{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "tl;dr : *Crowd-sourcing raw scores for your COSYNE reviewer feedback.*\n", "\n", "Following that message:\n", "\n", "> Dear community, \n", "\n", "> COSYNE is a great conference which plays a pivotal role in our field. If you have submitted an abstract (or several) you have recently received your scores. I am not affiliated to COSYNE - yet willing to contribute in some way: I would like to ask one minute of your time to report the raw scores from your reviewers. I will summarize in a few lines the results in one week time (11/02). The more numerous your feedbacks the better their precision!\n", "\n", "> Thanks!\n", "\n", "As of 2022-02-20, I had received $N = 98$ answers from the [google form](https://forms.gle/hjzWVemM4Jy9cBbZ9) (out of them, $95$ are valid) out of the $881$ submitted abstracts. In short, the result is that the total score $S$ is simply the linear sum of the scores $s_i$ given by each reviewer $i$ relatively weighted by the confidence levels $\\pi_i$ (as stated in the email we received from the chairs):\n", "\n", "$$\n", "S = \\frac{ \\sum_i \\pi_i\\cdot s_i}{\\sum_i \\pi_i}\n", "$$\n", "\n", "Or if you prefer\n", "$$\n", "S = \\sum_i \\frac{\\pi_i}{\\sum_j \\pi_j} \\cdot s_i\n", "$$\n", "\n", "We deduce from that formula that the threshold is close to $6.34$ this year:\n", "\n", "![2022-02-11_COSYNE-razor](https://github.com/laurentperrinet/2022-02-11_COSYNE-scoresheet/raw/main/2022-02-11_COSYNE-razor.png)\n", "\n", "More details in the [notebook](https://github.com/laurentperrinet/2022-02-11_COSYNE-scoresheet/blob/main/2022-02-11_COSYNE-scoresheet.ipynb) (or directly in this [post](https://laurentperrinet.github.io/sciblog/posts/2022-02-11-cosyne-reviewer-feedback.html)) which can also be [forked here](https://github.com/laurentperrinet/2022-02-11_COSYNE-scoresheet) and [interactively modified on binder](https://mybinder.org/v2/gh/laurentperrinet/2022-02-11_COSYNE-scoresheet/main?labpath=2022-02-11_COSYNE-scoresheet.ipynb).\n", "\n", "\n", "EDIT: On 2022-02-20, I have updated the notebook to account for new answers, I have now received $N = 98$ answers (out of them, $95$ are valid), yet nothing changed qualitatively. On 2022-02-11, I had received $N = 82$ answers from the [google form](https://forms.gle/hjzWVemM4Jy9cBbZ9) (out of them, $79$ are valid) and the estimated threshold wass close to $6.05$.\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Other resources I found:\n", "\n", "- https://neuroecology.wordpress.com/2020/02/27/cosyne2020-by-the-numbers/ \n", "- https://charlesfrye.github.io/stats/2019/03/06/cosyne19-gender-bias.html : on gender balance\n", "- https://twitter.com/jmourabarbosa/status/1488432239692107778 : on the correlation between the scores of reviewers." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## importing data\n", "\n", "The data was collected using a [Google form](https://forms.gle/n5wzU2WJ5E6n5X1E7) which thanks to a public link can be directly accessed to [pandas](pandas.pydata.org/):" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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HorodateurReviewer #1 scoreReviewer #1 confidenceReviewer #2 scoreReviewer #2 confidenceReviewer #3 scoreReviewer #3 confidenceAbstract accepted?Comments?
9414/02/2022 17:13:456.03.08.04.05.04.0NoNaN
9514/02/2022 20:03:126.05.07.05.07.03.0Yesintroducing artificial competition into a juve...
9614/02/2022 20:04:117.04.07.04.03.04.0NoNaN
9714/02/2022 20:05:008.03.05.05.08.04.0Yesintroducing artificial competition into a juve...
9816/02/2022 14:14:154.03.02.04.05.01.0NoNaN
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" ], "text/plain": [ " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "94 14/02/2022 17:13:45 6.0 3.0 \n", "95 14/02/2022 20:03:12 6.0 5.0 \n", "96 14/02/2022 20:04:11 7.0 4.0 \n", "97 14/02/2022 20:05:00 8.0 3.0 \n", "98 16/02/2022 14:14:15 4.0 3.0 \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "94 8.0 4.0 5.0 \n", "95 7.0 5.0 7.0 \n", "96 7.0 4.0 3.0 \n", "97 5.0 5.0 8.0 \n", "98 2.0 4.0 5.0 \n", "\n", " Reviewer #3 confidence Abstract accepted? \\\n", "94 4.0 No \n", "95 3.0 Yes \n", "96 4.0 No \n", "97 4.0 Yes \n", "98 1.0 No \n", "\n", " Comments? \n", "94 NaN \n", "95 introducing artificial competition into a juve... \n", "96 NaN \n", "97 introducing artificial competition into a juve... \n", "98 NaN " ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "url = 'https://docs.google.com/spreadsheets/d/1F2ptf6mlwvV5jaAv6iQusFbDElTIjrXi-HhURmz8E_0/export?format=csv'\n", "score_sheet = pd.read_csv(url)\n", "score_sheet.tail()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, thanks for the people leaving comments:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2 HL\n", "3 JN\n", "19 Reviewer 1 was in a rush it seems to read the ...\n", "29 Reviewer 2 had only a problem with the relevan...\n", "42 Thank you for this study!\n", "45 huge spread in scores with high confidence\n", "53 reviewers not familiar with the type of resear...\n", "62 Thank you for doing this!\n", "89 Thanks for doing this :)\n", "95 introducing artificial competition into a juve...\n", "97 introducing artificial competition into a juve...\n", "Name: Comments?, dtype: object" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "score_sheet[score_sheet['Comments?'].notna()]['Comments?']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Always useful, but let's leave it aside for the quantitative anlysis:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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HorodateurReviewer #1 scoreReviewer #1 confidenceReviewer #2 scoreReviewer #2 confidenceReviewer #3 scoreReviewer #3 confidenceAbstract accepted?
9414/02/2022 17:13:456.03.08.04.05.04.0No
9514/02/2022 20:03:126.05.07.05.07.03.0Yes
9614/02/2022 20:04:117.04.07.04.03.04.0No
9714/02/2022 20:05:008.03.05.05.08.04.0Yes
9816/02/2022 14:14:154.03.02.04.05.01.0No
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" ], "text/plain": [ " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "94 14/02/2022 17:13:45 6.0 3.0 \n", "95 14/02/2022 20:03:12 6.0 5.0 \n", "96 14/02/2022 20:04:11 7.0 4.0 \n", "97 14/02/2022 20:05:00 8.0 3.0 \n", "98 16/02/2022 14:14:15 4.0 3.0 \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "94 8.0 4.0 5.0 \n", "95 7.0 5.0 7.0 \n", "96 7.0 4.0 3.0 \n", "97 5.0 5.0 8.0 \n", "98 2.0 4.0 5.0 \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "94 4.0 No \n", "95 3.0 Yes \n", "96 4.0 No \n", "97 4.0 Yes \n", "98 1.0 No " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "score_sheet = score_sheet.drop(['Comments?'], axis=1)\n", "score_sheet.tail()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A quick sanity check for missing data:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "0 04/02/2022 08:54:01 NaN NaN \n", "9 04/02/2022 10:15:22 NaN 4.0 \n", "52 04/02/2022 20:16:41 NaN NaN \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "0 NaN NaN NaN \n", "9 3.0 3.0 4.0 \n", "52 NaN NaN NaN \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "0 NaN NaN \n", "9 4.0 No \n", "52 NaN No \n", " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "0 04/02/2022 08:54:01 NaN NaN \n", "52 04/02/2022 20:16:41 NaN NaN \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "0 NaN NaN NaN \n", "52 NaN NaN NaN \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "0 NaN NaN \n", "52 NaN No \n", " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "0 04/02/2022 08:54:01 NaN NaN \n", "52 04/02/2022 20:16:41 NaN NaN \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "0 NaN NaN NaN \n", "52 NaN NaN NaN \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "0 NaN NaN \n", "52 NaN No \n", " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "0 04/02/2022 08:54:01 NaN NaN \n", "52 04/02/2022 20:16:41 NaN NaN \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "0 NaN NaN NaN \n", "52 NaN NaN NaN \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "0 NaN NaN \n", "52 NaN No \n", " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "0 04/02/2022 08:54:01 NaN NaN \n", "52 04/02/2022 20:16:41 NaN NaN \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "0 NaN NaN NaN \n", "52 NaN NaN NaN \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "0 NaN NaN \n", "52 NaN No \n", " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "0 04/02/2022 08:54:01 NaN NaN \n", "52 04/02/2022 20:16:41 NaN NaN \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "0 NaN NaN NaN \n", "52 NaN NaN NaN \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "0 NaN NaN \n", "52 NaN No \n" ] } ], "source": [ "for i in [1, 2, 3]:\n", " print(score_sheet[score_sheet[f'Reviewer #{i} score'].isna()])\n", " print(score_sheet[score_sheet[f'Reviewer #{i} confidence'].isna()]) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It seems we should remove lines `0`, `9` and `52` to get a cleaner score-sheet and avoid overkill hacks. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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HorodateurReviewer #1 scoreReviewer #1 confidenceReviewer #2 scoreReviewer #2 confidenceReviewer #3 scoreReviewer #3 confidenceAbstract accepted?
104/02/2022 09:14:563.04.05.01.04.03.0No
204/02/2022 09:15:454.03.09.03.04.04.0No
304/02/2022 09:24:015.04.02.05.02.04.0No
404/02/2022 09:47:037.04.06.01.06.04.0Yes
504/02/2022 09:49:278.04.08.03.04.03.0Yes
\n", "
" ], "text/plain": [ " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "1 04/02/2022 09:14:56 3.0 4.0 \n", "2 04/02/2022 09:15:45 4.0 3.0 \n", "3 04/02/2022 09:24:01 5.0 4.0 \n", "4 04/02/2022 09:47:03 7.0 4.0 \n", "5 04/02/2022 09:49:27 8.0 4.0 \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "1 5.0 1.0 4.0 \n", "2 9.0 3.0 4.0 \n", "3 2.0 5.0 2.0 \n", "4 6.0 1.0 6.0 \n", "5 8.0 3.0 4.0 \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "1 3.0 No \n", "2 4.0 No \n", "3 4.0 No \n", "4 4.0 Yes \n", "5 3.0 Yes " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "score_sheet = score_sheet.drop([0, 9, 52], axis=0)\n", "score_sheet.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, the scores are integers and should be converted from the `float` format imported from google forms. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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HorodateurReviewer #1 scoreReviewer #1 confidenceReviewer #2 scoreReviewer #2 confidenceReviewer #3 scoreReviewer #3 confidenceAbstract accepted?
104/02/2022 09:14:56345143No
204/02/2022 09:15:45439344No
304/02/2022 09:24:01542524No
404/02/2022 09:47:03746164Yes
504/02/2022 09:49:27848343Yes
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" ], "text/plain": [ " Horodateur Reviewer #1 score Reviewer #1 confidence \\\n", "1 04/02/2022 09:14:56 3 4 \n", "2 04/02/2022 09:15:45 4 3 \n", "3 04/02/2022 09:24:01 5 4 \n", "4 04/02/2022 09:47:03 7 4 \n", "5 04/02/2022 09:49:27 8 4 \n", "\n", " Reviewer #2 score Reviewer #2 confidence Reviewer #3 score \\\n", "1 5 1 4 \n", "2 9 3 4 \n", "3 2 5 2 \n", "4 6 1 6 \n", "5 8 3 4 \n", "\n", " Reviewer #3 confidence Abstract accepted? \n", "1 3 No \n", "2 4 No \n", "3 4 No \n", "4 4 Yes \n", "5 3 Yes " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "for i in [1, 2, 3]:\n", " score_sheet[f'Reviewer #{i} score'] = score_sheet[f'Reviewer #{i} score'].astype(int)\n", " score_sheet[f'Reviewer #{i} confidence'] = score_sheet[f'Reviewer #{i} confidence'].astype(int)\n", "score_sheet.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## more data\n", "The message received by `cosyne@confmaster.net` mentions some numbers:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "reviewer_pool = 215\n", "total_reviews = 2639 # out of 2643 - why is that number of 5 out of 2643 mentionned?\n", "submitted_abstracts = 881" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## analyzing raw scores\n", "\n", "Now that we have all the date in hand, let's do a quick analysis." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(13, 5))\n", "cols = ['Reviewer #1 score', 'Reviewer #2 score', 'Reviewer #3 score']\n", "ax = score_sheet[cols].plot.hist(stacked=True, ax=ax, bins=9)\n", "ax.set_xlabel('Reviewer score (from 1 to 10)')\n", "ax.set_xlim(1, 10)\n", "ax.set_xticks(np.arange(1, 10)+.5)\n", "ax.set_xticklabels(np.arange(1, 10))\n", "ax.set_ylabel('cumulated score');" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(13, 5))\n", "cols = ['Reviewer #1 confidence', 'Reviewer #2 confidence', 'Reviewer #3 confidence']\n", "ax = score_sheet[cols].plot.hist(stacked=True, ax=ax, bins=5)\n", "ax.set_xlabel('Reviewer confidence (from 1 to 5)')\n", "ax.set_xlim(1, 5)\n", "ax.set_xticks(np.arange(1, 6)*5/6+.5)\n", "ax.set_xticklabels(np.arange(1, 6))\n", "ax.set_ylabel('#');" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of accepted abstracts = 47\n" ] } ], "source": [ "accepted = score_sheet[score_sheet['Abstract accepted?']=='Yes']\n", "print(f\"Number of accepted abstracts = {len(accepted)}\")" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Percent of accepted abstracts in survey = 49.0%\n" ] } ], "source": [ "print(f\"Percent of accepted abstracts in survey = {len(accepted)/len(score_sheet)*100:.1f}%\")" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "## retrieving the razor score\n", "\n", "The message mentions the method:\n", "\n", " Each review comprised a short comment and a score between 1 and 10. Individual scores were weighed by a confidence factor and averaged for each submission.\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is my attempt at deriving a score:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "p = 1 # trying out different norms... confidence=variance? confidence=std?\n", "total_score = score_sheet['Reviewer #1 score'] * score_sheet['Reviewer #1 confidence']**p\n", "total_score += score_sheet['Reviewer #2 score'] * score_sheet['Reviewer #2 confidence']**p\n", "total_score += score_sheet['Reviewer #3 score'] * score_sheet['Reviewer #3 confidence']**p\n", "total_weight = score_sheet['Reviewer #1 confidence']**p\n", "total_weight += score_sheet['Reviewer #2 confidence']**p\n", "total_weight += score_sheet['Reviewer #3 confidence']**p\n", "score = total_score / total_weight" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For which the histogram looks like:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAwUAAAE9CAYAAABa086QAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAXvklEQVR4nO3df9Sed10f8PfHBgUSKNBiVgGXOhlbpVpohiDIEgsuMI+gx6kcxig66y8UtJvr2FTcjzN2Dj822abrKEthhaj8WBEQ4UDDDxU0aYG0FBSxaGtpZIVAah0WP/vjuXIWQtIk9b6fK3e+r9c5z8l9/Xiu7+f5nCfPfb/v63vdV3V3AACAcX3F3AUAAADzEgoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABrdh7gJOxNlnn91btmyZtYY77rgjGzdunLWG04E+Lo5eLoY+Lo5eLoY+Lo5eLoY+Lsap0Me9e/d+ursffLRtKxEKtmzZkj179sxaw+7du7Nt27ZZazgd6OPi6OVi6OPi6OVi6OPi6OVi6ONinAp9rKpPHmub6UMAADA4oQAAAAYnFAAAwOCEAgAAGJxQAAAAgxMKAABgcEIBAAAMTigAAIDBCQUAADA4oQAAAAYnFAAAwOA2zF0AAKeHfbccyMWXvWXuMlbezh0b5y4BGJAzBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABrdh7gIAgP9v3y0HcvFlb5m7jNPCzh0b5y4BVoYzBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABre0UFBVD6uqa6rqI1V1Q1U9b1r/oKp6R1X9wfTvA5dVAwAAcHzLPFNwV5JLu/u8JI9N8uNVdV6Sy5K8s7sfnuSd0zIAADCTpYWC7r61u6+dHn8+yY1JHpLkaUmunHa7MsnTl1UDAABwfOtyTUFVbUnyqCQfSLK5u2+dNn0qyeb1qAEAADi66u7lDlC1Kcm7k/z77n5DVX22ux9w2PbPdPeXXVdQVZckuSRJNm/efOGuXbuWWufxHDx4MJs2bZq1htOBPi6OXi6GPi7O/tsP5LY7565i9W2+T/RxQfRyMc498wx/JxfgVHi+2b59+97u3nq0bRuWOXBV3SvJ65Nc1d1vmFbfVlXndPetVXVOkv1H+97uvjzJ5UmydevW3rZt2zJLPa7du3dn7hpOB/q4OHq5GPq4OC+/6uq8ZN9Sn1aGcOn5d+njgujlYuzcsdHfyQU41Z9vlvnpQ5XkiiQ3dvdLD9v0piTPnh4/O8nVy6oBAAA4vmXG58cneVaSfVX1wWndC5K8KMmvVtUPJvlkku9dYg0AAMBxLC0UdPf7ktQxNl+0rHEBAICT447GAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADG5poaCqXllV+6vq+sPWvbCqbqmqD05fT13W+AAAwIlZ5pmCnUl2HGX9y7r7gunrrUscHwAAOAFLCwXd/Z4kty/r+AAAwGLMcU3Bc6vqw9P0ogfOMD4AAHCY6u7lHbxqS5I3d/cjp+XNST6dpJP82yTndPcPHON7L0lySZJs3rz5wl27di2tzhNx8ODBbNq0adYaTgf6uDh6uRj6uDj7bz+Q2+6cu4rVt/k+0ccF0cvFOPfMM/ydXIBT4flm+/bte7t769G2rWsoONFtR9q6dWvv2bNn8QWehN27d2fbtm2z1nA60MfF0cvF0MfFeflVV+cl+zbMXcbKu/T8u/RxQfRyMXbu2Ojv5AKcCs83VXXMULCu04eq6pzDFr8ryfXH2hcAAFgfS4vPVfXaJNuSnF1VNyf5+STbquqCrE0fuinJDy9rfAAA4MQsLRR09zOOsvqKZY0HAADcM+5oDAAAgxMKAABgcEIBAAAMTigAAIDBCQUAADA4oQAAAAYnFAAAwOCEAgAAGJxQAAAAgxMKAABgcEIBAAAMTigAAIDBCQUAADA4oQAAAAYnFAAAwOCEAgAAGJxQAAAAgxMKAABgcEIBAAAMTigAAIDBCQUAADA4oQAAAAYnFAAAwOCEAgAAGJxQAAAAgzuhUFBV//qwx1+1vHIAAID1drehoKr+RVU9Lsn3HLb6d5ZbEgAAsJ42HGf7R5P8oyRfV1XvnZbPqqpHdPfHll4dAACwdMebPvTZJC9I8vEk25L852n9ZVX128srCwAAWC/HO1PwD5L8XJK/leSlST6c5I7ufs6yCwMAANbH3Z4p6O4XdPdFSW5K8uokZyR5cFW9r6p+fR3qAwAAlux4ZwoO+c3u3pNkT1X9aHc/oarOXmZhAADA+jihjyTt7p85bPHiad2nl1EQAACwvk765mXd/aFlFAIAAMzDHY0BAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABre0UFBVr6yq/VV1/WHrHlRV76iqP5j+feCyxgcAAE7MMs8U7Eyy44h1lyV5Z3c/PMk7p2UAAGBGSwsF3f2eJLcfsfppSa6cHl+Z5OnLGh8AADgx631NwebuvnV6/Kkkm9d5fAAA4AjV3cs7eNWWJG/u7kdOy5/t7gcctv0z3X3U6wqq6pIklyTJ5s2bL9y1a9fS6jwRBw8ezKZNm2at4XSgj4uz//YDue3OuatYfeeeeYbfyQXxO7kYm+8TfVwQvVwMfycX41R4DbR9+/a93b31aNs2rHMtt1XVOd19a1Wdk2T/sXbs7suTXJ4kW7du7W3btq1TiUe3e/fuzF3D6UAfF+flV12dl+xb7//Cp5+dOzb6nVwQv5OLcen5d+njgujlYvg7uRin+mug9Z4+9KYkz54ePzvJ1es8PgAAcIRlfiTpa5P8TpJHVNXNVfWDSV6U5MlV9QdJnjQtAwAAM1raObXufsYxNl20rDEBAICT547GAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGt2HuAgDmtO+WA7n4srfMXcZp4dLz564AWAZ/Jxdj546Nc5dwt5wpAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABicUAAAAIMTCgAAYHBCAQAADE4oAACAwQkFAAAwOKEAAAAGJxQAAMDghAIAABjchjkGraqbknw+yReT3NXdW+eoAwAAmCkUTLZ396dnHB8AAIjpQwAAMLy5QkEneXtV7a2qS2aqAQAASFLdvf6DVj2ku2+pqq9O8o4kP9Hd7zlin0uSXJIkmzdvvnDXrl3rXufhDh48mE2bNs1aw+lAHxdn/+0Hctudc1ex+jbfJ/q4IHq5GPq4OHq5GPq4GOeeecbsr4G2b9++91jX8s4SCr6kgKoXJjnY3S8+1j5bt27tPXv2rF9RR7F79+5s27Zt1hpOB/q4OC+/6uq8ZN+clwWdHi49/y59XBC9XAx9XBy9XAx9XIydOzbO/hqoqo4ZCtZ9+lBVbayq+x16nOTbk1y/3nUAAABr5oh9m5O8saoOjf+a7n7bDHUAAACZIRR09yeSfNN6jwsAABydjyQFAIDBCQUAADA4oQAAAAYnFAAAwOCEAgAAGJxQAAAAg3N7OtbVvlsO5OLL3jJ3GaeFS8+fuwIA4HThTAEAAAxOKAAAgMEJBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxOKAAAgMEJBQAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxuw9wFrIp9txzIxZe9Ze4yVt6l589dAQAAR3KmAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgEAAAxullBQVTuq6mNV9fGqumyOGgAAgDXrHgqq6owk/zXJU5Kcl+QZVXXeetcBAACsmeNMwWOSfLy7P9HdX0iyK8nTZqgDAADIPKHgIUn+5LDlm6d1AADADKq713fAqu9JsqO7/+m0/Kwk39zdzz1iv0uSXDItPiLJx9a10C93dpJPz1zD6UAfF0cvF0MfF0cvF0MfF0cvF0MfF+NU6OPf7O4HH23DhvWuJMktSR522PJDp3VforsvT3L5ehV1PFW1p7u3zl3HqtPHxdHLxdDHxdHLxdDHxdHLxdDHxTjV+zjH9KHfS/Lwqjq3qr4yyfcnedMMdQAAAJnhTEF331VVz03ym0nOSPLK7r5hvesAAADWzDF9KN391iRvnWPsv4ZTZirTitPHxdHLxdDHxdHLxdDHxdHLxdDHxTil+7juFxoDAACnllnuaAwAAJw6hILjqKpXVtX+qrp+7lpWWVU9rKquqaqPVNUNVfW8uWtaRVV176r63ar60NTHX5i7plVXVWdU1XVV9ea5a1lVVXVTVe2rqg9W1Z6561llVfWAqnpdVX20qm6sqsfNXdOqqapHTL+Lh74+V1XPn7uuVVRVPzU911xfVa+tqnvPXdOqqqrnTX284VT9fTR96Diq6olJDiZ5VXc/cu56VlVVnZPknO6+tqrul2Rvkqd390dmLm2lVFUl2djdB6vqXknel+R53f3+mUtbWVX100m2Jrl/d3/H3PWsoqq6KcnW7p7787dXXlVdmeS93f2K6RP67tvdn525rJVVVWdk7WPPv7m7Pzl3Paukqh6SteeY87r7zqr61SRv7e6d81a2eqrqkUl2JXlMki8keVuSH+nuj89a2BGcKTiO7n5PktvnrmPVdfet3X3t9PjzSW6MO1mftF5zcFq81/Ql2d9DVfXQJP8wySvmrgWq6swkT0xyRZJ09xcEgr+2i5L8oUBwj21Icp+q2pDkvkn+dOZ6VtXfTfKB7v7z7r4rybuTfPfMNX0ZoYB1V1VbkjwqyQdmLmUlTdNdPphkf5J3dLc+3nP/KcnPJPmrmetYdZ3k7VW1d7obPffMuUn+LMn/nKa0vaKqNs5d1Ir7/iSvnbuIVdTdtyR5cZI/TnJrkgPd/fZ5q1pZ1yf51qo6q6rum+Sp+dIb+Z4ShALWVVVtSvL6JM/v7s/NXc8q6u4vdvcFWbsb+GOm05KcpKr6jiT7u3vv3LWcBp7Q3Y9O8pQkPz5Nu+TkbUjy6CS/1N2PSnJHksvmLWl1TdOvvjPJr81dyyqqqgcmeVrWwurXJNlYVf943qpWU3ffmOQ/Jnl71qYOfTDJF+es6WiEAtbNNAf+9Umu6u43zF3PqpumFVyTZMfMpayqxyf5zmk+/K4k31ZV/2veklbT9I5iunt/kjdmbd4sJ+/mJDcfdvbvdVkLCdwzT0lybXffNnchK+pJSf6ou/+su/8yyRuSfMvMNa2s7r6iuy/s7icm+UyS35+7piMJBayL6QLZK5Lc2N0vnbueVVVVD66qB0yP75PkyUk+OmtRK6q7/2V3P7S7t2RtisG7utu7YCepqjZOHx6QaarLt2ftVDknqbs/leRPquoR06qLkvgwhnvuGTF16K/jj5M8tqruOz2HX5S16wG5B6rqq6d/vzZr1xO8Zt6KvtwsdzReJVX12iTbkpxdVTcn+fnuvmLeqlbS45M8K8m+aT58krxgurs1J+6cJFdOn6jxFUl+tbt9lCZz2pzkjWuvGbIhyWu6+23zlrTSfiLJVdPUl08kec7M9aykKaA+OckPz13LquruD1TV65Jcm+SuJNflFL8j7ynu9VV1VpK/TPLjp+KHCPhIUgAAGJzpQwAAMDihAAAABicUAADA4IQCAAAYnFAAAACDEwoAAGBwQgHAAlXVWVX1wenrU1V1y2HLX3nEvs+vqvuewDF3V9XW5VV9cmrNu6rq/tPyT1bVjVV11ZLHfW5VfbyquqrOPsY+F1TVU0/yuGdV1TVVdbCq/ssR2y6sqn3TuL843cQpVfXiqvq2e/7TAJxahAKABeru/9PdF3T3BUl+OcnLDi139xeO2P35SY4bCtbD9EL/RJ8TnprkQ939uWn5x5I8ubufecQxF32DzN9K8qQkn7ybfS6Y6jsZf5HkZ5P8s6Ns+6UkP5Tk4dPXjmn9y5NcdpLjAJyyhAKAJauqi6rquukd51dW1VdV1U8m+Zok11TVNdN+v1RVe6rqhqr6hRM47ouq6iNV9eGqevG0bnNVvbGqPjR9fcu0/qer6vrp6/nTui1V9bGqelWS65M8rKr+eVX93nTMY9XwzCRXT8f45SRfl+Q3quqnquqFVfXqqvqtJK+exnjXdLx3VtXXTt+3c/p5319Vn6iqbVNvbqyqnUcbtLuv6+6b7qYfX5nk3yT5vunMzPdV1YOq6n9P47+/qr7xKMe9o7vfl7VwcPjxzkly/+5+f6/d6fNVSZ4+fc8nk5xVVX/jWPUArBKhAGC57p1kZ5Lv6+7zk2xI8qPd/YtJ/jTJ9u7ePu37r7p7a5JvTPL3j/YC9pCqOivJdyX5hu7+xiT/btr0i0ne3d3flOTRSW6oqguTPCfJNyd5bJIfqqpHTfs/PMl/6+5vSPKIafkxWXvH/cKqeuJRhn98kr1J0t0/ctjP8bJp+3lJntTdz8jaO+pXTjVeNdV3yAOTPC7JTyV5U5KXJfmGJOdX1QXH+tmPZToT83NJfmU6M/MrSX4hyXXT+C/I2gv7E/WQJDcftnzztO6Qa7PWC4CVJxQALNcZSf6ou39/Wr4yydFeaCfJ91bVtUmuy9qL4/Pu5rgHsvbO9hVV9d1J/nxa/21Zm/KS7v5idx9I8oQkb5zeET+Y5A1JvnXa/5Pd/f7p8bdPX9dl7QXv38laSDjSg7r783dT25u6+87p8eOSvGZ6/OqplkN+fXoHfl+S27p7X3f/VZIbkmy5m+OfjCdM46a735W1d/fvv6Bj78/a2R6Albfo+Z4A3ANVdW7W5rT/ve7+zDSF5t7H2r+776qqxyS5KMn3JHlu1gLBybrj8DKS/Ifu/u/H+Z67quorphfwxzvm3fm/079/ddjjQ8unwvPTLUkeetjyQ6d1h9w7yZ0BOA04UwCwXF9MsqWqvn5aflaSd0+PP5/kftPj+2ftxfSBqtqc5Cl3d9Cq2pTkzO5+a9am33zTtOmdSX502ueMqjozyXuTPL2q7ltVG7M27ei9Rznsbyb5genYqaqHVNVXH2W/j2XtOoIT8dtJvn96/MxjjLtIh/c003jPTJKq2pbk04ddIH23uvvWJJ+rqsdOnzr0TzJdSzH521m7FgNg5QkFAMv1F1mbz/9rVbUva++C//K07fIkb6uqa7r7Q1mbtvPRrE23+a3jHPd+Sd5cVR9O8r4kPz2tf16S7dNYe5Oc193XZu26ht9N8oEkr+ju6448YHe/fRr7d6bvf12+9AX2IW9Jsu34P3qS5CeSPGeq81lTfffI9NGnN2ftHfsPV9UrjrLbNUnOO3ShcZIXZu3aiA8neVGSZx/j2DcleWmSi6vq5qo6NHXrx5K8IsnHk/xhkt+Y9r9Xkq9Psuee/jwAp5Jam84JACdm+lSeV3X3k+euZS5V9V1JHt3dPzt3LQCL4EwBACdlmlbzPxZ4we4q2pDkJXMXAbAozhQAAMDgnCkAAIDBCQUAADA4oQAAAAYnFAAAwOCEAgAAGNz/A2Fc17pMDfvwAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(13, 5))\n", "ax = score.hist(bins=np.arange(1, 10), ax=ax)\n", "ax.set_xlabel('Total score (from 1 to 10)')\n", "ax.set_ylabel('#');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "While the distribution of the sum of confidences is" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(13, 5))\n", "ax = total_weight.hist(bins=np.arange(1, 16), ax=ax)\n", "ax.set_xlabel('Sum of confidences (from 3 to 15)')\n", "ax.set_ylabel('#');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's scatter plot the outcome as a function of the score:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(13, 5))\n", "ax.scatter(score, score_sheet['Abstract accepted?']=='Yes', marker='+', alpha=.4, s=100)\n", "ax.set_xlabel('Total score (from 1 to 10)')\n", "ax.set_yticks(np.arange(0, 2))\n", "ax.set_yticklabels(['No', 'Yes'])\n", "ax.set_ylabel('Accepted?');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "An (overkill) method would be to fit a [sigmoid](https://laurentperrinet.github.io/sciblog/posts/2020-04-08-fitting-a-psychometric-curve-using-pytorch.html)... Let's rather look at the threshold:" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "It was mentioned in the message that:\n", "\n", " After considering additional constraining factors, the top scoring 54 % of submissions were accepted.\n", " " ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Official percent of accepted abstracts = 54.0%\n" ] } ], "source": [ "score_quantile = .54\n", "\n", "print(f\"Official percent of accepted abstracts = {score_quantile*100:.1f}%\")" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "threshold score for an accepted abstract 6.340\n" ] } ], "source": [ "threshold = score.quantile(score_quantile)\n", "print(f\"threshold score for an accepted abstract {threshold:.3f}\")" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Abstracts rejected above the threshold = 2\n" ] } ], "source": [ "false_negatives = score[(score > threshold) & (score_sheet['Abstract accepted?']=='No')]\n", "print(f\"Abstracts rejected above the threshold = {len(false_negatives)}\")" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Abstracts accepted below the threshold = 2\n" ] } ], "source": [ "false_positives = score[(score < threshold) & (score_sheet['Abstract accepted?']=='Yes')]\n", "print(f\"Abstracts accepted below the threshold = {len(false_negatives)}\")" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8, 5))\n", "ax.scatter(score, score_sheet['Abstract accepted?']=='Yes', marker='+', alpha=.4, s=100)\n", "ax.scatter(false_positives, np.ones_like(false_positives), marker='+', alpha=.4, s=100, c='r')\n", "ax.scatter(false_negatives, np.zeros_like(false_negatives), marker='+', alpha=.4, s=100, c='r')\n", "ax.vlines([threshold], ymin=.0, ymax=1., colors='r', linestyles='--')\n", "ax.set_xlabel('Total score (from 1 to 10)')\n", "ax.set_yticks(np.arange(0, 2))\n", "ax.set_yticklabels(['No', 'Yes'])\n", "ax.text(threshold + 1, .5, f'{threshold=:.3f}')\n", "ax.set_ylabel('Accepted?')\n", "plt.tight_layout();" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "fig.savefig('2022-02-11_COSYNE-razor.png')" ] }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "This result may be (certainly) due to an error in reporting the score in the google form or to the \"additional constraining factors\" mentioned in:\n", "\n", " After considering additional constraining factors, the top scoring 54 % of submissions were accepted.\n", "\n", "\n", "## gray zone\n", "\n", "It seems there is a \"gray zone\" for abstracts that were between the minimal score for accepted abstracts and the maximal score for rejected ones:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Minimal score for an accepted abstract 5.833\n" ] } ], "source": [ "score_min = score[score_sheet['Abstract accepted?']=='Yes'].min()\n", "print(f\"Minimal score for an accepted abstract {score_min:.3f}\")" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Maximal score for a rejected abstract 6.364\n" ] } ], "source": [ "score_max = score[score_sheet['Abstract accepted?']=='No'].max()\n", "print(f\"Maximal score for a rejected abstract {score_max:.3f}\")" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Abstracts in gray zone 10\n" ] } ], "source": [ "gray_zone = score[(score_min < score) & ( score < score_max)]\n", "print(f\"Abstracts in gray zone {len(gray_zone)}\")" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Percent abstracts in gray zone = 10.4%\n" ] } ], "source": [ "print(f\"Percent abstracts in gray zone = {len(gray_zone)/len(score)*100:.1f}%\")" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Predicted total abstracts in gray zone = 91\n" ] } ], "source": [ "print(f\"Predicted total abstracts in gray zone = {int(len(gray_zone)/len(score)*submitted_abstracts)}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Out of the total of $881$ abstract, it is certainly worth to put more attention at these $100$ abstracts which are closer to the threshold. Considering that these are certainly the ones that are less likely to go to such a conference (students, minorities, lower-ranked universities) it is an important issue to better consider their scientific value." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## bonus: reliability of score for individual abstracts across reviewers \n", "\n", "\n", "Similarly to that [tweed by Sdrjan Ostojic](https://twitter.com/jmourabarbosa/status/1488432239692107778) I also looked at a dependance between reviewers scores, but this is still in progress. Any help is welcome (you can [fork](https://github.com/laurentperrinet/2022-02-11_COSYNE-scoresheet) the notebook)." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "import seaborn as sns\n", "opts = dict(kind=\"reg\", scatter_kws=dict(alpha=.3, s=100))" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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GBCUhhBBVQ4KSEEKIqiFBSQghRNWQoCSEEKJqKF3M/VbNlFLfBNq8rscNagPGva6ER+p13+t1v6F+9/1m93tca/1gqStTC9ZFUFqPlFIvaK0PeF0PL9TrvtfrfkP97nu97nc5SfedEEKIqiFBSQghRNWQoFQ+R7yugIfqdd/rdb+hfve9Xve7bOSekhBCiKohLSUhhBBVQ4KSEEKIqiFBSQghRNWQoCSEEKJqrIug9OCDD2pAHvKQhzxq5bFqNXr9W9K6CErj4/WYvUQIIerv+rcugpIQQoj6IEFJCCFE1ZCgJIQQompIUBJCCFE1JCgJIYSoGhKUhBBCVA0JSkIIIaqGBCUhhBBVw/K6AkKsZ6mczYXxJKdHZsnkHIJ+k92dMba2RQj7a/u/Vz3vuygfOXOEuEnjiSxH+0dxHJfGkI9Y1CJnuxy/NM0rV+Ic7uugLRrwupplUc/7LsqrbN13SqkvKqVGlVKvLvhdi1Lq20qp14tfm8tVvhDllMrZHO0fJWgZdDQECfhMlFIEfCYdDUGClsHR/lFSOdvrqpZcPe+7KL9y3lP6EvDgG373W8BRrfUtwNHiz0KsOxfGkziOSySweGdDJGBhOy4XxpMVrln51fO+VzPH1Uwmc15XY83KFpS01k8Bk2/49U8Cf1L8/k+Af1Su8oUop9MjszSGfMu+pink4/TIbIVqVDn1vO/VSmvNT/7B9/nk37zidVXWrNL3lDq11kPF74eBzqVeqJR6BHgEoKenpwJVE2L1MjmHWHT5/z4+y2Amka9QjSqnnve9UhZe/0yz0D26kuZ3fozYne/DDL8LNx0va/26N/cweOliWbbt2UAHrbVWSi25robW+ghwBODAgQM3tP6IEOUW9JvkbJeAz1zyNXnbJehf+vn1qp73vVIWXv+UUvpzT7624t+MzWb58+cv8TP/9dvs39xU1vo9+sCusm270vOURpRSXQDFr6MVLl+IktjdGWMmvXxLYDqdZ3dnrEI1qpx63vdq1h4L0BEL0D9U3lZSuVU6KH0d+Lni9z8H/F2FyxeiJLa2RTBNg2R28RFmyayNZRpsbYtUuGblV8/7Xu36uhoYnc0yNpv1uio3rZxDwr8CPAPsUkpdVkp9DPiPwHuUUq8D7y7+LMS6E/ZbHO7rIGO7jMQzZPMOrtZk8w4j8QwZ2+VwX0dNTiKt532vdrs2xDCV4uTVGa+rctPKdtZorT+8xFOHy1WmEJXUFg3w4/u65rMazCTyBP0md/Q01XxWg3re92oW8pns6IzSPzzLfTva8JnrL5OcnDlCrEHYb7FnYyN7NjZ6XZWKq+d9r2a3bWzkteFZzozMsncdvjfrL4wKIYRY0samIC0RP69cWZ9deBKUhBCihiiluG1TIyPxLKOzGa+rc8MkKAkhRI3ZvSGGZah12VqSoCSEEDUm6DO5pTPKa8Oz5GzX6+rcEAlKQghRg27f1ETe0bw2vL5yEEpQEkKIGtTZEKAt6uflK9NovX4ytUlQEkKIGjQ34GE8kWMkvn4yPEhQEkKIGrVrQwyfub4GPEhQEkKIGhWwTHZ1xjgzMks273hdnVWRoCSEEDXstk2N2K6mf50MeJCgJIQQNayjIUhnQ4BXrsysiwEPEpSEEKLG3bqpkclkjqsz1Z/hQYKSEELUuF2dMfymsS4GPEhQEkKIGuczDXZ3xTg7miBd5QMeJCgJIUQduG1TI46rq365dAlKQghRB9qiAboag1U/4EGCkhBC1InbNjUyncpzeSrtdVWWJEFJCCHqxC0dUQJWdQ94kKAkhBB1wjIN9nQ1cG4sQTJre12dRUlQEkKIOnLrpkZcDaeqdMCDBCUhhKgjLRE/m5pCnBqKV+WABwlKQghRZ/q6Ykyn8gzHqy/DgwQlIYSoM7d0xLAMVZVdeJbXFRClMZ7I8OzZCZ4+P0EqaxMOWNy7rZWDO1ppiwa9rl5ZebnvqZzNhfEkp0dmyeQcgn6T3Z0xtrZFCPvL+9/L6/d8cDLJ4yeGOPb6GKmcTdhvceiWdh7e18XmlkhZy/byuNcCv2WwoyPKmZEEh25pxzKrp32iqrFP8Y0OHDigX3jhBa+rUbXOjMxy5NgAtuPSGvUTtAwytstEIodlGjxyqJednTGvq1kWXu77eCLL0f5RHMelMeTDbxnkbJeZdB7TNDjc10FbNFCWsr1+z587P8FnnziN7Whao34CpiLr6GL5ik88tJu7t7WWpWwvj3sJqVW/UCn9uSdfK3kFLk2m+NuXrvDQrRtu+Fx59IFda70fteT+exIelVIfV0q9qpQ6qZT6DS/qUCvGExmOHBsg7DfobgkT8lsowyDkt+huCRP2Gxw5NsB4ovr6jtfKy31P5WyO9o8StAw6GoIEfCZKKQI+k46GIEHL4Gj/KKlc6Yfdev2eD04m+ewTpwktKN8wzfnyQ36Dzz5xmsHJZMnL9vK415rNzSGiAavquvAqHpSUUrcCvwTcBewD3qeU2lHpetSKZ89OYDsuDSH/os83hPzkHJdnz01WuGbl5+W+XxhP4jgukcDiXUWRgIXtuFwYL/2F2ev3/PETQ9iOpjG0eGukMRQg72gef3mo5GV7edxrjVKKvq4YlyZSJKpozpIXLaU+4DmtdUprbQPHgPd7UI+a8PT5CVqji1+c5rRH/Tw9MF6hGlWOl/t+emSWxpBv2dc0hXycHin9ap9ev+fHXh9bsfy2qJ9jZ8ZKXraXx70W9XU1oIHXq+h4eXFH8FXg00qpViANvBd40w0jpdQjwCMAPT09Fa3gepLK2jQHl/9PGrAMJpLZCtWocrzc90zOIRZd/r+PzzKYSeRLXrbX73kqZ9MUXH7fA6ZiIln6T99eHvdKWnj9g8I9nHLp+vnf59tXTvNn/+P/WPXfdG8u3zW54kFJa92vlPo94EkgCRwH3rTAh9b6CHAECgMdKlnH9SQcsMjYLiH/0o3erO0SXqK7Yz3zct+DfpOc7RLwmUu+Jm+7BP1LP3+zvH7Pw36LrKMJLbNrWUeXZRScl8e9khZe/8o10GHODy9M8vS5Cf7t371KwzKt0BIMblgVTwY6aK2/oLW+U2t9PzAFnPGiHrXg3m2tTCRyy75mLJHj3t62CtWocrzc992dMWbSy38an07n2V2GEXBev+eHbmlfsfzxRI5DO9tLXraXx71W3dIRBeDsaMLjmhR4Nfquo/i1h8L9pD/3oh614OCOVizTIJ5e/CIRT+fwmwYHt7dUuGbl5+W+b22LYJrGkkktk1kbyzTY2lb6+Tpev+cP7+vCMhUz6cW7B2fSWXym4uHbu0petpfHvVY1hf10xAKcGa2O+0pezZj6a6XUKeAbwK9orac9qse61xYN8sihXlI5l0uTKdI5G9d1SedsLk2mSOVcHjnUW5MTaL3c97Df4nBfBxnbZSSeIZt3cLUmm3cYiWfI2C6H+zrK0oXl9Xu+uSXCJx7aTTrnMjhXvuOQztnFn10+8dDuskyg9fK417JbOqOMxLPEV2iFVoJMnq0R44kMz56b5OmB8Wuz+3vbOLi9pSYD0kJe7rvnGR08fM8HJ5M8/vIQx84syOiws52Hb5eMDqvg+eTZhaZTOf7kmYsc2tnO/s1Ni76mxPeUltx/CUpCCFF5VRWUAP70mQvEgj7+8R2bFn2+UkGpehIeCSGE8My2tgiXp1Jk7TcNhq4oCUpCCCHobYvi6kJOPC9JUBJCCEFXY5CAZXDe4xRNEpSEEEJgGIqtrREujKc8XZFWgpIQQggAelrDpPMO4ytMji4nCUpCCCGAwnIWAINT3t1XkqAkhBACgFjQR1PYx6CHgx0kKAkhhJi3uTnMlek0juvNfSUJSkIIIeZtbg6RdzQjcW9Wq5agJIQQYl53SxiAy9NpT8qXoCSEEGJeyGfSEvYzJEFJCCFENehqCjI8k/FkvpIEJSGEENfZ0BgkY7tMpyq/lIUEJSGEENfZ2FiYr3R1pvJdeBKUhBBCXKc57CNgGQzNVH4EngQlIYQQ11FKsaEx6MmwcAlKQggh3qQ9GmAymcN23YqWK0FJCCHEm3TEArgaJiqcnFWCkhBCiDdpjwUAGJvNVrRcCUpCCCHepDHkw28ajEpQEkII4TWlFO2xgLSUhBBCVIf2WIDxRBa3gpkdJCgJIYRYVHssgO1qZiqY2UGCkhBCiEW1hP0ATKUqNwLPqlhJQpRJKmdzYTzJ6ZFZMjmHoN9kd2eMrW0Rwv7ynuJeln1icIovPDXAsxcmyNkufsvg4NZWPnZ/L/s2N5e1bIAzw3G+8twlvnd2jEzeIegzefuOdj58dw87NzSUtWwvj3s9aY74AJiUoCTE6ownshztH8VxXBpDPmJRi5ztcvzSNK9ciXO4r4O2aKDmyv7ai4N85vF+XK2JBiwiPpO8C0+dHef75yb45MN9fODOzWUpG+DJU8N8+rFT2K6mOeQjFrDIO5on+0f4zmujfOp9e3hgz4aylO3lca83Acsk7DeZStZ4951S6l8opU4qpV5VSn1FKRX0oh5ifUvlbI72jxK0DDoaggR8JkopAj6TjoYgQcvgaP8oqZxdU2WfGJziM4/347cUbdEAQZ+JaZoEfSZt0QB+S/GZx/s5MThV8rKh0EL69GOnCPgMuhpDBP1WoXy/RVdjiIDP4NOPneLMcLzkZXt53OtVS9hf0e67igclpdQm4NeBA1rrWwET+FCl6yHWvwvjSRzHJRJYvMEfCVjYjsuF8WRNlf2FpwaKLSTfos9HAz4cV/PF7w+UvGyArzx3CdvVNAT9iz7fEPSTdzR/8fylkpft5XGvV80RP5PJGg5KRRYQUkpZQBi46lE9xDp2emSWxtDiF+Y5TSEfp0dma6rsZy9MEF3iojwnFrR4ZmCi5GUDfO/sGM0r7HtL2MdTr4+VvGwvj3u9ag77yNouRqi89wnnVPyektb6ilLqPwGXgDTwpNb6yTe+Tin1CPAIQE9PT2UrKdaFTM4hFl3+FPZZBjOJ0veHe1l2znaJ+MzlyzYgkS1PIs1M3iG2QlD0mYrptFP6sj087pW08PoH8OgDuzyrS3DbW+j8qd/F19aDUgqA7s09DF66WJbyKh6UlFLNwE8C24Bp4K+UUj+jtf4fC1+ntT4CHAE4cOBA5dfkFVUv6DfJ2S6BZS7Qedsl6F/+Ar7eyvZbBnkXzGU2nXcLryuHoM8k7+jly3c0wRUC502V7eFxr6SF1z+llP7ck695Vpd4Os8fP32Bj/zuF7l1UyNQ3iDpRffdu4HzWusxrXUe+BvgXg/qIda53Z0xZtLLfyKeTufZ3RmrqbIPbm0lkV3+Rv5sxuae3taSlw3w9h3tTK2w75OpPPff0l7ysr087vUqFrQwDVWxYeFeBKVLwEGlVFgV2oKHgX4P6iHWua1tEUzTILnEBTqZtbFMg61tkZoq+2P392IoRSK7+MU5kc1jGoqPvq235GUDfPjuHixDEc8sfpGKZ3L4TMWH7ip9t7uXx71eKaVoDvuYqtBgh4oHJa31c8DXgB8BrxTrcKTS9RDrX9hvcbivg4ztMhLPkM07uFqTzTuMxDNkbJfDfR1lmUzpZdn7NjfzyYf7yNmasdksmbyD4zhk8g5js1lytuaTD/eVbQLtzg0NfOp9e8jmXa5Op8nk7EL5OZur02myeZdPvW9PWSbQennc61lz2M9UhVINKV3BRHs368CBA/qFF17wuhqiStVzRocvfn+AZwauZXS4p7eVj76tchkd/uL5Szz1+rWMDvff0s6H7pKMDqugVv1Cj+8pATwzMMEPz0/yz9+xHcs0ePSBXawxdiy5/xKUhBCi8tZVUHpteJZvnhzmI3f30BYNlDUoSUJWIYQQy5rLgVeJ+0oSlIQQQiyreT5bePnvK0lQEkIIsSyfaRANWBXJgSdBSQghxIpaKpQDT4KSEEKIFTWHfUylcmsd4LAiCUpCCCFW1BwpZH9PZkuf03AhCUpCCCFWNDfYodzphiQoCSGEWFHL/Ag8CUpCCCE8FgmY+ExV9rlKEpSEEOImaK1x3erPiFMqhcSsfum+E0KIapK1HcYTWS5Npsja5VlIsVq1RPxMJcs7gXZdZC4UQggvua4mkbOZzdhk8+UdfVbNmiN+Tg/PovyhspUhQUkIIZbguJp4Os9MOo+7DpJXl9vcYAdfS3fZypCgJIQQb5CzXWYzeWYztgSjBVoixaDUKkFJCCHKSmtNIlvoosvUcRfdchpDPgwFvtbNZStDgpIQoq5l8g6zGZtkVlpFKzENRWPIR0KCkhBClM5cqyhe5wMXbkZLxM+odN8JIcTaua5mNmMzk85ju/U1nLtUmsN+rKYu8o6Lzyz9rCIJSkKImjc3ii6eyePU0YTXcmiJ+FGmxcWJJDs6YiXfvgQlIUTNklF0pTc3Au/saMKboKSU6gQ+A2zUWj+klNoD3KO1/kLJayOEEGskE13Lay5b+NnRRFm2v5oOwS8B3wI2Fn8+A/xGWWojhBA3KZN3GJstpP8Zn81KQCoTv2Vgx8c4N5Ysy/ZXE5TatNZ/CbgAWmsbkHdbCOE5x9XMpPIMTqa4Op1mNiOZFyohPzFYtpbSau4pJZVSrYAGUEodBGbKUhshhFiFTN4hnsmTzDplX55bvFl+4jLnxhK4rsYwVEm3vZqg9CjwdWC7UuoHQDvwgZLWooRSOZsL40lOj8ySyTkE/Sa7O2NsbYsQ9pd3XEe9ll3PTgxO8YWnBnj2wgQ528VvGRzc2srH7u9l3+bmspY9nsjw7NkJnj4/QSprEw5Y3LutlYM7WmmLBstaNlT+nMvkHZJZm1TOIe94N5x7KpXj+MUpXro8DUBDyFfR414N8hODpHIOQ/EMm5pKm5x12TNHKWUCh4qPXYACXtNalzd3+U0aT2Q52j+K47g0hnzEohY52+X4pWleuRLncF8HbdGAlC1K4msvDvKZx/txtSYasIj4TPIuPHV2nO+fm+CTD/fxgTvLM/P9zMgsR44NYDsurVE/zUEfGdvl7/tH+e6ZcR451MvOztKPjJpTqXNubtDCTCrvaSCac2EiyVefH8RxNU1hHy1hH46mYse9WuQnLgNwbjRR8qC07D0lrbUDfFhrbWutT2qtX11rQFJK7VJKHV/wiCulfmMt24TCp7aj/aMELYOOhiABn4lSioDPpKMhSNAyONo/Sipnr7UoKVtwYnCKzzzej99StEUDBH0mpmkS9Jm0RQP4LcVnHu/nxOBUycseT2Q4cmyAsN+guyVMyG+hDIOQ36K7JUzYb3Dk2ADjiUzJy4bKnHPpnMPobGZ+0EI1BKSpVI6vPj9IyGfQ2Vjc7woe92qSnxgEyjMCbzUDHX6glPqvSqm3K6XeMve42QK11q9prfdrrfcDdwIp4G9vdntzLowncRyXSGDxxl8kYGE7LhfGSz9ipF7LrmdfeGqg2ELyLfp8NODDcTVf/P5Ayct+9uwEtuPSEPIv+nxDyE/OcXn23GTJy4bynXO24zKVzHFpIsXQTJpElc0tOn5xCsfVRIKLv+flPu7VxE1N0xC0ODvmTVDaD+wFfhf4z8XHfypR+YeBc1rri2vd0OmRWRpDi58sc5pCPk6PzK61KClb8OyFCaJLXJTnxIIWzwxMlLzsp89P0BpdPCDNaY/6eXpgvORlQ+nPuXTOYSReaBVNpXJVm/7npcvTNIWX3+9yHvdqs6MjWpaW0op3I7XW7yx5qdd8CPjKYk8opR4BHgHo6elZcUOZnEMsuvzu+CyDmUTpb4fVa9n1LGe7RHzmsq/xGZDIlv4Cm8raNC/xaX1OwDKYSGZLXjaU5pybu1cUT+fJrZMlxTM5h8YVPoiU6rgvvP4BPPrArjVvs6SUwVOP/SWh7Xeh1L2r/rPuzT0MXlq+DbKajA6NwL8B7i/+6hjwu1rrNQ0LV0r5gZ8Afnux57XWR4AjAAcOHFixDR/0m+Rsl8AyF4q87RL0L38huRn1WnY981sGeRfMZQ5r3i28rtTCAYuM7RLyL73trO0SXuECerNu9pxzXU0q75DK2iRz628od9BvknU0gWXe0lId94XXP6WU/tyTr615m6X24sUpvn92nE8/forQCh/Q5qwmuK7mf8wXgVngp4qPOPDHq6rB8h4CfqS1HinBttjdGWMmvXxrYDqdZ3cZRsbUa9n17ODWVhLZ5W/kz2Zs7ultLXnZ925rZSKRW/Y1Y4kc9/a2lbxsuLFzbm6JiKGZNBcnU4zGMySy9roLSAB3dDcxnVp+v8t53KvNXA68yeTy5+KNWk1Q2q61/jda64Hi43eA3hKU/WGW6Lq7GVvbIpimQXKJC0Uya2OZBlvbIqUqsu7Lrmcfu78XQykS2cUvUolsHtNQfPRtpfivcr2DO1qxTIN4evGLQTydw28aHNzeUvKyYXXnHBRWKR2cTDMaz5Behy2jN9q/pRnTUCQzi7/n5T7u1WYuKE15EJTSSqm3zf2glLoPSK+lUKVUBHgP8Ddr2c5CYb/F4b4OMrbLSDxDNu/gak02X7iJmrFdDvd1lGVSX72WXc/2bW7mkw/3kbM1Y7NZMnkHx3Hm86/lbM0nH+4rywTatmiQRw71ksq5XJpMkc7ZuK5LOmdzaTJFKufyyKHesk3kXOqcS2TyDIwluDqTYXdXjKztVu2ghZvRHPbzwbs2k867DM0U97uCx73axIIWpqGYTJU2KKmVPr0opfYDfwI0Fn81Bfy81vpESWuyjAMHDugXXnhhVa+t16wKktHBGycGp/ji9wd4ZuBaRod7elv56NsqlNHh3CRPD4xfy+jQ28bB7S0Vy+hwZniWV67OEE/lMS2D3tYI3c0hgqu8x7AeTaVyHL80zUvFOWgNId/NHPdV5+ap1ntKAF9+7iKRgMU/2r9pVa9/9IFdcy3mJfd/xaA0/0KlGgC01vFV/UEJ3UhQEkKUVzrnMJvNk845db9gXldjiNDNDSKqiaD0xKtDDM9k+IX7tq3q9asJSit23ymlPqOUatJax7XWcaVUs1Lq36+61kKIdU1rTTrnMJ7IXjextd4DkoCWsJ94xi5pxo3V3FN6SGs9PfeD1noKeG/JaiCEqDq24xLP5BmNZ7hYDETxdL6m7hGJtZsf7FDC+0qrudlgKqUCWussgFIqBEh2TyFqiNaaTN4llfM+C7dYP5qKq9BOp/J0xEpzH3M1QenLwFGl1NzcpF+gMPBBCLGOOa4mmbNJZR3S+fU/ZLvSZtJ5Xhue5d4dbSumXapVc/u90ry1G7GaNEO/p5Q6Aby7+Kt/p7X+VslqIISoGMfVpNdxVgWvOK5mYCzBqaFZTg3F6R+Kc3mqMDPmyM/eyQN7N3hcQ2/4LYOw36xsUCrOKXpSa/1NpdQuYJdSyletayoJIa7RuhiEcg5p6ZZbtclkjv6h+HwAOj08Syb/5mNnGYor02uatrnuNYZ8zKyQ6eJGrKb77ing7UqpZuCbwAvAB4GPlKwWQoiSytku0+mcLBe+CrbjcnYswamr11pBQzOLr4nUGvHT19XAno0N7O1q4P6d7TRHls/YXusaQ775VmMprCYoKa11Sin1MeAPtdafVUodL1kNhBAl4RbvESWzjizquIyx2ex8K+jU1ThnRhOLZir3mYpbOqLs2dhA34ZCIOqIBVDq2hSbWp4kvFqNIR+nh2exXRfLWHsC4lUFJaXUPRRaRh8r/k7eCSGqgO24xczbMlhhMTnb5fXR2cK9oKuFIDSWWHxpiY5YgD1dDfQVW0E7OqJlyfJea+YGO8ym7ZK0GlcTlD5OYXmJv9Van1RK9QL/sOaShRA3xXZcklmHRM4mm3e8rk7V0FozMpul/2qck8VuuLOjCfLOmwO13zLYWWwF7dnYwJ6uBtqiMtPlZswFpXgmX5mgpLV+isJ9pbmfB4BfX3PJQohVy+QLAxVSeUcCUVEm73BmpNAK6i92xU0skbF6Y1OQPV0N7N7QwN6NDWxvj2CZ0goqhbkVmFdaymW1JFOnEFVIa00q5xQfktJHa83VmQz9Q3FOXi20gs6NJRc9LkGfwa7O2HwLaM/GBprD9T0YoZzCgcLdnGS2NB+WJCgJUSWytkMm75LOyf2hdM7h9HCc/qHZ+SA0vcRcmO7m0Hzw2dPVwLa2CKax6nynYo0swyDkM6WlJMR657qaRM4mmbXJ5l3cOg1CWmsGp9LXjYg7P55kscZh2G/StyFGXzEA9XU11G02hWoSCZhLLvp4o5YMSkqpMPCrgAb+X+BDwPuB08Dvaq0TJamBEHVkbjJrIlO/GRUSWZvTcwGoeD9oNrP4BW1LS/i6brielrC0gqpQJGBVpKX0JWAQCAGPA/3A/w38BPCHwM+WpAZC1DDbccnaLnnHJee4dbcGkas1FydS8wMRTg3FuTiRYrEjEAta9HU10LchNj83KBqUzpz1IOw3mSzRsujLveM7tdY/pQozxYaAd2uttVLq+0DFVp0VYj1xXE3eccnkHZK5+hspF0/n6R+O0391lpNDcU4PxUnm3nwMDAVb2yKFFlCxFdTdHMJQ0gpajwKWSXaRNEw3YzVDwrVS6n/pYj9D8ef6+agnxCLsYssnb+vC1+KjnlpBjqu5MJ6cnxN06mqcwSXSzTSGfPR1xdi7sXAfaPeGGGG/tIJqRcAyyDkurqsx1ti9utxZ8YJSKqq1TmitPzr3S6XUdmB2TaUKsc7Yjku6OFcona+vLrg506lcMTdcYUTc6eH4oklKDQU7OqLzqXn2dDWwsSl4XXoeUVvm0i1lHZeQsbaEP0sGJa31Ly7x+3NKqbevqVQhqtzcEg/pnEMmX3/ZtW3HZWA8OT8c++TVpZOUNod98wlK+zY2sKszJjnh6kygmI4pm3cIrfG9X83SFR/VWn9x4e90PQ4ZEjVNa03Wdus2a8JEIlvMDzfDqaFZzozMkl0kSallKHbMpecp3gvqfEOSUlF/5oJSZpFz5kYtNyT8gxTSC/0q8MXi745qrQ+vuVQhPDQ3GMF2Ndm8Q85x62qeUN5xOTuamJ8TdPJqnNHZxZOUtkcD9G2MFVpBXQ3s7IxJklLxJnPD9EvRrb1cS2kD8AfATqXUV4GXgR6lVERrnVxzyUJUSM52r+uKq5fgM2c0ninOCYpz6uosr4/OLpqk1GcqdnbGrsuO0B6TJKViZXNByS1zUPqfWuvfV0q9BPwfwD4gCvydUsrSWr9jzaULUSJ2seVjuxrbcck7hVFxOdutqwmq2bzD6wtaQaeG4ownFp8/sqEhOD8ibs/GBra3R/FJklJxE+aG8pfiA99yQek/KKW2Aj3AByi0lEa11u9WSkleD3Gdwckkj58Y4tjrY6RyNmG/xaFb2nl4XxebWyIlKWPhMOy862I7hW64V69M81c/HOT4lWnytovPMti/qYkPvHUzuzc0lKTspQzNpDl2eoznL0ySydsEfRZ3bW3h0O52uhpDZS376nSKx04M8czABPF0nqytSdsOi10XgpbBzg2x6+YFtaxxmYFM3uHyVJqBiSS5nIPfb9LbGqG7OVT2gQ5eHnfxZvPdd+UMSlrrnwZQSp0ELgGHgS1Kqe9RmDz7qzdbqFKqCfg8cCuFNEYf1Vo/c7PbE9567vwEn33iNLajaY36aQpaZB3NE68O8+3+ET7x0G7u3ta67Da01uQdje0WWjmuq3F04WvOKQSgxT6FfevkMH/03XO4WhP2m4SDBnkXfnhxihcvTfPL79jOj+3dUJb9PnF5ms8/NYDjaJoiPhoCAXKu5qkzY/zg3Di/eH8v+7qbSlZeOu9wZrgwHPvZ8xOcHprFXqK7pC3q546eZvZ0FQJRb3u0pOl5plI5njk3ieu6RAMWkYifvO1yeijOmZEE92xvKVtm7kofd7Gy+ZZSCQaprmb22kta678G/lop9RBwCLhjjeX+PvBNrfUHlFJ+ILzG7QmPDE4m+ewTpwn5DRpD1+4/hEzobrGYSWf57BOn+S8f2s/mlsi1IFPsZpvrYss7+oa72U4Px/mj757DZyrC/muN94BRmGGeytn80XfPsaU1XPIW09BMms8/NUDQZxCNXbv4BkzobLJIZHJ8/qkBPvlw3019ctdac2U6fW3F1KE4A2OJRZOUmkoRC1o0hHw0BC1MpbFd+Pl7t5Sl1ZDJOzxzbpKApQj5r73nfp9Ji88knbN55twk79rdXvIWU7mPu7g5c593yt19B4DW+mcW/PhJrbULvHizBSqlGoH7gZ8vbj8HlCZpkqi4x08MYTuahqAfV2u0LlxQNaA1BH0WE4k0X3nuEh+8q6ekk06/9sPBYgtp8d7ksN9iMpnjr18c5FMP7y1ZuQDHTo/hOPq6C+NC0aCfRCbNsdfG+NBdPStuL5m1eW14dsGAhDjxJZKUNoV8aK3paAjSEPIR8ZtvGpI9PL36sm/U5ak0ruteF5AWCvktUrksl6fS7OiIlrTsUh93URpz/61L0Rq/oTwfWusn1lwibAPGgD9WSu2jEOA+LiP6vKe1xtWFYZ2unnsUftZaF3/P/HOOq/nWqWFCfnPR/GZzGkMWT5+b4AMHNpe0vsevTBP2L/9JPBIweWlwuqTlAjx/YZKmyPK3VpsjPp4/P/mmi6OrNYOTqWILqJAl+/x4ctEkpZGAOb9Ew96NhfQ8/+bvThL0GQR8S//3XarsUhiYSM6vNrqUWMBiYCJZ8qC0luMuymfuw2Ypchd6kXzKAt4C/JrW+jml1O8DvwX864UvUko9AjwC0NMjJ9eNmgsiTvGr7Wqc4n0ZZ75FA5ri64qPG5XO2cRWCAx+QzGdL01a+4Xytks4uPxoMZ8BqVzpszFk8jYNgeWHS8/t92wmz+nha4vV9Q/NLprmX7EwSWlhzaCelvCb/qPfSNnlkMs5RFYYJOGzDBIlyhq9kNf7XikLr38Ajz6wy8ParCzQvZcNH/k9/vtv/wKZi0vn6+7evPK13IugdBm4rLV+rvjz1ygEpetorY8ARwAOHDhQP2N6lzHXkplrpWgNtusWJ4Pq+Umhcy2dSgj6LHKuJrBMXMq5muAyn+pvls8qDGoILBOX8m7hdaW21H5rrUnmHOLpPNOpHPGMzU/+wdOLbqMhaBWWaOgqpOjZtSFGZIUWyHJlL1SuYw7g95vkbRf/MveL8raLf4UPKzfD632vlIXXP6WU/tyTr3lco0JgXOq+7/dfH+dnvvAcx/7hO9y1rWVN5Sz7zimlTOBPtdYfWVMpC2ith5VSg0qpXVrr1yiM6jtVqu1Xq7mAouC6LLpzLZS5LNNzI83mfq8X/H01umtrC0+dGaOzaelTaSqZ59Cu9pKXvX9TEz+8OEXAWvoKlcw63N3bXPKy5/a7JWYQT+eJZ2zimTyzGXvRFqehoLetmJ5nY2HNoO7m0E2l5/HymAP0tkY4PRSnZZmgNJu16esq/XB8r/ddLG4uN2Qpsn0sG5S01o5SaotSyl8ckFAqvwZ8uTjybgD4hRJuuyQWu78yR6HQFLvA4Lrur4X3Ylz32r2XN1JKVW2guRGHdrfzg3PjJDI5osE3d+kkMjksU5XlIvGBt27mxUvT8/Oi3iiVszENxT+5szT3shxXMzCWKIyIG44zMJHk9OjiCzBbhiLkM3nv7Ru4e1sruzbE1pyoco6XxxyguznEmZEE6ZxNaJHjns7ZmIZBd3PpR795ve9icaniPeWgr8xBqWgA+IFS6uvA/GAErfXnbrZQrfVx4MDN/v0qyyCZK6SUcd1r91dct9Dl5bqFiV4KUOrNgabcAaMWAhJAV2OIX7y/l88/NUAik6Y54sNvKHKuZiqZxzIVv3h/b1mG5+7e0MAvv2M7f/Tdc0wmc0QCJj6j0GWXzDqYhuKX37H9poeDTyZz88Ox+4fivDY8u2TCyYjfpDFkEfZbOK4m5DP4pUPbyzJfxstjDoVlCu7Z3sIz5yZJ5bLEAlahK9V2mc0WAtI921vKMoHW631fSCmF5KEtmEnngcK6WWu1mqB0rvgwgNiaS6wQx9WMxhdPtb+Qvv4fcRP2dTfxyYf7OPbaGM+fn2S6OMP+0K52Du0q7wz7H9u7gS2tYf76xUFeGpwmlStkdLi7t5l/cufqMzrkHZdzY4n5EXGnrsYZXuL8aY365xOUdjYEuDyZ4keXpq9lFtjWUvb99vKYAzSH/bxrd/t8RodEMoffb9LX1VD2jA5r3XelFIYqjBQzDIWpFIZR+NlUCkMpVPHnudfBtZ/Vgq+iYDpd6EhrCq19wrRa7Sd2pVRYa51ac4k34cCBA/qFF164ob+xHZdLk55UV6wDY7PZ+XWCTg3FOTOydJLSWzpi7NkYY09XI3u6YnQ0BD2osViKoRSmUWi1WIaBaSh85rWAM/fcXMBZ68qoJbLqSqyHgQ7/4Yl+/vgHF3jt3z242mC95ItWs57SPcAXKCRj7SnOLfpnWut/vpqShfBaznY5M1KYDzTXChpLLL5UQ2dD4Los2dvbo7JUQ5kopbCMQtCY+zoXNOZaIgu715UqfG8Uf19FAabuzaTyNIZ8JWk9rqb77r8APwZ8HUBrfUIpdf+aSxaiDLTWjMSz12VGODuaWDRHXMAyiks1FOYE7e1qoDUqSzXcqLmWirkwsMx1jy3sGlvQYil8LwGlVkyn8jSV4H4SrHKektZ68A0nUH0tyymqVibv8NrILP1X45wsTkydXGLS5sam4HVZsnvbIliyVMOylCp2hS0IMH7TwDINLEPhM42SJnoV69NYIktrtDQJeFcTlAaVUvcCurhkxceB/pKULsQN0FpzdSYzPyLu1NU455ZIUhr0GezecG3Bur6uhrJlrV7P5lowllls6Sxo9fgtA79pSItGrGh4JsPda5w0O2c1QemXKWT13gRcAZ4EfqUkpQuxjHTOoX84Pj8goX9odn7o6Rttbg5dlx1ha1ukrj/B+0wDy1RYRqFFMxd0DCVdaKK0HFczEs+wobE0A4BWE5QSpczoIMRiXK25PJmenxN0cijOhfHkoq2giN9kdzH49G2MsXtDQ0nmR6w3c11rfssgYJr4rEIQ8pkSbETlTCSy2K6mq4JB6VWl1AjwveLj+1rrmZKULupWImsXk5MWuuH6h2eZXWSpBgVsaQ3PZ8res7GBLa1vTlJay+ZGqQUsA59p4F/wVQivDc0U5vOVam7catZT2qGU6gHeDjwM/IFSalprvb8kNRA1z9WaixOpa/eChuJcmkgtOl05FrTo2xCbH5K9u6thxWUSaoWh1HUBx1/sgvPJYAxRxeaCUsW675RS3cB9FILSPuAk8P2SlC5q0kw6f60VNDTL6aH4oustGQq2tUXmA1BfVwObbzJJ6XqhilkDlGI+8PgsY74VJMR6MzyTBqho990l4IfAZ7TWv1ySUkXNcFzNhfEkJ4vdcKeG4lyeSi/62qaQr9gFVxgVt3tDA6EyLG9QDUxDEbDMQuCxCvd5ZCSbqEWDU2mCPoOWFdbYWq3VBKU7gLcBP62U+i3gdeCY1voLJamBWFemUoUkpf3FbrjTw7Nk8m9OUmoaiu3tkeuGZG9sDNbcRVkVu9wC1rUuN5m7I+rJhfEkW1sjJfu/vZp7SieUUnNJWd8O/AxwiELqIVHDbMfl3Fjy2oi4q/H5/uM3aon451dM3bOxgZ2dsbIm5fSKoRQBn0HIZxIsPoSoZ+fHk+zaULpc3au5p/QCEACepjD67n6t9cWS1UBUjYlEdr4brn8ozmsjCXKLLNVgGYpbOqPzc4L2bGygIxaoyVZQYEEraK47TghRMJf4+sFbN5Rsm6vpvntIaz1WshJFVcjZLmdHE/OZEU4NxRmdXTxJaUeskKS0b2OhJXRLR6xmL86moQj7LSIBk5DPrLlAK0QpXZ5KY7uarW2Rkm1zNUHJUEp9AdiotX5IKbUHuEfuKa0fWmvGZgtJSk8WW0GvjyYWXarBbxns7Ci2gor3gtpjtZ2kVClFxG8SDVoSiIS4AecnCuu+bqtwUPoS8MfAp4o/nwG+itxTqlrZvMOZkcS1TNlDcSYSiycp7WoMFkbEFUfFbW+P1s3Q5IDPJBa0iPotWQJBiJtwfsyboNSmtf5LpdRvA2itbaWUZAmvElprhuOZ61ZMPTuWwFkkP0/QMthVnJjat6FwL6hUwzjXg7l7RJFi95xkCBdibS5MJIkFLFpLeB1ZTVBKKqVaKa4XrpQ6CEiaIY+kc4WlGubuA/UPxZlKLZ6ktLs5dK0V1BWjtz1aV0OVLcMg6CsMUAj4CgMWpGtOiNI5P55kW3vphoPD6oLSoxQW+NuulPoB0A58oGQ1EEvSWnN5Kj2foLT/6iwD44sv1RD2m4WlGuayI2xooDFcf0lKAz6TiN8kErDqphtSCK+cH0/ylp7mkm5zNfOUfqSUOgTsopAf8zWt9eIfzcWaJLM2p4dn51tAp67GiS+SpBRgS0t4PkHpnq4YW1rrd6kGv2UQDVgSiISooKztcGU6zfvf0l3S7S4ZlJRS79Jaf0cp9f43PLVTKYXW+m9KWpM642rNpcnUdSumXhhPLpqkNBqw6Ou6tmDd7g0xYsH6awUtZBkG0aBFNGDV7PB0IarZpYkUWkNvCQc5wPItpUPAd4AfX+Q5DUhQugGzmTz9Q7Pz84L6h+Mks4snKd3aFplPULq3q4HullBdLdWwFNNQRAKFQCSZFITw1vnxwsi7Us5RgmWCktb63xS//UWttYy2uwGOq7kwkbxuxdRLk6lFX9sY8r2pFRT218dSDathGQbhgEnEb9Vs8lYh1qO5oLSttXItpfmylVLfpDA36Tta68V6mOradCrHqaE4r1ye4cTlGQbGkuScN6fnMRT0tkfnA9DergY2NpUmSelUKsfxi1O8dHmaTM4h6De5o7uJ/VuaaQ6Xf9h3KcufC0TroUV0ZjjOV567xPfOjpHJOwR9Jm/f0c6H7+5h54aGspadytlcGE9yemR2/pjv7oyxtS1S8x9sxhMZnj07wdPnJ0hlbcIBi3u3tXJwRytt0dIsoSCWd348SWvEX/IBVas5c3cD7wN+BfiCUuox4C+01nW5ppLtuAyMX98KujK9+FINkYDJhoYgG5tCvGdPB3duaSFUhovshYkkX31+EMfVNIV9NAYsso7mmYFJnr8wxQfv2szWEn+aKXX5hlKEAyaxgG/dtIiePDXMpx87he1qmkM+YgGLvKN5sn+E77w2yqfet4cH9pQuJ9hC44ksR/tHcRyXxpCPWNQiZ7scvzTNK1fiHO7roC1am5k4zozMcuTYALbj0hr10xz0kbFd/r5/lO+eGeeRQ73s7CxdglCxuIHxZEknzc5Zzei7FPCXwF8qpZqB3weOATd95VBKXQBmAQewtdYHbnZb5TaZzM3PCTp5Nc6ZkVmyiyQpNRR0NgTZ2hqhuyVET3OYprAPpRTpnE087VCOu0JTqRxffX6QkM8gsmDwQ8CAzkaTZCbPV58f5JFDvWVpMa21/GAxq0JknWVVODMc59OPnSLgM2gPXtsv04Quv0U8k+PTj51ia0u45C2mVM7maP8oQcsgsmDSYsBn0uEzSWYLz//4vq6aazGNJzIcOTZA2G/QELrWIgr5DbpbLOLpHEeODfBb790lLaYyOz+e5J272ku+3VWdscUh4R8EHgReAH6qBGW/U2s9XoLtlEzeuT5Jaf/QLMPxxZdqaIv65+cENQZ9pHI2nUusUR/yW6RyWS5PpdnRES1pnY9fnMJx9XUBYaFI0Ec8m+H4pWneubujpGXfbPm1MJfoK89dwnb1dQFpoYagn6uZNH/x/CX+r5+4taRlXxhP4jjudQFpoUjAIpHNcGE8yZ6NjSUt22vPnp3AdtzrAtJCDSE/0+kUz56b5H37Nla4dvVjNpNnbDbLtrbSXs9gdUtXXABeotBa+pda62TJa+GRuSSlcy2hMyOziyYp9ZmKnZ2x4oCERvZuvD5J6ZP9Iyu2QmIBi4GJZMmD0kuXp2laoU+3JezjpcGpsgSl1Zb/8pVpPnDn5ppJ7/O9s2M0h1be76deL32C/dMjszSuUHZTyMfpkdmaC0pPn5+gNbr8/7X2qJ+nB8YlKJXRhfHCwC1Puu+A27XW8RKXq4EnlVIa+G9a6yNvfIFS6hHgEYCenp41F5izXc6MzF5LUno1zvgSSUo7GwLzgxH2dDWwvT267FyYXM5Z8lPrHJ9lkEguXt5aZHIOjYHl30a/qZhOlWcA5XLl+8zCMuCxgMlwPFNTGSYyeYfYCsfdZyqm06U/7pmcQyy6QtmWwUyi9ua4p7I2zSvM0QtYBhPJxZdhWS8WXv8AHn1gl4e1KVLX0nRtftv7Me77KL3t3gSlDUqpvwU6tda3KqVuB35Ca/3v11Du27TWV5RSHcC3lVKntdZPLXxBMVAdAThw4MANjfgrpOdJcbR/dH7Z7rOjCexF8vMELIOdnbH5ZRr2dMVovcEbxH6/Sd528S8ziCFvu/jLcAM/6DfJOprAMo2PnKMJlmnwwBvLN4vLg/tNY/4eUTpXGB1VS4I+k7yjMZc5rHlHl2X0YNBvkrNdAiucb+V6z70UDlhkbJeQf+kTPmu76/58W3j9U0rpzz35msc1ut7v/M6/pVlBT0u45NtezTv334F/Cfw3AK31y0qpPwduOihpra8Uv44WA95dwFPL/9XqfePlIX79Ky8t+tzGpmAxQWmhJdTbFllzd1Jva4TTQ3FalrlIzGZt+rpKP0T4ju4mnhmYpLNx6bInU3nu295a8rLnyn/2/CQ9IT9+y1g01dFYIscDezrLUr5X3r6jnSf7R+haZiDBZCrPg3tLv9+7O2McvzRNxzLn23Q6zx09TSUv22v3bmvl7/tH6W5Z+rjX4vlWbXzNm9jUFCrLh67VBKWw1vr5N8ylWTwh2yoopSKAobWeLX7/APC7N7u9xdy+qdCPHvKZ7NpQaAUVMiTEaCrDCLTu5hBnRhKkczahRS5S6ZyNaRh0Ny8+EGIt9m9p5vkLUyQz+UUHGyQzeXyGYn8JL1CWYRDym4T8Ju/bv5H+4QR5x1l0KHc8ncNvGhzc3lKy8qvBh+/u4TuvjRLP5GhYZLBDPJPDZyo+dNfau57faGtbhFeuxElmbSKLtAiSWRvLNEo+074aHNzRynfPjBNP52gILXLca/R8qzZWyyZ620s/yAFWF5TGlVLbubZ0xQeAoTWU2Qn8bTHIWcCfa62/uYbtvcmW1jCP/dp9BCyzIklKgz6Te7a38My5SVK5LLGAhc8yyNsus9lCQLpne0tZPlU0h/188K7NfPX5QeLZDC1hH35TkXM0k6lCQPrgXZvXPBzcX1yHKOQ3r9uPaMDikUO9HDk2wHQ6RXvUT8AyyNouY4nCBeKRQ701Nzx354YGPvW+PXz6sVNczaRpCfvwmYr83HE3FZ96356yTKAN+y0O93VwtH+URDZDU8g3f75Np/NYpsHhvo6aGw4O0BYN1uX5Vk201vhaNpU8590ctVKCBqVUL4W+zXuBKeA88BGt9cWy1GgRBw4c0C+88MIN/Y3tuEum9imXTN7h8lSagYkkuZyD32/S2xqhu7k8zdyFplI5jl+a5qXBqWsZFTY3s7+n6aYD0lz27bB/5aSn44kMz56b5OmB8Wsz7HvbOLi9paYvEGeG4/zF85d46vVrGR3uv6WdD90lGR3KqQbOt1V/Wq62e0rJrM3nv3+e3/mJvfzcvVtvdjNL7v+KQWn+hcVuNyAFfEhr/eWbrc2NWi9BqRYYShELWsSCPsm+LUT5rNugdGUqzdd+dJk//ehd3L/zpifPLrn/S151lFINSqnfVkr9V6XUeygEo58DzlKaybOiivgtg7ZYgJ6WMK3RgAQkIcSiptOFqS1bWks/8g6Wv6f0ZxS6654Bfgn4FIXo9o+11sfLUhtRUYYqLAURC1Z/4lMhRHWIZ2y069C1RAabtVouKPVqrW8DUEp9nsLghh6t9eJ5d8S6oJQi5DOJFLNwlyJDuRCifsym8ziJibL1piwXlOang2utHaXUZQlI65PPLAzhDvtNQj5TApEQ4qbNZPLY0yNl2/5yQWmfUmouvZACQsWfFaC11uUdWiTW5EZGzgkhxGrF0zb2zGjZtr/cyrNyk2GdMQ1FLOgjGpBAJIQoPcfVJLM2dtyblpJYJ4I+k8aQj7BfuuaEEOUzm8mjwbPuO1HF5lZqbQj6ZOScEKIi4plChjlPuu9E9VFKzS+OJ60iIUSlxdOF8W/2jLSU6prPNGgI+ogGrYrk8hNCiMXEM3mUAme2fIuGS1CqUkopItI9J4SoIvGMXVjcUrtlK0OCUpXxWwaxoI9YwJpfJE8IIapBPJ2nYYWVf9dKglKVCPstGkO+RdckEkKIahDP5NnSUt51uiQoeWhugmskYOFb4+q3QghRTrbrksw6NATLGzYkKFWYaSiiAYto0CJgSatICLE+zBaHgzeEpPuuJoT8JrGgj4gM5RZCrENzw8HlntI6ZhkG0WBhaQjpnhNCrGfx+ZaSdN+tO2F/IRDJBFchRK2Ip/MYCiIBCUrrgs80iAUtogELS1pFQogaE8/kiQV9GGX+oC1BaQ3m0v7EgjKUWwhR2+Jpu+wj70CC0k2RtD9CiHoTz+TZ1lbeOUogQemGzC0RUe4+VSGEqCZ5xyWVc8o+8g4kKK1KJFDItiA56IQQ9Wi2QiPvQILSkgyl5oORrOIqhKhnM8U5So1lnjgLNRiUUjmbC+NJTg7FGZpK4/eb9LZG6G4Oraqls5aEqOOJDM+eneDp8xOksjbhgMW921o5uKOVtmjwZnep6suGa8f99MgsmZxD0G+yuzPG1rYIYX/NnWZVwev3fHAyyeMnhjj2+hipnE3Yb3HolnYe3tfF5jLnR/PyfKvHcz2eqczEWQCltS57IWt14MAB/cILL6z4uvFElqP9oziOSzRgMZPJk7ddElkbwzC4Z3sLzWH/m/6uFKl/zozMcuTYALbj0hr1E7QMMrbLRCKHZRo8cqiXnZ2xm9p2NZcN1x/3uZZlznaZSecxTYPDfR20RQNlK78eef2eP3d+gs8+cRrb0bRG/QRMRdbRxfIVn3hoN3dvay1L2V6ebyUse9WfeJVS+nNPvnbzlS6B770+xonLM/zKO7ajlOLRB3axxtix5P571i+llDKVUi8ppR4rxfZSOZuj/aMELYOOhiABX2Hiqt9n0hINELAUz5ybJJN35v/GZxq0RgNsbg7TGg3cdEAaT2Q4cmyAsN+guyVMyG+hDIOQ36K7JUzYb3Dk2ADjiUwpdrVqyoalj3vAZ9LRECRoGRztHyWVs8tSfj3y+j0fnEzy2SdOE1pQvmGa8+WH/AaffeI0g5PJkpft5flWz+d6PFMYDl6JZABe3iz5ONBfqo1dGE/iOO6SI+NCfgvHdbk6nSYW9LGxKcTmljCNId+a1y169uwEtuPSEHpzKwygIeQn57g8e25yTeVUW9mw8nGPBCxsx+XCeOkvUPXK6/f88RND2I6mMbR4i6AxFCDvaB5/eajkZXt5vtXzuR5P58ueiHWOJ0FJKdUNPAx8vlTbPD0yu+RNOAUELYPuphAzmTztsUBJR9I9fX6C1ujiF4g57VE/Tw+UfglhL8uG5Y/7nKaQj9Mjs2Upvx55/Z4fe31sxfLbon6OnRkredlenm/1fK5XYnG/OV7dlfsvwCeAJTu9lVKPAI8A9PT0rLjBTM4hFr1+d3yGIuQ3CVomhqFwtWY8kV1LvReVyto0r/CGBSyDiWRtlQ2LH/c38lkGM4l8WcqvR16/56mcTdMKM/sDpmIiWfpuLC/Pt0qWvfD6B/DoA7vWvM2bZQRjbP74Vzj2Z/+Zx374PwHo3rzyNflmVTwoKaXeB4xqrV9USr1jqddprY8AR6Aw0GGl7Qb9JjnbJVBsAZmGovUNNxzztkuwDOmAwgGLjO0S8i/d8MzaLuEyTLr1smx483FfTLmOe73y+j0P+y2yjia0zFuadXRZRqJ5eb5VsuyF179KD3R44yCGFy9O8k/+8Bn+55/+Ee/a/bdlL9+L7rv7gJ9QSl0A/gJ4l1Lqf6x1o7s7Y/Nj6Zcync6zuwwjku7d1spEIrfsa8YSOe7tbaupssHb416vvH7PD93SvmL544kch3a2l7xsL8+3ej3Xz40V7pFta4tWpLyKByWt9W9rrbu11luBDwHf0Vr/zFq3u7UtgmkaJLOLdxkkszaWabC1DLmbDu5oxTIN4unF/6PG0zn8psHB7S01VTZ4e9zrldfv+cP7urBMxUx68e7BmXQWn6l4+Paukpft5flWr+f6+fEkPlOxuTlUkfJqJlVB2G9xuK+DjO0yEs+QzTu4WpPNO4zEM2Rsl8N9HWXpUmiLBnnkUC+pnMulyRTpnI3ruqRzNpcmU6RyLo8c6i3LhEYvywZvj3u98vo939wS4RMP7SadcxmcK99xSOfs4s8un3hod1km0Hp5vtXruT4wlqCnJVyxJXlqavIseDvbejyR4dlzkzw9MH5thn1vGwe3t1Qmo4NHZUN9znL3mtfv+eBkksdfHuLYmQUZHXa28/DtktFhFap28uwb7ym953PH2NoW4b//bwdKWcyS+19zQUkIIdaBdRGUHFfT96+/yS+8bSu//VBfKYupvowOQgghqtvlqRQ5x6W3gvfJJCgJIYRY1NnRBADb2ysz8g4kKAkhhFhC/1AcgF0bKjfMXYKSEEKIRfUPz7K5JUSsQimGQIKSEEKIJfQPxenb0FDRMiUoCSGEeJN0zuHCeJK+LglKQgghPHZmZBZXI0FJCCGE9+YGOfR1VTaXnwQlIYQQb3JqKE40YLG5OVzRciUoCSGEeJPjg9PctqlxzStz3ygJSkIIIa6TyTv0D8XZ39NU8bIlKAkhhLjOyatx8o5m/+amipctQUkIIcR1jg9OA3CHBCUhhBBeOz44zcbGIB0N5V8C5Y0kKAkhhLjO8cEpT+4ngQQlIYQQCxjhRgYn057cTwIJSkIIIRYIbr4VgANbWzwpX4KSEEKIeYHNtxH2m9y2qdGT8iUoCSGEmBfsuZU7tzTjM70JDxKUhBBCAJDK2fjbt3Kwt9WzOkhQEkIIAcCV6TQAB3u9uZ8EEpSEEEIUXZlK4+Yy3LapybM6SFASQggBwOXpNNmr/fgt70KDBCUhhBAkszYTiRyZCyc8rYflaellkMrZXBhPcnpklkzOIeg32d0ZY2tbhLC/5nZ33ngiw7NnJ3j6/ASprE04YHHvtlYO7milLVr+VCFeHncp25tz3ctzzut9r0UXJ1MApM+/6Gk9lNba0wqsxoEDB/QLL7yw4uvGE1mO9o/iOC6NIR9+yyBnu8yk85imweG+DtqigQrUuLLOjMxy5NgAtuPSGvUTtAwytstEIodlGjxyqJedneVbPdLL4y5le3Oue3nOeb3vJbLqRYqUUvpzT75WzroA8MSrQ1yeStP/796L1m65i1ty/yvefaeUCiqlnldKnVBKnVRK/U4ptpvK2RztHyVoGXQ0BAn4TJRSBHwmHQ1BgpbB0f5RUjm7FMVVjfFEhiPHBgj7DbpbwoT8FsowCPktulvChP0GR44NMJ7IlKV8L4+7lO3Nue7lOef1vtcqV2suTabY0hIGvG2oeHFPKQu8S2u9D9gPPKiUOrjWjV4YT+I4LpHA4k33SMDCdlwujCfXWlRVefbsBLbj0hDyL/p8Q8hPznF59txkWcr38rhL2d6c616ec17ve60anc2Sybv0tFZ26fPFVDwo6YJE8Udf8bHm0Hx6ZJbGkG/Z1zSFfJwemV1rUVXl6fMTtEYXvzjMaY/6eXpgvCzle3ncpezKlw3ennNe73utujhRCOI9Ld4HJU/uCCqlTOBFYAfwB1rr5xZ5zSPAIwA9PT0rbjOTc4hFl98dn2Uwk8jfTJWrVipr0xxc/j9pwDKYSGbLUr6Xx13KrnzZ4O055/W+V8rC6x/Aow/sKmt5nR/5PZTp4/983/vo3rzy9bacPAlKWmsH2K+UagL+Vil1q9b61Te85ghwBAoDHVbaZtBvkrNdAj5zydfkbZegf+nn16NwwCJju4T8Szd6s7ZLeInujrXy8rhL2d6c616ec17ve6UsvP7d7ECHRx/YxWoGsk0mcxz499/mV9+5g0f/5F/ccDml5uk8Ja31NPAPwINr3dbuzhgz6eU/HU2n8+wu4yg0L9y7rZWJRG7Z14wlctzb21aW8r087lJ25csGb885r/e9Fh3tH8HV8J49G7yuCuDN6Lv2YgsJpVQIeA9weq3b3doWwTQNktnFR90kszaWabC1LbLWoqrKwR2tWKZBPL34RSKezuE3DQ5uL08uKy+Pu5Ttzbnu5Tnn9b7Xom+fGqGrMcitmxq8rgrgTUupC/gHpdTLwA+Bb2utH1vrRsN+i8N9HWRsl5F4hmzewdWabN5hJJ4hY7sc7uuouYl1bdEgjxzqJZVzuTSZIp2zcV2XdM7m0mSKVM7lkUO9ZZvM6OVxl7K9Ode9POe83vdak8k7fO/1cd7d14lSq546VVY1NXkW6nem93giw7PnJnl6YPza7PreNg5ub5GMDlJ2WXh5znm97yVQ9smzq7mn9PenRvjFP32BP/3oXdy/s/2Gy1iDJfe/5oKSEEKsA1URlP7V117m8VeGePFfv5uAVdHBIdWT0UEIIYT3HFdz9PQIh3a1VzogLUuCkhBC1KHjg1OMJ3I8sKfT66pcR4KSEELUoSdPjmAZinfs6vC6KteRoCSEEHVGa81jLw9x3462FdM2VZoEJSGEqDMvDU5zZTrNj+/b6HVV3kSCkhBC1JlvnLiK3zR4YG913U8CCUpCCFFXHFfz+MtDHNrVTsMKiXW9IEFJCCHqyA8vTDI6m63KrjuQoCSEEHXlGyeuEvKZvLuvukbdzZGgJIQQdcJ2XJ54dZh3VXF+QAlKQghRJ54+N8FkMseP316dXXcgQUkIIerGYy9fJRqweMeuiiZfvSESlIQQog5kbYdvvjrMA3s6CS6zcq/XJCgJIUQd+N6ZceIZu2pH3c2RoCSEEHXgsZev0hT2cd+O0i9TX0oSlIQQosalcw7fPjXCg3s34Leq+7Jf3bUTQgixZv/w2ijJnFP1XXcgQUkIIWreYy9fpS0a4GBvq9dVWZEEJSGEqGGJrM3R/lHee9sGTGPVq7B7RoKSEELUsKP9I2Rtd1103YEEJSGEqGnfOHGVrsYgd/Y0e12VVZGgJIQQNWomlefYmTEevq0LYx103YEEJSGEqFnfOjVM3tHrpusOJCgJIUTN+saJq/S0hLm9u9HrqqxadeYuF+tOKmdzYTzJ6ZFZMjmHoN9kd2eMrW2RsqfIH5xM8viJIY69PkYqZxP2Wxy6pZ2H93WxuSVS1rKFN7w839YLI9TA0+cm+Gf396LU+ui6Aw+CklJqM/CnQCeggSNa69+vdD1E6YwnshztH8VxXBpDPmJRi5ztcvzSNK9ciXO4r4O2aKAsZT93foLPPnEa29G0Rv00BS2yjuaJV4f5dv8In3hoN3dvq/65GWL1vDzf1pPwrvtw3PXVdQfedN/ZwG9qrfcAB4FfUUrt8aAeogRSucIciKBl0NEQJOAzUUoR8Jl0NAQJWgZH+0dJ5eySlz04meSzT5wm5DfobgkT8lsYpknIbxV/NvjsE6cZnEyWvGzhDS/Pt/Um0nc/29sj7N4Q87oqN6TiQUlrPaS1/lHx+1mgH9hU6XqI0rgwnsRxXCKBxRvdkYCF7bhcGC99YHj8xBC2o2kMLf6puDEUIO9oHn95qORlC294eb6tJ4msTWDzXn5838Z11XUHHg90UEptBe4AnvOyHuLmnR6ZpTHkW/Y1TSEfp0dmS172sdfHaI36l31NW9TPsTNjJS9beMPL8209eX1kFqUM3lfFK8wuxbM7gkqpKPDXwG9oreOLPP8I8AhAT09PhWsnViuTc4hFlz+NfJbBTCJf8rJTOZum4PJlB0zFRFK6cmqFl+dbJS28/pmmyaMP7Lqxv/eH2PSWd7HjPz5cjuqVlSctJaWUj0JA+rLW+m8We43W+ojW+oDW+kB7e/Uu3Vvvgn6TnO0u+5q87RL0l36ly7C/MKhhOVlHy2isGuLl+VZJC69/+/fvR2t9Qw83m2Lwmce83o2bUvGgpAodnF8A+rXWn6t0+aK0dnfGmEkv/6l0Op1nd2fpb7YeuqWdiURu2deMJ3Ic2ikfamqFl+ebqAwvWkr3AT8LvEspdbz4eK8H9RAlsLUtgmkaJLOLd5ElszaWabC1rfTzhR7e14VlKmbS2UWfn0ln8ZmKh2/vKnnZwhtenm+iMrwYffd9rbXSWt+utd5ffPyvStdDlEbYb3G4r4OM7TISz5DNO7hak807jMQzZGyXw30dZelC29wS4RMP7SadcxmcTJHO2biOQzpnF392+cRDu2UCbQ3x8nwTlaG0Xr5PvhocOHBAv/DCC15XQyzD84wOLw9x7MyCjA4723n4dsnoUKtqIKPDqsdp1+j1b8n9l6AkhBCVJ0FpCZKQVQghRNWQoCSEEKJqSFASQghRNSQoCSGEqBoSlIQQQlQNCUpCCCGqhgQlIYQQVWNdzFNSSo0BF72uxw1qA8a9roRH6nXf63W/oX73/Wb3e1xr/eBqXqiU+uZqX1sL1kVQWo+UUi9orQ94XQ8v1Ou+1+t+Q/3ue73udzlJ950QQoiqIUFJCCFE1ZCgVD5HvK6Ah+p13+t1v6F+971e97ts5J6SEEKIqiEtJSGEEFVDgpIQQoiqIUGpxJRSm5VS/6CUOqWUOqmU+rjXdaokpZSplHpJKfWY13WpJKVUk1Lqa0qp00qpfqXUPV7XqRKUUv+ieJ6/qpT6ilIq6HWdykUp9UWl1KhS6tUFv2tRSn1bKfV68Wuzl3WsBRKUSs8GflNrvQc4CPyKUmqPx3WqpI8D/V5XwgO/D3xTa70b2EcdHAOl1Cbg14EDWutbARP4kLe1KqsvAW+cxPpbwFGt9S3A0eLPYg0kKJWY1npIa/2j4vezFC5Om7ytVWUopbqBh4HPe12XSlJKNQL3A18A0FrntNbTnlaqciwgpJSygDBw1eP6lI3W+ilg8g2//kngT4rf/wnwjypZp1okQamMlFJbgTuA5zyuSqX8F+ATgOtxPSptGzAG/HGx6/LzSqmI15UqN631FeA/AZeAIWBGa/2kt7WquE6t9VDx+2Gg08vK1AIJSmWilIoCfw38htY67nV9yk0p9T5gVGv9otd18YAFvAX4Q631HUCSOujGKd4/+UkKQXkjEFFK/Yy3tfKOLsyvkTk2ayRBqQyUUj4KAenLWuu/8bo+FXIf8BNKqQvAXwDvUkr9D2+rVDGXgcta67kW8dcoBKla927gvNZ6TGudB/4GuNfjOlXaiFKqC6D4ddTj+qx7EpRKTCmlKNxb6Ndaf87r+lSK1vq3tdbdWuutFG52f0drXRefmrXWw8CgUmpX8VeHgVMeVqlSLgEHlVLh4nl/mDoY4PEGXwd+rvj9zwF/52FdaoIEpdK7D/hZCi2F48XHe72ulCi7XwO+rJR6GdgPfMbb6pRfsWX4NeBHwCsUric1m3ZHKfUV4Blgl1LqslLqY8B/BN6jlHqdQsvxP3pZx1ogaYaEEEJUDWkpCSGEqBoSlIQQQlQNCUpCCCGqhgQlIYQQVUOCkhBCiKohQUmUhVLKKQ6Hf1Up9Q2lVNNNbud3lVLvLnH1brQOX1FKbVNK/YZS6sMLfv+rSqmzSimtlGrzso5C1AoJSqJc0lrr/cXs0ZPAr9zMRrTW/5fW+u9LW7U3KyYUXcpWrfV54BDw1ILf/4DC3JSL5azbQivUU4h1T4KSqIRnKGZKV0ptV0p9Uyn1olLqe0qp3UqpRqXURaWUUXxNRCk1qJTyKaW+pJT6QPH3dyqljhX/9ltKqS6lVIdS6sXi8/uKrZae4s/nitkG2pVSf62U+mHxcV/x+X+rlPozpdQPgD97Y6WVUl9WSp0CdiuljgMPAI8rpX4RQGv9ktb6wnI7rpTaq5R6vthqfFkpdUvx9/9b8ecTSqk/K/5uq1LqO8XfH12wH19SSv2RUuo54LOLHcO1vT1CVBGttTzkUfIHkCh+NYG/Ah4s/nwUuKX4/d0U0hFBIT3LO4vffxD4fPH7LwEfAHzA00D7gtd8sfj9SaAB+FXgh8BHgC3AM8Xn/xx4W/H7HgopoAD+LfAiEFpmP/4p8JvF7f3VEq+5ALQt8dz/C3yk+L0fCAF7gTNzfwO0FL9+A/i54vcfBf7ngmPwGGAudwzlIY9aeEhXgCiXULF1sYlCPrRvFzOn3wv8VSFVGgCB4tevUgg0/0Ahd97/94bt7QJuLW4HCsFubsmApymkd7qfQnqfBwEFfK/4/LuBPQvKbCjWBeDrWuv0MvvxFgpB4HbgxCr2+42eAT5VXGvqb7TWryul3kUhwI0DaK3n1ui5B3h/8fs/Az67YDt/pbV2VjiGQqx7EpREuaS11vuVUmHgWxTuKX0JmNZa71/k9V8HPqOUagHuBL7zhucVcFJrvdgy408Bb6fQmvk74F9RWELg8eLzBnBQa525boOFi3pyscoX8xV+hsKyDO8D2oGkUuqw1vqdS+/29bTWf17sdnsY+F9KqX+22r99g7l6Gix9DIVY9+SekigrrXWKwpLZvwmkgPNKqX8KhYzqSql9xdclKHS9/T7wmNbaecOmXgPalVL3FP/Wp5TaW3zue8DPAK9rrV0KAyveC3y/+PyTFBKmUvzb/auo9/+iEBxf1VrfRqGL8I4bCUjFsnqBAa31/0MhYN5OIeD+U6VUa/E1LcWXP8215cQ/wrWW3sJ6xVniGApRCyQoibLTWr8EvAx8mMLF9mNKqRMULvQ/ueClX6UQXL66yDZyFO4t/V7xb49TXLtHFwYbKK6NjPs+hdbEVPHnXwcOFAcQnAJ+eZVVvwM4oZTyAz79hsUalVK/rpS6DHQDLyulFlsG/qeAV4tdmbcCf6q1Pgl8GjhW3Je5JU5+DfgFVcg0/rPAx5eo13LHUIh1TbKECyGEqBrSUhJCCFE1JCgJIYSoGhKUhBBCVA0JSkIIIaqGBCUhhBBVQ4KSEEKIqiFBSQghRNX4/wESXilRCore2wAAAABJRU5ErkJggg==\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.jointplot(data=score_sheet, x='Reviewer #3 score', y='Reviewer #2 score', **opts);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## dependance of score and confidence\n" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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PHutlx9Fe6lMxVrbWcVlLLViz4pA6Y2bFp7mitY7M0Z2anJRSl6Q2GePKxXO4cvEcMnmXQ51DHOgc5IWX+3ju+BnqNv5S1CFWlVmRoJRSqtRScZsNCxvYsLCBvOtxvGeYz3/2iajDqiraNU0ppS5R3LZY0VqHO9QbdShVRROUUkqpsqQJSimlVFnSBKWUUqosaYJSSilVljRBKaWUKkuaoJRSSpUlMYURUiuEiHwfaIk6jovQAnRFHUQEZut2w+zd9tm63XDx295ljHl9qYOpdBWXoCqViOwwxmyKOo6ZNlu3G2bvts/W7YbZve1h0CY+pZRSZUkTlFJKqbKkCWrm3BN1ABGZrdsNs3fbZ+t2w+ze9pLTc1BKKaXKktaglFJKlSVNUEoppcqSJiillFJlSROUUkqpslRxCer1r3+9AfSmN73prZpuRani49+4Ki5BdXXN1hFUlFKz3Ww7/lVcglJKKTU7aIJSSilVljRBKaWUKkuaoJRSSpUlTVBKKaXKkiYopZRSZUkTlFJKqbKkCUoppVRZikUdQJiO9wzxwM52tu/vZDjnUJOIsWV1K7dtbGNJU23o5XcNZnjqQDdPHO5mOOtQk4xxw2XNbF7VTEtdqmrLHs45HOkaYk/HAJmcSyphs25+PctbaqlJhPuVi7LsqMvfd6qfe58+xuMHOsnkXVJxm1etauWO65ayZkFDqGVHua9FvZ9H/Z2rZhU3H9SmTZvMjh07plzu6cPdfPLBPTiuobkuQdIWsq6hezBHzBY+fOs6rrusObQ493UMcM/2QziuR3NdglTMIuN4QfkW27asYM38+qoru2swy8O7T+O6Ho3pOImYRc7x6BvJY9sWW9fPo6UuWXVlR13+Q7tO8fH7d+F4hrnpOHFbyLuG3pE8MUv46O0buGXDglDKjnJfi3o/L+H/XIpZqNjjXwUad/tDbeITkSMi8oKIPCciF3yq4vuMiBwQkedF5JpSlHu8Z4hPPriHdMJicVMN6UQMy7ZJJ2LBY4tPPriH4z1DpSjuAl2DGe7ZfoiaMeWLZY2WX5OwuGf7IboGM1VV9nDO4eHdp0nFLOY1pEjGbUSEZNxmXkOKVMzi4d2nGc45VVV21OXvO9XPx+/fRTJu0daYJpWIYds2qUSMtsY0ybjFx+/fxb5T/SUvO8p9Ler9POrv3GwwE+egXmOMucoYs2mc124FVge3bcDnS1HgAzvbcVxDY3r8Xy6N6SR51/DA8+2lKO4CTx3oxnE9GtKJcV9vSCfIuR5PHeypqrKPdA3huh61yfGbNWqTMRzX40hX6Q8YUZYddfn3Pn0MxzM0pCb4n6cS5F3DN545VvKyo9zXot7Po/7OFcPzDJm8G1n5lyrqThJvBL5mfE8Bc0Sk7VJXun1/J8114++sBS11Cbbv67zUosb1xOHuKctvrUvwxKHSD/wYZdl7OgZoTMcnXWZOOs6ejoGqKjvq8h8/0MncKcpuqonz2P7Sf9+j3Nei3s+j/s4V47a//Qm/e+/PIyv/UoWdoAzwkIg8KyLbxnl9EXB8zOMTwXPnEJFtIrJDRHZ0dk79ZRvOOSTtyZt0k7aE19yTdUjFJv9okzGL4WwITV0Rlp3JuSSmKDses8jkSv+LLsqyoy4/k3eJT/F9j9sSyi/pKPe1qPfzmfqfjz3+Pffcc4hI0befP/ME333wh9N6z0S3JUuXXdJ2XIywu5jcZIx5WUTmAT8UkT3GmMemuxJjzD3APeCfJJxq+ZpEjKxrSNsTL5N1TWg9bGqSMTKORzox8Zc363jUTNA0UKllpxI2OccjGZ/4g887HqnEJP+YCiw76vJTcZu8a7AnWXXeNaQmie1iRbmvRb2fz9T/fOzxT0TM3Q/tLfq99+08yWDG4Y+m8Z6J3HXL2ktex3SFWoMyxrwc/D0N/Dtw7XmLvAwsGfN4cfDcJdmyupXuwdyky3QN5tiypvVSixrXDZc1T1l+52COG1a0VFXZ6+bX0zeSn3SZMyN51oXQgzDKsqMu/1WrWumdouye4Tw3ry799z3KfS3q/Tzq71wxkjGLrKPnoC4gIrUiUl+4D9wCvHjeYvcBbw96820G+owxl3xG87aNbcRsoW8kO+7rfSNZ4rZw25WXfLprXJtXNROzLfpHxt95+kdyJGyLzSubqqrs5S212LbF0ATNh0NZh5htsbyl9NemRFl21OXfcd1SYpbQn5ngf57JEbeFt167tORlR7mvRb2fR/2dK0ah23ulCrMGNR/4iYjsBJ4BHjDGfF9E3isi7w2W+R5wCDgA/APw/lIUvKSplg/fuo6RnMfxnmFGcg6e6zKSc4LHHh++dV1oF/G11KXYtmUFwzmPY4XyPY+RnMOxnmGGcx7btqwI5YLZKMuuScTYun4eGcejoz9DNu/iGUM279LRnyHjeGxdPy+05p6oyo66/DULGvjo7RvI5j1Onhkhk3NwXZdMzuHkmRGyeY+P3r4hlIt1o9zXot7Po/7OFSMZs8i6HpV2vWtB1V6oC8EV5s+3s33fmCvM17Ry25UzOJLEwR6eONR1djSHFS1sXtk0MyNJRFS2jiQR3UgS33jmGI/tPzuSxM2rW3nrtTM0kkRE+1rU+3mJ/udFXag73XNQzx7t5ScHunjflpVTduiYyl23rA0z0Y27/VWdoJRSqkKEkqBefLmPh/ec5rdvXE59avIu8VOJIkFFfR2UUkqpkBRqTZV6HkoTlFJKValkkKCymqCUUkqVk2TMvwZLE5RSSqmycrYGVZnXQmmCUkqpKqXnoJRSSpUlPQellFKqLMVsC1tEE5RSSqnyk6jg8fg0QSmlVBVLVvB4fJqglFKqiiXjljbxKaWUKj+VPKK5JiillKpiyZhNNq8JSimlVJmp5EkLNUEppVQVS8VsMk5lzgmlCUoppapYKm7hegbH0wSllFKqjKQS/oCxI/nKa+bTBKWUUlUsHfcTVEYTlFJKqXKSCqbcGMlpglJKKVVG0olCDaryupprglJKqSqWivuHeW3iU0opVVZScRsRGMo5UYcybbGoA1BKKVUcy7a565a1037fovd9mUe/+zDf/t7fXHTZi5csvej3XiytQSmlVIXwXBdjzLRv171iLb/4xl+7qPcWbsePHZ3x7dUEpZRSVa6tMUV730jUYUybJiillKpyC+ekae/LVNxwR6EnKBGxReTnInL/OK/9loh0ishzwe3dYcejlFKzTVtjiqzj0T2UizqUaZmJThJ3AruBhgle/6Yx5oMzEIdSSs1Ky5prADjaPURLXTLiaIoXag1KRBYDtwFfDLMcpZRSE1vRUgfAoc6hiCOZnrCb+D4FfBiY7BLm/yEiz4vIt0VkyXgLiMg2EdkhIjs6OzvDiFMppcrS2OPfxa5j8dw0MUs43KUJCgARuR04bYx5dpLFvgssN8ZcCfwQ+Op4Cxlj7jHGbDLGbGptbQ0hWqWUKk9jj38Xu46YbbG0uUZrUGPcCLxBRI4A3wBeKyL/PHYBY0y3MSYbPPwi8MoQ41FKqVlrRUud1qAKjDEfMcYsNsYsB94KPGKM+Y2xy4hI25iHb8DvTKGUUqrEVrbWcrh7CMetnEFjZ/w6KBH5CxF5Q/DwQyLykojsBD4E/NZMx6OUUrPB2gX15ByvompRMzIWnzHmx8CPg/sfG/P8R4CPzEQMSik1m61v86/02dXez+r59RFHUxwdSUIppWaBla11xG1hz6mBqEMpmiYopZSaBRIxi1Xz6tnd3h91KEXTBKWUUrPE+jZNUEoppcrQhrYGOvqz9FTImHyaoJRSapYodJSolFqUJiillJol1i3we+9pglJKKVVWmuuSzG9IsksTlFJKqXKzvq2BXSc1QSmllCozG9oaOHB6kKzjRh3KlDRBKaXULLK+rQHHMxw4PRh1KFPSBKWUUrPIhoXBkEcV0MynCUoppWaR5c21pOM2u9vLf8gjTVBKKTWL2JawdkE9u9r7og5lSpqglFJqltmw0O/JZ4yJOpRJaYJSSqlZZn1bA/0Zh5N9mahDmZQmKKWUmmVWz6sD4FBneffk0wSllFIVwrIsROSSbzdtXAPAL7/lnSVZ38XclixdNuX2zsiMukoppS6d53nc/dDeS16PMYbPbz/I1t/+CFvW3l2CyKbvrlvWTrmM1qCUUmqWERHm1CToHSnvaTc0QSml1Cw0Nx3nzHA+6jAmpQlKKaVmoTk1CfpH8nhe+XY11wSllFKzUF0yhgGG8+U7aKwmKKWUmoVqkzYAQ1kn4kgmNmt68WWCXwlx28K2JOJolFIqWrVJ//CvCaoM9A7nGMn5SUpEiFlC3LaI20IiZvk327/GQCmliuG4HjnXI+8YLAvqU/GoQypaIUENaoKKxnDO4UjXEHs6BujoyyCWsKK5lsVz06TiNnnXO2d5ESEZs0jFbZIxi2TMImZffCto12CGpw5088ThboazDjXJGDdc1szmVc201KUudfMmte9UP/c+fYzHD3SSybuk4javWtXKHdctZc2ChlDLjnK7nz7UxeceOcDPjvfiuIaYLVyzZC7vf+0qrlvREmrZUZcfZdnb93bw6R/t46X2flwPbAsub2vgztetYcva+aGWPRNcz5B3PbKOR87xyLv+X88YMnmXE70jnOwbIWFbpBI26+bXs7yllppE+R5iUzH/2JZ1vCmWjI6U+2CB59u0aZPZsWPHlMt1DWZ5ePdpXNejMR1nMOswlHUYzDpYlsX1K5uYW5OYcj0xyyIZt4KE5Scuq4gmwn0dA9yz/RCO69FclyAVs8g4Ht2DOWK2xbYtK1gzv76obZ6uh3ad4uP378LxDHPTceK2kHcNvSN5Ypbw0ds3cMuGBaGUHeV2/+NPD/PX39+DwZCO28QEHAMjeRdB+MPXr+OdN14WStlRlx9l2Z99ZD+f/tE+ABK2YAu4BnKuf2y583Vr+OBrV4dSdhhcz5B1XDJ5j6zjkncMjjf+Qbx3OMeTB3vwPI+WuiSt9UlyjkffSB7btti6fh4tdcliii2q6UZETCku1AX/Yt3PPnqAa5bO5cZV4f94O99dt6wdO1jtuNsfeicJEbFF5Ocicv84ryVF5JsickBEnhaR5aUoczjn8PDu06RiFvMaUiTjNiJCIm7TVJckGROePNgzel5qMo7nMZR16BnK0d43wpHuIY73DNM5kKU/kyc3zq+PrsEM92w/RE3CYnFTDelEDLEs0okYi5tqqElY3LP9EF2DpR+ocd+pfj5+/y6ScYu2xjSpRAzbtkklYrQ1pknGLT5+/y72nSr9ZGVRbvfTh7r46+/vIWYLc9IJkjEb27ZJxmzmpBPEbOGvv7+Hpw91lbzsqMuPsuxCzcm2hLpkjERQdiJmU5eMYVvCp3+0j+17O0pedikYY8g5/j7ePZjlRO8wR7uHONWX4UxwWmCi5JTJuzx5sIdkTPzjSnCcScZt5jWkSMUsHt59muFceTahiQgJ2yLnlm8NaiZ68d0J7J7gtXcBvcaYVcDfAH9VigKPdA3hut5oG+v50okYrudxonfkotafdz0GMnm6Bvwv9JGuIdr7RugZyjGYdXh8byd5x6UhPX4NrSGdIOd6PHWw56LKn8y9Tx/D8QwNqQnKTiXIu4ZvPHOs5GU/daAbx/Ui2e7PPXIAg6F2giaV2kQMzxg+/+MDJS876vKjLLtQc0rH7XFfT8dtjIHPPLyv5GVfjEzepW84z+n+DMd7hjncNcSJ3mE6+jP0jYz/g3MiJ3pH8DyP9ESfezKG43oc6RoqVfgll4hZ09rmmRZqghKRxcBtwBcnWOSNwFeD+98GtkoJeins6RigMT35ycr6ZIxD3aX54njGMJJzOTOc43R/hof3niYes+gfyTOYdRjJueQcD9czo1Xa1roET4Twi/bxA53MnWLbm2riPLa/s+RlP3G4m+a6yZtNw9runx3vnfAgWVCTsHn2aG/Jy466/CjLfqm9n4Q9+S6bjAkvztD04sYYPM+MnjMazjmjCelo9xAnz4zQPZRlMOtccA56ug51D1E3wY/ggjnpOHs6ynfmWtsS3DK+UDfsM3ifAj4MTHTSYRFwHMAY44hIH9AMnHMEE5FtwDaApUuXTlloJudSXzf5psVjFoND4YxDlcm5NCZjuMbguobzBxOxRQBD71COgUyeuO2f4ypFD8JM3qV+ip0mbgtnRkp/cd5w1mHuFL2YkjGL7qFsyct2XEN6im9zTGDEDWdnjLL8KMt2PZji64YtkA3pWlDH9RjKumQdl2zQeWGm5HIutbWT/yCLxyz6Bi9tOKGxx79Sk+JOfUUmtAQlIrcDp40xz4rIqy9lXcaYe4B7wO8kMdXyqYRNzvFITvKrMu94JBKT/+q8WKmETdY1JCeon7rGkM272JbQOeAfrEWEuC1+R4y43+X9Yq7Z8nsnGuxJNi3vGlJT/OK+GDXJGBnHI52YuGKedTxqpjqiXYSYLTgGJtsqx/jLhSHK8qMs27b8DhGTle0af7lSMcYwkHUYyDhkIxwFIZGw/ePIFMeZ1CUeZ8Ye/0SkfKs7IQizie9G4A0icgT4BvBaEfnn85Z5GVgCICIxoBHovtSC182vp29k8l8tA1mHFc21l1rUuK5ePGfKQRh7hvNcvWTu6OPCydrCua2TZ0Y42j3E0e4hXj4zwumBDH3DeUZy7qRV8letaqV3im3vGc5z8+rW6W1UEW64rJnuwclrpZ2DOW4IocvzNUvmMjLFwWo45/LKZXMnXaYSy4+y7MvbGkZ7600k6xiuWHhplzYY4/es6xnKcaxnmK6BbKTJCWBFc+2U1xCdGcmzLqReq7NBaAnKGPMRY8xiY8xy4K3AI8aY3zhvsfuAdwT33xQsc8m/EJa31GLb1oRXSI/kHGzLYvHc9KUWNa6rls3FtoShzPiJYiiTJ24JVy2dM+W6XM+vbQ1mHLqHsrT3+YnrSJffm7Cj309cmbyLMYY7rltKzBL6M+Mniv5MjrgtvPXaqZtKp2vzqmZitkX/BEP494/kSNgWm1c2lbzs9792FYIwNEGPqaGcgyXC+169quRlR11+lGXf+Tp/4ruJEuRI3kUEPrR1TdHrdD3DcM6hdyhHx5jODC/3jnBmOFc250wWz01jWRYjE33uWYeYbbG8JZwfwqXgYcq6kW/Gx+ITkb8QkTcED78ENIvIAeAu4I9LUUZNIsbW9fPIOB4d/RmywcE7l3fpHsySdQzXr2wKpZkLYG5Ngrdcu4SRvEd7X1C+55HNu7T3ZRjJe7zl2iVFXYc1Ec/4J4GHsn7iOnlmhCPdw9Sn49z5ujWM5Fxe7h0mk3NwXZdMzuHkmRGyeY+P3r4hlIt1W+pSbNuyguGcx7GeYUZyDp7nMZJzONYzzHDOY9uWFaFcrHvdihb+8PXrcFxD73COrOPiuv65id7hHI5r+MPXrwvtgtUoy4+y7C1r53Pn69bgeoaBjEMuKDvnuAxkHFzPTHmx7mjLwXndvHuHcwyVoDNDWFJxm+tXNpF1jH9cybt4QfN9R3+GjOOxdf28sr5YN+96xGPlOyRr1V6oC1OPJBG23uEczx07w8+P95LJuaQSNlcvmctVS+dcUnIqxpGuQR54vp0dR3vIOR6puM1Nq1p467VLuXzRnFDL7hrM8NTBHp441HV2JIkVLWxe2TQjI0l8/scHePbo2dEUXrlsLu979cyNJBFV+VGWvX1vB595eB8vnjw7ksQVCxv40NYLk1OhhjSScxnO+Qf1SlaikSRm/EJdgM//+CAbFjawZU3pm/ynUsyFulWdoMZq7xsZHYtvtrPEH38wZgmWJdgiWCJYlt/t1LaEmKWD6qqLY4zBCbp6O57BcT3yrl/jz7te2TTRlVpdKsa8+ov+ARbJSBKfeeQA1y5v4vqVzSVZ53QUk6DKt+6pQlMYP2wqlgjxmD+gbtK2icf8AXZtkaKGe1LVyxhD3jWj3bsL1/m5nqn4GtFs4QQ/FOIh9WwtBU1QakKF9vRsHga58ESwFdS8RMCyZDSRFcYu1JHhK8vYBON6Bje46NXxgotfC88HN1XZhoMWpXRIl9uUgiYoddE8M+bXsss5iWzsdV1xW4jZ1ugUJ9p0GA1jDLlgRO684/nNb55/MblrDJXW3K8uTaGX80RDwpWD8o1MVTT/ui4z7jhfY+fjsoOaV+G8V6HSZQUJTmth01eYCqIwLURek5Aax2iCKuNehuUbmapahfMXxXQfti2/9pUIbrYtWHK2edESf5nZmMjOn6PInzjP03NAqihDQRNfYer3clR8H0iRGmPMcJjBKHU+/3yHO+WoAYVEFh/TC9Gy/EQ2WZOiXejFWCbNjp5nMDBa0/GM35Ra6A1XSESOq50R1KUZyjpYMvFI9OVgygQlIjfgj0ZeBywVkY3Ae4wx7w87OKWKNZrILvL9hURWaHYs1NJEwBgw+P1gRfwmSmvM38LrnjEY7+y5OREZfU8h0RgTrGNs3MbguNoDTs2swaxDTSJW1q0PxdSg/gb4JfxhiTDG7BSRm0ONSqkZ5hmDV2Szo1JRsWybu25ZW5J1zf+NvwYnz11/8fqSrG+6Fi+Zeri1osa4MMYcP+8pveJVKaVmmOf6w7aV4rZwzUbe+ebbSra+6d6OHzs65fYWU4M6HjTzGRGJM/kMuUoppcpc30ienqEcy0Ka0aFUiqlBvRf4AP7kgi8DVwWPlVJKVaCjwWziy8s8QU1ZgzLGdAFvm4FYlFJKzYDDXX6CuqyMpwKBImpQIvJVEZkz5vFcEflyqFEppZQKzdFu/4qhZc01EUcyuWKa+K40xpwpPDDG9AJXhxaRUkqpUB3pGqKtMTUj0w5dimISlCUio3NFi0gTOgKFUkpVrCPdQ2V//gmKSzT/D3hSRL6Ff33hm4CPhxqVUkqp0BzpHuaXLl8QdRhTKqaTxNdE5FngNcFTv2qM2RVuWEoppcJQ6GK+vMzPP0HxTXV7gN7C8iKy1BhzLLSolFJKhWK0i3mZ9+CD4sbi+13gz4AO/BEkBH/osSvDDU0ppWaeMYUBe8+9D8F4ioVlgjEYC/cdz5CK2zSk4tEFX4QjFdKDD4qrQd0JrDXGdIcdjArH+TuZMQbPnPca5+50mLM7IwY8zLg7rDEGL1jGcOFOaxh/h2fMAKsUXhst4+z9wmte8IZzYircn+L9XvCYSWLzggBH4zz/8wjW55kL73ujn9nEBzYTLDfu5zTOeyY6MI67DaOfzYX3x5Yz+lme85mP/7mZ897PeJ/TuLFO9Nmcvw0X/50Y+30Yu22eGbOdk3ymF2z/Of/nS7N5RRPf2HZ9CdYUnuM9foJa2lQdCeo40Bd2IGH6k39/geM9wzhuYbc4u6ONPbh4nLuTXXgw818bu9NNtEN75rwDIhMceMceOMYchOG8HWjM+xmvjAtiLd1Op5QqjqmAHe5o9xCt9UlqyniiwoJiIjwE/FhEHoCzsxkYY+4OLaoS++mBrtEL01R1GDv1xQX3gwUEfzqMwv2x01wUptIQOft8YZmxr1NY95j3X1DmmPcj+FNxBPdl3Pf7AUqwLEGcEhQ29v5476cwFciY7Rzv8zhnGwrvH2ddF2xbcN8K3jzea4UpGibd1knWfc52TrBM4XO64LM553MZs4ycuy4ErHH+p2PjGn1+9LOY+DtR+EzP/34U3l+birF4TvnXSo52D7OsAmpPUFyCOhbcEsGt4rzpmsUc7x3G9cykO814X8zC8oUv7zk77XgHxwkORufsQKPLTVT+ue8vrPvCg9EUO1DwnvN3wHMPPJMcTMaU769znIPReds9XhnWBO+3ZIIDG2fLPP+zKaxLqXJTl4oxrz4VdRhTOtYzzPUrm6MOoyjFdDP/c6CiZ9T93a2rae8bYSSns4QopWavTN7lVH+GZU3l34MPihuL73oR2YXf1RwR2Sginws9MqWUUiV1oncEY2BpczrqUIpSzFBHn8KfUbcbwBizE9AZdZVSqsKcPDMCwOK5lXEOKrQZdUUkJSLPiMhOEXlJRP58nGV+S0Q6ReS54PbuIuNWSik1TR39GQAWNJT/uTIId0bdLPBaY8xg8L6fiMiDxpinzlvum8aYD04vbKWUUtN1esDviN1an4w4kuKENqOu8Q0GD+PBrQKuElBKqerU0Z+hMR0v+2k2CkKdUVdEbOBZYBXwd8aYp8dZ7H+IyM3APuD3x2lORES2AdsAli5dejGhKKVURRp7/LtUHf0Z5jdURu0JJklQIvK3TFLjMcZ8aKqVG2Nc4KpgRt5/F5ErjDEvjlnku8C9xpisiLwH+Crw2nHWcw9wD8CmTZu0FqaUmjXGHv9E5JKOfx392Yq4Vqtgsia+Hfi1nxRwDbA/uF3FNC/YDWbkfRR4/XnPdxtjCqNTfBF45XTWq5RSqnh9I3maaitnvIUJa1DGmK8CiMj7gJuMMU7w+AvA41OtWERagbwx5oyIpIFfBP7qvGXajDHtwcM3UFznC6WUUhehfyRPQ7r8x+ArKCbSuUAD0BM8rguem0ob8NXgPJQF/Ksx5n4R+QtghzHmPuBDIvIGwAnW/1vTjF8ppVQRjDH0Z/JlPx3IWMUkqL8Efi4ij+IPi3Yz8D+nepMx5nng6nGe/9iY+x8BPlJssEoppS5OJu+Rdw0N6SpKUMaYfxSRB4Hrgqf+yBhzKtywlFJKlVJ/Jg9Afapymvgm7CQhIuuCv9cAC/HnhToOLAyeU6oiiAhx2yJmWdiWjI6UXgqWCLYlxCyLuH3uLRW3qU3GqE/FqUvGqEnESMVtknH7gmVjlqUjtaspWZYVjOw//dviFasB2PbOt1/0Oia6LVm6LJTtnSyV3oXf9/7/jfOaYZzu4EpFyU9EfrKI2X5SSsb82/lJyfMM3uiElf7kjoUpPwpzDhW4wbKFZQpJ6fzlSqUw47E3Oumk/9f1DI5n8LyxMwmb0ZlkXWNwXH8ZUwkz56lp8zyPux/ae1Hv7RzI8i/PHOO3Pvo3rJpXV9K47rplbUnXVzBZgvph8PddxphDoZSu1CWwLSGdsKlNxEjE/JpIsSxLsCguudjWzNZsRARbwC4yvvF4hWRm/L+ua3A875xklnf859TsUPjRUkkV9ckS1EeAbwHfxr8OSqnQ2ZaMJpuYJX4iGWcySEv85dT4LEtIFJFYPc+Qcz3yrofjGvKuRy6472ktrKoUfopUS4LqFpGHgMtE5L7zXzTGvCG8sFS1ExFqEzbphO2ff7HAFiE2jVqQunSWJaQse9yx2ZwgWeUdQ9Z1ybuGnONp82GFKvzfim05KAeTJajb8GtO/8T456GUmlLhfI1tCTFbSNo28ZiQjtuhnL9RpROzLf8HQwL8sZ59+aDGlXf82pfjna1xFZoQVfkp/FsqabebbCSJHPCUiNxgjOmcwZhUBUrELP9W6JVmC3HLwprh8zcqfIWehxMNeFbogOIag+eBa4zfwcP1cDy/FqYdOWbe2QRVOftkUSNJiMjHgeVjlzfGaC++WUpESMYs0nG/aSgZ00Skzip0QJnq4FJIWFnHI+u45Bz/QlJNXOEonFOspF21mAT1LeAL+IO5TjmTrqo+lshoIkrFbVLxC7ttKzVdfhMiwfkvvwnRGD9h+ee+/ISVd7XGVQqFT0+q5BxUgWOM+XzokaiyEbMsbNuvJdUmYpqQ1IyR4MfQ+Z02jDFnk5V7tudh3vVwPU1cxai2buYF3xWR9wP/jj+NOwDGmJ6J36LKWcyySMYLoxj4F7SO7cygVLkRERKx8S8tGNtVPu+as70PtbnwHIU8XkkjlhSToN4R/P3DMc8ZYEXpw1GlVkhGyaATQzJmaxJSVWWqrvKF7vFZxyXr+IlsNqrKGpQx5rKZCERdurHJKBmzScQsTUZqViuc50onzp7nclyPjOORybujFycXhrOqZlVZgxKROPA+/Gk2AH4M/L0xJh9iXGoKtiWjSagw3pxe5KrU1GK2RZ1tUZc89/BXGB7K8c5enFxNPQursgYFfB7/p8fngse/GTz37rCCUucqDOuTjFkkg9500xl3Tik1tcLwUAkuvDg5N6ZnYc71gsRVWU2FZ3vxVY5iEtQvGGM2jnn8iIjsDCsg5V8ImYxbo127k7EL29aVUjOncCE6ybPPFbrE54OEFbPK+0fj2eugKidFFZOgXBFZaYw5CCAiK9DroUqmcNHr2WuMtBODUpVgoi7x5aqqhjoa4w+BR0XkEH7tcBnwzlCjqmKF2lEy5l/wmrD1GiOlVPiqcqgjY8zDIrIaKMxItdcYk53sPeqswpxF6bh/044MSqkoVOVQRyLyAeDrxpjng8dzReRdxpjPTfHWWanQuy4dt0kl9PyRUqo8uEGCqqRTCMU08f2OMebvCg+MMb0i8juc7dU3q9lW0A4d04SklCpfhSGhqi1B2SIiJuhELyI2Ew60X/3G9rBLBdchKaVUufMKCaqazkEB3we+KSJ/Hzx+T/DcrFBISHoOSSlVyQpNfJU0NU4xCeqPgG34o0kA/BB/6o2qZFsSnD/yE5JeEKuUqgae53fDrqrroIwxHv58UF8IP5yZN3oOKaghlbLJbjjncKRriD0dA2RyLqmEzbr59SxvqaUmUcxvg8os+3jPEA/sbGf7/k6Gcw41iRhbVrdy28Y2ljTVVm3ZADuP9/Klxw7x1JFuco5HImaxeXkz77p5BRuXzA217O17O/j0j/bxUns/rge2BZe3NXDn69awZe38UMved6qfe58+xuMHOsnkXVJxm1etauWO65ayZkFDqGV3DWZ46kA3TxzuZjjrUJOMccNlzWxe1UxLXSrUsiuJa0xF1Z4AJKwxpkQkBTyGf+11DPi2MebPzlsmCXwNeCXQDbzFGHNksvVu2rTJ7NixY9rxtPeNMJJzRyffC7uXXddglod3n8Z1PRrTcRIxi5zj0TeSx7Yttq6fR0tdcuoVVVjZTx/u5pMP7sFxDc11CZK2kHUN3YM5Yrbw4VvXcd1lzVVXNsC3nz3OJx7YjWcMdckYcQvyHgxmHSwR/uS29bzplUtCKfuzj+zn0z/aB0DCFmwB10DO9ffvO1+3hg++dnUoZT+06xQfv38XjmeYm44Tt4W8a+gdyROzhI/evoFbNiwIpex9HQPcs/0QjuvRXJcgFbPIOF7wP7fYtmUFa+bXh1J2iRWVOUTE3P3Q3osq4NG9p9l3aoD3bFl5Ue+fzF23rL3U8QrH3f4w26+ywGuDYZKuAl4vIpvPW+ZdQK8xZhXwN8BfhRVMQyrOwjlpljXXsKAxRWNNPLTkNJxzeHj3aVIxi3kNKZJx2x8xIm4zryFFKmbx8O7TDOecqir7eM8Qn3xwD+mExeKmGtKJGJZtk07EgscWn3xwD8d7hqqqbPBrTp94YDeJmNBSl/RHBLH9mnlLXZJETPjEA7vZeby35GUXak62JdQlYyRiftmJmE1dMoZtCZ/+0T627+0oedn7TvXz8ft3kYxbtDWmSSVi/nYnYrQ1pknGLT5+/y72neovedldgxnu2X6ImjH/c7Gs0f95TcLinu2H6BrMlLzsSpR1PJIVMupFQWgJyvgGg4fx4HZ+in0j8NXg/reBrRLSZc61yRip4GAdtiNdQ7iuR21y/Ka02mQMx/U40lX6g2WUZT+wsx3HNTSmx6+dNaaT5F3DA8+3V1XZAF967FBQc4qP+3pdMo7rGb78k0MlL7tQc0pPcPBJx22Mgc88vK/kZd/79DEcz9CQGr9jb0MqQd41fOOZYyUv+6kD3TiuR0N6grLTCXKux1MHdW5VgGzeJVlhvY4njFZEbBF5j4j8LxG58bzX/rSYlQfreA44DfzQGPP0eYssAo4DGGMcoA8Irw1mhuzpGKAxPf6BqmBOOs6ejoGqKnv7/k6a6ya/AqGlLsH2fZ1VVTbAU0e6L5i+4Xz1qRhPHuouedkvtfeTsCf/4ZWMCS+eLH0t5vEDncyd4vvWVBPnsf2l/9yfONw95f+8tS7BE4e6Sl52Jco6XsUlqMn2qL8HaoBngM+IyHZjzF3Ba78K/O+pVm6McYGrRGQO8O8icoUx5sXpBiki2/B7ErJ06dLpvn3GZXIu9XWTH6ziMYu+wdJPqRVl2cM5hzmpyctO2kL3UDhNm1GVDf50DLVTNJ/ELRjMln6KBteDKXIjtkA2hCGeM3mX+ikKj9vCmZHSFz6cdZibmjw5JmMW3UOVPTLb2OOfiHDXLWuneMf42t71d+S7T3DXH/+fUoYHwOIl4RyXJ0un1xpjft0Y8yngOqBORL4TdGyYVjuZMeYM8Cjw+vNeehlYAiAiMaARv7PE+e+/xxizyRizqbW1dTpFRyKVsMk5kx+I8o5HKlH69uAoy65JxMi6k58ozbomlF6EUZYN/nQM+SlyT94jlAu7bcvvEDEZ1/jLlVoqbpOfovC8a0IZ8bsmGSMzxXc963jUTJW9y9zY458x/uSJF3NbfNka3vm2t1z0+ye7HT92NJRtn+wrO1p3NsY4xphtwHPAI0DdVCsWkdag5oSIpIFfBPact9h9wDuC+28CHimMWFHJ1s2vp29k8hrKmZE860LoXRRl2VtWt9I9mJt0ma7BHFvWlP5HRpRlA2xe3sxgdvLa2UDG4foVpW/BvrytYbS33kSyjuGKhaXv7v2qVa30TvF96xnOc/Pq0n/uN1zWPOX/vHMwxw0rWkpedqVxPUP3UI7W+nB674ZlsgS1Q0TOqfEYY/4C+EdgeRHrbsOfpuN54L/wz0HdLyJ/ISJvCJb5EtAsIgeAu4A/nu4GlKPlLbXYtsXQBAesoaxDzLZY3lL663KiLPu2jW3EbKFvZPwmlb6RLHFbuO3KtqoqG+BdN6/AEmEwO/7BejCbx7aE375pRcnLvvN1awAYyY/fjDaSdxGBD21dU/Ky77huKTFL6M+Mnyj6MznitvDWa0vfBLR5VTMx26J/ZIKyR3IkbIvNK5tKXnal6R7M4nqGBQ2VdV3YhAnKGPMbxpgLhjQyxnzRGDN5w6+/3PPGmKuNMVcaY64IkhvGmI8ZY+4L7meMMW82xqwyxlxrjCl9F6cI1CRibF0/j4zj0dGfIZt38Ywhm3fp6M+QcTy2rp8XWlNXVGUvaarlw7euYyTncbxnmJGcg+e6jOSc4LHHh29dF8oFs1GWDbBxyVz+5Lb15BxD50CWTN7FdV0yeZfOgSw5x/Ant60P5WLdLWvnc+fr1uB6hoGMQ87xy845LgMZB9czoV2su2ZBAx+9fQPZvMfJMyNkco6/3TmHk2dGyOY9Pnr7hlAu1m2pS7FtywqGcx7HCv9zz2Mk53CsZ5jhnMe2LSv0Yl2gvc/vaj+/whLUlBfqishvG2O+PEPxTOliL9SNwqweSeL5drbvGzOaw5pWbrtyhkaSiKhs8K+H+vJPDvHkobMjSVy/opnfvmlmRpL4zMP7ePHk2ZEkrljYwIe2zsxIEt945hiP7T87ksTNq1t567UzNJLEwR6eONR1diSJFS1sXtlUScmp6At1L+YsyA9eOsV7/ulZ7vvgjVy5eM603z8Dxt3+CROUiLwFfySIB4wx1wTPPWyM2RpaiEWopASllFJFCjVBfe3JI3zsP1/imT/ZyrzyrEWNu/2T/ZReAPwdsEZEvgk8DywVkVpjTDiX4yullCq59r4MMUtoDmmIs7BM1kniP4wxvwrsB/4/YCd+773/FJEfz0BsSimlSuBI1xBLm2oqarJCmLwG9X9EZDmwFL8L+PPAaWPM60Rkyk4SSimlysPhrqFQeu6GbbJefL9ujLkBOAUcA7YCy0TkcfyBXZVSSpU5zzMc6R7isgpMUMV05/q5MebfgH8TkVuBLcDV4YallFKqFDoGMmTyXkXWoIqZsPA3xjz8k2ACw2fDC0kppVSpHO70+7StqMAENa3RuYwxD4YViFJKqdI70OnPerSitcoTlFJKqcqy62Q/c2viFTfMEWiCUkqpqrarvZ8NCxtmZLLWUps0QQUTDn59poJRSilVOo7rsefUABvawh1uKiyTJqhgwsFlIjL5tJVKKaXKzqGuIXKOx4YQplqZCcV0Mz8E/FRE7gNGhzgyxtwdWlRKKaUu2a6T/QBsaGuMOJKLU0yCOhjcLKD0s9wppZQKxa72fhIxqyJ78EFx10H9OYCI1BhjhsMPSSmlVCnsOtnP2vn1xO3K7A83ZdQicr2I7CKYrl1ENorI50KPTCml1EUzxvDSyb6K7SABxXUz/xTwS0A3gDFmJ3BziDEppZS6RKf6M/QO57l8UXUnKIwxx897yg0hFqWUUiVytoNE5SaoYjpJHBeRGwATTLNxJ7A73LCUUkpdikKCWlfBCaqYGtR7gQ8Ai4CXgauCx0oppcrUrvZ+ljfXUJcsph5SnoqJfNAY87bQI1FKKVUyu9r7ubxCL9AtKKYG9aKI/FRE/lJEbhORyrziSymlZomBTJ6j3cOsX1DlCcoYswq4A3gBuA3YKSLPhRyXUkqp89TV1RW13N5TAwAVO8RRwZRNfCKyGLgReBWwEXgJ+EnIcSmllDrP4OBgUcvtbq/8DhJQ3DmoY8B/AZ8wxrw35HiUUkpdol3tAzSkYixsrLw5oMYq5hzU1cDXgF8XkSdF5Gsi8q6Q41JKKXWR9pzqZ31bZc4BNVYx56B2Al8F/hF4BNgCfGyq94nIEhF5VER2ichLInLnOMu8WkT6ROS54DblepVSSk3M8wx7Tw2wvsKb96C4c1A7gCTwBPA4cLMx5mgR63aAPzDG/ExE6oFnReSHxphd5y33uDHm9ukGrpRS6kJHe4YZzrmsb6v8ySeKOQd1qzGmc7orNsa0A+3B/QER2Y1/se/5CUoppVSJ7Ak6SFRDDaqYc1CWiHxJRB4EEJEN0z0HJSLL8c9lPT3Oy9eLyE4ReVBELp/g/dtEZIeI7OjsnHauVEqpijX2+FfM8rvb+7EE1syv/BpUMQnqK8APgIXB433A7xVbgIjUAf8G/J4xpv+8l38GLDPGbAT+FviP8dZhjLnHGLPJGLOptbW12KKVUqrijT3+FbP8vo5BlrfUkorbYYcWumISVIsx5l8BD8AY41DkaObB4LL/BnzdGPOd8183xvQbYwaD+98D4iLSUmzwSimlznW4a4gVLcVd0FvuiklQQyLSDBgAEdkM9E31JvH7N34J2G2MuXuCZRYEyyEi1wbxdBcZu1JKqTE8z3C4e6hip3g/XzGdJO4C7gNWishPgVbgTUW870bgN4EXxgyN9CfAUgBjzBeC9bxPRBxgBHirMcZMawuUUkoB8PKZEXKOx2UtsyRBBd3EtwBrAQH2GmPyRbzvJ8Hyky3zWeCzRcaqlFJqEoe7hgBYUe0JSkRea4x5RER+9byX1ogI451TUkopFZ1CgrpsFjTxbcEfOeK/jfOaATRBKaVUGTncNURdMkZrXTLqUEpiwgRljPmz4O67jTFF9dpTSikVnSPdQyxvqan4MfgKiunFd1hE7hGRrVItW62UUlXo5JkRFjamow6jZIpJUOuAHwEfwE9WnxWRm8INSyml1HS1n8mwcM4sSlDGmGFjzL8aY34Vf7iiBmB76JEppZQq2kAmz0DWoa3C54Aaq5gaFCKyRUQ+BzwLpIBfCzUqpZRS03KqLwNAWxXVoIqZbuMI8HPgX4E/NMYMhR2UUkqp6TkZJKhKn0V3rGJGkrhynEFelVJKlZH2MyMALKiiBFVME98CEXlYRF4EEJErReRPQ45LKaXUNLT3ZRCB+Q2zK0H9A/ARIA9gjHkeeGuYQSmllJqeM8M56pMx4nZRXQsqQjFbUmOMeea855wwglFKKXVx+kbyzKlJRB1GSRWToLpEZCVnp9t4E8FU7koppcpD30iexnQ86jBKqphOEh8A7gHWicjLwGHgbaFGpZRSalpmZYIyxhwCXicitfg1rmH8c1BHQ45NKaVUkfpG8rRV0TBHMEkTn4g0iMhHgqGNfhE/Mb0DOIBeqKuUUmWlbyRPY0111aAmOwf1T/iTFL4A/A7wKPBm4L8bY944A7EppZQaw7IsRGTcW2ffEJ//1P+b8PUlS5dFHf60yUQzrIvIC8aYVwT3bfyOEUuNMZkZjO8CmzZtMjt27IgyBKWUKrWiZooQEXP3Q3sveD7venzuxwe5cVUzm5Y1jfveu25Zy0TH+zIw7vZPVoMandY9mA/qRNTJSSml1IUyeX/KvlTMjjiS0pqsk8RGESkMcSRAOngsgDHGNIQenVJKqSll8h4AyVj1XKQLk8+oW12pWCmlqlTWCWpQ8eo6bFdXulVKqVko6wQ1qHh1HdKra2uUUmoWqtZzUJqglFKqwmXzWoNSSilVhjKOiwgkqmgkcyhuLD5VgYZzDke6htjTMUAm55JK2KybX8/yllpqEuH+2/ed6ufep4/x+IFOMnmXVNzmVataueO6paxZEG7nzyi3O+ryuwYzPHWgmycOdzOcdahJxrjhsmY2r2qmpS7cOYKi/txnu2zeIxnzL+KtJvrNqUJdg1ke3n0a1/VoTMepr4uRczyeO3aGF17uZ+v6ebTUJUMp+6Fdp/j4/btwPMPcdJz6ZIy8a3hodweP7D3NR2/fwC0bFoRSdpTbHXX5+zoGuGf7IRzXo7kuwdxUnIzj8aPdp/nxvi62bVnBmvn1oZQd9eeu/BpUssrOP0GITXwiskREHhWRXSLykojcOc4yIiKfEZEDIvK8iFwTVjyzxXDO4eHdp0nFLOY1pEjGbUSEZNxmXkOKVMzi4d2nGc6Vfkqvfaf6+fj9u0jGLdoa06QSMWzbJpWI0daYJhm3+Pj9u9h3qn/qlU1TlNsddfldgxnu2X6ImoTF4qYa0okYYlmkEzEWN9VQk7C4Z/shugZLf5191J+78mXzHqkqO/8E4Z6DcoA/MMZsADYDHxCRDectcyuwOrhtAz4fYjyzwpGuIVzXozY5fuW4NhnDcT2OdA2VvOx7nz6G4xkaUuNPmtaQSpB3Dd945ljJy45yu6Mu/6kD3TiuR0N6gs89nSDnejx1sKfkZUf9uSuf1qCmyRjTboz5WXB/ANgNLDpvsTcCXzO+p4A5ItIWVkyzwZ6OgSnnhJmTjrOnY6DkZT9+oJO5U5TdVBPnsf2dJS87yu2OuvwnDnfTXDf5TKqtdQmeONRV8rKj/tyVT2tQl0BElgNXA0+f99Ii4PiYxye4MIkhIttEZIeI7OjsLP3BrZpkci6JKYY7iccsMjm39GXnXeL25Cdp47aMXrNR0rIj3O6oyx/OOqSmKDsZsxjOlr6ZLerPfTYYe/ybaJms42kN6mKISB3wb8DvGWMu6uSDMeYeY8wmY8ym1tbW0gZYZVIJm1xwVflE8o5HKlH6L3MqbpN3Jx8tOe+aUIZjiXK7oy6/JhkjM0XZWcejZoJmuEsR9ec+G4w9/k3wOhnH1RrUdIlIHD85fd0Y851xFnkZWDLm8eLgOXWR1s2vp28kP+kyZ0byrAuhR9erVrXSO0XZPcN5bl5d+h8ZUW531OXfcFkz3YO5SZfpHMxxw4qWkpcd9eeuIOd6GIPWoKZD/A75XwJ2G2PunmCx+4C3B735NgN9xpj2sGKaDZa31GLbFkMTNOcMZR1itsXyltqSl33HdUuJWUJ/ZvyDZX8mR9wW3nrt0pKXHeV2R13+5lXNxGyL/pEJPveRHAnbYvPK8ecJuhRRf+7q7CgSWoOanhuB3wReKyLPBbdfFpH3ish7g2W+BxzCn0b+H4D3hxjPrFCTiLF1/TwyjkdHf4Zs3sUzhmzepaM/Q8bx2Lp+XigXT65Z0MBHb99ANu9x8swImZyD67pkcg4nz4yQzXt89PYNoVysG+V2R11+S12KbVtWMJzzONYzzEjOwfM8RnIOx3qGGc55bNuyIpSLdaP+3NWYgWKrsAY14Yy65Upn1C1O1CNJfOOZYzy2/+xIEjevbuWt1+pIEmHqGszw1MEenjjUdXYkiRUtbF7ZpCNJlL+LnlH3eM8w3/n5y/yPaxaxeG7NhO+txBl1NUEppVT0LjpB7e8Y4HsvnuJt1y2ddMSOSkxQ1ddoqZRSs8hIvjonKwRNUEopVdEy2klCKaVUOSpcIB+zqu9wXn1bpJRSs8hI0BGpGmmCUkqpCpbJu6Q1QSmllCo3mbynNSillFLlx2/iq85DuV5Bp5RSFcKybe66Ze05zy3+0L0c/8l2fnjXFyZ97+IlpR9iLGzVmXaVUqoKea6LMWb0lndcYjX1/OmHf/+c58e7HT92NOrwp00TlFJKVai+kTzG+BOBViNNUEopVaF6h/2pTubWTj6jcqXSBKWUUhXqzLA/xcqcGk1QSimlyshoDUqb+JRSSpWT3qAGNVdrUEoppcrJ2SY+rUEppZQqI73DeeK2UJeszktaNUEppVSF6h3KMacmgUhR8x1WHE1QSilVoXqHc1XbQQI0QSmlVMXqHc5XbRdz0ASllFIV64zWoJRSSpWj3uE8TVU6igRoglJKqYpkjBntJFGtNEEppVQFGsw6OJ7RJj6llFLl5UwwzJHWoJRSSpWVah/mCDRBKaVURSoMFNtUq0180yYiXxaR0yLy4gSvv1pE+kTkueD2sbBiUUqpalPtU20AhDmA01eAzwJfm2SZx40xt4cYg1JKVaWeIW3iu2jGmMeAnrDWr5RSs1mhk0RjWpv4wnK9iOwUkQdF5PKJFhKRbSKyQ0R2dHZ2zmR8SikVqbHHv7HPD2Qc6pIxbKs6B4qFaBPUz4BlxpiNwN8C/zHRgsaYe4wxm4wxm1pbW2cqPqWUitzY49/Y5wcyeepT1TnNRkFkCcoY02+MGQzufw+Ii0hLVPEopVQlGcw6VTsPVEFkCUpEFkgwiYmIXBvE0h1VPEopVUkGMk7V16BC2zoRuRd4NdAiIieAPwPiAMaYLwBvAt4nIg4wArzVGGPCikcpparJQNap6g4SEGKCMsbcMcXrn8Xvhq6UUmqaBjJ5Fs9NRx1GqKLuxaeUUuoiDGYc6vUclFJKqXJgWRYigohwqruPv/+7TyMiLFm6LOrQQqEJSimlKoTnedz90F7+7/f3YCVS/NJb3s3dD+3lxPFjUYcWCk1QSilVYXKuB0A8Vt2H8OreOqWUqkKO53d4jtvVfQiv7q1TSqkq5AYJKlbFwxyBJiillKo4TtDEV83j8IEmKKWUqjiFGpQmKKWUUmXF0SY+pZRS5UhrUEoppcrS2RpUdR/Cq3vrlFKqCmkNSimlVFnSbuZKKaXKkuNpN3OllFJlSJv4lFJKlSXtZq6UUqosaQ1KKaVUWXI0QSmllCpHrmewLX/iwmqmCUoppSpMIUFVO01QSilVYRzPq/oOEqAJSimlKo7WoJRSSpUl19UEpZRSqgw5ntEmPqWUUuVntjTxxaIOQKlSOt4zxAM729m+v5PhnENNIsaW1a3ctrGNJU21oZc/nHM40jXEno4BMjmXVMJm3fx6lrfUUpPQ3U2VhuuZqp9qA0KsQYnIl0XktIi8OMHrIiKfEZEDIvK8iFwTVixqdnj6cDe/943nePDFU6TjNgsbUqTjNg++eIrf+8ZzPH24O9TyuwazfHdnO88dO0PSsmitS5K0LJ47dobv7mynazAbavlq9nBmSQ0qzBT8FeD1k7x+K7A6uG0DPh9iLKrKHe8Z4pMP7iGdsFjcVEM6EcOybdKJWPDY4pMP7uF4z1Ao5Q/nHB7efZpUzGJeQ4pk3EZESMZt5jWkSMUsHt59muGcE0r5anZx9RzUpTHGPAb0TLLIG4GvGd9TwBwRaQsrHlXdHtjZjuMaGtPJcV9vTCfJu4YHnm8PpfwjXUO4rkdtcvxmvNpkDMf1ONIVToJUs4vjeVqDCtki4PiYxyeC55Satu37O2muS0y6TEtdgu37OkMpf0/HAI3p+KTLzEnH2dMxEEr5anbRThJlRES24TcDsnTp0oijUeVoOOcwJzX51zlpC91D4TSxZXIu9XWTlx+PWfQN5kMpX1Wvscc/27a565a1JBetY092hB90HQVg8ZLqPC5GWYN6GVgy5vHi4LkLGGPuMcZsMsZsam1tnZHgVGWpScTIumbSZbKuCa0nXSphk3O8SZfJOx6phB1K+ap6jT3+XXXVVRhjyJzYTa7zCMYYjDEcP3Y06jBDEWWCug94e9CbbzPQZ4wJ5wSBqnpbVrfSPZibdJmuwRxb1oTzA2fd/Hr6RiavHZ0ZybNufn0o5StVjcLsZn4v8CSwVkROiMi7ROS9IvLeYJHvAYeAA8A/AO8PKxZV/W7b2EbMFvpGxu/K3TeSJW4Lt10ZTj+c5S212LbFUHb8JsShrEPMtljeEv61WEpVi9DOQRlj7pjidQN8IKzy1eyypKmWD9+6jk8+uIf+kWFa6hIkbSHrGroGc8Rt4cO3rgvtYt2aRIyt6+fx8O7TDGYzzEnHiccs8o7HmZE8Mdti6/p5erGuUtOge4uqGtdd1syn3noVDzzfzvZ9nXQP+SNJ/PIrFnDbleGPJNFSl+S/bWwbHUmibzBPKmFz9dI5OpKEUhdB/IpM5di0aZPZsWNH1GEopVQpFdVnvIqPf+Nuf/UP5qSUUqoiaYJSSilVljRBKaWUKkuaoJRSSpUlTVBKKaXKkiYopZRSZUkTlFJKqbJUcddBiUgnUIkjI7YAXVEHEYHZut0we7d9tm43XPy2dxljJpvgFQAR+X4xy1WLiktQlUpEdhhjNkUdx0ybrdsNs3fbZ+t2w+ze9jBoE59SSqmypAlKKaVUWdIENXPuiTqAiMzW7YbZu+2zdbthdm97yek5KKWUUmVJa1BKKaXKkiYopZRSZUkTVIhEZImIPCoiu0TkJRG5M+qYZpKI2CLycxG5P+pYZpKIzBGRb4vIHhHZLSLXRx3TTBGR3w++6y+KyL0ikoo6pjCIyJdF5LSIvDjmuSYR+aGI7A/+zo0yxmqgCSpcDvAHxpgNwGbgAyKyIeKYZtKdwO6og4jAp4HvG2PWARuZJZ+BiCwCPgRsMsZcAdjAW6ONKjRfAc6/YPaPgYeNMauBh4PH6hJoggqRMabdGPOz4P4A/oFqUbRRzQwRWQzcBnwx6lhmkog0AjcDXwIwxuSMMWciDWpmxYC0iMSAGuBkxPGEwhjzGNBz3tNvBL4a3P8q8CszGVM10gQ1Q0RkOXA18HTEocyUTwEfBryI45hplwGdwD8GzZtfFJHaqIOaCcaYl4H/CxwD2oE+Y8xD0UY1o+YbY9qD+6eA+VEGUw00Qc0AEakD/g34PWNMf9TxhE1EbgdOG2OejTqWCMSAa4DPG2OuBoaYJU09wTmXN+In6YVArYj8RrRRRcP41+/oNTyXSBNUyEQkjp+cvm6M+U7U8cyQG4E3iMgR4BvAa0Xkn6MNacacAE4YYwo15W/jJ6zZ4HXAYWNMpzEmD3wHuCHimGZSh4i0AQR/T0ccT8XTBBUiERH8cxG7jTF3Rx3PTDHGfMQYs9gYsxz/JPkjxphZ8UvaGHMKOC4ia4OntgK7IgxpJh0DNotITfDd38os6SASuA94R3D/HcB/RhhLVdAEFa4bgd/Er0E8F9x+OeqgVOh+F/i6iDwPXAV8ItpwZkZQa/w28DPgBfzjS1UO/SMi9wJPAmtF5ISIvAv4S+AXRWQ/fm3yL6OMsRroUEdKKaXKktaglFJKlSVNUEoppcqSJiillFJlSROUUkqpsqQJSimlVFnSBKVCJyJu0MX+RRH5rojMucj1/IWIvK7E4U03hntF5DIR+T0RuWPM818Xkb3BNn45uEBbKXUJNEGpmTBijLkqGOG6B/jAxazEGPMxY8yPShvahYKBTiey3BhzGNgCPDbm+a8D64BXAGng3eFF6JsiTqUqniYoNdOeJBjRXURWisj3ReRZEXlcRNaJSKOIHBURK1imVkSOi0hcRL4iIm8Knn+liGwP3vsDEWkTkXki8mzw+kYRMSKyNHh8MBjhoFVE/k1E/iu43Ri8/j9F5J9E5KfAP50fdFBD2gWsE5HngFuAB0Tk3QDGmO+ZAPAMsHicdVwuIs8EtcnnRWR18Pzbg8c7ReSfgueWi8gjwfMPj9mOr4jIF0TkaeCT432GJftPKRU1Y4ze9BbqDRgM/trAt4DXB48fBlYH96/DHxIJ/CFiXhPcfwvwxeD+V4A3AXHgCaB1zDJfDu6/BDQAHwT+C3gbsAx4Mnj9X4CbgvtL8YehAvifwLNAepLteDPwB8H6vjXBMnH8kRReNc5rfwu8LbifwK9pXQ7sA1qC55uCv98F3hHc/23gP8Z8BvcD9mSfod70Vg03bSJQMyEd1DoW4Y/N9sNghPcbgG/5w7YBkAz+fhM/6TyKP5bf585b31rgimA94Ce+wjQHT+APMXUz/hBDrwcEeDx4/XXAhjFlNgSxANxnjBmZZDuuwU8IVwI7J1jmc8BjxpjHx3ntSeCjwVxZ3zHG7BeR1+Inuy4AY0xhjqHrgV8N7v8T8Mkx6/mWMcad4jNUquJpglIzYcQYc5WI1AA/wD8H9RXgjDHmqnGWvw/4hIg0Aa8EHjnvdQFeMsaMN5X6Y8Cr8Gs5/wn8Ef60Bw8Er1vAZmNM5pwV+gf4ofGCD8ZP/AT+NBK3A63AkIhsNca8Zsxyfxa89p7x1mOM+Zegae424HsiMu5yRSjEaTHxZ6hUxdNzUGrGGGOG8acE/wNgGDgsIm8Gf+R3EdkYLDeI3zz3aeB+Y4x73qr2Aq0icn3w3riIXB689jjwG8B+Y4yH3ynjl4GfBK8/hD+YK8F7ryoi7u/hJ8oXjTGvwG9GvPq85PRu4JeAO4JyLyAiK4BDxpjP4CfPK/GT75tFpDlYpilY/AnOTpf+Ns7WAMfG1c8En6FS1UATlJpRxpifA88Dd+AfeN8lIjvxD/pvHLPoN/ETzTfHWUcO/1zUXwXvfY5g3iFjzBH8Glahh91P8GsZvcHjDwGbgs4Hu4D3Fhn61cBOEUkAcXPhxJNfwJ9B9cmgE8THxlnHrwEvBs2dVwBfM8a8BHwc2B5sS2Falt8F3in+iOi/Cdw5QVyTfYZKVTQdzVwppVRZ0hqUUkqpsqQJSimlVFnSBKWUUqosaYJSSilVljRBKaWUKkuaoJRSSpUlTVBKKaXK0v8POLcnDwkmYuIAAAAASUVORK5CYII=\n", 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\n", 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