpY4+5ASETcpaFLvaioVF9ZldERiSIABmZEUK0O2qoELWmhwKrqbjF1XdeZaWucOx720zQ+F6rt9kK8Xl29cncmVlF1cXW3yBRi7MzKygkIkCL2HUoteZG6WM0uS9FakTvkpA4GME9Vzbsudil2AzCjGkoFKVhmnEdYJswTaQVUiAGGAUwdqA77eXO/32xvh/7CrWw3Gw4RW7UP+eyOP8uufW5rnv+0DWOiOZfTUqZc5iXP87yM4zKeihZYpnDYl/GkWZCNpiOpAaIArq13ohQjph4seAEz8FywLOgVmSAGiom7yBwc3PNseVm5Y4gA0J2dE/ab1PcD+sZkQBiIunNfzOcewkHcimoRWUo5TZOoxpj6vt8OWwCYp/n65u6P3/3wp+++/+GH94fjvtRMDCFyF+KKr6DggG6AjkwUmYjInRFIVLUueQIwCTH0KXqMAEAOIqql1lyKVInCiPeADfYCqgy0HYaIK82eu4tpEZlKnvKSpVaVKS+Pz2FmeVnykkuu1BsAO7A6iVFVBzA3VwZlCGGlzkUARFeTaTpN87gsS66lSJnGpVZrCE0pqlr9DM0yw8Ph8P33P5RSj4fjpt9u+u2vv/z1b776zRdvv3xz9ZopItCKkkPw1jyJrVpFgSgwces4WcOmFgb+M+umDmClLnf3N9fX7x/ub0+nY5+UAr79YqgFxIL6VGsuFVKHZlltyTnXqgADh0AYOXCKmxQ3gREAzHRZysPDUVSuXm2Gfvv69asu5uvrUkUpsUo5HG4ccq7HaVmqon1JX6RtO+bqfFefilaTS0QiiqhuauCgAMtcRCwE4ODMHMLGzFWtZBFRU0OoXTeEjrvEIQZTEsFSwV1T1w6jchUtJYMDUUCODkF0HKcitYoChRYhECLWquD50XkyB1V1d6LUDwNHIJYsR11m8WxWIqvL5mL7es1JAKwh9BMg/sxIfP4D8ISEb9mo9YSCF0v6ZJefWBxwLTC5Qc317vb+9ub2eDyq1NevXr158+ry1dVmuyHmtQz+gqNinWR8fAlwDvkfRe/F+ISy5uxTYqvzVtGj2tFsFj3WejcvH4/T96fTzWE8zPNcqhJ5Stj3oevIlfPiuVpdrBSVCrVUUZHK4Ijk55N4wI3MEIBxJev21nJeVUspqsoBiVskIGakNokcJT5Evgn8uo8HAAH8MtFrxPiJu+QO02lBNuboQJGDB3JTZMYQwF3d7UxrjYwcOEQDRxNgZqIAQO4uIqBaS6lSWmGjUMGWTnUAxxjUKmp23bobzPM8z/M0L1lK1UqEceI8dMOQQkAixwDIwB6jh0ARgcC1hadlqVI8k77b2CO6eRynDx+v94fTfn+a52VZ8rJkkTrPkQNXqVWrijIzEcWYwNGMzBaR6s4BUwgDc48QiGLXcdfNHBNgbRjUECJTaGB6pDWRfN65xBzXzgBmcFeDRv2OaM1RdneSmksJMXZdAgQzKyXXWvMzFQwAohnQNpuh1srE4OoKUl2yM7dkEnNMCYACp+ApglaRYnmxPHuZtBaPiUMX2rEkjd+EiWMIjAJuLuYSUDtQsApa0Y21Sl1qIVdxR6Uo42k5Hg431+/N7Hjc7XbbYXPRDxddv41pwxhWR/zPON/+LG+GiCGEoete9f0XXTdzOKnSPFmecD7Z8WDL4o7kzMtEqoZoxEaRmv2JEYbewd3MEJ0Dc0BRQEaK1PWp76KZSK2lgrmGVDBg6ixEY/Z+271+++btF1/sLt6k9LqdmvPzceFSymEaj+N4OJ32x2OpNcZut92+evWaicZx+v7jhz/+6U/f/fD+5uZ2yZOZBKaYQtd11CU3NFo512opqtVCiIERPBI1Kal5Ma2p71OKzIxI7divlQYWwM1rlWmatJQUwtV2O+Y5S2VmdnIAdR3n6TiN+9NxP52mZVlqlecu42M51wGdAMiMRMBdVS2QZfLAFNhi8MAemJiB0GrN94eH/f5+WeZSiqjc39+dDsdlXOpSNVdRAUAKzQrLPE73cNv4+PhduLq42m23l5eXQ983qBbAemrF6vQ1BWqIjaN3NeqPd4ufRF9Pyvfp7ydQi7nmPN/d397d3Z5O4zJPABA4dj0SI2S0CiIuVZupBHfEBoTtzicpBLBUM5Us5mJqpeacFzU1Txw8UJBibmRKhIEIADTn0/29cOhiukhpt9u9wYGZ+mdBFH5y80QYQkipA4BSKgCCo4qLlJgwAXUphhCkipghYjPb4EAMHIADpIgeOVoMou4UIhMTAoqgg6jYyuxOCOCqYlrNAFvHifiyqNRKRMyh1QTNodHmpxhDpBBDB6GvpVr1vKhMy+zoxTevnp4GEZDPr+ClMX1s/IZHHoYzCu3xg/7yDKqmKPxM6YAAoKLzlK8/3Hzzx2/ub29LWd69ffPlr7746quv3rx70/V9SJGYz5woZz7j55P+5Lr7c4P/fLxMyOP5XDp0tSx6XOqHXK/NDqL7Wu/m+eF43J9O4zSXqgZoFAzJiDxwrGJ18WWyZWlEJu4OqlCKTaQKUhV4oRBCTBxCSF1AUGJB8NYrQRSIrYqAGTgjBPRk5qVWoQdNR6IbpqF2D44ZSUPoCRAwPH82dz8dC7KGYCHEyDEyaXBDEJfitXrrg7WV65+QAqOCq1VVz0WUWQGruUuus0jFBqFAAkdVA8DIbMGtWp3rfJhFbFlyqVVUHc0ZFFyKSNWSCwciBozKEQbqEHsKTsiExuwM7uqlSAXw4elBpmn6cP1xnvI8LyU30NySl+V4bKB8RQRi7rpek1qAhjV1I4QYYur7zXa7C7HLWUQF0XMpZureYvJG30LQGutNVM3W49Kgsc+GkJiiG6kIQFF1c3F3avCP1pdlpioiBQnaadAlLyovKGvu9t9nWTjgdrN1I9daVbTWccyAta/KMcSUKLJIDajoYoo1Y559mb0WUAEnU6rITmhdpGHgrkuEtEyLSHXrCPpElxiChGRxZiyu8zxKreagFDX0dZ6XcTrKh3pz+11KvBnS2y/+4otf//bN299cXQViQvwMP+Nnxpl1DIC7eBW2oYv90L9C2Obs1++PJe8f7uW015LVHLhjAK4ZTJzWU9VMFEpRJhx6jC2vQ3z1inPnZQEm6lLYDrFL8XTQnLWqOvlSTpgnSpQCxy7urjZf/dXvfvNXvx02u83uXYjBXc5nlXx+HKZxRHn/4ePN3e3+dCqlEvN2t/vi3RcpdaWU9x8+fvvDDx8/Xh+Px1KyiTBBYO661HVdDDHGxMQAME7jPE8hhtTFvu9TlxIHJVzyMi8zL0tsX4mRkRExpUBMUVIjjNGqxbyqKnqxeiyjgAYOAC4mH++u319/uH24vz8cTvM05/ybub+AeFZWGGNMMaUYAzMBmpqaOihAbUqJkIgoMsfAKXIMyKQ5j+9vbu7vr82qlDJP0/3N9c2HD/u7++U0yVJVFZnACdnQsZYyAew2W0J4c3X1u9/+1dvXb4hgnE9LXoZuGLohhEgUAHGtS/lKXtPyn9iiZVNtnV9/vvntyUpILfM0Pjzc7/fHUlTUap3M0B1KlmnK5koUVbkUV0WiuN1smPquG1LqTEgEltlPx3lZRrUybGIIGFOIyDEioIospVap6kbM3dDHYYvE6mjzcry5/X6zeXV1+YYIt8MbxPiM/vNFySFGYg6IHa4sZsgczBrWqrVxshtJtVKEAw/D6j3FEENEJDOoxM4BMITVf3/UVEy1ai45LzIvMi9TrUsr6gOoqkyTLZO28nyIKaS45uCIEElKYYWuG0IXrniXenrY67IsUufF5XlJ1x2tsRr5euLLWvXFZsThzPMObkAIQGuLtp8ZCdvjr3H8Oc3hj2cUOZRcj4fThx8+/vGfvrm5fr/M48fL3c3HL6bTaZn/8ur1q93FLvZdTJFaUPjYMnk25ysc7nEV1kDjhVz9KCGP2AAnajmX/XF6Py3fqj6Y701PpUy55Cpi7TBiclWrVWNoAehqAOEMn25ljtYGjdWBADIieT/AMEAXMARCYoDm0COsHD4A5qpmakQMDqZmVh2UaGwnSofYx3CZ4jukgEjPn8rdl6UiW0qEwITuiMRkCI3A2cDVDdyAqDXztXSGgauqGATX4IhsDqJufqYmaGFWEQF3sADmrqqitVRVz7mqqLphIEYGRHOrVc08Rg6JAjt7ExIH1RacMEPXx80GagE3fq6Ql2V5uH8Q0QYapcYPSqRV1QRb1sPB1UrJCMQcS5GVYpYbZU1MkRFcRc1FVVbv7UxnaObuKmB4Rkm3UzwapI15rUHZ+fRrAkemGFLg6IZm3ljlHSyEdoC6mb8gbgTwabnPslQVNQAlN0FSJANUdxVBYA8cCTEw0zpFjBDcXEXdaIWsmHOAmGizjbuLmFIE8zLjsripMooGNaVawBTNQA3UwdShGM0F4xQeHjAwMYpVZu+7MM4TMKdus929ipSew8d/UgGfN5KrqFaVReqYl3kZyzJKmV2F3UKT2NgZMYWOOJBjA2qiA6q6ZM+Tu0Jh7DrqB04JNzuMnZfs6B7QY28cmgPdGNZcrBbxJKSWiGNMgSPHrttsX213b7t0wdwhPj8ECj+59/v9wWb6cHN9fXt7PJ6WktWg67rbu4eUkjvs94eHw0MuC4AHJsfQHAWtmjUL10L5mWmfkTGmWDZl2Axd1yGj1bXfqKUaCIBjw2cgM4TgzcIRQgwBEZaa7w4P1WqfuhgiMZnr+5v333344f7wcDydpmVZcn3LX1ystMFARF2XUkoxRCJydzNXMHN1MCRDAkADhKAQ1IIIk4HlaXr4/vrj3d0H1yol52k63N8d9g/LNEouWmWVXrLWF28qedFpOo7HwzSdlnl6oLvxNAaOKXWvr16HGMj5zLl9Jihpf9Ej5X7TFtbGJwL16QqtQaGXstzf375//913f/ru+uNtntsFykqFZ8ScUE1FlslrrczAnJhT5C5QIkgcEwKNp8N+P87zCVCIL2LsU6JW9q6l1OrTXIuIK0rlwLtXVxdIdVoOInI43t3dfXd5cUHojJTSjqlfewf9xV37OvPYDnpGQA7BFF0AHEQcQES01KqqMcWuT80kIri7qIErkTuu+SxTXUlAVa1UybUuS8lZq5haS/U25BNYBRMx0cAcY0q9JXcKgTgQUFPlrspakSBGQky1dGDS0srP97o5quL5xFfHlddsZfeAM2x+xeYQoJ0L8K2j42x1n+Nz1w5T9yolL3J3/fDDdx8/frjZ3x/KUqzqMk2H+/vb7SYQ5WWepsvNbjtsd5vdJqRkDqag6i1VgI1kjRqZWJMfQ0eznzHtcC4guFVZpuXwsP+wP32reg94CizgZuBITgzoqAImrsUDuCULBJuB3bGddqymgIrk2NihANVICqqAVnMRHxx6T5ERWIXNwMXRjRHcvRZB8NhB4wZ1JxNzMuRa9ZTrXRdvqz4g9IHSi63hUItQ8JjQAGtrCub1wXBNm4Gv51KSuol6da/rOZ4WMRhRYGDmGFKrO7e+WBFBc1NVWLtY0VGdHYECGTisTArczpRtlWnAdlg8dwP1EJJx66AzVAywvdx2CWtBF2J/6muvtdo4NvUQmBvKokudqKgZojmCqZpBWZaSCyOrmcgCDgiBUAJbjMiMIrrkAi6B0VpxCLwltWptKRZKMcYYAcwMc66lZjVLScBDc2DMjIhi7Lbbqz71pp5zPp2OpRRE6LrUdSnE4JAEa5HyuOfVc5XjaZzyJIwhMMboqdetowgAqJtLUWiK0BGcGVOKGhgQnZkZuGGnU8LNli6u0u4ihMAqWnKcR69FTWeGe/eg0vj6csnVDR1AVedlFlexOi8nYnRQYuv6yKnfXr599frXKtWDPdbM/CkH9uOBCOZeVY55fpjGm+Pxw93d9zc33918/OH248fpUAN1m00JsYaAHJAYAL0dqEmIZpQLSHU0K4sv1WrPBDEl7AZLvXWDaxEVMHCxSlH7LWAhMSNEVy9ZS5TtDt1tv7/e3G23uy9Suuq7L1N8Qxh+stYOfnN3VwPsj6d5XuZlmaZ5yUVEv4PvmTnG6Oal1JRC10VCZOI1OVNFcqmlZpkbdKzUWmo1d6BlnpZ+mC8uLrqhMwFUFKkuphwtJEoYAiOieztUGRAgxNB3iUM4nk7TNCJ6SrHv+hgDENw93N/sb6dpWmo2V2Z8TtGKRF3fpy5zDIAgqsQKGJrmOx+X02h5UMClVpW8TPv9w/X3Hz7c3b6vyyRlcallmuZlak0yDd+Obu7G4ExkpiL1eHj4wBgClbIM/S6l/ury1Zs372KMm92OgoEZnol7n4j5GxQLyRt//tr39RwM+Iy45Pz3Cn1zm8bTt9/+4b///X/7h//+j/d3H/ueAKHUaq5EtNteXF28Xub88LDP46xeN7tut+vR0aW6EiQeNheB0zLf39wcqyxdx2Aphl0gM68qc8nzskynUWoV0zCO/ubN5uryrzhWePhhXqZlGu/uv08JECQQXex+3XcBKTZb9UzrWi6Lu6uaWjv9kmMMqgSIDVtZcjZTQA8BG1rWrRHbuxswRSIGMEAjAjOrtaoaOKlqXU+bF1V0ZGD2QG6+HphpJkWkaAhRtZUTYyCOMSFyg9EAgEgxrSEyIvR97w5+mk1fbHM1L/LEI3Y+8cVXIjo6h0BruR3p3FIGuOYYWtl+Bc2vZXNHBAM7naa72/0f/+nbb/7w3cPtvTu+unqdIjFZilzm5ebDx9N42tzvdldXr96++YK/HIjVXCq0fYaIxBgYORAzAoK7gTmYi+rzB/lRQh7BQc3ykg/H0+1+f3t/uHM7EC0xOSLUCrVAKSjiao0R2WuAWpSShQjMbm6lailSq4l4dCd2M/IVnUIt41qygoNpCNz6ycgcVMHcTU1mr8VD9RApEDaMPTg24hS1ol7cBdB+XFuspaI7FzFEMqPAyAyro2mqKqLuzu5OINVqFZHW3952lThQO7k0xo7DyiTl7khIjK6GK3skKBi4YEN4AFnDSri1rzf3llpuxhGU3YMKu5m4ZNAKRsbEMSWCQLg81eEQkBGJOIS42Wz6rm85kipVRERrlbosy9pB1I5VdmVuz1DM5lIDByNKiIJghB4YxNfmPVVq8UPLG8YYuy6JlCqtIQpCoJgCGBNAYVJFM1N1BCIKhCiisKYaVUSZxbzV/J7FJe7tzLhaZ9GKIXjDxrKH4O3r1proDVuZgdHdnZlDpBjZiQGiejtAiRDJFGo1rSjF5xNOR8hZpTaKOgIw83Y+pwO0cMqkimgVLcsyciRmjB2rDvuH4+3N3bsvjvO8dGGTQlu+FXX6Y9tuJqpLXh6W+W48Xp8OHw/7H/b7H+5uP9zf3TzcHU77qRRztS5CA+A7gIiJQFUFtMBgjrVAnb3MKAXAmYhCAERTUVEr2fPsNWsMmiKDITFyQBVS9Ua+0CUkjCmmwMwUQtjEeBHDjrn/OYyWw+3d/UI6z/OyFCmqVeqc52lZlgUAUkotExhiaNo5hdR4dBefS3ZVEanWuFfMEai1fqqYiqGTirqDmopUQGAncgrEZypyMPMGkQZGd8vzPI3HKlW1dikOmyGmSEynaTycjrkUEXF3MPRnWS0EQGJcz0RwNXUz5LPCJeTQfgm1sNlFXVTqMk/H0+Hh4f52Ph1qntHMai15cVdEIMLGegZgKzQaANRKmfd7iDEA4Nu3X7598wXH2G82nDpDUvNznP6YvG05tVVPtIjPYe08/PGirHCrtSbfsl96Go9/+tMfv/7DP11/vFnmmXkDgNOkZsLMfSKmLoYQgy4ZcjYkIDSw6qqbQeCC+sFipJhCipHYUxeZN67dNE25ZMDFPEv1JZuoSXGV6fCqSG1klElknJcJwJiVkFzx9at6dWH9cJFS7/C0zd291NJOu2xaAhDYGh+slrLknAGMCEMipAhgKqKte7eYKjAZIlXJ7hoCg0NupKHqpto0TBFTY8MwFzCIHDBSakdfuJuquRuiBNEoWqu4UzvRDtYpFQQPgZnJYaWvM3nhw5uZmrTk+bmlARDbYYgOjw2Aa2v7+Vw4XLPU6zlvcMbYA6wswwSqdjicfvj+w9d//Pbrr7+tSyYH3HZdF1LELhIDaM6HksdxmpdsgJuLCwqdOYiCKpgBApCiBQzu5gTgzbS7ub70UT4x7YgIbkXkNM33h8P1fv9w3E+Ildk4AoCVqqWCFHInWkNTFIFajEk5mLgupZ5OdZpqOzvUOkd0DhijdQnCgMyIaFKlVis5crB2HlWTflNXsVLIXClI6nGzoS6FFCK17lQPANzQYUwrNvK5Lami7uq0sBmnwB4DAiO1zi6RUqq4NVYZr6XmXE0buA/cvKqaKDozxaGPKQZpDV3kKXCIAwKaai1ScjU1NyFi5khIgUBV1Spaw6oRMwO6SMUFQMkFtDG8Oo6m2SoDBaCA/gl/WAphM2yYOKXuzZu3V69emVopknNe8jJO0ziNUsVUW7XRXEUcAUQNIddqp1M13cBuS0RMFgiYQGGVXQcjijFFohg4boYhxjhOYtmYOcRht9sNm8GVSy6qxbSUsuRlWZaFMTKx27mcCKAq8yxqUmtBB4annPAyaanmgBwpJmdSczOFdixpS3eZYs1asjBhCGxmQBYidj2ZsCmjgaGDkxQ47WuePFA0hdNexlFKllpNRdyByBzUzJhjFxMCuTc6xFJlyRljCl2XmC8I0jLr7e3h/v5wPI6b/mLTmwM2jfUJZ1iL49WWJd/d3vzD9fv/fnvz7f3NDw8P74+Hm2Ua53EZj2WZjSgREQcjQBFfZj8ddZ6sVEP2NAAiqPg8wXh0ZtrueHeJm0tFtPGkp5Ofjr5MXosPvW63oU8cAgMyAJVsoghOMqTAw2a4eHX1xeurX22GNyHsGlPNz4DoHOD+/v5kxc1N1dXQkAxRzJeqohDEuhg3HbiBGxN6MFyxX66uCmboDULMjRSmCtTqZjXLDLOWduyCqymAe9F2LE7aVDyflUKIIbDWKLWI1HmeSi1m0vf9ZjeELiJTLiXnXEVUtC2FdU8g05a0VTd1c3c1WylCARmRCSJhCBSZiZAAPHiGWAO1Kk4+7U/7+2WewAzXQ0M9BAbnBsRp7jIiECM7Nbqew+GYus0XX3715a9+/Zd/9dtf/eo3XTcgB3EyNVoDtcZw1fzQxruC7WCqcxPcJ2tyLsr66gB4U9Rax9PxT3/647fffjtPCwCaoBrkxc0gRijZSzbCbrt5KxpyhbJILbUso5blzduLmKLqkrru4qr/lb2u7WjKuF1m+vDD6Xi8i10NyQOzWqNKlmXKw2Z7c3O/uwg5S57r6TSpFCLVCuMhv30zffFFfvf2q1ev39mzU6DAvdaiKrVUVTUDlQTualZyPY2naRpTiptN3zoGRGSeVbXW5igqMJsZTNNJpHRdR0R5kZJrLlVFwV3Nq2FVLkbm5ND13W47BKl5GU9WJ4HZzUVdRatIlclgQYgA7E3jgAIqtXplSmZeluUTbkAHVa8rJ0ILQtYsvAM6mq/0Cg2n5QRrWvqc7z5H62vWHs7wJQcV3+9P333/8U/fffj2+49gHgPPOS9L9+7VZtNthtQRwcPpdJrmqspd9+r0LnYbx+ZTEACotx1IZhDcAdxMW3/CzyXkG+H+ko/H6WZ/+HA4Xk/jKc8F3BCdAgB6VagCWgmRUocheoyeEnBAJLe1nOTt5AYVRwciCOwaQZOGp5yaI7o7VrFSpMriXomFWZjNHVqt1HFlLCQkJiAiR2TqAvWBB6aeMCLyC22GOPQbxWpnuhyVWk2IAMCWJZdSWgmcsDXftrN5EczJ0Qwd1MyN0QOAEBBJtlorgIdAjI1gHj2AiJq1c1ZNTFe2KbDm3xFT16V+SA5upu5k4lIdxJkJKSJWRCcMjNx6bp8vBxHF1p+G1HAMKXZd6mJkIiyltMRfY+4Mkc1qJTUjqKJaVQ3ACjmTE5OZrUy07ew510c264YpdRBRm+dxGo/E0A/dZrO5vLwygSVm02pWzBYzn+fZDWOIpusRT4QUQogxiFZoePpnh1tHvnRkxs50BphVq1TTCiosRUtWq+CCKmbqGNiJ2n0yOwcPxExd7Lax6x1FLM/TcTotfQqMZEYrA5WtTJ6raUYk4kZLqQKqYmZgAu6MZoEIQuQdeFcy7B/Gjx9vuzh0McXWL/B0SMqz/QGmXkWnaby5u/n6/fd/+Pjh2+Phfp5OUkSy5sVqRgRACjE5IpYKZYEyQ11AFM47FExQM7gQR+wH6gfoeivZlwXGox/2lmcwaVAddIUY3d1F0JTROVAK3LuxKQe86NLblF6HsIOW0nyRiv/kOfx4OB7KvCYlDLRWWYrmqrlKFUWRKqISuhhi1CpalVvDZ5UGAzN3QgocAkdCzrkgYDvCoNbqbo+ocEQwRCl1meYq4ufjL7kh11VMas7L8XSqtTq4qREj1eqNPVRE1VTUmzfI+qix3F1askAVWNXc1RB05f3Ac4XUkAkNXGstuUijazBw9Vpqnhc3RXACp3bYF3NMERApBCJsZxw3hjk1W3I+Hk/7w/HhcLw4nLrN1BWPUSNboNCaZ1aSHCBGM/ZcpYg2qlk6VwM/P9aTaQ3AzGop82k8Hg4P43hycyIWcVUwZXcADyqYswZyV9bKNSNxjJFMai1Fxd1VrKjOIehmFwADOGvR8bAc9tM45R1RiIzIKXEMRFSWeZqm493ddZWkPo7jfDqMpRCiSvFlkmmqh+N4PD28Hb86nh4e793MptNBqpRa3ACA+t44tCBXERVRzbxWYHZiJ4oA3E58WJZSi7oXVZvGU5XaTHstVouUom7GRAZYlYpCVkAOMXUh9DEm0Am8gleH6i6qXoo4LmKuiswdc8fYmuvNV8iRMS+AUKvyU1NfEywDF3cEwOaDroyesIJdGjnz6qCRr45qy7o0TMoZvo4N03Q+W0DFlrkcj9PxOB3HGR0ic8m5LDO7JPQ+hphYxKpIbVzoVUyVQiQiBDJybFltN1BvzoX7ORv2sgD3wrSba5HlMN7fPXx///D94fixLJNW02pmjgGA0IBVSYUDIUQPDJuBhi10AwFBFTVXRA8BY0Qw0OoqUCuGClwdXE09RAgBUopIXLIvWU/jWKrHBF0Pm40zIwUiQI6YEsToHJzYGtA8hC7GbeANU48Y8SUXDxG9ef0m2zLX3LCPVaRKMRVvfMYiKm7mAEpIaND+uDaoBJoBoqMAVNfspeo85Zxnd42RvboNXYiM3ogP0UxE1vp742sLkZiBgvdDuLzaNIaZskiZzcEcjEKIKap37BypZwi6VJeX+Bo8F3WljtPIjNvtNqWukciI1FpzU6MhUIxsZg4chVRBVMEcmVTyNEk7LRGBGmWzra06Ym4uguhM2AKkh/3t6XgYhr4f4tD3lxeXWj1wNCluxSyXvCx5EdGusdy4MzMHHoZht9uZyTRPeV7mM9csIl5sv3JcHOaS78fx/VSyVK0FrdI8yuk4azZ0ihxSjAEpELVaI6IRWuxos9l+8cVfXL56O07T3cP9dJTxmHFLQxdTAB5IU98Un6qYL2pq5pH7rusAILsitQoYcPOVACP3Xbrq4hXhcDwsP3z/vk/9pu93u4uu76E197+wkG6N7sVKLfMyHQ/727u767xkqW6VTFbvuhRUtZoBEFWxVkenGIAYjVaPFowQIUbrOuh6iwmJ0R1rwZw9Z1NlBHaLUsNsnrOtZVyIKabNsBn6XirNk0odwF+F8DrEHSAaGAHBUwfOyyDRYR7n03QyVTBgIhfP81Ln0hgI3R1ywcycQkgxpbjEJYRARKbq4iau4hQphNR3fQyJeQZ3d62lcTeDWaPhJA7MkYmp5AqlqisRdilCCtQCbpUyL3mcRBWJNCUTU3UxVXVVU3UTq6VKrbpR6J+ZdpFapVZBUjVzNTcFA1JTBa1Y2BitZRDyMub5NI05V3eMHDoHUjMzBVVwYYQuhMAUQg9EyKy+8p66GwIikVSbpvn9+w+A6TTV+8NydfX24uL1drMdur6ZduIma8jENdhcylJLERFVIlup1V8syLpPfAXbtZCkzPNpmo6lZDNDZHCsxdup5UTMFNxxWSoBauVprNMku912M+zQmBxDDIggkpeCVTOQDEMHTjfH6eHhtCwzgPd9v91GZogp9H0/DHmZi/l8f/+hSqKo4zgej1MqROSmKOLH4/jDh/cfbz+8ffubm9snPmk1fbi/byYJgWJKzGiaOFAI0PcBMJZS5uVkXgEHZo4xmbm7lCzjaS5Va5WSs5rO04JEKqAKKsDEXSJHckMzNgtEiXBA6MCi1lIzSsWWf0GwJZdci6irYWMVS/0mxqDVaxFXq1LEqgNwCF162YvYTsNc3cPmxLZE2CPEfT3Zr2Xf4RzPrWcUrEvqANTeXDEfZiIm1WppARGouknNc11OBrKg1a5LF7TxsxVhIgJgxBiZOACAGSi5mqmYu5u2Ekxrvyf8GdM+Tvvbu+9u7v90e/f18fhhGo+lZBUQITMgcFgh02sh0ttRO+JSPVenlpQi6zqoBWoBXWNDAEdVrAW1QkXvescNOSBTAEdTr6Xk3I75cCZKHQFQDNgPlDpgMjeQKo1quhWL3arqQjC5uVl5MoiIF7urzrpYllnyIqWKapF6PvMUkEJrrPNWLFzzFaYto7EiHk2t5Oo6AWDj+SJyVyCsrhi6AAhqho4xREKrgKbuBoYrTNzPWD1iQgpSDdAwOJAZSzuvycycBZCYEDmsIrTKWAOkEBJO83HJp+HUx5REZF7ycTzOeSp1MTODGgo1WFwuuZRSSiHkwGyAusIrKAQMROIO4ubqoA3P1PrX3KHWOk/HnCdiy0saj8cYooqXXEpZAHzohy4lJupit93uUggIjb3O+q7bbrZEuNvujofDM9NOv/7yd8bLMl8f9st4ZC2ghayQCblEr2ZiYACKYP6EOvFGyI+cMPWYBux6XIoRauig3/LFVdr2se2WWlGt5R5MLYiIiiMEJhRp9ETIkRExBIgxpdRvtpevXn+xuXiXtlddtxH1UuqSyzAonBPQL1SwlVrv5/n98fT18fjt6XS7zEepi7Vjo4mQwN1U3RVcQMwdXQ1UwcGRILJTBO4AEa1SLVAWCMkBoBabTlALInHqYLMhrQQWYoiEoaGNVMUNYsQYUsuUMAbGIcbLlC6ZEz2Zh2dsrT+KE8kA1GQpKsrErl5yrqW2ENjMABGsHZVqmrW2c42xwZZbl6ShoYBUKKBWcxYpboLoDZ9BTBw4xBBjjCkRkapLQzuYFjB3AYgAxhxMtcm6i5U5z8wNdwBOBIEAjCJSI079BPlPz/ndVs1qYIAKgO28tQYkRjAgQ6rqudRcailiDb7h3lADACCgYERM6AYGYlbbMeFnDhqwDAB397eORLEP3QXFXRyABIyN3BCchIgcAJm8mM2lzE31qAVYe9s/TaSc0fUrxN7dQUuZp+l0Oo7jOLkGBCJaAeFEUMDNcs7KEMFDKZmIN5vt61fvIpJJBdN51lKPDqdSC5ATX3Wpd8iOOSbrOF69Gi4uk2olhtR5r3hxlVRszkcKaUMR0Zm4VjnsT+6AhLWeluX6OJ5u7m69XgEMZ2UFqlpFqyghkK54Ohc1FWmR1VrmaIZNS6mqWotW0VJlnktZSQUAHJFXI1urO1PXh8ABCLVCVXXJZTaQpc4kec55EZW167yxuiM66Jkfs4hGJjARVwFrdHXi4Mjk+IKLrqWLz/4WAYLbmmZfq+r4ZOLBDRBddb1Ia5VbSexWEFijdahV5ilP07LMWarBGc9t6hVknJfDKRynKfYdx24X+WJ3sdtu+xQTU2RGRjV3dERnRGRaKR3O4Hv4Eez3hWk/HG8Wy9e339zd/0nqUWWRoqJuTo7kaEQGpAyOLVNhXqvBrOZeFWJqvgb2vUuGvMLefMUMGmnBuloZiF3jV2H3CIDojcCyImjkhEDMyB1vNpgSmJgWKVo4eNdxCEVkqvVQwp2rEfaqT1wWCLTpLnrq+6HE+WSnh2oOBiYu2Yg5pdRahtS0SrXajnVXMW1AucCBmNW0LjJpbpzQDVZmhGVR08JVkRDIYuDURwSsVUuWXKopVABkjwZVJdcSISCyuTs5JiB00aVxzau4sXXB+pBiiM89LzMTrV1IHOF4PIzjsXXTOICZF9FSG6OO2KgAEAIjQJVaa5VaWv/x6nkSh0AxhBhjaxtRqwq19SBVqIiLG4hILbNZkQLT6XB9/X48nVoq0k2JsB+Gvu/6rr/YXbx5/XroOnSf5+lwODh4l7qu67ouMYYfvvv+bFvwN3/5rwznjx+W8Ri0kGTyQiAMwuw4hE01F1GzuuSiZqbGjEjszivTUVKx0zTDNB+r7vttHXbh3Ztu24XpUMajA1pA2m5TCFw1tkMBavGSzdvxAA2ATh4YU9f1m93l1et3777cvfpV2l4hh9h1xGEl/P4cr4jasiw/HI+/v73927u7f9wfPpY80dqv2dLMkGeTuqIt2+nhrbRkboDAwboNbC6QI7phWWAeScRUbDw6jN4O493tQooqhbQyekRgM68COddadBgwxaASXGOgTd/tNpuLrh8QVHVBZMDgbUOds4YvwkSE1olZPauIubpZOyzAW124ZRYV12NOSBTV1k6kM+oesWVA65KJoNRSpRgYMcU+bDZD7FNKKXYpxsghAkDNtSwZ0NsBm2aE5HQGGDMxgZZa53FRsX4Yun4IHBADBUInw96CRo5Pz4HIjRsvRCcmIiRqh7qtHTmOANTalwg59p2j+BGz1Gme53kxc0JSXGk9zayoCCDTGe7nrrZWUd3NwEhErDqBE+5ev3tTsgBC6CuyqSM4tk5NcEAg1gi6SFm0FlU1P5/a/tKuvzTz2KDnJrks43jaHw77hxNBIgqEjIREjgiQ1V3NNXCIoUPmYUivXl2+e/cGXdtBwod9yWVZShYtMVGI+OoVUJB+A47cJX77bthexGmSWqu5Mvur192ySK25qhOHrovDZpim0/F4IsZhSHPOx9O8P410ffv64n+62PzFeTmAKTA7KrTGQTWoVdy11lxrFimAGEJgjkRBREUWVavncoWIlKruSIzIHAK3c/TMRQ2RYuhScHSsJeecpyw6rR1PBu7m6mQrc30IHAOySBVzL3UJjGjBajEtgEbkzOgIjUXtxXKYu7RDQZsaOKMgENCJqPEvAQA0Q7vq41aEXfvBCM67jwhjZA6Ul3I6jKfjOE2zVEEgIidwB0Y3M5tLGZeyVd1ut7uLi8tXl6+urjZdn5gDoQE0xdi4mQNzg8q4tTQwYpPQnzLtuZwy5NPp9nR6UCmu2njN28qtBOy4Hl3UXDBVRwHIruadeurAFU1BqpVsps7sfYebLcaISNw6DTYDDAN2HRC5C2riYdMBeuvJluIAmiJqInQEQ6kklcxodbK9iB7n8sGdCa7Qhnm+fb43CHrCFOJA2BF1MRyOpyN5ICghcOo7YjQ0dWl1cQxIhozYMiEt/ShVvaqBeavARe761OrcLa43U62CBAN3zIEomGEuaqoAoOIiVnNdQnaDEKCB2hVVCF3VXZGAiFRl0UWLBKhXbo+BibmKlmCI6qUsp/HU+nPAGxiXHVYm+VrXzjRwUJWWykQA1dqwDSHEzdCl1DEHkSJSimR1acAIcAWojX/GVNsJHWa2zLPbmpBytxgjc+i6fhg2KXVmrqqB2pkxoda6zP8fvv6kSZIky9LF7sTMIqJqZu4ekZVDFXp4jbcCHhF+AP4/ETYgwgYEolfdVVmZGYOHu02qKiLMfAcsWMyHrK428k1EUnq4uoow3+Gc7+zaTXvf9/rdQ5ZEA817165KEEuSuUhBSD4nO4kpqLpZs6iIRujqTbWiRBKUFIBb60/ut64b0j7PKglSbgHdfDevgMRMkpwFDJRcKUACItBsAKuZKIlwznk5ne7u3s3zPSKLyLIs83KeT6d37+6neWaWN9DEd3Vwb9vL098+f/rXn//2f/701798/Om322Xdd1cPDQQHa7Berd4icTAjkiC4qrY2kOooeTS/OBT+rUM3qLvXqu6BRNOE88xDXI1CggxB7uF9/GW7aqh6a3q9bIlhnvN2XS/Pvz1+/B/r+tt8eljOH+b5fZ4eRMqw1/57VR0CEGHKggzDf+we2nXf91b7OHdyyoAYA4bQNdTCDA5NESJidO/eFAPQ1dVBB1W1TGk+z2UqktOYZYz/Sy4JMQwUyNBChCQnToxMaONmRgwMC+seGQiYghFwQBUYKQnzFyfvl+uEMSWCIrkIMhswAAT4m5nc3M1NHTS8tb52bYCYp2k+3ZlpuLVqMRq+0f68hed4+DgOMAAshvsv3JHCzWIwTKPvfb9sF+6CREIoREJFOI12Jij6sHuPYwk8/p2k5suPu9V2q/VW6/r6+vzTzz9//Pjpdtu1OxO4AYANfcToS1Vba3vOcjrp6f7u/mFalkTsEb21tu9bt91DHY6esu7aWmOB03ksqhFJzQ1IOfnYnqSc0629vmqAqjUkmiYxS2opPGrdVRXQW91a70vZ75Yv3wVxmsCgq7beY2232z7lLAREgeRIyEPCEqBqhAGAg5bhHojALCmBqo8ZagQyC2TMnQDAhtgJwEwhNLxbb+4WEEeG+hFtwSx8YF483EPNRpVnzOCG4JJIUi5SOHEupeSJvnlFxqA74E2aBmHuPvbaNFSjNMwTTMgEzEAUQA44rM7o4WFgHsccNhKC9NbrVutWe+0QMTDmQkjATGUu9HB/+uF3P/zD73//8O7d3d15WebT6ZRTAg/rZhFNtampOhydQ5ibu0UYABBSre3bx+m7q71rddhbW3utvZnqUWISAstgriMCA5C7QgRRjFqhd+jd3TACwKltuK2+3TzAywTLCR4eUBIR0agKljMtJ2RBAKcwCEKSnOdarfcwM98VHEtBawBOdQdzQhSBAWyuaq9r9b1ewO5Bz7ft27sEo2dGlCS53J/PH+brM8JHpkvOTRLlKXXrW93UVIfaWFCIJDDlnPMgYECrndrBnstJypSX05xzQgj30O5122tTHDYPISLsB706QsMYTK03rdxG2q+qtd4gxlAFGCnlBMJt01br3jcwvFv8S2K7u/VeicKMa9tbq63tfdgbATklYhkQAg9X7cPTNmJqEYMduzWi0bLjcio5FwC8raHaWm02Uml8lL12fNkIwklo0KHC1DgzEZkNKwgRMhGr6tPTkxDNJUeEmbXWaq0RjogDh/nlp7Wt+W2r171VCyEu0/RDllNKhbFAlAh2C3c1b9221tfL9bHfnhhcGEQMYq1160hmJhySSQSt31q321prt5Gh4lHBsfet9xG/KTlnM+G9QyBzKmmap9PD3fuHdx+SnGrtapaSvHv/7sMPP55PyzwVYXkbG353BLe6fv74519//vNf//XPf/vXXz7+7aW3CEeFsADrrhXWi+kOywzTRMIUENpt36M1Z6Fckim1zdV9XbU1VKVti/Wi7iAMtiA7I4b7+NZkSKE6qJu6RwSaRt3Ve/feS07n0+df/vrPvX0CoeXu/e//8H/94R/+t/cfsnAe08I3Vc+Xows8PDDynCeZcsmSEiGp2u1622573SujnKYFAupet23bju+ejnQgpNHjuqqDBZijBQUJMlOe0nyaylTGfr33TuTMnFNCTgoCklOwCJdpYiJwJDXkEfBjAIRBI1Zi6HK1m5vllEXSd7oBDKThu2EqMs0JWczZ4w2qOFTRpq1trW21ra2ura3EtJzvH1qLCDe1vltAOKAfadzjajH3MegCB9Me6qHqSOAshCUlZvTo1/XFicahX3KZ8zwXjPxGmA2wQB8ePBpGLPz3N3sAAES3/np5eXr+7eXl8+PnT7/8/NtPP/2yrXW4gQDIdOxlOhGwUKt13W7zLHmiXO4f3i25QG23dbvebteX58u+1/mUp1MRzsKoCq1qEk7nVDoHaG237sc8MhdiTgSZmVrfzbX3LaWcSwooSIEUtXYgyCV1Ddv79+wdlDxH89rXy2Xb9wYRgnyay915WpY0LUKEAGhqEZ1ZmPjgrAEAYsoJkSOaajdVIpfEmYdbGFRr1+oBpuGDOjYIOSOUNYIAhTnlLCJq1nrTrqpdzXz0/sSEIIJMlKdyPs/LaZpKSanQNyVjuA82rTl0926DkDOWqnQkTTghoBAlwalQSjTMWz6M2QaDM0aIkpgACdGa9iGLc2PCklMSLkkSeUlwdzf/+OO7//yf/9Of/vFPDw8Py7IwD1gomY4Rq+9dW9fWzH3A7YYvxEYGKSD/fUP17T+MT6HafehQbBSZFjR0m4M7gwDgFghgY2vrYB6mXjNodwDSSq25haUUecYyY5lYhAnJ3AFCUoigJARAVxOLiVgSlFnqnm/XqmYRDcIBC9HbzGSMuiJGPDliI9yFQrB867AEwMSnnNK8LFzQSQP4ettUDQgl0zQJ9miG0MAG5Y0pl1xyPp1O8zJDDBx67037cMAz5pxO56XkDBhurs1vgt32N24oIAAwEA3WnDsjGOBBqU85ZQhC5AAHdDDDiMSJIB2Ckm5hiF8hjrDv+3W7jECadb3dbjdVHXPRAEBVGkoLxLHH8reL/ejUwnWA2ZAQUURSagBYa40AD9DuNqoEZhnRtOHfAmghQkTevXs3z/MYDDCzqrbWOmCrOwPqNB3dfJ4gcKR2foOihIh4fr4Z1PBcpnd397PNZUrvc15STsJFeCLKBGKmrW/Xy9Pz82+4spuJQErjxNcwsBj7V4QOpmHqrVrdoXUAMIeGOxBB1xYBzAkD3Q7nSGhot46eEoYLQY5AVSOkaZpOp9Pd3V3JSYQRaRBD/u78vV2f/vV//PNvv/zt5798evq43l7ddEwDwcJ7hbpDXcPa0GkoMVr4ulmtg+4AplR3uK22176uBpjLNCXh09m2te7rRmFZPCckIWZm5t6tda81agXTgWUI7cNOZo+fLykxoD09/Rbsy/3D7Vb31iNgWR7UOnPOZan7y7cfZ4BZgJEYKXGaUkrZh3ssvFvHAGQEj8PV/cZfGfNzIiIgDT+OTAhkEsIkY9E15jhETCTk4Q6GEQ6EBKkkyUxCLCzMplb3puFAlEpmSRCD5EBDpDQStyKs1q3WTZczlENHh+O5FU5JKEvOgpI80mG2j8HMcOgW+75vz8/Pny+vj23fWt21NddOEIwIHt7Nex/mIXzbOIxpFDEfe4pwj6CI0dX13m63y+Pnj7etpvwZiFnSw927h/sPfiYHAQ5yUo/WtHVTDXeAcVjgd7OHoV4arPjffvvlbz/9+fHp8+Onz799fP7ll99u1900JDMhBwEOM446KtTa9r0Rh1lPiU/nuWt7enr6/OnT9XqrVU3JlCIoZT4taVmWXLIN/lqAu2/77tBEqGSJsFJAhIhNxKObmjJDKrxIziWrdrWeEnNOiB6gKX29PhAppTlny2Uq3WKAlB0QmSjlPC1zAXBzHzaqITgfA/laW92bB7lBOAJwhLm7ahORnJMLqkZX7d16t96sd3M3JBShsadgGhAXGlDMw3QImFMiYpbExHGQ/RmRiZiAXF1DI32tGT1cTc1BDWq3vWkdHE1CPOS9hI4YyAgl8ekky5IXTMzoFqoD6KK9mzCFJ8JxB3tKclqWdw/37pFznnIqWTB65nj/7vy7H9//8OHdu4e75TTnnEejNQxY6qDuTa01q02H1wcwaOwL4u0R+o5Y8/dXu/Xobu5vHP4hfHUfMZFhjgA0VhDMgBYe4R1aj7ZHEtcOhGQmTQ3YuECZKRVgGZRJHJMuADigFYTIxqLEnCYE4Fxy7+q7IimQIwsLJQfnCHRi8gjrXdWImojy9C7lLOnrXYKIk5znspxPD1Kww1ZrK2nZZdPQJJizBFk22esQMSIRTWW6uzu9f//+7u7sHjqgMKpt4GzCRPh0WnLJozqzHkTQ2h5hxAQYQTAsLwAQFkNSR8BCKUsueUoJyuxAHqGt7tY1URLK0yTg6G5gwJ/pi21s29fX6xMgDoGbdh14qwOLqz0ARZiIAd7kFDjEDUDEAdC7au/u0Jv2boPUPDgzEKgagDjEB6UkM1MzIhz9+nBkppQ+fPjw/v37Wuu6rrfbrbUWEQjQaxuz3POCU5lLLjmX3nvrzbR/c7XD0+cbiCLenc+SyN2y8JklSYqUck5LznOSoqrbuhrU11cI664NyL/UdeEQRugCQdrc3XqP1qF2UoNAI2/mOv4yxlIlHFV9uKvNXZu5M2Gre+/NKBlnI6ZpKtM0lVKEv8ms/HeD08v18Z//+//75dP16efr+uq6yVt4qnp43WLfoFV0BQBvvTu4uTd1U/AIRDBFs7jc+u3Wtt2nuZSynE+nnOXx8+P1dd33Pk8qIlkwZSbiWr3tXjfolcIDx5TZHNx399eXFRG66vKUgvX08LxX66qEcDqd9n1Neb5/+P31un7PBA2HA5xobh5OQsSUinBlYDDVpg10uN1G4siQBw2fJBGSB4EeMmImTixZSpZCSMMshoScKJDH+NrChkOSE4+e3t23bR+3HgoNUI5HmDshmisSEBNJhPm+7q3W/u7Hb19z4TSQ4SychDGxg3y7cjS1wAjY6/7y/Plvv/3603q59NYSJwS0fQfV6Oq9W++h45MiEXNi4czCQBhHFM5XGbSq1m19ffpsHiSfgDKQ5LLUf/gjADLPJLNrAJFI6Na3XVs/mq3/ydUOw52se11//fjLv/zr/3h8fHz6/Pz4+frpt8+369Z7lITEDBjmBACq6m61tt5NlVSNiHIuz48vP//0y+Onl9t1H1m7gDRA16fTdH93nub89Pn5eq2MbK573c2bCE6zeKi5l+xmTuzkFmEOSJJzKkzzttV1XXNJ8zIRBZLlnL//OnLJ02lZiGieVZu6+pTSNM3TPM/z5K61VQ07Bu4Wvdte277WddsjKIIhGJAP/kxrAD7PGVGwmfqI62p1V7OxchZmSpJEGIHG4tvNwxwjCECIcim5FEkZiXtXMxsWFVXf9xbmTPxuji8YjoFS7QZNY6u6VdurVrWv92Eg+vhlU+bai/lMDDnxaAi3bdDYLYkcUjlTDyg53z+cf/zxAxHf5m2e8pRF642i39/ND3fLaSklCyGYjcU6mIe6j+huc2zdejPtpnoYo4iRiAEoxvv5H13t4ebePAzQxz1BEEgsSZDAXVW/rHVRhAKQCD1Qe3T1iJAKhEfkpweqxd4iV0/ZsiARaXfzwxdgDiIRATSAeYDhRG+2MGYfZtoYe1QCICQejfvwhTFhEs65lME1Ox4ywLmcpjwnnmLwJbuNXQwTEQMLTilzumNOIpP1DuGMTEHeXasOlTE6UCD6ANobuPfU8E12gICS0rxMHpaKELE7cBIRYbahQDf1VrVKE9oRWEpKSUhGUDhZ7wSJURgTAqq2UAeCL1f7WzrmMSYZnahIQsKIqL2P6tLDv2REj3Hrgc544+W5RwPDrTUyADwUK83cghMnEWZEHCFsSESIZDouoyH51jeNPYyW3cyO6DhiJgY4sttEUko5a9H+3danrkRlKnNKs5XkvVnbe11fbv3KTDnPwvmNGK/r08d2/WzbS9SbBxoLJSASV9AG1ty7h6uHBaAGdgMLIMYAcj8KNQR2x970dut198FpQsIIq22/rpf0mpfwENbe3xTujEQQDt973r78aO/b+nq9tm1zVUSmRAESCHCECVqoghmpowcBoTm2Htp9/Mf33ZmJsDATQifiKeeH++XubkKol1dh9unO5jMsC+VEhEU7bNxzceKRVh3gCI5hkJmX5XR///Dhw4fTuVh0wLg9rb/CX6h7KWnbb9Ny//7Hf7ru386xgYWJacgt697qtvfaU0oQkVKapqJVwWMk+KnqmB8c80FiEWHifdsstFdzc3AarLXwwXa05EBEJZWC4EOyo25q5q5qpk5CNBw1xMTDlMhE7KpqPTwqABMxHakUzINz9Z1swH3grSzUuipC9wgL8+gswByAHtBbu63Xx+vzb5fHX9bLpe2VAsPBtPe2920FVbQjfA8AHQAdBwZiDCaCkJIIIyfmlACgt3Z9famtA0qgSJ6Wu3cf3n9AQiC0GMzH8IE2VzcdQ44hjv878YNHqFvvbb/dXl+en16eX56eXn77+Pz0+Lzvzc23bRPpRB5hKZE7HecwMgK74fXSPn182bYansDFHZlIEg3Gq1pYMJCzADMhUK2q2jwQkREonFSjdyPUCGAhwAQguTALDEDXvu2vr+vUszvWTtrB09cXxcxeXy9qDcOnzHMRU7OuQpwEtNfX1+Zh7i6SkpRxEPVmrapquIGqu8FbBokha8ohaRjLI4ZsIjwCiNB9DFLM7NCs8/ggMRaSQyI1fjMY+xVwMDVTdTXraKqE6GpE8o+//6pwat1ue+0GtUftvjfb21GZOQwdBoIjekB47aSg3bV7H7dy77pvtXdzcxHTiL3i4OoPSuw0lWnKqr0kTkJ9t9r2deXLdbpd12laJRuxIPIwQXb11ro5AHBXq/toNo2YUhIRIiGiAOS/a0X+DlljER3AgALI0A+5eJ4mItz36r7Wuqs2IsyZiDMzH5OPgffshITuoQYW2DrACiIhYlZAmLWHdjRHM1SLUoIIkXHApdUQgpOUKEioRGZu5oiIyMg8lKtIiEBEVITnlOZSishXLDMizmXJqTBy7X1f97pXiGAiERYBZipZFp5yWUpp6/W6rys6WrUNNq8HcGPQDaq23vtoB4nQ9a1KYEHEaZ4DTIQQcQCVWITQECwstFnFCm6ururL3WkS5rH6BgiSMaIXTggBDQzt27PL3VU74hDgICJJkpILMUeM58wPG6CbH/zKA+8TBMhDGDGmuNC7I7g79K6qOsaDTJQSE4VHRwQmoGPrgSO7z1TXdU0iANhbGwt1VZ2maZmWkjIFMPMA18ibAn/brt88VdCrCBaaUk6IxTa4rK+/vj59vD3/DK5lmiFIezCxcNpvr+31k2/P0FYPUsqCmXMxB+te1963btoinHICEQ3w8XQQEg07FAGQ9ti3dnldVYEpDzV1OKrXdbsQg1PwlGvbe69uOvr04Zl6A39+BxgJoIAMgxPNIRhcgrOjg+kxse0KqhZAATgohBGm7oRkBr05FZnyAqC933Likum08Pt32Sw/vwpyPz/Ycop5piJAnvbVJDFyICGLI4U1sI7epUi+v7//4Ycf//CHP9zdn3ut23q7Xl8e1496vZJE7XU6P7y+3hRO3/qthmRNW9/3qqoksp/qvMzTPDHRVEoLsk21a91reKSUUk4pJWbGoUVkRgr1ZtZNPb48h+a9q/Tu5khcSuJEEN5qXy97b9ZbN7eg4MS55MFKQiC3AV1Ad+utDT7ZeNGmPJVcJBFCJv5mJxpg5qOSoKatddCtG3btFq0UzoXDe2vbent+ff7t+vLb9vq5Xq913Vrt2nRYVAEcIWgMqQDj8PSaKg7uMSETE4kQCI+JCqGpbrfruq4RCMjldCdJED3nzMyB5IFDUmXHr4H6+Z8Ba8LC1az2ttX9tm3r7Xp7fb0+Pj6/PL26dYhwvTGjJJTEKUuE1LoTEWIiTK708rSa/5akCJ2YK8LODClHoAKqeXQlj4qUJBEz33rtrecyQNrMPKr4UPUvYmImkIyS0LW3atfb+vJy27bWmptLV16SvXnfwMwef/sM5JwgF84lQUbX0SHatq17qwAgnO7u7qdSTE279ea9uzsC0NA7IjkAmCuxihC+IVLj4FH7ENyN0a2ZNQhzNyIhYZLxEB7XwME2td7A1AHJDvqIKUSvGBDajFniG45b7Xpda7VoGk2j9THTGSsV9+F5c4wIDG+KPXrVtrU6FcnC4d4GL8iBxZseknMRZqHaOsCYops59q77tm7r1axHQCknQEm5pFxSmYjFPVq3vTZ3IBbt3mprrasZM0G4B5MjsxBB/C9As8NRTEhM7GRAx8rUzc1Rbex5EYARAJEHsgkJhYOQwzGGl3ToIpAB3A1MUQ1ZAcIHXYuJhBkDTcPRkQKZECRAkFOZC0tyN6TdLFSdyCgwYpxK455DJhGahCehQvhNQDjiskypFMrJWnvTlHoulNMiGSQDEkREopiyqEgndsNatVe7wkpv1hd376ZBMC0plzLPsxC3tdfWzCsz5TkTI4T1rnXvdRugdA8DM6/u2nrdoO5t3+ve9qmuKYuICBLT6IQC0nBQ2N8jKGO0DMMOM9xVYyJ6XKVjQogIw1x4GHQjAoOGN5yQkBwDcdhI3nT73YmGopmFOUKt61u2gQGgW3hAkDfm9XohCCI2szAdOtBj3sU8eHljQvi2GvBavwo6AqDWm3ojTubCQq3qvtX1cn19egRvy1wg0NRzLjRNFFuSmrPnfHh8pzSdz/dasCbfaF9hvbzatqtEcACKJMGUIGVJKRHK2F+s23q71X1vRKmUsiz303xnavu+J6GUAamFr729brfH2/Vhvc6lzMzi7ubmYePnywe5v/vdjz/+P58+Pn+aP12fn7fbxb25+r7Fvltr2BsBkCSKQGacFiZGLtGahEMWuTvNSdgs3EIIrLfX16dcmqQZaPvxdxwUkgHJWnPvDW2vezNVyV6mSBkkYRi7ilYEE7P+8vIiCdfbBYOsa10bse9U85xTPkPky8utgwXcffk+bq+X15fnfa+tNjMnYt+trW2bNmIyN1f3HqZDZArDPFmmknOWNBaa6OgafdARmAgYLLyboop0H0qI3kZiRbStra/retu1q4cDQyoJAyTJ6MuJaEz1Q62zwGBMBICFtg4WBwXkmwLlKJrMR7Jcotjbermsl8vzul2nOS1Lce/b7fWnf/uXn//y5+dPv+23a6+79aat9aYDdEyjGERE4Qge4ZABPtRJGAQCiDjG/oOrfxC79fgzEicMY4QBuCVG4qGYBsZhkfJRYA/R9ffCIICR2bFdbrcX7dW03W7Xl+eXy+WybVuSQIxuXR0MgGXKpTCj+Vz31puaxe3au11vm8/zktO0b2oWKUPKMJ3KtExlwXlmIo/ozCFp/Ed1VPci41sNJmRO7q5dkZCzjHgURECKUtLd+aTq6602bWr0cPq6d1O1n3/6SBx5onnJ81KY8C17A/ZWa63EkhOKKEJ3i95CG4UmBsiCwg6IRAIQqoCkZeJlmZZlhiBV3De1btZsdKhjoGIeZK5EiUPIx6hkSD7Hgege6DrEv4SUspQysdDYum7QB3bsywe5re3T09osmoEODJKG2eigwODNvhiBEOSgQd2je5RqJRHGkVnqDohGOHqzAAx3u15fn1+enx4fL6+vIwir7jfrbdum1tyCXy5bKdO8LPf3D/NySikFIPiAIZqbQwQRMhAxBYKqujpiI6TW/2MZHQBAICIxkzPBsXH1rt0CelczR2BGIMLD8yQkgi6AEKrm5mMufFwrY5gcZIZmMIyCzJgTJRlEdw/XwBhDQg9CSjkn5tR6BVDVjujMNv5+iFl46FgJR747CAbDN4FpiJgyp0wgiOoA5qABKhnLqSAHgKv13tXNERwREcjNtIV1tZG2EmE2hqwucyrz/TRN59OJgvR6bbd9Xbc8pXmaMkvvzWrfr2271n3tWjUsYlA30ZCitVbrvrU1r0VEEucpT3OeUmYpbI7EQAHk/z4ncTxJgUAEPnDHCF8NTWP7DoiBX6JXARAcD5XFMFwfyt/RQFiYBmU8TirC3n1kzCDGUep6AICTEcDtJhBGLBBgZhhDlR9uhhBjkFtrPfR9Ee6+rrdvH6m2v0AHD2k95zzVfa97rfu+rxvGJtgJwc2BO0NgajF576CdzIEJlnl+//Dejdvst7wy8vW2tb4ZRiYUkcQsCXLOpZwQU2++77fb7XK7tda15CypnO/fffjh96Z6u74idBFIJYir9pfb9bfL8zwVPp0eclnUtGvr3lS72tfNwsPD7//v/7f/x8f3fzmVf/748799/lX3a2w3u73C68XdOYARU07s4JxwOXOZaD6jNleNzPJwPxPAetlbVSbvvb2+VKALcl7u6N0HdOCm1lvU5ugVFLdNTXspUDLmEpJAiCFS27FtsNd1r9u6vSzLtJRz5oThOYsrC59Od++Cea2tWoUvVzvA69Pr0+Oz9XFSILFHj74rJUIeWg7i4PGCAACZxcBul5RLRsKAKJ4tZg9D8ggAoqAY8/axC+zNVDuCA0Tb6u3lOjzrQMiZCdDGHFFG0UpClFlCkkpCD3Mamybv1qrCmyz/+6vdwp0AMuOUsO77dvn0+defn54+TVM+nSbVul5ff/q3f/n1p7/09WptjyN+arxTb5iYN+koEh4qqqE0DBwe80BHRslj3cZqan3o6gIJGUMYEx/IsRiSEEYETBjEIBREDuhxcFS+u9rdWm+3y+vj6/OnVle3vq6319fXdb21XoVlmBAhghwBJWXMKY8j1m3rXXurezVe+zzrPGnbm5kHADHe3y8PHyYSlxyI3nuz0ACN6B4KIIgjg+NNqBxs6vveiZBRRMYZQyx4Os3C0+tlfX297dVah96/zkpN7ddfPxP5fJLlVE6nafiEhyGsdW29S4KIxNTDKji5o6sQEDKlxCTBCZgFAHqnAEuJp6nM0xROvcVKNSzcDAnHoNgi3JwIg8e5efjaAb86GQfDCDgYIQtPUz7fn0rJ3azWxlyHtO7r1b6pw9499I3zMDreCBxFmR8inDFqAA3QAHVsElVoDPbjGDF4vGFdWq/7vr6+Pj+/PD0/PV5eX0z7gBwL016t9qgtHp+upZS7u/MPP9T379+fzueU0qgk3NUtCFF4uOsRCIbrKsIRoLX/+GqPsIB+/KFHZOk4rMc21+1t0czEx+bSLADRFHqPkWN+wDYxiA6daRj2ChgBKYQRZYw7wcwDxjw1QhkMR/YXhJnbWNcOwZqk8WIjQiApU7BAuBBed34mWGr72rW72+eX3zglFL7V6+Pl82V9Xus1ujYns157dbNDZRi4r7VtTbu5OQHSUOKYebeuauEAoVuPZikkUdqiQoP9Wvve52nyubhb36yt2tbe1mpmRzQhhiSWhCPZE9x63bVyx67SNbfpVEpkCWIhNERj+YaMhG98o6NSHH9thzfj+Gc8XMbfSA0OYNLhjTiKNQKiAV8Y1jkkHMJGgoDedb1tA7BwcNgGt596hCVhhCDisR4DQGYZMXlmOlT0cQS0h5l27V2/ia2M6O1RQffmuZZ5eYAIYitLWh4WdCwTE0a45YRcHMzQDNmRQRhzkXnJ5/MMkXoxBN13ZqEYIl0NUCdFMRrS8XBs1ereB4UFAdy91qpmktP5brl/mME3iF0S50mEb+vlrx9x3daP57v383w2cPXetXbrrX118ZUy/fjj77fbU1loOU3t/h10qrew3msldxwm4FKExKT4craUPavbFGYoDNNsYNCblezzFGw0MujUrHcnBvPo3a1DGBMGchcxEQ+ntuK+eoClBCIBTmbQVQHQFMATk5eJRoJ5KjmVlKcpkCzAO8I34oe2t7Y3AmSWMWrnJMN8VVvtvYUHB4eDmyOh9tjWcG9pTZISJ2FmIpQkd3fneS52vC42Ygm0a9sqAYwwC/DoYwBuAAEMlDklShSsVetaxwrJygSTq9oQqiMRBwGCxSEOGbC8b54rCFcCT4xLkYdTCevXia4ZNjJot7VfbrfL6/Pj86dft9eXGG4RH6YVCXpD1YyVLBMgOgQQCWcaw3oEGCOFITVq/XiFzNyHGVdYWHLJScD18vz5069/ZZYkUqZTSrkQN+UtUWZg8jcj4ndX+/Xy9Okj/vUv//aXv/z586df9/WmvY9LBDGQjTgoVBKdTuW0JJYIc2JAjAEaIkIPt16JmQndFQncXTuYhQeMo2zIZtfLfrvst1uDgHku4bJvBqCIY4dgQ1CVkrghYGERZkpJhqj+tEyIhNfdb+1byoC7b+stZSoTwaG6GK5YN/PaelfNGcA40wRpOF84HMLdAxwByZCCaPhO0YPCvbd+u20IBOEl0+mUckHiZO6tax+hB4jMWIpMJQuPIaJrNxjT4UQpSUlJJGEAIuWMIpBLySUjiukb2mm8HT2C3GI06IeuC45EArC3bmsscd56JgwLC+8GdpQJEW/5tr21vdbber2ul1r3vW632ncNU3d3AkyIGdmRuvm+133ft23b93q5XO4f7k+n8zRNQ/Iw4uKZkAB9SONsECQNIr57O/7d1a7uFUBHy/cWzfL2NIbjd01jmA2MKatCrYPcFMjBb3mIwwITjq2NEW4QQBCYQ3/D3DM7EbpRBLuPoGQ1670PwnSYRLKRHTnymYzFU/aIDfEa8dg77/vXp8zdf3v8FYWAeeu3l/XTrT7t/eKgcIta93VdPYKIxuJbm7Xae1O3mHNJuYSZelc36Ie0pq9Nb50eIImwEfToa2sU6+sa6oiou/Xd+q7a1EOJnRnGA1cmYUEiGPgoN/Nw7+ZdkZw4kBKEeMdQOH0PPRyDdHi744dCJPRw7H6ZT751y6NIPNy5Y2MIMPL5mBnjC8YV3gIFIty91b6tOxGIMDG+VRKOQOEmTPHWtY9VXEql97Zta++NCedpJubhGo0IHSXeN4+V26vaptG7ZkIVKSw+nzPiPUSS5BgarsKEbNgNugE5UBBRypQSp8SEzAjbhiJBAsfhpRYVAJ0PyHlz07pr3auZjZPZzfZtq3WP0OV0Pi/nsKLtlROkzAG39bput4+Pn6bT+WE53SGTo3etar23Am9ZY5LS3f39cpryTMt5iU664e1FiTuSuzk6MvFUJM+Qp8jZScJ5aHoIwQGbQyB1Tp4LkBOlxIJmXuvYxXrvMWJKgIOoc4qUgoC18m3rtWqeYJ6xTImZkIEAcpKS8zTLck6nZUolAaU8lzxNSEIs2OD57WoPAOvm3SillGQ5zWUqkpKaxs3rrvttta4EwsSShGAwHrS2FQmJWPKxnJrnuUzTTLOqtt6h1mjq5lrbft28aYSHq5v5CGIEHF4oIWFgUOi9r+vqbszks6KHR/Rh8HTgIYgkcHTtWrf9+8MrEIwxCuOpyMNS0HW/n9q6eJ3X9bqtt/Xl88vnj9vLk24ruh3ZNE6MiCzDon+Ee0GMMfuQjDDCMesfbrwA12GQS0ORBB4kLCIpp5QTI1irL48fIXAq02meT1lOKS1CTfmWqTAyBkKMMca3p+7L82eM65//9b//21/+fLm8bOvVvRMCETCHJEwJmGGa+N37OefsbiOnx1zDjQhSIvVoru7VnJhRmAC8Nt33vq9i0dQaYDXz6+u63aopppznGRGg1mamRG7RB7gaEUvJETRgatNEIqRoAZaLSCoe1NWJ/k7qb0RUSi655FTcvbbDq1Zbb6quxKixhAhPU8o5RYS7qrn6eEzsbfjnA4Kpaq31IdpNhc532TwRs7t35dq49w6AzDTPZZnnnBITb3ureyWilNM05WkqpWQhGX5mcwdQSYUTaw/V76BOOjKk3qQ38MXHOxLFwYeODgBoZI8SHSkmg4k3uPI4XA/eertcL88vz6+X1+t2AwRE0qDgBDDW4xjCXOY0LZITINR92/Z927bL5XK9Pjw8PAz7MbEwC7GMEz78sLWHx+E5+F/Q6Nyb+RrRCNUxhhJ7hCZ6vJUhgwAQMNLNiYckHtXGFNfR3dCZkZmIkJkAwSw6AAS6oimqB2dHjLEAYRqCzOQmFtijR3QmH0cBRJgCM4rIID7iKFmU2w5a2wqXdisA6cs9d9suQWCIu94u2/OtvtZ2UevhIx94DJ9xSH8RiJAJI8DGfW8Rb3lrxBBk6Kv119bODRPVy963NoD8Zt67IsKAvaecw1GtufcxRw8niCSUJEnAF7lREKEIA0CYM4iAVO1a7VuV4yh6DyNxjOb8CKCz8K4DXukwmHRqXTUcmBlJAAhiaEaIUACFmSKQyN7KMmu1mykSbNuuqsPyMKJxjp1VWDQDhN4bMQ96FCIlqSNHgxC2rRBiLiWlaZ5mQDT152d6efn0Vp7AVECCAhOLZDHihmE0UU4nDwrfTNVUA0ADPXrAcBKHmdbaLpcLUyYU6369XLd9jTAiHBNzNOzOHtw1JbYIbE1VK4TSITKAcO31dr0+ns90f3cPoIYdwt1BBySvuVqkVEqZy1KksLl6WOn/ieAAbhFJSqeHd7//05/+25w+P6WXuvvlun/gNN3ry8t13/aUgtDIHS1AEYEYGCzqrrXtrYNZDODagJi2ramhO2aFnuGN6RHW9bCfOqeU5zIJZwdXs5yn8935H37/4+k0vb6+amv3p/NpWXJJlMQQmKjM83z/7v7DP4iU3lVu7efXl/Fk4Zc6EQMoUIAzpyLsqCq9p5KSwbGBzSlJFhEODI8DSzniDlptvXVhHgHnfSQlm0UAMXnXJjJmTKYKgCXnQXYzte22DfBCt95aBYSUuElLPXW1fWtqHh7CkliYiFnGquDbwwoRhCEJZqbCPAvjMtn7d+w6C7y8Pr88U98ua5IbDqLQ0OUJkjAii6QyDJvJw7dtrXUf6bHDY0FEZqbWwSxoREx4DDolM/HoKZuZ9dY1q3bVrhDwcnd/Ny+nxFx4KkvKtAgVppEWOfjm336Qz58/r1f/+OsvT58f62BSuSE6UeQi796floXNWs58d57N4fK6r1tdr733SJlEKGVWN1YXsZTbMs1Tztu217pdXqqaOaiZqoUdQvHSdttu1tYLEmrXlOndh6VMkwiPOV9E7GtHQATSE0yT39b99WVlLinNiDBNOclXpL8I//GPP85z/vDDu2WZk6R9rxe4hVWFICAGSsRFZCppmdM8p5R5tJrUETr27rX2Vqua0ReuAKKCDXkDMy7n4m6qhkgLzeNOHvuUwRweSs95EbfpeIKTMI9QV89AiLRufa+9G7jT7db8+zUooAMaHsGkx6s/2HYATiPYgEmIEmFmnLIkPmhEMXr8Y61jdV+fX54en56eXp5bVwtMZZKUgTPnWYSZOQKE6f3d6d15PmXBsOvlddvWMG+13q4XBA/XfVmmMucy5TKxCBKPWhQDGAkZmIjo24SFf3e1q24RhmhIAIThIwht5BWNJay5hTuYBVkQIVFEjPH9qAEMwkUIMwXD2LW4D3sDKmEXYHMxyAkw0WitAAd3d2gGFKKzGAK8IVyQCUsR5gH9cbOAyNrF1LStoPjlah9jYY/QiNprbXut27ZvvTe30fYedXNwhEBKLEkiAhE4MQl64IhkZWECQgDfo722fdldfH29tb0REeVRikdAAIEkzoFE3Cq2PgYdFCHhglCERmLb2Ho4MRAjIYQjObFz9Gbtu373mPzgoZRDQLOBfPiamgv+lnBvbqYQgDTwOeQB4QZBROA+ggs9juWhR3czHaCB1qqZEY0F1hdl+HgdwHZrbWceLBdEpM5VJKWUhHFdiwhLEhE5nU8iCQLNvjO/EVjCoMTERNDDRrfhowXpbX/Df+lx442grRjKzf35+aXuTshhsO91XTczQwQz7epoaE4R7KZehhbdIBqhIwMgjw9lut2un29XvD8BRG37DcXZj5iK9bavawVHZj4/nJbz5GgA8X76Y357XxA4yd27hz9BwJR/Zfp1362qvwtUi19//vj42yfyTqjh7s0dRpoumXq99Zdru96sW8ibj0stWnM1AmB3FCMRYILeom6jUPM5z6eZl6VM89R6Ve/Labq7v//DH//w7t3d50+/7dt2Pp2nMo16u5uRwSx5Ws539x/KfHYHer7Bv71+aRYPY3W4hwU6sJMAOqZEJYnl7BxJEktKSYZcFxD8ywgvwD32ve1bHQEYg098hL0O/6S6EcPQJ/dOTIyYxtNv3kfCzEECNUnMiQJC3Vpr67b1NoL7JKc85Zx4yDO/faYOyiwTJaZEmIgoZzudQxtEx1Cr61xyYWI4xPQY6Al5cHeYSsnL6TSfZjPtve8jCD0w3IGYkQBM1d0tAIa4EswgIpXMmAzcNAIaEvXee2/aOyFenz/d7u/qefbTlE4pCxahzCRIhIFfpkBvP+tt7VW3tZo6ITMJIxIFJxDm+4fT3X0Ob8xQStrWZl5rH4LzNM1zzpISBYI5IIIkv7+X82l5+uT7tl8vdd2rh1uYqgPSaZoJpNe6rfVZdzONiIeH+f7+vuQpFSeOiNjWenldtVXr2Kvrnd1u6+vLVZLOEwDJXLJ8f7X/4fcf5rm8e3dfpoJIwtybHnglESFeynSapnkqU5GUSRKYOYGheYT3ruutruutN2XhnFMphZndTQk8tBQpUzYL7ZWY53kqOeckg681VM9DWyRSksi46gEpPLZtM+uAjHTkfnkFM9z3DkDfGhcQncmGb32UwUMZr6rgygSCNHHOgomwCE4ZszDikJGGQwSCq3bdb+vz5+ePj8/Pl8sVueTpJKmkMnOOHDHPcymTuTPiu7v53bmcs6D3oa7etzXMemvrDcJNe9Olz24AkSKTpBgB1sOhgTRm5P/x1X70E8dkd/y7iLGvBRZGZAAyPUSkQ/Huh3oVjz2wurubHq4DIkMMQGBCJuxEIpQhkIknmSZmBlOoran2cI7AACXWJEEUboYIxDRNsCyQMxGxKbedTJNpVhPtgR5fnjIk+vDuAwoG0WV7AdzNNu0buAWiKagZIBBSSimXTANknfIYDAbF12pIMhqBAqjtq7483pj319fbbo1mLuc830+pCAK0ppA67IYNkYNbAIxkSEYca2BPPKq9jAKSCQVMNSzazR0NGonmr/MfGDgZRnzDK7n1roOHDDQy5UbhNKIyEFEgYCBezHXgBYhwbMVrrW7QWwwX6diBDeZXgEWAu/d+4BiIiQiIxmZJzR0wCMljRAkMNYnvRJer5JweHh6mqeScAahV1W/SacPjl7/9olbTYJqKIBHgSPVFxGq+Q3QKj3A/tA1EmERItdZae71dWQULAvc+5u2ufaCeIyeRzIMjBB6cgAubSK0KgTllIgZEzuS2Pj1+rNsLener0ynPd1MAavPbzW9XB0Mmcm+1eYA6+N3v7evVTiml+9NZWBbCM9GpzO9+/4//FRBV21//9V/+9uf/8fL5t/X1WXtvbpIFOQDYPczQuqhi617DRKAUJsKSB58VASgUaz+iFK1jb6gKOEEmbM1T6jnD3YnLxImi3q5X9DArOS+ncy5T3Wtr1dURel+r7x1VF0nTfAfxNVXleKfNAcO7Wm2dicwjwmoD8yIJBI+IaCI44MIjDXFshygCWzeHsK4wzpcAJMrEOaeUkww4kmnXUcuGtQqmY/DzxWoTBMgkJU3LnJc5ldyaWte+N+2qyJ1rT0mIa62t1sPXNJ4rAIVhAR04o3E3rJ8/P/70y0+Pn377/Pnjx18/Pn5+Wm/byGbFiFCw8OFM1EhNKVbV3vft2vdNVREDvAsTE7sbtBZ+eJpHaWzQR3IOMI1NPBKNiB0RDTcAC+v77bK+znXOCWHIGhAJwQn+Pnzzhx//9O5+Pi8/Pv/41LU+vTy19n9ertfTkohR5BANe3jdq2qTBMtZJEMEMYIIJMFpmksWB42w+4d0WrK2vF7Tutd1681agM9LmeeScgYnj9ZatN3cXBhBBT0zTik5kmnv4eSdt11fni7X+/bhhxkQEk/huO+tTFjmIvKteBmSMITt+82sEXFrDUKFYZ74NOck+bTMy3mZpuxm+6oO3rV17dq11n65rLfbuu/VzCTJeKwISU0BQhLumcuman3ftiRiHWwyz/m4pcwtnBhFeDnNWVjbYIm7dRtbHkRxR1UASEyZiBEzvW0wxw9jZHLhgbhmIlGN1mztrWsX4SJpYkiMBE6h4OCmSORuZr22vrV6ud6eX1+fX19fL9emlsqU0pzyiSmHEyKxEMtMMoU5IDiIOTugDK5LzsNkIkzCyAjh1tsOEKot5SKpILIPZZ/HGASZ/ccD+YGx/ILsf+vUA3C4zjgIAYnIVS1GvDn4YQocN7uaqZuGk0cfwKsgAhISocRsHO7BBQAgSaSMrtCb3269VoNAIuAEI0IXKTCMCFKGPMU0R5lQRKynxLnuUp3DwTQI4ovllZB+ePdBSiKR+ZZbv/Z207ZyBIQ37IOtLSLTnKd5AkHDSMiACQMwwgmCAJOgERpHi3bdW7Xr6wqIt2039klSnlJZcp4EADCTMwAjJRIBkxHCQYc5jTDCwUcYADNxSkIJFZq1rjXClIBTyLev/TCYHiN897GJcg9kHCEFcOgch3SORBiP1KtwtUPB4jDG+BEAQQEEwRE05AwwwK0ERDF8SgMQARiHJeiAso0a9q3GiFAPCN8rIMA8TyNytPduFttW97p/81DF42+Pta1lmnPJnGSUpZIwZ2RR4iqswuBDiKDkNtZYDKGmULWHO6MzJhvosEMHGURQppRLctMvDKOU2Y0IjQlPyyJJgNDCNfR2e355UnBD9Pv39y7MnN1ELZlGGDrwtoKGBmrgaNi+PFfMPA3NVb/3CLp7+NHdmbHrflpyZv23qG17rdUsdAIAAlXvitrBbVTG3q06AAsW5lwQOQDDDdywt2gtEAiB7EhGJ+1Y907oEFYKZQFwvby8tH1joXlZcplSmVrtoa57w6YNuU7P/f7JyyxpSt83vDGizQG8o9WmhNAVArR3DMgpIY7IC/Q3wjccfo3xsB1k+ohwc1clAEaSkchUpqkUThyAVQHJidI4X713BIqRkTIMLkyUJc9TOc1lnlIS2Sojont07a6GrRMRoKqpfudFjEHTCzgOKwvtutf2+nr7/Pnp8+fHx8/Pz48vl8uttu7jqIIIVwdHFgjoxtCsVuyt79vaew0zxFBDYEahwy1qQ9k3Xmd3UAVwD8pCiYmZiY4IrhHVGWq9rtfXa871/sw5ASAhvwV4//1A/scf//hPf/r9jx8ut8tl39dfPv709Pz49PzJrDmYu7U+jK4Gph42zZInDnR3jGHzJrk/Lfd3i9re+r6cpUyYZ8qZbxvWarUbUtw9yOlUhKW3GJtW6xEGEOSKfQ9tMC3Ds9bDMVz2tV+ue90sHM7nqUyTmmmzMkXKRPL9igRCu64+6LDZzZljmhgKT2ma52WZl2kuAWBu+5im1r22quqt9fW27fveVQG+3kGIqKoRQYwiJNJNe933JKw12tT3nA61nnsAcOJSZIjDaq3btrdmA38OQAEcwQFMlEUmljQknN9d7RCZPDOUhKWwsNTmq1sLM+uDLyYIciQjuqqbASJ063vdr+v6cr0+Pr18fnpZ96oWqczTsuR8Elk80A2IxwwrRcjgY5nTyGBCAiQet3sYJcY8dKsU7tpaqPbeGqdGlMbiNeB4Jd3+YxkdYhCFmg/Omb8BIwXpm3hECEIRiaAI/CLRO95zG9kTABY6NvNmyMyJYRIhlITTjOczns5IFHXXVr1W33fvPYiCCPzIXwEWF/GcQRAiVI1ZESlQvCwAAKaIGGNg9mXOhYineSlzTiUj99vtrtWzt3UHcFfCAAoSSlOal2leJo9Qdx7QbsQI3/etdQQgcLIKikoNArxbg6BwIGIyhA6+qwKMuKlcWIRCo+/QNoMI5JE7yUIsxNAp1CPQOkpCYpkSASdvHXqQCUUaiP4vl6IOFJyOOcqXLxE9wNXMB70yBu1aZFg3EWJoIMBHSRE+sL5MyCQA5A4p8cgRhwi1AYJCGKmxiOP7HO57oXQEeAUeCe9h4aHooAAQL69P/DO9vDzlMo3ff9+2bx4qmKeJ2Qf4REpCRDWzplu3lK1MHoQR6M6mrh20ee3RzQNBUmIhCA5FV8MAGnnIQ7pCNE/Tci5mHQFSSjnlnIXQlplzofP9nBIHQlPfqq63ffWhnsVhop2mOUmZss5TtxZuDqwozimLEPO36ysL3/bb58vlt1YbugslFC5TRjjdfvjd5YcfPv/8E5O480BLqvu2+e0S644ePM8pz1C7mOnIl0qMFlAPIBeGEwaXJKXIlAmQppxK4lptvY2cFbQc1nvbLed9XkqS5NbRiaxSveH1xc3q9nLZLx9vT9e//kvO91dPXxWXAGZmpgjoij7edg8ACA8iLmWKwNq6uSFBOI4Qoa5HBPCIPKu1W1cMSCQYwYgJKSNlJEGEoXoOF6FcJlOrt7VrD9cAxFHfJklTyUtJc06j4BOalundh/ucZL/tIxhGu7URGaj+fR4JHI7PobqCkJROy/nD+x/2uieWRMla37c9PAjRTIdbbjjWAMFMD9qTKlCwoAEgoAgnYWGKkYaAAyRGgOSDMa6GHuTOnggYKQkhM5dUhHlf1+enz6Ex56k3izSUmG9ul3/HrFnOy/sfPpxOp/bhXWt7XuTXT395fvmk2i/Xy+X1mjYqU8qJEvOcS5kzCTo4MxOLK2nDKeVlyq0LAmuPWtfbbWvaACOXlCZJhR4eltO5DFYHkCOGCDugu6/r+vHjJ6MN8jKfGBkHGlwk5eSq8fxU3eg+hJPkLJJkhBh+e1j11j2MMNJZlnlmIhsYSEBhSSmXnHNKGGgW3n3r+3rZn18vtY0cajU7QvIGvbBrHxECCECGXZGwa7dWO6HueyTZE9P4Codpu0w5T/l6a0hPAxY+VjcIFEG1mTmmPJ9OtJzyPM/u+sWG9PZQATkIYEKSADJHVVRjQKHRb6DqkZNBCBDuZr3X2+368vL8cnl9vdzWve/NAplkIp6JF8Ry3BMB7oAGpjBaPyIcqZtmwBAAMEhzKJSFsnBKzMIkAogQFOGt7ogdKTELcRoP1/8qr50YSCJ0SBPVDgAnHTGmb1HwSMA40tYxAsxD1c08wiGC4mAFhrt1612R3QKECQozQS5QCuZEblB32zerNVTRA4mBIdzC3FsP4Zjm4ARjx69diQLQRIJHoh7weLEBv77zCMARApAFlySnUs5l7mkiM3MiAhSkwnlJ86nMS3ELbS4kSWSs8hmDBQDRHRtZBLqCY7hZqCMgBZESVrBVwQMTYsKUiDIRYOPgGGmJmDLnkoukhGJ79M1VwyxAgRNPUxYJld2bkib05Dt+scaYRxvhdGqjNacjdgsBv+zXHQIIAwSYGIgJEQkDxjgdw9H82MGzYBKEAV88LAtDxum9w5uukJBw3D2juZLEwjJ272OxOmydEaEGAHG9vZrrkzwRcko5l+nbnQ8C/vDhvepCLClJyskjau2tN7VG6Ekgy0gRNGcbEAQkI9ZcKOWMJAjcN9VdgyHJkIwQgAdBEi4pRUKEYEoiI8SbWWg58/27IoU9Yq/GKyF4mHWBCJfEo8ufppwlTaX0ptpUAwKsTCMD9+vVHt61vbw+/duvP/9zBAvfIWXiTD4zB5qPJW6M2O6gMfpbd79tURsh4lQEmZNKrW3fdzM3p25+27S1MIXMec4ppTyXQQ2DJEwIL892edWcaCqDyTxSrjmlDDEMrk7WsG283bDvUKnuL4+vvz1hUc+tvIt//D/gS9QL4XiWeKg/fAyUcCiKSylqUVsfgls3165q2to+KviurmpqHhaMo5YE9MAAiiAPNHcfeA8nxpSZGXslaKHaYaSkEaaUprnMp4WzgAwMYuQifH9ioiTcm/bWt20fWcbD8/ntaz6yVuAQM4ekdDqff7Afieg0L3OZtbXttkI4Ig4N0LjOR9DNWNAeCU7IAyqCEAfISdhUgYCIiBIhA2JX85GqZEoe4cCDgStChBQIHvu6XiiVtIz8TQQZ6d0A8T+52AEEoQjKJFlKS3F3mu5Oy2maBdmade2aSIhGhPmU82lZJFOg55LneQpLvQkDM+Ltdq27Xa/rdV2vr1utNRDTJLnwvKTTOZeJWjdkQzLkEGFz0K7btttTw1xP713KnIQHeEcS5ZJa7ZdLQxARLwtlHvyr7wz6CMhEYR7uCFRyTkki/Ii8IyKkRJKYGNgRKgk5atXttt+2vbUGcbBxiAGQPYbwcTytiIbHvEm9N4OAfXfCwdiwCGPmnKR1T83Vv2ilIaeUJCGyG97W2g2WxVlygLMA+YE3+HoJDiC7xwCKWlivak0xYGwpPaKrgo1wD/Cw1urtdn15evr8+bfX1+ttqx5MaUq5ME/EM1IBSoAMESNkbTCSXUOEGA/3xPDaEUvKmRkYoiTOY8wrRDKEzCP/Wj18CAxkzJMQIP7jgTxxpARdkRhB0cwDnNDjgImO79BxJOoNpryaqo0GEhFlVJJIMIB/AeFhEKHqzm6hBq3DtkFAuKF2ahVUIwCBMDyCgnCw4pWT87GJRPfovQ8hmKlgQF1x28IM+fsK0t2ffvt1WtK8Ts127C1HZOSgZGPYgYoZRXjiNKGQMCCBAVjQAbApzNDBO1jKQ62ZPGNU8D3IgRDFiRr4zdCCJ8ZABJBCOSf2QLW9tW5KiFPKcy6zZEioOW7Xtu+WAjPwInmaKSYK1zAK48vP4F+vdu9dx6CJmJlp2CuBABElJRYeo5FDFXh4YZFw+GxwoG4osvuYoCgiMI/UYYAIJEKUlMksHSxbESLqval1/BJHeWCCQHysxA8t37HDOfILAoJq67TvWdJpKsc7T/Rf/sv/juhvRSKYRe/eu5l1pC65ExtCuINqaNfee61136t7hAORIFDb977VUIdAQK7dfv346fV6661tN8gZRChM1d20S4ZCEAQkThyujmCMPhXih0lN3C1nRKttM2+3lAZoLSyZewTglDmnxPT1udK+X19+/uWv/99//v/9v1wppQfmQpxTyhHw8Zeff/7bXz5//NhqBQgmcsPeyA0BUZgBZcRXjMQ1DOgafotd4bahGRDgacr39/NpzlNhhAhQpkC0QDP04Ex5klJSZgCTIvPdu9PDD/PpIRGs8IzuBSIzTpkJXdfrVi+33fVU6U//x5dXZDmd7to9C4mQJCHCgGCRnEvKWVKm7q7eqZtpdK29D1zB6NqPPY+HGwSYB6AHAZC5RjRACENBIAgwg/BqEYCEJOytuVu4ciQiFOacEgk5erhpdwwAgTRL0JQt3FyuMiS2Hv5t/gUippFbIDyip5i5lPL+3Yd5Xu7v7u5OS9vX6/VliGpLyaVkGtAHDHPrratpAJjqvm3ruvbaDnzEaCbM1Vwk5VKYEyBCrWqGPuxvNlYbvTZOSXIa1Tbc4+l0fz6d37//sMwnZhkvSYR/IYV8e+qun359zqqqte4v15effv3l17/+9enz8+X5VtcuiQqXiUthYQBrtr7eOBFnYiSa8O7h4Xz6kVG02l/+8tefrp8/fb48vby02l2dRCRDWWQ6MbKpaaASd0pG4q4jIzvCrXXdG+1tnRVYCqAHdhST7LVH22LdPN9srRW5P3gJmYvolwuEhX/3ux9r3bZtJcQ24tLCJaVcCh68lzgwMgYckYVPU9lPs7u5jlIyCPFITz1i1hCQwiEgzGzQR0wRgYLAEGBM1AkhyBxr8+5dzboZYjAhkRIBoXtAQI8Ic6n9+nL5zf2aEyZJw71+XIKEzNjVWmvjQT/YAB4I6KGhIy3Bx0tRW73eri8vz6+vr9fLpXVzEJZMMmOagDNwAhJkAZbRdEMQ4hBqYBKcMi6Z5oSDHzSdEuLsWhEsMyVGIRqvwBDqs7CYmA0aY++mI6LQ/T8eyBMCMYigCKkSkQ+63EhJhIESQAeMUS+Ymb5N4wfJRtIBohzAlEH6A9MDCmjQFWoD2sIM3MAVzcj9KL/jWLETixOHSAz3KSJBoBkgBY3o5ObbTdcrmqIHJPrWM+bb66M19lYCjXrNETMxSbZwARMSEszCE+WZCgYHYFe13kdsdIREhFvTUCKQTIRsHE6h4WTBjgyYnLNzChYcxChPQJlYcuYZCKm2NktZ0nTK0yyFE3sKso2sZpYZZeE0JyYmQHUHN7p9HNFhAABu3rsd/FciGhaOCA8Y3jlEYVMzdjOMo+9hOhT1w3yLGIikCmYWPixmR5DXSLkZAZySGAARSA79FFJHjz5CAyPiSHpliBiBv45vinpiZEZmjiCzqLWBw9erHfEf/vDHlAabHjzcLazjyF2OqEH7UERFoDuZq3mrba91Nxt1PyNgq1vfNzDFgJSn2kx9lAG6u2XOIhjuR/IdEmfmTJSGaVkxnNGngnNJHuzuCIig3loFYFwkLyjg7qYGDoUgfy9m7n1/ff75t5/++7/98/9HG5T8LpUl5WIGdbdPvz09fn66Xa/aOxMxkBuGoRsMFvqA6aJ7wIA3gBmqYVNSlXBHBhGaJ54KJ0Z3MANgBwQSlwyUCFkGgIPIpykv5/vT3bv5/CDgJc/OiZAyYGGKsFrrfq2XW/eY7r75IMtpubfOR2wUBoS5EXHKmUXc/TgjHEKta1dtIyDuC9rTY/TAoe5gjhEMIAA6zlgwdgqGHqbowIjELCw5UWuuPnTHw106zB9EBBRAMWwlIMjBx4RqwMXCR4jnt1e7MI/R/phDAaFQkpSXZVmmUhK/PD8+PT221gPxtCzLaUnMxGP4eQQdIWHd96enJ+26E491GwANQUIEEHHOhVjCo2MfGhrGtxEIIHpQAAMTsnBaltO7h/c//vjjDx9+nJcTRQDgGz/+e1guAADU508rbl3bbbv98vnjX3/55eNPPz9/frm+rq1q5jlRTpQSipC76m3fONG05JKSq5WcPny4Z8x1bT//nGrV263erpUwJJEUSFOUBfMEAOZhkqDMVCbaCzaNaB7ggYPPY4BG7JIhHPI0CjfYK3hga3Fbu+MetMms8x1+K31govuH87ahu0bAXttYgZcyBfBhX6QgDA919eEMWeZicY4wCOtNw40EmYmYAdEiIgicAsDdXMEGF8kJ34qkAGdCATLA0FDXaDayYyQRESWRKSdmDgDE6OpSkEl7v+61M+Uk3295EBCg9d5aHfyAkYo06gcIU3N1bb1t+77t67qul+v15fV5XbfWFSnlMnOapMxSZsmT5Cw5kSQiHuTsoSAdaDFhmBItkyyZMFwY57mkTO4NwxKCEAhCQFioHzZ0cMeu1rH3bmamQehk34LC/l5Gd9RfVAoMgZUbh0MMQfawOgcgBjN5RHQYEi4RZiYREU44hKQAyJRyQgjsaGYYaAqtI9ax6HpT1seRzTPggRRABCwhAsxvSDvkYXJkogjat7g81+trX2/kgUh4nkte3r4bgIKe3LFFgLH1CdFzSYi7KliE2pzzXV6WXAqlfW+3297XvbdeSpFS0DAMtGkPxYIoEQgoyBMjBJhiByZcyvTjh3enuznN3KBe+9XA0SJzmu/KuSy99yJ5ztMkuXBmECDgmecoTJJSmoJTJw7B4d94GzAeV7t7VyXEkQcTPmTthoQCjIlTYkk01Isw8m+IRZiIINjd3vhgw6or7m4abqrqY8vSwQDaKByEmRjMNQaBnpBiDEuaKpZSRnL80NJH+HAkEvE05fPdqZSTcK67Xq8bf8uAQAABkIMLQTE2bwRG4OHOHgQHJZwiRiqt2xgGqZvDAIu4VusVoiE4Ea9rfX59uVyvL88XUxOcp5Q9AIVkzvM5nz9M84lLxrBu4Iw9MwCOAogBGIIgcIRMCAEfeW9uqtZdOwMjp6/yTO319eW35+fH58dnbVGmeHhw4bi+ro+fL8+Pl9fXdYRxSU6A3NV7d+9DIR5qZu24LNS89wCglIQECMi0h3e0bq02UEVwbx69IOUJpgWD0dXMa7gQpXnKp/MyzblMeTmdizDW/bXu15fnveromPdmTcMMwb+TOy3LrGHjXiemiOi9q1lvbVu31ntvas21D6WHmvUxLYqAN6bF2PVEqIUZQgwvr0Oom3d3DQPrrkGYppwLSUnMyQKsKyCO5Ve4tX1PVHIpUpJkabXt66bWWmtJJEma5mn4kiNigE+/PllEgDjQHd2M3AZ4OQBIUllO797/+Ic//skjyjSLSEqCb/kvAHB3z0wUALfrtVXdbntONdxKnhCg94bASUpOU5Js7q017RoBJeUyTSIyDFaScp7m6XS+/+HDh9/97k9/+tMffv/H3/3uTx/e/zBNs9Y60Djf/Hx3tafWph05eq239vL5+um368vreqttV+sRE4Git4CMJU1N97pfxXCe8zDW7+vldvnEmOquva8scD5PkrBMPE3kaEYuAsSGEcy8nAsEWmNr9NL2QAt0EpiXdHc/P7xf3n04nc+ztZiyXC719bXWHnlDN7itTYqWGZHCvUd8a1gY42sHIu3Wt9a79q45W61QylRScSYDHd13rbVbzym9e7gnppzzvu296/BkDA0dqLsBIAcgBgXgmJOMZW+EHeguJhd6K7UwCJlREk8p3d3N7x9OD3dzSgkJtq3VrshMIsNft0wpp/xdKJeptl1b1d4QMCcWScQ0zEhqptrXbb1cL4/PT5frZRthDL17ALKkwRAvS57mPC15Wso0pVKQGAIcAsHDcRjQIpyQUqLTaTpP0muDiAFcEJkZA8MobMjP7C0M1y3UYizUmLW21lrfd/1fgWaHWx0AhJFKKilFgBm0bq256Zs+9qC5jBiMI41nGPARGA5r8pDWM2FGRO14wGlQEFMEuh1P+QjqGkQWZkgCwiA0qFUjyIuJMtMgpaEp7JtfXvTlxW9XB0AWSngPX652hPNEwjBmTYycsEyJt9bWVreGe4eTTO/yeZbESK56qxZVvWkEDw2UqVozC2WgQVgMH1J/JEFyYICJ0/vT/bu7Oym46s2tbV6tGxdeSqFEaCEgGUUwJRAGRkTONLsCIhMzICtQINHQBSN+Y34bysQR5ekWeoxJ7NC0uQMyje9jDFTgDU77doK8VbYIgCJ4rE48zJwIiIdhw5iIhSOl9Pa4DfbyqLtUbYzxAQAR3f3QrBICDd0dEFPOUvKE0Ove8fudIhfk/OVEQxze0SA0CMcxGIID64hBAXRMLU1HygIhUHgLbwA1ooMDCsznUiYZ4QJTLuflFBScpZyn+X46vZ9zRgz1VkECHQk7EfCRUTrkhFhr673nQ2eBTggS6E6QKPjbQ1i1r7eX9Xq5XbbevDeZyjxNU9332/Wy75ubARJzSmVBlHDVUEITOtqI3k1HYACCCLHINGVAUDVt0bslDjd1BRKKQHNSAzKXRCehtju4TbPc35/uH06n05JLNrdaaxirhwP0bto6SgRE7d4NLP5ekj3PxUD5WLKE2hvLtfdeW621VbXuegg4LWCEOI8cFwwHR3AbeG4YvC5EBAIgCAJHGCmmGoZBODjrRBDILHDQPyDcRrQwCOaliKSUs1sg7G4xNHoMnCTJJG1u2jrzd87dQPCRmzYWTu74ZlFGolymh/cf/lD/iSgtp7tjyz5mU4SSZJ5mYVbVl+fn3hQB53mBiGnKvbbX12frysyn8/nh/qGrXm+3aeoRcT6f7+7uyjTlPLShOU/LfD4//PjjD//wD3/4wx9++PDjPJ2nvORUvPe3/Jkv5Ojvvo798noxVLTrfr28Pl0uL+ttrXvvzcwiFKzHvjYmyJnMXJsCkGtot23br5fXJEgovUatV0Rbljyf8nKSaWaFptHcYQQnEtFAuJzO3h7AOxJgbywJ7j9MP/zu9O796e5+muYUJZgAGAy8NtxWX29aW6UEKScWxu/lZxFRu6q5BXSN3rVWbU1TRe08T2SFGX1EIZr13puDTfMkOec0lTJCiPSLj8vUAt0QADgCHIICEZQihqz/Daw5lI0eAzwzhirII8Pw/nT6cP/w/t05J0bCbW576xqhfuRujcHld5egqUZVbW49SRKmJETM5m5qvbd1W19eX56enz59frxer027RyARpyx5ztOpzKdSllSWMi9lWlLJnNLb8NsxCAhgcFfDiSAlXpZymssGaKpEjMQpiQiij6vdwhStOzoBOAWRGw1zBg7+2PCB/odXu6q3OpweNE9lEAPM4uWyRuwRY0vAzMRJiPDuTOY+PINjWAcOQBjM7mHuRyYfABGnnMo0lVMpc2YePL5ACKSRbDp4c8ASxEZoBEIRDMjEiTNzAuCu2Cpsm7beW923dQdAEdb56yyCED+8W0QgBrUOfPht9l5v+3bdtrXtJefTVBgw1AgiEU45CWFY1G2tas10xErG7t69R/dwQidFjGBgDmJHVqQWBE7q3AHcFTojQsqTpEkyO7MROpHzWLVOwUUO/PCgEqMNTjGB/92diABDOg7aDfHgggCjEbbhcT9ODMSBxI1RpHNKiQhYaHjeIDAEOynE8f6Nv31TV9VDTxEwrLIDezf26KN9x0NWPTZPh5ppLEqIaEj8TG2eWm/edRfiL48WIi73qcwUb/gDCMQgdAALdwiXAb8bx7O5WhiMmgUBfIzI4hsTYDfX5qtHG4EQktLp7u79j+84UypSTqUsSSYmBggzScwiuXatREOsW1KaANAM0r7X2vhAWREhxUxgTFEwkvPXSOoAc6+mpi321ay39aTTghEp5fl8n8vkrbs7lmlmySQuqY8MXIBoXRBR3VJhkgiMXGSeEwK6em/YdrKOESRpvj8van1vW7P9emvzgtOMiUk4//FPH/70p3/64Ycfcs6fPn16enr89PjZevXbJV6e4vqSreWAADQHc3QH8u+eqZLIXUbsxL5vVre2rb0rE01CDCkjVvIKYTa+KkxZSjlyXT3C1FtrrXYnAk+j8kspcUopCwsnOHYOSJSnQsym1lqv+25qGEeMOaVjl1iWqUv1cGtKMearBN27VkzBxII45fwtb+tN6m96OJ/CInAkfgMAIEt69+6DcFqW87unD7f11lrLWaZpOt+d5mmSJKZ2ub6e7x/KvPz+T/8YZoggzI+fP/3bn/9c6z6V8rvf/cMf/vgnM79er4SUS37/7v2HD++nec45ExESc8opT9PptJzPp7vTPC385o37cqsjfA0b+fYl/9eff/ocV2Xfvf32+vKqdTPrFhbogWqw7/22tusKa018eB2w1uYYrfehWiJk7XG7varuIiQ5p8QkOJdCKbtDb3592Vvtt+s+HvV37853y71W761xgvv35eHH/PA+pRyqzc2BoMxyD0vr9Xbb92baOvE0TUspIom/+zoCavVaozbYm7dq2l117PPMtLUdDwvvEJ+FBcTWK1K7bftWmzsCJBqMMAoSyBgDLm4eaopghOQEb/lkxxBxRBiMaHFEHNPifLTP85SnQpkCvTs5k3vf21rrXhsi7qdlnn3+3VfWrJuZd3AbSe8QQzXmqr7X+vL6+vTy8vj0/Hp5va2rmtNbJiDnkvJU5tM83+WypLykY48D2jUC/dDJHSQGiqH9DhEuJc/LFGa1gnu0pgCRjZOMZQYbQN93MxvO4Zyz2SCTwsD2pZTsqtf+NU37+4G8jzKJRHiZ5/N5SUl0MLDDmNEsiESEc5ac0zRlRByY37126yMKFCKwda2tE4QQ9qrabJqn03k535+W8zTgToPLhjioq5SEWEa8U48YnSKmRKXINCViCeBOhA42W9w316srR6CI5Fy+Pbxy5iSDqwKBPNrYkXImjLkyEQliqFnrYcaEOTEjVG1am7q72VCQu0egB7pDAAYGSlAmzsgcGLWbVOzh3rEHenhYsEMORiws7IQK4QgeGIAxJtNfk4kiYIgmR2n0fXIEwhG4fhzODuMPQTHiuMCOhQ0xArgBROi4tw/ZZCASIckgflFXHf51QyIRHvuwUUkjRIzIeISjHIYDXDSu9oiR3jESnb/MFhGR0vj9kU1drSIk+JLkDFBOaVqGXOf42DhA2g7hGCFDmmemMBKXzEbK56hsEEY4EKmRKWpHdwc0EpAkOSfhfH64e/jhnRRMmVJmEhytPwABJShIwuJCRCI5pznnyQNNjSRTqoMOlFJKkpgyYaHIEOn1Nfev0gerW+21WQ/rg1Yy5enhBAV4MnOz2LeuBvOySCq9tn3b19utt4aIXS0VVu+cg5OT+MCDDyWAde5Tao16T9M05TJ7RfNaG3SDXECYkDFnnE+ynMv57sScAGhb99u+9rpx3XlbRTvD8ESSxbEZ+7a7QsCHu9P5VKZpioiX1xdGRzdPUqZp+BK3vV1v9UroYQCUs8xLOZ2WeZ5KyUPQ+vp6eX299KrWHZGYmA8Y0ZBvjHyq45e5b+u273urzc0IyMlMlU0kkvVurVsSQhSkVOZkKAZ1r71q7U5I1vU79/E4riKGRaprV+tkigQRBjEkSjDNS0pZUp7n5XK51FbneTqdTg8Pd/MyI0JrbXm5m093d+/eq/YRggYRf/vrX/ba9n0/n8//9E//l//yX/4rAN3WVVimebq/u7+/vz9WVISIxJKIEx/ZOUTEATRM/ObetffezJz5QHZ/+zF+fvz88/pJxTvFbnpR27o2VQ8IIA9o3VqvGiGTz5RSEiI2c9vbVltv1rcukgBouAmQBMk6BTDJxKWkiBEls+/ryHsNwlRKLueZgFU7c8x3Mp+BOcy7WwfAlBJzkhyt47raXmutQ1f7NkP9RtaISNN0z6wirWRtTXvT3g0CEVmkiGR/m9a+jX0BAdy9GVtkwNFuwyAkHSN+dW2qZu6mOXUVAEUeIPNxPkBrvdUeBEc+MPM0Tadlfn9/9+7+7v58WuYyUPWmikHWrW6wbWO43bWnf/jxa3JoHDN/h7FlGLt1863Wy219fH5+enl9eb1s+65m46sXSZyylClPS5nOeTrlPKc0EQsCjQj5AIjAwz0TBwfOEYlgoIJTFsnSBzGmm3tEDkJOLMw0lqu9KxrmnHMS5sFKNzNnkZzz2tdvn6vvrnYhLqlISmWa7u+X03kSQTVzV2ZszcyAiJk5Jz6dyv39OZcMAXvtt+umaggYHqp+vW3X6y0JzVPa17at7e7u9P79w4cf3t/fny1Mj1AAH5grPrDN5BG9tSGZkcSlpJxEhAalJYLDxRR69+fny+PnlwAUyWA59OuXs2+7SvjbDTJGB+YGahI8S+lqbW3axzt0uKV9hPuMJHIkM0cLHLI+SkiBSAJUiCdOM2chqPtG3oWxo3oMrwtRI+4EDooaiqgATjj+pwMt92VUfjBBAsDCNMBj+uYLYcA8ViA45IRhEQMVNzLlRzmAPhbtnHBgEdW33kbDm0RyoZLT6XRC3Nd1GydLSmk5Tb0LM3VtY7etX/Jjvm4Ej9n4gOR+w+4Y/XqMN5BQhHNK2b25q31/CJMQJR5++DCDCCIgAOSBCBolC6sh9GA1N8oiOWVCQjjyC3trrVPv0DtUxl77aVnO51PdIEk5vT8v7xdmA1T3Nj6Qx4CFEDGylMRFJEnKwpk5ewSIClGwMHNKOeeccxGZmIrwxJjWff2SYtdbe3m6bNfqHRnzlE/v3v/hj//437q1dbuqjnV1RNCyLCJc98vt8vL8SNttI2KLuO+16tZtA1JO7u6taRiSI2CkAtMpkZxBU6/9cl0fn24WxpnDeSTdBLTL9enXX1OrmtOy3nbmfH8/MUbRGq9Pa22w39wp3jYz47369uv40+9/nyc5390BwOPj48vz8/V2A4Dz6YSIe63PL5ePn55ZCDE40d15effu/v2Hh7v78+m0hPte6y8///LTT/j8dLnpPoSCY4vYuoN1SSlRnkqWJF21t1b3fV93UwUftx4HsgAnZgYENbaYOJ3meU6lbvWaL0+Pz8/by7ZuYyVESPH9yPGot1pNdd32NYZUVt3UhVhEhBiJc8mLnyUld5/mUkopA5KKkInuiabz6YPZ8DVguHcFgM+fP9da371//5/+83/9r//tf08pjwzTo/KNMAA3EOQkSXKRlIfsz30sy0Y0e+xtv/z/2fuvJVmSLEsU20SJmbsHOyRZZbHu6umZO3NxgYFAIAIIvgEi8wI8zL/M71x8B0TwBsEDBhjSNT1TJDNPHhLEiZkp2XvjQdU8PE5WdTcuni6ktKIi40S4mxtR1c3WXut4OByPJWUXsIl5X17CU8rLacqklQEcnxROKc8pqwERKQATOu/HDd/c7YbBNcVmIMg1TynPhzKzjJtNGMeSqBbIZRFbXORh64AH9gjAtdgyyelQBkFTJRBz1bsaAvrAiKqap6ksUp1X72mIw2bYAVAqUqVpqZWcCqClpdbCn6WyvQ+/+Plfw0ptJFWnaT4ejmkpUnUcNtvNjpixu4EUvGfnpNaS8+E0TcvSUr9EwIye2dTSkuZpmY6ziDjHSE3WBeJAxNBJi4vMS5rnxJ7DEIiYnbu6urq5ut4MwxjCOITgWEVTqkbzUqeGMnHei2gpHd57MXBNl7Z4Q3NKp2l6eHp83O/3p9O0LLWqGjRKOWaP7AAdUWA/+Dj6MDgfib0Bqnbut8ZtYGiKdr5LjXeTHWH7IwEQtiJYy4M7xuAbUoqRejkGAcdhdM4752qtuWQS8t61guqfNu3juBm3r+MwjJvx6mocN4EIVGSI2+urXHvhk4nYO9xswvXNLsaAiDnV07RI1db3XIueTtPxODnPQ+Cnp9P+8XR9ff3F29dffPHm1d2NmJZSWgdNB8W3Yh1SiwlUFQkdc4yB2fUYsftzDoEU4PHqabd5MEP28fC0PHw4rrYIUiq12Jr66Y+rPaom5YRFJEvNUqtoJ88kBnDsglM2qK24UE3UqhgTIUGLjwO7gcPgvXeoWkoWZVICQnLgIoCvnhNDE/oTQGkNg0jkjBpRbNeJab0FrTghJhVeePRE7CgAEiA6RnKgRmYCZ/4ZRmyt58zetYiTVTTnNM9TKWKgoOQcELngh+y03WpybrPZ3N5c55InfzydTvPcqiqN1Elbwx9AA0+1tDyc3SRQbm26Lf2ASM6F7ebq1es3y7I83/Q+bJ6PgtScACgVzVxTkwUDAG3UI4gN8S41g2ZATyzcWHaAzVA0iyTRrFYNhRwO23h9txNjdn7YeY6AKCo511RTqUVqMVEEJvbsg/PRe6dV1DtzThW7ngA59t7HEEKMIUTngnPBu0AUiJ+5d0ou+8f9dFpKNlNAoM3m+tWbb4w01anUpm7uCF2MDqHsH3/wbqmlM0aJmjFaQc2dt1QrlGRSALusIgwbH5zmmqelppLbrSVErZhmdV5U9enxMc1yfFq8G1MqohDGYTeE7TCSZImh5FkVAZCg3b6f4LaCj0PcbrfMVGs1VWQCgM1mg4jOh1w1HucY4zAWH93V9e765ur65urqarfZjqbqFjfuxxB9c+9a7qY552o9acSOfYzeO4UOGSIEZEeuoW6d8xyGOG7GGIJDckABefBhM44OSIucjhMi1SrLkppOwWfgcjNLOe33D3PJSjhur5wfcq5pKd6FIcYhRse8LNM8zyIVAIrEVDxNDe4MBo1ECpCJmYGAGnM2Ajn2EOJmdDEYI3r2zE3j7nQ6TdMkIog4DMNmsxnHMYQoKir98pHbHLenh4/vP/748Hi/LEvgsDLxX+7BQV08LaeTZPIuJUm5glkIwbMLITiHxLzd+e1uGyNqKc5zHGMqhU4zFA46BN5FP2Rv3ifi0GBnKrYs1UjRXJr1tM/ToZqSCSKoeHWEjmAYHKDlkqUkrMVHRAvmiMATsQXZbKTchPkU56nmBMtS5onHmWUwWLOlRLzbXpEjdoSIBnY8nBy76TSXVK6uru5u7+IwtEDNOTcM0XsvteacT6d5mpdUSpWKAMwUnDe10/H09Li/p4dS6jhG5xFJQsA4MqGKSk5lnjPRjOicd8Nm8N6HEO9evXp1dxd8mzXsmcGwioZNCptl2J2u5yXXToLUVcDWIWpFtYq0P5dSTqfj/nB4eHrcHw9zzlUEqVGGr2xk5Ik9ueD8wD6SC0DOsGGfW/gDuGKgmrY2gnX2MUTEhoQurY1C1VofE5hlT9GLeIaeeXU55478dewcI5qBYzYzuOT9/dy0392+urp9Mw5dsDEE38TfapXW29cUDhGREJjJB27Ro2z05koagL5pJNWqUg1QReSd+yDl09Xu9vr67d3NF3e3d63yf5ksxE5B0XD42vsZ273rxSpYGxO6dC5b1MJqxD7W5eEBVtMOUAoItn7Ehs/qtIXWSsqIoopCpI4VTatayyM6Di5ybKUdB8RKqQo0cEijNXLomYPjGDi4RgxNBK2JhxF8QHPKvDAA1KYPrda4XBWtkfAbgGrXkmr5bcDWK/lyySOPbmhNM4zGZIqqiiJqis7HwQfH7F1T0YgxDt45MJim6dOnT0c7lVpN2ZRNCaARPCATe+9vrm/evn2bUnryvlaZplm09/KqCiI04SXuJDkttNZm3K131lnPfzmOMbx+/eY3f/23acnfjz8cD/vpdDjvvz+++wMHQUAUw6rOIBKjmWiXglFCI6wmWUqVolaD9zEERiYjsibwUWutYrVJkFWzuOPbL3d+GwHQDVrkCJZrSWmeSxIpsMx1OpUiikzOuxAjO8fOD+M4bjbMQChIwIyAgI5QCXqvdlUrwA7sub2nlnqsx/mUclIVizGDuWG48VsnVEURgIewDcGjpWX6lE7vrS6mRSSnkpac50VSKaUWEQVFExbxtWhNueQitQzburmupdg8qXPj67e3IlJrLjnvHxYXwAVEOBAujp7QOKUqaiGOb25249evrqgEh+aoISc9kwpk+DzS/XD/wEdeavU+HA7Hw2k6HKday9NpQkSpejxNSykCQN4579G5onqcliKyP55UNef8+HSal5rruQcD2Dkfg6gYWhyGYRhjCOxdVfEhDOPo2DOzdz60XFwToAmOHHMjG0LUKjmnItXAkJlb25cIODbHcNH81uB4p+Pxh3ffZdXv3n83bHYhjNOUTtMyhGG73e622xD8fv+03+9zSdA0OYbYRCkBwQxKUzMMzocwhugAIZcP7959/PSjAZpDYzikY/ARAFNaTqfp8elxv9+bmvPu5vr65vZ2u9uGENOy5JR7N59zyASmx/3j97//+8eP78o87QbXM3UX482bt2nk0x//MD0cii2liBXdhDCM2xhCy1G7AJstx+AcqSDeXF19/bNvgOk0JcvO1ZGdA4+fHt8j6+766vrmZn883T89nJbHw/EJlGvCw+MyHwsYajUASK5Y67ilDbPlVASqAyPCSpZRZivOA3pkwhDh6jqURPef0mGf94+KWK6HfLPtV6Gqp2lBBnItMY5zmue0TMtUUx43wXndbHm7HUIIwfs4xBgCAJrpkvKylCXlUkRFiXiIgyrsn/beD0uqaUnjdvSeAAqxIqm25p0Ky6LzLNNU2WkV2GzQuYHIsQ/kPTkm713wMY7Bh7eAKpZLy/C3hk6pVb7/4/szAXsuNZfW/JanaZpOp+PpNE3TUlKpAkjsmrACA5IBIzKxdz46P7gwEIdWRgFtPi0SNlm4VRCMoDN+Qat9mqrkklLSBoPqAZYqqC4MniAwOYYhDipSclbVeZ7NdBgCInjPKmZq/5A8zO3N3dff3MYQY4wtYYK9Y7ThTpuPQbgaZDtXjPv3Ho6aaiMeKLXO83w6yGPMQ7zajLeb8W473gGYqKzK4u3wnSivNf1Zg0QANjrRjis9LwkCA3AcPQdRJPKfKwcjAwKAADTweBOn6iWP5h8wMhKxZ1JmU8RGotvhWlWqQ2ZgWgpqJbVqhmYBaXRh05o52DkgBiYjQHKIHlERCcEJdetnjUpmraJ3QRc823VVbTi4FgC/4EVC8ujETM0Y1KEZohFUIwSKHAc3tnBzjHGIwxCHELxjtwwLgYtxPy+JmMZh3AxbJq8CJVcA8C6Mw3a3vXFuybnGMHk3g2EFUimNhI6QWtNDS2G0Qj91IjMwMKlCZI4ZCJBsGN3d3U6qaSkfES9N+/7+I1AyNVJzCgEokQO1lHPrxwAmYywqWUq1oiiNMpaAsMOgoUpTeLAGL0dgRQgjADtQM0vLrKZFSs5LKkm1QprrdFpy7l4kEhkSEMc4jOPoHTKr9xwij2McxxiiD77JIbN3jtjnfHdWFCylHOf9PM+1qilUqYgU4mZ3fcObYOAA3TiMnmE+vS/pUy1pmU5pPqXlNKV5yXVZqAoaBilaFiFwzg1kolXzkpdZUk5LUQUwo+vb27dv3pZUjsfTab+fp1KrcTGESqhMFQBTqqpQioyMyxw3AZjAOaq1cRT2phR7aRDfffxYrD5OpxjiPM+n0+l4POZSGqUQIeVSTzkVEyUoplNKxeS0zK0S1NKtp9NcDNB5H5WI2DsXvR+CAwXCOEQ/BPRk2BtHXXDEXfoiDjHE4L0nJqK1cx201ALJsmQVy1YhUNgOIwGNgRgbevdylRtYqXmaj/vpCMdPLkTn47SkeUohDJtxs9mOIfjD4XA4HkrOBjYMIYTQupSho7lMEanh3H10gJjL/tPDh/t3yJwpn+rx4/EDs0PAJS3TadofDqfjERC899en6+vT9bAZnfPLspSUCRCRkBkZAXSZTo+ffkzHR67ZbNuSXZcjxAHqWIsdnuZSxRSc0RDj9W4XQsg1GYpn9I6io+AZ2F2Nm924ieNwe4OsA9chlXLKx2Hxu934xRd3X3z5xcf7gwHmuuwPhzQty0nmU5UMGghaVYpgmbLWIiLek0hGVmJSoiwmS572hxB82HiFpLUgmGMA1ZJqjSSF7YIVu9T6x+8fGk174/JL83J8OuR5kVJ8cNtjBBLR1E17jg2ECEiiJipVasp5WbKpxZgBaF5yrmpIRiyGJiJSDComMZUqssxlmsq0yLwYsVathpV8Pc0pnGYfC3sXVSoaxhA8jXEIPrQ51+qiIpJS/vGHT2fTvuS0nJbGP9/MekqplGII1igUAFs6DcmzCy42TrIhjFvvB2YH2IUSsFvN3hXRgnYgNAMjQwAiU9OSyzIvaNWkE+uAgopV1ZxsIYzeUXTeh2HQUmotuZRKhI6RHRMBMwHTZ/0jL5bKzdXdN19828jUibivOWgp2eeQGZA6vAu63VwLsnAGfxIxEaWUQQ6eHxkHx6N3G+c2zKOpWpsXhk27zBQ6/lmfy9AAzTz34nQ37dgooHGe07xkNaVaykVLHyLGwRNxrQ3tb6JKlUQqVO35Q1h7Ubq57c6LrjkUFfWNrRQSW6kA1Uy1Rs9Xw+ZqiDE4R+SAqGH8gQzJVn2sDoVt86f5LtbsnGqTFXiWXelXS03clp89ejRoMHLoPDlNuIWCY6Yw+M3gN9756MLgxzHE4PzgwziMV5vrzbg9zqfjdGo5QyKqIlJ0OiXn3NW2bRTRkXkexrjbbWrOKZeMtiBk77nxkhFpypOW0rrdWuMYAFXRXARAY3RVq9gsdlB79G64ufbLfFH1MUuHSfUkpZBaZFZyQq5kmaaERGEc2DllLFJSzYoCziCoFWn9i1KkZCmldsk+pkZA1tJaBAgGeapWG62W1AJSrH2REZppqfNSpjnlolUQiYmcI3BsMfIw+GHjxzHEwXnPYNbaLhy727t/7f1Nu46ac3p6WOZZezLNiND7eHX1dnv3CigYEjuTetjvl/3+0+Hp8fC0Pz49nY7HVGsRNgmORx9i5lLTgYi3m6FWMdVSKixlXuRYiw9uu/N3r+9++etv05TuPz5+AKxFS8laJUQfhhAH7zwXUTFiijGGXOtiFdHYYeMGbHPcMdrlmjf44/sf9/Nx9/AphJBzSWmZpqnWikjeuxBiw8ZWq8XKktMxH9syaRQLhI04ATGE4Yr8OLS54QbvYqP5ZecdORbUqpItFxTwiI6AwFxLJKmyAoP2IBeKak0FCgIjIBkgDLRxu3izEVUkIMYwhsv9ChGZ0Tk0LDnPUz0oQqlSqy7qJvG8OGIqJZfSmrAtJaTSzPoziFUJgRmJHRELYKqnp8PT4z0yn+w4pE2cxlZqlFpLrbXUipWIDHmfy7I/4IkAsEptMgdoaNR7wzTnPB9AUjRTbFqLL0x7znme5sP+tH88mppnt4njVYx3m5EdPx7nlJeiZkMMPNxsxuhCDCEdjw5xd3u7CTsPw8f7T5/2D2KnOMJmy9utr7JLSVJe5mk+3t8fHk9WnMMYeNgOu9vbayB5//77T0/7/eNpGPy4cZttQHVacKmS5mmZ9j66zXVw0ZDr6VhPx5LmolU8xd1w6/0zMCil8v/6j78Vq4bGnn3wjZcDRAhATWpdYgzOt/nRCg0eCBHZsTOjeUnH4/z0uF+W3HKRzN4UWn02S6mS5nRSyYg9CysVaoWcLVciAyHTpQjNBR8OSwqD99HFGMZNvF5ON7vr691ut92NQwzBU2PjFmtak+cLmeb54WGa5vk0TcuSSimIRL71+1FXCgJCcsTBxXHYbIdxG4eN8wGdR+S1ANZDXmxlduyhaZfsxKYEY1JlWZYTiVXv2AO6lqJvHU8lW6aaYvGOgvPDMCDAPE/zPNdSM1MwbT0/3nn/kvXhxT9CiJtxh71jsc9NsyZndJ6rANZ5drF1M0ErINsa3DezRGCoArVarVqrlCI516a3XWstJfeL7334a2tTp0Nph38+ojUi5n5HCAmWcjJMBmpQAMqLNc+tVtxoNRAMkAzFIV/QUPdYGRuh9Nmh6AVgNWYmZC2gFUiNzNDxMPjduNkMgQiIkIEYiBUJzmJZoNL5vDrKHDr2phehbUXO4eoBdCYg+qwrhti5MDSeGuIK3UHQRpHu2bsOVfXeBe+CY2Z2rW81RL/Zjbtla2bO+ZTyfn/IS05zggCmUHNdpqVKJaDNuCWkZZ6neUIAStCY2FsWQ6rVqi3j0+VHDU2xCcqYmVk1yzk/Pe3fjX6jaojPnpYZHO9PtRy0VEarziUiUFpSnU4JiYcxs3dNtlJM0RsHVAeV1LoSSV7mPC85ZWlyYcFzaAzwTME5MFimnJdam0yXmFStolJVxGrRUmSe8+mUliw5axFrJ8+MMbg4uBg5RAqRnSdQRYDGRvIv/9W/PGNTai3Tfr8scxFlIkUTS1UPSLP3FdkDMTnMGAyoNopqH4wdujj4zUgj8/Wwvb26vUsp/fjuh7xMjhFS9dF8Rp85LbYkDeNwfff2m5//8jd/+8/SPH94/5E85rocD1KLjlu+fTVc311tdjukDdJAQAH0Sk4h7bUQFFRGBWiE130ZXc6r0QE5iVicCYEREwWWlsRyLkYmdqaiEqRJENW2MJplb1IV3nvHvgE522xn57x37J1z3JiJ1bSqxjpIlUZLi4htjnrvQ/DMjLR2WzRbi2YE2JBOyD1p14FNMJ4GyBfLHAAJOtGfLbnWCtpKPABUhFHXtlAwJINWX9G+qTSS/C50CARKBERVbanzcpzSEZktYXU1U2oM861SbgjmAYiEJZuUslg5S1w3StUuAosIUERrck1GF/RZTnMdp+N+//BpOR01F4dudO52HF9vtzebwRDShMjoA99d7b754u3d1c4jSalLSZCzUwlk0SnAPM2POR+NrJRlWaZSFAGCC0PYEuy1QiC32+y++uKrL754e/vqZknT/Yf70/7eII+byrgdIoF4MJSMy6k+PSZ2JVcZNuQDlMVqNhVFAwLHEOnCfIjIjx8eqlQjYEfee0IgsyH43RiJA5EvWaZTqiJVdVUAwCaWjMQll2le9k/HeU6I5DjEOHgfnfOIoFZynuflJFK64VAwIzAWMVEgbFAe1SUXszlnH52PPkYXp3Cc5v3xdLW9utruNtshxsiMiKAmNTdHuI9pmR/3+3lZlpRU1QCda5zMDpFhXQdIjtj7OPph4+PowsDOQ497277Xg1RE6PE5IBh1a9+lFIAIm16XigF3yC+BoYHUqqK51GUpwfEYGzTed+owFUJU0WrmmBu0+nKZf9b8Zg0KB4BmYtp1lcC6nULotm9NHWPD8wOs+XjrarDtj9M0P+33x+N+no7O0dNTZNZcTimnJc2NiFy0s6eeHxciAAGdm+LXNquu98XQ8nii1Q2lwbnZX9LnWrXKYIrazhTMiBAdsdF6xxuCygAMiahD4zseqDWcO2YCzEtNSUouCBBj3G6GzWYTIxcpBmZM2HrcgRHZDKQT9phZLzL08KkJpJKB6OrTgJKZGmD/MnyxBXMIw9V1qaXWArAYtpSGgCl3VBI2pwgJyDXWplolIXsfnItDHFzr+U3LskzTMk15SYxci5yOpwbOJMKr7Xi92xyPB8cAVtEE0MC0ZK1aUqq5CKKyApF1L0ux7cqMwGiEdZ72P/74uzGMBG6aL8U37dOPx5KOzswzllBMLeU6z3WaCwDFOBEzETnXyA9cjCwkqlXUiuhpmo/H+XBcprmAEZEbvIueo6ch8GYMSHA8LacpT3PJWUSxqqpWgNYWiCZQRU3YpMtLpCxNpnVO4mZlBmJgh8yAoITQ1tDf/LPnC5Fa59O0LCnX6pyvIKk+zssfplnjvGd/jXzt4Q7Mkd/5zavN3dvddJqUccib4Wqzud5sbl+9+fKrn/1ySvNvf/sff/ju9/efftSSKKQwymgumyXF3dXtN9/++td/8y/+9l/996XMb99/by6d8r3wkpZy/SV/9fPhy29ev37zzW7zyxjuEIvN+/rx+/ndd/t0sAWCZ2MzQ+li5hfldsSvf/OzW8otHSpVqnQtDUB07BrlsGiTfmyolyaRch680gAwdtSFmjb6WOx7TKPSWC0wAqL13B4CrJl571zTEOtqLX219q/mF1+WqAx/m+HTxUrvZX4FUEU1VMTG+oQtgwY9Omg8Ou1k1l/2rOPaX8kAhAwEBFoB2JrcDZAhGzoDMtTGldi7VqlxK6ECWSemaAGOmDXhrBaYkPbdxaALMLwAmcLTw8eHD9/XZRqYNj7e7nbf3N68urmOQ8xSZk/Rx6vb7c+/+eqf/+avbzZjPc2Hp/3jk0CpdZoKIcec836Zn+Y0K+L9/UMtmhKeTqJVox8HvxlDHv3mi1ev//nf/LNf/vqXm+3mw4cPf//b39X8rtbKYHpNqB41IBCqBzHJWcT4BGBkwlaYETyrowIKNVmr2Z8fRS1QlYCa39/IVG0Tw83Vq6/fvvnizd0yzQ+PT0/7w+l4XFLJtRF6NCPXqs6aUxVtYqlWijhfYhiQQCSXklLO0uQ+m35ab3DGlr9TxGpmRcSsiLjCPpdpYTfNj/uT936IQ4xDQ/Axd1ELALhkzE0pHU/HKmIALkRmR213AARiz47YN9pPJO+8JxcMWQ2hudGmZze1RaqEhAyqaAjUQvU2W5CcwxD9EF0M5D0H753ziF4FElJGKDmXUucFgqer3eB8DN4PQxxizDnVknJeUspMNMTwmQf/wrTfPzz97vfftZ8bBU3732q2m016DsyxY9rOJr8XqnsXn1lKaZrmT/cfTvPRUIktldPjPhbJpeZewEdARF71oIi6PACs9Izd2OIKo2ciUkT0DD74VsZw/tmZN4NcM5/7Ry82h7Ywu8QzqKkZAFlffKBwJoS01SYDooLlUgQsYmDncGVbMVCTM+ygV29UTUS0SiO1bpuUoenaNoO4xuc9WGiNZdTKTigXnRhoQJVYGVSlqibRxawiWCXMZWqIhFKdYU7FOybnKATXOLIQsUtcVHl6POz3j/M8mYrUmpb5eCTR1ARBhnEIwbNDH3nITsQ3qJcBorngNo4DkjGT986HEFwgIlVlhuBpdzXcXO0chdMhV4/exVZDPz+OD++OaT4MRDHwMDhROU7LPJclKQB5l5sl8N4PsdEyOgWtjU2+yrykaUnTnJelGBABBXbB8Rh4jJy2lQj2x/k0pXnRUk0aFwQqM0ZHnpCRArNj9E6CqyVKqdZ0DLtmDVpnDWhKJ2goZ/+7DxHNqfXYolY7zeXh8f2P7/4D4A/LdB3H13F8u736pQ+vhuhevfoCAcbt3c3rj8u8DD6Ow3a3vX31+psvf/brVGrcXd+8evX9H//L+x9+//HH72opweHgWdV/+fbur//qqy+/HIZxZj6O29PNbXnzhZnhstDda725Kzc39e7OXt3EzbgROZSDTFO1WBdv4pCRpFqpZqb4ErWFAF9984VsYPX9z1rXXeaxca9WbYRdrfTQXK8+sLO0tH0REeC5hobwzKna7PKZia2b9lbaQ2b2LTHCLUCnvrespt2ey1jP53/4/UOC+eJqunfeKSOwVw1x/aFvLu1EoGchz/be1uJfE79DJDzvyKKq1rRcEQl6fw61Yzz767jW9frKBgAGhC6eZNDTBo2Kby072ktp2oC2ZbwbQtjBNmxvt1d347jzDsGqCKk4tMHx4FwAHIgxDhBz9qGCQa51SclUqrDzXkEB82IP5VQr1gqm4CnEEK+2V1+9+fJXP//VP//bf/bzX/7COUfor3evgttpXRzHm6vXb1+/2t3sUiofT/c5AYgzs5qxEJE6ETFxnnWzYc9OK+gLjxG9H0gBG/ETIRN4h1+8/eKvfvWLX3379TdfvJ5O06f7+0/3D58eng7H6TQvTa26gXXa3a+j1NIEq80Mici1dDYROIc4gDUSLeyeaAOEARiBnXFZCIDWCAYYmdABYCPqrrWkBXofI7ReehrNn62EqFZVQGJm5wM7v27ZrbHOswvNXhlw1zpvReWOM2/m45yBNmumHIHQDBuLK6yA0LbzO+dcjG6IwftA6EQMoAu0FxEqlqsv0tp5WoiO7CgtUGupZUmc3eJK+fMc8n/8/t0P7993E917s1TXGLcJQwDa6lXb2qzde8u6q9Iz7M3OqVRdUs65VCtZ5qejD9G1ZAwxMnMIPgYfQhxiS7Q6dl1aFIkAVnj8c+68Y+v6ujIwgOArwOG84FNKzD3LQmtjXfc81p6zft/V1m2gVRcQAddtBXPWpvM5LXM1HTaDmOZaBaBIUVMGKUgBvEMiWAWqapXaGBMJOgcGaJ94aC3wPc+DTpLfIZewPPteKkvJjwCAJqYnqUfVBFAVagWpIognAyDEpxM5R47QOQpd1xTBmmk3FZ3nfDxMyzIhglqdpyNgqRJcYh/ckGOM0UwR1QUO6nQWEWV0PnjvuQX3bROOcbi6uh6iJ1Jm9WzDEDabLRiVUosG0EGkwpo5NbMf35/mw3Hr3XYM261V1f0pTUspxRCJWcBARRxzCMEH5xyLaREpVUvnjFDp+VNB0FzUEZXCpXJVJbTDcZ6XKsraVIWJ2FPwNDgaPIeGNqHGN26NZqSR310mg1vzEoAQqmNiZn9RpTa1WhohEOViclx+/PG73/396fBINzfu+ubN7d3P7cv//ubVb3ZxHL/88s3rr9Mv8vH4aVmepC6MHOPt7urLm7tvDd148+btl19//bOv/vP/e5yP++WwEJTR0eDGX319/c9/c3Ozfdrff5znp8PTvccf397NgWxJuLsqgztS/WCLw80O3VSWT8vhU57vrTx4KhqwVrJG6W2KXXTp2ba/ff3K3XqmVjIHs0YucAb6IAB0hb+VRLa1tnVR4WeL1jFFsJbqztZuBYauG6a1g3UQa0fr4Xrv4cymuJr29U3nJGEbC+1f0GSDPZv3tZcI8JxkbEJJ509pgUQ/XdMGlq0mTbOQiQAJLGtZas0q1YgQlVAJBVeHYQUg4ZqV6MkFbGoa2Ps5+4RZb0brkdHm478M2uGLq6s38mqr7ujzxm+2cRyIqUhtGbMlKZuWupym+x/fu3x7O25HHzZhSCoGLMVEK2K43r0eFMRompbpNHfvA9gRRz/wjf/NX//Vv/rv/uVf/c1v3nzxhQhMU767++L66g3YfrfdfP3Vz3/5q69v7m5+fP/xuz98mo8FjNBACxVkUCfVSgXv4hDZu8GULrUJiGi7vVIjct4xMWP0vB393/z6V//Dv/zbv/rlN1+/fVVy3h8On+4fPz08PT7tnw7HJeVSq0HXJ1WVlEpOJaWcS5XSu1MNTNRblx5GQmpu4TjGzTgggagUkdKaoppeQ9dlwhBCiME58p5j8N77xoVVShVZJzhcXggze+KWcmcibpa5QUi4qbwAqZloY85gJGbuVNkASPTMxo0rloqIjYBQUKhFkyaoYiIiasw8DHEzDjEGMypFq+iSk6JVE1aooqVIqRpVuXGYWDCzZUmisCzZTFP68xzyS5rrkhsyrlnBFwYbTEHPufGeIafG+dfav1r3vyH1PBoDhujGrbPWONr6XBpBfJOhbdzj0Q/Bx+C9d85Rk19b/WVa3WF43jX6kyBaa+R4AU0xs2VOhLLeaFpL3aamjZyyp+W1d8N19L09H6EFGKXq8ZiWeamlGJiUnFOaQdmBmgCYteZhAuv9w83VUOQ1gCA4gxE7LatCVwewvus0OHqbMZeTrJRlOt13rhhJorNpBRAlqKQK1ZB7XQSam4XM6B3TmngABVFQsVIkpzovWbRKUhFZigsL++B88CHG2OrMxGbMfhssECv25uTgg1s7+zH4MITNEGII6B16BzEO47gxpcwVjIk84Qlgf76QGILGIQY3DGEcBgMDpCGqGhKxcyy1piURUaMyJSZAbGoQsjI+ICMyrL14RIAOIXjajIHRbq6XWo05IDkkJsfOs/cUGT2jbwBAR20qsXOuaeZVaW5ze+BVREQQm7whIOJ28wwUsiZiROgcVdVS5LA/fPgx5aNMG8ivH+20pzLL9M6Pr1x8FYbXLnqoJ7J9sidTA52lSi2O3Dj45fYGyK6Pn27fXW/KvQfNqmCkoCdJPzx9ylKf5uk4HafpdLJlilCZ1SnoXBfQp1ztVILfLMs+H4/ytOixqAkxMSArsCixdqN0MTbDEDexYWUv40042+E1MO1lNniuKTXDv6715qLDObA92/T2n54PabFBV/Jew18876fNQGIPk3tuG6FbyQvDDuBeJFLaBDdRrSK5lNI0ZLs/0Azxel6wtvOsuQEVrW2zrE24slWXnFWVJacp1VIJuaaSiWqtzfFu2UVsMIB2N/oCR6S18tD8HQFEY0QUM1IktfM5vGx+MwAg8jHEAqY25zTn2dAqYFYVRB8HP2w5bBSDueh2V7yxaz8IMQ8Dem9MV7W+KUUAVfH+/uHh/r6xJez30/39nonB4TCOu6vd7np3dXNlQDdPt1c3V+N2PEwnQyaKAKEUmqe6f5oen44mQI44ssvq2kQiAkaHLoZxO1x7f4FqRHRDNEBywTMFRze78YvX17/8+Ve//PlXX719dXdzJSrb7Xi1271+dXc4nY7TVEqttbEmqkqtVUoppdSSa5MpalDoqpJrNTAkaMWgEFwMYbOJ280IYFVKo79raIgmftAItpx33vlGKx+Db4EkIouoKiCwiP63v/+91J6TJ2LnAraWjMa41+aGc41yZ4WHtZroCpZUBQDVBj/CRsgNF3tLB4siQkedo5gVgHm2yHC18YDYsHC1Nt2lWmojVDMfSIGqWpV2IGTHYKrq2TlASjktaZnm5XJevTDt7I1Z10426wm17lijQlvKtLa2nxXZkIlcpxchhOeYmhiZkHo2r0fi/Wb1HFcvcPYW6v5h7e3cFSfOu06jvgBqQTWiiVzwul2s+DQlgKoC1ipo0PeXpoIhtfS0wvrWrrNpz5F9S6lV0ZxKzhWrMJPmnE8TlIYTMiYCImBQRiQD6naHXEswgrUafyfHaOT7JAImjd4e2vbanjm34tTF4yh5Ph4+rogDRZB2CwwrgBhkaA4BgrVW937jYI1csKeh1KSaCNQiRUSqymy8oA8UhqZUHr2LPo6tjS74IY40jAhiDBhD8N73RCwiEkqmYuhwAPKgnmBk2rngxwFFTarmC1AjIn715atyGwfP2xB2m4EJSy0GSA155VxK6Xg4AoD3vs0u570PATvUcJUMduR9I2pAUKi1IMBmjN6T1oIAQ4g+hM566huYuwFXhHo4QUSNqMypSK0VV3IeU2tJQCAwRDUV1d9/2kwXuC1FI8bgSQRy1TTXp3uTo9RoPj+Gkmz6cPr47/14O2zf7m5/zmG3P3w6nT7N84OqsbvdXH1Z8x9d2EitZrYJ9mpnX14PaQjVTqnUGZaHT9/94b/tg59rPqap5llLrioV0IhRCqeF6z6daP8J34FhqdWKucpBfbTBkUcg9ujNSlXMAi8xHI7Qd9eaVnvcYs9eULNeX4IeTDe57BZS67oam+OK4KijX7DDbw3Oyx+ZWquPqqC0hp/zx60hbjteD2ihlaG6I3GuuPdvjHx5IdYJvjWXMi9LktI3dLVVjuE5vl7zdJ3dQlVrk+vplYc1eQbQ2opNjZDTtNRSDJsuFJEj9kyOyCF7Jk/UcQgN+gcGaIjaXAoFUiIR4QpkRg0QYJfOCgAcc6kpLwCJMKUlL7lKETVD4hg2V7vN3avd6y93r19vXt/GV7fh1S2T41cShu325pWLA3jXWkQJSU3f//ju/Y/vEKXW/Nu/+2/7xwkMRHReluM8Za3gMca4udlsrge/8UaWajlO6dPD8WE/ff/Dx/v7/cPjodbK3sUxsPNMPg5hHIMBAOjd9fDq9s1m2JyvAhF5YDNERnLkPd++2vzi27fffvP6zd1miCRSDMx7vr7abDbxVb2u9bJWr6UUqbXXSNRqrSmXUouKplrnnIpUtca47ocYx6ERxAczrVJyzbkWW3uPzKApEWPfBg0BfcPLbzbBD4gOyTnyKZfvfv/Ds2lnxy5Ah3cyMZNr4TsBQGONbZycSND4sJv/2trnmu1tRa7P8CnOuxZD9iK3iVVFKaz1eutrHQGBCFs/3jQv05zmVAhhRAZyYqjNQ2ACM2UmFiKH5FI+TdNx/gdM+/X1sLka+tJdweLnZHjPd9H6D2xltEZsgozA52xdc4IRkOA897tRhxZo9iR+R7y3rH4z3z18Pnv0ButvG+IFQJ5fifCnTLstcwaTNQVYu81Wa3mS2kBDF5+yAgUuvq0t6c6Q2LWnFIBYjUQJwAE5QIfkjBiQzy4PriVJhDWdgO30qN8wA1M0ArDm9nSh0bVaeL4QESkpI770eNa/EhoTeGJELNCqPXB+QOvO12BGrYWfHPrgGkgX2KPz5GOryntEtgpJslQsDhw37wUMiUDAyDkGBnZMQKCoSlKxEiFQSoBYnQNEalCDnC/Uegj/+tdvya7HEAbvBteKiJXZhXHw3hNRY4cwg97SBtAw1KuDrADQ1kYIwTuH2NRmi5mG4L1jQmPG4ENrEOhl0cbZDK3TsudGOgyMuAlCnmfO2cghkyE27ogfDnSGZKtBNahqVU1EpWpZIJ+M0MYBBqsuzaf3x/37Txg+uPHH4eod8rg/HOb5IHpCBPK7cfvu8eN3zkcpwsSO4un9Q8inHerMMJPOJZ/2Tz9+PznKklJZrCREsKaLSAyGhqzeG7OhmonVYqg08GCNx/05NY3ExI7BPVtEBBzQb6i1qTGeK1xr8NHqVE2eBwBXXCysPSvdgreYnJFaM0pnd1uz1B0f0zUKTcmUzPo++3wm55/aImwIc+tuQ5/yrTq+1twvonZE9q4Le1fJKeeSG/S3G9i2oFYXfuV/1B5xaZtZrR8NehICezdW29ucdyE4INSWt7hI+v+pr8uqBAHYGsH0JIJ2rA9c0gwAwPWbN3jlD8clTLnxlzcWbgUI4+bVmzdvvvzqq5998+rN3dXVuLsad5uRicUoxO24veEQkbl1EphKTsvDw4OaeebWx1hqrbWmnO8fH7/74fvhZky6xDh8+Pgp6zRs3fWr3Rhj3AyidjgdTtPEnje7UVTZsYseAE0RuTFDSxFd0jLNh1h3ATpnjXP81Re3AIQrDubbL1/97OvXr++2QyCAWur6HJu+C3MIz8UdMBPxKnre+FWt1lpVTLWoLO1ns9b7GrwLjYDTMZiK1iq1SFmXMwHgBe8fmiICOReDj8MwhjDQatrnJdEFLQoiEbtGStM505xDIgOzLpNtLVfP7Mm5HrmtPdVtEVnfjLHvNg126lzzAKw1PZkAQkUotfWO5bRkBFiWuixpXvK85CVVIhoEilipVkWriDNiJgYTaakFJ4LLIrlcYsk/Z6PbffWzEc/pXLBeM28LkRAR9YWpxb5fAjRR6IuqXtd2Wxcxrik4XFloYLVFl+bsxVo3BFzrVufwes0OIq5Z9LZun99tkBYBq6poKwkdGECv5tRamyZgTzAiWm9z7Rdma/hLiIS+zRJFNOfZMXtmz8yEnnoTL7fSAnZEVnuc/XL7ntKqBtRaGhFZSc2MELGDQtCsi5Y/3wUjBNd2m3Pg0gIcBvTIgf0YRnK05JxraVBm5x0So/VMZVtMCASNjB2J2TGz8+wCs2N2zgyr2GlapiktaV4gcdOhRnbMEmqt1XsfmvRW0/5DMgMRBaiqlnNpD7I9p1yfhQqI6J//5otNsM0wBqZmFWutPoTt1c716S6tNHV+0s36itQO6DNzjXavN8MgGJRammvMjpumMDEycfNqq3RduWbgW4qsGXgEM1NCQKZSasPcOsfOBeccMLWoXVVpVSEAAAUogqVqypqKSrG6gC2wvcU3V3S34ZHw073e73PBRWiP/oeqeDyVUiVE8wE5BB9+jJsBESUXMvYU5Wj1sYySbgJMDg65pEnuPxUGswQlkRTwTN4jsQFaVjWs4xZjJDYygbIIGbvIgk6b9GVrtzBAJO+ZHF8CbEaKOxo9O3Yt9dbTMQb4HLav7qR1AgZ7UTxvcDnqoU1bLpfu9Tl59LyuqGHP+oL9bK030Qw103VDPnvbZ+f9M8wAEfkQnPdMBGqSitZyxr62C2sNptozkAYrjhZbW00LyPrVt6xrg14RN1Bvo+hpO0dzlVzbS4laVbHvlYiKa2kMwQAVzJDMSHuTjJoRWhfMeLnfff2LX26CfPz4cJqWq+12HKKJimgRjXHz+osvv/jqZ199++3u5oq9dQonQESPFJgjEPe4wLSUepqmjx8+/vGPf9xuYoz+eDzN87ykPM3z+4/vycEspx/e/8EFP83L4XS/uXJfurvNsL19dQVg8+OpSr663Y67AanFCVBqzak6R+xBxVTkND+ZSLy+2t7dtasInn/z86+aL+kdj8F9+eb2my9fXe0GAKmSYS2y2AUWu+/jPYA0cqtHB8CALjgD11JFTYht9S6BuvJkS4ATmiNGpwzdBW0xJIFRJ2jBxvceGl0rk2utlQhc6svn0WusjK1uxx7bHJBSRUUqAnrP3gdyHojbAkG0ViDWFb59DvLOdp2ZRRVb4F8zILS4DozW7txZal2SznNeljIvZV4KMy9JUtRcJBfJtXol57tdIGJiD+hEUfXFdbxscncco29LthnStdCp0HS5WzXZ8GwBW3i+VsbOQTZAD3tXx+miFH5+2Vrg60CUs+W6OKN1EtjZiPe0+eoc9HSfygtwIEBT2Gm5aDG13tzWeiF7sqHrT684o4ti+3ph67QgaGUeR46R3apotfp13FGLZyd0jdxXZ7CfNyEgqJq0jj/V1UcyM1RAfVkUvbq6+fbbX7egqkct3aNBRgzI0bk4DOS4SK2qik0B11OjY1Az6dSwvXWxxSQNl+xaWwchsypUscbkXFtOmp3rjkvLXvfRa+HnPZDPG+NL7yzlaQUyI8Dr691uwCFEJjJRkSpSnfeb7QYJpVYzBgjN7LZ71Y5Yai2V2z1qaVBm1xtlzDy7lrlBIue5BXCI0KYrU+cYsAap7SFVmzdgpsht4REANzaedi2tZNGV7dWd56kqpGIioIaqKGKSURaSCetEC5l6mWdLBZNaxYq5AAIBDYGGEUNEJmNKlIqK2iIlQy6sJ6oHtJP6Klu0W0dXnl8HFyPxDsuiJUnvsAwEDpKYmPkIxKAZalHVRmTIHRkHKKqiikCE4AiA6XJ5EDpGT8Co3BIC2qdHM+TUlpf1qbu64C+WMCgqILZY1C7Mr50d7RcVZewr37qzi+cjrq79ObZee3NWT7tl3FRNNecX9BWMxIDO0Bl6RVBanQ+ktTul2fMWDBqZofb0Vqv64+rXAPTkw1o+pLVNeA20EQBROtMYVkW2tcCIiNqzZbh2uimgAhlCEc5Kgo58dMGxJ3aXPBzb66vbK18M3TDf3lxvN6OJ1Cq5VHZxs9v6IQBhrkVSKmXJeVFRMxYlEdI15AGw+XR4evj0n//Tf/j7v//tZgzDGL//7sdPn+73h6d5TuwQ2Qouj8ePIXoDKLKMO7fZxmEY3QAlZcUErvgBSLDB06pUQGGvPvgwIFNgpMGNo/M+PAe7wftf/fLb1Y6R93y9HW6vNzF4BW3eyMX06fGedfwmdE51aKmWFasBuBp/tBWGZACmdhEQ9nodkTNb4zF0iEyNBballsjR+Tt2YRvsWyJf2iciZhcagI5btbjnrsAMiVwr6TUWk2d342IOW88yvsjHdxdmRXypylnwVwFqtZwlZ2HiWk2qliKtQCEKKdcl5cXjMnBKznts6jhqRty4NTebTUqWTvWMJf+sr92sQQvwOZHVgP2GTY2vrYS+ZqzbY+3xMz47pGa9gxxVoSe8Oo7VWtV+XdT91wDPgcGLxX6BbWtpLQNZIe7YV6pqfWnaHbO11kc5uwP9BIiRgVYr1SrhzeR34vqeAWw+2GrdCYEYnacejSM2Vg4zOPf4rm2+fSPk9dmeLV+rh7WablM/byWZFlVoJyh6voq7u9d3N2+e394zlYCADOiJAjF7T8xrrwJ21EPDKbWO34brM1NpwP+2nXEjBSEmQNLGDJNLLg2FgA0YcZ6cPXN74btgB4X0u9Ge/Vq+QTrK44qiQ8SNjxsHTI6RwaGRCgsxErCJSmNFbS0g7ADXXV6VscOce62jZ42rwtoCvYYBqnhGfqlp82DUtNQCZswrFLxNQVsvkqlVBM7DzHLKS0qlIXzk5rxGVC1la6loQ1A1rSQLLwc8MugsPsKCoM41ZLl3GAL7GMLI4wjRG4NgVclWZkwIS7HlIOWp5r3VZFRhY/Dauzfb8LO7eHXjhsBpzumURQqg0ugguqxUFMSkVpkPdcrW1pdj9MyOGA0bigiBmVDRXswqAABn4ESp4dbgOZSy82JpCae1VeSz6jB0AISBtpnVrPHz3O4T+zwBALAX3dekOALSKlxzEd9bF8hufI3noiA0GQu5xAC3vYYN2TAYRWOHvf4FXbjowptb0QZrthHOswnXDHB7KRq2UBu1y09wdxSA1uOcXQM8L+4WKOL51KCZdgS0qi4LKkbnRz94H5jdRekCwhDH7TButwo4bsZhGEQqliIAgJBq2h+fFAEJUzrO0/E0n3IqtVpOmrIWqWLSIqzj4fDw6ePvfvdfv/vjH0J0Qwyn47zfnw6HY84ZGYCtwnSa47AZQgzswmYTQxy990C5wgxcyFesFaCqaal5yckMmIg9DmPYbIbNMGzCdvSbYfsMMg3e/+2vf+EbaxtTKxdS63KHxlZC58fRkmfrPehhG0G7vW0D7qBkXO9zt/9tnvbU7aViFQD0PjfillRxTUuMkHGtlxrQiwJPCxtfhiXEznlrzDGEDJ07BNSwoYOYHbIzwFY+oHOTNqxglbXK3toAcQ0szFZZsJY6QlgLVlBVq1gVUGnhJ2jVxqwNpimVxdPsbFk4ZR8yERkaiCozDeOw2+1EdZYJLmRdX5j24z6//2ENwtdQeW0vtdWFOjv4z6Wll049wMudwmBFvcL6uNothdUX7o8YLpe6wfnTnw97djW6os6ax5uOl8AtEr42XFksqLEWQUvH9XXIrE0ZGM897GvWEdbL6pdLZ0tWmsRwo93QFV1syMYka4y++qSrZ4DPtnm9L2qkwl0gpgc7oEgGpBeFOGZm7z4PiHttBAjIkLQ1zOK61TXfzFpL+tnPWjEEAM3lJRUEbImCtp5UQU06AAigceEboDbiuXUzfLE4cQ2C10ytrQmzJZ0unhncn/wpAzVUce8ERSRwDtRAKltLnBEyP79LW0Vf3bkYjOcJcZaRb3Ott0mupl2tPWEzqJXAjIjAzIx6YgAQzIjBcUuWduh3SxnkAqVQrSyKpT7f/Dhev/32X7TLLllr1q2n7cC4wXkECcbeKkNFrAqGUBnBkUVvnowgg5EJgCpaZSvB8kYzaGWT0awCGARFRPKvXL3yaWD1VLEWKqJioBQcBK6K0jQRqgIIew1F0NCGIfsI7EGxhGoCBNTUISVenee1ATy9f0pTOtfXz2mxc4gMzWc658Rf2vVzir1F4L1dvb+/c0XrijUCOFfo173vnLEkes7a4/N5rDvg5aeaNla8dEEtkvMP3/0wHefdsPvy1VfbYdfkGC4isJ8uncvfnz/5IsfQ9zJaT8kMgKxn+J/3JWumBZ4LD+egph15zQD2XnYRMvTOXV3fquGS62WC8P5xKUX2h5oSKJTj3MDi0rrC3HIKRwkPM6DlvOS0pLyUIiJai5UiVVVN2q69LMuSwYer27uv2ZHz7KNsduV2SSIyjOM4DnHkEF2I3gfvfPA+eB+ZGcycc1c7cu5qtyutqNzg6mBAzDGGRpYSQ4h+CBzogmhWRN5/vHfNvOJF7qKHLeddcN1EEM8bf88LrW7WOVRYH8ezV9/MhFqP7Neb2N5GBLwGY40EZ02qAF3CIdpBzpYlpVTrc2S4GfnVLawUiU1oANRIlc3onNvrKwAVSQgNSdv5NcuNqNytQm2VnUbeICwKEqGoq47FsxCRo6SS5nl+wuM8exFLqaQymy1MFRFNclrcwZzpU8rjMDjvG8UPSNVabFmWeV6Wckn5APjv/t2/+5PT/y/jL+Mv4y/jL+Mv4y/jf46D/vGX/GX8Zfxl/GX8Zfxl/GX8z2f8xbT/Zfxl/GX8Zfxl/GX8/9X4TP+4/ccQjKj3jF4gPi4KnPDZj//wOBeW/snv+Ccc0C5+VFVdKf4R0Xt/UWc71xCfYf3P+KBnWONaAlzfaM8wflxpEHQF9rwo43W8kdnFab0Ya93+GSbaz8bODQV9XJ55K8a/fMHaG/CMCVi/nRGOrXj4fKp/8ozW4uLFOZ7/8Gff8icO8tNj9BoZ83MvNa+AKfjpy//sTz89hT9TOf2T4wIb9eLb+Qxfvvw88+3lnxuFRj8kUVO++3Of9mdP5ad//gmC/M+On1a6L3/9cvpcvPLiNjaUxYVCTJMe/9NHhRX6Yp/99vPjrv/6p13FnzyxP/37f2ioiq0X0nCXf66c/o8N+4fP+/Kwf/Kl/1M/tx8v52ciJHaOEFdSb0Bs+FW82JzOeIXLGvTLg8Lzo9CO0W5PfiUqWAFnF4CvM+7BGrK29UZ9dtxntNPlnOqfaS+eo10A13tB+7kavqKsLkE7lzcZ1v0QV7QrNlWNfsyfPIQO9VC7PBI+l+vbC84r5Awa6TV+u2h7Z7oMcVc8D/yJDf0ZONxwFi8W4MXrLw7xckt53oDOz+L5zet9vsC09W6RZ/J2uIAVPwNioD/EC7rGF6Z9grCoucO7naVf/e3/5tu/+V/G12/d7qqdKT6f0QqfwvVGwcX3M6iro1St484Qzh0APx3Wv6OdqSL7TUB7nkR2CbURU1GRlGtKf/i7//hf/v3/ox1qHMd/+2//7TiO68PVXJc5HU/zwzTdI6L3Q5rT8TDllHNKj4/7+4eHDx/vH58OIYRxHHwkdLLkQ6k5uA2BT6nsD6d379/vjwcg9RE3O+8Ya9GSJM1yPMyP++MylZLUilkFxAapRWK+ut7cvtpc3cbttTPCqrrfL/un5fi0zMciXWTLnOP/0//x/3x7c9su5He/++1/+o//z6Yp0REaImbae5HRWvOuY+dCvL6++eZn397c3CHxssxPD5+m06GWpFLMpHchGpjiszMDDZQI2lSuVifp/P9GmtmfQtsCzBqKxQxEnzcHAyRy6AKxY+a3X3z13/2r/6EvG6Z//b/6m80YWk8vtZbiBndxRIjQxCTWXjRcgX2wNjJ3AGZDNK6gpcvV1ufaC9hN37+qaSkl59Ig28ytN8I1yVpY8Z4iUqrklEupjTSwYe//r/+3//Dp/tg+59VXX/3Nv/5f9wZ6alRVtIJqzhDYNotfgKvwBVAMteupQEPeNoW7LtFysZJ6O/bZ/wRQE1GrqiJW+xcUtaxa1ApANRREBW5CpWhW85ynA5weh3f/+by5/+t/8b+7ubpT6BqNBnDWQ+v38oyY1z5JzpizMxLqubUMVk23zvOEtuKbXgDhzl0w64JfXWm43PbOPvDzlo52vpP/5bf/9/v779uLv/rqq3/zb/7Nxf74D9jqC2vz7MRZrVJrzTk3SPM6Mxw+zyAwA1mHmjKxa63wnRPp+eT/CaNvw4+Pj//j//h/KaUjf/+3//v/w5u3X/3ht39894f3+VS2280//1/81Zc/fy1ap2l+uD/kVEJw2+1wc3u93Y5DjMy8Gs9+BqJSRWutKdf7T+njp3Q66uFQPn748cOHd4/3n6bTMXgeN+Pt7Svv4vHxeP/x/v27758eH3Ipd69f/+2//Bff/vznt69fhRBUpD2wkvI8zbWImblGz6yNC7bUWhU/GD30W6wSp0diQsdoZrXYfILpyFYcmw/RxdGPt35z64eNi6PzntkTOUAuRadZ333M909SMokAmFzduF/++vrLrzbbq+AJJdXeGUNkjqtprvn9h3ffv/sDoowbz4xIGLabuL2K44ZdmI/TdDpJLVrrMuU56ZO4mQcar7LUx+9/Nz98oJI9wt/+6tduDUUSHhbbT/M0TdOypJxzrVVNnLcYebfbXO1211fXu80u+i1BrJlqBTHJdU7pVOosNZVSSy5PT8eH+4Ohee8aORh1g03e+9dvXr16fRuHgASH/eF4OKU5AeB2u7u+vrl7/SqEMJ2W+w/33/3uux++/+HDu4/LvCDh3Zu7r7/95upuF8dQpczzMk3zPKUvb7/55Rd/fZ5tL0x7FUlFLCfFRAgxxM32yl/drqa9755nRPyzOX9GSgNgl0lcZXgaI5h1nOKzY3A54VejjWfTbqvXcNbkghVe3vnfFVRM67xUZO/8+XiIeHNzs9lszFS0lJJ0WTTlqnOxiYAYQKEYZrGlSqq6iOaquUr25gBNtFjNuc5Fkhog+JTKtBxP82FajuwBmHItaigFctaUZFnSPC9pqVqxmXYARTBidgY5p2kC8kmZyaMipJpSXeY8H+dccpWqCOZd0IvoChGRycQM+/YpUqUW6LfGCIwQicnnQGD7zWgqRJxTOu0f5/kkJakWM1kTCwDafe5zmkK7bFZrN+hMBk1pt0kBrd1RjQvQ2rNqJmHVFcFG/8Rm1PQo+EWhJwaO0REaoTVJP27SYY0coNMA9FZ5xAbuN1ilG9asx6WeyBpJA8LKgLTC9i82ZdWqUiuVwE2Op5l259g3HwLMVs7RUmv2JCLdtINp65pbB7Hz48YxszszJ5OjlVy/N1zpc1rlwrSfvXPrvhQoNPFBq2ooSq0Lst3T1tH7eZbCmp79C7teNYuxKmmLenBVEyQEQFUyQ16AXvCzeu9jjNJ0UZABVqg82mrZe9jRlY/NLgx7P6t2cY3v8QySNzNdSRVXG3pe5RfdaOf5BwCrYMuzcht2He/+WjTr1ClG/LxfOedub29XuPI/mjvAs2lvp6mqpfG01WpmzOy9b7QNl+6CGTTzX0VUxTsfY7ygOzwf/J8y7Ow9X/52s91e31wP4+hdKGiMfhw311c3gBLjoMJpySHwdre5u7vZbjcxBiY6m/b22Y1Iv5SyLCUty+HIx8OSliUlqUWZ/BA2zrN3kTCYcSmwzHI65tMpm4EKI0SkAXEA8AZ19XvRTMGqqZqwout81RlrRXTP6ogI4J+5htVMQKvVzFYcgFPyFgJaIPJNaMUF5zyRA2BnWlkQVAVESbukkXcuhDiMYwxMwsWKnU17MaXC3ntYcfjYtEKZOLCPwYdYa3U5I5qAMQKoVsCEjvyYsZyqnuYZ0xQBzBSgr5GqJcuS6ryUeclzSrm2VgUwZFeExYJhARJySqAo1qjhjVAMFM1AUUShlJqWPBETB0R25KBH4SogoKjkiAO37VOsFsmqFiSIFSMFBmQz1Gol5zTPp9NpQoK48SlPQ/WsVrUUXXKdlzIX+fPyMDkv87RgnpVLLVNJk0khtLZ20QAI0ax1CQFA13W11brb51E7rSrvCIp63oFpdQaeF+RF1N5DRHvevqGbE4RudlRacw+iQS06JUsvuCyg52rKko774/2H+3fvPn6/P31I6ckxD2EjxZa5LPO8zMs8p1NKuSaFRmPiSplSnRaZiiSEquKWuRyPU0oJTIML0TuHRkYA7BGVbHC8C7Rx4CmAEYiJVNUaQgghGopBTqnoKcUNc6QQbbvjml0tYiZm4NgPMVymaHZXN9/8/Fe1FqlFRaXWvEw5zVprI4U3lZZXqiWfjk8/fFc/fXxPxGYmtahU0GqmTdHgnN/r+yueH4atHT3Q9K6bZJJRTxKdOxGxUUIQXhAsty5SRiLnvAsxjuOw2ex2N5fPopZcCxAaY1tka9LB0JSMGnWaqDKAIgEaIF0k2Tpbkq5x3XlWILSTvwjc20WqqdRzBxEQdWZIOjOSrGF2uyeiWmslAm6ZBGoiDy8oQVU1lVJESbR1NjIRk3byIkDsE3f1olocDAAAvS+yO092Ydqbuneb1J3llQEa4xl3BURC7J6uGSmBMIhYFaikueqiSqKoCgqmCAYKrXewckm+JpULHnyAVKcpB7VqiEwbomBGawB9uSS7ilHz7bDd7Bcxckv0n71t0/6HCxMO53vx4perRe9P8eIvF27BRcLXAOgnBvzCBv8DxtVefnRL0mittZSiqoh4Scf0MmUNjZo6pVRqNVUcMMb4WSr1nzx6BvWz91JjwWoMzqql1lrFzGL0ALhsCpPznsdhiDE65wChk+2f7197VGo9I6RaS3l6+Pjuux8Ph4eS5+vdOL6+bZsyMedcU05LXkrNiLjdbq+ur2McAGjJNVfVWkGNAGsuORWpYqoVBbHkklPT1ag17kpcQyoiHGMwBCHUakZojd3PlBkaFzk3970nHZnRE5IZEQCBAppSJ4BEAHOgaIpmiEpk7Jr0GBIqERmQsiGJgprmIobsCMVArLXwOkAHxMi+rQ6rpUBc2LPbZCuz2Gma7PSQoZEo9FFKmfOccpenKbW2VmI0AuNGe9RTVFjbLQdi770z71zM2XJGBKxVGzvIEIfbm9vNbowximhONaWiBkyB3eDdAACEkynXClI1pbKkssy5Sde04qb3zgfnMpu11teqms0QoCJK/3q5Pl6Y9jTPx8OBZS5BD4/39x9/8HevwvVtE2LDlUAALpfhRVCCa+t6YxnCtUEWm55pT+EZgK7h1bru7LyALzaT1Rk/JyRbANGpIg1a1k4UsAq+dITNtEpe0ulx//7Hj9/98P4P373/7jjd1zp5dmPYgpFUzSkty9I8tNMyL7k4F5idWKlSq0iuJaWSkqW5LHNKJQOYYxdDHAOHMATaMgwgoRZLqRC5GAYCMjWpRSQ3y3ecDsfTg/IMIXEQ9OKcMJE2b1jFzByTc3y56sfN9s3br0VKrUVVTTTNU1pOJScpWUqRWqQJv5iC2bzMS1r6jtcjbEXrTPvtxuBKo/ssi3tpgbrjRUZd7wiJgFyLl8/Ue0TMzjvvvY/eB2JHTXPF+zDEOAxE/vJxYFukzbMGavIriIBA2CbDZerHELubeHGC2DMV62TrCSRo0TyuDiSgtTKNSG0SG03hwTdOoZVZ+DwTn4sTBmBt72kfYY3//+JxWOtwVcNmmqH5OdKlH/FMl3WuYHa/tl1nLw41067n3DW0ePvMcA6mDODIwDVeYkRq2Wlb09VwTmwYIAOyAT1/GSkgGJl4EEOpKBU1X1zGh0/f74+f1CqxHzevxnjtw5bYm9mF9XyeNN1bN0Q8+9vnAlkv4yt0jsqLW3a2qeeDrJvPT8zi5Y3GNQRYs/3P8/OfEJ1/Nl68fo3XpQXrLXpu+6Zzn8Xr/fWdmFrqGcrz/+P4aQ7fMXvvwuBD9EBLVa1VTY3ZxYHHcWwJrRCic24VWejJs9UZw56atzXZIjWnOS1HAtlEtxtjDDGVnGsptaYkIpWY4jg672+ub+7uXg3jhshJVQGVUsGMEFsdQtrENTWAkktJJeWcc3bD5T1B51zj1QUmFQbH4B0AgAPz3jyrY2M2ZiU2ImNqbLxACKSKIGhKps2NQ1BEBRREblojZF0Bm0kUoKJ2/dbqKpIjhwSGWkyyCCoaBhfYB3NeTwtTQWMjbzyYspIXJACQpjqwjlLLsswppZxzybmUAobMaHq269D0gEvJAFKqETqPyNy2VTbjkmmtmLPzIW6GzWYbh1hyBchVAMSIg3ODcwOAMQciB4CimkqZ5mWYpkaZhIxhCMNmGMex5JyySinzNPvICmKgueSSSy3lsyn6wrTP87x/fBzckk0//PBHxdHfvB3vvhjG0Tl3xnKshc31kXat5I6T6CEeaGezADuLM1M346sI9Dl0b1siNHNkSH1Vw1lYZd0BEYCRgKGRjxCiEhd6sSABQLQsKT3s3//w/ve//+633//4xx8/vV/SCbR6FwY/e3ZMJFqLlFNaDsdlf1qWU6lFSy5xZAqM5kRgfzgd9kvJtZSqUn3wxDyE7c3V9avb169vv7zdvbna3AQ/MrFzwQePQD1slJxyneflw8f37z++K3CqOC3lac77JU+zWwgIEJoKOBp+tuXFONw6pyramAABS045p5yWnFPJqZRUS5GSpVatjZaw06SCtfsv3SlanaVnsWkEagn3Nf5d/6NNFJVdcHFwYeAw+BC88yGEEGMI0TkfQgxDY7AYmJ0BnLnIAXFZ0sPjBeWh4+AZ0ZiA6UIMkLGJ5yGuXsQ5E43YeUIu9EIBkAifMw6rXUcgW+eSKORcaxUwZXZhiL6JiACsG32bK9QC7EaOBm2Ld8457nG10XNyv7+N2LmWTq9VqzTyzJ4FbCyl7SZ2hE4vJffV0XIDsiqT9UJG541BWLNULfW1Cpit9r9b2gaoAVUQMSlWSy1Fikht5Efa1wgBBLItG0dUwVTg/ZojM7C/+/t/L1pEJcbxzdtv37z+9u7u62G86g5zO7PncnkDwED3ds5Fc2h6cM3An2ERn9n18555zspd3s/2vR/uHFnjmTnq7H2BgZl+FpWcT+9F/u/yBJ4RcLhSHNYqtZZSiog2duEWrDPTWsex83tXuy5mze1z3rtzxuflx/0Th11878M5HmLc7rbbq+3T/dzpNrVpR+EwhDb5ne85nBfQtItd+HxPW0zpHG030bshOCqpztP8dHg6zROQa9v+dnflmAnx6urm9tWrzWbnnAfANveaLwdIyIxmnUdzzfqJSClZPnN3ut+JaIzMEJyaF0RiNO/Ve/CMgdST90iOkBtsjwzMHCuhoAmoATWaG0AyJDVUQ0OgTtSO1GQDwERqzlk0Ow/BArNDI8u1QsIMbLhzw2YcGADmfFok1BA4EHpl8sMu7q6RamhUZOuopZn2nFMqKZVcEQgcK6NZn5lVJOesYmBUizn27MB5AhQkBTBtuBgFREbmlU2nwd+IkAyRKTBH5oBg3nsfPHu2Yrnk03Riz1XrMET0OO6G3c3udDzmnHIuaclP90+1lmEegEBUU0ppKeX6z5t2yTkvcw5lBk3pw1z91c/+6uqLr1WuY4xqLf5oaSVtmpgNs3oOrxDbZdVaSy3FVAHMEQfvr7bb3WYTQvArmei6gZ8X4jotuyN6/sNz4Z1aBASraTeoSER0uWUYWMrHqsvH++/ff/zDh/vvHvbvT/PTkhYtGrhWD0P0MbBoXUo+TqeHw/F0THlWUyQkI8dmqZZlqafDcnyaVJWIN5vt7e3tN19+9cXbt69vX726e/369sub3d1u3EU/OO7xG7Rik4poXZZ8mpbNOO62G+MKvk7p8bQ8HqfHp/3Djx8/piTOMWBDy71c8+zYOTU105ZNlrqpteSS11xRkVKk1QxLLjn37zVrLVqrSlER01UkR7U9kYaEOBNnPu+qiEDETNvNbnt9t72+HbZXLg4+xOBDCMH74JzDRhXtnXPeO28AUquagmnfOF9yfTtCZiQERmhQOaIzPyOuEiXdjK8bxBph94eLz45lL+jh+d0I3ZWWqrWKVGuLisk55x075DVbvm5/0O163/2pizcyE63syKj2MmzvZwWo3edUNVMBUEQ5Jw9wVS1a32TQyG3BRE3OyeszrfLqK69fa37DDEyVRZq/0+JNNVEQgSpWREvRXGVRyWrVoBpIC97IkMyzeVUlVbpIs5t99/1/O52eqkqM49N+P88LEt8RsR9aNWedDnZxCeeF2MGCdk6kXVoqPL++O/Hn+7ce9HNb2J/mOV5YXQFspKO4Ru8/+ah/dNiLiwZVla5fIGZGhE1KocHi1kkFqz/QA/xa5ez5heCdc825/KefxmeX+9NLaAi+cRw2240PoWZRtSZJyIzMjTG5RUvWpXX7oV4c8jMlDB/cuImooiLH4+npcT+lqUp1kVrRfRhYtjsm2my2u6urECMRG0DrN1orLo2EFBRUVGqpy7LM8+l4OkzTcdjhFTwX21tVihgByUxFuDJSg8g6BsfiqBISozEJAoIyIFpDbJwrO6pq3IWm0AxFTVTPTJ+qFaSVZEVFpBZVMVEEICBU0yxFkiYNzjkf2MgxNlWvaDwimAoiXF/fBP0G83WwShdglKYjJVVqrVJFRRBAsfO/9onR6LG1gpEIIkitGYAAtVYp7auISI9ORWopGaHBFKpUMWOVhp0BIkCiJjuGDkVlSQscUFQMdwRIDn30cYg+eESsuU7H2cCKKjk2sC5U/iJz/dK0gylKLVVOVvOUDjO+/v6767dfpnQXh6H5aOwcgNVS0rJM0ymnJFJhbXBCBCml5Lws8zLPVcRMvfObcfz5z372y2+/fX33atz5hq+mHrEgnIFynTxauxPRBKwAepnvWWmStMsJrFmEy8Sp6Wm6n/Ph/cfff7z/7jQ/ii3kBbPVKijmAMwbolQtU5r3p8PDfr+cihYKLlat05x0KankaU7zseRFHdFmu/3q9Ve/+MUv/tlvfvPtN9/cXt9uN7voRya3amsWTcuKL+9zVcRAdYzD67vX49WwvR4Vcsqnx/2HH378rqT/8OHHgyp2DRsQu1z4K6TIABt3InlstOeq4xnD3Ajpay2l5JxTTqnkVHOqJdWcSs5Sci1Vaqml1FLNpJVIepr3TMmMgGjk2blw/ertl9/84s0XX13fvnIusG9KMYSAbb+rnSlcUso552VZalpqzXlZUlrYx+3N6+frQGPsES6vrMq0Gm9adUV7gL5CqdZf4mraV5O/WoKzaQdAU5NalyWXUs2MsPlCDhRElBpIgPrHQo/J1Kw2O9Xl+9od6UZMyT7fw5s5JkY2MMVqWhuuU8Uuih6tA2CtOlvTCTlHPR0mukqy9GexUkwYAgEKQiXM3Ll5W8a+ilXVKtCA8f27WgETs/NKAUJg8wQGqlCr5qrl0qJ8+vju/uF9rcouPD7u52mJceNCvL5+xTxAo8zEMxjhZULswlqf7w6uIfvZtenewMrrv760v94u3wlrNQZgvQBoBn316FpGRsH+AbuOl0f97DfneF2kl7FbiruZ9rMQzDlF0L43101VzAyRnHMhhDN+/s+fyT9l/MS/IYxD2GzGEILWrArSfPHVtzy7rdwaMF9EMj3RAWv9QhGAKEQfh7h/eHi6f/jw4f5wmIbBb7bjZrsbxiumEdE1LUTnvY8DsyNEbbZV1sQVAKIZqJjkkpY5Hff7p/3j/vB0Oh2u7q4Brp4vqvGuOwdUVVURiymZAVJDzwqiYhe3BmiaXkamKqBaW3pSpamVkDVMmqAWUTRumRcVMZGiVVRrASkggqAMQGooaqgGVYoAFHUeohACE+VSDTEgbEwkz8459+qV3m4YhLXS0we4kDxYOZit5d4QrCn/4iWQWwwACQiQEJpAezXQnMqyNDBjKVUNQKqkJYFp4qUWLVmlGJHPKc9zIiLnQM2QiTyzZ81SapXjSaQig3euNgkJRw3A23p5kAnZcwCkLln7md/80rSrSqmTlmolzdWV/fff/4G3283VtQ+h9sQUdy8lpXk65ZybaV/3TlCRWkvOKedcalVTQo4xLtOppDR9PX3x9u04bEIIatSEJ9dSkZ1RSAZwTlDjuqX21GUH69maZuus1ZcX8f7Td3Paf3z4/uHw4XB6WtIsUk1VxQRbsc1y1jktx9PpOE2nZS5FSR2gImqpacnzPOeUJNC4vbu9u7l58/rVV1989fUXX357/fYOYzgs8rTsRUsuS15yS43X2sJkOQPRgcyotV5trjbb660LjGglO9It25ZsNGGppiKg1S72LwRoxeg1iO2DmW1tsFqjTxORKqWFzLWUWnItuaQl527ga6kll5KzqYBK2wesBTEq1iRQwQjNKQI69tH5wbEHgOaItlxNLeVchsq5LCmntCzzXFKqrUBQ6+7m7tK0N3FI6kINq7x3A+Q9kzWflbM+G6stP/9x/WcjpTfDWmSaltNpOR2nWsVR13ht8Vj/6gJ9jp1rknZrUpxoFbjrSW81IjBrcsLPq6WKnKapzXQREDFVbCqkLdq4aO2oq7RUm91KqGjG0FVUnpPyLTBpuDdoaPNe1Lc17Ws9v2cNIiSGYqSAAusPdE5rrUoUaLnUqSaen8rTfZ5Ol7HiPE3Hw7EUBaRlzgC8u37t/ODYXV2fFc/OXvdFocg6ir4LD/1krOn0nnDr2fvn1PU58r+8syswd/3lc2rFzucAq9D5P2zdL5/XGv6vNZfWvwbQ8kbURJ3aZISLUP2zd6l2+Ve3qjv+5IP+0XF5znaGG55HS6ORcy74XhgwWMsx3ZESUQAruTAh0aqDs6Yz+22E5+BXVVMqp9P09HR42h9qleDduBl3V7vN7ioOV0QRwKmIARAzO9/UyahBOFRUWsHJADSnNM/TdJym47R/enraP07TaUlLKePlhZT2BkVVrAZFNJVC2CTTHGDlddqfcRRmJoKmplVAKpiYARi1y1hFeRXUkAnN1KrknEqqLZRXjY4NzBORmZYCagosAqog3rd4BomWUgBpIECoqR4rxjhEGnY+BDajw/3ZtBO1hKR4V9UpCKwCMmamtZScFgIzUe/Ec2CKgCBVkACs6bugSmtYbsgxlVozGiJJ0VpUqxHq6XQMT4+1Jh84laWKIJJz3hRNS8lZagFQxyxF5tPcOngBwFRL1hYqeQnsHVInvb98HC9Mu4qWUmuqoFXFPNQ//vD9qRTvIxBXqabW86gALVpUFVkri4TIvP4ZzABEpYiKCAAu8/y0P9w/Pv7iePzZN9+8ef2Gzo42AvYGol7cW0tw3Wlf/3WRLIO191a0lmIXVR8R+cP3/zXV4/3+/eH0eDgeU84KWmvL9qtqzUWL5MM07w/TaZ5zrWpICETg2HKtKaXTPmmlL15/8bOvf/brX/3yZ19+dT1uRyScp+n97z5+vJ+eno7H43E+HZZ5LjUXzarFtBhUAAEwIkM2YkQCIheDH+JmM242m3EzKth8RJANqFfBWivoy3wdds3prp79XO08G8C+AxMBMztzFqOINjENaXY+p5KXWkWqlFJLKVarajWpKiWnHuWXlKUkkUpglGWa0mF/ZLqfT0upqZbSU1Qll1JKSbmUXErKNbW28ZJrKVILEznvyF/0IsJaXyfoRXY8S9ufc/IXofuFEb805PCsodTDdyIGwFr1NOX37x/vPz0dD5OKjD54x2uS3xoIgB07750PPsbNdhy3IzsCAsAmME2OyQBMFYBUDRrc73Lnyvnx4QF6JokBmNgzh1bToLW5W1fAeI/IERjMmbE1wK+irupmqqpiK1lJbzsEyKJZLBtmhapW1RrxgREBOSCH5IGdkQNyQKyNrAKA0LgpR6steYH5Afcfy8N7LRlceF7mClJBaoMCnYDeh+G3xGGz28UhjMPIxGYKKybuRZRuZwPbdEzPsJj+MrqIIQ3s5ft/YpltDdVXo28rerabdrtA8Px/MZ4ttJlJLx2qmVHXz26dl3gO68/fL9/VUveIuMb3jOdmr8+TBP/YCTVcZZshL+tuYlCs6yOd6/h9GkGPmqWKKqTcZMQbM8mLCsbq+TS7DCXr09Pxx/efDo9PeUnb3Wa72cQhxHHww9b5ASyYkRIDGBK5lrJaQyxQk1pFKpgCyDSdDoenw9PhsD8eDofT6SiNaeNiqEGqLRXW1eZTLmlJ1OgYBE3Y+QqDggqYtLWu0rpTTEXAClqlJslshFbROm5tVblXk1LzvMwnUTMkBt3GYEDRMarUtCg5Qa7VRLVUV4qbFybiakhIo4NghaUmyDreuDgM2xuHOONzyYrZBR+hCfcpkuVapGU0zSTnxazknENIgx9i3GwGh4St6ZWQm9gdk1/VY6Gl60QU0ar0iiGY7vdPAjbNYxy9gagVAHQ+EDhQyMuyLLmkBIBSJC9lOS6l1J7AK1VUxTSIhDH64J1nfEG889K0DzFeXd2gVQAFQMfOeZaSwAyRSq2i2vIb0TvvOIZg0PFBKsKE3rWKc090iWoqNeWSSk0iP376pIhVNQ7x+voqhIjU0ExA+ILJqLnrDbTzbNcv6n3r6jKVqjlrfTbtqvLHd78rOh2Xx/3xcDjOpVSAtq+CkOS6qBpQbcnkhpRRITTNJZeSHPHV5mrr7gJvvv3yZ9++/fKL3c1NUTp8ysdTfXwoTw/L48N83E/T6bhMh7RMpSaxZJAQKkAFLIgFqSgUA+h0LYyOY4zDMG62O+fDfj4dD7NkW2vNL7aDNRX9vIusdv2z2BZwbQ6HlrwVaSbYlRxiBNs2uVpV6B1WKlpLrWWZptM0zadpnqac5poTgCK7JZWH+4d5Wpg556Xk1Ja61iJSqxQRVQMxqGariKeYqveegQxfTLIeNyMw4aXU4bnWDitqjtYK+/qXc9z+jOhvDqoZ5iLTnD9+2r/78f6P372///SYl+KJ7na7zRB8604H7SiwFrh753zY7Da766txOwxjHMYQo2ciagiSc5UHwF7SMEuV+TSJaJVqRkhuiGOMo2vZAWpzWPt3UEZgNEZgAG7AWQAGo3UzNgXR1vGDaqoKRWqpdT/npyWlakUoGxYjNVJAU7aWzOSGlNA1MkZsyVNAbL3tqiCCRTAXzgWl6oVpb9X63hCk5XA4/PD9H0McX716PcbIr96McVyb4f4hg4prihwvrNyK8uqm5nmx/iSNfxHD29lE4bOFxbWaD3CO/f+hnLz9NAl/jtfP9fLzOC82+1PHXOs1L0L2y7fghQfyk9P4E0dbT0ZUtZQXvYhFtIi2fEK7RDWTlfCg1JpymZfSshvMFGMwbuHgc5XDwAzEOo9XlVpNlRA347gZwmYYYgxqWkoVWFgoBs/sEHvKoItVm5mKlJLT0lDiteZa0+l03O+fptNpOc2lChOFEBqW9vIaZ1FFE1GTarmUXLUIM7ARVqtW65KLT4QMZsxMQFZVq5pAzopWohMGNEIC81xB5rIAgFkBdYQq0vqz51MVNUAtaROcAbpzLU3VEJtRYVNqspUADr0nZgK1ikUQpEqkuhlMPdJy8dioP3FW76x6kNb9ay1rAwAiiihEUlndSlCKSI6c88ExkNWacfE1uZJd5lX+87m2ZaYqOSecjga1iGeHDVQYfERPjp3WliU1UCB0jtEHc76SWwBRVa0apJaM5NaG+9nqeGHad1dXXxp7RrdWRL1zIYQQByTOpdYqCOYd7zbDMA4xDui8GrZaLxMOvuGWenG21rrkclrycUpPh9PxNH/4dC8iX7x987NvvnLeO3R6oV8L3UdfA7P1X/YyWd98KITW5iHyEvcvKt+//77aUnSZpuV4KrW0RUFMaFJqTY6JGWoPmczUWuv4NKfR+9vr6+urm6vx9d329Vc3tzfOy8Pj8ePvph/elft7mk5cskNzICNkKVlLxqps1ogRK5IQJkBoWLxUcqtMW09jIiKzJ+eVWNBqzd45BGth6Ocbw4ppP9t1AOyckB2S1pLPDRDEZlZymWBqcaF3LgbnffA+EDlE7tuH1FrK8Xja7w/7w/FwOKblVNIspZiUWu3x/r6lklJeas7aSfE62AWJ2AXyEX1gHxobQ6vbhTj4+CJTR9hL7GcB+E4huabjn632uSKOiEBndHy/BdAdAgASscNp+eH9w3/8u9//3d9/94fv3j89HjzgzXb85s2bu6vdJrRewt7s1BOciEg4bja7q6vbV7d3b+5ev7kb44aR6Ez/1sV/0dYEVBtq2iAmyzKbGRPDZuvsysfogg/M3qEn82yRwTM6MkfQsQBAjBxIHRKTESh1Yj9oHmczQSXneVnef5psOUrWKmQYAaP5ABzESIAMm0Y5WUt0nR3fxvvYWSXMAQ7E3gcLsVR8vHgcoiid3AZNMS3p46f3PoQ3r95sx81mGCN7R4z47EHDxd5nawm9lyzOmbf1783SPBvm1Tzb6rTD2SzBnzSFax6gvaj99Kde9SfetrojKwiu/tSun7nk4M/Ydegcz920N5hbI062vo/jat0vP/rPnNOaEhCRUkqtZVleUIsUkVR7qcBaMh5M1YqIFltSmZd8PC2AAAQ+uI022VCAZ/X4FuY3YsMsNWstwbub62t/d+MZpZac0uG0zCkrhjCU27th6zeIBI3StbkqplVKTmk6nU7H42k+zdNpnk+n0+F0OtZSQGwYh93uehhHH4Zx84w+M4AkVk2zmdVCtUBVNPDoRhfVqBatc0o0iUouiYkQCERBzBRKBQIcfeO+QDIaXbF8SMelJM3OPBGqaCk5p5TmXGoVrVIHbg1xPThQJAESNiPwznnXci2M4ACIURQFuILJlCYkH7yLrWN+HYhAYEzomNQ584qGBhaC94EAjAiIGYmRHbZHhkjkQhiGuDEjz1UKprmkJaec2GFPyAAYA3PrW1IzqbXkBAbiPLvgXIgNqizDAKbsWKqCIaGToktMpjSf5kQJobQHLlWkKlcV0s+yQZ+Z9l3c7GLw0btm2h2Rcy4OI5JbcimloKl3vBtjHKILEdgpkIjUUrzjzRCcawxdgGC5Vp8zxYIhV3JKzhOGYWDnAFvnNJqCmrZeh55FbQDlHsvBMyK3FZ8An9N2piYipdWJz2sJcilVS1apFVRJzcAabMNURaV674L3VaytDxQAATSOfnN9dffV6zdf3NxtYBwNN/ePsCz106d8f18eH9LppKV4h5vd6AZG1jIvx8cT5EoAbMBgxISOGMDEFquWW3LHVvAaILQegkXJKSGQOCL7E3E7rInNNTIyAABm8s4PMTZcT7Pq3OaZWSkVYUkpE1dW11IpvoUdxIiuVzeB2XgYCdDH8ermNteapOaGU1EpteRlmU+nY9nva9Jak4qsGB1i9Owix9HFkZ3HlmPHRlwT4ri7vArmFqp3087dtK8Vc3o27AomvYsLARrGnVsRsJXp1Wwp9XhcHh5Pf/jh/X/744//+b989/s/frh/PJRURs9a6sCOVHE7DsExgZlCa0ZXBQNFXGSqqZaU05IIbAiet4MLzkwBSUERiC44Vc7PggE8gbExQnCwG2A3qPeFSdAUiilqRTPS0qj31ifOAMERBXQO2JknIDSiRqxBYGhqJlq5jlCSX454XKQsCbJFw1GDgAdFZ8DAiNj5Dzrlb6uwIuha0UY0UvBAERno80ydrGrqiEhMZiClHPeP777//c3u6vXtq00cKAxErD3Re7awsH47w+Qu5+kznL29BNf2v/56fH5jy+z/1B4+/6bXKc8h/Gd//rPjMp2uPRimFnx/Ztc/G23xnY36+b2XEt3nj7j45z92TmvzSzPtKS0pLZcuxfO+Rh1z0KJ2UTORlBspWiHCQYJC78I2AAC1NbVnZiJacslLVhFHuBmCXW+CYyY4HQ5priWntCRgYF/NADp6sJEumIjkPB/2+6fHh8dPj4fDYZpPyzKnNOecSskE6NmNw3h9fT2MmxCHGDJAOd+FYljEkgiIODUH6NkP3kc/1KpSpaa62ORydoGpXa0qiIGhKfrqdkKmiIAEHHKypyUlJNZCUJo/JVVqVSlWxUQdAnPH0bb0nyHZ2grDqk4E0RBbvQvMUpXMUlmRsNBWYghxHF64jtbucctn2HmLcs6F4KFhhpwLIcYhhhB6o5APIYxD3JgiWok+e+edd9478ui9Y8eExKwMFa0gCjFxC+W08QGpkKpDJPbEcdwgOWjNc+RrltPxlFN1PvQL7oA+ADt//fla+3a7oTBshjiGgNz4ydl7H4cNkpuXXEpBUEc0RseODVCRFUlEpZYY/NVmdI4NQGotJRsINKKySNsrdGEcg7+7vrq6vnE+EDsgMhBRQxSCNWSjlg7sFftzyK6m/RqwEddAA2KovHBYEIDJi4mJmCkxsYqoliq1UR/XGkKQAbtfbsiKHrzn4e7q1ddvf/arL998sd3qh2N5/2F6/14fH21eVCo6wIGXyGUXw5c34WrwDpfHY4GP5ZSMyERMxHmKg2NTKXUy4cKg5AFbtB09eocp1yVJqpJVm/dd4YwUvhx9c2xVR0MDA0c8hnhzdbXd7nzw3gf2HgBFNOc8wVxyQWRCJtKWp61VS01mRYEa8ULLDiJCHMbd1bXzDpvzQYzQUl/5aX+4v79/9+6duQ/LtK9lBlNEJHbehzgOYRjDsHE+MHsmph4XuWF8ztQBAvcsfEuKU29hxzOIrufrG0igNXKIGBjE6IchOuh0tIaUS3k6zH/44/u//90P/+nv/ut/+d33P75/2h+TAQZmI5Ra5uk0Odo6jDwwsXMM5MDMtFPX5SJpWh5Tmk5H73C7HYPnGAMigykCAciKBnt+HoQYnQsYdt4GD5uBd5s4Dk5Eap1TXnLOorWjOq3rT6Aqg0W0TaC7rb8aaQwUXWsIZPIRiRulDal4S4jzFo9bOB1lPi4C1VUdNGYdBDiii4RAxI2arTZKYEAwVMT1jM0QGpW8M0RAeTmrGoqvp0iQEMBMal4+vPv+dnf9i5/9/Pb6xjsPhPLcKv8cjEMvjp2N22rBWzWgcaOtaXGElZ/+uR/bnpF2f25cuA8Xpw3/qB09J+FbvN5cxrNF/8xC/7nRUoEXVfZn0/7novw/d2LnisIatdeUUkrpp6/s3i2hESqcscHWCLVSqt5z13rovIwrKB4QgLRqTnU6pdNhrrl6h7sxOFBGMJUJVErWWkDVeXTEz851u7MmpZbj8fjhw4+fPny4/3h/PB5TWkSqdvg1Bh+GYdjurq6urodhdCF4b2fT3rAX1TRXJW20SzQ4H12M7FE0m2mqKU/CKH09Q8PYkSECBXARXAdVAnNGSFq400KUZtBUGwrPmZEBMXnvGvZvJbBu/aktzWeECoitnbWK5DxpmU0qKCKe+EbC9fXgX2g+nUsbaqqg2kr9ROydD5GYqFEMxTDEEHz05IMLwY/Rb2IYGsFumzTM7Dyzpwbycc7VooVqj9A8s2fHhIimJkUKCrF4b+zYhdH5GMLgvXfs85KZ3Gk/9ThqhatiX3jPOI3zeMlGdzrVp31id3KMCMjU8qvDZudCFANEjMF777wP5Fi0BdF90iNAgx+r6FLL8XiY5mlJSdAZBUb2gcfNZre7juOGnYPuTdmKDsMqFaWj4Vu3unXO7WeZHuxJ+U5bx/8fxv60y5HjSBeEbXP3iACQWRspSurue+adD+///zMzc+90t7olUWKxKjcAsfhiZvPBA1lZ7GUGJw8PRVVlJhARbmaPPQtzHAcJb+3PEIxduVXIm65L7XisNu1fptZaKZv2g2Dg490PH0ecDuH4+4/vfj+O903j+dLOL3Z9buW66XzVfK11Vby6vZSWcPonOvx44NMYTVsW3hAR0RDcnQhD4GZg1apqbmbW17dGBjHwrsRG63au2jEp9N8eO7sQp/dmBDuHups0dpovAWAza7nu+E7tdhzasU9ENLfSqpuruTk5cFdadYWeMEfkgEIcb94oDMiAiG4ypuEu3tXgPK3Lcymza0P0rmoPMYaYJMYggTlw91MnJqIYvruvmPEWBIP8jQzXVwwIAK7u5mrQ1HO2nNu2rKWU092RSIgjAa+bLdv6y5evf/3b5//7X3/+13//+9/+9uvj47k1P4RwPBzupvH+kI5DGIOchjglGQMNUVj6w9M5v/0jpd1QSVsrteTSmilgK7ZtZVvXknNvit8K9APRaRBBSERTsik6szrM53V+Pp/Pl+u8ru77Vh+R+7mOZgI2EGhEyqKJcsLIyAiI5MhNrVYFMCEYGBJD3RZqOWgevBRjt9qUoGFI92kcumMQUmggi/pqXs1aN3sH11uZMGtgujvFfb8V3jkNu6iFEbADK9paba072dutrjq+lVrdgPKOEbi/AZT2yAhD7JDLvhrw7zgynffwfdv0X9Raf/MI/IelwH/6p81eae3fsPS3Y/f3k/ftrPi2At07g9e63v/uq0ud76yG/08ju+0+BN0NBFSttd0C5DewAb2mINwK/A6um7p5LaVsOedNVbYtlpK0GQS4QZrQ/8zXry+//P3Lw5enl+crYhCOYFXIulMugw8hvDsejyNwmmQ4phjoZmEHCGbeWlvm+eHr1y9ffr28nEsuakpE3chRmGOIKQ4xphiChCAS3srBHcAAu9+OmzlaP7g1l1WxNbfadUOI2G0ewAE7DR6gS99ZiHdiPDACElm3weSuaeiGL/1z2ieG3StqX+ICEQRGeXvPoqMDNtei6qXVrVKt2Mx1M0P99FEDv53aJUiEhExA6ADW7Ub6bxGkl3YURu6TCoUQYkgxDCFGETFQ3rWa1lm03YmLBUUYAV2deHed72b7ttdRRiRmbkEAgpkTMUmQkIIEcAwp9f6Aid8WdYL9d8H/prSfvz68fHnA3qwgIDPFFMbxcLobD0dJaZjGu7sTw7EJM2Kzvua3rqkOzL7f1rpu6+Pz0/X8ktclpmM8vHMUQGEJMQ0SAjE7uGmPoPC+9am1mdn+RIEgUEcddI/ug9sj0AWcgA4hhPF0CEN6+0asYatQsi9zvVyurdXdAMPJ1V2hqa6tuiKRvP/x3T/9/qcfD+8+psMBbfQKL89lWeG6Utlo9ErhF89/q/Vpq0/r9nCZ7/IB/jgFGGNMNeBqurbKRNaatgaGjGBuuelS2rwWcyRkcCV0ogDEW625NSBC7uELiujfp3jsZ01n9bvbza50v6qqupXiXs2hzyj9SAKAVpt1q2FQ1WalqVpTcyfA7gJF1le8Ag7k2JqhmpoZIAOIuZhx0QTybroPnI7bdl/z1bWA6747uiGcwsLUneSx2yazfHeT3Qjx/qp4u40/CL6nn6mbGqrBtukyl5eXyzxfzfFwOElER3y5bL98efg//+c//5//81/+7z/9/PMvDzU3QX5/PH16d//jh/ef3t+9Ox2GyGjK4IEgBRlCIEYA6AYDvUFkhoFEwXtIa6s117aVdr3m88vlej4v19laM9Vt+8Z4EoZTwjGGU5JDrIOUXLbLsl2fv37+5euXh+eX67w3w2kMcSAgQmT3gI7kJAgr5IBRMBAQgpnXZvOynq8LuqXIH+8OH98daq5am3gbsBlVhtocEfAYx7sTjWOIITiEbPRU9CXrYnXV1nXBhoCAhmTetGXVCqZqCm9zbghZCLwfB8zEiBAkckwskUIEZrvJVaDTWm5Ye2+zO7//pvgDRAZiQobOisVbndor+VtA/3Xsf63rtyf69fVfDNb//b7d92DnnTT3Hwvz/5d5/S357j8S6P6r7/CbYt/h/KraWusuC8zs5l08HCTEEN/+dXJgR+3BPv33NOjmRA5mXciaizVdF8lbVJ3cAzoBgJvnrV2vy1/+/Mv/9X/86+e/fTm/XD9+/PC7H39gArDuUt0E8TRNd9MBWUCSy6gUdJ9Q+7fx1nRdt6en5+en57yuAC4SUoxpSGGHLlikk++442y/6cocsFcqMHUyN7XSstpmue8qu/XCXvO77qd3iUTEJmgBKoAigFuX1CD3nXCPk9nVhwjgRL3W46sjNji6EwEz7Qhhp7j1S1O1Mpplrs6lNcrNc2lE5XqmFN6CMSHGMR64FhIGQDVvag6AQijcS76hd78ZAO+GBzHEEISZwBRufEZwxd1U2widCIxuI7ebWZeQGiG6IaBZQ21Umzh4UydCeyXp0S20MuyTvt/ErjeO8m/vzu9K+zZfz1+/WK3eGgIBsYlAiGkc0zDGYRin6XR3Op2O03GKQ+oWTTEmR1BVG1L/DfqVK1pzXsp8JuCYjoZYEW5hS9pa65h6d1DvHLl1XWut3f1xSKOI7GHDr/S5fVK4MerMiTFOg8RvU7u7L/O2lnVZt2XZlmVVVREWEgQSIGKKKcaQyCVQ/IdPH//p/Yf3IR4BqG6e57YVrZWieeSGcb6Wn79s//L8cs56zWXeNjrE5uboirZpfcnr87Lc6K1GiSYEBahqW2nzVs2AkYlcGIoyKW3V1qISkAJLQkJ2Bgnhu47+Zs3yeqr0abepLtuWa4PzZQeacjazEGRMw3Q4EGNrbV2XeV1KKdraPsoAIbJwCBIRCZxq2VbELuzZZ56+U8aIFAHZHdyVCEMIjCOCYJdvv5L0dzYc0X9yd93ex06J3OGd/R+ODqBqpbRcai61NG/N5zn3JB537flmj8/Xy7z85efPf/rz3/7073/968+/nF8uAfBwmA5pfDdNH0+HH07j+ylNkYXJ0E21qvZJnYkAvda65tz0NpYiduPQl5cLhPh03TCEp+fz8/NLy9lbFURBLG+m9lrXy+VvOMaRopM5aN3W7Tpv13O5vtTruV0WRVaWQlci6YNIYBoCcSB1e8ibtoYELBxEHLy2tm7bsqxR6O4wEPFhOiAIywBUVFvNuVZDqQIac4gbR89RBoeATiclqMo5Y85b3a+0AhBRdV0t1+1q80sDgMP71zfCjEx76gLdNIIkIaQxjVMahhADIoA1UL0tw26E1VZryaXmbVtz3kptqk4SQxyOp7vD8ZTGQVLcr3aXY/Vyjn0Hupf2vbH7T3jzb9by+2D3ffn4/tXvpj1ax/bF3NthnfaItt/O6//xVu3v8NVZ9m1D8Fq839SAt38fX8f91mouueS8btuWt476pJSChF2fEUJK8e1P9+5InmsrpUs0EIAchJBYDlNqRbsjdBRmJHJ09dLqumwvz9cvvz5+/uXh3/7087//6efredamgnwchnEIwoRuDBCZxbsShQzdXG/hRP3TMLfu5EMxpCGNXfa5F60YpY/N2A0g9uH5xm79/o24ddsMhIamaMaIJNGdzLD1riuyxBBjEJaO5AmLMAm7MEhA4Q7nCzEyBeaBOQoLIoE7I4mIA5gZMYfADm6mRMIU9ugSAiTosc2mbu6jYHLD56s+n/PLBS4Xl4snUGzNytv7ikOIPBIzIlmDVqxSN5XoUFaHGV0Nu0oIEZlwp+uRmTe1plbNGnTiAHQOhzdtTb1p12GCmUJ1EN5tOERCDDFKYERy0L217hQlEIpRYgophRCFmMy0o0yuZqqu5P8Nja7mbbmcLRcvFYEdeUMoiLsqOIY0DNM0HY7Hw+kwTFOYxul0PN3fhRSBaBwHdwdEYgICBddWtWyQKna6v3vOeV23bV23bQshIO7EPicytbzmdVuZeRiGwIGJ9joCPW1n17LfoAx3MyAMQ+T47Y24e17LlvO27l8AQMgARCiRwxjSu7t3H99/iDREDz8eh9+NMbYNt7lsL3mbm4Ehh4NgihXq1ddf1uXPDy9bg9pt5gCFSBDdbKv1ed2+znMnpxEhtXAArwDVfWu6bFXNhTgIAVJzrIZbs7W2RJwihYElEgaU24i5Hxhd144I3ikI0EWetWmuLddWq5pZLW3bFgA/HU8f3r2bDhMillov8/X55WXbtu6odQPz+9M7MAkitx5t5OBA+8Ti4EAsiSWFkJi6iX1zq0weWBBcbzd1P+EQEfmW5/fbDel+CuLt0twu4v42S9Z53q7LepnXLbdc9HJertclBj6eJjVci375+vRvf/nb//W//vQvf/rL0/NlW/OU4u/e3Z3G43EYxiCnMd1PcQpI2ppCM2um2hoCCDchQoacy2VetpJLawAuhCmmIY3VX16Wms2vOX99fH45XyLRFMPdmKYYKofX3Mqcr18eLu04sZ1gkMJ+vS7PT5f15dyWBUuWVkyxGZSiqs5MMYRpiDjGOKallF8+P75c12JOIQzTiIzNqmq11o5jUpT7ihUkikgSuG6l6rosy7bFuAWvHlChVRmBI2IADAMmMIBt8XWxbW0le6sOrsQFbbbqZavL7BLD4d1rNdrNec3MTfa9AKJwGIY4DjFFIQSr3pqW4qqopq3VVkvZcl6XdZ6X6/P5+Xw+L9tWqkkcpuPd7//wx59++gPThxhusgBHhz1TZs+fv3HM/98B+TeF379fKHxXTnbzR1Vt/TvTm9d/AcL/5qfsN2bf0L9d0v+GOvebnwy3I9t97wm2vK3rOl8v1+vlcj0vy1Jzj1abjsfj8Xg6Hk/DkEII33UyalZry7luxXtCqAMhBOY4iN8dBSRJbM04ECOZel5LyeXXz49//ve//+lf/vqv//KXL58fnp/OzHSYxnXZ1nkWHDlF2jEzVHKzZloMm6J7iEDkjuq7dVW3DT0d77zWbYvuykwdjKfdapR6HmG/uPi9NLQLutwUvHvIKboRQpQ4pKMZlqJuWVU5SDwdxsM0DKlfpBAiCzk0Eu/8POJIJEhEFIIMxJGIVbXkKszTODXVdd04SDoM2lreNg5DGsamlrUBOhKgMBG1XE1tujvEIP54Kb8+XT5/9cC2mAXSCEb69tJ2ihwRI5AWK1KJiume3gDuPfuMgJR69KbfCHc9l7Q2LU2rWrfF7MwiNDdrrVWrbXeC6d+zS52CSEopDjGkyIENkKr1VK3ucsuE3Kv7EGIUFlQFcOuZlVqJEP+7eJj9bO95JA4GXgEKAkIrWKVvfeZlfrmkIYVhCGMajtPxdErjIDEul6vmejhOIeD1cs7bptrQXYiiSHbG5jnn5+fnz0kY7P2H98fDsW/rOxgVQwAz7A2bu+tO0e1Tu+9N5m2Kvx0WN6LO/iLi3//+95fl7A+/rmUDIDNzBUBk4kOcPh7vfv/ph58+fRJ1X8ugm52vWyutbtdtnsvSjInj/TGOQxTwGDkwBUQj6NjcFHgMIYg4UHMo7pvto4ODhxyPpe4UFHN1VXMECICdQwbwzaichWMKYRAnI/nOLJCJQhB3AteuXjQHNWjWvUOxIno3JQUw1eu2+cu5uLv7+Xy+bjmrtT3A23ohNvBmWlolVADs9nU7Y8d3Ma8BEguzBIlE7OaATuQiJN1u9pbo0gV4Pf+76+72ZAAw8PZ6dn7bIO7E45tTG6A2Xbcyz/k653nZliVva6mliYgD/frl+ZevL3/52+d/+8vPv/76eH65DiTv7sfTGMYYkCQQjoFOY3h3Nw7DMK91yy1r58BQEJGY4iBDQJyX81qz6dosCU5RhiHFFLYtX1/my1Yu6/ZyXZYtJ+FDClamNiY+Msh+hNVWn87nmtd1XsTcanl5vjw/n0vpdj2mTmuu21ZLUTUQoRRVETiFYwgGcDX/uuRrbk4SN+dAjkZggkCJCkpDMQiODOgGpAal6VY6W8PVIectSUohBY7CkWUkR1xmn69tnvO2Ljk7WBQ2wureat22TdLxhx++VZNdJaU33RzBvhfWUrfr/PzrCxSrRfNWt9Vbu9lqV9XWrLRaWtnscm6Xs25Fq3pIVRe7H7AcqQ7UAiD12HhAMu+X+9WDDL6v66/1+7X16P8bb3Zet4Uwflec3b21BgCqfbMOr8v1bqz2H0H4777/7du8PfxewfwOHHZ7efjPX7tzbc4l522Zl2WZr/NlnudluW7rsm1rLVlrRYDLkKbpcLq7f//+I4DnXL5jyJuadYOrfdfW4QdCDEHGMbmhGqxrLrU8Pjyfny/bur08v3z55fHvf/v69dfnx4dz3TRKHId0d5zGlNBRq1WojIgGrUGrpi2bVQU0rFqhUVZk7eoMU2vNzVNKh8MxBHFtNzLad1aY2Blct//4/UeiBB4YBYHdWEhkSONxOtybkRS167WtC04DHUY5TjKO0Kf2YRCR0jYj4/tjOEyIAVAAEJiBE4aALFZqxllZ4mEstc6tpCRhGkrJs5YYGYZYmm7ZHI0EJTAxrdoUYBhjmCZtXtayXq7LLLkxCUJg+p5GR0jAgo6oXrgEEgbUncEIBLfccQNTaFVzKcIbAGoITJhzXkvOtbvMIrMEYRHZafoG2per/pq5sxPLdhlRd4HqV0Qtb4t7azW7ed62ppkZQuQ4BDO1Zu7WWoOyqwfeXo3vSnu/YPD6SDjA6+Po5s20tbrlFef9F4khpJjGMU1DGseXh8fr08v9u9PhOC51W66zlcqIIhJijM4CWkp5zht51ZqJaEgDESMCmBPAmFK8xYghgNtrcFmf0V/3s7sk+KYbMXjj3cjM/+Of/un58ph1vcxXZnFVMGKXROE+TT/df/jj+w9/eP/Ol3nL13J5mde5mmewl7KeazaVGDAYJOYAcghyiuFdjNlB3d31lMIUQ5AAXUYJ3ACrY1FrqinX+1KaQfcQA3cHM0C8LYL6amQfd7tqNnB7HWlfbzKmEIMbgbOICEsz8L6RBkMgps5YQWmtum+l5np+ma/eE65UHZmk25Ub3o5JRGr7Qshbq02rqfZIspu9pfUntxATkgMgYYgBMTkMyLHbtQYJLEzMKaVpnIi4v11wrCWvl9fkt113ZACqfgMBd6WP6s11Obd5LpfLrM0QUQ1ytV8ePv/y5eEvP//yy69f0XEM6ce7+x/ujmNAdD+vm2qNHI5TuL+fJA7nssyqWwMzIkKWQabT4RTvJ6IQnq4NMihiSHJ3NxymQUJYH84vL5fn63JZt9LMzKv5BrBJDUTDwV+P9tbaNi/rkh/8sl3Wy9Pl8fH5crmOYzodxmlIhDKX7TJn9Z7pgObIQJUFpwlrLRIuDk+5VVNRZBESiEJjoAmkUTAKjgJO7s27I5BZUa1mxWzNLczzGOIQ4xjTEIchjO6o17leL/lyXZd5Xjd31SiFGJBK0zW3dIBPbyr7DXbeSWEA4GBmRcuyXh6fP/8VLg+6zW1dyjK7ts6RcjekPp04unGZY51NG5lBLZyd8gtuL5BHTwFIHHezvBsIv3tw72fKPvPh24J7u/X74WM7H4tu+8k3Oe6vxdXdbxlubzfrr7L1fqzBf/m60e737qUnC8FuX9gXu3j77fa99I69t1JK3rbr9Xo+n5+fnp5fns7nl+t8qSVrq+B7ogp2oHsYLi93eVuR0PzNewUAN3DlPa4GYTeKNSAQIUhRm69SVdfLeb6cr9fL+vj16cuvX54eztfnRZsT8CDpOE7TlI6HMYXozfKWtWC3Wt6y5ty8ZbdqCEZSsSgm5+DAZmAGrtpaE+FhHIPwzn6xm74KAaC39N4Jv/RbQN7RlMEiIwOgKgbkNITTMd3dA4gUK5G2M+CYcBxwGmkaO8rLh4lD8BUNDKcTHQ7uYk67J2QIHkMIQZlyzo0lpZgRViYXGlLIrguRMpFIMVsRgJAQuxHViq4IRSTFWFPMKa5R1sCFURhBCIW/mwwRidgZiSFyCCTs2OnHcjPD7gOMNS+k67b28zYEEeaSy5K3rdSqao7MQYLEIArQOru5c0iRYLfdxd3+fd/4mCvoDkSZWi1lZRFwr6WWsiF7HGSYkruVrfYGt9/AvdN9ff0mHmavmJ2OcyNZfKOn2v4koKqhNdBa6rZta7iKxDg/Pz9/+Xo4TuNhMoLibQh0GiOERGmIKCPrBq6bnecFAU53d9M0xRACc3vdit0sS7pUE17rt99+nX3n9ao99dvX7WBACIIhoAQQAQYmlEOYPkynT8e7392dfjqko2V7/lKWZb68zOu6bLk6VPdLbktVAKyg11xTlinaKPR+DD8eUzE0BwD94TDcD2EMbNRjVgiAARyAwf1me94BwteEefMOEyHSDTZER6u2XrOvXr0h4VsVHxPHGDvoEySIBDbnZmKa2Bq11tRaK9Sfq07B3c0spK/rEJzIoQu6Oum3f4LYOyVmFncFNFBDNOyc3v1Eo36OI5FwFNk3hUOKaUwppWGIKYYQhiENwygit1xAfHl+/su30g4ppWEYTLX7rtsOsHa1aOmNZJ/RHHytZclFz+dmdr5cX86XspZTjHdpej8dPp2O7w6jMBStS87mfjxO797fHw5TcbyW9rxVQxYJKQSIqZFQjKe7wRzGQ44Fo8vxNPzw6fTu/hCHKMPBKMXn8zTPvkv2SYgGodjzpF+feaLIUnNb5vXrr89fPz8u66rWODIwohARGYIRjdNxnI5pTMMQpzGcDoOMU7ZFEavpVvKaFbeMSMSUIrcxHoPkUrWp9wG9NVdFB0RCFEAyk+o9GcN6RkDNW+XFHa/rNi/LmtdctlKzmWrNSOTA1SBXg/DdM9/ThFQBEUvN5rbrg+q2zS8Pv/6s4yDW2JVcSbotgRChWqvaSqm55For7NMbm3up5enhKyCt1e6LpukUhgMH3Gnc++nyVq/VBVz+Wt39tQbfevZaS62ti4bfsMi/nVW92Pa6fvOO3V0L3/6xb6/f1vibQ3trpZRScs7FwUUCGWlrztYFO/uPM2utllLXdVnm+Xq9XC6Xy/l8vV7meV6XJddcW3XvKWQAZmUrpo2Za1PT3taaw3drUQk8DJGRytZCEKT+bN7QTLct18eHl7//7cvnz1+eHl4u52W5Luu81aJMIgKdRkYAbcvnkp8f1Nxi4GGI7+6OKcbPX56eXi5j5CEKMavjWkExpPFInGozMyBEbdpqAwdmYSIAuW069kTzV9LMdxuV2wdtbXNraNXbqm1pyJW4BKyRiSNEwDaiFhoHPkzhdIyHqZNewjSGEDwN7sbD5JJUUQ3V9x9JLDxO0zBhHJllHKdQC8YUoxyOU5yqjJNIGtLUmg61ADox9giJOBRVnU73PCRcKqQEwwApQQiOVk1Lq29vEiFmDoCuRi3ELEGYWyNBCSTIhIBq4AbN1S1rqyXXnEoMQURa0WXJOdda9yxgIYkhOmEzQ2hgFRp6AwMH3GVyAGjqpTRUg91mwFXNmt3c+VybqjWJcjgdmXgZlvm6lNy0qZlZsf92avf9yHfzbpO120jf6E8I0HdnCOBdT1RRa62ZCHF+OT/x1xBTGgYeAg3h/fu7GFMDUkRkjpG0Ra112Tat9fT1IYVwSCmKIAGxDOMQUwoSkfbQ69tYcWPSwd5Aw03nsqP533kOeGub6oZYmSCSsMR3w92Pp3f/8P79p0N6nxDz9fqyLOt22bZLtVm9Oap5LpaLIzmQzVsZNhoDjcLvhvDpkJqiOSDYpzGeEifB3D22Xq09HGkPLifa9Uj7M+DgtyAMuCEjhA5WtORSrFVoyGT6DX4g5hiTaXPXEFKQaGaBdGjNoKpCda1at1atVaiF6x4R3Psj7+3FjYXYP6jOa31FEhzRiLthj4JqN072W/YXvgarhCASuZsmxWkYp8M0TuM4Dr1sd46oSOjUJQb/y5vzdC/tZtYzTqz3iE6AIYYgwrfzrKldt/Xry/n5PF/mpZYCph+m44/v3/0wnT5Oh0MKQxQKuDZ+vC5Oejwd7u/v0jhsS3lZ8+O8cRwGCsyxkWQDQxqmoTYfx21YvQKfTsdPHz98/HiaDmMcTxyn4/Hx/PIiBJF3Cqy2qqoz4WtVZKQgUVctWzk/Xx6+vhhaGoQDhyQhMQICATAd7k7vP36ajtM4xhgoBRZhWPNuKW2tlawK7kiAOgS2IR9iq9VNEczVtWbTCm4ERCTu5C5N3U21aWOstRTmDdkNrrXOpeS2mzI282oKDoaihk09/ca0vFlrnTystRYzFUIg91bycnn8SjYOxyhTkiGFGPeuUphzKW1d8qqXJdfWzMiQnLCpa2n14emylk2xAr8DPoQEHJi+A6JuBXZnycPe//prw35zqXJVraXkvEEaXkP5frMt78wv3MHMPRD7N3/g9hPhzb/4d3/EvHNO13WtpSBRjLty7ZsOHsFUtem6rssyPz8/Pz8+Pj49Pj89zvN1XRdtam7YWeQiQl2EorVCrSYCXeFj/lTy1pnkr79BCJKGJCxlrRKZbplX7uAGter1Mn/++5c//9vf/vbz56eHl+W6uUGUEEJIh7EvLjt/radxPp1fztd5GOO7d6d/+MPvTsfDv/31r3/9+6+f3t9/uD/FEMz8Zc4GfHf/KcRxy80MgoT+NgFgD6EhcCPEznTuA+a3cvCbq+puXhe3Bla9ra0uVWLFVBmKUIgCTlAS6sDDKIdJDgc5HPomOgwpiFAc3Z2TOJEZKEJD72uWKMwphZDSYY9vUdU4TiI8pqBmw7ERCUvseipHQPJuizNOrZkN4wAIIIszuwiEAMRmlmuBsr59M4wYiBDAGAqH0N1ViQNL4Nj1xujWXLVp85azZSlDLTHGwEGrbWvNW21FEdEJEChwQKEAQN7ACKp7M1VHtMAiLASo6s0Vdhu1HUnraCq84tQAMaUg4XA8jIclpMt8WZbrWnOtrWn7LnboN1P7DpvBvt8GBKebAQV2phQA3hKZZDc4jSxCvBvMEQuG4IRmcF03f3xWjtmRh4NzUnUwaKXlsv2l/dvLr58H4b5iHqbppz/84dMPP55O9ynGb+FHN2Kt+26eYTeH515RDeytG52Zff3yfN2et20V8nfH6UCHn04fPkyHE1Gwps3yer1cz3OuS9W54WZd4dtdenoA5+5nhc6RaBAehDJgH4w72ubWqvqWy2WZz/Os3hPfrCvLrYfT7kle/e6/7Z0B+y7FvWehOREIMQd5O3Awc4xJlVxbCCFIxNagKWyzXs75erFl0dq4Nsk1lEqqnbEJuxMJdgSmqfZNUW86dgauv8Yj7xJE9VdU/psNaG+Zhau0wKrUZZ5mWktbl5oixUQxegweosfgIsLsl/Pb22qH75gQAQ2I4JY9gmkcDnen81y28vL4cvnl68PX5+eny7WVJg53aTyl+GE6vJ8Oh5iiULUG5h9Od8d0WgHmrY7TCMxqPm/56/PLz78+A0sahrvD4e443R+md0cqbTIAEg4xJsCUUgwhBolRjsfpQ/FWNi8zewtoDORGm5Hrd48KOLoSoySJUxoO4+BoaZLDEMcUgrBqFxG1UsqWVxR3LGpEGMY4psSn0/jh/cnNxpRbc3NHh5jkMKW7QzpOcRpkiOglt3KtZW511Za1labQjJq6qb8yciNzJEKEYpZVFXoupDB3RiSQgxuwGv8235Hcul0JgyP0HUxTV62lXC5n0AqH0Sg1BFLFDIAIDuuWL8v2fL5erjP3z5JEgXJrpTaiOkI5lHanZkhIYoBg0B0MbwfM6+5879N9t7zducddEtIh6dZqrZlZgvrNgfK7FxE6dLlVZ8X7zaDPX5fZ322Jvy/qHZ6stS7z/Pz4NM9zrZWYYkoiskdp4c5BqaXkbZvn6+VyuZxfzufzMl/XZamtqrZOBEYkIDaOLh1mUJNmtnuTAgUzXJa1Z4J9ezr6I3vzQ0AAU+sRTiXr5WX++vnxb3/5/PXvD/layChJREARDrvNJPU4UEJ8eXpa1vU8r3/7+jCMsZh++PThQHjN28P5HIc0HQ7ADgaqrqZaKjrXrZqBh64l6eZ9+8bVjAEBlcxat+fr48LtPH7zLtywXMkrWEMrCFUoBOEYUxrGmCZAzqXmXMIwyDiChAYIXZBj4Oa1J4t280wG7PpLRIlMEswx51ZKJZZhBG26bTWKCVJV3Uplgehs6toUCJAxEBJCaVrdxR3c87ZeL+fL8/n8dFnPM3oh4VQ3tPTa/9Va21bI0Zu3nrXd3efCMMQBiMzdrRk6goKZeVOwxo7gxqrFS24tVy0K5tCsCJcocYwcOAhrlBalVe0D3pCGYRiAyBCa98Q9tVs4PDIycWeZAQEJ8tgd02lb8+F4fH56eX54uZ6v7aq/WVh9/9D/dp3Vh0zvAsbbnQ6EhLuYPqVxTMMU0kASkdhgrysGqt7M23nejJ+qwXC4i+OJJQFgK3W5XC9ff8VaBIzAHeHu/bvWWgxxiCmydMeGVyj+xrvuPDqzvZZj09a0tPpNpGRmX78+rvW8rish3B+HD+H40/F4YAnarGg2vWzL4zKvVbPT1qgqJcEgKIzg1NR2NyIzhI62ohDmVycK7RYUramvJZ/X5bwsnf7LCN1sXzvxqVd32z/b10PGO6EUDNmZEZkhoMS4d0/95GIOMVEDI+iSRgan4r4u9emhPj3A9YJmZCCO0UBV/QZhAXfqJaoZ1WZgQHuecteLQjeqNuiEPrOu1PRXCdEOC7sjM3KAEqAUr1VrKdsGQZSpidQQSu87wk3dKSFv3wVg3DAN7KJUBOC+tnWgIJxiA3++zr8+Pv38+evL+bJt2yHE9+Phx9Pph9PxkGIScUR121pm5N9NP7z/8G5pEK6rhNDMS23Lmp9ezp+/PhT1EMPd8fDh3V15/+7jnWz5qAaAJDEMxDH2kxAQYUjh7jgul7idkdQDGAKbw+ag9pv5DlyRQcaYjtN4dzw4tpBwGmIKEljAFBy06ZY3ma/Nc23SBmYc76aQEh0P47u7o6nFGGtVNUPwEHga4mGKhyGMA8eItdZWe2lfWt1azVuz0rxUaAqORMRBJAYfogRhJ3JEZo8hYDfu7IzcvlSvTcL3s6yR2c2PrCsjrFsaWa11NkOEENkYs5m7tX0NbctaL2t+uSzzuk3T8e5u5BidZPVtU2VHdKxATozMwGwA1gXM8Jbq+lqje/71nkbap4rOzuqm+s10t4D37rSB3w/tXWpqTZu50x4QjbeRt++mvhHm4bcvd/emmnNe5vl8frler9qUmGPKLPz6o8xMW9u2bbnV9XWe13VtrZopEkhgJ3YkIwYKIBFCAhQgpaS7QZowheBgtWZVc/hmYWHdV3YXe+NOhihaq9FSnh/OX395/PL3r+fHMwKPYZjS7lRC3XE6hhTjEFMUMbOvT89rbY+XayqRY8hNnTg3nbdtra0YhD0EnqBnt0JHdB0BYQ+A66R6YWHarbSwExb9Rmm6ncjffZxUr+jKqIiGAkk4hRAlxphiGoh4iYlYSAKyVHMt1QyQ0BBFeVs3dw8pxKFzjbszJElgQCpVy7ZdLleRcLq/a63Nl3mIAd1yaedliylOo7WmJTdgJKHELAhLycWNhIVxXdf55XJ+ejk/nctlRsjEXut2HH73OlPlUlTnLvHacmnNADBwSCENYXRENQPrztAKnerp6oaq4GZaQatqVS/marVqYcpBEDESEkIPmRQmQ0GkEG7qcXdt1Ry6N76rEmPkyEyvo7VwiDGmGFOMtdbDceqqbzXNOb+tHfAfSvu3xfY+Ee/aRwRAR+9i4DhMp/fvTu/en969P9zdjdMhpAElQnf8AwCEpq22suU1l40IKIiDWFPwAg41b3mZ1/NznS9oDd2cKNf60x+el3lupVq8PdRvmDC3+r7/ggjoYJfL+fHx69PT07f3AJBz3aqW4qAgDABlWV4MSMxjxJRwq600d0BhSkBMxGBoDay5N3cHp55J5G4G3syyaVYo5mZeABRJkapDdSjmZW9h3QCqWVVzx9fe6xtjjogJX32PHczRJCGNJCmElN6K35g4hEBgiiAhcBABQ6GGuz0fAIYQiNiZ0UFL242NwB09DGm8OzrQtjV3ICGmblcSWKJ2adONBWAGzZq2PoQ0s1Zbvly2bd1IhEW4BW3FtdayLEiMEMEjU3dLiiGkEELo0G2YOQB9MxHqrSjizgvtn0Svxw9Plz/9+W//61///L/+7c+/fnmar2si+XD/7sM4fhoPp5TGGA1gbbWCF7PSSoJg6BKIBd1t2RYnO/nUbX/cdcvbsnpe57ItXstP92HL7wiECGJgFIkhEHVkppoBggraEHAYhySSM11X2Lxd2/dK0c5wNSMAJhKhZrCHagMSUwBMMaQoBGZatGgjUQ6gkTt928Ga5bVeL+uylaYNAWKUeojHMaz9IOnQqqtZM+shkK1UXYvn6rUBSghBggzD6fTxw7vDYdgFW3uabCfieqsl52Xbtm1d0/fmgA7UdcZuoGhdtOj7IWUAYN6qVsy+5u4SqN2Av1Q3h85kSOMwHiaJA5CwSBxSDHI4HKZpYmHAfbPXF88dJrot2vdXL9X9xHDwm2s3ABA47jZuxAao5g6Gr752+1FlOWdVra31dKVOCOj1/vXowO+dZ24neO9nrLWWSy61OECIMSYMQWKMxPx6IJpZ68YYTCGEcUg5byXn1qqququ6VbVi1jtoZL4FcMh4GC3Jrg4gMO++VAhvtqKtatmad7s6c3DUZiXX9bplgodfn54fz1pUvuUSswQWYY6RU2QJzNIlRTxEFAFkd1KHZl6altq6Tt/cq1pTZ4D+gzp21pd3N4PW3cd+l94Csof9srWOje5Oct9DIIDgUVsSPAwDBXIGHicJAm45F5QkkXOt13mpXZENZAZqhkSn0zFGOZ8v7s7CHAIiGmBPjDflRoJQLuf58+cvMaXfmeZSvz48Hsax6ft53R6eX8bpcH9/l7e6LhswcuAphIj4Ml+LKSGcjpN14EutC88YXLQFrW/fy5bLatfuSlO3WreiTYX72m0gZgMPFISkIFZGM3Qw6uwwMzdHM3FwJCBkQlZoa85khuqIu4wO+1bZW7NaqhNqN+Nobe/HW8MeKGA3O0DuXKfY86hI2NGPteacSy4115i+s0L6LSDvr3vtPll25/a+hQdgkRCH6d37H//hn374/R/e//jj8f7dOB0kJmR2vDm7A7amudRlWeb5WsqidUPs+v2+5lVTrXlb5quW7KbILCHOl+syL9u6xhBba/vu7Rvl9fWG6i05udv5fPn555/PL89vnnnIpebScjZ2g2CtbZeas2EAGi0CxapuhkidRcmiCFZdi1t3GTIH7v/etYzFNatmw2Lu7g1AiYyowR7hqm/uDgVoe1vUP0fsiPRuj7XzBIF6qgF5SBwmkRRjim99gJkpBqmgiCaBQwgMBiKVSZkgJQbgEDyIM6J5ydWqdQ6Gek2n8f73P6CkdVFwFBEiYIQQB0lTK1tZZ3N3IHMyg9ZKLVvdSs1F27au1/PlnMtGHhiMzQwU0bBhqw1No2tAYuYYwxhjDCLEJAE51MMJPvz0rSaamint7QyCWwPfcn0+X//6t8//85//9M//8pe//PXzuhQGvj8cfro/fRqH9ykxkhnMVherGby6NVUyNoB9uvO2lubkY4qIEISF0VrLJdfNoeVIfrmcSslJkAmisBDHwIQIu72Go7dANgY6TcMwjE8Xbblkp8UwvomndXfT6qbuimCIoGbaus2fMxILDlHGKMzAYGSIZmTOjoJkCOhkzUtu87y9XJZSG6APKbSW7qa0bLmW9rqDuuFD1prWqrVZMzKSGMfxcLr/8OGHTz/88Y8/3d+futZGXykyalrKulwvL09nekFVkbfynlupvfUlXdaIt7RYJmByAG26Gxh4v42RkFBEYnADTCmlFEOMwEKMScOQ0uFwGIbUP1vVpu7miE7/VWmHVxJsT0WBDvnu94k5dBqj+j5W2nd7Ny+1qFqrDQFUBQDcadfFvslyDSK9xe7pbTvo1/NKtm2Z521dwVQIQwgxhBBCtynsTbKqKqJAEsQUwmEctZVWaz9/W6tV21rKWktRbwbdVDowM1FK/ConBlV34yCqluv6OvXW0ra1uFreOibtrem25utlNW0Pvz6dny5gkEIMgdMQ0hBSChJFUuI0AElXm2ptwAzc1QLSo02bajeuICTzPaYBkb4do3AjOLzu0XFHUXY2M7uD8425/B/ZCvvVdE/ajiF+GAcZYguoIZqwueWcKY4kodQ6r2t1M+xeVdrUiMhU4xAfH5/c/e7du+lwREJ30B7QqsykbnB+OX/59eswDtM0Lrn8+vXheDzEFM/X+ZevD8dTMcJtydfLDAQS5RhTInp8eSmtvrs7TTGBdYbw/mKAAXwCe7t4q7UueXN1b95KtaqmGpgZOXKIIQJSoRCIN4TK2JzMm+3xM11q7II3a9oev5SLkyo2YDLsqLCrmilwLgAO1GXJrePB3VQRALDsVA9y7oYx2H1riTCAeBym8XA65jXX3FL6zpL1N+38K+jdx7l9pWwA5qjuQ0yH9/c//MNPf/zf/vjpd78bj8eQAosTZ4CbEwmyU0QOIBE4YRhLmWtZGJXJuwtNdypkAhGan5/yMncuXC7lcr3++vB1yRt0f/jdtOhmqLcPPz2W18xs3bYO4b4p7XZdr8u2XJccAGJk7mlegEA8oJCAKAi7ASLC3kRaQ1ACJTI0RzRCI7jZ3t1gde1INQLsQpDdU2d/FLrfpogImwMweRf3+h6NtoctddycSIKEGIeYmLllLaW8nROZMAVCh+YeA8cUCNUie2AfB5mmQMxE5tbKVmvmmNCQka1WXy9hmk4fP8XxuG4OwCyh2y+mcRrGU9nm9frSVA3RnN2plqXmZVu2vGy1zE3cnqQShEASGZlQiCIykSGj7jHoSqwsGliZ/DXC7LuHBb4lczi641bq+Xr55cvjn//y93//89///Oe/XZ6uE/H96TjFdDcMd8Mgwqu3Zl7NFd2EImNAVJVhiN2PiYhEGCMNUzocxuZ4GMIYeAiITkIYhVyrtgJuRBiE1cGJAyOh9421IwzRDkOEcTgMKcQA5AW9MXsIb4VT5q36Yqa11ly3XHIuBdBbUVcngEA0CI+BYwwpxjjIMMRpGk7jNMRBG4xpHIdpSGMKW+Dapz5rZtW9AFQEJTJGF3QGI1XU5q1193u6u7s/3n/6+MPvPv3404+/++mHH3749OnD4TDZHnJmqqat5XWdz+fHr59/Mc/rhjZ7+87zJQQOgUyt230jIjPGKNOQpjEG8jGFKSUO8oo59We7VFuybkW1ac7buoRaGzF3J84CLsK15FZLziuyGLI5gzM6Upee36LXXwfofcdOe2nv564bmUHfa1GruDe8bvaN6o+IHTJm5hikw1dEu/pDVREgq2prAD0FmW4EvVZzKXkr67ou83w5b8tSS3azSpz3e3U/SvrWX23Pz+w4BJiBO5uRm7gFBwlhCJIBq4OqAVKKQ5Bwq56vQh4Ah1rKfP3LK6Kdt3q9ri23+WXe1qxVS67rsj0/vdScH74+X88LOg4xxSQhcb9pa2tVzdeCu406u7nWAm7ClFJgRt79ZZCReuAEuBH2aCJEBTMtrXZcPPZ53f31GvViT8QdUyFV+60B3ZvSDhDVR4cDMjFnwcrUCK3nDvcBp8e5SBAJCGaMiHazA2YJ0R1ZInLol7vvgntgpXUfzdi964VIiQOyOLMzAwsQQ8806zlX/RPv1GbvwZrMKCyhh6C4cHQ+CB9Fzm+alZ500e3wAdxcoZ/9qtQ0BhIKMXBEFqasUr00ra213r8hKaAjGTNGwCioZBlN1UpWIzLAVqEVq7mqWg+zI+lb7I6lABOCBMC9Ge0O//tK0Fz3TSq0pmbIEofxcLqzYfwuSvs3U/tNqrVzv/qOlAxAEQ2Ih3j6cP/hxw/3H0/jMRDVVkvOCm6w991AMko6AU2IY7+niJDYCV0IWBiRJjsAeAiYkhBBj5En4a2U5/OLEZ2XmRFjjMdxDD3rprNMqAfJdwthdoNc67KurZZwc8l2gFy3LW/bVtWpujaBiGjUE4acGImB9jdK7maq5IqgiE7gQrecgX6j7NJOMIQ9sXw/8fCWbuPg0LXgTByYRbiZ7yYBAMTYUe2OCvpuh9mRwiAc0aguxbR+L37DGKiPiMIkwqDshM7sMYXTnUwHcWglr+cn2hADMEoMg+WsVmUYD/f34+l9LAAgJAkREGw8nKbDXV6uMsTamgI6ijvWPOc1UlwxBFox64ZRPCAlliEwkjD3NEYhAiVxRkDH4DFACEa9ZXG97SFuNxW4mjdzRHNozV9e5j//8uVP//bzv/zzv//6y8PleWagD2k8DsNx2ClMCrZ428yquzCn0FWjVFXjEEgEO5UsMI9xOoyHw6AOpyndTbHkmBkDkwgLWufqMGMSBgBDFO6oCfZp1aOPKcAQUxDsyAYTRxFHpPb61Pc1OpgBGgukJJ3UOcQ4xnhIMQrnw8hmKY1pHIchpiGNYzoeD8dhrM3vjscP77acGwKmENY111pF6DjGu2k6xmHgKMgGTCAIjMAADE4AHkQ+fPjwh3/8H//wT/+/P/7T//jd7//w6dMPh+OUYsQbFqhNSy7r9fry9DimpKWWraxLUQpvD+QQOCVpraGaKgqhBI5BUgpDFEFLQilwTIklEHOPozD1ZatA23VZzbTmssoSaiHinX2riuBrGoY0MEttzZAMhCAiMAHwG8sMwL4ZxN3WbIcFDQkJOobkpe7npWruEFpr3zgciCjCgBi8P1zdKA1f/9+OeNZa932+mSJpq12Nvlwvy/m8XC/b9dq21bRBN+C/NTKd1HPT2JruaYC4e+N06KMHgDDFGCTFEEJlrlUdIKUoIYLfgLs+yxACYF63V5kAAJTatqVuyzZflrJVbUq15S3PF9rW9eX5Ml9X8YDCDqjq6lWzNtXe8zFzDCGGJCzeNAifjuOn9/dIfnccpxQjc6dhd8ZDFB5TZKRSDcBLq6Wq9fAHJ3A0B77JAne80fdI5Tf94W/ndgQYHJJCaIZqxQlv0UKv7GESCTH1LyIDZDMnohBjT15wQA6ROCDsoZ4E3aKbgDDEMExjjEkkiHlIKcTE0l35hxCTSFBpIQRHJ2FhYaTAAZ0CBcGOa+/rQ9g4OR2TnJJcEV83JEwSOBqoGipW7IwzgN5vinoiEkDi4GjACM6gAlAbNDADBEfrd3FEGBgquqKreaumSM3JFLRZra3V2kF8NmZhoJ2hTsTEiD0GjBAQzK1Wa2qtNtXWQSxVa9o/s2E6evzvpnbcq1dvTR07yVGol6sQ7t/d3X84ctAvv/7l4ctfwb0nEANYCIGYEGk6vTu9/yGOdyzj5XJ9evq6rc+1XNGNmVM6xOHAfV94fzpMw+l0WK+XdZnNfc7rL1+/LLUO40joUWQaUmAhxI5MqhkAHE537z98OByOgQO8YXO/3mRpiFWbZBPDKDIwDWiRPDAwu5MpWIUuNNNatdYWGHo8IBkKc4rxNE3HaQxMZWdz75xzdVPVnqgMqtCMzNAcwYhIyAXwNVapr9mChOM0HMZxSInRTdttbiEAqsWt1PXaWtW3U3snwzGTKrtTrWjZ2qatqpuRO3ceVJfbISMhhCTjwZnLHINIlBBDMEAHIQkIQLCvbkQ4iiBAA+jJDcBkTI1QCJUgEE6R6ijDFGMK6E6IQrhj4YQExkjAIUggZgB3q27mViAOby6Kz0+zNHOk2mxZy8+fv/4f//ynv/3t1/PjWar9dLwbQkgxMSEimGtxVYJGiEQRIVCPjAUHr6Dg1MAdMQY+DEHGcBjjMEjT+PF++t2HUyBft+zuiBADD4mFJbCMwdndABK6IBB4t0oEpsqizN0kIga8vxtNGm0t58Vsf+pd3YsNMYyn+OFwr79HVUP0u+N4f5ymMQWiD8dT3qqEuAO7QWKSNMRpTE0N9f5ulH/84X5ZS861lFpbA7DA9O4w/O7d8fcfT1NAEIiBYgrDMIxVsztVRYk//vDxH/74+z/+8aff//S7D58+3t2dYgx7s9gpnOIi0i34UkrTNN29+3B6//G6lvIGfkiDjFNQZTUxNUIYgkggN7XmgAYFbNuQJMU0juMwjQhYaxPZ1GxMIQkzADYFAKTdhaiqudoFyVudr2eKsQEChyEdowxM0u229ukZ3N0JiaV3SIYEhNB3irVq3lrR1rSBN/fayqa1MAfCbwS0bn4P3eSR+E34VbeABzXtqsCWMwKAtnWel/PL5eHh8vh4fX7aLue6zFZLd0VF4i4t2XcH3eSjw/vgrStYAdBeeTROwhRjuDuG+3t69w4OB1dr6q0Z4Gq33GgiZO4Xi2r5jmSKTuDUAVI3Q7eO6Ha5c6ttWTYrGzgQo4E1rbXVXEt3LB1iPI7j/d3d6e4UhX/8+G5I8Q+//xHRhxh+/PQ+BhmHGEQAgAjevzv9+P7eDZatfHm85vNq2gxId649+U3mDB1gxlfYZsdy4T97EcCAzE3rdTErmwY/AMbhJh4EQhKRkKLEKCEiGRCbOxOFjrrE5IDM4VuElAH146Zre2II4xBiohgCwDiOwzBECSmkaRjHOAwhUjNI6gQUeJAYgMbUVCyGxBSQGIUlhpgCRIku4xCnMWL+1qvEGA8ytVYrZm/VWkWkIJSIIiDX5m1rbhW0QK2gjVCNzMmN1NwUzfohSQAGpkB+S5FD7/FuhMjeSBFbl08R4J6xi4A9RVckBIkpMOOe39Cq1lKzazUwRGRTq6W1qoAYYmD5rpr/FpDvaTTfElQ5SBpdAscwDuHu3XE6iPv68OUxryuYl1LW9YoAMSXmQCT3Hz6a5vF4zyE9P3z99Ze/buuzltkdECUNp2G6n4534+EU0yQpHsO78TBer+dtXau2l8tZEVLeCF2IUuCuMsw5z5c5l2JqHz798A//+D8+fvrhOB1Kzq0WU/uWbYUoUbgIEhKgECXGiUAIiLxnUyl4NXd3NATogUEojABOwCnEwzDeHw7HcYisrWM0iHyrB+iObuSO5gwQiBIzAQlhYh6YBxFCi4SBKBCPMZ7G8TCkIQTQdjPaQXdszZvXqrpcq7a3Ij7oGX9MQmTmaM1a0ZabVgUz3L1yOt2FqSf7SZCUvNPuWIRZmMU6Tk8EQDuLWPszSggCaODmTgDcGW5IShSYx8g6yjCGmIKrwb6xY3MAcOn3qAgzAWBfYKI2dH11mQUAN/j6y/P6MitirrrM+S9///xv//rz89OLqJ/i8PF4HGIipmaWW9WuIEQ07igNhpsoqNcDde+cscTokUMKUwpDFDD/3YdTzfndFJc116YOHgQ/3h3HGAdm4JbI1GwE6JZvbkaA4n1Gxk6LCpJOB2lASPRY19cros3Waw5HkoHG45RSQkACH4JMURKzEE7H0cahZ1D2i8dCAsZtI/d3A4482vvRHBGomfdtrZsmggPTIFDXZVuWXGptN1oWigQKw3B/f/r08f3Hj+/fvb8/Hg5pSDtyvC9JEQWJArN0I4Hj8TBOx5jGr48v//75+tozEqEEEiEHMTMCCMzM1B0noXepG7tEnqYkchwTABamWmpkSkJJpK8q2Z3dCXY2HJnVbb1am+cXIyxuKPF0+jCNpyiDSLxd0v1u6RMbApgpERBjZ2LmXJcll1arllKWmuea51a2j5/+YZrubk/HDdV3vJlE7Xdcl59oqzXnvC7edDfr2rbr0+Pl4eH5188vD1+Xl6d8vXje0No+voSIzB2IfjWa6pSjfk+7O+wNfTNVd6MgYRjG5f2oJQUkIa2eiy6lltbNNJEZWXj3B2DWpm/55a1a2VrNrZVmTXt1R4C+vKtN13XN11qrOnhnuuZacin7nDOkejoI4BBDTDK8O314fw/dzppgCCHnPHTzCEQmvD9Ov//hg4icr+u85qeXeQ/f7PjjzXrutwV8N8d48x9ue8hv1d12NkpzKWQYQ3RnQMd9IxAkxJhCTBIisiGpuxGThNApYg7ExHBbwBDuE1I/myhKGJOESFEEcRyGrgtIMUzDMKaUJHAwTGqEFDhJEKBhUFMPIRIxMiPv4TQQJILEIcQxQvmWQhREiMZamQCsVdeG5jHEyBIRUdVM1ayCNrJGpg621wS60dSQkIkbuSIZI9xo00TAgEyEEFyruircUmp7HhF0lAD6Y08xhhC4SzQ7safk4g0YBZE60aTVBm7d3f+/Lu3Y18uvpd2RGEPEmEIKaaAgbvVSTLf5oWwrIYFrlOLu3kptDMDbDOsFa35Sh8fHh8dfv2jdENQVzOmKF6IvElNIQxyPcZjGcYohEWEaR1VDYldrtYqQuq/WNncwvZzPXz//er1cai3vv36ar9c//vEff/jhh6eHr89PDyFIivffqom5aqslo4EGpCApgSAaAKKCGxiQkYMz43BIwgzW3GtklhimNByG8XAYphQCeiFMjCNjAwPwiDARRsJAmEQOKb07HPTOGZkRA+G7w+F+OuTWtk3vh1ynNg3D/TjGGIRQDRo4mGmzmhsBNdDS2paL95isN6UdSXqClYGpVmultWpu+/EcEzmzE3EgKtQDhJmBiG9f++HvQDtvCVtrtm5ty7U2BwNCV+1bH0RiEg4hWEpDiimmFIYUUorW1B0JgzmBApoHMiEAgr6+dFPQFhgCswd+FSOa2b/8r39nhOze+d/XeY1K74djYh4lhCjO0NBbH526kz7eAsC7y7Ht/v0RJaJQM881qQWiyGEUGZnSFP/3nz58moalk56bAYAIffpw//EwRoUBtHk1U1EJitjIGpo1L2a1oXuPY3bDpjawKftbOcm65p///vA0xYeXFFOQIIIYAI5ER6IJcbhtj6k7PPQL0IMgGY25BTYRDIwSkFmBskPV0rYNS3mu7atqbHZd1ufr/PU6P1zXay5bUw58R6N5D7VmZup57wCwu0wAeq9GCMiAgClFskN5d7/O75vCv/96fb2zti2vaw6yZz93RmfvnbooCtVaLk1K3UodSi3F3XMu27Zu2+KmKfRSKIFRdlOjGMcDh9RjRHPZtpbXVjAEIQ/kgQERzQ0Noe8wTdmZqrubtoboxKhViCTnuizbVtatrPP8vM7Pphmsnu4+vpZ2uPHp4bYVAwMDN23aWsnrOs/z89P1+amuW922mrd8vV4eHi6PD+fHh/nyUrZFaybTQAgpUmAYGWMAos7EQ/PeQ3M3e8MebK5eihX1HozHDqhiWfKV1pGYtmLn6/br4/O8biGmIQ3jOMQYq4QQQozxN7qx8+MZS2o552XLy9ZKa0GqaWmt1FpK2dZtWbZWWj+ZDczNe/uIhENMQ0hChKaCnGIYxiGOqfsDoNq5toB9YoVOQBlTGFIy88B8QxZhlyu8Noo3f5Od02m6O3Pts/u+h3x9mfmyLANToKHrackc1BiAOSSWSJxCGFOSGEMMpIqEbopEzMiMItQtiLB/ZzNwAwTzXXKNTBSZgpCwOHQ1ShBOIkOMKUhk4iCg0RhBSCQwkAzJmpOIEwISMocoaQgYQ7RKkeF7aSghITN6IAdUDyhgPkqIMREJKtzsv14dkjobDRGDELugq2NURo1oic3Au41JU0cg3w3oHBIguoLBjYCF3uWg5u6tORboKQbCjIHA0RVaUXfvYu+eZmRNu7Pnb+6r307t+4rdbzpypJ0DHYNIQ9vKmquXbX6ptYqICIZopl6LtdbMaLm+hKDI1Fp9fDq/PDwjuDADkBv2YPFOqeA0xeEwne6Px/vD8TiksWN1WrObogUnMlcwc9Pr9fr09Pjy/Jy3db7O21ZardbKw9fPL8+Px+Pp/v61tIOqaTProg9XYR4TC2Ez7Bt0ARYUJEiJp+M4jqmWXMsWYkhDHNM4pTSkGAOi1oCQCEaChk7gTnggjASR6RD54+n4jz98vIujECMAo//44fTp/riW2tS0qDgNMR6nkQIBeSMjk1EkU2MA11fNmeFvAtsREeVmnwmOiqC7ywMyiIAEcHY1ZO7sSSQiAO8DPd5Me2F3H9pVTta0eCtbaxXR0KFrrMCUUQMbCAZg1rAdYrBhnFKMcZ/aKZhTUUC3AMrojqhqtaipEnsMPKRQB/lW2t3/8ufP1moGAKIoAQEHDIcxpiDMCD3eqIdLvDJY+5LSO1Vxd8ggpIickLGZlSKtsVlCTMSRkIOET/ef7o/VvKlX3Uv7EMIUAy45QjOvO2KhhEbe0BU1q7eG7syMUax6cx8ZIRK/qe216ctlXvL6PBMwOLkgJoAT4B3CEXFCECRGIOuNFHa2HiAZIQ4x3B3D6RCmUcZEIVaWBWhpdZ0v9Xyx84xLprWtuV62+rTmp62sqg1gmiKnWmrTPhTddNAdKd3LXH9e+9hAwEyU4jQOp8PxMn233G21taKBwm2Xh4TOgmkIY6CRICARShimOBwkjSix5Hxdy2XZ5nXLpam7IEURQWDyKJLG4fjuXRoPy3Kdl4tumUEZGwIwZIbMWBnFwdyg+yUAAILgPgdXB3cnc3VsreRW1rIt23qZz4/z9QmsIqi2b/YVO4MawA2gZ171BLaSy7at83W5nl8eHy9Pj9s8b8ucl2W7XuaHh/n5abmet21VaIAewBFZSJQdBUzAGMHAFXriFhEi77iYq2JDJwVkJzcFJwLBBtZa5bwRh7zV68v16+dfztf1dHeP9+/GmASZHMiB8fswK4DLy8VWtta01LJWc6tq0lqppdZOJwcCIzCHjlULdAY2AhEdhnQchiTSYfxB6DjG6TghuDXTXFfCSBSJEktkJncw3Z2R8Tuo/XaH4JsvuDEOdjP5Hl3S6Qdva4mZXdfVQ0gpeddDKEBTNojEETk4DsRjjL2amLG0ZsZEkIKIiEYD4Ni5ke4OCEyAjozEANTjqHtqD6NDjBKFAmMTTkGicCcEWRQjcCEWRmCMgdhB2AmdEPfvwxg4GBPzN7j326mLzIJABJLiUZDGGO9Opykmz63WhtYQDFEB0E270I0oAAUnMkYQY1ARiJHMDVprRav3u5wYiBBiqA6tWlWwPWunH37UeaANK5Ta+cIR90RdISQza7V0u4Xuq9Y5Xv49efm70r7z4Ts5vjNK0DuJnwi0bZutWM29zUszoxCDIyYmcy8VuqVG0bxsRRgI9HJZr5dCRClRCMAM1FuHLj5ZW97W5Xo9D893d3fH42kaxyChR4+1NIhE6gtYd0SWOIQ0NLUtl19/+XsgCujn8/N8Paf0La8dHLSBGzJyYhpjOgzDaZLA2BQkDCEOVmmLliIfT/HufjocB22t1ipMgYlZgkhKIuQtO5kmtAndwAIZI90xJvcRaZhG+pHi/x/XJRMRuiPYcQx3x+GSN0k4DfLhfuxZBcDoCFBj3ZIQjIGNSRG5ATZA7qj/t8e+83X6TEVMwkiJIYmK1NoMqSGoaeucgR2cdGvVWw9+3sH6Xp4InBwQjNzcq1lBqwANVKFmqIXBGSxBc6oeWptg+jiU6SgxhRDYnR2QpPf36EbOnRBYq60F1IUYRCREOWP8Zkfn/nKdXRtGkRgJIDARc++h97yRnh7Qsyi6GgEAHHqv0qFXuTX0DO7WrBbKGVWxNup+w0JxigI4IFkPEe0knk7K8kZojArQ0z8ZQF5XqWBG4FFIokBXXQEP4n95U9pFeJpSc11rWbeyaUWEADihTwQTwkgYkQKRONGt/dabkGiajj9weD+cDjgOcuI0riEsQEt+/HV7uD5eti8PeNlorrnoXO1S26VqBXfG6prGeL1c5vN5u17rutpUQEdget0L79JVeOXBem+UhIi/bxmZQuAukA4iuw5wHNKHTx/en8YpcmBBCofTu/uPn4ZxRKYvX359/np5XNvLZi/ztszbh9PpkEbwZrUZMxIM03C4uwMmR+DIBxucTaKMwxRTZDbCiuhVa15nABhSGjhFQSNvoEAogsgI4K5WRQPVQC2xK7O6mhm+WfSq+1q0b9dba+jaSq7rtszX5XpZri/z+eX68jJfXrZl3ta15q2sS3l5yfO1tg2oUSAkYEBEbG6aizlYZkUyd1ATgNg3TkFcqCmiGWoDMwdXIkMCFpfQUNQJDFFNSytb3pa15BIk3N29+93vfn863Tk4M4UQaqtfvzy+YchvUK+g5s3UDAhVrZRGa9VqUxg+3t3VMGiXTPmt+hB2MdMQw2FIKQRBCogRKQEk7w+5dqvYIDKleJzGKaVayvnlbGrr1lppPYVEHXoSzE76g53Uvg/osFsa3RytVE3JvjnYAIC5L9vmAEmNHR3FDa00aCoOrMZVo+Nhv/UCuLswuDPRMCQRSRQc+TgN45C8E5SbIjgxoJAzu9khBhGJREpWqc9p0GlS/d+BvMd6OHdSoLt0MkMfFBwRCIzRkTEg4y2Z8E2PoqYKwEgpjinKdHc83R9Pn47TSLReLtfLVbctl+Ld7qQBgAUSgODAbWexAziCJJlGN7WSI7aGik2bmdcu3EDm4AQIugdXMCGhOalqa9XMWq0FyQ0Qqdv5m4M205Z7g6XdRhSx57b/l6W9Xzu37mYF4MAAhLCrtrRpzdUUgBAHConDyALIGc36XzHwUmttObIG0rzVnJUZkZwYWLAnPXaNsKqrZvN1Wxdv2VsBPcYYa1F3FBlCSikNIcZutpKGcajNHLZ5vVyujw9fpyGu27ytc2v3b94HkotgSJwSU5I0SBxYImMD7+mogViQI8tBwkQ0gBthIGEzMvNajJsZK4PmYrWANnJFUzYTRna3XDHXQ7QhhMP7Uz2OnTGHZkjg5A0skg2J3EPXDxoAAMVABw8wDtF9AV/djMUFkAm+L+3uZq2ZNjcFcEAEb4i7fWeupW0zKVip1s3pa4GSbVs8b7jOdBi6hbxpVUM3Y3TxRla8FchZc2ZoDA3rijV30JFqpdaYEUO7PwUdRyNB5AguCHtcJgAYmvY8OSgN1wg9JqB/FRPIb54WdEBngsAYhaJID/a75frtVtHo+0b9NoAi3pIImbBLrsFRGBHdTb0WaIraXiUHxETEwJ1fCOiAZlq6WaExOjGg3YYgdAVXtVqqtuZqBCYEkckFApFGlDcuZsw0TcNS8rKVudRzXgFACK/kiWFkHIQnCQNSQCSHWluudaulqTLRe8Sh6R1KCNOYTjwcTCIBZFqei325bpfniz3PtLRSbGu+qW3qRsCBiH1dt3VZ1uslz9eyzO1wsjQSBGQBuNkw78Tu3eath3rsuVJvXinGMQ1jGoYUgwQidLVpHI+n++P9IUUmFqDAhzuc7jRGM7tU/Hot56zZaW1+zeU4GhC7areNq6rVtLk3B0NmCYEoDhyTBAmErK5ohdnVitUFwSmAOAZER0OqgMRdTwoorJHNAoAyjolN80allLcW8ap2Xtau7/Ky2bbk+bpdL9fzy/VyXq7n5XpZ5+u6XHPeSsmtZs3Zltnq5t5QgBOzcABEda1Wc8mlFcSKZO6oFhAH5hhDSGZCSojupMqtYVMDMiQDQidSCM21GnJrWy7bVnKxpkQ8DOPxeHc63XczcGKC743u1WrzjEBIcPN+cK2mpUGzyOGYRkMx3bV34LYrC9zdLQhHpk4LFaSBZUCO5rk1LT1+DELkaRpOh/EwDG6+rplJtqK7JbZ2T4RumGO77O1V4b6v4ffaQN3wxfS3U7v7pTYMekBKJIDBFMqyoSwkF8iusjVTtAbWY0137QcjCaCIRXMXx1qscMeowQzBEYkUwFpQGwEFMJqpW2NIhIHAGAfhxBjYwSAIGqExgaAjYkB0Qul218AIkWkQMuGohK9o5rfSbg0USZgihbs4vj/cf3r3/v27u2kg4Pis/LKdrwir16JtbdqBq8TG2gBRAZohIgOFgeLRtJEJWw3WzKtZaa2pNxBkEUN3AGJ4ZYKSdxHVvrlXNUQFNNfOPEUFb9p8D3137VkgaO2/yWu/4fx78wa72GM/MglEOMbIIQyT3BMfOCTC6n6GrcXGICSA6JVgFdgYNmEDqDsfxcDUVb21PlNg92xhAGYnrKZryVjLusy5ZDXHENPpdHc4HsfD5IBpHNXdANVR3Yvq+XKpdWtN32IRCHCQEcVcdCAMGFHFCwI4qWNVC1W31pq1pVa1+TJvZKZmzbApdLMAoTiFMDKzLcu25jo3vdZWqnIgyfVyXk9yGaDG6vdrtla7EQC6L6091/owz3+b53PVvBtku7mT43tKdxAOBkisWlZXCRhjcOk8tjfPfM1lfW611FJad7fd1rYutZWmLT8/2vkpEgciAyZ3uV70fNbl6qUwOo2Dl1pKXta1NEeSgXSEwtsTzI+1tLXhJD6IYtu85grUDGzboJU4pGEQDmYSVoWqLmDS/Wl3GyloBqbg7s2xd20OpEZmWN8ufRDff7xDrQAWmKcYmKVjyh0don2B5+hO+x4LuidWHxx2b26CTkdKKcQkJAigZtVBd+AeyZ1c0X1fPJMDO6AiGSAQU2AGcobAEGIhrubblufrCmVjb60AB0QIUSSCAH4HyDNxSqm6c63grA0BgZAqIQpyEhkSToeYpojizdd5nufrs+qmjchM/HeJdQw0DjKMIY0ZAzRrxqviRf1BLd/007WZVlBzJowAtbXWqpaseWvrXJdrma8lJJwOe7V7U9rxJoDtene17z31AI7TCHrspT3G0LGQIUVE2HLZiqlDM4KnK39+lBCJ6MuXL5+/PiFSGg9xrTxvTtyDF4w4N6vL2h6enta2rbnmTKRRYPTohhaQyM2AmCEgugmBm1vLrbqQmXurpfuOEQkSo2og5yGOkQ8xrWk6ny/X6/wWfqit/fr4HIUCQT2/rI9f1uen9fJynS/zMue81rKVkkvJTVvTZrVaLWgVXQlBpIvGRBy9aCslZ71oWR0KdNqqRcRBOEUNRS2IMpG7mEmrrM2RjUVRgdArorHwGqrl61zm1Zp2X7xa25aLbFlbMzcEr/W7vHYSkMAxREbWatqs20ixoRmiujeDpqANe8ztHp0MHR5Xk9qbO0YmPqRhkhictq3ldVVEdZMUptN0PE6HaYwpIrM61M7hbK21ashqar6nuPrNraOPBv1Hvlb31/n+LY3OAVbwQFhiCDGRpFZL2a6XWfEpRx4SB2A0QQzCItRpmICCFJhZxJghhXx+4XHAwEjEQEIURISFmdE8NZPgEbd9uU0Q3AHRokShgVCEGEQJjcmFFdEiu0MQFPKAMArDmGId8iK4ETuhfm/DDG7g4OQe0Ydi46bDqkPjI4xBLEY4BLwyLX6dtV6bEZONcYqAzWuwkhWNDRFFxPfIbzY0IOtTUbeKJ0J0QdQeywnwaqHigCidqSqBeu4RgCMwUQiyC10N1FzNte3Te63/dahrl3A2t7onzjnvl48AuyFA5BDjeCfjDxxPTGK21mrqLVjAxgoIXsgDO5EZ0taPaHc0I1VoDV9TZW/rhd2jT7XmvJrB5bIsS65FQ4h5W0vZ1N6lYYppQBEMEfuGFuEyL6qlqb49vAjpw3Q/QOCMoo2UdGnrWtUUmnGIOLZWwYtp03JWbZu37M2sGdYKqg3BAsVjSncx3aXslpuv6tdqWzVGiM2WbOulpNLC1mzdrNaeLo/u11Iftvzrsvx9Xq4AVRhFiKnW6k1dGnEix91lEJpLIGbS3cnj9Y20uq3Xp9Zaq63UWmq1kr1kq01bLSWrNRSmmGg4sruvCzx+ta9foFY5HPjjx7otBeDr14dlqw50CPA+WFwf4PLLudjFAo+CB2ItVrMpbQ3asmAt5FPkkQURqFbbqjZ3QQgCgFAVavPW/WNV1XtenJs1NWwGs0Q4fLvKH9/dgeZtXcAhCCJh1R18h5uPB9ycPWjn+vc7wwmdiYSJhZk5BElDHIMERkN3125BigBooM3cHRh8t+l3V4NWsVmnUDqSoRNxNz5qqvO6vbxcgusYUDvnYI+721MT3vYoHddwQ22g1SXszW4cJAxBxiTTkeJoBhXaSvmKfEbaEBnhQJAZVQgCcxCRICDUmjtWg83har50ix41beYKqBC4z8Y969XJHVShVstZ86bd8gFeT4a+wHZ0tNZqqSXnnLfyvdrqMA5o09hDckSIEByYSVubtdRWStWtWlaoDYhZWC6X69PT0zAMiGhmgNjU5q2QV21FzWzZnrNiONeirhYEh8SH0rYhhFvwubDE2F59ItRaa1g7hqfNHVzJqAGiqrlqZwQKc+S+VJW38ENt7fHxMTAEtO3xy+WXn9fnx/VyXvOy1txaa7p7e92oZwqmZMY3j0thEhHxDrFDrbqWdlXLjr20J0IVUYUI6E4mxP0oq05VgQGcWo+nbU4Kgbm1luel5c1bc8eW8zpfLy/PWmtraqZgqvbddMVCIXJKUShUqg2aNiN3MNdmOdd12yznbhvQS+0tXbtHADkgOSEIdTmcVoWi67xdr4tHbmAh8GEaxhRDYCJ2wGb782tqqmoI2lprjYiZm1AzYXeG/Ue+8ufNVJVaa0zEb/PrHLEKW0p0PNB04BBqqXnZstZGNYAkJ4yEkbpUsc8kDCSOPRqHgkAKOA0wRAiCPXOsW8wwhxumYxJxGIypkWsMlpIiVYOevG4A6jvObMLIxGqAhHlzZSoltNYjX9W7Ug3QvsO0zPp3YAVxFVLaKuQK2ThhVAGL5Ik9BwjsjI7G5EM6DGhNV1Hg7mKKSIT7MtxhF/G9mgM4IvQoXtU9z8PRfOc8A3R5DYddMAnuZgpAXZVixmbWmqtqU9XWG/n/urQbeHXLrsUUANiY3GRv1RCBHcUouiSKE8cRAcgqeZBIwQdsDLuJbgNjA+ywJyIZiLuYoTZvZTc634PIAN2wMVQyt9ZUt5y3bSu55m1rrdRWmtq7D/ju42EIx+lowzBKCNv1uqyLab2dabdHhegfP/40p2vMVOcrrWXeLnV+lpyleTpM8d2phhFR/Jrzy0zrgnm12rx1YpU1RAuMdwN+nAKxD6zOFXh1XBTZ8OBUMWzGT9emL9tyvtYtm7YuhJ2bPtb297w9bGVl0kRplBDjvLTtWoyhsBFgA3+2ehXrNqC19pb82zspOV/Pz1pbra3/w1uD1jADVJXaxFowEyRK4AjQGqwrPr9gbYEYtm29XJ4uL//2pz89vVxq83eH4ffvprHNuDxfq12N6f3xLh3IsCldGl6KbxmgeE3YCnKDqva8tCUrGQhiFEC00rw11z4NtZ4Z5tbUarXq2tzeA/zvf7gVRPhwOnjlr2XNpVXtuTOtmd3YpoC3nhXACVEEA5EwBiIhDMyRmREFMQZJEgeRwFB6EQNHcDanqrYVcOAUkQnVvTXPxVXBrfs6Nm1WGwuwcVUortfr8vj0cowSj8PupOdN3T0AMr/13jGzUlrZSllLW6ttGiXdxcM4DcMhxkFilEBSi27zNl+3y7pcylaaGRKiG+A+R1sDUEZncEFndEQwAL3pqtTQDXvjYz1mF8mRJcRhGIcYAzG5e2mNs+lvpEpdCkZaa97WZbmeLy/zfHk7YI0poqXUTYA6lQMQwMq61Ja3LW+5LLkuW523Yo6I1Fqrpa7C1+enPjJc57mV6lpVi5oZuNGLoZghAQ9RhiGMQ0yReZe0YwhhSDHGnodA6FDNqDVCwC5Ed9da1KyUWmpTczOv1UrWbVm1fufpr7VeHz4TGHhZHn49f/65XM51W7LVso8xfcDsRHpyd3ACIzTs5Ls9mtGhpzg1g6pWqmZ1NUMzYAoAGsQdCJlCZEA2xVbtNVUJwNyrtk1VGEIrOZdWi2k29e36cnkIpC2l8Tb9GhDyeHg1OmTkQCLIDOzdiBmquzeztdan+fr48qI5s1sQ5r5pAoBuG+fgRHATPl+W9Ul4ZSGHp8v1eV3CECCQIE0xMIFpa8bVGdRq3xDsy1GvtSKS9TAeN2SQJOi094r72zXdOZxu7mN7U0sIeZri/d3h0w/TdNBmuK6g4FUdqrZSqjmqsXbejEtAln2zXxXUmRhFfEyagjJbl24wUwjCJA7S58s+4gdugTGwxOAcnEMUToFY9saZWSAIBDFiFCl5M6L69OLXGW2DbdV10W3z8fAbGp0bqpETdu0PUa11q3Xd8shM61Kvmy0FqhFQkDCEUGOEIR4G0Boci5GogjlAM63bVXtwBthNQU1dyCQkRKSuaM3MHAx3/7ybUYlwilFEesS5Kja0bl9mQVQVwNyba3NVV4P/Zteu7s2tmhVTABSzYH3/AjsJ4aaBBkQiIDTHns8pyKkpcVNrasrQqHdL3WEUd78XAhBEQydEEBZm6t8NgFXR3fZQGAAgMsfadNtKWNbxUFyNEzBzCCxM6r6VCuCB5Y3VNyDiSYaY3E81A/G66mXJj1u5XkM1uDPCAMfAMcBmds5wWXFdvCpoN4Z3d0BmUuAg+NEwBUdS5AKUwYJTA24ks8Pzmi8v89PjZVuzdlm6eXaf1Z5aPddWY0DCNKUYDgvUrSxPVjZURHKElawZpupE0LJ+48n00l7K5VxMzV5hMnNQF3N2GKl73JFIoBS9tUKIqroVbC00JTWttWhZr+f55bnUJu14FWheYLOl6ua+ZV2Lo0EpMDdfim8ZrJDMZlbBrVQ9z2XNDZqTgzAhYG3emlvtk5F3Ho7V5qW4ujdkOAyvlwNgCsnQhSWjNlM3b7rjxNRvJOgbJiDErmYJhMIUkCJx6GYT7uIQHYNDcEDv1v0IgOjADqLmtbg5k6MRmFtplrOpIaG21mptrZlrAI6I1b1WzblsW04I7kBITKRFuy888fekU3f0RqBMHhgG4VFkEhlFEgdGIketTWubl2Ve11yLmXZLGWGXvknb71BERgEahCeRMYQh7M4/fltg7cS4zgJUKA1qI1VyYwBCA1BruUJRbWptb9/73hQAaq3ben14evj18+fneXt1GkGAFANoEN59rrq7q7u2VrVUb81VQdVbtZL7urY3BrXVum3dRTHnLW+b7giymbsiGTCCMEVtset/S2FhEqEgFEO3nYruEUA6WYsQkpDs9Atk06bgQu4I1azr0UvT2qx+t9zVkp9/+dm9ueX1+WF++FXzYtoagiLa7jeD/w9ff9YlR5Kkh4KyqaqZu8cCJLKyFlaTnHvPnHmc//9XZuY22d3Fyg1AhC9mpqqyzIOaBwLJS8ZB5SkgE0C4u6mKyCffEgC73WowMCIbqiPYGyt8N5COsHC1gd27eVCEEeieeDzy6XZroHEUiZBwBOqgm3f32snQuzbz7q6qti3XC6L3moczXQREcEpPfzu8IRBZ8pTnJIWQ0Sg4THXQ1Zr267p+uV7qsqB7yUl4FyruJqyEKVsOQO3QOUKttUkSA162balNtFMibYoBvbWrWdWeakqSa9Xah89/3KEzdzdXVW6m4lYYBd/4vIgAZGa9a+/GtR2fGGC/eIloejxNjw/5dKJc+m3bR9UIisCuuLWIFtgHP5ZzKbmkIHb0TaOZAKKIzQVLduEgckAjosQGOGx+E4QiAZEV0SmHEDCHpJCSGDPjcJEtJIkEE4Ows0ASKwkwzq+3ZVmAu+rV2wqu1hXJIL4temxkuaIGdpMVnLfES5HlNoXD9dYu13q51XWrrTcwy5zmLIdyyNFh3QzRY1CGwN2i9x2VuNuXDbLZkKsxIdmOut1pR3fnPkLhXRGAiOGmGOAc4gAOCG7WGysqQozR5X/HkI+36m6Ow119fO4DUseA0DAPTaArCYkY0eZiLslQ1MkUtbE27BVdkQmzEAAw69jXp8REBQCJaCpZRJqque0W4wHDRrjMKRXczVhTDuDe+rZcwzcAXy/X5fKyLUvrnlKiVIi/hd6ER78uHPHD6RHLzLWu3V5++aK6SVPpmGz3m4VBz3MiI3BHoMwkDNbDFZNiVsxBNtAFokAK5NE7KuHZ/fe6/rxcfr6dl7Wa+QgJcHD3cVkAAiTkw3R4fvrQu16vt2XdLq0G7ekBghLu3kCr3a/le2mv/ew63OdTmVLK2prDRtaL6yFNRQhEcJr56dFrW0tBYWUC21PmsshB+PnhES2063E6TPlAJirBoHMEmqzXcLPevBq4BTbETstrb+dmqr32ura2NevmajCcvg1c3buahvndyyIMvQMwYM61f/dceSBgzqWOxs88whFhmEEnJiEUxFHOM3Nh5qEABRJEcSAIUmMP6S4OPGeAkfpOEIiBApAB0MNMo4cbhqOPFLuICKytLeui5sF0SBOVbK6uBh6DvAJAlCSVrLqFdnQnEnzv+8sxFQ/CEMY0lZVLksyGWnVVbaPNH3djJ7KcYRzEwCCEY5qKFJFMLEACJInTI8mH+fDD8eH1cDofDm2pVWrQTnjHADdQgHXz681eL/p61tvqvQ+rJPTae7f1eluu1/V2W5Zl3dattaZWtbW2XG7nl9cXBUnP//I22ydhFxnpOKPYwN0yLKWcJE0TnDwear+u27rVujU1e4uAGzPjyB0ZIYHj5ickJmRiEc6JhYarp5QsOfHYSgkTQphp7zEWz0yIJNNUZE9mu68F1Wrr29av1w19a1vbH7X7V6/bb//+e4C6N91uertgOA0kkDl8V/ggkCRhZpBAVlAAD/RGw9ocY1gCGIaO+NrQ2Jkbu0GVhXcz6y0AGUJNuXV2R2AiZLj7dw7+CaKhGbiGd9NtWxnAtSXmYRIVAGmanuJf3pCWeZofjg9EAkEtmlu02mIY4blufXtdbueXs2oXEeYhKwFCFEQhnspUpm3EVVyu0+thnnNOLAZhHtE3d+vaW2/qam4BiMw5TWZwXtZuNqj7JUvOiWjYlmtEN2tEiMCDbOWUnKOr1drMVvd4/nQCOOylnfn5w/PheASmprbU1tUIWRgxRNDTaFPRMVzCH6k8JS4gYuiKYcSAyOJp6mVqWTqzj6aCkc1Fm1gXMwBzIkXsEgphptrD0Bq4gXVEAbKg7AgYBmBESugcPexyWWvv6YgyAbOmxKq9xxZxeDsdptq3bVRDQPNklwhGnPKk3V/Py8vr7Xy5bVt1t8R0nPIpy6EUVqi7qVDfO79wHiYOMKhFYzqzCANQDKAgHOQgBNqPEA7l6vAtEBaRBBEOQOjMAmlE7lp4mHqYRzcHs90M/X9Z2sN3A/qd3+T7Xt8hnNlFrEibE5zS5ymtLIGg7i0ogZAa9daVqvGyxuatZfFDJoNAMSJFRCGWlBCQiIauGRh0H76GOpclBJmAdqMFQgyE3nVdrwiSBLwvfV1clVkkz2k6cPpmn4uI05SKpDIdWM3O15evL1dK7owjARiJcKiG9lc40IchUUuZuplZJMAEJIg8OlbcPRfv6xLUiGtvX+v267ZetvqGUwEAQkhQQhJz3rchNpShzW2zHoFEPhNNiaeUmFlZO9j7tU+3ADMRSFmAElIxMDVgVdCWCCdgYEKiLMk8nNmQh2EhI3CEdDswfZJyyLNCz0hTM1drFUQ9zLAty2Uz1dZ7t+gaY+5s7mFm2rWptW6tax+LPPBACHANV3MDi+HMTzCuR5JgjK6ndy/EzRhgytnct03NnYGIRm/DmSkjCmJiTESJKRMPYJIBOXayxt37L9ic9jkKA2jPAR3MI/Po2k0VMBxUXZsCIibu5lV1M1MQIj7OE7aGsBICIXqEugESiwixQ2d1dsXvGGgBrAyeAQ7AKJGICgeTDXlmjPnOPWOkzEgJiZB5WNc8H0+P0yGThHltDWg1Ug1A1yI8z9PheLjeVl42a+5kow5EhAbU6rdFX17W3z9fPv2wfvyhH58CBqcsurXWl2U9n6/n1/P58nK9fL3crtuytfW23a7LLR0e/svTv3wnq4T9W92zQGIM0ESEhJQCHYA5IYlwylzVbIDcZjauBDNT5xjxlYjD6otZRLJwTpKTpJxlymma0vDDHUq90QIQMQkRCQ5msIxMxCGFGPlPXmpP0kbI6brw+r1Bmplu1xfzbt6hV+wqw8SWhFmY0H0kUuMw3yUGQIrUoguSsXhiEkECBIHEkBkKgwWloS4mTAiZkCHAzbtGILiHdXKlAEFMRI5oCBGO4CLB4uQjr25EdmqtFdyMCe/CtUDYacqjZSQRTogcHjCYCCN11A0BWBgZN9Nl3YCGp7AjBgIIkhCVPOWyBmJEzCUfp5JTSiJIBAiq3VSJYNjudutrbWqRJCNI79F7mMeUy8Pj8XQ6iSRmIt4V9DGsId0CgJg4ZLwfpoNd/y2PhBBPx8M0FUQ030PFhic1AwliHl5oaAguiDPHUbA4iI/Xs3NnjYmyQCkoYsPZAyH1nlFTYHIEDAWMlP3hoYtU981j1QjvFCYBBaLUlqsOPV9HQIiKZtb1uqoptZSeU37IksjCzHoMRc44G+HoitHGpQIortYVWnckvS3r9XK5vJ7ruhEETSLpKJHQqveqvfZetTeIQBFGyoIaw0zDIzRCIXR0khAehuAtYlz7wzGU+J6UsuM6u2KBkJgpQAACPEJYSs5hHhrgERb0vfLiDzS64UMXHvv+7248ZAggbIdiz8f6/FCfHnrJxUHMQc2QWNJrV7hpt6QgnX31benZfI4eYOiAioBD0nyvwephSMYYiEhAiMJOgcghmA8sBUXCzNraVNfllqWcpikTgCkj5+mU59N0OKb0BgADMf34lz8dpul4ONmynSEuORmhEoFwJA5hJzCwcCXraEq7ygKIiYQiuWG4IAowIdNOBNyNoyMQgAMFQDzILHp31bG4sKEMBYgwigDtsMHr60t1v1wva2vqtjOeAkvih3n68HAadKbWjd+prTyg7583A5B6bLVvyxrrLdVVXZ2Qj6eEVB6e3GELZEAb5yQAm9J5OSb5qUMz7BrYKi+b9t63rbfaWw/TRa3vjIboY8w13VMxzN09zGJPtx0hmzgiQcPcgxzGDmMIuVE9FL+brgJAtTPHsaREsEQNtASYkIQpEWWkhMAB7ECA7MDow98D6M0fa/jvBBKRIBA6giM57qZsbh6O2CNW72Hd3Ry6Wu1GSTKRAwVSc7tVm1H4cEJe5baMN9xUW+vqDsRFkrBj9+jx3a4dvIf26IaKYpkiU0wMSUiIATgcVM3UkXAw/nLOuZRSck75OM3Ph2NG6lu92Mv1tjSgxeN8u3VXSlyOcznNeV29mVZ3HcMgekDvsaz6+cv5nz9//uHTpx9+uj25PyZJw49sW21LVpNuslFY3T7//tuvX7+e19t1W26tPn7o/+X/9e2YDwa+m0HcLVnw7rBzVzO7D6NCzCI4jdOKPpJaR+zH0C3skX6E98xiGTJwFqYkzDnJVCRnHv6t7mN3L/ffPNwc2CE0jCyQJDEjAgQhCACYujZdclrTiFf51p8Eg0eoKwFkYkEaESCYcwCawwjEE0IhECIMNkZnFGTJlDNJJgrqRpbJC0Oko4e/eZ1GoAUioYeruQO6gXVCF6bCVIQDyGlsNWLKSAV7YGIQRHTy8T2QWexYDCCFfQecjjx4AHeP3puqalNVZSEhfDgdHx8fvr5er2vt2s3HBGERNqJTmDdiGVd1Zikp3Y3wISBU1d3nUqYp55TM/cvLy3VZGRNTZirMOeV0fHz8+OnDn/706XiYU07EcLttX79e16X13mJnLCCLpJyKlTv96tvHQYhTSpmJwANRRIzZ7uWJICQcwQMMKYQpi2d28SAPNHMbJjeo6ErQhXoWHz2GezafkGaiwoEIloQfH/Pf/tZSvvV+qe1cm1sj7yfhR+R8XjlWNsNwBWjhFekGkUHWCEFKLDlLZKkG/Q84NsXEQwbvjoHCpRxSPgFPFtS7tVb7ttq2AjiAYHFfbTu36LXeXtt27b3R6HNTSszV1HtT17AO3hGUUAUVbZA1NMDHvUZIQsOrDgfrx9TGNL+rWIkpwNDdHAFTyjAcuYEJOKX03Qv5rrSP8RzCIRDQ78uhCPMx2QZGKKPOyaa8dU3VUS2E6WGS2r1tze0u1NEWg70ZsSdIAI4qNf7UEU48uP5EY3OEAEjIQIk5ISdENnB3aKo3V4JObtfrutXmMElhRHLz90A2Ef30tz8f53meDsvLZT1fYi46TXUqppSzRCKgXdgx1ky82/cOP0C3QVEg2HVXsMsC910IAAIQoABkhDQEmuGjjMW9ugMSBWB4mK7rrbrV1twMAca1IQinqfz4/PDXn344ztOXl/Nam8g7dxG8r7hip3d11do6bhsuV2ybg8/WSAiWDwhM6rt+blAxW4+vLwQ4vXyR263VzVVB1XvH3rE36N26qVpTa+Zdvaub6VCs3rUvAOEBYYPPRRxIHmQB5tEBOroBGoxZBAf89Z2GDwDDOCARCjMxh0AOTIiMmABSBAeOrR2NQAiIsVCM3fUScTQrw1WaaGBLHrD7Xu0iHQs1VCcPDCAPb163jhaYJQCIaGv9t+sa8zw/Pc64Fylwt4iuOqAACiJH17Bq8N2pBwAf7l3qXrsbhlIkNSHFYAjU7m5BxMLgQIEGpIiMYatX7365rcKCxI7UAFaLc6tf1vX1elm32kc+kMNYFO+CdYDRX/VutfWupj6yeoRFkGg6HkAbukKvfS2FKbTXbb3dbpe6rr3n43cMefMYq587DL8/1PvfeRdYuQMRSRKSvd10Ix0EHyZJnEag2BDn3McKSTICpRCYEIUoZxZGZAAIDxpBIUhjsTVsM8AiaBxd2nt8AJAgDxIZc0zge8MaAEQQGbAGMEACkgDWSBkFBYWDcKhLwg2rYiB2w9ZQFcRgPNhmEY5uEjEjgrA6Asvw3R0Ltp3oeXcBwojMNIkUSZlzIA8HKDNTNegjb3p4CUR4eLg5EfhuTQHu8Z0b+7Js7JdhzWR9txgb2wcRPj0cHp5O85c5Lcu2tNa7h7kbgDMSM1IomA/tqJK11gNGepV7+AhifTidgkhSJhYPUHVgh901lwxh623rrVkrkRIysnj4si7n861uHYlyEmYmoDGNE42on3dAEOKcJDMLICANhgUQD9MKRhAEoWE+4yyYCnIC9D0oewAZuBvewRCmOwsBgMGOoABMAIigBPlQDj987IeZeu/X5Xq9hVYBO83lo2TCr7A2gWAHi+iADbAEYeAtcDyonMWyWCc1wHeShcSMOQlmoRI0Yz6Wh4fp+ICc1N0CIoY5i7Mr9m5br7RcLEXXbblZ7xAwmtyci+QMrXbtGIFuGM4wdokQYD5mEHRAiTG5IAkLIoxr2NRGksjd/ZcA9mB4QBRJCEwoI68ipf9tXvv9xzud7M7hwtZlRbkgzjl+eHZEc4fesFaXJPPMSAGg67rdrtuy9XXra4O1YzeyO0kKnILHxTFEtz4WdTxiWsmQsiPBUMhoN2+u6l1dta+1Ltv5Zdlqu9yaZGG3aGvrtT1mgOfxKpjpp7/+5TjPTAIBfJztdGjPD1vbaNvKlEAYiEbsACEJckIGCgDz1npzdTBmhwh6G8FHaO8+00AABySkSXhKlBgTo4+yNMBNRAFMSMQY5KZbsxYG4jEgSQvPSB+O83/68cP/81/+8uHp9PuXr5fbWtK30s6Mexds3ZQdk5ua2a3W7bau62WJ/gwNMsntE9MMagMn3J1larXfPlvd/PffdLloayMGspk1026uHhZgARpgDjtVz8zvB2z3jomIAIdQQAtSDA3vgTW8AlSi5tHdg5GEQRKmPKdvzxUCCEAOQHceDBPCFDhkZBxAAYRA8Db/wVA27iSrIRlBHPJ3JApCC1C/c0JHK2oWgOGGEYmIEM2hq5uqo3MXZiDEdd3+8c9fz1tT9z8/PTxlCQvXcIwh6w0P0oAeXs227yjZjFAIwwmDW9XXm5o7BvCQxCFADPRnmKozCw1yuDALshAnkSFpASJHVI9qtqrder9t9bpsy3Wp16pVRysPb58DBhGkYQ8+lVQyi6AwpiQs+HASiIRArlrXx+N8mqe55NwkezKC9O7jeOvYCAl3I98B8b3xqGKXLiMCMSdiGMZX5h6OwcyppJKlJE7DaxqJEAYgJ1lEeFjRj+UNjrnIfbBlifFbzufADMgjHJBSSiQ0SNl7DJshgJvrSFN7b39GCFlcApISWXA4qVO4JC8zppwwc1eqG9TrTa+bdodmvq2hzZM7oG3OxhwYzaFp0mCnCNq/gwD3YYG884AZhy4ysYxEk4llCuLu0Zu23tpVrSpIcqCdxQ5mgR7uQaPWA8B3hBqA15fXFS3nlLMIse902UCiROl4Ojw+nR6ejpflumzL8NuPMXSI5FwQcdxOCCCITNgHo9L2SsQsRJRzPh6PWURrzyS5TMSyVd+6N20v59d//Pzz2taH0+F4mKdpul6WX3757fX1tq5tKuXhdEpJGNHMVDUiEO9OiPdOaxYWokQIgJKEEyMTeKATIybEIswTuHgI8sSUEMxj158FBoGHO967OBo7hQgPCiJgDArD0X8nkscDPD5mM0jcXN2RONLjw2mafav99y+iLuAUgeEcQRbqwMOlkwhENIkC2L3vupf2lGkucsjpiOmBp6f84YmPJ3OofQtAFsk5sSVSI299uV279QUoItQgJMmIXJnKNKdSLILGmOfAMXbRKTDMrdtQJxgAABOEj3x6JLTo7m7qiI5w3wg77CPNsGofvXTKY+VU/jehrrDDOPvLvCsZdxGJY5iCtmgtthZJ0EOYOCdIIkwZoIaZ1d6W3qrWHrVDG0wrR0QDRA/VuxGCm4XHyAOOnYk//PuJU2bJgBLmRigExmgdPXSr3o0oTZwy0vCaad9J+hBLnnOeELEc5odPH3/4+98uW8Mpv/7z5yoxYpkZKYiQ2JlV2BEdSQzYLCAI7sx+AuQ9P2M4SY+cAiEuzBPLRFyQ0p6Ouvu9DoSTGBMjMdgIbERyRt3NWCARHaf88en0158+/vTD03GS18vtyvx2e42QaXfrHuQEAm4Wbk3VWtuWrXlLmU9bg64kThGEEEIQxETkHusKyy0uZ1iuoB3MhseB3+eR2GULO8vSd5cpH/6vb4W/O7SADtAxOkYHaAENoBN0jA7ew5lSLiXPc55mmufvnqvh12MR5hQjfgEZAEdph7i/1URjK/hW1/HbT+/34U53QEAP6gZr7bxUIQ5EUIWwIEFCwtGck0d0HVQTa123dev+lQnx0w/49LBtag7E6IGt27Z16Qrm5tHD349XieiplIk8g3oFpRjqBXPvQ09sI2NsPDuD9480XkfQbulP48LCQLAINe/mzbyr1aa9dt26V4ddrg/EKEQly+Nx+vB4+Ph8eno4HIcCbkQ6E3DKOE3RapmmeSqHuTwcp8fTvHkNDlE8vLNhvhOe91XeWL857Mcvxk7Ox5O8IydjMW97vUEWkiQpiYxOZWQ5EzEijz6GOUZvPuaCkXM3+PhAEXt65Zj5wg12/st9N3A/RwPMIyZiNPDau31XFJ28jwhUCEft0d08rIrVxpkkAxEwA7lDa1ANm2Jt7j0gnNEacAQ5YndQZ4PkREBkCDjICGG7OWcwgcBYde8tJ6MwTzgdRMTzwbbFoA8HG4IGxPtd+s4CZuxOPb7Dgq7nG6oejtNhnuepDJRwRKBKooewj9r+XFcHR4bzWbZtU9XwGJbiiASBkiRLmnPOide2LnWJsPHxItJcihAVluM04cfn58fjNM/IfFna6217vdyqtl9+++1yvRwP8+EwH+a51fby9XK7ba2qmiFhFqHxtvgd8PxOPwKuHhSuHnTngBMR7PcSEyWWLGwpIiGL7PHk+xMJeJfz4f1D3mmVg2wDEXvkOACEga/gzqCJvUrMEhEhiMeJpglyQiJEoPusyuAYPg93iEGvQrQdsfru42ARoWnOh3k6cT7xfEqnA85l2doG+2DGzMCEBhDm1gy7ImTmUlKWOZdTKqc0PTDnGFU5DEaXOB5sQNj99iLe3LXj/ofTIHeN5xrcwjGIBg/jDqoPOQ/LzlhhYeaU/9eAPLw78/fj47GrrxzJCQzBTeO2ADPnNM3TPIPkQm6gzUwdzNgcFE15lJIw2O3C0GJX2wAC3Jk1BLufaCA6MeSS8zxLPhGmsDup2rpp095U+/CgZJEkybS7Dc7ht4esN2ukRCgpf/rznyin6emJpvxyvbZ2swgGTETOHCKapIcphbJMliY16iYQjEyIyEiCJCACKVEySEKJqYhMLAdOR5YZ+RbksMek0phKBEAwCc6MGOiBzbEZtF1EGImxZDkeysfnhz99+oAQOaW18tugGG5uXXsPswRIAMN5qJtX9a259/gwg3ccebJj6IUhVyGEe8VGd4wgpKCAAA7mCCdg3/uHcbh2BmeEBjqSIW0em8fmsDpUiArQMBpGB+iAPjy0CQY8XoTSfMiPjw8PD4fHx/cfhzk1MFcDsz0ykxhgHOa9jo8uCgjhbWS//9ghk501N3zlmIkcadPo160DgYMmpt7JAdkRdhOPVLK79q4OZqrmJsx1q7/9/Lt0o623TdWJmDRobXa5bakFmzuEEd5NbwEAisjxcOxqW7I5+AiyNWtqa+2r96Vrr9qat26BdMd37oqW/dYCGFRR2HM5wGNXV1u4h6u7OmigDso+ZaG5yMNx+tPH018+Pfz0w8PHp+PDcSopMe6TJYxFySCyiUwlPZ7mD9usUDlFaThP3535seGG+7bN3fXbfQ1vVRUB0Ee/N+RgBgg7+JAEWYDYA8Ni9+wjREcfjxtGDE90c0RkZuZCSDaWVbjHtnu4WScgTpmRAcBH+iGSIwYSUEhKKWcHWHt7b/YSHt4ajqFYu7Ua3SHANzRGFc9SYg8XcnInczIDdxgAhGIoOgAFkgZZ8JBQRtBIyHI334eSQCQK4l125t0jHAszFzk988MjqpJW0Vq1al/1eiY+vxkODLsEuid2+vfL3XVZfG0YkYiLZGIYNocpJZlzZHIBYJgO5fhQPn/+en49L8taawMLGuAw8aHMD8fj8+PDw/FwXa/n21kEk5Cbd7XWlSIYfEp8+uE5ZZmPMzCfl/r76wV/xS9fzl++fP0SMJVpnss8F0I0ddWwCFVd163tZz2GBwEifvdxRKxrN6cQM6YdYEFECHLnXVmahEAIgpBB3AliWJbdE3N2SSLsvxD3XRziPbQsxgnaTNf1FoesJRk7FQRgEFKhBt/gIAADAgxAcwFP4Cl8TCzuYB6qpvodtZyYk3CZpnmeU5llLjLnyNK78t0oE8Y3iHsDw8wp4zxND/PhMD/OhyfOR5RDa76tW7iGaYQCGNCwG3rX6sVAJYaUcQf5YI97gX3iusthR0bP+AFMTJLy4LUQIgr/r/PaiVlSTtnMcTBLWRhp2CN4Ej1M+nj0h5OnNGixRdIxp4klEFZCn7PZbKThFH2FQbqO/Z0IoEDaU27eogPvcxjswj8klpRyTjkTSXQMJgh2F7fUtQzXVYfAe3JRuNE79lkE1KqMzIKIOB2mR39s3Q5PjybcOzlxIkojLYRxZbixX8A2iBnhyHgAPhJIkTmzJCoCB4aTRE0oQZLwiFDUDpg+Tcf+/Gk1ma+3S621926qESMMSBgeiT8gM1IEXt2vYMZigCsgD+dgTtPh9PD8QR0pTf/4Bd/sAlVNdQMz9IDWyWlbt2VZt9bVnLpZU93Mqoe6pjirf2522bprn4qesj1JlACCYAjfN6oxJjEHVIgO0AAqYiVskhSSIhliB6oR561fmq4RFaIjdMAxr2uMP42GCQMgAgclTkVSZpbvEuwc4LfLTVzdlCIKixARqiAmwDRCxgkIgwN5CGzvpvJ73z4OeQQGMCBFCKAGvKzbb6+vsMi8rs38eZ5TOA0xEgUAdfMOtDkstdVea2uvSwsgc1u29vnlMvweevNSZAOvX+K81Rwkhtg91Fu8n9r5VKYunqm7hvUAb72bGwymcevRu/e+H72IMSLs+OtdSD3w7/uTCt8krbAbSAQYYGBO6TDl5+P88XH+6ePprz8+/pe/fPjTUz5mQGt9W5drHvtSUI1WdVu33lqYYQA5c+SEk2IEFfmO+uDuux3M7mkW5nGv7btmDMDfpGg7hYqEGIUp5yQpjeT1sfSL+0vwAPM3Ek24jztKiNmDBqeGmUUS0PDBHm4xGB62q7AweBAvRo71/hvGvv2Nxjy+7d4UPUCjt163zZqCA5sliEyWo7MIOFhTN9/nDLNwD4odqRh77+ET834s9AHHj+wgiOHXBQDEgTh8GVhWyzOejJDlME/0RN6krdvtdauNWO4IRLiZIca9tP8hxiMshsu1NqvUlKk3RcbeFTIBRpnThx8eOeN8TB8+Pl7Ol9ttWZetrrUvrVfV5kx7xUGKlPg4l+NcDnNxt9r0clt6NyYmomma5kM5PBwoST4d+JBBOJX0+uWsXVPKpaRpSkwUEW5o+yp8d67bsT4kRPR3fEAz//z1XMo0u2CZlKnWvm2V1p469G7NnHo4BjpRYFgomnTgIAFA9G88puF+GhgRNCJdYp+v78gHekRXQzMIFvTC0d0jvPa+KKZucud6jrM2WjJEw32vPsp9NO21R+C3Yz4gQoJgDKYQgswBEnPCnrlm1kQmCIzgOELoJTEnSFOejofjw+l4fOB8DCxwXZdb9+iISuwMCL7rKWGknPsdXt9l7vTGFEUkRL+ThCMiAmMftM3NfOwqRg80EOX31Af4Q2lnkVwmD2LOEcjEuWSRQZOJUuzhUX/8YE8nlxTMyJRYplxOzM39VpI+HDSBTxnwGjqygRxcBy8qAmMsUu6mC/s3ds8LpgiGEEIhSsTEuKeVAQ4GsrCpJFEzdd/9mCAAfIgx3878tnVGykAsSOTCkBIyow06GCdkTgRBoIwv7L+h/qLtpeuE/Ej8MdGPOaVZHuYkwkR4onjmiAwbEgs9opV1PUZ6mB/mPz9MH3/68Xr9/PKyXK99WbWruW9uHfRTpD9HzsgG+Dm2ZJVZkOAlag8mQwuicpgePzxConzg37+C2r20976uw6EcukGv18vt9Xy1rVG33A1rt7W1pfWmje2Xqv9taf+81NbbQ6p/zfP/UUIweM89invOw2CNxgqwRqwBK8PK7CV7KZCyiWwW16q/xe2lrxXdEJApELuZumsERAiBwOB9oAhNRUpCIQuvYe/DN+PfPr+AdgBLTIdUhDDCGWgWKczDShEhhCgNIvWYCwCRge5tIAUgoACIcVHfwH+9nP/77793hOPhqIHtMSYRInRXB4SR/xZxrfp1WS/Lcl22rbbu6MgW/vW2XZdqDhYwlTTXnG5LTlwkZxZywICayluYBxHlVAgNHHMykW4Rt9YvtV1r37pVdd3B7b2q764Qd6L9/SffGAx3otwd+N//FSHRoUw/Pj/87dPzv/z0/F///Pz3Pz0+nvLxADm2vpxvX9O2dg03N3AD7V5rW29Lb4v1Tataw1BBE3Km7wQLXa317kMZhvvk8I5VigNGh7H5ICIa+rGdPTByNcdYtF8ub+pQADOzuxHq3XWjIJH2Dhg5i+QkOZlpr9tINwGAruo+HLhIhCOAx8px7EWJWWS42b9/rpraoEqstd2WtdfuHqKa3Yv33OpoQWBrpC5q3A1GEooPGkAAOALGHlfgo8sJxzErjeXU0IZgArsrYM1UB68FEKYZpiM+zTIdEZ3zFGZJzkyyi5Huzd1elr6viADAzEiMgdZ9tW3QOlloWVdBNfFgn4+5zE9Pz4e6/bCudV3qsmzXl/Pr59eXL+fXl6ubb3W93MKhQThiDPAmImrTQFxrH3IyJwIWYElTZmY5TvkwPz4/XD5dtXdmSllykoAh9whT2Na6Lps2jz7EEwHuA9N5exWq9utvn8t0eDDKJ6NS1nW7XS689kkRHTGgqVE1KSxZiF2QZpDZeWAPgB6Ee6cVMNjXBMCOfFfm7PsQQIjBvwSGKBgHtCW0dt+ULt5PWxMDHOjCblMAjjBApUCIfaMHTXXrFulb0zic/cy6aWNt4I2iC9mhcGiyLfnG3oiUAlkg5YQ5OYuTJCpZ5pKPs6QSkbZ1cW8QnchH/vG+WtDwRtH3B2zsuegesBz3+wLv8h/wCHSACNtj90yNAM3MzAhx+CrBuwblj6WdiDmVmVKeRh/BKUtKhSSnhClRSVAKTAWTABMgqXAjWhEb0UbUEqsn94jSokhkDiFQHo6gA8zYnWU9dk3TgLEhMEAAM0KGEHAMC0eH8EE53XnCd5vDO3Xfv9+H7l+9dUuC04gOHdinEUUqCZQ3j+RemHOWdCph6039q+rv1gjoC9Jr4hsAUMkEE0AySB4HAGecHQjj2Du+nPEox/nj8ePz8+PD33t/+fqyfnlpX1/7smlt17oubXt2+gElkRjSE+UX2oQ5CH+G5YWcFGpVdSSZjg8i+UB8BthLe1dbt8rIiWEQjq3bbdmWy6Vfr3JdDqoL1/N5+frbOWb915frvy/1V3UNfFQntR9Vi7lGtIirx+qxmi8ON6AFYQVcATaATmxJZJrkMEPOhnSr/dLtSriKeGaSPB8mYeqt1VqXdXNzERoSWBbKReZDPh7LPJeUc8rveVtxaTW0E3oyUo+udr5dEfChTIcyzTmbad0qM5VcItzU9qLCSISDpzbQe2bOpTzUGsLn1lf3c60vtQPJeWmZBQDVR0kdfDy4tfqyLOd1vS3VzRDuZpmmYaqOhpSHs4q87Y+JACng4S9/kbLrKrvZeV27em16XvtltddFz4teNlurdXU1v5fyO8GIYKwK/Y3AArumeZ+Xd971Xb16R+kQMKV0mKfH4/x0nE6ZZzTpGyzWJa9OrRrkSzVVN8bdBbeuy+16/nJ+eb1dbtvatNk489/ztnR324P9b70LDHYpMu42JTusScjMkngv7Xdq9L4tAULEcSeNDZJ7wF0JRyRArBbogcwsnEoiRtWuphExWJJDNx4ORDtHNRxcgNEBUHV444w/+g9HPRzCIFr4Fr6Z9W7kIeZSN8kiSZiYmnKz1CypJTdBf0v0w3vM5/ALIQwe/PygoN1he5R+GJthBwAYVxW5c++wbbbcYDpEzkA43JmYOInkJKN9I49994Tvno23Wxdx1PtWu0cFxJyFkLZWGTtMyMw5C3IusxyO5UGP2rw3Xa4fLj9cfv/16y8//34539Z1W9uqtqUkJafW+7o1c996X+q21m4QCt7DOphnikwinEt6xGMp6enxYG7Dq4eZ3KN3NQu32JZyu0lfuzYdmpphQvheR+3h19vSzTFNM0smar0vrce2bi2UxDghaJhCKHpn5kLyLBjAADzKdvjwwrKoGsjogYQURBZswQ4cAQFmIIFELJSYJYj7WA4ioFmvbmr7nwsYgAQYwEESJAFjN4CliBbAFf8gglFr5pUgAmKGAOHcjxzTsZRMheOQsU3U12RaHR0KI5EGgoKv2lOr0rYJhYgc3cnH9pdpvEzEAO+o4NqoxU4NfXus463Ndr/LqBF2hQbsnfQIAR30UhsutLuo5v0L+a6040hjzEIshEg4MjkEKKccSSqRIDDu0sBArkQX9zVAEVeA5mERTkM4NsjPAIjDiuVewgNNwwyIYuSJj5EdgFkyRQYn72FogbtgOXYOVow+ZaQGDzrB7kz7vbWImXn4uF58MLisM8PxNDetq5mosciUU3o4Ul+2DRfyM5hax4AX4Is4+zS5l+4nplDIAScAQyCI0pp+fW1dSJ6fHh7/9l//S6S0vV633z7Xn39rr9d2Wy7n8/VyzuoHRxJx4icu1zYTc0cA5/AKGstS16oWNB9OZQKm//b2MsxsWxsiJ4kpzZNwOKxb++3l8vr1JXoTgIeQZ7l9yr9zKb9+/vplWa9IwLgFHs2/9p60s/vN4rP6q/mrxQ3xhrwibYE1ogOQsKR0LOUwT0GkHhfVS2sVAnLK83E+Pnx8fpqK9G27Xi5fPn+ptYoQEyJCyjRNcjiUh8fDPB9E8jR9x9VUCA9PEBa+WX+9Lf/911/d/MPx4fF0PMzzum6fv34l4nk+mFptFRF5lBEmQeCIQTYhopLLD+ePp9OxachUtmVdlls3/OXrdajAdc+n9CFV2rpeWl9q21qniMx7P6nae+8tUIEYMRNNpaSUdCQfRxDA//vDx6d7ad9a//r1tWtszV8X/XJtny/95WZbtab3YEwfnhB47yt23RQGvo3FQ1QKDoADE77f9DvxIMamm4VSEmFEt225vvpVM+uUrUWvhku1XBZt6p5YCKLXti7L+fz65eXz1/P5ti5qffcZ+h4BHoy/Mf3Ee2ZODOYeCjOLMI0v5EFtEGa6+43CQJfHTD8aMFTdextkysIimZAjsFYlpsNxnuYsicz6Vlc3Gy41iBgQ4YEA4fgmi2XzYTlQW6u11db7jjS8v68Cd7APjakRrh5eO1QdFExiYmKyEPPsMQXMiHOiEpRg56YQIsVd0efAhHd2e6A7mO+fFxIgR2A4MDKm4YsD3Jsvt56LAYAghLl2IihF5qmMNQfunrd7B8ffm5aPNsndW2tNFRnT9IDCrXeASCIEQCIsFA4iPOHIJiXr3n5qzx++zMfDz//89ddffl9vt9taJ5+I+bY1NWuqa223rVbV0tvW29K21VpkjswzY8opZy7lAE/HwDE9BYywY9Wx3G21H5fctt7W3ptq021tde3vlboR0VtFhLotMhUpydxreOsdt95TUeYI17CqphFZ5ChZSe4+08QQ4WDNlXvHag6UxhPC1Ix0r+4AQBZ4J3QKpiCpKE5AGKQRqmBGw9I1ggMCUFECIygNZR0zTDPDRPkm1PzdngeadbObWe/WNRQYcj3MNh/mIvM0i59yHHMsl9gW1zZ2YqYGm6uvN0cMZHWcChp4CEIizEy+c4MB0IgAvG+0AfQ92/p+Dj0Qd63STjvYnxCACHpjGDPi2GINeCPuCPj/urQTkXDKInmH/oWZJDAxufq0VP16du19zilJZmEcQh4CJGnbdLueWm2923mx26q1DwreHv4WgW6harWadhe5L+0QzQwgUk5AxrUBMKkiQYTdKaZwJ9yOJKcd8fwGd757HdOcS0nj4tjVBsIfnh/+5T//5XVO/eV62bbXr+sjygnxjHEbw2uEAgLAxQO6zrcVXnhJ8DhJW7QbIwzWJ5jHy1pXPb/4rw8pP8xJptm21m6Xut1qvfW2Lb0u2qErm4eyEa1dt66gqBC/9+0CmnqvW7u+3l6/nPs8EdL7y8vV2raqBQCyRxwO3rsgI6ACbB7hsVW9XZYz/coi19vLsqxNLSD6sv4z4tjbr9Zia7dmL+oXi8VBhTxJiDiJDdCECYRrgC61mdeuy23ZtgbAZTqcPnx4/uHHT59+mA9Tb/3y+kqlrJczozNhSpxzmkp+OB2Px1Mp07BqeP95sAhDJPAsnHN2pKdta61JEodoZqvqao6B4a5um+q4XzTCwncy25iAAHNKr+o/tv7x4fRweJiu223T61bPS11ab+oWI698txjq7tVczcDicS5Ph8NcErNstV7X9evW1todAwNyRATUpmtt5goB+g473br9ctm2astm51t7vfbzrV3X3ocQeW8mAHa0785GxR1H3B/Ntw79zrEav7QTCgbzER3AtW/Lcnl51SlucCMteMpynOdjg4NRduaAPCBvJjPbel+W5eX8+vV8vm7b1u/W7g72/fm4TwY+NgEIsJtcD+x9ZG3lPKR6e6FDAAja/7t39zmMRKqh93UElJxIBInMolmLACKRnMpUWKi1TXtz91GdMPZJ3+67/71XYGYmEWbCurW61d77sAx+/yosfBhjGzgwICMKRr+nLrjDjtkFOSSAAnhiUhQIFkIWHrZtjEA8zL/fNCMQEEE02p3YpS8Eo6khQEQnCcTeu96uq0ddbshEFIwG7qfDQRB8j9/AO4syIkLyhN8rwokppSQpZQgg4pSGrAMxMo3tx86SoT04jYk4MpQiAU4M8yE/Ph5u12vdtiQpp4IBrtZ9BbRcSp6mw2E+HudpKvNxOhwPKSUaNOywABhSfHxbgCEh4TDIGU9IEs45mbp1m6u22qfDdx08EUC49dbrSit7eD4cMdhTM8AbUaB0gAVgQ5WwqympiTigROLk5BFX09tyW1vTJJy5MB+QNSKbzkP+QxiMpqqXRVOijWvffKtCxCzMIHIHZWJP26EACPKQHlQ9AhwwkIEToRC+W+bCaLyIA6N7W/uCK/NlEpEpl3xKfEiF5gztSu1C27Jstbt2baHh0M2AUspNiuaxNBi8QebRRgISAxEAeQcRZ3If6rD7lYC798sAqYiRmIR3dxNTsDB2SsBIwDtuSsBAhu/XVfA/lXak4cfG8rZjYxLAhBhd58sSrcH5qlPinIQ5sTDLblDZKi5Lqq313m+3ermtrXdzDQd3jGFy0qJWu91qqzZNpZSQJIjY1QGtgABlJHEPZA7EN4HFALJ2vNMdx+Cz3/bftStIeHqY5ykTY0AAIBNPOf346QPif/7tMP387z//8z9+/uXLy4Okp3n+Te3iUQ3Md5Mti7g0/4/zclP9vfXnQ5k9Jk8FMBMGo4fetNb1Ypcmy+1we0nzTAH9ttbzuS1b31rbal2rtr4b4CB0C3UbnOSbqzI929G6XV+vn3/9vEyFEN+r+My0beuy1d4NtXl70O6FpeScctq6dlVXa8uyqBGh9s2sDcMZ7esvtbVVEpj2unW7aTQLBSzMB5ZScso5Mw8bGIxoTW+37ba1Zd1qbeF+PD4e5vmHjx9//Ouff/jTn6bjqXvMLy/AsLxMpC0JzSXnnHPKJedSCksa1sffPg7ALAkAEvhc0ul0OhyOJGnbtsG38ggglJRQhHNyQnYfOdJra2tr6uGAwzMnIhLV5gBEn56enw6Hl3lb1r6pXmv9/XJbqvrY3N3VJgHgGIJ0IP5wmP/Lnz49n05TLtd1+/31gl+/bnZmjDnxcZpKymZRa1ML8+/ySDb1ny9tWfv1Vs+Xdr21Wq21PbvnTuIft+K+J8Nd6rKn0kPcDSN24vyuLbs/4GMMHcfbWl/P5y5d4iZtkm2SUymn4+E5xGR+nE7liIcyS06EtLVtxVvv9XK7nm/XpbV+f2/HTfbdARklZmwPhpiTkZGIgIlEJOU8lWnQ5RAgwtTUTHde4zdxLAz2rptHOBOnlEuZOafWem2t1oqIj4+P86GUKZnp7XY17cPknAnCXff8QFNVMxv9hbBI4pJFhOpWt632rvfYqPv7FXt2iw7TD0ZOlIwCYlR39QFY7OsZQsxIPcgZc/iMKCxF0gi1DYzAUAj1uywJ0AMN0XdKwli0w3BXAKIgNsDW22Z+WW4LEhJJotOcD5OcTsenh+OIwOHh1hB3ZgXJH0u7yDTP8/HAOQVCrXXrazeVwJQ4JRnQxli97qwGdCKgFI/P0zR9eno+/vTTx23dWq3hGAZ1qcttpVchEmTOU358PD08nA6nOZdMPIyF0cNaNzP18DHZIQ1+8jBTcA9nREhMhJL2tLihmT8c378KGIFDYb1ti2NQSseHR5uOtvW2tbU1JzfmFfDmEOo3NSFjciQMkhxkZl9qe+l6jeiMnGViPiE3kbnkWbgwI5ES1dbq71+jViysoOZdSimzCHASFOJRJ+JNgxMUEc1iM4MR2Tt4uWNl/w7VSjkVnsdj060t2w3PXxj58XCieS6SpkMWL+TZu/QGS+vVWjdzBwyi1Ce3A0AwoTAyAREQ7klYwyk/mJKgcAiH7RmP400cfS0QMDg6DOXn2MJDAGBwDLWTEAEnEmYRAQBn4Lvh4f99aR+MVBbZI7nuKtzx792xdQwF67GiBcTIVRIGTmAGtUpr0Dquq9XOo1ANrEE1erdts3Xr26q9WTiZgiRj4QAijhGtga1axPiLdykUwH0MGj8bH9j/tGO/31xEgei6xxq5u6ckz88Ph4M8HA+n0yPm6QZ4u1xfbtefz9dfr+t5a019NH6BoRHn6tXbFnyr+FzySVIGzAAcoRGvQIv7Zg1fXzM45wSOvda6LL01VdOu2kxVv8XJ73xvB3LKPB8Pz58+fPr4YcpirVe3wSd4eyGt23mprTZXrUkqoTq6agyzadyJTBC9NwUAdyOi+XBKKRMSuF7b6trVrHm0QEOAwESIsvOWATB2c6wxxjmCM2JOTJQfHo4fnh5+eDp9OB4OSRhBtVP0Y5F0msglEeWcs4wHbPcc47tk+a1kta7eew9TMwtgkUPJU0rhvmzb63XZWmvmhM5q7js2wszzVEpmdegO16ZL14hgiAAniFn4+TD/9PhIAKv3L7dlVa2DYzk0lxABw1KNH8v06Xj42w/Pf/3w+HQ4lpRfUwqgz1vN1zUzPM354+l4nOdjKaeprLV21fQOclyb/fPrslVd17YuvVbVHsNSHd7YPRCAEMOdBe4JUHea+X61f6vmsU/2FHt4MwHvhw5zAmZ31M393M1CzxYH4Pag6DGxYC4pl5QyQvTew6N1vW31sm7XdWtvPWIE63eAPIYjBhPA7q1DaVdI37fk97hG2knyxIHh35yEENE8/G5px4giKUkSSR5htTdVjxgJtIfTLAnXbRne2pk5iwgiuLkPdufYsO2OxgGmZKKMEABSW1vXddtqq/072djeQ42lK+eSAAAJuVkTpY7YYMi3HAAiHKADbBFiNjeVtSOTazBx9OhL0820efjejo0hwu7Lk3EBjddPzCgMwe681W0xv6gt7kiYc+qPJ3x++Pj8cDoddleRwd7YjwVa4Jf6DsgZfvUlTYc55dJdz5fzbblxQpEkwkwEg7AWEeBuY67ZG0giKJMATiw4t6xdCZlB+qbbUi/n2+22RQQxTXOZD9PhMJcp757CEWoqWFsfK3Qbfjiw71qGeNYigAazDcFpAA+MgCzfRZL4GNp7c4BuxtPEZXIDDVjdl96DMQgbihMYWUDciM6E6L5YE1PV/rXWl95vHorAjQrhEVDLdOAHSROIAMbN9fz68rJWOB7ywzSw4FRKmQ+T5AnotC0UlsYOP/YuOgK62WY2JuNG3JE3g22fBfavzDnnt3BbJOQw07rptti2pFIYXLyLd7Rmvdatbq2aByILC0tOZcrTnKdJze/ZCHj/tNCRlFFGYaUY8vux8xp8ShIExEEBCHSHMNhBanVV7wFOcg/tYULCAEACMIR3GvA/WNbsRh/MQjhILkA40ggC0REdwzx6MzSD2kINETAlKvOQQ2BX6B16BzPYaUKB7tC7b5uva99Wbc3doIWZQVJPeQTxcQCaG2q1sD0EZ5dQ7vPPO9rgG96J/xMgHxFqBmrqFgEB7iIylZOk0/OHDx9/+BPNh4X4//pv//0f/3H5Zdte1rZ1s4AEwz+FAmJV3cws1NwQOSgPBj+CN8dX5CtBNfBa6asCgFv01mutOpxlfEgn3W3wcTGnVBIzURJ8OM0fPn7469//+p/+01+eHk5C4Krq30GOtdt56aDKbtZaF+qBXQcKAEwEPJpv3x1FAjgfHh4/nE4PIlLX29fff97qNuzlgIgjAECYEtPQQpq5mcXQl6CnhDOIEDkUSfnD89PH58cPp8NDYQm3dWnXi93OGXrOPLpJISbmkVe6s1B39se3T6O2rrWBKyEstR7KdDzMcylI1My3fr5tbW2dPYAYAswDAJnllMtcOIA29V/ON70uBD4nPk5ymtIhp8dS4vnpOOWK/ni9qlk4XJbaoJvtOrLEfMj508PpX374+LcPjz8c5+OUmFg9HyabUhGROfHTYf7x8fR8PC1Hvda2rGvtPcu3A7I1/fnromq9m7V7TN+OVt9FrkPutI/nd/nqIF3Dt2sQ9wcX9tX1DrRikhGPhkwwJ5wTJqFgXCA2d+o6tU4RB5aPpcA0UypMPABVNd+63Wq7rPV12brq29nh/s7QCQAheFREZhkFWfbZFXZmOw7tXrgB4bA6G0bWd/gMIEZpD0TcjfJTQuS1tdbVIyTJ49PpcJhFSLXfrmfTPo1ce2aM8Ah0JwD6ZmJA+5ht5h6D0VhrW5Zt22pr7T1pABFJUiAxWEqDKMSSrGdNXWvtzNS7ckfT8LtBU4dYzS9VCZsb1GyEZBrr1mvVqmY+UJZd9ud35AN2EgQioeQkSdgliNbWblu91rp1RcRcMlqbMn36+HQ8HFJOKY/4cN7pmYjN4uv/OH876QiIKCIpJUnSN12W5Xa7PX04lVLGtnm4KQ9CsWGA7XMC758wiVCeEiVwl5xKSRMaWfNtaettpyogAieaSil5SFSHNb4lTo3bYMhurWrv5oZEYxyMGEgSRYQFjB5sBO4gfdsvjTYI3MO7moN2NCMND1T1ZWu3rUUmJAEmpIyoQdA4XZi76UvXaLX3em79qrpFKAD1SACHALN2nIgndMIAeNX+2/n886p8PD7+8AQC5p0l5TzNpZxy/rRZCk+4O4jvXtTg6t7cERBJKqUatPRYqvH0jSGfKR0kDZ3LmPkJKNSsbrbeAgwxoK/QN6tr37Zt3bZWAzAl4pxymefDcZ4PZSraWxpUIYTYyS0wnEd4v3KDCBBJ3pV25AHRhI/goYAwhT0OUVUVh2aKAAfz/671/9/t2neaD8CePIPD15sQkDCYVKhmWjE2a9F63G5Wa0RgyXgyLgVzwpzDxTL0m7fWrVn0Dq3ZtsW6WW2uBne56ojQSKlkSUVyYk50X5MMgyy8J4Tsht/71YR3Q9f9lH//KkB7Zwx3R0AmZEkMzALMIMlFyv8jQqby8dPTpz99+Lf/8fP/+OW3y3UdcZgjqlRHChOgO6pBc6i762dAQDU4a1ybbV3NA+ug9caOK/qInxyIz/7sM+J0mD8+PT49zE+nw8fnh59+/PB//svf/+UvPz2e5imLqTU1ou3thTS169oS+IS7rfcY1lOSacpEoJ0xADzMHNENIKd8PD6cHp6YCSEkZWI2VwQU3rNC78yoPSErnJhh/MthKm0BSJxyfnx8eno8TUUYgrS5GbUb9yWsI/hY9OwJH0TExDv1Ct/jjYA4z0dLKUzHFeVAtXnXqhGvt+1W+1p1bQrNtqYQMJhoWfjj0+nvf/owlykC/v23z//j8wtRHEv6y4env/3w/OFUJgE85OMkWOjj0yERPs7z76+Xy21pvY4My5LSwzT96eH08XRkpvN6W3sllpel/XZeLtvqAcySUzlO89PxkHsXBole0eTdalk9lqZuuwH70DoDAQEN4hshIgZAuJvvhpC4g4Jvz8GOD9771XvAE9GwTsMkUASK4DHzIXEWIsLuUX1gVmgp8TRPx9PheBJE8DD1anHZ9Mut/vq6/fx1u257ad+Bovydh3ySsU3jvZyMnfbIJ4l4W3gDgpmiw6ADMtGwrrJd8rQnqonIoMtsrZttHsFMp/kwzNWIYFu3VjcIzyJTSsJkZuAWu38NMFNGYeFk+3MOAIQgwiPdtbVuavFd3wuInMvRzVhMzJKaZVdz7dp7z7m3XFvrvarp3ZfdHCIMYlOjrZn5ujEAqfnadO1abcgXAd50iPEOaBmoBmMBK1gKozAqhIKpqfYWCIjRejMzZi6l5JJT3lWDPOYspuj2jnMxpPWhbmur9XK53q632xUgypSnuTDxWLK7mw7q0tgu0F2/QCJMACxMHmDW1BywMzImSodMIrnm3rppDzfrfRmt3oBliBBxStMsU099k23d1nXbPAIN1Ky3kZKE3W3weJBgmgrN9IeRysfN/AYwRAuFkZ9Va1P1QED0nEiYDTAIgKUTteimVbelbduiWt11t1cFhqjugCavftXl4zQB4q3b12pfqx8KMz8CQwtHa1J9dm29ZaMDgBASCg29GQRSUCYw2RA3BauwGbyudt30sXyrIWEQHfbV+E5ZI0GUCA7l6LCT/aq1qq1pV++ORJwoSyopZRFGQFPUTtpYGw04yAlYAilMwTu4IfgYsUSIRiS091B3iNZXNSW6y1M9zM1UezdEZLt3inRXoQIcMOV39+4fS7vfFXWISHtoMQMQYjB75j7LBras3VV9WXVZ3NWnQhjEgHOKkoARxN2bWQ/r0TZcK2zVtxqmMMzzmSWnlHNOpaScJSUSofttd59+vhXz8e3dR/W3w7b/v+8OPYSZuiECsFASESHh8ZucKJjT33P69On5b3/99J//85//9b/9x3/7t3/8/uX169fz19fLy/ly3ba1NRjsftxJ13UYcUAEYTW4NbvVtrWm5vvCInAHFsfbeEc0iSgQmfjhePzp06e//umHP//44dPHx58+ffjPf/vzT58+CAOEq2rvxvT6Jn4z89qUKCDtqzZAZOEypSNOSUi72p5H4uiB4SnlMk1lmghBcyo5NxFXDQTa2SKxjxAiOe/TtggKjU02joynkW1wOD4cDnMSxjCwCtpZN7YW3iGCgIc9027pmoWzEDIGIr9bwgEcH04wZDTurhpqTb33tmm7rFvVsCBzMNWt9jG3EdE0ZZH048ePPz4+TpKOOZ+yMOFxLn/99OFPzw8HEsEQEkkyP0w/uk0sj9P0P+bycrmsdW2q5jhJeijT8+n0MBW1/uv1ikwkcl7q5/NyqzUQgBhRWFJOomGJceLA75dXEdH1fkQQgPGNv/pGJh81XPs+te9A7hh2cX+ccR9Ux8WKOKi8BEIgDIlhFjwkeihyLMJMgajduzogZkZKqUzT4XA4HGY009Z6xNLtddPPl/rzy/rz13VtVc1iBxIwHXq8I+2lJJ6TyKCxpnv4RAyYbZT2PZjD7c7eIhoU5ggzi4CU0lRymaaUsqrV2pZ1671NczlM5cOHh8PhGOHrut0u197a4TDNJefE4d60hRndIThiSshpd+x5w+ACIEarrKpu/oephIincvJh4DH+52Fjsulacq25tVp7boPU3buqmpqFWXOPFl1dECNQLRbVzWwz152a+2Y18B5yBkJkppnABCEYgAZXeyzGBvlgBLISk+SUc5Ysgxk4bj0k4vh+FAGwiKaqt9vnz5/P51dAP5ymMuVcxmYNiSjMrblqN3cg2LM/EZMgpDREDBQe1qv12juxCIlQ5iLIxMJasbfaamuta1cPEOaU8zTPI54wSpRUhBM4ttbDw5vWpQ2aQ+196x0wWDh8vP/fdfCOI/4RcCjfe9cWHiOCz8LDNRCcADKQIzkDIXfEGr5pr9tW17X7m/MwIoZBNHBrpra9rPKUMxLVgC24Ug6JxzmFwNbM1dG19lDVGdMJk9AwEgf0oFDk4MxosgJuzW8328i/3vS66Okx3hZvrq7huBtDj/BhzsgJI6ExWISDa1h37a4KO9MDE9Ju2QWA1r2uUW/UFmwL9dXdnShMjNhUTTuEEezOmsw4kqW7AQJa+L20I+Lu2Tzyh1QNAnZbZuJxjQAAYFCeTu94jf/T1D7Eo99mC0IkhAQoAbN6u9aq1a9XfT3r5RbrGqawVtua3Va4LjDlyAzb6uer39a4Vagdm6IaeCCLJGRJI/EySXoTzAreXdvxDZ+Dd35kOMhR+IdU2j+cPQC4I4QJ4Y1QOlqCYQULhJCTMBN+ep4LPx/nv/744fOX1y9fzy+vly8v559/+/zr5y9fz9frWh1ss3aprOAyTJGHzVnbj4mZfbtzYl+r7u/+yPZjGVQ+YDKAqnZdm5xvxDScnI9zmjILUyKEd/OuMM8lJTCiGCHXyOxIE4UzClPdegUb4wxCYKiHb+uVGVKWiF6K2FzGOv0tB3iey/E4H6ZSSiIEAKedgHm3FUNk5iQiSAwxfJLD0LWDK0UMGHAwdQEROfE0y6GkU4oIq/qdDmM0OGMtFAAph7mZd+2smVJOZXo49q211nrrvfVWh6I27Hy7/vP3LxkpPT08HSfEj8w8l/LD08PpMFnrm1nmJDkdD3MOn6fbYco/PJxOOY2K6ohCXEgw0Dyuy/blukzT9PQ4P55SKRPlG54XhLis6y8vr7W3rW21bQIh3wdgwM4BxviGTsNOeht7Id+JZT60uwY70fPOPtth7fEbdjv5wW+954UnnBPNiQ5Ch5KmLEhkAWx9p5hEwB4Fad4tTGvT29rOS329ba9LvSx9qbpfxvsp/o7nDwAiEjntlWZ/gbsoa1wi96l9r1gDrdon9ggRkZSmMpU8ecS21WXd6laRaD7MT0+nx4fjXBJ4v12XZdlcPXGack7Ceyykabj73Q50mI0N5jmMMN99HxA+2PPqcJfRvvssmPPpXc7U+ApVVe7CWaSVPPXex1PVW++ttda0d3Azj81tmHeqx2be3NXj/6a0vz3IIyLKgnoDDAtvPZl5H6GB9/dx/7bdAYKYUhIe2MZQHCABdnw3tudSkIqatVpfzq/rcnv+cDqdDpJ4mC8Mz2sKSVRI2O/O4rvpEDihsSRmSVSco1lT62rd0EGQGJmRS0pCpeQ+9VZ73Wqr3cza1k29rjWlkbwLGCSUg1HNMHo4hiMChqE1V9OAbj3aZjlNh0O+33zolGJQEmHslomQwCEgGFCQbO9izB2CMRyN1Sx6793Mx16CgQB2B3gcYsMw8NUNW29dAbEDQZ7pIJCzJVG0m5ubkoGCB8VJ5EzoZqt1cZSIGT3IO0f1eKn96+viyBXx5fNVt/7nn7591l0b9P6WUZxEUkoUht7BOkYanS6TCKXC6ZBG68STpASIXfvturZmCPXy2l5/t+urLksP70RGoiQ9QlUZYEp596sZyxHthIZODuMSsRjsfh/C7+FEF+4RaneW7rhaIgBm6PC/Ke0D8RlkvPsiEQE5EC1mNe21rUtczvV6bdc1WgXrAGHXxc/XeLnAXKJwtGa31bcNto66c/1G8FxOKZdSUsopCbEMLcDdSf7b10APdk7ovbojfKNo7f8B/MGEBwBwmqappHFCh57lOyLywKUxHg7TcUofTvPffvz4+np5PV+v1/Xl9fKv//0//n//9h//9s9f//n567W2Zv3aoIcWliRCzE219d57097V7O3be48e0Juhh/AYewxgae3L5dbNX6+XL+fL2vSybJ8+HD88Hk7zJMLvL5Sc+OFQwLq4EzOScEqZ2ZjeArRa744WRAGOHuG2LmfEPseMEWUS8BkBwgPHByA8z+V4mA9zKTnFHvU12jrcm24AosHsBHAHs4ErmyqEM8IwkhURJAEkSoWmk5ym/CSm3XABe0/9HpuRYKI0QKTACFC3yftB9dFM1Xu32uq2bUvdlm29bVvt7bqs//HLbxlBMFKiD49HkVxSKTlb4LV37XrMJADADA7dPSIOJT/N09M8pywxFIse5+v625fzWvt57SDlo6QPp+OUJE+vBp9fr8vr7da1fzlfaq/h+vE0P87z+0mRCIUHfXMgr7AzPfxuvm8jwjP20c8R7v8NfmsBYI9xIuChpWbMiCXBJHjIeMg0yUgUTDlJAKIHdxNUwGAEigCzAfK4at3addler9vrbbssba29vWHKb5K67w+ICEOSexZLxGCOjaXCrvkaLvO4S1TijU8PxFhKnqZ5KhNzul6X2+12uy1d7fHp8eHx4cPz4+k4mfZ1Wa6vr9vWUipTKVkyoW+9997c/U3vh/s989ZC7I/M7ktlNqw49kSsdx8HIuV8uEfSvVX3IFKmId5JA4jvXXvrvdbWqmxbq1vv3Xofk6SDa8QuL35zNL2/ed+RRvZ/elcdW+rKFQBHozXUEQFg7l219lZrSzmnSIlGoE4eIWz2/dRepoI83bbtfL3cbjezNs/l4fHAo7g6hgOFCKcysEeKZr22Td1iJPeYBQcjIyMKjG68mzqoAQfJMCWgnPa9Ydd12dZl3Zatba0udY0NADilXDIEDO/84XM4jHYBCYPAUKu33nu1bdHnZwbIbx9IcI6gtzXoHl9kgfcVB45E2zB1B6YQUuxAZs3AgpCT5DsQBohAEIHRGSDctG2m3Q0CFCkLHFLCnIO5u21mbkYGhoBAN4QzY23Ka2WLHPCUQMBu3q+mX1b7RX1rUQPaeWH7LnVIezddxiySJKHnIERXsA7WIRyJaTf7KYcyqbu6kUhKOTGDarvdAq7Vut7O+vpFl5ttWwNoRJ1FSQzRHITokCeDYZAXAe4OoU5AY1kx7pj49rVv1D1c1SN855vdPTN6+o5S811pH5nDwwQG7txeJ0CsCIigplC3tG65du12r2eE7uSO0cMAtuZC4YaqYIHIVBIRU9rxv5xS5pRYEhIjcXxrIL6VdoD72X/bF96P27c97vj89+Hk/Zg4LikaxI5BA7nPArv11uDqjEBQIT5MRZAeDrN227b64/PjX//06V//8c9//cfP//3nX3/58nWt/bLVhQYHUtR9u+ts7ygD7u/822MSEe5qCm2Ajryu2ytxbXq5rcJYsvx+Xv79l88fHg8fHubH0zyVXKu8lZO55I9PD6027R3ybGmWnEWoJA0mt6jVhvT6bYtCCEyRBKcpCaKSZYRJ2COAeexlUk45CY6YcriHUo0/AgZtG2iHfBhJgCWQzbuHD5MAcCLhPM8k2YExH7A8OFJt3U19hHG9uxCv20YBh5IpIcdY4yITpRBj8pEt66E2q2rTXntf67bVTc0i4reXS6ttnlIuKaXCkhDA3K7b5u5P8+GH5XGJ0LD/6+ffvr5eDin9cDwep3yYsg/mhke413ZYel/NhKhtNT0+/Pj8FEC9q/V2uV56b1dEdWWELInZDvENqSPCkgXurLn95ndwHXakI195mDa985ogGHLwkcUAw/LyrolKhIkoM0xCx4yniR9mPmSZUhJJzKIGVS2pJiPJ+ThPx8M0TSUlISID7O63rZ5vt8uyrHU170wuCRElEIYbhPB3p2NYyr2N7LGvtMZNMpCdXf9114c7MaXEKVFKPD6/Zd1au2619daneX6eytPT08PpmBi3Zb3dbuu6mFlKUkpKicyG/l/38/jtpGMMJOSNezjYWDHssk2ID2Wqufdu75UXiCSc3c2GV+F+PQTx+IYjYRAhO/Mw4iq59ClPpdZSt621OjB6MCNzVgcPGrafsfN53qr8fj7uo8LoidxcI+DuNz9ehXu02i6X66+//kYAp9PxeDoeT8exQCml5Jxd3/GYAYjFla635fX1DBjH0+FwnHJJgGGqiEiBQTECPlgICLg39wDrAbGr7e+blJIKIjBgw25mCYSDKJAQ7zYogEx5ysx8mA/atNW2LOv5fLnebuZu6mrDtAmaam01IJDI1DGYgDEsDKzb94IFhJQDCSxwJyOPXV0QIhsBOfpOo7kbkEKYo4d4ILBR+B7INKrKmNoHQhbCKMjkI5SQmfMeHgljipbR2CCSsrScVpHrbWm3W7stVOuHTBPHl9p+Mfucy3mCTpMhuiHFdzCwaY9tJWLmRBFOhJAR0M21q6mN7VvKeZ5nc5eSgzCXiUQAaHC4vTevq9eNTAWCiRiQmYY9OwP6ngPOGjaq+47tMSITICQSdVM39SFDCCQgIEKnQMA+FK2j9g8C0B8MjL8v7e5DXWpm4YAAPrLvUAEB3FStVeqdzXksWJMQIoRTBAIMI7Boe7oTCWMmSsI5cUqSJElKJAlJANmRAugObAbAHtm9l5gBHbyr6/D9tu0+DY1rCf7wFbCHVEYE4oiTGtGAsY9We5qeR4CIJJGH44EAwuPT89Nf/vTpx08fP354mqZMCD///vWltta6AxJzAHRViwjc5Yrju951tDvoET40f+6IZCS4ruqR1sosCEFIP385H+bycCgPx/J0mg/T9OPf/09JO6oylfz8+HBbt2VrkecuB0qSMiXvgdibIrUBcQ24khCFIDGVxHNJQqiRM4Jn2WMpARCDBjQevjcF8e2NpXtoJd9XCSSJOCNRmA0azJA/S0rleORycEzOB5Nj92qXG/gG3hEJ3vlAXJYN99YBSZCG3wKBAAFTDIL+uEZxj8lqvW+1Xm638+221O12u00llamIpEDaWltqXXsHhKfD8dPl9tK6uf9//vFr3da/fXj+dDqWJHPJw0vMPXrJp4M/dl3VWu+1VvA4lunjg9+27ev5/DvhLgaPQKbmsdl3Jod7ad+hozu1wmL4xo9SNFxUcGSd4z1UdKTojFxK+FYemCNxJI7COAkcEj1M/HxIhylPOSOnAK4a1jT3PoXPx8PHD49PTw8PD8dpmiQlVVOPW90uy21Zb71vTDYXnDKPmFp1V4ucvjOaGamUIrKv8b7pMt5hZvcOeDALhGWayjTlUqT1vq7r5bZcLysi5pyfnh4/PD+fjnMSXm632/V6uZx7a/NhHl0IIujIhdyLwbsOPvZzeT+032ACM3M1YT7O87b11r5LgUJEFkGje+JnjOy5iHA2QB5QobuzSNpN7iy1kmqRLUvdemu9d+2d1XhoJnXYXI5ZaG/h4j48DQXBGxSD+505SGb3CSqitXa5XH79RXqtx+N8Op0enx4fHx5OD6fj8XA4HNS/Q/s9oKtdrtfL5XI6TQ8PhzJlZrTwsCDiIBhGJjkVEQbGCKzURzcxju+41RInFmJCQU7YOuoAycZlNBzLx3svWUopghwabWtMr7frrW7b9bbslLdAJLYINQV6o8mKs7uMW5m+H6gQpAAI0DB4wD3scKQ4W6ARjZxDGJkWCCN4zEOChFgZNWgstQhxSLRGXhgGCBDTmFGQiYkLBL4JH4gYmIQpkJy557Sw3Nxe19v1y5d+uf6Q6ZDorPZC9HLCVSY3RBbCxH+wmnUfoRlETuHjqA4ag6qrWZgAoojM0xwIopmSzIcjEPWudau1r9rVa8XWKIwQmUWQnAWFmccTuyseuquFDS+5t4iYwRrvpluvEOrDTB8wCNy9jfTAGBTq2N1YLb7PCv5jqCtEhGnvdXs3KSONlJkhSjFFgMSCuQizZ9vhtZ2zuS/QeO8/7gwjHjt/Gv46w+2fgHZwIODbgXnD2yP+UNf3w39/kADuMuH4I+Y4av5wOHGPeyJvxLCy3P+uITXY24OdvK1mvbPQPKUfPz66/yWL/PD09G///O0fv/7+69eXl+uy1dZVbWcTBxEmYWYCIrMRvPH2Hu83J2JEQG3V3BsnZkEAImqmtfV1reerfHm5TiU///m/yt3JTZjnki1QMSlOC0wIxAgiAGBJmBn2UxsIOBxfqAgJevTNEN06DEr8sCkYbtgYAH6vpfsMOvh+SAQBSJhSSXlKuUjKKU9IuEPM47BBpDIdnj6Ux48gx035vNh6WbfrNfoNQY+Tn54+vL0F12UdOImaWcpTSkk4MQmPS4MA0XfQZudyZuYpyZTzw+FQa+29RkSAN7XW23VZr1u99a7uX8/LL1/P//H7V0K4XK4PU5nL4eH0OB9PuaRuXd0NvINubi18iDg18LW2f54vrXeH+PDw8H/8lcZjYWYRMcRK/K6WEGJK94VvQESounbVbtrNdY83wAjEYIbBYkpC7zLoaV+1067+Z8JEmJiOhY4TnSY5zTIXyUkMsI2uDSFPOR+mH3/66S9//du//O1f/vzTXx6enkVytNZd121Zt6v7lpM/P2Q74JQJMbp5V+9qp+k7v623+k1E7j7Gd9rXLwO5M3dHBGIqJZUyWFbFzW/Xer5cL5eruSPz0+Pj8/PT4+l0mIurXi+X15eX2+1GhPM8H4+HnFOE30OF7A1fhG99POyr/fta6H74w7r21jAipTTlXEvnd5GCiJg4OfJQ2/gwTvPo3InI3SLuq0mH4WwfEamUMs3lcOi99tZVm3bdf7TeWx9L6nGEcQeueNyAe/u73zB7H2Lmw891Z68DmHut7fX1rL3fLuV6vN4u18t9dp+mCUnCv72Qy+W6nuN2W8ws5zTPk7mttQ6ua5JUcsk5p5SYOAKsqXYNi0Ei3/VRHuGBAsICNFpy6aqqI7DXdnQEYO8r6I4zUojQ4TB9/OE553RblmVZl3Vr3VSjaTcDCGDCJCMUnpOO5TLn8obGAwCijPCk3Tk50A1txIeABVqMyCVAMNx1zezIAUwBxMgOabcZon3YCxwRUbtnOSEFAgJxAHWPZla1K3h339MiiUCkMS2EF4gXs/PIAneYGm4Aa8pOKaXJiREpp1zuLPTx9XA8zkcZZRaIWJLkjJJCslFqjqThDgoYzIE0VLbIHQBrrdu6bcui2xJ1497FfFj9ESfhhCRODPtcEA6OiLb3bqPjJpJdl9hVEZCxjy3p4Oi6eyNM6OoRgOqhYOgQGH/goP1R144IbtZb+8ZWwxhh6rBbWwUjoiRhjp1u4kSw20Pu5ANmBBkT7dh1Inqg+R7dN7w0Yzjd75jXHxbmsSPviONMjvP+jn1yX4Xh/1Ta7z087JzVuN8nHu44HC73TmO3fUEAcHMzDW1mGk5CT4/HnNKHp8e//vSnv/zp13/9x8//3//4x3/88tuXr6+3de19aKBwd/xIgkxdh2MuvO1G7i/O98bZVFiZZdgH7N9ouLv3bnV4Gt2/mDBnyQESUj33SAJYMJgiCYuMPHnY16U7lYGTMENY2wzAzTGGfyjS3ensjrzvXMnBcbj3XwyAxJxyydOUypzyzLkAgquC2Pg9TlDm+fD0cf74E5anuHVfvmybLq+r1iu44qPA07cPZNn2q0/VtNih+JTSlKQAJQEZ2rH927irq4lA5FCKn45NtXWtrW61LuvSu0FgOJjG2vrZ1oCz/P65ME/Mp1xSypyLIq0eTW38eN3q13U9r/U2InGRPl/XRp9HtsrT8fjh+CCJibGrddXWVc2Evx8Th0Zw9zwOVeu9a3dVd4OdzIjADJwwJ8qZcmImgPA9j3mQKwcFGAIBBDEJHjIfJzlOcpxyKVlENoUwH1ZypeQyzz/99Ke///0//fmnPz9/+DilKSzUrfW61VurN4p2yCBPE0Iqidxta711ax2P+bvS/m44H4ATvlXZ2BfcZmbMlDKXIsdTyakgynVbz6/Ly+v1elumw/T0cPjw8eOPnz7mJOB2uV1eX15eX19760+PD8fjcZ4LM7ZW3TVC3WNv3e4P+bvx4c4FeneKzaz3PoLOiVn4exM3QGZBctytOvds+UFGH/iJxe74cAcLwCMsfDI101HSbXzevffW2lpbrX2toyLicOfkvUHje17O/b0Cjxgtwdbq1rqamQdBuMe2ba5a13VdlvV6u8zzPE/TNOWSJc/lh7+/cQIvl/P5q7ZamWiaSinZ3GptpUwpDYveaSpTkkSA6tpb16ZhDoAUO8FnjIEEyMwEiJyUhXvfYmvWBsET8Y4tvCEMoeCA6KWkjx+ejod529ptuZ3P12Wt69bWbTz/MSJqck4pOHsiJkmc87tqgoicAwx5N1x0NBswIRBSAPlwSBl1exj0UYA4MgWyB4CHo5m7Y9ztMQIxGC0YcKTsDCtAQ9KI2nWrTcFrUwJ0AiZmwAoAYRf3S/gVoAGqe/JBSJY8zelwCClIlDnyt7YNAOB4OHwox2FxYxGBlEumJJCyS2pBaBEABhQsjlS7uXcPdIdt27Z1q+uqdY2+ibc8DJN2AV1CEAyG3ScmkBwcaF9HIyEzMqEgoocHQsaEBOOzo2Ea6p4REoZ6GFBXa4Fh7mTfQXN/DHVlGj5RsKu37h7ssLvcIQRwwB6huu+chmndPuUw8lvkCwYA7pcTIPi9kO9PIeyL8Hd8K/hGREN8Y2K9AXf4FoQDiLiHyQGM6M/3L2T3cNl9qePOJNrfH3oj5sJOwTVX6117772b9ogASYecjw/4wePHn/qPP336T3//y3/951/+/Z+//OPnX3/+7cvvX18u12WtzSP47YIkIhphEN+6jTvkCIiB97xCIRHCwjEnfDrNjw+nx4fjYZ7KO/f1AdgMnMXcW7g5O1BEgBsisKAIsVDoWF8NUITGaiDCrRtAMBIIITANXyQmHMEuOJKoYB/Zd78iYcl5msp8OB6fcpnVvfXGBD6KGxPJ4fD44XB6TPPJuYTXtl2sLYjohtvaS34f6gpm3ppaRDNr3dbWp5wOOR+nPOdUEoyCR8OBcyQW770RBUBJ4hO4z2rWW9taW9d2WdYvt9vX6+2yLmurEc6EuWQn+Hy9+D/jf3z5HSBUtburwXndvlxul2Vb1k7ERfJrrenycprK4zx9mI5P08xCyGh+Z6JGXEjeUVP2WCLTMHPr1pv2PlDcfblOiMwwcutHWGJiTIwjJELw7u2D48pzhhhT+1zkOKV5yrmUlBOyEDiagsWIOUmDvmyuW12vN+Xqqpfzy+161nrjqLMEzOyRCSMxdjNGZOgEmOSPopJRXxFxHOWI+LaJixDheZ5SlpITCarqutS69XVp29aZ0w8ff3h4Oj09P5xOB4S4Xs632+12OW/rysLzNB2Ph5xSuHdzvdN3BqN7R5C/7drfFXgaREMMdwMFRHWvW6urXm/rsm3m77bUOyj8NkVT0EjXIGaOfZQdvP5h6HRvt8c4Mn7ZLGJ83mpde611Xbfbsq1L3VZVDQ+C4IhENDaKIomZkCgA3KP3VltLW0qpDtf+gT3hYJxE9NauZttWb9dBtcrlcPzbx78h7v3W7bYst15KOhzK8TClJI4+GNoiUlKZylxKIeIwH46O7o6BfDdTAERhTsgMRAHDrxxYIMBER54WRDj4WHqNBREj7oBGBGGkxIRFhFOinGVb21b7utZl2WpvaooESM6IjDx80Oj7YjKK1c7WGSlhCLtRLzgiYoz5Ymw5cL+CEYECnBkiRzgzuL/bXiE5oQP5HgkRO0EZgMB6X16vCl57Q6TEwsXFHT0q4qK9EUbOdDgERCAxixyPx6fn6cNHmWaI6LczWP9un0uEiXfuFwASpSychFIKSQoI/3/2/qTHkiRbE8TOJKKq914zN/eIyHzvZXEAmuwmugGCXHDLNVckuCMB/pf6X9xxxSWBXhFNoqpYb8iMCHc3szvoIHIGLkT0mllkFlFF1qaJ0PSIyAhzM7+qKiJn+oYARAZBAsBaPWDbipq5e9nKtm3rutayWS3smtGSCIto41WZWhhSMxsiJAqkZnvmXS+xxzvvA3RzcMQgQpAdJJMosah7Nd9AQd2JnIg/BsHfmLqSCLceT7tbAuyKHLu/Qeue017xEhIzMDcjmdZiBQpvmFfb51OxN4Mwdihs9H7Ljpe7n+b3rduxafeN/L5qbxlo4M49/3hX1vdtd9B5yxE6YZKaEXSEmZvWWmqp21a2TU3dQ5KknPKQxyGJpAD48sPnP/zhh7/76fPf//Tl3zw9PB6nLPQLIiGWqt6yht7Sbs3l/qje3U3HjhA4gwlSJhgED5k/n8Y/fHn86YfPD6cTvDdTgtZJa0KZDSbRWJqBEd0eQIi5YW4xWpOrKwP3wwvCA5F6+tPLEBbZadjRm3M7tEkkSWvCjsPxeBzyYV5nqxsBMCEEMdMwTuPxlMejpKEAu5uWm+vGRNHkaOqHsU80rlZYNTePYr5pFwXa+U9AgdTGwC2f9E4natLH1LKSBgcxK5te5/Xw8pJTYiGeqWphwjxmIHyZb7dtaQxjc7cAD7yu5WVe57VuxcY0HIeIxQLrD49HIfwyHqeUWTAoHHjHyeGymfo9RWsN2Gh4fq3N2jK8T5SwAX+EKWfJo6SEwpgIEuPIlJlTJwtCw7cRYEJPhEloGnga0pBzSpklATO6AlkzJmsdFYzwWsu6LiQFSWu9Xi7rfPW6cujAQbkJgAMjbrvmQTgIfaza33ZbtKS0lFJrrbW2/5JSmqZpHIeUxbyu63K9Xl9fbqUYBD88fHp6+vz05eHx05EZ1fR6u37//n2Z5zB7evz08PAwDpmZWqPaTe9yD+4d9bRvWHwTOGpVBCJ1Q7dGDoitlNu8Luu6beUDbqt/CxBR6941JCAienTOvPdFYG7qzZavVa1t+tB8zdrDcHe1Wsq2zHO+iDBCbMuqUZu/iCBmkZyHnLOIUEu0IkpJLAKIDePlTcsvPLSGVWibUHXbtgWpcUqnav/wDh20beu21ePp6eHxNI4DMfXRTbOpTzmlLCkToIZCwN7477o1LWFvUmbd+xjbx8HYnWQamAIdIoK4OccR7YTGdkwxESVkRmbMibZh2LY6D8OQ8+12uy2zYwD4rpq2133vVxT0wN32gyMF9TBPjIANLNmQctE7CB0sBUjQmvDhju57WyQAkILJAX1XXWgzfAwgD7Xttmh4MSWiEJdO6whEXE0NCXPiaEISJJKG4+l4Oj08PgyHY7hfbCub/xY0gL233wBlLExMKAzM1vgafVJDKKsDVK1Vq1ubIDWipdaqHGoYzjAge2D1qKa1OdUySZuIARn0DLipM/QGc0RA0E6UZUYIIGmLgiAlNaeqrqFEgph2HeO3+/jX//pf3//lepuXZd3T6N6o/s37u/dy9y7C/ptagb8/JOzjSNir9P6uoOPu98Xw8Z8f/wX/9u+It49xv8YhT1M332Siv//pCxPe53bvf/heKfSftNNsdlbsG9acuLWpsclyuaqVWpo0x7Ku87KVWutufA2AbSDd380HoAze/9GfUie9d+7kkFLOKackIsHp3qlzLabFPMyhBnmQCCUGBIemTWRWSp8M4s7OEqZd0K9ZCnV5wY8X/dVbvVdOjUJPxJwkE7HthUI7B1t7glOSYUIWByqlrPOstXSKhWqS9HA69icecT5fzbvLRodeIDab0I7G2BmaLeXqeVEP7f2FtPXWhyseal66w6SqWaOCCPUBOe4jyD1bRHOv1gRMgds0BDwgsvCQ0ihpEAHsmeM+DYL1nV3wvC7fz9/bT/QPG7AvS+yvGHYR9pa6QEcKdwHX+8oNgOh6V/0kb3qT3L7TvDNRWwrU1M2GYUzSRGbAI7RqI2tXLebv+DAtuFj/CSz58dOP93etZW6TqXvV6x1L1+DH0B0fm+NquHcdmC7CJ734ZBEGaPlGrbU0rbfUNEj3vLE/o14x78/qfbX+4Zm8deZbI6ENi9sCNI/T01Mep/Y7CTEJ7z+ytfr7enu/sPc/eR+NvduQ8fYf+mnVwXvalnFtTx/3Nd8LVXrbPtGjo9+bEm9XP0zifuDt2x+J5fT05X6u3i7FaqTUhAGJmKKjx4hZEjf/PWqdd3NvLAOI2LF87xLzjujtuzkizHrw3rkH/RG3996q+fuzj/vzelP1bzQFM7M2yOvLGhEAJMHdB8rdr9f5/UEd+6nfLXX6w+5IFdj3M94P+vvme9sgsL/bty/F/tpizwSjKfoBEFIrhXv6XM1Uw7yN/zsGmDkNA+dMzBDRfAjzkO+vIwsm2oME7t9FxJwaFGlfphjR1OXX7ukV90jS/4YRhE0lgqMxKXb+Be6EsB3q7bFPjuE3wQP3UNsLt/7w29prvM92JRmGfHj7xveh/ffr9+v36/fr9+v36/frv+/XXym7/X79fv1+/X79fv1+/X799/n6PbT/fv1+/X79fv1+/X79/9X1AUa3+a3G8n7KgP0fwUhd7r3B7NwBg5kA30CvbQyCARAdMv9ucBZvI6f9f3D/q01d4C4IixFgFstWztd5qzXaSJJ2gyxCZux2Wm3KEkeKx3YXHn4uz9FxOW8eHrCPn7sOx+7HVbbSrKDD47fgvb++8P046T/6S/9xFxL+6e//Pu0g+aAKXA7jcBjHRA37bhCmWtTUQRwT8ACUIsDczWrVUrQ2JQ7TPoTnPivCfQYNXX6hei1WGxzMHAAIISUaB348yfFAQ3Jhi9CIsOCqNG+0Viw1IpC4QdlBq5W11upWwQ0i8Hic/vjHL/ttxbYtAb5PKQkQrHvQdPc4DzMtplWtWnO4b8BdQiIWScLSAHaJKCEyBnVY532++g5X0QZl+3hVEbWZSSMI0oDEO5yhTSTvQ1DoSL42zyJE+r7Usms8YRh5vfsq0o5faHfUPwUEADYW6D43hgY7jQgzI6SUEyJ2ZMc+1aSuBcrtS+bWQAk7cAixwb483kMS3pFL+kbAfQ4KO/LU3dRhfUek/vHT55xyECMA2UY6Y71gVGQKYo2kCrUYBhKJMymjN/5rQHiXKtm2dSsrQCCFeZNzLWYK8A4htvNZoM2kG0yhYUCbmwQChDloRIXOG2zA/DHzqNW1KDEzkUN4OGG+A8sj3Oq6jyf3M+gOydtfDiD0QT1EewUQ0BTdpYMJ3gAB/TN/mHXeN+f+snf9jn687HNsiDfIQrwBcPpY9I2BG4FIw3i4P5ovh2FMHBHmttZtrdta182quzvsAnL3j9WPWiLARDJwGiSPkveB/E5q6n+7b4Y7aq0Pnd/Pku/AMUB4s9iFJrq7wxICILzbhu+P63neLls3FTSr388/d49oaCYUKacU0AgytZTaBJCbvvJuVvtmmtvBBGYQkFJKKeWciVBdmyaXqm9bKZtqsYaBYKJGESLGpsnz3lD6TSulPxSgu2eCh1t0s2KSTz/98a6GdCux1ne4a7xDA367Fvb328+1/Q7i3YuGDhTdsTd9r97BJ3CHed8hUHiHcdzxH/15348sfDv23gIr4pjw8M767UNof9F//F7/fZvw70+fiDBjTFk+fzo+PBwOx4EZVVekmKZMQm7a34wHmKMRWhrTcZpOxIhoBrZP+2M/ExuuCPF+R9CAj4YOCFQNrov9+z9//e9+/X/+/O1ZIUgwZxwGGAc8jDRlZgoMBTcIH+y/GvV/0RdZ6H/38t8qOEtC4AhgQOlG4FZL3bbqCugYirb515+/ff3527YWrY7Qvcugo0qaMlXfUl3kIfZtAfsjbkEG4/5d/19dmJL8n/6P/4fPT0/t3z1d8PTtD3/6u//iT0+fx8NJJMUaej2/Pl9utxWPVb7g8UdPn9ViLettfn6+fPv59fL95fn7y8vtdivrRgTjkKYpTynnzMLoHrXY9ba9Pq/PX+eXb8v1dV1vBdyz4A9fxj/9/fF//j97+B//NP7x8/owzW7nqnXR47fr9G9/Tr9e+OurV+dxyEwU5pfv86//8vL6a7k+x7agKv1X/+X/6H/7v/tft7uIiG/P/+KuOackaZAUiCu45Ok4PebDNIzDVm/L9XZbv90uz5fr5Xq7bdtWrQ45H6bjw+npdPyU8zjkPHJ6FD6hjeAYdlcchIYFb9pEzcXFLQAM6Ir4irQSBMGR0x9kPAClfnoFozMGMxNnpIycRUQk5zwQp//Lv/3+de6HF3sZtm/n8/nyehbmYRzlne1H51CFE9FxmsZxbGDEiCDExGxmS51F5MvjlyS8Fqu1qmotpWoZJB+n4zhKSmlZ12Vdc87jOKqaqTXgey2qVVmkmec2ABF0QE2YKUZ05/WuA4OmvqzlVuEft+l+Kv0v/6f/9Y8//CGGA4KNl5/z679Nz7+Kf6Njrul4tU/nC7z+uqGmKR+243g+pS2zEpqRK3FKyPiXX/7pzz//DFSJrfjtVs7PL79ebi/Q+LV7Ut/+RAsvtRS1YqFKppLT8fH0JIIeS7Vz1Regwokej5+/PPzdHw//w8PxHy7f1/l8ycMwjoOGVq85/STc4Zmm5Xb5S4N4edfYQaYOSRRhSYklAeI8z/OyRLiZzfPi7g8PDw8PD8fjIYlYLU11qIVljAZ26pseEf1umZNSSpJSzllSSkzETB03BeHuVdVKba81ukoaAaIHND8kVTN1kfTHf/Vf3jOw/+bvP/8Png5qetvmf37+yz89//Jy/Zdfr98WLcVqd3/qEdAjAhwFZMT0OT/+4fD5p8cf/3788Wk6Hoc0Mqcms9GS+X7U7j5EtBOn330FiJEJmNsvpATEQBLMTp0dBeHoHlqiFtDqtahqNf2//rs//7f/8q3dxVpu/7f/+//5tmzXWyGSw3j48unTD09PATSv9devL79+/V7qhuDjkA7TcBinMacmLuBq4cGMbn673sLh6fHph8+ff/rpxzTKrVwKKCQ6X+e//Mv37z+fz7/OtikHHA7p4XE8nIZxSqXUZSlhiE6tbiMIQpCUJAkKUMI0siSEAK9WrsU3SJDG4fi/+t/87/PQUdj/8mr/+GIQ0bCrSNhI1B3JCIGAIruhKiJjcydPROgeuxiDuVv7CSmllJOIcGNMWoOFqkcDZ9e+urjxKoWIWvT29jtVGzG10UMaThICmm6DmZp1/dN/9Zn/iz+8caf/ytTVDRGpCfO3lR5gDmqxVd+K5dGJG4GspcGB0auWVlVQQIMo94QDfc85PuhjvKst7omW31OgMFtLWbdNOzKz4wIjwtRVwZRIsCdsEAQM+uFGAsyDCHsVRghu7o3nDwIQ4bDO6+11vl3nWpp9Je1wzXdIzZ4mv/8Pv43ebzKZ/z/V7Xtitl9JeBiH45gPo+SEDEbRtUzN1dA0DFzDi1rs0ixNhsPMQj202TugAlWk4sFJ0A1KtbXWYgXI8oCHQxO400RwHOk44jCEsAaYukewAzlmoCwpjQc+AWpwSsKITVp1mbVuaynqEFCRPmqkNK7hThBEZE4gLIlYEKkdi2paVLdaayPi9nSU3kqR5t+MwDvgHHZ0bYO030sMAADEIFb3xe0adnWvTJzEiQOiqVrtDBzYW1O9KqOdGXEvx++v515pN/NQQoxGoQ4HAGJKJEkk5yRMLAyAbto+HeLuCWYWLMzc7nrH/UZzJyWixthsx0TDviIhejQeYESYWnDfd9jScKLG4g5o3G5sH7VpYX20I4HIHtmQlavJpjwjzhPEiZKQMa1zftHjy8I6HHJajArRWm0GMyBCGQWYhCgAXa2Cq3sQCoCEM0RTDumGkxFWSil1K1o7/z84otUBEIAR5EZVG6snjcPj09MfPj/99Dh93m7P5ufz+fLy+uLoTvHD50/30I6IIhKEhGjQPhyJCO2v0t1DawCYGSK0Ot3UVJVp3+nQ4qW/tU8QpdEDAD2a5kVDzBuoaRVNZposGwv3034/nxCRmdwpYrfGQIrWmLjTBXom8FYGtmCwlPW8XJ5vr8/zeS5LaeHu7RyK99DxACsBV515bU0NcjDAgJwBU9sG0ruP1D0dwz2AHJq6SAT10xECQOC+wcIg7tbr3Iv494sHmnRodD7FfY8DPvDACXikCBAwXefrSxDnAJlyfnp8vM23dZ216gqRiDIjgSeGlp4zoxPkjKYBzcJUC3v3dzV0Bw9qASaQgQBYqFkSW3UrbpuFIbgTBlGQUE4yTnkYB5AACUwAHGZu5iqo1UvVxvl8OzkI71boRAQIWi3Ceh8kGrsSeiYPAFGxYAvcuK+ZiECIloI7grp7VWx5onmYRTQlJuIQcHMPC2uqvJmZRQCAJIiUmbJI++PwnYajmqlpraSq7dO/19eCv9aQb8kvdLZoe4FggUVhWTWlOtQkCXqz0Hp/CYGicUMt7n98dN6oB7h3rD/vuQ52dtK+ZHvVTp2SY6Hzslznuaj6fsAjYripWq1QxZmahAQyAUeG7f3ycwCHsPadTMgIrmFq99CuqvNl+frLt+W21WJNOqFRwuFjhMb73yLup+Q7qZ2eysF/7iuLPB7Gh0M+jjJQsBm5hqt7VasFtVCFujksplHrWupa6tblMi3UopqFV3cLJCSJYHd0g61EqVrdOMHxlCZhnyxq5bAvD/J0osPkktRCiwJEVufqk8HAOU1HiVEMmAURCBxJkhl7LNUWTMZbpOmjFBIxoPdutwhxImLOo0hqDGNzK1W3WtdSS21SYAHRCzBsokjU+LgghNy7JgiwmwMQYgA2PYXG+kcqEWfXl7q+6gYiI04myZtcc4eZdPrZrtHQIjvvfOAPKtnRdV0c2nFcChHJrq3WVNnHIQ85caOxiQBAMb2TBsPdAKqapBCRCN8KQKdNQjvMWkyCbuiwh3boHw0AWgpPQcgEgCytRCN3MwBvPJ99/NSb4B8hNT5ojIUBpZgslc+AlyMiwMCIG72e07fbw9c66HQYUnJeEj+zXmx1oTxkGSDRiGQArrVaFGIkyoQDxBBhANDTDUazWsq8LGv1GuBATUwGmzd7BHqwGtVCLGmA6Xj48tOPf/rx8z+c0ufLS7X49fvL6+XyioIsdJr+Yae4AhHmlDyY2ZQQK4hITrmdLJ211R6gKQHknJg5zEvBNlQkfBfdW53ihszNw4qJzXTbtjaDqS3JZU5Jas2qmfltyUhqhq3ILO1IjF7zo++uea3S8a51/XZp1XXdzsvl6/X5l9evv16+n7d5M/VOXcX3OX9jjLWCz0I3K9W1NEs0hIAjQgCk9ox797bLvzg28iJ6U5HAQHRCCuSdYdV1v9vh6RgRXQUHPvaRY5cmfbsRRvqSDgeQA9eitVq19fo6X1I+jtOnKef0ZSQi1VK3da0lE45MORELOEFEsIQHmJGWADS1UnUTRxJkxApqqEGBApiQHBlJsuScCNCq62q2NscrEAZOmJinUR4fD9Pp4GhKaqQVVEtUiyqwMZRNUy3v3wchsaCICDMStaB2FwnFXabHdtKjapN8BSISlva6kJCJAFiYDMC0153RqMwRBJCTpKYXD7jVqqGBiNLUbYWYICKI0J2hizgiQkuZA0BVSy2lci21mTdmeZ///Y2q3T9YQgUAggEixlZt2cpYWHIaEgBiky8kQgiwCLfW8yckigDT5v8SQCRMSNI+Vp9CIjS9znCLiH3ISYgUQNXs+fL6/PqylrXZHlDvEmAAmkOtzhTMkJoRoeYPwbgLyAAzCBNDhBmEd8sCxfW2XV+v55frOhetHt5S1l7INYmk90lyqxG7kUWTlGvF1o4U2Jmr/1kvd1AFqxgbOIVr+OZWatV1swVsrTVscabwKHVb521d6rLouti2eauSiCJlnEY5nVr1z+5Rqx8Gfjg4R0qRSRGq+7ah1YcTf/ksjycEik2pmgAManxe+PkWz6/1UtwIMRG39U/ClIWGnKdhWuZrLZt9+WF6/zaEmSKYqZHIRUaQjJJJMiE12nSt3a1Da6tV+5SMiAD74ULtV/huCPKbBgpCE29EVsQCcbE4a73UbakrR0opdSXzYAB6Q1u8jelxHz0SfOwCAECt9XY+b1tR1fanJ7PYQ7uklFIax3HMKdygRw5svfqeLjO3AO9mbQ8kSYQ0eG6zzQYEQcQkAoimpqZuTgmpublJL/e9hyIPjS6+tjcP7qt2L/rfJaTtMeGZEDkGcvPyarohDZAEElW9btt3LZXAWCAPKCkQa6m363J24SkmErNYl+Va6wYAwpmEGGIaH2sF61rxXb69qJWitfZxaQS4ea3KoKoGwO6oyqXyQCx0Goen0+mHw+FTpsMwHcfjUV5fPdCL1hpNxXm/C2QhDgxuYkFAxP1A7BIoXYb8LlAV3tw+dtBNOCIxYQgzkxFCDSZmIRZOLIhgZkSldVDUPAK7PHQjlkNvR0XXAweArrO21y3YSh1mImNCN/DftPaWbX2J5dfr1z+ff/n1+v28XjfrGgLvmoeA9xFra8gSePjm27lcPFqwr1v9pMdPD+N0zGMXaoXdP3dH2sCdWd6HDoZB0D6XQYvagA7uwM3MmbtmgPuekLVGx91VCACAkB7yY5aSo851Wba5bGs11bquIZID0zjmfDqe5oCyzl5Nt5IoMTMiOARiEIXktgXdsWw2YzUkMHYPRVRi4xQ5AwAPJEMWIgwP06bb1p3g8sCHkzw8Tg+fDofjMeU819WqV/fqUSyqRXHTMKcIsfdvJKCrThpAK/C3spVSA5EQU0os0opUZA5VV62mrbUmYkyMhBxMSAGg1gTH2iQaARGY+1ge0AOEJaWUh8E8LAICXVW78EmbGGJmvr873EEUJpwT1yo1lYgAxGGo8K7A/a09zH3bQKsAEDGQEM2jqK4llg1T9lYqdDUNiAhQd/DA3cwPohcQRG0WIURCyE2wqDfsAcNBwZvVT5sPAZI6bFpfzq/P55e1rNGDPgEYBCBQeFR1IiOWYWSWEfi9Vy0yYSv5hFEEwcLcwpGR3UE3u77O3355nq9LLe7WMELvJuj9FXf8BHYsXpM03r+Ed+hWh2T9Zy/bXU23zcpqdXEmNwOrarVUXTebQ2ests1OjhFay7wu82Wbr3WZrWxm6gEhiQ4H/vQ4fn6ajlMeskBvfbhrjDIe5CBBZFGX1co65BhHGA5Vo26FzBBxKFW+veq3F/36WudKNHqe4BDMBxyS5AONeZym4fQ4LEvdVv00vA/tICwAIImGlMacUxqBB5AMwgZu5toctWutpYkyRRfk2Lvid+kjbNPQ3g+M+xSjpc0BGEgVZQO4hb6Gn63OWqsqEoVZuIFboO1YlH5E727b2PuV7zSR75fWejlfmoJHS5xbSd2+SkQ552HIQxKt0FyUCEGYWiMMEaWF9oiGNQIASZJzYiRT01LabAIJJaUum1KrqyeRpm7UBr4R0R5YhLtBrbshindDJYTe/N8FVt9X7cH+LLZKjGzudo7YKEvk0RMXq6uCmadEkRgfBI8QQ9X5tq7PzoxYAsqyyfV6LmWTJDkPxBwQhwkgslqtVsq2Vl3M6lZq2dTUSRABw8Gql8XRq06GGB5kRqo85EHkNAyP0/iY0oEwD9Ph4dPT7Tqv67Zti1r9TfZMraroNWe/u92lGKjJ2gFEkEJzibHo4CZvKA1CEOHmEqXSBon3fuyO9tqNc+7tmSZT1p1x27QPwsx3qai2IDvACd5+qxsbGuLHu7iuN9u2P7/+8i+Xn7/Pr3NdtUXSuP+wXnq/DQeRdvyfLbYUrWpl07VqaRkHi2Bw81br+nRw96O9N7xgX+MOgWAIAdCKMfSg/iUMb0+xoZqaXH8Xs3nfx0Y6DA8JqlClQoGKYAheq23rbA4JMCV5fHzs9g8BtdQxM0YLdX0+g4KMgBBOtdiCqsQYEEEBWJktSeSMSDS2kSBAmHu1cCCioGDG6SE/fpk+/3B6fDpJyubgZ1+1Vrfq3jqa5hZgkjDnD8uqT2ZKqYjhrmbbVmqtDkHEgTgyI++WBoTFtM2kwAPNAVGgqfVR8/RrP5aZEaj7zjZUrJl6ZOFxyCllRFjWbSvFq1U1JmYiaXKDiKnNiJrTIAIBiFAG1sRaJQAIcaT5Pxja+7hxn5RDPzix6/QbFPVScSvBpGaEgUwhTADUrJIYdtRoF0EmzsQiLALY0AHesqJ2NsY+62qVWRuM3bZ6WxZ1AwYWDAdsvntNNB4p0D2immOpvFSiItX4w40AI3YRp2iySM0KUNaynZ8v5+fLfF3LZvuyvytRt28Ph7s8bvcmfD8ei7fEvcWd1qW5w0n/467fjNb/qug31XVZy7aqbo4c4eZVTUuxZbPFbfa6+rX6DKZay7ytL7f1fFnmZSlWA1wIDmN6epx++Dx9fhwPY8pJGLC5A3NQliHzENVtqwvFghpRl1JvVoxKbRZThutav7/Ul9f6etGtIkrN43Y4TsfTeDqNQ07ChGDj6JLweJID8vu7EkJmOU3DMAwiQxBry1+JIaCGNYhAC+oNY4xNj703cprpZ8PFNGx8f3Qe0AyXsUGEiBRwtZitXEqdTRUJeUiYcpachkTSPS73FG3Py+7T9vs/AX/zSrD7+TabE+yWHG0mhTmlaRxb8E7CwQTQGr29G98ANe0nafNoxv4FwGa0Kn367ogI/qZGF/ucFmPPk4oWd2tN0TbbczNsGq6E99ZpGzUw7DNhAACY5udjekVjmMHq5hjumUrii/hSYAU3LBAb25YrTGk68KPHZ9GrlnLVbVuC5TrPtapIZs6I5BHjQEyjuqqWhS+3OUrZtk1rNdUQBGiQnTWWW5iWcSwAQiJIiXlgGYQHpowozZ1vPB5+/MNPSfLT05daVtV6PD2+2z2hWrtOvFnTwgPoGnjtNbY2OELrjkIECDMzNfR1EmEWFm5tbzFmIoBoob5VbvcMkokQOTcl4N5759T15NFMzW1fRq0eIAAgwtj/KzWNZ3LiDxiOr5dvYK+/3L49L+fVir07F+KefO4esx+WI0BQ8/QslwrNXrhYXa3W8M+H08N0AJKWebz/Xur5AcLerOwPtJlkRgDtUBa/47ED3KLbJ2jRMtdVvb77NETDyMADiqGpFyLgLKmCKQMyUkiiTILxkBlDK4MDokVHxgRGS7gMHCPUQI3YIgEHQoABGFEIY2YOR4gw1WqOgYSUE4UEJkwjP/54/Pzjw+PT8XAYVG1btuJ3qCQQUBLBHCiSSKbh8F6bM/YmYm/OISJxGgYAIOacUzPmgh1tPgwDS3NK22vq3QLVHSKMewbYAZXhAWHoQW4MUJmzx8SSUyKgRFybNdEuJNxxkExIDL1X3sA40VzHuCPYGvzg7fptaL9P6ftUpd0tRoADhjoXxbUGAqoQAwlHCCGlNtwJ3A87AmaS1EB/jMwRjTrR0gWLcMQI6KeXY4d6bKqX6/U63xwjZcmDgEafoyI0V1gkAnSzWKMGrOZw9HJ8u4+2E6Jl4RHeFE4RJUDKen35dj6/Xre1hu990zvhA+DO4XO0gNgH8LhH9q5h3Fk87bG1eeaeYP8nXR17/y5ruF+qts5bKZvaZiwcCGHqVsxL9eKxqd62sqxqZa1lW7byutTzrc6mQS45ktBxyp8/Hb58Onw6DVOWzJwoZZJEKXEiEAhc5/Wm7gBFfa1l063AVqAW81Jh22y5xetrvZx1uVnZIGKVJNNxOZ2mx0/T8ZjGsQlpuwjywBngDdWIwEyj0OM0jcOoIVtgdSM3gT2Gmamq7TgraMkZdVPge2hH7D35huOxcAOoiN5MytJAkjVi29abl5vp6h6UJCdCGkSGlBInQaJ3cxTY4/odCvWO1/ThIqKUM9TakJ2ACNEMdQMRc87TOBI0sdWECFprjdpHC4BI2ApuAGgVT99u0Q5YYhaPqq13DQDwNpN192oa4Aw7a8hNrUYANB6dO0TcEYed39mdkITtQ6Y1XZ4Ppr65beAFPSQ0R010Y9hWWiIUa+iCZZAVh3Q48g9Oy4BQ6tdtXVGU01bVPQCJUBouSyRJwoAwq8RkrtfbubY5sDsiBmApsS62zGFal2ljyaMkSSn7mNLAnBGbJGc4xXg4/PCH/PnpBytqtbrq1+fbvHTCgoeXsrm5t3zQ/a2o7ULBvRpsvgl9biJCxHnITa4/iQB3R8Q2iwzvJo1qqqrWLeBAhJHSOOScUydHEokICyO17/CG1NjHhjuMbk80OvWT6c6zatevt2/b+su53m62tjiH/Zi5/69HXL+LZ7ejAhG8OXbE5lsppbrOdS2hjTpCRJFGkDs+eD+hofnB9mKujaEC2kCoUUB9/713GF8r1NWsVq1zWV6322ZvoR0QIglGCESOZHlAAg5xQzdUJbNgAhZJx8OUuG6Llg0ILAKJgNDRLKK6mxkYhEeqlIZO1fOwAEMIRhRig3BrJgmQOQ0pNWc1OcjwkJ9++vTpx6dpysK0Xm+Na1CtdcepeXUOTIw05jQNB3znc+PutdZlWbZtI0RJaToe8zi2ECvNpBnAo5Nmc84DDW/QtJaPB8DuD8kM3AbkAeauZm4GZgwhLSwRHaYDM4/DIMQ7w+KOUiQPtPvoJ8CjiUobNPXuexIA+D58/I2G/B0GfF9GRNS8093QDEyxEroHWGUCGzglJBIEdy3oLihCGiAR6A5hLSG7Vzlmpt1fGbzRDAgJINR1XpaX8/lyu3p4HuQQY1IPp7Z4mJE5evoRERHbVkqpxNvx3a2ENbw7EqI7EAqnvK16fr68fj/fzre6VDB4w0fvkbX10hzd0RytF2ZOgYhB9+AO3cENmAmDQAF9f6z/iTP3D925j2W8qqmXbSu1FhUUosBwJE5pnCaPMTQXW1ZfyvwyX6+3pdw23yoZkgyYGU9Tejjk45imRJlgIBolDTwMMjIJAm9bnZfl+8v52/Pr+XK7zktpsssEhlQDq8WmsGjMBqvCukGZTTcjsPXFl7HeDusw8TCQpGCJPEg+pKdpenx8d49IxDLkQ0pDKbbUeqlVkklKgL0B1nzHvBPa29SGmpB/q6EJg/e4jhEesZmu7iuBQRpSTswsYgHmFpqcBDkSc7Ory83foZ0ieI/bvbzrxN69Xqe3zv+7lxOhZlWtVG2S8GqNqo4YwADdLiqQsI0nq7f+JYCb7UOlt2UWEa4NQB9M3NDvu2cJsiShBECbb/O2rPWWEg0puStzUi3h2ix13BWaQD1y22LqFhDNBIiJK76LJQH0fMHzYretamg6hA+wCK6MhUV1UFeLZvGz2ZIx5zQcR36ahstqtEWSnMYp5TALkeyOZq4eAEFMKUsSRnS37fU1dcyVgSFEoBt5RS0VwtaljAdj4ZQkT5yFmakbAIURepryNB0zZAGOaqY2r//mHtrDo2z13v7uCDPoEKHeLQ7E7uOBhNSQba2ZKizNxZikuzqFOyFb1QaLr7vXh5sJMwpJ6rbp9262hyH0Io1FpIt+IAL63kD33tjbR0i/7dXBFtscs5IhNHtMJABiTtLsnzDC2/xl02odXt8zSyRqQ33HCIIVStgVZypos61zmb9Mj0/T6ZDHMQ8gPUgCOAV5OBF0t1sMRIoWHjCgJdMtutzR/aauutbtVuZfby+/3p4vG98jSERYnUMramXdRF3di5uqWQ03BKNgda6IkMBbZmRh5t3xL9DdQdXXRW11YWGUNERygEAz0ApW0SpYCSvuHtwePgIR5JHTScancXo6HJ8e8uFgDutczpflcpm3rUBYY0YmabG2l96/0f5vZQYAJBFmlpxbK84bIlzh3tJGRG6cNWIRQUR3r1FdDQIASYigNSZL7VL80YKyhTuBM0AtRWsFxKraeKsOAQ2UEe7uYFaschUW6X90BAI0G449IIG588fezN+A0cFesu8jK4pwAHInM6w1ti0gECO0ViY3pzFoyIzhVguGD5I8pKVfgYZOQNgoS+3waphT76MvZGbEALO1lPP19nK5XOebh6XMB8ZawzRaXYIcLA3cSa0JWYvWqtNQ3m4l2kkK2Oh2gQRJYLhu5fu315fv5/W2mjrufamPVwB6oAcH8V7QGYb2rv79aA4MYmQhDHpDdP0nxXXED/t8n869W2Rea11L2WqdBvbmHEOUx/FoienAVaqt21wXu+r2UpatFoiYOOcschjT41Eej+NpTGPiTDgQjZxGGZLkCFLz27J+fXn986/f/vL9+3kuS1VHAiJKhEyOoegb+kpQiJVC3esG9eZenMBnLpe0soBkYAERGA4yngb/6fFPjx/uFFGER6KsfltquSxzMpvGiZliB1P26itgH7R3X4YWbxmAMRgcAwHCwletZy03DI/hOE4jYkIKRGcBTkRZhIlyc24ScIHKiNzPr/4a7wH9XqojAP4GeAYAzY6l1SzViAKRvLvSoDQX411bphXcbSbZXqy5tfO6Z/cAFG5mnVcDgYINRNLw1AAgSMxSqla1ZbuqzuPIx3Ew1Sxj1RJhgNIaXwBAItjQAhEWjogk3Cjw3FurfZ3p822z83qZiwN8cmSnhfCGtAA6JHEBw6geobAxVuYQoZySsDAa5Wl4eHIgVXcH86ihptXcAaGhK3NOwzBQ69V1YBZhCIVQWKhp+LYWVSOmacoomTCIoMHBLKpAliyHfDzm04GnqBHV/92//zPA8/2wqtUQ22DzbYbSwdsRZgHNjs8D6P6CcZ+h96sZsnNDDgWBQ/P0vcs/RYQw3/nsLAwdnBYW1s3OmJiQqZXwSEC7n1Jgx821M2L//++3OaqxIgc7e3X3YKQschyHKedBUrjd1vmKi4XFDpXERhpuyAGI1h3w8AU2Ky+zL3Odr9vtH04/atWnw0NEDJEhEhNDEBBQdA/J1mTt9VLvdOxlSivAIsJdq9a6Xdfb9/n85/PXf758XbZPAJ/2ZeVeZtgKrgW1kml4bRhKrZWc2CWwGgkxoaBQEOGmWN2J0KltO1CNsvp6s0QwDX6o4I7o5EamqAV0Ay1h1SO8c/QZKVE+psOX4fDDcXo6DuMEJMtlvb0ul9f5dlvMKkQwAVMIgQgQsjvU6g2+9vY63M2dRZrFn6S0j+HMIjrOpkVGBGchImzONIgdae0RAZ1DS6SqpTQPJ90hrRER6I7glbix14rqmHMSudsSqlsDFQdEcwFswCPCBl3mQfrYr11MDu/G0h9Cu5mVUn5TrwMAAjmGVg+LWpYbFxEijHAVoWW109EfTpH2cYm7hRuweUQYNEIyhHUXz/3UdA/VhphSqWYRl9v1fL3N66pmAY4YTIEJnCmCPBzBgZwIiAgCfJ958EdKH/TkxplY0mgFl0t5fbm9fDvP1yUc6H503ydJLSajBzollDGNx5wG8Rq62nYpZt0RsvU5GwcrWisOeo/+P60Z/4ZmePsc7y8122qZ13JdtmnIQ/PrTTgdMCQGnJKixuA+oI8s43CgqeIxBpOcxvz4MPzwefzyafhyGk6THBJPeRjTCMBqdttu53l5Pp+/vp6/ruezLTN7QURmktTOKERHcwJlN96QJBBreESNKGiOAWgUHf/AQBR5hHyAI1X4n7zfLaABpfHu1IrWagWNqimA7JUKAsBddgm7W2Wrt4AwGEPa1CPCAIr7pWyv27xgoKuMRx4UOJAYOHMySRuSE/fQzl7IlLofMQDs5+yOr2h/u0cI+i0bfB+XMhN7+wEsPI7jYRwP05BEwpsj+b4Eu3Ic9c4sUUrp7o9urmEWVgkoSWLqk/k7iG/ZynVez+fXl9eXZbuZl8eHoRzHmddBhjwkSQmD2+QL7u6oezreMuZukfuxMfSX67bWVVcl4MMKkwBXZ4sI19Bi1aiSWJ6G8TR6lhfdfp5v/3y9fN10Aznkw+n0mVMCwFqtVF3Wsqzr9XZZ10VtJQbzcrud59ut1urmhDykKfEEMVGU29Wrt+FndVfARhpqPY5qXs2rgVqYRTNSfMN9vd897sF0V4Zrs76eGNIdDw4IEB7ewjh0MR9i5pxSygkQCJCBAsPJDSl2lEPsOSYzp5zy0HtDrTENb7kC7Uw3vK+TgNb/fDOTpJ6q+vvJLgCIcA4hDwBX9F4mYF8zwhyEwkm4EBGS075W++tsa3MvxyBCQWfzWHyt221dXm7nH49PPxw/fTqeTtNxSsOYcqC0Ifxel4S32v0OH/ZGUIRoIitq8zZf5uvP129/vnz758uvf5m/TyQH+XTfP9m7IaMt67qtm1cFj6ZC5oFu6AFhQREEKERCCZGQXKETFgKFUkrogzEhZQ6hdrqCMyhFhVZlEQZQSALOkE4yPUzHHw6nL4fhNEhOupVlWa4vt9vrrdQ1zBo4oj0zNysGAGYGtQYzvT96GyZGmEWkmfG1mhghqKfqDndef8AG6A7m0Bo/5o4snfOtHqGl1lqqmXnch3+NnEuEkIRJpEbMZStm0jxkAd2t5QRaq1qb31HLS0UkSxqTTKlpV7WRnFHS4//n0N7pMvswiQgjMMw1sFhoKeHQQUvsOdO0qlskYRoocZs8q4MFWINmIDFF806O5uQJABFoFrVqKVXdAbGanq/X27IUqxZ+D+0tKwJow+2mDAW7IEazPrT0NyYLbXciUypVz6+35+/n8+t1WyoF+W9j6g6KAkcKyTyc8qcfHqfjWDdbL2voZa0b9DqAggEFgFts3uflsc/4/qOvd2V67GHl3Q2EF9N1q/Nct4P7SIwkiScQypEhs4VFjhgJDmmwQ6knhdWTUZY0PJ4OP3w+fn4YPh35OMiUeEhZOC2lLmX+fjn/cn5+uV5fbrdL3VYyywQkKIkkMwsjOTiaBVKYeoYq1qOiQyiAke99a29Crghrchnqj4/67h7BImrzaA/a1KqpmZqrmiJieGAgI3ejyYgOQ6IOVO6hHWAP7VDBF9NLWc7rrUBI+KTFLKj9HGYWT3kkM6LcUc7mFEhdpib24smhz1nueAvEd+CL9++DiIaUwMEN3BwRkqRxnKbDOI1D56SZ+05gi+br3BcHElPr8EE/8w3CwZRZhkRIqBCgYQFq4R7rtt5u1+fnb99fvm9lC/SqB9eS8DbI8PT06Zgemj35XSkCd0gU9QdHezT8kDX+ZdVLMVQciXnDsQatgeqOWqmUmA2dE+cxjcfpwvR9Wf7pcv63L6/LJkiPpzSN43E8HFikVttKzctKfJ3n27at81I8atV1Wa6327WW4uZJeBqO0/BJ8ES+vMii62JFy1Zq3VQJhQCM3Kpu1TaNmsA0arVSahHPWBE0ftM73XdOA+42+LYDBkE7x5syLjTegTTX7V2nr2VaKaUw34Ecvfa69yxjx0T1Yz6nlBOzQC1qBnvAxntQjz4jbxmdd0xIR/oQEzlxE4x+dzUVhAAn7yszwK3pV7iLe4fTNePutgPfWJsdmNJgdtG7Fl7dqpbrOl/m2/P1/DJfz8vtp/L5S90eD6ejT0PkLImDmAihW8TjPmdvOcL+RK2YrmV7ns9fz8//9PrzP55/+WV++b5d/u7002E/dxEgNQq0u9a63tbN1ZqTMSI4hAaogWmEOTolpiycM4lo5z4hISVJPjKAESONDAmdGtgA0akJ8zA3cBulgYdJpqfh+OV4+nI6fJqIydWWy3x9vt5er8ttJQIWIkEE8nA3V28QVfRAM0zpQ7OUiXPK0lXksjB7uLkx92+/w1rBwyHMPFC9C9ZoIAXmaAosVVWbCGGns70daDs2ToSJ0COWWrFWIkpd3TLcrNRaylZK0SY618gzKQ8pDUmmZvBMDBFulg8G49uN/A3Jmga4bQG4JabhYRGmUIuvs9XqEECCKeM4kVqMQ45o+Q4S4/4qAnurokOOzK0liGauquuyXW+3y+Vyvc1LLdUMsEkMtxPKiUJ2p9tWUnmQKgAGUuxYFiQmNoY3ymuXuHfz+ba8fl+uL+Xl1/n8ctXSYlBgE2fq063W04KAAApiHA7Dw6fj6dNxOh1CY82jb+4l6moQIDlhBhcNDiSMGmoetrdi75/h7R/7bOyvL7x/EXcO97uvEgCHBRQlcwHISEgY7CpgBsbhIp4GzMdhJGO3MdBASMYhHx8Ox8+n4+OUjwONiRMTAqj7bSm/vpx/OZ9/vS5z0c3JOUsWQgISksSSpImZRxgRGoKQMQo7UyGi1qmAAHCEaDrnDXoTFh4OWvz9XRatgLGWVcTUu8JDQx6padFqHZ/RlfLDfe/Gt6uL0DEAIGj4TcvrOl/W5batQMR57FsyTcSDeSX2lCcyBWjIZBGMBCph1E+tNv/onN8dRreP4f9WbM8pDY+P87IxLm0aJ9J0KL3WKkyMUKuqGre5KyMRBWGvxQNUm4AVmtZaVqtFCAeRIQuyYMBsdV7LbVmXpdxul+vtvJWlWC0e7rBudpMtI0BW8yMhCkvju8OeJuK7SGNmYeCE5h/q3XmYgJRLZaMoAVbqpbp5TGiiFc05mIUDo8Si29ft9pfvr39+vRI9PB4HRypaSUsS5Cyj5AAqRQnIq5u5uW7bus5z3YqbYUDidDqcHg5PAiffZOS8+KJbXW/L9Xy1KJIB0ZhgXm5b3dwVMcK11I18dgyoEBWqvYdk90mz1WrQHkDjsyEQcTQg217KQ7izu9Fdkgr36AUWncHYMnsnCeQAdnQgvuOTqQ1nA1zNaq0sItAIUPuyCWjHfR+r7OQIgH6wMzMAEr+pgQLApnUupSPIILx1Pq3Y5qtuiRkCzLSqWlMkxDaQCmyz2D4KvOM3OkOtQednWt3Cw1fbzvX2bT49TMeH8TiN02EYxzQMKSdJwkkkUVOWhSaabGq2aVnrdtnm1/X29fby6/X56/LybTlf67JYUXuXwSMUQctcLalldw2lJlpiDUHS6WFBDRDtQAZkQoIkjJmcFdASBoAhIrDLGJDNqUKQW0B4FsZDgkGYQBLlQxqP4+HT8fh4zGMGgOWyzOfbfLkt19mKIgQieWDZVNW0y7W2/ltiyWkap+HwvqbadxOYGaoiADOlnFmY2tijP+/GYY0a1NSCwDXAzUHRa7W6rVqqaUPFonBLJRsig/g+FYRwj2rVXCOCiRxwQE6pQ9BzSiWXqqrqjgTEgKyAXrWUwkiyI99P6cOp+9ti923Kvk8hAdA9rEbdfFt9ma0UdwsSHCb0YKIo1fbQztJLa/Mwfp8MWkSEhZqhe5jqVrb5Nr++nr+/vDyfL5vq8eF4OE55GlgoMIgwpUb8D4BAJvdeXCMGEjA1OQiQQu9Ce6/JELFs5fnb/PJtPn9b58umZq3viQjMb5rvb1AcBGIaxnw4HabjNB5HDkqSt9tWVnVbTF0SUyZjoARpSK5eoCiY9RzkN+gr+ACVu3cKWlCJJkmPHcz8cayABJQwkMw5IgEmIqRwoiB3CiNQROOEMubMkBGAiTnlNB6Gh9NweBinQ0qjkBARYtWy1OVyW76+Xr5e55e1aERgIpHMvbJgbpYtjAhNXxEEg9EEipiIIFXALsQAb53S3qMOC/Pw+n6RRWPirWVN4Wrq4fdFrR5r3aoZIgmJcDKrAdawxEw7j6SLXoJHbO6XbXtZ5su6rGWTlLyjoxLLSJy9BpGKjIjVQwlJWBLjwJF0w1o7NOhNcIgA6Q6ku1fvQO/zLBDm6XggRHAvhaIt/YhaK7glIWFS09p0yyKI0l0fuYGqVLUBj01r3TYKz8w5p9QUcM3WWl4ul5fX6+U6327nZblyQsniyBqwKWxFkd0EIJyw00p7EXEXzELE5jGjagCEqEpvcCeAGA+QnGIlVdzMV7XLihg4Zk2hDMCEJBBUV79q+X5+/fZy/n6ZD4fDA4u63darsQ1k0/iQcjb1LJlJKIiA3cnVrfEmIxBAOE3D4TSd2I+LaEIhh2J1m5fbOakxpiByEbzebuu2mhlCeFi1LRRq1Lqablrq9v6N4N7/aMEbIDAiiFpA7ypq+66LMHcEIgLsYllhFqhePQzdkYAFGSMFqkNRoM6tIWJGJiCMu1pwOAPsEoZI987BPklt45V7qKA9eUdEJH6faa1Vb6UEokMY9NCsEcUVKmC8tV0w2jipSYJEOLR4eccSNrJcH+gbgoeGLgEBvnm51vl5eT3m6TBMx/HQfh2GaUxDlpwk7QLh7m7Vaqn1VpbzNj8vl+/L+dv8+n05X3VdrWh4M+y534UDbIkNpIJXHIECq6Caad2qVggNBXeKSIRCiODoyG7sLpRIEggFmIAjEguCuEyB2ZwgKlb1UCeCYZIk3MhTw3EYT8NwHPM0hEFZy/X5evl6Xue5lMJCnCQQzWNZ6ro1V62ghpygxCxpGPI0fii7EADJIcAdzBApJck5jXlISVpARMQ2fFf3zaCaa20VXhSP0tXhVa2aWVOulcR5SEPOOaU2RGrYCDMLU3Ov6hHuHOzhAESSRDB5DINZVdWibgEGpB6qprVstbS2SDuy9WMG/1fkNyRosn/clTYhotbYFmtCYxhMSLgDC9wcoXNxIlDSwGBet2oVtjmllDABIQQTEjcCaKPhtuEKwTiOp+PxOq9rqVq0pMqZSBLtxPSIADBoLDRCQGkKt4iOb/OueP9uWECSnA6HQjGnShjV1mJrdYsADhrHYZoGD29llqlDy4eJOTGnxMyBEOFOSJmmz8dqbuHbbQu0CGeC6ZCffnwkgPkyX1/X2/Na1vDufbXXfkRE6NCZiO+fdu9k93EABUXQh98gwkNqPcBElIgyAAAYgO597mZphsx5wMScJMmQhzGnKQ9jSiNj5mACJAiATe0yr6/zcp7XpaoDATHt8IdWJzMzN4sRRPNQoBDyhJogZeMslBi4eocPtZOlkQMJIZrk8G/m1GYK4Vvd2tQKAgC6xpyZLdu2lK2aIuGUBgiFrtjASEzIrdHcPuRW61br8zy/zMta1Ryakid0+HGjpdaGdmEiDOomVJSGkLQhmoG+k7/GDvCk+697f/tjo6VBiTAiMUPqSpPruiYmSBIxElGShNAIzTvjjSIAqfW9TBteI8KJWVCyiOQhWOZSvp7P//Tzz//+z3++XpdtU3dDpJyHNA4Krm4eYBEskAeSxETc8L3tftsUwMyaaQ20JpwZAFTj2Hc6Av44Dk+m6VaHUvIy62pV3TMjQ2SJcSJmoHGVNKs+z+v5Mq/zFlUxDGBbq9fr6+LjaCcLP47UQC3TMJ0OjxZVbQBQ021db7VsCIhBYeg10NyrN7nNCLei27IGCmUAMma43ebbbS61tAfecIZr3Z6/vZ5fzttc372OUNVoo42u9OweYWa1JSfUmye7CGZP29qTMdVSi6NW2AKVJHKWPI4IkrYBRattAeDa7MVERO4/Ig2ZmIRFRKhRDXvwbgQ3tL3y+5Dlx94//4i1tQC9dxIQfG8ntNf1Bq7tIkpNqLRpcBk2QeYdw4v7ggZA4EAKbJaPDEG2xWq13myWjeWWsqQxj0NTfOCUWmu4TXlNi9dN66xlruu1bre6LrptVjTM+if9CC0irOOgjJXACEBQ1NDM1nWd5+p1rRbkBDEwZyFGQoSqCr5mBIHAAZCBgVMWSQcawsc1WM2jFluuut1MNx+GnE/TdBrHw5AmkZGBoNRtu5b1ZV1f13rTMGRKyOhIVW2rtqxlKxUIWViGYRiHNEycslFsru/fEhFz6iUWMpM08ZjWIfd9RRFABCK7C7qjIbpTOMJsAE5MaZCD1mRa20RmHGScOhKz8eat8zY7RIcal4eZmAFI3ck8MaUkkoeIUHc1L+ql1i2iOGkQeBCCMKYm0PBu9PYhtBNgG8u3zsBOMQM3rAWWpZbNxoFEeK+MDcMJOUJrKapGxNSCjxaLGpERA4AwCKDr1/relgcIIjocJkC43pZSFftXHTG6q0sjXKLv2vRAxOFgZg080k7g9/UVAo7jMIz56fGTjmgFtcS2VURYpVrxMBiO6fQwudu6buvivhp2TxDsAtMQZlqNBAOEhtN4tNBSAdxUPUKQxkE+Px0k83ggFKhWFNxWB2vadhEBzCCJHULdvIZbh9l3JuDu3YVNYu3jTJSFxpRTTiwJSQCk9QUCOACbuj9CMFJOg4CkNA45T0MeMw8SiUAa8rRJuwTMpbzM8+ttua5bce/KnC2Mt7SuqWo06i2iUSCQMxpDTcFJODEJASOQB/r7Ywq7jgvsGu1vl7tDeNECRN7BpZ2FqaZr2dayqhaIGFLyyB7asG+0N8nbmQoOq+pl2y7LeluLWkQ0QW01q6bFtACG1WJeGwaPurg7J6YUzKYISztnEQKofeJ3zLc+tH6ztnx/F7VuEJGEEKEautu6qCfhPRsm6soz2Mh7iNiwSQhuFtHNWwiRpVnIpCAuFq/X+c9fv/3LL7/85ddftk0jKInkPKAMnEeqDlQDHdAl0Tim1KXToAUz1dpcYe4xPiK01mYpYR8adfBZ6A9AyYBXtdtaim8sNQkmwpx4SDgk40lBbhbf6/Y6L8uyelXXpdpZV/dSk06TPRKJ0IjGTHSYDvbpKdBVVyJ3L8tyLduqhuCsJQoZe9Wqrt7sJ0y1bBU4OChIkXxeltv1tm2lFeINbFhW/fr9l5//8vNJPg0y7YEyTBt+u1nO9nrZzdxNEZvkZzPn63t7b5y7W9WKBWqEygZZU8J8GPJDTpSsQnBeCzdBYCbKOXES6kaYyJQxZ0QkaCZYDg0bvVvTtOiO78CxHR36N5G22L8TAAIcetehT9Cho9l6L8D3CbjtVLr7Gr3PY6BPmIAAmJGJhQgJFK1CbaNmAEAgERESJuH2V1MRbWMyr5vr5rqZ1vDaPgQ1EAwCdGGe+00EYElckWqQAQdncid3oWCv4Oqm1tjpFECQCBhQzaK6bSBgKVhy50IejiOPsDFsvlotZdNlKXX1cBiEh9Ph8OkwHgfOBBwNb6ab2uYJh+F4AAZIYOQKdpvXeluAGNhYOA95PE7DNEoagEjNwfUd5glImDM2pyXkdtYRIrqHofMuZYIdPxMIkBhyoCsUBFF0x5QkMGmttRY3A/eWQIkQUafOd4I79tfGRE2AAZEcQtUwkJGIeUjSgnI1K6VuiAKRCFSwzS4TS04pJwMo9xv52JDvy7K3ptvECCGEJaUWahXJiJG71TEQO4DWulxvL8cjlTokge6YZNZaV1KDxJGleS0Tk1uz4AxmFElI+PT0ABTFFLgJPTYFx45d3PlK0bZoeKuGmmhA22xvrWwi+unHn8Zp/OHzH5mGH3/4uz/96fb8en55vrx+v55fr/NlZsJxFHcfCtHZHSsCEKJFeGip67JiZAUxj0SYgjBP+enHpyGll+eXUrZ9WOvEPBzSVIdpmwwWxwIWgthKExkwjxgA7Fhm8KUdWdgEc++bIwBaI+P92xDhNOWchYgCUD0IiUK8k6iJEBPRmCilTJxTGgdJWUjYBQqFI0AEKXB1WKp/u16+ns/nZSlq8b5Wvau19JFik3dFgHC8w46QGIkRpbVPIjACHQGhWz8CAgFYdJHWd1drR7uRqSPuRAlqbWQ3q7Vs68zhGUlERhglcWMcA0IH0Dk4xlr1VmrxAKCmo+nmtZZluaT5JTAT56orgBMwC0samnpxY9j1Rxyxg6f3D77zfvaTGd8wafvlbqVsTCklQYqAOpetlAIxjEO+j1NBYFckbRbz0MVBiACwRf12ABOiAa1bXbbbv/z69f/155+/v54dYphy4iECPagq4OYNCt5ezTjK4TCmJC2U3ZF00Az0VFW1OShvpTDROI5CjOUtbTyU9aHMaVthq0vRLVDHVI5jTCMmZgyRQR5OK/JrKd+u/rUuL8tt2TZg41RocBDLfnKsU344pEeBkRhPD8dxypLIrA7fOKBer9f5tpoVVZrniromxFJra1W3LoQWo0QkDECBvm31cr2u6+ruTWDUParWebm8vn4fHqd7aG8dGgC/uzv24qGTgdrcOxAhCeeU7s+/oaKsluZCEodNKHhMdAx+GIZE6BSUljWZRYkQkpwTS6KGntj7ORHdof2eFkLT3EZEQo4Okm8b+52cyG/QmTBInmKMgAad02gaAb7fZQfoQu/z7YU/YETLQd8OEdwh+gjIzbCE2hps0NAmpIzUdwAaukGNqKAA2mqO8AgL17AaphCO4D1nh735QTta813iC7HYVnWrVhufs00nOMt0OjRC5HJbtttaPUIrpMRJRDAc1Gtdq4LkSDBib/QSogtUthXq6qaGTMM0nh5Px8eH8ThKJqCIcIqUWI6fP08/HB6mTw+HB0rk7Ksut/X2/Pz8/fvz9+fn6/UKhJJkPBxSTuZQm4IhfZTqY0mZTZsqPZh3R0UibHIF2gB4EOg+kB8TPAo/JLDNXmNtI/eE7CxFmKjl9IEIqlqrWoCZtdb1fdbSTtg+V2v9XST0KO7oju7d1S0gCyehw5jVrWEduKsc4sTzfzi072cbvA3dHZBYJOfIg3ioZJQEidsMHgk9vJbi86y3WbZyABB38zB3K4ERVBWJg0WomdFieLi5BjgRiBBz/vTpAQku81xC6V3vrKGliahFQ0TgVlACNgmq+7D33S3Q8fA4HabT8XEcjp8/009/tGXbXl8v37+9fv/2/PztuZYVQiHcNHMOZDMFN4xi6l4UeHPaDMXMB2YDEyQ+HEd2mG831RINp2KOCJJSHnM+pFSLGoBBIrAaVpQHksmRgR3doW4ednec6sdBYzneCcpv70Y4jUmSIKFFVAsi5K7vzIjEwIkxAIGzcE6SEpM0O7ZQCAsIDayOc/HzUr6ez98ul8uyVnfgO0LofQu6+WoAtW57ADVZyj56DiJgAhZgBucmIugYAV3PKZAAOfDjZIEQA8Ld1BVI+uSntdLN3VRrKWUlCJTESEPKIiySmooTITIgAKjHZr7ZvleAIszNtZR1uaZhQholTe5KCAbOQsxCJAEAYLGP2NtBiB0E0ZAg/dDdEXT7Cny/sAIggAhFOMBQW/Gn2aTDT5vnQg8zvYJsgJkma8LB1JxiAgDCHarZ5TZ/e3n9519+/fOv34puSXgax3GYthLramZgGsI0CI8S44DTmKdxSizUEf54L9gAwFQbA8rdyrqlnBGR3+n+AoSsS96WXGqYbe5OVBPVMcWQMYsL+DD68bAQnGd7IXvW5VyWdV2NtpBZavAAGhVRtvFapxWZmFLKlHIexhxhW3283h7H8ShyqYputG1OriGmHp0uCejePEeazDkhUK31druty6KqJIKIu+VvVd083mFlAaLbOrWcqg0PMZpOlnfiFiAyUWr0/sCK6uoeWq24b4BFoFImnEY8EEwJUlAIrcoDcqImJZaEOUnzIL7HUTfbMWywZ1cYvXpnQIAmGL/7+BFSdPLFh9DOTCkkAsgD0MIBw7zperY7oH313TPS/r4RmycNtp7Z/QAHhH1rMxLuljktw9zTgjYvaDTu94rGjY5vEAadvvm+rXU/K+LjjUTEZmu1olbDnBzQAQOAKY9Dm1djoFav67ZWRSQWS5JYqBZTV9BAwQQeEi5AhOiCLmCMQSllHtPx9PD4+dPh4TRMmdrvARDMAw9Px89fHn/88fOPT0+fUVCx3ubL+fLyy6+//PLzz4e/jN+/f1c3ZMrjiMRb0aja1KLe73MiJGbrbRFXi6osZNTUzs06FDaCwQeGKeOnFJ+zF9MS2+A0BFOWGNIe2bu9sqqWqrXa3iJFAGgTutY+7UL00BqfEe4WUAEIwLwxGajVPEToHtUbkIjbcZPexXX4Wxry/R3eb0EYRJAmPtmQR0xN2yla/hvuVqpzAeZtXtNtOUYMGEGAxAmBLVCrRjHkRrsXIux+9aZND4GZj8cjEFUI3xYAsN5DbLzczr/ruWrnlkDTD0FAQiKzO+o0IuZbdedBNlNmFmAaxvzEn4bD8PA0fv7xcLte1uUa7hBx/JQfnsbLebmeF7uFbuoQal4rUA0zQ+AwJucBUoSP42Cma11qAzZ4Y9CyOyBBmogABaVu7hghFlx5ECaqBWnGCAjb9zjsAJk9cry/iCmlxM1Gz6KqI7kggVMAYwijZ3ZCBAIilTDxJtnW/BtCHRa166Yv8/Z8m5+v88t1XlRbocftF3cR4r4G2hM0hyYOYA49czR0ozDByIKRSA06FaTVAwSIwCk4Rxo/3EjrBDXUSNMK3jWW3ay2X2oKZm46pjTmlFNOTeV7bxpUIIso7RMFdPKxRQQo+baWtM6S5163IQQYMZk7CQhTxhgARXfj3l0HHnEv299dfTd8rK4kpen0AM3fxa3WioR5GEjEwtey3W7XliUxEwKaGSDknCVJn703mU+PZsVeqy2bfX1++eef//LL88t1XpPwkIdpGIc8uFshZJTM8umUHiZhosR4GFPiQbhT4dW98UeJOXYOOBNhRGus3Su9+6VLLVuloEi5iBeIzbW4iQhORx8EjoMP42Ll5nq1crVy87I2B9fFBsABmbAW3moppsVRInSeb2XbhmFAolI3JOY0pDSV0hwgEpBQSpyERFCYgpmJJTEnQkEyJHCLZV2WddnKljizJLcggnHMD4/Huwh/3yDYULStwddtIO48bUIUYUKMMFNFBkSmQEJ0cIWtxhVxyyOkg8iBIS8baK3nqHSb4bpGUQ7MrYsjRJISIoZHVdXa8Q1tyxBzt/UDAHdwp2YmYoZmqsYEIUDWWuHvMy2obsWUSICJEATDPBrSvu9H7K0xagO8PT/Axtjrg7x9ueJbSd8cF5y8S8befwfsviANINPweTsytgkrYAP4wt7CbTHvTScB76fFvskjsAYU8y20dZqb/R4hoiSRlM1iK1qLbnVTW4va4QDjOPA4EA7IQFlwEMgMCSERmaQ8jBYiGZ94GMbD6WE6HsdpymMehnSYDg/H09PDly+PXz49fv50+jQOY8piocXWeT6czuOYZCQGdfRY1rW6MwkQR0IWAQSh4X2O0vGnjZ8bTt0xp6OHGsS8tZBThKdgAyy1lttyudyeX5dClU70gMPxlCQxunl4YFWtpAAFoWIXYkGAMDOPECZhwTfd+H1CA0CIjt7wS4gYCAZW1d2agztamx+7J6kwvDuvPhzBH6r2N9gHETLz8TgMA2FTM1aotZ1xrmaqoYalLPN8JfAkkjgxMQaHo+2ywIhkqbtSqqqHAToRsPAkCYiu67Jq6fUrAuCuvtuCA+4zDoCm9Nn2cAC8J7y6x7dv55SXMsN0OKYhDYchHwYSzBMfaaSkPChfa9v8D9vh0w+n1+/X5++X8bwsSwEOTpAyEYRbDVOviM5IRkHDIKpp3m6l1LKpVkfmMKjV3IGTECIBoxIQOJiGJknDkHSBkkMtmjXl7jV3v34zam85WtdCUvei1ug3bTSBwIQi5G1vYii5QtVm810Vi2MNuBR9mZfvt/nbbb6uZanqLfj0wTDLDqSLN65AY7cRuIM1yV1DM3IT9wyhBChQOVTCoCmsdn+WNFI+4Hj6cHghYgMHNLPq1tgDaI0pNatuGqamagaMOObEzDll7pIMFIg1MCJqoAP1OeMOjjaFZgprWlwyEQOgdyAzIDZenUkYs/V5U6tikBqgrz9V2OP629/f3o8wT4dDz0o91JSYhyyJCQlr1XlZCIH3hExVe3UOQcz3eq9tymo6r+X1sv76/dvP3355uc6lQpJdZkpSEk4JE/OY5MvD9IfPowdF4JCoERlE2APNuwUlEbdFhIhN58RUqFshf+gGbastq6ETIBeiYlpqqbUAIudMp2McBxzENnfEYITMnrhW9AjcDFhYSAh0c6vmpiE1Aub19fX1FaFp38ayruHIPIiEOTAnksQpcU6SJeXkZDw0wzehnUdj7uu6LcuyrsuUJ8mZCIhgmoZPj48pflOK7P2kvesE0EjPnU3eDUPdTRUDibGzw0ANiuLKUnhI+YB5BMqusLp6mf0207xl15GbUK57RFB3SrdayrZtXQSQOjClveJWrEPflF1J3j2cgoKh4VPe6/4CWLiGMzgB76NsorYb0ff8f+/19Pl7hw00xXrv0Yb2PsUbUCQwnHZIzw6F2SlEgN5+GrXuvTcZoJYYd7X5O57vPaxppxV9aD8EQPUoZpupeQ0mFs5CSCJJMrGYWYMtN6YSiPCQh+OUhtwoUcg4HIfhMMiURDisFx8QkHIehmk8HIfxMIzj8XA8PRyfHp9++PTlxy8//fjlp9PhOAwjgJvVrS60VVfRIR3ycBzGQ8qZ0hYlqllYcOtjQBN5+3AK9+jdjmgAhGh4cXNsKHB3QBTCJgXHEVHnZXk+vzy/fHs9F1z4NjEPn58GGTImC7TAommTyoSlTda4n5Cq6h5J5H4Q0w6+2Ff5LjmI4BgaFua1qpu1ErEBOcNinP7DoR3e4nrnv+0pcBBBzszsZuEWra1jGggQQogkwhG4zCsT81EACJrrGgRGUB9LNcRutDMdIJjbfhdzZvU2ZW8SVNCsKPfPAwh8V+JARIDU9pw7OLwXeDKzf/P/+MfAOB4fDsfD4WE6fDqcno5pZORQXUtZyrYq1sM0no5HRg6Ln/5Yl7nMt7LMZd2Woqu6qmlZrW7WnGcdgFBS5lQ5wLbNrrcrJxzGqRYtS63VJUkAqYFW0sLAERiHowzD0Q9VDzzrZqU2e8VGGdtr9t8MFhqcMyFyAKp5qYpAwMDN7mHnbO1NNAvVUpbtdlvmclthCzZOV9Xvy/V1Xc9lrRFBxJxYWHaWG9253NjmAruoV9MYMgczMmc1UUvuQ0Rga8uHRhg3ASeSzGng8STTSR4/+LUDYkcbtVOjyfFDE+XQYrvkcKPTVi5VJWDqxokNqx9oAA7oreMf2ESK25gfgsOxSRoRobAAUmAQSwdHChBUqjP62lz9Gte8x4ffYOh65/G9cCIAABIlTkQUEY1xkFIapgMjMkYAVFXuFFNoaPlGsVKtiRCCWoa+J8RxW7avzy/fX15u81WtskhQFIPNiF1I4jBRIjhkfjpNP33+pIalunuxCBSRYQinQM9qAEjCbg4IRJhSw/V2Q6rfDHquFaYNbHPebKteTatv28hWixDJ4ZCOh5RgAn+cpi+Pjz/99ENB2Ji8aHFMVaxkpxFSDmvOzg7k1ebL7fvL83WeN27q92sNpJTHBCiSJbMMLMppTKMOAiKZx2NGAQ9rb8HNy7Yt8zzfbqfpNA5TGw6Ph/HJnvSa/ANG3rsLHwJz7xYToTu1iU3zWLuTMhjQIDRq8VKhgkQaOU9pGIY8TFkE0UutWlbdwopZ9ajGpLWhKJBUddvKtm3NSLcpl71pkTC1EBiO3f6UA4LAMBCajPK7GL1vc0IkfNN09YDoGExAinuY3SdHHWayr86+lgER3uZK7YuIgU0KDu4EuRasoONf3DGww70DzT0Mzdveb894P30RItzaj9zz4A+xI8K0mlattaxFi+U85JTTmPMwsggiBU4gkCd5/HwkpCzpeJwOx3GchjSIgwMBJWYR4oYdMbM8mEVjt1IKxDwMX7789NNPP/3hx58+PXx6OD5MwzQOg4XdbmezUuu6rtdluc7X6/X1/P3X569/+fr9l2+vX5/Pt9tSKiUGJoMIAmTMeYyf/O6aRkhCTILSvH4RhViYAUktalU1Q0QQplGyIGO1bbu+vvz69evPv76cNzMeWDB9+TQ+fMZhUJQatGlsSVaRkuqu2YGI0I4Ebmjm2I/cCO75OwOiRvfWMPOiRVVrUTML71V+2wqaPoyr/oY9zL1ejzemRqvJRATK5sXualoEKBCNESrgaVtNWLMYge3grAACbMp7LWMOaoVGq/PaIdQH6S3JBYjYe0/Q+X8I96XbUVgiAk3Mz530LRE28z//89eqdRieDw/T6fPp6cfHT/YpT4zs5kV1dTOE4MRjmGQZpmE8Hh4/g26+bTrPt3m5rWVb13W+bgttm9eAyKnZOCZgn5ZsYIHm0FCO4eauEEjm6DV0BS0I1PDRMg4HOFQ9ghbTomBvcNmeP9Jv5XKJWCQTCwCZR3Vlb/hFR3QMCzetWrcGCVcopdxu5+eX1/PyevOCCQ+HOeyl3G62rWGYKA1Z6M7pQO4nRMAu8tqVMR3Dwc3BDNVJjc2SWW5dIAxmkITKGEQ8puE4pEnSQcajTA/y8DjAX13RTLJ7+zAasl21qDZCTXvP1kbyHr6Ph8D3NLMfOHsx3WYxAYFI7dO6VwhjJuIUFMKMHTjkGIZQMBTDdllvaH4YvRi5t+LfOvUfWvLY56kgKb3ZeqaE0I7lcHMCiiBoAmRCFNEsGokYyauquQNgNV/W8ny+fv3+crneHD0PjJKYxYA1yFGGgdMBMvoh09Pp8On0oI5bsbUs7goszUQsAWVLQIQoCrqXr01HktoU9TeThQq4BUg1WdWLg1lQ9W2rVR0ghpGHEclySsc8/PDpYfY/aOIifHtZ7aqmbDWHZIyMzuEA4EgGZBbl5fz927czYWLOjImpJ5AiRIxAgQJp5DEGQKCMKbOBuWorR1tov823y+X86fHTCR4QgxiGIaPjbfVS492Kggaaa4KVzeMEERpctzdlsEuit36zgtXQ6sW5phGHQxqmMY9TTlMShnANAC1ewyq00E6kBOAeW9Fa67Ztqmpmd5fenu3d41079frIdJ+89Rr6rSV+vxLnEQb3sA4+tjZUbzMcv38jIiK1VLZlFbhT41oJhPtM/m0pY0RTBYW2pe9Qk07QIWpNCWhpcjgRGllT3fR7BgDYUwJ37/h46PX//fKIspZatTXS3AGRJKVxHMbDhMTeznQMET4cRkJOIsOQhjGPU8ojQ0fmIgC2MNbmnSDN0omZRFI+HE4//vjT3//dn/7up787HY4pZYQIs21b1vVWtqWst2U+367n2/l8eT0/f335+uvz6/P32/W6zOtaaxAGoaE3vdtxsPcIeSZMzNDc2Ps4uLexTbW53wFSM4Ays7It9Xp+fX7+9dvz1+fXrVoaMswPafk+jSz8YJg3lMSUkTNiYY43piS6NTg5EUHzydJSw6NRmYchIWIbWBbV4m4Wrq2LEOERbUrT67GPKOzfHL+9XI/YcRq9SUDEIgQgZg7Fa6m1BuHIHASAzuAplJVoW+ISqx8cDp4TEbfu2F37gZnIEBGaQjIBgoep+S4W5N5WKyJgN4tr2txorRMfgdD4mhjo5GFBld/fw3LTdVtutK61hEA6pnGbjMigqG5aNzOD8Hkp5+vtMB0O02FIQ5ZEIGmgA09pSif3WurlfLu+3K54c43Hx+M4jgA0LTmyqtXjw3g4THkYtqIppU4TqVY30828BlA4RQI5DiMb61G1VFPT1b36LvkSiCiJU07vpz5EnGRgkkYB946h98YudC+1rPNlu57L7VK2a/VV1/Pt+Zfvz6+3l8U05/z5UTPeYFO2GDBJ3/RNn4Z3duP+kO9gmo6LdfNQQzMyE7VkPphHBCGIoBICC495fDwcv5zyKfGEPIIMcEj5t+sKAroVRQd/9VVcizdvxvA+VuwQZ3PXbisCrfnexIqtKTAzIUY7mYgQwV1rKWUZbDzIIQ/cGrWA5oAODHc2Wj/nY29cvrHY/7ps/80pvPd4MaecRBCxKU6Ea2LmjkPBJumYcwaAUoqatVbtWqoFIMltWb9+f/316/dfv7842MPDowwMzGaDaiYSInk4TU/HIZOPEo/Hw5jHABoyDJqKVQTfVDNnZh7yQOIeCIgppXA3VW/TnKbXVqAx/nosGTkZ0bVgqana4DAyuKEahKMjG5KGBoQwPj2e6JjlOPI4/kzfv6/n8DBFCGFIENxobEQwHcfT4zGPycKWpYQvOY05j8MwECUgd6zFwKCkgSbK0JQMsXPcm7WNu5dab7fb6+vrl89fPj99RgIRzEnAYKYKd2mqno41nHY3EIS9A7MzZ6HpzjZpmUAwt+pVQYM9H9PhMR9Oh2k65DQxUbgxBEYFM69g1b06oIYbbMUjVG0HcWKzCFPViEgpeTg4euxotF7IRIfME1PbxO4f5zxwHI4pnkxtK9ttvdVlc9PWf2qhPRCCAJlYEoqgMKMICiBGK7q7tBP1NjvcJ32hXs11b+juA/a2wxv3s+E++gd1AuDOsL0DnvbtCxGE6M3voQ093o1BLS7nAuCJBs5DYp/GaTqcpsNxPBwCoKpVNY8ushIRpWitdV7mNGMaUAYgacAeMAtVL1oBMOWc8zgO05APp+PDD19++Luf/vjD0w+H6UDEqmpaa13X+TbPl3W+rPPlen65vj5fzq/nl9eXl9fz62XeViCTgRLJVrXUahDAICAuH3pajJS5aRZwh0ZCuEVVbRqZ2B1ao5Ry2Rao3+z155dfv31/eT3PizB9SsMJS16f+QpYF+SxkUqJBiZOSWzXGfLwNnkRxE6hdSp9cJ6HlMYhI6JqLYirB1OwoAAysHIfxLTGLbgTv9sdfyU0G125sBtatjVIO1JEACKlXNlbEszUpmSAwaHJKzlACQBTAmACAE57NsssjWXKKM2We8dwgYeX6vOyzsu6biUYm5FDdIlZ8AhwcPSWjRJS8y4iBgj0TiK9xxHQEmX1QE9jRmCRxFmQwTSqeanu5hFR6jYvdVl0HsuQhyHlJrvYehbELBlSSpKFEhPF4WE6Hg8OgQOUOFro6TQNwyCSS6mH49CMlRWdDNjDEUhiOPDxkA+TuKuMICOmQuBNcLWZyzQlP07Dh9DeZJLbsBkAusoUBoC51bou8+Xy7Zf5+9fl9XuZz6q3up2Xy7fz63V+3dTGPMyAp6SD0wElcSPJEjijMzoBwY5UsLbDe3SHcMQAsEB1rMrVRM3UcgQQcEJncmIecj5Nx8+n00+PcuQYPNiCNMEHx4V3kLR9zLOrhqgWM/WwLtPRqh3cP5QTNQNX93AN9ybcghh9itx4QQS7vOG1FgEYiCBQHLi6gknyBOzEicSADdAA7V10+E1Qf5u8f8xPAKJrNLYkNRpgVjXcCDvc0KxnyE0fwN1Va6OzFDM10Kgvl9uv355/fT6/XpdxksdhHA+ZiEvlgiwEQnEY0ufHY6bIZEPOO4oWgQCNVEujUxMRcRCAqUOEsAR5RJhZA3a1LOX9fYyjj2aIJWwjDYkYgdxoK+EV2BmBHEDDKlTJ+DkdIbGkQSrpRctt6VrU1Mj11N7wMA6nx9Px4TRO53W5rGvxQCTOg3BKeWBmitBAk0zBAgjmWppKc0tyWypmvizL6+vL7XattSROKbGncA2iN2VThN7l2nU27zPmvd1J99Y3Qnc+CQ3TsCDjAcdTPn6apuM0DFOSkZE8lMPJBSxc0WpgdSCAaF6zPXXo8/VWyZnVWtsDCesqs7GvFt8ZrUQozBqgbtEK4v2djDIOdPKkhaV1yDQwzLD37nG/B2qirEiJMBEKIBrsrfidH7y3nDpLA53QpSWy1H0BW+fMMUAAwQNQwdVaJ5YAKJAC26Sj83ERGo7LAajX/L+53OP6uokQHxp/G1MeiASIGyLAI0qxZd7KWrRoNJBIKKAPI+YJxyNJxghyw1qjViu1ANEwThA05sM0TT/+8MMffvzDD59/fDg+MImZl7KVsrRGz+36eru83C6v19eX2/nlerncrufrPC+6BIOMlAgVILRa47MEgcRHY7Em7tbc6Qj7KdgF1gKgYTYBkCE8tKjdNiurvq71ulXVOqZ8GjlB2c5fo6yUDy6j0Yj5QPkgMiENCqSBfm+QIxEwt/YPABMHEFNz9GXGpj8SlCATq0Qx25IW9dqEhiPAI4iY/sMN+QhvUjDNrro3Kvu/gjsI8zhM4FI3BtdwZCQmAmcvbEAc6G7VrVAsVFqHhUmEGn8kCw9EgkCVGNEbQ8MN5nl9ebk+P7/O2zo+TJTYItCbS1LrWDdryMDWLW4RMRr9X8XsHXALGYQpAcU0HT9/+eGHH396+vLJWXGhADRDpEAAt3CzZbFtvSHcCGHMw5ASNM9OIvfYlm2e16WsjOTkkAABUAEkEsvj5+M0TRFU1B6/HKYpJUTbvCxat2rV8oCHh/TDT+PhFEvdnGaQwrnpyGGDDDZROE4o+QOgo5UkrR2GrUeHQRAQbrXM58v3X77/8797/cs/316e/fpq9VZtrrFu26azWR3KEjepY3pKw5QSJ8FAV3TgN5w4WEA1V3U1N+2FO0agA3uwBm/Om3qpSc0xKFFODESYUzqO48NhejoevowwQIFS3NRqhL5fV28xE7A33pv0j1a16q6xey4ANH4dUcuSwsC5DeFN1a26e7gDBHU/w4hwB1e3qMabj5tpMZWjwmiQPMQhp5xDRIbMFSNzKIQZ4i5i+5vCHfZg/9vjK1rMVDN3a9V5rRXCqXPKa7gpIiLI3rFXrapVaw3EYNmqvV7nby+X7+frZV43DXY0pzButqxIMbANVEfySTgLCooDraqCjo0ZDyHIKN3KzCNqrfOyuccgwpwgwNy367XB7WoIvAPYnIbyoMvMc8ENQDB4AiEVWtAWSEaI5Agr1Jd6JYyJpy/H6dN0SgXqZf7ll20+XwEOIpCEhQWAIkIkH46nz1++3K7btuq2XR3c0UhgGOXh05GZ1mWtHtQEKiEirAk5IXpzKAdECC9beXl9OZ8v67rIkVNOXsOKf4A+IIi0mqcPs5iZWe7YkZZERvcvawcYVDMDpUzDMR0/jcfHw3iY8jAmmijQvRZQNA411zAFVAeG1uVvmnQ55xbaG98xIlprpAEdYE9jo0d+v6u3MZGDWVUPTMe3jZ4au04SwHAYZT2Nddu0VugIgd7MJ0ZOAsgGKYADuBkqmrr1jhYgN/GJNv4g4qaqYm2iRT3B7k06gpBGsUN1LRG19wWjz/WbiTo1Jc3ex90FmPoNvtsbFreXNWURyDhJSuQea9lgxaAW1/V8vnz/+nq7zOu8gTewnjHD8TGdLDmmIYRIwtGqa1FVBSQmjSGSpKfHpz/9w7/6+7/7h8eHRxFR1bJt6zYv63VZr7fry+Xycnn5fn75vlwv6zyXbalRacAxjWrIFfRaQA2w9y+gac+RvO+iMCETuOmqFRA8QrspDCDgXSsKwyVYGCSBWo3zK6XbmJZjxuMobuXXrz8jfZM0Eg8kQxqOaTzB+BD55JSCBCQhJQAKYndSA3QMD3UMxzD0Cu4qBIIuxGlshV9U07WWuehSrKqZmWNEBP9GzPQ3R1fXTOwjo6ZRwrBT0YOAWYaBpgnAVUtAAAFRCHpCI1AMUI9SyZi8d32Tt4Y8N+lHyq056q6AhoDhvq7b7TavW1XzlhlHgJsbEFB0VGgfsrfJtrdB6d+aMgACETBQpJSnw2E8HvI4OKcJHJCIcjgQUli4u2m1Wk2LmjlDCJmGhptXdzd1QwgmR1i1UFkAaTN1BBbERCAQBtCywpRPQ44aZdGyllrq8ZgensbDpyRDxVwiFUgVxEACJdAcIEiIUgOHfbiNvgVbFy8Qupyqh5tVrWtZzsvLL5df/vny9Ztfzq6zUo0xIvz/zdefNjeSJGmDoF5m5u4Ajzjyqn5bZnb3//+ekRHZDys7+x5dmRlBEoC7m5ke+8EcTEZWT1MkqyIkmREA4Waq+uhzgHqouXGHnPLDxE40ohXDKIjBCQwi3EE9eo+m3vsgtHm4UziFZ0fUwOq0GzVl9yKUT4yZMQsV4TnnOaUzUFYlN68GzUAdfugfP56cY51/gNZqpv5e10e8JnNKwvcExgPVvDvO3DuAAaS/Z2uZhQ5MXptaN9fqdDKYLAoPkRIulGeaZlt6GIT2QDrMdj60Hu8vFuHvxX1c3+4DkgUiGp5MCAAjJCbA0ZhQmIHIzGB4nx50L0ICVX29XF9e3263tfc+lsFdQQ1ZpAhLwiXzeU6Pc5qTCA+5HNSuBsgAg2IKBDjMHmKs6BzcEYCFmdhtWF0NFMZ7RNxLOwJMvOe0rnnrqbsGAlJINvaG0Cl5CsiVmzFVBAoT7UuZz+dz//nT9frF9KbtmjKVkkvJOadhNA1IOZXn58d9b5fLVquxyLJMj8+Pnz8/Pz0/AcT3b99q30kAD8KYRzhgMPM8leVhRgx3hYDb5Xq5vF2v13mapzKrOIt/hB+O9fldPPqhe0REjCOcYYi5xlwz/J7NyaTgtOTTeT6dlpLnJJNgBkOPCONQDqMhARtIjUcIiySZpmmaJvpL3+EejgCj0uPdFW+wUP1u23VH3YZzbvfDigDvtYRySqfzkkvWrnVv+3rbt63Xptbvfh5BjMwMlBynwBRB3WLv3lr1Vk3NXZEAEoGwJ6GcMIlIEsnvj/X4JyAiHCMYItwF1YkdOIDCBjnK7jZ34RY4cjjhHq0Td/Leh2s3IurWTT1JJSIWsrDQgB5eLQJ619b31ute67pto7QnGbnhBEBmoBoiBM6mburhIzKLk+TT8vD89OnL56+Pj48iaTgy7XXb9nVdL9f19e3tz9fXP99evl3fXrVWU3X0EMIQ8AgMM1eEwwccCCGGubuk9PGcx/FBmbqNW2dcikQkxICBI7oNiJyRMgDg9CDLQ1lfU7vMEplCe71cVw9gTsI5cc55SmXB6YzlDGXBslCZKU2A4iHAEZGGHYMHOKCHm5paJILMmJkzH2S7UfccwAMIwQk8KCKEfxio/ja1w7CfAwweeVmcRAQABx6FxMyYEi3LRGjbrVt3BCCQhHNC5gj0HgHeVVk9oSsFcSA4hbMj0HArZZbetxFOb2a11dYbMWUpOWdhMTfzQLRR1ekw2KVDDRX38zzIeB/O/OCvvMvE4/C8ME48LYukMk+KQQwyokt7r61uvdUwPS+neVrWut+27bqt6o1zKqkgi/b2tm3XtjPnAOiB4HhZt713CFnr3rRPWeanzEG6275Sq/T0vHz66RTcdr1GrjRbbN1YDcMwnAARpQgncrRu+0cBnEfocKYNFAwjdHMnC+vWeyiEou6xXfT1e3t9tVAsgEmEAcmUNVAhGRYQDopmIU45mGIwHMxCLZpFbVGbt+Za3dXCnEATODqSBW4eu0U1AShL4ZL4lHHiEHSGIGuw1bp3sBo9IGgEmX6EHz6kZsBwuwo+RO13XvBBOGDOKeVcUsrMgiPPYFwhiEgCPrwwDGA4QoWHO1iERlh4hKl3C3NmAmQIIXQMRSTKC8IEimEYbYW7jdg79QnulKcPv/7hdKgNRtLhyQtu4YGIAThu8SAg5JTzXAqLwPGtDDhi7VHVbtf1dr31VgmjJGbGpi6KKcs0T5+W/LjkhyU/LOd5ykNtZQ4G7hHsYe+Zy0yQeIAHhDhNBQCFeMzCAJhSGirTH8J6AAh2wtXKXmfTQKhcPDiwGCeXKbJSAfFUzjKfrd26qVkXjC+fTv/P//031bW123keHJV5mnL32rs6GQI+Pp49/O1tNUMWenx4+Mc//u3r159O53Nte231tl+RIMZWGhwJhDjl/PT0/OXrZyLovb69vtzW2+Xt7e3t7enx6eEsLMASH2VjEdF6P6AXikFGCXMOOJzDEAEO9vB9Xx2OCmypwLzIaV6Wcs48kpWSu5uSKmkncEmEIWhDeITAIvM8n5bTvMwRoaZ+ZMjCoA0NNgkcHNEwdRsTVQQPdrDZ4Tz6Y8LCeGLOj1+enj4jpN708vry9vr9cvlz26/mCmMDxYhMnIpMjyQzodRmdKth0LXG3r2tRAEMQazCOC88xA7TNGg1dxjjbvIXDmHuLmwgnTh1FVLWztA7kII66KBB3DPKB6HuOK931v3947Bu7npbASVkQgwJwG7mrQOEWZD4ckruhTBMFSPOJzmdZD5zntDIzI0CIFDVVYMppVSmfDqfnj4/f3l++jwvJ2Su2lSt1lbbvrfttt8u15dvL3/8+ed/rOul1Y2QaGIKBvPeeuv9tvd17dumrcdIAgIkIU6pSCofD7qZdx2u8jhIYEdgKaKD997clId7EWEA92CQMi1nPi26UwaDXl2jq5oFgSl349r3lfANJFOep8fn+fGTxAPGQpScE4mhlx5hjjEc/8HVCQI6ojr3oO5B5OMDcEDAsQ+DkEEIwPxfAfL3uoJ39m/OmTmZ2fBe85EZSykXDidTbxGg5uahEXhYlwIhWI9O1tH74HMjCB6+UYfFGJm2gHCze0SmLMsSBCllHEqAcHMnQHpH2z8MV6O6D5Ev/SgVvQs3w8x719Z7N8MYoEGCghTMKCVPOaW6b9t6DVdCPC/nnAq9valzcC7hIgzg23rb17X16g7MmZATJkC9bY2bEqXazQANoUMAI2QBlXCLzJDYMLobZMhnKd1coUcouGK4gxQgGSET9hHkMveqKgiByAiJqVsntGhVazUzQmISQjb12hSdCVkHf8YAwKFa7OpbhwWgAAMlEWEBRLNo5k2j9tir79Xb5m0z7x5qgqbox+NcjZqi+bhY8rnwQ46CHd1Cu5u6a3OFMAwiGtnI8LfPIwYH1w7/QMQY4UKHpXUgYmKeSpqmqZTCkgbMO4yRImIIeu5Y4P0DhjsHGA1AD7K6OhoSFuIMkRHNDM09UCAvsBTYd0gTqB4+O+8q4I91/k62/nh5RQSOyBp2Ee+OR+CfgztgoMgRFDlPZbi7D/cAOEZUGA+kmTJ6EipzAkmOZA7qKCznZX5Y8nnOJSUCtDh4WON1OMTQS/swc1YLiKo9IHLOTBwOh4sQwDCQaK238PeDHgANvbJbCZtjV3cPNcgEAoEWUg1bcJacluX03Jm570SCTMtp+YXptt1aa4KPp+WhlEkSawUfQw55zvz4uPz881fhiTnO59Mvv/7y+dPXnOfL9fWQ896HYURgpjJNDw8Pv/z8y6+//mra3t5ebpdL2+vl7fL68vLl80+fnoOIJZePSecR0dQIURjRAtHQHACFWWQ4Vd+JQkiA4CNOioFS5JmmJU05Fy4ChUIA2cPMoLfoFbwDAyU+UpaJISXJOeeSc8kDez+eB8D7r+/ThB/I1P1zeH+9d9PCwUR5f7KIgSmoBM1IGcEhdyyNemUA9OHbes+ixgSYUj7N07k0R7hFc6UVEG340wQM3T51woaYBCVxERY5WMlj4qYDEwwwc2cz5k6aqAuxkHTtXUmVDNRgeCJ6vFf3fxnaAQCB7jg3IYtwEk4Q4F3bYUXZ1ezIlxGWnOjhqTw+JsmOrN2H8RV4gKpr9xAvwPN8en789PXLT8/Pn3IuEVB7q63t+77v67bf3q5v316+//n925/fv7e2u+kgCoODqdfatr2vW993bbv3qlbNuwEAEUPwh+oCMPjJ5ncCByECEwTE4A2O+BMMiDHGIkAgcTqdz6CPYOdsdUJ3cI5wszsxCCHMo0Vffb+oV/UK7UbTySmZ5Ggz5GJAQEnyhJTVwZwi0JCqixo0Gq1tIDrRgWEeEMr4+X98qP4Ty5r72MIiOZdSZmYeeg93szD3I7xYEqSErkPqB9WZHBNNRImQKBhdoodWYHAmoDKsQw8RDDAi0mHtpD2l9PB4Vhgeh27hePicRHgEQQC5Bw1PuqG+HvI4QgFB5r+9kfH8qeq279teS5/ICBmypMSZQAh4mZd5ngnBtE7ltMzLnBYIWndLSU/Pn/OcgaBrfX35zjlPaggkPAGQ9rbX67p+j+glswUB52bxcq2JnSFXxb0FbD2uOyY1Qix5BiRMRaxnb8m2a2vVOCHKCPr6oR6q+967IAYhEyajqt0ddFt1W8GVhJZzOT9OedpZehhGYB/6WfVw97X1jPuEVJZ8mouUeUqS0SGa6ta09qgNti321far1tWsGqgnjEKDzxaiJmaEkQtBRpwIMhh71Vat9eF0MILfhEe+wDDr+bG2u0dAkIeCI+KwlDH3kRwbIjSVfF7mZZ5LngbRwV3D7R0hByQE93eAfqwYYRDrnDAwHB3QnJwTrsEFYnaw1qI17RYomco5prPnGWPHYSZ2MOcOc9l3VQj87fMYnHtiIk4J1KMbdhvhNzEUWJKmeZ7nZZmn3FqHkTo6pAHmam5mCJiYElKZ5fRQOpWbiiONfZ4QMzI4mjpAH3i+UBKRsTCjgPAYRIW6tdpr7ZWEnh8fpbCNURIAcJgYem2thXw86FeWlJJOBjNqo91ipUgSCxr0mq7XuDJmydP0eP6sZYK6ZmHgnJgf0vSP31Sk1DVHP6WckeBgv5gGOnNME//260+fnr4E9FLy50+fTssDAGOwmqnpweSCkdqcHh8ef/31t3/7x7/99utvb28v220Lw1b79XL9/u379adrayqc8zRCsY4vD+hqTHSQLg+z9sgpAWThMeiOXCwmIgUOMAGkQmXmaebEzCEciSIBoEGYgjZvu1lzDBEmIQZCYko5y0iIGXPJcPz+gCgBgL/vXwYKRUTMMYB6v2OJ+MOwCwDBohSXvTe4ArKabdutmpokmh/oiD4YuV9qRrZZSjKVz1NGgQla79sbY45SEHyI1AEcsWP3uEVXg+WB5oVEiMiO8I77yhiOXbKIsmbmxJbNeu+9t0q9967YuyGOBc99xz428j9Ac5gTMeR5mpfTfDqXKSF711rbpl170/Xabi91vdS22+k0zQ/T+TyfH5PBZt4TDXsC6h6m1lon9XmK03L6/OXLzz//8vz0iUXUrLa2buv1dh1b9j9fvv/+xx/fvr28vlwHObm31nYdMnvtquqHTLlFr9pu1boioAfOGmA/DCIW0dwF6HBPZQwIBz8YNncfjEPAFe4Rwnx6OM/yuZSN94v3Bt5WQiLwiElwntPYbWjt1qtf+96uPJ2pLErJOWGZKBeQkqZ5fniWsqhjd3IUde5uHRRQAmgkaxE5gzMMlYYZYARR7ssHZdLfpna4d2Lv2sXBp3hnGt03kQjEkDKGEwZi97Bqjl2JOMvYDoCjByg49WADy+QZncEgwM1Ue2+9195qNyDgJHGQokY7godciuDO0oe7Lv54vfF+Wn4kZB//2kG7beu+rdu8F04AwQTAyIMgKJnnufSeeJdc8nJapjSD0zRNS2vnx8f5vHRr64a1FPRIeWJMZqRda9uRDkuJnEtvFrB27QqOmEimUHDStYVfqxSjTDGicJacMZSii6a073sLjoAwA4YfqomZt26OADwiiGIweOt67euVW1dVyXR6mB4eptsWbUdo2Du4BTlhBDT3TfXa4GmaMM8yT5IDrPW6V9t3rR1qg+3m28XWt14v3apH94yojCERFClc0CU5AioZswJGD6/ROqih+51jQyOoAJngbyDKIMZ7DPtMJKLhbWBj1SpMIjRNeZ5LyWXMduH36NU7EDiWK8eTgcNMywAMyImc2QmHw2yAIdgNeEJ8cOPWYiu19cpkzIIkiIyDJnRIhUaBp2PFQwfA9Dfx28DXR4pBjDvcHY/tHQLCWN0Ry/tkOsTwHNAtttpvI7/WgZCQRVICShmFOS1Z5sxZmIhiGDIaDiLCYB4EIBIfq8DAvdnL2+2yXpu2MuVpPkmCY8U+tBcAwyz6b3ljV8wJJ8bIyIIIyDthDfO6xfUNvv0BRavMRrmcpsIMlDKhSB606+cnSDLfLlzXNIpXzjmikJK6MioJ5qezn0VtZaGHU8mJawvTrq1pb8Mdj5BSTqVMP3396bdf//Hp6TOB1LVfXm/brVr3fd1fX98u1+tet2WRnMrHPJL7B/IOuoSZjyubmSEQeOCUPmKE1LWDxrhIZ5nmnJIIi6AgSgSAa2hYd+seBjQM5lCQmIRzTh8CPYF5sDt96EoG/8OPif39Fn33mzz2TaMngPiBLbtr2/e6mfN2CyBz73036xh2PFWEiIIsAg5B4AlRiItgwpn2+VbyFLYFNWYQocP5xM0jtDfXMI1edcSyEyELpcSUEiI5AI0Wm9MgIrIms8bciJi4ITclRALrADqEiqNC/IDNjQ2RJCnTXKal5CUnQfKI6NjCu6lp7b119MhEU5KpCCd0cg8HgkKJQaxjG4oZwFzK+eHhy5evX798fXp6LtMMgV211rbv276vt/V2u11evr9++/P127e3y+uqTU2jbn3fmnZ1HZ8OkggSg4HdReLEBB4M9Dcanbo3uyvdiflu1TmGyqHqYpYDfwZipBnhzPC82NPZ4JrW15dQq1UzUgCcTvn8MBOhm2ltfWuta283te7brQcZMkrinFOeeTl73306uRNSkjwzF8LUg7tTAAUNpxRHAiZwt2amFhY4kcH/bWkfE/IB57uactc43OiIWISRMCFyIBBBykTIOaVoDrW7Q7UgwwQTYRZkDkQNwBZcoRfoCYDcwrw33bd9XfetWa/q3dkCW9duHhAOeHiSBgUB3CeqMbA7DJJjBHlYeBzGGX89Z8doj11tXff1us7XQhRmPGKfhFOWAmiSSdLg7EOgEyMLL3M2n8/LVHK+bZ3MU6CU+fPnn1Ka395u19sa7kno8+cnSUxE67qTvG77bm4p5SnNgKlbqG6Xa00KxWnYpgpznikIrHieU9337k2ta78bNty/3KN1cwJwYAgM6y3A+nZ9a7c3bgp7APH5nJ8/LXvHt1er7tYcnAQFgdwNW+DuqdOJ5hMvmWS3re66Vx2lvVXcr3Z76+tL216b7Q4tMpMKRSIXmMRycidDgD2aOYSScXQwIzgSzQKGg8qg6NKPipKD6ThmVwMkw5Hs4hbgTChMU8nzNJVcRBjxEN2MjjLCYKin/QDoEYAIzO9QPDmxEwfR3Wqnu3YCWpytq+21l7zudU1cmezurP4Xd5/wvRM/NP/3nLuPD9Vf3bqbtdp6a642ImjsaG6QEM299ehqevciBcBoel3379ftbW97tyRIRtmYiUtKpyk/n+anUymJ+T1d5v6lqniX1EeEuXfztfV/vly+vb5Y2MPD6enZS0azwfU78GBzZxaBH6zXLz4lX54VF21moME7cFWL29WYe8HgdYdTpqfz9CmliXNKxJmTuZvplLg8n5ec9lla21V3ZipTqrW2vjluSFHKhFj2qoheEjLZrq23tbdde4+hfEE6LefPn77849d//PbLr+D47Y/v/+O//6//+f/7j7e3qxuMwf16uazrbZomTtMHPB4Q4Ui3PjIiEcEOyNvsOM/gBhHckXBXq9CBdRIsJU9zSSWxsEBCEANHR9cBdwUGCBGDECVioXRQO4czwvjFoEm+S9vj3mfEwTUbE73fsetAPAoD/rhrv2yvtb0SCQ6pekC4Afj9wWSmlCRPqcxpIRQ1oCTmIYlyOeV8Yp6IkrmM/vjocky1GzTtfdetBV+nqczzNC05LWXixIkc2QLBHCnIfawxmLkr3+1aCId/Lg5IAjHcwQ+Z6o/zFCMlkSnPJc3ChYmRPJEpdyUNrxDBELlImdNyznNB83arhqyJMUvOkLdq0T0cUiqfnj//+stvv/32j69ff57mhZBUrdVea621tVb3bbtcrm8vl5c/L6/frm8vt+2272tve+9Vx52BBEQkJUtKjIQe6EEAgpSZS0ol5Y/H3Nx712AKj8QjxzYiHDwIMUkSEWJmRCbKTCXxiacTpWfCXwDjDV+ieeu9ahckpsen5enTAwtFhFZte399u72+rXtvTeverJkTUkoJpoWW03p7ozwrCJV5efxUTg9zmRvy5qFOHgyICM7MSDJYE928W/T/wo0ujiSpwUlxNSPtFgFhw/kBkCPYY+QyACVMghAYXT13axZamzHuEk4EmTEhMnEmK16pE0MmFuhme2/XrV72vYX1iOH71M3VHJFicPLHMgjBbQi/8JjmcWy5ggap47BY+PhGBpcOtfl23W9v6+mxMEe4uJm2LpK6tGkqJafaqrnVXmlFDCiSiX0qVASLAE6ZfI5WI+LxdCLO17druDJBnuan5zMztdbMfJ5LLplTTpKEZJtWEdw3bm0ljNDoqhCWmBMxEpAAF07IHOIBroAjIOJDaXcN4kGYHK4D6q3W1mtT6sYGxKnMdHpIy6rbHnU1HWWIhMYJNMDdYbW4dDv1Tt6pD5PnMIwO1kKr9d3q2uut2+agEcyUODkkQGMIIkgBCVUMSB0xaKS14yGX9UAgCiZgRvnb1B4HueiAttCd0CFiiMRIMIvMpZSch7HuOzR0yIgiYiSjUgyEA4M9RoDN/UIdZjQB5tHVWwdpDakDjSvJzU2tmbWIDqbgBuEABIe+8wPORgT3CNsfpvZBvXbvI25Zu6uGmYcF0tDgH/AYIDKj2h3tB0Iyi9fL+v3tct02NQ3k5FgVlyRLyZ/Oy8/Pp6d5WkoiwAhgEWYe+Y8A4Ees3GH7U1u/rPu3y+3bdSslnTABZ5KCSAZNvQ1kGBBTLoH54/noNJs85Ckvc43aVaM5kwObku6ga9/g+rJJVpjotJwnykApPLuZKXCSlAhL5khC0pWQDNBqrq0Vh4LkWR4QchEHtPM8R8iOTRCmnE/zRDiUtPL86cuvv/7j89MXAvn2/fv/9f/5v/7n//yP69vqGoLJLNbber1erte3h4cz0unHT4PSR27zXdE+uv8DFT+4bQFj8YdKo2Qy4oBGIg4D13erzDsCODQYNKqdDCXZ0XKNwf1gxY8g7d7NfZiD011Yet8cHfYVbuaH0fIPpb32uvYrDr9Z+KjFBAgwAELpliMmiplQ1MMw4golnQRk76uGqbupMYO5IzKMJGQKEk/oIwZ7zjhnm5ImEcK7/cK7Y97h4s/33CgRccAACsJgdCZgit6g9/DhuvLhCwEEKAEnSplywpyQAd1RGRMCIyAjZMEMPCWZ8kje0HBlBkQWkuSym6NhkizT/Pnzly9fvj48PEpKvWnEZha11m3dtm3b1u36dnn54/v3P15e/nx7+3a7vm3bdd/XNswy7vI25AREQ1QCw46aEUrmueSSJPOPWFAAHKnb9/U0ACFxIiSUYVR136K7E0CwmWDfk0eRXKbz6WzdAaSbIcH5YX48FUmCCKrRqgkLsVxue6y7qlpXhEBUcowWb3VtwR2Yyvywvp2fnh+en0s5MSVnAR4yd7GA6gYAB4Z5B4j+89IOd3LEXbthDTqbAw7XQyJEH1A/jkhQYAomBifv0Datq/a6ttW0OzgTpMyZI5O77bapW8EkUD3Wbm/X/rpV5TACg7AgHx6LQHFX4o0NLfIwpggEolHgwdEPb+z4K9Lw45NGCGg91stWZlkfCzNAZO1aeZjmJgQ01YNqVOu+ba3uy1TCh6NGJ+Cn83SaBby11qdEZqZt1bay0DLNzw8PAf69bRCWEj3Op+fPX5nEet/WshTZ17Lvc2+19brt2qpaJk8Mw1vc1cFTGeJgYBTij7wtcItAIjkSeQfpzAMCeejcKXEuUWYuE6K401gHkRMx+GHd2N0udf3jEtC5sk8RKRhIgHoYmIWGd7dmvXbvAYaMdDDXD3obyMw0Q2Q0iRAcVImRHzsW6QNuZGeGfwHk71cv3Bfkcfi/U0mpJCk5l5T5uD0JAOGQLg2TED48H48bCGPsRYMgCDGNDmDkynWD2oFa5OaSjAYHWxDpAA0iOlpHUwyHd6PZH77eb9e/2wwgkerhNmqq7hYj58jDI5ipVmkt45lyLoOZMsa5CGxdXy7X769v274hgkhWi64AwKdSvjyefv3yNCdhQLfwiJRySmks0wbk+17dPWCr7eW6vty2W9Xp4WE+PU7zeZpPGNbq1lQ9DBGZRXKCEKh/vRFKJyGcsJ+pgt7CWnSsihDIDCmFQd2uV5fW2fWx4/wJJQWiGnbD8DHJsFDCEikTiSN6Tl17I26Igb5EsBUijrk8qMIqfc7l89NTRL9eVw8oZfrp6y//7bd/Y07Xy/rf/7//4//8P/7f27YiQqICnNz7ttXL5fp2efv05VOEfty7IR4SAB+5sEhIJHfZ8Z0XCQDo4RHm4IE+wjZ8IB9qvftoSAMRggZX7cDQPYLiWNAcnSMcf919uX6vwNBVW2sszJJSEjwsfm3sjyDAzIfDwZBBfjwYbqahI311TMpCMnI6Ncy0tXBC1po6ZyRWBN6n6/Ytyynh1Nat6tq09laHXRxTAcrhKUBySbMkSi7J56IlGzI4h4Jab44So/kddPmwQ/x6KNuJQQCDMRJFFlTBynWn6M1M3910jg8kAUmQGLKTAI/8DAxCR3RAABGiwhmoMDAHosGYoEe3FYLOaETAy5SXp+evX74+P3/KKWvXt8sbkQBg631bt3W93a631+9vf/zz27d/fn/783J5XbfL3vZu1cCCffT9gYDkJMBymOUHATDjMuXTkqfE6cfKTohMxEck7ggLDkZMORGRmo0NvpmCByFl5hu0a7xR2R/P/RmwLOenYElz7xpguaQinLOkJGrYcnAqeTnl1yu/XYlXpj3AWKjMbOgvL2/f17o7oeTTyx9fPn3+h/7y/Pnrcn7isrBAzpJLuVb7/VrDAZBxTPL8Yyb43y7g+1ru3eF17EYDYMSAOZoDEPCIJcYjolOYmQPcXMO7eWjgVgOhY7SIDJCAh2gSQ6AabRUvr/b91iIBJHIewQl8RGXDoFSPezYwMBxcR18NYz5DGDqBsXP/T2oJBoRF33V9W1/+ydrbvE5SmIRFJEny3eu10pD6hyPGvt6uWSRJEtnqWvb88PjAwsEGKQwVhM+PM0k4xOk0nU6TmV6Fk/A85Yfz6fPTs6ldehOAueQ5MTye921b1/UmaU3beIOqXTv0Bm7ISICcEib5wY1ucCEZObHMpSxFQKUzMUKlhD2oBzcAbWVCyY6kDl2BAqACDBqsWGADu7b992tYTS3Jp5yfM7IEujEpUxZPYsLIjJSRg0uRXDgVkonSQmlBWYJnwEyQCISACIFi4N/drTsAOMMxX/8LRf799xEB4ENdmVMi5JJTlqPTOlQa9xvjL34bDMaPH5GcMCgZEE5HFJWHA/QABt8VWYHUyYyhJ1mITlM5s5wQ02HIc7Tj8N4F4scXOq7s/2Sxi2ZWa2219t5MbQjKR6cCAdp7bbXrmOVjcBnNrDV9u96ut7X3miVyltOcU04IBA4UIQRZSBhD4/CGJso5D/HIe0WBCHNvrb6+vf35/dvb9VItRNJyOp2W0/n8wBh1T10VaY8AFk4peRDWv36oskxpwsSRPtWS8TTteI1WIQxgZhDYQMnq7aqrt/2691Nb8lPmcwBYqGRPEyIceT3AhyUak5BwSoUJrBc3BEKWKDJ3gKXop6fPKPbweLpcru6Q8/T89Pn58fl23d6+v/35z2/f//guzJ8+PaUiwH7dL023dd3e3t5u1+v29DgAjPtnAe8m+RAAFBgw8mHuz1nAONlj04iBw3KWkJgHAI4ogALIAR5AgIzMxEISGHxkno+pnWm4qqnqMA848OrxqMRd4DKWMhFDF30w5gLMtLZaa+va/67mOVTwGDQwhCOHDSLCu3lTVwRyqAqMRI7AkrTfdioUyZp1qwqbo2pQU8opCzJxEZrydJ7m+XSWeXbht4jr2rZbr7fuzfcAinfG0OGddxhSDqfnABvUPBy0CmEkATTEaOg/UB8itCsErNcbE2MEJwa02re9XrtWUBdinDEN1VYCSB40hFfsOPLmiCXNSz4ty9NPP/36269ff/oyL5O53l5XVTuUzGrren17efn2x7ff/+OP73++3q5729UUwgmDCQ833JFDy8wFWQLRPcKZMQkvU5oyo6v1+vHjoJHPDeCggxWGAH637u9matpNzRzcIbCD7r5vfU15fdBu1CbvptGCFMjdde9N9eTziRZAlsQPKc+nUy4l55SYs5C5jmgc87DQ2uuth8G+1+rWKfS2rrI8cJmY8zwvD+eHzem6++qyQ2lA6vRfx8PcNUD3jne4OI3FpzmgIYDCIfUEuze1jERCKZMrEriLWbvtffO4mC/mjxEPkSZIiRDdoinvG15e7eWt44Q8EaQgQaaBx/q9VwZBGqmOGOBjTBp2szRiI3hglPAvpR0BECjcvdn2tofrflvnhznPWXLKOaWc9rd6SVdJIsIkSAwXMuIoc8k5Bzgnfu7P8zw3a4C4+1rS/OXn5yc9r9uaUypFVGEquWsRptM8n6Zpvd7abeutMsD5/HBaln1bL9fLbT9ttdbW9q1Z31StV/JO2Bk7y8JI6WM9wcCBb2cpp2l5Ok8U3dp0K9M+tegAzfy2Rb+kjJIcqBuoAQ89lkGIOUKkwLj1BtfQ5JokPc5P5wMD4IDCWqJNXifpM6NzYimTTBNNiUrBMkr77DQBFsJEIAhIYege1s2qWTWPIBZzN/CQ+Di3j8dlPE8ejgg0lAZYCCMJCx0qo+MixIOPdJDWiAnJXd0OkxN3N4vhT4pACCM7GCMcwJJSMhd1cYVoiWkqT6f5S0mfiE6gDEGIjGg/0kUP26/AI8cC/+aniYPo77331lprzYcv3iDWASKhmda97q1yS7Vr62pmtbbLdf328rruG4CdZ35Y8sNpDirVCNz9ME1SjTD18KH0O5IfPy7dxxC/bdv3l+9//Pnn2+XCuUiS0zyfT6eH8zkJ7SU3VWIxN0QUIf3IAUaQc0pPxA9IVtIS88L5d7NLqIKV1DkyRQazffv29vKW3tbldp6+LOWZiIOcs0lx5gfmB07IKSghEYILAzHkRIyYh9sfUxAUQVomJE5Pn09bu16uV1MXLiXPOc+Xl9vl5Xp9vfa9nZ6evjx/nk7FyeNbtLe6b/Xt7fJ2uTxcrqPR+fhYAUD44ArGQX28ry2GSzXePS5G9MCo68JJJIsU5sKUESVcfQxsnCRnyM4ohMLC43uHfMXj8BtkYhxub3SP+iCEI6xs+A1bmB8dYozpu9VarRvJDzql8cT52OfCWMpDxBF95mFxhDCC+rEvCmeUvQWZQthIYHZMERgGHgSShDCLLNPycH54/Pp1eXgAV7lt/dpv13p7q7FpeBzlD0eUaACGj246IgYV5nBlpiACltEH8PD4wx8gxtj3ilhVtdZ9u11ZGMBVd9UdOTiTZJacmIEIgD3YPczU0KM7K7oLyVxyms6fP//062//+LffPn36jEi3dX17+369XVUVCUTSelv//PPb7//8/fd//nF5vdWtmwGSMCMJYQQDjMQ2uvdxZMPlKFColLSUnJms1zYEV+9fPkwkNADtMIgBQqy1IqIfSxu8E3yjqUHva628rae6VWqTt7ABB3u4em/u/fPzYyCnnERkXuZc5mnKU5HhKt21d3cFADNmZhHvvXUdqvNWm/z+zSQFChI/nM6fnz/jdGoyNzl1PnVMGvSUfriv/mVq//E2u++wwyHQB2UT0ZAAfRR4G/xNICYSyjOlhGBgNawq+uZgzQJbuFXV3DoxQYvaunogknh4aCAN2VsHUHegEWiaBo5Bg1kV7qpaezd1c08plzIJCzOWHn9/J2NbFhhOXr1G82b72lMWTmkkR7OwCB+mWlOSTEEa4mUueUpIwIm7a5kLMTLL3tpclvPpgYmJw0PX7UqIy2kiwn2vU05CUBI/nJdWMcJPy3Q+L4jW+oay5Llcb7v72jbDUOu13aJa2xjaSZZT+M/x8TPBGDFvQIFCnGms41MStRa29d6NhCRhnmg+5eVModgRmru5F/CMJCjiSDXg2oxUl6TnyWcCjsxJcrICfbK+lFAPRyZKE8qEuVAqRBkgA2TCBCiMTIHoDq7Qq/dN+9r6qhSsHNYiDKUoLH97sAYSdNjX0CEPzwh+ZNAfj9vYRCIQjCHsvvkbSdsaoXbQXj3g2Joel1LEMIVUs9ZBOlAzrJ0YszwIfRb+zDRjMHJCSYNi9f7q4j2F+v1///44weDKjv23mxOCCJeUc0qDbNPN3Gxdtwgc4GZYqMfIxjDTcMNAHlQsScR5SpwpaMjUAd0BkJk4APSeQDLq+n1fABGu2lvbW6uJmIlzLjnnlLMIZYjl4SGI6r4PHx33HxSv2le17lNBAdkZN/GL2xbq0CEiPEVMCai3/fZ61ctKtyW/LuVTypkTSnHJLvlB0pNk4kypiEjCSIwpXEoSUwwjYGUPkIBhhpE8i4sAI0Vgkom5IPBpOj8/PP305Wtb9+enx99+/rmcZkNv2q7rtTV9fX37/v1lnpfWPpCZI0aojAiPIM7BqiMiHBEFNlzffQgxDf3A5I8sFeaDNCYACQMQGZCZpKQiJZgyYRLJkpPkNKrd+OgtnHwMcofv6rD3GmV5POGMGEPXMJTj9wxiwOHD/sMd6+B38h0EBkRXRMKB0dxXpPftL0EMdleM9HcmEiFjkuAAxkhJOW1EAWhqfdvWt7fZjLp9X+vby+122ba1e7V7eA0dfiSDBEhIRAIA99IeQAboCAZgBu4HxfkHXVLACKEwc1Pt+76JjJ8vMINIylkwYYg3sGHqEWHqGuFIo2QCJVkez+fH56+//PbTL7/+/NPXZTmbmamWnNY1ar2pdgC8XK5//PHt+/dvb5e3fW9mAYAxfO0YGCnRyBzkwyqdPCgG9TIlnuYicwbhbmraP5a9Vuv10saanZiHMQ3c55MjQpiOACIIcDXWmqx5tKvu3TZou2rvZsNOxnp1bZtFBXw8zQ+nqUwTkyfBnIgoHEzNm3pzaBqMqUhkQTWLgKoWW8VmxgwkxLJ3u+6NyhmnM52MlqQEGmT2g6Ln72507xZDd7uOwe0MiCOjBe56OEIEIEdQBcQYVE7hRBg81kTNdXetuwc2dbfcekpMxGDo3btkmmOq0RR0aKNUm1uMxW3KDFCmkpJITuO4mqv32m+3ve6NpcyTDfYVgk//UtcRMIAjAAx81722uLZxrQ6mFAsl4XmZ5qXMy1SW5GKQfN9qnnKaRApvbR+pryLi5lOamta5zO4ODvu+ztP8+PCYU2JEZnRrOfOXL0+15lr3acqpEFUAjpxSomIBtapIJ2zecbtavW1gtp3T6aT2//J3t+/D2dHDdfjCOGaUlB0EKJS8eVW+ISNnLLM8Pi+tm5sbaN2rmhOEIwnnTMiusHeH3qfbPrGfkk2cz5Lm4jla7rpkiFCzwJAMXEBmkkLBZilIkAYsieNhDG3edt1vbb/Uet3JqIlqc3eU6B9L+1++VfFXXb97yToecXZDQAQDDYeAw8d/XNYIAO7ezbsN9OZwcjkckBwQwAEEQN1E1VoP2MNZETHzgv7I8MxUSAxTQclhPawfKsu/bqk4lLv/IqjEewcy7G4BQJiXnB9Oy2meAlDNr+u69b7dtt6dZAyzhznL2GmFmjXs3dVwyryUsmSeEzKGqQNAAAkJpeQAtTVV1d7dLCLexVd812CFmnUFQGIZ11AAkshyOgegWzTfXbsr/IWiRNTr9z1V1RPOWWajGYwcTcHQCFG7BE6ECdTa7fLWXvfvib7N+bnMc55Snj1NkPKD5CtnlsJlnnOZKLJQ7p1LTugKIYA7M/okTCPOF+OwFxWmNJUzYQ7Hp8fnf/z6b+h4KtP5NP/09UuaJ4243q5/fPtTm72+Xv7883vKJddPeD8ew+0KEVKSJClLEkkyok4jamvqu6qa6siAc45II+H0GEzwWLwQIpMHAmMgEeecwZA5EWbiNKxCDwJjh7E/VzdGQEIPP6KkRCJ8jNuIQMIAFAGmw80HCUUYwpH4b+RlP15VHL9poQhBePCFx5J04AKCKBzCKISByEiEiblwAFmQK4GlVCVZ4OrAW8V15estSWbFusd+rXUdS+Bh3wgAQTQMG8bWC2lc9O7H7izCA2001mra3XoMHsHf3kaomzXt2ra6SpJc0uk0T8syzVmKKPYatVtXr0CGaEfiNyABI0uay6evn3/55R//+Me/f/n60zyfiKV3tVkfH851X6+X1+122/bt9fXy57fvr28v2752cxhrXKQgB3IWSTKgQHSMgDDyYd5ImdM8panglAyxdsewjwd92/aX1+vYA0pKzHJXOzgAIPNQYyCTSCJEdk3eFtasvdZ6W9fr9bbVvVrPQkuR0Ga93tRXi58+tUBLRZipd+3aat/Xut022xt0p+4YkbLQJGTWm3lA9MEJYqaUSEo1uLzeULpMOkdZ8pOzqIcbAPxl/PCf5bW/WxK89zIR93zLcUt73J0HbfjxGCIiMUtm4RAKMI+CVtg60oHUIYEj+Jg53Fue4lRSNHWFu5cODS2uu6q2CC9FcqKQgXjRyOxFqHXXiGgr5NxTTjy3x38ZE0eTG8gjq9mHWwTC2OsguZEZq+3W17qXVYqEREikKZUl5TmnWVBQCk+nuZREiJYUPNahvQ4M8y2trTYmNvWAuu23IRMEDJko2KptlOP8tDiCeqSdmAHCXa1ubbvufR2ejuit+Yd1CTNKZmECgNb1tlc1YIJu0RW0g+rwxBTKuczT8uinpmttNNzg1SiwIlRAtkhm4iqhfKn0bYu94yTSJfec9172PgNAYQcOQmRgBkTqERahEICMQGAEjt2id2g19puvF9vedLt0cqqJFdRFp/LjqR8H42iESYYtC+Phm39YZPkdkn+Xzb5z5wbO2c26mfrYYd4JrAflLTAghkW0BXdz6hF1ckgYQbFl2U+zJpqQMnIGTkgE9rHNjb//4u+MgSEeOVjFw/b88bQ8nubTNI08b21thHmrWpJMxG7R1ffaamvD5l2dqtKtBRWYEy2TnCeaksAIExlzm3sYDDPeEWI/miMiEkmlTI+PD8/PT9+uezO/Xm+vb5fbtp/PJxECQJaUy1RKhwhD6jD8KY+vvq99vcHqyMVXtc20dTMIZ1D32l0ixCE6Qw9bt9V223beyjSXJZcKeUFJG8lGiTlzmZdcFoTExMtMJSeGB4gcsDPjPNWUTgAMYEGrR1M1EHQ2kiDkOU+fnj8x4qfHc068LDMw711Py7nk+bJfXl9u0/wdiX/Ky0z30u7RehtyMmEGADM11YPX1ptqr61qt5KmnBNwjM1u19Zaq3tLWCk2T0xY1U1tjWgISuiBfHh6/CWU+Is3N0ghER6Oh6QdkZnjsM3xsPewC7jfWy6Sj0Bylo80DiZKKISEg993CDzfWU80PrpxMBzfL7axN3UAJ/ccNAUmQAEkBzS3FMpW3av5vqPtOKxBu3s/ZAP4V1zI4I3dTxyNbIN7wHygB5gH2TGqB4ya/LcDEjF6GhaWLGXKZS5lKjTljlBrbVG7VyQX4aXM85QTc0JOnJYyfX7+/OXz159//vXr11++fPq8TAsEWbVeW99bdAcD776t+/eXl+v1pqqcaDpNVLt2Cwc8wr8BCILcCWAYnGMgRhBQ4kjDHhSvW9Vu21aJ0kdAHklYCiIiH84WFu7ud+q4IPK4z1SN0STazPVrjtSibf261T9ve/OO4iDIHBFoRhczv62KXrW/ru00XVX9trZ//nn5/W27rr626HoojTSidhsTDDGlqczLNC0zlxml1A7rpg5CaUopM4l7WNf/qrSPin6XId+VmTi+HeHQBAyl2eF6hQ4IZAYAKIlIOKVI4off58QUwpAFkwATkKm15v1Ww/eUGFnain0/Ln5mBCD3rqqt7+Y6zzknZg5kRkRhmcu0S4tY6667bcxdRJbP9eOYeDz7EAgDTiEMoVHXjzVRgDmgG7q32rd9iJmDAgTTLHnOZcl5ES6SZqmrzss0zdmT13UXkZILEYcFAb1+fym5TPOsbnvbiLmUvCzLskwtmjXLKZ2W2Sz22jkhortrb3Vf9/22RwMyrGbRh8XI/bNhKmXYamE1i22X5oiuFqYQiqEOEJGFppIWn9Sn1vNqtINvrt0r8o5wBQ/3orqITRh5M3mrsKslpibSJLWaa1swWAhTApGRi6CutVuAiwMGgbM0BMfDnnaP7Rq3i98utl6MIlo2F4c5zvrDwGthHk6ByCDIx/DJI5X1vVU8Rvs7z+5+iw60xgek3Y/AjTFa40GzQ2Q86m45HEM9esfAxby4ueqryPfz6SnLlKYFOQWn9zTQd4nLgFL/hTz31+l4z6cDJBaZp/nx4fw4lykl7YYOe5KmUgM9BuYgptq63tZtXbdwJ+TA1IKhR1YngrnweclTTghkDhoR5kHm4UJD4B9jzT9+ICIyT9PnT5/e1v0/vl3q6+3l5e2fv//x288/PTyeSyQRRuKU8jTPhKjcOnS4U+QDQNuu+w1uQF7bd22v3iu7MZqYR6+9s1ly9JbYmdRj19aba9dVPRuQAaI0oApCKJz3JZcZgJho3mEqifERo3jsRDhPa8kPIhNhAK4R3R0sOUOGPB4EOc2npWT8+fNo/as6bvs0zVNZXq6X675KfvHwh59+mZfHex3xPgjuEUxMpKamvQ+enLr23mprpl7SklJxAWXz8N6t7m3bdooUzsWciDysa/XYItoIZzVzJIhB4LXBaj8euvsLGPy8IeM8bOTd72GEAXR4bQETh4xfDwbnD9aZwlIgD2a/xuG9bPGODcWdz3wstQiADmbz8D1VD5TgU/AckAEDyBE1YRPw8BZaN9t69MF/G4jlAb4ezTHTsZPmuxDlLlSho7cGM6tHiDwCETLp30o7IjBxmlJZynSap2Uqy0SEHr7t27at3SpAX6a0lOWnh89fP31acskijDSV/OXzly9fvn758vPj06ecFwyqTbe93tbtersNVVvddb3W79/eWm+UeDpNKLyu23rbTH04+oQihNvQTyMGRXAAhBMyszEakquv12277XXvScoPt24u08L07iFhZtARUQqJCFHGYLeRqdIBuuB2TvrTA+AN/sN17/3SFROczzkVRkZQAI7mYdrrm72tW+FrIjGD1v3ltr7c9stua/Xh0zjkPD1QAQywZJnm6en54enpMc1LcKlKtxrdCCDx9MApWXNXdUP44Fnzn2yox+Pk4eDv/CcEHPrHQd81D8U4iPIOI+mP1FCNUgJkRqQIpbHVpJQ4JxJBBoeRJNFB9/Cu3dwC4D2DcAheEbBr9UNA3FSD0Ef3O83ldF7OmyK0tgcAu1P4v17IAXDMKvh+ewfSOKAH+IsAAObuMTDd4ZLlVXX1eumciQqlIuW0z6dyepjKlIhRhPZUD/YdAARwklLWIO+hgEErlq1MtzKEMylJzqXkQiSEQ0nQtTXTHm4YBIDh6D8wHAEJSWiQkZzwvoiNw/4qAMCJAbOkueTmUhuXnk5Udpk09UzJBIyqOakh+kycU8rI3EBVgzrLNBVzdTNPFHPishSZ5m3X21bX3hU0PAypJwTAfcwkAb3DXmOrse9Ra3Q9qMeJKCP/jQQ8NIyIQMQiJCkNl+/R/BocUggAO+5LAIJhREIAaO69t35wLIahyEE2OiD5wWILGlq9ERZiRtAngKmFu11v+eV6/l7KPJcFDwzqqOvwzqZ7X6S9s+p+eBfRzTyAWJDNDQ4RqAiLdHWLYEm5RG/qEOP6jIDW9e1tvVxXgJjnMj+cORcfStJQgkgiIjJ4TBCOyMKUmBNhuAVAAAHDnR0GSLQs89Pjw+P5dF332+Xy++9/vLy+PD89+DJNJaeURGSeZ0aqiGLwXtoRQCaQEmBV16av2t9I98kq9m2vYLduG4UtSALlJCed3NlqJltIRDJxDkxAgiBgaM7aAQYHiI+sNGHoGMWsgUG1XfY34cKEhB0xELgnNcOcuvAUjtpdGHMWN+3d3DwMMufTdM78av1yfV1N7d8f23sHj4SSZKjFHEJVW2t1rwiD2hY+gglSOp2Xp8enPS47dBVGciCCO3x07GKPhwADwMxdDc3C1bCRMwz7ZCKIoBEn9/ESGXM8IhIjgKM7DN+gYS6JI7WZIsiJhQF/8EsQSU6FCAgR3CgC3cjfj3kMQumo9I6hcLeshZG2HQEWozn2QA8OdCStpAgW6AjBI34A7+LuUbbhaIyJiYRJhFkID8D5/p2IFOARpsiABMiITNAJlD9sFpCwLBkFpvM0neayTAN2VtXeqvbqpgwhIo/z6evjp3/7/NtvX38+T3MRcVMiOC/nc54KMwVo62p929t13S+X28vb5c/v3//488/f//zj2/fXdW2BnpNISigChECorVs3raruvXs3QxycbACGCCemNBJjNVx9vdT1svemkfEjw4yZJY0dDvSuETCw4jJJSkKRMBgMwjsEJNAHpk8nenyQ3bh5d46HT/N84qcnITBtTTswMwJikAfeHC+7aeu9e2123dtt77W7WgiRCCK/5wQOx5AwM+1q2rm30GDMp1yQC/EEaQ5idDeO9COV/O8M+TvsHve4ykEjGLlVAQAeBoO/AYF8QDMOBEFq0DqkRAAMhEBBOHgqnEQmyVkyI5t6D99M19t1q7V1dY90yGYYAC1lQKhtPd5U70nioL2knJOcbKktEOoNuhkijOTZv9X192Upvv8CgfDOwP7xXcNIRx5Fw1roZkE9KFCQM+dpn855f5zmc85TksTMe865lDIEUYFAgpSJMhmoakdGvnP0iCmJfH76/LA8ghu4We/aW5geKBb+VWY+vIdwHKG55ESG4BiHTR8MMY+HIIEkK6kb3jolyAvPKh2LzsEmuHu7dXTjgEgiJRMjWHhXd+VFZ4VBYikUgfEw5XxevtsGt2Y9zNwcAMEYVKN30wBgNoP2nhenGMHOYil1kSasH2M8ABzCwZmYGCVJTklEEGnoltAs7mozv6dPDH0SEkKgm/XeDj7Ze6v2jtkfgUPkEOMOI0IECme37FjCQ/ttvb1cb4/n01OcPh0zcOCdHx8HP+autjs2dz9+Iu5ee7cAZEHSGBAgQCAFkUaoB4lkohqb23C9NXdvTS+X2+22lQzTnJ+eT5Rya5oY8IhIYaJDlEoIwphESuJE5IpjUT6EIO8SuJLSw+n0/Hh+vVyv2/r925/fv798fn4aOh0mypLSNDFiuEr7Ie2xnLksAND67v1qdpGopVe/Xfeb93W2rZBG4gyT5DORCEBfJB4AydEhdcxGpUDKCmqgwd3JEN3FPIVJAgzwyUFNY6+3cGFMTEwYg7qamtamSfZEEwS5R8kJMZtara13166J03l5mNKCnrZbr3tr/97/OrRIZZoOVgSCuXfV2vqYoUdgOTNlyQ/n8+PTA1ZV3UKYBQ+CfE6Ss3ACwDBEMkSOILUwdVQz7Bg+JEAiklM+DumxPzomHwIERA9EwkAkDw81tQij4UWIhAwUyEEeI0r4Qy0ZuasYCMGB5EFO5keWqN8JUMO0KtDtECYDYRAMyZx7QI9oFmQhQIHYG+4BVVAJUYgB2DGcAvn+4B8naNyfhMIog4k4Cv6xg0OKcA+9WzkJkxA0QuUP3GUinB8LJ1oeT9NpylNGBDON1rRtoV3QJfE0peeHx69PX355/ukfn359nE9FUq2rWkss7OBd67apt9r8ttXLdX29XP/48/v//I9//v7nH99evq/7bmGc2AOFpQgPBnfba91qDG5eN1NHAFRECiAICGYOgRC0iF5tv7X91lxd4q5RPN4IsSAcqxU3N8mSipSSUhJ2oWB0oCAOm6g9JHpeeDrJvuLmjTL89Pzw9JQ+PVLd19fX2iks0VBaqnPveNV66/u+9m3va9XWjRCzyDKXJSdico+tabNwQBaJQOumrWOAR+U8z1MqUyrzElx6sICz8yw/FJC/xcMgDtZfBLjj8aAiBbjTPfbYCSDEQhKgIwEhj7bXHGobhxiSsDAd2M3d0ok4MQki5LKU0nBrbrsb+cDM75QogOHnl3yQo8K6OXQkRkBHRmAok7TmrQcpQgjz30o7wF3wjn+loMfHjePxjo+7nQAAYxyUwx7cjYA8FKxHa+a16qrrxFJYEhGj5DRNhRMf8BUFZeJCh74fAwnnZV5O82CNkXHs0baGBt5da3fz++t0BAT8YUW9t7ZdLsJZ7m7XzEDs4CMPNpAGB4J4SqlnmWtaePJkDDSx9SATvfSdzAlq9RXtEl57QFcLBwYKFEBWl6oJMSOdPbj3utet1oT8lObN+7ZFs97I1ohORJncojXrzdyAiFNhLEJL9kmaYP+XT2M4pktKKWWWNKRCf63LAUZdvy+yj5BAgI8pMgdv7k4uGslhf32SBDS2noSIw40rZKhlA0NV6761tpt3HpyusbM5bDru3NExsiDeX8tfX+beem995E2EwzC5xe6R3H1YVREBRHFH7YTh1mvd933veri/Rqh5Z5SppId5ejovy1SGMxogCNMRsU0DINMIg2P3euisRtfNhKep/Pzl0966//NP1f795eWPP8/DvSkionhJOeIeo/PhB5UYmbGDV/W+Y2wkG+oevbYt6pVs79wDQ2jOCyYsxAme5/QFmB2t495ph0SRWKEpdOShKzMRzBmSCAWFgXWKqt129YA4XAuZUpZFqBHuWaYs85AUTmVSX1y91g5B7phTejydz/NpyXM19ME1+3AF55KHRGsQcZCIWepeW6tdnRyTyJDWqKm5BhgxcEJKgBIgI6OcEARj0OrZjczIAhjA495LO7mjmx0bIvtLsBARdNdQj2uQPNADCMAdjo0RQCAJMhAEx9/mEATAw8IunGAkowMBOGH4OwE1YLgo3EmZAe/QEkJFAPAKIRhECgib06agocEOCJLQFO29FXqv7O+xSOP+C4o4spGGIg7HoQJiZKB0zCHBAEom7yMSMT18OnGm5bxMc8klQ7gqJfQE1juoIScuc8lzoSRN7XJbOThKmIUHdjWvtSPiVpvCuve3y/ryev32/fWPby+/f/t2ud1aV2JhScPbffC5U85Iw3BYkhTNWm+9cuu1a++hMV4eEwtPKU1uodbVweK49T9+GoTIhBDgQyAfhIjh6B7gjmEMI5qlsr8luCRf3ey2863flDWf6PPn6elBTsXJqQp6DzW38WKTlJKM3NlBIBJgpiXo+fHh6/PTL1+/PD88siRz2GrfmzUdRlWeM5/mBOF1rxFIHEuKh4VlKsBTVd/rlLN/pP7+WNoPAgWEh+GYJoOQ3BHN4m5fjRARGqGIIxVbACmA1CNa8MBSJ06FiQ9Xo9EDAjCgICHLJGkmukVwBIXDMD+BwwdioCJpjHPm1tU8gDwCLCgghDOmTJIZESGY+G+69uEh4jBcaY8TNNzN8MNM/z7WE96vdgQa9GiCY20WI9KwWrt1kiABFCBGzpymlEpKRZDR0UmAMw3r1cELq2fTFiwkxLBjL0ZGoTCCKNzuXph3YO3jZ7PXetW3lHJOJSVJmVMiEWB0xkiDR4ABiBREk/DEssiECIXyQ3IDUN5LdW8KvUPcwsVV1MC6EJaSjh9+s9jbLPkhaG4Kvpfrumz7dF4ole97vOztZW+dsDK1JAjh5n1XqxoGzJKKwJxgSTFxk1D6eweFSDIUMCkx8RD73vkQcDeriSMfAA/NWziGD1f0UdqJhsPGgT8e4Mu7zTDer1IcIhigGJcsoJm31mrbe9/IGg2TMDgoBTwMjcdtfdfYx4/BBO5eW69dB9CERIFoAN29qjkgSuIkhDCFYQtE2Hvf9m3bd/fRhph5a3WTJMtcHk/z8+PpVAoijUAXYUr5MJEP1yFcgyOEBETSyGl1M0KYS/7562cL2PZ22+rb6+vvv085izCN/4qA3GwQDz+cDBh+v1t3rACVeRfZSaq5WoW+uu6eHAwkTUthlmwyp8+P5984Jxdf/bbq1cRcXFEMG5ETB7Mzu/BQsxew1Db3iH3fNVp4hIMpECR1IDTwlqiWVCHCrdc+q1c37M0S5yS5JDkvy3lZlmkiRQPjD/mbSJSnMpKBiUhYpkCf/e3trfVmpu5ASBFRW5X11nwzasTBCUk8SB3VsQcWBATgCHIjcxyBVPG+dB5BROBxR9jHBwL3vfuxaI8YLlnEwoM3fzxLAw4ayBzBoC/9uKQ+bl6Ee/86tA5Id6EGHomiYwevY0oZ4/ZwbFICHeCpBqIHaQdUBwzj8JRJGPs9SCvuRJW/yCp4P35+/Bs44mrhWH8db5MhAIEiMYBQ8MfSfv60sNA0lVJySgLhRp5CMqbavBtQTmkqlEUxXrababSqj8vCA/U3h15j2wywNb+t9fvr9dv3tz++vXx/eXu5XC0iT1MafziGgR5tEUsZKA1JlAiNmtuWtuvrrTe17hGQMjKmnKec523bux3JVIM1+BGeQwRG8AiEo7SHg6t7BwtPpITB0dlW0m+EbwB7J7sE39oNUsxzfv5UHiZK0YyxJKm7ubUeAYRTTmUhSkly5Ay5oPbIUv79t9/+9//27/+P/+1/+/mnnyXNFrTtulXddt1rbXVH0JKw7be3l5f1dut7O6F+LrGcKU3Zgczj1vdL2/7z0j50NUe2xMBGedRzg4jBk4xQhAA1AEOKsW1kjOESDACtAUEniIHrcMIx0Y5UvTgoIOrRPdTRgAIieu9DYpnSQFiZmd1Hx+2ByuEMEGiORlACEgpIgoGn/t3g6eBawxEDgvdO9e+GtO8V6N6bvv8W78usgyJ6aJhAwzmAXMlBvO3GpcugSwzwfIgGCQeXZl90P/XhirOm/S3d5rSQJ+8omAkkogNQHIvWH15d63rZ1ySWxCRJSiyJUsLEURhcIBiNICC66269RXe2tDBOnNxUwxpYUNGMaC7Qqr2Zkil0LcwueNk0vW113epWE5KLd61Ajdf9rPYYwIHRvK99B98ZW8kGrt5713qtsSs7SUoylZhFJ7KEzmM8eL+3QIQBMaUsko7CGQGH3QwGIh46nAO9GVscoWRh4G7atVcLj7v2hEb4h0eg/9Wk4VGuYexS7xtQGPbYHqr7tn17eZMleo6a0RMhRZC73Iej+4V3IDcfUR5zr3trqk2NJeWSKSUDaKoDKg3k0ZNMUxYZu3ntvW51s+jEkTKx4LAchRJCNKWUEw8KMkKYGfYWdqBXg8D0PnQPUk/v3c1EuGT+9PQQQOvef//+Wmv9/vLy/Py4zBMhCnNJJcxMze0HEsd+9ddNb72WKzy8nR56yZ4A0QWNyKcEU6Y0IxboYnvYrfvUYemcU1pElfcGCu6kxEMonEQOBBOcgHJOD8C575tq1Lq2iimllFIuwpQTzwgSRgSMFGa96+69662FYxgs8ykLDW8cKZ4mZCwolPIPCPA0TYNtNqZ2CDCzUkspRTuOdrC1+vb2utfV0w5Ly2SUGEgda/cbKQQ5RXIDtWaxByoJUmLhTMBwZ2UwCR28y5E07apmbge8dCBAozQTi3iEHVdMvC+QxiXiP47t4wYdBA9Hi1HkATCcRg2Gux9OhIV5CIATOmMIAh1CDoJAHY0cxKEzOTyfXIRQUAI0IJyG/P4+sdNgIUW4uY0sYAxk+FDzR4j2wVgiQuDhcv3jtUtMAGG972oVwLT33ro21eZgQDhR5pQ0/HW73Xx/xcta6/P+kHkcUNPQ7tpNm+q29+ttv1y3t7fbbatmA7Z9V9R4hLtGBz9yqZByLpQRnbK0xGLd2l7DPRxSTtM05VyIWLvVvZseRMW/5Y9AeNhhImmqZgZA5OgA4QEciN11DXsT/x68glgEqgslf3xezst0WsokQD3mvMQ5mW21r9ZMFbSq0E4IE0dwkICU/LCc/9tPj//+y9N/++3zz7/8kssZuHTFrtAVWuu1buA9cayXl9//1//45//4H7/f/hfWi9SSChZxD1Sz/Ueq1t+mdhrkphFXBGPhMCwVBkMDDNFw+NOpHdp95oBASgQEQT0i3AmDGZk5J0YCoCGf6A4IiBZNvVq0AEVycO9qZs4sPFwciZnYCM0dTANaoIdDmFookzFOgUyCDBj2L8na9+p+vItx8MZVCXfrlPfK8/5/gYHwbox8KE7gTqkKOJ4qDwdzGvFiit2oIco4BgHm4ygOA9K92Dr14aQqiJnT4/K0lLNVYMyEcvBm79PBx+re1da9MruwiQgLS6IkOGfwjJiJMo54q6a6W9+9GxnnxIjsQGpNXAKLZ+TQhHFrddMICAUDRIOXrRncdFut1oRSsHfWsQMpBEvXBLjufd76CaMlVg4L11DdW79UsCApWFhK9km0RKRwVscfnrIkAhyHSPRO0zzo6PeB3eMIbkfCsbwRYjcLV9emvQ3O8XDlRWI8BDxx/7TvBLwAoxgf9oc7Fd21t9vtCsx7E5rRF9TA4AA+DHAOHt3x6cf94N+/zHyvtZurB6eSckFiNd/DDeFwyAAcQHFKqGrrXtV669VdkSMXkkQe4eYYIEhFWJjVBpEQ3ay5MVNiHn/e6DAGNew92cHdElAWzlMmyVs3Q/rj999v1+u2rbWexq69pQamg6bw8ePoa9zM60XTFWFNkxWHFBwm5EIwEeVCNIFl3yFu3W69x9b7TQA5pcBm2sybgQqiCOUkiUm7q0FARpgTPSOmm1Ovre6sXUo5zcsplylJIUrgFBZu5qqGBq7qvfcGjgQ8E3MujCbNygzLmcfAV8pfEXZEVKTcwTYEgDA3tVLKPC+dWbWFhape9IIbyNnL5JmJEwObQ1NH1AgyCgnDbmpRAYOZKEnyjMH3nJCge2hLABBiEA1yJ40Liw5NeMQQXvC77f+QgeB9R+/hHj+08XeyyGh4hz8u4IFNHQM/HWi/i7u5ITqTCYVQDAozIiNydXe1CHN3DBBAgRAKEQBGkeAYuUgI72uve1LC0UH60II73Vn0cQw4h03j8G0iAib8OFEFhLmFmXoLdevaemu99egGxonTlFMgIO29a9+tOTmtW73OayamgG7arFXdm1Y17WqteW2676oWTERChIDhYRowIGQPG3K7YGIZzg9ASVgI675tWxorm1LSNJUkgoC9ad2rqh6xYvEO3wIMSMbNzUzNVN0MYKRZKbhBsoDd+gvZK8MbYEcgQAlMOcvzp+U8z+fTlAEiEHNC8K1yvkXrzU21WgsrmTNTEIjAaUqfH6av5/zplJ7P5flxnk5Pks+OGUIAxdRb28M7k1++/V7Q2+X1z/9ebd31xs7qUT3CujrPkB7e38i/hLrezY8OB5GxiR4tEh60IcBDi4FGqBSNxI1ZmVJQAiQEas02qsIpZ4oxLKMHqAcGoHpTrw4NSTEcyc3cwt2ngWMjBTOSobmjO6eRoB2A7tHBEZACEhIzcyD+a5DzQWPFH9/f6E/v33JwSeKu2T++2e9cGThu+7g3BEEHkoyETiPegBBwsFsBwQF9rO0HS8u9QnezGohKAYy1F1hzB2dXDKf7+pDGyPrx5bp5azoAIhGXJNzJEjFQZh4MHodQhwbQMZwhBEEiEFwtOHjCBBIAktCnRC2kg916v1Rf+9ZMa71o81qx9451U+QIAhOOkpEtknBbq6g/lAQoXr1br02xdtrVgby4FTAEYOREJAYU/BGQR5SUkFyYCcnDYtgbHACghVuYhvVwA4hhKzsoqmG9t816A3PEMdh2C4MBkvjh+XhvvjDQ7yCNH7nEBmNPGDUs3sxee5+2uSwlN8SzwwwyDTJJWNxhVAQc7q4fG3qPaN2G4ngM0LWFGyTCzJgTJXIwdfBEPubmdPBNAskIbJBOgFLJ+WGaTlPJkoQlIlgkp9J63/cdwgmCSQzBzc2dJbOIeZgpDasUAiBgxmlKDw+n523frq8QEabamqXU6n6FsN636+XWPN6NkAA+nabZT28NYccip8QzAlp0RzQE87Dq/qpQyYVdiUVQQmNdW4s1rrre6tUJKDFi5kDftTqYMsA0LZ/n6bmkRZv3ttadTBNTXubPD49Py3KSlBHIzU173db1VpF9OiUiJJLwcIs0BaWeBc7MP+kZ5q8oIiVP8THCDhmOdIGxaA9yQ5rnCSC0Z9NDDrf1vUdDdhegJJJ5aFuY7s7wjsfubUQlDT+XMRwMo65DczYq3JC0H8J2MPTDmgzxeBoREPwITrpvmcbrvjPbf/j6q7KMaR0Os1y4X2GjU73D6ELI5EIkFEQj+x0JCYjBOIjVBnkEh8yOCQ76EAYTBMQdZRhI9IHKOwACHWI3PAR341/dIbbBdAEAcjC89yvH6XB/e71o79HdhwPFOD8MKEScKLJ3rjertW978+7ouH+v3/CFfFjtmqNjCmRAhoDh4U655Hww8/Fw4Rued64BHgQ8pIYyKN9x99iJNMnpaaaE1i0viQtqdK99r1trzW34VB+cnr8+DR8LYHMzBBAmAmPsAhtZdW8WO9qFcE2l5RIykeRAdgDILI+n0+enzxxR8XbRda9rraY2zO0lzLwH5VQkU2HHviRJ4H19u778vl4+1U/PZXkYWUEITChOLpiHI0bOo78Vhmj7+vrNe92m0wKI7t6Wz/9laTfzYcqMR3jqAGMGbQmOJ22Ab4CuoDR4wCyWOJCROAVAN4ddU8JpEs93Kgm4g1lA99asOSiSUQxXhrFYVA8NYEQnHpncERFExALMDugRDqAeHYCYeTQCfyvt+KF6H7z3cfMfZyvey/idTwIHNRvv+6jjv36f4cbvaZBNIN5d7o0YiHFIYA8Q9a+/nMDBO1izwUEkx86xSp/yTCAR48+8/3U/RiC7h3aDiA4h7KIhQmGcWTwxAiGxh2uEAhpRJAb3YIiIw1URGRiQKSbBM2bnAqLXXr/v1+/X2/dbbd1VwRTN69avHUiN3ZYJT4X2vSdCswjmUiRAttq3qnVrvZqrK6NTdHMK4OHLKIEY8qP7+pjaD1O50T+iw32L7KZu3bQDGAJApHdDbrNmursp3p21w9QNAAWRDm/Ew+sT4PjxxfjHrYejqSMCO6g17K13bC3Vfqqns6dEJIxTYXE0D/W/0oEx3IYH3IczH6oaiIB0AOOOiqCMlhhIgM16iMOIej9Sk4iIgsgDYiyakKXk8rBMp6kkSUTM5FnyPE8AsG9beISTmY3zGBCJKeWMpgFOQXioYpwQWPh8Wp4f6/p26q2Caa+1C+8Rvdbe2r7edkeQvzwOvz7kB5xyR2209Ek2djXr5gP56G7XDn33KXROmgmyRPYet23Xavvq+25Ncikyg3Mo1b1bdcRTLvMsX87zTxistradaoWIknJeTp8eH77Mp5OkBBCmXduuVvXaAjQPBnLObm7dkgAmTcw8y0/pcf6UQRhF7Pfst7/OOH7AiIUpkAgxojChqbm59r7X2jetuhmbMYEAybCYPfgcSAwwejsIC1dzHW7XoyDau6RshAodcI4fca0O7o7j39HdzG3U1XGw7X1MAhwW5n/buw1YFA6N+cE2Oo4KHC3wu4iXAIhYiBI5EdDBiAIkAqQgCgRCUDvYqKNLGCMbohN7ovtG/941AGLctSEIdL9MY3BD8R37QqK/epDw4QD5flmZX96urTbv5hpuQcgkwplFhKAQFGu4t35b99tWwwAdLvWGTaMrmCEDF5rPuZyyFBl2fsQkUpgHuglmg8I4JkGzcLin9TkiEAWAg5l3C00Tn3CmTL33khMntOi1aWtVtUMAEzKO7PWPt66bWYQjAB/jSKNYBS7sN/DqXjk2yZpzlAmlIKdDS8Ah52l5fvwE5tDh9VLXve21q5o7ABxiBkSRXBgxhDIiQa/r6+UF314/P12/LA+fSxgedcoIQBgdyR2YKeeUUxLmW2vf67bu67QvzCO+Zoa/KvuPpd3NVcfsMiCbASd54H3reOCefmAY5oEGLoHmfax2eDj0A4Sq71XXtc9pximNDVIEq3vttrc+qEfMkCI0gTl4qFmVSIBOHMTIQcSCR7riKJx+nKJgihSQHBPRvzLkAeH9UcQDnkf/2CTD3fL5EDrdMfyjjkPg8a0H9zXAPWi0sKOLJSaWGFyD8LE0hzsYgO9n4p5oDgigzbztocCUwF0YTT1Gnt6P/P0ICAszd+9GoT1E2NULQ09kniLQAg0pWCBlLpMcQasRSONse4KcPDSiuziyIyfhPOES/MCt9t603lpf21VpN4RANJwqTYYJLeFQWxJFixQJ6dmnDGmK/mrtGrGrhzuDI0bCkAhGkI/uTgAsAuQDsbzP6sOWw4a/tlk37xA+TNoRh02NmjUPZYIsMhzoDkuQI7sFx06dxvfHnQ9uI6KyRiAEEYV7IDWwFgGAMtqdOYrmFEyA4tA1uo31KI6dUfTBcvzr4wjzEcEe2hti5JwpiQV0daYOCMIEjmgAjKkUuqdDChERp5SSJCDOglkwy1iy8sHm6xruh/0uYK1dtRNRSilgRNAQOZGThXcz9ciUKMk8L58/gdW63a6MUNeb9ZZSEmGIcNOPsQQI8FzaF+nTk2w7wR/r/v2q3/uuLebOERLRt9Z6XSdZPxX7NOFcMlmxrW3rtl47eQhRwojcaq299Wvzhg8PT8v5cclPUzrte933tu977z3ltJzPy+mhzAtLIWYc7mBOHrZuN7NqnhymQ0ZGIwTUhg80T+cznkkYRf644u32/nG4aT86bBiOFUAEKTFiMiJtx88zwNW7q7KiOrtnNVU1QqMRZ+poatbde4RCGLqGhmIQgAMFELrDSG/xgdgOL/lRVO7ycyQcVvPhf7E0EOA9OX5kqv0L4Wf09ERExx9BIw/rYOYhxPDxhMNpbaRpD6Aw7nwSHFckMhMg05FuyERE5ODoju40CCSDAHCH///qj/CuGnkHGeL9InzX/o/7D3kMNB8uq1ZHljcRc85JJEsSZEJGYaFgba5dt623aghMQd7Vq0bvECaIiBIEh1Uv4nj54y8Z749ZAMKDxZg6qZmZgYd3c+gGGGaIYGZAMZzCZeKuJsQErNXGCpgTSmJGpiDJf68diJhzOaQqqLa/envL+MpxC23oJmhCkIQpEQohgyBk4kJlKVOipKbq0VVrb127342ngiJSmLhxBzRgAwhgwyRAdd8vt+vrU9sjbCTRuDsCCgMKe2Sdp+V0Op3Py/n8+vZ2edvW7rOP90LprOXDu/ihtJu5dgMMAD+OXzgixqAbH1j2fQuJ4OaBjiNpDAwCGNmYA8QhwL013VZsk4Yh8PD6Jg9oGq0PSwcmRyZICVA9wM3beKCJghnd6TgIcdRmHMmv4+l28RAHpr8v2/9qjfGvh9Lfl+z41/fgvfwOMijA/XE+uHVwvHEctEl0AB6zPxGOvDgiCBhtHhwcsdERHFzYETA/fqKorqY9HIR0rI8dRiQpxI+lfZBiTUM7GAJzmHi4V4GWsWtSFwOwwEBBAc5qBxwFiXFAe/A+KHcjc9TAhDIJLTM/Sm1Wq8Vb1be9r15XNwc3SE7SgT0EvHAUNu41pZim04lyBmdszXx3dY0w5wgOByPCkHD5gVoOzBI4xAAjKVu7NjeNkbQd4a7uQ+JPcaga7vUenBkJ2I5tkeO7VR3dWUCHY93QALt7mLlpQCAxR0CAY3SITgRdI2m33l0QHIAlsDuohcZ7/4XgEHrXxL1/Gu42AAVX7RDCjDkBxGhD2IggHNA8FCgD3E2+WJgDIjEnYWTKgllAGJF4sHTdrNbq7sMzFRH3Xfe9ppw4pTvL+ogOd4WuGoCUYyJZypykkNpbSut6bXWv+8YipWSRMXf8UEtm2h7TTtMsOa5tbZe9v7Rm7gEUIB24dr+1faZX7v3kSFDQc2tdL5tdYLhwewmz3kG3aNcOnR+XVORU0iyUTNd932vdPWwu0+l8mpY551HXD3BrECzUeu8N0ALc1IabAYgTAFAkHjmNwjlxkhfp744UHqGtjqdA3CHiPWKVmcMC76EnxxrYuzq6m42QF1UnMTQMCwvrbt1cAYwoOIasfQDsY7keAINgrNp7194BgA5TuKNmH2z1GJFfR5rb/bGMCDge0h8xLbwLc+AIkX1H94/7gCCEbOBYCIDAMJRycEg4/EC07rQ5JHD2uM8ehBhBFBgxdMbH+DLCFX0Yzo5V0bE/8Pem9k5nOaaUY0cbdwreD8fcNSKIWXKapmnOKbPI2I7R3QFmW1ttvasLMSFFjNCeQAgQooSYEPmQAt8hh3AwDBSWJESEAcFKSNhar0MbG90hHBGYgCDAkWIQt2RiNafAMAAPFkyFJ0uZE5OAYy75I9Y6nINZZJqmkoggmlbXS6ELx6akEZGYErMIszBQEKEwTiKnNC25MHD3bm6DEmihEYOGDcSBCZxNqQMqYjccUD066L6v1+vbtt3mthEhgoIDEzEPCiflnOdlWc4Py8Oj5O9VL2GqWFMSYT51+78t7RHgNoB3PzJ8R6s4AnAFYQjC3sd2BA1FQCejgGADNwyjsMTEBGZem23buq4Zp7mUMlyZkAZhbYge4u6tNp4dcPfR+x4/64M24WY2OnohTxzo99n5b4/Y+5H5l18ccPqx0n4v/+//O0r5xybufgrvtX40NwMaI0JmZI5DEQ8w5shw8MML6zi6xzEZUEhQhFnXQCfkgajRe2v8w+cB4BDqrjFQgfBA8H33NfuyCScyQh+eUXdC64j5osMobeQ5jZQoh27QzFmdDAkkExiRZjrl/Lj06/+fvT9rkmQ5sgNhXczM3SMys9a7NbqB7kZzpoeUnke+kSOfDP8XfxlJEVL4wOdhc3oB0A3g4i615BaLu5vp8j2oe2RkVl3gogGSMyMwFOpmRUZ4+GJmqnr06FGtO9lfH+r9JMCERKaoyirUhMGHjC8J+5zdLPyTBmaZXMCa6axCxlmY1PkRjY6IDM1czZpKVZlbm80UHAmXfuu47EspKEXL/nLKdmOobxuhIznT0njpTIVhFREJ2DACmiD7MCytrTilhDnxkNNl4YGJl23ZACIMWiS1HUDNnkTtgdpwopTZ3d2XVtaMxAQlp5JSzpwICSwxpZSTQope38juyuCFIHc89ClnomAfAxBRiKnRuowBIOdsZqWUkgsAtqYQjo25qrWmRJxTv9lclrLR3skAAUWaSFN3BCOEnKiUIljg7IFM43hou92uHQ8sJo4NXUxEjq4CmCgDbEqeBvTiM9fmfpgrzwfXyWFOUIBTKGNl7LrcUVEHIiwmbiIic63H1g6AkgtuLvrhos8lUVrzLFJbHefpmAhfvXw5j8e5zrvb8c14TURdztt+2A49J8ZEzgiJylBKn8fx6iSlqaq73WFBsRPnnEspJedYdUu9xVK0hUQhionEEAJf5rqa32ZKUk2qgRA7MxUjEjFV86WvGy2LzGzp6jvPiJg4JU5MYGoCErG0RcGsWmtSaxVRPFXRmavZk3oeZsaUdCm2RHBgpHDwAAKO8ExLvvCUGvel0BoshBdhyU8ERG+ISz9xc/U4KhIS8rLHRnZgVXcOTWSCZfuI9bQAZMs+vIY9i4aOgT/s0KftNaWEXdf33dB1HREH6B/igGDmrmo15EejEoYKuVG05k4Dco+QTEE0KgEYmADBoqNXCMGHn4TgS9soA2miIuieeFk+hOQElIgYo+4YHdEgQcqUCLFtWgr1dYWS+/N8bhMZ5yl2bTLr8Fh8Rzz22RipMpt6JswdpRxuFBBSSWnTd5ebTd9nADMVMCMwJiNypKXojIn7zJnAXcyam2BoFTbNtZVx7Pe765u3SpmwT9yVVHLOc+OQ71SRlHO/uRgunm8ub7eHcZonEQV3YDd9FFF9kGtfnpivbqo6OIMv1OTl2S5cooCaFjYCuJuAaUIQQsbMSKpe3ceR95kIPJIa0aHSPVw/BtdwvMyMDM1AdFEqWZxfcG3u5mhO5ISOjAyLQh6c6tYfT7Ozvx+/7gRga5IOzvLy8d/HqPhHDrD4NISwNJIncIyMP0bJQDTAXYteFlB/4cUsspZo5uaaCCkaUSyKlI9H1CaomxiGHQCDhtOsebTDMVMmzNEHakHqcNEijVbngKEKTUCIDI7JnEUJGzozWXaIBNymdJfYDj5tajUdTQzYkUXYm8hBXJTENiqpc3NwgUl8at7QTAnErZqO0swpK7Fofhy2Izi4aFOZVSaRqbUK7oQpauEiKULEnDJzyIyAr+DHihsaQvS4hcSQeMm3aDQtXZS8ESE0wZBSbCsYwj7ERJxKxr5L2y5dldQz4RLiByuZl64YAOCu6k3sfPfCRSqOSk4xYzHYI4wIxIQ5ccmJmcgtEXJKLMYppZSYyB0KQZ9w6POmLyUzEbpZUI0BoDVJKeUcyT8spQBAKSXnDAAiCrDsuCutiXMufbcp3cYNQU1bO+zvpc1qysyJMDGVlBD5ZNrd4XY/A4z3O52POTtyAkxu1XUWFYDC3Kduk/MF8sY0tUmb6hGOe3bJ7E5MrEKqBH3XDd1VVjdCps4UpDXgaZ6PrU3E3g15c9FvNkMqKQrUVFurx/G4H8edtrmkItjq8Xj99v7t2/eJ+WKzffnc8FkCamo6WxPQ1KXcpX5KvJp2U93vD/FcmDml1PVd3/Vx90KvIJy2QKlT4lyW1kQRCga27o7WsFXXiq5EnpiyEiiIQyg7A3pIGa9m1V3NCDEYLbiIjZsDOC/5VFFrTcZxak0QMTIzUZ+O7H622JkYid1V10Qfk+dVCja6a9CKixM6kS9Me3B3F0O1BVBEMiKLPcoNVUMGHOHk+cdUi/QjrXnDRdKRAFfYEsmit5upLQg++Eq6WtQ+7MnqwJwyMQ/DpnRdziXIMsSYEoKpmpmJqJiHmwHIoQqNmJEI00DckZOLKXjIPTOAoS9NbIzieflCBgs01UIGV8GY3AmAiXzR2eeAbWjRTMXCECtUmnDKQGwGibtzWMvcRLW2msg6r8j7gseSW8nBlUF1J/SUkRMQApijQyz3UhITSKvSqpkgWGJI7IQGqODOSDniuTBv6o2A3EmVUfpZxmm6290qJqa+5H7Tb1LKgMDEKZeEiZD6YXN59eLy2f1ufzD3eRp9qYt8ZAgfC806+qpKDA8s+dhHAv1ZO1CFrxfRt5ijGzpDKGZ5Tsjk4GKuzexwNLIWZY6UcnM4HPbzPGmI/6KDq4rU2lRRjdQI0UWaroiogzuEc0FIQJDBEji5oaqJ2JNqqydVZGebc7z4JGqHE/x+9kE/+9XpqEvddCT+F9OOtja7XcpCllWwfIetK8nXthCrqXIwNV8PDB/AD2YgYuHAIhjQIrNeVQ+zpiMbexlKKiWowkyYCBVd1Sw2e1SCFI5QKPBzSU45cxnnWessTcyFSy4595m6nFudFSogA5FWrUebFGozIjQDGuuuoplPre7dK5IZUgU/qrp7Nc+qrHN5ZNrFmtjU6tjapG1UbWZKKw0UcWG5M3HmkihH+pmAYqVZTNwAkNAAgKKhOZI72EJBd1o6xjnGvYh8PBqSIRklSxmGIV1cdBd92TCSazVLzgLqugAHCwJj0FSryDkiz0RDV3LOOacTOjuPRya0xB0DlMSUc0pgiqFZBJBzLl3JmcBw09HVkDfbzdV2s+mHxMnMYvdl5r7vYU3KRLE4IkY5T1SGqKmpuWHiRD2nVJjYTNUMgXJKQ99dXmyZluqD2PxFmzyeV/94Db36NBtM9pzLdoC8BVWw6q7ujpq5Pcv23NOVp9RwmlUn0wYIGdgVZHbPzNh35WLTPRMAJSx5g8hNRCat82jWuq5wStvtRTcMzBkB3EXaOB7udve3u93deDhMx/nudn/9/u76/d3d3X47bPB1/8nz7fPLzxxsnI/z4f543Nebo1r7o6vPL1fM0cynsUU+OMQLp6kd87x0bV+V0M0NEVKilDln7LpUusS8dMR1aw6mldoMNjPURMJoxOCJAQk1iGW8YPsMDADWdQBASIk5pZSIbaXVhRwIOAbpcprmcZzMnIhK7tLi5/kKEK4bU+SVIfD0hbZPaMHiU/GmgtCYWkrO0VfJVMWb+tygqssSLMU6T0TJFFUXUbmoATplrwABcBGKX2QkokcH4pK0pIi3DTH2SndwR3PzqOk1U5NHbV2RcBh6Yu76jpkXSZiIrZma6DRPda7aLJrpYNT3sGJRJswppZKASQTAPTMzZ4ZMEPAFAaCZiTQADwNv7q7GZF3hUvpSci6FmQnI3N2AmImyIwbmiWTswAk59apm4Qo5Je7OAflS8mZjDE5eGaZM84atw3hmnlLobSlxiBwCoSu4sMy1HcaxErpMdZ5rnRG963KeG3FjAue1ck+icDDE/lAdR3EGc8qcutZ0Gse+kALNDqPbXGdwKLnb9Bfb4WLo+08//fSw39/evK/zBK6gjzlkAPBd/dpXHGYxOLFhQohnnNr6UYg2RXhlQIYETNBlGvrMhKbN1Ny0Vj+6IYCqAqdmtj/s5nnm0hMzUZCWQDU6YUS7AlANlmeovod6GKIHly6DsTutAsqLe/54PJjtlQ7vZwT28Gwfxe0P+fGzW3IKu9cjLCQ7XMJBX03IicgSGavlz4nyvnw3rpY9THv0mF2SbSvtbh1m3sSilGWpV0EA9OYGYjROSr5xHxwKZk7ISImToBiEfJsGwTYiWUNfkr+YEhdHUgh9KyEyJiemRHz5sncSIHKiNsu4w1nnquKNm/K9NhIzh2Y6AQiSG0EDP6qZaXVlFba6sfM7qFJFp9bGVkeR2U0REYGZAq0I2iYxpcxd4szIgLb+blFCOVU3rLHGiQIEAEAAdpIdpMD5o1pSgRTZOEMpvB3Ss013kVLBqKNtyVgwLOxC4AmWkajNIudxSUp8ud1EK4MIGJpEy5oQ1snh/AanGBYj7SmnrsslExpuOr7clIvtsB02Xe6I2NTAldbC6GDnBq0+pQSwVDRrsApFzZwImXNOyCmZa62TATFlcEuJN8MQcWOTNs+zh+QTyvnj+Ok790nFsBP8vNELpG1yzVgbCKAy157GK5wv3TslrzSNaM3dndmcTVkdQRJDyTyUcsGGCpBSB8jSxERrnc2sK6Ubhr7flNwRsbuZzHXej8f7/f3N7fXN7c3d3c3u5v3+9nq/ux/Hsdrz9GyLhS9fPPvcXflwP84OOk/78XAcX3dyKuIzh9bMT2sJYKYWUleJljRryoxsCEBMiT0lTIlT4kjAL4C7u85UJ/SZuKEJLcVuSy8V9EgaIcCS/QUvhcI2IXG8pGC40GVC3Szi+NbaNM3SBIl9iCMQP0UZHcBpqTujYJKCG4Cia1DwpVUAgdSYojonbL+Tm5nVpnMTsWX65ZQSh8onEaUw7YvgNi4AfPDmACmE/BKSEhKgL/Kh5BCdzmGhvkaQaWtxtIm7rqo8sSFiVzISJY5YTRGBFmaFq0qd5tbE1BEIgpOOhmzAnjPlTITshiKORhkTcSZPFDX+GNkws4UjYL66dKVLgTqklKPHkgOYNFFz9wSIiZEIUdFDJtSIE7uLuS4sg0dUlC7nzQAgE3tjGDOOhaWwN4kyVEImAEcwAHN1RzdCER3HWWWHOktFUzWbRYUZU6acSLMTAlMIC8Ciu+xoQG6gTSoBpS53gzuoKCRHc6mtST2OezeX3JNhn7qS88sXL+9e3n57edHanBKpNFc979YDH61rXzx+N3dnXqX4lgT7usOuneEQwM2RnNxSR5uuXF1snj+/BLM6ja2BiidmTkndx2lqZlNru/2xNulznzmrIZOllHNWdwnSfMqcUtSGRVcMBXSOVeYIyhZ1jkiEQGiPwxL4IGR/4tHQ+uoKCixmk1bC3ZPPLj+sBQkhUBhMFkPwQBPC9yYAo6i+XFkuDkE8WVIHuALNAGuZ7HIOjzO7oGZVTMzXAj8GRmA3xoZ+qFLBqntzvyDqKSNxZoDsBNBqNTMERUAAcgYFEnQEzkiJqOsyYo9oDioqc9MEHaW8fT6UTXEiB2xVxosJiXI+6uQ2g1dvTVRdIMSVEcBdzWYN3MbIFUGuHrlHIpPoJG1SqWCKgEtjM2IEixozQk5cutTn1BFQZNkj92MnXGNxNCHUYd3JHC16Zq95CEdMwStCRVJOjdiAvZS82eSrTfe867KhiTadq9ZC2dTN0JxOaRN3b6pzexS19323+eR1k9aaRHmEQVFTbQ1MCcEjrEBEs0ikI1Gg9H1P5HwxpIu+XPSbvgxMxR2DZ01mgYiamYgsarKRkAIw9+ho60vjk5JzCi7CeNxPteZuzqkkcLdWCoPnuc4QJVlLIPkwqd39b7+eDrsRiDbO140+rfRipuw+sWlmuKTxCu82bcfzfj5Um1k0Izgn8KSSkAqnzjV7S6iJPDuiESAxALTWxESqgmEufclDogyObiZa27gbD/fTYX/c73f3u+t3t2+/vb6/HY+7Ok4izd04pX4Yri4vXwI6pV6MRMk1uWamh56VCEiUFskN8+CsQ9Olpo0ocer6nAvFBrXEBstmENuXuaNVbZPXEX3i0oAE1AzUQpueeHHeIdS3ARGAE0eC7CFUCGBuIZfhmlxf9gxzZ3dcm1vC6bfxUQcAZ1IgAFc3rM0FLJESKrozKlAD0ESOAKaQE3dd6grkZo61qVQx1QaBKIKBMyMloszKzAYe7YtEPJJXkX0PsJEpJVzIBBGy0MI7ediizD0KJANeILSUjOUsoHIAtQjPQqEs59zlgujSWqvSqpoARQ4DIBhWnICYc6FEpIKq4AZoiSATpuiou6TIgouwIHzhkYRGTUaKSmAiZDVvTabjvD8ccmndoN3Ql65wYiJyb7oWt7lD9AVQwvONN2fcdATkKC3BCLY3GxVrCGrxUklAiEBuBJHGIxU4tHrfbufRp6MQQumA0M2NCPo+E7E0JzJmC/qTqba2dIhMRsil6y+G4RIpJyyZukwFzJEydgMiltz1OYEKYdr05dmzy1evXxPTeDyqVFPh7Vlf8480dV0yKrBmWCKwCt4pESUEBXAK+2RLaAJoRFBS2vb9xWa42AyuSq4EJuiZU0oFAJvaOE2HaZrmKktZV3DDI9vDZooAxGHXw8lENxel4IEGXbIJqEhm6YqdqOdn13AW/eIJfljJIxCaSifo3Rc9ipiewRpdqVsrh+t8/sZLdhJoDD5dtPA8reYF91qwhpNdWoVvT0CCrxiBOz7WqwEAda9q5ie7zsCEKdrY6uxam+pUDYlyoZRKZkZEdlJDFFtRNLTwwSBMfUimZWbqsnpu1mSamzUFT+A85LzpkRMgq3q/GZC567t2lHqU+dDmsensLiuFloKgh2B0ErW36ZF7pNpUqmkDV4Ro5ZCY0pITdUegMIIl9UwZARrUJaO3mPbF+8KT1xQ0KEN/1PQnbC4iGWFjlpKFEgDR0NF2yJelbDGZ69RqtSpeFW3V2GLEqOdBc2iqs8p5X5VSyovN82kax3F0AFowB5/GsdU55M1F1D1YQewOhNiVfLHttV0Q8MV2sx02m36Tc4/Oag4eqs7K7MviWwcAIGKAj7WGP4EppUBQzVxMaqtW59Yk51w4LhSZQ4zcVrITOTwqQf7VTXt/PVPCLeJkODvNkIZEktAHwmcwXuhdaXs8TnJ0VTRiTgwZPBkU8ILeoxRo5BW8udvKu7Go1GxmQJhz6rvcMzKYmUqrh3F/t9/dHna7w+6wu93f3eyu3++O+7nNLgIOzCmXbsjdkLsNIvQGm7lezK1Wc0s5PajRIQKniE0NYEnBurst88JMlRmYEyIkZDDVWWU2rQaIHPIY6m10OVA9Ek7K6qyuGtTMyEeT0wJURiVSjGWDWlPQKzrn7hZoJiIycUqcUlKzkNfklVdxPhaKHSiAhbeqCgoA7okwozMBJweIZB+YOjCGuiWRq3kVaSpNAByYKCEk9MyWE+SEiUAdavSBtwgVIphwMfNYj0C48t6DmcBI68kGf9fFTNQ4qAFoBEZnaVB3b7WqG4ouzcAwJ2LVVudapypNTJfCu6hhBUdizCWnTIQc7DomSlRS6qPO7WHb9EXUL2TIU+KUcsmllIIrK9sBUUwVTGGeRAXAiCAlTEAJCdWgiYmKakhDoInzQ7k+AEAmHJKrNPAj2t58pzQpNo8GTUHJic3fFvINU0Lk2ux4aHd38/3tISe8vCxdSSkREZaSCF3I3AWC/m/uYtoMkRKn0nXD9tlmezVsLsAoUdelvks9AgCqQxf5SjBs8xStA4a++/TTT4btME9Ta1VbHfP2eDavPt6vPcwgnZgXDon58nLbdxlACT0xgbs0CWkItWpeN12/3Wz60iUEIyw5gxshJc4pFXBQVYOqtmzU81RrAwcSNRWNGCXMd+SNlpmPkWWOSk9r6tM4H/e1K3K1RU7JVyLAwzzDkwppNEpaqodgyR8t63ChWONCJgEIz9b9oQ4enhj2ley+clMWZ9GBcBWXsBO/BCmKUUMYapl+Ide4GkYLvNxDpfJxVYwDKuLSIzklzMGbQ2RzNgc1sMnAq/LYooCBGAmwEKWUTUnRTx2clitcFqoSOEerscys5OpValUJNljhTelKwdRv+tLly6ttPbZ5Px934/5+3N1PfhRrhhZov3OUJRrFZkfyRNN/kYCINGLkAsOue4CRlBJ3mTvmzMhB0hHVAABtFZKJuRhgAYZ/SWtY6tH3LXTJkEmY5pykZKOUiFPf5W3uOmCuXmsb6zx7s2i6SZk5B4OP4l65i3u1R9VvzDRsOk6QEtnafn7ZecA5Z6QUZ0y5EHKkLC83A8LLix7R5os+9cNF122JOxUACEkQc9c1zbMk1wOfZ+bWmtQaatzMzEQezZSi9M/FVcVHlwaJjYmX4oKFqWruoGpk535jFR+buZgSXXDaZ9xmskI1gw5ul20abIfTrLOgETFRISoJCmAh6jKVjF2yDmfSg8xwNGAD0iRk5ABqRsiUcpeHjntGBG21HsfD3f7uend3t7vb393u726P+11t1cyQGBMTce4v+u5ywEKTVgCftIXF74cBEFM+M+2EuUQAAKEJutALARHAglpm7u6ZM6eu1jrd1+NmTom7i8QdmVep2PYsh+THnJpZsJuWvi6FmInYEQxcFzH/aIdJSzEiBrIaJZluEkgnIRAzd303tMHcmRkAc47Y+ElKFKJdAKy6tCHAE9/BCEyeSDGlsOBmBgTqWqUxMzMPJan17gBGTFgyZ8JEzgzMwU6nJuAOFVeI0TH4fLTIdLmDecxEkITASkSICQDdogv1wnT2RInikuFxaajZuB/FlRKXrh+2TAhu2mqdDuM8zq1KlLwYOBBgYoalTzwhE1BKyMhccqbS5cLMDhoakeZqgESUcko5pRxaQwicjJAg0g0OjkiWEnRD3srgDkhgqtIaMRpgM69qtYo0QUN2zMCcHuG0CTVDM9m38RrghnifyRKF1D8mIl4Y2IQIHBX8nBGTmVNqavP+OCcGSu7oPWYmTowQ0H1sVmZuaM3BoHTddnv5/Or5Z68/ff785Wa4AEWG0udh6Dd9VzghoIi2Nrfj7nh/t5OmiIRMn3362ef8BSDUOo3T+PVu+vnd/HAhj2bZo3zvA6ESABh56PrLy01iyom6nBBAqkgTERGdRefNprvcbLtcQvuQKWV2dE6cmUtQxsxRzM1Azac6mdeUOyT2RdN4LUhSXaxmGASIokU3BVetsx4OkzbInErJxHRebfVAGEAD8KXLcOj1KBjAkiFCR0JKBGS+euMKsBRcfQSZX1flAyQAtPLpFnWbB/5cuC9rIO9neAG5h8g5rICeLfHak0R/hP8LjsdMzBixbnJgB1B1E1VvzpMQ1UKcO0ruDEicnCiqfZ3JkCy+B9xANaASt9Bsj8SdoigIht6bM0FKmXPJxJtuyG2Sepz7XS4XmYec9vN0bNLUzXDlG7giGJo56aNbt8SgxOSrfMtiQQ0AiRJzyWnJsiOiuYd2vLkuIawDLPBRtKmGJRUYjxiXGh6IBA1BYsk852w5IWdgTn1KPaakqE1qraM0RUiLAnqXUlkSBEgAqG7NbD75FMt6AGbMOQH4Ui/HjIAqzVSDcCutgVlid0B3YKZN1+VEl5vi1hJ6ToVTB0BhJ4gYPRTGgHltVgugGpvrEqPQwjcEXCIeWxUWA9RqhqqeQFERZelsv3R2D7LC+UIPbV9IBCnRpsc+W6Ha+dh77Vy6NrOMPqsrEDkk9QTQZdoQ98x9odxjLt5xQznMY9tjzpAyOuNSkcQ5l5TK0A0lF/fW6jge7vf3N3fX13e3d3e3h5v3+7ubw3E/t+oAlDvOpe+32xefvLh6ccUljW1SkcPxsD8epnlW16XP+Pl2FQ0FQtqa1vXm7uYKoqEcbJ4pYepVZplkvDXw2o+eBnJwFbSRfAKc0Q2X0qolmsCFiocnuC0WaaRscOkYFtSPRYe4qggTLyKERDmXvjMAdPPI6Uau84RDLbtDgDOrvCJHRTpSIiqZSoLEIjqP475pA3A1r61lsJwwMW5KUi1umJn6zImB0IAsUHe1JUBhYmZQWyFEdMJg3S9ZV3OQgNBi1wQwNwUVUw2aXkxrdzU30+6s2srd53lWF1TmxIgdgKh6ncdpGmudRcI7AkNbqw4icUHgCTB6hyTGnKgkzkQEqAZqJuiEbsxc+pJzJuY1Uora2VPPmNDT975jsz5EoYlji/UFwXRUQwt9FUBmKumRZA1aIzl63el0T3SwPJmRGgM5LcIzS9GgAzgieAJI7rwmv8gRDVwdRb2KZoLI3ywyQmvciY4M1HfD1eWzV69ev379ydXls22/tebkOadScjcMm5RJbbbR63w8HI773a7ODREvrq6eX11tLi+6oW+tjtNx/Ortz+++PV3Ik37tgARkYCthJBghCwPMIXO6uthuNn0fNQRAptaiG5ZVZuj6nDh4KMExychMlBGymtQmtYGoN7Ha5Dg2UdheUN+HsEYiBqKg/ig5AkA0X0BnVzXVk1YCIZi1Wkf3xoyS6mMDHJx5Y8aSOeWUczJ1mVXc1BbFXE6YCkUf15CBEjB0NzV7JAn55O/IDOBSJRCkuYUQjUS4lPbFuo+yE4N4ycmdDDg+GagBmoFrVGs+4gQgIWeOJg6UkNLSNSWSUIAU3p+ajVNj902iDhOjEFoiZErA7AASf6JeFcwcdUn6m6iJrqfLBEvUUr0dxEW0dbljYu4hUpdlmzbPhu1zOezmw36ajlMdJ63qDayhRpcVg8foQzhtBJQRMVEKHPtkLxE4c8lcmDICupmYRCvSiAsCyMHljhnRwmExMHcFNAJjXu40oTN6SdoX5YTGxMw5p4LMgtZ0nNuobQZNnDsa+nwxlE1XSkohTkUB7za3anoOyEdBs67FZ+HJRZxdug4woFT3pV+UuQMh5QgyoAMI1VgwQ1URWajCKeWcozhOz0fYhpTS0PdMOKekwT8wExX3kN+HpegSAcBFtAZ2L3LCvcwsGF6nQe4FsWyGF882r59fvtykAapT8yKNZIRWTRQMMPpAcm2QU+rLpisXXe4zpuLUQ8pKsp+qz3kY0mYgLxzhak4ldaUMw2YgguN0HA/7+7vbu+vrm/c3t+9vb653t7fHu9vpOM6tacqpH4YXr169/vTTz//oB599/mk3lGke9/v97e3Nfn84jkez6t66y+elbM+eiMbUIkaiFOIFoYNzKhNUsQIlUx6SV0vzXZ32c+pb7lPKKacuQ0nWkefkBQwdAZkQ0REUQwIRV2rNsgOE++VuywKP8iuzWus0juDAzGthNzBzTtnMomjC3MEe2RJV0VYNFcgWZBmZ0Jk0Jxr6fuhKSigyAhjWo4iqNlExSwiAQEwwZCbHxNRlJjQHE7dmXhWrgIirEhKVlKSJqAUZFYkS4klP3wGrARkXZ0ZEMjGrGuquykBMjIhqVpvMtXVg25N/AqBuCsaITuqkYrWqTXWc2xTFTouLTk4JUsaUERBMAR2JE4eGTCCAjgjEiVJKgDkS7cScSwka4jnsSgjk7qJu4uronhNuN506GKwZBiYgJKQMCc2NGN0zcp+CEHAGzbbJpnufdtAOlIUJl6VdVdGYiJzXsmwURvNG5O7UqtdqTHx1eUkEXZ8BdZ6rgKRgV1sg+YviWUJLiS8226urq2eXV1cXlxfDZlM6xQBgODKDtek4jXc3t+/evj3sDtKamxNSq63Nsw89I6auKyUN1/vzefWk81tY92WThDPqtptJayZacrnYbIeudDlnzm5e59qkqjZAJY44QXRhmSISAyRVOh7lfncY61RDC2LxgCI5SoyJATkTkpk1X8M1XJ1KBwI3cMIEXVe2254QU0JmZwZ6CmVrpFly5m7IpeSUWKpaU1zM59K1HgkxAzIS4wLMO0oDWMIeOuPWIUBopQazbynsPHnzK86x0j4WqTR0JydHdyAHckwLyB4wFEFUD4LbY7EcACbKmQEICZmRGOLPokITfBJ0AWitzegiAh6hMYRwZcrJkdijjn7RYlU3BDd3NBeN0BgcCdiRMBxysdnaIjHRpZI5U+LERDlxTqmDfttvx2E+jPPx2CbR2ea9jjupo5m4P86PINJS6ga4pNh9qdVZaMacE60hu1no0KlK7J64ulNxMAhOBIiDASijMluiJRPJaImtzz50iJwqMHEqnLIzNZeqc62TizB2VDbpYps3Q9eXHEQbhsXjVnEVfyw0e5IUXU7D3d3AQgvWAMGciDTYu6ckQqTxOQGAgKyNIm3pNAcYOxScskS+cFAiZI+K7ZhbtTZVDRfhQRwCYCWDuqrO09wW+VVacmnu51cBAFd9j5cXm1eXz19ur676UhxExVtlm12rqrhFKbU0bBXq6F6wpMQ5d9T1lApQNiKBNtbahJFTP6Q4X+KUUteVrmRCl1YPu93N7fXtzfXd9c3tu7vb9/e3N/vdfhqPImIA2HXdxeXlq1evPv/88xcvnueS5zqP4+H6+ub9+3eH42Ge55wtFZBNe7RClutaAPRwhmICByoUtMRWoxFMn4HbtJ/bOJOlYsOWeei4Gwp1kdGObE/w4Q0Dc3YCYmRfCHi4glC+NjFfegWJtFrrPM9uHrX1OZclyo8CbFu6xDwR4kA1RPNo78SRL1RcSjg5Z8olp5SRoLTeXBHEBaItWSNlAgQqzNwxBUHdUQ3FYBKrSqKI4MwQaqBJUdAi9xeZ45SoS6nPCZHFSRVB0c0c5NSWAR2IMIcDhTg7VHWlB5QREZCBIBKDZt6qSGsy1VlUzIISjYTAmVMHuVDAVKqeiJm6nEvi5BZbVyYmTsgZkCyStMiUUgZYlhjgah1AMUQtozRPzBVMQSPKcEQXMooaxoSpzwQ5OssAr/vGaWgd5Xhn8wFkxmQYZeeGKm5umjQFQ8hA3EG0SkUQM1QBbQ7uQ9/F3q+q2szXWiAidkSLWM48M3PKQ9cPXZdzIozWTHZSKDf3pqoq+/24P4zjWM2hdMMqN+BS23ycEhPnhIT+eF49zbVHUnvhAK4YIDqY6fFw7HJ+9fx5hLiMoe0OIUwe1UqJyUFV0eOmOoGTKs3V3r27/+bbbzFp6ZCYEueLix4w55CfdAfEnJnJ1UAN7dSgwYMV6cRRl0mZ+WLTAyy6MUzYc3l8HUYUqup5GLqUGcFV4rHbahvMXEUlZeYUgjyeCjFQJL4cFnLxqh8LCEu46QYiCuJJEJLFtKOl1COWsyMSM4cEQOA0hhazP52amwGioZObACoufRTXwUxd4VhWzAGTLaI9gIC2cEaj31lkfzPj0GUGrXVuZoyFExMs7YwQ1NXcvbmRAZg3czFQJwPyRc0qPBcAk9ZUpUoqhUtJHQGbRHcDHi7S9qL4y0HqRibRye6vx/ff3N/bXKuYPZIZiCxVQEIrLLloJqx0hUTMQSBWN7Uate/g4XWvLSqWTFXsuYqgTFqSZrbEgADmzmxDsr6jvs+Oyb0j7Doo2QiaNZHRWkVHTH3qL8v2ottuyiKKGZVMEhrh0XziHEQBZE4LxrKkzBaxvJSSAUZvCmON8ioD1wX/MWkSFUGqZqYASIsAgjZRtTmcwsD0zos5w34Hc4h5eTFsSZj/eM9CiTGPgL7rOmZePIinvC384uWL15e4/exZf5XBp0mPDedq01HrvEhaMSG2ZtMo84RtplYaWs3eBjbuqE8Zm6uKibhoItp0XRk2PHQahdVMiDaN435///btN++v397f3e1u7nY3+/3dNB2rzAYOiRk5XVxcvHz54sWL55eXl+B4f3tX2zyOx3fv3717/26aJne9et5dPevOq60AgqsMtEbTsAqjh/secldmpnurtfWbIechO6ilVqs1It7kfFHKpmCO9U2wrEsP3bklhYVLb11bKXMAAKfsCbp7a63WuuRB1uLhpVLMTESkKcRTZ6bHW/CgRMAzQUUHcofgs/vyzdDMsxiaO3PqypCTU521opu1CsaQoml8IkdsDmLQBA5Vx7bIRQwdFYZZwJulhAlOpTtRVYtMvMmlyxkoz+K7WWtrcbMLkCI5QSLMDH2mxGxmswj52dRCzF0yRC6E7E2qqtVZWhW1SJQTBgDeYxmIMgBCKNBQn7t+6EuX02raMREhsSNp1IgFzGAhPhEkn4cwCkEVFNEI1LXZ8Tjvx7mqijtyoO6pz/miGzZ935eBmVS1SZ3q1NqjvJvWsR5ubT6SCgI5sBiZuDUHcFMHBUJ2ADOtomKiCq4RTiIjp5TUvVYxVTTIiXPKhRNjUsOqsS14Sbnvh0jwtTofD/t7Ltg8c5fTAJRARWeore4PowhcXD5n5r7r2jwfdjsEMNHDbnc87IKxcNjtzufV06g9+g8RMdLCkMK15ktaq9Nc51maQFfQQcXqVPf7wzSOVVopabPtAL1pUxXVaMcs8+z7g7x7e/v27e3mIj9Lm9KVru+QM1JyoGiYgOSJmdnJgQxV5ZS3jqgEomE3ce5SShxQOKITQpECZz2piTElKl3u+ly6RAxmtjbuXLh6AGYhGIeR2Ao83ZGRMyQPYH7Z1J9k32OdW5BpxSE50+IRweLo0lL5vkgArR4VLlXXeDpsVKetqlDnj6Nkvtj2ZmgO0WOEEzIvZPxoRuOAwRIMbIUIciYCm5qZO5uAB72ZUjAsDRb/Nkq8zNXRHN1pkeLBACNhERKS5qrG6uaM2TSCTE+cUsZEhN6jujcsXXI3JEKau82jebVITy0AEKw1h5HHpBXeIAiFRm2tBQ60bJSR0Vpu+1K7EblDS6yJtSTLTIzg7szQJSgJmcgpZSvkOSmjgIpUaaOJMhGlzKVPXcchwMy4NOx1NW3axJpYO9c+QiSiRavAI3PgBu6RJglnnICMlZat31TXZLevaVSm0EtZEX0z89Y07jst/SXP4MGTqV/tN6z2HuDBhIRH6fAgLRbm392ZU8Kz9jAIf/zJK/COX3RS5O64n9sRbWw+zy4CCJjAUMSnox32Mk+okq0p2ZxhKsQdUE8MZmKydu8MBI4IOTqoqDSRebe7u7l5/+7dm+v373f3u+P9Ybyf6iguyJj6AphyKmW73ZbSmcFhfxTdj9M4zcfjeLi7v7vf3QN51+dU+n5bOJ0tkFWfebVSiwuDIdtCSIQBJYuKihJmMHZhlIzi4AiSoDEqI/NywAVKi1kbyzWyb4tLvyK3D/uAL7KyoqLuzkRIQZmO+exqKiK1NXAgYs6O9Gh1XPIwJD9gG6E1aHLiwQC4i0idkRwauIICAhMBszEWBfFowIlLM5hm2AxUyQzMGcETc5d503FJZLPNpqGBAAsHyJZCPExIKaecOTN7W5jJzmZA6kZOTowp01BKyUkUxmYs/BgPIkQPn7VVqbPMo2gz1aD1ADNzgiiPcQ9jSZxyyV3fD0MpOWVwCtOOCAAKEACEGcYj5vBVEwbpCxOZB+HHoumbt2a1Sp1bM1UwsgWEQKTS0zZ3235IKTWt4+TzdFyEWtdhUrWOYA2jPtDQxZEcDRxAqzWwlAiA3EzFpyoiUTuLCYgy5UQmNs9irpkQiDilzDlRnsWj3YUqYJdy6QCx1nave5k1GSdLlxepFCJmJBSV2kTVUy5933dd1+UyjUczB7WcaJrGw2EvJo5+Nz9yfB+b9qCbISA5IS791nChH5OjmY/H6Xgct8Og6vM83d3cff31N/d3u7nW7cX29ScvOVGTGQk4Ua1yHOt+X+/uxjdvb3a7sfQppbLdXmwvNwaoCqIgGsQoJ0KiKN5GQTI3BArAG8xMjTglzl1X+q6kREiLIC4c88m0IwKn5Ohd3+UuUQplWYtyqSi1QghdVliyAhzz3GINU6IMbLaS3R+ocY9o+yEIhcnpJPgMiwcQRiuAcJXYndcG4Iv76WBKQQIhD9Lo48bB0PflVboUA5G12yw5knNQDQDFIfRxZJVRAVCKR8ggood5LKZDNwARJ07gHEJOS18hUEd1Mg9WF8UKJFxBqsjmqzRxEGA2xIRA6qbW1L1k6gt3fclccuGUU78dhovx2ctHFZaIFKSZRdEq8CzwKB9cmkc7REpvrvNcp1ZbxEBRqhPRWFg6XPhyVBi7BIk8kXeMhSPd6oAGSOIJLLHnpIkETVVEJ22TGwL3mEK+J2Rpl/SeA4I3lVlqldq0upfzRxKyBYEiARK6OQCnlHNRBzNPxJ7MRBYxzKXNEoQeWd/3UQ0jKvM0RbOZiK3NDJYS00WycLX0oOFhtXay6yczrysOEDXxiNh1nS7dTxZR+q7vibrzLfiHn37CMNzh+F6OUzvs6oF0NtBKDpQYs4gdD/Wwb/udqlB4eW4zGKg2MAMENjTV0URcjzKXedIpFyIjcPJWx9rGd+/eXl+/u727u7u9393up/1ss7li5lIyYcq5K7nvU1dE9N2792/evJ/meZymJrPY3LQ62NWzi5evrz79/MWrT656fRDDj9QhQNQ8wdotzKPkOCU25ZBNcwN1ncZJWlC5FBGZyE1Dcp857DFHm7IIEAmZ1jQ7RG4wAhCKzQLMlsLlU3we9LmclsI0C7KZiDRptZkZEmUvSOmcRfeqv3rRbfc67W3awXy0KigAxuhgNs/zPKuqI3pm4KDYK5ATQIi0oziqoijM6s0gIWbkPuOQOWcqmbucAAlb8+BuPcjA+HItwFU5KyaGQnhZUofUkN0JBZENCSAhFhqGXEquRscGyfkhoHJoM0BCSuzm2qwebdqrNovyAWAsnQHlIm4NVU3dy1CGbjMMw9CXPnclRDcwxFjBrZmrgyqawOIjoyEiJe5K3jA5QmsuNXQezKpqVXPEXHKiHHkZAiych67fDpvtZrsZhsRcNUUjxycQI7iha2RMPbr7Nie0Ao4AdRZX6DoCjpwNqrqpkTszl0x9x13JVetc1d2wEMTcyokpkZmBi0Nz6ImAWdQOx2OdtHDJ0F30V884DcOQh8GRx3lGhNKVlPLV1VUpJdDOoTYC6HKuTe92h93+vtbxkAforz5u2kvqNt0l0bpIQvsNIIAhBOy4gGatpJUFqE4wHW086PGgc1Umm0fkhE2JE4GzNJRqbZZWiaDr8kWfL7t82ZeroWzUQMDInUJHYe0wR+iAxrQ0uQUADFU1MIaUcMjUZcqJiDmyxmbUnZ4PIj2/eqYuw6YvhVNCBxVp7IWss97BCNCcl+qHMqTS5/AdoDkoIrAbzp20auAcIvoAeCqxcwQHxWxpMO6AC3Bm4hyoauzUSz91c5WHSqQ174lLoIMUzZbAkYwyFT4L3AuXi3Qh6pIWaM/RAC0hEqIBCgC5MqggdwwJMlpxzU4cradNUSEpJWJGQDJmQzcNCho4sFsGc1RCBVAAITBeBOxA2Rbo2YkhsxfCjEjuFjr45JQw59R1qeetuxS0wthdbrdn0woZMy7ilaDhXYOGWY8mOwjJgc0JzMzRnREzkQEaPSj6xS0LEmxA8TUnYRJiI0rMlIiQXN0MSC0T9uSDezFjM2veBFAxMRbAQb1U41GQq80gbI3ZAXCUeT8thbjn6SsDqBpZzOAgoTlHA3UCVgB1RwRHU4waEIjaOnBTJ3JKwEQZmcxAIhpCUnABijpqM1ouO9wXIDBU8dasSTi+tKSSiRBRFk4KoBMYIkVdEolqM6wWml7F+czxBeyHCwbaN4c2AvSIG6CE6JkQOSfqSG2mKVHrkhoyYknU5VSIsnsSYzEONxOSA6hCqgrc3GeFRSKyTXOdjnWe1ITQC2OfEyMAZsJgTZWcui73PRBZ1O7X2maRKmYOQJm7VOjy4ur51YvL7YvtcMHjmWlHyrlbSmGCkYoLKwfcARghOOayCMkTQzQJxYQEKTFzRmR3Mlt+C0gG5L5gl0thaoTm7u6hPk9ruvyBabPIziYiwJwzL/0GFcmRMidhi5w6EmeiR+VWSIUQ1sIXRCek5hAxOWojc1cxRPBCTIQAouDiEGvF0AjFoTo0BTGIsjmO6nbH5IiaHAiUUIUXERBamP4hwQWkLQmyARFhCkK5J/eFakWLsg6xZ/KUAQsiw0MtIiFdDM8geTckAFfSWVtqTdnd0NCBPfepH/Iw5L4kVVXzfrjYbC4v+otN2XYpZ85EOcrEwcEluauhKbhGYUfw64gy910eCN2dkZunikCEYpotN8SuZENGSgFoQCYeSj/0l313UXJHTI6pZOvyEVzw7HmknLthIMxIgikspBN6JsgIZI7EQB1xYvIEkrUSaQIoibqcu64rpSuacwF3yx2nLnPJlDvCTG5swpacjcsW8+DE5j6Lithx1kOVY9PSNHMz0OM01bmpSiGazVTE1KYmszkhusOotq+ym+ZpnNomQX82r/7tv/23D5uXq7k9Sc2dD1yoEEtFSEyNpX/A0p0DTzjzYgX9hD0uru9DX+B1+MPxH738mGd9esNCInt8gKg/W/4RLRfP3vhwDh+5KDx98+MTeXj3eUT+CC5dP/5woKeHOaNhfeS7z9/kiAiJ0+nmLKf86M1Pb9X5FeFaartkbR/eh6fr8/PjnKWYzl8/v77zb0f4YGosmYWlTABgLeJbc8nrYT6UAf7IYU5vX/dNgI/cMl8vafnn6emdHeRs/j0+50c3ZWWKIjyaUSstcpmwZye5PuFH1LrzGXD+8mnurNERwsNc8/UBrO9/OC988pAfFhI8+e3jc8EPXlk/Egvg4SRpOb8ggdjjD51DzaeXHy07hMfL1+GsTvbR3Fmy0b7av8dn/uT9y0k8TOj1u5dURbjN59kK/+hyfvjl09vxdH85Td3zJ4j4He/+2Fx8tIL87GYhrr89uyZ/uJHnqTdaKTwrPOhn732YLWd3Cx998eMz88fnff6kPtxNzsfD3Xi4oo9cddyvlWWA5xNGtJ2OtD7MD75l/ZqHuYm4zqin/4ePPcOzQ+H6zetbzh66f3D58ZHz2btOUOCzFElIaZy+9sGanS7r8V7xcJEPC/zUkNdPO0t8q59Nh3XjebhQWrivhCtp+OwG4KPzXjNQ9sABiTM781HOr5yQCZ/2pf/oOF/2tIT257fw/G5+sEY+GN/1++/83HdP0PhUPpO2+H/vWJnhv+FNj8Yywz/4zVMn5eP//A0H/65x9nUffdwfCu39+m/Fk/H+nifwcBa/8dhn7/fQ/Dp99Ds8ybPjf7BV4Xd/8bmf9/ht/sF7zn/zZJ/+Xt/1Hb/5jrmzStMhAHznev/+d/6x7/H46/H7LP/vOz48/q9ZHB/xQ7/fl3znHf5Na+XDk1m37l+/hu3B88Wzv8Ef/efJ3PjOIz7dD/zX/fbpeOp9feQTJwfm6U6CmNMTLvPvPB7yn7/2TR9347/X4T98NEQE33u/+k7L9R2/eNjZPva6A6jDE/m173ceH1lmv9We+4fxh/GH8Yfxh/GH8Yfx//TxB9P+h/GH8Yfxh/GH8Yfx/6nxCJAfPnnRPb/wU2pnzcmtuP8J4cdTevUsT3JWjhMCLisotuazztCpUFxZE44ICxP17BBw9qGHzjynrJ3bkg2NY9Xb/fTuLt7Tdd2/+Tf/pus6+H/bEJF//+///X6/iAr96Z/+yf/6v/4FAoLZPN7vdu/efPPTm7e/ABldZVKvathqr+0F1ivUjhFTntMlXv2g//wvy8WnzB1TYgIxrS0aQxgT5qWtZVD+XFVNVaWJ1lBUUXNdqXunJ+rLVIhe2EuzekRCYkQWldpqE1WzpjrWhbjl4G/mezEDdwIkTASh+usAunTVMgAHUzfxudZpHPe73X6/A1ciYA7FT0dcpQxCgyqylks5PsHaenNtg3CedF5zXGsO1Bbh+VOCMxKjUUK7XDcg/O9/+r9fbRbS6R//8R//y3/5L3/vD13NVDTkmpEw2iSmxL8Wbv7txvv37//jf/yPy6pE/Nf/+l+/evXq93Ts/6Hjv/yX//KrX/0qfn79+vW/+lf/6ne5SY95KthaOxwOd3d379+/r7Uy89XV1atXr7bbbdd1RL+3KGi/3/+7f/fvVBdCYF8Kc1rST35K0P/24zs+eU6wWfPSFsW7agoOoUVPnAh53abxYVF80JFyqbR0D93DeLFJ+/rbrwF81Up6+C+e2uGdXifCRxmMp+SpR18W/4l/PU4wPCTY/WQOlm3KwyRpO+zu9vc3h/u76XgUAVGook1NEULhpHTd//n/+z9P9mI/z8fWQlEqp0SI0mqb51YnabObuAtEw08AAgRHFWtzCw2JVHLpCyYycDVTkTq3OjdV9VA9Zywlxx9mbk1qXd6Qoh1vSoioS4mNi2qttUkTETdAz8+fffLF5z/6oy/+9I+++GHfbTHa+XB69+4fvv7qv51uziPTnrdD//r5souf6BGxnzuEBMSia4kUFhcharYcT1Y92Ndrmvhk1x9Iditx4sQuwbUvdTyeVakrcoGP2FF+Ns7asKA1gdW0p5T++T//55vNo/qrD4e7q5mqES46Vr+/vfSfOFpr//k//+eTaX/x4tlf/LMfkaOL7ndv3r87jvfzDt663lubTUGa0DRDHXs/PsN22SGV4ZBfwVW/vYD+1bbkiy73paQmepyaqgBYSdBn4qjiVjN1FdEmrU2tja211pqoipqF5Irq6ak6gAOtwni0yPgRI6WmMk0QGhVQfVwvyh0OMlcVdCdMmYAXoogBKrkThZMBpq7i4zwfDofrm+vr929VK4FzgkQLeRkIF00+DpVeJApRKkaIvpQQwvIn6/5AXfGlMY+DLW3RIPj66ybv6I5mpovSIP4vf/S/nEz78+fP/+qv/ur3+LhjDs+1juM0TdM8VyIqJfd933f92ibm9zAtf/nLX/6n//SfTqb9xz/+8Z/8yQ9/H1fwP3j43/7t355M+3a7/au/+qvf8eacYgkz2+/3b9++NfO7u7vWGhFtNsMnn7z+5JNPnz9/nnP+fVn39+/f/4f/8B9Opj1xKjnDmcmEx27H976Y+OvpB09R0brfujmYiWizOps75szQ5ZRXQUY6ecdxwJCuO82f9WB+ugQAMNXb+xsACAlFejxwlVuIEWp9p2eHZ5biyXjgZ4ZF+uC2+KNhpwjEAAhMW72/e3/95qubt9/e39y2BnPzcZZJVQAUwAE2m+3/8a/+j5Npn0Tup1nU3KHknJCkzm0a63SsdTSb3QRBES1FeZyhzDIeZ1VDojyUbttjInVrIvNcp+M0HWdVcXBiSJn7vvRDN/R9Tmma5/E4j+MoTXLJpcu5ZGLWtftDbe04HqdpktZMEb189olutp9+/nm32X56efGSqeTcldLN8+Fr+A7TvkYrUZcV1F4AgIeyrdUxxEWojlZdZLeHndTdbWkuBLB0dT8j1z5mKa4zw2ypM1lnNUUV79nTffIsz8/7t/Vz1V1Ed7v9br/PKW2GfjP0Xdc9OBzfMdXOT+PDt/22n33y5ievN5kOxxtQk1rv7765vv32frzf6SytSW2zQ1MjcZsgH8Ws6pbywPs8Sr65f/OL0nzory4unl09e6GWxiYqBq7gWBLwUufAiEvRe8qUlaU1EWmiIioSwqhLD7bocmy+unmOgOpKiIzUwC2xawjZ0nk8BBmJUnRAyjkNTHlp1xTNBuKWL32RYKj18uJi6PK2S9Nx36bR3QDMUR3V1955AQHAQptGiMLJmHOAq3UHiFjoRHj38PxxjeCD47uiUwsIRXTiNv339PZak+PxeH1z/ebN27u7+8PhwMzD0F9dXT179vzy8uLiYtt3XdeV0D+JGfJPMGb/FDvx/+nx5H7U2u7v77/66qu/+7u/+/nPf/7VV78ax4mZP/nkk2+/ffvjH//4L/7iL54/fz4MfewPv98YIObluV1/8tvvfaCP8zJPry6bGwKotvE4He73u52IlK7bbC7w2Yt+s8VcYBHLxwVG+Nj5fORUVxmGD+36Gr/jk38+mO3Hpv18E4Z1/w+q9ilqP53G6b6d1raH1YiA9KEg61S7dXbKj/9ajqwgVad5nucZHBixcMpEOQ8pFbXqrkyeGQszGkjVmhrhZGaYiQpjJjUTbbVaraJioR1EjCHWj8gmKNVBTSbTWa2qNVnlajWXkkuGxGqmqtEVHjgbICiryGF3f3395s23X42HMefNdnO53V4udWHr+MC0n9eerA/38YN0j/asocGiaqLmZmDElFKiRUgijhHduB8i7w8f6uIMPmArJ9tOp4cXs+H8tycX8rfZtpaJ7gBm3lTvdvtv37wb+vLi2SUzdV13frRfs4bPb8iZN/Lr3M/1zfDR1fLRj4zj7t37X5pIm6fd/dub66/ujrcHmeY2tzorEhiQuM9+c6fWhBqV2nblONG1b36R6jT0ly/qZ8LGdDlVMgE0Y0QpEIItwIRE5IDJ2SgZaxFdTXsTkdYCLD4z8Lao+hkAWAgVBo6TCJStqiI+UoHIxIyQcyl5KGXDXBAWq7x0kgJwwMVoq8B2M2S6yHS878f9TkXU1EAUommMKaIC6rp+wTFCDfDYAQx8rSd6qFlZ/rivK3z55SlgP1UW+IIv/fcxiEt8YXY4HN69e/erX/3qF7/4xfvr6/3+wMybzebFixcvX758+fLF8+fPr64uL7abvu9zLuerAH6T+/g/dXyfG/c/6OTX1N6jV+As7myt3d7eff311z/5yU//+q//6y9+8Yubm+tpmgHgzZt3Nze3tbZSOlV99eplKSUM2O/x5p+Q5PX0PpZI+t7HOo3TCeLjf7uZqbTxMN7d7G7e17nmvterF11OJTMkRiRHjk88iEV9jxFqS6egPP7+qGk/vbKUUHxg4J9McsLoAXrSE/APbIGv0Sc4AHpY9xDKOn3Xo7M9Gaknv5DW6jiNx8M4HaUKAV4M220/5JyZEyI7WmIoibuU0ICgujYtydG5I8wEBE3VIamAoDkDZ6Lo9cWMISiPnLAkZCNSAgE1U2hL4Z0jcSmEFN35ACCaAJGTG1mTw353e/3uzear6Tj1/aWJElJrj3qkPRGaRcTFyOLpsh/F2IiIKjqP03g4Hnf7aRzbXNUU0PvN5tnzZ5uL7bAZENmWWw0e7XTXGfyh++Znqw3OfLEPg/XHj/MMrvktFpoH8q9qx3m+2+1Fuq7ki+3W3UOh8zceIr43dMFEREUAMZKkvwuC+uSD1zdf/+3f/8pEVVqd99N0uzu+m+Q4yaQqKUUXUiM3FThOcAOOVe7KPMGdbb9CvWcszw/Xh6YXmy8SPydPaFDEmxgzLT2zQh3Cw9l1jFaZZMSWkkoui7hZa2sHX1Ex1KX5kZufrKEjIKh7dfdzhmbk5DPnXLrcDYkLAK9Lytd2Ko5u5EpuSEBdHq4upLBeblVN3QRETGqt0zwfah1bm93ayRo/9Op4lLg7bRHLDYZTtimi+zXb9PB3bAmncvnfvwVCxNba8Xj8+uuvf/azn/3yl7/86uuvd7t9rTWl1Pfdzc31119/PQzDdrt58fzZq1cvP//8808//Wyz2fzTGCT/D3YC/icMXF281mS323/7zTe/+MUvf/KTn3z55Zfv3r1rVa4unw9Dm6a51vqrX30NDvNc/9k/+4u/+Is/f/369dXV1e8x7w4ApxT4k0Dlw+3ugyt5OkFPx3l4x2keryZTw505Hur+Xg87rdWlTkTTxabru1Q6TgmjsWR0aHSCxf3+dQEVrlH7R6H4J3Z92SRPdj0M/7KZx3karIZg/RXhY9N+Hlw9WHcAB7Sl3zE4h0jRmkRG+41rej7udzdvm1SVak3doZrgPHPKyOwEQNEEG3IidDQxqdqqMCNn7FLpNxskNsNxmo6Ho9TZWnOIRkOMKTGmxPli2Pal01rH4/76+u3+/sa9AoqbWzXN6oZiIecHsIrnu4GIzNPxsL+/v7tBIxXvcj8M2/P8CHzYr31N+KyEucdzJF6ba7u7vr1++/b9m7eH+12bZlUFhMsXzz77/LPXX3xWSsESArHLZ06B7enRnL4QVuzf/SOTZrXdj+buE5/uIy7ZbxwO5t6ajPPMS0+tUzXhKc77eDwdFl1VW5O6Dmbu+0iSdvhhS471mB8sxl83dvt3Y/vKzF0NoKrOY92pzWqiLsWhgHesnBwLY01jg6Zw3WQsBz++U7uTaneHY9P+9cvy4tm2MKN6E2jiKQEnRkyICXy1sKuoPqMTmTFzKHWaSM4itbXKQlKNJfRM3cAWEMxV1ZpUkVkVAR6MEAECEHNKqaTSpdSvCt3gHq3LndzRhbQRVnQrjNhnyoTbQS06ZqhYm6ZpHKfbw/5uHEFqpPt8NcruKyTvp/TQk8e+xOKnQtKPRCSL0f+ukux/spl82JWmaXr37t2XX37505/+9Fe/+ur65kZEEDGl1Fq7v9+FamxK/Ozq6vXrVz/+8Y9F9LPPPjv3HR9Pzv+5xvt0E3+X0/ioS/0bD/jr3/DQ4n0xS4HqqM9zvbu7/+abb37yk5/+9Kc//dnP/uH29gYAu65st1tRBdgdDofD/k6ajOPcakX0aLa72Wxyzr/3e/5kc3ts2h9j63El/vi1ZW/xFajAlfIMJ2Emc1PVNs3z8VAPe52O1pqp1Jzn8dDmi24rHD0oMSThn55k7NiE+GHxdShphg0PUP6RVUfEs9cfYNt1rBMb4wpO94EW40wx6c9w0vOQ0E8v+3oXImonWntULLH72SV9bMa1Os6HO0BHMDQxsblVgWPI7FPOlB602KNdGRi4QyIuqWz7zdXli1x6Bx7H+dAdpDZVWTTOmYkTODHytt8MXU8bl81UsLvPg8ixyTzLbODkBYzAgNwTOrBGosQJE2czq3Uex31JPVNpraqI26Nn8ti0n4CNFTheZ8gaQzu4+Xg4fvXll7/8x5+//eqbw/1Oa3NTAH/24vlxtweEq2fPOCVfk/VnW9DqogGGJvrJKiOik6NDKDI/zKQPgvLTZn0+N75f2H6Wa0HAtV0s0nd4Bgtq+yihYGa11nGcdrvD/nA4HA7jNLdW+65/9vz5yxfPX3DCEh1iH27hP22IHqW9cUMwcBB3AawpeU5IglmlA3ueYHuFOQ160R33Os9a3UcNv6WO+2meMuq3jK+vLn4AjOYg5k2xODlmoAKUg1i2ZKqouSFgyPoDhJQyYSKiRJxZJWsxaSpNpAWh3tW9tXY4Ho5tmrQ2zeemHU57EDFxppzh1CrG1qjFDRXRldxRhaSyVnJDBE/syApohj3AAMihPz+BtXmODnFgABgC7wB2atr7mJKxzOrzP4/PcN1Vl+D+9w/JR9P3m5ubX/ziFz//+T9+8803u93O3YdhGIYNM7n7bre/v9/N86QiX2e++HJ7d3e33+//xb/4F+E+RptX+Bja/D97fP8b9t8n2/Gxg0cCJDqGJ04AMNd2fX3z93//k5/8/U9++rOfvXnzZhynnLvNZpNzAgdTMfMQ8p+m+e3bt8xU23w4HGqtX3zxxcuXL1e1f/gdbfw5nPkkGF1PHm1RykcAp6UB1dlY46743Iq34qkxNy7eKrhaG+dpf5yPxzqNJs1VHNGkSa2tNRMxNQ8WWvCkg94SxLr10A4E8CjswUXsBcKuMxExhzl/CNkf4/OnrfuxaYeIt+MWwEPEHcHAY3O+3qcz6x5QvLs7ugETEzJF81YP9fQzlx6Xtt2P7qUxKTEB8KxiLnOdrJkKIKYybLp+KCUTk4EBISdKOSXOF5vN86uLZ8+eXV0941TUMfNMkG1YOsWBOyVGpPE4jeM4HqVNx8vNZjtcbX6wlU9/MM67w7i/P+zGNgORI7BpzlJSNTNEBkAEIkzMOaUcpCcABzf8YLt6nGsH8LWs7DRjcPlxCRRMdRrH9+/ef/v1t+/evD3udlbFVcFtnisQXVxdvnj1ybY2IFqMI+CaslmTouFGhUcFgICEwEypFMqEj2cuPpjJR/vv2a9+48Anlx2PdJ14Z57BWQPi5S5EE+Do4NTaPM+Hw3G329/d73f7w3Ec57ma6mazUUdOuRt6AE98msRwtvJ/uy3AoTnsl4A2uOygCAbq0IxcOvIXA73cctmUOsA7bzsTlTaraZ0nseN+FDpu6FinigjE6I5A5MBAHaUeOQOwua1i5BZ7gRNg9MWL1jVOSEiOlIhTUnFmYVYmIVZRA3PXVkXn2mZpBvSwXhxEFAALIEb3qJRXeA3BEAzBDdzQDQXQlEzIGmlFN/DoGkzBoSeR5NYhDonHzJNT7EUA7ot1h4X2/oC9nwLm9ceVe7fmi07z6pRBOnn/v8eBAK6q+/3+3bt3v/zlL7766qvbuztR7fvh8vLi8vLSzI7Ho5mO47jf7cbxGJmX6A3z8uXLTz759LQLwiNE1h9/0X/X8RGrfAqVYthpq/2AGfBoWz9z0L//d32fE3P38KLmeY426q01M+/7npmPh+mrr77567/+b3/7N3/39Tdfj9M09P12uy2lINI8T3WuKgaAxElN94fj1998M82jqnr0AUpps93mnAnxd73566c/xJmXC3HQNSTHJdiwlS8K5/bphDMtyTFcslMIAG5gbq3V43E67OfjUebZItQzNzWNDvCqdipxepAtfKCnxlENkT64VF7y4sjRnBxxse4xYc+t+7rzfsdsOLuNq/0nfDTPPwDmH4WkEdOjAyim1bRz9P/FB+Tu8Z9lmIq0OWPHlBIlJwNUdyMABGMDdsjIiRMSMjOnlHPOqWyGTd9tcioI5Et1oZkBYk6pJ2Ja7gdoxQm0SVWwoQOgbtt3KdFUx2E6luNhrNPSfjs6i6m4e3gs5iCq2oQ5+xqAfHT1PKXR2YkUtjZTggX7We7f3No01yoCTJvLC2Kax9laczPkNM/t7Zv3XH4ybDfECQCiYs4R1EzNlhvpS+cMQgI1dE9M2+32kx98fvXyGZdEhA7RnyYaNy7/WxIF67M/f6q/aQE9ulBc/6yxmZ9m8WmEE61qtbVpng+H/e3t3d3t7e3t7eE41mbu0YmciNgcp7nuD8furmtzzYn6vkTb7O/tfzwdzEAFpblUD1Rem9dZj7tZ9q1PXjb0YuDPtomajmTz0W+rs5hMdri1CUD2tNn0m3Sx7bebvvR91kZdSd3Ql36Ty+COKibNVIwQGBOiA0Uf2ZgxfrKRS99qAHQnxwSEmCgZG5BjI+xMZnBQPUeGHOA4z2hWHIBjvaTFn/NgoxOaoTZwcFU0I1M0RRNtTURn9aoexD5tIqIVrLkReklUHSVMCRg4ArjjWdQODw7harfDb8eo6XnYVx/svK/Ryu/RSC7fM03T23fvfvXVV1999c3N7S24b7eb589fXF5eDsNwf38/z9M8z6oi2mqr8zQB+O3t7fXNzbt379+/f4eEgFhy/l2m1u/heh6ndRGiNaNJFDuLSNiJaNz3ODILVsoTKvVpe//1X/Q9z05Vp3l+9/bdmzdv3r17d3NzM46jmT979rzvh3Gc33z75r/9t//7q6++UlNm5pTV/H63N9W2XoO5r+6511rfv3+PhLXWuVY1/eKLL169epVT+r2k3v1jxir+toDeF7TaABSiP1NMd8RobLPi70uY7oBgeNrA0V2b2HRsh/u6v2/TqK2G5Vmy3qH2YBHvrrsj+ikcPEdeg5GEj7fL81w749KK50NY/vyVD128h+OtL56b/vVefXjDFkfSHGhZx4AAwLTIbmAE7gF9IOJal/7YrgPAeJhur3fDxoZhm7nrhgE7I4BEmSkDZuLEzKUrfd+nnB8iTsf9YRynmfjOAdR8nNo4Nea+K9uSu5wKEyNBbYopd6kgYUO6G+vUrOScS7+52PaXrw3dPOrgMbw2Mw0zNE7T4bA/HPZEDIvvhtE168lIT194fEPXWbdsTKI6HsfD4TDX2RG7zQaJAUkquxqm1ERvb26rSNf3pZS1ng3MvZmKRmfcpRsPE5GDq4J6Inj2/Fnqc7/tu4TMCZcM6kqCfgSg4glFOF8Yv+148lR9nSkRc6haE5mm6XAc73f3t7d319fvb29v97t9a0JcSun6fqCckNgBa5XjccppP02cCC4vt8+QSsGU6DuCj9+0W/nS8EjUzVzEa7V5kmkSG9U7TD0M7NtigGJZcnJGdTURm+5RUym+uepevbz85Nn2qsupy+yc+q4bNtu+71PuRNS8NfE2KycsiULiJtbJYtrdQiwmQjMHMDCLtoDkCMiJgbhn2ILOqodpAn+02SkyYcJUOBXmRMQUZSlOkbECEFR0MxNFVfLYZrS1Ok3zYZZj1bnNTWZpqmqe2TN7l0pOHQEkNiM1iDL8KNz9eNS+FrrFqlj/rF7jI8D+9zIejmPuIrLb77/55puvv/7m/fX1PNfSdc+fP3/9+nUpWVWnaby9u93t7sbxOM9zbdXBc8o5F2ae5/n29i7l4g5D35dSUuKUEq676hm+9d93nFZb8E4iLJ7meZqmaV7+11oL5Qla0q9LuXMIpKSUco72pw8/BJNgUVA5M/a/jXV3AAho5P379z/7h3/4h5/9wzdff/vu/fvjcXT3589fDMO21nZ7d/fLX/zi/v5+2AzDMKiZL8IgGn3u8bFBE9Xa6pu37+ZaHTEyXkR8dXU59D0iriDPbx/Bh/V9vKGt93lBn9HFlj7fDaxhsE3DtEM06AzJJl+a267hy+oQAJrL3KbDcbq7nvf3Oo+uuvweoxYpHubSGyUu/3Gu/SGa/vBZ4JprPw/NaWXLf5Bzf/jh40c7T8SvPz190k9te1BxH5Lw5O4UgDwxESGcyHsPN+ZDk+hEkDL1fd72pcucwYwACmem1MQt2pQaJsqJsqiqRfmQhNbXMm2QRLxWZ5Y5ac4lc1m8nsSUE+fMzNKkSa3SSpMLSptSui4jk5qEac9MJSUHr60djgfEu1bbiCMCParf/eBSnjDkHyw6LkSHhxuHiK2129vb6+vrw/6oIiml0pVWq5sDGRGZ+/5w2B0Pfd9vhoGJI22i4FVaE/HFQ3QAIEByAF1qUA7Hw8svPnn2+kXqcyrJzmgvcW4Lzy5Oc5WoWxfDbxe1n/bvYEL7St8Q9yjzatLGcTocjrf39zc3t9fX13d3d8dxFBEmyqX03dCVKEmK/s2uqvM87w/ke1Wpr+qLlAsSr9GVr0vg+45arc6iAsF8NPNpkuMoTYGJQzhNa5O5olRrKg1atTp5U3bK/eXzT1588cMvfvwnf/TDV89fJqLElPtuM2wvtpcRbZgBoKpZFU1ASEw5ITMAoAGiuofgAABYuGQOGIiQqamamlPKKac+9Z5wlEb7PTxmSwyXz6j0/eYylwWYInACImIECuIqmpoItAaqCK7g4ja1tpum+0PdjXVq49TmJmIO1JU8dF2hVLoL7gcgc2pNx+NU62QK0e8SYKHVnXv5Yd3X+nhak2++2v/Tzx/hEP0TxukY0mS33799++7LL7/69ttI7uaXL1++ev3q1csX+/3+2zfffvmrL7/+6qv73f00RuyuV1fPPvnk0z/7sz//0Y/+dLPdHsfx+v31NE3D0Pf9MPRd3/ellGgkCo8txH/XmD4wrdbaOI7v3r9/+/bt+/fvb25u9vv94XgYj2NtNXb2xJzTYrxPZjuse9d1XdcNwzAs17P8HT+UUsJx+a0uJM7qm2+++bu/+7v/6//667/927+7u707HscmCgBd/3XOxQFEZH84qFsVgWkWNUJc63kVEZkTLA2a1aNqIyVRvb27/8lP/+F+tz9Okzr86Ic//PyzjglPDs9ve9vxzIQR0RNYHtwJ3F20TnU8tvko8wjWcDXt5rh4so7oTr5gkOvmBhBurLm2JlOdDod6PHibCQGJgdkIwT10LEzVT4nb3zIldR6142rAca2Ce2Lgn2bcn9yTs9fP//5wPLHrtv4EEKVvDzw6IkL05ai4iFuuR3k44LOr5z/4/IeXV8+220t00KbzYazzPFlzm2ttTcTBOafD4YCJ2wJPqYEZxMzh0vVdv+GUeyZXFJ1bm8AdGTnRcLHt+y1mREZ0NVdtaiZpInJrMzv4XGdVAYKc0zZom4Qm2ubaalM1DNnMOP2PuShPovaze43LjYv69TDt0trxeNjv99M0ttaYGHz1gDBcQ9cqTYWQhmEgJiYGAgYgY1Y9QwOWbdVVZW6tzWOdp2mudQ6v+XTDT7P85IA+eRi//cBzZ0/Nqshxmu8PxyYy19paq7Uex3G/P9zc3l7f3N7cXO93ezVjomEYkJiYiRd3cJlbZrUJTrNqq62mUjb7Q0qp5ERMcAIhnkZX37l6jge53U9ExMQ5EyJq9GNmzgUQVVVr9Xk0UplmOUxwrKRWEg/bcvX82Rc//KM/+5M/+rNPP/n82eVVSbnLud8Mm2HT9T0hrjlqE9W5NcPMngzICYAMKUoWNabOgs3j4t03ERUNIh1p7tiN2MAN0BzMg8+6PLarF6+p9P32IpWeOGGo1C4EF0QzAHWtIDNIRW0RfTezUdp+nnfTdD/OxzpObVYHZO4AiTPmrvQDlQ45u/M8NzA0VdEa4jonh+oB4cTlHyGBuCSDwxouLgCuYD4uxT+/84jpMc3T+/fvv/76m2+++ebu7s7dN5vNy5cvLy8vAfz27u6Xv/zll1/+8s2bN+M4iggRD8Pw6aef/tmf/fmf/PCHr1+9ZuLD4egO5iYS+pRlmqa+77uuC0N4ind/99N+chHn/4jDh4Lbmzdv/uEf//HnP//5m7dvrq+vd7vdfr8/Ho8iUnIucWa5nAJ0AFhtJw/DcHl5ud1ut9vtMAybzSb+3mw22+02/hmOS0T23wecE5FxHL/++uu/+Zu/+Zu/+Zuf/uRn0zSrhr4GEhOuiQB3J6KQSlVTJo61aO6nyWFuUZlJQIDYRKe5zrUejseUS04FEXNOlxfbvutgCVt+O02bc/sWidO4zEVt02OBNpkOx7vr6bBr09EXGoqBu1r8AVu1nB5IoCtpCR3QzMW8iTVxFQQlWpqZuoNFUVxoTJvhQoxaYe0PI9sPHgRiVNLGD08F6b6PaX9y084s0a+7myc/CM2WbPKqfIYITrFVMwc3H23F/R0Q0D/ivfddf3FxOfRDStzmNs/zOE51nMHc1VqtaurglJM5IFNVUTcFAzRn55CIZsqly6kjSKouTUSbqiIZMgE1pAYLFVHIRVVUoQFMrRGgmdU2i4oT5JJcatf3KedWZ6lVW3NT9xRP2VZ45gml9mld+ylvFJp95uHFalTjiEirrdXa5trmSgZmpk1c1c2BAA2RqHB3cXX56tNPNttN7gplRuZwJDEIdCEk5gBm0mQ6HN9++xbAOLFqoELLZhzf6yfhmkBQHc7UxZZz/+6n/5Fh5ss8Vp9r2x9GxNv9cZym6TiOkWmrdZ7n+Tgep3FSMWJOKQfOZKp1buCEgCnlmHtxp0QVgCjlKnZ7d19yHoa+LLPXV4rA9yI27+7rl1/uhqG72HaXl13fM3NO2RJRJ47zVMXGCQ4IpLgb6Wb0XcvQPb/avtp8/umnP/iTH/3wzz57/fmzZ8+GYZO7buiHYdiWrkNCM1ONKSW11blVTKSIsujHZiIgIyBRA3C3wJgcQzbZ3avUcZ6O8wiEXe0VcGp+d7+balOlskLyiPjq1WfU9UwpuDWABMjBtkEwRHObre29HVAn0OomZiomk7RDmw4yH7QeW6uiqfTdsOkvL7dXl8NF3236VHrKHWIqU23N5lphHl2XfW6N2s+lFAEA/UGKIyApW7M+6GC+IPm/B7sevoSI7Hb7r776+le/+tX79+/DHj9//vzlq5fu/ubtm3/8x3/4yU/+/s2bN/vdrokg4osXL1+/fv1nf/7n/9tf/m+Xl5c556jpL6UEoaa1VucZcVdK6bouDOFiSX9/qqi/Zqjq27dv/+Zv/ua//vV//fuf/GS/2x+Oh/1+fzgcpmkK32UYhqFb4u8YrbX9fh9KrpeXl69fvw6eQUTwp2h+s9lcXl4+e/bs6urq2bNnL168uLy8fFK5++Fwh9babrcPzYA3b749jkc3wIW8iwCwRCqreEYcM4BA4iXKjKuLYyJSSuQeqOta9Onw5ZdfxiIy1R/98E8+/eSTwBh+29t4snm45gTjxIgW70KqWKt1v99fvz/u7nSewBq4hjUWsRYVqr7QURe+yBkZOTZNVEeLwmxnwpQ4BV+WEFVDsGLZ6s3RDB5itic3+YSCPVogzI/q2k/W/WTXv49pxxV2is/g2StPbtrpZJZBS/39YhcipcIrXX8J3vFRFvbDHyLIkLnuZruz8TiOh0lnBYWCKQGBOwFQSpxySRkTU0oK5gTABslTyV03DMPFdrhKVIK9BwDuzbwaiIMhE2EjczCmZkkUW4MWHe8ZTnkRdErozjOqyZxyV5tEkdvCifCVIYR4aqBxGo9N+3K3TobzpDgXph1iHpuoiUptEaBFvQQs6mTIzCmnru+G7eby5bPN5Tb3Xco5pE3BnTwoVIDurjYex13J4zy12oBwEULToGqvXQpWR3gJq36HLTd044/jtNvtj8dxrhWaqPlcW055HMdxHNe1v4j7qygCJk7h+iGiGUgTBErMSBwVNWauaipGiTmVpna3O/Rdt90MuOlLThHzwrKEf/MWME9+dyNamSENnUPHiXNXIDvm5ja3seF+xgIOwruJd5a1v7q6+IKfve5fPn/x7OWzy2fb7UXfD33fd/3Q90PXdZzYwcMPaXWe56m1KiYOgERNXU07hAJsrqgLtXJdFEiATAQIYjrLPNbR3OY2G1BVqq054EkYNR7XMGyp60OLGJZUDAMyIIA5aHUZrR1BRtQJrLo20TaLjNIOrR61TS4VXIm7ru8vrjaXzzaXF7nPqZRc+pQ75kJY+37KhyPCTm3JoeMKPsFZhhgeOHKxPenSNTvSVqf22eDwPcLEXzsQQhzpcLy5ufn666+//fbbw+EQVu3i4oKIbm9vfvGLX/785z//+uuv7+/vpTVi7rvu+fNnP/jBH/3xD37w+eefi8jxeDwcDqoakHVOiYkCKwroPpRIunVEmBt72u92CY/GAnSphoX+6quvfvrTn/7kJz/92c9+VudaWz0cDuM41loBICQf5jJFviC2+2mabm9v53lGxOfPn0dTlmEYTu85h+s3m83z589fvXr1J3/yJ5999tk0Td91XqefWpNxPN7e3rx9++7+ftdaQ+RIA598uwjyiOi8ztbcEjzcsVNEERdtZqJy6lshIre3t+4e+nQIwEzPrq6GYfhtrfsjC7eKtMCD0UICcBGZ5/lwnA9Hb7NrAxORJq2pmi7OaSQF3MEW+sgZIA8OZI4OjMgARuhuQMTIDoRmFgk2MzOnYOB7wLyP0/+wJkcBHm9ivyFqX4rLl74IdN4x5tFNWM43vofObswHK9FXIPRUNPihaY9TiYZLKSEpwAeX9HioaZW5SWutzlOVJkwpcy5cCiZ0JERMlLrSbQZM3KLGgMCTU/ZUcilD310M3YYhRVKACQGTQ3JUBzUzU0AHiqpCTEpuqMmBwNyUPOgTS9EeuoOakwFAimuhE4X2O5GsD4rfYk6sts0WboXFGlC1haWwzHQH99A0gbid4icPycG5pO2zi2G7KX3vCObuoiYKAdq6axM9WlNxRsysZq3V1ppIw6U3Bp8IkWaGIX8CALCsgXj9+2zBgULUKuM03tzcvX1/fX19ezyMan7kMXbDWmtrjZlTYqZEiRpWBGJKuCAOi4uhrqjSmhCnxAkA3cHMmmhhzilLq/vp2JU89B0R5pQQf8vslZNLkYrTUdvGYUNdKokTioNq83SUfDuDGbRKx5qn7kX//IvnP/jTdHE5WQX0Otcg+5Su32y2pe9Db8Cj05vINE+H42Fus7txYs55nqZWJy8ZiaCqtwbWHBUSLsq/BDkzCxloM2neRLSKIGanwsRd6czQz+UTlmodx8BtYpkDojtYszZaPXo7oI5k1a2ZiqjMIkepB2mjSQP3nBJyf3m1vXo+XFyVYUMJkRggI+TEnWfuyqaUDhB9Me2nvfyU34mtYyn0XfZBNAcFsGgP44v2LT58/J8+HACatNu722+//fabb76+vr5W1YuLi1evXnVdf3t7+4tf/PLv//7vv/zyy/1+LyJItN1uXrx48cd//Mc/+tGffvrpp33fv3v37u3bt+M4ImKJkXPf933PYZ/CwM/zzMw551JKYNp93wcG/rtfxWm01qZpur+/f/fu3S9+8Ytffvnlu3fvDvtDmJow5yHtEuVnblZrPa3WcRzv7u7iFXfvui5OPhyRyCmILGJQIjIMw8uXL//yL//yxz/+8f39/W84UXdVDVpfrbOImBkhWpDFHR0B0NepvODeEb0ws7uHZsDJwC9bnYiauisusDMSkaru94df/epXphLh8o9+9KNSyjnp4fuMp1H7Wfzq7m6AgG5uAburLefUxFozaeCYiIFDIBYW636eLT/JtHik5aOY11UNQ74Zmexhr194dHBaQSvb6eGM13/h+VUAEcJZrv3MsC+mPH4Rrzxhxz+J3ZfvOCnUATwFDxz8QZou/JglH7FAvu7oYEhEiVNOKaeUkQRQTiyGdX0/WuUiOtcq0sykdHm72fTdps9Dx11yBnEwB8JUUrcdKHF1EVcjB3ZMwCkxdyWVRImcwu8A8yUHmYipmJqToyEaMiYgEmjGtmyL5gi27JGJnNmYgBOkwuZIydxra7CUbqx+zAcb1ceEZle7vv55gL5XDyEK7BzDop/9Gs3MbdkU3Ygo5VRK6bvOEdTNWI3V9ZTDMkdXsIAUbGVziAhDimzIGSCzpEf8VKC3enMf3YDPfuGOIE3mOh8Ox7v73c3N3fXN3eE4qbmKiqiZrS1J1c0QgAtHPhiRQs73LBhdHPlojRanEhnc6I4XbU/N/Hgcb27vck5932VOH07fXzOeP3v553/6z9xnwpoTg0V6381NDMSyqx+M0VmJddh2V5/nq88vX732BOP9vk37Oh1MG6dU+r70fQouRmAu8zwej4fD4Xg8OkDXdV3Xd6VTNVVjzoAwzW3e71wrJei3XeoyOfjSPNXVtGmdpbpBSakrXSqbJs5c56rTeIad+rJRIKx1j+4ERi7Qqs9Hr0eUGaWCNdem2mprY61jk1F0NmvgwAycFWAWhWmq5lFhk3hOqeu6Gtu6O6iaiIQY8/l9Xv8TWAEujwzNUYEM0Zfq+qUs7qOZuO8zHn1KVcfj8d27999+++3799fjOOacw+g2ad988/WXX/7y22/fRLu/gNOfP3/+6aeffvHFF1988UU/DOM43t7evn//PpzOMJnzPD07PrvYLtnosEMngC2MYoTy2+3WHstU/VMuaY3U68pECXzreDweDweRBgABZYdvcTqfWmsDJKKcUtiqeZ6naQoBx3mej8cjAIzjGHB9ZBOmaTrl7Pu+f/nyZSD28eZfMxAh/IOu6wMJOHn/J/0WWJoDndqZOQLGLToZo/OrVlURdbAISU9KNWbWWt3tdkRYcnJTiNj92bNhGD6YCd+52HERzXqSagbwFQ8PGbJT6BXXY+ruTIxISGnps7zsK34q6o1DnSBxdFAREzGROJw5oC1CYWHXfZWF8IWBDyszaElTr0vj6RXRY6FZfLDiix0/AePrCw/GG3GlbC0P6TxqP7spD0mLJSMQOXNfhcwj9bAYCHMKEDmXVPpUOuLm0B60S1Y21/mTYkoldYkSgpdS+m7oh01XhoSZjbyZqzk4M6WSkRGREpiiLVgkJcZExisvLDxKA1VXdSNIkHx5rgBISIDknNCdgmOMQIGSElFOxqxIRgyUAJXMT5oCp5zEklx8vF09BeTXp7fY9ki2wxk89cCix1Ph86l71/qxNRkAZpHgcTWg6AcW/bbR3VwhBOFOeYJoY6eqqoZkSERmfpaVgYVdEpSoB5rUr4FY4nemdpymu7v7m9u76+ub/WE8HucmljhH7tzNxRuAI4CaQoOcmJhxSdJQOLMLwLtgX7CWQS9uESy9bhEcErOX0kSub276Ll9cbHGg8ttk4/7kj3/4lz/+o7u7d7d3b1q7Nz0COpqbuFRsmhV4wpLzkDcX/fDy8vKPuL/CZON0d9i9K6nU7ZWr5lJK16WSkdjc1bTVejgc7u/uDofDPNfN9uLi4mK73fT9QJS60vfM0OphnG/e31ibuo5e8cuck0P0ejZVbdrmWsdpKrnbbC6uLp8Pm8upSt4dd/txGg8P8wqRlinuDICgZEBuaM3a6PMR5hGlogqqmpmozU2OtR2rTmrVXACYyAmP4zROgpSImBKF8hWnJZLlRE1aEEJMmoPjKp2zuv6IixBieGPoZIBG7IgRz6zVEohI3412fb8RRRP3u92bN99+++239/f3ZhYEMQC4u7v7+c9//qtffXU8Hohou93mnDebzatXLz/77LPPPv3s1cuXqvrm5s3bt29vbm4AIKU0zfPN7c3wzXB5cfHyxYvXr1+9fv06zAkRiUiY3sPhMM+ziKSUTk21f5vx6MJFJCL13W4HAMxsZqXrcikp5650m80gqmYWQPoqEWMq6mbMTMMQ+MEJ7kbEsP1hVHJe7HHXdfv9/u7ubrfbRa5hGIbdbnd7e/s9ThtLKRcXF69evfz008/u7nb39zvVQGEc8cwiLdDM8q810WZB7oHVT3oo4SNgirZdJ18BCclM52n68stfHnY7NwPwP/uzP4v+7t9zpYfVxZUH8ASAXEAuDOFysKDPuZkZMeWUiBiQA4XHZYNaU7AAC8mZiBOXUohZWqtzlWky0ShRcYcI2fXBuscRzIHWPfYsTF/MylPG0JMQfLHfhA8UdSRei9lPGfhHofv5fwEw6tBPN2Qx/GuuAk5ptXiei/HRVSrJwY045ZLLUErPuQOaFkW61TMAAIRHju/QDc+3LwmRGXPKuXSl71IuGDFoUtflCagIGGKmSFC6AyiiUoSghkoLxwzAXURVqwIYU0mcmXEREhAzFAMFZCQnzkyO6G5ISKmnlB0JgBzJdBaZmqiIUIBDDrhwI55GIk8BeXj870du5+JDBhmBkQiIwNzJQNfM5bIsFt9qxfeXoyEAYYCobkAGikyL2AIiICwCPu6rZ+CxM5/s+pkVj0Mvs+C7VlH4AK21cZ7v7u6vb27v7u53+8M0N1ElIk45wIOY07gya9xPNTBcSolgKJCDpXqAmBNHCocTES3kgSZNR21tWoSH2jyp3Az9ZrMhxHJx8cH9/s71//LFyz/9wct3777+9ttye/PNbm8qVU10Bm1okICx0abxlrqr1F1h7hVsPtweDu/beFeGy4RWcipdl0pBZgdQ0Wkad/e72+ub25tbM0spd313cXHR933OCYlTLgVREXM3pG4QcGBASoi82PWgQ6iKamvCXBKnUrq+65iLO4r4DRzOLsUBDE1JnSC6sTZwAa0w7XE+YqsgCmpurmpNdRabmjVHC2kcAEqMhPM01/koAu6wlNEBEqec8zAMV88uzCuAE4IhgIE/tCaKibS47Babfbj86KgQ3qktGyQ4hDv3Tzft7t5E7u937969e/Pm7fX1Ta2ViMIG393dffvtt998883d7a2qBQl8GIbtdvv69Seff/7Fixcvuq57//767ds37969C8O28MxLWarIx/Fw2O92u2DabzabUxmxqk7TFDmm3960P06vukcv85ubm91+f7HdXj17Fl6LNAGH0nUXFxex9apIE6nzPM/zOE21VhMlopCBC27aOQrYllFLKe7gbvM87Xb7u7vbcZxUJedU6zyOx91uNwx91Jp+MJbNARFzTtvt9pNPPvnjP/7B+/fv3717P42zqhGslv1swflJRvrMQkQws/CHg2S3BjOw4udB13d3aTLCOE9jq/Xi59sgDBLR1dVVxO6/0cCfxy1nu9waYsFintcwb71cRGYqOfx1FFVTxQdccfncCbWEkIBNS6UuRHdxSk5sS107LKHcgyzE+snFmHtk7c9O8emFnC7nCUuOkB7l3h9z5h+u/RQ7xgHpoc5mCSzP/nkOJC8wzFocsHScAiLmrus32+102Hb9nviwJtrO786jUVK37S/ihNeKzUzIAGAUyTs4wdmUqFDBzB6S2Y5uiEAEnDAxEDuYmYYit5gDIKFnwEKhpkM5ASZxNCdHQuTMiYP84K5I5mROYlH+OI3TVGsLx+4UV55g7PPxpPhtwTIe5tv6wxqyr0+KGVMi5kj/nI57ejcucM4JUIrXF8O4guy4cFIBCaNHp5tbMCBwKd94YtdXf2OFnk4p8I88JV9oA+M4Xd/e3tzcXN/czfNsaoTIiWmlJBDBaRlH5i/0qMAhJSbsdSGYRBEgxVTNpXR933Xl/0/bf7XZkd1cwiCAbcIdk5ZkOZWVNN/b/TzTN/P/f0FfTZvXtkpVLMf0ec4Jsw0wF9gReTJJlqTunhBVJJNpwuzYABYW1nLWAhIzpxRDmEKIOceqqtqmyTnlHO7v752z3rlV2x5JT/+No23aVxeXBlhylDSFsR+GnKYQA+ckiIacE1snqgkrYAjDIaVw2L2L04PksVqv26Zq26aqa+OcAGZOMcX9fndzc3V9dfN4/9B1q/PzVdd2Xdc574nIAhoCA4Aim9MzQzANe4TkmxoNaeo1a3UVxg4zsCCzcGJDpmvacXgWSxAEmSElTFmheBSWHDiNEg4YR0pRkkhGZsxZQsohc2BksGQrS0wgxhICZJ6GYZzGmBLr8tRHYo3t1h0R+wrJoPeWUDhL6TpyQewAAVAZIgrnUQGz5p6PlK/QT6X/k6JdF9LNzc2vv/56dXV9DLnHGH/77bef3r69u72bpskY8t7Xdd227Wazubi4ePPmzWq9zpl3u93V1fXd3d3j46P2g1er1WquHe/u7tQmbrVanc3HdrtdrVbMfDgcNGwu06T/0LHsnsx8e3v37//+H3d3dyHGTz/9dL3ZjsN4d3e3PxxyZu/9ZrNd5tOYc0ppGqfH3WN/6FNOBMUxue97nKve+TMjs0zThAjM1TjmlPJut9vtHnPOiJRzijGO49D3e+es97/3+oiIMbZpmouLyy+++OLt25+b5qcQUkxBZYiVc7188pFsxlN8Xbrvy6ZHRKXxzYAo3ldV5UOIQcksKVXexhh/e/dOPz9n/uqrL51zxtolZ5jP8eVOdfyjj5l9S8txjnpL2ERCAkM6f4s6cpw5xIgAtmgQlxK+5AjEAhJLCQnGGHCO0SAZQUowC7lq3Tv3YBFk1mv76N1+cR3Hl/M8ss9Cs89D+7PojtrHnLfypeB7djteRvenA/R9LvUei6h2Rl3XuF6FfrXbPZaEDJ7i+twCeLoMa6x3FQkRoBFDbCACZynLNuUUo6QEAoaMQ9fYxvoKiFggz4I2hoy1BnSoMKU4BmZGAQSDYgSNkDHeV1VVta2rKvXICFFY0BhLiFk4hNSPY4iZgUOM/dBP0xjTEGKAeekKvLwHTxfy/FHNhaS6ZOLs8LrcuvJ/JCIy1jorxJwSCClDpcAr2kY/+oFFsfsoui+LYH6WCAWQl2cvwfOYPZ/Gi/fkw9uWvmMhhEN/uL+/v79/POwPMSmfVNmayjlydmbuaIdSv5yZM2ZrrXOmrmtE1OpHk19rnfXWWQcIk47J9f0wDDrxL8zK7zVEZFDHZdqm2azXTV0t0R1/ly2PIIbAWVO7qqm6rl4DCwgSpIRZLBJYsl7QZGFJk8SY4pjGPXBsKr9eb07OLlbbE1c1SFZAQoj7/e7u7vbq6t1+t8+cq6rabDZFPZvoKYEDJGvr1RoN+rGRHL1Hwgw5K68T0Xhb1VXbxmStF8EY0oiDMR7er6tyAgEIo8QMIMDMHIUnTgPEEeMEOS+ts8QSM6ejdFG3KVOU03Em9yfd9jILAyaTrLMxBussoaL3BMw6aUFmXmZlwlcMCBfajeJxohW6aMtBgfkPJ4x/80AAUah5v9tryf74+Bhj1Ck11Ur75Zdf3r27GoZBRLx1qtyyXq9PtieXl5dvXr+p6zoVydMIioHnMoYKAsZa7zwCpBQVtdYVqEvUe6/LteDGz43eAeDjDayXV5xSGobx6urqL9//5eHhUb9PSnm/3717d3V3dy8i1lhC9FXlvVfe/jRNhoyA1FUZ2XTe5Zx3ux0gDMNwOBwAIGeOMeh74JxvmialPE0hxhBCEBFrraLi0zQNw7Barf/GrT8aCk9JuxMxp8g5gY6tI5ASw+caePlV7suRPdVR+JmVtuaVYYw1hhFNzpE5O2tYYBjGq+sbQBqnoNvkycm2qZsXe9gHTxtnRhHiU19UZO47Hj0fBAQi5Ujr9lrm3cp3l/kpFkCz9OlFmDOAa5rGGhOHKU4xZU5czFhkGYx6AlqfnfYx/v5+IHmqAp+X7IVD94wR/+zT9D9aoMEyn/asokOAgjbTEQqi5zBPM80nVO4aIgowAhlbVUa6vm3ruibzBGo8Fe3Pl7x1rm4IsnLcDBGRITCACCxsxFhyYDMBeoXrfUXGAiKzJMyCQhads1XlkEAkh2CCtzkzZzWuQmsMkSPjyXgyznhvnAcyLnLOoNqmyJwk8BQSR2WGxkLuO3rCx0/n90P70UUjouA8BlS+7MiYCBGtMc55ppxD0L6zgvUEOHMy+Om+H0ew5U9LXjYv6yKPw4XbshwfW0/yBBF9eKvKzGro8viw2+8PIcSYMjOTtdZ5Y8g7W1XeWae0XqUZ64Yo81yAGrY652KMIKJ+ANY7JBLOwzju9o+3t7c319f7/W4cBwLSvcx73zRN27XDOI4hbFar05MTQmybGv6OqJFSGIddmEZhrly17rbGGO+qGEIs0Q8NGiQU0f2LOUUL7Kq626xOz1+fvf50fXZhqxqIcs7DON7d311fX11fXyHgql1vtpvt6UnTNkTEIpmZEEhzZ2NsU6MlU9Wco8EsecQYAC2Ss7ZqKs4CSJYFRHCcphyTtdE4n2J8diUxCiYYe4gJEIEz55HzBHnCHCEnlDyzTSQLJ/VV0AwxJ85ZEAidNdZSYUAwlaSVVSMBkArBfdFvKGWIpimqgqZcY7WyKr47AMxHya8uQ8i8LM9/+CihZRzHh4eHq+vrm5ubYegBQIldwzBoKX93d5tSds447+uqaup61a1OTk4uLy5evbpMKd3f3SOANuARcRzHlJIy6Zy1Tdu00Ijw0lyfhzusSrnFGEVEof5/6ORhzqERMYTw8HD/62+//vDDj4dD773v++G3337b7w+arwgIGcLZR9F7DwDTNAlz5atV263W667rvHMp54eHB+0RAMAwDMw5hGitcc51XXtycjIMwziO+LQhsAbpEMI4jkfOyx+/AOEY4263U+n4/X43TUPOYgzPDmjKiSGcVw4uDLQCSgs+x4ph3oy4NKWFs6iPYQatFQAAM8uh7/fff397d68zV9rO0++CzyD3Dx/Hn1MClMDCJZ9PBYgQDIFI0hcKEBENGVSKK5X0AOf+k/YhRICINut127TDvh8Oh74f8xSfqnUu+XXRdwCYufV/11ugdMAX9PhjdvwLlB6Ph9uKDOxcRB/x68qqVG3y+f4s0bw8lKfXF/RTWUra4JxzUOsbYcgsIDY8lY7PHon1HhkgEWYisIbIOCKj90+4YhDGLJaodhUZysIikkVI2AoTgrXYNLZb1dYZQGCWzBJCClMMU4whq/QtGstoogCyEKH1BsnoIF0WgQSMKIBZOMaQUoDiPm9ZDCR8SqZ03b4XAd/za5/r4LlAf0JdZGFYzCRwYwhVHJEIsPjXIsMRO/OoM146R8/r1FKEa+McjqgcM4Lw/BzwiK93dNIfRBsRQKQk7+r0YJyvkHLK2TpX1ZWvKueLzcaSAOq6lDl/zjkTogppOe9FhBBZRFuJ+/3u4fH+4f7+9u727u42xYCIXdO61Vot8mJKY5jaEATg5vZ2s1oZIu+9NXScBH/wVckpTONeOFhDbdMSQl1XIXRayXFiZlEqoyhDIGXJhNnXdbu5uDh78+X64k21PiHns0iI4XG3u7q6un94iCluVpvT07OmbnLiaQosQMYimcU8BRDRWuW/QDbASSQzGkEiss74ykFiCYmziCEjLFOcpikA2n48Cu0iPI2IgNMAKQpSlsRpkhyQg3BSQQBhTpxiDjGFKUwxTjkGThFyhMy6SxEUAmnZb4talshi1SiFSCNZdEhXIVQu4H2Z2dR+it5/zpLysqpBp00RwcwFxQcfzd88Ukq73e729ubu7na328WYiEh3+YeHB1VtG8fJGHLW1b6q67qpm9WqOzk52W5P1uv10A/G2vVm/ebNm91ut9/t94fDOI7GWEBKKYcQnTVEuHi8KlBERPv9Xn/WYsTyd572ch/0Dyml29vb77///u3bt7e3t9M0eV+puKwOpynz3Ds/46m06L2EGPUE2rbdbjd13TCz9y7GcH9/N44DM6cU1DRqAe+0uDzerAtFPaV56uF3jg9iYIXbz2JZ2BqZ2+XPw4x+PZabsOCFS4JIZKyznAt0Mo6TvrbOeeccEoWYWAQDppRT5u+//8FXtbFGRDbrVVVV8Ltx/aneOWo2L2dSohzOBbgUGRTNXAENETpnjzqYS8xCKB8t01I613NkBPaUzKnVmMBTn+L5vYWnc3mJxpe7twT14+iuXWWcR96Wf8X5FUMq3GqgOSUp6fn8AoqAAMETY74U7ADwvIsxAzBIKIKolEheYGRYZv1LylJymeMHgQjGGHIWvEFnyRiLRMDIWTlgzJizQSLnQDiFmDghirNmvaqayjVt1XVNt2qdd2gMIDHjFOI4Tod+HPopRc4MAIRk0BkxlLHMi6ljSMg8xTxOU4hDimNKo+REKGQRyQK6mMyT/s7Rgjk+XjDkcUmIjjD8pz9yqanLPoqIanwmCpUWit0i/oFQhA+ehXp5vm5mIKi81SoRd5RFLEEWnn/VkjJQ+S4fOmQeiLLWNQ2KQMw5pui8r5vaWqvZiG4eypuz1vLcCQSRpDPVznrvBYBZUkqTamJcX/3226+3t9cPDw+Hw34YB+/dZr1erzots0KM4zge+p4F6rq5ub331jV1vVmvCb0xT6N0H8yLc44h9CBcOWupbSofU5tyzDGkHCWzMGOpM1LmyDlzBmTXrE5PX3968enX7elr166RbB6nfhju7+/fXV0Nh4OzbrPZXlxeEtndbjdMU1U3Tdc1Tfv07oAIoYBRsU0EyUBZQACVReQBQ8rWRBS21uek04UxJp7Ss8fBYUABigOkxIggiZO6XCRQs1rOzCnlENM0xWEKQ5iGOA0cJkgRmAEJGWZpJx1I5zkBnZfsMq3JrPNvKSlpCyVF5syZYk4hBjRknSNjACiGFEPS9x4JiNBYNBbJFPj/g+vq9w/tst/f319dX6uAuQhb66y1+vG7u7thGJUW7pybddObVbc62W7Xq1VTNznlyvuL84vNent3f397e1s9POz3+5QZAMZpEpDKWdVg1Vb9ZrO5vLysqkr14Lbb7aID87G3A573LI8IJagqKSrG/uMPP+73+5RyTplmehERxRhzTspYWUZpmFln3621ufKa07RtjYiIst+vu65r2yaEaRhUEpFzziFELdljjEU/Y257H+F/f/vmI6Ixtqqqruu6rq3r6nDYxxTKxqVAOc764s+C+1zZyFy7Hv2RiJx1YkRx/r4PxhjnbFVV1toQpilMUwAl8YSYfvrlF0EwxojAl3/4YhH5/8BTWAof0GAsSxSdLwhxllJDtdJUzu+cghMC0iyTW1ydSt+zpLSoNTUJ8zAMSfW0p5DUxF4vusy1l6pqHn8qOcL7weMoI3r2kVKOH4vQzeH+ZVyfPwMRAUkIZwxl5mPh0noX4Pkijn/ee39cQrtSFAAga5oZYopRmGEx/Zwr3Rf5YhZOgMY5a1pH3hpjCBAlKyueOacMnEQYWSTF/dAzR2dNW7dnZ6vzk9V203Wrtuka5yvjHKBlwSnEYZp2u8Nuf+gPYRxiYmRAMSiEDMApckw55DGmKaQxxnEK49CHMEqKIGyQjLXGO0A7RVOkQUpChO9HkJemrnPaLk9l+1GGJLLYu8xBV3Pg8v8Z1Zq7NfjxnGJ+EDORAWDGBWbl5KMf/96jfLnIPgYZiUjOLADGWoeGyNicXYpmlrMu5g+5DL08aUyyMiFZ67yUM0/TOE19P+z2+4fHh9vb6/u7m7v7u/3+sT/00zTFFHNKiOhdVfmayOacEzMiOeubpsssdw+PN/f32+3mZLPtdPgVlxzl/fSFhRMAkAFEZf0ZZsfeMxe5QdSqVRJLypyFDWLbrs/PXn++PXtV1S2RQeAwDY93d48PD2M/WnLb7Wa7PfN1e3//cHV9Y53rVuvXb97UbQcIasSpkttk0IElAo4pAaccU0woYtBaS1WFLZCgOGdSCL1IDGmappABwMN8YTlMCMI5IidAAM4iCSSLEuJz5pyyDm3FKUzjNA5hHPI0cQyQkjAzUE6JXXEIXe7Q0ULS9cKgA29qLcus+48I6HNOKaaUUAwgkQAAp5RCjNrARoICaqKBWaT2Hz0Uit/tdre3t7c3t7v9PoRJV/Q0TYfD4eHhYb/fM7MxxlmrDfi6qlVmrm3bqqqMtXVdb7Zb3cZ9XXvvV+t1f+gPh8MwDimlGEKOkwbapmmUku29F5H9fl/XtfLyPuj9ukRfjaY6aK7UUU1wF47927dv//rXv97c3Cj/VEQ6AFWEZWYVjlUQeHl3xnHUuTst0qw1RJhSCjHc3d3e3N48Pj70fZ9SnFN5FuHd7lEr7JQSIlhrcp5r1SeBs98HUeZeobVnZ2dffPHFL7/88u7du1wOZs4ZCCADRI1Exyjxi/fvKLSXvx5hCeUe5idVC9RkKAOQMSIyDMPVu6t/szalaAgIYbPZKJfwRYZSEEvFzLUUKiP38z+W0DrHQAAdLFeEWGeyVN5zvgcyw9pLhAdQSeecOCUiw5lz4sw60TtPaOm5cUG/58QAXwTR39mHcYY6lns7hwYsZLrn9xxnEB/IFOW1OZDMX1eUWZAZmfFJYe9ZtY6EWpsfocSgvh2cUhynOI5pmoSz9ixo6TXDy313CqEfmGuLlWfALEygEr4QhSc10YnBCFfWSA79OIhkJG8Mdm212XQn21XbNr7yVpvoSAzkvfGV8Y7axg2rOE45ZUgCSSSLxJxCjGNOQcIQ+34chjCFMKY0ZYlAEUQIUMRytDFGzhMZDyV/mXPT5xfyHJCfS9W5Un+iKuguOW+sKPy00LUxQvqtl/dhXr1zQozL0n1aCrDAT4hPXI+jz5ASYmTu/B0vo6fv//HcQUBKXkrGIBjriDOa0qddivXMLKU5swBdBc/RhGMKMeXx5ub26vr63dX17d3N48PNOB44K1cnZWZESikf9j2hEUDvPZEOZdVdt9puT1KKh3G8uXtYdbfOuqaqyCwTJe8tsZKBSpEPKG+FBSGwRsSW5LqUGgUrEnRkV+3m1cn5m9X6zBunCjdjv7+7ud49PObEq8364vzNenMG5G4edv/x1x+MsScnJ1XbnZ5fAJDOcQCCNWDIABkmCRmEcwxTDJMjqxp8lXVQVUTgHcZpMoDTFHLepSRg/bKoOE0MIpxUZBGEQTIUDIizztIlnYGawjSFcYjTmGKQlCBnSTkL6rydLFRNWHYxnIM6K5KkdYKutGUHUfyG58SRVVZBsMw+ZBYRYgBBJmEq3au/q048Xm4AzNz3vRok3t3d9odDitFYy8w6rv3w8DCOIyJY65RrXVW+qqoltCsZrW4aMhaQWISMtdadpDiN493d3f393W636w+HcZo0m0wpaY2uMbvvexXG6bru/WJRWTk6KX5zc3N/f39/f6/6MMok1XRhwR6ur6/3h0OKkUWVflAn2TQ7McbknETYGgMAh4PaR40ppaqq1HYWAPr+cP9w/9NPP719+/a3d78+Pu6KrKkwJ44h6Fktw3vOOWNYRLShoLDERybfnr81iM65i4uLnPPt7a1K/YQQ+r4PIWVmkQLS0GwgWwLSXIfA0uKF0vDGGYpYNiKVrss5pRTJIIBS8/JSAqWUHne74X8NfX9QZX8lPby/VencFEEhfMzrqFSUugTnwEimbAcLoz2XMWFYot5Skz3vKsyxfpzBegBCY5GsmKUvWnAvmAdDn8LGezf5A3f+Wd1+FOOX4P68sl9eVSQCY4QsGKvV/fKJREjqcpkT5CQ5ohztlkQoDKzSZk/A8NJeQeAUYhiHMAxpmiRlA2IQDCFyqdbN85g4jOPD48hsBI3DYMAYFmRghAwypjilmMNkgBvnhNMwDQbFV4QEvnJ1XdV15Zwrl1HUUMSQVI4s1W3t00ZSlsiQsoQkIeVhmg7jkCH1SeI4jbwbwn4KPUASjEgZdH/PyIHCJDGBw1kuu5TuLx/K+732pd/2BNMtq3xeNCBSpEvmb7bMO2KJ0EozLnNERTKivBdHqRXKkt0V2LDIJ5RV9nQCx7H8+ITnjf5jVTuwcIhx6PsQEwDoe654g/b1AVGtX6xzy4ITkaw/lwhYUor9MNze3b67+u23367uH+6GfpfSJJL14nRgwFnrnNfd2fvKOd807Xq9Wa3W3nkylBINw/ju+qZrmq5pqtpb+3u71fwOqsodISoibea3v1w7AQOwAKCpTL3tNqdNt66qyhjinKapP+wfHx7uY4ht027WJ+v11jofU55imkJiDoJ4fXOz2mxWbVt5Zw1Zq1qwgAQCklMIYYxhTCk4VzgWlgjQIbEFRidN27n9gVGdso6uQhKCILAyl0WYFuGNnHPmlFNOOarIcAwpRc4ZckYWYgGFZ5lBb8Fs5YTabCfd1ATn3YiMcc5VVZU5L/WB8p+sWMcM2tsDFAFEY4xjnkcuCcgImZcp8O8eT+FfRJTDpQ6nu91uGIeYEiCmlIdhuLu7OxwOqv5bVVXTFmF/rbDVEKVpGgA0RL4iQEosYIhBkNBX/uRkW9f+9GTbH/q5kR+NMWqyojxQa23XdfoRXczHZ/jjjz/e399fXV3d3t4uku9KQe/7vu97lYnV+KQfzFnFtyWlPI7jfr/XgJ1zZs7ee2vMNI2Hw0Hn9MZxNMZUlffeM+f9Ybfb7e7u7h4e7sdxABDnDDirkSullGI6dnNXioCWE03TnJ6efvLJJ19++SWR+Tsx+bZtVXn+5uZGAYmbm5vdbh9DPk7lnxWRRFDaiB8oFmQ2kgEAHfPTFn7KWcbJWBVHr/RWxxgzc0opRrq7vfv++++9s5ofrJ4pWzx9c14w+Seu+9HyOib8PWFVitDPFKp5gzymIS2ZL8yt0fmTtSTiwo0qNdwMms7V7Mdegw+kvHPV+KzoWsI8fvgoZ40EqHo2BmcHWChJvJLrBAo4/7xZAUBAjIxUlGiKHJUAqLgFQEpxHMYwTTlGh9BZRw4qzFlH+AFq544vM4Tp0B+srbyv0AqgySlzTJlz4hRyDDnmFAE4JkKUTNEaHBF7GfrUT6lNuXKZCOaRWiwj2lY1GckwIANlwSyQGGLmmNIYwsmw3h02j7v1/UN3dfPrw0Ps+yGkESAjChpkRBbKBpmg6NQo5141/59jjC9NXZ9aHfK0zp49yBLAyzqYuxvqxlbQYe1v6mBREZWVXEjJQAAEWQAQND1E0t2aDAEVQTrVrjHzKNyLzPH4r++JEb5cglp8PDw87PeHGKZpmsZpmkXvAQCcr6qmXa3W3eoJKSLEhaMhIDGlYRz3+8eHh/vHx/vDfpdSYE7MmRCNcd5XTdPqgHhdV75SfbRq1a03m23btohU+dp7H2K4ubndrtebzRoNGWt+P4ggAOIsBDhnxoBQus7aaAPWTcm4xncnzWrj68ZaZxBSisPhsHt83O12wrJebzebbV23GWCYxpzZWJfCNIzT9c2tr+rzs7PTk23XNoRW76COzcZpnMY+TBOnKNYjAgIZIjAogsJMaKq6cd4LAgM/D+0Zy9rgzAk0XWYGJVaU6J6Lr2BMOWU1HAJVjiwLWJTP6L2PMYkIIAPO2lAixs4iEOi0l8qcl03kSQgJYdaXAGaZafWFkQfAAonnpfnRhfVymZXftbZ7eHhQkZn94TBNIaWEiDGmu7u7u7u7cRxF2DlfV3Xbtm1bQnvXdWpx1jQNKKUBiRGZU4ipH0cQtobW69X5+SkAjMPw80/N1dXV4XDQr22aRpFzdVVZr9d1Xb/faP+3f/s3Efnll1/u7+8RUfXjBEDH55Qut7w7RfXZWOs8AHLmvu/v7u7UcyHlBCJKFDgc9lri73Y7772K6XrvpjDtD+H6+urh4UEnBeq6MjqFgQSAOttmja28N9ZqQbwMp6xW68vLyy+//OqPf/zju3dXj4+7331XAAq7za3X608//VRzl2EYASBn2ec+xqBhDGb0XjMJOu71fqgwXcoMtaONMQKA5g0VOM1jEFHpApCSNaaqqnGcfnz7FkAWkfyPfVt4OaCoVftSDRMi6aLHQnNFQEJSO5inCqeAp7jcEVQQDl4Q5GYQXs1hYQ7uUnyclvofn5+RvPjD0/f73eP9f4ajb42AUFAJWmYN9ZOUKYtLhfr+U0ckWBa5ilGBAAoRAqYUh3GYppFTrBA33taA0eTEkkVExHt3/F1VRKGphxgbZ0hQEo8xTilNKYXEKUnKnBg4MJBB441Y02PeZfcwtuvBt40zCGiZhEmsDh+iNeisdc44j8YAGUYSIAYSRC16Qo7jNO6H/e3tux9+ND/9kn9716dDTjlqESzGMCIzSAIxZXMEPI7uT8fLdfb0HOYFvjxILKYaJYsCtSugsi0Wc18sTRIyxnrHwmPfW1sIY8xsyBAaFlAorijDIFhnbXaK9M8o1MvF8KGH+oHF92Ih5px3u8e3P/54fXMzjX3KaYEDdPC3atr1+uTNp582baMDr3Q04a2XhoTWmrqpm7Y2lpDAGLLGG0OVBvVutVpvurZr29Z5a20RJLDGaf0RQqibpqpqYY4pPex2Vzc3xpD3TrtJ+D5j6ymOAxKBEBpLVHQAZ+qEbkhCgMYYWzVVt62aFTkvRIIwxfD4+Hg49MxS1c3J6WndtCGl3aG/e3hImU/PTlNKKuzz9u3bFBMiWmMrX4PyaJFzStMwjEMfY4CcUopoLCDFIENOAuIQnbPOeWOtAu5HF6EGR6W6YBHJSe0pQFNhbbdzTimHGENIIarQtTALJ+GsuDs556q622xOpimEEASSqDmRCAD4yq03K+9tzomlEm7njsVxI1Gxe+GZzSGi5btmpqxlJEPOwgD4/kb8sQMRmEWH0JQot9/vwzSlFFNMzDyOk4q/Kshc13XTNk3dVFWtgVDVZlRBIcSImIVoivkwjHcPDw+Pj3Xlq1W32W62mzWIqEVh0zTMXFXVarXKOauFzNnZ2cXFxQfjuoj8y7/8iwq5A8B6vVYdjxCjGgqkWX+NhTPnmFKMwTADoSHjvDWGAKRtm81mczjsD4dD3x/GYbi5uVHmf4yhaeqq8sZQjOFw2A9Dv9vvpmlCwKqqdMZkHnUmpSZZa6tZDF+flPe+adrz8/NPPvnkn/7pn/74xz/2/fi7of3oaSBox/3LL7/URgMzh5BylpQ4xrTIzCkgX2B5pDKC9eJ7wRIkUaBkPCLFV0yT1pSy4g1aHqhXpkoxDH3/7t27yjsAWQT//95VBQUdFyQg1TfDGWDSzrto+33ZDeFFf2+5HCxGbjLXyrpdF96d8nGPeItATELa/0c86orOoO6zM53v1XsHfaxmXz7/eAM/ygKWRsLyEj/lWyJPp7ScgFnqTAAEFf2HmNIwjWOYYgqWcldBRSp9CZmBAVwFx89DZiWlGMdgka0NMkSaxGeomBAdWiNUPO0JwGAECXm6GR/9HertzOt00qwIwBZ/AIAMgCgYBUEyCaI+TWMtogFEIXTG1YYaZxuDBqR2xht8d2Xu7u+GaciS1BM+J8tin+52ufsvw8d7fu3zw34/nD49WtSinoUZgOZNc5ZoRkRUVxgHIuMwOGsdaWsqG2uNsSlzEXNNOXFGbUrnnFJ8gcCX1XHk1HT8dJcH/DGUTn/o4+Pux7c//vrrz8PQI4JzDgBFeJqmEGLTrk5Ph9V6fXl5ucT1IqbAKlgPhqiq/Gaz3vebu7vbaepzNs6Ypq5Xq/V6s9mst+vNtm3aqqoUKlbDlRSz1m3jOPqqssZa61l4dzi8u75pu7Zbdd4ao73hD7wtiMXtbnYOsg6LwKpyxREAScCoQGzd1c3aVS0aq3480zQ9PO6GYSAy3Wp1cnqGZId+vLm9e3d97avq7OwMEWNMv/32283NDQh6X7V12zadKVNmnEIYhn7sDykGlBxTVL7ZGOPDYQ+IXdMSka0cEOZZD+DpQlgKl4ILc05SkpQlZyj0eJWOTyHGKcYp5BA5ZimWCrlIADrn1puTuuk4c84pc2ROSUvxYgRhECXGACBER6qbx2Qoje4oMGselqodQLlJrG+9sADYv3ciXDQ/UKF17V5rRMkppxQ5ivLV1Kfce69W5nVdV1VV1bV6wW02G+2XhxCESJB2/XD3sLu5u3vc7YzZOu+32+3F+WlOqa4rEDjZnug4xn6/v729Hcex67rz8/Pz83MtIt9/I77//vthGFT5Thv8McackpLpENE6S0SYKTMrFAGQcjbO2qryzltjab1eXVycA4gSCMZhuL29vb+/n6aRiLx3VeUBZBj6h4d7taMFrXfruqlrwnkmquiLo3Pee7+0AZFos9mcnp598sknn332+Xfffff555//27/9+9/3OLRHRpvNhohUXHIYhsP+UAYimEMoNbcC8qocR+Zp4rHcOjlSatE5S8GcWU1pEcE5a5hUgM+YgvkpEQFADBEiphQf7u9TDCKy3Z60bfsyLh6FOjnqey5rS32wEQ0gsSxtTt0b5oofZis0eIqVMvPpnphQy7/M8VNmsF6eBEnmYRNihdqfFeuIH0Bzj67ivcmDZ78f/9MS2Y86RkugelnWz0mALDfqOLqX5gQAAhYyLSIiJs4hxZBClmQtWwS2wAxJQ7ugrZ5hAaqvkXMY4wAOLJpJhmii9WSdas7i/FA4C6fMIU5TCmEIKY45RRCBlC2jEbBARCQooEYqOXOMDMICaAyVOt4BEiJZMAbIOe9XW4/UWGtEMEm/6/fTfohjYgF0AJVaYyw3EQpO/uwV+HBRonFNAJHx+IOoqAk9pVpze4ZLEJpzCEtUKUfIOzeDbIhorCVjStcYxDprrLHWcM4xBP2GxxS8p/X0AQho3gVeLNrnn6FzscwZEIwzRGhs6euTJeudtU4b/E+rBJUaiILIpXIVY6hpqpPt5tXry6p2nNg5t+5WXbdq266uG+8r9a1KKU7TCIDWOmNokRUbhkGjc103KafH/f7u/qGt6+161dT1Bx8DEWqURCJCKyicIycRAGMsoREBBEJyaIyxtfWt8bVxvqgfpDgM/X63Tyl3XbfZbFfr9RTSGB8fd7vbu9vNdrverOu6qSq+ubExxsfd49X1tbMeBNerrqkcc4xhnMZ+HPucAoGEFBgAcjwMw93tHZKhEzGEQtz3+8fdfc5UVydP1zE374qIK0uegzZwLh33lFLKKXFMPKU8xRRT1on3zMJESroy1mj/GLS8VmMfENWZUlBfw7dzluiIt7nMusACXS29pPld1d4CZMGcRQDkaEDxY4csizPlpCW7cuD7vp8UXogxpayacQrJKn29qirnXdM0m/X69PT05ORECe2FqS4QWe7vH65v7w6HgwB0XXt6etJ1rXPOGmUgmZzYGHM4HB4fH+7ubgFAwfnVavUxyKHrOt18QwgPDw8xRvWBPT09dd7fP9yPw6BSECJirG2IyBhnbd3UigQIy6E/0C3d3FxfX1/3/WEYBoXxlaVfVZUA7/e7EKahHxQKooU0NbNrDNnSXrfGO/9k625tXVWffvbZF1/84fXr15eXr87PzxVg+NhT+OBflXPw+vXrGOPh0E9TEKGs3UDolUEbwoSIOuHUUGMsLXNk5fHOq3j+jwDIPEeAznlrjQ5XqTatNji884DAwiEEQwjCj4/53bt3P/zwQ9u2x7nvsss9D1QvLgwBSYgEUEEOkoSzt6Esv4515GaQfymRjr+ltvgACTAzGTAWLbicmPPsyVnA0+Wc3k8Tf+c4jt4f78HPheLzsh0AeDHim9OFJyRiSbmODik7S5nZozmMIKF1vmrqqm1zGiUbyImZmbPh4j9q/DMBMeXxTWHKB46YPLpoUqY8WSAiC4YYVbgSlYgd0zSOQ99DSj3geBjCYewf9sNZf7HennRr55y2m9VjHREycwYmq5wgb51DY4gsoJ2907LNobN0vuoeu/YXpDxMu4f7kJhs7dzKewdGURgqv5Dg+QN6jyH/VBkjIeX3sKlSRc8PSmYZo8JqLPdfDBnvq6ZuqqaqZtMnEUFjyJAp8RIQEbI458bDgIBzOiowD78/NaIAeDZlgvIaqOgjA9DvVO2cswiTIecdWUQCUgunggQAM1oVKC/5IDxdpUJnwoBIRJWvNut1zmm97jixc37drZum9d4DUM5CJUlPfT/klAmpbbuqqkQgDuM4DACw3qzrph6GQz+O9/cPjfeVc3VVA77cnxZgCgB0aaScc4oxRWbx3htjlQiGBsFVZLxxtbEVGgdock4hhGEY+0MvLOvtZrXeVHU9xUOIsR+H/aF3VRVTagidKcTOKYTbu3tCKywIr71ZSQ5hGsfhMI095GAQIkDmLICH/X73cGeMa5xHkjHi3f3N3d0Nmfrs5PgxlE4fzLsPswjn4hDIOeesc1eJOQlkwZAlxKz7TGYAq1atWUSMQeecMaQdeBbWtj9LHoYhS1JXCatJ5IutTptwujloIXEE4jEKowhmRi5jQR+lZL/cWbS/sz/slUd2OByGcZymKcYUQwwxTtOUOSNiVfkltOv49dnZ2enpqdbQR98tjyE+Pj7e3d6mFOvKrdfrk5OTqq6IEMgaY+uqVSnlh4cHJe6t1+vVarVareYECJ5v64CIn376aYxxv98vDq3aLAdE69zD48M4w/XKF3NVtbi1KnofU7y7u9MpgJvr677vNT+ofKVIhHM2xrjfPer3mdVGn+mP6ge0z10koZzqQvmmabbb7bfffvvnP/+/Li4u1uuNNqo/FF2O6j15+RFEdM6dnZ0R0TCMMcYY8jQF5VQOw6BStACFpOW9c+CtMVhyx2XzKXjzscaHCAOQtaaua53KCzHknJx1xbVdZApTiKGuvAiGEB4fHn/+6ae26z5W735ooSmehGoEyiBK0ANOUM6hTGmzPDHqygmX+P2staqBFBdZHiQmg5YJaB4h0SElWX78x1qhvxPs/2YecBzaZQ7/yzUvNkKgLltYWFwfePxHAUL/lQD4qLiv6qpbb3IciYSzEqQ4s+QyFgPkKjxqkaip6hSnIY3J5trVbJGdJMjMYNgQg2RGZgMIiVOI0zAO/ZDCtMtp2B/G3WHYHcZd/7g5vVhtm7p23ntrXcFmOUtmFPWRd94574x1ZCwaC0RIxWSO4rRytKl9bRBi6O93Q0jWxaYxtmvFC7B62Glof3lvPpAFyzMV5eK/K0vveQZ2ZM4ESuGuCrPIwIwsRi13Vquqa1XxTe+8vtwlI9S+vEXIYIigeA6VX7KssWer4cWSKm3Uj1XtunpEJMU0jlMIo4AQoTHWOatKkAAERojQ6tzskv3OGQYRGWuMEHNqciNb6dqVAlqGjLXOGJdSWqBIAPC+EoBhGImsMRYRVZcqxpBSEhZrDIH0fX9ze9u1bdM0yqF9cb1EpCmswpaQWHJCzgbBIjhDCGoMz7MFCGpzCwRz4mkYwxQAoPL1arVCovuHx92+DzH5qt6enFhrD/uDiNRVtdls67ruh3Gawt3dXQqxqXxTGUl9P+zGcT9NPQkzIYBgTlmEU/CWCIHTeHf9eH+4/+tPP75798tqdfZyTWlcLzJYUoBxUWOLlHKYUoic2ZBrm8473h3i4z7nmBMzADLmJDGmSW1CvFNn46flkDFxGsMUYhRhY6whZ8nIku4f4X6Cyw6H83+1alfTTDW7EQH40CD1h2hEWCbF9/v93f3dbr/TKjaEpJP0KmkSw4REiLWxxlhTN9V2u718dfnZZ59dXFxUVaUz8QBQeS8QpxDSNIbhUNf1drVufEWI+mpozUtIIvFwONze3qrsa9t2miJ8cJxdb9Z/+S//pa7rw+GgcLSG0mmafv3tt9/e/aaoAwAQUUrJOZdzXgRq9PSUmjqNo5LUREDn09q28b5CxMPhME3jFCZmdsbi8wb2spHLcag8kqbx3quc/na7bdvOe4/aVP7dgHEcvI6vV40SvvjiC2aJMWuCmFIEkHEcU8opxWlUo3dHZLxzs7t82f4XKpvMvdicy1krUASFloEirIvBOWuMUbWYpq4MkRrs8hHT/oNP52ihlRUmAECkwiQoLDlyDpwyKxt0tigVYTVswzlnLZXWDKHru1J2YJwr4Jm/bQyq1qOWzfN9xKd6+bg38ZFjQbCevR0fzg70mz4rygFEODNIzgkE0NkyYP+UtT3DnY8K0VI6HAUm3Q5N3a5OQZqmCeNlETcomqeSRbdWQ0cDokySiVPKkjkNUzSAaFkg5Bg4CwNkwcwWoDbWAGJiy1iBIWOZREgGma4OdzmG+/vbX13buapxvqvqpvIac2xlyRk0QOryQ2StMdaStWCopF0EGZhT9BK3tT9pm2tnpynlmKKJuUq87KUlr2N4Xm+8NHUVeJEHLRVsAfcLAFnE40RJJcBcJH6AgBl1lEgDmnOAJmlyiaDaqMp4LNs9EcccpxhD4JyPwurTe/+E4Myw1fxQn878Y4fW9zGl/jAcDrucE85Ea7Xhcs4743WqigiXoK73iogI0DoHoBr3YMiICJFTdQ49zZxzjAERAcRa09RNCGGagjGjEmeUTpxSTDGk5K0xYCiE8PD4eDgcpnFjimXTs5VfKhwUxCfRRUNIhM4Ybw2RFcExcE6JnzQBEARyyuMwpZCscU3TdKtVTHJze30YpynEqq4vLy915EnrtlevLj/99JOr6+tff3v3+LAbh+H15fnptsth1/eP03iIYSAAJhJhRGQWkNzVDgAljXe3V9+//cvbd7/eXt8Q+ucXUqocnSlgnvdFYJacJIUcpxhCThnANlVnu4RmDDlGyNMkgMTIGXLKIUzDeAiJSBV8SP2qgUFijmMYOWejmnLkrLG6LQPoPAGWHaDE9DLcB3OPbsbqeWECPrXrj1+TuRla3gQouGvf94+Pj/cPD4fDYdRQHmPOKWYd2Q8hBGMNIBhD1pqmac5OT16/evXmk09WXYeIOrpWeV83jWM2iARihFd1dbbd1N5D2ZZ0DRACpZRmXvoeAHSC7mh++uWeioj/9E//9Pr160VVBgCY+edffvnt3W+Pj483Nze73U4Fa0VEy3FzNJKkL+Dj46Oa0SFgfXQgoo7/9UNfRHC1TXx0JsfvtmalMCfuyldv2/bk9HS9WTdNY+3LlPe9xyFLRFnGypeL1aOq6tevX1lrwxRiiOM4juMwf+2YUoox4KCZum2bRmcxQCRjie2ABcMTkJwRoEzophQRwZC11lnrAFgHArUNr83IpiqhvW1bdaP4ncs5flRFOEu3TpqDsiTgJCCCBGRBBXE4A2fILFmKexeZBedQERIA0fRFQ9K8ewqLkDHWmYKM6POB5xMi74fnjxKcnj+Xj8b1+enMmd4cUlgzJgAQISzCM/MpvfczlzPUmK91mWqzsAAiVXXrfbVeb3XmMXOZeS6iCiIikOQpDmbkaHLGDCI5pHxAgyKZEqcpxxSz5EzCFZL13pA1gkbJYgQZAUkS8UM49IfDDVMnbm382labul3Vraucq2zdNVVXAzICk4hFcMY6Z8hZsDrwwGQJCDMChnFTuZO2batqfwhjKlosMuvKgHD59TuhfXlgmh9qEfj0CACWBcHHsoTMwMw6UozAOecYH+8ff/3pl8MwVG1bEgIouQOWWaNChQeBME3XV+/6w76ufNvUBSGF8tiXh/dUo82sj6cH/NEFVtgVOfMwjPd392pNoTCgQqOb7UlTtzhLK8w4lPo7FcZrmT7XwakszGytAwFt1+lZKVeZmZnJe2dtIeKO49g0TV1X0yg6Gj6NxrSd954ArSXmHOPE7F+oiyDohD0v3SVjnScDIIRoXUXWIRJnyRJAGFFIfZ6YGSSHFMYAAqtu1Xarumr2/f0vv/12GEZAs9lsLk9OdrvH25tbLTE3m/V2u7XO1nUdpkBIxpJIHqdDf3gIoc85CiCIAfUCIfLO1t7lFMdpiONu6h/S1BPkZ4xTgJQTCovK+qWQc9KJN2FOWrOnPMU8TOEwBVPX3vm26xAMwn0MHJPS1cvOa53RLqG11jlPZAUgccrAxjoEIkEy1hhnjAVdwwRHuN/8+1yylAc7o/QMRZJUPhLa5+sSAGCWEMM4Djrwdn19tXt8LBLrs7ib7vUquQcIIkyE3rvVqjs9O92ebNumUbaXTscpRI+IRHh6snXG6FBcXauWGSCgGtWr8szV1dX19fUwDBoInXNHHOwP7L9KoFt84fTn3t7cfP/9X3/44Yf7u/spTACgEV23DwWulSigr4SmBfoedW3Xta3W9+p/OE0DMxtTUPR5j38WfZmFSBBZ+9YqgNN13SeffPKHP/zhyy+/fPXqVV3Xf3NIQUR0Ln9RwVv8WPVuKF3RWntycvLll1+mlBWcRyQFj6ZJUsoq9WOMdd4jUdd1Rhk5x6EdERHYkLOUEsUUOKfAXFWoojrG4OFwSDkaosq7qqq8c26+DycnJ59//rm19vr6+jj/WP4gL+Il4twUR8Ay9W0NUuWJrGtav9pQVaE1zDGHcTj002G0xlVVpXoJMMsjhmmKKRLRZrPtus54B4Q5phCmcRxTzkjGlVkmmfFYOa7Uj2P0grX8zkOZf3vqiB19g+f4u/5IzjKLvhoCMjrNisU3ao7uslCn32tqFLz1CMYVQESjnjnG6By4IDPnjDNIxCI5Pp1lghhgQoMGEIQlsAyMTM5YAQwQGMQgOIOWwBI4QAAyQpEpCjJw5sQsWYQzsWRnTGcpgQxhfNg/hhhMZV3tfWXryjXOtd41vhLnwCYhEMigZwmcOPcxYEwOwLBI5hiZbJqLijLIr7oAv9trn/sTSx2jT0FDu4g8fbXKLmZVyWFgVl94RuCU0xQe7+7ph7d3t/e+qgAL70BEir0XlFlkpeDFGPvDHpDPzk6PfiS8AKie/oI62QBSMLoPdBqevgrUycYgYoxJmbGEKRrt7krXrXUVHf0QLDy6uR8x06mQs0xjFBCa6R5qo+mcq+taJT6kTMVY1bUYhsF7b63N1qSIMcZhGK2vfdU4T7UziMQfctRe8JLln8hYsiqsQWQckBUA5sxFkxHnSQLmDCnGOAUEXHXrpuuss9MUbm/v9v1gfbXarNebDQvvdoXw1ff9MI4i4mu/lrU1pm48QJ7Gvu8fUxyFow47AjBYY5C8Nd7ZOHEYIuQReDKQHMHzWX1JOQMnySnnlFPkpOKyzBrac46ZQ8rDGA/94ASxqryvvKvjlPvDlPqRdXMlY61x1jJkJHTe1VVNaFlA4kTMxjACIhORM8ZZ4/Q+6oSgkD7a4m+gffZiebl034vago76AmZ6PzgilhIi5xxieHx4UD89DbGHvp+mkDSNSZk55awDek8STOoluF6tT05PtcjWdXJ/f//u3bvNZqOoEgBsVquTzUZ15XRTm9U3SVj0S/Tn9n2v+NDHoPjl0K65c07XlS7a29vbX3/55erqahiGlJOuOpWt1fR0GAZjjI6zaw6qq7ryvu26pqqZeRjGh4fHw2FvLCkiTURaobNw2UOQuAgA4wxKkd6QumkuLi6+/PLLr7/++vPPP1+tN1VVfSy7WnKOaZpUWe/x8XEhEOilee91xF+pDFVVvX7zCgB0ClHV4Gc8qRjjEh2stdYY7xxVFZEKE0J5FQuL2Iq4EAknCWFKKXjnDGFTVyrREwLWlW/qerVqvfcIZI2t6/ry8vKLL74gov/23/7bCybdRx/ZXE3pXqTgLaLzVdOdnK3PX1WrjrzLaZqG/cPt/c48eudX3Xq9XnddBwAxpd1ut9/txnEkovPz89Pz86ppkHCcxv5w2D0+juOQspQsSlv48rxE/htI/Acu5Cj2yoeq/qemTInskMuEPmkKb4wOuSxJBsgStJ/VdaXoR017lRS71H7aUy2fhKwSo0iCApoMvDgtRs6UtF1LiVAAJkERX1kyxiCwQUPsDDpjLKFVy2kmAoQMqQAPwIhsJAtQ7apN59Bh5MPDw83tTeCEFrtVt153m7bZNM26aRtfoTFFvABy5phyCDkEzsCsQ+zqdmZymd95YnY+LZOn46VkTXkwBFr7LRZsSy07594izJKyBnlkVhgEEVLOKabD4z4DuGpnvMfj5kdhLcFct+v345ST85bVS3NeDi9AIWYuZyiINHeP5q7pR5caYdM0F5eX4xRWq5XqhxRpYwAy5vT09PzivG5qvUYismb5hk+zMABgjHOOnXMsknIGxK7rxmkc+oGZdTfUjXWxzVbEW3dS62y7Wg9T2A1jpgMDbderZrWqu5WrG2M+UJ2odo42QwAYEAXL+mUhFNLBL++dtd45JQswa6soJwExxlZNTcYOUwgpkbFoTGaZxulwOIhI13UIOIUwxfTu6hoJjTWvXl+uu27dNTmHaTyM/SGFiXMiMEIgVLorGhkNYeVM6+2qtn1FIYI3z+JhTFFykpy4/FLQRxF5yBlSkphkijyMacx9ZFmvt23btV23OYlZoB8HVabR6gpIDBprra8qBJNShohcdiQyaA05Y7wxVtt5ZfifnnYeLPy5o6q95MCz9DSIgOBLHYinQ0T2+/3Nzc0PP/7w9u2PqoseU1J9Q21OspSh/UXGWCljauWyPdlu1uuqqgFA8XzVlRORxXx9s9mcnJyoB4mG7aUoTynd3d39+uuvt7e3Dw8Pj4+POjj3+3H9xdsB83bsnNtsN6cnJ9M4zgIvWSt1LbVxzmWXMTalvHnnDVGM8XA4aOs95+ycsUaNMEXgSTpI32OYAQ8N7Urp/+yzz7786quvv/rqyy+/PL+4WK/XzrvfCSkiEmO8v7//+eef3759+9NPP81Kf3HmnYDe6ouLizdv3nz99deffvpZ0zQXFxffffedlNmZLCLKHgshqjLBbrfThH61WqlavuJns01ryZ3q7ELlDgcch0GEU4ycsyHcrFeIXde1TVv7wvm3bdNeXFy8efPJJ598olvQxx4HPI9b+g+ldT6nFyBmhkyMtdY4R8icnJ0V/WbydaXFj2ItOHe1dV9XgA+1XYIEkOXIH+gIVJgR1Ocn+cEnsnzOx5KVo8rp2dfpSKwAGmstoY6YIS7SenO4KA2KZzyEpXkLS6B5cWJLqC+5wdN/52/1dDbema71Dr1jZyOZQJKBIwKIs+isQ2etA0NCqqrJGZJYEWRBxizEgERkjfVoanRnp6efvHrTuRojR+Dr/cPj4/6wH5o4rGLf7Kuu8uumWzdtW7dtVTeNvlA5ppQK2VhAQHXdCgTOIlKkdZ8i9PPLfjHXXrB4RMycYe6KPd2g+TcUgKJGVyhvIMIIwMA555RzP8aUyQ1kbaFH642c99TlwZTgSWiNKTBDaYIeAQcvoaoC1c9L40MLbf48Imrb9vLyEpBOT0+lyEIZxAKnd117stlUVQ1SDP0QVFRjvifzYQw5572vUuYQAwC0bQsI/aFfWpIqUBNjVDAwxqiAmPd+5TZV0/YhDUPPLCS8bmvnvPOV8R4NwYtxcDVrKqOnMHeRQM3u5nvPAGKN8a5oiajiQoyqYaRMah8zHw7DFGLV1BkwscSU1Dy7aRrvqxDj/nC4vrltuvrkZHt+fnp5dpqnsX94HIfDNBxynCSnQmIRRCEQQWAQDe2urdyqsoeKxgDV8bISCDFKjpKzCtAwc4mcUkJ7zpiYEmNiyEMIMRM4ZytrXbda9eM0xElgkZKIaABN2eigeK4risT4hMY7Y90c2hVQPW7vIaDq/cCiTVkC/FNoBwwfWFtaLI7jeH19/cMPP/zrv/3r93/9yzL6RWSptHIMIaWjDqKGdrVe1Wm3rltpyT6Oow5/K7k6hKBdEq2b1bC8aZolxuuiur29/e2335RDt9/v1+s1APzNqv3FQUTW2a7rLi8vb29vpxDo4SHGWJL72c3eWrsQFwHAkPFeJ1ttzhxDeHx83O93AKCBRCt7YeGSRM1vqjwd1tqqcpvt5vPPP/vuj3/685///Pnnn7969aoEVHw5qnt85JwfHx9//vnn//7f//u///u/f//994+Pj6oIVGKYiN7zk5OTN2/e6O39/LPP1+vt559/RoR9P+jIu76kIhBCTCn1fY9H7KKqDAiQtcY566y1zhhrADjn2hCgkp5zEs6GcLVa143XMQERMWR8VZ+enH322edv3rw5Pz/v+/7FtbwIhMfbnf7DHF5x3hOePEx1sYGo+DKV4ULFDF15D51dEJT5YJ6VaoqjOkBxw8qzx95ca+P7hdP7C+y4j/niX1/EnfezhKeUAlFpHYUJzNqLRC0CeIYTsLSJ52J++UHzX95HQI8+KC8++OJTm8qdrFuD3oIzE9EIsc8xcA4ADM44a4xziIY5BU4ROBOLFbRAFiiDYWCD1llfGdfa6mSzvTi/WNctMj/2O3dThx3fj4ce0wGTG423tjsc1nW7bdfbbr3NrXcUw5jyxMBZcmAeppC4iA4CAL+ARD6U0Hy4al+eED57E6Vglrq+kPTGH4kZLTiOLNvkghooH03fbf3e2seh8t6YqqoNmSX+A75cEHPpsGQGsKRdH9sCijxI121PTkLKisy3baulzziO4zB676q6Ug6/dnMzsAgszpLHN4fI1HWTWUIMijE6W6B4bRZaa3VfVuiyqWtDxCLDMLi6tr4CTiYP0O8z72OLYWVjV6W2yU5eII9z7NJHqR9Rm18DgDlzSlPmBMDOG7GWU+KUhVKSPE4h5WgrK4xTSo/7/vrmLua83Z6sN5iZx3G8u7tv23a9WXfr1YponKbDMJAlEfbe1ZV/PDwe9o9jf4jTxCmBZEAEYoLCbyk3GckrgG6xMdIY9vSUowhAjJFTWOgesy2wzPAPAJHxlW/YJx7HMYawe9znLM5Xs/5JRUQ55RRTjMGAoWzGcdQTSZljLC18VH8/46319im0l8IdiyiTZphPvXaeQzvMQZ1Krz3OHlHz5Ygoc+3q6uovf/nLX77/y2+//XrYH5CKHbBIIqKq9ik1qluixoGqX2atXa1Wp6en5+fnJycndV0BwAIpI2IBUWMEAOdcCOHm5kYLr9evXy8Cc+M4qrmL+rv0fc/MagGn9PgPvw8feUeaujk5Pfnss0+Hoc+cq8of9ocQQkqZMzOIRYJiv0alfjUFIAoxhHEchmEY+pySryrvneLwR0ug/KbF1+ye7E5Ozj797NNvv/32T3/60xdf/OHNmzebzaaqlN4PTyDih45xHP/jP/7j3/7t3/7rf/2vv/zyy8PDAxEtU4VEpLH/8fHx7du379692+/3t7d3/+X//V++++67ruvevHn95z//kZmV36iMCBGJRTpwXMYEQDM2RGtIRXt85bx31hKgNLXv2ubhYR9CNAbr2p9sN92qJSpX6n19cfnq9as3n3zy5vT01Hs/DMOLayl45nvRHZcW6TLiPfNFyoaMaIzxzjEJ5Mo7b51TbEEHH5QVEUJQPSJmrryv67pp6qLtDZJSTDnFpNR0ZZjJUgy+v7e+V2g9uwrFL48/CsVs5qmaPz5kxk9EGJBAsnDixOryUNquOqrADEejW8s9W+r15b4sf31xbi+uouwGz/9l3XRkGciiGBMIvQwwjRxCZk5gkrHZOrCGhJ0RNJzJGvGIQjYiRA5JL1aAEK1qtJFxxhBR21SbVdt2lZss1iZ7EoMReYiH+zhcHXbNve8qXzmDkBEZEGLO/RRud/ubh90wBZYlx5sr3Pk2v6hxX1bty2N7OQ5Z7tDTp2mYFBEgVu/gmegIy58UBNXvoT1ATRjVKU6U5GCtdlC990Rmjus4n8CzYn0+zfkqllHOD600AFB10rquurbt2z5Oo/N+vd5UdWWM3e/3AGgIkYwIKDpHRGKQdOKa+YlGgiKCROR9lXIeBhtTBAHdUNQyS/du/YOmoTquO4yj6pbknC1wjcnEgx0A+irv27jZxrhh5hejVnqPNcdhgDmvEkOIQJIk58w5ArK6DrLK+YFJDOM4iUhVVSnLoY/3D4+/vntX1c3lq1dVVbPAu3fvbvZ7BqnbZmVtVVXWe0S01lTee2cJIUzDYb+bxiGlADkRsNCRSsIMwCAZa523rjJUW2wduGeRRWJKOaUC4BdorWRuGuoRyVW2QurQCFJKeRinEFPbdXXdEJJ3DhFnF/aEBjnzNE3MgmBEIHFUCQqDZi5anLW+zLkdAfJz6YkzzqkusAUPUUdYnlNTxPRiVWlH9vr6+vvvv//LX/7y448/TGEq45HGaGDIzMYYX3mFfKdpnL1K0Xu/2Wx0kH29Wi1d9r7vx3Gs69p7rzNm2n7OOT88PDCz9/7k5ATmjVUH3lTb9eHhQVPJtm27rjuaaP+7DmNM3dTb7fbVq1c6tGaI7v3D4dBP4xRjTCnPWTiZmXutqbawZM794dAfDmrG6qzxzpG6mOg2oL3qp9YtqY7TZrP5wxdf/OnPf/7zn//8xz/+8fz8om3b525J+N4fno5hGDS0/+u//uvhcKiq6vT09PLycrvdqt9dSundu3c///zzL7/8cnV1NU3hcOi9q+q6+errL9eb9R/+8Adm3u12yqpLKavOQoxJo+BCG1TegyHyzlaVb5qqqStfO2dNWK8OhxXAb/f3j7pfVZXr2kZEZ8RhtVq/ef36zZtPzs/P27b94CP4YLmJM9w8B0Vt8xPOM3gLkXnejK0xbrZNAlToyFok8pV33hlrMWc721iRMSwSk1MUEwBm744nUkjpVgMsg4cfraKWRODoK5/+DWAeOX3qAS3YLXPmlASFSISzZMyM/KK2nJvLS2pTwn75ns/C+XGYL18sIsJqC8THh7K5jxZY5+raoZARQPIkhikATAwcE4NJZJKhaIq0jDBKMiJWZeyNVQl1PUlCKlNXIAhsERpvt6t63VXN4Lmy4IkNskgYpjQFTGIEvDHekHfGWUNkYsr7ftwP424YQmQGu+Bf+MEXYz6eh/Y5DSjPRo221MNGIEuGIhUqgEjWkHcikvSzUZAIjWEyyrViEWQh4TLNLmW8Uu/6Mqd1hAgsKQXRso6PTp6obM8yA/eAQEDHraAXhyYIBtECe0mVJMoIKXKygBhSHMaBSAU1ARCcc76qiMg4m2cYYu7ngBAgIhnylW/aFsYhpsjMykRVWA8AqqomMjmnaRpFKpUSNdYZMsDcerNZ1TROTkLLI4WDxJFTFGbBF8UWFRYPAc2QCSEZIgTjHCKQZURk5501RkRiCClwZIgx+aparVbTlHa7se/7h/v7po0qZWqsJQQWVmFUIuq6rq78J29en5+fvro8q5wbh/6w3/WHfYoBikRg0YOmp2N5San4rXnXeUfPY7tawCy9+fLuCaMwS2LOaKx3FdWNa1fGe0AaDocQguz7OMWcMwnolHHmXFTjhXNKAGiIAQFVvoGEVJLIGmOssVbm9GMO7bSsIpg581Ii+gLFg/I4BABxAHiaQhYpvdhff/31+++/v7m5YebNelM31RSmvh/6fj8MI6KOrSmH3xljck4550Wg5vz8fLvdlkH2YdSR9KZplNqmtu7q26asb5WI13JcP0GheDWXe3h4CCGouOxqtfrHVMoBiKjyVde2m8369PRkv7vImY2xTd1OUxj6YX84xBi0rhIBHZ9WuCPlFEPUiQBrjXPeOrfMXM3BXNt3hSjTNPV2e/LJJ2++/PKrb77++utvvnn9+vXp6ekMSLz/In/41Q4hvH379vr6ehzHzWbz5Zdffvfdd19//bWO9RMZ5nx9ff3zzz//y7/8y3/8x/+6u7v78ce3Xff/1VT0m2++Xq9XX3zxxeHQi/DCq9e9SHOycRx2O6ujNJV3iJU1pvKubepVp6LSHgmnKWQ1JQ7T/d1t19Z15aw1dV2t15uzs4vXr1+fnpxofvD+wfykg/ksIs7bHCwAHhpEA2BFUmaOKUxTbwenIqA56qgzJknDOByG3o+1EoNCTlmZH8wxpRAimIkshRCVdZgV8ANaXi6eQyKV6hieGqofPko3HEVYmORJgFyf4Vylz5U4iEAuglUpMic1YuYUsxT1fSiElZLcGN1xnu7Tgk+DFFIWLmKm881TjiTrC5gyp8zFWlR/LzLVfllmTozHCskAEQokl4Ij69BmlAQkyEECRxwZTRKeeBoyZyEidWMTINFU3xEZIGThnCNng4S1kZW3G+823k2W2GAmiDkzhxCHHJNwRhGD5Iz1WpwIhpBiFkJjEDkzpFns64k2cASQz8cH7GGelpcAAQrSrB5WPLXzYoTqXIFTmAEEDRWQp9TVi+pLudlPYXLGETT1hJwFMWWroVGZHTS7Fxyf2/yXJ6RqnmP64IKT0jwAIGErXKGIMKcYowGRaZq05AIA52zKOcYQY3C+MtZQzpiRNborOqtYkyHrbNM2LDxNoxbHuuFqKWOtU9jtcDhYy0jGW2tFEDHFWBvqmsZRtJkskajr2dHrfXy9hAYMwjzsQdrXQIOgAjskQkRgnUFjMueUQ+SUgYhM5XzbtIjBmJLopRjHcbDO+coba7quY+Ywhd1uxzl5X21fXV5enp+erCXHfv/Y7x+n4ZBz1BeSEGZElmYXjFK6IxIZ61zVVLXkIM93MWbOwiis9vPzgtTQngUYENAaaxxUFHOeximEyOM0TVOaAiICEXChMs81BWRmzBlAkBBQlAKPCMX11VoyDmZFDpizkrlwL6RZOWLSLVB8weeVfPH80NB+c3Pz7t27cRyrqj6/ON9ut3f3t6pksNvtrHHWOUNW9yMkVLS3ruvNdntxcXF2dtZ1nbU2pdz3/W63Sylp5Nb6XiFrlSJXMp0auym+qiX7cZddJ7suLy9Xq9Xz4be/3XQvTau2W683J9uT3ek+hAgCla+mKTrnBKDvYRxHmG//MsCmU2chTMxsjFd31+PXVkSKsEDBz+qLi/PPP//im2+++dOf/vSHP/zhzZs3OkO/fP7zd/mj56/3Yb/fxxjrun79+vU333zzn/7Tf1KLHaUjPD4+fvHFF5vNpmna//E//scvv/z617/+YMienZ1vN5s3b15fXJx/++03Oefdbj8M4ziGcQwpZQ0GIYTDYe+dreuqqSqQ1hj0zjZ1terabtU0TeW9Tyn3+8Nhf7i7uzsc9of9br1qN9vNqlu9evXq8tXr09Oztus+HhSfQOwXoR2WD6EaAapAtwFBVWtWQyUTgiELQgiGkJT/GGIMMQqhAOTCiwEVzEkpYYooJqaU1J8pZUlZUCQX/VWZ4/SSdfzO+ZerKIOCmg+Ucq0gxUv5zAKYRZTLJXPIjcxMxiLozNjixVyIKkqBAmMACBEWTfDihqc7Ci/VuTzTRYGiixVTjInjTGFn1bpkFsDaP8UZYjQ6REzAiSFllEzEOvUjApw4hcyQAAPAiGlgyUBkrEFrEMkAGrLOOENGWFKKIQzZIVrjCDpvV951ziFxALWjBgOMkkRCzCmnjACWvHe5ykhksppjGccpJU6QuUhvAB8tmZedhfcka47Xll4uC2eOMQ59v9/th74PIQiIscZ6JyI5RqZUHDysIWvIGC6+R0RIAFCYjTjT8o7q7JxyShliBJSUuqWeL6SnssifFtb8h1kfH95vGyyXIwsTQFgIqfI+CmWWOMUU4hRC6d8j1nWz2WwAse/3HVHVWDIGzTzdJyJqtcCgUFFVVTmnw8Esw2+bzSaEEEJglrqujbHel0khYw0A9tPUjxO1vmpW1niQlJwH6iK42UP02fmXVF1QXxkAoTnf0eyICIksGXLeCmAcU0oZyFW+qdtV066ssd7Ber26vLyYQhinMI0T84Ovqrquv/7qq0Pf73e7aRzjOL558/rs9OR0s26r6vF+t3u8H4d9SiOoca01hkj1QBXBO6raEQms9VXddLGzJNHX4fmD0PdNFeShoDwqbQRElIDVqz0wTjEAkXHWOpemEFMUASR0Fi17dQtWI0MCJfnq0IDS24vHAZnSEBY14Z79Ome9Uw3tZXHMw3DAUMQulqo9P/fj02C23+/Hccw562DVp59+cnJ6QkS73Z6IFNq1Kasum244ObMxZrPdXl5cnF9caMkuANM07g/7x8dHbZMjYkrJe7/dbo0xOiOuUf/s7EzhXPVdvbq6urq6urm5URH4tm1fv379ySefaMbwgZfh4wciKptyu9nut/u7+4fD/jBNQQSNCTNViVOKKRV6PCCq5LHS0IjQOWetWxh8y2sLACxZzenPzs4+++yzr7766k9/+pPS5eYKm45PRn//e85cfxwzT9O03+/1XhGR9tqlaORVzvnNemutI7L39/c//PDDP//zP3ddW1X1mzevXr26TCk+7naHQ399fX1/j84ZZsoZ9NXeH/bOubby282KEL2zTeXbxq/aqu0a7z2znJ+f7Q59iGG3249TGKf4uukuXr1+9fqT07OzqnpqkbwfIOd6570OsTxFxRmKNoBGO9cIQIQ6C+e9c6YCxsmPvasQgwo6We+tcwJgnSNjkfAo4BWMH2cbJVF5nFLSzjWZvl9/5xMpbw7MBT/qxJbmgsULAhGi0n85c3H30FMxLDmbZUNZ8H9NDg0tZwqziW2xI1CvFL1zi69N4fMgsEgWzpxTzpEhMjBjsX3L2ruX+rgSScIhaQIUY4oxTmOQmCwZg5QyxMg5pBCHlA8IU2UYDTABMpIYMsaQcegsWsgc8zQOh6GvggWm2hjwztaVb5wNHEJOhiwY01iPLo0CBiABgqA1trK+ct6QZeKMnCAzSeSMx8nS03m/hOefh/ZjiVn9RJacUpjGcRiGvp/GKaekYorqNS4sWOSQdLjHkA7nFYNx7anPEX0GmPD5D83MkiVGyzMmBkv0P0r/5zdjYUjO3+Yj3Z9yIWWhGGO9qzthYDCJOUb1cjCGrLN2tepOtttx6MM05ZxA2Bi01nJ+UrsVEQZGBiovjl8Gf5etWV1AcmbdYhRBJSRjrYkJIDLabNuEDaIAGbSNWIf0QVazujEDmsIp0KAEQsKl1iyNC0BmjmGKkcnVtqq6uqrrChENma7rLi/OEfHm9u727v6wD+M4varrs7Mz51wMYRrHEIM1ZrPqmtob4DD2/e4+jAfOEYCJ0JJ11mibzlprrSokluYfIVrrq6rl2FnMo/HvhXaVgeHj0E5SLNhZgHMaU+5jTiFlzoKI1kBApfUAIs3MXVUi1tGPssgXhB+KeDHppIi1gEXGa6bRaT5C9ITGl4kNFcLA4w0KhOGl1a4OUqvwUdM05+fnr169Ojk96fu+fddaa0EghBAxMTMhTdMYUwSAuqrOz88vX706PT3VOjWEcDj0Qz+klJT4tsxWNE2jTX0RUctXRdqVGnZ9fa02a0qg05L99evXr1690u/8NwusFy+I9vU3m83h0J/cP/SHfhynnDOA5FwJFAUO1T+IOg8egnLLhbmua+f9scz7sucQmcrbrludn198/vnn33333bfffvvtt9+en5+rwM7x7vQPxXV1ZL+7u7PWjuP47t27t2/fnp+fK8xa17WS2XWcvWu7YRinKfz3//Y/7u7u/tf/+l/qj7dadU1bb7fbi/Pz8/Oz9XrVNA0iLBB9SmEYyBrTtc3JMOScVMCq8q6uXFt7550IbLfri4uLnLnr9t2q22y35xeXF5evT07PV6uV8oY/diG6675ftR8F+yeKE2BhpGlGSoTGkDXWGgvKglhiYymsSEqeOpOHZvqZ9udN+Tx9RZmLjPzSY3+5VH7niYgwMgqiMAoSI5c7CXnmtsyfCU/CwgBgrLWWZFaMLFdZBqvKaWRmRAFgmAn8WubMuP0Re0Z5HfM1FKt3ssYZb63xlBlSKnhBkfs7viwGjJjHvKxwThH0p6MhQRRBFokcxgAykRdjjehYjDiLXj0ECSimcYpjb2lfuW3lcmURwTqj80TDGMfMYsQgWSCHVgyTgAUGQEvOGV9ZZ9BmyYmygBhQQ/syQXBUin/gubwM7cepAAIw5xjC7uGxP/QiQgDq4IBlOO2YbAxAaIiYaHk4ul5A55MWmGTZPOflYowRBJWFeeI3wMtiXFMELkYJi/Dt8hjfP8oSN9bZurWJwSe1BcgxMYQKxFtDRHVVb9br09PtwdJOWDhN42R9VXmvpmTHufTSNTDGrlYrRDwcDsysw+tN02rGp2NOzKxK3da5Vdu0TeWdB+uiSFbOWtVUVVV7a9/TKy915pGK89KuUre7nCTnpOVFSmnoDyGxS6nyniATcM4JBCvnTrYnVd0g0n5/GMbdMI7dqhunSUScs3Xl2VDbVE3lJachDMN+N/X7nCaUjMKEYK113jn1op83hBmUJwKxzldVm8NB0kDPXVU0MgCzcJF6EwEq+vzGO0ssKSWZpnHowxSzOsWACKEQqUgmCyhDlhmZkXWOdDaeEW0EZwCDSIaM1V9IBOVVoOJSUgTNVfnnyCoGlcdbKH4MBUl5saQ0k1MYqa7r9Xq9Xm9Wq3XbdHXd1FXtnJvGaQrDNI0AoCpp1tntycknb968efNmvV4ba3UQ/OHxIeW0Xq+13Fd8W8epdZqu67r1eq0iNiKiynG//fabUufUsv3s7OyLL7745JNPTk9Pq6r6h+L6clhrV6v16WnY7/d9P+z3+3EcQiBjyDm72Wy6rnt8fCysvb5fdGqdc847/1yMlmfnrqqqLi4vPvvsiz/+8Y9ff/31H/7wh8vLy/V6vdD4//fOFgDquv7222+nafrhhx/u7+//8pe/6M355utvv/rq68tXr85OT+umrry3xp6enf7pz3/KmXeP+77vf/vtN2vN2dmpteby8nKcisbDyclJ3w8PD/cw6+SrRPChPzzuHu8fuu12lfNZYb0QGUKDyAh1XZ+fn5+dXxhr27bZbNaXF69OTk/rugZ4T0D6+XG86y5xd/mrPFGQnn/JMUtMhIUlcUwxhJA5WbLaSE4pZc7TNI3TFGLglIRZAT8dQ9AkfU7IChG9FO3laf4+W+vppCAn0QQFUYiZIaunYyyC59qKpaIRYA0VyUgkC2iFjBCBKYjaMt5chG8VPM+LUjULxKVEL8NgRCr3qzOA+kKzGEDra2dd7XxL1qfEKaaogmUizPlw94twodQYsAaQiQW5KBAKS8whjRkIbW3Jg/cgOU4mRomcjANPtTV1U6+ddwZJUDKnKaRhGPbAO2eHrsmrVkCIqPa2q6p9mmwOMaQkmMbMEUisRwMOEZBUjVoMCjADJOaUgVmJRGQMEh1pzcr7D+nDQrNleamOZggP9w/7h0dVhjJI1hpAYGbOSUQ9PwqEA3L0HaCU1grLvAjTy79DYS3hvLxKg/4jpbg8fW156L9Xs2ulZowxzpOvETPmbFK2gsxMCAgWEbz3dV2t2tYAoPAwhRBGJbdHY5PR/E6TUL2+Iv6qW7CSn7V2X626cZxU9EP5z6LidITGWCrIMDAQGuPruu26tm3qyhnzlO4sp18ymOVGzaG9UB0N51yGUWOMOQXJWQglT5InzrUAIFhrDDXWV/5wOKxXXQjxMIwqqykizrnNZu0Mbddrb00KY797HA67aTikMOo4p9bW7gmNn2vfovyDBGSs81UTpzqMVtslyxNbOCuSZ+LC3HQxZL31BJCRDjhCUjuBxFkABSwhq0JWaXtrKQ1S2kyFk7dAgIIAWr0YMtZYC4orEM4xvsT5ebQddd8s6h2lIBIB1jLmg4FnrouWwgh1/K9t2q7tmroZ+kGVdDnnMUzM3DTN2dnZq9evtVpFgHGa9vv94+MjAq5XKxHRESz9iYuaStd1FxcXS+xfiPEqeqhtoM8///yrr756/fq1ciSX+Pq7x4tPECJTVfVms7m4uOz7Yb/fKYOPCIiwrit1OdJlo/NUOWdVRNf6WFNT7XCpoM1qtbq4uPjyy6+++fbbP//5z1988QdliX+c5fcPhPm6rr/++uthGH755Ze//OUvV1dXb9++PRwO9/cPt7d3n3762evXr9eaeW3WdVOdn51/8803P/zw4/X19S+//PLDDz+en/+LMeaLL/bWuhjTZrP59ttvuq775Zdf3r17B3Map6oDu/3u7q7ebtdn+5PNpo2x0+ZtLlqD3Hbd6dm5Zld1XatTzt9Deiixeda8evHx45tTalKliKvhppKgmEUSBw4hpJgEWUTURxgixpTGYYwhKuSeco4h2OjRGFgoZ1K62nlhs7wn0/Y3DgHJCRiZBDQQA+RcVE5wToZIe3vWe1d5VzlbGevImOJOo3k5zuIq80qePSiypMQa3SWx5JxjzjHlJCklxfgFBVCIrLYJhURQ0BjTVNW66dbWNwvSrq8Y59jf/7rc6JQ4BY5BYpScsm5IYZrGGAVN1dXOOmONMBMZEYgxWUQAsuScrVQBk3NKWcKUhj4cQA7VMI5BfZK1p9PWvgn2EDBngSSQAFIROpfCRwJmzpwBMMeUY1ZIW5uN7zFV4fmoOMCL0K679Zwult1yCvH+9v7u6nrdraq6FmNQ2ckxxIlAIKXIOTGzpCQxKX8PRYxRDhEpx1H0B2hoPNp9CsgqwJxL+fTUAZon8XDJ4pZfT0v/Y0tQI+KymbNAFIWA1OdNG+klKSVAY8x2u25q/9u7q4fHPeeMHpyzzH6aJh1lAQBEhbby/MIpN49jjM75tu2IzDQVpXqlDs0SViKSJbMAOusa70627cXpZrNq6sobQzk9G7XCojJb/vy04AEBwVogImOUhxeRwHk0mYwVlBjGHo23lSkkSAbO3NTV61evfFU97g6CpPSryruT89PTzWa77ixhP/b7h4fhsIvjEKc+xckSGGutMa5A8aVqf8ozAEHEGOt8Y2wtYJ4jXFBGZZX9oXdR9LkUeTWPZK0PIe7MIWFICq0b/R+hpcxM1uiiodJsF8pAJEALIgRKnCSjZheOjMPZPrTE9Zker5UBKNF7dnplmAv30qT7QGjXgSjdhXUe/fHh0ZABgNVqpeJxGvZSSgHAEDlrN9vt61evLs7PN5uNs1a11h8fHx8fHquq2qzXuorUr0j5XzlnnVw4Pz9Xh3Xtsit1LqXUNM3r16/btv3uu+++++678/Pz3zF8+1sHIgghNXVzeXGRUhyGYZrGvt8PA7IwMJChqvInJyf7/V4XABR95co6i8XKhBHRWtu27fn5+ZdffvnNN998++13n3/xxcXF5Waz8d5/sPH0j58wVFX12WefMXPOeb1e//M///PDw8Pt7e04TL/9enV2dn5+fq7DCJ988ubV61fbzXa73X711Vd3d3ePj7vr66t//dd/Hcfh6ur6zZvX2+32u+++NeZP795d/fM///O///u/a8m7JDH9ob8xN01TNbWvKtc2tTGYOcUQphjB1E230fEH1d9dbtHfPJa4vjRDl4/DDEmXN61ATvqvBd3MOeeUYs5xjNMUMmcyiIgxhv1hn5lDjCFMzMlaK0hhCo+7XQKocrbW5JTSYoUmJQeXhV00ZxNHCwUXUOHF2UoIAiiUE0YGDIlDSkjGed/UTds2dVXXdV352leVd5W1lTGW0ACiEMziEwqfabuBZt4rkiCISpsz6J9YnQ2mEKYQpjGEUdOXzJwjgyjLhoWEOLuUmWNmSTknyRlKu52F87Nr2Q/TeD/kFFIIKUwxjNM4xDAJoq3a1la+blkopixksggKMwgSAGr7GoUlaT4wxmlME9JU5zBxjIwiiOItNd61zjXG5sxJhMAQYGZJnAuckFmHfg1RYSUkNcGkhTFXdt+ZI/fikXyAIa9rSotEQcjMfd8/3j/wFNtu5bv2qU7UxDZGTkmHkjKEHCJkLjlm+f9TBH7RGZDCooQnrpXSrZGWID7vBct/529U9nP8/Z2haC3pSLWwqMoJIRGKEJdqkACAELum6Zp6vz8c+l44axPUV1XKOjpRCkNm4Vw4BzFGLVOstXVdKUQ/DKOiSXNRR9qEwJm/3bXNZrU+P9mcnKzbprbWEOILr0eNQPpAlj8X2iAAFRERQBIAZaVa4USIBCmGnpwnVymlVgfHKu8vzs985X1V3z3sdrt9XVeVd+vV+vWrS4MSx3447HcP94fd49Dv4zQKBzLOzqbadlba1IIVAMrTZTbGWl9b3xjXED/xUmQutefVpwUyEhZzEWetNbYCmqa4b/qcYk4xoQCiAWRBsiZntsrhAAAQbYrjjPDMqtE6DUOkQJ91xvpnob303UvXXVO/Ja7ryyIA2rNX/7f3AXnts6gqnCLAS+p2dnamFa2uh2EYxnFUZTYFtIkoxxRDZOEUI4gYYwhRMSHtstd1rTp0RNQ0Tdu2bduqDtLDw8O7d+8eHh6madLvqdy0b7/99vPPP99ut0djb/87wRIRnHOr9foixXEcQxjV+DWEMeUsQZhlacWofVlVVc55QtIGmjGmaZrtdvPmzSd/+MMX33773dfffK3FelV90OjlfxON1591cnKikJj2wn766aerq6v+MLx79+7u7u6nn95uNtuzs7NPPvnk008//eyzT1erlbX2/Pz85GR7f393c3MTYxzHKee02WwuLi6UOeGcJSqkGa0fQphCDLvD/urm2jpDBoXz/f2qqasYQ2Y5u3yz2pzVdd21rRqo/UPXclygy8sZgflOlbCuUqNQON5zRI4xHg79OA45Z+sr7z0ABjXWjVNhRjUNZE4p94ceDAEBNg3AcXsaCroNS6P6wwzl9w/mvLu/B0QyjpGyIAMJmqaru26zXq9X3apt26Zuqqp2ZZLCFJRdLTVp2d2XMKUYnc4cAwoV0N0UUoFSOYs50DQN0xSnMU19Hvsw9cJZBDIYMDUYZ31jU0LKSSduVXmAVZPp6UJCSodp4hRTDGEcwjhwjoRUd127OunWp67qQkxIAwNHTpICkQxhtKESYw1ZYUkpxRxTZBFkxpQkxhxiMpBBhBCdocqaytopZQNikdhoTa326JR15hZJKcN5bjzwTBWcK+Ryn95DfN9jyPMRa0ObIppOTuOUpxhC3BJKypCzcpqFJc9jdpkoxDJHQWSU5jT3keZfesyJ31FRjvPI4lOyBjNHaxmQnZ/3DLXPIO1HC/cytfXUZdWZe+I5cyBCFNIfIaI+jNvNepymcYrTOLTduna1ttw4pZySFAvXKcWoeJ01VDfNZrNer9Zt2yJiTGmaQs6ZA5eJNUPWGm9N29brrjvZbLab9Wq1aprGWAJY2DFHJw9IRNr6LbOAGpGeci9AICJAdEhMmJiFBBE5pzGGgVzjKktkCIBzdtbWTeuqCo3d7Q+7x8ccm1VTG8KqcnHsD/v97vFh93C/f7jv94/CwdknNxG1g1xCezmd8lARiayrfNU23SZE/1zDTaMoKWMFC+3OuBni99YT2ZOO1W2dOcecGEDACGLKnJgRkAwJAc8UukKkQ5CncTUUJDLOWE+megrtSFoTzFVPmdkrOHxJGnUxqQ5d8R6eKbnLckLluLVt2zTN4XB49+6dSppcXl6enJyoH4ke9/f3+/0+xIBETdMIy93trTUmhjNfVYZotVoZMjFG5eVpwM4zj6lpGiXcIWII4XA4XF1d/fLLL/v9HhHbtt1utxqK1O5dR+P+t0r2+REJIIFFq+7mIjJNIeU0DEPY78c4xZjCFEIIiKi1qTqq6QZpjKnq+tNPP/3qq6//n3/6f7777rs3b94osV8N1z8WtP63DyLabrdK73/9+vXbt29//PHtjz+8ffv2p/v7h/v7h6ur67dv3/71r3/VAH9xcVHXNQBcXFyM43h1dXV3d2eMWa1WX375JRGtVu1q1VpriEg5jOrapy3oGOP9w0PKse8PV+/erbqmrioiarqu7rZ1XVfe00yH/Puj+wLIHwOZy59xpiHjHN1BSESxbtYuIRlMOR763TD2KafOdV3XAVHMSUmyTd3UTV05Dyz3d/djGGm0rnJd1xpjg9PxF4B5UnohmRdNxudn+8GrSDH98vNPgGR9hcaDsU23Xp+cnZ9fvnr1puvWVdV4X3nv9PZmzqrWPE1jjCHlhLPt8gIsLzsMzEoUAFB53zRt07RN01hXWVc7n6sqNjGtYhz7x3FP94fd4eF2GvsYo5Cz9QoM+bpmbhg8i2TJWXISFafm40sSBCYASyiUmCNzVVWr1frV6083p6+QupAg7R6ySMxpimMKfYwoIiHlLrElj1zSJAD0rrLWAVBKHKZoKSndAVWq2Tpn0FHOBiyida42JMrnSkkyI0LmPE1BGa1ZcswZY8yc57FynLXkX/Ien+fRJXmceRtYlL2U8DKOIwB0m42SNjhlyFnKsteCG4WyAkyAMylsCVil7uRlmS4LpSzu/JSLHI1VzZXqct4zbw7nCbrf3y/mJTGfy0LPWP5R4VkAKPIdfr1eTSHc3N33YxRhInTOWGvGsSiL5ZxFsuIkOhbcdauu7aq6Iqsz1U4lAJTE6ZytvKubqm3q9brbrtab9WrVtd57oxr7Hzl1IKO1KR4dCgCIiI4hgKBFA2BBTE5KnRfJMYch2j0iWW8Q0BCRdd5Xus66tmuqqqnrtm68tcB57A+P97eP9ze7x9uh36U4OQtqO+N9IcYfl+xzKCxoEKExxvmqbbrtMBLMOtkz+0/hMVFY0RAVVSxrZxktt6qbvGEEMQbGEFQ/gQG1n5aLapTknGIkJGDIWQxxqblZUMQAGGO8tbV1tTV1sb4gWoRmFdmcsYNCoJOZkqu2bzMmwO/XLBpIlNq22+3u7u4UR91sNm/evFF1T5Wmub6+fnx8DGFiEWtdVVUpxIf7B87ctm1VVdaY9XqtssRK1GDmw+GgM1dN05ycnDRNIyLjON7d3SkxXm2/Ly4uXr169ebNm8vLy7Ozs9/3aP97j5kUq5MdMcYQJhFOMQH8dn9/n2LSqT8zozi6GNQnZrvdvrq8/Pbbb7/74x///Oc/ffHFF+v1RkMpPAsJ/3eiuz5K773mnev1+uzs7PLy1fnZ+XZ78vPPP797926/PyhjQEV5Va6u6zplvQ3D8PDw8PDw8PPPP3///V+7rqtrf3p6dn5+/vXXX/f9gVnS0iMjqOvKe+e9Y4Dd/pAzp5arqqpbzCxZkzLm5yq//2DD+nngfAF9I2DBrNU/k2FxTGHOMYWUI0tWZowAxCRqmQyeLZF3Xp0nUowphqz658YQCMFShy2sNPlQKfjRg5kfdjvjXEsGGFOIxjdkTFXVTdtVdWONRzIimDIg55hiDNMwDuM4aGgXzk9vnEihEKuAvBJoyBhDKedlQIvIiggzChgiNAZUKCbltOsPu4fbfjiA8VWzAd+YesWmdowxS5xdz7Wl8QzMRtF3X1vdzIxkXFW1q023Pkm5SkNggcQ55RhzDDFEABbD6MmlyhhkUCCY0KCtkDCrxOEUhBJnNXtW9w8FYDjmPGUgS87Yuq69tVhEujimOI7TOA5TP5gpUMxWM8iZ4ai72PvUiBdVu8ycCr3DQkTO2rqqq6pKIehUKyqPmFlilsxSbOFVbAxL6mXK0tQpI0FUHRFEyFDkF0CEiJRulHICAzknDWMLU0Deezlm7KpYaZXI/pHovsT1slpLVx0A54YrCJWAX1BeIlqtOuY8jOM4xZwT5miMcc5yTuM4aIpT15XzvkK0zqsfpa9qQEophxhjDClFYTYqcLHqNuvVZrParDqlzTlbstffSUtUfA4En4V20MZoKVh1LSITkUF0Sv4CEIQscYw9AAuiRdN45wEtMxKapm7Oz05TTF3bnJ+dNJWdhv3j/c3t9a93t7/tHq85jpakqaqmqeqqUmI8qadsmXk7botoVm2QrKuaBqVChiMLDCWcyawjbclYa7wz2rpHMjpr3lSVscZ723VVP07DFPQdCClNMU8phZxAJKc4QU55Ms4qWRSIBADRIBkRa2zjfOtcbV0N88jb3MmjmYpUIjrMixYQGJDKmHwxnflY1X5ycnJ+fv7rr7+q5drhcHjz5s0333xzcnKiSMzJycnV1ZXy2HNKSmeNIYZpuhrGqqqU3rXebJSZ2DSNarDc3d0hYl3XmkCoGtJut9O4vt/vtfv++eefa7Gu4X8xWv2/chCRc/b09NRa631ljFVCqDJOAEDReDP7jKlajk61qR/r6enparXSyc+/J//+Pzyqqjo5OdGA/cmbT7755ruff/757duf3r59q/Lyfd+/e/dOmQrn5+fn5xenp6faSru7u3v79m3O+eHhfrfbf/fdd59//unl5cV//s//mciEMAEAErar9tWri27Vee/DOMVx6rp2s16vum69Xntf7XY77V9os+bvP/mlkvnoZxxRmxVpVFqUAM4s9CSSiWQG0VSJBeZJEgbtM9skIlrs5xxzDDlORqykKJyQeYao5yE5mbtc8LdTFAGICNa7erPOjOO+D8WsOY1hYkDCaSkJECBxSinqAJp+9xBjSnHBJRHRGgsAs0Jz5ZxBNMw4joH5EGPW/b9ox2bOOcUwjjH2Ke5juD7s7x/uAF1dR3YbsashW9fEmHJUbbqsDnjcMi/XhyAInFNMYeKURSQzx5T7KbhhYqSQckwxppA5ZclZJLFIyD6iiEes1F0eBcCQMUYgTzGNU5imSYg5x2lKw5SmmFPimNIUwq4fDjFTmhpZVU3ddG1bNdYQZ44pjtM0jmPoh3GYhimKrUxVk7HzbrZQg58dLzTk8dkKQ0QiQ8Y5Z50r9SIpsoqqWygpQS4rSVV/iUqRpJUQL5D7U1Ses8MnnL18obKwn4Yzy8J++rS5Oa/L/e+F+J7qhbLJoDGUs9GJ+vIZUn4YIlbed123Xq+mmGLOYRpV5V/hkRgDkbHOt01rrXXeV1VljRWAGKN+AiLUVWWaumubddetN6vNerXu2q5rKu+PCqz5yj504Fy1ozxnjIoUSe4FLSMhMUSWiYWTrleRyMKIhkxtq2JVK1womqfbrTO2rnzX1SRx//B4d/Pu7ua3w+NdnHpHUnlX11VTN+pzM1dpx7PLSgGap3PKcnHO13ZKAHG5OEOWTdagSUSWjLfGWdXetUUXgdAANdYYg3VlxilMIWp+G1KOMY0xTSklNdlCVgsfUWSKANFY56qqa9tN227qeu1ca53H56FdjriY8jTUXv6KBeJXeykReRnaQRXX61rBcFWeUZ0ixW+aptGKtm3b9Xq92+3GYdC9KcV4OPT7/X6322XOfX/QlFQb5Nq/V3rd4vKiA2/qBPPu3bvD4YCICg98+umnb9682W63bdseMbb+T8LnM9gVkRbhW71qfb4xJjUaQUStlU9PTz///PMvv/zy22+/VaL+6enpkmqUhBrf/xH/1w5EXMCDtm27bnV+fv7q9eVnn3362Wef/vTTz9fXV5oYHQ6F279adRcXOq12/h///u9XV9c///zzNE0p5b4/jGN/cXGxWq2++OKL/X5fN835xfn2ZPP5F5+tN2vv/dgPYz80TbPuVk3TeO9jCkqGUE+/1WpVOhxHe8/Hzv8ZBja3K+F5Ba97qMxLF0hRY9BQnVNiTsIFaU4pakaSQsgxzpTnSYfXYww5hhgojOPY92zMNI4pBM4ZMksuQs7aUFs2HcKn3XNh8h9vYkjUrFZN2zXdKiQ2IZFzxjlBDDGxTCpEvuhXlnG48v0AmZklpkSzPcFceqFqhIiojbsnMiISYxIZSXW4ZRaOLWQzTGAimH3Id/uROfgeMl71gerbvfF1Yk4a15kFwBJ9+2ZjTXnTi2BfzDEmHQOMMR364e7hIYH3NacMgWOSzChkrasbYSSo0FRElbGNNYgggoxW0DJxyByGKT88DhYip3Hf7x77Qx/CIcZ+irrXjSHmlKfElqzyg5qqRkTrXGOsdxVXbWjDOMWJMRpnVLFAORHv0ePh/dBOSFqFaeRQzjwZY8oQEZE1IoKGBEHdIUCF+2YsUAjRkhhiHcmeJ9SfFEJFEHAeT8fyZhqq69LCNMYeEd9fIHkoM7Iw//Z70V2Wq56hCyq1vl10hOfu0jJBKkbJwNstC1xd3/VDb9rWEiqLDJHI2Lppu/XGa9gzJqc0jmOMIaUEwnURmu42m9V2vWrbpqnrYmL98mw/vt+VxQ0IZcCyYDCwdJb1y7XZgsbobLfo/0GyiKQwMDxWQlXjyFDRVDe03a632zUhoOTdw+7u9t3t9a/3t7+FYU+QKl+1bd02jRqWaGg3xpCOpixx/YlDoXeunOyLDNIYK8yCTICE6Ixxdim5DRoSooxiAAmxctbbZuVr9apQHcycOCSOOUfJE6chT0OaxhQnTlEgAxnj63q1PTk/PX212Zy37db7xhgLJE+9diz7owZ4KX8FmGl0KLqnCSmHTvLLJwJgjNGa+/Ly8vXr17e3t+M4anNdXxQ1gKnrerVaTdOUQmRmBEwp9UP/cH//7upKtd/vbu/2+33btuvNRlHirutyzjo2plT5cRyHYbi+vn737l2Mcb1ea3NdI6gWiP//K4ittWpWpvQC772SkkMI2qL+wx/+8M033/z5z3/+7rvvLmaVvXkQ7u8r9/5vHAswYIxp27au68128+mnn3z9zdf3d/c3Nze//fbuL9//5aeffu4PfdM0r1+/+vrrr5u2ub+7b+r6f/7P//njjz/+9NPbYRxubm+urq6+++67b7/9ZrNZ/9M//dObN29u7m5Pz7afff6Z4ig55RyTd8670rl4+/bHd1e/qaeAc67rur//meiyOQ7tMLfbl+1yJo7q/rXk+Dh7QoUck+QsKeUUwzSOwwEEYkwhjDFMhtAg5BRZeBr6ECZEGRAcoTUmDKNqkTGDRncdUi3ggA4ZLbf4GXr4dJHGmtOLS++rqm0x5iZBu1o1XWecTZw5CiqJSrnAZcYLtcU3K+kgcwFiYUZYi9gEqOGTd65SPoreooXnyMycQZhZUNCSqdG2SdxhlBQTQH8Yf3t3syfrwVAZ2JlvdeXdV5f/H2sK85ezxMQx5ZRYAAVonNKUD0Gu+pC3Z2xsFTkwCJBxVd20LYKRbOtqZVztfdfaChEyJCEWw5IGCeNh4qvbPeYhhsPj/nF32AXmCDBmHrJGURzGYb8fpn7cPe4OZ2fr9bqyznvvK19Xlatabnic4iGmXWRCAhaRrCqaAlme85s+ABwdw+Dz7C6hQt9EzvvK2vXJdhrGyfZpnCRm5szl3SKyBo0xzhpjAJGF9cvL8jhaHDQfxhhXudVmffnqUom+qP2Dkij+/9r7kiY5jmNNXyIi16rqBWyggUeRkkY2txmbX6ifJx10kZkuOkgU51EkQVSvtWVmLD4Hj8zKRjcgcCRRes/a2UZUV1dlRmZGhLt/7v551s05FEiglX/j9NJRfyAolKFWQMhBWmtt4ZxNiQBCCMF7kUQjycZ0BwybpqljSvvd3vddHHofI6TEzNZZZVogNkSMoMVwESQZQlvYwtmqLNumWbRN29R1XTlnrTkq9YeuzMcEcXQq8yrTyyHJZOzTlQsRMpuUElLEqfpbogQfZe+RGZldJFNqKTZby2yC7w77/ebu6vrd95vb9dBtEGLhbFWVukUWrjD2ob+OKHLMj3yQIDluVg839NwMVIhIMSolLcwFrJi0Og8FMSmsxBlcR2BEm9uspgQhQYDkJRzicAjd3vc7329DHATJlnW7PD397OzsomlPyqpltsSM2ltx9MsB9MbhRDErMypZ/Q0laY27jJbUe09E88BPTk5ev349tW85OTmZKv41xUzJ4xTTA8CU4tD3y8Wiquumaa7W6/vNpus77cfqvVd9UNdVURR1XTGz9uLUOPFut1O62ZcvX3722WdqPcz0+j9eg+qRJ+tBPWNlvluv1xpc//LLL3/xi1988cUXr1+/Vt0/fltmx/inymRDTH4CImJZFm3bLBaLF+fnL19eXF6+Ojs/vbx8dX93b4z55f/45c8+/7xdLHa7bYxBWVvevn273W6+/vovh/1us7nf7bcamF+dLFeny7Pzs1evXtZN46zVum0m0qLHfhgG34cUtG3EdrtVC0Bh+b+JLD5W7UfHZWIH1bgcoRbGACEAaGv5IGm/Pwxdf9js+66Lwe+3KDHA2KXQe5+iD0Ov8ZHucAjBg7Kvem+Ykw9+8DEEEZKYJq5HHMm+MTNe5tE+BhUAgJDqdkHKe2JNuzDtYllWNVun2K3SpIw0pUcAgIhG/ayblvozikqiTIpgzOmeYIOHNwpG/4KQLNvSFg1SGcUMIaQYfdjv9h4IR6gxTd+uimKeSIfERBYxABokYEOQRAgHH3aHvT3sXJlSSgr+Ipqcy8xmbFtK2m0PgIUTsESUFOK22+2GXfL7MOx3++3hcABCMJyIDZIldoQH8X4Y7sOm74dh8O1mWzhXlVVbN4uqXhQ1A1kyFoExKgp/3Nve96eeTqOD2a3HiS1ccxeKqqya5uLyFRNvb2673T72PgTNeQJlHgDO3R81txSJjGFjDI97nzIcMhs2bI0tyqJdtKuT1en56eJ0WRYljg6qQkHauDgn1CG9p8c/wluDsyhDjKHvOsNUFoWG2A+H/dB3KSUUiCnCWK4nAEhQloUIHJZ7P/T399vd/qC7QJHjHBBCAJHIOeBjSYqyrOtq0TaLxaKqytI5Yw3zPDQ9jetvyzhwUPpUyCRNMKvVyniEiEBCMmIkpaAuspr7IBIkdLHDLomLwVWJrEMwKJhSPBw2tzfv1u++W7/7dr+9weQVb6ibuqoq5cBXy1rtOzWT5q0YkkZWxkCJzCsdj6slU+bqbOJZCYQWvkSt6EHKNP0SGZARDbIhNsyEBMACKAQRJUAcxHeh3wzd9aHbhiS2rJers7PPTs9eNM3SKWs3UVbikyI/3vzjCCcDCcef8e0nZpXuLOq4X15eGmO0aO3FixcKreszUwWvNygfTqSqqrKu6rZZnaxOT0/fvXv3w7sf7u/vr2+uN5v7ummUYkVvu0jqusN6faUd3rR6+/Xr1xcXF6enp4r8//P0+lyYebFYqO9+fn6u46mqarVaXV5evnz5UiEH3XB/miE9FjyulqMoolaUxXK1ODk9+eKLL/b7HQBcXFxoOUPfL4zhxbJt2vqPf/zj119/fXd3t93cXV+vv//+2//4/POf/ezz16/fvHr1arlYlEVp2TAxgpqfeUOyzrz47IWxRusXNptNWZanp6efmP2QVXvex8a8uby4cEwTwpx5Q7lPtgAMQ9+FTu7vE4iEJF4Z35L3/X57r8fQDGfscE95+5AEgBBj8MPQ7XaMyDDCAmRneh1IFCDIAYPHqv3BDUc0xglAiImNa6umbZdlVRvrkBglh7wm/XOMuyOmlDSnTTRrhxhyAF7xdpyYemUmMLMcETVvW0AQWYytXNEaVxOXQL3kIEOQOC32o1UQjZmvdKXeSkGCTwgsIoVhYAopSUrD0AGiJGEyjEYi9r4nIMuYTIjJxzREsQQsmmZvAIQj4b7v97f30e9j6OMwxJissZat48KxxRBEhsGnEKUfhmHYdl1/bW+tsXVZrtrF+WIly9PSlQKUEqAAjbeQOHea/Jhq1z06oyWZD07nL2huG1tb1tXq9AQQm6bZ3N4dtrvh0PV9N/QDIBpr0BhUfnGk4H0YNAdNYV2X/TWT88i1rLkoy7Zt2kXbtE1Rl8bq+pkiSyNNm4zDeYjVj2rlQ5KzvAyzy6wrJFoOa7hwLqZkbS5FlZkHQIhFYVfLhaSYt6ueAEnzFwgRJKKgQSqsKSw7Z+qyrJu6qauqrhXCzrcPcgW2HuZjC30mMYUhdATMYAB5pnre38VQYycgwEbb8cUgmZoVEopPATLJK0SOJRkXe/Ax3Nysr374/urdd7v7G4lD6aipi6ZuqrouytIcc/0QR+82sz7O/i/jm0ft/vD+a00BAgoBCMQEhEAgKNlYSJgSsjatBEgIidVmJkQZ+al0WyDtFi8GwCBaREtoCROxMbYoKldUxlo2rNTxMs5iHQnOFPdMzY/jzR7gPHb19LzSiLvykyjfquaoTyVPR8RyCtYLiGE2bKx1RZHrkcpivX53dXXV9/1+t0tjoHQYamZOSbQNjDZ/u7i4uLy81HKyf0A+/MfkvWOKhmM+++wzTVXb7XbKbL9cLjVd7uGE/In1+nS6Bw8r63piHsssF4uF94OI1HVdFKWywb969VLbtp6crFar5V/+8pfvvvvu5vbm0B1ubm+urtbr9frm5vry9vKzi4vlYlE3TTlmn0zcuhp/Kctyu93e3Nwoz7Rz7lMYhAiJifUiJqWlep4kRUJJkCCxMWQNGgYi5UqMKYaQ6SgxZeZmRJGYgowYZD6skj3DCKqTsgYmgAjIyiMCjJBQkozancYW0nRE5LNq13Ko9y4tivZtEUZyrnRlZVxhrFPIV6nQRjB4JJs1hnKNNVvrEMg5R8wELADWWMUr9BnS2GhjDhuMEDCgSCIRECY2zlpXsHFIDIBjcE0AEImnCKMao87ZeUpNDHEYgvcxJtFcM2MtEEY/pJTC4AmYkB3b0pWhd4euS8kn4Bh67w+9YUNIhoUxpZR8CsPBd7ttt992+xQ9Cihqidawdc6WZCxSBOA+xC6GfvA+xJCkHzwj+X5gwYaLVAs5JrYBE6Uw7Yh5x32EMD4ByGftDtmsgTEijYZt6aq6Pjk9bRbt2Yuz3Wa73+66/X6/2+23O0QsytI4S9YwEQL6vh/6jtm4wpWucIUjY8gYMtllVwoUpWxzhbPWMPORwBMIjjH8ae1OVfGgiRiPFvX8YrSMAgxTUTj1pQBAkiCIc26xbFNMxrCzBiZQZ4xjM/FyuSicdYUrq+rm9n67OwwxJgEmNgSWoSrsqq0XbdM2VVkW1uXGaDitqo+N72MSwnDoNo4dmgLFEgoIiybHjmbsaLUKgiRiddwFBCAFLwIpE7BEtVxjiJ5sSbbovd8edu9++H79w3e7u2vf7WpHbVW1TVM3TVGW1hXETCNNjGY5jMD7TLXru/lX0HK1B0QDAn4YQvDqsidhBY8EMSEyIIIEQMY40vsAIjBChJQIE2FM0bAgJUFMMUWJPnkf/RCGLgxhGJKQsICgMt5qXp4mjT5U2k/oQnnwcq7RP2YvatKWcqFPSeMz1f7Ubo6CgMxcEGlFeNXUi+VitVo2TfPu3bvr66u7u9u7u9u6rtu2RaIY4s3t7Waz1e4vb9680dS5H9uR/e+WbPIorexqtdKcwYy+jelyPwH4/gnjhPee2gTo6W4uUsFRPwkR1XX9+rU7PT199erVxcXF+fnZ73//+2+++evNzc3t7e2333771VdfvXz58vPPP9cWtEpgsFwuNdVRDxVC0MyvGOPV1dXNzU3btnNY/mODJqJHsfbRPyWUBERAEKyx1rIxwCSIEUQzlHlk76SxrElQIJvXojvnWPoE41rNPRNwvEVJRDBR7tQGytGph2UiItZa5jGgmvHw+RMXkSF4ESS2SgmZmaPYMjEh6CwBSWPcJMd3ENEYcU5EILpkjCWiYIIIWGsEgFmbW5bW2OnBPeG4Qw6lAQlbZmu0QiyBRImAiCCAbIwpm8VisWjb1jqbolhDc3ylH4btbhf6IYZg2RhmIAKEJJCixCEkjMayY9OUdfL7MOxCjJhCisPg9wdGwMSRE4EX38ch+j72h323OwRPqEhS4Zic8moZx2yIBYgPMe6DN8b7GAFRRHKpnA8CYIwti4qNi8GzMui938f2gfztIg0ZVTsbdkVRlEVVV0UqyiL/3DERkZZ8Nm1rVX8TIUIMIXhtjmKssdZY5DxZpkg7MxvO7cQmB1E/MU1+nLwsGXMsjtGDjwT0UAF9RiAEa3hkXzGJk4gFBGuNSDJMdVUYw5pSoJetc1n3awG01lVVfeg6H3PzGuUQrQrX1FVdlWWpLVzH8iqA492eRvhjVHzXdTe314UpSqd8y86QY7JEBvHYikOvP6NdyMxW1EoXUIpkEABIKJIixJRS3yWhbbe/327ubq72m1tIvnK2bYplU9d1U5aVcY6MzbH9sSJBAx8T9p6OClBGQsGcyvse3B1C9D4QEkWKnBJRRDSgMJLibpoqeGSlN0QGOTAEAsNgkgBFQYkSfQx9UMKgMEgKaNkWXC3KemGLiq0FxuzaA0C2M2ScRXlMcuRcVuaHfA3TdaUPP6vJddA8cJ2FE8A4XvTjOZkfFqGMmamk9OvOuaoqy7LQMq0YwmZzPy3W1Wr16tWrqQuqFp3/9Hp0Wpha+TaXh/GwfxMFr3J0A9QYmjt8KqpgiqLQZoFFUVRV/dVXf/7P//zm5uZmu92u12v1xb///vsXL168ePHi9PT05ORksVhoC11E7Pte6+uurq40NfLi4uL8/FwdUx3Jo7GNA0Aa/VEcm5Hmb0hu8pgoobgyVXXXNKauYb+L/SFEJYIU/drxmo/26TQdR+RQGTE0iK1EynkuE5Ix1tmy5LJk58gYNdyIOQ8PR9UONDZyP15OEtntOiLjClZ6lr4bnOtBEEwOptIImk1nHR8NWmuRWESIDSLaGCHXZUAsCkJ0zmpwEzH3pEjxuEZl3JmSpBB833WH/b7vuql4HbWAHAEpAqJ1xWK5apomCbDCGKNYa6u6GtjE4BEQiZImjIMkSCF6DqSNzJjI2bIqG6+E1sxBkk+BJWCKKaY+9J3vJAVIEa1xTWOYrTWOWW3zBBDICLEAEBsnUgNEZONKAMgUosa6smJXiDUDSvLDwQcfEysYDYzAkH8ezK4Pq3ZEHPkLtHLfMDvnCuecsyklJmLAOPiNABO5tm3a9uT01JYONUcqBz/SETU5ziSATBSMxDnyjjh26Tt+FvGpxTCp9vlon74IAEZkQsvoLAOyK5w2ZDPMRQwxRgIxhhZNVTgzlkDMQjgAhrlpGs2cyuWQSuaLyEQj9kBzB/fDo/oRur07HK7WobC2LIqqKMuiLFxtbWXIMZsxM5FmMXkFnNiAzaaQpKhQfE4QCzGGvo/7w3C/295v77vDHmNfWlOXbtHUi7ouytJah6xWjt7t0YrSOpPJo8hP96gWs15/FPYJIQUfEZMCXAGRc1ogzHj4UB0F3WYssyXjWCyDYWEioCQYfYx9DIfBdyFEQDHMRV00y3J5vli9KOuFcQ4JgbLvcmxUk/NyppdHx3z6SUe9joJKX/MxUXX+nvfwiaIAEjMZY6q6Wiza1Wq1Xq/X6/Xm/n6328WUiHixWJydnb958+bNmzcKxf9TU+I/RaZ1d3SY/vX++sfkPefy8fvqgDZN8/nnP1sslpeXl19//cs//elPf/7zn7/66ittdnd/f//tt9/Wda1hiNVqtVqtJqYgTaC7vb3d7XZE9PLly5///Odv3ryp6/oTxkfKo46IIvNEIp2lwhJTIioSNE23WBTLJR/2qT/EFCXmvYYg53RoWugUFJshe9mQldEdQM1DyUzMlq3DqrGLpVssTF1zUbC1isqoIzHm9CJiNvTnNzbFtN3srXWEdqAA0CFsQciXoXDaX3Nsyjg6dTHGscodNZgLeQtFNgwAmh5gABBHilImBMCUADDlNARNJ8jc8SGEvu/u7+5urq93m+3QDSkEiVEzbpJ4AA6DlySFK9tmCcSMyouRpW5bkLrvu77rg/chhBBDCJIQgTBC9GkgPR6hdUUNqxhDikkQBDkSRUJACCn2IQyDRwJrbOFc1ZJlY41lIgSIMcQQ0+jJAohjbq3jovbBK8IRQ7CGm7q2VR0N71I4HIbBx0Gw1Bg5GkSDyID8oCnXo+K32TLIhlBKSdnTEzNr60Zt2RklhMHv7jdrjQWuVkRknC3KkrQzDE1h5tk5csTl+AeaMqtGUQX//vyfNTp8Ynl8II8OEY0xTV2/OD/rvQckbUEpIqqhJSn9GTVVVVfVDJmZw93InPlWRWvhR9x+cmWePPlTo/wRm6D3ab8dBhP6g+9cXxadc31hD9aW1jhjjRoVytOERGqlC2h1nskl50gpxCTaViEhCEFgiAVJbcmBSwUXzlVFWVXak1SBrCe0Wo6mP8pafIhcqzalhx/AmNlhBCUKSEpRibF0WdOo2hFAtwBdA5atcsEbJiARSENKPklEA2VVVrWrm6pZls3StauqPanaJdsCmAVAy2amGy6zDU7bV+vz0K4wknu95WJ3EY0sfJJ8QLH9bRuOCBENorZvNFr8tlwu7+5uN/cbVe3L1ers7Fwp5x6mzv2IEz29ZH6cHLFuHCuXHv7p31PysOdaHB4pe/11yp9QMsHz8/PLy8s3b94osd39/f1+v/feK96uH55a0041gYh4enr6I4eIU0FbLjx+ICJAjIQGsIK4SjGIc1WzWPXdIflBnUKQhJIA1BsfUaPJj5pFM2ECM3OfDlJmN7bOVXXdLNrFSXtyWrYLU5RkHGq3maOnfbyXc78rpXR7c+tcCUApQhjCYXdYv1sT5mKYUTXThG9NKNex0cPYznUqh8oXMPV0IgKATFET9d9RvWtjj+CHvr+5vb26urq+uvb9EEPSvk+SPRPfHfb77faw2zV148rKsDmScABcvHzj/uNkt91ttvfbzWa33w59N3ifUgQRRGJCdQFNURSxijFIikmbmwEqy6aAmBi4LIvQaEoHEzGyIWZS01yUOignABACAMdQhNAGn1KuchJJTOisLcsSyioCpoRoxKExRYVsQb2kDEx/zGvHowbNULwoDUCM0TpnrBYUISLGEHfb7fV6/d03fwVEY+3y5EQAgFBz5dQulOlwegIRkNznJKMxeAThp7kzxZE/LYb39M4luXTSLBaLsihjigKgOXygiiqJpAwqaNeWnEz3EGt67wYZ5ski/vCm+Q/Y72KEvgffhx79gXtrD84enCsKV7qiLItiZNlU8hcDyLl3BGT+H0RENB69xCBpgAREYg1CwQaL0kFKlYgYY60C/saSZjjk2rkHtxNmCYuPUhen37Nt/+BCAFMGQkFSCjH0wxCiTzFpwzGakHlM2rI563VjrbGGrVVXFTGIJDK2bqvlanX2Ynly1rSrsm7J1exKsgUZg5RbCE+w5JOPZQwlYKafy/WhmBAEMIkmDfxokU/tqJHnDhE7h8aYuqratj07P99uN/vRa2+adrFY1HXzAb3+r5F/k2H8f8jjkc/fQURNJmia5vLy8ssvv/zVr371179mVru3b9++e/fu6urq7u5ut9vNy2XVu9X0CyU20FLAT0mJGAPYWZ7Y8UQAiQwZsoy2KOvVyfl+tx36LoQhxZBS0L0MlINJjpMQx0SrCZ4/nimr0pwaTNZaW7iicmXlysq6IrOHwTF3F466Pa/1aYwxxuurm7IsCSmFZK07HPr7+03fDyEE1MZM+bQPtvo8SGWDnt0HmJ3x4WMawXeRKVis+T+ibrv3XdcpsVLwforBAQgkSBK63W7D5m6xKItiSeT4wTN69frzVy//5+3tzfXNer3+4ebm6nDYDUOv51X1qWS/MBJXTu1aBEkIcTQ+ZCzgpmMeME2JtTL7T92aJCKQ6WdRqwUyYaZSkkoUcU4EicCwKck6IkPIuf/VR1T7/LYKQJSonQ299zGl2tmyKo2xSISSQvCb+/vN3X2/74qqdM7ZwuFknh2TKkf4brQjcXydLWiiKcj66CmOAUrAhxbCcaqNQPDTose0iIY56dQfIf8po2Q6zYc3rEfbwXRRmNuPPfrqB42DR/KR0RtA4+OQgkfwzKFw4nzq+mC7vnCucNZZ45y1rjDWGXZTmVq+HmIywIhAmKJABBEQEsOIzhiTA+dEhsYQvibSyKR5xhS5McPw+KcHKf+C4+p54no677th0NUXY/TB96EPUXv4oiFi0gADECITikE0WhlgxJjEJmk+jrHOFbZqmtVpuzptT86axbIsautKYCtkgA2oQQmgWMATmaM4hdJFJgT+6LKLCM4ogX60DvtkrXfcxo+8UMyuKKqqGpa9iAAqS12pKWBPrI6fWv6LavQfsRJV6ygxkcbgNdfh+vp6vV6/G0WpirQ7HABoZWDTNKenp9rK9vXr3GjuE0b3vl4fd7aZbY2IxIzkipKMsUVZt4sQQ4whSZLM7DZmi+Q98UEtUb4Pk77HTFUCEybPzGxIWyZyDrTrYpoIyqe593gSppT2++3gB0QMIdR1632IwXeH/W63S5LGC32gZcZDaWn28W/zk8w/PF5Nhm8FQGaqHcY2t9qN95HfpZ03Yhj6w353d3NdOOecc4bmetAVdduexoQhiQ8iyGW308IKGOMZudY+82KMiIBGQzA7jZqQhSMmAzBep7qED68lv84LPG+0ODUMAEiQQhoZ3YEIjBZ4lWXT1G1ZlPPyHJVHgPwY/FCDKEkKMfjglWWpLEu2BgkhoQ9hs9lsN1uJSSkei6okw6OVQrnbFtBk7IE6Z0dDUtEINeWIpnzm45ObdUDKfQfhKfmghz1/wUCjvs2oFIyu5HSX8zz7NJnPnE+I+3/s609+BYnJlD7KENTBTSFhSEgUCPvCsrOmsFw4W5SFK0rnKmsLrTLI9WIEBGyQECGSIEhMaTRuCMSCKjAkGOvrRATGFNQ8zlG1w3jrjmOXKQYA04p7T7+LyGHw+24QyQjQELyPQxJBJiZyiAYECA0TMJIlsSzGiXGJbTIuskV2ZAoummZ1slidLc9fLFanRdW6otRoTgROSIIkAAKaNYNwBOTH+4tjWAFG83jU4hmW10C7RvKeNrv+UepN5/7RBEREVeFFUeQlnGuK+dHu9uPG8C+1Bv4LyTHooDPZOXd2drZard68eTNF09fr9du3b9++fau9A7z3IlJVVdu2q9XqxYsXb9680RrFtm1ntf4ffARzp/3RH+UYw0MEADLWsjG2kLpVJqcZmJYbIo7r74n45XEZTF2zdY3gpGIpI+B5QIKQPmX2iEjXH3DolaOeiIiMdZaYYgze+7F99vuqGsfkANVpk16HGZ4xf2d+xrl2z/U62ml+3klvBIBhTBdKKfXd4f721rlisVhUZSHCcFQ0TOysLcuiaZohCZRlHcKQPYHcLHLU6zA22dUuPZh9nDRDEzRjHOFowEzK7wEGCijH5ncyU+36VoqSoiiPHiIQk2FyhavKoi7L2lpLD3kUHqj27m4rM5c6peSHgXbDy/akecVt2y7Jyd3+4CWlBJvDkgs5e3HiqrKuVrZyfYL7Qzx4IY6j0z651zCPn+SHAw/ePyIuT+nw0X0c433TuwgA/WY3fdB7/7vf/e5xHu+DY8H4HOfv/qsLeJRYdPp1GOLdrg8+Bo+SCAAHwYNPCIAYmaLhYBgNs7Edm73JFvdYh6pHEWWhSCkFJW4VzfDXZNl8B2hsnIOjzX8E5KfJlxfStGFM2n72ls7mfR+mq0CiVxcXg/e64GJKMcYoUZexht80DTfDPay5NppDYIj0I9oyng1G8ft+cw3+cLCO2eC4KUxFd5nwFuF9va6DPRorMF3E5OpogEtGvqrUH6Zvrtfr3/zmN//YJz6N6uFvD62+v3tO3t7eHg01kT/84Q/ffPPN33nMf4lcXV1Nr+/v73/729/+ZKdW8PJwOOz3+8PhgIhaRqtcp2qTaeO+t2/fKnWgbkGPH5/yD06/7vabqS0KTGHy4y54hBVhjlwe/aPZvzC3wD/sCsHoQ8LoJM7+cHyR8S+Zn+oIBIAMfT99rSyK//O//jcAWmvLsqrrhoglpcOh2+/3cdZdbQYmPDijPDJeH8QUplHDdCf0xQQhjit7toAe3PxjjQ8QUVFWTduenjZ1xfNPXV3/3yRpGPq+Pxy6w9B3IYaUIsDsaYxbo3rqYwhk5gBNKCcAjH1XUSsTYD6i2VFldDWn0aJkvz9vUNrMRgCUM5OS8DBsJbkkN11XbrfvHtzWX//61/Asz/Isz/Isz/Is/13kpyS+eJZneZZneZZneZZ/ujyr9md5lmd5lmd5lv9W8qzan+VZnuVZnuVZ/lvJ/wN4eZBNCmVuZHN0cmVhbQplbmRvYmoKMzYgMCBvYmoKMjQzNjk0CmVuZG9iagoyIDAgb2JqCjw8IC9Db3VudCAxIC9LaWRzIFsgMTEgMCBSIF0gL1R5cGUgL1BhZ2VzID4+CmVuZG9iagozNyAwIG9iago8PCAvQ3JlYXRpb25EYXRlIChEOjIwMjExMjA0MTY1OTE3KzAyJzAwJykKL0NyZWF0b3IgKE1hdHBsb3RsaWIgdjMuNC4zLCBodHRwczovL21hdHBsb3RsaWIub3JnKQovUHJvZHVjZXIgKE1hdHBsb3RsaWIgcGRmIGJhY2tlbmQgdjMuNC4zKSA+PgplbmRvYmoKeHJlZgowIDM4CjAwMDAwMDAwMDAgNjU1MzUgZiAKMDAwMDAwMDAxNiAwMDAwMCBuIAowMDAwMjUxMTE3IDAwMDAwIG4gCjAwMDAwMDY5NjYgMDAwMDAgbiAKMDAwMDAwNjk5OCAwMDAwMCBuIAowMDAwMDA3MDk3IDAwMDAwIG4gCjAwMDAwMDcxMTggMDAwMDAgbiAKMDAwMDAwNzEzOSAwMDAwMCBuIAowMDAwMDAwMDY1IDAwMDAwIG4gCjAwMDAwMDAzOTkgMDAwMDAgbiAKMDAwMDAwMDczMyAwMDAwMCBuIAowMDAwMDAwMjA4IDAwMDAwIG4gCjAwMDAwMDA3MTMgMDAwMDAgbiAKMDAwMDAwNzE3MSAwMDAwMCBuIAowMDAwMDA1NzAyIDAwMDAwIG4gCjAwMDAwMDU1MDIgMDAwMDAgbiAKMDAwMDAwNTEwNiAwMDAwMCBuIAowMDAwMDA2NzU1IDAwMDAwIG4gCjAwMDAwMDA3NTMgMDAwMDAgbiAKMDAwMDAwMDkxNiAwMDAwMCBuIAowMDAwMDAxMjI0IDAwMDAwIG4gCjAwMDAwMDEzNzIgMDAwMDAgbiAKMDAwMDAwMTQ5NSAwMDAwMCBuIAowMDAwMDAxODAwIDAwMDAwIG4gCjAwMDAwMDIxODAgMDAwMDAgbiAKMDAwMDAwMjUwMiAwMDAwMCBuIAowMDAwMDAyNjIxIDAwMDAwIG4gCjAwMDAwMDI5NTIgMDAwMDAgbiAKMDAwMDAwMzE4OCAwMDAwMCBuIAowMDAwMDAzNDc5IDAwMDAwIG4gCjAwMDAwMDM2MzQgMDAwMDAgbiAKMDAwMDAwMzk0NiAwMDAwMCBuIAowMDAwMDA0MzUzIDAwMDAwIG4gCjAwMDAwMDQ0NDMgMDAwMDAgbiAKMDAwMDAwNDYwNCAwMDAwMCBuIAowMDAwMDA0ODE4IDAwMDAwIG4gCjAwMDAyNTEwOTQgMDAwMDAgbiAKMDAwMDI1MTE3NyAwMDAwMCBuIAp0cmFpbGVyCjw8IC9JbmZvIDM3IDAgUiAvUm9vdCAxIDAgUiAvU2l6ZSAzOCA+PgpzdGFydHhyZWYKMjUxMzM0CiUlRU9GCg==\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"300.018787pt\" version=\"1.1\" viewBox=\"0 0 684 300.018787\" width=\"684pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:59:16.867016</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 300.018787 \n", "L 684 300.018787 \n", "L 684 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g clip-path=\"url(#p2ce0060c89)\">\n", "    <image height=\"271\" id=\"imagea6f788449c\" transform=\"scale(1 -1)translate(0 -271)\" width=\"670\" x=\"7.2\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.818787\"/>\n", "   </g>\n", "   <g id=\"text_1\">\n", "    <!-- Anomaly examples on CIFAR100 -->\n", "    <g transform=\"translate(244.94625 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 2188 4044 \n", "L 1331 1722 \n", "L 3047 1722 \n", "L 2188 4044 \n", "z\n", "M 1831 4666 \n", "L 2547 4666 \n", "L 4325 0 \n", "L 3669 0 \n", "L 3244 1197 \n", "L 1141 1197 \n", "L 716 0 \n", "L 50 0 \n", "L 1831 4666 \n", "z\n", "\" id=\"DejaVuSans-41\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-6e\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" id=\"DejaVuSans-6f\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" id=\"DejaVuSans-6d\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-6c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" id=\"DejaVuSans-79\" transform=\"scale(0.015625)\"/>\n", "      <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 3500 \n", "L 2247 1797 \n", "L 3578 0 \n", "L 2900 0 \n", "L 1881 1375 \n", "L 863 0 \n", "L 184 0 \n", "L 1544 1831 \n", "L 300 3500 \n", "L 978 3500 \n", "L 1906 2253 \n", "L 2834 3500 \n", "L 3513 3500 \n", "z\n", "\" id=\"DejaVuSans-78\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1159 525 \n", "L 1159 -1331 \n", "L 581 -1331 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "z\n", "M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "\" id=\"DejaVuSans-70\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" id=\"DejaVuSans-73\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 4122 4306 \n", "L 4122 3641 \n", "Q 3803 3938 3442 4084 \n", "Q 3081 4231 2675 4231 \n", "Q 1875 4231 1450 3742 \n", "Q 1025 3253 1025 2328 \n", "Q 1025 1406 1450 917 \n", "Q 1875 428 2675 428 \n", "Q 3081 428 3442 575 \n", "Q 3803 722 4122 1019 \n", "L 4122 359 \n", "Q 3791 134 3420 21 \n", "Q 3050 -91 2638 -91 \n", "Q 1578 -91 968 557 \n", "Q 359 1206 359 2328 \n", "Q 359 3453 968 4101 \n", "Q 1578 4750 2638 4750 \n", "Q 3056 4750 3426 4639 \n", "Q 3797 4528 4122 4306 \n", "z\n", "\" id=\"DejaVuSans-43\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-49\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 3309 4666 \n", "L 3309 4134 \n", "L 1259 4134 \n", "L 1259 2759 \n", "L 3109 2759 \n", "L 3109 2228 \n", "L 1259 2228 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-46\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2841 2188 \n", "Q 3044 2119 3236 1894 \n", "Q 3428 1669 3622 1275 \n", "L 4263 0 \n", "L 3584 0 \n", "L 2988 1197 \n", "Q 2756 1666 2539 1819 \n", "Q 2322 1972 1947 1972 \n", "L 1259 1972 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "L 2053 4666 \n", "Q 2853 4666 3247 4331 \n", "Q 3641 3997 3641 3322 \n", "Q 3641 2881 3436 2590 \n", "Q 3231 2300 2841 2188 \n", "z\n", "M 1259 4147 \n", "L 1259 2491 \n", "L 2053 2491 \n", "Q 2509 2491 2742 2702 \n", "Q 2975 2913 2975 3322 \n", "Q 2975 3731 2742 3939 \n", "Q 2509 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "\" id=\"DejaVuSans-52\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-41\"/>\n", "     <use x=\"68.408203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"131.787109\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"192.96875\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"290.380859\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"351.660156\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"379.443359\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"438.623047\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"470.410156\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"530.183594\" xlink:href=\"#DejaVuSans-78\"/>\n", "     <use x=\"589.363281\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"650.642578\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"748.054688\" xlink:href=\"#DejaVuSans-70\"/>\n", "     <use x=\"811.53125\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"839.314453\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"900.837891\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"952.9375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"984.724609\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1045.90625\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1109.285156\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1141.072266\" xlink:href=\"#DejaVuSans-43\"/>\n", "     <use x=\"1210.896484\" xlink:href=\"#DejaVuSans-49\"/>\n", "     <use x=\"1240.388672\" xlink:href=\"#DejaVuSans-46\"/>\n", "     <use x=\"1288.783203\" xlink:href=\"#DejaVuSans-41\"/>\n", "     <use x=\"1357.191406\" xlink:href=\"#DejaVuSans-52\"/>\n", "     <use x=\"1426.673828\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"1490.296875\" xlink:href=\"#DejaVuSans-30\"/>\n", "     <use x=\"1553.919922\" xlink:href=\"#DejaVuSans-30\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"p2ce0060c89\">\n", "   <rect height=\"270.500662\" width=\"669.6\" x=\"7.2\" y=\"22.318125\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 864x576 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["def visualize_exmp(indices, orig_dataset):\n", "    images = [orig_dataset[idx][0] for idx in indices.reshape(-1)]\n", "    images = torch.stack(images, dim=0)\n", "    images = images * TORCH_DATA_STD + TORCH_DATA_MEANS\n", "\n", "    img_grid = torchvision.utils.make_grid(images, nrow=SET_SIZE, normalize=True, pad_value=0.5, padding=16)\n", "    img_grid = img_grid.permute(1, 2, 0)\n", "\n", "    plt.figure(figsize=(12, 8))\n", "    plt.title(\"Anomaly examples on CIFAR100\")\n", "    plt.imshow(img_grid)\n", "    plt.axis(\"off\")\n", "    plt.show()\n", "    plt.close()\n", "\n", "\n", "_, indices, _ = next(iter(test_anom_loader))\n", "visualize_exmp(indices[:4], test_set)"]}, {"cell_type": "markdown", "id": "48c08ca7", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.1952, "end_time": "2021-12-04T15:59:18.016890", "exception": false, "start_time": "2021-12-04T15:59:17.821690", "status": "completed"}, "tags": []}, "source": ["We can already see that for some sets the task might be easier than for others.\n", "Difficulties can especially arise if the anomaly is in a different, but yet visually similar class\n", "(e.g. train vs bus, flour vs worm, etc.\n", ").\n", "\n", "After having prepared the data, we can look closer at the model.\n", "Here, we have a classification of the whole set.\n", "For the prediction to be permutation-equivariant, we will output one logit for each image.\n", "Over these logits, we apply a softmax and train the anomaly image to have the highest score/probability.\n", "This is a bit different than a standard classification layer as the softmax is applied over images,\n", "not over output classes in the classical sense.\n", "However, if we swap two images in their position, we effectively swap their position in the output softmax.\n", "Hence, the prediction is equivariant with respect to the input.\n", "We implement this idea below in the subclass of the Transformer Lightning module."]}, {"cell_type": "code", "execution_count": 34, "id": "cad86c76", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:18.412870Z", "iopub.status.busy": "2021-12-04T15:59:18.412388Z", "iopub.status.idle": "2021-12-04T15:59:18.414272Z", "shell.execute_reply": "2021-12-04T15:59:18.413887Z"}, "lines_to_next_cell": 2, "papermill": {"duration": 0.20176, "end_time": "2021-12-04T15:59:18.414384", "exception": false, "start_time": "2021-12-04T15:59:18.212624", "status": "completed"}, "tags": []}, "outputs": [], "source": ["class AnomalyPredictor(TransformerPredictor):\n", "    def _calculate_loss(self, batch, mode=\"train\"):\n", "        img_sets, _, labels = batch\n", "        # No positional encodings as it is a set, not a sequence!\n", "        preds = self.forward(img_sets, add_positional_encoding=False)\n", "        preds = preds.squeeze(dim=-1)  # Shape: [Batch_size, set_size]\n", "        loss = F.cross_entropy(preds, labels)  # Softmax/CE over set dimension\n", "        acc = (preds.argmax(dim=-1) == labels).float().mean()\n", "        self.log(\"%s_loss\" % mode, loss)\n", "        self.log(\"%s_acc\" % mode, acc, on_step=False, on_epoch=True)\n", "        return loss, acc\n", "\n", "    def training_step(self, batch, batch_idx):\n", "        loss, _ = self._calculate_loss(batch, mode=\"train\")\n", "        return loss\n", "\n", "    def validation_step(self, batch, batch_idx):\n", "        _ = self._calculate_loss(batch, mode=\"val\")\n", "\n", "    def test_step(self, batch, batch_idx):\n", "        _ = self._calculate_loss(batch, mode=\"test\")"]}, {"cell_type": "markdown", "id": "d732d394", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.190651, "end_time": "2021-12-04T15:59:18.796683", "exception": false, "start_time": "2021-12-04T15:59:18.606032", "status": "completed"}, "tags": []}, "source": ["Finally, we write our train function below.\n", "It has the exact same structure as the reverse task one, hence not much of an explanation is needed here."]}, {"cell_type": "code", "execution_count": 35, "id": "261279ac", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:19.193945Z", "iopub.status.busy": "2021-12-04T15:59:19.193455Z", "iopub.status.idle": "2021-12-04T15:59:19.195328Z", "shell.execute_reply": "2021-12-04T15:59:19.194922Z"}, "papermill": {"duration": 0.207853, "end_time": "2021-12-04T15:59:19.195437", "exception": false, "start_time": "2021-12-04T15:59:18.987584", "status": "completed"}, "tags": []}, "outputs": [], "source": ["def train_anomaly(**kwargs):\n", "    # Create a PyTorch Lightning trainer with the generation callback\n", "    root_dir = os.path.join(CHECKPOINT_PATH, \"SetAnomalyTask\")\n", "    os.makedirs(root_dir, exist_ok=True)\n", "    trainer = pl.Trainer(\n", "        default_root_dir=root_dir,\n", "        callbacks=[ModelCheckpoint(save_weights_only=True, mode=\"max\", monitor=\"val_acc\")],\n", "        gpus=1 if str(device).startswith(\"cuda\") else 0,\n", "        max_epochs=100,\n", "        gradient_clip_val=2,\n", "        progress_bar_refresh_rate=1,\n", "    )\n", "    trainer.logger._default_hp_metric = None  # Optional logging argument that we don't need\n", "\n", "    # Check whether pretrained model exists. If yes, load it and skip training\n", "    pretrained_filename = os.path.join(CHECKPOINT_PATH, \"SetAnomalyTask.ckpt\")\n", "    if os.path.isfile(pretrained_filename):\n", "        print(\"Found pretrained model, loading...\")\n", "        model = AnomalyPredictor.load_from_checkpoint(pretrained_filename)\n", "    else:\n", "        model = AnomalyPredictor(max_iters=trainer.max_epochs * len(train_anom_loader), **kwargs)\n", "        trainer.fit(model, train_anom_loader, val_anom_loader)\n", "        model = AnomalyPredictor.load_from_checkpoint(trainer.checkpoint_callback.best_model_path)\n", "\n", "    # Test best model on validation and test set\n", "    train_result = trainer.test(model, test_dataloaders=train_anom_loader, verbose=False)\n", "    val_result = trainer.test(model, test_dataloaders=val_anom_loader, verbose=False)\n", "    test_result = trainer.test(model, test_dataloaders=test_anom_loader, verbose=False)\n", "    result = {\n", "        \"test_acc\": test_result[0][\"test_acc\"],\n", "        \"val_acc\": val_result[0][\"test_acc\"],\n", "        \"train_acc\": train_result[0][\"test_acc\"],\n", "    }\n", "\n", "    model = model.to(device)\n", "    return model, result"]}, {"cell_type": "markdown", "id": "3a251275", "metadata": {"papermill": {"duration": 0.192005, "end_time": "2021-12-04T15:59:19.580159", "exception": false, "start_time": "2021-12-04T15:59:19.388154", "status": "completed"}, "tags": []}, "source": ["Let's finally train our model.\n", "We will use 4 layers with 4 attention heads each.\n", "The hidden dimensionality of the model is 256, and we use a dropout of 0.1 throughout the model for good regularization.\n", "Note that we also apply the dropout on the input features, as this makes the model more robust against\n", "image noise and generalizes better.\n", "Again, we use warmup to slowly start our model training."]}, {"cell_type": "code", "execution_count": 36, "id": "adc7b1bb", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:19.979138Z", "iopub.status.busy": "2021-12-04T15:59:19.978661Z", "iopub.status.idle": "2021-12-04T15:59:25.752247Z", "shell.execute_reply": "2021-12-04T15:59:25.752638Z"}, "papermill": {"duration": 5.981928, "end_time": "2021-12-04T15:59:25.752808", "exception": false, "start_time": "2021-12-04T15:59:19.770880", "status": "completed"}, "tags": []}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["/home/AzDevOps_azpcontainer/.local/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/callback_connector.py:90: LightningDeprecationWarning: Setting `Trainer(progress_bar_refresh_rate=1)` is deprecated in v1.5 and will be removed in v1.7. Please pass `pytorch_lightning.callbacks.progress.TQDMProgressBar` with `refresh_rate` directly to the Trainer's `callbacks` argument instead. Or, to disable the progress bar pass `enable_progress_bar = False` to the Trainer.\n", "  rank_zero_deprecation(\n", "GPU available: True, used: True\n"]}, {"name": "stderr", "output_type": "stream", "text": ["TPU available: False, using: 0 TPU cores\n"]}, {"name": "stderr", "output_type": "stream", "text": ["IPU available: False, using: 0 IPUs\n"]}, {"name": "stderr", "output_type": "stream", "text": ["/home/AzDevOps_azpcontainer/.local/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:901: LightningDeprecationWarning: `trainer.test(test_dataloaders)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.test(dataloaders)` instead.\n", "  rank_zero_deprecation(\n", "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n"]}, {"name": "stderr", "output_type": "stream", "text": ["Missing logger folder: saved_models/Transformers/SetAnomalyTask/lightning_logs\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Found pretrained model, loading...\n"]}, {"name": "stderr", "output_type": "stream", "text": ["/home/AzDevOps_azpcontainer/.local/lib/python3.9/site-packages/pytorch_lightning/trainer/data_loading.py:453: UserWarning: Your `test_dataloader` has `shuffle=True`,it is strongly recommended that you turn this off for val/test/predict dataloaders.\n", "  rank_zero_warn(\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "9c0f4106b2fa430d807e9c34f98e5bd2", "version_major": 2, "version_minor": 0}, "text/plain": ["Testing: 0it [00:00, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stderr", "output_type": "stream", "text": ["LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "983722707bb64460bfbdc38056f7d32d", "version_major": 2, "version_minor": 0}, "text/plain": ["Testing: 0it [00:00, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}, {"name": "stderr", "output_type": "stream", "text": ["LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n"]}, {"data": {"application/vnd.jupyter.widget-view+json": {"model_id": "ab0dc6637c5348a9839eded7ec182961", "version_major": 2, "version_minor": 0}, "text/plain": ["Testing: 0it [00:00, ?it/s]"]}, "metadata": {}, "output_type": "display_data"}], "source": ["anomaly_model, anomaly_result = train_anomaly(\n", "    input_dim=train_anom_dataset.img_feats.shape[-1],\n", "    model_dim=256,\n", "    num_heads=4,\n", "    num_classes=1,\n", "    num_layers=4,\n", "    dropout=0.1,\n", "    input_dropout=0.1,\n", "    lr=5e-4,\n", "    warmup=100,\n", ")"]}, {"cell_type": "markdown", "id": "b752953a", "metadata": {"papermill": {"duration": 0.212151, "end_time": "2021-12-04T15:59:26.177915", "exception": false, "start_time": "2021-12-04T15:59:25.965764", "status": "completed"}, "tags": []}, "source": ["We can print the achieved accuracy below."]}, {"cell_type": "code", "execution_count": 37, "id": "0c9ae3d1", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:26.590345Z", "iopub.status.busy": "2021-12-04T15:59:26.589872Z", "iopub.status.idle": "2021-12-04T15:59:26.592352Z", "shell.execute_reply": "2021-12-04T15:59:26.591950Z"}, "papermill": {"duration": 0.211453, "end_time": "2021-12-04T15:59:26.592461", "exception": false, "start_time": "2021-12-04T15:59:26.381008", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Train accuracy: 96.33%\n", "Val accuracy:   95.92%\n", "Test accuracy:  94.41%\n"]}], "source": ["print(\"Train accuracy: %4.2f%%\" % (100.0 * anomaly_result[\"train_acc\"]))\n", "print(\"Val accuracy:   %4.2f%%\" % (100.0 * anomaly_result[\"val_acc\"]))\n", "print(\"Test accuracy:  %4.2f%%\" % (100.0 * anomaly_result[\"test_acc\"]))"]}, {"cell_type": "markdown", "id": "93d2718b", "metadata": {"papermill": {"duration": 0.201663, "end_time": "2021-12-04T15:59:26.995547", "exception": false, "start_time": "2021-12-04T15:59:26.793884", "status": "completed"}, "tags": []}, "source": ["With ~94% validation and test accuracy, the model generalizes quite well.\n", "It should be noted that you might see slightly different scores depending on what computer/device you are running this notebook.\n", "This is because despite setting the seed before generating the test dataset, it is not the same across platforms and numpy versions.\n", "Nevertheless, we can conclude that the model performs quite well and can solve the task for most sets.\n", "Before trying to interpret the model, let's verify that our model is permutation-equivariant,\n", "and assigns the same predictions for different permutations of the input set.\n", "For this, we sample a batch from the test set and run it through the model to obtain the probabilities."]}, {"cell_type": "code", "execution_count": 38, "id": "dccefbde", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:27.411424Z", "iopub.status.busy": "2021-12-04T15:59:27.410941Z", "iopub.status.idle": "2021-12-04T15:59:27.581026Z", "shell.execute_reply": "2021-12-04T15:59:27.581442Z"}, "papermill": {"duration": 0.381038, "end_time": "2021-12-04T15:59:27.581610", "exception": false, "start_time": "2021-12-04T15:59:27.200572", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Preds\n", " [2.7691365e-05 1.8979923e-05 1.7386470e-05 2.7843047e-05 1.6143023e-05\n", " 1.7020926e-05 5.7294892e-05 9.9977750e-01 2.1365197e-05 1.8681889e-05]\n", "Permuted preds\n", " [2.7691472e-05 1.8979976e-05 1.7386521e-05 2.7843154e-05 1.6143069e-05\n", " 1.7020990e-05 5.7295114e-05 9.9977750e-01 2.1365277e-05 1.8681943e-05]\n"]}], "source": ["inp_data, indices, labels = next(iter(test_anom_loader))\n", "inp_data = inp_data.to(device)\n", "\n", "anomaly_model.eval()\n", "\n", "with torch.no_grad():\n", "    preds = anomaly_model.forward(inp_data, add_positional_encoding=False)\n", "    preds = F.softmax(preds.squeeze(dim=-1), dim=-1)\n", "\n", "    # Permut input data\n", "    permut = np.random.permutation(inp_data.shape[1])\n", "    perm_inp_data = inp_data[:, permut]\n", "    perm_preds = anomaly_model.forward(perm_inp_data, add_positional_encoding=False)\n", "    perm_preds = F.softmax(perm_preds.squeeze(dim=-1), dim=-1)\n", "\n", "assert (preds[:, permut] - perm_preds).abs().max() < 1e-5, \"Predictions are not permutation equivariant\"\n", "\n", "print(\"Preds\\n\", preds[0, permut].cpu().numpy())\n", "print(\"Permuted preds\\n\", perm_preds[0].cpu().numpy())"]}, {"cell_type": "markdown", "id": "e44810c4", "metadata": {"papermill": {"duration": 0.202216, "end_time": "2021-12-04T15:59:27.986209", "exception": false, "start_time": "2021-12-04T15:59:27.783993", "status": "completed"}, "tags": []}, "source": ["You can see that the predictions are almost exactly the same, and only differ because of slight numerical\n", "differences inside the network operation.\n", "\n", "To interpret the model a little more, we can plot the attention maps inside the model.\n", "This will give us an idea of what information the model is sharing/communicating between images,\n", "and what each head might represent.\n", "First, we need to extract the attention maps for the test batch above, and determine the discrete predictions for simplicity."]}, {"cell_type": "code", "execution_count": 39, "id": "a3aa3c54", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:28.404309Z", "iopub.status.busy": "2021-12-04T15:59:28.403839Z", "iopub.status.idle": "2021-12-04T15:59:28.411125Z", "shell.execute_reply": "2021-12-04T15:59:28.410728Z"}, "papermill": {"duration": 0.214883, "end_time": "2021-12-04T15:59:28.411233", "exception": false, "start_time": "2021-12-04T15:59:28.196350", "status": "completed"}, "tags": []}, "outputs": [], "source": ["attention_maps = anomaly_model.get_attention_maps(inp_data, add_positional_encoding=False)\n", "predictions = preds.argmax(dim=-1)"]}, {"cell_type": "markdown", "id": "53fdeaca", "metadata": {"lines_to_next_cell": 2, "papermill": {"duration": 0.203066, "end_time": "2021-12-04T15:59:28.821317", "exception": false, "start_time": "2021-12-04T15:59:28.618251", "status": "completed"}, "tags": []}, "source": ["Below we write a plot function which plots the images in the input set, the prediction of the model,\n", "and the attention maps of the different heads on layers of the transformer.\n", "Feel free to explore the attention maps for different input examples as well."]}, {"cell_type": "code", "execution_count": 40, "id": "73a6c7b3", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:29.243841Z", "iopub.status.busy": "2021-12-04T15:59:29.243370Z", "iopub.status.idle": "2021-12-04T15:59:32.280160Z", "shell.execute_reply": "2021-12-04T15:59:32.280550Z"}, "papermill": {"duration": 3.254644, "end_time": "2021-12-04T15:59:32.280702", "exception": false, "start_time": "2021-12-04T15:59:29.026058", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"100.469118pt\" version=\"1.1\" viewBox=\"0 0 684 100.469118\" width=\"684pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:59:29.364891</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 100.469118 \n", "L 684 100.469118 \n", "L 684 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g clip-path=\"url(#p674c230aa7)\">\n", "    <image height=\"71\" id=\"imageb2ff55a30a\" transform=\"scale(1 -1)translate(0 -71)\" width=\"670\" x=\"7.2\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-22.269118\"/>\n", "   </g>\n", "   <g id=\"text_1\">\n", "    <!-- Anomaly examples on CIFAR100 -->\n", "    <g transform=\"translate(244.94625 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 2188 4044 \n", "L 1331 1722 \n", "L 3047 1722 \n", "L 2188 4044 \n", "z\n", "M 1831 4666 \n", "L 2547 4666 \n", "L 4325 0 \n", "L 3669 0 \n", "L 3244 1197 \n", "L 1141 1197 \n", "L 716 0 \n", "L 50 0 \n", "L 1831 4666 \n", "z\n", "\" id=\"DejaVuSans-41\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-6e\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" id=\"DejaVuSans-6f\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" id=\"DejaVuSans-6d\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-6c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" id=\"DejaVuSans-79\" transform=\"scale(0.015625)\"/>\n", "      <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 3500 \n", "L 2247 1797 \n", "L 3578 0 \n", "L 2900 0 \n", "L 1881 1375 \n", "L 863 0 \n", "L 184 0 \n", "L 1544 1831 \n", "L 300 3500 \n", "L 978 3500 \n", "L 1906 2253 \n", "L 2834 3500 \n", "L 3513 3500 \n", "z\n", "\" id=\"DejaVuSans-78\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1159 525 \n", "L 1159 -1331 \n", "L 581 -1331 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "z\n", "M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "\" id=\"DejaVuSans-70\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" id=\"DejaVuSans-73\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 4122 4306 \n", "L 4122 3641 \n", "Q 3803 3938 3442 4084 \n", "Q 3081 4231 2675 4231 \n", "Q 1875 4231 1450 3742 \n", "Q 1025 3253 1025 2328 \n", "Q 1025 1406 1450 917 \n", "Q 1875 428 2675 428 \n", "Q 3081 428 3442 575 \n", "Q 3803 722 4122 1019 \n", "L 4122 359 \n", "Q 3791 134 3420 21 \n", "Q 3050 -91 2638 -91 \n", "Q 1578 -91 968 557 \n", "Q 359 1206 359 2328 \n", "Q 359 3453 968 4101 \n", "Q 1578 4750 2638 4750 \n", "Q 3056 4750 3426 4639 \n", "Q 3797 4528 4122 4306 \n", "z\n", "\" id=\"DejaVuSans-43\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-49\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 3309 4666 \n", "L 3309 4134 \n", "L 1259 4134 \n", "L 1259 2759 \n", "L 3109 2759 \n", "L 3109 2228 \n", "L 1259 2228 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-46\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2841 2188 \n", "Q 3044 2119 3236 1894 \n", "Q 3428 1669 3622 1275 \n", "L 4263 0 \n", "L 3584 0 \n", "L 2988 1197 \n", "Q 2756 1666 2539 1819 \n", "Q 2322 1972 1947 1972 \n", "L 1259 1972 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "L 2053 4666 \n", "Q 2853 4666 3247 4331 \n", "Q 3641 3997 3641 3322 \n", "Q 3641 2881 3436 2590 \n", "Q 3231 2300 2841 2188 \n", "z\n", "M 1259 4147 \n", "L 1259 2491 \n", "L 2053 2491 \n", "Q 2509 2491 2742 2702 \n", "Q 2975 2913 2975 3322 \n", "Q 2975 3731 2742 3939 \n", "Q 2509 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "\" id=\"DejaVuSans-52\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-41\"/>\n", "     <use x=\"68.408203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"131.787109\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"192.96875\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"290.380859\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"351.660156\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"379.443359\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"438.623047\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"470.410156\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"530.183594\" xlink:href=\"#DejaVuSans-78\"/>\n", "     <use x=\"589.363281\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"650.642578\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"748.054688\" xlink:href=\"#DejaVuSans-70\"/>\n", "     <use x=\"811.53125\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"839.314453\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"900.837891\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"952.9375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"984.724609\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1045.90625\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1109.285156\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1141.072266\" xlink:href=\"#DejaVuSans-43\"/>\n", "     <use x=\"1210.896484\" xlink:href=\"#DejaVuSans-49\"/>\n", "     <use x=\"1240.388672\" xlink:href=\"#DejaVuSans-46\"/>\n", "     <use x=\"1288.783203\" xlink:href=\"#DejaVuSans-41\"/>\n", "     <use x=\"1357.191406\" xlink:href=\"#DejaVuSans-52\"/>\n", "     <use x=\"1426.673828\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"1490.296875\" xlink:href=\"#DejaVuSans-30\"/>\n", "     <use x=\"1553.919922\" xlink:href=\"#DejaVuSans-30\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"p674c230aa7\">\n", "   <rect height=\"70.950993\" width=\"669.6\" x=\"7.2\" y=\"22.318125\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 864x576 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Prediction: 9\n"]}, {"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"698.51625pt\" version=\"1.1\" viewBox=\"0 0 670.400919 698.51625\" width=\"670.400919pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:59:30.887739</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 698.51625 \n", "L 670.400919 698.51625 \n", "L 670.400919 -0 \n", "L 0 -0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g id=\"patch_2\">\n", "    <path d=\"M 20.5625 140.921761 \n", "L 139.166136 140.921761 \n", "L 139.166136 22.318125 \n", "L 20.5625 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pd05ea679e7)\">\n", "    <image height=\"119\" id=\"image4f72d5cd2b\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_1\">\n", "    <g id=\"xtick_1\">\n", "     <g id=\"line2d_1\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L 0 3.5 \n", "\" id=\"mcee5d6d979\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_1\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_2\">\n", "     <g id=\"line2d_2\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_2\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_3\">\n", "     <g id=\"line2d_3\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_3\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" id=\"DejaVuSans-32\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_4\">\n", "     <g id=\"line2d_4\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_4\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" id=\"DejaVuSans-33\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_5\">\n", "     <g id=\"line2d_5\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_5\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" id=\"DejaVuSans-34\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_6\">\n", "     <g id=\"line2d_6\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_6\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" id=\"DejaVuSans-35\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_7\">\n", "     <g id=\"line2d_7\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_7\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" id=\"DejaVuSans-36\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_8\">\n", "     <g id=\"line2d_8\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_8\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" id=\"DejaVuSans-37\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_9\">\n", "     <g id=\"line2d_9\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_9\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" id=\"DejaVuSans-38\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_10\">\n", "     <g id=\"line2d_10\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_10\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" id=\"DejaVuSans-39\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_2\">\n", "    <g id=\"ytick_1\">\n", "     <g id=\"line2d_11\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L -3.5 0 \n", "\" id=\"m3743f94e5c\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_11\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_2\">\n", "     <g id=\"line2d_12\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_12\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_3\">\n", "     <g id=\"line2d_13\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_13\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_4\">\n", "     <g id=\"line2d_14\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_14\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_5\">\n", "     <g id=\"line2d_15\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_15\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_6\">\n", "     <g id=\"line2d_16\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_16\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_7\">\n", "     <g id=\"line2d_17\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_17\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_8\">\n", "     <g id=\"line2d_18\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_18\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_9\">\n", "     <g id=\"line2d_19\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_19\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_10\">\n", "     <g id=\"line2d_20\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_20\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_3\">\n", "    <path d=\"M 20.5625 140.921761 \n", "L 20.5625 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_4\">\n", "    <path d=\"M 139.166136 140.921761 \n", "L 139.166136 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_5\">\n", "    <path d=\"M 20.5625 140.921761 \n", "L 139.166136 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_6\">\n", "    <path d=\"M 20.5625 22.318125 \n", "L 139.166136 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_21\">\n", "    <!-- Layer 1, Head 1 -->\n", "    <g transform=\"translate(32.182131 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 531 \n", "L 3531 531 \n", "L 3531 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-4c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" id=\"DejaVuSans-79\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" id=\"DejaVuSans-72\" transform=\"scale(0.015625)\"/>\n", "      <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 750 794 \n", "L 1409 794 \n", "L 1409 256 \n", "L 897 -744 \n", "L 494 -744 \n", "L 750 256 \n", "L 750 794 \n", "z\n", "\" id=\"DejaVuSans-2c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 2753 \n", "L 3553 2753 \n", "L 3553 4666 \n", "L 4184 4666 \n", "L 4184 0 \n", "L 3553 0 \n", "L 3553 2222 \n", "L 1259 2222 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-48\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" id=\"DejaVuSans-64\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_2\">\n", "   <g id=\"patch_7\">\n", "    <path d=\"M 195.240761 140.921761 \n", "L 313.844397 140.921761 \n", "L 313.844397 22.318125 \n", "L 195.240761 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pd44a1ec703)\">\n", "    <image height=\"119\" id=\"image61aeef5b80\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "iVBORw0KGgoAAAANSUhEUgAAAHcAAAB3CAYAAAA5Od+KAAACTElEQVR4nO3csWpTYRyG8fMlp9ahHZwUQwfxBqSSzTFQdYhL3cWCF+DFeCEOBtE7CGpxlS6FljoVOqlNjENvoG/xX+Hx+c1vwkcevuUQTpu03VVX6O3RPNpPR+Oik9RrfR/tV4tF0UkuDEq/Xf+UccGMC2ZcMOOCGRfMuGDGBTMumHHBjAuWPQy9gmfTF9F+eOs42i9PTy8/Hgyj7+5+L7N9y+7K/fnNaH8w/hHtvblgxgUzLphxwYwLZlww44IZF8y4YMYFMy5Yq/7f8rujz9H+6Wi76CTXoLVsvyr96b25ZMYFMy6YccGMC2ZcMOOCGRfMuGDGBTMuWN/fuR19YHHyPdpPXr6K9uv9frSP3itR/Ox38WEr2veTw2if8uaCGRfMuGDGBTMumHHBjAtmXDDjghkXzLhg7fWX59ED1K/btf+1rXQ+eRjt1z5+KjrJ9fDmghkXzLhgxgUzLphxwYwLZlww44IZF6z8tQnvj/ej/c7dByXn+B95c8GMC2ZcMOOCGRfMuGDGBTMumHHBjAtmXLA+fZXAYGMj2k+/PY72XXcS7i+vrd2I9qvzX0UnufDzyTjar8/m0d6bC2ZcMOOCGRfMuGDGBTMumHHBjAtmXDDjgvXDzc3oA8uzs2j/5t4s2u91j6J9ovpZcSp9Vpzy5oIZF8y4YMYFMy6YccGMC2ZcMOOCGRfMuGDl78TQ35O+X8SbC2ZcMOOCGRfMuGDGBTMumHHBjAtmXDDjghkXzLhgxgUzLphxwYwLZlww44IZF8y4YMYFMy7YH2KXSAfUpXc9AAAAAElFTkSuQmCC\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_3\">\n", "    <g id=\"xtick_11\">\n", "     <g id=\"line2d_21\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_22\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_12\">\n", "     <g id=\"line2d_22\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_23\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_13\">\n", "     <g id=\"line2d_23\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_24\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_14\">\n", "     <g id=\"line2d_24\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_25\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_15\">\n", "     <g id=\"line2d_25\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_26\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_16\">\n", "     <g id=\"line2d_26\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_27\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_17\">\n", "     <g id=\"line2d_27\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_28\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_18\">\n", "     <g id=\"line2d_28\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_29\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_19\">\n", "     <g id=\"line2d_29\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_30\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_20\">\n", "     <g id=\"line2d_30\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_31\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_4\">\n", "    <g id=\"ytick_11\">\n", "     <g id=\"line2d_31\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_32\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_12\">\n", "     <g id=\"line2d_32\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_33\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_13\">\n", "     <g id=\"line2d_33\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_34\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_14\">\n", "     <g id=\"line2d_34\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_35\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_15\">\n", "     <g id=\"line2d_35\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_36\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_16\">\n", "     <g id=\"line2d_36\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_37\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_17\">\n", "     <g id=\"line2d_37\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_38\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_18\">\n", "     <g id=\"line2d_38\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_39\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_19\">\n", "     <g id=\"line2d_39\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_40\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_20\">\n", "     <g id=\"line2d_40\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_41\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_8\">\n", "    <path d=\"M 195.240761 140.921761 \n", "L 195.240761 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_9\">\n", "    <path d=\"M 313.844397 140.921761 \n", "L 313.844397 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_10\">\n", "    <path d=\"M 195.240761 140.921761 \n", "L 313.844397 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_11\">\n", "    <path d=\"M 195.240761 22.318125 \n", "L 313.844397 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_42\">\n", "    <!-- Layer 1, Head 2 -->\n", "    <g transform=\"translate(206.860392 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_3\">\n", "   <g id=\"patch_12\">\n", "    <path d=\"M 369.919022 140.921761 \n", "L 488.522658 140.921761 \n", "L 488.522658 22.318125 \n", "L 369.919022 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p81852aa511)\">\n", "    <image height=\"119\" id=\"image5c6711b716\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_5\">\n", "    <g id=\"xtick_21\">\n", "     <g id=\"line2d_41\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_43\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_22\">\n", "     <g id=\"line2d_42\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_44\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_23\">\n", "     <g id=\"line2d_43\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_45\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_24\">\n", "     <g id=\"line2d_44\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_46\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_25\">\n", "     <g id=\"line2d_45\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_47\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_26\">\n", "     <g id=\"line2d_46\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_48\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_27\">\n", "     <g id=\"line2d_47\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_49\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_28\">\n", "     <g id=\"line2d_48\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_50\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_29\">\n", "     <g id=\"line2d_49\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_51\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_30\">\n", "     <g id=\"line2d_50\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_52\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_6\">\n", "    <g id=\"ytick_21\">\n", "     <g id=\"line2d_51\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_53\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_22\">\n", "     <g id=\"line2d_52\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_54\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_23\">\n", "     <g id=\"line2d_53\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_55\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_24\">\n", "     <g id=\"line2d_54\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_56\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_25\">\n", "     <g id=\"line2d_55\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_57\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_26\">\n", "     <g id=\"line2d_56\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_58\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_27\">\n", "     <g id=\"line2d_57\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_59\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_28\">\n", "     <g id=\"line2d_58\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_60\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_29\">\n", "     <g id=\"line2d_59\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_61\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_30\">\n", "     <g id=\"line2d_60\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_62\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_13\">\n", "    <path d=\"M 369.919022 140.921761 \n", "L 369.919022 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_14\">\n", "    <path d=\"M 488.522658 140.921761 \n", "L 488.522658 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_15\">\n", "    <path d=\"M 369.919022 140.921761 \n", "L 488.522658 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_16\">\n", "    <path d=\"M 369.919022 22.318125 \n", "L 488.522658 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_63\">\n", "    <!-- Layer 1, Head 3 -->\n", "    <g transform=\"translate(381.538652 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_4\">\n", "   <g id=\"patch_17\">\n", "    <path d=\"M 544.597283 140.921761 \n", "L 663.200919 140.921761 \n", "L 663.200919 22.318125 \n", "L 544.597283 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p514c43ea0a)\">\n", "    <image height=\"119\" id=\"image5a6f4ae3d1\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_7\">\n", "    <g id=\"xtick_31\">\n", "     <g id=\"line2d_61\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_64\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_32\">\n", "     <g id=\"line2d_62\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_65\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_33\">\n", "     <g id=\"line2d_63\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_66\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_34\">\n", "     <g id=\"line2d_64\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_67\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_35\">\n", "     <g id=\"line2d_65\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_68\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_36\">\n", "     <g id=\"line2d_66\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_69\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_37\">\n", "     <g id=\"line2d_67\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_70\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_38\">\n", "     <g id=\"line2d_68\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_71\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_39\">\n", "     <g id=\"line2d_69\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_72\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_40\">\n", "     <g id=\"line2d_70\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#mcee5d6d979\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_73\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_8\">\n", "    <g id=\"ytick_31\">\n", "     <g id=\"line2d_71\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_74\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_32\">\n", "     <g id=\"line2d_72\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_75\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_33\">\n", "     <g id=\"line2d_73\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_76\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_34\">\n", "     <g id=\"line2d_74\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_77\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_35\">\n", "     <g id=\"line2d_75\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_78\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_36\">\n", "     <g id=\"line2d_76\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_79\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_37\">\n", "     <g id=\"line2d_77\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_80\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_38\">\n", "     <g id=\"line2d_78\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_81\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_39\">\n", "     <g id=\"line2d_79\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_82\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_40\">\n", "     <g id=\"line2d_80\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_83\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_18\">\n", "    <path d=\"M 544.597283 140.921761 \n", "L 544.597283 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_19\">\n", "    <path d=\"M 663.200919 140.921761 \n", "L 663.200919 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_20\">\n", "    <path d=\"M 544.597283 140.921761 \n", "L 663.200919 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_21\">\n", "    <path d=\"M 544.597283 22.318125 \n", "L 663.200919 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_84\">\n", "    <!-- Layer 1, Head 4 -->\n", "    <g transform=\"translate(556.216913 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_5\">\n", "   <g id=\"patch_22\">\n", "    <path d=\"M 20.5625 318.827216 \n", "L 139.166136 318.827216 \n", "L 139.166136 200.22358 \n", "L 20.5625 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p31481cd1b3)\">\n", "    <image height=\"119\" id=\"image1172e8a085\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_9\">\n", "    <g id=\"xtick_41\">\n", "     <g id=\"line2d_81\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_85\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_42\">\n", "     <g id=\"line2d_82\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_86\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_43\">\n", "     <g id=\"line2d_83\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_87\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_44\">\n", "     <g id=\"line2d_84\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_88\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_45\">\n", "     <g id=\"line2d_85\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_89\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_46\">\n", "     <g id=\"line2d_86\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_90\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_47\">\n", "     <g id=\"line2d_87\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_91\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_48\">\n", "     <g id=\"line2d_88\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_92\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_49\">\n", "     <g id=\"line2d_89\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_93\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_50\">\n", "     <g id=\"line2d_90\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_94\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_10\">\n", "    <g id=\"ytick_41\">\n", "     <g id=\"line2d_91\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_95\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_42\">\n", "     <g id=\"line2d_92\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_96\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_43\">\n", "     <g id=\"line2d_93\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_97\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_44\">\n", "     <g id=\"line2d_94\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_98\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_45\">\n", "     <g id=\"line2d_95\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_99\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_46\">\n", "     <g id=\"line2d_96\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_100\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_47\">\n", "     <g id=\"line2d_97\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_101\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_48\">\n", "     <g id=\"line2d_98\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_102\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_49\">\n", "     <g id=\"line2d_99\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_103\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_50\">\n", "     <g id=\"line2d_100\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_104\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_23\">\n", "    <path d=\"M 20.5625 318.827216 \n", "L 20.5625 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_24\">\n", "    <path d=\"M 139.166136 318.827216 \n", "L 139.166136 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_25\">\n", "    <path d=\"M 20.5625 318.827216 \n", "L 139.166136 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_26\">\n", "    <path d=\"M 20.5625 200.22358 \n", "L 139.166136 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_105\">\n", "    <!-- Layer 2, Head 1 -->\n", "    <g transform=\"translate(32.182131 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_6\">\n", "   <g id=\"patch_27\">\n", "    <path d=\"M 195.240761 318.827216 \n", "L 313.844397 318.827216 \n", "L 313.844397 200.22358 \n", "L 195.240761 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pbc0868af49)\">\n", "    <image height=\"119\" id=\"imageebf1f02f1d\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_11\">\n", "    <g id=\"xtick_51\">\n", "     <g id=\"line2d_101\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_106\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_52\">\n", "     <g id=\"line2d_102\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_107\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_53\">\n", "     <g id=\"line2d_103\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_108\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_54\">\n", "     <g id=\"line2d_104\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_109\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_55\">\n", "     <g id=\"line2d_105\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_110\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_56\">\n", "     <g id=\"line2d_106\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_111\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_57\">\n", "     <g id=\"line2d_107\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_112\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_58\">\n", "     <g id=\"line2d_108\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_113\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_59\">\n", "     <g id=\"line2d_109\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_114\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_60\">\n", "     <g id=\"line2d_110\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_115\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_12\">\n", "    <g id=\"ytick_51\">\n", "     <g id=\"line2d_111\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_116\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_52\">\n", "     <g id=\"line2d_112\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_117\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_53\">\n", "     <g id=\"line2d_113\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_118\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_54\">\n", "     <g id=\"line2d_114\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_119\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_55\">\n", "     <g id=\"line2d_115\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_120\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_56\">\n", "     <g id=\"line2d_116\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_121\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_57\">\n", "     <g id=\"line2d_117\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_122\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_58\">\n", "     <g id=\"line2d_118\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_123\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_59\">\n", "     <g id=\"line2d_119\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_124\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_60\">\n", "     <g id=\"line2d_120\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_125\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_28\">\n", "    <path d=\"M 195.240761 318.827216 \n", "L 195.240761 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_29\">\n", "    <path d=\"M 313.844397 318.827216 \n", "L 313.844397 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_30\">\n", "    <path d=\"M 195.240761 318.827216 \n", "L 313.844397 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_31\">\n", "    <path d=\"M 195.240761 200.22358 \n", "L 313.844397 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_126\">\n", "    <!-- Layer 2, Head 2 -->\n", "    <g transform=\"translate(206.860392 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_7\">\n", "   <g id=\"patch_32\">\n", "    <path d=\"M 369.919022 318.827216 \n", "L 488.522658 318.827216 \n", "L 488.522658 200.22358 \n", "L 369.919022 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p2024253e5d)\">\n", "    <image height=\"119\" id=\"image7e1201063e\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_13\">\n", "    <g id=\"xtick_61\">\n", "     <g id=\"line2d_121\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_127\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_62\">\n", "     <g id=\"line2d_122\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_128\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_63\">\n", "     <g id=\"line2d_123\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_129\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_64\">\n", "     <g id=\"line2d_124\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_130\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_65\">\n", "     <g id=\"line2d_125\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_131\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_66\">\n", "     <g id=\"line2d_126\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_132\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_67\">\n", "     <g id=\"line2d_127\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_133\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_68\">\n", "     <g id=\"line2d_128\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_134\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_69\">\n", "     <g id=\"line2d_129\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_135\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_70\">\n", "     <g id=\"line2d_130\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_136\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_14\">\n", "    <g id=\"ytick_61\">\n", "     <g id=\"line2d_131\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_137\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_62\">\n", "     <g id=\"line2d_132\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_138\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_63\">\n", "     <g id=\"line2d_133\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_139\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_64\">\n", "     <g id=\"line2d_134\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_140\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_65\">\n", "     <g id=\"line2d_135\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_141\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_66\">\n", "     <g id=\"line2d_136\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_142\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_67\">\n", "     <g id=\"line2d_137\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_143\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_68\">\n", "     <g id=\"line2d_138\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_144\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_69\">\n", "     <g id=\"line2d_139\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_145\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_70\">\n", "     <g id=\"line2d_140\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_146\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_33\">\n", "    <path d=\"M 369.919022 318.827216 \n", "L 369.919022 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_34\">\n", "    <path d=\"M 488.522658 318.827216 \n", "L 488.522658 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_35\">\n", "    <path d=\"M 369.919022 318.827216 \n", "L 488.522658 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_36\">\n", "    <path d=\"M 369.919022 200.22358 \n", "L 488.522658 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_147\">\n", "    <!-- Layer 2, Head 3 -->\n", "    <g transform=\"translate(381.538652 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_8\">\n", "   <g id=\"patch_37\">\n", "    <path d=\"M 544.597283 318.827216 \n", "L 663.200919 318.827216 \n", "L 663.200919 200.22358 \n", "L 544.597283 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pc489f1e530)\">\n", "    <image height=\"119\" id=\"image4fdd734d15\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_15\">\n", "    <g id=\"xtick_71\">\n", "     <g id=\"line2d_141\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_148\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_72\">\n", "     <g id=\"line2d_142\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_149\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_73\">\n", "     <g id=\"line2d_143\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_150\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_74\">\n", "     <g id=\"line2d_144\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_151\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_75\">\n", "     <g id=\"line2d_145\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_152\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_76\">\n", "     <g id=\"line2d_146\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_153\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_77\">\n", "     <g id=\"line2d_147\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_154\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_78\">\n", "     <g id=\"line2d_148\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_155\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_79\">\n", "     <g id=\"line2d_149\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_156\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_80\">\n", "     <g id=\"line2d_150\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#mcee5d6d979\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_157\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_16\">\n", "    <g id=\"ytick_71\">\n", "     <g id=\"line2d_151\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_158\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_72\">\n", "     <g id=\"line2d_152\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_159\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_73\">\n", "     <g id=\"line2d_153\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_160\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_74\">\n", "     <g id=\"line2d_154\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_161\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_75\">\n", "     <g id=\"line2d_155\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_162\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_76\">\n", "     <g id=\"line2d_156\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_163\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_77\">\n", "     <g id=\"line2d_157\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_164\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_78\">\n", "     <g id=\"line2d_158\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_165\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_79\">\n", "     <g id=\"line2d_159\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_166\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_80\">\n", "     <g id=\"line2d_160\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_167\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_38\">\n", "    <path d=\"M 544.597283 318.827216 \n", "L 544.597283 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_39\">\n", "    <path d=\"M 663.200919 318.827216 \n", "L 663.200919 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_40\">\n", "    <path d=\"M 544.597283 318.827216 \n", "L 663.200919 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_41\">\n", "    <path d=\"M 544.597283 200.22358 \n", "L 663.200919 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_168\">\n", "    <!-- Layer 2, Head 4 -->\n", "    <g transform=\"translate(556.216913 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_9\">\n", "   <g id=\"patch_42\">\n", "    <path d=\"M 20.5625 496.73267 \n", "L 139.166136 496.73267 \n", "L 139.166136 378.129034 \n", "L 20.5625 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p5bc11c65fe)\">\n", "    <image height=\"119\" id=\"image28a4f0db10\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_17\">\n", "    <g id=\"xtick_81\">\n", "     <g id=\"line2d_161\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_169\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_82\">\n", "     <g id=\"line2d_162\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_170\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_83\">\n", "     <g id=\"line2d_163\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_171\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_84\">\n", "     <g id=\"line2d_164\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_172\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_85\">\n", "     <g id=\"line2d_165\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_173\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_86\">\n", "     <g id=\"line2d_166\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_174\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_87\">\n", "     <g id=\"line2d_167\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_175\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_88\">\n", "     <g id=\"line2d_168\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_176\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_89\">\n", "     <g id=\"line2d_169\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_177\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_90\">\n", "     <g id=\"line2d_170\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_178\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_18\">\n", "    <g id=\"ytick_81\">\n", "     <g id=\"line2d_171\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_179\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_82\">\n", "     <g id=\"line2d_172\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_180\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_83\">\n", "     <g id=\"line2d_173\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_181\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_84\">\n", "     <g id=\"line2d_174\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_182\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_85\">\n", "     <g id=\"line2d_175\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_183\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_86\">\n", "     <g id=\"line2d_176\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_184\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_87\">\n", "     <g id=\"line2d_177\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_185\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_88\">\n", "     <g id=\"line2d_178\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_186\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_89\">\n", "     <g id=\"line2d_179\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_187\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_90\">\n", "     <g id=\"line2d_180\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_188\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_43\">\n", "    <path d=\"M 20.5625 496.73267 \n", "L 20.5625 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_44\">\n", "    <path d=\"M 139.166136 496.73267 \n", "L 139.166136 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_45\">\n", "    <path d=\"M 20.5625 496.73267 \n", "L 139.166136 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_46\">\n", "    <path d=\"M 20.5625 378.129034 \n", "L 139.166136 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_189\">\n", "    <!-- Layer 3, Head 1 -->\n", "    <g transform=\"translate(32.182131 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_10\">\n", "   <g id=\"patch_47\">\n", "    <path d=\"M 195.240761 496.73267 \n", "L 313.844397 496.73267 \n", "L 313.844397 378.129034 \n", "L 195.240761 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pc21e3bf519)\">\n", "    <image height=\"119\" id=\"image194821ab29\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_19\">\n", "    <g id=\"xtick_91\">\n", "     <g id=\"line2d_181\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_190\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_92\">\n", "     <g id=\"line2d_182\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_191\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_93\">\n", "     <g id=\"line2d_183\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_192\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_94\">\n", "     <g id=\"line2d_184\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_193\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_95\">\n", "     <g id=\"line2d_185\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_194\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_96\">\n", "     <g id=\"line2d_186\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_195\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_97\">\n", "     <g id=\"line2d_187\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_196\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_98\">\n", "     <g id=\"line2d_188\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_197\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_99\">\n", "     <g id=\"line2d_189\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_198\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_100\">\n", "     <g id=\"line2d_190\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_199\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_20\">\n", "    <g id=\"ytick_91\">\n", "     <g id=\"line2d_191\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_200\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_92\">\n", "     <g id=\"line2d_192\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_201\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_93\">\n", "     <g id=\"line2d_193\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_202\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_94\">\n", "     <g id=\"line2d_194\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_203\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_95\">\n", "     <g id=\"line2d_195\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_204\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_96\">\n", "     <g id=\"line2d_196\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_205\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_97\">\n", "     <g id=\"line2d_197\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_206\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_98\">\n", "     <g id=\"line2d_198\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_207\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_99\">\n", "     <g id=\"line2d_199\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_208\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_100\">\n", "     <g id=\"line2d_200\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_209\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_48\">\n", "    <path d=\"M 195.240761 496.73267 \n", "L 195.240761 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_49\">\n", "    <path d=\"M 313.844397 496.73267 \n", "L 313.844397 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_50\">\n", "    <path d=\"M 195.240761 496.73267 \n", "L 313.844397 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_51\">\n", "    <path d=\"M 195.240761 378.129034 \n", "L 313.844397 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_210\">\n", "    <!-- Layer 3, Head 2 -->\n", "    <g transform=\"translate(206.860392 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_11\">\n", "   <g id=\"patch_52\">\n", "    <path d=\"M 369.919022 496.73267 \n", "L 488.522658 496.73267 \n", "L 488.522658 378.129034 \n", "L 369.919022 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p2f6a2ab5fa)\">\n", "    <image height=\"119\" id=\"imageb351165d8f\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_21\">\n", "    <g id=\"xtick_101\">\n", "     <g id=\"line2d_201\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_211\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_102\">\n", "     <g id=\"line2d_202\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_212\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_103\">\n", "     <g id=\"line2d_203\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_213\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_104\">\n", "     <g id=\"line2d_204\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_214\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_105\">\n", "     <g id=\"line2d_205\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_215\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_106\">\n", "     <g id=\"line2d_206\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_216\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_107\">\n", "     <g id=\"line2d_207\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_217\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_108\">\n", "     <g id=\"line2d_208\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_218\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_109\">\n", "     <g id=\"line2d_209\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_219\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_110\">\n", "     <g id=\"line2d_210\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_220\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_22\">\n", "    <g id=\"ytick_101\">\n", "     <g id=\"line2d_211\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_221\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_102\">\n", "     <g id=\"line2d_212\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_222\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_103\">\n", "     <g id=\"line2d_213\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_223\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_104\">\n", "     <g id=\"line2d_214\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_224\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_105\">\n", "     <g id=\"line2d_215\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_225\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_106\">\n", "     <g id=\"line2d_216\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_226\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_107\">\n", "     <g id=\"line2d_217\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_227\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_108\">\n", "     <g id=\"line2d_218\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_228\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_109\">\n", "     <g id=\"line2d_219\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_229\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_110\">\n", "     <g id=\"line2d_220\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_230\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_53\">\n", "    <path d=\"M 369.919022 496.73267 \n", "L 369.919022 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_54\">\n", "    <path d=\"M 488.522658 496.73267 \n", "L 488.522658 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_55\">\n", "    <path d=\"M 369.919022 496.73267 \n", "L 488.522658 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_56\">\n", "    <path d=\"M 369.919022 378.129034 \n", "L 488.522658 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_231\">\n", "    <!-- Layer 3, Head 3 -->\n", "    <g transform=\"translate(381.538652 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_12\">\n", "   <g id=\"patch_57\">\n", "    <path d=\"M 544.597283 496.73267 \n", "L 663.200919 496.73267 \n", "L 663.200919 378.129034 \n", "L 544.597283 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p06b827dfc7)\">\n", "    <image height=\"119\" id=\"imagef231b68844\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_23\">\n", "    <g id=\"xtick_111\">\n", "     <g id=\"line2d_221\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_232\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_112\">\n", "     <g id=\"line2d_222\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_233\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_113\">\n", "     <g id=\"line2d_223\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_234\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_114\">\n", "     <g id=\"line2d_224\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_235\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_115\">\n", "     <g id=\"line2d_225\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_236\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_116\">\n", "     <g id=\"line2d_226\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_237\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_117\">\n", "     <g id=\"line2d_227\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_238\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_118\">\n", "     <g id=\"line2d_228\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_239\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_119\">\n", "     <g id=\"line2d_229\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_240\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_120\">\n", "     <g id=\"line2d_230\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#mcee5d6d979\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_241\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_24\">\n", "    <g id=\"ytick_111\">\n", "     <g id=\"line2d_231\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_242\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_112\">\n", "     <g id=\"line2d_232\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_243\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_113\">\n", "     <g id=\"line2d_233\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_244\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_114\">\n", "     <g id=\"line2d_234\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_245\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_115\">\n", "     <g id=\"line2d_235\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_246\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_116\">\n", "     <g id=\"line2d_236\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_247\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_117\">\n", "     <g id=\"line2d_237\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_248\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_118\">\n", "     <g id=\"line2d_238\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_249\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_119\">\n", "     <g id=\"line2d_239\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_250\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_120\">\n", "     <g id=\"line2d_240\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_251\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_58\">\n", "    <path d=\"M 544.597283 496.73267 \n", "L 544.597283 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_59\">\n", "    <path d=\"M 663.200919 496.73267 \n", "L 663.200919 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_60\">\n", "    <path d=\"M 544.597283 496.73267 \n", "L 663.200919 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_61\">\n", "    <path d=\"M 544.597283 378.129034 \n", "L 663.200919 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_252\">\n", "    <!-- Layer 3, Head 4 -->\n", "    <g transform=\"translate(556.216913 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_13\">\n", "   <g id=\"patch_62\">\n", "    <path d=\"M 20.5625 674.638125 \n", "L 139.166136 674.638125 \n", "L 139.166136 556.034489 \n", "L 20.5625 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p763fe92166)\">\n", "    <image height=\"119\" id=\"imagec0e25cbadd\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_25\">\n", "    <g id=\"xtick_121\">\n", "     <g id=\"line2d_241\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_253\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_122\">\n", "     <g id=\"line2d_242\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_254\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_123\">\n", "     <g id=\"line2d_243\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_255\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_124\">\n", "     <g id=\"line2d_244\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_256\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_125\">\n", "     <g id=\"line2d_245\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_257\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_126\">\n", "     <g id=\"line2d_246\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_258\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_127\">\n", "     <g id=\"line2d_247\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_259\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_128\">\n", "     <g id=\"line2d_248\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_260\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_129\">\n", "     <g id=\"line2d_249\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_261\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_130\">\n", "     <g id=\"line2d_250\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_262\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_26\">\n", "    <g id=\"ytick_121\">\n", "     <g id=\"line2d_251\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_263\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_122\">\n", "     <g id=\"line2d_252\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_264\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_123\">\n", "     <g id=\"line2d_253\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_265\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_124\">\n", "     <g id=\"line2d_254\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_266\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_125\">\n", "     <g id=\"line2d_255\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_267\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_126\">\n", "     <g id=\"line2d_256\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_268\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_127\">\n", "     <g id=\"line2d_257\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_269\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_128\">\n", "     <g id=\"line2d_258\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_270\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_129\">\n", "     <g id=\"line2d_259\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_271\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_130\">\n", "     <g id=\"line2d_260\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#m3743f94e5c\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_272\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_63\">\n", "    <path d=\"M 20.5625 674.638125 \n", "L 20.5625 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_64\">\n", "    <path d=\"M 139.166136 674.638125 \n", "L 139.166136 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_65\">\n", "    <path d=\"M 20.5625 674.638125 \n", "L 139.166136 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_66\">\n", "    <path d=\"M 20.5625 556.034489 \n", "L 139.166136 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_273\">\n", "    <!-- Layer 4, Head 1 -->\n", "    <g transform=\"translate(32.182131 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_14\">\n", "   <g id=\"patch_67\">\n", "    <path d=\"M 195.240761 674.638125 \n", "L 313.844397 674.638125 \n", "L 313.844397 556.034489 \n", "L 195.240761 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pccb23f1229)\">\n", "    <image height=\"119\" id=\"image181e0e0bf9\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_27\">\n", "    <g id=\"xtick_131\">\n", "     <g id=\"line2d_261\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_274\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_132\">\n", "     <g id=\"line2d_262\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_275\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_133\">\n", "     <g id=\"line2d_263\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_276\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_134\">\n", "     <g id=\"line2d_264\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_277\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_135\">\n", "     <g id=\"line2d_265\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_278\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_136\">\n", "     <g id=\"line2d_266\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_279\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_137\">\n", "     <g id=\"line2d_267\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_280\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_138\">\n", "     <g id=\"line2d_268\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_281\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_139\">\n", "     <g id=\"line2d_269\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_282\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_140\">\n", "     <g id=\"line2d_270\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_283\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_28\">\n", "    <g id=\"ytick_131\">\n", "     <g id=\"line2d_271\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_284\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_132\">\n", "     <g id=\"line2d_272\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_285\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_133\">\n", "     <g id=\"line2d_273\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_286\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_134\">\n", "     <g id=\"line2d_274\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_287\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_135\">\n", "     <g id=\"line2d_275\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_288\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_136\">\n", "     <g id=\"line2d_276\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_289\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_137\">\n", "     <g id=\"line2d_277\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_290\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_138\">\n", "     <g id=\"line2d_278\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_291\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_139\">\n", "     <g id=\"line2d_279\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_292\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_140\">\n", "     <g id=\"line2d_280\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#m3743f94e5c\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_293\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_68\">\n", "    <path d=\"M 195.240761 674.638125 \n", "L 195.240761 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_69\">\n", "    <path d=\"M 313.844397 674.638125 \n", "L 313.844397 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_70\">\n", "    <path d=\"M 195.240761 674.638125 \n", "L 313.844397 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_71\">\n", "    <path d=\"M 195.240761 556.034489 \n", "L 313.844397 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_294\">\n", "    <!-- Layer 4, Head 2 -->\n", "    <g transform=\"translate(206.860392 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_15\">\n", "   <g id=\"patch_72\">\n", "    <path d=\"M 369.919022 674.638125 \n", "L 488.522658 674.638125 \n", "L 488.522658 556.034489 \n", "L 369.919022 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pde2fafab6a)\">\n", "    <image height=\"119\" id=\"image25bd2fc09d\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_29\">\n", "    <g id=\"xtick_141\">\n", "     <g id=\"line2d_281\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_295\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_142\">\n", "     <g id=\"line2d_282\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_296\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_143\">\n", "     <g id=\"line2d_283\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_297\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_144\">\n", "     <g id=\"line2d_284\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_298\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_145\">\n", "     <g id=\"line2d_285\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_299\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_146\">\n", "     <g id=\"line2d_286\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_300\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_147\">\n", "     <g id=\"line2d_287\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_301\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_148\">\n", "     <g id=\"line2d_288\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_302\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_149\">\n", "     <g id=\"line2d_289\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_303\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_150\">\n", "     <g id=\"line2d_290\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_304\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_30\">\n", "    <g id=\"ytick_141\">\n", "     <g id=\"line2d_291\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_305\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_142\">\n", "     <g id=\"line2d_292\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_306\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_143\">\n", "     <g id=\"line2d_293\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_307\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_144\">\n", "     <g id=\"line2d_294\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_308\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_145\">\n", "     <g id=\"line2d_295\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_309\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_146\">\n", "     <g id=\"line2d_296\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_310\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_147\">\n", "     <g id=\"line2d_297\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_311\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_148\">\n", "     <g id=\"line2d_298\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_312\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_149\">\n", "     <g id=\"line2d_299\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_313\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_150\">\n", "     <g id=\"line2d_300\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#m3743f94e5c\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_314\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_73\">\n", "    <path d=\"M 369.919022 674.638125 \n", "L 369.919022 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_74\">\n", "    <path d=\"M 488.522658 674.638125 \n", "L 488.522658 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_75\">\n", "    <path d=\"M 369.919022 674.638125 \n", "L 488.522658 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_76\">\n", "    <path d=\"M 369.919022 556.034489 \n", "L 488.522658 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_315\">\n", "    <!-- Layer 4, Head 3 -->\n", "    <g transform=\"translate(381.538652 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_16\">\n", "   <g id=\"patch_77\">\n", "    <path d=\"M 544.597283 674.638125 \n", "L 663.200919 674.638125 \n", "L 663.200919 556.034489 \n", "L 544.597283 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pb1f250d953)\">\n", "    <image height=\"119\" id=\"imagee267fbcee1\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_31\">\n", "    <g id=\"xtick_151\">\n", "     <g id=\"line2d_301\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_316\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_152\">\n", "     <g id=\"line2d_302\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_317\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_153\">\n", "     <g id=\"line2d_303\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_318\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_154\">\n", "     <g id=\"line2d_304\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_319\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_155\">\n", "     <g id=\"line2d_305\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_320\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_156\">\n", "     <g id=\"line2d_306\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_321\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_157\">\n", "     <g id=\"line2d_307\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_322\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_158\">\n", "     <g id=\"line2d_308\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_323\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_159\">\n", "     <g id=\"line2d_309\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_324\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_160\">\n", "     <g id=\"line2d_310\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#mcee5d6d979\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_325\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_32\">\n", "    <g id=\"ytick_151\">\n", "     <g id=\"line2d_311\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_326\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_152\">\n", "     <g id=\"line2d_312\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_327\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_153\">\n", "     <g id=\"line2d_313\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_328\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_154\">\n", "     <g id=\"line2d_314\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_329\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_155\">\n", "     <g id=\"line2d_315\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_330\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_156\">\n", "     <g id=\"line2d_316\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_331\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_157\">\n", "     <g id=\"line2d_317\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_332\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_158\">\n", "     <g id=\"line2d_318\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_333\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_159\">\n", "     <g id=\"line2d_319\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_334\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_160\">\n", "     <g id=\"line2d_320\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#m3743f94e5c\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_335\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_78\">\n", "    <path d=\"M 544.597283 674.638125 \n", "L 544.597283 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_79\">\n", "    <path d=\"M 663.200919 674.638125 \n", "L 663.200919 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_80\">\n", "    <path d=\"M 544.597283 674.638125 \n", "L 663.200919 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_81\">\n", "    <path d=\"M 544.597283 556.034489 \n", "L 663.200919 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_336\">\n", "    <!-- Layer 4, Head 4 -->\n", "    <g transform=\"translate(556.216913 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"pd05ea679e7\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pd44a1ec703\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p81852aa511\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p514c43ea0a\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p31481cd1b3\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pbc0868af49\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p2024253e5d\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pc489f1e530\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p5bc11c65fe\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pc21e3bf519\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p2f6a2ab5fa\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p06b827dfc7\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p763fe92166\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"556.034489\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pccb23f1229\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"556.034489\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pde2fafab6a\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"556.034489\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pb1f250d953\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"556.034489\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 864x864 with 16 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["def visualize_prediction(idx):\n", "    visualize_exmp(indices[idx : idx + 1], test_set)\n", "    print(\"Prediction:\", predictions[idx].item())\n", "    plot_attention_maps(input_data=None, attn_maps=attention_maps, idx=idx)\n", "\n", "\n", "visualize_prediction(0)"]}, {"cell_type": "markdown", "id": "c342c0bd", "metadata": {"papermill": {"duration": 0.217865, "end_time": "2021-12-04T15:59:32.717940", "exception": false, "start_time": "2021-12-04T15:59:32.500075", "status": "completed"}, "tags": []}, "source": ["Depending on the random seed, you might see a slightly different input set.\n", "For the version on the website, we compare 9 tree images with a volcano.\n", "We see that multiple heads, for instance, Layer 2 Head 1, Layer 2 Head 3, and Layer 3 Head 1 focus on the last image.\n", "Additionally, the heads in Layer 4 all seem to ignore the last image and assign a very low attention probability to it.\n", "This shows that the model has indeed recognized that the image doesn't fit the setting, and hence predicted it to be the anomaly.\n", "Layer 3 Head 2-4 seems to take a slightly weighted average of all images.\n", "That might indicate that the model extracts the \"average\" information of all images, to compare it to the image features itself.\n", "\n", "Let's try to find where the model actually makes a mistake.\n", "We can do this by identifying the sets where the model predicts something else than 9, as in the dataset,\n", "we ensured that the anomaly is always at the last position in the set."]}, {"cell_type": "code", "execution_count": 41, "id": "7d06d854", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:33.159783Z", "iopub.status.busy": "2021-12-04T15:59:33.159310Z", "iopub.status.idle": "2021-12-04T15:59:33.162672Z", "shell.execute_reply": "2021-12-04T15:59:33.162185Z"}, "papermill": {"duration": 0.227646, "end_time": "2021-12-04T15:59:33.162786", "exception": false, "start_time": "2021-12-04T15:59:32.935140", "status": "completed"}, "tags": []}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Indices with mistake: [49]\n"]}], "source": ["mistakes = torch.where(predictions != 9)[0].cpu().numpy()\n", "print(\"Indices with mistake:\", mistakes)"]}, {"cell_type": "markdown", "id": "20752dd7", "metadata": {"papermill": {"duration": 0.217506, "end_time": "2021-12-04T15:59:33.599090", "exception": false, "start_time": "2021-12-04T15:59:33.381584", "status": "completed"}, "tags": []}, "source": ["As our model achieves ~94% accuracy, we only have very little number of mistakes in a batch of 64 sets.\n", "Still, let's visualize one of them, for example the last one:"]}, {"cell_type": "code", "execution_count": 42, "id": "aff3ca25", "metadata": {"execution": {"iopub.execute_input": "2021-12-04T15:59:34.041610Z", "iopub.status.busy": "2021-12-04T15:59:34.041142Z", "iopub.status.idle": "2021-12-04T15:59:36.836836Z", "shell.execute_reply": "2021-12-04T15:59:36.836406Z"}, "papermill": {"duration": 3.018115, "end_time": "2021-12-04T15:59:36.836962", "exception": false, "start_time": "2021-12-04T15:59:33.818847", "status": "completed"}, "tags": []}, "outputs": [{"data": {"application/pdf": "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\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"100.469118pt\" version=\"1.1\" viewBox=\"0 0 684 100.469118\" width=\"684pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:59:34.151133</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 100.469118 \n", "L 684 100.469118 \n", "L 684 0 \n", "L 0 0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g clip-path=\"url(#p8e2bfbac8f)\">\n", "    <image height=\"71\" id=\"imageb04a9d5758\" transform=\"scale(1 -1)translate(0 -71)\" width=\"670\" x=\"7.2\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-22.269118\"/>\n", "   </g>\n", "   <g id=\"text_1\">\n", "    <!-- Anomaly examples on CIFAR100 -->\n", "    <g transform=\"translate(244.94625 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 2188 4044 \n", "L 1331 1722 \n", "L 3047 1722 \n", "L 2188 4044 \n", "z\n", "M 1831 4666 \n", "L 2547 4666 \n", "L 4325 0 \n", "L 3669 0 \n", "L 3244 1197 \n", "L 1141 1197 \n", "L 716 0 \n", "L 50 0 \n", "L 1831 4666 \n", "z\n", "\" id=\"DejaVuSans-41\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 2113 \n", "L 3513 0 \n", "L 2938 0 \n", "L 2938 2094 \n", "Q 2938 2591 2744 2837 \n", "Q 2550 3084 2163 3084 \n", "Q 1697 3084 1428 2787 \n", "Q 1159 2491 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1366 3272 1645 3428 \n", "Q 1925 3584 2291 3584 \n", "Q 2894 3584 3203 3211 \n", "Q 3513 2838 3513 2113 \n", "z\n", "\" id=\"DejaVuSans-6e\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1959 3097 \n", "Q 1497 3097 1228 2736 \n", "Q 959 2375 959 1747 \n", "Q 959 1119 1226 758 \n", "Q 1494 397 1959 397 \n", "Q 2419 397 2687 759 \n", "Q 2956 1122 2956 1747 \n", "Q 2956 2369 2687 2733 \n", "Q 2419 3097 1959 3097 \n", "z\n", "M 1959 3584 \n", "Q 2709 3584 3137 3096 \n", "Q 3566 2609 3566 1747 \n", "Q 3566 888 3137 398 \n", "Q 2709 -91 1959 -91 \n", "Q 1206 -91 779 398 \n", "Q 353 888 353 1747 \n", "Q 353 2609 779 3096 \n", "Q 1206 3584 1959 3584 \n", "z\n", "\" id=\"DejaVuSans-6f\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3328 2828 \n", "Q 3544 3216 3844 3400 \n", "Q 4144 3584 4550 3584 \n", "Q 5097 3584 5394 3201 \n", "Q 5691 2819 5691 2113 \n", "L 5691 0 \n", "L 5113 0 \n", "L 5113 2094 \n", "Q 5113 2597 4934 2840 \n", "Q 4756 3084 4391 3084 \n", "Q 3944 3084 3684 2787 \n", "Q 3425 2491 3425 1978 \n", "L 3425 0 \n", "L 2847 0 \n", "L 2847 2094 \n", "Q 2847 2600 2669 2842 \n", "Q 2491 3084 2119 3084 \n", "Q 1678 3084 1418 2786 \n", "Q 1159 2488 1159 1978 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1356 3278 1631 3431 \n", "Q 1906 3584 2284 3584 \n", "Q 2666 3584 2933 3390 \n", "Q 3200 3197 3328 2828 \n", "z\n", "\" id=\"DejaVuSans-6d\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 603 4863 \n", "L 1178 4863 \n", "L 1178 0 \n", "L 603 0 \n", "L 603 4863 \n", "z\n", "\" id=\"DejaVuSans-6c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" id=\"DejaVuSans-79\" transform=\"scale(0.015625)\"/>\n", "      <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3513 3500 \n", "L 2247 1797 \n", "L 3578 0 \n", "L 2900 0 \n", "L 1881 1375 \n", "L 863 0 \n", "L 184 0 \n", "L 1544 1831 \n", "L 300 3500 \n", "L 978 3500 \n", "L 1906 2253 \n", "L 2834 3500 \n", "L 3513 3500 \n", "z\n", "\" id=\"DejaVuSans-78\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 1159 525 \n", "L 1159 -1331 \n", "L 581 -1331 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2969 \n", "Q 1341 3281 1617 3432 \n", "Q 1894 3584 2278 3584 \n", "Q 2916 3584 3314 3078 \n", "Q 3713 2572 3713 1747 \n", "Q 3713 922 3314 415 \n", "Q 2916 -91 2278 -91 \n", "Q 1894 -91 1617 61 \n", "Q 1341 213 1159 525 \n", "z\n", "M 3116 1747 \n", "Q 3116 2381 2855 2742 \n", "Q 2594 3103 2138 3103 \n", "Q 1681 3103 1420 2742 \n", "Q 1159 2381 1159 1747 \n", "Q 1159 1113 1420 752 \n", "Q 1681 391 2138 391 \n", "Q 2594 391 2855 752 \n", "Q 3116 1113 3116 1747 \n", "z\n", "\" id=\"DejaVuSans-70\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2834 3397 \n", "L 2834 2853 \n", "Q 2591 2978 2328 3040 \n", "Q 2066 3103 1784 3103 \n", "Q 1356 3103 1142 2972 \n", "Q 928 2841 928 2578 \n", "Q 928 2378 1081 2264 \n", "Q 1234 2150 1697 2047 \n", "L 1894 2003 \n", "Q 2506 1872 2764 1633 \n", "Q 3022 1394 3022 966 \n", "Q 3022 478 2636 193 \n", "Q 2250 -91 1575 -91 \n", "Q 1294 -91 989 -36 \n", "Q 684 19 347 128 \n", "L 347 722 \n", "Q 666 556 975 473 \n", "Q 1284 391 1588 391 \n", "Q 1994 391 2212 530 \n", "Q 2431 669 2431 922 \n", "Q 2431 1156 2273 1281 \n", "Q 2116 1406 1581 1522 \n", "L 1381 1569 \n", "Q 847 1681 609 1914 \n", "Q 372 2147 372 2553 \n", "Q 372 3047 722 3315 \n", "Q 1072 3584 1716 3584 \n", "Q 2034 3584 2315 3537 \n", "Q 2597 3491 2834 3397 \n", "z\n", "\" id=\"DejaVuSans-73\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 4122 4306 \n", "L 4122 3641 \n", "Q 3803 3938 3442 4084 \n", "Q 3081 4231 2675 4231 \n", "Q 1875 4231 1450 3742 \n", "Q 1025 3253 1025 2328 \n", "Q 1025 1406 1450 917 \n", "Q 1875 428 2675 428 \n", "Q 3081 428 3442 575 \n", "Q 3803 722 4122 1019 \n", "L 4122 359 \n", "Q 3791 134 3420 21 \n", "Q 3050 -91 2638 -91 \n", "Q 1578 -91 968 557 \n", "Q 359 1206 359 2328 \n", "Q 359 3453 968 4101 \n", "Q 1578 4750 2638 4750 \n", "Q 3056 4750 3426 4639 \n", "Q 3797 4528 4122 4306 \n", "z\n", "\" id=\"DejaVuSans-43\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-49\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 3309 4666 \n", "L 3309 4134 \n", "L 1259 4134 \n", "L 1259 2759 \n", "L 3109 2759 \n", "L 3109 2228 \n", "L 1259 2228 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-46\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2841 2188 \n", "Q 3044 2119 3236 1894 \n", "Q 3428 1669 3622 1275 \n", "L 4263 0 \n", "L 3584 0 \n", "L 2988 1197 \n", "Q 2756 1666 2539 1819 \n", "Q 2322 1972 1947 1972 \n", "L 1259 1972 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "L 2053 4666 \n", "Q 2853 4666 3247 4331 \n", "Q 3641 3997 3641 3322 \n", "Q 3641 2881 3436 2590 \n", "Q 3231 2300 2841 2188 \n", "z\n", "M 1259 4147 \n", "L 1259 2491 \n", "L 2053 2491 \n", "Q 2509 2491 2742 2702 \n", "Q 2975 2913 2975 3322 \n", "Q 2975 3731 2742 3939 \n", "Q 2509 4147 2053 4147 \n", "L 1259 4147 \n", "z\n", "\" id=\"DejaVuSans-52\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-41\"/>\n", "     <use x=\"68.408203\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"131.787109\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"192.96875\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"290.380859\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"351.660156\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"379.443359\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"438.623047\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"470.410156\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"530.183594\" xlink:href=\"#DejaVuSans-78\"/>\n", "     <use x=\"589.363281\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"650.642578\" xlink:href=\"#DejaVuSans-6d\"/>\n", "     <use x=\"748.054688\" xlink:href=\"#DejaVuSans-70\"/>\n", "     <use x=\"811.53125\" xlink:href=\"#DejaVuSans-6c\"/>\n", "     <use x=\"839.314453\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"900.837891\" xlink:href=\"#DejaVuSans-73\"/>\n", "     <use x=\"952.9375\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"984.724609\" xlink:href=\"#DejaVuSans-6f\"/>\n", "     <use x=\"1045.90625\" xlink:href=\"#DejaVuSans-6e\"/>\n", "     <use x=\"1109.285156\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"1141.072266\" xlink:href=\"#DejaVuSans-43\"/>\n", "     <use x=\"1210.896484\" xlink:href=\"#DejaVuSans-49\"/>\n", "     <use x=\"1240.388672\" xlink:href=\"#DejaVuSans-46\"/>\n", "     <use x=\"1288.783203\" xlink:href=\"#DejaVuSans-41\"/>\n", "     <use x=\"1357.191406\" xlink:href=\"#DejaVuSans-52\"/>\n", "     <use x=\"1426.673828\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"1490.296875\" xlink:href=\"#DejaVuSans-30\"/>\n", "     <use x=\"1553.919922\" xlink:href=\"#DejaVuSans-30\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"p8e2bfbac8f\">\n", "   <rect height=\"70.950993\" width=\"669.6\" x=\"7.2\" y=\"22.318125\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 864x576 with 1 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Prediction: 7\n"]}, {"data": {"application/pdf": "JVBERi0xLjQKJazcIKu6CjEgMCBvYmoKPDwgL1BhZ2VzIDIgMCBSIC9UeXBlIC9DYXRhbG9nID4+CmVuZG9iago4IDAgb2JqCjw8IC9FeHRHU3RhdGUgNCAwIFIgL0ZvbnQgMyAwIFIgL1BhdHRlcm4gNSAwIFIKL1Byb2NTZXQgWyAvUERGIC9UZXh0IC9JbWFnZUIgL0ltYWdlQyAvSW1hZ2VJIF0gL1NoYWRpbmcgNiAwIFIKL1hPYmplY3QgNyAwIFIgPj4KZW5kb2JqCjExIDAgb2JqCjw8IC9Bbm5vdHMgMTAgMCBSIC9Db250ZW50cyA5IDAgUgovR3JvdXAgPDwgL0NTIC9EZXZpY2VSR0IgL1MgL1RyYW5zcGFyZW5jeSAvVHlwZSAvR3JvdXAgPj4KL01lZGlhQm94IFsgMCAwIDY3MC4zOTc3OTM5NzIzIDY5OC41MTY4NzUgXSAvUGFyZW50IDIgMCBSIC9SZXNvdXJjZXMgOCAwIFIKL1R5cGUgL1BhZ2UgPj4KZW5kb2JqCjkgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxMiAwIFIgPj4Kc3RyZWFtCnicvZ1dr+TGcYbv51fMZQIkVH+TfWnBiRMjN0oE+CLIhSHLSgytA9lAgvz7FGfOOf1WDbua7DoSFrawtUv2Qw7ZrOew3x1//9Ptq1/5+w9/vbv7n+h//3v399/cv/r19//zX999/6+/+fr+3V9vjupfbmV1S6zrWhP99kf8banbkn3Z1kx1x3/7n7fbn2+0f9rmN7TrH2634Jaca6Q/zXld8raFWGn3PtbFl+i8x/qPWC9rWXz1zx233bAyjffH20/3g0G2Eku6e78txcXy/CV/+5fv77+7//n+1a/CfkY8nRxPZ8S9nJGfaMN638/L/t/uYN99uX/1z/7+6/++f3P75v7T+34dnQ6/n+1le9s7VW6hLGmrtAd+XrCcFvd+Wm5f72i3n+j/3f3vieMe4hJd3UqNfgv3nMJSa0rbO8nt62/vX/2jv3t3//aPj4/02z/c/v3+N+5v7/9x//a3t3/49vbN7UF0i9sSU62Bg0BV5Yh58asLMdSc8nkO/8qR3RK8C1viIFhWSdK6uOhyLbm6ep4kvJKUsLjVlbRxEiyrJHlbNmIoLoQ1nieJryRrXOgDFnfJF1ZWSeiuXbOPzyv0PEl6Jdnyslb/ch9jWSXZwlL8c5o4jZFfMeq6lOxXGoRhYFnFqGlJa3DZ+33o0yTllcS7SvPefmmKmQ3rKot3ZYkxJJ/WNaznYdYDmOCXuIZUioDBug5DU6OvYV235Ko/D7MdwMS40ISwRTnlt7KOEt3icvQpuJQvXC71FQXm6hLpY9lS2EloppDVw7tn2T/DuqzB0+S2/7o2s8Loa6bPYaOTy4dv5e74q6dT6Gk62X9dm1Fh/I32FaunuYuN38rd8be4pEQT2f4rXptHYfxaF1cr3XZ8/Fbujl/pFLnw/si+NHtC0+DdUnPdZx8cH8q98Ytb94bk2mQJA4ewbMG93QFt4FbuDuzp3IT4PO6LsySMH9NSNkePIj5+K3fHp7tw2+L6/OSvzY0wfipLphmFJiA2fit3x6fbfk3ped37a9MhjE/P4uRo6uHDf1S7o9MUVVx63vXabX8w/2GvSs1L8dSk8eFbuTt+oUaQWg3/+HV20gv33z4b+0eryZvYTiPeaaxv/9Zp0b90W3Ta5GKzz7aAfaljuMcxPlvqZ7v+A+tHw+KzCzmX/bwVajveNoZTGPgp/Jff/9/3f7n7v7v/0/e//8OdzaNvsvQ0mqcwfZiNp5kpxPXRWLHO2cdlS57uGn60UGfHBPt5dZvdIz7+QqZ2v8wqzu2pOPcziqOP+PCccNZznKdPct0/DHHdQV1vB6i5q9tGXQGdmAtt0tEDmT4CUgm6pQQM1nXtou5uS1uqcaPGzeQ7ISSaYLeHNjEYrOsw1N2t9Od5TcVdaJSOHtWx0Gy7PcyJwWB9IKTUSpVKTDStbybrCWm/hqu4g77wug6T8pJISbe0UodtEp9QHM3E9eU2Z3UdhjYLG42/xcfdZNAfOnRSBgHyXtMhSt0nxuiDo6eQyXzIxWmW2ucYAYJ1HWbziyP9WTM95S8Y8tGjvhZ6rLqHQDEYrOswlXqx1btIF9Z2YX45ePJHahar9/ImwrL+wxSXlpXEx4XqbeKDDyc0n0ozhiwfTrr0CZGX0EX+9gSYtyBEYRoELLoHSRiDEiEMcyKA0aVIwhj8CGGYIAGMbkgSxiBL2IYwW2owA10SMFPmhBRMnYBCdydJYdAohGEeBTC6SEkYg1MhDJMqgNGtSsIYBAth0LCARVUsiWKwLdY+o24Bi+5bEubT1atnCr3OnyznWCK+dCVi97WLPsI3YfqljDLQr+AK3Zxb9iVnn2b8K5z1L2qm6Kmatyqe/PS8pAdbzbxP+hHr7KBgP8f+9fEXyhqr/yX8Sx/x4V/xpH+RWtNHSXOx7Emwrjcl1F/SPUEgLl95nXH4qmld9jco6eVlE9R1GOoxc6DGkVrveKFZO2gFIj1ac9knbwGDdR2GekxCp488XjgvB41A8p50ZaUZSlzKWNdffrltCYlMzdPsf+HFxkEjQB056cqapWewug4T3OIddXOZnosXVPCgH0j7+8W0vt7kWNdhol9ISEncQ7zyYuOgH0j7K0ZHDwrBAmUdJcXH5Ljup/FCf3/QDaT9HWPZShBvS1ldh8mZOpetxpL3KcfiYGl/zUiGu4mf8bC6DlNos1Sjc9R2X/D1g36AtieCGrOXjwWoD14k1+XRRZGSpAu+fqBh+IwCDYt7iyHLx2/XqaPLJQf/9iCY1zBEQQ1DFl3DJIxBwxAGNQxhdA2TMAYNQxjUMITRNUzCGDQMuxHUMIAZaJiAmdIwpEANQwpdwySFQcMQBjUMYXQNkzAGDUMY1DCE0TVMwhg0DGFAw5BF1TCJYtAw1kWDhiGLrmES5tM1rCcMPQEg2zl2iS9dl9jN7aKW8E2YhimjjN6CkdJmV9Z1pV6szmhYPKthOVFHXvePWKyWogebf64YZMcLdXZQsJ9jDfv4CyuJ+vpLaJg+4kPD0kkNy9mRt6QoFy6xur6ojLrMmBJ1azWUC/3aQSuQSyBvoe5MXNWsrsNQIxJcdp5u2CvvV46W/a2JzGW/WAUM1nUYakRcyXGtvl55v3LQCuSNrjyXkzwxUB6s/KOxA6GH7cp6u4M+IO9vPUsWt88XXtdZalrWjZqFktYrL1kO2oGyv/WkqfvlHse6ClNcWei5SNeWd1deshy0AyV4etbvzwm5PBPqOgxNDnRhkbWvKV9QwoN2oOxvPRN5lHiJy+o6DDUjsaw0JdKkfcHcD9qBsr/1dGtIYpJhdR2GRqcmOtNV49cL5n7QEJT9rSfN5F78rIfVdZjHH6810KSXLkwyBx6GDynwsJxo5pDlw3spepKR9Pwh8WryMERBD0MW3cMkjMHDEAY9DGF0D5MwBg9DGPQwhNE9TMIYPAzbEfQwgBl4mICZ8jCkQA9DCt3DJIXBwxAGPQxhdA+TMAYPQxj0MITRPUzCGDwMYcDDkEX1MIli8DDWRoOHIYvuYRLm0z2sZww9AyDdOZaJL12ZoE2uegnfhHmYMsrAw6g9XvyWXdxCdXnGw9JZD2srKakRppswvK2yaCspoc6CVqluS9jK49HX9oLVDwc7GuTx1LkUtLqd06/uYA/zypeDVuy8YHn/jELvacuDVrFk6kmqi2nwsNWCVgwEqioHD1qd5lCDVgwEyyoJD1qdJlGDVowEyyoJD1qdJlGDVowEyyoJD1qdJlGDVowEyyoJBK1OY6hBK4aBZRWDB61Ok+hBKz6zYV1lEUGr0zB60IrDYF2H4UGr0zBq0EpM+a2so/Cg1WkUNWgV6UoluZOJDyj3Mg/7Dy03X8YdmBq1inSJ7qt+eeSiVbuj17jQ033cdKlBKzp1dKlFmfiAcm/85PKSYxn3WWrQKtF16Cvta+Xjt3J3fPrbdJaew4fZoFWia8/lJGJ2rdodPdQlkPcOjVpNWyVq4Oq+LIDH7KDcHZ/aY+/XsUSraatE7d5KzwERs4Nyd/wclkot99Cb1bRVKtR2xSxjdlDujl/Ssj0eXgNVVtNWaXNLqlnG7KDcHZ9mqlIvzn/YrIYl5iJjdlDuDry/Y6G/PRTiiaAVbzgPO2ues+p17mKLi60+26LtShvhUsgqu/Tc1sl799BsgiFoxTvntkqRHS/U8bBgN4duI0JPk4JjiFkdWU65HrMSVx3U9WaAx6wsogNxKg6DdV26eMzKYjsQp+IwWNdheMzKIjwQp+IwWB/oKItZWZwH4lQcBus6DI9ZWbQH4lTC06Guw/CYlUV+3iJVHOS9pkPwmJXFeyBOxUGwrsPwmJXFeyBOxWGwrsPwmJXFe1qeij8PoKz/KIXFrCzag48m5j0tfDAQHxE+sDgQwqAEAYtqQRLFIET4rGVG1FgGSiRgLHaEMEyPAEb3IwljUCWEQVcCFlWWJIrBmxCFiROw6OYkYQwShTDMogBG1ygJYzAqhGFKBTC6U0kYg14hDPMrgNEFS8LMuBbrnlG2gEK3LUnx6eLV84RO489TVj2zkLJ20UX4Jihf/TGuRawm7WsmZsWOGBYnsiOGOh4X7ObQvkTk6RewL33Eh32t10NW/KrAut6S8JCV7TXTR5hKvGiCug7DQ1YW+4IwFYfBug6DISuLe0GYil/IWNdffPGQlcW9IEzFYbCuw/CQlcW9IEzFYbCuw/CQlcW9WpqKs0BZR+EhK4uBQZiKs2Bdh+EhK4uBQZiKw2Bdh+EhK4uBQZhKPBSgPniJzEJWFgnDJxRKGEQPBhImogcWCUMYkDBkUSVMohgkDB+5KGHAMpAwAWORMIRBCUMYXcIkjEHCEAYkDFlUCZMoBglDFJQwZNElTMIYJAxhUMIQRpcwCWOQMIRBCUMYXcIkjEHCEAYlDGF0CZMwMxLGmmiQMKTQJUxSfLqE9XSh0//zjFVPMKS2XVQSvglKWH+MawGrSQmbCVnxlVJtZSI7YqjjccFuDiVMBJ5+AQnTR3xI2HY9YsXXtWFdX07GI1YWCYMoFYfBug7DI1amBX8tSsVhsK7D8IiVRcNaloqzQHmw5g8jVhYHgygVR8G6zsIjVhYHgygVv8OxrsKIiJXFwSBKJRZmQl2H4REri4VBlIrDYF2H4REri4VBlIrDYF2H4REri4VBlIrDYF2H4REri4XhIwotDIIHAwsTwQOLhSEMWBiyqBYmUQwWhs9ctDBgGViYgLFYGMKghSGMbmESxmBhCAMWhiyqhUkUg4UhCloYsugWJmEMFoYwaGEIo1uYhDFYGMKghSGMbmESxmBhCIMWhjC6hUmYGQtjXTRYGFLoFiYpPt3Cer7QEQCesOoZhtjiqpPwTdDC+mNci1dNWthExGpfVkfu91xf0VZRtjILWEXaMG5vQURYvInlg4jV+94eiZ/8M0esxGAP86qXI1Z4XlrV7x/q22kZBaz8ttJHGqn7HjxqtYAVYnwUdQoerzpNocarEKNVdQ4erjrNoYarkKNVdQ4erTrNoUarkKNVdQ4erDrNoQarkKNVdQ6IVZ2GUGNVCNGqOgQPVZ3m0ENVbC5rZZ1ERKpOo+iRKobSygMUHqg6jaIGqvgE/14dgPA41WkQNU4V3P7WfpWRDij3kg3B0S1Gn9Ow0VLjVMHvL+pXGemAcnd8T7fWqombmqQKcX8tv8lIB5S7Awe6naIft1Nqkiqk/U38Jr85Ccrd8enJn6of/7MGapIq5P3l+yZzdFDujp/pzslhLM5qliqU/YV7FTm6Vu2OTs1c8GHsymqSinrGZV8mJnJ0UO6Ov2Z6woWxHqtJKuonlzU6maODcnf8rdCTLY6NWE1SRReoU3YiR9eq3dFphlprHEuwGqeiOWxJ2ckcHZS7KUrv6FEWx947EadizeVxF83jVJ0uXW5xqa3n8au2J3WES3GqGMpz4yxv30OLiYY4FeuT23pEPF5c2IhHhQshDz1GhJsmZcYQpzoyGroKL+ep+GX3UR70AjxNZbEaSE0xlFYe+BXPUlnUBjJTDKWVByg8SWWxG0hMMZRWHlkny1FZBAfyUgyllQcoPEVlcRxIS3EV/ygPUHiGymI6b3kphvEsDRB4gsoiOZCUYhitPEDh+SmL5EBOiqG08gCFp6csktNiUmz6/6gOfk7CslMWx2HPIZScligYWI5IFFiEB2GY8QCMrjwSZsZ+kILpD1Do/iMpDCqEMMyFAEaXIQlj8CKEYWIEMLoZSRiDJCEMWhKwqJokUQzGhChMmYBFdyYJY9AnhGH+BDC6QEkYg0thg4oyBWlI1aYkikGsEIWZFbDoaiWjmZ9uWR0p6HX5PDvV0YgXM7skHiJshaaljHEtOzWpWjPZKTxiWHWIR4zLF/GwcLnjoWqJJNMvoFr6iE/V8tfDU+yyaOVBR8KjU7YXSB8RKf4K6aM8QOHBKYtqQUCKobTyAAVjUxbRgngUu4ZbefBCi4emLKIF4SiG0soDFB6ZsogWRKMYSisPUHhgyiJaLRnFSD6qAxAel7LoFsSiGEkrD1B4WMqiWxCKYiitPEDhUSmLbkEkij8DPsqjF8IsKGUxLvY4AuOC+MDAuER8wGJcCIPGhTC6cUmYGeNCCjQupNCNS1IYjAth0LgQRjcuCWMwLoRB40IY3bgkjMG4EAaMC1lU45IoBuNCFDQuZNGNS8IYjAth0LgQRjcuCWMwLuxTwbgw+qgal0QxGBeioHEhi25cMof56cbVcYNes8+DUh2beHG0S/4hklVoXMoY14JSk8Y1E5Riq57aCkM8YlyqiIeFSxsPjUvEln4B49JHfBpXuJ6UYkvUWnmwNoznpCzGBXkohtLKAxSekjKt22tpKIbSygMUnpGyOFcLQzGSj+po6R4mpCzCBUkoBtLKAxKej7IIF+Sg2I3dyjqKSEdZhAtSUHxl5Ud5gMKzURblggwUQ2nlAQpPRlmUCxJQDKWVByg8F2VRLsg/MZRWHqDwVJRFudjzCJQLsgID5RJZAYtyIQwqF8LoyiVhZpQLKVC5kEJXLklhUC6EQeVCGF25JIxBuRAGlQthdOWSMAblQhhQLmRRlUuiGJQLUVC5kEVXLgljUC6EQeVCGF25JIxBubBRBeXCnKOqXBLFoFyIgsqFLLpyydDlpytXRw563T5PRXV0Qm5xTUBEjAqVSxnjWipqUrlmUlFxX6PytnAClk9+lFkqytMDP61vscG2E1Y+SkV97O1SIGo/VbdLgaiPcZ5yFa+HoeB0YERqie9nYxSGIrdZNx+mY1AAANkobXwegzoxvh6AAgCMRWkEPAB1gkCPPgEBBqI0Ah59OkGgh56AAKNQGgEPPZ0g0ONOQIAhKI0A4k4nhteDTjA8xp+04XnQ6QTBIOKEExMmnzQGEXE6ATEINyEEZp5UCB5uOgGhx5rYDN3CTioCjzWdQNADTSTsLrwGK96r/VwJNZt53CWpaSbqRUoJ8tuJ3ovdUMNKvWUed0VqnimTkocgIxWt2hs87V81nMddkBpmKplagCi/l6hVe4OX/auFy/gfDlCTTCvtKUWZYGvV3uDr/lXCZWy6aoxpo36DOiERX2vV3uDb/tXBmr+p8SXv3FL3RcM8vAbl3rh1/5bgdeyyanrJ+/07gZPMrkG5N/w+O7qwjvVVTS+R5y1lSzK7BuXu+LSTbdvGxqrml+ipsdCtKrJrrdodPe7fAbyNJXUmvYTd4HG3K9JLx9203OJS+83+PuxJHeFSeolmk7eN5V17aBvJkl7C9hYWEcLxQpkdFezl2DdklmhOOk7+KwzdwZ7mkSYyS+xigyiT+qDnmaU5+cC0EkJgiEkVIJ5WmjMQzCkhBMaXVAieU5qTEEwoIQQGl3QVZAmlOQ/BbBJCYGRJheDZpDkVwVQSc2IIK6kQPJU0JyTveSQEeI8oqYPzPNKci2ASCQEwoKRC8CTSnItgBgkhMJqkQvAM0pyLQPoIp2/IJKk/nmDpozkVYSkFcBEMKWgy8pLemPYS/GYQEBP4RhXNTGQmYF5SgINZSgPRNUV+s8u8sQAJU5ZGojuLIDHoC5Awf2kkusAIEoPLAAmTmUai24wgmREbbJeY2TSGgdoICIPlIAvTHGDRPUewWJQHYZjzAIwuPRLG4D8IgwIELKoBSZRPl6FO795rxkXI6LjbfxGoS37AN2BCpIxxLWQ0aURTISM4YlzkB0cMZXZYsJdjI5KRn5/ViLqDPY0oT0SL8GLAxJHabvBo0ezrmBYqYi9kIGukQvBQ0ZwRYZwIITBlpEJgnGjOhzBIhNcp5ovUF0M8SDTnQxghQghMFqkQPEI050MYHkIIzBSpEDw8NOdDEBtCBggTqQg8NjRnRRgYQgbMEakQPDA0Z0UYFUIITBCpEDwqNGdFGBJiczhkh/SXpiwkNCdGLEzQxIhlCTQxeglZTIsRfltHEyP8lhNNjOTS/XkxAg4UIwDRxUh+28q8GAEJihGQ6GIkSAxiBCQoRkCii5EgMYgRkKAYAYkuRoJkRoywa0IxAoaBGAkIgxghC4oRsuhiJFgsYoQwKEYIo4uRhDGIEcKAGCGLKkYS5dPFqNPC93pykQU6bvpfVOqSJvANmBgpY1zLAk2K0VQWCJcBwVI8OGIos8OCvRyLkUzm/Kxi1B3sKUZlIgGEa7QwGKQukeIJoDkxwuwPQmAkSIXg2Z/JxWqQ+kEIDAOpEDz1M6dGkPdBBkgB6evVMO8z50WY9EEEDACpDDzpM+dFmPHBGxajPxqEyPjMeRGme9jiQQj9qBA83TNnRpjrQQiM+6gQPNczZ0aY6EEIDPqoEDzRM2dGmOVBCIz4qBA8yzNnRmzNfzMjtuRfM6OXLMS0GeE3aDQzwm8e0cxIrrCfNyPgQDMCEN2M5DegzJsRkKAZAYluRoLEYEZAgmYEJLoZCRKDGQEJmhGQ6GYkSGbMCNsmNCNgGJiRgDCYEbKgGSGLbkaCxWJGCINmhDC6GUkYgxkhDJgRsqhmJFE+3Yw6PXyvKReRneOuX25xzRP4BsyMlDGuRXYmzYjNBN/c/h+tSo1MCmVuZHN0cmVhbQplbmRvYmoKMTIgMCBvYmoKNjM2MgplbmRvYmoKMTAgMCBvYmoKWyBdCmVuZG9iagozMyAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDc5ID4+CnN0cmVhbQp4nDM3NVIwULC0ABJmpiYK5kaWCimGXEA+iJXLZWhpDmblgFkmxgZAlqmpKRILIgvTC2HB5GC0sYk51AQECyQHtjYHZlsOVwZXGgDWlBwMCmVuZHN0cmVhbQplbmRvYmoKMzQgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA2MSA+PgpzdHJlYW0KeJwzNTVXMFCwtAASpqZGCuZGlgophlxAPoiVy2VoaQ5m5YBZFsZABkgZnGEApMGac2B6crgyuNIAyxUQzAplbmRzdHJlYW0KZW5kb2JqCjM1IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzA3ID4+CnN0cmVhbQp4nD2SS24DMQxD9z6FLhDA+tme86Qoupjef9snJemKHNkWRWqWukxZUx6QNJOEf+nwcLGd8jtsz2Zm4Fqil4nllOfQFWLuonzZzEZdWSfF6oRmOrfoUTkXBzZNqp+rLKXdLngO1yaeW/YRP7zQoB7UNS4JN3RXo2UpNGOq+3/Se/yMMuBqTF1sUqt7HzxeRFXo6AdHiSJjlxfn40EJ6UrCaFqIlXdFA0Hu8rTKewnu295qyLIHqZjOOylmsOt0Ui5uF4chHsjyqPDlo9hrQs/4sCsl9EjYhjNyJ+5oxubUyOKQ/t6NBEuPrmgh8+CvbtYuYLxTOkViZE5yrGmLVU73UBTTucO9DBD1bEVDKXOR1epfw84La5ZsFnhK+gUeo90mSw5W2duoTu+tPNnQ9x9a13QfCmVuZHN0cmVhbQplbmRvYmoKMzYgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA2OCA+PgpzdHJlYW0KeJwzNrRQMFAwN1fQNTQ0VTAyMlAwNDJRSDHkMjQ0BzNzuWCCOWCWiQGQYQgkwRpyuGBac8A6ILJQrTlcGVxpAHGiEmcKZW5kc3RyZWFtCmVuZG9iagozNyAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDIzMSA+PgpzdHJlYW0KeJw1TzmSBCEMy3mFPjBVGNtAv6entjbY+X+6kplOkPAhydMTHZl4mSMjsGbH21pkIGbgU0zFv/a0DxOq9+AeIpSLC2GGkXDWrONuno4X/3aVz1gH7zb4illeENjCTNZXFmcu2wVjaZzEOclujF0TsY11radTWEcwoQyEdLbDlCBzVKT0yY4y5ug4kSeei+/22yx2OX4O6ws2jSEV5/gqeoI2g6Lsee8CGnJB/13d+B5Fu+glIBsJFtZRYu6c5YRfvXZ0HrUoEnNCmkEuEyHN6SqmEJpQrLOjoFJRcKk+p+isn3/lX1wtCmVuZHN0cmVhbQplbmRvYmoKMzggMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAyNDkgPj4Kc3RyZWFtCnicPVA7jkQhDOs5hS/wJPIjcB5Gqy1m79+uA5opUEx+tjMk0BGBRwwxlK/jJa2groG/i0LxbuLrg8Igq0NSIM56D4h07KY2kRM6HZwzP2E3Y47ARTEGnOl0pj0HJjn7wgqEcxtl7FZIJ4mqIo7qM44pnip7n3gWLO3INlsnkj3kIOFSUonJpZ+Uyj9typQKOmbRBCwSueBkE004y7tJUowZlDLqHqZ2In2sPMijOuhkTc6sI5nZ00/bmfgccLdf2mROlcd0Hsz4nLTOgzkVuvfjiTYHTY3a6Oz3E2kqL1K7HVqdfnUSld0Y5xgSl2d/Gd9k//kH/odaIgplbmRzdHJlYW0KZW5kb2JqCjM5IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzk1ID4+CnN0cmVhbQp4nD1SS27FQAjb5xRcoNLwm895UlXdvPtva0NSqSq8iTHGMH3KkLnlS10ScYXJt16uWzymfC5bWpl5iLuLjSU+ttyX7iG2XXQusTgdR/ILMp0qRKjNqtGh+EKWhQeQTvChC8J9Of7jL4DB17ANuOE9MkGwJOYpQsZuURmaEkERYeeRFaikUJ9Zwt9R7uv3MgVqb4ylC2Mc9Am0BUJtSMQC6kAAROyUVK2QjmckE78V3WdiHGDn0bIBrhlURJZ77MeIqc6ojLxExD5PTfoolkwtVsZuUxlf/JSM1Hx0BSqpNPKU8tBVs9ALWIl5EvY5/Ej459ZsIYY6btbyieUfM8UyEs5gSzlgoZfjR+DbWXURrh25uM50gR+V1nBMtOt+yPVP/nTbWs11vHIIokDlTUHwuw6uRrHExDI+nY0peqIssBqavEYzwWEQEdb3w8gDGv1yvBA0p2sitFgim7ViRI2KbHM9vQTWTO/FOdbDE8Js753WobIzMyohgtq6hmrrQHazvvNwtp8/M+iibQplbmRzdHJlYW0KZW5kb2JqCjQwIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMjQ5ID4+CnN0cmVhbQp4nE1RSYoDMAy75xX6QCFek7ynQ5lD5//Xyg6FOQQJr5KTlphYCw8xhB8sPfiRIXM3/Rt+otm7WXqSydn/mOciU1H4UqguYkJdiBvPoRHwPaFrElmxvfE5LKOZc74HH4W4BDOhAWN9STK5qOaVIRNODHUcDlqkwrhrYsPiWtE8jdxu+0ZmZSaEDY9kQtwYgIgg6wKyGCyUNjYTMlnOA+0NyQ1aYNepG1GLgiuU1gl0olbEqszgs+bWdjdDLfLgqH3x+mhWl2CF0Uv1WHhfhT6YqZl27pJCeuFNOyLMHgqkMjstK7V7xOpugfo/y1Lw/cn3+B2vD838XJwKZW5kc3RyZWFtCmVuZG9iago0MSAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDk0ID4+CnN0cmVhbQp4nEWNwRHAIAgE/1RBCQoK2k8mk4f2/40QMnxg5w7uhAULtnlGHwWVJl4VWAdKY9xQj0C94XItydwFD3Anf9rQVJyW03dpkUlVKdykEnn/DmcmkKh50WOd9wtj+yM8CmVuZHN0cmVhbQplbmRvYmoKNDIgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAzMjIgPj4Kc3RyZWFtCnicNVG7bcUwDOw1BRcwIH4lzeMgSJG3f5s72qlI07wfVV4ypVwudckqWWHypUN1iqZ8nmam/A71kOOYHtkhulPWlnsYFpaJeUodsZos93ALNr4AmhJzC/H3CPArgFHARKBu8fcPulkSQBoU/BTomquWWGICDYuFrdkV4lbdKVi4q/h2JLkHCXIxWehTDkWKKbfAfBks2ZFanOtyWQr/bn0CGmGFOOyzi0TgecADTCT+ZIBszz5b7OrqRTZ2hjjp0ICLgJvNJAFBUzirPrhh+2q75ueZKCc4OdavojG+DU7mS1LeV7nHz6BB3vgzPGd3jlAOmlAI9N0CIIfdwEaEPrXPwC4Dtkm7d2NK+ZxkKb4ENgr2qFMdyvBi7MxWb9j8x+jKZlFskJX10ekOytygE2Ieb2ShW7K2+zcPs33/AV8Ze2QKZW5kc3RyZWFtCmVuZG9iago0MyAwIG9iago8PCAvRmlsdGVyIC9GbGF0ZURlY29kZSAvTGVuZ3RoIDgzID4+CnN0cmVhbQp4nEWMuw3AMAhEe6ZgBH4m9j5RlMLevw0QJW64J909XB0JmSluM8NDBp4MLIZdcYH0ljALXEdQjp3so2HVvuoEjfWmUvPvD5Se7KzihusBAkIaZgplbmRzdHJlYW0KZW5kb2JqCjQ0IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTYwID4+CnN0cmVhbQp4nEWQORIDMQgEc72CJ0hcgvesy7XB+v+pB9ZHoukCNBy6Fk3KehRoPumxRqG60GvoLEqSRMEWkh1Qp2OIOyhITEhjkki2HoMjmlizXZiZVCqzUuG0acXCv9la1chEjXCN/InpBlT8T+pclPBNg6+SMfoYVLw7g4xJ+F5F3Fox7f5EMLEZ9glvRSYFhImxqdm+z2CGzPcK1zjH8w1MgjfrCmVuZHN0cmVhbQplbmRvYmoKNDUgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCA3MCA+PgpzdHJlYW0KeJwzMzZTMFCwMAISpqaGCuZGlgophlxAPoiVywUTywGzzCzMgSwjC5CWHC5DC2MwbWJspGBmYgZkWSAxILoyuNIAmJoTAwplbmRzdHJlYW0KZW5kb2JqCjQ2IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzIwID4+CnN0cmVhbQp4nDVSS24FMQjbzym4QKXwT87zqqqLvvtvaxO9FUwwYOMpL1nSS77UJdulw+RbH/clsULej+2azFLF9xazFM8tr0fPEbctCgRREz1YmS8VItTP9Og6qHBKn4FXCLcUG7yDSQCDavgHHqUzIFDnQMa7YjJSA4Ik2HNpcQiJciaJf6S8nt8nraSh9D1Zmcvfk0ul0B1NTugBxcrFSaBdSfmgmZhKRJKX632xQvSGwJI8PkcxyYDsNoltogUm5x6lJczEFDqwxwK8ZprVVehgwh6HKYxXC7OoHmzyWxOVpB2t4xnZMN7LMFNioeGwBdTmYmWC7uXjNa/CiO1Rk13DcO6WzXcI0Wj+GxbK4GMVkoBHp7ESDWk4wIjAnl44xV7zEzkOwIhjnZosDGNoJqd6jonA0J6zpWHGxx5a9fMPVOl8hwplbmRzdHJlYW0KZW5kb2JqCjQ3IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMTggPj4Kc3RyZWFtCnicMza0UDCAwxRDrjQAHeYDUgplbmRzdHJlYW0KZW5kb2JqCjQ4IDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMzQwID4+CnN0cmVhbQp4nDVSOW4EMQzr/Qp9IIBu2+/ZIEiR/L8NqdkUA3F0UpQ7WlR2y4eFVLXsdPm0ldoSN+R3ZYXECcmrEu1ShkiovFYh1e+ZMq+3NWcEyFKlwuSk5HHJgj/DpacLx/m2sa/lyB2PHlgVI6FEwDLFxOgals7usGZbfpZpwI94hJwr1i3HWAVSG9047Yr3oXktsgaIvZmWigodVokWfkHxoEeNffYYVFgg0e0cSXCMiVCRgHaB2kgMOXssdlEf9DMoMRPo2htF3EGBJZKYOcW6dPTf+NCxoP7YjDe/OirpW1pZY9I+G+2Uxiwy6XpY9HTz1seDCzTvovzn1QwSNGWNksYHrdo5hqKZUVZ4t0OTDc0xxyHzDp7DGQlK+jwUv48lEx2UyN8ODaF/Xx6jjJw23gLmoj9tFQcO4rPDXrmBFUoXa5L3AalM6IHp/6/xtb7X1x8d7YDGCmVuZHN0cmVhbQplbmRvYmoKNDkgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAyNTEgPj4Kc3RyZWFtCnicLVFJcgNBCLvPK/SEZqffY5crh+T/1wjKBwYNi0B0WuKgjJ8gLFe85ZGraMPfMzGC3wWHfivXbVjkQFQgSWNQNaF28Xr0HthxmAnMk9awDGasD/yMKdzoxeExGWe312XUEOxdrz2ZQcmsXMQlExdM1WEjZw4/mTIutHM9NyDnRliXYZBuVhozEo40hUghhaqbpM4EQRKMrkaNNnIU+6Uvj3SGVY2oMexzLW1fz004a9DsWKzy5JQeXXEuJxcvrBz09TYDF1FprPJASMD9bg/1c7KT33hL584W0+N7zcnywlRgxZvXbkA21eLfvIjj+4yv5+f5/ANfYFuICmVuZHN0cmVhbQplbmRvYmoKNTAgMCBvYmoKPDwgL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0xlbmd0aCAxNDEgPj4Kc3RyZWFtCnicPY/BDsMwCEPv+Qr/QKTYKaF8T6dqh+7/ryNLuwt6AmOMhdDQG6qaw4Zgm+PF0iVUa/gUxUAlN8iZYA6lpNIdR5F6YjgYXB60G47isej6EbuSZn3QxkK6JWiAe6xTadymcRPEHTUF6inqnKO8ELmfqWfYNJLdNLOSc7gNv3vPU9f/p6u8y/kFvXcu/gplbmRzdHJlYW0KZW5kb2JqCjUxIDAgb2JqCjw8IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9MZW5ndGggMjE1ID4+CnN0cmVhbQp4nDVROQ4DIQzs9xX+QCSML3hPoijN/r/NjNFWHsFchrSUIZnyUpOoIeVTPnqZLpy63NfMajTnlrQtc4C4trwvrZLAiWaIg8FpmLgBmjwBQ9fRqFFDFx7Q1KVTKLDcBD6Kt24P3WO1gZe2IeeJIGIoGSxBzalFExZtzyekNb9eixvel+3dyFOlxpYYgQYBVjgc1+jX8JU9TybRdBUy1Ks1yxgJE0UiPPmOptUT61o00jIS1MYRrGoDvDv9ME4AABNxywJkn0qUs+TEb7H0swZX+v4Bn0dUlgplbmRzdHJlYW0KZW5kb2JqCjMxIDAgb2JqCjw8IC9CYXNlRm9udCAvRGVqYVZ1U2FucyAvQ2hhclByb2NzIDMyIDAgUgovRW5jb2RpbmcgPDwKL0RpZmZlcmVuY2VzIFsgMzIgL3NwYWNlIDQ0IC9jb21tYSA0OCAvemVybyAvb25lIC90d28gL3RocmVlIC9mb3VyIC9maXZlIC9zaXggL3NldmVuCi9laWdodCAvbmluZSA3MiAvSCA3NiAvTCA5NyAvYSAxMDAgL2QgL2UgMTE0IC9yIDEyMSAveSBdCi9UeXBlIC9FbmNvZGluZyA+PgovRmlyc3RDaGFyIDAgL0ZvbnRCQm94IFsgLTEwMjEgLTQ2MyAxNzk0IDEyMzMgXSAvRm9udERlc2NyaXB0b3IgMzAgMCBSCi9Gb250TWF0cml4IFsgMC4wMDEgMCAwIDAuMDAxIDAgMCBdIC9MYXN0Q2hhciAyNTUgL05hbWUgL0RlamFWdVNhbnMKL1N1YnR5cGUgL1R5cGUzIC9UeXBlIC9Gb250IC9XaWR0aHMgMjkgMCBSID4+CmVuZG9iagozMCAwIG9iago8PCAvQXNjZW50IDkyOSAvQ2FwSGVpZ2h0IDAgL0Rlc2NlbnQgLTIzNiAvRmxhZ3MgMzIKL0ZvbnRCQm94IFsgLTEwMjEgLTQ2MyAxNzk0IDEyMzMgXSAvRm9udE5hbWUgL0RlamFWdVNhbnMgL0l0YWxpY0FuZ2xlIDAKL01heFdpZHRoIDEzNDIgL1N0ZW1WIDAgL1R5cGUgL0ZvbnREZXNjcmlwdG9yIC9YSGVpZ2h0IDAgPj4KZW5kb2JqCjI5IDAgb2JqClsgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAKNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCAzMTggNDAxIDQ2MCA4MzggNjM2Cjk1MCA3ODAgMjc1IDM5MCAzOTAgNTAwIDgzOCAzMTggMzYxIDMxOCAzMzcgNjM2IDYzNiA2MzYgNjM2IDYzNiA2MzYgNjM2IDYzNgo2MzYgNjM2IDMzNyAzMzcgODM4IDgzOCA4MzggNTMxIDEwMDAgNjg0IDY4NiA2OTggNzcwIDYzMiA1NzUgNzc1IDc1MiAyOTUKMjk1IDY1NiA1NTcgODYzIDc0OCA3ODcgNjAzIDc4NyA2OTUgNjM1IDYxMSA3MzIgNjg0IDk4OSA2ODUgNjExIDY4NSAzOTAgMzM3CjM5MCA4MzggNTAwIDUwMCA2MTMgNjM1IDU1MCA2MzUgNjE1IDM1MiA2MzUgNjM0IDI3OCAyNzggNTc5IDI3OCA5NzQgNjM0IDYxMgo2MzUgNjM1IDQxMSA1MjEgMzkyIDYzNCA1OTIgODE4IDU5MiA1OTIgNTI1IDYzNiAzMzcgNjM2IDgzOCA2MDAgNjM2IDYwMCAzMTgKMzUyIDUxOCAxMDAwIDUwMCA1MDAgNTAwIDEzNDIgNjM1IDQwMCAxMDcwIDYwMCA2ODUgNjAwIDYwMCAzMTggMzE4IDUxOCA1MTgKNTkwIDUwMCAxMDAwIDUwMCAxMDAwIDUyMSA0MDAgMTAyMyA2MDAgNTI1IDYxMSAzMTggNDAxIDYzNiA2MzYgNjM2IDYzNiAzMzcKNTAwIDUwMCAxMDAwIDQ3MSA2MTIgODM4IDM2MSAxMDAwIDUwMCA1MDAgODM4IDQwMSA0MDEgNTAwIDYzNiA2MzYgMzE4IDUwMAo0MDEgNDcxIDYxMiA5NjkgOTY5IDk2OSA1MzEgNjg0IDY4NCA2ODQgNjg0IDY4NCA2ODQgOTc0IDY5OCA2MzIgNjMyIDYzMiA2MzIKMjk1IDI5NSAyOTUgMjk1IDc3NSA3NDggNzg3IDc4NyA3ODcgNzg3IDc4NyA4MzggNzg3IDczMiA3MzIgNzMyIDczMiA2MTEgNjA1CjYzMCA2MTMgNjEzIDYxMyA2MTMgNjEzIDYxMyA5ODIgNTUwIDYxNSA2MTUgNjE1IDYxNSAyNzggMjc4IDI3OCAyNzggNjEyIDYzNAo2MTIgNjEyIDYxMiA2MTIgNjEyIDgzOCA2MTIgNjM0IDYzNCA2MzQgNjM0IDU5MiA2MzUgNTkyIF0KZW5kb2JqCjMyIDAgb2JqCjw8IC9IIDMzIDAgUiAvTCAzNCAwIFIgL2EgMzUgMCBSIC9jb21tYSAzNiAwIFIgL2QgMzcgMCBSIC9lIDM4IDAgUgovZWlnaHQgMzkgMCBSIC9maXZlIDQwIDAgUiAvZm91ciA0MSAwIFIgL25pbmUgNDIgMCBSIC9vbmUgNDMgMCBSIC9yIDQ0IDAgUgovc2V2ZW4gNDUgMCBSIC9zaXggNDYgMCBSIC9zcGFjZSA0NyAwIFIgL3RocmVlIDQ4IDAgUiAvdHdvIDQ5IDAgUiAveSA1MCAwIFIKL3plcm8gNTEgMCBSID4+CmVuZG9iagozIDAgb2JqCjw8IC9GMSAzMSAwIFIgPj4KZW5kb2JqCjQgMCBvYmoKPDwgL0ExIDw8IC9DQSAwIC9UeXBlIC9FeHRHU3RhdGUgL2NhIDEgPj4KL0EyIDw8IC9DQSAxIC9UeXBlIC9FeHRHU3RhdGUgL2NhIDEgPj4gPj4KZW5kb2JqCjUgMCBvYmoKPDwgPj4KZW5kb2JqCjYgMCBvYmoKPDwgPj4KZW5kb2JqCjcgMCBvYmoKPDwgL0kxIDEzIDAgUiAvSTEwIDIyIDAgUiAvSTExIDIzIDAgUiAvSTEyIDI0IDAgUiAvSTEzIDI1IDAgUiAvSTE0IDI2IDAgUgovSTE1IDI3IDAgUiAvSTE2IDI4IDAgUiAvSTIgMTQgMCBSIC9JMyAxNSAwIFIgL0k0IDE2IDAgUiAvSTUgMTcgMCBSCi9JNiAxOCAwIFIgL0k3IDE5IDAgUiAvSTggMjAgMCBSIC9JOSAyMSAwIFIgPj4KZW5kb2JqCjEzIDAgb2JqCjw8IC9CaXRzUGVyQ29tcG9uZW50IDgKL0NvbG9yU3BhY2UgWy9JbmRleGVkIC9EZXZpY2VSR0IgMjIgKP3nJPPlHvHlHOHjGNThGmvNWS6yfB+jhiOJjSOHjSd8jkFChkU0f0YvfEcWaUcRY0YOYUYLXkUIW0UGWkUFWEQCVUQBVCldCi9EZWNvZGVQYXJtcyA8PCAvQ29sb3JzIDEgL0NvbHVtbnMgMTE5IC9QcmVkaWN0b3IgMTAgPj4KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0hlaWdodCAxMTkgL0xlbmd0aCA1MiAwIFIgL1N1YnR5cGUgL0ltYWdlCi9UeXBlIC9YT2JqZWN0IC9XaWR0aCAxMTkgPj4Kc3RyZWFtCnic7djBTgJBFABBQEQFEUHl/z+Va18wu4sLMak+vsxMHSd5i/P0Fmn0XS6Xy+XO5ravtExcLpfLndH9SRm/pc/0mk6Jy+VyuX/sjmyV+l9wuVwu97HukH0Ll8vlcu/vvqRt4nK53H/vvqcb3E3apa5JuFwulzvCHdlTunbmkDrncrlc7nzutdbpI3G5XC53ovucBrx/TJ33L/hO+8Tlcrnc390LnyIhlwplbmRzdHJlYW0KZW5kb2JqCjUyIDAgb2JqCjE2OAplbmRvYmoKMTQgMCBvYmoKPDwgL0JpdHNQZXJDb21wb25lbnQgOAovQ29sb3JTcGFjZSBbL0luZGV4ZWQgL0RldmljZVJHQiAyMiAo/eck8+Ue7uUb7OQandk6gdNMdNBUZ8xcXCyxfR6diCaBji9qjUM8hEYvfEcse0cRY0YMX0YJXFxFBlpFBVhEA1dEAlVEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNTMgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3ZuQ6DMBAAUSchB+QgF/z/p6adxvEupIk002EZP9GAZcqMJjTneqHanA0qurq6urrf3Tu6oqS7R2/ER+G4rq6urm7D5c0nlHTZGdHiHF1dXV3dhFvQCjeSrq6urm7D5YHIFv1ofe7bdXV1dXUTLi96tMIaUG2Orq6u7l+6TxRYv0Mcjxxj6+rq6uom3BEF3BviPvmA+PtRV1dXV3ehu0MBt/bv74Fq9+rq6urqNly+0I8o4DJ+Ui5IV1dXV3eZ+wEDZSBfCmVuZHN0cmVhbQplbmRvYmoKNTMgMCBvYmoKMTk5CmVuZG9iagoxNSAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDMxICj95yTU4Rqy3Sxky11iyl9gyWBAvXI+vHMhjYwii404V4w6UotDPIRGL3xHJ3dIHnBIHW9IHG5HGGpHFmlHFWdHFGZHEmVHEWNGDmFGDF9GC15FCFtFBVhEA1dEAlVEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNTQgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3ayRKCMBAAUdx3cd9A8v9/6dG+DCHerOo+xoSHF5mirBLq0ID1O+L2MXqiI6p0dXV1dfvdFvFwG4SzL3RGNZoiXl5XV1dXN+OmoDcKtqwQ15foivh40dXV1dXNuGvEw9zEe8Ayt89Q9FWYrq6urm7Gjeb2BnEdtzBC3HJD0WV0dXV1dTPuFvGDDeJ6MKvvUBqQrq6u7t+4c8SZ+YD2CO+WOVafUBfM2Lq6urq6BW70fmOCosMoGsN1dXV1dX90OXBfEP88xx/6xTdup/tAfHbo6urq6ha4LJXVBPE2o7O6urq6uv3uB37MTV0KZW5kc3RyZWFtCmVuZG9iago1NCAwIG9iagoyMzcKZW5kb2JqCjE2IDAgb2JqCjw8IC9CaXRzUGVyQ29tcG9uZW50IDgKL0NvbG9yU3BhY2UgWy9JbmRleGVkIC9EZXZpY2VSR0IgMTYgKP3nJM3gHafbM3DOVlvIYiClhR6aiSSFjVwpeY5AQ4dDO4NGLXxIHG5HEmVGDmFEAlVEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNTUgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3aORKDMBBFQXnfDfc/rUO+A2FU2ASmX8ZUaVoRJJQ+2kU576Ln0DXqGytcLpfLne6WqHURl8vlcn/nHqPagdMQl8vlchdy1/Y94nK5XC6Xy+Vy57hfahPl/B5xuVzumt1aZcH3P5fL5f6Ve4lm7N9Hj+jtDlwul8sddw9R4/787S7n56h2lsvlcrkf3HzYRo13mNIt4nK5XO64+wLuxw6WCmVuZHN0cmVhbQplbmRvYmoKNTUgMCBvYmoKMTYzCmVuZG9iagoxNyAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDY3ICj95yTk4xheyWEnfo4floskhI0lg40nfI5cKXiOKneOLW+OLm2OLmuOL2mNMGiNMWWNMmKNNluMNlqMOFeMOVWLOlKLPE6KPE2KPUyJPUuJPUqJPkiIP0eIP0WHQESHQUKGQkCFQj6FQzuDQzqDRDmCRTaBRTWARTR/RjF+RjB9Ri98Ri18Ryx7Ryd3RyZ2RyV1SCN0SCJzSCBxSB5wSBxuSBpsSBlrRxZpRxVnRxJlRxFjRg5hRgxfRgteRglcXEUIW0UGWkUFWEQCVUQBVCldCi9EZWNvZGVQYXJtcyA8PCAvQ29sb3JzIDEgL0NvbHVtbnMgMTE5IC9QcmVkaWN0b3IgMTAgPj4KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0hlaWdodCAxMTkgL0xlbmd0aCA1NiAwIFIgL1N1YnR5cGUgL0ltYWdlCi9UeXBlIC9YT2JqZWN0IC9XaWR0aCAxMTkgPj4Kc3RyZWFtCnic7dq3UsNAAEVRGTA555xzMjkHA///T5R7Grw1M+/01lVl7TypmcQVljGPwWINu3jEBzpo0k033XTT7d2dwSG2sYeBwu4R3vCJDaSbbrrpplvpLuAUXnQHreIVd/jBF26RbrrppptupXsArz+LMwwXJ/DI/4AXtJFuuummm26lew7P55u4QFM84wnf6GId6aabbrrpVroO1l7fZ4F/+mwjI/AZMQ7P9tNIN9100/03XYfjfSzBF3ucnxdx+Yd3DCHddNNNN91K15Y/cCw+xlQxgTn4HtDvN5xM0k033XTTrXS3cI0VuFGPFqtwJrmB+3M/0k033XTTrXT9WNlxxC3lHmOFc7WPFG/TXaUP6aabbrrp9u7+AmAlz0cKZW5kc3RyZWFtCmVuZG9iago1NiAwIG9iagoyODMKZW5kb2JqCjE4IDAgb2JqCjw8IC9CaXRzUGVyQ29tcG9uZW50IDgKL0NvbG9yU3BhY2UgWy9JbmRleGVkIC9EZXZpY2VSR0IgNjUgKP3nJPPlHqXaNY3WRIbUSWvNWVvIYkK+cUC9cjO2eVwpr39cKK5/JauBH5aLII+MI4eNJIWNJ36OJ32OKnWOLHCOLW+OLm2OMWSNMmKNM2GNNF+NN1mMOVWLOlOLPkiIP0eIQEOHQUKGQUGGQzuDRDmCRDeBRTaBRTWARTR/RTJ/RjF+RjB9Ri98Ri18Ryx7Ryp5R1woeEcnd0cmdkcldUgjdEgic0ggcUgecEgdb0gabEcYakcVZ0cUZkcRY0cPYkYOYUYMX0QBVCldCi9EZWNvZGVQYXJtcyA8PCAvQ29sb3JzIDEgL0NvbHVtbnMgMTE5IC9QcmVkaWN0b3IgMTAgPj4KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0hlaWdodCAxMTkgL0xlbmd0aCA1NyAwIFIgL1N1YnR5cGUgL0ltYWdlCi9UeXBlIC9YT2JqZWN0IC9XaWR0aCAxMTkgPj4Kc3RyZWFtCnic7dq3UsNAFIZRkXMwOZtkcgabnN7/pSj3UOCtmflPbetTtfeOpGYFc9jFNpaKIXzgBq/4RpNuuummm27/rtffwxkuMVuM4BQt3OEF6aabbrrpVrqL2MECOqC1iSs84hrOi3TTTTfddCvdI7ifOyMOsVoM4g0zuMUX0k033XTTrXTb2McGPPSHi2W42m/BkXKPdNNNN910K90LuGQ/4BhrxQD86xRs/ZoL6aabbrr/pev1PUxP8Iz5YgI+uxiFR3sX6aabbrrpVrq2DuBC7Mu/8WISPrpeh68Zn5Buuummm26l697uLHDhPgff1zXwO42/nj+/I91000033Uq3B+/BA93fjBXTcG93XnjLn0g33XTTTbd/9wf3SqFGCmVuZHN0cmVhbQplbmRvYmoKNTcgMCBvYmoKMjg0CmVuZG9iagoxOSAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDI5ICj95yT65iLh4xjK4B7H4B+a2Dx+0k5nzFxcPbt0LmuOMWSNNVxcjEBDh0U2gUcqeUcmdkgjdEgdb0gZa0cUZkcPYkYOYUYMX0YLXkYJXFxFBlpFBVhEA1dEAlVEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNTggMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3ZuQ7CMBAAUXPfhPsK/P9vUmaaTVhCgzRTrpy80NiSKTU6IM6v6N60Rzc0Q2f0QEVXV1dXt919fR8/7YnGiPMK6erq6up2uHz4GHRBuybu81y+RDxqFkhXV1dXt8PtcS5wz+d8gLjmhHR1dXV1Ey43ep4XXIMx38lH54j3LSukq6urq5twk0WfVhDnvAPX1dXV/UuXG26P7xkivpL/J+rq6urqJtxoow+qgyaI7gbp6urq6iZcLvrAja5DpojzNdLV1dXVTbg/aoT4U7ZIV1dXV7fdfQPt3xrRCmVuZHN0cmVhbQplbmRvYmoKNTggMCBvYmoKMjIwCmVuZG9iagoyMCAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDczICj95ySV1z9eyWFCvnE9u3QztnlcKa9/J32OJ3yOIKWFHqCHHpqJIoqNJIWNJoGOXCl5jitzjixyjixxji5tji5sji9pjTBojTFmjTRejTVdjDZajDdZjDhXjDpTizpSizxNij1MiT1KiT5JiT5IiD9HiD9Fh0FChkFBhkJAhUI+hUI9hEM8hEM7g0M6g0Q5gkU2gUU1gEU0f0YtfEcrekcqeUdcKHhHJnZHJXVII3RIInNIIHFIGmxIGWtHGGpHFmlHFGZHEWNHD2JGDmFGDF9GC15GCVxcRQhbRQZaRQVYRANXKV0KL0RlY29kZVBhcm1zIDw8IC9Db2xvcnMgMSAvQ29sdW1ucyAxMTkgL1ByZWRpY3RvciAxMCA+PgovRmlsdGVyIC9GbGF0ZURlY29kZSAvSGVpZ2h0IDExOSAvTGVuZ3RoIDU5IDAgUiAvU3VidHlwZSAvSW1hZ2UKL1R5cGUgL1hPYmplY3QgL1dpZHRoIDExOSA+PgpzdHJlYW0KeJzt2jVyxUAQRVGZmZmZmZm/af8bcjgn8Vc5dNU7mZK5ykbV6uoCsxjDKLqLa7xhEld4RZVuuummm27zrg97OMEaJopbfKALL+hAuummm266Nd1HzGMDu2gpbD3A1g1GkG666aabbk23gQOsw3uhp7jHN8Zxh0Gkm2666ab7h+4xtrCDqmj84hSXmEa66aabbro1XQfTds/gPJxZ9zDe0Qa/4ReQbrrppvtvus6fnTmvYhudxRM+sQTHJ71IN9100023puuQYhH7GMJA4eqHrz+HZ0wh3XTTTTfdmq6Lcf7M89BNLBfn8F7og3dHK9JNN910063puoRxhEOsoL3wzC/MwL2OfqSbbrrpptu8+wMnBj3gCmVuZHN0cmVhbQplbmRvYmoKNTkgMCBvYmoKMjc2CmVuZG9iagoyMSAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDUwICj95ySa2DyX2D6D00tnzFxcV8ZlUcRoS8JsPrxzXCmvfyGmhSClhR+ihh6aiR6XiiSFjSaBjlwoeo4qdo4tbo49S4k+SIg/R4hAQ4dBQYZEOYJGLXxHLHtHXCh4Ryd3SCJzSCFySCBxSB5wSB1vSBxuSBpsSBlrRxhqRxVnRxRmRxFjRw9iRg5hRgxfRgteRglcXEUIW0UGWkUFWEQDVyldCi9EZWNvZGVQYXJtcyA8PCAvQ29sb3JzIDEgL0NvbHVtbnMgMTE5IC9QcmVkaWN0b3IgMTAgPj4KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0hlaWdodCAxMTkgL0xlbmd0aCA2MCAwIFIgL1N1YnR5cGUgL0ltYWdlCi9UeXBlIC9YT2JqZWN0IC9XaWR0aCAxMTkgPj4Kc3RyZWFtCnic7dpHbhsxAEBRufcWx723JI5LIt//cF7qGcZ41gb+X0qceVyRBKXJMd3SEZ3Swaw9+kP7dEFvNMnNzc3N/dr9RS/0e6CTWXP0j3Zp6JW5ubm5uSPuIbkv7NANbcxy+F+6JPeFV8rNzc3NHXHvyUX8jjyUc8xfof+0Tc7niXJzc3NzR9yfdEU/6Jq2ZvmxUzunM3qk3Nzc3NwRd0ou7l5Su19wfzJP3qssk5+7BeXm5uZ+G9dF0/d72HUM9xVL5N3FGnl+fqDc3Nzc3BHXL3Rd0B3DOXmRnmmVnPKH3wdzc3Nzc792PatPB3I+vGdCDt8kX+8dSG5ubm7uiOvC7eHbhd59gb9yLJCPrpOPDt6r5Obm5uZ+ct8BiHUtHQplbmRzdHJlYW0KZW5kb2JqCjYwIDAgb2JqCjI4NQplbmRvYmoKMjIgMCBvYmoKPDwgL0JpdHNQZXJDb21wb25lbnQgOAovQ29sb3JTcGFjZSBbL0luZGV4ZWQgL0RldmljZVJHQiA2NiAo/eck4eMY2uIYp9szndk6ktdBi9VGfNJPd9BSdNBUcs9Vbc5YZ8xcXGDJYF7JYVvIYlnHZFfGZU/DaU3Ca0nBbUfAbkS+cD68cz27dDm5dji5djK1eiyxfSuxfSqwflwpr39cKK5/JauBJYONJYKOJoGOJ32OXCh6jiSqgiOpgiOogyKnhCGnhCGmhSClhSCkhR+jhh+ihh+hhx6ghx6fiB6eiB6diB6ciR6aiR6Zih6Xih+Wix+Vix+Uix+SjCCRjCCQjCGNjCKLjSOHjSldCi9EZWNvZGVQYXJtcyA8PCAvQ29sb3JzIDEgL0NvbHVtbnMgMTE5IC9QcmVkaWN0b3IgMTAgPj4KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0hlaWdodCAxMTkgL0xlbmd0aCA2MSAwIFIgL1N1YnR5cGUgL0ltYWdlCi9UeXBlIC9YT2JqZWN0IC9XaWR0aCAxMTkgPj4Kc3RyZWFtCnic7dq3bsMwGIVRpcdxeu92eu/d6Xn/h/LIM5lzgHtGAdKnST9BqlnHDCaxg7HiD3f4xSke0aSbbrrppju4O48FTKGLVvGNc7zjCW9IN91000230p2DM2IYz2iKfXzgAM6CT6SbbrrpplvprmIafP9bmxgtjtDDF25xg3TTTTfddCvdCSxjCG6OMBcO8YNjvMJ5kW666aabbqXrgnsFrtVdfPNqS3BfZQRed48l3XTTTfffdD37W4Tv0EG7eIDPdLva9fMF0k033XTTrXRPwDPbG/CG8cJ/NnwHu46Ua6SbbrrpplvpvsC5sI09zBb3uIIj5QxbSDfddNNNt9K9hP/aeSbo7GAvxVv9/q/BM8FdpJtuuummO7jbBy3SYgYKZW5kc3RyZWFtCmVuZG9iago2MSAwIG9iagoyODYKZW5kb2JqCjIzIDAgb2JqCjw8IC9CaXRzUGVyQ29tcG9uZW50IDgKL0NvbG9yU3BhY2UgWy9JbmRleGVkIC9EZXZpY2VSR0IgNjYgKP3nJLreJ6rbMovVRobUSX7STnnRUXTQVHDOVm3OWGvNWWLKX17JYVvIYlnHZFfGZVPFZ0/DaU3Ca0fAbkS+cD68czu6dTm5dji5dja4dzW3eDK1ejC0ei+zeyyxfSuxfSqwflwpr39cKK5/J62AJqyBJauBJKqCI6iDIqeEIaeEIaaFIKWFIKSFH6OGH6KGH6GHHqCHHp+IHp6IHp2IHpuJHpqJHpmKHpiKHpeKH5SLH5OLIJCMIouNI4iNJIWNJYONJoGOXCl4jjFkjSldCi9EZWNvZGVQYXJtcyA8PCAvQ29sb3JzIDEgL0NvbHVtbnMgMTE5IC9QcmVkaWN0b3IgMTAgPj4KL0ZpbHRlciAvRmxhdGVEZWNvZGUgL0hlaWdodCAxMTkgL0xlbmd0aCA2MiAwIFIgL1N1YnR5cGUgL0ltYWdlCi9UeXBlIC9YT2JqZWN0IC9XaWR0aCAxMTkgPj4Kc3RyZWFtCnic7dm3TgNREIbRJWcwOWMw2eSc4/s/FOU9jX1rpP+UK2u+bseabVbQwgTaGC2+4U++0MEDmnTTTTfddPt3N7CMYZxjqnjDPj6xhxOkm2666aZb6e5iFUO4xkDh/Av4vAt3R7rppptuupWuL/RNTOIMY8UrbvECW45PN91000230t3COAbh//am+MEzftHtId1000033Up3G4s4gC/3o8KT+SGcv4ZHpJtuuun+m67z5zGNS4wUT7jCB9o9pJtuuummW+nuwL0wA7tzxTE8k7zD74M3SDfddNNNt9K9h7eOBXhc5rErxU+I7ghvzktIN91000230j2FXffCHWYL53tX8Rbt2llHuummm266/bt/O+ppLAplbmRzdHJlYW0KZW5kb2JqCjYyIDAgb2JqCjI3NgplbmRvYmoKMjQgMCBvYmoKPDwgL0JpdHNQZXJDb21wb25lbnQgOAovQ29sb3JTcGFjZSBbL0luZGV4ZWQgL0RldmljZVJHQiA1OSAo/eck+OYh4eMY1+IZzeAdyuAex+Afndk6mtg8ldc/kNZDi9VGhtRJgdNMftJOfNJPd9BScs9VcM5Wbc5Ya81ZZ8xcXGTLXWLKX2DJYF7JYVvIYlnHZFfGZVXGZlPFZ0/DaU3Ca0vCbEnBbUfAbkW/b0S+cEK+cT68cz27dDu6dTW3eDO2eS+zey6yfCyxfSuxfVwpr39cKK5/J62AJauBJKqCIqeEIaeEH6KGH6GHHp+IHpuJIY6MKV0KL0RlY29kZVBhcm1zIDw8IC9Db2xvcnMgMSAvQ29sdW1ucyAxMTkgL1ByZWRpY3RvciAxMCA+PgovRmlsdGVyIC9GbGF0ZURlY29kZSAvSGVpZ2h0IDExOSAvTGVuZ3RoIDYzIDAgUiAvU3VidHlwZSAvSW1hZ2UKL1R5cGUgL1hPYmplY3QgL1dpZHRoIDExOSA+PgpzdHJlYW0KeJzt2rVyAzEYhdFNHEaHHTAEHGaG93+vlDopvKozc79eOqpWmn+22aJtWqIBdUpXdD+hc3qmJm7cuHHjtrundEirdETjkvvskefZpA2KGzdu3LgV13tBd5awxnMl3Tt6IY98S3Hjxo0bt+K+0z6dkHcH3/xX8i5YoWWaprhx48aNW3HXaJ2myEf5TOmLbuiHXPpBcePGjRu34p7RAR3TLvVKXbqgHerTNcWNGzfuv3GfyAW+pV3MDNmxxyX53PZsf+bPcePGjRu33X0g7witITH2cFztGdy/O6G4cePGjVtxv8n9H8nhMu9zXe+CeeKZ32ssbty4ceO2u580Ii1nLG8l3+r+Ir1Ai8Sv0524cePGjdvu/gKK63VbCmVuZHN0cmVhbQplbmRvYmoKNjMgMCBvYmoKMjgyCmVuZG9iagoyNSAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDQ0ICj95yT45iHp5BknrYAmgI4mf44jqYIhp4Qjh40kho1cKHqOXCl4jit0jixwji1vji1uji5tji5sji9qjTBojTFmjTFljTFkjTJijTNhjTNgjTRfjTRejTVdjDZajDdZjDdYjDlVizlUizpTiztRij1LiUYxfkYvfEcse0dcKHhHFmlHFGZHEmVEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNjQgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3ZNw4CMRQAUXKOS845c//zUXooDLhEmikN+m+rteXNzdAZHdAF3UJPlEdcryKu53R1dXV1P7tdxGcooxUahjingbg+QLq6urq6Ce4UndARcV94hN7mIK5XkK6urq5ugttBS1RCW7QOcU4dcb2NdHV1dXUT3AnivcoeXdE9xDkFxPUi0tXV1dVNcHuI73++6PkM+DvnxO5VeG2jq6ur+5cuz88bVEM7lIU4p4m43ke6urq6ugkufxgjfh+co1bol/k8nuvq6urqJrixfYHndp7nI/Nj+0IW2Ud0dXV1db+4vFfhvsDvgwsUuVeJ3Z+MkK6urq7u7+4LgHj7WAplbmRzdHJlYW0KZW5kb2JqCjY0IDAgb2JqCjI1NAplbmRvYmoKMjYgMCBvYmoKPDwgL0JpdHNQZXJDb21wb25lbnQgOAovQ29sb3JTcGFjZSBbL0luZGV4ZWQgL0RldmljZVJHQiA0NSAo/eck3OIYut4nM7Z5Hp6IHpyJHpmKJn+OKnaOLHKOM2GNNluMN1mMOFeMOVSLOlKLO1GKO1CKPE2KPUyJPUqJPkmJQEOHQUKGQj6FQj2EQzyERTR/Ryp5R1woeEcnd0gjdEgic0gecEgZa0cSZUcRY0cPYkYOYUYMX0YLXkYJXFxFCFtFBVhEA1dEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNjUgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3YyU4CURBA0RYERJkUFGRSQAaF/v/fc9l3Ux0qrEjuXb6k6+z6VV5RoCN6RWdU5vpFPC90dXV1devdDhqgD/SOgjlbxPM10tXV1dVNuA20Q8/oD5W5fpCurq6ubsJtozGaoE8UrPDR/G+kq6urq5twHxA/7qMb7oUD0tXV1dVNuE00DVqgYH70vr1Burq6unfpPiLuz3x/5v58qeKcPeJ5uD/r6urq6ta7T6iH5miEkv//JdLV1dXVTbgt9Ia4t89QcC/waYTnX0hXV1dXN+F20QvivTBEpyrOie6FFdLV1dXVvd79B/rLAYMKZW5kc3RyZWFtCmVuZG9iago2NSAwIG9iagoyMzcKZW5kb2JqCjI3IDAgb2JqCjw8IC9CaXRzUGVyQ29tcG9uZW50IDgKL0NvbG9yU3BhY2UgWy9JbmRleGVkIC9EZXZpY2VSR0IgMzggKP3nJPPlHitzjjNhjTZbjDlUiztRijxOijxNij5IiD9HiD9Fh0BDh0FChkFBhkI+hUI9hEM8hEM7g0M6g0Q5gkU2gUU1gEUyf0YxfkYwfUYvfEYtfEcse0crekcqeUcnd0cmdkgjdEghckYLXkYJXFxFBVhEAVQpXQovRGVjb2RlUGFybXMgPDwgL0NvbG9ycyAxIC9Db2x1bW5zIDExOSAvUHJlZGljdG9yIDEwID4+Ci9GaWx0ZXIgL0ZsYXRlRGVjb2RlIC9IZWlnaHQgMTE5IC9MZW5ndGggNjYgMCBSIC9TdWJ0eXBlIC9JbWFnZQovVHlwZSAvWE9iamVjdCAvV2lkdGggMTE5ID4+CnN0cmVhbQp4nO3atw7CQBAAUZNzzibH//9EyptmDZagAM2Ui3SPbq2zsww90Alxfk9xfECc3xDnma6urq5usdtGfTREA7RP8Zw14nyKdHV1dXVLuBXEH86I82AvRO4V6erq6uqWcGsoR120RMcUz5khzidIV1dXV7eE+6G9sEGcf3sf6erq6v6tW0UX1ES4S9ljdfCcPJhzpejq6ur+pNtAvCzuIT4Eb1M8J7rfCO+fdXV1dXWLXb4H5LvCMeqgVYrncHVwHt176Orq6uq+cGnxP/BbjhHapXhOtBe4UnR1dXV1S7gLVEect1Bwzxx9/zxHurq6urrvu08Qz7KiCmVuZHN0cmVhbQplbmRvYmoKNjYgMCBvYmoKMjQ3CmVuZG9iagoyOCAwIG9iago8PCAvQml0c1BlckNvbXBvbmVudCA4Ci9Db2xvclNwYWNlIFsvSW5kZXhlZCAvRGV2aWNlUkdCIDQzICj95yTa4hjS4RsnfI4tb44tbo4wZ40xZY02W4w3WIxBQoZBQYZCQIVCPoVCPYRFNYBFNH9FMn9GMX5GMH1GL3xGLXxHLHtHK3pHKnlHJ3dHJnZHJXVIGmxIGWtHFmlHFWdHFGZHEWNHD2JGDF9GC15GCVxcRQhbRQZaRQVYRANXRAJVRAFUKV0KL0RlY29kZVBhcm1zIDw8IC9Db2xvcnMgMSAvQ29sdW1ucyAxMTkgL1ByZWRpY3RvciAxMCA+PgovRmlsdGVyIC9GbGF0ZURlY29kZSAvSGVpZ2h0IDExOSAvTGVuZ3RoIDY3IDAgUiAvU3VidHlwZSAvSW1hZ2UKL1R5cGUgL1hPYmplY3QgL1dpZHRoIDExOSA+PgpzdHJlYW0KeJzt2jduw1AQAFEq52wr5yzr/vdzuSMIDCoFzJRb8LH6C3wyOaEd2qMZSqIn4mM4vyDOE11dXV3dbHeMeqiDOK9Ff2iBOJ+jO9LV1dXVzXGPaIO2aIJKEc95PobzM3rZC7q6urq62e4v6qfURZWIz1khzpeI+0JXV1dXN8c9oDXijuBeKEd8/sd7QVdXV1c32+W9SpG9UI0eiPcnPP9533JDurq6ul/jjlDa/TPfoR4VcTnnt0JdXV1d3Rx3gHj+p7nNiOc8f/Hgd0Ben/AfD11dXV3dHHeIuBfaiG4jKrIX+D5XpKurq6v7gUuLe4Hv04p4/k8R5z8odS/o6urq6r65/zv9i2gKZW5kc3RyZWFtCmVuZG9iago2NyAwIG9iagoyNjMKZW5kb2JqCjIgMCBvYmoKPDwgL0NvdW50IDEgL0tpZHMgWyAxMSAwIFIgXSAvVHlwZSAvUGFnZXMgPj4KZW5kb2JqCjY4IDAgb2JqCjw8IC9DcmVhdGlvbkRhdGUgKEQ6MjAyMTEyMDQxNjU5MzYrMDInMDAnKQovQ3JlYXRvciAoTWF0cGxvdGxpYiB2My40LjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcpCi9Qcm9kdWNlciAoTWF0cGxvdGxpYiBwZGYgYmFja2VuZCB2My40LjMpID4+CmVuZG9iagp4cmVmCjAgNjkKMDAwMDAwMDAwMCA2NTUzNSBmIAowMDAwMDAwMDE2IDAwMDAwIG4gCjAwMDAwMjQ3MjQgMDAwMDAgbiAKMDAwMDAxMzgzOCAwMDAwMCBuIAowMDAwMDEzODcwIDAwMDAwIG4gCjAwMDAwMTM5NjkgMDAwMDAgbiAKMDAwMDAxMzk5MCAwMDAwMCBuIAowMDAwMDE0MDExIDAwMDAwIG4gCjAwMDAwMDAwNjUgMDAwMDAgbiAKMDAwMDAwMDQwNiAwMDAwMCBuIAowMDAwMDA2ODY0IDAwMDAwIG4gCjAwMDAwMDAyMDggMDAwMDAgbiAKMDAwMDAwNjg0MyAwMDAwMCBuIAowMDAwMDE0MjE1IDAwMDAwIG4gCjAwMDAwMTQ3MTggMDAwMDAgbiAKMDAwMDAxNTI1NCAwMDAwMCBuIAowMDAwMDE1ODUzIDAwMDAwIG4gCjAwMDAwMTYzMzQgMDAwMDAgbiAKMDAwMDAxNzA4OSAwMDAwMCBuIAowMDAwMDE3ODQwIDAwMDAwIG4gCjAwMDAwMTg0MTkgMDAwMDAgbiAKMDAwMDAxOTE4NyAwMDAwMCBuIAowMDAwMDE5ODk2IDAwMDAwIG4gCjAwMDAwMjA2NTMgMDAwMDAgbiAKMDAwMDAyMTM5OSAwMDAwMCBuIAowMDAwMDIyMTMwIDAwMDAwIG4gCjAwMDAwMjI3ODggMDAwMDAgbiAKMDAwMDAyMzQzMSAwMDAwMCBuIAowMDAwMDI0MDYyIDAwMDAwIG4gCjAwMDAwMTI1MzUgMDAwMDAgbiAKMDAwMDAxMjMzNSAwMDAwMCBuIAowMDAwMDExOTE3IDAwMDAwIG4gCjAwMDAwMTM1ODggMDAwMDAgbiAKMDAwMDAwNjg4NCAwMDAwMCBuIAowMDAwMDA3MDM1IDAwMDAwIG4gCjAwMDAwMDcxNjggMDAwMDAgbiAKMDAwMDAwNzU0OCAwMDAwMCBuIAowMDAwMDA3Njg4IDAwMDAwIG4gCjAwMDAwMDc5OTIgMDAwMDAgbiAKMDAwMDAwODMxNCAwMDAwMCBuIAowMDAwMDA4NzgyIDAwMDAwIG4gCjAwMDAwMDkxMDQgMDAwMDAgbiAKMDAwMDAwOTI3MCAwMDAwMCBuIAowMDAwMDA5NjY1IDAwMDAwIG4gCjAwMDAwMDk4MjAgMDAwMDAgbiAKMDAwMDAxMDA1MyAwMDAwMCBuIAowMDAwMDEwMTk1IDAwMDAwIG4gCjAwMDAwMTA1ODggMDAwMDAgbiAKMDAwMDAxMDY3OCAwMDAwMCBuIAowMDAwMDExMDkxIDAwMDAwIG4gCjAwMDAwMTE0MTUgMDAwMDAgbiAKMDAwMDAxMTYyOSAwMDAwMCBuIAowMDAwMDE0Njk4IDAwMDAwIG4gCjAwMDAwMTUyMzQgMDAwMDAgbiAKMDAwMDAxNTgzMyAwMDAwMCBuIAowMDAwMDE2MzE0IDAwMDAwIG4gCjAwMDAwMTcwNjkgMDAwMDAgbiAKMDAwMDAxNzgyMCAwMDAwMCBuIAowMDAwMDE4Mzk5IDAwMDAwIG4gCjAwMDAwMTkxNjcgMDAwMDAgbiAKMDAwMDAxOTg3NiAwMDAwMCBuIAowMDAwMDIwNjMzIDAwMDAwIG4gCjAwMDAwMjEzNzkgMDAwMDAgbiAKMDAwMDAyMjExMCAwMDAwMCBuIAowMDAwMDIyNzY4IDAwMDAwIG4gCjAwMDAwMjM0MTEgMDAwMDAgbiAKMDAwMDAyNDA0MiAwMDAwMCBuIAowMDAwMDI0NzA0IDAwMDAwIG4gCjAwMDAwMjQ3ODQgMDAwMDAgbiAKdHJhaWxlcgo8PCAvSW5mbyA2OCAwIFIgL1Jvb3QgMSAwIFIgL1NpemUgNjkgPj4Kc3RhcnR4cmVmCjI0OTQxCiUlRU9GCg==\n", "image/svg+xml": ["<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n", "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", "<svg height=\"698.51625pt\" version=\"1.1\" viewBox=\"0 0 670.400919 698.51625\" width=\"670.400919pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", " <metadata>\n", "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n", "   <cc:Work>\n", "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", "    <dc:date>2021-12-04T16:59:35.443130</dc:date>\n", "    <dc:format>image/svg+xml</dc:format>\n", "    <dc:creator>\n", "     <cc:Agent>\n", "      <dc:title>Matplotlib v3.4.3, https://matplotlib.org/</dc:title>\n", "     </cc:Agent>\n", "    </dc:creator>\n", "   </cc:Work>\n", "  </rdf:RDF>\n", " </metadata>\n", " <defs>\n", "  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n", " </defs>\n", " <g id=\"figure_1\">\n", "  <g id=\"patch_1\">\n", "   <path d=\"M 0 698.51625 \n", "L 670.400919 698.51625 \n", "L 670.400919 -0 \n", "L 0 -0 \n", "z\n", "\" style=\"fill:none;\"/>\n", "  </g>\n", "  <g id=\"axes_1\">\n", "   <g id=\"patch_2\">\n", "    <path d=\"M 20.5625 140.921761 \n", "L 139.166136 140.921761 \n", "L 139.166136 22.318125 \n", "L 20.5625 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pad35e7e34e)\">\n", "    <image height=\"119\" id=\"imageadfe19a9b1\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_1\">\n", "    <g id=\"xtick_1\">\n", "     <g id=\"line2d_1\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L 0 3.5 \n", "\" id=\"m29bc816bb4\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_1\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 4250 \n", "Q 1547 4250 1301 3770 \n", "Q 1056 3291 1056 2328 \n", "Q 1056 1369 1301 889 \n", "Q 1547 409 2034 409 \n", "Q 2525 409 2770 889 \n", "Q 3016 1369 3016 2328 \n", "Q 3016 3291 2770 3770 \n", "Q 2525 4250 2034 4250 \n", "z\n", "M 2034 4750 \n", "Q 2819 4750 3233 4129 \n", "Q 3647 3509 3647 2328 \n", "Q 3647 1150 3233 529 \n", "Q 2819 -91 2034 -91 \n", "Q 1250 -91 836 529 \n", "Q 422 1150 422 2328 \n", "Q 422 3509 836 4129 \n", "Q 1250 4750 2034 4750 \n", "z\n", "\" id=\"DejaVuSans-30\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_2\">\n", "     <g id=\"line2d_2\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_2\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 794 531 \n", "L 1825 531 \n", "L 1825 4091 \n", "L 703 3866 \n", "L 703 4441 \n", "L 1819 4666 \n", "L 2450 4666 \n", "L 2450 531 \n", "L 3481 531 \n", "L 3481 0 \n", "L 794 0 \n", "L 794 531 \n", "z\n", "\" id=\"DejaVuSans-31\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_3\">\n", "     <g id=\"line2d_3\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_3\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 1228 531 \n", "L 3431 531 \n", "L 3431 0 \n", "L 469 0 \n", "L 469 531 \n", "Q 828 903 1448 1529 \n", "Q 2069 2156 2228 2338 \n", "Q 2531 2678 2651 2914 \n", "Q 2772 3150 2772 3378 \n", "Q 2772 3750 2511 3984 \n", "Q 2250 4219 1831 4219 \n", "Q 1534 4219 1204 4116 \n", "Q 875 4013 500 3803 \n", "L 500 4441 \n", "Q 881 4594 1212 4672 \n", "Q 1544 4750 1819 4750 \n", "Q 2544 4750 2975 4387 \n", "Q 3406 4025 3406 3419 \n", "Q 3406 3131 3298 2873 \n", "Q 3191 2616 2906 2266 \n", "Q 2828 2175 2409 1742 \n", "Q 1991 1309 1228 531 \n", "z\n", "\" id=\"DejaVuSans-32\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_4\">\n", "     <g id=\"line2d_4\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_4\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2597 2516 \n", "Q 3050 2419 3304 2112 \n", "Q 3559 1806 3559 1356 \n", "Q 3559 666 3084 287 \n", "Q 2609 -91 1734 -91 \n", "Q 1441 -91 1130 -33 \n", "Q 819 25 488 141 \n", "L 488 750 \n", "Q 750 597 1062 519 \n", "Q 1375 441 1716 441 \n", "Q 2309 441 2620 675 \n", "Q 2931 909 2931 1356 \n", "Q 2931 1769 2642 2001 \n", "Q 2353 2234 1838 2234 \n", "L 1294 2234 \n", "L 1294 2753 \n", "L 1863 2753 \n", "Q 2328 2753 2575 2939 \n", "Q 2822 3125 2822 3475 \n", "Q 2822 3834 2567 4026 \n", "Q 2313 4219 1838 4219 \n", "Q 1578 4219 1281 4162 \n", "Q 984 4106 628 3988 \n", "L 628 4550 \n", "Q 988 4650 1302 4700 \n", "Q 1616 4750 1894 4750 \n", "Q 2613 4750 3031 4423 \n", "Q 3450 4097 3450 3541 \n", "Q 3450 3153 3228 2886 \n", "Q 3006 2619 2597 2516 \n", "z\n", "\" id=\"DejaVuSans-33\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_5\">\n", "     <g id=\"line2d_5\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_5\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2419 4116 \n", "L 825 1625 \n", "L 2419 1625 \n", "L 2419 4116 \n", "z\n", "M 2253 4666 \n", "L 3047 4666 \n", "L 3047 1625 \n", "L 3713 1625 \n", "L 3713 1100 \n", "L 3047 1100 \n", "L 3047 0 \n", "L 2419 0 \n", "L 2419 1100 \n", "L 313 1100 \n", "L 313 1709 \n", "L 2253 4666 \n", "z\n", "\" id=\"DejaVuSans-34\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_6\">\n", "     <g id=\"line2d_6\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_6\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 691 4666 \n", "L 3169 4666 \n", "L 3169 4134 \n", "L 1269 4134 \n", "L 1269 2991 \n", "Q 1406 3038 1543 3061 \n", "Q 1681 3084 1819 3084 \n", "Q 2600 3084 3056 2656 \n", "Q 3513 2228 3513 1497 \n", "Q 3513 744 3044 326 \n", "Q 2575 -91 1722 -91 \n", "Q 1428 -91 1123 -41 \n", "Q 819 9 494 109 \n", "L 494 744 \n", "Q 775 591 1075 516 \n", "Q 1375 441 1709 441 \n", "Q 2250 441 2565 725 \n", "Q 2881 1009 2881 1497 \n", "Q 2881 1984 2565 2268 \n", "Q 2250 2553 1709 2553 \n", "Q 1456 2553 1204 2497 \n", "Q 953 2441 691 2322 \n", "L 691 4666 \n", "z\n", "\" id=\"DejaVuSans-35\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_7\">\n", "     <g id=\"line2d_7\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_7\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2113 2584 \n", "Q 1688 2584 1439 2293 \n", "Q 1191 2003 1191 1497 \n", "Q 1191 994 1439 701 \n", "Q 1688 409 2113 409 \n", "Q 2538 409 2786 701 \n", "Q 3034 994 3034 1497 \n", "Q 3034 2003 2786 2293 \n", "Q 2538 2584 2113 2584 \n", "z\n", "M 3366 4563 \n", "L 3366 3988 \n", "Q 3128 4100 2886 4159 \n", "Q 2644 4219 2406 4219 \n", "Q 1781 4219 1451 3797 \n", "Q 1122 3375 1075 2522 \n", "Q 1259 2794 1537 2939 \n", "Q 1816 3084 2150 3084 \n", "Q 2853 3084 3261 2657 \n", "Q 3669 2231 3669 1497 \n", "Q 3669 778 3244 343 \n", "Q 2819 -91 2113 -91 \n", "Q 1303 -91 875 529 \n", "Q 447 1150 447 2328 \n", "Q 447 3434 972 4092 \n", "Q 1497 4750 2381 4750 \n", "Q 2619 4750 2861 4703 \n", "Q 3103 4656 3366 4563 \n", "z\n", "\" id=\"DejaVuSans-36\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_8\">\n", "     <g id=\"line2d_8\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_8\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 525 4666 \n", "L 3525 4666 \n", "L 3525 4397 \n", "L 1831 0 \n", "L 1172 0 \n", "L 2766 4134 \n", "L 525 4134 \n", "L 525 4666 \n", "z\n", "\" id=\"DejaVuSans-37\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_9\">\n", "     <g id=\"line2d_9\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_9\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 2034 2216 \n", "Q 1584 2216 1326 1975 \n", "Q 1069 1734 1069 1313 \n", "Q 1069 891 1326 650 \n", "Q 1584 409 2034 409 \n", "Q 2484 409 2743 651 \n", "Q 3003 894 3003 1313 \n", "Q 3003 1734 2745 1975 \n", "Q 2488 2216 2034 2216 \n", "z\n", "M 1403 2484 \n", "Q 997 2584 770 2862 \n", "Q 544 3141 544 3541 \n", "Q 544 4100 942 4425 \n", "Q 1341 4750 2034 4750 \n", "Q 2731 4750 3128 4425 \n", "Q 3525 4100 3525 3541 \n", "Q 3525 3141 3298 2862 \n", "Q 3072 2584 2669 2484 \n", "Q 3125 2378 3379 2068 \n", "Q 3634 1759 3634 1313 \n", "Q 3634 634 3220 271 \n", "Q 2806 -91 2034 -91 \n", "Q 1263 -91 848 271 \n", "Q 434 634 434 1313 \n", "Q 434 1759 690 2068 \n", "Q 947 2378 1403 2484 \n", "z\n", "M 1172 3481 \n", "Q 1172 3119 1398 2916 \n", "Q 1625 2713 2034 2713 \n", "Q 2441 2713 2670 2916 \n", "Q 2900 3119 2900 3481 \n", "Q 2900 3844 2670 4047 \n", "Q 2441 4250 2034 4250 \n", "Q 1625 4250 1398 4047 \n", "Q 1172 3844 1172 3481 \n", "z\n", "\" id=\"DejaVuSans-38\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_10\">\n", "     <g id=\"line2d_10\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_10\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 155.520199)scale(0.1 -0.1)\">\n", "       <defs>\n", "        <path d=\"M 703 97 \n", "L 703 672 \n", "Q 941 559 1184 500 \n", "Q 1428 441 1663 441 \n", "Q 2288 441 2617 861 \n", "Q 2947 1281 2994 2138 \n", "Q 2813 1869 2534 1725 \n", "Q 2256 1581 1919 1581 \n", "Q 1219 1581 811 2004 \n", "Q 403 2428 403 3163 \n", "Q 403 3881 828 4315 \n", "Q 1253 4750 1959 4750 \n", "Q 2769 4750 3195 4129 \n", "Q 3622 3509 3622 2328 \n", "Q 3622 1225 3098 567 \n", "Q 2575 -91 1691 -91 \n", "Q 1453 -91 1209 -44 \n", "Q 966 3 703 97 \n", "z\n", "M 1959 2075 \n", "Q 2384 2075 2632 2365 \n", "Q 2881 2656 2881 3163 \n", "Q 2881 3666 2632 3958 \n", "Q 2384 4250 1959 4250 \n", "Q 1534 4250 1286 3958 \n", "Q 1038 3666 1038 3163 \n", "Q 1038 2656 1286 2365 \n", "Q 1534 2075 1959 2075 \n", "z\n", "\" id=\"DejaVuSans-39\" transform=\"scale(0.015625)\"/>\n", "       </defs>\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_2\">\n", "    <g id=\"ytick_1\">\n", "     <g id=\"line2d_11\">\n", "      <defs>\n", "       <path d=\"M 0 0 \n", "L -3.5 0 \n", "\" id=\"mb7dafc2b9e\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n", "      </defs>\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_11\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_2\">\n", "     <g id=\"line2d_12\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_12\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_3\">\n", "     <g id=\"line2d_13\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_13\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_4\">\n", "     <g id=\"line2d_14\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_14\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_5\">\n", "     <g id=\"line2d_15\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_15\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_6\">\n", "     <g id=\"line2d_16\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_16\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_7\">\n", "     <g id=\"line2d_17\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_17\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_8\">\n", "     <g id=\"line2d_18\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_18\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_9\">\n", "     <g id=\"line2d_19\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_19\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_10\">\n", "     <g id=\"line2d_20\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_20\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_3\">\n", "    <path d=\"M 20.5625 140.921761 \n", "L 20.5625 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_4\">\n", "    <path d=\"M 139.166136 140.921761 \n", "L 139.166136 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_5\">\n", "    <path d=\"M 20.5625 140.921761 \n", "L 139.166136 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_6\">\n", "    <path d=\"M 20.5625 22.318125 \n", "L 139.166136 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_21\">\n", "    <!-- Layer 1, Head 1 -->\n", "    <g transform=\"translate(32.182131 16.318125)scale(0.12 -0.12)\">\n", "     <defs>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 531 \n", "L 3531 531 \n", "L 3531 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-4c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2194 1759 \n", "Q 1497 1759 1228 1600 \n", "Q 959 1441 959 1056 \n", "Q 959 750 1161 570 \n", "Q 1363 391 1709 391 \n", "Q 2188 391 2477 730 \n", "Q 2766 1069 2766 1631 \n", "L 2766 1759 \n", "L 2194 1759 \n", "z\n", "M 3341 1997 \n", "L 3341 0 \n", "L 2766 0 \n", "L 2766 531 \n", "Q 2569 213 2275 61 \n", "Q 1981 -91 1556 -91 \n", "Q 1019 -91 701 211 \n", "Q 384 513 384 1019 \n", "Q 384 1609 779 1909 \n", "Q 1175 2209 1959 2209 \n", "L 2766 2209 \n", "L 2766 2266 \n", "Q 2766 2663 2505 2880 \n", "Q 2244 3097 1772 3097 \n", "Q 1472 3097 1187 3025 \n", "Q 903 2953 641 2809 \n", "L 641 3341 \n", "Q 956 3463 1253 3523 \n", "Q 1550 3584 1831 3584 \n", "Q 2591 3584 2966 3190 \n", "Q 3341 2797 3341 1997 \n", "z\n", "\" id=\"DejaVuSans-61\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2059 -325 \n", "Q 1816 -950 1584 -1140 \n", "Q 1353 -1331 966 -1331 \n", "L 506 -1331 \n", "L 506 -850 \n", "L 844 -850 \n", "Q 1081 -850 1212 -737 \n", "Q 1344 -625 1503 -206 \n", "L 1606 56 \n", "L 191 3500 \n", "L 800 3500 \n", "L 1894 763 \n", "L 2988 3500 \n", "L 3597 3500 \n", "L 2059 -325 \n", "z\n", "\" id=\"DejaVuSans-79\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 3597 1894 \n", "L 3597 1613 \n", "L 953 1613 \n", "Q 991 1019 1311 708 \n", "Q 1631 397 2203 397 \n", "Q 2534 397 2845 478 \n", "Q 3156 559 3463 722 \n", "L 3463 178 \n", "Q 3153 47 2828 -22 \n", "Q 2503 -91 2169 -91 \n", "Q 1331 -91 842 396 \n", "Q 353 884 353 1716 \n", "Q 353 2575 817 3079 \n", "Q 1281 3584 2069 3584 \n", "Q 2775 3584 3186 3129 \n", "Q 3597 2675 3597 1894 \n", "z\n", "M 3022 2063 \n", "Q 3016 2534 2758 2815 \n", "Q 2500 3097 2075 3097 \n", "Q 1594 3097 1305 2825 \n", "Q 1016 2553 972 2059 \n", "L 3022 2063 \n", "z\n", "\" id=\"DejaVuSans-65\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2631 2963 \n", "Q 2534 3019 2420 3045 \n", "Q 2306 3072 2169 3072 \n", "Q 1681 3072 1420 2755 \n", "Q 1159 2438 1159 1844 \n", "L 1159 0 \n", "L 581 0 \n", "L 581 3500 \n", "L 1159 3500 \n", "L 1159 2956 \n", "Q 1341 3275 1631 3429 \n", "Q 1922 3584 2338 3584 \n", "Q 2397 3584 2469 3576 \n", "Q 2541 3569 2628 3553 \n", "L 2631 2963 \n", "z\n", "\" id=\"DejaVuSans-72\" transform=\"scale(0.015625)\"/>\n", "      <path id=\"DejaVuSans-20\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 750 794 \n", "L 1409 794 \n", "L 1409 256 \n", "L 897 -744 \n", "L 494 -744 \n", "L 750 256 \n", "L 750 794 \n", "z\n", "\" id=\"DejaVuSans-2c\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 628 4666 \n", "L 1259 4666 \n", "L 1259 2753 \n", "L 3553 2753 \n", "L 3553 4666 \n", "L 4184 4666 \n", "L 4184 0 \n", "L 3553 0 \n", "L 3553 2222 \n", "L 1259 2222 \n", "L 1259 0 \n", "L 628 0 \n", "L 628 4666 \n", "z\n", "\" id=\"DejaVuSans-48\" transform=\"scale(0.015625)\"/>\n", "      <path d=\"M 2906 2969 \n", "L 2906 4863 \n", "L 3481 4863 \n", "L 3481 0 \n", "L 2906 0 \n", "L 2906 525 \n", "Q 2725 213 2448 61 \n", "Q 2172 -91 1784 -91 \n", "Q 1150 -91 751 415 \n", "Q 353 922 353 1747 \n", "Q 353 2572 751 3078 \n", "Q 1150 3584 1784 3584 \n", "Q 2172 3584 2448 3432 \n", "Q 2725 3281 2906 2969 \n", "z\n", "M 947 1747 \n", "Q 947 1113 1208 752 \n", "Q 1469 391 1925 391 \n", "Q 2381 391 2643 752 \n", "Q 2906 1113 2906 1747 \n", "Q 2906 2381 2643 2742 \n", "Q 2381 3103 1925 3103 \n", "Q 1469 3103 1208 2742 \n", "Q 947 2381 947 1747 \n", "z\n", "\" id=\"DejaVuSans-64\" transform=\"scale(0.015625)\"/>\n", "     </defs>\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_2\">\n", "   <g id=\"patch_7\">\n", "    <path d=\"M 195.240761 140.921761 \n", "L 313.844397 140.921761 \n", "L 313.844397 22.318125 \n", "L 195.240761 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p3f047439b5)\">\n", "    <image height=\"119\" id=\"imageec296bb123\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_3\">\n", "    <g id=\"xtick_11\">\n", "     <g id=\"line2d_21\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_22\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_12\">\n", "     <g id=\"line2d_22\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_23\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_13\">\n", "     <g id=\"line2d_23\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_24\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_14\">\n", "     <g id=\"line2d_24\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_25\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_15\">\n", "     <g id=\"line2d_25\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_26\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_16\">\n", "     <g id=\"line2d_26\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_27\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_17\">\n", "     <g id=\"line2d_27\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_28\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_18\">\n", "     <g id=\"line2d_28\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_29\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_19\">\n", "     <g id=\"line2d_29\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_30\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_20\">\n", "     <g id=\"line2d_30\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_31\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_4\">\n", "    <g id=\"ytick_11\">\n", "     <g id=\"line2d_31\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_32\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_12\">\n", "     <g id=\"line2d_32\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_33\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_13\">\n", "     <g id=\"line2d_33\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_34\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_14\">\n", "     <g id=\"line2d_34\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_35\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_15\">\n", "     <g id=\"line2d_35\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_36\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_16\">\n", "     <g id=\"line2d_36\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_37\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_17\">\n", "     <g id=\"line2d_37\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_38\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_18\">\n", "     <g id=\"line2d_38\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_39\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_19\">\n", "     <g id=\"line2d_39\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_40\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_20\">\n", "     <g id=\"line2d_40\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_41\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_8\">\n", "    <path d=\"M 195.240761 140.921761 \n", "L 195.240761 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_9\">\n", "    <path d=\"M 313.844397 140.921761 \n", "L 313.844397 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_10\">\n", "    <path d=\"M 195.240761 140.921761 \n", "L 313.844397 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_11\">\n", "    <path d=\"M 195.240761 22.318125 \n", "L 313.844397 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_42\">\n", "    <!-- Layer 1, Head 2 -->\n", "    <g transform=\"translate(206.860392 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_3\">\n", "   <g id=\"patch_12\">\n", "    <path d=\"M 369.919022 140.921761 \n", "L 488.522658 140.921761 \n", "L 488.522658 22.318125 \n", "L 369.919022 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pc02064692f)\">\n", "    <image height=\"119\" id=\"image4bb9055d15\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_5\">\n", "    <g id=\"xtick_21\">\n", "     <g id=\"line2d_41\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_43\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_22\">\n", "     <g id=\"line2d_42\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_44\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_23\">\n", "     <g id=\"line2d_43\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_45\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_24\">\n", "     <g id=\"line2d_44\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_46\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_25\">\n", "     <g id=\"line2d_45\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_47\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_26\">\n", "     <g id=\"line2d_46\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_48\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_27\">\n", "     <g id=\"line2d_47\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_49\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_28\">\n", "     <g id=\"line2d_48\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_50\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_29\">\n", "     <g id=\"line2d_49\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_51\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_30\">\n", "     <g id=\"line2d_50\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_52\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_6\">\n", "    <g id=\"ytick_21\">\n", "     <g id=\"line2d_51\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_53\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_22\">\n", "     <g id=\"line2d_52\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_54\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_23\">\n", "     <g id=\"line2d_53\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_55\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_24\">\n", "     <g id=\"line2d_54\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_56\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_25\">\n", "     <g id=\"line2d_55\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_57\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_26\">\n", "     <g id=\"line2d_56\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_58\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_27\">\n", "     <g id=\"line2d_57\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_59\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_28\">\n", "     <g id=\"line2d_58\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_60\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_29\">\n", "     <g id=\"line2d_59\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_61\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_30\">\n", "     <g id=\"line2d_60\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_62\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_13\">\n", "    <path d=\"M 369.919022 140.921761 \n", "L 369.919022 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_14\">\n", "    <path d=\"M 488.522658 140.921761 \n", "L 488.522658 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_15\">\n", "    <path d=\"M 369.919022 140.921761 \n", "L 488.522658 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_16\">\n", "    <path d=\"M 369.919022 22.318125 \n", "L 488.522658 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_63\">\n", "    <!-- Layer 1, Head 3 -->\n", "    <g transform=\"translate(381.538652 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_4\">\n", "   <g id=\"patch_17\">\n", "    <path d=\"M 544.597283 140.921761 \n", "L 663.200919 140.921761 \n", "L 663.200919 22.318125 \n", "L 544.597283 22.318125 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p0735244ca0)\">\n", "    <image height=\"119\" id=\"image7db03a4a98\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-21.921761\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_7\">\n", "    <g id=\"xtick_31\">\n", "     <g id=\"line2d_61\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_64\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_32\">\n", "     <g id=\"line2d_62\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_65\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_33\">\n", "     <g id=\"line2d_63\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_66\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_34\">\n", "     <g id=\"line2d_64\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_67\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_35\">\n", "     <g id=\"line2d_65\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_68\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_36\">\n", "     <g id=\"line2d_66\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_69\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_37\">\n", "     <g id=\"line2d_67\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_70\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_38\">\n", "     <g id=\"line2d_68\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_71\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_39\">\n", "     <g id=\"line2d_69\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_72\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_40\">\n", "     <g id=\"line2d_70\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#m29bc816bb4\" y=\"140.921761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_73\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 155.520199)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_8\">\n", "    <g id=\"ytick_31\">\n", "     <g id=\"line2d_71\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"134.99158\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_74\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 138.790798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_32\">\n", "     <g id=\"line2d_72\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"123.131216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_75\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 126.930435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_33\">\n", "     <g id=\"line2d_73\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"111.270852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_76\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 115.070071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_34\">\n", "     <g id=\"line2d_74\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"99.410489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_77\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 103.209707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_35\">\n", "     <g id=\"line2d_75\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"87.550125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_78\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 91.349344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_36\">\n", "     <g id=\"line2d_76\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"75.689761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_79\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 79.48898)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_37\">\n", "     <g id=\"line2d_77\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"63.829398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_80\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 67.628616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_38\">\n", "     <g id=\"line2d_78\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"51.969034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_81\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 55.768253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_39\">\n", "     <g id=\"line2d_79\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"40.10867\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_82\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 43.907889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_40\">\n", "     <g id=\"line2d_80\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"28.248307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_83\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 32.047526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_18\">\n", "    <path d=\"M 544.597283 140.921761 \n", "L 544.597283 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_19\">\n", "    <path d=\"M 663.200919 140.921761 \n", "L 663.200919 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_20\">\n", "    <path d=\"M 544.597283 140.921761 \n", "L 663.200919 140.921761 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_21\">\n", "    <path d=\"M 544.597283 22.318125 \n", "L 663.200919 22.318125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_84\">\n", "    <!-- Layer 1, Head 4 -->\n", "    <g transform=\"translate(556.216913 16.318125)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-31\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_5\">\n", "   <g id=\"patch_22\">\n", "    <path d=\"M 20.5625 318.827216 \n", "L 139.166136 318.827216 \n", "L 139.166136 200.22358 \n", "L 20.5625 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pae1bed9a54)\">\n", "    <image height=\"119\" id=\"imageeb226c9210\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_9\">\n", "    <g id=\"xtick_41\">\n", "     <g id=\"line2d_81\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_85\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_42\">\n", "     <g id=\"line2d_82\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_86\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_43\">\n", "     <g id=\"line2d_83\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_87\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_44\">\n", "     <g id=\"line2d_84\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_88\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_45\">\n", "     <g id=\"line2d_85\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_89\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_46\">\n", "     <g id=\"line2d_86\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_90\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_47\">\n", "     <g id=\"line2d_87\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_91\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_48\">\n", "     <g id=\"line2d_88\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_92\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_49\">\n", "     <g id=\"line2d_89\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_93\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_50\">\n", "     <g id=\"line2d_90\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_94\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_10\">\n", "    <g id=\"ytick_41\">\n", "     <g id=\"line2d_91\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_95\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_42\">\n", "     <g id=\"line2d_92\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_96\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_43\">\n", "     <g id=\"line2d_93\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_97\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_44\">\n", "     <g id=\"line2d_94\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_98\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_45\">\n", "     <g id=\"line2d_95\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_99\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_46\">\n", "     <g id=\"line2d_96\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_100\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_47\">\n", "     <g id=\"line2d_97\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_101\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_48\">\n", "     <g id=\"line2d_98\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_102\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_49\">\n", "     <g id=\"line2d_99\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_103\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_50\">\n", "     <g id=\"line2d_100\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_104\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_23\">\n", "    <path d=\"M 20.5625 318.827216 \n", "L 20.5625 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_24\">\n", "    <path d=\"M 139.166136 318.827216 \n", "L 139.166136 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_25\">\n", "    <path d=\"M 20.5625 318.827216 \n", "L 139.166136 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_26\">\n", "    <path d=\"M 20.5625 200.22358 \n", "L 139.166136 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_105\">\n", "    <!-- Layer 2, Head 1 -->\n", "    <g transform=\"translate(32.182131 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_6\">\n", "   <g id=\"patch_27\">\n", "    <path d=\"M 195.240761 318.827216 \n", "L 313.844397 318.827216 \n", "L 313.844397 200.22358 \n", "L 195.240761 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pda2b003fd9)\">\n", "    <image height=\"119\" id=\"image502719b870\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_11\">\n", "    <g id=\"xtick_51\">\n", "     <g id=\"line2d_101\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_106\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_52\">\n", "     <g id=\"line2d_102\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_107\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_53\">\n", "     <g id=\"line2d_103\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_108\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_54\">\n", "     <g id=\"line2d_104\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_109\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_55\">\n", "     <g id=\"line2d_105\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_110\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_56\">\n", "     <g id=\"line2d_106\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_111\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_57\">\n", "     <g id=\"line2d_107\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_112\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_58\">\n", "     <g id=\"line2d_108\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_113\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_59\">\n", "     <g id=\"line2d_109\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_114\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_60\">\n", "     <g id=\"line2d_110\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_115\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_12\">\n", "    <g id=\"ytick_51\">\n", "     <g id=\"line2d_111\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_116\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_52\">\n", "     <g id=\"line2d_112\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_117\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_53\">\n", "     <g id=\"line2d_113\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_118\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_54\">\n", "     <g id=\"line2d_114\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_119\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_55\">\n", "     <g id=\"line2d_115\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_120\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_56\">\n", "     <g id=\"line2d_116\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_121\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_57\">\n", "     <g id=\"line2d_117\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_122\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_58\">\n", "     <g id=\"line2d_118\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_123\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_59\">\n", "     <g id=\"line2d_119\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_124\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_60\">\n", "     <g id=\"line2d_120\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_125\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_28\">\n", "    <path d=\"M 195.240761 318.827216 \n", "L 195.240761 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_29\">\n", "    <path d=\"M 313.844397 318.827216 \n", "L 313.844397 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_30\">\n", "    <path d=\"M 195.240761 318.827216 \n", "L 313.844397 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_31\">\n", "    <path d=\"M 195.240761 200.22358 \n", "L 313.844397 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_126\">\n", "    <!-- Layer 2, Head 2 -->\n", "    <g transform=\"translate(206.860392 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_7\">\n", "   <g id=\"patch_32\">\n", "    <path d=\"M 369.919022 318.827216 \n", "L 488.522658 318.827216 \n", "L 488.522658 200.22358 \n", "L 369.919022 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p4f5766fe4e)\">\n", "    <image height=\"119\" id=\"imaged8ccc0ac7e\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_13\">\n", "    <g id=\"xtick_61\">\n", "     <g id=\"line2d_121\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_127\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_62\">\n", "     <g id=\"line2d_122\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_128\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_63\">\n", "     <g id=\"line2d_123\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_129\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_64\">\n", "     <g id=\"line2d_124\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_130\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_65\">\n", "     <g id=\"line2d_125\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_131\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_66\">\n", "     <g id=\"line2d_126\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_132\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_67\">\n", "     <g id=\"line2d_127\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_133\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_68\">\n", "     <g id=\"line2d_128\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_134\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_69\">\n", "     <g id=\"line2d_129\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_135\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_70\">\n", "     <g id=\"line2d_130\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_136\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_14\">\n", "    <g id=\"ytick_61\">\n", "     <g id=\"line2d_131\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_137\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_62\">\n", "     <g id=\"line2d_132\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_138\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_63\">\n", "     <g id=\"line2d_133\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_139\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_64\">\n", "     <g id=\"line2d_134\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_140\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_65\">\n", "     <g id=\"line2d_135\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_141\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_66\">\n", "     <g id=\"line2d_136\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_142\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_67\">\n", "     <g id=\"line2d_137\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_143\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_68\">\n", "     <g id=\"line2d_138\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_144\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_69\">\n", "     <g id=\"line2d_139\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_145\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_70\">\n", "     <g id=\"line2d_140\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_146\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_33\">\n", "    <path d=\"M 369.919022 318.827216 \n", "L 369.919022 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_34\">\n", "    <path d=\"M 488.522658 318.827216 \n", "L 488.522658 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_35\">\n", "    <path d=\"M 369.919022 318.827216 \n", "L 488.522658 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_36\">\n", "    <path d=\"M 369.919022 200.22358 \n", "L 488.522658 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_147\">\n", "    <!-- Layer 2, Head 3 -->\n", "    <g transform=\"translate(381.538652 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_8\">\n", "   <g id=\"patch_37\">\n", "    <path d=\"M 544.597283 318.827216 \n", "L 663.200919 318.827216 \n", "L 663.200919 200.22358 \n", "L 544.597283 200.22358 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pa9ce33fced)\">\n", "    <image height=\"119\" id=\"image3e164c3180\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-199.827216\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_15\">\n", "    <g id=\"xtick_71\">\n", "     <g id=\"line2d_141\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_148\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_72\">\n", "     <g id=\"line2d_142\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_149\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_73\">\n", "     <g id=\"line2d_143\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_150\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_74\">\n", "     <g id=\"line2d_144\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_151\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_75\">\n", "     <g id=\"line2d_145\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_152\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_76\">\n", "     <g id=\"line2d_146\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_153\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_77\">\n", "     <g id=\"line2d_147\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_154\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_78\">\n", "     <g id=\"line2d_148\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_155\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_79\">\n", "     <g id=\"line2d_149\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_156\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_80\">\n", "     <g id=\"line2d_150\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#m29bc816bb4\" y=\"318.827216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_157\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 333.425653)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_16\">\n", "    <g id=\"ytick_71\">\n", "     <g id=\"line2d_151\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"312.897034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_158\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 316.696253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_72\">\n", "     <g id=\"line2d_152\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"301.03667\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_159\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 304.835889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_73\">\n", "     <g id=\"line2d_153\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"289.176307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_160\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 292.975526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_74\">\n", "     <g id=\"line2d_154\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"277.315943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_161\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 281.115162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_75\">\n", "     <g id=\"line2d_155\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"265.45558\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_162\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 269.254798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_76\">\n", "     <g id=\"line2d_156\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"253.595216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_163\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 257.394435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_77\">\n", "     <g id=\"line2d_157\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"241.734852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_164\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 245.534071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_78\">\n", "     <g id=\"line2d_158\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"229.874489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_165\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 233.673707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_79\">\n", "     <g id=\"line2d_159\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"218.014125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_166\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 221.813344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_80\">\n", "     <g id=\"line2d_160\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"206.153761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_167\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 209.95298)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_38\">\n", "    <path d=\"M 544.597283 318.827216 \n", "L 544.597283 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_39\">\n", "    <path d=\"M 663.200919 318.827216 \n", "L 663.200919 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_40\">\n", "    <path d=\"M 544.597283 318.827216 \n", "L 663.200919 318.827216 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_41\">\n", "    <path d=\"M 544.597283 200.22358 \n", "L 663.200919 200.22358 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_168\">\n", "    <!-- Layer 2, Head 4 -->\n", "    <g transform=\"translate(556.216913 194.22358)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-32\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_9\">\n", "   <g id=\"patch_42\">\n", "    <path d=\"M 20.5625 496.73267 \n", "L 139.166136 496.73267 \n", "L 139.166136 378.129034 \n", "L 20.5625 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p86f60d31a4)\">\n", "    <image height=\"119\" id=\"image2af1176d3a\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "iVBORw0KGgoAAAANSUhEUgAAAHcAAAB3CAYAAAA5Od+KAAADOElEQVR4nO3dvWsTcQDG8d9dzqRpirXWStSaCobSCIKiiODiILazoIujHbR/gXZ1U3B3EKGDgoLg4OLqH6BTsTSirRbfKL4kNWlM7pzc7xn78P3MT47Qb2/5cVyi2bFrWRBk3W1lHkKhIM0jdT+6O/f23ItV6dqvzoxJ+9UHDWk/feOdtI8qw9I+ltbYUYhrjLjGiGuMuMaIa4y4xohrjLjGiGuMuMaSdKujfSJLtX2/r+2LRW3fauWeLu5bkS491z8t7dN+pO07XWkf70q0vbTGjkJcY8Q1RlxjxDVGXGPENUZcY8Q1RlxjxDWWxOUh6QOZeFacDQbSPkq081PlueiFjbPadylpz1BPHdyU9nGlLO1DpJ1dc+caI64x4hojrjHiGiOuMeIaI64x4hojrjHiGktCrJ1XqiL1OWT1+4znf2/Fz570+o8QBtoz3d9bI9K+lv6Q9uq5O3euMeIaI64x4hojrjHiGiOuMeIaI64x4hojrrEkbW9pn4i0/wf1/czxUEm7/tqn3Nvzez9K136WHZb2MxNfpX17W/vbFHjfMv4jrjHiGiOuMeIaI64x4hojrjHiGiOusaR78aT0gcqydsS2fnlS2teeaEeEy4vV3Nvnc/ula8cj2tHsn/k92vXr49I+2/iiXV9aY0chrjHiGiOuMeIaI64x4hojrjHiGiOuMeIaSyqvtbPc9NdvaV97JL7Ct6v9BNrRx/lf+VtY+itdu3ehLe1XbtelfePmW2mfZdprH7hzjRHXGHGNEdcYcY0R1xhxjRHXGHGNEdcYcY0lnePac8Xl5c/Svnm9Ju3r97Wz7vfz+c9bZ65qP9+m/hTesbvaM91ZdULah/UNac6da4y4xohrjLjGiGuMuMaIa4y4xohrjLjGiGssmq0uSA/DZi3tWd5ouCztVYP6odzbKw9fStd+emJK2q/dOiXtj9x5I+3VvyV3rjHiGiOuMeIaI64x4hojrjHiGiOuMeIaI66xpNfQnlsuNbVnc7vT+d+HHEIIxW/aO457o8Xc23tLl6RrT41o76wobUrzEE0ekPaD5gdpz51rjLjGiGuMuMaIa4y4xohrjLjGiGuMuMaIa+wfZDuIAnAaQIIAAAAASUVORK5CYII=\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_17\">\n", "    <g id=\"xtick_81\">\n", "     <g id=\"line2d_161\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_169\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_82\">\n", "     <g id=\"line2d_162\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_170\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_83\">\n", "     <g id=\"line2d_163\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_171\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_84\">\n", "     <g id=\"line2d_164\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_172\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_85\">\n", "     <g id=\"line2d_165\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_173\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_86\">\n", "     <g id=\"line2d_166\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_174\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_87\">\n", "     <g id=\"line2d_167\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_175\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_88\">\n", "     <g id=\"line2d_168\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_176\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_89\">\n", "     <g id=\"line2d_169\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_177\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_90\">\n", "     <g id=\"line2d_170\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_178\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_18\">\n", "    <g id=\"ytick_81\">\n", "     <g id=\"line2d_171\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_179\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_82\">\n", "     <g id=\"line2d_172\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_180\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_83\">\n", "     <g id=\"line2d_173\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_181\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_84\">\n", "     <g id=\"line2d_174\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_182\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_85\">\n", "     <g id=\"line2d_175\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_183\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_86\">\n", "     <g id=\"line2d_176\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_184\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_87\">\n", "     <g id=\"line2d_177\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_185\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_88\">\n", "     <g id=\"line2d_178\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_186\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_89\">\n", "     <g id=\"line2d_179\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_187\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_90\">\n", "     <g id=\"line2d_180\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_188\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_43\">\n", "    <path d=\"M 20.5625 496.73267 \n", "L 20.5625 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_44\">\n", "    <path d=\"M 139.166136 496.73267 \n", "L 139.166136 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_45\">\n", "    <path d=\"M 20.5625 496.73267 \n", "L 139.166136 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_46\">\n", "    <path d=\"M 20.5625 378.129034 \n", "L 139.166136 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_189\">\n", "    <!-- Layer 3, Head 1 -->\n", "    <g transform=\"translate(32.182131 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_10\">\n", "   <g id=\"patch_47\">\n", "    <path d=\"M 195.240761 496.73267 \n", "L 313.844397 496.73267 \n", "L 313.844397 378.129034 \n", "L 195.240761 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p5722fc46aa)\">\n", "    <image height=\"119\" id=\"image11e7839482\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_19\">\n", "    <g id=\"xtick_91\">\n", "     <g id=\"line2d_181\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_190\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_92\">\n", "     <g id=\"line2d_182\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_191\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_93\">\n", "     <g id=\"line2d_183\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_192\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_94\">\n", "     <g id=\"line2d_184\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_193\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_95\">\n", "     <g id=\"line2d_185\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_194\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_96\">\n", "     <g id=\"line2d_186\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_195\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_97\">\n", "     <g id=\"line2d_187\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_196\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_98\">\n", "     <g id=\"line2d_188\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_197\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_99\">\n", "     <g id=\"line2d_189\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_198\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_100\">\n", "     <g id=\"line2d_190\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_199\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_20\">\n", "    <g id=\"ytick_91\">\n", "     <g id=\"line2d_191\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_200\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_92\">\n", "     <g id=\"line2d_192\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_201\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_93\">\n", "     <g id=\"line2d_193\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_202\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_94\">\n", "     <g id=\"line2d_194\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_203\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_95\">\n", "     <g id=\"line2d_195\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_204\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_96\">\n", "     <g id=\"line2d_196\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_205\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_97\">\n", "     <g id=\"line2d_197\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_206\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_98\">\n", "     <g id=\"line2d_198\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_207\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_99\">\n", "     <g id=\"line2d_199\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_208\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_100\">\n", "     <g id=\"line2d_200\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_209\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_48\">\n", "    <path d=\"M 195.240761 496.73267 \n", "L 195.240761 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_49\">\n", "    <path d=\"M 313.844397 496.73267 \n", "L 313.844397 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_50\">\n", "    <path d=\"M 195.240761 496.73267 \n", "L 313.844397 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_51\">\n", "    <path d=\"M 195.240761 378.129034 \n", "L 313.844397 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_210\">\n", "    <!-- Layer 3, Head 2 -->\n", "    <g transform=\"translate(206.860392 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_11\">\n", "   <g id=\"patch_52\">\n", "    <path d=\"M 369.919022 496.73267 \n", "L 488.522658 496.73267 \n", "L 488.522658 378.129034 \n", "L 369.919022 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pdee8c6f53d)\">\n", "    <image height=\"119\" id=\"imageb980069c5e\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_21\">\n", "    <g id=\"xtick_101\">\n", "     <g id=\"line2d_201\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_211\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_102\">\n", "     <g id=\"line2d_202\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_212\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_103\">\n", "     <g id=\"line2d_203\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_213\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_104\">\n", "     <g id=\"line2d_204\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_214\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_105\">\n", "     <g id=\"line2d_205\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_215\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_106\">\n", "     <g id=\"line2d_206\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_216\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_107\">\n", "     <g id=\"line2d_207\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_217\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_108\">\n", "     <g id=\"line2d_208\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_218\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_109\">\n", "     <g id=\"line2d_209\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_219\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_110\">\n", "     <g id=\"line2d_210\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_220\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_22\">\n", "    <g id=\"ytick_101\">\n", "     <g id=\"line2d_211\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_221\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_102\">\n", "     <g id=\"line2d_212\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_222\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_103\">\n", "     <g id=\"line2d_213\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_223\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_104\">\n", "     <g id=\"line2d_214\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_224\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_105\">\n", "     <g id=\"line2d_215\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_225\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_106\">\n", "     <g id=\"line2d_216\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_226\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_107\">\n", "     <g id=\"line2d_217\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_227\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_108\">\n", "     <g id=\"line2d_218\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_228\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_109\">\n", "     <g id=\"line2d_219\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_229\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_110\">\n", "     <g id=\"line2d_220\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_230\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_53\">\n", "    <path d=\"M 369.919022 496.73267 \n", "L 369.919022 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_54\">\n", "    <path d=\"M 488.522658 496.73267 \n", "L 488.522658 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_55\">\n", "    <path d=\"M 369.919022 496.73267 \n", "L 488.522658 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_56\">\n", "    <path d=\"M 369.919022 378.129034 \n", "L 488.522658 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_231\">\n", "    <!-- Layer 3, Head 3 -->\n", "    <g transform=\"translate(381.538652 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_12\">\n", "   <g id=\"patch_57\">\n", "    <path d=\"M 544.597283 496.73267 \n", "L 663.200919 496.73267 \n", "L 663.200919 378.129034 \n", "L 544.597283 378.129034 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pa255f7c335)\">\n", "    <image height=\"119\" id=\"imageef688956c4\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-377.73267\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_23\">\n", "    <g id=\"xtick_111\">\n", "     <g id=\"line2d_221\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_232\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_112\">\n", "     <g id=\"line2d_222\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_233\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_113\">\n", "     <g id=\"line2d_223\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_234\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_114\">\n", "     <g id=\"line2d_224\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_235\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_115\">\n", "     <g id=\"line2d_225\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_236\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_116\">\n", "     <g id=\"line2d_226\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_237\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_117\">\n", "     <g id=\"line2d_227\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_238\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_118\">\n", "     <g id=\"line2d_228\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_239\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_119\">\n", "     <g id=\"line2d_229\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_240\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_120\">\n", "     <g id=\"line2d_230\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#m29bc816bb4\" y=\"496.73267\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_241\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 511.331108)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_24\">\n", "    <g id=\"ytick_111\">\n", "     <g id=\"line2d_231\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"490.802489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_242\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 494.601707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_112\">\n", "     <g id=\"line2d_232\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"478.942125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_243\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 482.741344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_113\">\n", "     <g id=\"line2d_233\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"467.081761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_244\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 470.88098)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_114\">\n", "     <g id=\"line2d_234\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"455.221398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_245\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 459.020616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_115\">\n", "     <g id=\"line2d_235\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"443.361034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_246\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 447.160253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_116\">\n", "     <g id=\"line2d_236\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"431.50067\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_247\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 435.299889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_117\">\n", "     <g id=\"line2d_237\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"419.640307\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_248\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 423.439526)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_118\">\n", "     <g id=\"line2d_238\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"407.779943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_249\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 411.579162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_119\">\n", "     <g id=\"line2d_239\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"395.91958\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_250\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 399.718798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_120\">\n", "     <g id=\"line2d_240\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"384.059216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_251\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 387.858435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_58\">\n", "    <path d=\"M 544.597283 496.73267 \n", "L 544.597283 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_59\">\n", "    <path d=\"M 663.200919 496.73267 \n", "L 663.200919 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_60\">\n", "    <path d=\"M 544.597283 496.73267 \n", "L 663.200919 496.73267 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_61\">\n", "    <path d=\"M 544.597283 378.129034 \n", "L 663.200919 378.129034 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_252\">\n", "    <!-- Layer 3, Head 4 -->\n", "    <g transform=\"translate(556.216913 372.129034)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-33\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_13\">\n", "   <g id=\"patch_62\">\n", "    <path d=\"M 20.5625 674.638125 \n", "L 139.166136 674.638125 \n", "L 139.166136 556.034489 \n", "L 20.5625 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pb3b8ad59fd)\">\n", "    <image height=\"119\" id=\"imaged733fc06c2\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"20.5625\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_25\">\n", "    <g id=\"xtick_121\">\n", "     <g id=\"line2d_241\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.492682\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_253\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(23.311432 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_122\">\n", "     <g id=\"line2d_242\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"38.353045\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_254\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(35.171795 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_123\">\n", "     <g id=\"line2d_243\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"50.213409\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_255\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(47.032159 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_124\">\n", "     <g id=\"line2d_244\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"62.073773\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_256\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(58.892523 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_125\">\n", "     <g id=\"line2d_245\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"73.934136\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_257\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(70.752886 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_126\">\n", "     <g id=\"line2d_246\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"85.7945\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_258\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(82.61325 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_127\">\n", "     <g id=\"line2d_247\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"97.654864\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_259\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(94.473614 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_128\">\n", "     <g id=\"line2d_248\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.515227\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_260\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(106.333977 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_129\">\n", "     <g id=\"line2d_249\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"121.375591\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_261\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(118.194341 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_130\">\n", "     <g id=\"line2d_250\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"133.235955\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_262\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(130.054705 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_26\">\n", "    <g id=\"ytick_121\">\n", "     <g id=\"line2d_251\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_263\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(7.2 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_122\">\n", "     <g id=\"line2d_252\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_264\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(7.2 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_123\">\n", "     <g id=\"line2d_253\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_265\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(7.2 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_124\">\n", "     <g id=\"line2d_254\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_266\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(7.2 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_125\">\n", "     <g id=\"line2d_255\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_267\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(7.2 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_126\">\n", "     <g id=\"line2d_256\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_268\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(7.2 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_127\">\n", "     <g id=\"line2d_257\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_269\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(7.2 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_128\">\n", "     <g id=\"line2d_258\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_270\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(7.2 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_129\">\n", "     <g id=\"line2d_259\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_271\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(7.2 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_130\">\n", "     <g id=\"line2d_260\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"20.5625\" xlink:href=\"#mb7dafc2b9e\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_272\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(7.2 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_63\">\n", "    <path d=\"M 20.5625 674.638125 \n", "L 20.5625 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_64\">\n", "    <path d=\"M 139.166136 674.638125 \n", "L 139.166136 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_65\">\n", "    <path d=\"M 20.5625 674.638125 \n", "L 139.166136 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_66\">\n", "    <path d=\"M 20.5625 556.034489 \n", "L 139.166136 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_273\">\n", "    <!-- Layer 4, Head 1 -->\n", "    <g transform=\"translate(32.182131 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-31\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_14\">\n", "   <g id=\"patch_67\">\n", "    <path d=\"M 195.240761 674.638125 \n", "L 313.844397 674.638125 \n", "L 313.844397 556.034489 \n", "L 195.240761 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#pad3801ef8c)\">\n", "    <image height=\"119\" id=\"imagef0e3daf166\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"195.240761\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_27\">\n", "    <g id=\"xtick_131\">\n", "     <g id=\"line2d_261\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.170943\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_274\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(197.989693 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_132\">\n", "     <g id=\"line2d_262\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.031306\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_275\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(209.850056 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_133\">\n", "     <g id=\"line2d_263\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"224.89167\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_276\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(221.71042 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_134\">\n", "     <g id=\"line2d_264\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"236.752034\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_277\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(233.570784 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_135\">\n", "     <g id=\"line2d_265\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"248.612397\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_278\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(245.431147 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_136\">\n", "     <g id=\"line2d_266\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"260.472761\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_279\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(257.291511 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_137\">\n", "     <g id=\"line2d_267\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"272.333125\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_280\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(269.151875 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_138\">\n", "     <g id=\"line2d_268\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"284.193488\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_281\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(281.012238 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_139\">\n", "     <g id=\"line2d_269\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"296.053852\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_282\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(292.872602 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_140\">\n", "     <g id=\"line2d_270\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"307.914215\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_283\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(304.732965 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_28\">\n", "    <g id=\"ytick_131\">\n", "     <g id=\"line2d_271\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_284\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(181.878261 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_132\">\n", "     <g id=\"line2d_272\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_285\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(181.878261 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_133\">\n", "     <g id=\"line2d_273\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_286\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(181.878261 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_134\">\n", "     <g id=\"line2d_274\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_287\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(181.878261 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_135\">\n", "     <g id=\"line2d_275\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_288\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(181.878261 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_136\">\n", "     <g id=\"line2d_276\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_289\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(181.878261 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_137\">\n", "     <g id=\"line2d_277\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_290\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(181.878261 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_138\">\n", "     <g id=\"line2d_278\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_291\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(181.878261 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_139\">\n", "     <g id=\"line2d_279\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_292\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(181.878261 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_140\">\n", "     <g id=\"line2d_280\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"195.240761\" xlink:href=\"#mb7dafc2b9e\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_293\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(181.878261 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_68\">\n", "    <path d=\"M 195.240761 674.638125 \n", "L 195.240761 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_69\">\n", "    <path d=\"M 313.844397 674.638125 \n", "L 313.844397 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_70\">\n", "    <path d=\"M 195.240761 674.638125 \n", "L 313.844397 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_71\">\n", "    <path d=\"M 195.240761 556.034489 \n", "L 313.844397 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_294\">\n", "    <!-- Layer 4, Head 2 -->\n", "    <g transform=\"translate(206.860392 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-32\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_15\">\n", "   <g id=\"patch_72\">\n", "    <path d=\"M 369.919022 674.638125 \n", "L 488.522658 674.638125 \n", "L 488.522658 556.034489 \n", "L 369.919022 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p3e848e2d93)\">\n", "    <image height=\"119\" id=\"image3ddb08ed95\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"369.919022\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_29\">\n", "    <g id=\"xtick_141\">\n", "     <g id=\"line2d_281\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"375.849204\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_295\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(372.667954 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_142\">\n", "     <g id=\"line2d_282\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.709567\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_296\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(384.528317 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_143\">\n", "     <g id=\"line2d_283\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"399.569931\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_297\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(396.388681 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_144\">\n", "     <g id=\"line2d_284\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"411.430294\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_298\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(408.249044 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_145\">\n", "     <g id=\"line2d_285\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"423.290658\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_299\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(420.109408 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_146\">\n", "     <g id=\"line2d_286\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"435.151022\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_300\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(431.969772 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_147\">\n", "     <g id=\"line2d_287\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"447.011385\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_301\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(443.830135 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_148\">\n", "     <g id=\"line2d_288\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"458.871749\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_302\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(455.690499 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_149\">\n", "     <g id=\"line2d_289\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"470.732113\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_303\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(467.550863 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_150\">\n", "     <g id=\"line2d_290\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"482.592476\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_304\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(479.411226 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_30\">\n", "    <g id=\"ytick_141\">\n", "     <g id=\"line2d_291\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_305\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(356.556522 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_142\">\n", "     <g id=\"line2d_292\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_306\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(356.556522 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_143\">\n", "     <g id=\"line2d_293\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_307\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(356.556522 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_144\">\n", "     <g id=\"line2d_294\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_308\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(356.556522 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_145\">\n", "     <g id=\"line2d_295\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_309\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(356.556522 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_146\">\n", "     <g id=\"line2d_296\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_310\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(356.556522 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_147\">\n", "     <g id=\"line2d_297\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_311\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(356.556522 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_148\">\n", "     <g id=\"line2d_298\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_312\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(356.556522 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_149\">\n", "     <g id=\"line2d_299\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_313\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(356.556522 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_150\">\n", "     <g id=\"line2d_300\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"369.919022\" xlink:href=\"#mb7dafc2b9e\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_314\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(356.556522 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_73\">\n", "    <path d=\"M 369.919022 674.638125 \n", "L 369.919022 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_74\">\n", "    <path d=\"M 488.522658 674.638125 \n", "L 488.522658 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_75\">\n", "    <path d=\"M 369.919022 674.638125 \n", "L 488.522658 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_76\">\n", "    <path d=\"M 369.919022 556.034489 \n", "L 488.522658 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_315\">\n", "    <!-- Layer 4, Head 3 -->\n", "    <g transform=\"translate(381.538652 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-33\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", "  <g id=\"axes_16\">\n", "   <g id=\"patch_77\">\n", "    <path d=\"M 544.597283 674.638125 \n", "L 663.200919 674.638125 \n", "L 663.200919 556.034489 \n", "L 544.597283 556.034489 \n", "z\n", "\" style=\"fill:#ffffff;\"/>\n", "   </g>\n", "   <g clip-path=\"url(#p5c07aa41fb)\">\n", "    <image height=\"119\" id=\"imagef9c3160ce3\" transform=\"scale(1 -1)translate(0 -119)\" width=\"119\" x=\"544.597283\" xlink:href=\"data:image/png;base64,\n", "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\" y=\"-555.638125\"/>\n", "   </g>\n", "   <g id=\"matplotlib.axis_31\">\n", "    <g id=\"xtick_151\">\n", "     <g id=\"line2d_301\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"550.527464\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_316\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(547.346214 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_152\">\n", "     <g id=\"line2d_302\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"562.387828\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_317\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(559.206578 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_153\">\n", "     <g id=\"line2d_303\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"574.248192\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_318\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(571.066942 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_154\">\n", "     <g id=\"line2d_304\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"586.108555\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_319\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(582.927305 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_155\">\n", "     <g id=\"line2d_305\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"597.968919\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_320\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(594.787669 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_156\">\n", "     <g id=\"line2d_306\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"609.829283\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_321\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(606.648033 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_157\">\n", "     <g id=\"line2d_307\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"621.689646\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_322\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(618.508396 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_158\">\n", "     <g id=\"line2d_308\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"633.55001\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_323\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(630.36876 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_159\">\n", "     <g id=\"line2d_309\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"645.410374\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_324\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(642.229124 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"xtick_160\">\n", "     <g id=\"line2d_310\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"657.270737\" xlink:href=\"#m29bc816bb4\" y=\"674.638125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_325\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(654.089487 689.236562)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"matplotlib.axis_32\">\n", "    <g id=\"ytick_151\">\n", "     <g id=\"line2d_311\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"668.707943\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_326\">\n", "      <!-- 0 -->\n", "      <g transform=\"translate(531.234783 672.507162)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-30\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_152\">\n", "     <g id=\"line2d_312\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"656.84758\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_327\">\n", "      <!-- 1 -->\n", "      <g transform=\"translate(531.234783 660.646798)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-31\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_153\">\n", "     <g id=\"line2d_313\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"644.987216\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_328\">\n", "      <!-- 2 -->\n", "      <g transform=\"translate(531.234783 648.786435)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-32\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_154\">\n", "     <g id=\"line2d_314\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"633.126852\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_329\">\n", "      <!-- 3 -->\n", "      <g transform=\"translate(531.234783 636.926071)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-33\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_155\">\n", "     <g id=\"line2d_315\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"621.266489\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_330\">\n", "      <!-- 4 -->\n", "      <g transform=\"translate(531.234783 625.065707)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-34\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_156\">\n", "     <g id=\"line2d_316\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"609.406125\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_331\">\n", "      <!-- 5 -->\n", "      <g transform=\"translate(531.234783 613.205344)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-35\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_157\">\n", "     <g id=\"line2d_317\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"597.545761\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_332\">\n", "      <!-- 6 -->\n", "      <g transform=\"translate(531.234783 601.34498)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-36\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_158\">\n", "     <g id=\"line2d_318\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"585.685398\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_333\">\n", "      <!-- 7 -->\n", "      <g transform=\"translate(531.234783 589.484616)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-37\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_159\">\n", "     <g id=\"line2d_319\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"573.825034\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_334\">\n", "      <!-- 8 -->\n", "      <g transform=\"translate(531.234783 577.624253)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-38\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "    <g id=\"ytick_160\">\n", "     <g id=\"line2d_320\">\n", "      <g>\n", "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"544.597283\" xlink:href=\"#mb7dafc2b9e\" y=\"561.96467\"/>\n", "      </g>\n", "     </g>\n", "     <g id=\"text_335\">\n", "      <!-- 9 -->\n", "      <g transform=\"translate(531.234783 565.763889)scale(0.1 -0.1)\">\n", "       <use xlink:href=\"#DejaVuSans-39\"/>\n", "      </g>\n", "     </g>\n", "    </g>\n", "   </g>\n", "   <g id=\"patch_78\">\n", "    <path d=\"M 544.597283 674.638125 \n", "L 544.597283 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_79\">\n", "    <path d=\"M 663.200919 674.638125 \n", "L 663.200919 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_80\">\n", "    <path d=\"M 544.597283 674.638125 \n", "L 663.200919 674.638125 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"patch_81\">\n", "    <path d=\"M 544.597283 556.034489 \n", "L 663.200919 556.034489 \n", "\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n", "   </g>\n", "   <g id=\"text_336\">\n", "    <!-- Layer 4, Head 4 -->\n", "    <g transform=\"translate(556.216913 550.034489)scale(0.12 -0.12)\">\n", "     <use xlink:href=\"#DejaVuSans-4c\"/>\n", "     <use x=\"55.712891\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"116.992188\" xlink:href=\"#DejaVuSans-79\"/>\n", "     <use x=\"176.171875\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"237.695312\" xlink:href=\"#DejaVuSans-72\"/>\n", "     <use x=\"278.808594\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"310.595703\" xlink:href=\"#DejaVuSans-34\"/>\n", "     <use x=\"374.21875\" xlink:href=\"#DejaVuSans-2c\"/>\n", "     <use x=\"406.005859\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"437.792969\" xlink:href=\"#DejaVuSans-48\"/>\n", "     <use x=\"512.988281\" xlink:href=\"#DejaVuSans-65\"/>\n", "     <use x=\"574.511719\" xlink:href=\"#DejaVuSans-61\"/>\n", "     <use x=\"635.791016\" xlink:href=\"#DejaVuSans-64\"/>\n", "     <use x=\"699.267578\" xlink:href=\"#DejaVuSans-20\"/>\n", "     <use x=\"731.054688\" xlink:href=\"#DejaVuSans-34\"/>\n", "    </g>\n", "   </g>\n", "  </g>\n", " </g>\n", " <defs>\n", "  <clipPath id=\"pad35e7e34e\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p3f047439b5\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pc02064692f\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p0735244ca0\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"22.318125\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pae1bed9a54\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pda2b003fd9\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p4f5766fe4e\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pa9ce33fced\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"200.22358\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p86f60d31a4\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p5722fc46aa\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pdee8c6f53d\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pa255f7c335\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"378.129034\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pb3b8ad59fd\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"20.5625\" y=\"556.034489\"/>\n", "  </clipPath>\n", "  <clipPath id=\"pad3801ef8c\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"195.240761\" y=\"556.034489\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p3e848e2d93\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"369.919022\" y=\"556.034489\"/>\n", "  </clipPath>\n", "  <clipPath id=\"p5c07aa41fb\">\n", "   <rect height=\"118.603636\" width=\"118.603636\" x=\"544.597283\" y=\"556.034489\"/>\n", "  </clipPath>\n", " </defs>\n", "</svg>\n"], "text/plain": ["<Figure size 864x864 with 16 Axes>"]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}, {"name": "stdout", "output_type": "stream", "text": ["Probabilities:\n", "Image 0: 0.07%\n", "Image 1: 0.11%\n", "Image 2: 0.07%\n", "Image 3: 0.11%\n", "Image 4: 0.17%\n", "Image 5: 23.27%\n", "Image 6: 0.16%\n", "Image 7: 48.91%\n", "Image 8: 0.10%\n", "Image 9: 27.03%\n"]}], "source": ["visualize_prediction(mistakes[-1])\n", "print(\"Probabilities:\")\n", "for i, p in enumerate(preds[mistakes[-1]].cpu().numpy()):\n", "    print(\"Image %i: %4.2f%%\" % (i, 100.0 * p))"]}, {"cell_type": "markdown", "id": "fafec094", "metadata": {"papermill": {"duration": 0.236848, "end_time": "2021-12-04T15:59:37.319392", "exception": false, "start_time": "2021-12-04T15:59:37.082544", "status": "completed"}, "tags": []}, "source": ["In this example, the model confuses a palm tree with a building, giving a probability of ~90% to image 2, and 8% to the actual anomaly.\n", "However, the difficulty here is that the picture of the building has been taken at a similar angle as the palms.\n", "Meanwhile, image 2 shows a rather unusual palm with a different color palette, which is why the model fails here.\n", "Nevertheless, in general, the model performs quite well."]}, {"cell_type": "markdown", "id": "3ca49cba", "metadata": {"papermill": {"duration": 0.234811, "end_time": "2021-12-04T15:59:37.793046", "exception": false, "start_time": "2021-12-04T15:59:37.558235", "status": "completed"}, "tags": []}, "source": ["## Conclusion\n", "\n", "In this tutorial, we took a closer look at the Multi-Head Attention layer which uses a scaled dot product between\n", "queries and keys to find correlations and similarities between input elements.\n", "The Transformer architecture is based on the Multi-Head Attention layer and applies multiple of them in a ResNet-like block.\n", "The Transformer is a very important, recent architecture that can be applied to many tasks and datasets.\n", "Although it is best known for its success in NLP, there is so much more to it.\n", "We have seen its application on sequence-to-sequence tasks and set anomaly detection.\n", "Its property of being permutation-equivariant if we do not provide any positional encodings, allows it to generalize to many settings.\n", "Hence, it is important to know the architecture, but also its possible issues such as the gradient problem during\n", "the first iterations solved by learning rate warm-up.\n", "If you are interested in continuing with the study of the Transformer architecture,\n", "please have a look at the blog posts listed at the beginning of the tutorial notebook."]}, {"cell_type": "markdown", "id": "88cdba30", "metadata": {"papermill": {"duration": 0.240818, "end_time": "2021-12-04T15:59:38.270965", "exception": false, "start_time": "2021-12-04T15:59:38.030147", "status": "completed"}, "tags": []}, "source": ["## Congratulations - Time to Join the Community!\n", "\n", "Congratulations on completing this notebook tutorial! If you enjoyed this and would like to join the Lightning\n", "movement, you can do so in the following ways!\n", "\n", "### Star [Lightning](https://github.com/PyTorchLightning/pytorch-lightning) on GitHub\n", "The easiest way to help our community is just by starring the GitHub repos! This helps raise awareness of the cool\n", "tools we're building.\n", "\n", "### Join our [Slack](https://join.slack.com/t/pytorch-lightning/shared_invite/zt-pw5v393p-qRaDgEk24~EjiZNBpSQFgQ)!\n", "The best way to keep up to date on the latest advancements is to join our community! Make sure to introduce yourself\n", "and share your interests in `#general` channel\n", "\n", "\n", "### Contributions !\n", "The best way to contribute to our community is to become a code contributor! At any time you can go to\n", "[Lightning](https://github.com/PyTorchLightning/pytorch-lightning) or [Bolt](https://github.com/PyTorchLightning/lightning-bolts)\n", "GitHub Issues page and filter for \"good first issue\".\n", "\n", "* [Lightning good first issue](https://github.com/PyTorchLightning/pytorch-lightning/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)\n", "* [Bolt good first issue](https://github.com/PyTorchLightning/lightning-bolts/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)\n", "* You can also contribute your own notebooks with useful examples !\n", "\n", "### Great thanks from the entire Pytorch Lightning Team for your interest !\n", "\n", "[![Pytorch Lightning](data:image/png;base64,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){height=\"60px\" width=\"240px\"}](https://pytorchlightning.ai)"]}, {"cell_type": "raw", "metadata": {"raw_mimetype": "text/restructuredtext"}, "source": [".. customcarditem::\n", "   :header: Tutorial 5: Transformers and Multi-Head Attention\n", "   :card_description: In this tutorial, we will discuss one of the most impactful architectures of the last 2 years: the Transformer model. Since the paper Attention Is All You Need by Vaswani et...\n", "   :tags: Text,GPU/TPU,UvA-DL-Course\n", "   :image: _static/images/course_UvA-DL/05-transformers-and-MH-attention.jpg"]}], "metadata": {"jupytext": {"cell_metadata_filter": "id,colab,colab_type,-all", "formats": "ipynb,py:percent", "main_language": "python"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7"}, "papermill": {"default_parameters": {}, "duration": 100.878464, "end_time": "2021-12-04T15:59:39.519049", "environment_variables": {}, "exception": null, "input_path": "course_UvA-DL/05-transformers-and-MH-attention/Transformers_MHAttention.ipynb", "output_path": ".notebooks/course_UvA-DL/05-transformers-and-MH-attention.ipynb", "parameters": {}, "start_time": "2021-12-04T15:57:58.640585", "version": "2.3.3"}, "widgets": {"application/vnd.jupyter.widget-state+json": {"state": {"0b303c4195e64ef39fbeec6143263f98": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": "inline-flex", "flex": null, "flex_flow": "row wrap", "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "100%"}}, "0b80c7deefb24e7ba07594e61433755d": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": "2", "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "0e657111ed994cd18ee73800d5175c7d": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "117e6a6b8bf847059db276d064c2b13e": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "13f1b84e24984ba0b79e6125f96f99f3": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "169f7657723445bea5d0a4765d680159": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "178462769c7f44169c8ced0b55763811": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "236a5851e62d43d7b60a7d52dce28c1a": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_e3e6a9b6686f420f80e224eca063a19f", "IPY_MODEL_24d5d210a2b24f36a66613fa0ccb4233", "IPY_MODEL_e1bd4f10532642b8a15721a759eeb58b"], "layout": "IPY_MODEL_b49848bb32524b95a97c93ad92127987"}}, "24471f587ee94549b81ff8a94a6e0a78": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_512f768512c74743b343a6e8251d6ff1", "placeholder": "\u200b", "style": "IPY_MODEL_b7ff55f2178541fc99b01101431fd146", "value": " 79/79 [00:00&lt;00:00, 147.56it/s]"}}, "248e84e3800948aaa5d4b99a97521525": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "24d5d210a2b24f36a66613fa0ccb4233": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_87fe3739fd654f94bc44066ccbb7f227", "max": 87306240.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_dd2bb7a927774638a5d1894442cb22b2", "value": 87306240.0}}, "29f9153bb21a44b487d35377cb438123": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "2b58bae07432436298a33aaaf21cd6e4": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "2bd4ea3a82024c858491e89acc4aa047": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "2ca1e45629ec4679a85bd781162d6b1c": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "2f853c9d6857487ea62b0226abe31f79": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_178462769c7f44169c8ced0b55763811", "placeholder": "\u200b", "style": "IPY_MODEL_13f1b84e24984ba0b79e6125f96f99f3", "value": " 79/79 [00:05&lt;00:00, 15.23it/s]"}}, "2f8d30ea351341eb8601ad7c4e38834c": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "301dc13411cd4b16957a001be48e9feb": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": "inline-flex", "flex": null, "flex_flow": "row wrap", "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "100%"}}, "334865d5a9b24d738acc57ecf7793f00": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": "inline-flex", "flex": null, "flex_flow": "row wrap", "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "100%"}}, "336b58f1c17b4c2998f77978c46f92b2": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_b68f68938fb444f8bda9725eb32bac90", "IPY_MODEL_7aa0e6f3f2884d28b3ab91fbe177cdd1", "IPY_MODEL_5f2d0ce055ee405b923e0a374e5932c6"], "layout": "IPY_MODEL_e3bf53dac0194713bd220e0fe48fee33"}}, "344aba03213349f591500fe672e8afdf": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "35f58d761f794fdea716c3eeb2c6ec80": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_77e443eccd6342b989fbcb88945429d3", "placeholder": "\u200b", "style": "IPY_MODEL_a58d18832c084ab792d67eeb729c7635", "value": "100%"}}, "37ccf9ab76824da89ed0187799f2ea08": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "3a3f8db09b6d4cc5b53b747e2b7b9da6": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "3aa4aeee7b5f4eb5aee77dce65dcade9": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_35f58d761f794fdea716c3eeb2c6ec80", "IPY_MODEL_4fd7a34138db4283a966e6fb6a31b988", "IPY_MODEL_2f853c9d6857487ea62b0226abe31f79"], "layout": "IPY_MODEL_0e657111ed994cd18ee73800d5175c7d"}}, "3c5caa9157bc4baf9a570f8782e29475": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "4180b35ca339453686f92f651153f871": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ce6b8e1c9e7346ff92a0fd9dd9816ef0", "placeholder": "\u200b", "style": "IPY_MODEL_2b58bae07432436298a33aaaf21cd6e4", "value": "Testing: 100%"}}, "45a9d84f4f2c4e7bb899ba0057f9745d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f48bac3019244c07803f84c2e6d95ea0", "max": 1.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_522def02fad0470a9d6abc40677772dc", "value": 1.0}}, "47a76bee08d74e2799d591493ecb37f2": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": "2", "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "4fd7a34138db4283a966e6fb6a31b988": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b15347bd314048409dbc07933d388917", "max": 79.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_248e84e3800948aaa5d4b99a97521525", "value": 79.0}}, "4fe895cd281b4d2f91f744ffc6f1a0bd": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "5007ffc533144720b1d8aabfe6bc2ec6": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "508f4a8250ff41eab6f008a7094da94a": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "50e6daea1e294714a838e9a83f7f66ed": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "512f768512c74743b343a6e8251d6ff1": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "522def02fad0470a9d6abc40677772dc": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "563fcf83e0ce41379f34ddca6f1339a0": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "575514ed749f42a997a2baa322b6efa5": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d4079c1c7a0e419fb8aca46a9ecefa25", "placeholder": "\u200b", "style": "IPY_MODEL_7da963515d2c41e889a004ca662079e4", "value": " 79/79 [00:00&lt;00:00, 288.13it/s]"}}, "5c105436e67d40e0b6da633b6a00ead8": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "5f2d0ce055ee405b923e0a374e5932c6": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d2f30746e64b4ebba654f67c9f23b32f", "placeholder": "\u200b", "style": "IPY_MODEL_bcf6aea6625647039795bd8c30585346", "value": " 391/391 [00:27&lt;00:00, 14.99it/s]"}}, "60febcf280f34ad8849e28a112b83802": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": "inline-flex", "flex": null, "flex_flow": "row wrap", "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "100%"}}, "65135f33d2c940b19ad2b625abb25376": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": "inline-flex", "flex": null, "flex_flow": "row wrap", "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "100%"}}, "6a189067bc0f406594c18d8e8f5640eb": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "71e812687f0749799bf97615573d22f9": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_50e6daea1e294714a838e9a83f7f66ed", "placeholder": "\u200b", "style": "IPY_MODEL_5007ffc533144720b1d8aabfe6bc2ec6", "value": ""}}, "73ef64d0e797442ab771d4e2728baaab": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "7428277b5ed04997b19990cc745ba65f": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "767da7c44af140cdb3413c158988e913": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "77e443eccd6342b989fbcb88945429d3": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "7aa0e6f3f2884d28b3ab91fbe177cdd1": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_db005c58c17c46bc904b0e844c4c1dc8", "max": 391.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_e5dedb39aecd428ea3dd6d2e15dbb49d", "value": 391.0}}, "7c565ce6f14141dca6e213b4c0a463a0": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": "2", "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "7da963515d2c41e889a004ca662079e4": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "7e7c9b0794174e2aaa68e3682517db1d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0b80c7deefb24e7ba07594e61433755d", "max": 1.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_8c3f67d4af6d4c9cae34014915f7cc58", "value": 1.0}}, "7f73079d25064959932573707f3e2c52": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "8474a73379874c7a9597a35a15c7e585": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c8a127a3c7d8451f9a464af27ccec9b4", "max": 1.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_896c1b7cd27a4e46b437fdb3666edf55", "value": 1.0}}, "87fe3739fd654f94bc44066ccbb7f227": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "896c1b7cd27a4e46b437fdb3666edf55": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "89c0145b83d34648bacf9da6ad15d74d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_dd915efd78e44054a1826e4be665b035", "IPY_MODEL_8474a73379874c7a9597a35a15c7e585", "IPY_MODEL_575514ed749f42a997a2baa322b6efa5"], "layout": "IPY_MODEL_60febcf280f34ad8849e28a112b83802"}}, "8c3f67d4af6d4c9cae34014915f7cc58": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "983722707bb64460bfbdc38056f7d32d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_d83de3be21e04615a11e3659d3a83abc", "IPY_MODEL_7e7c9b0794174e2aaa68e3682517db1d", "IPY_MODEL_24471f587ee94549b81ff8a94a6e0a78"], "layout": "IPY_MODEL_334865d5a9b24d738acc57ecf7793f00"}}, "99532397f9914f338666889ca9cd1285": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "99f1cedd123941169dc16b83030bced1": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "9c0f4106b2fa430d807e9c34f98e5bd2": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_f47589b9dfad41088d797c8ce2a9761a", "IPY_MODEL_d51b5e09340f4c24b51ac50bd1ef8c8f", "IPY_MODEL_cfc6b274acec498c870a3d5ef0252cf4"], "layout": "IPY_MODEL_65135f33d2c940b19ad2b625abb25376"}}, "9fe2ccea8542438f8b6f3adaf6a5e302": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "a58d18832c084ab792d67eeb729c7635": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "aad913a268f3461a947ea946df80ce7d": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ab0dc6637c5348a9839eded7ec182961": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_ce0141f331ad484189ed4500c2287b0d", "IPY_MODEL_aba0095cda6a462d94fe0e0979e1bd9a", "IPY_MODEL_c7741f8ad62e493a97a27ea1f32acc15"], "layout": "IPY_MODEL_0b303c4195e64ef39fbeec6143263f98"}}, "ab80d9dadcc34224ad525011c3a46c9f": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_117e6a6b8bf847059db276d064c2b13e", "max": 169001437.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_3c5caa9157bc4baf9a570f8782e29475", "value": 169001437.0}}, "aba0095cda6a462d94fe0e0979e1bd9a": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_47a76bee08d74e2799d591493ecb37f2", "max": 1.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_2bd4ea3a82024c858491e89acc4aa047", "value": 1.0}}, "b15347bd314048409dbc07933d388917": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b49848bb32524b95a97c93ad92127987": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b68f68938fb444f8bda9725eb32bac90": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_344aba03213349f591500fe672e8afdf", "placeholder": "\u200b", "style": "IPY_MODEL_508f4a8250ff41eab6f008a7094da94a", "value": "100%"}}, "b7ff55f2178541fc99b01101431fd146": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "b9ed1cfedbeb4586bab29909930e47b1": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_4180b35ca339453686f92f651153f871", "IPY_MODEL_45a9d84f4f2c4e7bb899ba0057f9745d", "IPY_MODEL_d51f7aa60a654aae991f9b2ccd974311"], "layout": "IPY_MODEL_301dc13411cd4b16957a001be48e9feb"}}, "bacb5883fee34339abc34dd04428fd19": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "bcf6aea6625647039795bd8c30585346": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "c7741f8ad62e493a97a27ea1f32acc15": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7428277b5ed04997b19990cc745ba65f", "placeholder": "\u200b", "style": "IPY_MODEL_2ca1e45629ec4679a85bd781162d6b1c", "value": " 157/157 [00:01&lt;00:00, 163.00it/s]"}}, "c8a127a3c7d8451f9a464af27ccec9b4": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": "2", "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c9833783e4f24255a6dbfb6716d13e22": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ce0141f331ad484189ed4500c2287b0d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_767da7c44af140cdb3413c158988e913", "placeholder": "\u200b", "style": "IPY_MODEL_dc3260543b5f40d58b6b604961c71781", "value": "Testing: 100%"}}, "ce6b8e1c9e7346ff92a0fd9dd9816ef0": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "cfc6b274acec498c870a3d5ef0252cf4": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c9833783e4f24255a6dbfb6716d13e22", "placeholder": "\u200b", "style": "IPY_MODEL_3a3f8db09b6d4cc5b53b747e2b7b9da6", "value": " 703/703 [00:03&lt;00:00, 197.32it/s]"}}, "d2f30746e64b4ebba654f67c9f23b32f": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d4079c1c7a0e419fb8aca46a9ecefa25": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d4443194a5e84e52a7f9e44f7e4d7e6b": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "d51b5e09340f4c24b51ac50bd1ef8c8f": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7c565ce6f14141dca6e213b4c0a463a0", "max": 1.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_37ccf9ab76824da89ed0187799f2ea08", "value": 1.0}}, "d51f7aa60a654aae991f9b2ccd974311": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2f8d30ea351341eb8601ad7c4e38834c", "placeholder": "\u200b", "style": "IPY_MODEL_d4443194a5e84e52a7f9e44f7e4d7e6b", "value": " 8/8 [00:00&lt;00:00, 132.04it/s]"}}, "d83de3be21e04615a11e3659d3a83abc": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aad913a268f3461a947ea946df80ce7d", "placeholder": "\u200b", "style": "IPY_MODEL_9fe2ccea8542438f8b6f3adaf6a5e302", "value": "Testing: 100%"}}, "db005c58c17c46bc904b0e844c4c1dc8": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "dc3260543b5f40d58b6b604961c71781": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": ""}}, "dd2bb7a927774638a5d1894442cb22b2": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "dd915efd78e44054a1826e4be665b035": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bacb5883fee34339abc34dd04428fd19", "placeholder": "\u200b", "style": "IPY_MODEL_29f9153bb21a44b487d35377cb438123", "value": "Testing: 100%"}}, "e1bd4f10532642b8a15721a759eeb58b": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_73ef64d0e797442ab771d4e2728baaab", "placeholder": "\u200b", "style": "IPY_MODEL_7f73079d25064959932573707f3e2c52", "value": " 83.3M/83.3M [00:00&lt;00:00, 116MB/s]"}}, "e3bf53dac0194713bd220e0fe48fee33": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e3e6a9b6686f420f80e224eca063a19f": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_99f1cedd123941169dc16b83030bced1", "placeholder": "\u200b", "style": "IPY_MODEL_169f7657723445bea5d0a4765d680159", "value": "100%"}}, "e5dedb39aecd428ea3dd6d2e15dbb49d": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "efc763b5cd4e4ed9b3e3881bad434e2b": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_71e812687f0749799bf97615573d22f9", "IPY_MODEL_ab80d9dadcc34224ad525011c3a46c9f", "IPY_MODEL_f72acb891d864ee79f5d536286cc4667"], "layout": "IPY_MODEL_99532397f9914f338666889ca9cd1285"}}, "f47589b9dfad41088d797c8ce2a9761a": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4fe895cd281b4d2f91f744ffc6f1a0bd", "placeholder": "\u200b", "style": "IPY_MODEL_6a189067bc0f406594c18d8e8f5640eb", "value": "Testing: 100%"}}, "f48bac3019244c07803f84c2e6d95ea0": {"model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": "2", "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "f72acb891d864ee79f5d536286cc4667": {"model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5c105436e67d40e0b6da633b6a00ead8", "placeholder": "\u200b", "style": "IPY_MODEL_563fcf83e0ce41379f34ddca6f1339a0", "value": " 169001984/? [00:01&lt;00:00, 103277285.22it/s]"}}}, "version_major": 2, "version_minor": 0}}}, "nbformat": 4, "nbformat_minor": 5}