{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment\n", " \n", "Hi, my name is Svetlana (https://hub.tripleten.com/u/855fe797). Congratulations on submitting another project! 🎉 I will be using the standard color marking. \n", " \n", " \n", "
\n", "\n", "Great solutions and ideas that can and should be used in the future are in green comments. You have successfully normalized the `review` column, employed advanced techniques such as lemmatization and vectorizing, trained multiple models including a dummy baseline, and applied the `evaluate_model()` method for their assessment. Great job! The results look very good.\n", "\n", "
\n", " \n", "
\n", " Reviewer's comment \n", "\n", "Yellow color indicates what should be optimized. This is not necessary, but it will be great if you make changes to this project. \n", "\n", " \n", "
\n", "
\n", " Reviewer's comment \n", "\n", "Issues that must be corrected to achieve accurate results are indicated in red comments. However, there are no such issues, great job! \n", "
\n", "
\n", " \n", "**To sum up:** thank you for such an excellent job! You showed strong coding skills and a solid understanding of this topic, which is quite hard. I hope you enjoyed working on this project. You have successfully analyzed the distributions, employed advanced techniques such as lemmatization and vectorizing, and trained several models. The models were trained and evaluated correctly. \n", "\n", " \n", "I've left several comments, but I do not have any questions, so the project is accepted. \n", "\n", "\n", "
\n", " \n", "✍️ If you are interested in Large Language Models, check out [Intro to Large Language Models](https://www.youtube.com/watch?v=zjkBMFhNj_g) and [Tokenization lecture](https://www.youtube.com/watch?v=zduSFxRajkE) by Andrej Karpathy, one of the leading scientists in this area. He has also recently published a nice [Deep Dive into LLMs like ChatGPT](https://www.youtube.com/watch?v=7xTGNNLPyMI) tutorial where he explains all LLM preparation stages and a very useful video about how he uses LLM [here](https://www.youtube.com/watch?v=EWvNQjAaOHw&feature=youtu.be). This is a comprehensive guide on how to choose the optimal tool for your tasks while saving time and money.\n", " \n", " \n", " \n", "I would also like to recommend this new **Language Modeling from Scratch Spring 2025 class by Stanford**. This class has just started. There are three links: [Recorded lectures on Youtube](https://www.youtube.com/playlist?list=PLoROMvodv4rOY23Y0BoGoBGgQ1zmU_MT_), [course website](https://stanford-cs336.github.io/spring2025/), and the [GitHub repository with assignments and jupyter notebooks](https://github.com/stanford-cs336). This course is up-to-date, so the information there is super relevant today.\n", "\n", " \n", " \n", "By the way, Hugging Face has a good free [NLP course](https://huggingface.co/learn/nlp-course/en/chapter0/1).\n", " \n", " \n", "Here's a link to [AI for beginners](https://github.com/microsoft/ai-for-beginners) course by Microsoft. \n", " \n", " \n", "
\n", "Congratulations and good luck! \n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Project Statement" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Film Junky Union, a new edgy community for classic movie enthusiasts, is developing a system for filtering and categorizing movie reviews. The goal is to train a model to automatically detect negative reviews. You'll be using a dataset of IMBD movie reviews with polarity labelling to build a model for classifying positive and negative reviews. It will need to have an F1 score of at least 0.85." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Initialization" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import math\n", "\n", "import numpy as np\n", "import pandas as pd\n", "\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "import matplotlib.dates as mdates\n", "import seaborn as sns\n", "\n", "from tqdm.auto import tqdm\n", "\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.pipeline import Pipeline\n", "\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.naive_bayes import MultinomialNB\n", "from sklearn.ensemble import RandomForestClassifier\n", "\n", "from sklearn.metrics import (\n", " classification_report,\n", " confusion_matrix,\n", " f1_score\n", ")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "%config InlineBackend.figure_format = 'png'\n", "# the next line provides graphs of better quality on HiDPI screens\n", "%config InlineBackend.figure_format = 'retina'\n", "\n", "plt.style.use('seaborn')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# this is to use progress_apply, read more at https://pypi.org/project/tqdm/#pandas-integration\n", "tqdm.pandas()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load Data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "df_reviews = pd.read_csv('/datasets/imdb_reviews.tsv', sep='\\t', dtype={'votes': 'Int64'})" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 47331 entries, 0 to 47330\n", "Data columns (total 17 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 tconst 47331 non-null object \n", " 1 title_type 47331 non-null object \n", " 2 primary_title 47331 non-null object \n", " 3 original_title 47331 non-null object \n", " 4 start_year 47331 non-null int64 \n", " 5 end_year 47331 non-null object \n", " 6 runtime_minutes 47331 non-null object \n", " 7 is_adult 47331 non-null int64 \n", " 8 genres 47331 non-null object \n", " 9 average_rating 47329 non-null float64\n", " 10 votes 47329 non-null Int64 \n", " 11 review 47331 non-null object \n", " 12 rating 47331 non-null int64 \n", " 13 sp 47331 non-null object \n", " 14 pos 47331 non-null int64 \n", " 15 ds_part 47331 non-null object \n", " 16 idx 47331 non-null int64 \n", "dtypes: Int64(1), float64(1), int64(5), object(10)\n", "memory usage: 6.2+ MB\n" ] } ], "source": [ "df_reviews.info()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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tconsttitle_typeprimary_titleoriginal_titlestart_yearend_yearruntime_minutesis_adultgenresaverage_ratingvotesreviewratingspposds_partidx
0tt0068152movie$$1971\\N1210Comedy,Crime,Drama6.32218The pakage implies that Warren Beatty and Gold...1neg0train8335
1tt0068152movie$$1971\\N1210Comedy,Crime,Drama6.32218How the hell did they get this made?! Presenti...1neg0train8336
2tt0313150short'15''15'2002\\N250Comedy,Drama,Short6.3184There is no real story the film seems more lik...3neg0test2489
3tt0313150short'15''15'2002\\N250Comedy,Drama,Short6.3184Um .... a serious film about troubled teens in...7pos1test9280
4tt0313150short'15''15'2002\\N250Comedy,Drama,Short6.3184I'm totally agree with GarryJohal from Singapo...9pos1test9281
\n", "
" ], "text/plain": [ " tconst title_type primary_title original_title start_year end_year \\\n", "0 tt0068152 movie $ $ 1971 \\N \n", "1 tt0068152 movie $ $ 1971 \\N \n", "2 tt0313150 short '15' '15' 2002 \\N \n", "3 tt0313150 short '15' '15' 2002 \\N \n", "4 tt0313150 short '15' '15' 2002 \\N \n", "\n", " runtime_minutes is_adult genres average_rating votes \\\n", "0 121 0 Comedy,Crime,Drama 6.3 2218 \n", "1 121 0 Comedy,Crime,Drama 6.3 2218 \n", "2 25 0 Comedy,Drama,Short 6.3 184 \n", "3 25 0 Comedy,Drama,Short 6.3 184 \n", "4 25 0 Comedy,Drama,Short 6.3 184 \n", "\n", " review rating sp pos \\\n", "0 The pakage implies that Warren Beatty and Gold... 1 neg 0 \n", "1 How the hell did they get this made?! Presenti... 1 neg 0 \n", "2 There is no real story the film seems more lik... 3 neg 0 \n", "3 Um .... a serious film about troubled teens in... 7 pos 1 \n", "4 I'm totally agree with GarryJohal from Singapo... 9 pos 1 \n", "\n", " ds_part idx \n", "0 train 8335 \n", "1 train 8336 \n", "2 test 2489 \n", "3 test 9280 \n", "4 test 9281 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_reviews.head()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "tconst 0\n", "title_type 0\n", "primary_title 0\n", "original_title 0\n", "start_year 0\n", "end_year 0\n", "runtime_minutes 0\n", "is_adult 0\n", "genres 0\n", "average_rating 2\n", "votes 2\n", "review 0\n", "rating 0\n", "sp 0\n", "pos 0\n", "ds_part 0\n", "idx 0\n", "dtype: int64\n", "\n", "train 23796\n", "test 23535\n", "Name: ds_part, dtype: int64\n", "\n", "0 23715\n", "1 23616\n", "Name: pos, dtype: int64\n", "duplicate reviews: 91\n" ] } ], "source": [ "print(df_reviews.isna().sum())\n", "print()\n", "print(df_reviews['ds_part'].value_counts())\n", "print()\n", "print(df_reviews['pos'].value_counts())\n", "\n", "print('duplicate reviews:', df_reviews['review'].duplicated().sum())" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1 81\n", "2 1\n", "Name: ds_part, dtype: int64\n" ] } ], "source": [ "dupes = df_reviews[df_reviews['review'].duplicated(keep=False)]\n", "print(dupes.groupby('review')['ds_part'].nunique().value_counts())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The dataset holds 47,331 IMDB reviews across 17 columns, of which only three matter for modeling: review for the text, pos which is the binary target, and ds_part the predefined train/test flag. The target is balanced at 23,715 negative and 23,616 positive, so a constant baseline will score near zero on F1 and no class weighting is needed. The split is already made and near even, 23,796 train and 23,535 test." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## EDA" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's check the number of movies and reviews over years." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 787, "width": 1590 } }, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(2, 1, figsize=(16, 8))\n", "\n", "ax = axs[0]\n", "\n", "dft1 = df_reviews[['tconst', 'start_year']].drop_duplicates() \\\n", " ['start_year'].value_counts().sort_index()\n", "dft1 = dft1.reindex(index=np.arange(dft1.index.min(), max(dft1.index.max(), 2021))).fillna(0)\n", "dft1.plot(kind='bar', ax=ax)\n", "ax.set_title('Number of Movies Over Years')\n", "\n", "ax = axs[1]\n", "\n", "dft2 = df_reviews.groupby(['start_year', 'pos'])['pos'].count().unstack()\n", "dft2 = dft2.reindex(index=np.arange(dft2.index.min(), max(dft2.index.max(), 2021))).fillna(0)\n", "\n", "dft2.plot(kind='bar', stacked=True, label='#reviews (neg, pos)', ax=ax)\n", "\n", "dft2 = df_reviews['start_year'].value_counts().sort_index()\n", "dft2 = dft2.reindex(index=np.arange(dft2.index.min(), max(dft2.index.max(), 2021))).fillna(0)\n", "dft3 = (dft2/dft1).fillna(0)\n", "axt = ax.twinx()\n", "dft3.reset_index(drop=True).rolling(5).mean().plot(color='orange', label='reviews per movie (avg over 5 years)', ax=axt)\n", "\n", "lines, labels = axt.get_legend_handles_labels()\n", "ax.legend(lines, labels, loc='upper left')\n", "\n", "ax.set_title('Number of Reviews Over Years')\n", "\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's check the distribution of number of reviews per movie with the exact counting and KDE (just to learn how it may differ from the exact counting)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 488, "width": 1590 } }, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(1, 2, figsize=(16, 5))\n", "\n", "ax = axs[0]\n", "dft = df_reviews.groupby('tconst')['review'].count() \\\n", " .value_counts() \\\n", " .sort_index()\n", "dft.plot.bar(ax=ax)\n", "ax.set_title('Bar Plot of #Reviews Per Movie')\n", "\n", "ax = axs[1]\n", "dft = df_reviews.groupby('tconst')['review'].count()\n", "sns.kdeplot(dft, ax=ax)\n", "ax.set_title('KDE Plot of #Reviews Per Movie')\n", "\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The dataset is concentrated in modern cinema, with movie counts rising steeply from the mid-1980s and peaking around 2005. The apparent collapse after 2007 is an artifact of reindexing the year axis to 2021, not a real trend, since the data simply ends there. Polarity stays balanced across all years with meaningful volume.\n", "\n", "Reviews per movie are heavily right-skewed: most movies have only 1 to 3 reviews, with a hard cap at 30 where roughly 420 movies cluster. The cap is deliberate in the source dataset and ensures no single film dominates the corpus, so the model cannot learn film-specific vocabulary in place of sentiment.\n", "\n", "The KDE panel illustrates why smoothing misleads on this variable: it assigns mass to negative review counts, which are impossible, and softens the hard ceiling at 30 into a gentle bump. The exact bar counting is the correct view for a bounded discrete variable." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 23715\n", "1 23616\n", "Name: pos, dtype: int64" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_reviews['pos'].value_counts()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 389, "width": 1190 } }, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(1, 2, figsize=(12, 4))\n", "\n", "ax = axs[0]\n", "dft = df_reviews.query('ds_part == \"train\"')['rating'].value_counts().sort_index()\n", "dft = dft.reindex(index=np.arange(min(dft.index.min(), 1), max(dft.index.max(), 11))).fillna(0)\n", "dft.plot.bar(ax=ax)\n", "ax.set_ylim([0, 5000])\n", "ax.set_title('The train set: distribution of ratings')\n", "\n", "ax = axs[1]\n", "dft = df_reviews.query('ds_part == \"test\"')['rating'].value_counts().sort_index()\n", "dft = dft.reindex(index=np.arange(min(dft.index.min(), 1), max(dft.index.max(), 11))).fillna(0)\n", "dft.plot.bar(ax=ax)\n", "ax.set_ylim([0, 5000])\n", "ax.set_title('The test set: distribution of ratings')\n", "\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Train and test have near-identical rating distributions, confirming no distribution shift between the two splits and making test F1 a trustworthy measure of generalization.\n", "\n", "Both are strongly bimodal, with ratings 1 and 10 accounting for the largest shares and a deliberate gap at 5 and 6. The source dataset excludes the ambiguous middle, so every example is clearly polarized. This makes the task easier than real-world sentiment classification, where lukewarm reviews dominate, and any strong F1 achieved here should be read with that caveat.\n", "\n", "Errors are expected to concentrate at ratings 4 and 7, the two categories closest to the polarity boundary, where review language is most mixed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Distribution of negative and positive reviews over the years for two parts of the dataset" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/.venv/lib/python3.9/site-packages/seaborn/distributions.py:1666: UserWarning: Support for alternate kernels has been removed. Using Gaussian kernel.\n", " warnings.warn(msg, UserWarning)\n", "/.venv/lib/python3.9/site-packages/seaborn/distributions.py:1666: UserWarning: Support for alternate kernels has been removed. Using Gaussian kernel.\n", " warnings.warn(msg, UserWarning)\n", "/.venv/lib/python3.9/site-packages/seaborn/distributions.py:1666: UserWarning: Support for alternate kernels has been removed. Using Gaussian kernel.\n", " warnings.warn(msg, UserWarning)\n", "/.venv/lib/python3.9/site-packages/seaborn/distributions.py:1666: UserWarning: Support for alternate kernels has been removed. Using Gaussian kernel.\n", " warnings.warn(msg, UserWarning)\n" ] }, { "data": { "image/png": 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rGBsbw9HREV27dsWQIUNgaWmpdv6aqAtXdl++ePEiDh06hAcPHojf98yZM/H5558X+XtQdBy9ePECu3btwqVLlxAVFYXs7GzUrl0bPj4+GDFiBMzMzGTyeP78ObZv344bN24gMjIS+vr6qFu3Lvr06YPBgwfDwMBArbIIgoCTJ0/izJkzuHfvHt6+fQsAqFixIpo1a4auXbuie/fuSr+zBQsWiN/RoEGD8NNPP6m13iNHjmDq1KkAgHr16uHYsWOFfkeqaLIdpCQYvEFERETvjGfPnmHSpEkICQmR+Tw6OhrHjh3DsWPHMH78eEyaNKnQvKKiovD999/LVQ4C+S+vxsbG4vLly1i/fj1+/fVXtGjRQmPbURKvX7/G5MmTERgYqDLd3bt38fnnnyMtLU1uXnZ2NtLS0hAZGQk/Pz+sXbsWq1evLvKLT+rYuXMnFi1ahKysLJnPHz9+jMePH2PPnj34888/C30hUh05OTn46aefsHv3brl5ubm54n69e/cudu3ahS+//BKTJ09Wmt+JEyewcOFCxMbGys178eIFXrx4gf3796Njx45YunQprKysSrwNpe3169f45ptvcPv2bZnPY2NjcfbsWZw9exb9+vXDwoULddpzSnp6On744Qe5H2lZWVm4dOkSLl26JFOpERcXh6+//lrhdp06dQqnT5/G7NmzMXToULXLcPv2bUyaNAkxMTEyn0dERCAiIgK+vr746quv1KowS0xMxP/+9z+cOnVKbt6bN2/w5s0b3LhxAxs3bsT8+fPRo0cPtcu5e/duLFy4EJmZmWovo47z58/jf//7n9z5kJWVhaSkJDx9+hQ7duzAhx9+iAULFshVGOhCYGAgpkyZgqioqELTPnr0CDNmzEBwcLDcvOjoaERHR+Ps2bNYv349Vq9eLVfRZ2RkhJ49e2Lnzp0AgMOHD6sVvBETE4Pr168DyO+d6KOPPlJn0xTKy8vDqlWrsGnTJrn9n5iYiMTERAQHB2Pbtm0YPXo0vv32W7kKCXt7e9SpUwehoaGIjY1FSEgInJyc5NYVEREhU+EYFxeHp0+fokGDBnJpo6KixMCNatWqyQVupKWlYcqUKQobi3Jzc5GRkYHXr18jMDAQ27Ztw4IFCzBgwAD1vxgl7t69i6lTp4plk8jMzERqairCwsLg6+uLNm3aYNmyZRpvdC6KHTt2YMmSJTL7NT09HYmJiXj06BG2b9+OJUuWwMLCQmdlLA5tPoutWrUKa9euRW5ubqFpd+zYgV9//RXJyckyn2dlZSE5ORkhISHYuXMn+vXrh7lz56rdWFFe7rHSzp49i+nTp8t9F6GhoQgNDcXu3bsxa9YsDBo0qNC8Svu+cfr0aUyZMkXumRPIf/ZNTU1FREQEjh07Jl7La9asqXb+6j6DlwWauB9IhIaGYvz48XK/v4D863d4eDjCw8Nx+fJl/PHHHzh9+nSRAnwK8749f3Xs2BH29vaIjY1FaGgoAgMD1XpRbd++fRAEAQDQuXNnpfcsf39/zJ49W+7eB+S/wBAZGYljx47Bzc0Nv//+O6pUqaJ0nZ988gnu37+vcN7bt2/x9u1b3L59G5s2bcI333yDMWPGFLod0rT1TEtEREREZQvbfNjmowrbfNSni/rD3bt3Y9GiRcjIyJCbl5CQgISEBDx+/BhHjx7FkSNHxLpzTStKO0BRabJeojxJS0vDDz/8gOPHj8vNe/36NV6/fo3Lly9j3bp1WLhwoVznaqroqs507dq1WLt2rVw9g6QO4+7du/jzzz8xYcIEjB07VmPrLarU1FRMnjwZFy9elPlc8r1fvXoVe/bswW+//aajEhaftq7BRam31Wb9oJ+fH2bMmKG0bn3fvn347bff0KFDB7Xz1Kbs7GzMnz9f7h6bmZmJwMBABAYG4p9//sGaNWsK7QAoJycHixcvxj///CPXJiO5VwcEBGDjxo2YNWsW+vbtW+Lyf/PNN0o7vomPj0d8fDyCgoKwbds2DB8+HNOnT1f75XUgf3/OmjULiYmJJS6rtmnyGVjX9/ZVq1bhjz/+QF5envhZeno67t+/j/v372PHjh347bff1GqD12RduLTk5GTMnDkTZ86cUX/DiujQoUOYM2cO0tPTZT6XPG+fOnUKW7duFYPM/vjjD6xatUrmewPyfz/cvXsXJ0+exIYNGwpthwsLC8PkyZPx8OFDuXlpaWmIiIjA0aNH0bhxY/z2228K29h69+4tBm+cPHkSs2fPVqtd9fDhwzJ5lIS29n1xMHiDiIiI3gkxMTH4/PPPERsbC2trazRv3hz29vaIj4/H9evXxR/Ca9asQb169eDj46M0r5CQEIwYMUKsHNDT00OjRo1Qr149mJqa4vXr17hx4wZSU1MRExODkSNHYuPGjWjVqlWxyu7q6oohQ4bg9evX8PPzAwBUrlwZXbt2lUtra2urNJ+srCx89dVXCAoKgqGhIdzd3VGzZk1kZWXJPUAnJiaKlfgVK1ZEvXr1ULVqVZiZmSEjIwMvXrzA/fv3kZOTg8jISAwdOhQHDhzQ6MtW+/fvx9y5cwHk9xzbpEkTmJqa4vnz57h16xYEQUBCQgK++uornDhxosQV4b/88otMBUOVKlXg6uoKOzs75OXlISEhAc+ePUNoaGiheW3duhWLFy8WX4KytLSEm5sbqlatiry8PDx9+hQPHjyAIAg4f/48hg0bhp07d8r84Cnpfi/Yi4uyXkqKKy0tDaNHj8aTJ09gZmaG5s2bo1q1akhNTYW/v78YRb9//37UqVNHp5WVksANQ0NDeHh4wNHRERkZGbh+/TrevHkDIL9Xpjp16qBLly4YNWoUgoODYWJigpYtW6JatWpISkrC9evXkZiYCEEQsGDBAjRu3FitH/evXr3C4sWLkZiYCHNzc7Rq1QqVKlVCTEwM/P39kZ6ejtzcXKxevRp5eXn45ptvlOYVGxuLESNGyDRI1q9fH87OzrCwsMDbt29x8+ZNJCQkICkpCd9++y1++eUXtX6knjx5EkuXLgWQf6x5eHjAyspK7HG+uI4fP46pU6eKFW4GBgZo3rw5HB0dkZaWhps3b4qNF0ePHkVkZCT++usvmJiYiHlUqVIFQ4YMAZDf88O1a9cAAHXr1pXrRUcTvbC/ePECixYtQnJyMiwsLNCyZUtUrlwZiYmJMj2iAMCNGzfw5ZdfIiUlBUB+IEaTJk1Qu3ZtGBoaIjIyEoGBgcjMzERoaCgGDx6M3bt3ywU19O7dW6ykOnHiBH744YdCez86fvy4+L16eXkVu3IgNzcXkydPlqlwlr4Gpqam4t69ewgPD0dOTg7WrVuHuLg4zJ8/Xy4vT09P8Trp7++vMHhDUQWgv7+/wuANf39/cbply5Zy86dNmyYTuFGrVi24uLjAxsYGOTk5iIuLw5MnTxT26FRcN27cwJgxY8RKLz09Pbi6usLJyQnZ2dm4e/euWKFz5coVfPrpp9i5c6fMy7CWlpbiMV3Ydb4k99Zdu3bJ9EpiZGQET09PVK9eHYmJiQgICEBCQgImTZqE7777rtjrAYp+ntra2orpr127hufPnwMAWrdujbp168qkL3gcafNZ7M8//xTvn5IRAUxNTREZGSl3Ti5cuBDbtm0T/65QoQLc3Nxgb2+PzMxMBAcH48mTJxAEAb6+voiJicGGDRsKbTgs6T1WU8+ORfHgwQP8+uuvyM7Ohq2tLby8vGBtbY3IyEjcuHED2dnZyMjIwI8//gh9fX2VQVSauG8U1du3b8UXR6pWrYp69eqhUqVKMDU1RVpaGkJCQvDw4UMIgoBHjx5h6NChOHjwoFo9fRXlGVyV0tivmrwfpKSkYOTIkeLLD/r6+nBxcYGTkxPMzc3F4LpHjx4hPj6+WOVV5X18/jI0NES/fv2wfv16APlBGYUFb+Tm5sr0kqjs3Dxx4gSmTZuG7OxsAICpqSmaNWsGBwcH6OvrIywsDHfu3EFOTg7u3LmDQYMGYd++fahUqZLC/CTHhbGxMerXrw9HR0dYWVlBEATx5an4+HhkZ2dj2bJlAKB2AIe2nmmJiIiIqGxhmw/bfArDNh/1lGb9oYSfnx9+/PFH8W/p79PAwAApKSkICwvDkydPxN+h0rp06YL69evj3r17YscATZs2VTiip6r2gqK0AxSVJuslNMXJyQlDhgxBamoqDh48CCC/J/SPP/5YY+tIT0/HiBEjcO/ePfGzypUro0WLFjA3N0d4eDgCAwPFAKqvv/4ay5cvV+sld121S/7000/YsWOH+Le5uTm8vLzEDjT8/f2RlpaGzMxMLF++HG/evMGsWbNk8pCc/0DR68LVlZ2djXHjxuHGjRviZ/b29mjRogUsLCzE7z4wMBATJkwotNfxwrRu3VocOeXMmTNifW2XLl3k2qqqVKmCjz/+WBx9Xvr7lHwvqmjiGqxIUe6j2qwfvHbtGubMmYPc3FxUr14dbm5usLS0xMuXLxEQEICcnBxkZGTg22+/xZEjR+ReeJZ8t4UdWwBKPPKxxLJly8R7rLOzM1xcXCAIAoKCgvDs2TMA/z1f7d69W+moNHl5eZg4caJMO5+trS08PT1hY2ODqKgo+Pv7Izs7G0lJSZgxYwaSkpIwYsSIEpVfUjdpaGgIJycn1K5dG1ZWVjAwMMDbt29x//59vH79GoIg4K+//kJWVpb4DFOY27dvY/Xq1WJbScuWLVGhQgW8fftWYSeAypTGftXkM3BJ7+0ltW3bNvE5qVatWnB1dYWRkRGePHmCBw8eAMhvjx09ejS2b98OFxcXpXlpui5cQhAETJs2DefPn4eenh6aNGmCevXqQRAEPH36VCOjOPz777+YP38+8vLyULt2bTRt2hQmJiZ4/Pix+Mz08OFDfPfdd9i0aRPWr18vBvQ5OzujYcOGMDAwwP379/H06VMA+e36P//8s8pRMEJCQjB06FDExcWJnzVo0AAuLi7Q09PDw4cP8eTJEwBAUFAQBg8ejO3bt8sFd7m6uqJ27doICwtDYmIi/v33X4UjIEmLi4vD1atXAeQfwyXp7FJb+77YBCIiIiId+/3334UGDRoIDRo0EIYOHar2ctOnTxeXa9KkidCgQQNh6dKlQlpamky6+Ph4Yfjw4WLazp07C3l5eQrzTE1NFXr27CmmHT16tPDixQu5dMnJycKcOXPEdG3atBGSkpKKtuEFXL9+vcjfg6+vr7hMo0aNxGUjIiLk0mZmZorTd+7cEVasWCE8fvxYad5v3rwRpk2bJuY/YsQIpWkjIiLEdB07dlSaTpJGss9atWolXLx4US5dQECA4OHhIaZdtWqV0jzVERcXJ34/Li4uwv79+5UeA69fvxa2bdsm7NmzR+H8q1evCg0bNhQaNGggNG7cWFi/fr3cMScIgvDw4UPBx8dH3IY5c+YozK84+10QZM+bBg0aqL2cunlKzqnp06cL8fHxMunS0tKE7777Tkzr5uYmpKamFprn77//XmgZ1Pk+pNNIyjlo0CAhPDxcJl16erowadIkMW23bt2E+fPnCw0aNBDGjx8vvHnzRiZ9QkKCMGTIEDH9sGHDlJZT+vrTuHFjoUGDBsKUKVOE5ORkuTwnTJggpm3YsKEQGBioMM/c3Fxh2LBhYtpPPvlECAoKkkuXkZEhrFq1SnB2dha//4LbLtGxY0eZa0Tjxo2F3bt3yx3/0teHonjx4oXg5uYmU+awsDC57dq8ebN43jRo0ECYP3++0jylr2vTp08vVrkUkd5nkuvBvHnzhJSUFJl0WVlZQm5uriAIghATEyO0bt1aXO77778XXr9+LZd3bGysMH78eDHdhx9+KOTk5Mil69y5s5jm3LlzhZa5b9++YnpfX1+5+epeP1auXClzvzp16pTCa+Dx48eF5s2bi2mPHTsml+bo0aPi/EmTJilc3/fffy+eG5Jr+fjx4xWmnTlzpphfwetucHCwzHXmwoULSrcxPDxc+OOPP4SzZ88qTaOOhIQEoW3btjLXjfv378ulO3TokODq6iqmGzdunNI8i3udL0xoaKjQtGlTmbyjoqJk0mRmZgoLFy6UuVapKoe69/OinqfS55+iY1maNp7FpO+XjRo1Epo3by6cOXNGLp30tXDv3r3iMh4eHsKePXuErKwsuWWuXbsmc8xs2LBBYRm0cY/V1rElMXToULl73eLFi+XuGVFRUcJnn30mpm3WrJnCfSYI2rlvSN/rFD0DC4IgnD17Vli/fr3cuqSFh4cLo0aNEvOaNWuW0rTFfQZX57moOPtVF/eDrVu3ivN9fHyEkJAQhevMy8sT7t69K8yZM0d49eqVWtujDJ+/8o9T6TIU3PaCLly4IHNdlzzjSHvy5Il4T3N2dhYWL14sJCYmKlz3p59+KnN9VmbOnDnChQsXhPT0dIXzc3JyBF9fX/F60LhxY6XfpyBo/5mWiIiIiDSLbT752ObzH7b5FE4bbT66qj/s06ePmOann35S+H0KgiCkpKQIx48fF5YuXapwflHblwSheO0AgiBbD3b9+vVC89ZUvYQ22tDUPX+Ls4z0ddLFxUXYunWrXF1DaGioTNuGh4eH0jo7bdSZFsWxY8dkzrsZM2bI7c/k5GRh6tSpMulOnTqlNM+i1IUXxerVq8V8nZ2dhbVr18q1Qz1//lzo3bu33PmsrBzqHn/qnB/SinIt0/Q1uDj3UW3XDzZp0kRwc3MTDh48KHevevLkiUz7wowZM5R+V9o6tgRB9hogOXY8PT2FS5cuyaU9e/aszD191KhRSvPdsGGDzPGwbNkyufq7mJgYmXr5Ro0aCXfu3FGYn7r32GXLlgnHjx9XWneal5cnnD17VmjVqpWY340bN5TmJ30ONGrUSHB2dhbWrFkj12ZUcNvUabsozn5VZxlNPwNr6t5eFNLHTuPGjYWmTZsKhw4dkkt38+ZNmfPoww8/VNieJwiarwuXPiYl15wPP/xQePTokVza4tZdF7yeuLu7CydOnJBLd+zYMcHFxUVMu2XLFsHFxUXw9vYW/P395dJv3rxZ5llF2TGamZkp3lsaNGggtG7dWrhy5YpcukuXLgleXl5iur59+yrcD6tWrRLTTJw4sdDt37ZtW6HnvTrnmjbaQUpKc2OIEREREelQVlYWxo0bh6lTp8r1smBra4vly5eLvUNERETI9AgibcuWLWKPCl27dsX69evh6Ogol87S0hJz584Vh22MjY3V2pC+6srJyUGDBg2wceNGhb1pSA8316xZM0yePFlhL+gSFStWxC+//IJ27doByO8VouDw5CW1ZcsWMX9pLVu2lOnh59ixYyVajyQ6GgB8fHzQt29fpZHtlStXxrBhwxT2SpuXl4e5c+eKQwr++uuvGDt2rMKePVxcXLB161YxCnvfvn2Ijo4u0XaUpqysLHz44YdYvHixXC9QZmZmWLRokdiLRlpaGi5cuFD6hUR+OevUqYPNmzfL9URiamqKhQsXiuUPCwvD33//jVatWuH3339HxYoVZdLb2NhgyZIl4rCoAQEBCofnLSg7Oxvt27fHL7/8AktLS7k8f/31V3h6egLIP4aWL1+uMJ/Dhw+LoxC4ubnh77//Vjh0vYmJCSZMmIDx48cDyP/+//zzz0LLmZOTg0WLFmHgwIFyx786w1EqsmbNGrFHt1q1amHz5s1yvbXp6+tj5MiRmD59uvjZjh07EBERUax1akJOTg4GDBiAH3/8UW4oeCMjI7HX/F9//VXszWnYsGFYsmQJKleuLJdfpUqV8Ntvv4k9kTx58kThsMrSPfAcOXJEZRlDQkIQFBQEIP9Y7tatWxG28D8vX74Ue+i2tbXFP//8g27duim8Bvbs2VOmd7fVq1eLPR1JSI5lADI9PEmTjLzh5uYmjqZx48YNubyk0wKQ68lFuvez4cOHqxxevWbNmvjqq6/QqVMnpWnU8ddff+H169cA8s/frVu3okmTJnLpevfuLfYUDgDnz59X+n1oy6pVq8Rh3OvXr48NGzagatWqMmmMjY0xa9YsDBgwQCs93WiDtp/F8vLysHbtWoU9uUiuhSkpKViyZAmA/GvC5s2bMWDAABgZGckt06pVK2zZskUcFeLPP/+UG6q4oPJyj5WWnZ2NwYMHY/r06XL3jKpVq2LDhg1ij1Dp6eky1xJpurpvdOrUCWPHjlXZo2jNmjWxbt06ODs7A8i/TqvTi39RnsF1SdP3g8DAQHH6hx9+UNgjGPDf6EVz585V2gNbcbyvz181a9bEBx98IJbhxIkTKtPv27dPnO7Xr5/CkYEWLFggDnU/Y8YMTJ8+HdbW1grX/eeff6JevXoA8nv5unv3rsL1zp07F+3bt4epqanC+QYGBujXrx8WLlwIIH9/7tq1S+W2SGjjmZaIiIiIyh62+bDNRxW2+ahHF/WHqampYs/j1apVw+zZs5X2jm9hYYGePXti6tSpJV6vIuq2AxSHpuolypPw8HCZ0W5++OEHjBgxQu57rF27NrZs2QIHBwcA+XWta9asKTT/0q4zLbhfevTogUWLFsntT0tLS/zyyy/o3Lmz+NnSpUvF60ZpSE5OxsaNG8W/J0yYgC+//FJsz5SoU6cOtmzZAnt7+3LRHqDta7C691Ft1w9mZ2fjt99+Q58+feTuVfXr15fp7f7kyZPi/U1XsrOzoa+vj7Vr18Lb21tufqdOnbBq1Srx78uXL4sjtUtLSUnBH3/8If49atQoTJkyRa7+zt7eHmvXrkXTpk0B5O+3kl4zp0yZgp49e8qdzxJ6enro1KkT1q1bJ362fft2tfLOycnBN998g6+//lquzags1U1q8hm4LNzbs7OzsXjxYoWj3TRv3hybNm0Sv/8nT57g0KFDCvPRRl24RE5ODuzt7fHXX3+J7UzSNHF8ZGdnY/Xq1QpHtPLx8UG/fv3Ev3/++WcYGRlh69atMu37EiNHjhTbGvLy8pS2NRw5cgSPHj0CkP/89Oeff4rLSfP29saGDRtgaGgIIH8EDkXP/H369BGnz58/L46oqIz0OxXqjHakjDb3fXExeIOIiIjeCXZ2duIPZUUqVaok89Knoor87OxscRhPY2NjzJs3r9CKu8mTJ4s/sgt7Ebc0TJ06VekLMsUl+aEGQByOThMGDRqEhg0bKp3fp08f8cE+NDQUKSkpxV6X9LJ2dnbFzufcuXMICwsDkD8srKLhrqXZ29uLw3pmZ2cX+nJVWWJkZIQZM2YonW9iYoJevXqJfytrHCsNU6dOFRvqCrK0tJR74XvmzJlKz20HBwe4u7sDyB/aUjLMpip6enqYPXu20jwNDQ0xe/Zs8e+bN2+Kw59K27p1qzg9b968Qs/lsWPHij8ojx07VmhFsaura4l+0BaUlJSE48ePi39PmzZN5VD3w4cPR/369QHkVwDs2bNHY2UpKhMTE0ybNk1lmri4OBw+fBhA/rlcWHoDAwNMnjxZ/FuyrDTp7//cuXMqr2vSy3fu3FlpBWNhtm3bhtzcXADA119/rbBiTlqrVq3EytiQkBC5oaPt7e3FF3Tfvn0rDqkqERERgVevXgHID/Tw8vICACQkJODx48cyaV+9eiW+jF29enW5ACxNXbvVJQiCzHH59ddfq3zRuGvXrjKN0aXZoJ+UlITTp0+Lf0+bNk3lEOHTpk1Tep0sS0rjWax79+5iUJEyvr6+SEpKAgB89tlnaNasmcr0Tk5O+PjjjwHkH+uXLl1Smb483WMlLCwsVFa2W1hYyFwnT548KVfhWh7uG0ZGRuKQy5mZmTIBCqpo4xlc0zR9Pyjta3RB7+vzFwCZF46kgzMKiouLw/nz5wHkB0V98skncmkePXqE69evAwAaNWok/nZRxtzcHF9//bX4d0l/A3fv3l28Pylq5FVEG98pEREREZU9bPPJxzYfxdjmUzhd1R9K7xtbW1ulQTWlQZ12gOLSVL1EebJnzx6xHsTFxQWfffaZ0rQ2NjYydYlHjx4t9OXM0q4zvXz5Ml6+fCmue/bs2UqPVz09PcyZM0d8UTs8PBxXrlwp0fqL4siRI2KHQVWrVsXYsWOVprWzs8OkSZNKq2glUhrXYHXuo9quH+zQoYPCwEaJ9u3bw97eHkB+QIimAyuL46OPPoKHh4fS+R988IFMp3N79+6VS3PkyBGxI6dKlSrhm2++UZqfsbExfvzxR/Fvf3//UrlmNmvWDE5OTgDUr5usXLkyxowZo81ilZimn4HLwr29RYsW8PHxUTq/fv36GDJkiPi3omOyNOrCv/76a622l3Tq1Elh4ISE9H0SyH8+lxzjhaW/f/++wjTSgZuDBw9WGNwm4erqKtN+oajtvGbNmuL7OFlZWTh58qTS/F68eCEGTpiYmCgMWlGHrttBlGHwBhEREb0TOnbsKPZ4rIz0Q2RkZKTc/AcPHog9rLdu3VquV35FqlSpIr7E+vTp00IrnrTJxsZGYe8HhUlPT8e1a9fw119/4ddff8WCBQvw008/if+ko6ElEfWaUNiDtaWlpfgiryAICveZuqRfvj1z5oy4n4vq33//Fac//PBDtZaR7kle3RcA1TFx4kQ8fvxY/KdpzZs3FyuKlCnsnCoNpqamKnvjByDT21itWrVUNiABEF8UBSBW3Kri7u5e6AuQzs7OMt+XpAcXiZiYGPH8qlevXqFlBPJ/oLq5uQHI73XnyZMnKtMX/LFeUrdv30ZWVhYAoEKFCujYsaPK9Pr6+ujfv7/4d8HvoDS1adMGNjY2KtNcvXpV7Jmoa9euhd5jgPxKPkkD161bt+Tm165dG66urgDyr71+fn5K8zp69Kg4XZIXFC9evChOS15ILkxh1y3p3jkK7kfpv728vGTSSipFJKRH3VD0Mr10L3CHDh0qdDSDkgoJCRFH2zEwMJDp+UMZ6Qoo6e3RNunzr2LFimjbtq3K9DY2NiUelaQ0lMazmDrXQm3f78vLPVZap06dVAZaAPmNTJJK6czMTNy+fVtmflm5byQlJeHff//F5s2bsWLFCrlnX+mGV3WefYv7DF7aNH0/kL5G66I32vf1+QvIb8yWXB/v3LmDZ8+eKUx38OBB8VnG29tbrndVQPa46NWrl1oNb0X9ffPo0SMcOHAAq1evxuLFi2XOt4ULF4rrfPLkiVq9VmrjOyUiIiKisodtPmzzUYVtPoXTVf1hhQoVxHP36dOnGv2OikqddoDi0kS9RHkjXb+varQbia5du4ojaGRlZcnVFRZU2nWm0tsj/fK8MlWqVJG5Jpfm/pRel4+PT6G9t/v4+CgcRbqs0fY1WJ37aGnUDxZ2f9TT05Pppb8stAdIOqtSN42i80H6HOvVq1ehQTGurq4ybfqaOsdCQ0Nx5MgRrFmzBkuWLMH8+fNlnoskz3oJCQmIiooqNL/u3buLwahllaafgcvCvb2ox+T9+/fF4CGJ0qgLVxVgogndu3dXOb/giB+FpZc+5xS9F5OSkiLT2amiDqIKkm47V7QfANl3H1QFRkjP69ChQ6HtlMqUxr4vjrJ9JSEiIiJSk6qhoCWkh1hV1KPPnTt3xOno6GiZISpVkfTMLAgCoqOji/3AWFINGzaUGx5VlYSEBPz+++84ePAgUlNT1VomPj6+uMWTo4l9pq5mzZqhWrVqiIqKwqtXr9CrVy/069cPnTp1gqurq9pDFEpXLJ4+fRo3btwodBnpH7bq/OAvK0pz/5RE7dq1C62AlK6clwxvqG56dbZLUkGnTjpJr9UFG8Wkrz8ZGRlqX3/Cw8PF6ejoaJWVio0bN1YrT3VJ98Dt6uqqVkWVdC8tDx8+hCAIOumdQ53vQnqfPH78WO19IpGYmIi0tDS53sp69+4t9gh1+PBhhZVNgYGBYgWJnZ1dsV8Kjo+PF3stMjIywurVq9VaTvolUEXXLS8vL+zatQtAfuXp0KFDxXmSAAYTExO4u7vD0NAQ1tbWSEpKgr+/Pz7//HMxrXTFq6LhWtu3bw9zc3OkpaUhKCgIPXv2xCeffIL27dujUaNGRbrnqUP6mK5Tpw4qVKhQ6DLSx3RsbCxev36NKlWqaLRcihQ8/wrrMQfIvwZJBwWVRaXxLKbO+S99v9+zZw8OHjxY6DLSQ7QXdr8vL/dYaZJecFQxMDBA06ZNxUrQ4OBgmR7FdH3fiI6OxrJly3Dq1Cnx5YXCqPPsW9RncF3Qxv2gZ8+e8PX1BQDs2rULQUFB6Nu3L7y9vVGrVi3NFFyF9/X5C8jfh3379sWff/4JIH/0DUU9U0qPyiHdYCJN+nrn7+8vjp6liiAI4rSq692BAwewbt068dgrTHZ2NpKTkwt9sUYb3ykRERERlT1s82Gbjyps8ymcruoPjY2N0aVLFxw7dgw5OTkYMWIEfHx8xNFwJb3VlwZt/n7URL1EeSIIAh49eiT+rU5doZGREZo2bSqOUvzw4UOVow+Udp2p9P5QZ3uA/LpKySinBUep1Sbpsqpz7FlaWqJBgwYICgrSYqlKTtvXYHXuo6VRP1jwZWpFylJ7gJ6entgRnSrS582bN28QExODypUri58V9xyTBMOU9By7cOECfvvttyLlEx8fLxMgqkiTJk1KVK7SoOln4LJwb1fn2ufs7Cy2K+fm5uLx48cyx54268IBoEaNGjLnsjYUdq8suC+kOy1VpLD3Yh4/fiyO6G5ubq7W9czFxUVmPzx69EhuJJ+ePXti0aJFyM7Oxo0bNxAdHa2w8ynp4A11Ol1URtv7vrgYvEFERETvBHUqz6VfEMvJyZGbHxMTI04Xt2ebxMTEIi+jKUUZfi8yMhJDhw5V66FUmroV/upQZ59Jv5SvaJ+py8jICL/88gvGjRuHtLQ0xMfHY9OmTdi0aRNMTEzQpEkTtGzZEu3atYOHh4fSlwKlj5Hjx48XuRySH7zlgSbOqdKgTjmlK+a0sV3Vq1cvNA0g2xtYXFyczDzpY+vly5fiUKZFUdj1R9NDdEpvg7rfgYODgzidnZ2N1NRUWFpaarRc6lDnu5DeJ4GBgcXqUSEpKUkueKNXr15YvHgxcnJycP36dcTGxsr16CRdEdGrV69i9+AiGUUCkB0itygUXbekAy1u3Lgh8zK1pHK9WbNmYiNpixYtcO7cOQQGBiIvL09sKJQeqcLLy0tuPRUqVMCCBQswffp0ZGdnIyoqCqtWrcKqVatgbm6OZs2aoWXLlujUqRNcXFyKvG0FFeeYrlSpEkxMTJCZmQkgv2K3NII3pMtaWEVyUdPpUmk8ixV2/qempso87ygaWrkwhd3vy8s9VlpxjrOC9zpd3jcePnyIzz//vMjP6uo8+2pzCGxN0cb9oG3bthg2bBj+/vtvAPk9KEmG1a5UqRKaN28OT09PdOnSRWGle0m9r89fEgMHDsSmTZsgCAIOHTqEKVOmyPx2un37NkJCQgDk7w9lI91IfwfSvR2qS9H1ThAEzJo1C/v37y9yfqmpqYUGb5SHc46IiIiISo5tPmzzKSwftvmopsv6w5kzZyIoKAhhYWHIzs7GoUOHcOjQIejr66NevXpo0aIF2rRpg3bt2qkdaFMc2vz9qIl6ifIkOTlZHN0TkK2zU0U6XWHBYqVdZ1qcusoaNWqI05oMfitMcc/nsh68oe1rcFHbArVVP6hOfbam7o+aYGNjo1aZ7ezsZNrH4uLiZII3pI9bbVwzVFm1apXaHRhJU+e5SJ2O33RNG8/Aur63q3Pt09PTQ9WqVfH8+XMAqtsDNFUXLq006q0LOzcLvlNQ2L1V+j0aRdce6fOwWrVqanWupq+vL7MfFJ3LFSpUQNu2bXHu3Dnk5eXh6NGjGD16tEyae/fuiR1D2draqgwALYy2931xFR5aTURERFQOaKLndk0Mfy2JOtaFwoaalDZlyhSxEt/CwgKff/45/vzzT/j5+eH27dsIDg4Wf8ht27ZNXE46urikSru3fU9PT7GXe+nvKjMzE4GBgVi3bh0+++wz9OjRA35+fgrzKGlPF7o8PopKF6MhFEdRy6mN7VL33JN+ib9g5U9pXH8kw5lqivQQl2ZmZmotUzCdJhsHi0KdfaaJfaKokkN6JI3c3FwcO3ZMZn52djZOnDgh/i09bGhRaeu4qlSpEpycnADkV7hIKv0iIiLEe4t0MIZkOjExUexp59WrV+LoItWrV0fNmjUVrr9Xr17Yu3cvunbtKlN5nZaWhmvXruH333/Hxx9/jH79+uHmzZsl2tbiHNMF05bWMS1d1uJcg8qq0rgWFvZ9aaJXq8LKUF7usdLUPSdU3et0dd/IysrCxIkTxcYGOzs7fPXVV9i2bRsuXryIO3fu4NGjR+Kz788//ywuq86zb1GewXVFW+fW7NmzsXr1arme2N68eYNTp05h/vz56NChAyZNmlTkF4gK874+f0nUqlVLvL/GxcXh3LlzMvOlR93o06eP0pHqtPH7Zs+ePTKBG23btsWSJUtw5MgR3LhxA/fv3xfPt8ePH8s0yubl5RW6Tm19p0RERERUtrDNh20+hWGbj2q6rD+0t7eHr68vvvrqK1SqVEn8PC8vD0+ePME///yD8ePHw9vbGxs2bNDa96jNOhtN1EuUJ9LHE6CZusKCSvsaIr1N6h77umgLADRTr1oWafsaXFptge9ae0BRrp2qzoniHLeauGZeuXJFJnDD3d0d8+fPx8GDB3H9+nW5uknpDuvUqZt8X9sDdH1vL861r+AxVBauOSVV2u/GSH+Hmm47lx5J4/Dhw3LzpT/z8fFR2sahjrL6zM+RN4iIiIj+n/QD5LBhwzB79mwdlkZ7bt26JQ4LZ25ujj179qBevXpK05fnysSCatasiSVLlmDOnDliT/q3bt3C3bt3kZGRAQAICwvD+PHjMWPGDIwcOVJmeTMzM/HH7oEDB9CoUaNS34Z3nTqVImWN5NgpjHQllYWFhcw86etPp06dsHbtWs0UToukK9DS09PVWqZguoLfQ1kivU9mzpyJzz//XGN59+7dGxcuXACQX/EgnfelS5eQkJAAAKhTp45aQxMrI72PLC0tizV6iDKenp5ij97+/v5o2LAhrl+/Ls5v1aqVOC0dyOHv74/GjRvD399fJi9VXFxcsHr1aiQlJeHGjRvitfvBgwdib19BQUEYPnw4li9fjp49exZrm4pzTBdMW1rHtHRZi3MNKqvKwrNYwcrHgICAQnuBfx+oe06outfp6r5x6tQpMVisSpUq2Ldvn0wPYAW9S8++Etq8H3Tt2hVdu3bFq1evEBAQgFu3biEwMBDPnj0DkP8i0KlTp+Dv749du3ahTp06Glnv+/r8JW3gwIHivXffvn3o3r07gPxjWLq3wgEDBijNQ/o7WL16Nbp27Vricm3evFmcnjhxIiZMmKAy/bt4zhERERFR2VAW6hlKA9t82OajiK7rDy0tLfHtt99i4sSJePDgAW7evCnWGUh6YE5MTMTy5ctx584drFmzply94KyJeoni0FUbWsHghvT0dLUCHjS9/ZokXX51j31dtAUA+WWVXKuKW69aFpWFa3B5rx/UBnWvb4Dqc6I4x60mrhmbNm0Sp/v374+FCxeqvL+8S89FEtp6BtblvT09PV2tEWFUHZPaqAt/10l/h5puO+/UqROsrKyQnJyMx48f48mTJ2jQoAGA/GAJ6TaOknR2CZTdfc+RN4iIiIj+n3SE+Js3b3RYEu26du2aON23b1+VlfgANN5Lbllgbm6Otm3b4ttvv8W2bdvg7++P3377TfwxAADLly/H69evZZarWLGiOB0bG1tq5S3PijqEsSZ6PC9t6p4j0dHR4nTBIVXL4/VHeujPqKgotZaJjIwUp42MjMpcZb006X2i6fO9c+fO4rYHBQWJQRCAbC8SJa2IkL5mpaSkaLSyXjrgQhKIERAQACC/ZxHpoBNnZ2fx5feCaQvmpYq1tTU6d+6M77//Hrt27cL169fx888/i0Oa5+bmYt68eUWqWJZWnGP67du34pDQQOkNl1ycskpfg8qqsnAttLa2lhnSubxck7WtOMdZwfNBV/cN6WffESNGqAzcAN7NZ19t3g8kqlevjo8//hg//fQTjh07hgsXLmDixIlipXhCQgIWL16ssfW9r89f0rp27Spu0+XLl8VtPXHihNjQ2aJFC5UBM5p+3omKihKHMre2tsa4ceNUpk9JSRFHxSEiIiIi0rTy/syvLrb5sM1HkbJSf2hgYIBmzZrhiy++wJo1a3D16lXs2LEDnTp1EtOcPXsWp06d0vi6tUkT9RJA+WlDs7KykunxWt3tl67bK626c3UV5xyRdBADlO72FKes6qbTpbJwDX5fnhWKIjExUa2Ahri4OJXtY9LHbWldM3Jzc8X2R319fUyZMqXQ4IF38blI28e1Lu7t6lzTBEGQedZT1R7wrj33aYv0dxgdHa3WqH15eXmFPv8AgLGxsdghFSD7jsTly5fx9u1bAPmjkLu7uxe57NLK6r5n8AYRERHR/5N+0fT27dsaHS5aHaXVo0xMTIw4LV1xrcyNGze0WZwywdTUFD169MDff/8tPrhnZ2fj0qVLMumaNWsmTt+6dUsj6y5PPQkVh3QPCJLRBFR5/PixFkujHXfv3lUr3Z07d8Tpgr3HSB9bwcHB5aKHfOltuHfvnlrDRUp6gJMsX5aPf+l7gqbOdwlTU1N069ZN/PvIkSMA8htezp8/DyD/2vDRRx+VaD2VK1dGtWrVxL+lv/+Skh5N4+bNm8jLyxPvF+7u7jIvv+vr66Nly5Zi2tzc3CKNvKGMpaUl+vXrh7/++ktcX3x8fLG3U/qYfv78uVrXLOljw97eHlWqVCnWuotKuqz3799Xq8c1Te5/bdH1s5iicmj6/Nek0ryGSt/DlMnNzcX9+/fFvwve63R13yhvz77a2K/avB8oU61aNUyYMAE//fST+NmVK1eQlZWlkfzf1+cvacbGxujbty+A/AaR/fv3A8gfhUPik08+UZmHpq930udb3bp1Cx3KPDAwUGfXeiIiIiJ69+m6noFtPrrDNp+yW3+or6+PFi1a4I8//kCbNm3Ez8+dOyeXtqx8l4pool4C0E4bmja+Nz09PTRs2FD8W51jJScnR2Vdoa65uLiI0+oe+wXrKkuLdFnVqadNTU3F06dPtVgizdDGNbgkZSjr9YOldU0UBAH37t0rNJ30sVipUiW59jFdnGPx8fHIzs4GkB8cJB0gpMizZ8/EESN0RRv7tbSfgYtyby8uda59T548EQOPDAwMZO5bQPlp+ytLnJ2dYWBgACD/3qLOc8ijR4/Ea6mi/SBNuiPLY8eOiceq5N0JACV+XwIou/uewRtERERE/6958+awtrYGkB81rMkfE+owMTERpyU/KrVBX/+/R8DCeid//fo1zp49q7WylDW2trbw8PAQ/5ZEc0t06NBBnPb19ZXpTaK4Smu/64qDg4M4/ejRo0LTnzx5UpvF0Ypbt24hIiJCZZqnT58iKChI/Lvgy+o1a9aEk5MTgPzjQPqlu7JK+gX9uLg4XLhwQWX6vLw8+Pr6in+3atVKm8UrsbZt24q9Xt2+fVut47copCsjJBUQp0+fFq/L7u7uqFmzZonXI33d+ueff0qcn0TFihXFYzYxMRGnT58Wez2RDuyQkBzzKSkpOHPmjNh7joODQ4m309HREfXr1xf/LnjtVpeTkxPs7e0B5L+ELt3DhzLS56qi7dYW6fPvzZs3uHz5ssr0ycnJpf5cUxy6fhaTkD5vdu7cWWZfLC7NZ4hz584V2rPfpUuXxPPPxMREriccXd03ivLs++DBA5lGZV3Q1n7V1v2gMNK9bWVnZ6v1IoI63tfnr4IGDhwoTu/fvx/Pnj0TGzmtrKzQo0cPlct37NhRnD5z5kyJe2KTbmxUZ4SXnTt3lmh9RERERESq6LqegW0+uvc+t/mU9fpDPT09md+kiup0pTsIUmdUitKkiXoJQDttaNo6BqXr5g4ePFhonamfn59YD6SorlDXpLfn4sWLhbYrvH79WiYArDTbuKTbHk6cOFHofj1+/LjGOlDRJm1cg4uqPNUPluY18dChQ4WmOXjwoDitqH1M+hw5duxYofv3/v37Mi+GF6fNrSjPREDZqJvUxn7V1TOwOvf24lKnzVb6mGzatCnMzc1l5mu6Lvx9YGlpiSZNmoh/HzhwoNBlpK+jrq6ucvtBmqenp9jx2KtXr3Djxg2kpaXJ/F6RfqeiuMrqvmfwBhEREdH/MzY2xogRI8S/582bJzeEsiolfcCztbUVp6V7StI06ZdkVVXS5+bm4scff3wnAgqK0mOC9JCL0sN5AkD37t1Rq1YtAPnD6c2dO1ftFzpTU1MV9tZRWvtdV5o2bSq+xHX37l2EhIQoTbtjx45y0RNMQYIgYOHChUqPhdzcXCxYsED8u3nz5mJFoLQxY8aI0ytXrizSKCS6GN7R2toaPj4+4t+//PKLyhd7t2/fjidPngDIrzyTftmwLKpSpYpYGSAIAr7//nu1hyTPy8tDXFycyjStWrUSe6F5+fIlbt26JdOLRJ8+fYpZclmjRo0Se8Q4c+aM2Cu3Ogo7rqQrTtesWaPw88LSqhp1o7DvUCI3N1fm+llYTzrK6OnpyRyXa9asUfkccPbsWZmXzwcPHlys9RaHtbW1zOgtS5cuVVkRvXTp0jLdY5SErp/FJAYPHixWbAcFBWH16tVqLxsXF6fWiBKaUJrPECkpKVixYoXS+WlpaVi6dKn4d/fu3WFlZSWTRlf3DelnX1WNFOnp6fjxxx+LtQ5N0tZ+1fT9QN1rtPTw2Pr6+jLbVxLv6/NXQXXq1BHvpREREZg1a5Y4r1evXjAzM1O5vKurq7h8RkYGvv/+e7Ub97OyspCYmCjzWY0aNcRn/6dPn6p8keX48ePiiGNERERERNqg63oGtvloD9t8Cqer+sOUlBS1f1eq2jcAUKFCBXG6KOduadBUvYQ22tCsra3FF5ile6EvqYEDB4r5BgUFYffu3UrTJiUlydQV9urVS66uUNe8vb1Ro0YNAPl1HIsWLVKaVhAELFiwQPwuHR0d8cEHH5RKOYH8XscldTxRUVHYuHGj0rTx8fH4/fffS6toJaKNa3BxlJf6Qen7i7aviYcPH1Y5wtD169dx+vRp8e8BAwbIpfnoo4/El7ZjY2NVtrNkZWXJXDO9vLxQt27dIpfb1tZWvNYkJycjICBAadrAwMAyEbyhjf2q6WdgTd7biysgIEBlAGNISAh27Ngh/q1oRGpN14W/LwYNGiRO79ixQ2Ww6YMHD2SeDwprO9fT05MZWePIkSPw8/MTr+9ubm7ifaIkyuq+Z/AGERERkZSRI0eKvXe/fv0a/fv3x4kTJ5QOJxwXF4fdu3ejb9++2LRpU4nWXaNGDbHiJTIyUq3hKIujffv2YkVgQEAAlixZIldhGxsbi4kTJ+LChQsqI6HLi+3bt6NPnz74559/lFaipKam4tdffxV7WzYwMIC3t7dMGgMDA8ydO1d88W3//v0YO3asysrU4OBgLF26FB06dMDLly/l5hd3v69atQrOzs7iv7LK3t5e7FlDEAR89913Mi/xAfm9SGzevBkLFy6U6V2ivDAyMsL58+cxY8YMuZdQExMT8d133+H69esA8n+Afvfddwrz6d27t/hdpaam4rPPPsOuXbuU/nBMSUnB4cOHMWzYMMyfP1+DW6S+8ePHi9eIsLAwjB49Wu4lvby8PPz1119YvHix+NmQIUPESvGy7NtvvxVHYnj8+DE++eQTlT2URUdHY+vWrejRoweOHz+uMm99fX306tVL/HvTpk3icWJkZISePXtqYAvyGxG++uor8e9Zs2ZhyZIlSl+6zcnJweXLlzFt2jT07dtXZd7SgReSF6zNzc3RtGlTubTOzs5iBaQkbcE8Clq6dCmGDBmCgwcPIikpSWGa+Ph4zJ49W7y2W1palqgHrxEjRohBNQkJCRgxYgSCg4Pl0h07dgxTpkwR/+7YsSNatmxZ7PUWx/jx48Vr5pMnTzB27Fi5ytesrCwsWbIEu3fvhpGRUamWr7h0+SwmYWVlhZkzZ4p/r169GtOnT8erV68UphcEAYGBgZg7dy46duyoVo9OmlBaz45A/nVpx44dWLZsmdx96fXr1xg3bhyePXsGADA1NcWECRMU5qOL+4Z0jzoHDhzA5s2b5QJsXrx4gVGjRiEoKEjnz77a2q+avh8MHjwYU6ZMwcWLF5U+q4SGhmL69Oni361bt9bYs977/PxVkHTjqHSjqqJGU0X+97//icf9lStXMHToUJWNs6GhoVizZg06deokN8S4nZ0d3NzcAOSfy5MmTcLz589l0uTl5WHHjh34/vvvYWBgINMjKBERERGRprHNJx/bfN7PNh9d1B8GBQWhU6dOWLVqlVhXVFBubi6OHz+O7du3i5+1a9dOLp30aMuXL19GcnJyicunKZqql9BGG5qxsbH4omN2djb8/PyKvH2KODo6yrzAOX/+fOzYsUPueiqpZ5OcH5aWlhg/frxGyqBJ+vr6MnX8R48exezZs5GamiqTLiUlBTNnzpR5UX3atGkyPfxrm5WVFUaPHi3+/fvvv2PDhg1ydZxhYWEYNWoUYmJiykV7gDauwcVRXuoHGzRoIE6fPXtWa6OrGBkZITc3F+PGjcPVq1fl5l+4cAETJkwQA23atGmD1q1by6WztLTE119/Lf69YcMGrFy5Uq7cb968wddff407d+4AAAwNDWXOzaLQ19dH+/btxb9nzJih8D58/PhxjB07Frm5uTp/LtLWftXkM7Am7+3FZWRkhOnTp+Po0aNy827fvo0vvvhCHN2lfv36SjtJ1GRd+Pvio48+QsOGDQHkP1eMHj1afMaRdvXqVYwZM0YcQaZx48Yy70IoIz2yxqlTp+Dr66twXkmVxX1vqJVciYiIiMopCwsLrF27Fp9//jlevnyJ2NhYfPvtt6hQoQLc3NxQqVIlCIKAxMREPHv2DC9evBB/4JR0eFQDAwN07txZ/MExfPhwtG3bFtWqVRMrLWxsbPDll1+WaD1OTk7o06ePOGzg5s2bceTIETRt2hQVK1ZEZGQkbty4gezsbFhYWOD777/HnDlzSrTOsuDRo0eYN28efvrpJzg6OqJ+/fqoUKECcnJyEBsbi1u3bsn00DFmzBhxiD5pH3zwAebOnYu5c+ciNzcX//77Ly5duoR69erB2dkZFhYWyMjIQGxsLB49elRor8Sltd91afLkyfD390deXh4ePXqE7t27i6MOJCQk4ObNm3j79i3Mzc0xZcqUMvMinLrGjRuHbdu24eDBgzhz5gxatWqFihUrIjY2Fv7+/jLH1bhx49CiRQuF+RgYGGDlypUYNWoUHj58iJSUFMyZMwdLly6Fm5sbqlSpAgMDAyQmJiI0NBTPnz8Xf/x27969VLa1IEdHRyxcuBBTp05Fbm4ubt++jR49eqB58+ZwdHREWloabt68KdMg5ObmhmnTpumkvEVVpUoV/PHHHxg7dizi4+MRGhqKL774AlWqVIGrqyvs7OyQnZ2N+Ph4PH36tMgVxX369MHmzZsBQKYBpUOHDrCxsdHYdkyYMAGRkZE4cOAABEHA5s2b8ffff6NJkyZwdHSEqakpUlNTERkZicePH4vHbGG9oysaYcPDw0Nho4Cenh48PT1lGjgA1cEbgiDg5s2buHnzJgwMDFC3bl3UrVsXNjY2yMjIwOvXr3Hr1i2ZnsOmT58OU1NTleVWxcbGBsuXL8eYMWOQnp6O0NBQ9O3bF82aNYOTkxOys7Nx9+5dvHjxQlymdu3aKnvl0pa6detixowZ+OmnnwAA/v7+6Ny5M7y8vFC9enUkJibC398fCQkJMDIywuTJk/HLL7+UejmLSpfPYtL69euHiIgI/PHHHwDyh1s+cuQIGjZsiLp168Lc3BxpaWl4/fo1goODddJ4XJrPEN9++y1WrlyJjRs3Yt++ffD09ISNjQ1evXoFf39/mfNw1qxZSnvC0cV9w9vbGy1btsSNGzcgCAKWLFmCHTt2oHHjxrC0tMSLFy9w+/Zt5ObmokqVKhg+fLhMz4ClTZv7VZP3g5ycHBw9ehRHjx6FqakpnJ2dUbNmTVhYWCApKQkRERF48OCBmN7U1BTff/99Mb4Rxd7n56+CevTogYULFyIhIUH8zMXFRWY4c1UaNGiAFStWYPLkyUhPT8fdu3cxcOBAODo6olGjRrCxsUFWVhbevn2Lx48fF9pL2zfffINRo0YhLy8PDx8+RO/eveHu7o6aNWuK57jk5arJkydjz549iIyMLPb2ExERERGpwjYftvlIvI9tPrqqP5T0sL569WrY29ujYcOGsLe3h4GBAd68eYOgoCCZUUlatGih8OU+V1dXVKtWDVFRUYiNjUXPnj3Rpk0bVKhQQQxYatq0qcxIr6VFU/USgHba0Lp3745169YByA80OHDgABwdHWXq7qU73FDX9OnT8eDBA9y/fx85OTn46aefsGHDBjRv3hzm5uYIDw/HzZs3xaACQ0NDLFy4sMx25uXj44ObN2+KvbXv3bsXx48fh5eXFypVqoS3b9/i2rVrMvtzxIgRMqPalJaxY8fiypUruHXrFgRBwPLly7Ft2zZ4enrC3NwcL168QGBgIHJzc9GsWTPUrFlT4UvOZY2mr8HFUV7qB9u1awdTU1NkZGQgODgYPj4+8PT0hLW1tXhNbNOmjVygYlFVrlwZXbp0wV9//YWRI0eiYcOGcHFxgSAICAoKkhkByN7eXuU16YsvvkBgYKA4+u7atWuxc+dOeHl5wcbGBlFRUfD395cJWJg2bRqaNWtW7PJ/9dVX8PPzQ0ZGBiIjIzFw4EC4ubmhTp06yMrKwp07d8T23IEDByIsLEzlCB3apq39qulnYE3d24tr2rRpWLRoEaZMmYJVq1bB1dUVhoaGePr0qRioC+R3Mrh48WKlwY6argt/HxgbG2PFihUYOnQo4uLiEBsbixEjRojXBiA/sE56RI6KFSti+fLlagUS1q9fHy4uLggODkZiYqJWOrsEyua+Z/AGERERUQE1a9aEr68v5syZg1OnTkEQBMTHx4s/KhWxtraWiYovru+++w7+/v6IjY1Fenq63EuuDg4OGqnQnTt3Lt68eSP2IB8bG4tz587JpKlatSpWrFghVj6UZxYWFuK0IAh48eKFzIu30oyMjPDll18q7TEagPgQP2fOHISFhUEQBDx9+lTlcMX169dX+jJ2ae13XWnWrBnmz5+PH3/8Ebm5ucjIyMCFCxdk0tjb22PlypVyvcSUBw4ODli/fj0mTZqE2NhYhUPTGxgYYMyYMZg8ebLKvCpUqICdO3fi559/xr59+5CTk4OUlBSVoz2YmpqicePGJd6O4vLx8YGZmRlmz56NN2/eICcnB/7+/vD395dL++GHH2LBggXlqodlV1dX+Pr64ocffsC1a9cA5PdQcubMGaXLVKpUSa0hPBs2bIgGDRrIjEQBaLYXCSA/cGLx4sVo3LgxVq1ahcTERGRnZ+P27du4ffu20mU8PDxU5mtnZ4d69erJ9LKiKKBDomDwhoODg8pGG+lrd25ursrrrIWFBWbMmIGBAweqLLM6WrZsia1bt2Lq1KmIiIiAIAi4c+eO2OuPtA8++ADLly/X6NC/RTFkyBDk5eXhl19+QVZWFrKzs+WuF1ZWVliyZAksLS11Usbi0OWzmLRvvvkG9evXx88//4yYmBjk5uYiKCgIQUFBSpdxdXUt1V7NSusZomnTpli5ciWmT5+O+Ph4nDp1Si6NiYkJZsyYIdMDnyK6uG+sXLkSY8eOFffdy5cv5QLu6tWrh99++02rI5ioS1v7VZP3A+lrdEZGBu7evau0l6IaNWpg6dKlYu9MmvC+P39JMzY2Rp8+ffDXX3+Jn6k76oZEx44dsWvXLsyaNUs8T8LDwxEeHq50GQcHB1StWlXu89atW+PHH3/EggULkJOTg+zsbAQEBMg0gurr6+Orr77CuHHjsGfPniKVlYiIiIioqNjmk49tPu9nm09p1x+amprC0NBQPM5iY2OVjo4C5L/4vGjRIoWjGOjr62POnDmYOHEisrOzERsbKwYpSfTt21cnwRuarJfQRhva6NGjcfr0aTx//hzZ2dm4ePGiXJriBG+YmZnhr7/+wg8//IATJ04AyB+R/NixY3Jp7e3tsXDhQple8MuiH3/8EZUqVcLatWuRlZWF1NRUuesnkF/3OX78eIwbN04Hpcyv/9m4cSO+/fZbXLp0CUD++VXwu3d3d8fvv/+OFStW6KKYxaLpa3BxlIf6QSsrK8yYMQPz5s2DIAiIiIiQG9Xa3Ny8xMEbQP6L8qmpqdi3bx8ePXok81K2RJ06dbBmzRo4ODgozUdfXx+rV6/Gzz//jJ07dyI3NxcJCQkK2xesrKwwa9Ys9OvXr0Rlr1evHpYvX46pU6ciPT0dgiAorP8eNGgQZs+ejS+++KJE6yspbe5XTT0Da/LeXlwjRoxAQkIC1q5di7CwMISFhcmlqVy5MlauXFlop0aarAt/Xzg5OeGff/7Bd999h4cPHwKA0mtD48aNsXLlSjg6Oqqdf+/evREcHCzzmbe3t8bb38vavmfwBhEREZECtra2+O233/DkyRMcO3YM/v7+ePnyJRISEqCvrw9ra2sxAveDDz5AmzZtNPIysoODAw4dOoTt27fjypUrCAsLQ2pqqsYr083MzLBx40YcOXIEBw8exMOHD5GamgpbW1vUrFkT3bt3R9++fWFjY6PwRbryZtSoUejWrRuuXr2K27dv4/Hjx4iMjERqair09PRgbW2NunXrolWrVvj4449VVjJItGrVCsePH4efnx8uXLiAu3fv4s2bN0hJSYGpqSkqVaqEunXrwt3dHe3atROjzhUprf2uS5988gnc3NywZcsWXL9+HbGxsTAxMUGNGjXQrVs3DBo0CHZ2duX2ePPw8MDhw4exe/dunDlzBpGRkUhLS0PlypXRqlUrfPbZZ2pX4JmammLevHkYM2YMDh8+jOvXryMsLAwJCQnIy8uDlZUVatasiYYNG6JVq1Zo166dzl/K7tixI06fPg1fX19cuHABT58+RXx8PExNTVG5cmV4eXnh448/LlFPKbrk4OCArVu34vbt2zh58iRu3LiB6OhoJCUlwcDAALa2tqhVqxaaNGkCb29veHp6wtBQvZ/bvXv3xrJly8S/ra2t0aFDB61sx7Bhw9C3b18cOnQIV69eFXspysrKgoWFBapUqYL69evD09MT7du3V9gTXUFeXl4ywRuqRtIoGNihKi2QP3zpZ599hqtXr+LOnTt49uwZoqKikJqaKn7v9evXR5s2bdCnTx9UrFix0PKqy83NDcePH8fhw4fh5+eHR48e4e3btzA0NIS9vT2aN2+OXr16aaQSvKSGDRsGb29v7NixA5cuXUJ0dDSMjY1RtWpVdOzYEYMHD0b16tXL3fVVV89iBfn4+KBLly44duwYLl++jPv37yMuLg5paWkwMzNDlSpV4OTkhObNm6N9+/aoU6eOxsugSmk+Q3Tp0gWHDx/Grl27cOHCBURFRSE7OxtVq1ZF27ZtMXToUNSuXVutvEr7vlGpUiXs2rULe/fuxbFjx/D06VOkp6ejYsWKqFOnDnx8fPDRRx/BzMysTARvaHu/auJ+cPDgQdy5cwf+/v64d+8eQkNDERMTg4yMDJiamoq9b3Xq1Ak+Pj5Ke7oqiff9+Utat27dxOANU1NTfPTRR0XOo2HDhti/fz8uX74MPz8/3Lp1CzExMUhOToaxsTEqVKiAOnXqoFmzZvD29oa7u7vY+1tBn376KTw8PLB161b4+/sjJiYGpqamqFKlClq1aoX+/fujUaNGJdpmIiIiIqKiYJsP23wK8y63+ZRm/WGzZs1w9epVXL16FYGBgQgODkZ4eLj4+9rS0hI1a9aEm5sbevfuDVdXV5X5dezYEb6+vtixYwdu3bqFV69eIS0tDYIglLisJaXJeglNt6FZWVlh3759+Oeff3Dx4kWEhIQgOTlZZvTc4rKwsMDKlSsxYsQIHDp0CAEBAWKdUIUKFdCgQQN06NAB/fv3h7m5eYnXVxq+/vpr9OnTB3v37sXly5fx8uVLJCcni/VB3t7eGDBgAKpXr67TclpaWuLPP//E6dOnsX//fjx48AAJCQmoUKECnJyc8NFHH6F3796l2rmQpmjyGlxc5aF+8NNPP0WDBg2we/du3L17FzExMWKAgiYZGRlh4cKF6NGjB/bt24f79+8jNjYW5ubmqFu3Lnx8fDBo0CC16nwNDQ3xv//9D4MHD4avry+uXbuG6OhopKamwsbGBrVr10b79u0xYMAAVKhQQSPl79KlC44cOYKtW7fi8uXLiIqKgoGBASpXrgwPDw/069cPLVu21Mi6NEGb+1UTz8CavrcX1zfffIP27dtj9+7dCAwMRExMDAwNDeHo6Ihu3bphyJAhsLKyUisvTdaFvy/q1KkDX19fnDx5EqdPn8a9e/fE0ZDs7OzQrFkzdO/eHd27dy/yd/Xhhx9i2bJlMkGqmu7sUqIs7Xs9oSw80RIREREREREREVGZMWzYMLGn/G3btqkcWYeoNMyYMQMHDhwAAPz8888l7oXtXbJ69WqsWrUKQH6jxtKlS3VcIiIiIiIiIiIiIioPXr58ic6dOwPID0BUNPoMUWlzdnYWpx8/fqzDkhBph+bGpiEiIiIiIiIiIiIiolIjCAL2798v/j1w4EAdloaIiIiIiIiIiIiIiIhUYfAGEREREREREREREVE5dPbsWURGRgIA6tWrh5YtW+q4RERERERERERERERERKQMgzeIiIiIiIiIiIiIiMqZhIQELF26VPx7xIgROiwNERERERERERERERERFcZQ1wUgIiIiIiIiIiIiIqLCrV69GomJiYiPj8elS5eQkJAAAKhTpw769u2r28IRERERERERERERERGRSgzeICIiIiIiIiIiIiIqB/bv34/IyEiZz8zMzPDLL7/AyMhIR6UiIiIiIiIiIiIiIiIidTB4g4iIiIiIiIiIiIioHNHT00OFChXg5eWF8ePHo379+rouEhERERERERERERERERVCTxAEQdeFICIiIiIiIiIiIiIiIiIiIiIiIiIiIiIielfp67oARERERERERERERERERERERERERERERERE7zIGbxAREREREREREREREREREREREREREREREWkRgzeIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi0iMEbREREREREREREREREREREREREREREREREWsTgDSIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi1i8AYREREREREREREREREREREREREREREREZEWMXiDiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIhIixi8QUREREREREREREREREREREREREREREREpEWGui4AFU9sbLLSeRUqmMPQ0AA5ObmIj08rUr4lWVaX62a5y0+538dt1uW6WW6WW9vL6nLdLHf5Kff7uM26XDfLzXJre1ldrpvlLj/lfh+3WZfrZrlZbm0vq8t1s9zlp9zv4zbrct0sN8ut7WV1uW6Wu/yU+33cZl2um+V+t8ptb29V5DyJyhpV7ywQFUdJr71E9B+eT0Saw/OJSHN4PlF5os26G4688Q7S09OT+b+0ltXlulnu8lPu93Gbdblulpvl1vayulw3y11+yv0+brMu181ys9zaXlaX62a5y0+538dt1uW6WW6WW9vL6nLdLHf5Kff7uM26XDfLzXJre1ldrpvlLj/lfh+3WZfrZrnfn3ITEb2veO0k0hyeT0Saw/OJSHN4PhHlY/AGERERERERERERERERERERERERERERERGRFjF4g4iIiIiIiIiIiIiIiIiIiIiIiIiIiIiISIsYvEFERERERERERERERERERERERERERERERKRFDN4gIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiLSIgZvEBERERERERERERERERERERERERERERERaRGDN4iIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiLSIwRtERERERERERERERERERERERERERERERERaxOANIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiLWLwBhERERERERERERERERERERERERERERERkRYxeIOIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiEiLGLxBRERERERERERERERERERERERERERERESkRQzeICIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi0iIGbxAREREREREREREREREREREREREREREREWkRgzeIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi0iMEbREREREREREREREREREREREREREREREREWmSo6wIQERERERERERERERERERERFVdkZCT+/vtvXLhwAdHR0TA2NkbNmjXRs2dPDBkyBGZmZsXOOz09HZcuXcKVK1fw4MEDhIeHIy0tDZaWlqhduza8vb0xePBg2Nvbq53f9u3bcfLkSURERCArKwtVq1ZFhw4dMGzYMDg4OOh8m4mIiIiIiIhIOxi8QUREREREREREREREREREROXSuXPnMG3aNKSkpIifpaenIzExEQ8ePMDevXuxYcMG1KpVq8h5P3r0CJ9++inS0tLk5iUkJODOnTu4c+cOtm7divnz58PHx0dlfi9evMDYsWMRFhYm83loaChCQ0Oxd+9eLFu2DB07dlSZjza3mYiIiIiIiIi0h8EbREREREREREREREREREREVO48fPgQkydPRkZGBszNzTFu3Dh4eXkhIyMDx48fx549exAWFoaxY8fC19cXlpaWRco/JSVFDNzw8PBAx44d0aRJE9ja2iIuLg6nT5/G3r17kZKSgqlTp8LCwgLt27dXmpd04MbAgQPh4+MDU1NT+Pv7Y/369UhJScHkyZOxc+dOuLi46GSbiYiIiIiIiEh7GLxBRERERERERERERERERERE5c7ChQuRkZEBQ0NDbN68Ge7u7uK81q1bo1atWli6dCnCwsKwZcsWTJw4sUj56+vro2fPnpgwYQLq1asnN9/b2xvt2rXDhAkTkJubiwULFqBdu3bQ09OTS7tp0yYxcGPatGkYPXq0OM/d3R2enp4YNmwY0tPTsWjRIvz999862WYiIiIiIiIi0h59XReAiIiIiIiIiIiIiIiIiIiIqCju3buHmzdvAgD69+8vE8QgMWrUKDg5OQEAtm3bhuzs7CKtw8PDAytXrlQYuCHRpUsXdOvWDQAQHh6Ohw8fyqXJzs4WgzGcnJwwatQohevq378/ACAgIAD37t2TS1Ma20xERERERERE2sPgDSIiIiIiIiIiIiIiIiIiIipX/Pz8xGlJ0ENB+vr6+PjjjwEASUlJ8Pf310pZvLy8xOnw8HC5+f7+/khOTgYAfPzxx9DXV/yqRr9+/cRp6e1T9Jmut5mIiIiIiIiIio7BG0RERERERERERERERERERFSuBAYGAgDMzc3RuHFjpelatmwpTt+6dUsrZcnKyhKnDQwM5OZLygoAnp6eSvNp0qQJzMzMACgua1naZiIiIiIiIiIqOgZvEBERERERERERERERERERUbkSEhICAHB0dIShoaHSdHXr1pVbRtMCAgLEaScnJ7n50uuVLk9BhoaGcHR0lFumYD5lYZuJiIiIiIiIqOiU/5onIiIiIiIiIiIiIiIiIiIiKmMyMzMRHx8PAKhatarKtDY2NjA3N0daWhqio6M1XpZHjx7h4sWLAIAGDRooDN6QrNfc3BzW1tYq86tWrRoeP36MuLg4ZGVlwdjYGEDZ2mYAqFDBHHp6elrJm95P+vp64v92dhalvv6AAGDdOj1YWADTpwuoUaPUi0CkMbo+n4jeJTyfiDSH5xNRPgZvEBERERERERERERERERERUbmRmpoqTpubmxea3szMDGlpaUhLS9NoObKysvDDDz8gNzcXADB58mSF6STlVbes0stJgjfKyjZLGBoaaCVfIj09PRgYlG5g0MmTwEcfATk5+X/v3q2HixeBJk1KtRhEGqeL84noXcXziUhzeD6VD/7+/hg+fDgAYNu2bfDy8tJxid4dDN4gIiIiIiIiIiIiIiIiIiKiciMzM1OcNjIyKjS9JAAiIyNDo+X46aef8ODBAwBA37590alTJ4XpJOUtSlmllys4rcttlsjJyeXIG6RR+vp60NPTgyAIyMsTSm29YWHAkCF6yMn573iOiwO6dRNw8aKAunVLrShEGqOr84noXcTziUhzeD6VL9L7KC9PQG5ung5LU/oMDPS1ljeDN4iIiIiIiIiIiIiIiIhILePPfa903ppOv5RiSYjofWZiYiJOZ2dnF5o+KysLAGBqaqqxMqxfvx579+4FADRt2hQ//vij0rSS8halrNLLFZzW1TZLi4/Xzoge9P6ys7OAgYEe8vIExMWlFr6ABmRkAP37myMuTv7FrKgoPXTpIuDo0TRUrcqXC6l80cX5RPSu4vlEpDk8n3QvKuoVBgzoDQCYNWsOfHw+Upo2KSldZvp922f29lZay5vBG0RERERERERERERERERERFRuWFhYiNNpaYUHEaSn5790Ym5urpH179q1CytWrAAA1K1bFxs2bFCZt6S8RSmr9HIFp3WxzUTvotmzTXD3roHS+eHh+hgwwAyHDqXBzq4UC0ZEREREpGMeHi1w+fJNXRfjnaS9MT2IiIiIiIiIiIiIiIiIiIiINMzExAS2trYAgOjoaJVpExMTxWCHqlWrlnjdR48exbx58wAADg4O2LJlC+wKeatbst60tDQkJSWpTBsVFQUAsLOzg7Gxsfi5LreZ6F20a5chtm0zLjTd48cGmDZNOyPYEBERERHR+4fBG0RERERERERERERERERERFSu1KtXDwAQHh6OnJwcpemeP38uTjs5OZVonWfPnsX06dORl5cHe3t7bN26Va3gCOn1SpenoJycHERERCgtqy62mehdlJgI/PCDfECGvX0eXFxy5T4/csQIr17plUbRiIiIiIjoHWeo6wIQEREREREREREREREREVHp27RpPbZs2QgAuHz5JpKTk7Fnzz84f/4sXr+OgqGhEVxcGmLQoEHo2dNHZV5RUa+wd+9OBAT44/XraOTl5aJKlSpo3bo1Pv30M1Sq5KBy+YsXz+PkyaN49CgYCQnxMDQ0QsWKdqhSpQpatmwJD49WaNSoica2ncq/5s2b4+bNm0hLS0NQUBCaNWumMN2NGzfEaQ8Pj2Kv79q1a/j222+Rk5MDW1tbbNmyBY6OjmqXVSIgIABubm4K0z148EAcMUNRWUt7m4neVX5+hkhOlg3GMDAQ8OefGahbNw8ffWSOsDDZ/nCPHzfE6NHZpVlMIiIiIiqhgvUemZmZ8PXdDT+/U2LgfO3atdGjRy/06dMfhobKX6vPzMzE0aMH8e+/FxAa+hxJSYmwtLSCk1N9dO3aDT16fKhyeQC4e/cO9uzZgfv37yElJRkVK9rD09MLn346DDVq1MSECWNx584tuLl5YPXqDXLLv3nzBv/+ex63bt3As2dP8eZNLHJzc2FjY4uGDV3QtWsPdOzYBfr68mM7eHu3kPl70aJ5WLRonsxnI0eOwRdfjAMA3Lp1E5MmfQkA+P33dfDwyF8+OjoKAwb0hiAIGDZsJMaNG69ym8+cOYl582YDAJYuXYnWrb3l0rx8GYH9+/fg5s0AvH4djezsHFSsWAlubu7o338gGjZspHId5Q2DN4iIiIiIiIiIiIiIiIiI3nOvXkVi8uTxiIx8KfVpOgICAhAQEIAzZ85gxoy5Cl9EOHHiKJYuXYSsrCyZz8PDwxEeHo59+/Zh9OgvMWzYSLllc3NzMXfuDzh/3k/m8+zsbLx8mYaXL18iMDAQzs4XsWnT3xrZVno3dOnSBevXrwcA+Pr6KgxkyMvLw8GDBwEA1tbW8PLyKta6bt26ha+//hpZWVmwsrLCpk2bUL9+fbWX9/T0hJWVFZKTk3Hw4EGMGTMGenryvfjv379fnO7SpYvc/NLcZqJ32eXLBnKfTZ6chdat80fdmDIlExMnmsnMP3qUwRtERERE5Vlc3FtMmTIRT58+kfk8OPghgoMfIiDgOn7+ebnCwIenT59g5swpiI6Okvk8ISEegYEBCAwMwKFD+7Fkya+ws6uocP3bt2/F+vVrIAiC+FlUVCQOHdqPM2dOYcGCJSrLn5ubi379fJCXlyc3782bWFy+HIvLl//F0aOHsHDhUpibm6vMr7iqVq2Gpk2b4d69O/DzO61W8AYA2NpWQMuWreTm//PP39iwYY3c6JJRUZGIiorEyZPHMGLEFxg9+kvNbYSOMXiDiIiIiIiIiIiIiIiIiOg9N2fOTERFvcLHH/dHhw6dYWlpiWfPnmLXrr8RFhaGkydPwtq6AiZNmiKz3NWrl7Fo0TwIggAzM3MMHjwELVp4wcDAAM+fP8LGjRsQHx+P9evXwNLSCn37fiKz/MGD+8TADVdXN3z00ceoXr0GzMxMkZeXiWfPnuLff/9FfHxiqX0XVD64urqiRYsWuHnzJnx9fdG3b1+4u7vLpNm8eTNCQkIAAMOHD4eRkZHMfH9/fwwfPhwA0LdvXyxevFhuPcHBwRg3bhzS0tJgbm6O9evXo0mToo0CY2xsjGHDhuGPP/5ASEgINm3ahNGjR8ukuX37Nnx9fQHkB3u4urpqZZuJCLh0Sf51qf79/wvM6N49B4aGAnJy/guyun7dALGxerC3F+SWJSIiIqKy74cfpiEsLBSffDIYbdq0hbW1DcLDw/DXX5sQFhaKK1cu4fDhA/j44/4yy718GYGJE8ciJSUFFhYW6NdvIFxcGqNy5SpISkrE5csXcejQfgQHP8SMGVPwxx9/ynV8cfbsGaxbtxoAYG1tgyFDhqNZs/zfcnfv3sb27X9hzpxZsLW1VVp+SdBH8+Yt4eX1AZyc6sHWtgLS0lLx6lUkjhw5iAcP7uHGDX+sWLEEs2fLjqqxbdsuvHnzBt99NwEAMGbMV2jbtr1MmgoV7NT6Lrt164F79+4gKioS9+/fRdOmikeFTExMQEDAdQBAp05d5L6Xf/7Zhj/++B0A4ORUH3379keNGo6wtLRCePgL7N+/Bw8e3MPWrX/CxsYWAwYMVqt8ZZ1Wgzfevn2Le/fu4d69e7h//z7u37+PhIQEAMorPgpz9epVHD58GIGBgYiNjYWBgQEqVaoEZ2dntGrVCn369IGFhYXS5dPT07F9+3acPHkSERERyMrKQtWqVdGhQwcMGzYMDg6qh+uViIyMxN9//40LFy4gOjoaxsbGqFmzJnr27IkhQ4bAzMys8EyIiIiIiIiIiIiIiIiIiMqA4OCHmDNnAbp27SF+1rBhI/Tv3wfDhg3Fo0ePsG/fbnz4YR/UrVsPAJCTk4NfflkoBm788cdG1K/vLC7frl0r9OjRHYMGDUJsbCzWrFmJjh27yLyMcO5cfuBGo0ZN8Pvv62Qa8u3sLNC2rTeGDx+BsLBXWv4GqDz64Ycf8OmnnyIjIwOjRo3Cl19+CS8vL2RkZOD48ePYvXs3AKB27doYOVJ+5JfChIeH44svvkBSUhIA4JtvvoGVlRWePHmidJmKFSuiYkX5nla/+OILHD9+HGFhYVi6dCnCw8Ph4+MDU1NT+Pv7Y926dcjJyYGpqSlmzZqls20mete9eKGH8HDZ3pSrVctD3br/BWXY2gJt2+bi/Pn/7kl5eXo4edIQw4Zx9A0iIiLSruRkYPp0U1y6ZIDMTPkR+8qr/wYf1IMgWMLEREDbtrlYsiQDVlbaX39w8EOsWLEaHh4txM+cnRvCy6s1hg4diLi4tzhwYJ9c8MbChXOQkpKCBg2csWLFGrkAC0/PVvjgg7b4/vtv8fDhAxw/fgS9e/cV52dlZeG335YBAGxtbbFu3RbUqFFTnN+kiSvatu2AL78chYiIcKXlNzAwwD//+MosK+Hu3hy9evXGpk3rsWXLRpw6dRwjRnyBmjUdxTR169aDmdl/o3HY21cW63eKqmPHLli5chlycnJw5sxJpcEb58/7iSNqdOvWU2ZeaOhzbNjwBwBg5MgxGDVqrMwIlQ0buqBLl25YuHAOTp06gQ0b/kD37j6wtrYuVpnLEq0Gb3zwwQcayysxMREzZ87E2bNn5ealpKQgLCwMp06dgru7O1xcXBTm8eLFC4wdOxZhYWEyn4eGhiI0NBR79+7FsmXL0LFjR5VlOXfuHKZNm4aUlBTxs/T0dCQmJuLBgwfYu3cvNmzYgFq1ahV9Q4mIiIiIiIiIiIiIiIiIStkHH7SVCdyQsLCwwPz58zFgwADk5eXh4EFffPfddADAxYvn8eZNLABgxIhRMoEbEg4ODpg6dRqmT//+/18uP4zPPhsuzn/79i0AoGlTV7keGKVZW9uUaPvo3dSoUSP8+uuvYvv9ihUr5NLUrl0bGzZsgKWlZZHzv3nzpniMAsDPP/9c6DITJkzAxIkT5T63tLTEhg0bxHcWdu/eLQZaSKdZtmyZ0nceAO1vM9G77vJl+XuNt3eu1MuE+T78MEcmeAMAjh5l8AYRERFp3/Tppti3710eQU9P/H/fPn3o6QFr1mRofa39+w+SCdyQsLa2gY/PR9i+fSueP3+GlJQU8bfU3bu3cf/+PQDADz/MUzoyRqtWH6BDh844d+4MTpyQDd64dOkC4uLyf1eOHDlWYfCFo2MtjBw5RgzyUERPT0/hstI+/3w0DhzYi4SEBFy+/C8+/XSoyvTFZWNjCy+v1rhy5RLOnfPDpElTFNbpnD59EgBQvboDmjSRHV1y167tyMnJQcOGjeQCNyT09fXx7bff4/z5s0hPT8OFC2dlvtvySr/wJJpRvXp1eHt7F2vZ5ORkjBw5Ugzc6Nq1K5YtW4Y9e/Zg3759WL16NYYPH46qVasqzSMlJUUmcGPgwIHYunUrdu3ahcmTJ8Pc3BwpKSmYPHkygoODlebz8OFDTJ48GSkpKTA3N8fkyZOxa9cubN26FQMHDgQAhIWFYezYsTLBHUREREREREREREREREREZVWvXh8pnefq6op69fJ7Y7x5M0D8XDKtp6eHXr36KF2+e/fu4osP0ssDQKVKlQAAV65cQkJCQrHKTu+3Tp064fDhw/j8889Ru3ZtmJmZwdraGk2aNMHUqVNx8ODBMtPxYq1atXDgwAFMnToVTZo0gbW1NczMzFCnTh18/vnnOHz4cKGdTQLla5uJyppLlwzkPmvbNkfusx49cqCvL8h8dumSAXirIiIiIm27cUP+eeVdFhBQOttbcOQHac7ODQEAgiAgKipS/Pzy5X8B5AdXODmpHqWiWTN3APkjfEhGmwD+qwfR19dXWYbu3XsqDGBQJi8vD2/exCI8PAzPnz/D8+fP8OJFKOztKwMAnj1TPmKkJki2JSEhHjdu+MvNj46Oxv37dwFAYWchV65cAgC0b99J5XZbWVmJI4Q8eHCvxOUuC7Q68sb48ePRtGlTNG3aFJUqVcLLly/RuXPnIuczf/58BAUFwdjYGCtXrpTLo2nTpujatStmzZqF3NxchXls2rRJDNyYNm0aRo8eLc5zd3eHp6cnhg0bhvT0dCxatAh///23wnwWLlyIjIwMGBoaYvPmzXB3dxfntW7dGrVq1cLSpUsRFhaGLVu2KOxRg4iIiIiIiIiIiIiIiIioLGnYsJHK+U2buuLZs2eIiAhHdnY2jIyMEBoaAgCoVq06KlSooHRZY2Nj1K/vjNu3A/H8eYjMvB49euHOnVt4+TICgwd/jHbtOqJlSy80a+YOO7u6Jd8wei84ODhg5syZmDlzZpGW8/LywuPHj5XO79evH/r161fS4skwNzfHmDFjMGbMmBLlU9xtJnqfCYLi4A1vb/l3jeztBbRqlYurV/97tSonRw+nThli0CD5YA8iIiIiTWnZMhcvXpRa3/w65+mp+L1vTatVq7bSedKjfaalpYnTjx49BACEh7+At7f8qB2K5OTkIDk5CRUq2AGAWA9SvboDrKysVJahenUHREa+VJpGEAScPn0CR48ewsOHD5CZmak0bWJiglrlLS5v73YwN7dAWloqzpw5idat28jM9/M7CUHID4YuGLQSHR2FhIR4AMD69auxfv1qtdYpGcGkvNNq8MakSZNKnMfNmzdx6NAhAMC3336rMvhDT09P4bAr2dnZYjCGk5MTRo0aJZfGw8MD/fv3x+7duxEQEIB79+7B1VV2iJZ79+7h5s2bAID+/fvLBG5IjBo1Cvv370dISAi2bduGL7/8EkZG7/LwRURERERERERERERERERU3kleKlCmYsWKAPJfFEhOToKdXUUkJSWqtSwA2NnlL5+UlCTz+Ycf9kFk5Ev88882pKSk4PjxIzh+/AgAoGZNR3Tp0hmDB38KC4vC10FERKTKkyf6iI2VfRGyTp081KghKEz/4Yc5MsEbAHDsGIM3iIiISLuWLMmAnh7w778GyMxUfySGsi5/cAU9AAIEATAxEdCuXS4WL84olfWbmpqqKNt/37P0IALx8fHFWldGxn/blJycXw9ia6u80wsJW9sKSoM3MjMz8cMP03D9+lW1yqAqsEMTTExM0a5dB5w8eQyXLl1ARkaGzHd85sxJAECDBg3lAmfi4+OKtU7p77U802rwhibs2LEDQP6wJ0OHDi1WHv7+/khOTgYAfPzxx9DXVxyR1q9fP+zevRsA4OfnJxe84efnJ073799fYR76+vr4+OOPsXz5ciQlJcHf3x/e3t7FKjcRERERERERERERERERUWmQflGhNJcFgHHjxqNPn344ffoEAgNvICjoPjIyMhAREY4tW7bg77+349tvp+Djjz8p0XqIiOj9pnjUDeWBGL165WDWLNnPLlwwREoKYGmp6dIRERER5bOyAtaseTdeUpdmZ2cBAwM95OYKiItL1XVx1JKXlx/IUa9eA/z4409qL2dvX1njZdm2bbMYuOHm5oF+/QbC2bkh7OwqwsTERHw3fvz4Mbh797Y46oU2devWEydPHkN6ejouXbqArl17AMgfbSQk5Nn/p+kht1xubp44PXLkGHTsqHxgB2mmpmYlLnNZUKaDN7KysnD27FkAwAcffAATExMA+VFNMTExyM3Nhb29vfi5MoGBgeK0p6en0nRNmjSBmZkZ0tPTcevWLaX5mJubo3HjxkrzadmypTh969YtBm8QERERERERERERERERUZkWF/cWVapUVTr/7du3APIDNaysrAEA1tY24rLq5J+/jLXC+VWrVsPw4aMwfPgo5OTkIDg4CFevXsCePXuQmZmJ5cuXoFGjJmjQoGGRtouIiEhCUfBG27a5ClLmq1ZNQPPmuQgM/G+5jAw9nD1riD59OPoGERER0bvOxia/3iM9PQ1169YrVh6SOpSEhMJH8VCWRhAEHD16EADQrJk7fv99ndKBDCSjpJaG5s1bws6uIuLi3uLMmZNi8IZk1A19fX106dJdbjnJ9woABgYGxf5uyyvFe66MePTokThsS4MGDZCSkoKFCxeiVatW6NChAzp37ozmzZtj5MiR8Pf3V5pPSEiIOF23bl2l6QwNDeHo6Ci3TMF8HB0dYWioPO5Feh2K8iEiIiIiIiIiIiIiIiIiKksePXqocv6DB/cBADVq1ISRkREAoE4dJwBAVNQrxMcrfwkhOzsbT58+BgDUretUaFkMDQ3RtGkzzJw5C8uXLweQ/6LC+fNnC98QIiIiBXJzgatX5d/1adNGefAGAHz4YbbcZydOlOm+comIiIhIQ+rXdwYAvHoVibdv3xQrjzp16op5JCUlKU2XlJSIV68ilc6TdKrRsWNnpYEbaWlpCA9/oXQdJR05tSADAwN07twNABAQcB2JiQkQBAF+fqcAAO7uLVCpkr3cctWrO8Dy/4eyu3//nkbLVB6U6V8T0oEPgiCgf//+CAsLk0mTnZ2Nq1ev4tq1a/juu+8wduxYuXyio6MB5I+YoawnF4lq1arh8ePHiIuLQ1ZWFoyNjQEAmZmZYoVj1arKe5wB8iOCzM3NkZaWJq5b0ypUMFd6Eunr64n/29lZFCnfkiyry3Wz3OWn3O/jNuty3Sw3y63tZXW5bpa7/JT7fdxmXa6b5Wa5tb2sLtfNcpefcr+P26zLdbPcLLe2l9Xlulnu8lPu93Gbdblulpvl1vayulw3y12+yl1QUfIor9v8rpXbzMxYnPbzO4m+fT9SuOy9e/fw9OlTAIC3dxsxjw4d2uLIkQMQBAEXLpzEF1+MVrjeM2dOIyUlBQDQtq232tugr6+H1q1bi39nZKQWaVnJ/2Xl+yYiIt25f18fiYmy79m4uOTC3l5QuVyvXjmYN0/2sxs35EfwICIiIqJ3j7d3e+zfvxeCIGDv3l348ssJRc6jefOWOHr0EPLy8nDmzEn07z9QYbpTp05AEBQ/m+bm/hdwnJ6eoXRdR48elElbkOSdeADIysoqrOhq6datB/bu3YmcnBycO+cHJ6d6iIp6Jc5TxMDAAK1atYGf3yncuHEdYWGhqF27jkbKUx6U6eCNxMREcXrjxo3IzMxE27ZtMWnSJDRs2BApKSk4deoUli9fjuTkZCxfvhx169ZFly5dZPJJTU0FkB+8URgzMzOZ5SQHqiSPouSTlpaGtLS0QtMWh6Fh4T8E9fT0YGBQvCipkiyry3Wz3O/HsrpcN8tdfpbV5bpZ7vKzrC7X/T6W+33cZl2um+UuP8vqct0sd/lZVpfr5jaXn3Wz3OVnWV2um+UuP8vqct3c5vKzbpa7/Cyry3Wz3OVnWV2uu6TlljAwUNzrn7bWzX1V8uUlQQYAcP78OZw6dRI+Pj4yy6SmpmLOnDn/n14fgwcPFvd1t25dUblyZcTExGD9+vVo3749nJ2dZZaPiorCL7/8AiC/DfWTT/rLHCuHDh1Cr169YGiouOn68uXL4rSjY80iH2dl6fsmIiLduXRJ/j7Ttq3qUTcAoHZtAQ4OeYiM/O/+ExGhj5gYPVSurDrwg4iIiIjKN0/PVnBxaYzg4CDs3Pk36td3RufOXZWmDwl5hqioV/D2bid+1q5dR1SoYIf4+Dhs2bIBrVp9AAeHGjLLRUSEY8uWjUrztbWtAEtLK6SkJMPP7xQGDfpMJhADAIKDg7Bx4zqV22NtbQMjIyNkZ2fj1auXKtOqy8WlMWrUcMTLl+E4ffoE6tVrAAAwNjZBhw6dlC43bNhInD/vh9zcXMyePR0rVqxC5cpVFKbNzc3F2bOn4ebmoTRNeVKmgzekAx8yMzPRpk0brF+/HgYG+YELdnZ2+PTTT1G/fn0MGzYMeXl5WLFiBTp37iwzKkVmZiYAiMP3qiJ9MEuWKzhdlHwyMpRHOJVETk6uypE39PT0IAgC8vKK9kOxJMvqct0sd/kp9/u4zbpcN8vNcmt7WV2um+UuP+V+H7dZl+tmuVlubS+ry3Wz3OWn3O/jNuty3Sw3y63tZXW5bpa7/JT7fdxmXa6b5Wa5tb2sLtfNcpevcheUm5tXKuvmvtJcuaWnmzRpgqlTpyIgIADdunWHpaUlHj9+jE2b/kRoaCgA4NNPP0P9+g3EfW1gYIh58+bh66+/RkpKCj799FOMGjUKrVq1hr6+Pu7evYONGzfi7du3AIBp06bBxsZW5lj5/vvvsWTJL+jatQvc3Nzh6FgTxsYmePv2La5du4pdu3YByO9gz8enl9rHWVn8viWKE+hEREQlc/myfCep3t45ai3r7p4rE7wBALdv66N798KDP4iIiIiofJs7dyHGjBmBpKREzJkzE6dPH0fnzt1Qo0ZN6OsbID4+Dk+fPsaVK5cQFHQfgwcPlQneMDExwaRJ32HevNlISEjA2LEjMGTICLi6ugMA7t69hR07tiEvL08Mgij4fri+vj66deuB/fv3IiTkKb7+ejQGDfoMNWs6IiUlBdeuXcGBA/tgbm6GSpUqISIiXOG2GBoaomHDRrh//y6OHTuM+vWdUb++s9ihhrW1NaytbYr8HXXr1gObN2/Agwf3EBoaAgD44ANvWFhYKl3Gyakexo//Br//vgJhYc8xfPgg9O7dFx4eLWFnZ4esrCxERb1CUNB9nD9/Fm/fvsG2bbsYvKFtJiYmMn9PnTpVDNyQ1qJFC3Tt2hWnTp1CSEgIHj9+jIYNG8rlk52dXeg6pYeBkV6/9HR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7zLMt7Nu3T88884x+//13+fr6prqszz//XHPmzDH/Xbx4cTVq1EilS5dWbGysjh07ppMnT8owDC1evFjXrl3T1KlT092hFxoaqqFDh+ry5cvKnz+/mjZtqnvuuUdRUVE6cOCAQ+NMyfXr19W/f3+7HdvWM2t4e3srMDDQXP65c+c0ePBgTZs2LdkZ7rp166bQ0FBJd3aQWllfJ9nJMAy99dZb2rx5sywWi+rXr68aNWrIMAydOnXKbsdUVFSUhgwZor1799qNr169eipSpIjCwsK0d+9e86oMn376qSIiIvTSSy/Z9dmwYUNVqVJF586dU1hYmLZu3ZruGepv3rypv//+W9Kd95knnngi02Nes2aN3nrrLcXHx0uyfw/08PDQuXPntH//fiUkJGj//v3q27evFi1apFKlStktp0WLFubtuydoWMXGxiZbp1JrGxcXp/3790uS8uXLl+xHqBs2bNCHH35o/tvX11eNGjVS2bJl5enpqYiICJ07d04nT540x5ZV0dHRevrpp3Xw4EHzvjJlyqhZs2by8fHRhQsXtGfPHvOHya+88oq++eabZDtwHnroId17772S0n+fT+s9IS2XLl2y2x5Jd7bldevWlcVi0dGjR3Xy5EnNmzcvyzu8pYy9Tm23c+l9Vrl7256YmKjXX3/dbueZn5+fGjZsqBIlSigyMlIHDx7UhQsXlJCQoClTpujmzZv69NNP0x3D+fPn9d///lfh4eEqVKiQmjdvrjJlyigsLEy7d++2axsQEKCXXnrJ3CmYL18+1a9fX1WqVJGXl5cuXbqkPXv2KDY2VmfPnlW/fv00f/58Va9ePd0cWdnGZvUzRGbEx8dr2LBhOnDggDw9PdW0aVNVqlRJkZGRCggI0PXr1yXdORDz0ksvacaMGal+Lsiu7UZGJCUlmTunfXx8dO+996pixYoqVKiQEhISFBwcrP379ysiIkJRUVF6++23lS9fvjQ/+9uaNm2aeWYf61gKFCigS5cuOfz5yFV/1+zaHkjS+PHj7SZu2L5Ok5KSFBoaqtOnTyf7gUh2ccfPX3369DEnb6xevVrvvvtuupOlFi9ebN5+5JFHnP7dULrzPdt6EKdixYqqXr26SpQoIW9vb4WHh+vkyZPm5+6dO3fq2Wef1YIFCxw66O2sz7QAAADI+zjew/EejvfYc/W+Q+nOpIZnn33WPGmKh4eH6tSpo+rVq8vHx0cxMTEKDg7W8ePHzStL2qpevboGDBhgniVaunP15W7dumUoR0aOAWRGdu6TyC7WdfCPP/4wf9z60EMPpbgPyZH9lymZPn26xo8fb/7b29tbLVq0ULly5XT79m3t2rVLoaGhSkxM1OzZs3XlyhX98MMPDj3fOXFMMiAgQM8//7z5PmH794yPj9eBAwfMfZjbt29X//799fvvv9tN4MjKfvCMmDdvnt0xy3z58qlFixa65557FBYWpn/++UehoaEaMWKE3njjjUz3I915j7KOKb338vvuu0/FihUz2+/YsUNnzpyRdGd7UK1aNbv2d697ztzeZmSfrbP2DUZFRWno0KE6efKkChYsqKZNm6pcuXKKjIzUrl27dOPGDUl3ru5QtWpVvfDCC3b1Wf18kBmHDx/WhAkTFB8fr2LFiqlly5YqUqSILl26pICAAMXHxysmJkYffvihPDw81Lt371SXtXr1ao0aNcrcT2h7bCEqKkq7d+82369WrlypS5cuafbs2Q6djT81N27cMCdulC1bVjVq1FCpUqVUoEABRUVFKTAwUEePHpVhGDp+/LgGDhyopUuXOnRimbi4OL388ss6cuSIvLy81LhxY1WsWFFxcXE6evSowxld8XfNzuNsWd22Z9Xly5c1btw4hYWFycfHR/fff79KlSqla9euadeuXYqOjlZiYqImTZqkpKQkjRw5MtVlZfd+cFtr167VV199JenO37NJkyYqXLiwecWfrIqIiNDQoUN17tw5+fr6qnnz5ipdurRCQkK0c+dORUdHKy4uTsOGDdOKFSsUHx+vZ599VhERESpevLiaN2+uYsWK6fLly9q1a5fi4+MVERGhV199VWvXrlXhwoVT7DcpKUnDhw+3uwJMsWLF1KJFCxUtWlRXrlwxl3f79m2NHj1at2/f1tNPP51sWU8++aQmTJggSVqxYoVDkzdWrFhhV59ZzvzbO4UBAACQi/3www9GzZo1jZo1axoDBw50uO6dd94x6+rXr2/UrFnT+Oqrr4yoqCi7drdu3TIGDx5stu3UqZORlJSU4jIjIyONzp07m22HDh1qnD9/Plm78PBwY+zYsWa71q1bG7dv387YwO+yc+fODD8PiYmJxqBBg8y6Xr16GUeOHEnWLiYmxpg4caJRq1Yto2bNmkajRo2MCxcuJGv3yiuvmMsaPny4ERoammK/MTExxp9//ml88MEHKT6+ePFicznvvPOOQ2NxVHZldMbfukOHDma7oKAgh8YTFBRk1tSsWdNYvHixQ3WOLrNevXpGrVq1jIceesg4cOBAsrarV6826tWrZ7ZfsmRJusvs0KGDQzkceT5s29SvX99o3LixsWbNmmTtVq1aZdSpU8dsO3PmTKNOnTpGmzZtjF27diVrP2PGDLNt7dq1U+3f9nVnfR46duxoHDx4MFnbBQsW2D1Xqa1bhmEYCxcuNNs1adLEWLBggREXF5es3Y4dO4y2bduabadOnZri8mzfJ+vWrWuu/zdu3LBrl5iYmGI/jhg6dKjZR6NGjYyVK1cma3Pw4EGjU6dOZrv27dsbYWFhqS7Tdt3OLrZ/M+tz8fjjjxvHjx9P1jY2Nta8/fbbb5t1jzzyiLFz585k7RMSEoy5c+ea25Q6deoYe/fuTdZu4sSJdu9D6ZkzZ0667++OvF5OnjxpNGzY0KhZs6ZRq1YtY9y4cSk+/xcuXDD69+9v9/52t/j4eKNRo0bmOMPDw5O12bFjh7mM+++/33w9pdRnQECA2bZ///7JHu/atav5+CeffJJsW20VERFhrF692vjqq69SfDwjbN+769SpY8yaNctITEy0a3P27Fmje/fudq/XtN6/M/M+74inn37aXG7Tpk2NTZs2JWvz559/Gs2bN7d7v0orx8CBA802Ka3vVhl5nWb0s8p3331nt/1ct25dip/BVq9ebTRt2tRsu2rVqhSXZ/vZz/r6//jjj42IiAi7dnFxcebf+tq1a0arVq3MurffftsIDg5OtuyQkBDj1VdfNds9/vjjRkJCQrJ2ztjGGobz1i3DsP9cZs3TvXt34+zZs3btEhISjMmTJ9utE1OmTEl1udm93bDd1v3www8ptomNjTVGjx5t7Ny5M9XtXWxsrPHLL7+Y60izZs2SrSO2bMdbt25do2nTpsYff/yR4nKtHP1clJm/q6u3Bzdv3jSfqzp16hj+/v6pflcKDg425syZYyxYsMChsaSGz1932L5PL1q0KM22CQkJRuvWrc32f//9d7I22f3d0DDuPKf/+9//jKtXr6aa7dixY0aPHj3MfidPnpxqW1d8pgUAAEDO4njPHRzvcQzHexyTE/sOZ82aZT7epUsXIzAwMMXlJCUlGQcOHDDGjh1rXL58OdnjmTm2lNljAI6sq87YJ+Gs42eO7t/NaM2ePXvsjrcNHTrUCAkJsWsTGxtrfPnll3br84wZM1JcnrP2lzoqNDTUbj/PI488Yhw6dChZu2XLlpn702rWrGm8+OKLqS4zM+/hjjh79qzRoEEDu2VfuXLFrk1sbKzx+eefJ3stp5bD0fUvo+/lttvl9N7LnPEenJl9ts7cN2j9bPLOO+8Yt27dsmsXFRVlvPHGG2bbRo0aGZGRkSku01nrlpXte4B1/Rk3bpzd82QYhnHlyhXjqaeeMtved999Kf7NDMMwzp8/bx5PtH4+OXfunF2bxMREY8aMGUbt2rXNdp9++mmqOR15D9y4caPx888/J+vL1oULF4znnnvOXNa7776balvb14B12zJw4MAU+7d9vhw5bpGZv6ujNdl5nC27tu0ZYfteYl0n33zzzWTHpUNDQ41hw4aZbWvXrm3s2bMnxWU6Yz+47TpZt25do169esb8+fOTPdd3v5YcldL7yfvvv5/sebhy5Yrx6KOP2r1fd+/e3ahVq5YxceLEZP2fPHnS7rjBxIkTU80wdepUu/fWr7/+Otnyrl27Zveaqlu3rrF///5ky7p48aL5vNarVy/Z++Ldbt26Zf79a9WqleLfwZHXmjP+9s6WO67DBAAA4ERxcXF68cUXNWrUqGRnlSlWrJi++eYb80ymQUFBdmfhtjVz5kxzhu7DDz+sn3/+WZUqVUrWztfXVx999JF5mbiQkBD9/vvv2Tkkhyxfvtw8C3qjRo30v//9T3Xr1k3WLn/+/Bo2bJheffVVSXfODjFt2rRk7axnqvb29tYXX3yhokWLpthv/vz51b59e4evZpCdsitjXvtbZ1Z8fLyKFi2qX3/9NcVLD3bu3FmDBg0y/71y5UpXxrMTHx+vSZMmpXjZwi5dutidoeqLL75Qvnz5NGvWLLsrCFg9++yzeuCBByTdOYvAmjVrHOrfx8dHM2fOVIMGDZI93rt3b40dO9b894IFC5Jdflm6c7aEL7/8UtKdM+bMmDFDvXv3Vr58+ZK1vf/++zVz5kzzzCPTpk1L9wxiCQkJatOmjb777rtkl3X28PBIsZ/07Ny50+5y8xMmTNBjjz2WrF2DBg00a9Ys84wNV65csTuDjaslJCSodOnSmj17tmrVqpXscetZn3fv3m2e3atSpUr6/fff1bJly2TtPT099dRTT+njjz+WdOdsJtYzRNnq2rWreXvz5s3JLjd8t+w6k8Rnn32mmJgYSdLo0aP1zjvvqEiRIsnaVaxYUdOmTVONGjUk3bmqzd1nsPby8jLPfp+YmJjiZYFtL209dOhQSXdeTwEBAcna2l6R4+7nNjIyUseOHZMklStXTu+//36qZ4ArVKiQOnfurFGjRqX4uKMuXLhgdxb59957T08//XSysydVqVJFM2fOVPny5SXdef2m9Dd3pu3bt5tnvLJYLJo0aZI6dOiQrF379u31448/ymKxZNvVSZzp4sWL+vnnnyXd+Sz222+/6ZFHHknx7GydO3c2z5wl3Tk7m2EYaS4/ISFBvXv31ocffpjszIf58uUz/9YTJkwwz3o1aNAgffnllypTpkyy5ZUqVUrff/+9eaavkydPpni5XVt5aRtrFR8fLz8/P02fPl1VqlSxe8zT01OvvPKKXn75ZfO+KVOmmFcssZVT2w3r57+WLVumur3z9vbW0KFDzbMy3b59W8uWLXNo+UlJSfrpp59SvKKSI1cScJXs3B5Yr84h3fm81b1791TPolimTBkNGjQozbOwZZQ7f/7q06ePeXvRokVptt2yZYt55sJKlSqleFbC7P5uKEm9evXSwIED07xCTO3atTVr1iyVLl1aklK85HpKnPGcAgAA4N+B4z0c77mbOx/vyal9h7b7i997771kZ923sl7h4KOPPlK5cuWy3O/dHD0GkBnZtU8ir/n222/N7+2NGzfW5MmTk12p1dvbW2+//bbdvs1Jkyb9H3v3HR5Ftf9x/JNKEkIvoYYSQHoLRZFepAhKES8W8IoKKqCiYr96bYhiu4oFVFSKCkiVDtJB6RB6TQgBQksjpJffH/ll3M1ukk3YzWbh/XoeHmZnzplzJrszs3vmfM+x2k5oyhntpT///LMxU2+ZMmX0008/qWnTphbp7rnnHn388cfG6/Xr11t91uFIX375pZKTkyVljRI+bdo0ValSxSyNt7e3XnvtNQ0dOtQlngNIjr8G29Jm6+i2wZSUFPXv31+TJk2ymEHB19dXEydONK6BCQkJ2rBhQ77H5WipqakaNmyYXn75ZYtrZZUqVTRt2jTj2p6YmGj2jMbUV199pYSEBElZs85Mnz7dYvYZd3d3Pfroo3r55ZeNdbNnz9bZs2cLXf/u3btr1KhRec50U7NmTX377bfG/eGPP/6waWaEtLQ0NWjQQN99951q1Khhsb24PAuw93M2Z9/bU1NT1aVLF3300UcWM1mVKVNGn332mdHvIyMjQ5988onV/TiiHdxUWlqaJk6cqPvvv9/ib22Pz0ZKSoruuecevfvuuxZ/hypVqui9994zXi9cuFCHDh3SmDFjNHbsWIvy69evr5deesl4vXz5cqtlxsfH6+uvvzZejxw5Ui+88ILF/ipVqqRvvvnG+F6UlpZm9X2oXr262rRpIynrfV25cmWex7xixQrjnta6dWvVrFkzz/S5cfR77wgEbwAAgJte+fLljS9e1lSsWFFdunQxXltrzE9NTdXs2bMlZX3pfvvtt/OdInP8+PHGF3bTzrlF5aeffjKW3377bfn4+OSZftSoUUbHrmXLlikjI8Nse/YU0L6+vlangC4O7FFHV3yvb8STTz6ZZ4er++67z1g+cOBAUVTJqu7duxsBF9bk7BT6r3/9K88poU3T23pc//73v602KGYbOnSomjRpIilruu558+ZZpJk/f77i4uIkSQ8++KBatGiRZ5lBQUHGVOExMTHavHlzvvV87bXX8v3MFoRpJ/fu3bura9euuaatUaOGRo8ebbz+7bff8u1k7UhPP/20RYe/nH788Udj+eWXX843/eDBg40Gqy1btlhMDVuzZk21atVKUlYDS14NEmfOnDE6ypYoUcJqcJItjh49qr///luS1LhxY6tTlJry8/PT008/bby2dt0yDXzK3rep7MaP6tWrm3XmNQ3UyJk2534lmT3QKVu27A1PZW+LuXPnGve4Ro0a6cEHH8w1bZkyZcyCRZYuXZpvQI49mV5Hevfunec04W3atLHaQb44mjFjhvEQ8Omnn87z2iplPTDp2LGjJBnTXeelRIkSmjBhQp5poqKitGTJEklZDY75pffw8ND48eON19l58+Iq91hTzzzzTJ5Thz/99NNGJ+yEhASrD1Fd4b4xZMgQYzm7k0N+evfurbZt2zqqSnZh7/uB6TU6v/ujo9yq37969+5tPOzds2ePTp8+nWta0+COIUOGWL2X2vu3YUGUKlXKeIB++fJlnTx50qZ89v6bAgAA4ObA8x6e9xSEK77XBeGstsPi0F6QzZZnAIVljzYJV3Lq1CmzgIU333wzz46ozz//vNGOGB8fb1OwRVG2l2ZmZmru3LnG66effjrPjsa9evVS586djddFGbwVFxen1atXG68nTJiQ6yBX2duzAxWLs6K4BtvSZuvotkEvLy+98soruW4vUaKE2fU3t8DSolSyZMk8B0orWbKk2TOTlStXWjwbi4uLM+sMPmHCBGOgJmtGjBih+vXrS8rqfG96fjqKl5eXBgwYIElKTk62OlidNS+++GK+37Wczd7P2Zx9b3dzc9Mbb7yR6zXC09NTb7zxhvF6165dVtvMHd0O3rx58xsajDE/Xl5eZoFOOQUHB6tatWrG64oVK5o9Y8vprrvuMgLVTp8+bTXQ8o8//jCCsCpWrGgMfmaNt7e33nzzTeP19u3brb4Ppn+j/J6nmm6/kb+tM5+BFBZPPwAAwE2vW7duxugIuTGNuD137pzF9oMHDxojM99xxx2qUKFCvuUGBAQYHXxPnDhRpJ09L126ZIxkXq9ePTVs2DDfPCVKlFDLli0lSdeuXdPx48fNtmeP7hEbG5trVLaz2aOOxem9rlGjho4dO2b8M51dwl7y6yxet25d44dNTExMviPnOErv3r3z3J5zVKX80jdo0MBYjoiIsKkO2Q11tqax1onddCTy/v3721Su6QOX/BqVbrvttjyDVgrD9DhMO7vmZsiQIUbDyuXLl/PsbOho/fr1y3N7Wlqatm3bJilrVB9ro5JZkz17RGZmpvbs2WOx3bRhIa/GZdNtXbt2zbNRMy8bN240lu+++26bAiDy+1yZzpCR87OclJRkNC63a9dO5cuXNxpcc6ZNSUkxAlS8vb2NwJZs5cqVM+7RJ06csLnh9EaYBqPkNYp8tl69ehkdaFNSUrR3715HVs+M6d/TlmtQ9qhUxZ3pZza74Tw/BbkW3nnnnbmOxpht27ZtxkguvXr1yve7oiS1aNHCeChm7dzPyVXusdm8vb3Vt2/ffNOYPmjKL2DLWfeNjIwMhYSEaO7cufriiy80ceJEvfPOO8Y/01l0sr8z58cVgqPsfT8wfaC9Zs0a4ztyUbpVv395e3ubzeaV2+wbV65cMd53Dw8Pq/cBR/w2zOnq1av6888/NW3aNH388cd69913zc65gwcPGmltOecc8TcFAADAzYHnPTzvKYji9F474nmPs9oOTWcDcPbsJPk9A7gR9miTcCWm7eaNGjWyOlq1KT8/P7N2FluOvyjbS0+dOmXMVOrh4WHWzpIb0xllTWcfd7S9e/cqJSVFklShQgV16tQpz/RlypRR9+7di6JqN6QorsG2tNk6um0wODjYGPAoN/l9Nylq3bt3z/eZZJcuXYxO/MnJyRbPxkw/t+XKlcv3Gau7u7vZ8wJ7XTPj4uK0adMmTZ8+XZ9++qnee+89s3bJrVu3GmltaZcsU6aMEeRQnNn7OZuz7+2tWrXKNwDltttuMzuXcn6GiqId3NHPidq0aWMx41VO2c/kpazfRnkFWvr4+Bh/18zMTKvXH9P7/913351v0EPz5s3N+tpYO5f79Olj1GvPnj25XvciIiKMa4uXl1e+zyhzUxTvvSN4FnmJAAAARcz0i2NuTKewtNYQtG/fPmM5MjLS5imis0dxyMzMVGRkZKE75haUaX2TkpJsrq/plL6RkZFmX2r79u2radOmScoaTWX58uXq16+f2rdvb1NjS1GwRx1d7b2+EaVKlcp3Oks3NzeVLl1aSUlJkrJGu8o5RWNRyO88zo6Kz2b6o9Ua0069tjT+litXLs+pV7Nl/8CTshqAMjMzzTpOmjZszZ07V4sWLcp3n5GRkcbyhQsX8kybPcqTvVy8eNGso2br1q3zzVO+fHnVrl3b6Hx7+PBhp3S+q1GjhsX0xDkdO3bMGEnC09NT77//vk37Nh3xyfT9yda3b19NnDhRqamp2rlzpyIjIy2mt5bMgzdseXCQG9PP1fbt23X+/Pl885iObG/tc9WkSROVLFlS169f15EjR3Tt2jXjumbaIJsd5NG+fXsdP35cx44dU0xMjPG3379/v3H9aN68uUWDj7e3t3r27Klly5YpLS1NjzzyiPr162eMlpTz3L5RmZmZOnr0qPE6ZzCJNV5eXmrWrJkxutLhw4fNRuBylIsXLyoqKsp4nd9oUFLWNcjNzc2pM97kJzo6WmFhYZKy/ra5Tbedk+lI7fa4Fpre748dO2bz/T5bbGysEhISch3hzJXusdkaNGhg00iWpve6nKMzOfu+kZaWppkzZ+qnn36yen22JucMSrmx9z3WEex9P2jRooWqVq2qCxcu6Pz587r77rs1ePBgde/eXc2bN3f4FPG36vevbP/617/0888/S5IWL16s559/Xp6e5s35CxcuVFpamiSpc+fOVkevdMRvw2wnT57Uxx9/rE2bNhkjveUnJiYm3zSucL4BAADAOXjew/MenvdkcWbbYd++fTV//nxJWbOoHjp0SIMGDVLHjh1t+h1vL7Y8Aygse7VJuBLTTs22tJtLWW1/M2fOlGTZTphTUbeXmtanTp06ec42nM20LfPy5cu6ePFinjOF2ItpXZs3b27TTKQtW7a0abYTZyqKa7AtbUiObhu0x3eTombLOe7h4aFmzZoZQQJHjhwxezaW83Obs93SGtNz7PDhwzd0zYyMjNTHH3+sVatWGc8s82PLs4CGDRvKw8OjUHUqKo54zubse7vp/TS/dNmfvZzBOI5sB8/m6Hbr/Pq4SOb9YurVq5dv+vz6xRT2/p8d7GDt/l+6dGl17dpVq1evVmZmpv744w89+eSTFun++OMP43tp165d8x2YLzdF8d47AsEbAADgpmdLo6rpj8nszi+mLl26ZCxnj4pTULGxsQXOU1im9Y2IiDCmJC2InPV96qmntGPHDu3bt0+ZmZlas2aN1qxZI0mqXbu2goODdccdd6hbt25O63hojzq62nt9I2x94JA9laIkY5TyopbfZypng1B+x2ba6GLtnM/JdPpJW9OlpKSYNSxfv37dmOpdUqGm0M5usMyNvacxNX344+PjY/P+q1evbnTCtbVTrL3ZUlfT8z0mJsYu10op68FOp06dtG7dOmVkZGjp0qV6/PHHzdKEhIQYDWtly5a9oWAA0+MwHUHIVtY+V56enmrdurU2b96sjIwM7dy50xjJyXTEqXbt2knKCt6YOXOmMjMztXPnTvXq1UuS+Wgb2WlzevXVV3Xo0CGFhYUpNTVVixcv1uLFi+Xu7q569eqpTZs2uvPOO9W5c+cb7ih87do1s+tY9erVbcpnmq6oPtOm55+vr69Nn2l/f3+VKlUq32uFM2WPdiaZT5teEPa4FpqeN7t37y7UrC9xcXF5Bm/YojjcY7MV5l6X83xw5n0jJSVFTz31lLZs2VKgfKb35rw4Y6rwgrL3/cDLy0sfffSRRo8erYSEBEVHR+uHH37QDz/8oBIlSqhp06Zq27atOnfurNatW9u9c8Kt+v0rW1BQkIKDg7V7925duXJFGzZsUM+ePc3SZD9Qk8xHhzTliN+GkrR582Y9/fTTNj8czWbLA2pXON8AAADgHDzv4XlPQeroau91QTiz7bBTp04aPny40Wn/wIEDxoBHFStWVHBwsNq1a6eePXtaHdTIXhz529EebRKuxvQzZevxF6TdvKjbSwtzPBUrVlSJEiWUnJwsKeuYiiJ4w7Su+QW4FDSdMxXFNTi/60BRtA3a47tJUSvM58z0c5rzdWGuGampqYW+Zh4+fFj//ve/C3yPtuVZgCu0SzriOZuz7+22foby+kw6qh3clKM/HwW9ntjj+mP6d7Tnc/N77rlHq1evlqQ8gzdM0xdWUbz3jpB/qCYAAICLs0cnIntMi2zrSKT24Ij6+vn5aebMmXrppZcsvrSHhYVp/vz5evHFF9WxY0d99NFHxqgoRckedXS19/pGuNLoPwWtq72PLb/pIbP5+vqavTZtBLLHSCr5fbZsraetTOuf89jyYtqZ2dZOsfZmy9/Ckee76UwaS5Yssdhuuq5fv35mDyQK6kY/W7kdQ/asGpJ5EEZ28EaNGjWMa23btm2N885a2pz7M1WpUiXNnz9fTz31lNlUsBkZGTp+/Lh++eUXjRkzRh07dtS0adNu6BqbPdNKNls/1874TJuWU5BzuyDnqjMUxX22qM7/vB6yuNI9Nlth7nU5zwdn3jemTJliBG64ubmpX79++vzzz7V8+XLt3r1bBw8eNB4Smj4otHW0SXvfYx3BEfeDdu3aacmSJRo4cKDZ3yA5OVm7d+/Wt99+qwcffFB9+vTR2rVrb6j8nG7V71+m7r//fmP5999/N9u2a9cuhYaGSsq6l3bt2tXqPhxx3Y2KitL48eONwI3q1avrhRde0C+//KLNmzdr//79Onr0qHG+jR071shryznnCucbAAAAnIPnPYXD857CK67Pe5zddvjGG29oypQpat68udn6K1euaNWqVXr33XfVtWtXPfPMMzbNDFoYjvztaI82CVdj2nae24A1OeXVTphTUbeXmh5PQT73BTkmezGtq62fPVvfI2cqDs8CiqJt0BWfBdjj2VhhzjF7XDNTUlI0btw4o6N1+fLl9dRTT2nGjBnauHGj9u3bZ9Yu+cEHHxh5b5Z2SUedW868txfm2pfz81MU15wSJUrccBl5cUafmMKcy7Y80+vSpYsx69DJkyctZug4dOiQTp06JSlrdpDcnm/YwlW/8zPzBgAAgA1Mv6QOHz5cb7zxhhNrkz/T+nbv3l3ffPONXfbr7e2txx57TCNHjtSxY8e0c+dO7d27V7t27dLFixclSYmJifrhhx+0a9cuzZgxo8h/4N5oHV3tvXZVGRkZzq5Cgdj6cCoxMdHsdcmSJY3lnD92d+zYUeipH4uKaf1zHlteTH/km+6juDFtWLjtttusBlkUVvfu3VWqVCldu3ZNx44d0/Hjx42pk9PT07V8+XIj7Y2MJCGZf7amTJlizHpxo6wFbyQlJWn//v0W28uWLavbbrtNR48eNdKmpKQY05R6e3vnOdWqv7+/nnvuOY0bN04HDx7Url27tGfPHu3evdsYsSM2NlaffPKJ9u3bp6+++qpQDVI5H2gkJiba9JDDGZ9p03IK8oC8IOeqM5j+vf39/Qs144U9mJ43r776qv797387pR7FSWHudTnPB2fdN1JSUowRoSRp0qRJGjhwYK7pi8PU9I7gqPtBzZo19eGHH+qtt94yZqrZs2eP9u/fb3xuwsLCNGbMGL3yyit69NFH7VLurfr9y1SfPn00ceJExcbGatOmTbp48aIx4qPprBuDBw82m1nOlCN+G86dO9d4INKwYUPNnj07z1HyXLnzCgAAAG4+rvYMgOc9PO+xpji0Hfbq1Uu9evXS+fPntWPHDqM99+TJk5KyOsmuWrVK27dv12+//aY6derYrWxHs0ebRGE56/mZabttzkGQcpNXO6GzmR5PQT73zjgm07ra+tmz9T1ypuJwDXb1tkFHsfWcyKvdvjDnmD2umatWrVJERIQkKSAgQL///rsqV66ca/qbsV3Skc/ZnHVvL8y1L+fnx1HfmW92fn5+Rlu/Pa4N2by9vdW7d2/NmTNHUtYsG40bNza2m8660adPH3l7exe47tlc9b1n5g0AAAAbmI4EfuXKFSfWxDaOrq+bm5saNmyo4cOH69NPP9WmTZu0cOFCDR482Eizf//+Qk1H5+w6utp7XRyYzhhg61Sv9oh+L0oXLlwocDpvb2+zH6ulS5c2+9HpCp8v06k/k5KSLKYfzc25c+eM5XLlytm9XvZSoUIFY9ne70d2g0Q208CQLVu26OrVq5KkWrVq5RnUYAvT65bpVLk3qkmTJsZn+OjRo4qJidHevXuNqcpzzqTRrl07SdKJEycUFRWlffv2GdOLt2jRwqbRSDw8PNSiRQs99thj+uqrr7Rt2zbNnj1b3bt3N9L8+eefWrVqVaGOqVSpUmbXLFtHhnHGZ9r0/EtMTMx32nkpq0N6cb++mp538fHxTgs2cdR548psPR9M73U5zwdn3TdCQkKMxuL69evnGbgh2X6srsbRn2s/Pz916tRJzz33nGbMmKHt27frf//7nxGcKEmffPKJ0YHmRt2q379M+fj4GEGe6enpWrRokaSs6+fKlSslZf3uue+++3LdhyN+3/z111/G8lNPPZVn4IZ0855zAAAAcE2u9gyA5z0877GmOLUdVqtWTQMHDtQ777yjZcuWacOGDRo3bpzRkS4mJkaTJk2ye7mOZI82Ccm1np+ZfqZsPf7i/CyoMMdz9epV45mG5JxnAbbWNTIy0lHVsZvicA129bZBRynM5yyvZwGFuWZ4eXkVKnjDtF3ykUceyTNwQ7o52yWL4jlbUd/bbX2f8vpMFodrjisyPZft/dzcdADLpUuXGgGqGRkZWrp0qdV0heGq7z3BGwAAADYwnRpw7969Nk2paE8FHV28RYsWxvKRI0eKZPSNxo0b64MPPtDQoUONdevWrbNI58ypQ22po7Pfa1dk2rASFxeX79/s/PnzLjfidVRUlMLDw/NNlz3LgCQ1atTI4vNu+vnas2eP3ernKAEBAWYNQHv37s03T1RUlMLCwozXpiMoFDeNGjUyGm2vXr2qM2fO2HX/pg0Ny5YtM84N05EkBgwYcMPlOOpz5eHhoeDgYElZI6ns2rXLmFVDsgzeyH6dmZmpHTt2aMeOHca27MCOgnJ3d1ebNm309ddf68477zTWW7u/2CL7QW82Wz7TaWlpOnDggPG6qD7TAQEBZg1m2TOe5GX//v3F/r5VuXJlVa1a1Xhty3vgCK52PS4KJ06csOk7o+m9Luf54Kz7xqVLl4xl00CC3OzcubPAZbiCov5c+/j4qE+fPpo5c6bROJ6amqrNmzfbZf+36vevnO6//35jOXu2jeXLlxvna9u2bRUYGJhrfkf8NizIOZeenu6Sf3cAAADcvJz9DIDnPfZxqz/vKc5th1WrVtXYsWP1zjvvGOu2bt2qlJQUs3TO/Pzkx15tEq70/KxRo0bGsq1ttqa/94vbsyDT+pw+fVoxMTH55jE9nkqVKhmznzqaaV0PHDhg0+wrzmpXL4jicg12lbbBorwmml67cpOenp7nszHT1yEhIUpPT893n6af28aNGxfqmF3tWYAj3ldnPGez9d5eWLZ8j5Hyfj7ljO/MN4PC3P9znsu5CQ4OVo0aNSRlnbvZ/Qz+/vtvYwCyGjVqGP0RCstV33uCNwAAAGwQHBys0qVLS8qK5i5sp9HCMh2tPHvE87zUrFlTQUFBRvrff//dYXXLyXR0dGtRzQU9FkfIq46Oeq9Nj9vW0XVchb+/v8qWLSspa4Sn0NDQPNOvWLGiCGplf4sXLy5Qmpwd2yWpa9euxvKvv/7qEg+LTI9j4cKF+aZfuHCh0bBcuXJl1a1b12F1u1E+Pj66/fbbjde//PKLXfffrl07o/Hs/Pnz2rlzpxISEvTnn38aaW50JAlJ6tatm7G8Zs0au44oYRp08ffffxsBGbVq1VKVKlXM0rZt21bu7lnNDNu3bzcL9Chs8EY2Nzc3s+PMnrmkMEzf80WLFuV7Hq5du9Z4sFOiRIkbnimlIEzPP1uuQdkjshd3ptdCe593turUqZM8PT0lZTUyHj161Cn1sEVRfYdITk42RvLPTUpKipYvX268tnavc8Z9w/QBSH6jTGVkZGju3LkFLsPeHPG+OvJ+kJeyZcuqdevWxusbuUbndKt+/zLVoEED495z5swZ7dixw+z3nWlHJWsc8dsw+34v5T+l/dq1a5nhCAAAAMUKz3tsx/Me64rL857i3nZo+t6kpqZadJ4vDp+fvNijTcJRz88c8Rk0bTc/fPhwvu2liYmJZu2EpvmLg6CgIFWqVElSVid009nRc2N6fbX2fjpKq1atjIHGrly5oi1btuSZ/tq1a0V+7yoMZ99vs7lK22BRXhPXrVuXb6DY5s2bjXZea8/GTD+3UVFR2rBhQ577y8jIMAamkQp/zShIu+TBgwfNAlCcwVHvq7Oes+V3by+sPXv26OzZs3mmOXHihA4dOmS8zvns2ZnfmV2Z6bm4bNkysxmorDlw4ICOHTtmvM7rfunm5qb+/fsbr7Pvxab35P79+99wkJOrvvcEbwAAANjA29tbjzzyiPH67bff1sWLF23Of6Mdp7Ib9iTz0QTy8sQTTxjLn3/+udkX6Pzk7FyTkpKi69ev25TXdFpM05GXsxXmWGxhrzo66r02Pe6C7M9VmI5akldHzcjISE2bNq0oqmR3P/74Y56NBgsWLDAagNzc3HTfffdZpBk2bJjRUHno0CFNmTLF5vKjoqJsGrXE3v71r38Zy2vWrMlzNO1z587p22+/NctbnEfPksyvlbNmzdK2bdtszptfR0Q3NzezmTX++OMPrV271hjtoWXLlqpVq1YBa2ypefPmRgNVUlKSXnrpJZtHOklJSVFsbGyu200bXDZv3qyQkBCL9dnKlCljzGqxZcsWY5QUb2/vXAMe4uPjba6r6bXbdFS5grr//vuNxt1Dhw5pzpw5uaaNi4vT5MmTjdd33323SpUqVeiyC8q0Q+6KFSvyHCFo9+7dZlPMFmcjR46Uh4eHpKzryoIFC2zOa68OwAEBAUbwVGZmpl566SWbR7XLyMhQVFSUXephi6L8DvHFF1/keU2YOnWqUQc/Pz+zRtdszrhv1KxZ01jeuXOnrl27lmva77//vlgE6zjifbX3/SA6Otrmsu11jc7pVv3+lZPp7Bsff/yxcY8tU6aMevfunW9+e/42lMzPubwevEdFRemDDz6wuSwAAACgKPC8h+c9tiruz3uc1XZoa7tYZGSksezu7m72d5Ok0qVLG+200dHRxS6Awx5tEpJjnp854jMYFBSktm3bGq/ffffdPN+Tzz//3OjY7e/vb7Wd0Jnc3NzM2lO++uqrPP9Wf/75p1nn82HDhjmyemZKly6tu+66y3g9efLkPDulT5482SVGFXf2/Tabq7QNOuqeak18fLw+/fTTXLcnJCSYPRvr3bu3xbOx0qVLq1+/fsbrjz76KM9nLLNmzdLx48clZd0TTM/PgrC1XTIxMVFvvvlmocqwJ0e9r/Z+zmave3thZWZm6v333881uCo9PV3vvfee8To4ONjorG/K3u3gt4IBAwbIz89PUtbfIK9rZEpKitn70L59+3wHZLv33nuN5dWrVys2NlarV6+2uv1GuOJ7T/AGAACAjR599FHVr19fUlZD2JAhQ7RixYpcpy6NiorSnDlzNGjQIP3www83VHaNGjXk6+srKauTW3bn2bzcc889RpT09evX9eCDD+q3337LtQNXfHy8lixZouHDh+vdd98123bp0iV17dpVH374YZ6jE2zdulVffvml8bpz584WabL/hlLW9Ifnz5/P91hsYc86OuK9Nj3u/Ea1zhYREaHbbrvN+FeQH91FzbRR9scff9SqVass0uzbt08PP/ywYmNj5eXlVZTVu2FeXl66fv26Ro4caTaiQ7b58+ebNQDdd999VjvllypVSq+++qrxesqUKXr55ZdzPQ8yMzO1e/du/fe//1W3bt3yHUHEEW6//Xaz8+SZZ56xOvrTwYMH9eijjyouLk5S1vSpI0aMKLJ6Fla7du00aNAgSVkjVI0aNUpTp07N9eFgcnKy1q5dq6eeekpPPfVUvvs3nVlj1apVZqPK2GPWjWz/+c9/jIaVrVu36uGHH85zitnQ0FB99dVX6t69e57TRDdp0kT+/v6SpLCwMONhTW4zaWSvDw8PN0bmaNmypdnIMqYOHTqk7t2768svv9TJkyetpklPT9fy5cs1a9YsY521a7etAgMDzTqXv/vuu5o9e7bFNf7MmTMaOXKkIiIiJGU9gBozZkyhyy2MO++80wiUyczM1JgxY7Rx40aLdFu2bNHTTz+tjIwMl7i+BgYGmp0/r732mj788MNcG4fT0tK0ZcsWTZgwwThf7eG5554zRl87duyY7rvvvjxHNYuMjNRPP/2kPn36mI0q52iF+Q5RGF5eXrpw4YJGjhyp8PBws23p6emaOnWqvvrqK2PdqFGjjOuDKWfcNxo3bqyAgABJWSPPPfvssxYPAlNSUvS///1Pn3zyiXG9dCZHva/2vB/MmjVL9957r3755ZdcG6+vX7+uzz77zPj+7eHhoY4dO9rlWG7l71859e3b13hAavp+DhgwINd7rCl7/jaUzGd5mTp1qtXRSA8dOqSHH35YFy5cKBbnHAAAAGCK5z0877kZnvc4q+1w2LBheuGFF7Rx48ZcP4OhoaF6+eWXjdd33HGHMUJ7Nm9vb+N3fGpqqtauXXvDdbMXe7VJSI55ftagQQNjedWqVXabSeD55583OgPv2rVL48aNs5hhNSUlRZ988ol++uknY93YsWNVsmRJu9TBnh555BGjzTAmJkaPPPKIjhw5YpFu2bJleuGFF4zX3bp1MwtkKQpjxowxzpHjx49r1KhRVts3P/zwQ82ZM8clngNIzr3fZnOVtsHCfD8oLC8vL82ePVsff/yxxXX84sWLGj16tPHMzsfHR2PHjrW6nzFjxhjtfmFhYXr88cctgt4yMjL0888/a9KkSca6hx56SDVq1ChU3U3bJRcuXKjp06dbBNhkP987dOiQ09slHfW+2vs5m73u7YXl5eWl9evX65VXXrEIAoqNjdXzzz+vv//+W1JWcN7zzz9vdT/2bge/Ffj7++vpp582Xk+bNk2ff/65xd/sypUrevrpp7Vv3z5Jkqenp9m9Mzd169ZV06ZNJWX9vf/zn/8Y/TCaNm2ab/CHrVzxvfd0SqkAAAAuqGTJkvrmm2/073//WxEREbp8+bKee+45lStXTi1btlTFihWVmZmp2NhYnTx5UmfOnDEaHm50qlgPDw/16NHDGBVnxIgR6tSpk6pWrWo0opUpU0ZPPvmkWZ7PP/9cI0eO1OHDhxUfH6+33npLkydPVsuWLRUQECAPDw/FxsYqNDRUp0+fNqbWtTZ6a1xcnKZPn67p06erbNmyatSokQICAlSiRAldvXpVx44dM/sxXrt2basd8CpVqqRWrVpp7969Sk5O1r333qtOnTqpUqVKxgg7NWvW1IMPPljgv5O96uiI97p3797G6O6//PKLDh06pMaNGxs/1iXpgQceUGBgYIGPuzi4++67NX36dB09elSpqal65pln1KRJEzVs2FAZGRk6duyYDh8+LEkaN26cFixYoHPnzjm51rZr1aqVypQpozVr1mjIkCFq2bKl6tatq5SUFO3bt8/scxUUFGTWcJHT4MGDdfbsWX399deSsqYq/+OPP9SwYUPVrVtXfn5+SkhI0MWLF3XkyJE8Rw8vKh988IEeeOABhYeHKyEhQc8995w+//xzNW/eXF5eXjp16pT2799vPCDw8/PTJ598YoxkU9y98847unz5srZs2aLU1FR9+umn+uabb9S8eXNVq1ZN3t7eiouLU3h4uE6cOGH8yG/SpEm++65fv74aNWqkI0eOKDY21mhY8vLyUt++fe12DA0aNNCnn36q8ePHKzExUfv379f999+vwMBANW7cWGXKlFFKSopxLbR1dCMPDw8FBwdbPPTLbQrU9u3bmz20kXIP9MiWPYrHlClTVKlSJTVs2FCVKlWSh4eHrly5okOHDpmNRtOmTRvdfffdNtU/Ny+//LIxXXJaWpreeecdTZs2TcHBwfLz81N4eLh27dplNPh6enrq/fffL3Rj8o14//33NWzYMF25ckWxsbEaNWqUGjRooMaNG8vNzU2HDx82Rg959NFHtXr1ape4vo4dO1bnzp3TwoULlZmZqenTp2vmzJlq2rSpAgMD5ePjo+vXr+vcuXM6duyYMZKYvUbxkbJm3/j66681atQoRUdHKzQ0VI899pgCAgLUvHlzlS9fXqmpqYqOjtaJEyeMQJ6iVlTfIXr37q3w8HCFhISob9++Cg4OVmBgoK5fv66dO3eadd5v27at2Sg2ORX1fcPd3V3PPvusXnvtNUlZnTf69OmjVq1aqVq1aoqJidGOHTuMmSXeeecdvfjii4Uqy14c9b7a+35w9OhRvf3223rnnXcUGBio+vXrq1y5ckpLS9Ply5e1Z88es5H+nnjiCVWtWrVAdc7Nrf79y5Svr68GDBigX375xWy96SirebH3b8NBgwZp+vTpCgsLU0pKil566SVNnTpVDRs2VIkSJXT8+HEdPHhQktSwYUN17NhR33///Q3+FQAAAAD74XkPz3tuluc9zmg7TEtL09KlS7V06VL5+PjotttuU82aNVWyZEnFxcXp7Nmzxm9CKavj70svvWR1X7179zZmZZ0wYYIWLlyowMBAs47pef3edxR7tkk44vlZr1699OmnnyozM1MbNmzQPffco1atWpkFUPTr10/NmjUr0HG3bt1aL7zwgj766CNJ0vr169W1a1e1b99eVatWVWxsrLZv366YmBizuvz73/8uUDlFpUyZMvrkk0/0xBNPKDExUaGhoRo0aJBatGihoKAgpaamav/+/Tpz5oyRp3bt2po4cWKR17Vu3bp65ZVX9M4770iStm/frh49eqh9+/aqVq2a2d/ey8tL48ePN96n4syZ91tTrtA2WJjvB4WV3V7/3Xff6ffff1e7du1UpkwZnT9/Xtu3bzebdee1117LNTgtMDBQ77//vl588UWlp6dr79696tOnj/FsISEhQbt27TJrg27ZsqUmTJhQ6Lp37NhRbdu21c6dO5WZmakPP/xQs2fPNgajO3PmjPbu3av09HQFBARoxIgRZrOIFDVHvq/2fM5mz3t7YYwePVozZszQokWLtGbNGt1+++2qUKGCLl++rO3bt5s9gxg9erTatGljdT/2/s58q3jssce0e/durV+/XpL0zTff6Ndff1X79u1VpkwZXbh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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 787, "width": 1591 } }, "output_type": "display_data" } ], "source": [ "fig, axs = plt.subplots(2, 2, figsize=(16, 8), gridspec_kw=dict(width_ratios=(2, 1), height_ratios=(1, 1)))\n", "\n", "ax = axs[0][0]\n", "\n", "dft = df_reviews.query('ds_part == \"train\"').groupby(['start_year', 'pos'])['pos'].count().unstack()\n", "dft.index = dft.index.astype('int')\n", "dft = dft.reindex(index=np.arange(dft.index.min(), max(dft.index.max(), 2020))).fillna(0)\n", "dft.plot(kind='bar', stacked=True, ax=ax)\n", "ax.set_title('The train set: number of reviews of different polarities per year')\n", "\n", "ax = axs[0][1]\n", "\n", "dft = df_reviews.query('ds_part == \"train\"').groupby(['tconst', 'pos'])['pos'].count().unstack()\n", "sns.kdeplot(dft[0], color='blue', label='negative', kernel='epa', ax=ax)\n", "sns.kdeplot(dft[1], color='green', label='positive', kernel='epa', ax=ax)\n", "ax.legend()\n", "ax.set_title('The train set: distribution of different polarities per movie')\n", "\n", "ax = axs[1][0]\n", "\n", "dft = df_reviews.query('ds_part == \"test\"').groupby(['start_year', 'pos'])['pos'].count().unstack()\n", "dft.index = dft.index.astype('int')\n", "dft = dft.reindex(index=np.arange(dft.index.min(), max(dft.index.max(), 2020))).fillna(0)\n", "dft.plot(kind='bar', stacked=True, ax=ax)\n", "ax.set_title('The test set: number of reviews of different polarities per year')\n", "\n", "ax = axs[1][1]\n", "\n", "dft = df_reviews.query('ds_part == \"test\"').groupby(['tconst', 'pos'])['pos'].count().unstack()\n", "sns.kdeplot(dft[0], color='blue', label='negative', kernel='epa', ax=ax)\n", "sns.kdeplot(dft[1], color='green', label='positive', kernel='epa', ax=ax)\n", "ax.legend()\n", "ax.set_title('The test set: distribution of different polarities per movie')\n", "\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Train and test show identical yearly review patterns and identical per-movie polarity distributions, confirming the split was drawn randomly across the full corpus.\n", "\n", "The two polarities are distributed differently across movies. Negative reviews concentrate at one per movie, while positive reviews spread across a wider range and cluster near the 30-review cap. Popular films attract many positive reviews, whereas negative reviews come from a long tail of lightly reviewed films. Overall class balance is unaffected, and because the pattern is the same in both splits it poses no distribution-shift risk." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", "\n", "Good job here! \n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Evaluation Procedure" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Composing an evaluation routine which can be used for all models in this project" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "import sklearn.metrics as metrics\n", "\n", "def evaluate_model(model, train_features, train_target, test_features, test_target):\n", " \n", " eval_stats = {}\n", " \n", " fig, axs = plt.subplots(1, 3, figsize=(20, 6)) \n", " \n", " for type, features, target in (('train', train_features, train_target), ('test', test_features, test_target)):\n", " \n", " eval_stats[type] = {}\n", " \n", " pred_target = model.predict(features)\n", " pred_proba = model.predict_proba(features)[:, 1]\n", " \n", " # F1\n", " f1_thresholds = np.arange(0, 1.01, 0.05)\n", " f1_scores = [metrics.f1_score(target, pred_proba>=threshold) for threshold in f1_thresholds]\n", " \n", " # ROC\n", " fpr, tpr, roc_thresholds = metrics.roc_curve(target, pred_proba)\n", " roc_auc = metrics.roc_auc_score(target, pred_proba) \n", " eval_stats[type]['ROC AUC'] = roc_auc\n", "\n", " # PRC\n", " precision, recall, pr_thresholds = metrics.precision_recall_curve(target, pred_proba)\n", " aps = metrics.average_precision_score(target, pred_proba)\n", " eval_stats[type]['APS'] = aps\n", " \n", " if type == 'train':\n", " color = 'blue'\n", " else:\n", " color = 'green'\n", "\n", " # F1 Score\n", " ax = axs[0]\n", " max_f1_score_idx = np.argmax(f1_scores)\n", " ax.plot(f1_thresholds, f1_scores, color=color, label=f'{type}, max={f1_scores[max_f1_score_idx]:.2f} @ {f1_thresholds[max_f1_score_idx]:.2f}')\n", " # setting crosses for some thresholds\n", " for threshold in (0.2, 0.4, 0.5, 0.6, 0.8):\n", " closest_value_idx = np.argmin(np.abs(f1_thresholds-threshold))\n", " marker_color = 'orange' if threshold != 0.5 else 'red'\n", " ax.plot(f1_thresholds[closest_value_idx], f1_scores[closest_value_idx], color=marker_color, marker='X', markersize=7)\n", " ax.set_xlim([-0.02, 1.02]) \n", " ax.set_ylim([-0.02, 1.02])\n", " ax.set_xlabel('threshold')\n", " ax.set_ylabel('F1')\n", " ax.legend(loc='lower center')\n", " ax.set_title(f'F1 Score') \n", "\n", " # ROC\n", " ax = axs[1] \n", " ax.plot(fpr, tpr, color=color, label=f'{type}, ROC AUC={roc_auc:.2f}')\n", " # setting crosses for some thresholds\n", " for threshold in (0.2, 0.4, 0.5, 0.6, 0.8):\n", " closest_value_idx = np.argmin(np.abs(roc_thresholds-threshold))\n", " marker_color = 'orange' if threshold != 0.5 else 'red' \n", " ax.plot(fpr[closest_value_idx], tpr[closest_value_idx], color=marker_color, marker='X', markersize=7)\n", " ax.plot([0, 1], [0, 1], color='grey', linestyle='--')\n", " ax.set_xlim([-0.02, 1.02]) \n", " ax.set_ylim([-0.02, 1.02])\n", " ax.set_xlabel('FPR')\n", " ax.set_ylabel('TPR')\n", " ax.legend(loc='lower center') \n", " ax.set_title(f'ROC Curve')\n", " \n", " # PRC\n", " ax = axs[2]\n", " ax.plot(recall, precision, color=color, label=f'{type}, AP={aps:.2f}')\n", " # setting crosses for some thresholds\n", " for threshold in (0.2, 0.4, 0.5, 0.6, 0.8):\n", " closest_value_idx = np.argmin(np.abs(pr_thresholds-threshold))\n", " marker_color = 'orange' if threshold != 0.5 else 'red'\n", " ax.plot(recall[closest_value_idx], precision[closest_value_idx], color=marker_color, marker='X', markersize=7)\n", " ax.set_xlim([-0.02, 1.02]) \n", " ax.set_ylim([-0.02, 1.02])\n", " ax.set_xlabel('recall')\n", " ax.set_ylabel('precision')\n", " ax.legend(loc='lower center')\n", " ax.set_title(f'PRC') \n", "\n", " eval_stats[type]['Accuracy'] = metrics.accuracy_score(target, pred_target)\n", " eval_stats[type]['F1'] = metrics.f1_score(target, pred_target)\n", " \n", " df_eval_stats = pd.DataFrame(eval_stats)\n", " df_eval_stats = df_eval_stats.round(2)\n", " df_eval_stats = df_eval_stats.reindex(index=('Accuracy', 'F1', 'APS', 'ROC AUC'))\n", " \n", " print(df_eval_stats)\n", " \n", " return" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "I know it was in the precode, but it is a great opportunity to point out the following: \n", "\n", "\n", "- According to [PEP8](https://peps.python.org/pep-0008/), we should always put imports at the top of the file. \n", "\n", "\n", "- Notice that the `type` veriable is green in the function above. When we see that your variables are green, we should think of another name, since green color indicates that this name is reserved in python. \n", " \n", " \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Normalization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We assume all models below accepts texts in lowercase and without any digits, punctuations marks etc." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9508028a23ee4eb4929d59114e2a3961", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/47331 [00:00\n", " Reviewer's comment \n", " \n", "Nice code! If we don't normalize the data, punctuation and digits can create useless tokens such as '12' or '!!', thus increasing dimensionality without adding value. As a result, it may reduce the model's generalization ability.\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Train / Test Split" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Luckily, the whole dataset is already divided into train/test one parts. The corresponding flag is 'ds_part'." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(23796, 18)\n", "(23535, 18)\n" ] } ], "source": [ "df_reviews_train = df_reviews.query('ds_part == \"train\"').copy()\n", "df_reviews_test = df_reviews.query('ds_part == \"test\"').copy()\n", "\n", "train_target = df_reviews_train['pos']\n", "test_target = df_reviews_test['pos']\n", "\n", "print(df_reviews_train.shape)\n", "print(df_reviews_test.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Working with models" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 0 - Constant" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "from sklearn.dummy import DummyClassifier" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DummyClassifier(strategy='most_frequent')" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model_0 = DummyClassifier(strategy='most_frequent')\n", "\n", "train_features_0 = df_reviews_train['review_norm']\n", "test_features_0 = df_reviews_test['review_norm']\n", "\n", "model_0.fit(train_features_0, train_target)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " train test\n", "Accuracy 0.5 0.5\n", "F1 0.0 0.0\n", "APS 0.5 0.5\n", "ROC AUC 0.5 0.5\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 547, "width": 1624 } }, "output_type": "display_data" } ], "source": [ "evaluate_model(model_0, train_features_0, train_target, test_features_0, test_target)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The DummyClassifier ignores the text entirely and always predicts the majority class, negative. Accuracy reaches 0.50 because the classes are balanced, but F1 is 0.00 since the model never predicts a positive and therefore has zero precision and recall on that class. ROC AUC of 0.50 confirms no discriminative power. This establishes the floor: any useful model must clearly exceed it, and note that always predicting positive would score 0.67 on F1, so 0.67 is the more honest benchmark to beat." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "Good. You can also check the result using different strategy values.\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 1 - NLTK, TF-IDF and LR" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "TF-IDF" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "import nltk\n", "\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "from sklearn.linear_model import LogisticRegression\n", "\n", "from nltk.corpus import stopwords" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[nltk_data] Downloading package stopwords to\n", "[nltk_data] /home/student/nltk_data...\n", "[nltk_data] Unzipping corpora/stopwords.zip.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "(23796, 71531)\n", "(23535, 71531)\n" ] } ], "source": [ "nltk.download('stopwords')\n", "stop_words = set(stopwords.words('english'))\n", "\n", "corpus_train = df_reviews_train['review_norm']\n", "corpus_test = df_reviews_test['review_norm']\n", "\n", "tfidf_vectorizer_1 = TfidfVectorizer(stop_words=stop_words)\n", "train_features_1 = tfidf_vectorizer_1.fit_transform(corpus_train)\n", "test_features_1 = tfidf_vectorizer_1.transform(corpus_test)\n", "\n", "print(train_features_1.shape)\n", "print(test_features_1.shape)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LogisticRegression(random_state=12345, solver='liblinear')" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model_1 = LogisticRegression(solver='liblinear', random_state=12345)\n", "model_1.fit(train_features_1, train_target)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " train test\n", "Accuracy 0.94 0.88\n", "F1 0.94 0.88\n", "APS 0.98 0.95\n", "ROC AUC 0.98 0.95\n" ] }, { "data": { "image/png": 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ivvvu52L9PJMn/08HDuxXQMBQ9e3bX15e3oqIuKhZs2Zo//69OnTogH7/faqeeOKZYl2nILZsCdGhQwfUsmVr3XXX3apbt77i4mI1b95sbdkSon379uqPP6bJ3d1d8+fPUdeu3TVs2AjVqFFLUVER+uOP6TpwYJ+2bg1RYOBCjRgxyuIaRqNRtWrVVs+efdS8+W2qXr2GHBzsdfFiuLZvD9WyZUsUFxeniRNf0R9/zLW4kfX29tZrr72liRNf1oUL5/XVV59p4sR3TPOpqal6773/KjU1Rc7Oznr77Q9KJHFQUNndV6Ss3SryUr++j86eDVNkZISSkpIKlWxxdnYxPU5IuJrnsTnnc8Z3vd27d2nOnDlycHDUSy+9XuBYCiMwcJHOnQuTj08DPf/8S2bFK+np6frrr1lavnypLlw4J1dXN7Vt214PPPCwmjTxNTuPq6ub3nnnfxo/fqyWLw/U/fc/pDp1Cp+AOHMm6/2oXbtunp+TevV8TI/zeg8L6qOP3lNY2BnFxcXK1dVVtWvXVceOnXXnnaNUtWq1Ap0jLOyM/vOf8Tp79oxSU1Pl4VFZTZs2U69efTVgwCCbfu6Bm13HGp3lWcFTMSkx1warHpa8jkmXm2j/fjtdvix53fhNkQAUk0GFK5wt7zIyMjR//kxduhSliIiVysjIUPPmBVv8DODWUdJ5lmrVPHX8+DFVrVrVdNytmmfJT877y+rVa1rM79mz0/S4R4/bC3VuP7+e+vPP6f9/nl1mBSy7d187b7dufoU6b3HFxFzW1q2bJUkDBwaYxnv37qvPP/9YKSkpWrFiqZ555nmbxHPq1AnTYp3WrdvJ1bVwnUps6ezZMzIaszo/5pdzuj6PUdgCluwcVUJCQp7H5Zdz6tKlm2rWrK3w8POaN2+OhgwZbpH/ioyM0PLlWUVErVu3VcOGtileAgAAAIDyjHUzN05ISJBpY4ecnVcHDgzQihVLTbmNwuZqrDl58rjp8fW/uxulsGtasp05c6rQBSzOzi66evVKvmtarl7NO7/Qv/8g/fLLj0pISNDMmb+rW7ceFhvqHj16WJs3B0uSBgwYJFdXt0LFCgDIG6vQAAC3PGdnZzVs2NjUalKS6tatp5o1a+X72ri4ODk7u+iHH341WxCfvdtjtq+//tFq+8pWrdpo4MAALVu2RJMmva/du3dq+/ZQdezYucg/z759e/XWW++b3fg2bdpMXbt216OP3q+TJ08oMHChHn30iRu+IP3QoQPq3buv3ntvktnNXseOnfXUU4/qwIF9mj9/rtLT03X33WM1YcJLZjF37NhF9903Whcvhmvhwr+tFrA88sjjqlWrtkXXjWbNWqh37366887ReuKJhxUbG6P58+fqP/950uIcPXv21rBhIxQYuEjLlweqW7ce6tOnvyRpypTvdeLEMUnShAkv5VrUkN2qtjgmTnzHYueHqKgI0+OqVavn+fpq1bLmMzMzFRUVYba4ID916mQVXKSnp2v3bssdLnPKuQNmRMRFq8ekp6fr7bffVmZmph566CE1aNCwwLEUlNFo1B9/TJMkvfHGO6pQ4VqL37S0NL322gsKDd1iGktNvax169YoOHiD3njjbb3//lumdsZS1t/9oEGDtWTJQi1ZskBPPfVcoeJJSUkxLVKpVi3vohF3d3c5OzsrKSlJkZEReR5bELt27TA9jouLU1xcnA4e3K85c2ZqwoQXNWLEXfme4/LlaF2+HG16HhUVqaioSAUHb9TMmTP0v/99Ih+fBsWOFYDkYOeg/vX9Ne+oeecxNQ2UNr+ozEyDQkIcNHRoeukECMCqTFl2YLmVZGRk6O+/Z5l2UpOkdev+UWZmhlq0aF2KkQEoa0o6z+Ll5aq2bdvIaMzQ5ctZi99v1TxLXjZsWKuzZ8MkSR06dJa7u7vFMcePHzM99vXNvWuoNU2a+MrOzk4ZGRlm58l5Xjs7O4sNI2601atXmoowchawuLi4ys+vp/79d7VWr16pJ5981mpn35KW873JqzNrYXz44btWuw8XRtu27S0W/0RGRpoe57f5RfXq13JSRclj1K/fQMeOHVViYoKOHDmc63uTsxjq8uVopaWlmXWGcXR01Dvv/E+vv/6Czp8/pwcfHKuxY+9Xw4aNlJ6eriNHDmvWrBm6ciVetWrVLnKHXQAAAAC41bBu5sZZuTKrc2zNmrXUunVb03iHDp3k7V1Vly5FaeXKZcUuYAkJCdapUyclSbVq1Vb16jXM5p955jGz++6iCAgYqjfffNdszHxNS975hew1LZIUEVH4/IKPTwPt379XZ86cVkxMjDw9Pa0el9+alsqVK+utt97Xu+++qX379ug//3lAo0ePVd269ZWUlKh9+/ZozpyZSktLk69vM5ttjAIAtxIKWADgJnDlivTaaxUVFGSvlJSbdwfgChUydfvtRn3ySbIqVSrtaK4ZN+6BfL+ct3YTntOQIXdo/vw5OnbsqIKC1hfrRrxXrz5mN+HZnJycNHLk3frss0mKi4vT6dOn1LhxkyJfpyAqVqyoV19902KBgL29ve64404dOLBPiYkJqlatutVigYoVKyogYKimTftFJ04c09WrV+XmZr6rQe3adfKMoVGjxho2bLj++mu2goLWWy1gkbKKU3bt2qlz58L06aeT1LJla50+fUp//TVLknT77VlFLraWmJhoepxfR5WKFa/NJyYmFeo6zs7Oat++k0JDN+vEiWNavXqlBgwYZHHc6tUrdeLEtV07csaX059/Ttfx48dVp04dPfnkk0pMNBYqnoI4cGCfoqIi1b59R912m/nO3zNm/GYqXrnjjjvVv7+/XFxctHfvbv3++1RNmvS+1XP6+w/RkiULtW3b1kLHU5jflZT1+0pKSlJSkvX3sCBq1aqtXr36qmXLVqZkz4UL57V+/VqtX/+vUlNT9Nlnk2QwGDR8+Eir57Czs1OHDp3VrVt3NW7sKw8PDyUmJurIkcNasmSBTp8+pdOnT2rChCf088+/q0aNGlbPA6Bw/H0CLAtYfLMKWCQpONieAhagzLEsYDHcvLdfZjIyMrRgwWxFRUVazK1fv0Z16/qoUiXLhdJAeUWepXSRZym4tLQ0XbhwXhs3rtPvv0+VlJVLeeyxp6wen73pgiR5eVUp1LUqVKgoFxcXXb161bRraLa4uKznrq5ucnJyKtR5iyt7EUirVq0tdu309x+if/9drejoS9q2bau6du1+w+PJfi8kWXQBLmty5jFcXAqecypKHsPPr6fWrFklSfrllx80efJXsrOzMzsmNjZWc+bMvC7GBHl4VDYba9mylX77babmzZujefNm67PPJpnNOzu76NFHn9DIkaPl7u5R6FgBAAAAlE83az7nWg7aoMxMN/I5BVRW8jlxcbHavHmTJKl/f3+zjVnt7Ow0YMAgzZ79hzZtCtKVK1dUqZC/1IyMDEVGRmrdujWaOvUn0/i99z5QMj9AAZivk3DJ81jz/ELh1rRIUo8ePbV//14ZjUb98ssPevXVNy2OOXs2TMuWBVqNLyc/v16aOvVPzZnzp5YuXawPP3zXbN7Lq4oeffQJ3XHHnapYsaLVcwAAio4CFgC4Cbz2WkXNn++Y/4HlnkHz59vJYJC+/z65tIMxsbbIPy+ZmZm6fDlaCQkJSk9PM41XrVpNx44dtdjFsrBy7jZ5vWbNmpseX7hw/oYvrOjUqUuuXxQ3bnwtedGrV99cd7XIGWN4+Hk1adI0z2vGx8frypV4paSkKHuRoZtb1k3+6dOnlJ6ebvVazs7Oevvt9/Xkk48oPj5O7733X50/f06ZmZmqUsVbr7323zyvO2PGnDznC8Jah5XU1FTT45w7TlqTc5FI1s9fOA8//Jh27AiV0WjUhx++q/Pnz2nQoKHy9vbWpUuXtHLlUk2f/qscHR2VlpaW63XOng3TjBlZnVHefvttVaxYUYmJCYWOJz/ZiZ6+fQeYjScnJ2vevNmSpAceeNhs4U6zZi3Uvn0nPfLIfVbP2aLFbbK3t9eJE8dlNBoLtTtrauq198LBIf//Jmf/Povyu5Kknj37KCBgqEX3oebNb1O/fgO1aVOQ3nzzFaWnp+vbb7+Qn19PVali2Sb4ww8/tZoIa9OmnUaOHK1PPvmfVqxYqsuXo/XNN5/ro48+LVK8AMz1qddPjnaOSsu49m8B1Q+SKsZIyZ4KDr7xu0MDKD6Dbp4vQnOTkZGhhQvn5rrbeps2HShewU2HPEvpIs+St7w6wPr6NtPzz79ssclDNvOChbwXFFjj7JxVwJKQcPW68yb8/3z+mzmUpJMnj+vo0SOSpIEDLReldO7cVZUreyo2NkarVi23SQFLzvyHs3PJLG547LGnNHas9TxGQeVcIJKtMHmMnDmpouQx+vTprz///F3Hjx/Vli0heuWV5/XQQ/9Rkya+Sk9P086d2/XDD9/o0qWofPNOmZmZWrPmH61du1rp6ZZF/0lJiVq9eqW8vatq6NDhhY4VAAAAQPl08+dzDKb/Tz4nf2Uln7NmzSrTvau1gpqBAwM0e/YfSk1N0bp1a3THHXfme868ckNS1gafI0bcZTE+ceI7Sk4ufNFITta+Cyj6mpbCf37vvHOUFiz4S1FRkVqyZKFSUpI1duwDql/fR4mJCdq8eZN+/PEbJScnycHBQenp6Wb5j5zS0tK0cuUyBQVtUGam5QZmly9H659/VqhWrVry8+tV6FgBAHmjgAUAbgLbtt1aCxxDQ8vOz+vs7JJvB5BsISHBWrRovnbv3pXnYv64uNhixVSvnk+uczlvJm9EQcH18tpBI2cnlbyPu7awPredEU6cOK65c2dq69YQRUdH53qujIwMXbkSn+sOmC1atNRDD/1Hv/76k6l1qsFg0MSJ76hy5cq5nleSGjZsnOd8UeW8gU9LS1OFChVyPTZnYiCv43LTsmUrvfLKRH366UdKT0/Xr7/+pF9//cnsmAoVKuipp57Tl19OlmR9wcunn36k1NQUDRw4UL169ZLRmFHoWAoiuxNMy5atzcb37t39/916Kum++x60eF3jxk3k7z9Yy5cHWsw5OjrK3d1DMTGXFR8fV6jdUp2crr3nOZNsuclejFGU35Uki25E1+vR43Y9+OCj+vXXn5ScnKylSxdr/PhHLI7LaxcXBwcHvfbaf3XgwD6FhZ3Rxo3rFBUVmW/rXwD5q+Tkrm61/LTx3Lprg3ZGqfFKaf9YHT1qr4gIg6pXt0yYAiglhlvz73Hx4nmKiAi3Ote6dTv16MEXN7j5kGcpPeRZis7R0VFDhw5X69Ztcz0m5z18bjmWvGR33nB1Nb8fdXFx1ZUr8UXaObM4VqzI6r7i4OCgvn37W8w7ODioX78B+vvvvxQUtF6JiQlycXG9oTHlPH9SUsksJKpatdoNuQ8vTB4jO4chFS2PYW9vr48++lQvvviMzp07q61bQ7R1a4jFcSNG3KUjRw7p0KGDkmTx+8rIyNA770zUunVrJElDhw7XyJGjVb9+A2VkZOjYsSOaNWuGgoM36uOPP9CJE8f13HMvFTpeAAAAAOUP+ZzSQz4nd9m5C1/fZvLxaWAx36SJrxo2bKSTJ09o5cplBSpgsaZixYpq1aqN7rrrHvn59bR6zPWda0vK9Wta8mK+pqXwG3+4ublp0qTP9corzykm5rJWrVqhVatWWBz3+OPPaO7cmYqNjbHaFSYpKUkvvzxBe/bskr29ve699wENGXKHatWqrdTUFB08uF/Tpv2qvXt36403XtbTTz+nMWOKt7kIAMCcXf6HAADKuk6djKUdgk117lx2ft6CtO/MzMzUxx9/oFdffV4hIcH53gAXtRtDtrxaV9rZXfuf/oyMG1NUkFNeN5w5Y8kr5pzdJYxGy9/90qWL9PDD47R8eWCexSvZ8nt/77//IbMb96FDR6hLl275nvdGybm4JL+FIDl3y3BxKdqup0OHDtfPP/+unj37mO2cam9vLz+/nvrtt5lq1qyFafz6v4GlSxdr587tcnFx1RtvTCxSDAV1+XLW7/v6RMvp06ckZRWq5LajbF4Leq595gq3o3phflfStd9Xfm10i2P48JGmnye7KKuwHBwczHYs3bWraOcBYMnfx8puVE2vFdfRhQUoY6zUr1zfCe1ms2jRXwoPP291rmXLtvLz62PjiADbIM9Sesiz5G/GjDmm//v++1/0wguvqnbtOkpLS9MXX3yiWbNm5PranJtzZN9TF1RKSrKp6OX6brseHlnPExKumi1EuJGMRqNWr14pSeratbs8PCpbPS57d9Pk5GStW/ev1WOy//fc2m6b1uQ87vp/C2S/F1Lh32NbMy9oKnjOqah5jFq1auvXX//QAw88rOrVa5jN+fg01JtvvquXX37D9Dmzt7eXq6t5AcvChfNNxSsPP/yYXn/9Lfn6NlOFChXk7Oys1q3b6uOPvzD93ufNm63g4I1FihcAAABA+UI+p/SQz7Hu9OlTOnw4a4MGf//cO8Jk38Pu27dHFy5Yz8fnlDM39Oef87RgwTKtWrVBX375fa7FKzeS+TqJvDdMMc8vFG1NS7NmzTVt2izdddfd8vKqYjbXvHkLTZ78le6//0FTfsFa15jffvtZe/bskiS9/vpbeuqpCapf30eOjo5ydXVTp05d9c03P6l9+47KzMzUDz98o2PHjhYpXgCAdXRgAYCbwCefJMtgkDZutFdKys27gKpChUz17GnUxx+XnTaoOW9sc7Ns2WItXbpYUtbuCXfffa9atGipqlWrqkKFirK3z1qc+sEHb2vVquUF/rIc0pkzp/Xpp5NkNBrl6emlsWPvV4cOnVSzZk25uLjKwSHrnzpLly7Wxx9/ICn/xQibNwebJQX27dutlJTkfHd/OHnyeDF/Gqlq1eoWyZ2qVaubHkdFReTZCSYyMkJS1uKJnK8rrKZNm+mjjz5Venq6oqMvKT09Xd7eVU07bK5atdx0bIMGjcxeO3Pm75Kktm3ba8eO7dq1y04ZGRm6evVagik2Nsb0eM2aVZKkihWdC51MuXr1qiTzHT2ka7ukVKlSxeI12by9q1odT0lJVlxcrOzt7eXubpnIyEuFChXk4eGhuLg4RUZG5nlsfPy1nWmrVSv67yo/np5e8vDwUGxsrKKioop8Hh+fhqbHly7l/bMBKLiBPgF6M/g188EmyyW7NCnDUcHB9rrrrvTSCQ6AJSsdWG7eu6+szisXLpyzOteiRWv17NnXxhEBtkOepfSQZ8nf9R1g27Rpp4CAIXryyUd14sQxTZnyvdq166DmzW+zeG2jRtdee/TokUJt2HHs2FHToo7GjZuYzTVu3ETnzp39/w4YR3XbbS0L8yMVyfbtobp0Kes+Nzh4o/z8Oub7mpUrl2nIkDssxrPzHQVdHJNzscX1C2JyvjdHjx4p0PnyExUVqStX4ot1jooVnS02AKlW7VpXl6iovO/1IyIicryu6HkMNzc3PfbYU3rssacUGxur+Pg4eXh4mAqQjEajwsMvSJLq1/exKBBaunSRpKzOLNa67mZ7/PGnTfmrZcuWlMoCHgAAAAC2dbPmc7JuiwySMpWZST6nPFm5cpnp8bfffqlvv/0yz+MzMzO1cuUyPfzwY3ked31uqKAuXDhvltMoikqV3C26xJqvack7v5C9pkWSqlcven7B29tbL7zwql544VVFR19SQkKCvLyqyM3NzXSd1NSsPE+DBg3NXpuZmally5ZIkurWraeAgKFWr+Hg4KBHH31CTz31qDIyMrRiRaCaNKHLKwCUFApYAOAmUKmS9P33ZefmFOaWLFkkSapTp65++um3XAshivtF9K1o+fJAGY1G2dvb67vvflb9+j5Wj4uPL9h7e/lytD7++H+SJFdXVyUkJOj06VP6/vuv9eKLr+X52gceGFOo2K2ZOPEdDR48zGwsZxvZM2dOq0mTprm+/syZ05KyFhIUdbeKnBwcHCx2xJSkI0cOmR63aGG+ICa7JWxISJBCQoLyvca7774pSapRo2ahFxNkF5jExsbK29vbNO7ikrU756VLl3J9bW5FGHv27JbRaFTz5reZkmSF4ePTUHv27NL582eVnp5uKqK6XljY6RyvsWwVXLKKn6C9yTeXB0pNfXcfNfdqoUOXD14brBgn1QuWTvdRUJCDpOLtMAXgxrpZO7AsWfK3zp8/a3WuefOW6t27v40jAmyLPEvZRp7FkouLq/773/f0yCP3yWg06rvvvtL33/9icVybNu1Njzdt2qj773+wwNfI2cWibdt2ZnNt27bX+vVrJWVtDGKLApaci0AKavfunbp48aJq1DDPdWTvxHnlSrzS0tLk6OiY53lydgC+vhtNgwaNVLlyZcXGxmrv3l26evWqPDwKt0HG9X7++QetWLG0WOdo27a9vvvuZ7OxunXry97eXkaj0ZRTys2NyGNUrlzZYqOWkydPmLr4WCvCyo7Tx6eBxYYmOVWrVl1eXlV0+XK0WewAAAAAbl43az7Hy8tV9vYGGY2Zunw5764lZdmtls/JyMjQP/+sKPTrVq1anm8BS1F99NF72r17Z7HOERAwVG+++a7Z2PVrWvKSc75+/ZLJL1Sp4q0qVbzNxvJa03L5crTi4+MkSb6+ua+/kaSmTZubHp85c6a4oQIAcqCABQCA/3ejFp+dOnVSktSjR89cb8IzMzN15MjhG3L9m1n2e9uoUZNci1ck6ciRg7nO5TRp0vuKjY2RnZ2dJk/+SvPmzdb69Wu1YME8de9+u7p27V4SYRdK69ZtTY93796p/v39rR4XHX1JZ8+GSZJatWpzw+IxGo3asGGdpKzFAC1btr5h18qPl5eXJCky8qJZAUu9evUlSSdOHFdiYqJZy9ps+/bttXrOOXP+lCT16tWnSDG1bt1We/bsUlJSko4cOZzrop1du64lhm7k7ysmJkZxcbGSZPYeFdapU6dMj3PrXgOgaAb6BJgXsEhS00DpdB+FhdnpzBmD6tcv/7tMATeDTN0af4tLly7UuXPWv4hp1uw29ekz0MYRASivyLPYVpMmvhowwF+rVq3Qnj27tGVLiEUeo0kTXzVp4qtjx45q//69Onz4oJo1a5HvuRMTE7RiRaAkycmpgvr1M89N9Ovnrx9//FYpKSkKDFykcePGl8jGGnnFExS0XpLUoUNnDRs2PM/jExIS9OmnHykzM1OrVi3T+PGPmM03atRE+/btkdFo1PHjR60WTuR09Oi1z1bOrjZS1ud+0KChmjPnTyUlJWn+/Pl65JGHC/yz2ZKjo6OaN79N+/fv1YEDe/Ms3snOYzg5OalZs+ZWjykJ69atMT3u18/y3xzZm40YjcZ8z5Wenm72GgAAAABA/sjnlIydO7ebuo2MGnVPvusqDh7cr7/+mq3z589p797dZutEyrpatWrL27uqLl2KyrdAZs+eXZKkqlWrqWbNWjcspnXr/jU97tt3gNmcvf21JdP55ReMxvQcryO/AAAliQIWAAD+X85d+9LSUkvsvNk3PHm14gwK2qDo6Ny7RcC6gry3ly5dMtslNDcLFszT5s2bJEnjxo1Xmzbt1KBBQx04sF9RUZGaNOk9/f77XIudIbMFB28v/A9QAPXq1ZePTwOdPn1Ka9eu0TPPvKCKFS0TOsuXX9uJs2fPohVfFMTSpYsVEXFRkjR8+EiLm/T58wNNj7N2g7GT0ZhhthvMM888ZkpcFOd9a9KkqYKDN2rbtq1q0eJaoUibNu3k6uqqq1evaObM3/Wf/zxp9rrTp09Z3al12rRfFBq6RZ6eXho5cnSRYrr99l76449pkqTly5dYLWDJyMjQqlVZ13dzq6T27TsW6VoFsWTJAlN75bZt2+dztHXp6elavnyJ6XmbNu3yOBpAYQ30GaSvd35uPugbKK36XJJBwcEOql8/rVRiA5A/Qwl0OitLli9fpLCwU1bnfH2bq29f68XUAGANeRbbe+CBR7R69SplZGTo99+nWt2IY9y48aZuqJMnf6gff5ya68KRbN9//7Wp68iQIXfI09PTbN7T01PDht2p+fPnKDr6kr755nO99tp/CxTzqVMnlZKSUqiiiHXr/lVyctauunfeeZd69+6X72sWLpyv48ePatWq5RYFLB07dtKiRfMlSatXr8yzgCUzM1OrV6+SlNW51tq99j333KtFi+YrOTlZ3377rXr37lWgriUZGRlas2aVBg4MMBt/8813LXY3LSm3395L+/fvVUJCgjZsWGt145TIyAjt2BEqSerQoZOp821Ji4mJ0YIFf0mS6tatp06dulgcU7NmLZ08eUKnTp3QlStXVKlSJavnOnnyuGk31Ru5IAYAAAAAbjbkc0pG9noEe3t7jR//iDw9vfI8vmPHLvr7779kNBq1cuWyG1LAcn1n1pJiMBjk59dLixbN15kzp7V//z61bNnK4rj9+/eZOrD4+fW6ocVS//77jySpY8fOpg1Qs7m7u8vV1VUJCQnav3+f0tPT5eBgfRl1zo1Ja9UivwAAJcmutAMAAKCsyNlS8vz5cyV23rp160qSNm0KMn1xmtP58+f0xReflNj1isvPr6P8/Dpq1KhhpR1KvrLf23Pnzmrfvj0W88nJyXrvvTeVkpKS53nCwk7rhx++lpTVAvSRRx6XJLm7e2jixHdkMBgUHR2tyZM/LOGfoGDGjLlPkhQfH2eKM6fz58/pzz+ziibq1Kmrnj17Wz3PqFHDTL/f3ERFReY6t2PHNn3zTdYi67p165niKi1dumQtxMnuCJPN2dlZo0aNkSTNmPGbPv30I+3cuV2HDx/SggXzNGHCE6bCm/T0dK1f/6+ef/4pTZ06RY6Ojnr//UlFXozRokVLU4HH0qWLtX+/ZaeXOXP+1OnTWQtDR48eYzUZsnPndtPv6sMP37WYDw+/YLbjqzWbNgVp+vRfJUkVKlTQkCF3WL3OlStXcj1Henq6Pvnkf6Z4e/S4XdWr18jzugAKp321jvJ2vq5DUpXjkvcRSVJQELv5AGXHzd2BZcWKJTp9+qTVucaNm6p//wCrcwCQG/IsWWyZZ6lf38e0qcW+fXu0c6flphH9+/ubuo4ePXpEr732omJiYqyeLz09XT/88LUWL14gSapdu46efPIZq8c+/vjTpiKNwMBF+uST/ykxMTHXWNPT0/X333P12GMPmnYkLajsRSAVK1ZU1649CvSa3r37SpLCws7owIH9ZnN+fr1UrVp1SVmFLrt27cj1PL//PlXHjx+VJPXrN8DqApSqVavphRdelSQlJSXq/vvv17ZtoXnGd+rUSb300rOaNeuPAv08JWXYsBFyc3OTJP3003emLq7ZjEajPv/8Y9NCo7Fj77d6nqlTp5g+68uXB1o95tKlqFzjiI+P1+uvv6irV69Kkl5++Q2rC1l69OgpSUpNTdW3335h2rQjp5SUFH311Wem5927357rdQEAAAAA5sjnZClOPicpKcm0hqF167b5Fq9IUuXKldW2bQdJ0tq1a5SaWnLFQ7Zw991jTWswvvrqU6WkJJvNJycn66uvPpWUVdRz991jrZ7nww/fNb331vJaUt5rWiIiLuqNN16S0WiUk5OTKT+Tk52dnbp185OUlauYMeM3q+eKj4/Xjz9+a3pOfgEAShYdWAAA+H++vk3l5FRBqakp+uWXn+Tg4KDq1WvKzi6r3rNq1ar57khpjb//EP3ww9e6dClKjz/+kMaNG6+GDRspNTVVO3Zs07x5s5WamiZf32b5LkiHOX//wZo/f64yMjL0yivP695771fr1m3l5OSkI0cOa+7cWTp3LkytWrWxWuAiZS2YeO+9t5ScnKwKFSro7bc/MCso6NSpi0aPHqO//pqtjRvXaenSxRo6dLitfkRJUkDAUC1btkT79u3RggXzdPlytIYNu1OVKlXSoUMHNH36VCUkJMjOzk7PPfdyrrtDFMT999+jdu3aq1s3PzVo0FCOjk6KiLiojRvXafXqlcrIyJC7u4fef/9jVahQoQR/ysJr0eI21ahRU0ePHlZw8Eb5+fU0zY0f/4j279+nHTtCtXjxAtNiG0lydHTUxInv6L33/qtLl6L03/++JkmqXr2G3n33Q7Vq1aZYcT333Et68slHlJKSohdeeEYPPPCQ2rXrqNTUFK1Zs0pLliyUlFUENHZs0YqAwsMvaMKEJ9SyZWv16HG7GjduYkp8nT9/XuvX/6v16/81LeR4+unnVbVqNYvzrFixVK+99qL8/HqqXbsOqlevvlxdXZWYmKQjRw5pyZKFpoWsnp5eeu65l4sUL4Dc2dvZa0D9QZp9+E/ziaZLpEvNFBxsr8xM6QZtQgSgMAxWClhukj/OVauW6tSp41bnGjXy1cCBQ2wcEYCbAXmW0vHAAw9p/fp/JWUVW1jr+vnGG+8oLi5Ou3fv1PbtoRo3bpSGDLlD7dt3lJdXFSUkXNXhw4e0bNli086Y1apV18cff5Hrhg/Ozs765JMv9fLLE3T2bJgCAxcpOHijBg4cpLZt26tKFW9lZkrR0Ze0Z89OrV+/1tThtTAuXrxo6uratWt3q11qrendu59+/fUnSVkFMDk7pjo4OOiNN97WSy89q7S0NL3wwtMaNGiIune/XdWqVZfRaNTZs2f0zz8rFBq6RZJUpUoVPfPMC7leb8iQOxQVFalff/1J0dHRGj9+vDp37io/v6xuLG5uboqPj9fZs2HavDlYW7dultFoVOPGvoV+T4rD3d1DTzzxrD77bJIuXgzXY489qAceeFiNGjXWpUtR+uuv2aYFI/37+xeri+yMGb9p164d6tt3gG67rZUqV66sq1evas+eXVq0aL6py8+jjz6hDh06WT3HPfeM09KlixUTc1nLlwfq3LmzGjHiLtWr56OMDKOOHj2i+fPnmnIZPj4NNHhw2d+kBwAAAADKCvI5xbdhw1olJWVt6pG9oUZB9O7dVzt2hOrq1SsKDt6ovn3736gQS1y9evU1duz9+vPP6Tp8+KCefPIRjRs3Xs2bN9H58+f0888/6/DhQ5Kke+99QHXr1ivytT79dJJiY2PUu3dfNWvWQm5uboqNjdX27aFavPhv09qZV16ZqPr1faye46GH/qPg4A1KTk7Wb7/9rCNHDikgYKhq1aqt1NRUHTiwT3/9NduUu+rQobM6d+5a5JgBAJYoYAEA4P+5uLhq1Kh7NGvWDB09elgvvGC+o+Q33/xUpC9p7757rLZv36rQ0C06ezZMH3/8gdl8hQoV9N//vqfNm4NL/UY85y4I7u4epRhJwTRvfpseeeRxTZ06RVevXtHPP/9gccyYMfepYcNGuRawTJ06RUeOZN0oP/3081ZvYJ944llt3x6qkydP6OuvP1e7dh1Uu3adEv1Z8mJvb69Jkz7XK69M0KFDB7V+/VqtX7/W7Jjs3SO6dSvYzqO5MRrTFRS0QUFBG6zON2jQUG+//T81aWLbBRXW2NnZafz4R/TJJ//TDz98rfbtO5gW0jg5Oemzz77W3LkztWLFUoWHX5CLi6vatGmr8eMfUZ069VShQgVVruyppk2bq0eP2zVwYIAcHR2LHZevbzO9994kffDBW0pISNCUKd9bHFO3bj19+unXRe70km3//r1Wu7xkq1ixop599kUNHz4y12OSkhK1evVKrV69MtdjGjVqrHff/Ui1atUuVrwArBvoE2BZwOIbKG16VZGRdjp2zE6+vhmlExyAPBl0cxSwZO+8fr2GDRvL33+ojaMBcLMgz1I6eRZf32bq1q2HNm/epB07tmn//n1q2bKV2TFubm76/PNv9eOP32jhwvmKj4/T7Nl/aPZs690/unTprldfnZhvR87atetoypRp+vrrz7V69UrFxFzW3LmzNHfuLKvHOzg4aMSIUYX6HKxatcy0WUPv3v0K/Dofnwby8Wmo06dPau3afzRhwotmOYBOnbroo48+1f/+966uXr2ipUsXa+nSxbmcq6EmTfos3x1UH3zwUbVq1VyTJ0/W+fPnFRq6xVQAY02DBg311FMTCvwzlZQRI+5SdPQlTZ/+q86fP6dJk963OKZbtx564423i32tU6dOaurUKVbnKlasqMcff0ajR4/J9fWVK1fWF198q4kTX1V4+Hnt3btbe/futnpskya+mjTp8xLJ9QAAAADArYJ8TvHzOdmdYw0Gg3r1KngBS69effTll5OVkZGhlSuXlasCFkl67LGnFBNzWcuWLdHRo0f0zjsTLY4ZOnS4/vOfJ4t5pUwdPLhfBw/utzrr7u6hl156Tf36Dcz1DPXr+2jSpM/13ntvKjY2Vps2BWnTpiCrx3bo0EkffPBxMWMGAFyPAhYAAHJ48slnVbduPa1cuUynTp1UQsJVGY3GYp3TwcFBkyd/pUWL5mvlyuU6ffqkMjMzVbVqNXXs2FmjR49V/fo+2rw5uIR+iqLbv3+f6fE999xbipEU3EMP/UfNmjXXvHlzdOjQQSUnJ8nT00vNm7fQiBF3qVOnrlq+PNDqa/fs2a2ZM3+XlPVF/MiRo60e5+TkpLff/p8ee2y8kpIS9cEHb+v7738xtUC1hcqVK+vHH39TYOAirV69UmfOnFJSUrK8vb3VoUNnjR49Rg0bNir2dV577b8KDd2iQ4cOKDo6WklJiapc2VONGjVWnz795e8/uFgdXkpaQMBQzZ8/RydOHNe77/5XH3/8uWn3F0dHR91334O6774Hrb7233833bC4/Px66vff52jevNkKCQlWVFSkHBwcVadOXfXp00933XVPgXeJtaZZs+Z6++0PtH//Xh0+fEjR0ZcUFxcro9GoSpXc1aBBQ3Xo0EnDho3Ic0HNuHHj1aSJr/bv36fTp08qNjZW8fFxcnR0kpeXl5o1a67evfupZ88+Nv28A7eaXnX7yMnOSakZOdqB1w2RnKOlpCoKCrKngAUoE6x0YLlJ9OjRW3Z2dtq1a7tpzMenkQYNuqMUowJwMyDPUjp5lgceeFibN2fd8/7++6/69NOvLY6pUKGCnn/+FY0aNUarVi1XaOgWXbx4QXFxcXJxcZW3t7fatm2vvn0HqG3b9gW+tru7h956633df/9D+vfff7Rjxza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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 547, "width": 1624 } }, "output_type": "display_data" } ], "source": [ "evaluate_model(model_1, train_features_1, train_target, test_features_1, test_target)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "TF-IDF produced 71,531 features, with train and test sharing identical dimensions since the vectorizer was fit on train only and test merely transformed, avoiding leakage. Test F1 of 0.88 clears the 0.85 requirement, with ROC AUC of 0.95 confirming strong separation. The train/test gap of 0.94 versus 0.88 indicates mild overfitting, unsurprising given roughly three times more features than training examples. Note that NLTK's stopword list removes negation words such as \"not\" and \"never\", which discards genuine sentiment signal, yet performance stays high because negative reviews carry ample unambiguous vocabulary." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "Correct. The model exceeds the F1 threshold and has good precision. \n", " \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 3 - spaCy, TF-IDF and LR" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "import spacy\n", "\n", "nlp = spacy.load('en_core_web_sm', disable=['parser', 'ner'])" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "def text_preprocessing_3(text):\n", " \n", " doc = nlp(text)\n", " #tokens = [token.lemma_ for token in doc if not token.is_stop]\n", " tokens = [token.lemma_ for token in doc]\n", " \n", " return ' '.join(tokens)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5fb86fcc88684c59834965abfd897e92", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/23796 [00:00" ] }, "metadata": { "image/png": { "height": 547, "width": 1624 } }, "output_type": "display_data" } ], "source": [ "model_3 = LogisticRegression(solver='liblinear', random_state=12345)\n", "model_3.fit(train_features_3, train_target)\n", "\n", "evaluate_model(model_3, train_features_3, train_target, test_features_3, test_target)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lemmatization collapses inflected forms to dictionary roots, merging \"loved\", \"loving\", and \"loves\" into \"love\". This cut the vocabulary from Model 1's 71,531 features to 59,139, a 17% reduction. Test F1 is unchanged at 0.88, while train F1 falls from 0.94 to 0.93, narrowing the overfitting gap by one point. Fewer, denser features slightly reduce memorization without improving generalization. With roughly 24,000 training examples, TF-IDF and logistic regression already learn reliable weights for inflected variants separately, so lemmatization adds little. The substantial preprocessing cost is not justified by the result at this dataset size." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "Great! \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 4 - spaCy, TF-IDF and LGBMClassifier" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "from lightgbm import LGBMClassifier" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LGBMClassifier(random_state=12345)" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model_4 = LGBMClassifier(random_state=12345, n_jobs=-1)\n", "model_4.fit(train_features_3, train_target)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " train test\n", "Accuracy 0.91 0.86\n", "F1 0.91 0.86\n", "APS 0.97 0.93\n", "ROC AUC 0.97 0.94\n" ] }, { "data": { "image/png": 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Kfv2yczF9+w7QL7/8oN27dyomJkZeXl4lvk5AwPX79YiIsHz2LF3btm0xTqQ1aJD5pBU5Bg4crD17diozM1Pbtm3Rvfc+UKTrnDhxzPg4v/xCnTp1VatWbV28eEGbN2/QxIkvFOk6OXJPRpKamlqscwAASgffdgMAUEzx8fF6/vmnNHnyK9q0ab0uX45Qamqqrl27ppMnj+vXX3/SqFFDFRh4xOLxGzas05gxI7Rw4Z86e/aMkpISlZ6erqioKwoODtLKlcv0zjuTde5ciHWfWAEiIsL1r389qunTf9aZM6eVlJSk2NgY7dq1QxMnjteGDeskScHBp/T446M1c+avCgk5o+TkZMXHx2nbti168snH8yzGv3TpooYPv0/ffvulduzYqvDwMKWmpig1NUUREeHasGGtXnnlOX3wwVsWZ9xs1aq1cXbGnTu366+/5lu8zueff6KwsEuSpNdff8tqzSuSdPjwQUnZBSM+PlXz3K9167bGx0eOHCrydTw9PeXu7iFJxhVfLLl48YLxsaUmmY0b1xkfd+lyfUnahIRrOn8+VDExMUWOLT+//TZN+/b9I1/f6vrpp9+KtWzriBGjNWHCM5Ky3+v4+LhixZLzXkmm78eNfHyqqk6dupKK917daP36tdqxY+v/r/ryQqGPu3Tpoq5ciZSUf7y5t0dGXjb+LgCoGBp4NJRd1g2FXL6BCgqiEQ0oW5ZWYCnd37sLF0K1bNlfFptXHB2dNGLEY/muhAcAFVleeZarV6/q6NGj+vbbb0olz3LhQqiVn1nx5S7ez2sWyVWrrs/q+dBDDxf63Pfe+6CcnCpJklavXm7y/56srCytXr1cUvbqK/fcc3+R4i6pEyeOGVc7yWnIadmylWrWrPX/8ZbOTKaFtX79GqWkpEjKXn0lZ/Wa8sg0j5H3ijl+fv7GRpLi5DFy51kKyql5e3tLkpKTk00KUyz57LOPlZSUpH79BlosiAIAAAAAlC/Wqpspb/mcv/9epYyMDNnZ2alPn+yVcPv2HSCDwaD09HStW7emVK6TOx9krckxpMLXSeTOPRQnvxAXdz2/4OXlne++OfmFsLBLFlcTLoz166+/L4WdrAUAUDZYgQUAcMvz92+mmTPnauvWzfr55+8lSZ9//o2qVjVtLMj5klzK7sR/4YWnFRR0Qvb29urdu586deqimjVrKT09XYcO7de8eX8oJiZar776vKZP/0M1atQ0Hh8dHaUpU95TWlqavLy89eCDD6lZs+by8PBUSkqKLlw4r4MH92vr1s0mMXz++TdKT0/To49mL2t5331D9cADQ032qVIl75krSsNbb72uyMjLeuSRsbrjjk6qXLmyDh8+qGnTflRCQoI+/vgD+fn567XXXlBKSorGj39arVu3lYODg3bv3qmZM39VamqqPvzwXc2du8hsJsXMzEw5OjqqY8c71aHDHapfv4Hc3d0VHx+v8+dD9ddf2YmLNWtW6bbbamvcuAlmMY4bN0H//LNbJ04c07fffql27TqY3HyuW7dGa9askiTde+8D6tq1m9k5ykpiYqJx1tSCbohzbz937myxrnfvvQ9o1qzpCgo6oV27dlictWLGjF8kSfb29hoy5D6z7UePZieTHBwcVK9efe3evVPTp/+swMDDxn18faurX7+BGj16TIlWaImJidHcub/LYDDozTffNfs9PHBgn2bNmq5jxwKVkZGp+vXr6957H9TgwfeaneuRR8Zq375/tHfvHs2bN1tPPPFUkePJWX1FKtz7df58qC5fjlBSUlKxC1quXr2qr7/+ryTpqaeelaenZ6GPLWq8Oc6dO5vvKj0AyhcneydVMzRRhI5eH6wcp/3BYRqr220XGHCTyzKYN08bDKU3N8ylSxe0bNnCPJpXHDVy5Bi5uZXtSngAUBpKO8/i4uKg/fv3afr06TdlniU/ue/xatSwvNTe4cMHJGWv5NquXYdCn7tKlSpq3bqN9uzZpbi4OJ09e0YNGjSUJJ09e1qxsbGSpJYt25jMTmkNOQ0qLi6uuuuuHpIkg8GgPn36aebMX7Vz5zbFx8cZJ+0oawcP7jc+7tSpq1WuWVw5jT9S/nkBBwcH1apVR6dPnzL5nBVW7pxHzooveUlIuL49JORMnoUv69at0c6d21WlirsmTnzR4j4AAAAAgLJB3UzR5Kwc26ZNO1Wr5itJuu22WmrevKWOHDmk1atXaNiwESW+zunTwcbHN74XZSknV+Dm5pbvpKxVq1aVq6urEhISilXT4ux8fcKu3PkDS3LnH0JCzqhGjRoFnj8zM1OxsTE6e/aMFiyYp61bN0nKzpl07HhnkeMFAJQeGlgAALc8Z2dnNWjQSCdOHDeO1alTVzVrWi4MkLKXIA0KOiE3tyr68svv5Ofnb7K9VavW6tt3gCZMGKuoqCv68cdv9c47/zFu37Fjm5KSkiRJX331nRo0aGRyfIsWrTRgwGC99FKyvLyuFwncuDqGl5eX2bFlLTg4SP/7309q1qy5cczPL0C1a9fVa6+9oMTEBI0f/5ikLP3882+qVau2cb+AgOxkw+eff6KIiHDt2LFN3bv3NDm/j09VzZ+/zOLNd/v2HXXffQ9qypT3tXLlMs2d+7uGDx9lVsjn4OCgt9/+QI8/PkrJycl677039eOPM+To6KiIiHD9978fS8p+n5999iWLz3PatB/Nlpktqho1amrBgmUmY5GRl42PcxIZefH1vX7DHRERUawYHn30cZ08eUJ79uzU5Mmv6IEHHlK7dh3k6empS5cuatGiBTp4cL/s7e314ouvWSxuuJ6cqKL58+fom2++NNvn8uUIzZo1XZs3b9Dnn39bqGSBJXPn/q6kpCTdd99Qs8KbFSuW6uOPPzAp6jx+/JiOHz+mvXv3KC0tVZs3bzRZtvhf/3pSe/fu0fLlizVu3ATZ2RWtyDQy8vrrXq1a9Xz39fXN3p6VlaXIyAjVrVu/SNfK8d13XysqKkotWrSy2JiTH9N4C/p8XX8+xf18AbCdRu4Biog/ajJ2KOy4RAMLUGYSaq00GzOodFZgCQu7qCVL5ltsXnFwcNSIEWPk5lalVK4FAGWttPMs3t6u6tixgwYOHKQRI0aUOM+SW3nIs+QlIyNDc+bMMv7co8fdZvtERl42Npo0bNhY9vb2RbpGkyZ+2rNnl6TslXRzGliCg08Z92na1K+ooZdI9iylf0uSunXrYVwlRJL69RuomTN/VVpamtat+1sPPDDMKjHlvB52dnZq3LhJic8XFnZJw4bdU+Lz5M5/5Lh8OTvv5OzsrCpV8v/boXr16jp9+pRiY2OUmpoqJyenQl+7Xr3r9x0HD+7TyJGjLe6XlpamY8cCjT/nlX+Ij4/X119/Lkl68smJ8vLyKnQsAAAAAICSK+91M7nZOp9z6tRJnT6dnSvIWTk2R79+A3TkyCGdPHlcZ8+e0e23Nyj2ddLT0zV37h/Gn9u0MV1pdf/+vXruuSeLff4c8+cvNXufc+paCqo5kLLrDs6ePWOcyLUo6tfPnV/YbzH/JUkxMdEKDT1n/DkiIv8VWIYOHaLw8DCL2267rZY+/PDTPFc7BgBYB/8KA8BN4GpqvCZteVlbL2xWSkZywQdUUJXsK+uu2t31SbfPVMXJdrNfJiYmatGi+ZKkJ5540uwmPEeNGjX12GP/0meffayNG9fptdfeNM5OGB0dJSl71of8bqQrVaps8kV9eTBs2EiT5pUcnTt3VY0aNRUeHqbY2Bi98srrJs0rOQYNGqJvvvlSqakpOnz4gFkDi7Ozc74rVxgMBk2c+ILWrFmppKQk7d272+JNbN269fTssy/p008/UlDQSf388/d68smJ+uCDt3Xt2lU5ODjonXf+Y/XXNzExwfg492wSljg7X48tJ3FTVM7Ozpo69QutXr1Cs2ZN19y5v2vu3N9N9unevadGj35M/v7NLJ4jPj572daEhGv69tuv5OrqqvHjn1GvXr3l6uqmM2dO69dff9SOHdsUGnpOb731mn74YXqx4t28eYMMBoNGjXrUZPzcuRB99tnHysrKUuPGTTR69FjVrl1HERHhmjfvD61bt8ZsNR9Jat68pWrVqq2LFy/o9OngIheaJCYmGh8XtKJK5crXtycmFu/9OnTogJYvXyx7e3u9+uobMhiKVhRrGm/+n6/c8Rb38wXAdlrf5q/t8aZjZ64dkzTQJvEAtwLHa7crzc10BrEsmTecFFV4+CUtXvxnHs0rDhox4lGbzv4P3IrIs1hXYfMstWrVKpU8S3kXExOjM2eC9csvPygo6KSk7OaVVq1am+2b07wiSd7ePkW+lre3t/FxfPz1c8XFxRkfe3l5y5p27dqu2NgYSdlFH7nVq1dffn4BOnHimFavXmG1Bpac18PV1a1ITR62kJMXKCgnIN2YF0gs0nOrW7ee6tatp9DQc9q5c7sOHTpo8TM6d+7vJp/T3Hmx3L777itFR0epefOWuuee+wsdBwAAAADkuFnzObm/L87Kyqpw+ZzSqpspT3JWjq1UqZJ69Ohlsq1Xrz766qvPlJaWptWrV+ipp54t8vmTkpJ04sQx/frrTzp69Iik7NexV68+JQ++kHLu34uSXyhOjUTLlq1VpYq7rl6N14oVy/Tgg8NVp05ds/1+/vl7ZWRk5Iov0Wyfgtjb2+vxx8dr2LARVl9tGABgjgYWALgJTNryshYEzbN1GFaxIGieDDLo294/2SyGgwf3G5emzKv7P0erVm0kZc+McPLkcbVu3VaSjEtsXr0ar61bN+muu3qUVbilrnfvvnlua9iwkcLDw2QwGNSrl+X9KlWqrDp16uj06WBdunSxwOulp6crOjpKiYmJysy8fkPq7u6hmJhoBQefyvN9uPfeB7Rz5zZt27ZFc+f+roiIMB08uF+SNHbsE/LzC8jzug88MEw9e+b//hbEwcG8oSI1NdX42FLDRW6OjtcLB1JSUoodx/HjR/X336vyfL3/+WePPD29VKdOPbPVbCQpOTk7wZeWliY7Ozt9/PHnJrN7+Pn56+OPP9drr72gXbt26PjxY9q0ab2GDStawcH586G6cOG8mjVrYTbDx9y5vys1NVV16tTV99//amw8atrUT507d9Wzz47XkSOHLZ63efOWunjxgoKCThS5gaUo71fuQo/ivF9paWmaOvVDZWVlafjwh4s1S0zx4715krjAraJj/QB9e8J0LNJwVJmZUhEn3gZQSPbJ1cwaWKo5VyvROSMiwrRoUd7NK8OHPyp3d48SXQNA0ZFnsa5bPc8yffrPea4AW7lyZd1774N5Fjvk/rLexSX/SRcsyV2EkJBwvbHAdPIN6xaJ5BSB+PhUVbt2Hc229+07QCdOHNOxY4E6fz7UYlFDabtetFH019iSatV8NXPm3BKfp2bNWmZjqanZ+YjCzCKaO29QnDzGE088pbfeel2ZmZl67bXnNX78M+rRo5c8PDwVFnZJixbN1/z5c+Xo6Ki0tLQ8r3Pw4H6tWLFU9vb2euWVok/mAQAAAAAS+Rxru1XzOenp6Vq7do0kqUuXbnJ1Na2vcHf30J13dtHWrZu0du1qTZjwjOzs7PI9Z365ISl7cpEpU/5rNvGEv3+zUskvWFplJafuoKCaA+l63UFOTqIoKleurEcffVzffvulkpISNXHieD311LPq1KmLXFxcde5ciGbPnqm//151Q34h//qGzz//RunpacrMzFJ8fJwOHz6oxYsXasaMXxQaek4vv/y6XFwKbs4BAJQdGlgA4CbwT/huW4dgVXvCd9n0+idOHDM+vvfe/oU+Lioqyvi4a9ducnOromvXrmry5FfVpk07delyl1q1aqvGjZvIvhxXntapUy/PbW5uVSRJHh6ecnfPe7aPnP3ymhUhPT1dS5b8pTVrVurUqZPGm1BLcs/iaMmkSW/p+PERioqK0vr1ayVlz+IwevRj+R7n5eVdJrOM5k4q5Pe8srdfb0aoVKlSsa63ceM6ffDB20pNTVXDho01btwEtW7dRi4uroqICNeGDWs1Y8YvWrLkLx06dEBffvmdqlY1LcR0cnIyrtDRuXNXs6VpJcnOzk5PP/28du3aIUlav35tkRtYcpbZbd68hdm2HTu2ScpuPLpx1RwHBwdNmDBREyeOt3jenMRXzgyuRXHj+5Xf+5C7eaQ479fMmb/q3LkQVa9eQ2PHWn4uBSnK58s03vI1aw2Agvn7mM9kleETqPPnpQbFX40cQBGVpMAyMjJCixbNU1ZWptk2e3sHDR/+iDw8PEsQHYDiIs9iXbd6niU/jRs30bBhI/JsRsj9RXtxZrlMSrqel3F1vT7zZO5ZKJOSrDfhQXx8vLZv3ypJ6t27n8UCjz59+unbb79URkaGVq9eoSeeeKrM43JxcdXVq/Gltnqpg4NDsSatKAwnp+x8RHp6eoH75s4bFCeP0bNnb40bN0HTpv2ohIQEffHFVH3xxVSTfdzdPTR69Bh9993XkmRWHJKammqczGPYsJFq1KhxkeMAAAAAAIl8jrXdqvmcPXt2GVeO6dt3gMV9+vUboK1bN+ny5Qjt379X7dubT9BRGDVr1lLPnr00cuQjFmtXnJ2dyzC/4KTk5OQCaw6k63UHOTmJohoxYpRCQ0O0bNliRUVd0X/+847ZPjVr1lLfvv3122/TJKnAFVTq1jWta2rbtr0eeOAhvfzyRK1Zs1LBwaf0/ffTaGIBABuigQUAbgIdatyhc/Ehtg7DajrWuNOm14+JKXoRvGQ6A4CHh6c++eRzvfvum4qMvKz9+/dq//69krILBtq166hBg+5Rly53lUrMpenG5oHccgoL8ttHul7ol3uJzxzx8XF68cWJOnnyeKHiKWgWBy8vL02YMFEfffSepOwigbfeet9myQ7TIpD8lzXNXSRSnFk+o6Oj9NFH7yk1NVW3395AP/zwq8l5atWqrUceGSt//2Z68cVnFBJyVl98MVUffvjpDTG7GIs0OnTI+/evQYOGqlbNV5GRl00SVoWVk6y67TbTGUSvXbumqKgrkrJXU7GkefOWsre3t/iZyvm8FafANHfCIikpKd+CjuTk64UsRZ359ty5EP3++wxJ0osvvlrsWV1N483/85U73tKaRRaA9dR1ryf7TBdl2OX6Xa92TEePZ6hBg/xncgJQXOarpBRXZORlLVw4R5mZlppX7PXQQ6Pl4eFVatcDUDTkWazrVs+z3HffUD3wwFBJ2XmSy5cva9Om9VqzZqWOHDmsZ5+doJ9++k1eXub/X/D09DQ+zimeKIro6GjjY3f36+fy8PDItU/Rz1tc69f/bSyM6NfPchGIl5e3OnS4Q7t27dDff6/Sv/71pNn9fu6fLa1yZknu/W48n4eHh65ejVdCwjWlpqaazXhanuTkBQrKCUg35gWKV7AxduwTatmytX7/fYYOHTpgLFqpVKmSevTopSeffFaHDx807l+liumENzNn/qrQ0HPy9a2uceMmFCsGAAAAAJDI51jbrZrPyVk51sPDQ3fe2dniPp0732VszFm9ekWBDSy5c0OSQZUqVZKHh6fc3NzyPa4subi4Kjk5uUj5heKsDixl52EmTfq3Ona8U3/+OVvHjh011n24ubmpb98BeuKJp7VkyULjMVWqVCnyddzd3fXmm+9p9OhhOn36lGbNmq4JE54pVswAgJKjgQUAbgKf/F97dx5f85X/cfydRSILIkisQSyx70vta9GVlhatVqmii7ao0amfDjqtaU03Zaa0tXXRlqK2KoJYi8SW2NcSS4QI2SPJ/f2RyW0iN3tukq/7ej4e85hv7vd8v+fcONLct+/nnK4fy0522h66TQnJRbcqYlFzdiitrtW7619d/12s40hJ+esB+QULvstyFcx7VarkneHr5s1b6scfVyogYIv27Nmlw4cP6vr1MMXExGj79q3avn2r2rXroP/+d67c3bNfPeB+8vnn/zYXr3Tp0l2PPPK46tatp/Lly8vJydn8EMGTTz6i69fDcnwQISkpSStXLs/w9cGDQapSpWq21926FaFbtyKybZMTR8dSmVZ2qFTpr91NwsOvZ3v99evXzMfe3t7ZtLRs8+aN5sKT554bmWWRQps27dS6dVsFBu7Tjh0BunPnToYddLy8vM3FJTmNw8vLW+Hh1/O120lMTOoWw/euzBEbG2M+TttN5V6Ojo4qV87D4oM116+HSVK+dtRJ//c2PDwsw8NBWfVjZ2eX6e97Tn766XvdvXtXVatWU3x8vDZv/j1Tm/Pnz5qPDxwINL/XTp26mv9sM443p/kVZj7Oz/wCULzs7ezlpUa6qsC/XiwVr93Hz+mxR/yKb2DA/cwu8++d+dl/JSUlRStX/pRt8Yo1dgIEkHvkLEUrp5ylXDkX2dvbKyUlRbdv//XAfX5zlg8+mJXjwhtFqXz58hlWy6xXz0+dOnVRq1Zt9P7703T16hV9+OF7+te/Psl0bcWKleTh4aHIyEidPXtaycnJeVqw49SpE+bj9DtfpD8+depkXt9SvqU9BCJJI0cOy7H91atXdOjQgUw7xabPFRISsl/4JE36Yo7SpTPmJ3Xr1lNo6CWlpKTo9OlTaty4Sa7umZWkpCRdvHihQPeQUlcfvTfr8fLy0rFjqYtwREVFZftAR1hYai7g4VG+QEU5rVu3VevWbZWYmKibN2/IZDKpUiUvlSpVSpJ06dJFc9vatTNuF/n994slpWZTu3Ztt3j/tD+b+Pg4c15SvrynWrdum+8xAwAAALj/3K95zr2LNBglz8mKkfOc6Oho7dyZ+tn19u3b6t495yKigICtmjjx7WwXlLw3G8qtuLg4Xb16Oc/X3cvHp1amP79KlbwUEXEzx2cOpL+eO/DyKtgzBz169FaPHr0VHx+vmzdvyMHBUZUqVTJnXaGhl8xta9euk68+atWqrerVfRQaelFbt/pTwAIAxYgCFgC4D5RxKqu5vecX9zBsRtmyf61C6eFRvkAfwpydndWnz0PmrUWvXLmsPXt2avnyn3Tp0kXt27dHn3/+maZMmVLgcRtBTEy0/P03SUrdbvXdd9/Lsm1UVFSu7rlo0dc6fvyopNRVOmJiYvTZZ/9WixatMu30kd6KFcu0cOFXeRh9ZpUrV9Hy5WsyvObq6iYvL29dvx6mP/+8kO316c/XrFk7z/3/+ed587GfX4Ns2/r5NVRg4D6lpKTo0qWLGR7GqF27jo4fT91RJTk584OW6aUFVfnZ4SataObe4pf0u9bcuBGuatWqZ7o2KSnJYtFMSkqKDh8+KElq2LBxnsdUq9Zf3/c//7ygevWyfig87c/Ly8s7zzuapK0we+XKZU2blvPf90WLvjYfL1u22tzfvePNTkHnF4Di51umoa7GBGZ4LejSUUkUsADWYLFsOh87vNnb26tjx27avn3zPa87aNCgYSpfvkL+Bgig0JCzFK2cchZPTzc5ONgrOTlFEREx916eQW5ylvnz5+r11ycW/hspZA899Kh27dqubdu2aOfO7QoK2p/pgX07Ozs1bdpCO3ZsU3x8vIKC9qtdu9ytwBodHW3+vFyuXLkMhQW1a9cxF8YcOXJQMTHRcnOz7qqfly5d1NGjwXm+bsOGdZkKWNIvypHbHWTSFu6ws7PLtMJpixattG3bFknSnj07C1zAEh5+Xc8/P6RA95Ck2bO/VKtWbTK8VquWr6TUsf755wU1adLU4rVJSUm6ciX0f9cUTibg5ORkccGYkyf/KpS6N5tJy0PWr1+j9eszZmj3ioyMNGcmLVq0ooAFAAAAQAb3a56Tl1ykKBX1czMlIc/ZsmWTEhNzt1BGmri4WAUEbFG/fo8U+niOHz+q118fW+D7LFu2OtPn+Vq1auvkyeOKjo7WzZs3slxo9MaNG4qJSZ2XhfXMQenSpS0+E5K2EK6Tk3OGxVfyqnx5D4WGXlRY2NV83wMAUHD2xT0AAABKCrtcPnxWv/5fD4UGBx8u1DFUrVpNAwcO1tdfLzF/wN+wYUOh9lGSXbp0SUlJSZKknj0fzLLdn39eyNVWpSEhR/TttwslSe3aPaDPP/9Sjo6Oio2N0XvvvWvedrSoNWvWQpJ08eKfunnzRpbtDh06YD5u2rR5nvtJX0SSnJyUbdu07/u910mpq56kuXIl+xU80s5XrFgp23aWpD2smbYCaBp3d3dVqJB6LiTkiMVrjx4NtriKub//Rl2/HqaaNWvl64GMtD8rKeOfx71u3rxhXlE0P39WhaVq1Wrm731245VkflCpUiWvHHckAlAytaiSuTDv1K2QYhgJYCsyl7DY56OARZKaNGmm7t17/3Ufe3sNGvSM+XceALgflNScZcuWzTlcVXKMHv2q+TP6vHlzLbZ5+OFHzcfLl/+Y63uvXr3CvDtJv36PZvjzsrOzU79+qfeNi4vTmjWr8jr0PEu/+8pbb72tadPez/Z/aYU627b5KyEh48q66R9iSHu4ITtJSUk6d+6MpNQHNO5ddbRXr75ydk7d1WXNmlXm3W5Loow5RlCW7U6cOG5+H9bMMWJjY7Rv3x5Jqb//eHtXtlpfAAAAAICCI8/JWlp2UaFCxRxzi2nT3k/3zM+67G5bIuX2OYn02YM184XQ0Es6ffqUJKlr1+653vHHkvDwcEmSi4troYwNAJA/7MACAMD/ODk5mY/v3k3Msl2bNu1VunRpxcfHa/nyH9Wz54O5/hCfW25u7mrQoJGuXw/TrVuZd5VwcnJWYmKCeZXC+0X6gpL4+KwfBli16pcc7xUbG6sZM6YqOTlZ5cqV0zvv/EMVK1bSqFFj9eWXcxQcfFjffbdIw4e/aPH6F18coxdfHJP3N5ELXbp01+bNv0uS1q9fq+eeeyFTm/j4eHMIU6uWr3x8aua5nypV/tph5vDhQ9luO5tWzGBnZ6cqVapkONe5c1c5OjoqKSlJ27dv1dChwyze4+DBIN2+fVtSxqKX3EoLuQID92U698ADnbRu3WotWvS1unXrmWF74OTkZH311X8zXXP69El98slHkqSRI0fneTyS5ONTU7Vq1daFC+e1ZctmvfbaeItbE69fv9Z83LVrjzz3M2XKNE2ZMi3bNt98M8+8K5ClVVal1D+/zp27adWq5frzzwsKCQm2uNpqSEiweQeWzp27FfrPMABFo2PdBpp7JuNr10xHi2cwgI2yU/7/G9qoUTPZ2dlr586tGjBgcL4KgAGgJCupOcvt25EWxloycxYfn5rq0aO3Nm/+XceOhWj//j/Utm3GHVY6depq/ty6e/dObd78u3r37pvtfUNDL2nhwtSdPZ2dnfXUU0MztRk8+BmtWrVc8fHx+uabeerQobNq1qyV45hTUlK0efPv5lVTc8NkMmnjxt8kSb6+dTRgwKAcr3Fycta+fX8oJiZG27dv04MP9jOfK1/eU76+dXTu3FkFBe3XrVsRKl/eM8t77dq13bxaaOvW7TKdL1++vB577AktX/6jbt68odmzP9bkyf+Xq/d25swZ3b2bqIYNG5lfq1KlqnbuDMzmqvxr2bK13N3dFR0drQ0b1unZZ4db/Pv0229/7XbStWt3q4xFkr79dpG5UOrJJ5/KdD4334dBgx7TtWtXLe50DAAAAAAoXOQ5ll25ctlcqNO9e88csxdJOno0RMuWLdWBA4EKD7+uSpW8CnVMrVq1sVq+0LlzV3388b+UkpKidevWqFevPhbbpT0nYW9vr86du1plLJL09ddfmo8t5Qu5dfz4UV27lrrziq9vnQKPCwCQf+zAAgDA/6Tf8vLy5dAs25UpU0ZPPvm0JCk4+Ihmz/7E4s4PaSIibmZaqXLv3j26cSPrnTeio6N1/HjqA6jVq2feGjNtrNmNM80338xT585t1LlzG61fX7L/kbd69ermUOO339bJZMq8yvXOndu1YsXPOd7rs89mmXcD+dvfppgfCHzmmefVokUrSdLChV/pxImcV+IsbN269VDVqqnFJd99t9Din+PcuZ8rKuqOJOmZZ56zeJ/169eY/2y/+WZepvMdO3Y2fz+XLFmg8PDrFu/z668rdOLEMUlS48ZNVa6cR4bz5cp56NFHB0hKXT3F0jyKjY3V7Nkfm78eMGCgxb6yU6VKVfn41FRo6EWdPZvxiewhQ4apVKlSunTpol555UX5+2/SqVMntGvXDk2YME6HDh0wh2mnTp3QnDmfaezYkYqKuqPHH38iy0AlN4YMSS3YuXPntv7zn88znb98OVTffZe600/16jWyfPBj0KDHzH9e1vT000PNK/R+9tmsTCvRJiTE67PPZklK3W3n6aczP6gEwBiaeTfK9FpCuWBFRBTDYABbYJf5d9OCatiwiV588dVC/4crACgJSmrOYmkHypKcszz//AjzZ/vFixdkOm9vb6//+78Z5pUnP/hguvz9N2Z5vzNnTuuNN14272z72mvjVbly5l0xKlXy0vjxf5OUugvLa6+N1sGDWe/oIUnnz5/TxInj9MMP3+buzf3PoUMHdPXqFUlS9+69cnVN+/YdzCtlbtiwPtP5gQMHS5ISExM1c+Z7WT7Mcv16mL744lNJqZ+Rs3oIYsyYV807u65Zs0offvhPxcZmvTtwUlKSfvnlJw0ZMljXrl3L1XsqDKVKldKgQUMkSRcunNfSpZn/LEJCjmjt2l8lSS1atFLDhpl3dpRknueDBj1m8XxSUpIiIyOzHMvGjb/p++8Xm/tJX2QEAAAAACiZyHMs27Dhr+dXcptdpLVLSUnR779nzi5KsgoVKpo/x+/bt0dbt2beAWfLls3mXVf79n04w9xJc/nyZfn5+alRo4Z67TXLi47GxsZkm7F8990i8wKx/fo9kmF3mDTHjoXo5MkT2b6n8PDrev/9aeav+/V7JNv2AADrYgcWAAD+p359P/MKDV999aUcHR3l7V1F9vap9Z6VKlWSs3PqzgujRo3VoUMHdOxY6ooJBw8G6bHHBqhevfpycXFRVFSUzp8/q8DAffrjj93y9a2rxx4bYO5r8+bfNXnyeLVt215t2z4gX986Klu2rGJjY3Xu3FmtWPGzudhg8ODBmcbatGkzXb16Wbt2bdeqVb+oWbPmcnJyliS5ubllu6pkSVaunIc6dOik3bt3au/e3Ro//lU98cQgeXtX0a1bEQoI2KLfflurKlWqKTo6SpGRmXenkaSAgK3m0OHhhx9Tt249zefSHux44YUhio6O1owZ/6eFC783/9kWBUdHR40fP0mTJ09QTEyMXn75RQ0fPlINGzZWVFSU1qxZqW3btkhK3Zq1b9+H89VPzZq19PDDj2ndutUKD7+uESOe1dNPD1Xz5i3l6uqqsLAw+ftv1KZNGySlPqgxevQrFu/14otjtGfPToWFXdOHH/5Tx44dVY8eveTm5q7z58/q++8X68KF85KkAQMGqUGDzA9V50aPHr21ePE3WrBgnt5/f5b59dq1fTVhwmR99NH7OnXqpP7xj79nuO7BB/spMTFBAQFbNWfOZ5JSv88jR47WiBEv5WssaR566FGtW7dawcGHtWLFMkVE3NRjjz2hMmXK6Pjxo1q06BvFxMTI3t5eb7zxVoG2qy0MPj41NXToc/ruu0U6ceKYXn75RT377HBVq1Zdly+H6vvvF+vUqZOSUgu6atTwKdbxAsg/L1dvlbrrqbul0lWsVDilI8cS1KVDqeIbGHDfylzAUhgryqV93gCA+01h5Sze3p6Kjo7SqVOntX37jgLnLJYWXCjJOYuvb1117txVO3YE6NChAzp8+JCaN2+RoU2DBg01deoM/fOf/1BiYqL+8Y939OuvK9SnTz/5+NRSqVKlFBZ2TTt3btemTRvMO+AOGTJMTzyR9W4njzzyuMLDr+vrr7/UrVsRGjdujNq1e0CdO3dTrVq15e7urjt37ujSpYvas2en9u7do+TkZNWtWz9P73HDhnXm4+7de2bT8i/Ozs7q0KGTtmzZpMDAvbp580aGByUefbS/Nm/+XQcPBmn37h164YWh6t9/oPz8GsrV1UWRkZE6dOiAVq5crjt3UneTHTHipSx3wHVxcdGHH36qt956XZcuXdSaNau0c+d29enTTy1atFKFChVlMkk3b97Q4cMHtG3bFoWFFV3hSnrPPPOc/P036tKli/rPf2YrNPSSevfuKycnZx08GKglSxYqOTlZzs7OeuONifnuJzo6WgMHPqKuXXuoXbsH5ONTS/b2drp8OVSbN/+unTu3S0p9yGjq1Bns/goAAAAABlBSn5sp7jwnrQClfHlPNW/eMlfXNG3aTBUqVNTNmzf0++/rNWzYC4U2nqIwevQr2rt3jyIjb2natCk6ceK4OnbsIknavXuHfvzxO0mSh0d5vfTSy/nu5+LFP/Xmm6+qR49eatOmnapWrabk5BRdvHhB69ev0aFDByRJfn4N9eabkyze48KF8/rgg+lq2rSZOnbsqnr16svDo7wk6caN6zpwIFDr169RdHS0JKlNm3Z6+GHLC3YAAIoGBSwAAPyPq6ubBg0arB9+WKJTp05o/PjXMpyfPftLtWqVunOCk5OTPvtsrt5/f5oCArbqzJlT+vTTj7K8t5ubW6bXkpKStGfPLu3ZsyvL6wYMGKhhwzLvvjF06DBt2+avxMRE/fvfMzOce+ihRzVlyjTz1wkJCebjsmXLZdlXSTFx4ts6e3aUwsKuKTBwnwID92U47+1dWTNn/luTJr1h8fobN27oo4/+KUmqWrWaxQ+wlStX1oQJkzVjxlRdvPinvvjiM7311tuF/2ay0aFDZ7311t/16acfKSLipj79dFamNg0bNtYHH/zbvJtGfkyc+Lbi4+Pk779JkZG3NH/+fyy2c3Fx0aRJU8xz/F7ly5fXxx9/ocmTx+vy5VCtWrVcq1Ytz9TukUce15tvvpXv8Q4e/IyWL/9RAQFbtXfvHrVv38F87rHHBqhatepasmSBjh07KpMpRT4+tfT440/o8cef0LRpU+ThUV7Vq9dQq1Zt9PjjT1pcRTavHBwcNHPmx5o06XUdP35M27ZtMRcYpXFyctL48X9Thw6dCtxfYRg9+hXduhWhdetW/6/g551MbR59tH+BgiQAxc/Ozk6VTI11RTv+etE+WQEhJ9WlQ5PiGxhw37JQwKKsH8S8c+e21q1bqcceGyh39zLWHBgAlEglNWdJ250ivZKeszz//Ejt2BEgSVq8+Gt98smcTG169eqjChUq6t//nqkLF87rwIFAHTgQaPF+ZcuW05gxr6p//ydz7PuFF0apdm1fzZnzma5evaJ9+/7Qvn1/ZNm+dm1fvfLK67l8Z6m7hG7b5i8pdUEGX9+6ub62e/de2rJlk5KTk7Vx4wYNHTrMfM7BwUH/+tfH+uc//6EdOwL0558XMuwcm56Dg4NGjHhJw4e/mG1/1apV17x5C/X55x9r06YNunUrQj/99IN++ukHi+0dHR01ZMhQtW/fPtfvqTC4urpp1qzP9dZbbyg09KJWr16p1atXZmjj5uamd9/9p+rV8ytQXwkJCdq0aYN5cZR7NW3aXP/4xz/l7V3wfAYAAAAAYH3kOZkdOXLIvMtL167dc70olb29vbp27aGVK5fp/PlzOnHiuBo0aJinvouTt3dlffjhp3rnnYm6efOmvv9+sXmn1TQVKlTQBx98LC8v7wL1FR0dpTVrVmXapSdNp05dNGXKdLm7u2d7n+DgIwoOPpJtm4cffkwTJkxmcTEAKGYUsAAAkM7LL49TjRo+2rBhnc6fP6eYmGjzqpT3cnV10/vvz9Lhw4e0YcNaHT58UDdu3FBCQrzc3NxVrVo1NWzYWB06dFa7dg9kuHbcuAlq27a9goL26+zZM7p584YiI2/J3t5eXl7eatKkmR59dICaN29h8UNTvXp++vLLBfrhh28VHHxYt25FKDEx0eI4jx4NliTVqOGjjh07F/A7ZH3e3pW1YMF3+v77xdqxI0BhYdfk5OSkypWrqkuXbnrqqaEqW7asxWtNJpM++GC6bt++LQcHB7377ntydXW12LZPn4e0e/dObd78u1atWq5OnTqrQ4ei/f48/vgTatKkqZYt+0lBQft048YNubiUVs2atdWnTz89+uiAAu/m4eTkpOnTZ6p//4Fav36Njh4N1o0b4UpMTJSbm7t8fGqqTZt2evzxJ3IMFWrVqq1Fi5Zq5crl2rbNX6GhlxQXF6vy5T3VtGkz9e8/MMsCmNwqW7acnntuhL78co7+8Y93NH/+ogyrn7Zq1SbLPqZP/6BAfWfHw8ND//3vAq1Zs0qbNm3Qn3+eV1xcvCpWrKjWrdvpqaeGyNe3jtX6zyt7e3v9/e/vqnv3nlq9eqWOHz+m27cjVa6chxo2bKTHH3+yxBTbACgY3zINdSVhR4bX9v8ZIokCFqCwmSwUsNhnsZJ4VNQd/fjjEiUl3dXSpYs0ZMhwlSlj+XdYALifFUbOkpiYIHd3d9WoUUP16jUocM5iSUnPWRo2bKy2bdtr//692rfvDx0/flQNGzbO1K5Fi1ZavPhHbdvmrx07AnTixDFFREQoKSlJHh4eqlXLVx07dlLfvo+oTJncF1d269ZTHTt20dat/tq7d5eOHz+mW7duKTY2Rm5u7qpcuYoaN26qHj16qWXL1nnaaWP79m2KiYkx95MXHTp0krOzsxISErRhw7oMBSyS5ObmrpkzP9bBg0H6/ff1Cg4+rBs3whUfn5rdVa1aTa1atVb//gNVrVr1XPVZtmw5TZ06Q889N0L+/hsVFLRfV69e0e3bkbK3t1e5ch6qW7eeWrduqwcf7Kc6dWrIwcFeyckpeXpvBVW9eg0tXPi9Vqz4WVu3pmY4SUl35eXlrQ4dOumpp4aqcuUqBerD3d1db7/9fwoM3K9Tp04oIuKmEhMTVb68pxo2bKRevfqoe/de7LwCAAAAAAZTEp+bsaSo8pz87Bybvv3KlcvM9zFSAYskNW7cRIsX/6Rly5Zqx45tunr1qiSpatWq6ty5m55+eqjKlfMoUB8+PjU1fvzfFBS0X+fOnVFERIRSUpLl6VlBTZs2V9++D2eaO/fq1etBlSlTRkFBgTp16oRu3AjXrVupmZibm7uqV69hvlfduvUKNF4AQOGwM5lMmf/1Hfet8PCoAl3v6elm/seWiIiYQhoVUDSYvzCqgszdhIQEPfRQDyUmJmrKlGl66KFHrTRKILP8zl2TyaR33pmkHTu2ydOzgt5//yM1bdo819cnJiYqOjpKnp4V8j5o4H/4vQFGMX3dAs39880Mr9W9+nedmPvPAs/dSpXYMQL3n4LkItX/2UWJnoczvHbqhSvycM244ld0dLSWLl2ou3fvml9LXYF9uCF2RMT9i99vYFQlae6SsyCvStL8BfKCuQujKsy5Sy6C+1FBnxeR+G8EjIu5C6Ni7hYceU7xYf7CqJi7MCoj5SLsgwUAwH3s2LEQJSYmqlq16urT56HiHg6QK3Z2dpo6dYaaNWuhiIibev31sZo793Pdvh2Z7XUpKSnasWObhg8fotdfH6uoqIL/QwwAlHSd6mVeqelKckgxjASwAXY5rwETGxutpUsXZShekaSkpCStWLHUWiMDABQRchYAAAAAAABjIc8BAKDkcSzuAQAAAOs5fPigJOm550bIwcGhmEcD5J6rq6s+//y/+vDDf2rDhnVauvRbrVq1XG3atFf79g+oSpVq8vAor/j4eN24cV3BwYe1a9cOXb16RZLUvHlLxcXFqkwZVskDcH9r49Mg02uxbsGKjy+GwQD3vcwFLHayMx/Hxsbqhx8W6e7dxMzt7OzUuzf/MAYARkfOAgAAAAAAYCzkOQAAlDwUsPzP5cuX9e2332rbtm26du2anJycVKNGDT300EN69tln5eLiUij9BAQE6Oeff1ZwcLAiIiLk6emppk2b6umnn1a3bt0KpQ8AANK88MIovfDCqOIeBpAvpUqV0v/933T17Pmg5s2bo7Nnz2jHjm3asWNbltd4eXnr2WeH64knBsnens0GAdz/PEqXl1N8NSWWvvzXi+Uv6PDxKNWryc9B5B65SG5YKGCxSy1giYuL1Q8/LFRiYubiFclOjzzyhKpXr2nl8QEArI2cBQAA4P5ELgIAwP2LPAcAgJKHAhZJW7Zs0aRJkxQdHW1+LS4uTrdv31ZISIiWLVum+fPnq2bN/D9okJKSoqlTp2r58uUZXg8LC1NYWJg2b96sp556SjNmzOBhSwAAgHQ6duysBx7oqEOHDmj37p06fPigbtwIV2TkLZUu7aIKFSqqSZOmat++g7p06S5HR37FBWBbKqY00hVdzvDalpBjqlezSTGNCEZDLpJ/dnZ2io+P+1/xSoLFNo880l8+PrWKdmAAAAAAACBXyEUAAAAAAChaNv9037FjxzR+/HjFx8fL1dVVY8aMUfv27RUfH6/169fr559/1oULFzR69Gj98ssvcnd3z1c/n376qTmMaNSokUaNGqUaNWro0qVL+vrrr3Xs2DEtW7ZMnp6emjBhQmG+RQAAAMOzt7dXq1Zt1KpVm+IeCgCUOLXdGumKaVOG1/b/GaIxooAFOSMXyQO7zDuwJMTH6edfflRCguXilYce6q+aNX2tPTIAAAAAAJAP5CIAAAAAABQ9my9gef/99xUfHy9HR0ctWLBALVu2NJ/r0KGDatasqVmzZunChQtauHChxo0bl+c+zp8/rwULFkiSmjRpou+//16lS5eWJDVr1kw9e/bUsGHDFBISom+++UYDBw4s0OodAAAAAADb0dS7oXZdy/jayYijxTMYGA65SF5kLGBxlKNW/bJUiVkUr/Tt+5hq165TFAMDAAAAAAD5QC4CAAAAAEDRs+m9R48cOaLAwEBJ0sCBAzOEEWlGjhypOnVSHzZYsmSJ7t69m+d+Fi9erKSkJEnS1KlTzWFEGhcXF02dOlWSlJSUpEWLFuW5DwAAAACAbepcv1Gm164kUcCCnJGL5I0pXQGLgxz0tJ7OsnilT59HVadOvaIaGgAAAAAAyCNyEQAAAAAAiodNF7Bs3rzZfDxw4ECLbezt7TVgwABJ0p07d7R379489WEymeTv7y9J8vX1VYsWLSy2a9GihWrXri1J8vf3l8lkstgOAAAAAID0OtarL5nsMrwW5RqilJRiGhAMg1wkj+xSx5RWvFJf9S02e/DBh1W3ruVzAAAAAACgZCAXAQAAAACgeNh0AUtQUJAkydXVVY0bN86yXdu2bc3HBw4cyFMfoaGhun79eqb7WNKuXTtJUlhYmEJDQ/PUDwAAAADANrk7u8opps49L15TyLmbxTMgGAa5SN7Zy16DNEh+8rN4vnfvh1SvXoMiHhUAAAAAAMgrchEAAAAAAIqHTRewnD17VpLk4+MjR0fHLNv5+vpmuia3zpw5Y/E+OfVz7ty5PPUDAAAAALBdFZIbZXot4PiJYhgJjIRcJG/sJA3SIDVUQ4vne/bsq/r1LZ8DAAAAAAAlC7kIAAAAAADFw2YLWBISEnTr1i1JUuXKlbNtW65cObm6ukqSrl27lqd+0rfPqZ/0569evZqnfgAAAAAAtquWa+YClgOhx4thJDAKcpG8MylFcYqzeK5HjwfVoEHWq7UCAAAAAICSg1wEAAAAAIDik/UyEve5mJgY83Fa2JAdFxcXxcbGKjY21mr9uLi4mI/z2k9ulS/vKjs7u3xfb29vZ/5/T0+3whoWUCSYvzAq5i6MirkLI2P+wmja1WqmPZczvnYj4TrzF1kiF8k7OzlordbKJJPaqI359YcffkStWrUqrCECVsPvNzAq5i6MjPkLo2LuwqiYu8gtcpH84+8ZjIq5C6Ni7sLImL8wKuYujMpIc9dmC1gSEhLMx6VKlcqxvZOTkyQpPj7eav2k9ZGffnLL0dGhUO5jZ2cnB4eCBRtAcWH+wqiYuzAq5i6MjPkLoxjbt7c+n1daKvXXZ8mmVRvIwcFmN15FDshF8q6GfTud1XGt1VqlKEUtTS3V/5H+atu2Tc4XAyUIv9/AqJi7MDLmL4yKuQujYu4iJ+QiBcffMxgVcxdGxdyFkTF/YVTMXRiVEeauzRawODs7m4/v3r2bY/vExERJUunSpa3WT1of+eknt5KSkgu8A4udnZ1MJpN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" ] }, "metadata": { "image/png": { "height": 547, "width": 1624 } }, "output_type": "display_data" } ], "source": [ "evaluate_model(model_4, train_features_3, train_target, test_features_3, test_target)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "great 47\n", "good 42\n", "bad 38\n", "excellent 38\n", "waste 34\n", "love 33\n", "awful 32\n", "perfect 28\n", "wonderful 26\n", "terrible 26\n", "boring 24\n", "poor 24\n", "life 23\n", "nothing 23\n", "script 22\n", "dull 22\n", "poorly 21\n", "disappointment 21\n", "see 20\n", "fail 20\n", "dtype: int32\n", "\n", "features never used: 58527 of 59139\n" ] } ], "source": [ "importances = pd.Series(model_4.feature_importances_, index=tfidf_vectorizer_3.get_feature_names())\n", "print(importances.sort_values(ascending=False).head(20))\n", "print()\n", "print('features never used:', (importances == 0).sum(), 'of', len(importances))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Reusing Model 3's exact features and changing only the classifier isolates the effect of the model itself. Test F1 drops to 0.86 from 0.88, with substantially longer training time. Feature importances show LightGBM identified sensible sentiment words such as \"great\", \"bad\", \"excellent\", and \"awful\", but split on only a few thousand of the 59,139 available features, leaving the vast majority untouched. Gradient boosting excels at feature interactions on dense tabular data, whereas sentiment is close to additive over words and the matrix is extremely sparse. The linear model is both faster and better suited here." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "Very good job! \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 9 - BERT" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "import torch\n", "import transformers" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertModel: ['cls.predictions.decoder.weight', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight', 'cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight']\n", "- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", "- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n" ] } ], "source": [ "tokenizer = transformers.BertTokenizer.from_pretrained('bert-base-uncased')\n", "config = transformers.BertConfig.from_pretrained('bert-base-uncased')\n", "model = transformers.BertModel.from_pretrained('bert-base-uncased')" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "def BERT_text_to_embeddings(texts, max_length=512, batch_size=100, force_device=None, disable_progress_bar=False):\n", "\n", " ids_list = []\n", " attention_mask_list = []\n", "\n", " # text to padded ids of tokens along with their attention masks\n", "\n", " for text in tqdm(texts, disable=disable_progress_bar):\n", " encoded = tokenizer.encode_plus(\n", " text,\n", " add_special_tokens=True,\n", " max_length=max_length,\n", " truncation=True,\n", " padding='max_length',\n", " return_attention_mask=True\n", " )\n", " ids_list.append(encoded['input_ids'])\n", " attention_mask_list.append(encoded['attention_mask'])\n", "\n", " if force_device is not None:\n", " device = torch.device(force_device)\n", " else:\n", " device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n", "\n", " model.to(device)\n", " if not disable_progress_bar:\n", " print(f'Using the {device} device.')\n", "\n", " # gettings embeddings in batches\n", "\n", " embeddings = []\n", "\n", " for i in tqdm(range(math.ceil(len(ids_list)/batch_size)), disable=disable_progress_bar):\n", "\n", " ids_batch = torch.LongTensor(ids_list[batch_size*i:batch_size*(i+1)]).to(device)\n", " attention_mask_batch = torch.LongTensor(attention_mask_list[batch_size*i:batch_size*(i+1)]).to(device)\n", "\n", " with torch.no_grad():\n", " model.eval()\n", " batch_embeddings = model(input_ids=ids_batch, attention_mask=attention_mask_batch)\n", " embeddings.append(batch_embeddings[0][:,0,:].detach().cpu().numpy())\n", "\n", " return np.concatenate(embeddings)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "10edc1a9a200403db12eca2f8096584a", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/500 [00:00" ] }, "metadata": { "image/png": { "height": 547, "width": 1624 } }, "output_type": "display_data" } ], "source": [ "evaluate_model(model_9, train_features_9, train_target_9, test_features_9, test_target_9)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pretrained BERT served as a fixed feature extractor, taking the 768-dimensional [CLS] vector for each review with no fine-tuning. Compute cost restricted training to a 500-review subset rather than the full 23,796, so this is not a like-for-like comparison with the TF-IDF models. Test F1 of 0.76 trails them substantially, and train F1 of 0.99 indicates severe overfitting from 768 dense features on only 500 examples. ROC AUC of 0.85 confirms the embeddings do capture sentiment signal, with the F1 curve peaking at 0.78 near threshold 0.35. The limitation is sample size, not the representation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "Well done! \n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## My Reviews" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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0I did not simply like it, not my kind of movie.i did not simply like it not my kind of movie
1Well, I was bored and felt asleep in the middl...well i was bored and felt asleep in the middle...
2I was really fascinated with the moviei was really fascinated with the movie
3Even the actors looked really old and disinter...even the actors looked really old and disinter...
4I didn't expect the reboot to be so good! Writ...i didn't expect the reboot to be so good write...
5The movie had its upsides and downsides, but I...the movie had its upsides and downsides but i ...
6What a rotten attempt at a comedy. Not a singl...what a rotten attempt at a comedy not a single...
7Launching on Netflix was a brave move & I real...launching on netflix was a brave move i really...
\n", "
" ], "text/plain": [ " review \\\n", "0 I did not simply like it, not my kind of movie. \n", "1 Well, I was bored and felt asleep in the middl... \n", "2 I was really fascinated with the movie \n", "3 Even the actors looked really old and disinter... \n", "4 I didn't expect the reboot to be so good! Writ... \n", "5 The movie had its upsides and downsides, but I... \n", "6 What a rotten attempt at a comedy. Not a singl... \n", "7 Launching on Netflix was a brave move & I real... \n", "\n", " review_norm \n", "0 i did not simply like it not my kind of movie \n", "1 well i was bored and felt asleep in the middle... \n", "2 i was really fascinated with the movie \n", "3 even the actors looked really old and disinter... \n", "4 i didn't expect the reboot to be so good write... \n", "5 the movie had its upsides and downsides but i ... \n", "6 what a rotten attempt at a comedy not a single... \n", "7 launching on netflix was a brave move i really... " ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "my_reviews = pd.DataFrame([\n", " 'I did not simply like it, not my kind of movie.',\n", " 'Well, I was bored and felt asleep in the middle of the movie.',\n", " 'I was really fascinated with the movie', \n", " 'Even the actors looked really old and disinterested, and they got paid to be in the movie. What a soulless cash grab.',\n", " 'I didn\\'t expect the reboot to be so good! Writers really cared about the source material',\n", " 'The movie had its upsides and downsides, but I feel like overall it\\'s a decent flick. I could see myself going to see it again.',\n", " 'What a rotten attempt at a comedy. Not a single joke lands, everyone acts annoying and loud, even kids won\\'t like this!',\n", " 'Launching on Netflix was a brave move & I really appreciate being able to binge on episode after episode, of this exciting intelligent new drama.'\n", "], columns=['review'])\n", "\n", "my_reviews['review_norm'] = my_reviews['review'].apply(clear_text)\n", "\n", "my_reviews" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 2" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.14: i did not simply like it not my kind of movie\n", "0.16: well i was bored and felt asleep in the middle of the movie\n", "0.54: i was really fascinated with the movie\n", "0.11: even the actors looked really old and disinterested and they got paid to be in the movie what a soul\n", "0.31: i didn't expect the reboot to be so good writers really cared about the source material\n", "0.47: the movie had its upsides and downsides but i feel like overall it's a decent flick i could see myse\n", "0.04: what a rotten attempt at a comedy not a single joke lands everyone acts annoying and loud even kids \n", "0.82: launching on netflix was a brave move i really appreciate being able to binge on episode after episo\n" ] } ], "source": [ "texts = my_reviews['review_norm']\n", "\n", "my_reviews_pred_prob = model_1.predict_proba(tfidf_vectorizer_1.transform(texts))[:, 1]\n", "\n", "for i, review in enumerate(texts.str.slice(0, 100)):\n", " print(f'{my_reviews_pred_prob[i]:.2f}: {review}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 3" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.20: i did not simply like it not my kind of movie\n", "0.12: well i was bored and felt asleep in the middle of the movie\n", "0.49: i was really fascinated with the movie\n", "0.10: even the actors looked really old and disinterested and they got paid to be in the movie what a soul\n", "0.27: i didn't expect the reboot to be so good writers really cared about the source material\n", "0.50: the movie had its upsides and downsides but i feel like overall it's a decent flick i could see myse\n", "0.03: what a rotten attempt at a comedy not a single joke lands everyone acts annoying and loud even kids \n", "0.92: launching on netflix was a brave move i really appreciate being able to binge on episode after episo\n" ] } ], "source": [ "texts = my_reviews['review_norm']\n", "\n", "my_reviews_pred_prob = model_3.predict_proba(tfidf_vectorizer_3.transform(texts.apply(lambda x: text_preprocessing_3(x))))[:, 1]\n", "\n", "for i, review in enumerate(texts.str.slice(0, 100)):\n", " print(f'{my_reviews_pred_prob[i]:.2f}: {review}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 4" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.53: i did not simply like it not my kind of movie\n", "0.40: well i was bored and felt asleep in the middle of the movie\n", "0.60: i was really fascinated with the movie\n", "0.38: even the actors looked really old and disinterested and they got paid to be in the movie what a soul\n", "0.73: i didn't expect the reboot to be so good writers really cared about the source material\n", "0.61: the movie had its upsides and downsides but i feel like overall it's a decent flick i could see myse\n", "0.26: what a rotten attempt at a comedy not a single joke lands everyone acts annoying and loud even kids \n", "0.80: launching on netflix was a brave move i really appreciate being able to binge on episode after episo\n" ] } ], "source": [ "\n", "texts = my_reviews['review_norm']\n", "\n", "tfidf_vectorizer_4 = tfidf_vectorizer_3\n", "my_reviews_pred_prob = model_4.predict_proba(tfidf_vectorizer_4.transform(texts.apply(lambda x: text_preprocessing_3(x))))[:, 1]\n", "\n", "for i, review in enumerate(texts.str.slice(0, 100)):\n", " print(f'{my_reviews_pred_prob[i]:.2f}: {review}')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model 9" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.14: i did not simply like it not my kind of movie\n", "0.00: well i was bored and felt asleep in the middle of the movie\n", "0.87: i was really fascinated with the movie\n", "0.01: even the actors looked really old and disinterested and they got paid to be in the movie what a soul\n", "0.25: i didn't expect the reboot to be so good writers really cared about the source material\n", "0.90: the movie had its upsides and downsides but i feel like overall it's a decent flick i could see myse\n", "0.01: what a rotten attempt at a comedy not a single joke lands everyone acts annoying and loud even kids \n", "0.95: launching on netflix was a brave move i really appreciate being able to binge on episode after episo\n" ] } ], "source": [ "texts = my_reviews['review_norm']\n", "\n", "my_reviews_features_9 = BERT_text_to_embeddings(texts, disable_progress_bar=True)\n", "\n", "my_reviews_pred_prob = model_9.predict_proba(my_reviews_features_9)[:, 1]\n", "\n", "for i, review in enumerate(texts.str.slice(0, 100)):\n", " print(f'{my_reviews_pred_prob[i]:.2f}: {review}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", " \n", "Nice results! \n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "1) Models 1 and 3 both reach test F1 of 0.88, clearing the 0.85 requirement. The honest floor is not the dummy's 0.00 but 0.67, the score for labelling everything positive.\n", "2) Model 1 is the recommended choice. It matches Model 3's test F1 at a fraction of the cost, since spaCy lemmatization takes roughly 20 minutes of preprocessing to deliver no gain in generalization." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "3) Lemmatization reduced the vocabulary 17%, from 71,531 to 59,139 features, and narrowed the train/test gap by one point. With ~24,000 training examples, TF-IDF already learns reliable weights for inflected variants separately.\n", "4) LightGBM underperformed at 0.86 despite identical features. Sentiment is close to additive over words, so the interaction modelling that boosting excels at finds little to exploit on a highly sparse matrix." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "5) BERT's 0.76 reflects sample size, not capability. Trained on 500 reviews against 768 dense features, train F1 of 0.99 shows near-total memorization. ROC AUC of 0.85 confirms the embeddings carry real signal.\n", "6) Caveat on generalization. The source data excludes ratings 5 and 6, so every example is clearly polarized. Real-world performance on ambivalent reviews would be lower" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " Reviewer's comment \n", " \n", "\n", "Excellent, thank you so much! \n", "\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Checklist" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- [x] Notebook was opened\n", "- [ ] The text data is loaded and pre-processed for vectorization\n", "- [ ] The text data is transformed to vectors\n", "- [ ] Models are trained and tested\n", "- [ ] The metric's threshold is reached\n", "- [ ] All the code cells are arranged in the order of their execution\n", "- [ ] All the code cells can be executed without errors\n", "- [ ] There are conclusions" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.23" } }, "nbformat": 4, "nbformat_minor": 4 }