From 4960643e7c6527c56ab330330af01d4b076bb699 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=92=D1=8F=D1=87=D0=B5=D1=81=D0=BB=D0=B0=D0=B2=20=D0=98?= =?UTF-8?q?=D0=B2=D0=B0=D0=BD=D0=BE=D0=B2?= Date: Fri, 25 Oct 2024 22:20:23 +0400 Subject: [PATCH] done --- lab1.ipynb | 198 --- mai/.flake8 | 2 - mai/.vscode/extensions.json | 13 - mai/.vscode/launch.json | 16 - mai/.vscode/settings.json | 38 - mai/assets/quantile.png | Bin 113581 -> 0 bytes mai/backend/__init__.py | 52 - mai/backend/api.py | 57 - mai/backend/service.py | 59 - mai/docs/path1.png | Bin 22640 -> 0 bytes mai/docs/path2.png | Bin 76078 -> 0 bytes mai/docs/path3.png | Bin 132359 -> 0 bytes mai/docs/path4.png | Bin 39117 -> 0 bytes mai/lab.ipynb | 0 mai/lab4.ipynb | 2936 +++++++++++++++++++++++++++++++++++ mai/readme.md | 55 - mai/run.py | 16 - mai/utils.py | 79 + 18 files changed, 3015 insertions(+), 506 deletions(-) delete mode 100644 lab1.ipynb delete mode 100644 mai/.flake8 delete mode 100644 mai/.vscode/extensions.json delete mode 100644 mai/.vscode/launch.json delete mode 100644 mai/.vscode/settings.json delete mode 100644 mai/assets/quantile.png delete mode 100644 mai/backend/__init__.py delete mode 100644 mai/backend/api.py delete mode 100644 mai/backend/service.py delete mode 100644 mai/docs/path1.png delete mode 100644 mai/docs/path2.png delete mode 100644 mai/docs/path3.png delete mode 100644 mai/docs/path4.png delete mode 100644 mai/lab.ipynb create mode 100644 mai/lab4.ipynb delete mode 100644 mai/readme.md delete mode 100644 mai/run.py create mode 100644 mai/utils.py diff --git a/lab1.ipynb b/lab1.ipynb deleted file mode 100644 index ae6c6d7..0000000 --- a/lab1.ipynb +++ /dev/null @@ -1,198 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Начинаем работу...\n", - "\n", - "Выгрузка данных будет проводиться с помощью Pandas из cvs файла (Данные по продажам домов). Выгрузим-ка данные из cvs файла в датафрейм:" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Index(['id', 'date', 'price', 'bedrooms', 'bathrooms', 'sqft_living',\n", - " 'sqft_lot', 'floors', 'waterfront', 'view', 'condition', 'grade',\n", - " 'sqft_above', 'sqft_basement', 'yr_built', 'yr_renovated', 'zipcode',\n", - " 'lat', 'long', 'sqft_living15', 'sqft_lot15'],\n", - " dtype='object')\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "# Загрузка данных\n", - "df = pd.read_csv(\".//static//csv//kc_house_data.csv\")\n", - "\n", - "# Вывод столбцов\n", - "print(df.columns)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Ураа мы справились с выводом данных**\n", - "\n", - "Помимо вывода, подсоединили дополнительные библиотеки, которые помогут построить графики :)\n", - "\n", - "Приступим к построению диаграмм..." - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# 1. Диаграмма распределения цен (гистограмма)\n", - "plt.figure(figsize=(10,6))\n", - "sns.histplot(df['price'], bins=50, kde=True)\n", - "plt.title('Распределение цен на недвижимость')\n", - "plt.xlabel('Цена')\n", - "plt.ylabel('Частота')\n", - "plt.show" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Диаграмма №1 (Гистограмма)\n", - "\n", - "Данная круговая диаграмма отображает распределение цен на недвижимость. Bins позволяет установить интервальность исследования, так на графике заданы 50 интервалов, для более детального отображения распределения цен. Это позволяет сделать вывод о том, что большинство объектов недвижимости находится в более низком ценовом сегменте и дорогая недвижимость встречается реже." - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# 2. Связь между площадью жилья и ценой\n", - "plt.figure(figsize=(10, 6))\n", - "plt.scatter(x='sqft_living', y='price', data=df)\n", - "plt.title('Связь между площадью жилья и ценой')\n", - "plt.xlabel('Площадь жилья (кв. футы)')\n", - "plt.ylabel('Цена')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Диаграмма №2 (Точечная диаграмма)\n", - "\n", - "Данная точечная диаграмма отображает связь между площадью жилья и ценой. Массовое скопление точек в нижней части графика сообщает о том, что большинство объектов недвижимости находятся в доступном ценовом сегменте с умеренной жилой площадью. Площадь влияет на цену недвижимости (с увеличением жилой площади возрастает и цена). Таким образом, наблюдается прямолинейная, положительная корреляция между ценой и площадью жилья." - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# 3. Круговая диаграмма, показыващая состояние домов\n", - "plt.figure(figsize=(8, 8))\n", - "df['condition'].value_counts().plot.pie(autopct='%1.1f%%', startangle=90, cmap='Accent', wedgeprops={'edgecolor' : 'black'})\n", - "plt.title('Доля домов по их техническому состоянию')\n", - "plt.ylabel('')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Диаграмма №3 (Круговая диаграмма)\n", - "\n", - "Данная круговая диаграмма позволяет отслеживать в каких состояниях объекты недвижимости находятся. Значения варьируются от 1 до 5, где 1-2 - это плохое и ужасное состояния, 3 - среднее, а 4-5 хорошее и отличное. Преобладающее большинство недвижимости находится в удовлетворительном состоянии (где потребовался бы небольшой ремонт). В плохом и ужасном состоянии доля недвижимости состовляет < 1%, что является очень хорошим показателем. \n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "\n", - "# Урааа, всё вроде получилось, теперь будем пушиться :)\n", - "P.S. Markdown и правда прикольная и нужная вещь. Однако, почему по началу работы проект не видел, две установленные библиотечки, а после того как пересоздали полностью весь проект, всё прошло без особых проблем..." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mai", - "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": "3.12.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/mai/.flake8 b/mai/.flake8 deleted file mode 100644 index 79a16af..0000000 --- a/mai/.flake8 +++ /dev/null @@ -1,2 +0,0 @@ -[flake8] -max-line-length = 120 \ No newline at end of file diff --git a/mai/.vscode/extensions.json b/mai/.vscode/extensions.json deleted file mode 100644 index 37c2cc0..0000000 --- a/mai/.vscode/extensions.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "recommendations": [ - "ms-python.black-formatter", - "ms-python.flake8", - "ms-python.isort", - "ms-toolsai.jupyter", - "ms-toolsai.datawrangler", - "ms-python.python", - "donjayamanne.python-environment-manager", - // optional - "usernamehw.errorlens" - ] -} \ No newline at end of file diff --git a/mai/.vscode/launch.json b/mai/.vscode/launch.json deleted file mode 100644 index a43b215..0000000 --- a/mai/.vscode/launch.json +++ /dev/null @@ -1,16 +0,0 @@ -{ - // Use IntelliSense to learn about possible attributes. - // Hover to view descriptions of existing attributes. - // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387 - "version": "0.2.0", - "configurations": [ - { - "name": "mai-service", - "type": "debugpy", - "request": "launch", - "program": "run.py", - "console": "integratedTerminal", - "justMyCode": true - } - ] -} \ No newline at end of file diff --git a/mai/.vscode/settings.json b/mai/.vscode/settings.json deleted file mode 100644 index 06082f2..0000000 --- a/mai/.vscode/settings.json +++ /dev/null @@ -1,38 +0,0 @@ -{ - "files.autoSave": "onFocusChange", - "files.exclude": { - "**/__pycache__": true - }, - "editor.detectIndentation": false, - "editor.formatOnType": false, - "editor.formatOnPaste": true, - "editor.formatOnSave": true, - "editor.tabSize": 4, - "editor.insertSpaces": true, - "editor.codeActionsOnSave": { - "source.organizeImports": "explicit", - "source.sortImports": "explicit" - }, - "editor.stickyScroll.enabled": false, - "diffEditor.ignoreTrimWhitespace": false, - "debug.showVariableTypes": true, - "workbench.editor.highlightModifiedTabs": true, - "git.suggestSmartCommit": false, - "git.autofetch": true, - "git.openRepositoryInParentFolders": "always", - "git.confirmSync": false, - "errorLens.gutterIconsEnabled": true, - "errorLens.messageEnabled": false, - "[python]": { - "editor.defaultFormatter": "ms-python.black-formatter", - }, - "python.languageServer": "Pylance", - "python.analysis.typeCheckingMode": "basic", - "python.analysis.autoImportCompletions": true, - "isort.args": [ - "--profile", - "black" - ], - "notebook.lineNumbers": "on", - "notebook.output.minimalErrorRendering": true, -} \ No newline at end of file diff --git a/mai/assets/quantile.png b/mai/assets/quantile.png deleted file mode 100644 index d44e6ff80502a6b1aef1dcef58380fcd0402ebca..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 113581 zcmd?RXH-*P*Dsnv2@skfM5=U9s?ww?NC`y*lwN{}AT@N97P?9`^dg9Wh*arP0}&Ar z6sb~!2q-mxNQbk-|9zhKIrqysFrxuwA5_WAP|Ta zseRK31R@76$-Q9|z^_yzOa}0a%<+c)4G`#EBF&K<>8}^=B+1N2D~>B4+1>^L!q#k!8QkHhdMME->u_fSq%bZCHKhjw*0v^VX{DzAq{6Yu{a2G>e9%NR6 z`nrhauv;L_k3GAdzpEe84$Uxj$O+=xuT%{2NFB9gx1VlASA!})p!MO7w&29~8Ujcx zn^r7O5C z(u@hu<_vIz;jz#}!WXHj8kkKYDuAYpwF8V3!VLEKbVEuxX(_GAHXM(79!cfgJ#nCk zi?@?Qt^F+RU_1(dv|J?**+>JXVha!i0d#o11}UZpoIdD6uQKoHM)lZ2Ub7I2aokjO z6yU$Pl#Wd2BFsO(fY_G)i9vqdlILK>dpz4sXUws|^i2>r8!|}TsHUpoM;aw?(DGq) zf9svJj)A#<^X~7ex)IsXl4$GY6?>uU`3)=5R0@Ll_qbhS+r$Jr+kd`#6)cRzrtod6 z#kcwz*#;j|H!AkExK*JTf;a+d_N>Wf3%r#QXB1+-ZEE?UV*wSTRbo10gp|lsb1=`& z2vc_SgN96NYLAaZ{IDted4+89T^*x7$?2c|ahCd6{)dE25FokUr`;$T)bWoc#ECqW z!dvTGidJNw4a6LSI8AFt!~i}Fo9Tgcu>1?%6~E~jkLuE*tjImU{;$(&ER{{xCCz9M zsTS)r?pKi5!Z1h3Z7jct5bwCk&gKi*fTmH0F0}3P{DBtk*Gz>iWzL*x; z7_@;o)vYFqXQXu~r{3t0eJN6Hh;eAQ?yF9SX560B^?V2+R>(AM zYI>_<`gSDyjL7$b4`LCT8dX19BquiB4Cm###NdBxgc|{Z+_68SM>V==M&eh0xB@C9 z<$wcE3)ectsU)kfQ#HJ6hX|5H1f0PVZrFr*ICmQ#u$eQ!V8PE^Brj=i5qTYLxCAZ^Utco z)L{h-vrQ65A^b<=dy)(qXg~0}TLk5_bLNX1zvegf9!oXV09qw5N)q3(oub;QC$}_n zYm;X)-;NYS<@Wq5Uewa?(xKoDt@0IL<@yUOSX9n}f;)%O@%v&eu3iR_H{F%e)5StMotMC6VR8 z0=tVMs#;n=ZRTHgTp}jJ+Kbx`M&(_=fLhWD|MQru>}?cN*$2yCrO;o<5L!`Ta@3L! zAV<>CD`9gzV;kL)o6Z>{l%;#q!-4;NPcrW#Nvl8aNSi}?$QMYN(8$U}u;v-ZIqBPu<0r8$VlEhoc(Zu#3 z9+P;J25KXT;HQE9I{$ z;2a81n#Tb7Eql*WwrOaCf;-WFUO?dBk05)6mjwdDEr(v48&XH^I&V1NeB9#A|GUVA zyMyOJVwZc)Jf?mjEel9ONCH!N3**2i555>~z)Fah-Afn*WMOe-oRTCA?^wP)J$SP5 zY;ZG3=mHz?P=N?4(jo-MDAo)S3_m{(kE!OtnBo(F!P_+?clYhwOIj8V8p{6YyU%86 zqoXu6vHT_bXTHWlEr(l^He^5>&<`tgvmq)8MjTzrJQB-0J}m%_GtB#YiDCdVB{->~@1K#Fz;&q(wS=ZS+= z>=1=rEwDIAI6$C;JnYFofqMAEnZF~ErvI6wk-!D^|DKy?A^o7^63&buhRT{tVyU?% zNfyAC;U@pjO8)=zvoMVD0tAV@6OXqm@*9_leuv9IEP^XFh*R)J`%9v4yEm9opHK+H zqZWo4j|g&iuuL_iR*j zO!{3bXw5V=pgB1teMi)B*>U34duEsSbDVvmztEe{ zDR!<_He=o7IY08WIa7`dc%))XXA>v-0*^@g2!s$Pn{iY7u}>+3vsnD9-4!N`vo;f9 zg)xT$UU{!R#)3fXn|liH?vBMd-xWPS;OM0E$VPSa4_VOH*{4SE8_Z0Y%8!zDYqc?^&EA(8anyJ!g>^3YXFW+ zNWOCPGZq&tHO1P|iVMcM_)JfkvE4Rw%F4cVqWle<*TTEnzEC00*e1htE1nS86TG*D z^PRUVy*w9H5h4`r(a@=!jxU%l8yFMnEWRht?nEA4kNb@aa~DBk?~}avolUNM25cy| zj!HLUkn@$C$)PyP&NumJK4KW)P7R`0nzD*P_7k1gsTO7%hB8656ffC6k|9_-#7d60 zJ36YC1c-jokLY6wUm|aE;?{7D^;PY=eysxu1n-`1@@>?gI>~M^LF6}VztA!Oz@(Ve zjA!m`CBg=Jut!jBO&(7A&zAmKo@&O$X0`z-He#%0RS@Tfrv0`+k$<h}-itc#+-IDAF7Kc64 zt8?Y~e#T9C1d%$?rMHrM-NV4MMNNBKVSc*7EyqRytsmJpFZZTRmfHWkjvxm~1v1xD;_%?b9^V11lHDl16FZVUyEmWy^gebcgnd(SxMloI(8{Bfqdk$;_4Nc(; z%;Y5NyM@_QpSz{t0#cz1>Lbwrq99p*3JZSx&Q7~2_J*?a&Yc5w#W->ssovgqsmPI} zHH?sp_18MdV$e`nU2^4Py(EK3=)FCM<!2Np2nPSHic-$JzI@?=EagVJi-)bJ#ol!)&d{X{IayEbL3q z2dEXVb+(hc2McpY&YvauKZb$}CV{^<-;Jx-MEp78yQBFNL-jKNZ5CcdN2mu4Arx0MCQk zXbW1>?ycOE|3Kma?(F+a>9U8M)7cKbDgCn(eS%#^(2UFzhMg@$KAryhB_+N z$FYrw7eiI@+Qyt>V&f~aZjdd3JvZ&igzh%S;ZdnD>XOQe=E9KR`>ziLau!(ri}-K% zEaq5C67iVX=gx1(lOe8Lcvd6ZX)p3Am-{2|34$l#BQU#4uy(5cf+8V3k}(MUWUhP1 ztRdJ=xGKysvZ!pM|COiYo2(r+s$}i>qe;7=KqNNu48BC!<(to+ zY6`>?XviD=l*+z$i5i0G$k!=GZv~%5_01Xby?x+yO$i(%wKLL-<76T*B{wy8bJ5!i z;T9Nk(hd#=*RvQB!@Pw$PdOo${tYVRW{)5_&>*p$op!m1_U1YONuA*Ne9iP0MK|7ZEnv2 zdv=Ej?jX|ecIl(mKk_*nCf}|eHJ^4Mh>hiM?P~m7e%kFJ zKUfuSkqm5z1=65NT)TkY@+CG|0b01?QH-MW4*sN3w-$%(_Hu zAjHJ-yFX>f^VfFYtdgF~Ka`;Axq(h_){%}onS^Mn+- zZ3=Dya1}$+kvo)8NrXmtM$*B-Pg(iCU)r}Z^dPyR?{UYTs0P`LhdzLaZO`EL@+*cc zVH=tt;r+LK;dmkZ{Q|y@oAMWT?Kgr-T6;M&Ytd^+)=BvRrfQ7Tlcqy4i>kUSYZ=#M3w6aFHQA%y>vA>?L~EwM+3 zNr~{EHtB-IeGcK{_50v6&&K^w3cz6`(v7yyyd~-Sf0?oT@8>rEpN)KXBl_h&2fU9y z+!~W=ZzdIf4HpN?jh&ly`)ZRodx0{-B+Rhu3(efItQmpjmk(K-cv~Lrb|vlPt98K} zeM41xb=z*B4ZZM$2eWkKPMmPv;=d#QrOI^Fk{sjb&1Aw;6*{3QV-|$e_h`$y$@-ud zmmZNn08(QvfFB|f36VvtICorckIM}*573Z(V}aa46d&pjWW1XEqaTi1tV&d}0csOZ z2$KzfJej6GZJxDyfHwN=$Rp|+v3pQ3l{|v=sjf#{+@i4?4u8^ z3T8uY!wzY%hHsd>w-{uc+xu-Kwo>x(0i^2DO>%iM`3vJzPUKIFnD|XQ8w7E-6dk(~ z5f4ZBFDsx5VD)ZcYxl-k#+`XYQ?phPgjWK4kY-KzBzRJ@=ajW`tE-(pMinIVr^`c? zq7*D~M{zc}O7`w5<)aa>r9@=lvph?bH(^k8n+u{?kCVd$cRql38>J{zM0ZRPDW@Rpc-9*C@M*FS_v_FP2HW$&Q1^^8c~r* zC_=DkR-GeupoLE=ss3tFcC5|M@tK;8sjXJPY;;mJqR(Z)JZ?A|&#@4;J)IW(A}ue4 z>VX!`cxsQ^8O@3Uaz3IL(HX;C8h^&f$Eo-Ds`R~3+}nNuSNy!9^MYs_EBBnE0w?jv zu4Ca0S|tXd&8GyLPA07K;Une6hN#82Z`T@~1%`j=37uAeRVLHkHsyKE1Ry4<+bQU7 zwM}|5THVEX-j!C}AN`qBEAb9EWdL_;q6H;+uerAe2wQnwo7y0uFKB9^Q`8Dl;Pl?! z5QBVOY?l8LGfJ6Yg|d<|mtsA+`R2TtA*G%Rl{M}36iY9kby_?|70RvCHet^jU%yycG1>fNBAABF!35WoF_M7N|&AfnR_1fQKWfuBSDNHfDSN+t1l{3qoYy z+;8e+TOWoT1w;r1M|x0$;bp5(kZXEf-WF^ihXcD9n;L&l_$FEwxog76p~85gbWQrQ zX+lP0PbEw~@y-_gUS|p#rNr=&mNuAbcEmwSSf!aJ% zUs)ttnm-c72+ghLnJf6AwpoKnx%t~QtS^g{rK6-sP@Uou($fUaK4gyAA51}Wk64@k z%vAezx~hXc`Nf+d&*+}RaV{+OJ>*0;U=UyJ$UzlFZZ~m0*_X{gRRAtZbzfx+PZXE62zp_EbMy2xr5nS6;;ZN!>02#$qLV{kYHoGe7_B-rt>#jt*qz z%U7l9)jNA?+DWX59q}<85*UM>2fAj&qrIup6gi27RukX(T)) zyoQNuTl~Fa%<}yu^yE8TLmYko=;6payZf`;MQx8gRX8TBw<=f14_JyKVsp?=myomU z#+@j!Q=MQ3bN(2>n(kOl+~1vU>^;GWN0{>N-B>Qw#}<1U^;6rC{p1$nZkLwgPph#( zH*COI%N)YWSvw3U2zkT{Msj&lL9*(n8K+lelpK!LmP_r*?J{>1*15HVt-dSY0(QD1 zVYgn@Y~gqbH6x!x^?xZWm6lYRWEmH~ek-Q?3CC?Q6<~IiTFlGhp8S>Q?HWOFY>%oM zO|!4X-0pGf$wr4^BsG}61S#5ccFX9_8vylxGU^aqGw;;POfU_%zS)` z+A1u)WK57H3=T(CyLaE!eR##|O<)eNIqfm8W;}*Bww?Y;@nx*)jR-DoIN08LJ@ei; zzc2USHN4 zyGKe^8WO%)ydJbd{IE%v_zTYX5?@bK^3#o36ZY1E{j+E!leJW4W9gt9wINsqfgfNj zI~R4rdhesuW{Da0O)L3z`qRVGu{=dOVeOs?!4~O z_4;yWX5>%f*(NxO!_u3mX-i=)ntKqE8H`@KBpbZ!q4$gs&bBl$uJq6na#t_l=H|ys;kI7EG=*731)n23!4!o2ox7@sTt?SoNAnDp^^| zkxP{F1jTEmmb*p?E57E1oa=5P@y7#yu7KsaK7Px*Q!9!!mIV(iY51oOcaK%9cQLFm zDw+F%ZM$G{bvL9qzJqsJ3AnbSd|7$EXph3bb(JjGNR(HHn8Atib%b)j;&n1XI@UVz z#P~}FWdhrNf3_Mg;U0@gUh^Gr_xRoYd;!4jO~SE0KDeRQ#?!~IvK>sNdH$^Yb=}G` z!8}@%RDKwI1$$do;gQa7oV#<*5x(1kuuesMsv;hnlNWc#(v|LLvzw5Zj6M8K-P68g zVVBrP=+YF9tsQHxTy+;7 zbIzjnI%4fFJ=5HDPphlIkh=NLmO@c4_wi}@zn)L%!}5G^VujdHIBKghz^X`9Vp+qy zkam%!^HYa3d-{al_f2Hq4yH?u$NQ6nXxj9#kQYD@3$$b?kP&c65R-y@0Xb zz530KR_esii2RhYN9FGhqV49=MHYJT@YYIdIe5I6)uxw3Lb(Isc(>WyPrx&3aQju4 zP&P}4>7<$)kRlgarE9QstuYlh7ucU|VkZWx8mw$BpT_ z^k3^ge;8>bFd%1D=DA65?(a8B5Ry4Bg-2ki5=4b>|O`pSGBi{>TZy5rV zT~!}GSuC$W6tYn3dh+A%e9mmfnj^5)H-n?p&QkNj{Qo{eV1mNYM>e=dx6+2!py`Va9NIELPaoz8Ic z+g5JNa!^~4rsOEqS$z~1OF4@F!IVb((_WbSHRsBL=+xh)O!lmYy110!NZLB~6 zM)naY3Gx0iTw49arx)cp<2HxF9g|Mpa;H z#0%GR_2oGfn}I_WDUmzZ8!L*fi)lj?!HXI%B5FigqY4R$hhE2m_&h8%)e`?g z`zfHAVAa=hou22#>I47uzEJ=e4pGg3x9^H(*aF^L-SD@D>w6n<7oYD>m)!WKrZn*e zn1>~me^-i+{|cgPzWe)2t8G<&Ynz>jwJ$ANZRDMdUuw9QVHTu8%oKJl{h>ei2_Y_m zYnYA|Kz;-1%#OwBX-bqM1HUU9>(V+r-?p2%-&jDaqJb!UnXx(!lOO6IF?)@BR7lbI z`D04fvXhk^e7p> zjeLZn#Rci8<|Dl2%X~yyZ2H1^$IHqNCXM6w=o97)JDJ#bzFn(ALypA4zX;g6jf}Nt z!uLG+ih{Km@Qy;AQ$1+s2u{=5Xce8@(#;2cHE#~)m${7z71XT6Azpd8M{j9~(-5U^ z6sGUxfQ@Hxo8vQuPURse5M+AS^K)1GpVf7!3gYN__YAj249WL&JhCATIB!nn6pecb z<_@9c#7b!B?}zVc*lTz0+Qt%=5%n9D)t`8(REYE}8#Eh9!f}YB&6z(A=EWI$iMqSR z`X%oq`dG%x3J$72SsP#a(`|;?V4(0i@~XDU%Yr59McW2m`pgXggJGcNBbg=^rA5dB zN*3^RC5b~56ljL%T=B&oq~*?L(DHGHN*lr5RF=>U9MK>I_{h2eu<)dqpEWhC8n({H zktI>fzf#AS-;T9dz5O_26D9HYm^=!7^*!~A;GP_BhNJCe8#)N!jqj*?%?{pv?K)Kw?D8-ss{>R1epQYz1gsAQSp6I036Y+4j|IURURcsqfS`f;@wx$v;=#Vu_ zmXEkj`Rp_Ix{u!sEm)pv?HWER1g!}4wBJpx%msg}>$re>${!&l__TbRI{)+&_&NW? zy53p?r2ullqA;;1z2cXKL*y$z`KW9?jkIN<(h(2WP!1XEJN)Q$}SR0lA>QLZI#cdPE4C77F8l1Yn zuao_@Q6A_DPIygwYk;H8ycsk>fc3OuBAmRMnbds zkm(wl#Z92Mi?glJD&ytGrbq?&<45OPZY*IEKA`t_l;h&cqm}-q4AJiP4R_n!`F>%E zr^*m+3s6#7Pko$Nvd;l7D7bU)a(MH~F?&p>tWWaM+ zsaUeJKN9A^ci^|=gkVhN%JyK)LJVtgoGa{VyBFdx2UuFb#w zW%Cwvxj2~$XPiA;5<35;rjHq9p-3rp8#>M!{ZSIwfp0&2DOxSgv)^E`br-oMahGM^ z7~Y-C54M+I90cn@1~8>anbLT|pG`^Gm7^Z1y=+jFYMU?z`>1_1toVp`79*M}#HiYSh1g2IjV}U~GrhbW#7WI=npM$DbEj6=iaAXz zgfWIjf0_f>0i)v+!1>cx@ZUX@ z2sfS}v_3AkW&ixdh;#iTI=qf_CKsxEaH7*NHSVs5(97=@Owo!A{Lo&st~C!+Q7x$v zH0fz|k=bnm4ondtNe9cReSw3g-?8qHpfWR-->=gg?^-X$QPUreEdxO(zsg-J`lsz% zQ7#=Qq$#o!8NY2dux!-pMtcKQZ|v$%_VCbmPb)P0YH+LpH7i6eT!3 zfA7$J9N+?8jHSYH#NvDAeh+8v#*#NKOPaNoJ`(J_Q9dWq*Hltz@ScO~$}3t&ZL;Lp zN(5bn^q_r}2KYnK-(^izull#x70ZFM%VUs?QR--$GvlA^uzw*Nnd3qYEpar7!Ra7WNG~dF0gy8#`<~y)X&^_Ozg`6nd{} z|Bf=^W@)PIDdvqEc zqRxNGuVF#m7sCa4G7~slB6jH_S|{fyP{}`6A|~ukAxBrk73~9*>12*a6Hx7q(wk$X zYR#BSN7Gp_TQS|QcP3&&EX`V;ZN|D)In;Q>LRNJa2D>y_W&{U&abt?8vz zmSoMe5%0+xRl~Iu3FWZGn^kHYxnyg4zm30-DH1+Co?-3}V~y^>XN)f+{cp9qU+n0kQURs=QTPgV4?&pz^HG*E9J}%zVhln|r=+ zTV%*eB%ToWSY;YOG|N4A%0F)qo6dKgdKJbB~Q@RG=|uNGl4_x8~6?4oqW4hf<3 zzf{&eA936)(bXR#dV<&4#pbxYFQ7)`;~rb&1{_^3dYbY;JhqJTsQBnm{!ffqtpWIf zNyags+xf-vZ?cS5k_aH(!!RW>SX6wbNQ+f}gx*C&7cOQ_LzpBsIDS@)J;1G8?wt1g z#jR?*Rq1raN|I-4_LS<^FU$(1b6^`-s2qfUHL&&Jv7vT_>Mh|zgGBZAr3St*-3^tbHgjXvGiuEzOI=p*o?ukm_}ZC$(BQf%V~z&h~nI(j%35tu#pI|RVKX3 zSBDp?th{@}_Zy|=4QPvFirph=K0m46n6W-ruTB;*pF4jwW#GZs>5#>2RwF*l`rf#} zatqOP>oyI?48@m`t8`1lS>Nhme7M6&zf-kwULUkb3bPkU$3ykc1I#7!k{6%^jH13Ev3jZ2cErYzd z$`(_2GyPfu>{c#3-DJ}{B5cimTxI!0^D@OiFnt?37-8;<{F;?tCfoQ;+B4W2q7I9= zy?T9j^4E7d`D)trN=Js*ov)bYKA97};HrIDfX9ZgvZ$Ry-(o* z!{*ne(j$kou}}9&TT<@>yP{ZfZ}?hjUWPCR=2$)AqjFyl-dHynYn&`^u6@mOGCgJDF`fN)DCo zULQ<3$9t$qc=cGtO}ANC+Tb{-eA_^T^Jam#MW@D}wQp6s0akU;S$X)tZ;V8@ozLt@ zbLN6IYP;vVi+6qTSV_?{As;tMzH2k8*{h*U)Wl=ijJXSjq#89BJ33;C`kd(++L`PS za@p@{Uu=)^km7|jWq)3daWJKT%!|>riYZ3?2;H#NH1O*)#)C-)?JM_G3|KK>SN-uQB5*;DC4 zh@ZSwtt5vjC8P6WKL={RvJB$VI$@dtEtv^eZsjKYRl@>0%d#3@M zCdEbE=)*6H*`YB~*8|D8#a0g26y07>mSuh5cX~uN>KygXvvDus>D-zyeDVY}c@CSj zcA0!!GFrwG)kTMxf~Zb`$Cxhs#Y0SH+{}>&?Oe z{zgtl#V50}65vuupdPipP|?&(q6#>>Hioj;-r}N8)~}Go&`jFB>6GE6GP;=aEFGFi zInln4JWv1Jx~$YHrF69~KK_)?aPv8g_o3m=yH!V!)nJzz}R?ox!YF0RFPt ziwqCzFa7eeCc9X1sY3;6WMdI01IoUQ4GO>vKQSe5jJ&IXm}7DpWT=ZPKWnwkr)ke0~zh#4_ln^fH8 zkgMTM{P&_Sb^#b6D${PK8revBVD zgWVJDoHm<*BV?Il)r;|L8B{od?Vpl-M+Qc%{Ku|VcKoF67_rzENAsI+n;U5>q~Oa5 z`WT=N9k^d8_<&T1L%MdpcUGkTf7VT)2O`BFneYT=k~nvOBvvs3HG9}$1Bd5OzH#~J zNx_a6nm3(;fV%Cil@Ex4C#XPmpd6RKgqt%hMdR-kW+RmhQb{*yfms=(GicIv$&=o9f9^IOPAj@Q4#1LecjheK!<0A5bXLD~6Tvyr7)Wgg9oSqC&#{iTmOg7B9cj_A5 z8YdNzkjDP+*~HF!A(TI6$xf?)q-pe~3Y6uD< zwWy0U{{k)nX?~wcoo4|k{T68#1Sf|n(?$Vp5V8`;qgI&91zO}aw2=|ZwGX$o_a%YG zj`us#lIH@3fEI%kkMb%8Cr)bbxadNT0Io**fDvE}&}Y$G$wV7g*b;DI)ckw~*aboR z&{Ma=68F}!W5|@94mcpr?)lfscHWQKv18=yy#GxvU=&}<$#$V-phN^Mu!fS*GZP7R zzZ*b@g6qk#0lY9e1?n;u#_Di-1Yy9+jM`c$FGHs6uRcQVqul{o|4oM>&I$D6=gP8S zy$IPz^Plw5YP~T)C2Ox34GimLZwQ=o@S62HX~()mMS=P{I0|?~D02;LuwI>{()*Gx zZct;8Y;-%oxqnkn5@A+`KBnkM0b<74$Q3Y-2KZ-7gZjWg*uO80LOP=-!Tg<)4QYqU{?n!5^R6p~CI*#ItX+cD$VtDX%er9fi@9GB47n3)>h*KD#v1X#W^v)d!pEUeSHo^ro8j~FtUE9b= zq`-~#V6I_@3AeO+c~xZq{|YoUq}bMwG!Frx!LlbtX{uXT(fIIp>ok+-+7OaJ?!O-+ zEd}@tmz|XgsqE6lQ3PS;r0xU{iNs>}53V{nm^4`X>P5s-pA~4$fzI141bmG}UFrm=Ea;jZ+V6-}( zVAEFts|1w&8u|i}0iB(nwADcdEF~QQRI6p-lO(eit6lKyn(9V$R>>{=3z7eih`IB= z*iHz;iempS8_EXh?$?P)vITG)(g6IKi5LMb;><{LW`tiLYXKLK>~$P&b|HWzUr19dSTEZHYXI?@MSheB5R^3lAL$SzCjf{8CM7P}| zYXQ`)OXKVFshkFOU=_p=BbH1T;liLQs;U%Q%70ezN%COh?IfNr^eP9IZI+7U0L-AI z{*Cw7Bq1m+Q3q*2D1|2uXFVP7g_2Kn@?wQ7# z!X_-9q=_Ap^r+M%SW2O$zntF+&%!g3bd2%>*=5NBC`V=ftyh2nO=b05yjW^x36!-V zm;GhIXbHwJV{M6x%$=0H|J$ zq!5!q2y!Ak4iJ_Xfe0j6fc0;6sDO%sY<*N=N34zAXl>{F^!PSQ&<1V~NvvnQfM8rj z_^b9*A&E46Bd09cKXdC?Z@b@2+R3q)0qx<8Um>YUM-#aw!E)Wq>W zl>f)ihfhbHVTDr`h33bAXzp&FilyU*}LAS9k&HOUe=YMn5I_1tK z@t17q3H(_K$;k(l!BlXm>=Z#=@`^Rt{{GpWbpEBXAyPz1Ahm8C;P2vwaJtcI|MA2# z$9cxU|GHVIvSUoJA*cb`2xvtm3jhp9GjaVmEqGKRhZ!qyHu>qc_Ic|ptFZ=YW?+fz zJ=a#WNvb=WMg0Ni39yAOj!Y9;0FSye7~A6;{6EuC4ustD1{e}IiQUBxe_{b`V^4K0 zrr2@uIBT3Mo~NXvAF>W|C%2K|_!p71FG;PZg&|esRlG!TA~&8y81Ruvzf2WOo=G|x z!yaS?17=hwRwa^eAa+QN9sZRDwV^nnopP5i>{_L81+~1eniME`?xy)>nw#kW3V`z4sZ)hB&Ag}-|P;Tljsk=PbD;s0Qh1tf=B zkKz_d(@4}9ZF>T<0Hx!Yn`Z^C5kOA@E~wK9clPHJ%5=yV2sw#K>(kGz#{AD1mkuy) zn`Av&fYWdht)i={1yIf10#G(o9kkfN1nlx`J*10CW$ADRl@muDB>O+@l*qs~x!i>T zg!c?Uc)<97q6%H2%yz=MduRaO|qsy8-^AsQmYNh+6i4!rZjLu-4UN9*XPCLT*7e0A}MT7-n zIN9u?EY#)}zW(tqM~kEHjXH2pxYXgHcAhU3P`U&=x#qX%YygGuB??L)uMOTiYxWC3 z>?zW!P@~CWxInrNFWUHqpKXWe09>K%KLb{(dd|e1*f5ycW2ZMI0iMy1ULg`hvfCei zAo|eMGM?D&Hqwwp0l*ZI_5_d#WkvUc2iRdte^4{XklA@>Cj*oN;wBrtr7}aeI;scG zgoFyT46CZp#6iT#Ujw+5cKtfaUTv5B41;~YukmjT#=mn5ZUFTc;NBIDWHb--a$PVvD_~O8_+7emR~REq zdmYZg^Ox>sD{Ll%a@Ur|d%5aply1D~yoqkw=@nug1-Iw5(soE6^s16I;BuRjgF5H` z6|(gKui|x|TR{u#K1@bfz)6J7F$Qt$@mLEH1R1cH4`@5eJ12ODP*D0w+!<6tbAVGw#eM+JME)VYaPo4;;)#$@W}_Gs#-Z#H0Hc2A=I z3AYy7uC85%(NBo~eVZQks1)T2SLL8M<)Sa$srux^o5PORxZ|#-a8BM+aw_}XqpOT? zDBx`7-8D7WF|!ayNZ{8U{6Yr~EQSuuj|oN@e&S3JZ`14~K&;MpNWg+;(=0DNo%bb2 z{KyA7Zfeh3o=a4f;76Q$27HzGttQfE-=)63#?L?QXP`0zY`5OoW@kcK!Q~jU0wFCI zIx-nKI688BPD3>u%iH@c=Uzjbke%mIM)2<9w#OI4nfS(K!j;23z?I;YbIuBM>k&j{ zs+{w9A$wpuJMaVgHnVe3TaMmU*j_s%sPLKFmbV%$ewS}A7|xwImn1w43%V%tyAjs5 z{10^`)F*T4TJ#cVn>L1jXXXKMx0|2=H04oi;aSDQcZY^*BNsau=Tw(WYmN#Zt#skO z{w!U=@Cn9D#5^?RrgroP{Hg`+Bc5=G6Itj}VwPQjLA5~)`1c;2j>Vm?hVP#$afGxB zi+U6*#H@LU5$pQqPQ*`6(hKHdw$;i6`QII0u(N)=IxiW{grN*O7V;N72NuRv+Bfot zKkaEhE)1R%8e7_KYSbHV&Cvf{pIoRZ9e#V|vAE=ye_>E-n$KhjSAal);?GAez0tJk zL4JKMT|kbIq5qhE+!`f$9fmvHep#NiAQ346Ddp$pMu1~##d43JgsrbP10XMsX>tQ@ zKCycWREjvpw^8!$eIBN!D%73pH<5o*9r?hcuETtq{}j{+n+cV$s?61Go2X4vX52Tq zygFu*cBC89tV|uebpG(fGK7B>J7oWJ5HRr4Vj2LLyL$~BRR7~b0qjQ4Do7q>$rh|( zseYAkufNuQC^QiMkBQ`0=^Hd&r{NCIJHY4^6vE82Cw;S?z1{hPAit8J3f zx18GxGA#-}G`Pn&FQDJp%K3Nmr3#!}-Gc%WgbB<0MZ zUHr2k4Zx$`Fh{DMG9mV0jpQtUz$JBaj%E@g?xf0XnJuqK? zm87)ZqgdkB;BzbS`R`moAb_xwQiHRtvP(=c6C;jbJXJ(UP$+`=M`67+ob}f7YPLkF zRLO2OboW7~$faYm8A^gz$!_HX^BGdZUrp~~`S-c1Z@lvK;|;y$>AhD5l>#b@A6lr* z#&@}~zNZ92MCw^r$DP--Ga|UVk?Sm@BDi%=$L(2p>R>h#foO-7q|8h2{bLofPt}&L zBg{YN(^26H>^`)7J)QYjQpx?4uud0HARz4b-Cn&$S=4(cGMICP{L!>2+ z*q`;Zo7&6!P*07H{9$^@cLhA2dKD(4^o9SAx(G6UH2@VzV7u~X{%!r**iftrf0(k4^{n?u_OqndEc67MBBBN6A4Bla++FdA1soS)YMw9DC5 z(SsK8v=<&s4yxztwj(Q6=qPwa=qvOG%uQ}4k+w{XLXKw`w0oatZ#8}^N8g|fdNC0B zJ#`GXYLQmQF|{q*qVKeLO_;8~IOJRQjwKgYup<1|J5kB|DjeDY*N0!IuP|mmFDh93 z*!MT-4hOw`7=56y&u<@+){6I|Tb~bKFC&#v4+DL3zh#{sMhHLRG+wD52#dl2XG45@ zAAv%G^RZ8ab*q6M6u!p7y=&1!z?*1F$vGe^W2N+MgFKs!ZyMdVQ7h}OJ)&&C_BR30 ztz_d&L6?PS)X%wEY5D7JUBO+Fnz8~?Uv|C#x&R3}{l{Yz^y4>yQ=A%ji3Of=zOWwaV}?x1m3voEh={CWSggibkC(Vz@lMfNH*Bx+#8Y zXjB=E=o3PV{2%g?F1K56c=n}bWUrs*ScYJZGa3|;fl_OW)xTkZMdrV!rh%bK38m~oj^To*qngR?+ zo_qF`n2k`$4yqF*_Gfe{kmb;DaI0Sy1T}kc0&^>4N}|<`A`W?gYY*tG9FR-_Z=V1* zcc@kO#MopDT!*h+LR?Hphxbb;}0O2GllIh)EWI+qxH^EYn}>91z4*2TmtLdCJ=N+?ro`NI`8a`G?XYPL16c_X8!ie1ODn z#$do4NB~mkpOap2#Ab$^eY66$hxK2deF((YPTe}u4WNjDPx=en44p(BE_4!g!}e71 z?Bz@^=nx!HzM*ZjGu|WwOG*-ej}iAf3ZNrznVuUm3VFbg6-k1^z{i=_^xT2hA+V7| z`mac~H;l72^fM_kM1)mBx=A_R3U=k7o|Ii3NnUg0^Z>R65ch#papIx~e;En@?wJ0N zqIEaAGK#pfX#1~CkgueC@-a;Y^;B95uzkP3LxJW)vr0~q6tM=Qh_MU3P6i`vHoL4f*IZ@J>zZ@@SMh+7XzrCncfJ+^EEJ%$*L4&Cr~zl4 z;5?>=+uqneg;&({xV%lj04az;awPyGZEgAr>Zy3$DS9(LHnGBTM#O_yRJ(dqDL#919E|yRiu#LG5 zV6gELa#3F3$j$&3uUoDKLiwf+wSHbh41iY+C&DUZ*GRP_mBp8JzPVESU)zi<_IpNLl9$a{n80)@k_E*sHB(lU+@DcOq?X)>XfyvM_0^W*ki9_@*lg@ z?V)B1!PV3znIf-O1bY7HAU;k(zcN){-?n*Lw^u)xT^_Xr6&Va6cX{eHI}H2dE0B$6K=nRyr>=CWDQs&oj5kRZB56FuS+%DBh z)68+1tud%UjfntPG7x-tM7G`IZIrv;mNlUoJ)}HVvr87&`hZ4~?u_1({{Z(O408RM zVwN;pm2OULTa~ny>cCA}If8Fbn;BXU&5KOn7*jK?#AO0P8cxj=j|4)iFn&WZBciT$;P;+NP6<^2&>11*%@=s!-EMvnKMlgUz{=j zj;LjabW&Wu9{Jh6WNc#TWk#0INBl*=sM6#iB!f`UXGRjFJ}jTA)ohlVZpHAFrj} zmsuZ?eG8XjTp&Y*HlJ@49eA>d?ei4}rwUy5GHZjJ{U#8w0!7s&daEb$yAoq;&)IW*NCGlo6;X>J+Jl<_P8H;~4Ytd{rS5f>=k$3=fy zU~K`qO+6%~t#>hEORt1DIMJ>~VyApCh-i*OJLtatMy3J)q>ckCB3c{?4$K&z{TP|* z-VbZxHeu=MgSDafekqq^K%~5n89mu*S>pUlsBlpv+5nhnQxV#*OW|Gf=FAw40VmDt1>*AL&W_CJ*zoBkByW%~{0$u8O zp~7mjnv8|Md^gfGe%B$!yUVo}9HT`opuHBW+tr8nrMwB8FTNm6Uu+qB;K^obr@sBs zXwf5OBEov2mZyNG`wY}OVc}wjTWf2f?KlS0jDP`}(fLYassO)^uK0?u%w_q5ewN~EcgS>;Q+u@lycuX>h0Crwj4MXP$ivOLQ9E=b zk*7eo@FeRxJw)OompbUyz>;+M>!Dj!;VMpC4S~#QG6a%%lk_I(2jA}@b%rswA+crW zvPLI?kCvS6jg%s*BE*sc>o3^zhjGNxPl>hD-iv*iD7U3&C#H}xB1jvO9BzZ!$5`95 zDH`JjQxP!JDV=byA#k~k&x2`k{HZQ%4c$&k>KiA5>En?Kw=W#tN312i9$CPgg@`gX z!!?T@GEzZ0_EntvMKfLJY<`3M9)@TlFY1O}?p*j({0fS8Ko$_g;_92_c$FaiJZ**r z)RO{JHEEo|{&L2*S-$h;O|Y$|-IFc7(#%Pd!IO*_p+(X3cTE2C0d>XGPb~1~7p^EV z{UkS0KlP?1Idm!dDs><>aOfh46>|u22-ce>cADru)QZ01TOY60?npV5xOMMQ$;=2W zg+E-&4VhJ*u@6#Q;EIDxmbgFK(JZhM1NjrOR2{a`f~~#v$==4fNQM^@rkp!dZ)BN6 zWEW<49LlFY0W(o5fk}GMILIPrgrlb5mp6=jk4DoiwQd)i{{dC?cynTLjp4K+lq}S8 zCpEji(Rncx()R)7MwG1-;AFLX1&_q;ted8!q`n9Lc1^vQc?7A!2@p6?6W(h$^&9gM zXN7S4JTy0O!S#G(`>6c5y`D%Z_WGSpkF6gC{=ZTS0P>K^cC$(#pP-XtbS#K8)bS-NkA+J5Dos(VW#!s82U|6h*{tbei(=>QmdZ zG490CncxC4R7h?5n{7Jf*sAm^2K;6Q?xIGN%S+_N@>56+*n6k3OzE|^?san)pd<0ftYYF<3_a|oI+ zN-QQQzq~&1QE;FUV=Jej@OE_QLtMlCTWs)hlTSJ`$K7?#>%}J}{n67_kXs#^pgn7& z#Vd&-ZRt39HK!M5*?Vu`z8?D=x`kI=LNHagWU7Zlr#W!hu^>rc}9!7hci*sL=0_6>h^y{Uvs;)i-%Ri4XmbIxd-AZ9uli)HGkA_eEw2ej-s)N zDj#jwy8Mg7#zj$r2GIWfTqD2SARga%X+$joCXwVl@rk@no|V7NzuzlI_M5A9Aj=uk zeR?_R^XqiecD)e=Jq+AF0ua)#DAFL*e=W>KU^;5!ULOU7*RPENA80nf5d#O&(e6-@?3>6+R_mueH4F4m2Ra z!#ME+wUq?}Cq1HDK`$q@(==s%X#P3=y2{0Cd3(Ps?+^*iv0+;CrWrVfVxlFP{A(k3#UQ^%0MQ1fr zX(b<^FSrg|)XXQpJGLuN=ex4DmuF$VS`HS=!8HHey-J#P^aCa`XM=RmY^$rnIsTl& zWHXQ0uEvqnbLBiIb^LWGNqCJoPV=22?S#%0Tjo)Tw&6C_%;$ll)$QSZ*X;0lWPhE# z1Vi|??FCVQv=}zf{e7`iZ~=WkR{P!9^|36xMVu6_WdDCehUdxx zha@gFJ)9N8_j=u|%GNboe41p1$GojSFBE>S>$}}Ef46bBc&Cv^we;mya&78}UWMd- z75&L47aq4K`5~A9Nbpr-oO7|RC9cR^_pw83HJQQjlZ*36NCW*ZN+{uljU3Atq^|d` zF;kgsue#HOi5#j;*Un>(I0@eB)p(>fVyAT!@%#>i zg*H^qGWyuWiB*1VehF-Z{Mt^W{K&LJ~ zchP*Fa%16js1Fy3u|%|H)tkh^DIQ-TnGYj5kByCrz7HdZsWMajH@KuRYRno=?pLKt z9*`<%EOA48-hHyoKdIPFjk`nava1#&Jx3lI12I;oM;>biQ`_UKoy|>+#q~6{ga>a{ zujMQ;qZ2lVpDK~%(|C)S$FNOz*5V^4zrisnJk;+x#`p6ow6DW71I$K}{Rf0BDDS^3 znCE_e@wMk50oUVY#-6)cmfyLayq_m=R= z){gv&p<~WFyfXcU%dV}|AUHOtQ#YrQc<1v)h!Oclrcux2ceZYoie4Ja z-mqzwe>^>m+Y^EkT`g5L_%W^v4X~v*b(l*U8_Vv0hRp9=yuLK^vYd$>L91})sdjWl zxC&lcd4@w6x{AFMKMwyvDIE%oN)lHdC(V(! z@5nqeewpn71gny1T#XMpDH`qtF=oGNz19m{Ely6#`Uv!x_ml5LMh%NP*_yu8dt~`_ z>%%G~o;*WA&Lp%r4H)HF&I;N_uPa9hF$Pt%Zv-Qe#G01(j*Y!Rafp9-Pwz`-b+@ay zVTEDd#ySJ@Wv7V5-5fC7@G{qm)Uo$o;y75P}v-FO;}~f zQw}cL^T=fj{>VQp1`}rcUaE>%l@VJB^=>6CMY&vt4(p@+i9IFr)syy5$2>Y!RoIN{ z6z+d+ve26ca-5_s%#v(mbp*9&!~9Vj6Sh8$YAvrX(3&}&h|Y&AvOT<^(D@BS*Ap=& z&rn@+%42B!zamba$2@sYxQR$&waSNP`&dVh}ogw*|Y>p3ZUAJfp)qBWl{V!^1gcow`0I8ce-S^ptONZJpb! z6gU#{Ot5d_{Pobs?^--A*WBK|fvqTN&AtO+l|B^f@QQh_A=tnT_kdh6b^5B-bQ>!z z$CR;FfVNO^B+m-wb<1tB-NsTGR%!OW{G_zuLC;+2Pyb}ZV>1O_6baO(+|g+?FoT?@R~@j9LP67-P*(MhuDCs!v7u$Y?#&J17FEazUOt!op+zz}J0-V^1yNhI z83J88FAgh~_|atxgJUWwI!?ZL8yp3`tdYtOITN>iI{!5fTw-8)OCa<4$xE1g+3B^X z=_T1NAgC+BhyVk2B(#jSg?{*A_$0sLLwB~!caD}Nd z5t3$pVYy)8{C*-AnJgwxz1yV?Sm1{Y$E-XAE zfEYxg~v`Y)ZEui!4d0+y>+Nz)-tz8=f_@FfSpwcmmOZ@ zIZ@Ay)1SGXCkgM8MW0rJUjwnp8!wdFf2vrIb&kP&-qfMyHpvEalQP4~^Q*PQh@r{) zV}f75w>q@YbW;^9A8X?%k)PhN->3^k>Qfh=n{V%557hqNFDlM^;!NHR2_caLPtL<0 zEgGr2i;NK`Ya)HVodYWWJeq;3cZ=1gzjCglu#^*LQn8fMEPH>JrFh|;4ppTjmYXcN zhwl02cj-YG4>V72?5Ziwd6YsZEYFsitE4!51f^*iD%Vn7GX_HHx!@jb*J0N8?g$T3 zU8wSDh3B_D9+NEFxjGMlXm_X5Rt9fh+2|_@jxHbfHA`LmUIOg*VS+a9yqxK)u2K=$ zupTgm_4w}8!jDOLm@6K`+{}IjSEEH&$wsvbk0bXcVp^rgIY1I@$IQCfCk`~MPw^C~ z+I@`tgo}+B8qvixq$@Um)4|lavd2=RiM6Pq?Me|# z0Le_T@E-OPJ&}&@-4!j#di~G5JtC|6P77^u@n=m$e+duoX3?;OOpDZZdBE_4YQRXC zz*{7?KYeQ1@L@7>WGV1f>jsdbQtvAJv18Rx#=*!J2?`P;Ui10$IgPekMHDYR^1l%> z{%%|DcxK(`a6y#nQe*ruO=qR189PHPwlv6W;Fo*hBQZFeJQ}^c<$l6B@TiUxR8SXu zOm7fo@&`BM-ROkX!h_%A6ool&Mjxs% zFfzXmyLwTWn7xLs5=v{)pL&>A?8D(j1S@ps%i6<}P#%-~Fj8Z7?xJgYR5JP~6=LeD z=ci>(bcvIZF>4WC-hJi6ol^ip^rZUSsw|uq)ZFSRYl>ix{L#MC9>?e1ghHv`<*)MIZ-qtwTrkMELch$*)IGt5w1x+j zU7iOBpHx&22`cNGu~)VsTI?md(IO99Oj*~~cN?mBt3K(trX4>l3caAtlBk;RISR8} zJ6{)de_j0Tx$ux!uD8Z&EZ1#4Avi<8yAoh zYcs~xz(jx7-_0l4&$4t)aU{~Ff6g#pe6;4?7+8b=r^FA9}lEHQ2Gi{cRw2EO7g83y< zyPEo}Wh0Aol&?b)u`>(vG6oB&5Am;IbY(mx@{8*!l(N*VIYBs$YI_B3S>fXOQ|BTQ z&&D!{G-_V32F34K3NULpS9Gb>&=QL=Yr+LSU!}ILhu&Y2jRkA_eN%vOz%LkUJHzHa z^=R%l_LGl{Msv?;b8=INl{`_!SqDd#z>&9~2gi(@j=QMlZ|_Ir*@zjb3mLRgWfD+m zrk&E|6aN-e{b3GUxz`%rJ(&{-ZJ;MP#|K8F)a2J=jL{`C2wQKpaR-4V+bOl^;-9^! zc?+fFHssWNbo60sG((ywk>-LBp}V%bWc{?H)WS}p^uq6Z$7QSM&l~7I&pIY>a$u~$ zEL^f53{j@B1EJOSXivRc$bs97j}?=LeUmY#{=^MFSD$C~JJuYWq;qu*#)#VB1 zS%4QbtMw`FB#AW{nocliZnipmDAq4f_MdM#D|YotaGWCb8pQ9B-Kvw#@BU}7KWtil zgfO`<#O%#Mv^T-hyApse>q`uF?a&T*$X5nuP>nn>)cB? z(oxTo$Ax=hqrf3N`HBwTM2}hO{l^=)*8k2$MlirB|DW)}f8z{)58x$Q_*~!;0L8hv zs!ocknf~nU4P_9ZnfmUJ0<@!|o4*zSkWu*t^t_mW7mEB#k456n;4=Q-qaJ4D09NTi znH15)xepLnJILEf+MRg{-_L{G@%C^XZYYlKG@gW>E?%Jky!&tYz?^^S#;hOk2*7c* zem4YJ;0Nx*g!dFUV7Pa3Lt>V+3APc+r?{mGc?mc-ujR-r9B;U?+H^Pp1R^)&Xiphj z8SZ^YfP|cMF=PO+Mv@90mTsiLhCHVgU z+iK#^Lv@=t)_Q(G37{3wH!(_PzpW$JBI$1+yjjhExMcxuFHo%i#+7&ehEv2gMb1Pr zMsoj8T-k;k;KV-1VJFhup1%1{OCwqB-CCke5g-_2mdNJiQP`({VfbEMAbJ5p1E?Xd z_6_;xGr;Kv+VqDwdMSt4FvfWDR!nG^91in^&B{bQT}hJe8vZR!K(v3)okC)8@%&|MnsO!!p?zf4dCVsv$qvt#WNzr zJcbX+nrY7n^ZmLw#4dcXp9=+Ez{36yrTbU)|3CaLjJZvZ>-<0vDh?Hbra?_?L=IRE zm^=v&By6k{s>h0@|g}JA~2CIN$6B~13IE7k~}gs88!51Q5ahFSXrT}Ppx0dv27JQvT71W-z+M% z|9j8j>hQ6PaM<-U!|=DLh^T=*k1O)_$(|5KaF*e@xoDDPX{WeKeB?6P-Onqum7$sZ zEyh{y7gry&u|J4Riy7?C(YF#j_gf)9{dCHh8!-YQ*Q)N_TId7^aQ1}$;xfFNKtj7_ z?Tc8dNJB(;tt*Miw5wm$a3M;&xcc2cM!`G%x0&A139SshoCL}Z#egs&|IEs!lccnuAeR52Ak#i zC*itk|Ki3k+e`B$tPM+j^KmRm(ae9)jZg^R$j3ODrv8zq6-D1jltEr$`2{oq-(0M6rE0Iyw?W`wgXKk-$1fL4k4hqo6pQ*+ z^YnA*gE;|5UEzdCdl!pqHOx`p!{4VJ3=@Z3{^n)sNYDZyuw{<`jBseH_f_6F-QsJq zjV65PH~O?DDbHYv!63>r&s1a}k%*kq>=oE`x0*|}yjMwV_VViE0lZR}Njcym&)2eX z*EZ0aTULs{3p!k>qZ25xg6~VTRAztP`dd8>WA&y>j-qmDj|)3oDm0|9Zy+hYaT_vq z@}??MqFiz#q$LO1E8RE+}E)G}%%@twjN~9NrVsJ)=SGaIvOJ(nR!|3el z>;v-rBMGvO$8>Lo`bs=qM_)&e0El2U_!AY)RdLNG8yQ4sfanh#FjFuCYpdAd&EsYq7N?hADg~O+V(=BH5yV z;zM_l{Le$e#F}?vsWQPHpDsJB#5IQq2f6cTx%#$Jqo+wdxWi{;r6}U}Z37j!gYS6o zczSK4^2$25>_`v#RxQM3q+-XnBR{k7z^^*mLVh?z-s%1}b-Q9z0y*y!!WgP$m)$Tup z&)5MmF==FDScIkV!0Os+(1rG5|LSa`Y(DxA?N;Snm!H>lhhT#*&Pb|Y5^~zB3^jva z<`Qyo+2|32nhAPrzAY;%%1dRDmh#ywA}0cHodmEiHuXytw8c8EM6edhcjczsuV&+5 zR2{JE<6Qfg-|u^^*R2GVm>cI%HJwYJ-SPO-<6{@8%p1zrV9SiKvs7~#p3QEx@wYcs zr0Q0Sp@dKsW>E@_!MX%3*RG7^?oK=EnvsVGNQ~vFZc(-6%&iq(b9TqoP_;@47bY~- zZ#UnHN=7NRp6F_C{IG?V`(9v`24B=V171sBvFqyse=$(_iu+WJyhUS&{Cuwuqu%uR zPi^2XCElvYGsPIJr-|O}s#rUoD&Bf4^1(ANiN41Tz&%Uuyy$6RV&X1}F>Fsnel(s@ zT5zNp84inat!#3^WUW)W zRSW5925H&XHOH-%C@u~QhmfN@GJdiXRCCKddIT(!N-Q3H7?p4Js9p&w%z}4n)7g|s z81eIiL(5{f`t+tb0u*V-p4pGt2mXT^h98Ifrzdlui`w*QbK;QSf5Qgdr~S)%9$u%I z&4cNSJ@UV^)(-nVnEPRmYz>LAUr5coLWo@j$J`+xGAY?f=PM0dnv#Wh>`sC}h83pD2En^L$D&>I5#8|w=M4=&j7vU!x zb*Y1m*I@u=m^t*+n2gD=WcNTCY#jGeP7SjmS3GcTzPS^9-LYzxk&gET;axUHUuJi( zCN1bKVq3TrBp;%UFmdOeiOS&DLw)!44%5zS;(BSaw^g>qT6MTEmYHHZQFdU~*&XQg zwym5)@bf5by$evyYjr`?m9(I!oHRm;exoHaH%~DvdYdX@i}GW=_yU9CrosVaQLG%P z5h!%xTmH-UZc&3ts&_)L3dKu>J&m(NO0STEsCeqQ)A-lw{ko zg|`@9ekSn&JOs`yzKAsQ^ENijH5EyNr0-pqTjd;vOQNp^fLhLl+f3XV8_U`B6Jt2Q zMstVvej;hg$8eGM5Q{Oz?e*8Pu!4l{!wE`zdsKgzLY|rz%`2#sPQjC9h*aD5;$ddP zQcYAzJ3yL%v!~mryV5e}LodjsSvh1?HXXm~x~XrjIAa+$!rzbhRD4c|3{J*{q}eU@ zg!+(a6m^2*jtf&qViO+=Sm}q4LuZ08t3g&SsO>&tVzYj)XKou!;eW8u zFjK*WL9bpS#U}iO6ird#bN4v7FX}znMk-{0x&k1f1W%lK?5pfa6wU(V`Eds^n>P4{ z46^q3ANw~w%MXnSJ$XtU3&79 z7%n{36v=#sxgyBu=4UB8wZnJ-sja2#)~hx_!QMvCkBLskbO{% zk4#UtTNI`y*^`@!8j-O57PIknmF~=Vn=a$=DY0eE2E>oG!c%Cws=E3x7K};HS$K~) z%WWmiG*@c*8j=XrY?Dm5BsjA?y85|_QnwWF_K>Cu+=cE3o5YSM*NsEU_V-kVG;26F zupPt&?fz?B@EX5j4qoLjW#{Caphxu6Iiq~*6`&HG>HF^IF1HStTlZJ4ip_aj=!#{87v2n+Mc&RmxsDlvV7-Y9_k;QFc4nFF^+2Cf7rSVZ@NW5HzqFNj zvB_ng(bI2C6}yHnRHh?Egc~XglCu_Q+oU#pIPjx`$T~e$AuZb6ZxSozKV>$xuUmU$ zfliNGAMif1|8`46RBS&vWg=P#a{mL}=c^oST7=!bQ0$reuRwVnni6#IAts7vH`bf& zKJTd-MIY4OV8Nmz$;X&&oNIg(wh(S`(ljrQ6CZqbYOP!vnbmud5^r-wm#S>ye*c&} z`>Ki}@bk!>zad!on+McV&mINI0UCozJ4D&@_;+H5b93T zA`%9K9@pH4FdJ+W?k~HO3?~l=!P$dN62u0tLLby>ON`Y#F4f8tdJ4m_QVA38$Zp#T zyu18XM-=d>uR!bOG!#CJK2c}-p&$65DhBmWt9>7wFz67oRt>Jxkg4YCMqfxomP$2W0CCTvRxhNORb0LbzW~doQWG~ z@~=NEKU*4FjcH(s-(4=ooRH9#=Md%06$=-0`+l3P8Z5?GQ6OK1y!SC8V-oAB5LI|4C`4Q;VK+%_=P3|x=A_8#yGES22f^Jlq?y@$ zSlMR^w_+Da7!~VKFz)r0>|plW@7=E%>wO?1*Fsa|QeUGQFqxLySw-80<%H~KU&p{Z zx|@Zn`x`hwc?6x>0kyRn+jJ&TBgRW$`@v8-Df!kTTQ$PEDZZYdLKmFr9b=d~QBf2c z#u2N}u=koa268%g*Wi)!tptT17?2yF%b?yZ}v&QDt=12Dd z>ID7iK3iiWz|+6-j(%OLT)>@u)^J<^FzG+;6m+zI+b^#@EMVARR#JIUl^7D1qmvV6 z%j|)xGUutJBC-ct#xi2F4)FG@eYgm<**UrgWZs8Ij98RRmh?&_{p^|Qe)HsKuwnmYix5lQp`!(o{+V*9SS8w;|vuLhC1>DZ0OSkh?)RLtDs=f@^Rr$`_@$5k( zlkPnw#x=TtxRH%LQv2}WND($HCR(2R{v*wq$nEEO0v7;2-|!M>8LBeHeb(e|f4S_> zvtR>hf?_HbkOkRg%Fv$}V-60o1emAXwdmA^)^SiZ=QDm=j%iE1jYhkqm8$u*_si#Q z4qjndMkh^M(S(-!l&!QN$&3S$FPA?qE>}ZznWB+V{aq{d)C2bj^;_(<{5N(jlTfhM zvV8{*TI#EceUU|Qdp9!SRAWx+>F7f0i-n1UHknlHy0Yj{ zy8G1?iKWDo>LLOgBg&#sA3?RSn%TM(Kk_>LUu&$&&M5gZ`UVcfu+Lzg9rBW~!a%Ys zG(R>ljScQDtQD?BJJx{Plp=@`Q|y{u;5c>(p)CqM*DToJg0|gmrBq8-_A5P@A-u!K zSU5~w;rH!#Y*}Z;o1TgQMO`zUadCF75i|O%4sANqPn-3U*WRU^1ZIr;>!Gk?O3Gr}`*@4`1`43= zV*A1QR@&?NBECxG0R6hU#Gl~em<23#ktR{SUqPZ)JM)y%>tY~>5@V|1bt%ahup7&% z>C2iTKQ%~aFfg;ZGmM``nabZD;_5iV{t=kpnDYXj;xBV(Lf#duH5IBlfn}e&3{{jE zL)+ut?goz>ACUq8rOEcb$0xThARcC$MJ-`Xad{Px24 z6xf(K3smt5+d@I|*t;S-j3fVi=cMeM;;YBSXMPX1Gn-%MEWlR5T!;prSeRWYeTwB3FatVXs@G)f;Dd9Y1&2bi1#rOnOJ| zjuP0HtX*mIMZu)3t8{)$xL6<5%)~6(!NcKV47I- zJUF;IL^M@nbBpfGhfHz~1d0HuK7C@~@3j+1rg9Jm?+}S*@V-V6c8SWg3<;;U(gxPY zZ#10}Ve$8sOQkwwibB^k*^l|J>Q`B8d*KVYRkiJ4{VwCmj~%74USo)e!Q^39_4T~8 zOb2f1Hp8H-kzwbCjr?o9uDx6!Re>w7qFdcE)t5l1^2NbvTK+Nbcn!d*%!12~bHHM# zGLh~E`OpvsImCgg#5;MJ6^~+<-k;PYUWmdgzvsW~pQp$hW-nG(WUC->2c)+b-lfDZ zBFz1hcU8lu&+1kJw)n#KJs}kxzPHh3AEm0aX7)Pa5BaHQh02yLO$40oZpio%OA?HN z2QS4|WUmuO845elHjqGy@n%+vs^!yBSi4MVwrs`fh%_@;d)#?OF4Js%nD4Sf5PfQG z@NL%lWyKc%+8=uRz7>DW+36^v9O(C=-&~o~2P7A4x}&l`nzVDF-R%b}9|epEmv%a! ziKGc7%6x{-UVOAKRM$sgr{|1dg}t{`sL8n>HPEMrSY=q;_So!M2#Fo#8ZZ@Z-YRjc zuQ=;yiJrcteJA&JaS`ScSsr!mBl;Tg@X8@D&uEP~q{fIQLBNmu_!Uw9yF-Q9&{V1| z##y(`5Vg4+A8W}3L?CmFW47bV?NGvT-w!z~XN%R+SVn^Ghh?X!5dCp4p_#OympU?N z#zhX{KBylsvgOB}69Oypy!JXZiU@E12C)Ko0XKUL}zX3#A2WJ^`{s1 z6NoJ*j}cOhX{Z^+x~5z+m4JKK9C3(3t#tlkDgwlIwZ*3firLe_>K|wx;}0Bgh(PPS zr7`R$7j$$v=FY{ZNf}?NAjy0`GwU{9L&-^z71^z;UaRsRX;&2|cVnL?v}3TnulEug zpgLtEBUU{h2l~rSjT5WR)8ItzsvXwxBTug*-HQ_<9XO}%z)Dqi<747;rUQy zW!*hnrt6`J@0y(Wii$**nGr;<)oSC&gZDd5g9O!eb=xPuef|34$NP>i1W0QB(tB@@ z*<$V}2Gz-&CQLoPgUgW^owItLovd_6yuNLC=l2d~rfH-$P-nONLSC~sbH&U2nVfP} z=!{9<WrRbl}^x5-zwiww|^egw&L_fFuK?e@zqbZ4|v+OYddMfSS|;% z7U?o3RQf7ZB%8s_4b#J?cI4J>@qWEq`TL^Zq-pO;EM6LkbvrmB$sLU_=PgyU)t-dY z)Ity%fu`~5Qjfm(-jlLo0}nGBQL%5|?z~{Bv{f1B4wEaR-|xD(J@v3r;eI%mnDLZM z2_;KU+jyfydey1gMeX!%XU#?<7S5z+*`|Bo+;E*|l(5VE7&b0>I-+jk>VPxDqGmQ1 z24_+nqvQY77ZcxG?v~q}Gs9?tpIJWB1&_d#hh5Sd1xL+IW(H9vK5z~Hl-^X1y>>)T zuHP1?up@bac6BEwtDL_#!vH)ezX8b9OO$Z`Qzog|$JwD>W;jzh))l;mbcYDtq8fkN zB93Oe*FfuxH0X0H?@BM%1_xP-Ye(JrX(p*r$k|*pad^aoMjkHEEtj=`7QUe+xs9#A z?3_OjAVV0;SV?6CpHKMNRf+3_$TjBZ^Uq)#KVhXC7tVQ8Gb_fd3({-estm3X%ojU6 z+4}H&dXH+n^SSFvqfq5n^KrWXFPWKKMcDYeWWS?t@#Vhv!($mP72kGsCz3_%uo)QQi!4bdy5(N#5cJGfz$elx;N^>fII9PjG6A-9T} z=aR87Qa1QnrCA@=79Em%3o^8ecBOKd9>KNYLg(FC(}B>$g-s9ax>x%OZZ+m$YOL^r z^HZ6@<3K)x$LUqGLs8?&Rh=k@d5c}TW-pnh(3ngV$lXP&i`1o~^H%8w%176`bGo?Q zLF_vyV=ChHPhArwYgBy7KR`X{f3UV##b}b{OukddpZ&ahE;w#yQjj0@ac8l znMtd=6W_@Uo3P|nSNv?FUpuUjY!4`1w2Ci6(9^&C*dcDG3NwLB%7|8MK;sTC?MF26 zi%{-6^NbbBbFX|Yn8+)sBNu8`GzS_vY(g`Qu-(BlV#YMp4>L0Jcru|+d}pgA#JEvd z7UWp-bo@^S1_R$VYp2%vr)-+MUyTkODa}uI;(8h8twNU~Isj1%SIk|-?ans3ZJt%l z+X;5Wqkc-kcLdKg!3+-x$EB}Mox3#{%|MsJ6WPxsUI?l!PpU;Ohe1x7Z`Im+MDgXg zP^*R&ty?@by!DGg-n0XhH8Kz%=>(zqMFW4O`LSf3O&13;gm03*O*-pZLuf`YQQN%T z#J9GY@F|w(C)L9eaPvgtgk>8q{gYj5tF< zauyt1?Xu!WP%SB$-lyZ84n}b4M)pRONmps=REK$B_(E=G#|O8cOFWzNte)G>vOXN2iaiS@srV}hg zEIZ9kaPLr|vZVo{kXHuxh##SXh!OlAX|(R$Har#(3wDKZNkn3 z))>4waY7a@hi|Z z)X6}-i9#%HFml9qw|_*e=8KV$#DrZIIWOq7*rVzTbfx66zhU3wUBr*~1XjW26r_1` zKLhtvaB5F{Pt!*NH(ekn^Ho>AQ^2!LnENIw@{#B4`AC2Cb)NcMMb!JrKP5Y}@8@P( ze~A}@h$i3!4K;_X#xh-kmA(rVr5L3OzId~yYubu`t__*@Y0KkxzX!<*W~H8dAZbO9L?kN1 z>LrHCb>Db+Ll+m=|AmG~I#-Z1$sAKoCMUch-nd~usEyvfAOUIXdsDxpY?FSQsWjc> zclqIKSZ_U`VHG6zT#&DJuxhYpBHQ{Oc-(9b9UOODaXf>quV0|y^DGkPCjvD{emd!d zzQ!ZFMUm~R$K@Bs&*WntY+QORtJ6?LAhhtD-BYa!6Ih=+!wj;x8-%jLE;rJ+WX$)N zx*AGhNzXgI^OlEv4Th!La zQL{b|ClY%?%cKbVtWEOFRn$Md9xqsbS~;#*QQ61Ptw4E}pF6|QyMB(hVIv6D zWp#^GuO-1)R&;3dkmtBqk%i(j9JHSlIcVqee+#00L@g|~@uw}XYFM9O0umJ*+j;UM zvqGR~0&QdI#5kt7fm$Yz&0UE=edFSjc6|$CP>304)G6d_A$NgfF*j79 zeojL6sls~9vdiVC$6J5t?=o0pFOBkCE)R6tmhV;O29L|IS35cpCy05kvYB zPh6#b2dHiy$}3?NR+&Damj?6Umry}r`13%V3db)hamBb_-iAK4MYEa2jWdTiCSc(s zT@{RziBl|u6PI#_Cf@OtecR`?q6uR76+{`aVhZn6)HjH!m5vyf0v0~^B{E2_Pdqvb zWSf;z+F&-`WHOpmnbG{gr?dX27FW$>mAvC>!j7DIF17D5Z&qy47TshEGSJIu;i>}J z@{dq>p04l5VV7u>xvY`!e6eJsoze_N^gJ!~?&=BP**pWHYTe$w{r}G=n!beX_O~h~ zn|nIAtNgbpiM=}_Y#%?W)qC~Ub;dO%qJDPjpt4xkp{$XnN;1_$lJBM9nsFMV_fM+OPID7i`q76 zI9+riqAXz@xC7rMZm#amB8gx-S?kI4FQ60ae9Ce8443k;lun@}!=9FtIWb{|2$PH9 z+K})3$l3!{*h5w1>b-A*9F1UWwx1k|FUg+vx}8f<+v}JSJv-N_r4hd*J+HX$LBC#( z|Aalf!H%Dz;_ew`22MyW(L(9H=ALB`VJ&5;0TbJu^{+S-I(J%WfHu;{(fQfw6=@3% zgmU!WXR~!D1LE?TJR6rw7ck%d)H>dd$9)b8byOdUKf4aW|BJ9UkB9Po+s9{& zCHuawjqJtPMV9O&vV?3QDM=*Rml^AXmMKLcgd}81*%?bHvX`Baow1dD{av@-pZD{5 zp4a#F`u*h(v)$KuoyU2c$9Y`$jTpMd>VJY+k0@0T9&dQY=61ogCs_xta3q;vWo*kYbxdQW}BRi}>r)nRtjUYvjs zcP2&QYg3@3a#wI};=2jRzXRbHUGZlx}fR zbHbI{B4yvHmG)0d&sWverwcmaPd<6dT5E#5L>U%JpJ1*P5be_H0f4`M>o)Cgqu0zyzNoaxP%bI@&6NR=b z&2nTPRXJ7p33nwqe`ExW`uF+__VYQ1XVfEqn{ChB-zG?J{~2C5`XlQ_zgjsiP6PdH zeL*uQ{vXIHNjeeZ$2oRcVlXsDe*fc-Roi=?$4;csYir)z7!xe?@#+d-c-EzSm619$ z+-#_~n0k^p>L3UxJy2CU009D(seZ?VScZ~teHWyG!g zyT>foR){}WBUi$wyvxb*TCS49I90=W!ahcX7?UL07E+<*+XzdPtKH9puYb9`a&Z>n z2Qxn?$k8Ln z=fUntVTwDHz$#dajsr)1C12k3nrI~F^`nRx3-@4Rr8uC+Xi3U>RXR>c2|s7`Ku@AG zqZ@zOZCA0LVubIX2!3SQ$AVj(g|kHtA>&w}%b|x-9H&d5pzxxzG{MTjdaB6JdgM3q z1oA{@l-X~X6_GpCQH+H(WmT7omztp64_2#40BA9~Db+Bug1>_XnNDc}=T5961Wul5 z&CTTH@lsH-r@E<^e}ztJ6yBSLkUepU@*I3*Ip#ieFEs@?_bsr6j^do7cU&K7k&_A=5~#^*7}PQ9ZQ3TD_21=s_9hr{0=9)H+bIbD2wsnk z{F`tktWd@mP+o&cF?OHtsO@*+3zP=oH+6D4P+#57UR_GQT=#Mk-Fv5hodYB&GI=gF z4@x=SW=&n8bM#Xh@A}7oJfk&J5l`_-P$A>1>dW$vfG2Q!RZ&hJ*oZ;csC`^aa6|iE zJgcXkpxdr_H>Z*d7Q(f9MPfe5w@uW4oampwT({FemNQNz!SV=ve5osd)u!6lq{}c% z1VlR`E8;LM7+;M$EC>NJbFaJ+(1k=N{8;DwE4iDemihai&w}6%=O+ZIh=Y zS0=MY|+@ zIu;l{(09?>QxjAOnlQQw2EP5T>DR6ER1r|g7@kn>!`n@HkP{}y z>*)4rpFq-#u!48x)_r|wPCMjlrgY|OPA7gc@l`@17ru@>#fKs|!x752PhC7{2vx;L zDRa;J(LdbHN37#oBM>5Q6)lTym+9u1yoPaZRc zr>MA86vsb0p>Z{T=P35mNAMA}B+-$z{ngn>h4jm49by~35!t3W#QsF0JFX-W8=k#w zr1wi+MKTx^hFs*^9t34#NTmSl#NpNB;k7u-FfUtdS-f9QAK|yA6?EDse!b6uiIKZp z#-~FWkk)|+h_%S`Z&O-lLj21TeCP$=FR72q0{Lp;Bc%8Y_WGoG^1EM$WD9=0*29O@ zDaLoRZlKR0Ht4O}&T$OBOBF;a6p8wD*kp@p6VKm+s;GY4OpGtSN+YasLhkz? zew5O_44L4Ihl`FQcTs!PuwJyOAO0rZLJ10t*-bhKh24txyC}9v=5({9S_?c?IDBKn zao?+PC?bn>9o6CCAk5o4-JGsEjT%mN3R-Op`03!?$cNzw%wx36kPB(W;ynu0Xi<*A zr{IQ~k4Q~UwIA}J_FzG?_)3( z!?SgO_S%e!aJ_~eVHH8B>GV6Gst0dFs_4X_u><{8cx8gzG1p83thD=WZKkQ$N6Jo; zJNF(p5|%m1Dcyz;X6ixwj{|0JkV{hvcjYnFZfF&{md}oBwX}{6QG&RcfaahdY7QkqsyZRHJ^L9q5PWuw#7D}l*%Lz@P>}he=$&o z{iQ?&4`b$#{s<+Gn8v9$dbD&k`t|ygqC>E2kHg1rz%01DI(S#Z!$AxgRl1Q77jm`@ z#TFJ>?(#nB_3%DuBi~EQb>u_bDZZd+BcyB~%aTN|HTlU8&WUJT6oot#wb}3H4QR9`HrQUxqoMhJc-<1;Jf3 zGsXa@Aq9N)+C>hv8#fdc*m@#X$-3g+4G3IQyWi!WWcK3iq?aR|GF7IRYWoqNV;v8+ z{Znk$!wFY{m*dGI2TYuPk_x91?Fo{@IS>cm28BB1>WoHsukKwr777J zHK1^Qd4J@5BF51ARf-b_ig4)!IpMJse6s_iQ1KJBp1L7}BJocawieaX&ccn7*pco( z4AhDn2!|5xIm<19VDi)E5Px^ZkPzGn{k)@Ce&uT$`)x=-BStIeN&+S9-5f$T5nva; zqAR*Vmo-GKTswqm{=w-(d?P>vCS9GAPrc?x5Xdsau+kDIMW;qTUS=HJV&_-#|xAnML<1x6O z$@9;t`LDw~h9oXhN~P{)IT-v>&gRL&< zlClOCMs9y`pN>k0f4~okWb$p+V9&qY(R*|FtId*PacVej_4Cn{A93iM4vax)%{U-m zIMiSCr6@-`ryD^HaU3ZU?VWzpR&iZR0fo3}a!ZePk9BXyhiRs9)~bMRzm#9najy|G zSri+^-R-5!NEz0RrVxc2LL|Bu6r|0|e3b*Y4%HcpBffQ=bx;0tv~!ZVl}yHedhGKo|mjmABt{@0<0H?=SQ zX*H0oYTHZ&Wa>kHR?a;#>l{?k@VaRd8g9BT6{{Y+Wx+H`%t?qTF(p7btVsHuFWRE4 zAj(l-DC~UoEPhQx@0fDP`gCwvA0$o|7&MJj>@u=)yAXXSUaCHSQF>Zr9Ikhj0!_KK zJ@H2Q&VBzm4g*U^0GAOU?xPU%gSK$U^J^P#Uc&P&p?ng@1XwrnACdT!|k>UhAw_X7iwPRPDldmipr7gXM=qk)ELMD z@`A<6mE{sr5ayU`UI9kS{+*6n2-f)0+pY}4DewyO_gtMV+Y_o}Q0c#TQ56PQLskW+ z>Vz191r)uCyYK7qjR~=(;a0WqAU=3pXcX(8RDAc@)ytBnO^@qdg4}WX$w{b>AX2Vz zkI5md_0pD>6OSWJqb0I3+z0 z{cw)iLv~%ee3vZNT7+M{LknIi4ZnMtQ8?a?wyj@-t4PhqgB@g14O$IN2?Q?OY7QUR zfg4u|=7dX71iaW*=k3bL(UYFhxPDPqx0*N3PJMb^A0#vuWc*M1*stVy0djDMGWDY| z;2xXM9ttTSVIv^}3QdFkjhl%uS2_IoS*O>bIhu?QE<{W7YdNdP!tIJLy?)QAjC7_y ziXK8Pvi_q>fl_Z4$`StKfT z9|A(1SM3~g@M>!93gwm8of}el+ahMRmY(GY_KjXa;Tj#v{@sOJ^U&+D>vVR|>zl0g z>GA9uHrl>^vNOwDVUiE@zgfs2@9TG*`gq~nH`=SA3~_GD=J3I^t0%m-QoB~rnlAR zFkB&$J8NgVu~@Zl<7BSg(2L0U+Yxir_o4TelUQ} zI04opOFBM0?qbr3C!rhGLp))j-(P5Ecs37}v^p6YX59&4`ZL2BJy@_X>uA78EvfqI zsrn6gK8$>?K(`Fq=n*%Mn>nJKI?tVkM%Y&o`*NK%6K!9@!$23g!O5#ly$ZdgJ(#V7 zSG$mE;yV=*g#@A>E>)U~999VH*q+eqT9&EPWOO_AA&aF%q}ruCculyA!vBEMOM(+% zn%jx*kf@{wJF9WB$nq`#MHHJdDdC=gbmbPGYs=kdw2d{_J)G-Du6{k3`}DhnN>)rw z{zCnOJ{c81stc|r^rv#NTeNk*^lhtK1v8n}Y@vRu2lSren6o&sckp zl=)`=G%S08;HkjdtlK&uZSQeY+?`(Ke6nDJdf?*OvEa?+Q>ZyL z|Evb)-0R=oHEtiqxk)2p_>2sPMWDqX?~Tq zegP_u$Gc`sgK<^5NCWz+K$4Li6fFmF{R@SP>hBkg&nh>5g#0@8*fmZosHpBoGmiRo`5x(l|J=4+x{NM!9Za<2(r32%$|nu_WDPkPCK0>*v1(ZbO0U zk^F=t`tz)VNyGUTQ5M|HjQ6wqTeAKiD`BOS_#i*6V*-jRFoi>av2b0EMs6YikMn9> z%Ss7(s0mgoMf$GGxFVTV@KZ`3sfhkGSlLsk!c~HAaK2h$&Ab9>&{??;qv8ds5!yOi zyxPs*nNjh(CPMo?&nCyVNhC-)BNWvOtqcC+wNCkLM6H3=_KUREGA9mE4wU+C^!U_3qc^oNYfqS3QOIC!B7amr)tps}{UfcBoRy`&f}g_Wi;5^AF{xv&BoY zv2#k5SvvcR-W5Z{)^WWpZq30SvINQfUf81ndbMp5ONlFtZb+Ss&-%G<7>X%q;Sg_9 zepoWYQNt#1FjPf5jt^mt)lZV4iDu_jKkRvt9lRJ>kP;1=9q{C-E7tZaiDF=pPG3tmXHX+^ z4vyH$Z1kXyD884**|EPM=#cDFR#sZtl=z~iN|P=3`tDS6($0L`hj!vJV{Lg8@7NE>(gh$>4c!pfEWK~oo7k{n)u2n)~xiVFqN)aYe^?_6z4STF{p zIHluqUtT3XfQd)tC}1MIqV9KFqUUG({b8D@(`GS)73N86Yl~}(KZ*OLA&jX(Pv^th zPp~eVaFUgYIx)Jr>_rVB51^WOOkn~r>S#O1Y|yu*%Cn~A5ojH;vI-{$cDl=Wma`Ic z2Ym%D8Dvk`zWCv(ZD;6e5_QJx!gU=^)k>FwMRk9Fmw2hr+3{08bMcLf*{d;9aBpwI zmR(X_mQEJVA58|T3Xou!4*!lrV4>SmUJoa{Uk=jO+-V}#T4mk|3-}K}+x!neOP5vn ztY6PRnv*ZGB#sQz*NMAfY8-5^If68k z#{lN5p+EpMqa?FgGe)4A(myz8=1J)EJK>77hVWp^Gq0IVOHZ0)#PvC8jhR`VwkJqR zNqDS#R6R9ot-Mh(0azO*W04>&B#BfJ`?vP#XlN4`?Hx&06<6cH8b@={cVAzn?D{%f zoB8s9V9_}7@b=Taz>wdFbJ8;@n_swpAHy(v?)6{SYy9`3_Lz6+cys{_>yFo|h_QOQ zid<`CUm;oNrX#CZRTq*%s?6nfSuw7H_)&&|kp*B9%A7i@JVjNqL+nKV@wjMNVdGqE zspDGXV}XqncR0#vUsTB&Lb%eWibt^;plEKaH7?;r8z)dIV~Sr^X~zn`u9zPqsd+w$ zU9#J&(>t93w_8K#9aT{S^nae$0`P5n3wRvJhIsx*#fO;BiDTWTzo;`((nmWz2^enF z_F1OGP81WpDrV}Ll$j{9pa9Omsk2$rIT>prgIUgA z?XmbyD+w;4r10-AyT7WHEMSCie&f4%<8$4bS`@O!u%dV9+5Oqx=n0>fc*I`}lgLliYKJaw>&{BQH{Vi&N|0-XiODdH9i>NnxTiW9$5TYubc5#*H`0v0%<;Pj zkM=ArqwS?*MhxSDWq}du;OomMILESAPP!S zMMrxIFFCGmIoLiX-n4H7%z@<=QBg@) zM*QuS6&2r0bUJmxdOPZEqryCa0@dqhS=@S2Z(ROB3jXvfEse}PSykvT){Ndb$8^RQZ=J6ip5|1c+>Ix-3uC_*msd- zXgSZo7{{LjBGM_6pq;U09sH!oc@)r!N5MMy$=D@8Rl>c1biHG7Q?&k7gqC*JE~PUQ zs)3P{mAJl|OlNXy&wkhch2;LT6>oKMNotO-#RfK2`dOcM)T>(->T1PI42}N)3h6sI ziEUkebj3lpo45j}`-b7HDAEqn*S^I`N<$fvmZPNIkOrx!iTp`a#2iqVDowrQy`tSX zT*jok8M}*zCBuxanuH}M@>d6!@sFjw<2_{-vnA}%-gr&Qv&?6r+Wydb$iZK>IEWWU zAb0o!p3(jU+vk1#-5KwEs477t6n8Z+)z&q|>OVIvs-xT@$x6L<=I$OJ7u#cr;)`6l zFGm%cb9}mtnR2ym#f-VQZizmOkEM%X3y)|wWnOc2L1e)^FQWCAgcx&OP2Zh)!;03q zt$9p_N*O|1$z4edz=s*eRHc1EHO!h70@e1jht&rXyTp<&VQc*XF-e$Tnuw%dF}{lqt|5r)^=o-iUxA^Gk@QA z>#X}h0)1>1M*q>8f3PhwZ(Hk}>`~sy$O8|QeYA~ugxo1@YuqemyVHK7@zrxi9q!+y zliCYKCq2d75A7!aywi5-YFW@+nS9+iA18|$v+kw4`NkCYQ{rEEkNb=bp*>;mH4Bpf z0?VQ|{k9L;tBzE(Sdji(xJ+3Sq`vcEk%{;?)EWH-xYvyYA?_xe}pQbCf4Km5PyzsC6p&<<#PyQ4KqM@lNwp6)! zY?Z3$aW6YRalJK}&dNEtC=@SUyr!MKanQ@yD|w;H#O1=881Gzv!IHXzr?xeJ``9M$ zUH@v9!&M>tD$lkw`(Y0si`)G}+D|&ak2~b!?&tgVgo0z%gx4$HX0_?n(l!fGWY6uV zCN=S3x!&KpV8n^APk_?i9}Hx*wVQPJy-s;iXbfNQR18LJT?Q}Cr)d30tsE&BDH+3c9l^s%fj`4WP2Gn=4Tk(hulB+>anvcfMeWAVqwTqZ8xhy1 zF_Brm3#U(+4b$@*xs0`MeJ|a-(%mgRQCFKd;mfRYQ)!34<_>wAp}Ba5o}|%_*DP-G zk4SY%go}Ve_77*GM&HG2fN1}I7@FH{kqV!wsk8Jm!q`}_o0`_ z``Zhjssfe<_nul6T01AV5Zw|DW|Bl`dFar%Q1?I*MmJt#s!uwb!1=P74yhN<$)@1F z-QR4HXI}C1JYVHPHE||#5cfe4ZUnz6c-Q3BAn?Q{ke9) z#=!jJn%~ERjje&*orJ{aW=UzY;!#%Z2$dqq ztVF|6peoVhtP?YYWc*it@Wb54yTxi|U4Kc{A>+?EM>M?2+|IR?;^a@XUkn3WX(U)P zCWHT6=u6)seO_UQpK%{`*XPdp{WJ=)BHg9U02lgxhO_Pqeap?2*iwBHP+B3c6Eye$ z*Vx{UQNcveCbqR#E^@}GR1|13G7jIow;ynd&sWBpn$CDrODY?zUWvOKtLr>8(u3m1}?eb*aW#&VL}?Y|FAaatK7w7`aoRj(TtC- z6*eM?ZxS?dm;Ry-d#o6qv^`}Ay3_?WMqa(!c4p~9EJrY!$Ne@er=$l-l@sgR%q6U@y^4L-i}`1s&NDeul`(ETEcRbhg$@+Oa2XJzFVwSJBCr-qGXr}M_K!*7 zfS;R-$t#@&z0RxGpf3d-h^)H5IN`oPV``6N5@5+^YC$z8VfgV;eaVyK>JQ3^Z>C;v zj~R2|F%OfgqrlYAKJJHVd5pw)bEgOTi#Y!QgVM8y!7wBL5pXye+9GeW&mKEKo{(9< zzJTA&r+YYn z;{2*q&m8XTZjL0rxiW5Ed+Q}N$6bNy{j)5+cQcujnCOtgkWdx3$GRnMYSis1A4HC*|_Hh5N2>TRH&Uvz9$_O~b`WgHd-RpGA( z1i%C^6Dq)w)C37fw1}$2z{a2nPe)R@WnzRSoNe&)&mt->dxhXbx;W1&m=QDLLpg%) zXWn^0zwhQkQoKI11Ud%;f7CkXxVg=4dmZ$(F7CfJRh}lu7Lwv4DKj0*kAr6SH)to- zM_?(=9MOYLeUo&amh2$4%`Oc8xpT^QB?4wAT&>V-;|RFDHrIn=D7fgt!b3Ge_9U?W zyY9QY5=f+NsUZ)bwK#142bclef0$mH3aH6hILS}Yj0=qO^f|Z@qelLeUd=0EEMhn8 zy5IlVp8Gz_5#&&JSRu8u@rxn1k>%*b2jvj!n7X5sAGc(^bob`K9!jZIVxB`7>E3%0 z7b#Ida@tuI0t727M_3o&y^-wdO%#q?4E%!?IWO1JD5T?mjz-&;&G1`FrOvh;`8{wD zK;E~mnNoZqnZj*qX4m)r-l~gBuT%RoaykmUbSA;KMp?VTtmTqzRsqDRkIl1R@DzAO zjaq=D^yc+1DLhFc?AIRDcRa41_WC07Y1i)msLP8{V6Dsot-LomOG@<8FlwIK7I_^F z$*-eiWuhO--h)R^<2@@-R)tKsq7t5M(j@p4aFDL%NN#|V@UWGB60=B?*aiWluFrTq zRrdSrOaGMPrwqBaX-(Au(N4bROfRyp6*?YJ6q2xzXdR$zq1K1UajZM%X)>+6E7zjtmR&z($0DT#3E~%pg@7MXH-GwsEdhIdgF{;E=$B6O)S3U zeAg}>*=Of(@)gYO_7D_+U>QOL3+iPS4G1y>D*`*P>$)4ETV=L6=4RXyIf?58cRD?n z((v5r%(B;$-@(m6NFtUa^u!r(HgDsV<5%jE*krxt>a$9}UlRBME@R?ir;I|oKfj{} zUHC76pxVmhap}SKr4yt)e05ONrZv$HE)&67NH+$LT3VS#kEapuTA= z4C(7u4lH4eINr$^Ta0uxcoItWRzRcTltxquE$}|M43|=^`jSSRuH3mzRl9q_v4)v^ zlsrs~1H5JF*t&<~CB$4qcf&lSYA*xj11IcRp)}{!lBw-8Mk{aGZ!vD$;c@n&kO{Jrqb(TxYRNAL{Ho$JpK)8$7|N8qGd3IpyJCwIzgx;CP z--Gr;&&@dmB`taG76Ovuru+Icr_1O;{)AV>MFQb0>O8cqZXf%9HzbSblrEZL<>=M5 zVV-c#<-T>tpXIYOklMSkx_gh_Yt&RsYdp-TMo4EtX068|#rIN92aqHRQ41$4R|I-I z%gb)5{gKeEk22KBx}wT@E6xsd!Nl{xAOR>4CE5ynHZ>xNl*U(EoBU%-9l=XTSmJr0 zxRg|Oepc6IQ_Fmm_QEBbYRs=U4?8pj(oqXyYpdq^XQ!D!9T}kC6Jy1>GV|Vw(-x;< z+>>+FZhBqm%nDD042Al=Tx4Z0Q9~%2kB#MDbw|`FBofH20W7$7+HQQr4HSe08@?c6 z%)JiI;eMTp5w*;nM!~K zrBmmjFd~cpoH%0m%`H(Pfw!o-OYxe=l_`|aNwYGw2LXR*8i{XDaS2=7wO(cCGoBy6 z2cHRWDol2&c?ufYL8D_54IXb31bYS-Tq}BJvCqs%Sw?=*f`)e`1YY(@#;Z)mf9dax z2Y0Lg0#wq?6xB;9-oj10LnvN?(pv~}x8X^S2RZNZ%iA1x9#azQsQ65wR8Kz33fyY; zCwS;@<6i}7X>;NDozW)f4d{jMGrRQ7V;mFrLT@iX7QT=9&Fn_1c})!T7q+eGMmU-$V?(@bCJ?XG~yx zlY#QpY^ZO+1^)a2OG1UR@MKtki6Fl%&7|Zk z^(=Km>VUx+9s}?#ic^T^8Wq172JiZ5-h!!7^dPI&!DK`63+kK$Sud7~`uCMmmoE!F z=~Xo%nyFsew}zjTu~@A=4ac^=Bh6{c*5G;|kwJ?a-R0Qn9hZ^*zN~RuGC1Ew+t-Hb z3D<6|#lPtLucACC9g3y0d078?S;4K|n0eg0Tn-+V8T5YyWhi_8x1dZz)`P8HQu$?Q zq(D`>!{S)T)7lorpAg?_93Z}ane-p@#m8aw^QOx_L`cDcl#!X?gUk-z0JH%R;@E`U zrZ}@wybXRlrr&Xj1pEZ|QyUr}CDMDrzi2=kK&kFW+~zIdNlLRsZP@kIek6* zbo*rTL*1TBpd1dGfzGh9<%12wWZV+b=hg|YXD7(71TR8*Gk-e6Knu|RIdHs8wEk!& zNI+maR!0>`7ERYoTw>zGFJSWEJ%u&4U+RQs)^r(|)9iA8rRk3%-%Mg3UZ8rn-JfuV zpMrNeN#COL5GIY^yLNuEK*!ezssg{#u=bJ>kOpd#Z0Z$BNlyY1O#{8OT#&0aaM1O( z1YN}se*o6EyvVJV^C{4_cwr1}3%ARUS<@&@_4}jA*RnK;L&4uC7Uw->r@M#W zT!^L4?5(1)5CFoo;+k`9pyyM?ybC6tcADH|Jx!ogXm4@eoC@20;YLm}81>{Ob#Fqv zevLh)9W^PY0&-JBd@^Jj)`H+=jcVN-B{RTNXuMYxR7twu`6qf}O+3l9#AhOHf2VhS ziuF&}B@X2Mq@%{5{q64}wc#7?th%xfmQ|ACZTS^YJg^(PP6=j=xn<`;g5UX9oBoF3 zM|0wDfx>^ES)gP<{BYwQxNoS6N$~K5v9USo`%ZM@bOU4W9jBJV7?D$-7T;)S-?|%s z9H`m46A(ha%*@NnoTu^102m~AaHcFBDR9(j3d^a6PEh)*#L-tYB>$>7TA&K*UzjNi ztg0jDx#lkzZZB+nPkVE~zMe?ZMjayi^MwwbITJ8PJWEpSM77^Be6v%Kp%r%;r-gd4%U~&SjebjnhGlSx7QZ#jvGMC&HP)AEeA#SZ7 zCr@>UR1$GBtg%Ly*o9yPxY5@w?%h*=#L-r)e)Nm9{UEAX_ZjDrnlKvaRs@{i@?GF~%X!xVd4fs6drsxsjbZ=e9ETaTS?e$TT% z)68ySm+YI}efKMsRu12qx{Q9^=bcg-MrHQ zj@dKK9CJ))PxRE>>x1vam~lBCMjVx}5jZJ^^XL`FPh_v=6khTF{`Kt@(>pM8wCp|u zFw7vG^^V6`XBtww6kz;_uVd}T^^dk{vOwNqiA7*q|14lnkUSbeu+X^20eFyy8zT_R zid8|2;iTL(`aFS)D6{4flXvlbIHl}=R1Aot-*Q>AX-t3k^aMZS;ON~iLPcv;ov_Vs zm=e2fo3G%5Mvn*opFumMI0Au~ z9pKaV(k*Jys!Dl7*QS^PtyetrCFPhN&-{;DC+oQk=phAZb0A&IP0u1t^|@h^_()P`w7i61tilwu zFK)NmetQ*WRo>QS$f~R4;6)Pwil>%c$AshkH~s-EG*&V_vDx5=3MJSUY7a#ii*w)^ z)XO|zI{f5kGyN9A>Sgr#m|^~t6NE_?LykRYfA24?4371wg_y|%K^*_Z{u-+X?}fyT zITe&3L`oVGu9$W-xSM3GwiLn?NcMIn^n?TpE=d6=H@7u7)z^>)^{CD&q2;_BWdHbf zYBh^7{~1DwQQ|5$4BC@#aJVW8F^+|QiP{hOa+jrZhs^OI^JWe0j5u)CP~JE$?Vn|+ zBttF$XXGdz7P1%mzxPKEgtt7W6C&V#6iDKYD&=mW*+ z3rg-;l>O)_Geon5{xsI&xxv`3%S$;vkcVdhe@D@6{))?e{&Kam_Y|W}n#Ht_ zZobtUKmSF#_%2nWD^htQee$4?<5BBPW{wlUMj)GV121uR&vIH?Gj12d#eV&0}U1?G@y!1sgju? zvP$`cq1#PSb`O&qEjyIs2;!E%L%yOnGmt~mI4_40w5pFY|FrrB7?0tQLEu#Wc7}V` zD|6w&8LmINj@ z#%2u>;N1HD>@}D}wsO;1fdbu2QoTNzw?%a&JcU}ZpDqfg<384li)(AuccqZ11oJ+?+}HG`tP@mqrw-V zPV$UUyb>;+yCuR2mVz+Sjzh&_TP5F6Kf#84LLkxS95a70sBlyBiaU{a)dTTwV5iuR z2lNnBZ^^_?x87Lpc{pyReVs1$(FIFDEdUM}`cB10iMh=W@_9y*xSju5yGGL{GD7l} z64gzg=(Lf-RQ!=efZUpYmkEc;p>zYo%fF7DrjGq5oTbsFH!6m+fKgH5`-EF!uA>dd ze|vUL{8E^<+_H()g1Oiljtw*OMB zi<#A3$nv)Klea%NCJ!3ampaPU?PB|dN0-i=IkT31edPmSGcVP4gk3{--$=+-1w~3p znqo>X0dnvwJ~nrZ8FiLj%|gamYZlJ#{QbsGBBbyiGr&hMNm!)>Rq-?FE?iei*oUk> zM|RdDn<%n-Vbh6H4YI3rFvcKR;0m`NvI3?bWP9MJKms)GQcJr=o zaoPb8j}QN4W7T+m>nQN#S1lr*KK0_FeDb{E9rum>-lB2KlML^&dREW0Ehr)-g+As$ zy;jMacs~1*pBwz=&KMTrjeT&+z_3|v2Zc>3_ORCQmK+aia1dBlsvM!@GPP)Gb`Uy@q^H{6q zeL`bFG99bcfa8x&T9tk>_kDqj_W*xLef!>co&X5H$l+-w(fp$QW^^l*Wk{ zFr_j$`yggq_k-|4H96_;d_q5~(Vo+qQ9U@+bCRs+TB*yB7ZJ?RiHkx6PXejV$%&gR zMEYQoCOzLJ58u~H-zN+WO;H7XDuw4d?AeLZbGT4?%x0M@6BR2hH(bBqed4Tn#tQcvX8Uo|L|FQ5@fo8pid<$>i^2+t2n zQ{>?*q@+Q-9Vat@c!=){0JUH#?M~aW z*@snfib~3%)zK0AMP`8iv_69T-i&T?nFKTD*A#Zedpw$(k%^aq=)vfgJ{PLh8ahSW z$jR+VqKYX5AP9l5%5k^s#u8dS8mR}Jqk7)gp<(OOP z@K&L7nP5Y>=p7R+l`r&k>gQXkp4QMwp9{b3Cet)|vT2Zx)bcjS2 zOaq`6EZSQf9Om4W@=|?5arzQZiNtn2D8(s=C%$8}r8QHQG+O5Eh8NT7j;J~>mJ5G) zhfZ{V-X^0s#%_420Me?k2x z;So`@3|59XPf+}iYEnxMqkzrFYWhY6;VG)=Q(Sj7FxRX7P1I6w7S7qXCKjp;Tz2pduK z*aOgoyjIxd!K?N9H7p51i3y}5R}8^t<>J1$(?%#5YJUFe#h|jTK@;<=;c6|}fFQkZ zC&te^LlX{4y#4X9guXUWCFK)oa1W%i52bI&u9lw5>?jKmxmzWl1a8W^jGTiX7jul% zemX0JE5^sN(^7lfA2k#6;;rI|cdrn_CjYS)NU5V(2TV-$&0kU(tDhqsp;!7v z&tb5sRmf?4wYmXEz7x1RT)j`2t~yvf)P^|Je>sKDMV+Mm#a+#x${*I^C6t|{;R~zf zrG4dj`PI;K(2^BH(0*)3+`*gRxpYomtf!a0NAMtcqZ4`y1@84t0{swt#f96?bZ@zq zJp>*PmS}xmGnI8=*(yCZ7mLz{C**O&p=3#uFc)oCKSfNFK=3&#W5Der*}#a{25#LX ze0*fQ{pElDeoiYt!&(mG&xT)Hy@@q>)v%b|B^mEAJx0lh^Z*cNSJ)npOS;Z&x z$CVpj#4~sIRP~Xxh4@Jz6kUK&ZP0}!<)%$zDDycF+3-~UfHuY-AM3(#x*31Vwdli! z3236_rMn}#zjlGSmw1_+Vj7%9D>4PUrL?Cl0&+;;R~v5vDF%6MmrkL|Xt!zN`@$Qr zE3|Km?o7qCR?Y^1ae)U30`oGnAPnqP*5i8>{Bw+JkTVp!*2s>TaS_eIjX6>*?P!l&lfR;JQ7*A|&{bkbB8? zN*NMDp`lkIy*{iO;6(y|3C0tXNgLC9+i#jf=1whtA4iDbi%#W^Np;qLX!NZn_l~CoAk@Cn$;!P{!Ds?b#A`hoPYLo(EK0$;pU=sWxn1x zhEuxMpA7l1uq1qX>nP@v=fw}Z-&^ovp?U0y`dS+#J?J_Nm{9{o3E0Scs5%cq%lXQw zy#ha0l0#PQMqprliWC0yS4+=&-;T8H7LoRR?UXc{5Gj}a$y2@a8)aEi{WmH^p8vgg zephe;0{7w~q@~+1*2#~LTM+p0oQe08>_tM3dwP8doZN33W!2wrCyb30Fvj?@Oo9t2 zE7r_U5AhS9s#LdLHY(mMZ@{^3 zEN)d8h27WOR~>P})Um z!#~RFgX+pPacX4@xgJa3>TV{!D!K{2((^`JhiHurb;Dk ztpB%YAnqSMvu~bQW2!qcEq9(2+g+3Br6Ky)C8etNK^P#PghfId|pZ_9@=>#SgFEZCZ7;``QSc%|lpzm5U^`Mgg6RDH8`xL4Oa zYloMNeZXwBh8Va!CHIt0<*TS|ab$_k9~#FMO(jtZwa%yw!*@U8$elIEt;C@@vL8FJ zIsP5il{$oCw;Cmc&rvjK`!4Yk6?X1H)JcMeQlii#6rF4`hgy$lkurxgTK_9j9bDa+ ze@3pzvPMUmT$2`lkzZ`mefXC0avmu?Nhl{-jzp^E3WPv`0D+#}s|4U!oYRe>Ng_+R z$r1h1`=*NMPAP4RnBA{{?hNcTofPBgd1d2rd zJCqGZ>5m0vl#>D$wOmH!DR0T}`@`N1&e!KY0uaseXu$A%g`a@|J~jK4_QDIUE7d>X>=Sm;Y1FAY; zjE>+=;K?P~VJhgF3xuQtLXMPU6w|HZ4^6KgE1&qA#gKVQf+UZ0ZGJCB z2F6~$Cxap15+5nFq{cbjJP>P&kpQkZlU(Ew~8`}|{*EuLy?toc{-P))ve z2Dv_fKg!$*;<#Z1o-@xD>ACNf#{VYaQkNTu5v^pF;*Va`(=(nW zC_2e>jRElJEnMYZDy-`FYQFVBy}0my8>=9L!natNK%cKR{b8%CtsGaYNf>Qoi9OFE zwH}oPA|!3+V9_v$#~OGN-i6-IFHSz>A!Mq8j2nYrmcvh}pF;%G`P^@A zBA2~Wkw%PhumV;cKsLk<3D@QizbWeO*SCcKSewfCPEw&V*5fq=&a70(nMG7?7FALK zx1Y#BGlmhm!EvxJ*ku*#dj|$_ng2{JFIa_Anq5l~uM8fg%Q?vj>{;Wf z!jyUm^%FEwf5M$pQ8DGTrtboFnusDH;GtH!QN`_)oj1EA3zS@n2ze z3A+Mom{j)WBD9xi5A`C510@YKVP*}Xuo0Q!Zo=uM{_(X?_QLxmOm5&)OS}3%9Oaq1 z%X`^-G}RKR+%)n>{fQIRlIZE7reiapwL_UQCBgllU^^>V2(1} z5Wg^Iv8G&TB8)ljrY1OJo1C=$pd{3DH#-N9cJw-_{q9@^z%Ug+P7miqN?C;!6mU0V@pAW?fT3L3(*hf=@E5`QXVbJVn{Pw4Mk?RBxav>N z-Sg<`cKs|lu{zG2NVjG%MM>$h2wEdLbk~0R%vRzbbSCgj+7f*$XbTlTK{(y@ZYMrj zlcyI*`CIoizn-o~R!btprhD7gmbWXb7M1$91oxNfLpCB)>n3EZny7z#)K)j+Jt-Cu zs#seVTiWZ=h!<<#FK!o5xw&@ZF$o~<=2`PAWv%upbAU>{$(0=57jDXuxp!(uKgr~I ze|AhkaJblfpR<$Y`KPhu4;!a5@6PYf*8Ze2inUh@G=zV}YqI!xI11mD+>xD=k9xTE z-r}Uoh#cp?jh8IgFCo@KoqXL-BuhjnBPTI7xA8QA?qTSrJQBQCQe z7o~l55oxhgi5YthLS?9TMBICm7D_`0%Odocqln>=85?_TAJ9EW$^}P7r$Qex&^-u} zJwK)}PUZ1*bcs8ds}EVhO5t}$zSe+Z9CVx{Q!o3gzYRUT{|UwWoZE1GWc{$d(LZRe z3)|ZrBu{&4+2_JU1J-wGug)YniP|YwV~mRD^SPXDP|2`$V>7y8;W$AOg-e6mZN1Pe zmU;>(>;m2ZK+lH86M&s|=%m0JibP36HJ;{GSU@T)8T&@|CS^E{>|IW#>vkXnLb`;O zgm$bjJCR2l@LWk{zp}(~d9ow-cdiHg>Ij6<7<<1HIMeAmCPgV*!q8`I!Qw-L-e`_#;4EF7WB$|hsbijGN zJkcO3LpG2Os1wI`8Sl*w%29?w8%&V{%eYlr)$+7AGU)T|oMn5L2jPci2P-x19Q?LB zT%r3(W^;San_QE{4~-Dv3(1>xMTSplQI|4$wX@W)B%2DfEf-;jPT}?C(~3>{u3#Gg zGd6sDobCrh`p+g}9EmuL>z97BOuxLnTv3P@sZHnSX0x=Bdr3hq;(cUHe`{}_Q_YcC z^W|cL`dizLH-5kDfOfTd=flwkBvv&gs>jDBzdW7Uk_+OP>ZA_I>kT*tc(uYN0NFy+*t^K=( zBOk19hnb?g9?I8=rI)uOg+1N_&Vc40u1WR#-MSH0S_A-Aqo_-I3PX(q=b}y|C+8*{ z$2q;?Hgh+E2p3acm0&pgF$7kIcJ4Nnmex=iD^WBz9oKoEWTmTFU&oW7QjEKu&Bcxh z%Q-K;q=1;vsXexg5om+L6!+*-`k0>JV7@q|XHk0e)X=N77n_s@2aXnRuHo2FxGaC~ zZ(3%S4%o8lp{-3$rBrT`jF&goQ+mHW=Lb}eMK208`!MdKGhQU zJj}~D{v~kVcR^wO8a7|e(4Dn-cZ?aqaa}fjKDdRzGLWA2XGXI@By;ItkF8o4iGM4`*;)>AN zn=@i!wceMR6xfQN9XPjgjU)eb3F+h!({=EtzCqbc3h{2=EylFdWF7Ky9wf_*4dknp zQEe@a0?h2@*_?k4aGz^|`#X`G}%BBIzaE@MQ zQ!g1rN}=QgObsbbd}_JSU3BF3kuAGL+sQ>WM{v5gV9S5|!6MtH6Y(kp_1*9yJZ}nf zZC-87=VtTWAqKR;2IB(hENts^+DWcga5L{^Dr#e7tZPGb$rRXnb1;n!cxPaG3ccnW zTxd&`K3&d%F1ioDC8y}~AYwsF3VSDW7P0Ys&6{&*yW@4mv)=Gog?On3N=V6xWBa`w z=?Hlv zZo2NWZu<`_{)eoAJuom)97+4D{1Of#zjZl~^bo@9xzoI+2^Uu!r_De}PyE-PxLps->o} z2rY~BOH=&AckNo6#39R9x>8sPoMrWYD4ts-x+$>DCsZO|IngC3egWN^Ko1&(59Nuv zCl#t&V*IdZjO)r+)+Ufp-(4OFauu^+!CS;)8pxq>ei8^5Ykc=5OddOx+;>X{s4>3r zL6J+VHC-VMu-^O3z*Tr3S8O24B6tI)B!rZJ2O5l%H0|F!^xr`oSw5TCYl}fB?jjmH z%?KPEAys;)YwcEG>Az89vhNqC4wyP?-8Yt_5;ybZpv62=L(Mv5=i8a~qW3Xx#k{I3 zF3`UNNB+3&S=<*EMSp57SQW9_c|Fun$5A9y%#_fS<;BC7GLBr?k47Fky~JOiG%bm@|l zQ1Edlp)r_Q>{3GM?_BwgTI^no+N*~H@%_gs9l7NId2O&SFLC;Dq|L+EBK|?{S-u%^ zTR@uOe_62TEGW4gF-F9XF9OnW+AuB!+MadK@K;+xgae#k<@!I1fKKP9F>@N9JF<=$>=ZcWaM-dPh%HY20TkzNbqW13+Q5FYpxB{@t)GN z?s~eBCg8V)At3O;!Cy}eBKVrqs^ffv(|>i)oti~uy3Lk}=ZUx1$~pwn)!b;7H`l$d zM(+($a^hUDQ)?VJ-`wKM^qsSEuh`C~77}V2^wH#3(QTd)W3jQ;nOj6}yt`_+-el6s z@fni0jh0b%_&UwQZKpLD!NQpN54O14Pl$S6BOF8`f|tG*DL?qOWt^e4FBCw(ssEwh z|FsIblF3|9V_;=ypLt*h0h$4dj1vMH6K%u)s%mclxJR+%Bn5F6D|lqDV*FrW5sV_? znwBt(8(R7~39s7zj?OMu8ES|)TrCNagtOs|7?x`zFrt(yTAe9!Nw;&!RAcZU4rZ94 zus-k{&8OpfcG1ng-E47o{#Nn$R4))Cwp*w7(;V+gaG2Wid+M@|E9Xo1;Li>RpIRrO-I zgJVvCTy>Y@_lJVW{ZoDM+aSgde;2Dm^rQt=BF%0OY5b8pyT`e{X6m}*Hu~CjPqE`f zR+mC(&t}K>nLIenU)vW)f}|nE*&@e1`M#$~smyhQC+@yC1VTVVCsM*ixZf?{8YS&h zk7$6sU6vnE%(F?dz5xGKdhhU0W^pBAP-flF5iIPhO-A9ic%t}}>PkBC+XIn~5e zdJr%@-c%}(kJoeGQy3bQhD+;ztxL?n3$z66@0$Bj{q6l`9Bks{=Xsxt)8*M+8qSqr z+&-q+gNueeR!*LkHkkaNl(xD?Pwqykk8$bgZR@W-(@hcjVjLVrnen!Yn&0$?!nr=e zTtlSP^p*)PHf}fK=IzZzDloKh@qn`kD(+6(8^+gC$S~DZV5pPLeoR=jMOsiWI-JQm z0nB=HN1`n)IL@iZ%YxQ~*3?C$h6=wkYmWc?>{|xl%%3gdb_%NWeCy)sdQf##*W0DK4RH#4G^?^0@Gqr5h+# z%FiJuv#e>zbVq{%;}#R3!Py?8^|2g#%hc6$b)WaE#>C>kEKmk~`!7cmWb|Ln@|`B% zqWXae6f&}bVlwXODf`E@f5Cz8R0fOvDf)+f$vi`z8Q!`_`h~AH1RHT*g8Lfh-cnyR zSc`tFw4Q9dxJEJ;h0ZF~yuQ>JGSIF^p?u~jnVR@kx3lHMvBIF?_CD-a22yy7%-*T% zXSj499r@T=n`vY(s-woCSG?~=ZMq7cV0PfKT)sudBYK2%AQYkNcU4}>r?z{LqWWmG z^NT$31AgK+t>zUU0my(r<>7S3tZE4J&1MJ?y+?idx#lK7^EHv&^y|0&1`RYN}Ubr0e4ZEu{$Cm!RV2MR!g-cm*R<#2jau(9PNV3qgKwJ{jfS$WiD7l zMbT*5Fk|j#3%xV}2~YSA^fs!b$@BuQUOUrTlEm|4$^KWoY$aS`^iG&E%!|Guf=cHB zv0tw}AsZwqH`6vjL>Kvnsjnf}jK!9Ie*W^e@Y&HjNKutxi@g}&H0}Ix3P@*)yUF(N8wOjcApyyx!W1 z!d%fY>h(lNwO22S92juz^@$erh0X3vTEq&2ORsLc*NPo8n3cgo8M1+T2|k^@AEJNG z`JI2qvS8)ni;5$1U6Pd*Q)ujFe?ljhwkO3e79aSn)Yva*c5x?}Vf4KBK43^)Bko`s zs4egUwT1s_^N>a*>%x_-bsKo=YxQ{u`zy*iKqY7ty{3^r$Jw)YNx<|rZ%YW&(Ia>P zfo^A&H?BdCa>=w4!~xwiiR&+$)_!fW)WQ^JF}So}ItAmWh|x>%u7}x*00S#wZ0|ky z&+bb?Ol*89y)S! z%jx@)>#bl_sf{ml$;ihrO=0aDF-Xl)xf*C-`zV?9`Cm+wsPocNpgdJ?ub-cr z`xRTWkCZ7Zn-I2kYdNIky(4>mQ6nBN04GgNp(m$xXX(*(41ijQBJVRZH* zP7HBhtPCkkW&prUYGF#wyOFV;+bR|M1J10|&D2=proFPO!e5oGUS>dQOyj1{2a=%g zU)FOPmllhz;7+N~J2oA&*f&%E|&xKuqDFn-||al1>4j z$Fm`B4IaT8FN6Y+;iz9ww7{z za5vjBhDN5$E;^U93g6ruD;WDrWYlRKy0o3U3$$KU=IJ0?s8=2N(f%b-B&TP5Ua6To zvBD+;Nz-UqULIy~a>w!@xjOG)yxt(ZsukUWw7Dr+?$unX-)(Cv0AK>l#*tKM7NaVw zZ6X;nTpXx65{d_2|C1Z6e9+x*NND&dUlQN}pX1QQ%k4zz4A8#P57s#i8Obee&C~8E z!057raIFm|XGR*~*E+5r&gcEYP91Lm4xxOLyWu=^n+eg>M$4730I%74{ne`s^vxp< zxTAbTjI%R{8ENy?B4s9hg2r=E291!f0d2$7f7*tkr;yUg^^?p^R@^H))enTOw}Fjo zNuWo1r&aLmPp#{}27fAIHD`?3AU|)s*1s_saJsrLoH21`?U|2yoNZTom}bCW*-|;) z1#ROm#tB(yd>wG!!FjA8Qe+;g^0nsCNhPQ7vqR;>{@l*-?i&M(X88UUrNKT;z>;h@ z05|z~Xb8xLV+M{l`WjFXQoe5cg7&N=$fAKwS zmLpq)=IiQ@#0|y|&m}69u`~qv9wMJk2Vye?KB%rH%l}3?WB|=Be(5k`=LuHtnXnQ> zjjHYO*VeZtFU?5+qYV3Nm z-Mc^{I=!B#t;RJ<1Q4|bAQ$c4(7vt@e2B$vLQss%Q zbOsaB99f)3e_uYWVNRbo(bp^ZkELObeDbS+gCKkw4u<<^a< z4AKT8#UZXs{P+v-Ckyt4v;4KJ^b+5`u9D^3f#qIrS(SV5yLbPXC4U42vw4;YkuwL3 zb=IPzw{r(p-V6N>4bCrBN(vWDFK5p(rIe#$gqrtr5XS-7AA!XhGLj0BDTlzBgoREw zNj)l6mkU4`6l)*hTSF(>zdbC3oS{WH>BWK-@M*7?q6gbt(p@gCD%=a>A9pVaQJr$X zPM}+u-@Xt`oXB(b8~>BQutF0}!b=>HEuIWu~H%%)zUZ%qd0Zt}cv zV`mqj^fN*fZBj{u8iB88={V;VwI5=g+~76wblok71`Hsd36ob z&3Z)EJ*C_J2FVMk@8#r;p2B?!sPD#>UuV`E) z*dGO#)9B@ST?{#`OBws6uu@$&Jg6bi^a+FG?b~SWV0Jd9AzKPz<<87wjv|R@@F_q4A0$hOu7x$=M&i^BR z`-d_Hk03u^WxT_|tr39KeU6OFZ_=iOx>6t%&hV{6(W{=9%XCR0{#afsPdjbB>yE^F zRjZnt2Ix)Z!L0}FXdKiZ-&I#=m%yC-a6c^54INlr9UQ(k9oby#RNA=rsyvOPL3f<0 zJXIkv?iBun;5S{z7CCehxfL4v>$I{vNF>Zd^>VDFVrG5(a8r2fe(x+}`L$H;_!aA; z8kjl8Dz?IH&BcZs*t|Z{yiuhV7^_?3tV`C<>h?|q{dABwaW*A%p&LQ5RcjJEXkCD3 zhTMBOK@<}@$nX~@sH}}zZ{VlwEY)g_zS?vWb%g_wd_)OxE1wY5Qu)b$61Lr-ffvGK zME5%^&)US;^m$GyVTHxhC$7?xYu|SiI(<1;FF8q~(73UC9Hd8Ky@~-aR<38Z(Ljp! zjohAHM84ZBAYB_LHpn1YKpyB+{YPX7bS(aJmh-#slKy9n=Oo0$+vl^xQE_uR=84fj z3WUr7!V+cMW3lC*Ollxo{Lge(&oWaRSXRnypM*9_?`h?tk_kqnai!N^$Znw%R*RxS zmlwt7uWz<=;Kk7=YEqq1H-%#aqZITB-S{CRj<4@F{9Orw;3O9}Uc5f)qPiA094Nkd zgY1%x*IU!gx=!vvkGHwu9uu>BW!h~Vj&Eq&3u{gs1(I!huoCoo{kJqL=t8v~AAK&e zg8XRAuP#RpFjlU^rU&1={ag!uUOn@$Txk0Vs11QFXaW&-*`0wwwuGrZjsM6>woVauTat2oaS%yfWa zxnnigLtkRpbjy&9jGXO#Y6@hR|4>g~I8O=EcxO2Pi7Dn@hZ_#+B$buv$nb_bpvd=6 z{$t8K9(c)JgLyWo1=@b%op*GNbZJO`p|+@W22SZT|0j|QZpXvNs6sLRM3Z^@0#C$` zFbnAz4tGmbXb<>IYngR_uW~3x!5cW4CmattHl6Zp!*gkR;NEm zFc}C{I88P!Zxbsivd-rnokkIY^JAGjP94WT29q7shsvvec?u3H6&E@No`^#RU%g;! zvc(u4`23lv1Ou>F!efd}0mtzm{-;4DkM>-MZ?nyb0Cc)6GGTIPdcs-$NBr}etA@QK z62Q;T&o%#4m>jMj?mx?NciO5Hy9IjUVRv{$M92IHe8Scnb=o&q$r%l|e$)5_-74ii znPD?yYiViv9C-3`7P!*{KC_MA8n+V8AkS-VybkX}C(ykbR6hp#liUpiwa5Rw^~%9s zxNx>_*qVB2|Kr<={@ETM3D2?Y#!^u>s2zkWc}HkhcVAY)+qAbUV*Oy69h$A$Bk?ZAvr1>ZMiPCFZepf5{{u0!t}cG z*@kX0I6&4Ml@#N%J+8|>OwfUx8VQz9Wq@utuT#4+biBaQ=x}&pzv>(BaoSFUPfA{h zCXBg`Dedpn^@?QmJXET=b=)FS0YeJR|-$DD<6Bwrd? zzY&McOymBgU~Gs#`lz;5iWu~&6EV?ygY0wCFZ<<%bakSGph8ME2+Dvot&Nwjcol+l zYiu1r$oCSmuWX>1-p30@R*D*3LF3Ey2fxM0QQhudr+@s^zz&NC?LExr>z;cxgiHTy z=qzU*#`?S3njgPsHP!Bgv9{x@*F3Yx8n?y1vs09uLfXPU9OHo^xE-foNhs??) zxETiBiyzu#DB0r?xvi+|)Efw+hZYL_H@riHW8FIHPL-G@9s#SM_hb5+v$xP=q5T=~ z2#HL!-9_7@@Q;z>M1%kAm7*6S(C@LBEcG^)OMcC1-W< zS)as%AdrcZ`nVm1El8=xrPEkEeRzk|RXoxE6@n;U2v|oRt$6uU?>uy!P5kx~pI)SX zjq~CtY~$%Qdp(9&UeT}cMufip=O3iWVJgqVr(S+F_X?9NQp5H`iIG!qp!AcKjR2Pq$Q6FKe=ct^@yU2Oi zrlwE%NaH8{RVE1Y#IW^MMeAXHm7qx2p#c;}#HqE)`KqEr+SZ(ArRBU;39g&8R&S61 zJM*R?hhlhFV))#;FW!s)dsW=rNbatB(BhqR3ToGX4xm`y1BhoZA!kP+!$9`YgT9SB zbZ1mpxL^DXUph*%SQT9SkRlg1vwt0X9Y$GE#cGx2QF&Z9|3l9RE}Dh-!6%G=dof>$)IMG9) zi;QgWd42!SS)&apZ}CV;!q3gnnLYk`y~e_hYe7?3i|`Ad+wX>(ilUv5q4V7P*VRg~ zdf|;PLs3wIP!!+Gd}R@GYBk%7arOud@x z{nY(frT*T~k-t*kJ}E%zo2s#$4*t@YXGVUN*df=Q>BOL31mf3FKFg`iYP)dl&8_^_nXZF?vlBrUZ8-b7@A@?>=U>YgcOouH zGcv$h&b&|#Rk7O;@A5L|wf5*2W)aqI*~c-p}2Q1FUuNDAFfAMEHzz-eM^qR7tb(4jTZ_nSipC|Okw zZK|igQj5`4_?#R>6KBQ(y%!`_2RWh$L$AhH7Qb6giD`V zszCbpI@NOvw>^Pu$J^a<*ja@GD;I>gnQzROe$}__5&2^)6SN^2hl-sUW)&B%>+ONz$S+HQJ*+ufFcHXH=w2uN}Y! zO4Z8^3%~F6+Pmo8%FM;EIqSimkkFR48*Xycu5@$A^=Hi`N@Nb9>Ref>yf~#u`Pj~$ z*Jl5vH^KH!Jeg_u6yxIM%v{ytn268y4fl%q$;~nA(C;FLv-+38irnG#wpjWKf43UQxIwTrg?46X z4UE^ZwZ7xd!2 ztEFr^Kg!sFU#QJV3;8QIh$DRyS1Lp3B9UKIs>^XBOmt)?P9GApVmkPG_?kP(hz4;G zVz>~wjT*P!4c}L6lEb|37(8^PF)+~~s65s~Ubw|QH7?Q_DGtdmsJMaD*l!ZN}Qq$6z6GhTgqv-6FsNc_j@5B&N7}5*q+X>#?C?) zy7%+^rnlBe)`UP1`(9UB z9nxy^c~9H zwD`o_Og+odOaC{2!VcfV70s$QTUxEbEJU~YxFvr!*XCU6Se$#op6AmU3>{9i&+o}2 zCp>RhLE`=Bq)Jh%F(LKl|^$?+|Dfhq#RYj(U~ zw7%HdbFYTL>Y%PXC2w;kY&(DB-C2Q!PX}!tSz-Z+W>TbrXDpDt0Uu;@ub*SW9>sCJ zk2>zQOF<}-ABf9iC{1@dg}29ohvBiIKV)W?Ee2qt^QeM=#; zxvj(Immb|Mi@fkYt&E`X0rqPwo8#6^Ww|z{A=t(H%z9>bmdo?^s!syhvb)E#TFPZ# zl^0u$MzX4^x(b}>6dN4|J=}dvR(y@CW@P%v^T_x@xJ${@;ez!0)Xv+N7xc}s7zxW{ z<==%%f}A~vPEHQnx?9l;lK%CZtF7Z>Tqnfhwp$}zn1Z`Sw|OhMuQO# zWfG;hEYL6TU_Kmj{E}&N9@S1(S>j>M{lz0n21XaYkD!Rf;51m`y&P+(`#hXyCP?#r zcgGrT%qU*7~zMbr4s09qKb zd#oW(DjR(e>rp{sw79Dlt?!)gUd7_1Q?% zMRNx1d6M4;Gp!grt8g81@P*I(F$dfc@?<@+pP(9(Q;&4xyS(PajZ=H?2L>=nkPHe- zcJo(hn)&eW^wyf~?CXv8c+{gp%M06JZRfx0N(P1?N0o)m`zs24={YN_ZXinO*#<)c z{%p_L;{ve|xt^Yi8sb|;z8cp(ed8B#5bO2>#O>x--6*|gwlpoRRf~AHo|C7_ZA95GPmG# zLc2Tf0;2DRG?Y<3(1zf=DcfqH_D&%5K6l2vtPYpls)0)^5a>#F8GKEl<)M@QR+kMY z9QIrtNex&sy%u#BeZZVMpLbKzRuh@}WaZYw&2hVN7P~)JaJ#+6%xLd@I;OwtKkF-3 zU=OFf_xF3gCg$*5&)((J<6aR{g)ZGkLn?dM&4dBptIC~Ucofd7WmcT&)V93EFTz$v zRi(T(^uejA_|&5DT%KZ|ue-)PPgcIe>wj#mZwZ@O;SxyR6GUbc;kCkx?M47w{_<$I z6_#0?#>PrW;$)wM$dp7kZsBQ@K70CiiX(h&uJ)rQ0Z4+pBjEbW-JUCPJyycP`0LLO zJ6^x_5r0CeRyc;^0#p05=Od$s+llm2rg%cJH7WQ~>R z%u~!Pin??J9%(QixA$b5Tg1F)T{1_LHBinwtsal!%zVVfqw7ovPgtWixw;+YG>sHF zLdl{CPYCiuZ>oNhBZ8XhRRg+bt)cYpC*bkGZ!G@yYt;xFBi2;j)XNlzF3wP*NK^Vg zKyqo=ptd|88Z+N(yL^{XVmzZ9^$t9)mudF-CB|=I4}_Fs!|$_;E0ii`7a7yIZ~!*| zKCe9OT1vKIkMCbU)^YQB=r`OQi>~qad1I^hCHS5Ff_bafc5BfT0o8>C9VIqXXL1|gY#kHMKk-6%3V9*o$m zF@OcBPr7x9waIghdJ{+mpp#ET>Z*wRmP0<{^`{;hH)_3-x;urr?U8kLcRE6SrTm1C zRwa-lu-0oD>`bk@V_QX=F5HP6p2R*Q! zg!5;vMNzJ_eiQ$U2H%PfM2`pGk>mi(%hx1|5~X>{0!XR#MWs&B z^6RQ%vGrcB`rE%N4%UG=V~FNw<_%xd=u4Ue#wVZ6epzbEh>>crr_F>SjfSXsb`!JF zS(Nn_ig6mO+tS7WC&_<*!C6(cRBOG>3@!z+Wz4B@N4YH zP8dI~G`0j~_`aO7h95sFYuU;QzTRns#jOf++cC;E3r~`?_q6VQ-wGoWRHgXyg(G&I z!&go#F_IvSktK0dRyN65?(~r!8+x;|dZPNj&4cE(OtDlp2R6^*X>Sy0=%RZl8%#OXF3A6}R zbl+desIgij?0TQ~OJ*Z6iJD`{;V{p#JUe8w(ktJ2dp91&?P0D&&b6McMj>rtBw`B9 zucO0!Z)drYrS@Ed*IsVI7#z91yF>l7Ea|6FTM!eE^w?%vj_Gf_gh8EvM;A?xYoeeM zbnlmF69_)#r%sD10{qGf;=Y20E=7w(tBFzPCaNP|a@XIsql{ivOHC8*!1nqiR-dY5B+%J(C* zU!F^M2PvTC`HnlJwjoHBjKL8_)e^J@qK8SvnAchFM0#OvF5cwcY`98u7xJya&gARU zLAFk8Y!9M;QwuTkCutYhU7%D8#h7#Hdwd!nNja!mRSG{J36Um1<9pP%&`AOkUny$b z|K9(T$qnRVX_7=3QJ(@Yn3PPwsZ5}@uDbc0xN0DE->lUoGDV6U<$CKm3S=p4_oEnN zuNP6aJrCEC`*hIe04#*L`d^B!U6+NB8m%>NQ`4=TO_?{wYcjQ)V~z2o@ryA%V~xe8 zL(Z+2AM8j5QIhp{DT5N1etPbk1H19{$f|#I5vX%?3Sw+$r|}FsDG-Flg9X#4G3E*p zRtqbVQ$L^q97^^Z(sM>$F+z*2n&-UalvwWecDGqhWDOVvjYI4-wW8sSgX$u75_&~D zm>N@Je5kAqqfhb*J;)LU^{y7>IsNtoQ&j>}tWMhoVu)5_`n9V*v$Ij6OFdb|UME=^&# z@=QCy)YNDNo}K?Lb@ftvBqm|aX7L_WhiDh>f!>4q%}3JYGJN`p*NselpL#L{2%}Bg zZ)~y7P<|}40Gj%TCSLYsIwBy6 zHT~;YU6H7xDAw=Sf%9)Jpdalmi!QCuK7Qa=kFtEXMn##GyiJ|h^;p8I9V+7xUTY>n)eIh1>?}6@DShqD@Oq}Nq-jjs>evy4=Bxo#bJ8_ zKZ6D%9C4+qD`0U3PY`dg>@sx=N)(D;I4=T_AF#GRf}2D7_A42E=O8dW28?_+G_dEq z88xlXHYh{+aY(}WLtu|zP^@=*zO41WE#Po897p4HG*utM@|Dd4(O~xV78*;Ne%utQ z!F2u6A1s_2h*GQfQNXD@`)})X&h{0x@@kOT_T>pZ4w~D2;?zh9|LV?48vV&PlhuSu zxDcI&#c8KEQEbO;+qOX@Jrp*a^UCqfw~&{(@{TearCd}JG$sv+WV!xbKPRkfHtQ3< zyTPy89{O3_L&FPt=sq-e6-Pr4e3fZ*pUnmDK8xqN;e+X+&<}1TVUNalSE$2MxUh?^ zMxNx&NQKnr-LwCF7EI^z7vu8FJEER#G(FZ=^yu_h8*4=M>%E#A zZtE~`=S7lcn=G%g1w5x&El%@4iI*DyAip{N6)GKT!t20+D~d zCVQr2FH7JGJ%88DY{81|N&h-z8M)#ihXV zN2OA=r*pH>#qS(RJJ76A>w|gFZisJQ6Pn1Hs&ZD)gP(^3N0Qod1q?>Kv0DoNScBd2 zzURAZ>p(BMHeBS>Q|2?@r_9%PXzy(O-aZ`mbsvM*FHodj{88>evChI)GBD^qp78hZ zL&0ikc;)dV{@=sEhr;CX$|b~vM&QSuRV5cixYRRBnsWNhQhGDj8k0@!sR4*Fb{o3? zyO(U({~nE1-7g4JKf+pnc; zZz3|kXi^%Dtkzkhw?&RzGFU1sj>nhzQ4agi4Jv4?wxt~&4Ued~KU?lw>sN&DVO+t1 zK0vc4PTKI*A^1u4*Qb}&2SNU5Faw<)${Mtz(TKVHPN)DZF@Z<5)RkS@G(c||y9!qH1*7{Pk7xV{kquWW4TuZI( z>7H+yAQczIX4G%Vb5hx7+&t3vL(V-_ZSBy&v>7uuFb%I?4N2XG>u!vNy~p_9XcR(ilZ-4@7DgxoY_|r+ldYV z$>j4^v>w#ea0jQcBFHVfd-Qb;aq-kXe|lpb#csNn3-IDwPrSm4z8C)T>`mEo9_i#Z zU*0YdS=T`d0A`Wmu|^s&JXyAZ&7pi-ER;_b_l>NxANh0q{}KiP-unCX!*~QY#}7_4 zrf9@lTNGKBzr=6!+Bzuo6*sl#N>7a8f$Ez90aW02?|i9j2POjQj*6E@w{s#cBAtJb zzj4Mam9VKd1hi?xCIoHt+OB@o%_#&mo?B6~$U|RgtJxdo{bkW|`MziUMCM;{-H zSnHeHs{X-P;f7uoUoHB)zivB(fi9puJTAa=M7ui{wa>nH+fai1Q9)-QuLU!8;DvE^ zdbceOXN-&k6Xyddd8c8ZM}g#aiC!?&c-M1(&P~ru-Q`7M@@|aMFx%mrpRA0F&(nm# zH0oz%KN6k5v2HKVyq$~#;sMijGTh=`QrhIcI>i*LO-$IEtgcFk z{}$<}_C~x>R4e&4CRdTLFfeUNTNcys=syNBisgv59# zTo7C5X{^-R*^0HVcz;h_TB&l_eXz^WgU2ujJmJXjnIKcCs4tF&CkX0W*A5B+mP9d8 zESaX~Bsi{>eYeh9XBff!$fK~~(JV0fKJiAn`uoI;MtPP)#<+IlbpRI_>0x`8YKNE4 z)CGneCv2p;ud#?(;&sXY7%6znVfydu=00XOaS4)A_jJX>UWgyOV&Fj+M?s=Ku6GoB zI+NAlIb*J`f3hRedK0+Lx~|y!!y}ofExSoN*qPbY*2n>KSy6;^kUZku@jAmgqR;0J zLJ+yseHxUjyO-o4pAnp)F@%DzY8BO+7Q};siRDl;@^|pb55j+u4@?1yuRHhS6r~E%*ItT)-n1oL_wAQO~Nb1 zVM8GD`0ox1@vYH5{_mTn|3BYcq`h-`_6a^_%d2=ZdNg5FII3WTA{*sY zX~iP`kfH?q6^!d$p%4|pQN}`v9Ewq}e$V&UCX87t@Xj|4KQwUfm=Bzw=%YVqU2YSo`lXhKNfGuP9}oA3!vH&a$Mde(ct1{DB60OrCgoi z;oxKR2Tu>&drbmovX6EPGcg81R+UF;CC`gh9sSlrwXeUW5tD(+L_1$75B>T@FKM2h zoL|-TJd8q0Q*`1He_^7gj0^(#anhIwL$mELn-*)Tj0PXN_tu>mK}U(!p5*DjZvFmX zEsKYh#6ggmapsP9ui}Q2C5%&T_+jjOPLE<0PS?0ST20#@piu*c%UkkiYwc+xO-hEV z9OAMN+V$Bs0aQH1N-lY|D00N;9GjmkqJ zw6zjisKtv%5@h=$*_ozN#4He5$%k4xlTy;O%s|yh?msqJh686&}V?@&^W`x4kMkk@JOC(%okcDL^8x zzqa=tMf39lZcX)z8L_2G^%cjE7wR$BDodbo6$zmvd?gfXudazUJTnUMpiUOm4?^~l zS8~J{eb-?YJIRoZ_qW1fW6LQ%Irf)l+f!QZi8tU=<7o)She-okRMR_R0DGz4>W zZbc7Q>^v+t(0i=zs*S!!$M#cht4ZBa@tN{7SS_uL!8Y)B#JYTO^}B|gB^%CBKOW7H z1^anouKiVnCu4TN!xHrYr}cT7=GwWl8Q$Jh?uK%0cG=0C_H8uyXI72Yiy5Mn$t*8@ z5pMQ}6x1}9lZhwAjax0k7@lYYOxI;PS^xX(^Zh;lKl(rVKk&%?e&5%9 z&DV9^*ZVq;4y6AebM-8`vD4noT~RMN@1?P=@Rc@j zdU~Cs>*cq%4(nE?R7go7&b@-F#Sz9BWykmCl$dZ#*iHAnl~NBQ`R?mpro(c9V%=i` z$sAXlk?HaV&Cg{tg6m-yc-IGyUhPHrkHC7I(Y(+~F;Qt8<0N;;z<0$rVaz^$+1qT=?;pKlN=@S!~0KR+Jc@ z@WQymj)HZGckKP}6Frn#SZzy%hB8@ocH_eOHNL_x?{5qr|1R;bCy-&q$pjz#eOb-E zmyoGsJGRD@nGEYNxHUc2@FldnM!Zh|C&y0XT65{QfQvMqSbo2JM^^6liH~UeujeH` z&)h@u zg&Q;OVHi7tDkaOr~5m#B2;fqp9&KU6)U%0FoIEkOBJ@swso7Ms`9KA z2d$(QZ{5&_=@+zf^nZx^+}}b*)=DQVe0oBy%is3X#>EGlKxiuIInfB&&rCl4>Qre% z)*3K&g+F@iD2njrQC>4fmCWU-jmG%;Vk>B^7Z98En_=RG^PF92&f}t{L+XJXGmsduq9TF|M&J* zzQ9TKc1hth4uO46v-;)cAHTl-L^tONO0-?Q@$6A{jIzXqha>4SxUdo7Q!|(gqrXn| z>TfzeH#{L=g)#ghjtEP{7q>0!{Pv-|f{Tay0XjTx-XQ7S1m*E`~#`tdo)ELp6? zUf_K=gUGb1QJ4-lx7)eh zMD!b~kXTb~RIYZ4h_L?sSU+x(+nK&J$M^4iNEZ6BA516bap+JSgr|->tbZSZib^oP z86uw^9c50HR;9;++msLbT5V;~AWz*Yc^m&w(9u^vy zHW`=JHiCJ+8nAoo7au>Y%_%auxpAT>_3pHOp)7GPt^Zz7Z@3#SsbulKC-1s$y`&A= zhrH)?dGPU0iS{j%0r&R?yRt_d%7wLZHdj;opJj?^sJgyC=@{Nwi<^jIaY)-wJn?v$ zQ1{jbU9BHuGt$;x@W5HS?5xyzsemV*x%&>r`%< zEraECMXP%r>Ku0#s>k-(`>zj69abw!sk9c(t=Mj}OTT{Zoa}Z>{}`+H%&VuR>qTIw zkozh^iP!5(Mex^|OR9{1Fs0o0Yh@_QsrxJf#J^nhl;%c>?8ynv!&_OU1U5+ns}nAH ztxpHsU-w(9`PLdcf+<$}9^85t`aUC4pT=Q-aN%jD%+yJgdB{q`U-GI8b2$VtznQJ9 z#@fer>_P=$9=)=|EdnqD?V$C??EW_%YUf`+TyuyCD_)seX1y%hJ;tTpWhqzp!lKl? zcNI7p|yH-Wo_)8FO`_QNR?OvXAPbdI0Xw_)Rh0oZ$l)6>nl-E_q6x!c$MaQe8zct+;8E9Ww+^_ecIY9Dnp;|K0_g+EBszy1cT+PL*1 z?REa6wGiBaS!OLABH~1w*N8y$@z8bdSYIRZ(D2ZNX+^pq2EfMx7WS|s5lI= zF)U4}3azny%avjG|9Z&f@SrMlTJzXYMKjKE{4hqP_=ix^!}>Ux*RK?&udN8@#nJo! z$;-m3n2xRZR^m5?D9DA)D9NlT8*g;QbzW-2?NVB8M$86g$2&x&eSa(Ot_P#x&)q5d zunt!m|2Y3BYCgh=e(&9>=vRZK*>kE|En!z2Qp+y;uy~opGX*+?u`x_=FXvZkP+#+R5DMvnUAs}??Y^8M=5V;nEN z*9^mYrK~jk(Zz1))mPoxN!I>%>Whu?6+0Yh*f3e&NZqY5P}bYF$r_FQP`C>&u<-`C_G4ZT0k!OO#aFiih8nADx3nb++`o+vJ>j*$I{@8Z+zuxNf-( zlMMr|sVgIP<0{Yho{!=0t@IoRhmU*;%FlYuI9hKwU^!=}G$RbZ!o`}`6effZ)LebT zLS21pF8k+dYR`<-lfI6?Wd>Y!Tr}5orfgjwwG)y>)=L`_#q{~(bA1y zCnH|&`L}w)!uL3yivPW>_=D3#l3MDEq{WaIJlpgVw%4AF`bF0Rx4Le?{@kJ!9+=tvbWU0j?;HJ33;i8)0{PW%X&X zUTN0_n3sd;lJKK17D84o8b3(<9+>}cL~qDrwq)1KVRB`i`iM&`ZA10h&j$#0nwa&< zeGc>aS&DLh9Vz{mjKTlKPZ2_ba81fCX4lcQxR)paGz0>2{9#b ze2TG3H+sq9m*lu$86|P8+CVJ1o%*QkTkVt(*H!aWD;)_k4u)n`KexY8%7^FUw)2Wz z^W(Ffqta;WcW(#7cB@F_dz<}%i^_+!x??_T&n)HK=x6l1^fo(BBg8ynA5EF|lA}J8 zxrSV8KYy?By9YO4y=BhS%BsKB;3e$a4rNB+3pZ-+BBcM8EJVvy27kG(OX5^3PTs?L z-@sj2+Lyo0!gws=5g*=3rux;vKfnpi{qn?(gpXClpZPc^3kGsT+dTw!C5+~y9DQBq zEwf+aMg(_^xzesYikX$V@bLXh!F-pF48S7nIX1w7x100>R5s?{K153MWq%&hw>F%U zXp1Qg-niuKJA5n^{&1Qq4@(^tx7Z@H*jo7F|YCH8xGP51B5ACKur0_GE+1r7dK;QTHeC2@PKVvVM@&|i1jI74Z#*YT1rj7GoZ z^wHDRe*U%dCQJ07x$mwD-c9fKebb-U-h1RvR>nD}x(pvlcklj^n=G3tn;cyG=#_15 zvyyzV)HW%;sz1mzX-ZTM6M`%_GI zbvDDtpQ==m?EY!iIa|L>`#CQAyv)15KgT0H(~(~qOJdyPYyb1WXl!|b4;zJhBUkC@ zK2Wz!CLCSilbnNXnNrv=DK5{y!Amp!AiF-Pr+ov{D7Vw>uh0l7Hgwzo_(b`G5SiD_)w9lM!yEUetTGm}q?AAxUY?ks-US+d&227uH|~ znkYMY(Jv-ZPFgXUlsg)q84*sX zhP~Ae@_00SyufKP_+!_0oUhEvrh*oajNZjk}jA`x?7tr1L;XamuX|iuy6zVCyeiLXI}i-sepX|5)!V8B@;DnAmX|-ZH(EOKrq8#vS+B zYo;OOMGPZDefNIasEJOOErVY9JzwtKVEG$m#*_CB?Pfm8WC<#ts#7cuM15>G-+y64 zy3ix1K>*h1{(jB$>jf5gsgMK*6Pq zlKCMK>@C|rqu(XqkYy(Jvv2XMx<^t%eFHgW?y|z*iLGpZ2AzLlg|!EqT3Fn;r=Ej4 zEo?B=YW3$Yx8ZyF_g#(O8e=nK{QBGVj)~5%WH;PfR65y<#|+sCU*gwPUQm8Xo8%Qa;A%Zf%_s`wQm& za1JceIMyh3)*W$*u_kv>Z$o?DKlsF)$7?in8WU4>{%2HG<%xX^2QS(zJ-c!}j{Wj+AXR~9>v_ktXXK}Jh>*JMr6YOu z?&UgNlljAq>3jJvD35sX33(ytxVU4{D-Jv4)Gmr9LCZSXANAhiJZA4b=VCXtP$~PH z8FYAgQl9%2z6lL;j@uG!ZfnNqJ);l0Y?36qvf%G-c_IdK z!fSdL<729R3Ac*MVC52%_~XfY0(E!WUN^@t8w?Td941@T{TQW*n$H#DS-Rc={&&heI)lS{IYmsuta(HCD|L!Q;P))a)jpdFf zsEuCu6SlP-R_LR@mR_E8JNEcZ^D!<#u5w;W_vBUG@x5^_(d#IaZKU2Ubf#R|Yc0u# zCu7$hZQnEoL$khZXIaiVCBRn=M=xc)pNfvL`C;7>q8|v?c#aodtx>%!KSC1~*Zpa6 zs3%Gy8%%&%J!sjkSfAl!bFgAO>^qO;6S+G~h_KjNcee8Q7OKlw{fN3LuIAaNti+eW zm!DlVT#`u}VMJTT<*L6~obju?Vw7(@GD^f7g=CzY!IG2-jEbx}CG0!)fr~)qJ3sG# zis+cC_b*yPa_@M*ii&Y;w4C+jUgZZ3d=Dxct*-DW)MZe#D7@UwfJM~=d^}?aO+SElk8u}MS>THGD(r zU|zZ(o%1V)GT*7p*nc&aMBi3n+On`h%azvvoj zAH~GTdWp%pb+sf?2k|%r%>CLqpL=v~^V;(<2`}4Y*Pm_2pRPT6^<_BE^Uibfs4g-p z9k;`^YcuOP;IHqa3PF!!^aGp21596Bo0>yW?msjEJ6<1kwdl2vSn&z=pSN*-cUzRF z(uf|Jl&^%|+KuE^)&DnD`~QE<|IdN{Z#j@IAWa1BkDjmI7O^B&o;T!<_2y*}@pwO8 zgsLPu2irzh7uR5y0Zq;%jA*csYnn~EhD46i-icEV9s@(7L)AL1-um+qu1GT;kOfMi z1AY>MF6lC8rwWuug1$Aa)RFL9q_epF`5NUKi5ljiS3g+JWvHu*E-YvmJvyF$2Wo6& zW)ifgZ!KPY?m1uzqz|MCER}CNFnR623fc!=37>82dVyjBLu7AYZw}hb>OVy&ld7LS z8+wS^;U-Zg)!08Vw1qn>^QLA@a+p;|McZ{vOWAKM5q|U#x?`nRl@AsqEOzuvs;wxL zm@!wq4(ympTNl9v+HfqnnpSGbB_BSf3lSgC$ncPR)7a`Z#C5$W`l&9VDNKr&p+$>> z%Jh*GK9U80%!12v!5uH<+`kNd_gfs%*o~VI`8fRsu!SS}zc+cxI_bsEpf?e72yHXf z=XOLn1~Fc((P4+ly7{!WCR{>9c44fxk6^RGDr;u9H+^tIxJi*Vd}gMA)+7Nmex(Yy zU;A$FDRIP#qFAo`7dO07a~zI$uhUA&nY-9N^s|}p^8?|_I$;G_^QO}YTTSBW$9;6T zj~CzvL`=f|dxO2v6QY_MoT2Kd20J1$>woTHbhkp~-F|0f%)IMZuGJ(==Mly`@Vhs7 z+gpSQ#<)59rnO6f-<35|1ze9orFcL6P{!GY*hX3yJ7x<{t46l=PMovEcI zya0EerV@$N3~7KJMYS@~pC4B`#?W=)*2Vhl=Yf*EJtMtJ*hqvViBuof0yi8*?i~}a z`MCvl$R6&vH*I5U;yu5HZ0`nM8H)P9IrrAiL5-G|-vRErB0&KryRYMRZ}3Bn>15 zB^;bV-l$J@9_{e^@sI2XKk&CrJTInGF3#py2FP%pvfh!Nh~ z4juDd3wB1$a4VL&*~qYC?w74~8_!;0EN$=+^A4||$F#w%BGAzKGrh`Z)VDAq!F;@m zi(OLhwnvV~$WtYH?hogFdZC-)NB?}A2B3{De?5DOq6ja*a|(+=N{7-O{9PRKN$H$moeiWq z*<#E-c9`McN2r1ZS&|z-L-@|PAkjp$^(%V*=$NFpsD$I_Kx2H7l*Gl+x}Ni`D%VB} z+5HEwU!;Wo@A#ldey!A7|IsE}ioJXBKwkPBdYy*M`Z&X!HP?5mQ^)h$Gs479%MA~b zq(rO|w4TT^Mh$2(wK`KMb8HT}ohhSpuo}%j7;|)|IL)JFH+&|E#+s;oUx|)~`f&h5 zn;Eezb&7!2%8qa&^kDg{<&Y!uZR8p;COZ#5Hl{WhPEy7nIRCEZGEP1p{t@jH{=LZ1 z(Gzgk1@srD3W)MiWJJyP?DC0oBt60Mb;Lf&6H-VAzs5+e@v^;szQzPE3z4P( zZYRMG-{Um|&}sA1#JxpJYN$WgS>Ju={N20Jfq47RZ~QXrFNEq7YzWEqQ~^IZNKK8) z&PBh)_+e(%P~Un^kC9J-Bz2{?^-%j$guksYFWeU+x?{N!c1~bNmf%A~0j<2zTjS?R z8sU+B1L4I3g6*f(WC(+2GM}Fc60-8K^YSCgTlSKiUfSbg5dHI43KGHj(@QY{^Pa*( zk#9qA?}P1oHnWfVuT3;d3_{2*FZdurKVIVtP_GhQCl-5fBvJ5LT~CMO04b5B8x|ymoPN3SP(Qi<6(;C8XejPcFZ5CAYFd~x!aNiX=;+O zD2e({h8FDld+)xUkX(0Xxn^JSflr=iHjv3)spgU3v?cLn5@73om(El%R-RcdKDw_X z-1j%JixL%ogS@nre6c^7Fv+7o+)sM0!xY!a1C*%5sguAiH*<+VSn#`Nlnt9k`WEgR zX8+^eVZUQP5^CE9O{+~rY*bvd&QqW=iGMBEOUxf1x+==)}LkvFn<*X7d#&q?kY!UMDc z+NPLL82(H^>$l_`G9bDevcxpWT@q^C^Zt~r$1je)|C4j#%smwF-K3SK3p`IzOqBq< zZoq%9mLU#hja@}^HXNIwrXGeq3;!1LE#SK}`FJp^+QR}diutp}F8?jQNF2%@+kv!P z^JUF_EWWV7#_DdNOp3jdeD(AhOc{Nns3zl#j?a+KT%ju>#G{U=pGg0`dGNJ^Pkah< zZ+>}_bl`1-x+A;=L2D50P7P6V=Ifzrz+X$ky6UT#&Fg1aGuv%=D+(nrJ^ty?} zcSf2x1S5fe89oaa>7zx23e;^XqP4#!KRcQj5C#tELfS2z&yz7V5^!xt&kijRRMI^V zSApse|6n@kxV8o65oI0>O7fE_g&470wZQaes8t@5+Zz$>DN(4KWlEw|H)wd;$ZF`ul_{iHfzH2w_vjq7O8-v7T!+!v`hHW#^COd<8Yh(_ zFZlz4Gn$xweD_k|1O}LQVxO!lAj7N_Lp$$zIgVTv&^o-3uaMcjjRO~6pDFL+Ae!9*U`HqCdOyoa zuN?duh)4^Fnc#sxMyxSK8$j}yOgS^0L@^3Q_&$<2VGgPPfzo@6DnX`aOco!Y*a;#; zo545(K?f3t924mepn4p7Obv()5(?Hj#$4~#K2_(JFC%dYu?1}idlOuEU12<=7aUI| zfU6(AP9JTAnO6&tn_wRZWTnudPLLV<0tRxxv%Zi9(u_+`=s-GWH3z;#0Pk-Sp+ayI zwaD6E(*2tcUfizk$QQ)3z=Cumoem`*UoZtYuJWk!+FnsqsHeVUy&5y22ctnAJhLVcd%?`4NnN5!X~yDpyoOTHw%lKU?iOyt5xx567LqjJRp zM<6-wc0$^3wdoO4dBszZqkR_A$=@zt_7h(SYAUjM4eU5Yt z=3SY=hy_IB4TrX~rT*;>z;_J)lZIT)6#By6q2SR1L*)5-r*4LWE~mg#VzgA9J(dUW z2uXc31Hx=08%5IaKvog^*sJ)GQ#Jb@WVtEj5=M&=A5ROLMfyL%%0phPigNHHi14j1 zNV>vL5yT1LhwMVC`cy?tot5oBAA__eZf-c*&>lpc;TD41Z2<0aWDASVosjxE;#g6; z`n_M}rH!qDXv$`gf4gB*QV|>;{#zVnsdOalW5+*@#m`${o^ahyY2L_LvyU7Dd9Q9?s9JiIzazuk>^d$ z0XR-EEUNDY8&i26v0vZrS26fjcx!2=AwQtOSS24yUR~XFqt_h?WQLfMO~%vR%ML{v z!~fp-!gEn@m0(ivJGj}N6ki}0R(`nw0!QxWqWLa1QHt2tX`@ayg-%O$t6p>JcQktV zuj`q2u4k#egzOPCxd98CTyR@POjGU@%#ooM{d)&4OAp5wUSvHvuN;dOA-c?v}?55p2)&ow)THA&cC4A*!2 z8g=l_#4GkSASd~DYh31Bl9buC#elec&pg=^?cYv)k5OKT$0w4QoyXaPV2gV|^NhI$ zXMv8^6%COF!k7Dd$vr>ur{p}eFY%Qe#k>ci{1 zNeY~F&APxr3xzFY+kI!cc@+QZ0ajMPs@=&2?UW|ENsFX7{k3`!=%Jdm;} z$e%&%a8XYb!G#yMOzDud$-z|4&nC}yw~eH3HXe3pisdqu9s~YmX=lyOG3le%x zH7pI#c+6L$UI@te=|k$yz@ni}Jx#s?P!H;_S?|C_Y2zEfS^2V7^bO#)Co+HgQt41W6pRa*B1g&k<1kYXg zp&3@fRG;EJNGtFcFo0ZRBUVZ!Y9`s=ho0Dau+~Y31sgZj<+2HDgX<<>8GyMP|MG!s zQlYS}fYg)4@C(5m&tlHbB>J5>qq96f-HU}x3U)i58UcU}6C{6QVISg!3sJ4%ULdP> zQ8Lb=OG*C?5J=4*!pB6qY1n@oL4XA)+6BwO0aNzJIj?PolY^8$=x) zVH~&!N9T#**Tu3uptWZW*(=wI2z3Nn!s-M2qnBW1!gV)NAC+jfYGRB^E9OITr#Zxi zFALzSI{`liqjB;kB6OrdL|(GAh_Q?R^ql4hOvB1N?jv;yn5C zFr|Jo(wh?I|B{-81L(F)vdbxWd4v7=+oZasuQ>-Ev$pJB7E4|6TSWp$SQh|uvmvjm zz&W3>7J@6rBsmCSWDg^x+|l$?;3W^(mCl)6hz`hyj~6q%d4n^7*50k51a`}IpJI(M zRu*<}!dCNRmPFHdJ4t~QGuY3-|pp6I%U)3IOYg^nV9)!@9f+WOW z=M?R15>7pTnp}T*s@ds+oA+Bo`FY83U&YWi;`rxc*$zOuE7=f`NariX6k-I`Fc-sO zxZ2$f1*+-~mh;H&w!`x~IN*C#QPvgq?I1{$&wHr>@G673HGbio|2OeFjXa%y%mLe0 zJ^tP~Sl=W3o`O9@Fc#H(gv{sNnS18C&D8Pdc?cLIl@`Gi03WA1 z5SBZiB2eD-4q`Bu1ygOfBD!jMQZaXjzw)(?@uA3XimRVG8Ra#URNgR{nRcc@T9$NX zY+M$CxulPi*KR*Kq5YREBa%94x9O0QLkm)7X;+4}+r&H&GFCXNpZXb^;94>HFi<9` zS#P9zTCyvo;*IF6+{dLgBJ4M{n~EuZv9kdHoj)G{2#13b4uQ!KGuxxEkzYdXxF`cT z=OYF1!-f7v7En^H{ZJnPOqtZ@+z!lxl!EmGKj*efEHe$t296NHs!3yffM99nhNP}V*jj*+t_twElLw(*#8guZ1@F&oD3N}q zdI~bO9tfdn`?zRmUT!1Wajeq@>7&yUVCHX!fih3*XbtWGIyn5em`)aW-B+~Mkp6sn zi_X2@M7(@sFr3huqj#dEEu~B%kfnDBGogmw*$wHhwxf0DD-55ytxD&6(t>^I$n&Dd zJDk_lACX^{Qi0XX3j|hB%tFEJ6)B{@ugXO|FG*9|zI{8)65Oy*E?e|Cu1R02O7X==GnTY--6}Vb}k1lLBVAR?o#Pfp2yx(RXl3 z0P-6>6L6h}>LJE2u7Hm4M);#{>-C$P^C$NV1^md=J-8zW{*g}D1S6=d$>pcrs-bKG zbg=_sp6T#bvwIN#Ti9d66u6qxJ2``}$8}wQP=!im^?rn>af)(T*YoSZSQGmzyr2i% z@eeU@^-#X9lgF~nAtaTd8x@P1C{Vcc&B(XWd9KW{ z1vfvFsq5234z#?;-C%}AhM!*R4A&FXn#4e^;XS=3A5Rn4Yw&SycDTt234QExM*5Z7 zR#WNawJ>#kNsJTjaq)Sr;TUJ?tKjUf8QzlYB{7|o-AT3Xt6Cmgs|AK4nkQ(07`D(K zoL$&k?k*DMfsK1Ge0d!qpYQ@?U@?#voV-~?5XX@c!I39{qJJY}f$Z2SR@-k39j6q- zpL8*sI6OGp#Q~K5N)qk0jpdu3^1M`=7=Tost$Op12{fBRO`Xa^l~F7KsN8BkWJz*0 zuF@!)Q+TaTz;v3e>c1-WXCqgfmZT59bfkT+;8E+i-*lOx8FDJn=e2;Cp}&T=C<72P z+a&H-%y+5CC$WxNc{j`+$&=)7OPzm2>}5}iV}K|LQaND<&R#Ct{`?WgxL`#|fCSmE3kL?@d0LSiZwSSq#6MU97C~Zm_&y71a_2q^IYWM z32Ah3Pvh@hAj?;EpeF>r6`R1@?tMjPE)Z_Nul@Q>gh65n$SMX^KsDDLW@6ug(j{I# zt}_vt@L&NR^}CK3txx#W0Qv+{z&#g;NxN?B2??<_Vf>4&TsM<9Pe1@*P!os`H<1#q zJ~c$YyzII3Uxssk>FQg)6hPG#j+POujhZX?2A$3Gb2m}=OrT)7zL^(Wst2zeuN$|+#Ivqr~5u%dF+su~Jb;225p>z*#+h{Q||*N4z%LgY@*t+rzNIf}6$^5xfPbqG6@>-@n2>qg#s%J)8g3NnSAZgiQ<5jpAtOZmcB8erA%YL6xy&k3RY_ zcEK)xS_R1(_-T$$5hNeR9E)Z<&O?@`ykz}D%B8W6Z$NTTzmRbWBsN-tM~vg*#)cn< zbRP0I2AulabflqgYP+l|kl%D{{_yV^7`~-xpbV=C5qxY+T+If`FO&bBgO@@W-of`o z+H*1kj8|x%nFCP}sM##J8XAjtEVp@&cK&V$AAi6SxNz}c`kqeeh@3w>Q^1u=FFXWY z2M^-%VQ^Ml2d<$!Z|6!Vg`o8&Q3^}s)Zl+Q(*UJA!wOHZuTj&mYo7y-&nYJ#WvD+Z z@n>>!mi3%81s}mv4ONhABxn=@ARy`oamz}_MO_}(@t?*JVs*$6t;^cR!Tn+qE` z&rEMIkbXj*VlUEz_;YM=A0+elTR~CQA^V6UADj~yjJBC&*6zQTp#CbFSCxDbmgbxl zP;8&}t@9{$6CLK1(MHu*#IPTyiFE#v+(V9cS3XTc1TAxLr`(*sijK4VfXh%@v8nD)qt z6+b_w8!eFtoQA|%XyDKdpFzjNf&`d5v}QEzp6rGCP-#y zc&b-&v!PQp_DpFw?l7c$s%_ol4eRZ-@9YYI|G79o1=4`CokpHk;kxgjgJ10vbCZ@O1e+2vt*@n)1nt>?B%Rm@1xLj|hQVTjn(Px26rI^Y9a*$& z1QSJ>Yn@zVZU9JH;Kvz*WJ@ujm`5;XRi$vrRvsrq0a3kO#Xm|<8?s@Bbdie1(ijkJ zn4l|7W5!bKFRv!4&sdDnk)I`W;8O4S#euRqKM8 z_aTjT&fpSA$c86Ay&!H91%W!{dlgIk%OIHjlommcxoz1Dq$*}-QTBC|51NOu?+#(& z6q<74y89Q1RNLiuI*dq!6BKekGhYaqCq~Z*cj}lD3azzMN7x`-B4AI!iOeM$+8lE+ ztUY#$Jg>!ddo%wyy!LYltajehgz3{6eNMn@kNnnj*hk$a89JWo8Cu8jurXa z1uwI?-r4I#H$e8-faxE=V#Z~P0wDevyPS)@i216f|C^@u`~HC_NET$uv1xXglZ}h@4DniN2rGB_fchuIMgPPgABdCyeKYo4iFo>6+IzF74YGP2*#kRx>lw z;$)?r4y>Cm)JavK2f(L9UzDQzho`(WZ)1^EFOFJ`6H(KG>Q=nvS;<x~%F_A)UhU)$U%YTzT zuvSy-j#&1_xpV<%nN}DeHAB?%yeFr++G*NAnbT?>z_ETZ%sod*lEIwD<~%KO6pSDu zh^9eK#E;zsr|5-ZDfk&HJmfdW53SWuryDv=j~C@ug%`k@#3^z>GGJT^spJY%DR#iC ziG-|W?U?I-3M_nXVL^I1H|!bUfm#5rU1aAHV6ZMEzw|#v(qbe5ut(ifYhTcFc4~B} z%$EXw{+8X&RPBW8-Yw=ZD&mbRJWmr61Vq0>)gf|{E!$p-ev*`#SOPvdp+ptcV?3;h-*6-7^Kw$fc>uye29r~D2BDb_VeM$!~}tI z{xcOI6iM^Z$Rj6SDQ;+Wqzwp@af%zHzE8?{_0u@!_70DCFfDA^8cBPtuoXl`zb3~Q zfbD)x-)eM5mDL=+{hGRXZ-tr2asr}25(3UUKXZD24=dA9k#59myn~(*fZPk$=p|Mv zC77=$tK8GhB|DvztcM_RTNi6Qr30#PHO16|leB?k16<+*<@xX0ZY8B?sNx(q5y(oo zKBmN1}IPxB+l}#IE^cws?rx)tqo#q zA2UwOh=D?j>j$w}Z&DK7W+h$*I4V%#HXOBFDImK3s2jMk!fSiW zee`XdzP)jZT`xo@zSk@7*I^DUJ$*ny2SHZ=pjfZig}Z+!O<{~;g)I~>eWg+aUWr4} zrNQ6reF5EEQ`Y*hKAx>-O3oiIzhe)@vsK+QEowM#YuzYm-ml1_hukHbyk;)s%iw(4NbMQ^GoIyqcjD0F8Yzup@+^ zv>zCuNDnTn&DrH^H6lZYTpiB>?`kEvS_FES%ipEDXY-x+FH(9OT08I+g^Fi2IA;74 zpfIm0L?lA?7jjF!fK#dI{zU{zoD!Nl_Bh>ERk<4! zL5FQqvIcS6)x}^iCQS2UlN7}iE1TBvC+O-2x*WU+%0WZx1;xw9{ZLdH@e;Ej)};DC zxK42+0VzVfkxyX_t-r3U!Un=n%M+}TR}&{01Q$ZWd}!2hB`iR6W_@Ck&b{68&s5zm zsb#S$F-5<-em(X5w`$Cn7*U%3{?W9hvPgy}@*c3~vB|6HB~J^`WG&2n*uHR!kd0`(+O!3`=f6ix)7 zt;wNE8<3s75#c1cP3e@eUaN}K@1Qzw35+nE9zZ7h@mGz{#==C@hzZM=SX}`C;YbC7 zAHEJQs!30%oia=}`Z1zm{Lqyo@G#I!+`_CGeUDQ<7;`-#TMI0WfgJvOBi(QS0J&03 z&6;T=OKm;241kCBZrQ&x4!*X87yFZD3b^w^=FKt9bl?%P_0Wz)?*pRN2bi2_@#4<% z3@EWiP+ z@*y}Wmo0Jx@>^IfgxHa~C!lszmYRt{O)Jxtx8o|701g;8r zI?Ns@41IUbItEWtnSBYAN31E5XPS1(UcZt0z5$ZhWOuWnF){!dOl)aMbujySVQs6bBl_bSHDhITb|5vz-z1p7tA}0K@-<|Iq2!p3D6}as6?hq<-N@s z`0GddW^G5fE7S@Bk-mO`OyqeJ#~)L1i+`UeVT!jjHs^6+jcU^{kVRr45#{B=kriF% z$Q}7L1*tyZg0vg*oa{%D|3^Fv5gg=&x&qZ;G@&wi%_1kO58d>x>g&s(ka-INPgV8h zHJ0umf6JYDrFix9F=e!4gN*cQ98j3wUx;x3OfLCzcn9w}e3PXG_toB4bf+0N9$)sjPqHH?0`CY_!dKPDj+5*GtQJVk;vp5PLcftMYy^Sv z6-0FT*HTR9JI^m2TSpGX6AMp+LE->Gp7-1t8%@GjCEG=NB_$J)^KbCaU8SdcZ>Cy- zF^>Q)nBcO!n#g;lKvuwOX?5 zL`~J129mo3)y)3BC6!*la>OxZL3Lrd0x+I#9Bkdkqr_RjK_D=phQLNI<^_P=nrZTN zFq}{y5f${{dxlR-w#jSjs0T_wivE+iSJUhZU~3jtKH}*-s{i&e97o!KCe`tqORLqH(9e2!J$fg?;&-SL~<9xKcachVbg)2 zWCCz?@9)`o%|T_vp98`Q=*v?!tr-W;L+wWIV?;d#9JZ>hPjGlQ?;ockob}OAjXKfq zaCDz-t8BGT>_QT9K76Sxg49zBa<#@EM6MNi>T{kDFJ!uz^a+_yU-j5L0h(SyQvfD* zQnhZ)@_MaputW;y@mZuoJ!uRu(5C8vNFsqy9-HSs=WAP(RQfN#heJjQ%xzpu30J~6Ce1sg*wzow3 z@LFx*jZYu}5GV_licI_Te>7Onq6^bEn#^ksx_ioPE_I-2=5mMtDiSQ_*Ln`Mbo$8{ zvBHjM$76X5mW(=zPB$faQ?nj=4(I-7!}kCBH-;0zuP0zZjs5PA%IB6Cl?>?u2JTAl z+iF^$@133EIU+5bG+ggINTPGSuguV%&=Uz|D1fmtXFf2AFEz^`Ylc?9*5>Q5yd7*D zG45j?NHDUv7bPGn3*1P_0N)erW_TE)8&vr&?hG~>wsr4aFGc=O5NkJGi0QQ(X5%6X z`7Mst`2Pg@`OUFDu4b^Ujz|W5bk5vhqjY?cp)I*QT$S{^v*PAg9OYZ#Mi-vQ@0}pj zL7vnf<1Tm4zqQ%j0+K6PXIoabzhSyQT6}%pR3?Hzpgi4ONApvNFKhTH|$;ufj z9V%%zJzjSHM*okSilu8?9=tvsdXA!B}6|E=~-`ndSNMMaNeQ6 zgB##zR`1z*--&s9M9<-B&HugQEw6Camd&1UYe{amlrsF?c#RdRh{5(XsObW=cnlaS z+68*`6*0S*hv92K|1h%sTgvIhYh?2-)?yySs9(#4&K z?8qnpNH+oeq>LKV`7~S!>NcrwKd1t9E*-_cJ>-Umj|Is@gTnkPS!>wcq?@5|sETZ6 zbWz9l5&NBYg_wPDe3jV25Wu}XkhfK60$HpFX(+-e!%Z=+kY(oD$Pzw#D+u=|H#Uc8lx)xD{O0zwAlK|2wB-ICRxnEfw>LR&tuE@loFb| zV!8>PmobKDkGX#;AxZh#B?Ut`rzZJdyS&`{LlUCO8B0}8_J1^x&+uj;f5`Lo|AJcm z?Y#Y9UXCOc=DTcMTH1D?>!pO|CqwVlxq*Z(Q?ph)?QB3_Dla_i$nxX6r`!N1cJ zL~X0DJSy+W|3u`k(mxxLXi#<%ks+)4I(WI^HfoQlha|n^y(6U>xOg+_t%~{{9tQtV z_f+S1z|TiJS2mLU|E@><9|_xiz_WWCa;v-jpa27NDd>1iIT}cgN+@RKG*Z)5Dm8B! zzj#4m-GjStFN;oH7yf=45O%%{vNtWDM8*nr#P&-KJG)DNcPj1Pt<tX$fC!g>|V1zE8)?^J-Kjtu}i!MgDqRG_^+j}~xluzft$l=e+ui>Eh zr0wDlH;ZJMqR2dAaW#Vx{`-#nqoCmS8fjA8iOSm+FY0 zU5HpvYc}Vv8y>m3SQ} zx`AxZabil!q&3iiuST`TT(HfExGn)S(3O3D&6iTL`%uh{EmDW9=P!TRjfek^WV8Wr zVG<^Rre?oWpJ!OC3L)~;U`gIzrX_8fW)R(1`q!w<5Ceyb>fsv9mEoA*(SD269Q zSDJSY1`Ns%@YQilOl-XM|AUnUqo3Y@Da8K|V{aW5Wz@9~(@3kdlmY@ucY}fmNJ)1K zNDkdFgoGe1U4nE=4V@}6gn)DmJv2izF!39o_j$g*zq1x=hPCFNx$k|>xz66#K4)KZ zg<7^#X*ct-&2$nZZ4$)X7zl2mz;tgj^P3`pFv!mh_HT6Gykl1P@4+v&uUTxunhpMI zlNP>=E|^3UD)=S0Txjn}Q8qRL<=sXf%kT`7_nBj5uVhkshQo-jj(>-HXnL48^b_UAF=5Ez~+LhWk*+vxHM>MRH;wyjB)-4}UfPkxCMTbhyc@ zEri{n!H>;vq$8d>uX5a0)P`%>f4CTlS=2L(QSvj+q+34u+uA=@7{HVCJf77xaD4d3 zET)wD%*k2YuXT)CO~BTUnH-!e*G>&*(}U|};tWuQ%(k_{9&yb*;$+uR)o!Wm4`1wR zsc-O2_%WWyZEA*&^rQYKR>5QX@~>9|&3}r6%rv^}ul(BL z-Glq~QA_NV#~3V}mWqp}49dejdhl?YcKV{BaQY&s_ozRFCecpoN8648{nn>3eI%^-gxV`wRW58p1;l9`j?Ko*%EDv*2Uh)E4_ZFo4d&H1O5FR|A-2Wi7n}0al6?qB9XrlNw~#KV%ON2r z=WiuEzh6U4-zHhKbRnJiZXm{eN0W_NfeMneC}(Ck{h#u~DYEP;Z?k31lq7Su;ve^OH8^JhD^9 zkGAXly%TtDuCJP+e@uKM#vz86X+E<6HzyQV5?TSLi-W84fIA8|Df*jXSvUfEAn;?s&+0!CFc`5kExE5lYFf~!p}gEmADHq|_=t_T|1M7!mL&gV(W;Wrl1y27Luehr z6}-j&E;Z-hz8D=UGD;v2kNjEQQDiDn=hQuC?{`f0Vd<*-9oW_dBZCy3P+`3n>l961 zU({vl;$xV5-LU1xoh$pp((rU|2hL>R(<6*mMgKz0N&4Rsq>mV+_<70v{y9MFl(2B8#>fS zW_m6AME#Ru`b>C{tAQ1I=OK2(ZlWA~7;AS)|NfBTg$8d93A(#k4leF45)Az+N~wYW z>rXAkm$f1}>-ju~6RWGP^Zdlfp=F`)UfFg0XX4dj&b;- z<$<4yIhqU9RD-)|R%40Q^UI(@VwOT#HW#Ay0O76Ogq-9%Wg{61W~3hyZF)3!=?Re4 zW~t8aSrve1r4cT(Jaj8O(BEkLVtTT88OYqpoWX-R5qf+@d2{Hkhv^A7S!a5w;^?A5 zXN+up&OosQC%T#Bv}aL{7q{2vR><>0?5O02pM@pR<-|f8yqGy@X&c;sUMEN{9r&XA ze%ABsYlC~XG^b4Bkw;%n?TWICLH@Z>>=_-|{2-U85uBMz$t@zg*wQ{lfUbI&cL(wd|6MY>uQ205Mj~Nbs&S0iLiL& z{@C4&iVuttBn_8DO|v^{{3A4|ry8nHEBnIP9|JLoTlG`hP-RTOJr53IzU{VS%nJVz ze7JMh{`_-160?%IpLN^4r69sI2J)q+xXJ&{OqkCXc|Z zW@lAr%CNEECKQUMvqk3Y*Ed1y_?8=s2WX6rxDQ&h6J2q2hIp#}n+3*wdz3Hmh}hbB zczoG<^UFM@x?HL~bijUGJzDO5@NQDb|3b8oMXCpds-eiy#0r(fwdfN6KY1xIQi_QQ zJ)}f`lb^vylyw#w(&B_3%m7KW4^ITuU}Vlovf^x9qPvnY0h$ph!i^dsL!60AiwOjP9;tf#7zU%#QPIB;Yo1B34U;3OQ z6EglM9$*0&=~XwFKfqFPT))zIJIgN&Jn3L*EbtcqUh#|?FTQVgm?7#@A~}FmtKF1w zd#naVCk@#)_;2K_&J_d;6oM>k0Zda8uPZKptULQd7w^zFGG$lWmd;L9hm>(x-7zhw z9J$=T5KAH8YOi4^!!G&oNMwpC?|l#4WfdaN95c^chX!t6TUQTqP;z}P`W@FPB0Hk2 znt5jsu11T&OEhFHM0rR%KZFtOrdyv8G)T7tK-#uUXya?^w`In ziPh}($(8$+%u`WWiJ;5K7v+@}U_KepajcyDv1sF!MNm*uB9Cs*_bn(0WD&QLvL`Pw zT;XvBQN*0|o@48OxL0s}O4(h{$vpf$IEKOUx0|NxhOe&onB$k=O<4l;F0&9J1@16z zD0vNERHvGCtW!m7Y!P!9E9;b*c)tgY8AGGP)vp~^;I#Lhg?mCoDAU($S8a1U&`DZs zjB%n}YIZ_{Xp_Ykkz@|$=~voGw+V$Mjqh7vzD~|&GB!7fSpt7O!wWSc*6P@3wH#EKHF&f? z@fY{~8$7P4FS+XxIz}I}Er2nbp1S_qpGkqY8qsTVy8XRW?$`cCJ#AOdx;H-TVhs*? zy9lLH$A{FI)3=|df4t>?_1dFE(4dtURq1(ea1jJzAdV|G4bqa!Qd{($k>1>N7CBRP z03CpbFSOHAou7h!??hlHGKVl^fO;nGN>iW{K7Q%M%5ybc#fgAZ66Mq0O*wme$Q#dN zw4ph(yuXe<&B$byDI*fp;goe18z6W7RQRjO2g8^9)J_M~%yN)sdpK+T)(YL;A9Ufx zTN>2cPQOmVvWbryh+VpzF19K7c!3MgHHWc8ixL-J2qB*2)rw}u(!g=i?Vc_@>QP(gi-J7?K~~g?JcpM@TQcHu-h`>T-|%9ULulaw#R(nidZ{cjMru zxu+9*8EOR>C+0uxE}(C5Qy%jqO?t^kBxtR(X%V0pL+IW<4qM}w2d`)87Nh+XyW^EC zbNJo{9Z|==3+=Iw$}}txTm@-Lc4ma)ieijPLz=bXVU2q{BJ{F#fEJLmZuLuS<~vXQ zf;zd7TUE9yNR%)S>+s0J(Q+apQZp6r6i1TH&H)Ukz$?&LV$h+t*&HA0Q-rNERzg+g3RbTS|EQr_w1RnIlRUh%o=QE`+JpUjn)|Pc) z&yMB))8oot=5r=L7x51W_AWX^jI*h-i01lScu_+!o5FAVQ8SPK`Xn4L(!LBlGckif zhSh5_4ogcT%-MmFc=sDS*hH@eR=rKNvD>jBY)u!2;hJ}V645stRi`oip)*HPMidn2 zX*}w~DmJiQWM?!ew0QH%Yi*%tcDyB%>SE(a{os%lIyKH9JJuzh6oj&} z$MS98XtdPRo~}lUuNd%Nyw!L$t#j%d=0SyT~p0`}|3mapzX>#8KpTd!}rxtKt8d zliE&+0i3vo(N<2kH`$Rl#ZW)~qME0XgoTKX^B#W-eI z`qXaBU2KJR@xf*xw$J(e4p0y>kUnh8REPxa?&oBCu8VLaP;h>JgE?gXC#j zq?pefm~m^npNDpocwYA#$uMraJ4i`8Ag_V2U1V5f|u$Mk-NyjPyfS5b)FiSw`9N+i;VtiWKo ztN;LCu6RzJe~Vy3bL!f&iJs=1!NjUl7&-_n2p_8O2*m{TAx0+!L4>z(-t?6KUF_L( zHx$z9@@o}t3|`yDbzIqEh;x;>jBnCDlc0wuE+O-i)d$O6Q-cHT^m+zu!xOD^f^!g; zz4W8NiR?h^HQ?M@FWdSp_qW3DY_MxG*a5P^rXZj@5PJ+ot1d5pc8x(}3EW^~fgldO z<5)CM?QXF7;(HM2m^k4IwtdPPJ{<8_0(G9~>ILrD3y!8t)O72%<%{lkdFw=810R)P z#V3l%BTZv!x(_|G-$sw!KJ#aCoL6|=gvt;tE4R1ir;}p#JlBWL=)cyEeKEs;aZkd# zqY1fQ3i`DuJTvMZ1Lui1`CqlWJYg7X-|e1n+MDJ4DVbTym$h?coQFV~czW`nF5LM< zXZd*Ihqnz|t=Vw%yaI+IfvC5%r`?ZK(*>^WUk)xG0X+rLM^|S zL)XyBZ$pD^?Pd=3)w;V-T|^=Up`pCp_ezC|hJ0s@m)tB@SA6#Q7ui@?QVFVWUh5GP z^ZwRwacNa|*f?A*3^iPNRY(&0Zt-xk;dr00(z08GQi2l?`gK5tcE!2BSFOkd!t+R# zlaD$)w&XiH%pqmu>RfSMq7Qd{g8Lf=74`#`D25qjYQQ0NG3bmTbb&}WRZP;^#Sr1> z(%b^Ty=95J76b05K;z+5{FJ#%G_o~9F;RV7z17*kzkN#_zs8iwv6L$P)84XtESStx zEHH;-0c%fOU|6&?ecbcWbLSZX3d3MfiDTQm{=A{*_Spy_HMq4i;C_cEBjosd&xDe; zYHSFnnCHS2nSV%1V=yc+7z3=iU)1A!kW9=Pq7oskcXpX z(N4}ZM|)9r`+xJ_#mj#x4`o4i_9$))$Sb@xxY$vAeLJsFmiZ)WCCpI%<2ml{Cbvg2 zHx68o$8d9NEv_Tiz=q?6kLUBE$Wz&kW^|-Qq%X>Wf?$0FGH~9WGU<6T&M|4N+=Y7o zVc1Pm4skiPw{GTaFfIunp7CTpu2^=rIqw{%?7ht{(fbfJvPerho zE24oMn1V6tQpQ)I4lhPstdhFod~1VNOEIhC4rX<%)1c%se)a&*{5F`k5HeSL?s*}q zqyeQ%qCG*~_}-DLXfzzmNM^5G+y}n|vq2kra3j865^vlLMz^e0Fn_*R|G0es(Q6HQ z0K0E$yuGL=$+3W3{Uj$KS4I7vUP`xE3*e0h7z7dFee;7nC1hIbL!~|WK6;&*Nz-)X z%z`AqhaZkHY3y{lHswkKUTz=qfA3xA6K4#uVWPFvW%4OF`oaS)wqGN33A!%Sn+PD| zUeKd`8O|9-_|CeZXO%UT{GVGq{q6-uZo~)=imS1I-4v5ly8ZRyh1{Lq%3}L!Yj7%k zs>yq*%{zI0*!QMDk)7S3oyEMbcv$oGXP*DOgzjh8Pw3Y-tE=fG`J~!F!6`|Er^B|3 z^Kw1rryKKz)Mv{`))%)9 z#;}+}V)&-5aEa4;GFDI$af5Y!jGg6u7TTCV98rDOioj3ET{wqM1o@^{!5(T{f6F}awKC7BV@ zt`f-J9d}JKk@n31zu=))m?gGonJ7^Bxb}2D3k#L5Bq(gs)p;2cgoV6)1d!g?{peQ; z1Ym-n1o;>!7T9Gky$I*9GS#(?NbAQ^mo)d0&u?2<_X35IGRcVa@uT1O^Ygvj_Jg-PKEZd24zlf|h0;{2{!@QA3sMt?8HwGcNmUiljj z+?J3>65tu1rzZh=&tP{Ki+UNI@L#pm`JE?iX4}W|QC-OLbx32%F~7`2B5h$`ud6P$ zJH5McWwyw65vl*C6xWQn=9`X}8aS-1<`yrgz79l{!k8OKZ>a_P^7GY3K062_istE2 z!#wXar9h^H=q1+rr$5ge-gqwa8t=uAn*X)%L-O^$xD|K#5C%bZ*BHYn#>OIhkwF17 zkb^@r#Bl~rjaX}v!m}*oJN5x#yTFi9T-OZz8%Ti`*N4Esyg)a0quU8*W6V?SLn^oG zh5cY#4BY>0krz@)kK18g8-tdq32g8DNpMFT*vgE@eZr8@g>7CA~x5 zLmC)&yWI*{?pF5@5&Ube5x_N43ACTP?~A-U;kI*@KS2~tV@JULM1cNHXSMZr#L;OM zzFZ#W7)DjK*@~C*Yh4&%>Ff%zITu&4&XV*kDB;Sy_cjCgQqR{flaxnqay2@l9=Ly)E7-fEU@iG($pqKCYk=luB$yZDi z*twsQ&JIRs+GkcW^sFKGgGO4u+?|?5BQ_qLb7~A~K9*dI=wz_6eIa8^JcJx#HfCj= zPUphnVl~%!;jgyQrXwt4O9^}E&b2I{iy z2U%DuKdrZMzUbvIWMKM`<59V9m#Jcpsmf)&eRY7}VCQ-uUvJk>;x{mV8pHOOV}7Hp zvT_kc3wT>_!(tyTQhtZ*MfhDbL9ryZzYars%`#;;oIwSa+zH{>F9EE)qD8c|V$_2DH zqWx6{hxa{YP?Ij#k_fy0c)$MOp@*yVnSDQPb(@f*#|_gdFPt4NQMva|T+FO{Z@|S4 zRu<5`&-4I}oo-Hr))14}d1u{@DR`~&w!fL_7VAPkJc~wpLSs<*egq8YE{DGva_R2J z;<3y_NcIs=i7?3aZL?vt(^XwhuQ8NM*O|N*x$G99=;Z-ryV`%^Wxc*_$MG4bub1S4 z_QAF@?Y-QP_46xwjLQW4JzOqtSKoo)X+R-ZZr%jUKA zFth$lM{(*y>DKHhZthgbQ2LIWTnG?Ko^&@K5}?t|#@8Vwm827pof`%T-n9tX0)+O|_1ss?Fqhdi@Aq}u*UN@49#KL=?f&Er)J2;lKewR`1fBbZA0+h(^RR}j*;N-l&}p4YD%tM#7070p|gRB3{O>9L~4wZ>vwRwI9ImVtkLT9HtExp->Pxq)&DjeP>Ze56oee{K_+AVxi!E#@Y z-kw|R;5+a7W_Zyn9rSqaxnysc-D^cxgsXRjAfUhcW)NEcHdOq0WpAUY@|MMNEUt^$ zN5z|eL=VHS5!Kj#=oh3FMF;gw^@~rj^KA%`iBzolonDxh3|Xk2CK8tA4c&g21kCCm z_l}4ima5>h2uRS0XSykOo%OmH@U(KGZXNZTvV$2I%xeoEd4-&-6M&N=#<(QO{7qX; z&IViV9YFUhcn!1?e&E$mLzF>JgNV@)4uUoHd6hQ2fyg{sT>TgPX>RZ*o8!;$N_afV zdmwTJafb^H%fsB`%JSdz7Y%KWj2ng@f57gIH!Mha!xBwOl5F_r$6K8?@i52RHlwBi zaI!V;jXx$VoB8^I@f!fWJ@lx1=i^f*fzqPI6yL|H1AHFoY_pIcMgY3ltWk63zQ{^ep20k0UW`^f-ryp?z!Focq{EhCOB-Y?B%tF5U~4& zR@Zr7j0C0J0Jn*J+H~kFt9g>t5gx-SWJf_(7w046@xiT)Ohgj^)78Wa>$?I-mu%qF z#h3W~fZxAF+}2*fP5IxSU85_^5zme0@YDrhex(g`{{5lBCd5+v@xyiU_LUFbeDH(w zl0F#lpvikrG!tGHo5n319}$^U;(l;Or78Es&mx?-CK3~7{{gxml6|pyh(g5#i`B*B zm75&M8X6vMo|v-TLx;Bx7l1k!1cM7mhBJT1(H4;lmH;!LX}~~HUxt!ysH}kG#kK6y z_UNT^CAqoUxV+7>a)1B7HJOdM93t)87~ZdEm#lkW^C7;{vzOr28WS3{cc-W7_D$r? zGz_v@ieBT0r6oV;h708Run{rL0_4fDJ6{Hd2<-mZ1s{pZb@26GWo0{xr@Vi-7WmgA zJOexEh!VJ{#3I3QhNXGm`;-3RS}>hl;Is3<(S3od`%3;ne#SH>svA*ZhVpk@AENn9 zGl<5RgLM!)fnrGNx}H`K#?b`c=|2lqrf6le zXP4`(HQC)+9AZt`X#yHC-NB*0%Mk+q7&_<|hI5)mwQG9uf?vCK}TE!IQNt z@{1hq9ump@?+*qr(SjdkashAboM=PI4L(u{5Z^v;Xs5F9><80y857UmabP<48`ihj zBcYq{Q`0OwMv}1yeLb&c^xHrcgzy+frH!JYRN$XSZB31xuEzMduvyx1hc2I8L}jI~ zFuDn2(ssYFh~izcA_kz|SePshW1t@HJ=5O>9)OkrmSt#0zb?g2W3cuIf4$!D*YlU=R{dO%>GQNeoo5y%P{z;jB z&+6(WJUa1#w|{Jl_t@pdM&W!;^kL)Vdaqv=kx(NOQzFCR#&I?b?wkT)a%ZIay`Nw( z&GMERPfbp+9+PDuRVwsl-u}5V$px{&F>~&TL!9(&QBv5hHu7;`-Cp2@M{sULLKzdT zwe5>j^es6IIf9N9b=s#6oUNu}60L?sbe7omFAUifo0B?u&Vq=wiXVRzx&JsIICW}! za+t#KaF9YTA7cJ*2wSWLbI$20`_8qFpG^X6uP?+I5>50sHXDTlg&dt^(-J>g9evtO z6AV|_-@`fh3{hbc~COYOUeB4Zi32FKp&G1 zR6_rXF|c;JwPXgljXNN7ROs_OeKn>b^w4dCdzR_s>6JhXoCt!~P=5Rss{RwlGxEdV zWO0L=mcW?cTHy;E8k7jSxnfeOZ{qttZ=CsPp(iTt#Wn>xG z%)z43zx{m}<6yVRz7$b+ufOC};^k|yuH`%t>b=ud8X!4|@)FL8X4=^`zTBf`XPeos zUT&V6;nC8uHv>5cYP!1W{X4bG{N&%(~ zIJ;*%EjvEf#6Mp&SJf%M)S z#1;4(@|w+h3H})*xg{iQ>sl&%#4$jKoiwpomL0W6zFHd%#Tn~enxp>?{<%kK^ zk;cYd0G9jscM4S0F);sep59z>|Kc87te^x^_gS*aY{#LUh-$Zr?K^OMWvz#G)OxnE zXTW|XA?HsMdLlTM6y0H`V6p1MND4s7FFW-;gX?5VOhhe%KWb$r`*3)kj)TTCG?zV zdhnb?aV6N09@ts>ts%VI*_FIXY}`ME>K;c3X;{I~SGfCfb(J&5hm` zel_HmnS)KuI_=ig@nZfE9*gAu=_t8YfRC>BuG<0ihHq|{9NQ3F^1LnZn)w(oACxas z8}31A%IxWETqeGGWY~!5&Y?20DOvgZO9~;InnE`FzfBnC)b)wxp36^6@^y18UT3Cr zf*8X%o%F{&w;&)T_k?aqo47uW;w?Dc!a!%Ey9Ggi7?C z?q8p(1ppQu8ZKvs4=L+n<+rbq4&Pk7?!g;b@sBAK-R@BHeYr_*ERtjyqmR;ZkPU7> z=ra=R0v$M{ojtxil0&hK1+fVUs@f-JAMM08ZE2CSR%(A;>|+k#9pap;yF4EiK8|-s zuU8$kHBGn~L9Ndaq%`9kd+FNSt4sSYdKl*a8bfu3pD)m&nDp__7oR5MG6$F8JZw|MBlixc=gBO((FUon) zmP*;VEFtxuFb;@6-#qW=>$37c<4Xee6Gpe|oo$wCwjy&x>VOt9|fDbtzSz2L^vPj~B*i_cqG%`B0oipY5>o?&NCa_K#g zvfhv7vTUR6wtz;=12T7O%NV9mPAEekV9rqJqiwy&&a*YlL{M;tXUi*7mfh zK71A@i5-=>tlh1s2M^+y|GAzJG?tSRJ-|wi9KOS3Gt%UU2DP#~uCqq>4is*07@h!PBzp31m7<^I@*CnF=qm_0(YuwM_~s->JD_ZJhbXspV(mgt2yNHI&75)I+tK zJ~FphPL}$fW#aj|B!DXLYjAqpv-2WIWE$29jH-30Q~^#(u_b3WomAIYZ*lIiY>$WN zz6Ee_XU30VD-N#(u{0_lt6j&2jL=JxYlWt~(&kA;LWG?5f7y6oyNpZTlfY4~5> z0Q@hVby4=_uJx#^1!*n?pkS(uXg_kxdy6FO7p zmFJiTho6Y$YC8;!R4a2C&Y4>_Q!i?vZ z=1~KyN4~Ef8f}K}uvxA8jgS3gomQ%#em0H&RiS|4x>@}jAPYapw%`<>)M>vnZ^{8H zTQNFK)J0@*@NHW6JeSZ7T_U*Lx{K930b{V~>=#&E)1vs!RTY*$V(-%9D^1TteX2A5 zG}zPkkDg~3IR7MlZh_6?*Y9Z+h0lH8FP<4;`J8*Y{ogMVeN`YAz@ys~3h#NAwb2>0 zBp=k$hFzaDhKd|nu>~|nlZtoWUo*bmWgc{gZdZmWO@I2|Po`SnNVn?r+SC6VYM{Uu zWX_p04Q{2`;R}r>CZZ2qu;vz$X8DX zP*3Vc^}QOqc>PMX+R~sf=}Tzj2x9|hc4SPd;76`(2sh9D^%qzjH8CFI z{upL_?=vf0`H0k5YHZ!jVqWafW*URy)f(;%KCi7PIaF?W8z$@u0L|+R6fVP2SMpI( z>8&aU|DKoJ_kBI^&*j+RafI9}0J!TU2DubkU`8ubpZR4CcX&@c_TMe+Nhf0%#$1d0 zz-xSvX%zo-0>;GuH#}`b#s1tLOFijDM*r409G?WtXAhNK;k5!B!Mme^;RChTlNx*r zPW=S5F0EEg$a~&WdzHr6=2x{3_OBt~rbWu%_rvEY_cnwkgN&}VzDXd&)x+vJlUK{o zn^&9M`w8`iz~Jutw5e+To;6(9)lp>q=_{eTENGkT5*ur3^8bv_TKnV4f#XUSGrE=c z7UY7-I8dT$b726nNd|EMJBA)HDr$A>AYH(5A@u#k!na_(*z48rn+Z2&{&ZZ*(Z@CI zim`^dLFGuUVOaLl?|&j#zx74f&~BS1C+&wAGFnWajIpR}GWgwY7~DJ0XwuhtPdX7)=o$k zmPK^8`m^MYvj#rewc^Jz_`m$mNzQ0!ws^UI>%RX~-axp9P>_j|g;8Di&3`x4UDs0d zRQh13^S>MaVA%BJ;23Lz24`oP$l&Pdd+oQF<>-|iW*!MeP}||X934A6c&9L%F1=Oz z6`Sl8FNdGC?E6Ui95Y9>9O5HZmH9eI9VWOfbQp6qpWs$Oq|~ZRpx5^FFP47k!#@R? z*YCMmRe=JsVSLu2T%gS7^f+GWuYV$gWZEtUkaQCIx$NB zD_82GC8r3{Sq&h`Yz}l6(1KSz>UUFK!6~Hr4r_)@kcTmh)EXx)(LIWYYw4vRW#gxG z+>QNw26K+E#Y=Qema4H?3VP4m=Th-FNEws88t+e!{huJfFg=NN|)LnslRh3jej)t$CT# z-C%uqGFYj*JNP>i^foj8t(gdyJ16VvPFvM_VXXIgbkwq4<=h?{Fxh5mgPZp6gh65M*$cuo^ zP0f*r$O|1wgqJuhO`_|VQ;L*@rUAYC!Fu3Uo9s=FR=6I^#S(o7#V?-IU_f}*jj`5t zMwnMOOlkun+HD9Ha^5p}|K>lfL}MkZ$e-_?^Lo<#6?^2~x=O2UH|fx6Q|x7Q95Od^ z?^(D-air3O&*uPs&Fr5Pe?KHkgr#BUbNtDkO(eI?UO(%5&4tzG)kWBpF#wav>J~>d z)gIpWTT;%1h|-g-*Sj#Q#XFbo4^%Z6&U+BLb78966H&*M^pW&ottfFJ>950xOnIbmqmf ztly)uC%Oug(UOkvk4lC*DRVZ}uk+9TsqTtzzUeY=Cf9Q%5F3n37tkFNR1J5R3kQU? zza+=JgRbmU>89dL#24WA5m0~jet)|uQDOVFWLWNc(rNaEYKq47q-&LKv6$tJzG_5C zgh$QF72wqV8?8CJSoI5arT??tn>W*07_|Feb5zG*|9@MG2*weK{clrw@^480x3T{R zsQ-IS>Tk?S@xNx6Zz4>tN&AmUhFF)*CT*b2GkOsCUZZwXpK$9IGb^*a|6{cFe zWMAmDhdrynfLuLxFo9VeYpU4GAIpw}Sl^Gg(pVPA#|YQ(S(wEM9NovRtp+trXh+?P44z#ol_!pDslg4#-Ky#5RiepZT~F;|D{ z>V24wP|bQecFlgE`}{ret)9ztT<6i2mfF?+{L3;oS1l_|Zl7(RZ@qEvOxzzed`mwp z2I;A%mYA&*t3Tz)`sp(T?F)Y?=J+e*RYvhWCW=AKt&ZWj}<)(unz5Gc=>q$ z+mlW?^9NrBS7P@F)j{?Byg`!uum=Zy&v>gFChg=Kmz`_{2g7b!mp#R8r%yiR+gSqR zo0XVh4>^8~dP>_r&40xKYYEw0c)%DJi1qILZL%2(j69-LZL?{L|@^D`7G%_Ru;35{!QdNSRMP*Z?XEQ0}n>c(Z=36 zm-5C<3NNe|)QEt@ZqGfjw&dqs85zob%5nNFHf^~Mm?l6uLuHM#boLk5=la5A?2p|3 zld9!5gl*q!qLdKM!gL}!ck10T@0{;gvX1I$D?^qw^f<+qrMxlKER=0(|9gq^NWVH_ zW8kMxoyJCM{IM5AF6*nU5-*RbCcEr_v&VrKC@nm@a;%ZWAq;t+c#V~Z(d$`Gi;qro zH(sqAXM_Eh{@>Kyp@M?J)CFiRO}wq^Cem zXBM}C?pAo5GgalL)4;a`amkT}-ffVXT?{!S^jaGHhCOaicWHFYj@V`08J z)eNdK_KCtkn&q@&VP?rRF$DP`^)N39v-NIG$|osK*0qEctIcu@U*q-%?hLm=Liq$Z zpy|9`weI4JZGL&05vq%v8GtHU{YsQB6wQWFGvS@46NWBEJfIael|8&;*( z7%KYyjyZm(7&e66+g#Wi-@Y}Y4P>7_W>g2{L2yp3qZ|CgY>(n8pyam{9R0jpSXmRl zr4AVTTvcnl8dn#HDT=BI3vlIrUN+M|2%dBc;}p_TDr^n3nI@HBxTu9cpK8YeAKCsf z>kK7pVmMOND`zJPvW}*@{9$RhaCIoCt|chYeOUkNa*1g9fy~|v(X(Ks)WaH; zhESP#9AK@k zowSMG{Z&15`fxSAy*y5u*QbQ=Tkc+VMKAW-)&>Mp(5EUh4hR}ek_6;^-44u@o^yO5 zKkq0wlnWJTce2^Bam%W5D*<6< zFFkkMVl+7k>?Cay_HFds>6VPYT@TVe&Cw$+ni~*n zf(bYA`rD3`Y}kEZ#>2U3PpuC}B+k$?mt+SUIn*UF;VP`GYV zRC}vU8>P31np;zw7%oW+RdWSjsf(%_LbQfxWinPvDMd6~M2QY+C@N+(=bCa=%xa!h zLSvp4_4!}^wf={Ht?&JNIxl;_opaXS`H)%t)Fm+iA=OMO@&ngu?T2iW;IX)Pu;6YDv4^iHf;Is3_n6)V#~jWJq) zr0&(V#g{IX=f|xTZ$ux>)(N;cz^mjs{dsjI=7 z%!H!!1CDy{m;rCz<~{?uf=^a?Z~oH-1KuaJQgCf&{fr~1%0UQ~t8TmF57n~1Kx(q~?(E(+;Vg_3|u zAtZ#iQa0&U-uP{|*buV;Fzuo?zaW0%OrOtz$`ly2Gv!oS)J4Z@HC$31b@UR3XQbpR zd}Ni;99giG3Cy(9$BQHO7R$V+XtHwJ zE}X1B-e^xvOLqaeu6I{_4>GWN=PiZka*&EaKS+6f@ZxE2KvGNDcnMTK#b~%Vu5^)! zVm+i94365KUl96|4EVP6z{7p#$0g%-zfC@>g>{yM zyNay0u`fT#czyS+mB&|$T|4uSR7BNrI0mG{8RDPS9WhA7%_kc~pCki12QoqcHpHtsAq@Yg(ah$`#J(}$Y1WV)Gf{MAdDdMdc zOcg76RWI1&(aSw5X2&YcIzxTV0{$q$EvNUl?u|c|(*JAVyzXkR_)DY(!XcVvFd)M5 z_wEo&`XxMkNqz^s01Jd*hL%gH?(wm3d1ce}P|d{b&`c>yB%F%WogV>pR<9G+)Qyli)FD6wh-%rD zPG30dVl3~jHnrLvT-j-ThR2eo(b7%$Xmw1(30(=5pX?KF_yJd2nt2kI2vb=Q5b zQTC(;(CeG!f8}?$IKrFGJvyDPX(Hf5bNGMa2#?%M)ZDj0Y@yvS3s_BO2 zGKfc}WZJl)f8<1n^%ybcvo&Ic5EA~#VI)`HAm^|;!UWKL89idOo++O`I8sV%dGdAq zEU65Ksc{S15__5YjgJKhv)u|=_>-ua!I6D`ty;DIh0C0OdOKm_8uE zj%<$c8H!{+sRj0NuU_^zZUVg~b=hA5bY)Kc8L_UnRxsjkozX+*O#Eo!-~y1GrPUEJ zy(yiUmUXST9>0j#zs20xiJG*wsm^X=97S!u**hV4;ANJP5Bwij=NcIrS@*&5eT739 zB55(e_aQ65b`7vFUv)#5tyykXSdPSj7#=21=NTE);ozo18E{9uIevN3QwJLDQxl!B z9)J-&cQHZyBs{}6ZiB=Th-qWHRgbJ4Ov-39<>RqBsMQr-<2p@{e@WbEG_6=Q6_KQe z2QTfHBb(pD*jqQ9^%c44QEe0+Igc?Og;tAcbE&pfP_gJY!e_N~ntt*`)LxC@<~Ro8 z`!Q1ltX3kpU@SAJ!qC0@;t?7wX97OQU@^xel)Yw&BRE<}WaclMcWHK>HL``)!=~5` z1u0sN&bz&{>I)(ReHEK%)o2uJ_jkE(ckM#La85T+@tgrGv4gj>yI)T7C5^fj%t{SN zsT3kJ(!|nkVEDVpkV$RA(++D_59&p$KwA-HR8Cns@;ZAzXyG~l#T3fsa@ zZ$|8RX@2q!@*#QWt3}VzaY_wm6HBdn`>dGtzX%CjH`ym*((Fce8hWoGcL*8xfQoFN z4#8m++b5^&Dq>BZinxjxPrG9+X0#7f*#6c9;|a;jxJ6EdKwC)8S#H(y6tVVD%v;MW zZrZbj2%(9}7)acFMKzpVW;RD{7Yo4>=`@m(9x0S+-@@K#XGcXVW!0$ z7)jJiZ2wS0S&1akvzCi?7+(HG75y?j*FgV(O{?Gq#7Eh0?s^e;MLYH416(@9}%>k7Dulye&7Y)&i{>ptP$B!bgK!itE0W1(Vk8P!jOk zgNS4O^;sKu6Z+_6BiF}gTJsyfsx`rXIH~MuCW@%cS;L&|cM_Qts?#kFFv zca2Rw7E^{JkVpA-Kt?Zh!{vj~YtU{EdN>f(ZBku-7*$WH`fI*l&PQD?due+^IJtu% z06%x5CV4)!JBvFUv#UX$c>>&N?N70uRU+MCsaW3|!dyXl(pF1uc%|SKy-cnH=6SwG z*S}AqI1jHejJ|y$KQaS!yRV$*tRFE1C~MBu$(Awj06T`G0=sNg0CTF*5_Xz3%g2L* z=@$sM^gn+I_Qr*UP(&XrOV3QsX{lzzwk6w0$dpbm3`#oyfU~`t%KXARs&y5UX4w-w z6w_76>_jH0n(8o=X`|DO&>1a-=z1@RZ>m3G3JD{4o|RiM0cKz7JYS;&4+{5b8dIZm zy01`I4)+Z>YiDk3l%rE2GRvPxMAW!HqI0eF%zeR)(4(wb^Lz8DQ<^2c#dM9Uc9^%k zadV!`YIR1J7@@4WzV+U`o!qHl+Zrk5SV_dLE%t3_Lf!QriSL%SBhYE(%^;-}b3Ca3 z-UpAMq{0Q^{Wn<`1@Dtn8kKmcdYc`cj~x^z0`e}&f!zJ8Yz(?YAb+T{?Y_Jr^Oa_C z?e+bDH>2u-7?;RbmMwUN^x zE`xbMjm~*E?Z08l+O8Pllp7rT6GE-2XgKn5L29ydn#Y9@bXk_MY>#Pome;-u{|{@k zx_$C1cwq!oL-&`b?gV)+NQjco>Mb7!TN{f&^}p&?jQTpc_(7NhSwdy$D@WCuqahbm z5!@96ep-`;h4CX29_eMG1E9v8{wW(&8G`#A_CyW@w;FZk#mmsmcdGnU93MI zMD4=#gB{Ee>4uv{9my4>l)BoFFa4~p0Gf3qS(dJ%HjEqpvP{R9s-AfE03|;5Q+Pm` zIrevd(PZa}9}1L`{G*YW&~Ec_)_kY@7~(AFvRe^B;Gw473-Y}5F^MJw;7xR>l8p8V zHahrAyI0+Dk{r0n+g+2iRQ;^Rv{1EMl{(Shdsra32aurl2*>xXn-`TcWEZp3D;NBL zDG=N{CvT^Vm91yRUR33)ombt&DYD6biyC0S$(t7@I85hAzD50w_ttX^EmUV36I#kA zyC3pXe3fSkDy3I{9;3O&rB1UI%SC&?(#k@wkz_F^a}9!t(nm_HxVY6KeqHv-)_fvu zByapR@iw%{ZxoGH3|)y>xD4xjI`OQ{a9xt!YWw+BL;LUKHp^fIian^QDK(>U({wP3#?m!0$JV~RfP z5o&~cxdtnv@>^oz3~!A^gip(6_MQes%_2dk)irY0qJr*tQZS^nRCpJx>dL)?6n zKph)57Nl8|k{mBxX^tIBSa#THlotQP73(dFzV`UTVd*7|R7D)ao0S{GSpIplI$Y5; za3_K}VVhmFHrk})>@6Eu9YEO@rw3g~ZPqhrmhaP9@owT>!q;A);FIGPe5@l=UszVh zE7dHqOGmLb@*~)cy7ABQn(_Y|tpBI+_kRa&QSAtnk`e!;ec7Z2007A14eju5E_inY z+Ry#C092qVYRXUzWf<%(R0E*~N2tLRp-==ADq$I_{(lHQzHW~&0slYY4wxBzOaPb~ LS{M}Gat`}9E=kmY diff --git a/mai/backend/__init__.py b/mai/backend/__init__.py deleted file mode 100644 index 2ef306b..0000000 --- a/mai/backend/__init__.py +++ /dev/null @@ -1,52 +0,0 @@ -import importlib -import os -import traceback - -import matplotlib -from apiflask import APIBlueprint, APIFlask -from flask_cors import CORS - -matplotlib.use("agg") - -cors = CORS() -api_bp = APIBlueprint("api", __name__, url_prefix="/api/v1") -dataset_path: str | None = None - - -class Config: - SECRET_KEY = "secret!" - SEND_FILE_MAX_AGE_DEFAULT = -1 - - -def create_app(): - global dataset_path - - # Create and configure app - app = APIFlask( - "MAI Service", - title="MAI Service API", - docs_path="/", - version="1.0", - static_folder="", - template_folder="", - ) - app.config.from_object(Config) - - dataset_path = os.path.join(app.instance_path, "dataset") - os.makedirs(dataset_path, exist_ok=True) - - @app.errorhandler(Exception) - def my_error_processor(error): - traceback.print_exception(error) - return {"message": str(error), "detail": "No details"}, 500 - - # Import custom REST methods - importlib.import_module("backend.api") - - # Enable REST API - app.register_blueprint(api_bp) - - # Enable app extensions - cors.init_app(app) - - return app diff --git a/mai/backend/api.py b/mai/backend/api.py deleted file mode 100644 index 2f6d2be..0000000 --- a/mai/backend/api.py +++ /dev/null @@ -1,57 +0,0 @@ -from apiflask import FileSchema, Schema, fields -from flask import send_file - -from backend import api_bp, dataset_path -from backend.service import Service - - -class FileUpload(Schema): - file = fields.File(required=True) - - -class ColumnInfoDto(Schema): - datatype = fields.String() - items = fields.List(fields.String()) - - -class TableColumnDto(Schema): - name = fields.String() - datatype = fields.String() - items = fields.List(fields.String()) - - -service = Service(dataset_path) - - -@api_bp.post("/dataset") -@api_bp.input(FileUpload, location="files") -def upload_dataset(files_data): - uploaded_file = files_data["file"] - return service.upload_dataset(uploaded_file) - - -@api_bp.get("/dataset") -def get_all_datasets(): - return service.get_all_datasets() - - -@api_bp.get("/dataset/") -@api_bp.output(TableColumnDto(many=True)) -def get_dataset_info(name: str): - return service.get_dataset_info(name) - - -@api_bp.get("/dataset//") -@api_bp.output(ColumnInfoDto) -def get_column_info(name: str, column: str): - return service.get_column_info(name, column) - - -@api_bp.get("/dataset/draw/hist//") -@api_bp.output( - FileSchema(type="string", format="binary"), content_type="image/png", example="" -) -def get_dataset_hist(name: str, column: str): - data = service.get_hist(name, column) - data.seek(0) - return send_file(data, download_name=f"{name}.hist.png", mimetype="image/png") diff --git a/mai/backend/service.py b/mai/backend/service.py deleted file mode 100644 index c4a3935..0000000 --- a/mai/backend/service.py +++ /dev/null @@ -1,59 +0,0 @@ -import io -import os -import pathlib -from typing import BinaryIO, Dict, List - -import pandas as pd -from matplotlib.figure import Figure -from werkzeug.datastructures import FileStorage -from werkzeug.utils import secure_filename - - -class Service: - def __init__(self, dataset_path: str | None) -> None: - if dataset_path is None: - raise Exception("Dataset path is not defined") - self.__path: str = dataset_path - - def __get_dataset(self, filename: str) -> pd.DataFrame: - full_file_name = os.path.join(self.__path, secure_filename(filename)) - return pd.read_csv(full_file_name) - - def upload_dataset(self, file: FileStorage) -> str: - if file.filename is None: - raise Exception("Dataset upload error") - file_name: str = file.filename - full_file_name = os.path.join(self.__path, secure_filename(file_name)) - file.save(full_file_name) - return file_name - - def get_all_datasets(self) -> List[str]: - return [file.name for file in pathlib.Path(self.__path).glob("*.csv")] - - def get_dataset_info(self, filename) -> List[Dict]: - dataset = self.__get_dataset(filename) - dataset_info = [] - for column in dataset.columns: - items = dataset[column].astype(str) - column_info = { - "name": column, - "datatype": dataset.dtypes[column], - "items": items, - } - dataset_info.append(column_info) - return dataset_info - - def get_column_info(self, filename, column) -> Dict: - dataset = self.__get_dataset(filename) - datatype = dataset.dtypes[column] - items = sorted(dataset[column].astype(str).unique()) - return {"datatype": datatype, "items": items} - - def get_hist(self, filename, column) -> BinaryIO: - dataset = self.__get_dataset(filename) - bytes = io.BytesIO() - plot: Figure | None = dataset.plot.hist(column=[column], bins=80).get_figure() - if plot is None: - raise Exception("Can't create hist plot") - plot.savefig(bytes, dpi=300, format="png") - return bytes diff --git a/mai/docs/path1.png b/mai/docs/path1.png deleted file mode 100644 index a94aff4e59161e7abd4c8c20923a5596f7094c49..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 22640 zcmeFZc|6qb_dl#nNm443ElJ2QT9CbXQ&EWQ%rr5|GKB2Lv{=eEh(WfLlEjQ{h75`r zj4a7IjO@!8%#3x$@_VWG=X-y@_h0wp{^!2$$Nl?*@tV2jdY$WB&vVZ6I_JE+G&R1? zckt9fE-o&YS3%Tw;+sKfBNq3^*5;^}d_`T)P_pp%3lPaDt~TcvVw}mW!%pU;8;Q z&NnUPW@ShnOS>9>_T-U$Cyq#eKJf9h(w^Oyl%9W=e17o7!7m3>xtrBwWuF;w+hBix za{FrGKT*A$F`qXzMLB5zhF&%~ zU0uf-V}y?d1qWX`CS%-s>-A;1TWJ?};Nb8C=N==fc9FMn?|tC%MG-$)AfAMlkT_?O zMeP5UK=<~wX-b|vDrMk=q_TSmyScdD@IFRZV;1FMeG!g4t&XI)AG5^gz+6w}fBM2~ ziVmYiR6R^@V4i?{sk?yTS6630;XtcWlz7mvXL+~f{8L~XxxSnMk-Nuvj-5Lc=2W@) zEFRe5CuhVYFcU&+OI-@%Sx!7{)Th8WuKQwQnCob9tw+i>MIayL9dvY0_u)Vis~@h} z%->$|69?XD>Pmq1L+)U()nfaB%c#fp)|lWVo)+NmkCAZ)$xPBeOJGLx1DRlrL%Evk z9SolCxd5}-K0o~Z<*|BN%Qtdcq~;j@%d`k=37-5lqI~DgMSm!u~Ugp#1!J%K0 z_ovDM0K($t`u5bd#FD}@QA=spo(AT*tsb_Er4D5B#{S(FJRg}^*&>kCfEy~X=V`$X zu2(#LlMy~4HP7!kHe_hzaWL z!a-z99zb~7qi*46c_c_nQJhXRA^hG(sI!g&whoe3#)?bKORF(MReOk75>BWBCg9_Q12~2_>A!y!GG$p z#rh8kO|W}aNW)cYJn`#i?tPP8{D-PE1MCBO9h1Lqw91sAlUb7njypbc=c^^5c;+MO zGX@h`bLB`9)c1Eetf!6R1nVEryn^imfhZls(dvZ*6o=(z91V@;T?n1~h$A;5>n)|$ zqQidZ{sBDx5Sf|6J_{lv$y8(I0TCH64_Iqs{~lN%Z8cLAqiC1)at~`V$EF54!tGof z(!B+XT)^hczM(g@`&W8_lSaP&tB8 z(7EDSLd@nPQ$n49&5m1!MM`8G_X~dLn~Ll^=+F02=dV)X)))%-ENFFUsY0XsAr=z2 z_6DcvMyjq$M5OS^3T345A8d8)7q5!gH>{-qs`5ehF}7aS5yz+_MLEKs7-%dF#mxH zHc0k{Hy9Dbj$_E-&g)-HL{q1bp$O}Mt~A(sCasRR99-r0Fv8XFyi?;YRmJ?TpBs1w zyl%!yQdovW=XLFJ3BZSHl*6sFGy}Z_F@yovfY9|HykyJu-^AvUPyx&XNQHK5e*i=< z^+Dn0o2m%sj>LoSbg=_Ll3fvlYlcPD1GHGIKIsLAa(eEEST99w+)b=^B^g^?yyIdwoAc()O{4=w#Z%&<~vBPURVpTE^~5e z<+9aopN7HJ1rY9@#&oZLZDC$93xuf80BXy}O$QhkYMi z-;vWu0j75Nt(@(sTG{dC)ya0=5z9fVt=Lt7EId{X{f0FFqqg7gfvqnbX8WaqyaSy9aqrfA$M~_|ATh%c^&`4QRot9IC4m=ah_d_ zyVp5-tN*v=yqE+(YMG%?dI941YjeaCT`N!YYTyj2rQZb9WkVp>`UTtAMzP66h=zin z-O>L{h>>p*z)biZ^2~cZW1%6gC9A|+Dec&DI9MoRaz=v)Cc0$%)ES`z?wM}aq84mM z6zmQUSGO4M%*lS3KQUXP0IBY%eE;3|)Y}4{+8v!8aUbF0+RI zHO@bQJrO)*{XW34NyTNXyMMI2_?lYHCs1y+peMo%%c7~Q54iCHing+gfM0;sg@Hh5 zQMH|02KlsCEPfJ01FmT_RCVJZPdf@Zjqn&c9jS8?;{E-(!qL?70GQ=OI9!qv9i>_$ zC=ykjDCB{-XMBPJt!WbhjQ(*p5JS9cy$c4Ta>m6cYuVHO8%Hw6;E{u(TOO#SmNKw7OV<&G5Pop#1sylh;lV?1 zk*d6{sM3YrIvqcodp&9@?TTmY0b_w?G+b@=|_#6x|VH+Xkq z-Jv}EVe;>4~jk0Uuw@isK{KL0~|<-Yp>yP{}8s9zV7g^yV)OHH_F` zW{0>&_@4&GJ+UT5!XZ5mgBH>V*ELYU-@UB@cL>LZ*h^K71#{tDa=V3}*^y<2@rB9tqs<1=c# zJ(12l`dD{&nSC-woB9-3-qooYHqQO#BMc{Xx$6=zzGLVBna5k&rbyN(KyZiGAISx% z^_TtsKR7}isyh0P6d}AnTR_mGLK##uU4z@0g@&CN-nwlaID`tPdmgSgm`w2nRnCpL zJCxL{%Rt3~8sq#|-*qjmtVG;=buPU5l}zMJS6-y>CFiiTOAjIfS(Cf?WZIPj+is^_ zlny@J;^S2p#smBQ;^;i9yz9|c4yY};Fdx6}Q;u1DsK+PiF2>RKDr$BOExwQA44ox^a0-Tef3en`pO_DAc< zCrGphf;E|M%@>4(-%yugJGK3%TGL*2m)E1S)V4c78S=~5tPRGNVh)wY^&PPcVfA|8 z=A0-Q_zO!h!c!6{Fu~fzMebO?bM5fJ!;~o&a5l12Iq+x;R`IClR~#-T;-oU%(#rm3 zTj|E^R9$L+^w8KP(eZr=sxFVua|Q*OgYz>pUhUx{fUuU|D$TU&F3x&Pl8k-o9SN@k z`)uaDT+gi|VC$XfNUtTxktco+hMgwV!0pI|jECpibjr@OB{L6@KNjqJK%M4p^pKIz zAS^3wel#+Ej2ubW&LM$!UzI7jcC}`;E!H`{5?D~n6|1PDm^(sJGRC~oU?PbxYPxjo z?Ly=o^9NNV?9uV-Hq6Rb>`^K33u-i1N51=kc%Pg!9oNYXJ&h6j=Ihpt9m_F?jIaT} z_+FfJ@3+wT5tkAyO1q^EElq}oJaNWJUJcEqWy;3_>+!3vOf;}=j92)wsI7Xkjxe6c z(KC6j^QwOfoXL^uq>qbsu&%Z7RVGeksxH?7<4sE-XA zMS7C8H$Q{5H>QP7wr-``XxDdZL`FPg@n^p6oQjI+H=a5O6IPya*zi;3daFKWSwq&U zDUYw+#7b1wizxr@I-=x1KRB1cXnSu9z`N^Fkvo8)+k&Y1U8);7>SXMe{>eLeoRsD3 z4~Td6tdBe9FWLV)_L%aheJ3Z0G6SsPohv1SEvCAbqvE5Dd>NckAc-ou3keDHf4k@8 zt@f0ljTdQvL@_?$I89Ji2(vlHs&{tB6!%C({Epae+tRG?Cz2B-UNuMaTa`cYUNT(# zY*QMsG;{K2F9gY&+&z%Cncr-xjk0M=_CsRNfK=1MoaE@IFzZXvjj1SR_dG-Kd4cU! z#O3ig2_32yq2>36o@$2=T-GWDp5doub%1>P*Zeh`EyHY~C8fvms#}sVX{Fz_<^#u3 z>lA~O4;s9;awyY2p{=PG<^xA&!ggf6nhBhE>wG+X z>K&@9$ECqHgEp7ou%#`x!O+b6TLaiC((pT-9@p{hU(gUn!{dYKYv__&<9gmwb?&VMAJ3K~x%n$!O}oA2BbMBjDw)*_NYCG!t^;K*9_f8IWipR% zO`*1AXg*!HRpC}`)qc-#gQqi(CpF-qp@V$>%ah^bsbS7oPZ?`Q;cx|MSjzK782sL} z>pH{xQk#yxwLt-}LF}a&Kzx_RN`UKav9h-_%2RZ$#kn&DldiYh|K_eT=(wuMX|>}< zq%26E_1C*M?|{qXT(M?SnwX25j*;A4y zFv)za5Ts1%@=Ko~(zn-2Fx{2WuIXVA9@bxgzNsM>1}{r@4J8hKW|&HNIMI8D?5=1Y8K1$lC6Q|eyb#V_F* zM&8EFtR9Uikjrq)f2ISDnXLLml^<8EKJk!)IN^K8^Rj}@)2>^4BpUOz-0uuu{gP93 zG^(z|9qigQj|rLIwd#c%=X-@a^vgsUR%tVpeFpR{xoou33`kedh1xY)w|d&RAM8NO z+f>j99Nfg`8*6$zj0~~CY~c%K*_UHoDXJ~Zf^2_@{RP6cN|Li;7+=lGS{sUyot={% zVMyVAiA_kg1@2&APnm zFXd<4-FK~f*u*1l3vMgl9m%T@jqW+TE6pSm%sQis2pe77lP*r__v7JBDik8cAKafHzWrvcX{m+DG}9(ZQG zEq8MnPp|FZGCc=UrEQomA0)%kzOGrn)aNP~8v~?>->Gy@bUxqfz|C;JNi#D^^Wjo+ z>25TRcvC)09$r@>6vIQlZTk49a>?aO83bKx%!2aXscnt@NXCP&lpCW*khxK9tV%|Oy+HVtRj;0)NxK2F@k^R9NTH-f^l7si0#J1a6iT*Qs zVJt|*X(`|)gRPX=I4i1EOzNU~s{IRTMWRBz`9vBs06mbpLB;uBx%oJbw>ZMgP5y;OE_ z;KHb{syc`kI_oIV?$|rIOjwQ$VOe<_|H#zn)tdV3oQe7*4zr=X9~U!1LRpQB9@uv2 zt5a5#+}*FZ>jSnQSM3$H2|jrmO2Z_KZvOQVA0Rc)m$^Yx2o&CKSAE_ zb~``V|3tyFLLD7ahyWF?_L$NK#e)aU5Qz9+Dt->|XC?GkLb(xNOags!XXmyiw7|?~ zr(u<7@pnW=)8iOcT_Wd&Tl=-)dT|q>+YNoL7}A+VQ+Kg}&k?f2xanaV^y)Q%GD{$xuS% z#n{x#vM%3TU1!KWg4rfHtk)oH;x2>jBVsV@(;6}Hi!Kzkg7p29q16%O=lKEF2WDRkZrke>WEf|BEbzVNM!X+ak-MCCq2{rLR z(rIjFPqJ1V;Jl4GUxWBiD&zemss?7@`fP4tt3>4YEABvgrUWj#IZ=_DB?8#B*;%fE zz}I5H>E50JWRd7XpKe)Wbghft8S}LYP>H6!2Tt8$?HIIMC7bdI7TElrzY_giS|(IA zY$6~dpsISaE-s&S`3xwpvCNEyZhlR#V3#j-3G5d%no2l>jQZ}_zXgvX2v&vWmySRw z7&USIzrID)H;tt62idyAR^xpWVtdp=nbrYx=By?lePd_h>PFd|g_VOI)dCKyFWIDW z_g_TJ`K8sytQB_yQ}#l;$5aljAGnMJ&0YC%kX#s0^c~h8dMm?T*jS9ej;S>B{VQ?$ zEobmQOQ=TbQuroXyi0W-*<@~9zxkLL6h2}5tdQ>`^;C3Y3?bNzMwnAC%XCO7(lb0C zKdosN)iW+vY79d^7;Nk5N0xXR!zYU+?WXcqR-Wc`aGhoaO=UR1~wE&(r}BR-)9wGa0~`i#SG4S7&3rId@{+j<>MIM8Fo zVBgAqm`%?_rUa%8U=(j*Hl768FPpl_JmkTM&eNHKsX`tV-9Yd=5_u2JNA?R&tGVEr zF@m4os2T(U^RddzdhgDF{I9NhDSIz%s%HU;SA|tMJbYtRSp3jK4x%Hk9Kn26;@*p3 zBh#)5tmYe}9g&{{Y@lD=!E>&iQ7x||B3&H$=>eEmB~U$ z`(S~ozGnBbyqbc5(50L9wE!_HU&pK_XqhM=Pa)FVLwk{;pQ%*p+`fk^bN$ba=YzV0 zGXB^`(p}k~jNBXdVrcph+43BtXw|qjDbFS^hdYmq_Bn_=s`j#=vh~l)@(y_r`oCrn zsK2(x<sg1i{%hQ>qu*c7t36PrZFH?3RrAp2fJxSI7M~FP z#qJ;DC=DIUw$Z&4pbscd{GH0J=%Gh2Kw_!edDmiE-+h4O9i_tEFgfy5-G;hEQ?#PR?vWOKa51EwOoKl?}@ChHTRvUT3k(@9^6qjt4^&mF2=9x2@4 zgN4_78V(X}WjlvYz@f+X0?J_?^8-p8Jgb`FDU zSviF)5EuJcWRX&FcWXrv0FssAk9F^5`PU_TR1~O!KiV>qM~=J5>>|9b`KdiGHB7Sl zDB=Q8)k@OvC6B?1xqTlKbf`atBzP`Dkhk<6oe!A_@D8_l7_9IUeByFAADLm{uw!oY zfb`acUV6J;bu*YvmQV@CRx?|nJ9II>pm;JbRsg-=Sh(1J{Ppj_th*6(nulmVJY zzP3NZ?!uSusD%xcm<-b`($}}bI@C`Gia`I zG?PE@lyA{xURY)GfSOXf_Uswe@f>ZzOrP}NLDuCl%a|a5=65$$N=?Ow&@&x@!CStr z)_6j9ncKrz=b)k{pB4=XW*H^eA_k{UB6S=2NTImXSwCeFvy!Z9j0_ zewVpLGPX95Phc7R@_v7-oO7bopzC*0cyKc1RhB%n++RGYvu!8$U?Hp)>fJZb)~S5T zUoN8TD6$%mq70n1=kz~zZ|_V|&{1IjwsorELld%%9@6l+bLo6#(p!@!SKWS2t!AkC zM1&NzzE&_bQ6mLOTS=s6Y8Ow?3L_-VL1kWyW^W5eDR1 z22o_gH1j<)Cf-4=7v7VitiaWZ!}^|{o-4b*i>Tn#kSrnQ*u4eOQwKRx&Oj>bQd{!31LTv5 z;ZxKR?rYqok3XO}&p$Q9Pko4i9 zdoR9?Us;Y3TaX~Bmx6;fZk!xy*}7uW_R^qsT^^7}q%HX}kd3?ltE{qLqGxgU88&EZ za1U&0PJf=^ws&3g7N^#ait9worPpTg>aEB0xdK^|%tuAzQlNJp20+4)x4rTQU(}HC zJbhl+ZX22?t7p7q8G3a0scYI8!|YY2!QkftrwcZ`QxdkqQ-&9IGJicIB7zGdbJQR?N5Zqe4gD99>#Jx1@Hmc7``_9>{IgNMqwpjBMy>Ju14qwUa!w zj-mJwaEo*4^*`msefK;pu=Ap0>jt}1B3(Fz2kp=gH@7oWBv(H-N7p6EnX3d}*lqig zDA|%+TpHBt<|@_B8=vqT;bF+~Wb zL3@gU{JIk@arws;CuG;w$EHV#+YKhEN|M3X643&QLehbq%Uf3bm!E0&j;pC6*-LY3 zvh583F~JkhTPn2a+&c3)wc^(<6xBj`xHC;XGryz#}4JoUYUuZjA{zAS{33hi;QkM$#9f%oQlQL z7(Gd=Yc@aIXkcRCn6h9p&}f!4Z{Obg}UVgN|vd~c6#M7SZD(%c)=|@#jb`ORxPq^7V=)XVQ ziYTTl*o~gP7cC^&ntL&2=Y9{Og_wWtH@Yb0mU1DiFnZPHBa(GvyQ1l&AqnG$hZ4otsVmXZborLH z0)2dcjXpwwE(4{U8I#SACcV^qt%_bD_^Ri{6-4#qvu@T_^!cgBmAzUKut!uY{Osv* zkpK>NWv|pvprwW>V|R{Y;4xQXNI<7V%NOmV5+=JZah2__^X9<^ET0LLilZSC@LttO zsbp14y9d!j9{q{EIz6yvDl>*&Uc9TlNG_}1&hr!Yd{x_(e}Wt*iZ|ie=B&QuAS)!|G-eD=YUU-EP_M`u z75jWg=d&!QEWjqaSJ{1gQK zJHkC59%5%kAp^K7P{4bNbFL)OrQ8{DPvOz{LTBnl1l-=vEa!YE^?ekO0MK7h22HxBF${gQXWJ(E$>u#u~xw^;|hr4_<(f&7=|p`ZX36U>&^NB^1e9{XUKsPdTszB z3}J;w$E)^MRDZsXzqw-tE9KGvinYs!XelI&D+d71o&I9Pi=U3OH?^EEq80Eat(af- zjDY-m@ZMKJp##WLgnLE7@&(yaV-el=zb;y7)s@6onj=O{vHCT57LYh7$y7STmH8BB z{}p4an{+)Isn;e_b;xd1>3+1(UBI9Tlrf}n_-PlRUcUF930J0*X21w{2Kzf=lmyD^ z?FmExa{i;)Yg$)=aO`y_7~K?;aY^|kUu7(!1o#rmYQS|g#vO|cQefEU<3v|Y_Bp%A zaIy#Xb6s_l1Zj-_&^)YcM#P^#EDjNwh;={&yyzD|!=pc6ayGhCEoSwdb7t7BwxTEt z$@;#_I7-aUXb_xbZs@ATL=M)@5p9{`tbosVaV29d_CMRBrjil(S_1S7wW7`LdCUVN z*Gw-BIco9EWvnuY=5>Uj-Q4RZ3I+u~)i{9}Q*G@biSJ_- z@=YfSyX5tKde|qE9P*@dE^Di(n|wlP)t9tRETika(}2bwo6ol8=T`$TYQ|hodaeTH zCaN~;5}u{djx}+EqVqr~EK{lT zKK5PGCTim?x>pbwQ1~1-xYzy;5DFif{C~D-y~6@lnU^OMBciJKr$anbUHMkFwivKH zv0E3jooWF#2jUG9zF=Y%HnGzXzW?D)nef`5)|6Ku*|ZLFw4B3HjEr%{w73%Rt;Z6T zU0=yDS#kViX6^ok(*Ut}qtSfA8LS$lt`0(mzVH>e;DY!q{h=ZqzQnodo!(-uH?)BM zPQ4vQae5a#`>q}gUnAV?-dMpOq{m-)p)9U}Po=}$l zA>HGkEitJ5i!Y5G9QL`k7g*<;{y%GfS7uvR@~3gJ1x5^ zjy__30)<7OI`)4WT2~@C^Uf-j2WWqPWAR6Y1};FRJi>9^s;2i(uUBE+AJrMkAH&e; zLSJr23t`}PA)cj4cX4>P4yCL-_h1`;;^7&2O7)7a5kw@jHp?eP*!{o<^?Qm!EtvqoMOtza%AXs+dWmBF3IL}JIodTi3$j*leWC<3-n0HfcDy7#Awxg6-W?@7+T zBDk9_&Q9DmiP~@@xFu})RfT{N)pT3tEFcAD?`gYHUml0j;~JKtS;W&Hq)+?|De32XlXv|#h*yOqzzF$G zIwR_N4)<+e4 zsV@x&X!*5Wkrhf%^W7qDmgRI5n23QL(vhuZtfc*M}E7A<>wIP85Noq0}Hf2*95EI6~!O?s>e+_UJ~ zR`=D(9|iQ>*ibP-S721nd+EcDwxe`QsY&Bl;VuCzcJB3M>xNB4MKQ%Oe@pJCv5~T5 zbNY3lYIf1`Jg$NMIM@cxCc!$~q#lck2q3I`Do2qxdM*|jGUi7WEhauH@XbGi94%%w z9$T3$DeFX;)Al?G`s0vdelFd%Hl*TH1zl*}lnZ4|>F@b;yzIn`hV94vY{%W`Qiy65 zxDheS)lh3{CC&=+5=i9oyS$@Z&VBggC5N_BB0Zmdf3@KCoAJUfNM_Q4`O_Z}wYGI> zt@*4xwpB0@$a~^vLK}SgmB+)oTzf{B2_$)J0OxmX-dsf>o$F23U-xiX#CbfJ&)ST+ zJ7GsN6fXp0z|F3(Yhi*9|5`;i+8tcKQocz}s;I>T#2u$tt>(GElt^C-$Q8d14jZ5| zPMNoGOH>uP)|nBF`I7uH?%tC>HqLCyQ27{yi0~#pMtZwDRS^Ipn^g4v7K1G$2G&|J z+u7qj6*K0*uB%#rkJqy{aPewNMA28}Y;$X^BuYmV=HI#DDCM~|=w2~`d{t2@=E^PG z*i;Q==UYa^nu^*Dd1;7|sO}iO{IeFi$Ovek}RF z<|2<*@6?*&yIb>}jOp341wOqOYkGS-s?WeZc1I`T*1^9~82WhP5znDaOa@-g_Z*ruIL|O)-0|=(a zJAG%j0+6iTb_zb{`%#%X-M#pidLc(02%64*A;Km-1swP1aB9tfZ*EU|Z>{WFPuUAC9{yAb0Kc?e#Si*y3jHVa`%`k;vGyEas>wW$toQj9)I$@nQT;dN!Xy z{-_w?%th#(;$4Qla{9U{Vn!3;nvy;PUPQBBSlM66S`a@`2Y;eN?lWg<%?Gx1;AVNz z$3BMn*bHNFvY8ifpx}QUD4$I}*F>klei`BVxO{!8<`~|P61@D=#E|H~xq-CLBbMLb z5VdWYar%H5mp*g|VB6c034VO?fe2=g_OB;Wl17ci`jb(;?`W;*m%v=M@Tt2c4pZRL z+HP^M17YbUP1(JX!dfZsgxR2z=~J;&4o~AI!d?F3x&VUmf0K-4wH+p3dJw+vdWNti zWYgYxq*Dk^A?^W)!jt)tKip{|kRvLHuT?u#ve?8L{2!mZe=uBOV+{#ykec5m;=#<} zu%_Did4)g+q6HN{%M1H_Q=wF_fG7GMOZ_Emq-!>T``s&UnuZPsuO8YzSL=CY@!kGk z$uX6~k=oO3KudE+>>qE_dvAU)5H{s7d~}7=^lfBO%Bs8JXtuh#XlP%~$cuVyLG8fr zBscGtfmd~EB5emrA?&7WP;zRdSkQ~A9fmm6v_n3;`2<1s$5*zeC1FEpQ<3sDH5W#z zEGoyNp?n3FVj^)+~ zsaiQG(YO6(F+uOJ#G|j0kqGZa*hqcCCOyy*c;bc@5^m4sGH}|6^1|-v$F&^+i>+GIQQb3>YUG%u9J0 zt;k1l2yn3u{3cWv#o}bHhT}E{+ao8YUbKh9MYM(RT2-T;jq30ZAOe^yFE8sLb_1;0 zMJQaX2XP=$G|*|SjZk}HYhy~sYQleeId8Fpg*q@CGDjGZ=iff3$;n0?LamK`2oeU` zzyLP=a);SYoN7v*7^0Rx5KNlVW-P$k#@Zv)(Apx-I!yP}WltTxQt_gI={(pZI-BQG z=+fgapj%&-iSIl|6gQZwDA9+1NdL*!zc@JyT41-Wh9wKxzjnBt zwRw!E1t}TW_}t`y)hmuJ(>ytTWS&{JD8 zzex2-yjcfjsO)HW&ceHUxBt5UCD6rJxDe{p{&^!ze1^l#dHxoG#QjC*9;`}}6@*R@ zET1v2-Uz)MQ#F#HG|#?X_Zd4}X=9CfL}a`i4$rJ*m*Q5-b@+vJ7HRGjG-^xt$|@Ba zQJJDCM)e*TgE1>jB1#vw-~qoMfSsa_}BN`+zv|%>s!sR6v`m7SFsPQqD`h|GVkN)X;4HfNWS9JT{PVx< z!1Zr%t5>KFi9`7#wHC|+k3f+!hPp_kmyzn+j6=@G=+GFCHu&1ZuV*h*y>;L7Kko>D&K`K2 zIIww-v3Ce22tdOuyhIDv1Ls3f`yahy3D3z!{Mv z*O7Hg;30AClG(LuFq<0(FiIg^$7=ZsJOdOzuMKvMh^6Qpi{nt+>o?oCv^UOs(Zc_S zV!7*>!b1G^x7)PA>-d`XTUoLMdnbaOruuXZfOSX2jT$^y7R_$dgAE9I`T)DS$yQr{F;yOZo;rNq87TTrrbj4V-Z^TJH3nDzw-+cT=_-grKbhfwZOqBL-U& zIBEB**pOp{FL9S!mAAs1Md5MSw$ji|_8dpVlh{d5vCWf4A`-l!*o{cysF(~r#s83F z`O>Z@#{Vu`05c5XAxHN(^!Y2Vvkk8ng^d^6+=vT(iq$!bW*bPKeE@j2-QL^X01)g@ z>yaY}C>z$tW^(ivqzREcLR8UnSt!TUN05d})dj<7 zFswEI1P#mkuGc}x;N>gThy*wJo)FbmjR1sn$AUNpduePHxceji#?=?3 z_;|Cs#Cy4tCQ-y@q1aakt;*XxqX|%qLqXCnTPGc6RIdpMQ{$ESURwN}`!>+ivThr# z+GDEgkhbVTDuY!{dv#tFdxh-qA|?_f0O&l_{&PN1p5`Sl9O5;pJRS4uO~#OSr%>X4 zhubOu+O1xd0@fxSNCR)n@-}-`jYh%>$Px$aAeM}9PQ9HDlu;=W2Efa!bG3fE8aKMJ z5UHB&5A7QrjN)4jSItCvu1#H9;Mopo)EbG+8xq@^DLs)#J+b9A(2`XAf^QiWZl)i_=+6R&(Jr$enswYjnM{ql&ZBpErWj3o zpUqe2)l{~8F~Y%z8Z@fHAmZC-c1DYZ@AAELCVLI9S7GcK0y5W2R5#`6lNC9H%wS-V3Adk_%75MZDR#6&@=61G8k5C=5 z{2|&B(Nh95<=l|-nYiL%e*7wneGs4~m$UzJq^0l)tvVIAHZoApek0$!XI0v2H}g&W zMtzN);dQ9XfoSRQuB@C=_)8PcJ_zKt6qt30KY5iZtN?W>*v7FOR@8I)BTasGYF}`IP?*Ih zEbtFfuCo3Hfo~ax)>N+)Lu+jY@tb7-V9KCR^4gt~Fwe^P_>lEI$ZKj<6Qlb_3IV_L zNO}EP%^PAv<*KDFvl?lY$k`bLvU)Xv;pJ(uxd8;{AmvJdBxrCQeWX0QQj0jbMyXrl z&mIKQ3VN@PyEt;J@qKiB?QuIHps2&=8>+x8pMU3nD0h0zcGPcRSX=@vNP(_Oc}j#~ z0_IDA-d>=wcSYV)6Xr?kNOVn?0mn~vE}vNLdLyS#X;v>srPY+6y)=L%7q|;-k&E6N zKmmJda!sH6OC8_90=IakmQlwuswYNC{osY0H^lGkIG22ZB)}K}RnrgGA3M^a+}vGb+J~ek# znjRt8z4Jl@uqErZc%x#D%;UpDMbg@q-I!lqvgV_ekpobm1yIiGi2OlvU0iyvqDg;; zNLOf}RYW*no_gq=d$G|%X1<3!hXP0NbAu{MQ?dKGhQ9wLqa`>ZYaT{rOaUs_+u?-Z zg@#pWPw7=@8IQ_<(m`*@YwN^?)nV`A8AETuB$Ha1stMf%qaHg&Dz0ZQy!tgrGH|)j z#x!*K0wK(cQ&bo>L9d_d4}BHG(qolSmdOGAN8oN9CBJe=VG4-OPfa-j0t`3F2q4H`S^RR|R9n)*d z$trRGP>Q=A^NpP%`ww*uQnpzzng@WCJ(03n5! zssIGJq%dNUT_e2|iW9(Cl{s7Yd^PzE#}`B}dH>Sh~Ld@V6g(gt7*KtMjhyz{8Pd%PwXp!+426Ze0=`+fde;Lh)nKB_kW zAgnUMextq^Y4u9_Y%TMKm(NMgQ)Spq-bgql?+|6D(v>@~1MYmpmthFcpspJ;G5U^nr{iKYY{boizg;ERl zPHX{3jN9TB;Qm4H&h0yoJT*%fjw!N>&e5i%0pjhyv=7eH+=*<)wt4)oX0AOP%5{rt z+ZBo0?Hy%ENQ%i&kz9su+GtahaT{_gVMrO*hK{gziAfoe&1f6KxP=+F!N$&{A@}Pr zYA`YkX55Z(JMRq7bI$qq?0?R`-}8R!d%yR6*Lv4lzu#JwIhu+qIDFps<7Pi^R4c1V z)oDEskC=+~m~@LRJJ@M)>Gz}xKS$VyCDOcE!YnF6D{+O?kKzV%wK|yc>eWsu>b{v% zrl{qmwoWVWO-k__#Jf@Rgd%iUo~4>QYiE~|UiMFRPtvTLaFt9n=n|wN)e_heTyU|e zON-zH5PgCZISfO>$JjZjdP&j_Byy@q=^$#xY$?D|37X%Cc8eZ=x|Y~1`*P6>#3wVW zE$$$Gtow6f<~MBDa9>wof9FJcQR1YgIavy z_kYj-HehkO=!?^?rfJX7!u)CoM#r4XCapEd?ZjrjY926$e`1<(kB1aqmJ*w1uGTLi zP09EN2|LF#eP`;%nc4p!HW%sU!%l2+sJ>#G6V8SEG8thPZ7Dt;v}g|%G`ZlX6|jD8 z^!>^lE4Q)Md$;sKcDT9>$8064p!1`;O`RRw<*Tq-sMI`!J+qRwBtVz7t}S+O$DB_& ztyaX9$18PG^~oitq@Gs6#c@3g^FJTLEdd$<7k*Y5N_*qsRP75?W;*M9sJFP(kFMzGvQknBg(r7pa>n{p4lk{`|S zHBIGi`hVeTa{olTG+gD&-#5FnwxN0#{~8*)jD&<5b>E%d-4~^$kkdawm}ZQ1Ffppp zH^S0v{Vz% z{smTOOYCnla*k=z4zkX>`fk?!klR)oKp+45q7l0XZ;$Cb`m0>HyRB93D=cRIW5L1b zJFPRx8BkCic?>LVfP&DUYxJBX(;5Rwzs0Gbz3Virk@pBU;;8`pSH(==Y zJgaRVEvZOMpMrTex0Dt*S^lv9Jrfx=bI`&u!bW$U(zZ{D&R9vWDS@ZR2koJAirs9< zt{%xo5viIFZ6+MGG-827*?4e74><|1bcjz|4MU;#_fV4xrgvXd5i$(JJ zsz4v13P_>}AS`a*QsZ;|7S+?zQU(jZ6|)KGuTj<(ZI4)EU8ji_jxti~-S5A?P=*`+ z=A+L)ql)0?@1v%l=#5q`4NJl9sh;7^6yNVS5TpSTdWl;Wub%Z8uOO{~1hK~m9EyB@ zsVN*OIjQQ_oXl_pqfTtyMNbx^#}8`nc8?XL;I1od{pvM%6KZA+)v$(=?x}Bpo}f{C zLmmo1a5>=~fVYKNUeIB}sp>1MHIm1J8L_sI^L=0hfW+HYzo_a+&|+R0Bi9fFn zHQ-T-dF+YPcGqVzjCM$Z_;e8DAiD-!2F?r6_s4>x0s>)?{~h7ZGF+Q$yjA%%1~TLi z1jVEZMJBR#G7SWh+w+8GGxMxuy;B;x`^HsaqbhS@4(NHOAWxBDy$v-8ho9UUUKSed zkz2RMqwQ|$B9{z%7ojM6ikK|M6pUWx)I5|6EO!VKp3CWJ*Rq;AP^C~}GMv5s?5|OF z;EEplxlfq+AY%TXh70YNo($UOhI}%R0*G>dzO$F}vtCx5ilB-#A3lTcvm9g(F(|K* zfdj^vYrX0A5+WJ3+w;X-T4qBfC3sB=eFI08oz;g~(Gmr*h9EKiZc%ewDwKo7IxlsF1YA(XS<3> z^+}=t;2WHtPJib5{#^9IR%C$BWd@harntGS{^bIL*?J){UY-0Qgd{m zR74!gs5(B_pg>s=5NxkD-(+SRlljUXbE#>8 z9LB*dB=Ehkx$Qa(_(z=qqqh$UgYUk}9UiIBnDw7)Qr}aP%LR3ND0;U)Oi#KKMv@jW z#%zOxygM2cJz6a{4DDa>au)UNnP?1Zq9c@US$^`XK2GW&9e7K!faSxst6 z-mk(Lvgno)`V~g-5knKb^d&4ds|01pc>lwd^~*yheMy5dD22B1Xa_}30EU|!LOlh8 zQXk5g7W{&%lx+02{wXQzbMKVS`6ECnJ*9-E2w>%3Kq*u$m(B^PZR!&DH$%xH2 z*rZd!bI}BHtbOlWjC(}D2qjR-&-bf5W7cScor{b_++FQQCAIvxT|DlUGG z5h$D4ESI# z)C#+Ny|Ls4iMnpRzQABrU<*eefKYZwXomqILbT{}iQk%knopNMvuJTu_qHdby47s4 z3w=WW*Ah3+v^8()4S#%ab-W9;ljDz98bplkM4?7|#F1Co$xTyG`yfZZy58B*%Coj! z5c5@U4o1RvN$2+9A!;HY7ln^&V?7j zr8H%Cp~K{km8A{e$>NI-WFtIrWmwUic*V`oQ85mF@W?#tB&~3Oh`55XqBbqf$6K-w ziOE|}!n0W=^{0kZGLcBjpRCH45`0i27?qcX@k|eFFbxN5-u;?|j-SwCyq@(OD zJ1Y6eKRI9KutP8!n14~>78^^vd;xXQL8H+*z%oDf-I}21g#+#o^esC9MQHf5&`hr6Z5#xyG{8aQfwnipPXtW(8P*n->Ob04xm(b2bhwokpB^to%QT5& z+5i_o#HVTNK_pQC4i=BO=Dmg(g8rr-2&S)wM0W~gD9c#aw0xUKwDdW zqlfmob-^y+imi?E)%d-jK&`FttYxZBtKn}z&^Ni4E5}w%e-`x9IpdmMxJMw}SX+n* h{GFnL`zZMhqoN(-Pibk=Wk95e=@pC1g%@u}{tJ06F!cZc diff --git a/mai/docs/path2.png b/mai/docs/path2.png deleted file mode 100644 index 3b22399aa4a6871783030d686eb1a4b19a9bed13..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 76078 zcmd42cTkgG^zaD+A}AmzNC&9`0)q68NSEHEMtYOpqy|AnrS}qgF9J#nEd)e*ClsaE zKrbPXvqTxHMy=#&X!`V#kF!`j;6{0@vg==jfbkqvV0Zed?{Qfw<4S@T{w*~*xd3u)5$BX?Z9XNMSpz2k0TT|vGk+14BSk8#F3%sdF!v_GjEH}tm+ZD^4AC* zRG&Onk4WzL7nx_r^}a_{r%D9l`sLNt)i~T!Vq1C{9T!CQR|fCRckEG=e8Tc!nF8zm zIlH`jA!_+Z^j2P#0{4uf;C>M78&L4}EiUfdOhs$87{ZbYw9W%5P6EF8(hU9{coQD&I7d6IHiG=;?I9^rB%n`;h#Qi}MTk!b+3K zzf80Pq@<+Vwb-3n!vx!~;#f@WOPQ01Z)u;1{&qfGMTop^dP}F3BV||lVqPQpC-=|)%*4X$V-SAV ze+?6(LbcJq@0@PwPq!JzByGI^GW@@~D@vqXvG5+?OyN_KyoFEx??EvtD&g!uv}(Rd zuu}ARNibrD{w3oTMG3wBn|`don3?gP__MkG2Nfot=)0wY!*sLS+$1zxr|rGPWaN`+sEx`i}%`?*}ZEwB6+0 za96XcMu76LQ8xiO6qf@$TJ-Eb zMJ-DTuG3{J@vP&IvS5#hU0hrW+YVZzxn5=5p9?#RWEm%*kWuh}oTlZT{A@mG-8BsS z<}j99eHIW9up9hOX#sZ=t3b}{6X?x(N+hGJCvr{x8uq<^a2B0Fqp#|>>&bx-2`k$Qpn{K5R;EHc(f}5 z!qA+e;^HuzN;g&|ExNcVqHORnZctqY+-S$nwIBVwTRGeoa5!V|uinES|6$#FK`hSZ zIGQb~h+Zp6x6+rMoS2v>P?4``-Qjg{b?ts~=dTV5G+!TeT5PX43?y;-9xSvB$E-A4 z2%HK=F#Nq6zDMoK;m8rQKzo~MrN13CCU+TQTy2)>?a6+ZoHqLYYw=8!U|=8Hp=FD= zz0(BVx~y*9v`0#vU57lsA@&uptUNo5Q?o&0oJ*#xB zorkWEZ#z@$u8}3lEq3U)pHO z4Dn2McAucVTQrE3QIL52+5Wt$va&L2T#2IM9CdnHK}61R^m(?RF)0pV8!uZ5e557S zDSx#}G0jF|0tjs+g~tfvdN7PPwq>ubJR-sTZ1}Rad5yGjnH4cyJ9MtkT>)zB7RYgM zj#psKpVY{SMcsWQP<(@yzbVTV7IJ2AW_PYy?~AXxD%RE)uUJ=Q2`w&*(K>miaJZmV~)Gg%-AHKR->vFSG_ zfGOx9^rmA@@O>X{GC&3V;$}K-JM562YH3Q+t|z29X$|4O%O!)}NZxtp9a2Q#o?_lq zZ4Rysr3%SBH&<=u$U*xJm`m-iO`8CWZs<4Il6oj(J~9-KCRx#_CQyo)K6z{^%**D+ zfgjb7xxww1)DHGot||Mf6Tu+q{>@(#PCFzqDZV2BYDj+uj-E2;55(+3v95lvoQW&i zyq17S&~mwm%Dm}-D5a~Rat*+?NB(a&q`eky`f65cq8d&8jE>0)F>W4@-uD2S`@JiH z@v{q0@@Q{#5wjTPIJ78_#7#Jd9rrv!z(F3y0EUeVl|bQ=@85NAc#{a8oI1^HE9*Um~zEgbFx3Hn`$QXo$*iT z)VswKxaj`SvF9tb5FmM1t>#h1-M^}F^hs?wU{DO}H8o<{!Za&(NmoXT7ktpG=_OWh zlKL|?rmffbslKHi&};uwze4ls;%+{6<)l2{)@r*CDpI||w-Q{UWSG2VY&V>b*LrpU z&q;n44-3;jMrzxoymWWe>=_b-e#2Tqf*LX6M&9lm<;nRgU$}F}&sFI6g!X9J1AAK< zlQ^M0Q7mEQSkdQmC(vu~O(|A187YVl19zPAhf@62^Or3+zY_}yP7c!^)g5{ro;=L4 z_ZkZWVsr}Bm+A%p8=GPxB;I=}{C4iDGQDoLxc*^qGne>A(Y-z?t~EyZHyW0QEyhCj zo93sWnOt38T9$<4U&1NX@7t2C*crZr=k=>aHl)WSd^S{NmbUdY}Ea{l)HP=l6?)o{iZue!7*9v}D#myN7R-RqxkXx{zRmNwR= zI*rEFuko(+IDQ=EtKW;*gdy5^o`Xmub>V(IBgxzqr>jR6-9x+%N`E3Zmok zAbMLu^T+giO#eE`c)L4&MIzhq;{sSLu+3>EsVE zobSQ#x)8i5^$xMQyo@q~Y6g|y;+~|P z&mcmJIySR*bJ(}r&nq8AH@t5g83rwW&P!lbiJ-GJk|WXBpnnZ^&%wx1wh=w%7*7rt zSt51&tI!|TKU)hiA6Ol6wXvY>;ES@;R%=y^OT9XkmzM{Gx($~kYFGMxw}1F}1~9UD zQFkk|xc+jeeL>EC`0*D%*DULkjRBJQbmv|T*Is_7pLc%$HFQpEP21;>_GrQ9kc+kG zon^c0t(&X7Y3Q-L*7M@vn0GOWKf4GYPz}>YleM4Cxw_;nT9nz9NC*A3+MZ=`Ff7mt z_$DMLN=lqO3bhS{OZvcnFV%3pk6Li&@{ve-jM&T+Toc5u2~I)Rw&ZVGFeb*mb+?&L zm`Un5ehW{U4(zxLEM;*q1tO2XA^A5hei#EZ)4lE?>v~kSuzwu$aPy1ZhmGStmRYFg z=vdg53}nE_;Tg?{)%j`tT6l zu$yl$`f~su2Tt8ir!*H&+vWsCZIxS$2#!HFY44%*tB)2^KZPmHBgp=22x966Qy1JF z#HrYrtk|o6415S0&`fg{BW61>d56f*c*a@8G;`h`7Km$SRs9Y-cdZBT^#Q^Fg}&qPCgn*6E`^O6@{+8;BLEYm#n+~x(*v-5tp%N5m*75Z5)4uqC-ArG#?x7cWJ-;i#RS265Zm&?bVkS0|+DS#^qUeUnK z_3X02gci(z-2I+Pf)8?-4t1$>qt^9C7ihn|f%64anR?!h{xel@t;imoH*iOd5a;0GJ_(}tSN{D_m{Is2`_`1;e@sO?vj4v_dE&y=~-=t6ArPfq?=|ftC-Wxw2J<_;}%O?LwB~>7J`B zKbIIv7cBGH8nqYbMDJA9Zhz&g(f#YtsHI;O?CAh85419#DK6ujgg^Zk?a;ltA(U*S zEujQmo3a+^=M~&!a$7SjeZ~E+u_cuKg5fBwy{;U}!8Q3$og;2|jT1 z;#-8=Us14O65aW-_P|97#pEwlt}=Nr^JiJz1Z4x_rAd zyUCq@#vkV;{CeP2e94R`#3y$*K0wDRpv{9JCA*G2#D^pWad23M&5@~vz;IEdLYlp3trtvcZ+dxaMY+O-QCQG>$AC5P@7A^~xAEuv=E)iiTIT_ zhflLQ6|KymLd_6&sE~Uw+U;b2uK87PJQlL;vZSWzQC{GW^q7om^xcfrtQhFqoC3N@ap)IHXNX<9Wjx9h1M+3c(94eE)2&cQjAwvVYe>1o%^(grmk}E z*XvgU!#WpQ7whS9%~xT|qTj*Z$xo5%09ep*qVt@fR33xUu?*&jbGSR_6Mt)Uh7a ze8BhsQhkbAAn1-KtJXpb#F0HfG}?Jru=0u5yYAMr#94YG!gf0r0^f0ek{7Sh9p`KZ z)mU#p%UoU@UI2epiEP2roi1VBMA*gCz2oFxoQvj?`sEWW6oh3&M!tVT=@zF3c%%V@wVrwQEf+g& zMx#cz08V+ahlgdYbi!*5po1_49eFP~ejfN(arUF_6>Ebs3r0CL!K1kMg`6VtfXVGk z0v4}3U3maLt73WYrQWUiuvyx{dekr`w?l`BpmI;JW5j-T5;|s|H}IuoPuaEQX_}LD zPc*Q2>{Z_4;p|AUP>ZDR6}!7~YD(mn)gd-3kF6*OH;uDS)|9uJo;aRYaI%Z6^PHyT`cUMZ-?}WC?Ru!{+GI zAXp<|T>0{;o|Ut5f2#Oyrwf1R1spoW?^cbt!lQm*n&L8O5&Y_Ox7=QmXP<6B;>3!wOmnz`WWm6Q|WC{lP^PI7K2v# zG*SFYg#B;-Q~N@3kY#iLd7( z+2?cdK2P80CKh!LGS;_xDZ>4pVz%+d5j7OYYo^=QyZ8P(?s_)E**z5D~Z^}8(_U@PBDN^u$O{co)_|ad6>+L^{L1;#v`2dQ= zQo&Q>(VT<+l}|+4dhu6$_CKohJB-5)^bHL2q&8biY6C06@>+iMWE`@!iY=9wtOiv9 z2o1QE;~Uf=UpK@*YeCjl&vuMj#9(#f_1wd_X;n`pKmq{u*HOPUhaUZr#y+mt=JM0W z)4h51w%h!6^c5cuUW}YDTep1w7huXMC8+!ZA7Zpc?7a>)q*e1)A^6-NI9&SY4)QCa z=!qUv-c=yx&OM;j=^v)Puky8DFOY-TVFx)45qFaqyg*rA!E>YnWfk?Kn5!$2L64_d z*(~zg2&6%617&(>Zg**oaF8KK;Q5IozjDg;$F@dEf!?i?)7|(V^yV69)`#1si@~JsHr;(CB#JHaS)zZE_^nQZm%6HPS5W){`SLON&2A zB&RQ4u2&H0YG=+B{UVAt*jIxmn$R2r{=#@@1U~z8aI_X~dw{ZU=n8$6=VVbszm zn5n_v^mzr3oOujds&>LPgnYWGmJJQq#(Va219rvfeF>XyfG*}82_Dz2nWbOZ1Bjl~ zai8(KdQ~Ws?vc~50&9H_lBXR(VeTUi(3uTt+I3m{#f9 zK*Eg9wuLpU64}K+l}k#vjE+j9C<1Cr;=)WNR-VaviUUW_D8{uwR>k0H#_U1^zn z>7&>m+IJ?Y-K3a>0@U0tO(uTRB0dU1;T|p~$x7}dQ|GEYb1(aDE?S)B68wU5T)5&% z79H-qA;u>!Ua=3&B_+OFp&~vggZc6GR?}n+c_>lS35)8ofI||?yUd`CgoQ+MEfF1C zs<7k9#vKW?5p-zlWh!Y%~dv#UM7QOA&)|*9<9&% zVC^OkUeuE;6 zwklsC{qR`%`Ujnq7ZAY9M39qP+pGLpz;~(kIQO96s@KBAB|!q4l~(-3Y5~+f;p|16 zR8O4Lm2U0(D#+=$Cz($+voo0$E4Z89)t}Nbd{4fQQkH4m0W?>;rA*ztB$Twm&=?5<0!UJ+RvxLra|$DKEXgDe6^|GUh97 z-Z_?6pY1r|5LD_N_AYlK;oV1nnYE(#P&B8kq{qF?!-Tse)2HG7uGUkcUHE^%wWS_f zua(@kgrRi|c8_r5xE=1`H*bWN14%wr&nhbn7nlPZajj_HyU$(LDIn@ms(Gt&R=F! zZiiKN9m;ToH72@$L*$Pu#1DHU&XaBKThzAjTsy3v&HZG$=UmI+QD(VcI<9^K38fPq z@+dozcFyHou8BSOj_PG0Z;}Wdfl%xgiHc_DF5f4WI8O$5i-=H<=e5;;8-S;?;Kk6R zQ&D?x8|v?SR$ zUPt@mt>VsAl~!9!x9=+z&a~mO5bFCQB`)ixQsRq>ZS8QBjt?f5H`H_UXSw-6oV+(n z_4*iJU`z7&3m$zzx`K^~t`p?TU1?&^F+j3tpy1)A% zA3(hAsLn6*EZxOW+Urkr@gDc|cEa|0-B@bfP~CtxgN620JBD2IjXf!&M1IELVZutq z_4k-!gdpm4Vzt-Lx9@~YD$hwrOg4-1|7>TeGH0Z>Ia0f^x*E zJONO$T-lq04E{ORL=t<@k1Y}Z0KZ!JZb;#7_mIbG)1chEwUCA`!EwHS3y4;!jFB9E zthh)M+SpLyTZDkPC}_JcuLqT2hS;Dxl5>S=0q`?38h63e+ONig&WC4cF|@xPvW}q} zSy@bu@rI2dG<7xc{J6zS33Vxa<~)}$K3`GGfq2h?HcdKScz9Ig(=l?iLxLr>pc5!` zul%kiYHPkcb$I6COYC$WL9wHltK!hXCJbSYvBNN=z18iCiqVkaL&~7eH)_K^$=7=G zh;K>AQYD6kKDnOP83AWL^3L{Omdz<;py+B3BWa00H8|oLST49F@_ap0!h=OT7ik-I zMnzG z#%gUKIs8V}TjekYKACCbn4$$S@#=iQN#Iu|4tytEW06imL`Q~cdDQPW(^61w+ByU= zN8cfOZpnbi9e+kne5)2m3!2glei*+b0~&Pru|U#2AMy;e+9&BXy~HOa_N#@o#W$(E za^i*4zT8PY_?+F8f(*WVx?i$&DX=BIT&mk+em*HDpnActg5ed`nau=W-wg_IC90qu zd^2SNr(Qj0=qyhMpdUg`$bn);!z+1yNHtYT>gt6T!AsW>R#i=e;;mPM-KaAw@&t#Y z%b3~duTGn3IG*9^TFxrWrayG=a1mZecU3@@ik%h}87M_sHlUT~y6r)fyr2|5|Db~c z7$%ibM(vRIp_-FmiB6i2*x+cNNNVUutFs8g_mQ85I&3H)5Qxabdn2JI@u<-mqdBDS z6f+mv9Uju+W;@cQZaPuQ@rY)n)!#Go%q!C&W2bTu%Lcg~BsY7;C6h#aUlX@a>SGwb zG&x!5U%ZP#zr&{yDpKks=2SP3AtcowQNR)S!NpNPFV zm4N7{&V2>+2H(K*unJ@)@PQ-Yi2CfTu^X~$7z;zWVJ@HuN>!i(J>BcQ(dYwI)KL`U z)qM_G!fonqVge%TL(tw*0SAo#QB7f`;Af7WD~@_&9r)p^IKG6VZ*Rsi+efXN4Z-<& zr5-guo+{wsb(8$Vn+kK7ZA6R71h}R>H?8@y0{Dig8o&g>d;g8Gv`Xbifbe%EF( zmy4^Wv^y_U8_;f*v#~&r_x;5`OqxKV%(vYWKwtjwJxM1~>KPls)>vMdM+cg#-CYXL zLd5P5?0CHo_WOtJsVrXRM`awX6ChXm(XTLvKZ@HIRmNSSo0X0C@mFlvfWI%gS+M!J zI(W|>{-v=Nj4D&SE|Xn~o&=s=NtBE+OStfoPPGqr{tI@fQ<(#o4@An=w!rDHrSY17 zUt!Oov(Q`N(O+U#tZ;z|zGr);xVsc^$tvi7 z6jFui|0Mg{bLPB~I78WuIX(AZs0^M8+kdw`-=9vvkTs>!{vj{7h-0=28B2*fLPe(= za*D!af=Kkk@%nljZbe~@c&|3x%8QezU=}$^RF!X!PWTd&GItFo@1NEbBhwqm;J*GK zXXZq`+-+N75Bn)s70h;p+Uhzz!k~6{eD--Jk6}gA7p~O0?vIrDaX7Yi>GojC;CJJ` zSZlSzqefyB2VTN7d2QR*4!=#pR=+;=9hUKcIUGe2usp5ibAEC9*dU7G)9A}ApotLV zI?rE!y#k;9&e_B&@s87ZEKt=5dGbVDRp)jBAr8E_^wuH#Vt8@rrNZ$9=hZ83aLk_ARNO<{n+;Sn0?fT6dW7HqeQE&)Kzo zKE}OxWrSJ!g?9Xup8NfaJELe$>3Xo5bZfLssj%OS6T3q}kksygtw2C+)J{pE#h7;+ zWvX>`83Z*(c`yAhI9U}SfAe+7`S5>8tHiZ^Vw?29a0W8E@!kd?Vb{5=b+1^ zD|Q$@yo8*!__a5v+ix0_!XK=aB`;#qD~|FwPQ|vo&72<5O43YvPq*!tCL#v_Y)G z`hJr$rRGG7p9qcIq zcFfjrkq4EKY!ywrz1lOgUDvMD%e1U{$}quu_2qimM}eQEgJ9<(BM^-?f2G+ZXLFzJ zkPT5-K*r3X7x7|P$yt3>Nn5JBWqopc*|%AB9BnlLvDl4>H&p)^CEh9O)~PL$-q;#= zw_FXL%*wHn>OrvS%i+*4eD`36iA4{3`cv*7vGsFRdKUp)h9S3isw5!J0JUtCD>>)u z`wGC?sm<)%XQ-v}9>Ru?#5HTJf6}_i^NIpZ0MwU^143*n`1(gd3f<-7nDZ{LM4(39Shsb8~dzZ#fqmque)MG7BFmvY(6(MVEl_hN>0vE%qSo=}rV`&Rz!mZq@W?=S(s zz~-Tvb=E+gGKTcxya16=WE`TwH&QE?La>OzW4S~s!oT$lY{0tn4&P;YnOZ*ly@0w1tD0~LCg7^InH=O(`vOe+Mn5Tho6D@JORF!W z^bO*|D`<6fQ{?(A$JbjI4S4rIXgA7}NR%Z1t04oktb=p6>VdJ_1tl@_YPTz*OfWEa zNyZOGE zab5EoJBKGi(iJ4Wc`-s?WJVGnR~3xraY}Rd4`&3g1vPL%{Oi{gDrU_-eXdTv&7j&M zlO_{<+M;-%WtX#-tPi@^Eg5l-WKSQcH;rBMBj9%w*sm| zhT2dEk9xD2{wx)_QB&O!g>}WPHkVXK(u)o9`(wa3lgk7Vt=n>@M|5**xFEIR9C^f8 zG&>{FtZil)aW((W{#)zDUTHc7H+lZg_r^kQe=ckM^JF{@_vcl#o!b|OoZN_^%+J{m z6y)Bruznz5k@bLNAMVEw2e0jzAdtFDXR1^4PsUtbxhkOT#Po;jE2+q*ONDSNx>_K5 zDQphDaqcJk>U;ojv_ClCm^Vj|CPvZ#!*&s7J@d{`@!H9qQSqW0g^+~&S|!Q5Nfn%A z(UNz(w6uL9Sg6{=wA#9uy@gl(`$`OA+bRaVIti`x+4PD!C6apgdrF<02ge|R4z0a` z^M{2(iNq^)OJ!0w1mbR`kCw4ASEfhUuu9MX8hU+aarvFbw5zYwD{1DU~X@71plidj9)&j#NaT`5AWQ zWsbC5`@Y{SdkY>01U04jI1bOPYp65}NZU+*Jk8zF)O|$WAR(dWlerX{S_$_#DuyP> z*Ctsln$%#|7Wv$$x~(hj29Ou-+7QZRpGyZVVTRB?$wSgv8;Ero$&0{}uW+v(CDq}) zA-59&x12=HJ{I@UdFpM@q-&x4LVsZ(h-K80C1 zty##ONr$+_7X&b;1`V)~spNH2T&4J*FDn3{&YYX35pBcol!!ru5Vnm<^QB$!*+ffXxmD5s_kcM7hk%Xlw%;{XJ1J_ zlhrmr@;d-}!Sa$P&5W2ZHS$}GJ(|27UNf*ro`5M$greIQ!Akz81-Ct#qjt~5bk(i- zp+7C6CG4dp2LRAT_s`N(2g0VWJC$=4RmIu-Wm^iTblLiBl=O5)0nr`?mT!JOo0`S5 zvk0SxU_Ktt)}C+69>_@haP+t6F@%mM^Smc_v0%sr{|ys#npZ(c>^gta?=v%-d1csu zmaOEZ-Kdp-2!MCbW6Lbk!}Ee9EWf`aNrhKk2uv>QFBDw9h|T?dMn<7&8DWv`Xk^Kj zM5wJtal;1A8c^<=iCW^Ja`Nbr@NqJyUcpYrzW)O7y| z$jG${AYQBi0A~R}$k}u7>T8rth9L@#u1wuMA!@yJX_Hi(g<*<>S<2I|PQ+~_!7U_Xf;Htan+Mg6-c-cE0eITzqUKC4y-oZf`0~SkHnVmiN z+!LccAh|Y1C#iZY_Y|{%d_S+NqIMCY%9$gPcfgyp8$SO%en=pXJKJLz6(FOYhduTY z6@Jbo`0>`V7kBjvtF-uJWNdfTFZ(cPvuZ+fNnf9y!s ze18Ryo4Zqb+hnX<`L+ZwHGX%Z!2`&!*c9)B`v5{jni{klT^DXUK*ox`$~a1!<4(a>D6s5KHoEQt4ZTWV=T}j zKy{&XA91FQd=q7fC;(jdi?p^T+#rmX`p(GXpM|&B6Jyr;Wj=%BS+?T5t|ma8s(nTc z&!&Zh!nRBqtyF!=kYm}GwCE|uJT_k5Ng(_J!j4sCHLwdCJOOQ2y0lF5W$r@%W8C6c zSy=fZ6E}EtGZ}A`-nAH)oFN2t==r39HKjda zRw`cOcOifI>w1TB-nGF&9~DW6WU!L zp%uHl3{ZW(NmKP`XWJPFwPy8wDnubyZr}V{?o8?OhSEf-mPlre z*+1&Bq9uAv=Ig8Jy#xa6DPq0v_%p9GD}+#HMb}Ora&Jrx9Ob4@J}@si&pOAOhFPbK zap?+qc`{R;%FL_hSS)$QMOHaZIr!v$I$-Sj*u@mmSgxS8XEcT~FD`EmKbbxcyT0T{ zSxmQ&x2LWajRlzgNT-LBozy}K%!h89riTz~ZJxt@_ql5q&I%976F1{qa*EQ!W<2)S zTHmI({$>JDJmWm{2l58?bp_I#$n)y#+Tagbn^n0pRT}g4D?{bd!`hRU$C&DS&nz4K z0upW;FQ{95Oc{+Demqz19=TH(ub=sXu=`iWSY3owh*ee z8uKkiyyiQ@Mbbkh26L~5+ySnE@MsxW$tT>_SCQFZ<2!X8Vu_QX7-{55oiAMa)++f6 zRt2WEnaTa3tfWJyGV62U%ou3InaHr_L2bfu2El{*RuS&N-6@&MKWx!_z7yTzOWJLA zR$s6h`9+EDfXYn+3H6Vk9~bbcsoW72FV8?P#k z&q}7Az8@K6fmt}STyxg9@cxw4zT7>lnvXGF8u0tBMF&a&5UFoIjKEhzOJ=djLBY|*C5&S!$ z+CexwM2YEUE4Oxkq=!+YT`T_KapS%$9hNRFP~M`9t0tLn!^cOTiD=+kN4JiFW&J{s z(MuwdoztH>K#h^Dn=Gs}aTd>r?F6K5T~AK+8dX2XF-p0pI1T#BBY5Z*)bLJVU*?xv z`B?N$@TPNCFs$1b#Yi0G4WdowG?~1?ZHmXgLgW<$4uKF0X#D+|<`nq`?#cGHjSwus zbnTLg7GsJw)RlRY`y0Wp2pq{1AVoGEmUwgDRBo@aZmA$Y{9)L>eIQe1J~4PcSyh03 ztfKoXXWd@>6Zi3wCjtNB@8U7rAK+lqjSv2&pUg1KUgyhA&vy!vd(3CNd4!L5V|VM4 zkcn{}ZkB6?y=>4E$vLy9Ii3CO?yp-Fha5|;pJ*MY(P#BZuTQI-Ea^Xmj-R&2_S{eV zH71>VHR$LZ{ak8{MEq$1SqN2R51+F~d#CF`yfY{C@?HAyPc!uZE};-xOFM;BfYb}V zS%Z>q8)+}l)=rF8jxxH)+h#yRa~JdV%Q8YWhwHKVSkJ)vcQ8lrSYqUOHM|+?yMI1AI z^d+$2dODzy8pZ~H=e5<=oZWN~8gJ$HOrBUZqEK*q(T$qJOHa*9DAi+8^UzyPX->}w zoIJp*fH}tnGhA+=4vZ_Jd6a6RgRt?HnsvlUoMp?K=bl#ZPl@dte?%8P=^+D~1qS$^ zvIatx4i9u5AAXP+Gig4Uk+DxCBF|U~ZF~>!gM{|enkKn$kWaq-I0(p6L0gyOaQmyn zb~EK<{R6|kfIb6YaX?e6({dQsI zbBWLk*6b1HpvzPyLn*4XM`==rfgrj0$M0W6OnNFLj{dxbSQp!q&<+Nh&gl+5^(nKm zR7&p482gxp&AG1HhG(Xs1ewdm=xN3|5iiAU)~*fPgmv!58Ba}KGu|Wjd7EYQHx9N4 z`+58?T<7=)*GEKWx0mrdd*J8L8`;0d4>17=O$tT+!4?w^2XB4)ZZo~1CBmH*i;mvj z0;qVV8NkptYS627f8N;bqb!uHmQR^Sv8_1PL<*|`C*b<5s^WRUm~-ihIRviwh=}#7 zQQ|0yG6ig6_a-hRs=90FL-jU>G!z5zX7##qWZn`M5~f($A5gb;gAlNOJ_JAVQ4r zZz8S#0|fR=e%uidq7LZjNT$(-uiWM{up`7x^?yJ8^#9k>b>ZLM8%^P{^4EQ($K6*b zrK=J-J3p@iCfk22{Pb_*01r>)gO2=l3hwY*euuXB|5D(8&v@zouVT2_zozr{#TI$3 z^P>516&HTDI;XO>IYxjfK%PlvR!1>Zuv0B92R{y+6iG<_kas%KGkam6D)>E{bxpUeI&*f}Cw`_Z)c?7zd0;j0gRtAnv`=u@xP_@#oLswu*BwYBdj!ugkGK08);v&LZ*{g6jBXB{BOwQEnoldpC2ShDi?+Y3r z6%vg1fI0sB*{_HsC21?(>yhEd@yiD?@Un09rKITEN2UXQB!>if@I{G_1_h0;mVDB1 zBi9{9^;#5qaZcS&)%!N9|FmsEz_Gag&oDCCX3X@&ATq3-%D_4XHFNC%7n$%W)t9B1 zP;tp*Kl%J4RV16VglTNqBnXx_=e%JZz-XJiPN#Y#KCF+>q$hVi6)LNG%UWv*yMP#q zR{ippJw6vhK#bP+huGaV$wsi@%TwP|9rsrF(tNk3Y{+CF5^}}T$ z^Gzo02M~41=9^Na!6iAU)$5P8Dg9J`n_aN^&L+HJb@z&91dk5h~RjxcNKT}i_~OukG{A3N5TOAExU8{i{J_oC$N(QM)G z21BY$eP)gVhnwktAT-}cZmjLwVZt6vU{i0C$C&PZAn^zL}hS4qiITXM%P-G=W9I0Ok?R;R=4OOect zi#NhKupzqNfmJT&mjF4(;DZsV%G#AP`mz$H@c`k0byCRy9qjWQadA6UQA;mLaEmiE z@eG>|{nD?*cTQcozzfmquqz&+YdA-Ug`D< zl<1*4LTGeYE|R?!S}LP-i^*6IXh&ont9dD{L+d6@S2gOB!xyJC>U6$!I5b{{xKGQ5tA(rr? zhqGqmUgoODlQOd*3pT#xTrrUCWrds0H*s<|OBLHpK|;X3O|=~6{O49pN!?G4wT^eR z#0%?XX%oo45K3psMxIcryxd7+djsb*-=0BDs^(PgkCY<$U|e99(Aunnc2JbEs|8{A*&ZqZaxPj9$2JP5|tWNgaW@t=!87P7^% zTcca|CIPHe3a{2NjImE_9WDZzon!$fGY)S7-F+LbJKK74rHICw8ZI;7tRXp@d>y2w z^^BPfICb|5*)Z0J{++rs_P&$C=~xN+Ia_mbx@YS`AWO_uI%mV`+oE(b`}Qr00{`}9cqu6$vc`|B6GKrazS8TA}7wVd3-_)!ot zJ?@5LTfjN8s8m7P0W-n#-G|yu#$V1lA@y~*|DwOFmN|;?8qTj7%-@nLP%ERh>=|rN zxYYteW_K%kKIu%#-^KKx_B@vK^Q>2QjU2uIikr^ORv0V&NJewJVNT$7r(Cf zHh$RpTG6WJBF5#lXx>oe)f`1t_D)j;<^_0M-%C;s z3Sse*uK1NC4%kl$$O&DN6gr7}n5m;vhc3^f2sF5xBl#dKUbQ5?8*E}JofycZKdXJ^ zofU{sZ^=&rDt(o>IXy#15wLJiH=;g_>eX%uWj*FDcNQ`VBz^+Le6FyRY2Y=PD~T}c zAkUi}Z6w;s&XVLaE8iNX+Yg0Qqki8D1Uvv3Sark|D=>a2cjZ;1_FK%Jk@)l$g8E%) zFx7^vXa5wG5-Sqs8;EE(5;IF72zoI~6wJ_NB^kA5Xc z^B(%J%hjqGMx+1aTvM2yAt$sU{0z;wu^#5em<~1`6i)3 zJsS{pNnRMs(ULeJmbM zz27N>vK-PZ?GDU6pWQ&N=~^*hb~qZh6NONE0?=S9udH<}e)al%!HQaTVnT;F7*%W6N^ zA(W0#1v5z=)ti$3F*eg7Cr>FP?t4?ux`5qo>ZNv!e&7Sx2mk%lYb4NfFvg+@TX3K0 z48+dKzFD(uG zP~fxg7EZj<**Y2!6YG;KwgDKiE{;fUEv$;xB+~wrEIB5xusIeb?W8B7QId> zjT$j_R(8ZRGA~;lo7Zhgz#1c>JA5`Pp&9T7cX*{Ma87?q;vt=B|ByUc0~72cd=tGo zZ1&d+Qv!(?@0T;=S>wVn=Zp7#JP-@A@FZ@+)ZXcjyOq3(7_M5$ZdKo;HT^Jm?QGtO zBp>3b*j4Mwey7--^j2=#1 zjZX99f%GKm8u{y}ehoT>?nC1HxKD%DkUB_EgKw-Bek^^-ZVU-#cBkQ6-Gup@QBP=z zODH{=KQ5&LGK{}EXvVH7-Wa~%_Y+JG{Y`ZWEyfTewYBX`By`|G97U`Rc9sY($mNtAF<~W zuINqYXzuTy*y?Uu(q>8+)vwWs2BTkX%+)*s?Uz_z+!=@UyU&;6k75(_*!-w$bg!!LDup- zNc%}n=m+^MU=u%aIJTk#%D|?5gB_SezZFpgEgj=U!t+32P;|kRo zaS9*0Q0Ei|VGe?D%+AQqB69tSX2YzD`_2MlJ(x#G;HT?Qu(Rp3cdi@il&maQIPy9m zxJ?<^%{XqJ{|R`UDmlnOKDWv}mv*-0G#S!l$1DY1bXXx87>!3; zbBaW}WrbBRj^b&?l{4F+7bnvg_(*6cni)RX{7CRa(rxijAGl=zRIt5TN zyZXdDzMDAiy8an=d$q3_x|g7l+C2Jss~{-9M4z#s&+hAc6+-#)9+33LL&JMxENil!M z>B+O2-^1e)_P3cy`CfNR_4663$TbU;xFLy4GtaYWokqQPaLop&6EefMDo}`qjyP$3 zEQR?!4+fArO&4lGxJZrUzsCLc>C2`<{JITa1ZUoYJUDCQneIm#ZLr_Am}S*tB>g<5 zx;nB{)P?FE+ShNIGjR+3oOu-U)s8IjDBvOX8Vsl@LJBlnBWzq7a7^iiicz{0NLw(b zj#5g7-664v$<<_%CBJ#W)E7=sjk`6G_|x zy7O|G-uN;|+9;m`vzYe`K4u*=(xR*?Wz9N>fjhpx(gQ}F+leeu&ka(am>jB~JJuBl z@Z5WQik9)|KBZ`-Me7oTjE^*0d4K)E6dICx#O~FzXm8~gf-_YoTz%c-OkbAw?dGa3 zlRV^};P~-|8(2on-pyH-Tg`(v@n19nDX1*RsM$N#ijgx`C!N*9nkg|^hFs$&^Iu2Y z*9(Vrf^pxXr{2V7hA)>w8Kf*$EX|cICz5vcC*Ibj`dK&!sA_Pr$~#?`)X}iJqAKak zviOW6DieRJ=Oocw2EDI#|7t{=Le_=;`7JBxZ63@wvXRHPUCq<{a|S%lC)i7XB^O!) z+{V**9L@M}T4US1cdO|#QYfG0{M~Kl0j;)LSF4{k+5+fR2nof#=nbO&!yTUG{t(Gv zMWe?&{yG-&^DP!9g@8Jr>m29JD3;q#pOOH`uLi$)pF+t6wCJk{vWi%JvtK)>C^GL> z9ET`d`!ck0db*)n@&WfQq%>znx_38j5V!<^I#U$B#lMvdyI3f%>XfI`o5|7}@!_63 zP;hipa$K&C`*Bj-q>usHMvVRDnoc!L zFE6?3`nlAd9m1z`&oMeawPVcF+P&b=uT_H(Pu5nYLokD4!;qO1ru6;3iWl|HHk_9B zXeyG2=hMV$<5I=;*!pNTLvY|apwX5d^FVp1Lk|axbQ?fpYW^Zh>fcpL8qvZIAnNR^g+rl%hK1j!etNf{)6-0Z2>;=vY zzWCHa&3UJ@K1IO0i6~#6xXZTfy(dIV;?Z4i^sG|<__MjpP?jQ6=ev1jj#9%K&Z^(+ zNSZmit*npf0pEp1kx+=I4Ck0=$m1Tj{2PmLmXV;*!V0@Y5p6WY3E;o>s#@C1I4u&> za+er4bkL!NZc%?#$m*HATs5V}YjQq`we0?UIf%?S<-J>s0?ir1Q0KmlcRg-cer55A zmEI7So^#?8&KuIaU5V0_Av9{>v0%dH5ytXb#p}AAVJKwB!GhvK7W-0O7qyC(&nKW- z^`e$Gjfa2K3M!1+8ffF}AR&LDydtkmG33rfWW0$j}Q0N2ncw{z%p0$Zx~d>W@R1 zMxp}Myw2%oP2>91(M*FI!g;-9AHWmxm6$Z+3sFYdfNIp~&%CrIQA4*7YzrJ7Bo;h9U zv{t@dp$1hB@#*T#sBd|%pAcw5uLif5<$MTq4>E|^#)8Elle<#G zLvlKdA?=v@p?#*@=Q7yrAv^3g)VeF)36Lg+H^qs;hMfAW z=>YS?Tp;-$7nlf@=e9-St+G;U8KUWVT%!sCyW1`A z-@nb|eScy7@Q(@(UbF(ZV0F^%{O}~a({`|+24xulx0FC>kdtbU$Zq^muA9Tl<}6$L z^IR<0zg5V19+h^mC$RqV+moxbkO)-e*$R4OZd4=a{S}{HT+-3eeD)^tz%Ges=ySvF z<5;bE#bf&VG3QCyxTiSaT;fH}n^*S!(lFK+kmIFea9(o`3A${;%kA1QER{eUwvs%8oAL@kV zP2*198Y*qhHE~mZWx4y^b@pJFow*;VS9&MfJ*!?|W_C1+?lj4AxZW;7yXefcD0rRN zYANn?|6P~aJXtP94S_P;2EUwfSdJ|U3{UeQjE58i={l|to%~wgCM%NIV8`Nr$9H$T z2~>`xq4=o?*}>fY^Bgwy*#7X7R$1m#=_Rqs!{D^vRfqi^xrx5-awSVQ(r*S^j&`v6OqeR?JwA&rV_a+ z{LW4XJfN!Ph?6^`ZNlJ``F3su!V4jvadcXcFZ1*mHry(;xw2B_Re6Rp^PK2EX z`tsdsfqJK{v_#vd{AyU zc?!t57}L(}dAGqCVAlV}W0F~|5j6{HPz;QT=|t<)Ehg%jEBI)u$95n2joR0tObr#{ zzxB1_i)p`oi6GhEc2#c*ea?px7ipjx>fufGVqME0uBk?SZx!heGOg2AvG+Ri*mMj* zHBeEQ;>xQ^W`LAK*-n60LK0(FHvn)oGE$!`o!0)g9{vljzKeB*)v9IR8mrgsPrfJB zijtSum9tv10~2rRm5Ws&NJ+QyvxachN7H=soIa+iNevRr!#Ohxc*?bQ8~Dw>LWeFi zY+^`WAl!*DiZ*GfV*1y$a7Wd^YD3(~_$)}^Y{yq11Ko`%!SYNpqdwn=ajecTMwISxLaJ0rIeq(X>CEg3e}Paez-$$ycw$sz5@Hxi5{Af@kL; z(^%lYJ(k{3{L4tnmh!*JlFXAeO7$wza;c|G#I;g_UA*hAbfN+~G;@9gs=hcpcG_=+=G)k&F2C9^V_XHM^%e=DE$g*NxI zM{EifojR1B8ikNU)#RxD{K~dBM?b!!@i0V4{7LHIzZ;3+xU&;{`7)2q~9!dcbHG}AYDOX<%+6rbTL8x?+gbbvBG ziL{LH>uwT@d*1qSioqFD_ho5P6S8KW?TzmqcKg^NI>CX=nF!$dGWAO6Qx(d&I?O#n zfhEph#?mTQN8XC;XK{B6txlKZE8(C`I+uW~y`2Um5mnMB1$LWC(INr5Jzx8Oq!*{Y z)2(Dm4B0izZ>i$ucC~of|3bZ^<_CXr~l)$v9Sbq;wV1wO&hYVQs5=#*d zd?qFNMc^n~BDKsyU42V>1$@LQ=fAX{@1o(_Vz}MEXp9=4cAIYk2Qa@1z+X|?bJw?O z+6a8RdXZ>xgCi(#?Tgs2-MTSL;Kw&h?j?Eno+GhVT2qi#Ph$1Zf{ka>tG}ZvN=#y^ zYg#3|ET$>!cAk0z86x?IKExGLHF9v>IX_nguHb-rKYs@2-z>SD#e zBsE-047R=fAX=E-^}6NWm0LNQR<2TFqK1hNn-?hp-Fe2e;Vb^84vjy$sTzws5JbSL?l`!m32X*51BEet6=ISlV4? zpRsfe;_F?bfG+v-gfod|g!+2LN=H>5+6A>_k(B^>3+-0-If=WuK+ij@(kdNqDgOAT zs7%rjf3XS^Q3{F4``~n(=Hxm03(fQE^WR<|7i_SC?W5%WOm;SYJbU*xn~Bn@!4sMJ zl6{3UUx8JSC=TZ~C@IOu&0Am!7@5xSO+=KsZ=4wZF^_V>R9Pf>ofxmtin~ASBX=k6 z{vAyuuyv2j!9LL2Y3({pAcyc=v3TOOV?Azp-1XW_2x)6MOZ{8uC7%OhbX0#Fs;bR} zpKM~2$wA%rX;|`8jFS?qRE_daew-^hEi~1jA8Ckal1*^x#Knno{J5VvS&TXreqh`7 z!A!-Gj9zVF@tedd!du?~+Uj|x&nWrbGAjFGX&>h|F8hK;ifPG%(n|VhZjy6ry=g6B zW355xaS-3f)!sjD#D7~t10U(-182ExP+JV_axui+tbkbi74L*VPowF&2_hAxedl@D z^3z9nRr7fk=bu;-&z_fYUtb%m#B^MWSs*=7z4zWLh{1V1gj!B9#iYsBM{)k>LyUbe zg;w+JozMMj<^G-~@QvRNjm%MB2HX4%yA%P^R8?gt7O%}z@A0fGZJa0EG56z(I)lEo zEGK|=?ZSRe^5+&nCSr+&u$k6Qd z3-Z+l24SoG->;=ysGzY=ax5|is6bJ&HigZvE}jv>LC5~;eg zOOzlz!hGX1IK=Hzt^3UFi)9X+Y8Evl1KFY+uUbx30@rYEOvMCAy@4=?FsbLUjxuK^ z!se;3bDXVQBhGw!-90Ad^GF^SpHdd3x8)luO9G~U2E_Nz;FI7)Q~09&=Q${Nx2u>B ztyns%4m8{+pLb+KH09;j>mP$p>w%qi!YL15Bv7h0tN$^w z{adN&v2Fk2A&Y)!z1p}6aj-jGOo$jwD&PF&6DJ1k)+Nt> zUL%!Fq~^e67TMCSj>PJl7RK`^*XEp?KThFH{eygC5ck6?J+@tq3y^c_QxsG3;ukI6 znvw48x9^e4a*5MdX%h-laGihIx_=N~3A%t(=8aV#e_X@xNO{nvVNTpTBdP4_AW>4O zVy|AYybp{z^FLh_45f(n6Hf!xC?i=GHx>4%yVVSDyUKHD>JcT~?P_6HRL4@+u;{t+ zOc$!9m5_9z;(*chI%&qhf@cPoBjb7n&>B7<&ykwPBhIbq?rmZVj+dqDc^KxQDoRM{ zjLgr?xK~~&?OxQnl%<`OD*lkzeIWoHC-%CWS=6%(kxti#&uBmSF=rY(^1I3=y*htW zw4e7dBf(~aT~TPa#^Yl=#za}EVt$v=n63HbE3>#9C>LfH*GPsb7hOHDa zXer73gv`II?&-<~NY;WSS2^$BtBVlgnFJeykJq81Z+_jt`-FzJ9ZQ(}M{;@N(re(# zm1@%e9pmud8KJdOJKMh`@|QM{|9tO1UH^%^#DB97t8f1APWAufppq+G^mohL|GC2} zD(vjV9k>3SL;oN9!nWVT87THi@;L2m&XWlkff-d(EYHj?&m4BQZ}>`&nfh}5^&AgH z%0PNa$3-tLf-~e1U-vFS-P|?*HJhBMrwrNq+Fcr zkQmePzuI3_?*1P6wz4-m_0z$|J&yhbJwG^8WkYnj(*-302hC-rF^oFs+9QwkA!C;=QK``6#>!S16lfkm%ZKou=>-PW6d=Y z2vWoaf#mSbQJyA+q5RZaiomd8P%lT-Zm3*-utVujPSA&F1Ulc6U7INAuhA+U9ADRc zebb7M#x(rK#ce*1>Otc@N0OL({qrWexpN-VF9Rem_C8(>C%OZ~(?-I`Epm5Us`1X` zYOT}^Pq*`?{~6H2+ztnSr<_x+#`hHbce*lpe7yYm>kFP~AEX5|v}=X7TDb09TNcjk z_Qa<2YJ+m=m%wju25{4PSVG$k5}tfnWKnD<`BwU&ufAc>SE%3Qp{ev-_X*p;8^M0+ zGr*f*_YcCo6^;=#OoOk%G)8oBsOciC_%vIH3E_&fXu%|1$ZVxtO;AHD9#K*|iQ-g5 zM2_J{>Fq?2GA(Ct9q{>V@9sJj0{?iMdK`Inc1Cpc<}<5} zC02crIKGzs={aXAeU5MV{B}|8UiGNee4tDXM~q^QCPP8( z3-~)zh1i95K+DC)NoB|@!Erecitpl{g&kM5aBAz=lg3i9Rc_|@=u6X(u#fyp$~T!r zm9;z9ijz`rsh)pe6|!O%CACdD7d=mC*X3%$3k)^tcHjE*7tVM>jI&dK=GgD))1086 ztQCT*<@GErf|N%vdFcImQ#$9-Cl+&}Gyn8?WVbTY!jU>-bGpjsn*vNlV*4fHD8*VJ zoS7t>42R7ZZ$hG9ahaeVC5`i_ zV-RHYfJ36}zDy{$u449qciKA8_N@xpTgREv{%x^qt&ZV*?q3fsuN#&R)Z?eNc-@<$ zTT$me^VuiO1fIsw(NQ4eF5xvUx~VAvj51!`RBDkJc6|O~nknx^ftCt^52tuPRlyCa zA2F&z7u$C@dE8ICn|Usq_L`s>VB4;!Jsq#t=kbVk=4I`hGK{w%TDw^8@@m$O=GjDR zmoi8Eo;gDkI@nbW6u_^E8ZHYb`dE}AmlIdssJBP}xY8z;y_|7j56&}XPR7dPoa}bS zXOa~*vfvxGzE46k+TQlb8|KnuGxn9vh*O3mC&G>81DXsb2iW4Mg zdqcI2{F&vKv;+9i|c0T)KeM73n)0jyS3ds{Ynf%t@rEgI@MZ z`_umxt+J^G^$?}Gk&r2p%VA6mhIIemBiO$S9k59wN_6`v#$8tkwjwps zt3B)lR?!4L@{@J@X2Zifnt6dJvqgz4v83U1hpo zv3q5ZzS&4LM7FJN?;Z*DlQ?DO7~B^dW%~}~-nU)T*;*I$on>54Pp;U2VTcn%F=0Kn zdB_Lm#s<-1>p$ejAgJ{^RrH#2OiQ_uQi zB*sDX^l0d=J>_bsUj2Jr22--9Y0c0fCwTzUR!SNZ^V{2PzV!!%D7nZmxE2tTtt}TCK{< zna3xamonRY6xPzt&kk{ytY|g3Jz6>Qi;x}j?h!r3PlpkT{sUr-iXzwW6`){_lrwi0&;c6V&+p&=q=5%7aa(i~^V zv$e5##yMGqG|&*kx9y2T2BON<1h-B;DT9S)h#OegOd#Au;F+7u)B9eTR+`f8Gr;6L zmf>UTDyew-tR6d@rOnS(Drt$*cf~-lbXkyAKuII!Pa#5r-%s~x#pJM5^SsGCbxnNs z;$}fzNMx&XY@vpP`WegAI7HoF+d?!f)htp@CD1fGTw9o-s&vYY-Dt)sYj83a5 zi&42o4Skp)jHCqDFkX$OBekj%pCG;JH8V8?JNW-ZfdQ_s)MIx=Imuu2~Sbmb$V)zK_(LPR*@6|1>;%O^oM#wJlmAp4av51Tg z_nAF4bqsYTaA{e2J~}db+L9`6f1*@06q8fyZ?<#YK&p@#=S2-$HZBI$&Ls(+og-F# z)qPF`kB)|jrno#KQStNHd9n|9=MLVN20ytF^2CMCCtjr26ViaeZNfDpEgeDu4dUyu zafl0b&5Oll`4!mh{#N|if)jsJLT%6mY;(^YTkikhn~Bn;Cj|95 z4V{EONEm^%Mngs-{#<*1B@`Un?A7-_V69ot9%i1(j$7c2Cf;KKvgJEOokLIXb4t8; z>c;KmT{v|%AT!N$wtAkp0Xz380MLSGsum;)81zE}{CEq|8>x~KHKwGz%@xgQQfY`6 zQ9+ADPMR}i!$#m|ndRcML%SMu^ z+AQ+qs7cbN>U->Ddf%rBL$~HUgmUh%ig4vS)gdY@z_!LSqaNBxQj{vPXyZMp_3&|$ zK+FCLs4{%)Dbbeg&IACJRMeQ7`*JE!4lk;>v0|xZG}qe}?G=?%kD%8m7a!r#*S21o z*Xux9NV*rafaKzx0!}6o;~D^CJ@nGPoP!qDWd-8q0$S%FXf1k7nNt|0_P~OI1JNSN z&(x~XwdWm);deCWL=3ZzbUu0&GiS}3TWujGeGGJ!7!Tk!1iJe^MgZB4fp1jubA^nB4a^JKOO~MVYo9ZGY&%!J?lJ51lm4GR{&8FWF zy~mG0Wr8(|wgHWN=*4|)zp;l^-^7cc=uM|EgqtQC_9i5VncWq6^Y|)K#7jw$9owt$ zTB!k8#EjgjDTCwibw%n;=e5D@PBqOn6=^JOs;dT~V*}Xr_@x`Z&d4O5i;xCd*j~_| zW67c9zBQr#5rw;+_iT75-7607kurkr#I3X~zLqC{;979Tx-*jHSrPn4gX#4pS^kpZ z-qM;7J#dI1wOYqaszDH1n)SiQ6D0~nf2I>+-ATgap^;f+Xs&!=&o;ASKm(Bk80A}O z3qNxj)(vb)*tQvqSSg!@f~(e$q5P-XDN6u$xh_;-y>Bz7OH1vy?9)w zPT>>$8^Zl#p4QkJ!!zywR~C`A|8vUKG||Q%k8b|6`dFdtbf9O&S|T|U0Vq)}Wb)$|P3cl7 zieq}xo3=Hnurl`R{msz605w*<2@C0i#GZuLKA2%wY|`)GBggwF4?_oXHx)+riML*w zs^5l-q)~5F7TB+LQJFSbC$?H;LL#zHfP;5e>wu{lmrMx%UPEuQ7MSRa99 z!^*7)79(Toa3rFI83_jZvkji0E5+Bw>L zA4XX9P9l@YBIF+IZj4yZmKlT8P*BMClkgzSAs#awmRh;VwG+1zM!++ zt4+Ej^=|9gt^nQqy|(;m4&$ol=ci&DvZarp83UbEFQhT*1ECz)3nOyA?7@Kb3H0^R zOsn01OsPmBc|JKL_g8dXi>|xJiPq}E^A_bI`RC<(l1~%%Zg2zxwq+`=MLS3eCe$Xw z-aikU;ZiFiF+JJeY0#(&W+SreIs7iXr<-d&?D4)wjV`v^7Tn-ehT&VR#-?SsqRx-L z$h(uDZG=lVW?ZkyUQL^jil$le_L#~Vo|jy!_8a$Lw0*=%&jf4E!16ddlp3G;%&Klp z|2hIH?-NT=28&G4E5uavN(n}saze`iULQ-m6N+qjf8{JIPg<7FYm%odN=ZgUL`>Vu zWG1utnbZ$DClT%ntu`LjSFpkRi^)^|R1eLBEPd_{O@xj9*0x(E#;zBx-dr8O?twFP ze84ruhx&HSvavRev_Wd(D(%X1$`ciA49wLx$J`PyT`kiUO#$exv4D1Pti}(jqgH$=)F7!-El)yWDpk@EiHW{aZ z+g4I0J{Y&U6+9wYQh zXiOU7TB{CrxKEgCTMQ1>2%#{P5g)TiQ_k)DuK zgN!FFZvqrtsTdfUZ4g+yZmiSf@DHso0z^=(PPYmFS#!gCBkMTi)6tW)X9d4LKD$w< zu*bjr$m!{xPTIxCxz_cavD;E@;X~n}?3j>s$=5Z!pQ>`Bco$xFxoA zYf-H%_=X4lX0+1jjp;0)b9!b2nW#MxHMh?$OT&ZWUdFo7cdJ!Ii57`9PD@Tnz5EpM z86mJcv-#Ft_+&^%p%eCgelYn^#w!)dv!$n2q4#+o7;8N4mQA{SMj+hTm^?l3mrQW+Hj8 zE%GOw@_wriZ|;t(o%6@uWj5%Dc1=XW$P{<*OUknSTdGZRL+W_S%uYrDqtpf?=#+{3 z;QHDnD}7)g`(YZFxqVGvZ))?xoYG{|VKzPi7duW1<(+J{tNge@KefXA{(66Jfa+vL zQewPB+{~>w?IvZ{-%E{$O3BDZ&)H5t2d8mYr=0OYnt=qWyt0mYHMH~R<{tAb%rAj@ z2?Y4@5m~@q>jtcaS}LiOx&h*IBS13 zt9!fs2w0TZjp5Gwz*T-FXJhd!TuzVadz-s#OqXw9(j*5yh?bwS&Y@lwYuNH}1{xX` zUAqOPtPdVmf{n;AG{kAFw)e_@g}9n4Cat8(1-Io8Ya~<%>#j0Sw|J8?OV6{8brUIb zP{icsVNsydU-~TJL*o1Ci%~n{?UGbIx0pW7fw-1@z1DE1HxDTzI@daO>hVF;nK;M^ zBM*KP*~uo|t^&3Dgh%}GA>{_nOhuF%F?U`^uEllTToD&*3kfuJ^t_s*$1mn(n~4x& zV(NaH1dvW3KDZZIkq_A2*%$V)KVpLzVrPcf!d1%a2MkYU9OEClWvGzAzk|6!qjs&X zf>g`3FSxWBv{5moZ=3s2^qcWr?}Op!H@P*MYtvCIJq*sFg*fw1>;^aW@`s^(q1@+ zm#93O(S3p#`j}8B^8gY`xZXC7e`)yW>2#^aZ1K-biqbZFN@};|7Ozc5kB8ccz2+%N z7uY3;O_P@?;&O&BeE$|L@cwXXCq^RuY4FLz;Purc(JxgNy5mJ>u^d^Gz8UXI z9q5R2d)dg8lH?h{jgC*w;hP)Y##yOKRMv{ip#IdrsA&zERCDbrR+c2(!0CP{02)Nt zBw#$wEuA21-GyRlRw`-WCJ2S8^hIr2RI@GdZi4N1~)$Kc&}7 z$$K0Z98Mfnoi^(1&?87UoI%}}B4CykagInv)Wpxc+^F1^@W}eREY9%K^;bm9Q!5$Q zG=hx$j3zmmZ3juPU;lmt$rDz$>rF>wk#sr=_fO|;@^Fv8YE8VoFgarFm%+=Mr~NR# zYfUZw*$+Tk_ehmo{s{hiNIOxeM7uazyr;c!04rIJk_Mv2Bpm)CAqj6~w!3t>-o>Y} zv9AeBZ!mMid$z3)dTGWV>rAG}mdjqa%AV3I_2%|!qvU=dJIXF0Kq(t{Oj;wW zRX*do^r=^k&uO5BTCH{3%K#8W!Bc~yy`zN~QUrXLqI7MQMYiauSl4eE*o<4ifwP#N zQ|0Bn%vI?``W|C5g^XCwLjJ6VE7hiH*-Z~ZkzHs@Uh08oC3eP6*#*P;#|?F9LclND00W~w3%FZZ4pS+ z+h{3NSX}SM1!}-B3Y5^fki4kX!-pMTh9Af>FS!VfH!O@i z!k^Nd-_`J=5iIBQIUiULlfL-TF9q4;dDh}-0Ues$c*tWQgH7*}XTATYq|yH1Sk$|s zDvt-?wg%hrB!cwi;{0WSVH!n><^9}9xFI^I6cpwVkD$AB%++R-y0xD*R zEa&~f$4*gGG3x;tuwlZ0RNCHejjH}md5P+1q-aCl5lG(&7>~HA(UkzxSNl>KgijT?ORj(o;?70wPW3X0qVObczNzTH<;bjJ3Fs?J+X~fKfmRx zx9jVoY0MKMl=Q`6*5gDiP~#+7<3ug2Z#!}LBHy>6JGS|{=?Mxiiw7QeI9gVJ95@o0 zZYmJ1n5n*oHT{x)?v$yzSu0KS-jZ}}ena6Z-|Jf9K)d!w9T@VR=*8R9@rDpTAtme= zl$F;1;mSqAfoSh3WWVY6Vo*K#z1i5i{uC7Mw;}8W?x_x6=|?;g_%<2@^hSczPyaH^ zIP@sVigfMC(gfpv2ZCc-odOs~M#m(YFu(uEx_6uF&J1x@5Ph^{Nx4?-S8^tS9)EM$ zAGCD2w&|TPW%o8Rjx-C&llC-QZ8(Lvfopg1iR?WdBxbxLs4skrBEVROp+5l99%}QV zy;Kl~Wt98@&dnczi$_6@fgWrSh64B1X2mKzCqb5>0-W!yH_{`thw=R$K%ryU+D)sG zmB-XvWbDQl{1vmHCKZcmd!jXvB`eTvuDa!*^q0)lGdJ93#pZ8(isgjZ*5wHYs9i+B zj6PaZEAk%`it@%pzD1AY1DvC zh?~x4i%q?(__|gW7H40dLtMGz#pSqqPC?%=vn3VyxrNuIP^VDh-M=KXj^f@%ZW5~k zn~vk$Brh}#&-;iEu9s^mKtf=auAg+IL*2C#=n?r@>o+g}R9Yv}eVSQFOZz22qGhGj z&okthKL@d{KVrQO8|Zw4D(f+_X3xt#CdD0#^(`qlPp1(Tr}A-^@jWUJuF0p8UcB3!^}` z{QY->)4o*qiCEt>63^I%EAqvA&aKvBnxAc$m0)_O*JfbZG=|70z{s0pk5ta{tFs2E zGO7%~J$PBRXI&AN!bQeOh2Du(gE>E*)$z4<^T513qO`bY@nZOKVqwWcMnXT+r;hO% zEw^w@=Qmd?HyO=~UujyzRkJ!3l4Pq#YS0wbZ(XUWw=X#u1?vs|xWSqxugm71pXlX_ z8)c>`s5W7C0oDXPOJN+51sO^M*y`ccsUbIq9? z?`g`Ch)sr+)R{6UkWag|)M2;wy0`U&R%W03sAY;5>w*^$giz}^&9Txuv@us5W``M% zG&R{7ZBWk@^y&}Hp8m9PQeCDu&;4)%r?Z4e^-9Hg|CEJ1HNOpZr5Ghu%`J`)2TDiR zVUg2ZhVF7_jBvo>-r&4vX5;2|QPz;%N_E;mHisLeBi8)s#zCDZE$yuYuWcx$@2u3P z&jeItRa@1to)Tjj$ZIYLT6zEk6B zrpx|zWKR!ks20+~FXw!=OVQ0e37u=lcK-7BeL??jDX+<%TZTzrKFg}m2^huADb z7`ru($s5HG~}Qil8Le8KjsC+*_U23k;mz zN!OLpZBvNz16P_Mt~?4Lo-wGwJVYiDfnRGr7vB35*)!E@Md(HJ`D2nE_r+39W@4nsbpFJVJY^!71dn z!*gnk?n%vx>u(3sB{ryq`sRpa^Gae>-sSGy!&G6%Up}83GQiAD+Fv7P*f;X@cj&7K zHMJsX>cix9PKN#Ic0c6he>@4~XDb}-UOlx*QH94!>@D6Y<=WdgO?BaZi$JI}%Xhzm zduWX4YMKS~20iG&in|0ot-u>y-g?5#t2(j()`o#QNq_I98C2+AbVvTfp&@QvE&Yo^ z!$C!-x{D$sA)u7aq(G|%qMZYSA4_J&;UqKUin|ly>(PnU;i&I28aj< zC`c0TorasaFsQHo4f#dqiCBj(6w@XxP}YydHv z*SnJ&NY#qCpo*~Sty#@{e1Wdtr+fQi%j$mrRI#C`76dFLE}F~6jH~LBPPo_Hh8M~4 z9`P56Ef??NQkwus?g~7!gqX!#w6VMIoTz@$Cj~*yh01rnQY-66Bla&dE0P}&;Zf3i z2W|<1`)M{g3^d6f=0|~?@oV%rxPr)mHsi3?vm*kS_gsAdaQ8w~Z&D7u`m(Puk#9x? z;}MOCiuJGEjZ#qV@DvU;4$vFZYRTXPjJY1}ofbDNLqzvfe6*Xjx$V0r95PI!9-A*C zw`CPY@rr#kMUtn7?T_u+1(tnBbh#p7UUnIiZ}6fcm(DH%=fa7VheGOi61pQp9}3WN z#z~eW*eRCWy~b-->EOE&R-16IS-T87o9i@>w8{9f5=28B@jdS?B~404tajokV?qtU zUsFT=NKH5aZMp>tyVd#Ih*(JCyQ=WGGKr5M=jUz%IZFx+K}1?nz9c+_7t1yP?j$eN z^1{f1h=R1Pz;$h0-{J=Dd?0lVcV_F4!xb4jj^I;y1Gse1!g?5RZC53_+1g*_s1bjU zD;3-pC_G5W_L!=dED05@>h!0g|AFJyOyUCS&*9!oWl9!vnyPMZapVb^c68N<{enm< z)bDwucP(5OOaN36Xj*nA>WE3}7=#c-dQOxIpwI{T8z%XsiNv-9%Ju$0*`{3jycpYC zTj4=(;h19|zUyCT=I3U833Bgn^lrl*yvm`8Bdmd&LRB6NJDG2P&-Gdx0{de~#|(9? z8-0A>YhkSOonEr9Z`)$VDJ|`VuAvH0gk!}Z2Aa^?_32h8ogH3u>e_Q0+zFLO0;^#k zoUs&=vXqOTe>qG9v=p)}XY%uBGgoub;hjf*Me!mn!y8^>oM*$ObDk0HLW=Jk#N2Rs>*oVsK@C6o0tvq>=%#>Gnwubpz zjB(mgUhJW3!b2qYeV0X-#E!;$@>$f2NYy5hiN*NO%fl@BwwkeHw_=UO!AkuV@Jy@b z3>J^Hlt{C$tG95m!nk^tb3Pz=CtM%9^l~=Jozgg+S0Y9~K4;ria z*xR)0G>l4eELp%pjE!$CXX+Q>&Uskx?waH`AV@$84UoFUYu2j6c1yB(%)j=BGL`%^ zGYli-&9PVl%g@Y6xfaosML)q&YymreBDyI{za<;txY%C{Oh(GzcTv2C*767s#>CG) zjvl#9v<(veE=05mVrue>J&=mDUOXL|ZZ%^`hQLaC}Lj+1&0HC|+2p?}ew?Kdcb@(L5 z9Fs6F3aLn)vN6%OL6_1;@|jQK_eM5)^<{FuV8^#NY8Ke5#zPfEL01gRI$U_BgUcfR%4H_*#_%dnGl z*9?^;#RZ2YsHg3M@S8uG=DrH%nF6FGHXMJiUk_;jaTd(;8?Zszd>#ohGL_UOhEeZK zbhqJR{)LBq{5KZa&FPY3|APc}<1YrFcK(lHvNu<1E%e^VODV?v$5kSImpWr~$p4Wv zJUwCuFB6jSSUvpb2N#z|CRa(1tD}x8+tiGWqr!N zA}>8%apkKJ;Wx#9a_XQ{v)*u}wSf#NK-Krwtw%9;1q38cu5x-v;rXf5foUxPOisb? z7xpJX80f2(Gt!F-dq@FoNqNrst_4F^_wg+(iSO4vb#<`0((&~;&Ke48*(PJI-+^wN zqYgG>nn-#f!*9>4B+jZLj^Ti%+NaBN=+$}1xxt?E74EDz>MW>4uJ2a6bVvr(6`o71Qhj;0C5}PzXpn2>wP@K`%l~CC~w|d zFdfip_Pdeuxp;q>(GhZn+#$LB#zp3A^uqxF)6;R_Ca^H570Xz6_k+9yvC!QFMyVd@31AkUsLf^*Te81@1Zj zs`b9|=0Eze5K@*sHmn13`HFn!^qX8TgqL&)m5H!|IlE zT!7gsvhATcl(*DTEbLDturT=R?=6m;uhto=XOhUbo;&Be_(U7!B60D8(o;fK0^}x9 zb99n+Y#%LN9Uh2mbw9M<`AS{^{4F<6!dV`QiirVTL33bf6tmNBFf>%NH*#v5oz(^z z_Tt9922fNN7PD1{2$Qti1vxU^7YEY3dCN?~KH`RRnv?;Bk;Gzqtj)GX2id!>lmkbw zk2q?WSbuwE3)F23!KMcX*S_iHof5f3YXdOUV0wl|^~EJuVj6-$#gEhM!!J(QsQlG= z)MciIWA#O{Xiu*zESs5QH$lMV(%|r%x(X_xg4_+Kz`z!2NSV4FM=Lrq{>Bep3CQ*g zJV2wI1$Rkf;?}aDt_GW(>Xu99lz!pNUg_C^fd{|&AlX%hUS+Id>z6+bb=>0C`UE_b zIhHD@zY_9U+vfMSd#*NVwS-msg9j|_@%CGWNEiP$f;rD=1&M6?$*ngiux>-k(i9Ww zc{pZKEiK{??uJyG_9*Ujt*GvH-_qL^N$bYwjk6|Jf0=nql`5EZ;QM)pG(iUJgzxF1 z+Wz)#8ERAy{RSD-Dt?tt(G7{Iis^$NO_(3HH?dER6VID6oa>uR8~d`X=b}5c)r>R2 zX_Lw^5{JaNhdQxqI(#117%4O1N}7|Gpv-yG+>&EgWa=AJb*_V-#=c7+5%9n;v%{ij z*#IF0*q|shv|;G!-@D=Rd~JTKG+mm0MlA(QpTMA$9TIYzS@$G=o8s#P!_bM9+oJ@S z0^?c8!dF>nP_ohGPpU4BAF;`<#x3E&ukp>kqzwP+&cF5MFeBSo+%$GZlm8O%Afz@= zdu=bWf|6+V=rOE)={|U3Wdjg}`r{HBx6~UfN{b$HldR9n*xj|IYx~hR z$GX7GWaj=mmW!%X+V=Nd74TdE`11CAz+)eBU77%o;&IV0ZK#xsS8T62m$=T(JAZcv zEvAM6=m2)Ux>^_@sm!WL~#b{_8g$z=F zsy`CndXXFQIeq*pcDh4wZs8kk^Z6Q#Mu&Zc-}!q61%-oeU@*FuWXK=SHya5O{QSUD zv(xGA?T?{l`%5+sbIpg`Sd^p@Y`Ft6^tw#Ba)xW~o}>#p$Anhp96|#dxs9Lx zEnGf4yN`!;PXjEI>F$9~iA00j%TDUgfH);X-;dsRAE92-F3!Q%8r+mBSbq$WX;#Se z)VO?h(E!P^5>Swe|G%nM(o z2L>2#o9UNBY6s~#W!nZPdrSGl;uv*Cx=OOcIp|LLnM&xaNcKOHe4m}QxNgb51eJ*xjC4t))JCrJiX0w>OAGv%LYjjER zYb|3uh>7_&RdY0eX$ij3uq-KN(dhRNwsFh$g8XB6fV41ri zbGVGH_xL5e|7`rjah8Hv5b|$RWc{O(!hX1Cva+a;#H<U|> zUQAVvFybNi1AlM)!Wzk(bYIqM&{%C<_tW4z;KHw&^TVl20uPiOF2vRFPHL`w&7CWw z9u|Pk$feMgp6p$Jb=|C>nPp~j|Dv>PVg(2W{3~s}oiN!f7RE9@%OLbsgBwm;8^${6aQP@$azJ>1I&zzRnZId z`)-myx9^xOrkV_qYOOKpfm?6=?~{|eegAW^0^~KVAA|q5ImU0-(LA3+6bJ)2?cQ@* zK@;5N4fsp$zuNJeYa7}*91TB@Yq`kSEhL~Yr&}{aoj@@(^Bdk8TDKZ&?kO=y7td^;^y|o`1j$zv4dsBE9T>oGrJPoK6Yi)aat)Kt@ zd5!R&RvVm~QPdK~j{gg_P;IxQqDB3m3yJ^I6X9<)!JF3o$CKU+0Anrmzb+z|2HmXO zZf&4@vHhe>Y0ym@B*!9PflewH-O1})ik4q`;h$-lidI`IBxd@)9ousUeP=Y~^2r%j z$emlXVL7Y!k49DoTWptv<~ec!bolW5e7n>S>(|tp_{3R^=w2ynXl4``5Me+105nU` z&TA-+2Mx8gru|16g<*Rk9gQWuP2I1sFDU3}Lt5!X%N9Wt5 zsNd7s2Xc9AJX#!nffacaP2DJ)AIfmN5P$sHqRBhq2IVqE@Y8VK zp)|#Le1)H7*4>Wg`PE}(0QG}b`!-+8M6rms2$mLs0l2lU)Ka{f>mg)jtx62-MisKLRAWEmQFW4Y?oSIX-A5l0 z>OH=ktEYl(9w~qdI@qdG*RuGr6*03Q*M;A+A0gMp96EdqWr}O{jwm4!K+hw8%cYfo zi`mozouRqAfeYQ;A32~}Ey)9T-@8OL`ZA;Ob-iElmP;8`Dq5}_ID8B%VKOx;bYxz8 z!$jCQ`0VB{oC9EZu^%jub!(;gbqY;O`BTYnLyJ-USHO0_O{JHK&-0HomAN>M zGa#L=sn1k(7cXv{+<8-YO~4Jr;x!TV)rHb;-~+6;!!g4g#E^44!Ce26O)S4U{wnev zD$Qr3`$)XE@Db2yN&lM?&Mely=0T4eCz^kwc3Obex$A1XB+ZLjcv5GEHM+z!Hf+ec zBLjw+c1vAtM5LNDg~}rv6K8Bir)BfL@8*Th%Bgja+C<&u9XsqedHXYl{DP{{t=Cb- z(urN>g15MAg;07qCyH|f?a*Tj(=J+b=5PWQI=GNzJA>kk&~lyPi1-j01&f$eyhcdUD_W)Fcg zg6L>5!*hvNjq+KPsOvuc|@lV zdr7DMU?qCLE9rnOu0_}y%<@kCXjA$FOz&M&a^F|7mjbA69vb{&#~bBcd*pri@#Np8 zkZXeJYJb{42&Tko17(zrc+NA*;2J3<-?dRam1e-gT8WaUSqZ#IDe%~EopQaxBI=>gpDC4Zf7|8Z1s&(zOTw^vAd*6b_oD%@RjuIBqApLf9Z$QcCFQt6NK zC564HBbc9Xa~mA8z3UM#X?p2cRWh@(D~Hy=-x;<~s*=*$0;k@{Y# zQ(JfVOl87LHDM`dFhhZ$ehK{9uXm=+sTPxflxqZKKsTKXvgpH+b34K?Il;E8%8XD< znjTjwTQzgpd*)ti5uNO{Eht0<6F3UsU$l4PF>(LnIr95GIn_QkaA&{_Jb_RmV`~h; zixBUwnD`tg9vX?FE|=MUgOBN4co4(=(2~1}; z?u`9m7=BS#Lot<3sb|yLH4SLZ&NBaS1xn(zHzje4oe23920VQ~#m<;HVOkkGb$V3V z>eXxKV-ywu1Y)LIu*ds(T_Mc9kD<(b?pQ5zK^j2zMAjLu)@s59&s>MBM-(1vR6`mX z4QNF=UAsScqsHYlvS}U$EJAt{j??2$KM4mVXijq{T$|5I3;ul5{R=>u4ZC>~Hg4qR z_M3t!^KfVnj&$3cRsgW6JX^CH>-N8WP9w7Ao&u7&^UlBJKCcoUYwMd zu7pp&511#DBBSi%lIPxfn9f!gai6n3k~1h*LB=k9I@nLBb0aFSx)ur_Zud;-UiKpK zA$&s}C>;03CD#8E6l-R{yfMo1Aj`o05tF-TwRNp-mf!Djsdgf?KgH75jl}6pxcyxz zVfSZd?BOOsEs7wK{*?r9pQkb&RehfZZ7-|ikZR@E8Nzq@Y3)jrXdT zRfTO7(sGwo78tk1f)wsA8MAhl1NHRt2RGZ7vO{g5SOoLG^TiT!2j5A4_a(;Ot?iR` z1qivlGVa#VFmileR#uouZF-Bq<7a|}`FaMz6Km`^E0ppjUk{jaxy`|gR%Zskf3+o3 z;`L~X6Bcr=B__&XEUsngb=R%TZ?3SzkhqR+PAm7ubL7?%ZEmU?|J>gz* z+hq5vl4%o-Il}Hfh+xi5p$6^NzXB5OcseEZRX}({n0c2QZ(i`!r9rSuw{;5ajPt^Rv1yGB~@BP zzv1xNG^%{6^R={({(zx$gOYD#(ttW}2RA_rEUJ&MM_DJ1lt$|6+~?5^DXSOE(tW9} zShSo)z*L(jTVSmH=5keXq@1FUsq;Wr=c7W-Ozok4-{Xf#{F!Rdxz8^?#qEAuotFg( zIfFDFgTUIKl+Ar?h?>h1(vsUz)N$uJLl4u={i0+3T)HGxHq#TUqX`3E>fecQBI02#$0A%TWlsK^JR9>hsbsl%Q zedq>P%LTnae+}$Ti6ND@p3|nz#<;-U)=DXMyJqml$uOT?h*-H_WW(fry!%!U{rlnp zM($U%(;t;>E(BGaYNw~OO4&~B_{?Ul>a6+DCQqi*&&0_IiJj!p5ijni`v;~Y^d8MK zZVKrQukB6TL3ZthNO|!v#T6S9sT3n-M;9D1&-iHrc-e1%B^LNrA+lyN1qunZGRe=V zD@5+qHk6qpbwb>uy+oa0mt6@Z)fM1$_NAp+4f6i_O3T$eD*S+D7Y;a1c~SvH-w%0x`g86M$erTLE#Znnf;S z3sd(9NN$Tb_MB;wXDss)$iRJAi~>Q)-WF7ES9zCqBxKjnp$h?k7IaIUT}4YsFNKIo zaAF@IPy1rpIx8S~_;?zA$^Q;e@pwCX9thdKeCbS;a!z-zd*x@45!@G%!JN@+KIPmb zu)6xd*8v&cES*oSd3nvM-QaUX0OVVx-I&6v6+VPj4~MJRi}li7CGN5SN}8!jCk13v zH-GhZd0krX6OYOK6}C-7IwwS?s=mr#lKE_bv*7@R9MsW;q1psF@Dr-TuOLpP6ImU< z6PXE*yo)OG_*{DzRj(gnEtoZjCT*iAsxTr8a34EbKN>}9I-1rAAy_RHVvYHmDVUqB zwL&WEL)febz9LmT5xC;XKhE_pn`7uF*@r**>Mxyzo4aMWxx2Ae(3?c(4(n9kh43ed z2pEHvYykz@VmF;?e@e9-&Epeseho@!>evKFr^lG*0aw&`Jv)yOwLLg83Nd$4lee=! ztV6*$Y7|YnmMV}JRYU6YIIV}Gr>>snU2w0}<)n@!3_)7+!~kIishLY4v14g0dzY5S z3RX{c%x^LXJz2JO)O4L^Q84K2PCGbl)o+>W4B8m_cK%0b?f-=^!v#A zbS&@N|7mli{@P2_Trq;nmKBFmN|5bG2XyInCqrd6W{6OhD%!D=_#Nui#%*% ztN7SsGZ52z$jA6<^~6a?gB z{Cvf7mG)gV^lV<6xu6oRp(|HSJI*;`$=G|C0C{$_$9}*Ud6*h)nb@zRu!1g(%*lso z65|(T?*)Nj)KhR7xLmtVe?mHnpTt> zugT2che`#-2T`ugzpu|BWfs8VDV{N+Mrk#F$eB{|JbxMM=O2nTj4PcUpON0daLV~| zr@D$a1zIIv+*8*k&}#d|)<6?gU)IP!h+n#bg@j%(sDH@l27 zUl)n#1(c7Q4Y|3@`vSDLNChUBs zb~WX8m<@H1_-lHoiKN1cez$FY%5+}9;YId^rDrtemlUMXqHpfW62_yDTh^)+ny{jP zN4##C= z=2(}8B50b5kD$dEk(c&v1ABC7_1Q;}+Pu|?*GW+#$NqvQ+eEe!z4TyV{IciH-hjzk zo0`5Cv8`{53? zH5V6aC(cF_n%V+{4r>yyf%#XrE%wKy_2@o$3Cq*GXPsKC_I!UlPH?Ys=4#Dv2Yiy* zxN3!w(2hX8OULT&2g4680-@mLvjHKvyEYngI^RhQPcB<7;a;QvojD~k3dISY^Uk(I z*M^jH&mD#R{L59r9|&jk@3{|SLGQ=lc(zYg>$hN-gv*G|*PCkAQD%#!SrrJKWZkyB zp{bNhUy|NZ|5=I4C(z0UR8`*0!}~hP>#nP%A0$p~RQ)Z#D~@MSoZ9NQ>|BLbGBe8I zu?l37Q1TieraNcabSxGkO}|x7wJ7zDV=T21^W4X)4X|pvRWth`ZE|Hez|*3h%hAUW z>yPm+pT58>2M_nF&EuYzvoTf|U$(~rDe7tEB^WCl5(sf$Kw2QWV`a@URw)R{qtqvE zE=wLPk55lG$7chgO5YhtR1h4&pe3Z=PQZb->c_KY_E*{t6|lhj$*OhDubPBY*)N?y zxoOWVA%Rw>zdn!K6$riIzWp-LArRDbZuXhZUWD9W>ec4DrjA#Yrbmz-m9bjs`(YtP z_rnGI{4LkFme87B{wqfMsnC2y+&&}kE*yyd3!V<4Uw>1<*+%Hq2=enOKj4$qrCG-Qf`^v2e@>{ zt-|)v>sR3K`Z4R;QEp7tbwmvoQ`Qu}HpiT~rb>Ho+BakESM46IcR1b|-KFO)X}ug~ z>aXLtZ9Q@x;CLL$6MTvq#~+bF2uz-Po3I164(UFCQ=#K%+u-|PcL{Vw4xV0LAn&fM zi-es|logJ?&Or+FKJZ&dL&I3XURLRq-q9Bg<+eA7icgn3JlNQWOJ!3rKR2y9k}gE8 zjs$fjBm}V--%-4lppE@8MqF}fTym+_0kMUZElK8tXkE296u(9NoTxj{6G+W(5NO-Xg^v@S*bKl=Xvx3ampWH z@VrV!I*l=bNdeLSt$fJae>w{b=7mrUu1I_aJC0HAp>p(#w{1jG_$f}?qv6M8f8q-k zI>-uxoO2Y%)ok7w;H5e$9tU*LZ04U0p-X)atBTLK2%ZRh9Qf01sK1M&Lyq%nKysxQ zld_(X{z88T0{JCyt3tQ%?XREFR|j?j*@B_DSw&e?EL3G#2M1HWzfUBlmR-$jb_jMK zBuQv|QG$Hmra~5e~{iMLvANVm#%2ooq;~5Tl`ggW3wZyi()6t%_ zFM>kTPxojit85Gp-8OrcSHC!+knL$l?{GyF@+{M?WRxcF<>S-#7(1tki3d_kAq+4n1-UU(n zA}SYOZ5cKKs`4L;@T@eC*vZ+Uv8Sfj_k2cmTRCVnS>DO&J1Y-V{HJkOd?~Bn&z9XN z-tMm!K^x<1NSMVZK6x)gc}w^Pi~YdEiw#qPy#AlOyf*9IitG8en|Wd{=5P|Y&9=h! z&|d?DCehMEKOD^VNMi6R`+2+vzQ}D5vPtQBW<0fw_2Z|Xi3u=e7*b(P%u74T0xy|n z7X?*QDJFPmTvd&N^<#c=A--3f6j9k$&SSt$M#+<*$)5+var++N=v#jP_x<>#XcmjS zw_)uwpX+#)S+R|k41YX%9FFi_6mgjk<^_;lhB+&aVB40FyO?`#f!C|{?7@LgI3cSq zqV*-*60|@LHKAiE?TtA^EbexP*gWrDUsQh2jXI`0 zfa&}ZkZ;j0H`yMq-TlGdTn(XiajaZeU?ZcUPVUFyrNc)POzDCG?UUcdXC`fPOs1rR z6#5S%N}NIE5T5KK@0JMs|a%m!CIDh8*)o*P==43|=ofDIP>-+s>&#)^LkF)sA(U<76=yh{s} zXO^m?{FN~$Ri&4VAH||YcQbF!v>KA3Tz$PGyDvbb~$$FqJ*bt12#F-hB+wegwD4DN2h z={pzQFp-;1O>2;R$!{WOIzYRV5a&}DILm-Z_&Ep4UrKt zSY76T2g&KH1W@Lv3==!W&kmRf3U|%%+N-Z~yp);bi#s7uJ!UKD4^&(hs7@9ba%f8= zVOy{<%Bo`bNu%2sQrSP%y^hk`{s{Hr!D)$;XM{ z&fQ%w74;jmf?~9;UZB3$bO_@$HDD=TVEGmYwIAwRO~T z8%%r~^5H7~zV$i7o#XS=Y{$x;?sz{zgmmHyRknUh7#FK#GU1!;N|+2#u*!pK0$VF}2zCS+O}>!S2bAd7H&lE7BQPIT zkzG7ii5W)rTRKgdta5W(e<@~3DCvvBFAsdp%*>qk+Z@_y>v|XCYV9ca*hnD~Z7bnZ z6Zjrla#dsBw_=QqcM97|!*!Ts_hhS4*IEE{zs#S#G_ToqR|JpI2j*uU7q^9Pi;|Q$)U-(RNifs+^O0Z3zOW5_4^94LrJHFkxwKpx_`F6A9 z>Rt9MYpXgVj<`=|B$;d7*4FwLBq^7*g$Mln^zEc-qc#=yL4{KmlSvH8;JE<#JFl>v z95Oil2OW2JjEAg1#J!8DE3E1{fXn4h+vhIyAi#U^Oa5EEIKC{py>e~Jcf=sZg*4YA zGn4xpGN{0N+P`dL%kWdvaK8Ez@y!+9*4t|Qlg!%NH!8V2V_a6+%T~?q96=gO7^|AL zWOEe8+a13jK>DMYXLQ$=XI0l)rw2!B4I3o9W;L~f#f}>}J3ervWU_XGmhfZqvrN7; z8>(dNn21>w(EMd7(woMBu=}+s>v7M`L{_Nn(6R@_?^kscF>3fJ zUa(P7C6slXd;C+1kSlmh35U-U=e*c4seKBJ{gFx}SQkV7jB77qRv2#;Yjeh1KM2Tn zjsyZ0Im&Cin#bUWWi9Fs;_lYSx|RxRq9U0VK6H3hU`BaG7QQ>6ZX1MEw`o5H`axq) z6Ewrabf?g)7W^~VxkYw8>RvjshHW)6yw*}Zv$VuZv@^d(c}xYyUE25_73~~T(-P44 zvCO%~XxetQOHsa#qktRg!sWQj9#7)+v0rYZidRo{r}2G9MG8qTS~9#VMVdu%Hn7YS zcA-xB@N2%4PlAVp-K?TPU*ML4l0HIFb{HB1iFw!<_1;H-^j@WFni#e9uz%+yp2sDSl6;Z7qj6K9H&Pi>bJJ^tq9K@VSDM}r}=tK-yh z8QCMLDXJtYS}O_NZQf4Vy-6WQPx57ST2G$Bw2+!c{z3hW+d;qjoM)OSiFb5N4*u0x zBBg(Rbj4P`*CcwL&Ij2;rGtWXVgQbgcs3qY7nTryEKBJ#C* ziN7M4B|)Ui-0Uv4D)uu|V2K5`8ET_2FC=*B_RGYZ_0oDya8pgFF3fs$oe(Wb3ilF? zUoo0o_ZOEd%?n%Wek~f*0XePHpr|pygt@z%LyNhfnb<`NNflH>V^R86DiIe=WN;oc z|B8>|yA1XHb3j`yecd{V!-VrP7vw7g$L6vj5f(k&1 zU7Y7}Fym+r!i)A1JMWV7FMm*(||a7ZI)rRPYLKS%_1u!;fAISja5 zn}6KA_x?nx#H63cK@nvYU^IRenO5vG_g4R^)!pUxG>m>vk>Y?VGvL6LRTK-$^@)Qp zz0%O?o3CJU*VV4CV9F%=fzLhY8XxiAosZ8`ULVz*Kf9W|UDcmC5P#|v>s^^Hqu!V@j%)T!&yYH7GvE96t@EU{_Lm$QcV z*}PJ5One`H2`=Aah94N0>pg#hBXuSm)E+TbmecS4KIFhv@xpiSd@DDt#tH=&@*t^XNc$zin8 zg=S%M`Fsp8fB(8CaF*FmKCx1Q*V0~ngOcq)hjH0-rD>2`DJ{Y{aooh`l~pcXC+c*y zH(RDp?^%puphes=qg&eAPfKLRBHgyaMZ>y?dNS2grRcX9(bcUeRCZW)p4dIDAL%)d!|$#StypjE z5#sD1eajw~TCKR*@2+FKv3rXuR4OAeL%@JP&AQ6JUM;_qj1$oUxh!5$zgh`f;hQ~K zDjlj+L3~226k8s-ogFY*n3oE%o$A&&o_;Z`@z3%Hl!6TS=QtI8GkOO(oFNyrhQ1ql zWHwkPozx;;if>}590O)YM=dYX3Z4Cz$cKl9+9)V)Jyjj+$7cBAN!oNl7+h7POeG*7 zw$2_8LPhgPKYiVI;6_%86^Yy;PshFsoXiR2riq5JtoFAXffFS|E|Md1(nu>Hw}Ckuol&uypZDm{$}UVbe%lu zn4Tae?B=Ld?EW><;g(_OUx$4ECx=g(j5+@5yx)KB{5vEP*|Zwb(<6`g_&P(-^_9AY z#`f+&bdF3+k7bIHRS@t5UA#OzJi4ea_ppRKHxoTPJtr$}1I5LmoRxS5_PB-iu<43J z__Q;GEydWk2w?x5CABS0{5022i<%1@+d=Jfh;8rgehQoMK_idUnKe zOwf7GQ6$M>qzV%N45Fa+-+P}Pbcs6lZk@EgJ+J{Q*xnr^x(!$bNaDvQBy3j%S3xO) z`Yz-t{=36rUa^=ZiJ(1958qzV0#sL}(a?14hjB>u_v;RPif0xY9bz&vGEz%Pt{In; zkMA@ll{6vv+mJNnw691&`M~G|=%v+fyL;yMjQH5+HRKsIMWckb$&nVn_a1}L6Us%# z-Z6^g;;eg_MF&(7x^Tj(^Uj>apk}QWtvU0syebj5%2@Y|Wgn4TT8md|jU$dPl5Ans z#!Sbx`N~N?F}sPxY`qXGSyHa#q8L7dX#qrZ^;DCTS2;^k(+~b#(P6d$JM=hUpIPnU zIn4o>QTmhenSCAo1asB-Z7Ow5&v{z9x!N1PFVK_VcidBw${VtD=v%~L!phSLXB#y# ziXIQxOc{s=ortmdd7AEA=>?$F;pmKLU~-J(>NOz*w@6*Mj}EWirx)K=znBr(=&+m{Jg)=(I+WbW(X`l{Ai*qmqa1#2r0a^bYuv+=gnwg?(lwOo4 za{}UK1M13hd9`}IwLN9~NhOZ#tR+L^;eu-qt_NZ3H{Lfr#zORzWOp--d6kDfIh{Wp zY;SK5kF6$cEV+9;TZ_x5btDX&)r-bVHc}agjkJLKStzz7*BI?6$|dI_<$dI&qB`ya z#n8lb{uMY$vwuuyBE0-hSh7i_Z;fG^zhq{G6O5DST+i>wy%L&6U!o07TDDl@tWq9h zon@Rg`lF6Qz5+j&vfqI+XwTwx=a9X@V>O_yiRR&Kj;m^rGxkAZI#z8w;af$t@Ta+G z8q;&w7Sb-Jlix&~P(8m4hZh+PU}04OcZFdXjGmTOiko=*voIDztp_MJ=XnQ=PG+jP zP0=Dnf=wR<&{q<;q?|@8$zI+5Oligdrva+DwBt;SRO*{1A^Tjjw!>BmkT}lFt!EnC z9X5K-sl6Q@qJ`gcoLAO*OXKO}rjS1z23_{%SDiMPQ|VD;zBE0g3GATNQsruLB3)jG zD2nIp@oU|9xRiI2*%Z?dO1j;N9**u!n9(R-kiWB2<)>7YHvD8sy%?SM$4x~kqI%u0)Ei_y`_be|&VP(88)G zCLJGt(mTv@V6it?T_N;!htV=-JW*{;p!ybCsQq_#FrLT87z{4}IR49f=TLeH59lS&DOS z7Cn6?oo!*oc(5jG6_W4u@B5hMJvDY7g18~X4T1{}w# zWRbQOy;p8%567xc436%okjU`f)nCrsvEmoTla84v4Wtn$i>ic@EcFeDM@eJlr7!be0dtz5 z;v5h7nHyb!MI*&jjV!l%h~|ldH@==Ht!W14FA{6&p+DVqq$C&)WSQ z1TcA2jEyss=vi1;%18)37k^{RDJj)JL`0&g#F$fzyg(O}Kcex)eRKH&B49IwU{`f6#K8Zs1G%wLmU2YIZMMZG~Zj%^7c<{h8 zNATgW0@eywz}5s8shDr|Q4JU+b)DkEW22+-25uhA8`?LK_YK99x`rnwZ6QR0bvLsu z=68((<$F$V)4Ss1}w4LES7v~KR(79$;@4u_Z^`a5=@$oS} zkhZkUJ9?F^oG$phsHo`J+q!coM`oq6m%ZwmOf4uPEG(Q`R@P5uQ1? z6_PP+Uzjj_1kvVJj|E;skb~{(x#z3PS>i1jCM=Rg58;KEh})|FaEUnO9(XDAE6?uwN+tE2^SRx>W>+2ho%Eg( zIuQ=)v*dxn@#J5ti2UZ19gEy4JL4ObX_JK_672)B8q3E7NVQ8T$m~7|vQt?rHe(1rtGVaYTU5jIBG&#y8tfp`4^}-}q)U{saA*s4>R9X3J(b zhI_ZCwB+m=dQ6}8j7xb^tc-jeCa56W=r=T;zZExjX0WA0QEfaFl>9DeBstn+h=#k@6$GBLU$SD+o#6g9L{t~VMTt}tEnWl&P z2*d%S+0>wABOnJJt<>iTXYNN)cy{vJz2ov!_i-hKWhvtHUaa8a5^_5-ayl0{r&RN? zvK;o`tAq&r>QzYNk||A)U(r&lRb$awS%tF#7I8WYQ^SVctPitHa##2hdn1mS$Z2Y|Y<0TECki0?&*kj%DFnV?R_Yi`7&4pG>ek6`uDQlqWz}G1xxno80f8*3&WzRA<*x z>-b5ZGyp8ynpJG&7guw{v824ZY87<+)c4aQV&aWsQcH2=YB&e{YpeMi zOTEhCN+yeGrIs)9?PGS1Y96bsuVw3hn(V4j)8%VZZJRe>?=CU;QE5rJ|43@vdpyOV zlvLus@bfLmLO4V=29ZL7IUq^j;57AX_I*}{uohEG^Y;siciV|uwd$TBK>aO7_PZy4 z=-ImqE;Sa)mXGm{jFg^S0U2ym0kf0iFZI35*U<&cYhOB>+S(qFop~zgl~@?$m>V7F zb&Vy}u>V1v5q--pO6p7&_>duu#J-zVnnZAAx!G z9P7lfH*RsCm2fi5Td?DtvG^q8vDS6vQQkY3!}cut27lAk)|LZ(gdVRQ$#u_NH0O@Lg)c0 zAs{Fsy_Zm=O9_!KEddoNp-4-l1_VM0MM{7WlANILZ?2i|nls;=`Rg41$(3ZYv-eu- zdG>1ey|_MSb-=kK`vAM()4f6(VM@TRo^#^Q93n>f=AU3?ct7j8Z5>{xC2w;;d-ZDc zUn>N9Y8)2Nrm|M7heWO94-XcO%?K zB}ZWCx=_JY*JLjEX=koSFSuT*i~!?DfkAq7Lkf{FcS6_0brv{!y$G!*^`_||?BkT{ z>1@4`@Uxv(6lt&VkgYVg4ETTfBJhVr)|c%?!7$;14-KU;|hm zkG!Q!P_)BjPpqVpBKfc0bCjtG+%{PQ-L6CcTw&YxV?M&5RbX;B+33+Uz%R710R!S~2Rq0^sp5IzV47bw6VRJQMHH53VmUE-o&g&GY%0%!rJDOYz!?%xCmwqyA=s)z@qc(L1;X95|>c58QX7o{VE& z^_Frl5BK@b2~?dLxjqhvBg1-coAX=BoF3#oy_%THkGq)tVcl<4o#*St3!d3G+L_Ix zQsy`3KV;wN=drCZ(K1Sra_$JJAz21mVDr0b?6j`W?*70eo)DbTdfk3Vp_2+oz561E zHgpxP;(H!zd-9z)9r2X@(+SL^A8@z>L2e6x6r3mp=ID+zXRyj`W!}LFqj=1I=G^bG zU>BT~Q~Um@%OOSTybD$r`pF7EV)VMkzSugiV;`VGM@Qb-oAf{xr`xPfg!;twcW5Qo zz0#{`>G99hCx*ubuq*sM*e{ae5Z2+CcKKXo=V8e8Vy$mCNvP11nU_P@GpO5jN#;ZJ z-B0dvx}~k&GG&#{@U&~>$BEVqYVs`G{;-NGKJiS4C9K5s8uKF?F-r6C3fqRx`daa`z>))$sP+rVIKs&tX5??nGBw+70wURsJ}$T)p9oys;k1 z9iK|qZGY6p^q%1gR8PXwVzK)^Nhk7Er{Av{jg5Nr^ywP=v7csJ-ymIb*x@2VpQP-y zw|-J|_?RyD@#p;juRiKoIVtdL9@21I)ngzeLelBg$(@^(epw-s$=ELw0lzfwe0=kE z2FsI&*sqt@nO|dY9U>GmFOa_TT=4PK1q9W>od(mhDE6F8pJHh{LY!G&X3=+(jM}?` zUog>XaCDPAia-93xG;fN(Q2ou{d>$OW z(Y}upQM;c<|MRRX>pkQTl}!5!PU6uYoZ!5NEv1Bheo!EzIe7#M zVg;4N%WCAf7EIsn-|ae)Z1On{c`FzUd_$x!F0N-e+f^Qoz>e~-lKQi+`k+<}nI4ms zbnLNa?_WaQMBZM|KMCH+-WZg!re!&Qd3io-KWnpUe3cTzR-NbY9P4|X)(wK49hQF! zLgbHy_-XV-T~~57GqG3FxcRs|U{5Qtjckngej!CbD)_7hw@BdkW<}A*8qmz>xgbZ4 zgIYsh4m@}L()?GBPbEE{MG;c!CGKHfME2$I?FT{3y{aV~V-|Q8k&x3hKeT~NH6l{7 z3+Ae@`aRBTJ9@K*NN#lFq(aZ?*O^M_d#RVLMCTk+#}zsNUQyx^B%``zPa}k-lyl(#o|}-YEX$7%{GB4b zRq>_w(_F#mH)Bq1=+fZORhm<)%w5&`5N2ysoML8Y$RwXhv3y8!X9X&u9zyKhr#Z71 zHdxdZ{+1e)-h$`3sF-$Il){4tFZ3{`l!b>>oE%yzI-u2yaDB_#VNTeC(*x~yGn|Tl zI9NoxtKnZfJX3ndg<)N1tgcO+5}@f+!V*}ibF!BqXPq;jW`bs~1|`q!>X?yF;a@=R zc`(h)AI8<{x0%aIIBmb&kpS7aDP{(gJV!Y&odrdYisBtd=8? z5qf@B<R0b<=7A1}Cc2<-H+SYs(O1s)B#nIm09 z!8e(9Ps&_`&8k9Rr+#MmFAV?M3WfO0vGCPr1jy;(5l;5(Z*Tt%LMvIIr&NXP^4rx9%@>!FGNJ{8e^Tjh z5Da3U+7JH;P5#ULx@~t59@h93Pxx2jzP`TR`{=;yPXytAFg_Ua=uc$G{eKoVWrzOn zB7y5~8kjJsfWk+;pm?6NDt9>fc4%#EsGUnHs43I%Q>E3lYisEuOv8^6y62=cG+kii z;~BM~_oG7#Y2IUxB*pqo>v#APG9#3NibH(24Y`)f@ zuzFFaLWxbF#$dw!3t`EeG$wB#urb9B91$Fd-maAaKp$n<4UgiRTO5Ltxxe6?`lSsW zJ-Uw86v*a;Ip;2a=qT`egT4>vz2^808%y9i!_sO=T;9jkPe$dKehg)3{|DH6dOBW* zkobL@jJH&QRGKS%nJk`=3GRFWt)Fi3*Vag{4OKAr1gC(nI9P%hl*`Dn4>o4TZw&A< z?$jE@H0yJ_ZZNJfQ2jP%E+7yadGO!|15zZx$^jt9m2Lt~j%l>Bda6wgKLdoHJ?|O# z9yz7+e?k0~`FPj}5J{$0n~j#DyhwccVXb4|q9pac7-1{yP7XcHHv8Nc0_%3DN&Ak+HE@U^?|4p(he+I`h4#pds+Bi?mHK29%S5B zZ=7VqN?76aoP$_AcH_;GFCEttlu6lm;QKC_+yH^Mx=Eii)-BlNyH!|q&7e2|?(i9XlN_VOM`*6{;Q^Y5B^Doi<`TO+C{q@IxZgUYQ0N{OY&f~Ui?~JVL&64@Cs*Sen0yu~ zWa|qzdj2Y?NK@e>73|WVXF4Hhg;(eTbc5(BpXJ*d7vBZm{%Cr~mu~NUD(|k7-teW2 z+IeVWZTZ)uBCGO(7(1QYIr!C@p!|qDx!&7D>qN-RQx^b@(CIZL%xi)%(++v1I(FhV z*w~@}0stWq))muRV{hzW)ZG9LzMT37Ha1bP+-Lqa!P5>olc%hy3saov@@1Xr(%Vxk ze}l6X4xbaM17zJcC4RR1BH82nS0Xn?T%0jGOxt(5?sdy4m3yFa!{8t_lKig;q4Bmm z)&ME6^)qs*O-;FkHXvwMZ~_AYQ$4Vw0Zq)=Fa-~WidrEXlHJc>u24%?`c$`jD<7g) z@NU&6vS6+!T%s)!zGS0RpH91(S=(1{%A#dmi``s(D_xZt#<`E9-k%|-KRCZwtX@2f zR@TlBd;Dyy>j?xlxT*@a2;%%i|3xdUateJ*aNV1B#X1cu5%0zWts+=dv+Lq;?e9!! zd+i{6J*}F-ucs&3k4(sbLW>CL&&T(ke6()a)N9<+LQYKo${wwYFs`qE)WH1~gQzV8 zwRwbcEDN`&WR=&!>r@_2N^8Y~d`kF%9m3mB-XqKFkV%!4z$YXWwyR~c|NKtF`<|NZ zS>fOPw(*t#jsDU%J!|Gtt0HaK&4(VZe-HEtA2q^_REpTZk2}Yrjln!Bjk7Mgv9z zPw#7`R`FQSL+;fh+br_fSl-l0b*=5wjC#*kpopq#i2?(yw*u`gH+9j?u9gI|!{7UE))eHu5WAFGVZEn(PJFz-h>Ot#w73v9O6|)$No^THjoZk3dq@uu52Q#Fzi&~;%GP)6&CaQrKm7S&Igu#59=`3| z4WN?K>vNLy7)DN>D6X$JW=mwB2cKFE2WQkJ7e9N}_@+#CSxfjka6BB_&dxDSIfa<> z3^053fslhpOrk&PC{vX&r(Re~d!5f3^H6dPBIxi}rIBMzUa8DU1nBlUSy3nDZ^-vsiNKaCy}rqtM}1DuObaVVdpXT0 z8EA)D+H4I-Lkcu(wm0cx`y#{TjzhVS4+Qh~1c`i9xxrL^i%RzL`-xRMrVD!p!{@Ga zR{Zfw8n&+Kq)#zhd zd6Yp%4km56sQNxWhoA!W4Q&ZVZWydrgu@RGd#ki95PM@C#^_nV?clD!&(mYBw3hhG z*xCKFOq!Gp0;HrAPt6kuQRX5!NiMKy{ysS)EhwA6l!s5^bxhf%n?VwKdAaaxW)W-GeRW3@)k2gcAK%_ zWMhWyV-fMnJTdkX@qU!u<p-d9!Xf*&|2nw98@hCVdiePF+ZU_Ge~ZAVMWj*DSA0@Dhe zJJ0p#Q&OQg?N#WZ9s6?X*HD;{Z9-*kO{?wYUzQsD;As&ddaVk>Nq=G(3)?`YqD zq_ti}EALp&gH$~i77Wc^;Y@ZWNC!@jCcr%%@2)kHPR-4Io73G5J0mP?3Y*|%Am6BD>tzTB)~(vFK7Wvf%z0b>`g&raGkat_bw%FdMochoc5jI50wB^Zsi+ z-V!zP3y0UI7eI77TTj+2Era^?svCD7Z_uD+r9zJ1ljeI)qd#Sn^BdQXZtsS-1irQ zlD;7J_6R|WtK!<_+Ap||2TSJ(bu6sKU8aQ;yTe{i`~`w0)SU~j;2SN69(;>dFjs+C z*v6^NO10G~+h1SB1U__yiyLrzP^fQfrTUk;TOl=@w6o>>92%_KP?35+mYt6^?N;O9 zbXvR{HfqcjGft)7$h#!3;ewVL8a!tXWExoVY>@T^8?nJ^%TR|Ce~D9dRjo6ptcLgj zAw^bKVrmC#9(v7EDuR9DK2MCUC{}z&^Tw9g9OE`rrgm=u9Ivc2YX!R1uPi-Ku`6N3 zOI`T;0ka*5M^DCSJGkrl;BJ4y#gX?oBYPwRYRH-B za}O&XSk@AEgB%P4Uv+g9`NlE~Wl-m{C-0E@{L#zp-WtwB9cz{SLtjkb&YynOkE!JG z*;tO)ckI6d@i<#=AhiVKsUOb^D-u2!%P3mim^M}6U1S*MFGKR>p&jMl!_Hiau7FuCnA7#u_uP;#|C=L~u_%}mw}TwJv*!8_gP-IMkVb{KXu zKh$kgVk=*ouiaeJ`H476aI;CcuqgSp`WPpurLCWI3frV!}y|XabYr);rhiB zf)`xapU3)hWUYr92^YU!M5{`n`Ua~9_I{&tIuVR6wDQ*lY+j<;C6R{kbS3Y7>)bT{ ziYs03WIIs3ea~}p{*`mAshh6p%tHRmpt5>89=5AM_+Lg@Z>sloRO1jCJ)6(g6<>ax z$(t+K-|x~O1^OK!;s_`KS7SR(fSFDuK@akf91A1Qk-m6E(2y__m~rlP{P+&Z|ExK> z_oFM}OZv1oe5XbzwO&$g|K`Vsne+1td7DN@N=h?7E0-z^oGsPZXi$dBL#7lc&n0t^ zBCF-w!uWN4%U_|FT&)|Qj+uXHZ@w)RS*eLA4M)AqdD_~q;?&V-w)0#UD$Jck!0B6( z<%%BM-Sezu8TET!o=mJ2wns8^!p(^V(_KOKgWO$C3eOXksGRy~x%#tzak>rV+ug-c zKYc&Zoay1~IcC-4#cU&JkoNN;mfv(p*T(CPZ(NKyFRo`)Yg}&;(NOjB3G<^m>EMv0 zUhH)^Pi0DzJdW`V*+QkxJ;Svh)HHw3A<4bJ@Evgb9Y$^GEws~V8ubUEq~i~k zuFCIcuEd9NC?9%=cuta=A$?PPB*J+BKpfs?Bjm5I6&0|@!za~i4m(;ei9L*VFB{zry7XdjUuZ^vgW-8Za-FXR zxZri`UwFIp`6%N!&^>(O6L+%P;A^3YlDwz`P>g9qQ@ywSxL1ZG$W8)vcfCQ(vZd&>xjqo&As|-@WnVN+4Z@VAI@G`qonT?V$iqJ@13d2NSu+P z3xiCz@HN$wkXt`$HF9qqO;VU{^-}>QCzDMziJw=J5^bMrxlW43ngp4eomyL-6S@G} zKG-G?gS&QWLIT%xMgsYPt>1K~=`Y{o#dUqfK^y1SWlk6i=jT;NO|a#j+N-{5qY2$8 zJcTQvL)cY!xigpp;UYa+*h5(m@2o(Nx4u4TmNl`$B7fLu_ z?2}O7TjTh9YA>7i%!x|p>splh zEnqEg7ahfR$b{hkko}HS@-G&@mUcNRz(o7~)19?s-XKy%a6aEHJ;#HKaf)WU??C|; z@8cR~cU(W`r4~$@?SB9@+~k#et(pAVGT7;z?)1s|ZK?0{i?4CtPR2D!o+_$G^Ozl- zv#(B_xMpwe=-yo$Y5}@~!(uyh$bn{9cl^x?)}UJVSDavL)13{56YC%cZtic%i(Z>?M=4D;zw|HCZKieayPg{OyRwC70BFGpq!K`uQ}4! zPgfUglpaFq70m8Lta$w>Q%U#Pt?#?My?)#DF+1kJgiT(rN6!EM?~84Yuw;%bU#~Fj)+b8$-cDT(F6N!-q{|*)b7EY_`HZDq#`mTkmvIgM#qqt%! zd6a(u06LngByxFrdYCK2r?9JFTtf?)MuHF9(GVrGhN?yb1f1F0Xh(43M&ZX$nzzy< ziNw9-93sH{GnU3uMAFH)7}Ps;!}IeZ#*|pxFcRCn!-97*#Cvz?(zY{vax?aN96d!QMyL9%xIS)Ws9 zNE)h7X-zvbE+ZuY)a`WS?h7KEdMLhGW>h+`Iy^CPjXBhaZ|$ep@d$$z2`dp!Ioi*DNmq{6h`-aFrU@!lShHm}Vepq5aP@yJZPDby!EDY-A%)6wVqiW>U|N?$btQNPt8jRAyxH>D6mlzgLo}g1BezkZLw4DbeWecl(ELZ(y8m_v)b|K2zR8ACM`3B{i$z z)#54!*Ch8OH{DLl^41<#A;^t$?~Y+~rvJ#z)RL;|iL`cmN_+7OCR9<`2@2AH+uUGux44+J+QIL1lBukzhkpsoXVc{6J+aQ zfNv%RNoA+^#HQAyv-CEMO~{UScxnMb`K=7DoNx{w(azPr`+F*~xQS|nq@DPSY z(rK@TU&tK4-_6?-FU2DSA=5Vx;)uCjc1XuDRA1qQjQ=cd)-1h4y`?%-ZSqXOrvl67 z=IDic4oExO*elr2h8y?jfC9?UiC3g zZ`xg3y}TU=d2sEp82E)C>0;g%Oq|0kq`p>SoC@km0jH*sizBHxRZ_=AKq~^s(?%<%GG^~ka;I1?`bY~|yM*TqLsacljjoa{Hw(J}fFYqkolYg_^isY|Ym+9hCI+9w*S$t=B; z-GyP{@=j}#(!O`VwKI7%R9OWp&+1k{Ud+<=-R#qUW#3!7a&13@Unq*fmIin7_eX8bcP+N<&m^P7k-_Z`;wDcq=RKw=OKv7$ ziHq3hq-;mNoZ}f@+r#N0@D$)Xq`uvyLV41sb@u-@RFZHop#s1^OEa|W%lyXP<%LGg z&CLa3qBI0j%FXyT$Ad-75~9R+0oBd~6RY83+=24%X@0=7~3?5KM?B z0r6aE0~_5v4+cOBD5Kqg z*vfmf{%hv(rmCmgpC?*(G#lkARsfKhxRK#8Ao6Oz&W^+A+h-;m`d!u+!aGZq2|{?l zADD!(EZ|WL@=5Mgt*Ome(FM*@j1HLiJX4Un3E4`JZ+$5!Ez+CD3li!EgbsqUM;OfL-Qpjd9}H8BSZd3{mD(2G8$TpU#F(j%CR3lhUw#|JBnQ2 zHq{VU8Bd`aF0&_u9xfF%i|#VU*O{VxNClWuuv)c9fH7*oMl>~2p~xsaxn8uwy%|Q< zDSio#_FaK?rL>8Z)@>k~N4uxL)WHmSQw0rlBCWgH_G9BSYEz61%Yf(_n73>2;tMDP z>cy@!Z`>rA0EeWOlnDG5=j{KZ$fZw{4Zz9DcKzdyjH`VUczd;#yFFuJ&6$=-xw&HO z?CeR^&IY6McdCm~5wsqMTmkvv4JJq4mLr#;-gts)ZVbD3McUZ;i<)carHEHDB?d0o z#_U~j8DG zE4t;}|NQ-TU&t|#PG{zT!(qrMXwjJKWe~rHw|7Z*icqujD^JI_xv`16y5PtiJqrrK zj~EnWOu3pV;q>lh((R)10Yn6>O1rmhIthelWS_)0=Lp%|RGZ|y*zjD!C(O}W=*#9z zkKXAwa=%sfo<vldr-lDO$Hsr8meKC;T%wVFpxF_I>8cIC) zTl0ncd#lTfrC)_0y5s&1?uJQjW#!54dU7D+#h>e9Nt1F+OOlcVs z%y-r&0~x+Ocbz~5(;4jr&s-P&W=~Tz@N-_i`qAy#gq6or$i*Wq=Y?qDZdU7}85 zDm;wekJxZzZunCx>CIsvlV+!+FhK2LjP0G0$_Hqxip3z`pw|QI{Ru()zS^dKQBU2o zstD_@HQ!}in^@PN{5MMtFfy*r!!qgO-ETj+iP30iRz@~cr*WAo{Mc0DO7%p3zDtVy z$X#P@R~cFLj{r0VbrSA>^OwTF&EHmdJr%i?a#zK#(P~MtA~BhdKi)kZ$F=i(AhE~X zntyUhFSSfTd%sOw!&|!nm2Vw=vxZybH65MMMXiVTpYrjWnNYqZBeuznCNjE2*PrP; z3o26cLqM^_lTPv%f*Xt7XUZm_<@nRG%R!EVRiz7Or0Bne)HiyYm}-x;;_Kkqz^Wu! zziHulPGDS5UCSzyJb8ghvbD?4?#|A_;$lF*P)~XJZBp^q?Eekm87D0(tK;Zc!rV<# z*i{aikX`7B=nPuSx~x}&pXsi>;y#L)3vBY<;%*95FKqSR{PZ>w(yVT0S4f+Uli^#GvDw1|F@xq%Jr#n_xn5!jc4crZ2oo@f8JqvsYvsY$XuR#WFl=EnL)^Q@}B?l z**~DBLGXr;NqYd5yie3o7`W}z+I9@lrcDUy3tJ?_jx`&RJm&6}o{)3BW z48Ub(BB|ufe>Du!Q0V3%G&B+GAG|jGe>T%2bF@V11H-P@% z2Q|}vlRz4$gGAl&`l6%TzxFot3;!{M=YPfz@Lx7N{tE^6-(((0YPErr`HwG!QBQWt zGyKw(E8f5DJM`aVe9wO)g+?*(&$a&xZ#7uwGE&*X_|(|g{NLfaXe;AQ4VGMNgaeY2 zkCyWEQ2^!D8o=qx=uVbk1_X6q*MHMO7eOh)Fermna7$LVqDyQvKb^2zHsVWKh^r9)z8EYtO^NgMYa&TV9EqQyYnOK?<+CiLMde)_ zv_-g|Rz*%ziVaX4n|^O6^IrW%o1y_PPkfpzeI(FBRa&9Q`yF}wdw|`4Q?!5jRR0`& z1}%Q2`^RXacjs%qixvoyVY+V%d1#ex;MyOt{)VxIO3gR06|a+%x6xZhPtr}f5hh7V zihI3uckcX$b7jf|5X&T+ifxO6w|Il91~8>P{&^qL8e8*|K_UC2rZA$iEU-Kcpj@^& z1V=g#t~a?1Sr8qdro5&58QW~#uqV9`DL2XQo4I?b9;uBhZ++D>MHZ}<-l^aFf_6zy z&y$(FHa6c7;*st%Qt~BnlGyn`tL5d>?!m)mivOy@{9r&0HmI}hUU4m|sbD&7B_BwP z+iP>tY2{U`M{Po?RdEsNJ4t(RJ1T{;0(ViW19SLyi|3B6zsNaB+MDTGWCKoL^ppEw z2AV1ZjS|-DPtHu-!XESmgn55S-yF?FQ+8mh@c5nj4ma1$MMK2^#E~I= zW{1BsQA(F+fPxpMP*YEes(gFD+c^1R!T$o^svmKzAy8DXMjz)iIFNCx6DvLG&G_w0 z!{zmy@c4$sGwZS=X=K_>X6}(q&!M%0oOpp-sXM72ilX$NQAFHL_KFkLd^exEAgQxg zgd|9)AyXuIiB$Y>e_dRmg>&+*1Aw3Z3I1g*9LZYF_eSAZ<5%y}6lF!63v*vV1Qw_8 z$O(BIF0CDvXjAgmZfYI&dz)|D>x@dB2Q;s%6H_4r@er^G?@q zvRt57*&NNA^!Nx~nVi_)94Fyb8t^hkH^+@`_@tvXOSv?`4)`FxRcE-zn8cch)#NiG zY(o*AhAmjM#N)T!wmh|-r6}50<7o}$*PjRu1|w}+r#lU8YE=;mXudGZ^T85;cQ39j z(wp~ePq1*O172IZ?-uiLr7ZD4Zvb|&b?p`q=+R)&&8;K*(pI-K)qce3ux)}9qCR}l z_1B$65}M@@9dFV*rbS4#92m^OwKv3~ss;*XI z5oAUPZbsfuvi7S}$Re=xvUtDg!Bbsft%~*oS^4neg>CEkvQ|9{Cf-~8RRYWV$x4VC zgbZ-hFKi_`@~VyAWxr>xMx!C2_M3=eTg6R?tP2oK*Dc7JZ)Uy&x%5m@`l+z5%n|^E zIbxObF^5Ne?=#l~n;SmjQ3x2MreW-+M_cityv+XOCg5`R$UFe2cv;TqLRBN4x@MV| zAVDDtIaV(reeVg+6#-q)JOO%^1p}r-4Qo<6fxMF!Ki}4Xgv9P)*uEU14ki@vBE8W& zU0T}l{+JPPP^>e%-ge1&3HQAcw<;&^iZoVP-PWTUSU0w z%K=KMh?ZnI$HQ^F06fd8w>!`7rITeIAr$Uu(05oaEFnKG`5!%xJbH>e;HfP|Eh@TEj znNz&)+lnVzm-^ zh_tf4F|%>6$jv4z!YT)sGTV?XD1z86#PH?u)Dgt++c4+A7K$t+@WBLm$H@2W0L1*p zV1vI_-;G0Q;RUu$1)Qk5$VA$1NrRrweED@6$MaZ{c7o=g|JpLmnx2ei7g&MmDfKmQY+I5 zDnlRyxX=n-xcGKx^s+0=i_g}-)w8w!xNtI-b zW85Tnd7M-$T+r>LdsGv1X{^031;hcy*)M*eLoTk$d?XmSlhGIs4I6a;u^T_q$ z6LuhqrBu_frh%VSkqFH6N5P*{N4{P4Gk z-4zdrXK65Ce+=4ORljF>%|tsL1+S-4x>(qH2PHmjHIp_#8pbwj8N^;uY zM{#VVW1ZQlA3r^RRrC}=*Al&)?Hpj{r$A-%ckxCy{cZqH?f8~P8I;o`} zhrI%k@39yNkMn*7dTA4K;E%iVeUC$gwCF_jNeWiS)Vp*4TFl%YBwRD8vbj;Qsm-#R z2Y1`C5w*mypuI}aLsQBVqh8HLH>pz!P$R3MXG$NXewLhQo_gYCp+HsaE zz*{eE2R=8BSehDjPl2lwT}kO7y9H0DykJ%^k6+|IB;^5q@AG|&kb3J7zZhC1%NN%R zar{;|*$R)W6}MZ6Yj4QDuh~cd*246*{k5v@m? z{yht~fJBFW0b*8W!qvF59-yVK-+( z&xgm99SE;4ro}4+>dl4snBPwJ)u(+vkB{pFO`t9G<#kE?D)xz*q;ab<&30b4Kcc@OW-Mo3irq8i00R6szD(Y3VTv?a|8UfTW>*Mc~0k zw*ip64nAcYgJ5g@yrai&m^d7f=XcYQN9tn4KCEV!9>+t&u4Q3G9>EK2G1`e*c`AV1 z!$=89+~>LQW=tH{J;!PL&&#W;H59#3S^zIVE7|ESV)Pwm@jHmmE9qj{diW_(rhw{MRIltM@TW zO;b}-1gF^_l?^MCR}5Ia&;QO^wkIqx%11JD@h)V4`Te!$X;$wLDhX@pZ+b8I;LeRD zPW9vLW~i&x%emLvEm*QXZ4{ve?N{C%#}{;_O*ERilQ&A6nlcl7;%>~+K57RY-EdkR zEz9na@A{o;nbjVUl8?yt`IBI%T4a&OZM>kpKlS_as~jKb2L-iU_70&{Z!UOS#T}nF z^aiZ5QkO<)*EzrS)rv;cw+M%jD}r~R*pz_*eNv7ms}H?WZQk!p#?_0*MX_UQJhJuo z5d#(AYqp)8+_YnR{jEb*_u;WI{(sX($g!++Gw$41CXEmF(kx-k6kJnVTb!RCrZYI; z#RJ|=%vKCY`h680{Si=Fi%SnpxeK)NTDoBF%LmOZE$eyjra&0$?NK8Gb4W*56Dop( z)%%Zd>$2w@*M3x^gQ2u}laUdb9$>tsp}Dybl+V(IUh~2&pk)Hr$8B={UP{=L0Pn*vTmS zrs*b-azwn~OW@MbhAGIwalV?plTDi!tWZeKkX00cy9bQ8e2_m1A}zos!tDIym+xdBLGDl zbAE2)pdP)nY25;OCNdzRL-fmW}#iw3$escKm1E|A@{U zvhNQO6crWS4(B;iJ?42d_4-Hj-I9$l+_Zu+nd|yb+A7+~qQ7ZuY&OxjW~JX*a4N$pM{_LRTb*n=v~~wVo>amu z)`xLCDq@?hJ8{R1P57PJr1|q?iN{^}>;^PW%WZdt-9`$3pY5CF5?=QAF#<8<%_B|g!>|XxYWqst7_b#eG@BZBq zmm$&dgHuJ|);>Lzf%d<_2Xm3$9jDoTU{8SU&ZObQ)4`oyZ^LL!|56{<@Wl=|-2@`) z-gh2>g0z#Uc{d=wbVUJC zgKqHE5T{quu*~5W9NCrAN=#|@k~A(^^)lqb%bl?B?_C|MuwU#=Ju7M)*|JN$L~4^; zI_BS;7tAVkoq-CMH_DnKezYavK!C$mLfV0P&Rtv<35c# zJ97gc=k3ecBQ(iLXRp0EEC2RcaK4Cjvu>I=fE$zv-Dg*dTLYcoINo5QTrI`@ry2*( ziTe2ac5jrH=vZWtrR>(sdLYjmeK)cNF{`s6>`z|v^mYeLfxE=d{Z`{ct+X2(UGXxk zv(NK&eUaHhu3HQ7ep6H`zxM%@y_UqRq+hbS>`T3JD>rTd58rpol;Z1ewvx!L zrjh=4MU_hIc_qC)gwcpjnGEEBhP7kaUNJJfuE|URtP9`N4SHrwLG5@zF~UYhJXdJm z2csPww|1zQCYA4W6uUi|duu1Ymkrgo<*x&R^lHSlVn$A`2UR!B)??Jb_KGZ3e{Yzljv@Z)wybrh&I9?3(Ah zq#v&jH88&Rlsr${;6neZ@8%%ju(~~0N9+(oiLP&SM5^sH-Cm)MM1IA7O_O6w^K-b(`C*BtwtMPkL zb8{WQtB$vX)oQn4#5lMoDmT~DlB6Sx%qQpJL8hkBm2JW_9?0I}nz&jyr-{yahT2j=R^cMKR*Z;fSI!9&E{{aq{%4z7;)7($T7i|2h>Za1 zXeVl|nV)Nt&zR74M(%A!Lo3J73`4C)GJhCRPgbXdV9p`_nntm0LPkUCX zZt6A}4zp_Wx_CS2$6S`hE;Go=8`-}jla=a+=nJkEcnfG|$xGQmIB2}3-{*@;rIfb% ztZN@t>Agr;DxdrsaIqBTSh2R_h+38Qk$x;E`dsw^n`)p7J@CGw52sGEyW6ui^U19Hom@w%eL73euXxJ% z{U{{8!{pn-XZ*|At%o+jX9;v9eroHhb-q#CvH@7Csm|fd%?cUF2Erc({1-XcjmDFz zLi=o=6x~^7Dcr4meyq_x#JazFv7mOl!?UV91sUSdcJb8EDrYTw`3+?u4j@p>NhHpX z8dw$zQLU3>i0#sUSNj493yu$6Q+q9`wuPpF`JhJKljP!|n~Um!N2T-g^=f?C<$lKk z|8l>ekU6NxS3BAj^U)JuGDq^sD=b7B8^^e+d=b|H9royt#;1F6^c1OF@5Wz?f(rq~ zUP4?sN%^z%B^UQ6!b5JY?Q)@!^_nlnPAUe!&vQPVOJyvhSDJ#=fSn^fLC+dMz(}kV zY_FT^QqP;phDJ)EJiL%fc|Rb5fT(0J2*QP4_E0mkNior7ZR;KOvcT+Z8u;8pV`#~o z*gq%5k9%&o?Rpbj%~hv+zvV7G)tc4+s%-t7{Mf1!W_6Z+LHU=R@rfkvU-NH=_I`=X zR)N~V%0%{J;9RLRV+6i4PkI+_vKMczg?8)6P;LO25UJp6vwyf%N4(VYh>2eaB=1{T z{}IacOExlJNU<)fHbCIfeKux;Eaq!5Z&0@pyVs-_?C-F#q<5MDa#Yf+hE;L4j*k~A zgzvT6SyjvGVB@r?j&pZBM_`uJ!k%czZiJ4H=Wk0!H)~akUZw_%3Sbs3@^8&Qy| zcnk;C;L-QuuVj@P0iT~R4eLY6td!se(+W0;w&VBg zLgnwKc$b8bdn27Esr0N)w+fZ+!;QiYed(8Rh)Wxm;i-9lp>DlS`e;jH4VU|NIo(u< zEk(e?fCyZ#$|Dhae%fTkB4cdw2!I;w=6bL)INlRBx9PRERt7)13abmd1@xLlAv)9s z>(vCoBTI0y&fKMakq`GHy?p(hEI#Gil$&aU)CKdMtW}Vy(Ph}cg40y;RBw%2e;5NF z;8W+IWsq8s0CPBQmq^~AXR;fsxHi}s*|&+uvY~tit-YCp1v3?l@HlE0qc#Al1cW>t z6ZPg%-4dZeo`&pR`5uKbpwO2nTH4b^Tm z{F8`2vCh<1vK&B{IWvbD?MloVM8D3nSgDmemX9+{MFpb1=qf(FFrt+cFIk?;f&#&H zY>(o2cxrQ~wtTCteCaDvD5F`kQ+lUFubumfaUJpQnZ2IffDX(-V;HY~`#V<#!c0G*kN$w;E6Y@9DIhEeztM#3& zH3EmQc6IA0i4t!%Q^eEVxjfC~7XnQ)7P-h6{^;VHKkWfl8geDdDY2^v8QKprM4HyP;%!0Oa1EOh@+i zPoy&J>YJl3*7}Yd6@*H|qIE@4XG|J>uP=>%jCx8EAzsw>Aa$6h%*U;*x>jrk@Ur0t zKJ!nMTsOagSGL|`v}eX(b^zs#oY;+P%RF~?!SU^KPozsMy~s~%HK26*h1zl1st)Mb z>38YaZuDw_-DCKD_|!F=oYMF@95C*C)S95+OdtZ6vu^jLE8v%&>Asc0FuKX1(~cU! z#eoK1vvrQ?Sbb&9Ui!h^;ji5jLD$nE?~vtzqH2Nn@}_R6hEd;FBF@9bp?#{!pT(ia zXySEotnbU!`CA(qlVz_mzYAntI`Ex1M7oj1z&^q}62!DVG&~XkVMhpU7qHvq`!2`OH0F8zPxHwc( z=JbGh3k1sIq_vC9#kRG2cYE6|KIXu~cY?AL4fTOzX6-VNb8A;>2}c@U^-Dvu0X^h5 z1Yy|wfr#2oxac5+KUlUPFVE%xRVAa#kXK-;D``Z-drWP2xM>-HaXdr+4PzeUTQm0X zDBN4bQj!2;iB%-H5ucHvGMydS8~PE6As&MbuxU0}#WAg0Bg?CQk@n zR#vu=$XngpGj}nVYL512#iCcQ+IBj)^1KQn3V_!Chyq@5{B+vfClO$(04|c-3GqkO zne0qPiIsx>!#t7~_wS{t@`RpEAQ4-+>j~sd#7Q2C(rn?$*fWQuCG^$_7-lb1Jyg}7@xaH4N_*OswhL#)%cNxNhaK1rG zD|kyf$#h}UiOSlF14I^uGe?B>pB-D4)tnYe)qFgn8nk`&O1GE3%uGWgy1Ns zs+#h?@tg;*_JFf{0}6vFS&uj4ey3bcx9xo>Go3;558wy7O%T%IZ6+Q|Yxwc863b>X zu3wN(D0L`dS1F5=tV0~Q8qGbIm*E4+c3 N7@1uuzjXV_zW^`RWu^cC diff --git a/mai/docs/path3.png b/mai/docs/path3.png deleted file mode 100644 index 557256db46e81b78d13946712b1f107a82f9f9a7..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 132359 zcmeFYcTiJb_b&{HA~wE)iYP^?0@4MfC8E-sf`D|Tg^q?MEnr1NX`zRvG?6A>+HSP-fMkUIq|p54UQi< zcZ7|N?YNQQO-nX5&M4Mz^6(*6i~qr&NY)>Fkfp(Ow(3E_71jeMNY_l4jjcB6=>GkK ztY_{AhIT=0Y(g)7|Ja@0@jYf^W0n}*)V=e_8BgcF=Lia4W&%~}plrwg;qyA$a7{ZE zKlhV{@Eqvj{^>dV>z~o{Ftvu-iz9~S%$uo%8IgezlU|N0f4L>KCh-I25rKiV2Oheb z6n)!f1bj)wU+t9>|CZtDE}vF1aJ_%znyU$p*$zta)KEERB!)T{4J6zzR>9?lX@Guc zTA-;Kk4Hu;f$AJdP^E>mqW727Q8g+$ z=ADBYI6=FPh{kqm2Ql5&IsCgbH8HIH24uTPq&HtD68lCS{SleRT^a-2c+B$&ZZ-sG ztik(+Vi-Zx=25A$$ND5P9Yt+jq8r;+%mPzuYn67_!{D;;-GM-CpKMJ7Mjgm=>{w6z z5Wp86qqYkL?(*$+U}!otkX3WcURg|P%x-2(Z43~VmY&|*mo7^HsP=0xr;(kW%&5|A z;&ZPnJ}ysZXJ^-^XG-gb{OmqGcsmn3YPOY6Z8va^CR@`YH=Z1oPtJ6K*fHis7`o>9 z+A9I!p-RZ=U1t@{IE_Mp&d=Yc=Cyo@0-c33$Tb98Ht0f-Rc=29wWLMAA+nd;PK+kj z!;zrXoy~=rSN(W&X?Bw&>t5T8kw}{Y9Dr({YViQ&z%&*O1}Z=!@aZ zgT&O&HRR5vu`A3a=fW6J=dQK}qrRYz1U#D}l3U7P(lN+2;HhLPd<`hR@q>rVL-Iz8 z9U=>p+Nr&p1)X;JBDD<+rVl2eU$Tq=R}gXBgY43&^1Qy=s&ohNSag^V$75b@`9}%+ zb1p6!{E75ykd3Dz`K5bnWO(r7%X=M|o*IJ~akq)>J-GOWXE^Bz2AT>)@tnqIdc5Ww1&-#5u~Pv*4e4QDcXtPHa%oiNx`Tw+ z98?gi)Xz^qp($z_%zaXKp#1TAr?(ucWm|D9?Q2 zuOxCQGN;w=kKPZc?qnU5l{de5@bJ^-c_UhJqn|6_yGc?@fwDos z`-~rhRE#8vTC_{;_X}KQj21AqUym_oiH~6IR6=0t=Ux}Y8vN=-x3aA^i^K9)4F;pv zP~Yu$BzKW~@QfJNcp4c%O#&Id9EO%P!O#KWR)seeUO+{Q!WsUz-o?P--f#DRoJ;42 zY{e|nm=x$Jni=|YLkHKBO3h1CPv3XMVlBuoM2GI_-h!X!XC&@>Zu@V2W$GAoGNG7U z3PYV7gCQ~#)1ITnaCt@6BJ?+CAP&h~(g&Q?ws1xw{4Z^~?SA255?*gJiJe5VE%eVU z&Ov$$Wii3k2tpS*mMe=(-*37b*lx`T`E-*(h=VuLn89=dD^gf{IkOGIq%Jy%T!Pj< z$MyM^{lMOtxG!IRhVv%6{npTzUUlsEg@@sraZ5B(Tv;Pyi9|~b>##-d4Pv0`Kb~wQ zAkoRtg~tw6_byy;i+J;zwTBt)pB;R)h%?W(+V~k6?H=>*_Z{}L<6|u%3cGK{qZyQD z)MH_ignt&ZujA3CD@{bCKI{CTUc#9vB0Ec6v#}K_LdYUDy$B%f`94in3fs-3sO-*L zIA;{BwIVTR>kj~N?JHHhSE*4N%mG|43LTYr`B;8x0sWDo^FGo|nO7u~0{|(C=#QDA zFnqs$=Xbfxl4%*?0?!}zZ07JxXN`+-%*FTn%NXYrb=DeD-YcqzZe=Pk??OU;>FsVN z#axcR`8EHEz~SfDrH6%8qPCi2Xw8JTjz0<*D+SZx7yoj4u#_Dvt)rtuNwZUVj>KxH ze96bM>qxVUsMO(RiI8R?ytINsrbYCsRVeuG-!8d2{f7B*B9ObzkLC|*ZMcE+C2)~4 zb`4&`xPBfu|CITs0p$bz-NT;2&836tLv&DDL&!wz9EhY1vfSOCU1jSj~TI(QSY(3FsM| zl)c~~+;QR$O>E2J5OaU1+hCXTsV;YphO^|dTPoc#cvx@U^A7=AmMogdprUv%%3tz> zhIDM71coCV@al*EHR66JRu2w9AcO>ySe78!wLhw*|2Fn)Y_To410p-ILK{l8`GrOk zeu`hY{I~S+wnA{l|Rr1@Zj5 zub_NXx9BdAxh1pV!8B-W;L90W4=rRDzi4SF8$ zvELQLBwC%=E9Q!1Y_e=6np_<=uzI*4HI(GHeT>2%fxaV@??<>#Ol|8$?9{r5Wb>+N!a2k(6B{zOGb zE|QThQgMF|%C$~O7&=7qsm>239nQ>*{oDHaj>pkGmSToqE&3w7pbp=CBebpI%K`YU znTtzG^Z?s$d8ULw86j&Ey)1F#0+jAQc<>Vf@93Ci%(g>zxMvYy}%S@XV1oGFzZ6Qr{qify}$X2h^Y?xGWvqB!Vv)na6=a1 zhE~^o$pRgJ08e>E1(dm8z^oSpLS`WJH8{gJ4AC->dvr9vtN=0%Q6*e4Z8M{lebur+ ztKLuasOAn5ZVJS#2c)kCI~|qWO~0QQxSD4175sZf*EWrK_OxkurpCe-;UNJYmagcL z0`3}VJpA=6id^B69>c)JWH9$!m=$?9BktY%jQ%n6lD6At+v&>1)=A1EPNHD+e#X+( z7u;;(mttC zhS`~?w^s@a03$W!Td=%ZhOTJp`9-%0;P%fOl$VL_OIJOCL8Adrl!R6Gx+Xg!o1^jW ze>DAE0=Ip!1x~43UH2%Q`dT4+#e{Mx>3afyo3CWn=O+TXt}OW^xG#N*A=}1yF#V>L zGPCc+bLVHx8SL%u%-{eZcn+j5j(<)CCoOma1&sWo!8}T|oRCj8pNi~%hR|m*bSK*B z-y>E8mPmPZZjUg#)l*2>4}Kf~upn%`3v)S%(E~A~vcSg>BzpciKOX5W`O=kx4Kh(_ z=LUzYIbiBsj`KZI(v9D~@TB|b>fG!RvnxP{wC1TA!OY}Ot5D^lm3Cd~dZiTl|F{QIaonam>24Xn zmGQbwwyE%0l~pmFx77mHt^o|@1`qS6(?U&od2h36(2Socs;o8XKAMVBuyr}NLd)j- zF~tj_De0zR>Cnt5`l>Cw&P8f%D7b9ReuE=wiX&~Rzaj9?U_eQJNzO5>1;`<#5XwgF z_%@Wpu7KrOpgwX|4)lW)w4YeezCRI2&u9ygQ5o-k4KRZIO3kLYl^)-H<7bqSJBJM1 zM3}g7m_kqy8qe!`Z89{R<^K#p@}-rP71TEItsmLUd5hfC+%Z7+rkLXFH%gyZIkt>I z29Tz-Grz_5AhhQUev|hKjM)>T#u+`B6PuKorjAO@$8>Li%Xc>Oi_?S+l`NvRv>;ol z`J>a1gOS>x8$WTcxuV)(8!I#0 zIk5>YmQE}yl*GIbm&AD~6=U=>Q5oe4oYQPw~} znjL0FTGA_-FuW$L5Kiji0s2|=Dv5=Gl@?(US$oAerjqHcE-YBXAtW?(y2ex3RZVi| zetxCLU|cw7^xm!_9M**6b5!b{{`9bjUf-fNG6Y>wfUnI5J05k8{eg9pc^0+zS4c}{ zs*?*EP~8F*;SHrC&;DTfpsoP@p)72h2y>^K@O|GeV5DB>OCP5|ztu;UN@v`QD&UD; zzCk%G$aixukV$~IIB2pI&+;*7Fj738LfNFy#>xN^@SX1pGgb6#w=73hXAW#sDJ6?F z@~mi6jo!taVO_}w!D@ol$Xcq&w7si$b|2E&~U+$wL~TZ!$hH(D`f@3nC_XL z7@QVnGtbB4iOG^aN_>#qr<4$WjA{$tv(}na6j0zd@3e|E)iI6kr@XLT>gjpevF;ac z3FU@}Q{#7M$A~BlgHlYmLWH$nS&GVj_6@DnAFk9A-M?H_uI)LSD-{Gt9fE3Pln>#6 z%>R(#qYfu((<-3++QXuvF zI9}V_!Ab$8YdR>?Q=~Nc-%V_6rw;uadHqIhS; z7ym=XfpiRd;{kbuO)GKT>EGE zwG)Cpjrf$1^@+bd{?Yp3b_V<}kL6T$p)zxU@ox{TFM)LGVKMHL;G>Ur)n-N;QB_w& zHcU37uH`^^uZaLR3a>~>B@MO~fX;cWfC*1qk~C62x7ty+ROo7+TYV-9zD*R9C7}iT zO=4FWPwvvn!gq_Lg_UjvDeP{3);hv26s#ZeshB6tzeFB zU!8_S1M$k;>a^l;Bl7X&uS`3b30>Y1HR8y{C#YbMSc>a zSSQ;XPbU)Ozmr7%XMte$*IP@k=(}_DO@$_Cbk&qwr}{Ngx(W*LGYE#5bU6TYuK4? z8g^K0eW8prY zN^SJ)78!$CHq#9xDPem%=62C5jU#vw31cNR*L0W)@%h3?^R9f0Z{~z9ZA_~=|5Tf~ zue=$Lq;!XO=lTZN6lk+t4Q`WjCIK4vc;YoVSOIR60Yb(1Z7Pg zs#+@8;y5vlT4OvG+xqF`i>+Id>JD7y&s>RI=vGB#HF|rbE1ZdJB*Zp6>TcSeq=ecU z&Ux!lauC>7IEnjAaf>Tqx?yXih0I*Fve)-dz6$x9NzjsB4;92?aG5X zO)vCRbuIelkpiZ7`c<~P_8(1$l%R6<(B6X!9^iy9;Sh%);hJd0lrvb^gTh6yUH#gF zi3)cVJ&J+y#eqHD&7|Z0!S$s0y_HAUZ^8-2W)9LX& zr$TbuK6|)6Ev&X}qCjKaBVq=z_!!hMGjqPJe-pX9Nz4T0k1c>^4y-AWC7FX|6MgHp zsKwSz>MVVG2|T+FDyFxNeeLi0fSB-#tPJs{nJE_CorofXTZq|GiwgKB1Mjm{x2zFq z6jn}rNqls$%23zw< zB3{FxQRDswo_V2m%{@pwr3CN6rN2H_7cg8m-HjL_%ekcfWY$<$n|VKL?il57UWx1_ zF3BUZE)lnA1u0VGZx(*aQ?=w}xdiutY6P~ktb^Lvu4j+V%Al&qDJ-wQjjlBuTA7q{ zftHca9e=~`+V{y3@gV7B-(@kaKn$=M(Q1P@5@m%L9(p2;1KFD^7Ih51FB~r&G|2zC z^~64(`@=HsTUC9uAgF88&0}mgLXP^eygux;QP%L4OpJ6Kb6=#<8M!-#82hq~DnI~R z>7GrBMJe)d(nrTo%;?rP|BJIjQ`2Mfux>rZ^1FnYx>-#fRnI`0`*hP_WTp?yOr(t* zvbH@|lG*Dq#ED&4petQO!V#=(cvT0znHaW=S?-M~IsIcm9dr3NOjDpl;=h%1W^1?j1Uw$InQDe0? zI<%|~u>CNdzM9Da81(_2u$o3!!5LR*$YsQ%ze#CnwRTARaKq*LGV z(r(n!7T3&$XKmY3B_ON%jIfes6}HR!N_}`MKK^REMgyK@FD@HZ+== z2NtOkTvlMN`}lhk)d=X5OD*9ZGw(uRhyMwe%pDb-W_$Cd zC#G!!;eDY|aB4^FP*w?YP`sNJ==&_N$x3SVywgkACN_L!zFj&P^(w#^`B*q80rFh? zL1f1HJzw9v?v@yZ>X_*=2dPH8(6;xh3lVqH8!-KSA5u{wKgEPMv-N`u4ML~7tH8F! zId&~U25(U-f)+#ICMbUGiZdVjN+(Z-IqwCn$T!DehrDP&s9>&f$n9~N$ee)`gM#D* zfqGMY@#?sb)tAz@Z~gRBENVSR)O1Z6D<8I6O808+YQ4UW40W&gp@)Q#M3TiKY1@wG z0H>v$$AmgN1)jAnYs(U;tE7*fr&4=W#x4&aoqch@)@_A?oZvodHLeJe5ql?j>RRJ6 zEwHCiwax~~<@^#sRapg!c3G?;PJ2KPjmRH~zJ+>6SM&pOnAO*&^i9l+?qQTa*cOwbp7_+>AvX9q7^4}%&<;K6_@%LsOucygXXE6A1!-_}Q(Q7{myory>UQw265zh_ zz2F))f9Hv_!FnoUgpZg5*f2Bp)BndzyhF7myRy**3bNGi5zKsM#Vt)f-v3GdNJ$>k zou@YkE8ZJw7b86(=XoVnKq)=yj@10-K}llD1a8o&Z3dvI;gmak!3s28Sk;`^fEj)Wi==N67lbcWim=%5;w851fIn&g)@{WvZJYj3Ru@Z;nTM}GRg=NQ1 z(M)yZ!khwlfwa7C*tYgk_Pukgl_nVv14?{F=Y2C47fRMMRMZJ|@~vi!1cCM13WFav z0No;K@WurlYbbidyk^E*e7^Ct7ZCdF(JSsu3tY?Pw3V@`^FrGXnT9TBTK3e52H-p$ z{a@glflf7-oN^;y>c6@iJtrX%+Psxk4d%n^cwhT)?cG!3E0|1uk z9+}L|Y1rMN=(8-RbgewxB@{^dkbCvv^%H_uFK|tx7Ae4qbLI-aR02dFKV%Koqt)8} zqFC3jV;jAJx#NxgKqx3QMi&sWIJ&iQqs<*D57JN`m^bpglOT}Su(~Jh$kiR!sBHxz z?Pf=n`I_cYPgM_Eg{4f)8|_Z1BzXx{r^PzgOR|#=BGr2NB9uyzzqWb@7eq2W6S2GZ zytd}}f17ffl!H<7sg^Wg%bFR9Kp3f3H?_+|jX;~tMcuHv_xoC#CK7jgFs)yb7NV0@ zj}tX_73}!V4t$)E1;{tk{85m$sF@kMr`3D?QMGEIz1Cuar|N zy4PP3%@`$qP{`1lMoF#~BOcqjq=VoOO0?-4P9yIN!pbTaww`5ogSPl|!eNe?YB7D; zqUu8YM$1nlDnFmDGp_mGR2<=cIYO?~0tGI8Y6pI}!nJkc)9Y=tL|bAO=dcB$q9#9? zPbxoM!7eZk5YQ?DThS#lPV4_y)meK*}8b_U6F5JD_PvjU;5r8$p(P`#H)sSS;!cD*R+( zPZ4AYng7}aAcTDEzZ7p85tw~t)>Gdjyt>0F_YOdkr|02{ih9hN4>VN-BxBeD8qrJm zZsd}pwPQIM>MU*@>Mj#>#L2vDCFcQ0bi^tX;m%!6y0=FK2QAosp0jaoNV1)>^T!S< z2=$!1q=9Zm3dJi82PPi)^)1qpv|@_TvwmmYyLOg;HZ(5dy~A{PdM*sVHqgj>RW!_7 zt4%Qk1fFC7%kKJRhwpI_0Lxf+l`K8u8yfGS`^GDIH7pxg$#3+SJ({&sQa^>Sn!*A8c6F3QvQ^K*w%Ll&hal&+=z6^g@$qochomby zW4>H>Ra*C8I=`O1lXTPH$0yTj#sD#%cWaK}?wVH@fUv_-?H7J$9+L~+9o=yZM#Vfd zNOH`PNa}s4@pI-fqdtCHzwxczNSI1esv3`t@~%s&0lL5Pa?<&iijSXjHEURW=*!qZ zT4#ZW3K!63)le}B*!AX7t$e&aK`XCcd}F{d`doGV0*~=il3-Xib`00OU1JohY{VQq z#HVfNyG{wKN?8-`&o%b|X3(q4g6WzqZqciR{Y@@)gnTsa6%8nc91Jf0x(S%7aMHZZ zcqoS=MrCP|rxzuY##+2O&U0=}r%e1qtHm!#J7+ZA7>el}7vkZ4!`0S4hr2NX<#iZY zD=xVW=h@;uwNsBOJRP}Ljo7x|9s&gymgota!T`ZhZTVdO8;ev-J}&&KJW3sAKyb;| zseRCy7}yN;N-|TL+Snw-$ns2uFkU+rX_gj3~Eqt)pP zn6wO4`$Qdksi}v%OX@s5o39Ti8fjN47*z~}UnwXDt+zVb=bO4aCQxdl2E|ybe(RY= zRCPK9B=S!XkH=P4JDq^+Ym9j6&kN2eLuZM1RfJ9PDJicUrydZQk*H9JZVOmjCxt@& z#`Ar}c(h^rlMmevc}NIYprgt%pvbiRuW6C?g5h_XT0-hGeQVO2T~@{AJAbivybW&Z zd-s!&do`cCr&w?ZFqEVTlYou;UJv{vGDbZ&lX6`-ciPr-7e&-ie~6(ucn@P#I4q~( zF2-o|n#=6UD=yQyZ?o$S!xUf;+_8L7xP_$La-k^6?A|pRL4foqq`m{iHL!G&YQ%nu zb~jwJ&bD(b70ngaXB7d`KB;{!MWL$2los<#J4ZQBGkUz*YL&00I=uK?7- z6eH9|gL6Uzo0j@(4gLVIs}(=Zet(q|kbG^Zi*lypM|H>nJNs_(?!h|K6QWv*jg%91 z@T>4Is@aJMb+g?!dv<3>Nu>qPnG>ngF#|D0A*#cP{Awl%LUU)0%1K#HxP5(oAxx+9 zdW27ZRZxCWR$Z&%1g6%8LpP|(Q9hx%%_he*nylGAHv+@%MiLtjsI7Q>Q;)eW-!{jg z!#}8@j$Am%pLKKE4U9nc?T*&_?U{dhzO%om$eO!7*N#%zz{ayx&A8BQ>4$D9r3}`;SddKwyxbm zJ9a>(zT@jiN2fwN-xaEy`QOV(8)CX0>9->h|%bfhElGF<(Yg|9TZxhzTGrT2*gnrpnDEug zPthr8wXE*K=(~56?ra%lXvpj9Ow*{xlcWr4_^-UU|qo(VgYv#-FoXh}Q zozZap(DR`Pe$(?Dd?A`(EVxa+tsorSew;f<&ZppRX3aR+zPr5-aKWY3gofgTk z*Me>kHhYuwDBCeKL4zgIBY8_RH&_C^x^@t-m69|WbAveBhICds?+n@XXxaFBbQUwH z&s997El+#Jg`GNZu;=X)(Fd9=wYW9cnAw+?Y9R2}vvw!s+m_I`c~I=0QxB&gvy0%e zkQ%}8Ej8}NBVVKH_0Ft-=7->vSCBI!9KY4aXTg6vB1cFf7e;5INCR8bzBPF|Vp08f z60-jl@xGc+8k~3azHq!&{htIj8{7AsF0L#-`Bc=2++@C8Q-QW7Cug09PgWc+S@QSp zNySLk2=64!jJCY?oyLM{I%R~AN_oG_JbIr0FM`g8cP6XTL!n$RrGoDZA~{)PZ1>hh z{}Yq`|5?yfaw8=v>YFkU|36Fch%bubv~KZxdTeaZNAFUNG(hv$sm))*7t?Lshu`V( z9_E};eI7&_P)GRIbl3>87eoS3SjOM77sa5M(N-rwG-6fb{06suhJ+_OTW$wr3tI3A z`1|aCUnv99r8na_ME_kV@!!Jw|Jx**z7sBrPm|pOR7M3e_S@HWOYNl z(h?K&xMn{QVt5_%ySnDqeh({y@%_Rbxn|oq@i~U(Me$~$Pp08DjKCw^tf}8yyPt=Z zVJVz^ZtP)qE$WFbtA*{=Y4!qX6T`})i>lH-9wk@4?OSSh7k`0ZjM)5nKd6cSC(>*= zl|swnxfdE0~{9Xi+#|4^O;1;r9KU%qZ`aIX<(#E!Op)NYhri zld|C2w9=c=t|NDO)9!h+eTy!OkZ?yGi3a|Yj;`INl7kwnZrd!=dJD?DA_JFdc~S1q zGx&ajUqmBTf>!4b(xKY5Ao(?)VUS9t4_Af*+*$G?^idHA%s_a8AqRZDUoJfbw%&H1FSxT)M~kNk;@ z#wjXZn3Zd^EG@W!DeP_7Hd?Uuuv|#DCZ?S}J67j|aMz3Lb-)H_`Zklv$c zglC!x$rcY*EWEuDDkN)RBE;IKv3EG5wmdnwR7X@V@OrB=zc;yPYH5W$Onuh`%Q7U{ zGlxYF3`B^1?1x;g8xN!me;2oU(~Q!M>u1d=gLEffehMb>3%Wc--~>b!38{E3tTbF+ zr7Yg0@6GNRA*0L53H}+Ld~>gIZgaKfb#&ORC#!Zwv-SJO`^$=-4K~Q)G%hJ!(P;S; z06&&QHVG=P4r+!e(FG~TlBNo}Y9A@zoGoW ze|Z($cTUBl>TusZL|Mb-s<^gpzh&Rb^Z?(MJI~AtT4lRiLhvHcS2kANkBc==phC18 z?$1^tPqHLvXz*Fe#pv-iWW8Tc<%dA}D(}v$b;~aqd{p(TJiIqhr88xW2sn zxLj;_;T`ya_7uOAm-OK3^>uq`hj~upqhhQBGhNbiI4zjU z8BYg#dW`o8QEuhVjzAfnel@|Yh*-#1>xc_CzG3$zAXIrk$GK^6@ugPX9c)XV(r0V@eFs{7l?rHn( zReZ=;23LO4kmc{~$ri)fo~i$U3VUKzB);a$q;!tGdm^9^l`~+?g}ueUJuSw3CVXbkXsS&Bok>8@D~xD@=xXqF*l=|%}bT0B_w>YWo0 zao7AE=`e?XW@RhnRQmUeMCk9^K5YCKviV~d!9yU}45scOFIA1_X0Z-hL7+a}GONsB z+|ahz=@;EB0_OUNmXNotu6hl+^vfD-VAa@GfTq`U_-G9|IprCFEQo9=A-Y|N;$~Aw) zTGq+!etCrpE7Hs^GZYqvh_#l|Dax~4IPp*bX!FS|B2?ALY-CKH?m)fl%ozXpdkIa$jOaCM72x+oy_WpFJ!`cuJ?jY8T@28)ya z%DvE_W^Xu362un_)DxE~d7x z{nqV3AbrJRF${tW!!sX*s_nog2wN)-HVBQQ{H?x6aI6nCQdl+41I7-4ox7gDbNn|= zKjVfCL>kR=uPXVPh^A~fxx8E?xp=9wR~UV(qP*PYsXSSsvtHfz0r@J2dGEY8vO{uP zpEL{1X4YDML&ywXu?Ji)lznUR_bMKHh0g8Nz{{?s2v!*jd9|WuuTy=rq_p(MUXKC5 zRjEYQqJ$sD6xO-Wroy{`{i0BiDBILxmn0Kvd4K42-_{+>ytcJ(Sd#cQGopXLWcfq! zNww@Fmg|+T5Jv^Xg0<0US43(Ll`91eM?r5NAn9I@7zm5yez+Po(9byk1agAwx1uPx z!8f>h^278+u7O|~gz4JIckTI#7JXxtRG`-Ny*&3+bK(j)`-PhCuR4FHgl*r)Q)OT? z#gJ1P;%yebf6Qd>$&FsC_bUNf_cyNvm9r2Hhp1$;>5UA73?4($^dTdR-26e&?Vd2H zgQA``8Qsx7>D+1|S!IEXhClE!rY-g5ckq$2MltyIa-@BvrhVzN;2Dr+_!i|rP$uM% zs}kJ>xaYi}Nsr2MR40Rxgo_w&^WD**`;+aV2y`cQUxRz49wF`6ne&qnX4GL5`mx0E zoLd)w{j`;5QSi5V>}Gc2dd6m10O7ro#-kas-J=j~_tnYBoIhv<`#9DD{h>q!9e~SQ z{vbULi#09}=3|3NjZPXpYpXk^6yIP%tCQCn((@>3OF~~rn;sU1-jLL2exvlXF7>rk zV88^pPSV%hCJPKoqArJ6!LglJ$o7&1PeZGmn{nq4ze1bk3!iG-p|kJ^MwWtW8Zo<7 zU876dUB>exUKyf3LPbEH{Y6M}eQDfEwOq>S^xL?gvzMW(g9#;#s_#M`sOQznOeu|3 zcc1XGTjV|FgL;P!OYP;k^T7j9<}Vw3sRRv?v4xPz&4f^R&2>lb)w3yvmO^H(Ypa9A z!RvnnG;?^zRPVjf-a^NSuqw9!mwRD_Nvo;rJUfXC(zd;1$Z$XjWTGkWm(2$Ot@1d4 z$|c`i;e`MdcLTkNu~wrDsoO8Xpxf`uU4C`k*1DuRM=9~@_+?Y(4)6m=!U$eGMUl7g z*DZr=+isqhk>FK~Pv*i8>1TG@r@S0%CiiUIg_Ae|VM*DCXCb#`Ry29MQx^4f8EF*`F{9+E{Xr| zMO6Q(e>(P`!l@gdK{nPVWghY0`TkZ_efGZjzbL=@fAq{cfTpj9wf)O+3X7qJN&Iv8 z6a0SZ|JG6ZuQI9suVmSU9(L#H>Za(JP%w-ekSfp7`baF{UwdaL$6L~G78i- z`3M}onEs`Z^IeCs+EfhBM$?-HBW+xawjs;=ik}b@_3z5)k7xE5`a9fac^C}_w6`xA zU51uz`cgVy%6a1fD_)fiL%ZKpPiH*1D$~)mS&wa(bVpeqEf&v;8nC!L|KRRB|D`<< z=t{u^z%DTJWX8nX;a=eH@;FeB_R$@2{51=2?>7y>$NLJam16d@^|qV8e337gmK%p< zhR$wX{x$J1YS{Ye)2AcjBk#z^4U6Y5S181)$ei>YgKa5GS9zxlK4$MYN$mvox9vG0 zJ9K@JO*Ag=>t^7vJAsK|Xept14c^@B(!#ue;u^Vr1jCAPMFza~f z&GptVx_>MYRaw?0)4(QaPCl>Y4myVrS%lJPlv#jZWiWFZaeZhH)HvITHUlcJ^y|3 z-h^<++YrFQAT@4xD)kctsTy@@Zat-Z??(i8&&8>F7x+Qk=In#<4-qM!?@!G_e?o$6 z&peh1f{+4iuWQ<*AzlnZ1RR{D93o$MnAS*>M1=ZPRXsT*H?ywT9BQmk>r3rxsuy3j zy66xll*YiuXf;;5WeDs}TuM)8*JuwaO0!in9$LQh6kuIPN0qq;``uDYgQfVc`>?#F z`u=wAop0xiOTG(_j7n}kHutWk#6Ngu$|f$~aho3gQ7=HF0;lo3p*6y)jO<_k^p2C| zs3JL;Csy>Gdfnol9>|V7qB5i4B&TY*8l-Y=gxD&il|$~h9QI*c-MFJO#A^uBFqre;SoIHVP zA%rf_=9RMVb)S6N1hvm*hN=u~uwd-R&al2w6l?1(J=s0EVbp-=a9WCczkTA0$@-Ve z7t7c2<8o&GxD1VCl%)8;0rTjRHD~Z98_CA>oNZ{lhqd9_gR(m`y@)LvIhcKyXq;Nl zQkH7c4S;nhFe^pY!4!DP%-~M%k1FT3{`dT0A+0y#W{@7!P6{+0H52c_x2!izce=d$ zQYeW2WIi1?L@BpSSfm8{Mw=Lm|8eSY%d9X%tcH&>XB00jOlvn{di^IVE9wqHM(c_4 zrM7{z7Y~)Z4`+Q#8r+tK{xfbAftOD?ImI!h=c;_W&{sN=vk_fB;}|)!i*$TT1?hh2 zRz=&sQtLEDEMqlwtgB3JN9q~Bv+4fX?tQA~+I)a|My4oZp3B0Z7fqJi_hn)Sk zASrcX(kL@eIrnDg?UiAzNKjBgUDteC-HpZyiORedQf<~cv_wqOY-2|1jfCf_1$au> zD(-Z7eDdh3;{A8@UX*@hTzwP9Xt0u2U5y4a)onBnA#e~8GRE>w!9xFEVoUu-hyed;AjVe?WeO-jb`1E-RTu4{WPZ?}?$XGFF&nh=%H!W?I1GmJAMZ9W#yF-8=G(d~)h0X29_M z^H#HKU#o6R85|{7Wj>FXxz?c(u%#w8(mc>Gv^{*2wi>y8cS?&D@wsP75}o4%`ou-L z5A^Nxjo;Bac}hV0T(isQ@kRsuv-d+rci!E0n(?-lQ!V)gtnbr4S#ih5zIB_&i+*Dq z?-r`un;BA&%buZaYU83(QuPC?kaLqP(f-sR#~qvL4&t|GMyRF49%wR{&| z8#!-bvTAF+a=fTbS%G_HstR*F!bKxX`?;@nILUbh)(A7_J1h-72R;1ho%1SzIP#Hm zJJN0F)}FiaZ0Pd<6n;tSLs+L9N8F*3wkA`VAXBkdsu?E!$ZONIQv6nb9gj%HY_CU> zR3OCEwN=^V)pT=AJy4rAj378|e zp7BN&QT!H3jJI8izgs%1RUFgb(B_O1dN|!t=O}|Rz4dK2_}qtpO6awpW9sWDuIRPQ zK4U^#Z)udZ|Fq2fwOc2M4@-M@h1Y8Hrls60!`#w^CLbcF2^Icogf`27s-S89sMU{n z$CjHmSrju%HC8ZEjdWoSn*0{mzb0V`NdNY&#DwrUPFo$zx3ip@F)Ql-5W3xBrKuGn z@KHQKYE((3VuTL>dp4}9^H$rPeOZTVG*9q0u~~q)iqp8r!Z~w_NNE186`;a=uZHfhPeA=)R5hMJI%#%$BX5vA`!E4?GYsm zwOTl|J-loNc|QO>n|?5D`IBuc`SaBZ5d1D(2CG zJ(B_qE0{s%O+Zxa^)TQkD$~{e5FBzJQRSGsN1X?h(}HY;n4EjNom$2Iz| z3tN>kLv6eQ#q-v=hgKR#qf4Az_=0OI1MFHpue2RY@bw6pCWY_WMZ_ffL1|%$ zy_4w<9&U|c0R}A4q3%V~U+j}JSR7l94Gz;HoELhtrr}aZprth>t+2k_yce-#HnMa* z0S(=Cuee3hF_+KVzGviD4^`BhmOUVl)OEy&q~lqm>pg|ny5hBTh-)zw9aZq{bZWZ! zx9(=Z!sx<8*7+OA>;Mrqq%v)3hWg@4+%0I!<0kh)3Au~J%Tj^nf;#RZA$Iy#0OHnf zi+@^S&P?6QSG2*1aluR^vPM29Uzzpi;E!|f%E&@{m5p1$nHdD&rGb)i^;PajY*~g= zhTt#dkv=s~>F|0hE))6e$`dS6Ofy>PBL$80I06Mm%KG*5Vv9SbxkS2(-Xtv^D4(|1 zrZS|*^2geQAK#F?n|i8Y6(w`t?5meQ^~;j7v{4|{$-GTHfWYUgCMsG=6lP{zNzX2~ zS#Pa8V?tQ{XeAOPJhB&53`!Cl(Uf=b=Phqzm(-~_&(#>+ybcXiPecUtnrx8e`Zi=3~bm;8q^#4< zNqFk(U9C`I1kxqHbBzu37QDURq5x9U4oQZlx$yVgAR5_%eRXlCz4W`-tw=q3NB)zpsO zlLeb8+7+p#&+^&F7Ju;U~^3_YN=EVa6;^)<1!z$~29Nelp;yRKdh_?ada--)x zFr58+LZtT2yHD%hYD<^<_gTv2NvlsnkE#;t5GQ=5Wa~3@z8ImSdW1Vtq&r%PC)qJfd?->W(jtd?c7A9(W?XS0aL%!+f(<*Wl>G z!db%#Ze5Zqk>AWG{CE|)WQ#h*oWF*CbuJ*D2^=P#?XWO!tTesec{-RSRs}8IbYb|g z+BA=(LBgpk;q~QRx>Yx7uH0#jf9Z?J(>w;6cv7NfpKKqK3W6!R#IYOUoQ=c4h{&L5B!`G^=iMxGo7i=QM z?;YGGVKlW%sRMRdtp^(e=52g0k=eX|*;HP1UFoQ*uRy>W~6t-y_om{*pzS^5nri-aZ&WN;@CH<*-%67%Ae{gT(u>kNDuf=Q z^cG@6L}?OwM|y7|bg(1669^cob@gwYcXqP&8(T< z@4CJd+W%(q8mPE!@NwT+7YQ*}ImX5dp*|Es+_abT+P(Dqr^gN+M`RL8B@yZ!zg92|8=_!j)GYwP&Gtzq5`i*?Vb)*58Phb^X$( zIeLX@?OHqrKe3b`gf{vRr^W7XEBIN(CTVjDEU{u+QFV+(1H^;(shoLs`s??lJxt9W=9O4u=HuJ>eCC^Wv|iJQJBluYd4cvh_C zRFFhST}!*1GSOJ1x821$ie}$t$`V*ud9bET5;2aFPcm>82X)8hcYAs#QMjYy%@#%N zoa%W647OaMtyXy|+attiHIGUnCFG6yLBJ*kK7~~0?~ec32yfl zL}xI}4knvcqs@nEO*k;$$YQ-k;0Na4QlQBW1K_#T7s2IsjDnPixMr=%UFJPT7!pfB ztHetLp$$DfRTs{^p2(^4@v+u*7PmS! zfs{$z)PsDUxHY3bjcYo6?$b{cgpFfE*6UKHhyT9Ns?`tgxsar9l$yOa)t!f&mAO9@ z-I@VA1-{9hEZ@OZPfXAE0ypduDiy~2*>T27`5|uVz!^zr?gQ=S^#d9Y#FpR z;2Al-yJOI>hYJXjeYN4R>ciLACB=!veau5VZK-yPGS4I_hxHu=K8091#G3qO8Oguz zlT^OV>Za-kEC)3@?%^+A#4cL}#%Av~`y4WtaY(5o!?#>XBP+)D$^}?cN|lN!w`(i4 zI~%}nd75?Aa~z@)^Inp}RD*a7X?8>k$=(CQHwiBh!tkBXpuoF@|4LGCbMT!K4)II& zR#$Y1Z#~Pqk&+xZ=PseXo;9CGd6ouvp z=8lA$YLrPvFf{Y>g(z&h8V<;a%v9pCLfnf}KfBqtqdng)*;S`%c0;9UT2-jo#7$M^-Tg9)AD6X z>B;Hw!n|HhoQ8ZMu+-V@X`x*Oh7Xm|a{79Z)Y;azc9n9hg(b1)xu)eVYfoxc`7)aKrdNN&V_ z;d-ewf5k8Cir^WL7V1b2Q$T*_N_PKw#e_if{yMA`0$2y3dU>OL!X`D zfi}>{DkQ?DiLI(rb5Ev``j@w5e8Atf5B7m6^Cc$0Ir~)AqAzxEzEvhsVMxlNzT8pZ zad435){;_9uUeOoNI>Y;5nrYsbQEn4slZ8#Iy;{jO-y+j(pfedag~QFDW!fc17q1p zPr_DTxH}2xtDf$?{%<8wz-55rzu0w!Hpw+`tf?=+S81*|O9D(^Dd(ixhv`+dC*rJ-;QFP6f1#-|1xr9n>+iQ>5 z(A=_H&f;-4J17ol1MK&76|bLnf{cE)Z}o~Dfl!zj&mNY>WI{V_03coC+=buY*#W-R z0K?7YmEEJX^G#tGrIhx0oW4~B7wu}Sb6Ut!X!9DZY~kG$!H768hW)AKG?l@_uZKxa zJs}&=w6gaXey4dz|M}v9Pp!`H@6cKNO|zJPIj!Be`NPkO{r<)UeQopR!oO%gX)0HL znpuC`9#k>uH}wYOP4uuI{)4Fxv(Wp_{-DmwL|dN&QG{`J&LSgE{USg#tSjgeKL$rN?k(=Rpr!G9!nAIy*b?UD_1 zu9LndVYg`9?qDm8Q90te^!DUwJgDG-(Sjx^q4*-}`jK>j;eqneEiP>CH96@Tb&CzU z=YpZhuN(dV5g4+xfxD{=k^dz879Qp>w?xif{w@=CB&Y&1JK0Ak#%$JgNPd=TQIAux zdXMhVnd3@CsKPZuYYcc!UTWDmK?$St1r+;5s;%w&2)`VZxhuYPnv{fFnD-f;PgFcI zmN49m|EHduRjhh(Wl~Zd*M{1X}z4G`dR8av}Q*v?9oOa9>2vG9)&!NYnc8JrX>fyoyCB@%YpwCYLODfwD$K7xXrlCAgFz!Sx^7r4jZk??X$`Tt<4=zC-PKOl+ zeLlS&uI5;sv$|KbPLHEGzdy zF=O7`E+BE=ky>%2!UG01W}vFQB9=FQ1yonsEG_JKxWh#F^l23&w~_~_XDd?xo( zh8utQ)=#zfSagf;ueRBL3aRn&sP3-*MEnfkKyB}2NmU$taQrC~0>eod*}S+N_ZR=u zKUdfu&or3jD}DwP?dzG`^SA=^-SR`1=%Zc}dbkc^Rba|e|NY8;AAX<|eyWourkBR2 z_S+{Y_o6N-fD!)BC3F<8Caiu7KdP16ef6_^Z~Jz1e!o7ix(6%U?{>l*%NkZ0N?p5{ zBem6GRk$Su7jMfplA+HSm}b-uwOl{kX#dj#K7`*?bnPjnZU5~ z7%|t+eNtWG?2f_tG`ok8nNEX^Js>JJ!?^7t!H|aNY#yf{wM?3`TG%-KVQ9o28vJKG zM7;ZFJWQGJ9sCrzk?}uBNVWex!Ym#2oFnn$(J`p#`)7pt^Wg(WH&D}${-y0yoIkqP zyP3#o0g&Lz(a(SM2Uo0j>;^5qVyo%p3uqU>D}#H|XoKFR%?o#0w&Mp=1xd?}n<-$1YV@^+v_bRD9|%zDwZZ!OI61mreoWqUFf)=Fenw z3)OS3-MNHLjwf3j{{1t+xHE3eD*?^Xe&7b<$!w@8*=c-fg-4&HhRQ4xN;`4p$eMFx za;z*hRNu)ew+`*MLnepphgN4L;oBht?J$su6C9@P1iT|nvg*(ZCvgdAoHE=A&mHV= zFkc0ifjZ&e*K}o22)Szn=vj(q{A|x|GPl}Ev-W?3Jc^_L4fjy2_)p}=f8?AEH;<5H zY5xp}3}3GW<3g6B|3OPJ+~ZCg{pXAS3rfdk@@qMLF!&xoWtF_Y%F{3##2rB@@i}@( zei)_;AInXpG@3Z28lL=4_a z9P|5G-Qy!Vvn1lBG72VSuG;4=S>s|+_=u%hB%yKDCnpLBGCX%Ze1(h2q-cc|Z96)? zMM-V&+$JdT{`I{+ZL40Ji8b+cqrnT5aDX~}U9PZcNJOlZ)EJwZ8=2G4n>Q&oDpZy! zRQOp<+tRI;Al&#qpr3*eS z3rIeT`n;9vYC?u^L4H4v3rBn-WT2X%?Ab_pA*Wm$=kq{1Dhw3q`ij8-a9*W}Pa~d0qr8&aOKw&2dR}w^!tLNJ8)u ztH&~r>sLE(&2_>k`no#KMM=r4L6*x;&$}N62Q<-)YRWM6G73}4RogpPcLV;(c6RLq z1?Vqpl#DaB`z6z1kB+M6!}P}9n)4mU-4LxPCtlVY z#UR@KUA-$un}XKxuIMfUPnqYA(jGS;Bg(G?GbRITNSOBqScuza^BDy+xJ7M%2kDrb zOpGXy`7}zoH>!q4^n`>p9d8JHxH$bHTkiFQs+wE$ z)pw#vsG!sBqU@cre&!wP%j8jvthh7A$`RW^syrn->izgdk_8|}4&xlp;vdKx8v+1291Su`#L;FfVE8QSo_o+%|7QY(9 z?1$$np`!}m)}froSrw7DC)a{focfPm%pYd8KXji-ehXp}R9Z=NPYomLzU2tWS4gJx zdfzd{uEt#A^lkyGsv9)2{d!m35#cQMs2&|xT=`Be@TbFElg*!LtF+OuJO z8)uzx(-83dd4pCpHnUFYi+bA{@hbW&j;ot*ucntpM(unUu`qS;tUk&1H%0GW|ml&MX|mCem!yU3Z1?|zJZUtZ^6aop9TMT6hdmtV=0c!dqUKcxLZ0Rd*yMWO{)Bi*@>@) zG?^~KFCZIPH-~74W2CMgm3MmT7#{-tFv9NyuijX3`>LfG6Ec`T^i+qEJ?=Y4uBsYt zg+qmEG@ zC6|YWc@F&;+4+0$i+{C+#o$NHfgpnp+=omNmy)mqlXdA1*2eyo*ib>^hN|u4-R#ED zvw8vL&|B!p954EyuW>+nWwf>+=Y_VAH=j(QIUkA$lSzb{XL`7!C*$$tgO~9#OkN!$ z^2YXp*NjzN-#kl+VF6vUS=9;`(xy+fzf*C%?i%#+e&~Z6c7MCtr*4~P#R$ghyboiQ z_9(5hlY#^lrame@VI)vQ$@!h+^uz6*tv{{5RZt@E&Wion;m+$fbMA#05qGu~R~uJV zbZ?++%Ytz%?}?3t{=8MUPo!ys3k>LW^%phJ%(`Z`KT5?0M~BQEHnJxSlYm zqL%M=JD$~1BFKM@l$|~5y>-lpa98^UU^_Pmp6$lU6rHY9J(HeZ z;A`UdGioHp^dk8rkWtja#er2A6Ui=gsY+%cc1i?y)|y!M)RFM-SGI^GEaLQSF$d z6#dxU@8n>&l>4{F9_zKJnCga%H74dhy{zsT@69BY-TZ9#xF%ajxX{+F03=0d#<@?W zfe||XBk!QAEe+oxoM7bp0;2w_Cv3dwKyAu`zeq_3^RkHeunTA}+}OwZ3~kyHQm=aG zxeg~V0-Wa=ji40!#f}jsa~LPdX_s6ROiIDpPuGt3F-Mwd!=Y?nmTT&3d)lNLhiCYqu3E8ep@FhXa?psJLI2qf){%fqE& zf0*$z$4q0+yx}hp7@)(j=x4rl5^>y!V#@D8Nh*;HseCZjD#XUBuo3MM=J-lGYrii< z8XZaFKWhIu*7gHx-z?wq3nUA_5J@Y*{n4$#X783DU%%r@w)&V$m8QEa4~C{k3ZlE~ zN>2HGd)Vi>`zurg-BAJQG}y(GPJVw7;Iek0q2DPTW1-e|}UC1SAW zm}|Cdgsn%sY-k zk^XSh9dC$!91Ut#zjoJsk<)F>v~NjOr?&YScZY|GNsDZR_;&F2mjuPVJVY_9CF?^1 zo6FX7ogRgiNcKe6AX^KofpMKR7u95MTyLVkN_J|S$g0QVlDn0+J=?@3nvCQ_wm-2F zeQUCrT8&;IUKolP)My!9$|I<)UNxyyZM!38MIc{I_;|riK%SJ#t0g^nz~zkUwErolwpgr zuoR?JmsbD$v-|=Yw&XJSRQy@Vs_e0MS#RAVwu-MW^0K5n9-^-Xw(tU6=50Tf+B%L1G@o2ks3z>@w-P7|o*S~o+LD$Z{{kGg*b>@W$ z6$&9Jh2juYMR70>rN39BPD3ii5h=$EDj!#<7UFHb97VRC&S`!S7T(tNm1=pCN>|*{ zcraJDG>Ay@{1TF2TJz;}Mnl}}$=$GDmNdi)W zNDzj2qW!30Wl0%9XxQLeaZZx4%yS zGp112OE%K{fud$>N_8tOhSASo7Pi2xZMl#V)Rvh%be_l97s^uTEg0sy!%+J9TMgHO zU`AVhMBP>CcQ*7VkB1`Y5K)4wLF4*xr&q%XSFEYs6~n#tP`pj{i4^nk-S3a#Z(&tO z&Y~M?jNwAyL@qm45(H7I=i+r5lJ#}=LsS7Uzq`w~QaQ+z^(zO!Xr1(JZ&zHJ3W;TW zLP%_BCM{P`nT2bM6j~iwmxg=83MJMAHYc77#X+bay>{2{hH=jm^_*sR$H3mpk{dH3 z`zYDBG>Um-#_2C_c9mhpU18ms&Bmv+q!6DBs%gO?gKVARxx(R#3fX;ZiOChj{+qJ7 zlgXAt(O;#yYa=!Sclv5g;2FdLISz>IZA-S=$CMk*zqUr%cVSfph#NM9226Od(cLWv zh0Hsn z*Q-U_|N9_2@N0&r>9qgeD>7ZMd5*XQaK_P&VX-V~8pVJnSvuON)ujjePgs%TO44ZZ zmK6Xo1`MKFbM-C7+MYrV@`RM5%Q9rafIz29X^L?ltJi3eS<|0$eysl+`~82^dLIoe zK*#+rT+RP&kqr#ng#UD={=vF03_v3qXkvfPWLQ!z_Wu*@`meF||3qQ_%UOH$+Yhr# zUxWW0mi^b-{Ku^o#LS@04Z&xj(?P!GSDly{KCFvUpPIY}U4N$W_mJRqB2$o#o^IF| zXl7y2wIv@f0cdV`R`{2~kGpBwqhTKZtjt9&Gd{rS>Rz9ej7?5vHQd{Htt)^L>i8wz zWE;&~cK(#$U&Q3Po{ewq5Pk^jkdmC@HJ)Ta+xXYW3wD0Z2=_AnQ+`ZYwM* z9v9YSe4u9Vg|kS;TBt})VpQp7oNN3&z*;;-v#r)m3Zu?;A%nWQ0TuIeOY>tHn=8?Tpp@Ys@Ka5vIi;4qBi%=e#~ zQH5bI9CyKjtRC*kKkMo~jl&8}P*qOXk|CO77oSRWI&73*)ZY}_?L+;Z+COXVK0_Ku zrG_sagV5aLP*RA+%X-V>pqgVe5C|_qa=891ZyS(>Z##^f4!<*yEt999+SB(LVq7YO z$!v{ykY|>mNwL#=Kblz&pc!q5J_wImaKi%oE4}Xr*cTf^Erk=G_w#v36OH8++Skpv zOd0cZ1(ijMDlNNqE6VX?GtT;LELM=LZ4vUa?mPa`FDQ)hn+*%aMDZ7AQM_Z&LL zrT_hghot~ZukeCVtBv{EQLQt3UbOFE0Szc z$o<>Uy8(HA&2hv%jz!bv<&iOGDTXrL;dEw?VLJ;qoI+rK1D-G#dJNdr#&yevj7)U9 zR07xCCwJ>-SuF53$kfSv&{7yU0vldjYAYzT6A%p8qu#6vwfAP>%TQw1Kw&$4Vim?4 z5i4wzl{eYD0sZ+AHsWt9P<K%J9jat?*bugD96LYg0Eqy$1E(A_%3LB&8!4c zbB=MbOlK$b)-lf@IUtIvbX=|B!D_i&$f<{{qY*Xf{g;!&EF}UgjVwy-*Q4EE=m`4M z0M_!ag-^h#)|QcgXH~z^sZba?QD0`!^_3ZtFi^J_e!>#GtNCM7d-@SI-(C5=zPt|^ zle~QCy;i*9uNqRrR4i$@-4=ORKHR_?3!i?X% zLc!jm=-+uT6#Fs2xAMW9Wi$Ok(SUD!x|iJ4dj*3*QKyX+-stMlnTmqMp)b{jMfLu@ znlBhGWluSeRw?LP(y^nLwtVdtx(!d9J9UE9Lv~CrD@NWL0!>8` z2%`4&(Mdw8y;T$O=3aDSV$&Mxei&y=TXeUPv3KIR%vIIm^TPR1^U!ZPEWeX@m`jp) z${i#g68p2`zxwBj^GJI;Y&;59(F1d!-Y4Pd~y_#+yq5n&bL+tTP?o?o= zJ-Aw=&9QYw&b;d|ZD^%hcmd_duCEtd!3~lVjTZJnR2az+e^IzIb<06pFZaJr2!)`6 z`a`Ef*OOe9vL}h{&N;Wb_Y-GRvg~K8`pTZ8I2fKXF^0S9k$DEqE2_h0$R_^qx(;CP zl7okE9g4jM;%(o3Hj%SZ$);{6pN8C^Sf}EwZA`m*XA|1Qwi6S05jut>g;R)<$Fagt zoR{!&HjmI>rb2SrCuHv3mm-gpYLQRfxT$y}?A53+VihIkZ-+=7SP(8pLke1n`L_YL z8lso7e*3AlbIZ8vf{ipd)hz|~yLR1JG7Qk3JF|`@+q_8=s$r(f)V3S1)lYnM#njB8 z(kN1?$~E*>ND!n&%NN-N?Lay8=`v{pWf&CR+XCVZTowJX<4D|-!qAb(Q)3H1g!*s8Y*_v^V@ zx9m5BLZ)9L_r3IEG^Pik*jpYv)JEo}3}vlGW|Qfb7|RqZePp-Py%FIi2M0;8oXWz3 z!!+@(#=(OaMH=xPecnW6Oy03W%Q8bguDJ0D!oyk3gx74oCzCI=^N!%S{4qcnVzeEo zlxE)a!z>ECe8B*G*N&oL@MtCq>_P1M-V+c?Oot&sDhd+Gk+HPJ*c|fKPeHkQ`hxNv z66Ua`q|$CCFVUfoiO=p2br9-wiJKOfF@g1BP2wxi4P|{6wyE|eA}1IgU?>|{FA#O5 zU^1Fb*cGBDz}iVTR~LS8jyP%lb>`EOlZ6Eh#z*h87Gykrkcrx=Y-8Pc;*&k$8x|17IzlRDf7(k5ge|%BrrbvGk-bGyEyI zJlmg>552@gmT{-VuAXtJ-u*ID^}16EPz_E6oro`U8ZN^RYtao`LK`Z(`SevHX5W0B z*CP(o#Rd)rQK5*eFJVL6Vg8T!s_ekS;}VtlMh{Y1aM)t-^lG<(gxyyp9}s8dm}#A@ zKTf8RVOgMx<8Gt{%XjZCiAne51<%xO ztT7T+k|-Y|mof#j?mA2wI*_iY`=aFb2m=$Z3O7@y(a(B$^@brxO^?F6%=Ab{0>fgp zLF)Y=h-EbMvLcyQiI`6|vF3@5wTxe_NV*dM+p0t04E!q}Qy&xRk~*I(DC3SV2kVSc zB~durJaYL|==gH*t0ri6Bgw^=M*mVtK8M6%QUho^!5(PWPZ9=N@nr3-I%G`66>Gtz z(25y19+hNjcH-**>$-Deo)~kMk0nmu-5Qot@ z*&4vF{59v(We2%|5m5BYFPzs+*ZP?dVKRJDryk&JfKVD(AHe$DGwTAyKFTY)72rSo zpQ`x~>aLY;`JMdez#YiD3rkGSWRP!d%Q(kX4_=Jg za~iIuz69Me?UOVR?M|^oNgMQJW-D9!_P7MxB=U_@(8Sb(N}{@V6F#f^QWSHKAgxov z$b;ClnBLw(s`F`cA`n;Y*>s-dP%bBI=oLp!knoZdV2{P9442d%8#YyOt|scZ9e9RR zVVBLq&ee1!lsfdN1x5=jlLi-GYMsjY=ehmmyx4Y3LyxvL?{#jq4Bm9y#XdrXkeKT1(QpX^!swTSEP4ZCNP$`Of) zB`#)OhQ_h6Ed5?jOl!EGaV6+2k(Zx1pLz~ zUm}i&qdO9}K2&S9O|@ivh9n+(S4)6*fx%`PDBSMiv82yDv1yDIV^@lgr$u{Jtj$a-T$`)XTFtQo{bfQ)~% zJRBLzE&qhXX9p&IG{9wv?fC*T{wk6Ud48B|z! z5khza6#eW&Eh=CiE2z8ADJE7V!6+xK{@*7~_(PNwu9acwwMvtdfQ z*C<`iEIWKXRAQ(^bpGS@Hpyu<9R>zNlbdLG@@Kv&?!MoWoJ zQ`++d7VVKzB>9_Qj>!)ujd$nt(mDLoNFCFc6nio+_PiQ!-HBy)iLmF0_PqpL0yXA(M)5CYZk&i% zUn4UWn*+dHJ-Wbyw+AUEQlw~fwNXUDix@S;`PrQ+ika`6UDGU2;1(nr_2x?XsUl`WJiGl875Gw&Y_!!D-Lzii0&tP^v}69EXZNR{y;-PX#*#uL z#umI}j=j;Fsf4r>MQv6ZpLF+A`% zNQ5;}b+Y^^pe^KK_T&jI${#h-wYS?Cf2i2Nd>PSr$fic@Dm1*(rcU*pNtOs{P{=kA z6)gldcTtK~E z{l40_Z5bD}%xPw68F9+f9PnbjwV2}lyRsm2ue1ht$UHyhTb2A-=3RiTGbl3MrblxtnXYdN~@1 zo|xbeUCi~+6Y|04eZI^dzF5Zom7<)Tr)Jjxmx4C(;zhpX=IWjsp7jd@SR3ub9pYs~ zr2AHRrt*4k=?es5xpqCLiW1h7ImTO;voc-K;nTA{Mg$tMe0|&p9@7c#D3NZkxoBVPgLO8PTNX$kWp^6M{Rf}j{eG|Hv{`Z z!Vi_lvWh2n2Y>CGv?@8G>g{EXaq9xFOaD`=cf-qg9lIxBYI8jirp_Dd9KF{z$ z;LPtV=6u&Dyi*f`LPPahR?@AfH9lI9t|rRMes%p5e4h&G-1iA!tz-7^&N_2eP&uoN z{T<4i->P01T8$fDixU?`^ad_3-LiRKbHCT_6j@tXyu!<1;NE4cJ5=f;wP%Qz+&qR3 z?4GSNoqHf;J^(jaRq{CxvUDy$E`vS^SWQzC$$#4UFETM#KMNC-JRczoELk( z1pu$tEZe3d_472?=P6-vqj*O+p2M|^JT@iumPJ^7=*_6>DjyG`71mZbz2L)%$8%J< z9xsmH^+=zO%%D&9zB+c888DPzu$n6uv}5<6L^b6}dq8OWNLKguV2@#bA6vcm@% zs{&1^n2C}})QaE13K_`n^p%a+EmqGMbhD`dKQS&tZ>Ph$Afx$cOq#{oQq{D_?(`Q| zp_(D(=_z$lv)*Y{pCw@En;|?G+!`-_3x*9z=YE)Yt@>mJGWxK1!>A(8EI?NtMwMUX zQBF3+eP@GTQ}E9oRjWp*s242%z1rghK(P&gps>HTXxM+X%y4VX|BI;5_}mev>PE zGBu61?%7Q-pE>VSnk>_Cf2X&huY6;iE9-0-X*G4pR05A3xY`<2)CM!>HlxHmqJmf;~#WQyH$s7i%n>F588-C?=x^#-bE zA92*^S$XDq0^;}m42dru*u;jr^<7bUfQV3SV-~#46eV2o!UJA`J;)X_qJ3sH_Jj`$ zaBS=kB7I^&fo%($T3bthB25$ZG7EV2dBYEVv%fPntV4&Z9#wdEEc9*F2@0}~1Zp?p zk})LkgvyRkc#Aivm^iNXUGboh2HC|AF<+`m=>6q|+bQ#5KdVQMi&%96_!2up@TitJ zBwRQ+-VyD!{wlJy%gVKEe7)KFAkfb`9$}NASL>}V?Y(@#*P>{;#FP{B3VBhAQypha z3l=&|lo3%e2dTK7fYOJhDC?} zf_@%je$Wp@D#(~uRi-VqTAllKZ^5^HxkL?+Bu&#s`k_mRDMq|>>bjleUU~TbiyriI z3V7m$?^aUI3wGY5jL37p3%D8X1s|F9z$t9P#{HN?U4d{k`=h;mb_^N1Q5M}4IncFf zi9|d66!TdH#dJ7O1U-$oKh3Be8TBkYLJO!7s5@Z=gVM4%Qsa9L@G%XaU%@pKlYiA+ zKekPmu6z0Up%@0^d?CJtt2{XD%P7rMY*yKOH5Pp3pB1<%l)S=YeM+JRRM1{~xf3L81 zgdMGsFR>}M8&h>^OvjNfDq2a+xkemwthiQ6bH@vkj%<4E9ad5KJs9ZVizbsui+2U| zV~{RfR-2gL6U^mXL}j`1HY?lP*se!}1WIn39-%oS~K=_6Uy?+-ei=Q zoe``(a1z=`p*gba(XxB%@d@~dCl$_jqbKo%)P=7*_m6BIpGda4DX-;hlLgBbFT{Gn z{ed8%RTIg@6~3Y-W|)nItx?j|9?Q#g8${H+AKZ!ZYd<+1ry!XRvCV^&H&C)w7g5u8 z%Z&qWWixKss>%NM=v?BH&DV?g1{!Ue0=iHGHBt`Klo@zG=O`tFCisX@b@?3dP~08L z_L#SrJWlLu?Z(#%m9sTWN{v$uvdO=>95eUbRcdS>B)iWH1Qu*yT$n%ycSye@xUNR4 zRXD?Jx%$a@%MbB&Bgjrt!(?tjz|m6sCJxWWI#Z46tC-q)PS*B4#IR1HD%h3DFo&VC zwn^@7c~TnmyiFYhVt(;&JyB+D0 z6B84YQR@2-#U4BdQRCyncMACAq#EY_JM+c`hMQiGVognF1e-S01+(QM3dEM8)tdNt zgJ}8I%I~2a;-$nS6ZHtw!0|Ml+BQN-5kSr;O&%1J?;AO|A~HmKphx2wr!UbirFPD^ z{OmQhY1$2#zTc*?WC2WD9+VxqWny?wGA#5M;o7%5nGXxUZbxRePw!~D4rVCz z8{t$*L!{|1M!5ZCT9aP5xLof25kG_ieDN7XMiq}?X3%(cq>o)F!$e$1IBhNM73o_} zyk%r283U&-x0nE(We_Ue=p|W^7@zL9HJ;-k49#gn5(ADYJR$ESDx6@ri9g!(ZlNl) zyEG>Dg06w>@uj_DecD3+ZDZT}#>>-gf?^ifCV$DMZK=Nev`KH-eUPw$tMY))Mp@|Q z1*I|wzS;j{yBENnjnw!fr}+P;6E&V$^ia$SWaOJ4o;6vKNu*?wOjho&G&=%#5`>I$ z^Zk^qmy*CHF8|Z{N7=(ShMRu5w5;`6g_Zxg-Q0^9x0Ra}T)Nj4| zOvT}7Edf>t0vDWOR|OCkPrYD$P3fI-33A4v-pNPXwa6R)2ZU;Jwz+2vRds_&|0bq@ zeow2ZNRP;wy~F4R*nc(jpNH}o`5jIp5+GJB0R}C&Y(Z{j1LT1HuCwoC_TZ7z^$tCJ zoRn%-fUxk5u+JbR=KYZXWk*TeQQ^_@dC?L7zk;DCkTxT1nH2AJ(gjk z@6z}`rcXbh=HrM_!7St#un6)uo0&#P?{bp~FJThaZ~VVzE@_Om*!&iZ@gWd>$ zOQ_{98FLJC}=G5dJkM^-F0w|KnYai^JdeHd~#a-++Pm*Dq8-7Wd-bSoim zNBEGY?E3tM>leEMbIVf;n}e~Yj?*_l1+o{ZF*~zTT&<^ExeLpvX-dK-Jvq2$I!Cri zxtgW$vma(#uN~v3wZ|kn>9_YN9}lAa%KPw5H3=sLkClb(+xgb2uZCar?|J1b`+gV; zBwj-LVfyU#=L~Ln9@ld4g{s|7n{xHw81HyLQut0Q7x^-{6%UCplkH%>AC_Ne4nq5IjmruU>8M6BjxV}Y^T5XOimj{|HOh4 zZxm;40`#sDO!dp1^%3}NrE&``-(;#lED(p5j-rC=#H%rqr!Rgh!Wv4c&Ppg$l0ad_ zMHaArHDMFtYNHNrpu!{@)gk#;QVH(}VT7?1I{|dnB>;u{@PEu)g8#`}J_S?;|6S&i z{Qo|4*`wppFzdWzdjYjF5Z}<7s?w_SzG5eEwR8apvzV2MXKxMv&9LpbF1#ZM~(25@VUB;4niTOMr`QQk`uX#l%K5!O3G(vKr~ezOGm({Vb$wRiWzhN}4z?G*zj~ z29qo>(x7u_)KIwbO%$Z9>uEK^!WV|gJ=}oRM?6C*&5CMbmb9FrZdDKCJ38gb8yu9D z784BAUzBEaH+j~YeOOIZ0N9KN(sP>YT_=P9zFS1W{tjTtN#k9GGy<`#JUW-BvU@zM zGV)0@y=_`;HY01OTgB0oD?H9E&CfJ{CVV;zkuG;L)-GxxVqEzp!LG<{iln?9^IaDo z+S2RRm7lcw_@KK6pE3Q-`wALYh<3i$xgVSxbGeyl;@xIcErU*SkaF1JEXTw9-TcvP zzB4W7iUis%;&M2Xzpyp+ObDe@g2UpB1SWVx?i|c{B2;HoTsyo$f%-Dr#)Lqev`L0@ zgr1LqvE;_&qWSF^VCBqsTrH%$^K-iAL;$qypob`hLdR^3sE?CM11${=?Bg#HFj;Ng&NtM34W><<_d6KG!X_2?FXqmNJ~@k5178hf)640L1K`vRjpD^?kB^ zYT?#_!l|H~_C4w7)n4(th6t;u2o7sU;ehG22eL#o#LkeGYLJbNz@pkv_Scm#_$EgH zG*-x10F+@F5gzhL869h}q&=}7(WFI=`n;5pzChLWuS_^X&vX9)T;blmHX|i32G-Ae zla0OmI`D-Tk-hnA+6V=qzoX*5A}~HVPm5p^?V8kXWISQ5F`l0l82Y53_9BZH^h|`r z?1=U+SlGhH@M1gr)5`*)UMY&Oq|kP;MN3lf?c8||AjvqOq{m#^|CG*nv%@C?$xOG6 zvNPg&ZyQyzZm%uYCnkuQXDFe(md@w%81 zm(Ccbxd$noD;!_;YhfVXz$u^AGm{~1vZ^?wjoYx?ZnNxj{Wf4#e=iZ1Cs;@PT#uwU zEi5Q^Q2Ny{IoX*hy`R3(x3q^s_cjwbrz3o`!!ezb zy2<9DpVSW?q=ILv^Z~8eQOpxBt3@s`bi{t@jAVG4+dRR`WPOYt;mO0>u=6cKe~!pv z0KHfBm{2R1((VU+arr!>3_5I%XsLxyeOw{8-uA3}Txw+;>i#~W*uKMNa{giwkGjv- zxnG5WD+kH0a5uXSJ>$6!w>Xe;UHoK~jQiS^NzxK>*Sx*Mw|#wQz9^;Yh<;M}CI;f* zWAltkr*`5`NmpERU$cf1(Io8?@%9`gx{l5ECTRLXUVfNj+%`1=d5b&~~Jk?9UXz_uZlVd)Bt!EY4N3 z`gKeY8{)F{>BhiL43$&0Xd!H1heyFiu5U2u>gCCl0$~KEG{Cl$jF#au5i#?CU6C9{ zL6tK6jq45k?ZFb_Ox6MMUHP!ZYHqh)rxoPGzH=Vk+qkjTjs*KAH7~kSu}>(`!n@8< zcLV=Lp0E}vxDl|*y?uemZt`emBG935;|YO``2VPT&#`m5)na! z7*huv0qwG6U0f=U772YO&nf)Q{W7NFC+Jv34r&b(w6_>_hEzu==c3-eEqFqkIgt3G z=K0K0%caNpCQ1z&Suc}%Z*m{aj4W$qBt0p{Sh-b};b?7PLQx)FKb7lC2YIK4 zW5aoE<1+`^fK6jsUD5p>?;O^@=#=fu3`dWHw3E9N(A0=3bme^V0Jp>aH4DJyjbvjj zjSCD?NjFvvlq2mLpUBmH*^bi-llP0RgHXSN}>R_{7CkGp-xR+J*O@HKUgzEN5gMqj4`#GA1@M}8R@&L!(vPXgk{l$d|AuG;-_ABt2Je0 zGqYr|Cxrh9Q0g~${siu0ujxM0+c%9$tp3vJ;uotn$*VGl;+A2N+J`ql=g#y#SJ=uB z@P%+)Cex*I2WbrNq|nVWCFDUFc}U*amQ`${DKg!L+gkPZSA~a_o1V4HQ(bXIdpXVC zPdE;))R_S!K`%TLo19wHvPD%tTQmwH8GIr2{ObEFA|3_W@bb;hY^PACtCAnLbw*me zkDcPr-##$K;u4Qw+5;Ew8X(r_2Q2}IM=rRez4VuAYBDCz7&80iaXHv~qRCiiT3lT8 z=>Ru}?{RxL)$j$RH#T(4b>NYx-gaWE^y}D$PPd*oZh9A9J-fB#?(mt8qi&mXR}d~F zilfzPEJ`WYsrgKgYBLgSC$CegvVLKMI#ouUQLLy%-Ii_SlB`G^O^cPD`q5{_ULoFC z>}=95$4$)HOyvf(afoN(n#e#~WeJ>49%&^jsCM{DxayVx!*EbJ>YpV+B4bvEp8e!4 zoeO8irTlT#t|gn!8Qy9!xbSfcl*}yTWy5jC8rTzl$i3HMk@0`->%XbYPoEZ}I`0r=5Eu(XfC4-7odZZ;YxI- zOjV;pkK3~_AaVoHshscmHdZBWskSkz_lQ64rN*^OO@}xLU>c6q@P|-|RXHC?onhHj zl0SFllnyS__tBTjc0;1q67t2AZ$G;HA^#_bnz<;qg_av;%FnVLbj__=VSn{~yiS@M z<0(9ck2i(njZ$Sgpu^v2Sf6 znbb&cn0RKVT}9||tL0j$8ZJa=y=ng*G0031WBcaEv}5+&)_9kkxPpt6T?;IoN!jGZ z5M-vvx;p{7p`)buuWjC^*ewf1x7Iy__NQ_?Bk zmzFnh0h8KC>zk2S6p1H@Q-GIu&D}FpH@8zT)G%X!LOZ`6rf?tkDSUuFS^1#6D8>`}Q~z4WSdA*F^fKUOf& z1Lxs+y}|kPn+m2p6IAb7uh@6Ehbz*|mS`GYhwkz48>V@d*C}r!-e!dUV2H_laK_2k z9bGIQz9nKD_(0F{27uG{vY2XFI$TJC$##viT+f`}rOb2W?$po} zW71UYDmi1)4>=Fdsblj5?fSAPj~d5!qQ*4%FIlth-jJitG${0)f0iJSQ7QWPL76Gf zbPD2}USPR_P1x=y|1tK%9eS)(&|aoGd7pFiHVy#|*I`X=`x5t>!BN^H_L~lAZ3@{T z_sWG35V7LFtw=WJYEv*?JJb27G)3H0(*OB6%rk3BhrJT#5=_cH5;>$}FDF{e8;xF_Q>sgwlRwdVp^1a+ zVqjz@| z0})?C(&%O9XOm1072tXtngR61wYjZDAp(3gpu4@>QsI(^!rH)m=U@j5$R}Mk-v!UU1;X396W@-@+2OLkYuXBrKUQ_i`^S_sbiaN4=bSN6<^kN4DW1 zj>nqKo>Y|hwyNI33jXXeZZu>g*B{Q9)uqPH=%GP+iZ#7MP zlOFc%s68h_eCg;2{PsSrHQtlRqL;^!&TD^lQ?78kD~&VP+Rauzitda&v)<&ropVcB zZPn-i%m_l|^vZU8Pb5Duo*UOo*E3|&J+o*}66!?nKbdqYk?%HES z)~TJ{Nzv~iw3FEP%;Vt4%+4@Ea_0L1UQI2K;i>fDTewY`u~=gwIaGDK7V0ci`tz1( zPvMj))C@h9XJM#jrtSRKB-a!l z`u1Xl(Ho&@>dCrlF4^-7DsO=bjV~dVr`xt2gHYx~a;FR0jZZ<*xms>DrG6@5 zd*xcD46Q-nS0hWBYrU4sg4$J+mlF<`rd)8RwtPaG|HQ)@-6s=tpux}JG*iDw%d(nPN0i=#<(NX}7IVykQ>D7NusyYzIM)wIRhg05|$clL1S>Doi%)K>0&bMM=KVt*k&vA?o* zEad^($cPUQzIf(K?KE+kdmzbHJ{Q{K=;P8qpHlHqTb0my_Klux?13w(w|N+Ul%Dqn zRBOk)7IwV=S&e2Zf=tv^mKnSfkHt*hqw{gl-it5wHbUdJ+;JlNo9c=NW2ie8DaTp_ zuji!DY#ubq;GSh9RN#)>ILL{*9>`P>M2RFcM<1=u>c$6;6n(Rp$W@$!4&U0uJkZ85 zEX~R}zLp4$7yjqR!P->J zG8GuT#%JtV;hTkO!Vf_cZ*UxxLwPLHtaj!qxEk-D=Nf8(&$-ZIC{2USt!?FM*x|?W z2!6eNuLmw!xT9~@F4uYoe4CLgHp(~{@G@g{|GYr4jfm`=2x2)m!*>&|U)u42@xr{Q zzqSxvX#)ao^i;tyM&n`K1)jBOQ#%LKjb`rbp&PSi}(+e1w%#K^RM(G6ijbXaKC5iq3^gM*&8 zlOjIvVUoX0x>oAywZ}dz;EhC2#FkX)LI-nq5T5dLm8)^pxJ+ZCt{|I{2ALY_Ds$lq z;FRE%OZNUi2ZZlh?@o?qTj=MMVbNAC+Tv)96 zKO*rX(lPfr%l2U^h8~lrOI^O?;fOn5tS@dAwb=7sr2ol}9$#*H7Z-tqp%1)xaHh&< z1!F@@BinDLa)_h$19<2s+<{eBUA^@F@h{H4ysDJ0Wk|gTC^u5|i1uS^oigrGk8P6b zyEvZdcgU~3dCNwti9(fT)7=ScY&KrHO>#QI&}AIsW1riyC_< zFHi8wqxKe)x18Z+(|xh?GeU|pAHM^H44nT+Zv0j6=Dj|yipOY92!U-}3rTHA1}@l3 zQv3c|5v0-UA|vFkZFHtk>g`MRc>mG!xIo|s+W(GJ%YUxE^Pgm7{{Qf{Up!vFNB8}m z|5tJ+Zg~EQZ}H!9LjUV^f5>o@k-sj9e`^gNbG|0}@E_$?ufdP2s{cz|P(K^~7bv6t zh1*K6io}{sHU9ciT(g`ZG|+Rue=s^&(Vj$8;%88&JqMmgjVl{P_-f;{u5^Eb$jEduo5W7 zXjJIfEPzt5x??uiH93I8^JrQqX>*RsPP4`K4OaT`9twY4dR? zz29SGd-;6Aq?TyZh4;RPYy;od#^aGAH}s=Ao_ebn;eGX};m{WR~Umji|W>+1Qxbwv%yrBfj*1-}S7;kCRGBO)d?tS63$Q}xRmx8+Of$P;f(qe8EF z6A`%$ylP*$>wM%1rRsFUcKS%QeIGhOj7d2Zmd|L&JD2CRZnA?er;8DntemF|PW2wa z^*C>1FRETVv-Y6z*|d>JGidu|ZieK(L0ung({NJ{S)4ND+r6rGBLDH@2N8{(Z@=rU z?BjxVU)kWH;W+{kt--gu15t!a=p?Fj&Uuo#^T^$WvU`4hJd3$4S~`ebH z9qmuqj_E|CmRzwUx`5xNCe$7&xYOCjZ^Adl{h+s+x;-;Y-r035y#ez~J~_J4%{8^M z^463ONe^J#-1tPAniHTrk-L}7@b=kCqo3cPV#$thkU&inEBjt;`sB>m=K&K!TE>^x zo^%+dAwnBTewx`(L5#9pHtFU*a;L}DeAFMJ|Q78Iy!~NOl{i-WJ5Eu(6#Z(4ghW)Tfg_KaQh^X}@%JbH85#_@Ow`$P8R zbZW$2ARcX=!QplKQdHG%+DfmL6cMzmB6g#Q)#FypkmJQcvK;R{yT+fA_*4~1wB;%= z1T_?<4zFkx`E~>BI=bE0-WR{Wkm^r*7_nRfb$#wykQf+mka`m-rL;b+YV<;&PX~^S zak)b!5)UjyM5}59j@xE4--v*7&H=PeH$R^6sfCh-mbAUm*)*n3r|960wjyKV$?iF= z1kIj|Dae%AA>lt3Me7LM@-qget?;O|bVEqO*t$#>vYwwFhzYW5=_t?(r#dg|<`qy< zHcsQi-%AV5=W2vr_rZKlzM$`KQs#yXZqz6nZ1LvaE1alhDPo+0`&Rd2MjHfXk29;# zw6tn8&0}|i_4^g}IWX9>PkNoA8#B;@LiQ({us+v8fI9Z@c^{;94!CA>#;NY1gaN!g zm7dAaOR68YyH>3yB83nbS|Q!b6|7aCcQc&wm7W$Jm6_XQ|8YB=b=!;#yjP=Rl{~Ge zzJCpK4613Y*#_fxO{V#yv~(f0$GV=w<|#lwLroj&DxjcBXS(Qc~R6u9q*J7IO-3Ezg3)KdT6J&~tchHs5yTzuN= zjVJMlkrwd48{S+$F+EVl3FZ{T4ZS+9WO%$L^xUA7~7$ z48JzjnU7dCd?QaM5PC~OPUqtTGNo811#Kw;6Q>!l=Nt*rOw{?J(g<6nK14Usm5x;k zX(Tv+DCbdOYmtmXjm4ME8pwS=2dgj8#Nx_}{2)8u@`AtV7**wS=x5TndcIZHexl9@ z-%s6xaOVh&5U^s*HuxIQ3+g53f+ptMiJv~hUml|mxZE#jFnELzolUy9mns=|;iKTX znmR#CGHM`;*k-!kUL3LE#5B%Kp{Z=^kUSX~u+}vEB_hs}9Cm`Mg%E{FhAp4mYphg~ z3x&{Y?9l1JFh=$#q8|4>Y5KVdMq;~#<>xwyNr)_~&#EfYjmOnr@D^VaMaF%iD+A%i zlvpgG6q|ec-E4*9e2D4olIe7r$(cw6@({sf@6v_tu+_Ox&fe2|$ZrroTNmn8qGo&Z z&5H-h{Y#3)X!(GMR3qKFKaMvt_fK{lupT=l^t@iP0G-+|xUHwv(2ge!ZRR4UyrDZ);~A z)Dys6=J;j^zEwEZ6W8u02 zGZtq>s6)fY9bVT3X6&I;1qPGtZc#S_B9U6W@abvMlL9FB6AlQ%wLZ`|dp|%)Q_ZF9 zV42Eq!fd=Ga5IZ=P>4%Ltp@|nX)#Npn5#Ptz$?K&u#YEd8$?1cv#w@E_8ldT%>6ZYBF=SM7}Mn83Urq_>S}{g4CMXr@W;EsR#iyDsI8}@J}HeP#pb9Xv)!?w^s@(-a(dBt zu7C@Qck!zp(0ORtBSD!EuaanV<&eQN^fdPel`v}c9RCq=CvLrVk?b*UA3#2|{aWSP zSyEj#aE%_ft4jB3C#sJm4!u`=r6mf`+-?(ilfdIaf~&w_ri4RFL}FsdTg?e8n+#z} zxEp)=_rQS7^0YhK;jJ8S0V8@ltt{b5EZH;SR7b?*%SNuZg;nKTDa()OD* z(fW@xt07WxQZG0uWpAlHezwfQ162x^$Ljjwtvx^Onr0_l3r-f_hBAGyWZ7v&R>Q;K z=c~LLFWq?N(Wjbx7oqtX2)2!86UR9}!{YJYZ1T??DqDo~-KR)q^@9rhfG>y|)Qx@n zWn1{i3jFl?B8Yv)Igs+rn*@j4LW%~91& zZv=Dti=YVK1Y!jWoRu94aHTG^$;%Gk<9Sv1P@$V=q{PIg3{L%G(Sq>lys6X(g{nE? zn8sMq0~lLq@k)Kdu`j`9Z+B4dGcWndqM_3L7T_ldOhvld%IzNAz!)x5{f@);;%kiv z@&O6nDAz5YbH>Dt^|q(byDOVXJ&5vc3t{s^Hvr+@y5cw4*B#}1H&3g@P9|K7g+xVj z+Yoac?v|=dZ&+)a>y@GE)Sztri#+3A*xu1gAzHyZHS0~qo~LYg68WR8IC=o`5*ngj zBJS6Km_k+R-BV#QqR9O{r8kcxxv@7T!W%#DTj|E_D~Uu(eLhVIfsGkNZr&-PD0d0pV9)F|{~XDWRJ?Az=?nAW=Tu?0Z3sQ6t<o|ieEr`2ia)m~x# zapQ!2Xj{IpRXDx1!Z^2RIW;h_E3e-A&@e4^mAr?0MZ&o67P7PCDe75oI>*7{6=$J+ zvBVQy{76ad8=)AcjVIpyAUyVZrC_$|WInA|YgPxl)r(I^C*BK!JfsQug+k@_0OD;) z$=wl06Ta@qya{XBta7;IFk~)Ls7{Y$uW_?DjqAhR*JtmGtlUokLAyta23I|AD!)zv zV9zEr4i~s^CD8Bk!9Y@*M{ps;3h!lZf^hp~kxI%`1G7>$9Aey6#Q*1paeQV}#|AR^ z3{^jgPgH_N^sf$w)sFdq*+Zzqqoc>Vm|0t4f`UWB7G$yQ;4>PYsqLogF}prW&$eTM zho~y8YAu45GZJdA@<+Kwl4wG`qt1=&-7%~Pp20S1^~Ak^&+)Q4IA5KLGi;NErHY96F`uO1+0Hlj&U|I+SqTHD zjnYO_ms9HO;feQy4GfbTj{8kCGUz0a56;kg`;RwuTU3P7=-iKWeS(B4j*ng)2+)FJU8QU}|3M4INJV8gl^*iP$DuzD0O{jW)Up>420}a&e!Nf9XYH;vF)XK`q zaXQz%)g432I`eBWv_wA=2J_S{U5mj?m;ju{pbt{+)L$1sy=x!NWZI~3u#rB zi5djD>(6+c4_QhIl2^Q*wf%V(V$SzDoAp)Vt*U~#Ao8)>9U9c%56mspg(*U+=clzD z^hBKINs!$4nJK%&A^MQmb!9r0ZE@MXJAOQ(fzmZ&$*o1xZa+TH&8>eudofJAY*06` z260t^4&5|EIZ}eWxQEk)C)8U9&xBq3wP#y3l*{s;JFM5?tas*3u9i206}C9|bm-&D z1Rs-AbpXIBO4+AZVY2DBJ1^pA_UdB`PHgH=(V{<+Aj?mV;p0Z*(@f4M8v;%~o1Bwd z#RlpU`9gexp~n5PU!urNhzb;2_9jSF6smLI>Y8lBU{)sNEn@YbB$YALWZJI!>98{^ z4qmoV!}a(CANJo#ix&D=}?TDR-;Wbny6}PCsXSNzwkh3B8>brfNMx+u+ZDASY zwv*+Fbc7po0S;P z$)Rt*ec6{vpGCut$Shr>h2y-icPpH)lON(sO@HEJy}VyrSP24iR;oikN}BOz$%Sk= zF{qs^!C(6eO-;k9zs*fWEw!;2ow`v=WuSb^!qrZ~H{!T}WOiUBcXH}5icgD%%eh65 zC=%*$3C#)R>FBM(djX9-=cJ^$snkr6uo;)tMTE!XJ&I4Lu<-@R+}-o#T}EfD7}GWc z0fV>p&kc<%lZ*Op*7A6~r49@3lSyEHT%~_ctfnC68_ehYn71q8!0r3VeB;sKrE`RF zMn{g9KPJ{cW%Khv;aUFos%6GyNpNcQkj}^cA10QqbTQyg&Mc#WLzDWW_uzD|6|bq9 zJ5G@;j{(`2_)C}((xU*VKb;tVbUv?J_QKB6o8@_f`s^p2+LwRY!ke+@JrdTkH$Ouy zSn2!wUOT8V*RrP3GL<@R_aM!=KfPHDFP8F`qdq_GYri_9?d{K5IZ@Qo#(lKDr4@D* zE=3-gG-KkS4QowLIG%nw$!g+Uhr+Xj2d-FA3_hqMvr;Z_%ytiMY2%B5m=lJL_V|Wa z@iG;|I136P;QMf0!ekjHU=PqIZ70jdfDgOxbtz z8Po+qMNu-OxQt(IW%vx!lRgnI$eo~0xg{#-=fld}c95ODpv`>o%!ub) zbv4ReCE43&Z?5>q#*!Mp?eyM2R6f{M>v#u9ks$Auc0hwC8r>Uo>+F1WqOqgpuz2Yc z+2N@PYaYxU4kk^-=hrh9-`shp)_e~Dm@DS(unWS_W;+(d44b--(#)`Eq{D@c& zxiuImm3?Xbh?(lz*jR&Ol5;!T~&U_V`SzLS3b5xKajit|3@_+rj*>`iY{5l@>34dTZ8G z4rYoee*QQjQvdY|rBgaDrYaqV*Les7=mYIFxi*Hva~5N>wa3rR{0nHN%NuwQ6E||^ z;)7>1ujfFrzgT<^u*r8URq7ew0Kl+sd>90WbQw=z16Yuo6b@S8A1m4T&-j8$G6W)M&t2@*(JIT5(t0x^PbN*-=HVG;4 zS2<>hqR)C)_)Pa#ceY=z!B1qzw`_TmZM?}i(%(2N&@?iklLNtOYd-|9=kJC_vp+sB z3e+fDGh2VO|82hP2}O^I1Z?BLN+|K{lA~D%t#=Q3V(s+DVxc;6Li6&>$|V3{O5~0q zF9;-l6rfZSaYa|MVcPz1XQ%a{=`-5b+v!Wndd)P&^37#5Nb${eMbIZ^WDc{(mHgNT z3v>As_kv|78_pbH=oKf?PVSi2)fQQeixZjqy0!lDHGoa!;+ay^PGi6gQ{%_X%s05C z6vU^Q-Ik_8_a3c$W!60|l|7CSBq2F~4_$e$wZC41nOA@;_WyVpvcYQ4{XQEmKD3no z#fti%Fa8mi2%+fdIa5}BT=??P#Z7s|CjYg8U!f8)2Fmcp{kv>{B5}nkA@i;%n~_{) zb8G8p2+2rR`x7ICqK+po&CqshUJFg<%tQ86PA>ssq@4M5IYk{a)8Gpirr7)=L3vuA zdZGKZJOM4UtYiTS73sMagswY9uOuXV3q%P3Vrz~e;?4Goqm=g_4#{2GF+g+N1YPsnggSmKp{qAt1}JV%YDU)s>e zrL2ZZ<+zqG?cUE`sS5Dodl0do-481py>8oU4J6R4Yj3;b%%J`ZvpuyEC&YS96g#DN zzEC-Lg2CW&KP>Mw)SgJ4>}|MxA!8-u%>FtMsCkLcA%)yy%EUAH-t`lmSmv9{)XAJW(cMa|#V z1_avLl37k42WpI*($0Gc5)P$8g{*N(J+5X&<9u~(GG@M0Oi0rcdx6^fNnL!k0fX^A zDBc5s{D>}nOK3l7JRvUf-pB6cKAu7LgUb5el~Z#zhEDJ zFRaE9NS&h_v4Zq+U;P@g*=f3`6*&>i8t81FHwS^<^1_vITY-;4(y zdJ@nM?F#x}gfRQ;SjWktMqE10&83b|irAgaG>PEd)3uax@Xr|I(A$@uhvt4c%avE% zU0hwsGw%^3t+T_!8mW0b2aB!Li^=JR-zy2@GEaA~VV^gAz_JhLji$p4cH7xOL;J}y zXl5DedaQZ$D`()J-SidR81RpxqN2;tH)3L;N&)`zy*}Rl0FbxKV6kGl6a}umx}`9| zM~7sRJ}0d-EIT#OMy?nc8F?b*^0 z&BE(Wr!D9^XS4Q;UBY{SlcjE#@6|tV8+JWkJjkCE4sWe7H~)JYe_vc>a1HKrD$DW~ zE1<=ur#}c@CvE=|VO9J>Cg{onI&Hq;&WF5=2Mn-P{2LOz{)GGLJzo*=YPP>&s!!2g zgV{&J5N`S93{XfaG{z&W_6L*+xrsh-(CABBLhAW z{S70}i5KZXgRp1CSkC#QoSdAd&)5qN(COZo2w>-8AN5GsG^CV{==#$?@g)7~nW3>U zoDA23{D0J|?~-KDA>{MX@(Xp3nKRW5XMp%u;}+EMsyBJOtR|@>L=(6-2qH zi_wcE=}{=8bzoicW^Bso?_M7njOHkwtfz;ExQS1|o~L+!nz60xcjtY9!e~Cy6Lh<- z>uuYxk*g2uL(?>E(@?hHAjm=c`;N{y2}`*WA0K}Lf!0a&wQg!Z6lvYs<+xc&cKb|v z&P()sSByR`3$fi3!#oXDC-AM0|1DLxBgXAoS+Di?>^Q(E;dp02rilz31w!qVqt-l!O?slIKF4w`4h;O4r8Jg}0?~^3NczLeuVp>9n&m|FT@3 zKQ}qF%MrA4GI}RlYX} zE!{q4WIVHJwto+Je-upobN%$o2wVSLoOQ>$%|13+i=@QFpV)yLvL`9n10PxzmOc#u zdn|fH-Z}@v9hQWBG&ffdvb&YZc(UXJ4B{~AFmF!oDyCc5+*ZPzGoc4^D!rl{zP8N*O?N*q>BeIQLqgR2V$neQov9AkDKlP z3MYd-0J9INd;;9m+{B=FIuXT3m<<^vJ=a0_W>JPKLrkZBKH< ztNB*{1hmONQoAo)ZfvHOAQ0{D>S{_B_7ZZOH8wLd+L?#;dEu6h(VwMb?k6oL*N!7G zJ;(EUcbk-@3Dt-NdY^4%cMvZy15SfteV1`(VW#sGY1)teVk(}7Y^ENFVmh(wT#aBE zSn9sZ`GF|5Tq-;nC+MVb^gL>^7pDn2{%C?BIqRu1lj#yRE;E?V#e`34QPEvd%wG5& z8jelox=lQn_7^u%8<=YVu)L}6;=-Nmu}XHn0>IF*0U8SWM~@!*>^%e?6Vs+G{En&N z1Vm2$XkW1#HkBE`Xf28R6AJL2O1ZSao&1I-&@x5{DP^!^50?^AA7 z!$E?h!9V@~pVz0W{{pn3!*zGzb@rL8l2T-qKA$%ZSMhIPiuD1(9lw54u6cr_KhoYP z@()-IEjh@v2`pCo`(6J9^v(YrgZv+1hyEA8zV9aCNkuxe=-R2Y^mm-Sp4F3n+r$1^ zx2}{Nr}lnbH6fE96ufjrBDdp0x^Isg0i4QN0wt^qJaZKihU)EvNsS>NIQ~L)Xcdmb zsbVJUP##Oju0g#>zwX<|sbr-ZwHuEIbZb5_t8czn&(_=AQMccoea!;xoc!>2o^-5z z4tRZ*RD3+vlH4k;^Xlk|Y-^M#V9M^_fIWD^r~`QSSD>KUe{dAs83?T8@Kff{c3v&2 z{YrfW79JcF;m>U^A0KDTn#7Uw54d~zj;X%+>{W88-Gy{3$-aBalN|pyU{RW zbt-6hJHyj%fbCPK8I0}P0LxSS@v$u!2P!LD*wg1!H08q9Yw6@jeDR~T8F|rx&^Uua zm?8qaR+xgO$`@gOolx2qRnzEAiJF8=%g5#;&qq^@k6%?enZ-u6oBdvj}&qdb!YZw)SRbiFM7^+2UJ=l;ZK$hz6^%nRHg#2`l&b zQuY|Lu5^|t?f8U&)PW`abE<5;)ze9hTqCYn>iR3it%K(Hg%h$hv7Lsa%&sH@V=JDN z;DK2;pK7PIV$4C2i{Cd$te4lW8!Dh>G@4P3*r2`2SO49P9Yx2q7ed9 zA%vA>*>9)hr*<@_ioL!KowML24D^6>X}Uq3Jscg@Et(bzC|2iHS6Ta4$J{fO?3HtG zrfi=MP(zS9y>ex9)>GTgxObYx68VOjg&W0KnE+4yN95bAg@TvzX$O@5PU2fk5l03VulguOCRi6nNGA8BgzdG2n{M>Do1^ZY#7TcMIepF2^a-f9 zQU~0oV%UdGLK;6P08F$%MGz0r2>on12%7Q=>=BYsvT^PiT*WEUNOU>nGL@4Zo;!=L zxtAtWu-EMhZZBKj0N@c?sP2Y$#%!rlk#f(4c+XLdum*_DWZwF6O6`>p-R}!oMR{UF9<2=te2EZ^T~1XNw$E=08M|8Z zD9pgvGrn}PVp<_ydPC`{LxU={3p7*zh@RV6f<|Wbb+1E4j~oYS2&J#!YAV-vPnOS( zy^n=fo-nF@x8dDdJH>ZN1~#6%#Gn^PMXGNeGnB#UHhm3j5sPZ-bVx)R;8sOz?L)LgaT z91I!a*9%4P4-hD;yfG{0teCj6<-+Ov8}AwMKycS;6xz`1?qwt)o-cC0-@P}xR}7o` zgwJy=**8|qx#&i?-+)>%I4y)5ii4_X=UH_%$b5fu8A<1^8GJS4kYibf>}{G+yH%YC z2`QRGN{Dr><75h0E%!#oIGt4VnnlfpkJa|$x%NTHCQI*RAuo1h<0i7S zMUoLt$w&19+x*^}`<*=?XcQ+(;#g40@g&E}GRS-NWi?0dZr`G^`U}$As55#K`d@p@ z+9_QKrN|QPNU8G%p3xqG>9Kp02+Lch2&wLm<`U9Xw~h~aqI>U$MT1qa*Wd=+z8uel zVwdmx$lj0IzxD5h5if?4BQj{fg0M+TBtFAC z`lOpCJxdk_tG;;)sa#IpopSl^$}QLh>EWZ1E4>D?mZF!#OdUCTt@T8w6fg;{qbt3o zM_NThAxf_UB9Wfq;^A zV70nrE+_jq^0+~aVt}p=UQru9FCpgC=gS-5*=F04<#lY(Z0rIhn=zmGFn(pyd7!Ry zGE@Lo1}`rIBuwwz$D*n50X8*RuJ_knM)X#>=}<|NatepbozXngqt6;S(O`mGcgq4e7Ilf14=O0eo<9%@B<}=L$eQqlk zXQ+yiED}Qfa=-u3gdxm>;Z7Pgql6=sb)=*nPgR5o)b`he>`aLqQ`m!27MIt)3fQX^ z<=#YCtju*gP>Xtfn^-ai{jrFEs;f8dnqx&oypFAL9_39w3$7u8)aOdu+!kEFSL4vV z8aC;KP}JxR?huwQe^K8wlcJ z$IX9yADlb!?{Mb-NfW<6jp#br|4p#$pF_=eJu)gP^q-IPD70qWkX#tazxzUGM@|e; zIu4raCbpIyF4FSdVM)JyDuhnVY$#3Qlp z%JkppnYd<;Se(cF-AMn3X$XC+#JdjP_=fNj3TcYl45xwu)=d{bq}M*;AIW|?v;>L` zXe*#qsdPMH`#JkVh0EiJ#i%cju{%hU0x5B4uH5-gdmGmo@{6T>XM_pNUx`Uv9!}3r z&l$t_2mX4wEkU(L)AP#`XoMm=p*RMh+Qm6ePg`pt-Y;fga=SK3o^Nj3Lf$NYzLki8 zK||}#4U(guFl3@R;y7Fm1H&WnEJGK|XVx7v)Darc;+yz9rx}Y^_{x6C|N3|nPKp&v zf!}?eX+YB zUe@&hk*AeG!)G-b>tAb&zSai#vM=PzeF2hRYl`0i0acPy>YgvN9_H6ebmX;4Zhq0boDHYS z6$pc%BlC@2qty)9`4P9@@5uRKFIEHm@8dWlTPVJh1ZOC#C zvW=ROG5gG0=BRM<JB-R9+sD6qmDd5ICHsnoOI% zGlsFY55Gcmy|im|jDeNgvutc4eP${s?}zv#IrA6lB%6p}vlpW%d%+;5*#@wOWlBe9 zR+o8>U7A8k1|c_?X+d1*)Wo8 zM>)oPs8+gccB=0xQ~f%eFW^`pxp(6*jF#Z+%T1dcKNK?ola8S@oeVc-v(^3HCPx<# zUpQcShD7T2`ZE^sS`&51>+R|%G>Wk^;u}!^^9_`%=M__%92qT<{odYGRkYq%!fWkj zWlOTW3N{6cGCA5Z)empIY_^|5aJno&d~-7@r%wqV%v|D7cU6Q+j{Md=Wb(Z!q*q+F z=j5aOqc1xKVdMf?xIT8VJ7KANT&D%LX*n46VtYVUDzYBb*98`G`2A2O@oS*vWM@5$ zJ#rRscQIMf6A?rr5*@uqaj8k_`_OZ!K_9j|%Z zL2`=r<~gSILEhrbDk+E`n~obwuZYmS8|g-f-4&*gjA|0|SNb6#Wj>!FDGXO&*;v0M6K-#q@HlO@&|%2N0U#w zVtR%*j=&>@jJka=9pn;Ieq*Psv(fq4L?aJ|=S5+Ap!})k4{_7X^86VM26%>bUB89w z|3lkbMzs~a>%MI%r9de~N{d@5#Y%C97I(LxE$$v9SW8=^SaElU;7M?IcMD!TSdkEd z-t@osKA-L#_l$AISzj0~sJN+KIjr=tRvw6ac z6^G2VHA8#G7WP0Gj|NOb zM24I~NEnMJ`BS?uCfPR)n~zo`GVFNdi68A3U(Gw}4*j_X$o*U8)|{rT-pB@o9C%{Z zUqy*y_j6|jh?76F#5>0U_r618IM;Ue_U`{|P>ERt7YV7Ui01pd>kO*Nm)XS%h}Aqw zmv&|@)d&A-!%~4ArIPVjytF4!PAx>-71#iWb^Z6fPU(pf;A|N*e@PL0`@Bro=xF?XHq^ zJN=~Q>1U>B+t5>mJ8*csZ>*xQf7PJbYj~Ay&&5BGg!+nha7Jo|Nbo1t9Q41Y4}bG^ z=8rKxYWBF{l&5*WjU8XU&}gu%xm5TMH>|UFWzh zTbOkrD8z2*YzMQ7IketAosq6s`KnyvVBX=qsa>c4SbJLBU403` z96k0?o3!3)nN>wg$U9;yAQ>oHfY1kKAmsl&S4baVrisK~HM0yH$I?Cq@uH94Figll z09zGK#6C^B-ZP6;|B>rE1QmT17S_vu`t?PDjIZ`{a?}$4Al=1QZ$h(>>BWWsptdPz z;rK6Ck%=DC-C0Se(pMwDk=MtSl=53PxG1G4B*9U*>w{Ed}o2mRi$QK>SSC zp7O^p;hD77F4NQdr^az+tdmk7#JH61Y2bM=2K=~-FeZ8G2pt>_?1H55e226Hd(i_= zAsG8vX8tLb%z*f6oH->zU9pg#P4DwYi4HYBRQM<}50U)!ah-5!_iTw}+v{NAe+nTH zGU{R0UFfhBCPm{{jdte*2G2>#Gh!lhQg2&(l~bCu*|uj{Ud%ce?z&Z>A^VQMjLF_*7c6NlBQe-V4z;wVWTA9Vvu3^H^ZToA`NOo=!;UX3YUfl zGgw$MGjtRZ(+k+FM!KP=Qht9O?o@<$%LeNh^9*LsbS&xOo2cFoqjT!pV!0F`!mkk1vaI z4INSk#$Rv0nETH%w3xH5pWRqMk**eFOGP?X{riDAB0bUz>}`^3J*xl18T@n-MQOs=?-Flg!75KN} zdLJ+(UgIkBwEz3#msHMYXErmf__cjeJ=8vZ6U#$Wde`q+ybh@4K?MY=ZTnF3xdT`D z-C2~^wXs?PpDNqX7qI&y?2X<*Panbe3A+p6qGl04@mjjRSoW>mzCW#n@o^4`8`p}O zs7bwZegxD{;P8;Ss_ZiilHm)OoK-+;MnPh#GfVvSYW9uNRB0GySux(hAK$R75r z8n~;O-b1UgM3_hA92n5gvk14ztM-BJA`X9O-TS#bDzJ~`GHiAuM|)bY&_-Hgu2UEaCK6z3rPWrAwBrL6i;^w?3CFms*lWK)yU zq0+Ip!t?%N^xuA8I{O^7dgK!4EqKNxyl!;Y(#QtsrROMjXlM;t>&h>7F$d6Hn1A_{ z;jmK~{E+)NXIqJkugrJviESQ>IhV-s%Y9Eb+qp+#T7{w!#|L7OQ#GZ4#M#-A>-=<< z*Jl$$n((Kv{AlGcB@MHB_zqj`i$A9MrCj&xKw|JP3!k#7Zn2kRY(yCe$ z@pUy|<+D_bFyUM%IvgfHSgpe9vuslZwkGZFG(nQi#LR5IK`n-l_|!e~GTKw;<*M#x z-g>B+MD!>nn(a-ORAq^U&(VZ+)HfT1e;mOPtln1bX7_tpl-kI(Ro$as$+>LSuMgMKXbvLl- zxojy?BM{R{x3_qs86u$tsMnMcg24W)W|PYM4tE28Bxd+hhfn)YP1=|nGc>*|S>e_q z8 z%Vgo1LhQc6;ZeDAQJw1}S!8=y$5l(wdITUS5@+-eiLG-j`^>D~Xv;TCt;0!G$`^4) zlO*RU3Gd|`rr?#cYS{%X7cU~b2}hf^I6u5OEV?`FYYch)L&24--h`UmNbv^V z;38B>^XluL%JfBVn4?!X2ywsNLglKry_58^3kh^8A8KXt!4_Modt~}tZ#LWo>qQ^a zU(Eg8P2H$4(XX8(8xj%;k?PYSY$6Jn#B3t$1~&j7i38Ee%_g_H%@{>>Cg+_1t}doc zH%;b`++3rfF{k=Q#e+BrGl7JhcLTY>nkb_Z-`JDHP$w=Rc4*9Xx)#kHVY*n3ijMxRea5(qyb703VCH@3FMEplMZ|9Pu|f8$di*<@1xiQOTyGsp96CJFr)pQF6tuNgz>WLH}3hLQEpifMrKQ0ePWutn*jlE@0MKJ?zSw z%nimw-{}OY+&cnzo0+pa)Z7GZU}f#I9EKEWG_jIv&@3)T0v1jBh@0?8b=H57d#5J^ z_qdIYQVUlgKW+g2F@tP%^6eO586TpK%b&p(qyyfx8eajeTv8In)CrS{)~L}im{*;E zmv+DmVh@!jX_Q^9uwZ30yuF&vAT>J53%$(Ww-orss@a+{Zf4u&cVab(juNbD{l1mR z^XpWS>a#eab+q?V)21Yqy3|oZqZX$+%^*Q0IkSLnI`-))uHA5~@-d*$fFT!TVXR>1%$>@Q86;oCwa!Vhu z_4aXC&&_6NdlTxl_6y4rQMxiZMFk0Bc9fc$TDp{zROb1*u4=cFUv5#6awYp9Zge6) z*()l8V`f4t&Ww=QYE5XC<>&t4RUT|YrjWAv7}+tx>BSEpOxFj_h}agJbqhwloEIS* zKNMv}XL-m^R2f<72Bq?1HOAlzN>Ldk_AW(<%8Oze9>-gy-P3ky1FN=^FrhOKFpL(u z0?sJkJ)KWd)NPSflRebc%}o5Tpx?9gcy>wXxw-YBw7s4HyufL|D|K;zA0gNnsUz_l z7!NA7aIZ_ReceQG4;}?%C0w?vN$%=F zHfHO@zd^kQ&~Y%E3Ah=DruO3N{fZU(Lx&?dxS8XxfC?l`Ka#q9rE7ZWwE`G=R*}HG z;|PpgY`xyVN`I%bGXPG5w@p{d8sj(>_^bcY7Rs#l+U5D0QZ#YC0Sydp>RtXeGehlW z)GIlHb6Fj~>V9B_=5U&0`?tPYPkeegtz)-N!>&TR_L(_adH@50c$8fH;)@ei(|!2D z+!)`{;3)e{^C2`Nv)_I7YM@@qG5--`+^f&D=iJC>)R&g{J(6<;gGd$l&OVn=$$f3u z9#a1p#>t}0#BBV5Tp_X6x8!5I>yjJf$`uC|naHNVlrRh9T10Sg%;69bv^19bpRR3o z$DRW!aPHfSv%~!WTSC2z4{OSO zFD565xzf-9qrN!7!#83mI?c!so)OR^N}UF40Xi#BTs!KAkGmjej!9?61sTr!NFA3q zPw-6~JNH<^tLHC;%tU<2LJZE?tY6mh6i5woe! zIoE$f%D1ZjzOR5k3=qVGXqjHmv1wZ5V!#WQ1w8uO3 zXOs+W@yuSehEzD0n#Vah)Qn7Vz1CCzKDvP|9|ri^V!Yb@r$<(7^r&x&t5)OBF4Opz z%eC($^U$~C_$c7I{n%0G;L{TKuX6^s|G@p8J^)_$wo`+H?*|C!a$c;MB zS%|{)IfnvN5hxq>STESco9@I57M}oCNy$5MLnWQHQAbV*lW;kdSI$|QMEmRlt6Xd~ zmBj3zDcx4qDN7)0tf}q#unh*h(`vweBz`z9C)vYbz$Ca^C(Nk99U(mce8VENP#dubduviSL| zGwMATRRa(wGW$0k?=sOP@2TA_61BG0z~*#~C{a4Qa;SWuC88Kh_Bjg=UVPOMWyr)J zR)n32DGN(7Nev~eYRhRPhjLWPWIV{;!-9_3X=n0y>%+IuQ!S}VX)KXHJmfkRWoT#Yt& ze*NkbWcGPtaP?;@PY&)Jz~1ajXnR)4t-xG@_jC?=!S6kh7O2KHI%BWWf6794KCBNSM&N7zO(Fg2##~%>ocRB#@6H&P+ zV9my^&VO&M^J3gCkXfCHd0A-7M>I1ZM@+ln8tRsYbc=k`2Wp@QAQgZ z;tY7fbMHz@Az=z~V}_dR4KmIb1yPLgZRDw`$^&|8qD*GPUFii;5fqv`i;Gy+nZ0?= zBRwUnbANs~ z>ZwGWyu08BemOOlkUo>MlH6sWy1z6}_ucrS{L~enfu)q=xmc*IZ8)Z(yP+SuBM~j@ z&L61UiS;BI^}PpPn}kWkp@E@aL@j4GBkv}A=7LXW*{fk(a7N=pl?-F=gOH+=7$eTb zNcYo|zMa2j^QaR}>qm!7OntFe?=CVB-J8~1Mt}T4Dc7{v!$CX_?b;A`PV9^bL@u7VpE1V@T%46&=E_x8oGdihDIS}$?4@=!t@`N+JxPDo1doH_FORCSB@vujm%BPf7BcYbh`k~Xq8|0?Yp72}5=wKTYy zBPJh}CS%#*&SZG@Tc2*$xRv8zLS==2vT`3uKwb1@+~WZVziYLXr4^9u#ZI>vg5m5% z6ky$|SbelFu5@k&Ali~Q%KUU4@2EIkrMIVWP)97_=mbrFXyWuh^`LvIsA;0*5;(mr z%g}A!<+2H$vS#!J70tXTel6N&&%^*~1ogia(y!~@4I?=d^(>G0y3C=T7p!eNwRBvG z=`err*6ohCoH-IfpKIkOay_QD5tF>oJI*b!)BZiR)R^hXap&faYMzT{sB>j@Ypg&S zzilGF&p}8ri?VFIp3BY=Kq&d;m&f}?`5cP644PXN+=<02-1a(##oJ*%&zaZ?{KepA znX|P@$QReHUSnQ=zfYFWa~?Onx_@C9m%EwneLyY5G-hrmFaLQ*KWd9yD6yh1;45P3 z-476Na6Hr#_ke!q@9?N_UG@~a!)*ugj~|1ldef&)C0g$@g_gqtZ|-!5b!!XB?f>+Z z-n_rxsx*vvq0<^awMVfdhZ$Hk%aRYX&TJ0Z7|e1;c42L{(EIhzR$qIC>!N_!ERxqd z1}tcLBqze8GtZ)IrR1YlMyl}q%S*u50WbY$SndG4Kt{OH!@@JME{^jrE-h4EnvL=A z{9rL+1RlFoLk z#2l#R5m>lWL)=PSpsChWPEP50p77o3aWZMihB zoyIe>FfkM|Qm0&22yEL&!}ite^u z%T6PH{1oR*@aoTKh`etnCL&03kw%=v(-$#2i+?9r-1nn-3*0_G5UX{`DAvY`G!rG^ zO7rnE`bN(fsCMA@jLx(+`fozPd~xuHL(|Yle6`7z#yI^?+qFw=M33M_Xhbpd zq_~f<8E0u21m8hfXExU_-+$a4hGWei{x}{{HcDjLQzi{In}E9C4~HYSB$nc4oAlC z)f`JK^S8zq*Pu{t9@c1*{RNy-88?gr)-ER^;0u29fqEwHE-I_x_|D+_k zJA2OOq6*CdZEi4p0EQ!fUS4)Jq|&tNrj4#RDO(?Fc`?TDvd0MwT`bz2 zoGg6T7ax)T(fr}bM(nBj{){>1+i)PhKNpsvmbb8*v%Y}E{MQYOsJ5F*acc*u4uP0w zJMwoQ@e>1wQ0*t*@IJpDBA|^gq_bK#Nxy>EUVb`rC1sWyXh7suln%cZakyX7JKbJ; zQLC>e?C9e(qcmFSOjzj>{xu%jJ}97zfzK$`ox*4V74&-hb%v;bJuTX<4!EHufvZ~l zjiT$un}YqYZ|6oYZr8K|YxT6*X$;Dld(N*1k)ty_RXOg`yn@@jh!M(7@treLiPu)D zWcQfq?^;|toPQ(WPx_{>gm#y?1qW5Bqg2K$et&Y0eesXV?utm(lH&k&c6G7X;B0DD z($DJw%#G&!f5P%Jab#PVBkYc;A3jM^-Tg+jL(E82TdkjLY1`lqxrm!Qa;3bm9LJKf zKGAh-nhii$*wlLO(c%oJa~wqYO47Z$^;`5+Sc&+H8J=a#k^$yu-WF@ss5y39t5Ykz zwSMJU@S|@>-`E8L27!;KXXFB$R5Sy7Ki_REf&)!bDlt1jRk!@D^pDVnJlVwjTC)^@3>*`J8Q+&yh!W0-2U#skdrjCUwSHKZpIB?ohw*z~!Mf z$;ng2WuN70MEwZ2ri@Jo(lBd=5sqRVl+;3<4uchD<)QH@Hqii*ndD|v>rKw~>>;0M zKOdy5SEzo$1MWrdvo7xQHL624VSG+ZJ{xXGA%mSn!!k~?eKi+lJb+(a*+j`jne{Oi z@~w|Pt;KFM^|0ua@A|FTES8iVU(0QNf`5?QEzt%iT8(xf&9^vHsI;YkdK3m?BDlaK zwG(Sh*T2b!m}hA`t2JuUttgeEE8-GWL^cYSAsZ>CeP~r_cX1n_?Ma9ZOa3050{w<{ z-o`dG)--9!*C5owaTi$oFx}^^b1UV*nfWFKpA~V_QDiQT?PrniU2vi5`TH=t=C?>Z zi{$u0`o}_KZI)WZqK;v|*$iHBERcqjFd-h$qvR-26$-*^s$%iR`u$aDNYey94<7h6GZ4PljpjJSB>dB%gm~m9TJ8CJqgt>O zD)pb8Oq?e)1F|xW3ABXriE*!$y1|d6?DTtnN?l1gg9l%7uX+EZWgXA9GOzh^A538I zw`3K*=$iYP-%1VrJazMn$H0Em?=mZHZgKt*R?)9a1}=L<-SWP31}eTQ0gte2&8u2V z45PgA#HZrM9;Vg07`GcbXT+caFtz@-9DL_brYd72+bssy6^}@#p#x|>vU)8fpq_Tr zsgmjw4LDXnDJ{LY_UQv?S90@E61kwT_V?H%ozu@^NfA5ZzHE9Ijye^BQ>7qUpMck` zZW*m@Mdp}|-ZGhSxeKTjfu~So2p{1P4zpsl5`2}}=5GgX{I)~;-jS1IA~)*IIPEme zWQ9&y$sAT*7SHkKh}VvMTCsFjrP!}{<8tw^TxcTJ%BjM~dQKjyf^~N0{3U9lWv(Y?7I?6) zR~0hMq$K~2h0p%+P6FG5OW=0Zx_7)RZ9NPn7dV$EaAUwf_p}K5FLsmw0SQ|4sp90UfK{!q-W&Vp zb!YR;$V@O3A@4p1Co-TWQ(DMVi=2H!wHjk@$n?J=JyQ5K-L_LdBQ6$YXkUiGk{8r- zD`6ld)5y?Z1wmaJiEx#n!cI>s34ZqUT&7B7%a}iouMQz)WGY7)Ap8$6ivJdb`4-Nc zAFzILs+~0+H)XIguis6vYSCN&y>)!TU8X*yHHC6_=ivt{_d4iZzp*`Z@7o;k_CB^v zkHY8!))JpI-11l3<-Z(~JEU5Ll>11~q;TuP7n{H#)hG`Ev&818+CKN&=S-8<>%!l8 zSo_xnh-$?h20UeF`j9a7IZvFxfrBsg~2W;AyoPIczHaL^DjGHDr;{+yFdd z3?*kKT(3QaT!R7vhpr5&O#R_Ek8)Q)|u>opJfMVE3L{uii>rNcqFP>+EyNWn})Qdmm1aM(vu3rF21Uk|dB6gVpH)G*gl~RkBes&`KZn zQvbdH0>WeTPqvTw>H1AiubYIq&<#5BvHOzO1$r}k4JA(r(AJeX#(_miw1tCN+Y7p~ z=+*f%XPPYxTpH<7r`|4yE9ay^jnSWqu>&COKSVLscc079$eu|R9M_8Xdb1uRnc-X>Pghnl8q+x@@V%r9+eN zcjQhqSl;uQtTjmpSkI2O%p1|@gFZkU|;i>#B{F39>d(B|iIclu+1=HO(6 zf9*6w{aV)y|CQ1Vo9BS0gQyEx78PeNYarUnD8I#CqIW^Sq`js@3wfO>2cUFaJ75+x zVRtkmPv=Umb-{QvKnmRs+p8K4b~ngzT(tmV$}JjEolz)7uA40Oymm&Raz}gt$RD9A zV{p#vW`6P3ZEG!Ne{-O~?RI_>4zFCELmk@p#P3wBP+yzP`8${Puvn`R$H{ zDayj{EM%nEUz8$8+|gAac4q*}HsoLUHOaihDS(=@AB_|wn`w;}i>4h!`-`$_w^^xz zdvb4$chhgEOaOaAle$Itom~W=}+2vTE%@% zrvw%lou&%>;wr9eStE;9u}M#fQ9CWAeFBzl>%rm=r7 z1_yP39ckA$)Ku3_`tJzW?f-2rrmHIZ+~J1*809sxa=d*(>(9Q!4*J^l7xNe1{dfL@ z)J8Xj;{`ZBzdE_56?ZufzmY7muD z_ad+~BOM%Rao@Uz$sNiyp~$~fT^!cm5| z+#)Sb)uUNqd_;@s7<6Sk_U%vi3&(qa&T_z;}gemB8(Ec^!VLYG&J`gAc zodI`0@|R7%xOK_ktkY}uJeo!=+@s2z z`T8@+S+7I;W|cAo=74mLLhjndkSz@l4oC~!Z;yO(r$P)zw5>*x2&nu{co& z4Cn;GP~));FYUZ{hBWWxOddzPD;6r<%2}a_EQUOa=i}}FUWm@n%i_Dd!^;SM2514h+{?pFV5`p5pZXy&^_gRa-r~(~d z%Cp2g${p1zbj>ut+D*vE4$X~8Gz|`Z!d$2lK2?c}tnxyTvd%hu0-}IVD}?OS(|M@F z7=_!lzbBAv)3rfpmZ!LX$E5rO|9Cu~mRjXI>ixq)$KbIYT)mc?bYn`%wWgJFO4ovp zM=9WLA#EJu`~2+>i=3J%o7K>n`QKkcZf7FrS0<^wMf$OP($Texf?g`{hPY#QkEg^n zus?2d9AtESaPG|+6{)F2`#H1GOZ7L3h9(FE-U{qoJfMks#LYjgFY9*$c9L+&?&YFg zHKW&)!dE8U(3qDG85tUxmdqYzd6Txz(zP8lwrsL=?K#NU>m=Tc$I0cKK9Xj#$b-)_ zxRjiJE*P}?7?59W(@j3Qf!Y$hpu!u(#Kuc|h+(!-C-zR&k0YeEVTzD`lHZM-d#gT3 zFJ=S7vfsBa?{gBSeNw8{NuSfWw;wy-l$`x$k(s9;>|C{r8pIN`e4Ic*sGB`RP9ZhI{Vda2IDapFvo9Ac8Jo|6<>=hdu!`$Zam1JOdvhC)dsw}d~C zt-guXF@&pa5ZDg2SCk1l_#lnr1a5gJ>>y6(w`)0ZhBww4q{onWi>=-nEVcY7mkAoE76Wm+#a$H z$drxvJX*2>I;MMhh9OVhUy;*n*Ly3%bnk=Mohdjw>C4byfcw*zc0M=K4J70zGNvBX^2?# z>o{om0e1mPX=>S4D-+>@fZtIkG>bBHmUCPdaGmVk4|duQbU9R0LY|@TGQ{-@kdXbY z10=mtfKKy)Ooa zqsD-rqv9dIu<_3>IrD6;-u>V|?hqBaiyAfDx(o{qB8lVo4V4a%dRa4VI+R8Et-(8Z z@!w?^kt)^6XZ~CQ|IVRW-mz_WPpJNnE@6E>qksOPqyy7zHO%lU zHfq2ChDTKzgEH9{df&!;4`c}VB+O7LMHshc_Lwep)+{`od5nfxOq&u#MwpxPJ19Q> z9mlI*mG6`z;z z`aaU6U+reXv0SXgBb(*X@5#flzF@EtZh!hew@=)kX^;>V-TB>f!*SuO04kjjEtWn=O;k?KkqUP)A*T4-Oxt5b8!-LXu_hPy} z-f&%2Hy$Yf68$GK8jp;_Q!zf{HAOO!FYUxu^S!i@$RaUxO@fiPvNef6$3 zyWb*;qfPrQ5WAyy0J+hTS*1G?rMXSBcu0#1+nj#}|FlEWS@vl7B6>)>3%8|GLT_1n z5@WReBD)+#0o2%<89XI7nd_Q0&!}*xjJd0V6j1v{P4}aze$lWDB-cq^6u~tKUh*tv zJK`J(#7dj)JIEZCridY13WFsuf$uha@k4%u0BZ<14}O}fC(=-2{Bz<ftyV?S4 zFwuZRT+vjTjv_~MQ7mpqHK@5A=#(a67GW;6l!)(y_B%hdx{5C%EIXev!$9zKPyE>P z5k!Q%CJr-q=eilxKOqm?rt-xB?+BGOM<4RBcN!pb+z!XU=n{CAFyBVfL0&dhq^2b1 zhBfEENiY)PD4lztnGM{JM4ptTwEFFnavnpzFdjWDJHbbe&2+GxDnVNV$jG7u5|Krs z3b{BlM=eTh#jU1*-;H&%XnnJng|&0yuY z8#6s{ac5cSo0HPEV^TbGwNW#u6Q3AuDyZXT1Z<0GdMv zoQZeg=|%55ueHuT$Hi7-6VS%%fU1Rtgcm_5v2lZB+rdJDQ$KXF=Cg9TBa{= zKDbABMqI`IgLw7R1df1N5*GV9#oI$0&AFhgGZXiEN&L4Kqgr#RCUXfnnsb_Y6|%AB zI&9@CAX%>f>eW^@mfuvK+(e7m4bGF-Rg z!^jzo@TvxST=cLZeV-+)z&XQSPo*<`((4wd``LhfK8KXHp{|0VLDr7JOyVh^*Jvhj zyYAD-B~xE!9X_*&d9~lql|=dxmHD$Z>EU_L0p|xLRx@IgiN{xjAF%0sDue?{>Zk(M zUKos=GxcRuB1pem%4QHtrdFc{aJcBN_0`&0ufE*gFc(wlo(814-ffE9_e%o`jkz^f zus}Y?SMdUKwW64!E1CB0Z-^?g(QRw6s)g!#$ku6&x7f90%nj9%Qd#W>liP?$FESWK zIB3dXH{SX+b4_UkcBc^;EoY!Xg4WjXWI*6pY+K6Jd}Z0NBw)(I3Cp^9Of~=$DDNcY za#I??E(8mRUp9DsydxNYmn0{B2N4b@c2G_8bB00t8I!Ad)yrjYRehd%^*Y_byg6O$R`B%{u8@p8mTi^ugGwXH7wA+jO71h&$zR zO~h^SmFyvmLSM34qI*%FQ9bPL4=Hr*i57n%4csGSBV$Ly7n9 zX|ACj@Jc5g(d2wUkCE~--ZOhFsz&WdZhinyO!S8Ke2mc#se zb$7UC-ijlSRMdpX?8M=JVQx{-0tK>POFBXo;vXDQ^hB-#VskebssMA2Hm7*a6S_*N(6L(B75>`?=0=1uOw zkZ_KT(6dsiyatCt1FKn7Ctu}0q&EdK)g(c-V#;a=9aFj*{0kdQkN@jr_)dqF&X^e> z=q$BQ_R2a(bHxgEsx4IGthYSsd#vOrptw4^!-FsDbMZ1HBal1VG$E#G65un?bQ@7~ zIOR9!>5#QY#k6Ay-#!~H6BjuwXucjft++7OW583y`2I__&e}jNH>X3Rk(ly*U>}oR z*Rmx(U1k_C+FTFqMmL$vk`I@amye(an6vZ)_~-TP>`KotA$&<$3eysik@c0V<0b)wRr8}t(W?Y5IFARLQs5^%h!tomv`*p#m(hL|qW0bP z+a+<9VetQw9?!9AUpG8r^&i$o!af6iuFx>IAO`z2>}!Bv8=@f0ope<6kvlmnRu_B6 z9i78Fvj4ik$>$nI|0%P-#Xj4)D5}d&WP!VYG^viM-Dxp$CwwHwf@S>eSWQa^84&!| zHtu_*8`!YUR_kNi>YtTd*3}qDHw2Th;$`026Bqe93^+iAGQk0UZ;Zvo%_^ zrf5{<^3lsNXLS|Tl*VjPYenb{B1CoEQ?N-Eu5Z6BOC`K6B&Kxn%W5NZ5L(cxkFs0E z8as_;WUw@@vy@6~7J6XdzuJp9`8M4B@*A(MQj^_~<7A?VLiS>5K1Y*|VWEN{1quRp z)MuWHv>Wm|?X{Qc1WB*q&LrlHcxyrnyfke~7R5sHok)VsF-t%c8YDpZO|?<(RT`MBB&heF)Nmm2|-v_ua% zR(KD-_z)*>odsIv6Z8E^ab*eKsDH|*$rfNXCY3tKm?udt=HmxCMJY#UW80Kr_xs~{ zd0AEUc-xPEXFi#Sz1I=1o!77sCM$N;Ph38m7F5H1XMFEtD4ze6=> z;VcL7{2ONjke^~G%+k=T?Q@BbqhUwgVNf__A#mmLWOa+ zg?gBh#*Q|&WOGQ^fRM;L$3MgEQ$B7^k#ED&vx9s}E7&xa?ZhmYUR7ny*XPL@PF+b)1(N^D@_|@DuB;!oQ2vf+0*=pewq(n`8hes9bd9Hv)=^W+jl2U zJ3$!nLBIv5FB+_-;}IwFoLW-t@7FEvyg966IC*@|D6f2IY&NhNobYE0^&e;4gzC4@ zq_8qi9d#8WU;mm89u%NhKQQ@5P?l%ZR}kzi)Kp|P1lQg-S4k@y&TPfubFpq>-W&L_hvq-#>m&G<2K+~4;Oc>AB7W>^h&Jf+1>l%<7@_a}=NzQ{UTpB{7M(zeW z-PY2t1u$XrlYu@ISy#G@bn3Xv|K$7wkshuPPWc~5=;l#s9N)m=9;J&S#d- zy`J@zs6&Rn4U=Q|^?CgS7Srf(gFIBmY&6JwUKRP+nhGBEr%GMvF*xCCf3ttFc7s}~ zr}?P2kG!rzc$vYCcsJr(kyc`ho1ctbOPuyvks?#IZi`j#PWE5|9iNOyk)0K^%dN)f zdK$!{priAi0(sW24@Q87b@Y6S`4DhxKGEGnf`-{yRTm}o{S!r*lD0P$t|XhqSH9F3 zNXR1Xqrfluj*8n-fn;hG`?_qn8fPplH6fWxoZ6Dvy!xh}Y5JA)HSWdk`Q}I|vkKi# z1z~xTi=yg01XpZsvc2H5Q!q9EwG&kZP|2wrbjn+tDSGzX;X*zJ=OPg`19ijOe;aJu zXAivd1fFyHxO5|01XB}2$ESQh=v9ROe$0rj&GMX#6Ugd~Th!*v{qzK%>ea-i-B1U= zRn2Uor|l49DaS}@1L$;k2CjKuuvE^$961S6M8hoc6f1z)N``^Sg70nnXxaK!r{YRS zb0pCMB-#7#q8+G+}zyJR!Ew+*+3Sv4u&E5Li*AE?zL~zz6eQa zZdl^@Go`1N>0M6g!&#Ym&?ojpU4Tuu@A#bonE88@fK@?^=_5=S?YO#bFf){1|CVQZ zi)a~<3!$Np#1PwTqYqO48&T3glmMCo0Z0+BCx%8M@7HK?-pn}k-z`H9|9Lqx)^{Gm zNeth!;f~`G$ri@%QBnWoLCMg!$`+VD8B#7B`T4gUXEY6Kj6922SVbbM1v7<0_*7q4 z=5NakkA;JRX~R=1+L~x%W{ngM!c-WZsOi!aN-eCmT|9}R9d27<1=P+fsOtG zP<)yDHc0O3-2{0A&xpEo`YjyNdgE%|G9u|w` zMzsxXTrPUD_br`*Ji42IbiERRwl9`w6^*N#L>1Af#P8<>nhwLL+47s?FvU>w(3G|4 z8;0DD^^9plApaypfB41o=wIo1VjpsDgmy_B2C!ma(La+nh;qVy@FO0c=wId|WLJjR zBy?tJo+S3I^4x$+>1kJdybPdU2yeMCcRWTY610&zQhY&@O#YguD11ZT*vGO~iG9NY3+PR&4_7P|-EM3=N4Yg*cefIKWSY1b}H6zSks?^TK!b>1s zi&nOAFlP%c_c-@BVZW0sBxLJmPip<98E=w^BVk_;$q=h?depRwaGEK+p99^nbJQfm z455}!4(Kb*rabwW?jJ1H@V|0r6P{pk6td{bW0=h6z|@r_p7MsC7|a}YkO;$I)dxbR zPME~D$4yr@LnoRIIf64Zc6whjsRHF9C}_y+sM;t3JQd*{pUqJ>CAL)L`e^VxRv zwk!BJm##a=`jE5?X-Ng(EGS__t=E4~*4{}5(HwqUw?~T;vSH1|gAn?P8E7qE)m=)$}m~DqdQf+$ogBnMPBKFh{cuS%0X)8Ed#3# zH|T$8t~loI-tdG|u_U+jJItOVli2TUVp&>`p^}Y`{+tbT3^~NMGnK0Oma@n^E~Iif7f;0OpO&S5&)O0-IQOoBvJipwK~UHTMv{O zGCE$t;`gdO3g`>o*@ve_u=-r!9+TSh=pm~I>pw514BBuBS6B5q%<7>Zmi?%_J1G3x zyW$M6rC!G=UYR){E6oqahQZ2fD-Ex>3Rr~%3s_A@CEer(e%2SHwB1HC=drf7RQW#Q zPeC*9Coaqn4zawGO#=qc)rL#*4d!V-$&?(bPn zeFKJ(I!BhPe@)KdU`5ycTT8rLjJg#beeFuDTP0m&!bsn%wCctERnGNX)L4i1AVy1F zLli$P;2+9!h=X&2MO%O-?ay*1=z-9 z6(b_fOn}7&NG`w6-l&$~_nQ0<3Z4P^%AcX{BJ-xKALH(HM#Rn4OI2~Y)#HQD;MAsy z=0`k{Ndmp_$GtP(AE~oLwWtv2Li53g26AuJB^LY(ja9PlZ>g#Fk=e@5BC!bsWvk44 zzgWC#^E~N5C5Ah`WSA?1XO&9qNufh_dY}9Ezgcp=l0${$>QC ze?wn^+C3_}+AP=o_78vjxoip7)AxFB3_zs@k81B#R&Ec|>vtCR(Y%dy6BhI zNtzLX=}Ce+FA)~h>tXBS>$w2~lmfb?>lJU*PZf?ny`9>4`YYBzAhbd(x?~s`V04<` zO&a-$`_^}_Kp1h+RnxYk=Tmcij_lxnMs~nEDd1oSTd7~>JosAUii-ZkgateCc2VOJ zIS;woyF$7*IG^MA_@I)i#uxd9HP#+5Mh70ylkM~iMUmOJI_DZ(dUoCIr*4h2e zS85vIxX|v`c>n|B6G^k2rVAMkghz{f*~f za;e8=+{0v5(lJb7Say+p#I$YJQ6Hok*BITd+_@%uZp|aos?fAt{1VR}pFhzrEc5?2VRT-_2CC?82tGEmbb!q08N!k`pK3(=flY zxA#G?H^#G>z4Q@wU$mMT!s*34#7}>(dF^Cj>@kNN8>T^U+a6m-(A%><#E1Uum`*K} z&kZNC{s|tHIJ91_(*|Y0Bbi3s8teFyQc|53G_baq$~ zWwMaLdiXAUfQ=hpxaiA#0Z=ZX#(g~HOI>3EQ-4-+F=a&FPlG$xNU?4l2Z6A9*O^-t z7Ya@DTqC|I9b|Jbxn;8$0Bket&HJ})P>GMMQht+~zaHI8)Q0UaRZsbxTMHBo7b=Q) z57m^qM@J>_3WVPw%aykp3`0`|tG?{p;+#mVZ7q5gM4`0WM#N;&?&HS9*xW=IoHFySli#jeO_a z-cbvzEgwVn#$@~-$^c9MR|cgumO$tM|Z%HCLiaGolm^yrj~IpXEU&Q#ge1jtG8Bt%huXDcu~8&LvSwXnc~P zT0y-Pekya+{aKyefZFlGDzXJ$8fvHIxp+1M2(~xx5X^ouWZ)MPJ?N*(^-AIw_b4{_Drzw1qxm|!M%T4Btz?! z70XttWKd8MG%LuF3OJ=>=oiPsQc?k8=Yt#M)T;&?8t<6RZB68hK&%eL>on~j-|*+H zRxsQ?tSTmgj_FB{Sq}%!__*baxf(VWtn5zDBzb!K45V5BhkE8gN9)M?MhFa~lv49N zY|E&6N{8c8Qsh@|(kDYu5cRf?Y+DO^@eazc#7+rF?w%@qMUa@r&YBvRaBBk9#Z*#52 z`^{2B%OSM{f-FL-lN*ed&Zp$dQgC>yyuB#`JQ@?4yZN6&Fv>3W7pG}A!#!L!^xj#2 z|B>Bn2XR+vfp&ylP*^348jO`zXQB$kG(s$!fzyE%Xw5AJ4`B>zb3ZTcJ@5-UD z1R8`qeFVY^Blw{B$ZQSqf{e2yN%cnyJz3e%GbfjsvQRTKvpykJ`;RmKSL~FC072;3 z|9GWwd8$ZB{ln>fcI4mTDJK8zK#&7;dgSkapFJKAAoTGF989&FKnlDnomOJzPBuoh z2`>NJTZ$oSphKct|K)+?z9_I4Fn(ZgE{y#(((c-Y98{m*YgU)$PXUmJd**+s5cDX* zzGC;{(wFONdz%)E){3Nyk$71U+P^s^1XVK{JZTEAFmi=!$0i2iYD)2qSEKzeFj2bI zAB2Z?n7o$ez?9)hcAfuA|C+4)>Hg2j_rPAq zzSf5B;{vX+8sr3KSS2bNfj#^$>&8d@ANn=0GXulm<`v{%-6CP*QvcUzcv3m?zle;f zf+Go=q#=(@DGM*bV3Ge0;`sl-i!A_o$GXJ-{TSp%ptOKAa{V7b?*GoA_+Oyx-|u9$ z()6|IVoWG>oA5{=8d%x+)S~&}{|!$ExIf}5=Kme-c7NQswbQNf$+Ydozn;DY|9SdO z1?l$Sx*7aWOvKf{IW)PXWpA;*twMhcRXD9Im{wL03+z^@9VbJ;Ys~$^T1!=a)+7?g zDg1MjzZ;O|N>y7=lW4Uze+Fh%+{hHa8I+N7VdR_{x_sL^rPqq=cP5KgGko*z8P;>$ zhKGCGf_Mptq4~JrSY@S4hFPXxW{98Ebqnz>QXoU zp580vl?{G&8o1^y#nCSJ_y6tjzeJrM07Z+Iq4z|)<4HkoK*CI$#p$o;$O@i4NCL?rGn)QBm+B2Jo)g($Llw+@75vXZHuug zQ0T0&FneWNKUvAASBE1&p49-rJbqo5l@J;5}S^q+_ zUQ`6pQAswQgW{c=JEf+!h6et4c6PRed0tUnO>U>I?)N6jEt=ou)88;i-o8Mx@-#~x z0KmRwk!u*8Cx{w;Wh+%cm|d15?jOtDNetJ#UDGKOzl)=(Gmy5Rx%le_eZXtE_aYEV z|MrXrN31$HmUX3G+Ah>;|3PM*nh<|ISKINYG-5}5F)QQ3D|Yxa-PC7r|26tn2(V=V zSHy}rf}%Ph@>}jd+qVYi>uMUZHtdacU3L%ex25E|;;Me}vqqCJS^Z8?ZcGaZ!zUqh zd>6#r&+c%$u`-xgRx|VwMZr!NJkaU~);8xbTZCVSG z=YIRr)gScUR*lbcVEx^#jBl0NJ=XLlmvfB8#FmJDRmAmWb0wJqA~$^MrAQdxbNyQQ z8?Qhuc7%tG17S^FQR_=76r4-DPYdK<)JhrD=2|~#y+@pRCF-LrgaxJL@#9V&SlPPt zQM($_8EpSEaPaRHIaR3}y5_xSc?xJ(%1C1B^v&!RC(Op$C(cpQ$}E#@zg?X^!I~Y= zY3F2~;%E;O@e45}Z#b?zZGQG@8~R!34YWHf_>v?X2KL~~{czVOVwqp;Ff#W&IPsea zSqeY>eDcm&Vv&PLU`R~eWb3&aGqBFOjda)gQ^#OEaQ%D4iIY-vWPHPVa8LcJ_@oc4 z97H>pIG?8&Gpfs};J-wj#bbUf#p64!CoJ)Cd^B*?pVV1PVB7of*z)66qKDRtd|YIS zmfEt{B>o-w;+E7=Wa!uGTFmHHkGwV|e_pqSY-SIFZi%ZeYbDHXdeR`I?1t8Zo<4ui zVZF1$AJr#tN&7weU&)2CuOpaz z@j5m_#je0xS~jvdVwJ)MJKv~9c{HB8j4hdmNDb5z=>nWTb(wcsG;GEeNQVra8GYDl zDdBUtj~O4@>|Db`DG@~7+KJq9v(Bw4pxi;R3#;+`9F}kjw6p8*-Q9yxgDE+8@-$H) zgO9d>ooLd9*_R;d%^md8voCbp)oV9_a{pe!5PC51GpQ#!S4cZ%ERK19 zX7uu;_wcp@X-?c8O^;Lm0bj`OW7T*+Vlhfr7cw8BnL-nXStUSC zkTa^9TUD5sB@$|XcJqMYCVZ7^(x)aYFiW&K*r%f8{}ubZFO+&_9AZu?Q%lu*{u3wN zua-1MWw$!_PhTK}uU1xN&Nn|*#ETTW%jcuUm!6i9Kow!4v1&Bv>!wPwZuRebb!S>7 zsLFs(_NVlCFe~kv!id{XS7}8yo4)O%q}auw18e+h`NzVT<0Dzc>@>LmEm|8Df%LKe z6E3LNsN7LrH21|7EE=-n8A%Sg-^MoFlIG9Hd6JM8(Wr7qnqn5sn>m18F1g=NE-|0U z{1ITJa(7`w;y0>3AQZWpM)s%rLv-<+4mCpGBvMELp~w>t?S6RztrW}`fApA)fB zkgJ)tWD(G%uaLDWW#kIix3`C!uLRF9%_vUMT}=7JPDSF&^36LUZZ376i+zPHE?+OL z81^&fc|eHJdZf!KrDj6mJ;iF`i6cd^#7v!9WRb6OLcYOFC-5#~n7DavnFD>Jnlqe2WR zLF*8ABTS<7s8o-RMF%}<^*Rp^%>e;(n`Mx~3OLuREMgPc>7y-GOFT4=C*2;9{2|hz zMy9e?JUBTtk8fBCH1J;1gs0}wsqqeJN!l2`!To|cAZD}0xzq*zRMG(w)@Jn&;;DHW zIxu+Ya*b%zzIshUGfn(K1$qi7tEkQa*oShTDkx>0c#UoD+}Rz}GW_UVY`xr}K3jIt zUm8=dHC7BfR$yf9Pty0&U+O8jR!arCM%M!HO?iDQ|d~RuauIt(5F|`xoh#(y*Yi6Q({~kV(9QKA97TADXf!4{t(f zjQ{<~tFNm_0;H6rZ!m#h4pQUCUR6QIt;S;w+zj6-YR>q}+SPJWG+W2Mk|le`^U7?B z(%Vpx%#wU^X{rczKhdz|9|g707z`J&xg!09%9as#pQin7u=0lc(f|S zEzZ8w&7LGUjLHpEj0G5xbHvG(Sw9Svp`I+a7@2!DC&qR&U7~`^j$E7oo7^U$p( z6K7qJgMPs8*fpdA9+1CwUAp0Nf-tEjlx^!U{5B&*gCGlwzd!28>o16jx>5UEv%cSa zEDOz~*0Ju$7dInOv9cHTJ>aKhgv)tHJq+%h2-_qKe zS`q8CE@KK`MV5i4b!an39mog3y0y}k0sU?scY*RV=*)jQ9RMBb==T59rh?B%jO zb#EVU@GcS9ChlY_|B;KWeIX~wR?l30w1VXX2!x8#u-b9fkJon3g%Pj#3txr=ujn6M zy*H?covPT;%gmw5GLCV+PDeNJ@f;&9d?^hACT2=K&JgOE)rA_EI$%SFW~z$VbPU*mmI47q>ds@KO)|d-d_O| z*?YV!b>%R-8}?i`{VWb-=ud+dEt$rMR|Fs)m8-I3rcdfUU3_V3Vs766l**TF%s0vH zmdC6zf%n;hPl_@hWTOHWY!x4qx9w(c{H@J4Uh5ZD@;H(Uo%Hu!X60DGd_!jiY7{Bv zm8JB?IE+e-!tWXK&2;-Uwn*{;%B|H-n{Nq>&r_|26WeaXpmMG2{}Ayk&*uvaEQ9ef zs;BdnFE3`=oB{M>p6H$XvSXw?t#kSHh$ebqz>P1{ZgF<<*yeo3}*<;hq zlA<}{-GxNdU5HT+NSThbXR+}8weaF@YJO~etV^m(g> zXdRK@)@+`#PGWVJvNp7(^~P5xvEZ@H?aoPKC&32&_LJh%Zh7OlROj_9Rry%AXM1{} z>DiB(#KDy{)zwFi<+++NPn(>EiTifq(~GU54DX?{>vK(jx|%(hh;AXBxA~;8-c6`A zy5O5VtAfkW>94UHAnTaZb#!S>hI`tmN3&ug*K);G+Cf=Dk=m)YR`dA>`eoCT#g6)c zln=`v045!W8tcPr%i3gC-6{G94H-H029@}}SFncK!)1z#HI*d>^=BoZ$B3U0Of^?M zi$ASIHA&aca{0*7CQ-GO)M{z7t>FNMy7@0p*-WRS=UdJ{IE!C#h)6AWp8A=z&vXc7oQs*+f{Dlu`{jka>pESuh=ocG^DCCj1$HNJ zkmUk*&w6S0;hjbCtF#T_l9K^RvPM9&~z6o(G~2;HyPlEx9!di%(C?4A8(BCdynQGmu9f^Tw09sGlS2B z)ojk9)QW^Z9~`@sPv=GJgvg7`y34jT#Y7(FP?;D9oLO-le90phs?;8CUrl8j;>iyf$rHOC(Eyf>BK9L zU)8Gunx%PyZv;X$sIIS&h$Czk-#!au>{UDnj)`+WTPqA*s!V4ubD`{D?sxultp9E= zqGzu?W_@D?;F`dtC8S!jnuQE5VO{tBSU$cEw^%zy?RXl$D zSggN8&ZV&A`I~x=suHXCb+8~*eaQ>8P{7pRbZMqMglCx8l={hdPs#358zH#Nlmz%RfJ;PWj9God}h{Ev`#S z91RUhcBIZtGCRbuyd8q(V3S2&Gi6ANAkcczVxBZ>#B#{v6dNT~5mK?z)~HP`Q=c#o zAtEk{dS9S*n_20ZMaloDR!iuheUcPq!Jl%fZ(0t_9ElOW(2N`R-E6_K2kqj3e=CZkjkMT#uX~80O+jUP@BfkH{ zsXYDOY@Foi@tV$VZ5ejO{;Qxo91UwRSb5oy)rZB3oJl;@Xm}0S>Y*6qIR72ITw>Ll zLuSkU`Rl?t++HfQrT*KZrtG6NMI%aOMa*2tLh?wCVZ$nsh}WCswq{_c{i%vuIsd0) zk$-Yb=11@=ox~;dipRaqbG*?FKQ5^=CY6+D0q72@COrvBV|gF_W+pxY zC}rv)>ycoFO7lU;n#@|Sx(qw?SE)z~>Z&n^q#)OPgrqZVz@{yvcN`aT+6V3Z{C#m< zRx!=Up$}!Y;X?Z8L~DMS`baK~G0TTiPwHGHeO>TXUeDF$j||p*G?$L^21Vs1k=@LF zv|}4J2-*nLC;i$_OyA#@VXDn0J<^lBm5;$(OOLBVTaR@QuJ?$-Gho;)3Vk`0xL_^gpE<*x?NK*OWTB{l)cb9p`Q7Er?UEWx>Fd#o7t!-L zbOHZRtae?^1|XM^qxOPwjq?t7IHlC!b|yNATa)V+&XvvM&dOfRgo^S zfuD`1RPRsTWLQw|ebdU^x|q20$o42|z2*7SaJg6uJeR$5#!ft>m@(hJr-T#ndg@%U zV7$`jY`Ka}yWF{rkDrZq$bYjMm_eGld#{+Aiz;)u*h$_eS-+&RdeKm>Sii=`Nr5?2 z#k5t9Es8kU5K~s>hyc~ZX8a8N{#qy(6K;%+=s1zABkkX%1Ld~dF5)zPrifh=LOxLY z-1~E1jB|d#gH)1GVM~o}VDM*5BfT?bMf8xGJ4eS;WB13mQR&%*j}1ASw~570$A=rU zN^6cEad@G3=X|U_&Ajbxx5H5;rVN~Wx1IiP*pYleS+ERlU%j2{Fg_lS`jX^RqtBLt zmi}(#B&;iHT7b}S{?6gB8L46=|H%Ae*{3zt-X&jR?ieaa*3)d1-}YAj%etQ)rdU(b zd9nQ<*msZ1o7*?*;QCJI6XJ(g$0HS z`Y$q8ZBen=@Bch~>~6c-(%Sr@t!vR-I8QB&L=pJZ>DGhAw!D~|N|t;sNbQ_ir?%;6 zu(10VeX#XxCA;VTY}Ye+9z3)%k__3c*9*(w$C`L!#hVI4vWRW~We{#4a=q48<8ZSS zd75WAX8Rp$HeO>{1xQpqmhAk2wFKgdS4HUgc@d4%J4|dwq+`BlOCx>-)BFr19sxZa zj2Lpjcg7aKNYi$4Lm_$*p8Q$4qt?Ccu6wJv<%q{}atbt(L4mOtjm=dV^XPl{JieAC z(+JM+%Dtv~A-@RgIG8=S{9CUanDB{d)i_4^MZ!`39aQ?o%+Fp8jl;DXtJv4DUz;D8 z-0^%62J>TI6w|r!UhFV-w71lL5}FjlOE|Bn=p{nuRA?zJi+x>;eHwZ)yDG1%J!e== z7uR)vlvsjpPbL#5&44hg{S@8t4XDW;Jqlni9+EUCLS9dL*LGd@0 z#1xNPBvf%@o_zz!zBDAQOwZv!F)Qd7`5+<^`3@sLQPu#-j>laos&Y#X-L4&b@zQaK zs+P2)qgb%PSNi#bqr)%p&jh-pEK!~lGRr)weRKA{vrqL+3?v{o_YK$0KJ)kL?zs)(yQP%j+N?G(k*cc_Zr?Jw7+qeR}z!`g)w9e7U)YxBkHKIdZIPvG)%#R05goq3zWID9nXFMs2B z&DkPM9JO!trXYNOkSGZkSh5a|+GB$gN@6-B?e%kq2XCoN6`Ch8rehu z5KZ#zL-2U0P9v*Fk>29xVY#k?h8zjSPZ?}e?PQbzXp<%GKrr>JJoXQXB_7J#LQQ`H z;)~jwNh{|Ge5%s#N%~alMrkwOs&aQnc$6U6*{~(K6C*?P$mz%@M|4<0G;ERvGpo(3 znK9|^hD5Ujz^ly=Csca3Pc}?`W>Hx=ZaUwpWlTJGa;Yw`^o{<|U`D=m#1XRIE2wDwSE~FHVF|9)+HMW5!-M6Q_|UTV#KMh$R`Xp9dxPV2<%sXpOdpT4PnZXWeM z-vJ^M5RD;`0xyGx6`COxN|;DCOSoKp;ezc8Fg=lt6mqo;sefZr0eeu} zLMtgapAE}OYN^|SYs!<|n*>kxb)z6HE0m*E{N%pn`DP4(U=T>9nII|jZXq9Xv$*<$ z11PB7%&VaKsQ5G{DYAbssL_8WTbh~1Sl+;;Ox}O}ibE<(AVi4DhU&4v-!`&poyBXf^)KpRC`>xng0qWTktO2*g~#RLX~_ilVa z#r9WbgTqZD`y;tWMg2kE649ge;GS$+H+Mv9GhE_njU@5S)8*3nktTg2mUh*0Es6{x zbkWf*t)xV4=LS#dhslBz4po#C$K$z@Z?4Ms& zs2)b3y17#?N9|Uda|5 zrcOT{$4ww@3k-yRB2~q-cpYAIVyQ&Sm07OE%z&PcUmz1R+Aa^n72TW2VO93i9d1qd zT5KN2w`cjo&_R?rysj=wfXar5c5gB(4;d?V^s{c1v1D%X+>L)Gj7pno>Wr*CZzoUP zk@*=jzXEkC$v!I${Wd+SxTfvTH*N2T#bM20Aj1B8KN{fYcnn}vNpPIZ(n0gw!R`%v zjxL-JEG#D=%r5tcw15*%)DyVpQMwGso}XMA$v-0D00~$vA{6e;z84l*bzW}IUu5Gk zsur1sHi2+$lI#s`gg~K znu|6^tT$g@kyG}~D2n!1dfQhwr{+P+?nPMwRqGM^=m$FmlXqbhC>>_x#D3Kd-Bs3(n86F1oU^hJ%_qHUbxO@o2Ek zLCijfnP~oDKNApk2MmOQai8N!&s>R)(}vW%AKB=qI$2~yr9KO1fVanIE1YS$dBTf! zTq{r)w3?4KoMGYV(=ZTZ;JRnTU)ucK+Ta)ET;o^|E_Ppjltg&8Dkd*~6^r3_dU@pF z^Il#v+hl}zLO;xvl_JUcg^4y=CmF8|ZO|eH9(wMiT`(`%@MQRP1o}d6umZK{gZ(qP z=AW?Q&lQ;*ZY4~lIlNk0e7Txn^62Y0>7Z3x`&4uc>6X&^fHODuu`=((l8Non3mc%n zvFc0mzh5+UcWog9U+|gZb)F-hDa!>`au`5Jf#J!e)UQ}^Zm*ZFXfJwQ;jdjdtQJ2d z&hOFHVeQ?{_Yq30Vpq-_?&m0QV_6RO(1NQQ(T&3ebqC9LP+etykMK^3(K)*l{cIBu zJ^Xe0{??gm5i1gpd_bJ(CtWMuj7Q1C{EGg3t^^Y~fw_+MeM(iT@c7Z!cjFMbw90Nw z%K8?AlNiI%919l(Spk7?&}MxPyG^FEInI5Te8e!(jF}XafUb7 zX2&_yO3L#ats1f^6sNf4{$A{NJLybdA1kVcH-$T%h#J!$>Wwg&lalQ1GQvDf`J!WM zSdz)ZpYL^t+nIa4gv}i<3PEmR#JXPx(;Dk2f_sdDCTYR@l!}V{rFittm|t45(?1%z zz~`*Ep`+~kTpZai$<*80fRQW9zYooedxsnpSgWX7qfyU5PIf)&MJRNlYcY?nJT#Zq zdJ|tQoMiQGpPX)rNz2p7<;7eiyQdp+^```f$KS@_XN@7anag)aKJ4K!i~c2rD{kM7 zpLFTAp8WA&k|WYqJ;e5lx{qhy5<+EGOKrPMGP^waUN^iw-uJo!*~Mr=W-s732_fZs z`l2#OrIL#+3(6~!#& z6O~2w#bRI4ZPQiAV4B?yXTYA&`Zw<~tys4D)ClhZY_YWJ?dw2i`YN1*V9MY@01bom zkR0V>K~t}7qFQF)*vkxugQh=Z?+#h)e>~i|z0qs~WGr=7r8qjV>TUgf_d(dmw`Rxl zi{h;Q9Ft3J9O(Vdpf5KOKSi`{K~=7oEqO-t`7Jqm_Gn%lA~g4#XDs3sRfVS`~|AF6*2NR9j2(xNAKP6=g zh{2jjH4sasw1tghs|B
aWM+g6rUldQW4vykk*V!69UmIT8 z#FNV1BEuTIc9H-ZdQ{6J(aN=h^~*4YN&{4%5wgTCT8{!-O&~0fC3WN6An8Ljd-;|( zFm>Wt4PwF*&8Fv~)~{!Em{#Fd zjWb_m>OOSsquN^)-F%HGKy?FAF$A^do$E)z2S;jqnUf}n(%U9uMjaHsJ}#5})q}md zx_iStu;&^-V<;UxGabynm62BT$E%DR;YwsGa=1!y1Gi=;CFLF5J8Iy4w0j6O?eVtb zd*_qUR?)G=n^QOQLo*A|6={Eq;Jkgu5t9e=Mm=?W2&ld=P0CryIjx1&5fB=xY}VeZ zZe)-Zso(4APXWfadZR5CK3cUr9Y=dNA4Y-pR@s|ZOnb6K91>c$8tOVnT1Sx!T=U1v zBGG7A|N7(VI_nZGUbv;7A2sFkICiV~?ROyxIDWY(`I?^1f@cp-zw=UooyUHoC;X84+rY5UB4q4 zpL*+waJ6d7(pndwTGNZk!z=gP_$yXcJNe!t4lRw=qZ2QE%H3Gu1oZ-zBpmaxEV2t>hj`C&AUq?x4rCPaxJo ztFTU9*Rl~=C}-)_v=&9F3R~qW+qL~CUV1*ob)Aal-dy7gtAoX{qpW9eZM%rOhrKY- z5%f^&dWpZIy~DUdy+M^p?h{cga?QRv@9CxOH`9N25;NFfN5&HSrOa?Bb7i-#rQ&qJ z`@xZBHO-uk$j+w!q_?o9uE#C*WHkJkA-)0fy46B?Rvy6))?4@Bc z*sWZg9bE@Ut`JF1Wb-1$RK$pC#p@#T>AN}f*k30LYui@^L!SDxDG5cNmi>dP{or7x zz2i^w6i73&GOg17HeNhjntVS10VZ*B!GSrFnwdLCOFc}kVsEG}5XXu(9uL$#i z#eP>tO*!?Du(qdkU#jHMzUpmt?Rp0H1E?=lqob;#_ezxQSRKCEXX9b<3;*6ct$w_y zdOXv^ocL5}2++5CkiVjPB|_|@0~c&w@rf}`0NLD9Mzn%HTqW|z?>yZ`lV1zr37yUM zn-}bgRA)W+JT4@hF^dQXJYNT7)jxM8U?Z+CAxoE3C(X(7C_edTd4+{Ck2dNLCmx+W#GNED2J?b#Z%I}n@gUefY|6R)K(B#k(o82DA4P|a z=X0SZzj72p`8-eCjyKhnjx4^ak7$hmC+Qu$U4MOO#ZiCi5@p*>t?Ji4%@Di`!Xr~! z#6^*4S2V<+x`BImpE1|!l=+>n%FYjnq%YnH zBow?=&MmkK6@AG03u}qozQ}qOUOPDYl}YT8TUIyY3Ep^ky6)^J?)dvd`aQ=Jaljez z%@);j(-7!JxP~U|buil4-OuAFk+3kL^w_rM>++LN0tQe4pj9P_c??+1fxD)*PU-z% znl>5cxCfkYGH*z3?coGlWxrWHDsgmI5IrIc!}6oE|EX-zXMlb$++1py}EtKeHhoE-Mjn!{IQP6{)ZPL1em!*%vofXEbXI9N{j}=}vV}!OE3gB?2P26MKym z*T_2}aS5wTOt&?zq_pz)s=*Kx=(_*Fza#qRKNoT?zZfV8dGcAGd-&p`Qp0R(JL_W%MX2|;f_ktuqHed7pvEz2vcqu1@4YZVjVfP*_3 z;lkj8mWgpOf?*u30<338o}^+5EWh~)bBi@X8iQS}cUhy+wi7x`rD7Md@ySaU6y$YQ zhVP@15;UaI1=0u>rTEvz(>u=$6@Cfo*AM?QPKW|tXZ5ECc-hnBTA8sP z(b|0F{nPJq`Tj`28#TV8oRMW?+?|Go`JL_o(kb@eE!Qfz)NK^|fA?t&a{lw6{qIc! zv;V(d>&SO81hEyN)5m*r)7ZA9YUX3A)B`P+pl97$); zanhBi~rcS>WJ87tVo1{o)&sQd47-DR+t1H4C&t zRP5avhzz_CMoQ=f@6%ML2IsvbT6)*~dmJXR-Ry3H&0Ipp@$+~k)``g#WrY>+)`rP7 z8&SM6y{OXCMDxpuTU$39%&#LRf7zw>!>~fO!GoK->k!dh%1rC#adr1^NGbAvX_JWJ z8#R``9=(Hefo_-4Eg>~=-2opP>-#o#9a7Lk6d)(dE*z**{%Sdb*!3OLx%r1`)uo<2 z&IWmChu^u^E}2@qO51cH_|L}QTvxGZr7*g&f~T^v9i9rNfDbI~fH*3EWou1$zHvaC z5}eh}aI6d=oFu3Trlz=hd6-M1I>9itlQ7msMGeDuE+TEFx$lb`q8aaj>yiDVY4BDy zu|0sX1Gpr))IYK-&aGW1?>8WD*N>~r?9dh?*nVhvzl}d)MI{X{Y_6JtLY?`$z=qr&Zx!0^iKjipR@lG4X8CqlG~ zx~`&%-<|?lUo`0qBsms@?l>qD56|v5E^aLYz{-H8QS4*;|8y+2F*>VgS;nn(PR*CY z#O5D|jO6!p4h!zjtf?Dd*!F{cXtw4T*Beo|Gimq6y^js32hpV;LB@Io6~@>llWrp3yoX+fwZ10AEHu|9dZ zrcaR|=eVn=q-M#Xqal;sT}tiUC=VjjDs(6YWM=WR`PG|C56^l#qzM+F{)y!1c#FjT zYtI!xQmiLbfbG3H{8SdF<^^qVRe=ve^Jh59OTE?%neu~4* zi&1zVXUVmUFC`(jZQo~-RdJ#zS%trieWfzG#pY&@txjVU&drUCT4nU6(&lrP7gGPH z%wL<&>lJ|ppGb+55?Vd1g=y1L2jcELg-!K7iId$X=8ao%tZa{e)4X*|v;v`cqn7n2 z9msrIxxS3Yzk>$uWS%|Y?%!YMXaoxe*;sAp^_#XG8=w33DLp;9eh3+4#+ggst<7Iu zoFw0WEbRXN)rJj)yLb3tUs&Uh8w;_!?XT9&b81#fvN=MEze6TAC2TV0C2a3(qMQa* z;JM;JM(|`7!5O+qASIvotI&QM* z_w10#e=W;tatW=p-}q{wP85x!N*qR_e0(zgSV4Q|M){o9JdD$p9n!`>;bqD8i?sec z7QbN*hkWfHOXdFBpLI+k5|}E4>}Apb@&#?fn|zui$}|0y1A7#%AifxIZPb8#Tpsc& z6{`!h3jdI`GZG@LQ}N#)QzD`9q|Sa^Y|SgIdeP zVwLzQy`D^HvrjPqD(%QjHGcf>$H|T`W8I(~q>p8ec*g!Ny7;~(JNFOs8I#Hy--L$R z+mGLM(kAt%DeZS?7mWphi}CFJw;L))@ehpV2RCv!(I>YkMKec~Uuc;lrO za!^h-H(6i;?z2QtR0f-j(RQ{YX13Vk$eXX^dN!=w+;P!Vl&&#Xv3N&SxmLyNatSLK zsy~>9HBJwZ{%|QaS*_>mk6Xp0+3}V;pt*Vu@1bA(({?HK*o`etch(QX~ z?=DDcW?=!iW8ym;1KYR9eTHwp)HP+s-Xaqtx&2ibCmfm8C?$0{px^!v)$AlU-Y%dG zW~}kX&xF{ZcH|I)5}4>QvmZtClJRUOr#{r1`gLdO8pkr|fa(4>)!j^@l7AC&4YP$k zd)wH&q01uwBNX$k3hR%{7Yie__X-BC1mPcwp(^uxYa7vJgnvIDmJR%o<859FHIijc zWE6<_8))#-_cF2OyxLm;@j zySsCN;K762#oaBqYxb@%;r24isVIs5Fr_Fi+%IhSZ&_vypcbW^TH z0;|eLDAZJ6g~&@lg-1f--c!Ee6II=?#_yFZH{&xD8yv-U-jRai7#ekK=a_p6#kxNf z-Ty8ufH_+>JMnq6$-hZ5HoaBvaeW9s7$IQmPehPAfu72tKAZ=KD#>9<9Xt)5yZtt| z6fT-^T_?UC5C3nel+*-+k^{OthOb|&bk8cZhiZ2jTBfJ{a?G&Sp{mf{on?2W3y@H$ zRC@7zWbutH%P?BPt-n``B4C1W{Q6orEWSp`q_hK~`7}8mWl7%vxy{hrF4xoBrae{V zBq_0+0{V&ok%FbM8AhOM;XD(~)-LZXr^mCrczV~VfQ&$vO!J!|!H|(P1$t*jbhs5OFWe^xBPfn#lBV)^ zcg+z89Sq}Il~b;MMyZ;_(KwL$1{}500Z4|#`R@gk1f->W)l3gZhJQqwJ*B9(#iN>@ z7D=o8L*Sy@+C?~8E1HPCS{EbPn^vuHAr#oXavW&cvQyw zs|s0q5d}cG!@BdcAI68YZ%0uBEC>e!2hTMQ0{-sM1nh5bsX|J0zWulmrwcc3bRgG= z47)U!!vEN=8HWT4zv!UO=n*|%^-ZGmo(n}t-PW&IHr`SWecf(??oV){@#E**`dzmet%#OY2*I zPxN-5$<`n+@Bbw@`f`SUKtl>I7*I1k;Ac+~Z=3xf`aJ%<6bbclQs2dqAdt4nFw-;r zpi(2Ujtz2|1D(r2jb|Bm9b@UP69#j)4wxKs5|BD6RUA;jgMv!apyjNrWx4yc#ShG8 zo0hPZ8pIbOO;D}i7=?S$3~^}`bbrhIb9@X6h0200t1(D)jL^E8uBo-d52^ZX>{mz2 zN`>}@1E-9gySl6)culhPg792q`%i#NKQtUO34$|sPSvxHH1ys^lPAph=0}IDg#!F; zgw}b;puv2ufCaZh5wbhG%SIdAn0u?^`E<(AY*uktsK%ji*!3DEeToo#k_}!4%6@r} zX8oq)w)zF%``^NbhLt@lbzzR|gY2TUCt2X(JBBEBG@f8bb`0>C>>V9>5Uw_VU+o@E zjf0cnHTlH!^E8H;%D@mlzUJ}=^xE;!9B5Hf2i~hr7$IzB~2JsSf2o^T=tJz8gc_Wz$wx?nZDc z-#3yLB45Wro--UmhyBOzb8EohYxyQoD_h(Zo>_L@lIHZpiz&?h6@JzXS?Jx8LG`ib4qn z>@=rYo<1L`+EA7rHFSByXo%Mp8xNU|rrk%gP&Rag_~2=IQN#|VsPAY;)b2mNNmbf` zUrzSQip(;T$}3VF%EfJR-b#hU?#&PnV4w>nLoF7^QFc&qVMcDJ3Y-%1nRBfxLX8v7-iLCIRlVsxBTl&`6 z;&go3PTBQ8{A<$d5FuQx8CVFY-JD6TGM@2KHxW&Y(;2O;V47IfLMVSjfgk7iti~N% zL1*7`Him{p#z1VGG@sB!T(i-2>k%ouHH)t>&6?wQVvf7-)qLRLfz)iP*LDwcEJ&J&b5DuSe*nu_R>pAK%ZMn1 z@0O%J+o^EUFqNGsu+8f8W0BlYWctq^xak~>r_>EUZ7Q@4M@jpO$|*0e79=JT3Q=W? zV+Ve5VKbZEa7n}d{m&)_oAT{`D$C-jJ~b8RD4_SWW%UU~?{VW}gelVDZHj~IX1&Sg zKXV2Rjeig*$O{rBV(I^}^?bg_>gUbipS#$QjZa9#sbWZ9{quZt+x4+Mdqh^<48VW9 zzY9K}MZLWpHwYz)rJenZh-)QAZ`m%N=yCUVq=Qun;XQYPpa?agh1gOr6Ts&e2A^cO zSu^P~wsi$wwpfzf=^&`AyO7tO$=yMiF;Y_Zr2@rwgs8O1wM#>Q@yN@Ejq|1R&Oe_D zrvK}&E8P9&v<$w_Z;AbJ{J^}a^754Kj^Q)7Rz+u@#=Dq{@1Q7^0RXZQ{eU+>i zx$2Dbhe}SeE;R*G7AccDLn?y-ZlJFjV;=46G!>OsWTLXea(#& z0Bv@m{Bx-o8uS~&_@)K_dg~$DwKzMfX2d>wLH&izBL-%E8GV{T8l>A|!uE5*4qUN* zPawf7a7ujq!L-;OBd~Wyz*yVoAzFN82KAlPn8FpzSFFIsK|c-ydel2L#7dMca4#0@ z?}9nC;BQx*Lqxcz^VD%={t{2Qxjtkk60905;lfVCC-Aoax7prazpJu9Tn%vVPuzjk zp5nM2@x0J$3oEbC#cg%r43Q2ZIJ5sOybIjOVmRE3o-?Oqhr| z4;no~*|RuH84{2(!Yiu;X`UI39(sZgea+_IaO5ZokkzQe-1i5q**JA47JzIL#?0j8 z!djE^T225KrkmxKCn1RgzPEmb(3mB#%HXot>w{XqW&9;G|c@vFkrpIg1SyfgcZ{L(QD zX1x>Q<6xqP>0XWXbL3x%G&>gtqkQ~PRyyzKd4<@f@6p2MCzy}@XtnZ-zA)e&N6YO< z;6}plGH>^3hD4kbD(#_=*uQf=G#5uksptLje5DV5od>rS_A(iA4Jx|u1SS)xiQdJi z5KlF4Of})PM3b(-%xRtmGT(2TwRZ~l1!KCpNZcGoa#-x?4+`2-3siPwF=lt3uyazh#-?%0z4QfgscOvb%JOM(>tG4Et`dKdFySSHxnJ!S)U8 zD!lOrigA>Kh6+`L5kw* zKTBm>;VH?);b(z-Du^6(B8H0nw#b%Inliti;dSE7e>%EQSE5!M15vm^k7VdHXZ7Du+TJ4XVHu8x0?|J)O9lH>;X6W>z$!uoBWA2R z*JvmvJx>n&ol%r5Y*fR6P>fE!8|decNJk4&tw)<30q;{^oQaK3yD{4_E)<@imfCdE zq*}XuG(!Jl|N1{B7gRHF6ZYt>dr6}nZ;^Q|^3g3?)uR#aRpK>y%5t`-wL`W>J~DCb z2Ft;^h#Tqk^Qad{@Au+ZmHI4J*?VI%_LvJLBmU6z#3E?O%jra_N*y%EnLw9SQ_i#d zLSY-7eO>05*Gt(CmZH?Tj``CsQS};Q`ebc}j{h70-uM(VA!JiD^2%>q%Hqj21Kca< zP^gEf+!wcgxWy_4wQ%N4KD{YC#L1^aX=2Pn0IPH@%|-2fic?knz5i+SYGy5 z`qyP_Yoyws@sbhp!6ZWpq*)YeNBL`W9U(KjH|$5n#);Vyo?!VsFC+ZN_gMnlUNCj| zrCh||g)LC+byXra0SCWX0*!AC?m-8xf`+u4)gkx`%GdA#G<)^a=F{$sqvlXu=*&F@ zw9X&*o_%=gYM06kw0s9JR4v@jrJt^bpMk2*U#{od$`3@7PZZF#d0s`Y8!m0fMjB5O zS0k@mER6geuMN+eR7fe9f(r*#-u&dnd*ch2FoXdPzd`5 z^3D4Gn^)~>^l!?CThDI$aHi&A(+S)`bmbp+Uac6#T{SJGQ!5!NVn;8~w zo)p0NNP~AtQd^(kTKP_;?n)y|&{!2;f9ud5i-sI>HRq#z^SUjFCsN6Opg#f%s;j-= zW&x)sk^AdE-_pd|!y=FaGFvt3YfkApV_%_UL~ZN=s?MN|er2bI&$#C3u4TCT=7cz9 zxV-hR7ThjD2EP#Qq+i&k_JU;#cE1Y59k8otNrS4do@~};{4B8&4=>9O-@5GQ{d8~4 zRX$#X@HR4YZ-GA1cC+=hC}WG;NgU&<7P**i4DT~5 zu4Uapct6vUh1AjGD7%}3XcmsjM5*`?+uD_hmPw8x*ZeQb`~ppeY8Je zPg2lvJYPc579ouLGg*P(V!GU9E_Mu?a3WW?)@6-Sk&)WQ!?}xiOy+wS!r)mb5`K7g zg`$j?V!xah7mN7X2mNaNAYo?F!w1_6^7>ZI<<{c_hwu$~4|z)w$*tpH%<6^Yvnm)> zhmbNDt6^$rybosON znq7Bxe&U<#a$~-;{I_?jmP{hLv5kv%FMkN7nmta#14SsuI*inpzI1cMT%bX@MX*F# znF_iyLT1}~pH&zy0QWh|Sy}W8iNN5mKPDDGsReR-Cqe?UI=4RUdhAPG7xIUHn)6*y zrxxtIP#ud$pe6+u|q4jaI+D+VvB_rG^BZ zv57>U4+np-t;W@ni7<2IS$9lTnBa*w73~*SE_SmrFF%BQ%y@IH<6cc103hS`Nw&_; zyuUSkm-SdyGQ&E%T!Mg#YSjzdFboWvXSG^e5pVkzPU> zu$AAhdO4QT!<6x^k(Se+V1I|_#6gO<>nU<7kQPc!8CALc6o0FDQt~-sb0DV8X1L+~ zOtiZYla=0S$PG&sN0y18JafXJr{y7TsYA?q6%u==+hVcURQ;eH3+JUw#)p zQZ_&(X!w%9(fmSoXMgo%P^;HKH1xQamq53J_(PlC?CS0;q%=4J*{s?W9{&CRtT7SM zfL?wPndC<2?Z{G}dlmptFEwTql->!DS<6{ex$j{hW?kQlm| z*8yIXO{EMXjfR554o+eJ>v3gkGMCB<|K5Eu?*@O! zWS_2lUKOJBigvN zzJ|GeF=Qx{XtM3$x=GVP6K!6BK!XApz1khi>kstq<6a)i`CpGE^N*ZBzyaQ5ha|Je z_!wY>yPzA!@KJ__4`5ml$s21%?@;tP9Dn@Iaacx$=5>#HFu@6dc5!bfKJt-LBt{MS ze`EwviCnz9dA-P5?yq_^{a9x&jYfp(mD_R7E)$ko@nW{YSo^Pp@TJA4r&m}c9XfjPrK8C8-@DZa)xB)!&((M?9 zpEP=?e)VworI+qs=>BkJAvC8S=fZGANdw1U&NE|(43sN}6LBlh>avN#h9NZuVg7^g zVvW$2W(kb}*|Jl)(kgQ4EWi(ezl;0r(k=*+w>X7{R=nPjwE2(3c0yF?yoFyiO`O#1 z8@qTsVDjM;3%4W|6cy3)ovslw8`UFWso(e!xz8T2mEu@laO4Vk08{Ew3x$5Hm`@~^ zOJW1wA^%voVUp&gE6T?A5A~38%uTAVnsbWwckpZM(1w56*0};PL^v57W_2}q8Lm~y zJ|m>cz+{UkGku$3Au3Xgj4>UthlgN_EFtnXPVs z9ZzIi)q)Iv!*o7GOHbUgSDa51F;Lu!fc4w zK1B|?nvf^%5a{j9S1q3))O;_OriC=a)e3`v`Z3GO?b(TVn`JQWj*3kVeIoBy=uVEE zBgder9hnbDl;n)1q{W|u3yXj8ZyB6mpDfri_>i};JC$tDcihT=Jgca|-@UlvJ!W0} z;$m=LpEx~Xm`r<79y2dbpSz;kpIVMh?I6uc{(MF`hS|deFP!P(_i0F3crE_UcMf(> zkGGSD6tEWbir%_;co?=1Gn?uy?Ksnes(!345!zfds8JengB1r2&6@NoU;WB|uCR$Hjk(5Lfv2A+TP?&0{K463e5c!|&IUwy z-PL0%j@6*LcTW28lo$G~a$p0Ei6vJ5vok3A)6MuyYx@VaGBY=z_ALOh*wU`)$}=`j zym2m72<2|>f+M%lC7LnO#>EB6(*h~?TF~kV=+{?}AB~42LIp;O5RByodpNRVjsjf6 zmH|v{6rnTZCd#n5fQ7omcKy=Oz5W$sPvR3TsJtEDP=Ti9K`^KKp3j;Ux|33Ig_UQ}cfOjK`uH z<|StbU3X6>-cgL6>queeQ3|W~GmWQ!`rqDvERWV#f+={d9Cdzl&M(+Z7qAd*vvD#V zn5Z2#r}gN4=TPn^lgScU{V%c>;~W_1Gz|cCAy8Q$RV>i**B_={cnS0&!I-{MLqWA4 z2GTxidKxoY6-#IhW+Z;(-;FfCeDtNTp#c6%GXm?>&8TTji5tbl>-NVW1{yt<+87&f zWCxe}AN5%dbrUtGHNSg1bdz}|nch&VmZq6A@IA7dVaHZu$6{1kpXV>j3iu|HRNlYL zC$S&sT(EKhZYBW?2}W~PlWNzY3lrlm$n*^=v1Tugx`S2u|0jyn2Cd_r2tqHOEn9Iy ze&E_ga%bmXGf}YS-v-sRzV(IJ{30S)vMDn>;riaROG94~ab6A<6B`CU|IH)REI|MN z?+0PH+ZYs&|ytbUP|SZFC)G3-&3YGhZAEMirT#=E$@uJ zW@*DyHk0%X!M({+Q`#I*hMzW?*8^YhWC zkAkw9he#Zw=|#mnM4D7+qP{w2rIm@Yo~_G=M>G3JJ)gKhYV4B{7IoMZC$Dnru1);R zYLllTs|3?!8F^lJ1=oOD_u$j$s*_nyI)_QQgIR;y(&(7d@b~b%C7_VZ4bzlu2Nt9D z=W*u|DQ<+32)M`XT$+8xaDnkxu=|G><$#c?Zt2pQ^Sss}|LG^OZ~KkNLRKrU_JX%k z!09)=bp;01acAPz-@hleez)8CgbLJ*{>;h!|^r)(26I!;eYn zAee^rsi&Pa&%!F5XzfMzAfh7lbjXFD#LH9paLB<8N6^^zWd4q=UeuRsM-2%=yvJIk zdtDmAj%7`!EsFb6lgiC4ul0$#U#Iic&Lx zMi5I{Tyr_A5$p!`n=k$%mzx>nFoQH<5aOto*R>fpR*#R2|AZAaxXWweITJLUWr#4e z+jb_^MEa`o2$@MAc30(RL-vX*%zYKIKGim_Si1wHIL_yFS~J(A>Dm0mSzJ!a$yIz1 z>Q{CPsl`e_K`BFulW=k!dTS|FC0@@wMKyX;wbMX+v$07nJ=A8VRaQ8K&G>R=ppRDJ z>@uBYuwDwiyh2LBi68!tVCCfcYrG6lH1>(z&%^0lWY@arJ6Uo0-u0`&%nN|^5s_)< z*#26tftV7YEP2vXZ;uELQuNyCmxS<_RO0&IgUJG94pUQhz-1f{r;$#)mz(}8Y8fS-8$uY2D|0b?_l2%8HMo6Q zq3c~J6_vHpBQ#$e$GU%v`i|t`8x@`3|A@%eOztFbNANW(y&}b|%QIYht=1qR*Qw35 zM4Yt}!-0o9YB(4HWKr9Kh2!|5TSUKSrowUXEL?s*9(J3dil=l0zQlaA^1t}y8L}Cv znlON@B`N=i25{AV?MR(pXeUrs^sXX|K8}T#Nwt!&D$ajVOnals@`Tbw6^T>wghPoU z0`TXQRQAO^f^Lx?qXxrG_(o_};C<3~o^GriJ_dKJ{}$eqe2748sCHNW`TqmoY&V5( zNt4&1U!;gd9V1I0)yV%v)QsLAe!}WgonEH(*H18R?8Q%TdtWZTKete@z=~5TF=dly z?MS&_hH(HWQ`i%Lia0VDSmyHa_2jH7uCcR9p1Hx!A+pR){|M)i zkexh|S5oVDfVDJwXiEdbt_>`@Tn=$Z993jyR1Y1teN@36Qi+9}i^I1>&>0tM?{3u4}(sy?vk0RbLlz(Rd~kiz8nLj z`iNM|=#5*m8u3jHe#)KVlwiD($r7LwIYHu@ScfB)q1l`QX@Q@NkYV7zX5XCdO<@3*GT&GkgmaM}PD6LoQ7d@Vpt=7ud| z?@bYH=>%7FL0#p)qn}#;8U5V;7y235g!niSwG2XFNY)T2QBm5U`~qK+dk145i%?}et*5&A4_pV9?Pi*S(vk$<(p~4PRLY!tS_x| zcam-!MVVI3H7AlHBD2R!Q{hhaU}B@&u2kE;?xMcYS6)!CE&%6QLB+qBubTA3r1l1v zN-ku5YwP&tf=g3?znng*qS$miG8w43g0#cdajzep!QY-YEHeoZp zDKN+MK;9IR#jWejz3_J{YF5EHMf(gD{V@!CWqm<^tA2o^f);_^Ij4|fWaca?3KOv{ zsvJoJ;0=!1r}7soV$o^_zRp)7_Kvr7UX-@wz{I@$9DY6_{u+a;neyvERh@)`_3J=h zkV-X(XUGB;YS(T;1ikY|YCX2Y7o7>Ert;Hb)RNyjb0yHztPh7kK6$3i2@+g?1l(#i)IE}YM~ zyYXqd^#sCSMt$a<>Pd;_l;BsEEWa4(Q$N zzN~3U#<@Q1$BQ&*Rie)k3~ey%G=`L@K{28}Dz=vz(tIIyTDuv#di%L8GEeGYZ8k_x z@{OWc^XlZWhsuMFblIWOtYE&)pOZ!nMd(=fbCc=5u9WXdAE5Af2zw`Z2> zBf6N00ftl8q=3m=gOdf-w=y7wRm$!0g&3MfR1r;H3*TOr(4RAHSQ6O#`PY_HH!bCZ zgsV0PQ&akmNsm}3kw$609N#z7EY}HB`&bX!Wl>4rNi5hXg+Qi;_7dGw>33M|9v=`S zu(QlN{7Q%gp~atMq(3$KtSCKi4l2rU8AHD+`kBpI#*Dt!$Bfk&hx;U)d+8D zfDv=@RNkL{1)qi&vZuf3Gk886!&XGtVcE8xw(AP)?$WMEA1qmQ^OLwN3{difMPe|{3Hc9TkP1@P)iA3>w3DTyH zIsHtjDx%w-chyMfPghl*Z!7{0g~UHMn--;Ba)k2gyQThrL#oAg%)SkS`R1aZQ9*qO z=_GF(Hsz@T&AbRJ>+=)U%F<@r>?0NMEKn`1B|?_)C!kevX{S0cDvE0;fiM+S%Q^}c@sy$C-#X6Lqx^X{y+FTc% z-|S3O?>0_%E;><*^wZ>(v>`P(P1cojN;RWeu)Y0>221rHS8c8cn7ExfJwFXBqeAa`b6*vIk z*52f8Bd0qiJS0lEZxBg=(bmq$9tfQ`TAs%S!K4$WRpim9vY_v-)xR1}rCQN3jwt#l zLXkggq06m!>f+`kJ^X-jjdh5av$8dxD#f{kot(TI*~{hmZ;;n{-UjzCqIyrX29BB2 z-ws&k?dB4^1j}CYPJ^j8%>(haQ_woszHm0D;!Ny0cI~s}NiW}FUi zyI~&~P|Noz>r@Ryj^B@tehpe)_aQwxBi}q~!fM6(M5h|yT%wi$L+OWB&Af~y_2^}$ zV>x>)v{uoE5NMi~i7B`82z5_-*I@ngI@Ri?2!3%>2u!BQtGF#dc0{GsB-S($3H}m? zh%#Wg&PzHuKK;$UErn8vcmIg$sG>8h&A#3A(tWTY3!>E4`n8=qlS_?(L&f{t8(@jw z<7UaivcKTmq4obpJ`A`0xS}5=cPN=s$i|vccG^jERjy<;io5kfXnO+Hm+vmyQcG0a#1uz|G( zO|y}1_F4h1IlBBY$G6dX?P|)i_3~)p%kh7DII>x!s>y_q!pZb1+x4WchcJy&2))3u zz1mPoWpEV&f&vN{H8oJk*H%yneqQ)i=UE$)h5=}(sW9xhW(eKg-PovlWjG}UR;nLL zW^oS+qt@gjCqyXXkoe69vMNS)$BXP|!>@Dy!EGsPYX1$kl}Nh_`J!Dc#Gh1h2$D%RA@vAL~*{m`4AIg@CX=TSQ|1#vWhRTS8MJ+^M22X4~K>Q&{= zoG+pD$~4(}$wEWH2QUH$ubn+5qgFF0*J4P9?6<{ac2o7O-MZDOY1$E00rwkjB{A5@ zo$k^nsaArzUmc=NGKV1&9bYpJ`abNg>+M?YOrpGHAnZCr6Xt;T+FKtN%py)76Z}x* zsv4CTH1y$DQfm{`(`+Eq2UM0@Pcx^*XwHoBK*>7@Jt-~?xMy;oWVvPiEa+W@1t=@g zn>h_P9}CmK8$0Z9YND8ggt zAeVd!mPonX)FDYF20Z4`3Sat|O3wP9F?kmf3g7eYfFc%>`2ZDW_xX>})}3*bjdJ?# z&q7%wFyf*}MD5}3#Ye@7!>;Q+7vN!jH;1#Y26VBzqA|?#!pN|t(nym_J+7lqB;zJt z805as7Z#x!{P%&H;B?c0qN$>oimjE#{{RM`a_#1c$so%j8L3;^?xbdxa~CHLs*!%v zJ(x@^lOwnO?GXR~w0+1G_}hF-JzQT);oEAUw=F(Ip4BeccnU|%F=rMch>YAz@|$tf za1<->x$|FL8kJ<-=1oT+vP1uxW34*JNq@dgO?>(0VBnjbT@0nSu~;}>s9l2qu}Wkx zK2zYSzEx2*D|9z^K45|SF|NK|)d>R0iQFjGB*2C%Kd+bAVR0{#AKK?}pl-$|QxM9! zm7s2PI38+6ANlNw?WFW7Q$`1Y(a6Z;KbfWQEX|K$>;tu})?M|Yc0uLY`Orb+bIN(3 zy{+XO&P4CVhd|eWNuPhKeRl2<9VA?68G(^%My(SCq=nv_rdzr)?zfl z(q}qFZQaVRO59)JW5tjeGT)??0o^evOf?I08;+m-hu!!2}wP77E z>hl*riE_$qRVOVSdMC?<&gl!zV2a*PeJcy0l3~~=L4#U(#~FxJ&GlQOS6-%D?ZzFb zs$)n<$*md*E$GvVK!CSYFt8hq*RllhCudd)KP#}h&pW89SGe*SheYjVLU zqpz0Wy+3qeSWCt+kF$dk=O3sU{i;(|uLW2|WEy$YsT}NAu|mtuhkJX|&J5b6M+S;M zY0!O5Pf6{|98&a7gcR(*Y?Ai+KPe-IOdV&C(6VL^)6SQA2fbJ{sJZ<-g zJd+huzRC+CS_(w~u@5US$-sSDSlhJq_de?8QGmQM@2@pqMl0Bc$FE!|y(x+D7$f{5 zScHV*(1No2*rT4ZTV;|J$&iVtvm8~@-B1hydfK|yMx_YF;fVw~Dz^*h8jj6{IWAw# zyMiSs!N+fc!p^)n%JX>u1MSya9QCv+eXDGw2%2j0kGRoZkJWkY-gqMP2^u{6byHFM z)6nvHq)-)jHTTZpVqSBpq_#C1W;c1OW^#F0$gtpMe1b}06|dI-p=?4Ey9&u%u8LEF zH|`!M;Rx)(8D3iI4&>WcZnbbyZ;>)u=iT2CuHtupQerQS8`4n;xQ`SFmnpM1O)Pp` z>&H4g5mu_#p4to6_FKByW1Vwwdn-~wlWb^}T&X=u2{f7#k=?Fi;n@E+q+3KD3-?0{q$tFZCBV5bO$S>Urw zC#SuP-zHoesw1=`nIpv zX-PSqZB%Es)w`2q?n`xWAOa_V3aW|pCuy~_!jgWWn5yA3@N3I2u2*8e!qn2oyq_;z zi|Sr`=q`oSPAYCr2V6X?{vpr1p2mlHj zAfxtJJ@|I{zTe_sh`prDSmYIpF;KR%rsF#?*BMIJB$uxLyh;56V+$Mp+>OELQ)t9J z)*u8KOOfOTtaUkiHC2kqt+bAB(0b^Lh%G1{gIgglQfl{aLb05Tz=3c4oT-fCO(fR~ zQzW3@XN+_RE^E+^>9D);ty&jJE-0bQ6gZeNX<83e`0)fE7c#(hpSPK|zAviyJzc1J zZ4W4lEHMCq33xg^rOQ!SuD#9v1OglB-JvERHJ1GpOJ{RMjcqwjsI#P>eq-iornn5P7?+ndvFym(BT4&&(P?h z>m&p734rhxRf&UleBv{^?@!t;oFwQkKMV!()BJ3KAP|L(wm0AGjy5O-P)V%6|ag06k|kOCfU7p<7MTa1SA zNOWvdUyys_hm@yjGzil3Ox`3vur7IKLL<&QDEvon23*u4zk1~po(#Dpy5H=~`9BA} zMZ3hswJxSp3(6P!_{nzq3nEY4m;^p*VNc+$MD{&&(Yy)_Vy-orMen(}j;WT> zxx`?zkRJ`*w11cbM)Ty_f7Aw`kURmmlJqQl{8JvwMI7RdTb)Niz-OCdN)>8mg;mjT zYYApj{vv(=Zp4&5XX=j(@#GB+e1>pEt`wGa~?)8$D|n=~T_kQ%&Z4WD)&`omhU+ zAL zfbOWlsk-dX3SPIUJ5@hcli{jH80MY*5CK-`?up$O(+YNKZ@G6eH2T#w7Bk_HSyF(y z+Ej-~HPDTn#bare$-okPOu;YY$k$Xo#T)Ilr4Wkn0!h>FhMp9WFW&$qXZjLw=A1ft zHUUU-0)rH-c3?i_?2@yN?DNbh?REtRrA}Tq@hnz`OLSpj5g{@KtN5a>uuJkl!rv*a zUmofscN>X$+{rKiPr++(>ijsZx~}*X)Sy?^nTTxgb+Do&%f*!d8T864D{nS*++ci0+_wy z)r10BsO{@ieJ$xsL;BD*PNeDY-(!mcn5FOp7S4VDJA9l#y`xQBaW)+Bq&qryk$L<1 zy$9s}o3O!e-|DmEbi+vSto-NsVpEa&HA9eTjL?4sXE$>kafLz#?xNAK5Z4S2(t^$Y zNXSPWF<@ZF?JnDVUha{fW)3uO60d0OE^Xbsz0sPMAoc2SE8z}D!Jxvm?v`3!A4dE9 zH)e`yvVTtd7%BN1PsH_S8JxfH3uu@80SgF6?iOy&7?TR5n(xniZ|#4Fd>WPhLdD(b z;Q2wmJ2EvF1`D}LPef_~QFmsCbDZe4B5CA(H|trv#7&y!DcQ_;6hRXGk+v#Z)}fD* zSmaDIJ;jfFqV4n#XbT-m%i4Rh0d0As-#7t|fX%PwMtbB3P+ugQw z=^t+Gx=rj0$=oPNG!@VGHNPWaK}ZQKWNE=yO*8ZFzlXSfF{6kYlYY*05@Q@oX!ZAC z!LU*YV9vxLaS?wPXEOrSglQB3>Pi(Io@8E}kp7(| z>!?$4!8B;XnT~2(2h92sqbF#pL!kvYnN+2j#Cbj+tU6xQQ9ujA-19Ml7jV!Zt7Iga z1`JlSqyix-KYTx`+;(NA26K}#8EpZL5kw{1ci>E=Ya*i@B5f<@!dy!k`>LMGU*2-dCZ}|02bcUIlc|Sk(hM= zwn-4oisze>U7?J!ZtB@_t*}BU>M4?Rzn5WF4N`e`8bf$#aWA|Os#W(!cYMY!$OS}v z=w4E=1ehjlyIpU}pj;5=2K5w@?^~`XHaZB8Je{_K1I+bMIWEc zY5hi4har_KTb_TXt*DqL1}UIzX}L64s{kS4dA$fm&vLU}qlga&bwx#`ejO;Rx>#r` z5t76(F9k!@ASY1CA#Lq_C+6?0L$occ_H78AjqUOHx`S<30?pDSjAzlow~pGhl6D}; zq5Q>!C>n!+J+$A5%oL@RT1#aPo3PU`{MA7lRy=>VJCoV&uw&(i8Jx?v$mRp7et?5+ z&sdlaQb(z(fkhHthq=$c=BBJ_e>?*~d1Vq`{b4Foi3jY(^jgr7qohwnBvOl9Eqov^-^oB?p45XyTmEiH5yB}zsWy>H~ z_badD{Dz9YRXn_RIUP>uad?1bfM?ETVNoNGT4R3CyNU-AMS}0GCMM-}-~s4vl=qOb ziDBdAkHUkH%62TZqrc%Uw;~l!fFY|Uy;-vIx7BcaygOO2coA|1jayV6`bm90Mam1d zpx``=!=(7oT+f8&T+)OtDvB!RiBXxxRRuuGq-YL&OpX_=4F)R1H7H`cmYII3-S>m) zIStEul36Gi*rIX$S?t+{fNiMW6)m9ssT?*QBK4Cgw!%%E#XW7?0jsobgk;-%BV4@! zDI{?Cf~0=)xfAp=EJZtTk|i3>iZO9vrGGw1&z3{hI+c*~#TcpL{NXYU?;c5=gqcl08;pz2a_8WclR9E_5o-1eUDdCf9v5 zB4$e1y6IMPR{F%*c(%tlJ_>Np1Ua+U_Re{V|C8G<{>|;TTV`n=2HIuousM=YCyD_* z2|tiVmptH-`hzWnh{aK;yUw#Hv-X+(k39b6WMq)yeC&uJsq}rTf|@oSqX@ z2M=4G2Pdx#7vWT<{GQ?CAPHybFN?4k0XWd*sZX!~u^Lce28n!I8;bJYM=J@!N!k22 zVp#(D9I3}_`*+zYE6Rt`rH^M`A_wYcUf4&#+N5tsOnPM2BkHf$F|L|ukksk5jL}F7 zV&WJN5XYE{IT`m^MHT#Ad_veSF9kPDJ&{cI!ZVw?*yWNrU&f7oGFpvZjtq?a77hv; z*VG?%$9A_jxf+F6&ab*O4u7S{%VFh$?eyL>VD}3CZiQ3dku5u8>;yHZw3Og!bMw?~ z%hNnaOM;#M$)2%J@2^x}LEvAhsOQRds#HU2*Z;~;?C+wFs(tBnjq0@?`u~zjg6GAN zj4OON(9d)XoPHO$m>UHbatLSUs6 zEAB6eW8(c^?vt6W#W*W}L^0ydme=k2fCSZFYZWjT7+|#!Oa2puL`7*~K>t_EHR(c# zaAYWwr6bM(+Enhg3E;8@(2-jAvLZ=LS|vjvGC+yH5dKo8=4-GS`ww53EG@tHO8gAp zctXrKRTL{X5(M4e78LSm-)_RpAk%x4k*%Sl{xA|q9~F0mBkgkr20-jT2r=7s{ihZ~ zzS~BAwamwzHer=sff6-6ng`t9n2YfByty)T9Z~$z3{PAqkU2EIFq^LUrGV_;nZEPj z)cC@|JI?(a?fY@EkE3KQwvlkEj-%F!b)&uovd z+p!aa{rl!vqJdJsj`VhuAiCc}wT7kCna74tUJjw*R85LAyB*$GV&cywTkN=VcYO*b zS5KRTnux=_=)>fvF!RXDFIn1+Vgk5FE`|B+;YoyvA?U7^(p4?5l@vC6?~;G^By7$# zx}i%#Ts&KKx7+6rdB-_9GM;$#5)30CQcvVdS@n2o)qiSO;>jZUFRB+0Cng$`Z=yCT z@m%pNC0PIpmgKg{dXE|*qhG->w15|r*6kLJ?p-=! zgOP61vTo3|)Op+0xM1thuO5|jp3`(s)S(l9SDpEz;uc3FRK&_653Z{dfgsbU<)1}y zNM|~tQr1@yz~1~e@>V1>Q1~0T*_w%c)Zw=bS#YKJzJwFAD-g8R$maYl9N?^uRc`}> z3NA4ItSFrXzC#3eUMPO-n&M2ILQ9+7 z*<818qTD{@wbiR@ZHTRIfxqbup>DJwo2aimK}7~Rz+t}s5Xy&v&hEc zyCTxh#DvezQyS$HLd#WS!^+{bLQk@0OywE~bHA0h;A`dmW^`8!h z&i@&k+ps+!b1#bDqCqDkKN!bNxW=wrwLgAppG9e=Ga2n)${zx z1SA3y>?;Vu2*fxOV(Zge-3>_M-z7jeIIA-v!U20|SUIOB{N!8!3KGekJk9iuNG ze{YOH*jQv_*4vTCr^NHq&WdL-y~Rp#9?!|M$iQ(;G;izu>0%BOoZh=<;YD$n`}_#< zN@|*nZ{~&;{wdV*wARva7U43xUvmFEm|dU>o_7w^BPSJ15%k(pz3Nzfy&CO!ynRs_ z5qq#4>eY$&9glQPW#3$AY~1R53KPRspZry1x)hBU7t!wdz^*q>`1dw)D&`x5#rE$# z9ksJoWkCavmY(B;DFxqN*Vrr*zm?&S;JK>0w2u_?xF%+gWw)M^O~u z2iTfrq;{FM@}Z)`2>vAQSn}hBM{AT=PANDRPyGPw-{*NhKJWSjY-|kMTIade zI?vU(Ch!!XyYziuj&u#qY`w1PETm&4)!S;3wQ=07BobV!%JnYqvvJIuWlLdu zY#*j%`DXr!@0qIh+M5dASAU@m6y*7%-qi;6zBYFBngu_K_Y#xu3gmKUwyNK7-eJBk z9m?h_FsLAslxHo(&$X(-n}G} zI}cM8M4pIr=TC1$@_MDR1?hYM>jnFj8uU5YEuhzBTz$Mjm5 z(|5n;P3^vX%%vHd?Ngkcsv9P%s%zd=v@0RC%$Ksb&T%5MAtC%BQ+^A0_E=V(5n0S%rk4IPMRqVLv(#~6dH0l3OOru2@0fFLJ@6bsD+dYLb6 zKXzur6k1Zk5CKbp9sce(8R-8oR#0=>t~;3rzcQ^mOC~h==iV{EnfKba0vsUpHi_=TbyHJYE(WW@+}f!JQ4X;hG#M>O^=zJ zUKWQ!c$PE}j*pkyoj1HF91{&!#IXDz~z|4m=!(ygjFW!IU*$om;RjH^yA z)}w2TzDjb0F5@6MV5h!NsVB%vi*#|XbNkkSs{mIfF)1pemjlJelbU&xdm5Q6tRDCO z?#N8q(9$atWRn^GGe>II8!oA^jckcEcI1{<7?ap(*I8wW{w44}sl;m3UYfXQJQcaW z-u>$(M5@m@D*A<9u>$kEK?wsnmA8%gqHBgWgkfUCC8QP>n}T0`g0xz59t{c``Hp24 zVB0ocdb>*vYWP!#Yj44`@Q2Xo_NF~pbCKXC^+w(f{nqNv2f4sB2s%Ph& zty5`p8p7xpdD%viB%xfC6G7MFmi{uqH`X_)#F*Y@3$=pTjXU~q9!|P;j>+7}$E>N{ z2CeX;`b;|aEDGv6=#4YMjjfkX_%rp#`baBHvyrYs0`LeF8$t_LhZR@5SI*1zuJV26 zI7{nXsT|URr6ua-IH+xFyIQn1=*})%jzNxX2vbwK?T2X3zJW}v>$k-`vfnb>jvI0L zvEvifi8kfBHI_^JR&m{N#j;Z?=+M|9e?$2XR-T1PXP{Qyv0|tycW!C&otA1pG~pBq!^F_NTMW z*y{A;YF=gF$ruyc#^+Vd8)lgJV=vk!zPevQ(Ham8`}v^qpLMwy8hIb{#pSBZZKyhp z;gIGa9iPf(p?8v1_X_|)9-c^7RPk5XuMhh5wuNQnU<}6X($F1)UW-sl;OexJ=2mlhLJ=Zu+XQ|Z# z)?NHr49Walwene5mJGvA21|$-yCFu0An8~f;95P{)&{>FS>E$%+W*c#yswzV7?J#^ z4jOj}7ys}aJbAR$G^u6P82hoXFP~ZcsC`m-$o^i-beG?d6u(7lFdP>_CD|TEjl2Hg zAB@3#9QSKn%0v0owiwwt@9VzK+aWSneY`O{+Q?|OCLLcTAhZ?8C)TL@Fy}@wIYU6; zmZfTs#q!yR@qc0ro+`+^--4`32djix#VN-h8{7{$^ioy3AhuuLeDwE=Qq1nhB`3Ad z8S=QZ*S(}gBaasfT7VGXU%M#Gikv*%_MD$QmUU#o`g^(XQgaC7?;KXDFk*fyvm+In z9#^g3CjX8wh-r%4`0-}_C)+Z>BGt4G3e!Mp-;Vismip{IWSljU0J$|3&aAYp05m1% zRh88lINx%YEO!{!U6a32EJ^1mpUXf0qy*?7+n0oZIHs2>%H87Tnkx~05kgzgl91zS zo1#74$URI_nf7vB!dxcnPZxO^9~UWwZ^;4+2OUnfToG<_Grs8y7OJdvZ|J72E(N4v z)2e#!A2=YkrD`$VY2$-f6tua%1Lx(GS4|q~c^sS+Pbr0+Q_4G1T3B<3hnTOOBn6+s zUyNKe=D^;!JP=@av~CoSY80_5fYc{S3a@;(lO{2pT~R&^HN%BiWNV{zgYTiJ^c%=k z80ktd2Y>rWH5ikE=ViY&xzY);vYHorv|3`>zcUSG zV~P>(d2VKnIkzJx+I&t;^0u3f8AbUVIfS>7_b`{sP|gKMsFMOsF6W5KE})afJ^ zIr{l1lYQNkN@ubTu9;hRK$OE@6f%1>YOl}`3%!T>GRnVJwJw#vN^qt@#?=H2LmSEw z64j@g-(PP1)de^^>wl=c#ShII&&&5j%FpkhhUnX>tM*0elbMIUqIY_L#-<3^#d20=50=4G;HeFWc?f7;^oHEimhJ z+9??bZY|`-%1m;(Yp>JX9RhGulDHLUqIQHX#u=49*p6A6j%?fL&V9~&j(<{ujGON~ zJbZF&>qF1H;YQsPss(!GSr%O-6127J%0I&k8P1q)y8ArYu{R30 zn69|>l|^}RD2q$KB)Lrnm9_1LtUt)8U#h9S+%~pF0PqnC=cVySr#Rw8A!ze#&_Po$ zqy`+6)0eg~!)uMwbP)1!w!#q8vQFRV7fm)&^Evxb(lhIcS2 z#)!fa?hXtdXAH4*yUB|i;7$`RIcL+T9Zd&?^2%5UU&mF(Wr{FY5hdOz?-rL3nQU&oWXCu@mX;>du&_NHe$UmNk1r;Hm$FBNolfN!a`OX3xOq8bxh-LcId&Od#jeZNW0G-2fXH;!(niPKt z=c0!ScTjQ7X=5r?m#OFyZci|qN|hRYgItV-XpwligQ=h^m<>BUFjTtPBih z?P)Pr(T(02+{`R)XGB>!v?P`J@X#uAnwGMa6}dE5{LfU;l6P9pQ!<44WMyBb)kOFS|M%r z<#L9G$5CN5dnV78W|EGaQAS?hJ;CEn3g%+P`VF*_RW%+{+zM096p|?wnqs+4m+HL| zT8zH4Wq)eR5Lsf?b(*uVhU51REfNWCGp&VLDWs`_-WBwXbVNq1L-zsSQhFI7O*kU9%m+W5C1wVxF42T z6M|(b19o{j<(Hft54B@qyhK{nuj(LLK^UqfahoM^suEUNgQAGD&-Ig?Ls_XI5Da5? zngT5r?v2QAS=GGI*6J+ihZ@<>s&F`*$A29+Xp9+lW0anKib?J{n+=hWZL$LXeo@3w zM18Jn8BrQ2eo7_AVnER|Y*vvwe6s;zREQ7Tj5W;9 zBypT?^p2AjC_fO)GA@bU(C9*DAz7&FX4ezxSQ{k1*(iEdr}J zhxv2<Ko1RryBfdjFyu$TZE2}IIS6Aol;ZEZ3nflWRQ zd*8|U=oU>%m&;4;IZHJ>C{Jg2@t~Cqk@(@=7MGnY@peD&RJi*G%Aiq70C$nDLG#Sz zrYY@`q?9v2rdUp3vNAWdqaVq6f8Rz!J(MB_zyrkYXbT7wWN3xPTK(J@sP2F3|90{> z0!Yh_A(lg3TKqpzKl=?7CLy|>epNXHrof(*()Gr13BKD(^V|g)5`Ud?cP!o=hzRU6 zH9eHe5~txt?mrKe|NX03LPA$L>kuU&Hl9_ZcCq6dvaW_S7if?59z6LOsqM`+d1#fDk^Heu97<(}>45E+9?Zk;7&mG8FzLIzV1Z~=a_yrHR*NBuk$D7Fm19El`hsA_3 zY8u)hHH-J;=kzm+q6I*u6iHb^AT*3pFWUeD;~r8Rkax?b3zQs&os#>v+ zvPHD1f+u=RET-}O`nFf`(tw`w0)!-o$NNOiF0ni0C{IUB3Bod$SPsN-G66X_>NxRYZ2Euq@nWv4dn7DGeJl=wQR@;u^EI zAzUbUgU{n$d3XpzGNno(aa`lP97;4gXO6!SdiYBeid@SL4 zZ@VhnYActvm}0Xuz64|cT+i@Tm9;h>`*L#7Y$agu$S1-%kBbRU>j#ZwJ$t^)B@n6% z!do0Y;`Xm9tX1=dwVR?{bMYx3z=@z6xpyIAds_=^irdYfTCCp(3b08U_B#C$bA7>v z<7}Q4`6_2xJkc?$mLL9NLP1aEg8pUq!N|n;lM=tHp)cs>iieaoA2E3g*3p#EeHYA$ zQHsf@&(1DTd?PNaK+Nx?j_z4{o_ZQUq%Gh&=KIz~Etzw^`LPKR{&4KB#AcAMv%GEW^OCOZ@* z&Y3kn?ZvhP)JLjEhg{xo-F4}*W{WUKC+R}m_ffwn~xFbTlqac3DhAk+u2f)7WR#k5uT*R@3LbB0A~rv z-o!Rz@-+~FT^d-8K=>bD6YmjuvD7f0t%S7x{a6;sklYnZ7)DI%mcJFc8t^OSdvZ6B zuD7<T37to z_rdy!;#uFHda&j0Roj%df1p3yDOuijh1&3t+{!Zge0+gdW%$w0n3>`5IJWN~E!!Ix ztK;l$M<;V{$eyxS7jKj`NiRcrQdy!iO(e~y3FoOI@B-^x&a6sxy{69ricZO@uY42S z6{Mk?tDfH~NG9BWN>ofMKrr+px0@hMm)%EJGXU?O z8|CxoZgD1HsL?ie>2(FpB*QvZRE4+KW=u1}$8aJ=JcDO1oyX7 zI{|f-+m~5Y43bF-qNncwS7~=O=e|Uo8JKe@tkJk$BrGW8EZ*SUdF0IZ;%->3A%x|h z*(wAcT`%6%dqFoSYp&|J4RB%*0oQT1t6bghZ6ThHW2>qXh1z4uxVuqCa4H!G?9WUn z8G`^%Bg#bVi3tBQ5md?Cr*HfHLlv%eG2XEQd8Yw1g3hPb z@`ARiM;79ox>{rf<>x7-YJ+hH<>pRDBMtFkAb)pVt)>E5t;E$DNWJ~{-|u8> zzpK;FJoRoqYrjcJnUrkCZY}P4FjV#D-L~C)C#rHrlF!bz&nh3E>xN0uvrs+Lp(4$O z!I9BDUn1SPG3%Q9nq`Eyz_hK0hxU!tEsV^Q+VK*Tr;WXskK#(e*6xHt!U(&kiS3i& zzoQ-v*>}vc->)l2H#8GBWZyy|$fb086TNVCgIMwE?XuTyeHpYvJK&&Ei?Mk^l;c*S zKK_J^_M~_IPZNdUpQ&R#-C{=Fsg+YtgbOob&9ez$&M=8@D$uxQhM)5$*g7`o4X*v}L&{iq1~_jFOKPJ)#=kxxtfW*q0Q zSKw1i=HR*;To58%AGmi0yNT&dYR&y&{oINTk%ey@p;|_-KPbojkbd&O*uz5@vtXmu z;}JUWjq%7!a`x~MZ7;9auaD4lR=XwtDje-;BRhp0xAi!Dgr!k8(%96O-|L#glfY?b z*2D4V1eMg9i;KJ=Bxl3g5p$mTt!{SDwXRVRM2R*4Zo-oN3rn2Yk`HFNllSvp()x@S zt4aa8SXD+y^hdQmbwl6L)v^5}@(_Ca?hn-wublaLYe|wgB>vVNn{C#4P@vGz+b|aZ z%V&gOoW86s;_&ZGNH`ZsNNvQ4HW#hiPat9-Z)9=o@BKuFqlApQk#uhq zmpNphrEfqbTTnaG_Up8|ab|}QWni^RhNm?ns-|8Hu01|SGhf%oL4S9Rhqa$HA z9Pu{sQ7_gnnQ3`{@%kfNzd=gmQ25?HU`-BFH1)!2iyJZS&~S5ydCV4Z=W%kcqY`wR zo3WIFC2Z|SkcNlePhCwK-*H5}f52)W(MTzKIdXvey;$ChvMP{81$X^oFcqN8&pbJn zsbn*dlIjcohsOoNt0phLmryl=<-BfQ8hG%xMbIxjYiB~c=7A?9VE!o>9t!3n`tNX7 zL<>oV)|T!*L?DCp$-OlMgZC&Kcy4t+6E|!cN1T*;ORO7+y+(bJUpG1^G4}GlrZg@M zT}8{U{q{Q2$`2_b%?fS$A#Jp*G&l1JWMvxE(sBV5wa7%KbwVQ=MLchpwweY${08zh z4TOf*zAx)N64f3Z?261u8R+(te_=4~YopTQ8|)tV2ZHse_6m)|*rqNGQ1zBAA9nw> z(UjAK?fGIbxSPHe5kp>ePYxDpuGJN5Fc?F{fqStKb0j!U8|H+wk9`DQwlCUV3@Wi8 z!u@6XD!sSx`grY&b55_ZQ2RLsP`Ph7?m8Z=Juv=_<+aM1pgMx(=9#7(Ak*ve1}GHFZl>N!LL z84BwAz}#JwL8h&LBZzN3&debH!Y(86GS*plFnOxCjAv~1MIzSOg~Jff_9oN&>>ZCF z`wp2F?_)|;jZYcem^SXDGS?JpoMj_3qr1$qK1bauZCZh*ze8ne7nR+*WtfZ&=S0qG z2OEN(6_KxPOoNJ>2NHG1E(^+C)>d9~DUl=C-OMOVe4 zyMX+)95uV8Nx;ZLy=VGdkiH4IY|tw_rXMA=`b1^U_Ey9lt_+B%$ze;UcvN*$k9cjzy8IC<2lLCWOduot|pSned*ti~d@9n1>E4I+8MC*Ud z&HAx4P&b7ts8_d$7KOJGS0t{Fr{{d-gv!8{Zr)$|mFAp{;R(piRf~Bstq(-(Y^;FEU6_b}STr(*z8Lw~Kt|T_rSuQ&w+Mi)hM8jO}uOz<}OL%6;q6shreHQT=LhjYn4R{%j3=79X!s z=cPQYQz8}XS_N-`EL&O?&XsAQ7=Y!xl7UIxNm5OyJcTqmXgSwPsw~Y^)6A{~ePQyo z+`qLX<5k8S{y+J2u?&};^!tx8w*w*Tu802-4pc*$38ZtVt+Lm-@k4&0 zAIWFA6P~FjYE0G2j59`fyC>0q_h{t{6lct5IR(F#^=fpTuIVr9pNbMvp`8zG8tLj< z_78#aINd(0zQZGNbl=bsIlg#!P#{_iK~f&sw^yilui+e6ifOy|8hiYMdB3#7j*UOO zbgdunh`E?tPm6R$VH!#%KlHrPeCn(jDSsjs&#d!mdiA-?zByZaVmYaBSoX@hDd@T& z8ri4%%Inrfnw=EP$Xra5r8xO#bCW@k+B=}6)_zszvg%G!v)o_7aUhn(@@ixQ4>#S! zQLYpuBfXjH_#R2rD{VY_#O;Z4%=z&zdfJvGK|5LW=;y7=bDVK`c}BTB2)t5J>usjH zKH~9ycIYO|@h>{7@+Kymtl<2oyDCKe%RC&$bbK`5I|5>HJo*WDQApXi>AZx~vf7|} zlSDW(Al7!Jd4I

^(dk*{it$#T)fU-16+o^LESJ7cscIOb{|&Id?&QS-2qxQlP2h zzY>3opYwuzerQuE7?jy@u@tAa1^v-kkw~olrg0R=>w>?YdRb2-nEwfP>(+M4sryNk z0CS$#>SJ%~=byL^1$3$JpM3nv-9&scJ8~T=m{C^tNIB-`RLi53)6+Go!YXS~|J{aA zAE0KuNWCFd8C_^e4|q1@MZu)6lVq4TwB}8%wb*>J-yD^s3Az(`r*$B%0gRZOvffeE z)JNjCSshYqs1HM2trhYD(d@>&3Uy6g*ix5NJFYYruFb!y9DK~~`b7i6sPtGHlC{35 zz9X+HGV<(pJLiQc)41PU2(Il_4evGA$2Y3T^T8!*VfSi%Hk=9#jLa;|0AziGG>A4P zv-4jbZ>_$D!~yH7!WOv%JotD*+s@NAP;wcnidDY-WL6itdfLnfoiCp!K*s*A`Lr}} zn=eu*oW3pnyNmq6a~o}>S^lSVwoiP=d8wW1syxj%ucG8TtZ8K=Afq=~b9ej8+=mO99}2m(k|#Hh zhOMi|eAnfCma5$?fG3P18oyb?&|Ve_?m|t(WuT{ipi11rMxkLAj+@6;wWF~(<-)n~ zh6h7-VKvAG-KG%y2bzhPU)XPw;Mmh-otIq6a2|gNYn=ONvzWYPGw>!ESE3=E>jfyeLo8EfhQ*mY z?kUfSJLoyCYl{iSXm(;KjZ|HZYc zw`PD`b=nV@3GbG7vhS9T&OcK_eY#V}kdy`DBT$h8}~yi&hoE|Eu#5U>b6Ddk$jy{dKso# zALV_i>_N{85(yXxM}F)vYQtp9xk7ZmedA=^Tf4~JJ!Z{S<(TdlL#m!gHr8Y0F6gJ0 z#nrKBiGs;5H(So{!T+}fxhToli@E$nc3wdEio${ z=vN`TpCCkk{N4f*Rrt^8AjkedU7sk$3G(~7n@n_h@)w+p8QG@qoQEEEbrV$n4A+34 zA)mLON^<5bf2zr3z(^KJ50Y_+>uQ^OI#?8mD{Q}f&h}q%+S+Q}jM3-I#DC}8pEb}u zDA*i+R;m5*&V#}M)PJ-XM+QIm1%m$yKfiRkFDK*9b)kO|Z^(H~K$P@%?<1r`x6W8# zk;n}SjxaayY3MQkx8c{Xk<$wc?3&~5KM>xOMeKpW&Aj6O+c<5c*oM{BZe%h5){Uz4 zJ@)QN1iA(>pc0oqM`yHm?=zW4k@jQnAThnJB>Z-7tKP2{qw*RoQr{TJFm&Z)Z%?e` zM=?gj1{a{dy7an(rehboyL{@{2Y(yH0*qT&*@D*JQnvn*J#S#{V~VxN(vDpkSWex^ zFyLqbk#RZMR*|YmigAT2ndaFUnE#YtKgkp`Mavr|jclCki{!;DlCyJdfLv*O3}97% z0y!y>BrR_}JfSF02;&Za|btsb{GJ9FZtICb6s=!T)80${+r!W>JGrn=U zx|CqC?uZ*SII%vs#rP^xh~|1?ZVPdZ((S&GEz;h--u!S!_m^Mo^O>4L!zrUXsvXF{>veU$rpR#Dua`qP=if@+XoZYnxdp=SGM%NB1P30jShEV{8y7}%&9sozsZ za=4e9*LC5&%N_w08)$d|l*D+Q&}#WT`2IW9?j|Ri){CKqsik_@I@>15?NJSDpyNl3 zsTDG0K*>|-8U=M~XT>-)bpuMD58I-bFbEG8axl$vC!p_pkMs9>n*;Hf zxVk&Sf2F&o4I9VsCtRZHg zB5pVY;c-KlltKDUPbb!1d4*62#o!JC4+CJUMmo`tF#kzg-ERPt%~w|IZ6BnVLRhSs zvfdO&K)flC;feW0Rn4HTAZPTg$IH1YH5%wsO)farUp=R=B{ z?APtv3wsjRjPqKny+#!?wq@9LcT4StH?~g$Ey2g2fLtT#qRPGOFs$WrUev+mitj%G zazKsEWX+D&j~&TnJ`}H(r>QtUZoe%%XZx}fRAn*oaX^ZL@FoaIBlG+R`V}2JO|taH zMaZ>>q^*C38x07St4Q3r2+X|9Q*ueIv-GiB^Od$^ z$?#7-YY&NwINyI4mqzx)YGC(1u=~x;87nH`$~Z-g_ejyubw0N4yTstSnVe;V)}V`7 zO3J8~ijhn8_*&?-4HAR)i+o@Uwdzhb2WWUda|`zv(P0tAho1(w^6+Hz;A0$l!!5W>Bfr~rYR6+R7 z`P!&eKYSk%ME~f@b~SuY)wlhEZdWwL(JzFo{@gnIDFN*RYv%lCC*sKy71VxjulpRO zpMpXjR9P!@98^Cp64d+cRz^2Bko2b!P6yTo@V9}y;urj>#bN;pz|PFPZh&WztWvn2 zQFt>4f>m*0Z5G^J6poJ1OVFk(9=Xc3UmbmSAZv*X|NVXCTdV5~ET#V_O|Oy@uS1J* z-S`s*@K|>yJ*yg17O-u#9@MuyVyJ&VSR(rh-hOphrVEVYjl!3ri?3v1;qd>W=>AnJ ze{!8+1sItBI{xp<#`{^K2+MT(J^m}V5-u9{fAL@GN1S6A_5dI=waP!qXy8QsRkJXx zFn`e7+Z&SmuPXqERrC0|O?dMNt`a&|N74QMg@25zz%NvOiC1L#H{<~IzkU6GL=lW4 zPDt?2$U~*e?4|`V+5Xu7W>H^#W_W6TKHHYifG+{b54hMP&gvnbZRacH+o#A#QcO&p z#ugUaf|uByZy7pPP;=`^UIr$TCPV(SA;^9T$rw;gIhrO$wns~^W*>rYxwW?jsLxo4X3ngU0 zV9I!(7glq+fE~i)z!s%}v3}MT1-?l70*!~kogwbuaz(lEi$>=}Tdl-=oVUl}m^X>I zN~3YNacr?y>DGw4tbN1!&Lz$p%SCYB`4%`U{J~d4_vC7@1CO@YuyqebWo7E2m4K}{ z`dD1`yvMXb$fJi+xQ=PAtNWak6!IG0HG%%l_%=DC1K~8c#QlQVftvRIY6X(^w?0^q z?f*$)w*vGBwY1OUFXn0feOPGs1sD9=5J>*7DO%a~55fBCBc=ZT`1YJ=Gc}tNghjNTsAJ-2`lt| zxZE>4f7=YJ5Zp7;?+VY&ZbU#I-$ z{!#+yIj8&%5!~>_AWmVQQ?kjIDr44iMe8WVjJWSjHkuU$^5D(68rA^x{n zq@67j6cm@y&evIO6x7=235t03)Icbst+p5ft5I^qusNuFIrerhqr6IryeFU%&IZ@JxG5)YaLaB;&!-X-ys3?zttycdiuIQDo$1@FH_gJxVVjLXrtQO&-3$}mX&Y$pSQ9VzPyWHHY^(7GDdpF;n z57r>e9xtPI#9cmlH7YgVKCW@L7b9TCx9TbiaN#MU@>$6sd%bDmVXrI*?7{JaBROL@ z5bLVV&+H+Vs6n$$lp|r9lDV9w&k@;q55`QF3Ug-Qv#he~@xGBBDo)xR9EYT!hkIEEge)eFDu7f_?D>pc%;GR>m}<3j4ATY{m%XQcaf1MiXVuX_T*rTRvfm3f_r6q_ zpgfyJ9iP2BSlwft>PZX%>8s-8yOIDHdyn z3)8?>*HbgE*rvt8gf9?q!s$d6OlD8+Zlvw}Z`IKC$c>X8q*y83fdMo?o+YP#wBL6s zQhA}-z~06E`#jWe25;NzQCv~%^S-$u)GeP5b%Q9im2YoDEj-j_IdRgELGWMC<=AZ4 z-FZzpiYjsQ5dmYWt-K%o)-!u zpNG`ek6dd#Rn4p`vj;A5C3Uno_54?L!BD{VNIZ4Bm z=m*G3OEt<~&WLFRwzrSCxf%VGgIwn8SMTWmEINydr>2+wX?c@`K4js<*{poNq1HtU z{aW`=PC>yv^Mks=9X9M22F52o)G83UTtUo?HUFU72{^SQZoZi_|})=^j1t>XS_2zWNB z8C&Zw)>3?xDDLI?9U0M*4^Z~ihv~Sw(|gSmNN7W20IFHDZH9~EXPSc#6}bW-yfAd1 zFk@8bo6kmC+^>x;={n7#cXgGk=XCq5r8_5twW!!0_u9S46~Zy^Sz?7A*O`>BZ=2Ug zXC#;0?hpTsD!t?Y+}vn1cj8{?+}X({P=9qm%hieReS|L{d!poS~3(h=~V^~{AX1I+y~I_i-x z($lFmAE~l2Z#UFfU$$IOeR*u<2`@HmYXFiSnSw&{<+qZG4dE1{!`v9l>DbNIyww_$ z@Xq^vMLgR*fp!ae#@_5Gg%cbhWP6zQ&=Pk*-njMh-PBQ9`o_;rR9E9MEmEvBA|XdM@=>J9eVO&tbC6O^~G4{@-D>gCb&WMC`mV z8&^fqSfy0;!PkdMnRc&{7@mqK z*Y=h=`oczfneAqwv$C&eJqfV6lM``LfbzV)gxjGr4f!eKQd#?y-B4v=LqI!vsn^-O z)*T&OavRikkqiHtHd`A`u#U`WvWx#Dlzl{Yaio+wk#PRe{r$p;IwT+vlkPlcfvpY&5hrI=-Bn2B`whgAy#=( zt8`ga?9TWLO3YE)Y}<)MjN+6>;9@*!9hDD#pGSo=nNKwdV{&=sny8pj z;eUF3TF0y)SmnjQCN)Ly!Ht>ak*UFHL|x!#lDA*qVgD?0leB3>)HfvtXdlj0xg1mc zc027?T>Kpl?ppGo5RB91@v6P)t0DdU6Zy~nt67lR$w9_mR`XmW{m&jVqY@ukaX1p z@2}alms`sEYD{lJl&sh^7q((Kq2UKovZP24A3A}FDG)c7=cMA1qDqrr+696*?H3xI4f z-#p>Zfprck&Gh`2-pI1fYw=pMoE71#xr7VXO>Pg_pV*LhAu0c z>OS($&^Z3$zn&%zq`O7)KhWiW6)A(BZpMgG5&N6)U8-3LW?pYJ{vus0u4eNhYIRFw z9oqrN-5fm(r)p|{ECvg~ z07-t!0}9U|9_C^Oxo@uXlyuQcDy=N_3#F%;wm74MddHwgX_;eh=#w z_HCH6b*c_4LMp>lYKNQpjW@_Ga1A|beb@Wya#ZPS)-)(ATZZq+{dST7 zvl>){?nof5&%g{uR!_(zkRodpm5W(*1tUUz4Gtc{x;=7`V&1lK2ubl8(&*A!hwdPk ze>fd-)L6F<89$@seOuhHYEv@gk=B>0`fYUcwh1w(Sk{l>zu?1lw-`zzjt!CO3+#B9 zmY{`BN)@|E>2 z%khZS=p{GngO2Op+#Wy{F$+WOcQg04)-#<%@Xw5b1HDFd9khzSaC$v69TceA-WF47 z;P9s2N8YBk@eUi%oi{%IbnjN^=m5Ri%8YENL;zZu&0*xVE2Z&RxD&%xQe;v2w>R2ns1z24_A8UIENOkHaBsgtd>>Gjk*XL?s40;*;Ayc}Bn=$jXMuzXb zW{Z`gM6H*;@(;xGD)gvb9KJp_IE}Li=<#taa=}m|Lv6BHk@M#g>DK_xcO^0(JF02- ze(zHT&AsBpjSEg)`!O4@@uB48Ld#4;_ZV%<-`uMUCv0_Nd%eBDgs<|D684}n_W0UdD*_vJrj&~ zrjtV|VqXhrp@eu1(28oh+E;D;{LCQ{5rVBVzVIURQ6E3BtO;8k(2N}Z%67MfEB=&& z?x1+suU`9_%`1#o*O2GHnXK&HqFV=Zjm^*ixDKBOHFe^&$zP*T4F?ReDAg2mS&!zO zJ_;zD{YaW97LBZ7d6{BAmLTcxPt%fL(JIORe9M)LZa(+6lQgC--9Zl+2*Ym`dEi2* zq(YGnkAdP0an3Y>w{l@`$?WeV=!x%7e9!MYJS}TVoZk^e*=1N2iAEz|(}bp_dleA` z+#jw)1y@?U0l)L_BJX7H+>3x3NPJgIsN%%#RK z`C(DOtH`Ljq{?Ca9xluCiF<-n*u34HLhI?4c@M6`EJ3@;ADL+~ zA^iisvpWw)#!z9F*vEU{tfIIag&3weN*dLz+@_V}G1>pL~k)Q|TNhBJO}g9Op=|&A9?o_*6%#8P=U>F+sW+xco3aA)%|`7(+-ibxqCI z(Q84vAP>r=)DA%yHy*0sGi{)`E#r0-0N{kn33>a>_7{DDVmzeyX)3x$lo_jjlH~ss zrjmAQNDBx0vX~c2u$Q%?VCp}4IR4J6jx4OD=kCvMFiaC+7G%tqHq5{7XZD%#eQLU_ zbaJb-tmOo^azV(`Q4o{6Mv*prYB%T6NGu;7?IZJG8X@=(R_E8lhTO0@P8}(uRtFSyg$SQROiZ9iqPv;U$)6SuxuJ#0 zFBwX2%&%hHeOa{bMwIchA8iOy87gW~iha+}*;j>OckGu`pdjh+;Frc1JltGdTqM_& zTzbtP5psBe*AiCuB00`|2-0;T%;O+a*;b|UC4TKeh3$^V1)u5c>#wg9r5R&@Y8alr z5>{?Y7(hrlsap17tUR(iJ8Oby24B^-GYS%Y{iw482HSo!U6})Gu7vp~$9YuCD74K6 z%`iguy|N+ee%MOVh%u5lE~1loQn_cjjWc_LQ<$NyI}Wn4%A2z#24ms7Ls5iD&l^2B zh!Zhz>Ww!JG>U3>A}ma$!u9k8OIb@`ioWExf?HpY$${!j%3Mi7yrd@tQ3(nj#H`n@lpcGq~KdEXz zNPkWI|0LOC2Of<^9?1KS8T!8s&A%7ZzcC9YwVxS0u$apDUk>r-@~85zUi>ZF|K%Z% zE@?z%OAC%qOg!P(+s9M(-9Y&?+z?>8K}y+5?07^BbHU|I|EQD=EvH65uNFq=K4PG< zg)37Xc^Mh1^+IJY2z}{l$9(4oO(b4l4gOduqMwpqTzq}smxX>tJm}a4yy?wPC&nTA zb&2-V)iDHL+|6toc!2rt@)x*kll_R{0;c_VNZY%q7l2v=+B~rrrO7ET@N!W~g>p@e zkyilZHiQ&?-oMUu1CJJ49QD{Uz7X?vhd*G3=TaRC&et3M?wDH!q|}O6t;&V8=x(u2 zy}j``z4oxKqinTD%^Cr((H~xJiybOF8pR_4GH`HMagpmni z-}K#u==LgmY6a6EasbsPK)TJjm+Tos{g*#u`XAF+M#nC8DhBB@$5z8-m_{&r;q-__Q-Amh(@gh=l zfR~nMGaQb@Iu=q{9`n8WJ?%k5M6)}<_*OksNnk`DGYXilkV_N6hTa_DlkqC3Ce>R& zf3f7GLYm!=1CPB}7QGCK`?jf+)|N~w?XW4yk_CSY4ZuYL(Wr@?tiIFuqtl~%mJ@o6 zsDXT2`}ks^85oe8PzwWDr`jCj5Wv@lY>uyNoW6mxnrW7hXX9~x|Cw9NU3=O-Lg{b{ zp7i_{l0N9(9t~-|)o<^0eq!rk+8GS#(n8u5i{i37+$5w-nHmHpAnY`1M^tpdJ^v{L z&v9x$wx8ZtlsXC?RW968OCV3r%UCSpiQYZ4FfK)nJd#qDoFi_6-f&U3L*atWo3V12 z!5rM-)Sg}lJvIachid!{?pToUqv<7hZv@hWSyuL56Z1utr;J8DIM1?szbg@rFMFmP%( z4C-z3Dv|ANLJPLfeE8NkRr{gPhG+RS_*)e8U`B03*392`|+4C8-Z(m zHd#@d%X+m%aYAMe$*fDTdeE`62^@DrsOsO&(yoNZXxYJt<~i#p6Rl>0@;56PUj4p!QT%Apv$1ED!PeIAoRCL`eu$9Mrt_l zJ^%nyUn*HKHZ`2m5A`^-f9ebUX}q)9K3-$&rgezjT(OL7?94gzk+FwComzon(S4De zX7W29M3t)j3WJTjeSev{a9i>vMZ~Vh*wCQf7QR;7N?1pd9eU!35}T5YEyY(}4aqc} z$nQkTOj7GsU%S8VT%0d#yjoJK;M3MW+0;C@HOb7%%33^R!$1sd!W5Q&?sy40$Hw0E z`;jq)GVLx@FEB)%LNx~CO9W>q%i9)pumZ0)G-Jc1XT|d|oyY1D)ARMkdM+aLca7aP zDvU|n$I4)H@sw&OkW*tehj(4IdY*p31S(0t>OJxJo-eAhm3occLe-x$R;{xpyUFow zk2-~#$~eEe_eO6Us`XND-37BAUpVoC^D}Mb8S-KB7`tGN7#x?P@HN(78$)WIMT5=O za-(}^8@tE71qt6K6vx+y;Dw|r>7Yh2rIS3uO)}0Oth5o*#(GT;xKr73!#ZDq)ehXn zU3n?wv}+#k^e^BUf`hiVyh#N(ZL-?@mOhKLH5`?NJoj@Jxc=1x?~r#UirQO!dZH<* zXx*@SsN>FI?<$uLvA9&MR@i$XaRks5qma@!y@Vutwgl#@qr>aZSSat5F0Yit$Nzy@ z9e*f%8Q1Gi!Yo#+g8>H_TK(O{H>+o(`#+W2-Fe6noh@d*FIsW?NU`mZPSO@qx^P<-SY`8L18H<2kf(p8)mk7Ta;{&vo z)oYbBX1Oj&qd|3FjB0_N4$F@EFB2ZEQX;wT^$g8`-_ZAg>|Ngiu1vzwaj>YUR2O)XU(TJoXE zyIU@--vGcL$(9OD-{CI7{J<>vfP*>w?TVQE^)*-VX88-Lb=Pm2uh?6}!LXoSk-!~| zd?*du?5K}_yJ6m9Z6#ywb8cws8241}DL!GHuC4r850Ti~N^!!-OV8%OcBk=Dzwz_Z zFv69=g#G8!ikiFEhyt);LoTUu3Kv{$B{m>ViTt2I zhHokSwQ_n9X0V3G<+@sGfz+@!|H$qihIz)bCra^Km%&)O?r5ZU^ThC5EyPgaiXu(4 z33M*6S~WbOt?xeeuH0~)!)ma&md{Lhfuiv@V9p#a@^rxLt!UXumnZr;Ic7k}lS0*r zc~QgnBS>zGjBk&%StvTn`jHU{lID<2J1l}LUItntzZbk<;HQUfCKj(c@uZuEhhI67 zqwU~x8fYini#y7s$eUB&Go+Q zD`WmUUB3{eytB%CW!`qg7Pc84F16K1RI4R`-87Oj$g^SH#zpD97=cKvizeZ^5^gt= z-q%*-t49C{`%&$5A(f00SJM)ZcZW3SVY-2U#GB04)H@6WU6rU8sS1fDeWta-%cNrD z3-ysH!G#|x{MJtnvK$=ZpW52Tl~EF{&yFUPc%no;X*N&j7~9#sVvKQb-1xMVp8Udw zbO70udk#@}!@mKN4!UXz@pJ2C$6CI8e4Fpal&;A;pVy7igcdk3mj@;w?msG`%XjjU ze*se4keb4F0{JQrRmCH!JUGzSi*tFQi|}z+o^0eFuPLl;M&?P87BoAY)uSu{x|L>< z^P}22N$I>Lj#uOd)^AqOMTIxtwQS2-U?;mM4db4JWiy?6e2BO#Ua2To^~Ra{{HoPe zDYXe%WlJ#dds4X}6?dh3NzTlL@bnkq!Q&?PJ+Db49$mYk&f1+Yvo>ZuXQ^oIB@raW zH)&r={(N2dw!Fj0`csVpF${`_C12QdW+AvB18aIkNnWeLm0(Q1?k1j#C;4*b*~Bt` z)W}9w4>;=;LAINbYIaVPH!)ae2WYXzjc8gWXjq>}Lken<~Y2-FkF7C7ERVthQ zl&;;biCv=EyatCZvqhK97Nkh8gOW4t$Zk)cE$Qf~gTn{rR)H!*SH;A-=CC8~GxVf` z{_)_%$i(!2?G0s($qZqRP_)!<88c)$^G~`-^|UXYepX_f5wy^92<~PY169$J>Ywvt z3Ga~@v}S-Vz)JapUhb6Wj-rHvV0E_2;!z8diqzI*I6y{0*22$nU4;urbbkYcTgS`2 z;ycvtInyQF`0?XsM_0!sjf0*+h`E5T@3t$O1h_Hmc%^}c2Wx3<>%=Xkm3euk8cN-o z{w2lc-nNhEAliKT`>A0ZWO;LY6s1Cu45B701(`a1Nj79aH}1&yO?w7-Zi00iI-{^> z0HNz!Qx0`IP1M~k{@XmK-=aA!%+cV;qr(KPJP{J6A0vV46o6&$wxvz2bO8IF9Cw`i z`F@74ya0zUxkt;N6zG&4iRjf$xoPg;;P9hGH#Ov5zxH;&=Kl|X#eZ*Q{xi}c#2mb} z)I|Rp&WUjkQxV$Iar<$_e`mA*+Q@?o=W$c#iT)!YW^$1Yr(jvKe>V0}N@v+4&L;!m z%B$Ra8ew7@NuisLRg%Q44%*7hw)`e{WoHhG*p(}+z!UpZLhp<%1*nF_AlCXrlx?QJ z<`|(>Z4SEllYx4v%IC<$G1{hs+^+q_?-<8ZQ14+u%T(nMu^{Sf4#uj=Wo5E`)M%d@ z(@8DIj+6pG?Yb(Q-ktgoATE9)6UYOwe*5|WAW}JUJ&2YVE1R@Ji;ItMCX_gJv{-u7 zn7mQ+H{IRYUSq^bg#LF_$yL&fm|NRLP@)ZAifrf{AIoAql58OeTThp;s(ib*(*3;j z>xXhd8>hLsXX4GQS>OD0uqP@&PEPLhQ3Ql$EZ%;eEx66+vrec^9pgr}@3)W7@b(9? zmfA4j9XfFVb{WD=ZG8=hR24K5U6e$y8UzLgPA}2dC~Ds|frr&>Ew?U1YtnU^l2Zp} ziS}&mqg>F3*P23zUQOrH3%$I&kjf#Ibm|;G?92i8x%%eV%WGYC0W;H`sC1Ij-qYi1 zHhCbf^+X0R>0UKgo)^2bwKWCo>wr;9e#jJD)g~X*b|tVav?)2O2^3M2k#TX0@l`!$ z!B}2u@Iugtk&llL7^tjl?dD)vYMEL zTQ}`}4)S%r#?Z-w7~WN%`C)U}B=O+VwH}(rDRaha1zHzTpJsY;jMh)#D=V6qHErS_KhZEcCB9Y4rdMgVT$WqH?CXRN5*SuSaYB)Y`#>@Y6@3hOE zXCSj;>geu3-#qem_dRgbA+SdU;1Cmj2Y=%zo>aOT(kxKy5TP)6Q)%+|g2K8Ti_FZ- g^s%gn!pqxmzz)+#t{(F}xSL7qww^jh)%Nkf0C0+Za{vGU diff --git a/mai/docs/path4.png b/mai/docs/path4.png deleted file mode 100644 index 4f65865e508744a75e444b5462ed1065aa29069c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 39117 zcmc$_2UL?=*Di|Nt!zcWLX#HVZbdpM(u<0UQU#|ksgb;e%x{;o!RH-VxMmhut zDugIV3%y1XDIq`%p#%cSeZ&5~bN_FgbH_RN+&k`d3`|zuMFx87}v3-FOhd%IP|IJy^-;&yRnCUO>80R_E#lTnA;z}c>a5B1NfHaC-eI!e$_uI zc;fcw%j0RM&y{@KVDHQ{tG#(+td)H1eDXGPQ*%1JudO&wY#}ge{=wcHKio6P*vE(F zw(5h&<1NC32dAgSQLXEStqfuUcC4$bi&&@PyEaL^ib5nozUAP?6c&#@wQ;z8`!-nu zm1Yw9Er)7Dc&NURnwpAzhem5QOnR4x>{FaU4gqaYh`rsr`O^Xx*ojVuWZv_VO<=ATd(hFKE$=FUlQRbwnV==-nU&ep0`CY zrVf4RRh{b0n%yXJ`J!N^*dEMaC7bEK*`L8E+>)B7dE`YlsHfn3yuFFM0U`Rz)y3!A zKvy2$^-=)LJ+3`GHimO%?~XC12rO%HJoCki7xnK#89(Q$_qV1{@;M6JH3v6R!6JcW2Wa$+Y2Dryl`Fk>jPW9ea)w{6e6yJ1kF!}yX@MUiDMrK)X z`tyx&0@LY+DCc_?-V1xV+pWdpD;hf3Wh8u$G-=vw8Raz94_o$>tAAyB#xhO?c)Bln zmWF@{I9oa?zy@*zI)cL7gF;=rFI3(FZo@TcSkki}Tj|t>&d5u4xkeQzu!L-Wc+?T3 z%IW!P0pFK~ncyjxLqQsP!g#n-$XqnB^9k)5aP321?5PX!D4)>^FPn$ zynV|$_c!2!3dQ+_2Ul{Q1f3t*HqAjwzX5vjbgfV+XFafc5UZ4P;_Q_I1}FCZ`676w zw?%~)Xf8c}pb0)PMCQC7sC^P;eFb>;@lt(1W8d}jTnw(ZUw4Z7dA6OkiK4x8MJ8=0 zg~D6cyJZVY#gIw|U)?N{c!Aq*-?NI?Ac2r0oa82KS0( z{p;JS0gO>BA7ZUi=nRu7yw>Q9!m0f-myW$fe6Jo?|s&G zJ2EGDvXn8S!Vh%v4{0gZHmp5M>pqMR&!)Fgu|MZJxNW{}ob|{)rP%uOrq>DJTccma zO4Qt5nmVN_fgK#g^jI{c>y%%kyvZTJEQnpv5;f>cQ`NAHsI}%rm+lm4>~sIdBbaY*W%jGd&!sFxJh8_^RyQmEH;b4c95I!SCp^a%TaNLS;TnEQ=wyX zcA4$df7y%TH5JiI@A1VFn|0X*t%-eMnTnO|^oZ5Q;+A) zKC@=}CzT*wXAtXW%$UDr<}8ajPk3xb>8EQc808g{Y;udW3+97#RaYBPYQoMD5J+=R zn!GGvkcgj|^3RX^q= zMh(Gf5f6hH*C8RSokbD_Sal|4h~S+*7{)TJ5ko<>V>YUMq|X)L*O_ZAD2668n z*ss&5<DG)5zY0S$ghvh0am0%RYLmegWYQUdtbWke?lU1fG8cEC$k%`T2Dqa!4U5 zt{)hlLhX9)AA&820Iu-En(r)OJgPnrFk5 ze+yCDYYMMT!Xc?wrqecqbRw8j1cf#S!iyC`R~@}iOIY8jZ1dGtyR07L6MsDFsz;w3 zW~-nzuhzZSz9ny-a7%NR+@$yO<6$ffBg5{(ZzY|*TGZ6Ku7Ls8QX_)BR1P5@p(z7A zkbsSw(0lDQTPIH*FMgS|b}Kk|;f;q-``8S%sfBCrN3xlao~$#$tA&dzWR)ylLTzWK zqvFox_|_@uz}BXTAS{`GS^yEYKG7egnj1olYg$87M)^1qoN#fnlvJ}-XzMnw*KK(W zY-4fE0d`0!GVPa}_IK?2M{JxWgq=bjDa#eCwy{~vmJ@-8rH_yW{?>$bZ=u+`C<%nV z9n(wN(^qaW4;~c*O^x}QER~KKG(Ub7u*1{~w(v5~%v#9lCtf(AWYZXbK4X1*q8$#&|shEkPeJaDIeb*|60NG6{2t_j` z();Z+?*J1FZI@=BKg#uxZh7~jx-)A%-6;R?g=m7n6+CF2y~y6n!w;_&ewbS zuUN~DSpSM03y7j;VaK-cAd2)Cm@t>+<-1d9tk|{I+4ZfWtV3c(#}7$=Ec`w@q>C9X zq-Xnk7QAi~aG5m1)klD#Py~MG-jEiEE%40ZtUDZSv~*pB;Wr|?y) zY^lguD{>Ip8qJjR(?<*8o0oj`x2Pj85&AOk%%;YhhgDa7WOU33_h2hwub;V<>Ad#m z3mOq8Z48+y9-UnC_l2gVrF)APkTO4eFNz5Q5fqT#-rK>a<=aMoi3mLYReGuD`?T)2 zV!|@8fyGmnT9IV6+=Y9GTFb?_kb10;Mz#AKXIq+{7-!CI&n}gwQ*A8IM>i|G2FoPz zB@UTtRWdRSi!GqTtrpUcHU2C*m;BknqlJnIuf8R-|JTgK>x)M5@XN4~IXmz0%xCty z9c_Uxjk>3@4C_^22&i;F!W0Mp$a?<7YQ`0zQN);>a3JiC5`AQ@t;pq!tyLuOr1>(cKu(2dobmu8HVl)BB6XNt3^>M%VPIK4v?~&lmlo zxAWC39_2<>dl>}NFKv5pTXX+H$}?YBVeP!@IP0hZ3=hMv<9QLY&mzJ>J6{aYj&QUo ze)DxyU9G&c_Hhy0PA_Fh39h0Aqh z{_zc5fHUi50BZW!{o{8^SKZ4RvJAhWlP8}Q>6J{`%p1cm7eAeuLR-elpip!mrC4j( zjS}6Jv2r$@ns(4y*S1)F);E+FUO~Pt|z{eha znPw9!YEooR3w-;rw|I=Y*X2|&0L;oi!RefPo}Sj zIVD}sF=S|>+V@{-T8Ui-%eU_jfERt|KTcyV)I6}rL4X6!SLrdwW;RD0ygY#+9$Voo z?k*+9YDZr``TA#B?hM%0w|%9qFX{Y|zNE?)(n!?ON}7Yev}E1})j$#~uQtq4oYB)u~W>bOSXjpHGwpzt7w#lp9__q0(g)1spKV9T zH6{`z$%iOU<*e#W->L4unoNI+7oNv=J_(DrRSrXUm%T|JKe4sK_{ohVAy&m)hI{O3m~syXLY0 zvuh%pXf!GP`x^9CTGU}_xuS;I&`DXOgjNG1^QJqD%}7CpJBJ-Lixez?ui%pswAmRm ze|GQ|!Xygc+WV6nS*sh{FvnTsFiIa*xD}b&aB;s+HAsVttB&mRQei6PFU`vQ;X@NI zwlC)x7AE&0QRIXzzuYNi9(yN`=wmkWx8>qvGIB-WS3HPXx=~#$Gfd|HJ}jh_`nDJ+ z31#VP1Izj9UvgfCYG+mNY_8>|7(L`Jlkl~{V+vgJwkpdF%nBc>dEpE2wg&T}CvuQ* zG@@J0Z4y*Itg4>6TU%DF_TB;Mg7?|B>Wm9j0ZaedR0CwLPSF|5h zwCzP0q83hrZaNpt7vQ|0tfbU_tLEgIEqw3G3kdc19nB^ZeLCztI+i}lS}=Sag`0;K zi22Wl;_tI0(%Gj>nCYw>S!8i=-)g&F_|^*1qtt`GVP~Vp(CiQV`H5Q?q?hI|zOhKq z0ieUqk7C_at-I+^zF{^a&g_=HzCH(%e4I2c*83jL(>8POlT5viT>AH-^HvTf7t>4q zT+9k%?loViDcIX1=N8P*gf8Y_=Np{^cJ(#uKN(-lizM5rBYPCvTgUd7Py#2WKrJc- zdOy{=qJq+HcB0_>6qoUP-4ruF$Dz8lT%&BmZ%FqpzyoBL@uC zeDER5weRRN-}>kUk@wE)fMKCXHGp~1+1#kD-e%5b0TxOk9$}hqxXFS}{5zw*|{@ z|B{7z65|xADG9*iUDV6Ty~0D|+JzS6;W-;`=ho_}F9B5+%++E2#{nY^Lo_3+PnM|l zvXH}E1Dy5lLZy_IJTHr9(QyT!vW|a>>Gug}1K-0Ie@Z8Jy8(|IPW)mwW%;Hjcw8721H=ltY3LysmOc3Jt-oHlG;01Mv2(;&IR{d`!ei6tEFjSaBxcpIkqF z4B7%OFD6x>dzKHZ%MyWUju37#iFF>bO%GrM|4={mv=N! z3}3>jDJy{2^K#+)46sHgT*OWnS-#Z$!Pb#rGuHfE*E9TFTPjohud46WV=hL0SVuv= z&XkiH%+^j`AY|y>Z@<*B0RT*gFmBF*4RDJ6Oy1)|QqFA0Rth^DY~1}U$W701?R&ld ztWH0+&5R{qwX?LP{Kw*LC%&QR4OdzAcVM__+FMV=wRU-*sXQP3N}W-a3~i9M-#r!G zbJji*u-ZeNsS~FJMOtS+SiQ5I*HV4!IH3rH+rNFbIR2thngCD3_6&?b{M)3oobOBB z;!(g0t%3%5Av@GXUh>lwlR%b0yT-nRdH$fv^YJy|ig>hLK-{~Lohtf#PkJNty0s`U z1g_n?{}25}b9_~PstdK&qGs=4Z)mw>%(>q~9VugN^{7a8-k(>5$0Z~5ewW-E*&m#gxevQ!4EU16 z-%`{JK~N+;7cvm%(FNb%Tl4fkdxkm@o)x`2d*ME;!wvB86aKJo@%&NbHBV1XjjEwUaQrARwzICGQ54}XR}y7raCahZ>k6>IRVMSC{Y(meEjXE z7Fwp<8bCGk?G}zvetQ&$*^^Yp_aihzeaop|CcQu0iX=fcxrQJT7}QeQi-P%KrT z=H$4)gx7fFSV_gw6!?We345bh4~s+S%JB@hPre7zs44@Sbk4eT;u4g`G_bGzxXlW| z#l|nWI{6l>Vp^#h5NCbMh#yn!iB|nAITro(5y)&boiyp;6rUHxt~IyZPhe1!b%kLn zRXks`@*pOA401XNre`n84mICpnUQE7)?MtGfV&R_tKz5N`0OKl`1G;vhRwOU%6!r= z3M|fkRY__MoIPV@HRHRnmWPmC+i@5ksdB*8PiV5PRg$y^`~OO!xjl547)e_O)ylhrukWe$O?m z54Y{=yWl#e&=KH0)@qU{2jvU?9_MjuABPdEH9yA&Pl0UBHUtYBNP zT5j}Gpzg{1U=azayb$+2Lb*^^_rikb%>EFqS~*pWmA&E|q5QtES_NPG8Qk%-{X#U{Dm2*O5D8zFVR-@^LA<2(9!2qb$5jcAu-j2aLR8#sxVi`IO1 z*fpKVX)HwGw-6Wfl&7~5>W954i4|3+px|ltvaaWDQ=S%b&SQzo-CAa>&f1R9)Dt{GdnQiXNAM)Rs(p0 zX+*-ay%7uB;-Hws%Ny(BD`>{oq@LREkxv{UL*E$Jix=J5Yt;{~MIJ5>rA9`i3CJ2< zh)n)vGucf06i8?HgZ!oYJb*~}@q0bJ6tY|_lV7%8#`rcENTMkiMz=InT}9Cs*h-n1 zEqouoRqGS4$#US()$rB+(uVsrF3KejuYxZmX%`4EnUM1%K70hDw(c zY0i)7!Oa@;lAnz7Q8j*zGr8(Lwc_xt7aTGDfa-q>ipJwFwg`MehN zbnx2Z;vKN1!*_)jgzoN=z0o*Yb&q6RmrKA5MLQHnrv0TjBf)DTg)1GpbKA`={u6X! z16TWDYGggYk0PO+>f-UKMI;jr_sXWvhrcJ!uuoa?_dE+m9rJtK>Pq#U-H5H!n$&ZV zt%XAFH=sIfOdP|^8M4lFG;b<0lUy_Ci(FDWg9{wodrPwo1g<00@6OG z8^O3Sp`>!hmoR#79Ii8va%2_nt9+idnv23_WR`_|@1Z7{Yl(~CBG-l)#Isk4e@iqV zo}0C*i2i#gsVJH*9WS#D!iT#&hU^TH5{mm{;ku;nD@^^dNcQlB_hrl5kj2k-v_eZg zkgTW}2~3-^jp(ajr29^=9VIba<(}T%pO-oUi9H^9LN>aiBE6Lq$?8o)p16>dniDmYp-DuRlpvRPf_#PDrZ;SMG$%ADojGB+Du(_h11yShhZ z!`$|^sux@Y*BZ^3=6j6r;?5>tEzsrOu|1@7++^_rc1|C?B(2>TUJG!njg3Gm&e*3$ z34=7&zuyomkyXgtS{p52iwvI*U4*Az^3x>q-SKd^*#QMKI%K@UhdlVqOm3m2F7$LvMC)jdg|CyD!8bw~Y zPLrT2@0_do)W`fl7wn>SsbL^~$2J2%p&|DL(}aTef9^n7JH=^tfW`aa_msn%acB5N zAN*zi6-ZG&mMcKxw_GZA=iVrn70b+ieJ6~~XEQDK7GI%E1*u8z#7p#ohu=N_C&;;c zgQV~4u^448Z=H6NrxI2XY95?uPa@SF};}GVCQ4Ny2G_0bA)`DU-u88$VG12pqWX0531?+ z%*;%~ygSBOs`8k~&G(-EYJN(bT##$YoOw>i<%bsOM`>}FRe~_=w;>Rlfg^2A`6G&R zcYEH3m=!p%P>Z8Uw_%~n7%*sk2lvh+FPSkqf;Outn zMBOI`&78@^;uGMzuoDd_nyZ{%fo*P}SMrLYRE3EQ__hsdZUQ z&LYZG!~Ou%jSgA9H0=U~+|_p4ZV3T6*->lCY!q{q)Wjco*&nl(c>}DO^BXYM>)ag; zGM&zp5vLivM9`OaGe^mPSW#HR!=_vDC!zKvhbp6omC^p z^g$mM`9^5$HTd~Vhof*Qi=frR29gqEV+yOPche=pKjVm6gdL{}fWlU}2yBsIHi_dq ztB`H80C=yeG-mCcFzNY)hWKvYyPcfb8TfSZOk+|2JIq85LyZoZ6TCR=@IEvFBN)J9 z&*EKQn$7}64YWBV{C5@szHbwQC&QVI@B}J+n+?s_vVZCA_|0L<(J`CXS=TeGL}8;9 zu2TwVa!~`B%Z;Gm@kfRCvic4HSEFh38o>7qnA_Ya-rJ^!1}VB9(hPoHu-#&It$BvE@ff9CT9~I%J9Q^97_ErPn2}X)-Dy;b)wrCQlMTWSk_1JkC z?kRD1%Gc^_IA)U<@)e?m)oLj3i_$OTf5HG5SbI5$FyJW6DH-XCY1q{20n(1yz%(H%=@7@{J+}5c6<= zq^7;}EGYb+Ao($%&!5CC8FG#_@65Ugj5Fqj#QUBDD6e`q%-GsnvF+k1j+>q<{+y}@ zuiD_;cZugB$IV|JL=cz8fzQ9RoI~nmivjE#+gg;vcZ6BSHm*ug0m9udA81|=I36IT zql?hpUBX`m+5=*K2ev@{+XX~zf=rBxH%>lOd20%Qi^8+5RDU%UAt#UDs!`%Z_K60E5X~Ekynk-PjUQciD1gZ~Q znX8TcY36pjzp4h1y9Vg}dLT2M%?B$@B*gyl;dv$SNoxQqZdr_n(6b2Q0bxT~zj_@_ zz4`9L)}=v?hJ7QtF}kv0QU=c%QR@cYNExt#f)VDC(%rw%)z#H1Y5gzH>&Kt9=ZyJd zSjye28HJQ^edaGG|JMxvA1sy33-ajbD3Mb$GSK#~dXN7$^N*na6oRNl`>Y8SbDRbF zIl0mCOwSJvCA3s~voo3YJs;0ml{c)a57$WL2?1Sr+It)PO)tpvM5!c5SbO?puZ}Lc zQPmyeUtUsLk=X5}hLuf{FC>3>bUeU}9l1QgdHBbN7Fu+M?fAGzZy`kFvSbqAX(vqU zuaX$iNrRW~)t;)0CaVQFM*w{g5%+dopz-7@8{v}|zs1q4tPD?|y&o-Q#Nn)tCQJ?? ze9C8ac6KwugP;$L@FzYHFJ22q!h{Tf%c|k^#aKu}=KJc`HA4l3aWR@(e{e9(&b`dJC9yR59k}<28*3Vjl^)B1z!s{ zXB&SP0%>XTp?}VKdQOfHs!YA$SB!u00+IC9V2wr2xZ-BtpyM^JxK%Fm80YVp$lOTD zu*gp14PO@dXz-101VOJK^!DL>HMn;+6lSSng4SJ-G#_%^Tr;mlC8XLt^tW%2 z6LN|Qbqt=s%RST;O&3@BqwIJBsc3S+b4?%~mn0?}{doi&l{PHjtQs||t=fg?dA1Zr zF)bX$VLuo0DlhDDlje6@T<1PRDLGk{+pGyo*R_CJzscB8bnrrqt9eJbt8uZPIAnP` z14ee6*eaMaqOC0t_eCHxbYM|l_Nw0|ua%YmO)mKPYX8LniqC4f<};cy>-X340&ci= z4N+8d53=7H2XtGXd`kJz=Q-soM#&QSbFmpApLNZfqfYw=662ILm@8R}im|xNOf9Q` zswAHNW~odTxdYf|OSz2WR&br}_4`p551NF{4IeK+dbGs~CgvZG%RsodIwwFEb zv-GmWJ|NdznO?j(Xa#c3skfr~$0nm%{Csbm4ZMra69VBN_^rfmX@f(%IFnp)%N~g^=(PynMuoCB$b_%h zzV1;riy`-MOK4?TNL&afUx9p)j7l)N#CP_iL3C1r89b~Ty*d%lUSePUdzEHzzxvYq znD@ydfgORJ3zN>cF*Bi<|gq>sC z+^0`(&Is(7s=GfCkZC`=s2C!bndx98fi#H^G?fsv0{efA6}g7~T}Gx0d(7jTVkIi; z(WrT~k5%z?-L=2fU0HigL2cB$GwhJ-iWg~i19`!tGlS#mrM7M1U#{y0wKRcwM*YV6 zql7k*PU74FRuZy(%}P<@>z9?YvVaYFf` zRfkiv%(A^hi$YHBpLZhs2xSZ`zkh;NZ#i+)2QJy0jEFy`lX4n4?dSMFz`C>E$oe)t ztUr0yRx;s;Wj~@tOw1L3-I}`gHTDAW@5maG+LxgsPR8h4l!lw|P>e4sQr<6_1q(y# zkp@1(?;5JMikfPGG}r){cuG)kMy__4vK+FG#oakn8ToVdB%w<#8zSSxLaRU&3H*{^=E~v2sUt+gd0g6>Z0q zw?Cn9Ed4UlGHE-$vTQqnHe?!SS!9Mh%vTb(ylk!v`LsW%^j!jGBFR{uaqB@P@pxp5 z=Jjqp3KQkiR(i3bDI2wG=$g1cc@`299Kr3AH^<4_KJ18&5te5zkTOsvNi?QSSG-_? z>)`w7>ObddY*pQT6LZ4!D_Fv%c7pyY{^JVI?l=l{6?ZBXs>2&ttH=UWt_3W z+a9N7M!4|e1d-d$X8K8weC3;QID6mdzt5OP`DNzY^ZK){Di)b(NXsw>|J;m|%8eb& zH-I%qh{#!2IiA&8t+QOCL`>AUVF_#I5>rzXhNy?ua*=5g%QPh06Ghk;Z*CEl$2bKeC>>FAw(Ke#;Z>OWrzn* z+{;5VPz~Tl(W6!;FaHlR$B^}}Qk>g8u(s|3$o(@~)Yd=%ucj9*)cQ`;czSsOg}w$k ztv1S6JcW{~}oyyJYzL z`N<=I3tVlM9H9U2gz!Ib!T+>jH620kt$d>nln(vBmUaV0WG##Xtpz|$)t`fo^y2Z}uik>!|K;(wHIkLn!+r{qQa33u}D>;Q)AUse<-f=_Y0jBBGzq{v2* zc@M&o(U!nMMK-v6e%8Bxz)8``cCct;Hz%JT@Q8NPvwPK+=qGkyc&n!QuPg1Yuz-Ix zW5=a0t?88={4S`tzP?^vz-8sUG9cTR0>8eFI_?UCd;Fsl3rFv}9RyaPQtJk=4{|MK z-6V7TW$D6y@ekGOU@&;^XAIq?>r-A*0>~?IVHD4O!kaUo6TbsR=hAKYvQTKfazNK7 z$bA#&0~_l*ZV(X=372f<^u5Rn%v9a5$dqc$U&%FWgbLCEwsGxzQhOC0aF2&RT zRY9Y`KleIFRr2%E8G7`Wb zo^8C#Cw=RQ5;AeUgv}O{M7-!KvTg9Sn}&{o2RZlwDIaIaUxDZr^uRfBJB#zf1WPCj zxOX`4DI>A2PPkL!6^E{wYTvne$WFxt(wDdku8-gS{$okr;9b4h2q5%wshZVa-Hz`k zjGQ!aUF-~q3bV_GY-r_Q;lW5GW}FO!uiu~6j=cMT01GzG+4fWk_TF<0pVNStSy~#S z*AN+@8~zl<=kj;D2Msx3=u^3WRCarbbY_+mZWHz`5$q!qepyHI)R_e*&`?=92~%6# z)oL&WyJRh!%8|D6A>mg=FMu|Cr?&411kr*zO^N2T& zXQR94Y5P;wm6ZDxYt^3C-6RmRHQdW}d@|>^s^I2m;74h1em!SsCwcIsyb5@{jsM z6pB!Ndtm(m`^_)wo_-QyQl=3GdF5_qK$5aG({0Q8S>`EyWI&)BK0AH71?LAD&jrN~ zDf-2>nE|;}vD^8^C$}qXBdo<+aEBm+9lWcCwG@}HJ03V-qY;E9ofS(iGEMTD*p{uO zDk=iX7$h*#wJrq%e$aT1Zzc?>?(Oct?U8(`Fto^x(uAr*944h?iPk)H+>Med2hy?d zC{Jt0$)Ba_q3d-SX-CN2g0e2O>U`2$9uQ*p(qCb35BBH_i->;uHmPG1}Za>(l zkE4H?ad8xC<&m|y4fgSgL3|O)iwstQZ>H0>Usx=?PX1t_*C`2J&BZRt2mJPGDQ8%(f{x5ZoXW zc;84)g2rEp5L`4)3T^lMEi~*QXCPc{p0acPagadC#Js*q9dAt?ws&Wu7IC+K`0@<#$wEFinbfCMcGb+jMFOvy`$>SuTE04u~W4 zm9WQ&B}9&$KFUZym0J^{ZEw{&K{8$wF`A5bTs69Y=&?c_f$m#0d z0R=tMo*pPj3AuWavyD6-jg2b}3lwtd$D9L_>$<37Fy&r2Nt0B24+$qf2`)ukB4ZN;9gbv1Nr z0Ly|B(4%!G7l^TEEQ=qPCV!ZEUz%n5dD)*Cwbxpx(Y2=fWWQkw$Zjtp)f&T9#x(1N zbIZ3KNvLAc7q;%)tm(c(A>te>cCcEC}f=EqvO>V5o1rHhBNeGGGQ;f7P|WpCGuIlp^0^=xt22r zDcXrAXI$1K__5L4!?#A_v5@Jd%9`sMx?MwQB& zmfpQtb`ur3Hxdc#M*2Q3?OsE~6!H-1X=dj5W+2S{MxgIEyCC}&dvGqy$}wawSGfQ! z<6yHjV_AgTAag$^pb%gwh1lH}$~j?ceGT+a0i7(Y$4#oBe$0w6sW_*`Ut&H~G8<&z zPOww_mc+D=@I$fVkr;fCNw+1NqnNJqjsvQP0Bvg!DVMM_mh^XLw)dMe}dIi zx-)PvMl|jKf*ra8EFw;bn1JR#ia;OWiHa4mf<4r@@U^d>U3{mx ze`KanI#+3%TD`ttN&0wL#uYmPz?9F?)fJ(}i8&DfM41O53Nq8y=B>^Z#Li@jNIQIM zMy^xQzD`L13svX-hBWRu+-F7$H><=a^b!39XhJLrZ#6ur;2CtZQ*jaCc-5fs=*c@$V1v>Gl6$TL1fost@2$1ZTtxw>+fI#*h87e+c=1 zG3Nj?yZ(FzAUvP0rP6EvuP~J6Wr5=W5A7)W{FBGIssK*rxAeBC=#n+csWRW?XeDrf z=R8N-6QzI-t~~@&WvtTvN^QT)JNNtd#^^(4dJ-IZ+P7u3!5sLv`$zkMiLT8+G=ZaK zoXoxMYEH8lkYR!;GQXw#7um65#d*ih($Z3U=SQ+($=L@ova+sOehqOsuvv|=@^T|f zx*a;mi>7uSSP?(Ed%M2ydh0Wb%W4urYfJWifa<|4w*2+mP`@_a7yxy0vy3ja;Ire8 z0=Iz!KDY!$j0i_kc;ZZ&SE}pi5-?%r)#tZ;9yM)V^-9=E;sH^1>AimA3}&EDT_y2zNJURS@6qR<9x92PKy`7o zYNi;&T#55!P`(>v_Y3~--sy)^KuzgWlmDn2Eqx0Ie2T&n+v=*p$ z^>3Pc0o1z!{uX~mt0jaSsQIH;p6V#&62jVWd*8te0`su=tHQ#tyNy!AhU zu_tcUE7PG4w@v05P2cBUcq-_gZ1RE9`I9PR9^e=}lJPHcF~6<;lVJY0yd1K1L@%+c zC=I{S=S}(?n0DK8sDME%&3|8pudOGGai<FdD1Yh0M&#?@nynRX?d6+uU>BPjSD{XSIt5}hWR-aVMV%<%w7Uq4;E7Ue2G;F&Ab$okY#Qi8SVy#JETh%8daiwQ>7s_|kK2&Ts3XCbM zA?-}9gdn;R9_O`kBYiYf{?NVph^Zdluh#ixYs@=1Qemezk5n?btE(V|@*}2QC7d=` z8wi%qeFavt*F5y0u$k)va>awvkXl}0jTbcG)FH+wi@2rs+ zOFHW3_7TXi^$5jKz{jJDq8k+2x?bu-qVgaBdM}zR|MmY|;}yYZ6?=Po)sEL>7f)}V z^TKc{teUWGje8xU|1GoL$g$29IAhor&UE<=yxxX6n&wAr68I%~FkmUX^pTK=MTtD$ z#L^du8oynJ!r<;#ze!zc_lv&TV9a@C+RHfrmCg{WfpTEd6lUW2>{j(VlBOZWYshQ& zDsLfqbzc3&VW=*9`%Omem2e52R>}@~D9X8JP&el}W)hOsw3OV^>3U{2%$0cU53O8h zMTveM<`Zp825VUXvUA?=26|sPiMZLkzhL!CUQP>-(V}U&G}rjIdf6Nd&7gO1x~dAc zYLZY(TgcdZ#~&O%^e%XT;^JxIwiR0ZXflar=(-qBf|_fw>(m)+uG zvw^tg&lrj zSDnf9E=^6q$N;$q^|DaxG81uJI_X&F}BjKPb`6LUTfW26yKO(z<7~%`Dz{Kz^@S=KID)s@ym^I4i?hE z!I4Fj{Ff5AKHLT|l~;@gA_Z!%`HP~nB$w$QrOMFBx(uMm=z$P=_X$T#?N?ve0E7ZkMn*~`91!>>!fZN6 z7RANFjoUSrTaJHRP0Z46_LIQw9M|Zu7y29NERe+8TS!yA0AmLkzj>WD5!LL+yjrL( zFSa#(t?a12{NFYc?m|UI7jtFVlcgy;*e2c7_ibKxV=N~6BWfNbHH>+;yXh12!;AFZ zvPAYH2Aj9=R4E+9+v`VtN7oard0Huide-3bqWn&q44>X`_S6;cKl;8#O(|nn1#t z5v!SB`v;RryM)%$NifBP=yYevbZ~=8nyR*_umm71qIC5Z^wOfY71s7pVIiS)4T(u- z`Z7Rt#okfKL^CaSxy@QCKbLYsMWi#1^#s&`q^% zqi`*8O6QLIvHHa(jo;lL{}oQG8Zlq`i9MxE`#bXe{pQ~#?M7Z7q2qtlFS}R?jXTtS z)b+k~yEv3t66`MCUZN~&nk!LDuo8SiD|f9uF?4}2+`K#ga-3vR*m!%V9418~Z0?G@ zX;TPQN{txBvG*=Tw`z~P&?-j~ij>|M!56$x56Y%`gZcM#gNO6x`G4#@#hqmZtSUW^yxw(t`KMfDapkd(yOeMr$6@U5?i1~Fosm(04E*Ab zevMzK&t5~q{y1tQsbOn;Vq<08x?rF6Lt)TjZ`Og7LS$cVh;!)k(Q~rSjB; zbU>?jt$N&BRFK!oX;IP1X=#Ag=d?fxep3iyaB7TisPOimL% zXvvN8;J0eE!FKdG9|M2SW`_$t;{eOf$_AFqP`EiVy9o9r}aHBWE$)575Uu+ZFuA&CMWq| z5*FN1psAjgy`(>N$AWLA<+peO<``|b9Smm3CbZqG_J*q#Y%<^NpP8SEJ-wX@ht6debVzt(_ zULdrxc#i=mu3c_@%h0)2CPPiYCJ5gSq<^JhEe+gAI(u%_%dc!_Cq-RrmB35&U(|U9 zuky$JAGLjVTvOTFwT{ zmb=KMq?kTTyDyP%QG&q|W?W24_Q!!q4*R0Sc~m^>H!`zxf?;!3^VS<-Jq8W3bQQ8h zTl#j*HH1^G$w9x(T&e0ZzI^QqGoj$#Pt4#9`Rb~`WyuSj#Lr9P)|{$d&jra;WxV*t zlZ!awo0o6yu(8=hT5Tvu&0{Wg-Mom=7K+qt^eK}`3|iu?hw@)N@KEUiQHd?>GCn1 zSb}$BYV!Ds%830-O0&+*hg^jBlNxW=G$72bnn&@tEl0@|ainaY+{n;ql$*hij3&>R zaBpQHJLhB^Jp)W%IQx;l<&K61hBR)>yZR8)l{rU?xg*@XW<<=*a$A(y!tt?6K2)8}r#oG?9bk=;(yd0)=M*d%=Vz5Ur8HBC)1S{UCI9 zndOPL>xghOY_y*5hK*(UM2ra_k(>nNmUgjmC1PbHV|!oMNnk4yS|w5|kC~%x7T+Z_ z$LcG@?_ZAMs4`*e^YHpfAN}Q>jEkkRM7+OQQ-UG$K7$JiBIh*|wMivHT+0KZ+4{Lp zaw3Mr0m~&h)Ae}f%VrU^j2A^({k$Krc>VyIu$zy7rJpZ+#=u|Sb(vw^()B`6>`R@a zs>CEy1FV!@-AuNCV@LA6!UXq=uK5mi&@#Qf&N<^I2Orl=waUvfPAYmOTQrVvOcd90 zKZpArDSGGaXL8f5Hkis-yZ6Oaw+XKOjSky`J+Do>>Uqdl?S0I$8vIBzImKPa%uK{) z6=@qx^SKcJSVed7M>ID-~ z+>o8VL>8Ko4&lcg<120(g0se45VYFVH)9T)}_~scdR~#M?fmTYtZV-m#k1 z(OJ1BQmZ_dmGVlVG}k-YUZte5h)=%LhQfH+NiSZ)lKF4}*D14;1u5&^lT#f7UWA9H zCXp+%$kMC?4@jHMSHwu!EwU#Xqs{nGBocaN`ivdo#YY-c73JV~sN3~vRnbCEg?RO> zOZDR9>uxG-+lW=6d(M1dU}YxJcSFR46(!`_{F8@$$)hr!4^vu-`COqyOiAz{c4xo%V>qw=zU`$F#!cw2|XZ3j{b+L?;h)>+>WJ>W^(kukQJdGj>d;;RfGJM-RDKu-)l&~?1) zODNzTzLVQAtfykL=e^?<(l0YqyNjjNJivuZRSGnakWdeqp5STsxaBfLi}76^YA;_2 z#GO!CTs};?cW*{2|BS#cPwdkr?^}Qab*`l{2U1B2%ys#&=4S1o6Sf8z71#8bxRc>! ztMM|nMrBR6_L?X#`50t>QBR0v*Z1nxgJ)YQ+N@Ft8=3^ouKwlb;5joR#z;p!yLq`=V>uM1Y6>$ z3Rh}HDVb^z`S_}k;uhSkZ3`gK0A1cIS%uX)bOUFAsnpahP_K5Lj-mGNvqE=9-v}VS zjZuK<>W(23yT66^`mM}65OM+P;} zf&OU6;7Z~VH?Qo(`2FZj0t1MoXsZiS_#(VdZ}xDG9gITUBO3UqWx^OlZIklENnv{b zqB|azpuC0a>E0?UCO)%j{>`&`_M!&IFV6VliHJ{?`Yz(NNXooq;YRwFf;HYjm+;!t zc})0BYkqKQks}l?uP^kg=DF^qzU0?&D)}kac5GYX~oH^m^#1G)js+iCe)6$4!lkOUM5z8CjSj zVX^SpBAmgZLMUP&8|E#V57R1(hrArEj65_td3r6!euqp`9AM%(a6CR`P6CC0vdd%+W`>X$&8K=4piw zbe8dsMbt{ID`B(pR^qBeATBvZ?~?HXk-FQmB1pNS%R~CAAGgiHBy{&$Q#o-AaG4&u zc}NMFaNuX69=Bp>DBr<&@42xcyW0zJX(3t3vWABqethSf!jtYTNJe3boxV=M(4+=$ z6}A!!-!upt(k@5nQwG`hqWP_XNaxPr%E5F%g`$Y6D0?jX1fMcb95yx9w|9p!k8dfM zyG+Vk7)fo9+-~G1bWV_$i{*t(*g_+Q6-+W}JsYGJ#LTjfoJ@cQ3K(pY2lsYMQPYGn z^BhNvXXUdMU3}h5D5Y=A=YCaB?>e*uD<(Yr@Pbmxv=b!vH7;L8=(MBCJ=u~&uds=@ zVrO!tasj+Y^f|eB@MiI?Wwdh1gQ~w!tdu^iu-f8E+YXt#F>gz1NTraXoV}i<3TC7V!D<@L&?dIpJ z3$LextQaiP%rjNk{F0GpBb>HBy$!EH?W>?MDkPardZ^qB&=;^AvGjH`@gsRVIcv5X z-SwYo61tCck1mHl%89S#P{|KaoEK@I@1Bucy=S~^LM)syF0V2bw@h99WrXUTe<(uI ztsakfS{0hmTw0|V+BH!3}bY8DV0GNnPPpfr%jPCD|)SjDQ^GEm>gY zs#*JW(JuM`cUj{?Dpr-4LnjywL@Y&vdJ^S$R9oA&hAjqe6A|9ZYHFw<-)wR!;|t-H zgnnd(SLMaNh^A#{E2%L5bj7H9$#5VCb61nP<|PkBTq~RTwcG6$A*$dI>9t&< zNrfC#1y!G!fBUl^0Y%xY@b<8Ib9G8`q@`!!Wi8u)Bzy03b=3i>8qZD73g>Mz-)e(k z4+Gxb!RHB`GaM!At{YC>;(@{<)0qaT2=_gA`5bZ{ng#a0E>uw$Mb*WMNpEerE2F#f zPSAGn)t<%p+(%4`w11 zM+)W6uQ4X4Stu6~`(JRk4giFca0E3_FFa9mF2dgnJ`?y=+ztKe(0jJG-!W@mU^&1N zx#=x7#|%`EsVb<5kb~hd9M%6|+0ks3HjJo7owLbetC0j*#F9K|>jJ`fi3FEl<`jRA zX9koOm5&l858R;>zuHmEeNXE1%JFbjn}>1T#uo>u02RSIpatnaV@l0a32EIo+*Vdk z|*o&8UP5lL1%;7*G5NZ%=mmHrj1C z*Dov$%DV@5?ORMjH)-HO0pQ4Q_LI#8+qyGaij1k4?r4<06d;xg%(L z^XLz>za9C(kspjdo={6M->;9^ttQ)&(+aof)wKslf|z*C4|ldIZsZq~CUz<~%_?;Dh1e5k zyO^IV)AwDX^RE82XP6?@o>LwZ@^Ii0rk#um1MG=M1Q&~|EeDN-`RCcrqab9IrOmpyFKgq1G$f*dd+k7c$vcA4Rx#LSjn`D zfR|20!m6sUZsB=cb(2dM*uq# zk)4w2dvW2}oG))53=so zba%)x->IyB9lrml4$RVxr75E$PIpHF>6SeQfNRXWJ>&_4$Me!$i>-I0m~vdwA~x{|CgIb1#@@z?Prx~~R*QxiFi!X=MM}J#;c}($SMxp1FnOm=!yDyfA=@xvWEgS6%ZN9&SF^;JRw4SWVhG@Wx_?!{PKJzMK>`D2&t7 z{YA^999=yoOzlBqx`A$YPa8X2H9tH_8eRVucK({R^~MD~KqruvaF9b7|4<$Ag%6b$ z0|NX04D1J!?rU(L#IFASX4EyJZ`w%O5}l*h)%H7%9(Oui(qibLjMH>pk+o(hmxW7M zRL8d>!s`N5vScKLjEgQ_yUjesOuviXs2F`o2)r4l=wV+yk(3|4#$5bm!1@IzJMp|` zcvfdRwxmN0GmkMWT+QVOxMRQ_ZT)q%t=(-g_j}=?8R|?}&8&94E~Mz?dD8Q1U3*&> z{BIVL+wb}ol#53@f;6$8UlzlyuT;8YE7wSk3*j=7Y{-Dx%zTVoi^ZIwM45#-xoLGS zCCE-@t+M>y=rfn)r?WDqATr!SsNxk)PD#DA<0B1P5UR%#^|K>S7*tg0yhEjWLMm)| z(8q1cIvQ)8W@%r?=hlA3=#H72hN-s+Od?NsGcR<1Fc15oXsP;`1>UgeX-dT7L!zzY zMx1nJ-k?+BhOK6JMQ!u=RD4Es5;Hz&sb!V2VG)9>V#j@KEQSj=kNeSKikt9U8C!>@ z4d*(-+Ku@2$1&P^tSj)C#Jp{#g0S@Tm&8id^SGn8!c5qZno zYJ+|6knpM5@F!ZSf+;ChrZZBPOf;_ByOSTgEi0(E%S=_46FsV|Kh)5!TsotXpm0tg zXExMBq+0k;^>l&rJlq2|>e4+O6`d>m*!+3(N}Zi4bmX^~jYnBpIxnMorD|M0l*mla z;#Rv#qwDL19vli!}1} zh_6hI^5PR#aKYT36_3yNK^1kF<|_Fr`2mh4hYmn^@ z_=tsT3|x1{SZ}hDrBV={Gny>)4IRP5T6Hh0V$d6US?+oaQD4t&m2}lQ*ZZDc$*aV@WyT@zCY@t1byl}BT4%UzF%5B4piHdi#20f#)pR()HDGZsLHp*A>|?y;77 zg2{;q+r6vBof-JWj{EQTN)}E}A?Qeh)%(0`p;pP$g#i;Mo|V#7g84SEY3kK4+(yztj3OV0q9rxcqf3miQAehhP`&|$+3X$l zpR)1}4&)8j8(1twwO1O$Dah>ASwyXgJd~MVgHHSssaPb*0BDx*oQu_sh8;)iM- zZ3XfshAf_1Y%VHOgRisW4O*+u0CQfEmgt^^R@-Khj3&9sd$TYa-$>bXkY9aiRJidh z+iT#NFlDKK-kh$D+b|K5@ttH_iph->G{9*<$*(r#3i9&8fj+d?W=9$qCZ@nq%G7Bj zmT%7+_SsRnZjsG%1Z3BHeh&KgIo~@Yz;xfJYtxAz|=m;Z*7#+{d! zmv&LC99TB|5aQ6eGr(;im`OBf3OLc}ACP=>yD~8exjyAh%F3_;Y^!iO$%=nX&mXv9 z3lF=*{xO+~#DN3blKVS7=r2iWS$TQFLGJXC`*SiQW9Q}G2FuF14pq_X^i16On0}cNe0r&ixOGJ9nb^5W%^QUnH6N7DnarD5;%GPw#m^C$iC{_p-2oi}i%7yA_a>oTQCY|~$UMQx`sz@%O>5ZUaSAE-C9KYl_U4Tru; z2jAOMBT)7lNt{Eo(1qgKUOp$TkO8DWd z{IG@wjk;ATg#0m%*ghUL*Y;I7bSK|5AmXs)0W0AFp~|NZ3P#~aizC7nj+9^Eaj|2| zM4$SeM~2FVA~{u~hglIrkwG{+f6rT{?swI7^JJjuEq)T5ao8#0$2*&|;5%O*CaMvh zoxQ8Zus@c*tIK&G#8F`qmXmojzf26fFhn5D9sn^2+|^YN9)B6}`eY+Z9b4&zv6luqhUxTtJ*c?3bjf)WAQm7wu-8|gV8C9H z?AEF&ds#w-APJA%7E;xd+x+iV_yFc!n<$+t^o%25yu-Uy$&71(zvtT04NXI%HbtbC zgw5CL)XH+QQfo+Ye!1W*r?}L4^#sn&^zhb?iy?-X)m#}bR4cBT`zI*ZZTj>x`4T*6 z%#~BqvrS1*f%C|GMMaTPgFx5nFo$^l(Z?D&Tx*YkP-7{)y~N2# zsG2rkK2wy|-Zp2~q~Lv%ZJr&kuH+D6WAFQ3*M9;!Vz1s^jgli}em91U@UU$Sq07PP zBf*Ce49=GCYR5zVYx{=(j>Ld@>6NgVZ_8q$+jz%1fPY1B))&jjnIfpMMw66t`?~-H zU6~~EB-Jr{Akr|MM8M<5C|kE_q>K#wtYl<6^+~$JuzdwTcAF*{hsc?)PFqu?j!;J* zrowXEZ)$c|p=#vK*S@U~D;q$f$rgBNYXiHy0MB#zU|BfvS}FA9)&$n@{$iU!@}mF3 zJNL1MKKqOWcZ&&NUS;CdVqzXgpXK_*J}zDs2%cK0HwfJ9j4Aa~*UeXu$jV-MC9~XA zm10TR4r2(E%Q3U#`6Ol*yWGG}+z7NdDrxJ=g}2yxYF_6_mzwv96Z1iWUmDnmftE~s zsX5o*CPtP4mw0giC{2j`ZgsW}DdU)8;>Q8b)GQA@(%3{jAiSqIIA`3Q&VJfjU94D1 zg5?&Mk%k!E=-IASa0jKO=mFA@)RpVZoqE0{Y+Z9pQ+~B!%q{Gc!kd$-;ND`Ca7ViV zPV$q;98#sXaYuQKye#||Dd!qXe>QKwL)L(=A5LVGx>onO7dxov=`J<@+h>TigYnj? z)7oROj#=dhXnRb(AE3jo5YlNuzo*{gBz8p74|mx^N9ts$s11YbC`l^Nh;(>HeJe7v0KxJ7JKEua!f;8H!9B2Lrw7#dZj(<;vGqC4CB`FCmF;kzaac&n|h zVwe#Orba6DMXc;DBO)I!?@C%;X)qn#Nts3niIM>`|By83GU_%M`)kA(=R!F7m(qL@ zW?kKiJbA*?Dr1#|xKX-W9FKy4*F_dN_`@54JBeRFk$g*{@BNea-)|LeZ`o%?kVuQU zQ%TpAJHZ*WH}&OJdZ3259Nc+xb_C8N;z7Cw*j4Io^#^DR>i0@^7f#pj*BTK!kMY8N z)l#^7i&y11m_!SrL{VcagUl-|!HZ#2ZV;Dw#==WWQ8g-XmY>V}5bjApZyyF5S9|)W z3guYm5oHASbrsW70c^)UoCm;v?jD_wx1W4HLB~$s=j=Fm{&gym^^S(Iz}Bp6R_>}H zComhlVXsmTG0aMf9OJ-rteGl68dxH4=~eZhR0V= z12-jAnAqy!`X#!J*dFe#uC97gcTOnz>VF9naUw|f7x`miY zXB_CplKs1D{O^!YU=mbj=i-8N4gyiRTlY)nJGURkO+StVD+Usz+#PeB#W(Rue*hJA zy)nCTUamg`hP6zvhMu{v-=KS`{rL$#259c?)seoaBDmA@>CfDovqnKf4gErfqEwV( zbCif6JMd|WF1 zG|_LiVw5j`JxA=`r)N7oujWC5js+_;K(0%X*#C1hOC}c=mnv-Sm3Rq#Jl$2e{q{r? z=w*}~uy;o!`Cks9-I1pARnVeBZWdTlfox;X;_cl?>$){d_Lihe^8zEOP-dyWmM0*W z>zOs{C)-m~cMmq{AIq~^Amd1>r~oAT?M({W1}H6dAJ7tuPRey94xk(Ytg63`Y;Q&x z>V3Ddrb~$?J7~&f0OBMP9|nVZeqX0H!hu+lhYpDamXq;bI$hGGuhQ$j?4YY$ZM!zh5_lIh6vU3?W<`*?t{BnP z;u&Tv(%WUS#&VucW%+!?RCf83j6=)5`e4z_&8eK-S(J`dUs5kbM%#jfF!07n`L};G zOUeRE=*AxC)ECiR@Y?aT)6j;^yf@a&~3M z27GdyC3*ffokZ?b6O+9*VZ8xda|9u=%A0D=Rpny9!8~4O#&Ory4rT^N*DFY8ySJ zU2vP3?IcDCo%K4V3|s4GuV;!YdS}K-c>_$D{4`ZdJn5!P^U5nvQZ;LZqNKu~-g>Dz zUGoESZRbwIWCVc2kS%r(vM;f4<9ReLK{d{5=5xQ4%|M|=x2P3X zueUz0);Yq=E8*nJUY8YQzik@1rObB7i^3N9Se@CCZu@*Hx^hitG}l_aU1DlIM!Il< zG?a?*4#>@Q4NJFfwE8+0jkgAx>!2VN;){KbMQd#M@KU3@|6~U>Ykz_ZhPVFePy^4< z{sx16?Z9y?B-K8R=9&et??B$lo7hz>dwPBK$ntV|0i({3RY9jcmr7F%*Mdlm&_JR@ zJQpP^KO}^MyLh4{R5i4-$g(G2%S`gVrEh&!LXVM-@x-|W)lNb|u?X8qFH<3!k@8Hy z);_BC=1`$sJ8M4z_~$GEZ21v71c1w-J}9YcC?B~)9hCJpR_g7#48p@j9;0XGRjOm~ zF8nb6_9^7TZRNolJ1x`a&iGc+G_id^@r2)ztT05p?=3)=bE(S7Dc)11;-9=(C`_WpOKJ zt$U4Xs59ZvTk7_qzcFPkN%159yrdHuPHI*(`PI?V~%yjL8VwT_2WQvrZwa_w4B7|;^Ag9_3{ovNY)3AC5&G0%E zeR%wYdYQYh{x@qy#djWSIF$)(aF5m8Y<>C{wLb!45cVmA7vVAsWJxr*C;rJ=h@Gh%vN zBP^EGEa=`n?5QUqje1&;(7s9C@bsc(^E5)20oBi=*e3y$E$_ZGGO6*KiI-V;lKttD9nnv?wYy*pvH{ikkfCW#QZ>qNa0ob`ItS4^0m@!ceHEluuVzea}V1seQ^u z?;Xu}Y$>u54%u>WeZ7-(_*)L~n_dxZrq9t1EbygUGgk)_mfE8q&irG=q@Eomzb7i` zrLzIs?EzOEbV8Q%lS;#-JF3*xgyLRcN>@c(aaWdz9G|?qRtj-$ZN+!+JX|Drbj?r6 z*j)9Rl^zk|ek>X=^@+oX{%o1-AdrS&u$D-1VuDdygU%sD*VC7TjA4P$&@T{f1LF|cB1neB#g4i8$rw@O)9Vvmx`{5SY_&nzJh zFY}M(F{U%QPMZ`|>%)7lAIg6yxbM%yAqXq=!=}le8D!AQU@S!2)`4AdFr(%D{B69e zGrxryV?Q+qP*ic`V}3JngeRgXM^T!k1j2yP{~5=-PLLHJ)}PKspb|W+oBVBumvg}# z5w=$Nrtd&chasVj10eZ#yJ(|_3Max$Qj_D(j2z&Njo)AFiZhr{VpDIZHrywwypDV$YJdSKYS>%RP52tWy1J!jrmN!0e`sB& z71(IUooDo4nswv9Hy{}}hfuXLSdO3h}o${&>gG9=%EANvUuQpO8;ULEmRA*CJkNL!bTSH)Iit~sewLaYFcLNxuEIf~n6CR@ehOU2L7ggZL!(J*AAQZ+M#ua6LsPQs)s(Uk zz1Pji#CF2<%)Fc$NWK&3Ezq87buBq1&N>2k!p(3!W>tD}Zr89&&3|dJu2^g&AnXJv zNkHC?AeIv$#GZTt3ow{zIsrkP;teldosp?p&3yN3{_xPF%7Ktpf=h3_|K%_+??BSB z1!keP1v9G(UCmUe@VFwOuP(Jvk;8+x9HLmP*ZV7&yNhA&Wf9pqiYJ5NTE1p0srw;; zdS3D#@ky2YgR#?PbZx(3g_nt2bO##^DVlo46yt0;ULMpnX1hSU{Vx66AusbMUw2Yqf# z*j{0Ja4Z8yuC0KGY&n66xQK}8j&!pw8?K@ZLve}m+_k|-He1hr9R$C=4*qDT<_XN18&j!a^{F9&-=03?TsbB-k~SyEGy%WcxiWk z$F%rkaR9kLm_O0`%ncL|H!JJDlO10q?~OG?7J`O_W0)2S@Mi_fww;c*dwl-GrRRV2 zHP1U2SU}QWA@TF0*2|_NJNM8P(AhTEyhaW{|Ed7=_W1`*DXV-u)-j~^8545u5%xe_ z$GK>8?unK}*8j0|wpoe2U*T^dF2Qq*AZD)82sHsTNU9jl1rGO3u zV$e;+O}5}OJ-Kj-VLZ@z>tL6r;@aCCHWbY6yMDjI;))!dFLn3mK${q&XWq&5%_6Wi z`8QRN4DA^6?(be$!fFNU&Qv-MFlqL+Vn!(k=@&Raw^nM)`ItR18(wvfju%W8e^i!M zWC;`s2XFS&2-2vii??g@oI!DY&!nCS!#&r5)Kxm9vzR}ZCK_-NBQdp^rUl-=kxtuz zlJ*4rf1s26DLDnm=Rx5LdyKwwzcHGrz-uIiymNk$-`8wd$zIb=0%6@$EoQFpFHvLx z!N{Z!mn%W9*Z+0><_{yU^zqaLuOJ2-9*AQQc0)X3?Jm>!!g!*Td`Ejm)9zcI>5W3ZQqgZ@fSQQfz*#bf}19+ri7+tul7Y_bk^-UF9!b( zlkr?`^cCUpo7CKe5?v2c2eY50fxx_>9LzzQa~08nmPNC#=#`A@mr1vLX?Q}_b?3M)(B@TE>WOJP(+z^vR$VS7UPX9%CJ8P?th4 zy9`O{znT^h#hl93UxjUpSzo*Unxlt(_X%Nl^LzVy9_QRKUU;xIO$&({&>wxf0OpSURtl+HF7e5Z!+e24ZBR!{%r-q{_znh!$1u}?guKf*rU z+!-)8c79TsshxFAB$|2Whmrrq5C6EY`R(Gd8iG35`Wr#_=%MBNV^CsHeOH!_W1ONa zll-b7ZL%fKYGrn)R2W=1{YMN;5mmEB9KFr!UMvTX+<2V0`0Q&if-SDbNI4rj(~Tr$ z*mfSXmv>L^k4L#1kvmzsyDuWQH=&en7y3rbo}+rV4CJ>~J${7P_U!iBCdC5!j*hCH z)Y&5OZi#{9hPMm&;O}_=gY2bG1b-FX-QBlcuQ1JD*V>Kxn&dPRq(!c|I|r{)+wII8;+k+;*<+duv8 z`lk-gk2MO8xy#x##b^yIe)jqD0Y9pO7-p$LQ1YF@E{izjz3&ggTR)b&^q^Dkh#`Mg zm;yZq!%LEtBI#qt6BQGL!e>a)k=aDZgx~fpU`qoU&CvJZAKMKh6l8%{r~c(QyYy+y zeP_TG{r6+^M-+Me=dR2UN(JY^>6IM-yOW6pL}5t{rA<%1|Ks@G9T2+VQ>G#YW*{7U zBJ#DfIChE=x&P69^k)O@RqL3$R+jGWsD1vHG2zmVFYSr3C{YXZi_wh`7%q%(9?a>) zydkn%UBk*KFQN>aUo%F~m!Yad9q$e<^(v35Dj#yYdr~+~JBx*a*>IT|K#O*mKNz-Z zdvk^E3VeYrv{bmCPEBeb9u`U8`v4=zIQ1Dt4wEGYW5d+}A#ERbi3;V}mepiN0XbxQ zxe+nS9_V3wSSjta&Yg_Yo54!7({x5RFrIY)g$#o2m-?tO$_AyD7mAn-qxb2>vvz@d zQS@gpXKvnK%3l?=P*B)f?$CKGQPc2j?^+CW>s7h^$BPix?hP#g+c>_9;o+?TvmS2i zQyGWseIxx91LvZzQEFDq(c?@D1@z724Q^S|@C%v|H0sHHhxi|G;h4gOx3zCSOfE|f zU7qP@1`~v$O#AUgDf>I<($emp2o#u_)=NI@tL9Ew;k@+bDDMmuvyc#evokJj1A&{Iw_3kxJ50#RLjxrCwXb^ z_gY@|Jcjt-UR;P23GTJ21B+31j37e<%;sH7gj7%!#oq}7^Sjb93rlQiSt>1wrnaf zs`Qqa^e|VPg)eCP<8@@|pEVdzVn7IcU7( zA@mKCs`zw|E#sf|oQmstOeLx`YKgRlWSCb&T3kNipEHC9cY9rjg2C7v9|{ zZ1K}jskW_up?y)L8sQ8{4v)b70Q{HDd$CW7C3TcGW9AtG?Qmc*S*Jho+dwP=BPdeBnG=C1LO)Hx&bS zzK9ztmNl=Onz6g@B(3mfsUiux?k?M3;PNyJ8zgeA?NyATc*3jPbBW$am8B;kz%2lYlq%foBjT5lCC{Hg60auqB zD=upzuMOOilS0^CSvnTuxm`=nZVZ*L_LPW2c?bc2(@Ad)^FRJd*u?9a?9-m&8!chL zBpg4}Kh?pa{@DMxPI$Y_LTq_@rLa+pLPi}CJqX$}j_8xlzF^L4#WQm?+{*3kf!-Wl z?SN3j<9Nah2sm8#XOFa2GjBLdsLD!BtMsVrcc>41Im!?dmR)p=jR`Jv4C7ilFQZKG~_w#*dVwR<~j zDNoI(uA;F)_fR~{2oXaLCVlj|M)iqn)Mo+c!a~UW8h&(Yd|BgB#nKwTm9mdhn4{Xq zYUS5ysXYd`7Y57tzN+nuii2pWC?OvipF{(z?XA4RyV~2UO9{R8ADuT+ReXIHo4n_j zYTC=Z%!GWtJ^$uo9ud9b9KONN^kkHXz>hjRD=f&@ypMCmoT%LxqR=0DNhORxTe41? z9J!u)qyF`+(3|$Yk8|=vUO&Dnk6cOVGnezXnHw*sEH7!T$GPJ4rcQU4<}pZ)u%in^ zuMc!<;z(R7H)?~FEm-S_>rmV4$zQw6i5NXC0XU*d#;1D!As9gxTW8bE%VSYXO1Z!y zg^LD&KSr47Id{_P)ZKaF)w{( zPU3;JknSasv+W@ieq!p^UQL__^hlh4!P=CeJ`a~tBEpA-OU}ki@jb%ORfgG7?@LsB^qKc%%wWohf(!ELa#g zGX$KOZ#hL1U_+Jg!tv)Sqb-3-5FhmhT+27X&lV3VM3Npe?YV3rO)GN6u9_+uyTtLf zq7h?r9eRaU_G!Lmq!T(X@5?lpw0@PY<}leh4O$-mytGt!$w!B>N2gMdo0});+B9xp z`?Nl{y$u;<7m*QNYEYo65O6zrpjS>wOnjB-wvs~DawyORXOK)wD2KH?v0MFA(FU(0 z=0c|K*@wGzS6?rj{8De5AS7+ZGjS4`w}Q*D8vb}aFp-1&#a)FK9LiMd<>x5BUA&~_ zQY)888w;m~YccZrgwOVM93KlY_?k@GoG}0>;5~6#&}wV%+hQisaKUkT_JJ2NGVXWK zxR0O3t!`zpuzOJ}yX@~2#3b+-$I5SgW3Y;I9PBWgnw*oob&V|w8|jgR%5zp3$S{Vr zry1b*HU_L_6c$FO%_>EfAZoAKl}?NttwqjP^tEI7^tYUpU)6f}s7>8_RX&@m75==@ zH7rR1&39l3wZQt0udL)PXv36;yyiI57hjDj^~|8()vwjf7Im8vpZ)f}NYHBWTraM8 zfB;PlB~%KGt8ua}^t?)`p$;2LA+ALiP@(Yl@ffAkPm`hsteW0#z;fQC$E6E-U$W5@ zy79G8kT`g&7boso0+$beQz|=-gnKsmSzElq4KbsJ=h{`xxN8^hEQFrfCcUH%KJ+7& z!P)BrYo~r;4(&c%yVVk-XZOT_A|pDUJ9ylgySCph(N9^Zk1(XFpTL^R>G8Z(G&Cdd zd9^-MkjMHeDAhYIBith-FM{;!y;}@tsJTDiY+TIGl#X&M-P*H<&)5HUfEhUOJpD|* zxACNLH2LgX(fBo8C!e)(nT?Lm>+d1(U z?ZS0nW@Lgj7Bkhu*)_w`X}G>V_q$2L(fI4cCO=|U^9HP$uM>9f_%j984!xzPpAJr4 zZ0;P*6^WleT33MTE+}}iQ5)!{CUkaWx=4lCeoobDsIm|;OIq{`kR1;v@g^jCC488h z4m?p%P%d(QN${)^${IW{UR(&6z*A9vydi=NY*6!kaoK~Kf$N>5k(-?vnguQZJ`)Vu z{FVf39SIK$65;VZ%%5^4aN`DT#ANHty0whyTC?;>7+4#{WX6~~cc!aTv7$)G0ulq5 z!WW_&Z~R4)-Vm3}1Xcn?klnS`KO-Lhl*YH&GV(k_4f!>eN=^oNkwLaj_F`M}S0oG! zI6Ag%EY@!cgJqTCbaiJ);oYGPEyYB_1LpVhyec#^AC8uQ9 z_U0yCz3^p{#Q1N1C7CW5c^ghgv1E#TmAH0R)Vs*kStRHrSnpU+<8>dbg-csK|FM?( zJ5rU&*$JSNN;*Ol&~1R3kCfS_Eij3!`Qxb*f8W}RHpRA1zm?fMB)#>-@XXC(FJ4C} zim!AAcYF7L0s3y!)ZZbZ?FmPNvNmgvlP$9jOi$BTV9e%vXGnUe8 z5m>W+9c-#C+L=(2MfhwlnlWUmGy_F@kqNgqW9BwDR`4we&{SOkY+JH2anPf6H?Eko z+|MaFik6xOFFYpC-8I!+|R;$3e>=Sp^Q_D-$!pII-MX)^>79ilLaInF{bz+VUQvoOmbwG#9DjO{npL|- zlh`<0i^r@F@-hS_CN8+iBQ%w4qVUj;0Hz`H+61IpoezL#x}S)!g)*QKmAMwRn7U7% z0k^u9%Ft+o)(nl*N>G~P?3pU7qXbr0ZY&M8cTa4AO`__a&P~W_A;)W+M<%l|>x8wl zYepZR@(0vmYccs-gBzsnB+dEOp#kJLe?wA6Mr|vzH7{ufv*bL5mq_gNNa?(7mVfo`!~X{{3N~v1 diff --git a/mai/lab.ipynb b/mai/lab.ipynb deleted file mode 100644 index e69de29..0000000 diff --git a/mai/lab4.ipynb b/mai/lab4.ipynb new file mode 100644 index 0000000..fb3d496 --- /dev/null +++ b/mai/lab4.ipynb @@ -0,0 +1,2936 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Лабораторная работа 4\n", + "\n", + "Датасет - **Цены на бриллианты**\thttps://www.kaggle.com/datasets/nancyalaswad90/diamonds-prices\n", + "\n", + "1. **carat**: Вес бриллианта в каратах\n", + "2. **cut**: Качество огранки.\n", + "3. **color**: Цвет бриллианта\n", + "4. **clarity**: Чистота бриллианта\n", + "5. **depth**: Процент глубины бриллианта\n", + "6. **table**: Процент ширины бриллианта\n", + "7. **price**: Цена бриллианта в долларах США\n", + "8. **x**: Длина бриллианта в миллиметрах\n", + "9. **y**: Ширина бриллианта в миллиметрах\n", + "10. **z**: Глубина бриллианта в миллиметрах" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Бизнес-цели**: \n", + "1. Прогнозирование цены бриллиантов на основании характеристик.\n", + "2. Анализ частотности и сочетания характеристик бриллиантов, которые пользуются наибольшим спросом, чтобы лучше планировать запасы. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Загрузка набора данных" + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Среднее значение поля 'карат': 0.7979346717831785\n" + ] + }, + { + "data": { + "text/html": [ + "

\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
caratcutcolorclaritydepthtablepricexyzabove_average_carat
id
10.23IdealESI261.555.03263.953.982.430
20.21PremiumESI159.861.03263.893.842.310
30.23GoodEVS156.965.03274.054.072.310
40.29PremiumIVS262.458.03344.204.232.630
50.31GoodJSI263.358.03354.344.352.750
....................................
539390.86PremiumHSI261.058.027576.156.123.741
539400.75IdealDSI262.255.027575.835.873.640
539410.71PremiumESI160.555.027565.795.743.490
539420.71PremiumFSI159.862.027565.745.733.430
539430.70Very GoodEVS260.559.027575.715.763.470
\n", + "

53943 rows × 11 columns

\n", + "
" + ], + "text/plain": [ + " carat cut color clarity depth table price x y z \\\n", + "id \n", + "1 0.23 Ideal E SI2 61.5 55.0 326 3.95 3.98 2.43 \n", + "2 0.21 Premium E SI1 59.8 61.0 326 3.89 3.84 2.31 \n", + "3 0.23 Good E VS1 56.9 65.0 327 4.05 4.07 2.31 \n", + "4 0.29 Premium I VS2 62.4 58.0 334 4.20 4.23 2.63 \n", + "5 0.31 Good J SI2 63.3 58.0 335 4.34 4.35 2.75 \n", + "... ... ... ... ... ... ... ... ... ... ... \n", + "53939 0.86 Premium H SI2 61.0 58.0 2757 6.15 6.12 3.74 \n", + "53940 0.75 Ideal D SI2 62.2 55.0 2757 5.83 5.87 3.64 \n", + "53941 0.71 Premium E SI1 60.5 55.0 2756 5.79 5.74 3.49 \n", + "53942 0.71 Premium F SI1 59.8 62.0 2756 5.74 5.73 3.43 \n", + "53943 0.70 Very Good E VS2 60.5 59.0 2757 5.71 5.76 3.47 \n", + "\n", + " above_average_carat \n", + "id \n", + "1 0 \n", + "2 0 \n", + "3 0 \n", + "4 0 \n", + "5 0 \n", + "... ... \n", + "53939 1 \n", + "53940 0 \n", + "53941 0 \n", + "53942 0 \n", + "53943 0 \n", + "\n", + "[53943 rows x 11 columns]" + ] + }, + "execution_count": 190, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "from sklearn import set_config\n", + "\n", + "set_config(transform_output=\"pandas\")\n", + "\n", + "df = pd.read_csv(\"data/Diamonds.csv\", index_col=\"id\")\n", + "\n", + "random_state=42\n", + "\n", + "average_carat = df['carat'].mean()\n", + "\n", + "print(f\"Среднее значение поля 'карат': {average_carat}\")\n", + "\n", + "average_carat = df['carat'].mean()\n", + "df['above_average_carat'] = (df['carat'] > average_carat).astype(int)\n", + "\n", + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Разделение набора данных на обучающую и тестовые выборки (80/20) для задачи классификации\n", + "\n", + "Целевой признак -- Cut" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'X_train'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
caratcutcolorclaritydepthtablepricexyzabove_average_carat
id
388360.40Very GoodFVVS262.056.010494.714.742.930
302600.40Very GoodESI163.057.07254.684.712.960
331690.36IdealEVS161.856.08174.554.582.820
10290.70Very GoodEVS158.459.029045.835.913.430
538090.81Very GoodGSI160.756.027336.066.093.691
....................................
29370.77GoodEVS263.457.032915.805.843.690
75140.90GoodFSI161.863.042416.216.183.831
483440.56IdealHVVS162.153.819615.275.333.290
32120.70PremiumFVVS161.860.033485.675.633.490
356540.31Very GoodGVVS263.157.09074.324.302.720
\n", + "

43154 rows × 11 columns

\n", + "
" + ], + "text/plain": [ + " carat cut color clarity depth table price x y z \\\n", + "id \n", + "38836 0.40 Very Good F VVS2 62.0 56.0 1049 4.71 4.74 2.93 \n", + "30260 0.40 Very Good E SI1 63.0 57.0 725 4.68 4.71 2.96 \n", + "33169 0.36 Ideal E VS1 61.8 56.0 817 4.55 4.58 2.82 \n", + "1029 0.70 Very Good E VS1 58.4 59.0 2904 5.83 5.91 3.43 \n", + "53809 0.81 Very Good G SI1 60.7 56.0 2733 6.06 6.09 3.69 \n", + "... ... ... ... ... ... ... ... ... ... ... \n", + "2937 0.77 Good E VS2 63.4 57.0 3291 5.80 5.84 3.69 \n", + "7514 0.90 Good F SI1 61.8 63.0 4241 6.21 6.18 3.83 \n", + "48344 0.56 Ideal H VVS1 62.1 53.8 1961 5.27 5.33 3.29 \n", + "3212 0.70 Premium F VVS1 61.8 60.0 3348 5.67 5.63 3.49 \n", + "35654 0.31 Very Good G VVS2 63.1 57.0 907 4.32 4.30 2.72 \n", + "\n", + " above_average_carat \n", + "id \n", + "38836 0 \n", + "30260 0 \n", + "33169 0 \n", + "1029 0 \n", + "53809 1 \n", + "... ... \n", + "2937 0 \n", + "7514 1 \n", + "48344 0 \n", + "3212 0 \n", + "35654 0 \n", + "\n", + "[43154 rows x 11 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'y_train'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
above_average_carat
id
388360
302600
331690
10290
538091
......
29370
75141
483440
32120
356540
\n", + "

43154 rows × 1 columns

\n", + "
" + ], + "text/plain": [ + " above_average_carat\n", + "id \n", + "38836 0\n", + "30260 0\n", + "33169 0\n", + "1029 0\n", + "53809 1\n", + "... ...\n", + "2937 0\n", + "7514 1\n", + "48344 0\n", + "3212 0\n", + "35654 0\n", + "\n", + "[43154 rows x 1 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'X_test'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
caratcutcolorclaritydepthtablepricexyzabove_average_carat
id
324520.39Very GoodEVS260.958.07934.724.772.890
24320.72Very GoodESI163.356.031835.675.713.600
164561.21IdealHSI162.159.065736.816.754.211
460450.56IdealDSI162.556.017295.285.243.290
111151.00GoodESI162.459.049366.356.403.981
....................................
402500.50PremiumFSI159.661.011255.155.123.060
33080.73IdealEVS162.356.033705.755.803.600
78941.12Very GoodISI160.660.043126.736.774.091
213680.36IdealDSI162.253.06264.574.592.850
461440.50PremiumEVS261.359.017465.105.053.110
\n", + "

10789 rows × 11 columns

\n", + "
" + ], + "text/plain": [ + " carat cut color clarity depth table price x y z \\\n", + "id \n", + "32452 0.39 Very Good E VS2 60.9 58.0 793 4.72 4.77 2.89 \n", + "2432 0.72 Very Good E SI1 63.3 56.0 3183 5.67 5.71 3.60 \n", + "16456 1.21 Ideal H SI1 62.1 59.0 6573 6.81 6.75 4.21 \n", + "46045 0.56 Ideal D SI1 62.5 56.0 1729 5.28 5.24 3.29 \n", + "11115 1.00 Good E SI1 62.4 59.0 4936 6.35 6.40 3.98 \n", + "... ... ... ... ... ... ... ... ... ... ... \n", + "40250 0.50 Premium F SI1 59.6 61.0 1125 5.15 5.12 3.06 \n", + "3308 0.73 Ideal E VS1 62.3 56.0 3370 5.75 5.80 3.60 \n", + "7894 1.12 Very Good I SI1 60.6 60.0 4312 6.73 6.77 4.09 \n", + "21368 0.36 Ideal D SI1 62.2 53.0 626 4.57 4.59 2.85 \n", + "46144 0.50 Premium E VS2 61.3 59.0 1746 5.10 5.05 3.11 \n", + "\n", + " above_average_carat \n", + "id \n", + "32452 0 \n", + "2432 0 \n", + "16456 1 \n", + "46045 0 \n", + "11115 1 \n", + "... ... \n", + "40250 0 \n", + "3308 0 \n", + "7894 1 \n", + "21368 0 \n", + "46144 0 \n", + "\n", + "[10789 rows x 11 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'y_test'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
above_average_carat
id
324520
24320
164561
460450
111151
......
402500
33080
78941
213680
461440
\n", + "

10789 rows × 1 columns

\n", + "
" + ], + "text/plain": [ + " above_average_carat\n", + "id \n", + "32452 0\n", + "2432 0\n", + "16456 1\n", + "46045 0\n", + "11115 1\n", + "... ...\n", + "40250 0\n", + "3308 0\n", + "7894 1\n", + "21368 0\n", + "46144 0\n", + "\n", + "[10789 rows x 1 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from typing import Tuple\n", + "import pandas as pd\n", + "from pandas import DataFrame\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "def split_stratified_into_train_val_test(\n", + " df_input,\n", + " stratify_colname=\"y\",\n", + " frac_train=0.6,\n", + " frac_val=0.15,\n", + " frac_test=0.25,\n", + " random_state=None,\n", + ") -> Tuple[DataFrame, DataFrame, DataFrame, DataFrame, DataFrame, DataFrame]:\n", + " \"\"\"\n", + " Splits a Pandas dataframe into three subsets (train, val, and test)\n", + " following fractional ratios provided by the user, where each subset is\n", + " stratified by the values in a specific column (that is, each subset has\n", + " the same relative frequency of the values in the column). It performs this\n", + " splitting by running train_test_split() twice.\n", + " Parameters\n", + " ----------\n", + " df_input : Pandas dataframe\n", + " Input dataframe to be split.\n", + " stratify_colname : str\n", + " The name of the column that will be used for stratification. Usually\n", + " this column would be for the label.\n", + " frac_train : float\n", + " frac_val : float\n", + " frac_test : float\n", + " The ratios with which the dataframe will be split into train, val, and\n", + " test data. The values should be expressed as float fractions and should\n", + " sum to 1.0.\n", + " random_state : int, None, or RandomStateInstance\n", + " Value to be passed to train_test_split().\n", + " Returns\n", + " -------\n", + " df_train, df_val, df_test :\n", + " Dataframes containing the three splits.\n", + " \"\"\"\n", + " if frac_train + frac_val + frac_test != 1.0:\n", + " raise ValueError(\n", + " \"fractions %f, %f, %f do not add up to 1.0\"\n", + " % (frac_train, frac_val, frac_test)\n", + " )\n", + " if stratify_colname not in df_input.columns:\n", + " raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n", + " X = df_input # Contains all columns.\n", + " y = df_input[\n", + " [stratify_colname]\n", + " ] # Dataframe of just the column on which to stratify.\n", + " # Split original dataframe into train and temp dataframes.\n", + " df_train, df_temp, y_train, y_temp = train_test_split(\n", + " X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n", + " )\n", + " if frac_val <= 0:\n", + " assert len(df_input) == len(df_train) + len(df_temp)\n", + " return df_train, pd.DataFrame(), df_temp, y_train, pd.DataFrame(), y_temp\n", + " # Split the temp dataframe into val and test dataframes.\n", + " relative_frac_test = frac_test / (frac_val + frac_test)\n", + " df_val, df_test, y_val, y_test = train_test_split(\n", + " df_temp,\n", + " y_temp,\n", + " stratify=y_temp,\n", + " test_size=relative_frac_test,\n", + " random_state=random_state,\n", + " )\n", + " assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n", + " return df_train, df_val, df_test, y_train, y_val, y_test\n", + "\n", + "X_train, X_val, X_test, y_train, y_val, y_test = split_stratified_into_train_val_test(\n", + " df, stratify_colname=\"above_average_carat\", frac_train=0.80, frac_val=0, frac_test=0.20, random_state=random_state\n", + ")\n", + "\n", + "display(\"X_train\", X_train)\n", + "display(\"y_train\", y_train)\n", + "\n", + "display(\"X_test\", X_test)\n", + "display(\"y_test\", y_test)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Формирование конвейера для классификации данных\n", + "\n", + "preprocessing_num -- конвейер для обработки числовых данных: заполнение пропущенных значений и стандартизация\n", + "\n", + "preprocessing_cat -- конвейер для обработки категориальных данных: заполнение пропущенных данных и унитарное кодирование\n", + "\n", + "features_preprocessing -- трансформер для предобработки признаков\n", + "\n", + "features_engineering -- трансформер для конструирования признаков\n", + "\n", + "drop_columns -- трансформер для удаления колонок\n", + "\n", + "pipeline_end -- основной конвейер предобработки данных и конструирования признако" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from sklearn.base import BaseEstimator, TransformerMixin\n", + "from sklearn.compose import ColumnTransformer\n", + "from sklearn.discriminant_analysis import StandardScaler\n", + "from sklearn.impute import SimpleImputer\n", + "from sklearn.pipeline import Pipeline\n", + "from sklearn.preprocessing import OneHotEncoder\n", + "\n", + "class DaimondFeatures(BaseEstimator, TransformerMixin):\n", + " def __init__(self):\n", + " pass\n", + " def fit(self, X, y=None):\n", + " return self\n", + " def transform(self, X, y=None):\n", + " X[\"Length_to_Width_Ratio\"] = X[\"x\"] / X[\"y\"]\n", + " return X\n", + " def get_feature_names_out(self, features_in):\n", + " return np.append(features_in, [\"Length_to_Width_Ratio\"], axis=0)\n", + " \n", + "\n", + "columns_to_drop = []\n", + "num_columns = [\"carat\", \"depth\", \"table\", \"x\", \"y\", \"z\", \"above_average_carat\"]\n", + "cat_columns = [\"cut\", \"color\", \"clarity\"]\n", + "\n", + "num_imputer = SimpleImputer(strategy=\"median\")\n", + "num_scaler = StandardScaler()\n", + "preprocessing_num = Pipeline(\n", + " [\n", + " (\"imputer\", num_imputer),\n", + " (\"scaler\", num_scaler),\n", + " ]\n", + ")\n", + "\n", + "cat_imputer = SimpleImputer(strategy=\"constant\", fill_value=\"unknown\")\n", + "cat_encoder = OneHotEncoder(handle_unknown=\"ignore\", sparse_output=False, drop=\"first\")\n", + "preprocessing_cat = Pipeline(\n", + " [\n", + " (\"imputer\", cat_imputer),\n", + " (\"encoder\", cat_encoder),\n", + " ]\n", + ")\n", + "\n", + "features_preprocessing = ColumnTransformer(\n", + " verbose_feature_names_out=False,\n", + " transformers=[\n", + " (\"prepocessing_num\", preprocessing_num, num_columns),\n", + " (\"prepocessing_cat\", preprocessing_cat, cat_columns),\n", + " ],\n", + " remainder=\"passthrough\"\n", + ")\n", + "\n", + "features_engineering = ColumnTransformer(\n", + " verbose_feature_names_out=False,\n", + " transformers=[\n", + " (\"add_features\", DaimondFeatures(), [\"x\", \"y\"]),\n", + " ],\n", + " remainder=\"passthrough\",\n", + ")\n", + "\n", + "drop_columns = ColumnTransformer(\n", + " verbose_feature_names_out=False,\n", + " transformers=[\n", + " (\"drop_columns\", \"drop\", columns_to_drop),\n", + " ],\n", + " remainder=\"passthrough\",\n", + ")\n", + "\n", + "features_postprocessing = ColumnTransformer(\n", + " verbose_feature_names_out=False,\n", + " transformers=[\n", + " (\"prepocessing_cat\", preprocessing_cat, [\"Cabin_type\"]),\n", + " ],\n", + " remainder=\"passthrough\",\n", + ")\n", + "\n", + "pipeline_end = Pipeline(\n", + " [\n", + " (\"features_preprocessing\", features_preprocessing),\n", + " (\"features_engineering\", features_engineering),\n", + " (\"drop_columns\", drop_columns),\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Демонстрация работы конвейера для предобработки данных при классификации" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
xyLength_to_Width_Ratiocaratdepthtablezabove_average_caratcut_Goodcut_Ideal...color_Icolor_Jclarity_IFclarity_SI1clarity_SI2clarity_VS1clarity_VS2clarity_VVS1clarity_VVS2price
id
38836-0.907744-0.8634761.051267-0.8374900.176170-0.648004-0.857040-0.8560460.00.0...0.00.00.00.00.00.00.00.01.01049
30260-0.934483-0.8895791.050478-0.8374900.876071-0.201125-0.814688-0.8560460.00.0...0.00.00.01.00.00.00.00.00.0725
33169-1.050350-1.0026911.047532-0.9218850.036190-0.648004-1.012333-0.8560460.01.0...0.00.00.00.00.01.00.00.00.0817
10290.0904960.1545300.585622-0.204531-2.3434710.692631-0.151165-0.8560460.00.0...0.00.00.00.00.01.00.00.00.02904
538090.2954920.3111470.9496880.027554-0.733700-0.6480040.2158901.1681620.00.0...0.00.00.01.00.00.00.00.00.02733
..................................................................
29370.0637580.0936240.680999-0.0568411.156031-0.2011250.215890-0.8560461.00.0...0.00.00.00.00.00.01.00.00.03291
75140.4291850.3894551.1020150.2174420.0361902.4801450.4135351.1681621.00.0...0.00.00.01.00.00.00.00.00.04241
48344-0.408624-0.3501231.167088-0.4999120.246160-1.631136-0.348810-0.8560460.01.0...0.00.00.00.00.00.00.01.00.01961
3212-0.052109-0.0890950.584874-0.2045310.0361901.139510-0.066460-0.8560460.00.0...0.00.00.00.00.00.00.01.00.03348
35654-1.255346-1.2463161.007245-1.0273780.946061-0.201125-1.153508-0.8560460.00.0...0.00.00.00.00.00.00.00.01.0907
\n", + "

43154 rows × 26 columns

\n", + "
" + ], + "text/plain": [ + " x y Length_to_Width_Ratio carat depth \\\n", + "id \n", + "38836 -0.907744 -0.863476 1.051267 -0.837490 0.176170 \n", + "30260 -0.934483 -0.889579 1.050478 -0.837490 0.876071 \n", + "33169 -1.050350 -1.002691 1.047532 -0.921885 0.036190 \n", + "1029 0.090496 0.154530 0.585622 -0.204531 -2.343471 \n", + "53809 0.295492 0.311147 0.949688 0.027554 -0.733700 \n", + "... ... ... ... ... ... \n", + "2937 0.063758 0.093624 0.680999 -0.056841 1.156031 \n", + "7514 0.429185 0.389455 1.102015 0.217442 0.036190 \n", + "48344 -0.408624 -0.350123 1.167088 -0.499912 0.246160 \n", + "3212 -0.052109 -0.089095 0.584874 -0.204531 0.036190 \n", + "35654 -1.255346 -1.246316 1.007245 -1.027378 0.946061 \n", + "\n", + " table z above_average_carat cut_Good cut_Ideal ... \\\n", + "id ... \n", + "38836 -0.648004 -0.857040 -0.856046 0.0 0.0 ... \n", + "30260 -0.201125 -0.814688 -0.856046 0.0 0.0 ... \n", + "33169 -0.648004 -1.012333 -0.856046 0.0 1.0 ... \n", + "1029 0.692631 -0.151165 -0.856046 0.0 0.0 ... \n", + "53809 -0.648004 0.215890 1.168162 0.0 0.0 ... \n", + "... ... ... ... ... ... ... \n", + "2937 -0.201125 0.215890 -0.856046 1.0 0.0 ... \n", + "7514 2.480145 0.413535 1.168162 1.0 0.0 ... \n", + "48344 -1.631136 -0.348810 -0.856046 0.0 1.0 ... \n", + "3212 1.139510 -0.066460 -0.856046 0.0 0.0 ... \n", + "35654 -0.201125 -1.153508 -0.856046 0.0 0.0 ... \n", + "\n", + " color_I color_J clarity_IF clarity_SI1 clarity_SI2 clarity_VS1 \\\n", + "id \n", + "38836 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "30260 0.0 0.0 0.0 1.0 0.0 0.0 \n", + "33169 0.0 0.0 0.0 0.0 0.0 1.0 \n", + "1029 0.0 0.0 0.0 0.0 0.0 1.0 \n", + "53809 0.0 0.0 0.0 1.0 0.0 0.0 \n", + "... ... ... ... ... ... ... \n", + "2937 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "7514 0.0 0.0 0.0 1.0 0.0 0.0 \n", + "48344 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "3212 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "35654 0.0 0.0 0.0 0.0 0.0 0.0 \n", + "\n", + " clarity_VS2 clarity_VVS1 clarity_VVS2 price \n", + "id \n", + "38836 0.0 0.0 1.0 1049 \n", + "30260 0.0 0.0 0.0 725 \n", + "33169 0.0 0.0 0.0 817 \n", + "1029 0.0 0.0 0.0 2904 \n", + "53809 0.0 0.0 0.0 2733 \n", + "... ... ... ... ... \n", + "2937 1.0 0.0 0.0 3291 \n", + "7514 0.0 0.0 0.0 4241 \n", + "48344 0.0 1.0 0.0 1961 \n", + "3212 0.0 1.0 0.0 3348 \n", + "35654 0.0 0.0 1.0 907 \n", + "\n", + "[43154 rows x 26 columns]" + ] + }, + "execution_count": 193, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "preprocessing_result = pipeline_end.fit_transform(X_train)\n", + "preprocessed_df = pd.DataFrame(\n", + " preprocessing_result,\n", + " columns=pipeline_end.get_feature_names_out(),\n", + ")\n", + "\n", + "preprocessed_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Формирование набора моделей для классификации\n", + "\n", + "logistic -- логистическая регрессия\n", + "\n", + "ridge -- гребневая регрессия\n", + "\n", + "decision_tree -- дерево решений\n", + "\n", + "knn -- k-ближайших соседей\n", + "\n", + "naive_bayes -- наивный Байесовский классификатор\n", + "\n", + "gradient_boosting -- метод градиентного бустинга (набор деревьев решений)\n", + "\n", + "random_forest -- метод случайного леса (набор деревьев решений)\n", + "\n", + "mlp -- многослойный персептрон (нейронная сеть)" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn import ensemble, linear_model, naive_bayes, neighbors, neural_network, tree\n", + "\n", + "class_models = {\n", + " \"logistic\": {\"model\": linear_model.LogisticRegression()},\n", + " # \"ridge\": {\"model\": linear_model.RidgeClassifierCV(cv=5, class_weight=\"balanced\")},\n", + " \"ridge\": {\"model\": linear_model.LogisticRegression(penalty=\"l2\", class_weight=\"balanced\")},\n", + " \"decision_tree\": {\n", + " \"model\": tree.DecisionTreeClassifier(max_depth=7, random_state=random_state)\n", + " },\n", + " \"knn\": {\"model\": neighbors.KNeighborsClassifier(n_neighbors=7)},\n", + " \"naive_bayes\": {\"model\": naive_bayes.GaussianNB()},\n", + " \"gradient_boosting\": {\n", + " \"model\": ensemble.GradientBoostingClassifier(n_estimators=210)\n", + " },\n", + " \"random_forest\": {\n", + " \"model\": ensemble.RandomForestClassifier(\n", + " max_depth=11, class_weight=\"balanced\", random_state=random_state\n", + " )\n", + " },\n", + " \"mlp\": {\n", + " \"model\": neural_network.MLPClassifier(\n", + " hidden_layer_sizes=(7,),\n", + " max_iter=500,\n", + " early_stopping=True,\n", + " random_state=random_state,\n", + " )\n", + " },\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Обучение моделей на обучающем наборе данных и оценка на тестовом" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: logistic\n", + "Model: ridge\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Python312\\Lib\\site-packages\\sklearn\\linear_model\\_logistic.py:469: ConvergenceWarning: lbfgs failed to converge (status=1):\n", + "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", + "\n", + "Increase the number of iterations (max_iter) or scale the data as shown in:\n", + " https://scikit-learn.org/stable/modules/preprocessing.html\n", + "Please also refer to the documentation for alternative solver options:\n", + " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", + " n_iter_i = _check_optimize_result(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: decision_tree\n", + "Model: knn\n", + "Model: naive_bayes\n", + "Model: gradient_boosting\n", + "Model: random_forest\n", + "Model: mlp\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "from sklearn import metrics\n", + "\n", + "for model_name in class_models.keys():\n", + " print(f\"Model: {model_name}\")\n", + " model = class_models[model_name][\"model\"]\n", + "\n", + " model_pipeline = Pipeline([(\"pipeline\", pipeline_end), (\"model\", model)])\n", + " model_pipeline = model_pipeline.fit(X_train, y_train.values.ravel())\n", + "\n", + " y_train_predict = model_pipeline.predict(X_train)\n", + " y_test_probs = model_pipeline.predict_proba(X_test)[:, 1]\n", + " y_test_predict = np.where(y_test_probs > 0.5, 1, 0)\n", + "\n", + " class_models[model_name][\"pipeline\"] = model_pipeline\n", + " class_models[model_name][\"probs\"] = y_test_probs\n", + " class_models[model_name][\"preds\"] = y_test_predict\n", + "\n", + " class_models[model_name][\"Precision_train\"] = metrics.precision_score(\n", + " y_train, y_train_predict\n", + " )\n", + " class_models[model_name][\"Precision_test\"] = metrics.precision_score(\n", + " y_test, y_test_predict\n", + " )\n", + " class_models[model_name][\"Recall_train\"] = metrics.recall_score(\n", + " y_train, y_train_predict\n", + " )\n", + " class_models[model_name][\"Recall_test\"] = metrics.recall_score(\n", + " y_test, y_test_predict\n", + " )\n", + " class_models[model_name][\"Accuracy_train\"] = metrics.accuracy_score(\n", + " y_train, y_train_predict\n", + " )\n", + " class_models[model_name][\"Accuracy_test\"] = metrics.accuracy_score(\n", + " y_test, y_test_predict\n", + " )\n", + " class_models[model_name][\"ROC_AUC_test\"] = metrics.roc_auc_score(\n", + " y_test, y_test_probs\n", + " )\n", + " class_models[model_name][\"F1_train\"] = metrics.f1_score(y_train, y_train_predict)\n", + " class_models[model_name][\"F1_test\"] = metrics.f1_score(y_test, y_test_predict)\n", + " class_models[model_name][\"MCC_test\"] = metrics.matthews_corrcoef(\n", + " y_test, y_test_predict\n", + " )\n", + " class_models[model_name][\"Cohen_kappa_test\"] = metrics.cohen_kappa_score(\n", + " y_test, y_test_predict\n", + " )\n", + " class_models[model_name][\"Confusion_matrix\"] = metrics.confusion_matrix(\n", + " y_test, y_test_predict\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Сводная таблица оценок качества для использованных моделей классификации" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Матрица неточностей" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.metrics import ConfusionMatrixDisplay\n", + "import matplotlib.pyplot as plt\n", + "\n", + "_, ax = plt.subplots(int(len(class_models) / 2), 2, figsize=(12, 10), sharex=False, sharey=False)\n", + "for index, key in enumerate(class_models.keys()):\n", + " c_matrix = class_models[key][\"Confusion_matrix\"]\n", + " disp = ConfusionMatrixDisplay(\n", + " confusion_matrix=c_matrix, display_labels=[\"Less\", \"More\"]\n", + " ).plot(ax=ax.flat[index])\n", + " disp.ax_.set_title(key)\n", + "\n", + "plt.subplots_adjust(top=1, bottom=0, hspace=0.4, wspace=0.1)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Точность, полнота, верность (аккуратность), F-мера" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 Precision_trainPrecision_testRecall_trainRecall_testAccuracy_trainAccuracy_testF1_trainF1_test
logistic1.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
ridge0.9999451.0000000.9999451.0000000.9999541.0000000.9999451.000000
decision_tree1.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
naive_bayes0.9998901.0000000.9998901.0000000.9999071.0000000.9998901.000000
random_forest1.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
gradient_boosting1.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
mlp0.9995070.9995620.9998360.9995620.9997220.9996290.9996710.999562
knn0.9839700.9793000.9787400.9745780.9842660.9805360.9813480.976933
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 198, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "class_metrics = pd.DataFrame.from_dict(class_models, \"index\")[\n", + " [\n", + " \"Precision_train\",\n", + " \"Precision_test\",\n", + " \"Recall_train\",\n", + " \"Recall_test\",\n", + " \"Accuracy_train\",\n", + " \"Accuracy_test\",\n", + " \"F1_train\",\n", + " \"F1_test\",\n", + " ]\n", + "]\n", + "class_metrics.sort_values(\n", + " by=\"Accuracy_test\", ascending=False\n", + ").style.background_gradient(\n", + " cmap=\"plasma\",\n", + " low=0.3,\n", + " high=1,\n", + " subset=[\"Accuracy_train\", \"Accuracy_test\", \"F1_train\", \"F1_test\"],\n", + ").background_gradient(\n", + " cmap=\"viridis\",\n", + " low=1,\n", + " high=0.3,\n", + " subset=[\n", + " \"Precision_train\",\n", + " \"Precision_test\",\n", + " \"Recall_train\",\n", + " \"Recall_test\",\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ROC-кривая, каппа Коэна, коэффициент корреляции Мэтьюса" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 Accuracy_testF1_testROC_AUC_testCohen_kappa_testMCC_test
logistic1.0000001.0000001.0000001.0000001.000000
ridge1.0000001.0000001.0000001.0000001.000000
decision_tree1.0000001.0000001.0000001.0000001.000000
naive_bayes1.0000001.0000001.0000001.0000001.000000
random_forest1.0000001.0000001.0000001.0000001.000000
gradient_boosting1.0000001.0000001.0000001.0000001.000000
mlp0.9996290.9995620.9997540.9992400.999240
knn0.9805360.9769330.9959600.9600980.960107
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 199, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "class_metrics = pd.DataFrame.from_dict(class_models, \"index\")[\n", + " [\n", + " \"Accuracy_test\",\n", + " \"F1_test\",\n", + " \"ROC_AUC_test\",\n", + " \"Cohen_kappa_test\",\n", + " \"MCC_test\",\n", + " ]\n", + "]\n", + "class_metrics.sort_values(by=\"ROC_AUC_test\", ascending=False).style.background_gradient(\n", + " cmap=\"plasma\",\n", + " low=0.3,\n", + " high=1,\n", + " subset=[\n", + " \"ROC_AUC_test\",\n", + " \"MCC_test\",\n", + " \"Cohen_kappa_test\",\n", + " ],\n", + ").background_gradient(\n", + " cmap=\"viridis\",\n", + " low=1,\n", + " high=0.3,\n", + " subset=[\n", + " \"Accuracy_test\",\n", + " \"F1_test\",\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'logistic'" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "best_model = str(class_metrics.sort_values(by=\"MCC_test\", ascending=False).iloc[0].name)\n", + "\n", + "display(best_model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Вывод данных с ошибкой предсказания для оценки" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Error items count: 0'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
caratPredictedcutcolorclaritydepthtablepricexyzabove_average_carat
id
\n", + "
" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [carat, Predicted, cut, color, clarity, depth, table, price, x, y, z, above_average_carat]\n", + "Index: []" + ] + }, + "execution_count": 206, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "preprocessing_result = pipeline_end.transform(X_test)\n", + "preprocessed_df = pd.DataFrame(\n", + " preprocessing_result,\n", + " columns=pipeline_end.get_feature_names_out(),\n", + ")\n", + "\n", + "y_pred = class_models[best_model][\"preds\"]\n", + "\n", + "error_index = y_test[y_test[\"above_average_carat\"] != y_pred].index.tolist()\n", + "display(f\"Error items count: {len(error_index)}\")\n", + "\n", + "error_predicted = pd.Series(y_pred, index=y_test.index).loc[error_index]\n", + "error_df = X_test.loc[error_index].copy()\n", + "error_df.insert(loc=1, column=\"Predicted\", value=error_predicted)\n", + "error_df.sort_index()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Пример использования обученной модели (конвейера) для предсказания" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
caratcutcolorclaritydepthtablepricexyzabove_average_carat
45000.9PremiumHSI161.958.036296.26.153.821
\n", + "
" + ], + "text/plain": [ + " carat cut color clarity depth table price x y z \\\n", + "4500 0.9 Premium H SI1 61.9 58.0 3629 6.2 6.15 3.82 \n", + "\n", + " above_average_carat \n", + "4500 1 " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
xyLength_to_Width_Ratiocaratdepthtablezabove_average_caratcut_Goodcut_Ideal...color_Icolor_Jclarity_IFclarity_SI1clarity_SI2clarity_VS1clarity_VS2clarity_VVS1clarity_VVS2price
45000.4202720.3633521.1566530.2174420.106180.2457530.3994171.1681620.00.0...0.00.00.01.00.00.00.00.00.03629.0
\n", + "

1 rows × 26 columns

\n", + "
" + ], + "text/plain": [ + " x y Length_to_Width_Ratio carat depth table \\\n", + "4500 0.420272 0.363352 1.156653 0.217442 0.10618 0.245753 \n", + "\n", + " z above_average_carat cut_Good cut_Ideal ... color_I \\\n", + "4500 0.399417 1.168162 0.0 0.0 ... 0.0 \n", + "\n", + " color_J clarity_IF clarity_SI1 clarity_SI2 clarity_VS1 clarity_VS2 \\\n", + "4500 0.0 0.0 1.0 0.0 0.0 0.0 \n", + "\n", + " clarity_VVS1 clarity_VVS2 price \n", + "4500 0.0 0.0 3629.0 \n", + "\n", + "[1 rows x 26 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'predicted: 1 (proba: [4.76016150e-04 9.99523984e-01])'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'real: 1'" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model = class_models[best_model][\"pipeline\"]\n", + "\n", + "example_id = 4500\n", + "test = pd.DataFrame(X_test.loc[example_id, :]).T\n", + "test_preprocessed = pd.DataFrame(preprocessed_df.loc[example_id, :]).T\n", + "display(test)\n", + "display(test_preprocessed)\n", + "result_proba = model.predict_proba(test)[0]\n", + "result = model.predict(test)[0]\n", + "real = int(y_test.loc[example_id].values[0])\n", + "display(f\"predicted: {result} (proba: {result_proba})\")\n", + "display(f\"real: {real}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Подбор гиперпараметров методом поиска по сетке" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'model__criterion': 'gini',\n", + " 'model__max_depth': 2,\n", + " 'model__max_features': 'sqrt',\n", + " 'model__n_estimators': 20}" + ] + }, + "execution_count": 209, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.model_selection import GridSearchCV\n", + "\n", + "optimized_model_type = \"random_forest\"\n", + "\n", + "random_forest_model = class_models[optimized_model_type][\"pipeline\"]\n", + "\n", + "param_grid = {\n", + " \"model__n_estimators\": [10, 20, 30, 40, 50, 100, 150, 200, 250, 500],\n", + " \"model__max_features\": [\"sqrt\", \"log2\", 2],\n", + " \"model__max_depth\": [2, 3, 4, 5, 6, 7, 8, 9 ,10],\n", + " \"model__criterion\": [\"gini\", \"entropy\", \"log_loss\"],\n", + "}\n", + "\n", + "gs_optomizer = GridSearchCV(\n", + " estimator=random_forest_model, param_grid=param_grid, n_jobs=-1\n", + ")\n", + "gs_optomizer.fit(X_train, y_train.values.ravel())\n", + "gs_optomizer.best_params_" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Обучение модели с новыми гиперпараметрами" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": {}, + "outputs": [], + "source": [ + "optimized_model = ensemble.RandomForestClassifier(\n", + " random_state=random_state,\n", + " criterion=\"gini\",\n", + " max_depth=7,\n", + " max_features=\"sqrt\",\n", + " n_estimators=30,\n", + ")\n", + "\n", + "result = {}\n", + "\n", + "result[\"pipeline\"] = Pipeline([(\"pipeline\", pipeline_end), (\"model\", optimized_model)]).fit(X_train, y_train.values.ravel())\n", + "result[\"train_preds\"] = result[\"pipeline\"].predict(X_train)\n", + "result[\"probs\"] = result[\"pipeline\"].predict_proba(X_test)[:, 1]\n", + "result[\"preds\"] = np.where(result[\"probs\"] > 0.5, 1, 0)\n", + "\n", + "result[\"Precision_train\"] = metrics.precision_score(y_train, result[\"train_preds\"])\n", + "result[\"Precision_test\"] = metrics.precision_score(y_test, result[\"preds\"])\n", + "result[\"Recall_train\"] = metrics.recall_score(y_train, result[\"train_preds\"])\n", + "result[\"Recall_test\"] = metrics.recall_score(y_test, result[\"preds\"])\n", + "result[\"Accuracy_train\"] = metrics.accuracy_score(y_train, result[\"train_preds\"])\n", + "result[\"Accuracy_test\"] = metrics.accuracy_score(y_test, result[\"preds\"])\n", + "result[\"ROC_AUC_test\"] = metrics.roc_auc_score(y_test, result[\"probs\"])\n", + "result[\"F1_train\"] = metrics.f1_score(y_train, result[\"train_preds\"])\n", + "result[\"F1_test\"] = metrics.f1_score(y_test, result[\"preds\"])\n", + "result[\"MCC_test\"] = metrics.matthews_corrcoef(y_test, result[\"preds\"])\n", + "result[\"Cohen_kappa_test\"] = metrics.cohen_kappa_score(y_test, result[\"preds\"])\n", + "result[\"Confusion_matrix\"] = metrics.confusion_matrix(y_test, result[\"preds\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Формирование данных для оценки старой и новой версии модели" + ] + }, + { + "cell_type": "code", + "execution_count": 211, + "metadata": {}, + "outputs": [], + "source": [ + "optimized_metrics = pd.DataFrame(columns=list(result.keys()))\n", + "optimized_metrics.loc[len(optimized_metrics)] = pd.Series(\n", + " data=class_models[optimized_model_type]\n", + ")\n", + "optimized_metrics.loc[len(optimized_metrics)] = pd.Series(\n", + " data=result\n", + ")\n", + "optimized_metrics.insert(loc=0, column=\"Name\", value=[\"Old\", \"New\"])\n", + "optimized_metrics = optimized_metrics.set_index(\"Name\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Оценка параметров старой и новой модели" + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 Precision_trainPrecision_testRecall_trainRecall_testAccuracy_trainAccuracy_testF1_trainF1_test
Name        
Old1.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
New1.0000001.0000001.0000001.0000001.0000001.0000001.0000001.000000
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 212, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "optimized_metrics[\n", + " [\n", + " \"Precision_train\",\n", + " \"Precision_test\",\n", + " \"Recall_train\",\n", + " \"Recall_test\",\n", + " \"Accuracy_train\",\n", + " \"Accuracy_test\",\n", + " \"F1_train\",\n", + " \"F1_test\",\n", + " ]\n", + "].style.background_gradient(\n", + " cmap=\"plasma\",\n", + " low=0.3,\n", + " high=1,\n", + " subset=[\"Accuracy_train\", \"Accuracy_test\", \"F1_train\", \"F1_test\"],\n", + ").background_gradient(\n", + " cmap=\"viridis\",\n", + " low=1,\n", + " high=0.3,\n", + " subset=[\n", + " \"Precision_train\",\n", + " \"Precision_test\",\n", + " \"Recall_train\",\n", + " \"Recall_test\",\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 Accuracy_testF1_testROC_AUC_testCohen_kappa_testMCC_test
Name     
Old1.0000001.0000001.0000001.0000001.000000
New1.0000001.0000001.0000001.0000001.000000
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "optimized_metrics[\n", + " [\n", + " \"Accuracy_test\",\n", + " \"F1_test\",\n", + " \"ROC_AUC_test\",\n", + " \"Cohen_kappa_test\",\n", + " \"MCC_test\",\n", + " ]\n", + "].style.background_gradient(\n", + " cmap=\"plasma\",\n", + " low=0.3,\n", + " high=1,\n", + " subset=[\n", + " \"ROC_AUC_test\",\n", + " \"MCC_test\",\n", + " \"Cohen_kappa_test\",\n", + " ],\n", + ").background_gradient(\n", + " cmap=\"viridis\",\n", + " low=1,\n", + " high=0.3,\n", + " subset=[\n", + " \"Accuracy_test\",\n", + " \"F1_test\",\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 215, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_, ax = plt.subplots(1, 2, figsize=(10, 4), sharex=False, sharey=False\n", + ")\n", + "\n", + "for index in range(0, len(optimized_metrics)):\n", + " c_matrix = optimized_metrics.iloc[index][\"Confusion_matrix\"]\n", + " disp = ConfusionMatrixDisplay(\n", + " confusion_matrix=c_matrix, display_labels=[\"Less\", \"More\"]\n", + " ).plot(ax=ax.flat[index])\n", + "\n", + "plt.subplots_adjust(top=1, bottom=0, hspace=0.4, wspace=0.3)\n", + "plt.show()" + ] + } + ], + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/mai/readme.md b/mai/readme.md deleted file mode 100644 index fba5c63..0000000 --- a/mai/readme.md +++ /dev/null @@ -1,55 +0,0 @@ -## Окружение и примеры для выполнения лабораторных работ по дисциплине "Методы ИИ" - -### Python - -Используется Python версии 3.12 - -Установщик https://www.python.org/ftp/python/3.12.5/python-3.12.5-amd64.exe - -### Poetry - -Для создания и настройки окружения проекта необходимо установить poetry - -**Для Windows (Powershell)** - -``` -(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python - -``` - -**Linux, macOS, Windows (WSL)** - -``` -curl -sSL https://install.python-poetry.org | python3 - -``` - -**Добавление poetry в PATH** - -1. Открыть настройки переменных среды \ - \ - \ - \ - \ -2. Изменить переменную Path текущего пользователя \ - \ - \ -3. Добавление пути `%APPDATA%\Python\Scripts` до исполняемого файла poetry \ - \ - - -### Создание окружения - -``` -poetry install -``` - -### Запуск тестового сервиса - -Запустить тестовый сервис можно с помощью VSCode (см. launch.json в каталоге .vscode). - -Также запустить тестовый сервис можно с помощью командной строки: - -1. Активация виртуального окружения -- `poetry shell` - -2. Запуск сервиса -- `python run.py` - -Для выходы из виртуального окружения используется команду `exit` diff --git a/mai/run.py b/mai/run.py deleted file mode 100644 index 39333c8..0000000 --- a/mai/run.py +++ /dev/null @@ -1,16 +0,0 @@ -from backend import create_app - -app = create_app() - - -def __main(): - app.run( - host="127.0.0.1", - port=8080, - debug=True, - use_reloader=False, - ) - - -if __name__ == "__main__": - __main() diff --git a/mai/utils.py b/mai/utils.py new file mode 100644 index 0000000..7190903 --- /dev/null +++ b/mai/utils.py @@ -0,0 +1,79 @@ +from typing import Tuple + +import pandas as pd +from pandas import DataFrame +from sklearn.model_selection import train_test_split + + +def split_stratified_into_train_val_test( + df_input, + stratify_colname="y", + frac_train=0.6, + frac_val=0.15, + frac_test=0.25, + random_state=None, +) -> Tuple[DataFrame, DataFrame, DataFrame, DataFrame, DataFrame, DataFrame]: + """ + Splits a Pandas dataframe into three subsets (train, val, and test) + following fractional ratios provided by the user, where each subset is + stratified by the values in a specific column (that is, each subset has + the same relative frequency of the values in the column). It performs this + splitting by running train_test_split() twice. + + Parameters + ---------- + df_input : Pandas dataframe + Input dataframe to be split. + stratify_colname : str + The name of the column that will be used for stratification. Usually + this column would be for the label. + frac_train : float + frac_val : float + frac_test : float + The ratios with which the dataframe will be split into train, val, and + test data. The values should be expressed as float fractions and should + sum to 1.0. + random_state : int, None, or RandomStateInstance + Value to be passed to train_test_split(). + + Returns + ------- + df_train, df_val, df_test : + Dataframes containing the three splits. + """ + + if frac_train + frac_val + frac_test != 1.0: + raise ValueError( + "fractions %f, %f, %f do not add up to 1.0" + % (frac_train, frac_val, frac_test) + ) + + if stratify_colname not in df_input.columns: + raise ValueError("%s is not a column in the dataframe" % (stratify_colname)) + + X = df_input # Contains all columns. + y = df_input[ + [stratify_colname] + ] # Dataframe of just the column on which to stratify. + + # Split original dataframe into train and temp dataframes. + df_train, df_temp, y_train, y_temp = train_test_split( + X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state + ) + + if frac_val <= 0: + assert len(df_input) == len(df_train) + len(df_temp) + return df_train, pd.DataFrame(), df_temp, y_train, pd.DataFrame(), y_temp + + # Split the temp dataframe into val and test dataframes. + relative_frac_test = frac_test / (frac_val + frac_test) + df_val, df_test, y_val, y_test = train_test_split( + df_temp, + y_temp, + stratify=y_temp, + test_size=relative_frac_test, + random_state=random_state, + ) + + assert len(df_input) == len(df_train) + len(df_val) + len(df_test) + return df_train, df_val, df_test, y_train, y_val, y_test \ No newline at end of file