From bb5df5ad0634721daca69e77ac2e2d489736caf2 Mon Sep 17 00:00:00 2001 From: Chelsea John <36626249+chelseajohn@users.noreply.github.com> Date: Sun, 23 Aug 2020 03:04:38 +0200 Subject: [PATCH] Updated files --- .../accuracyPlotGeneration.ipynb | 109 +++++++------- .../local_experiments/cumLossVScumComm.ipynb | 98 +++++++------ ...umulativeCommunicationPlotGeneration.ipynb | 59 ++++---- ...nicationPlotGeneration_video_version.ipynb | 137 +++++++----------- .../cumulativeLossPlotGeneration.ipynb | 131 +++++------------ .../lossPlotGeneration.ipynb | 109 ++++++++------ 6 files changed, 290 insertions(+), 353 deletions(-) diff --git a/experiments/local_experiments/accuracyPlotGeneration.ipynb b/experiments/local_experiments/accuracyPlotGeneration.ipynb index c872dfe..569bc05 100644 --- a/experiments/local_experiments/accuracyPlotGeneration.ipynb +++ b/experiments/local_experiments/accuracyPlotGeneration.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -52,18 +52,18 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9b3f134343c24e06bcb8e0c2dcce4d2a", + "model_id": "73ebf7d335ef4bf99e425df1cda9620c", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Dropdown(description='Experiment:', options=('.ipynb_checkpoints', 'RadonMachine', 'hessianCifar100Exp_2019-05…" + "Dropdown(description='Experiment:', options=('.ipynb_checkpoints', 'examples', 'test'), value='.ipynb_checkpoi…" ] }, "metadata": {}, @@ -81,14 +81,14 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "hessianCifar100Exp_2019-05-22_11-22-01\n" + "test\n" ] } ], @@ -99,14 +99,14 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Learners amount is 2\n" + "Learners amount is 3\n" ] } ], @@ -128,7 +128,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -142,18 +142,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "files = []\n", "correctSums = []\n", @@ -170,37 +159,38 @@ " file = files[i]\n", " where = file.tell()\n", " line = file.readline()\n", - " if not line:\n", - " time.sleep(1)\n", - " file.seek(where)\n", - " else:\n", - " pred = [float(x) for x in line[:-1].split('\\t')[1].split(',')]\n", - " label = [float(x) for x in line[:-1].split('\\t')[2].split(',')]\n", - " correctness = checkPrediction(pred, label)\n", - " correctSums[i].append(correctSums[i][-1] + correctness)\n", - " accuracies[i].append(correctSums[i][-1]*100.0/(commonStep+1))\n", - " currentStep = min([len(a) for a in accuracies])\n", - " if currentStep > commonStep:\n", - " commonStep = currentStep\n", - " if commonStep % displayStep == 0:\n", - " clear_output(wait=True)\n", - " cutAccuracies = [a[1:commonStep] for a in accuracies]\n", - " mu = np.array(cutAccuracies).mean(axis=0)\n", - " sigma = np.array(cutAccuracies).std(axis=0)\n", - " fig = plt.figure()\n", - " plt.plot(t, mu, lw=2, label='Mean Accuracy', color='green')\n", - " plt.fill_between(t, mu+sigma, mu-sigma, facecolor='green', alpha=0.5)\n", - " plt.legend(loc='lower center')\n", - " plt.xlabel(\"# Examples per Learner\")\n", - " plt.ylabel(\"Accuracy (percent)\")\n", - " plt.grid()\n", - " plt.show()\n", - " t.append(t[-1] + 1)\n", - " if commonStep % recordStep == 0:\n", - " if recordUnique:\n", - " fig.savefig(os.path.join(experimentFolder, 'accuracy' + str(commonStep) + '.png'), dpi=100)\n", + " if line[0] != 'T':\n", + " if not line:\n", + " time.sleep(1)\n", + " file.seek(where)\n", " else:\n", - " fig.savefig(os.path.join(experimentFolder, 'accuracy.png'), dpi=100)" + " pred = [float(x) for x in line[:-1].split('\\t\\t')[1].split(',')]\n", + " label = [float(x) for x in line[:-1].split('\\t\\t')[2].split(',')]\n", + " correctness = checkPrediction(pred, label)\n", + " correctSums[i].append(correctSums[i][-1] + correctness)\n", + " accuracies[i].append(correctSums[i][-1]*100.0/(commonStep+1))\n", + " currentStep = min([len(a) for a in accuracies])\n", + " if currentStep > commonStep:\n", + " commonStep = currentStep\n", + " if commonStep % displayStep == 0:\n", + " clear_output(wait=True)\n", + " cutAccuracies = [a[1:commonStep] for a in accuracies]\n", + " mu = np.array(cutAccuracies).mean(axis=0)\n", + " sigma = np.array(cutAccuracies).std(axis=0)\n", + " fig = plt.figure()\n", + " plt.plot(t, mu, lw=2, label='Mean Accuracy', color='green')\n", + " plt.fill_between(t, mu+sigma, mu-sigma, facecolor='green', alpha=0.5)\n", + " plt.legend(loc='lower center')\n", + " plt.xlabel(\"# Examples per Learner\")\n", + " plt.ylabel(\"Accuracy (percent)\")\n", + " plt.grid()\n", + " plt.show()\n", + " t.append(t[-1] + 1)\n", + " if commonStep % recordStep == 0:\n", + " if recordUnique:\n", + " fig.savefig(os.path.join(experimentFolder, 'accuracy' + str(commonStep) + '.png'), dpi=100)\n", + " else:\n", + " fig.savefig(os.path.join(experimentFolder, 'accuracy.png'), dpi=100)" ] }, { @@ -286,7 +276,8 @@ "change = False\n", "while True:\n", " for f in files:\n", - " where = f.tell()\n", + " next(f)\n", + " #where = f.tell()\n", " line = f.readline()\n", " if line:\n", " change = True\n", @@ -368,9 +359,21 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [default]", + "display_name": "Python 3", "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": "3.7.6" } }, "nbformat": 4, diff --git a/experiments/local_experiments/cumLossVScumComm.ipynb b/experiments/local_experiments/cumLossVScumComm.ipynb index d60bebe..f4b6ef1 100644 --- a/experiments/local_experiments/cumLossVScumComm.ipynb +++ b/experiments/local_experiments/cumLossVScumComm.ipynb @@ -40,12 +40,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c45a88a2d8134469a555caee7a6d0f46", + "model_id": "f1282cc3f6fe4443902b575144ef388a", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "SelectMultiple(description='Experiments:', layout=Layout(width='550px'), options=('.ipynb_checkpoints', 'lossS…" + "SelectMultiple(description='Experiments:', layout=Layout(width='550px'), options=('.ipynb_checkpoints', 'examp…" ] }, "metadata": {}, @@ -67,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -76,14 +76,18 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 15, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'deepDrivingExp_2018-12-04 18-23-42': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.001)'], 'deepDrivingExp_2018-12-04 12-03-50': ['periodic (B=32, b=4)'], 'deepDrivingExp_2018-12-04 18-32-47': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.01)'], 'deepDrivingExp_2018-12-05 11-20-55': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.5)'], 'deepDrivingExp_2018-12-04 09-45-56': ['serial (B=32)'], 'deepDrivingExp_2018-12-04 12-33-03': ['periodic (B=32, b=1)'], 'deepDrivingExp_2018-12-05 13-23-45': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.2)'], 'deepDrivingExp_2018-12-04 11-22-56': ['no sync (B=32)'], 'deepDrivingExp_2018-12-04 12-25-34': ['periodic (B=32, b=8)'], 'deepDrivingExp_2018-12-04 11-40-47': ['periodic (B=32, b=2)']}\n" + "ename": "NameError", + "evalue": "name 'batchSize' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 31\u001b[0m \u001b[0msync\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;34m\" (B=\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbatchSize\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\", b=\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msyncPeriod\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\", $\\Delta$=\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdelta\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\")\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 32\u001b[0m \u001b[1;32melif\u001b[0m \u001b[1;34m\"Periodic\"\u001b[0m \u001b[1;32min\u001b[0m \u001b[0msync\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 33\u001b[1;33m \u001b[0msync\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"periodic (B=\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbatchSize\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\", b=\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msyncPeriod\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\")\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 34\u001b[0m \u001b[1;32melif\u001b[0m \u001b[1;34m\"No sync\"\u001b[0m \u001b[1;32min\u001b[0m \u001b[0msync\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 35\u001b[0m \u001b[0msync\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"no sync (B=\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbatchSize\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\")\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: name 'batchSize' is not defined" ] } ], @@ -130,14 +134,18 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 36, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'deepDrivingExp_2018-12-04 18-23-42': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.001)', 19517215329.0], 'deepDrivingExp_2018-12-04 12-03-50': ['periodic (B=32, b=4)', 4269390120.0], 'deepDrivingExp_2018-12-04 18-32-47': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.01)', 9148694958.0], 'deepDrivingExp_2018-12-05 11-20-55': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.5)', 1219826439.0], 'deepDrivingExp_2018-12-04 09-45-56': ['serial (B=32)', 1965274572.0], 'deepDrivingExp_2018-12-04 12-33-03': ['periodic (B=32, b=1)', 15247820052.0], 'deepDrivingExp_2018-12-05 13-23-45': ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.2)', 2439652365.0], 'deepDrivingExp_2018-12-04 11-22-56': ['no sync (B=32)', 15247823292.0], 'deepDrivingExp_2018-12-04 12-25-34': ['periodic (B=32, b=8)', 2439651798.0], 'deepDrivingExp_2018-12-04 11-40-47': ['periodic (B=32, b=2)', 7928866764.0]}\n" + "ename": "KeyError", + "evalue": "'test'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[0mcumulativeCommunication\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparsedLine\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 14\u001b[1;33m \u001b[0mexperiments\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcumulativeCommunication\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 15\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexperiments\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mKeyError\u001b[0m: 'test'" ] } ], @@ -146,9 +154,10 @@ " cumulativeCommunication = 0\n", " for f in os.listdir(os.path.join(d, \"coordinator\", \"communication\")):\n", " f = open(os.path.join(d, \"coordinator\", \"communication\", f), \"r\")\n", + " next(f)\n", " for l in f.readlines():\n", - " parsedLine = l[:-1].split(\"\\t\")\n", - " if len(parsedLine) == 5:\n", + " parsedLine = l[:-2].split(\"\\t\\t\")\n", + " if len(parsedLine) == 6:\n", " messagesAmount = parsedLine[2].count(\".\")\n", " cumulativeCommunication += float(parsedLine[3]) * messagesAmount\n", " else:\n", @@ -160,14 +169,18 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 11, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "[('deepDrivingExp_2018-12-04 18-23-42', ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.001)', 19517215329.0, 5.025832460000004]), ('deepDrivingExp_2018-12-04 18-32-47', ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.01)', 9148694958.0, 5.949998249999999]), ('deepDrivingExp_2018-12-05 13-23-45', ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.2)', 2439652365.0, 6.820228570000004]), ('deepDrivingExp_2018-12-05 11-20-55', ['dynamic hedge (B=32, b=1, $\\\\Delta$=0.5)', 1219826439.0, 6.843057519999999]), ('deepDrivingExp_2018-12-04 11-22-56', ['no sync (B=32)', 15247823292.0, 10.978826459999999]), ('deepDrivingExp_2018-12-04 12-33-03', ['periodic (B=32, b=1)', 15247820052.0, 5.908310829999999]), ('deepDrivingExp_2018-12-04 11-40-47', ['periodic (B=32, b=2)', 7928866764.0, 6.154315659999999]), ('deepDrivingExp_2018-12-04 12-03-50', ['periodic (B=32, b=4)', 4269390120.0, 6.698042299999998]), ('deepDrivingExp_2018-12-04 12-25-34', ['periodic (B=32, b=8)', 2439651798.0, 7.03857363]), ('deepDrivingExp_2018-12-04 09-45-56', ['serial (B=32)', 1965274572.0, 4.521745229999999])]\n" + "ename": "KeyError", + "evalue": "'test'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[0mcumulativeLoss\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ml\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'\\t\\t'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m \u001b[0mexperiments\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcumulativeLoss\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 12\u001b[0m \u001b[0mexperiments_dict\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexperiments\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[0mexperiments\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexperiments\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moperator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitemgetter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mKeyError\u001b[0m: 'test'" ] } ], @@ -178,8 +191,9 @@ " for wd in dirs:\n", " if 'worker' in wd:\n", " f = open(os.path.join(d, wd, \"losses.txt\"), \"r\")\n", + " next(f)\n", " for l in f.readlines():\n", - " cumulativeLoss += float(l[:-1].split('\\t')[1])\n", + " cumulativeLoss += float(l[:-1].split('\\t\\t')[1])\n", " f.close()\n", " experiments[d].append(cumulativeLoss)\n", "experiments_dict = experiments\n", @@ -234,18 +248,19 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 7, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "['periodic (B=32, b=8)', 2439651798.0, 7.03857363]" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" + "ename": "NameError", + "evalue": "name 'experiments_dict' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mexperiments_dict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'deepDrivingExp_2018-12-04 09-45-56'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[0mexperiments_dict\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'deepDrivingExp_2018-12-04 12-25-34'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: name 'experiments_dict' is not defined" + ] } ], "source": [ @@ -255,18 +270,19 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 9, "metadata": {}, "outputs": [ { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "ename": "NameError", + "evalue": "name 'experiments_dict' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mexperiments\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexperiments_dict\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moperator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitemgetter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0me\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mexperiments\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m\"no sync\"\u001b[0m \u001b[1;32min\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: name 'experiments_dict' is not defined" + ] } ], "source": [ @@ -302,7 +318,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [default]", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -316,7 +332,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.7.6" } }, "nbformat": 4, diff --git a/experiments/local_experiments/cumulativeCommunicationPlotGeneration.ipynb b/experiments/local_experiments/cumulativeCommunicationPlotGeneration.ipynb index e3b6133..d9cf1ff 100644 --- a/experiments/local_experiments/cumulativeCommunicationPlotGeneration.ipynb +++ b/experiments/local_experiments/cumulativeCommunicationPlotGeneration.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -41,12 +41,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4f7d083b0b7945af948e39032f6faaa7", + "model_id": "68281d69d8ef46319d8fac6feb580179", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Dropdown(description='Experiment:', options=('.ipynb_checkpoints', 'VGMM_CENTRALIZED_exp_2018-11-21 10-34-05',…" + "Dropdown(description='Experiment:', options=('.ipynb_checkpoints', 'examples', 'test'), value='.ipynb_checkpoi…" ] }, "metadata": {}, @@ -64,14 +64,14 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "deepDrivingExp_2018-12-04 12-33-03\n" + "test\n" ] } ], @@ -82,14 +82,14 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Learners amount is 9\n" + "Learners amount is 3\n" ] } ], @@ -106,7 +106,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -120,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -132,7 +132,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -147,29 +147,22 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": {}, + "execution_count": null, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 33\u001b[0m \u001b[0;31m# do not need to call plotting if no new lines were read\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 34\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mchange\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 35\u001b[0;31m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 36\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 37\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] } ], "source": [ @@ -180,20 +173,20 @@ " for f in files:\n", " where = f.tell()\n", " line = f.readline()\n", - " if line:\n", + " if line and line[0]!='T':\n", " change = True\n", - " parsedLine = line.split(\"\\t\")\n", + " parsedLine = line.split(\"\\t\\t\")\n", " lineTimestamp = float(parsedLine[0])\n", " # identify to which point in time this line will go\n", " xPoint = math.ceil((lineTimestamp - startTimestamp) / frequencyStep)\n", " # the send_model log has only 4 elements in line since the learner ids to whom\n", " # the model was sent are written in the topic, i.e., newModel.0.1.2\n", " # that is why we need to multiply the size of this message by the amount of learners in the topic\n", - " if len(parsedLine) == 5:\n", + " if len(parsedLine) == 6:\n", " messagesAmount = parsedLine[2].count(\".\")\n", " messageSize = float(parsedLine[3]) * messagesAmount\n", " else:\n", - " messageSize = float(parsedLine[4])\n", + " messageSize = float(parsedLine[5])\n", " # if we do not yet have this point on our axis - add it and all the previous ones\n", " # the value on all the new points is saved from the last position\n", " if len(plot) < xPoint:\n", @@ -231,7 +224,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -252,7 +245,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [default]", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -266,7 +259,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.7.6" } }, "nbformat": 4, diff --git a/experiments/local_experiments/cumulativeCommunicationPlotGeneration_video_version.ipynb b/experiments/local_experiments/cumulativeCommunicationPlotGeneration_video_version.ipynb index 23638d0..f45ed30 100644 --- a/experiments/local_experiments/cumulativeCommunicationPlotGeneration_video_version.ipynb +++ b/experiments/local_experiments/cumulativeCommunicationPlotGeneration_video_version.ipynb @@ -2,10 +2,8 @@ "cells": [ { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": true - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ "import matplotlib\n", @@ -20,10 +18,8 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": true - }, + "execution_count": 19, + "metadata": {}, "outputs": [], "source": [ "plt.rcParams[\"figure.figsize\"] = (16,8)" @@ -31,18 +27,18 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "016170d3d6334742867e7b70ce638b9a", + "model_id": "7c45f07c53e040faa39cd7662d3a3032", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "A Jupyter Widget" + "Dropdown(description='Experiment:', options={'.ipynb_checkpoints': '.ipynb_checkpoints', 'examples': 'examples…" ] }, "metadata": {}, @@ -61,10 +57,8 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": true - }, + "execution_count": 21, + "metadata": {}, "outputs": [], "source": [ "experimentFolder = wFolder.value" @@ -72,14 +66,14 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Learners amount is 4\n" + "Learners amount is 3\n" ] } ], @@ -101,10 +95,8 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": true - }, + "execution_count": 23, + "metadata": {}, "outputs": [], "source": [ "communication = []\n", @@ -118,18 +110,18 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[<_io.TextIOWrapper name='deepDrivingExp_nice_2018-10-12 12-17-31\\\\coordinator\\\\communication\\\\registrations.txt' mode='r' encoding='cp1252'>,\n", - " <_io.TextIOWrapper name='deepDrivingExp_nice_2018-10-12 12-17-31\\\\coordinator\\\\communication\\\\send_model.txt' mode='r' encoding='cp1252'>,\n", - " <_io.TextIOWrapper name='deepDrivingExp_nice_2018-10-12 12-17-31\\\\coordinator\\\\communication\\\\violations.txt' mode='r' encoding='cp1252'>]" + "[<_io.TextIOWrapper name='test\\\\coordinator\\\\communication\\\\registrations.txt' mode='r' encoding='cp1252'>,\n", + " <_io.TextIOWrapper name='test\\\\coordinator\\\\communication\\\\send_model.txt' mode='r' encoding='cp1252'>,\n", + " <_io.TextIOWrapper name='test\\\\coordinator\\\\communication\\\\violations.txt' mode='r' encoding='cp1252'>]" ] }, - "execution_count": 23, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -140,16 +132,16 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": true - }, + "execution_count": 25, + "metadata": {}, "outputs": [], "source": [ "# coordinator\n", - "data_sendModel = files[0]#.read()\n", - "data_violations = files[1]#.read()\n", - "data_registrations = files[2]#.read()" + "data_sendModel = files[1]#.read()\n", + "\n", + "data_violations = files[2]#.read()\n", + "\n", + "data_registrations = files[0]#.read()\n" ] }, { @@ -161,44 +153,15 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": { "scrolled": false }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1539339530.805\tnodes\tnewModel.1\t33884063\tsend\n", - "\n" - ] - }, - { - "ename": "ValueError", - "evalue": "invalid literal for int() with base 10: 'send\\n'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 161\u001b[0m \u001b[1;31m# here: index 4 = message size\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 162\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvline\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 163\u001b[1;33m \u001b[0mmessage_size\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmessage_size\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"\\t\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 164\u001b[0m \u001b[1;31m#print(\"violation message added with ts \" + str(float(vline.split(\"\\t\")[0])))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[1;31m#print(\"message_size: \" + str(message_size))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mValueError\u001b[0m: invalid literal for int() with base 10: 'send\\n'" - ] - }, { "data": { "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6oAAAHWCAYAAAB+A3SNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAQAAGEWoAgAAMIpQBQAAYJT/B5Eiu2Y4nJwkAAAAAElFTkSuQmCC\n", - "text/plain": [ - "" + "
" ] }, "metadata": {}, @@ -235,11 +198,12 @@ " file = files[i]\n", " where = file.tell()\n", " line = file.readline()\n", + " \n", " if not line:\n", " time.sleep(1)\n", " file.seek(where)\n", - " else:\n", - " timestamps[i].append(float(line.split('\\t')[0]))\n", + " elif line and line[0] != 'T':\n", + " timestamps[i].append(float(line.split('\\t\\t')[0]))\n", " \n", " currentStep = min([len(ts) for ts in timestamps]) #minimum not needed? just length of any list; because above always one timestamp gets inserted per worker\n", " if currentStep > commonStep: #if everywhere has been written something\n", @@ -268,7 +232,7 @@ " #print(\"maximal time step of cut list: \"+ str(time_step))\n", "\n", "\n", - " \n", + " \n", " # get data of registration and violation files up to this time step\n", " #print(\"CHOSEN TIME STEP:\" + str(time_step))\n", " #check for registrations up to time_step\n", @@ -277,8 +241,8 @@ " # check in buffer (if not empty)\n", " while rlines_buffer != []: #as long as buffer is not empty\n", " #print(\"checking this line in buffer\", vlines_buffer[0])\n", - " if float(rlines_buffer[0][0].split(\"\\t\")[0]) <= time_step:\n", - " message_size = message_size + int(rlines_buffer[0][0].split(\"\\t\")[4])\n", + " if float(rlines_buffer[0][0].split(\"\\t\\t\")[0]) <= time_step:\n", + " message_size = message_size + int(rlines_buffer[0][0].split(\"\\t\\t\")[4])\n", " #print(\"registration message from buffer added with ts \" + str(float(rlines_buffer[0][0].split(\"\\t\")[0])))\n", " #print(\"message_size: \" + str(message_size))\n", " # delete message from buffer\n", @@ -290,15 +254,16 @@ " # read new lines\n", " where = data_registrations.tell()\n", " rline = data_registrations.readline()\n", - "\n", + " \n", + " \n", " if not rline: #could it be that I'M waiting here too long?\n", " #time.sleep(1)\n", " data_registrations.seek(where)\n", " break \n", - " else:\n", - " if float(rline.split(\"\\t\")[0]) <= time_step:\n", + " elif line and rline[0] != 'T':\n", + " if float(rline.split(\"\\t\\t\")[0]) <= time_step:\n", " # here: index 4 = message size\n", - " message_size = message_size + int(rline.split(\"\\t\")[4])\n", + " message_size = message_size + int(rline.split(\"\\t\\t\")[4])\n", " #print(\"registration message added with ts \" + str(float(rline.split(\"\\t\")[0])))\n", " #print(\"message_size: \" + str(message_size))\n", " else:\n", @@ -306,13 +271,14 @@ " break\n", "\n", "\n", + "\n", " #check for sendModels up to time_step\n", " while True:\n", " # check in buffer (if not empty)\n", " while slines_buffer != []: #as long as buffer is not empty\n", " if float(slines_buffer[0][0].split(\"\\t\")[0]) <= time_step:\n", " # count number of points in this string which coincides with the number of nodes receiving the model\n", - " message_size= message_size + int(slines_buffer[0][0].split(\"\\t\")[3])* slines_buffer[0][0].split(\"\\t\")[2].count(\".\")\n", + " message_size= message_size + int(slines_buffer[0][0].split(\"\\t\\t\")[3])* slines_buffer[0][0].split(\"\\t\")[2].count(\".\")\n", " #print(\"sendModel message from buffer added with ts \" + str(float(slines_buffer[0][0].split(\"\\t\")[0])))\n", " #print(\"message_size: \" + str(message_size))\n", " # delete message from buffer\n", @@ -323,16 +289,16 @@ " # read new lines\n", " where = data_sendModel.tell()\n", " sline = data_sendModel.readline()\n", - "\n", + " \n", " if not sline: #could it be that I'M waiting here too long?\n", " #time.sleep(1)\n", " data_sendModel.seek(where)\n", " break \n", - " else:\n", - " if float(sline.split(\"\\t\")[0]) <= time_step:\n", + " elif line and sline[0] != 'T':\n", + " if float(sline.split(\"\\t\\t\")[0]) <= time_step:\n", " # here: index 4 = message size\n", " # count number of points in this string which coincides with the number of nodes receiving the model\n", - " message_size= message_size + int(sline.split(\"\\t\")[3])* sline.split(\"\\t\")[2].count(\".\")\n", + " message_size= message_size + int(sline.split(\"\\t\\t\")[3])* sline.split(\"\\t\\t\")[2].count(\".\")\n", " #print(\"sendModel message added with ts \" + str(float(sline.split(\"\\t\")[0])))\n", " #print(\"message_size: \" + str(message_size))\n", " else:\n", @@ -346,8 +312,8 @@ " #print(\"buffer\", vlines_buffer)\n", " while vlines_buffer != []: #as long as buffer is not empty\n", " #print(\"checking this line in buffer\", vlines_buffer[0])\n", - " if float(vlines_buffer[0][0].split(\"\\t\")[0]) <= time_step:\n", - " message_size = message_size + int(vlines_buffer[0][0].split(\"\\t\")[4])\n", + " if float(vlines_buffer[0][0].split(\"\\t\\t\")[0]) <= time_step:\n", + " message_size = message_size + int(vlines_buffer[0][0].split(\"\\t\\t\")[4])\n", " #print(\"violation message from buffer added with ts \" + str(float(vlines_buffer[0][0].split(\"\\t\")[0])))\n", " #print(\"message_size: \" + str(message_size))\n", " # delete message from buffer\n", @@ -359,23 +325,24 @@ " # read new lines\n", " where = data_violations.tell()\n", " vline = data_violations.readline()\n", + " \n", "\n", " if not vline: #could it be that I'M waiting here too long?\n", " #time.sleep(1)\n", " data_violations.seek(where)\n", " break \n", - " else:\n", - " if float(vline.split(\"\\t\")[0]) <= time_step:\n", + " elif line and vline[0] != 'T':\n", + " if float(vline.split(\"\\t\\t\")[0]) <= time_step:\n", " # here: index 4 = message size\n", " print(vline)\n", - " message_size = message_size + int(vline.split(\"\\t\")[4])\n", + " message_size = message_size + int(vline.split(\"\\t\\t\")[4])\n", " #print(\"violation message added with ts \" + str(float(vline.split(\"\\t\")[0])))\n", " #print(\"message_size: \" + str(message_size))\n", " else:\n", " vlines_buffer.append([vline])\n", " break\n", "\n", - "\n", + " \n", " message_sizes.append(message_size)\n", " #print(\"message_sizes: \" + str(message_sizes))\n", " \n", @@ -3826,7 +3793,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.7.6" } }, "nbformat": 4, diff --git a/experiments/local_experiments/cumulativeLossPlotGeneration.ipynb b/experiments/local_experiments/cumulativeLossPlotGeneration.ipynb index 9c2b915..67746f0 100644 --- a/experiments/local_experiments/cumulativeLossPlotGeneration.ipynb +++ b/experiments/local_experiments/cumulativeLossPlotGeneration.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -35,18 +35,18 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2459740b23744d858bcd70e4bf536fe7", + "model_id": "d96739e944df4939882af03b6fae1e0a", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Dropdown(description='Experiment:', options={'deepDrivingExp_nice_2018-10-12 12-17-31': 'deepDrivingExp_nice_2…" + "Dropdown(description='Experiment:', options={'.ipynb_checkpoints': '.ipynb_checkpoints', 'examples': 'examples…" ] }, "metadata": {}, @@ -65,14 +65,14 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "deepDrivingExp_2018-11-08 22-36-22_dynamic0001_9nodes_stopping_lr0005\n" + "test\n" ] } ], @@ -83,14 +83,14 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Learners amount is 9\n" + "Learners amount is 3\n" ] } ], @@ -112,7 +112,7 @@ }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -125,29 +125,20 @@ }, { "cell_type": "code", - "execution_count": 104, + "execution_count": null, "metadata": {}, "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mline\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreadline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mline\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 16\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mseek\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwhere\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] } ], "source": [ @@ -167,14 +158,14 @@ " if not line:\n", " time.sleep(1)\n", " file.seek(where)\n", - " else:\n", - " losses[i].append(losses[i][-1] + float(line[:-1].split('\\t')[1]))\n", + " elif line and line[0] != 'T':\n", + " losses[i].append(losses[i][-1] + float(line[:-1].split('\\t\\t')[1]))\n", " currentStep = min([len(l) for l in losses])\n", " if currentStep > commonStep:\n", " commonStep = currentStep\n", " if commonStep % displayStep == 0:\n", " clear_output(wait=True)\n", - " cutLosses = [l[1:commonStep] for l in losses]\n", + " cutLosses = [l[0:commonStep] for l in losses]\n", " mu = np.array(cutLosses).mean(axis=0)\n", " sigma = np.array(cutLosses).std(axis=0)\n", " fig = plt.figure()\n", @@ -197,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -221,10 +212,8 @@ }, { "cell_type": "code", - "execution_count": 39, - "metadata": { - "collapsed": true - }, + "execution_count": null, + "metadata": {}, "outputs": [], "source": [ "def displayLoss(prediction, label, name, **argv):\n", @@ -260,31 +249,9 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7wAAAHjCAYAAAAABBM8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 14\u001b[0m \u001b[0mline\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfile\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreadline\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 15\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mline\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 16\u001b[1;33m \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 17\u001b[0m \u001b[0mfile\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mseek\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwhere\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 18\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], + "outputs": [], "source": [ "files = []\n", "cumDisplayLosses = []\n", @@ -303,9 +270,9 @@ " if not line:\n", " time.sleep(1)\n", " file.seek(where)\n", - " else:\n", - " pred = [float(x) for x in line[:-1].split('\\t')[1].split(',')]\n", - " label = [float(x) for x in line[:-1].split('\\t')[2].split(',')]\n", + " elif line and line[0]!= 'T':\n", + " pred = [float(x) for x in line[:-1].split('\\t\\t')[1].split(',')]\n", + " label = [float(x) for x in line[:-1].split('\\t\\t')[2].split(',')]\n", " cumDisplayLosses[i].append(cumDisplayLosses[i][-1] + displayLoss(pred, label, lossF, epsilon = 0.001))\n", " currentStep = min([len(a) for a in cumDisplayLosses])\n", " if currentStep > commonStep:\n", @@ -336,10 +303,8 @@ }, { "cell_type": "code", - "execution_count": 46, - "metadata": { - "collapsed": true - }, + "execution_count": null, + "metadata": {}, "outputs": [], "source": [ "for file in files:\n", @@ -399,31 +364,9 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 31\u001b[0m \u001b[0;31m# do not need to call plotting if no new lines were read\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mchange\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 33\u001b[0;31m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 34\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 35\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], + "outputs": [], "source": [ "plot = [0]\n", "syncPoints = []\n", @@ -432,9 +375,9 @@ " for f in files:\n", " where = f.tell()\n", " line = f.readline()\n", - " if line:\n", + " if line and line[0]!= 'T':\n", " change = True\n", - " parsedLine = line[:-1].split(\"\\t\")\n", + " parsedLine = line[:-1].split(\"\\t\\t\")\n", " lineTimestamp = float(parsedLine[0])\n", " # identify to which point in time this line will go\n", " xPoint = math.ceil((lineTimestamp - startTimestamp) / frequencyStep)\n", @@ -447,9 +390,9 @@ " if displaySync:\n", " where = syncFile.tell()\n", " line = syncFile.readline()\n", - " if line:\n", + " if line and line[0]!= 'T':\n", " change = True\n", - " parsedLine = line[:-1].split(\"\\t\")\n", + " parsedLine = line[:-1].split(\"\\t\\t\")\n", " lineTimestamp = float(parsedLine[0])\n", " # if model was sent only to one learner it is not a synchronization\n", " if parsedLine[2].count(\".\") > 1:\n", @@ -485,7 +428,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -509,7 +452,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [default]", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -523,7 +466,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.2" + "version": "3.7.6" } }, "nbformat": 4, diff --git a/experiments/local_experiments/lossPlotGeneration.ipynb b/experiments/local_experiments/lossPlotGeneration.ipynb index 269e889..9b84004 100644 --- a/experiments/local_experiments/lossPlotGeneration.ipynb +++ b/experiments/local_experiments/lossPlotGeneration.ipynb @@ -48,18 +48,18 @@ }, { "cell_type": "code", - "execution_count": 126, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f7e57ca2200449acbeddf5e25d4bf6d5", + "model_id": "0f3326ca89f3428ebc08b0f8781c874e", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Dropdown(description='Experiment:', options=('.ipynb_checkpoints', 'RadonMachine', 'hessianCifar100Exp_2019-05…" + "Dropdown(description='Experiment:', options=('.ipynb_checkpoints', 'examples', 'test'), value='.ipynb_checkpoi…" ] }, "metadata": {}, @@ -77,14 +77,14 @@ }, { "cell_type": "code", - "execution_count": 133, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "hessianCifar100Exp_2019-05-22_10-56-30\n" + "test\n" ] } ], @@ -95,7 +95,7 @@ }, { "cell_type": "code", - "execution_count": 134, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -124,7 +124,7 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -145,12 +145,14 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7AAAAHgCAYAAACcrIEcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOydeZwcVb32n8qsycwkmewrJIEQAkmYhGy8YAgE5AYRRLwE9IKsKl65eL1yvff1sugV9SpeUF9A8aOyKEkQEVlkExgSCGSfhOyZJJNkJpNk9r1neqn3j5Mzdaq6qrq6u3qZmef7+cyne7q7qk5Xner6PfX8zu9ouq6DEEIIIYQQQgjJdgZlugGEEEIIIYQQQogXKGAJIYQQQgghhPQJKGAJIYQQQgghhPQJKGAJIYQQQgghhPQJKGAJIYQQQgghhPQJKGAJIYQQQgghhPQJcjPdgHgZNWqUPmXKlEw3w5WOjg4UFRVluhkkS2H/IE6wbxA32D+IG+wfxAn2DeJGtvaPzZs31+u6PtruvT4nYKdMmYJNmzZluhmulJeXY+nSpZluBslS2D+IE+wbxA32D+IG+wdxgn2DuJGt/UPTtMNO7zGFmBBCCCGEEEJIn4AClhBCCCGEEEJIn4AClhBCCCGEEEJIn6DPjYElhBCSWoLBIKqrqxEIBDLdFKIwbNgw7N69O9PNGPAUFhZi0qRJyMvLy3RTCCFkQEIBSwghxER1dTVKSkowZcoUaJqW6eaQU7S1taGkpCTTzRjQ6LqOhoYGVFdXY+rUqZluDiGEDEiYQkwIIcREIBDAyJEjKV4JsaBpGkaOHMnsBEIIySAUsIQQQqKgeCXEHp4bhBCSWShgCSGEZB2apuGmm27q/T8UCmH06NG46qqrUrrdW265BS+88EJKt0EIIYSQxKGAJYQQknUUFRVhx44d6OrqAgC8/fbbmDhxYoZbRQghhJBMQwFLCCEkK1m+fDlee+01AMDKlStx44039r7X0dGB2267DQsWLMDcuXPx17/+FQBQVVWFT33qU5g3bx7mzZuHdevWAQDKy8uxdOlSfOELX8DZZ5+NL33pS9B13VM7dF3Hvffei1mzZmH27NlYvXo1AKC2thZLlixBWVkZZs2ahbVr1yIcDuOWW27p/ewjjzzi5y4hhBBCBjysQkwIIcSZVI338yAeb7jhBnz/+9/HVVddhe3bt+O2227D2rVrAQAPPfQQLr30Uvzud79Dc3MzFi5ciMsuuwxjxozB22+/jcLCQuzfvx833ngjNm3aBADYunUrdu7ciQkTJuDCCy/Ehx9+iIsuuihmO1588UVUVFRg27ZtqK+vx4IFC7BkyRI899xzuOKKK/Dd734X4XAYnZ2dqKioQE1NDXbs2AEAaG5uTmInEUIIIcQKBSwhhJCsZM6cOaiqqsLKlStx5ZVXmt5766238PLLL+Phhx8GIConHzlyBBMmTMA3vvENVFRUICcnB/v27etdZuHChZg0aRIAoKysDFVVVZ4E7AcffIAbb7wROTk5GDt2LC6++GJs3LgRCxYswG233YZgMIjPfe5zKCsrw7Rp03Dw4EHcfffd+MxnPoNPf/rTPu4RQgghhDCFmBBCiDO6npo/j1x99dX49re/bUofFs3S8ec//xkVFRWoqKjAkSNHMHPmTDzyyCMYO3Ystm3bhk2bNqGnp6d3mYKCgt7nOTk5CIVCHneBfXuXLFmCNWvWYOLEibjpppvwzDPPoLS0FNu2bcPSpUvx2GOP4Y477vD8XQkhhBASGwpYQgghWcttt92G+++/H7Nnzza9fsUVV+CXv/xlr7jcunUrAKClpQXjx4/HoEGD8OyzzyIcDifdhiVLlmD16tUIh8Ooq6vDmjVrsHDhQhw+fBhjxozBnXfeidtvvx1btmxBfX09IpEIrrvuOvz3f/83tmzZkvT2CSGEEGLAFGJCCCFZy6RJk3DPPfdEvX7ffffhm9/8JubMmQNd1zFlyhS8+uqr+PrXv47rrrsOf/rTn3DJJZegqKgo7m1+9atfxTe/+U0AwOTJk7Fu3Tp89NFHOO+886BpGn7yk59g3LhxePrpp/HTn/4UeXl5KC4uxjPPPIOamhrceuutiEQiAIAf/ehHye0AQgghhJjQvFZhzBbmz5+vy4Ic2YqsdkmIHewfxIls6Ru7d+/GzJkzM90MYqGtrQ0lJSWZbgZBdp4j2fL7QbIP9g3iRrb2D03TNuu6Pt/uPaYQE0IIIYQQQgjpE1DAEkKIF/pYtgohhBBCSH+EApYQQrzgsWItIYQQQghJHRSwhBDiBWU6FkIIIYQQkhkoYAkhxAvBYKZbQAghhBAy4KGAJYQQL9CBJYQQQgjJOBSwhBDiBQrYtKJpGm666abe/0OhEEaPHo2rrroqofX96le/wjPPPONX81BXV4e8vDz8+te/9m2dqWTNmjWYN28ecnNz8cILL5jee/rppzF9+nRMnz4dTz/9dO/rmzdvxuzZs3HmmWfiX/7lX+A07d6jjz7q675NlPLy8oT7hx2XXXYZmpqafFsfIYQQf6CAJYQQLzCFOK0UFRVhx44d6OrqAgC8/fbbmDhxYsLr+9rXvoabb77Zr+bhT3/6ExYvXoyVK1f6ts5wOOzbuqycdtppeOqpp/DFL37R9HpjYyO+973vYf369diwYQO+973v9Yq2u+66C08++ST279+P/fv344033ohabygUwu9+97uo9fYHbrrpJjz++OOZbgYhhBALFLCEEOIFOrBpZ/ny5XjttdcAACtXrsSNN97Y+15jYyM+97nPYc6cOVi8eDG2b9+OSCSCKVOmoLm5ufdzZ555Jk6cOIEHH3wQDz/8MABg6dKl+M53voOFCxfirLPOwtq1awEAnZ2duP766zFnzhysWLECixYtwqZNm2zbtnLlSvzsZz9DdXU1ampqAABPPPEE/v3f/733M0899RTuvvtuAMAf/vAHLFy4EGVlZfjqV7/aK1aLi4tx//33Y9GiRfjoo4/w/e9/HwsWLMCsWbPwla98pdf13LhxIy644AJccMEFuPfeezFr1iwAQvTee++9WLBgAebMmePoCE+ZMgVz5szBoEHmy/6bb76Jyy+/HCNGjEBpaSkuv/xyvPHGG6itrUVraysuuOACaJqGm2++GS+99FLUet99991eZ1fu23/913/FkiVLMHPmTGzcuBGf//znMX36dPzXf/1X73JO++Ouu+7C/Pnzce655+KBBx4wtf+BBx7AvHnzMHv2bOzZs8f2e0rs+gcAvP/++ygrK0NZWRnmzp2LtrY21NbWYsmSJSgrK8OsWbN6+8PVV1/t6w0KQggh/kABSwghXhioAvY5LTV/HrjhhhuwatUqBAIBbN++HYsWLep974EHHsDcuXOxfft2/PCHP8TNN9+MQYMG4ZprrsFf/vIXAMD69esxZcoUjB07NmrdoVAIGzZswKOPPorvfe97AIDHH38cpaWl2L59O+677z5s3rzZtl1Hjx7F8ePHsXDhQlx//fVYvXo1AOALX/gCXnzxxd7PrV69GitWrMDu3buxevVqfPjhh6ioqEBOTg7++Mc/AgA6Ojowa9YsrF+/HhdddBG+8Y1vYOPGjb3u86uvvgoAuPXWW/Hoo4/io48+Qk5OTu82fvvb32LYsGHYuHEjNm7ciN/85jc4dOiQp/0LADU1NZg8eXLv/5MmTUJNTQ1qamowadKkqNetfPjhhzj//PNNr+Xn52PNmjX42te+hmuuuQaPPfYYduzYgaeeegoNDQ2u++Ohhx7Cpk2bsH37drz//vu9whMARo0ahS1btuCuu+7qvRnhhF3/AICHH34Yjz32GCoqKrB27VoMHjwYzz33HK644gpUVFRg27ZtKCsrAwCUlpaiu7sbDQ0NnvcnIYSQ1EMBSwghXggGAYcxgCQ1zJkzB1VVVVi5ciWuvPJK03sffPBB7xjZSy+9FA0NDWhpacGKFSt6BeWqVauwYsUK23V//vOfBwCcf/75qKqq6l3nDTfcAACYNWsW5syZY7vsqlWrcP311wMQIlu6dKNHj8a0adPw8ccfo6GhAXv37sWFF16Id955B5s3b8aCBQtQVlaGd955BwcPHgQA5OTk4Lrrrutd93vvvYdFixZh9uzZePfdd7Fz5040Nzejra2tV8Cr6bpvvfUWnnnmGZSVlWHRokVoaGjA/v37Pe5h2I5r1TTN8XUrtbW1GD16tOm1q6++GgAwe/ZsnHvuuRg/fjwKCgowbdo0HD161HV/PP/885g3bx7mzp2LnTt3YteuXb3rtTtmTjj1jwsvvBDf+ta38Itf/ALNzc3Izc3FggUL8Pvf/x4PPvggPvnkE5SUlPSuZ8yYMTh27JjrtgghhKSX3Ew3gBBC+gShkBCwNkF8v+aLmRXtV199Nb797W+jvLzc5IQ5CawLLrgAlZWVqKurw0svvWRKW1UpKCgAIARkKBRyXKcdK1euxIkTJ3pdw2PHjmH//v2YPn06VqxYgeeffx5nn302rr322l4x+OUvfxk/+tGPotZVWFjY66gGAgF8/etfx6ZNmzB58mQ8+OCDCAQCru3SdR2//OUvccUVV5he/+53v9ubfl1RUeG4/KRJk1BeXt77f3V1NZYuXYpJkyahurra9PqECROilh88eDACgYDpNblvBw0a1Ptc/h8KhRz3x6FDh/Dwww9j48aNKC0txS233GJat90xc8Kpf/zHf/wHPvOZz+Bvf/sbFi9ejL///e9YsmQJ1qxZg9deew033XQT7r333l7HNhAIYPDgwa7bIoQQkl7owBJCiBfCYfFH0sptt92G+++/H7Nnzza9vmTJkl4BWV5ejlGjRmHo0KHQNA3XXnstvvWtb2HmzJkYOXKk521ddNFFeP755wEAu3btwieffBL1mb1796KjowM1NTWoqqpCVVUV/vM//xOrVq0CIFzCl156CStXrux1f5ctW4YXXngBJ0+eBCDGZx4+fDhq3VKsjRo1Cu3t7b3VgktLS1FSUoINGzYAQO+2AOCKK67AE088geCpImP79u1DR0cHHnroIVRUVLiKV7n8W2+9haamJjQ1NeGtt97CFVdcgfHjx6OkpAQff/wxdF3HM888g2uuuSZq+ZkzZ6KystJ1G1ac9kdrayuKioowbNgwnDhxAq+//npc61Vx6h8HDhzA7Nmz8Z3vfAfz58/Hnj17cPjwYYwZMwZ33nknbr/9dmzZsgWAEMHHjx/HlClTEm4HIYQQ/6EDSwghXpACNi8v0y0ZUEyaNAn33HNP1OsPPvggbr31VsyZMwdDhgwxTf+yYsUKLFiwAE899VRc2/r617+OL3/5y5gzZw7mzp2LOXPmYNiwYabPrFy5Etdee63pteuuuw433HAD7rvvPpSWluKcc87Brl27sHDhQgDAOeecgx/84Af49Kc/jUgkgry8PDz22GM4/fTTTesZPnw47rzzTsyePRtTpkzBggULet/77W9/i9tvvx0lJSVYunRpb7vuuOMOVFVVYd68edB1HaNHj7YttrRx40Zce+21aGpqwiuvvIIHHngAO3fuxIgRI3Dffff1buv+++/HiBEjAIiiVLfccgu6urqwfPlyLF++PGq9y5cvN0135AWn/bF48WLMnTsX5557LqZNm4YLL7wwrvWqOPWPRx99FO+99x5ycnJwzjnnYPny5Vi1ahV++tOfIi8vD8XFxb1TAm3evBmLFy/uLVBFCCEkO9C8pkxlC/Pnz9edqkJmC+Xl5Vi6dGmmm0GyFPaPPsr77wMLFgBDhqRsE9nSN3bv3o2ZM2dmuhlpJxwOIxgMorCwEAcOHMCyZcuwb98+5OfnZ7ppaG9vh67rKCkpwY9//GPU1tbi5z//eaabBQC49tpr8ZOf/ATTp0/PdFN85Z577sHVV1+NZcuWRb2XjedItvx+kOyDfYO4ka39Q9O0zbquz7d7j7cVCSHEC0wh7vd0dnbikksuQTAYhK7reOKJJ7JCvALAa6+9hoceegiRSASnn3563O5yKpGCur8J2FmzZtmKV0IIIZmFApYQQrxAAdvvKSkpcZz3NdOsWLECV155palCbrYwY8YMzJgxI9PN8J0777wz000ghBBiA4s4EUKIFyhgCSGEEEIyDgUsIYR4IRIZUAK2r9VHICRd8NwghJDMQgFLCCFeCIeFiB0AFBYWoqGhgYE6IRZ0XUdDQwMKCwsz3RRCCBmwcAwsIYR4YQClEE+aNAnV1dWoq6vLdFOIQiAQoHDKAgoLCzFp0qRMN4MQQgYsFLCEEOKFASRg8/LyMHXq1Ew3g1goLy/H3LlzM90MQgghJKMwhZgQQrwwgAQsIYQQQki2kjIBq2laoaZpGzRN26Zp2k5N075n85kCTdNWa5pWqWnaek3TpqSqPYQQkhQUsIQQQgghGSeVDmw3gEt1XT8PQBmAf9A0bbHlM7cDaNJ1/UwAjwD4nxS2hxBCEmcAFXEihBBCCMlWUiZgdUH7qX/zTv1ZS1peA+DpU89fALBM0zQtVW0ihJCEoQNLCCGEEJJxUjoGVtO0HE3TKgCcBPC2ruvrLR+ZCOAoAOi6HgLQAmBkKttECCEJMcDmgSWEEEIIyUa0dMzzp2nacAB/AXC3rus7lNd3ArhC1/XqU/8fALBQ1/UGy/JfAfAVABg7duz5q1atSnmbk6G9vR3FxcWZbgbJUtg/+ij19UBRETB4cMo2wb5B3GD/IG6wfxAn2DeIG9naPy655JLNuq7Pt3svLdPo6LrerGlaOYB/ALBDeasawGQA1Zqm5QIYBqDRZvknATwJAPPnz9eXLl2a6iYnRXl5ObK9jSRzsH/0UX79a2DaNGDevJRtgn2DuMH+Qdxg/yBOsG8QN/pi/0hlFeLRp5xXaJo2GMBlAPZYPvYygC+fev4FAO/q6bCECSEkXljEiRBCCCEk46TSgR0P4GlN03IghPLzuq6/qmna9wFs0nX9ZQC/BfCspmmVEM7rDSlsDyGEJA6LOBFCCCGEZJyUCVhd17cDmGvz+v3K8wCAf0xVGwghxDcoYAkhhBBCMk5KqxATQki/gQKWEEIIISTjUMASQogXKGAJIYQQQjIOBSwhhHghEmERJ0IIIYSQDEMBSwghXqADSwghhBCScShgCSHECxSwhBBCCCEZhwKWEEJioesifZgClhBCCCEko1DAEkJILKRw5RhYQgghhJCMQgFLCCGxkAKWDiwhhBBCSEahgCWEkFhQwBJCCCGEZAUUsIQQEgsKWEIIIYSQrIAClhBCYiHHvlLAEkIIIYRkFApYQgiJBYs4EUIIIYRkBRSwhBASC6YQE0IIIYRkBRSwhBASCwpYQgghhJCsgAKWEEJiQQFLCCGEEJIVUMASQkgsKGAJIYQQQrICClhCCIkFizgRQgghhGQFFLCEEBILOrCEEEIIIVkBBSwhhMSC88ASQgghhGQFFLCEEBILOrCEEEIIIVkBBSwhhMSCApYQQgghJCuggCWEkFiwiBMhhBBCSFZAAUsIIbGgA0sIIYQQkhVQwBJCSCwoYAkhhBBCsgIKWEIIiYUqYHU9s20hhBBCCBnA5Ga6AYQQkvUEAsCqVcBZZ4lxsDk5mW4RIYQQQsiAhAKWEEJisX8/sHcv0NJCAUsIIYQQkkGYQkwIIbEIBMRjOMxxsIQQQgghGYQClhBCYtHTIx4pYAkhhBBCMgoFLCGExIIClhBCCCEkK6CAJYSQWHR3i0cKWEIIIYSQjEIBSwghsQgGxWMoJIo4EUIIIYSQjEABSwghsWAKMSGEEEJIVkABSwghsaCAJYQQQgjJCihgCSEkFjKFOBIRacSEEEIIISQjUMASQkgspIAFjDlhCSGEEEJI2qGAJYSQWMgUYsCoSEwIIYQQQtIOBSwhhMRCdWC7ujLXDkIIIYSQAQ4FLCGExIIpxIQQQgghWQEFLCGExEIVsEwhJoQQQgjJGBSwhBASCzqwhBBCCCFZAQUsIYTEQp06hw4sIQMDTplFCCFZCQUsIYTEginEhAw86usz3QJCCCE2UMASQkgsVCeGKcSE9H9CIaChIdOtIIQQYgMFLCFkYKDriS9LB5aQgUVrK29WEUJIlkIBSwgZGHR0JL5sOGw87+lJvi2EkOymqYnnOiGEZCkUsOkmGReIGNAFI/HS3Jz4snRgCRlYNDdTwBJCSJZCAZtuWlooYv2AxTVIvCQjYOnAEjKwoIAlhJCshQI23bS308Hxg5MnM90C0tdIRsByGh1CBhYUsIQQkrVQwKabzk6gqyvTrej71NVlugWxodOeXSQqYHWdApaQgQbHwBJCSNZCAZtuurqEiCXJke0CNhKhS5xtNDcndlNB180pxOp4WEJI/4QOLCGEZC0UsOmGDmzyhELi7ng209oKHDuW6VYQle7uxM69cFjckJAwqCWkfxMMiuE+PNcJISQroYBNNxSwydPZKYKLbKa5GTh+PNOtICrBYGLZD+EwizgRMpCQww04XIAQQrKSlAlYTdMma5r2nqZpuzVN26lp2j02n1mqaVqLpmkVp/7uT1V7sgamECdPV5eYYF4dl5htUMBmHz09ic0FSwFLyMBCClie64QQkpXkpnDdIQD/puv6Fk3TSgBs1jTtbV3Xd1k+t1bX9atS2I7sgg5s8sgbAO3twPDhmW2LE1LA6jqgaZluDQGSc2CZQkzIwIEClhBCspqUObC6rtfqur7l1PM2ALsBTEzV9voMnZ10YJNF3gBIxE1LF83NIv0smalbiL/45cCyiBMh/RsKWEIIyWrSMgZW07QpAOYCWG/z9gWapm3TNO11TdPOTUd7Mgod2ORRHdhsRQZAtbWZa0NDQ+a2nQqSSRnXdY6BJYR4QxYJ5LlOCCFZiaaneK5KTdOKAbwP4CFd11+0vDcUQETX9XZN064E8HNd16fbrOMrAL4CAGPHjj1/1apVKW1zsrS3t6O4uNj+zRMngLw8YMSI9DaqP9HeDrS1AcOGAUOGZLo19pw8KURPcTFQUmJ6y7V/+ElHB1BUlPrtpItwGMjJSXz52lqxP4YOjW+5UAiLb7wRhfX1AICjV12FA//2b4m3w4W09Q3SJ2H/SBP19UamxfjxmW1LHLB/ECfYN4gb2do/Lrnkks26rs+3ey+VY2ChaVoegD8D+KNVvAKAruutyvO/aZr2uKZpo3Rdr7d87kkATwLA/Pnz9aVLl6ay2UlTXl4O2zbqOvCDHwBjxwKf/3za29VvePNNYO9e4JJLgIsvznRroolExHGORICzzgI++1nT2479w29efRWYNQsYNSr120oHlZXAmWcmtmxXF/A//yP2R7z7vrbWVI10clcXJqfo+KWtb5A+CftHmvjJT4xsjWuvBQoLE1tPVxcweLA/bfJwA4/9gzjBvkHc6Iv9I5VViDUAvwWwW9f1/3X4zLhTn4OmaQtPtaef5T0q9PSIixBTiJND7r9sTSFuazOK/mSyEnFbW/+Zi1bXk5v7V7opfqQQcwwsIf2X7m7z70QyacR+1mkIBPxbFyGE9HFSOQb2QgA3AbhUmSbnSk3TvqZp2tdOfeYLAHZomrYNwC8A3KCnOqc5k8iLIos4JYfcf07BQXc3sH17+tpjRS3c1NqauWJT/UnABoPJ7UcZhLKIEyHEDWvhvWQErJ/XegpYQgjpJWUpxLqufwDAdf4QXdf/H4D/l6o2ZB3SOezuTn4830DGzYENBoGVK4H8fGDOnPS0JxIBBin3gqwB0IkTwLRp6WmLSnt7agRsJqYG6upKLnOBDiwhxAvW329l+EDcUMASQkhKSEsVYnIK9WLGNOLEcapCHA4DL7wAVFWltwJvRYX5f2sAlIlKxJGI2D+1teY5TP0gE1MDBQLJBXCqgI03ycM6D2wy1ZAJIdlNtjqwyQhpIP7fPUIIyWIoYNOJXwLWb0HS13ByYPfvF8WdADFeMh37SdeBDz4AWlqM16wBUKrGwbqNCe3sFN8/GBQVNf3k5El/1+eFQCC5c0YGoeFw/IFgKGTuS3RgCem/WIcZ9JcxsLxpTgjpR1DAphP1ApLoxUTXgepqf9rTF9F1Y9/19JiDC3W/RCLpcQrr64HGRuDgQeM163YrK4FPPvH/DviGDc5iShX3fjvAJ074uz4vdHX548AC8QeVVsFLB5aQ/ov1dyZbHNhkBWymajEQQkgKoIBNJ+rFLNELW2dn/ynMkwiBgFkIqhflmhrzZ9ORRrxvn3g8cMB4zSpgu7qAP/8Z+PWvgd27/ROy9fVifXa0tRnP/e4vmRCwyaYQq0FovIGcdbsUsIT0XWL9/vZXAcvikYSQfgQFbDrxI4W4rs7eWRwoQbV1v0mnMRKJFrCNjalvj0xZPnBAtCESMacTqxw/DqxeLQTgypXep4Xp6hLVjK20twNbttgvkyoBGwymZ79a8auIExB/IGcNYAfKuUZIfyTW+d9fBWwgYC5GRwghfRgK2HTihwNbV2cvkI4cSWx9fQ3rfpMCtr4+OtBItQPb2QkcPSqed3UJgarOAeuErgvhaxXcTlRW2h/z9nZRsMpOUFpTiP0aD9zZmZn5d+N1YK0uSzIpxHRgCek/xKoJ4KeAzaYxsMFgct+FEEKyCArYVGK92xnvGFi7YjlODmxlZXxtSyXd3amreOjkwNqNC061U1hZaf6eBw7EN+7W62f37o12YCMRIziyVkEGzA5sKCT6jR90dIi/dFe0DAREAOZFPOq6eyGWeG8ecQwsIf2HdArYbKpCHAolvw5CCMkSKGBTyf795v87O4UQ6eiILWB1HfjrX6Mvpk4C9siR7Jknbvv2xMSjl+quTg6snZuZagdWpg9LDhxwTh+2w8tnw2HRj1RBCoj+I13Viopoh9X6eb8KOXV0iG2lezyVPF+89PFAINol9rOIE9PwCOm7pFPA+pm2m+z1PRSiA0sI6TdQwKYS6/jExkbgV78Cnn02tgA4eFCIMquzWFcngnlrUN3YmJzjePCgf6Jk61aR2upEe3t0Vd5du4A//jH2uq3CX4oROwe2uTl1YiMcjna9jx6Nr8CRFwf28GFxrK0OrCrQWlujU8itAs4vMe80B2+qkcGbl8yF9vbozyXjwMplNU08hkKcU5GQvkg4HPs6aRWKybiWwaB/0275IWDpwBJC+gkUsNQdh/gAACAASURBVKmip0c4Z+pF59AhEVifOBHbfVuzRjzKMZaAWFYKB1X8BAIiKE9UwG7dCvzhD8A77yS2vMrx46Jo0OHDzp95/XVRlfdPfxIC9OOPxfOqqthzpto5sD099unWuu69UFK8vPeevTO3fbv3dXhxYKXLa3VUrf9bHWjr+36lU8sbBpkSsF6CuLa26M/54cDm54vHcJhzMZP+w0C6GRMr+ykSiXYpE3Utw2Hxl00Clg4sIaSfQAGbKo4fF4GBFGTBoDmN020u18OHDQGoClh1HKMqfqQ4ScRlW7tWpCpHIsIxTrZirRyPefiwfWC0dy+wc6d4vmsX8POfA2+8YXx282b39duNgT12zDkIS0Ua8aFDwIcf2r9nFY5uNDe7B4+y2BPg7sACZgGr69Hv93UBK497og6s3wKWacTESl+dpmSgFAAEYgtYO4cyUdEnf3P8ErDJuqfBIB1YQki/gQI2VWzdKoShFHSdneb0UuuYxK4u4+K6dq3xenW14faoAlZ1YLdvB554AnjllfjaGImYt6XrwN/+lvgdedWBbGmJTpHt7gZee838mjU42L7dPWCwc2DdqvkmItwCAbHf7aau6ewEXnzRH9eip8c9mDp50tiHVmFsFZDqjYeurmiB1djoT5v7qgPrRwoxBSxxI9bYymxl48ZMtyB9xBKwdr8v2SJgrXOgxwsdWEJIPyI30w3ot/zmN0K8Pvkk8LnPiaBZFaAnToiLkRxX99RT9uMnZXrsuHHOAvaVV8RnXnsNePhh722srY2+oFVXA+XlwJIlQE6O93UBwi1UxcHhw0BpqfH/O+/Yi0KV7m7h0M6da/++nQPr5mZ7dWC7u4WrunWrWSwOGwZMmiQeS0rEuNd4XNZYtLQAQ4bYv6cWiWptNfcXq4BsbhbBWVGRffu6u8WxKSpKrr3y+Hp1MdvaxH5Llngd2Lw882tWB1bdl7GQy1LAZh9dXcDgwenfbiQCDLLc/62vB047LT3bj6f/uhEMAnv2CHFUWJj8+rKd9nZDCNrtv3QI2ESPXSgkfndyEwzbKGAJIf0IOrCpQqbJ7tghHq0ObGOjcWFra7MXry0t4jNSoNXXi+cff2we27lvn3g8ciS+O7R241SrqoBly4C77vK+HsnWrc7rb2gANm3yth63NGKrgAmF3AtGxXJgg0Fg/XrgF78Q446t4q+lRRzLdeuAN98UlYb9xK2QkzyugPieanBl54BKF9ZJYPuRRhyvA/vrXwOvvprcfIihkDF1jRcHNlYRp3A4vkAu2TGwsW6iMK0vcWKNmU8VduPX0+nAxjNdlxtHj4pzK9VTjmULHR3m3xMr6RCwXV3xO6m67t5uL7CIEyGkH0EBmwIG9fQYY1erq0VwUFVlvjg2NxtBtlUU6bpwAx99VBQ7kuuqqxNpyW++aRZ5Uih2drqLOSt2Y582bBDbf+454K237C+0dq/V1UVPG6S25b33vAf91dXO077YpX+6uXJO4qGrSzjNjzwiikr5OeF8PDgFoh0d0anRqnvtJmCdxGW6BWxHh/jcpk3AY48lnv6mnjdeHNhYRZxk27wiA9jcXOGc6Lr3oLaz07iJ5UR5ed8dP5lpMiFgg0H78zadAtYt6yQeDh0Sj6mecixbkOe90+9IOgSsnNM6HmTGR7IClg4sIaSfQAGbAor37DEuOLouhKAMYmVqY3OzEbSq07GEQkKk/v3vxnsHD4o7pzU1RpCkppeq4x8/+shbI3U9utBSZ6ex3o4OIWJ/8xvhPjY1ib933hGFl6zVfdeti95GU5MQXceOxQ7irbz5pr3g8SJgVKSLbWXt2swKh4MHxTF2EpUHDkR/f9VZtXNZpeDNFgdWrQzd2Zn4vlaPeaIOrB8CNifHSKv32g/37o1dbbqmxqg6TryjFslLJ4GAff9Jp4B1G/cfDwNNwMrfrXQKWOvy3d3xC1gpXJMRsCziRAjpR1DApoASmT4sKS8Hdu8Wz6dNE4/SgY1EzA7sCy8A27YJoVtUJITwJ58IN1N1TI8cERfG6mpzMOWUprt5s/niVVcnihE98oghbHbsMLuku3YJ8fnWW0K0/vznQvg1N4vKwZLWVufpYw4fdp+ep7HRPmioqjLSsCWJ3kG2CjddF+O+Msm77wqX3el4WeeYBbw5sLqeOgHb02MEXvEKWCD2+Gcn/HBgrf0mnumV5HceNMgQsF6ntNi1K/a+qq8XmQ8DRUT4RSCQummy3JAF91R0XfwuJiMw4sEPBzYQMIRwMn2vra3vTMUjj5vT+Wv3uhx7Gi9ODmxPT/zXMT8ELB1YQkg/ggI2BQyV4mjKFPG4aZMhSM44QwTCHR0i+Dp2zAjK29qEY5ObC9x6KzBrlni9qkqML1VTcuVcslYB9Mkn0Q3q7hYicssW8+c2bRLbfPllEYBs2ybeu/128bh7d3RgoutCcG/caHynjz8WgdCHH4o7+uoF+4MPnMeNNjYCjz8utm/HW2+ZL7jxuq8S1a0GhGDI9JgvGUjZBaKRiL2AlcLU6U56e7sQialKIVYd1M7O2EGdVcB6mffWjngcWLlvYjmw8QTsdg6sFycjEBBOu1vRr64usS8jEX/mYR5IdHUl3qeS3a5VwAYC4himI6MjGDSmaUsGNQMnGQF78mTfcfYScWCBxISfk4Dt7k5cwCZTPI5jYAkh/QgK2BQwVBbf+cIXxOPu3YaIGztWVLQFRHCrijv5fOpUYPx4QwBXVYmCPqoDe/KkEGJymp6RI8WjdRwqIIoUdXYKoSkvgC+8YLithw+LlN1jx4CCAuAHPwBGjxYXe3Ue2u5uMSb3D38A/vIXMXZUjnF85RWREvvMM8CPf2xMl2NXnEpy9Khoj1M6XGurObUy0eBwyxZzsJdp9xUwvotdCuSxY/bfVTqYbo7esWPeHdgjR+IrRmQN2mOl4XpxYL1sXw0qYwlYuW/Uz+m6GFO9erXRpmQFrJebKfv3i/7tdrzUduzalT4Hrz/Q1SX6VLorQtulEMvzNdGbbPHQ2Cj6SbLTs8j0YUD0w0QFcV2df9871U5uImNgAf8FbCZSiOnAEkL6ERSwflNXh8HHj4sU4H/9VzGFiFpcacwYYPhw8fzwYbPTJgXsGWeIx9NPF4/V1cJpOHFCBNAlJcacqzI1Wbq11dXmi1QgYIxPbWkRQbKuG2NsZ8wQj+vXG+sZOxa47DLx/65d4vHkSTEeVqb1yvG4Tz8ttiGF6rhxQpRs2hRbcMpl2trMQejhw0K46roY0/vRR2KdiQZJzc3mGwVWRzbNaGog0dQUfVfczn0FDGHqJohqapwFbFeXeR9u2iRuonjFGrS7tUPXzdM+AfYC1q4StpV4Uojld1fnTAyFRHr8nj1Gqns8AjbRFGJ57rS3Owt1azv8mjNyICCrufo5rZXX7ToJ2HQ4sLLPeE1jd0IVsN3diRey81PAdnamTsTqunF84kkhBhITfnIZPx1YViEmhBAAFLD+89574vG004AJE4Dp0433hg0Tc+1JAXvggJFCquuGmJACdvBgISbDYUOETpwo1guIlF8pdi68EBgxQnxWdRg/+sh8UV63TgTWlZUiGP/c54CzzzbeX7JEVFqV7vGuXaKo1K9+JQKn0aNFu2Qlzro64QiEw+J7ffWrxjjfWOJIumHWIPSNN8R+PHxYrPfNN4Hf/97sBseLrNrc1uZfBc8EyVOFX0dHdBqknYsOeHdg3d6XLmw4LFx9u5RzJ+IRsHbjUO3SPa3jnO2IJ4VYtikcNjsg8rlcPh7HSS6rOrBeUpnluakGzlashX84v6x3ZL/wa0qZeLabDQI2GdGo3nSUJFqEqr7eXwGbKpdQpuoDA9OBDQbpwBJC+g0UsH4jqwDPni0eFyww3hszRjxKAauOMa2tFRfYYcOMdGDAPI4WEK7s2LHG8jKt+KKLgEmTxHMp1o4cia5KXFsLPPyweH7WWUJQX3klUFws0pZle6+4Ahg6VAgRmaZ8/vnAHXeIzwFGACQf5feTAjbWnKlqiqkUN7puiCzVwTt6NLkxgnv3CnGTYfcVAHJV4dfWZg7AOzrMVaVVvDiwR464Bzly38ppnXbv9h5MWYNzN8fGmj4MRDuwoZA4HrGEpBpU9vS4izz1Rohcrqcneh7Znh7vc9nK/ZOX513AWseCO7mEVgeWAtY7UoTEOw42WRcqWwRsMg6sXQZCouNg/XRgu7pSJ7LUY5ZOAWtXhZhFnAghJCkoYP1m61bxeOGF4vHyy433rAJWDRik2DvzTGDFCuHcapohYOWFyypgGxpEauPChcA554jXN2wQIvbpp+0vWG++KR6lyC4pAf7lX0TxplGjxGtFRcDFF4t1n3ce8I1vAFddBeTnC+ELGCJFPsrvJx3kgwcNcbJhgxDOUpR2dZmDeini1Dvw1hTUZIhEhBDPAgGbp37v9nZzAC5TvO3o6BD9wC1lMlaAIwWsTD3v6RFOrBficWDtBKxVaDQ3i+8SS0hag0q3wF1dlwxSg8FoAQt4D9jtBGwsEWT9rk7f0doGjoH1TqIOrNu4fC+4jYFNh4CVTmkyotEvAdvRIb6znwI2VWmu6jFLRwpxtjmwTCGOja5nbk54QkhcUMD6ia4bbuU//IPxmJsrnlsFrBp4SQE7a5YQol/6EnDnncY4WEAI2smTDQG7b5/Y5siRIn14/nzx+po1oqiSnZtTXy9c2IICYM4csT7ACM5HjDA+e+ONwH/9l0gzlq+ffTZwzTXiuVXATp0qHseOFQK4tVVsr6dHpAR3dBiVjq1BpAz41Wkx/J5XMd4xnynClELc3m70g44OMb2OG+3t3p1DOxobo6cRcpoCyYqbgG1qMgtvOwFrnW5DiunaWvftWoNjt2BZbZMMRv0SsPn53gWsVcjY3XTQdW8ObDoKAyWLX/OSxkOiAvbkyfiKl9ltt7vbLCbkudFfHNj2dm/H1A8xrZJKAWt3c8tKf69CTAfWnba2zM0NTwiJCwpYP6msBFpa0D18OHDuueK1oiLhYObminGxQLSA7e4WKbKaJpxUyYQJYszruHHG//n5Qkzm5RliYNIksezSpeJ/tVqxFZlePHOmEKIzZ5rfVwXs+PFivZKJE4HrrjOEshShUqx8+tPiUdMMF/bAASHqZWAgC4fIZQad6oJ2AlZ1YHVdCPZkgrbm5qxI0YwaAysDx7feih0Iuk2T44XGRjEGWF1HZaW3ANRNwL7+uuHqAvbueThsXoc81rEEbDwOrCoU5XeySyEGkhOwsfqhNQiyO2YtLdGOSjgcLa7UYjvZSEuLKJKVbhJNIW5tTU5wyWWt00pZX0sFajG7VDqw771n1HNwQ82o8YN0ObCZFrCZcmDDYWZ5uFFfz/1DSB+BAtZPjhwBhg9Hm0z/lfzwhyJFVwrX4mIh3NrbxYWsqkoEJhMnGuNYJWeeaTib0o3VNMOFlZ8BgLIy4ay2t4uLdThsdrxaW42xtP/4j0JkyxRliSpgpXAGxHjYL35RCOdzzxVtaGgQgUBjo/g+n/2sIUjlONjKSjF9j0TOeyvFr9y+nYBtbzcCit27gZUrxRQ+WSBCkyHX6sZVVwtnWLrTbnhJuXWjsdEsNAGxP70IECdRduyYuLnwzjuiH+u6vQMLmMVGX3Fg5bIFBf46sE7bt342C7IGXMcp79qVukJKbttN1IFta0suTVBuV11HugSsGlz77cA2NYnzt65OTD1WWRnbhfVbwAYC6RkDa7fvIhHn8zrTDqy85iUqrnTdeUwuMaivZyV4QvoIFLB+smwZsH07dn/nO+bXzz1XjDOVDBpkzAXb0mJUgj3jDLOABIQ4/dSngEsvFY8SVcBKtzcnxxC5//u/Yj7Xxx83ROGaNeICOHs2cPfdQoSOGycKOQHCJR461FivLNY0aJCoSlxUJP4fPFikQ+u6IYbGjBHfSYpttZBTU5MQ79KBPnTIEDhz5xr7ATALWMBIUZNBfE0N8P776MvkWQXo0aPAq696WzhZAdvRYV95+O233Z17uayKbIc8Hg0Nwm1vbnYOAtRCTl4FbKIOrFsRJ9leL6gOrBwOkEoBaxVkhw5l/qaN2zHauTN+F9QLLS328yRLVAc2nqlXkk0TlH0oEwJW7QeJikY1db27W/z2yDm5m5vFFGtyf65d676u/pRC7LbdTAvYZB1Ytd9wHKwzdGAJ6TNQwPqNpiEsnVbJ+PGGSJTIz7z/vggAc3OFsCwtNX9uyhTh2H7qU2Id+flC1KoCdt4847mcv1WmIdbXA88+K8TJ1q1CtH7724agHjTIEL2lpWbneOhQIVaXLTPEp0QuI507+b5MSS4pMbdx0SJzcScpYGWxKxmESgEr2yfv8KtT6Hzwgbf5Q9NBa6uY4ieO4lBRAra+3hBzXraXjIAF7MVUT49wt52mKrIrbtHeLoSN+t3Ly52rKANmoSOPdUuLe+BvFaxOwXIkYl6PXREndXodOf1TLOwc2FgBqJcUYqcx3qqADQZFO5M95snQ0eGcxtzSYsxT7TcVFe5TXsnjGw7Ht38GugPb3m7038pKMaxETtO2ZYv5fN6zx73oVV9OIbbe9HDbn4m0ya0KcbpTiNXl6MA6QwFLSJ+BAtZvhg41glzJoEFmkQkYAlYKwM98xijGpJKfby7kNH++GCdrFYeS++8H/v3fgf/7f4HvfEeI56Ym4KmnRIB/3nnmzwNGGq9125om5oX9P/8n+nvK+W1lYCvF6dlnGyJYurAFBcJplf/v3CkuokOGCPe4oEBc0Lu6DFEjx9nKOQZPnhT7dfFiEXj85S/JpdD5RWWluDkgxxZ7oLcKcUGBeIwn+D5xIrkCNG5IESvnL7W+Z72wd3dHT23U2ircXCekAxuJmN12J6fNLq3P6bi3t5uDUrsUYvX1SMRb+mmqijh5cWDlfLXWKYjSSW1tdGaEZNcu8djR4W/qnSyI5yZg1X0cj4CWQywSbZebgE11wS21Hye6LbXfWYX3hx9Gf97Jhe3uNvplXxOwuu79dwVITPTJZaznRU9P+h1YdTk6sM5QwJJEyHSG1ACFAtZv1BRclSVLjBRcwBCwgBB3ZWXiudWBBYwxrjk5wAUXCLE4dapwZidPNqobA+K5LPJUWAj80z+JqXF0XQjpiy82fx4w0n6tAhYQ21NdWYm1+NOMGeJRtgkQYrmgQGyzoEAUoSooMAKFsWPF/pLp1A0NIiDSNDGvLSAuKDKInTBBOMzjxomA1Wn6l44O4dKmoxy+FJ9OAb4NvfPAyjHGbtPiWHFzN/2gu1uI2FWrzN/JyVmyE7tuolAGvK2t5h99NUXVToSqOAXL1hsBdkWcrOuMlUYcCBgBn5pCnIgDa3V8vAhY6XBlWsA6ZQjs3Gk899OFraoS/c9pDKYqJAHv42BlIbFEndLubuM4yt+XcNicru5FyCd6E8oPB1btd3IfynXZpWI7ZbuoGQR+Oc+pnAfW+vsQz9CEvl7EiQ5sbHp6xO8sx8CSeIknhiO+QQGbLgoLjfRewBCR48YBy5eL50OGRKcaA+YiTSUlQsjOnQvcdRfw4IPmz2qaISblOm+6Sbifl18OjB5tFs+AEJKDB9sLWCfkHLKSWbOM51Lcjh0L/Md/CBEMCAEtxTIg9kFRkbFdGSgNHy7ELyACeDk2c+pU8zhfJ+dyyxbhDG7Y4P37JIoMYq3TyLjQm0Ic63vYka4pVfbsAR57TKQW+jk3ntNYZylgQyHg+eeN7dkFlW4OrN3nnBxYILaAra83xEZenvhza4PcnjUICofNxy4YdBZ8dgI2FSm6XnESsDJ9WOJnISc5n3Z9vf2+VoWkbIsXZB+x689eRKXaFrmOeIqMSexu/MTafiTivwPrpaJxe7u9w6BWGrdLyU2EVDmwdr9h1u+cDgErnd90T6OjtoEOrD3yvKADm176g/jL5PV5AEMBm07KyoSLCAiRef31wM03G0Gxk4CUolNN5Z09W4hTaxVhALj6aiGWZbrj0KFCxC5eLNxYq6OqaUJMxSNgZ8403Ki8PLNotrqzKlYBO2SISJ0GhOsCiDbOnCna1dxsFHCaM0c8DhkiHp2CLhmoeB1XmgyqC+Pxh7g3hVjemMjk+EY3QiExtc+zz7oX04kH6SRaj01trdiHzz8vCoPJmw92x9gp0LTu/3gdWDsXqaHBCBq9OrBeHGKZGmyHKgSly+XVge3pEen2lZX+9avaWnGBtgbPVhHm10U8EDBSkwH7rAPrPvYqnmUfsROwTpWznbYr12FdVyw3sr3dXsBWVbnPfW3t3344sHIdbuvSdfvfNlXARiL+OHupErDWeXvltlRSKWDlue6UVmzF2jY6sKlHnnsUsOklVhHHbCcS6R8ivA9CAZtONM1wWzVNiLTBg4337dKH5Wc/+1lD6AGiaNKwYeaxsJJBg0QK7h13GOMsJaNH229j6tT4BOzw4YaLPGaM2dUdPtw8BY+KHAcLiLYXFRltkk6rTIMeMUJc+GUAK8fuSgHrFCjKACiOtN6EUUWCl+3pOnJlwCtFf7YKWMnBg96rJMeirU384FsFbEMDsHq1kRa+YYMItJJJIY7Hgd26FXjuueh1OjmwbsfaqV+qFzm3uV1bWoxtxptC/MYbovK401jmWMgpvSRyXLquR4tEa+Dhl4DdscN8vOzGwVr7QLwOrPUY6XrsKtzW7crz2LquWAL24EH749ncbD8GVX3f2pZEXE87BzYYdHf37PavVWwnmx0SiZhT9v3E7oZFulKIIxHjnJLfzW194XD0/qaATT0UsJkh1cOiUk1HB/tMhqCATTeTJ5uLMqm4CUhZJEmiaSJt107ASsaPj96Wdfyrun45FtULJSVmAatOEwSIYk5WiouFCB83TjyXDqxcj7zgS2E7apSx7OjRhvjNJgGrBkZeHN/ubgwKh4UQkoWwsl3A+kkkIr6v3b5SxzR3dYlU8GQcWC8Ctr5eiL6//tVwgVXq680OrBSwx487B+xO/VI9zvK72hWTiUSMMcJSbHgVsKoIUx0yL+g68Le/GZkQgNl5tx4zqyvvVwpxRYX5f7txsH47sB0d3qZV8kvA2gnClhYxF7SX1HJA9I94AyfrzSP1XHAToHb9z7q/khWwMi08FQLLTsCmy4FVn3sRsHYuNIs4pR4pYDkGNr3U1/ftmyrt7RSwGYICNhMsWGD/upMD60RZWWzX1CpgnRzYUaOEc+uVggIxTjUvT1QSLi42v28VsMXF4vOaBtx6K/DP/yyWLSoy5puVTJhgdmYBc7GqWCnE8gLd2Zn6H8Z4HVjZZjX9267AT3+mpcXbvvroI3sxYHfcIxEx57Dd59xSiNvagI8/Fs/D4WhXyZpCLAVsKGROc1WJ5cAGAsZ47717gR//WAgXleZmITSkc+NFwHZ2mtsfr4DdtUuk0W7fbrym3h1XhU8kEj29ih8OrFq0TVJTE31+2AlYL+eQPAbWY9TS4q391jGwuh6fgNV1ZwdWOu9yShsrdiI9XtHY3BztsEvcBJx131iriCfSFity+VQILLubhKkUsOGw+WaYXF5+NzeRZHfd8kPAnjyZnmtiX4VjYDOD7Jt9lY4OViHOEBSwmWDmzGjBB8SXwgsIgRdLdHoVsPGiacD554vpesrKoqcOGjvWnFZ83nnG//n5olhVYaFYbuJE87ITJ4rvpb5+2mnRAjaWAwuk1oUNhcxBjxcXSLZ5yBBxLHJzRTCTyqCip0cIpmwRya2t3tzqlhb76Yk6OqKDz337oo91KCT+urvNFxi3QFV1FaVbpQrY/HzxPBw2Cz2VWAL2wAFDREiBKIsWSZqbzQK0vT12kR+r8IslYN9801x9trxcPN+1ywiw1TRhdf82NkYH4X44sFb3FRDf3Sr4rMe/p8feQbWmOasCVt2fXgWsut1QSGw3HgErK63bpZ3J77hli71jaLd/4x0H6+aaxuPAWquIx1reC6kUsHZj1FKZQmw9tvE4sJ2d/juwx44Bv/oV8MILdGDt0HWmEGcKu5uhfQmnInck5VDAZoKcHCH+rMQrYL0wfrwRdOfmRlcgTgaZNmw3dZC1GvLcudGfk0J03DhzYSk5DY9aoGrqVKMCsxw37BQoxisqE8UaZHoRZTJIKyoSf3IfpjKN+N13xTzATtMOpZvaWu8Bod2FLRQC3n/f/NpHH9kv39UVfZy8CtiWFrEtKXSsDuzhw/b9K1YKsXoc5H44ciR6WhjVTZWp125Yx3A2Nzs7PfX1Yp89/bTYP7t2GYK3p0dUoQbMAlDt33aFN+T45kSJRKKdaIlVnNuJJetYKl0HNm40vyb3oXUanpYWb78V1u3aTcnjJmBlQTogWlRJAR0M2t+48cOBdROw8TiwdjcGs0XA2vV5O8c7Hgc2EIhvqiBrG6wCVi3sZCUVDuzx48Y4djqw0cjfeoACNt2Ew/4VicwETCHOGBSwmeL8883uaX6+eZ5Yv8jJMQRhvGnCsZDiyzr+VSLTiE87TWzbKmDl9x0yxHhv8GCjWNWZZ4rPjBkjnGRNE66t6sDaBQHpcmClMJLtiSeFuLhYLCed+FQKWBm0Os2pmW7cChh5ZcMGQ3DV1jrPVRkIRAeqbgGyeiGVAlLeXS0oMDuwAPDJJ9HrcHNgIxFzcSUZTOq6+XWrAwvETiM+etT8v+oqWJFOZ22tuLnx3nvm97dvF/tJFTyqgLULOJKtxnjokPPy1r5rJ5asn2loiE4rV9evHqeWFm9zkHoRsG5CTm2Pejx13SwS7c5Vvx1YmaEgcWu3VcDa3azzS8AmI7B6eoD9+6Nft+tX8QjYSEQ44/G0Q8UqYNXXrLg5sIk6Peo8xXRgo1F/JylG0gsdWJIgFLCZYuhQ8zjR0tLo6W38QqYROxVwShQ3BxYQwnXwYOG+AtFFoqTwKygw3istNSonjxwp5rq95RbjfZl2XFBgXwAHSJ+AlaJz/HjRJrvAw4oMdouLhRjy4sAGAskJAym03aboSCd+lM2PRETxJV13dl8BEaRaf5VkoQAAIABJREFUBYZboHrihHFTxCpg1SrE8rXt26Nvorg5sMeOmR1hNdBVA++mpvgEbDhsL3rs0ogjEXP6c11ddN84cCBa/DU1GQ6r0x3zZDIe7NKHJV4ErNWBrakRwkvd3+p5pL4uBVqsNGJr3+no8D6NTiRiLpClbquz0xw4W49bJGLftnhEYzhs3kfxCDhr30u1A5vocIfDh+3Ftd25E08KMSBumnkNVGM5sHafkXR0JO/AWvefWtCODmw06u8fizill3DYfN3ta3AMbMaggM0kl1xiuJDxFnCKBylg/Rr/KpHC1UnA5uSISsnnniv+HzzYmEcTML67k4AtLhafGTzY2IZ8zymNOBIxX4DSkUJcXGwcv1iCWQZpQ4eKGxYypdtNwD71lJgaJdHAQ7Yz3qI+qSKZNFOVAweEK7Jzp/Nn7BxYt0C1s9MQOdKtUh1Y2f/ka3V10QUo3BxYaxq3ekwrK41909QULSrdBOzx4/bBrd0xP3QotpsbiQDvvGN+Tc51rOvOAjbRQk6BgJj/14maGnOQYCeWrFWkZdqxFG3hsFlsJiJgk0khrqkxCxj1GNil6Kq/Y07p2V4d2KYm4Pe/N98IsC7rJkA7O83tSaUDCyT+W1dZaX8Mk3VgAXG8ZGp9LLwIWKfv6McYWOtvh+rAJjp/cH9G7c90YNNLJCL6u1/TsKUbphBnDArYTDJ6tHAXi4tTM/5VMnGiEI5+C9hYKcQAsGyZkXapaWaxKwVsYaEhAEeMEP8D5kJXcjn5nlMhJ+uFPx0ObFGRdwEr2yv3mUyXdnJYdV2IkEAgsTQbXTcCdbUgUX/hlVfcv5MqYGWGQ6wAToozGQSqY2BlX1bFhNVRdhIwwaCY41RFDWK7ujBUurCtrc5FfuxwmsPUznV3Gmdqxa4oUmOj6Kt2RYYA8w2jujpvQYmuA2vWuAcBoZBZNNuJJWs1Sylg5fFxc0rTIWD37jX/7yZgrenfTu3yIhorK0UBn1jjiGOdF2obUi1gvaS52g0hqayMPk903R8BCxgVy2NhFbDWKsTqa1b8GANrzVhQt+t07g5k1P1NMZJe5PW7r6YRM4U4Y1DAZprRo8W0Mqedlrpt5OYCkyalTsA6ObCAITgl6mfVFOL584FPfUpMMSRdLnVMsNyWVwEr1+F1eo1EkIFAPAJWBk3ScZZz3ToFFT09hlhK5Ae+p8f4cbXOATkQUFOIZX/yKmDtHFjrGFggWiS6FXux7n8ZOJ06/0daqxGruAlY6/hXidWB7e52dzpj0djoXnBDihw5p+zjj4vUYKdzMBwGXn7ZeeoYFfU7Ookl6bYGg8b5Il+zihh5zgWDxvNYGRuJClhdj84UUI+n3bFVj51Tu7yIrvXr7QVhIg4kIL5LKlOIAW8O7L595qJYTU3inLWK/e5u+/Wp25MuUCyOHo1OVbfDyYFV25HIGFgv4ioUir5WqMd2IM077hX1hiQFbHqR19K+WsiJKcQZIzf2R0jKGTnScOJSxRln+J+m7EXAWrFzYAsKxLouvdT4H0jOgR02TARcgYD4gbGbtggQ7x04AMyeHf8YZDWFWBbHilfAjh0rHp0cWDXISmSuNKswrq/3/0ZGNtPVZfSJkhIRvHV1iSDc6XgfPy6WkcfELoXYbbxiPIG8DGjPPRc4ckQIWDlm3IqTgNV1Zwe2sVG0Vabu79iR3BivpiZ3B0eKh4MHjWJdL70kUr3l+Z6fL37vRo8W1XbV4lVuHDkCLF4snjvt45oaUSCvtjZ6qiInAevmhFqxirymJvspU4JBY7w0INpj/W2ItV31fHcSsLH6WjjsXOBMLpuXJ9oba12yjU5j/dPtwNbWipsjZ5wh/pdjtq370um3tbtb9JFBg+IrbLRxI3DNNe6fSTaFONcSmsUjYBsb3QvXUcBGowoQjoFNL8ncoM804bA4XylgMwIF7EBh7lx/KxAD3lKIrTg5sCpeUoidxsDKALOgQAh2GTgWF9uLlrffFimVubnAOed4/x6AOYVYfgevKcRy7Ou4ceKxpUUsm5dn/t5qIJLID7xVbNTViXmIBwptbUbQJwuAhcPiNVVgqJw4YXZV43FgpXjxigxip08H3nkHxUePir5gLXgGOAvYxkbnoFS67mPGiOdenE43GhvdMxpkxoN1/KyTwI6Ho0eNbbsJWMCcLtvaKvaPVcjIc1EVPG4CNhyOFjpO48o7O83H0G6cdqzt+uHAHj3qLJTksqWlQix7dWCdsjjSLWCPHxfivLpaZBjJGyGymrQ8V90yFzo7xe9tPONCvfTlZIo4dXZGXxPl742XQLmhIfr7WAWs2w28gYi6X+nAppe+nEIs4yv2mYzAFOKBgpMDmQy5uWLMqgwUvODkwKr44cBKAQsYc9899hjw7LPmz8tgxOpuHj8ee6xQMkWc5OcnTBCP9fXAL34B/OxnwAcfRH9etjHedGg7B3YgoY4lzc01+o9bwNrYaB7XKu8Q2xVxkp+X24hnrkjAEBeDBxs3M5wEQmtr9PFvaQFWrnTfhhRCe/faj2uNBy8pxLt3e0uzjJe2NrH+YNA5kK+rE+9bxwAeOxYt8uW54VXA2vUZJ2Gp9gO79GG5fdlvEhWwsUSjmmLrtKysv+DVgXX6jZOZDYkSj4DVdeMc/eAD0R/U6blU0epWwf1nPxO/uy++6L2djY2xU5yTdWDdxsDG2sf19dF9VV1fd3d2BNx+FfPzAwrYzCH7gZfzKtuQ1xQ6sBmBApYkx8SJ8X3ezoG1jpNVKw0PGiT+1IJP6rJOqVKFhYbL2dQkXNaGBhHQyR+dzk4jGFMDyIYG4MknReqjG3ZFnJqbxQ/ysWPmKTMkMrCVQePkyUBZmfhffkf1Dr/6/QKB2NVjrcggXY61TVUl4mwdB5KIgNV1YNcu43/5vQoL7QWsrhuiMx4Bq+vGBVstEOXkzEQiZhFWXw/87nexb0rU1Yltffih97Y5UV/vfpMmGATefDP57Thx5Ii70IpEhLCxFiw6dsw5hVg991tbnQNru+06iYlNm4z3jh1zFqCyTXYCVq1EnKgDa50KSUV+H/nb4FXAOt1gsc4rG+/NnHjGwKrB7p49IkVdFYfWY+qEPHedxpA7LRNrOEeiDmxPj3jdaQysrscWfrEc2GyZSidZx95POAY2c8hrqa7HH99kGnkNycbYZwBAAUuSIxkBq46JU5EiQ9OEu1lSYqQ/SwERy4HNzze7ohs2GJ+RAlF1idQAsbZW/JgePuxefKarS7RxyBAj9TcSEXfzf/Mb4faq7QuHgZ4e6Go15qIiMZ7q7ruBFSuiv5P1Ih/vOFj5AyunUqqv97+oVVsb8Mgj8bkY6SIRAQuY3Rx5ccrPN5a3XrCkiIwnaJduSm6u6N+xBCxguLC7dwvx6qXKb12dkWqZLF6Cu1ROh3D0aOzAd+/e6DbYCVi7FOJIxNmxiyfNdPNmMTzByX2VtLaKvmSXAi4rEet6YlWIu7rcnXD5fcaPN//v1lbAvRCcbE8kArgVJLOi6/E5sNbK39abJl4d2ESJVXDGKhC9ViGWfVL9XCQSn8CyE7Dqtnp64hvzmyqyqRoyHdjMofbtbLqp4QX5u80+kxEoYElyJCpgCwqMQhU5OcZ4RE0zj02UAlYSK4VYHQMrHdjdu80ulbzbrgZ3qqskA7Rg0NltktsdMsQQ11Iwy4A1EjELzlM/zsHi4mghrj5XL+zWH/R4x4nIdY0cKfZlKOT/3LhNTSIAcBJIwaAQW3/5i7/b9UJXl3Fxyckxxk7HCtZVkR/LgQUMZzseAau6r4DR793ckepqYNUqYPVq79uqq/PHfc0GvAjYLVuiX6uttRewkUj0+ZDMlDUq69YB5eWxBaycW9eOkyfF+053+N368aFD7jer5PcZN0787rqlZgNivzhVILau8+jR+G6YqNXWgfgFrDWA9OrAJkosAZtoCrE8p92mdfEiYK37zypg/XRgE0kFDoezaz5aFnHKHOq+z6Y+4QWmEGcUCliSHHLcnleKioSQUIUbYAiDggJzcYmiIrNr63UMrDq3rHxt6lTxaCdg1dRBNUBzEoxq+rBEVhQePx6YNk08VwXsqbaGiosNsaLuB7kuOwErq1TH68CqU8jI6sN+j4OVF/y2NvtgZsMGsc937kzdlEZuJOLAStTvk5/vLGATcWCdBKxbAPX669Hzicairg6Q88v2dU6ciH+qG0D0TWu/l66fVbD6JWAB4P333R3p1lb39+vq3L9vKOTcX9zGvwLmFGJ5Xrh9x54ecd54cWD37YtvDm63qrl2WAWsFXWfZsKBTTSFWBWw8rcyHgEbiYh1BALm31rr9D1+OrDxporL9mSTULQ63Jm4Tg1U+rIDyxTijEIBS5LDqZKrE5omHFVV+AGGMLCOhy0udhewToGP6sACQrxcfbXYfm2tuHhKATtokDlNTw3Q1EBl3Trg978X21QLOEkuuwz40peAO+4QVWUBewe2pMRwn1UBW1Ag2qJWspXfT6YAJ+rAFhWlbhysbKuuRweLgYDh/snqv+lGbjMvz+hnXgWsvDDl5Ihj45RC7IcDKx/9Hp/Wn4IxXU9cjNv1vY6OaIcu0YJJidDSkpyABZz7stv4V3W5kSO9ZybU1bmnfqoCNlbFarvlJG7ngFrAyYlYc+wmy4kT7s6jnYANhcy/G24OrPp+PAJWHU/oNOes3w5sIvs32wSstaZBNhWY6u/0BweWKcQZgQKWpJ+hQ6MdWCkMrBWJnQSsOo2OGiSpAjYnx1h2zhwhaMeOFRenPXuE2CooMNKgZaCoClgpQHVdVLs8ckTMpWnnwBYUAGeeKYTOmDHm5WVbcSqF2M6B1TRjfTKQsQrY+vr47vapAlY6sKkSsEB0ML5uXXQhqnTjhwObkyP+nBzYhgbRR5IRsEM0QEN2BXbZiNd5Y71QV+eefqqSir4by4E9eTIxx7mx0XtF9LFjvTmwgPOcspLOTrHtujrRv72eD/E4sC0t3gtOhcOpGWvpNrxEvm/93/qd3BxYwPi8tX+6/f6rn1X7q5cU4kRvdCXicMc73Viqse5TCpL0YL1Z0NccWKYQZxQKWJJ+hg1zdmC9ClgpJnTdfKFWBSwATJkiBMLixeL/yZPF48cfi8cJE6Kn21ELqkgH9sQJ48d1926zMLRDFbCWuStNAjYvz+xiW8fBym0OGyYqFUci8aUA2zmwqUohBszBeHu7sZ/ld8zEBSoZAevVgQ0GxXdPRsB+6iDwKID5lUD+CQD9yDn1Ez/dI7siR36mEMciloBtbo59w8muL8cqoKQWTRozxrsDqxY3s6OrS7ivErd0Y+tyKm4CNpb7ChjjdTs6UpeB4JZG7EXApsKB9SJgnVKIu7sTC8QTEbDZ7MAC2dW2/ozV6e6rDiwFbEbIzXQDyABEFaQStxRitYhTfr5wKnVdiL3ubnHRlwGYVcBecw2wfLmx3smTgY0bjcB1wgSjCFNzsxFwjRghgqDmZrFOdUqcqiqjTU7z6xYXi/Z1doogddgwYwysmkIMiM/JINbqwMrHwYNFoNnYKMS0HG/rhhwPJbehjoH1cyJ7NThSg/EPPhCBwFlniXZUV2fegZViMV4BO2iQELFOAhYQQiNhAasDo9qA4QBGHQPwKyA4FOgZA3SPBtpmAd0TvK+beMNNwMpU1RMnhMMuhdmmTeI8/PSnk99+a6vzTTDZhlipwFbxFwrZF7JSkWMs8/LEb5P8/Ywl0mNNN9PVZRaYTU3GTcNYy6kkK2CDwcSmHYuH48eBc8913r71fy8OrOoWOzmwiQhY9XUnBzYUEtcMa3ZULPpDCrFVSNGBTQ/W62hfc2A5BjajUMCS9DN0aPQJ79WB1TTxmUBAXGibmuynX5BCQ3XNAOC008zrnzjRuNCrAnbUKCEsjh8XLqp0HnJzxcVNzhPqFnyOGSPE7smTIkisqQEAdI4bF+26yqDZyYEdPFiI1j173As5SbdB08Syui6WzckRbZX7rrPTve3x4OTAylTPiy4C1q4VzzMtYJNxYNXiY3YXrPr6+C7AJgGrAW8vA3b9FfjsSOC8TiCvVfwVVQIjPgLaZwANFwPd471vg7hjJ4aamkTF7MpK+/TT998Xd94vuMB8cy0R2ttjp/rGuilibeOuXbHTZtXflbw8o1/HOi9iiY7mZvPNvkQdWDeX3YuABcRvUSoKOEnicWDtpq5JtQPrVDDKyYFNVMD2RweWAjY99GUHNhQyfrfYXzJCylKINU2brGnae5qm7dY0baemaffYfEbTNO0XmqZVapq2XdO0ealqD8kihg6NFk9uY2CtQaLdOFiJOo2OHcOGmQXxhAlGsSerAytdztpaY+zXRReJR/mD5eTAAuY04lCo10lpLCuzTxtWn8uxvWqgKddnV8hJ14FPPgF+/nPgj38Ur1nTnGUBLfU9P7ATsKGQ2JeaJipVex1jlwpk+5IdA6veDLG7YCXlwALIywf2AXhtNHDg28ChbwDHrgeaFgGRPKB4L3D6k8CUXwKjXweGVALgnd+ksOsHwSCwbZvzOSL7k18BeLIp/e+/b+53GzfGXkZ+bylg5e9Ysufnvn3moNRrJWKvDmxPT++NwJi0tqbegXXCzoF1mhtWxcsYWKdgORJxdmC9FHEKhRKrTpzIPuYYWAL0bQdWvT7Qgc0IqXRgQwD+Tdf1LZqmlQDYrGna27qu71I+sxzA9FN/iwA8ceqR9GeGDo0O9J1SiEtLjRRfidtUOtYUYjtOO00UYpJT9MiAyypg5UWsokKst7QUWLgQWLPGWCaWAwsIAXv4sLhgjx2L7pEjnQWsOpVOMCi2k5cnxJcsNiXXJdfR0AC88oohsmWRE7txusXFImBubzfalyx2AlZWIC0tFe2MVzj6iby4+OHAyn4ViUSnYdfX+1OFOBgEMAgIjhR/7TOBxouA0g+BYVuB/EYgfwNQugEIFwLtZwMdZwCBiUBoOEQlKJIy5O9CtgTgLS3ACy8A//RP4rcmVpovYASKhYVmAZvs+WndJ36PgX3rLe/nWKod2LY28Rtrdw2wCsREijjF68Bax1I7CVhZEdlKKJTY8e8PDixTiDNDX3Zg1VopFLAZIWUCVtf1WgC1p563aZq2G8BEAKqAvQbAM7qu6wA+1jRtuKZp408tS/orQ4dGj790SiG2ilcgeQE7ebIQsBMninbI9rS2GgVTRoww2ihT1qZOFY7F1KnGuLTiYtFGu7L7qoCVU3+ceaZ4tI6BtT7v7DSPfwWEezxxonAgKiuBmTOFiPrTn4QrO2SIEFltbWJsnwwK1QDLbq7ZZLETsHI/ynG3mRSwMhgZPDhxASvHwObnG8c7EhGvSY4fjy/wkX1Vigd5Q8LOHQkXA/VXAPWXA4XVIq24eA9QUAcMqxB/ABAaAnScBbSdA3ROA5ATvS6SOLpu9IlsCnIPHgTeece7g2FNIZaZGX6fn346sAcOiPHHXmlpSa0DC4jfXTnnt4qdA2vdt4k6sE7BckOD+X+5vUgkevoeJwEbrwOr6+ZA3ivZJmATKeIUDotrgV+1JAYi/cWBlXMHq33BzzojxJa0jIHVNG0KgLkA1lvemghAvV1cfeo1Ctj+jN0daycH1g4nASvn2Rs0yCwQrcydK9zW884T/8vpdlpajKIuI0YYjphk6lTxeM45hoAdMkSkINs5DVLA1tUZgcFZZ4nHWA5sZ6c5yJTMnCkE7K5d4vnRoyKIKioC/vmfgfJyYMMG8T16p2dxcHj9wjruKhAwBKysfOwkHFUnOVXI9hUVJZ9CLJ1YGRSqAjbe6rjy8+PGiUeTA+vEICBwmvhruBTIrwOKdwtRW1gD5HYagjZcKMbNtp8SszpLHiSNGnBlUwAOiPmWczzesLA6sFLA+h1AtreLfi779vHjIitDvcGo69FTBckiUzIA7O4GXn45vm23tqbWgQWA9etFpXvrjVZr37CbYivWZ+J1YK1CUv7G2c0/a9d3E3Fgu7sTSzu2S6nOJImkEIdC4nxzizWIO/3FgQWib2gHAubYjfhOys88TdOKAfwZwDd1XbfeDrW7PRFV817TtK8A+AoAjB07FuXl5X4301fa29uzvo1ZRyAAzJgh0jBj7bvCQmDGDIyvrsYMAMfy87FvxgzktbbiQgDBIUPw4dlnu69j1izTv2UTJmB4SwsQiSCSk4O1CxZAz8nBBcOHo+BUcPXhZZchOGwY8saPx6K//x3dI0Zg4znniGBMOo0WFo8ahcL6eqCpCcGiIqy79FK0FxSgfNs2I+jp7BTfHcAwXcdcAC3hMA6NGoUyAE0jR2LbqfcLS0ux+O9/R6iyEuumTsVZ77yDcQAOL1uGQ2VlGNvaipkbNqCurQ0dkyZhCoBDp5+Ow6eWP233bkzbsAGHCwpw6NRryXJOQQHUZOSNpaU4vbsbYwDsnjMHJ2bMwLhjx3A2gNr8fOw9td3Jr76KqatXY+sDD6BNOtMp4Lz8fJQCqBg/Hq3TpmEJgEh3N9acdVbMO6RDNQ3zALQUFWHrunVAKIQL8/KQFwzig6lTEXIbAx2Ds9aswQQAe4cORe2MGRhcUoJFADoBbPB8bGYAODUuW9cxBDUYjQ0YjfUozjkKDNsGDNuGHpTgOJbiGJYhoPmUOj4AyensxKdOPd8+bhwafTqHvNJeUIByH7Y5ed8+nAHgyMSJOPjJJxg+bhzKADRrGir8/k5r1hhBfkuLkfUi6ewU2SXDhpmXKy83zs/WVnGjR97s8YIsYJfqY/Tyy0YdBYmct1uludncFk0zX+t03bjBCYibouXlpusDAJERZDf1UkeHuX90dYnlIxHMGjwYo+THNA0brdsGhBANhWLPO6wSDousonjjHXljIVvipOnTzf8fOBB7rHUkIo5hH3HZsjIuDYWiz89sa6MTbW3mtq9ZY+4L1hvcWU5W9o8YpFTAapqWByFe/6jr+os2H6kGoNbYnwQgal4DXdefBPAkAMyfP19funSp/431kfLycmR7G7OOykrgD38AbrwxdsDx+utiXOqp9LAJtbWYsHdvrwual5uLpXv3xrd9xREYNHw4LpYVdEeOFBf00aNx4fHjRuGOO+9ErtzOokXA9u326y0t7S3Skjd1Ki6urET5jBlYunix4Yzu3Pn/2XvvKEmu68zzF5lZ3nRVV3vvgEajgQZIEJZwNCJoRYGUQPGsNBpK5FAr6ogzOqM5u9rdmbOaXY00RytRIw3JkeGQogwlSiRFI3qiQYBoeNtoB6C9re6u6rJZNmP/eHU7brx84dJUVwH5nZOnsjIjI168ePHifu+7xrgBw2U3sCUXL3LjXNmOXt8Pn8/q1RTOnOHur3wF9uwBYOOmTWw8ePAyKV5+6BDL51Y3NxeLbJbfz63wbzx+3GxfC4ib4Fx5o5uff964NAI7ZmbYcfDgZYNr9blzrJbjPv00zM5y0+OP1zeGZG6c3Agmm3ShQG5mhnv37i1X2W3MZVRdMj3NvffcY67l3EPqzoMH45N4JWFOpd6+YgXbR0YuG0ztY2PZx28IO82r6QJ07YOul2hu6WcD32CD/w0YvQqGbjZxs41S4NmgVt13HTmSzmOkhti9fXuVY2MOx48DsKFYZMNttxklEegZGKjN/jVuvNF4i5RK8Ad/YIjVL/+yCeW4dAk+/Wm3Gvee9wRE90//NHuyq54eM9/Nh9J3++2mrJLnmfP8nd8p3+aaa8Du2w99KDB6L1wwCbkEt90G995rPGqeeCL4/L77zPFsPPggu4eHg+u3c6f5vVVruGN0lHuLRbj//vDvDxww3jz33JP6tDl71mSYv//+bPfCd75j2mW34Upgdhb+838Of/bBD8L118f/bmTEXGt74WWBYkHapefOwWc+E/7sp3+6dhUS6okvfzl8P7///WFvt5MnYd26+W9XhViQ4yMB9cxC7AF/Cez3ff8PIzb7OvCv5rIR3wYMNeJfX6eohQuxXUInC/RDaOnS4L2s+Iv7sKC3N3C76+mJXoXViZL0Km+lLsRgXJjBGAGzs7B1q2kPGMLd1GQMFnHjtZM4QX1iYHU2Z4nHinMhljbU221I2ifnnsWNWCdx8jyjJMmqarWkWwzrzk6TDTsuBrYSTC+Dgbvh2K/C8V+B4V3g56HzZVj7t7D5T6DvR8YNuYF00Nd8IcXAZoUdAyvzRz3uRVngOnIkyK7+9a+b/vva16LHu8zn4+OVZWoeGpo/N9U9e4Lsz1Gu5a5YUb2t7WKcNQux7f4t13J6utz1vVYxsHKMSsInFooLvmseTxsDu1DOYbHC1feLxY3YnpMWczzvIkU9Fdg3A78IvOh53lyGEX4b2ADg+/5ngX8B3g28gvGc+0gd29PAQkZUEicXoghsUgmdOIgBZ7+XlW7XirduT0eH20DRBFa7yUYlcWptNURpcjJws7IJ7I4dJmGLGA033RR8l8vB6tVGYZFspLVM4tTfb9Tmu+4K+lnasXy5MVaPHTOTeXd3+cKEi8BWEkOVBWKsdXebY7a2mms1MREoPJcuwd/+rSmTtGtX8FuJ0ZHrJTGwer+VQvqtqytMYGtuFHkwsQ7OroP8O6D7Oeh5CpouQd/D5jW5HMY3QXETFDfC7CJYAb8S0Nd8MRuvch+2tpqxLYtP9TC6JD/A3r3BZ+fPw+c+F+QccEHujzRZlV3wy6KR6ovvfjdcls2Ga87V8cHVEljb8I+Lga1VFmJpY9Z7YSGV0XGRqDRze4PAVg9X3y8G4uf75UnTGgR23lHPLMSPkFDPYS778Cfq1YYGFhFqQWDTZCCOgjY6tALb0QFvf3v8b1taogns+vWGVG7eHCaqWrHVBNPzzHZjY4HhZxPYvj5To/bcOaPe6bgpMEbU8eOBAVdLAvvII6be7IoVAdGTh3hfn/krCa5EfdXnoA0k6a/5JLBnzrjrB7/8sjGqX3opTGC1Ait/66XA5vP4uRyeK0FUrTDbAYNvhsHboe0odO+Fzn0mm3HLeeidU5EmlxvT1M6bAAAgAElEQVQiO75pjtBW4Sr9WoI2bF8LCqxkUV+yxMw9otbVcuwNDpp97t8f/jyOvEIwL8y5Oy94zM7CP/wDPPCA+3tXQqk4BVbmh7QJhorFcDKpKAI7M1O7OrDVKLALJYmTq4JAg8DOD1x9vxgU2KGh5IWlLCX1GqgIjfRpDSwMVOJCLESkWDRkTRPY7u5sJRSiCGwaCIF1obfXZAeOIq9gfnv11TAX80pHhyGY4qLiymR3ww2mJuLNN5cbm2vWlO/ffj86Wlmad4ml0quL8hAXwirXQSe2kmsmv9MuZPNFYOUa9/QYVUcnK5HFAvuho2vIyt9aE9iuLtNXTU3MtrRQKBZN39Q1AUQOilvMq//dJoNx21FoOwZtJwJC2zNXtmRyBQy9AYZvhNL8xn0uKCzkLMRZIPehhEE0N5t7tFg0r2piu20MDJhFrUrVvUoV2CuB4WH46lfd37lIkSZxaRXYqHmnWAzP9fr3NlFwLWBWosBWSmD/+383Y+JjH0vOQ1BvVKPALhQSvlixWBVYV0hDQ4GddzQIbAMLAy0thkyleZgJ2c3njdE1MWEe/prA9vVlI7BdXUF9z6wEtrk53uCz92eTRs+Dd7/bxIhNTwdkV1xUXAT2ttuMurt2bfl3msDmcuFFgeZm46oqZQyyqtXSp/rBbRNYgf5fuxuXSmFjrd4rrmKMSJyzuIjr0kcSp2c/dGwCWw8Ftrvb7HPlyoDATk3NX4Igv2BU1qJkTp01hLb9qCK0/bDiu7Dsh6Ysz8i1ML719VeaZzErsM88Y7wn3va24J7TBLatzYz/iYnaEtihoegkd3GQrLhJSm29MDlp2r4iY9Zu27UwDmkU2CwuxJrARimwEE1gK1Vgsy7m7N1r+vbUqfL8EvONhgvxlcNiVWDTEthGLdi64nVmfTSwYOF5xmhKozppw37ZMpPt7dy5cgJ75Ej64+dyQX1YHQObBnEKrAuuCa2nB+6+28S2yr7k4egisJ4XneFu6VLTpslJQ4bt43V2GsI2OpqNwPp+4AanDR3bhVigFVjPCxYbJibC7tbzpcCKm6QsKLgIrG1ExsXAVktg5bwlDnfNGmblelxRwygf1JoFYBY6D8GSp6DjMHS/YF6zzYb0TqyH4gYoruc1n9V4McfAPv20IYOf+1zwmSzqNDWVe0nUCqWSqVudFVNTxuX/Si0UfOUrxivmE58oX5yrFfRCoMxBgmqTOM3MmJedxMm1rWw/XwqsnEO95/40aCRxunKotQJbKpXXZK4H0hBYSZZW7zr3r2M0CGwDCwe6NmAcNIFdvdoQ2DNnwkmcbDIFgcIQhfe+N31bNVpasikWUStyd9wBzz8fdjeG7MWwPc/0y9GjARnu6QlcZjs6jLE0NubupyiMjweTtBgevh88xFtbTT8IObVr42oCqxWAehoxvh8YS21tRmmyCazvhxVY/RC0FVjJRKy/q7Rd2oUYYPVqSjK2F5RrWh5Gd5hX00VTmqdzH7SeNRmNO182m810wfBOGNkFk6tISIGwOLGYFViZ+3RyI1uBhfooIC6lJQmTk1cu/nVszMTFg1FU60VgZe4slcoXXLMosL7vfrZNTIQVWPG+ccXnVaLAVprESc5hIahtjRjYK4daK7BjY8GcVk+4CKw9ZiRRWYPA1g2v8eXyBhYVKiWwYOrR6TI67e3lLpgrV9ZnMqmFAgtG2bvzznICa/+fBuJGLO1ar8otV5rISbtki3FVKhnjKZcz7RdFp709mojbBLaeRowYbrmcuU4tLWEC6/uGcGtDRBuCNoGFYAxVQ2BnZ82xxQ0eFpACG4PpPhi4C45/HA7/WzjzAbj0JpjqhcIILH0MNv4ZbPw0LP0xFAaT91kvvPoqfOELoRqYVWMxx8AKafm5nzMLWps3Bx4YTU3hnAILAZOTVy7+9cCBgOjXc4FN5tFTp8rnwSwK7PR0mAzIOLUJbNwixXwqsNKehTDWGi7EVw61VmCzhI1VgzQKrHg/NFA3NBTYBhYO0hYE126vUqf1zJmAzLa0BKUhzp4Ntl261KiQOnlPLdDcXBsCC0FJHvuzrNi4ER59NFBY16838W9QWwIrE7SQuiVLjDFmq68QdlGcLwVWDBFJvtTcbIh1c7M5brFY7ro3Ph70kYvAJimwIyPwT/9k4pSvuca9jfRfc3Owv+XLAwK7oBTYCMwsgZHrzQvfxM12vQBdL0HLBWh5EJY9aFyLh6+HkZ1QqmAxplK88ILxQnjllXCpqWqwWBXYUsmMd88zZbh27DCfy30rSZxgYahicGUJrM6YXM/5SebPV14p/2521rzSEFht9D/5pCnp86//dRBHLHNVa6uZx6Uer34WaXfjtAnkKo2BlfbUsh55pWgkcbpyqLUC68r0XWvYIVAClwtxg8DWFQ0C28DCQVoCK0Rkasok2MjljJuXuPG2tARqoE1gz52rLYFtajLHr4ULsexPE9hCoTLV+KqrjAEjpH7FiqDPdCbiLNAE1nYd0wQW3C532kC2Fdhqkx0Ui8bd8KqrwjEwNoGVZGFLl5qxMTAQjoWFsHudPGD1NUgisEeOmFq4LS3ZCGw+z6z0kfSr75vau319YRK94DBXa3ZiHZy/z8TKdr0InQdMEqi2E7DiOzC21RDe0WvAr7NrlfRhLY2IxUpgheBInWmBjOt6xsBWijNnrgzBKRbD7rz1JPQyD0jpMRtCQDWSCOzJk2ZukrAalwI7NWU+03OKjktN6/VTiQI7PR2o2wuh1IiLRDViYOcHi1GBjUrS5rpPF9MzYhGi4ULcwMJBWhdiCGciXrnSvD95MviuUCgnxEuXVuaOm6YdtVJgC4VwG7PGv+pjbNwYZHVubg76qZYKrCZiYJSdZcvguuvKfx9FYHUcbaV48EH40pfg4MHw5/IAaWoKFj4g7EbsUmAFlbgQS5/E9a/uN6V2lMXAHj8On/0s/OAH0ftacMjD2FVw9gPw6r+HM/fD2DbAN/Gyq78CW/8AVn0VOg6CVyeFqx4EdrG6EMuYtuc/TWDrGQNbCU6dujLHPXgwTGrq7UJcLEaf69RUujI6+prp2NmJiXASJ7nGkmBGo5LESpUQWD0vLgQC23AhvnJIGstZMR8KrMt9GBoK7BXAQl7Sb+D1hrQKLBgyJJPVqlVmtVkmkDgCm4VopkGtCaytwNaKcBcKpp9OnAjU4qwEVj8cbAVW+mH9epO104UoF2LZXzX1AEVFPX8+cI+EsAJbKATt1KV0hMDm82YMJcXAJimw0idpCazad5kCe/68+Vtrt/f5gt9skjqN7IL8GHTtNcps26kgm7Gfg+I6o8qO7oSZDAtZcZBr31BggzFtL4gtZBdinWxqPiHuw8uXm/uv3i7Ehw9Hn2slCqxNYHUdWL1AFrXfLNe/kiROmrQudhfiBkGpDi71e6ErsA0Cu2DQILANLBxkUWDtRE7PPhv+TmJgNepBYIV05fPJWY4FSQS2Fgqsa7/iTlyPGNg0cbpRCiwYQ6ia7IFCru0HmCsGFgIFdnAwIL+S0dqlwGpyLe9rRWCVAlsWAyvj6bXwIJztgEu3mlfTgCGyHa/M1Zw9bl7LvxeU5ZlYY+JnZyscF/V2IV5M1ySLArtQXIivBCYnA3feG24wng+1JrA6XGJqKtp9WL7PSmBlXAqBldrbEK7HXa0C6/vVK7ALYaw1YmCvHGqpwJZK2cOiKkEUgXXdT4vpGbEI0SCwDSwcZIkjdWUiFugYWL3vqGRLhULlaopOKNXRUT2BLRTCpLVWBFYUWKgNgbVX3ltbTexpXLkM7aIoD5rubrPfalUf2Z+dcTaJwGoFds2acgJr14GFwOiPGjOa3E9NuZVlXbM4ToGVtqQZn8WiKcO0a1ftXeVrjemlMHCPeeUmoP1Vk/yp41AQMysorjcJoEauzUZmGzGwARajAnslsHevMao3bAgS4NWSwPq+yYzd2go///NmbMYR2LQKbJwLsbRfz39xLsRpr7+Ora1UgV0ILsSVltEplRoEpVq4+n5ysrJ6rpOT87Og0FBgFwwaBLaBhYMsE5YmsCtXGlIoblhCCjQhFsLiIrDLloWTPWWBJrCdndGTm0aSApvLGQIyPl5ZBuKo/UrCK+mXLKuVvl+uwOrY1ZYW09Y4g0S7EMt2S5ea/bqMxNOn4dvfNvVxtVuwjdnZYH9xBFa7EMt46O8351IoBDHCLgVWJ3FKioHVD62xMTeBTRsDm0WBfeYZoxhNTMC99yZvv1BQajWuw6M7ITcJbUeg9bR5tR0LCO3y70BxoyGyozuSyWy9Y2AXE4GVMR1FYF8vCqyUzXJ5e5w9a7L3ArzhDfUh9BMTJsGbPK9On44v81SJAqsJ7ORk0P5CIZiLXPv9yU+MJ0tawu4izWmwGBTYhZLEKUtG6MWIqGfoxET2RViJ964nSqXypI+CRhmdeUcjiVMDixOa2DU1BVlvRWkTAiuTvxAW16S4YkXl7bAV2DRIUmAhaKf8zaJOR+23UDD9JGqpa3U/CpOTQVHuQsEYX3qCbmlJVovlmskDoL09PnHM/v1GEf3yl42yGAVtEKV1Ie7qMp+J4dXbG1y/WhNYF+S4khVZDmcrsGLgpblOsiAxX7Xw6oFSC4xdAxffCqd+AV79LTjzwbmsxXloPwYrvw1b/hDWfw56H4Xmc4AjhrDhQhxAxlGUC/HrRYH91rfgD/8wnGUYzD3/pS+Za3rDDeYlc3stFVjpW983xnDSwmktYmDlOz3/TU2Fx+/kJHzuc/DVr6a//rpfshBY3daFSmAXSgzsQuifeiLKY6uSOUjc5euJoaHo535DgZ13NAhsA4sTNlnSNWDBkBPPC9yI4xRYV83StKg1gRWDUvYl53nffdnbpo8nRH7VKvN/VjdiIUXd3YERJKQWjPGbpBbLuYhK3dERbyRK23wfvvY1eOop937t5FL64acJrOcFx/O8IJETmPdi3CfFwNaSwFp9Fklg0zwI5bwXQmKUWsFvhpHr4PSH4PBvmYzGo9sNmW07Acu/D5s+awjtim9C8/ngt40kTgGSFNhcLpgTXqtG86FD8PTT5r0mjr5vFsmGhkwYwXvfG54r6kFgId24dBHYtFmIZ2fDLsQ6PMV2IR4fN2Riaip9Jtes56KPJVgIY61SF+IGga0eUc/QSs57PlyIXXPBiRPwwx+G21wqNZJ8zQMaBLaBxQmbLEl8py6vA8kEtqOjusROmtikVUnjCGw+HzYm29rM9tddZ8riVAIhb1B5HKwmsDoRiCawaRVYMQ7SEtitW83fb33LXYPNdoXWCqQcS5cTEsiYAENgXS6Urjqw4n4Y9ZDNqsAqRMbAvl4JrEapxWQzPv3z8Op/gNM/C0M3wEwnFEah52nY9GlY+zdGmX3jJGwGZmpo1ESV0envh7/6qytX+iUJSQosmHHteeGyK68VFIvwjW+E/xf098PRo+b+/9CHAi+YahXpc+eMqnlCxXPreS7NPZ3VhVjHZYoCq12I5frbBFa3K23G80pdiDWBXQhq/0JO4vRaJ7CLTYF1jZUHH4RHHoEXXgg+q8fiaQNlaMTANrA4YZOlNWvMX3lAixFiE1jbgOvqqi7OtNYKLJi2v/GNxqi46ipjZHqeUWH/7M+yt1EbqZVmItYEVgyQrAqs/b0msK4Hlhzn7rsNqX/5ZWMUSnIVgU1gh4YCt3BdBxbC10sTWF0jOMmFWI4fFUOsH6JJBNYax6WoLMRpDKrXOoHV8JuDuFl840bc8xR0P28yG3e8AlLN6fwp8PfA8A1QqjK5VZQCu3+/cUt94QVYu7a6Y9QDSQosBG7ExaIZS7XO2J4Gzz9v2hEX814Jvv1tc79KojlNDOQ+XrkynAlfL67pzMFpceiQIa9795ryYpBdtZyYKDeaS6XyJDdz55PTc4+dxEkrsDYx1gTWrosd1zZBFkNd/26hEtiFEgP7WiewtVRgJQa2kns1LVzPYfFY0M9d2W4xeeksQjQIbAOLEzYZ2rABfuqnAkPBJrDiLtrUZAwkedB3d7uJl04KFQc7iVMaJE2uTU1GdRTlUYzMNWtMbFZcPKgLOoOuJCrKmshJCGxXV2DgaAW2rS29Aivo6Ag+i1NgOzqC6+dKeGK7vOltpH1pFNjWVnNtxGjM54MVYv07ibeOcrXTRk0SybX6LKTA+n42F2LZ9vVAYEPwYGoV9L8XLrzV1JrNX4DDT8I2YPks8D1TomdypSnRM77VvPyMj0BtcGkiIeM3rftlNRgdha98BW69FbZvT/ebNApsc3NQCqxYnH8COz0N//zPtSewJ0/Ciy+aefDOO2H3bnccpt03kktBYv2z1qmWezaKsGW5p23MzITbM7ffvJ5HJYmTJrByjjaB1e1KG0NfqQKrz6meNXbTwkWiXIsErt/Vm8AuBIJfT8QlccoKWWiamQnPaxrVklsXIZVnvOvebiiwdUWDwDawOGGTJc8z2WrlvTx4enrCyYLAGGZJBHbpUre7qo16KbAaejK+5ZbsBFb/vr09eEF6siOGeTUxsJJIKqsLcXt7sBDhIrDyAJHMzXqbOAVWx8AuXWrGTFub2UexaEi+KwZWYqbTENiorMya+CvMaoVkYiJYREljUMkDNK58z2sdpXYYusWMnT9+0gTJ3NkBv7Aa2g9D6znz6n0SZpth/CqY7ga/CWa6TIbjOJXWNmCmp82Ymk8Ce+CAUXubm9MT2DQKbFPTlU3kJIs21bgBHjxo+uc97wnmUUkat317oI5rEhXVN2CurRDBK0Fgo+Znm8DOnU/ejv+3Fdg0LsRxWZE1apHEaSEQtCg3VruPbTQU2OoR1feVKrBgxmIUgS0Wqysx58o0LMe1F4+gQWDrjAaBbWBxIo4saQK4ZElYaQNDnERFjCKwy5enI7D6AVcrxcKefG0CmhU2IW5uDhTYsTGz4v7SS8ZdWdRFG7WIgZXthHDGEdiZGbP/XM78Jg2BXbfOuO1ljYH1PLPQAQEJHh8PE1h9DTSBda3oVuNCrBVY+yEuZCkK2hiMKt/zeoGMyxLwNPCW/wW8aWg9ZUrzdB6A1rOm9qzG8u/A6LXG3Xh8E2CVsHDFI7a0BNdzPjJAn59LVJVWvdJKfhoFFq6M4SzXTDL0Zq0DCfDoo3D8uKmFvHmz+UzHm7vOL6pGrvxmbMz0tav0ThzsRGyQncBGLYDpcej78QqsHLOpKZj34xTYSpI4SdKaNCVf9O8WqgIL6QjszEzlYzUNFiqBnZkptysqQS0VWE1go2yx4eHqCKw9/2sPK1d8e4PA1hUNAtvA4kS1BFagCZmGfJ70gK2XC7GGfojGEZi0+2tqCvrg5Zfh2WfNeX7ve7BzJ7z5zUG2YkFSFuK2tvhrsno1nDljttMEVtpmP7C0+qoJZhyBXbPGEFiXAiv9pvuvpweuvjpcbsmOg3UpsO3t5lwnJsx29sMyTRInGVfWw/SyC/HUVLnxKmTJhVIpPFbHxsIKcz0xPW2yuq5bV7/Yo6zQ1+AyMWqC4ibzGrgHmgag/QjkJiA3R27bX4HuF81rttm4GY/shLHtxt3YpcBC0Pejo/WNwYKAwKZVvaamzPiQElgatgJ7JQms7tvZ2cpIgTZiBbrmstxvLgXWZdhWo0i7FNisSZziFFi9zzlPjTIFFoL5sVAI5iq7jI7uj0pciGWfaRYxsxLYehJEiCewaX6XtLBYDRYqgS0Wsy/ouFAvBTYKIyNBIstKYI8VfX82FNh5R4PANrA4EfegTCKw2lCJUmDb2gyxyUJg7fjaKFTjQlzJg9K1PzFkRGVes8YkSHrpJfPq6TGK7BveYMiny4XYjoGNI7CbN5v962004bf7Wce/QqDAujJkStvEPTCOwGoi6nnw4Q+H92UTWFcMbKFgHt4TE+bYcQQ2KQbW+u2sLnPhUmCjENV/84EHH4Q9e+Dnfz69S2sa7N9vjOlbb83+W7teq4tUTi+FIWtuKFyCJc9C50FoOQdd+81rttWU73nvRSgCwxhld2bumsj1LJVM31dbtzkOWRXYOBdZVxInuDKunTaBjXIDjEMSga1EgYXKlMIkBTbNAkSUAqsNabV/J4GV76U2urRN97eeL9LmRbDHyPR0dgKbpg9GRsx8Wy8SG0WiksjH65nATkzUhsDWOgYW4sdUtR4ycQqsPm5DgZ0XNAhsA4sTzc1BRkkb2o2pUDAJnjRsBTafN8aSnmyEwCa5EdsPLh1fG4WsCqz+X4rRZ4k5cu1v2TLTjrY2eNe7jPI6MmJc8F580RDFJ5+EZ56BBx4wD9JczhA8bdSlTeK0YYPZlyawHR3BAyxKgZVr1dFhzr1YDMd3+n7wEBECOzwcEBbbhTjJ0LANXJcCm8+bh/f58+UrunYMn9RXtI2vKAIbp8DGPQyj+m8+IDU1+/trS2C/9S1zHjt3ZieEuq9831zHNC5vMz1w8S3mVbhkXI27X4DWM7DkeXiz2vYDQPGLMLsGfvYcXAROAKXDwHXUo0pdYXQ0GO9pSVWU+zBEx8BeaQW20uyd0ieu+MzmZnP/e575Xlxe4/qnGgJrE0iorA5s3L6t/Ze5EEM4DCLKhdiVlTkJLgU26+/S/GZszMzL9QqJqIUCG4VqvDFsr5qFhFotcNVDgY27HtXmKLDHSpQLcUOBnRc0CGwDixOeZ4wt1wq1bahKZmKBJg2yitja6iawSbAJUWdnchmCagisHDMLgXUpsD098Ou/HrjDgiHz73ynKddz6hQ88YQhs3//98H3nleZArtuXVgBAXMdXAYnBNdVrpXnGRV2YMAorBKHWiyah6DEt0kM6+iouba2Ait1dqMenFEuxPo65/NBuQ37gTg7a4yWXM78Jiqjq1w/y2i+XEZnZsbtQhwF+4E/nwRWVPFaJjCamQnOYXS0OgIr/2eN2ZrpgUu3mVfzOWg/Bg89BKPjsDEHbyhB7whwEN6of/hVKH0LxrbC2NUwvsUkiKJ6t+J2XWc27RyQRYGVbRaCApsVvu9WYXQmcnlu6FJBcf1TCxdiSfbT1JTdhTgKEfGrTgVWE9j2dncpIT3XRC262bDn7LTjUf8uDUEbHTVz/0IlsHHnXY03hq2SLyTUaoGrXjGwUWgosK8pNAhsA4sXaQmsTQCFTLS0BMSktTVsgLe1pUvKZD9U0/ymGhdiKG9rEqIIse1ardu3bp1RND0vKNAtpM2lwNqZnjWWLjUP8aam4Lfibi2IcoHVBM9FYOUBIgsRS5YEmYhdBNbzAmLpQpoYWO2KZ18H6Q9x0y4WTRujCKxt3GhvAPthm0WBTauiVItSKXDZriWB1QS8EjLuIrBp3BujMLXSvHbvgUvj0NMNn7sEn3gXbOiG734VmqZgC7CrHbrGA/djgJl2mFxl3Janl5i/Y9tMPdsM6LAJbBqFpxIFdjESWJfbsH4v93B7e3hhKa5/dLx/VugxODFh+rfS2qk29HMvyYVYE1h5TU6G5wg9H05Nme+T7heXC3EaZM1ePDZWXyJQTwV2ZCQdgZWYb30vL2QCW28FtpI5P40LcbXPqLQEtlEHdl7QILANLF5EPWCTMiGKoaKL1tvqYZQCm8+HH3g2gZVkQ3GoVoFNKleTdX9R8Dx4//vNg3T//oDwuhRYreTaEBdurfAIoWtqClx9dRZL24UY3JmI5YEk12rJEpMsSsifTWClHWkJrCsGVlyI9fEFWu3p7IQLF9wP4wgFFogmsHEPQ9ugiIqdqzVGR4M+qmUGXm0YVHIuLgJbC8g1aG2FS8DFHui7Gh4qgVyeu26Cd7wROg5B58vQehIK41A4DBwO9lVqMgmiRq43tWmlJu34uHG3v/HGsjmo4+TJcHumppLd4qMURs8Lz5ULJQsxVEZgo4iRTWDtc0yjwFZLYCXpTa0I7PHjgbt+WgJbKAQLh5OT4XlJ32NSOzYrga1EgU3TB6Oj9SUCtYiBjcLQkMkhkYTJyWBxQTA1Vdl9MB+oFYGNOr9KkuElKbC+X/0zKs6FuKHAzjsaBLaBxYsowpTkKiikqBICu349HD1q3kscrkZfX/yxIbsCa5PkOIO14MiUmqToxiGXgw9+EPbtg02bwse3CazEl0ntUoG4cOskMdo12Hbpg3IXYnAncpIHiFwruaZCcjXhEMS5oqVxIZYkTlBOYOUhphNl2QR2djZw0XORiubm8nq2kE6B7e42D+n5ciHW16KWCqzeVyUENipbcBzSGEz2eJqeNtdSH29kxLgfD91iXvhQGDJJoZoGzfu2U9B2ApY8Z16lPExsgIk18NIgHNsHs0W456dChw+5EEM6AhuVpEgWj/T/C0WBrYSwJBFYmfekH8RVVn7nep5I31bjQqx/XysCe1gthGgXYt0HEs5gK7Ay/2nj245LTXO+lSqwUUp5FBarAlsqpZ8TJdGcfjYvZAW23i7EpZI7w38ckmJgp6erjymOU2D1cRsxsPOCBoFtYPEiaoW4EgJrG4EuAlsohAmsy3BMIrBp6uRVo8CuXg0nTmTbXxLyebj++uB/Vxmdjo4wGdWII7AQuPROTpaTPtuFGMKrqDaBtVVaF4GNM/jTuBCnUWAl3kyfi0ArQvZY9bzg+sg5SDmnNAS2r686AnvokNlHmoUYKF9MqFXJC20Y1MqFOA4PPmjKSX384/FGkz2epF6xRtkqv2cI7cycd4bvm1fLIHQ/b5Ta1nOmpE/7EbgL85rdA1PHYGIdTC2HqWV0XJy7t8UTJE190qgyMa55YSGV0cmKKGUvToHV5N41bmuRhViOpeq1ln2fFWfPmn22tUUncQLTjy4XYgjfVy4X4jiUSuXjvhIFNg1BW6gEVpTbqLbNzqa/j6anzfZ67lnIBLbeLsTgDr2JgnhwQfQ4LBarH0dxZXQaCuy8o0FgG1i8qFSBrdSFuKcnXFvTpeQlGf5pyGM1BHblSuNCqx981SiwLkTFwEKZQUVraxCv2txsVNzly01mWb2N7E/gciEW92yX6mcTWNuFuBIFVgiCnJcgToG1XVwGLTAAACAASURBVIj1uQi0Qe1a0LAVku5uk/E4TRKnvj44cqQy0tffD3/3d2Yfn/hEOvctfS0kI7S+ryrFfLsQv/qquZZnz8LWre5ttJqlFVjb2E9SXZ54Ar77XfjYx2D1W+HiWyE3bpJENZ+Ds89C9zCs9+eU2kB1bfl9TKbjEy2wZxymUxjIUTGe9n2w0MroZEVaF2KdaTnOfVhvWwsCKyqb6/us8H2zkLpjR7QLMZg+FZJgK7ARcbRMTiZff1d/VKLApnUhXogENokwuRLxRWF62lHma/r160IMZh5duTJ7e+pJYPWY0BUQIFqBrXdd8NcxGgS2gcWLSmNgCwVjmEQR2NZWsxrvIrA68ZFLyevudrvx6mMnIU0SpygsX27apY9frQJrwxUDK0TTbtv69cHk3dxsFgB+7dfC27jc9NLGwMp2QijTuBCnUWCLRRP3OzVlSg7phYl8PkxOteqYxoVYjL+WlngFViAENo0CK+MzbSZRjTNnzN+LFw2RSxO7ZdflHRnJTmAHBuALX4C77oI3vcl8Nt8EVq5bHFEplQJjRO4BrcBKBuykOKvnnjP7OX486ONSO4zuAHbA3xyB48Nw1Tr46L3QchpaLgCnoP0ibAQ2jsOdwPQXoXgNDN0Ixc04Mx1rlVG7+L+WFdikJE4QVmBdsehQOwV2YqLc6K9WXTtyxBBYtd+c3U6tTDU3RxNYmwAkna+LwKRRYO0yYwtBga1XDOz0dPq5a2rKTWAXogI7O5utCkIckhTYtMhCYKshlPp6aPsH3O+zlHBrIDPqVBm6gQbmAZUqsGAMFu16p/dlJxoS9PaGFVgXEfK8eBW2FgpsHAFbvrxcWamXAjsxETzEpc9cBDbpuC4j0RUDK8RoeDh48EUpsDaB1YsdUQqslL6ROpF79pjPb7kl3If5vHl1dJgHlCaodhZiKCew8mBuaytfbNHkyD7vNAS2o8Ps1/ezk5D+/uD93r3pfiMEVvqnkiQZx46Z3+3bF3xWTwI7MhIdIxtnuOtkOHK+WoHt6THXc3Iy3oiSurlR10fGy+AEjG+Fwbvg7P3wL3fAR4G/2QK7++AY0DQN3S/C+i/Cpj+Bpbuh7Sh46ny1C7Gev+z7sbk5KDVzJdQfl4KRBVHlWbRXBIRJepR7taDSGFiJcxdIjL9GtaRM4mCTFNgoF+IoAptGgXV5GaQhNdql2W5fFBa6AhvVtqwKrKss0UIksLWcG5IU2LRIQ2AnJsxzMY40J0G31ybYUfNXw424bmgQ2AYWLyqNgQVj6EcpsLLffD58jJ4eQ3qFdEQRyWoJbC0U2LjfV7saKPuXh3NTU9An9jXRBDaKONpui7Kymc+7y9f4fvBws2NgOzsNER0bMw+RLAqs1LkVY/b0abPtDTeEiab0n8uNWBvLUQRWiOLy5e5roa+X5wX7SZOFuLU1+rhJuHAheP/SS+XJuFwQArtunflbSSInGUe6fnK1MbBRBHV0FD71KfjHfwx/n0aBlX1KNlf5TCvqUfWBBRI/D9EEVs7dNn7Pn4dpYGIT7FkNvw18+6fg4j0w3Q3Ng7DsIVj/Bdj2e7D+L2DZ92D7EFwLLB+EZcPGTbnpAjSfhBNfg5c/A6/8OVz6NnS8ChuaIc/8uxFXq8BGGbFpY2BdqNSF2B5/EuOvUa1he+GCGWdZCaxLgbXJf9L56sUuQZrzsTPr6jnaBalXW08it1AIrE28KlVgxVMkDkm16uNQy+zIcWQyy7MkTWZruU9qVX85jsBGvW+gpmjo2g0sXlSjwKYhsGAIkUx8PT2GHPX0GDfLKEIWR2DTtM2ljGhEnbfE7dZbgXUpxELw7LZJ/CtE95etwGr11Xb1WbLEPDiGhoL3EJDJXM640V64EI4FThMD29NjCFl7e0Ca3vCG8mzTcq5dXUZN0w9aMUIKhWgief68+esisLYLcVtb8H8aBba1Nb58TxykXYWC6d+TJ8MLEDZ0Ddh16ww5q0SBles9NBS4PddKgc3lzD7l/4sXzf+arOvt0xJYGUPa8GxuNmNicND0g2se0ATWRRA1IZbEP3IP6HEj/T7QBBfvgIt3G/LZ/gq0HTcZjyV+9mOy838yr03qeA9bx18H/C6mJNDE52FyB4xuh8k1ON2Ta4l6uBDra29nIU4TA1upC7F9r2oX4ubmcvfDSnHkSHQWYnC7EEs/6AUUO4lT0uKFi8CmUWBt8jM7a/ohalFxfNzcA1fChXi+Y2DtMS+fZXV5HRgw57RiRfQ2jz8O73xn+DNdxi5rWytF3H7q4UIMpv1ZSxEKXApsa6s5flQW9YWoor9G0CCwDSxeVBoDC4b86N/rB6hNYMVwlCRCvb3GEK6XAlupC/Hy5eZBl6TAVktgxc1Vx3u6FFitBkJ6AuuKfxUsWQKnThkDXtyu8vnwA2nTJkNQDh92uxBH9Z+4H2t3wptvNn9dCqyovpq0pVFgZTytWJHsQtzeHlb7ouBSYLMYANPThnjlcoa0P/mkUWHjCKxkHe7oCGJvq1Fgfd9c156ecNuLxezxvDq5mHZBdJVa0AZyGhfifD4YQ7YCK9cqqh+OHAneuxRYPVZ83+xbxrYmsMePm/eXjbUcjF1lXgC5CVN/tuUYnHwEWoDN66C3C4YugjcDzd2wZie0rQa/BGMX4cgLMHkcemeh8wJ0Pgx9D8NMF4xeDWNXw+RKmOmm5oS2HgRWk1chAS4FttYxsHEEtqvLPD9qRWBdCqzkYYiLgbUTNwmmppLDD86dK/8szfnY5GdmJv53Mg8sVhfiLFmIXWEP4vKaxqYRnD9v5p84Avv88ybngDwrSiV4+mkTLpOmrQtNgc1CYKshlPq3Mlf39JiFbB1f21Bg5wUNAtvA4kU1Cuzq1eFVzTgFViDxY/J3obkQ62y/WfZXCVpawgRWyIVu27Jl4T5OIrDyEHKV0BHoWrA6/lUfZ8sWeOopY9zJA0fvK06B1dtefXVAzLQBIe9d7qLaYJYyOaLSNTebB1wWF+K2tnC8ZRS0K2RU+Z44iCK5dKlxmRYCe/31sHu3WdX/lV8J96O4D/f0JLvOxkEbeZcumTE0OxvEI4vxH0UyXNDX3UVgozKhxilPWoF1ldERggBuJXpsLCCh4DZu7UWH8XFzrKkpGB6mVCiQ6+1NJlalVhjfBv2r4P97xPTDb/0K3PdR+Iu/MNvccAPce3/wm6EhePiP4K//Gk68Cr/6Ftg+Ysr8NA1Dz9PmBaZu7UwPTPea11Rv8H66F/yYTN9RqEcdWNt9GLIpsHZMcFoiYd+rOga2lgT21VdD532ZwLa1BbHeUTGwdtyrhl2DWkPPYRAsLlWiwNqlhWzIHHYlCGy1SZxkcWtmJtkmiXIhlv3ocZc0Di9cMIQqioxKnz/zjCGxYEqISWx+EhaiAhuVwE2jFi7ELgVWCKzEd9tJPBsEtm5IRWA9z9sKnPR9f9LzvHuBXcBf+b5/Kf6XDTRQR1QTA7tqVfj/JALb3Bx8LqSmEgJbiQtxtQS21gqsfYwoBXbZsnTHtePMkhRYMAaWHf8q2LTJ/D1xIogF0uQnSYHdts24et59d/CdVv/SxMCK4tPRYdo6Nmb6bGTEnGdbm/nOpcDqfqpGgc1CYLW6t2ZN4E4tZAeMS7YuMaMJrPRFJS7Eup2Dg+F4ZjG2xsayEVi7vFNaAhtnhEcRWBm3unSSi8iL+3BXl/neZbjb12x83Mw3c/ub7O2lLZcLZwKPg52kSN+TUfNCWxtMASd7ofdu4N3QchY6D0L7YWgagMIYNF80LxdmOsKEdnI5jG8x2ZajkFWBff55ozJJJmdtxIoxmURgkxRY8WiZmDD7TzsGZUyJMasVWBkjtTBsrfvtsgtxe3tAYEXlshXYONUqjsDquNtXX4UvfQl+5meiy09pTE2Vq25x89RiV2DB9FVSreapqei6unb7hobC1RBsnD9vEuNFuR5LjOxTT8Gb32za+eCDZuE3DeYzBjat+3TaJE5Q+xhYsRtksUgWrQUNAls3pFVg/wl4k+d524C/BL4O/C3w7no1rIEGEhFF5NKskuvYTHtfLgLb0xNMpEkKbFtbeT1UQT0VWHEZsttVLwVWoOuZ6rbZRD5rDKzLWBSV9MyZIBGFbRy0tRmjVsrC2G65SQrsG99o3Gj1g9OlwMpx9UqxbTBrAtvbGygXK1aY/btiYG1jO0mB1epQXOxtHDSB9TyjvD78cJDIbHS0fDzXSoHVcWKDg8F16Ow0Bs7AQPY42CQCWyoFfaYNnjQxsDq5m1ZOkpI4ifvwNdcYhTuNAivbzH0+1dNDmxwrqb36921tZhFGFjjGxqJj7XWdVAA8mFxtXhfvnftoCpoGw6/mub+FS4bgFsag7WSwfx+YWAvjm2FinXnNqkWqLAS2vx++9jWz2PKxj7n7wo5PFrS2BpnG5R6JWgyF6ghsd7cZvzqJk8wbdTBsQwQW3C7EMp/ocW8vpsTdx1p9PXbMHOP48cqSOCUdS65PPeMINYmanjb/26XobOia0EkEdnw8mcC6shBrBVZjZMSQpig75/x5M18MDLgX02V/Q0Nw6JC5nlkyPc+XAisLP3H3pkCP3/lO4iQEVmfYbiiw84K0BLbk+/6M53n3A5/yff9PPM97tp4Na6CBRIiLoZ1xL43KaU/+UQRWyIAY1RAQ2CgiJKV0Tp4s/67eMbCuds2HAisKZZwC6+qvpqbyLMRpFNjTp83f1la4/fby7TZvDgisLnsC8VmIBfaqbxyBjVJg9TnIOWmiaO9XEJXEKcqg0uqr5wWLLllIn7gQS7vuvttcv02b4KGHjLuZbeRqAivxn1JDMq7Ukw3dzkuXwsq6NgKzQK6DJppQvlLf1pbehViX0XEpsC0t8Uq0KLA7dgQE1lYYXAosXB5jUzIPVaLAyjhassRNYPN505YyAuuA3wxTK82r/EsojMwR2wHzt/UktB8LEktdPt+tcOkWGNuWncBCWCm0CcDkZHkJHQjOsVg0Rj7EE9NK4mDlXLq6AgIr/VkvAuv76QisXPepqWD82eMoLYHVCmkaF2IX+YlbaJtPF2LfN+7zFy7AJz+ZnB1ZEJfECdLNXUkuxPbnY2Puetu+H8zlx47FE1iARx4JnklpFwlqWZ82TQmlNAQ2iwtxNW2PciGW/cq+GwrsvCAtgZ32PO/DwC8B75v7rAZWcAMNVAFtiGhUUiamUDAG3OysW4HV9ROTFFiIJrC1yEIscVmauEv2WVe76q3ARmUhTkNgu7qyJXESJdz3jZL17ne7V7e3bIFHHzXvbQIbtfDQ3h5OTqVRiQsxBIT7zBnYvj0c/6r3paH7UBOPqAehJrBQWRInV7t27TLvtculhiawnhcY68PD5R4OUSiVwqRxcDBMYOVaZM2onKTAQkBgsyqwmsDaKp+uVawxMmLiHpuaYMOGwLV0ejo8HuXcZYw7FFigMgVWxlFPj1kAsucBUf/leldcRsczSZ5muqG4UX08Be1HoO2EIbStp0zm5I5XYaYdPjEFY5j6tmdjXFjB9CUYciAxmK46mi4FFgIPmbQKLGTrD72AItdarq0ui5U1OVmaYzY1hZOMRRFYISKy8KQRN3foBE7Sf2mzKrsU2DiCN58uxP39QXK04eH4Y+pzSKPAJiGOwLqyE0cR2EuXgt8dO2a8iaLaBWEbJQuBrYUCm6Ym68hIumeJPa+7XI/rrcDqe62hwM4L0lr6HwF+Ffh/fd8/4nneZuCv69esBhpICZerbiUEVmKdxsfDq/HahVggGWaTCKwLtXAhdhF3cf2U9sX9vp4KrBj2nhcm/a52gSE9dgysLqNjo7UVPvQhc7xt26LjYzZsCBYkZHFC4Lpu0qdRBNalwLa3m9+NjweJOmzFZ/t2E2v00ktwzz3hDMTgHqt2RuwkF+IoApuW9M3MGOIongM20hBYCNwl0xodep9C2GwFVs4tqwJrJ+9yZRm2M9Xa30ft0yYILgVWMjTLfSGGooxLSbJTLIbvC7lmS5cakibnPdcnk7b3R1oF1iawch42XB4RtYLfDGPbzQsgV4Qlz0LPk9B0CZZhXhsB/ykYHYfBW2FiPWUZj4XACsnv6Aiug7hIJxFYjTgFtpJasJpMtraa6yf3i1wLIZBRC2pZoc9Vj08dA5vLBd+5CKw8T+MIbDUKrCsGNu7eng8FVtrz0kvBZ5J8KQppCKx8niYTcRYXYiGwLugkcceOxbfLRloCW6sY2CTyCukXYfVc5fvBuNaIIrCzs+a+SBNrq9V6uQYuF+KGAjsvSGXp+76/D/gNAM/zeoEu3/d/r54Na6CBVHDFg2ZJOW/va3w8OgZWQ2cCdSGKwEqG1TjoiTeXc6/Qt7SEH4w6Zf58ZCHWx9AEUfqut7f8uC5DrbMzWxZiMKQwCU1NpgTM0aPlBNbVjtZW089RxqRLgc3lTPtHRsyDtqcnnJkZjCtzW5tx6+rvT+dCbLuzJ7kQa5UNshPYixfNA3np0nhFWI83XQNWHuCVJHIS47W3N4gV1rHN0j+VuhDb7pquZB+VENgoBTafN+N2fNycixxf2i+qiSaw0n8QXLPly50ENrMCq7PSpiGwWoFNWwKkUpTaYPAOGLzNuBx/+W9g9DzcDbzVg6595jXdAyPXwlQfzHbC9BIYVob62JgZ8zrLbxYCq+NCXajEhVgncZIYchnXra0BgbUV+Gqg5x6XAiufafd3GdPy246OsDJto1QKkyQhGK4kRC641LuFoMD6PuzbF3xWCwJbrQIr/7sIbBSx0/WtL10yL9t2iTqv+Y6BTUNg0+ZUcHlf6PmtVAq2cZW4KhTShb3oxFylkrmX9L0m3zfqwM4L0mYh3g389Nz2zwHnPc97yPf936xj2xpoIBku169KFFgIHux6n6Ky2Q+BpUvjDY8oAtvbG37IuKDbr+sXutoq0IpXvevA2sfQLsTyue0+HHXcrC7EWbB5c0Bgk2Jg5ZpHPcQ00fQ8Q15LpSCj7MiIGSO2C3E+b1ydn30W9uwxD9b29uDcXGPVHn9ZFVhX+Z442KpwVHs0+dM1YOVcqyGwHR2mXy9eNNmjIZxdulICK4QxjsDaLsRRmS91OZKoGFg55vi46QfpEyGD8rsolVMM0+XL4cCB4Hd2DKwcK4k06OPabu3zrcBGIgczS+AMcB44DBy7AT7QDl0vGnV26aPhn/wuMABcBJZ8A1r64NenoAdoG4R9wNJDJnHUFmDdJLS/AoVRUyP3jiKsAiaBfBO0HTW1cfPjkB+bS0g1AN4s3D4DpzL2h54H7DhsXS+4lsQsSoG1Caxujx2z19lpnk9jY+77YGAg+I3vhwmsroMZ10ab/MQtlMxHEqfZWeMWLao+mHamJbC1iIF1LQDEKbBRY1EvLoBRYdMS2Pl2IU6zj7QE1u4PF0kV2Ocp1zoNgZU2ay8hsQ1KpeC4DQV2XpDW0l/i+/6w53kfBf6n7/v/yfO8F+rZsAYaSAWXAlstgdX7zOWMcW27wyYpsFFp7tMQWG1YJpWeEWgCm6TA5vMBAasUUS7EkunUReCTFFhxL6sVgd22zZQH0EpeVDvEqIsie7ZSWiiY9grJsl3d9H6uu84Q2BfmpkxNFF0KrCawWjlLS2B1+Z7x8fQE1rXooNtj12uFsHFUSSZinWSoudkYkdKXkoUY3IrQgQPw8svwzneW3yfSV0LWXO58LmMDzHV13dtagdUkwF68kXGrDVethOq/tvGuCaz+Xiuwk5PBNc2iwMo8sFAUWBvasBzKwYWfggtvg7ZjJna2MGJe+UEoDMBSzIuT5nWT/HgS1gA8Zv59J8CBudcc7tMHHge+EN2uezGq8MDD0HwKzrdAfgP4a0yJINu9GcpdiDX0YkK9CKxeYNExsOAmsPJbWXCZnAzCLzS0+/DERHB/ytzt+o3dRmmPPIOiCJ5206y3Aqvdh8Gcf9ziUD0U2CgXYlcMbNS96SKwN9zgbldUe9O0dSG7EEP5tXPN+4LJyfRx6NJHmsB6XhCuJIn5GgR2XpDW0i94nrcaeAD4P+rYngYayAaXAluNC3FLS/nvly0rN0KSCKwkdLHVqLj6bYJcLpgQowisfWy9X/1doeBeEW9qyuYSF3d8rcCC6SsXGbKJs7i6Sfzx5CT86EeBEVSta92aNfCLv2iulR3DKv0rEHflNC7Esg8oT5hkuxCDyeQrbqUQXmxIk8RJjp0mC7FACOzQUPkKvA3brdmGi9DY7sPgTmqVBE1g7fuuszO4Ri4j8MEHjUG9YUPYSBOXwFwunQuxbexEZVF2uRDbdWDB3V+2AuvaZnbWtE/HIruyEJ87l92FeEErsHPQ4/uycZuD4mbzEhw7Bn/1eegDeoF7boSNy+BrP4Cpdti4DvxDcNdKaBqH0RHo7oT2FcYFebYVzp6Ai2egBVjSBuuWg1+A2XaYbTPEdHopeNMw+WNYex6WjQIvQDfAk3PtbDKJqsa2QHETTK4A8m4FVrAQCaz8lUUoIXD2/KQTOGlyoReD4gjsxETQnvZ2d3kugbhp6v3XGlIOR9yH+/rMItrkZPz4t0vvuJTnemUh1gnB7HOxCazLG6ZaAiuLEGlrtEahVgqs77tdiDWSCGya85DYWiivQV8oBATWteDQQF2QlsD+DvBd4Ce+7z/ped4W4OX6NauBBlKi1gqsixCvW1f+WZILMRhCoB8gra3RNVxtyIQYdQxbJdZEwlZHXaiWwNrH0OSjrc1NYCXLqTaq5Vpdf71JdvSTn5j/q1VfBVKc3SZHkrBLt1k+d8H+vU1gbaXAjmO+9lpzfhBWYJNciNva3IkhHnvMuPO9611uArt2rck0+8orsFFlgnUhLYG1XYgh7OYblYE3DjreWZ93Lmc+k3O2jcDZ2cCT4eDBMIHV8YdyfcTITEriBNH3hcuFeHo6MGZtF01tNNkKrCuuWHseyILK+HhgGHkeU93dhkToxSBJIOaCi8DKPBRFYK+UAquvQ5wxffEilDDuxueBFZ1QuAqe+gEsa4f2pUZ8nbrBLLQ8/ji8445wua2nHofvzJXZ2rkFfvZno4/3xDg8+G14+3boHIRCP2xtgS3NRhHueMW8AEp5mFoO7xszKm/307CvF/YCs5g50M4EXCskEVgZn7rEjhxffivPEXFptfMQuBI46d9LZu8oDA8H94sQ2CiiqL0u6kUCSiU4e9bMpR0dcPXVQajHxERyOAEEJNi+B+tdRsfGyEi0ipv0mes4cW0F03eVigXy+ySkUWAl67D9mUaSC3Ea6PbaGcV1rga7fxsEtm5Im8Tpy8CX1f+HgQ/Wq1ENNJAatYyBbWlJT2BXrEhetVu2DF59Nfi/tzf9iqUQzDQuxEuWhBVCO8FS1P6rga3A6uNHKbDSNldimfe8B3buhO9/3xCvNEq1DVtV1XAllHIR2CwuxBBNYO397NwZEFhNFF0GQFdXoEoXCmEFVgyqhx4y/bhrV7m6B0Gt0f374a1vjR93oqbabvKCJLKl2w2VK7BaKZaYWN2/2pgcGAgMildeCZM4vYggBFsMRG3oxCmwLrhciOMULheBjVNgtVEkxEFnhO3oCMaCXgxyKWUCVxkdMH0d5UIsZbrEVbAaIzUL0taBlVhFiT8fGwvHIesMzWmSOCXVmWxpgQlg/wwcuWDIc1cz/OZvQn4E2g9Dx2FTGqh5AFrPwlr58QjcNQJXAV8HZppMYqrt08ZzeTql8ZwGeu5x1YG1XdxdCqzcg1EutEkENslYHx4OK7AQvVDiUng1qlUAwbRl/37zfseOcMbp2dnoJFv2+HTdg1kJ7OxseB6TPo0qo2PDVl91G5I+k/2mgXZtrmZuqJUC61oAyarA2gTYBd1v0i555sk1KxbdCw4adqWLBipG2iRO64A/Ad6MSYvwCPBJ3/cdhS4baGAecaUU2DRKqk3ispAyOYc0BNYmHja5dKFaAqsf6pJ9VbB0afQErY+rFVgwrrYf/SgcORJNgOPQ0RGt/rkUWI0kAmsbSrI/HQPr+24XYjBurr29ZruVK4PPXWO1vR0+8IGgjZKJWmLMcrngof3yy4Hxrsfuxo3m/4sXjVIZpa5KJtR8Plp9lvIbYvAWCm4CK30xOpreuBHDwiawsi/JEDszE45N1Yb09LRJ1rVtm/lfE01trEfFSaVVYGW/QvLkmvh+4JYO8S7EdgysbpOO/RWvBilxBOX1jltazO8nJ6PvN5cCC9EEVpLGtbUZQ2t83F1nudbQ7nkQb9wODJi/GzfC3r2mjVEENmpBSfdXEoGVuVYvRo6MzLWxC0ZuMC8AbxJa+uEnD8FLr8I7b4HrXoJVY/BvAKaAf4R/jXnNfgm8vEkW5XvGdXmwBfpbYOkdUFxvyg+lgZ575Jx0aQ9bgXURWHmWRGUV1sRJv5+dNfdCnJrl+2axTNoj92alCuzevcZzpxqUSgEZWbMmaL+Mp4mJdATW1T6dsTYJWgkvFMJxlGmzELsIbFy7bKR1C46Kzc2K2Vnz/PrhD+GDH3Q/o6amokM6BK7xY593LQisPl+bwMrcPzERr8BOTJjfNghsTZDW0v+fwN8CPzf3/y/MffZT9WhUAw2kRq1jYF37026SWWBPyFEKlwtiXKaJgY2rtzpfCqx+6K1dG/0Q1G2zCSyY34nbb1Z0dqYnsPYCRFwMbD5ffj4uBVbIjMQwa+Ry8JGPmIeZPrZrrObzJvGThijyuq4jGPVR2my7lW/fDs89ZxSGKAKrXXijrpnUyB0fNw/gzk43gc3ng7jvixejsxpraAVWj2N9z+mEVDLuxFiTciQHDgQEViuwcl1nZ8uVENt9UpBGgc3nw274du1eCBtWWRVYzzNtHxkJyLo9DyVlIvb9aAK7ZIl7DpBxvWKFWRQ4edIoU/WGbQzHGcfiOr5+vSExo6PBdZBazpBegU0yJqOMZ8k8ruG3mLq1h1vgCHB+A/xwNQz/M1wHtLbApi0weBy6xqC3hJF0MbmgWi6Y7MirAA6Dn4OZTvCbTLztTLfJ2Dy5EENnWwAAIABJREFUHIZvNJ8L9LlqBdZ2cZd7VlyI9eKBLLK6CKztgm+TqKRSOlIvuxICq71PBHv3mpjVNWuij5kEUVkh/CyS8ygWg9AI+3cacURR5u2k5Fbyt709IJN6P/pY4+Pl/eFKDpmFwMp3SbZBlDKcFaWSmbfPnYt/Ro2OxhNY13ydRYFNW9e2Fgrs4GBtEmA1AEDK1Fss933/f/q+PzP3+jyQslJ9Aw3UEfOhwFYKW0WsJYGNU2BzueTf11KBta+BS7GO+l0tSvoI4uJm7TFhG55xMbCuDIWuGNgo9VXQ1RVW4aUcT1Jb9Wd2BsrTpwOXSvs6CPEQFzkXdBmbONiEKypT9KZN5u/hw+79DA7CoUPlx5cYWOl/TdZ0PKhASN0b32j+HjoUGHyawOqSJS6DW28v1yLKoNauwvl8dGmmNAqsK1GS3ady3lEENikTsbhMa8ItiFJg5ZzkOh454t53reFKVONCqRQosBs2mL/ahVjUccjmQhyXhVRf2+bmwINCXO9dCI3BdvgB8CngS6vhzAPw5e3w68A/vAte/t/h0P859/cj8MfAN4GR5YAPTcPQfNG4Jncegp4nYeW/wKY/ha4XzDZyvtLGOBdiqXnt+2ZcSt/l8+EsxK66pFqpst1YteLtgiwu2gQ2avzq+7VUKo+ZnJiAhx+OPl4aiNsuhGuBagU26ncaSUQxToXVCwiuWqUuQlQqle+zWgU26Tt7n7VQYGUfuoSRjSQ3YlffxhFY+xwnJ9PlA3EpsLK4oQms3ef6eIODjZjYGiKtpX/B87xfAP5u7v8PYyqwNdDAlUWt68DW0rWjo8O0TybP+XIhBmPExGWErKUCa5O+qJVUaZfApcBWgzil3FY67T6LcyF2qaS2Ajs66k7gFIeoDNGu48k+Z2bKH9jyMLUJ7JYt5nzOnjUPTtc4SVuyKC2B3bLFlAt69VW47bby/Xz960bZ+5VfMQsdmsCCaePZs24Cqw1mMdZuuMFkEB0ZgTNnjBqjFRVJmDM9XW4I2QRWFPw0LsQ2IdTjxu4rWwl1bQPlibFkm0oVWJs0V0Jgjx5177vWsI3KKON4aCiovyzjudoY2PZ2s78oQqrvq2uvNePl3Ll0BFbGoL0v+WyiFLgI+3k40wRPYF4d7zfZkfNFkw05N2nIbOESdL9gCO3qr0Lfj2FkB/QNwjXAteeh7zHYDMxMQ2kGbgD6/y/43ihMnIX/4sNp4OyfQdc98AagKQe9c/G7hWL5fWD/by8ISThCFKS/5NrKeE6jwMr+9dw4OWkyUvf3p/P2cEETWO1JpBXYqN/ZbbOhP4tzxdfbucIaoo41Ohq2V9IS2LhrND2dvIgf5dqcFRISA/GlBZMSOenM2IK4JE4uF+I056LrH8uzRMawdiGOU2AvXartov3rHGmtx18G/hT4I8xy36PAR+rVqAYaSA2XAltrF+JK4XlGhT1xwvxfiQIbFZMZ50Is34+NzY8CaxPYuBga29CvJYGNI2G1JrDymbjeTkwED8m05X+ixmkcgY2rAWiP3UIBrrrK1Dg8cCCchVWgXYjjoN1idX1Gm1SJ+/fRo+Vuc6USnDpl3p865SawPT3lBNauqzozY1bs5f7avt0kyDp4MExghbxK34kCJLGrtgtxV1c8gdUKbC6XXoHV6qAofS4Ca/eprcDaBnCSAmuT5iwEdu1a8/78edOurFnB+/vh6afhLW9Jly8gLYEVpaavL1hI0IsTaV2IdZva2oySEkVI9bXdtcvE7UF8tu2oMjr2tbCNaVGXpf1+M8yotk/OZYe6dKshsct+ZNTZvkfgciLlfeb1/wCXjsJMCZYBw98L9rNu7jX85/D0n8O/B5gG/hD+K8AFOPhumPxpWH0f9L0JJqw+dHk0pCGwoqQmEVgXQdbXTX73yCMmZ0Al0PNAoRCM/6wKrGsRSY/puEROLgKr9xflnWDHI7uOsVgU2AsXouNvkxTY06ej2yhIciFOo4pK3whJbW4O5oY4BdZ2IU4qa9dAaqRyIfZ9/7jv+z/t+/5y3/dX+L7/M0CFM0YDDdQQtVZga0lgIXAjlvjAtKjGhRgCg20+FNi0pYHs49bahbgaBTYuBjbOhVhnyr10yfzNosCm/dzlQmzHfrncn5PciG0CGQVNuKamAnJqn2tXl3GxnJkJFm4EAwPBw/zcuSAxUy4XtP2mm4z6t3178DvbhfjiRWPsLF1qji/bHjxo/mpFpbk5aKPt9uVSYKH2CqythLq2gXJVW7aR9kQpsGkJrB5XfX1uY1G2KRQCF91KVNgHH4QnnjCvNKiEwOp7T4hflAJrj1NJVAWB+3pcybJly8z9tmlTMH7SuhDr+VGuWRoCG2tU50wM7OFPwolfhMFb4HwLvAIcWwe8BQaAnllY5kM/sOE/wNsfhmWfhd/rhM8C3juh963wLLCvCQo7jTJbBGZOwyufhYfvh6+th93bYeNnYNOfwJY/hN85C58Hvoghy5segUsPQSni2tkuxJUQWA0Z9y++mC3zuYbtQmwvClWjwFZCYLUL8cCAuY/kuWJvrwlslIKpVU7dlqj2pCGwtYyBlX1MTUUrrXH3GQSLohpZsxCnqXktbbXjXyGwB1xqrk1gGy7ENUPaGFgXfrNmrWiggUrR0hKdIbaSfdWawIo7bU9PfJyVjbQuxFG1ZeVBXC8FVupQ6rakQVYX4rR9ls/HtyOtAusigXEuxBAY0ZItNm3fVqLAahfitWsDt/SWFndfbdtm7o+TJ93GSVoXYl1KR//GRYJEhdVZW8Eoq4L+/jB5lv1s2wa/9Evhusa2C7EoknJvibtrf39YUbEVWDGQbAKrFVhIT2CjFFjdVy73Yb395GSgSNkuxPaiQpQCW4kLcRRZs7OCQ/Y4WN8PSK89BqJgJ9KJMqTFUO/rM3/TEljX+d50k6n72dNjjhs19+dy8Gu/Br/8y2acytiMU2BdJZcguwKbiDwUt8D5d8FnNsF/Al64Ezo+Cb8BfGop/G7BWGvb/h2suBPad8LZNngYmHgANv93+APgL/tg/Z/DbwG/moNln4br/29YcS8098LMJZNhuXlgrv4t0ISxIjcDG/fBqU/CN6+Gg/8NpiziMTRkxoatwEoCPBt2/+oxoRNK+b6Z3yrBQoiBjXIhfuwx+PGPzcu1vSZ8LvfhqLb99m/Df/tv7nnuSimwEE3CX3wxul3Dw+7Fi3rEwMrv7IVQCOatpCzEg4PVu143cBnVENgqC3A10EANIBlSBVFxhWlQTwU2i/swpFdge3rc52u7tkTtv1JIllTIFjeclcCmdV3UyXpsSBkajc7O4NhaAczqQqzbKCvlaV2Io849jjBrBbatzbgIQzR5b2kxxr7vh0vPCCpJ4pREerduNX+TCGxa92VbgZXzkLi3QsG0RVybNRmqpQKrk+HEKbD5vPlfjGyXApvLlSdyilJgBVmTOMW5EEfBRWCzKrDnzgXHPnEinbohRp3ch1HGsRA8IbDSJ7J4lIXAvu1t8OEPB0nv4uZ+zwvuSyGwaRVYPVZqTmAVZHt5jvnAkRwc8M17fWw5vlbjmpqCGtQzJZjeANf/R3j7g/DBi7DjB3Ds43Dk12Hvx+FjwMdb4Pe2w+8CB3dAfjWMHoanPwn/2AvfvBYe/VeG0I48A96IIbt35WDlq9CFufZ2vOvsrDsGVr/XpNflRpoGpVJ4scGOK58PBVZfZz0nyX1tEzSXAhtHYG3CdPy42bcea/a+o6D7q5YKLEQT2LExQ2JdiLruWbMQV6vAagIbpcD6vrERGgpszVANgY0tnOR53uc8z+v3PG9vxPf3ep435Hnec3Ov/1hFWxp4PSOpLElatLTUvj6XqERZEjhBsgIrD9ooYlxvBRbg/e+Hn/mZbHUis2YhTlvCKI7AusaE5wV919oaLAKkdSF2KbC1ciFOGwOrCWwcAV21yvx1JbtISyJdCmzUtdmwwZzb2bNhI0sff3o6UE2Sjm3HwIqxppOFyRgcGYlWYG3Do14KLIQJv0uBtbeRMj9xC0NZkzhVS2DXrDG/uXgxm4vmsWPBe9+PzkitIX0rbU3jQgzhkjAQJrDFojGSXWWtbOiSS0nISmAh7DGjP7eNWSHikJ3Ayr7a2oKx5cpCLLWVIUxgpe9kO31+ngd+L0yuguk+GPRgHGjtglwrvAQ8fzUs+wLc9RWj2uYKMLwfjn7RENqW/wJX/5FxN/7VEqz/Onwa+MDz8OLvwMDT4CtvBLs2p8vVVlApgbXL6OhFIe094frdiRPBcWsVA6tdiHXMpWv7KAL7zDPw/PPu/etjuFx2k9TBtLWa0yCtAguwZ4+7VqvLfRjC18O+jq7+qESB1fOxdiGOUmCldnSDwNYMsQTW87wRz/OGHa8RIKn41ueBdyZs87Dv+zfOvX4nQ7sbaCCAXjmvJimQ59U+wH7JEtOmWiuwknAiar9JCmwtkidt22aywGZZNMiqwKYlxy0t2QghBH2nDde0LsQuBVa7EKdRYaPa5ToP7UIsD+O2NuOu+453wH33hbfTkLIfWgEVZFVgJyaSSW9TE2zcaN5r8iLHF68EcU1Nq8BevGgMAFuBhXQENsqFWLZPS2DFXTvOJVeTU1lwsAmsVmC1O7UsmOh+cd0rSTGw9nHTEFi9TT4fXMcsKqwQWCGZr7yS/Js0CqzO/ikk0h47OomTTp6V5JUT50Jso73d9M3ERDTJtAmsXT7JRWCnpsILBXrfZ8/CZz4T784t27e3B8eRzzwv/EyR98ViWIHVZYhsF15XyafOzmBfU1NGuV1/v1Ftf24Y7nsCbv40bP4ITK6E2SY4ATydh4mrYBZYPQZH/wC+8yb46hr40X3wzCeh91Hofg46DkJzP0w56ioLzpxxE5wk2C7E+r6OS5g3OQlf/CL8zd8E29qoNolTEoHVBFTI38wMfPOb8I1vlJcVg7DrdSUEVo/JWhPYuFI6/f3uhbCohQu7DJE+L5cLcT1jYEVpFvug4UJcM8QSWN/3u3zf73a8unzfj7U8fd//MSaNQAMN1Be2C3E1qGVWXDAPxL6+yglsHBFqbb2yCqwgS2yvnexGu+a5UAsFNuqaSt9pw7USBdZ2Y0xyR0xql90fWu2zFVjPM9mFJeGOiwymUWBr6UIM5XGwo6NBQXpJuiSkKKmvVq0yfXzxojHOBgeD+0og12BkpDwpi31NxfAQIydrEidxIc6qwNrnqbcRtUuPd729ayEnKQbWPm5WBRayx8H6fkBg3/IW8/eVV5LJRRoCK4qqJvP2GJSFLE1Y0ywmZVFgPS9YBHHFwWrXSLmXZXu5vi4Cq9VXCF/XgweNEf/gg9Htku3b2oJzkc90zgLbhVjuZ7lX5BrY56bvCx2vrcehPp98K/TdDFf9r7DzU3DsV+H534D/DfjLThj9dfg48NXN0P0z0LYWJs7B2e/BmS/A8u/Dqn+GtV+CTZ+BZ94I378Lnv53cOJL0HSRy46A4+PJyX5csMvoSD/I+UYRG1koGx+PVtXqocDqmrFy3SYmgmslWeJ1m/T+5XuojMDGlffJirQuxII9e8L/+346F2J7EcK+VqdOpVsAsRVYlwuxS4GVY4qHVkOBrRlqbK1nxu2e5z2PyXv3733ff+kKt6eBxYhaKbD1wvLltXchBmNoJBHYesXAamRRYKNqIkY9DNMqsDrWMW370hLYtAqsznja2ppsUKVN4qTLDekkTi7i19FRflytwNqlCiopo5PkQgxGnf/+943hPT0dqK8rVwaEWs4j6djNzfChD8HnPw/PPWc+6+sL95MmFNog1e6S9rZTU2bciZuptCNtDKzebyUKrN5GjLfVq4Pvdb+4+rreLsQQEFg7o3QUzp8Pal5ee60ZjyMj5vO4Wp1i1ElbXYa0y3XP5VbteeZ6aAU2CboGaBosWWII59BQ4FEgcNUVve8+0x9r1wbfQdiYtWMSXcTmxAkzVuxjQliBlbEjbYkisHqBxXYhtgmOi8B2dAT9G1cH1q4BWyiYaz0JHOiA1k/Ae94GIy/D8EHY+wN49XFTAzc/Ds0XoOkSnH/EvMDE0s62wMQamFwD+3th1/3Qvj79tbQVWOkHqS0cpcBq910XadFEE7IrsJrA6n7X+5Q2aOI3YanUUg/e1W4XgU0iV7UksLrvwYyR6enoeeqVV8wirDzPBgejr4+eE21lV4hzPm/+/umfmve///vxiSDTJHGKqik7MxMsUDUIbM1wJa39Z4CNvu+Pep73buBrwFWuDT3P+zfAvwFYuXIlu3fvnrdGVoLR0dEF38bXFJqbA1WnUICF1vetraYW5759QMrxMTZmzuno0ehVxtWrjdrhysBYLJrfDw+7+0O+rwWam9P3+eRkcNzHHjN/N292Z6GE9O1sbYW9e93b5vPu9k1MmO3b2sLf2/twnd/U1OXtlhaL7FJfHVu1iiMrViS7o7e0lO13dHSU3Z4XbkOhwJaVK9kAvNrTw+rZWdqBJ3bsYFwMYr1Pm/T7Pnd0d9M8PMxjfX1MzMWO5iYnuXt6mlI+z4937Yo1+to7O7kFGJ+dZTSXYwWwb9s2+qOuzfbtvPG736X78GH2DwzQPDvLVuDkjh2cvvVWbvmnf7q86cubN3Mq6Rpv387KpiZ2fPazAPRv3co+9ZvVJ0+y/aGHOJPPU2ptZS3w8tq1nDp4kK0rV7Je7eqx66/nlnye3OwsP1m7ljcD062tPL5zJ3cCM9PTPOJoz62eRxvweHMzxZMn2bpixeX97tu0KdQXV69ezZp9+zjU3U3npUusAQ5t2sRptc1Vq1ax9qWXONTdTc/p06wADt58M2fmtimMjnLn3LZn167lwPbtjLa0sHvu+57paW4EBvN5nne09/p8nj7gxa1bubh9u7k/osopCaanQ2Mvt3Ejd//FX1AaHOThbdvw5xYNVjz6KCsfeYTzt95K/+23U5ojMWuOH+dq4Nz117P/mmu45qabWPXjH/Pq0BAn7ror8rCrTp/mGuDM8uWs3r8fSiV2X311aEz2Tk5yAzC4cuXl85XPBA9fdx2zbW3c3t5Oy5zhP9LVxdNJ40uM0pRz4jXr17Pq6FEOtLVx1vpN09AQbwam2tp4VL6ztukqFLgJGM7neWbuu/Uvv8xWYKa1lcLEBGfa2jg4993VDz98OWbr+PHjHH7zm8vadNfMDHngx+vWUTp0iHvVd9NNTfxE5pqpKbb39bEaODg9zfTBg1wHXPA89r7wArt6e1l68iQvzM4yoOcnmS+BLU89xQbg8ObNlPJ5tgEnOjp4FWLn2tZz57gNKBYKHD51ip3A+bY2XhodhYcekt6BqbfB0tvC/doFXYUTdE0foGtiP13TB2jJX4KOI+Z15Cdw5N8ylethpGk7I03XcKH1dkabro6c27yREe7xfTMHzpUcu6m7m66BAZ5evZqR5cud59N+/jy3zL1/bN06JiYnw9v5fviaRz2DwJBb2db3zXajo7yxUKAbOFMqcVB+WyqF97t7d+gZ2ZXPc9PcV0+sWWOeDwcPwtGjjI6OsueHP0Sqgfd7XmgOBYytYZft0dDzw/Hj8cmjkjA+zq25HG1AqamJ3PQ0T3Z1MSZhCy48/HCweBNnG+RyQX8PDpZv9+Mfg+eRHx/nrjkS/PAPfsBs3KLs3HW6rVikFXjshhsuP0s3P/ccG4Ej09McE9tN4/HHzRyzfbshswvNRmVx8pYrRmB93x9W7//F87xPe563zPf9Mj8C3/f/DPgzgDe96U3+vffeO38NrQC7d+9mobfxNYUf/ACefda8X7MGfu7nrmx7bBw7FsSSkXJ8PPUUPPkkfPSjsG6de5u//mu45x63yvrkk+b1vveZchE29u0zk2otsHkzfPCD6bY9cgS+8AVDOD/8YfPZpz4V/dD80Ifg7/8+eb833QQ33wx/9Efl361YAQ88UP75uXMmruz220Ffj//6X8Mr5lu2lJ/f7t3w9NPmveX6t3FkhI0zM0Fd0ijs2BE+LnNjo7XVXDvBhg2XDeytp09fVjNuOXeufBV91y73cZctg+Fhbnv0UbjmGvPZXJ/n2tu599Ch+LbOHad9aIj2OTX12uFhro07x+uug8OH2fHNb14m8+taWlg3MhKsfgNXjY5yVVJfgVl5v/122LOHFUuXskL/Zu56rT558rIqd9XQEFft2lWWgOi206cvq/5vnkt20pTPc+fx4wAUikXuPXCg3OidM3Ruldhjtd9rBwbCfTFHnq4+evRyzO7VQ0Nc7drm2LHLi1vbm5rYLtuIWu77rCqVWHXwILu3b+de+X5uv72Dg8FnGnPKzPUDA2ZMvPe9yR4NZ87A//gf4c+6u8kND3PP448Hbtv/8A/Q30/fc89xzRe/aK7LHXdcnlNWLl3KyoMHLyfa2rpnD1uvcq5PG8wtwq0eH788Nu7dty88t82R795cLjhf696769gx02fK7b+rVHL3j8Z73mMWqr761fjtLFxz8CDX2PWY5+6rZs+LPu7cteseGQm2mftbWL4cTpxg9fnzrLauNcCGBx9kw403hkMbSqXLqtPdxaKZC3O5ywuDTZ4XPHPOnLmsxG0fGYGdOwFY1tnJvXfccVlB2tXfH56f/v7vg7llTpHfUixe3n79uXOsHx+H++8vP99HHzULlnNjsq2piZ3XXQfA8kuXuHdoyCQEFPzjP5bPY+98J9w298x45hn4+tchPwKtp6D1NCy9BC2naJ4aoG/ycfomH2fT6Beg6yrY8ACsfR8sfRPklOfGnFtqLp8PrsOcK+lNhw6Z/nvggfK5QC0E3bZ/v1HWdV8Vi0bRE7S1uZ9B0jdSL3nrVtN/P/rR5Tl39dgYq2XfQ0PhZ9wHPmDImLRdxZvfcuCA2ccDD8C117J7925ulwzxwIozZ8Jz6OU+Di8chHDkCPzkJ+b9+98Pb3hD9LZJeOKJy4pxrq8Pzp7l5qefTo5Hffvb4c474bvfjX7GtrQY2+HSJfjjPy53D37f+8xzQoVG3LVypblvorBnj5nf5uac2/r7A6+JuWfy5okJNudy5e1629tM+Mvx4+a5uAD5wWLkLdVkIa4Knuet8jwzK3ied8tcW2KiuBtoIAK1jIGtB9avT97GRlISJzDGYdT51ruMjkYlSZz0NYtrS72yEIPbhVi3Me73ehu7jeJCnIRKXIh1DKzrGFFxqeK2qxM5pU3gJG0Ac2ztPhiHnTvNdTl5El5+OWhHLhd2J82S+fsd74Df+A1405vCn7uSOLnK3UA40Y+cy//P3ptHWXLUZ6Jf3rWqblV1VVd1Ve97q1sL2gUINVILLCEkjAxINgw22GbGwxifZ8PjjPXmeWYeZ7CN5wweG3vM2EfD2BgMZrc8ZjEY2sJIQisCbd201N3qfVV37VW3bt33R9Sv45e/GxEZmTdvbZ3fOXWq6t7MyNgyM774fkuxqOrl8ivlJsRJgjjZfGBPnFCWEm1tYdPQINDHmO4DXx9Ymic+z0bTMVQnMsWr1bTZ4sqVah790z8Bn/609mumDbvNm1U7Dh50R9XlZpw0/6WJosyTC4TnIM8JzsfD14Q4Tgo1Vy5YGcDJdj1+LKAXw3Sv2qLujow0pqiaPbZGz0Fp4s6fKdyEmAcQo3PlvWGrA9CcCTH1d63W2I+ufqV6A0CtCxjdAZx5A3DkF4G3nwLe+hJw098C2z4AtA0qs+Rnfxf4x9cCXx0EHvpF4MDfABOnVTkBgO48UD4CdP0YuG4S6JxtrzRzJfANTpMJsTyH+5662mUK4sT7XV5ndDSsgvJjqY/imBDPlw8smQVH+cECyg/85El7BGJA1bNeVyTZ1O/UDj7PTDEiOCi1U70eficD7ijEdD3apM+COKWGlq32gyD4HIBdAPqDIDgMlWK7CAD1ev1/ArgHwL8LgmAawDiAd9brScLIZbjowRcezaTRaRXiBDki+BBY7i8nsdCDOPn6LVPAlqiHfpIoxKWSWoAlIbCcPEoiVyqlG8SJpxuiFyilcpGwkUFaIPCXtK//K9WpWAy/iKMIbKmkFOHHHlMv9lxOp74ZHFRKkO/1OUx+35zAErkolcxEkxNVHsAGUPOI8gLKwExJ0uhMTESn0SHVZO3aRqWno0P7lEr4RiFuJogToFTXl15Si8tLLlFEdmZGjcOv/Zqq/wMP6OBNlYpWajs61JifPKkW2tLkneBDYE3BU2wRxJMQ2Djz0BXEqVkCS/cqJ/w0xlu2KPL61FM6hRY7ttbWhjxF0y0UdBl8XCWB5T6w+byep9Jv0xbEicZJBnHikASWbxhMT6ux5f75UQTWNOfHxtR5PZuAzk3Ahp8Hrvsj4ORu4NDXgKNfB0b3Awc+q34AAAHwGUAtQe9XH70DwNsAnPkOkH8ZeKYA9G5WqYE6ZtV2TgSnphrrI99X9bo6zhTlPo4PrOzfkZEwgeXqJZ1n88Vt1ge2WSLGoxDTnHdFIubnffWrbrI7M6Oef08+af6e2sHjRZii9HPQPAXC/q9AeIPZ1C/j43pOZz6wqaFlBLZer78r4vs/BfCnrbp+hosICz2IUxJQO1yLLx8Cu9AUWJkXEXCPGamZppctRxIFFlCLcEk25SLDRND5MbToo8VDswqs7I/2dt02egnaCLJtEd6sAkvX5C9onwX/dddpc+j+ft22pAqsDZWKWvyOjYUJo1RgZUAjWojS/+WyWqSYFsjU7vb2ZEGc5JjJVCcmS43ubrVQM/lTxwniFBXtm+BSYGnByNMYBYEiUu9/P/B3f6eU9q1bw0R8YECdc/KkncDyXJxxFNh8XvXr+HjzBDaJAmsK1JaEwE5Pq3s7CPS9wceV/r7hBrWZsGePmusi2nCNSKhLgS2VwkFn5AYL9QMnaYA9jQ49R1wKLD23ZBAnajuRwLa2cLokDk4MbGamR4+G75VcAVj5M+qnXgeG9yoie/TrwMkHgZkpYAbAFAAMqhy3Zw4Da4eAFWcAPAw8z6Lf9t84+/MN4CNQuXDxDDC5PUzATSTGtCn2O1HiAAAgAElEQVQGREch5t/L/j1/Pux+I4M4yXMk8Z6aCt8fi0GBBfTmpwuPPWafJ9ROvlES5c9bq5k30QB9P9k2cXi7MgKbGpbIaj/DRY2FbkKcBD4KLE8jIsGT1rvKT4KurvACo5UmxMWiaosPgaVFunyxuuZEb28jgYqrwAKKQMUlsL4KLDdXon6PS2Apau+5c6qebW3xFFi6Jr3web5SFwYHFTE7dEiTaPo8qs5xEARqXg4Nab9IUkpNBFaaSXIFFmgksPW6DjRmKtcnjY5NgSWYCOwddygTbBPx4ybEMrp0taojbRYK/lF2fUyIicCSmg6o+f+ud6lx5mPLj3MtEHnkXpr/cjFNYyUXj5VKNIEtl+1KNaDaHWcecgJr6ntqiw2cwNbr6r6s1xX5onlhUmBXrFBK/aFDajOK0lUxBfbCJoCPCTGPtEv9R/1AaYvoPqc6zMyEU2nZ0uhwENGne4gr3vS8JjN6Sk0jEaXAAorYXHaZ+bsgALq3q58dHwRmasBn/hp476+oOfv+96vjvv1t4KmHgHe9CrhyELhqA4ATwInvAKcfVj89UD8AgKfVz1f+GOi+DFh2ORCsAdpfAqr9wHQngJx6DtC8sbXLpMDyeSDviYMHwyayvF84GSZIVX1kJJwhYb7ywNKmzenTjfdTUlCQSBNMJsRRBJYrsNKlw5UHFgj5sHsr15OTjfdxhhCynsmw+LGUFVjXIshFIFqpwK5cGSawSUyI4yqwUeCEXb5Y4yqwksBGKbCAWsjRAp9S+kSZPschsL4KrE1NzefVIuHYMWVGvGGDfw5YXo+o65hwyy3K5Gs2aAsATWZdynlcEIGluelSYGmMaUHHFVjAbhJYKJgJgo3ASkXYdAygFmwmkrpiRZgocgSBNuuW5olSffXtYx8FlhZ6Mi1OEOh8xLIN/DwTZP8CdhNiuXisVFTduK8vv4eLRbWBY4vmTsdQX/l4MpXLmhSPj4fJrw+BzeX0Zlutps2Hly/X55kILHdP4N+TDyzNeTIhJkgyazIhpv7jacGq1cZ7gm98Sb9xWz5UOoebEMuUSUNDak6ZzIdZG0N1kXCNsUQuD0wYTKzLZWVRvHcZsO4mYNW7ZqPHjgJHv6HS/Pztd4Av7Ab6Ady5EthwHpg8A5z6vvoBcCFEeT1QJPYnzwGd/w2oiHskisC6FFjyOSeYTIhtCiwQn8CmqcDSxhugXXnI1NZE9OPClmIH0O3gG+NR6i8nsHITLcoPnD/7fBXY0VE1L6W5cprgG1SLEIu35hkyEPjCcCH6wCYBKRFJHy6tUmALhcYchHH6nNoUh8CazK4kXO1tlsD6KLB8UU3kNaqP45gQcxMl+swEl4ok/WCTmBAT4hDYLVuAD3847LPX0aGibZoiliaFXFT4EFhfBVbm0+TlBoF5zACtrJl8lnl/rlzpZ+oqYasvLWTj+L8C5jnZ1aXOHxtTi0JuQuwDOo6rEBJRPrD1uluBBXRf8CBdgPrbZa0CaIXaZ7OMYDMj5ubQUdek4zmBNQXnovGlXK3ye25CbNpg4X/z4GDk7w2YCSxdo1bT7ZLPjSgCywkpNyGm8aLPiBz4EFibaejBg9H5tzmI5JgCslHb6ZhCBVh/D3DF/wscWAvsBfAQgO/sAPbfB9z9MnDrt4Br/xAY+AVgfC0wXQGCOlAcBk5+Efj7S4AnPwwc/ydgZD8wM92osNZqqn2kVhs2Ki5Akq44QZyARsumucwDS+3K58Om867nRFowKbAyD7MENyGWpJKeBTYfWN6mOATWlT84DdjutUWCJSJXZbiosRQVWG7mlQStUmC5QkCIQ7KDQNXNx4S4UPBfVLqiLkeZEEf5wPqaEBNo86FYdO8CJ1Fg+WcmuFQkUj3JfyiuCbErcFUSXHll9DFxIImNKVqwjw8s0EgI+cI7lwsrXKVSo8mbVJdMc5h/liRSOV0baPSDlZGqfe93rgwSgkBtWh07psxWz55Vx8mNLBt6e1WZQ0OqX00bUlEElsgRj5JL8CGw7e06IJYJNJYdHe57lqO7Wy1Mh4bC8Qh8FFj6fmIiTGB7e8NqTr2uVVqac6YAUNyEmAiBjcACel5MTuq5Lgns5KSeVybTVDm3bOoTJ5RcgaXxkv6IJv9XKl/WQYJybN59t/l7CSJ5JmsKuoaJLPM5MjUF1GaA8ipg1Tpg1e1A/qfAv1CgqBpQOg1ceQAY+ibwwsfVDwDkysDMWmBgOTC2ERjdpsrj5bsUWFt7eP35ObJvJYGdSwWW6kf3++Cg2oA4cSK82dkKUDs5oRcpuYzn2BRY8ru23QN8vvqaEI+OJtvUjINz56Lz1S9gZApshsUPnj5hqRBYHwXPhagoxEn7qa+vscy4qreM0htFslupwPb3N74kkpoQ8/ObUWBdUYgJNgJrWuATyER1NofjnCmwcwW5qKBgSy4F1pfASoLFyzXNT1LheV1Mx9BYJyWwUQpsXAIL2CMRAzr/JflU+4CTXZsZsYnA8oUeNx+WmwU+BDafdy/UqH/iBHKiPqEUUQTuz+sCJ35c1SaVn4LcEImkjRKTibFUYCWBNT1T6Dw5V8iahEzTATOBpf7mmyg8MA+BkwQTgeU+sPy3hI8CCwA/+lG0P6Msx0Rgqe1RBNZEdEMkJQ9MDQIr/j/gjseBLe8DVrweaF8DzEwCwYtAz2PA6i8Cm/8b8OivAqXPAb8F4LcBvGEcGDmgikqLwNI9FJfApukDyxVYQFsIzaUCy9tvy0VPsAVxKhTC90ycTQAXWq3A1uvxrBUWIDICm2Hxg6t0S8mEuJndN1KeXCpfkr7q62ssM2450q81ysw5rg+shKt+pgWxjwkxX2gDjQqsD4FNEsSJf2aCS7lftUq17cwZ9SKO6wObtgKbNkwmxEEQJpg2AitNiOWilRMsaUJsu0/5GJnmcBAoUpXLmX1HfWCLRJwkhQ7B5Qf7wgvqt80v14Yo80BO+kw+sDbzYUAp+ZdfDlx9tfqfm9kCekPJ5VdH/RMnkBPlIv7Rj8LKVhwFFlBjR9HByUqCk0IbYXQpsPL6si7UzmrVrsByE2ITMZKbpKQYywU6J78+CqyNwHJi4ArIVa8D3/2u/XuOC+bBhojidA2TIs/7w0TyTSRlYgJYfh3wmvuB2x4E3nYYuOcVYPQ3gVNvACZWA/kp4Mjnga6HgRsAXAng56eBBzYBX78aOPYRoOcRoLJH5a0tDAGwBHFymRCTCexCUGCp702p3tLG6dNhc3i+uRJF5mwKbFdX2OImjhm2C60msBMT7vtoEWCJyFUZLnq0takXTabAalAwIRtMAY+i0N/f+JKL66crTYjTVGBNZSVRiKPOJ2JkUjG5CbELtna70ujwzyRIubERqnxeEaV9+4D9+5NFISYsFgLLf/O/qY/4gpp/Pzmpxvab3wSuuUb3EfeBHRgANm60m7u1t0dHjb73XvXcShqoQy62CVJVi/NcdCmw1B5f/1dCVCCnKBNiWwAnQJnd3nOP/t+kwPoS2DgKbH+/inj73HPAww8Dt9+uPo9LYE+dUuPX2anbVypp82JJYH0UWHl92wZYtdq42UH3ka8Cy4OJ0Q+/5/i5PApxMz6wUQvv559X0bvXrnUfl9SE2ETorQqs4RxCqQeY2AK80gO88nqgeBp4Qw/wLw8DX/qukpiuB7CzAzg3G+1Y3nozRWCqX/3cdg44DOAUgGAUQC1cFyKsy5crwrZQfGAB/Yw4fVrVOe213E9+AnzlKyqy+5vepD7jBNZmuk6YnFTHB0H4/dfZqV12fBTYmRm/4Emjo/p+aQWiFOdFgCWy2s9w0aO9XfkwLBUC26wPLKBexFEBklymWCb09TUmG09CENMmsC6T6bhzwicPLKBTPgDhhXWaJsT5fDhvI8Fmksp/m7BxoyKw+/apl20u59e/8pomIjHf4ASWbyCYCKzsI1MQp4ceUouekRHgjW9Un3MT4kIBeO977fWJUmCBxpQzcWFTYNM2IZb+rmkT2Kg8sKYcsDbYCKzLhJj7wMbBzp2KwD7+uPq7oyN+ECcy6edppuIqsDIKMT/OVBdq5/S0Ll8SWK7AuggsXYsIr48CyzdXZ2YUAfD1gZ2e9vMjfOYZfwJrSoklgziZzuPHRfk52t61oXHsBwbfAxwaAh6dVZEfAfA7zwPBy8AjXwAOP6SU18LI7O9RoO2Y+nkzL/gUUP9dYGYT8OxBVKqDwOisytjbqzYxF4ICy+fr8uXKH/z06fD9kAbI/eHUKd1OrnCOjLhT+NC6p7MzvCbo7NT94sqFzMGje9swOuoXET0pMgKbIcMCAb18lwqB5ZEikyIqV2cSgtzf37hD3iyBbdaEmPtAxzUhttXP53yTSW0QaIUuai76mBCXSo2BiAA3gXWZnm/cqH7v2aPr7ZtzbzEpsMWinvsuE2J+PD92dFT30fHjjSbEPlYHPgS2WRARkYv+pEGcALcCS0hKYKNMiKN8YE0mxBI2AmtTuclnFIj/zF21Cti6VW0IPfoosGtXfAU2isASQTL5nBJkHlh5fRuBrVYbI1bTJkEcAstVYbmAN/lNcj9dIqRjY+p3lALra/bocxzVzWVCbCKepv5IosDS+V/6kurDu+82m3aOzwAbd85GM14e/i43roJEFU8DDz0ArID6GQiA5QByLwFP/wfcACiC+xoA9X3AXQBwEljzGaCeB+oFoLAJOLYZ6H8NUDTcL630gQXUht7Zs8qMOE0CW6/rlEOcZPLNiZkZpUrbNrps1jSdnXpsp6f9VFNfAttKnD+/qFPoABmBzbBUsNR8YIH4akDc8+MS2I4Osz9mEhPiNIM4uZQGoHkCa2sfrxelGiFCmFYaHRuBNREiHhXXBvKDpcVDHCK60AksLd6np8MBklwmxASpwO7bp3e/x8d1lFhuQhwF3l/NbkbZQDkcZQqIpGl0APM9VCwqE9zz51Xbe3vj1bO3V5U7PKzqJudvVB5YXwWW7pU4QZx43yQZp5071Xz54Q+Bm26KH8SJfP6iFFiTzylh9n6eKZfNPrAuAisVWCL63ITY5QPL/zYpUDYFlupFqWOKRaW82YgnletrNSStEkzwMSFutQI7PAw8+6z6+61vVcRFnk/z36TuzbQDE+uAcyuArzygo4jnc8B//PfA6tPAFZOYePlbaKufULlrMaRILmoAXmSFPQd87x+AXBFYczew5VeBlbernLny+mkrsIAisM8/n74f7IkTehz5Josc29On7c8JU8olQD2TiGz6Rhj2OY7MlVuFc+fCOYAXIRY3/c6QgbDUFFigeQIbRTLiElgyI2w2CrEM4hRFYH0UWHlOM/XzSaMj61UsAr/6q8Av/qL6P60gTpJYEZKaEOdywIYN+v84c2yhB3EKAq3QcSXPRGajFFgirzRGhw+Hy83lohcXc6HAEpGUKSDSNiEG9P2/YkX8TauoSMSc9LlMiKMUWCLAcXxged8keeZu2KD6ZGJCqfVRCqyJYALhVDxc0YwbxMm0kSWvRffvNMtDSm0nAsuvzcmZVIT5teKYEPN60fjTfWYCHeOrwPoQWBlICAibENfrrVVgZ2bC1hPT02YCSwTJZZ5K9ahUNImt5oDxK4Ab/wqPDH4e+ORrgA8CePgO4GMl4HcB7HsHcOSdwLG3ASM7gb5XA/UacOhLwO47gb/fCvz0k0BtInx9X7Jmg02BBdKPRLx/f/i6VHdJYF3Rq10Elp71vqTex8x4ZKS1Kuwij0AMZAQ2w1JBkmAlCx0LjcCSGWGzUYilihuV6idKgeXfx80Da4KvCbGs18qVuo+aCeLEr8cDt/DPk5oQA9qMGIhHRDs6dPCqVuenSwoiONyE2OQPG6XAAqq9116r/uYElpfrwkJQYNMksDS345oPE1x+sM0EceJwEVhTMDQ6h5B0nChFlQ+Bpcjn/PtSKaxqu3xgTUGcyAeWK7A+BJarrNT2jg5dBm0c+PjAUp0ksbEFcQIa1fYjR2AFRTluBYHl/UP5dimiskmBNfVHEgW2Wg2TlGpV9XkcBVaWXy6Ho6nzc0YmgJMAJtYCx7qB5wAcWwGMbgeGrwTO3gW86YfA3QeBq34X6NwMjB4AHvt14O82AcUHgOKsL2izCizVy0Rg01ZgyXwYCG+yyDGhaOAmmOYKECawvqQ+isDOzKh518ooxEvABzYjsBmWBjIFthGtIrDyvLhqzLJlYfVqoSmwvibErnqlaUJMx/JFn6lsHwUWCBPYOHOsXAZ+7ueAt7/d/5y5Biew1L/5vMqz2tOjv49SYAFFXikIDCkCnGDFIbCtUmB7etS9NDQUXlCmnUYHUBF3y2WVsiYJXH6wUT6wcRVY+Uwgn0uTeWCzCiygzX+PHYsmsLSBx79fuTL8TOQqqzTZTaLAmoLABYFaKEtzcx5gifxRTSbEvj6wLgWWftNYuwgsHedrQuxDdE0KLBBWYU1Bo+TmgVRq4xBYTlKI0Mrz6X72IbBtbeFo6vwcKqenR28G8UBOdN2OtcDl/wF4y15g5xeA3quBieNA5VvApj8F1t0PzOyz18UHJgW2p0fNpTTVx5kZ4ODB8HWlPzX1l4vAmszNAdWPPCiaD6KOGxtTc4p+twIZgc2QYYFgKfrANqvatMqEuFkFVi5Cm/WBbTWB9TEhlmjGhJgTZqoL94N15YDl59iwcqXus7imwFdeCVxySbxz5hImApvLAe96F/Abv2EOcMP/p4V9EKg8nzKQCJkPU7kuzIUCm8+rDaF6PbwgaYUCu2EDcN99yceflFuTAuuKQkyBhnK56H7kBDafV8eTogaYzYib9YEF9DzxUWBNBFZGo3aZEEel0fFRYDlJlZsdpZI+l5RvXxNikw+sKfCPVGBpQe8y4aTyW21CDET7wcqy+TgBdgIryYivAutjQszvea7A8rKILPf26melJLC8jrk8sP5e4I4ngTd8Bxi+FqiVgPYjQPljwN4/S06wTAQ2CNI3Iz52TI0NjbFJgaWNLZfya4pYDah+TNuEmMa7VvObx3ExNWW2LFhkWEJyVYaLGpkC24g4BPaWW5TiRKl3gkC9mD73OeDF2SAPaSmwMhpoGlGICWmYEPv6wLqItY8Jsa3cINA+TFyBpXbYFtk2ciaRyykVds8ev6iuiwk2E2LqU4LNhLhUUpFAKWjRzIwONENlJTEhbpUCC6jF6LlzyoyY7tG0gzilATJ3ljv/lBcR0CmKAL0Y5AGcovyOiQAXCsDP/7xuN5XZagX25EltCuwisMVi+Hvu/wqkE4XYtbFHqvTUVNj0lL6j431NiJMqsHQefR5FhnjU5CgkNSHm9eP+rfxZyc2ux8fVcbydJoJSr6vzeL9NTfkpsERoxseBT30K2LQJuPVWc1vK5bDCyCPjEmnp6tLrA1MqHdkfQQAMvgE4/lYAdwD93wZ6HwMe/wBw4nvAVb8HdG9rbLMLJhNiQG10HT6syOSmTfHKNIH8XzdvBvbu1blaZ2b0OPb1qc0nF2m2zZVKRT3fac3kk+PVl8ACan74prrzxRJQX4FMgc2wVJD5wDYiisDyvrr0UrVgpwUQLQJ/7ud0Oh5agDarwEoVJEqB5aqMCWkrsDytBhDfhJjSrCRVYIFGFYUT4mYVWAC47TYVPTWpOehCBc0tng/TNP42E2IAuOoqZS4LqHHk6lhSE+K4yl6cTSEiTOQHS7v2QRCO9uqLVj1D6Xkmd/55apUoAhsFHsX4kkv0AtilwEp//CTtL5fV87FW0/ki4xBYqfT7+MCaTIh9FVh+fVOQKKnA+kYhbjaIUxR43too+BBYW85elwJbrap2BIGe05OT0SbEQCP5lgrs1JRZgSWSe+iQ+nnssUaybzMh5vWhdnR3m02IXXWv1dQ160Xg1J3AyC8DhYoK9vQPO4B/eSdw9FvA5Bnz+RI2Apu2Hyz5v5LlCM1RPlfpmqdP28sxKbDkL86fOz5zOeoYSWBtSKp+L4EATkBGYDMsFdACcSmZEM+VAtvWZg/M0tWlQvv39NijZ8btc7kQjSKwgHsHMm0Cyxf+rvNtdfJVQl31kn5scQisj9rW1we88Y3xzcgXOrZvV8rE61/vVkptCqwJnFwkDeIUV4GNY9pNG0sUiZgvZF35kW1oFYGl/pCmlJxEcAJJizxf/1cqw2WFEaXA8nrGBamo1DZfE+JcTvsHE1wENi0FVn7Gy6fvaCEdJ4gTJ7Ay6JLNBzaO6WUcAhu1wPfxgQXCxJP6pFgMHxdlQizLAcw+sKZAWHQMV2Kljyi3uuAmxFQuH4uurvgEVm4IjF8N3PljYMv7gCAPvPy3wO47gC/3q4BPT3wIeOXH5rJ4ea0ksLUa8PLL6m8isDSHSJ0GdBA2G4El9RwIzxXqQ5vvvg1xFVgTxsd1Dum4yBTYDBkWEJaiCXGzfnO+eWDXr3crPjt2ALffrv9vNg+sPD7KhBhwE4AoE+Ikmxo+BNZWJxvRl4ijwHI/Ptt14yiwSxWFAnDzzYoQuJRSbgpM59mQlMB2dKjjOzvjz8G0CCxhIRDYXE7dq7aAN0Q+pQLrG4GYl2H6HIj2gQWaNyO2lUuQCuyKFY115j6l0oSYq5ZE0CgKMbc8MCmk/H95TR6hm46XBJaTIB8fWG6+Cui/kyqwcUyIgWgV1qbAShNirsDSfOT95KvASusDE4E1nS8JLNDoL8zT6NDagT6rVhGQcpzPq2PiElhJumo1FaX4NfcDP/sicNlvA/2vA/IdKnLxnv8OfOMq4BvXAi/8MTBxylyefDbS84wCiDWDM2fUdcjnl2/M8ABXlFpORnMn1Gpm33ZOYGVEbRfSUGD3709O8pcIgV1Cq/0MFzWWoglxXGIoEbVopgcxzwtqw44d4XJzubDfWjNotQKb1CSQFipxTYh9FdhWmRAvJVW1oyN5KgEexMmEUkktOotFt28lJybcxDXq/iwWgV/6pWTj4UPWCNKEmPy4uK/5QiCwgBrPyUk1pjL1BAXekgvBpCbE8nMg2oQYaF6BtZXLyy8UlNJUKCirAQmTAkufUQoeIovMR3uGE9M0FVgiZ0SapVuHzQdWqqVzqcBSfVzvDiK4tr4w5Xil90JaCqwM4sR/E4j48mfhyZNhH1Equ1JprHe1ijzfeCiX9fNB5pC2qYMmAkuorAOu/pj6e6YGnH0c2P9p4ODngFeeUj9PfRhY8xZg8y8Dq++0E1javBsd1YQ7Kai/ePR52jTgBJb6UfYFb6uLwPLn1lwpsPv2JV8jLhET4iW02s9wUaNcVi/2pURgW404BFaCAoAAc0NgfRXYNEyIgXRMiKPmYlwTYt8gTvOhwNKCOilMRDUI1AIhKYGNUkqJwEb11+CgDtARR4EFlHVDEsRRYInAvvKKquNPf6r+37JFH7NQCGx7u6onV6JkCh0Z2CcNAktj1dUV3nwDWqfAughssaiU19/+bfNxrijE9D2ps1zV5MHKkhLYYlHfE5TGQ+Y6tZngSwVWKqBJFNgzZ9SY9fbOvQJL59sUWE50k/rA+iiwZHbPiY0MOERj09mpr8MU2LzME9vXp36fP69+aHMnjgJrQi4P9L9G/Vz7ceDI3wMv/RVw7BvA4a+pn3I/8IYJ4GYAHT8Cis8BCJR/7XQX8MECcGQaKD0OFDYA051ArR1AzHe5KcL26Kjqc77Zsm02AJVNmZyejlZgTfmrbWiWwNbrisCaXCJ8kCmwGTIsIARBOHBLhmjQIkYqB77n0su9WaXYx4TYV4FthQlxXAW2FSbEC12BXbECOHo0+fkmosoXiEkQFWxJLqJtKBbVYu/06fgENiniKLDlsiK8o6PK7I6ihm/dqo+JMydaOX+IHPKxjiKwtPD2IZa2gG90r+VySnniC7i0fGArFVX20JBb1ScCy+sl4fKBpe/HxrRvIz/H5GpgirLLP8vlwvcLXWt8PHwNU11kfX0UWOnPa1v0V6vA/fer437rt+IrsFHHmvwaef1cJsSc6JM/JSmGvgR2crIxiBMQtkqoVtX1a7Vwe6QJMZXd2anryxTYHCdzpZIa8w0bVGTe/fuBq68OX1tCbgb4ELV8m0rDs/5eYPwYcOCzwEt/CZx/FrhgDDE9+zOL4jngeqgffDNc3kwJqOeB+ux4BdMAZoDJlcDIdmBsiyLBqAHBDFA+DmwEsA5A4TzQVQBegerz8XHdViKww8Nm1bdWC48JwWRCnHYQJ1M+3FOn1HOG/LyjorNLZApshgwLDGSalcEPxSKwbl2yhTjv54WuwCY1ISa0IohTLud+6UgVJZdT0XFHRvTLVmI+fWCbJbBdXY2KQrncXFuiCGyc/lq9WhFYHuVVllsqpZezL25+3uXL1UJnzx61sKlUworgQlJggcaornRdkwkxHesTCCvKhBhQqoWLwDYTPG/lSk1gbfB5T0URWK7QSlXTpMCaom7L6Msc1NdjY+YIxM0SWGlCbFvQHzumrj8xoeoyPW1XYKtV4DOfUeP7pjepcfRVYKNMiLmfqMkHlgd7qlT8CezQUJgISgW2rU0T2OnpcHtOngyTF05gaYOIEeILJsQ8T+ymTYrAHjgQTWB9FVgb2lcBl34Y2PF/A8N7gX/9K8D3HgaueY0Kuoc6kJsECsPAY98EcAK4cQ2wfBLIjwH5cSBnGc+Og+pHYiOAOwBgj/r5fQAvAqg9AZx6ShHbjgLQNqxTIr3yis55T7ApsGSaPNdBnPbtU78nJtR8lKkJXZie1nN4kSNb7WdYOuARGDNEo1hMZj5M5xKaVWCJzMmIkfOpwPoQWFosyxeWjwLra17MF6VbtoTNQiXmU4G1RbH2hUlxJFO3pPAxIQb8+uvWW1Ubd+ywl7tqFXDQsIhKgigFVs673l6dXgNQ6ivfIFloBNamwPL0U/S5KSiVDT4ENiqNF0UkTYKVKxUhiCKwUeMhTXi57zX/vlrVBFaqury/TCa/vA42P+CpqfBi2kZgW+UDe+SI/vvcObcC+/LL+uell1Q+57RMiDmBpb+5Dyw3sY5DYKWKSr6xD/sAACAASURBVPWh/mhvV2RjYqKx7ZOTYfJCZXd36/uL+8CaohRv3Kh+79+vybCNXNnyN8d9/wcB0L0dON0GnAZQbQdqsxt2tU6g2gfsXwM8eQIYvwq44YbZE2cJblBTPwAwUwCCOtC+H+jcA7QdBhAAyAH1HDA8CgyPAT0VoDMPYBjYUgfwGHDsPcDHAGAa+PolwB/kgJ8A2PMpoOPdQAd7DnACa4tCHCeIU1oEFlAbGXEI7BJRX4GMwGZYSmhvz0yI46AZApumAktBSeRiYz59YK+6CvjxbAoA1wu6ra0xiqOPAhtFEkw+sFGYTx/YVhHYNBRYVxAn/tuFnh7gppvC5coxWb06PQIbpcCuWRO+FvnBUhoIbj4MLBwCa8oFK4M42UyIkxJYystMkH0r+2b7drWwp/yRcUDuGK4+jKPA0rPFRRhNm12Am8BGKbBEYKvVsFpjIrBtbXYfWF8TYhvh41Yd58+7CeyxY+p3oaD67bOfBV77Wp0+xQTfPLAmAstdHGS6HV8CK9O2mBRYOo9HpCZw8kJ17e7WY8Z8YHPcFJ/qPTioxnpoSCmPy5fb6/7cc42f1WrJN7DpOqZ3G70PQkphAMxYngEjV6gfiQceAJ56CrhrF3D99cCXPwe07wXuXQusrgKHTwAzeWBbN9D3CrALwMHfVj/dO4Ct/xbY8q/jRSFu1oRYjrMksFNT4Wf/yZONz3sXlhCBzdLoZFg6qFSaVwMvJrS1JVcb+EM8jU0DVyATwK3E8cVZWgR2yxZg8+bo80318iGwUXWyLUpdSEOBXbcuPmnM55WPaDNoJYH1VWB9nx10nDyegqKkgSgFdt268P+UegJQG0JSqY9DSudTgc3nG1U5rhxFwURg5fjLcuT9EgTAm98c368MUBuClYo9eBfVz1eBJXXVZrLLF7vSBzZOECebGfXUVJhEyJQ+QPiZEVeBJYLmq8BOTtpVVSKwb34zcM016u8f/MB8LKAURz73OCQxtSmwMt0OI4xGSAJ75kz4f0lgee5kPtbUb1zB5QqsVGW5Alup6PYFgVZhacPGRK7GxswbOnHNiDlsUYgBbZorN4fjgjbKaD7n2oDHAPzgOuD0/wPcB+BPB4G3nwL++lLgswBy1wGFTmDoBeDJDwJfWwfs+Y/AjmFgOYBSDgiqSg0uVVV6oPpEekGcpM+rJLAHD4avETeVTrN9uoCQrfYzLB34JLrPoLFqVXKyw1/4aWwaRBHYZvLAJl2Q/8zPqN8u8miqV6tMiKOQhg9sb69bsTChvT1e0CETymWzH1orTYhlf/kofK5yKbJsGmhvd99XLgK7Zk0jSVtoBNY3CjHPGeszF0xBnGR7pI+r6T4dHFSKTVy0twMf+hDwsz9r/94nWr7NJ1N+PzXVSGBp3vA5EGVCLL8nlbpaDefjNEUhXr/eTmBtUYipPfTbRpp4WpNz58wBbQhEYNes0RuzruMpAI5U6Hm9ODGldplMiLkCy4mxhCSwlPqKrm9TYOn6VJ+1a9VvihtAQYYocjuthUwKbKUSHj9uRsyvzfH88+HI3YSkBJb3kYvANuurKaMQ05yvVrVJdLmsIifPrAO+DmD43wL3nAVu/hqw4iageg44+r+A95wF/gTArX8JbPs9YOvHgH9YA3xlAPjKcuDdx4DXAJjxCDIWh8COj4f7nqLM//jHwLe/HZ/AylzEixgZgc2wdNDsIvpiQzPKadoKrGkR6aPA8qAvtnKS1m/1auDyy91EwqXA+kQZtkGaA/tsEnAfuCTqEaDuoUsvjXdOR0fzEYNN58+1AutLYG3lpklguboj0dERJqyANiEGzObDcebDXJsQczNO7gPLo66Wy373AJXB2xuV59XW3ltvTRaR2BWgjeZY1Mah9Hm1EVipwPLr8rrL8/lGgak+NE5RJsTt7WrOx/WB9TEhlkHhzp+3E5qJCUV2CwVVHyrXRWCJ0JnGn8aJq1VUFv3mQZw40XWROhuBJcXU14SYCDopsNzMvlTSBDBKgQV0DtQDBxSxNJErk/kwYG+rjGdh+p7ONfV/2gosT6MDqH4kU1rqC3p2HzsG5IrA2ruB2/4FuO0hYPWvA88XgBEAMznleztTBoo9QHnW+mjbCPB/AXjzA8DgF4C9nwaO7DXXy2VCLOcs38Sr11WgPgD47neBhx5SPvemzQUbkqalW4DIfGAzLB1kBHbukKYPrCyP4ENgTQszGRCqmfq94Q3uxaaJ9PCUHaYgT/wYG5pRYG0+xT7o6lJRjuPkdaXFbmdnvBQXHKRm8AVLWgpslA9sXALrUmB9fYF7e8PqkgQRWFPE1cHBRnJLfm2Tk835vwLzb0LMgzjFiUBMZZDCafNv9FFg6bi1a7XikQakEuRCqaTbb8u7OjWl56MtkjBgvo9caXZIgZUmxJLArlwZJnLSfy+KwNJvExEi8+H161VgpvPn7YSG1NfBwfAmiIvA0hw0jUVfn/r83Dl1zc5O9bunx63AUjodG+T9TCogRca2mRBTuVKBPXUqTHDa2lS9KhV1H1BqH05gu7rC86G/Xx0/MqJMmmX9x8a0OivBx+3sWeCLX1Tj1NcHvO999n6o1fS53j6wCeAisGRZQPcBRW2nuURYcSOwshf4o0+rPvrQb6k+XLMG+MV/o46ZOAX8xnXAhkPAlmlg2fPAWwDM7Aeqg8DYemB8g/qpdcZTYAE1Bh0dSm0l4k3jOTys3iW+bjxLiMBmCmyGpYOMwM4d0oxCDESb/toWsHJhZjLPa4bA9vW502q4TIgB+0I1ytydFJgoFZGDtzupctnVpc6NExSCE9ik4ItBQqsVWFqk029fkkQqV1IFNpdzR5OmnJw28r5ypd1v85ZblOWArFcczFcQJ5MPbJwATlQG/y3/BqJ9YF3HNgsqz6ePXRt4NhNirsDy/01tdJkY071sMyGWBJbmbL0eHltfAutSYC+7TP0mMmkCkQ4iIdQel7kkLeRNY5HLaTP9l19Wv+nadB63GqF2TkwkJ7BAYx5Ymwlxb696bpGSyFPkkI81r1u1ihwd09kZtlwKAq3C7t/fWP8XXrArfJzADg+rcRgbUxHRjx+398PMjB+BHR1tzs/WRWCJKNJ39Nw0meSagjjx913bCuC5tcB/AvC1XcAPtwHPA5gBUD4B9D4GrP4SsOXjwMY/BQp/Cez/a2DMkHrORmABrb7W62GzdZmCzoXMhDhDhgWIzAd27pC2AisXWNIM1leBlWWZ/JvShMuEWNaFQ6byMJXBF5VxFFjXdaNAL+U4ZsSLlcBecw1w1106TYMPSSKFH2icV2S+GIVVq9x9RSa/trabCCygImfv2tVovrqQCGycNDppEVg5/nJDKipicJqIq8ASfIM48bEnCxDT+YBboaV3qS2IE12fz0VutksWMFEE1hbEqV7XCuzWreoak5ONaWcIRJYoCjTVybVYJ6JgG38KxEURX4nARpkQuwjs5KTum6kp3R56H9gUWDLN5v1P1h4nT4b9xClAFye/09PIU1+QuTIfcyJvp0411v/ZZ+3t4eMm+/rxx93nuQhsLqc3Fl0q+vAw8IlPAI880vhdtarawq06TL7a1E9kli0jQwPmNDryGU5lD5WBh5YBHwXw74rAoV8GTt8KjG4GZopA6QxQ+gHw8HuAr60Bvnk98OP/DBz4PHDyQWD45cbrUx8Qga1W9TyKS2CXkAKbmRBnWDrIFNi5Q6ujELvM4TiiCGSr0yq5TIiB5ASWK1FAPB9YoDkFFlCBnPJ5v93vNAiszQe2lUGcyuVwoB4fksTHwaTAdndrU14bNmxwj09UMK7BQb3BE+VrxsvzRSsJLKl1tCAsFv0UWF8i6aPA+poQx7muL+IosHz8XSbERFrlMaSyVavmueRSYOk5UK2GF7w2BZbKGB9XdarV1LUnJ9UPkWtS8ugcmwnx0JBatLe1KX/vnh5Frs6e1SorBymwRMTiKLC28ScCa1NgbUGcXAS2Xlf90damiDERE1JgJYElskmEi/f/ihVKMT15UvvEkwlxoaDrNus/m6dzaWzLZX19evZNTYXrX63azYeB8LhJdfnHPwZuu838DI8isFTP0dFwrluJ/fuV+ez3vw+8+tXh5zNXX+U9wtM90X0wOKh+c4sDwuSkmrtBoOsr03Fxf25S1seqwLmVynRYNRxoOw70HAd2ADjxT8DZJ9QPx6odwNmdwOQsqR4bU/UiqwRupj8xES+Q0xIisJkCm2HpIK0UFhmi0eooxFFROF2fp02uXTBdn1/TtlCNS2DnWoFta9NphKJAC4BmFVhJIFutwEr4KrCmvwGtnEapsBs2uJ9VUQR2xQrt5+yDhURgg6DRjFjmgeULQZcCaxpXqrvrHpT31nwQ2GYVWFMQJxmsi5uhm+5NHwIr/eg5gSoUlP+kzKfM1a39+4H/+l9VwBlAkxYaT5sJMamva9aoNtHzkoiBrNPp0+o9RPce1cXkQ06IUmDXrlVlnjihyolSYImcRuUBpTrt2xdNYKndU1PqfuH3CvnBPvtsow9sodBgfnwhCjGRQdP84tGWAdXfrgBBLgV2akrnUpeIMiEG/CIR800FSbRlCh3AHGyM7gPqa9P1aJz4PSY3wkwEFhCEOA9MrAHO7wR2/T3wjjPALf8H2PEhYN09QP+NQL0IdL0AbLgfWP8XwMDfAyc+CzzzoC6Gb5BOTACHD5uJtwkZgc2QYQEiaeTVDPGRtg+sKU+h/N90HdPOLD+3lYtxoLUKLF+0zoUPrFRBt2/3O6+VJsTNbEpRn/nOzzQUWMBNYIMgnHbEBEkIOHiamMVIYIHGVDrcNE8qsK4gTv39jZ/5KLCAeVHrqmtaaIUJMfWfyYT4rrvUj6mveB+4FFgOTmAHBsLjxUk1nXfggCIrhw+r/yWBtZkQE4ElRZUIHgWw4SD1aWCgMQe3yxIiisAWi+r69bry6TQpsKRyU1qYKAUW0GTzpz/VZdkILEUX50GHymU1zpdeqsbw+HEdaIw2FkwKLF2XntN8TnECy+vvCjQHuBVYAHjsMbOViI8CS/V0RSLmZPOZZ8LfUd+aNmo4gaX7gNYSLh9UPlckgeWbMVYCC30MABTagTV3Add+HHj9F4HbHwLGfxc4+zpgpgS0HQN6ngTO/Xdg/88Bgw8ApVNAdRSgW31iQl3jz/4M+MlPoq1ylpAPbGZCnCFDhvjgkXbT2DiIUmCDQL0g5MN3xw53WYvVhDiuD6z0GU6iwEof8g0bzMdJLFQf2CgTYgkfstwsgR0cVAsqHxPiKOuCUsntH0aIS0hbTWBpvtCikKfTyOX8gzitWNFoOufjAwuoMaBFpqu9rgBuSdCKIE4ESWDzeR2MzdQH3ARS9i9X/up1XS4nsGTKS88eTg5ogU7zk0iIzQdWkj7yaSUC61JgyXyY/F+BRt9UE+hd4hqL9esV+X75ZXMQJ/pNEYJ9FdizZ9XcrVbV2PCoz4Aug0yDeTAtum6hAFx3nTKffeEF9ZnJhHhWVb1AYGlO+xBYU39zRBHYkyfV+MjAckkUWDqH3xec3L7wgtqsofGUAZwAtw+si8DyyNMEmwI7NBTuQxOBJR9W09ppvA04cxtw5mZFYMvHgYGzAB4Hlj2lfjYCuBnAEICTzwDdHcDoNuDLX1aRpHftaiyXruubXWARIFNgM2TIEB/0IE+LIEYpsEDjIqu9XUdPtJ073ybEpnYEgV8U4jg+sPI6SYifJKCUXiEKC5XAxo3g7EP6eVlyTHwILG0KJDUhTmImHnczo9X3TBwF1kVgTSmLLkYFVgZWIrjmKq+LqfxKRZ3D83UC+lqcwBJ5NZEDInsU2InKomNtCiyRFlImXQqsicBygs9NYKem9JyK8oEFwn6wRGJo3sqNJio7iiBMTITNhysVPUdJmSR/S1JgeT5ePlbXXx8eWx7ESSiwF0yI6ZmeBoHlx9qUPROB8/WBBXS7v/lN4A/+IKwK05jkcqqdL77YWB8bgaW607NA5s7lMM0V+WygPjxzJvy5zQTattFxIedrGRjfCJx7LfDizwIHPgCcvwaotQO12T7rBrD1HDDwj8Cm/wGsux946c+BUw8BoweBmnABWELmw0BGYDNkyJAEJl+zNMojmBYVcpG1Y4f5+nNJYJMosF1d0fWK6wPrswEQBUmqgwDYuDH6vGYJLKULmusgTrIOPqqYTYHl0a5duWCJwCY1IZ4LAmtKRZUmZCRiUx5YClBFx9hMiKWCEZfASssFW12TQpadNIhTkjQ6fK6aCCy/X+VcKxbDJJlAimapFA6mZCKwPKUO99/k0ZFtCiyRO6ojEVhfBZbPYU6shod1JFdfBRZQJs3nzoXbJO/TOArsvn16bnd0hH3aeb14dGKpwAJKNaQ0Q4DTB9apwMp0PYRmTYgBcz7yOArsyIg69umn1W8yRwc0Obz8cvWbR0z2VWA5oae87bItJgJrU2BlFGObb6ppnvCcvhy1GlDtA068FXjx3wNffSvwbgC/BeCrA8DQlUCtBLQfAdo+D3z7JuDvNgJf6gEe+iXgxPeA+kxGYDNkyJDhwoM8rRQ1PgT2kkvC//MXt62sVptDJlFgo8yHgfgmxK1QYIF4BLZSSWZObjOZLZfDuXDjIo4Cy1MtuGAjsDy4R3e3vf9pQZw0CnESP+ckmxlzmQtWBnGinKJAY65GjmXLGvvAl8D6KqHNElhOquJcVx5ji0Ls8oGNUmBdJsSlUqOZMs89WSrpqK1UV+kDy9VhQJMNXhfqD06EZmbC5A7Qz0ypwNbryhwXaLR8oD7iZqYjI5rkuPLA8voNDKj6HTyogylRm4FGBTaKwI6MqIBDXIHl5XEC29Ghx5HIpHxOvvrV+m/KA+syIU5TgXUFcSKYCGwcH9jhYd33QHgO0Ni+9rXq9wsvNKr/JgLL7xuaY0GgrylJqA+BlRGpST23EViTUj897Rf5nzaSTgF4pAQcfxvw0oeBY28Dhi8DOq8C2tcAtXHgwGeAf3oD8JWVwFP/Cuj7LtD3PWDg/wDH7gOOfyf6egsUGYHNkCFDfKStwPooiK9/vd6Jd0XJ5efawu+nhSQKrA+BXQgKLBDtB8vrmcsl8xm0EViZaiMu4gRxSmJCbNuoCAJz0Jz+fnMAFQlbf7S1hdvSKgUWmFsFlvsUkpJNfUsLVNN91tPT2Ec+UYiBsALrQltbcz7+tGFBaKUCK8c5isDyDSvZv1yBpfI5ee3rC9dJEl5K+cLJCy3keb3omcN9VTl5pXp3dqrzxsbCZY6MqEV/R4e9jziBGBlRZqYTE34KLNBoRkxEUD6fSL00ETaOvXvD6YloLpoIbHu7rh8RdbmZsXatzmHa09OowM6S6pxUYE2RuHmqHiCZD+yRI8Af/7FqJ9C8Ajs8rMsCNIGluubzaqNo9Wr12b596ntfE2K+kUPXJFWfIDct5PsZaLyHaN7EIbCuqNkcMo0OoKIXD18JHLsX6PsfwNsOA299EbjiPwEd64HJU8C53UDf94G+B4GeJ4DR7wHnHHl+FzgyApshQ4b4SNsH1keBLRaBO+5Qf9vMh+W5tAvaKkTloZ0rAiv7L4kCayKwK1a4SSnPsQckMyM2ETZS44DkfrBzaUIsz43y2UyiwEp/5MVKYLkCOz2tAr0AOqotV91lnkpev44OPwXWFsQJiO6bIPCLTm1DT4/eRKNAdD7XBZL5wNpMiE19wO9VE/njpAYImw+bFFtpninNUYl48LqQGfLwsI6eKpVJIJxKhytwpEqanvNUH+kzWaspM2JfAksBiE6eVNem/qbzZMCoqMBqlFeWjpOEkivD7e16HIjAyrEKAuCd7wTe/W5F5KQPrI8Cy+cm1YuTfI69e4FPflLl5TUR2H37FPElItmsAjs6qs2+AT3+pOh3dqr6b9mi/ifyacohTWNGQbeA8Dyja9IziSAJLJl9c8h7Yt26cD0lTEq9K+iY7TjTGJGZdedm4MqPAHcfAN76ErDy94AzO4EztwAn3gwMfhRY8xa/ay5AZAQ2Q4YM8cGjEKdZHsG2wNu+Hdi2zW4+LMtqNYE1mZ5GmRCTihxVbjNBnJKQFhP5jPKDleQ2LQIr1Z0kmGsTYg5TWbwdSXxgbT5XUVhoBJYHcTpxQqkx/f3aZJz7SNrS6CxbFo58K+vt6wPr0zfNmBFTKhYqhxa9+Xy0susisNQfLh/YZkyITQqszAEr6xpFYE0KLJmBc0JBqrvcsDH5wboILI2tyeT02WcbSYkNZE1x5owibXQO9bXsJ1faFw4fE2KuwFJbTfd9Z6eOOE0mxFTu0JAK4iQJm8llA9CEy6a+PvusIngvvWQ2ISYCTmNvI7BE4GzP51xO15XXhcaT+pk2XsmEnMx/pcINhJ8Z0s+al0XjLNtGY2F6Jsh7aM0a1YaxMd3WJ54AvvENtVnTjAIr88BKUBoqQhAAnZuA3I3AmTcCZ3YBL28HXtkOVAyBMBcJMgKbIUOG+JiPKMSAehDfeafdfFie22oCC5jVIVNdCAvVB9YWGdllRpwGgTWZCtv+joO5jELsM3+lmbFtjGwKrOxrX2KahIzOhQI7NgYcPar+JpInfWAJcsFIZGYuCGwzqXSKRe0Hy9vgEyjLteHB87TyNERxCCwnorJ/XQpsFIEl/0KbCbFUx2W0WZMCC8RXYOm5wY+na7z4ov47ahyIwJ4+rYmNaXPBV4El+JgQk08roElc1LOdTIiJ0J06BUxNuYM48f+p/rYATvQ9n3vT05qkUbuk6TmHjwkxEH4nkcIqCSy9c/g4Abof5TtJKt18npG1hPSBNSmwEnId0Nur6z80pNr8rW8Bjz6qNkNMCmwSE2K+GUAYGjKbLnO19tFHgXvvBf7Lf/G75gJERmAzZMgQH/OlwALqxeBadMylAgvY/fCAxeUDayOfcRTYqPRAJlBd+QLAV610wWZCbJqzzZoQy/42leVr5u1rQrwUFFhJYKUPLH0m60P3kLRSoPHxDeLk085mFNhCIazAckSNC7WtWGycs1yZo2OlohsVhZiT1LgKrGnDzOQDG6XA5nLhYD1ANIE1KbDcqmVwUC3Mqd+lDyygFv1kaho1B9rb1XOuWtWmrKYAW3EVWEmgbAqsVJKjNvSIwHZ2qnGdmACGhpCbng6/V6IIrE2BNRFYTox8CCwPVuTqf/4+ueoqdezkpGoTNyEGlF82oMjhzIyu09q15s1GkwJLc6xZAtvervqTCPHQkFKt6X4YH09PgbWdx6M1E3gUYjKTftWr/K65AJER2AwZMsTHfPjA+oKf62Ou2yzk4i8qgIwvgeULjFYrsDzoh8TAgH0Rn6YJsc1kMu0gTqa2+JoQ+wRxMv1v+szWLlsQp6QK7EIjsFyBJRLhUmClnzVgVmBtpHUhmRBzRPWxbR4A6l41bfLEUWA56TQR2GYVWG7eDJgJLFdgifiZiAXgZ0I8MAC8//0qrQo3oSVwcsnNgaNA6t4zz6jfaSiw0gc2yoSY2hH1PCQT4iDQKixtFPGgZPIdQeUSybERWOpDTkI5gfIhsBMT+lzXJjjNgSBQJtJchZcmxKWS+n5mRs0L6sfe3vBGttxw4CSZypfqM7WPxsJEYPn9TXOVCOzwMHDokP6+WQIr+zQJgT1+XP2+6iq/ay5AZAQ2Q4YM8TEfUYjjltXV1Vw5vohjQuyb21SaEJte8qbgFLbrRqGry+6TFwT23KZpElhOItPwgbUpsKbFh68JcTM+sL6bDL4+sIuVwHIF9uRJNb8omI/0gQXMGysmBda2udBMECd+LCFOVOJiURGpZcuSK7CmeUL5PuWxcQgsJ6mybrlcY1oQF4GVim0cE2JfBZbI2IkT+jMiWURQeCovOp8H0eEEVgZjcoHUPYqGy/teEtikCiz1HyewXO2mfnE9D4m40jnUZ+QTycfZpcDW62YT4nrdrMDGJbB0TBC4CSyRy/XrVd1NBJa/c2ij4ehRVTfyBabxA+zm+IBZ5eftcymwJgLLTYg5oeR+sabrcIyPA5/5DPDcc/ozmms0112BnGRZgBrDkRFV502ZD2yGDBkuJtCDvFUmxM0soOncuTAfBuIRWAo+EwUfE2Ke97BZBTaKeNrKS5PAAnoR1SyBzeXCAXM4TIuPuTAh9h0jXx9Y335ZaD6wnBzV62oe8+eJVGBtKXSA5ApsqeQ/5pLcmVIk2UDtWrUqPoEdGFD+51df3fhduRxtZh8VhZhMTQF3UBoZjKdUShbEiUiLTYElomkL4jQwoNp0+rQue3hYfUZKF58rksDOzITVUSIQPnOAxvzFF3V7edup3YC/iiaJugxcRptqMuiQTwouKksqsPwZYiOwk5OK/JkU2PFxHS26GRNiakvUBvjWrapelOuWE1hpQgzocSK1k0ywXQSWzzMqX/qPEmG0bfjIz6QCOzSUXIHdv1/NuyeeaKwPrXFM5xGJ56CxIfPhLVvSW8PNAxZvzTNkyDB/SFuBbYUJ8VyYDwONCwEXsfExH6YyoggsX0g3S2CjfFdt5ckXeTNBnAAzgU1iQuxS4GwE1icybDNBnOQcjzIhXqoKLBBuC5nYAmYTYpcCy/swDoENAlWHJAos5dz0AV179er4JsSFAvDLv6zyX0ukocByE2IXgfWNQmzygTWRF35uLmc3IZYEtlDQliDHj2uC1dOj28fbIQksKYsEIhBxCCwt/Hnf0zPPlu/ThOlp1Td8M8dkQpzL6c9nZtRvnxRczRLY6WmzAss3AKpVvQlABIp/lgaBXbcOuO8+nXXAZUIMJCOwPFe8jcAmVWCp7OPHw/0Zh8By1ZRA9yLdD6bzpqfD1gqAJrBkPrxtW+N5iwgZgc2QIUN8LAYT4oWqwPogisAWCuH2Ndt/S1GBJfiaEHPTu7jl+mzAxDUhlqa0SyUPLBBe7FGUXqAxDyzQeH9xxS2pAkt1SBKFOA6BpfJNBDbpM47mabM+sMWiIjjkXyhB9W0mCrFpke4bhdj0LKG5cuyYOQIxnyt0PhEdadpLRCuOtf1qbgAAIABJREFUDywRYN73RCJOnAgTZBd4BGLpk0rfFYvh/KyEOAos1Y3GjvepzQd2clIRRNPYSQVbmhBLgguYCSyNRdz1AyeYLgWWiBttUvkqsPRcGRsL11sqsHEJLOX+JVAObAkXgeX+q1Q3cr2wqf60cQHoTRNAb8SY7vtFhIzAZsiQIT4oDcR8RCH2LWsxE9goH9hiMawwz5cCK1/kpsVtFKIIbLMKrG8QJyC67nNpQgyE275U8sAC4TEwKbAuH9iuLj0OzRDYpAosr28UuAmx6zkRB2T6y+tOf3MCGxWFuFQC3vIW4MMfNi9kab4lzQPLVSbedlcUYu5jKTdsAN33nMDy5yC/Dj3TqDwbgfUZB67yAuG+r1RUG6am7IGPJExtlAqsLYhXlA8soF0oOjvD5/Pr5XL2YFQyCi+B96HJhFiSrHrd7QOblMCePavKCIJwm+RGg0mB5WMn3QiIcE5O6rbyNrgILK+HJLDy8zgKLPXV2JiqS72u78U4BJabeWcKbIYMGS5qFIsL24R4vgjsXJgQFwrhhVsaQZxc8CWwQRA/lU4rFFiXCbHJh4+Oieq3ZqIQxzUhproS5jIPbKuDn1FbcjmV9oTg4wPL570PgbU9o2QqGhskgV2+3D8yMZVfqYSVZiB5H9NzN8oH1keBzeXUWJj6iMYoqQ8sEYBiMayS8XODQD8Th4e1/yU3SeagPjx61KzA8nGh5xARgGYIbC5nJ0GAnsPSZNMGmQOWl0n9Tf0p57+PAksqvQzAZ8uJysudnNQRmiWkwioVWE5g6/Ww6sdBx8V9NtFcoX6uVMJzu1IJ9xeZ2vOAjrzNchxpzkxOqvk4MwP8wz/odseNQiz7+5JL1G8bgZXpcehYQPX11JTq03o9TMxtBJaivAO6z2dm9PhSbt1FiozAZsiQIRkKhcyEGGiNAlsuu0lYsbgwTYiBxl3nKMy1CbFpAU7/JzUhTjMKsYnASsLiU9e4x3HMlQI7MNCoiJjS6HDwe8hGYKNSWQHJFNi2NvW/SR00gZfPg6656hUFeu7G8YG1BXFy1UUS2Lg+sORHKAms7HMah+lplcMTsPfv4KAO5ERmkDYTYm4OCjQS2Dg+sIDbDNVEYJ9/HvjGN4Bnnw0TO8CtwMpryPeLjw8soNvFYyXI57zJ0iUJgTUpsIAmXLZgQnHXDzSmtPkg2xME4fbS3AoCPX6ujR8qn9T0L34RePxxPVdcPuOVikrfdOWV4ec2ryMpnnGiEMsIz3Qf8qjMNgJ78qS+DvX5mTNqPHp6krn8LCC0+C2VIUOGJQvawU8DaZsQFwrxlcCk4IsAmRYgKYGV55kIbKWi2jk93Xg87cCbdnlNiOor03iYSJVPWRKtDuIk56hLgY1jQuwa52ZMiE0LLO4rF3V+1HV9MFdBnKQq6RPEyYfAtsqEmJQV08aNRBCE2yHHr1kFtlkTYjLVnp42EwkiV75pdGjsZmYUoSEfxVIpTNTktcgP9uxZbdpoI7AUyOn4ceDAAfWZTYGVBJan0wHi+cAC7qB5ksDWasDXvqb67tFH1Wc33gjcfnu4TiYFlkBzW5Il1/PQNO+5Aiv71UZg45oQmxRYQLW/UlG/eTuI8MYlsIWCIl2mAE6E/n6dQob7uff1qXnjQ2AnJ4Gvf13PeU5geeAtWbd77mn8vLtb1Xf5ck2ikwRxAlT/0vOwrc0dhRhQ43PypDK9lwGcuOXLIkWmwGbIkCEZ0lRg0zYh7umJl6+xGfAFtqsdHR3+BFbWXS5AKegQLahN/RVHuYxSlExltbeb+7gZBZb6Mk0FVm4qzJcJsfzMx4SYjjERplaaELeawF5xBbBjh06PQfAhsHFNiJsN4tTWpuc5XdtHgaV71Iakzzh67sZJo2PbaKQFuamecQhsqRQOgkZ5JukaLqWRB3KixbVLGaJND/JzjFJgiQC4TIhf/erofJhxFNjDh1W/dXaqVEgA8Mwz+nhSMvl9Lcs0KbAywJmESYHlyr8pZoH820Vg45gQA/ZIxEkJLBB+h5rmCd9okAQWcJsQcwLLzXn5ZodpMxGwP2eozHXrwjmwTQT2kUeAv/qrMCHlBHZ0VPdle3s0gQW0HyyVQ3M0I7AZMmS4aJGmAktBoXjZSSEj9LYaLgLL/1+/PjmpNimwgJvAxunDKJJo+t6mQqVtQtysAiv/pyA4HHNhQmxa9JvAj6NjTITJZ3wlGfRFqwlsXx/wC7+gg5AQfHxg01RgfdoZBLoO9FzxIbBR49NMECcbgeXPF64A257Tps0cArXR14SY/x4dDSuwnGjI+chT6RCBdSncXLVvawvPD5MCS4t7lwnx1q3Ae9+r0haZ0jYBbgW2v1+14+xZRTAoX+zllwO/9Ev6+pQKh4iejwkxb1PUszCKwPoqsNLklxDXhNgWiXg+CawtSB4Q9oHl4AqsbW7a2kLPOMppGwSqPyTprNWAxx5TlgVkXQCE+5SbEHd0KFUXcBNY8oOlcjICmyFDhoseaSqwVB6hWQV2vgisaXFG7Vq3Lvk1TEGcAN1O0yI0jnIZ1d/zSWCbDeIk/2/GhDhNBdbULvLXkseY+tqnX5pR+eYDpjQ60oQyzSBOvv1D/R/HhDiq7GYV2CgfWECrq7aNM1cgPiIHU1NqcU0+reS6wGEisER2pAmxSYGla9Hi2qXA8ijQ8jlvSqNjI7BSVQOAjRvDJrccnBjJey+f19+fOqUJ7JYtun31emOqIJcJMT0D+fyPuudNZuVdXbosXwJrQ1QaHR8Ftl7Xx7eCwHLCHqXAugisKWewi8Danpk33QS8731qMyMI9HjKPLsTE405X+v1RhNi7gObEdjWIAiCTwVBcDIIgmcs3wdBEHwiCIJ9QRD8OAiCa1tVlwwZMrQArsVPEpCpFdDcAno+Cayp3vTZ+vXJr5FEgY2TsidKGbaZEJuwEAisVJyiCGzaCqyPD6xJTbGZEZoWTfl89LgtRgIblUaH9wXvw1YFcQL0XF/oCqwE9WdUWSbQYr5aVYveWk2RgLY2PwLL08HYohBTHfm1AHf/UiAnwE1gqQwTgaUIuVQfPqf4Boksm8oslRSR5n1LhGD/fmW2mc8rQgzoZ/H58+q3jwJrIp1RCqxpEycINKlzpeKKS2CrVd2HUoGlcTAR2OlpPc7NEliTD2xPjy6X3+M+BDaf13XnJr6cwNree7b7uVAA1q7Vz2o6n+YCgRNYmqsyABYnsJVKdBRiQN+7Y2PqZ3h47tdILUIrFdi/BHCH4/s3A9g2+/NrAD7ZwrpkyJAhbRQK6ZkQA8DOneq3VKHiIpcL75a3GtyU2kZcCoXGgDVxIFUUuo6LwL773cDv/A7w67/uLttnEW9aINtM7eIS2FYHcZL/N+MDa/Mr9PHh9jEhtqm0JgIbBPEUmThIi8CWSsDmzf6bED4+sLbNjVaZEAN60RlHgY0qO80gTjYFNspn0mVCTORgago4ckT9Teqn6f7J5XSduI9flALLc8ESXASWAjkBjWo8byuVQf6MnEQRKaBNoCgCS3OOSGpHB3DVVeG5Sd9R0Kb163Vb6ZlIKjYRQU7GbATW5ScrYYssTWasMhK26V6i/K0SFF2aW15NTOj0LoAmsNQXJgLLTZRbocDmckr57uxUY8kjB3d0uAksoPubE3lubh5XgbWV7yKwND+4+kqfU19KAmsaM0AHchof15G7BwbSXbvNE1rWgnq9/iCAs45D7gbw6brCIwB6giBoYoWXIUOGOUXaCuy6dWrHuhnzYYJ8UbcSQaBfhLZ0FWvWNEcKbNGNXQQW0Is939QLcY6xEdjOTvcGBJk9mcoulxsVuKhFuAkmU25CWibEfEyS+MCaFk8+i9io68T53oY0COyddwL33Qe85z3+1gBRPrDSbYErjK00IZYENg0FNs0gTqYoxIDuT1cdfBRYCgRjI7C0mUJ1qlb1QlsGcXIpsASbCTGNA1mzcDNI+TziQahcAZxkVFmTMrVzp2rHnXcCd9+trn/55WE1jupCZsI8xyYRWKnAvve9aqNxx47GZ3QSBdZGYG++GXvf//7GKLm8vFxO18GkwlIfVirhjQp+LLWLNmtbTWBtEe/f+U7gN3+zMZ9wX1+4n03vMElguVqfxIRYguYMbWYQzp/X17ERWN7flYo255+ZcWccOHpUjQ2Noe/zeIFjPtPorAFwiP1/ePazY/LAIAh+DUqlxeDgIHbv3j0X9UuMkZGRBV/HDPOHJTM/CgX1oE2zLatWqRfEYuufTZvUS7lYbKz7qlXqRenRJufc2LYtvMu6e7d6cW3frnLVuUjj1q32wByFQnTdajV1HY5q1X7ejh06YIlEW1t4g+HJJ/Uie3paJXv/538OnyPbHoVyOVy31av1AvPJJ9WLn7fn5Mlwf9owNBQu95JLVL2efRZ44QX9eb0eLicIGttkupacP6Oj6pizZ4Hduxvnx/r19nE1leeLyUl3P/hgeBh48EH19+Bg48aFCT/8ITA5iTWrVmEbgOn2dvzLpZfq73O5xvbQGIyP6+94/1MdTKjVgD17outVKACXXgo89JD6f3o6un9KJXffj48n6+NcDjh0CL2bN+Oq2Y+e2LYNw1u3YmRsLDw/1q1TfWGrR6XSeK8QRkdxSy6HYGYGYydOoAPAkzfeiKFLLlF99tJL4eM3bcJly5djAMCz/f0o53LYCuDw4CBeuuYa3Dx72IFyGQf49fr70X7llXgNK+rRyy/H2Jo1jXUqFoFqFfl169D7utfh9PXXhzcweLm1GnYBQLWK3Y89Furr0rlzeB2AqbY2PLR9e/jenJpqHJfxceBVr1LWBIDqs8cfV8/2WWuf0sAAXvfZz1445bGf+RmMzhLttfv2YesPf4jD+Txe3LIFt0xMoB4E+OdTpxRxWbkShUsvxU52yae7uvDK7t3omZzE1bOfnezrw3OuOTM8rPugrS3UjpGODhwldZgwNhY65sbOTpTPnsXDa9dikkddBtC9dy+uBTDU34/y2bMoT0zg4a4uTD78sCqjXsct4+MIABzp68MaAC8uW4ZD27cDhw7pHL/VKgYGBnAZgBO9vXg+5j1QXLUKN83+/eA112AmSpV+/nngpz9Vf/f1oW3HDrx29quj7e3YK+b+tW1t6AbwxOAghrduRW5qCjcDqBWL+P6OHUrttN1PHm3ZsXIlVu7dixcAHGfllI4exetm/z43M4Mfbd+OnulpXA1gJp9HrlbD+ZkZvNLZiY0A9pfLOPjEE2rMzp3DQ2vWYMr2jD18GFi2DKu7u3EJgKMrV2Lv9u0q2vRsHRbjunQ+CaxptWVcodTr9b8A8BcAcP3119d37drVwmo1j927d2Oh1zHD/GHJzI+vf13tLO/cGX2sL+p14MtfBhZb//z5n6tgCRs2NO5y33+/Mje75JLIYpxz4w/+QO/I3nST6qN6Hfj93wfuvde9A0z1M2HVKnW+C+Pj6vocb3qTym1owv3361x8HPm8qvvTT+vP3vEOvSv+yisqjcA73xk+74/+SCWW98X27eE59Gd/ps2n7r1X5WjkxOWee1Rql+9+VxFcG2SbP/YxtaC5666w6XS9DnzkI/r/jo7GNk1MqPM5Nm4Mz5+nnlKRKd/7XmDTpsb58clP6qAcJpjmow8OHgT+9/+Ofx6hUlHtpU2Vv/kbYO/e6PPuvVctNs8q461CsYhdfJx6e1X0Yo4//EO1sXDbbWpuAYpgfvSjal696132601N+Zk3796t+pmuPTwMfPzj7nMuucT9HHvhBeDzn4++tsRrX6vUvS9+8cJH1x07BtRq2H3zzeH58YlPqDbKPiN89avqnjPd/08/rQjj5CQ6jh0DggDXTk2p++aNb2wMdvQnf3JBabv8wIELSuTakRGs3b9fkb7JSWzM57GR1/FTn2pI2/LqU6caVVNA3aM0H5Yt08QEUHNdtmOW8O7q7lYpSgizAXRKQYBdZ86E++fcOfW84fjQh9Rmxyc+oe7td7xDEdrPflbXoV5X9/nYGNDZiRvGxnRdZ1WztQcPYu2PfgQACNrbseuGG7Ti+73vhS55VS6n5g97jg5MTmLgpZd0JFuJu+4CbrhB/S2ecbuvv77x3fL009rkGbiwGXDjc881ju/sBl03872/8eWXgbe+Ffj+99XzbGYGKJWwZlaB3XLkCLbs2RN+bu7ff6FNg6OjGPTZQOKo14HLLgMKBdy8f3/08Xfcofv4wQeBH/zgwlery2Wsln0y+xy/7qc/1b6jAPL5vHoWve1t6n1uwkc/qlVUG2bHbcf+/dhx/fXa2uALX7hwSM+pU+pas8/M3MAAcOwYlp05g2Wz1hCbenqw6fWvv/Def92zz9oDkK1erTYQDh5U/05OYvWePcqiYDaV2WJcl86nEfRhADws51oAR+epLhkyZIiLtKMQA+rFeMst6ZY5FyBTJFN/lErNRSAmmIIGBYF6OUeNg8tnL6kPrMuczeYH29nZaB4oTYh9ghtFwRbEicxT0zAh5v/LPuQ5MW3lNusDazo+7vc2NGtCvGZN2CLAZm4uIU2IZcAU19wwmQ1HtcN3XrW3h30j04hC3GwQJ18f2KQmxMVi+BqDg/p/23ym76emNMGSqaBMPrD83FzOPl9cgWdMwXWoHPLhJdgCOAHq2SXdNbq61LUvvVTVlZQ2fs0g0FYeW7aEx4KbEPMATnz+tbeHr0tl8+dluaz8WX/zN9Vmjct1wWTmLWEzWzaZEJNZKzch5n6b1K6ODt3eVpgQB4HaqHjb2/yO530i+9w0z6i/qQ94ACfAHsQJ8Lun6fyxMa1KA+G/afOG+pasEcbGdF92dqr+o/KiAjlNTuryfJ/HCxzzSWAfAPCe2WjErwVwvl6vWySCDBkyLDjw4EVpYi79V9MCvRBML7DVq90vPV/YggatWBEd9KpZAmvyQ3W9BG2+SZLAyoBdNgIbN5CTjWiWSo05h4FkUYh5uVE+r6bvedAb23GL1QdWmn/6zH/yKeYE1hXAiWAisJQDNa1gVB0dYfLEF442zKUPbFICKwMfye/4NXj6GhuB5T6wtPCXRMy0eRQE+plRqdifZy4Ca3oe0XyRVgqcwEp/5lwuvAHX16fr87rXhf1V5RzYulX9ftWrwp+Tz+HQUJgIyiBkpojs/FlaKqm5WKkoi4Pbbw9fx0VgTfNA3k8uAmvygZ2cbEyhU6m0lsDGhexTHnXfdA/LXLCSwLrepXEI7Pj4BUsTAGECOzmp5igRTopizDcMurrCaXlcBFamO0pjPbIA0DIT4iAIPgdgF4D+IAgOA/jPAIoAUK/X/yeArwO4E8A+AGMAfqVVdcmQIUML0AoFdrGCXvymFxgP5tEMbGlbfAh/swQWUIsnHlQiqQLrmxNSXjsObEGcTGSHHx+XwFKeTVvwLp5KxIRSKRx8I04aHdPxEkkJXLPEj5MdwG/BRH3IyZkr7Yf8zLQpkRaBlQos1U0GWZHXd6EVCqyEDIhlKstWj2IxPoE1KbB0P9sUWKpfV5da0LtywMYlsPTZiRPhfoiKKtvbq10WeET7tWvD9ZPz+sYbgauvbiyTAtuNjuogTzKfLinePM8nnUsol8Nlu6xZ0iawnHhT2ZzA8ty2dK9QP0sCSxsIc01g29p0wLHJSfPYSwLLAzgBzRNYOn983K7AAuFUVMuXq/kwNqbnJb1jqTwXgSXQMUtEgW0Zga3X6w7HE6Ber9cBfKBV18+QIUOLkXYU4sUMlwlxGubDsmz+Urb5vXCkQWA5IQPSMSE2Xdt0blomxFEENokJsS3tU5QJMaD6kOdWNJkQt7W5zTxdWCgKrM+CiZt5b96syMAVV4SPcanzrSawcowrlcZFJ0czY5PL2YOgyTywtIFimiPNKLDShJiPqanuXIGllCuAvt9XrVIBdeTcoPpJomtCXBNi+uzUKZ1KBoiOKss3K0Qwo9B38poyJQ8hl1PEaGgIOH5cfUYKGkEqsFQ2V2CjCKzL6sM0D2wm+i4C29kZbUJMfTTfCqyc//Qcoo2ChaTAyhgPIyO6b3t6tH/1rP92w/3iQ2CpvEyBzZAhw0WNtPPALma4TIjTWkTzl700IY5CWgosx1wS2DRNiIF0TYhdKYwILgWWw0Rgmxm7+SCwvb2NdfZZMFHfkk+kNI8E/E2I6f+0Fsjt7Y0kPMoPNunYXHaZCrhGC1UJale5rNS+ctlsFg807wPL+5Y/Z2y+/pzAEmkhQrBzpwp+c911jXXkx9kIrMwnK2HaJOH+hhxUN5cCS5AE1lS+D5YtUwSWgunJ55wksNQe/ryUfSD7I64CKwlwXB9Y7lfJCSyZTPsQ2NngXi2BzSXDZgIO6HExEViZckkiLoHlG2BRBLazUwU7o76kPqY54LIGISwxBTZbfWbIkCEZMgVWw6XApgVTHljArUoQWkFgXS9BF4HleVhNymoaCmxcAutrQmwq12WCafqbo1kCG9Uv80FgTelP4iqwNsQlsGn6wMrciVG5YJMEcSoWFXF3jSt/7t59t4qyCpifPT55YF3zl9qwcmXYxNtUJie83AeW7ucgaAyQxOtNRNH2POvqco+nS4HlZvr1uo68OzAQX4GNuqYN1A+kwMr5JE22qWz+PGzGhNgWxInfm3F9YKtVTWyJwHZ1xfOBbWXMC3kPUltdrhmy7pzAmiwxOJIosJQeTuaF5SbEPT2NzxuqJ238XIQKbEZgM2TIkAyZD6yGS4FNCzYF1mcMmiFBtuNcO9GuIE5BoBderVJgo4ItJTUhjqPA+hBY2S5THzez+TAfPrAmAhvHBzbK5NX2WSsJbFtbY1lRBDbq2qax27lTLVZd42p77iZRYKNMiKlvo/xfqSyTD6y8n2335tVXq3Q2ttRc9OywXd+0SUL3DidQe/aoVC5tbSqS71wTWCKH0qfaZkLMXQjkhpYMtMX7xkeBBRpNlHkdOUw+sNPTjQS2u3vxEFjTPUzjIhXYQiF6vOP6wFar2ieaCCyNB1dge3sb76MkBDZTYDNkyJABrYtCvBjhCuKUFmw+sD5wvXiTKLAyTYyEKbonoIlrXAIrrx2FuEGckpoQmyIJyzJN1yNEKbCFgjuoTasUWApOlQStJLBxFNg0oxCb0KwJsaxbT4+Kcht1rs3yxfZZVBAnVxRiCmC0bZu93vx4rsD6Elj6v1AIR/iVoIW6rW98FNjpaeAf/1H9vWuX+t5lQlypuBf7cU2IOZYvD//PFe8g0HOdq+SmDS2bSwYfJ9+I8TYCW6sp8kM+viYFlsiWicDy8uaTwNLmz+bNqh2XXtp4Do2TyYQ4ivj5PG9o3VStqvlIfrBEZKk/uALb29u4KSwJbJQZ9syMPiYjsBkyZLiokSmwGnNhQtwMgU3bhJj87lwwEdGoiKSAWb3l137LW9zXBZIHcUpiQtyMAhtFYIOgUalxHR/3extcSlfUeTxYDsFnwcR9YG2YLxNiE5o1Iab0MYSdO/U5aSmwUSbE3JzfVN7OncAHP6jTw9iuQ2WZgjjJ+Wu7N6Pg2vQCzHOMxoiI1KOPKt/i/n7g+uvVZ6ZnY2enaqdLfQWSKbAESWC5AsvnLn/GmFwKbATWpOaa4ENgeYRhvnlZrWrTYlJgly2Lp8DyNEVpw/Q8LZdVrvkPf7gxWjrQqMDygF9pEFge6Iv7wVIf06YRJ7B9feH5k8/rMujzKAWWq6+t6u85RkZgM2TIkAyZD6zGfJoQ+yCtKMQEH5NeE4GlBaVrMWqaU3S9yy5TQWDWrg1/byOk8v9moxC32oTYdNx8EFgg2VweGDAraPOhwLZ6g61ZE2JpxcCjifv6wHIkiULseoZTuhFTsCETbCbEkqiZctX6gIhWHBNies5Uq4o0ff/76v83vUlf1/RspI2jKAIbR8mSCqwsWxJY3i+bNysVjqLRcvgosK77T/rYAnYCK5/bJh/Ynh49ViYCOzXVGMRJ9k1aMD3/aMxs6c9cJsRR7z3fZyYPLnbmjFJHqf+IwJ47p8hzPq+eNbyPKJ8toD+PCuK0xMyHgYzAZsiQISmyKMQac0FgbUGcfFAo2BfFSRRYn5egXPiWy7oMWgjF8b8NAuDWW9X/r351+Ptdu8IL44UWhdjXhNjUH64gXa3KAwskW+jYzAF91FAeJMiG+fKBNaFZE2IgXD9OaJKYEKcdhdhWD18TYl8F1vcdEqXAmkgaV2BfeUUt4pct04oyN9uV8CGwuZz/fSKfh7JsXhdJYN/zHuA3fkP1ryRRfCPF9sxpVoHlAZyoroAaY0r3RES2t1cHO5qeVt/bFFi6R30CESaBi8DS9SVow8UUxClqrH03Y2QgJx7NmZ6hp0/rYwuF8H1ULjcGP5NBoCSWWAAnICOwGTJkSIpMgdWYaxPiJAtz24I7qQlxFOSCjSsFLhNiE8pl4Mor9cv9sst0GX19KvALX1wsFRNiYP4UWJ/8whIuVTJq4ZTUhHgu8sCa0KwJMT9G+jYmMSFOEoXYZUJsq4crajHN54kJbXrZ3R0+J6kJscsH1jbWXIElU01SuAD3GPoQWMCfEFQquq3t7Y3n2UyIAdWvuZw24eWgNhYKjXllferoQ2CPHFG/qe84gQUUSSWFr7c3HBuAfD2J6EoT4lYSWNOGF3+GuAhsq3xggcZUOmNjuv9oztH129tVP0kCS9datUq1c2ysMV0UR6bAZsiQIcMsMgVWY6EHcQLmnsBKX1ZOYKPUFIn2dqWyEgoFnU/yzW9WfcMXaXGDOCU1IXYFcUrLhNgVxGmhEViXKhm10F/IaXRMiFJgfa5Nx0g/wCgFNgga+2khKbC0WCZVMQ0Cy4mahG1u0TlTU1rR4qTUNYa9vekSWEojRNc13ft8LvN+caV9sT1L0ySwL7+sfm/YEL4WbVJwdY/KoN/SjHguCWwSBdZmQlwspm9CPD6uLANOnlTpdMplHW2bH5vPh/tIpqKjjQWa4wDw5JPApz6lxyZTYDNkyJBhFpkCq5HLRasZzWKxEViXAhuXwK5a1bjIuf6lpmLZAAAgAElEQVR6FUWSzAFdBNaVRocH00liQuwKgkPwVWBNioEr4EarohAD6RNYX/O7tNLoREXgbRb5vLtNcRRYSZRc48qD+8j6mOoYZZId12TbRWDld+QX22oF1jYOdA5XYH0J7PLljf67JiQJ5FSpNPatyweWPndFdpf9klYQp1oNOHRI/b1+fbhsInek/PEIxSYCW6tpf2RAz0/Zz2ndt0kIbEeHmqPT07q+VFbaCuzYmLrOiy/qugVBeJyJwPI+4gpssagJ7KlT+phHHlHjtn+/+j9TYDNkyJBhFlkU4jB4vr5WgBZ+tuATUUiTwPq8BLmpHtAcgTWRuO5u4O1vN9cpjgkx78uo6LtJTYhtZfoosC5EHd/MhspiUmBtimQrN5QAtwlqHB9YU0qVqHLlXEwShZiTJte1oq4D6HHgzwkfAutjxVMo6PvbVCfb3OLBhEwmxK75umGD3/xJkkqnoyMegfVRYG1+/VF15IofJ7D1uvr72DFFsvr6Gq9F5I6rey4CS39HKbA86nUzSEJgeQqjyclwFOK0FFgehRjQBJbSOpkIbKUS7lu+KSsV2GpV/02+sXStjMBmyJDhokexmJkQc7S1zY0CK32dfGFbrMUJpETwVWC5347JB9b32jbYVIY4QZx8iAAh7SjEPj6wLrTShLivL/793YwC20waHdM9MRcEttno3jYF1nYuJ+py3toierv6Mwjiq8hRAcnkvE9DgeUky3R9WxtI8UyiwEaZiBPSUmBlECeTBYepTrZ4Ar4ElsgR0Oi7CgAHD6rfZD7MrxVXgSVlN4rAXnaZ/yZtlIm8BH+G2K5B84mng2qVDywAHDigP+/uDr8rKYhTsRh+b3IFlmJDkAJ74oTegCACSwpsZkKcIUOGix5kNptBYS4JbBLYXly+JIcf50NgAW1yBoRfyqTMNEOwJHj7bCqPicDK/nTVaT6COLnQShPiQsHPB5CjlQqszeLDZro/3wqsz7VpfKQC64oYTkTOZ+MlisAC7nFJQmClAivHISmBddUpisAODakoucVi2LXBl6S6EIcQbNqk6rBxY/oKbFICC7jNiMn/lT/LJYE1KbCcBNJvG4Ftbw+P4caN5nzgpngApuNkPTmiFFhA99fkZGvT6FC/HT2qP+/uNiuwhYIef67AFgqNkYuPHdPnZwpshgwZMhjgS2QuBrTahNg3Uq4Nc+0DC9gJbBCo/1tFYJtRYF11SjuNTqtNiJvt37hmxGkQWNs9ZCN180lgXfkr45gQ+yqw/PM0TIiB1hJYkwIrlXIflZ+TlDgmxERWufrKr98KAuvqz82bgfvuA664wnzvr1unzEG3bzf7wJrqS+bVrSCw9XpjACdeHx8CS8fYCCy1k1TY5cvVfWUipqbnkSnfuKwnhw+BpWM4gW2lAkspiFwmxMVimMDSfVMsqr7L54Hz51U/mwhspsBmyJAhA0OrF4iLCTywQivAX1hJMNc+sICdwAJhn540wOs0VybEzUYh5n2aJKr3YiKwvkGcbObxtk2TfN4ebKjVPvrbt9u/81VgTSlVfDZFfE2Io/ogLRNiUnvj+sC2UoGVGwxyo6AVBHbNGvfx0hqEUCgoMvaBD6gI6zKNDmCvb2dnch9YwExgJyZUdFzKncvdQWgMTFGI6Tu6pkuBpfRAgLZC2Ljx/2/v3oMlOcv7jv+ec86c++6eve9K2uiCFksCwYLERRALSYAQpCxhI2KpCAYbrLjKwnHskIIkvmG7HIwTquLCWFBWQTBkcQTYikvFxcaK7YBBCAsJCYQlTGKB7qsFLUIrrfbNH90v09On79Pd0z3n+6na2nNm+sy80/NOTz/9PO/7rm+TFGwXn1dBKh/A5i2jIw33c9NjYH3g6vefX3IqXkIcz8DGl9yamRn27Yceyg5gycACgKqNxZxWbWVgqwbJk8jA7tw5PJGJB7BNZmDTTpKjJXpeV0qIq+yLvBLRcS+olAlgo2VtSYquA5s0IZN//CRmyX07a4boupx8cvLrKjpOPa1Mu64M7LglxGVmIfbbR9voA5TobVUC2GgwU2YZnbYDWDNpz55if5cUwEYVzcBKycfS6IR0eZ+9aBDof77xxuHkQtELkdH2jFtCHG2zz8CeemrwfzyA3bw5+XU0kYH1+/lb35KOHBk+Vl0ZWP9aDx0KAmS//7ZsCR4jmoFdXh5+z5x+enDfaacN7/ev0Qf3990XXHjwHn00WIOXZXQAAInaGgNbZwa2zIRQVQJYs6AsLinIWF2tdwx1mRLi6P1tlBCnbRPdj1XeV7P0vysSvOQpE8BmjQeVimdgpXIBbNpzt1FCPDubnIUtM648aamWtM9F2cqBIiXEWfu1TAZWGl0L1j92fGbvogHsvn3Dn6tmYOMXzeIZvLoD2G3bigcIeePfi46BldIvBhYNYKPB4kUXBZ+nu++W/uIvgtui5cPRtmYFsEUysNG+54O6tAzs5s3J7/M4AWzaZ8MfTz73uWEGc3GxvgysX7v1+PEg2PT7b20tOwN79tnSL//ycB9J6wPYO+4IHnf79qC/HD8eZHrJwAIAEnV9Eqekk58yQVOVAFYKrt77q8hRbZYQx8v2oifVbcxCnPaYMzPD+6oG81kT/oxr69byZXFpio6BlZJPLLP2T9rFmTaGOJx55vrbygSwdWVgq8xCLGVfwBo3gPWfySrL6LziFcMT+apjYOP9Ir6v8y66FBF97p07q83qLhXLwKa1d2UlfRx43lq/0uj+3blTesMbgsf0M9nGA9joMjrO1RfAbt8+bEvRDGzVSZyyLt6+7GVBJvj004Og8ZWvDALEvM9SmePN3r3B//feOwwut21bn4GNjoGV1l8Q8rf7iZy++c3h40cnMUvKwGYF/z3AADYAqEPXJ3FK+vIv81hVZiGWggD2ttvW3952CXF8PODcXFC+NW4JcdpJS5ESYkl61rOCE4m8sXNpigQ7Vc3MBCdG0TFVaZoOYLP63CQD2NNOC4IEf6IuFd/3c3PJGdgqY2CrlhBnqRLARv/Gv+dVMrBbt0ovf7n0iU+MZqTKLKPjT/x9pjAewNZRThkPYKsMyZCyJ2Hy26a1d3V1OJ4y/phlS7SlYRD7x38c7Nv4fvP96vjx4F/SMjr+MxkNYH3gmhbA+vLhpDalZWBXV4dticsaA5vVj886S/qpnxq9rUjmsmwAe9ttwbHVB5fbt2dnYJOeJx7A+osOe/YE+/y++4LJnfzFA//6FxfrW293QghgAaAOXZ/EyS8D4L/IpHJZPx8APvVUuTKkE04YnQDEa3sW4rSMR5kS4qQZVMcpIZakSy9Nv6+IIs8/jl276glgi64DG//ZqxLANj2JkxTs//37pdtvH33uon+blIEtklWvq4Q4r31xdWdg096jpaXg4s7NN+dnYLP61vx8EMCuro72oaWletYxjz73zp3F+lxS38zLwMYvDkStro5eQMl6niRJmbidO6W3vCXYR0mZysFgOEtvUgY2KYD1+zspgN2yRXra04a/Fw1g/XNGv9eibYwrEsDmTf6UpmoG1u+PHTuC92t5Ofjnv1/ilT5J3y1+hm0fwO7dKx0+HPzsx8RGZy8+66zeT8JJCTEA1KHrJcRS8dlO0/iT0zIZ2Lk56elPX3972xnYogFsVrlv/ERu3BLiOjRZQiwVHwfbtRLiNiZx8uJlxE1lYLP6VFoGdpwgPqkdWa9tYWH0ffLvS9kS4sXF4eftVa9aP+tqXFbf8seqJsa/SsMyXal4CXGRybHiAWxWe7PGwBbJMvssX9LfpwX50XGwWQFs1jI68fGo+/cPf48HsFu2JAewi4vljoH+u6BsAFt3BtZP9nX//cOJonbtGu7zN785+OdLndOqL6ITE0YvFEdLiH0AG+0LZ59dvK0dRQALAHXoegmxtP4kqEoAWyUwOOOM9bdt2lTv/opmG8pkYIuWECe1tUgAW2airCqaLCGW0gPY+P7MCwiy9pW/P+lnr6slxFJw4p10UplnbS35xDit3VWW0RknyzjuLMRJJcRJF4Hiou/nnj2jryHp+bP6hr+viRmIvaWl4HXt2FHsvU/ar3mTOOUFsGljYIsEsGbZY0mT+PY+/ngQpPollNIysEePDteWTcrA+vZ6Cwuj+yRtDGzZANY/dlY/LtvHsv4uzeJiUDb91FPD8u/du4ePsXVrELQnfe+nVff4MuK1tWBfxQNYf6zZtGn9uOYeIoAFgDrUVZKWpo4MbB0BbJnsq5c0+cjmzfUGdmbDE5ykSZzSxpgVLSFOem+LzEJcZ5Y5SdMB7AknrL9tZmb97LtFAoKsk+kmSojbCmAXFkYDpKLPu3t38u1ps0t3vYS4SgY2KYDN6ifxNpllZz39SXsTEzh5S0tB0DAYVA9g4xcnosfGpjOwUvUA1s/S64P4+IRT8Umc/FjV6AR2SeJBdVIJsX/vyx4D8y42t5GBlYZlxNJwndu0THxaABu9SOWrDPzj+gD20KHgf98Xzj672XOVlvT/FQBAF6yuNptpG3cMrFRPAFvXNPxNfIH6L+i6Soij72fZDOzMTH7WsQ5FllwZx8rK+pP/vXvXB1/jBrB9ncTJi44jLPqeZ80CWiTISbsvuk3XA9ikx8vqS/E2+aV60vggyGenvKTS7aqWloaPX7WEOOviRF4Gdnk5/TGbCmD9+/bd7wb/++fJC2B99rVIJY9v08xM8Hjz86Pv9eJi9gWMrAC2iRLishVF0QB2aSl4jWlLwBWpvnjGM4J99uxnB7/744sfF+tfwxSUD0tM4gQA9ahzTdMkXSghHgySZ3vsCv8FXVcJ8cknB4vZS+kZ2LwToaaDqKbHwErBTNIPPzz8fd++9QFAkQA26yRwnDGwaevAtjGJk1clgC27hE1WkJO0/aQzsP59iT5OvD1J711W0BV//ryKkNe9LrgAc9ppo7fHx8SOY2lpuI5pkfc+qc1mw0nykt7brM/X7GzyxZAyGdiyS6okZWCjtydN4nT8eLUAdtOmYb9ZXByOufXHk6Rjg9+fSRYWhmNzk7QxiZM0GsAuLgb7zI+H9fIysP6+o0eDaplf+qXh7fH31M8o7cff9hwZWACoQ5PZV6nfJcRtSSshrjoLcXRynrSsYNb7PjfXfAY27cS2zueNj5eqGsA2lYFNy1ZOKgNbx/PmBY9FM7B1T+KUF8BG/8YvB5KVgU2aQKhMBjYvM3bmmdL5569/3qTZn6uKZmCrlhBL6RfV8jKw0jCAjj9e0yXEjz4a/B8f7+zf+zoysFu2DG+Lvt/+57SLPWnH5qYysOMEsEtLwb+0EuK0ZXSk7BLq6Pu/tBRUzjR9rtISAlgA6IMuZGD7EsCWKSFOm83VbHScZ1IgkHdSU3RM3DjSTlDrzsBGnXRS/RnYccbAJp2QtTkLsVQtA5uljjGwky4hLhLAmq3PwpYZA5t3PEp7L+rOwI5bQiwN25p0US1vzO64Gdiy+yOegfVrwPrPog8+6whgo68t+nqyMrBZn8G8AHacSZzKBIfLy8Pg3JeBp30f5WVg00T33eJifUOAOoAAFgD6wJ/4TToD2+UvwLQSYj9DZlReBnb37tFZIMsGVf6xmg6i0gLHOp9369bRk8ktW4L96QOU6ARaWZrKwCYZDLpfQpyl7DjJJkqIy85CnFZCnBXASsN+5GVdDIk/f5GLSHFLS/XPQuwDwCKfu7wMbNLFibwANmm/lglg42OE88QD2MXF5Ox7dBbiJ54YP4CNvt/+tdUdwFbNwM7MFN/fns/C+jk0imRgy6xdHg/+u3wBuiQCWADogzoysPETxbLjdqcxA5t2MrBv32h2KG29yizTUkJsNszC7ts3vN1nYZeXi2Uexglgy/bVvPLuukXLHJvKwPZtEicfgNQZwNaRgd2+vd6+sWfPsB1pM0hHlc3Amo32r6LKTOK0tlbuopffNpqBjb4uv5avH/d67FgwmdCxY8O/z7vAlBfA5pUQp1lYKD8LcdHvvbIXRnwA69dwTZvEKRrckoGVRAALAP3QRAC7kUqI05bRSSvZ8oGa32dl1yaVpqeEWMoPYIsoOolTlX0d1/YyEW2MgW27hDi+nEva83jxMbBJAWxS4Bg/LuUttxR97VUysHWWD0tBSX1U3sWWtL6cdkyShgFOGWUysH4Zl6L8fn388eD/paX1/dPvB5+FlerNwDZVQlw1AyuVD2DPOUc67zzpkkuC39MysNH7qgawZGABAK2rYxKncQPYwaDbX4B+Qpj4SXLVDKw03GdJgUBeFqeNALaNDKw0nMgpGsD6iXCKnrQ1tQ5sFywsDNvYVAlxWgY2bcbVcUuIk7KJWcef+fnyy+hI5TKw0mibqmRg6w5g422omoFNOyZJ1TJnZQJYqVoA6zURwPp+Ec0+d3kMrFR+feGVFenii6VTTkl+7mhfyBojnWaKM7AsowMAfVBHBtafYPoTiioZ2C4vgO7L1uLKBrCrq8OMR1YGNk8bM+G2MQZWknbtCvZFdAmGpjKwSWuFtjmetarNm6UHH2x/Eqe0yWPGnYXYP2c0AClSQvz0p4+WE5cNYPOCrujjVcnA1jkDcZK8DGzZEmKpWslzXqAWV2YcbBsBrO9DdWdgFxa6k4GN/13TGVgCWABAq+qYxEkKThYPHQp+rhLAtjmza1lJS3JI2ZM4JZUQ+/GvUnYGNk8bGdjFxaCtfrH66HPXaWZGesELRvdv2QC26hjYptdYrosPYNsuIU57vnFLiJPakRUQ+3HHV145+rdZ68BK/c/AFnnOqCoZ2Co2bSoX+HYtgJWCC4nRrGYdY2C7VEIc/7siGdi0YS9J4sF/1ytZSujwpXQAwA/VkYGVRk8Wp3EMbNkANikDGy2T7XoAmzYDcBPP+7znjf5eNoDN6jtZAWyX+1yUP1lsexKntBPYcUuI4+3IWyZkfn70/qQT7rwAtsjEZ9H7y2ZgZ2aS10yt07iTONV1kTBpaZ0s4wSwfhkdb25u+DqPHh3eXjaAPeGE0T4zqTGwRS+ilS0h9vwxNGts+zglxGaUEAMAJqArAWyXs2FpJcRJQV7ZALZqCXHTAawUnPw89tjobU08b/zkZ2EhOGErGsBmtSlrDOxGDGDLLKOT9nx1ZGCj7cgLOMyC7X3AklTlkBfAFulL0ccrm4EtO9tuFeNO4lRnBraMbduGMwfnKZKB9cMwDh2STjst+PkHPwj+L1rNc+KJ65/HGyeAzdrH8XYtLBT/HI2bgU2bhTjarjIlxPPz0kUXDS9m9eVYWgABLAD0QR2TOEkbMwMrrQ++0k4GFhaGSxtI42dg2yi5bisDm2TbtnoC2GkpIZaaKyEum4Gtu4S4yOtaWBgGsFUysEX60jglxE2XDyc9Z1xbJcRls4Gzs8H44AcfzN82XhYerzaZnR3u6+jj+Z+3by/2OuMBbNI6sFWW0cnqy34iQD8so8x3Xlb/XV2VXvKSIKC/7z7pH/9x/d/55XL8ckNFSojTXqt/nB/90eFtZGABAK3yJ351ZmCrrAPb5S/A2dn0cZZlMrBRXS8hlpJPmtoaq9xEABt/T7p80SSq6RLismNgmyghzhN9r5JOuJNKkKOTyxWZNXecEuIuB7B1lxBXee937CgWwEbb6NeBjvdPX5L80EPD2/1j79pV7HXu3j36ex0lxHmVRP61+LG7Zb7z0i4azMxIl18+nG34+HHpXe8aZqSjx9C0ALZsBnbr1vXvZV+OpQUwBhYA+qALGdiuL6MjpZ9ApGVg87IA45QQTzKAbSsDu3178QA2q+9OQwmxX+6jK2Ngk5bBGacddQSwaUGV/5w1XULc9AzEUvVZiOvOwFZRdBxsdL8mZUKjAWw0iHrggeD/ogFsfF/UEcCa5Weny2T5o9L678teNgxepeBzsH//8PfohZu0i3llx8DG+/pg0I/Z3AsigAWAPpiZSV/vsYzouKhpKyGW1s9o6qVNjpF3EuWv1lfJZrSxjI7UnxLimZnsctfodlFd73Ne18bA1tGWcQJYv330uJUXwJKBnZ4AdsuWoA88+qj0+OPSk09KjzwS9IHt26sdG/37HZ0EqmwJsZQfwJZZqikq6Vh4xhnSeeetv/1HfiT57/IuVBXNwPpJ9ry+HEcLIoAFgD7wswhWWQ8wapwM7MpKt9eBlYqP+yqT7Vhd7V8JcRcDWCl7wiGvr2Ng/bqVTYyBjZcDF8nAJj1OWWkn1mmSMrDRv037HPnPbdkxsHl9o08B7LRlYGdmhvv7oYeGpcTbthWfhTjOT4wX/S4sm4GV0i90Jv19mcBvMFjfnmc9K/l7+/TTh/sh7UJR1TGwZsNJtLwuD/+poONnIgCAH6rjCuo4AWwfyo+aCmD7VkLc1hjYHTvKBZhVAti+ZA7MgixsEyXE8SVsigaw4/aD6ElwkceK9oWkJXjSLsCVycD6dhSZHTbahrW16rPElpH1eYgvNRRVtCqkSdu3F7tImhfA+tcQLSOOlg9HtykrvhxMExnYMln+uHgfiweS3sKCdPLJwzHEXnS/JP1cpIR4cXH9a+zLcbQgAlgA6Is6voD8l2Xemo59VTaALXISVTUD29YyOpMsIc46IU+S1q5pGAMrBQFsHQFIPAiK77e2SoijJ99FHistAzsYZH+GyoyB9Y9bpF/MzAz31YED7Rzz8iYQyvu7SV4oHAyKrZNbJAMrjc5E7MfC+qC26uuMB7B+FuS09iXJ+4y2EcBKQRlxfPs6MrBLS+sflwwsAGAi6vgCmp1dv+j8NMkrDfPaysC2kU2ZZAlxWdNcQiwN19IcV1IGNqpoBnbcYCgazJQpITYb3Q9zc8UC2DJjYIseD/32z352se3HVTWA7UIJsbR+7GSSogFsdCbiujKwS0vr+0nZADZPmYnC4qLH44WF7D6dFMCmTeJUZgxs0j7q04XAAlhGBwD6oq4voNXV4fT906apEuIq+6utEuKkJYK6ml2vEsB2NRhPUtcst3kn5EUD2HGVLSH2x6jBYH1Z5CQysH77vXuLZRbrkFdCnKYLGVhpOBlZlmh/9O9ZVgAbnYnY3zZOCXF8P87PS489lty+KsbJwEa/g9bWso/Fa2vSqaeO3lZHBnZxkQwsAKAj6gxg+xQUlLERS4izStC6Jml/+Bm2vaLLRHRRkexVEWUysE3un/n5Yf8qG8BG5V1UqbKMTpkA9sCBYtvWIWniKP/6imRgJ/35jc5Unyb6mc3KwG7dGmx7+HDwb2Zm+BmpawyslF9yX1bVSZyk0T5c5KJJvDIgbxbi+PExKcNLCTEAoDPq+gJaXe1XWWYZZdcknYYS4rxyui5JC2Czfu/y64mbtgysNMzClglg49tOsoR4dVU666xi29Yh/l6trUkvfWnwc1Yw1JUS4iIBbHSN4aQA1r/Xs7Ojn4kdO8Zf0zwpgK27hLiuMbBZ41+9eMa7bAY26TtvaSnYLvo9P2UlxASwANAXZGDzFT35K3OyWHX5oLZKiGdn0yfP6ZqktsXfgz4HsHWVqcbXzO1bAJuUgc36DPnPWJFgoWwJ8YED7fah+MXB5eUgy7ZnTz9KiIsEsFJ2ABtd+ze6NE/053HGwDadgT3zzOFjlv3ejVYBVTkepI2BTQtgZ2fXX/jx+yd6OxlYAMBE1JmB7VNQ0AR/Ql0kMO36OrDS6FX4LmfXpz2ArTP4SFsbMv48TQew/iS8yQB2bi4oLS0ydtu3o+jx8Oyzi21Xl/hrX14OXvvFF/djEqeiAeyWLUFbt2wJfk+7yBJde9cHsEWPvUmKlBAXncwvzdOfLl11VTDhVNMZ2Li8ZXSS9lt86IwPXOMTSk2RDg+UAQCMIANbH7+AfBErK9VOKhcX25tMaXlZeuSR4Ofdu9t5ziqqlBBPekzgpMzPDycPq7qMTh3ayMBKo9m5LFUmcWpTPJjywcVpp2X/XVqGrW1FA9grrwwmTvLBUvx1z81JTzwx+r76GYjHCdIXF7NLhpeW6nnPd+yQfvZnJefK/V2dAWz8c542lnxlJZjp2fNBd7QtU5aB3aDfCgDQQwSw9TErnqmcm6t2Rb/NE9FoqdiJJ7b3vGVNewa2Tl3JwLYxBlYqH8B29YQ8KQPrZQWxXcnArqwEx8e8wG11dfS4mHaRJSmAHafPJgWw0WN50QC8iCrHnnFLiLMmcUrbb2kZ2Oj3wpRlYCkhBoC+oIS4XmX2Z5GlJSYpepJ80kmTa0ceAtjioq87vg+is8B2KYD1gURShiwvgPXBTZ6ysxC3LSuAzdKVAHZmpp4Ldv51bN8evFfLy+XK0dMkrXEaDWAnfaz27/fycrXhHFkZ2LS+Ee9jSSXEXb3gUxEZWADoCzKw9SqzPyd9UpQnutRJ30qI4ydlfV5Gp05ZGVgp2E/Hjk1PCXHRALbrGVhf5ukzmEUD2K6UEEtBFvPRR4tvn/T+Rmcb/umfHh332pcMbBWLi8HrrDqhW9okTmUysEklxF294FNRBz4lAIBC6voCWlwstlzFtJumANa/n3v3Tj6Dk4UxsMVFT8r9RDlRPoBtev8MBsFFryLPMzcXtKvsOrBS8SWIyo6BbZtfYuaJJ4Lfy65N3YXPb9kgMO/CVPyiWt0BbPT3SR+rzYLAscr4Vyl/DGySIpM4dfWCT0WNlhCb2SVmdqeZ3WVmb0u4/41m9qCZ3RL+e3OT7QGAXqvrC8isvuU++qzM/ux6FtCfqHS5fFgqX0I8M9ONE/pJiO6rvXvX3z/uepplrK0Vf56FhWpjYMsugdXVAFYafe+KZmB9X+9Cf687gI0bN4DNmoV40gGsNFouXRZjYAtp7KhnZrOS3iPp5ZLukXSTmV3vnLsjtulHnXNXN9UOAJgadX4BEcBO1xe6P0nu8gROUvkAtusXDprkX7tZ/wLYKiXERXW9hFgKAqrvfz9478q002ewJy0eBG7eLH3ve+nblw1gx3mNCwvrs/ldKiGW6svAxteCTttv0QB2Zmb4fvjvhay/7akmM7DPl3SXc+6bzrknJB2UdFmDzwcA07qglgIAABgDSURBVI0Atl7TFMD6K+1dz8AmTWpCAJvMv3Y/CU6c329t7KOtW7sXwHb58+vbuLRU7nVnZdnaFA8Cn/tcaf/+9O2TgvSs1zHOa0wqRe9SCbHUTAlx0Qzs0tJwH/kAtssXeypqMoA9UdI/RX6/J7wt7jVmdquZXWdm+xpsDwD0W10ngNL4C71Pg2n6Ul9eDk5iksZKdknZMbAbOYD1wX5S9lXqdga2SglxUX4yoD4EsEXHv0b/rguZsngAu2ePdMklxWfBlZorIU7StQzsykr9kzhl9floP4t+r/n3pcuflYrMlV2gt+gDm71W0iucc28Of3+9pOc7594S2Wa7pCPOuaNm9nOS/qVz7qKEx7pK0lWStHv37nMOHjzYSJvrcuTIEa1ycogU9A+koW+07PvfL3+COUGZ/eP4cenwYWnbtnYbVdaTT0oPPTR628LCaLuPHpUOHQp+npsrvj7otHn0UenIkSCjlNRPH3wwmMRp925pZqbZ48fRo6OliVkOHQre02ibf/AD6bHHik/UlOf++7s92/bDDweTOM3Pl3vNDz4YbF/nxUpV+G45dixoi7drVxBMfe97wXEzbmlpfcbx0KGg3yRZXKy3CuiJJ4J9LqVf8GnTkSPVLxI//rj0yCPBz3v2jGacDx9Oz+zee2/w/2Ag7dgR/OycdN99o7clNreb5x4XXnjhzc65c5Pua/Ky3T2SohnVkyR9J7qBc+7hyK/vl/TOpAdyzr1P0vsk6dxzz3UXXHBBrQ2t24033qiutxGTQ/9AGvpGy7785aA0ricy+8eTT0qf/7x0/vmttqm0+++X3vve0dvOOEOKvq6775Y+9KHg5xNOkF772taa1yl/8zfSzTdLb3yjdMop6++/5prgpPUnfkJaWGj2+PHww8NgOc/HPhaceJ9zzvC2O+4IXstrXlNPe/7wD6Wf/Ml6HqsJH/mI9I1vSGeeOdq381xzjfRjP1Z7dUjpvvHYY9Lv/m7w89KSdMUVQSD1+OPS7//++iD2RS9a/zo/+lHpzjuTH/+Zzyy3X/J8+9vS+98fBHdXXlnf41b19a8Hx7Uq/uEfpA9/OPj5Na8ZzS7fcEP6fvu93wsC5/37h9s4J/32b0snn5y5v/t47tFkCfFNkvab2almNi/pCknXRzcws+hlkkslfa3B9gAAMDRNJcSDgXTqqZNuRb6y68BSQtyNEuItW4q/F/PzzY6Blbo/BCI+iU5RXRkDu7Q07F/RLODionT22eu370oJcRfGv0rBhbeq0sbAStnfWb7iIbqNX9Jnmr7rQo19Spxzx8zsakmfkjQr6Vrn3O1m9g5JX3LOXS/pF8zsUknHJB2S9Mam2gMAwIhpGxfU9RmIJcbAljEYpE/gJA3XVq253DT1uYqOr04bA5u3DmwZXRjnmMUHVGWHKHRlFmKzYB8fPhwEsFFJFw8IYEeN0474uNeoIgFsfI335eXp+65TsyXEcs7dIOmG2G2/Gvn57ZLe3mQbAABING1f6m0EMuNiGZ3iBoPsTM7sbLBNnYFhlqKBVdOzEEvTm4FdXGzv/cyTFsAmBeVlA9i6g3QfwHb9wkYRPrifnV3fF+LBaVRaALu0NJUZ2B582wEA0IAp/FLvPALY4gaD7AlpZme7UW4aRwBbPYDt0kU1HwxWzcA2tYxOEr+/u5KBHYffN0n7qGwJsTS1GVgCWADAxjSFX+qd55dAid+W9nsXA7S2zM/nZ2C7uH8IYIcZwSoZ2K7YtCl43+Kz1ybt+6SsbJslxLOzQf+atgxsXFb/8H0tqYS4S/2qJgSwAICNaQq/1DvPbH1wQwY22fx8fzOwTa4DK3U/gK26DmyXjkmbNg2Xz4mqo4S47n5rFnxepikDWzaAJQMLAMAG0MWT/42AALaYXbuyTzz9GNiuIQM7PSXE8fJhaX0AOzOTHFi1GcBKwT6fhgDW77eqASxjYAEAmGJdmSxloyGALSa6/mOSLmdgN3oAOy0lxEkB7Ozs6OtaWko+lrYdwC4sTH8JcZVJnKY0A9vBIx8AAJha8eAmHtiwDmwxXQ5g4+0aDOoNYPOC+0kbDIb/yuhaAJvWv1ZWpMceC35OC9LbnIVYktbWurEE0biyAtisQDSrhLhL/aomZGABAEB7ymRguxigdUWfSoiTlgQZR9erJ+bny49/lbqVKdu8Wdq9O/m+aAY87XW2nYHdvr3+x5yEmZmgfyftv6x+n5WBncIAlm8GAADQHkqI69HVDOziYvJ7upHey8GgfPmw1K1AIyuYjgawVTKwBLDpfPBadh/Nzwf9J/53S0vdujBSkw4e+QAAwNQigK1HVwPYwSA5U9T1st86TUMAmyWadU17nW2uAyutX+6nz+bmypdDmwVBfPyzt7zczePEmKbvFQEAgO7KGwNLAFtMV0uI08ocpzALlGp+vloA25d9RAa2WVUCWCk5iO9LnyqJMbAAAKA9jIGtR1czsGm6GGw3ZTCoNga2LxnYLgaw07CEjlc1gJ2mID4HASwAAGgPJcT16FsASwlxvr7MolukhDj6WlZWRicXaqLfdn1irzLqzMBOKQJYAADQHgLYehDAdlfVEuK+KDsL8ZYto8FVXwL1SZmdJYDNQQALAADakzcG1mx4GwFsuq6OgU2zkQLY2dnRIG/alM3Abt48Glz16cLLJFTNwG7bVn9bOooeBAAA2pOXgZWCAPb48X4FaG0jA9tdZkHWcVqVDWC3bJE2bRr+3qd+Owlzc9X20Qbar2RgAQBAe4oGsNKGOiErjQC229bWJt2C5szODgPXIsvokIEtp2oGdgMhgAUAAO3JKyGO3kYGNh0lxN3WlxmFq1pZCfpfWh/MGgNLAJut6hjYDYQeBAAA2hM/4U1ap5AANh8ZWEzS6qr05JPp98fHwG7dOhwa0Kd+OwlkYHORgQUAAO2JB6VJYwVnZoKTuGlaGqNuBLCYpNXV7JmW4wHs7GwQxErJVRcYIoDNRQ8CAADtiQawc3PJy3DMzJB9zdO3AJYT8umyslIsgDUbTuC0YwcXpooggM1FAAsAANoTDUy3bEk+me1bcDYJfRsDS9AyXYpmYFdXhz/7ABbZCGBzEcACAID2xAPYJGRg8xHkY5KKBrDRz/j27fTZIvhs52LvAACA9hQNYBknl40MDSYpr4TYB2CbNw9vIwNbDBnYXPQiAADQHjKw9ZidJcjH5KyuJo9f95IysASwxRDA5qIXAQCA9kRno11bS96GADYfa0VikvJKiM2Cf9EM7PLy6O9IRgCbi0t3AACgPUUzsGRqsjFODpO0vJydgTUL+mj8M757d7PtmgYEsLkIYAEAQHuiQRclxNX1bRZiTJfZ2WBSprxt4hnXPXuaa9O0oLoiFwEsAABoj9kw8EorJyQ4y0cGFpOWlYGVyMBWRQY2F0c+AADQrsFAWlxMD8DIwOabn2cSJ3Tb/Pz6IHfnzsm0pU/m5rg4lYO9AwAA2jUYSJs2pd9PAJuPDA26buvW9RdZ6Lf5yMDm4tIdAABo12CQPv5VYhInYBps3TrpFvQTY2BzEcACAIB2FQlgycAC/bZt26Rb0E9kYHMRwAIAgHYNBulrwEoEsMA0IANbDQFsLgJYAADQLjKwwPQjA1sNAWwuAlgAANAuAlhg+pGBrYYANhcBLAAAaFdeAMsap0D/LS5OugX9xPEvFwEsAABo1+pq9sktGVgAGxUZ2FwEsAAAoF07dkhm6fcTwALYqAhgcxHAAgCAdu3YkX0/ASyAjYoANhcBLAAAaNfOndn3E8AC2Kjm5oJjIFKxdwAAQLuWl7Pvn5lhEhMAGxPBay72EAAA6BYysACAFASwAACgWwhgAQApCGABAEC3zM4SwAIAEhHAAgCAbpmdZRZOAEAiAlgAANAt8/PZ68QCADYsAlgAANAti4uTbgEAoKMIYAEAQLfMz0+6BQCAjiKABQAA3bKwMOkWAAA6igAWAAB0CwEsACAFASwAAOgWAlgAQAoCWAAA0C0EsACAFASwAACgWwhgAQApCGABAEC3zM5OugUAgI5qNIA1s0vM7E4zu8vM3pZw/4KZfTS8/wtmdkqT7QEAAD1gNukWAAA6qrEA1sxmJb1H0islnSXpSjM7K7bZmyQ94pw7XdK7Jb2zqfYAAAAAAPqtyQzs8yXd5Zz7pnPuCUkHJV0W2+YySR8Mf75O0kvNuOwKAAAAAFjPnHPNPLDZ5ZIucc69Ofz99ZJe4Jy7OrLNV8Nt7gl/vzvc5qHYY10l6SpJ2r179zkHDx5spM11OXLkiFZXVyfdDHQU/QNp6BvIQv9AFvoH0tA3kKWr/ePCCy+82Tl3btJ9cw0+b1ImNR4tF9lGzrn3SXqfJJ177rnuggsuGLtxTbrxxhvV9TZicugfSEPfQBb6B7LQP5CGvoEsfewfTZYQ3yNpX+T3kyR9J20bM5uTtEXSoQbbBAAAAADoqSYD2Jsk7TezU81sXtIVkq6PbXO9pDeEP18u6bOuqZpmAAAAAECvNVZC7Jw7ZmZXS/qUpFlJ1zrnbjezd0j6knPuekl/JOlDZnaXgszrFU21BwAAAADQb02OgZVz7gZJN8Ru+9XIz49Lem2TbQAAAAAATIcmS4gBAAAAAKgNASwAAAAAoBcIYAEAAAAAvUAACwAAAADoBQJYAAAAAEAvEMACAAAAAHqBABYAAAAA0AsEsAAAAACAXiCABQAAAAD0AgEsAAAAAKAXzDk36TaUYmYPSvq/k25Hjh2SHpp0I9BZ9A+koW8gC/0DWegfSEPfQJau9o+TnXM7k+7oXQDbB2b2JefcuZNuB7qJ/oE09A1koX8gC/0DaegbyNLH/kEJMQAAAACgFwhgAQAAAAC9QADbjPdNugHoNPoH0tA3kIX+gSz0D6ShbyBL7/oHY2ABAAAAAL1ABhYAAAAA0AsEsDUys0vM7E4zu8vM3jbp9mDyzOxbZnabmd1iZl8Kb9tmZp8xs38I/9866XaiHWZ2rZk9YGZfjdyW2B8s8N/C48mtZvbcybUcbUjpH79uZt8OjyG3mNmrIve9Pewfd5rZKybTarTBzPaZ2V+Z2dfM7HYz+zfh7Rw/kNU/OH5scGa2aGZfNLOvhH3jN8LbTzWzL4THjo+a2Xx4+0L4+13h/adMsv1pCGBrYmazkt4j6ZWSzpJ0pZmdNdlWoSMudM4diExR/jZJf+mc2y/pL8PfsTF8QNIlsdvS+sMrJe0P/10l6b0ttRGT8wGt7x+S9O7wGHLAOXeDJIXfL1dIekb4N38Qfg9hOh2T9MvOuTMlvVDSz4d9gOMHpPT+IXH82OiOSrrIOfdsSQckXWJmL5T0TgV9Y7+kRyS9Kdz+TZIecc6dLund4XadQwBbn+dLuss5903n3BOSDkq6bMJtQjddJumD4c8flPTqCbYFLXLO/bWkQ7Gb0/rDZZL+uwv8naQ1M9vbTksxCSn9I81lkg4654465/5R0l0KvocwhZxz9zrnvhz+/Kikr0k6URw/oMz+kYbjxwYRHgOOhL8Own9O0kWSrgtvjx87/DHlOkkvNTNrqbmFEcDW50RJ/xT5/R5lHzywMThJnzazm83sqvC23c65e6XgS0fSrom1Dl2Q1h84psC7OiwDvTYy5ID+sUGFJX3PkfQFcfxATKx/SBw/NjwzmzWzWyQ9IOkzku6WdNg5dyzcJPr+/7BvhPd/V9L2dlucjwC2PklXJ5jiGS92zj1XQTnXz5vZ+ZNuEHqDYwqkoPTzaQpKv+6V9F/C2+kfG5CZrUr6mKRfdM59L2vThNvoH1MuoX9w/ICcc0855w5IOklBpv3MpM3C/3vRNwhg63OPpH2R30+S9J0JtQUd4Zz7Tvj/A5I+oeDAcb8v5Qr/f2ByLUQHpPUHjimQc+7+8OTjuKT3a1jmR//YYMxsoCA4+bBz7uPhzRw/ICm5f3D8QJRz7rCkGxWMk14zs7nwruj7/8O+Ed6/RcWHtrSGALY+N0naH87qNa9gcPz1E24TJsjMVsxsk/9Z0sWSvqqgX7wh3OwNkv5sMi1ER6T1h+sl/VQ4m+gLJX3Xlwpi44iNW/xxBccQKegfV4QzRp6qYLKeL7bdPrQjHIP2R5K+5pz7r5G7OH4gtX9w/ICZ7TSztfDnJUkvUzBG+q8kXR5uFj92+GPK5ZI+65zrXAZ2Ln8TFOGcO2ZmV0v6lKRZSdc6526fcLMwWbslfSIc+z4n6SPOuU+a2U2S/sTM3iTp/0l67QTbiBaZ2f+QdIGkHWZ2j6Rfk/SfldwfbpD0KgWTazwm6adbbzBaldI/LjCzAwpKuL4l6V9LknPudjP7E0l3KJiB9Oedc09Not1oxYslvV7SbeFYNkn6D+L4gUBa/7iS48eGt1fSB8NZpmck/Ylz7s/N7A5JB83styT9vYILIAr//5CZ3aUg83rFJBqdxzoYVAMAAAAAsA4lxAAAAACAXiCABQAAAAD0AgEsAAAAAKAXCGABAAAAAL1AAAsAAAAA6AUCWADA1DCz3zGzC8zs1Wb2tpRtft3Mvm1mt5jZ183svWaW+X0YPt5ZOdtcYGZ/Pk77m2ZmHzCzy/O3BACgmwhgAQDT5AWSviDpJZL+JmO7dzvnDkg6S9LZ4fZZXh1u2yvh2n+dfg4zY016AEBhBLAAgN4zs3eZ2a2Snifp85LeLOm9ZvarOX86L2lR0iPh4/ysmd1kZl8xs4+Z2bKZvUjSpZLeFWZtn2Zmp5vZX4TbfdnMnhY+3qqZXRdmdj9sZhY+7jlm9r/N7GYz+5SZ7Q1v/wUzu8PMbjWzgwmv641m9mdm9kkzu9PMfi1y378ysy+GbbrGB5JmdsTM3mFmX5B0XsH999bwdd9qZr8Ruf1PwzbfbmZXRW4feQ4z+5aZ/Ua4L24zszPC7VbM7Nrwsf/ezC6LvK7/aWb/S9Kni7QRAACJABYAMAWcc29VELR+QEEQe6tz7lnOuXek/Mm/NbNbJN0r6RvOuVvC2z/unHuec+7Zkr4m6U3Ouc9Jul7SW51zB5xzd0v6sKT3hNu9KHwcSXqOpF9UkK09TdKLzWwg6fclXe6cO0fStZJ+O9z+bZKe45x7lqSfS2nr8yW9TtIBSa81s3PN7ExJPynpxWEm+alwG0lakfRV59wLnHN/m7fvzOxiSfvD5zkg6RwzOz+8+2fCNp8r6RfMbHvGczzknHuupPdK+nfhbf9R0medc8+TdKGCiwAr4X3nSXqDc+6ivDYCAOBRtgMAmBbPkXSLpDMk3ZGz7budc78XBpfXmdkVzrmDkp5pZr8laU3SqqRPxf/QzDZJOtE59wlJcs49Ht4uSV90zt0T/n6LpFMkHZb0TEmfCbeZ1TDgvVXSh83sTyX9aUpbP+Ocezh8zI9L+ueSjkk6R9JN4WMuSXog3P4pSR/Lef1RF4f//j78fVVBQPvXCoLWHw9v3xfe/nDKc3w8/P9mST8ReexLzcwHtIuS/lnkdR0q0U4AAAhgAQD9ZmYHFGReT5L0kKTl4Ga7RdJ5zrkfpP2tc+5JM/ukpPMlHQwf59XOua+Y2RslXZD0lBnNORr5+SkF37Mm6XbnXFI5778In/tSSb9iZs9wzh2LNzPhd5P0Qefc2xMe83Hn3FMZbYwzSb/jnLtm5EazCyS9TME+fMzMblQQgKY9h3/t/nX7x36Nc+7O2GO/QNL3S7QRAABJlBADAHrOOXdLWEb7DQWlu5+V9Iqw3Dc1eJWCKFdBCfDd4U2bJN0bZmZfF9n00fA+Oee+J+keM3t1+BgLZrac8TR3StppZueF2w/M7BnhzMf7nHN/Jenfa5j1jXu5mW0zsyUFk0n9H0l/KelyM9sVPuY2Mzs567Vm+JSknzGz1fCxTgwfd4ukR8Lg9QxJL6z42G+JjAV+TsU2AgAgiQAWADAFzGyngmDruKQznHN5JcR+DOxXFWQL/yC8/VcUzGL8GUlfj2x/UNJbw4mInibp9QrKa2+V9DlJe9KeyDn3hKTLJb3TzL6ioMz5RQpKif/YzG5TUL77bufc4YSH+FtJHwr/7mPOuS+Fr+8/Sfp02IbPSNqb85q9a8zsnvDf551zn5b0EUmfD9tynYJg/ZOS5sLH/01Jf1fw8aN+U9JA0q1m9tXwdwAAKjPn4pVJAACgC8Iy5nOdc1dPui0AAHQBGVgAAAAAQC+QgQUAAAAA9AIZWAAAAABALxDAAgAAAAB6gQAWAAAAANALBLAAAAAAgF4ggAUAAAAA9AIBLAAAAACgF/4/26yBTaG5P+8AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -170,38 +172,39 @@ " file = files[i]\n", " where = file.tell()\n", " line = file.readline()\n", - " if not line:\n", - " time.sleep(1)\n", - " file.seek(where)\n", - " else:\n", - " count += 1\n", - " losses[i].append(float(line[:-1].split('\\t')[1])) \n", - " currentStep = min([len(l) for l in losses])\n", - " if currentStep > commonStep:\n", - " commonStep = currentStep\n", - " if commonStep % displayStep == 0:\n", - " clear_output(wait=True)\n", - " cutLosses = [l[:commonStep] for l in losses]\n", - " mu = np.array(cutLosses).mean(axis=0)\n", - " sigma = np.array(cutLosses).std(axis=0)\n", - " fig = plt.figure()\n", - " plt.plot(t, mu, lw=2, label='Mean Loss', color='red')\n", - " plt.ylabel(\"Loss\")\n", - " plt.xlabel(\"# Batches per Learner\")\n", - " plt.fill_between(t, mu+sigma, mu-sigma, facecolor='red', alpha=0.5)\n", - " if useMovingAverage and len(mu) > movingAverageWindow:\n", - " muMA = movingAverage(mu, movingAverageWindow)\n", - " plt.plot(t[movingAverageWindow:], muMA[movingAverageWindow:], lw=2, label='Moving Average-' + str(movingAverageWindow) + ' (mean loss)', \n", - " color='orange')\n", - " plt.legend(loc='upper center')\n", - " plt.grid()\n", - " plt.show()\n", - " t.append(t[-1] + 1) \n", - " if commonStep % recordStep == 0:\n", - " if recordUnique:\n", - " fig.savefig(os.path.join(experimentFolder, 'loss' + str(commonStep) + '.png'), dpi=100)\n", + " if line != '' and line[0] != 'T':\n", + " if not line:\n", + " time.sleep(1)\n", + " file.seek(where)\n", " else:\n", - " fig.savefig(os.path.join(experimentFolder, 'loss.png'), dpi=100)" + " count += 1\n", + " losses[i].append(float(line[:-1].split('\\t\\t')[1])) \n", + " currentStep = min([len(l) for l in losses])\n", + " if currentStep > commonStep:\n", + " commonStep = currentStep\n", + " if commonStep % displayStep == 0:\n", + " clear_output(wait=True)\n", + " cutLosses = [l[:commonStep] for l in losses]\n", + " mu = np.array(cutLosses).mean(axis=0)\n", + " sigma = np.array(cutLosses).std(axis=0)\n", + " fig = plt.figure()\n", + " plt.plot(t, mu, lw=2, label='Mean Loss', color='red')\n", + " plt.ylabel(\"Loss\")\n", + " plt.xlabel(\"# Batches per Learner\")\n", + " plt.fill_between(t, mu+sigma, mu-sigma, facecolor='red', alpha=0.5)\n", + " if useMovingAverage and len(mu) > movingAverageWindow:\n", + " muMA = movingAverage(mu, movingAverageWindow)\n", + " plt.plot(t[movingAverageWindow:], muMA[movingAverageWindow:], lw=2, label='Moving Average-' + str(movingAverageWindow) + ' (mean loss)', \n", + " color='orange')\n", + " plt.legend(loc='upper center')\n", + " plt.grid()\n", + " plt.show()\n", + " t.append(t[-1] + 1) \n", + " if commonStep % recordStep == 0:\n", + " if recordUnique:\n", + " fig.savefig(os.path.join(experimentFolder, 'loss' + str(commonStep) + '.png'), dpi=100)\n", + " else:\n", + " fig.savefig(os.path.join(experimentFolder, 'loss.png'), dpi=100)" ] }, { @@ -257,8 +260,8 @@ " if not line:\n", " time.sleep(1)\n", " file.seek(where)\n", - " else:\n", - " losses[i].append(float(line[:-1].split('\\t')[1]))\n", + " elif line and line[0]!='T':\n", + " losses[i].append(float(line[:-1].split('\\t\\t')[1]))\n", " currentStep = min([len(l) for l in losses])\n", " if currentStep > commonStep:\n", " commonStep = currentStep\n", @@ -364,9 +367,9 @@ " for f in files:\n", " where = f.tell()\n", " line = f.readline()\n", - " if line:\n", + " if line and line[0]!='T':\n", " change = True\n", - " parsedLine = line[:-1].split(\"\\t\")\n", + " parsedLine = line[:-1].split(\"\\t\\t\")\n", " lineTimestamp = float(parsedLine[0])\n", " # identify to which point in time this line will go\n", " xPoint = math.ceil((lineTimestamp - startTimestamp) / frequencyStep)\n", @@ -378,9 +381,9 @@ " if displaySync:\n", " where = syncFile.tell()\n", " line = syncFile.readline()\n", - " if line:\n", + " if line and line[0]!='T':\n", " change = True\n", - " parsedLine = line[:-1].split(\"\\t\")\n", + " parsedLine = line[:-1].split(\"\\t\\t\")\n", " lineTimestamp = float(parsedLine[0])\n", " # if model was sent only to one learner it is not a synchronization\n", " if parsedLine[2].count(\".\") > 1:\n", @@ -450,9 +453,21 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python [default]", + "display_name": "Python 3", "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": "3.7.6" } }, "nbformat": 4,