{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "#

Evaluation par les pairs : Concentration de CO2 dans l'atmosphère depuis 1958

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426.35 MLO \n", "2025 427.00 426.21 MLO \n", "2025 427.73 426.19 MLO \n", "2025 429.24 426.47 MLO \n", "2025 430.21 426.80 MLO \n", "2025 429.52 426.93 MLO \n", "2025 427.56 426.76 MLO \n", "2025 -99.99 -99.99 MLO \n", "2025 -99.99 -99.99 MLO \n", "2025 -99.99 -99.99 MLO \n", "2025 -99.99 -99.99 MLO \n", "2025 -99.99 -99.99 MLO \n", "\n", "[816 rows x 10 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_file, skiprows=63)\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ensuite on modifie la première colonne afin de bien les identifier\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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moisdate decimaldate?CO2(ppm)seasonally adjusted(ppm)fit(ppm)seasonally adjusted fit(ppm)CO2 filled(ppm)seasonally adjusted filled(ppm)institut qui fait les mesures
19581212001958.0411-99.99-99.99-99.99-99.99-99.99-99.99MLO
19582212311958.1260-99.99-99.99-99.99-99.99-99.99-99.99MLO
19583212591958.2027315.71314.43316.20314.91315.71314.43MLO
19584212901958.2877317.45315.15317.31314.99317.45315.15MLO
19585213201958.3699317.51314.68317.89315.07317.51314.68MLO
19586213511958.4548-99.99-99.99317.27315.14317.27315.14MLO
19587213811958.5370315.87315.20315.85315.22315.87315.20MLO
19588214121958.6219314.93316.23313.95315.29314.93316.23MLO
19589214431958.7068313.21316.12312.42315.35313.21316.12MLO
195810214731958.7890-99.99-99.99312.41315.41312.41315.41MLO
195811215041958.8740313.33315.21313.60315.46313.33315.21MLO
195812215341958.9562314.67315.43314.77315.52314.67315.43MLO
19591215651959.0411315.58315.52315.64315.57315.58315.52MLO
19592215961959.1260316.49315.83316.30315.64316.49315.83MLO
19593216241959.2027316.65315.37317.00315.70316.65315.37MLO
19594216551959.2877317.72315.41318.10315.77317.72315.41MLO
19595216851959.3699318.29315.46318.69315.85318.29315.46MLO
19596217161959.4548318.15316.00318.08315.94318.15316.00MLO
19597217461959.5370316.54315.87316.67316.03316.54315.87MLO
19598217771959.6219314.79316.10314.79316.13314.79316.10MLO
19599218081959.7068313.84316.76313.28316.22313.84316.76MLO
195910218381959.7890313.33316.35313.31316.31313.33316.35MLO
195911218691959.8740314.81316.69314.53316.40314.81316.69MLO
195912218991959.9562315.58316.35315.72316.48315.58316.35MLO
19601219301960.0410316.43316.37316.63316.56316.43316.37MLO
19602219611960.1257316.98316.33317.30316.64316.98316.33MLO
19603219901960.2049317.58316.27318.04316.71317.58316.27MLO
19604220211960.2896319.03316.69319.14316.79319.03316.69MLO
19605220511960.3716320.03317.19319.70316.86320.03317.19MLO
19606220821960.4563319.58317.44319.05316.92319.58317.44MLO
.................................
20237451222023.5370421.62420.83421.72420.96421.62420.83MLO
20238451532023.6219419.56421.12419.67421.27419.56421.12MLO
20239451842023.7068418.06421.56418.07421.58418.06421.56MLO
202310452142023.7890418.41422.01418.30421.89418.41422.01MLO
202311452452023.8740420.11422.37419.97422.20420.11422.37MLO
202312452752023.9562421.65422.57421.60422.50421.65422.57MLO
20241453062024.0410422.62422.55422.88422.80422.62422.55MLO
20242453372024.1257424.34423.56423.89423.10424.34423.56MLO
20243453662024.2049425.22423.65424.95423.37425.22423.65MLO
20244453972024.2896426.30423.50426.47423.66426.30423.50MLO
20245454272024.3716426.70423.30427.33423.93426.70423.30MLO
20246454582024.4563426.62424.07426.75424.21426.62424.07MLO
20247454882024.5383425.40424.63425.22424.48425.40424.63MLO
20248455192024.6230422.70424.30423.13424.76422.70424.30MLO
20249455502024.7077421.60425.11421.50425.03421.60425.11MLO
202410455802024.7896422.05425.66421.70425.29422.05425.66MLO
202411456112024.8743423.61425.87423.31425.54423.61425.87MLO
202412456412024.9563425.01425.93424.87425.76425.01425.93MLO
20251456722025.0411426.42426.35426.07425.98426.42426.35MLO
20252457032025.1260427.00426.21426.99426.19427.00426.21MLO
20253457312025.2027427.73426.19427.92426.36427.73426.19MLO
20254457622025.2877429.24426.47429.34426.55429.24426.47MLO
20255457922025.3699430.21426.80430.13426.72430.21426.80MLO
20256458232025.4548429.52426.93429.46426.90429.52426.93MLO
20257458532025.5370427.56426.76427.83427.06427.56426.76MLO
20258458842025.6219-99.99-99.99-99.99-99.99-99.99-99.99MLO
20259459152025.7068-99.99-99.99-99.99-99.99-99.99-99.99MLO
202510459452025.7890-99.99-99.99-99.99-99.99-99.99-99.99MLO
202511459762025.8740-99.99-99.99-99.99-99.99-99.99-99.99MLO
202512460062025.9562-99.99-99.99-99.99-99.99-99.99-99.99MLO
\n", "

816 rows × 10 columns

\n", "
" ], "text/plain": [ " mois date decimal date? CO2(ppm) seasonally adjusted(ppm) \\\n", "1958 1 21200 1958.0411 -99.99 -99.99 \n", "1958 2 21231 1958.1260 -99.99 -99.99 \n", "1958 3 21259 1958.2027 315.71 314.43 \n", "1958 4 21290 1958.2877 317.45 315.15 \n", "1958 5 21320 1958.3699 317.51 314.68 \n", "1958 6 21351 1958.4548 -99.99 -99.99 \n", "1958 7 21381 1958.5370 315.87 315.20 \n", "1958 8 21412 1958.6219 314.93 316.23 \n", "1958 9 21443 1958.7068 313.21 316.12 \n", "1958 10 21473 1958.7890 -99.99 -99.99 \n", "1958 11 21504 1958.8740 313.33 315.21 \n", "1958 12 21534 1958.9562 314.67 315.43 \n", "1959 1 21565 1959.0411 315.58 315.52 \n", "1959 2 21596 1959.1260 316.49 315.83 \n", "1959 3 21624 1959.2027 316.65 315.37 \n", "1959 4 21655 1959.2877 317.72 315.41 \n", "1959 5 21685 1959.3699 318.29 315.46 \n", "1959 6 21716 1959.4548 318.15 316.00 \n", "1959 7 21746 1959.5370 316.54 315.87 \n", "1959 8 21777 1959.6219 314.79 316.10 \n", "1959 9 21808 1959.7068 313.84 316.76 \n", "1959 10 21838 1959.7890 313.33 316.35 \n", "1959 11 21869 1959.8740 314.81 316.69 \n", "1959 12 21899 1959.9562 315.58 316.35 \n", "1960 1 21930 1960.0410 316.43 316.37 \n", "1960 2 21961 1960.1257 316.98 316.33 \n", "1960 3 21990 1960.2049 317.58 316.27 \n", "1960 4 22021 1960.2896 319.03 316.69 \n", "1960 5 22051 1960.3716 320.03 317.19 \n", "1960 6 22082 1960.4563 319.58 317.44 \n", "... ... ... ... ... ... \n", "2023 7 45122 2023.5370 421.62 420.83 \n", "2023 8 45153 2023.6219 419.56 421.12 \n", "2023 9 45184 2023.7068 418.06 421.56 \n", "2023 10 45214 2023.7890 418.41 422.01 \n", "2023 11 45245 2023.8740 420.11 422.37 \n", "2023 12 45275 2023.9562 421.65 422.57 \n", "2024 1 45306 2024.0410 422.62 422.55 \n", "2024 2 45337 2024.1257 424.34 423.56 \n", "2024 3 45366 2024.2049 425.22 423.65 \n", "2024 4 45397 2024.2896 426.30 423.50 \n", "2024 5 45427 2024.3716 426.70 423.30 \n", "2024 6 45458 2024.4563 426.62 424.07 \n", "2024 7 45488 2024.5383 425.40 424.63 \n", "2024 8 45519 2024.6230 422.70 424.30 \n", "2024 9 45550 2024.7077 421.60 425.11 \n", "2024 10 45580 2024.7896 422.05 425.66 \n", "2024 11 45611 2024.8743 423.61 425.87 \n", "2024 12 45641 2024.9563 425.01 425.93 \n", "2025 1 45672 2025.0411 426.42 426.35 \n", "2025 2 45703 2025.1260 427.00 426.21 \n", "2025 3 45731 2025.2027 427.73 426.19 \n", "2025 4 45762 2025.2877 429.24 426.47 \n", "2025 5 45792 2025.3699 430.21 426.80 \n", "2025 6 45823 2025.4548 429.52 426.93 \n", "2025 7 45853 2025.5370 427.56 426.76 \n", "2025 8 45884 2025.6219 -99.99 -99.99 \n", "2025 9 45915 2025.7068 -99.99 -99.99 \n", "2025 10 45945 2025.7890 -99.99 -99.99 \n", "2025 11 45976 2025.8740 -99.99 -99.99 \n", "2025 12 46006 2025.9562 -99.99 -99.99 \n", "\n", " fit(ppm) seasonally adjusted fit(ppm) CO2 filled(ppm) \\\n", "1958 -99.99 -99.99 -99.99 \n", "1958 -99.99 -99.99 -99.99 \n", "1958 316.20 314.91 315.71 \n", "1958 317.31 314.99 317.45 \n", "1958 317.89 315.07 317.51 \n", "1958 317.27 315.14 317.27 \n", "1958 315.85 315.22 315.87 \n", "1958 313.95 315.29 314.93 \n", "1958 312.42 315.35 313.21 \n", "1958 312.41 315.41 312.41 \n", "1958 313.60 315.46 313.33 \n", "1958 314.77 315.52 314.67 \n", "1959 315.64 315.57 315.58 \n", "1959 316.30 315.64 316.49 \n", "1959 317.00 315.70 316.65 \n", "1959 318.10 315.77 317.72 \n", "1959 318.69 315.85 318.29 \n", "1959 318.08 315.94 318.15 \n", "1959 316.67 316.03 316.54 \n", "1959 314.79 316.13 314.79 \n", "1959 313.28 316.22 313.84 \n", "1959 313.31 316.31 313.33 \n", "1959 314.53 316.40 314.81 \n", "1959 315.72 316.48 315.58 \n", "1960 316.63 316.56 316.43 \n", "1960 317.30 316.64 316.98 \n", "1960 318.04 316.71 317.58 \n", "1960 319.14 316.79 319.03 \n", "1960 319.70 316.86 320.03 \n", "1960 319.05 316.92 319.58 \n", "... ... ... ... \n", "2023 421.72 420.96 421.62 \n", "2023 419.67 421.27 419.56 \n", "2023 418.07 421.58 418.06 \n", "2023 418.30 421.89 418.41 \n", "2023 419.97 422.20 420.11 \n", "2023 421.60 422.50 421.65 \n", "2024 422.88 422.80 422.62 \n", "2024 423.89 423.10 424.34 \n", "2024 424.95 423.37 425.22 \n", "2024 426.47 423.66 426.30 \n", "2024 427.33 423.93 426.70 \n", "2024 426.75 424.21 426.62 \n", "2024 425.22 424.48 425.40 \n", "2024 423.13 424.76 422.70 \n", "2024 421.50 425.03 421.60 \n", "2024 421.70 425.29 422.05 \n", "2024 423.31 425.54 423.61 \n", "2024 424.87 425.76 425.01 \n", "2025 426.07 425.98 426.42 \n", "2025 426.99 426.19 427.00 \n", "2025 427.92 426.36 427.73 \n", "2025 429.34 426.55 429.24 \n", "2025 430.13 426.72 430.21 \n", "2025 429.46 426.90 429.52 \n", "2025 427.83 427.06 427.56 \n", "2025 -99.99 -99.99 -99.99 \n", "2025 -99.99 -99.99 -99.99 \n", "2025 -99.99 -99.99 -99.99 \n", "2025 -99.99 -99.99 -99.99 \n", "2025 -99.99 -99.99 -99.99 \n", "\n", " seasonally adjusted filled(ppm) institut qui fait les mesures \n", "1958 -99.99 MLO \n", "1958 -99.99 MLO \n", "1958 314.43 MLO \n", "1958 315.15 MLO \n", "1958 314.68 MLO \n", "1958 315.14 MLO \n", "1958 315.20 MLO \n", "1958 316.23 MLO \n", "1958 316.12 MLO \n", "1958 315.41 MLO \n", "1958 315.21 MLO \n", "1958 315.43 MLO \n", "1959 315.52 MLO \n", "1959 315.83 MLO \n", "1959 315.37 MLO \n", "1959 315.41 MLO \n", "1959 315.46 MLO \n", "1959 316.00 MLO \n", "1959 315.87 MLO \n", "1959 316.10 MLO \n", "1959 316.76 MLO \n", "1959 316.35 MLO \n", "1959 316.69 MLO \n", "1959 316.35 MLO \n", "1960 316.37 MLO \n", "1960 316.33 MLO \n", "1960 316.27 MLO \n", "1960 316.69 MLO \n", "1960 317.19 MLO \n", "1960 317.44 MLO \n", "... ... ... \n", "2023 420.83 MLO \n", "2023 421.12 MLO \n", "2023 421.56 MLO \n", "2023 422.01 MLO \n", "2023 422.37 MLO \n", "2023 422.57 MLO \n", "2024 422.55 MLO \n", "2024 423.56 MLO \n", "2024 423.65 MLO \n", "2024 423.50 MLO \n", "2024 423.30 MLO \n", "2024 424.07 MLO \n", "2024 424.63 MLO \n", "2024 424.30 MLO \n", "2024 425.11 MLO \n", "2024 425.66 MLO \n", "2024 425.87 MLO \n", "2024 425.93 MLO \n", "2025 426.35 MLO \n", "2025 426.21 MLO \n", "2025 426.19 MLO \n", "2025 426.47 MLO \n", "2025 426.80 MLO \n", "2025 426.93 MLO \n", "2025 426.76 MLO \n", "2025 -99.99 MLO \n", "2025 -99.99 MLO \n", "2025 -99.99 MLO \n", "2025 -99.99 MLO \n", "2025 -99.99 MLO \n", "\n", "[816 rows x 10 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data.columns = \"mois\", \"date decimal\", \"date?\", \"CO2(ppm)\", \"seasonally adjusted(ppm)\", \"fit(ppm)\",\"seasonally adjusted fit(ppm)\",\"CO2 filled(ppm)\",\"seasonally adjusted filled(ppm)\", \"institut qui fait les mesures\"\n", "\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On décale ensuite les années afin qu'elles ne soit plus en indice" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearmoisdate decimaldate?CO2(ppm)seasonally adjusted(ppm)fit(ppm)seasonally adjusted fit(ppm)CO2 filled(ppm)seasonally adjusted filled(ppm)institut qui fait les mesures
019581212001958.0411-99.99-99.99-99.99-99.99-99.99-99.99MLO
119582212311958.1260-99.99-99.99-99.99-99.99-99.99-99.99MLO
219583212591958.2027315.71314.43316.20314.91315.71314.43MLO
319584212901958.2877317.45315.15317.31314.99317.45315.15MLO
419585213201958.3699317.51314.68317.89315.07317.51314.68MLO
519586213511958.4548-99.99-99.99317.27315.14317.27315.14MLO
619587213811958.5370315.87315.20315.85315.22315.87315.20MLO
719588214121958.6219314.93316.23313.95315.29314.93316.23MLO
819589214431958.7068313.21316.12312.42315.35313.21316.12MLO
9195810214731958.7890-99.99-99.99312.41315.41312.41315.41MLO
10195811215041958.8740313.33315.21313.60315.46313.33315.21MLO
11195812215341958.9562314.67315.43314.77315.52314.67315.43MLO
1219591215651959.0411315.58315.52315.64315.57315.58315.52MLO
1319592215961959.1260316.49315.83316.30315.64316.49315.83MLO
1419593216241959.2027316.65315.37317.00315.70316.65315.37MLO
1519594216551959.2877317.72315.41318.10315.77317.72315.41MLO
1619595216851959.3699318.29315.46318.69315.85318.29315.46MLO
1719596217161959.4548318.15316.00318.08315.94318.15316.00MLO
1819597217461959.5370316.54315.87316.67316.03316.54315.87MLO
1919598217771959.6219314.79316.10314.79316.13314.79316.10MLO
2019599218081959.7068313.84316.76313.28316.22313.84316.76MLO
21195910218381959.7890313.33316.35313.31316.31313.33316.35MLO
22195911218691959.8740314.81316.69314.53316.40314.81316.69MLO
23195912218991959.9562315.58316.35315.72316.48315.58316.35MLO
2419601219301960.0410316.43316.37316.63316.56316.43316.37MLO
2519602219611960.1257316.98316.33317.30316.64316.98316.33MLO
2619603219901960.2049317.58316.27318.04316.71317.58316.27MLO
2719604220211960.2896319.03316.69319.14316.79319.03316.69MLO
2819605220511960.3716320.03317.19319.70316.86320.03317.19MLO
2919606220821960.4563319.58317.44319.05316.92319.58317.44MLO
....................................
78620237451222023.5370421.62420.83421.72420.96421.62420.83MLO
78720238451532023.6219419.56421.12419.67421.27419.56421.12MLO
78820239451842023.7068418.06421.56418.07421.58418.06421.56MLO
789202310452142023.7890418.41422.01418.30421.89418.41422.01MLO
790202311452452023.8740420.11422.37419.97422.20420.11422.37MLO
791202312452752023.9562421.65422.57421.60422.50421.65422.57MLO
79220241453062024.0410422.62422.55422.88422.80422.62422.55MLO
79320242453372024.1257424.34423.56423.89423.10424.34423.56MLO
79420243453662024.2049425.22423.65424.95423.37425.22423.65MLO
79520244453972024.2896426.30423.50426.47423.66426.30423.50MLO
79620245454272024.3716426.70423.30427.33423.93426.70423.30MLO
79720246454582024.4563426.62424.07426.75424.21426.62424.07MLO
79820247454882024.5383425.40424.63425.22424.48425.40424.63MLO
79920248455192024.6230422.70424.30423.13424.76422.70424.30MLO
80020249455502024.7077421.60425.11421.50425.03421.60425.11MLO
801202410455802024.7896422.05425.66421.70425.29422.05425.66MLO
802202411456112024.8743423.61425.87423.31425.54423.61425.87MLO
803202412456412024.9563425.01425.93424.87425.76425.01425.93MLO
80420251456722025.0411426.42426.35426.07425.98426.42426.35MLO
80520252457032025.1260427.00426.21426.99426.19427.00426.21MLO
80620253457312025.2027427.73426.19427.92426.36427.73426.19MLO
80720254457622025.2877429.24426.47429.34426.55429.24426.47MLO
80820255457922025.3699430.21426.80430.13426.72430.21426.80MLO
80920256458232025.4548429.52426.93429.46426.90429.52426.93MLO
81020257458532025.5370427.56426.76427.83427.06427.56426.76MLO
81120258458842025.6219-99.99-99.99-99.99-99.99-99.99-99.99MLO
81220259459152025.7068-99.99-99.99-99.99-99.99-99.99-99.99MLO
813202510459452025.7890-99.99-99.99-99.99-99.99-99.99-99.99MLO
814202511459762025.8740-99.99-99.99-99.99-99.99-99.99-99.99MLO
815202512460062025.9562-99.99-99.99-99.99-99.99-99.99-99.99MLO
\n", "

816 rows × 11 columns

\n", "
" ], "text/plain": [ " year mois date decimal date? CO2(ppm) seasonally adjusted(ppm) \\\n", "0 1958 1 21200 1958.0411 -99.99 -99.99 \n", "1 1958 2 21231 1958.1260 -99.99 -99.99 \n", "2 1958 3 21259 1958.2027 315.71 314.43 \n", "3 1958 4 21290 1958.2877 317.45 315.15 \n", "4 1958 5 21320 1958.3699 317.51 314.68 \n", "5 1958 6 21351 1958.4548 -99.99 -99.99 \n", "6 1958 7 21381 1958.5370 315.87 315.20 \n", "7 1958 8 21412 1958.6219 314.93 316.23 \n", "8 1958 9 21443 1958.7068 313.21 316.12 \n", "9 1958 10 21473 1958.7890 -99.99 -99.99 \n", "10 1958 11 21504 1958.8740 313.33 315.21 \n", "11 1958 12 21534 1958.9562 314.67 315.43 \n", "12 1959 1 21565 1959.0411 315.58 315.52 \n", "13 1959 2 21596 1959.1260 316.49 315.83 \n", "14 1959 3 21624 1959.2027 316.65 315.37 \n", "15 1959 4 21655 1959.2877 317.72 315.41 \n", "16 1959 5 21685 1959.3699 318.29 315.46 \n", "17 1959 6 21716 1959.4548 318.15 316.00 \n", "18 1959 7 21746 1959.5370 316.54 315.87 \n", "19 1959 8 21777 1959.6219 314.79 316.10 \n", "20 1959 9 21808 1959.7068 313.84 316.76 \n", "21 1959 10 21838 1959.7890 313.33 316.35 \n", "22 1959 11 21869 1959.8740 314.81 316.69 \n", "23 1959 12 21899 1959.9562 315.58 316.35 \n", "24 1960 1 21930 1960.0410 316.43 316.37 \n", "25 1960 2 21961 1960.1257 316.98 316.33 \n", "26 1960 3 21990 1960.2049 317.58 316.27 \n", "27 1960 4 22021 1960.2896 319.03 316.69 \n", "28 1960 5 22051 1960.3716 320.03 317.19 \n", "29 1960 6 22082 1960.4563 319.58 317.44 \n", ".. ... ... ... ... ... ... \n", "786 2023 7 45122 2023.5370 421.62 420.83 \n", "787 2023 8 45153 2023.6219 419.56 421.12 \n", "788 2023 9 45184 2023.7068 418.06 421.56 \n", "789 2023 10 45214 2023.7890 418.41 422.01 \n", "790 2023 11 45245 2023.8740 420.11 422.37 \n", "791 2023 12 45275 2023.9562 421.65 422.57 \n", "792 2024 1 45306 2024.0410 422.62 422.55 \n", "793 2024 2 45337 2024.1257 424.34 423.56 \n", "794 2024 3 45366 2024.2049 425.22 423.65 \n", "795 2024 4 45397 2024.2896 426.30 423.50 \n", "796 2024 5 45427 2024.3716 426.70 423.30 \n", "797 2024 6 45458 2024.4563 426.62 424.07 \n", "798 2024 7 45488 2024.5383 425.40 424.63 \n", "799 2024 8 45519 2024.6230 422.70 424.30 \n", "800 2024 9 45550 2024.7077 421.60 425.11 \n", "801 2024 10 45580 2024.7896 422.05 425.66 \n", "802 2024 11 45611 2024.8743 423.61 425.87 \n", "803 2024 12 45641 2024.9563 425.01 425.93 \n", "804 2025 1 45672 2025.0411 426.42 426.35 \n", "805 2025 2 45703 2025.1260 427.00 426.21 \n", "806 2025 3 45731 2025.2027 427.73 426.19 \n", "807 2025 4 45762 2025.2877 429.24 426.47 \n", "808 2025 5 45792 2025.3699 430.21 426.80 \n", "809 2025 6 45823 2025.4548 429.52 426.93 \n", "810 2025 7 45853 2025.5370 427.56 426.76 \n", "811 2025 8 45884 2025.6219 -99.99 -99.99 \n", "812 2025 9 45915 2025.7068 -99.99 -99.99 \n", "813 2025 10 45945 2025.7890 -99.99 -99.99 \n", "814 2025 11 45976 2025.8740 -99.99 -99.99 \n", "815 2025 12 46006 2025.9562 -99.99 -99.99 \n", "\n", " fit(ppm) seasonally adjusted fit(ppm) CO2 filled(ppm) \\\n", "0 -99.99 -99.99 -99.99 \n", "1 -99.99 -99.99 -99.99 \n", "2 316.20 314.91 315.71 \n", "3 317.31 314.99 317.45 \n", "4 317.89 315.07 317.51 \n", "5 317.27 315.14 317.27 \n", "6 315.85 315.22 315.87 \n", "7 313.95 315.29 314.93 \n", "8 312.42 315.35 313.21 \n", "9 312.41 315.41 312.41 \n", "10 313.60 315.46 313.33 \n", "11 314.77 315.52 314.67 \n", "12 315.64 315.57 315.58 \n", "13 316.30 315.64 316.49 \n", "14 317.00 315.70 316.65 \n", "15 318.10 315.77 317.72 \n", "16 318.69 315.85 318.29 \n", "17 318.08 315.94 318.15 \n", "18 316.67 316.03 316.54 \n", "19 314.79 316.13 314.79 \n", "20 313.28 316.22 313.84 \n", "21 313.31 316.31 313.33 \n", "22 314.53 316.40 314.81 \n", "23 315.72 316.48 315.58 \n", "24 316.63 316.56 316.43 \n", "25 317.30 316.64 316.98 \n", "26 318.04 316.71 317.58 \n", "27 319.14 316.79 319.03 \n", "28 319.70 316.86 320.03 \n", "29 319.05 316.92 319.58 \n", ".. ... ... ... \n", "786 421.72 420.96 421.62 \n", "787 419.67 421.27 419.56 \n", "788 418.07 421.58 418.06 \n", "789 418.30 421.89 418.41 \n", "790 419.97 422.20 420.11 \n", "791 421.60 422.50 421.65 \n", "792 422.88 422.80 422.62 \n", "793 423.89 423.10 424.34 \n", "794 424.95 423.37 425.22 \n", "795 426.47 423.66 426.30 \n", "796 427.33 423.93 426.70 \n", "797 426.75 424.21 426.62 \n", "798 425.22 424.48 425.40 \n", "799 423.13 424.76 422.70 \n", "800 421.50 425.03 421.60 \n", "801 421.70 425.29 422.05 \n", "802 423.31 425.54 423.61 \n", "803 424.87 425.76 425.01 \n", "804 426.07 425.98 426.42 \n", "805 426.99 426.19 427.00 \n", "806 427.92 426.36 427.73 \n", "807 429.34 426.55 429.24 \n", "808 430.13 426.72 430.21 \n", "809 429.46 426.90 429.52 \n", "810 427.83 427.06 427.56 \n", "811 -99.99 -99.99 -99.99 \n", "812 -99.99 -99.99 -99.99 \n", "813 -99.99 -99.99 -99.99 \n", "814 -99.99 -99.99 -99.99 \n", "815 -99.99 -99.99 -99.99 \n", "\n", " seasonally adjusted filled(ppm) institut qui fait les mesures \n", "0 -99.99 MLO \n", "1 -99.99 MLO \n", "2 314.43 MLO \n", "3 315.15 MLO \n", "4 314.68 MLO \n", "5 315.14 MLO \n", "6 315.20 MLO \n", "7 316.23 MLO \n", "8 316.12 MLO \n", "9 315.41 MLO \n", "10 315.21 MLO \n", "11 315.43 MLO \n", "12 315.52 MLO \n", "13 315.83 MLO \n", "14 315.37 MLO \n", "15 315.41 MLO \n", "16 315.46 MLO \n", "17 316.00 MLO \n", "18 315.87 MLO \n", "19 316.10 MLO \n", "20 316.76 MLO \n", "21 316.35 MLO \n", "22 316.69 MLO \n", "23 316.35 MLO \n", "24 316.37 MLO \n", "25 316.33 MLO \n", "26 316.27 MLO \n", "27 316.69 MLO \n", "28 317.19 MLO \n", "29 317.44 MLO \n", ".. ... ... \n", "786 420.83 MLO \n", "787 421.12 MLO \n", "788 421.56 MLO \n", "789 422.01 MLO \n", "790 422.37 MLO \n", "791 422.57 MLO \n", "792 422.55 MLO \n", "793 423.56 MLO \n", "794 423.65 MLO \n", "795 423.50 MLO \n", "796 423.30 MLO \n", "797 424.07 MLO \n", "798 424.63 MLO \n", "799 424.30 MLO \n", "800 425.11 MLO \n", "801 425.66 MLO \n", "802 425.87 MLO \n", "803 425.93 MLO \n", "804 426.35 MLO \n", "805 426.21 MLO \n", "806 426.19 MLO \n", "807 426.47 MLO \n", "808 426.80 MLO \n", "809 426.93 MLO \n", "810 426.76 MLO \n", "811 -99.99 MLO \n", "812 -99.99 MLO \n", "813 -99.99 MLO \n", "814 -99.99 MLO \n", "815 -99.99 MLO \n", "\n", "[816 rows x 11 columns]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.reset_index() # l'année devient une vraie colonne\n", "data.rename(columns={'index': 'year'}, inplace=True) # renomme l'index en \"year\"\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les cases de ce tableau de données remplient avec la valeur -99.99 correspondent a des cases vide il faut donc modifier cela avec des cases vide :\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearmoisdate decimaldate?CO2(ppm)seasonally adjusted(ppm)fit(ppm)seasonally adjusted fit(ppm)CO2 filled(ppm)seasonally adjusted filled(ppm)institut qui fait les mesures
019581212001958.0411NaNNaNNaNNaNNaNNaNMLO
119582212311958.1260NaNNaNNaNNaNNaNNaNMLO
219583212591958.2027315.71314.43316.20314.91315.71314.43MLO
319584212901958.2877317.45315.15317.31314.99317.45315.15MLO
419585213201958.3699317.51314.68317.89315.07317.51314.68MLO
519586213511958.4548NaNNaN317.27315.14317.27315.14MLO
619587213811958.5370315.87315.20315.85315.22315.87315.20MLO
719588214121958.6219314.93316.23313.95315.29314.93316.23MLO
819589214431958.7068313.21316.12312.42315.35313.21316.12MLO
9195810214731958.7890NaNNaN312.41315.41312.41315.41MLO
10195811215041958.8740313.33315.21313.60315.46313.33315.21MLO
11195812215341958.9562314.67315.43314.77315.52314.67315.43MLO
1219591215651959.0411315.58315.52315.64315.57315.58315.52MLO
1319592215961959.1260316.49315.83316.30315.64316.49315.83MLO
1419593216241959.2027316.65315.37317.00315.70316.65315.37MLO
1519594216551959.2877317.72315.41318.10315.77317.72315.41MLO
1619595216851959.3699318.29315.46318.69315.85318.29315.46MLO
1719596217161959.4548318.15316.00318.08315.94318.15316.00MLO
1819597217461959.5370316.54315.87316.67316.03316.54315.87MLO
1919598217771959.6219314.79316.10314.79316.13314.79316.10MLO
2019599218081959.7068313.84316.76313.28316.22313.84316.76MLO
21195910218381959.7890313.33316.35313.31316.31313.33316.35MLO
22195911218691959.8740314.81316.69314.53316.40314.81316.69MLO
23195912218991959.9562315.58316.35315.72316.48315.58316.35MLO
2419601219301960.0410316.43316.37316.63316.56316.43316.37MLO
2519602219611960.1257316.98316.33317.30316.64316.98316.33MLO
2619603219901960.2049317.58316.27318.04316.71317.58316.27MLO
2719604220211960.2896319.03316.69319.14316.79319.03316.69MLO
2819605220511960.3716320.03317.19319.70316.86320.03317.19MLO
2919606220821960.4563319.58317.44319.05316.92319.58317.44MLO
....................................
78620237451222023.5370421.62420.83421.72420.96421.62420.83MLO
78720238451532023.6219419.56421.12419.67421.27419.56421.12MLO
78820239451842023.7068418.06421.56418.07421.58418.06421.56MLO
789202310452142023.7890418.41422.01418.30421.89418.41422.01MLO
790202311452452023.8740420.11422.37419.97422.20420.11422.37MLO
791202312452752023.9562421.65422.57421.60422.50421.65422.57MLO
79220241453062024.0410422.62422.55422.88422.80422.62422.55MLO
79320242453372024.1257424.34423.56423.89423.10424.34423.56MLO
79420243453662024.2049425.22423.65424.95423.37425.22423.65MLO
79520244453972024.2896426.30423.50426.47423.66426.30423.50MLO
79620245454272024.3716426.70423.30427.33423.93426.70423.30MLO
79720246454582024.4563426.62424.07426.75424.21426.62424.07MLO
79820247454882024.5383425.40424.63425.22424.48425.40424.63MLO
79920248455192024.6230422.70424.30423.13424.76422.70424.30MLO
80020249455502024.7077421.60425.11421.50425.03421.60425.11MLO
801202410455802024.7896422.05425.66421.70425.29422.05425.66MLO
802202411456112024.8743423.61425.87423.31425.54423.61425.87MLO
803202412456412024.9563425.01425.93424.87425.76425.01425.93MLO
80420251456722025.0411426.42426.35426.07425.98426.42426.35MLO
80520252457032025.1260427.00426.21426.99426.19427.00426.21MLO
80620253457312025.2027427.73426.19427.92426.36427.73426.19MLO
80720254457622025.2877429.24426.47429.34426.55429.24426.47MLO
80820255457922025.3699430.21426.80430.13426.72430.21426.80MLO
80920256458232025.4548429.52426.93429.46426.90429.52426.93MLO
81020257458532025.5370427.56426.76427.83427.06427.56426.76MLO
81120258458842025.6219NaNNaNNaNNaNNaNNaNMLO
81220259459152025.7068NaNNaNNaNNaNNaNNaNMLO
813202510459452025.7890NaNNaNNaNNaNNaNNaNMLO
814202511459762025.8740NaNNaNNaNNaNNaNNaNMLO
815202512460062025.9562NaNNaNNaNNaNNaNNaNMLO
\n", "

816 rows × 11 columns

\n", "
" ], "text/plain": [ " year mois date decimal date? CO2(ppm) seasonally adjusted(ppm) \\\n", "0 1958 1 21200 1958.0411 NaN NaN \n", "1 1958 2 21231 1958.1260 NaN NaN \n", "2 1958 3 21259 1958.2027 315.71 314.43 \n", "3 1958 4 21290 1958.2877 317.45 315.15 \n", "4 1958 5 21320 1958.3699 317.51 314.68 \n", "5 1958 6 21351 1958.4548 NaN NaN \n", "6 1958 7 21381 1958.5370 315.87 315.20 \n", "7 1958 8 21412 1958.6219 314.93 316.23 \n", "8 1958 9 21443 1958.7068 313.21 316.12 \n", "9 1958 10 21473 1958.7890 NaN NaN \n", "10 1958 11 21504 1958.8740 313.33 315.21 \n", "11 1958 12 21534 1958.9562 314.67 315.43 \n", "12 1959 1 21565 1959.0411 315.58 315.52 \n", "13 1959 2 21596 1959.1260 316.49 315.83 \n", "14 1959 3 21624 1959.2027 316.65 315.37 \n", "15 1959 4 21655 1959.2877 317.72 315.41 \n", "16 1959 5 21685 1959.3699 318.29 315.46 \n", "17 1959 6 21716 1959.4548 318.15 316.00 \n", "18 1959 7 21746 1959.5370 316.54 315.87 \n", "19 1959 8 21777 1959.6219 314.79 316.10 \n", "20 1959 9 21808 1959.7068 313.84 316.76 \n", "21 1959 10 21838 1959.7890 313.33 316.35 \n", "22 1959 11 21869 1959.8740 314.81 316.69 \n", "23 1959 12 21899 1959.9562 315.58 316.35 \n", "24 1960 1 21930 1960.0410 316.43 316.37 \n", "25 1960 2 21961 1960.1257 316.98 316.33 \n", "26 1960 3 21990 1960.2049 317.58 316.27 \n", "27 1960 4 22021 1960.2896 319.03 316.69 \n", "28 1960 5 22051 1960.3716 320.03 317.19 \n", "29 1960 6 22082 1960.4563 319.58 317.44 \n", ".. ... ... ... ... ... ... \n", "786 2023 7 45122 2023.5370 421.62 420.83 \n", "787 2023 8 45153 2023.6219 419.56 421.12 \n", "788 2023 9 45184 2023.7068 418.06 421.56 \n", "789 2023 10 45214 2023.7890 418.41 422.01 \n", "790 2023 11 45245 2023.8740 420.11 422.37 \n", "791 2023 12 45275 2023.9562 421.65 422.57 \n", "792 2024 1 45306 2024.0410 422.62 422.55 \n", "793 2024 2 45337 2024.1257 424.34 423.56 \n", "794 2024 3 45366 2024.2049 425.22 423.65 \n", "795 2024 4 45397 2024.2896 426.30 423.50 \n", "796 2024 5 45427 2024.3716 426.70 423.30 \n", "797 2024 6 45458 2024.4563 426.62 424.07 \n", "798 2024 7 45488 2024.5383 425.40 424.63 \n", "799 2024 8 45519 2024.6230 422.70 424.30 \n", "800 2024 9 45550 2024.7077 421.60 425.11 \n", "801 2024 10 45580 2024.7896 422.05 425.66 \n", "802 2024 11 45611 2024.8743 423.61 425.87 \n", "803 2024 12 45641 2024.9563 425.01 425.93 \n", "804 2025 1 45672 2025.0411 426.42 426.35 \n", "805 2025 2 45703 2025.1260 427.00 426.21 \n", "806 2025 3 45731 2025.2027 427.73 426.19 \n", "807 2025 4 45762 2025.2877 429.24 426.47 \n", "808 2025 5 45792 2025.3699 430.21 426.80 \n", "809 2025 6 45823 2025.4548 429.52 426.93 \n", "810 2025 7 45853 2025.5370 427.56 426.76 \n", "811 2025 8 45884 2025.6219 NaN NaN \n", "812 2025 9 45915 2025.7068 NaN NaN \n", "813 2025 10 45945 2025.7890 NaN NaN \n", "814 2025 11 45976 2025.8740 NaN NaN \n", "815 2025 12 46006 2025.9562 NaN NaN \n", "\n", " fit(ppm) seasonally adjusted fit(ppm) CO2 filled(ppm) \\\n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 316.20 314.91 315.71 \n", "3 317.31 314.99 317.45 \n", "4 317.89 315.07 317.51 \n", "5 317.27 315.14 317.27 \n", "6 315.85 315.22 315.87 \n", "7 313.95 315.29 314.93 \n", "8 312.42 315.35 313.21 \n", "9 312.41 315.41 312.41 \n", "10 313.60 315.46 313.33 \n", "11 314.77 315.52 314.67 \n", "12 315.64 315.57 315.58 \n", "13 316.30 315.64 316.49 \n", "14 317.00 315.70 316.65 \n", "15 318.10 315.77 317.72 \n", "16 318.69 315.85 318.29 \n", "17 318.08 315.94 318.15 \n", "18 316.67 316.03 316.54 \n", "19 314.79 316.13 314.79 \n", "20 313.28 316.22 313.84 \n", "21 313.31 316.31 313.33 \n", "22 314.53 316.40 314.81 \n", "23 315.72 316.48 315.58 \n", "24 316.63 316.56 316.43 \n", "25 317.30 316.64 316.98 \n", "26 318.04 316.71 317.58 \n", "27 319.14 316.79 319.03 \n", "28 319.70 316.86 320.03 \n", "29 319.05 316.92 319.58 \n", ".. ... ... ... \n", "786 421.72 420.96 421.62 \n", "787 419.67 421.27 419.56 \n", "788 418.07 421.58 418.06 \n", "789 418.30 421.89 418.41 \n", "790 419.97 422.20 420.11 \n", "791 421.60 422.50 421.65 \n", "792 422.88 422.80 422.62 \n", "793 423.89 423.10 424.34 \n", "794 424.95 423.37 425.22 \n", "795 426.47 423.66 426.30 \n", "796 427.33 423.93 426.70 \n", "797 426.75 424.21 426.62 \n", "798 425.22 424.48 425.40 \n", "799 423.13 424.76 422.70 \n", "800 421.50 425.03 421.60 \n", "801 421.70 425.29 422.05 \n", "802 423.31 425.54 423.61 \n", "803 424.87 425.76 425.01 \n", "804 426.07 425.98 426.42 \n", "805 426.99 426.19 427.00 \n", "806 427.92 426.36 427.73 \n", "807 429.34 426.55 429.24 \n", "808 430.13 426.72 430.21 \n", "809 429.46 426.90 429.52 \n", "810 427.83 427.06 427.56 \n", "811 NaN NaN NaN \n", "812 NaN NaN NaN \n", "813 NaN NaN NaN \n", "814 NaN NaN NaN \n", "815 NaN NaN NaN \n", "\n", " seasonally adjusted filled(ppm) institut qui fait les mesures \n", "0 NaN MLO \n", "1 NaN MLO \n", "2 314.43 MLO \n", "3 315.15 MLO \n", "4 314.68 MLO \n", "5 315.14 MLO \n", "6 315.20 MLO \n", "7 316.23 MLO \n", "8 316.12 MLO \n", "9 315.41 MLO \n", "10 315.21 MLO \n", "11 315.43 MLO \n", "12 315.52 MLO \n", "13 315.83 MLO \n", "14 315.37 MLO \n", "15 315.41 MLO \n", "16 315.46 MLO \n", "17 316.00 MLO \n", "18 315.87 MLO \n", "19 316.10 MLO \n", "20 316.76 MLO \n", "21 316.35 MLO \n", "22 316.69 MLO \n", "23 316.35 MLO \n", "24 316.37 MLO \n", "25 316.33 MLO \n", "26 316.27 MLO \n", "27 316.69 MLO \n", "28 317.19 MLO \n", "29 317.44 MLO \n", ".. ... ... \n", "786 420.83 MLO \n", "787 421.12 MLO \n", "788 421.56 MLO \n", "789 422.01 MLO \n", "790 422.37 MLO \n", "791 422.57 MLO \n", "792 422.55 MLO \n", "793 423.56 MLO \n", "794 423.65 MLO \n", "795 423.50 MLO \n", "796 423.30 MLO \n", "797 424.07 MLO \n", "798 424.63 MLO \n", "799 424.30 MLO \n", "800 425.11 MLO \n", "801 425.66 MLO \n", "802 425.87 MLO \n", "803 425.93 MLO \n", "804 426.35 MLO \n", "805 426.21 MLO \n", "806 426.19 MLO \n", "807 426.47 MLO \n", "808 426.80 MLO \n", "809 426.93 MLO \n", "810 426.76 MLO \n", "811 NaN MLO \n", "812 NaN MLO \n", "813 NaN MLO \n", "814 NaN MLO \n", "815 NaN MLO \n", "\n", "[816 rows x 11 columns]" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", "data = data.replace(-99.99, np.nan)\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pour la suite, comme c'est demandé dans la question 1 on trace un graphique qui vous montrera une oscillation périodique superposée à une évolution systématique plus lente :" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": 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RLJ5U4Dagq3OuHjAQWBkc/i2+GiwL6AB0A34XdvppwfXPAH4K/N3MTi7DfTwCtAM6Aq2BlOC88Os0xCcObwru4wXg5uC+/wm8F0p6Fbu/OsCnwOv48b4KeNrM0p1zzwKvAX8KntUPI5zfEPgQeCK41mPAh2bWKOj7CWBwMHY9Cb5LZvZjYCRwHf4ZDAG2Rrn/aCI+Q+fcHmAwsC6Iu65zbl2xuNsAbwA/x3/PPwLet6IVfZcDg4AWQCYwLF5AscYzrFnE5x7pd6M0z1JERORYo8SSiIhIxWgMbHHOHYxwbH1wHCAPOMvMGjvndjvnvg72DwXGO+feCKqdtjrnSpVYcs7lOOe+ds4dDKql/gn0TfD0s4G6wMPOuQPOuc+BD/B/jIe845ybFtzja/jETiR5+D/Gz3LOHQri2hnE+KFzbpnzJuATWb0j9HEIqAmkmVmSc26lc25ZcGwo8IBzbpNzbjM+WXBtses/EIzjR8BuIDxBFvc+zMyAG4GfB89iJ/BH4MdhzfKB+51z+51ze4P2/3TOTQ3u+2VgfzC2xV0ErHTOvRg8rxnA28BlkYe0hAuBJc65fwfnvwEsBEJJqHygvZmd6Jxb75ybF+wfjk9YfRM8g6XOuW8TvCZQqmcYyRXAh865T51zecCjwIn45FfIE865dc65bfhkZ7TvWbhExjPR7y+U7lmKiIgcU5RYEhERqRhbgMYWea2d04Pj4Cto2gALg+lLFwX7mwLLIpybMDNrY2YfmF80fCfwEIUJrXiSgdXOufywfd/iq35CNoT9/D0+ERXJv4H/Am+an6r2p6AiCjMbbGZfB9OVtgMXRIrRObcUX9UyEthkZm+aWXJYrOHJkG+DfSFbiyX4iseayH00AWrjq2kWmtlC4CV8EiRks3NuX9jnM4FfBVOntgf317RYbOFtuxdrOxRfBZWI4mNA8PmMoHLoCnyl2Ppg+lfboE15fM8SeoaJxB1831ZTtu9ZuETGszT9luZZioiIHFOUWBIREakYU/AVDZeG7wym6AwGPgNwzi1xzl2Fn67zCPCfoM1q/NS4w/EPfNVK62Cq3W8AS/DcdUBTMwv/f4lmwNrSBhFUCv3eOZeGr0S5CLgumEb0Nr5K5VTn3En4qVARY3TOve6cOwf/R77Dj1co1jOLxbmO8rUFP33vB865tsG/Ns65U8NDLHbOauBB59xJYf9qB9VExa0GJhRrW9c5d2uUvosrPgYQ9rycc/91zv0An9RcCIQWHz+s71kCz7BUcQeVYU0pw/esmHjjWZb+En2WIiIixxQllkRERCqAc24HfkrWk2Y2yMySzKw58BawBl/Fg5ldY2ZNgkqN7cHph/BTc843s8vNrHqwVk4iU4DC1QN2AruDCpXif1RvBFpGOXcqsAe/YHSSmfXDT6t6s5QxYGbnmlmGmVUL4snD32MN/PS2zcBBMxsMDIjSR6qZ9Q8SGfvwSZ5DweE3gN+ZWRMzawzcB7waqZ+yCp7Pc8DjVrjw+BlmNjDGac8Bt5hZd/PqmNmFZlYvQtsPgDZmdm0w3klm1tUKF7KO9azAJ3PamNnVwfflCiAN+MDMTjW/QHYdfLJzN4Vj9zxwp5l1DmI8y8yKJ6hiifcMNwKNzKxBlPNHAxea2XlBFduvghgnlyKGSOKNZzzFx7s0z1JEROSYosSSiIhIBXHO/QlfJfQoPqEyFV/5cJ5zbn/QbBAwz8x24xfyvtI5t885two/pehXwDb8YssdShnCncDVwC78H8ajih0fCbwcTO25PPyAc+4AfiHnwfhqnaeB65xzC0sZA/jpR//Bj8ECYALwqnNuF3A7PrnwXRDre1H6qAk8HMSyAV/h9Zvg2B+B6UAuMAeYEewrb3cDi4ApwdTC8RRdq6kI59x0/No8T+HvbylRFp4OxmIAcCW+imcDviIrtDj0v/DrS203szERzt+KrwT7FX7x7V8DFznntuD/f/BXQb/b8OtshRZxfwu/aPXr+O/JGPwC5AmJ9wyD78sbwPIg9uRi5y/CvyHxSfyz/SHww+D7V2YJjGc8Iwn73SjNsxQRETnWmHPxKpBFRERERERERERKUsWSiIiIiIiIiIiUiRJLIiIiIiIiIiJSJkosiYiIiIiIiIhImSixJCIiIiIiIiIiZVK9ogM4HI0bN3bNmzcHYM+ePdSpU6diA6oiNFaJ01iVjsYrcRqrxGmsSkfjlTiNVeI0VqWj8UqcxipxGqvS0XglTmMlkeTk5GxxzjVJpG2VTiw1b96c6dOnA5CdnU2/fv0qNqAqQmOVOI1V6Wi8EqexSpzGqnQ0XonTWCVOY1U6Gq/EaawSp7EqHY1X4jRWEomZfZtoW02FExERERERERGRMlFiSUREREREREREykSJJRERERERERERKZMqvcaSiIiIiIiIlF1eXh5r1qxh3759FR1KuWrQoAELFiyo6DCqBI3V8a1WrVqkpKSQlJRU5j6UWBIRERERETlOrVmzhnr16tG8eXPMrKLDKTe7du2iXr16FR1GlaCxOn4559i6dStr1qyhRYsWZe5HU+FERERERESOU/v27aNRo0bHVFJJRBJjZjRq1OiwKxaVWBIRERERETmOKakkcvwqj99/JZZEREREREREjhGvvfYaq1atqugw5DiixJKIiIiIiIhUmA0bNnDllVfSqlUr0tLSuOCCC1i8eDEA8+bNo3///rRp04bWrVvzhz/8AefcUYnrmWee4ZVXXgFg2LBh/Oc//wGgX79+TJ8+Pea5jz/+ON9//33B5wsuuIDt27cfuWAD//rXv9i8eTPNmjWL2qZnz56l6jP83ocPH878+fMPK8bK5r777mP8+PFA0WfbvHlztmzZEvPchx56qMjn0o5tNOFjXlqzZs3io48+Kpc4EqXEkoiIiIiIiFQI5xyXXHIJ/fr1Y9myZcyfP5+HHnqIjRs3snfvXoYMGcKIESNYvHgxs2fPZvLkyTz99NNHJbZbbrmF6667rkznFk8sffTRR5x00knlFVpUP/3pT/n5z38e8dihQ4cAmDx5cpn7f/7550lLSyvz+aWxcuVK+vXrd8Sv88ADD3D++eeX6dziiaXDGdvyosSSiIiIiIiIHDe++OILkpKSuOWWWwr2ZWVl0bt3b15//XV69erFgAEDAKhduzZPPfUUDz/8cNx+9+3bxw033EBGRgYdO3bkiy++AHwFVLdu3cjKyiIzM5MlS5YA8Morr5CZmUmHDh249tprARg5ciSPPvpozOvceuutdOnShfT0dO6//34AnnjiCdatW8e5557LueeeCxStfnnsscdo37497du35/HHHwd8EqVdu3bceOONpKenM2DAAPbu3VviesOGDeOWW26hd+/etGnThg8++ADwSaO77rqLrl27kpmZyT//+U8AsrOzOffcc7n66qvJyMgAoG7duoBP6t111110796djIwMRo0aVbD/tttuIy0tjQsvvJBNmzYVXD+8oufFF1+kTZs29O3blxtvvJHbbrutIMbwapvQ9QD+/Oc/F8QYGq/DsW3bNi6++GIyMzM5++yzyc3NBWDChAlkZWWRlZVFx44d2bVrFwB/+tOfyMjIoEOHDowYMSJivJFcfPHFdO7cmfT0dJ599lkARowYwd69e8nKymLo0KFF7jU0tu3bty8yttnZ2fTr14/LLruMtm3bMnTo0LgVeDk5OfTt25fOnTszcOBA1q9fD/hncffdd9OtWzfatGnDl19+yYEDB7jvvvsYNWoUWVlZjBo1ij179vCTn/yErl270rFjR8aOHVuWoY6pern3KCIiIiIiIlXOz38Os2aVb59ZWRDkTiKaO3cunTt3jnhs3rx5JY61atWK3bt3s3PnTurXrx+13+eeew6AOXPmsHDhQgYMGMDixYt55plnuOOOOxg6dCgHDhzg0KFDzJs3jwcffJCvvvqKxo0bs23btoTv78EHH6Rhw4YcOnSI8847j9zcXG6//XYee+wxvvjiCxo3blykfU5ODi+++CJTp07FOUf37t3p27cvJ598MkuWLOGNN97gueee4/LLL+ftt9/mmmuuKXHNlStXMmHCBJYtW8a5557L0qVLeeWVV2jQoAHffPMN+/fvL5KQmzZtGnPnzi3xOvl33nmHWbNmMXnyZPbv30/Xrl3p06cPU6ZMYdGiRcyZM4eNGzeSlpbGT37ykyLnrl+/nvvvv5+cnBwaNGjAueeeS8eOHWOO1bhx41iyZAnTpk3DOceQIUOYOHEiffr0SXi8i7v//vvp2LEjY8aM4fPPP+e6665j1qxZPProo/z973+nV69e7N69m1q1avHxxx8zZswYpk6dSu3atUv1nF944QUaNmzI3r176dq1K//zP//Dww8/zFNPPcWsCL80obGdPXs2W7ZsKRhbgJkzZzJv3jySk5Pp1asXX331Feecc07E6+bl5fGzn/2MsWPH0qRJE0aNGsVvf/tbXnjhBQAOHjzItGnT+Oijj/j973/P+PHjeeCBB5g+fTpPPfUUAL/5zW/o378/L7zwAtu3b6dbt26cf/751KlTp7TDHZUSSyIiIiIiIlLpOOeivrHKzPi///s/tm3bxtatWwv+0A6ZMmUKv/jFLwBo27YtZ555JosXL6ZHjx48+OCDrFmzhksvvZTWrVvz+eefc9lllxUkgRo2bJhwjKNHj+bZZ5/l4MGDrF+/nvnz55OZmRm1/aRJk7jkkksK/qi/9NJL+fLLLxkyZAgtWrQgKysLgM6dO7Ny5cqIfVx++eWccMIJtG7dmpYtW7Jw4ULGjRtHbm5uQeXNjh07WLJkCTVq1KBbt24lkkqhWK666iqqVavGqaeeSt++ffnmm2+YOHFiwf7k5GT69+9f4typU6fSr18/mjRpAsAVV1xRsC5WNOPGjWPcuHEFCajdu3ezZMmSEomlSy65hBUrVnDgwAFWrVpVMCZ33HEHN9xwQ4l7ePvttwHo378/W7duZceOHfTq1Ytf/vKXDB06lEsvvZSUlBTGjx/PDTfcQO3atYHSPecnnniCd999F4DVq1ezZMkSGjVqFLV9tLGtX78+3bp1IyUlBfDVeStXroyaWFq0aBFz587lBz/4AeAr004//fSC45deeikQ+/sybtw43nvvvYLqu3379rFq1SratWuX8P3Ho8SSiIiIiIiIxKwsOlLS09OjTkNKT09n4sSJRfYtX76cunXrUq9ePe655x727NnDj370oxLnRptedPXVV9O9e3c+/PBDBg4cyPPPPx8zgRXLihUrePTRR/nmm284+eSTGTZsGPv27Yt5TqxpTzVr1iz4uVq1ahGnwkHJ18ObGc45nnzySQYOHFjkWHZ2dtTKlFixJDIe0dpUr16d/Pz8gmscOHCg4Od77rmHm2++OWa/oQTOypUrGTZsGNnZ2VHbRroHM2PEiBFceOGFfPTRR5x99tmMHz++zM85Ozub8ePHM2XKFGrXrk2/fv3K9TkfPHgwZj/p6elMmTIlZl+x+nHO8fbbb5Oamhoz5sOhNZZERERERESkQvTv35/9+/cXTF0D+Oabb5gwYQJDhw5l0qRJBW/s2rt3L7fffju//vWvAV/xcsstt/Dkk0+W6LdXr1689tprACxevJhVq1aRmprK8uXLadmyJbfffjtDhgwhNzeX8847j9GjR7N161aAhKdI7dy5kzp16tCgQQM2btzIxx9/XHCsXr16Bev6hOvTpw9jxozh+++/Z8+ePbz77rv07t07wdHy3nrrLfLz81m2bBnLly8nNTWVgQMH8o9//IO8vLyCe96zZ0/Mfvr06cOoUaM4dOgQmzdvZuLEiXTr1o0+ffrw5ptvcujQIdavX1+wPlW47t27k52dzdatW8nLy+Ott94qONa8eXNycnIAGDt2bEFMAwcO5IUXXmD37t0ArF27tsj6TWXRp0+fguecnZ1N48aNqV+/PsuWLSMjI4O7776bLl26FEyHfOGFFwoWVU/0Oe/YsYOTTz6Z2rVrs3DhQr7++uuCY0lJSQX3VzyuSGNbWqmpqWzevLkgsZSXl8e8efNinlP8uzdw4ECefPLJgmTXzJkzSx1HPEosiYiIiIiISIUwM959910+/fRTWrVqRXp6OiNHjiQ5OZkTTzyRsWPH8sc//pHU1FTTj0I9AAAgAElEQVQyMjLo2rVrwSLRgwYNIj8/n5dffrlEtcbw4cM5dOgQGRkZXHHFFbz00kvUrFmTUaNG0b59e7Kysli4cCHXXXcd6enp/Pa3v6Vv37506NCBX/7ylwnF3qFDBzp27Eh6ejo/+clP6NWrV8Gxm266icGDBxcs3h3SqVMnhg0bRrdu3ejevTvDhw+PuzZRcampqfTt25fBgwfzzDPPUKtWLYYPH05aWhqdOnWiffv23HzzzTErYcBPOcvMzKRnz57079+fP/3pT5x22mlccskltG7dmoyMDG699Vb69u1b4tzTTz+dkSNH0qNHD84//3w6depUcOzGG29kwoQJdOvWjalTpxZUTA0YMICrr76aHj16kJGRwWWXXRYx+VYaI0eOZPr06WRmZjJixAhefvllwL+Vr3379nTo0IETTzyRwYMHM2jQIIYMGUKXLl3IysqKuzB7yKBBgzh48CCZmZnce++9nH322QXHbrrpJjIzMwsW7w4JjW2HDh2KjG1p1ahRg//85z/cfffddOjQgaysrLhvnjv33HOZP39+weLd9957L3l5eWRmZtK+fXvuvffeUscRj8Vbgbwy69KliwutSB9aXV3i01glTmNVOhqvxGmsEqexKh2NV+I0VonTWJWOxitxGqvEHamxWrBgQbmutVJZ7Nq1i3r16lV0GOVu2LBhXHTRRVx22WXl1md5jNVLL71UZMFoqVoi/XfAzHKcc10SOV8VSyIiIiIiIiIiUiZavFtERERERESkCnjppZcqOoSIhg0bxrBhwyo6DKkgqlgSEREREREREZEyUWJJRERERETkOFaV190VkcNTHr//SiyJiIiIiIgcp2rVqsXWrVuVXBI5Djnn2Lp1K7Vq1TqsfrTGkoiIiIiIyHEqJSWFNWvWsHnz5ooOpVzt27fvsP9YPl5orA7Prl2QlwcNG1Z0JGVTq1YtUlJSDqsPJZZERERERESOU0lJSbRo0aKiwyh32dnZdOzYsaLDqBI0VmXnHJx5JqxeDfPnQ7t2FR1RxdBUOBERERERERGRUpo92yeVAB5/vGJjqUhKLImIiIiIiIiIlNL774MZDBkCr7wCO3dWdEQVQ4klEREREREREZFSev996N4dhg+Hffv8dLjjkRJLIiIiIiIiIiKlsGcP5OTA+edDaqrft3hxxcZUUZRYEhEREREREREphdmzIT8funaFFi2gWjUllkREREREREREJAHTp/tt586QlAQtWyqxJCIiIiIiIiIiCcjJgVNPheRk/zk1FRYtqtiYKooSSyIiIiIiIiIipTB9OnTp4t8KB9CmDSxZ4qfHHW+UWBIRERERERERSdCePbBwoZ8GF9KmDezdC2vXVlxcFUWJJRERERERERGRBE2Y4CuTuncv3Hc8vxlOiSURERERERERkQS9/DI0agTnn1+4r00baN7cVzMdb6pXdAAiIiIiIiIiIlXBd9/BmDFwyy1Qo0bh/uRkWLGi4uKqSKpYEhERERERERFJwLPPwoEDMGxYRUdSeSixJCIiIiIiIiLHpfx8uPhiOOUUuOOO2G9127EDHnkEBg+Gjh2PXoyVnRJLIiIiIiIiInJceuwxGDsWmjaFJ56A3NzobZ94wk+F++Mfj158VYESSyIiIiIiIiJy3Nm7F+67D370I3j3Xb/vyy+jt//kE+jRAzp1OjrxVRVKLImIiIiIiIjIcWfiRJ9cuuUWaNbM/5s4MXLbvDyYMcMnlqQoJZZERERERERE5LjzySdQqxb07es/9+njK5acK9k2Nxf27YPu3Y9ujFWBEksiIiIiIiIictz55BOfTDrxRP+5d2/YuBGWLCnZdupUv1ViqSQllkRERERERETkuPLtt7BwIQwaVLivWze/nTWrZPupU/2b45o1OzrxVSVKLImIiIiIiIjIcWXsWL+94ILCfWee6berV5dsP3Wqr1YyO/KxVTVKLImIiIiIiIjIceWddyA9HVJTC/eddBLUqQNr1hRtu3MnLFoEXbse3RirCiWWREREREREROS4sWmTX6T70kuL7jeDlJSSFUszZ/ptly5HJ76qRoklERERERERETlufPQR5OeXTCwBNG1aMrE0fbrfdu585GOripRYEhEREREREZHjRk4O1K0LmZkljzVtWnIqXE6O33/KKUcnvqpGiSURERERERERqdKeew5eey2xtnPnQvv2cEKEjEhKCqxfD3l5hfumT1e1UixKLImIiIiIiIhIlZWXB3feCddfDxMmxG7rHMyZAxkZkY83berbrFvnP+/YAUuWaH2lWJRYEhEREREREZEqa+pU/+a2WrVg6FCfGIpmwwbYutVXLEXStKnfhqbDzZjht6pYik6JJRERERERERGpsj75BKpVg3vvhbVrS66RFG7OHL+NVbEEhQt45+T4rRJL0SmxJCIiIiIiIiJV1n//Cz16+H8A8+dHbxsvsZSS4rfhiaVmzaBJk/KJ9VikxJKIiIiIiIiIVEm7dvnkzw9+AGlpft+8edHbz5kDp50GjRtHPt6gAdSvD8uX+8/Tp2t9pXiUWBIRERERERGRKmnZMr+mUnq6Txadckr0iqX8fBg/Hnr2jN1nz57wxRewfTssXappcPEosSQiIiIiIiIiVdKyZX7bsqXfpqVFr1jKyfFrMF18cew+BwyARYtgzBj/WRVLsSmxJCIiIiIiIiJVUiix1KqV36an+4qlSG+GGzPGL/J94YWx+xwwwG/vuQeSkpRYikeJJRERERERERGpkpYt81Pg6tf3n9PSYOdOWLeuZNsxY6BvX2jYMHafaWlwxhmwYQP85jfx2x/vlFgSERERERERkSpp2bLCaiWAdu38dsGCou22bfOVTKFqpFjMYOhQ6NbNJ5YkNiWWRERERERERKRKKp5YatPGb5csKdouN9dvs7IS6/eRR+Drr6FGjcOP8VinxJKIiIiIiIiIVDkHDsCqVUUTS8nJULs2LF5ctO3s2X7boUPi/ZsdfozHAyWWRERERERERKRCOQd9+kBqKjz9dGLnfPst5OcXTSyZQevWkRNLp5wCp51WfjGLd8QTS2ZWzcxmmtkHwec/m9lCM8s1s3fN7KSwtveY2VIzW2RmA490bCIiIiIiIiJS8aZOhS+/hM2b4c47fcIolvx8eOMN/3N4Ygn8dLjiU+Fmz058GpyUztGoWLoDCF8261OgvXMuE1gM3ANgZmnAlUA6MAh42syqHYX4RERERERERKQCvfiin8L2m9/A3r2wZk3s9k8/DfffD4MGQffuRY+1aQPLl0Nenv+clwdz55ZuGpwk7ogmlswsBbgQeD60zzk3zjl3MPj4NZAS/Pwj4E3n3H7n3ApgKdDtSMYnIiIiIiIiIhVr715480247DLo0sXvW7Qo9jnvvw9pafDRR5CUVPRY69Zw6BCsWFHY14EDSiwdKdWPcP+PA78G6kU5/hNgVPDzGfhEU8iaYF8RZnYTcBPAqaeeSnZ2NgC7d+8u+Fli01glTmNVOhqvxGmsEqexKh2NV+I0VonTWJWOxitxGqvEaaxKR+OVuMowVnPn1mfnzk60bj2HrVt3AT354IMlJCWtjdg+L8+YOPEcBg9ez4QJS0sc3727PtCJt9/OpUePbXz66SlAGgcOfEN29p4jei/HoyOWWDKzi4BNzrkcM+sX4fhvgYPAa6FdEbpxJXY49yzwLECXLl1cv36+6+zsbEI/S2waq8RprEpH45U4jVXiNFalo/FKnMYqcRqr0tF4JU5jlTiNVelovBJXGcZq7ly/HTYsgzPOgLp1IT+/Nf36tY7YfvJk2LcPrrkmhX79Ukocz8iA226DmjUz6dfPVzXVqAHXXNO1RHWTHL4jWbHUCxhiZhcAtYD6Zvaqc+4aM7seuAg4zzkXSh6tAZqGnZ8CrDuC8YmIiIiIiIhIBZsxA5o0gTPO8G91S02NPRXuiy/8tk+fyMcbNfJvf5s923+ePRvS00tOmZPyccTWWHLO3eOcS3HONccvyv15kFQaBNwNDHHOfR92ynvAlWZW08xaAK2BaUcqPhEREREREREpXytXwq5dibVdvRrGjYOZM6FTJ59UgviJpU8+gcxMaNw4epsuXWD6dP/z7NlaX+lIOhpvhSvuKfyaS5+a2SwzewbAOTcPGA3MBz4B/tc5d6gC4hMRERERERGRUvruO5/wycqCefPitx8xAgYPhjlzfGIpJDUVVq3yi3oXN2MGTJoE11wTu+/OnWHhQli2DDZu9DHJkXGkF+8GwDmXDWQHP58Vo92DwINHIyYRERERERERKT8vvuirlZKS4NprfRIomrw8+PBDyM/3nzt2LDyWmuq3S5b4RFW4v/wF6tWDm26KHUuXLr7vl17yn1WxdORURMWSiIiIiIiIiBxDDh2Cv/8dzjkHhg/3FUuHYsxBmjABduzwCSCArl0Lj4USS8Wnw+3YAaNGwU9/Cg0axI6nc2e/ff55vy2eoJLyo8SSiIiIiIiIiByWKVNg+XK49VZo1QoOHIC1a6O3HzsWTjwRxo+HqVOhefPCY62Dl8EVTyzNmOGTVYMGxY/n9NMhORk2bIAbb4SGDUt9S5IgJZZERERERERE5LB89hmccIJfM6lVK79v6dLo7ceNg/PO85VH3boVPVanDqSklEwshRbjDlUjxXPZZXDBBfDUU4m1l7JRYklEREREREREDstnn/kFuE8+Gc4KVlZetixy2127/PpJxRNK4SK9Ge6bb3xlU6y3wYX729/8Ok41aiTWXspGiSURERERERERKbM9e+Drr30FEvhqo6Sk6ImlOXPAudhvagsllpwr3Dd9etG1mKRyUGJJRERERERERACfyBkxAr76KvFzvvzSv+UtlFiqVg1atIg+FW72bL+Nl1jauRM2bfKft2yBFSsKF/uWykOJJREREREREREBfDLokUfg979P/JxRo/y6SL16Fe4766zoFUuzZvkpcykp0fss/ma4GTP8VomlykeJJREREREREREB4L//9dvPPoONG+O337QJXn8drr8eatcu3N+qlU8shU9lC5k1y1crmUXvN5RYWrDAb3Nz/bZDh/gxydGlxJKIiIiIiIiIAD6x1KAB5OfDW2/Fb//cc3DgANx+e9H9rVr5Rbo3by66/9Ahv8ZSrGlwAM2aQcOGMG2a/zxnDiQnQ6NGid+LHB1KLImIiIiIiIgI+/fD55/D0KHQvj28/Xb8cz7+GLp3L6wwCon2ZrglS2Dv3viVRyecAD16wOTJ/vOcOZCRkdh9yNGlxJKIiIiIiIiIMH06fP89DBgA55zjF9mONJUtZN8++OYb6N275LFWrfy2eGJp1iy/jVexBH7NpoUL/XS7+fOVWKqslFgSERERERERkYKkT5cu0LYtfPddyals4aZP99Pgzjmn5LEWLfwaSsXfDDd7NiQlQbt28ePp2dNvX3nFV1MpsVQ5KbEkIiIiIiIiIuTm+nWNkpMLEz8LF0Zv/9VXfhtKAIWrWROaNo1csZSWBjVqxI+na1eoXh3++U//OTMz/jly9CmxJCIiIiIiIiLk5vrkjZmvWILCt7JFMmmSb9ekSeTjoTfDhQu9ES4RtWtD//6+6qlatcKYpHJRYklERERERETkOJef7xfIDlUFpaRAnTrRK5by833FUqRpcCGtWhWdCrdxI2zYkHhiCfwC4s8/798+V6tW4ufJ0VO9ogMQERERERERkfLjnE/EDBkCp52W2DnLl8OePYVvazvhBP+mt2iJpQUL/BpM8RJLmzfDrl1Qr55fXwnivxEuXN268NOfJt5ejj5VLImIiIiIiIgcQxYuhJtvhoceSvyc3Fy/DV/HqG3b6FPhJk3y21iJpbPO8tvQdLgpU/w0u06dEo9LKj8llkRERERERESOIZMn++2oUXDwYGLnjBrl39aWlla4r107+PZb+P77ku0nTYJTT4WWLaP32aqV3y5ZUnhOZiY0aJBYTFI1KLEkIiIiIiIicgwJva1t0yb47LP47V9/HUaPhvvv9wtmh4QWy160KPI1zjnHVyBF066df6vbjBk+wTVlSuwKJ6malFgSEREREREROYZMngwDBvjKoDffjN320CH43e+ga1cYMaLosVBiqfg6S2vXwooV8ZNEtWr5CqVvvvHrK+3ZA717l+5epPJTYklERERERETkGLFli68wOvdc6NmzcMHsaKZNa8SKFXDXXVCtWtFjrVv7RbyLJ5Y++cRv+/ePH0/Xrj6xNHGi/9yrV2L3IVWHEksiIiIiIiIix4ipU/22Rw+/xtHSpf4tcdGMGZNMcjJcfHHJYzVr+jWUii/g/cEH0LQpZGTEj6dbN9i5E5580seTkpL4vUjVoMSSiIiIiIiIyDEiJ8eve9S5s38r265dvoopkj17YPr0hlx3nV+4O5K2bYtWLO3fD59+ChddFHt9pZCuXf12xQr4xS9Kdy9SNSixJCIiIiIiInKMmDED2rSBunV9Ygl81VIks2ZBfr7Rs2f0/tq1g8WL/VpMABMm+ITURRclFk9aGtSpA8nJ8NOfJn4fUnUosSQiIiIiIiJyjJgxAzp18j/HSyxNn+63nTtH769tW1+ltHKl//z1175SqW/fxOKpVg0efxxeeskv5i3HnuoVHYCIiIiIiIiIHL4tW2D16sLEUvPmPgm0bFnk9jk50KjRfpKTa0bts107v503z6+RNHeu39apk3hcw4cn3laqHlUsiYiIiIiIiBwDZs70244d/bZmTWjWLHrFUk4OtGmzK2afHTpA9eqFi4LPnQvp6eUUsBwTlFgSEREREREROQbk5PhtKLEEfjpcpMTSnj1+Ue42bXbH7LN2bZ9cmjLFT4lbvBjaty/HoKXKU2JJREREREREpIpbtgz+8hfIyoKGDQv3R0sszZ4N+fnxK5YAevb0FUvz5/tFvJVYknBKLImIiIiIiIhUccOG+aTP6NFF97drB1u3wqZNRffn5vptq1axK5YAevSA77+HN97wn5VYknBKLImIiIiIiIhUMvv3wx13wJIl8dvOmgWTJsF990Hr1kWPhZJAc+cW3T9nDtSvD6ecsj9u/z16+O1LL/n1ltq0iR+THD+UWBIRERERERGpZD79FJ54An78Y9i3L3bbp5+GE0+E668veSy00HakxFL79v6tcfGceSakpsLmzf6cGjUSuwc5PiixJCIiIiIiIlLJfPABJCX5tZAeeSR6u/374bXX4Kqr4OSTSx4/9VRo1KhoYsk5n1jKyEgsFjP/xrlp0+C990p3H3Lsq17RAYiIiIiIiIhIIefgww/hootg7VqYODF62wUL/PpHAwdGPm7mq4zCE0vr1sH27YknlsBXRHXtmnh7OX6oYklERERERESkEpkzB9asgQsvhLZtYfHi6G1Di3BnZkZv0749zJvnE1ah/qF0iSWRaJRYEhEREREREalEPvjAby+4wC+UvWYN7NkTuW1uLtSqBWedFb2/9HTYudP3A4WJJb3dTcqDEksiIiIiIiIiR8CWLfDDH8KKFaU7b+xY6NYNTj+98A1sS5dGbpub6xNH1WMsdBOqZpo1y2/nzIHkZGjYsHRxiUSixJKIiIiIiIjIETB6tK8+euqpxM9Zv94vkj1kiP8cSixFmw6Xmxt7GhxAhw5+raUZM/znuXM1DU7KjxJLIiIiIiIiIkdA6A1qr74KeXmJnfP++377ox/5bWiKW6TE0qZNsHFj/MRS3bqQmuoTSwcPwvz5SixJ+VFiSURERERERKSc7dwJn3/ukz6bNsFHHyV23nvvQYsWfnobQJ06kJISObE0e7bfJpIk6tTJJ5aWLoX9+7W+kpQfJZZEREREREREytm4cb5K6fHH4eSTCxfkjmX3bhg/3lcrmRXub9MmcmJpwgSoVg26do3fd+fOfvHuzz7zn1WxJOVFiSURERERERGRcjZtGtSsCb17++qjhQvjn/Ppp76aKLS+Ukhqqj/fuaL7P/vML/Jdv378vjt18ttXXoETToB27RK7D5F4lFgSERERERERKWcLFvhKo+rVfWJo0aL454wZ46ubzjmn6P60NNi+3S/sHbJjh09enX9+YvF07OiroKZNg9at4cQTE78XkViUWBIREREREREpZwsWFFYFtW0LmzfDtm3R23/6qV/k+8c/hqSkosdC6y3Nm1e4Lzsb8vPhvPMSi6dBAxg1yvf/s58lfBsicSmxJCIiIiIiIlKO9u2DFSsKE0upqX4brWpp1y644gpfmfTooyWPR0osffkl1KoFZ5+deFw//jGMHg3/+7+JnyMSjxJLIiIiIiIiIlHs2uXf7lZ8faNYFi/21UThFUsQPbE0eTJ89x089hjUq1fyeJMm0KhR0cTSokV+SlvNmonHJXIkKLEkIiIiIiIiEsGXX8IZZ/jpZv/+d+LnLVjgt6HEUosWfnpbtAW8J03yb3fr0SPycTNftRSeWFqyxCeWRCqaEksiIiIiIiIiEbzzDhw86KeyPfpo4lVLCxb4N6+1aeM/V68OrVpFr1iaNMkvrl23bvQ+Q4kl5+DQIVi+HM46q3T3I3IkKLEkIiIiIiIiEsHq1XDmmXDPPTBnDvz3v4mdl5vrq5Rq1Src17Zt5MRSXh5MnQq9esXuMz0ddu6EtWth1Sp/niqWpDJQYklEREREREQkgtWrISUFrroK6tSBjz+Of86UKTBmDFx0UdH9qamwdKmvgAo3cybs3QvnnBO736yswvZLl/qfVbEklYESSyIiIiIiIiIRrFkDTZtCjRrQvLlPNMVy8CDceKM/5w9/KHqsbVtfZbRiRdH9X3/tt9HWVwrJyvLT66ZP9+srgSqWpHJQYklERERERESkmLw8WL/eJ4kAmjXzU9Bi+fe//TpIkd7ulprqt8Wnw82cCaecAsnJsfuuUwfS0goTSyeeCKefnvj9iBwpSiyJiIiIiIiIFLNunV8oO9HE0v79cP/90LUrXHppyeOhxFLxN8PNnOkX7jaLH1OXLoWJpbPO8hVMIhVNX0MRERERERGRYkLT3lJS/LZpU9i82a+HFMnXX/tz7rkncpKoYUNo0qRoxdL+/b7CqWPHxGLq0gU2bYIvvvCLeYtUBkosiYiIiIiIiBQTSiyFVyyF7y9u+nS/jfV2t9TUohVL8+b5dZlKk1gCX6n0wAOJnSNypCmxJCIiIiIiIlLMmjV+WzyxFG06XE6Or2465ZTofbZtW7RiaeZMv000sZSV5RNXL76ohbul8qhe0QGIiIiIiIiIVDarV0P9+v4fJJZYClUURZOa6qfTbdvmp8bNnOkX+W7VKrGYataESZMSaytytKhiSURERERERKSY1asL11cCOOMMv3ZSpMTSjh2weDF07hy7z+Jvhps5Ezp00CLcUrXp6ysiIiIiIiISJi/PL8bdtm3hvho14LTTIq+xFJrSFi+xFOpv0SI4dAhmz058GpxIZaXEkoiIiIiIiEiYsWNhwwYYNqzo/mbN4NtvS7afMsVv4yWWWrSApCS/gPfSpbBnjxJLUvUpsSQiIiIiIiLHNOdgwYLE2z/zjE8iXXBB0f3Nm8OKFSXbjxnj11eKtXA3QPXqcNZZvmKptAt3i1RWSiyJiIiIiIjIMe3Pf4a0NJg/P37b3bvh88/h2muhWrWix1q29BVLBw8W7luzBqZNg0svTSyW1NTCxFJSko9LpCpTYklERERERESOWevXwx/+4H/+/PP47WfP9hVO3buXPNaypV8bKXydpTFj/PaSSxKLp21bPw1u+nRo396v3SRSlSmxJCIiIiIiIsesxx+H/fuhYUP48sv47XNy/DbSekktW/rt8uWF+8aP99Pbwhf6jiU11S8Onp0NXbsmdo5IZabEkoiIiIiIiByzZsyArCwYNMgnlpyL3/7UU+H000sea9XKb8MTS4sXQ0ZG4vGkpvrt6afDyJGJnydSWSmxJCIiIiIiIseshQt9NVHv3n5aXHhSKJKcHF+tZFbyWEqKX4A71MehQ7Bsma9YSlSnTnDddfDee5GTVyJVjRJLIiIiIiIickzatcsvrt2unU8sQezpcN9/7xf47tQp8vFq1fyb4UKJpbVr4cCB0iWWataEl1+Ofg2RqkaJJRERERERETkmLVrkt23b+uRSw4YwcWL09tOmQX5+5PWVQlq2LEwsLV3qt61bl0+8IlWREksiIiIiIiJyTFq40G/btoUTToBzzoldsfTCC1C/Ppx/fvQ2kRJLpalYEjnWKLEkIiIiIiIild6aNfDXv8LBg4mfs2CBXxMplPjp08cngzZsKNl261YYPRquuQbq1o3eZ+vWsG2b72PJEj+17YwzSncvIscSJZZERERERESk0rvlFvjlL+Hf/078nIUL/ZvckpL851jrLL3xBuzfDzffHLvPXr38duJEn6Rq1cpXQ4kcr/T1FxERERERkUrtyy/hww+hVi0YORL27UvsvPnz/TS4kI4doXbtyOssTZkCTZtCZmbsPjt18hVN2dk+saT1leR4p8SSiIiIiIiIVGp//zs0aQKjRsGqVfDuu/HP2b7dL97dpUvhvqQknzhasKBk+zlz4ieVQn306gXvvef7b9cu8fsQORYpsSQiIiIiIiKV2pw50KMHDBwIZoVve4vl66/BOejZs+j+Zs18circgQM+2ZRIYgmgXz9Yu9avr3TbbYmdI3KsUmJJREREREREKq2DB/0i2e3a+UROSgqsWBH/vK++gmrVoFu3ovubNYPVq33SKWTRIn+djIzEYgq9Ne6++7Rwt8gRTyyZWTUzm2lmHwSfG5rZp2a2JNieHNb2HjNbamaLzGzgkY5NREREREREKrdlyyAvD9LS/OcWLWD58vjnTZ4MHTqUfMNb06Z+jaYtWwr35eb6baKJpS5dYNYsuPPOxNqLHMuORsXSHUD4DNYRwGfOudbAZ8FnzCwNuBJIBwYBT5tZtaMQn4iIiIiIiFRS8+f7bWgto5Yt41cs7d5dnalT/fS54po189vw6XBz5vi1k1JTE2iRE6AAACAASURBVI+rQwc/LU/keHdEE0tmlgJcCDwftvtHwMvBzy8DF4ftf9M5t9+5/8/enUdnVZ77///cJMyzA5OMGUmYx6CgAqKitdJqa6311Go9tmp72no6nA6n33adn99vq6ej1WPtUetUJ0TFqogMQYIQyMQQCPMgIoPMYyDJ/v1xZfs8yTPtAAkJeb/Wyrrz7L3vzX72cin99Lqv29ssaYOkWkWLAAAAAICm6pNPpBkz6jbHb7Tt7+42YIC0Y0f8neEeeyxVJ05Id90VeS5asLRihQVXLVvW7dkA1H/F0h8l/VhSVdix7p7nfSJJ1WO36uOXSPoo7Lrt1ccAAAAAAOeBP/1JuvlmaevW4HNWr7blax072ueUFOuPFOseS5ZI777bUz/+sTRyZOT5Pn1s/Cjsf32uWSMNGhT8mQCEJNfXjZ1zN0ja7XleoXNuYpApUY55ERc5d4+keySpe/fuys3NlSQdOXLks98RH+8qON5V3fC+guNdBce7qhveV3C8q+B4V3XD+wqOdxXc+fKu5s0bKukC/eUva/W5z30SaM7SpaPUo8cp5eZaI6T9+ztJGqk331yhsWP3RVz/+OMpSk7urQkTFik3tzLivOdJrVpdrkWLdmjo0I0qL2+hrVsv18SJW5SbW4fE6zxxvvyzhXOn3oIlSeMl3eicu15SG0mdnHPPS9rlnOvped4nzrmeknZXX79dUp+w+b0l7ah9U8/znpD0hCSNHj3amzhxoiQpNzdX/u+Ij3cVHO+qbnhfwfGuguNd1Q3vKzjeVXC8q7rhfQXHuwrufHlX27fbuGVLpiZOTNzQqKLC5txwgz77/pmZ0r/9m9Shw1BFeyX33y8NG7ZP119/ecz79u8veV4fTZzYRytWWNg0deoATZw4oO5fqok7X/7ZwrlTb0vhPM/7qed5vT3P6y9ryj3P87zbJc2UdEf1ZXdIerP695mSbnXOtXbODZCULmlpfT0fAAAAAKDh7NljPZZatZLmzJEqI4uJIpSVSceP11zS1qOH1KZN9J3htmyxpXM5OZGVTOH69g31WCors9Hv4QSgbhpiV7jafiPpaufceklXV3+W53mlkl6RtFrSLEn3e54X4F81AAAAAIDGboWtZNPXvy4dOCAVFCSeU1hoY3iw5JyUliatWxd5/bvv2piTszfuffv0qRksOSelpyd+HgCRGiRY8jwv1/O8G6p/3+t53lWe56VXj/vCrnvQ87xUz/MyPc97tyGeDQAAAABQ//xg6bvftTE/P/GcwkKpfXtb/hYuO9sqk2pbuFDq3Vvq0+d43PtmZFj11P79Fiz16ye1axfgSwCIcC4qlgAAAAAAzczy5baMbehQqXt3qago8ZyiImn4cCkpqebx7GxbCne8Vn5UXCyNGmUVSPGMHm1jYaG0di3L4IAzQbAEAAAAAKh3CxeGAp2RIxMHS59+KpWU1FwG5xs0yBpur10bOnb0qH0ePjzxs/j3XLaMYAk4UwRLAAAAAIB6tWGDVRhNnWqfR460pWwnTkS/fsUK66N0/Lg0bVrk+exsG8OXw61caWHTiBGJn+eCC6SUFOmxxyyQysmp2/cBEEKwBAAAAACoV7Nm2RgeLFVWWhgUzTPPWOi0YoV01VWR59PSpORkqbQ0dKykxMYgFUuSVU9t3y516hQ9vAIQDMESAAAAAKBezZolpabajxSqKoq1HG72bOnyy23JWzStWtkubuEVS8XFUteuUt++wZ7JX5Z3yy1S27bB5gCIRLAEAAAAAKg3O3ZI8+aFqpUkqX9/qXPn0E5xta9ftUq65pr49629M1xJiVUrJWrc7Zs8WWrZUrrnnmDXA4iOYAkAAAAAENiePdIHHwS71vOkb3/bfv/+90PHnZMyM2s23/a9/76NQYKlDRuk8nKposJCqiD9lXyjRkmHDkljxgSfAyBS8rl+AAAAAABA01BVJd10k7R4sbRrl3ThhfGvX75ceust6Te/sb5I4TIzpfnzI+fMmyddfLE0ZEj8e2dn2/OsWyclJVlPpqD9lXxt2tTtegCRqFgCAAAAAATy179KeXnWePvttxNfv2CBjbfdFnkuI8OaZx89WvN4SYlVEbVI8L9W/Z3hSkutv5JUt4olAGcHwRIAAAAAIJAnn5TGjpV69ZJmzkx8/QcfWD+lPn0iz2Vm2rhuXejYyZPSmjXS0KGJ752RYeHT6tUWLLVuHbongIZDsAQAAAAASMjzLATKyZE+/3nb6e3EifjXL1xou7tF44dA4X2W1q6VTp0KFiy1aWPL61avtiqnIUOsGTeAhkWwBAAAAABIaNcu6fBhKT3dgqWjR6VFi2Jfv3atNfq+4oro59PTrYl3eLDk7xIXJFiSbDmcvxSurv2VAJwdBEsAAAAAgITWr7cxPV0aP95+X7Ik9vULF9oYq2KpbVupb9/IYKlVK1vmFkR2tlRWJu3bZ0v0ADQ8giUAAAAAQELhwVKXLraULT8/9vULF0rdusUPiTIzawZLy5dbWBR0SdvIkTbeead0xx3B5gA4uwiWAAAAAAAJrV8vJSdL/frZ55wcaelS66UUzQcfWLWSc7HvmZlpfZv8eyxfHnwZnCTddJP1V3rySat0AtDwCJYAAAAAAAmtXy+lplq4JFmwtGuXtG1b5LXbtklbt8bur+TLzJSOHJF27LCfnTulUaOCP5Nz0rBh8cMrAPUr+Vw/AAAAAACg8Vu3zpbB+fyeRkuXhqqYfIn6K/nCd4Y7csR+Hz36zJ8VQMOhYgkAAAAAmpn9+6XNm4NfX1UlbdhQM1gaOtR6IRUVRV6/cKHUqVPiZW3hwVJBgdSiBbu7AU0NwRIAAAAANDP33SeNGGG7qQWxfLl0/HjN0KdVK1saF95827d4sTRunJSUFP++l1witWtn1VAFBdKgQfYZQNNBsAQAAAAAzcixY9LMmdLBg9LDDwebM2uWjddcU/N47V3dJOnoUWnVKuvBlEiLFrZrnF+xVJf+SgAaB4IlAAAAAGhG3nvPwqXMTOlPf5L27g02Z/hwqUePmsczM22JXGVl6FhRkS2d83swJZKZaUvn9uwhWAKaIoIlAAAAAGhGXntNuuAC6emnbXnb7Nnxrz90SFq0SLr22shzGRnSyZPSli2hY0uX2jhmTLDn8XeGGzBAuuWWYHMANB4ESwAAAADQBL3+uvTXv9ZtTnm59NZb0rRpVlHUpYs0d27s648elW6+WaqokL74xcjz4c23ff4ucd27B3umz31Ouvpqaf58qVu34N8FQONAsAQAAAAATYznST/4gfTAA1Z1FNTcuVaBdPPN1lh78mRpzhy7XzQPP2xznn46es+kWMFS0GVwkl07e7aFUQCaHoIlAAAAAGhi8vOlrVutV9KcOcHnvfaa1KmTNGWKfZ4yxe6zaVP06+fNk0aPlr7xjejnL7pI6to1FCwdPmzL4oYNC/5MAJo2giUAAAAAaGJefFFq3Vrq2FF6881gcyoq7NobbrC5klUsSVJubuT15eVWfXT55bHv6ZxVLZWV2ed162zMygr2TACavuRz/QAAAAAAgOA8zyqPrr9eatXKeiZVVtrStnheftl2gLv11tCxtDQpOVnauDHy+mXLLFyKFyxJ0ogR0vPP2zP4AdPAgXX7TgCaLiqWAAAAAKAJ2bpV+vhja3g9daq0e7e0fn38OZWV0n/9lzRkiDXL9iUlSX371tzVzbdwoY0TJsS/d06OLYErK7MlcUlJUmpqnb4SgCaMiiUAAAAAaEIWL7Zx3Dhb3iZJa9bErxJ6+WULfV59VWpRq7xgwABp8+bIOXl5tqTtooviP4/f1HvpUguXUlJCS+0AnP+oWAIAAACAJmTxYql9e6s+8sOkNWtiX+9XKw0eLN10U+T5/v2jVywVFgbb3S0jQ+rc2RqKl5WFdooD0DwQLAEAAABAE7JkiTRmjPVG6thR6t07frA0fboFPr/8ZWS1kmQVSzt3SsePh47t3Cnt2mX9kxJp0cICqMWLrXk3/ZWA5oVgCQAAAACaiOPHpeJiWwbny8qKHyzNmGHh0803Rz/fv7+NW7eGjpWU2BgkWJKkSy+VVqywZt8ES0DzQrAEAAAAAE3EkiXWV+myy0LHsrKsIsnzos8pLLQ+SNGqlSSrWJJq9lkqLrZx2LBgz/XDH0o/+IEFUZMnB5sD4PxA824AAAAAaCLefVdq2VKaODF0LCtLOnpU2r5d6tOn5vX790sbN0p33x37nn7FUnifpZISC5w6dw72XB07Sr//fbBrAZxfqFgCAAAAgCbi7belK6+0IMeXlWVjtOVwhYU2jh4d+549etgubuEVSyUl0vDhZ/68AM5/BEsAAAAAcI68+qr08svBrt2yRVq9Wrr++prH4wVLBQU2jhwZ+74tWkj9+kkbNtjnQ4ek9esJlgAEw1I4AAAAADgH9u2T7ror1DOp9jK22ubOtXHq1JrHL75YuuCC2BVLKSl2Pp6xY6XZs61P05IlNl56afDvAqD5omIJAAAAAM6BP/9ZOnJEqqyU/vM/E19fWCh16iRlZtY87lz0neH8kCjeMjjfxInS7t12j0WLrIopfOc5AIiFYAkAAAAAGtjJk9Ijj0g33ijdf7/07LPSgQPx5xQW2pK2aLu7RQuWNm60ht5XXpn4eSZNsnH+fAuWhg6t2ccJAGIhWAIAAACABpaXZ0vh7rxTuuYaqy5avjz29RUVTsuXS6NGRT8/cKC0Z4+0d2/o2Lx5Nk6enPh5BgyQ+vaV5syxKqfx44N/FwDNG8ESAAAAADSwd96RWrWSpkyRRoywY8XFsa/furWdystjN+GO1sB7/nypZ8/IpXPROGdVSzNnSkePEiwBCI7m3QAAAADQwN5+25aodehgP927SyUlsa9ft87WpcWqWPKDpbIyacIEq4CaN0+6+moLjYL4+c+l1q2lrVula6+tw5cB0KwRLAEAAADAGXjrLas+ChrGbN5sAdC3vhU6NmJE/IqltWs7qkMHKT09+vl+/aS2baXVq+3zhg3WjDtIfyVferr0178Gvx4AJJbCAQAAAMAZeeAB6eabpS1bgl2/cKGNU6aEjg0fbqFQeXn0OUVFXTV+fPTG3ZIdz86WSkvtc0GBjWPGBHsmADhdBEsAAAAAcJqOHbPd144erVmBFE9RkVUXDRwYOjZihFRREQqGwm3eLH30UTtdd138+w4dGmoAXlhoy9oGDQr2TABwugiWAAAAAOA0lZVZP6Nhw6TZs6UDBxLPKS6265PDGpMMHmyjv5Qt3KxZNk6dGv++Q4dKu3bZT0GB/RktWwb7HgBwugiWAAAAAOA0+RVGX/uajeG7skVTVWXBUu3d3VJTbTnb2rWRc2bNknr2PK6MjPj3HjrUxuXLrSpq9OjEzw8AZ4pgCQAAAABOU2mpVQXdeKN9ThQsbdwoHT4cGSy1bi0NGBAZLFVVSfPnS6NH70+4u5sfLM2YYX9GrB3kAOBsIlgCAAAAgNNUWiplZkppaVKbNtGXsoXLz7exdrAk2X1qB0vr1llIlJ19KOGzXHSR1KuX9MIL9pmKJQANgWAJAAAAAE5Taak1yE5KsmAoXrB07Jj061/bsje/p1K4zExp/XqrUvItW+afSxwsSVa1dOSIdPvt0pAhdfgiAHCaCJYAAAAA4DTs3Stt2RIKibKz4y+F+3//T9qwQfrb36I31c7MlI4flz76KHSsoEBq317q2/dYoGe6807prrukJ59UwqVzAHA2ECwBAAAAaNb27JEeeEB68826zZs503aEu+46+5yVZUHT0aPRr3/zTWnKFGnSpOjnMzNtDF8Ot2yZLZtLSgr2TLfcYqFSq1bBrgeAM0WwBAAAAKDZOnTIlo/94Q9W7bNvX/C5M2ZI/fqF+iVlZ9sYbWe348dtmVxOTuz71Q6WKipsBzl6JQFozAiWAAAAADRbxcXSzp3W++jgQelXv0o858gR6a23pNmzpZtuCi05S0+3cf36yDkrV0qVldGbdvt69JC6dLG+TZItqztxgmAJQONGsAQAAACg2fJ7In3jG9bw+umnLQCK5+c/l268UTp50pae+VJTbdy4MXJOUZGN8YIl5yxEWrrUPq9caePQoQm/BgCcMwRLAAAAAJqtNWusOXafPtLkyVaNFG0pm+/4cenZZ6XPf15avlwaNy50rn17qWdPa9BdW3Gx1LWrLZ2LZ+xYacUK+3NWrrQm3xkZp/fdAKAhECwBAAAAaLbWrJEGDrRqoTFj7NiyZbGvf+016cAB6fvfj15JlJYWPVgqKrJqpUQ7teXkWMVUUZEFS5mZNOIG0LgRLAEAAAA4LyxYIH3ySd3mrFlju7lJFuK0by8VFMS+/tlnpZQUaeLE6OdTUyOXwp04YVVI8ZbB+caOtXHpUguWhgxJPAcAziWCJQAAAABN3tq1tpTtgQeCzzl8WNq+PRQsJSVJo0bFrliqrJQWL5amTpVaxPhfUmlp0o4d0tGjoWOLF1s/piuuSPxMPXpIfftK778vbdtGsASg8SNYAgAAANDk/fKXUlWV7dZ27FiwOWVlNmZnh46NHi2VlEinTkVev3at9WDyq4qiSUuzcdOm0LH58y2IuvzyYM81caL07rv2O8ESgMaOYAkAAABAk7Zpk/TKK9KkSVYp9PbbweaVlNjoVyxJ0ogRUnm5tH595PV+JZPfiymaaDvDzZtngVXnzsGe63e/s2V5EsESgMaPYAkAAABAk+b3RHr4YVtK9vLLweb97/9K6en24+vf38aPPoq8ftkyqUOHUOgTjV+xtG6djUePSvn5FnoFddFFFkY9/3ziXeQA4FwjWAIAAADQpJWW2lKzQYOs/9HChYnn5Odbg+zvfa9mv6S+fW3cti1yzrJl1oMpKSn2fbt0kTIyLBiSpLw8qaKibsGSJPXqJX3ta3WbAwDnAsESAAAAgCattNSWoLVpIw0dKu3ebT/xPPWU1LGjdMcdNY/36mVBU+1g6eRJWzoXbxmc7/Oft75Khw/bmJwsjR9ft+8EAE0FwRIAAACAJm3VKqtWkqTBg20sLY19vedJs2dLV11lS9vCJSdbuFR7KVxRkYVL48Ylfp7Pf96unT3bgqWcnMg/BwDOFwRLAAAAAJqs8nJpw4bIYGnVqthzNm2StmyRpkyJfr5v38iKpbw8GydMSPxM48dLXbtKTz9t/Z/qugwOAJoSgiUAAAAATdbatVJlZShY6tFDuuCC+MHS++/bePXV0c9HC5YWLbLG3N27J36m5GTprrtsd7qqKoIlAOc3giUAAAAATZa/5M0PlpyzqqV4wdKcORYehe8GF65vX2n7dguFJFs6t2hR3fok/fa30u2327K6Sy8NPg8AmhqCJQAAAACNxvHjFuQENXOm9S/KzAwd84OlaPc5ccJ6H11zjYVQ0fTpY0vs9uyxz+vX2+9BlsH5kpKk556TNm+W2rYNPg8AmhqCJQAAAADnnOdJjz0mXXSRNHas9SZKZP166ZVXpPvuk1q3Dh0fPFg6dMiqjmp7/33bre1LX4p93759bfSXwy1ZYuNllwX7LuFatar7HABoSgiWAAAAAJxzixZJ998vjRljgdA99ySe89vfSi1bSj/4Qc3j8Rp4T59ujbUnT459Xz9Y8neGKyiIrIoCABiCJQAAAADnXEmJjS++KN19t7RihXTsWOzrP/pIevZZu7ZHj5rn/H5LtYOlkyelN9+Upk2zQCqWAQNsmdzy5fa5oEAaOdKWtwEAaiJYAgAAAHDOlZVJnTpZSDR6tO305odN0Tz8sC2f+/GPI89dcIE1za4dLJWUSAcPSp/7XPxn6dzZlr3NnClVVEjFxfZMAIBIBEsAAAAAzrmyMmngQKsUGjPGji1bFv3aykrpmWekW28NLVurLdrOcMXFNo4alfh5pk2zIOrdd63hN8ESAERHsAQAAADgnFuzxoIlyaqNevWKHSyVlVlz7ilTYt9v8GBp9WoLoXzFxVKXLlL//omfZ9o0G//zP20kWAKA6AiWAAAAAJxVR47YMrWgDh2SduwIBUuSVS3FCpb8XdrGjYt9z8GDrdJo06bQseJiacQIq4pKJCNDGjLE+ixdfLGUmpp4DgA0R/UWLDnn2jjnljrnljvnSp1zv64+Ptw5t8Q5V+KcK3DOjQ2b81Pn3Abn3Frn3LX19WwAAAAAzr7Dh63Sp1Mn6ckng89bu9bG8GBp5Ehp3Trp6NHI6/PzrfIoPT32PWvvDFdRYQ3BR4wI/lxz5kh5eVJhodSC/0seAKKqz389lkua7HneMEnDJU11zo2T9JCkX3ueN1zSL6s/yzmXLelWSYMkTZX0mHOOfRcAAACAJmLmTPtp106aPj34vLIyG8ODpawsG9eti7w+P1/KyYkf9mRn2+gHS2VlVsFUl2CpWzdp/HipT5/gcwCguam3YMkzR6o/tqz+8ap/OlUf7yxpR/Xv0yS95Hleued5myVtkDRWAAAAAJqE9est7Pn616XcXOnYsWDz8vOl5OSay80yMmysHSwdOWJhUU5O/Hu2by+lpISCpaVLbRw5MtgzAQCCSa7Pm1dXHBVKSpP0qOd5+c6570t6zzn337Jg67Lqyy+RtCRs+vbqY7XveY+keySpe/fuys3NlSQdOXLks98RH+8qON5V3fC+guNdBce7qhveV3C8q+B4V3XTnN9XXl6WunXrpP7916m8fJgeeWSFcnL2xbz+yJEjeuWVxXriiRxNnrxbH35Y9tm5EydaSLpCs2ZtVvfuWz87vnJlZ1VVjVCbNiuVm7s37vP06DFY+fltlZu7TM8/n60LL+ysXbsWa/fuM/6qDa45/3N1OnhfwfGucKbqNVjyPK9S0nDnXBdJrzvnBstCoR94nveac+4WSU9KmiIpWgu9iJZ/nuc9IekJSRo9erQ3ceJESVJubq783xEf7yo43lXd8L6C410Fx7uqG95XcLyr4HhXddOc39dPfmK9jf7t34bpV7+SPv54qOK9itzcXL377qVyTnriiR7q169HjfN9+0onTw7QxIkDPju2erWNt98+JOEStYkTpYceknJyJqqkxPo/TZoU54Easeb8z9Xp4H0Fx7vCmWqQFnSe5x2QlCvrnXSHpBnVp15VaLnbdknh/2nordAyOQAAAACN3Pr11lC7TRvbsS0/P/Gct9+WbrhB6tcv8lxmZuRSuJUrpc6dpd69E9978GBr2v3889L+/dLUqcG+BwAguPrcFe7i6kolOefayqqSymRh0ZXVl02WtL7695mSbnXOtXbODZCULmlpfT0fAAAAgLNn714Lb/yd2gYNktaskbyINQghu3e31tat0hVXRD+fmWk7xoXfY+VKacgQyUVb71CLvzPcf/+39X6aMiXYdwEABFefS+F6Snqmus9SC0mveJ73T+fcAUl/cs4lSzqh6n5JnueVOudekbRaUoWk+6uX0gEAAABo5DZssDEtzcbsbOnwYenjj2NXF61Y0VmSdPnl0c9nZto9du6Ueva0gGnVKulrXwv2TJmZ1hR83TrpllukCy+swxcCAARSb8GS53krJEVs5ul5Xp6kUTHmPCjpwfp6JgAAAAD1Y331OgS/Yik728bVq2MHSytXdlbHjtKwYdHP+zvDrV1rwdJHH0kHD1rFUhCtWkm33y61ayf98Y/B5gAA6qZBeiwBAAAAaDoqK6W//13avj34nPXrbbnZgOo+2+HBUiwrV3bWZZdJSUnRz/sh1caN/vU2Bg2WJOnpp6VHH5Vatgw+BwAQHMESAAAAgBreeEO6804LcObNCzbnww+lrCypdWv7fPHFtvRszZro12/bJm3e3EGTJsW+Z58+tpRt0yb7XFJio987CQBw7hEsAQAAAKjh0Udt+VqHDtLDDye+/tgxaeFC6Zprah7Pzo5dsTR9uo033xz7vsnJtlucX7FUWGjL4zp3TvxMAICGQbAEAAAA4DOrV0vz50v33y9NniwVFyees2CBVF4uXXttzePZ2VJpafSd4V55RUpPP/xZs+9YUlJCFUsFBdKoqN1aAQDnCsESAAAAgM+89ZaNd94pjRwp7dplu7LF8957Ups20hVX1DyenS3t3y/t3l3z+NatUn6+NGlSrRNRpKZaxdKuXda8e/ToOnwZAEC9I1gCAAAA8JmiIql/f6l7d2lE9R7P8aqWjh2TXn7Zqpvatq15LivLxtrL4fLybBw7dl/C50lNlfbtk+bOtc8ESwDQuMQNlpxzvZ1zP3TOvemcW+ac+8A595hz7nPOOUIpAAAA4DxTWBhabjZ8uI3xgqW//MUqmn7608hz/s5wtRt4L18utWol9et3LOHzpKTY+MorknOhsAsA0DjEDIecc09LekrSSUm/lfRVSfdJmiNpqqQ859wVseYDAAAAaFoOHLBlZyNH2udOnaxiKFawdOKE9NvfStddJ02YEHm+Vy+7R+2KpeXLpUGDpOTkKM2XaklNtfHdd6WBA6WOHevwhQAA9S45zrnfeZ63KsrxVZJmOOdaSepbP48FAAAAoKGVlNgY3iB7xIjQ8doWLbJlavfdF/28c9F3hispka6/Ptgz+RVLJ09K//VfweYAABpOzIqlGKFS+PmTnudtOPuPBAAAAOBcKCy0MXy52cCB0ubN0qlTkdfPni21bClNnBj7nllZNYOlnTutmbe/zC6Rjh2tGuoXv5BuvjnYHABAw0nYJ8k5d4Nzrtg5t885d8g5d9g5d6ghHg4AAABAw8nNlXr3lrp1Cx1LS5MqK6UtWyKvf+89afx4qUOH2PfMzrYd3fZV9+levtzGYcOCP9fChVQrAUBjFaQB9x8l3SHpQs/zOnme19HzvE71/FwAAAAAGtCHH0r//Kd09901j6en27h+fc3jO3daSHTttfHvW7uB9+kESwCAxitIsPSRpFWe5yXurAcAAACgUTh4UPrOd6SZM6WqqsTX/+xn1mz7hz+seTwtzcYNtZpgzJ9v49VXx7+vHyz5y+FKSqS+faWuXRM/EwCg8QsSLP1Yik0krwAAIABJREFU0jvOuZ865x7wf+r7wQAAAACcvieekB59VJo2TXroofjXfvSRtGCBdP/9Uvv2Nc9dfLHt7Fa7YmnxYrs2UeVR375Su3ahYGn5cqqVAOB8EiRYelDSMUltJHUM+wEAAADQCFVVSY8/bk2vR46U3n03/vUzZtj4pS9FnnPOqpaiBUtjxkjJ8faZltSihTUAX7NGOn5cWruWYAkAzicJ/jMgSbrA87xr6v1JAAAAAJwVs2dLmzZJDz5ovZOefFKqqIgdAr36qjR0qJSREf18erpUUBD6fPy4LWn70Y+CPU92tlVElZZaI/CgO8IBABq/IBVLc5xzBEsAAABAE/H227ZM7aabpLFjpWPHQs2za/v4Y2nRoujVSr60NNsV7tQp+1xQYEHVpZcGe56sLFtul5dnn6lYAoDzR5Bg6X5Js5xzJ5xzh6t/DtX3gwEAAAA4PYsWSTk5UqtWFixJ0tKl0a99/XUb4wVLGRlWabRxo31essTGnJxgz+M38H7pJalDByklJdg8AEDjlzBY8jyvo+d5LTzPa1P9e0fP8zo1xMMBAAAAzd3evXW7/sgRa5B92WX2OS1N6tIldrD06qsW/GRlxb6nv3StqMjGxYul1FSpW7dgz+QHS/n50ogR1ncJAHB+CPSvdOfcTc653zvnfuec+0J9PxQAAAAAKTfXwht/CVkQ+fnWvHv8ePvcooU0alQoFAq3c6e0cKH05S/Hv2d2ttSmjS2B8zwLloIug5OsQqlXL6ueevzx4PMAAI1fwmDJOfeYpG9LWilplaRvO+cere8HAwAAAJq7t9+2kOiPfww+58MPbRw3LnTM75FU27vvWlB0003x75mcbFVLhYXS1q0WSNUlWEpOtj9/yZJQ9RIA4PwQZFe4KyUN9jzPkyTn3DOykAkAAABAPZo/38Y33rDm1336xL/e86R//lMaNMiWv/n69pU+/dSaeLdrFzq+YoXUtq00eHDiZxk9Wvr7361/k1QzuAqiZcu6XQ8AaBqCLIVbK6lv2Oc+klbUz+MAAAAAkKQDB6TiYukb37CqpeeeSzzn73+3Xkrf+17N4/362bhtW83jq1ZZBVGQnkejR1v/pmeftXBq6NAg3wIAcL4LEixdKGmNcy7XOZcrabWki51zM51zM+v16QAAAIBm6oMPLFC64w7rUVRSEv/6Y8ek//gP6630zW/WPOcHS1u31jxeWmrVTUGMGmXj7NkWMiUHWfsAADjvBfnPwS/r/SkAAAAA1PDWW7ZMbdw4W6q2alX86598Utq9W5o+PbICqW/1+oPwiqX9+6VPPgkeLGVnSz/9qVVS3X578O8BADi/JQyWPM9b4JzrIWmsJE/SMs/zdtb7kwEAAADN1P790gsvSLfdZruxDRlivZPKy6XWrSOvP3VK+u//tmqlyy+PPN+rl5SUVLNiqbTUxqDBUosW0v/9v3X/LgCA81uQXeHulrRU0k2SviRpiXPurvp+MAAAAKC5evpp6fhx6Tvfsc+DB0uVlVJZWfTrFy60aqQHHoh+PjlZuuSSmhVLfgVUkMbdAADEEmQp3I8kjfA8b68kOeculPShpKfq88EAAACA5qiyUnr0UWnCBGn4cDvmhz+rVknDhkXOyc21iqIpU2Lft1+/yIqlDh1Cy+QAADgdQZp3b5d0OOzzYUkf1c/jAAAAAOePkyelhx6yPkkPP2yfE5k1S9q0Sfrud0PHMjKkli2llSujz8nNtebanTrFvm/fvjUrlkpLrW+Sc4G+CgAAUQUJlj6WlO+c+5Vz7v9IWiJpg3PuAedcjGJbAAAAAL/6lfSTn1jPpB//WHrsscRzHnnEeiJ98YuhYy1bSgMHRm/gfeyYlJ8vTZwY/779+knbt1tFlGTBEsvgAABnKkiwtFHSG7LG3ZL0pqRPJHWs/gEAAAAQxZtvSldfLa1da8FOfn786w8ckGbPlu6808KkcAMHSuvWRc5ZssQqoSZNin/vrCyposKeYc8e20EuaONuAABiCbIr3K8b4kEAAACAxuh3v5Nef90qjm68Mfi8HTuk1astJJKsN1JJSfw5CxdKnmdhVG0ZGdKMGbYDXHjolJdny9nGj49/72nTpPbtpSeflP7lX+wYwRIA4EzFrFhyzj3hnBsS41x759xdzrmv1d+jAQAAAOfeCy9IixZZMFNYGHze3Lk2+g21hw+3iqNjx2LPyc2VWreWcnIiz6Wn2zK2LVtqHi8uttApXn8lSerYUbr1Vunll0OVUyyFAwCcqXhL4R6T9J/OuTXOuVedc485555yzi2U7QrXUdL0BnlKAAAA4BwoL7e+Rvfea8HNQw8FnztnjnTRRdLQofZ52DCpqip6nyTfggXW6LtNm8hzGRk21l4OV1wc2j0ukbvvlo4elX77W6lzZ+vlBADAmYgZLHmeV+J53i2Sxkh6VNJCSTMl3e153jDP8/7keV55Az0nAAAA0OBWrbKlZ5MmWbg0fbq0cWPieZ5nwdJVV0ktqv/G7Yc/y5dHn3PwoIVEsZpwp6fbuH596Ni+fdLWrdKIEYG+jnJyrCn4/v22DI4d4QAAZyph827P8454npfred6Lnue94Xne2oZ4MAAAAOBcKyqyceRI6bvftYqjl19OPK+szHos+cvgJKl/f1uOFqvP0jvv2P0nT45+/sILpa5da1Ys+fcKGiw5Jz36qHTBBdKYMcHmAAAQT8Lm3QAAAEBzVVRkS8ZSUiyUGT5cev996Wc/iz9vzhwbw4OlFi2sp1FpafQ5Tzxhf86ECdHPO2dVS+EVS3UNliSpZ08LvjqyvzMA4CxIWLEEAAAANFdFRRba+EvGrr7aGnkfORJ/3pw5UmqqVSmFy8yU1kap/1+3zhp3/+u/hpbORZORUTNYKi6WLrlEuvjiIN8m5OKLo/dxAgCgrk4rWHLOEUgBAACgyTl1Kvi1+/ZZcDN2bOjYNdfYPT74IPa8vXtbaf78mtVKvsxMaedO6dChmseff15KSpK+8Y34z5SRIW3bZg24pbo17gYAoD4EDoicc08652Y75zIl/X/1+EwAAADAWffHP1p1T5Dm25L0j39YiPTVr4aOTZhglT5z50afc/Cg9MMfDlNVlfTtb0eez8y0sfbObgsWSKNGST16xH+mYcOsMfiKFdLx47akrS7L4AAAONvqUnm0V9IXJP1cUp/6eRwAAADg7Dt5UnroIWnPHum224JVLj39tIU24RVBbdpYOFRWFn3Oiy9KW7a014wZ0SuJ/GApfDlcebmUnx+7t1I4/57FxdLKlVJlJcESAODcqkuwtM/zvGOS7pPUv34eBwAAADj7ZsyQPvlEuusuaelS6c03419fVGQ/d94ZeS4lRdq8Ofq899+Xunc/oauvjn4+NdV6KIUHS4WFFi4FCZb69LEd3YqLT69xNwAAZ1ugYMk510HSI5Lked4Rz/Mur9enAgAAAM6ip56yUOexx6R27eL3SJKkRx+V2reX/uVfIs8NGGDBkufVPF5ZKc2bJ40cuf+zZt+1tW5t88ODpbw8G4MES85ZkFRcbD+dO0c2CAcAoCHFDZacc/c557ZJ2ippm3Nuq3PuvoZ5NAAAAODMnTolffihdP31FuyMGxcKc6LZu9f6K91+u9SlS+T5lBTpxAlrwh2usFA6cEAaPXp/3OfJyKjZYykvz44F3dltxAhp1Spp2TJbGhcrxAIAoCHEDJacc7+QdIOkiZ7nXeh53oWSJkm6rvocAAAA0OgtX267qPkVQRMm2LHaO7P5Xn3VgqN7741+fsAAGzdtqnn8/fdtHDEifrA0cKBVLFVW2ueCAgu7gho+3JbOFRbW3LEOAIBzIV7F0r9IusnzvM/+k1n9+y2Svl7fDwYAAACcDX510vjxNl5+uVRVJS1eHP36uXOtl9HQodHPp6TYWLvPUl6eNGiQ1LVr/M7gI0aEdnTbudN6P9WlT9LkydKQIdIDD0g//3nweQAA1IfkeCc9zzsR5dhx51xV/T0SAAAAcPbk5VmV0SWX2Odx46yB9qJF0rXX1ry2qkqaP1+64YbYS8z8nkbhFUtVVbaz2803J36e0aNtLCwMLX8bOTLw11HPntKKFcGvBwCgPsWrWNrunLuq9kHn3GRJn9TfIwEAAABnh+dZsBTeGLtDByktTSotjbx+5UrrsTR5cux7tmkj9epVs2Jp/Xpp//5gS9oyMqwxeEGB7Twn2fI2AACaongVS/8m6U3nXJ6kQkmepDGSxkua1gDPBgAAAJyRjRulXbsid1zLzpZWr468ft48GydNin/fAQNqViwtWWLjuHHSnj3x5yYlWYVSYaFVH6WlSZ06xZ8DAEBjFbNiyfO8UkmDJX0gqb+klOrfB1efAwAAABrUunXS668Hv752fyVfdra0YYN08mTN4wsXWg+lPn3i3zclpWbF0pIlFg5lZQV7rlGjpOJi29mtLsvgAABobOLtCpcmaZTneU95nvfvnuc94Hnek5LGOOdSG+4RAQAAANupbdo06ctflg4fDjYnL0/q2jUy8MnKkioqLFwKV1QUbKe1AQOk7dttdzbJ+iuNHWu9m4IYPdoaeG/blrg6CgCAxizef/r+KCnaf7KPV58DAAAAGsyDD9pOapWVVlkURF6eVSvVDnyys21csyZ0bO9eaevWYDu0paRY/6Zt2yxcWrlSGjMm2DNJ0o03Sj/6kTRzpnTPPcHnAQDQ2MQLlvp7nhex34TneQWypXEAAABAg3nhBemqq6TWrUO9kOLZtUtauzayv5IkZWbaGN5nqbjYxiBL01JSbNy82UKlioq6LWnr2FF66CHp858PXuUEAEBjFK95d5s459qe7QcBAAAAYjl61EKcO++UqqqCBUvTp9s4dWrkufbtpf79owdLQSqWBgywcdMmacsW+51eSQCA5ije/z+yzDn3r7UPOue+KdslDgAAAGgQfgA0aJD1JCopsaVr8Tz7rDR0qDRsWPTzWVk1l8IVFUn9+kkXXpj4eXr1klq1srCrsFDq0iUUNgEA0JzEC5a+L+lO51yuc+531T8LJN0t6XsN83gAAAA43yxbJj3+eN3mlFbvSTxokDR5svU3WrAg9vVlZdLSpdIdd8S+Jjs71LNJsoAoSLWSZMvX+ve3iqWiIqtWci7YXAAAzicxgyXP83Z5nneZpF9L2lL982vP8y71PG9nwzweAAAAzieeJ911l3TvvdLrrwefV1pqvZVSU61Jdvv28ZfDvfyyBT233Rb7muxsa7y9ZYv1Y1q/Xrr00uDPlJJiPZxWrGAZHACg+YrXY0mS5HnefEnzG+BZAAAAcJ5bsEBatcqaV3/rW1Z91Llz4nmrVkkDB0rJ1X97nTBBmh/nb6jvvCONGyf16BH7mqwsG1evlk6csN+vvDLY95Bs6dusWfb75MnB5wEAcD5hDwoAAAA0mEcesR5GL70k7dkTfzlbuNJSWwbnmzzZAqGdUerod++25XbXXx//nuHB0oIFVgVVl8ojf2e4q66K3iAcAIDmgGAJAAAADWLbNumNN6S777YG3MnJ0uLFieft2CF99JE0eHDomF8hFK1q6b33bMldomCpSxepZ09r4L1ggTR+vNSyZfDvM26cdNFF0p/+RH8lAEDzRbAEAACABuE37L73XqltW2uUvWRJ4nl/+IM1y/7yl0PHRoywnkvFxZHXz5plS+CGD0987+xsaeFCW2pXl2Vwki3H2727ZiUVAADNDcESAAAA6t2JE9Lf/ibdeKPUr58dGzfOdm6rqIg9b98+6X/+R/rKV6S0tNDxpCQpPd12dautuNju3SLA33Szsmxnt/btpS99qW7fSaJSCQAAgiUAAADU2fTp0lNPBb/+n/+UPv3UqpV8l14qHTsmrVwZe94//iEdPSr96EeR5zIzbVe2cKdO2e5ufv+kRMaOtSV506dLGRnB5gAAgBCCJQAAANTJzJlWQfSv/xo/FAr33HNSr17W6No3bpyNS5fGnzd0qC19qy0z06qNTp0KHdu0ySqgBg4M9ly3327L2Wi+DQDA6SFYAgAAQGCeZ4HSsGHW/PoHP7Bj8Xz6qfTOO9Jtt9kSNl+/ftZrad266PPWrrXQ6etfj35+4EALkTZuDB1bs8bGoBVLzklduwa7FgAARCJYAgAAQGA7dliFzze/Kf30p9LcudKGDfHnvP22BUBf/WrN4y1aSKmptnQtmuees2tuuy36+cxMG8OXw/nBkn8OAADUL4IlAAAABLZ6tY3Z2dK119rv+fnx58yfL114YfRd2tLTowdLVVUWLE2ZIvXsGf2+0YKlsjLpkkukTp3iPxMAADg7CJYAAAAQWGmpjYMGWbjUvn3iYCk3V7ryyui7tKWnW1+kysqaxxculLZti70MTpI6d5Z69Ki5M9yaNcH7KwEAgDNHsAQAAIDASkuliy6SunWzfkmjR8cPljZvlrZulSZNin4+PV06edJCpHDPPWeh1Re+EP95MjJCPZo8z0ImgiUAABoOwRIAAAACW73aKpV8OTlSSYl04kT063NzbZw4Mfr59HQba/dpmjtXuu46C5fiSU218EqStmyRDh+WhgyJPwcAAJw9BEsAAAAIxPOsYmnQoNCxnBzp1CkLl6JZsMAqnMLnhPODpfA+SwcOWEg0alTiZxowwBqKHz8uLV9ux4YNSzwPAACcHQRLAAAAzdSLL0qvvRb8+h07pIMHa4ZEfkNuv6l3bYsXS5ddJjkX/XzPnlaVFB4srVhhY5CAKCXFxq1bLVhyjoolAAAaEsESAABAM7RokXT77dI3vykdPRpszj//aeOYMaFjffpYU+4tWyKv//RT63906aWx7+mclJZWM1jyq5+i7SJX24ABNm7aZMFSWlri5XMAAODsIVgCAABoZqqqpG98Q+rSxSqQXnwx8RzPkx55RBoxomaw1LKl1Lt39GBpyRIb4wVLUvRgqVs32/EtEb9iyQ+WWAYHAEDDIlgCAABoZtassWbZDz8sDR0qPfqoBUfxLFhg/ZW++93IZW39+kUPlhYvtp3jwoOoaNLTLRiqqLDPfkAUa/lcuO7dpbZtbc6mTcGqnAAAwNlTb8GSc66Nc26pc265c67UOffrsHPfdc6trT7+UNjxnzrnNlSfu7a+ng0AAKA5y8uz8YorrHKppET6+OP4c2bMsADnK1+JPNe/v/U4qu3DDy3oadcu/r3T0y1U2rZNKi+XVq0KXnnknC2He+MN+0zFEgAADSu5Hu9dLmmy53lHnHMtJeU5596V1FbSNElDPc8rd851kyTnXLakWyUNktRL0hznXIbneZX1+IwAAADNzqJFVumTmmqNtSVp2TJb0haN51l/pcmTo4dE/ftLL7xgu8O1bGnHysttKdw99yR+nvCd4bZvl06elCZMCP59UlKsefgll0hXXx18HgAAOHP1VrHkmSPVH1tW/3iS7pX0G8/zyquv2119zTRJL3meV+553mZJGySNra/nAwAAOB88/7w0a1bd5uTlSePHW7XPsGFScrK0dGns67dta6fNm6Ubboh+vn9/69u0fXvo2JIl0okTFkYlEh4szZ1rzcCvvDLw1/msgfd//IfUunXweQAA4MzVZ8WSnHNJkgolpUl61PO8fOdchqTLnXMPSjoh6Yee5y2TdImkJWHTt1cfq33PeyTdI0ndu3dXbm6uJOnIkSOf/Y74eFfB8a7qhvcVHO8qON5V3fC+gjsf3tWxY0m6++7L1LFjhf7xjyVq2TJBoyRJn37aSps3X6brrtug3FxLglJSRum99yp07bXLo85ZsKCbJKlr18XKzS2POH/gQBdJw/XGGyUaMeKAJOnvf++vFi36KSlpkXJzK+I+k+dJbdtO0Pz5O7V+fQdlZLRQSUlRwu/i69Onq8aO7a2MjFLl5lYFnldfzod/thoK7yo43lXd8L6C413hTDkvUafGs/GHONdF0uuSvivpJUnzJH1P0hhJL0tKkfQXSYs9z3u+es6Tkt7xPO+1WPcdPXq0V1BQIEnKzc3VxIkT6/FbnD94V8HxruqG9xUc7yo43lXd8L6Ca0zvyvOCNaqu7dlnpTvusN+fe066/fbEc156SfrqV61CyW+qfd99tpRt/36rFqpt6NADcq6LlkfPnbRpky2re+op6c477dgVV0jHj9sSuyBGjpQ6drS+TP/+79JvfhNsXmPUmP7Zaux4V8HxruqG9xUc7wrROOcKPc8bHeTaBtkVzvO8A5JyJU2VVSLNqF4qt1RSlaSLqo/3CZvWW9KOhng+AACAc6WiQpo4Ubr33sQ7s9X2wgu2DC07W/rDH4LNmTdP6txZGjEidGzMGOnQIWndusjrd+6UVq3qrJtuin3P3r0tkPJ3hjt2zJbCBVkG50tLkz74wN7HlCnB5wEAgHOrPneFu7i6UknOubaSpkgqk/SGpMnVxzMktZL0qaSZkm51zrV2zg2QlC4pzmp/AACAxuOhh+L3KYrlr3+1QOXxx6W//S34vE8/lebMkb72NatAKiqSjh5NPG/ePOtflBzWEMEPmVatirz+jTckz3O6+ebY92zVSurTR1q71j6Xlloj73Hjgn+fyy+XOnSQHnxQuuqq4PMAAMC5VZ8VSz0lzXfOrZC0TNL7nuf9U9JTklKcc6tky+LuqK5eKpX0iqTVkmZJup8d4QAAQFOwfLn0k5/UffnWsWPSL38pTZpkVUu/+EXwubNnW8PsadOkzEw7tmFD/Dlbt0obN0ZWEqWl2RitYmnGDKl372MaNCj+vceMCQVrpaU2JpoT7jvfkQ4fln72s9NbFggAAM6Nemve7XneCkkjohw/KSlqBwDP8x6U9GB9PRMAAEB98CuN5s61Sp2WLYPNW7JE2rdP+uEPrVooN1c6eNCWqiXy3nvSRRdJo0aF/rx162yXt1jefdfG2sFShw5Sr162K1u4U6esmurGG/fKuXZxnycnR5o+Xdq924Kl1q2t71JQhEkAADRNDdJjCQAA4Hx17Jj0/PNSjx7Wp6guy+E+/NDGyy6TUlLs982bE8+rqrJg6ZprrLeRX3FUOxiq/ZwPPmhB1ODBkefT0yMrllavlsrLpYEDDyV8Jn/ZW36+hWQDB0pJSYm/CwAAaNoIlgAAAM7AokVWZfT731vI8957wecuXmzLxbp0kQYMsGObNiWet3y5tGuXNHWqffYrjqItZfP98Y/S9u32nNGqgzIyIoOpwkL/3JGEzzRypAVJS5ZYxVJdlsEBAICmi2AJAADgDBQU2Dh1qi0HmzMn2LyqKguWLr3UPvvBUpCKpfnzbQxvch0tGAo3fbp0xRX2E016urRnj3TgQOhYUZHUsaPUq9fxhM/Urp0tw3v/femjjwiWAABoLgiWAAAAzkBhoS1F69rVdldbvVryvMTz1q6V9u+3ZXCSze/cOViwtHixBVG9eoWORVvK5isvt+VpfogVTUaGjeHhVFGRfacWAf/GeM010rJl9jvBEgAAzQPBEgAAwBkoKLC+RZKFOwcPWkPuRPLybPTDHucsLEq0FM7zrDdT7ZAoI0P69FMLq2orLbVG3CNHxr5verqNfjhVWSmVlIS+WxC//rXtUuecNHx48HkAAKDpIlgCAAA4TXv2SFu3SqNH22e/ifaGDYnnzpsn9ewpZWaGjqWkJK5Y2rZN2rEjVOnk84OhaMvhiopsjBcSpaZaZZIfLJWVScePxw+jamvVypbclZZK/foFnwcAAJougiUAAIBq77xjVT9B+c2t6xoseZ4FS5Mn12ykPWCABUtVVbHnhu8kFy7aUjZfUZEts/N3noumdWt7/pUrQ3OkugVLkpScLGVl1W0OAABougiWAAAAJG3ZIn3uc9KvfhV8jt+42w9fBgywoChRsLRqlbR7d83m25IFP+Xl0iefRJ9XWWm7u3XrJg0ZEjk3vOIoXGGh9UqKthtcuGHDbMc5yYKldu1qVlQBAADURrAEAAAgaeZMG197LX7FULiCAgteOnWyz61bS337Jg6W5s61sXawlKji6ZFHpKVLpT/9ySqDwrVubcvPalcsnTplYVGQyqPhw63H08GDFiwNHy4lJSWeBwAAmi+CJQAAAFmw1KKFtHNnaLlZIoWFoWVwvrS06MvRwv3jH7ZrWt++NY/7y9nWro0+7y9/kSZNkr7ylejn09Mj/+yyMquCChIsDRtmY0mJVFxc92VwAACg+SFYAgAAzd6BA9KCBdK991rlz6uvJp6zc6e0fXv0YClexVJhobRsmfStb0We69vX/vxoy9k++UTauFG64YbYS9oyMmyu54WOBWnc7fN3cnvtNenwYYIlAACQGMESAABo9t54Q6qokG6/3Rpqv/9+4jm1G3f70tKkvXul/fujz3v8cetd9PWvR55r0cKqjqJVLC1aZOOECbGfKT1dOnTIdqvzFRVJ7duHdo2Lp1cv6cILpRdesM8ESwAAIBGCJQAAcF45dKjuc556yqp9cnLsp6zMKnbiKSiwyiG/ysfn90nauDFyzsmT0iuvSF/+su3SFk1mZvSKpbw8qW1ba8Idi7+ULnx+YWHwXknOWZi0b58FWIMGJZ4DAACaN4IlAABw3njySemCC6Q//CH4nHXrpIULpbvusmBlzBhbSuYvIYvlgw+kwYOlDh1qHo/XgHvhQgu+vvjF2PfNzLQG2qdO1TyelyeNGye1bBl7rl+V5PdZqqy0fkl1qTz685+ld96xpYG1G4QDAADURrAEAADOCwsWSHffLbVqJf3qV9Knnwab9/TTVs3jL00bM8bGZctizzl40IKlz30u8lxKio3RgqWZM6U2baQpU2LfOyPDluVt3hw6dviwNdMePz7+d+nXz77/mjX2ef166ejRugVLAwdK111ny/IAAAAS4a8MAADgvPDBBzbOny8dOSL99reJ51RUSM88I11/vdSzpx27+GILaOIFS7Nn29wbbog8166ddMklkcGS50lvvSVddZX1PIolM9PG8D5L+flSVVX8/kqSVRhlZoaCpfx8G/2wDAAA4GxufbmQAAAgAElEQVQjWAIAAOeFlSutWignxypu3nor8ZxZs2y3tW9+s+bxMWPiB0tvvWVL7saNi34+2s5w69ZZFVK0MCqc3ycpPFjKy7MKoksvjT9XkrKzpdWr7fcPP7ReTllZiecBAACcDoIlAABwXli5UhoyxH6/8koLZnbtij/nmWekbt2sYincyJEWAkVrBL53ry1pu/762A2xowVLCxfaOGlS/Ge64ALpootqNuDOy5OGDpU6dYo/V7KG25s3S8eOWbA0bhzL2gAAQP3hrxkAAKDJO3HC+gkNHmyfr7jCRj/Miaaiwmn2bGnatMiG2H6FT3jVkO/nP7eldj/5Sex7p6VZqBUeTC1caMvs/IqkeDIzQ3/2qVPSkiWJl8H5srNt2V1+vlRaKl12WbB5AAAAp4NgCQAANCoHDkhf/rK0eHHwOWvW2A5ofsXSyJHW68jvuxR9TicdOiRde23kuYEDbSwrq3l840bpiSek73wnFGJF4+/OtnFj6FhenoVDziX+PhkZoYqlkhJrwF2XYEmypuSeR7AEAADqF8ESAABoVP7nf6Tp06VbbpH27w82Z9UqG/1gqWVL60cUL1hatqyrkpKsmXZtqanWCNtvgu374AMLa7797fjPk5Zm4/r1Nu7YIW3aJF1+eeLvIlnF0s6dVvE0Y4YtuUu0hC78z27ZUnrlFZs3dmyweQAAAKeDYAkAADQa5eXSn/9s1UA7d0r/5/8Em7d8udSqVahSSLIG3KWlVskUzbJlFygnR+rSJfJcy5YW0NSuWFq61JphJ1rOlp5ulUl+MLVokY1Bq478+5eVSf/4h3T11dYLKoiWLW1+ebntjBekLxMAAMDpIlgCAACNxhtvWKD0hz9YmJKbm3jOqVPSSy9ZX6XwXkmpqVJFhfTRR5FzPv1UWru2Y9RlcL6BA6MHS2PGJG6G3a6dNGBAKFhatsyCr2HDEn8fySqWJFvOtm2b9LWvBZvn+8UvpL/+Vfr3f6/bPAAAgLoiWAIAAI3GBx9IHTvasi+/4ujo0fhzpk+XPv5Y+t73ah5PTbUxvM+Rb84cyfNcwmBpwwYLriTp+HFpxYrgS8uysqTVq+33oiJbpteqVbC5qakWXv3v/0rt20tf+EKweb5bb5XuuaducwAAAE4HwRIAAGg0liyx4CYpyYKlqioLZWLZscOqczIypOuvr3kuJcXGaMHSrFlSp06nNHp07HsPHGih0qZN9rm42CqgggZL2dm2s1tFhX2HUaOCzZOk1q2l/v3t+//971KHDsHnAgAANCSCJQAA0CgcPWq9ki691D6PGWPjsmXRr6+okK65Rtq9W3rmmcjlab1729I4PxjyeZ40e7Y0cuR+JSXFfp6sLBv95XD+c9QlWDp5Upo715qQ1yVYkqTf/1566y3pS1+q2zwAAICGRLAEAAAahcJCa7Q9bpx97t5d6tMndrC0cqUtlfvzn0NzwiUlWZ+j2hVLq1ZJn3wijRmzL+7z+H2O/GCppMSeqWfPYN8nO9vG556zceTIYPN806ZFVmEBAAA0NgRLAACgUViyxMacnNCxMWOkgoLo1y9ebOOkSbHvmZoaGSz9/+zdeXhV9bn+/3slzCiTzMiYkARCIEyCMgoKKAoOreLQVmur1tYOtrWD7e+0XzvYc6xtrbXVOqGt4ohaBIFAQkhIIMxDIDKJoAioDDKFkKzfH09W997JHtZGAiF5v67La2WvnWdl7XW2pz33eT7PZ9EiOw4atD/q/bRsaSGSFyytWeN/+LZkS+kkaeZM65zKyPBfCwAAcK4gWAIAAKfd7t3SxIk2/NqP8nLb2a1PH6lt28D5fv1sKdvx49VrCguljh2l7t0jX7dXLwuWXDdwbvFi64Tq2LE05n316WM7u5WVWXdUPMFSixY2++noUenaa21uEgAAQF1DsAQAAE6755+3OUYPPODv9597zoZj/3//X+j5tDQbYB0uoCostCVwjhP5uklJ0qFD0meVq95cV8rLk0aO9HdfaWnWsVRSYvOS4gmWJCk/X9qzR3r55fjqAAAAzhUESwAA4LR75RULfF55xZaQxfLQQxYS3Xhj6HlvOZm3HM3zySfS5s3hZysFS0qy4+bNdty+3XaSiydYOnhQmjvXXscbLLVtK7VvH18NAADAuYRgCQAAnFZbtkgrV1q3UrNm0tNPR//93but5ktfqt59lJJix5KS0PNLl9rR20Eukqo7u+Xl2XHUqOh1Hi/YevllqVGjwEBvAAAAGIIlAABwWr35ph2/+U0bWL1uXfTfz8+344gR1d9r3tzmIVXtWCoosF3fBg+Ofu2ePW22UXGxvc7Ls6Hc6emxP4cUCKaKiqSBA20INwAAAAIIlgAAwGlVVCT16CF162YBjhfqRJKfLzVpIg0aFP791NTqwVJhoS1La948+rUbNLCuJ+8eFi+2ACvB538D6tLF/unXT5o+3V8NAABAfUKwBAAATqtVqwIhUXq6tHevzUSKJD9fuugiW2oWTlqaLYXzdnYrL7elcLHmK3n69rWd3fbts4DK7zI4yZbmrV9vS/tYBgcAAFAdwRIAAAhr40ZpzBhp1y7/NYcO2aDsgQPttbfkbMOG8L9/9KgFUeGWwXnS0qTPP7eh25J1Hx0+HF+wtH27lJVlr/0O7va0asUSOAAAgEgIlgAAQFi/+52Umyv93//5r1m92o7BHUtS5GBp1Srp5MnoIVHfvqHXKCy0Y6zB3Z4+fazb6amnrCtqyBB/dQAAAIiNYAkAAFTz4YfSjBk2++ipp6RPP/VXt2qVHb1gqUsXqUWLyMFSUZEdhw6NfM2MDDuuXWvHvDypbVspKcnfPXnB1MKFFkY1aeKvDgAAALERLAEAgGqefdZmGb36qi1X8zu4euVKqVMnqWNHe+041rW0fn343y8qsvCpU6fI12zbVurc2XaXc10pO1saO9au7Ufv3lY/ZoyFZAAAADh9CJYAAEA1RUU22+iqq6Tu3QOdRdG4ri2du+ii0PMDB1onU3l5+L8TrVvJ07+/dSxt2ybt3Cldeqm/zyHZ8redO6WcHCk52X8dAAAAYiNYAgCgDjtwQHrmGamiIr66tWstzJGkAQMCy9Ci2bRJev996YorQs8PG2bDtzdtqn5vmzf7m3mUkWFDu+fNs9fxBEuSlMB/4wEAAKgR/NcsAADqsF/8QrrjDumtt/zXHDpkAZEXLPXvL5WUSMePR6975x07Xnll6Plhw+y4bFno+RUr7Oi3Y+nECemJJ2yZXVpa7BoAAADUPIIlAADqqJ07pX/+035+5BH/dd48pOBgqbzcOoaieecd6yzq2jX0fO/eUsuW0tKloeeXLLE5SX46lrx7WbNGmjLF/3wlAAAA1CyCJQAA6qhHHrG5R9//vu2ktny5vzpv2Zu3G9uAAaHnw5k/32YY3Xhj9fcSEmzuUtWOpYUL7dpt2sS+p759pdtus8/06KOxfx8AAABnBsESAAB1UHm59PLL0tVXS7/6lXX4zJ7tr3bdOqlFC6lbN3udlCQ1bWrdQuEcOybdeaeUmir98Ifhf+eiiyyYOnrUXh8/LhUUSOPG+bunBg1sp7of/EBq3NhfDQAAAGoewRIAAHVQfr60e7f05S/bMrRevQJL3GJZvdq6lbzlZomJUnq6BU7hzJtnM5keeURq0iT87wwebGGXdw8FBVJpafxDuAEAAFC7ECwBAFDL7dghPfaYBTN+vfqqhTxXXWWvMzIiB0PB9u+3WUijRoWeT0uT3nsvfM38+VLz5tL48ZGv6y2n87qeFi60wGr06Nj3BAAAgNqLYAkAgFrs8GFp8mTp3nulmTP91739tjRpknTeefa6Xz9p8+bYO7u9+64FWFOmhJ5PSbFh4N5StmDz50tjxkRfotajhy2v84KlJUssbGrRwvdHAgAAQC1EsAQAQC32P/8jbdwodegg/f73Now7ln37pA8+kEaODJzLyLDAaNOm6LVvvy21b28zkYKlpNhxy5bQ8zt2WCfT5ZdHv25Cgu3stmaNVFFhg8SHDYv9WQAAAFC7ESwBAFCL5eVZN9BvfyutXCllZ8euWbXKjgMHBs7162fHaHOWDh+2Ad+TJ9sytWBesFR1OVxWlh1jBUuSdSitWWPh1qFD0tChsWsAAABQuxEsAQBQS1VUSMXF1m10000W9ixcGLvOC5YyMwPneveWGjaMHiz9858W+Nx5Z/X3eve2Y9VgadEi63Dq2zf2fQ0YIH3+uc1/kqp3RQEAAODcQ7AEAEAt9cEH1kWUni41a2ZdR0VFsetWrrSZRm3aBM41bCj16RN5gPeJE7ar2+jR0vDh1d8/7zypc+fqwVJeni2583aQi8YLup54woZ9p6XFrgEAAEDtRrAEAEAttWGDHb1lbEOHWrAUa87SqlWhy+A8/fpF7lh6/XVp1y7p/vsjXzclJTRY+vBDafv26jvIRTJ4sC2Z271bGjKk+nI7AAAAnHsIlgAAOANOnpQ++SS+Gi8E8paZDR0q7d8vbd0auebQoQbavFkaNKj6exkZ1gV18GD19554QurZU7riisjXTkmRSkoCwVZenh2Dh4RHk5AgvfKKdURdf72/GgAAANRuBEsAAJwBv/mN1L27zUzya/166cILpVat7LU3kyjacrhly2z9W7hh2l7nk9cJ5dm0yWYl3XWXhT+RZGZKn30mbd5sr/PybElb8CynWFq1kgoKpHvv9V8DAACA2otgCQCAGlZRIT3zjHT0qHTLLTbPyI8NGwJhkGSzlpo0iR4sFRRcoPbtw++4lpFhx6pzll54QWrQQLr99uj3M2mSHWfPtmNhoYVdDRpErwMAAEDdRbAEAEANy82Vdu6UbrhBWr1amjUrds2ePdLatTaLyNOwoQ28LikJX3PypHUsTZ4cvvOoWzcbwl11ztKSJTaTqX376PfUs6cNAJ8zRyotldasCR9gAQAAoP4gWAIAoIb9+98W6DzxhNS4sS0F81NTXm4dTsGSkqQtW8LX5OVJhw831FVXhX/fcawDKrhjqbzcOqCGDfP3Wa68UsrJsW6lsjKCJQAAgPqOYAkAgBq2ZIk0bpzNFxo0yEKZWKZPt2VmaWmh55OTbSe28vLqNU89JTVvflITJ0a+bkaGdSx5A7g3bJCOHIkvWDpxQvrVr+w1wRIAAED9RrAEAEANOnFCeu89m48k2Y5oy5dHn7O0erUtg/va16q/l5xsnUI7d4ae37dPevVVacKEj9W8eeRr9+snffqpLbWTpKVLA/flx5gx1jWVkyO1bWvL6wAAAFB/ESwBAODTnj3SsmXx1WzZYrOP+va118OHS8ePW3AUyfTpUqNG0rRp1d9LSgpct2rNiRPS1Vd/FPV+qg7wLiyULrggcN1YEhOl737Xfh461JbXAQAAoP4iWAIAwKevfEUaPVr67DP/NcXFdgzuWJIiz1kqK7P5SldfLbVpU/395GQ7bt0aen72bCkzU+rZ82jU+/F2mfMGeC9dakvu4gmIbr9d6tBBGj/efw0AAADqJoIlAAB8WLRImj/fdkN78UX/dcXFFtqkptrrrl1t97WVK8P//pw5tqwt3DI4SerSxQaAB3csnThhnUejR8e+n3btLBRat046dMjuz+8yOM/550vvvy/dd198dQAAAKh7CJYAAPDhwQelTp2k/v2lZ57xX1dcLPXsKTVrZq8dRxo4UFq1KvzvT59u4c+kSeHfT0iQevUKDZZWrZKOHZNGjfJ3T/36WcdSUZEN8fY7uDtYkyYsgwMAAADBEgAAMe3cKS1YIN19t3TnnRbkeEvJYikuDsxX8mRm2vmqA7w//VT6z3+kW26RGjaMfM3k5NClcIsX23HkSH/31K+f7QbnLce76CJ/dQAAAEBVBEsAgHqlvNyWgMXj5ZftePPN0uTJ9nNubuy6zz+XSkqqB0sDB9ospQ0bQs/PmGHnIy2D8yQnW8eS69rrxYvtXMeOse9JsgHeR4/aLKeUFKl1a391AAAAQFUESwCAeqO8XLr8cusYqtotFM1LL0lDhlh40727LYlbsiR23ZNP2t+57rrQ85mZdly9OvT8nDk2i8l7P5KkJFv6tnu3vV62TLrkEn+fRZImTLCd4DZtin++EgAAABCMYAkAUG/84Q9Sdra0fbv/Adw7dtig7WnT7LXjSBdfHHlXN09pqfTII9Kll1afYZScLDVvXj1YKi6OHSp59ZIth/v4Y/tn4EB/n0eyAeILF0p9+kg33OC/DgAAAKiKYAkAUC+cPGnB0tSpNoD74YcDS8miycmx44QJgXOXXCJt22aBTrS6jz6SfvCD6u8lJto9BAdLx47ZTmt9+sS+Jy9Y2rJFWrPGfvYTSAXr39+CLG9pHwAAAHAqCJYAAPXCsmU2W+mWW6TvftfmG61bF7suJ8eWjaWnB855y86idS1lZUmNGknjx4d/PyUldAB3SYkFXX6CpW7dLJzasiUQTg0YELsOAAAAON0IlgAA9cL8+baMbfz4wNK0qsOzw8nOlsaOlRKC/hNz4EC7ltctFE5WljRihNSsWfj3u3e3jiZv1tPGjXb0Eyw1bCj16GHB1Jo1FjQxgBsAAABnA8ESAOCcU1HhbxlbsHnzbAB3mzZS797W8VNcHL1m+3absTR2bOj5Jk1sTlFwx1GwffuskyhSt5JkwZLrSrt22euNGy28Sknx93m8neFWr45/GRwAAABwuhAsAQDOOXffLfXrJ33wgb/fP3hQWro0MCepcWMLZmJ1LM2cacfg+UqepKTIwdKCBXa87LLI1+7e3Y47dthx40apVy+7Nz+SkmxXt5ISgiUAAACcPQRLAIBzyq5d0jPPWLfRmDE29DqWefOk8nJp4sTAufT02B1LL75oXU7huoh69bIB3uHMnCm1bSsNHhz52uGCJT/L4DzJydKRI9Y9de21/usAAACA04lgCQBwTvn7320p3EMP2S5q0eYced5+2wZwX3xx4FzfvraUrLQ0fE1JibRihXTzzeHfT0qS9uyRDh8OPX/kiDRrlvSlL0kNGkS+p65d7bhjh7R/vwVLgwbF/iyesWNtYHdWFh1LAAAAOHsIlgAA54zjx6Unn5SmTJGmTbNza9dGrzl5UnrnHWny5NCgp29f62J6773wda+8YgO6b7wx/Pu9etmxatfSrFnS0aOB+4ukcWOpUydbzpeTY2FZtJlMVQ0caPOVgsMyAAAA4EyrsWDJcZwmjuMscxxnjeM4GxzH+XWV93/kOI7rOE7boHM/cxxni+M4JY7jTKx+VQBAfTZjhvTJJ9K999pOaC1axO5YWrLEOoKmTAk9n55ux0hzlrxh3507h38/KcmOVYOl116zwGjkyOj3JdlyuB07bCZT8+aB3eoAAACAc0VNdiyVShrnuu4ASZmSJjmOM1ySHMfpKulySf8du+o4Tl9J0ySlS5ok6XHHcRJr8P4AAOcQ15UefdQ6jcaNs26i/v1jdyxlZ9vvVu0G6t3bzpeUVK/5/HOpsDD68G0vWAoe4O260qJFNuw70cd/gnXrZsFSVpY0erTUqFHsGgAAAKA2qbFgyTXe5ImGlf94m0P/SdL9Qa8laaqkGa7rlrquu13SFkkX1dT9AQDOLRs2SKtWSd/+tgVCUiBYct3Idbm5NouoVavQ802b2pyjzZvD15w8GT1Yat3arhkcLG3dKu3bJ11yib/P1L27dTyVlET/WwAAAEBtFWWs6BdX2XG0QlKypL+5rrvUcZwpkj50XXeN4/1fBqaLpMKg17sqz1W95p2S7pSkDh06KCcnR5J0+PDh//6M6HhW/vGs4sPz8o9n5Z/3rLKy2kvqq6ZNi5STc0SS1LhxJx06lKqXXy5Qx47Vp3CXlTnKzx+pyZN3KydnS7X327XrrxUrGignZ2XI+eeeS1KjRp118mS+cnIqIt5b+/aDVVRUppwca5uaO7eDpD5q2DBwj9E0btxeFRV9NWTIZ0pKKlZOzsmYNbHw3fKPZ+Ufzyo+PC//eFb+8aziw/Pyj2eFL8x13Rr/R1IrSdmS+ktaKqll5fn3JbWt/Plvkm4Nqnla0vXRrjt48GDXk52d7cIfnpV/PKv48Lz841m57muvue4//uG6J05E/z3vWT3wgOsmJrru8eOB95YscV3Jdd96K3yt9/5rr4V//557XLdlS9etqAg9n5HhupddFvsz3HKL63btGnh9112u26KF65aXx651Xfu7Bw/6+12/+G75x7Pyj2cVH56Xfzwr/3hW8eF5+cezQjiSlrs+M58zsiuc67oHJOXIlrv1lLTGcZz3JV0oaaXjOB1lHUpdg8oulPTRmbg/AMCZtXev9NWvSnffLY0ZYzuixVJcbHORGjcOnOvTx46bNoWvyc2146hR4d9PSZEOHrTla579+6X16+2+YklPl3bulA4dstdLltgubQk+/9PVcWwAOQAAAHCuqsld4do5jtOq8uemki6TtMp13fau6/ZwXbeHLEwa5Lrux5LeljTNcZzGjuP0lNRb0rKauj8AwNnz8MPS8ePSN78pFRRI27fHrikutsHdwVq1kjp0iBwsZWVZTfv24d9PSbFj8JylggKb2eRnVzfvfjZutIBq/Xr/85UAAACAuqAmO5Y6Scp2HGetpCJJ813XnRXpl13X3SDpFUnFkt6V9G3Xdctr8P4AAGfBkSPS449L06ZJd91l51avjl5TWipt2VI9WJKktLTwO7sdPSotXixNnBj5ul6w9N57gXN5eVKDBtJFPraPSE+3Y3GxtHSpBVIESwAAAKhPamx4t+u6ayUNjPE7Paq8/q2k39bUPQEAzr7Zsy1cuvNOC2YSEy1Yuv76yDWbN0vl5eGDpdRU6bXXqp9ftMgCqUmTIl+3e3epYcPqwdKgQVKzZrE/S8+etjSvuFjascOWwPkJpAAAAIC64ozMWAIAwPPqq7Z8beRIqUkT6zhasyZ6zYIFdvRmKgVLS5M++0z65JPQ8+++a9ePNF9Jss6kpKTAUroTJ6Rly6QRI/x9lsRE+/sbNkj5+VJGBjOTAAAAUL8QLAEATtmSJRbgnDzp7/ePHpXeeUe67joLZSQpMzP6UrhVq1rpxz+Wxo6V+vev/n5qqh2rzlmaO9cGcDdtGv2e0tMtGJKkdeusy+nii319nP/Wr1snFRayDA4AAAD1D8ESAOCUPPKIdfZccYUdXTd2zYIFFi4FL3sbMMB2Vvv00/A1L77YTZ06STNnht9tLS3NjsFzlt5/315HWwbnyciw+U1Hj0rLl9u5wYNj13lGj5Z27ZIOHyZYAgAAQP1DsAQAiNv27dIPfyhde630k5/Y8rEPPohdl59vM42CA5jMTDuGWw5XUSFt3NhCkybZDnDhdO9uc46CO5bmzrVjtMHdnn79LBQrLrZgqXVrm53k1ze/Kc2aZc9j6lT/dQAAAEBdQLAEAIjbvHl2/P3vpS9/2X5eujR2XX6+dQMFL08bMMCO4YKlkhLpyJEGGj488jUTE205nLecTbJgqWvXQDdTNBkZdly/XlqxQhoyRHKc2HWehARp8mTp4Yel88/3XwcAAADUBQRLAIC4zZsndesmpaTY3KMmTWzGUDQnTkhFRdWXi7VvL3XuHH7OkhdWDRsW/doZGTbnSJLKymzJ3aRJ/gKipCS7/6Iiu8aQIbFrAAAAABiCJQCo544e9T98W7LfXbBAmjDBgpuGDa0LKVbH0sqVNhg73I5rAwZEDpaaNz8Zs/MoI8PmHO3fbwHXoUP+lsFJ1vHUt6/tVnfyJMESAAAAEA+CJQCox06csF3NvvY1/zVFRdLBgxYseYYNs+CorCxy3Vtv2THcjmuZmTbjqLQ09HxhoZSWdijs0O5g3m5x69fbMrjERGn8+NifxZORIe3bZ8vnxo71XwcAAADUdwRLAFCPvfaa7aD24ovS7Nn+anJz7XjppYFzF10kHT8eOuco2I4d0p//LN18s9SpU/X3MzOtW2jjxsC5o0dtaVqfPp/HvCdvTtLatRYsDR8eedh3OPffb/dXXCy1aeO/DgAAAKjvCJYAoB579FEpOdmWgv3oR/5qCgutpm3bwLl+/exYXBy+5te/tmVzDz0U/n1vgHfwcrgVK6Tycqlv30Mx76lLFwuSsrOtzu8yOE/fvtL3viedd158dQAAAEB9R7AEAPVUSYnNMPrOd6Tbb7duoX37ote4rgVLVXdp693blp8FdxwF18yeLV13nS01Cyc52XaK8wZwS4Fh4H36xA6WHMe6lmbOtL8Xb7AEAAAA4NQQLAFAPbVkiR0nTgzsuhZrAPcHH0gff1w9WGrUyHZXCxcsbd0q7dkjjRoV+bqJiVa/ZUvg3NKlUs+eUqtWUQY3BbnqKql7d1vSNnSorxIAAAAAXxDBEgDUU0uXSi1bSikptqtbYmKgSygS7/2qwZIk9ekTPlhavNiO0YIlybqWqgZL4f5OJPffL23bZkvaHMd/HQAAAIBTR7AEAPVUYaF1KiUkSM2a2c5q0TqWTp60mUytWgV2YQvWp4+0ebP9XrDFi20gdlpa9PtJSrJgqKJC+vBDadeuQCcVAAAAgNqJYAkA6oCPP5bK/K0YkyQdPmzzjII7goYPl5Yts2AnnN/9zpbPPf641LBh9ff79LF72Lo19HxenjRypAVY0SQn285yH30UCLji6VgCAAAAcOYRLAHAOW7BAptFdPvt/muWL7cAKTi4GTpUOnSoejAk2e/+7W/S1VdLN90U/pp9+tgxeDnczp3WxTR6dOx7Skqy45YtFiw1aiRlZvr7PAAAAADODoIlADiHffihNGWKzRT697+loiJ/dV5H0EUXBc6lpNgxXLC0bp20d690/fWRr+ktdQsOlubMseOkSbHvKTk58PcLCy1Uatw4dh0AAACAs4dgCQDOYf/5j3T0qLRwodSunfSLX/irKyyUeveWLrggcC64Y6iqefPseNllka95/vnShReGBkvvvit17Sr17Rv7nrp2tSV2mzZZRxXL4AAAAIDaj2AJAGqJwkLp4B0gFKgAACAASURBVMH4aubOlbp1syHXX/ualJNjc4qicV37W1WDmw4dpObNwwdL8+dbONSlS/RrB+8Md+KElJUlXXGFv13aGjSQevSQ3nrLwjIGdwMAAAC1H8ESANQC69dLF18sTZwoHTvmr6aszOYrTZpkwc2IERbmrFgRve6DD2zYd9VgyXFsOVrVYOn4cdvZbcKE2PfkBUuua8vtPv/c3zI4T1qazWSSCJYAAACAcwHBEgDUAn/+sw2rXrpU+vGP/dUUFlpwM3Givb7kEjvm50ev8+YrhQtukpKqz1hau9bCpZEjY99Tnz7SkSM2tHvJEjs3alTsOs/jj0t/+Yv0yCNSr17+6wAAAACcHQ3O9g0AQH23d6/0r39Jd9xhnUTvvuuvbs4cKTFRGjfOXrdvb3OTvEAnktmzpaZNpf79q7+XnCzNmiWVl9u1JZt3JNmucbEE7wznzXFq29bf55FsRtN3v+v/9wEAAACcXXQsAcBpcvy4dN994WcURTNrllRaKt11l4U927b5Ww731lvSmDFSq1aBc5dcYsGS64avKSiQpk+X7r7bBmVXlZxsy+l27QqcW7HCBoN37Rr7noKDpYICBnADAAAAdR3BEgCcJv/v/0l/+pP0f/8XX11entSmjZSRIaWnWyi0aVP0mi1bpOJiaerU0PPDhkn79oUGQ8F++EPrCvr1r8O/H25nuOXLpSFD/A3gbtfOPsucOdKePTY3CgAAAEDdRbAEAFVUVMRfs2GD9L//a3OSXnnFOpD8WrzY5hclJFiw5F0vmrfesuOUKaHnU1Ls6A3ADnbokC1Pu+MO6fzzw1/Xqy8utuOxY3YvQ4bE/hyShU+DB0vz5tlrOpYAAACAuo1gCQCCvP++LS174YX46l55xTqNnn5aOnDA5hj58fHH1h3kDbju3duWqMUKll59VRowQOrRI/R87952DLccb+lSu0dvyHc4XbpI3btLOTn2evVqm7c0eLCfT2OeeUYaO9aWzmVk+K8DAAAAcO4hWAKAIG+8YTut3XWXtH69/7oFCyx8mTZN6tBBeuklf3V5eXb0gqWGDa1rKFqwVFJiIdFXvlL9vQsvlBo3Dt+xVFBgHUXhdoPzOI40fryUnW2BkrfDXLSacPeQnW27yzVgiwgAAACgTiNYAoAgs2bZnKGmTaXf/MZfzeHDFvSMH29BypVXSvPnWzATy7vvSs2aSQMHBs6lp0cPll54wZbN3Xxz9fcSEuz+wwVLS5bYtVu2jH5P48dL+/dbt9KiRRZ0dewY+7NUFW44OAAAAIC6hWAJACodOGDzjm64QZo0ScrNjby7WrDcXOnkSQtkJGnCBLvW8uXR6z79VPr3v6VbbrHZTJ6+faXt26WjR6vXuK70r39Jl18udeoU/rq9e1dfCldRYfOVoi2D81x6qR3nz7fnMWZM7BoAAAAA9RPBEgBUmjvXAqKrrpJGj5Z277blXLFkZdnysxEj7LUXMM2fH73un/+Ujh+Xvvvd0PPeznAbN1avWb1a2rFDuvHGyNdNTrb7Dh5CvnGjdPCgv13aOnWy+U0PP2w1o0fHrgEAAABQPxEsAUClBQtsmdiwYYEwJTc3ek1FhfTaaxYmNW1q59q1kwYNCuyMFsm//mV/p1+/0PPeznDezmzB3n7b5iBNnhz5ur17W2D14YeBcwUFdvTTsSRJf/qTdVRJBEsAAAAAIiNYAoBK2dkWoiQmSmlpFhDFCpby86WdO6vPOxo7Vlq2LPKcpQ8/bKING6Trrqv+XnJy5J3h3nrLwqH27SPfk7czXPCcpSVLpAsuCLwXy6WXSg88YMvgunXzVwMAAACg/iFYAgBJu3bZXKKxY+2149hObd6ubZG89JJ1Kk2dGno+I0MqLY28lK6goK0k6eqrq7/XsKGUmlo9WNq1S1q1SpoyJfo9pabaMbjjqaDAlsE5TvTaYL/5jZST4//3AQAAANQ/BEsAoECA4g2ulqQhQywYOnAgct2cOTbo+7zzQs97y9vWrw9ft2TJBUpPl3r1Cv9+uJ3hvHucMCHy/UhS587WnbRmjb3+9FNp0yb/y+AAAAAAwC+CJQCQtHCh1Lq1Da32DBpkx9Wrw9fs3i29/740cmT19/r0sWO45Wz79klr17aM2nnk7Qx35EjgXH6+1KKFdUNF4zj2ObxgqbDQjn4GdwMAAABAPAiWANQ569ZJl19uS9v8OH5ceuMN6corpYSg/604cKAdV64MXxdtIHbz5taNFK5jacYMqbw8odpcpmDeAO/gneHy86Xhw20GVCwDBtjfLi+3+0xMlIYOjV0HAAAAAPEgWAJQp+zdK111lZSVJT33nL+at96SDh6Ubrst9Hz79lKXLtGDpUaNAgFUVeGWs0nS889LycmfV9sNLpjXObVqlR0PHLCgaMSIqB8lpP7YMRvgvWSJvW7e3F8tAAAAAPhFsASgTnn6aemDD6SUFAuM/Jg+XeraNXS+kmfQoEC4U9WSJTaHqXHj8O/36yeVlEgnTgTObdokLV8uXX75nqj3lJQktWwprVhhrwsLJdf1HyxlZtpx5UrbnY75SgAAAABqAsESgDpl40bpwgulu++2Dp9t26L//qFD0vz50rRp4ZeYDRxoYVDwrCNJOnrUQp9oc4vS06WTJ61ryPPOO3YcO3Zf1PtyHAutli+317m5UoMG0rBh0T+Pp08f213u2Wft3pmvBAAAAKAmECwBqLXKy+Ov2bRJSkuTpk6117G6lubNs/Dn6qvDv5+ZKVVUVF/S9uKLUmmpog7g9gZ4b9oUODd/vt1f+/al0W9M0uDB0tq19neysixUqrr7XCSNGkkTJ1qdRMcSAAAAgJpBsASgVsrPt6Vg777rv8Z1belZaqoNzu7bV5ozJ3rNrFm2G1ykjh5viHZwsOS60l//KvXvL40aFfnaKSl29IKl48elRYukCRP8fZ4hQ6SyMmnxYuuOuuwyf3WeZ56Rune3OVHdu8dXCwAAAAB+ECwBqJXeesuWcN14Y2jHTzR79tjSttRUez1xoi0hO3o0/O+Xl0uzZ0tXXGHLzMJJSrIZSsHB0oIF1kl07722ZC2S886zZXklJfY6P9/Cpcsv9/d5hgyx4x/+YF1T48f7q/O0ayfl5Vk4F+0+AQAAAOBUESwBqJWys234dVmZ9Pe/+6vxAigvWJo0yZaRLVoU/veXL5f27ZMmT458zcREW9LmBUtlZdL3vmcdQLfcEvue0tIC9zVvngVYY8b4+zw9elh9Vpbt6OZ3vlKwCy9U1N3nAAAAAOCLIFgCUCOysqSvf136xz+s2yYeBw7YbmbXXWezgRYv9lfndQZ5wdKoUVKTJtLcueF//513pIQE62yKJj09ECw9/rhUXGxL4Zo2jX1PaWl2X65r85UuuUQ6/3x/n8dx7LPfcov0ne/Y3CQAAAAAqE0IlgDUiN/+Vpo+XfrWt2wpVzxycy2MuvRSafRoafVq6eDB2HUlJRb2dO1qr5s2tfrs7PC/P3u2NHy4dMEF0a/br5+0c6fdwwsvWOdQpGHfVaWm2vK8deukVav8L4PztG0r/etf0kMPxVcHAAAAAGcCwRKA0+74camgwJaM3Xij9Mtf2vBpv2bOtFBo+HDrOnJdm08UzRNPSM8/b8vWEoL+N9ugQdLGjbaELdjHH9s9RVsG5/EGeM+bZzXXXuv/s6Sl2fFvf7Oj38HdAAAAAHAuIFgCENXHH0vPPWfhjl+FhTbb6NJLLfBJSJBefdVf7dat1hX0jW/YMrZhw6SGDa2LKZI9e6R77pF695b++c/Q9zIyLFTylsl5vN3irrwy9j1lZNjx5z+349Sp/j6LFFiW98ILtvvc4MH+awEAAACgtiNYAhDVL38p3X67lJPjvyY728KkUaOkli2lgQOtg8mPBx+0IOmnP7XXzZpZ19HSpZFrXnnFls499ZT9bjBvcPW6daHnZ8+WOneWBgyIfU89etiSvi1bpJSUQBeSHxdeKH31q1KLFtKtt9owcAAAAACoKyJssA0ANlPoxRft5z/+0TqQ/MjOtjCpVSt7PXy4dRKdPGm7okWyerUtZ7vvPgt9PH36RB7ALdk99u8fWLIWLC3N/ua6ddJNN9m5sjJb1nbDDTYg2w9vWPfQof5+3+M4NmsKAAAAAOoiOpYARPSvf0lHj0rXXGM7qBUXx645cMC6ky67LHDu4oulY8ektWsj17mu9P3vS23aSL/4Reh7qanS7t02BLuqrVtt6d3NN4e/bqNGVh/csZSfb9fyswzOk5ho4dq0af5rAAAAAKCuI1gCENG//22dR08+aV0/zz0Xu2b2bOtMuuaawLnhw+1YWBi57s03pUWLbCmc1+nk8eYUvfde9bqnn7Zld7fcEvnaGRmhwdLs2bbcbvz46J8FAAAAABAdwRKAsPbtsyBo6lSpXTtp4kTppZdsllE0b74pdewoXXRR4Fz37lKHDpGDpdJS6Uc/sqVs3/xm9fdTUuxYNVgqK5OeeUa66iqbZRRJRoa0Y4ct7ZMswBo2zOYeAQAAAABOHcESgLDefdeWp111lb2+5RZp1y4pLy9yzYkTCZozR5oyxbqIPI5ju6GtXh2+7u23pW3bpP/93/AzmJKT7XpVd3abNct2hLvzzuifxRvovWqVLe1budIGiwMAAAAAvhiCJQBhvfOOdR4NHGivp0yx4dUzZ0auWbmylQ4fDl0G58nMlDZulI4fD/+32rSxrqhwGje2ndmqBkvvvCO1bi1NmhT9swwebMfly6Vly2yp3ogR0WsAAAAAALERLAH1wNtvS+PGWaeOHxUVtgvbFVcEOo+aN7cd1jZtilyXn99W551nf6uqzEwLdKoOAK+okObMsVApMTHytVNTqwdLixZZ51G0OsmW8nXvbsGS13F1ySXRawAAAAAAsREsAXXc8ePSd74jZWfbXKFIy9GCFRfb7m5jx4aeT0qyXdjCqaiwYOnKK63DqKrMTDtW/fvLl0t790qTJ0e/p9RUm7HkzXj66CNpyxZp9OiYH0eSNHSoVFRkO8L162edTgAAAACAL4ZgCThHbN8uZWXFX/f3v0s7d9oOb+Xl1r0Uy5Ildqza1ZOUJL3/vl2nqqVLpf37G2nq1PDXTEqyrqeqwdLs2TaDKdIyOE9Kis1H+ugje714sR3HjIle5xkyxOY4LVxYPTADAAAAAJwagiXgHOC60q23SldeKe3fH1/tM8/YPKGbb7bd0XJzY9cUFEht21oYFCwpyXZi27Wres2bb0qJiRW68srw10xIkPr3l9asCT2flWUzkNq2jX5Pqal29JbD5eZK550X6ISKZcgQO3buLP3P//irAQAAAABER7AEnAMWLLAuorIyfx1Hno8/ltavl66+2l6PHm2hUVlZ9LqCAutWcpzQ817QFG453JtvSgMHHlCrVpGvm5lpHUuua68PH7ZOp/HjY3+WqsHSokUWmIXbRS6cESOkO+6Q/vOf2CEWAAAAAMAfgiXgHPCHP0hdukhdu0qvvuq/zls6d9lldhw1ypaTrVoVuea99yy8ufji6u9FCpY2bbK6ESM+iXo/mZnSoUO2nE6yrqOTJwP3F03nzraUrqRE+uQTacMG/8vgJKlJE+mpp2y+EgAAAADg9CBYAs6g/HybdRSPEydsntCNN0pf/rI0b54N1vYjK0tq00YaONBejxplx0jL4UpLpZtuspqvfKX6+xdeKDVsWD1YevNNO44Y8WnU+6k6wHvBAhv0PWJE7M/iODZnqaQksLOb38HdAAAAAICaQbAEnCHvvSddcYXNSvrrX/3XrVljgc/FF9uStrKywHDtaFxXmj/flpklVP6b3qmTdf6sXx++5tlnpZUr7dilS/X3ExOlnj2rB0sLFtj8pHbtSqPeU79+di9esDRvni25a9o09ueRAjvD5eZaB5I3NwkAAAAAcHYQLAFnyG23SY0aSZMmSd/7nrRjh7+6ggI7Dh8e6PipOgA7nNxc20HNm6/kSUmxcCacOXOkXr2kKVMiXzcpSdqyJfD65Em7R68bKppmzSwcWr1a2rzZAq5Iu8iFk5pqy+jmzbOgrXFj/7UAAAAAgNOPYAk4Az791MKXH/xAeugh6ybKz/dXW1ho3UMXXii1aiX16BHo+InmmWek88+Xrr8+9HykYKmsTMrOli6/PPp1MzJsvtGxY/Z67VrpyBFp5EhfH+e/A7xnzrTX117rr06yYMl17e9fcYX/OgAAAABAzSBYAs4Ab+naqFFSerp17ixb5q+2sDB0kPaAAbE7lg4dkl57zeYlNWsW+l5KigVdn1YZh7R0qfT559KECdGvPXKkhVDe/XvzjvzMSZIsWPrgAwu+hgyRunXzV+f97ZQUG2Z+333+6wAAAAAANYNgCTgD8vNt6PXQoVKDBtLgwRbkxFJSIm3fbsvgPJmZ1nF05Ejkusces93f7ryz+nspKXbcvDn0/Lx5Nv9o3Ljo9+QFSF6glJdn4VDXrtHrPKNH298pKZFuuMFfjadrV6u7/36b9wQAAAAAOLsIloAzID9fGjQoMKR62DBp1Srb8S2aX//aOo5uvTVwLjPTloNFGsB98KD08MM2W2nw4Orvp6basepyuLw8u8dWraLfU5s21nW1eLFUUSEtWuR/GZxkIdnevTYk/Pvf918HAAAAAKh9CJZQL1VU2HKuM6G0VCoqCg1fLrrIzq9dG77mxAnpj3+UZsyQvvtdqUOHwHsDBtgx0pylv/xF2r/fQqlweva0bp/gYMl1bXndwIH+PtOoUba8b8UKC4kmTvRX57ngAvtbDRvGVwcAAAAAqF0IlnDOeuAB6emn469zXekrX5G+/nX7OR5FRdKf/yxlZfmvyc21EGn06MC5IUPsuGJF+JqHHpJ+9CPbQe6nPw19r0cPqUWL8HOW9u+XHnnEBmJHCokaNrSd34KDpV27pM8+C+w6F8u4cTaP6Uc/stfxBksAAAAAgLqhwdm+AeBU7Nlj4csFF1hI1KiR/1rHkfr0kX75SwtYInX2VFVaKo0da7OLJOkf/5Duuit23Usv2e5swbutde9uy+LC7c4mSXPn2nK52bPD3/+AAeE7lv70J1sK96tfRb+nlBRp06bAa+9afoOla66xgCs315bPBXdUAQAAAADqDzqWcE56/XVbzrZvX2Db+ng88IB0yy3Sgw9ap44fRUUWKj3/vHTlldK3vhUazoRTWiq98YZ1EHnzlSQbXt27tw2irur4cWn5cltuFklmpi2jq6gIPf/yy9Y91L9/9PtKT7e/ffKkvfa6nzIyotd5GjYMdFJdcYW/GgAAAABA3UOwhHPSjBnWddSzp3UOxctxpNtus6VwK1f6q1m0yI6TJ0vPPWddUo8+Gr1m3jzrIJo2rfp7qanhg6Xly23GUrSB2AMG2K5wW7cGzu3bZx1Ql14a86MoPd3+xpYt9nr1aik52Tqr/LrtNulnP/PXtQUAAAAAqJsIlnDO+eQT28Hsxhvtn8WLrTMoXoMG2THSnKOqcnOto6dNG6ldO9upbfr06B1PM2dKLVtK48dXfy8lRdq+vfrOcHl5drzkksjX9ZasBc9ZWrLEjn52aEtPt+OGDXZctSowFNyvxo2l3/1O6to1vjoAAAAAQN1BsISz6tFHA51Afi1fbp1GY8bYkq/y8vCdP7G0aWMdT36CpbIyKT/f/qbnzjttadz8+eFrysulWbNs2Vy4GVCpqfY727aFns/Lk9LSLLyKJD3ddnYLnrOUl2d/Z/Dg2J+nTx/r2lq/3sKtbdv8BVIAAAAAAAQjWMJZM3Om9L3vSVOmBJZk+eEFQQMHVu+8idfgwRZUxZKVZUvPgnd269vXjlWDIU9BgS1Pmzo1/PspKXYMHuBdUWEBVqyQp0kTC5+CO5by86WhQ+29WJo1s8HlGzbYoHCJWUkAAAAAgPjVWLDkOE4Tx3GWOY6zxnGcDY7j/Lry/P85jrPJcZy1juPMdBynVVDNzxzH2eI4TonjOGxgfg5wXZux44UTfn3+uXTPPYHOm9tu81+7YoUNvm7Z0rp+EhO/WLC0fXv05WylpdL3vy8lJUlXXx04f9551lW0fXv4uv/8x4ZcT5oU/n0vWArutioulg4c8Nc9lJkZ6Fg6dswCshEjYtd5+vWzjqU5c2yHN+9+AAAAAADwqyY7lkoljXNdd4CkTEmTHMcZLmm+pH6u6/aX9J6kn0mS4zh9JU2TlC5pkqTHHcdJrMH7w2mwebP05JPSr38dX92bb0offyz97W/ST35i3TY7d/qrXbEisNyrcWMbOv1FgiXJZgxF8vzz1lX0179W7wbq2TNysJSVZXOSWrYM/37r1hZMBQdL3nwlPwHRgAHSrl3Sp59aqFRWFl+wlJ5unysry7qVHMd/LQAAAAAAUg0GS645XPmyYeU/ruu681zXrdzkXIWSLqz8eaqkGa7rlrquu13SFkkX1dT9IdTMmdLu3fHXZWXZsaAgvjlHL78sdesmjRolXXWVnZs9O3bdJ59IH3wQOkcoPf3Ug6X+/e24fn3k33nzTVs2Fq7zKFKwdOCAhVVjx0b/+337ht57Xp7UoYN1R8USPMDbz8Dvqq6/3jq/jh6VvvQl/3UAAAAAAHga1OTFKzuOVkhKlvQ313WXVvmVr0t6ufLnLrKgybOr8lzVa94p6U5J6tChg3JyciRJhw8f/u/PiK7qs9qzp7GmTbtY6ekH9Ze/rFJiHH1iL72UrtatW+rgwYZ68MEP9I1vRGjfCfL55w00d+4luv76XcrN3SbXlTp2HKbnnz+i1NQoCY+kZcvaSOqvxMTVysk5IElq3ryHtm7trnnzFqtRowr/Ny9bytey5SWaN+9TDRhQPRn75JNjmj+/QlOmfKRFi6oPgkpM7KkdO7pqwYLckOeWn3+BXDdDrVqtUk7OwYh/v02bZL37bkctXJinhARpwYJhSk09rEWLYidlhw83lDRCr722RatWtVa3bk20fn2Rr8/t+fvfpePHE5SQUKHT8a8P/x76x7Pyj2cVH56Xfzwr/3hW8eF5+cez8o9nFR+el388K3xhruvW+D+SWknKli2B8849IGmmJKfy9d8k3Rr0/tOSro923cGDB7ue7OxsF/5UfVZ//7vrWsTiun/8o//rlJW5bsuWrvuNb7jupEmu27u3v7rnnrO/VVQUOPftb7tus2aue+xY9Np77nHdJk1c9/PPA+dmzLDrrV4dvuapp1z3yScjX/PSS1132LDw7z344DpXct0FC8K//+ST9rd37Ag9/4Mf2H3G+jxPPGH127a57scf288PPxy9JlinTq57662u27q1/c/hbOPfQ/94Vv7xrOLD8/KPZ+Ufzyo+PC//eFb+8aziw/Pyj2eFcCQtd31mPmdkVzjXdQ9IypHNTpLjOF+TdJWkWypvWLIOpa5BZRdK+uhM3F999847ttRr7Fjpn//0X7dsmXTwoHTZZfbP5s3+ltMtXGizhYKXs40aZUuygndIq+rkSenVV22A9nnnBc6nptox0lK8v/zF6iLp18+Wo1WEaXbKy2urli3t/sLp2dOOwcvhXFeaN0+6+OLYO7RlZNhx3Tpp7Vr7eeDA6DXBBgyQ3n5b2r8/vvlKAAAAAACcDjW5K1w7b8c3x3GaSrpM0ibHcSZJ+omkKa7rHg0qeVvSNMdxGjuO01NSb0nLaur+YI4dkxYskCZPlsaPt3DmYOSVWyHeeMN2PZs4URo92s4tXhy7LjfXfj94WLQ3U2jr1sh1CxZI+/ZJN90Uet7bzWzTpuo1+/fb/KRIwZBkwdLhwza7qWptTk473XCDfc5wwgVLb75pQdWtt0b+m8F/WwoNlrywyY+LLpIOHZIGDZKmTPFfBwAAAADA6VCTHUudJGU7jrNWUpGk+a7rzpL0mKTzJc13HGe14zj/kCTXdTdIekVSsaR3JX3bdd3yGrw/yHZjO3bMdgUbOtS6bVasiF3nutLrr1unUqtW1mXTvLmFRtF88IH0/vuBIMoTK1jau1e6916pbVu712DNmtkg8HAdS/n5dq+xgiWp+gDv556TSksTdc89kWu7dZMSEgLBUnm59MADUlqa9NWvRq7znH++hVNesNSpk3Vz+fXjH0tLl9qucG3a+K8DAAAAAOB0qLHh3a7rrpVUbVGP67rJUWp+K+m3NXVPqG5ZZU/YxRcHloIVFUnjxkWvW7XKAqJf/MJeN2hgS7FiBUteR1PVYKl1a/snUrD0ta9Ju3bZLnThlpelpYUPlhYvtm6jYcMi31N6uh3XrQvsUOe60hNPSOnpB5WZ2TJibcOGtrNaUVHgGhs3Ss8+a8/Ej4wMC5UaN7albfE47zzrWgIAAAAA4Gw4IzOWcGYcPWqBSDyWLbMZRa1aWcdLUlIgbIrm9delxERp6tTAuZEjLViJtpTurbfsb4Vb7pWUFD5Y2r/fZhbdd590ySXhr5uaasFS1c+/eLE0ZIjUtGnke2rZUurSJXQp3Xvv2fUuv3xP5MJKEydK2dnW+bVypZ2LZ97R6NEWRq1dK/Xv778OAAAAAICzjWCpjigpsWViQ4fasii/ioqsxjN0aOxgyVsGN2aM/U2P121TXBy+rrhYeu016VvfslCqqkjB0ty51k3ldROFk5pqc5I+Chr3fuyYPYtoy+CC64M7nubMseOwYZ/FrL3ySun4cSknxzq5zj8/sLTPj7vvtiVwFRUESwAAAACAcwvBUh3xq1/ZrJ8dO6Sf/9xfzYcfWhATHCxlZtqSs0OHItcVF1sIc/31oee9WUUbNoSv+81vbB7SffeFfz8pye6/rCz0/OzZgdAskrQ0OwZ3HS1datfyGyxt2hToeJozx67ZsePxmLVjxlhH1OzZ1rE0YID9z8Kv5s3t2SQksKwNAAAAAHBuIViqAzZskF5+Wfre96yrx9tdLBZvLlBwmOF12gTvclbV66/bjm7XXht6vkcPC46qDsGWbHnca69J3/hGaJdTsKQkG34dvDtbebmFPJMmhe9y8qSm2jE4WFq8ZKQMLgAAEv1JREFU2O7Tz7K01FS7x717bUnhokXVh4RH0qSJ7aj3xhvSmjW2Q1u8vv51C/l6946/FgAAAACAs4VgqZbYuVO64w6bPRRrAHZVM2ZYgPKDH1j9nj3Svn2x67KzbcB08MDoXr3suG1b+BrXlV580cKaTp1C30tIkPr2Dd+xNGuWdQ/deGPk+wm3M9zy5dInn9hys2i6dLHZTcGh2uLF1kXVunX0WinQ8VRSYvdaWipNnhy7zvPDH1owdOSI7ZB3Kjp0OLU6AAAAAADOFoKlWuK556RnnrHt66N15oQzZ47t6ta2bWBGz7p10Ws++0x6+mkLeoIHW/fsacdIwdLSpRa+3HZb+PfT08N3LL3+utS5c/Td2VJS7Bhc/847FlhNnBi5TrJgbdCgwPDskyelggJ/y+CkQMdTSYk0fbp04YXS2LH+aiX73WuusZ9PNVgCAAAAAOBcQ7BUS6xfb91C77wT345ie/dKK1YElm15u63FWg732GPWXfOTn4Seb93aOn8iBUvTp1sQ9eUvh3+/Xz/p448tuPIcOSK9+6503XXRZw916iQlJ0sLFwbOzZ5toVmbNtE/j2SBzrp11hm1apUN8/YbLHXrZkvaFi2ye/3qV+MP+B5/XHrkEQZwAwAAAADqD4KlWmLdusDw63jMnWvHSZPs2KGD1L599I6lgwcb6o9/lKZMCQRRwXr1Ch8sHT4svfSSDe1u0SL8tdPT7Ri8HG7OHNuhreqw73DGj7dwp6xM2r3bQrNYy+A8gwbZEraNG6X58+3cpZf6q01IsPlGL75ou7N99av+6oJ16mTLER0n/loAAAAAAM5FBEu1QGmp9N574UOeaGbPlu6/3wKN4OVXGRnRO5ZeeKG7Dh+Wfv/78O9HCpaef94GXN9zT+Rre8FS8HK211+X2rXz1z00frwFWMuXS1lZds7vEG1vaPbKldZ1NGhQfHOLxo2Tuna1cMlbGgcAAAAAACIjWKoFNm2y3c/iCZbKy20nsTZtbNh08BKz/v2tY6i8vHrdJ59Ib73VWXfcYYO2w+nVS3r//dD6igrp0UelIUOk4cMj31fXrtL55wc6lo4ft/u75hp/S8u8DqMFC2z4dqtWocPFo+ndW2reXMrJkZYsCXRx+fXnP0s7dkg33RRfHQAAAAAA9VWDs30DCCxbq7oU7uRJ27UtnMWLbfe3v/61+vb2GRm29Gzbturb18+YIZ08maB77418P716SSdO2C5nXbvauYKCwGDraEu9HCd0gPe8edaB5GcZnGQDyAcPlt5+Wzp0yOZNRZvLFCwxUbrkErtHKf5gCQAAAAAAxIeOpVpg3TqpYcPArmiSdNdd0mWXRa559VUboh1u/pA3PDrccrjnn5eSkz+P2h3Vq5cdt24NnFu40EKjq66KXOfp18+CJde1kKddO/+zjiTrGCoqsiDL7/Btz/PP23Pr3j16ZxUAAAAAAPjiCJZqgfXrpbQ0C5c8nTtLubm2w1pV5eU2t2jyZFv6VVXfvtblU3WA98aNFthMmLAn6v306WPH4AHcOTkWWPnZnS09Xfr0U6t/+20bhN2oUew6z7Rpga6oeIOljh1tcPeWLaHPEwAAAAAAnH4ES7XAH/4gPfZY6Lnrr7eOnzffrP77eXm2DO7LXw5/vaZNbQlc1Y6lF16w5WLjx0cPlrp0kVq2DCxnKy21mUV+u468JX0/+Ykt57v9dn91wX9/3DipSRNbFncqIi0hBAAAAAAApw//53ctUHW2kmRdPykp0htvSHffHfreK69YeDR5cuRrZmRIq1cHXldUWLA0aZLUpk1Z1PtxHKv3Op6WLrUh3GPH+vs83s5ws2dbGOW9jsdjj9mMqMaN468FAAAAAABnBh1LtZTjSNddZ7ONDhwInI+1DM7Tv7/NSDpyxF5nZ0u7dtmyND8yMgJzknJy7H5Gj/ZX27Gj1KGDBWMvv+yvpqq0tPDzowAAAAAAQO1BsFSLjR1rQdKaNYFz+fnRl8F5MjMtFFq2zF6//bbUrJl09dX+/nZGhnTwoIVR2dl2vdat/dU6jgVi+fk2uBsAAAAAANRNBEu1mLdzW/AQbq97aOLE6LWXXmozirwZTUVFNq+oadP4/nZRkVRQEN+ubpINEG/bNr4aAAAAAABwbiFYqsU6dbJd2IKDpcJCm1nUsmX02vPOkyZMkGbOlMrKpFWrpCFD/P9tby7S44/b8G6/85UAAAAAAED9QbBUi3lDtL3d3VzXgqXhw/3VX3edtHOn9PzzNnx76FD/f7t1a9uZbcECKSFBGjUq/vsHAAAAAAB1G8FSLecN0a6okDZvlvbv9x8sXX211KiR9POf2+t4OpYkacYMKSnJ/l6rVvHVAgAAAACAuo9gqZbLyJAOH5Z27LBuJcl/sNSmjfT970t799rSueTk+P52u3bSihXSf/4TXx0AAAAAAKgfCJZqueAB3oWFUosWUp8+/usfeEDq0MHCKMeJ/++3bGkBFQAAAAAAQFUNzvYNILp+/aTu3aWjR6Vvf1u6/HKbeeRXixbSkiVS48Y1d48AAAAAAKB+Iliq5c4/X3r//cBrb7e2ePTqddpuBwAAAAAA4L9YCgcAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU0KwBAAAAAAAgFNCsAQAAAAAAIBTQrAEAAAAAACAU+K4rnu27+GUOY6zT9KOypdtJX1yFm/nXMKz8o9nFR+el388K/94VvHhefnHs/KPZxUfnpd/PCv/eFbx4Xn5x7NCON1d123n5xfP6WApmOM4y13XHXK27+NcwLPyj2cVH56Xfzwr/3hW8eF5+cez8o9nFR+el388K/94VvHhefnHs8IXxVI4AAAAAAAAnBKCJQAAAAAAAJySuhQsPXm2b+AcwrPyj2cVH56Xfzwr/3hW8eF5+cez8o9nFR+el388K/94VvHhefnHs8IXUmdmLAEAAAAAAODMqksdSwAAAAAAADiDCJYAAAAAAABwSmptsOQ4zjOO4+x1HGd90LkBjuMUOI6zznGc/ziO06LyfA/HcY45jrO68p9/BNXkOI5TEvRe+7PxeWpaPM+r8r3+le9tqHy/SeX5wZWvtziO86jjOM7Z+Dw16TQ+qzr/3Yrz38Nbgp7FasdxKhzHyax8r85/r6TT+rz4boU+q4aO40yvPL/RcZyfBdXU+e/WaXxWdf57JcX9vBo5jvNs5fk1juOMDarhu+X/WdX575bjOF0dx8mu/Pdqg+M436s838ZxnPmO42yuPLYOqvlZ5fenxHGciUHn6/R36zQ/qzr93Yr3WTmOc0Hl7x92HOexKteq098r6bQ/L75boc/qcsdxVlR+h1Y4jjMu6Fp1/ruF08B13Vr5j6TRkgZJWh90rkjSmMqfvy7pwcqfewT/XpXr5EgacrY/Ty17Xg0krZU0oPL1BZISK39eJuliSY6kOZKuONufrRY/qzr/3YrnWVWpy5C0Leh1nf9enebnxXcr9N/DmyXNqPy5maT3JfWoL9+t0/is6vz36hSe17clPVv5c3tJKyQl8N2K+1nV+e+WpE6SBlX+fL6k9yT1lfS/kn5aef6nkv5Q+XNfSWskNZbUU9JW1ZP/rnWan1Wd/m6dwrNqLmmkpLslPVblWnX6e1UDz4vvVuizGiipc+XP/SR9WJ++W/zzxf+ptR1LruvmSvqsyulUSbmVP8+XdP0ZvalaLM7nNUHSWtd111TWfuq6brnjOJ0ktXBdt8B1XVfS85Kuqfm7P7NOx7M6IzdaC3yBfw9vkvSSJNWX75V0ep5XfRHns3IlNXccp4GkppJOSDpUX75bp+NZnYn7rC3ifF59JS2orNsr6YCkIXy3/D+rM3CbtYLrurtd111Z+fPnkjZK6iJpqqTplb82XYHvyVRZyFvquu52SVskXVQfvlun61md2bs+O+J9Vq7rHnFdN0/S8eDr1IfvlXT6nld9cArPapXruh9Vnt8gqYnjOI3ry3cLX1ytDZYiWC9pSuXPX5bUNei9no7jrHIcZ5HjOKOq1D1b2eL4y3rWuhfpeaVIch3Hmes4zkrHce6vPN9F0q6g+l2V5+qDeJ+Vpz5+t6L9e+i5UYGgpD5/r6T4n5eH71bgWb0m6Yik3ZI+kPSw67qfqX5/t+J9Vp76+L2SIj+vNZKmOo7TwHGcnpIGV77Hd8v4eVaeevPdchynh+z/u79UUgfXdXdL9n/Iybq5JPu+7Awq875D9eq79QWfladefLf+//buN+TOuo7j+PvTHITbA8sKiqVzoIj9oVmWUJEZ+SAKlRVMrQlJjAjJ/kFhRNGTSoiCoILyQaCMSiVBceDCHihlba4lazMsiZUUZoQlLGffHly/g2fbOTf3uXbcue/7er/g4j7ne65zdp0vn23X/Tu/63eW2atpBpUrOOV+jZityb3aBjxSVUcZYLbUz2obWPoo8Ikke+mm9P231Z8EzqmqrcCngdvzwho511XVG4B3tu0jp/mYF2lav86gmxZ6Xft5dZL30E1vPFGdjgNdAWbtFQw3W9N6BUCStwHPVtVozY4h5wpm7xeYrRN79VbgeeA1dJdJfCbJFoadrVl7BcPNFUzv1610J8m/Ab4FPAQcw2zN0isYULaSbATuAG6qqqVmA07L0GCyNYdewUCyNUOvpr7EhNqazBXMpV9gtqbt/zrg68DOUWnCbms2W+pvVQ0sVdWhqrqiqt5M9+n+461+tKr+0W7vbfUL2v2/tJ/PALczkKm1ML1fdCeGv6iqp6rqWeBeujUWjgCbxl5iE/BXBqBHrwabrSV6NbKd42ffDDZX0KtfZuvkXl0L3FdVz7VLcB6kuwRnsNnq0avB5gqWPH84VlWfqqo3VdWVwFnAHzBbs/RqMNlKsp7uF7TbqurOVv5bu1RkdDnS31v9CMfP6BplaBDZmlOvBpGtGXs1zSByBXPrl9ni5F4l2QTcBeyoqvHfhQaRLZ2aVTWwNFqtP8lLgC8C32v3X5lkXbu9BTgf+GObrv2KVl8PvJ9uivcgTOsXsBt4Y5Iz2zoc7wIOtumQzyS5tE0H3QH8bAGHftrN2qshZ2uJXo1qHwJ2jWpDzhXM3i+zNbFXfwYuT2cDcClwaMjZmrVXQ84VLHn+cGbrE0neCxyrKv8/ZPm9Gkq2Wg5+CPy+qr459tDdwPXt9vW8kJO7ge3p1ig5j+7c9OEhZGtevRpCtnr0aqIh5Arm1y+zdXKvkpwF3AN8oaoeHO08lGxpDmoFrCA+aaP7lOxJ4Dm6kdIbgE/SrWj/GPA1IG3fbXSLjP0W2Ad8oNU30H1ryYH2+Ldp3zKx1rZZ+tX2/3DryaPAN8bqb2m1x4HvjD9nrWzz6NVQstWjV5cBv5zwOms+V/Pql9ma+G/8RuAnrR8Hgc8NKVvz6NVQctWjX5uBw3SLmt4PnGu2ZuvVULJFdzl8tfe5v23vo/u22D10s7f2AC8fe87NLT+HGfsWpbWerXn1agjZ6tmrJ+gW3f93+3t70RByNc9+ma2Te0X3QcJ/xvbdD7xqKNlyO/VtdLIgSZIkSZIkzWRVXQonSZIkSZKklcOBJUmSJEmSJPXiwJIkSZIkSZJ6cWBJkiRJkiRJvTiwJEmStEBJdiZ52aKPQ5IkqQ8HliRJkmaQ5OokleTCObzWl4Cnq+qfczg0SZKk0y5VtehjkCRJWjWS/Bh4NbCnqr684MORJElaKGcsSZIkLVOSjcDbgRuA7a12WZIHkvw0yaEktyVJe+yJJF9Jsi/J70aznJJsSHJrkl8neSTJla2+LsktrX4gyc4FvVVJkqRlcWBJkiRp+a4C7quqx4Cnk1zc6luBm4CLgC10g08jT1XVxcB3gc+22s3Az6vqEuDdwC1JNtANWP2r1S8BPpbkvBf7TUmSJPXlwJIkSdLyXQPsard3tfsAD1fVkar6H7Af2Dz2nDvbz71j9SuAzyfZDzwAvBQ4p9V3tPqvgLOB81+MNyJJkjQPZyz6ACRJklaDJGcDlwOvT1LAOqCAe4GjY7s+z/HnWEcn1ANsq6rDJ/wZAW6sqt3zfweSJEnz54wlSZKk5fkg8KOqOreqNlfVa4E/Ae/o8Vq7gRvH1mLaOlb/eJL1rX5Bu0ROkiRpRXJgSZIkaXmuAe46oXYHcG2P1/oqsB44kOTRdh/gB8BBYF+rfx9nmEuSpBUsVbXoY5AkSZIkSdIq5IwlSZIkSZIk9eLAkiRJkiRJknpxYEmSJEmSJEm9OLAkSZIkSZKkXhxYkiRJkiRJUi8OLEmSJEmSJKkXB5YkSZIkSZLUy/8Bo2OmHSE9YTcAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Créer la figure\n", "plt.figure(figsize=(20, 10))\n", "\n", "# Courbe brute : oscillations saisonnières\n", "plt.plot(data[\"date?\"], data[\"CO2(ppm)\"], label=\"CO₂ oscillation périodique + oscillation lente\", color=\"blue\")\n", "\n", "\n", "# Mise en forme\n", "plt.xlabel(\"Année\")\n", "plt.xticks(np.arange(1955, 2025, 5))\n", "plt.ylabel(\"CO₂ (ppm)\")\n", "plt.title(\"Évolution du CO₂ atmosphérique à Mauna Loa\\nOscillation saisonnière et oscillation lente\")\n", "plt.legend()\n", "plt.grid(True)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "# Créer la figure\n", "plt.figure(figsize=(20,10))\n", "\n", "# Courbe lissée : tendance à long terme\n", "plt.plot(data[\"date?\"], data[\"seasonally adjusted(ppm)\"], label=\"CO₂ (évolution systématique plus lente)\", color=\"red\", linewidth=2)\n", "\n", "# Mise en forme\n", "plt.xlabel(\"Année\")\n", "plt.xticks(np.arange(1955, 2026, 5))\n", "plt.ylabel(\"CO₂ (ppm)\")\n", "plt.title(\"Évolution du CO₂ atmosphérique à Mauna Loa\\ntendance à long terme\")\n", "plt.legend()\n", "plt.grid(True)\n", "\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "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": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }